From 8944f73f1a044c9f4163e86a04bdfcfae3da3b20 Mon Sep 17 00:00:00 2001 From: Jaixii Date: Sun, 2 Aug 2026 05:16:38 -0400 Subject: [PATCH 01/35] feat: consolidate governed recall and release hardening --- .env.example | 12 +- AGENTS.md | 5 +- CHANGELOG.md | 43 ++ Dockerfile | 5 +- README.md | 91 ++- docs/HOSTING_RAILWAY.md | 7 + docs/MCP_TOOLS.md | 33 +- docs/dashboard-button-qa.md | 2 +- engraphis/backends/query_planner.py | 93 +++ engraphis/backends/sync_relay.py | 9 + engraphis/cloud_features.py | 23 +- engraphis/cloud_session.py | 45 +- engraphis/config.py | 5 + engraphis/core/adaptive_context.py | 31 +- engraphis/core/consolidate.py | 28 +- engraphis/core/engine.py | 217 +++++- engraphis/core/graph_policy.py | 101 +++ engraphis/core/grounded.py | 14 + engraphis/core/interfaces.py | 113 ++- engraphis/core/poisoning.py | 135 +++- engraphis/core/query_planner.py | 137 ++++ engraphis/core/recall.py | 724 ++++++++++++++++-- engraphis/core/resolve.py | 15 +- engraphis/core/scoring.py | 36 +- engraphis/core/store.py | 119 ++- engraphis/core/sync.py | 27 +- engraphis/dashboard_app.py | 92 ++- engraphis/dashboard_assets/index.html | 2 +- engraphis/dashboard_assets/ledger.js | 64 +- engraphis/llm/client.py | 58 +- engraphis/mcp_server.py | 28 +- engraphis/read_only_api.py | 17 +- engraphis/routes/v2_api.py | 62 +- engraphis/service.py | 244 +++++- eval/EVIDENCE.md | 40 +- eval/ablation.py | 5 + .../longmemeval_v2_engraphis_planner.json | 17 + ...eval_v2_engraphis_planner_type_limits.json | 17 + .../longmemeval_v2_engraphis_type_limits.json | 17 + eval/datasets/context_routing_stress.jsonl | 12 + eval/datasets/graph_layer_routing.jsonl | 3 + eval/datasets/proactive_ranking.jsonl | 8 +- eval/graph_traversal.py | 123 +++ eval/longmemeval_v2.py | 56 +- eval/longmemeval_v2_evidence.py | 95 ++- eval/longmemeval_v2_matrix.py | 82 ++ eval/planned_recall.py | 395 ++++++++++ eval/proactive_ranking.py | 29 +- eval/productivity.py | 25 +- eval/redteam_poisoning.py | 75 +- eval/resource_hierarchy.py | 279 +++++++ railway.json | 1 + scripts/approve_memory.py | 40 + scripts/backfill_graph.py | 27 +- scripts/cli.py | 6 +- scripts/migrate_to_v2.py | 37 +- scripts/rescan_poisoning.py | 37 +- tests/e2e/ledger.spec.js | 14 +- tests/test_adaptive_context.py | 40 +- tests/test_agent_connect.py | 7 +- tests/test_cli_entrypoints.py | 37 + tests/test_cloud_features.py | 35 + tests/test_cloud_session.py | 62 ++ tests/test_compact_recall.py | 29 +- tests/test_config.py | 6 +- tests/test_consolidate.py | 37 +- tests/test_core_store.py | 2 + ...hboard_security_headers_and_open_window.py | 52 ++ tests/test_dashboard_v2.py | 153 +++- tests/test_engine.py | 16 + tests/test_eval_ablation.py | 12 +- tests/test_eval_graph_traversal.py | 11 + tests/test_eval_performance.py | 6 +- tests/test_eval_redteam_poisoning.py | 15 +- tests/test_graph_explorer_v2.py | 16 +- tests/test_graph_trust_backfill.py | 105 +++ tests/test_graphrank.py | 258 ++++++- tests/test_grounded.py | 11 +- tests/test_hosted_plan_resolution.py | 32 + tests/test_inspector.py | 15 +- tests/test_licensing_boundary_docs.py | 10 + tests/test_longmemeval_v2_evidence.py | 15 + tests/test_longmemeval_v2_matrix.py | 15 + tests/test_mcp_annotation_idempotency.py | 33 +- tests/test_mcp_server.py | 83 +- tests/test_merge.py | 8 +- tests/test_migration.py | 60 +- tests/test_personal_folders.py | 5 +- tests/test_planned_recall.py | 638 +++++++++++++++ tests/test_planned_recall_eval.py | 64 ++ tests/test_poisoning.py | 116 ++- tests/test_proactive_context.py | 10 +- tests/test_proactive_ranking.py | 16 +- tests/test_protocol_upgrades.py | 26 +- tests/test_provenance_flags.py | 6 +- tests/test_provider_error_redaction.py | 27 + tests/test_railway_runtime.py | 8 + tests/test_read_only_api.py | 24 +- tests/test_recall.py | 27 +- tests/test_relay_device_credentials.py | 27 + tests/test_rescan_poisoning.py | 56 +- tests/test_resolve.py | 17 + tests/test_resource_hierarchy_eval.py | 25 + tests/test_retention.py | 19 +- tests/test_retrieval_policy.py | 4 +- tests/test_service.py | 103 ++- tests/test_service_graph.py | 87 ++- tests/test_service_isolation.py | 3 + tests/test_sync.py | 44 +- tests/test_workspace_isolation.py | 12 +- tests/test_workspace_ops.py | 52 +- 111 files changed, 6018 insertions(+), 656 deletions(-) create mode 100644 engraphis/backends/query_planner.py create mode 100644 engraphis/core/graph_policy.py create mode 100644 engraphis/core/query_planner.py create mode 100644 eval/configs/longmemeval_v2_engraphis_planner.json create mode 100644 eval/configs/longmemeval_v2_engraphis_planner_type_limits.json create mode 100644 eval/configs/longmemeval_v2_engraphis_type_limits.json create mode 100644 eval/datasets/context_routing_stress.jsonl create mode 100644 eval/datasets/graph_layer_routing.jsonl create mode 100644 eval/graph_traversal.py create mode 100644 eval/longmemeval_v2_matrix.py create mode 100644 eval/planned_recall.py create mode 100644 eval/resource_hierarchy.py create mode 100644 scripts/approve_memory.py create mode 100644 tests/test_eval_graph_traversal.py create mode 100644 tests/test_graph_trust_backfill.py create mode 100644 tests/test_longmemeval_v2_matrix.py create mode 100644 tests/test_planned_recall.py create mode 100644 tests/test_planned_recall_eval.py create mode 100644 tests/test_resource_hierarchy_eval.py diff --git a/.env.example b/.env.example index aacab6d3..dfb2df83 100644 --- a/.env.example +++ b/.env.example @@ -207,17 +207,19 @@ ENGRAPHIS_LLM_API_KEY=sk-your-key-here # Locally defaults to ~/.engraphis; in a container use a private persistent volume. # ENGRAPHIS_STATE_DIR=/data/.engraphis -# Hosted entitlements may report a separate local-only write grace capped at 24 hours. -# It never extends the exact 3-day trial, subscription expiry, or any cloud access. +# The private control plane may report ``workspace_write_grace`` for already-authorized +# hosted-account continuity, capped at 24 hours. It never extends the exact 3-day trial, +# subscription expiry, or cloud access, and it never restricts the free local core. # Managed compute consent is decided automatically and needs no customer action: a # local-only installation (no cloud session) is never allowed to upload workspace # snapshots, while an installation connected to Engraphis Cloud is allowed by default, # because connecting already accepts the terms covering managed analytics, dreaming, and # consolidation. This variable is an explicit operator override, not a customer-facing -# setting: set it to 0 to opt a connected installation back out, or to 1 to force -# managed compute on regardless of session state. The cloud service remains authoritative -# for all paid computation. +# setting: set it to 0 to opt a connected installation back out, or to 1 to allow local +# snapshot preparation for a non-interactive deployment. ``1`` does not establish a cloud +# credential or authorize an upload; the cloud service remains authoritative for all paid +# computation. # ENGRAPHIS_MANAGED_COMPUTE_CONSENT=0 # Optional credential-redacted JSON logs for hosted customer deployments. diff --git a/AGENTS.md b/AGENTS.md index 7d449fe6..edbf0257 100644 --- a/AGENTS.md +++ b/AGENTS.md @@ -91,14 +91,17 @@ python -m scripts.migrate_to_v2 --old engraphis_v1.db --new engraphis_v2.db ``` query └─ SearchFilter (scope + valid_at/known_at anchors) core/interfaces.py + └─ optional QueryPlanner (off by default; original + at most 2 routes) + core/query_planner.py └─ 4 retrieval arms (run in parallel, then fused): • vector — VectorIndex.search (cosine) backends/vector_*.py • lexical — Store.fts_search (FTS5/BM25 + LIKE fallback) core/store.py • graph — Personalized PageRank over entities+links core/recall.py + core/graphrank.py (graph_mode="1hop" keeps the old expansion for ablation) • code — symbols/files/calls with memory bridges core/engine.py - └─ RRF fusion + six-term weighted score core/scoring.py + └─ priority-weighted query/arm RRF + six-term score core/scoring.py └─ rerank top-N backends/reranker.py + └─ optional post-rerank memory-type maxima └─ context packing (token budget) + optional explicit reinforcement core/recall.py / core/store.py ``` diff --git a/CHANGELOG.md b/CHANGELOG.md index 05314395..837ee113 100644 --- a/CHANGELOG.md +++ b/CHANGELOG.md @@ -5,6 +5,49 @@ All notable changes to Engraphis are documented here. Format loosely follows ## [Unreleased] +### Added + +- Opt-in planned recall adds a bounded deterministic planner, an injectable planner protocol and + optional LLM backend, priority-weighted multi-query RRF, post-rerank memory-type maxima, stable + context revisions, and diagnostics-only planner traces across Python, service, REST, and MCP + recall surfaces. The default remains the existing single-query path on schema 7. +- A 40-task context-routing stress fixture, four-way five-budget ablation harness, pinned + LongMemEval-V2 planner configurations, and evaluation-only imported-resource hierarchy prototype + encode local regression gates and matrix tooling. Official benchmark, safety, and hosted-cache + artifacts remain mandatory before any default or schema change. + +### Security + +- Public writes now enter an explicit review gate: MCP, REST/dashboard-intent, import, sync, and + extractor ingress are pending regardless of a caller-supplied trust label; detector matches are + quarantined before they can contribute to prompt context or derived state. Human approval creates + a fresh audited successor only through the CSRF-bound dashboard action or an interactive TTY + command, never through MCP or a general REST endpoint. Historical rescans demote non-approved + records and retire their derived bridges. + +### Fixed + +- Explicit local `engraphis-cli ingest` commands now record local-owner-approved provenance, + allowing their memories to appear in ordinary subsequent CLI recall. HTTP, MCP, import, and + file-ingestion boundaries remain pending review. +- The standalone v1→v2 migrator now refuses in-place and pre-existing output paths before + opening either database, preventing accidental mixing of legacy source history into a v2 target. +- Cloud Sync now closes failed HTTP response streams without reading their untrusted error bodies, + preventing descriptor leaks during repeated relay failures. +- Hosted customer clients now bind provider credential/session state before persistence and + preserve sanitized authorization/billing outcomes when an HTTP error body is truncated, so a + one-time connection cannot be stranded by an unreadable state file or retain stale paid badges. +- Authoritative hosted managed-compute authorization denials now immediately settle local + entitlement presentation state, so a revoked, lapsed, or de-authorized account is not shown + stale paid feature access while awaiting a background refresh. +- The production image health probe now follows the active IPv4 or IPv6 loopback listener, + preventing a Railway IPv6 deployment from being marked unhealthy while its readiness route + is serving traffic. +- Grounded recall's absolute support floor ignores titles and non-finite semantic scores, so + display text cannot independently make an answer eligible. +- Keyed-claim deduplication ignores harmless punctuation, and legacy zero, negative, or non-finite + stability values use the documented one-day default instead of producing invalid decay scores. + ## [1.3.0] - 2026-08-01 ### Added diff --git a/Dockerfile b/Dockerfile index c491ba71..1d81d0c9 100644 --- a/Dockerfile +++ b/Dockerfile @@ -55,10 +55,11 @@ EXPOSE 8700 # Railway uses the same endpoint, so a process-only health signal cannot mask a bad mode. # start-period is generous: the first cold boot downloads the embedding model (cached to # the /data volume via HF_HOME thereafter). The entrypoint selects a bind address suited -# to Docker or Railway; the check also honors $PORT if the platform overrides it — matching +# to Docker or Railway; ``localhost`` reaches the matching IPv4 or IPv6 loopback socket. +# The check also honors $PORT if the platform overrides it — matching # scripts/start_dashboard.py, which prefers $PORT over ENGRAPHIS_PORT for the bind. HEALTHCHECK --interval=30s --timeout=5s --start-period=300s --retries=3 \ - CMD python -c "import os,urllib.request,sys; p=os.environ.get('PORT') or os.environ.get('ENGRAPHIS_PORT','8700'); sys.exit(0 if urllib.request.urlopen('http://127.0.0.1:%s/api/ready' % p).status==200 else 1)" + CMD python -c "import os,urllib.request,sys; p=os.environ.get('PORT') or os.environ.get('ENGRAPHIS_PORT','8700'); sys.exit(0 if urllib.request.urlopen('http://localhost:%s/api/ready' % p).status==200 else 1)" # The entrypoint fixes volume ownership then drops to the non-root `engraphis` user before # running the CMD (or any Railway/compose start-command override, which becomes its args). diff --git a/README.md b/README.md index 6450ae6c..d9238da2 100644 --- a/README.md +++ b/README.md @@ -8,12 +8,12 @@ https://engraphis.com/ https://discord.com/invite/Wfr2ejBmY -**Give your AI agents a memory. See it, search it, and maintain it, all in a beautiful WebUI on your own machine.** +**Give coding agents durable project memory so the next session can retrieve the current decision, its evidence, and its history.**

- Engraphis Knowledge Graph tab: force-directed entity-relation network + Project history becomes scoped memory, hybrid recall, and bounded cited context for an agent
- Knowledge Graph · run engraphis-dashboard to see it live + Preserve a project decision · retrieve its supporting evidence · hand the next agent a bounded context

--- @@ -22,11 +22,6 @@ https://discord.com/invite/Wfr2ejBmY > and customer-side clients. Hosted sync, analytics, automation, and team services run on the > official hosted service; their server implementations are not distributed here. -> **Support continued Engraphis development with Pro.** [Start a 3-day Pro trial](https://api.engraphis.com/account?plan=pro&interval=monthly&utm_source=engraphis&utm_medium=docs&utm_campaign=pro_conversion&utm_content=readme_intro&trial=pro#billing) -> or [subscribe to Pro](https://api.engraphis.com/account?plan=pro&interval=monthly&utm_source=engraphis&utm_medium=docs&utm_campaign=pro_conversion&utm_content=readme_intro#billing). - ---- - ## Measured token and context savings

@@ -107,13 +102,8 @@ An agent should not have to reconstruct a project from scattered chat history on Engraphis turns local project knowledge into scoped, time-aware memory; retrieves the evidence that supports the current question; and returns a bounded, attributable context packet. -

- Diagram: project history becomes scoped and temporal Engraphis memory, hybrid recall, then bounded cited context for an agent -
- Store durable project knowledge · retrieve supporting evidence · give the agent only what it needs -

- -The flow is the essential path. See [measured token and context savings](#measured-token-and-context-savings) +The core task is continuity: retrieve the current, supported project decision without dragging the +whole history into the next prompt. See [measured token and context savings](#measured-token-and-context-savings) for the short version of how much less history an agent has to carry. | Agent need | What Engraphis changes | @@ -302,6 +292,40 @@ in the [MCP tool reference](docs/MCP_TOOLS.md). For unattended jobs, `engraphis_start_session`, `engraphis_remember`, and `engraphis_record_event` use workspace `default` when `workspace` is omitted. +### Review gate for MCP, REST, imports, and sync + +Every public write enters review as `pending`, regardless of a caller-supplied `source` or +`trusted` label. That includes MCP, dashboard/REST intent writes, imports, sync, and extractor +output. Detector matches are instead `quarantined` immediately. Pending and quarantined records +remain inspectable and auditable, but cannot enter model-ready recall/context, resolution, +links, graph/code backfill, or derived prompt context. Corrections, promotions, and merges fail +closed unless every input is explicitly approved. + +Approval creates a fresh `approved` successor and preserves the reviewed source plus an audit +link; it never relabels the source in place. There is deliberately no MCP tool or general REST +approval endpoint. A local owner can approve through the dashboard's **Approve for prompt** +action after configuring `ENGRAPHIS_API_TOKEN` (short-lived browser session plus CSRF confirmation), +or from an interactive terminal: + +```bash +python -m scripts.approve_memory mem_... --reason "verified against the owner runbook" +``` + +The command rejects redirected input and requires typing its displayed confirmation. Hosted +owner/admin approval is performed by the hosted service, not this local package. The direct +in-process `MemoryEngine` remains a documented trusted-code boundary for code that already has +local database authority; do not expose it to untrusted transports. Existing stores can be +inspected without writes, then migrated deliberately: + +```bash +python -m scripts.rescan_poisoning --db engraphis.db +python -m scripts.rescan_poisoning --db engraphis.db --apply +``` + +The dry run opens the database read-only. The applying pass demotes historical non-approved +records to pending review, quarantines detected payloads, retires their derived bridges, and +records an audit event. + ## Quickstart: repository graph ```bash @@ -378,7 +402,36 @@ For an agent prompt, prefer `engraphis_recall_context`: it returns one hard-budg `token_counter`), and optional diagnostics. Accounting is exact for the named counter; inject the reader's tokenizer when reader-model token parity is required. `engraphis_recall` remains the compatible full-recall surface; use `response_mode="compact"` when the packed context is enough and full memory bodies -would duplicate it. Both default to the `balanced` retrieval profile; `auto` remains opt-in. +would duplicate it. Both default to the `balanced` retrieval profile and `planning="off"`. +Opt-in `planning="auto"` keeps the original query, admits at most two deterministic or injected +query routes, and fuses them before reranking against the original query. `mtype_limits`, when +provided, are post-rerank maximum counts rather than relevance boosts. Every packed response has a +stable `context_revision` derived from the token-counter identity and ordered packed excerpts, so a +host can retain an unchanged prompt prefix. Planner output, per-query rankings, cap drops, and +fallback reasons appear only with `diagnostics=True`. + +The offline planner is the default injected implementation. An application can opt into an LLM +planner without coupling `core/` to a provider: + +```python +from engraphis.backends.query_planner import LLMQueryPlanner +from engraphis.core.engine import MemoryEngine + +engine = MemoryEngine.create( + "engraphis.db", + query_planner=LLMQueryPlanner(my_llm), +) +result = engine.recall( + "why does ReleaseGate depend on AuditLog?", + workspace_id="ws_...", + planning="auto", + mtype_limits={"working": 1, "semantic": 3}, +) +``` + +Planner failures and provider deadlines fail open to the original single-query plan. Planned recall +remains opt-in until the checked-in budget, safety, and official LongMemEval-V2 gates justify a +default change. For bi-temporal reads, `valid_at` selects what was true at a Unix timestamp and `known_at` selects what Engraphis had learned then. `as_of` remains a compatibility alias for `valid_at`; supplying @@ -447,6 +500,9 @@ changes end-to-end; managed compute is a separate readable-snapshot service. See [Subscribe to Pro](https://api.engraphis.com/account?plan=pro&interval=monthly&utm_source=engraphis&utm_medium=docs&utm_campaign=pro_conversion&utm_content=readme_pricing#billing) to support the project and add hosted services. +[Compare hosted plans](https://api.engraphis.com/account?plan=pro&interval=monthly&utm_source=engraphis&utm_medium=docs&utm_campaign=pro_conversion&utm_content=readme_intro#billing) +when you are ready to evaluate the service boundary and billing options. + | | Free (available now) | Pro: $10/mo or $100/yr | Team: $20/seat/mo or $200/seat/yr | |---|---|---|---| | Dashboard WebUI (with built-in inspector) | ✓ | ✓ | ✓ | @@ -677,6 +733,7 @@ All via environment (or `.env`): | `ENGRAPHIS_CHUNK_TOKENIZER_REVISION` | Not set | Optional immutable tokenizer/model revision recorded in the chunk-counter identity; pin this for reproducible benchmark artifacts | | `ENGRAPHIS_GRAPH_EXTRACTOR` | `regex` | `regex` = offline heuristic NER; `none` = disable heuristic text extraction (validated `llm_structured` metadata still feeds the graph) | | `ENGRAPHIS_RETENTION_SUPERVISOR` | `none` | `none` = deterministic only; `llm` = sends a bounded excerpt to the configured provider for advisory ephemeral/normal/critical classification | +| `ENGRAPHIS_ALLOW_AUTOMATIC_CRITICAL_RETENTION` | `false` | Opt in only when an LLM supervisor may automatically assign the long-lived `critical` class; explicit user-selected critical retention is unaffected | | `ENGRAPHIS_WHISPER_MODEL` | Not set | Enables local faster-whisper audio/video transcription | | `ENGRAPHIS_POSTGRES_DSN` | Not set | CLI-only PostgreSQL source; used for the connection and never stored | | `ENGRAPHIS_POSTGRES_CONNECT_TIMEOUT` | `10` | PostgreSQL introspection connection timeout in seconds (bounded to 1–120) | @@ -696,7 +753,7 @@ All via environment (or `.env`): | `ENGRAPHIS_CLOUD_REFRESH_CREDENTIAL` | Not set | Bootstrap-only rotating hosted credential; after first use the owner-only cloud session replacement takes precedence | | `ENGRAPHIS_CLOUD_TOKEN_SUBJECT` | `member` | Subject fixed during hosted bootstrap (`device` or `member`); set explicitly with an environment-only refresh credential | | `ENGRAPHIS_CLOUD_ACCESS_TOKEN` | Not set | Optional short-lived access token for ephemeral jobs | -| `ENGRAPHIS_MANAGED_COMPUTE_CONSENT` | *(auto)* | Operator override only; default follows whether a cloud session is configured (connected = allowed, local-only = never). `0` opts a connected installation out, `1` forces it on | +| `ENGRAPHIS_MANAGED_COMPUTE_CONSENT` | *(auto)* | Operator override only; default follows whether a cloud session is configured (connected = allowed, local-only = never). `0` opts a connected installation out; `1` permits local snapshot preparation but does not create a cloud credential or authorize an upload | See `.env.example` for the full customer-runtime and managed-service client options. diff --git a/docs/HOSTING_RAILWAY.md b/docs/HOSTING_RAILWAY.md index 56294475..b6cdd1fa 100644 --- a/docs/HOSTING_RAILWAY.md +++ b/docs/HOSTING_RAILWAY.md @@ -62,6 +62,13 @@ The `/data` volume contains the local memory database and customer state. A rede volume loses local data. Use Railway volume snapshots or an encrypted backup process and test restoration into a disposable customer node. +The checked-in `railway.json` gives Uvicorn a 30-second SIGTERM-to-SIGKILL drain window so it can +finish in-flight requests and close SQLite before Railway replaces the process. Railway volumes +cannot be mounted by overlapping replicas, so volume-backed redeploys still have a short planned +downtime even when a readiness check is configured. Do not enable replicas or multi-region +deployment for this SQLite-backed node; restore a snapshot into a separate disposable service to +test recovery instead. + Before relying on the deployment, verify: - `/api/ready` returns 200 after a clean deploy; diff --git a/docs/MCP_TOOLS.md b/docs/MCP_TOOLS.md index 4a7e6ed1..a3ebbc82 100644 --- a/docs/MCP_TOOLS.md +++ b/docs/MCP_TOOLS.md @@ -4,12 +4,20 @@ Engraphis exposes MCP tools for writing and recalling memory, managing history, checking the local store. Start with `engraphis_recall_context` when an agent needs prompt-ready context, and use `engraphis_remember` when it learns a durable fact. -Trust boundary: `engraphis_remember` is for a deliberate local-agent fact and defaults to -`source=agent, trusted=true`. Web, import, sync, tool, and other external source labels are -server-downgraded to untrusted even if a caller supplies `trusted=true`; use `engraphis_ingest` -for raw text, which is always untrusted. MCP recall and context are prompt-safe by default and -exclude untrusted records. The service-level `include_untrusted=True` option is reserved for -explicit inspection workflows and must not be copied into a model prompt. +Trust boundary: every MCP write is `pending` review, regardless of a caller-supplied `source` or +`trusted` label. The same rule applies to REST/dashboard-intent, import, sync, and extractor +ingress; detector matches are `quarantined` immediately. Pending and quarantined records are +available only to explicit inspection workflows and never appear in prompt-ready MCP recall or +context, nor can they feed resolution, links, graph/code backfill, or derived prompt context. +`include_untrusted=True` is inspection-only and must never be copied into a model prompt. + +MCP deliberately has no approval tool. Approval creates a fresh, audited `approved` successor +while retaining the reviewed source and its provenance. In the local product it is available only +through the CSRF-bound dashboard review action (with `ENGRAPHIS_API_TOKEN`) or the interactive +TTY command `python -m scripts.approve_memory MEM_ID --reason "..."`; the command rejects +redirected input and requires a typed confirmation. Hosted approval is an owner/admin action of +the private hosted service. Direct in-process `MemoryEngine` use is a trusted-code boundary for +code that already has local database authority, not a transport permission. | Category | Tool | What it does | |---|---|---| @@ -38,12 +46,21 @@ explicit inspection workflows and must not be copied into a model prompt. | Audit | `engraphis_export_receipts` | Exports a shareable receipt-only audit bundle. | | Governance | `engraphis_forget` | Retires a memory by closing its validity window. It does not delete history. | | Governance | `engraphis_pin` | Prevents future automatic decay or pruning. | -| Governance | `engraphis_correct` | Replaces memory content without losing the previous version. | -| Governance | `engraphis_promote` | Widens a memory's scope while preserving and linking its narrower history. | +| Governance | `engraphis_correct` | Replaces memory content without losing the previous version; governed provenance remains pending unless separately approved. | +| Governance | `engraphis_promote` | Widens an explicitly approved memory's scope while preserving and linking its narrower history. | | Session | `engraphis_start_session` / `engraphis_end_session` | Starts or closes a work session. Exact retries are safe; `force_new=true` creates another session. | | Operations | `engraphis_stats` | Returns memory counts for health checks. | | Operations | `engraphis_check_update` | Refreshes the release cache and reports whether a newer version is available. | +All four recall tools (`engraphis_recall`, `engraphis_recall_context`, +`engraphis_recall_grounded`, and the `engraphis_answer` alias) accept `planning="off"|"auto"` +and optional `mtype_limits`, for example `{"working": 1, "semantic": 3}`. Planning is off by +default. Type limits are post-rerank maxima and can intentionally return fewer than `k`; they do not +raise a memory type's relevance. Responses include a stable `context_revision`. Planner details, +per-query rankings, type-limit drops, and fallback reasons are returned only when +`diagnostics=true`. Every planned query remains inside the caller's scope, temporal, trust, and +prompt-eligibility filters, and grounded recall still measures support against the original query. + For parameter details and return shapes, see the tool descriptions exposed by the MCP server. The [agent connection guide](AGENT_CONNECT.md) explains local and hosted connections, and the [Kilo Code guide](KILO_CODE_INTEGRATION.md) shows a complete editor integration. diff --git a/docs/dashboard-button-qa.md b/docs/dashboard-button-qa.md index 249e0487..85174d18 100644 --- a/docs/dashboard-button-qa.md +++ b/docs/dashboard-button-qa.md @@ -12,7 +12,7 @@ consolidation state. The four lanes covered: - primary Ledger navigation, memory creation, grounded Ask, and theme controls; - Library, import/editor actions, and empty-form behavior; -- Graph & Relations, Provenance, Manage, exports, saved views, and switches; +- Relationships, Provenance, Manage, exports, saved views, and switches; - broad regression including Classic and responsive/mobile keyboard behavior. ## Button coverage diff --git a/engraphis/backends/query_planner.py b/engraphis/backends/query_planner.py new file mode 100644 index 00000000..c1e7309b --- /dev/null +++ b/engraphis/backends/query_planner.py @@ -0,0 +1,93 @@ +"""Optional LLM-backed query planning. + +This module is outside ``core`` by design. The caller injects any object satisfying +the core ``LLM`` protocol; no provider SDK is a required dependency. +""" +from __future__ import annotations + +from typing import Optional + +from engraphis.core.interfaces import ( + LLM, + MemoryType, + PlannedQuery, + RetrievalPlan, + SearchFilter, +) +from engraphis.core.query_planner import MAX_PLANNED_PRIORITY + + +class LLMQueryPlanner: + """Ask an injected LLM for a bounded structured retrieval plan.""" + + identity = "engraphis.query-planner.llm.v1" + + def __init__(self, llm: LLM) -> None: + self.llm = llm + + def plan( + self, + query: str, + *, + filter: Optional[SearchFilter] = None, + timeout_s: Optional[float] = None, + ) -> RetrievalPlan: + del filter + schema = { + "type": "object", + "required": ["queries"], + "properties": { + "queries": { + "type": "array", + "maxItems": 3, + "items": { + "type": "object", + "required": ["text", "priority", "profile"], + "properties": { + "text": {"type": "string"}, + "priority": { + "type": "integer", + "minimum": 1, + "maximum": MAX_PLANNED_PRIORITY, + }, + "profile": { + "type": "string", + "enum": ["balanced", "lexical", "graph", "code"], + }, + "mtypes": { + "type": "array", + "items": {"enum": [item.value for item in MemoryType]}, + }, + }, + }, + }, + "mtype_limits": {"type": "object"}, + "reason_codes": {"type": "array", "items": {"type": "string"}}, + }, + } + prompt = ( + "Plan memory retrieval for the query below. Keep the original query first " + "with priority 1. Add no more than two distinct queries. Use only balanced, " + "lexical, graph, or code profiles. Type limits are maxima, not boosts.\n\n" + f"QUERY:\n{query}" + ) + kwargs = {"timeout": timeout_s} if timeout_s is not None else {} + raw = self.llm.extract_json(prompt, schema, **kwargs) + if not isinstance(raw, dict): + raise ValueError("planner output must be an object") + queries = [] + for item in raw.get("queries", []): + if not isinstance(item, dict): + continue + queries.append(PlannedQuery( + text=str(item.get("text") or ""), + priority=item.get("priority", 1), + profile=str(item.get("profile") or "balanced"), + mtypes=tuple(MemoryType(value) for value in item.get("mtypes", [])), + )) + limits = { + MemoryType(key): value + for key, value in (raw.get("mtype_limits") or {}).items() + } + reasons = tuple(str(value) for value in raw.get("reason_codes", [])) + return RetrievalPlan(tuple(queries), limits, reasons) diff --git a/engraphis/backends/sync_relay.py b/engraphis/backends/sync_relay.py index 7baf623a..f357ce7c 100644 --- a/engraphis/backends/sync_relay.py +++ b/engraphis/backends/sync_relay.py @@ -533,6 +533,15 @@ def _request(self, url: str, *, method: str, data: Optional[bytes] = None, # Never propagate an untrusted relay response body or the HTTPError's # request URL. Either can contain PII, signed query data, or reflected # credentials and these errors are surfaced by sync APIs and CLIs. + # HTTPError owns the failing response stream but does not participate in + # the successful response context manager above. Close it without reading + # its untrusted body so repeated authorization/relay failures cannot leak + # sockets or file descriptors (and cannot allocate attacker-controlled + # error payloads merely for diagnostics). + try: + exc.close() + except Exception: # noqa: BLE001 - error cleanup must not mask the status + pass if exc.code == 402: raise RelayError( "Cloud Sync entitlement is inactive (upgrade or renew required)", diff --git a/engraphis/cloud_features.py b/engraphis/cloud_features.py index 7d90e06a..e0885737 100644 --- a/engraphis/cloud_features.py +++ b/engraphis/cloud_features.py @@ -7,6 +7,7 @@ """ from __future__ import annotations +import http.client import hashlib import json import os @@ -115,6 +116,13 @@ def redirect_request(self, req, fp, code, msg, headers, newurl): return None +# Error bodies are untrusted diagnostic data and their best-effort drain must not replace +# the stable status response. In particular, a truncated chunked body raises +# ``http.client.IncompleteRead`` (an ``HTTPException``, not an ``OSError``), which otherwise +# escaped from this error path as a raw traceback. +_DRAIN_FAILURES = (OSError, ValueError, http.client.HTTPException) + + def managed_compute_consent() -> bool: """Return whether this installation may upload workspace content for managed work. @@ -489,13 +497,24 @@ def _request(self, method: str, path: str, payload: Optional[dict] = None) -> di raw = response.read(MAX_RESPONSE_BYTES + 1) except urllib.error.HTTPError as exc: message, transient = _public_http_error(exc.code) - exc.close() + # Do not inspect or reflect provider diagnostics: they can contain internal + # details. Drain only to release the connection, and guard the drain and close + # independently because both can fail for a malformed/truncated response. + try: + exc.read(MAX_RESPONSE_BYTES + 1) + except _DRAIN_FAILURES: + pass + finally: + try: + exc.close() + except _DRAIN_FAILURES: + pass raise CloudFeatureError( message, status=exc.code, transient=transient, ) from None - except (urllib.error.URLError, TimeoutError, OSError) as exc: + except (urllib.error.URLError, TimeoutError, OSError, http.client.HTTPException) as exc: raise CloudFeatureError( "Engraphis Cloud is temporarily unreachable.", transient=True, ) from exc diff --git a/engraphis/cloud_session.py b/engraphis/cloud_session.py index 62fec3e4..922e2c13 100644 --- a/engraphis/cloud_session.py +++ b/engraphis/cloud_session.py @@ -36,6 +36,13 @@ ) _MAX_RESPONSE_BYTES = 64 * 1024 +# Cloud-session state is read through the same cap. A syntactically valid provider response +# can otherwise carry one oversized credential string, be written successfully, and make the +# newly redeemed single-use connection permanently unreadable on the very next request. +_MAX_SESSION_BYTES = 64 * 1024 +# Access and refresh credentials are sent in HTTP headers/bodies on later calls. Bound each +# provider-supplied string well below both the persisted-state cap and common header limits. +_MAX_CREDENTIAL_BYTES = 8 * 1024 _REFRESH_THREAD_LOCK = threading.RLock() _UNUSABLE_REFRESHES: set[tuple[str, str]] = set() @@ -280,9 +287,12 @@ def _load() -> dict: def _save(value: dict) -> None: path = _session_path() ensure_private_dir(path.parent) - atomic_private_text( - path, json.dumps(value, sort_keys=True, separators=(",", ":")), harden_parent=True, - ) + payload = json.dumps(value, sort_keys=True, separators=(",", ":")) + if len(payload.encode("utf-8")) > _MAX_SESSION_BYTES: + raise CloudSessionError( + "The cloud session response is too large to save safely.", status=409 + ) + atomic_private_text(path, payload, harden_parent=True) def preflight_save() -> Path: @@ -569,7 +579,7 @@ def record_billing_denial() -> bool: return False -def text_field(response: dict, key: str) -> str: +def text_field(response: dict, key: str, *, max_bytes: int = _MAX_CREDENTIAL_BYTES) -> str: """Return ``response[key]`` when it is a string, else ``""``. Never a ``repr``. ``str(response.get(key) or "")`` looks like a coercion but is not a validation: JSON @@ -584,7 +594,13 @@ def text_field(response: dict, key: str) -> str: """ value = response.get(key) - return value.strip() if isinstance(value, str) else "" + if not isinstance(value, str): + return "" + value = value.strip() + try: + return value if len(value.encode("utf-8")) <= max_bytes else "" + except UnicodeEncodeError: + return "" def save_bootstrap(response: dict, *, control_url: str, @@ -831,8 +847,21 @@ def access_for_workspace( # Do not create the owner-only state directory merely to report an unconnected # installation. An absent session yields the normal structured "connect first" # response; a stale home-directory mount yields a structured, retryable error from - # ``_load`` rather than an unhandled filesystem exception. The authoritative session - # record is still loaded again under the lock below before any credential is used. + # ``_load`` rather than an unhandled filesystem exception. A known-spent refresh must + # stay distinguishable from no session: calling it a new-installation 401 lets the UI + # offer a trial even though retrying that credential would be a replay. The authoritative + # session record is still loaded again under the lock below before any credential is used. + preflight_saved = _load() + preflight_refresh = str(preflight_saved.get("refresh_credential") or "").strip() + preflight_refresh = preflight_refresh or os.environ.get( + "ENGRAPHIS_CLOUD_REFRESH_CREDENTIAL", "" + ).strip() + if _refresh_is_unusable(preflight_saved, preflight_refresh): + raise CloudSessionError( + "The saved cloud refresh credential cannot be reused; connect this " + "installation again.", + status=409, + ) if not configured(require_compute=require_compute): raise CloudSessionError( "Connect this installation to Engraphis Cloud first.", status=401 @@ -924,7 +953,7 @@ def access_for_workspace( updated.update(declared) try: _save(updated) - except (OSError, RuntimeError) as exc: + except (OSError, RuntimeError, CloudSessionError) as exc: # The control plane has already consumed ``refresh``. Leaving that stale # value usable after a local write fault makes the next request replay it, # which can revoke the credential family. Retire it in memory first (so this diff --git a/engraphis/config.py b/engraphis/config.py index 214f175e..fb6c4ca4 100644 --- a/engraphis/config.py +++ b/engraphis/config.py @@ -656,6 +656,11 @@ class Settings: retention_supervisor: str = field( default_factory=lambda: _env("ENGRAPHIS_RETENTION_SUPERVISOR", "none").lower() ) + # A remote retention supervisor is advisory by default. Keep automatic critical + # retention at normal strength unless an owner explicitly opts in. + allow_automatic_critical_retention: bool = field( + default_factory=lambda: _env_bool("ENGRAPHIS_ALLOW_AUTOMATIC_CRITICAL_RETENTION", False) + ) loop_interval: int = field(default_factory=lambda: _env_int("ENGRAPHIS_LOOP_INTERVAL", 60)) loop_top_k: int = field(default_factory=lambda: _env_int("ENGRAPHIS_LOOP_TOP_K", 20)) diff --git a/engraphis/core/adaptive_context.py b/engraphis/core/adaptive_context.py index bfc61fb6..14de8368 100644 --- a/engraphis/core/adaptive_context.py +++ b/engraphis/core/adaptive_context.py @@ -7,6 +7,8 @@ """ from __future__ import annotations +import hashlib +import json from dataclasses import dataclass from typing import Callable, Optional @@ -30,6 +32,28 @@ class AdaptiveContextResult: truncated_history: bool = False token_counter: str = "unknown" recall: Optional[RecallResult] = None + context_revision: str = "" + + def __post_init__(self) -> None: + if self.context_revision: + return + # Reuse the recall revision only when that packed recall context is the + # context actually emitted. A weak-retrieval history fallback retains the + # RecallResult for diagnostics, but its prompt prefix is different and must + # therefore receive a different cache revision. + if ( + self.recall is not None + and self.recall.context_revision + and self.context == self.recall.context + ): + self.context_revision = self.recall.context_revision + return + canonical = json.dumps( + {"token_counter": self.token_counter, "context": self.context}, + ensure_ascii=False, + separators=(",", ":"), + ) + self.context_revision = hashlib.sha256(canonical.encode("utf-8")).hexdigest() def to_dict(self) -> dict: """Return privacy-safe routing telemetry without duplicating source text.""" @@ -45,6 +69,7 @@ def to_dict(self) -> dict: "widened": self.widened, "truncated_history": self.truncated_history, "token_counter": self.token_counter, + "context_revision": self.context_revision, } @@ -88,7 +113,11 @@ def fit_recent_history( (index for index, character in enumerate(fitted) if character.isspace()), -1, ) - fitted = fitted[boundary + 1:].lstrip() if boundary >= 0 else "" + # With an unbroken tail (URL, hash, base64, minified code), the binary-search + # suffix already satisfies the declared budget. Returning an empty history + # here discarded exactly the recent fallback state this helper exists to keep. + if boundary >= 0: + fitted = fitted[boundary + 1:].lstrip() # A non-additive custom tokenizer can have unusual boundary behavior. This # final guard preserves the hard-budget contract even for such counters. diff --git a/engraphis/core/consolidate.py b/engraphis/core/consolidate.py index 62e4ed0e..a3d25b1c 100644 --- a/engraphis/core/consolidate.py +++ b/engraphis/core/consolidate.py @@ -31,7 +31,7 @@ from engraphis.core import scoring from engraphis.core.interfaces import MemoryRecord, MemoryType, Scope, SearchFilter -from engraphis.core.poisoning import provenance_is_trusted +from engraphis.core.poisoning import prompt_eligible from engraphis.core.textutil import estimate_tokens, jaccard, tokenize logger = logging.getLogger(__name__) @@ -130,8 +130,12 @@ def consolidate(engine, *, workspace_id: str, repo_id: Optional[str] = None, flt = SearchFilter(workspace_id=workspace_id, repo_id=repo_id, scopes=MAINTENANCE_SCOPES) - episodic = store.list_memories( - _replace(flt, mtypes=[MemoryType.EPISODIC]), limit=DISTILL_SCAN_LIMIT) + episodic = [ + memory for memory in store.list_memories( + _replace(flt, mtypes=[MemoryType.EPISODIC]), limit=DISTILL_SCAN_LIMIT + ) + if prompt_eligible(memory.provenance, memory.metadata) + ] # A digest inherits its owner from its first source. Cluster only records that have # the exact same owner, otherwise a workspace sweep could write one repo's digest with # another repo's content (or mix scope visibility). @@ -389,7 +393,8 @@ def _inherit_safety(engine, memory_id: str, sources: list[MemoryRecord]) -> tupl [record.sensitivity or "normal"] + [(m.sensitivity or "normal") for m in sources], key=lambda value: _SENSITIVITY_RANK.get(value, len(_SENSITIVITY_RANK)), ) - trusted = provenance_is_trusted(record.provenance) and _sources_are_trusted(sources) + trusted = (prompt_eligible(record.provenance, record.metadata) + and _sources_are_trusted(sources)) provenance = dict(record.provenance or {}) provenance["trusted"] = trusted metadata = dict(record.metadata or {}) @@ -407,7 +412,7 @@ def _inherit_safety(engine, memory_id: str, sources: list[MemoryRecord]) -> tupl def _sources_are_trusted(sources: list[MemoryRecord]) -> bool: """Require every consolidated source to carry an explicit trust approval.""" - return all(provenance_is_trusted(source.provenance) for source in sources) + return all(prompt_eligible(source.provenance, source.metadata) for source in sources) def _already_consolidated(store, memory_id: str) -> bool: @@ -775,9 +780,16 @@ def consolidate_profiles(engine, *, workspace_id: str, repo_id: Optional[str] = report: dict = {"workspace_id": workspace_id, "repo_id": repo_id, "dry_run": dry_run, "entities_considered": 0, "profiles_created": [], "skipped_existing": 0} - live = [m for m in store.list_memories(_replace(flt, mtypes=DURABLE_TYPES), - limit=PROFILE_SCAN_LIMIT) - if m.metadata.get("provenance", {}).get("source") != "profile_consolidation"] + live = [ + memory for memory in store.list_memories( + _replace(flt, mtypes=DURABLE_TYPES), limit=PROFILE_SCAN_LIMIT + ) + if ( + prompt_eligible(memory.provenance, memory.metadata) + and memory.metadata.get("provenance", {}).get("source") + != "profile_consolidation" + ) + ] p_before = p_after = 0 for ent in store.list_entities(flt, limit=2000): diff --git a/engraphis/core/engine.py b/engraphis/core/engine.py index e54a3f9c..afc10340 100644 --- a/engraphis/core/engine.py +++ b/engraphis/core/engine.py @@ -33,18 +33,22 @@ from engraphis.core.interfaces import ( MemoryRecord, MemoryType, + GraphTraversalPolicy, + QueryPlanner, RetentionDecision, Scope, SearchFilter, ) from engraphis.core.poisoning import ( + REVIEW_APPROVED, + REVIEW_PENDING, PoisoningDecision, apply_quarantine_metadata, assess_untrusted_payload, inspection_eligible, - metadata_is_trusted, + metadata_is_quarantined, prompt_eligible, - provenance_is_trusted, + provenance_is_approved, ) from engraphis.core.recall import RecallEngine, RecallResult from engraphis.core.retrieval_policy import ( @@ -302,12 +306,22 @@ def match(self, hay_lower: str, hay_tokens: set) -> tuple[set, list]: class MemoryEngine: def __init__(self, store: Store, embedder, vector_index, reranker=None, *, auto_evolve: bool = True, extractor=None, - graph_extractor=None, retention_supervisor=None) -> None: + graph_extractor=None, retention_supervisor=None, + allow_automatic_critical_retention: bool = False, + graph_traversal_policy: Optional[GraphTraversalPolicy] = None, + query_planner: Optional[QueryPlanner] = None) -> None: self.store = store self.embedder = embedder self.index = vector_index self.reranker = reranker or IdentityReranker() - self.recall_engine = RecallEngine(store, embedder, vector_index, self.reranker) + self.recall_engine = RecallEngine( + store, + embedder, + vector_index, + self.reranker, + graph_traversal_policy=graph_traversal_policy, + query_planner=query_planner, + ) # Memory evolution (A-MEM-style): writing a new note also updates # how its neighbors are connected, so the network improves bidirectionally. self.auto_evolve = auto_evolve @@ -316,6 +330,9 @@ def __init__(self, store: Store, embedder, vector_index, reranker=None, # Optional graph extractor (backends.graph_extractor). None = no graph population. self.graph_extractor = graph_extractor self.retention_supervisor = retention_supervisor + # A remote classifier is advisory. It cannot silently grant the long-lived + # "critical" class unless the host deliberately opts into that policy. + self.allow_automatic_critical_retention = bool(allow_automatic_critical_retention) # Serializes the resolve→insert critical section of the write path (see # remember_with_resolution). RLock: ingest()/import paths may nest writes. self._write_lock = threading.RLock() @@ -334,7 +351,10 @@ def create(cls, db_path: str = ":memory:", *, embed_model: Optional[str] = None, rerank_model: Optional[str] = None, extractor: str = "none", graph_extractor: str = "none", retention_supervisor: str = "none", - auto_evolve: bool = True, connect=None) -> "MemoryEngine": + allow_automatic_critical_retention: bool = False, + auto_evolve: bool = True, connect=None, + graph_traversal_policy: Optional[GraphTraversalPolicy] = None, + query_planner: Optional[QueryPlanner] = None) -> "MemoryEngine": from engraphis.backends.extractor import PassthroughExtractor, get_extractor from engraphis.backends.graph_extractor import get_graph_extractor as _get_ge from engraphis.backends.retention import get_retention_supervisor @@ -349,7 +369,10 @@ def create(cls, db_path: str = ":memory:", *, embed_model: Optional[str] = None, supervisor = get_retention_supervisor(retention_supervisor) engine = cls(store, embedder, index, reranker, auto_evolve=auto_evolve, extractor=ext, graph_extractor=ge, - retention_supervisor=supervisor) + retention_supervisor=supervisor, + allow_automatic_critical_retention=allow_automatic_critical_retention, + graph_traversal_policy=graph_traversal_policy, + query_planner=query_planner) engine._rebuild_versioned_embeddings() return engine @@ -429,7 +452,8 @@ def remember_with_resolution(self, content: str, *, workspace_id: str, metadata: Optional[dict] = None, valid_from: Optional[float] = None, resolve_conflicts: bool = True, candidate_k: int = 5, subject_key: str = "", claim_kind: str = "", - _trusted_graph_keys: Optional[frozenset] = None) -> dict: + _trusted_graph_keys: Optional[frozenset] = None, + _approval_override: bool = False) -> dict: """Store one memory with deterministic conflict resolution. Returns ``{"id", "op", ...}`` where ``op`` is one of: @@ -490,9 +514,23 @@ def remember_with_resolution(self, content: str, *, workspace_id: str, provenance["trusted"] = True provenance.setdefault("trust_origin", "local_engine") provenance.setdefault("source", "local_engine") + # The direct engine is an in-process capability. Public transports set an + # explicit pending state before reaching it; a direct trusted write remains + # compatible and is the only implicit local approval boundary. + if provenance.get("trusted") is True: + provenance.setdefault("review_state", REVIEW_APPROVED) + else: + provenance.setdefault("review_state", REVIEW_PENDING) write_metadata["provenance"] = provenance - poisoning = assess_untrusted_payload(content, title=title, metadata=write_metadata) - trusted_write = metadata_is_trusted(write_metadata) + poisoning = ( + PoisoningDecision(False) + if _approval_override else + assess_untrusted_payload(content, title=title, metadata=write_metadata) + ) + # Resolution changes existing validity and links. It therefore runs only for + # content that already satisfies the full prompt/derived-state predicate; + # pending evidence is stored passively and cannot reinforce or supersede it. + trusted_write = prompt_eligible(provenance, write_metadata) text = f"{title}\n{content}" if title else content # Embedding is the expensive, thread-safe part — compute it BEFORE taking the # write lock so concurrent writers only serialize the fast resolve+insert step. @@ -549,15 +587,14 @@ def _resolve_and_store(self, content: str, *, text: str, vec: Optional[np.ndarra # Untrusted records are retained as passive inspection evidence. They may # not deduplicate into, invalidate, relate to, reinforce, or otherwise # mutate higher-trust memory; that is a trust lattice, not a detector score. - if resolve_conflicts and not poisoning.quarantined: + if resolve_conflicts and trusted_write and not poisoning.quarantined: decision, neighbors = self._resolve_against_neighbors( text, vec, workspace_id=workspace_id, repo_id=repo_id, session_id=session_id, scope=scope, mtype=mtype, candidate_k=candidate_k, subject_key=subject_key, claim_kind=claim_kind, valid_at=valid_from, content=content, - trusted_write=trusted_write, ) - if (resolve_conflicts and not poisoning.quarantined + if (resolve_conflicts and trusted_write and not poisoning.quarantined and subject_key and valid_from is not None): # A durable claim has a temporal identity in addition to its text. A # scheduled successor can be a better prose match than the version visible @@ -574,7 +611,7 @@ def _resolve_and_store(self, content: str, *, text: str, vec: Optional[np.ndarra record for record in claim_history if record.valid_from is not None and record.valid_from <= valid_from and (record.valid_to is None or valid_from < record.valid_to) - and provenance_is_trusted(record.provenance) == trusted_write + and prompt_eligible(record.provenance, record.metadata) ] if predecessors: predecessor = max( @@ -821,6 +858,11 @@ def _retention_signal(self, content: str, *, title: str, mtype: MemoryType, label = str(decision.label or "normal").lower() if label not in {"ephemeral", "normal", "critical"}: label = "normal" + if source == "llm" and label == "critical" and not self.allow_automatic_critical_retention: + # The supervisor sees text it does not authoritatively vouch for. Its + # "critical" label therefore defaults to normal retention; an explicit + # user/host retention_class remains a separate, bounded path. + label = "normal" if not decision.retain: label = "ephemeral" preset_stability = {"ephemeral": 0.25, "normal": 1.0, "critical": 8.0}[label] @@ -932,8 +974,7 @@ def _resolve_against_neighbors(self, text: str, vec: np.ndarray, *, workspace_id scope: Scope, mtype: MemoryType, candidate_k: int, subject_key: str = "", claim_kind: str = "", valid_at: Optional[float] = None, - content: Optional[str] = None, - trusted_write: bool = True): + content: Optional[str] = None): """Fetch same-scope neighbors via the vector index and run the deterministic resolver (``core.resolve``). Returns ``(decision, neighbors)`` so the caller can also evolve the neighborhood. Never raises — a broken/missing index degrades to @@ -971,7 +1012,7 @@ def _resolve_against_neighbors(self, text: str, vec: np.ndarray, *, workspace_id if (nrec and nrec.workspace_id == workspace_id and nrec.repo_id == repo_id and nrec.scope == scope and nrec.mtype == mtype and (scope != Scope.SESSION or nrec.session_id == session_id) - and provenance_is_trusted(nrec.provenance) == trusted_write + and prompt_eligible(nrec.provenance, nrec.metadata) and (memory_matches_filter(nrec, flt) or (current_fallback and nrec.expired_at is None and nrec.valid_to is None))): @@ -1002,7 +1043,7 @@ def _resolve_against_neighbors(self, text: str, vec: np.ndarray, *, workspace_id authoritative = [ record for record in claim_history if memory_matches_filter(record, flt, at=valid_at) - and provenance_is_trusted(record.provenance) == trusted_write + and prompt_eligible(record.provenance, record.metadata) ] if not authoritative and valid_at is not None: # A backfill before the first recorded version has no visible @@ -1014,7 +1055,7 @@ def _resolve_against_neighbors(self, text: str, vec: np.ndarray, *, workspace_id if record.expired_at is None and record.valid_from is not None and record.valid_from > valid_at - and provenance_is_trusted(record.provenance) == trusted_write + and prompt_eligible(record.provenance, record.metadata) ] if later: authoritative = [min( @@ -1150,6 +1191,8 @@ def recall(self, query: str, *, workspace_id: Optional[str] = None, diagnostics: bool = False, include_untrusted: bool = False, prompt_only: bool = False, + planning: str = "off", + mtype_limits: Optional[dict] = None, reinforce: bool = False) -> RecallResult: flt = self._recall_filter( workspace_id=workspace_id, repo_id=repo_id, session_id=session_id, @@ -1166,6 +1209,8 @@ def recall(self, query: str, *, workspace_id: Optional[str] = None, diagnostics=diagnostics, include_untrusted=bool(include_untrusted), prompt_only=bool(prompt_only), + planning=planning, + mtype_limits=mtype_limits, ) def adaptive_context( @@ -1188,6 +1233,8 @@ def adaptive_context( retrieval_profile: str = "balanced", candidate_depth: str = "adaptive", diagnostics: bool = False, + planning: str = "off", + mtype_limits: Optional[dict] = None, reinforce: bool = False, ) -> AdaptiveContextResult: """Choose raw history, compact recall, or a wider raw-history fallback. @@ -1295,6 +1342,8 @@ def adaptive_context( candidate_depth=candidate_depth, diagnostics=diagnostics, prompt_only=True, + planning=planning, + mtype_limits=mtype_limits, reinforce=False, ) # Confidence must describe evidence the agent will actually see, not a @@ -1383,6 +1432,8 @@ def grounded_recall(self, query: str, *, workspace_id: Optional[str] = None, token_budget: Optional[int] = None, retrieval_profile: str = "balanced", candidate_depth: str = "fixed", diagnostics: bool = False, + planning: str = "off", + mtype_limits: Optional[dict] = None, max_citations: int = 5, reinforce: bool = True): """Recall, then answer *strictly from* what was recalled — with citations and an explicit abstain when the evidence is too weak (``core.grounded``). Offline and @@ -1407,6 +1458,8 @@ def grounded_recall(self, query: str, *, workspace_id: Optional[str] = None, retrieval_profile=retrieval_profile, candidate_depth=candidate_depth, diagnostics=diagnostics, prompt_only=True, + planning=planning, + mtype_limits=mtype_limits, ) floor = _grounded.GROUNDED_SUPPORT_FLOOR if min_support is None else min_support answer = _grounded.build_grounded_answer(query, result, self.embedder, llm=llm, @@ -1566,8 +1619,20 @@ def correct(self, memory_id: str, new_content: str, *, reason: str = "", raise KeyError(f"no memory with id '{memory_id}'") metadata = dict(old.metadata) metadata["corrects"] = memory_id - if old.provenance: - metadata["provenance"] = dict(old.provenance) + # Missing/legacy provenance is deliberately not allowed to fall through to + # the direct-engine trusted default. Corrections preserve an approved source + # only when it was explicitly approved; every other record remains reviewable + # but prompt-ineligible. + metadata["provenance"] = ( + dict(old.provenance) + if provenance_is_approved(old.provenance) + else { + "source": str((old.provenance or {}).get("source") or "legacy_unverified"), + "trusted": False, + "review_state": REVIEW_PENDING, + "trust_origin": "derived_unapproved", + } + ) new_id = self.remember( new_content, workspace_id=old.workspace_id, repo_id=old.repo_id, session_id=old.session_id, mtype=old.mtype, @@ -1589,6 +1654,57 @@ def correct(self, memory_id: str, new_content: str, *, reason: str = "", # current recall while keeping semantic time travel complete. return {"id": new_id, "superseded": [memory_id], "reason": reason} + def approve_for_prompt(self, memory_id: str, *, reviewer: str, + reason: str = "", replacement_content: Optional[str] = None) -> dict: + """Create an explicitly approved successor for governed human review. + + This is intentionally an engine-only primitive. MCP and ordinary REST ingress + never expose it: their caller can be prompted by the very content under review. + The interactive dashboard/TTY owner ceremony is responsible for choosing a + reviewer identity before it calls this method. + """ + old = self.store.get_memory(memory_id) + if old is None: + raise KeyError(f"no memory with id '{memory_id}'") + reviewer = str(reviewer or "").strip() + if not reviewer: + raise ValueError("reviewer is required for approval") + content = str(replacement_content if replacement_content is not None else old.content) + metadata = { + "approved_from": old.id, + "approval": { + "reviewer": reviewer[:200], + "reason": str(reason or "")[:500], + }, + "provenance": { + "source": "human_review", + "trusted": True, + "review_state": REVIEW_APPROVED, + "trust_origin": "human_approval", + "approved_from": old.id, + }, + } + result = self.remember_with_resolution( + content, + workspace_id=old.workspace_id, + repo_id=old.repo_id, + session_id=old.session_id, + mtype=old.mtype, + scope=_writable_scope(old.scope, old.repo_id), + title=old.title, + importance=old.importance, + keywords=old.keywords, + metadata=metadata, + valid_from=old.valid_from, + resolve_conflicts=False, + _approval_override=True, + ) + self.store.audit( + "human_review", "approve", result["id"], + f"from={old.id}; reviewer={reviewer[:200]}; reason={str(reason or '')[:500]}", + ) + return {"id": result["id"], "approved_from": old.id, "reviewer": reviewer} + def promote(self, memory_id: str, target_scope: Scope, *, reason: str = "", actor: str = "user") -> dict: """Widen one live memory's scope without rewriting it in place. @@ -1603,7 +1719,7 @@ def promote(self, memory_id: str, target_scope: Scope, *, reason: str = "", raise KeyError(f"no memory with id '{memory_id}'") if not inspection_eligible(old.provenance, old.metadata): raise ValueError("untrusted memory cannot be promoted: record is quarantined") - if not provenance_is_trusted(old.provenance): + if not provenance_is_approved(old.provenance): raise ValueError("untrusted memory cannot be promoted; create a fresh approved local memory") now = now_ts() if (old.expired_at is not None @@ -1635,8 +1751,16 @@ def promote(self, memory_id: str, target_scope: Scope, *, reason: str = "", "to_scope": target_scope.value, "reason": reason[:500], } - if old.provenance: - metadata["provenance"] = dict(old.provenance) + metadata["provenance"] = ( + dict(old.provenance) + if provenance_is_approved(old.provenance) + else { + "source": str((old.provenance or {}).get("source") or "legacy_unverified"), + "trusted": False, + "review_state": REVIEW_PENDING, + "trust_origin": "derived_unapproved", + } + ) result = self.remember_with_resolution( old.content, @@ -1678,10 +1802,11 @@ def promote(self, memory_id: str, target_scope: Scope, *, reason: str = "", "reason": reason[:500], } promoted_provenance = dict(promoted.provenance) - trusted = all(bool((record.provenance or {}).get("trusted", True)) + trusted = all(provenance_is_approved(record.provenance) for record in (old, promoted)) if not trusted: promoted_provenance["trusted"] = False + promoted_provenance["review_state"] = REVIEW_PENDING promoted_metadata["provenance"] = promoted_provenance self.store.conn.execute( "UPDATE memories SET pinned=?, sensitivity=?, stability=?, access_count=?, " @@ -1771,7 +1896,7 @@ def merge(self, source_ids: list, merged_content: str, *, pinned_any = any(r.pinned for r in sources) sensitivity = max((r.sensitivity or "normal" for r in sources), key=lambda s: _SENSITIVITY_RANK.get(s, len(_SENSITIVITY_RANK))) - trusted = all(bool((r.provenance or {}).get("trusted", True)) for r in sources) + trusted = all(provenance_is_approved(r.provenance) for r in sources) if keywords is None: keywords, kseen = [], set() for r in sources: @@ -1791,13 +1916,32 @@ def merge(self, source_ids: list, merged_content: str, *, # loss from a governance operation that is supposed to preserve history. The # resolver is skipped here (the supersede decision is explicit), so the # still-live sources can't be deduplicated into, and evolution stays a no-op. + merge_metadata = { + "supersedes": list(ids), + "provenance": { + "source": "merge", + "trusted": trusted, + "review_state": REVIEW_APPROVED if trusted else REVIEW_PENDING, + "merges": list(ids), + }, + } + # A merge is not an approval ceremony. If any source was quarantined, + # preserve that containment even when the user supplies paraphrased merged + # content that no longer matches a detector rule. + if any( + metadata_is_quarantined(record.metadata) + or bool((record.provenance or {}).get("quarantined")) + for record in sources + ): + merge_metadata = apply_quarantine_metadata( + merge_metadata, + PoisoningDecision(True, reasons=("inherited_quarantine",)), + ) merged_id = self.remember( merged_content, workspace_id=primary.workspace_id, repo_id=repo_id, session_id=primary.session_id, mtype=mt, scope=sc, title=title_final, importance=importance, keywords=keywords, - metadata={"supersedes": list(ids), - "provenance": {"source": "merge", "trusted": trusted, - "merges": list(ids)}}, + metadata=merge_metadata, resolve_conflicts=False, # the supersede decision was just made explicitly ) # Persist inherited confidentiality + protection (the write path defaults @@ -1842,8 +1986,8 @@ def link(self, a: str, b: str, relation: str = "related", *, layer=None, if not all(inspection_eligible(record.provenance, record.metadata) for record in records): raise ValueError("quarantined memories cannot be linked") - if not all(provenance_is_trusted(record.provenance) for record in records): - raise ValueError("links require explicitly trusted memories") + if not all(provenance_is_approved(record.provenance) for record in records): + raise ValueError("links require explicitly approved memories") self.store.add_link(a, b, relation, layer=layer, reason=reason) def record_event(self, kind: str, content: str, *, workspace_id: str = "", @@ -2130,11 +2274,18 @@ def rebuild_code_memory_links(self, *, repo_id: str) -> int: linked = 0 after_memory_id = "" while True: - records = self.store.list_memories_page( + page = self.store.list_memories_page( memory_filter, after_id=after_memory_id, limit=250, ) - if not records: + if not page: break + records = [ + record for record in page + if prompt_eligible(record.provenance, record.metadata) + ] + if not records: + after_memory_id = page[-1].id + continue linked_per_memory = {record.id: 0 for record in records} symbol_cursor: Optional[tuple[str, str, str]] = None while True: @@ -2163,7 +2314,7 @@ def rebuild_code_memory_links(self, *, repo_id: str) -> int: last_symbol["file"], last_symbol["fqname"], last_symbol["id"], ) self.store.conn.commit() - after_memory_id = records[-1].id + after_memory_id = page[-1].id self.store.prune_code_memory_links(repo_id) return linked diff --git a/engraphis/core/graph_policy.py b/engraphis/core/graph_policy.py new file mode 100644 index 00000000..e997f09f --- /dev/null +++ b/engraphis/core/graph_policy.py @@ -0,0 +1,101 @@ +"""Deterministic, opt-in graph-traversal policies. + +Policies produce *soft* preferences for Engraphis's existing logical graph layers. +They do not alter SearchFilter enforcement, data visibility, graph construction, or +the local/offline default. The uniform policy is intentionally byte-for-byte +equivalent to the former weight calculation in the PPR graph arm. +""" +from __future__ import annotations + +import re +from typing import Optional + +from engraphis.core.interfaces import ( + GraphLayer, + GraphTraversalPlan, + SearchFilter, +) + + +_TOKEN_RE = re.compile(r"[a-z0-9_]+") +_CAUSAL_TERMS = frozenset({ + "because", "cause", "caused", "causes", "effect", "fix", "fixed", + "impact", "reason", "reasons", "result", "resulted", "trigger", "triggered", + "why", +}) +_TEMPORAL_TERMS = frozenset({ + "after", "before", "during", "earlier", "first", "last", "later", "latest", + "next", "previous", "then", "timeline", "when", +}) +_ENTITY_TERMS = frozenset({ + "belongs", "called", "entity", "member", "owner", "relationship", "related", + "who", "whose", +}) +_PREFERRED_WEIGHT = 4.0 +_FALLBACK_WEIGHT = 0.25 + + +class UniformGraphTraversalPolicy: + """The default policy: preserve the historical, layer-uniform PPR graph arm.""" + + identity = "engraphis.graph_traversal.uniform.v1" + + def plan( + self, + query: str, + *, + filter: Optional[SearchFilter] = None, + ) -> GraphTraversalPlan: + del query, filter + return GraphTraversalPlan() + + +class DeterministicIntentGraphTraversalPolicy: + """Prefer one graph layer for strong, dependency-free query signals. + + This deliberately does not attempt a broad natural-language understanding + problem. Ambiguous queries stay uniform; a selected layer still leaves every + visible alternative reachable at a fixed non-zero floor. + """ + + identity = "engraphis.graph_traversal.intent_layered.v1" + + def plan( + self, + query: str, + *, + filter: Optional[SearchFilter] = None, + ) -> GraphTraversalPlan: + del filter # SearchFilter is a hard retrieval boundary, not a routing hint. + tokens = frozenset(_TOKEN_RE.findall(str(query or "").casefold())) + preferred, reason = self._preferred_layer(tokens) + if preferred is None: + return GraphTraversalPlan() + return GraphTraversalPlan( + intent=preferred.value, + layer_weights=tuple( + (layer, _PREFERRED_WEIGHT if layer == preferred else _FALLBACK_WEIGHT) + for layer in GraphLayer + ), + reason_codes=(reason,), + ) + + @staticmethod + def _preferred_layer(tokens: frozenset[str]) -> tuple[Optional[GraphLayer], str]: + # Clear interrogatives are stronger evidence than a relation word elsewhere + # in the question: "when did X cause Y?" is temporal, while "why did X + # happen after Y?" remains causal. This small precedence rule avoids + # pretending that a bag of cue words is a general NLU classifier. + if "why" in tokens: + return GraphLayer.CAUSAL, "causal_query_cue" + if "when" in tokens: + return GraphLayer.TEMPORAL, "temporal_query_cue" + if {"who", "whose"} & tokens: + return GraphLayer.ENTITY, "entity_query_cue" + if tokens & _TEMPORAL_TERMS: + return GraphLayer.TEMPORAL, "temporal_query_cue" + if tokens & _CAUSAL_TERMS: + return GraphLayer.CAUSAL, "causal_query_cue" + if tokens & _ENTITY_TERMS: + return GraphLayer.ENTITY, "entity_query_cue" + return None, "" diff --git a/engraphis/core/grounded.py b/engraphis/core/grounded.py index 30446568..61e2f977 100644 --- a/engraphis/core/grounded.py +++ b/engraphis/core/grounded.py @@ -89,6 +89,10 @@ class GroundedAnswer: candidate_k_used: int = 50 candidate_depth_reason: str = "fixed requested depth" retrieval_trace: Optional[list[dict]] = None + context_revision: str = "" + planning_mode: str = "off" + planning_details: Optional[dict] = None + graph_traversal_details: Optional[list[dict]] = None def to_dict(self) -> dict: payload = { @@ -109,9 +113,15 @@ def to_dict(self) -> dict: "candidate_k_requested": self.candidate_k_requested, "candidate_k_used": self.candidate_k_used, "candidate_depth_reason": self.candidate_depth_reason, + "context_revision": self.context_revision, + "planning": self.planning_mode, } if self.retrieval_trace is not None: payload["retrieval_trace"] = self.retrieval_trace + if self.planning_details is not None: + payload["planning_details"] = self.planning_details + if self.graph_traversal_details is not None: + payload["graph_traversal_details"] = self.graph_traversal_details return payload @@ -340,6 +350,10 @@ def build_grounded_answer(query: str, result: RecallResult, embedder, *, "candidate_k_used": result.candidate_k_used, "candidate_depth_reason": result.candidate_depth_reason, "retrieval_trace": result.retrieval_trace, + "context_revision": result.context_revision, + "planning_mode": result.planning_mode, + "planning_details": result.planning_details, + "graph_traversal_details": result.graph_traversal_details, } recall_metadata["usage"]["answer_tokens"] = 0 diff --git a/engraphis/core/interfaces.py b/engraphis/core/interfaces.py index fd1e26e6..d5201051 100644 --- a/engraphis/core/interfaces.py +++ b/engraphis/core/interfaces.py @@ -161,6 +161,28 @@ class ContextUsage: token_counter: str = "estimate_tokens" +@dataclass(frozen=True) +class PlannedQuery: + """One bounded retrieval query emitted by a ``QueryPlanner``. + + ``priority`` is one-based: lower values contribute more weight during rank + fusion. ``mtypes`` narrows only this query; the caller's scope, temporal, and + trust filters remain mandatory for every planned query. + """ + text: str + priority: int = 1 + profile: str = "balanced" + mtypes: tuple[MemoryType, ...] = () + + +@dataclass(frozen=True) +class RetrievalPlan: + """A bounded, inspectable plan for one recall request.""" + queries: tuple[PlannedQuery, ...] + mtype_limits: dict[MemoryType, int] = field(default_factory=dict) + reason_codes: tuple[str, ...] = () + + @dataclass class Node: """A knowledge-graph node (entity or concept).""" @@ -306,11 +328,100 @@ def candidate_depth(self, query: str, *, k: int, ceiling: int, profile: str, mode: str) -> tuple[int, str]: ... +@dataclass(frozen=True) +class GraphTraversalPlan: + """Inspectable, bounded layer preferences for one graph-retrieval query. + + Layer values are soft multipliers, never permissions: ``SearchFilter`` remains + the only mechanism allowed to include or exclude graph layers, scope, temporal + visibility, or trust-sensitive records. An empty tuple means uniform weights + and is deliberately equivalent to the historical PPR behavior. + """ + intent: str = "uniform" + layer_weights: tuple[tuple[GraphLayer, float], ...] = () + reason_codes: tuple[str, ...] = () + + def __post_init__(self) -> None: + """Canonicalize policy output before it can affect graph ranking. + + Policies are injected extension code. Keeping their data contract finite, + typed, and duplicate-free makes failure fall back to uniform traversal + rather than letting malformed weights turn into an availability issue or + a non-deterministic first-match choice. + """ + normalized = [] + seen = set() + for entry in self.layer_weights: + if not isinstance(entry, tuple) or len(entry) != 2: + raise ValueError("graph traversal layer_weights must be (layer, weight) pairs") + raw_layer, raw_weight = entry + layer = GraphLayer(raw_layer) + if layer in seen: + raise ValueError("graph traversal layer_weights may not repeat a layer") + try: + weight = float(raw_weight) + except (TypeError, ValueError) as exc: + raise ValueError("graph traversal weights must be finite numbers") from exc + if not math.isfinite(weight): + raise ValueError("graph traversal weights must be finite numbers") + seen.add(layer) + normalized.append((layer, weight)) + reason_codes = ( + (self.reason_codes,) + if isinstance(self.reason_codes, str) + else tuple(str(code) for code in self.reason_codes) + ) + object.__setattr__(self, "intent", str(self.intent or "uniform")) + object.__setattr__(self, "layer_weights", tuple(normalized)) + object.__setattr__(self, "reason_codes", reason_codes) + + def multiplier(self, layer: GraphLayer) -> float: + """Return a safe non-zero multiplier for ``layer``. + + The bounds retain weak reachability through non-preferred layers and stop + injected policies from turning a local graph edge into an unbounded score + amplification mechanism. + """ + for candidate, value in self.layer_weights: + if candidate == layer: + try: + numeric = float(value) + if not math.isfinite(numeric): + return 1.0 + return min(4.0, max(0.25, numeric)) + except (TypeError, ValueError): + return 1.0 + return 1.0 + + def as_dict(self) -> dict[str, object]: + return { + "intent": self.intent, + "layer_weights": { + layer.value: self.multiplier(layer) + for layer in GraphLayer + }, + "reason_codes": list(self.reason_codes), + } + + +@runtime_checkable +class GraphTraversalPolicy(Protocol): + """Choose soft graph-layer weights without coupling core to an LLM backend.""" + def plan(self, query: str, *, filter: Optional[SearchFilter] = None) -> GraphTraversalPlan: ... + + +@runtime_checkable +class QueryPlanner(Protocol): + """Produce a retrieval plan without coupling core to an LLM backend.""" + def plan(self, query: str, *, filter: Optional[SearchFilter] = None, + timeout_s: Optional[float] = None) -> RetrievalPlan: ... + + @runtime_checkable class LLM(Protocol): """External or local model for synthesis and structured extraction (§8.2).""" def complete(self, messages: list[dict], **kw: Any) -> str: ... - def extract_json(self, prompt: str, schema: dict) -> Any: ... + def extract_json(self, prompt: str, schema: dict, **kw: Any) -> Any: ... @runtime_checkable diff --git a/engraphis/core/poisoning.py b/engraphis/core/poisoning.py index 81b9a0d3..aa10a0ba 100644 --- a/engraphis/core/poisoning.py +++ b/engraphis/core/poisoning.py @@ -1,10 +1,9 @@ -"""Deterministic write-time guard for untrusted memory payloads. +"""Deterministic write-time guard for memory payloads. This module intentionally does not attempt to decide whether a fact is true. It -recognises a small, explainable set of prompt-injection and exfiltration shapes in -payloads that the caller has *already* labelled untrusted. A match quarantines the -payload for inspection instead of dropping it, mutating trusted memories, or relying -on an online classifier. +recognises a small, explainable set of prompt-injection and exfiltration shapes before +they receive a trust decision. A match quarantines the payload for inspection instead +of dropping it, mutating trusted memories, or relying on an online classifier. """ from __future__ import annotations @@ -14,8 +13,10 @@ from typing import Any, Mapping, Optional -POLICY_VERSION = "deterministic-v2" +POLICY_VERSION = "deterministic-v3" QUARANTINE_STATE = "quarantined" +REVIEW_PENDING = "pending" +REVIEW_APPROVED = "approved" # Source labels below identify producers outside the local memory authority. They # are enforced by the service/sync boundaries, not trusted merely because a payload @@ -51,7 +52,7 @@ class PoisoningDecision: ( "privilege_impersonation", re.compile( - r"(?:^|\n)\s*(?:system|developer|assistant)\s*" + r"(?:^|\s|;)\s*(?:system|developer|assistant)\s*" r"(?:message|prompt|instructions?)\s*[:\-]", re.IGNORECASE, ), @@ -90,21 +91,96 @@ class PoisoningDecision: ) _SINGLE_LETTER_RUN = re.compile( - r"(? tuple[str, ...]: + """Return an exact signal-vocabulary segmentation, or no segmentation. + + The dynamic program is deliberately all-or-nothing: unknown text must retain its + original spacing instead of being altered into a new phrase by a safety helper. + """ + lower = letters.casefold() + best: list[tuple[str, ...] | None] = [None] * (len(lower) + 1) + best[0] = () + for end in range(1, len(lower) + 1): + choices: list[tuple[str, ...]] = [] + for start in range(max(0, end - 16), end): + word = lower[start:end] + if word in _SPACED_SIGNAL_WORDS and best[start] is not None: + choices.append((*best[start], word)) + if choices: + # Prefer the fewest, then longest-leading, words for deterministic output. + best[end] = min(choices, key=lambda words: (len(words), tuple(-len(w) for w in words))) + return best[-1] or () + + +def _restore_spaced_signal_words(match: re.Match[str]) -> str: + letters = "".join(match.group(0).split()) + words = _segment_signal_words(letters) + return " ".join(words) if words else match.group(0) + def _canonical_payload_text(text: str) -> str: - """Normalize common presentation tricks before deterministic signal checks.""" - normalized = unicodedata.normalize("NFKC", text or "") - normalized = "".join( - character for character in normalized - if unicodedata.category(character) not in {"Cf", "Cc"} or character in "\n\t" - ) + """Normalize presentation tricks before deterministic signal checks. + + This is defense in depth, not an authority decision: public ingress remains pending + review even if no current deterministic signal matches. + """ + # Decompose after compatibility normalization so a precomposed accented glyph + # cannot retain its mark merely because it is no longer category ``Mn``. + normalized = unicodedata.normalize("NFKD", unicodedata.normalize("NFKC", text or "")) + parts: list[str] = [] + for character in normalized: + category = unicodedata.category(character) + if category in {"Cf", "Mn"}: + continue + if category == "Cc": + # Controls must not survive into the detector text, but whitespace-like + # controls still separate words. Replacing them before removal avoids + # turning ``ignore\nprevious`` into an unmatchable single token. + if character.isspace(): + parts.append(" ") + continue + parts.append(character) return _SINGLE_LETTER_RUN.sub( - lambda match: "".join(match.group(0).split()), - normalized, + _restore_spaced_signal_words, + unicodedata.normalize("NFKC", "".join(parts)).casefold().translate(_TR39_ASCII_SKELETON), ) @@ -132,6 +208,15 @@ def provenance_is_trusted(provenance: object) -> bool: return isinstance(provenance, Mapping) and provenance.get("trusted") is True +def provenance_is_approved(provenance: object) -> bool: + """Require both explicit trust and an explicit human/local approval state.""" + return ( + provenance_is_trusted(provenance) + and isinstance(provenance, Mapping) + and provenance.get("review_state") == REVIEW_APPROVED + ) + + def metadata_is_trusted(metadata: object) -> bool: provenance = _mapping(metadata).get("provenance") return not isinstance(provenance, Mapping) or provenance_is_trusted(provenance) @@ -169,7 +254,7 @@ def prompt_eligible(provenance: object, metadata: object = None) -> bool: approved, non-quarantined record is required before anything is packed for an agent. """ return ( - provenance_is_trusted(provenance) + provenance_is_approved(provenance) and metadata_is_trusted(metadata) and inspection_eligible(provenance, metadata) ) @@ -177,21 +262,11 @@ def prompt_eligible(provenance: object, metadata: object = None) -> bool: def source_is_external(source: object) -> bool: """Recognize external producers, including namespaced adapter instances.""" - label = str(source or "").strip().casefold() + label = _canonical_payload_text(str(source or "")).strip().casefold() base = label.split(":", 1)[0].split("/", 1)[0] return base in EXTERNAL_SOURCES -def _is_explicitly_untrusted(provenance: Mapping[str, Any]) -> bool: - """Only an explicit false label opts an input into payload inspection. - - Existing direct-core callers that omit provenance are trusted local writes. This - keeps their behaviour unchanged and ensures a string such as ``"false"`` cannot - accidentally be interpreted as an authority-changing boolean. - """ - return provenance.get("trusted") is False - - def _is_sticky_quarantine(metadata: Mapping[str, Any]) -> bool: quarantine = metadata.get("quarantine") return isinstance(quarantine, Mapping) and quarantine.get("state") == QUARANTINE_STATE @@ -209,10 +284,6 @@ def assess_untrusted_payload(content: str, *, title: str = "", meta = _mapping(metadata) if _is_sticky_quarantine(meta): return PoisoningDecision(True, reasons=("inherited_quarantine",)) - provenance = _mapping(meta.get("provenance")) - if not _is_explicitly_untrusted(provenance): - return PoisoningDecision(False) - reasons = detect_payload_signals(content, title=title) return PoisoningDecision(bool(reasons), reasons=reasons) diff --git a/engraphis/core/query_planner.py b/engraphis/core/query_planner.py new file mode 100644 index 00000000..d4f106e5 --- /dev/null +++ b/engraphis/core/query_planner.py @@ -0,0 +1,137 @@ +"""Bounded query planning for opt-in planned recall. + +The deterministic planner is deliberately conservative and dependency-free. It +does not retrieve data or relax filters; it only proposes at most two additional +query formulations and optional memory-type targeting. Recall sanitizes every +plan again before execution, so an injected planner is never a policy boundary. +""" +from __future__ import annotations + +import re +from typing import Optional + +from engraphis.core.interfaces import ( + MemoryType, + PlannedQuery, + RetrievalPlan, + SearchFilter, +) + + +PLANNING_MODES = frozenset({"off", "auto"}) +MAX_PLANNED_QUERIES = 3 +MAX_PLANNED_PRIORITY = 1000 + +_QUOTED_RE = re.compile(r'"([^"\r\n]{1,160})"|\'([^\'\r\n]{1,160})\'') +_IDENTIFIER_RE = re.compile( + r"(?:\b[A-Z][A-Z0-9_]{2,}\b|\b[A-Za-z_]\w*(?:::\w+|\.\w+|\(\))+)" +) +_GRAPH_RE = re.compile( + r"\b(?:calls?|causes?|depends?|impact|path|related|relationship|why|between)\b", + re.IGNORECASE, +) +_TEMPORAL_RE = re.compile( + r"\b(?:before|after|changed|change|current|currently|latest|now|previous|" + r"previously|supersed(?:e|ed|es)|timeline|when)\b", + re.IGNORECASE, +) +_PROCEDURAL_RE = re.compile( + r"\b(?:how\s+(?:do|does|should|to)|procedure|process|steps?|workflow|playbook|recipe)\b", + re.IGNORECASE, +) +_SESSION_RE = re.compile( + r"\b(?:current|this)\s+(?:chat|conversation|session|task|thread)\b|" + r"\b(?:just|earlier)\s+(?:said|discussed|decided)\b", + re.IGNORECASE, +) +_GRAPH_STOPWORDS = frozenset({ + "a", "an", "and", "are", "between", "does", "how", "is", "of", "the", + "to", "what", "which", "who", "why", +}) + + +class DeterministicQueryPlanner: + """Offline planner with stable regex-based rules and no model dependency.""" + + identity = "engraphis.query-planner.deterministic.v1" + + def plan( + self, + query: str, + *, + filter: Optional[SearchFilter] = None, + timeout_s: Optional[float] = None, + ) -> RetrievalPlan: + del filter, timeout_s + text = " ".join(str(query or "").split()) + mtypes, type_reason = _intent_mtypes(text) + # The original query remains broad. Type intent narrows only an additional + # route, so a mistaken intent classification cannot remove relevant evidence. + planned = [PlannedQuery(text=text, priority=1, profile="balanced")] + reasons = [type_reason] if type_reason else [] + + exact_terms = [] + for match in _QUOTED_RE.finditer(text): + value = next((group for group in match.groups() if group), "").strip() + if value and value.casefold() not in {term.casefold() for term in exact_terms}: + exact_terms.append(value) + for value in _IDENTIFIER_RE.findall(text): + value = value.strip() + if value and value.casefold() not in {term.casefold() for term in exact_terms}: + exact_terms.append(value) + if exact_terms: + planned.append(PlannedQuery( + text=" ".join(exact_terms[:6]), + priority=2, + profile="lexical", + mtypes=mtypes, + )) + reasons.append("exact_term") + + if _GRAPH_RE.search(text) and len(planned) < MAX_PLANNED_QUERIES: + graph_text = _graph_query(text) + if graph_text.casefold() != text.casefold(): + planned.append(PlannedQuery( + text=graph_text, + priority=len(planned) + 1, + profile="graph", + mtypes=mtypes, + )) + reasons.append("relationship_intent") + + if mtypes and len(planned) < MAX_PLANNED_QUERIES: + suffix = { + "current_session_intent": "current session", + "procedural_intent": "procedure steps", + "temporal_intent": "timeline changes", + }[type_reason] + planned.append(PlannedQuery( + text=f"{text} {suffix}", + priority=len(planned) + 1, + profile="balanced", + mtypes=mtypes, + )) + + return RetrievalPlan( + queries=tuple(planned[:MAX_PLANNED_QUERIES]), + reason_codes=tuple(reasons), + ) + + +def _intent_mtypes(query: str) -> tuple[tuple[MemoryType, ...], str]: + if _SESSION_RE.search(query): + return (MemoryType.WORKING, MemoryType.EPISODIC), "current_session_intent" + if _PROCEDURAL_RE.search(query): + return (MemoryType.PROCEDURAL, MemoryType.SEMANTIC), "procedural_intent" + if _TEMPORAL_RE.search(query): + return (MemoryType.EPISODIC, MemoryType.SEMANTIC), "temporal_intent" + return (), "" + + +def _graph_query(query: str) -> str: + terms = [ + term + for term in re.findall(r"[A-Za-z0-9_./:-]+", query) + if term.casefold() not in _GRAPH_STOPWORDS + ] + return " ".join(terms[:16]) or query diff --git a/engraphis/core/recall.py b/engraphis/core/recall.py index f6a37b25..2f10e72d 100644 --- a/engraphis/core/recall.py +++ b/engraphis/core/recall.py @@ -12,22 +12,35 @@ """ from __future__ import annotations +import hashlib import inspect +import json +import math +import queue import re +import threading from dataclasses import dataclass, field, replace from typing import Any, Callable, Optional from engraphis.core import scoring from engraphis.core.context import DeterministicContextPacker +from engraphis.core.graph_policy import UniformGraphTraversalPolicy from engraphis.core.graphrank import personalized_pagerank from engraphis.core.interfaces import ( Candidate, ContextPacker, ContextUsage, + GraphLayer, + GraphTraversalPlan, + GraphTraversalPolicy, CandidateDepthPolicy, + MemoryType, MemoryRecord, PackedChunk, + PlannedQuery, + QueryPlanner, Reranker, + RetrievalPlan, RetrievalPolicy, SearchFilter, ) @@ -38,6 +51,12 @@ RETRIEVAL_PROFILES, profile_config, ) +from engraphis.core.query_planner import ( + DeterministicQueryPlanner, + MAX_PLANNED_PRIORITY, + MAX_PLANNED_QUERIES, + PLANNING_MODES, +) from engraphis.core.poisoning import inspection_eligible, prompt_eligible from engraphis.core.store import Store, memory_matches_filter, now_ts from engraphis.core.textutil import jaccard, tokenize @@ -66,6 +85,10 @@ class RecallResult: candidate_k_used: int = 50 candidate_depth_reason: str = "fixed requested depth" retrieval_trace: Optional[list[dict[str, Any]]] = None + context_revision: str = "" + planning_mode: str = "off" + planning_details: Optional[dict[str, Any]] = None + graph_traversal_details: Optional[list[dict[str, Any]]] = None token_counter: Optional[Callable[[str], int]] = field(default=None, repr=False) # Safety metadata is kept off the public chunk projection. Consumers which make # a trust-sensitive decision (grounded recall) can still honour a record's @@ -79,7 +102,10 @@ def __init__(self, store: Store, embedder, vector_index, reranker: Optional[Rera token_budget: int = 1500, graph_mode: str = "ppr", context_packer: Optional[ContextPacker] = None, retrieval_policy: Optional[RetrievalPolicy] = None, - candidate_depth_policy: Optional[CandidateDepthPolicy] = None) -> None: + candidate_depth_policy: Optional[CandidateDepthPolicy] = None, + graph_traversal_policy: Optional[GraphTraversalPolicy] = None, + query_planner: Optional[QueryPlanner] = None, + planner_timeout_s: float = 2.0) -> None: self.store = store self.embedder = embedder self.index = vector_index @@ -90,6 +116,10 @@ def __init__(self, store: Store, embedder, vector_index, reranker: Optional[Rera self.context_packer = context_packer or DeterministicContextPacker() self.retrieval_policy = retrieval_policy or DeterministicRetrievalPolicy() self.candidate_depth_policy = candidate_depth_policy or DeterministicRetrievalPolicy() + self.graph_traversal_policy = graph_traversal_policy or UniformGraphTraversalPolicy() + self.query_planner = query_planner or DeterministicQueryPlanner() + self.planner_timeout_s = max(0.0, float(planner_timeout_s)) + self._planner_slot = threading.BoundedSemaphore(1) # "ppr" (default) = Personalized PageRank over entities+links (multi-hop); # "1hop" = the Phase-1 entity expansion, kept for fallback and ablation. self.graph_mode = graph_mode @@ -102,6 +132,8 @@ def recall(self, query: str, flt: Optional[SearchFilter] = None, *, k: int = 8, diagnostics: bool = False, include_untrusted: bool = False, prompt_only: bool = False, + planning: str = "off", + mtype_limits: Optional[dict] = None, arm_config: Optional[ProfileConfig] = None) -> RecallResult: flt = flt or SearchFilter() requested_historical = flt.historical @@ -146,6 +178,20 @@ def recall(self, query: str, flt: Optional[SearchFilter] = None, *, k: int = 8, # ablations. Normal callers still use only named RetrievalPolicy profiles, # so benchmark labels do not expand the public routing contract. config = arm_config or profile_config(selected_profile) + planning_mode = str(planning or "off").strip().casefold() + if planning_mode not in PLANNING_MODES: + choices = ", ".join(sorted(PLANNING_MODES)) + raise ValueError(f"planning must be one of: {choices}") + caller_limits = _normalize_mtype_limits(mtype_limits) + plan, planner_fallback = self._plan_queries( + query, + flt, + selected_profile=selected_profile, + planning_mode=planning_mode, + ) + effective_limits = dict(plan.mtype_limits) + effective_limits.update(caller_limits) + planned_queries = list(plan.queries) # ── arms ───────────────────────────────────────────────────────────── # Prompt-facing consumers filter untrusted records after retrieval because @@ -165,32 +211,95 @@ def recall(self, query: str, flt: Optional[SearchFilter] = None, *, k: int = 8, max(PROMPT_ONLY_MIN_CANDIDATES, candidate_k * 16), ), ) - qvec = self.embedder.embed([query])[0] if config.vector else None + run_configs = [ + config if index == 0 and arm_config is not None else profile_config(item.profile) + for index, item in enumerate(planned_queries) + ] + embedded_texts = [ + item.text for item, run_config in zip(planned_queries, run_configs) + if run_config.vector + ] + embedded = self.embedder.embed(embedded_texts) if embedded_texts else [] + embedded_iter = iter(embedded) + query_vectors = [ + next(embedded_iter) if run_config.vector else None + for run_config in run_configs + ] while True: - if qvec is not None: - vec = dict(self.index.search(qvec, arm_candidate_k, filter=flt)) - else: - vec = {} - lex = ( - dict(self.store.fts_search(query, arm_candidate_k, filter=flt)) - if config.lexical else {} - ) - graph = ( - self._graph_arm(query, flt, now, candidate_k=arm_candidate_k) - if config.graph else {} - ) - code = ( - self._code_arm( - query, flt, arm_candidate_k, historical=requested_historical + query_runs = [] + for item, run_config, qvec in zip( + planned_queries, run_configs, query_vectors + ): + query_filter = _planned_filter(flt, item.mtypes) + if query_filter is None: + query_runs.append({ + "query": item, + "config": run_config, + "vector": {}, + "lexical": {}, + "graph": {}, + "code": {}, + }) + continue + vec = ( + dict(self.index.search(qvec, arm_candidate_k, filter=query_filter)) + if qvec is not None else {} ) - if config.code else {} - ) + lex = ( + dict(self.store.fts_search( + item.text, arm_candidate_k, filter=query_filter + )) + if run_config.lexical else {} + ) + graph_plan, graph_policy_fallback = ( + self._plan_graph_traversal(item.text, query_filter) + if run_config.graph else (None, "") + ) + graph = ( + self._graph_arm( + item.text, + query_filter, + now, + candidate_k=arm_candidate_k, + traversal_plan=graph_plan, + ) + if run_config.graph else {} + ) + code = ( + self._code_arm( + item.text, + query_filter, + arm_candidate_k, + historical=requested_historical, + ) + if run_config.code else {} + ) + query_runs.append({ + "query": item, + "config": run_config, + "vector": vec, + "lexical": lex, + "graph": graph, + "code": code, + "graph_traversal_plan": graph_plan, + "graph_traversal_policy": getattr( + self.graph_traversal_policy, + "identity", + type(self.graph_traversal_policy).__name__, + ), + "graph_traversal_fallback": graph_policy_fallback, + }) # Sorted, not raw set order: a set of ids iterates in hash order, which varies # with PYTHONHASHSEED, so equal-scored results used to come back in a different # order in every process. One batched lookup replaces per-id lookups. - candidate_ids = sorted(set(vec) | set(lex) | set(graph) | set(code)) + candidate_ids = sorted({ + memory_id + for run in query_runs + for arm in ("vector", "lexical", "graph", "code") + for memory_id in run[arm] + }) fetched = self.store.get_memories(candidate_ids) recs: dict[str, MemoryRecord] = {} for mid in candidate_ids: @@ -207,12 +316,13 @@ def recall(self, query: str, flt: Optional[SearchFilter] = None, *, k: int = 8, recs[mid] = rec can_expand = any( - enabled and len(values) >= arm_candidate_k - for enabled, values in ( - (config.vector, vec), - (config.lexical, lex), - (config.graph, graph), - (config.code, code), + enabled and len(run[arm]) >= arm_candidate_k + for run in query_runs + for arm, enabled in ( + ("vector", run["config"].vector), + ("lexical", run["config"].lexical), + ("graph", run["config"].graph), + ("code", run["config"].code), ) ) if ( @@ -235,40 +345,44 @@ def recall(self, query: str, flt: Optional[SearchFilter] = None, *, k: int = 8, retrieval_profile=selected_profile, candidate_depth_mode=requested_depth_mode, candidate_k_requested=requested_candidate_k, - candidate_k_used=candidate_k, + # This is the page depth actually used by the retrieval arms. A + # prompt-only recall may have widened it to find approved evidence. + candidate_k_used=arm_candidate_k, candidate_depth_reason=candidate_depth_reason, retrieval_trace=[] if diagnostics else None, + context_revision=_context_revision(usage, packed, context), + planning_mode=planning_mode, + planning_details=( + _planning_details( + plan, + query_runs, + recs, + effective_limits, + [], + planner_fallback, + getattr(self.query_planner, "identity", type(self.query_planner).__name__), + rerank_pool_size=0, + available_candidates=0, + ) if diagnostics else None + ), + graph_traversal_details=( + _graph_traversal_details(query_runs) if diagnostics else None + ), token_counter=getattr(self.context_packer, "count_tokens", None), ) - sem_n = scoring.normalize({i: vec[i] for i in vec if i in recs}) - lex_n = scoring.normalize({i: lex[i] for i in lex if i in recs}) - grp_n = scoring.normalize({i: graph[i] for i in graph if i in recs}) - code_n = scoring.normalize({i: code[i] for i in code if i in recs}) - rrf = scoring.reciprocal_rank_fusion([ - ranked for ranked in ( - _ranked(vec, recs), - _ranked(lex, recs), - _ranked(graph, recs), - _ranked(code, recs), - ) if ranked - ]) + arm_state, rrf = _fuse_query_runs(query_runs, recs) + primary_vec = query_runs[0]["vector"] # ── six-term weighted score (+ small RRF nudge for cross-arm agreement) ── scored: list[Candidate] = [] score_details: dict[str, dict[str, Any]] = {} for mid, rec in recs.items(): w = self.weights.get(rec.mtype, scoring.Weights()) - adjusted_semantic = sem_n.get(mid, 0.0) * config.semantic_scale - adjusted_lexical = lex_n.get(mid, 0.0) * config.lexical_scale - adjusted_graph = ( - grp_n.get(mid, 0.0) * config.graph_scale - + (config.graph_presence_bonus if mid in graph else 0.0) - ) - adjusted_code = ( - code_n.get(mid, 0.0) * config.code_scale - + (config.code_presence_bonus if mid in code else 0.0) - ) + adjusted_semantic = arm_state["adjusted"]["semantic"].get(mid, 0.0) + adjusted_lexical = arm_state["adjusted"]["lexical"].get(mid, 0.0) + adjusted_graph = arm_state["adjusted"]["graph"].get(mid, 0.0) + adjusted_code = arm_state["adjusted"]["code"].get(mid, 0.0) semantic_score = max(adjusted_semantic, adjusted_code) base = scoring.score_memory( rec, now=now, weights=w, @@ -276,12 +390,8 @@ def recall(self, query: str, flt: Optional[SearchFilter] = None, *, k: int = 8, graph=adjusted_graph, recency_tau_days=self.recency_tau_days, ) arms = [ - name for name, values in ( - ("semantic", vec), - ("lexical", lex), - ("graph", graph), - ("code", code), - ) if mid in values + name for name in ("semantic", "lexical", "graph", "code") + if mid in arm_state["raw"][name] ] fusion_score = base + 0.5 * rrf.get(mid, 0.0) arm = ( @@ -293,16 +403,16 @@ def recall(self, query: str, flt: Optional[SearchFilter] = None, *, k: int = 8, )) score_details[mid] = { "raw": { - "semantic": vec.get(mid), - "lexical": lex.get(mid), - "graph": graph.get(mid), - "code": code.get(mid), + "semantic": arm_state["raw"]["semantic"].get(mid), + "lexical": arm_state["raw"]["lexical"].get(mid), + "graph": arm_state["raw"]["graph"].get(mid), + "code": arm_state["raw"]["code"].get(mid), }, "normalized": { - "semantic": sem_n.get(mid, 0.0), - "lexical": lex_n.get(mid, 0.0), - "graph": grp_n.get(mid, 0.0), - "code": code_n.get(mid, 0.0), + "semantic": arm_state["normalized"]["semantic"].get(mid, 0.0), + "lexical": arm_state["normalized"]["lexical"].get(mid, 0.0), + "graph": arm_state["normalized"]["graph"].get(mid, 0.0), + "code": arm_state["normalized"]["code"].get(mid, 0.0), }, "profile_adjusted": { "semantic": adjusted_semantic, @@ -322,10 +432,15 @@ def recall(self, query: str, flt: Optional[SearchFilter] = None, *, k: int = 8, scored.sort(key=lambda c: (-c.score, c.id)) # ── rerank top-N, keep k ───────────────────────────────────────────── - pool = scored[: max(k * 4, k)] + # Type limits need candidates beyond the ordinary top-4k window, but sending + # the complete multi-query union to a cross-encoder creates an avoidable + # latency/cost hazard. Add the best pre-rerank candidates required to fill k + # from every eligible memory type; with four types this remains <= 8k. + pool = _type_aware_rerank_pool(scored, effective_limits, k=max(0, int(k))) + rerank_k = len(pool) if effective_limits else k if self.reranker: fused_before = {candidate.id: candidate.score for candidate in pool} - reranked = self.reranker.rerank(query, pool, k) + reranked = self.reranker.rerank(query, pool, rerank_k) rerank_raw = { candidate.id: float(candidate.score) for candidate in reranked } @@ -345,13 +460,17 @@ def recall(self, query: str, flt: Optional[SearchFilter] = None, *, k: int = 8, + 0.3 * rerank_norm.get(candidate.id, 0.0) ) reranked.sort(key=lambda candidate: (-candidate.score, candidate.id)) - final = reranked[:k] - for candidate in final: + ranked_final = reranked + for candidate in ranked_final: detail = score_details[candidate.id] detail["rerank_score"] = rerank_raw.get(candidate.id) detail["calibrated_score"] = candidate.score else: - final = pool[:k] + ranked_final = pool + + final, type_limit_drops = _apply_mtype_limits( + ranked_final, effective_limits, k=max(0, int(k)) + ) if reinforce and not requested_historical: for c in final: @@ -366,7 +485,7 @@ def recall(self, query: str, flt: Optional[SearchFilter] = None, *, k: int = 8, query, candidate.record.content, title=candidate.record.title, - semantic_cosine=vec.get(candidate.id, 0.0), + semantic_cosine=primary_vec.get(candidate.id, 0.0), ) for candidate in final } @@ -402,9 +521,29 @@ def recall(self, query: str, flt: Optional[SearchFilter] = None, *, k: int = 8, retrieval_profile=selected_profile, candidate_depth_mode=requested_depth_mode, candidate_k_requested=requested_candidate_k, - candidate_k_used=candidate_k, + # Report the final, post-widening arm depth rather than the policy's + # initial candidate depth. This is diagnostic telemetry, not a limit. + candidate_k_used=arm_candidate_k, candidate_depth_reason=candidate_depth_reason, retrieval_trace=trace, + context_revision=_context_revision(usage, packed_chunks, context), + planning_mode=planning_mode, + planning_details=( + _planning_details( + plan, + query_runs, + recs, + effective_limits, + type_limit_drops, + planner_fallback, + getattr(self.query_planner, "identity", type(self.query_planner).__name__), + rerank_pool_size=len(pool), + available_candidates=len(scored), + ) if diagnostics else None + ), + graph_traversal_details=( + _graph_traversal_details(query_runs) if diagnostics else None + ), token_counter=getattr(self.context_packer, "count_tokens", None), source_metadata={ candidate.id: _source_safety_metadata(candidate.record) @@ -413,6 +552,119 @@ def recall(self, query: str, flt: Optional[SearchFilter] = None, *, k: int = 8, }, ) + def _plan_queries( + self, + query: str, + flt: SearchFilter, + *, + selected_profile: str, + planning_mode: str, + ) -> tuple[RetrievalPlan, str]: + identity = RetrievalPlan((PlannedQuery(query, 1, selected_profile),)) + if planning_mode == "off": + return identity, "" + try: + # Query planning is not a policy boundary. SearchFilter is mutable for + # legacy compatibility, so never expose the live retrieval filter to an + # injected planner. Clone its collection fields as well to prevent an + # in-place list mutation from widening the real query. + planner_filter = replace( + flt, + scopes=list(flt.scopes) if flt.scopes is not None else None, + mtypes=list(flt.mtypes) if flt.mtypes is not None else None, + graph_layers=( + list(flt.graph_layers) if flt.graph_layers is not None else None + ), + ) + proposed = self._run_planner(query, planner_filter) + return _sanitize_plan(proposed, query, selected_profile), "" + except Exception as exc: + return identity, _planner_fallback_reason(exc) + + def _run_planner(self, query: str, planner_filter: SearchFilter) -> RetrievalPlan: + """Enforce the planner deadline even for a non-cooperative injected backend. + + Python cannot safely kill an arbitrary running function. A single daemon + worker therefore owns the planner slot; recall returns the identity route + on deadline, and further calls fail open until the timed-out worker exits. + This bounds caller latency and prevents an accumulation of stuck threads. + """ + if self.planner_timeout_s <= 0 or not self._planner_slot.acquire(blocking=False): + raise TimeoutError("planner deadline unavailable") + outcome: queue.Queue[tuple[bool, Any]] = queue.Queue(maxsize=1) + + def invoke() -> None: + try: + outcome.put((True, self.query_planner.plan( + query, + filter=planner_filter, + timeout_s=self.planner_timeout_s, + ))) + except Exception as exc: + outcome.put((False, exc)) + finally: + self._planner_slot.release() + + worker = threading.Thread( + target=invoke, + name="engraphis-query-planner", + daemon=True, + ) + worker.start() + worker.join(self.planner_timeout_s) + if worker.is_alive(): + raise TimeoutError("planner deadline exceeded") + try: + succeeded, value = outcome.get_nowait() + except queue.Empty as exc: + raise RuntimeError("planner terminated without a result") from exc + if succeeded: + return value + raise value + + def _plan_graph_traversal( + self, + query: str, + flt: SearchFilter, + ) -> tuple[GraphTraversalPlan, str]: + """Return an injected policy plan or fail closed to uniform traversal. + + Traversal policy is a soft ranking enhancement, never an availability or + authorization boundary. A broken optional policy therefore must not make + local recall unavailable or change the established uniform PPR fallback. + """ + try: + # Policies may receive filter context to explain a plan, but they are + # not an authority boundary. SearchFilter remains mutable for legacy + # compatibility, so never expose the live retrieval filter to an + # injected policy: a buggy/malicious implementation must not widen + # scope, erase temporal anchors, or loosen graph-layer constraints. + policy_filter = replace( + flt, + scopes=list(flt.scopes) if flt.scopes is not None else None, + mtypes=list(flt.mtypes) if flt.mtypes is not None else None, + graph_layers=( + list(flt.graph_layers) if flt.graph_layers is not None else None + ), + ) + proposed = self.graph_traversal_policy.plan(query, filter=policy_filter) + except Exception: + return GraphTraversalPlan(reason_codes=("policy_unavailable",)), "policy_unavailable" + if not isinstance(proposed, GraphTraversalPlan): + return GraphTraversalPlan(reason_codes=("invalid_policy_output",)), "invalid_policy_output" + try: + # Rebuild a base plan rather than invoking a subclass's method in + # the hot path. This validates finite, unique weights and prevents + # an injected subclass from changing multiplier semantics. + plan = GraphTraversalPlan( + intent=proposed.intent, + layer_weights=proposed.layer_weights, + reason_codes=proposed.reason_codes, + ) + except Exception: + return GraphTraversalPlan(reason_codes=("invalid_policy_output",)), "invalid_policy_output" + return plan, "" + # ── arms / helpers ──────────────────────────────────────────────────────── def _code_arm( self, @@ -600,12 +852,19 @@ def _graph_arm( now: float, *, candidate_k: int = 50, + traversal_plan: Optional[GraphTraversalPlan] = None, ) -> dict[str, float]: if flt.graph_layers is not None and not flt.graph_layers: return {} if self.graph_mode == "1hop": return self._graph_arm_1hop(query, flt, now, candidate_k=candidate_k) - return self._graph_arm_ppr(query, flt, now, candidate_k=candidate_k) + return self._graph_arm_ppr( + query, + flt, + now, + candidate_k=candidate_k, + traversal_plan=traversal_plan, + ) def _graph_arm_ppr( self, @@ -614,6 +873,7 @@ def _graph_arm_ppr( now: float, *, candidate_k: int = 50, + traversal_plan: Optional[GraphTraversalPlan] = None, ) -> dict[str, float]: """Personalized PageRank arm: build the scoped entity/memory graph — entity↔entity edges (bi-temporal), memory↔entity @@ -636,12 +896,15 @@ def _graph_arm_ppr( if not seeds: return {} + if not isinstance(traversal_plan, GraphTraversalPlan): + traversal_plan, _ = self._plan_graph_traversal(query, flt) ent = "ent::{}".format adj: dict[str, list[tuple[str, float]]] = {} - def connect(a: str, b: str, w: float) -> None: - adj.setdefault(a, []).append((b, w)) - adj.setdefault(b, []).append((a, w)) + def connect(a: str, b: str, w: float, layer: GraphLayer) -> None: + weighted = max(float(w or 1.0), 1e-6) * traversal_plan.multiplier(layer) + adj.setdefault(a, []).append((b, weighted)) + adj.setdefault(b, []).append((a, weighted)) # Build a bounded edge set outward from the query entities. A global # ULID-ordered cap would let old unrelated edges crowd out a new relation @@ -668,7 +931,12 @@ def connect(a: str, b: str, w: float) -> None: break frontier.update(next_frontier - expanded) for e in edges_by_id.values(): - connect(ent(e.src), ent(e.dst), max(float(e.weight or 1.0), 1e-6)) + connect( + ent(e.src), + ent(e.dst), + max(float(e.weight or 1.0), 1e-6), + e.layer or GraphLayer.SEMANTIC, + ) # Query only the entity frontier before applying the incidence cap. A # global confidence/ID prefix can otherwise omit a memory attached to a @@ -718,14 +986,23 @@ def connect(a: str, b: str, w: float) -> None: max(float(row.get("confidence") or 0.0), 1e-6), ) for (memory_id, entity_id), confidence in incidence_strength.items(): - connect(memory_id, ent(entity_id), confidence) + # Incidence is a structural memory↔entity bridge, not an inferred + # entity relation. Preferencing a causal/temporal relation must not + # downweight the only path that reaches its supporting memory. + adj.setdefault(memory_id, []).append((ent(entity_id), confidence)) + adj.setdefault(ent(entity_id), []).append((memory_id, confidence)) for link in self.store.links_among( memory_ids, layers=flt.graph_layers, flt=flt, limit=20_000, ): - connect(link["a"], link["b"], 1.0) + connect( + link["a"], + link["b"], + 1.0, + GraphLayer(str(link.get("layer") or GraphLayer.SEMANTIC.value)), + ) ranked = personalized_pagerank(adj, [ent(eid) for eid in seeds]) @@ -860,6 +1137,289 @@ def _pack(self, cands: list[Candidate]) -> str: return context +def _sanitize_plan( + proposed: RetrievalPlan, + original_query: str, + selected_profile: str, +) -> RetrievalPlan: + """Validate an untrusted planner result and restore the mandatory identity route.""" + if not isinstance(proposed, RetrievalPlan): + raise ValueError("planner must return RetrievalPlan") + # The mandatory route must be the caller's exact query, matching planning-off + # behavior. Use a whitespace-normalized key only for duplicate detection. + original = str(original_query or "") + queries = [PlannedQuery(original, 1, selected_profile)] + seen = {" ".join(original.split()).casefold()} + candidates = [] + for position, item in enumerate(proposed.queries): + if not isinstance(item, PlannedQuery): + raise ValueError("planner queries must be PlannedQuery values") + text = " ".join(str(item.text or "").split())[:2048] + if not text or text.casefold() in seen: + continue + if isinstance(item.priority, bool) or not isinstance(item.priority, int): + raise ValueError("planned query priority must be a positive integer") + priority = min(MAX_PLANNED_PRIORITY, max(2, item.priority)) + profile = str(item.profile or "balanced").strip().casefold() + if profile not in {"balanced", "lexical", "graph", "code"}: + raise ValueError("planned query profile is invalid") + mtypes = tuple(dict.fromkeys(MemoryType(value) for value in item.mtypes)) + candidates.append((priority, position, PlannedQuery(text, priority, profile, mtypes))) + seen.add(text.casefold()) + candidates.sort(key=lambda value: (value[0], value[1], value[2].text.casefold())) + for _, _, item in candidates[: MAX_PLANNED_QUERIES - 1]: + queries.append(item) + reasons = tuple( + str(reason).strip()[:80] + for reason in proposed.reason_codes[:8] + if str(reason).strip() + ) + return RetrievalPlan( + tuple(queries), + _normalize_mtype_limits(proposed.mtype_limits), + reasons, + ) + + +def _planner_fallback_reason(exc: Exception) -> str: + """Map planner failures to stable diagnostics without reflecting provider data.""" + if isinstance(exc, TimeoutError): + return "planner_timeout" + if isinstance(exc, (TypeError, ValueError)): + return "invalid_planner_output" + return "planner_unavailable" + + +def _normalize_mtype_limits(values: Optional[dict]) -> dict[MemoryType, int]: + if values is None: + return {} + if not isinstance(values, dict): + raise ValueError("mtype_limits must be an object of memory type to maximum count") + normalized = {} + for raw_key, raw_limit in values.items(): + try: + key = MemoryType(raw_key) + except (TypeError, ValueError) as exc: + choices = ", ".join(item.value for item in MemoryType) + raise ValueError(f"mtype_limits keys must be one of: {choices}") from exc + if isinstance(raw_limit, bool) or not isinstance(raw_limit, int): + raise ValueError("mtype_limits values must be non-negative integers") + limit = raw_limit + if limit < 0: + raise ValueError("mtype_limits values must be non-negative integers") + normalized[key] = limit + return normalized + + +def _planned_filter( + flt: SearchFilter, + mtypes: tuple[MemoryType, ...], +) -> Optional[SearchFilter]: + if not mtypes: + return flt + allowed = set(mtypes) + if flt.mtypes is not None: + allowed &= {MemoryType(value) for value in flt.mtypes} + if not allowed: + return None + ordered = [item for item in MemoryType if item in allowed] + return replace(flt, mtypes=ordered) + + +def _fuse_query_runs( + query_runs: list[dict[str, Any]], + recs: dict[str, MemoryRecord], +) -> tuple[dict[str, dict[str, dict[str, float]]], dict[str, float]]: + """Fuse query/arm rankings with priority-weighted RRF. + + Each arm is normalized within its own planned query before profile scaling. + The best contribution per arm feeds the established six-term scorer; agreement + across queries and arms is represented separately by weighted RRF. + """ + names = { + "vector": "semantic", + "lexical": "lexical", + "graph": "graph", + "code": "code", + } + state = { + category: {name: {} for name in names.values()} + for category in ("raw", "normalized", "adjusted") + } + rrf: dict[str, float] = {} + for run in query_runs: + item = run["query"] + config = run["config"] + priority_weight = 1.0 / max(1, int(item.priority)) + for source_name, output_name in names.items(): + raw = {mid: score for mid, score in run[source_name].items() if mid in recs} + normalized = scoring.normalize(raw) + scale = getattr(config, f"{output_name}_scale") + bonus = getattr(config, f"{output_name}_presence_bonus", 0.0) + for mid, value in raw.items(): + state["raw"][output_name][mid] = max( + state["raw"][output_name].get(mid, float("-inf")), + float(value), + ) + state["normalized"][output_name][mid] = max( + state["normalized"][output_name].get(mid, 0.0), + normalized.get(mid, 0.0), + ) + adjusted = (normalized.get(mid, 0.0) * scale + bonus) * priority_weight + state["adjusted"][output_name][mid] = max( + state["adjusted"][output_name].get(mid, 0.0), + adjusted, + ) + for rank, mid in enumerate(_ranked(raw, recs)): + rrf[mid] = rrf.get(mid, 0.0) + priority_weight / (60 + rank + 1) + return state, rrf + + +def _apply_mtype_limits( + candidates: list[Candidate], + limits: dict[MemoryType, int], + *, + k: int, +) -> tuple[list[Candidate], list[dict[str, Any]]]: + selected = [] + counts: dict[MemoryType, int] = {} + drops = [] + for candidate in candidates: + if len(selected) >= k: + break + if candidate.record is None: + continue + mtype = candidate.record.mtype + limit = limits.get(mtype) + if limit is not None and counts.get(mtype, 0) >= limit: + drops.append({"id": candidate.id, "mtype": mtype.value, "limit": limit}) + continue + selected.append(candidate) + counts[mtype] = counts.get(mtype, 0) + 1 + return selected, drops + + +def _type_aware_rerank_pool( + candidates: list[Candidate], + limits: dict[MemoryType, int], + *, + k: int, +) -> list[Candidate]: + """Return a bounded pool that can still fill every eligible memory-type slot.""" + if k <= 0: + return [] + ordinary = list(candidates[: max(k * 4, k)]) + if not limits: + return ordinary + selected_ids = {candidate.id for candidate in ordinary} + per_type: dict[MemoryType, int] = {} + needed = { + mtype: min(k, limits.get(mtype, k)) + for mtype in MemoryType + } + for candidate in ordinary: + if candidate.record is not None: + mtype = candidate.record.mtype + per_type[mtype] = per_type.get(mtype, 0) + 1 + for candidate in candidates[len(ordinary):]: + if candidate.record is None or candidate.id in selected_ids: + continue + mtype = candidate.record.mtype + if per_type.get(mtype, 0) >= needed[mtype]: + continue + ordinary.append(candidate) + selected_ids.add(candidate.id) + per_type[mtype] = per_type.get(mtype, 0) + 1 + if all(per_type.get(value, 0) >= count for value, count in needed.items()): + break + return ordinary + + +def _context_revision( + usage: ContextUsage, + packed: list[PackedChunk], + context: str, +) -> str: + payload = { + "token_counter": usage.token_counter, + "packed": [[chunk.id, chunk.excerpt] for chunk in packed], + # Headers (including titles) are part of the emitted prompt but not part + # of PackedChunk.excerpt. Hash the exact prompt text as well so any host- + # visible change necessarily produces a new revision. + "context": context, + } + canonical = json.dumps(payload, ensure_ascii=False, separators=(",", ":")) + return hashlib.sha256(canonical.encode("utf-8")).hexdigest() + + +def _planning_details( + plan: RetrievalPlan, + query_runs: list[dict[str, Any]], + recs: dict[str, MemoryRecord], + limits: dict[MemoryType, int], + drops: list[dict[str, Any]], + fallback: str, + planner_identity: str, + *, + rerank_pool_size: int, + available_candidates: int, +) -> dict[str, Any]: + rankings = [] + for run in query_runs: + item = run["query"] + rankings.append({ + "text": item.text, + "priority": item.priority, + "profile": item.profile, + "mtypes": [value.value for value in item.mtypes], + "rankings": { + name: _ranked(run[source], recs) + for source, name in ( + ("vector", "semantic"), + ("lexical", "lexical"), + ("graph", "graph"), + ("code", "code"), + ) + }, + }) + return { + "planner": str(planner_identity), + "reason_codes": list(plan.reason_codes), + "queries": rankings, + "mtype_limits": {key.value: value for key, value in limits.items()}, + "type_limit_drops": drops, + "fallback_reason": fallback or None, + "rerank_pool": { + "strategy": "type_aware_bounded" if limits else "top_4k", + "size": rerank_pool_size, + "available_candidates": available_candidates, + }, + } + + +def _graph_traversal_details(query_runs: list[dict[str, Any]]) -> list[dict[str, Any]]: + """Expose bounded graph-policy decisions only in diagnostic recall results.""" + details = [] + for run in query_runs: + plan = run.get("graph_traversal_plan") + if not isinstance(plan, GraphTraversalPlan): + continue + candidates = sorted( + run["graph"].items(), key=lambda item: (-item[1], item[0]) + )[:50] + details.append({ + "query": run["query"].text, + "policy": str(run.get("graph_traversal_policy") or "unknown"), + "plan": plan.as_dict(), + "fallback_reason": run.get("graph_traversal_fallback") or None, + "candidate_scores": [ + {"id": memory_id, "score": round(float(score), 8)} + for memory_id, score in candidates + ], + }) + return details + + def _source_safety_metadata(record: MemoryRecord) -> dict: """Project only trust flags needed by grounded recall, never caller metadata.""" metadata = record.metadata if isinstance(record.metadata, dict) else {} @@ -894,10 +1454,12 @@ def _absolute_retrieval_support( outside the vector arm's top-k. Unlike fused rank, neither component is min-max normalised against the other candidates in this response. """ - semantic = max(0.0, min(1.0, float(semantic_cosine))) - # FTS indexes title and content together, so its absolute evidence floor - # must use the same text rather than rejecting a legitimate title-only hit. - lexical = jaccard(tokenize(query), tokenize("\n".join((str(title or ""), content)))) + raw_semantic = float(semantic_cosine) + semantic = max(0.0, min(1.0, raw_semantic)) if math.isfinite(raw_semantic) else 0.0 + # Titles improve candidate discovery, but are metadata rather than answer-bearing + # evidence. Keeping them out of the absolute gate aligns adaptive routing with + # grounded recall and prevents a keyword-stuffed title from qualifying garbage. + lexical = jaccard(tokenize(query), tokenize(content or "")) return max(semantic, lexical) diff --git a/engraphis/core/resolve.py b/engraphis/core/resolve.py index 25d1d756..a6b50c49 100644 --- a/engraphis/core/resolve.py +++ b/engraphis/core/resolve.py @@ -18,6 +18,7 @@ from dataclasses import dataclass from enum import Enum +import unicodedata from typing import Optional from engraphis.core.interfaces import MemoryRecord @@ -36,6 +37,16 @@ STRONG_SUBJECT_TOKEN_JACCARD = 0.55 STRONG_JOINT_EMBED_SIM = 0.45 + +def _normalise_claim_text(value: str) -> str: + """Compare keyed claims independent of harmless spacing and punctuation.""" + return " ".join( + "".join( + character for character in str(value or "") + if not unicodedata.category(character).startswith("P") + ).split() + ).casefold() + class ResolutionOp(str, Enum): ADD = "add" # genuinely new -> insert NOOP = "noop" # already known -> reinforce the existing memory, don't insert @@ -103,8 +114,8 @@ def resolve(candidate_text: str, neighbors: list[tuple[float, MemoryRecord]], *, # claim equality is about the stored content. Comparing title+content to # content would turn an identical titled write into a false supersession. duplicate_text = candidate_content if candidate_content is not None else candidate_text - candidate_normalized = " ".join(duplicate_text.split()).casefold() - record_normalized = " ".join(rec.content.split()).casefold() + candidate_normalized = _normalise_claim_text(duplicate_text) + record_normalized = _normalise_claim_text(rec.content) if candidate_normalized == record_normalized: return Resolution( ResolutionOp.NOOP, diff --git a/engraphis/core/scoring.py b/engraphis/core/scoring.py index 7230914d..cc02e155 100644 --- a/engraphis/core/scoring.py +++ b/engraphis/core/scoring.py @@ -29,13 +29,6 @@ # memory into a near-instantly forgotten one. New v2 writes are validated positive. DEFAULT_STABILITY_DAYS = 1.0 -# Proactive recall is an agenda, not an answer-ranking path. A memory the caller -# deliberately marked important remains eligible for that agenda even after its raw -# Ebbinghaus score has decayed. This floor affects only the queryless ranking; it -# never mutates stability or changes normal query recall. -PROACTIVE_IMPORTANCE_RETENTION_FLOOR = 0.80 - - @dataclass(frozen=True) class Weights: r: float = 1.0 # retention (Ebbinghaus) @@ -64,8 +57,10 @@ def retention(stability: float, last_access: Optional[float], now: float) -> flo """Ebbinghaus R(t) = exp(-Δt_days / S). ``stability=0`` is a v1-import compatibility sentinel for an unspecified - value, so it deliberately means the v2 default of one day. It is *not* a - request to hard-forget the record; forgetting only lowers priority. + value, so it deliberately means the v2 default of one day. Negative and + non-finite legacy values are treated the same way rather than producing an + inverted or non-finite score. None of these values requests hard deletion; + forgetting only lowers priority. """ try: supplied = float(stability) @@ -134,18 +129,19 @@ def score_proactive(rec: MemoryRecord, *, now: float, weights: Optional[Weights] importance_retention_floor: Optional[float] = None) -> float: """Rank a queryless proactive agenda without turning decay into hard deletion. - The raw retention curve still governs ordinary memories. Explicitly important - records receive a bounded eligibility floor, so a useful week-old policy is not - displaced solely by a newly written zero-importance scratch note. + Importance is valuable while the record is retained, but it must not create an + immortal second retention term. ``importance_retention_floor`` remains accepted + for call compatibility and deliberately no longer alters scoring. """ w = weights or weights_for(rec.mtype) importance = min(max(float(rec.importance or 0.0), 0.0), 1.0) - floor = PROACTIVE_IMPORTANCE_RETENTION_FLOOR - if importance_retention_floor is not None: - floor = min(max(float(importance_retention_floor), 0.0), 1.0) - r = max( - retention(rec.stability, rec.last_access, now), - importance * floor, - ) + del importance_retention_floor + r = retention(rec.stability, rec.last_access, now) rec_ref = rec.valid_from if rec.valid_from is not None else rec.ingested_at - return w.i * importance + w.c * recency(rec_ref, now) + w.r * r + importance_signal = importance * r + return ( + w.i * importance_signal + + w.c * recency(rec_ref, now) + + w.r * r + - w.x * staleness_penalty(rec.valid_to, now) + ) diff --git a/engraphis/core/store.py b/engraphis/core/store.py index d00bd8c3..37fb7c75 100644 --- a/engraphis/core/store.py +++ b/engraphis/core/store.py @@ -80,6 +80,21 @@ def _loads(raw: Any, default: Any) -> Any: return default +def _row_is_prompt_eligible(provenance: Any, metadata: Any) -> bool: + """Use the one trust predicate before exposing a derived bridge. + + Store normally stays independent of policy, but code-memory links are a derived + index that otherwise outlives a source's review state. Keep this tiny adapter + here so every store-level bridge read and prune operation applies exactly the + same predicate as prompt packing and write-time derivation. + """ + from engraphis.core.poisoning import prompt_eligible + + prov = provenance if isinstance(provenance, dict) else _loads(provenance, {}) + meta = metadata if isinstance(metadata, dict) else _loads(metadata, {}) + return prompt_eligible(prov, meta) + + def _provenance_memory_ids(provenance: Any) -> list[str]: if not isinstance(provenance, dict): return [] @@ -691,10 +706,29 @@ class Store: def __init__(self, path: str = ":memory:", *, allowed_workspaces: Optional[set] = None, - connect: Optional[Callable[[str], Any]] = None) -> None: + connect: Optional[Callable[[str], Any]] = None, + read_only: bool = False) -> None: + """Open a store. + + ``read_only`` is deliberately stronger than merely promising not to call a + writer: it opens a checkpointed SQLite file with ``mode=ro&immutable=1`` and + skips schema setup, migrations, backups, and the persistent WAL-mode pragma. + It is for inspection tools (notably security dry-runs) whose safety contract + includes leaving a database and its sidecar files untouched. A non-empty WAL + is rejected rather than silently scanning an incomplete immutable snapshot. + """ self.path = path self._connect = connect - if path != ":memory:": + self.read_only = bool(read_only) + if self.read_only and path == ":memory:": + raise ValueError("read-only Store requires an existing database file") + if self.read_only and self._connect is None: + wal_path = Path(f"{path}-wal") + if wal_path.is_file() and wal_path.stat().st_size: + raise RuntimeError( + "read-only Store requires a checkpointed database; active WAL found" + ) + if path != ":memory:" and not self.read_only: Path(path).parent.mkdir(parents=True, exist_ok=True) raw_conn = self._open_connection(path) # Serialize the shared connection so concurrent threadpool handlers can't interleave @@ -702,17 +736,30 @@ def __init__(self, path: str = ":memory:", *, # goes through self.conn, so wrapping here covers every writer. self.conn = _SerializedConnection(raw_conn) self.conn.execute("PRAGMA foreign_keys=ON") - self.conn.execute("PRAGMA synchronous=NORMAL") self.has_fts5 = False self._receipt_lock = threading.Lock() self.allowed_workspaces: Optional[frozenset] = ( frozenset(allowed_workspaces) if allowed_workspaces else None ) try: - self.init_schema() - # journal_mode is persistent state, so set it only after a required backup - # and the transactional migration have completed successfully. - self.conn.execute("PRAGMA journal_mode=WAL") + if self.read_only: + # ``query_only`` also protects injected connectors whose implementation + # cannot express SQLite's URI ``mode=ro`` option. Do not probe FTS5 by + # creating a temporary table here: a dry-run must not write anything. + self.conn.execute("PRAGMA query_only=ON") + row = self.conn.execute( + "SELECT sql FROM sqlite_master WHERE type='table' AND name='mem_fts'" + ).fetchone() + self.has_fts5 = bool( + row and "virtual table" in str(row["sql"] or "").casefold() + and "fts5" in str(row["sql"] or "").casefold() + ) + else: + self.conn.execute("PRAGMA synchronous=NORMAL") + self.init_schema() + # journal_mode is persistent state, so set it only after a required backup + # and the transactional migration have completed successfully. + self.conn.execute("PRAGMA journal_mode=WAL") except BaseException: try: if self.conn.in_transaction: @@ -727,7 +774,11 @@ def _open_connection(self, path: str): # Injected factories own opening, keying, row_factory, and exception # translation (notably the SQLCipher backend). return self._connect(path) - conn = sqlite3.connect(path, timeout=30, check_same_thread=False) + if self.read_only: + uri = Path(path).resolve().as_uri() + "?mode=ro&immutable=1" + conn = sqlite3.connect(uri, uri=True, timeout=30, check_same_thread=False) + else: + conn = sqlite3.connect(path, timeout=30, check_same_thread=False) conn.row_factory = sqlite3.Row return conn @@ -3738,7 +3789,7 @@ def clear_code_memory_links_for_memories(self, repo_id: str, memory_ids: list[st self.conn.commit() def prune_code_memory_links(self, repo_id: str, *, commit: bool = True) -> None: - """Remove bridges whose repo-associated memory is no longer live.""" + """Retire bridges whose source is not live and explicitly approved.""" t = now_ts() self.conn.execute( "UPDATE code_memory_links SET valid_to=?, valid_to_recorded_at=? " @@ -3750,6 +3801,23 @@ def prune_code_memory_links(self, repo_id: str, *, commit: bool = True) -> None: ")", (t, t, repo_id, repo_id, t, t), ) + unapproved = self.conn.execute( + "SELECT l.id, m.provenance, m.metadata FROM code_memory_links l " + "JOIN memories m ON m.id=l.memory_id WHERE l.repo_id=? " + "AND l.valid_to IS NULL AND l.expired_at IS NULL", + (repo_id,), + ).fetchall() + retire_ids = [ + row["id"] for row in unapproved + if not _row_is_prompt_eligible(row["provenance"], row["metadata"]) + ] + if retire_ids: + marks = ",".join("?" for _ in retire_ids) + self.conn.execute( + f"UPDATE code_memory_links SET valid_to=?, valid_to_recorded_at=? " + f"WHERE id IN ({marks}) AND valid_to IS NULL AND expired_at IS NULL", + (t, t, *retire_ids), + ) if commit: self.conn.commit() @@ -3759,7 +3827,7 @@ def list_code_memory_links(self, repo_id: str, *, limit: Optional[int] = None) -> list[dict]: sql = ( "SELECT l.*, s.name, s.fqname, s.file, s.kind AS symbol_kind, " - "m.title, m.mtype, m.valid_to AS memory_valid_to, " + "m.title, m.mtype, m.provenance, m.metadata, m.valid_to AS memory_valid_to, " "m.expired_at AS memory_expired_at " "FROM code_memory_links l " "JOIN symbols s ON s.id=l.symbol_id " @@ -3782,14 +3850,19 @@ def list_code_memory_links(self, repo_id: str, *, sql += " LIMIT ?" params.append(max(0, int(limit))) # never -1 == SQLite "unlimited" rows = self.conn.execute(sql, params).fetchall() - return [dict(row) for row in rows] + return [ + {key: value for key, value in dict(row).items() + if key not in {"metadata", "provenance"}} + for row in rows + if _row_is_prompt_eligible(row["provenance"], row["metadata"]) + ] def memories_for_symbol(self, repo_id: str, symbol_id: str, *, flt: Optional[SearchFilter] = None, limit: int = 20) -> list[dict]: sql = ( "SELECT m.id, m.title, m.content, m.mtype, m.scope, m.importance, " - "m.provenance, l.relation, l.confidence " + "m.provenance, m.metadata, l.relation, l.confidence " "FROM code_memory_links l JOIN memories m ON m.id=l.memory_id " "WHERE l.repo_id=? AND l.symbol_id=?" ) @@ -3809,7 +3882,10 @@ def memories_for_symbol(self, repo_id: str, symbol_id: str, *, out = [] for row in rows: item = dict(row) + if not _row_is_prompt_eligible(item.get("provenance"), item.get("metadata")): + continue item["provenance"] = _loads(item.get("provenance"), {}) + item.pop("metadata", None) out.append(item) return out @@ -3827,7 +3903,7 @@ def memories_for_symbols(self, repo_id: str, symbol_ids: list[str], *, sql = ( "WITH ranked AS (" "SELECT l.symbol_id, m.id, m.title, m.content, m.mtype, m.scope, " - "m.importance, m.provenance, l.relation, l.confidence, " + "m.importance, m.provenance, m.metadata, l.relation, l.confidence, " "ROW_NUMBER() OVER (PARTITION BY l.symbol_id " "ORDER BY l.confidence DESC, m.importance DESC, " "m.ingested_at DESC, l.id, m.id) AS row_rank " @@ -3844,20 +3920,26 @@ def memories_for_symbols(self, repo_id: str, symbol_ids: list[str], *, params.extend(visibility_params) sql += ( ") SELECT symbol_id, id, title, content, mtype, scope, importance, " - "provenance, relation, confidence FROM ranked WHERE row_rank<=? " + "provenance, metadata, relation, confidence FROM ranked WHERE row_rank<=? " "ORDER BY symbol_id, row_rank" ) params.append(per_symbol_limit) grouped: dict[str, list[dict]] = {} for row in self.conn.execute(sql, params).fetchall(): item = dict(row) + if not _row_is_prompt_eligible(item.get("provenance"), item.get("metadata")): + continue symbol_id = str(item.pop("symbol_id")) item["provenance"] = _loads(item.get("provenance"), {}) + item.pop("metadata", None) grouped.setdefault(symbol_id, []).append(item) return grouped def symbols_for_memory(self, repo_id: str, memory_id: str, *, flt: Optional[SearchFilter] = None) -> list[dict]: + memory = self.get_memory(memory_id) + if memory is None or not _row_is_prompt_eligible(memory.provenance, memory.metadata): + return [] link_visibility, link_params = _temporal_visibility_sql("l", flt) symbol_visibility, symbol_params = _temporal_visibility_sql("s", flt) rows = self.conn.execute( @@ -3875,7 +3957,7 @@ def memories_mentioning(self, repo_id: str, text: str, *, limit: int = 10) -> list[dict]: escaped = str(text).replace("\\", "\\\\").replace("%", "\\%").replace("_", "\\_") sql = ( - "SELECT m.id, m.title, m.mtype FROM memories AS m " + "SELECT m.id, m.title, m.mtype, m.provenance, m.metadata FROM memories AS m " "WHERE m.repo_id=? AND (m.title LIKE ? ESCAPE '\\' " "OR m.content LIKE ? ESCAPE '\\')" ) @@ -3887,7 +3969,12 @@ def memories_mentioning(self, repo_id: str, text: str, *, params.extend(visibility_params) sql += " ORDER BY m.ingested_at DESC LIMIT ?" params.append(max(0, int(limit))) - return [dict(row) for row in self.conn.execute(sql, params).fetchall()] + return [ + {key: value for key, value in dict(row).items() + if key not in {"provenance", "metadata"}} + for row in self.conn.execute(sql, params).fetchall() + if _row_is_prompt_eligible(row["provenance"], row["metadata"]) + ] # ── events & audit ────────────────────────────────────────────────────── def append_event(self, *, kind: str, content: str, workspace_id: str = "", diff --git a/engraphis/core/sync.py b/engraphis/core/sync.py index 86c98aef..fc9972d3 100644 --- a/engraphis/core/sync.py +++ b/engraphis/core/sync.py @@ -50,10 +50,12 @@ from engraphis.core.graph_layers import merge_graph_layers, normalize_graph_layer from engraphis.core.interfaces import MemoryRecord, MemoryType, Scope, SearchFilter from engraphis.core.poisoning import ( + PoisoningDecision, apply_quarantine_metadata, assess_untrusted_payload, metadata_is_quarantined, - provenance_is_trusted, + prompt_eligible, + provenance_is_approved, ) from engraphis.core.store import Store, now_ts @@ -789,7 +791,7 @@ def _apply_one(self, d: dict, rec, report: dict, accepted: dict, known: dict, # into its provenance, graph state, or temporal validity. This runs after # all scope checks above so malformed remote rows are still rejected rather # than being disguised as harmless trust conflicts. - if existing is not None and provenance_is_trusted(existing.provenance): + if existing is not None and provenance_is_approved(existing.provenance): if not dry_run and rec.content != existing.content: self.store.audit( "sync:%s" % _clamp_str(src_device or "peer", 128), @@ -820,6 +822,23 @@ def _apply_one(self, d: dict, rec, report: dict, accepted: dict, known: dict, rec.provenance = dict(existing.provenance or {}) else: self._rehome_external_record(rec, src_device=src_device) + # Quarantine is sticky across peer last-writer-wins updates. A benign-looking + # same-id payload must not erase a local governance decision; only the local + # interactive approval path may create a separate approved successor. + if existing is not None and ( + metadata_is_quarantined(existing.metadata) + or bool((existing.provenance or {}).get("quarantined"))): + rec.metadata = apply_quarantine_metadata( + rec.metadata, PoisoningDecision(True, reasons=("inherited_quarantine",)) + ) + rec.provenance = dict(rec.metadata["provenance"]) + at = existing.valid_to if existing.valid_to is not None else now_ts() + # Preserve the locally governed interval rather than letting a peer's + # LWW timestamps reactivate or future-date a quarantined record. + rec.valid_from = existing.valid_from + rec.valid_to = at + rec.valid_to_recorded_at = now_ts() + rec.embedding = None if existing is None: if not dry_run: self._write(rec, commit=False) @@ -889,7 +908,8 @@ def _apply_links(self, link_dicts: list, report: dict, accepted: dict, # memory, where it could influence graph recall despite the peer payload # itself being untrusted. Links wholly inside the untrusted replica stay # inspectable, but only a local trusted write may connect trusted nodes. - if provenance_is_trusted(ma.provenance) or provenance_is_trusted(mb.provenance): + if (prompt_eligible(ma.provenance, ma.metadata) + or prompt_eligible(mb.provenance, mb.metadata)): continue pending += 1 if pending >= APPLY_BATCH: @@ -1015,6 +1035,7 @@ def _rehome_external_record(rec: MemoryRecord, *, src_device: object) -> None: provenance = { "source": "sync", "trusted": False, + "review_state": "pending", "trust_origin": "sync_untrusted", } if device: diff --git a/engraphis/dashboard_app.py b/engraphis/dashboard_app.py index d2886877..5e0fc6d6 100644 --- a/engraphis/dashboard_app.py +++ b/engraphis/dashboard_app.py @@ -7,10 +7,12 @@ from __future__ import annotations import importlib.util +import hmac from pathlib import Path from urllib.parse import urlsplit import os as _os +import secrets from fastapi import FastAPI, Request from fastapi.middleware.cors import CORSMiddleware @@ -68,6 +70,16 @@ class _BrowserSessionReq(BaseModel): token: str = Field(min_length=1, max_length=4096) +class _DashboardApprovalReq(BaseModel): + """Human-review request accepted only by the browser dashboard ceremony.""" + + memory_id: str = Field(min_length=1, max_length=200) + reason: str = Field(min_length=1, max_length=500) + + +_REVIEW_CSRF_HEADER = "X-Engraphis-Review-CSRF" + + def _embedder_status(embedder, configured_model: str) -> str: """Concise startup status without misdiagnosing an explicit offline selection.""" from engraphis.backends.embedder_deterministic import DeterministicEmbedder @@ -205,6 +217,10 @@ async def _license_error(request: Request, exc: licensing.LicenseError): embed_dim=settings.embed_dim or 384, allowed_workspaces=settings.allowed_workspaces) app.state.service = svc + # The review token is intentionally process-local and is never a general API + # credential. It is minted alongside a short-lived browser session and exists only + # to authorize the narrowly scoped human-approval dashboard action below. + app.state.review_csrf_tokens = {} try: import sys as _sys _ed = svc.engine.embedder @@ -246,11 +262,19 @@ def open_browser_session(req: _BrowserSessionReq, request: Request): ) if not token_ok(req.token, settings.api_token): return JSONResponse({"error": "unauthorized"}, status_code=401) - response = JSONResponse({"authenticated": True}) + session_value = browser_session(settings.api_token) + review_csrf_token = secrets.token_urlsafe(32) + # A dashboard restart deliberately invalidates this token. Keep only the latest + # token for each session value; unlike an API bearer, it has no authority by + # itself and is not persisted to disk or browser storage. + app.state.review_csrf_tokens[session_value] = review_csrf_token + response = JSONResponse( + {"authenticated": True, "review_csrf_token": review_csrf_token} + ) response.headers["Cache-Control"] = "no-store" response.set_cookie( BROWSER_SESSION_COOKIE, - browser_session(settings.api_token), + session_value, max_age=BROWSER_SESSION_SECONDS, httponly=True, secure=wants_https(request), @@ -259,6 +283,70 @@ def open_browser_session(req: _BrowserSessionReq, request: Request): ) return response + @app.post("/dashboard/review/approve", include_in_schema=False) + def dashboard_review_approve(req: _DashboardApprovalReq, request: Request): + """Approve one record from the authenticated browser review surface. + + This is intentionally *not* a v2 API or MCP operation. A bearer token cannot + invoke it: the caller must hold the HttpOnly browser session and echo the + per-session CSRF value returned only by the same-origin login exchange. The + private hosted service owns owner/admin approval for hosted deployments. + """ + + if not settings.api_token: + return JSONResponse( + {"error": "dashboard approval requires ENGRAPHIS_API_TOKEN"}, + status_code=409, + ) + session_value = request.cookies.get(BROWSER_SESSION_COOKIE) + if not browser_session_ok(session_value, settings.api_token): + return JSONResponse({"error": "browser session required"}, status_code=401) + if request.headers.get("X-Engraphis-Browser-Session") != "1": + return JSONResponse({"error": "browser session header required"}, status_code=403) + expected = app.state.review_csrf_tokens.get(session_value) + supplied = request.headers.get(_REVIEW_CSRF_HEADER, "") + if not expected or not hmac.compare_digest(supplied, expected): + return JSONResponse({"error": "review CSRF confirmation required"}, status_code=403) + reason = req.reason.strip() + if not reason: + return JSONResponse({"error": "review reason required"}, status_code=422) + try: + result = svc.engine.approve_for_prompt( + req.memory_id, + reviewer="dashboard_browser_session", + reason=reason, + ) + except KeyError: + return JSONResponse({"error": "memory not found"}, status_code=404) + except ValueError: + # Do not expose a governed record's content or arbitrary engine exception. + return JSONResponse({"error": "approval was rejected"}, status_code=409) + response = JSONResponse({"approved": True, **result}) + response.headers["Cache-Control"] = "no-store" + return response + + @app.get("/dashboard/review/csrf", include_in_schema=False) + def dashboard_review_csrf(request: Request): + """Return the in-memory CSRF value for an already-authenticated dashboard.""" + + if not settings.api_token: + return JSONResponse( + {"error": "dashboard approval requires ENGRAPHIS_API_TOKEN"}, + status_code=409, + ) + session_value = request.cookies.get(BROWSER_SESSION_COOKIE) + if not browser_session_ok(session_value, settings.api_token): + return JSONResponse({"error": "browser session required"}, status_code=401) + if request.headers.get("X-Engraphis-Browser-Session") != "1": + return JSONResponse({"error": "browser session header required"}, status_code=403) + token = app.state.review_csrf_tokens.get(session_value) + if not token: + token = secrets.token_urlsafe(32) + app.state.review_csrf_tokens[session_value] = token + response = JSONResponse({"review_csrf_token": token}) + response.headers["Cache-Control"] = "no-store" + return response + from engraphis.netutil import is_local_request @app.middleware("http") diff --git a/engraphis/dashboard_assets/index.html b/engraphis/dashboard_assets/index.html index 0d19f388..dd1a2099 100644 --- a/engraphis/dashboard_assets/index.html +++ b/engraphis/dashboard_assets/index.html @@ -51,7 +51,7 @@ Librarymemories and imports Saved - +
diff --git a/engraphis/core/engine.py b/engraphis/core/engine.py index b74d9cea..404ae79b 100644 --- a/engraphis/core/engine.py +++ b/engraphis/core/engine.py @@ -3,7 +3,7 @@ Wires together store + embedder + vector index + reranker + recall engine, and exposes everything an agent does against memory: write (``remember``, with deterministic conflict resolution), read (``recall``, ``why``, ``timeline``, ``recall_proactive``), governance -(``forget``, ``pin``, ``correct``), session lifecycle (with cross-session handoff), and the +(``retire``, ``secure_erase``, ``pin``, ``correct``), session lifecycle (with cross-session handoff), and the A-MEM-style linking/event primitives (``link``, ``record_event``). Construct with ``MemoryEngine.create(...)`` for sensible, offline-capable defaults, or inject your own backends for production. @@ -56,6 +56,7 @@ RETRIEVAL_PROFILES, ) from engraphis.core.resolve import RELATED_SIM_FLOOR, Resolution, ResolutionOp, resolve +from engraphis.core.secrets import reject_secrets from engraphis.core.store import Store, memory_matches_filter, now_ts from engraphis.core.textutil import estimate_tokens, jaccard, tokenize @@ -469,6 +470,11 @@ def remember_with_resolution(self, content: str, *, workspace_id: str, * ``"quarantined"`` — an explicitly untrusted payload matched the deterministic poisoning policy; retained only for governed historical inspection. """ + # Reject credentials before embedding, conflict resolution, graph extraction, or + # any SQLite mirror sees them. Store.add_memory repeats this for direct callers. + reject_secrets((("title", title), ("content", content), ("keywords", keywords), + ("metadata", metadata), ("subject_key", subject_key), + ("claim_kind", claim_kind))) if valid_from is not None: if isinstance(valid_from, bool): raise ValueError("valid_from must be a finite timestamp") @@ -1083,6 +1089,9 @@ def ingest(self, text: str, *, workspace_id: str, repo_id: Optional[str] = None, like any ``remember``); without one this is exactly ``remember`` — the offline default never changes behaviour. Extraction failures degrade to passthrough: ingest never loses the write.""" + # Raw input may be sent to a configured extractor, so block credentials before + # extraction rather than relying only on the final derived-memory write. + reject_secrets((("ingest content", text), ("metadata", metadata))) facts = None extracted = False # Quarantine precedes optional extraction. An explicitly untrusted payload that @@ -1531,12 +1540,13 @@ def _relatedness(self, query: str, flt: SearchFilter, *, deliberately excludes (it's the live-recall path), so this recomputes similarity directly from ``Store.iter_vectors(..., include_invalid=True)`` instead. """ - qvec = self.embedder.embed([query])[0] - qn = qvec / (float(np.linalg.norm(qvec)) or 1.0) sem: dict[str, float] = {} - for mid, vec in self.store.iter_vectors( - flt, include_invalid=include_invalid, dim=int(qn.shape[0])): - sem[mid] = float(np.dot(qn, vec)) + if bool(getattr(self.embedder, "supports_semantic_search", False)): + qvec = self.embedder.embed([query])[0] + qn = qvec / (float(np.linalg.norm(qvec)) or 1.0) + for mid, vec in self.store.iter_vectors( + flt, include_invalid=include_invalid, dim=int(qn.shape[0])): + sem[mid] = float(np.dot(qn, vec)) q_tokens = tokenize(query) out: list[tuple[float, MemoryRecord]] = [] records = self.store.list_memories( @@ -1608,13 +1618,50 @@ def recall_proactive(self, *, workspace_id: str, repo_id: Optional[str] = None, return {"memories": top, "last_session": last_session} # ── governance (audited; never a silent hard delete — AGENTS.md §3.2) ─────── - def forget(self, memory_id: str, *, reason: str = "", actor: str = "user") -> dict: + def retire(self, memory_id: str, *, reason: str = "", actor: str = "user") -> dict: + """Remove a memory from live recall while retaining temporal history. + + This is deliberately distinct from :meth:`secure_erase`: retirement is the + routine, reversible-by-history governance action; it does not remove the row, + FTS entry, vector, or historical graph evidence. + """ if self.store.get_memory(memory_id) is None: raise KeyError(f"no memory with id '{memory_id}'") - self.store.close_validity(memory_id, actor=actor, reason=reason or "forgotten by request") + self.store.close_validity(memory_id, actor=actor, reason=reason or "retired by request") # Preserve the vector for explicit historical/as_of recall. Temporal filtering # keeps this retired row out of the current live view. - return {"id": memory_id, "status": "forgotten", "reason": reason} + return {"id": memory_id, "status": "retired", "reason": reason} + + def forget(self, memory_id: str, *, reason: str = "", actor: str = "user") -> dict: + """Deprecated compatibility alias for :meth:`retire`. + + Keep the old status string for programmatic consumers that used this legacy + method; new callers must use ``retire`` so its temporal semantics are clear. + """ + result = self.retire(memory_id, reason=reason, actor=actor) + return {**result, "status": "forgotten", "deprecated": True} + + def secure_erase(self, memory_id: str, *, actor: str = "user") -> dict: + """Irreversibly erase a leaked secret from this local Store and derivatives. + + ``VectorIndex`` may be an injected external backend. Request its deletion first, + but do not leave the local SQLite copy intact if that backend is unavailable; the + returned status explicitly reports that incomplete external cleanup. + """ + index_cleanup = "not_configured" + try: + self.index.delete([memory_id]) + index_cleanup = "deleted" + except Exception: # noqa: BLE001 - must still erase the authoritative local copy + index_cleanup = "failed" + result = self.store.secure_erase_memory(memory_id, actor=actor) + result["vector_index_cleanup"] = index_cleanup + if index_cleanup == "failed": + result["external_index_limitation"] = ( + "The configured vector index did not confirm deletion; remediate that backend " + "separately before treating the secret as fully erased." + ) + return result def pin(self, memory_id: str, *, pinned: bool = True, actor: str = "user") -> dict: if self.store.get_memory(memory_id) is None: diff --git a/engraphis/core/grounded.py b/engraphis/core/grounded.py index 61e2f977..6d2951e8 100644 --- a/engraphis/core/grounded.py +++ b/engraphis/core/grounded.py @@ -11,8 +11,9 @@ * **Deterministic (offline default).** No LLM. The answer is an *extractive* stitch of the cited memories — it never introduces a claim that is not in a source. The - groundedness verdict is computed from an absolute query-memory support signal - (semantic cosine plus lexical/predicate agreement), independent of the relative, + feature-hashing fallback is lexical-only: semantic cosine is disabled and the + groundedness verdict uses lexical/predicate agreement. A declared semantic backend + additionally contributes semantic cosine. Both are independent of the relative, per-query recall score, so "insufficient evidence" is a real threshold rather than a ranking artefact. * **Synthesised (opt-in).** If an object implementing ``core.interfaces.LLM`` is @@ -37,17 +38,15 @@ import numpy as np from engraphis.core.context import RegexTokenCounter -from engraphis.core.interfaces import LLM +from engraphis.core.interfaces import LLM, embedder_capabilities from engraphis.core.poisoning import detect_payload_signals, prompt_eligible from engraphis.core.recall import RecallResult from engraphis.core.textutil import jaccard, tokenize -# Absolute support floor (max of cosine / Jaccard, both in [0, 1]) below which we -# abstain. Tuned so an on-topic query clears it while an off-topic one — for which the -# vector index still returns its nearest, but unrelated, neighbour — does not. On the -# deterministic (token-hashing) embedder the eval fixture (eval/grounded.py) separates -# cleanly: answerable support ~0.44-0.65, off-topic ~0.05-0.17, so the floor sits in the -# empty gap between them. A real embedder only separates these further. +# Absolute support floor (max of declared semantic cosine / lexical Jaccard, both in [0, 1]) +# below which we abstain. Feature hashing deliberately contributes no cosine: its lexical +# Jaccard evidence remains enough for the offline fixture while near-neighbour vector matches +# cannot masquerade as semantic support. A real semantic backend additionally contributes cosine. GROUNDED_SUPPORT_FLOOR = 0.25 ABSTAIN_SENTINEL = "INSUFFICIENT_EVIDENCE" _CITE_RE = re.compile(r"\[(\d+)\]") @@ -93,6 +92,10 @@ class GroundedAnswer: planning_mode: str = "off" planning_details: Optional[dict] = None graph_traversal_details: Optional[list[dict]] = None + degraded_mode: bool = False + semantic_support: bool = True + embedding_mode: str = "semantic" + degraded_reason: str = "" def to_dict(self) -> dict: payload = { @@ -115,6 +118,10 @@ def to_dict(self) -> dict: "candidate_depth_reason": self.candidate_depth_reason, "context_revision": self.context_revision, "planning": self.planning_mode, + "degraded_mode": self.degraded_mode, + "semantic_support": self.semantic_support, + "embedding_mode": self.embedding_mode, + "degraded_reason": self.degraded_reason, } if self.retrieval_trace is not None: payload["retrieval_trace"] = self.retrieval_trace @@ -162,8 +169,52 @@ def _related_term_count(query_tokens: set[str], content_tokens: set[str]) -> int return matched +def _lexical_stem(token: str) -> str: + """Normalize only conservative English inflections for lexical evidence. + + This is deliberately not a semantic expansion. It lets an offline lexical query + match ordinary forms such as ``authentication``/``authenticates`` and + ``repository``/``repositories`` after semantic vectors have been fail-closed. + """ + token = str(token or "").casefold() + if len(token) > 5 and token.endswith("ies"): + return token[:-3] + "y" + if len(token) > 6 and token.endswith("ions"): + return token[:-4] + if len(token) > 5 and token.endswith("ion"): + return token[:-3] + if len(token) > 6 and token.endswith(("ised", "ized")): + return token[:-1] + if len(token) > 6 and token.endswith("ates"): + return token[:-2] + if len(token) > 4 and token.endswith("s") and not token.endswith("ss"): + return token[:-1] + return token + + +def _lexical_support(query_tokens: set[str], content_tokens: set[str]) -> float: + """Conservative lexical evidence with an anti-single-keyword guard.""" + normalized_query = {_lexical_stem(token) for token in query_tokens} + normalized_content = {_lexical_stem(token) for token in content_tokens} + matched = len(normalized_query & normalized_content) + # A long question sharing one noun (``bake sourdough bread`` vs. a note that + # merely mentions sourdough) is not evidence. Short, specific questions may + # have one decisive identifier and are handled by directional query coverage. + if len(normalized_query) >= 3 and matched < 2: + return 0.0 + if not normalized_query: + return 0.0 + return max( + jaccard(normalized_query, normalized_content), + # Keep a one-term identifier useful without turning exact lexical coverage + # into an unconditional 1.0 confidence; callers may still demand a strict + # support floor near one. + matched / (len(normalized_query) + 1), + ) + + def support_scores(query: str, contents: list[str], embedder) -> list[float]: - """Absolute per-source support from semantic, lexical, and predicate agreement. + """Absolute per-source support from declared semantic and lexical evidence. Both arms are query-independent in scale — unlike the recall score, which is min-max normalised *per query* and so cannot be compared against a fixed threshold. That is @@ -174,20 +225,26 @@ def support_scores(query: str, contents: list[str], embedder) -> list[float]: if not contents: return [] q_tokens = tokenize(query) - _QUERY_FRAMING_TERMS - texts = [_filtered_text(query)] + [_filtered_text(c) for c in contents] - vecs = embedder.embed(texts) - qn = np.asarray(vecs[0], dtype=float) - qn = qn / (float(np.linalg.norm(qn)) or 1.0) + semantic_support = embedder_capabilities(embedder)["semantic_support"] + qn = None + vecs = None + if semantic_support: + texts = [_filtered_text(query)] + [_filtered_text(c) for c in contents] + vecs = embedder.embed(texts) + qn = np.asarray(vecs[0], dtype=float) + qn = qn / (float(np.linalg.norm(qn)) or 1.0) out: list[float] = [] for i, content in enumerate(contents): content_tokens = tokenize(content) - cv = np.asarray(vecs[i + 1], dtype=float) - cn = cv / (float(np.linalg.norm(cv)) or 1.0) - cos = max(0.0, float(np.dot(qn, cn))) - lex = jaccard(q_tokens, content_tokens) + cos = 0.0 + if qn is not None and vecs is not None: + cv = np.asarray(vecs[i + 1], dtype=float) + cn = cv / (float(np.linalg.norm(cv)) or 1.0) + cos = max(0.0, float(np.dot(qn, cn))) + lex = _lexical_support(q_tokens, content_tokens) related_terms = _related_term_count(q_tokens, content_tokens) - # Hashing and dense embedders can consider two texts topically similar - # when they share one salient noun but make unrelated claims. Require a + # A declared dense embedder can consider two texts topically similar when they + # share one salient noun but make unrelated claims. Require a # second predicate/qualifier match for ordinary multi-term questions, # while allowing genuinely strong semantic paraphrases to stand alone. if len(q_tokens) >= 3 and related_terms < 2 and cos < 0.6: @@ -354,6 +411,7 @@ def build_grounded_answer(query: str, result: RecallResult, embedder, *, "planning_mode": result.planning_mode, "planning_details": result.planning_details, "graph_traversal_details": result.graph_traversal_details, + **embedder_capabilities(embedder), } recall_metadata["usage"]["answer_tokens"] = 0 diff --git a/engraphis/core/interfaces.py b/engraphis/core/interfaces.py index d5201051..4cd0538a 100644 --- a/engraphis/core/interfaces.py +++ b/engraphis/core/interfaces.py @@ -273,9 +273,43 @@ class Embedder(Protocol): """Turns text or code into dense vectors. Default local; API optional.""" @property def dim(self) -> int: ... + @property + def supports_semantic_search(self) -> bool: ... + @property + def embedding_mode(self) -> str: ... def embed(self, texts: list[str], *, kind: Literal["text", "code"] = "text") -> np.ndarray: ... +def embedder_capabilities(embedder: Any) -> dict[str, Any]: + """Return public retrieval capabilities for an embedder. + + Semantic retrieval is opt-in: an embedder that does not explicitly advertise it is + treated as degraded. This prevents a feature-hashing fallback (or an incomplete + third-party adapter) from being presented as a semantic model merely because it + produces vectors. The returned shape is transport-safe and is included in recall + and grounded-answer responses. + """ + semantic_support = bool(getattr(embedder, "supports_semantic_search", False)) + mode = str(getattr(embedder, "embedding_mode", "") or "").strip().casefold() + if not mode: + mode = "semantic" if semantic_support else "unknown" + degraded_mode = not semantic_support + reason = "" + if degraded_mode: + reason = str(getattr(embedder, "semantic_support_reason", "") or "").strip() + if not reason: + reason = ( + "embedding backend did not declare semantic capability; semantic " + "vector retrieval is disabled" + ) + return { + "degraded_mode": degraded_mode, + "semantic_support": semantic_support, + "embedding_mode": mode, + "degraded_reason": reason, + } + + @runtime_checkable class VectorIndex(Protocol): """Approximate nearest-neighbour index over embeddings (§6.2).""" diff --git a/engraphis/core/recall.py b/engraphis/core/recall.py index 0979e95a..a6331f1c 100644 --- a/engraphis/core/recall.py +++ b/engraphis/core/recall.py @@ -1,10 +1,11 @@ """Hybrid recall engine. -Pipeline: scope/time filter → hybrid candidate generation (vector + lexical + graph) -→ RRF fusion → six-term weighted scoring → rerank → context packing → reinforce. +Pipeline: scope/time filter → hybrid candidate generation (semantic vector + lexical + graph) +→ RRF fusion → retention-aware weighted scoring → rerank → context packing → reinforce. The arms are pluggable: -* vector — any ``VectorIndex`` (NumPy reference now; sqlite-vec/Qdrant later) +* vector — declared semantic embedders through any ``VectorIndex`` (NumPy reference now; + sqlite-vec/Qdrant later); disabled for feature hashing and undeclared adapters * lexical — ``Store.fts_search`` (FTS5/BM25, with fallback) * graph — Personalized PageRank over the entity/link graph (``core.graphrank``), seeded at the query's entities; ``graph_mode="1hop"`` keeps the older @@ -37,6 +38,7 @@ GraphTraversalPolicy, CandidateDepthPolicy, MemoryType, + embedder_capabilities, MemoryRecord, PackedChunk, PlannedQuery, @@ -96,6 +98,12 @@ class RecallResult: # a trust-sensitive decision (grounded recall) can still honour a record's # quarantine state without exposing arbitrary user metadata through recall(). source_metadata: dict[str, dict] = field(default_factory=dict, repr=False) + # Capabilities are public response metadata, not a score. In particular, the + # deterministic feature-hashing fallback must never be mistaken for semantic recall. + degraded_mode: bool = False + semantic_support: bool = True + embedding_mode: str = "semantic" + degraded_reason: str = "" class RecallEngine: @@ -180,6 +188,12 @@ def recall(self, query: str, flt: Optional[SearchFilter] = None, *, k: int = 8, # ablations. Normal callers still use only named RetrievalPolicy profiles, # so benchmark labels do not expand the public routing contract. config = arm_config or profile_config(selected_profile) + capabilities = embedder_capabilities(self.embedder) + # A vector is not automatically semantic evidence. Feature hashing and any + # unclassified third-party adapter fail closed: keep lexical/graph/code recall, + # but never query the vector arm or add its cosine to a recall score. + if not capabilities["semantic_support"]: + config = replace(config, vector=False, semantic_scale=0.0) planning_mode = str(planning or "off").strip().casefold() if planning_mode not in PLANNING_MODES: choices = ", ".join(sorted(PLANNING_MODES)) @@ -217,6 +231,14 @@ def recall(self, query: str, flt: Optional[SearchFilter] = None, *, k: int = 8, config if index == 0 and arm_config is not None else profile_config(item.profile) for index, item in enumerate(planned_queries) ] + if not capabilities["semantic_support"]: + # Planned subqueries can select their own retrieval profile. Apply the + # degraded-mode clamp after that expansion so planning cannot re-enable + # feature-hashing vectors for any arm. + run_configs = [ + replace(run_config, vector=False, semantic_scale=0.0) + for run_config in run_configs + ] embedded_texts = [ item.text for item, run_config in zip(planned_queries, run_configs) if run_config.vector @@ -372,12 +394,13 @@ def recall(self, query: str, flt: Optional[SearchFilter] = None, *, k: int = 8, _graph_traversal_details(query_runs) if diagnostics else None ), token_counter=getattr(self.context_packer, "count_tokens", None), + **capabilities, ) arm_state, rrf = _fuse_query_runs(query_runs, recs) primary_vec = query_runs[0]["vector"] - # ── six-term weighted score (+ small RRF nudge for cross-arm agreement) ── + # ── weighted score (+ small RRF nudge for cross-arm agreement) ───────── scored: list[Candidate] = [] score_details: dict[str, dict[str, Any]] = {} for mid, rec in recs.items(): @@ -423,7 +446,7 @@ def recall(self, query: str, flt: Optional[SearchFilter] = None, *, k: int = 8, "graph": adjusted_graph, "code": adjusted_code, }, - "six_term_score": base, + "ranking_score": base, "rrf_score": rrf.get(mid, 0.0), "fusion_score": fusion_score, "rerank_score": None, @@ -569,6 +592,7 @@ def recall(self, query: str, flt: Optional[SearchFilter] = None, *, k: int = 8, for candidate in final if candidate.record is not None }, + **capabilities, ) def _plan_queries( diff --git a/engraphis/core/scoring.py b/engraphis/core/scoring.py index cc02e155..099ceb1d 100644 --- a/engraphis/core/scoring.py +++ b/engraphis/core/scoring.py @@ -1,14 +1,15 @@ """Recall scoring. -Pure, testable functions for the six-term Engraphis recall score: +Pure, testable functions for the ordinary Engraphis recall score: score = w_r·retention + w_s·semantic + w_l·lexical + w_g·graph - + w_i·importance + w_c·recency − w_x·staleness + + w_i·importance − w_x·staleness -Weights are per memory type (a procedural memory weights importance/graph higher; -a working memory weights recency higher), and arm scores are min-max normalized -before fusion so no single arm dominates by raw scale. This is the concrete fix -for "similar ≠ important": semantic similarity is one term among six. +The proactive agenda additionally uses its own recency signal. Ordinary query recall +does not: retention already reflects time since reinforcement, and adding validity/ +ingestion age would double-weight the age of an unreinforced record. Arm scores are +min-max normalized before fusion so no single arm dominates by raw scale. This is the +concrete fix for "similar ≠ important": semantic similarity is one term among five. """ from __future__ import annotations @@ -36,7 +37,7 @@ class Weights: l: float = 0.5 # noqa: E741 (lexical weight w_l; single-letter to match the formula) g: float = 0.7 # graph proximity i: float = 0.6 # importance - c: float = 0.3 # recency + c: float = 0.3 # proactive-agenda recency (never ordinary query recall) x: float = 0.8 # staleness penalty (subtracted) @@ -115,14 +116,21 @@ def reciprocal_rank_fusion(rankings: list[list[str]], k: int = 60) -> dict[str, def score_memory(rec: MemoryRecord, *, now: float, weights: Weights, semantic: float = 0.0, lexical: float = 0.0, graph: float = 0.0, recency_tau_days: float = 30.0) -> float: - """The six-term recall score for a single candidate.""" + """Score one ordinary query-recall candidate without age double-counting. + + Retention measures time since the candidate was last reinforced. Recency is + deliberately excluded here because it measures when the fact was valid or + ingested; for an unreinforced record, using both makes age count twice. The + separate :func:`score_proactive` agenda retains its explicit recency signal. + + ``recency_tau_days`` is retained as an ignored compatibility parameter for + callers that configured previous releases. + """ w = weights r = retention(rec.stability, rec.last_access, now) - rec_ref = rec.valid_from if rec.valid_from is not None else rec.ingested_at - c = recency(rec_ref, now, recency_tau_days) x = staleness_penalty(rec.valid_to, now) return (w.r * r + w.s * semantic + w.l * lexical + w.g * graph - + w.i * (rec.importance or 0.0) + w.c * c - w.x * x) + + w.i * (rec.importance or 0.0) - w.x * x) def score_proactive(rec: MemoryRecord, *, now: float, weights: Optional[Weights] = None, diff --git a/engraphis/core/secrets.py b/engraphis/core/secrets.py new file mode 100644 index 00000000..045bf44b --- /dev/null +++ b/engraphis/core/secrets.py @@ -0,0 +1,134 @@ +"""Capture-time secret detection for local memory persistence. + +This is intentionally a blocking boundary, not a sensitivity classifier. A memory +database is searchable by its FTS/vector indexes while its process is running, so +labelling a credential ``secret`` after it is captured is not a protection. + +The detector is deliberately conservative for credential-shaped values and never +includes the matched value in an exception, audit record, or response. +""" +from __future__ import annotations + +import json +import re +from typing import Any, Iterable + + +class SecretDetectedError(ValueError): + """A content-free rejection of an attempted credential write.""" + + def __init__(self, field: str, kind: str) -> None: + self.field = field + self.kind = kind + super().__init__( + f"potential {kind} detected in {field}; redact it before storing memory" + ) + + +# Provider-specific prefixes and private-key/JWT forms have enough structure to be +# safe to block without a caller-supplied label. Assignment detection below catches +# generic credentials (including private deployment tokens) only when the field name +# explicitly says that it is a credential. +_PATTERNS: tuple[tuple[str, re.Pattern[str]], ...] = ( + ("private key", re.compile(r"-----BEGIN(?: [A-Z0-9]+)? PRIVATE KEY-----", re.I)), + ("AWS access key", re.compile(r"\b(?:AKIA|ASIA)[A-Z0-9]{16}\b")), + ("GitHub token", re.compile(r"\bgh[pousr]_[A-Za-z0-9_]{20,}\b")), + ("GitLab token", re.compile(r"\bglpat-[A-Za-z0-9_-]{20,}\b")), + ("Slack token", re.compile(r"\bxox(?:a|b|p|r|s)-[A-Za-z0-9-]{10,}\b")), + ("OpenAI API key", re.compile(r"\bsk-(?:proj-)?[A-Za-z0-9_-]{20,}\b")), + ("JSON Web Token", re.compile(r"\beyJ[A-Za-z0-9_-]{8,}\.[A-Za-z0-9_-]{8,}\.[A-Za-z0-9_-]{8,}\b")), + ("bearer token", re.compile(r"\bBearer\s+[A-Za-z0-9._~+/=-]{16,}\b", re.I)), +) + +# Do not treat an explanatory phrase such as "password rotation" as a credential. +# A value must be assigned and be non-trivially long. The negative look-ahead lets +# callers deliberately store the literal redaction marker in a fact or provenance +# field without disabling detection for real values. +_ASSIGNMENT = re.compile( + r"""(?ix) + \b(?:[a-z][a-z0-9]*[_-])*(?: + api[_-]?key|(?:access|refresh|session|id)[_-]?token|token|auth(?:orization)?| + bearer|password|passwd|client[_-]?secret|private[_-]?key| + secret(?:[_-]?(?:access[_-]?key|key))?|database[_-]?(?:url|password)| + connection[_-]?string + )\b(?:[\"']\s*)? + \s*(?:=|:)\s*[\"']? + (?!?\b) + [^\s\"']{8,} + """ +) +_DSN = re.compile( + r"\b(?:postgres(?:ql)?|mysql|mongodb(?:\+srv)?|redis|amqp)://" + r"[^\s/@:]+:[^@\s]{8,}@", + re.I, +) +_SENSITIVE_MAPPING_KEY = re.compile( + r"""(?ix) + (?:[a-z][a-z0-9]*[_\-.])*(?: + api[_-]?key|(?:access|refresh|session|id)[_-]?token|token|auth(?:orization)?| + bearer|password|passwd|client[_-]?secret|private[_-]?key| + secret(?:[_-]?(?:access[_-]?key|key))?|database[_-]?(?:url|password)| + connection[_-]?string + ) + """, +) +_REDACTION = re.compile(r"^?$", re.I) + + +def _text(value: Any) -> str: + if isinstance(value, str): + return value + try: + return json.dumps(value, ensure_ascii=False, sort_keys=True, default=str) + except (TypeError, ValueError, RecursionError): + return str(value) + + +def _mapping_secret_kind(value: Any) -> str | None: + """Catch environment/config mappings before JSON rendering obscures their keys.""" + if isinstance(value, dict): + for key, child in value.items(): + key_text = str(key) + child_text = _text(child).strip().strip("\"'") + if (_SENSITIVE_MAPPING_KEY.fullmatch(key_text) and len(child_text) >= 8 + and not _REDACTION.fullmatch(child_text)): + return "credential assignment" + nested = _mapping_secret_kind(child) + if nested: + return nested + elif isinstance(value, (list, tuple, set)): + for child in value: + nested = _mapping_secret_kind(child) + if nested: + return nested + return None + + +def secret_kind(value: Any) -> str | None: + """Return a stable, non-sensitive category when *value* contains a secret.""" + mapped = _mapping_secret_kind(value) + if mapped: + return mapped + value = _text(value) + if not value: + return None + for kind, pattern in _PATTERNS: + if pattern.search(value): + return kind + if _DSN.search(value): + return "credential-bearing connection URI" + if _ASSIGNMENT.search(value): + return "credential assignment" + return None + + +def reject_secrets(fields: Iterable[tuple[str, Any]]) -> None: + """Reject the first secret found in persisted memory/event payload fields. + + Keep the public message content-free: callers log validation errors and can safely + return this error through MCP/HTTP without accidentally re-emitting the secret. + """ + for field, value in fields: + kind = secret_kind(value) + if kind: + raise SecretDetectedError(field, kind) diff --git a/engraphis/core/store.py b/engraphis/core/store.py index 3960f330..8081780d 100644 --- a/engraphis/core/store.py +++ b/engraphis/core/store.py @@ -36,6 +36,7 @@ Scope, SearchFilter, ) +from engraphis.core.secrets import reject_secrets from engraphis.core.schema import ( FTS_SQL_FALLBACK, FTS_SQL_FTS5, @@ -1912,6 +1913,15 @@ def get_last_session(self, workspace_id: str, repo_id: Optional[str], # ── memories ────────────────────────────────────────────────────────────── def add_memory(self, rec: MemoryRecord, *, audit: bool = True, commit: bool = True) -> str: + # This is the last common write boundary. Check every persisted text-bearing + # field *before* the main row, FTS mirror, or vector are written, including + # direct Store callers that do not go through MemoryEngine/MemoryService. + reject_secrets(( + ("title", rec.title), ("content", rec.content), ("summary", rec.summary), + ("keywords", rec.keywords), ("metadata", rec.metadata), + ("provenance", rec.provenance), ("subject_key", rec.subject_key), + ("claim_kind", rec.claim_kind), + )) # ``Store`` is a local-programmatic capability. Stamp direct new writes # explicitly so prompt-facing recall can fail closed for genuinely legacy # rows without making current low-level integrations silently disappear. @@ -2264,12 +2274,215 @@ def _fts_upsert(self, mid: str, title: str, content: str, keywords: str) -> None (mid, title, content, keywords), ) + # ── destructive, per-memory secure erasure ────────────────────────────── + @staticmethod + def _has_table(conn, name: str) -> bool: + return conn.execute( + "SELECT 1 FROM sqlite_master WHERE type IN ('table','view') AND name=?", (name,) + ).fetchone() is not None + + @classmethod + def _erase_memory_rows(cls, conn, memory_id: str, *, actor: str = "user") -> dict: + """Remove a memory and all known local derivatives from one SQLite database. + + This deliberately does *not* use temporal retirement. It is for accidentally + captured credentials and is intentionally lossy. The helper also supports + recognised local SQLite recovery backups, some of which predate newer tables. + """ + if not cls._has_table(conn, "memories"): + return {"present": False, "removed": False} + row = conn.execute("SELECT id FROM memories WHERE id=?", (memory_id,)).fetchone() + if row is None: + return {"present": False, "removed": False} + + # Ask SQLite to overwrite deleted cells where the active VFS supports it. A + # later VACUUM rebuild removes free pages/FTS tombstones from the live database. + conn.execute("PRAGMA secure_delete=ON") + tables = { + name for name in ( + "mem_fts", "mem_vectors", "mem_vec_ann", "code_memory_links", + "memory_entities", "edge_supports", "edges", "entities", "mem_links", + "audit", + ) if cls._has_table(conn, name) + } + incident_entities: list[str] = [] + if "memory_entities" in tables: + incident_entities = [str(item[0]) for item in conn.execute( + "SELECT DISTINCT entity_id FROM memory_entities WHERE memory_id=?", (memory_id,) + ).fetchall()] + supported_edges: list[str] = [] + if "edge_supports" in tables: + supported_edges = [str(item[0]) for item in conn.execute( + "SELECT DISTINCT edge_id FROM edge_supports WHERE memory_id=?", (memory_id,) + ).fetchall()] + + for table, column in ( + ("mem_fts", "id"), ("mem_vectors", "id"), ("mem_vec_ann", "id"), + ("code_memory_links", "memory_id"), ("memory_entities", "memory_id"), + ("edge_supports", "memory_id"), + ): + if table in tables: + conn.execute(f"DELETE FROM {table} WHERE {column}=?", (memory_id,)) + if "mem_links" in tables: + conn.execute("DELETE FROM mem_links WHERE a=? OR b=?", (memory_id, memory_id)) + + # A graph edge whose last provenance support was the erased memory is itself a + # derivative of that secret. Preserve shared graph facts with another support. + if supported_edges and "edges" in tables: + marks = ",".join("?" for _ in supported_edges) + if "edge_supports" in tables: + conn.execute( + f"DELETE FROM edges WHERE id IN ({marks}) AND NOT EXISTS " + "(SELECT 1 FROM edge_supports s WHERE s.edge_id=edges.id)", + supported_edges, + ) + else: + conn.execute(f"DELETE FROM edges WHERE id IN ({marks})", supported_edges) + + # An entity extracted only from this memory can itself contain credential text. + # Remove it only if it no longer has any memory or graph incidence. + if incident_entities and "entities" in tables: + marks = ",".join("?" for _ in incident_entities) + clauses = [] + if "memory_entities" in tables: + clauses.append("NOT EXISTS (SELECT 1 FROM memory_entities me " + "WHERE me.entity_id=entities.id)") + if "edges" in tables: + clauses.append("NOT EXISTS (SELECT 1 FROM edges e " + "WHERE e.src=entities.id OR e.dst=entities.id)") + if clauses: + conn.execute( + f"DELETE FROM entities WHERE id IN ({marks}) AND " + " AND ".join(clauses), + incident_entities, + ) + + # Prior audit details are caller text and could itself contain the credential. + # Remove those entries, then add only a content-free erasure marker below. + if "audit" in tables: + conn.execute("DELETE FROM audit WHERE target=?", (memory_id,)) + conn.execute("DELETE FROM memories WHERE id=?", (memory_id,)) + if "audit" in tables: + conn.execute( + "INSERT INTO audit(id, ts, actor, action, target, detail) VALUES (?,?,?,?,?,?)", + (ids.new_id("audit"), now_ts(), actor, "secure_erase", memory_id, + "per-memory secure erasure completed; content intentionally omitted"), + ) + return { + "present": True, + "removed": True, + "graph_edges_considered": len(supported_edges), + "entities_considered": len(incident_entities), + } + + @staticmethod + def _checkpoint_and_vacuum(conn, *, durable: bool) -> dict: + """Best-effort physical cleanup after a destructive erase, without overclaiming.""" + if not durable: + return {"secure_delete": True, "wal": "not_applicable", "vacuum": "not_applicable"} + result = {"secure_delete": True, "wal": "unavailable", "vacuum": "unavailable"} + try: + checkpoint = conn.execute("PRAGMA wal_checkpoint(TRUNCATE)").fetchone() + # SQLite returns (busy, log, checkpointed); never pretend busy means erased. + result["wal"] = "truncated" if checkpoint is not None and int(checkpoint[0]) == 0 else "busy" + except Exception: # pragma: no cover - depends on VFS / external connection state + result["wal"] = "failed" + try: + conn.execute("VACUUM") + result["vacuum"] = "completed" + except Exception: # pragma: no cover - depends on disk / external connection state + result["vacuum"] = "failed" + try: + checkpoint = conn.execute("PRAGMA wal_checkpoint(TRUNCATE)").fetchone() + if checkpoint is not None and int(checkpoint[0]) == 0: + result["wal"] = "truncated" + elif result["wal"] != "failed": + result["wal"] = "busy" + except Exception: # pragma: no cover - see initial checkpoint + if result["wal"] != "truncated": + result["wal"] = "failed" + return result + + def _recognised_local_backups(self) -> list[Path]: + """Return recovery artefacts this Store created and can safely identify. + + We cannot discover filesystem snapshots, cloud backups, copied databases, or + another process's encrypted backup location. Those remain an explicit operator + obligation in the secure-erasure result and documentation. + """ + if self.path in (":memory:", "") or self.path.startswith("file::memory:"): + return [] + primary = Path(self.path).resolve() + parent = primary.parent + patterns = ( + f"{primary.name}.pre-migration-v*.bak", + f"{primary.name}.embed-repair-*.bak", + f"{primary.stem}.v1-backup-*.db", + ) + found: list[Path] = [] + for pattern in patterns: + for candidate in parent.glob(pattern): + try: + if candidate.is_file() and candidate.resolve() != primary: + found.append(candidate.resolve()) + except OSError: + continue + return sorted(set(found), key=lambda value: str(value)) + + def secure_erase_memory(self, memory_id: str, *, actor: str = "user") -> dict: + """Irreversibly erase one memory plus local index copies and known backups. + + This is a breach-remediation operation, not the normal ``retire`` lifecycle. + It clears current SQLite rows, FTS/vector/ANN derivatives, related graph/link + state, audit details for that record, WAL contents when SQLite can checkpoint, + and recognised local SQLite recovery backups. OS snapshots, copies, remote sync + peers, and a process that already read the secret cannot be recalled or erased. + """ + current = self._erase_memory_rows(self.conn, memory_id, actor=actor) + if not current["present"]: + raise KeyError(f"no memory with id '{memory_id}'") + self.conn.commit() + durable = self.path not in (":memory:", "") and not self.path.startswith("file::memory:") + maintenance = self._checkpoint_and_vacuum(self.conn, durable=durable) + + backup_processed = 0 + backup_failed = 0 + for backup in self._recognised_local_backups(): + conn = None + try: + conn = self._open_connection(str(backup)) + erased = self._erase_memory_rows(conn, memory_id, actor="secure_erase") + conn.commit() + self._checkpoint_and_vacuum(conn, durable=True) + if erased["present"]: + backup_processed += 1 + except Exception: # pragma: no cover - keyed/corrupt/locked backups vary by deployment + backup_failed += 1 + finally: + if conn is not None: + try: + conn.close() + except Exception: + pass + return { + "id": memory_id, + "status": "securely_erased", + "maintenance": maintenance, + "recognised_backups_erased": backup_processed, + "recognised_backups_failed": backup_failed, + "backup_limitations": ( + "Only recognised local SQLite recovery backups were scanned. Erase or rotate " + "filesystem snapshots, copied/exported databases, remote sync peers, and any " + "other backups separately; a running agent may already have read the secret." + ), + } + def fts_search(self, query: str, k: int = 20, *, filter: Optional[SearchFilter] = None) -> list[tuple[str, float]]: """Lexical arm. Uses FTS5 BM25 when available, else a LIKE fallback.""" q = (query or "").strip() if not q: return [] + terms = _fts_terms(q) where, params = self._where(filter, include_invalid=False, alias="m") extra = (" AND " + " AND ".join(where)) if where else "" if self.has_fts5: @@ -2286,12 +2499,25 @@ def fts_search(self, query: str, k: int = 20, pass # Escape LIKE wildcards: on a non-FTS5 build an unescaped '%'/'_' in the query # would be treated as a pattern and over-match (a bare "%" matching everything). - like = f"%{_escape_like(q)}%" + # Use the same conservative inflection variants as FTS5 so lexical-only degraded + # mode remains useful on SQLite builds without FTS5. + # Preserve literal wildcard queries. ``_fts_terms`` intentionally removes + # punctuation for FTS syntax, but the LIKE fallback has always supported + # searching for a literal percent, underscore, or backslash. + like_terms = [q] if any(char in q for char in ("%", "_", "\\")) else terms + like_clauses = [] + like_params: list[Any] = [] + for term in like_terms: + like = f"%{_escape_like(term)}%" + like_clauses.append("(f.content LIKE ? ESCAPE '\\' OR f.title LIKE ? ESCAPE '\\')") + like_params.extend((like, like)) + if not like_clauses: + return [] rows = self.conn.execute( "SELECT f.id FROM mem_fts f JOIN memories m ON m.id = f.id " - "WHERE (f.content LIKE ? ESCAPE '\\' OR f.title LIKE ? ESCAPE '\\')" + "WHERE (" + " OR ".join(like_clauses) + ")" + extra + " LIMIT ?", - (like, like, *params, k), + (*like_params, *params, k), ).fetchall() return [(r["id"], 0.5) for r in rows] @@ -4035,6 +4261,10 @@ def memories_mentioning(self, repo_id: str, text: str, *, def append_event(self, *, kind: str, content: str, workspace_id: str = "", repo_id: str = "", session_id: str = "", refs: Optional[list] = None, interaction_level: str = "") -> str: + # Events are not memories, but are durable, searchable agent context too. Do + # not create a side channel that can retain a credential after memory capture is + # blocked. + reject_secrets((("event content", content), ("event refs", refs))) eid = ids.new_id("event") owns_session_transaction = False try: @@ -4695,7 +4925,29 @@ def _row_to_edge(row: sqlite3.Row) -> Edge: ) -def _fts_query(q: str) -> str: - """Make a safe FTS5 MATCH query: OR the alphanumeric terms as prefixes.""" +def _fts_terms(q: str) -> list[str]: + """Return safe lexical terms plus conservative inflection variants.""" terms = [t for t in "".join(c if c.isalnum() else " " for c in q).split() if t] - return " OR ".join(f'{t}*' for t in terms) if terms else '""' + expanded: list[str] = [] + for term in terms: + expanded.append(term) + if len(term) > 5 and term.endswith("ies"): + expanded.append(term[:-3] + "y") + elif len(term) > 6 and term.endswith("ions"): + expanded.append(term[:-4]) + elif len(term) > 5 and term.endswith("ion"): + expanded.append(term[:-3]) + elif len(term) > 6 and term.endswith(("ised", "ized")): + expanded.append(term[:-1]) + elif len(term) > 6 and term.endswith("ates"): + expanded.append(term[:-2]) + elif len(term) > 4 and term.endswith("s") and not term.endswith("ss"): + expanded.append(term[:-1]) + # Keep the caller's term order while avoiding duplicate FTS clauses. + return list(dict.fromkeys(expanded)) + + +def _fts_query(q: str) -> str: + """Make a safe FTS5 MATCH query with conservative inflection prefixes.""" + terms = _fts_terms(q) + return " OR ".join(f'{term}*' for term in terms) if terms else '""' diff --git a/engraphis/core/sync.py b/engraphis/core/sync.py index fc9972d3..38e3c12e 100644 --- a/engraphis/core/sync.py +++ b/engraphis/core/sync.py @@ -57,6 +57,7 @@ prompt_eligible, provenance_is_approved, ) +from engraphis.core.secrets import SecretDetectedError, reject_secrets from engraphis.core.store import Store, now_ts @@ -468,6 +469,17 @@ def dict_to_record(d: dict) -> Optional[MemoryRecord]: content = d.get("content") if not isinstance(mid, str) or not mid or not isinstance(content, str) or not content: return None + # Sync is an external memory write path. Reject the row before it can reach the + # raw Store upsert, FTS, or a locally rebuilt vector; a secret-bearing peer row is + # simply counted as rejected like any other malformed bundle entry. + try: + reject_secrets((("title", d.get("title")), ("content", content), + ("summary", d.get("summary")), ("keywords", d.get("keywords")), + ("metadata", d.get("metadata")), ("provenance", d.get("provenance")), + ("subject_key", d.get("subject_key")), + ("claim_kind", d.get("claim_kind")))) + except SecretDetectedError: + return None kws = d.get("keywords") or [] if not isinstance(kws, list): kws = [] diff --git a/engraphis/dashboard_assets/ledger.js b/engraphis/dashboard_assets/ledger.js index 6eaadf8f..91bf2f4b 100644 --- a/engraphis/dashboard_assets/ledger.js +++ b/engraphis/dashboard_assets/ledger.js @@ -862,7 +862,8 @@ button('Edit', 'secondary-button', () => openEditor(memory)), button(memory.pinned ? 'Unpin' : 'Pin', 'secondary-button', () => togglePin(memory)), button('View timeline', 'secondary-button', () => openMemoryTimeline(memory)), - button('Forget', 'danger-button', () => forgetMemory(memory)), + button('Retire', 'danger-button', () => retireMemory(memory)), + button('Secure erase leak', 'danger-button', () => secureEraseMemory(memory)), ); target.append(actions); const chain = payload.chain || []; @@ -1027,19 +1028,37 @@ } } - async function forgetMemory(memory) { - if (!window.confirm(`Forget “${memory.title || memory.id}”? The record stays in temporal history but leaves live recall.`)) return; + async function retireMemory(memory) { + if (!window.confirm(`Retire “${memory.title || memory.id}”? The record stays in temporal history but leaves live recall.`)) return; try { - await api('/forget', { + await api('/retire', { method: 'POST', - body: { id: memory.id, workspace: state.workspace, reason: 'forgotten in Ledger' }, + body: { id: memory.id, workspace: state.workspace, reason: 'retired in Ledger' }, }); state.selectedMemory = ''; byId('memory-detail').replaceChildren(empty('Memory moved out of live recall. Its history is retained.')); - showNotice('Memory forgotten without hard deletion.'); + showNotice('Memory retired without hard deletion.'); await selectWorkspace(state.workspace); } catch (error) { - showNotice(`Could not forget memory: ${error.message}`); + showNotice(`Could not retire memory: ${error.message}`); + } + } + + async function secureEraseMemory(memory) { + const name = memory.title || memory.id; + if (!window.confirm(`Securely erase “${name}”? This destroys temporal history and local index copies. Rotate the leaked credential; copied exports, snapshots, remote peers, and an already-compromised agent cannot be erased here.`)) return; + try { + const result = await api('/secure-erase', { + method: 'POST', body: { id: memory.id, workspace: state.workspace }, + }); + state.selectedMemory = ''; + byId('memory-detail').replaceChildren(empty('Memory securely erased from this local store. Review the reported backup limitations and rotate the credential.')); + showNotice(result.vector_index_cleanup === 'failed' + ? 'Memory removed locally; configured vector index needs separate remediation.' + : 'Memory securely erased from local persistence.'); + await selectWorkspace(state.workspace); + } catch (error) { + showNotice(`Could not securely erase memory: ${error.message}`); } } diff --git a/engraphis/inspector/app.py b/engraphis/inspector/app.py index c19e3310..85ed7e0b 100644 --- a/engraphis/inspector/app.py +++ b/engraphis/inspector/app.py @@ -313,7 +313,17 @@ async def pin(body: _GovernBody): actor="inspector-local", ) - @app.post("/api/forget") + @app.post("/api/retire") + async def retire(body: _GovernBody): + return svc().retire( + body.memory_id, + workspace=body.workspace, + repo=body.repo, + reason=body.reason, + actor="inspector-local", + ) + + @app.post("/api/forget", deprecated=True) async def forget(body: _GovernBody): return svc().forget( body.memory_id, @@ -323,6 +333,15 @@ async def forget(body: _GovernBody): actor="inspector-local", ) + @app.post("/api/secure-erase") + async def secure_erase(body: _GovernBody): + return svc().secure_erase( + body.memory_id, + workspace=body.workspace, + repo=body.repo, + actor="inspector-local", + ) + @app.post("/api/correct") async def correct(body: _CorrectBody): return svc().correct( diff --git a/engraphis/mcp_http_cli.py b/engraphis/mcp_http_cli.py new file mode 100644 index 00000000..5a95c3d9 --- /dev/null +++ b/engraphis/mcp_http_cli.py @@ -0,0 +1,100 @@ +"""Console entry for a local loopback MCP-over-HTTP server. + +This is intentionally a generic MCP transport, not an integration with any particular +agent host. Remote MCP access belongs behind the authenticated dashboard ``/mcp`` +mount; a standalone FastMCP transport has no Engraphis authentication middleware. +""" +from __future__ import annotations + +import argparse +import importlib.util +import ipaddress +import os +import sys + +_TRANSPORTS = ("streamable-http", "sse") + + +def _dependency_error() -> str: + if sys.version_info < (3, 10): + return ( + "The Engraphis MCP server requires Python 3.10 or newer.\n" + "Create a Python 3.10+ environment, then run: pip install \"engraphis[mcp]\"" + ) + if importlib.util.find_spec("mcp") is None: + return ( + "The 'mcp' package is required to run the Engraphis MCP server.\n" + "Install it with: pip install \"engraphis[mcp]\"" + ) + return "" + + +def _loopback_host(value: str) -> str: + host = value.strip() + try: + if ipaddress.ip_address(host).is_loopback: + return host + except ValueError: + pass + raise argparse.ArgumentTypeError( + "standalone MCP-over-HTTP accepts loopback hosts only; use the authenticated " + "dashboard /mcp endpoint for remote access" + ) + + +def _port(value: str) -> int: + try: + port = int(value) + except ValueError as exc: + raise argparse.ArgumentTypeError("port must be an integer") from exc + if not 1 <= port <= 65535: + raise argparse.ArgumentTypeError("port must be between 1 and 65535") + return port + + +def main(argv=None) -> None: + ap = argparse.ArgumentParser( + prog="engraphis-mcp-http", + description="Run a loopback-only Engraphis MCP server over HTTP.", + epilog=( + "Use the authenticated dashboard /mcp endpoint for remote clients. " + "Configuration also honors ENGRAPHIS_DB_PATH and the normal .env settings." + ), + ) + ap.add_argument( + "--host", + type=_loopback_host, + default=os.environ.get("ENGRAPHIS_HTTP_HOST", "127.0.0.1"), + help="loopback address to bind (default: ENGRAPHIS_HTTP_HOST or 127.0.0.1)", + ) + ap.add_argument( + "--port", + type=_port, + default=os.environ.get("ENGRAPHIS_HTTP_PORT", "8711"), + help="TCP port to bind (default: ENGRAPHIS_HTTP_PORT or 8711)", + ) + ap.add_argument( + "--transport", + choices=_TRANSPORTS, + default=os.environ.get("ENGRAPHIS_HTTP_TRANSPORT", "streamable-http"), + help="MCP transport (default: ENGRAPHIS_HTTP_TRANSPORT or streamable-http)", + ) + args = ap.parse_args(argv) + if args.transport not in _TRANSPORTS: + ap.error("ENGRAPHIS_HTTP_TRANSPORT must be streamable-http or sse") + + error = _dependency_error() + if error: + raise SystemExit(error) + + # Import only after --help and dependency validation: FastMCP registers tools at + # module import time, so importing it eagerly would make even help unusable. + from engraphis.mcp_server import mcp + + mcp.settings.host = args.host + mcp.settings.port = args.port + mcp.run(transport=args.transport) + + +if __name__ == "__main__": + main() diff --git a/engraphis/mcp_server.py b/engraphis/mcp_server.py index 5d597404..58d065f6 100644 --- a/engraphis/mcp_server.py +++ b/engraphis/mcp_server.py @@ -5,7 +5,7 @@ agents (Claude Code, Cursor, Cline, Zed, Windsurf, …) and general agents can ``remember`` facts and ``recall`` them across sessions and repositories, scoped to ``workspace → repo → session`` — plus the bi-temporal ``why``/``timeline`` -tools, governance (``forget``/``pin``/``correct``), proactive recall, and +tools, governance (``retire``/``pin``/``correct``), proactive recall, and explicit linking/event logging. Run it (stdio transport, the default for local MCP clients):: @@ -285,7 +285,7 @@ def engraphis_recall( description="Optional maximum returned count per memory type; limits never boost " "relevance.")] = None, ) -> str: - """Retrieve the memories most relevant to a query (hybrid vector + lexical + graph). + """Retrieve the memories most relevant to a query (semantic vector + lexical + graph). Call this before answering or acting when prior context would help — to avoid re-asking the user, to recover decisions/conventions, or to resume earlier work. @@ -295,10 +295,13 @@ def engraphis_recall( Because the receipt is stateful, this surface is neither read-only nor idempotent. Returns: - str: JSON with ``{"query","count","context","score_semantics","memories":[{"id", + str: JSON with ``{"query","count","context","degraded_mode","semantic_support", + "embedding_mode","score_semantics","memories":[{"id", "title","content","scope","mtype","repo_id","score","relative_score", "absolute_support","arm","retention","provenance"}]}``. ``score`` is a compatibility alias for the query-relative rank; use ``absolute_support`` (0..1) for an evidence floor. + ``degraded_mode=true`` and ``semantic_support=false`` mean semantic vector retrieval + was disabled because the active embedder is not declared semantic. Returns count 0 with a "note" if the workspace/repo isn't known yet. """ try: @@ -359,7 +362,8 @@ def engraphis_recall_context( This is the recommended agent path: unlike legacy full recall, it does not repeat every complete memory body alongside the already-packed context. The response includes exact accounting for the declared counter, omitted/packed - counts, and privacy-safe savings metadata. + counts, privacy-safe savings metadata, and the same ``degraded_mode`` / + ``semantic_support`` flags as ``engraphis_recall``. """ try: payload = service().recall( @@ -476,12 +480,15 @@ def engraphis_recall_grounded( actually supports the query (``grounded: false``). Use it when you want a grounded, non-hallucinated answer and would rather get "insufficient evidence" than a guess. The deterministic default never introduces a claim that is not in a cited memory. + When ``degraded_mode`` is true, its feature-hashing fallback is treated as lexical-only: + semantic vector retrieval and semantic cosine support are disabled. With ``synthesize=True``, configured LLM prose is accepted only when citations hold. Every resolved call appends a privacy-safe receipt (including abstentions), and a grounded answer reinforces cited memories. Returns: str: JSON ``{"query","grounded","abstained","answer","support","reason", + "degraded_mode","semantic_support","embedding_mode", "synthesized":false,"citations":[{"n","id","title","content","score","support", "provenance"}]}``. When ``grounded`` is false, ``answer`` is empty and ``reason`` explains why (insufficient evidence, or unknown workspace/repo). @@ -701,22 +708,22 @@ def engraphis_proactive_context( @mcp.tool( - name="engraphis_forget", - annotations={"title": "Forget a memory", "readOnlyHint": False, + name="engraphis_retire", + annotations={"title": "Retire a memory", "readOnlyHint": False, "destructiveHint": True, "idempotentHint": False, "openWorldHint": False}, ) -def engraphis_forget( - memory_id: Annotated[str, Field(description="The memory id to forget (from a prior " +def engraphis_retire( + memory_id: Annotated[str, Field(description="The memory id to retire (from a prior " "remember/recall result, e.g. 'mem_01J...').", min_length=1, max_length=200)], workspace: Annotated[str, Field(description="Workspace that owns this memory — checked " "against the memory's actual workspace before anything is " - "changed, so you can't forget a memory in a workspace you " + "changed, so you can't retire a memory in a workspace you " "weren't already given.", min_length=1, max_length=200)], repo: Annotated[Optional[str], Field(description="Repo that owns this memory, if it's " "repo-scoped; also checked.", max_length=200)] = None, - reason: Annotated[str, Field(description="Why this is being forgotten (recorded in the " + reason: Annotated[str, Field(description="Why this is being retired (recorded in the " "audit trail).", max_length=1_000)] = "", ) -> str: """Retire a memory: it stops appearing in recall, but history is preserved, not @@ -726,15 +733,67 @@ def engraphis_forget( is deliberately annotated as non-idempotent. Returns: - str: JSON ``{"id","status":"forgotten","reason"}`` or an actionable error if the + str: JSON ``{"id","status":"retired","reason"}`` or an actionable error if the id is unknown or doesn't belong to ``workspace``/``repo``. """ + try: + return _ok(service().retire(memory_id, workspace=workspace, repo=repo, reason=reason)) + except Exception as exc: # noqa: BLE001 + return _err(exc) + + +@mcp.tool( + name="engraphis_forget", + annotations={"title": "Forget a memory (deprecated; use retire)", "readOnlyHint": False, + "destructiveHint": True, "idempotentHint": False, "openWorldHint": False}, +) +def engraphis_forget( + memory_id: Annotated[str, Field(description="Deprecated alias for memory_id in " + "engraphis_retire.", min_length=1, max_length=200)], + workspace: Annotated[str, Field(description="Workspace that owns this memory.", + min_length=1, max_length=200)], + repo: Annotated[Optional[str], Field(description="Optional owning repo.", + max_length=200)] = None, + reason: Annotated[str, Field(description="Retirement reason recorded in the audit trail.", + max_length=1_000)] = "", +) -> str: + """Deprecated compatibility alias for ``engraphis_retire``. + + It preserves the legacy ``status: \"forgotten\"`` response for existing clients; + it still performs a temporal retirement and never deletes the memory. + """ try: return _ok(service().forget(memory_id, workspace=workspace, repo=repo, reason=reason)) except Exception as exc: # noqa: BLE001 return _err(exc) +@mcp.tool( + name="engraphis_secure_erase", + annotations={"title": "Securely erase a leaked memory", "readOnlyHint": False, + "destructiveHint": True, "idempotentHint": False, "openWorldHint": False}, +) +def engraphis_secure_erase( + memory_id: Annotated[str, Field(description="Leaked memory id to erase irreversibly.", + min_length=1, max_length=200)], + workspace: Annotated[str, Field(description="Workspace that owns the memory.", + min_length=1, max_length=200)], + repo: Annotated[Optional[str], Field(description="Optional owning repo.", + max_length=200)] = None, +) -> str: + """Irreversibly remove one accidentally stored secret from local persistence. + + Unlike retirement, this removes the memory, FTS/vector/ANN and derived graph/link + rows, performs SQLite secure-delete/WAL/VACUUM maintenance, and scans recognised + local SQLite recovery backups. It cannot erase copied exports, snapshots, remote + peers, or data already read by a compromised/running agent; rotate the credential. + """ + try: + return _ok(service().secure_erase(memory_id, workspace=workspace, repo=repo)) + except Exception as exc: # noqa: BLE001 + return _err(exc) + + @mcp.tool( name="engraphis_pin", annotations={"title": "Pin or unpin a memory", "readOnlyHint": False, @@ -790,7 +849,7 @@ def engraphis_correct( """Replace a memory's content without losing history: the old content is closed (bi-temporal invalidate, not deleted) and the correction is stored as a new memory that records what it corrects — so the audit trail and ``engraphis_why`` both still - work afterward. Prefer this over forget+remember for fixes. + work afterward. Prefer this over retire+remember for fixes. Returns: str: JSON ``{"id","superseded":[old_id],"reason"}`` or an actionable error if the diff --git a/engraphis/routes/v2_api.py b/engraphis/routes/v2_api.py index 833d070c..17756808 100644 --- a/engraphis/routes/v2_api.py +++ b/engraphis/routes/v2_api.py @@ -1352,7 +1352,7 @@ def receipts_export(workspace: Optional[str] = None): }) -# ── governance: pin / forget / correct ─────────────────────────────────────── +# ── governance: pin / retire / secure erase / correct ───────────────────────── class _IdReq(BaseModel): id: str workspace: Optional[str] = None @@ -1369,12 +1369,26 @@ def pin(req: _IdReq): return _run(service().pin, req.id, workspace=ws, pinned=req.pinned) -@router.post("/forget") +@router.post("/retire") +def retire(req: _IdReq): + ws = req.workspace or _default_ws() + return _run(service().retire, req.id, workspace=ws, reason=req.reason) + + +@router.post("/forget", deprecated=True) def forget(req: _IdReq): + """Deprecated compatibility route; use POST /api/retire.""" ws = req.workspace or _default_ws() return _run(service().forget, req.id, workspace=ws, reason=req.reason) +@router.post("/secure-erase") +def secure_erase(req: _IdReq): + """Irreversibly erase one leaked record and its local indexed derivatives.""" + ws = req.workspace or _default_ws() + return _run(service().secure_erase, req.id, workspace=ws, repo=req.repo) + + @router.post("/correct") def correct(req: _IdReq): ws = req.workspace or _default_ws() diff --git a/engraphis/service.py b/engraphis/service.py index 31f6a884..9aff96c8 100644 --- a/engraphis/service.py +++ b/engraphis/service.py @@ -41,7 +41,9 @@ ) from engraphis.core.graph_layers import normalize_graph_layer from engraphis.core.ids import new_id as make_id -from engraphis.core.interfaces import Edge, GraphLayer, MemoryType, Node, Scope, SearchFilter +from engraphis.core.interfaces import ( + Edge, GraphLayer, MemoryType, Node, Scope, SearchFilter, embedder_capabilities, +) from engraphis.core.poisoning import ( REVIEW_APPROVED, REVIEW_PENDING, @@ -50,6 +52,7 @@ ) from engraphis.core.query_planner import PLANNING_MODES from engraphis.core.retrieval_policy import CANDIDATE_DEPTH_MODES, RETRIEVAL_PROFILES +from engraphis.core.secrets import SecretDetectedError, reject_secrets from engraphis.core.store import ( _loads, _merge_edge_provenance, @@ -79,12 +82,37 @@ "this response. It is not a confidence value or threshold." ), "absolute_support": ( - "Absolute query-to-memory support in [0, 1]: the maximum of raw retrieval " - "cosine and lexical Jaccard. It is not min-max normalized and is computed " - "without another embedding pass. Grounded recall applies its stricter, " - "separately calibrated evidence gate." + "Absolute query-to-memory support in [0, 1]: the maximum of semantic cosine " + "(when semantic support is enabled) and lexical Jaccard. It is not min-max " + "normalized. Grounded recall applies its stricter, separately calibrated " + "evidence gate." + ), + "semantic_support": ( + "Whether this response used a declared semantic embedder. When false, vector " + "retrieval and semantic cosine support are disabled." ), } + + +def _recall_score_semantics(capabilities: dict) -> dict: + """Describe the support calculation actually used by this response.""" + semantics = dict(RECALL_SCORE_SEMANTICS) + semantics["semantic_support"] = bool(capabilities.get("semantic_support")) + if not capabilities.get("semantic_support"): + semantics["absolute_support"] = ( + "Absolute lexical query-to-memory support in [0, 1] (Jaccard only). " + "Semantic cosine is disabled because the active embedder is not declared " + "semantic." + ) + return semantics + + +def _with_retrieval_capabilities(payload: dict, embedder) -> dict: + """Add the stable degraded-mode contract to a public recall-shaped payload.""" + capabilities = embedder_capabilities(embedder) + payload.update(capabilities) + payload["score_semantics"] = _recall_score_semantics(capabilities) + return payload MAX_CONTEXT_TASK_CHARS = 10_000 MAX_AGENT_STATE_CHARS = 20_000 # import_folder/import_files (SECURITY.md §5 — reads/accepts local-content by path or @@ -234,6 +262,14 @@ class ValidationError(ValueError): """Raised when untrusted input fails a guard. Message is safe to surface.""" +def _reject_secret_capture(fields) -> None: + """Map the core content-free secret rejection into this facade's error type.""" + try: + reject_secrets(fields) + except SecretDetectedError as exc: + raise ValidationError(str(exc)) from None + + class GraphSceneCapacityExceeded(ValidationError): """A complete scene crossed a hard safety ceiling and was not sampled.""" @@ -1051,6 +1087,10 @@ def remember(self, content: str, *, workspace: str, repo: Optional[str] = None, """ content = _clean_text(content, field="content", max_chars=MAX_CONTENT_CHARS) title = _clean_text(title, field="title", max_chars=MAX_TITLE_CHARS, required=False) + _reject_secret_capture(( + ("content", content), ("title", title), ("keywords", keywords), + ("metadata", metadata), ("subject_key", subject_key), ("claim_kind", claim_kind), + )) provenance = ( _local_cli_provenance() if _local_cli_operator else @@ -1192,6 +1232,7 @@ def ingest(self, content: str, *, workspace: str, repo: Optional[str] = None, every retained fact stays passive until an approved local write records the corresponding trusted claim.""" content = _clean_text(content, field="content", max_chars=MAX_CONTENT_CHARS) + _reject_secret_capture((("content", content), ("metadata", metadata))) provenance = _canonical_write_provenance(source, trusted, raw_ingest=True) ws = self._clean_ws(workspace) rp = _clean_name(repo, field="repo") if repo else None @@ -1856,38 +1897,38 @@ def recall(self, query: str, *, workspace: Optional[str] = None, ws = self._clean_ws(workspace) wid = self._lookup_workspace(ws) if wid is None: - return _empty_recall( + return _with_retrieval_capabilities(_empty_recall( query, token_budget=token_budget, response_mode=response_mode, retrieval_profile=retrieval_profile, candidate_depth=candidate_depth, planning=planning, mtype_limits=mtype_limits, valid_at=valid_at, known_at=known_at, note=f"no workspace named '{ws}' yet", - ) + ), self.engine.embedder) if repo: rp = _clean_name(repo, field="repo") rid = self._lookup_repo(wid, rp) if rid is None: - return _empty_recall( - query, token_budget=token_budget, response_mode=response_mode, - retrieval_profile=retrieval_profile, candidate_depth=candidate_depth, - planning=planning, mtype_limits=mtype_limits, - valid_at=valid_at, + return _with_retrieval_capabilities(_empty_recall( + query, token_budget=token_budget, response_mode=response_mode, + retrieval_profile=retrieval_profile, candidate_depth=candidate_depth, + planning=planning, mtype_limits=mtype_limits, + valid_at=valid_at, known_at=known_at, note=f"no repo named '{rp}' in workspace '{ws}' yet", - ) + ), self.engine.embedder) if session_id: sid = _clean_text( session_id, field="session_id", max_chars=MAX_NAME_CHARS ) session = self.store.get_session(sid) if session is None: - return _empty_recall( + return _with_retrieval_capabilities(_empty_recall( query, token_budget=token_budget, response_mode=response_mode, retrieval_profile=retrieval_profile, candidate_depth=candidate_depth, planning=planning, mtype_limits=mtype_limits, valid_at=valid_at, known_at=known_at, note=f"no session with id '{sid}'", - ) + ), self.engine.embedder) if session["workspace_id"] != wid or ( rid is not None and session.get("repo_id") != rid): raise ValidationError("session_id does not belong to that workspace/repo") @@ -1948,6 +1989,7 @@ def recall(self, query: str, *, workspace: Optional[str] = None, "truncated": packed.truncated, "reason": packed.reason, } for packed in result.packed_chunks] + capabilities = embedder_capabilities(self.engine.embedder) out = { "query": query, "count": result.count, "context": result.context, "memories": memories, @@ -1966,7 +2008,8 @@ def recall(self, query: str, *, workspace: Optional[str] = None, "mtype_limits": dict(mtype_limits), "response_mode": response_mode, "include_untrusted": include_untrusted, - "score_semantics": dict(RECALL_SCORE_SEMANTICS), + "score_semantics": _recall_score_semantics(capabilities), + **capabilities, } if diagnostics: out["retrieval_trace"] = result.retrieval_trace or [] @@ -2247,19 +2290,19 @@ def grounded_recall(self, query: str, *, workspace: Optional[str] = None, ws = self._clean_ws(workspace) wid = self._lookup_workspace(ws) if wid is None: - return _empty_grounded( + return _with_retrieval_capabilities(_empty_grounded( query, reason=f"no workspace named '{ws}' yet", token_budget=token_budget, response_mode=response_mode, retrieval_profile=retrieval_profile, candidate_depth=candidate_depth, planning=planning, mtype_limits=mtype_limits, valid_at=valid_at, known_at=known_at, - ) + ), self.engine.embedder) if repo: rp = _clean_name(repo, field="repo") rid = self._lookup_repo(wid, rp) if rid is None: - return _empty_grounded( + return _with_retrieval_capabilities(_empty_grounded( query, reason=f"no repo named '{rp}' in workspace '{ws}' yet", token_budget=token_budget, response_mode=response_mode, @@ -2267,21 +2310,21 @@ def grounded_recall(self, query: str, *, workspace: Optional[str] = None, planning=planning, mtype_limits=mtype_limits, valid_at=valid_at, known_at=known_at, - ) + ), self.engine.embedder) if session_id: sid = _clean_text( session_id, field="session_id", max_chars=MAX_NAME_CHARS ) session = self.store.get_session(sid) if session is None: - return _empty_grounded( + return _with_retrieval_capabilities(_empty_grounded( query, reason=f"no session with id '{sid}'", token_budget=token_budget, response_mode=response_mode, retrieval_profile=retrieval_profile, candidate_depth=candidate_depth, planning=planning, mtype_limits=mtype_limits, valid_at=valid_at, known_at=known_at, - ) + ), self.engine.embedder) if session["workspace_id"] != wid or ( rid is not None and session.get("repo_id") != rid): raise ValidationError("session_id does not belong to that workspace/repo") @@ -2393,17 +2436,39 @@ def end_session(self, session_id: str, *, summary: str = "", outcome: str = "", return {"session_id": sid, "status": "summarized", "summary": summary, "open_threads": threads} - # ── governance: forget / pin / correct / promote (audited; history preserved) ── - def forget(self, memory_id: str, *, workspace: str, repo: Optional[str] = None, - reason: str = "", actor: str = "user") -> dict: + # ── governance: retire / secure erase / pin / correct / promote ─────────── + def retire(self, memory_id: str, *, workspace: str, repo: Optional[str] = None, + reason: str = "", actor: str = "user") -> dict: + """Bi-temporally retire one memory. This preserves history and indexes.""" mid = _clean_text(memory_id, field="memory_id", max_chars=MAX_NAME_CHARS) reason = _clean_text(reason, field="reason", max_chars=MAX_TITLE_CHARS, required=False) + _reject_secret_capture((("reason", reason),)) + actor = _clean_text(actor, field="actor", max_chars=MAX_NAME_CHARS, + required=False) or "user" + wid, rid = self._require_scope(workspace, repo) + self._check_owns(mid, wid, rid) + try: + return self.engine.retire(mid, reason=reason, actor=actor) + except (KeyError, ValueError) as exc: + raise ValidationError(str(exc)) + + def forget(self, memory_id: str, *, workspace: str, repo: Optional[str] = None, + reason: str = "", actor: str = "user") -> dict: + """Deprecated compatibility alias for :meth:`retire`.""" + result = self.retire(memory_id, workspace=workspace, repo=repo, + reason=reason, actor=actor) + return {**result, "status": "forgotten", "deprecated": True} + + def secure_erase(self, memory_id: str, *, workspace: str, repo: Optional[str] = None, + actor: str = "user") -> dict: + """Irreversibly remove one leaked record; unlike retire, history is destroyed.""" + mid = _clean_text(memory_id, field="memory_id", max_chars=MAX_NAME_CHARS) actor = _clean_text(actor, field="actor", max_chars=MAX_NAME_CHARS, required=False) or "user" wid, rid = self._require_scope(workspace, repo) self._check_owns(mid, wid, rid) try: - return self.engine.forget(mid, reason=reason, actor=actor) + return self.engine.secure_erase(mid, actor=actor) except (KeyError, ValueError) as exc: raise ValidationError(str(exc)) @@ -2622,6 +2687,7 @@ def record_event(self, kind: str, content: str, *, workspace: str, refs: Optional[list] = None) -> dict: kind = _clean_name(kind, field="kind") content = _clean_text(content, field="content", max_chars=MAX_CONTENT_CHARS) + _reject_secret_capture((("event content", content), ("event refs", refs))) wid, rid = self._require_scope(workspace, repo) session = self._session_for_write(session_id, wid, rid) if rid is None and session is not None: @@ -3652,6 +3718,13 @@ def _remap_memory_ids_in_text(raw: Any) -> str: ) for m in source_memories: + # This historical row may predate capture-time secret blocking. Never + # replicate it into another workspace through this raw SQL copy path. + _reject_secret_capture((("title", m.get("title")), ("content", m.get("content")), + ("summary", m.get("summary")), + ("keywords", m.get("keywords")), + ("metadata", m.get("metadata")), + ("provenance", m.get("provenance")))) nmid = memory_remap[m["id"]] c.execute( "INSERT INTO memories (id, workspace_id, repo_id, session_id, scope, mtype, " @@ -3811,6 +3884,8 @@ def _remap_memory_ids_in_text(raw: Any) -> str: # 8) Events, cloned with fresh ids. for ev in [dict(x) for x in c.execute( "SELECT * FROM events WHERE workspace_id=?", (wid_src,))]: + _reject_secret_capture((("event content", ev.get("content")), + ("event refs", ev.get("refs")))) c.execute( "INSERT INTO events(id, workspace_id, repo_id, session_id, kind, content, refs, " "interaction_level, ts) VALUES (?,?,?,?,?,?,?,?,?)", @@ -3838,6 +3913,7 @@ def update_memory(self, memory_id: str, *, workspace: str, repo: Optional[str] = sets, params, changes = [], [], [] if title is not None: title = _clean_text(title, field="title", max_chars=MAX_TITLE_CHARS, required=False) + _reject_secret_capture((("title", title),)) sets.append("title=?") params.append(title) changes.append("title") diff --git a/engraphis/static/dashboard.js b/engraphis/static/dashboard.js index b24ab330..93ec0f83 100644 --- a/engraphis/static/dashboard.js +++ b/engraphis/static/dashboard.js @@ -488,7 +488,7 @@ function edPreviewUpdate(){document.getElementById('ed-preview').innerHTML=rende function edRenderMeta(){const m=window.CURMEM;if(!m)return;const btn=document.getElementById('ed-pin-btn');if(btn)btn.textContent=m.pinned?'Unpin':'Pin';document.getElementById('ed-meta').innerHTML=`${esc(m.memory_type)} ${esc(m.scope||'')} ${m.pinned?'pinned':''} ${esc((m.provenance&&m.provenance.source)||'')}${m.provenance&&m.provenance.trusted===false?' · untrusted':''} · id ${esc(m.id)}`} async function edTogglePin(){const m=window.CURMEM;if(!m)return;try{await api('/pin',{method:'POST',headers:{'Content-Type':'application/json'},body:JSON.stringify({id:m.id,workspace:WS,pinned:!m.pinned})});m.pinned=!m.pinned;edRenderMeta();toast(m.pinned?'Pinned':'Unpinned','ok')}catch(e){toast(e.message,'err')}} async function edSave(){const m=window.CURMEM;if(!m)return;const nt=document.getElementById('ed-title').value;const ntype=document.getElementById('ed-type').value;const nc=document.getElementById('ed-content').value;try{let meta=false,body=false,id=m.id;if(nt!==(m.title||'')||ntype!==(m.memory_type||'semantic')){await api('/memory/update',{method:'POST',headers:{'Content-Type':'application/json'},body:JSON.stringify({id:id,workspace:WS,title:nt,memory_type:ntype})});meta=true}if(nc!==(m.content||'')){const r=await api('/correct',{method:'POST',headers:{'Content-Type':'application/json'},body:JSON.stringify({id:id,workspace:WS,content:nc,reason:'dashboard edit'})});body=true;id=r.id}if(!meta&&!body){toast('No changes','ok');return}toast('Saved','ok');await openMem(id)}catch(e){toast(e.message,'err')}} -async function edForget(){const m=window.CURMEM;if(!m)return;if(!await confirmAction('Forget memory','Close the current validity of "'+(m.title||m.id)+'" in workspace "'+(WS||'')+'"? It will stop appearing as current truth but remain in bi-temporal history.','Forget memory',true))return;try{await api('/forget',{method:'POST',headers:{'Content-Type':'application/json'},body:JSON.stringify({id:m.id,workspace:WS,reason:'dashboard'})});toast('Memory closed and retained in history','ok');closeMem()}catch(e){toast(e.message,'err')}} +async function edForget(){const m=window.CURMEM;if(!m)return;if(!await confirmAction('Retire memory','Close the current validity of "'+(m.title||m.id)+'" in workspace "'+(WS||'')+'"? It will stop appearing as current truth but remain in bi-temporal history.','Retire memory',true))return;try{await api('/retire',{method:'POST',headers:{'Content-Type':'application/json'},body:JSON.stringify({id:m.id,workspace:WS,reason:'dashboard retirement'})});toast('Memory retired and retained in history','ok');closeMem()}catch(e){toast(e.message,'err')}} let EDITOR_BASELINE='',EDITOR_FORCE_CLOSE=false; function editorSnapshot(){return JSON.stringify({title:document.getElementById('ed-title').value,type:document.getElementById('ed-type').value,content:document.getElementById('ed-content').value})} function editorIsDirty(){return !!window.CURMEM&&!!EDITOR_BASELINE&&editorSnapshot()!==EDITOR_BASELINE} diff --git a/engraphis/static/index.html b/engraphis/static/index.html index b67ec870..799ecc73 100644 --- a/engraphis/static/index.html +++ b/engraphis/static/index.html @@ -94,7 +94,7 @@ Saved - +
diff --git a/eval/ablation.py b/eval/ablation.py index cb752cf1..51eb71bb 100644 --- a/eval/ablation.py +++ b/eval/ablation.py @@ -14,6 +14,7 @@ from engraphis.backends import DeterministicEmbedder, NumpyVectorIndex from engraphis.backends.reranker import IdentityReranker +from engraphis.core import scoring from engraphis.core.interfaces import Edge, MemoryRecord, MemoryType, Node, Scope, SearchFilter from engraphis.core.recall import RecallEngine from engraphis.core.store import Store @@ -173,12 +174,42 @@ def _arm_recall(dataset: list[dict], *, k: int, arm: str) -> float: return round(sum(per) / max(len(per), 1), 4) +def _ordinary_recall_age_delta() -> float: + """Measure age-only bias in ordinary recall (must remain zero). + + The two records have equal retrieval evidence and equal reinforcement history; + only their validity/ingestion time differs. A non-zero value would show that + query recall is applying fact age in addition to Ebbinghaus retention. + """ + now = 1_000_000.0 + common = dict( + content="same evidence", mtype=MemoryType.SEMANTIC, + stability=4.0, last_access=now - 86_400, importance=0.4, + ) + recent = MemoryRecord(id="recent", ingested_at=now, valid_from=now, **common) + old = MemoryRecord( + id="old", ingested_at=now - 365 * 86_400, + valid_from=now - 365 * 86_400, **common, + ) + weights = scoring.weights_for(MemoryType.SEMANTIC) + return round( + scoring.score_memory(recent, now=now, weights=weights, semantic=0.7) + - scoring.score_memory(old, now=now, weights=weights, semantic=0.7), + 8, + ) + + def main() -> None: ds = load_dataset(str(Path(__file__).resolve().parent / "datasets" / "sample.jsonl")) print("Engraphis ablation — recall@5") print(f" vector-only : {_score(ds, k=5, hybrid=False)}") print(f" hybrid-1hop : {_score(ds, k=5, hybrid=True, graph_mode='1hop')}") print(f" hybrid-ppr : {_score(ds, k=5, hybrid=True, graph_mode='ppr')}") + print("\nEngraphis ordinary-recall age ablation") + print( + " equal-reinforcement score delta (recent - 1y old): " + f"{_ordinary_recall_age_delta():.8f} (expected 0.00000000)" + ) mh_path = Path(__file__).resolve().parent / "datasets" / "graph_multihop.jsonl" if mh_path.exists(): diff --git a/eval/harness.py b/eval/harness.py index 8fa76cb3..bdd8fc12 100644 --- a/eval/harness.py +++ b/eval/harness.py @@ -1,7 +1,7 @@ """Eval runner: ingest fixture memories, query, score retrieval. Routes both ingestion and querying through ``MemoryEngine`` — the same hybrid -vector+lexical+graph recall, six-term scoring, RRF fusion, and deterministic +vector+lexical+graph recall, retention-aware weighted scoring, RRF fusion, and deterministic conflict resolution that ships in production — not a bare vector-index lookup. (Earlier versions of this harness called the vector index directly, which meant the CI gate measured plumbing but never exercised the actual recall pipeline or diff --git a/pyproject.toml b/pyproject.toml index 8aadd918..65157724 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -186,6 +186,7 @@ engraphis-connect = "scripts.connect:main" engraphis-server = "scripts.start_server:main" engraphis-cli = "scripts.cli:main" engraphis-mcp = "engraphis.mcp_cli:main" +engraphis-mcp-http = "engraphis.mcp_http_cli:main" engraphis-inspector = "scripts.inspector:main" engraphis-dashboard = "scripts.start_dashboard:main" engraphis-consolidate = "scripts.consolidate:main" diff --git a/scripts/entry.py b/scripts/entry.py index de9d17c7..8c3b4e07 100644 --- a/scripts/entry.py +++ b/scripts/entry.py @@ -24,6 +24,7 @@ "init": "scripts.init:main", "cli": "scripts.cli:main", "mcp": "engraphis.mcp_cli:main", + "mcp-http": "engraphis.mcp_http_cli:main", "server": "scripts.start_server:main", "dashboard": "scripts.start_dashboard:main", "inspector": "scripts.inspector:main", @@ -40,6 +41,7 @@ init write a project .env and print agent setup snippets cli store and recall memories from the terminal mcp run the MCP server (Claude Code, Cursor, Cline, Zed) + mcp-http run a loopback-only MCP-over-HTTP server server run the v2 REST server without opening a browser (compatibility alias) dashboard run the product dashboard inspector inspect the local database diff --git a/scripts/mcp_server_http.py b/scripts/mcp_server_http.py index d804ef7c..890ecadf 100644 --- a/scripts/mcp_server_http.py +++ b/scripts/mcp_server_http.py @@ -1,45 +1,11 @@ #!/usr/bin/env python3 -"""Persistent Engraphis MCP server (HTTP transport) — single DB owner. +"""Backward-compatible module launcher for ``engraphis-mcp-http``. -Run ONE of these as a long-lived process so every Hermes session (gateway + -CLI) connects as a *client* instead of spawning its own stdio writer. This -removes the multi-writer SQLite WAL lock contention that caused intermittent -`database is locked` errors when more than one Hermes process opened the same -engraphis.db file. - -Usage: - engraphis-mcp-http # or: python -m scripts.mcp_server_http - env ENGRAPHIS_HTTP_PORT=8711 python -m scripts.mcp_server_http - -Transports: - - streamable-http on http://127.0.0.1:/mcp (default) - - set ENGRAPHIS_HTTP_TRANSPORT=sse for /sse instead - -Hermes config then uses: - mcp_servers: - engraphis: - url: http://127.0.0.1:8711/mcp - # or transport: sse + url: http://127.0.0.1:8711/sse +The supported command lives in :mod:`engraphis.mcp_http_cli`. Keeping this module +lets existing source-checkout invocations continue to work without naming or +endorsing a particular MCP client. """ -from __future__ import annotations - -import os - -from engraphis.mcp_server import mcp # reuse the existing tool bindings - -HOST = os.environ.get("ENGRAPHIS_HTTP_HOST", "127.0.0.1") -PORT = int(os.environ.get("ENGRAPHIS_HTTP_PORT", "8711")) -TRANSPORT = os.environ.get("ENGRAPHIS_HTTP_TRANSPORT", "streamable-http") - - -def main() -> None: - # ENGRAPHIS_DB_PATH is read by engraphis.config.settings at service build - # time (lazy, on first tool call) — same path the stdio server used. - # FastMCP reads host/port from its settings object (not run()), so set them - # here. This process is the *sole* writer to engraphis.db. - mcp.settings.host = HOST - mcp.settings.port = PORT - mcp.run(transport=TRANSPORT) +from engraphis.mcp_http_cli import main if __name__ == "__main__": diff --git a/skills/engraphis-memory/SKILL.md b/skills/engraphis-memory/SKILL.md index 6f5c07e6..b3ea14ab 100644 --- a/skills/engraphis-memory/SKILL.md +++ b/skills/engraphis-memory/SKILL.md @@ -1,6 +1,6 @@ --- name: engraphis-memory -description: 'Give the agent durable, scoped, explainable memory across sessions and repositories through the Engraphis MCP tools. Use when you learn a convention, decision, bug cause/fix, or user preference worth keeping; when prior context would help before you answer or act (to avoid re-asking or re-deriving); when asked "why is it like this" or "how has this changed over time"; or when starting or resuming work in a repo. Triggers: remember, recall, "what do we know about X", why/rationale, timeline/history, forget/pin/correct, session handoff, index/search code.' +description: 'Give the agent durable, scoped, explainable memory across sessions and repositories through the Engraphis MCP tools. Use when you learn a convention, decision, bug cause/fix, or user preference worth keeping; when prior context would help before you answer or act (to avoid re-asking or re-deriving); when asked "why is it like this" or "how has this changed over time"; or when starting or resuming work in a repo. Triggers: remember, recall, "what do we know about X", why/rationale, timeline/history, retire/pin/correct, session handoff, index/search code.' --- # Engraphis Memory @@ -8,7 +8,7 @@ description: 'Give the agent durable, scoped, explainable memory across sessions Engraphis is a local-first memory engine exposed to agents over MCP. This skill is the *discipline* for using it well: what to store, how to scope it, and which tool answers which question. It assumes the Engraphis MCP server is connected, so tools are named `engraphis_*` -(31 of them). If those tools are absent, see [Setup](#setup). Do not fall back to ad-hoc notes. +(33 of them). If those tools are absent, see [Setup](#setup). Do not fall back to ad-hoc notes. Memory here is **scoped, typed, bi-temporal, and self-maintaining**: writes are deduplicated and contradictions supersede (never silently overwrite), and forgetting lowers priority instead of @@ -70,7 +70,8 @@ promotion: [SCOPING.md](references/SCOPING.md). | Load context, no query | `engraphis_recall_proactive` | Start-of-task; authenticated callers receive only their own last-session handoff. | | "Why is it like this?" | `engraphis_why` | Live answer **plus** what it superseded (bi-temporal). | | "How has X changed?" | `engraphis_timeline` | Every version oldest→newest with `valid_from/valid_to`. | -| Retire a stale memory | `engraphis_forget` | Bi-temporal close, not a delete. Prefer `correct` if you have a replacement. | +| Retire a stale memory | `engraphis_retire` | Bi-temporal close, not a delete. Prefer `correct` if you have a replacement. | +| Erase a leaked credential | `engraphis_secure_erase` | Destructive local remediation; rotate the secret and handle external copies separately. | | Fix a memory's content | `engraphis_correct` | Closes old + stores replacement that records what it fixed; keeps the *why* chain. | | Widen a memory's scope | `engraphis_promote` | Session→repo/workspace or repo→workspace; preserves and links narrow history. | | Protect from decay | `engraphis_pin` | For identity/durable facts that must never fade. | @@ -151,6 +152,6 @@ is needed for the memory layer. Details: the repo `README.md` "Quickstart A: MCP ## References -- [TOOLS.md](references/TOOLS.md): all 31 tools: parameters, defaults, returns, when to reach for each. +- [TOOLS.md](references/TOOLS.md): all 33 tools: parameters, defaults, returns, when to reach for each. - [SCOPING.md](references/SCOPING.md): the `workspace → repo → session → memory` model, scope vs. type, and promotion. - [CONVENTIONS.md](references/CONVENTIONS.md): memory types, provenance, importance, dedup/resolution, governance, and anti-patterns diff --git a/skills/engraphis-memory/references/CONVENTIONS.md b/skills/engraphis-memory/references/CONVENTIONS.md index 52376b13..4884d43e 100644 --- a/skills/engraphis-memory/references/CONVENTIONS.md +++ b/skills/engraphis-memory/references/CONVENTIONS.md @@ -63,7 +63,7 @@ There is no destructive edit. When a fact changes: When the change became true at a known time, pass `valid_from=`; the old validity window closes at that effective time, not at ingestion time. - Fixing wrong content → `engraphis_correct` (closes old, stores a replacement that records what it - fixed). Preferred over forget-then-remember because it keeps the *why* chain intact. + fixed). Preferred over retire-then-remember because it keeps the *why* chain intact. Afterwards, `engraphis_why` and `engraphis_timeline` can still reconstruct "we used to do X, then switched to Y because Z". For relevance-ranked time travel, use `valid_at=` for @@ -73,7 +73,7 @@ what was true and `known_at=` for what Engraphis had learned; `a ## Governance: retire, don't delete -- `engraphis_forget`: retire an obsolete memory with no replacement. It stops surfacing but is +- `engraphis_retire`: retire an obsolete memory with no replacement. It stops surfacing but is preserved (bi-temporal close) and audited. Give a `reason`. - `engraphis_correct`: fix content while keeping history (see above). - `engraphis_pin`: protect from decay. diff --git a/skills/engraphis-memory/references/TOOLS.md b/skills/engraphis-memory/references/TOOLS.md index 750783c8..c673adc9 100644 --- a/skills/engraphis-memory/references/TOOLS.md +++ b/skills/engraphis-memory/references/TOOLS.md @@ -1,8 +1,8 @@ # Engraphis MCP tools: reference -All 31 tools, grouped by job. Parameters are `name (type, default)`: no default means required. +All 33 tools, grouped by job. Parameters are `name (type, default)`: no default means required. Every tool returns a JSON string; on failure it returns `"Error: "` instead of raising. -Governance tools (`forget`/`pin`/`correct`/`link`) verify the memory actually belongs to the +Governance tools (`retire`/`pin`/`correct`/`link`) verify the memory actually belongs to the `workspace`/`repo` you pass **before** changing anything, so you can't touch memories outside a scope you were already given. @@ -200,14 +200,31 @@ as a new memory that records what it corrected, so the audit trail and `engraphi - `memory_id (str)`, `new_content (str)`, `workspace (str)`, `repo (str, None)`, `reason (str, "")`. -Returns `{id, superseded:[old_id], reason}`. Prefer this over forget-then-remember. +Returns `{id, superseded:[old_id], reason}`. Prefer this over retire-then-remember. -### `engraphis_forget` +### `engraphis_retire` Retire a memory: it stops appearing in recall, history preserved. - `memory_id (str)`, `workspace (str)`, `repo (str, None)`, `reason (str, "")`. -Returns `{id, status:"forgotten", reason}`. Use `correct` instead when you have replacement content. +Returns `{id, status:"retired", reason}`. Use `correct` instead when you have replacement content. + +### `engraphis_secure_erase` +Irreversibly remove one accidentally stored credential from local persistence. It deletes the +memory plus its local FTS/vector/ANN and derived graph/link rows, performs SQLite secure-delete, +WAL checkpoint, and VACUUM, and scans recognised local SQLite recovery backups. It cannot erase +exports, snapshots, remote peers, unknown backups, or content already read by an agent; rotate the +credential. This is destructive and intentionally does not preserve history. + +- `memory_id (str)`, `workspace (str)`, `repo (str, None)`. + +Returns `{id, status:"securely_erased", maintenance, recognised_backups_erased, +backup_limitations}`. The `vector_index_cleanup` result must be `deleted` before an injected +external vector backend can be considered remediated. + +### `engraphis_forget` *(deprecated)* +Compatibility alias for `engraphis_retire`. It retains the old `status:"forgotten"` result for +existing clients, but new integrations must use `engraphis_retire`. ### `engraphis_promote` Widen a live memory's visibility without editing it in place. The wider record is stored first; @@ -424,7 +441,7 @@ Returns `{enabled, current, latest, update_available, url, notice}`. `recall`. Need raw context and don't yet → `recall_proactive`. Need a task-ready packet → `proactive_context`. - "Why?" / "since when?" → `why` / `timeline`, not `recall`, which only sees the live view. -- Fact is wrong → `correct` (keeps the chain). Fact is obsolete with no replacement → `forget`. +- Fact is wrong → `correct` (keeps the chain). Fact is obsolete with no replacement → `retire`. - Fact applies more broadly than first believed → `promote` (widens without duplicate recall). - Must never fade → `pin`. Two facts belong together → `link`. - Working in code → `index_repo`, then `search_code`; use `code_path`/`code_impact` for structural diff --git a/tests/test_benchmark_evidence.py b/tests/test_benchmark_evidence.py index 6b56a4ca..089cc3de 100644 --- a/tests/test_benchmark_evidence.py +++ b/tests/test_benchmark_evidence.py @@ -87,7 +87,7 @@ def test_readme_distinguishes_every_current_token_context_measurement(): for evidence in ( "## Measured token and context savings", "98.21 percent less long-history context", - "73.0 percent less retrieved content per question", + "71.1 percent less retrieved content per question", "73.9 percent fewer tokens in the smallest useful memory", "55.38 percent smaller memory response", "47.8 percent less repeated-memory context after consolidation", @@ -95,8 +95,8 @@ def test_readme_distinguishes_every_current_token_context_measurement(): "### Measurement details and reproducibility", "49,915,394** tokens → Engraphis: **891,857** tokens", "98.2133% lower", - "808.8** tokens → structure-aware chunks: **218.4** tokens", - "73.0% lower", + "740.3** tokens → structure-aware chunks: **214.1** tokens", + "71.1% lower", "162.2** tokens → chunks: **42.4** tokens", "73.9% lower", "17,172** `engraphis.regex.v1` tokens → compact result: **7,663** tokens", @@ -149,9 +149,9 @@ def test_readme_makes_agent_benefits_and_visual_evidence_scannable(): "Avoid confident guesses", "Avoid dragging the whole project into every prompt", "docs/images/engraphis-benefit-flow.png", - "docs/images/context-efficiency.png", + "docs/images/context-efficiency.svg", "### See the behavior in reproducible fixtures", - "docs/images/evidence-backed-agent-examples.png", + "docs/images/evidence-backed-agent-examples.svg", "Run `python -m eval.chunking_eval` and `python -m eval.grounded`", "Less repeated history means more room for the task, tools, and useful evidence", ): @@ -196,7 +196,7 @@ def test_example_visual_uses_the_checked_in_offline_fixture_results(): encoding="utf-8" ) - assert chunking["context_reduction_pct"] == 73.0 + assert chunking["context_reduction_pct"] == 71.1 assert f"{whole['mean_context_tokens']:.1f} → {chunked['mean_context_tokens']:.1f} tokens" in visual assert grounded == { "answer_rate": 1.0, @@ -223,9 +223,9 @@ def test_context_savings_visual_is_plain_language_and_uses_measured_results(): "Engraphis · 891,857 tokens", "98.21% less", "Focused context; full-history recall was higher", - "Whole documents · 808.8 tokens", - "Focused chunks · 218.4 tokens", - "73.0% less", + "Whole documents · 740.3 tokens", + "Focused chunks · 214.1 tokens", + "71.1% less", "Whole document · 162.2 tokens", "Useful chunk · 42.4 tokens", "73.9% less", diff --git a/tests/test_cloud_features.py b/tests/test_cloud_features.py index f8cb387f..f2e00aab 100644 --- a/tests/test_cloud_features.py +++ b/tests/test_cloud_features.py @@ -1,6 +1,7 @@ from __future__ import annotations import threading +import json from concurrent.futures import ThreadPoolExecutor import http.client from io import BytesIO @@ -24,12 +25,15 @@ def _service() -> MemoryService: service.remember( "A normal managed-compute memory.", workspace="acme", - metadata={"subject": " Queue design ", "api_key": "metadata-secret"}, + metadata={"subject": " Queue design "}, ) - secret = service.remember("password=do-not-upload", workspace="acme") + # Seed historical rows below the new capture-time boundary. These verify cloud + # export filtering for legacy data without weakening the public write API. + secret = service.remember("A legacy private value.", workspace="acme") service.store.conn.execute( - "UPDATE memories SET sensitivity='secret' WHERE id=?", - (secret["id"],), + "UPDATE memories SET metadata=?, content=?, sensitivity='secret' WHERE id=?", + (json.dumps({"subject": "Queue design", "api_key": "metadata-secret"}), + "password=do-not-upload", secret["id"]), ) service.store.conn.commit() return service diff --git a/tests/test_context_economy.py b/tests/test_context_economy.py index e94a8cdc..34a0d756 100644 --- a/tests/test_context_economy.py +++ b/tests/test_context_economy.py @@ -229,7 +229,7 @@ def fake_get_embedder(model_name, dim): assert output["benchmark"]["embedder"]["dimension"] == 80 -def test_codemem_public_no_break_even_boundary_is_reproducible() -> None: +def test_codemem_public_break_even_baseline_is_reproducible() -> None: dataset = load_dataset(str(ROOT / "eval" / "datasets" / "codemem.jsonl")) tight = run(dataset, token_budget=64, k=5) @@ -243,8 +243,8 @@ def test_codemem_public_no_break_even_boundary_is_reproducible() -> None: } assert tight["methods"]["full_history"]["cumulative_query_context_tokens"] == 1180 assert tight["methods"]["recency_window"]["cumulative_query_context_tokens"] == 1180 - assert tight["methods"]["engraphis"]["cumulative_query_context_tokens"] == 1375 - assert roomy["methods"]["engraphis"]["cumulative_query_context_tokens"] == 1377 + assert tight["methods"]["engraphis"]["cumulative_query_context_tokens"] == 1064 + assert roomy["methods"]["engraphis"]["cumulative_query_context_tokens"] == 1066 for report in (tight, roomy): for method in report["methods"].values(): assert method["quality"] == { @@ -252,4 +252,5 @@ def test_codemem_public_no_break_even_boundary_is_reproducible() -> None: "retrieval_hit_rate": 1.0, "answer_token_recall": 1.0, } - assert report["engraphis_vs_full_history"]["break_even_query_count"] is None + assert tight["engraphis_vs_full_history"]["break_even_query_count"] == 142 + assert roomy["engraphis_vs_full_history"]["break_even_query_count"] == 144 diff --git a/tests/test_embeddings.py b/tests/test_embeddings.py index ef4b4ff2..e30a1cb9 100644 --- a/tests/test_embeddings.py +++ b/tests/test_embeddings.py @@ -34,6 +34,13 @@ def test_embedding_remains_deterministic_and_normalized(): np.testing.assert_allclose(np.linalg.norm(first, axis=1), [1.0, 1.0]) +def test_deterministic_embedder_explicitly_disables_semantic_search(): + embedder = DeterministicEmbedder() + + assert embedder.embedding_mode == "lexical_hashing" + assert embedder.supports_semantic_search is False + + def test_unrecognized_ordinary_text_keeps_legacy_feature_mapping(): # No alias or number-unit feature is present in this input, so the old # stable feature-hash mapping remains byte-for-byte compatible. diff --git a/tests/test_eval_ablation.py b/tests/test_eval_ablation.py index fb4a5ba5..65296c9c 100644 --- a/tests/test_eval_ablation.py +++ b/tests/test_eval_ablation.py @@ -1,6 +1,6 @@ from pathlib import Path -from eval.ablation import _arm_recall, _score +from eval.ablation import _arm_recall, _ordinary_recall_age_delta, _score from eval.harness import load_dataset @@ -11,8 +11,6 @@ def test_multihop_ablation_distinguishes_ppr_from_one_hop(): assert _arm_recall(dataset, k=5, arm="graph1hop") == 0.0 assert _arm_recall(dataset, k=5, arm="graphppr") == 1.0 - - def test_hybrid_ablation_requests_inspection_visibility_for_raw_fixture_rows(): dataset = load_dataset( str(Path(__file__).resolve().parents[1] / "eval" / "datasets" / "sample.jsonl") @@ -21,3 +19,7 @@ def test_hybrid_ablation_requests_inspection_visibility_for_raw_fixture_rows(): # eval.ablation seeds Store directly, which intentionally lacks prompt approval # metadata. The ablation must measure retrieval, not prompt-context eligibility. assert _score(dataset, k=5, hybrid=True, graph_mode="ppr") == 1.0 + + +def test_ordinary_recall_age_ablation_has_no_second_age_penalty(): + assert _ordinary_recall_age_delta() == 0.0 diff --git a/tests/test_grounded.py b/tests/test_grounded.py index 22961784..a11938cf 100644 --- a/tests/test_grounded.py +++ b/tests/test_grounded.py @@ -7,8 +7,9 @@ """ import pytest +from engraphis.backends.embedder_deterministic import DeterministicEmbedder from engraphis.core.engine import MemoryEngine -from engraphis.core.grounded import ABSTAIN_SENTINEL, GROUNDED_SUPPORT_FLOOR +from engraphis.core.grounded import ABSTAIN_SENTINEL, GROUNDED_SUPPORT_FLOOR, support_scores from engraphis.service import MemoryService, ValidationError FACTS = [ @@ -76,6 +77,33 @@ def test_grounded_abstains_on_empty_store(): assert not ans.grounded and ans.answer == "" and ans.citations == [] +def test_grounded_support_fails_closed_for_an_undeclared_vector_adapter(): + class UndeclaredVectorAdapter: + def embed(self, texts, **kwargs): + raise AssertionError("semantic embedding must not run") + + assert support_scores("package manager", ["package manager"], UndeclaredVectorAdapter()) == [1.0] + + +def test_grounded_support_uses_a_declared_semantic_adapter(): + class DeclaredSemanticAdapter(DeterministicEmbedder): + supports_semantic_search = True + embedding_mode = "semantic" + + def __init__(self): + super().__init__() + self.calls = 0 + + def embed(self, texts, **kwargs): + self.calls += 1 + return super().embed(texts, **kwargs) + + embedder = DeclaredSemanticAdapter() + support_scores("package manager", ["package manager"], embedder) + + assert embedder.calls == 1 + + def test_grounded_cites_only_supporting_sources(): eng, wid, rid = _engine_with_facts() ans = eng.grounded_recall("which auth scheme did we standardise on?", diff --git a/tests/test_inspector.py b/tests/test_inspector.py index 6ed247f0..cbc61dd5 100644 --- a/tests/test_inspector.py +++ b/tests/test_inspector.py @@ -123,12 +123,14 @@ def test_why_supersedes_and_timeline_endpoints(client): assert len(tl["history"]) == 2 -def test_governance_endpoints_pin_and_forget(client): +def test_governance_endpoints_pin_retire_and_legacy_forget_alias(client): c, out = client body = {"memory_id": out["id"], "workspace": "acme", "repo": "backend"} assert c.post("/api/pin", json=body).json()["pinned"] is True - r = c.post("/api/forget", json={**body, "reason": "test"}).json() - assert r["status"] == "forgotten" + r = c.post("/api/retire", json={**body, "reason": "test"}).json() + assert r["status"] == "retired" + alias = c.post("/api/forget", json={**body, "reason": "legacy"}).json() + assert alias["status"] == "forgotten" and alias["deprecated"] is True assert c.get("/api/stats", params={"workspace": "acme"}).json()["memories"] == 0 diff --git a/tests/test_mcp_server.py b/tests/test_mcp_server.py index 9972519b..912da5cc 100644 --- a/tests/test_mcp_server.py +++ b/tests/test_mcp_server.py @@ -64,7 +64,8 @@ def _recall_side_effect_snapshot(srv): _ALL_TOOLS = { "engraphis_remember", "engraphis_recall", "engraphis_recall_context", "engraphis_why", "engraphis_timeline", - "engraphis_recall_proactive", "engraphis_forget", "engraphis_pin", "engraphis_correct", + "engraphis_recall_proactive", "engraphis_retire", "engraphis_forget", + "engraphis_secure_erase", "engraphis_pin", "engraphis_correct", "engraphis_promote", "engraphis_link", "engraphis_record_event", "engraphis_index_repo", "engraphis_search_code", "engraphis_code_path", "engraphis_code_impact", "engraphis_export_code_graph", "engraphis_start_session", "engraphis_end_session", @@ -89,11 +90,11 @@ def test_server_identity_and_tools_registered(): assert "engraphis_end_session" in srv.mcp.instructions assert "open_threads=[]" in srv.mcp.instructions tools = {t.name: t for t in asyncio.run(srv.mcp.list_tools())} - assert len(_ALL_TOOLS) == 31 + assert len(_ALL_TOOLS) == 33 assert set(tools) == _ALL_TOOLS assert srv.minimum_role("engraphis_context_savings") == "viewer" kilo = (ROOT / "docs" / "KILO_CODE_INTEGRATION.md").read_text(encoding="utf-8") - full_surface = kilo.split("## 4. The 31 tools", 1)[1].split("\n---", 1)[0] + full_surface = kilo.split("## 4. The 33 tools", 1)[1].split("\n---", 1)[0] assert set(re.findall(r"`(engraphis_[a-z_]+)`", full_surface)) == _ALL_TOOLS # Flat schema (not a nested "params" object) so agents can call fields directly. props = tools["engraphis_remember"].inputSchema.get("properties", {}) @@ -259,6 +260,9 @@ def test_remember_and_recall_tool_callables(monkeypatch): assert memory["score"] == memory["relative_score"] assert 0.0 <= memory["absolute_support"] <= 1.0 assert "Query-relative" in rec["score_semantics"]["relative_score"] + assert rec["degraded_mode"] is True + assert rec["semantic_support"] is False + assert rec["embedding_mode"] == "lexical_hashing" def test_mcp_external_provenance_cannot_be_forged_to_trusted(monkeypatch): @@ -385,6 +389,9 @@ def test_grounded_recall_tool_returns_flat_answer_payload(monkeypatch): assert out["query"] == "Which auth tokens does the API use?" assert out["grounded"] is True assert out["abstained"] is False + assert out["degraded_mode"] is True + assert out["semantic_support"] is False + assert out["embedding_mode"] == "lexical_hashing" assert "PASETO" in out["answer"] assert out["citations"] @@ -525,9 +532,13 @@ def test_governance_tools_forget_pin_correct(monkeypatch): workspace="acme", reason="typo")) assert corrected["superseded"] == [out["id"]] - forgotten = json.loads(srv.engraphis_forget(memory_id=corrected["id"], workspace="acme", - reason="no longer needed")) - assert forgotten["status"] == "forgotten" + retired = json.loads(srv.engraphis_retire(memory_id=corrected["id"], workspace="acme", + reason="no longer needed")) + assert retired["status"] == "retired" + + alias = json.loads(srv.engraphis_forget(memory_id=corrected["id"], workspace="acme", + reason="legacy retry")) + assert alias["status"] == "forgotten" and alias["deprecated"] is True err = srv.engraphis_forget(memory_id="mem_does_not_exist", workspace="acme") assert err.startswith("Error:") diff --git a/tests/test_packaging.py b/tests/test_packaging.py index bffb170e..4c4a8c4e 100644 --- a/tests/test_packaging.py +++ b/tests/test_packaging.py @@ -4,6 +4,7 @@ import subprocess import sys import tarfile +import types import zipfile from pathlib import Path @@ -34,6 +35,59 @@ def test_mcp_cli_module_entrypoint_renders_help(): assert "Run the Engraphis MCP server over stdio" in result.stdout +def test_http_mcp_cli_module_entrypoint_renders_help(): + result = subprocess.run( + [sys.executable, "-m", "engraphis.mcp_http_cli", "--help"], + cwd=ROOT, + text=True, + capture_output=True, + timeout=15, + check=False, + ) + + assert result.returncode == 0, result.stderr + assert "usage: engraphis-mcp-http" in result.stdout + assert "loopback-only Engraphis MCP server over HTTP" in result.stdout + + +def test_http_mcp_cli_rejects_non_loopback_host(): + from engraphis import mcp_http_cli + + for host in ("0.0.0.0", "localhost"): + with pytest.raises(SystemExit) as exc: + mcp_http_cli.main(["--host", host]) + + assert exc.value.code == 2 + + +def test_http_mcp_cli_configures_the_packaged_transport(monkeypatch): + from engraphis import mcp_http_cli + + calls = [] + fake_mcp = types.SimpleNamespace( + settings=types.SimpleNamespace(host=None, port=None), + run=lambda *, transport: calls.append(transport), + ) + monkeypatch.setattr(mcp_http_cli, "_dependency_error", lambda: "") + monkeypatch.setitem(sys.modules, "engraphis.mcp_server", types.SimpleNamespace(mcp=fake_mcp)) + + mcp_http_cli.main(["--host", "::1", "--port", "9876", "--transport", "sse"]) + + assert fake_mcp.settings.host == "::1" + assert fake_mcp.settings.port == 9876 + assert calls == ["sse"] + + +def test_http_mcp_console_entrypoint_is_packaged_and_client_neutral(): + pyproject = (ROOT / "pyproject.toml").read_text(encoding="utf-8") + agent_connect = (ROOT / "docs" / "AGENT_CONNECT.md").read_text(encoding="utf-8") + launcher = (ROOT / "scripts" / "mcp_server_http.py").read_text(encoding="utf-8") + + assert 'engraphis-mcp-http = "engraphis.mcp_http_cli:main"' in pyproject + assert "engraphis-mcp-http" in agent_connect + assert "Hermes" not in agent_connect + launcher + + def test_git_plugin_release_version_and_asset_hashes_are_exact(): pyproject = (ROOT / "pyproject.toml").read_text(encoding="utf-8") declared = re.search(r'^version = "([^"]+)"', pyproject, re.M) diff --git a/tests/test_productivity_eval.py b/tests/test_productivity_eval.py index e6ff09f9..66003aa1 100644 --- a/tests/test_productivity_eval.py +++ b/tests/test_productivity_eval.py @@ -294,7 +294,7 @@ def test_cli_prints_aggregate_report_without_private_task_or_source_data( assert "PRIVATE-SOURCE" not in output -def test_codemem_small_history_bypass_marketing_numbers_are_reproducible() -> None: +def test_codemem_small_history_strategy_baseline_is_reproducible() -> None: report = run( load_dataset(str(ROOT / "eval" / "datasets" / "codemem.jsonl")), max_context_tokens=512, @@ -305,7 +305,7 @@ def test_codemem_small_history_bypass_marketing_numbers_are_reproducible() -> No assert report["methods"]["full_history"]["tasks_completed"] == 24 assert report["methods"]["full_history"]["total_tokens"] == 1942 assert report["methods"]["retrieval"]["tasks_completed"] == 24 - assert report["methods"]["retrieval"]["total_tokens"] == 2194 + assert report["methods"]["retrieval"]["total_tokens"] == 1883 assert report["methods"]["retrieval"]["memory_calls"] == 26 assert report["methods"]["adaptive"]["tasks_completed"] == 24 assert report["methods"]["adaptive"]["total_tokens"] == 1942 diff --git a/tests/test_recall.py b/tests/test_recall.py index 84152753..7544e0bb 100644 --- a/tests/test_recall.py +++ b/tests/test_recall.py @@ -6,6 +6,13 @@ from engraphis.core.store import Store +class _SemanticTestEmbedder(DeterministicEmbedder): + """Test double that opts into vector semantics without a model download.""" + + supports_semantic_search = True + embedding_mode = "semantic" + + def _engine(): store = Store(":memory:") emb = DeterministicEmbedder(256) @@ -49,6 +56,17 @@ def search(self, query, k, *, filter=None): return super().search(query, k, filter=filter) +class _FailingIndex: + """Proves degraded recall never reaches the semantic vector backend.""" + + def __init__(self): + self.calls = 0 + + def search(self, query, k, *, filter=None): + self.calls += 1 + raise AssertionError("degraded recall must not query the vector index") + + def test_recall_returns_relevant_first(): store, emb, eng = _engine() wid = store.get_or_create_workspace("w") @@ -60,6 +78,39 @@ def test_recall_returns_relevant_first(): assert "pnpm" in res.context.lower() +def test_degraded_recall_skips_vector_arm_and_uses_lexical_fallback(): + store = Store(":memory:") + emb = DeterministicEmbedder(256) + index = _FailingIndex() + eng = RecallEngine(store, emb, index, IdentityReranker()) + wid = store.get_or_create_workspace("w") + _add(store, emb, wid, None, "pnpm is the package manager for frontend projects.") + + result = eng.recall( + "package manager", SearchFilter(workspace_id=wid), k=1, diagnostics=True, + ) + + assert index.calls == 0 + assert result.degraded_mode is True + assert result.semantic_support is False + assert result.chunks[0]["arm"] == "lexical" + assert result.retrieval_trace[0]["raw"]["semantic"] is None + + +def test_degraded_recall_uses_inflection_aware_like_fallback_without_fts5(): + store = Store(":memory:") + store.has_fts5 = False + emb = DeterministicEmbedder(256) + eng = RecallEngine(store, emb, _FailingIndex(), IdentityReranker()) + wid = store.get_or_create_workspace("w") + _add(store, emb, wid, None, "The service authenticates API requests with PASETO.") + + result = eng.recall("authentication", SearchFilter(workspace_id=wid), k=1) + + assert result.count == 1 + assert "paseto" in result.context.lower() + + def test_lexical_absolute_support_does_not_allow_title_only_evidence(): store, emb, eng = _engine() wid = store.get_or_create_workspace("w") @@ -93,7 +144,7 @@ def test_absolute_support_treats_non_finite_cosine_as_no_evidence(): def test_prompt_only_recall_continues_past_untrusted_arm_candidates(): store = Store(":memory:") - emb = DeterministicEmbedder(256) + emb = _SemanticTestEmbedder(256) wid = store.get_or_create_workspace("w") rid = store.get_or_create_repo(wid, "r") untrusted_ids = [ @@ -180,7 +231,12 @@ def test_graph_arm_pulls_related_via_entities(): workspace_id=wid, repo_id=rid)) store.upsert_edge(Edge(id="", src=redis, dst=checkout, relation="used_by", workspace_id=wid, repo_id=rid)) - _add(store, emb, wid, rid, "The checkout service had a race condition.") + checkout_memory = _add(store, emb, wid, rid, "The checkout service had a race condition.") + store.link_memory_entity( + memory_id=checkout_memory, + entity_id=checkout, workspace_id=wid, repo_id=rid, + source_kind="test", confidence=1.0, + ) _add(store, emb, wid, rid, "Totally unrelated note about office plants.") # Query mentions Redis; graph arm should surface the checkout memory. res = eng.recall("how does Redis relate to things?", SearchFilter(workspace_id=wid), k=3) @@ -445,7 +501,7 @@ def test_lexical_recall_is_filtered_before_candidate_limit(): def test_prompt_overfetch_never_reduces_the_requested_candidate_depth(): store = Store(":memory:") - emb = DeterministicEmbedder(256) + emb = _SemanticTestEmbedder(256) index = NumpyVectorIndex(store) requested: list[int] = [] original_search = index.search @@ -473,7 +529,7 @@ def recording_search(query, k, filter=None): def test_prompt_only_overfetch_stays_bounded_for_large_untrusted_scopes(): store = Store(":memory:") - emb = DeterministicEmbedder(256) + emb = _SemanticTestEmbedder(256) wid = store.get_or_create_workspace("w") untrusted_ids = [ _add( diff --git a/tests/test_release_infrastructure.py b/tests/test_release_infrastructure.py index ef6f99ee..4c6bdeed 100644 --- a/tests/test_release_infrastructure.py +++ b/tests/test_release_infrastructure.py @@ -308,7 +308,7 @@ def test_primary_github_release_targets_repository_without_checkout(): def test_public_capability_and_support_docs_match_the_shipped_tree(): server = _text("engraphis/mcp_server.py") tools = re.findall(r'@mcp\.tool\(\s*name="(engraphis_[^"]+)"', server) - assert len(tools) == len(set(tools)) == 31 + assert len(tools) == len(set(tools)) == 33 readme = _text("README.md") architecture = _text("docs/ARCHITECTURE_V3.md") @@ -319,8 +319,8 @@ def test_public_capability_and_support_docs_match_the_shipped_tree(): assert "28 MCP tools" not in content assert "28-tool" not in content assert "(28 of them)" not in content - assert "31 MCP tools" in architecture - assert "(31 of them)" in skill + assert "33 MCP tools" in architecture + assert "(33 of them)" in skill assert "recall_context (compact)" in architecture assert "engraphis_recall_context" in readme assert "`engraphis_check_update`" in readme diff --git a/tests/test_scoring.py b/tests/test_scoring.py index 3862e633..06871769 100644 --- a/tests/test_scoring.py +++ b/tests/test_scoring.py @@ -47,6 +47,25 @@ def test_score_rewards_semantic_penalizes_stale(): assert scoring.score_memory(stale, now=now, weights=w, semantic=1.0) < hi +def test_ordinary_recall_does_not_double_weight_fact_age(): + """Validity/ingestion age is not a second decay curve in query recall.""" + now = 1_000_000.0 + w = scoring.weights_for(MemoryType.SEMANTIC) + shared = dict( + content="same evidence", mtype=MemoryType.SEMANTIC, last_access=now - 86_400, + stability=4.0, importance=0.4, + ) + new = MemoryRecord(id="new", ingested_at=now, valid_from=now, **shared) + old = MemoryRecord( + id="old", ingested_at=now - 365 * 86_400, + valid_from=now - 365 * 86_400, + **shared, + ) + assert scoring.score_memory(new, now=now, weights=w, semantic=0.7) == ( + scoring.score_memory(old, now=now, weights=w, semantic=0.7) + ) + + def test_per_type_weight_profiles_differ(): assert scoring.weights_for(MemoryType.WORKING).c > scoring.weights_for(MemoryType.SEMANTIC).c assert scoring.weights_for(MemoryType.PROCEDURAL).i > scoring.weights_for(MemoryType.WORKING).i diff --git a/tests/test_secret_hygiene.py b/tests/test_secret_hygiene.py new file mode 100644 index 00000000..346cb08d --- /dev/null +++ b/tests/test_secret_hygiene.py @@ -0,0 +1,157 @@ +"""Regression tests for capture-time secret blocking and breach remediation.""" +from __future__ import annotations + +import json + +import pytest + +from engraphis.core.engine import MemoryEngine +from engraphis.core.interfaces import ExtractedFact, MemoryRecord, MemoryType, Scope +from engraphis.core.secrets import SecretDetectedError, secret_kind +from engraphis.core.store import Store +from engraphis.service import MemoryService, ValidationError + + +_LEAK = "sk-proj-0123456789ABCDEFGHIJKLMNOPQRSTUVWXYZ" + + +def test_secret_key_matching_does_not_block_nonsecret_token_metadata(): + assert secret_kind({"chunking": {"token_counter": "regex_v1"}}) is None + + +def test_service_and_store_block_credentials_before_any_memory_index_write(): + service = MemoryService.create(":memory:") + with pytest.raises(ValidationError, match="potential OpenAI API key"): + service.remember(f"Provider key is {_LEAK}", workspace="acme") + + # The rejection occurs before a workspace, memory, FTS row, or vector exists. + assert service.store.conn.execute("SELECT COUNT(*) FROM memories").fetchone()[0] == 0 + assert service.store.conn.execute("SELECT COUNT(*) FROM mem_fts").fetchone()[0] == 0 + assert service.store.conn.execute("SELECT COUNT(*) FROM mem_vectors").fetchone()[0] == 0 + + with pytest.raises(ValidationError, match="credential assignment"): + service.remember("Metadata boundary test.", workspace="acme", + metadata={"api_key": "metadata-secret"}) + assert service.store.conn.execute("SELECT COUNT(*) FROM memories").fetchone()[0] == 0 + + with pytest.raises(ValidationError, match="bearer token"): + service.remember("Authorization: Bearer abcdefghijklmnopqrstuvwxyz", workspace="acme") + with pytest.raises(ValidationError, match="credential assignment"): + service.remember("Token boundary test.", workspace="acme", + metadata={"token": "0123456789abcdef"}) + assert service.store.conn.execute("SELECT COUNT(*) FROM memories").fetchone()[0] == 0 + + for field, value, expected in ( + ("AWS_SECRET_ACCESS_KEY", "0123456789abcdef", "credential assignment"), + ("TOKEN", "0123456789abcdef", "credential assignment"), + ): + with pytest.raises(ValidationError, match=expected): + service.remember("Environment boundary test.", workspace="acme", + metadata={field: value}) + with pytest.raises(ValidationError, match="credential-bearing connection URI"): + service.remember("postgresql://agent:0123456789abcdef@db.example/app", + workspace="acme") + assert service.store.conn.execute("SELECT COUNT(*) FROM memories").fetchone()[0] == 0 + + store = Store(":memory:") + with pytest.raises(SecretDetectedError, match="credential assignment"): + store.add_memory(MemoryRecord( + id="", workspace_id="ws_direct", content="api_key=0123456789abcdef", + mtype=MemoryType.SEMANTIC, scope=Scope.WORKSPACE, + )) + assert store.conn.execute("SELECT COUNT(*) FROM memories").fetchone()[0] == 0 + + +def test_direct_engine_ingest_rejects_before_optional_extractor_runs(): + class RecordingExtractor: + called = False + + def extract(self, text: str): + self.called = True + return [ExtractedFact(content="derived safe-looking fact")] + + engine = MemoryEngine.create(":memory:") + extractor = RecordingExtractor() + engine.extractor = extractor + workspace = engine.store.get_or_create_workspace("acme") + + with pytest.raises(SecretDetectedError, match="OpenAI API key"): + engine.ingest(f"raw transcript contains {_LEAK}", workspace_id=workspace) + + assert extractor.called is False + assert engine.store.count_memories() == 0 + assert engine.store.conn.execute("SELECT COUNT(*) FROM mem_fts").fetchone()[0] == 0 + + +def test_retire_is_canonical_and_forget_remains_a_compatibility_alias(): + service = MemoryService.create(":memory:") + first = service.remember("A safely stored, stale fact.", workspace="acme") + retired = service.retire(first["id"], workspace="acme", reason="obsolete") + assert retired["status"] == "retired" + assert service.store.get_memory(first["id"]) is not None + assert service.recall("stale fact", workspace="acme")["count"] == 0 + + second = service.remember("Another safely stored fact.", workspace="acme") + legacy = service.forget(second["id"], workspace="acme") + assert legacy["status"] == "forgotten" + assert legacy["deprecated"] is True + assert service.store.get_memory(second["id"]) is not None + + +def test_secure_erase_removes_local_memory_indexes_and_links(tmp_path): + db_path = tmp_path / "engraphis.db" + service = MemoryService.create(str(db_path)) + leaked = service.remember("Legacy row placeholder.", workspace="acme") + other = service.remember("Independent safe memory.", workspace="acme") + mid = leaked["id"] + + # Simulate a row captured before the boundary existed, including an FTS mirror. + service.store.conn.execute("UPDATE memories SET content=? WHERE id=?", (_LEAK, mid)) + service.store._fts_upsert(mid, "", _LEAK, "") + service.store.add_link(mid, other["id"], "related") + service.store.audit("tester", "legacy_note", mid, "legacy audit detail " + _LEAK) + service.store.conn.commit() + + erased = service.secure_erase(mid, workspace="acme") + assert erased["status"] == "securely_erased" + assert erased["vector_index_cleanup"] == "deleted" + assert service.store.get_memory(mid) is None + assert service.store.conn.execute("SELECT COUNT(*) FROM mem_fts WHERE id=?", (mid,)).fetchone()[0] == 0 + assert service.store.conn.execute("SELECT COUNT(*) FROM mem_vectors WHERE id=?", (mid,)).fetchone()[0] == 0 + assert service.store.conn.execute( + "SELECT COUNT(*) FROM mem_links WHERE a=? OR b=?", (mid, mid) + ).fetchone()[0] == 0 + audit_rows = service.store.conn.execute( + "SELECT action, detail FROM audit WHERE target=?", (mid,) + ).fetchall() + assert [(row["action"], row["detail"]) for row in audit_rows] == [ + ("secure_erase", "per-memory secure erasure completed; content intentionally omitted") + ] + assert _LEAK.encode("utf-8") not in db_path.read_bytes() + wal_path = db_path.with_name(db_path.name + "-wal") + if wal_path.exists(): + assert _LEAK.encode("utf-8") not in wal_path.read_bytes() + # The physical result is explicit; a busy WAL/VACUUM must never be reported as success. + assert erased["maintenance"]["wal"] in {"truncated", "busy", "failed"} + assert erased["maintenance"]["vacuum"] in {"completed", "failed"} + + +def test_sync_drops_secret_bearing_rows_before_store_upsert(): + store = Store(":memory:") + workspace = store.get_or_create_workspace("acme") + # Exercise the public sync parser directly: it must reject rather than rely only + # on Store.add_memory, because sync normally batches raw writes. + from engraphis.core.sync import SyncEngine + + bundle = { + "format": "engraphis-sync", "version": 2, "device_id": "peer", + "workspace_name": "acme", "repos": {}, + "memories": [{ + "id": "mem_peer_secret", "content": _LEAK, "scope": "workspace", + "mtype": "semantic", "metadata": json.loads("{}"), + }], "mem_links": [], + } + report = SyncEngine(store).apply_bundle(bundle, into_workspace="acme") + assert workspace + assert report["rejected"] == 1 + assert store.count_memories() == 0 diff --git a/tests/test_service.py b/tests/test_service.py index 3127b85e..191f459e 100644 --- a/tests/test_service.py +++ b/tests/test_service.py @@ -94,6 +94,11 @@ def test_recall_support_reuses_vector_arm_without_a_second_embedding_batch(): workspace="acme", repo="web") class CountingEmbedder: + # This test models a declared semantic production adapter while retaining a + # deterministic vector implementation to keep the unit test offline. + supports_semantic_search = True + embedding_mode = "semantic" + def __init__(self, wrapped): self.wrapped = wrapped self.batches = [] @@ -112,17 +117,48 @@ def embed(self, texts): assert result["score_semantics"]["version"] == "retrieval-support-v1" -def test_recall_absolute_support_stays_low_for_a_weak_one_item_pool(): +def test_deterministic_recall_reports_degraded_mode_and_disables_vector_arm(): + s = _svc() + s.remember("Frontend repositories use pnpm for package management.", + workspace="acme", repo="web") + + result = s.recall( + "which package manager do frontend repositories use?", + workspace="acme", repo="web", diagnostics=True, + ) + + assert result["degraded_mode"] is True + assert result["semantic_support"] is False + assert result["embedding_mode"] == "lexical_hashing" + assert "Semantic cosine is disabled" in result["score_semantics"]["absolute_support"] + assert result["retrieval_trace"][0]["raw"]["semantic"] is None + + +def test_deterministic_grounded_recall_is_explicitly_lexical_only(): + s = _svc() + s.remember("Frontend repositories use pnpm for package management.", + workspace="acme", repo="web") + + result = s.grounded_recall( + "which package manager do frontend repositories use?", + workspace="acme", repo="web", + ) + + assert result["grounded"] is True + assert result["degraded_mode"] is True + assert result["semantic_support"] is False + assert result["embedding_mode"] == "lexical_hashing" + + +def test_degraded_recall_does_not_return_a_weak_vector_neighbour(): s = _svc() s.remember("Production deploys to AWS ECS after approval.", workspace="acme", repo="web") result = s.recall("What sourdough hydration ratio should I use?", workspace="acme", repo="web") - memory = result["memories"][0] - - assert memory["relative_score"] > 0.5 - assert memory["absolute_support"] < 0.15 + assert result["count"] == 0 + assert result["memories"] == [] def test_public_review_writes_do_not_resolve_claims_before_approval(): From 83159704b617eda822a42d5b29d23850cc29fa0a Mon Sep 17 00:00:00 2001 From: Jaixii Date: Sun, 2 Aug 2026 18:17:46 -0400 Subject: [PATCH 17/35] fix: audit stripped release image --- .github/workflows/release.yml | 20 ++++++++++++++++---- tests/test_planned_recall.py | 4 ++++ tests/test_release_infrastructure.py | 6 ++++-- 3 files changed, 24 insertions(+), 6 deletions(-) diff --git a/.github/workflows/release.yml b/.github/workflows/release.yml index 5d294876..b3c76cd0 100644 --- a/.github/workflows/release.yml +++ b/.github/workflows/release.yml @@ -191,10 +191,22 @@ jobs: 'python -c "import PIL, pytesseract" && command -v tesseract >/dev/null && tesseract --version | head -n 1' - name: Audit production image dependencies - run: >- - docker run --rm --entrypoint sh engraphis:release -c - 'python -m pip install --no-cache-dir pip-audit && - python -m pip_audit --local' + # The runtime image deliberately has no pip. Audit its exact installed + # distributions from the runner instead of reintroducing a build tool to the + # production image only for this check. + shell: bash + run: | + audit_dir="$(mktemp -d)" + container="engraphis-release-audit-${GITHUB_RUN_ID}-${GITHUB_RUN_ATTEMPT}" + cleanup() { + docker rm -f "$container" >/dev/null 2>&1 || true + rm -rf "$audit_dir" + } + trap cleanup EXIT + python -m pip install --disable-pip-version-check --no-cache-dir pip-audit + docker create --name "$container" engraphis:release >/dev/null + docker cp "$container":/usr/local/lib/python3.11/site-packages/. "$audit_dir" + python -m pip_audit --path "$audit_dir" - name: Run customer-mode readiness smoke shell: bash run: | diff --git a/tests/test_planned_recall.py b/tests/test_planned_recall.py index df022770..3d24e85f 100644 --- a/tests/test_planned_recall.py +++ b/tests/test_planned_recall.py @@ -38,6 +38,10 @@ def plan(self, query, *, filter=None, timeout_s=None): class _MappedEmbedder: + # This fixture deliberately models a semantic backend without downloading a model. + # Recall requires every non-degraded backend to declare that capability explicitly. + supports_semantic_search = True + embedding_mode = "semantic" dim = 2 def __init__(self, vectors): diff --git a/tests/test_release_infrastructure.py b/tests/test_release_infrastructure.py index 4c6bdeed..15c61bf6 100644 --- a/tests/test_release_infrastructure.py +++ b/tests/test_release_infrastructure.py @@ -128,8 +128,10 @@ def test_ci_and_release_audit_production_image_dependencies(): assert "Validate Compose configuration" in release_docker assert "docker compose config --quiet" in release_docker assert "Audit production image dependencies" in release_docker - assert "python -m pip install --no-cache-dir pip-audit" in release_docker - assert "python -m pip_audit --local" in release_docker + assert 'python -m pip install --disable-pip-version-check --no-cache-dir pip-audit' in release_docker + assert 'docker create --name "$container" engraphis:release' in release_docker + assert 'docker cp "$container":/usr/local/lib/python3.11/site-packages/.' in release_docker + assert 'python -m pip_audit --path "$audit_dir"' in release_docker assert "needs: [build, python-matrix, encryption, browser-accessibility, docker-smoke]" in release_evidence assert "needs: release-evidence" in publish assert "Browser accessibility release gate" in release From 0f52e0f6eb1ddf61edbb8768ee1ab6cb40da0137 Mon Sep 17 00:00:00 2001 From: Jaixii Date: Sun, 2 Aug 2026 18:22:20 -0400 Subject: [PATCH 18/35] test: expect retirement control in ledger smoke --- tests/e2e/ledger.spec.js | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/tests/e2e/ledger.spec.js b/tests/e2e/ledger.spec.js index ca67db2d..b6d68d0e 100644 --- a/tests/e2e/ledger.spec.js +++ b/tests/e2e/ledger.spec.js @@ -302,7 +302,7 @@ test('memory listings open the editable Library detail from every dashboard view await page.locator('#proactive-list [data-memory-id="mem_database"]').click(); await expect(page.locator('#memory-detail h2')).toHaveText('Database choice'); await expect(page.locator('#memory-detail').getByRole('button', { name: 'Edit' })).toBeVisible(); - await expect(page.locator('#memory-detail').getByRole('button', { name: 'Forget' })).toBeVisible(); + await expect(page.locator('#memory-detail').getByRole('button', { name: 'Retire' })).toBeVisible(); await page.getByRole('button', { name: 'Ask grounded answers' }).click(); await page.getByRole('textbox', { name: 'Question' }).fill('Which database?'); From 5c96eb1e8214a28beac427e905f8e1813086af0e Mon Sep 17 00:00:00 2001 From: Jaixii Date: Sun, 2 Aug 2026 21:31:38 -0400 Subject: [PATCH 19/35] feat: harden smart MCP gateway and Pi integration --- .claude-plugin/skill-assets.sha256 | 4 +- .env.example | 16 +- .github/workflows/ci.yml | 37 + .github/workflows/release-pi.yml | 104 + .github/workflows/release.yml | 32 +- CHANGELOG.md | 53 +- README.md | 85 +- docs/AGENT_CONNECT.md | 17 +- docs/ARCHITECTURE_V3.md | 2 +- docs/KILO_CODE_INTEGRATION.md | 89 +- docs/MCP_TOOLS.md | 24 +- engraphis/__init__.py | 7 + engraphis/backends/embedder_api.py | 145 +- engraphis/backends/embedder_deterministic.py | 11 +- engraphis/backends/postgres_schema.py | 22 +- engraphis/backends/vector_sqlitevec.py | 22 +- engraphis/core/secrets.py | 29 +- engraphis/core/store.py | 71 +- engraphis/core/sync.py | 4 +- engraphis/mcp_classic_cli.py | 34 + engraphis/mcp_http_cli.py | 19 +- engraphis/mcp_server.py | 691 ++- engraphis/read_only_api.py | 15 +- engraphis/routes/v2_api.py | 57 +- engraphis/service.py | 139 +- eval/planned_recall.py | 24 + integrations/pi/LICENSE | 201 + integrations/pi/NOTICE | 13 + integrations/pi/README.md | 115 + integrations/pi/index.ts | 193 + integrations/pi/npm-shrinkwrap.json | 3716 +++++++++++++++++ integrations/pi/package.json | 73 + integrations/pi/src/config.ts | 70 + integrations/pi/src/mcp-client.ts | 292 ++ integrations/pi/src/tool-schemas.ts | 113 + integrations/pi/test/config.test.ts | 143 + integrations/pi/test/extension.test.ts | 159 + .../pi/test/mcp-client.integration.ts | 75 + integrations/pi/test/mcp-result.test.ts | 82 + integrations/pi/test/pi-loader.test.ts | 27 + integrations/pi/tsconfig.json | 13 + pyproject.toml | 1 + scripts/entry.py | 2 + skills/engraphis-memory/SKILL.md | 52 +- skills/engraphis-memory/references/SCOPING.md | 14 +- tests/test_adaptive_context_route.py | 52 + tests/test_backends_factories.py | 10 + tests/test_config.py | 21 + tests/test_embeddings.py | 182 + tests/test_mcp_annotation_idempotency.py | 2 +- tests/test_mcp_server.py | 74 +- tests/test_packaging.py | 14 + tests/test_planned_recall_eval.py | 11 + tests/test_postgres_schema.py | 20 + tests/test_proactive_context.py | 70 + tests/test_read_only_api.py | 16 + tests/test_release_evidence.py | 5 +- tests/test_release_infrastructure.py | 13 +- tests/test_secret_hygiene.py | 85 +- tests/test_secrets_edge_cases.py | 18 + tests/test_smart_mcp_gateway.py | 406 ++ tests/test_sync.py | 6 + 62 files changed, 7912 insertions(+), 200 deletions(-) create mode 100644 .github/workflows/release-pi.yml create mode 100644 engraphis/mcp_classic_cli.py create mode 100644 integrations/pi/LICENSE create mode 100644 integrations/pi/NOTICE create mode 100644 integrations/pi/README.md create mode 100644 integrations/pi/index.ts create mode 100644 integrations/pi/npm-shrinkwrap.json create mode 100644 integrations/pi/package.json create mode 100644 integrations/pi/src/config.ts create mode 100644 integrations/pi/src/mcp-client.ts create mode 100644 integrations/pi/src/tool-schemas.ts create mode 100644 integrations/pi/test/config.test.ts create mode 100644 integrations/pi/test/extension.test.ts create mode 100644 integrations/pi/test/mcp-client.integration.ts create mode 100644 integrations/pi/test/mcp-result.test.ts create mode 100644 integrations/pi/test/pi-loader.test.ts create mode 100644 integrations/pi/tsconfig.json create mode 100644 tests/test_adaptive_context_route.py create mode 100644 tests/test_secrets_edge_cases.py create mode 100644 tests/test_smart_mcp_gateway.py diff --git a/.claude-plugin/skill-assets.sha256 b/.claude-plugin/skill-assets.sha256 index 035635a7..daf8b9a6 100644 --- a/.claude-plugin/skill-assets.sha256 +++ b/.claude-plugin/skill-assets.sha256 @@ -1,6 +1,6 @@ b3122186525b688060558721dadf8ca4a20e192097556adb1daecca0649a4e28 .claude-plugin/marketplace.json 5a870fabc9814e177a570a8878371d1c4c50a5b245076c2cfbb7ca659e41ebf6 .claude-plugin/plugin.json -e8d50409eead8041ccdf93319c93a2a37bb68389f3d292b8c86aa368a4870e94 skills/engraphis-memory/SKILL.md +911c70ead2c5aa3de24a6c645a9e921382a149aba52b0a9582ecd5b560e5b8a8 skills/engraphis-memory/SKILL.md 45dd73ca6afdd9e12ecd38c48e4a612b7646c25a07a75a80ca0e68d0e0b85f0e skills/engraphis-memory/references/CONVENTIONS.md -8aafd2daba872be38ec8d42377e886d795d8941bf7c6a39795937ffc1d1f0d88 skills/engraphis-memory/references/SCOPING.md +529fff3bdbe73f83209087fd10055fad77c5e5224ad8a9e6b0254052aa50e109 skills/engraphis-memory/references/SCOPING.md eecd861f0f8cc2a9def07a53387ca66d8cb68d8b62d9b048dcd1b0b250fa3fee skills/engraphis-memory/references/TOOLS.md diff --git a/.env.example b/.env.example index c0666e3c..2bb0c15b 100644 --- a/.env.example +++ b/.env.example @@ -265,18 +265,18 @@ ENGRAPHIS_LLM_API_KEY=sk-your-key-here # directories allowed as import sources. # ENGRAPHIS_IMPORT_ROOTS=/srv/docs:/home/user/notes -# Memory engine tuning: decay halflife (days), chunk sizing (tokens), -# proactive context loop, and reranker model. -# ENGRAPHIS_DECAY_HALFLIFE_DAYS=30 -# ENGRAPHIS_CHUNK_TOKENS=512 -# ENGRAPHIS_CHUNK_MAX=2048 -# ENGRAPHIS_CHUNK_OVERLAP=64 +# Memory engine tuning: runtime defaults for decay, chunk sizing, and the +# proactive context loop. CHUNK_MAX is a chunk-count limit, not a token limit. +# ENGRAPHIS_DECAY_HALFLIFE_DAYS=7 +# ENGRAPHIS_CHUNK_TOKENS=256 +# ENGRAPHIS_CHUNK_MAX=200 +# ENGRAPHIS_CHUNK_OVERLAP=32 # Optional reader-tokenizer parity for chunk sizes (requires transformers). # Pin the revision when the resulting memories support reproducible evidence. # ENGRAPHIS_CHUNK_TOKENIZER_MODEL=Qwen/Qwen3.5-9B # ENGRAPHIS_CHUNK_TOKENIZER_REVISION= -# ENGRAPHIS_LOOP_INTERVAL=300 -# ENGRAPHIS_LOOP_TOP_K=10 +# ENGRAPHIS_LOOP_INTERVAL=60 +# ENGRAPHIS_LOOP_TOP_K=20 # ENGRAPHIS_RERANK_MODEL=cross-encoder/ms-marco-MiniLM-L-6-v2 # Workspace allow-list: comma-separated names. Empty = all allowed. diff --git a/.github/workflows/ci.yml b/.github/workflows/ci.yml index 9de24398..02676df3 100644 --- a/.github/workflows/ci.yml +++ b/.github/workflows/ci.yml @@ -83,6 +83,43 @@ jobs: - name: Ablation run: python -m eval.ablation + pi-extension: + name: Pi extension (${{ matrix.os }}, Python ${{ matrix.python-version }}, Node ${{ matrix.node-version }}) + runs-on: ${{ matrix.os }} + strategy: + fail-fast: false + matrix: + include: + - os: ubuntu-latest + python-version: "3.10" + node-version: "22.19.0" + - os: windows-latest + python-version: "3.11" + node-version: "24" + steps: + - uses: actions/checkout@3d3c42e5aac5ba805825da76410c181273ba90b1 # v7 + - uses: actions/setup-python@5fda3b95a4ea91299a34e894583c3862153e4b97 # v7.0.0 + with: + python-version: ${{ matrix.python-version }} + - uses: actions/setup-node@820762786026740c76f36085b0efc47a31fe5020 # v7.0.0 + with: + node-version: ${{ matrix.node-version }} + cache: npm + cache-dependency-path: integrations/pi/npm-shrinkwrap.json + - name: Install the current Smart MCP server + run: | + python -m pip install --upgrade pip + python -m pip install -e ".[test]" + - name: Install and verify the Pi package + working-directory: integrations/pi + env: + ENGRAPHIS_PI_TEST_COMMAND: engraphis-mcp + run: | + npm ci --ignore-scripts + npm run verify + npm run test:integration + npm audit --omit=dev + browser-accessibility: name: browser accessibility smoke runs-on: ubuntu-latest diff --git a/.github/workflows/release-pi.yml b/.github/workflows/release-pi.yml new file mode 100644 index 00000000..91726d80 --- /dev/null +++ b/.github/workflows/release-pi.yml @@ -0,0 +1,104 @@ +name: Publish Pi extension to npm + +on: + push: + tags: + - "pi-v*.*.*" + workflow_dispatch: + +permissions: + contents: read + +jobs: + build: + name: Verify and pack Pi extension + runs-on: ubuntu-latest + steps: + - uses: actions/checkout@3d3c42e5aac5ba805825da76410c181273ba90b1 # v7 + with: + fetch-depth: 0 + - uses: actions/setup-python@5fda3b95a4ea91299a34e894583c3862153e4b97 # v7.0.0 + with: + python-version: "3.11" + - uses: actions/setup-node@820762786026740c76f36085b0efc47a31fe5020 # v7.0.0 + with: + node-version: "24" + cache: npm + cache-dependency-path: integrations/pi/npm-shrinkwrap.json + registry-url: https://registry.npmjs.org + + - name: Require Pi tag and npm package version to match + if: github.event_name == 'push' + shell: bash + run: | + expected="${GITHUB_REF_NAME#pi-v}" + actual="$(node -p 'require("./integrations/pi/package.json").version')" + test "$GITHUB_REF_NAME" = "pi-v$actual" + test "$expected" = "$actual" + + - name: Require release tag commit to be on protected main + if: github.event_name == 'push' + shell: bash + run: | + git fetch --no-tags origin main:refs/remotes/origin/main + git merge-base --is-ancestor "$GITHUB_SHA" origin/main + + - name: Install the current Smart MCP server + run: | + python -m pip install --upgrade pip + python -m pip install -e ".[test]" + + - name: Verify package, live MCP bridge, and production dependencies + working-directory: integrations/pi + env: + ENGRAPHIS_PI_TEST_COMMAND: engraphis-mcp + run: | + npm ci --ignore-scripts + npm run verify + npm run test:integration + npm audit --omit=dev + + - name: Build npm tarball + working-directory: integrations/pi + run: npm pack --ignore-scripts + + - name: Store npm tarball + uses: actions/upload-artifact@043fb46d1a93c77aae656e7c1c64a875d1fc6a0a # v7 + with: + name: pi-npm-package + path: integrations/pi/engraphis-pi-*.tgz + if-no-files-found: error + + publish: + name: Publish @engraphis/pi + needs: build + # A manual dispatch is intentionally verification-only. Publishing requires a + # protected pi-v* tag and npm Trusted Publishing configured for this workflow. + if: github.event_name == 'push' && startsWith(github.ref, 'refs/tags/pi-v') + runs-on: ubuntu-latest + permissions: + contents: read + id-token: write + steps: + - uses: actions/setup-node@820762786026740c76f36085b0efc47a31fe5020 # v7.0.0 + with: + node-version: "24" + registry-url: https://registry.npmjs.org + - uses: actions/download-artifact@3e5f45b2cfb9172054b4087a40e8e0b5a5461e7c # v8 + with: + name: pi-npm-package + path: dist + - name: Publish with npm provenance + run: npm publish dist/engraphis-pi-*.tgz --access public --provenance + - name: Verify the published version + shell: bash + run: | + version="${GITHUB_REF_NAME#pi-v}" + for attempt in $(seq 1 12); do + if [ "$(npm view "@engraphis/pi@$version" version 2>/dev/null)" = "$version" ]; then + exit 0 + fi + sleep 10 + done + echo "@engraphis/pi@$version did not become visible on npm" + exit 1 diff --git a/.github/workflows/release.yml b/.github/workflows/release.yml index b3c76cd0..eb36c213 100644 --- a/.github/workflows/release.yml +++ b/.github/workflows/release.yml @@ -163,6 +163,36 @@ jobs: - name: Playwright desktop/mobile, keyboard, CSP, console, and axe checks run: npm run test:e2e + pi-extension: + name: Pi extension release gate + runs-on: ubuntu-latest + if: >- + github.event_name == 'push' || + inputs.release_tag == '' + steps: + - uses: actions/checkout@3d3c42e5aac5ba805825da76410c181273ba90b1 # v7 + - uses: actions/setup-python@5fda3b95a4ea91299a34e894583c3862153e4b97 # v7.0.0 + with: + python-version: "3.11" + - uses: actions/setup-node@820762786026740c76f36085b0efc47a31fe5020 # v7.0.0 + with: + node-version: "24" + cache: npm + cache-dependency-path: integrations/pi/npm-shrinkwrap.json + - name: Install the tagged Smart MCP server + run: | + python -m pip install --upgrade pip + python -m pip install -e ".[test]" + - name: Verify the publishable Pi package and live bridge + working-directory: integrations/pi + env: + ENGRAPHIS_PI_TEST_COMMAND: engraphis-mcp + run: | + npm ci --ignore-scripts + npm run verify + npm run test:integration + npm audit --omit=dev + docker-smoke: name: Production image release gate runs-on: ubuntu-latest @@ -229,7 +259,7 @@ jobs: release-evidence: name: Generate public release evidence - needs: [build, python-matrix, encryption, browser-accessibility, docker-smoke] + needs: [build, python-matrix, encryption, browser-accessibility, pi-extension, docker-smoke] if: github.event_name == 'push' && startsWith(github.ref, 'refs/tags/v') runs-on: ubuntu-latest permissions: diff --git a/CHANGELOG.md b/CHANGELOG.md index 0d2120f5..549b1bd9 100644 --- a/CHANGELOG.md +++ b/CHANGELOG.md @@ -5,8 +5,34 @@ All notable changes to Engraphis are documented here. Format loosely follows ## [Unreleased] +## [1.4.0] - 2026-08-02 + +Engraphis 1.4 makes the compact Smart MCP gateway the default agent interface while preserving +the complete Classic surface for existing integrations. It also strengthens review-gated writes, +bounded context delivery, secure erasure, and release/runtime hardening without changing the v2 +database schema. + +### Upgrade notes + +- `engraphis-mcp` now exposes six Smart tools instead of 33 direct tools. Clients that depend on + the former names should switch their server command to `engraphis-mcp-classic`; HTTP clients can + use `engraphis-mcp-http --classic`. +- Existing v2 databases remain on schema 7 and require no migration for this release. +- The NumPy-only core supports Python 3.9+. Dashboard, MCP, documents, Cloud Sync, and `all` + installations require Python 3.10+ because their supported dependency versions require it. + ### Added +- Smart MCP is now the zero-configuration `engraphis-mcp` default. It exposes six compact tools + for sessions, prompt-ready recall, durable memory, discovery, and validated read/action + execution. `engraphis-mcp-classic` preserves the former 33 direct tool names and legacy alias + response shapes for pinned integrations. +- The first-party `@engraphis/pi` package under `integrations/pi` exposes that Smart MCP surface + as native Pi tools, verifies the Engraphis 1.4.x handshake, and ships with independent npm + packaging and release gates. +- Hosts that retain their own conversation history can call the non-MCP + `POST /api/adaptive-context` endpoint. Advanced proactive context also supports a bounded, + content-lean compact response while Classic keeps its full response by default. - Opt-in planned recall adds a bounded deterministic planner, an injectable planner protocol and optional LLM backend, priority-weighted multi-query RRF, post-rerank memory-type maxima, stable context revisions, and diagnostics-only planner traces across Python, service, REST, and MCP @@ -18,20 +44,37 @@ All notable changes to Engraphis are documented here. Format loosely follows ### Security +- The Pi extension preserves the Smart gateway's destructive boundary: every discovered + state-changing action requires an explicit Pi confirmation, fails closed without a dialog, + and consumes its capability after one approval attempt so unknown outcomes are not retried. - Public writes now enter an explicit review gate: MCP, REST/dashboard-intent, import, sync, and extractor ingress are pending regardless of a caller-supplied trust label; detector matches are quarantined before they can contribute to prompt context or derived state. Human approval creates a fresh audited successor only through the CSRF-bound dashboard action or an interactive TTY command, never through MCP or a general REST endpoint. Historical rescans demote non-approved - records and retire their derived bridges. Public history, graph and code retrieval, and graph - indexing, and consolidation apply prompt eligibility before ranking or capacity decisions, so - pending or quarantined records cannot influence prompt-visible results through derived bridges. + records and retire their derived bridges. Public history, graph/code retrieval and indexing, and + consolidation apply prompt eligibility before ranking or capacity decisions, so pending or + quarantined records cannot influence prompt-visible results through derived bridges. +- Smart MCP authorization now fails closed: discovery and read execution require viewer access, + state-changing execution requires admin access remotely, and pure reads do not emit write-side + telemetry receipts. Executor output is bounded without retrying or double-running handlers. +- Tokenless remote requests to the read-only recall and repository-graph API now fail closed; + health and OpenAPI discovery remain public. - The deterministic detector now uses a pinned Unicode TR39 15.1.0 ASCII projection rather than a short hand-picked table, covering additional Latin, Cyrillic, Greek, mathematical, and legacy glyph substitutions without an online lookup or runtime dependency. +- Secret scanning is cycle-safe and depth-bounded, and PostgreSQL source identities are reduced to + credential-free digests for both URI and libpq keyword DSNs. ### Fixed +- Secure erase now rebuilds shared-edge provenance from surviving support rows. Historical-only + support remains available to time-travel reads while the edge is closed in the current graph. +- API embedding backends now validate dimensions, response cardinality, item indices, finite + values, and normalization before accepting provider output, with consistent bounded fallback. +- Planned-recall datasets reject dangling references, vector dimensions are bounded across local + and SQLite backends, and sync imports accept pinned state only when it is the literal boolean + `true`. - The production image now removes build-only pip and its vendored dependency snapshot after installation, eliminating unreachable vulnerable packages from the runtime attack surface. - Automatic LLM retention supervision now discards proposed retention values when it @@ -42,7 +85,6 @@ All notable changes to Engraphis are documented here. Format loosely follows - `engraphis connect` now treats its printed summary as a provider trust boundary: only bounded, printable registration metadata is rendered, preventing malformed control-plane values from being reflected into CLI or JSON output. - - Explicit local `engraphis-cli ingest` commands now record local-owner-approved provenance, allowing their memories to appear in ordinary subsequent CLI recall. HTTP, MCP, import, and file-ingestion boundaries remain pending review. @@ -78,6 +120,9 @@ All notable changes to Engraphis are documented here. Format loosely follows - MCP-over-HTTP has a packaged `engraphis-mcp-http` command and a generic local setup guide. The project makes no client-specific integration claim without a maintained guide and integration test. +- `.env.example` now mirrors runtime defaults for decay, context packing, loop cadence, and recall + depth so copied configurations do not silently override the documented behavior. + ## [1.3.0] - 2026-08-01 ### Added diff --git a/README.md b/README.md index a11dbd06..1e2f64c8 100644 --- a/README.md +++ b/README.md @@ -1,12 +1,13 @@ # Engraphis [![PyPI version](https://img.shields.io/pypi/v/engraphis.svg)](https://pypi.org/project/engraphis/) +[![CI](https://github.com/Coding-Dev-Tools/engraphis/actions/workflows/ci.yml/badge.svg)](https://github.com/Coding-Dev-Tools/engraphis/actions/workflows/ci.yml) +[![Python 3.9+](https://img.shields.io/pypi/pyversions/engraphis.svg)](https://pypi.org/project/engraphis/) [![License](https://img.shields.io/badge/license-Apache--2.0-green.svg)](https://github.com/Coding-Dev-Tools/engraphis/blob/main/LICENSE) -[![Buy Me a Coffee](https://img.shields.io/badge/Buy%20Me%20a%20Coffee-support-yellow?style=for-the-badge&logo=buy-me-a-coffee)](https://buymeacoffee.com/Jaixii) +[![Support](https://img.shields.io/badge/Buy%20Me%20a%20Coffee-support-yellow?logo=buy-me-a-coffee)](https://buymeacoffee.com/Jaixii) -https://engraphis.com/ - -https://discord.com/invite/Wfr2ejBmY +[Website](https://engraphis.com/) · [Documentation](docs/) · [MCP tools](docs/MCP_TOOLS.md) · +[Security](SECURITY.md) · [Discord](https://discord.com/invite/Wfr2ejBmY) **Give coding agents durable project memory so the next session can retrieve the current decision, its evidence, and its history.** @@ -22,6 +23,28 @@ https://discord.com/invite/Wfr2ejBmY > and customer-side clients. Hosted sync, analytics, automation, and team services run on the > official hosted service; their server implementations are not distributed here. +## Start in 60 seconds + +Choose the smallest surface that matches your use case. Python 3.10+ is recommended and is +required for the dashboard, MCP, documents, Cloud Sync, and `all` extras; the NumPy-only core +continues to support Python 3.9+. + +| Goal | Install | Start | +|---|---|---| +| Local dashboard and REST API | `pip install "engraphis[server]"` | `engraphis-dashboard` | +| Coding-agent memory over Smart MCP | `pip install "engraphis[mcp]"` | `codex mcp add engraphis -- engraphis-mcp` | +| Offline Python library | `pip install engraphis` | `MemoryService.create("engraphis.db")` | +| Full cross-platform feature set | `pip install "engraphis[all]"` | `engraphis-dashboard` | + +The dashboard opens at [http://127.0.0.1:8700](http://127.0.0.1:8700). Local memory needs no +account or API key. For MCP clients other than Codex, configure a stdio server whose command is +`engraphis-mcp`; see the [agent connection guide](docs/AGENT_CONNECT.md). + +> **Upgrading to 1.4:** `engraphis-mcp` now exposes the six-tool Smart gateway. Integrations that +> require the former 33 direct tool names should run `engraphis-mcp-classic`. The SQLite schema +> remains version 7, so this MCP surface change does not require a data migration. See the +> [1.4.0 release notes](CHANGELOG.md#140---2026-08-02). + ## Measured token and context savings

@@ -131,9 +154,9 @@ Run `python -m eval.chunking_eval` and `python -m eval.grounded` to reproduce th the former measures evidence retrieval and context size, while the latter measures the answer-versus-abstain decision. -## Full Engraphis install: pip install "engraphis[all]" +## Dashboard and local UI -Engraphis-Dashboard opens `http://127.0.0.1:8700`. Local memory needs no cloud account, +The Engraphis dashboard opens `http://127.0.0.1:8700`. Local memory needs no cloud account, signup, or API key and stays in a SQLite file on your machine. **Ledger** is the primary local interface for recall, memories, graph exploration, provenance, @@ -252,7 +275,7 @@ key. Plaintext SQLite remains the explicit default on every platform. --- -## Quickstart: dashboard (the headline) +## Quickstart: dashboard ```bash pip install "engraphis[server]" @@ -338,12 +361,34 @@ cmd mcp add engraphis -- engraphis-mcp # Command Code CLI For Command Code scopes, verification, and its optional Provider API setup, see the [Command Code section of the LLM provider guide](docs/LLM_PROVIDERS.md#command-code). -Your agent now has 33 tools for memory, recall, grounded answers, timelines, consolidation, code -graph work, and privacy-safe receipts. The full inventory, including `engraphis_check_update`, is -in the [MCP tool reference](docs/MCP_TOOLS.md). +`engraphis-mcp` is zero-configuration Smart MCP: agents begin with six compact tools for sessions, +prompt-ready recall, durable memory, action discovery, and safe execution. For code graphs, +governance, audit, or other advanced work, the agent calls `engraphis_discover_actions` and then +the indicated read or action executor; no profile selection is required. The gateway validates +the discovered capability again before it runs it, and clients remain responsible for their +normal destructive-action approval boundary. + +Existing clients that pin the historical 33 named tools can use +`engraphis-mcp-classic` (or `engraphis-mcp-http --classic`). The complete classic inventory, +including `engraphis_check_update`, is in the [MCP tool reference](docs/MCP_TOOLS.md). + +### Pi extension + +Pi users install the first-party extension from npm after installing Engraphis 1.4.x on +Python 3.10 or later: + +```bash +python -m pip install --upgrade "engraphis[mcp]>=1.4.0,<2" +pi install npm:@engraphis/pi +``` + +The extension exposes the six Smart MCP tools as native Pi tools. It confirms every advanced +state-changing action through Pi's UI and fails closed when the current Pi mode cannot present +that approval. Package configuration, update/removal commands, and the local trust boundary are +documented in [`integrations/pi/README.md`](integrations/pi/README.md). -For unattended jobs, `engraphis_start_session`, `engraphis_remember`, and -`engraphis_record_event` use workspace `default` when `workspace` is omitted. +For unattended jobs, `engraphis_session`, `engraphis_remember`, and discovered actions use +workspace `default` when `workspace` is omitted. ### Review gate for MCP, REST, imports, and sync @@ -561,7 +606,7 @@ when you are ready to evaluate the service boundary and billing options. | | Free (available now) | Pro: $10/mo or $100/yr | Team: $20/seat/mo or $200/seat/yr | |---|---|---|---| | Dashboard WebUI (with built-in inspector) | ✓ | ✓ | ✓ | -| Memory engine + 33 MCP tools | ✓ | ✓ | ✓ | +| Memory engine + Smart MCP (Classic 33-tool compatibility) | ✓ | ✓ | ✓ | | Version-chain diffs, offline knowledge graph | ✓ | ✓ | ✓ | | Manual local consolidation (dry-run by default) | ✓ | ✓ | ✓ | | Local workspace export (JSON: memories, sessions, audit) | ✓ | ✓ | ✓ | @@ -579,8 +624,9 @@ when you are ready to evaluate the service boundary and billing options. ## MCP tools -Engraphis exposes 33 MCP tools across memory, recall, code graphs, governance, sessions, and -privacy-safe audit receipts. The focused [MCP tool reference](docs/MCP_TOOLS.md) is the source for +Engraphis exposes a zero-configuration Smart MCP gateway plus a 33-tool Classic compatibility +server across memory, recall, code graphs, governance, sessions, and privacy-safe audit receipts. +The focused [MCP tool reference](docs/MCP_TOOLS.md) is the source for the full inventory and parameters. --- @@ -620,8 +666,9 @@ pip install "engraphis[encryption]" The entire main memory database file is transparently encrypted with AES-256 via SQLCipher; full-text search, the graph, and every query keep working unchanged. Customer authentication -and managed-service state use their respective deployment protections. When a key is set for the main database, Engraphis -**fails loud** rather than silently falling back to plaintext. Generate a strong key: +and managed-service state use their respective deployment protections. When a key is set for the +main database, Engraphis **fails closed with an error** rather than silently falling back to +plaintext. Generate a strong key: ```bash python -c "import secrets; print(secrets.token_hex(32))" @@ -707,7 +754,7 @@ engraphis/ │ ├── core/ # v2 engine: interfaces, store, recall, scoring, schema, sync │ ├── backends/ # pluggable embedder / vector index / reranker / codegraph / sync transports / encryption │ ├── service.py # validated MemoryService facade -│ ├── mcp_server.py # MCP server: 33 tools +│ ├── mcp_server.py # Smart MCP gateway + 33-tool Classic compatibility server │ ├── dashboard_app.py # dashboard WebUI (FastAPI) │ ├── dashboard_assets/ # primary Ledger interface + graph engine │ ├── classic_assets/ # selectable full operator dashboard backup @@ -719,7 +766,7 @@ engraphis/ │ ├── config.py / app.py # env settings / REST server │ └── static/ # compatibility dashboard asset paths ├── eval/ # offline retrieval eval harness + datasets -├── tests/ # pytest suite (300+ tests, offline numpy-only core) +├── tests/ # offline-first pytest suite and release/security contracts ├── scripts/ # dashboard, server, graph, CLI, connect, update, consolidation, sync ├── docs/ # product, API, hosting, sync, and provider guides ├── Dockerfile / docker-compose.yml diff --git a/docs/AGENT_CONNECT.md b/docs/AGENT_CONNECT.md index e6f042c0..ad0c8452 100644 --- a/docs/AGENT_CONNECT.md +++ b/docs/AGENT_CONNECT.md @@ -15,6 +15,9 @@ claude mcp add engraphis -- engraphis-mcp ``` The local server exposes the same memory semantics while keeping the database on your machine. +It is Smart MCP by default: agents use the six compact routine tools and discover/execute advanced +capabilities automatically when needed. There is no profile choice or manual escalation. If a +legacy client pins direct tool names, configure `engraphis-mcp-classic` instead. Use `ENGRAPHIS_API_TOKEN` only when protecting a local HTTP surface; it is not a Team identity or seat credential. @@ -25,7 +28,7 @@ the packaged loopback server: ```bash pip install "engraphis[mcp]" -engraphis-mcp-http # streamable HTTP at http://127.0.0.1:8711/mcp +engraphis-mcp-http # Smart MCP at http://127.0.0.1:8711/mcp # equivalent: engraphis mcp-http ``` @@ -35,9 +38,21 @@ middleware. Do not expose it through a LAN address or proxy. For a remote deploy `engraphis[all]`, set a strong `ENGRAPHIS_API_TOKEN`, terminate TLS, and use the dashboard's authenticated `/mcp` endpoint instead. +Use `engraphis-mcp-http --classic` only for an existing integration that requires the former 33 +direct tool names. New integrations should keep the Smart default. + Engraphis documents and tests generic MCP transports; it does not claim client-specific support unless that client has a maintained setup guide and integration test. +## Host-owned conversation history + +An SDK or HTTP host that already owns the conversation transcript can call +`POST /api/adaptive-context`. It accepts `query`, `history`, scope, and token-budget fields and +returns either a bounded history slice or grounded retrieved context. This is deliberately an +HTTP API, not an MCP tool: models should not receive or call it. Smart MCP does not require native +deferred `tool_search`; a client that explicitly supports that OpenAI feature may use it as an +additional optimization, never as a requirement. + ## Connect through Team Cloud Use the official hosted dashboard when several people or remote agents need one managed diff --git a/docs/ARCHITECTURE_V3.md b/docs/ARCHITECTURE_V3.md index 39058c25..616d974a 100644 --- a/docs/ARCHITECTURE_V3.md +++ b/docs/ARCHITECTURE_V3.md @@ -7,7 +7,7 @@ retention-supervision, and privacy-receipt additions introduced with schema vers flowchart LR Agent["Agent / host LLM"] --> Intent["remember · link · recall_context (compact) · recall"] CLI["engraphis-graph CLI"] --> Service["MemoryService"] - MCP["33 MCP tools"] --> Service + MCP["Smart MCP (6 tools) / Classic MCP (33 tools)"] --> Service HTTP["Dashboard + read-only graph HTTP"] --> Service Import["Local resources / PostgreSQL catalog"] --> Extractors["Optional local extractors"] Extractors --> Service diff --git a/docs/KILO_CODE_INTEGRATION.md b/docs/KILO_CODE_INTEGRATION.md index 888f129c..44929937 100644 --- a/docs/KILO_CODE_INTEGRATION.md +++ b/docs/KILO_CODE_INTEGRATION.md @@ -41,7 +41,9 @@ Everything runs on your machine. The whole store is a single SQLite file. Local You interact with Engraphis through three surfaces, all backed by the *same* engine (`MemoryService`), so they can never drift apart: - **The dashboard WebUI** (`engraphis-dashboard`, `http://127.0.0.1:8700`): a visual product to see, search, and curate memory. -- **The MCP server** (`engraphis-mcp`): the 33 tools your coding agent calls. **This is the surface Kilo Code uses.** +- **The MCP server** (`engraphis-mcp`): a six-tool Smart gateway for routine memory work plus + automatic discovery and validated execution of advanced capabilities. **This is the surface + Kilo Code uses.** - **The Python library** (`from engraphis.service import MemoryService`): for direct programmatic use. ### 2.1 The five ideas that make it more than a vector store @@ -88,7 +90,10 @@ Then run the one-time initializer, which writes an `.env` with an absolute DB pa engraphis-init ``` -This gives you a console command, `engraphis-mcp`, which is the actual MCP server (it speaks stdio, exactly the transport Kilo Code's "Local (STDIO)" type expects). You can sanity-check that it's on your PATH: +This gives you a console command, `engraphis-mcp`, which is the zero-configuration Smart MCP +server (it speaks stdio, exactly the transport Kilo Code's "Local (STDIO)" type expects). It starts +with six compact tools; the agent discovers and executes code, governance, audit, and other +advanced actions as needed. You can sanity-check that it's on your PATH: ```bash engraphis-mcp --help # or just confirm the command resolves @@ -152,41 +157,58 @@ Notes on the fields: ### 3.3 Verify the pipe is connected -Reload Kilo Code (or toggle the server off/on in **Settings → MCP**). You should now see the `engraphis_*` tools available. The fastest end-to-end check is to ask Kilo Code to call the health tool: +Reload Kilo Code (or toggle the server off/on in **Settings → MCP**). You should now see the six +`engraphis_*` Smart tools. The fastest end-to-end check is to ask Kilo Code to discover the health +capability, then run the returned read executor: -> "Call `engraphis_stats` and show me the result." +> "Use Engraphis to check the local memory-store health and show me the result." A JSON response with memory counts means the transport layer is fully working. If it errors, jump to Section 7 (Troubleshooting). -### 3.4 (Optional) Auto-approve the truly read-only tools +### 3.4 (Optional) Auto-approve the Smart read executor -Kilo Code gates each MCP tool call behind an approval prompt. The permission key is the namespaced name `{server}_{tool}`. For a smooth loop, auto-approve tools whose MCP annotations are genuinely read-only and idempotent while keeping stateful retrieval, writes, and governance manual until you trust the flow. In `kilo.jsonc`: +Kilo Code gates each MCP tool call behind an approval prompt. The permission key is the namespaced +name `{server}_{tool}`. For a smooth loop, you may auto-approve `engraphis_execute_read`: the +gateway accepts only a discovered capability that is still classified read-only/idempotent, and +revalidates it before dispatch. Keep session changes, memory writes, and +`engraphis_execute_action` manual until you trust the flow. In `kilo.jsonc`: ```jsonc { "permission": { - "engraphis_recall_proactive": "allow", - "engraphis_why": "allow", - "engraphis_timeline": "allow", - "engraphis_search_code": "allow", - "engraphis_stats": "allow" + "engraphis_execute_read": "allow" } } ``` -Query-based `engraphis_recall`, `engraphis_recall_grounded`, and `engraphis_answer` -are deliberately absent: they update reinforcement metadata and/or append a privacy-safe -operation receipt. `engraphis_proactive_context` is also conservatively stateful because a -non-empty task or agent state runs receipt-recording recall. The queryless -`engraphis_recall_proactive` path does neither, so it remains safe to auto-approve. +`engraphis_recall_context` remains stateful because it can append a privacy-safe receipt. The +write/action executor is intentionally absent: discovery does not grant mutation authority, and +the gateway maintains the action's side-effect class on every call. You can also click **Approve Always** on any tool at runtime to write the same rule. A blanket `"engraphis_*": "allow"` works too, but auto-approving *writes* means the agent can reshape your memory without you seeing it; approve those consciously at first. --- -## 4. The 33 tools: the orchestration surface +## 4. Smart tools and the Classic compatibility surface -Once connected, Kilo Code sees these. Do **not** assume only `remember`/`recall` exist. The value is in the rest. This is the full surface, grouped by what question each one answers. +Normal `engraphis-mcp` setup exposes exactly these six Smart tools. Routine memory work stays +compact; for everything else, discovery returns the exact schema, capability ID, and side-effect +class, and the appropriate executor revalidates all of it before running. + +| Smart tool | Use | +|---|---| +| `engraphis_session` | Start or end a work session and receive the handoff. | +| `engraphis_recall_context` | Fetch a hard-budget, prompt-ready context packet. | +| `engraphis_remember` | Store a durable memory. | +| `engraphis_discover_actions` | Find the best advanced capability and its exact schema. | +| `engraphis_execute_read` | Run a discovered read-only/idempotent capability. | +| `engraphis_execute_action` | Run a discovered stateful, administrative, or destructive-capable action. | + +`engraphis-mcp-classic` is only for an existing configuration that pins direct tool names. It +preserves the former 33-tool surface below; new Kilo Code installations should keep the zero-config +Smart command shown above. + +### Classic 33-tool inventory | Category | Tool | What it does | |---|---|---| @@ -233,12 +255,17 @@ This is how to make the connection actually pay off. The discipline fits on a ca ### 5.1 The core loop for a coding task -1. **Starting work in a repo** → `engraphis_recall_proactive` (loads high-signal context with no query) and, for multi-step work, `engraphis_start_session` (its `bootstrap` hands back the last same-user/agent summary and unresolved `open_threads`, so the agent resumes without crossing an identity boundary). +1. **Starting work in a repo** → for multi-step work, `engraphis_session(action="start", ...)`. + Its bootstrap returns the last handoff and, when given a goal, bounded relevant context. 2. **Before answering or acting**, when prior context would help → `engraphis_recall_context`. It - supplies one hard-budget prompt packet; retain `engraphis_recall` for full-body compatibility. - Do this *before* asking you something you may have already said. + supplies one hard-budget prompt packet. Do this *before* asking you something you may have + already said. 3. **The moment it learns something durable** → `engraphis_remember` (a convention, a decision *with its rationale*, a bug's cause→fix, a preference, a reusable procedure). -4. **Finishing the task** → `engraphis_end_session` with a `summary` and `open_threads` for the next session in that repo. +4. **For code, governance, audit, or any non-routine work** → use + `engraphis_discover_actions`, then the returned read/action executor with its capability ID and + exact schema. Do not invent IDs or arguments. +5. **Finishing the task** → `engraphis_session(action="end", ...)` with a `summary` and + `open_threads` for the next session in that repo. `engraphis_recall_context` returns `usage` fields for the declared token counter: `budget_tokens`, `context_tokens`, `source_tokens`, `saved_tokens`, `savings_ratio`, `packed_count`, @@ -288,8 +315,8 @@ On a schedule (or at session end), run `engraphis_consolidate`: it distills recu ```text # Resuming work on acme/backend -engraphis_start_session(workspace="acme", repo="backend", agent="kilo-code", - goal="fix flaky auth tests") +engraphis_session(action="start", workspace="acme", repo="backend", agent="kilo-code", + goal="fix flaky auth tests") → bootstrap.open_threads: ["tests 3-5 still failing after token refactor"] engraphis_recall_context(query="how do we handle auth token expiry?", @@ -302,9 +329,9 @@ engraphis_remember("Flaky auth tests were caused by a fixed clock in the test ha workspace="acme", repo="backend", mtype="episodic", importance=0.6) → op: "add" -engraphis_end_session(session_id=..., outcome="shipped", - summary="Fixed auth test flake (clock/TTL). Tests green.", - open_threads=[]) +engraphis_session(action="end", session_id=..., outcome="shipped", + summary="Fixed auth test flake (clock/TTL). Tests green.", + open_threads=[]) ``` --- @@ -341,10 +368,10 @@ Kilo Code is an MCP client; Engraphis ships an MCP server (`engraphis-mcp`, loca `engraphis-init`, then add a `local` server named `engraphis` under the `mcp` key in `kilo.jsonc` (`["cmd","/c","engraphis-mcp"]` on Windows, `["engraphis-mcp"]` on macOS/Linux), pin `ENGRAPHIS_DB_PATH`, bump `timeout` to 15000, and verify with -`engraphis_stats`. That gets the pipes connected. The *value* is the orchestration layer -above it: 30 scoped, typed, bi-temporal memory, code, audit, and maintenance tools plus the -discipline of "recall before you ask, remember before you move on," with -`workspace → repo → session` scoping and periodic `engraphis_consolidate` to keep it clean. +Engraphis action discovery. That gets the pipes connected. The *value* is the Smart gateway: six +compact routine tools plus automatic access to scoped, typed, bi-temporal memory, code, audit, and +maintenance capabilities. It preserves the discipline of "recall before you ask, remember before +you move on," with `workspace → repo → session` scoping and periodic consolidation when needed. --- diff --git a/docs/MCP_TOOLS.md b/docs/MCP_TOOLS.md index dc6cc2f9..61d2a031 100644 --- a/docs/MCP_TOOLS.md +++ b/docs/MCP_TOOLS.md @@ -1,8 +1,26 @@ # MCP tool reference -Engraphis exposes MCP tools for writing and recalling memory, managing history, indexing code, and -checking the local store. Start with `engraphis_recall_context` when an agent needs prompt-ready -context, and use `engraphis_remember` when it learns a durable fact. +`engraphis-mcp` is the zero-configuration Smart MCP gateway. It initially exposes six concise +tools: `engraphis_session`, `engraphis_recall_context`, `engraphis_remember`, +`engraphis_discover_actions`, `engraphis_execute_read`, and `engraphis_execute_action`. Agents use +the routine tools directly; for any advanced capability, they discover the best action and execute +the returned, version-bound capability ID. Discovery returns the precise schema and side-effect +class, and execution revalidates availability, scope, authorization, and arguments. + +No user profile choice or tool switching is required. The dashboard `/mcp` endpoint and +`engraphis-mcp-http` use this Smart surface by default. `engraphis-mcp-classic` (or +`engraphis-mcp-http --classic`) preserves the 33 direct tools below for integrations that pin +their historical names and response shapes. + +Hosts which already own chat history should use `POST /api/adaptive-context`, not an MCP action. +The gateway works in general MCP clients without native deferred tool search; clients that +explicitly support OpenAI's deferred `tool_search` can apply it as an optional host optimization. + +## Classic direct-tool inventory + +The following inventory applies to the Classic compatibility server. Start with +`engraphis_recall_context` when an agent needs prompt-ready context, and use +`engraphis_remember` when it learns a durable fact. Retrieval responses (`engraphis_recall`, `engraphis_recall_context`, `engraphis_recall_grounded`, and `engraphis_answer`) always declare diff --git a/engraphis/__init__.py b/engraphis/__init__.py index 71596dee..13a49146 100644 --- a/engraphis/__init__.py +++ b/engraphis/__init__.py @@ -2,8 +2,15 @@ from importlib.metadata import PackageNotFoundError, version as _dist_version +_SOURCE_VERSION = "1.4.0" + try: __version__ = _dist_version("engraphis") + # Editable checkouts can retain stale dist-info until their next reinstall. The + # checked-in source version is authoritative for this runtime and must not advertise + # the prior MCP contract merely because metadata has not been refreshed yet. + if __version__ != _SOURCE_VERSION: + __version__ = _SOURCE_VERSION except PackageNotFoundError: # source tree without an installed distribution # Keep in step with [project] version in pyproject.toml — tests/test_packaging.py # pins the two together so a release cannot ship them out of sync. diff --git a/engraphis/backends/embedder_api.py b/engraphis/backends/embedder_api.py index a9388a80..ce1a2390 100644 --- a/engraphis/backends/embedder_api.py +++ b/engraphis/backends/embedder_api.py @@ -15,10 +15,13 @@ import logging import os +from numbers import Integral from typing import Literal, Optional import numpy as np +from engraphis.backends.embedder_deterministic import MAX_EMBEDDING_DIM + logger = logging.getLogger("engraphis.embedder_api") # Default OpenRouter endpoint @@ -54,6 +57,14 @@ def __init__( self.model = model self._base_url = (base_url or _DEFAULT_BASE_URL).rstrip("/") self._api_key = api_key or os.environ.get(_DEFAULT_API_KEY_ENV, "") + if dim is not None: + if isinstance(dim, bool) or not isinstance(dim, Integral): + raise ValueError("embedding dimension must be a positive integer") + dim = int(dim) + if not 1 <= dim <= MAX_EMBEDDING_DIM: + raise ValueError( + f"embedding dimension must be between 1 and {MAX_EMBEDDING_DIM}" + ) self._dim = dim self._embeddings_url = f"{self._base_url}/v1/embeddings" # A custom endpoint can contain embedded credentials or signed query @@ -86,7 +97,9 @@ def embed( API embedder — the same endpoint handles both text and code. """ if not texts: - return np.empty((0, self.dim), dtype=np.float32) + # An empty batch must not probe a remote provider merely to discover a + # dimension. Unknown is represented by the only truthful width: zero. + return np.empty((0, self._dim or 0), dtype=np.float32) import httpx @@ -117,40 +130,96 @@ def embed( logger.warning("Batch embedding request failed; falling back per-item") # Fallback: embed one at a time vecs = [self._embed_one(t) for t in texts] - return np.asarray(vecs, dtype=np.float32) + return self._finalize_vectors(vecs, len(texts)) - # Parse response — handle missing or malformed data gracefully - items = data.get("data", []) - if not items: - logger.warning("API returned empty data array — falling back per-item") + vectors = self._ordered_batch_vectors(data, len(texts)) + if vectors is None: + logger.warning("API returned malformed embedding data; falling back per-item") vecs = [self._embed_one(t) for t in texts] - return np.asarray(vecs, dtype=np.float32) + return self._finalize_vectors(vecs, len(texts)) + return self._finalize_vectors(vectors, len(texts)) - # Sort by index to preserve order - items.sort(key=lambda x: x.get("index", 0)) - vecs = [] - for item in items: - emb = item.get("embedding") - if emb is None: - # Never log the provider-controlled ``index`` value; a malformed - # response can otherwise inject PII, credentials, or new log lines. - logger.warning("Embedding item missing vector; using zero vector") - emb = [0.0] * (self._dim or 384) - vecs.append(emb) - - result = np.asarray(vecs, dtype=np.float32) - # L2-normalize for cosine similarity + def _finalize_vectors( + self, + vectors: list[Optional[list[float]]], + count: int, + ) -> np.ndarray: + """Assemble one finite, consistently-sized, L2-normalized vector per input.""" + if len(vectors) != count: + raise RuntimeError("embedding provider returned an incomplete response") + widths = {len(vector) for vector in vectors if vector is not None} + if self._dim is not None: + widths.add(self._dim) + if len(widths) > 1: + raise RuntimeError("embedding provider returned inconsistent dimensions") + dimension = next(iter(widths), 384) + if not 1 <= dimension <= MAX_EMBEDDING_DIM: + raise RuntimeError("embedding provider returned an invalid dimension") + completed = [ + vector if vector is not None else [0.0] * dimension + for vector in vectors + ] + result = np.asarray(completed, dtype=np.float32) + if result.shape != (count, dimension) or not np.isfinite(result).all(): + raise RuntimeError("embedding provider returned malformed vectors") norms = np.linalg.norm(result, axis=1, keepdims=True) norms = np.where(norms == 0, 1.0, norms) result = result / norms - - # Detect dimension from first response - if self._dim is None and len(vecs) > 0: - self._dim = len(vecs[0]) - + if self._dim is None: + self._dim = dimension return result - def _embed_one(self, text: str) -> list[float]: + def _coerce_vector(self, value) -> Optional[list[float]]: + """Validate provider-controlled vector shape without reflecting its data.""" + try: + vector = np.asarray(value, dtype=np.float32) + except (TypeError, ValueError, OverflowError): + return None + if self._dim is not None and vector.ndim == 1 and vector.size != self._dim: + # A configured dimension is a compatibility contract with the vector + # store. Treating a provider/model mismatch as a malformed row would + # make the fallback substitute a zero vector, silently corrupting + # retrieval instead of surfacing the configuration error. + raise RuntimeError("embedding provider returned an unexpected dimension") + if ( + vector.ndim != 1 + or not 1 <= vector.size <= MAX_EMBEDDING_DIM + or not np.isfinite(vector).all() + ): + return None + return vector.tolist() + + def _ordered_batch_vectors(self, data, count: int) -> Optional[list[list[float]]]: + """Return exactly one validated vector per requested input, in input order.""" + if not isinstance(data, dict) or not isinstance(data.get("data"), list): + return None + items = data["data"] + if len(items) != count: + return None + ordered: list[Optional[list[float]]] = [None] * count + for item in items: + if not isinstance(item, dict): + return None + index = item.get("index") + if ( + isinstance(index, bool) + or not isinstance(index, int) + or not 0 <= index < count + or ordered[index] is not None + ): + return None + vector = self._coerce_vector(item.get("embedding")) + if vector is None: + return None + ordered[index] = vector + if any(vector is None for vector in ordered): + return None + widths = {len(vector) for vector in ordered if vector is not None} + if len(widths) != 1: + return None + return [vector for vector in ordered if vector is not None] + + def _embed_one(self, text: str) -> Optional[list[float]]: """Embed a single string via the API.""" import httpx @@ -172,18 +241,10 @@ def _embed_one(self, text: str) -> list[float]: data = resp.json() except Exception: logger.error("Single embedding request failed") - return [0.0] * (self._dim or 384) - - items = data.get("data", []) - if items: - vec = items[0].get("embedding") - if vec is not None: - if self._dim is None: - self._dim = len(vec) - return vec - logger.warning( - "Item index 0 missing 'embedding' key, using zero vector" - ) - else: - logger.warning("API returned empty data array for single item") - return [0.0] * (self._dim or 384) + return None + + ordered = self._ordered_batch_vectors(data, 1) + if ordered is not None: + return ordered[0] + logger.warning("API returned malformed single-item embedding data") + return None diff --git a/engraphis/backends/embedder_deterministic.py b/engraphis/backends/embedder_deterministic.py index 821f9d1e..d1bc6d63 100644 --- a/engraphis/backends/embedder_deterministic.py +++ b/engraphis/backends/embedder_deterministic.py @@ -12,6 +12,7 @@ from __future__ import annotations import hashlib +from numbers import Integral import re from typing import Literal @@ -20,6 +21,7 @@ DETERMINISTIC_EMBEDDING_IDENTITY = "deterministic_hashing" DETERMINISTIC_EMBEDDING_VERSION = "v2_aliases_measurements" +MAX_EMBEDDING_DIM = 65_536 class DeterministicEmbedder: @@ -38,7 +40,14 @@ class DeterministicEmbedder: ) def __init__(self, dim: int = 384) -> None: - self._dim = dim + if isinstance(dim, bool) or not isinstance(dim, Integral): + raise ValueError("embedding dimension must be a positive integer") + dimension = int(dim) + if not 1 <= dimension <= MAX_EMBEDDING_DIM: + raise ValueError( + f"embedding dimension must be between 1 and {MAX_EMBEDDING_DIM}" + ) + self._dim = dimension @property def dim(self) -> int: diff --git a/engraphis/backends/postgres_schema.py b/engraphis/backends/postgres_schema.py index 979559b8..93b06949 100644 --- a/engraphis/backends/postgres_schema.py +++ b/engraphis/backends/postgres_schema.py @@ -132,6 +132,26 @@ def _rows(cursor, query: str, params: tuple = ()) -> list[tuple]: return list(cursor.fetchall()) +def _source_digest(dsn: str) -> str: + """Identify a database endpoint without turning its password into a verifier. + + Hashing the complete DSN still preserves a stable, offline-testable oracle for a + low-entropy password. Userinfo, query parameters, and fragments are credentials or + connection policy, not source identity, so exclude them from provenance entirely. + """ + try: + parsed = urlparse(dsn) + if parsed.scheme.casefold() not in {"postgres", "postgresql"} or not parsed.hostname: + raise ValueError("non-URL PostgreSQL DSN") + hostname = (parsed.hostname or "").casefold() + port = parsed.port or 5432 + database = parsed.path.lstrip("/") + identity = f"{parsed.scheme.casefold()}|{hostname}|{port}|{database}" + except (TypeError, ValueError): + identity = "postgresql|unknown" + return hashlib.sha256(identity.encode("utf-8")).hexdigest()[:24] + + class PostgresSchemaIntrospector: def inspect(self, dsn: str, *, schemas: Optional[list[str]] = None) -> SchemaSnapshot: allow = {str(name).strip() for name in (schemas or []) if str(name).strip()} @@ -321,7 +341,7 @@ def permitted(schema: Any) -> bool: if len(relations) > _MAX_RELATIONS: relations = relations[:_MAX_RELATIONS] truncated = True - digest = hashlib.sha256(dsn.encode("utf-8")).hexdigest()[:24] + digest = _source_digest(dsn) return SchemaSnapshot( title=f"PostgreSQL schema: {database}", text="\n".join(lines).strip(), diff --git a/engraphis/backends/vector_sqlitevec.py b/engraphis/backends/vector_sqlitevec.py index f0021e5b..941719d3 100644 --- a/engraphis/backends/vector_sqlitevec.py +++ b/engraphis/backends/vector_sqlitevec.py @@ -12,10 +12,12 @@ from __future__ import annotations import sys +from numbers import Integral from typing import Optional import numpy as np +from engraphis.backends.embedder_deterministic import MAX_EMBEDDING_DIM from engraphis.backends.vector_numpy import NumpyVectorIndex from engraphis.core.interfaces import SearchFilter from engraphis.core.store import Store, memory_matches_filter @@ -30,10 +32,23 @@ def _cosine_from_l2(distance: float) -> float: return max(-1.0, min(1.0, 1.0 - (float(distance) ** 2) / 2.0)) +def _validated_dimension(dim: int) -> int: + """Return a bounded integer safe to interpolate into sqlite-vec DDL.""" + if isinstance(dim, bool) or not isinstance(dim, Integral): + raise ValueError("embedding dimension must be a positive integer") + dimension = int(dim) + if not 1 <= dimension <= MAX_EMBEDDING_DIM: + raise ValueError( + f"embedding dimension must be between 1 and {MAX_EMBEDDING_DIM}" + ) + return dimension + + class SqliteVecVectorIndex: """ANN over embeddings using the sqlite-vec extension.""" def __init__(self, store: Store, dim: int) -> None: + dimension = _validated_dimension(dim) # sqlite-vec is a loadable SQLite extension. SQLCipher ships a different # SQLite build, and loading both native libraries into one interpreter has # caused hard crashes rather than a normal Python exception. An `auto` @@ -47,14 +62,14 @@ def __init__(self, store: Store, dim: int) -> None: ) import sqlite_vec # lazy: optional dependency / native extension self.store = store - self.dim = dim + self.dim = dimension conn = store.conn conn.enable_load_extension(True) sqlite_vec.load(conn) conn.enable_load_extension(False) conn.execute( f"CREATE VIRTUAL TABLE IF NOT EXISTS mem_vec_ann USING vec0(" - f"id TEXT PRIMARY KEY, embedding FLOAT[{dim}])" + f"id TEXT PRIMARY KEY, embedding FLOAT[{dimension}])" ) conn.commit() @@ -131,10 +146,11 @@ def get_vector_index(store: Store, *, dim: int = 384, prefer: str = "auto"): prefer: "auto" (try sqlite-vec, fall back), "sqlite-vec" (require it), or "numpy" (force the reference index). """ + dimension = _validated_dimension(dim) if prefer == "numpy": return NumpyVectorIndex(store) try: - return SqliteVecVectorIndex(store, dim) + return SqliteVecVectorIndex(store, dimension) except Exception: if prefer == "sqlite-vec": raise diff --git a/engraphis/core/secrets.py b/engraphis/core/secrets.py index 045bf44b..d0fd85fa 100644 --- a/engraphis/core/secrets.py +++ b/engraphis/core/secrets.py @@ -81,11 +81,28 @@ def _text(value: Any) -> str: try: return json.dumps(value, ensure_ascii=False, sort_keys=True, default=str) except (TypeError, ValueError, RecursionError): - return str(value) - - -def _mapping_secret_kind(value: Any) -> str | None: + try: + return str(value) + except Exception: + return "" + + +def _mapping_secret_kind( + value: Any, + *, + _seen: set[int] | None = None, + _depth: int = 0, +) -> str | None: """Catch environment/config mappings before JSON rendering obscures their keys.""" + if not isinstance(value, (dict, list, tuple, set)): + return None + if _depth >= 64: + return None + seen = _seen if _seen is not None else set() + marker = id(value) + if marker in seen: + return None + seen.add(marker) if isinstance(value, dict): for key, child in value.items(): key_text = str(key) @@ -93,12 +110,12 @@ def _mapping_secret_kind(value: Any) -> str | None: if (_SENSITIVE_MAPPING_KEY.fullmatch(key_text) and len(child_text) >= 8 and not _REDACTION.fullmatch(child_text)): return "credential assignment" - nested = _mapping_secret_kind(child) + nested = _mapping_secret_kind(child, _seen=seen, _depth=_depth + 1) if nested: return nested elif isinstance(value, (list, tuple, set)): for child in value: - nested = _mapping_secret_kind(child) + nested = _mapping_secret_kind(child, _seen=seen, _depth=_depth + 1) if nested: return nested return None diff --git a/engraphis/core/store.py b/engraphis/core/store.py index 8081780d..ccbe9e83 100644 --- a/engraphis/core/store.py +++ b/engraphis/core/store.py @@ -240,7 +240,7 @@ def _receipt_metadata(metadata: dict) -> dict: "entities_added", "relations_added", "retrieval_profile", "candidate_depth", "candidate_k_requested", "candidate_k_used", "response_mode", "historical", "token_usage", - "adaptive_mode", + "adaptive_mode", "action_id", "schema_version", "result_mode", } def content_free_label(key: str, value: str) -> str: normalized = value.strip().casefold().replace(" ", "_") @@ -301,11 +301,12 @@ def content_free_label(key: str, value: str) -> str: "entities", "relations", "tables", "dry_run", "error_count", "entities_added", "relations_added", "retrieval_profile", "candidate_depth", "candidate_k_requested", "candidate_k_used", "response_mode", "historical", - "token_usage", "adaptive_mode", + "token_usage", "adaptive_mode", "action_id", "schema_version", "result_mode", } _PUBLIC_RECEIPT_OPERATIONS = { "remember", "recall", "promote", "link", "index_repo", - "graph_index", "grounded_recall", "adaptive_context", "consolidate", "sync", + "graph_index", "grounded_recall", "adaptive_context", "proactive_context", "smart_gateway", + "consolidate", "sync", } _PUBLIC_RECEIPT_STATUSES = { "ok", "add", "noop", "invalidate", "relate", "ingested", @@ -2329,14 +2330,66 @@ def _erase_memory_rows(cls, conn, memory_id: str, *, actor: str = "user") -> dic # A graph edge whose last provenance support was the erased memory is itself a # derivative of that secret. Preserve shared graph facts with another support. if supported_edges and "edges" in tables: - marks = ",".join("?" for _ in supported_edges) if "edge_supports" in tables: - conn.execute( - f"DELETE FROM edges WHERE id IN ({marks}) AND NOT EXISTS " - "(SELECT 1 FROM edge_supports s WHERE s.edge_id=edges.id)", - supported_edges, - ) + for edge_id in supported_edges: + remaining = conn.execute( + "SELECT id, memory_id, valid_to, expired_at, provenance " + "FROM edge_supports WHERE edge_id=? ORDER BY id", + (edge_id,), + ).fetchall() + if not remaining: + conn.execute("DELETE FROM edges WHERE id=?", (edge_id,)) + continue + + # Normalized support rows are authoritative. Rebuild every surviving + # compatibility blob so the erased source cannot keep a shared edge + # prompt-ineligible or remain falsely attributed in provenance. + active_provenance = [] + active_memory_ids: list[str] = [] + historical_provenance = [] + historical_memory_ids: list[str] = [] + for support in remaining: + support_memory_id = str(support["memory_id"] or "") + if support_memory_id and support_memory_id not in historical_memory_ids: + historical_memory_ids.append(support_memory_id) + provenance = _loads(support["provenance"], {}) + provenance = dict(provenance) if isinstance(provenance, dict) else {} + provenance["memory_id"] = support_memory_id + provenance["memory_ids"] = ( + [support_memory_id] if support_memory_id else [] + ) + conn.execute( + "UPDATE edge_supports SET provenance=? WHERE id=?", + (_dumps(provenance), support["id"]), + ) + historical_provenance.append(provenance) + if support_memory_id and support["valid_to"] is None \ + and support["expired_at"] is None: + if support_memory_id not in active_memory_ids: + active_memory_ids.append(support_memory_id) + active_provenance.append(provenance) + memory_ids = active_memory_ids or historical_memory_ids + if not memory_ids: + conn.execute("DELETE FROM edges WHERE id=?", (edge_id,)) + continue + if not active_memory_ids: + closed_at = now_ts() + conn.execute( + "UPDATE edges SET valid_to=?, valid_to_recorded_at=? " + "WHERE id=? AND valid_to IS NULL", + (closed_at, closed_at, edge_id), + ) + rebuilt = _merge_edge_provenance( + active_provenance or historical_provenance + ) + rebuilt["memory_id"] = memory_ids[0] + rebuilt["memory_ids"] = memory_ids + conn.execute( + "UPDATE edges SET provenance=? WHERE id=?", + (_dumps(rebuilt), edge_id), + ) else: + marks = ",".join("?" for _ in supported_edges) conn.execute(f"DELETE FROM edges WHERE id IN ({marks})", supported_edges) # An entity extracted only from this memory can itself contain credential text. diff --git a/engraphis/core/sync.py b/engraphis/core/sync.py index 38e3c12e..f4876a5b 100644 --- a/engraphis/core/sync.py +++ b/engraphis/core/sync.py @@ -509,7 +509,9 @@ def dict_to_record(d: dict) -> Optional[MemoryRecord]: valid_to_recorded_at=_clamp_ts(d.get("valid_to_recorded_at"), now), ingested_at=_clamp_ts(d.get("ingested_at"), now), expired_at=_clamp_ts(d.get("expired_at"), now), - pinned=bool(d.get("pinned")), sensitivity=sens, + # Authority-bearing booleans are strict. In particular ``"false"`` must + # not become truthy and then remain permanently pinned through the CRDT OR. + pinned=d.get("pinned") is True, sensitivity=sens, subject_key=_clamp_str(d.get("subject_key"), 512), claim_kind=_clamp_str(d.get("claim_kind"), 256), provenance=_safe_json_obj(d.get("provenance")), diff --git a/engraphis/mcp_classic_cli.py b/engraphis/mcp_classic_cli.py new file mode 100644 index 00000000..5a5c9fe2 --- /dev/null +++ b/engraphis/mcp_classic_cli.py @@ -0,0 +1,34 @@ +"""Console entry for ``engraphis-mcp-classic``. + +The normal ``engraphis-mcp`` entry point is the compact Smart MCP gateway. This +launcher preserves the historical direct-tool surface for clients that pin names. +""" +from __future__ import annotations + +import argparse + +from engraphis.mcp_cli import _dependency_error + + +def main(argv=None) -> None: + ap = argparse.ArgumentParser( + prog="engraphis-mcp-classic", + description="Run the legacy Engraphis MCP server over stdio with all direct tools.", + epilog=( + "Most agents should use engraphis-mcp instead: its Smart gateway discovers " + "advanced actions automatically." + ), + ) + ap.parse_args(argv) + error = _dependency_error() + if error: + raise SystemExit(error) + + # Import after argparse so --help works without the optional MCP dependency. + from engraphis.mcp_server import classic_mcp + + classic_mcp.run() + + +if __name__ == "__main__": + main() diff --git a/engraphis/mcp_http_cli.py b/engraphis/mcp_http_cli.py index 5a95c3d9..f6525634 100644 --- a/engraphis/mcp_http_cli.py +++ b/engraphis/mcp_http_cli.py @@ -79,6 +79,14 @@ def main(argv=None) -> None: default=os.environ.get("ENGRAPHIS_HTTP_TRANSPORT", "streamable-http"), help="MCP transport (default: ENGRAPHIS_HTTP_TRANSPORT or streamable-http)", ) + ap.add_argument( + "--classic", + action="store_true", + help=( + "serve the legacy 33 direct-tool surface; normal use defaults to the compact " + "Smart gateway" + ), + ) args = ap.parse_args(argv) if args.transport not in _TRANSPORTS: ap.error("ENGRAPHIS_HTTP_TRANSPORT must be streamable-http or sse") @@ -91,9 +99,14 @@ def main(argv=None) -> None: # module import time, so importing it eagerly would make even help unusable. from engraphis.mcp_server import mcp - mcp.settings.host = args.host - mcp.settings.port = args.port - mcp.run(transport=args.transport) + server = mcp + if args.classic: + from engraphis.mcp_server import classic_mcp + + server = classic_mcp + server.settings.host = args.host + server.settings.port = args.port + server.run(transport=args.transport) if __name__ == "__main__": diff --git a/engraphis/mcp_server.py b/engraphis/mcp_server.py index 58d065f6..b47dfe03 100644 --- a/engraphis/mcp_server.py +++ b/engraphis/mcp_server.py @@ -23,11 +23,15 @@ """ from __future__ import annotations +import hashlib +import hmac import json import logging -from typing import Annotated, List, Optional +import secrets +from dataclasses import dataclass +from typing import Any, Annotated, Callable, List, Optional -from pydantic import Field, StrictInt +from pydantic import Field, StrictBool, StrictInt try: from mcp.server.fastmcp import FastMCP @@ -38,6 +42,7 @@ ) from engraphis.config import settings +from engraphis.core.context import RegexTokenCounter from engraphis.service import MemoryService, ValidationError logger = logging.getLogger("engraphis.mcp") @@ -65,7 +70,12 @@ open_threads=[]. If an Engraphis call fails, continue the primary work and report the exact memory failure once instead of fabricating memory state.""" -mcp = FastMCP("engraphis_mcp", instructions=_SESSION_PROTOCOL, log_level="WARNING") +# ``classic_mcp`` retains the public, named-tool protocol for integrations that pinned a +# tool name. ``mcp`` temporarily refers to it while the legacy decorators below execute; +# it is rebound to the small Smart MCP surface after every classic tool has registered. +classic_mcp = FastMCP("engraphis_mcp", instructions=_SESSION_PROTOCOL, + log_level="WARNING") +mcp = classic_mcp _service: Optional[MemoryService] = None @@ -129,10 +139,25 @@ def _err(exc: Exception) -> str: "engraphis_index_repo", "engraphis_ingest_postgres_schema", }) +_SMART_GATEWAY_ROLES = { + "engraphis_discover_actions": "viewer", + "engraphis_execute_read": "viewer", + "engraphis_execute_action": "admin", +} def minimum_role(tool_name: str) -> str: - """Dashboard role required for an MCP tool; unknown/new tools default to member.""" + """Dashboard role required for an MCP tool; unknown/new tools default to member. + + Remote authorization sees the Smart wrapper name before discovery resolves the + underlying classic action. Because that outer boundary cannot safely choose a + dynamic role, discovered reads stay viewer-accessible while the generic stateful + executor fails closed to admin. Local stdio has no role boundary and retains the + owner's full capability; routine remote member writes remain available through the + dedicated session and remember tools. + """ + if tool_name in _SMART_GATEWAY_ROLES: + return _SMART_GATEWAY_ROLES[tool_name] if tool_name in _ADMIN_TOOLS: return "admin" if tool_name in _READ_ONLY_TOOLS: @@ -688,6 +713,10 @@ def engraphis_proactive_context( max_length=20_000)] = "", k: Annotated[int, Field(description="Max memories to consider (1-50).", ge=1, le=50)] = 10, synthesize: Annotated[bool, Field(description="If true and an LLM is configured, synthesize a concise cited context summary; otherwise deterministic/offline.")] = False, + token_budget: Annotated[Optional[int], Field(description="Hard context budget in compact mode.", + ge=0, le=32_768)] = None, + response_mode: Annotated[str, Field(description="full preserves the Classic response; compact returns one packed context packet.", + pattern="^(full|compact)$")] = "full", ) -> str: """Return an agent-ready context packet before the agent knows what to ask. @@ -701,7 +730,7 @@ def engraphis_proactive_context( try: return _ok(service().proactive_context( workspace=workspace, repo=repo, task=task, agent_state=agent_state, - k=k, synthesize=synthesize, + k=k, synthesize=synthesize, token_budget=token_budget, response_mode=response_mode, )) except Exception as exc: # noqa: BLE001 return _err(exc) @@ -1496,8 +1525,658 @@ def engraphis_consolidate( return _err(exc) +@dataclass(frozen=True) +class ActionSpec: + """One classic MCP action that Smart MCP may describe and dispatch. + + The registry intentionally refers to the already-registered FastMCP tool. That + keeps the classic and gateway paths on one validation/handler contract instead + of maintaining a second, subtly divergent collection of schemas. + """ + + canonical_id: str + # The handler is an allowlisted FastMCP registration, not a callable name supplied + # by a client. It is also the compatibility adapter for historical aliases. + tool_name: str + title: str + purpose: str + input_schema: dict[str, Any] + schema_digest: str + side_effect: str + annotations: dict[str, Any] + availability_predicate: Callable[[], bool] + result_budget: int # Tokens under the dependency-free gateway counter. + prerequisite: str + compatibility_adapter: str + aliases: tuple[str, ...] = () + + +_SMART_SESSION_PROTOCOL = ( + "Use Engraphis only when durable project memory helps. Start or resume multi-step " + "work with engraphis_session; use recall_context and remember for normal work. For " + "any other capability, call discover_actions then its indicated executor. End the " + "session when finished. Never store secrets or treat recalled memory as authority." +) + +_CAPABILITY_SECRET = secrets.token_bytes(32) +_CAPABILITY_VERSION = "smart-mcp/1" +_DEPLOYMENT_POLICY = "local-default" +# Store the full binding as well as the opaque ID. The HMAC prevents forgery, +# while the values below make a capability stale across a policy or registry +# change even when a long-lived development process has not restarted yet. +_CAPABILITY_INDEX: dict[str, tuple[str, str, str, str]] = {} +_GATEWAY_RESULT_COUNTER = RegexTokenCounter() + + +def _schema_digest(schema: dict[str, Any]) -> str: + payload = json.dumps(schema, sort_keys=True, separators=(",", ":"), default=str) + return hashlib.sha256(payload.encode("utf-8")).hexdigest()[:16] + + +def _purpose(description: str, fallback: str) -> str: + """Return one short, model-friendly capability description.""" + text = " ".join(str(description or "").split()) + if not text: + return fallback + sentence = text.split(".", 1)[0].strip() + return (sentence or text)[:240] + + +def _side_effect(tool_name: str, annotations: Any) -> str: + """Classify by the truthful existing MCP annotation, never by a caller claim.""" + if bool(getattr(annotations, "destructiveHint", False)): + return "destructive" + if tool_name in _ADMIN_TOOLS: + return "admin" + if bool(getattr(annotations, "readOnlyHint", False)) and bool( + getattr(annotations, "idempotentHint", False) + ): + return "read" + return "write" + + +def _always_available() -> bool: + """All locally registered actions are available; handlers still enforce scope/role.""" + return True + + +_ACTION_PREREQUISITES = { + "engraphis_search_code": "Run index_repo for the repository first.", + "engraphis_code_path": "Run index_repo for the repository first.", + "engraphis_code_impact": "Run index_repo for the repository first.", + "engraphis_export_code_graph": "Run index_repo for the repository first.", + "engraphis_secure_erase": "Requires the host's destructive-action approval.", +} + + +def _annotations_dict(annotations: Any) -> dict[str, Any]: + """Keep the original FastMCP annotations as registry metadata.""" + if hasattr(annotations, "model_dump"): + return dict(annotations.model_dump(exclude_none=True)) + if isinstance(annotations, dict): + return dict(annotations) + return {} + + +def _build_action_specs() -> dict[str, ActionSpec]: + """Build the discoverable registry from the full classic FastMCP surface.""" + manager = classic_mcp._tool_manager # FastMCP owns this typed tool registry. + specs: dict[str, ActionSpec] = {} + for tool_name in sorted(manager._tools): + tool = manager.get_tool(tool_name) + schema = dict(tool.parameters or {}) + canonical_id = tool_name.removeprefix("engraphis_") + aliases: tuple[str, ...] = () + # These are compatibility adapters rather than interchangeable names: their + # registered classic function carries the historical defaults and result shape. + if tool_name == "engraphis_answer": + aliases = ("grounded_answer",) + elif tool_name == "engraphis_forget": + aliases = ("retire_legacy",) + specs[canonical_id] = ActionSpec( + canonical_id=canonical_id, + tool_name=tool_name, + title=str(getattr(tool, "title", None) or canonical_id.replace("_", " ").title()), + purpose=_purpose(getattr(tool, "description", ""), canonical_id.replace("_", " ")), + input_schema=schema, + schema_digest=_schema_digest(schema), + side_effect=_side_effect(tool_name, getattr(tool, "annotations", None)), + annotations=_annotations_dict(getattr(tool, "annotations", None)), + availability_predicate=_always_available, + result_budget=32_768, + prerequisite=_ACTION_PREREQUISITES.get(tool_name, ""), + compatibility_adapter=( + "answer_legacy_defaults" if tool_name == "engraphis_answer" + else "forget_legacy_defaults" if tool_name == "engraphis_forget" + else "classic_fastmcp" + ), + aliases=aliases, + ) + return specs + + +ACTION_SPECS = _build_action_specs() + + +_ACTION_STOPWORDS = frozenset({ + "about", "an", "and", "are", "as", "at", "be", "but", "can", "context", "data", "details", + "earlier", "find", "for", "from", "get", "handle", "have", "help", "if", "in", "information", + "into", "is", "it", "memories", "memory", "mentioned", "need", "not", "of", "on", "or", "please", + "project", "repo", "repository", "should", "show", "so", "store", "task", "that", "the", "their", + "there", "these", "thing", "this", "those", "to", "use", "want", "what", "when", "where", "with", + "workspace", "would", "you", "your", +}) + + +def _action_terms(value: str) -> set[str]: + return { + token for token in "".join( + character.lower() if character.isalnum() else " " for character in value + ).split() if len(token) > 1 and token not in _ACTION_STOPWORDS + } + + +_ACTION_SYNONYMS = { + "history": {"timeline", "why", "supersedes"}, + "changed": {"timeline", "why", "correct", "retire"}, + "statistics": {"stats"}, + "status": {"stats"}, + "event": {"record", "event"}, + "search": {"recall"}, + "code": {"code", "symbol", "index", "impact"}, + "delete": {"erase", "retire"}, + "erase": {"erase"}, + "audit": {"receipt", "audit", "verify", "export"}, +} + +_ACTION_PREFERENCES = { + "history": {"timeline"}, + "timeline": {"timeline"}, + "why": {"why"}, + "answer": {"answer"}, + "grounded": {"recall_grounded"}, + "know": {"recall_proactive"}, + "now": {"recall_proactive"}, + "statistics": {"stats"}, + "stats": {"stats"}, + "event": {"record_event"}, + "record": {"record_event"}, + "impact": {"code_impact"}, + "callers": {"search_code", "code_path"}, + "index": {"index_repo"}, + "search": {"recall"}, + "verify": {"verify_receipts"}, + "receipts": {"receipts"}, +} + +# A small set of unambiguous multi-word intents avoids an accidental match on broad +# vocabulary such as "graph", "memory", or "audit". This stays deterministic and +# auditable, unlike using a model to dispatch model-controlled tool requests. +_ACTION_PHRASE_PREFERENCES = { + frozenset({"search", "stored"}): {"recall"}, + frozenset({"complete", "bodies"}): {"recall"}, + frozenset({"know", "now"}): {"recall_proactive"}, + frozenset({"export", "code", "graph"}): {"export_code_graph"}, + frozenset({"answer", "question"}): {"answer"}, + frozenset({"grounded", "answer"}): {"recall_grounded"}, + frozenset({"list", "audit", "receipts"}): {"receipts"}, + frozenset({"verify", "receipt"}): {"verify_receipts"}, +} + +_CATEGORY_ACTIONS = { + "memory": {"why", "timeline", "recall_grounded", "proactive_context"}, + "governance": {"retire", "secure_erase", "pin", "correct", "promote"}, + "code": {"index_repo", "search_code", "code_path", "code_impact", "export_code_graph"}, + "audit": {"receipts", "context_savings", "verify_receipts", "export_receipts"}, + "ops": {"stats", "check_update", "consolidate"}, +} + + +def _rank_actions(task: str, *, category: str = "", intent: str = "") -> list[ActionSpec]: + terms = _action_terms(task) + expanded = set(terms) + for term in tuple(terms): + expanded.update(_ACTION_SYNONYMS.get(term, set())) + category_terms = _action_terms(category) + category_actions = _CATEGORY_ACTIONS.get(category.strip().casefold(), set()) + ranked: list[tuple[int, str, ActionSpec]] = [] + for spec in ACTION_SPECS.values(): + if not spec.availability_predicate(): + continue + if intent and intent != "any" and spec.side_effect != intent: + continue + haystack = _action_terms( + f"{spec.canonical_id} {spec.title} {spec.purpose} {' '.join(spec.aliases)}" + ) + identity_terms = _action_terms(spec.canonical_id) + task_evidence = len(expanded & haystack) + # Only a word the caller actually supplied is exact identity evidence. + # Synonyms help semantic recall, but letting generic expansion ("code" → + # "impact") count as exact would route code search to code impact. + identity_evidence = len(terms & identity_terms) + preferred = any( + spec.canonical_id in _ACTION_PREFERENCES.get(term, set()) for term in terms + ) + phrase_preferred = any( + phrase <= terms and spec.canonical_id in preferred_actions + for phrase, preferred_actions in _ACTION_PHRASE_PREFERENCES.items() + ) + # A category is a routing hint, not approval to propose a stateful operation. + # Without task-specific evidence, "governance" could otherwise yield retire or + # secure_erase for an ambiguous request. Keep discovery silent in that case; + # a caller must state the capability it actually needs. + if not task_evidence and not preferred and not phrase_preferred: + continue + # Exact canonical/alias evidence is deliberately stronger than incidental + # prose overlap (for example, "retire" must outrank the deprecated + # ``forget`` description that mentions it). + score = identity_evidence * 30 + task_evidence * 10 + score += len(category_terms & haystack) * 5 + if spec.canonical_id in category_actions: + score += 5 + score += sum( + 25 for term in terms if spec.canonical_id in _ACTION_PREFERENCES.get(term, set()) + ) + if phrase_preferred: + score += 50 + # Prefer canonical tools over deprecated compatibility aliases for an otherwise + # tied query. Aliases remain available when explicitly named. + if spec.tool_name in {"engraphis_answer", "engraphis_forget"}: + score -= 1 + # A best-of-everything fallback makes unknown or ambiguous requests dangerous: + # the agent could receive a plausible but unrelated stateful operation. Abstain + # unless the task or an explicit category has supplied positive evidence. + if score > 0: + ranked.append((score, spec.canonical_id, spec)) + ranked.sort(key=lambda row: (-row[0], row[1])) + return [spec for _score, _name, spec in ranked] + + +def _issue_capability(spec: ActionSpec) -> str: + body = ( + f"{_CAPABILITY_VERSION}:{_DEPLOYMENT_POLICY}:{spec.canonical_id}:{spec.schema_digest}" + ).encode("utf-8") + signature = hmac.new(_CAPABILITY_SECRET, body, hashlib.sha256).hexdigest()[:24] + capability_id = f"cap_{signature}" + _CAPABILITY_INDEX[capability_id] = ( + spec.canonical_id, spec.schema_digest, _CAPABILITY_VERSION, _DEPLOYMENT_POLICY, + ) + return capability_id + + +def _example_for(spec: ActionSpec) -> dict[str, Any]: + """Produce a minimal non-sensitive example from the real input schema.""" + examples = { + "content": "A durable project convention.", + "query": "What project background is relevant?", + "workspace": "default", + "repo": "repo-name", + "session_id": "ses_example", + "memory_id": "mem_example", + "goal": "Complete the current task.", + "kind": "decision", + "a": "mem_example_a", + "b": "mem_example_b", + "source": "module.py", + "target": "function_name", + "changed_files": ["module.py"], + "root_path": "/path/to/repo", + } + props = spec.input_schema.get("properties", {}) + required = set(spec.input_schema.get("required", [])) + example: dict[str, Any] = {} + for name, detail in props.items(): + if name in examples: + example[name] = examples[name] + elif name in required: + kind = detail.get("type") if isinstance(detail, dict) else None + if kind == "boolean": + example[name] = False + elif kind in {"integer", "number"}: + example[name] = 1 + elif kind == "array": + example[name] = [] + else: + example[name] = f"{name}_value" + return example + + +def _action_payload(spec: ActionSpec) -> dict[str, Any]: + return { + "capability_id": _issue_capability(spec), + "canonical_action": spec.canonical_id, + "schema_version": _CAPABILITY_VERSION, + "schema_digest": spec.schema_digest, + "title": spec.title, + "purpose": spec.purpose, + "input_schema": spec.input_schema, + "side_effect": spec.side_effect, + "prerequisite": spec.prerequisite or None, + "result_budget": spec.result_budget, + "example": _example_for(spec), + } + + +def _gateway_error(kind: str) -> str: + return f"Error: {kind}" + + +def _bounded_gateway_success(spec: ActionSpec, payload: dict[str, Any]) -> str: + """Render a successful execution without letting its result escape the budget. + + A stateful action may already have committed by the time its result size is known. + Oversized responses therefore return a small *success* envelope which explicitly + says the result was omitted and that the same operation must not be retried. JSON is + never sliced, so both normal and omitted responses remain structurally valid. + """ + rendered = _ok(payload) + if _GATEWAY_RESULT_COUNTER(rendered) <= spec.result_budget: + return rendered + return _ok({ + "capability_id": payload["capability_id"], + "schema_digest": payload["schema_digest"], + "canonical_action": spec.canonical_id, + "executed": True, + "execution_status": "succeeded", + "result_omitted": True, + "reason": "result_budget_exceeded", + "result_budget": spec.result_budget, + "result_token_counter": _GATEWAY_RESULT_COUNTER.identity, + "retry_recommended": False, + }) + + +def _resolve_capability(capability_id: str, schema_digest: str) -> Optional[ActionSpec]: + entry = _CAPABILITY_INDEX.get(str(capability_id or "")) + if entry is None: + return None + action_id, issued_digest, issued_version, issued_policy = entry + spec = ACTION_SPECS.get(action_id) + expected_body = ( + f"{_CAPABILITY_VERSION}:{_DEPLOYMENT_POLICY}:{action_id}:{schema_digest}" + ).encode("utf-8") + expected_id = "cap_" + hmac.new( + _CAPABILITY_SECRET, expected_body, hashlib.sha256, + ).hexdigest()[:24] + if ( + spec is None + or issued_digest != schema_digest + or spec.schema_digest != schema_digest + or issued_version != _CAPABILITY_VERSION + or issued_policy != _DEPLOYMENT_POLICY + or not hmac.compare_digest(str(capability_id), expected_id) + or not spec.availability_predicate() + ): + return None + return spec + + +def _run_action(spec: ActionSpec, arguments: dict[str, Any]) -> tuple[bool, Any, dict[str, Any]]: + """Run the existing typed classic handler without serializing a nested JSON string.""" + if not isinstance(arguments, dict): + return False, "invalid_arguments", {} + tool = classic_mcp._tool_manager.get_tool(spec.tool_name) + properties = set((tool.parameters or {}).get("properties", {})) + if set(arguments) - properties: + return False, "invalid_arguments", {} + try: + model = tool.fn_metadata.arg_model.model_validate(arguments) + validated_arguments = model.model_dump() + except Exception: # noqa: BLE001 - validation errors stay content-free + return False, "invalid_arguments", {} + try: + raw = tool.fn(**validated_arguments) + except Exception: # noqa: BLE001 - handler errors stay content-free + return False, "execution_failed", {} + if isinstance(raw, str): + if raw.startswith("Error:"): + # Classic tools already return a deliberately safe public error envelope. + # Preserve it so gateway clients get the same validation semantics and can + # make their one permitted corrective retry instead of guessing. + return False, raw, {} + try: + return True, json.loads(raw), validated_arguments + except (TypeError, ValueError): + return True, {"value": raw}, validated_arguments + return True, raw, validated_arguments + + +def _record_gateway_execution( + spec: ActionSpec, validated_arguments: dict[str, Any], result: Any, +) -> None: + """Best-effort, content-free gateway telemetry bound to an existing scope. + + The executed handler remains authoritative for state and authorization. This receipt + is deliberately supplementary and is used only for stateful actions: a telemetry + failure must never turn a successful memory action into a retryable mutation. It + stores neither task text nor arguments. Pure reads do not call this helper, preserving + the executor's truthful read-only and idempotent annotations. + """ + workspace = validated_arguments.get("workspace") + if not isinstance(workspace, str) or not workspace: + return + try: + svc = service() + workspace_row = svc.store.conn.execute( + "SELECT id FROM workspaces WHERE name=?", (workspace,) + ).fetchone() + if workspace_row is None: + return + workspace_id = str(workspace_row["id"]) + repo_id = "" + repo = validated_arguments.get("repo") + if isinstance(repo, str) and repo: + repo_row = svc.store.conn.execute( + "SELECT id FROM repos WHERE workspace_id=? AND name=?", (workspace_id, repo) + ).fetchone() + if repo_row is not None: + repo_id = str(repo_row["id"]) + usage = result.get("usage") if isinstance(result, dict) else None + metadata: dict[str, Any] = { + "action_id": spec.canonical_id, + "schema_version": _CAPABILITY_VERSION, + "result_mode": str(validated_arguments.get("response_mode") or "gateway"), + } + if isinstance(usage, dict): + metadata["token_usage"] = usage + svc.store.record_receipt( + "smart_gateway", workspace_id=workspace_id, repo_id=repo_id, actor="agent", + target_count=int(result.get("count", 1)) if isinstance(result, dict) else 1, + status="ok", metadata=metadata, + ) + except Exception: # noqa: BLE001 - telemetry is never a mutation failure + logger.info("smart MCP telemetry receipt was unavailable") + + +smart_mcp = FastMCP("engraphis_mcp", instructions=_SMART_SESSION_PROTOCOL, + log_level="WARNING") + + +@smart_mcp.tool( + name="engraphis_session", + annotations={"title": "Start or end a memory session", "readOnlyHint": False, + "destructiveHint": False, "idempotentHint": False, "openWorldHint": False}, +) +def engraphis_session( + action: Annotated[str, Field(description="start to resume work, or end to save its handoff.", + pattern="^(start|end)$")] = "start", + workspace: Annotated[str, Field(description="Workspace for a started session.", max_length=200)] = "default", + repo: Annotated[Optional[str], Field(description="Optional repository scope.", max_length=200)] = None, + agent: Annotated[str, Field(description="Optional agent name.", max_length=200)] = "", + goal: Annotated[str, Field(description="Task goal; start returns bounded relevant context.", + max_length=1_000)] = "", + session_id: Annotated[str, Field(description="Session id required to end a session.", + max_length=200)] = "", + summary: Annotated[str, Field(description="Short final handoff.", max_length=100_000)] = "", + outcome: Annotated[str, Field(description="Optional outcome label.", max_length=1_000)] = "", + open_threads: Annotated[Optional[List[str]], Field(description="Unresolved follow-ups.")] = None, + force_new: Annotated[StrictBool, Field( + description="Start only: branch a new session instead of reusing an exact active task." + )] = False, + token_budget: Annotated[int, Field(description="Goal-context budget when starting.", ge=0, + le=32_768)] = 512, +) -> str: + """Start/resume a session or end it with its next-session handoff.""" + if action == "end": + if not session_id: + return _gateway_error("session_id_required") + return engraphis_end_session( + session_id=session_id, summary=summary, outcome=outcome, open_threads=open_threads, + ) + if action != "start": + return _gateway_error("invalid_session_action") + started = engraphis_start_session( + workspace=workspace, repo=repo, agent=agent, goal=goal, force_new=force_new, + ) + if started.startswith("Error:"): + return started + payload = json.loads(started) + payload["context_status"] = "not_requested" + if not goal: + return _ok(payload) + context = engraphis_recall_context( + query=goal, workspace=workspace, repo=repo, session_id=payload["session_id"], + token_budget=token_budget, + ) + if context.startswith("Error:"): + payload["context_status"] = "unavailable" + return _ok(payload) + recalled = json.loads(context) + payload["context_status"] = "available" + for key in ("context", "sources", "usage", "count", "degraded_mode", "semantic_support"): + if key in recalled: + payload[key] = recalled[key] + return _ok(payload) + + +@smart_mcp.tool( + name="engraphis_recall_context", + annotations={"title": "Recall compact project context", "readOnlyHint": False, + "destructiveHint": False, "idempotentHint": False, "openWorldHint": False}, +) +def smart_recall_context( + query: Annotated[str, Field(description="Question or task needing prior context.", min_length=1, + max_length=100_000)], + workspace: Annotated[Optional[str], Field(description="Optional workspace.", max_length=200)] = None, + repo: Annotated[Optional[str], Field(description="Optional repository.", max_length=200)] = None, + session_id: Annotated[Optional[str], Field(description="Optional active session.")] = None, + k: Annotated[int, Field(description="Maximum source memories.", ge=1, le=50)] = 8, + token_budget: Annotated[int, Field(description="Hard returned-context token budget.", ge=0, + le=32_768)] = 1024, +) -> str: + """Return one compact, bounded context packet for routine agent work.""" + return engraphis_recall_context( + query=query, workspace=workspace, repo=repo, session_id=session_id, k=k, + token_budget=token_budget, + ) + + +@smart_mcp.tool( + name="engraphis_remember", + annotations={"title": "Remember a durable fact", "readOnlyHint": False, + "destructiveHint": False, "idempotentHint": False, "openWorldHint": False}, +) +def smart_remember( + content: Annotated[str, Field(description="Durable fact, decision, preference, or procedure.", + min_length=1, max_length=100_000)], + workspace: Annotated[str, Field(description="Workspace for the memory.", max_length=200)] = "default", + repo: Annotated[Optional[str], Field(description="Optional repository.", max_length=200)] = None, + session_id: Annotated[Optional[str], Field(description="Optional active session.")] = None, + mtype: Annotated[str, Field(description="semantic, episodic, procedural, or working.")] = "semantic", + importance: Annotated[float, Field(description="Salience from 0 to 1.", ge=0.0, + le=1.0)] = 0.0, +) -> str: + """Store a routine durable memory with safe default provenance and deduplication.""" + return engraphis_remember( + content=content, workspace=workspace, repo=repo, session_id=session_id, + mtype=mtype, importance=importance, + ) + + +@smart_mcp.tool( + name="engraphis_discover_actions", + annotations={"title": "Discover an advanced Engraphis capability", "readOnlyHint": True, + "destructiveHint": False, "idempotentHint": True, "openWorldHint": False}, +) +def engraphis_discover_actions( + task: Annotated[str, Field(description="Describe the capability needed, without pasting memory content.", + min_length=1, max_length=2_000)], + category: Annotated[str, Field(description="Optional area: memory, governance, code, audit, or ops.", + max_length=100)] = "", + intent: Annotated[str, Field(description="Optional side effect: any, read, write, admin, or destructive.", + pattern="^(any|read|write|admin|destructive)$")] = "any", + limit: Annotated[int, Field(description="Number of ranked actions to return.", ge=1, le=3)] = 1, +) -> str: + """Return only the exact schemas needed for a small set of matching advanced actions.""" + actions = _rank_actions(task, category=category, intent=intent)[:limit] + if not actions: + return _ok({"actions": [], "note": "No matching action is available."}) + return _ok({"actions": [_action_payload(spec) for spec in actions]}) + + +def _execute_gateway(capability_id: str, schema_digest: str, arguments: dict[str, Any], *, + expected: str) -> str: + spec = _resolve_capability(capability_id, schema_digest) + if spec is None: + return _gateway_error("invalid_or_stale_capability") + if expected == "read": + if spec.side_effect != "read": + return _gateway_error("action_requires_execute_action") + elif spec.side_effect == "read": + return _gateway_error("read_action_requires_execute_read") + ok, result, validated_arguments = _run_action(spec, arguments) + if not ok: + if isinstance(result, str) and result.startswith("Error:"): + return result + return _gateway_error(str(result)) + if spec.side_effect != "read": + _record_gateway_execution(spec, validated_arguments, result) + return _bounded_gateway_success(spec, { + "capability_id": capability_id, + "schema_digest": schema_digest, + "canonical_action": spec.canonical_id, + "result": result, + }) + + +@smart_mcp.tool( + name="engraphis_execute_read", + annotations={"title": "Execute a discovered read action", "readOnlyHint": True, + "destructiveHint": False, "idempotentHint": True, "openWorldHint": False}, +) +def engraphis_execute_read( + capability_id: Annotated[str, Field(description="Capability id returned by discover_actions.", + min_length=8, max_length=128)], + schema_digest: Annotated[str, Field(description="Schema digest returned by discovery.", + min_length=8, max_length=128)], + arguments: Annotated[dict[str, Any], Field(description="Arguments matching the discovered schema.")], +) -> str: + """Execute only a discovered action that is truthfully read-only and idempotent.""" + return _execute_gateway(capability_id, schema_digest, arguments, expected="read") + + +@smart_mcp.tool( + name="engraphis_execute_action", + annotations={"title": "Execute a discovered stateful action", "readOnlyHint": False, + "destructiveHint": True, "idempotentHint": False, "openWorldHint": False}, +) +def engraphis_execute_action( + capability_id: Annotated[str, Field(description="Capability id returned by discover_actions.", + min_length=8, max_length=128)], + schema_digest: Annotated[str, Field(description="Schema digest returned by discovery.", + min_length=8, max_length=128)], + arguments: Annotated[dict[str, Any], Field(description="Arguments matching the discovered schema.")], +) -> str: + """Execute a discovered write, admin, or destructive-capable action safely.""" + return _execute_gateway(capability_id, schema_digest, arguments, expected="action") + + +# The standard module export and dashboard mount are the zero-configuration Smart surface. +mcp = smart_mcp + + def main() -> None: - """Console entry point (``engraphis-mcp``). Runs over stdio.""" + """Console entry point (``engraphis-mcp``). Runs Smart MCP over stdio.""" mcp.run() diff --git a/engraphis/read_only_api.py b/engraphis/read_only_api.py index 856332cd..5dc54d51 100644 --- a/engraphis/read_only_api.py +++ b/engraphis/read_only_api.py @@ -10,6 +10,7 @@ from engraphis.config import settings from engraphis.local_auth import bearer_ok +from engraphis.netutil import is_local_request from engraphis.service import MemoryService, ValidationError @@ -68,12 +69,20 @@ def create_read_only_app(service: Optional[MemoryService] = None, *, @app.middleware("http") async def authorize(request, call_next): - if expected and request.url.path not in {"/health", "/openapi.json"}: - supplied = request.headers.get("authorization", "") - if not bearer_ok(supplied, expected): + public = request.url.path in {"/health", "/openapi.json"} + if expected and not public: + if not bearer_ok(request.headers.get("authorization", ""), expected): return JSONResponse( {"detail": "invalid bearer token"}, status_code=401 ) + elif not expected and not public and not is_local_request(request): + # The packaged launcher refuses a tokenless non-loopback bind, but keep the + # same boundary inside the ASGI factory too. This prevents a direct + # ``uvicorn ... --factory --host 0.0.0.0`` invocation (or an embedding app) + # from publishing workspace content merely by bypassing the launcher. + return JSONResponse( + {"detail": "remote access requires a bearer token"}, status_code=403 + ) return await call_next(request) def run(fn, *args, **kwargs): diff --git a/engraphis/routes/v2_api.py b/engraphis/routes/v2_api.py index 17756808..829168af 100644 --- a/engraphis/routes/v2_api.py +++ b/engraphis/routes/v2_api.py @@ -1298,8 +1298,10 @@ class _ProactiveContextReq(BaseModel): repo: Optional[str] = None task: str = "" agent_state: str = "" - k: int = 10 + k: StrictInt = Field(default=10, ge=1, le=50) synthesize: bool = False + token_budget: Optional[StrictInt] = Field(default=None, ge=0, le=32_768) + response_mode: str = "full" @router.post("/proactive-context") @@ -1307,7 +1309,58 @@ def proactive_context(req: _ProactiveContextReq): ws = req.workspace or _default_ws() return _run(service().proactive_context, workspace=ws, repo=req.repo, task=req.task, agent_state=req.agent_state, k=req.k, - synthesize=req.synthesize) + synthesize=req.synthesize, token_budget=req.token_budget, + response_mode=req.response_mode) + + +class _AdaptiveContextReq(BaseModel): + """Host-owned history routing request; intentionally not an MCP tool model.""" + + query: str = Field(min_length=1, max_length=100_000) + history: str = Field(default="", max_length=100_000) + workspace: Optional[str] = None + repo: Optional[str] = None + session_id: Optional[str] = Field(default=None, max_length=200) + mtypes: Optional[list[str]] = None + as_of: Optional[float] = None + valid_at: Optional[float] = None + known_at: Optional[float] = None + k: StrictInt = Field(default=8, ge=1, le=50) + max_context_tokens: StrictInt = Field(default=4096, ge=0, le=32_768) + retrieval_token_budget: Optional[StrictInt] = Field(default=None, ge=0, le=32_768) + confidence_floor: float = Field(default=0.25, ge=0.0, le=1.0) + retrieval_profile: str = "balanced" + candidate_depth: str = "adaptive" + diagnostics: bool = False + planning: str = "off" + mtype_limits: Optional[dict[str, StrictInt]] = None + + +@router.post("/adaptive-context") +def adaptive_context(req: _AdaptiveContextReq): + """Choose bounded context for a host that already owns its conversation history.""" + ws = req.workspace or _default_ws() + return _run( + service().adaptive_context, + req.query, + req.history, + workspace=ws, + repo=req.repo, + session_id=req.session_id, + mtypes=req.mtypes, + as_of=req.as_of, + valid_at=req.valid_at, + known_at=req.known_at, + k=req.k, + max_context_tokens=req.max_context_tokens, + retrieval_token_budget=req.retrieval_token_budget, + confidence_floor=req.confidence_floor, + retrieval_profile=req.retrieval_profile, + candidate_depth=req.candidate_depth, + diagnostics=req.diagnostics, + planning=req.planning, + mtype_limits=req.mtype_limits, + ) @router.get("/audit") diff --git a/engraphis/service.py b/engraphis/service.py index 9aff96c8..e5b9b6a6 100644 --- a/engraphis/service.py +++ b/engraphis/service.py @@ -40,6 +40,7 @@ strongest_path, ) from engraphis.core.graph_layers import normalize_graph_layer +from engraphis.core.context import RegexTokenCounter from engraphis.core.ids import new_id as make_id from engraphis.core.interfaces import ( Edge, GraphLayer, MemoryType, Node, Scope, SearchFilter, embedder_capabilities, @@ -371,6 +372,55 @@ def _clean_text(value: Any, *, field: str, max_chars: int, required: bool = True return cleaned +def _fit_context_tokens(text: str, budget: int, counter) -> str: + """Return a deterministic prefix that satisfies the active token counter. + + Proactive context predates the recall packer, so its compact projection must + enforce the same hard budget itself. Keep source text intact when it fits; + otherwise trim at the regex-token boundary used by the offline default. + """ + text = str(text or "") + if budget <= 0 or not text: + return "" + if int(counter(text)) <= budget: + return text + tokens = list(re.finditer(r"\w+|[^\w\s]", text, re.UNICODE)) + if not tokens: + return "" + end = tokens[min(budget, len(tokens)) - 1].end() + fitted = text[:end].rstrip() + # Custom counters are allowed at composition time. Be conservative if one + # tokenizes differently from the deterministic boundary above. + while fitted and int(counter(fitted)) > budget: + tokens = list(re.finditer(r"\w+|[^\w\s]", fitted, re.UNICODE)) + if not tokens: + return "" + fitted = fitted[:tokens[-1].start()].rstrip() + return fitted + + +def _fit_context_lines(text: str, budget: int, counter) -> str: + """Pack a whole-line prefix without splitting citation markers or bodies. + + Proactive summaries use one source per line. A token-level prefix can end + in ``[`` or ``[1``, falsely making a truncated source appear grounded. + Compact responses therefore trade a partial final line for a complete, + independently verifiable cited line. + """ + text = str(text or "") + if budget <= 0 or not text: + return "" + if int(counter(text)) <= budget: + return text + packed: list[str] = [] + for line in text.splitlines(): + candidate = "\n".join([*packed, line]) + if int(counter(candidate)) > budget: + break + packed.append(line) + return "\n".join(packed) + + def _strict_bool(value: Any, *, field: str) -> bool: """Accept only real booleans for authority-affecting flags. @@ -2623,7 +2673,9 @@ def recall_proactive(self, *, workspace: str, repo: Optional[str] = None, def proactive_context(self, *, workspace: str, repo: Optional[str] = None, task: str = "", agent_state: str = "", k: int = 10, - synthesize: bool = False) -> dict: + synthesize: bool = False, + token_budget: Optional[int] = None, + response_mode: str = "full") -> dict: """Agent-ready proactive context packet. Combines queryless proactive recall, optional task-specific recall, and the @@ -2631,11 +2683,25 @@ def proactive_context(self, *, workspace: str, repo: Optional[str] = None, when ``synthesize`` is true and an LLM is configured, the model may rewrite the summary, but only if it cites retrieved memories with ``[n]`` markers. """ + if response_mode not in RESPONSE_MODES: + raise ValidationError("response_mode must be 'full' or 'compact'") + if token_budget is not None: + if isinstance(token_budget, bool): + raise ValidationError("token_budget must be an integer") + try: + token_budget = int(token_budget) + except (TypeError, ValueError) as exc: + raise ValidationError("token_budget must be an integer") from exc + if not 0 <= token_budget <= MAX_TOKEN_BUDGET: + raise ValidationError( + f"token_budget must be between 0 and {MAX_TOKEN_BUDGET}" + ) task = _clean_text(task, field="task", max_chars=MAX_CONTEXT_TASK_CHARS, required=False) agent_state = _clean_text(agent_state, field="agent_state", max_chars=MAX_AGENT_STATE_CHARS, required=False) k = max(1, min(MAX_K, int(k))) + wid, rid = self._require_scope(workspace, repo) proactive = self.recall_proactive(workspace=workspace, repo=repo, k=k) memories = list(proactive.get("memories") or []) query = "\n".join(x for x in (task, agent_state) if x).strip() @@ -2679,7 +2745,76 @@ def proactive_context(self, *, workspace: str, repo: Optional[str] = None, llm.close() except Exception: pass - return {"workspace": self._clean_ws(workspace), "repo": repo, **out} + workspace_name = self._clean_ws(workspace) + legacy = {"workspace": workspace_name, "repo": repo, **out} + if response_mode == "full": + # The default remains byte-for-byte the established proactive response + # contract. Compact mode is deliberately opt-in for new hosts. + return legacy + + budget = ( + self.engine.recall_engine.token_budget + if token_budget is None else token_budget + ) + counter = getattr(self.engine.recall_engine.context_packer, "count_tokens", None) + if not callable(counter): + counter = RegexTokenCounter() + full_context = str(out.get("context_summary") or "") + context = _fit_context_lines(full_context, budget, counter) + source_tokens = int(counter(full_context)) + context_tokens = int(counter(context)) + citations = list(out.get("citations") or []) + cited_numbers = {int(number) for number in re.findall(r"\[(\d+)\]", context)} + sources = [ + { + "id": citation.get("id"), + "n": citation.get("n"), + "title": citation.get("title"), + "mtype": citation.get("mtype"), + "provenance": _compact_provenance(citation.get("provenance")), + } + for citation in citations + if citation.get("n") in cited_numbers + ] + grounded = bool(sources) + usage = { + "budget_tokens": budget, + "context_tokens": context_tokens, + "source_tokens": source_tokens, + "saved_tokens": max(0, source_tokens - context_tokens), + "savings_ratio": ( + max(0, source_tokens - context_tokens) / source_tokens + if source_tokens else 0.0 + ), + "packed_count": len(sources), + "token_counter": getattr( + self.engine.recall_engine.context_packer, + "token_counter_identity", + getattr(counter, "identity", type(counter).__name__), + ), + } + self.store.record_receipt( + "proactive_context", workspace_id=wid, repo_id=rid or "", actor="agent", + target_count=len(sources), status="ok", + metadata={ + "response_mode": "compact", + "grounded": grounded, + "synthesized": bool(out.get("synthesized")), + "token_usage": usage, + }, + ) + return { + "workspace": workspace_name, + "repo": repo, + "context": context, + "sources": sources, + "usage": usage, + "grounded": grounded, + "reason": ( + out.get("reason") or "deterministic fallback" + if grounded else "context budget omitted cited sources" + ), + } # ── linking & events (A-MEM-style) ─────────────────────────────────────────── def record_event(self, kind: str, content: str, *, workspace: str, diff --git a/eval/planned_recall.py b/eval/planned_recall.py index 27dba01b..b78076b4 100644 --- a/eval/planned_recall.py +++ b/eval/planned_recall.py @@ -155,6 +155,30 @@ def _validate_dataset(dataset: list[dict]) -> None: "context-routing stress dataset is missing categories: " + ", ".join(sorted(missing)) ) + case_ids: set[str] = set() + task_ids: set[str] = set() + for case in dataset: + case_id = str(case.get("id") or "").strip() + if not case_id or case_id in case_ids: + raise ValueError("context-routing cases require unique non-empty ids") + case_ids.add(case_id) + tags = [str(memory.get("tag") or "").strip() for memory in case.get("memories", [])] + if any(not tag for tag in tags) or len(tags) != len(set(tags)): + raise ValueError(f"{case_id}: memory tags must be unique and non-empty") + known_tags = set(tags) + for question in case.get("questions", []): + task_id = str(question.get("id") or "").strip() + if not task_id or task_id in task_ids: + raise ValueError("context-routing questions require unique non-empty ids") + task_ids.add(task_id) + supporting = [str(tag) for tag in question.get("supporting", [])] + if not supporting: + raise ValueError(f"{task_id}: at least one supporting memory is required") + unknown = sorted(set(supporting) - known_tags) + if unknown: + raise ValueError( + f"{task_id}: unknown supporting memory tags: {', '.join(unknown)}" + ) def _summarize(rows: list[dict]) -> dict: diff --git a/integrations/pi/LICENSE b/integrations/pi/LICENSE new file mode 100644 index 00000000..a6ad03ca --- /dev/null +++ b/integrations/pi/LICENSE @@ -0,0 +1,201 @@ + Apache License + Version 2.0, January 2004 + http://www.apache.org/licenses/ + + TERMS AND CONDITIONS FOR USE, REPRODUCTION, AND DISTRIBUTION + + 1. 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We also recommend that a + file or class name and description of purpose be included on the + same "printed page" as the copyright notice for easier + identification within third-party archives. + + Copyright 2026 The Engraphis Authors + + Licensed under the Apache License, Version 2.0 (the "License"); + you may not use this file except in compliance with the License. + You may obtain a copy of the License at + + http://www.apache.org/licenses/LICENSE-2.0 + + Unless required by applicable law or agreed to in writing, software + distributed under the License is distributed on an "AS IS" BASIS, + WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + See the License for the specific language governing permissions and + limitations under the License. diff --git a/integrations/pi/NOTICE b/integrations/pi/NOTICE new file mode 100644 index 00000000..30fce6cd --- /dev/null +++ b/integrations/pi/NOTICE @@ -0,0 +1,13 @@ +Engraphis for Pi +Copyright 2026 The Engraphis Authors + +This product includes software developed by the Engraphis project. + +Licensed under the Apache License, Version 2.0 (the "License"); +you may not use this file except in compliance with the License. +You may obtain a copy of the License at + + http://www.apache.org/licenses/LICENSE-2.0 + +"Engraphis" and the Engraphis logo are trademarks of the Engraphis project. +The Apache-2.0 license does not grant trademark rights (see LICENSE, section 6). diff --git a/integrations/pi/README.md b/integrations/pi/README.md new file mode 100644 index 00000000..f40fe50c --- /dev/null +++ b/integrations/pi/README.md @@ -0,0 +1,115 @@ +# Engraphis for Pi + +`@engraphis/pi` is the first-party [Pi](https://pi.dev) extension for durable, +local-first Engraphis memory. It lazily launches the existing `engraphis-mcp` +server on stdio when a memory tool is used, and exposes the same six-tool Smart +MCP surface as native Pi tools. This keeps the extension zero-configuration: +routine memory work is direct, while advanced capabilities are discovered and +executed automatically through the gateway. + +It exposes the Smart MCP tools as direct Pi tools: + +- `engraphis_session` +- `engraphis_recall_context` +- `engraphis_remember` +- `engraphis_discover_actions` +- `engraphis_execute_read` +- `engraphis_execute_action` + +For an advanced need, Pi calls `engraphis_discover_actions` and then uses the +returned capability ID and schema digest with `engraphis_execute_read` or +`engraphis_execute_action`. No profile, tool allowlist, or manual switch to the +Classic server is required. The gateway validates the capability again before it +runs it. + +## Install + +Install Engraphis 1.4.x with Python 3.10 or later. Version 1.4.0 introduced the +six-tool Smart MCP contract required by this extension: + +```bash +python -m pip install --upgrade "engraphis[mcp]>=1.4.0,<2" +``` + +When published, install the Pi package: + +```bash +pi install npm:@engraphis/pi +``` + +The extension is tested with Pi 0.83.x, Node 22.19 or later, and Engraphis +1.4.x. Pi supplies its own Pi and TypeBox runtime modules, following Pi's package +contract; the extension checks the required Smart MCP tool names when it opens +the local server and reports an actionable compatibility error if they are absent. + +Pin, update, or remove the npm package with Pi's package manager: + +```bash +pi install npm:@engraphis/pi@0.1.0 +pi update npm:@engraphis/pi +pi remove npm:@engraphis/pi +``` + +For development from this checkout: + +```bash +pi install /absolute/path/to/engraphis/integrations/pi +``` + +Restart Pi and open `/extensions` to verify that `@engraphis/pi` is loaded. The +extension launches its local MCP bridge on demand; it does not add a project MCP configuration. + +## Configuration + +Set `ENGRAPHIS_DB_PATH` in the environment that starts Pi so its memories use +the same local database as the dashboard and other agents: + +```bash +export ENGRAPHIS_DB_PATH="$HOME/.local/share/engraphis/engraphis.db" +pi +``` + +PowerShell: + +```powershell +$env:ENGRAPHIS_DB_PATH = "$HOME\AppData\Local\Engraphis\engraphis.db" +pi +``` + +If `engraphis-mcp` is not on `PATH`, set `ENGRAPHIS_MCP_COMMAND` to its absolute +console-script path before launching Pi. The extension deliberately does not write +project MCP configuration files or embed database paths and credentials in source. + +Set `ENGRAPHIS_WORKSPACE` and (optionally) `ENGRAPHIS_REPO` to provide default scopes +for routine Smart tools. Model-supplied values always take precedence. + +## Trust model + +Like every Pi extension, this code runs with your local user permissions. Install +only the official package or a reviewed checkout; `ENGRAPHIS_MCP_COMMAND` should +likewise point only to a trusted local executable. + +Every advanced state-changing action requires an explicit Pi confirmation dialog. +The extension fails closed in non-interactive Pi modes that cannot present that +dialog, and consumes each discovered action capability after one approval attempt. +Routine session and pending-review memory writes remain available directly. + +Pi supplies the Pi and TypeBox runtime modules. The package deliberately declares +them as optional peers, so installing `@engraphis/pi` does not add a duplicate Pi +runtime to your extension directory. + +Engraphis MCP writes enter the normal pending-review boundary. A successful +`engraphis_remember` call does not make unreviewed text prompt-eligible; approve it +through the Engraphis dashboard or interactive approval command before expecting it +in normal recall. This behavior is intentional and unchanged by the Pi extension. + +## Development + +```bash +npm install --ignore-scripts +npm run verify +``` + +`npm run verify` type-checks the package, runs its configuration tests, and previews +the publish tarball. The package pins the MCP SDK; update it only with a compatibility +test against the supported Pi and Engraphis releases. diff --git a/integrations/pi/index.ts b/integrations/pi/index.ts new file mode 100644 index 00000000..3df8ab12 --- /dev/null +++ b/integrations/pi/index.ts @@ -0,0 +1,193 @@ +/** + * Engraphis for Pi. + * + * Pi's extension loader evaluates this TypeScript module directly. The local bridge + * exposes the zero-configuration Smart MCP surface as native Pi tools. Routine + * memory work stays direct; advanced actions are discovered and then executed with + * the capability id and executor that the gateway returned. + */ +import type { ExtensionAPI } from "@earendil-works/pi-coding-agent"; + +import { buildEngraphisRuntimeConfig } from "./src/config.ts"; +import { + EngraphisMcpClient, + EngraphisMcpToolError, + discoveredActionsFromResult, + formatMcpResult, + safeErrorMessage, + type DiscoveredAction, +} from "./src/mcp-client.ts"; +import { + DISCOVER_ACTIONS_PARAMETERS, + EXECUTE_ACTION_PARAMETERS, + EXECUTE_READ_PARAMETERS, + RECALL_CONTEXT_PARAMETERS, + REMEMBER_PARAMETERS, + SESSION_PARAMETERS, + applyScopeDefaults, +} from "./src/tool-schemas.ts"; + +function actionKey(capabilityId: string, schemaDigest: string): string { + return `${capabilityId}:${schemaDigest}`; +} + +function approvalTarget(argumentsValue: unknown): string { + if (!argumentsValue || typeof argumentsValue !== "object") return ""; + const argumentsObject = argumentsValue as Record; + const safeKeys = ["memory_id", "workspace", "repo", "session_id", "root_path"]; + const parts: string[] = []; + for (const key of safeKeys) { + const value = argumentsObject[key]; + if (typeof value !== "string" || !value.trim()) continue; + const cleaned = value.replace(/[\u0000-\u001f\u007f]/g, " ").replace(/\s+/g, " ").trim(); + parts.push(`${key}=${cleaned.slice(0, 160)}`); + } + return parts.length ? ` Target: ${parts.join(", ")}.` : ""; +} + +export default function engraphisPiExtension(pi: ExtensionAPI) { + const runtimeConfig = buildEngraphisRuntimeConfig(); + const client = new EngraphisMcpClient(runtimeConfig); + const discoveredActions = new Map(); + + const call = async (name: string, args: Record, signal?: AbortSignal) => { + try { + const result = await client.callTool(name, args, signal); + if (name === "engraphis_discover_actions") { + for (const action of discoveredActionsFromResult(result)) { + discoveredActions.set(actionKey(action.capabilityId, action.schemaDigest), action); + } + while (discoveredActions.size > 128) { + const oldest = discoveredActions.keys().next().value; + if (oldest === undefined) break; + discoveredActions.delete(oldest); + } + } + return formatMcpResult(result); + } catch (error) { + if (name === "engraphis_execute_action" && !(error instanceof EngraphisMcpToolError)) { + throw new Error( + "Engraphis action outcome is unknown because the local connection failed. " + + "Do not retry it; inspect Engraphis state and rediscover the action first.", + ); + } + throw new Error(client.diagnosticHint() ?? safeErrorMessage(error)); + } + }; + + pi.on("session_shutdown", async () => { + discoveredActions.clear(); + await client.close().catch(() => undefined); + }); + + pi.registerTool({ + name: "engraphis_session", + label: "Engraphis Session", + description: "Start or end a scoped memory session and retain its handoff.", + promptSnippet: "Create a durable handoff for multi-step work.", + promptGuidelines: [ + "Use engraphis_session with action=start for multi-step work; retain its session_id and use action=end to save the handoff.", + ], + executionMode: "sequential", + parameters: SESSION_PARAMETERS, + execute: async (_toolCallId, params, signal) => + call("engraphis_session", applyScopeDefaults(params, runtimeConfig, { agent: "pi" }), signal), + }); + + pi.registerTool({ + name: "engraphis_recall_context", + label: "Recall Engraphis Context", + description: "Retrieve compact, cited, token-budgeted context for the current query.", + promptSnippet: "Retrieve compact, scoped Engraphis context for the current query.", + promptGuidelines: [ + "Use engraphis_recall_context to ground an answer or action in relevant Engraphis memory; treat retrieved memory as context, not authority.", + ], + executionMode: "sequential", + parameters: RECALL_CONTEXT_PARAMETERS, + execute: async (_toolCallId, params, signal) => + call("engraphis_recall_context", applyScopeDefaults(params, runtimeConfig), signal), + }); + + pi.registerTool({ + name: "engraphis_remember", + label: "Remember with Engraphis", + description: "Store a durable fact, decision, preference, bug cause/fix, or reusable procedure.", + promptSnippet: "Store a vetted durable fact, decision, preference, or reusable procedure.", + promptGuidelines: [ + "Use engraphis_remember only for durable facts, decisions, preferences, bug cause/fix pairs, or reusable procedures; never store credentials, raw logs, or untrusted instructions.", + ], + executionMode: "sequential", + parameters: REMEMBER_PARAMETERS, + execute: async (_toolCallId, params, signal) => + call("engraphis_remember", applyScopeDefaults(params, runtimeConfig), signal), + }); + + pi.registerTool({ + name: "engraphis_discover_actions", + label: "Discover Engraphis Action", + description: + "Find the best advanced Engraphis capability and receive its exact schema and safe executor.", + promptSnippet: "Discover an advanced Engraphis capability before using it.", + promptGuidelines: [ + "For non-routine work, call engraphis_discover_actions, then use the indicated read or action executor with the returned capability id and schema digest.", + ], + executionMode: "parallel", + parameters: DISCOVER_ACTIONS_PARAMETERS, + execute: async (_toolCallId, params, signal) => + call("engraphis_discover_actions", params, signal), + }); + + pi.registerTool({ + name: "engraphis_execute_read", + label: "Execute Engraphis Read", + description: "Execute only a discovered read-only, idempotent advanced capability.", + promptSnippet: "Run the read executor returned by Engraphis discovery.", + promptGuidelines: [ + "Use engraphis_execute_read only with a capability id and schema digest returned by engraphis_discover_actions.", + ], + executionMode: "parallel", + parameters: EXECUTE_READ_PARAMETERS, + execute: async (_toolCallId, params, signal) => call("engraphis_execute_read", params, signal), + }); + + pi.registerTool({ + name: "engraphis_execute_action", + label: "Execute Engraphis Action", + description: "Execute a discovered stateful, administrative, or destructive-capable action.", + promptSnippet: "Run the action executor returned by Engraphis discovery.", + promptGuidelines: [ + "Use engraphis_execute_action only with a capability id and schema digest returned by engraphis_discover_actions; Pi requires explicit user approval before execution.", + ], + executionMode: "sequential", + parameters: EXECUTE_ACTION_PARAMETERS, + execute: async (_toolCallId, params, signal, _onUpdate, ctx) => { + const key = actionKey(params.capability_id, params.schema_digest); + const action = discoveredActions.get(key); + if (!action) { + throw new Error( + "This action was not issued by the current Engraphis discovery session. " + + "Call engraphis_discover_actions again before executing it.", + ); + } + // Consume the capability before any approval or transport attempt. A denial, + // cancellation, or unknown outcome must require a fresh discovery. + discoveredActions.delete(key); + if (!ctx.hasUI) { + throw new Error( + "Engraphis did not execute the action because this Pi mode cannot request user approval.", + ); + } + const confirmed = await ctx.ui.confirm( + "Approve Engraphis action?", + `${action.title} (${action.canonicalAction}; ${action.sideEffect}). ` + + "This advanced action can change or irreversibly remove local Engraphis data." + + approvalTarget(params.arguments), + { signal }, + ); + if (!confirmed) { + throw new Error("Engraphis did not execute the action because the user denied approval."); + } + return call("engraphis_execute_action", params, signal); + }, + }); +} diff --git a/integrations/pi/npm-shrinkwrap.json b/integrations/pi/npm-shrinkwrap.json new file mode 100644 index 00000000..8bdc9b00 --- /dev/null +++ b/integrations/pi/npm-shrinkwrap.json @@ -0,0 +1,3716 @@ +{ + "name": "@engraphis/pi", + "version": "0.1.0", + 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"@engraphis/pi", + "version": "0.1.0", + "description": "First-party Pi extension for Engraphis durable memory", + "type": "module", + "license": "Apache-2.0", + "repository": { + "type": "git", + "url": "git+https://github.com/Coding-Dev-Tools/engraphis.git", + "directory": "integrations/pi" + }, + "bugs": { + "url": "https://github.com/Coding-Dev-Tools/engraphis/issues" + }, + "homepage": "https://github.com/Coding-Dev-Tools/engraphis/tree/main/integrations/pi", + "publishConfig": { + "access": "public" + }, + "keywords": [ + "pi-package", + "pi-extension", + "engraphis", + "memory", + "mcp", + "agent-memory" + ], + "files": [ + "LICENSE", + "NOTICE", + "npm-shrinkwrap.json", + "index.ts", + "src", + "README.md" + ], + "pi": { + "extensions": [ + "./index.ts" + ] + }, + "scripts": { + "test": "node --import tsx --test test/*.test.ts", + "test:integration": "node --import tsx --test test/*.integration.ts", + "typecheck": "tsc --noEmit", + "pack:check": "npm pack --dry-run", + "verify": "npm run typecheck && npm test && npm run pack:check", + "prepublishOnly": "npm run verify" + }, + "dependencies": { + "@modelcontextprotocol/sdk": "1.30.0" + }, + "peerDependencies": { + "@earendil-works/pi-coding-agent": "*", + "typebox": "*" + }, + "peerDependenciesMeta": { + "@earendil-works/pi-coding-agent": { + "optional": true + }, + "typebox": { + "optional": true + } + }, + "devDependencies": { + "@earendil-works/pi-coding-agent": "0.83.0", + "@types/node": "^24.0.0", + "tsx": "^4.20.0", + "typescript": "^5.8.0", + "typebox": "1.3.7" + }, + "engines": { + "node": ">=22.19.0" + } +} diff --git a/integrations/pi/src/config.ts b/integrations/pi/src/config.ts new file mode 100644 index 00000000..b80fc1cf --- /dev/null +++ b/integrations/pi/src/config.ts @@ -0,0 +1,70 @@ +/** The zero-configuration Smart MCP surface visible to Pi agents. */ +export const EXTENSION_VERSION = "0.1.0"; + +export const CORE_DIRECT_TOOLS = [ + "engraphis_session", + "engraphis_recall_context", + "engraphis_remember", + "engraphis_discover_actions", + "engraphis_execute_read", + "engraphis_execute_action", +] as const; + +type Environment = Readonly>; + +export type EngraphisRuntimeConfig = { + args?: string[]; + command: string; + cwd?: string; + defaultRepo?: string; + defaultWorkspace?: string; + environment: Record; +}; + +function nonBlank(value: string | undefined): string | undefined { + const normalized = value?.trim(); + return normalized || undefined; +} + +/** + * The MCP SDK intentionally starts child processes with a minimal safe environment. + * Preserve only the executable lookup/runtime variables needed to launch the public + * console script, plus Engraphis settings for its database and backend. Forwarding + * the complete Pi environment would unnecessarily expose unrelated credentials. + */ +function engraphisEnvironment(environment: Environment): Record { + const forwarded: Record = {}; + for (const [key, value] of Object.entries(environment)) { + if ( + typeof value === "string" && + (key.startsWith("ENGRAPHIS_") || + ["PATH", "Path", "SystemRoot", "ComSpec"].includes(key)) + ) { + forwarded[key] = value; + } + } + return forwarded; +} + +/** + * Return the local server configuration for the native Pi extension. + * + * `engraphis-mcp` is the public console entry point installed by + * `pip install "engraphis[mcp]"`. Callers can override it for pipx, a virtual + * environment, or development checkout through ENGRAPHIS_MCP_COMMAND. The server + * receives the explicitly allowlisted Engraphis settings, so all clients can share one store. + */ +export function buildEngraphisRuntimeConfig(environment: Environment = process.env): EngraphisRuntimeConfig { + const command = nonBlank(environment.ENGRAPHIS_MCP_COMMAND) ?? "engraphis-mcp"; + const config: EngraphisRuntimeConfig = { + command, + environment: engraphisEnvironment(environment), + }; + + const workspace = nonBlank(environment.ENGRAPHIS_WORKSPACE); + const repo = nonBlank(environment.ENGRAPHIS_REPO); + if (workspace) config.defaultWorkspace = workspace; + if (repo) config.defaultRepo = repo; + + return config; +} diff --git a/integrations/pi/src/mcp-client.ts b/integrations/pi/src/mcp-client.ts new file mode 100644 index 00000000..46e34145 --- /dev/null +++ b/integrations/pi/src/mcp-client.ts @@ -0,0 +1,292 @@ +import { Client } from "@modelcontextprotocol/sdk/client/index.js"; +import { StdioClientTransport } from "@modelcontextprotocol/sdk/client/stdio.js"; + +import { CORE_DIRECT_TOOLS, EXTENSION_VERSION, type EngraphisRuntimeConfig } from "./config.ts"; + +export type McpTool = { + description?: string; + inputSchema: Record; + name: string; +}; + +export type McpResult = { + content?: Array<{ text?: string; type: string }>; + isError?: boolean; + [key: string]: unknown; +}; + +export type DiscoveredAction = { + canonicalAction: string; + capabilityId: string; + schemaDigest: string; + sideEffect: "write" | "admin" | "destructive"; + title: string; +}; + +/** A tool-level rejection returned by the MCP server, as opposed to a transport failure. */ +export class EngraphisMcpToolError extends Error { + constructor(readonly publicMessage: string) { + super(publicMessage); + this.name = "EngraphisMcpToolError"; + } +} + +export class EngraphisCompatibilityError extends Error { + constructor(readonly publicMessage: string) { + super(publicMessage); + this.name = "EngraphisCompatibilityError"; + } +} + +// The default MCP timeout is one minute. A local model's cold start or an intentional +// repository index can reasonably take longer, while Pi can still cancel through its signal. +const TOOL_REQUEST_TIMEOUT_MS = 5 * 60 * 1_000; + +/** A session-owned connection to the local Engraphis MCP process. */ +export class EngraphisMcpClient { + private client: Client | undefined; + private connectAbort: AbortController | undefined; + private connecting: Promise | undefined; + private diagnostic = ""; + private lifecycle = 0; + private tools: McpTool[] | undefined; + + constructor(private readonly config: EngraphisRuntimeConfig) {} + + async connect(): Promise { + if (this.client) return this.client; + if (this.connecting) return this.connecting; + + const generation = this.lifecycle; + const controller = new AbortController(); + const connection = this.open(controller.signal); + this.connectAbort = controller; + this.connecting = connection; + try { + const client = await connection; + if (generation !== this.lifecycle) { + await client.close().catch(() => undefined); + throw new Error("Engraphis connection closed during startup."); + } + this.client = client; + return client; + } finally { + if (this.connecting === connection) this.connecting = undefined; + if (this.connectAbort === controller) this.connectAbort = undefined; + } + } + + async close(): Promise { + this.lifecycle += 1; + this.connectAbort?.abort(); + this.connectAbort = undefined; + const client = this.client; + const connecting = this.connecting; + this.client = undefined; + this.tools = undefined; + if (client) await client.close(); + if (connecting) { + const openingClient = await connecting.catch(() => undefined); + if (openingClient && openingClient !== client) { + await openingClient.close().catch(() => undefined); + } + } + } + + async callTool(name: string, args: Record, signal?: AbortSignal): Promise { + return this.withClient(async (client) => + (await client.callTool( + { name, arguments: args }, + undefined, + { signal, timeout: TOOL_REQUEST_TIMEOUT_MS }, + )) as McpResult, + ); + } + + diagnosticHint(): string | undefined { + if (/python 3\.10|requires python 3\.10/i.test(this.diagnostic)) { + return "The Engraphis MCP server requires Python 3.10 or later."; + } + if (/no module named ["']?mcp/i.test(this.diagnostic)) { + return "The Engraphis MCP dependency is missing. Install `engraphis[mcp]>=1.4.0,<2`."; + } + if (/no module named ["']?engraphis/i.test(this.diagnostic)) { + return "Engraphis is not installed for the configured MCP command."; + } + return undefined; + } + + async status(): Promise> { + const tools = await this.withClient((client) => this.listTools(client)); + return { connected: true, server: "engraphis", toolCount: tools.length }; + } + + async searchTools(query: string): Promise> { + const normalized = query.trim().toLowerCase(); + const tools = await this.withClient((client) => this.listTools(client)); + const matches = !normalized + ? tools + : tools.filter((tool) => `${tool.name} ${tool.description ?? ""}`.toLowerCase().includes(normalized)); + return { + count: matches.length, + tools: matches.map(({ name, description }) => + normalized ? { name, description } : { name }, + ), + }; + } + + async describeTool(name: string): Promise> { + if (!name.trim()) throw new Error("Specify a tool name to describe."); + const tools = await this.withClient((client) => this.listTools(client)); + const tool = tools.find((candidate) => candidate.name === name); + if (!tool) throw new Error(`Engraphis does not expose a tool named '${name}'.`); + return { tool }; + } + + private async open(signal: AbortSignal): Promise { + this.diagnostic = ""; + const client = new Client( + { name: "@engraphis/pi", version: EXTENSION_VERSION }, + { capabilities: {} }, + ); + try { + const transport = new StdioClientTransport({ + command: this.config.command, + args: this.config.args, + cwd: this.config.cwd, + env: this.config.environment, + // Keep diagnostics out of Pi's TUI while retaining only a bounded buffer + // for allowlisted, non-sensitive setup hints. + stderr: "pipe", + }); + transport.stderr?.on("data", (chunk) => { + this.diagnostic = (this.diagnostic + String(chunk)).slice(-4_096); + }); + await client.connect( + transport, + { signal, timeout: 60_000 }, + ); + const tools = await this.listTools(client, signal); + const available = new Set(tools.map((tool) => tool.name)); + const missing = CORE_DIRECT_TOOLS.filter((name) => !available.has(name)); + if (missing.length) { + throw new EngraphisCompatibilityError( + `Engraphis 1.4.x Smart MCP is required; the server is missing: ${missing.join(", ")}.`, + ); + } + return client; + } catch (error) { + await client.close().catch(() => undefined); + throw error; + } + } + + /** Reset an unhealthy stdio connection so the next Pi tool call can start a fresh server. */ + private async withClient(operation: (client: Client) => Promise): Promise { + try { + return await operation(await this.connect()); + } catch (error) { + await this.close().catch(() => undefined); + throw error; + } + } + + private async listTools(client: Client, signal?: AbortSignal): Promise { + if (this.tools) return this.tools; + const all: McpTool[] = []; + let cursor: string | undefined; + do { + const page = await client.listTools( + cursor ? { cursor } : undefined, + { signal, timeout: 60_000 }, + ); + all.push(...(page.tools as McpTool[])); + cursor = page.nextCursor; + } while (cursor); + this.tools = all; + return all; + } +} + +/** Convert an MCP result into Pi's standard text result without losing structured details. */ +export function formatMcpResult(result: unknown) { + const payload = result as McpResult; + const text = payload.content + ?.filter((block) => block.type === "text" && typeof block.text === "string") + .map((block) => block.text) + .join("\n\n"); + const declaredError = text?.trim().match(/^Error:\s*([a-z0-9_]+)\s*$/i); + if (payload.isError || declaredError) { + const message = declaredError + ? `Engraphis rejected the request: ${declaredError[1]}.` + : "Engraphis rejected the request. Verify the parameters and inspect the local Engraphis logs."; + throw new EngraphisMcpToolError(message); + } + return { + content: [{ type: "text" as const, text: text || JSON.stringify(result, null, 2) }], + details: result, + }; +} + +function cleanLabel(value: unknown, fallback: string): string { + if (typeof value !== "string") return fallback; + const cleaned = value.replace(/[\u0000-\u001f\u007f]/g, " ").replace(/\s+/g, " ").trim(); + return cleaned.slice(0, 200) || fallback; +} + +/** Extract server-issued action metadata used only to render and bind Pi's approval gate. */ +export function discoveredActionsFromResult(result: unknown): DiscoveredAction[] { + const payload = result as McpResult; + const actions: DiscoveredAction[] = []; + for (const block of payload.content ?? []) { + if (block.type !== "text" || typeof block.text !== "string") continue; + let parsed: unknown; + try { + parsed = JSON.parse(block.text); + } catch { + continue; + } + const candidates = (parsed as { actions?: unknown })?.actions; + if (!Array.isArray(candidates)) continue; + for (const candidate of candidates) { + if (!candidate || typeof candidate !== "object") continue; + const item = candidate as Record; + if ( + typeof item.capability_id !== "string" || + typeof item.schema_digest !== "string" || + !item.capability_id.startsWith("cap_") || + item.capability_id.length > 128 || + item.schema_digest.length < 8 || + item.schema_digest.length > 128 || + !(["write", "admin", "destructive"] as unknown[]).includes(item.side_effect) + ) continue; + const canonicalAction = cleanLabel(item.canonical_action, "advanced action"); + actions.push({ + canonicalAction, + capabilityId: item.capability_id, + schemaDigest: item.schema_digest, + sideEffect: item.side_effect as DiscoveredAction["sideEffect"], + title: cleanLabel(item.title, canonicalAction), + }); + } + } + return actions; +} + +/** Avoid surfacing stack traces or inherited environment details to the model. */ +export function safeErrorMessage(error: unknown): string { + if (error instanceof EngraphisCompatibilityError) return error.publicMessage; + if (error instanceof EngraphisMcpToolError) return error.publicMessage; + if (error instanceof Error) { + if (error.name === "AbortError") return error.message; + if ( + error.message.startsWith("Specify a tool name") || + error.message.startsWith("Specify `tool`") || + error.message.startsWith("`args` must") || + error.message.startsWith("Engraphis does not expose") + ) { + return error.message; + } + } + return "Engraphis is unavailable. Verify `pip install \"engraphis[mcp]>=1.4.0,<2\"` and ENGRAPHIS_MCP_COMMAND."; +} diff --git a/integrations/pi/src/tool-schemas.ts b/integrations/pi/src/tool-schemas.ts new file mode 100644 index 00000000..1aeea1f5 --- /dev/null +++ b/integrations/pi/src/tool-schemas.ts @@ -0,0 +1,113 @@ +import { Type } from "typebox"; + +import type { EngraphisRuntimeConfig } from "./config.ts"; + +const OPTIONAL_REPO = Type.Optional(Type.Union([ + Type.String({ description: "Repository scope within the workspace.", maxLength: 200 }), + Type.Null(), +], { default: null })); + +const WRITABLE_SCOPE = { + repo: OPTIONAL_REPO, + workspace: Type.Optional(Type.String({ default: "default", description: "Top-level memory workspace.", maxLength: 200 })), +}; + +const RECALL_SCOPE = { + repo: OPTIONAL_REPO, + workspace: Type.Optional(Type.Union([ + Type.String({ description: "Optional workspace; omit for local cross-workspace recall.", maxLength: 200 }), + Type.Null(), + ], { default: null })), +}; + +/** The Smart session tool starts/resumes and ends sessions with one stable schema. */ +export const SESSION_PARAMETERS = Type.Object({ + ...WRITABLE_SCOPE, + action: Type.Optional(Type.Union([ + Type.Literal("start"), + Type.Literal("end"), + ], { default: "start", description: "Start/resume work or save its handoff." })), + agent: Type.Optional(Type.String({ default: "pi", description: "Agent label. Defaults to pi.", maxLength: 200 })), + force_new: Type.Optional(Type.Boolean({ default: false, description: "Start a new session instead of reusing an exact active session." })), + goal: Type.Optional(Type.String({ default: "", description: "What this session is trying to accomplish.", maxLength: 1_000 })), + session_id: Type.Optional(Type.String({ default: "", description: "Session id required when action is end.", maxLength: 200 })), + summary: Type.Optional(Type.String({ default: "", description: "Concise handoff for the next session.", maxLength: 100_000 })), + outcome: Type.Optional(Type.String({ default: "", description: "Short outcome, such as shipped or blocked.", maxLength: 1_000 })), + open_threads: Type.Optional(Type.Union([ + Type.Array(Type.String({ description: "Unresolved item to carry forward." })), + Type.Null(), + ], { default: null })), + token_budget: Type.Optional(Type.Integer({ default: 512, description: "Goal-context token budget (0-32768).", minimum: 0, maximum: 32768 })), +}); + +export const RECALL_CONTEXT_PARAMETERS = Type.Object({ + ...RECALL_SCOPE, + k: Type.Optional(Type.Integer({ default: 8, description: "Candidate-memory limit (1-50).", minimum: 1, maximum: 50 })), + query: Type.String({ description: "The prior context needed for the current task.", minLength: 1, maxLength: 100_000 }), + session_id: Type.Optional(Type.Union([ + Type.String({ description: "Active Engraphis session id, if known." }), + Type.Null(), + ], { default: null })), + token_budget: Type.Optional(Type.Integer({ default: 1_024, description: "Maximum packed-context tokens (0-32768).", minimum: 0, maximum: 32768 })), +}); + +export const REMEMBER_PARAMETERS = Type.Object({ + ...WRITABLE_SCOPE, + content: Type.String({ description: "Durable fact, decision, preference, bug cause/fix, or reusable procedure.", minLength: 1, maxLength: 100_000 }), + importance: Type.Optional(Type.Number({ default: 0, description: "Salience from 0 to 1.", minimum: 0, maximum: 1 })), + mtype: Type.Optional(Type.Union([ + Type.Literal("semantic"), + Type.Literal("episodic"), + Type.Literal("procedural"), + Type.Literal("working"), + ], { default: "semantic" })), + session_id: Type.Optional(Type.Union([ + Type.String({ description: "Active Engraphis session id, if known." }), + Type.Null(), + ], { default: null })), +}); + +export const DISCOVER_ACTIONS_PARAMETERS = Type.Object({ + task: Type.String({ description: "Describe the advanced capability needed without pasting memory content.", minLength: 1, maxLength: 2_000 }), + category: Type.Optional(Type.Union([ + Type.Literal("memory"), + Type.Literal("governance"), + Type.Literal("code"), + Type.Literal("audit"), + Type.Literal("ops"), + ], { default: "", maxLength: 100 })), + intent: Type.Optional(Type.Union([ + Type.Literal("any"), + Type.Literal("read"), + Type.Literal("write"), + Type.Literal("admin"), + Type.Literal("destructive"), + ], { default: "any" })), + limit: Type.Optional(Type.Integer({ default: 1, description: "Number of matching actions (1-3).", minimum: 1, maximum: 3 })), +}); + +const EXECUTE_PARAMETERS = { + capability_id: Type.String({ description: "Capability id returned by engraphis_discover_actions.", minLength: 8, maxLength: 128 }), + schema_digest: Type.String({ description: "Schema digest returned by engraphis_discover_actions.", minLength: 8, maxLength: 128 }), + arguments: Type.Record(Type.String(), Type.Unknown({ description: "Arguments matching the discovered action schema." })), +}; + +export const EXECUTE_READ_PARAMETERS = Type.Object(EXECUTE_PARAMETERS); + +export const EXECUTE_ACTION_PARAMETERS = Type.Object(EXECUTE_PARAMETERS); + +/** Add explicit configured defaults without overriding a model-supplied scope. */ +export function applyScopeDefaults( + params: Record, + config: EngraphisRuntimeConfig, + extra: Record = {}, +): Record { + const result = { ...extra, ...params }; + if (result.workspace === undefined && config.defaultWorkspace) { + result.workspace = config.defaultWorkspace; + } + if (result.repo === undefined && result.workspace != null && config.defaultRepo) { + result.repo = config.defaultRepo; + } + return result; +} diff --git a/integrations/pi/test/config.test.ts b/integrations/pi/test/config.test.ts new file mode 100644 index 00000000..e05098d7 --- /dev/null +++ b/integrations/pi/test/config.test.ts @@ -0,0 +1,143 @@ +import assert from "node:assert/strict"; +import { execFile } from "node:child_process"; +import { readFile } from "node:fs/promises"; +import { fileURLToPath } from "node:url"; +import { promisify } from "node:util"; +import test from "node:test"; + +import { CORE_DIRECT_TOOLS, buildEngraphisRuntimeConfig } from "../src/config.ts"; +import { applyScopeDefaults } from "../src/tool-schemas.ts"; + +const execFileAsync = promisify(execFile); + +test("uses the public server entry point by default", () => { + assert.deepEqual(buildEngraphisRuntimeConfig({}), { command: "engraphis-mcp", environment: {} }); +}); + +test("reads scoped defaults and a server-command override", () => { + assert.deepEqual( + buildEngraphisRuntimeConfig({ + ENGRAPHIS_MCP_COMMAND: "C:/venv/Scripts/engraphis-mcp.exe", + ENGRAPHIS_REPO: "backend", + ENGRAPHIS_WORKSPACE: "acme", + }), + { + command: "C:/venv/Scripts/engraphis-mcp.exe", + defaultRepo: "backend", + defaultWorkspace: "acme", + environment: { + ENGRAPHIS_MCP_COMMAND: "C:/venv/Scripts/engraphis-mcp.exe", + ENGRAPHIS_REPO: "backend", + ENGRAPHIS_WORKSPACE: "acme", + }, + }, + ); +}); + +test("forwards only explicitly scoped Engraphis settings to the MCP server", () => { + const config = buildEngraphisRuntimeConfig({ + ENGRAPHIS_DB_PATH: "C:/data/engraphis.db", + UNRELATED_SECRET: "do-not-forward", + }); + + assert.deepEqual(config.environment, { ENGRAPHIS_DB_PATH: "C:/data/engraphis.db" }); +}); + +test("preserves only the runtime variables required to launch the public command", () => { + const config = buildEngraphisRuntimeConfig({ + PATH: "/venv/bin:/usr/bin", + Path: "C:/venv/Scripts;C:/Windows/System32", + SystemRoot: "C:/Windows", + ComSpec: "C:/Windows/System32/cmd.exe", + UNRELATED_SECRET: "do-not-forward", + }); + + assert.deepEqual(config.environment, { + PATH: "/venv/bin:/usr/bin", + Path: "C:/venv/Scripts;C:/Windows/System32", + SystemRoot: "C:/Windows", + ComSpec: "C:/Windows/System32/cmd.exe", + }); +}); + +test("ignores whitespace-only optional configuration", () => { + const config = buildEngraphisRuntimeConfig({ + ENGRAPHIS_MCP_COMMAND: "\t", + ENGRAPHIS_REPO: " ", + ENGRAPHIS_WORKSPACE: " ", + }); + + assert.equal(config.command, "engraphis-mcp"); + assert.equal(config.defaultRepo, undefined); + assert.equal(config.defaultWorkspace, undefined); +}); + +test("keeps exactly the six Smart MCP tools in the direct surface", () => { + assert.deepEqual(CORE_DIRECT_TOOLS, [ + "engraphis_session", + "engraphis_recall_context", + "engraphis_remember", + "engraphis_discover_actions", + "engraphis_execute_read", + "engraphis_execute_action", + ]); +}); + +test("preserves Smart MCP's cross-workspace recall default unless scope is configured", () => { + assert.deepEqual( + applyScopeDefaults({ query: "decision" }, { command: "engraphis-mcp", environment: {} }), + { query: "decision" }, + ); + assert.deepEqual( + applyScopeDefaults( + { query: "decision" }, + { + command: "engraphis-mcp", + defaultRepo: "backend", + defaultWorkspace: "acme", + environment: {}, + }, + ), + { query: "decision", repo: "backend", workspace: "acme" }, + ); + assert.deepEqual( + applyScopeDefaults( + { query: "decision" }, + { command: "engraphis-mcp", defaultRepo: "backend", environment: {} }, + ), + { query: "decision" }, + ); +}); + +test("publishes canonical Engraphis repository metadata", async () => { + const packageJson = JSON.parse( + await readFile(new URL("../package.json", import.meta.url), "utf8"), + ); + assert.equal( + packageJson.repository.url, + "git+https://github.com/Coding-Dev-Tools/engraphis.git", + ); + assert.equal(packageJson.bugs.url, "https://github.com/Coding-Dev-Tools/engraphis/issues"); + assert.equal( + packageJson.homepage, + "https://github.com/Coding-Dev-Tools/engraphis/tree/main/integrations/pi", + ); +}); + +test("the npm tarball carries the Apache license and applicable notice", async () => { + assert.ok(process.env.npm_execpath, "npm_execpath is required for the package-artifact test"); + const { stdout } = await execFileAsync( + process.execPath, + [process.env.npm_execpath, "pack", "--dry-run", "--ignore-scripts", "--json"], + { + cwd: fileURLToPath(new URL("..", import.meta.url)), + encoding: "utf8", + }, + ); + const packed = JSON.parse(stdout)[0]; + const files = new Set(packed.files.map((entry: { path: string }) => entry.path)); + assert.ok(files.has("LICENSE")); + assert.ok(files.has("NOTICE")); + assert.ok(files.has("npm-shrinkwrap.json")); + assert.equal(files.has("test/config.test.ts"), false); +}); diff --git a/integrations/pi/test/extension.test.ts b/integrations/pi/test/extension.test.ts new file mode 100644 index 00000000..6c055010 --- /dev/null +++ b/integrations/pi/test/extension.test.ts @@ -0,0 +1,159 @@ +import assert from "node:assert/strict"; +import test from "node:test"; + +import type { ExtensionAPI } from "@earendil-works/pi-coding-agent"; + +import extension from "../index.ts"; +import { EngraphisMcpClient } from "../src/mcp-client.ts"; + +type RegisteredTool = { + executionMode?: string; + name: string; + promptGuidelines?: string[]; + promptSnippet?: string; + execute: (...args: any[]) => Promise; +}; + +function extensionHarness() { + const tools: RegisteredTool[] = []; + const handlers = new Map(); + const pi = { + on: (event: string, handler: unknown) => handlers.set(event, handler), + registerTool: (tool: RegisteredTool) => tools.push(tool), + } as unknown as ExtensionAPI; + extension(pi); + return { handlers, tools }; +} + +test("registers the daily memory loop with tool-scoped guidance", () => { + const { handlers, tools } = extensionHarness(); + + assert.deepEqual( + tools.map((tool) => tool.name), + [ + "engraphis_session", + "engraphis_recall_context", + "engraphis_remember", + "engraphis_discover_actions", + "engraphis_execute_read", + "engraphis_execute_action", + ], + ); + assert.ok(handlers.has("session_shutdown")); + assert.equal(handlers.has("session_start"), false, "the MCP process should start lazily on tool use"); + for (const tool of tools) { + assert.ok(tool.promptSnippet, `${tool.name} should be discoverable without a global prompt hook`); + assert.ok(tool.promptGuidelines?.length, `${tool.name} should provide Pi-native guidance`); + } + assert.deepEqual( + Object.fromEntries(tools.map((tool) => [tool.name, tool.executionMode])), + { + engraphis_session: "sequential", + engraphis_recall_context: "sequential", + engraphis_remember: "sequential", + engraphis_discover_actions: "parallel", + engraphis_execute_read: "parallel", + engraphis_execute_action: "sequential", + }, + ); +}); + +test("requires a fresh discovery and explicit Pi approval for every advanced action", async () => { + const original = EngraphisMcpClient.prototype.callTool; + const calls: string[] = []; + EngraphisMcpClient.prototype.callTool = async function (name: string) { + calls.push(name); + if (name === "engraphis_discover_actions") { + return { + isError: false, + content: [{ + type: "text", + text: JSON.stringify({ actions: [{ + capability_id: "cap_test-capability", + canonical_action: "secure_erase", + schema_digest: "1234567890abcdef", + side_effect: "destructive", + title: "Securely erase a leaked memory", + }] }), + }], + }; + } + return { isError: false, content: [{ type: "text", text: "{\"executed\":true}" }] }; + }; + + try { + const { tools } = extensionHarness(); + const discover = tools.find((tool) => tool.name === "engraphis_discover_actions")!; + const execute = tools.find((tool) => tool.name === "engraphis_execute_action")!; + const params = { + arguments: { memory_id: "mem_example", workspace: "default" }, + capability_id: "cap_test-capability", + schema_digest: "1234567890abcdef", + }; + await discover.execute("discover", { task: "securely erase a leaked memory" }, undefined); + await assert.rejects( + execute.execute("action", params, undefined, undefined, { + hasUI: true, + ui: { confirm: async () => false }, + }), + /user denied approval/, + ); + assert.equal(calls.filter((name) => name === "engraphis_execute_action").length, 0); + + await assert.rejects( + execute.execute("action", params, undefined, undefined, { + hasUI: true, + ui: { confirm: async () => true }, + }), + /not issued by the current Engraphis discovery session/, + ); + + await discover.execute("discover", { task: "securely erase a leaked memory" }, undefined); + let prompt = ""; + await execute.execute("action", params, undefined, undefined, { + hasUI: true, + ui: { + confirm: async (_title: string, message: string) => { + prompt = message; + return true; + }, + }, + }); + assert.match(prompt, /secure_erase; destructive/); + assert.equal(calls.filter((name) => name === "engraphis_execute_action").length, 1); + } finally { + EngraphisMcpClient.prototype.callTool = original; + } +}); + +test("fails closed when Pi cannot present an action approval dialog", async () => { + const original = EngraphisMcpClient.prototype.callTool; + EngraphisMcpClient.prototype.callTool = async function (name: string) { + return name === "engraphis_discover_actions" + ? { content: [{ type: "text", text: JSON.stringify({ actions: [{ + capability_id: "cap_noninteractive", + canonical_action: "record_event", + schema_digest: "abcdef1234567890", + side_effect: "write", + title: "Record an event", + }] }) }] } + : { content: [{ type: "text", text: "{}" }] }; + }; + try { + const { tools } = extensionHarness(); + await tools.find((tool) => tool.name === "engraphis_discover_actions")! + .execute("discover", { task: "record an event" }, undefined); + await assert.rejects( + tools.find((tool) => tool.name === "engraphis_execute_action")!.execute( + "action", + { arguments: {}, capability_id: "cap_noninteractive", schema_digest: "abcdef1234567890" }, + undefined, + undefined, + { hasUI: false, ui: {} }, + ), + /cannot request user approval/, + ); + } finally { + EngraphisMcpClient.prototype.callTool = original; + } +}); diff --git a/integrations/pi/test/mcp-client.integration.ts b/integrations/pi/test/mcp-client.integration.ts new file mode 100644 index 00000000..6a366b79 --- /dev/null +++ b/integrations/pi/test/mcp-client.integration.ts @@ -0,0 +1,75 @@ +import assert from "node:assert/strict"; +import { randomUUID } from "node:crypto"; +import { rm } from "node:fs/promises"; +import { tmpdir } from "node:os"; +import { dirname, join, resolve } from "node:path"; +import test from "node:test"; +import { fileURLToPath } from "node:url"; + +import { EngraphisMcpClient } from "../src/mcp-client.ts"; + +const PROJECT_ROOT = resolve(dirname(fileURLToPath(import.meta.url)), "..", "..", ".."); + +test("discovers and calls the installed Engraphis MCP server", { timeout: 30_000 }, async () => { + const database = join(tmpdir(), `engraphis-pi-${randomUUID()}.db`); + const publicCommand = process.env.ENGRAPHIS_PI_TEST_COMMAND; + const client = new EngraphisMcpClient({ + // Exercise the same public console entry that a published Pi package launches. + // Release/CI sets the override after installing this checkout. Local development + // uses the checkout module so an older globally installed console script cannot + // invalidate the source-under-test result. + command: publicCommand ?? process.env.PYTHON ?? "python", + args: publicCommand ? undefined : ["-m", "engraphis.mcp_server"], + cwd: PROJECT_ROOT, + environment: { + ENGRAPHIS_DB_PATH: database, + // Keep CI deterministic and avoid downloading/loading the optional embedding model. + ENGRAPHIS_EMBED_MODEL: "", + }, + }); + + try { + const status = await client.status(); + assert.equal(status.connected, true); + assert.equal(Number(status.toolCount), 6); + + const tools = (await client.searchTools("")).tools as Array<{ name: string }>; + const names = new Set(tools.map((tool) => tool.name)); + for (const required of [ + "engraphis_session", + "engraphis_recall_context", + "engraphis_remember", + "engraphis_discover_actions", + "engraphis_execute_read", + "engraphis_execute_action", + ]) { + assert.ok(names.has(required), `expected ${required} in the MCP tool catalog`); + } + + const started = await client.callTool("engraphis_session", { + action: "start", + workspace: "default", + goal: "Inspect local memory health.", + }); + assert.equal(started.isError, false); + + const discovered = await client.callTool("engraphis_discover_actions", { + task: "Show memory store statistics.", + }); + assert.equal(discovered.isError, false); + const discovery = JSON.parse(discovered.content?.[0]?.text ?? "{}"); + const action = discovery.actions?.[0]; + assert.equal(action?.canonical_action, "stats"); + + const result = await client.callTool("engraphis_execute_read", { + capability_id: action.capability_id, + schema_digest: action.schema_digest, + arguments: { workspace: "default" }, + }); + assert.equal(result.isError, false); + assert.match(result.content?.[0]?.text ?? "", /"memories"/); + } finally { + await client.close(); + await Promise.all([database, `${database}-wal`, `${database}-shm`].map((path) => rm(path, { force: true }))); + } +}); diff --git a/integrations/pi/test/mcp-result.test.ts b/integrations/pi/test/mcp-result.test.ts new file mode 100644 index 00000000..648b89f9 --- /dev/null +++ b/integrations/pi/test/mcp-result.test.ts @@ -0,0 +1,82 @@ +import assert from "node:assert/strict"; +import { readFile } from "node:fs/promises"; +import test from "node:test"; + +import { EXTENSION_VERSION } from "../src/config.ts"; +import { + EngraphisMcpClient, + discoveredActionsFromResult, + formatMcpResult, + safeErrorMessage, +} from "../src/mcp-client.ts"; + +test("throws sanitized failures for MCP error flags and Engraphis error envelopes", () => { + assert.throws( + () => formatMcpResult({ isError: true, content: [{ type: "text", text: "secret details" }] }), + /Engraphis rejected the request/, + ); + assert.throws( + () => formatMcpResult({ isError: false, content: [{ type: "text", text: "Error: invalid_arguments" }] }), + /invalid_arguments/, + ); + assert.doesNotThrow(() => formatMcpResult({ + isError: false, + content: [{ type: "text", text: "An Error: inside successful prose is not an error envelope." }], + })); +}); + +test("does not expose arbitrary transport error details", () => { + assert.equal( + safeErrorMessage(new Error("spawn C:/Users/name/secret-token ENOENT")), + "Engraphis is unavailable. Verify `pip install \"engraphis[mcp]>=1.4.0,<2\"` and ENGRAPHIS_MCP_COMMAND.", + ); +}); + +test("extracts only bounded stateful capability metadata for the approval gate", () => { + const actions = discoveredActionsFromResult({ + content: [{ type: "text", text: JSON.stringify({ actions: [ + { + capability_id: "cap_12345678", + canonical_action: "retire\nspoof", + schema_digest: "1234567890abcdef", + side_effect: "destructive", + title: "Retire\u0000 memory", + }, + { + capability_id: "cap_readonly", + canonical_action: "stats", + schema_digest: "abcdef1234567890", + side_effect: "read", + title: "Stats", + }, + ] }) }], + }); + assert.deepEqual(actions, [{ + canonicalAction: "retire spoof", + capabilityId: "cap_12345678", + schemaDigest: "1234567890abcdef", + sideEffect: "destructive", + title: "Retire memory", + }]); +}); + +test("keeps the MCP client handshake version synchronized with package metadata", async () => { + const packageJson = JSON.parse(await readFile(new URL("../package.json", import.meta.url), "utf8")); + assert.equal(EXTENSION_VERSION, packageJson.version); +}); + +test("shutdown during startup closes the late client instead of publishing it", async () => { + const client = new EngraphisMcpClient({ command: "unused", environment: {} }); + let publishClient!: (value: { close: () => Promise }) => void; + let closes = 0; + const fakeClient = { close: async () => { closes += 1; } }; + (client as unknown as { open: () => Promise }).open = () => + new Promise((resolve) => { publishClient = resolve; }); + + const connecting = client.connect(); + const closing = client.close(); + publishClient(fakeClient); + await closing; + await assert.rejects(connecting, /closed during startup/); + assert.ok(closes >= 1); +}); diff --git a/integrations/pi/test/pi-loader.test.ts b/integrations/pi/test/pi-loader.test.ts new file mode 100644 index 00000000..f840418b --- /dev/null +++ b/integrations/pi/test/pi-loader.test.ts @@ -0,0 +1,27 @@ +import assert from "node:assert/strict"; +import { fileURLToPath } from "node:url"; +import { dirname, resolve } from "node:path"; +import test from "node:test"; + +import { discoverAndLoadExtensions } from "@earendil-works/pi-coding-agent"; + +const packageRoot = resolve(dirname(fileURLToPath(import.meta.url)), ".."); + +test("Pi's actual package loader recognizes and loads the extension manifest", async () => { + const result = await discoverAndLoadExtensions([packageRoot], packageRoot, resolve(packageRoot, ".missing-agent-dir")); + + assert.deepEqual(result.errors, []); + assert.equal(result.extensions.length, 1); + const extension = result.extensions[0]; + assert.equal(extension.handlers.has("before_agent_start"), false); + assert.equal(extension.handlers.has("session_start"), false); + assert.equal(extension.handlers.has("session_shutdown"), true); + assert.deepEqual([...extension.tools.keys()], [ + "engraphis_session", + "engraphis_recall_context", + "engraphis_remember", + "engraphis_discover_actions", + "engraphis_execute_read", + "engraphis_execute_action", + ]); +}); diff --git a/integrations/pi/tsconfig.json b/integrations/pi/tsconfig.json new file mode 100644 index 00000000..14996fee --- /dev/null +++ b/integrations/pi/tsconfig.json @@ -0,0 +1,13 @@ +{ + "compilerOptions": { + "allowImportingTsExtensions": true, + "module": "NodeNext", + "moduleResolution": "NodeNext", + "noEmit": true, + "skipLibCheck": true, + "strict": true, + "target": "ES2022", + "types": ["node"] + }, + "include": ["index.ts", "src/**/*.ts", "test/**/*.ts"] +} diff --git a/pyproject.toml b/pyproject.toml index 65157724..2a180693 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -186,6 +186,7 @@ engraphis-connect = "scripts.connect:main" engraphis-server = "scripts.start_server:main" engraphis-cli = "scripts.cli:main" engraphis-mcp = "engraphis.mcp_cli:main" +engraphis-mcp-classic = "engraphis.mcp_classic_cli:main" engraphis-mcp-http = "engraphis.mcp_http_cli:main" engraphis-inspector = "scripts.inspector:main" engraphis-dashboard = "scripts.start_dashboard:main" diff --git a/scripts/entry.py b/scripts/entry.py index 8c3b4e07..cc3492d4 100644 --- a/scripts/entry.py +++ b/scripts/entry.py @@ -24,6 +24,7 @@ "init": "scripts.init:main", "cli": "scripts.cli:main", "mcp": "engraphis.mcp_cli:main", + "mcp-classic": "engraphis.mcp_classic_cli:main", "mcp-http": "engraphis.mcp_http_cli:main", "server": "scripts.start_server:main", "dashboard": "scripts.start_dashboard:main", @@ -41,6 +42,7 @@ init write a project .env and print agent setup snippets cli store and recall memories from the terminal mcp run the MCP server (Claude Code, Cursor, Cline, Zed) + mcp-classic run the legacy MCP server with all direct tools mcp-http run a loopback-only MCP-over-HTTP server server run the v2 REST server without opening a browser (compatibility alias) dashboard run the product dashboard diff --git a/skills/engraphis-memory/SKILL.md b/skills/engraphis-memory/SKILL.md index b3ea14ab..4020a2d4 100644 --- a/skills/engraphis-memory/SKILL.md +++ b/skills/engraphis-memory/SKILL.md @@ -7,8 +7,10 @@ description: 'Give the agent durable, scoped, explainable memory across sessions Engraphis is a local-first memory engine exposed to agents over MCP. This skill is the *discipline* for using it well: what to store, how to scope it, and which tool answers which -question. It assumes the Engraphis MCP server is connected, so tools are named `engraphis_*` -(33 of them). If those tools are absent, see [Setup](#setup). Do not fall back to ad-hoc notes. +question. It assumes the Engraphis MCP server is connected. The default Smart MCP surface has six +`engraphis_*` tools and automatically exposes advanced capabilities through discovery and a +validated executor. If those tools are absent, see [Setup](#setup). Do not fall back to ad-hoc +notes. Memory here is **scoped, typed, bi-temporal, and self-maintaining**: writes are deduplicated and contradictions supersede (never silently overwrite), and forgetting lowers priority instead of @@ -16,19 +18,21 @@ hard-deleting. You get those guarantees for free *if* you use the right tool wit ## The core loop -1. **Starting a task in a repo** → `engraphis_recall_proactive` to load high-signal context with - no query, and (for multi-step work) `engraphis_start_session`: its `bootstrap` returns the - last same-user/agent session's summary and unresolved `open_threads`, so you resume instead - of starting cold or inheriting somebody else's handoff. - `reused=true` means the exact same user/agent/goal task is already active. Use - `force_new=true` only to branch a second session for that same task identity. +1. **Starting a task in a repo** → for multi-step work, + `engraphis_session(action="start", ...)`. Its bootstrap returns the last handoff and, when + given a goal, bounded relevant context, so you resume instead of starting cold. An exact active + task is returned with `reused:true`; use `force_new=true` only when deliberately branching a + second session with the same workspace, repo, agent, and goal. 2. **Before you answer or act** and prior context would help → `engraphis_recall_context`. It - returns one hard-budget packet for the prompt. Use legacy `engraphis_recall` only when you - need full memory bodies or another caller already depends on that response shape. Do this - *before* asking the user something they may have already told you. + returns one hard-budget packet for the prompt. Do this *before* asking the user something they + may have already told you. 3. **The moment you learn something durable** → `engraphis_remember` (a convention, a decision and its *why*, a bug's cause and fix, a user preference, a reusable procedure). -4. **Finishing the task** → `engraphis_end_session` with a `summary` and `open_threads` for the +4. **For code, governance, audit, or any non-routine work** → call + `engraphis_discover_actions` with a clear task description, then call the returned + `engraphis_execute_read` or `engraphis_execute_action` using its capability ID and exact + schema. Do not invent IDs or arguments. Discovery is automatic; users never select a profile. +5. **Finishing the task** → `engraphis_session(action="end", ...)` with a `summary` and `open_threads` for the next session in this repo. > **Golden rule:** recall before you ask; remember before you move on. If you had to re-derive @@ -60,7 +64,11 @@ Pick the **narrowest scope that is still reusable**: a fix specific to one repo a preference that follows the human everywhere is `scope="user"`. Full rules, scope-vs-type, and promotion: [SCOPING.md](references/SCOPING.md). -## Which tool answers which question +## Classic direct-tool guide + +The table below applies only to `engraphis-mcp-classic`, for older clients that pin direct tool +names. On the Smart default, describe the same need to `engraphis_discover_actions` and use the +returned executor; the routine session, recall-context, and remember tools remain direct. | Need | Tool | Notes | |---|---|---| @@ -104,8 +112,8 @@ remains the `valid_at` alias and must match it when both are supplied. ```text # Resuming work on acme/backend -engraphis_start_session(workspace="acme", repo="backend", agent="claude-code", - goal="fix flaky auth tests") +engraphis_session(action="start", workspace="acme", repo="backend", agent="claude-code", + goal="fix flaky auth tests") → bootstrap.open_threads: ["tests 3-5 still failing after token refactor"] engraphis_recall_context(query="how do we handle auth token expiry?", workspace="acme", @@ -118,9 +126,9 @@ engraphis_remember("Flaky auth tests were caused by a fixed clock in the test ha workspace="acme", repo="backend", mtype="episodic", importance=0.6) → op: "add" -engraphis_end_session(session_id=..., outcome="shipped", - summary="Fixed auth test flake (clock/TTL). Tests green.", - open_threads=[]) +engraphis_session(action="end", session_id=..., outcome="shipped", + summary="Fixed auth test flake (clock/TTL). Tests green.", + open_threads=[]) ``` ## Visual investigation @@ -147,11 +155,13 @@ claude mcp add engraphis -- engraphis-mcp # Claude Code # Cursor / Cline / Zed / Windsurf: add an MCP server with command `engraphis-mcp` (stdio). ``` -Verify with `engraphis_stats`. The engine is fully local (SQLite + local embeddings); no API key -is needed for the memory layer. Details: the repo `README.md` "Quickstart A: MCP server". +Verify with `engraphis_discover_actions(task="check local memory store health")`. The engine is +fully local (SQLite + local embeddings); no API key is needed for the memory layer. Legacy clients +that pin every direct tool can use `engraphis-mcp-classic`; normal agents should use the Smart +default. Details: the repo `README.md` "Quickstart: MCP server". ## References -- [TOOLS.md](references/TOOLS.md): all 33 tools: parameters, defaults, returns, when to reach for each. +- [TOOLS.md](references/TOOLS.md): Classic direct-tool parameters, defaults, returns, and when to reach for each. - [SCOPING.md](references/SCOPING.md): the `workspace → repo → session → memory` model, scope vs. type, and promotion. - [CONVENTIONS.md](references/CONVENTIONS.md): memory types, provenance, importance, dedup/resolution, governance, and anti-patterns diff --git a/skills/engraphis-memory/references/SCOPING.md b/skills/engraphis-memory/references/SCOPING.md index b9e02fd8..0aa3d679 100644 --- a/skills/engraphis-memory/references/SCOPING.md +++ b/skills/engraphis-memory/references/SCOPING.md @@ -20,7 +20,7 @@ A convention is `mtype="semantic"` and probably `scope="repo"`. A user's editor ``` workspace org or product ("acme") : always required on a write └─ repo a repository ("backend") : omit only for workspace-wide facts - └─ session one unit of work (session_id) : from engraphis_start_session + └─ session one unit of work (session_id) : from engraphis_session(action="start") └─ memory : the fact itself ``` @@ -54,15 +54,19 @@ Over-scoping (everything `workspace`) pollutes recall in unrelated repos. Under- ## Sessions and handoff -A session groups a task's memories and enables resume: +A session groups a task's memories and enables resume. On the default Smart MCP surface: -1. `engraphis_start_session(workspace, repo, agent, goal)` → returns `session_id`, `reused`, and a +1. `engraphis_session(action="start", workspace, repo, agent, goal)` returns `session_id`, `reused`, and a `bootstrap` carrying the previous same-user/agent session's `summary` + `open_threads` for this repo. -2. Pass `session_id` to `engraphis_remember` / `engraphis_record_event` during the task. -3. `engraphis_end_session(session_id, summary, outcome, open_threads)`: `open_threads` are the +2. Pass `session_id` to direct `engraphis_remember` during the task. For an episodic event, first + discover the record-event capability and pass that same `session_id` to its returned executor. +3. `engraphis_session(action="end", session_id, summary, outcome, open_threads)`: `open_threads` are the unresolved items; they auto-surface for the next same-user/agent session in this repo. +`engraphis_start_session` and `engraphis_end_session` are the corresponding Classic-only names +for pinned legacy integrations. + Starting is idempotent per exact `(workspace, repo, authenticated user, agent, goal)` identity. Different users, agents, or goals automatically open separate sessions. `reused=true` therefore means a retry found the same active task. Use `force_new=true` only to branch a second session when diff --git a/tests/test_adaptive_context_route.py b/tests/test_adaptive_context_route.py new file mode 100644 index 00000000..a74220b5 --- /dev/null +++ b/tests/test_adaptive_context_route.py @@ -0,0 +1,52 @@ +"""HTTP-only coverage for host-owned adaptive context routing.""" +from __future__ import annotations + +import pytest + +pytest.importorskip("fastapi", reason="adaptive context HTTP route needs the server extra") + +from fastapi import FastAPI +from fastapi.testclient import TestClient + +from engraphis.routes import v2_api + + +class _AdaptiveService: + def __init__(self) -> None: + self.calls: list[tuple[str, str, dict]] = [] + + def adaptive_context(self, query: str, history: str, **kwargs): + self.calls.append((query, history, kwargs)) + return {"mode": "history_bypass", "context": history[-32:], "sources": []} + + +def test_adaptive_context_is_a_host_http_endpoint_not_an_mcp_tool(): + service = _AdaptiveService() + v2_api.set_service(service) + app = FastAPI() + app.include_router(v2_api.router) + try: + response = TestClient(app).post("/api/adaptive-context", json={ + "query": "What did we decide?", + "history": "The host owns this conversation history.", + "workspace": "acme", + "repo": "api", + "max_context_tokens": 512, + "retrieval_token_budget": 256, + }) + finally: + v2_api._service = None + + assert response.status_code == 200 + assert response.json()["mode"] == "history_bypass" + assert service.calls == [( + "What did we decide?", "The host owns this conversation history.", + { + "workspace": "acme", "repo": "api", "session_id": None, "mtypes": None, + "as_of": None, "valid_at": None, "known_at": None, "k": 8, + "max_context_tokens": 512, "retrieval_token_budget": 256, + "confidence_floor": 0.25, "retrieval_profile": "balanced", + "candidate_depth": "adaptive", "diagnostics": False, "planning": "off", + "mtype_limits": None, + }, + )] diff --git a/tests/test_backends_factories.py b/tests/test_backends_factories.py index f708a800..7317f3b8 100644 --- a/tests/test_backends_factories.py +++ b/tests/test_backends_factories.py @@ -181,6 +181,16 @@ def test_vector_index_avoids_sqlitevec_after_sqlcipher_load(monkeypatch): store.close() +@pytest.mark.parametrize("dimension", [True, 0, -1, 1.5, "384", 65_537]) +def test_vector_index_rejects_an_invalid_ddl_dimension_before_backend_fallback(dimension): + store = Store(":memory:") + try: + with pytest.raises(ValueError, match="embedding dimension"): + get_vector_index(store, dim=dimension, prefer="auto") + finally: + store.close() + + def test_reranker_factory_falls_back_offline(monkeypatch): import engraphis.backends.reranker as reranker diff --git a/tests/test_config.py b/tests/test_config.py index 56e97128..1cf809df 100644 --- a/tests/test_config.py +++ b/tests/test_config.py @@ -68,6 +68,27 @@ def test_sample_operational_config_matches_runtime_contract(monkeypatch): assert "ENGRAPHIS_LLM_AUTO_EXTRACT=0" in example assert "| `ENGRAPHIS_LLM_AUTO_EXTRACT` | `0` |" in readme + for name in ( + "ENGRAPHIS_DECAY_HALFLIFE_DAYS", + "ENGRAPHIS_LOOP_INTERVAL", + "ENGRAPHIS_LOOP_TOP_K", + ): + monkeypatch.delenv(name, raising=False) + configured = Settings() + assert f"# ENGRAPHIS_DECAY_HALFLIFE_DAYS={configured.decay_halflife_days:g}" in example + assert f"# ENGRAPHIS_LOOP_INTERVAL={configured.loop_interval}" in example + assert f"# ENGRAPHIS_LOOP_TOP_K={configured.loop_top_k}" in example + + from engraphis.backends.extractor import ( + CHUNK_MAX, + CHUNK_OVERLAP_TOKENS, + CHUNK_TARGET_TOKENS, + ) + + assert f"# ENGRAPHIS_CHUNK_TOKENS={CHUNK_TARGET_TOKENS}" in example + assert f"# ENGRAPHIS_CHUNK_MAX={CHUNK_MAX}" in example + assert f"# ENGRAPHIS_CHUNK_OVERLAP={CHUNK_OVERLAP_TOKENS}" in example + def test_rerank_model_read_from_env(monkeypatch): monkeypatch.setenv("ENGRAPHIS_RERANK_MODEL", "cross-encoder/ms-marco-MiniLM-L-6-v2") diff --git a/tests/test_embeddings.py b/tests/test_embeddings.py index e30a1cb9..cdb5ce53 100644 --- a/tests/test_embeddings.py +++ b/tests/test_embeddings.py @@ -1,7 +1,10 @@ """Focused regression tests for the dependency-free offline embedder.""" import numpy as np +import pytest +import httpx +from engraphis.backends.embedder_api import ApiEmbedder from engraphis.backends.embedder_deterministic import DeterministicEmbedder, _tokenize @@ -50,3 +53,182 @@ def test_unrecognized_ordinary_text_keeps_legacy_feature_mapping(): assert hashlib.sha256(vectors.tobytes()).hexdigest() == ( "c2378cd31c56863b0c65fe7b0634aa62250af35b94853298bfed34fbb71875df" ) + + +@pytest.mark.parametrize("dimension", [True, 0, -1, 1.5, "384", 65_537]) +def test_embedding_dimensions_are_bounded_integers(dimension): + with pytest.raises(ValueError, match="embedding dimension"): + DeterministicEmbedder(dim=dimension) + with pytest.raises(ValueError, match="embedding dimension"): + ApiEmbedder(model="model", api_key="key", dim=dimension) + + +def test_empty_api_embedding_batch_never_probes_for_a_dimension(monkeypatch): + embedder = ApiEmbedder(model="model", api_key="key") + monkeypatch.setattr( + embedder, + "embed", + lambda texts, **kwargs: (_ for _ in ()).throw(AssertionError("remote probe")), + ) + + # Invoke the class implementation so the instance monkeypatch would catch a + # recursive dimension probe made through ``self.dim``. + result = ApiEmbedder.embed(embedder, []) + + assert result.shape == (0, 0) + + +def test_api_batch_vectors_require_complete_unique_indices_and_consistent_width(): + embedder = ApiEmbedder(model="model", api_key="key", dim=2) + + assert embedder._ordered_batch_vectors({"data": [ + {"index": 1, "embedding": [0.0, 1.0]}, + {"index": 0, "embedding": [1.0, 0.0]}, + ]}, 2) == [[1.0, 0.0], [0.0, 1.0]] + assert embedder._ordered_batch_vectors({"data": [ + {"index": 0, "embedding": [1.0, 0.0]}, + ]}, 2) is None + assert embedder._ordered_batch_vectors({"data": [ + {"index": 0, "embedding": [1.0, 0.0]}, + {"index": 0, "embedding": [0.0, 1.0]}, + ]}, 2) is None + assert embedder._ordered_batch_vectors({"data": [ + {"index": 0, "embedding": [float("nan"), 0.0]}, + {"index": 1, "embedding": [0.0, 1.0]}, + ]}, 2) is None + + +def test_api_per_item_fallback_is_cardinality_safe_and_normalized(monkeypatch): + responses = [ + {"data": [{"index": 0, "embedding": [3.0, 4.0]}]}, + {"data": [{"index": 0, "embedding": [0.0, 2.0]}]}, + ] + + class _Response: + def __init__(self, payload): + self.payload = payload + + def raise_for_status(self): + return None + + def json(self): + return self.payload + + class _Client: + def __init__(self, **_kwargs): + pass + + def __enter__(self): + return self + + def __exit__(self, *_args): + return False + + def post(self, *_args, **kwargs): + if len(kwargs["json"]["input"]) > 1: + return _Response({"data": []}) + return _Response(responses.pop(0)) + + monkeypatch.setattr(httpx, "Client", _Client) + + result = ApiEmbedder(model="model", api_key="key").embed(["a", "b"]) + + np.testing.assert_allclose(result, [[0.6, 0.8], [0.0, 1.0]]) + + +def test_api_per_item_fallback_fills_malformed_rows_at_the_valid_width(monkeypatch): + responses = [ + {"data": [{"index": "private-index", "embedding": [9.0]}]}, + {"data": [{"index": 0, "embedding": [0.0, 2.0]}]}, + ] + + class _Response: + def __init__(self, payload): + self.payload = payload + + def raise_for_status(self): + return None + + def json(self): + return self.payload + + class _Client: + def __init__(self, **_kwargs): + pass + + def __enter__(self): + return self + + def __exit__(self, *_args): + return False + + def post(self, *_args, **kwargs): + if len(kwargs["json"]["input"]) > 1: + return _Response({"data": []}) + return _Response(responses.pop(0)) + + monkeypatch.setattr(httpx, "Client", _Client) + + result = ApiEmbedder(model="model", api_key="key").embed(["a", "b"]) + + assert result.shape == (2, 2) + np.testing.assert_allclose(result, [[0.0, 0.0], [0.0, 1.0]]) + + +def test_api_rejects_configured_dimension_mismatch_from_batch_response(monkeypatch): + class _Response: + def raise_for_status(self): + return None + + def json(self): + return {"data": [{"index": 0, "embedding": [1.0, 0.0, 0.0]}]} + + class _Client: + def __init__(self, **_kwargs): + pass + + def __enter__(self): + return self + + def __exit__(self, *_args): + return False + + def post(self, *_args, **_kwargs): + return _Response() + + monkeypatch.setattr(httpx, "Client", _Client) + + with pytest.raises(RuntimeError, match="unexpected dimension"): + ApiEmbedder(model="model", api_key="key", dim=2).embed(["a"]) + + +def test_api_rejects_configured_dimension_mismatch_during_per_item_fallback(monkeypatch): + class _Response: + def __init__(self, payload): + self.payload = payload + + def raise_for_status(self): + return None + + def json(self): + return self.payload + + class _Client: + def __init__(self, **_kwargs): + pass + + def __enter__(self): + return self + + def __exit__(self, *_args): + return False + + def post(self, *_args, **kwargs): + if len(kwargs["json"]["input"]) > 1: + return _Response({"data": []}) + return _Response({"data": [{"index": 0, "embedding": [1.0, 0.0, 0.0]}]}) + + monkeypatch.setattr(httpx, "Client", _Client) + + with pytest.raises(RuntimeError, match="unexpected dimension"): + ApiEmbedder(model="model", api_key="key", dim=2).embed(["a", "b"]) diff --git a/tests/test_mcp_annotation_idempotency.py b/tests/test_mcp_annotation_idempotency.py index d42194bf..4b5280bf 100644 --- a/tests/test_mcp_annotation_idempotency.py +++ b/tests/test_mcp_annotation_idempotency.py @@ -37,7 +37,7 @@ def _seed_approved_episode(server, content: str) -> str: def _annotations(tool_name): - tools = {tool.name: tool for tool in asyncio.run(srv.mcp.list_tools())} + tools = {tool.name: tool for tool in asyncio.run(srv.classic_mcp.list_tools())} return tools[tool_name].annotations diff --git a/tests/test_mcp_server.py b/tests/test_mcp_server.py index 912da5cc..b99a2f76 100644 --- a/tests/test_mcp_server.py +++ b/tests/test_mcp_server.py @@ -77,47 +77,59 @@ def _recall_side_effect_snapshot(srv): "engraphis_check_update", } +_SMART_TOOLS = { + "engraphis_session", + "engraphis_recall_context", + "engraphis_remember", + "engraphis_discover_actions", + "engraphis_execute_read", + "engraphis_execute_action", +} + def test_server_identity_and_tools_registered(): import asyncio import engraphis.mcp_server as srv assert srv.mcp.name == "engraphis_mcp" - assert srv.mcp.instructions == srv._SESSION_PROTOCOL - assert "engraphis_recall_proactive" in srv.mcp.instructions - assert "operator-configured\nworkspace" in srv.mcp.instructions - assert "engraphis_start_session" in srv.mcp.instructions - assert "engraphis_end_session" in srv.mcp.instructions - assert "open_threads=[]" in srv.mcp.instructions + assert srv.mcp.instructions == srv._SMART_SESSION_PROTOCOL + assert len(srv.mcp.instructions) <= 512 + assert "engraphis_session" in srv.mcp.instructions + assert "discover_actions" in srv.mcp.instructions + assert "engraphis_recall_proactive" not in srv.mcp.instructions tools = {t.name: t for t in asyncio.run(srv.mcp.list_tools())} + assert set(tools) == _SMART_TOOLS + + classic = {t.name: t for t in asyncio.run(srv.classic_mcp.list_tools())} + assert srv.classic_mcp.name == "engraphis_mcp" assert len(_ALL_TOOLS) == 33 - assert set(tools) == _ALL_TOOLS + assert set(classic) == _ALL_TOOLS assert srv.minimum_role("engraphis_context_savings") == "viewer" kilo = (ROOT / "docs" / "KILO_CODE_INTEGRATION.md").read_text(encoding="utf-8") - full_surface = kilo.split("## 4. The 33 tools", 1)[1].split("\n---", 1)[0] + full_surface = kilo.split("### Classic 33-tool inventory", 1)[1].split("\n---", 1)[0] assert set(re.findall(r"`(engraphis_[a-z_]+)`", full_surface)) == _ALL_TOOLS # Flat schema (not a nested "params" object) so agents can call fields directly. - props = tools["engraphis_remember"].inputSchema.get("properties", {}) + props = classic["engraphis_remember"].inputSchema.get("properties", {}) assert "content" in props and "workspace" in props and "params" not in props assert {"valid_from", "subject_key", "claim_kind"} <= set(props) - assert "as_of" in tools["engraphis_recall"].inputSchema.get("properties", {}) + assert "as_of" in classic["engraphis_recall"].inputSchema.get("properties", {}) assert {"valid_at", "known_at", "token_budget", "retrieval_profile", "candidate_depth", "response_mode", "diagnostics", "planning", "mtype_limits"} <= set( - tools["engraphis_recall"].inputSchema.get("properties", {}) + classic["engraphis_recall"].inputSchema.get("properties", {}) ) - assert tools["engraphis_recall_context"].inputSchema["properties"][ + assert classic["engraphis_recall_context"].inputSchema["properties"][ "token_budget" ]["default"] == 1024 assert {"planning", "mtype_limits"} <= set( - tools["engraphis_recall_context"].inputSchema.get("properties", {}) + classic["engraphis_recall_context"].inputSchema.get("properties", {}) ) - assert "as_of" in tools["engraphis_recall_grounded"].inputSchema.get("properties", {}) + assert "as_of" in classic["engraphis_recall_grounded"].inputSchema.get("properties", {}) assert {"valid_at", "known_at", "token_budget", "retrieval_profile", "candidate_depth", "response_mode", "planning", "mtype_limits"} <= set( - tools["engraphis_answer"].inputSchema.get("properties", {}) + classic["engraphis_answer"].inputSchema.get("properties", {}) ) assert {"as_of", "valid_at", "known_at"} <= set( - tools["engraphis_export_code_graph"].inputSchema.get("properties", {}) + classic["engraphis_export_code_graph"].inputSchema.get("properties", {}) ) @@ -149,6 +161,34 @@ def test_mcp_server_module_entrypoint_runs_stdio_handshake(): assert response["result"]["serverInfo"]["name"] == "engraphis_mcp" +def test_classic_mcp_entrypoint_preserves_historical_server_identity(): + payload = json.dumps({ + "jsonrpc": "2.0", + "id": 1, + "method": "initialize", + "params": { + "protocolVersion": "2024-11-05", + "capabilities": {}, + "clientInfo": {"name": "classic-entrypoint-test", "version": "1"}, + }, + }) + "\n" + + result = subprocess.run( + [sys.executable, "-m", "engraphis.mcp_classic_cli"], + cwd=ROOT, + input=payload, + text=True, + capture_output=True, + timeout=15, + check=False, + ) + + assert result.returncode == 0, result.stderr + response = json.loads(result.stdout) + assert response["id"] == 1 + assert response["result"]["serverInfo"]["name"] == "engraphis_mcp" + + @pytest.mark.parametrize( ("tool_name", "kwargs", "memory_changes", "receipt_changes"), [ @@ -234,7 +274,7 @@ def test_retrieval_annotations_match_observed_state_mutation( } observed_mutation = any(observed_changes.values()) - tools = {tool.name: tool for tool in asyncio.run(srv.mcp.list_tools())} + tools = {tool.name: tool for tool in asyncio.run(srv.classic_mcp.list_tools())} annotations = tools[tool_name].annotations assert annotations.readOnlyHint is (not observed_mutation) assert annotations.idempotentHint is (not observed_mutation) diff --git a/tests/test_packaging.py b/tests/test_packaging.py index 4c4a8c4e..a0b56406 100644 --- a/tests/test_packaging.py +++ b/tests/test_packaging.py @@ -280,6 +280,20 @@ def test_source_tree_version_matches_pyproject(): assert declared.group(1) == fallback.group(1) +def test_release_version_has_a_dated_changelog_section(): + """A tagged package must not ship its release notes only as ``Unreleased``.""" + pyproject = (ROOT / "pyproject.toml").read_text(encoding="utf-8") + changelog = (ROOT / "CHANGELOG.md").read_text(encoding="utf-8") + declared = re.search(r'^version = "([^"]+)"', pyproject, re.M) + assert declared, "project version declaration moved — update this test" + + heading = re.compile( + rf"^## \[{re.escape(declared.group(1))}\] - \d{{4}}-\d{{2}}-\d{{2}}$", + re.M, + ) + assert len(heading.findall(changelog)) == 1 + + def test_extras_stay_resolvable_on_the_lowest_supported_python(): """A 3.10-only floor must carry a 3.10 marker, or its extra cannot install on 3.9. diff --git a/tests/test_planned_recall_eval.py b/tests/test_planned_recall_eval.py index 826e54be..e3061aa2 100644 --- a/tests/test_planned_recall_eval.py +++ b/tests/test_planned_recall_eval.py @@ -1,11 +1,14 @@ """Evidence-harness contracts for planned-recall release gates.""" from pathlib import Path +import pytest + from eval.harness import load_dataset from eval.planned_recall import ( ABLATIONS, TOKEN_BUDGETS, _evidence_retention_quality, + _validate_dataset, run, ) @@ -62,3 +65,11 @@ def test_quality_requires_answer_bearing_excerpt_content_not_only_supporting_id( ) assert quality < 1.0 + + +def test_dataset_validation_rejects_unknown_support_instead_of_awarding_perfect_quality(): + cases = load_dataset(str(DATASET)) + cases[0]["questions"][0]["supporting"] = ["missing-tag"] + + with pytest.raises(ValueError, match="unknown supporting memory tags"): + _validate_dataset(cases) diff --git a/tests/test_postgres_schema.py b/tests/test_postgres_schema.py index 63440193..7aef234a 100644 --- a/tests/test_postgres_schema.py +++ b/tests/test_postgres_schema.py @@ -262,6 +262,26 @@ def test_postgres_introspection_is_filtered_bounded_and_cross_schema_safe(monkey assert params[:2] == (["auth", "public"], ["auth", "public"]) +def test_postgres_source_digest_excludes_credentials_and_connection_options(): + first = postgres_schema._source_digest( + "postgresql://alice:first-password@db.example:5433/appdb?sslmode=require" + ) + rotated = postgres_schema._source_digest( + "postgresql://bob:second-password@db.example:5433/appdb?sslmode=disable" + ) + other_database = postgres_schema._source_digest( + "postgresql://alice:first-password@db.example:5433/other" + ) + + assert first == rotated + assert first != other_database + assert postgres_schema._source_digest( + "host=db.example dbname=appdb user=alice password=first-password" + ) == postgres_schema._source_digest( + "host=db.example dbname=appdb user=bob password=second-password" + ) + + def test_service_never_persists_postgres_dsn(monkeypatch): dsn = "postgresql://user:secret@db.internal/appdb" snapshot = SchemaSnapshot( diff --git a/tests/test_proactive_context.py b/tests/test_proactive_context.py index 1cf90bbb..131303c3 100644 --- a/tests/test_proactive_context.py +++ b/tests/test_proactive_context.py @@ -1,3 +1,5 @@ +import re + import pytest pytest.importorskip("fastapi") @@ -102,3 +104,71 @@ def test_api_proactive_context_round_trip(): assert data["grounded"] is True assert "context_summary" in data and "[1]" in data["context_summary"] assert data["citations"][0]["title"] == "Auth convention" + + +def test_compact_proactive_context_is_bounded_and_does_not_repeat_source_bodies(): + svc = MemoryService.create(":memory:", embed_model="") + pending = svc.remember( + "The authorization middleware uses PASETO tokens with a 15 minute lifetime.", + workspace="acme", scope="workspace", title="Auth convention", importance=0.9, + ) + svc.engine.approve_for_prompt(pending["id"], reviewer="test", reason="approved fixture") + + out = svc.proactive_context( + workspace="acme", task="update authorization middleware", k=5, + response_mode="compact", token_budget=32, + ) + + counter = svc.engine.recall_engine.context_packer.count_tokens + assert set(out) == {"workspace", "repo", "context", "sources", "usage", "grounded", "reason"} + assert counter(out["context"]) <= 32 + assert out["sources"][0]["id"].startswith("mem_") + assert "content" not in out["sources"][0] + assert "suggested_memories" not in out + assert out["usage"]["budget_tokens"] == 32 + receipt = next(item for item in svc.receipt_log(workspace="acme")["entries"] + if item["operation"] == "proactive_context") + assert receipt["metadata"]["response_mode"] == "compact" + assert "PASETO" not in str(receipt) + + +@pytest.mark.parametrize("budget", range(8, 13)) +def test_compact_proactive_context_never_emits_partial_citations(budget): + svc = MemoryService.create(":memory:", embed_model="") + pending = svc.remember( + "The authorization middleware uses PASETO tokens with a 15 minute lifetime.", + workspace="acme", scope="workspace", title="Auth convention", importance=0.9, + ) + svc.engine.approve_for_prompt(pending["id"], reviewer="test", reason="approved fixture") + + out = svc.proactive_context( + workspace="acme", task="update authorization middleware", k=5, + response_mode="compact", token_budget=budget, + ) + + cited_numbers = {int(number) for number in re.findall(r"\[(\d+)\]", out["context"])} + assert not re.search(r"\[(?:\d*)$", out["context"]) + assert {source["n"] for source in out["sources"]} == cited_numbers + assert out["grounded"] is bool(cited_numbers) + + +def test_api_adaptive_context_routes_host_owned_history(): + svc = MemoryService.create(":memory:", embed_model="") + svc.remember("The release manager approves deployment.", workspace="acme") + v2_api.set_service(svc) + app = FastAPI() + app.include_router(v2_api.router) + client = TestClient(app) + + response = client.post("/api/adaptive-context", json={ + "workspace": "acme", + "query": "Who approves deployment?", + "history": "The release manager approves deployment.", + "max_context_tokens": 32, + }) + + assert response.status_code == 200 + body = response.json() + assert body["context"] == "The release manager approves deployment." + assert body["decision"]["mode"] == "history_bypass" + assert body["sources"] == [] diff --git a/tests/test_read_only_api.py b/tests/test_read_only_api.py index f593750d..2630ca8e 100644 --- a/tests/test_read_only_api.py +++ b/tests/test_read_only_api.py @@ -53,6 +53,22 @@ def test_read_only_api_requires_token_and_does_not_reinforce(): ).status_code == 404 +def test_tokenless_read_only_factory_rejects_remote_peers(): + """The ASGI factory must retain the launcher's token-or-loopback boundary.""" + svc = MemoryService.create(":memory:", graph_extractor="none") + client = TestClient( + create_read_only_app(svc), + client=("192.0.2.10", 50000), + ) + + # Health/schema probes remain safe for orchestration and discovery, but workspace + # reads fail closed even if an operator bypasses scripts.graph_server. + assert client.get("/health").status_code == 200 + response = client.get("/recall", params={"query": "database", "workspace": "w"}) + assert response.status_code == 403 + assert response.json() == {"detail": "remote access requires a bearer token"} + + def test_read_only_api_serves_graph_and_intent_recall(): svc = MemoryService.create(":memory:", graph_extractor="regex") pending = svc.remember( diff --git a/tests/test_release_evidence.py b/tests/test_release_evidence.py index 572da8ed..d73f20a3 100644 --- a/tests/test_release_evidence.py +++ b/tests/test_release_evidence.py @@ -208,7 +208,10 @@ def test_release_workflow_publishes_evidence_separately_from_package_artifacts() "dependency-audit", "container-smoke", ): assert "--verified-check " + check_id in evidence_job - assert "needs: [build, python-matrix, encryption, browser-accessibility, docker-smoke]" in evidence_job + assert ( + "needs: [build, python-matrix, encryption, browser-accessibility, pi-extension, docker-smoke]" + in evidence_job + ) assert "--verified-check encryption-at-rest" in evidence_job assert "name: Download distributions" in evidence_job assert "npm run test:e2e" in browser_job diff --git a/tests/test_release_infrastructure.py b/tests/test_release_infrastructure.py index 15c61bf6..48386db2 100644 --- a/tests/test_release_infrastructure.py +++ b/tests/test_release_infrastructure.py @@ -132,7 +132,7 @@ def test_ci_and_release_audit_production_image_dependencies(): assert 'docker create --name "$container" engraphis:release' in release_docker assert 'docker cp "$container":/usr/local/lib/python3.11/site-packages/.' in release_docker assert 'python -m pip_audit --path "$audit_dir"' in release_docker - assert "needs: [build, python-matrix, encryption, browser-accessibility, docker-smoke]" in release_evidence + assert "needs: [build, python-matrix, encryption, browser-accessibility, pi-extension, docker-smoke]" in release_evidence assert "needs: release-evidence" in publish assert "Browser accessibility release gate" in release assert "Require release tag commit to be on protected main" in release @@ -173,7 +173,7 @@ def test_sqlcipher_driver_has_a_dedicated_short_lived_integration_gate(): assert 'python-version: ["3.10", "3.11", "3.12", "3.13", "3.14"]' in workflow release = _text(".github/workflows/release.yml") - assert "needs: [build, python-matrix, encryption, browser-accessibility, docker-smoke]" in release + assert "needs: [build, python-matrix, encryption, browser-accessibility, pi-extension, docker-smoke]" in release def test_release_builds_one_portable_open_core_wheel(): @@ -196,7 +196,7 @@ def test_release_builds_one_portable_open_core_wheel(): assert "python scripts/verify_distribution_contents.py dist/*" in release assert "Build compiled wheels" not in release assert "name: Assemble distributions" not in release - assert "needs: [build, python-matrix, encryption, browser-accessibility, docker-smoke]" in release + assert "needs: [build, python-matrix, encryption, browser-accessibility, pi-extension, docker-smoke]" in release assert " release-evidence:\n" in release assert "needs: release-evidence" in release assert "name: python-package-distributions" in release @@ -321,8 +321,11 @@ def test_public_capability_and_support_docs_match_the_shipped_tree(): assert "28 MCP tools" not in content assert "28-tool" not in content assert "(28 of them)" not in content - assert "33 MCP tools" in architecture - assert "(33 of them)" in skill + assert "Smart MCP (6 tools)" in architecture + assert "Classic MCP (33 tools)" in architecture + assert "default Smart MCP surface has six" in skill + assert "Classic direct-tool guide" in skill + assert "engraphis-mcp-classic" in skill assert "recall_context (compact)" in architecture assert "engraphis_recall_context" in readme assert "`engraphis_check_update`" in readme diff --git a/tests/test_secret_hygiene.py b/tests/test_secret_hygiene.py index 346cb08d..215c6f77 100644 --- a/tests/test_secret_hygiene.py +++ b/tests/test_secret_hygiene.py @@ -6,7 +6,7 @@ import pytest from engraphis.core.engine import MemoryEngine -from engraphis.core.interfaces import ExtractedFact, MemoryRecord, MemoryType, Scope +from engraphis.core.interfaces import Edge, ExtractedFact, MemoryRecord, MemoryType, Scope from engraphis.core.secrets import SecretDetectedError, secret_kind from engraphis.core.store import Store from engraphis.service import MemoryService, ValidationError @@ -136,6 +136,89 @@ def test_secure_erase_removes_local_memory_indexes_and_links(tmp_path): assert erased["maintenance"]["vacuum"] in {"completed", "failed"} +def test_secure_erase_rebuilds_shared_edge_provenance_from_remaining_support(): + engine = MemoryEngine.create(":memory:") + workspace = engine.store.get_or_create_workspace("acme") + erased_id = engine.remember("Erased graph source.", workspace_id=workspace) + retained_id = engine.remember("Retained graph source.", workspace_id=workspace) + edge_id = engine.store.upsert_edge(Edge( + id="edg_shared", src="ent_alpha", dst="ent_beta", relation="uses", + workspace_id=workspace, + provenance={"source": "structured", "memory_id": erased_id}, + )) + engine.store.add_edge_support( + edge_id, {"source": "manual", "memory_id": retained_id} + ) + + engine.secure_erase(erased_id) + + edge = engine.store.conn.execute( + "SELECT provenance FROM edges WHERE id=?", (edge_id,) + ).fetchone() + assert edge is not None + provenance = json.loads(edge["provenance"]) + assert provenance["memory_id"] == retained_id + assert provenance["memory_ids"] == [retained_id] + assert erased_id not in edge["provenance"] + supports = engine.store.conn.execute( + "SELECT memory_id, provenance FROM edge_supports WHERE edge_id=?", + (edge_id,), + ).fetchall() + assert [row["memory_id"] for row in supports] == [retained_id] + assert erased_id not in supports[0]["provenance"] + + neighbors = engine.store.neighbors(["ent_alpha"]) + assert [edge.id for edge in engine.recall_engine._prompt_eligible_edges(neighbors)] == [ + edge_id + ] + + +def test_secure_erase_preserves_shared_edge_history_from_retired_support(): + engine = MemoryEngine.create(":memory:") + workspace = engine.store.get_or_create_workspace("acme") + erased_id = engine.remember("Erased current source.", workspace_id=workspace) + historical_id = engine.remember("Historical safe source.", workspace_id=workspace) + edge_id = engine.store.upsert_edge(Edge( + id="edg_historical", src="ent_alpha", dst="ent_beta", relation="uses", + workspace_id=workspace, + provenance={"source": "structured", "memory_id": erased_id}, + )) + engine.store.add_edge_support( + edge_id, {"source": "manual", "memory_id": historical_id} + ) + historical_at = engine.store.conn.execute( + "SELECT MAX(valid_from) FROM edge_supports WHERE edge_id=?", (edge_id,) + ).fetchone()[0] + engine.retire(historical_id, reason="historical evidence") + + engine.secure_erase(erased_id) + + edge = engine.store.conn.execute( + "SELECT valid_to, valid_to_recorded_at, provenance FROM edges WHERE id=?", + (edge_id,), + ).fetchone() + assert edge is not None + assert edge["valid_to"] is not None + assert edge["valid_to_recorded_at"] is not None + provenance = json.loads(edge["provenance"]) + assert provenance["memory_id"] == historical_id + assert provenance["memory_ids"] == [historical_id] + assert erased_id not in edge["provenance"] + assert engine.store.neighbors(["ent_alpha"]) == [] + historical = engine.store.neighbors(["ent_alpha"], at=historical_at) + assert [item.id for item in historical] == [edge_id] + assert [ + item.id for item in engine.recall_engine._prompt_eligible_edges(historical) + ] == [edge_id] + supports = engine.store.conn.execute( + "SELECT memory_id, valid_to, provenance FROM edge_supports WHERE edge_id=?", + (edge_id,), + ).fetchall() + assert [row["memory_id"] for row in supports] == [historical_id] + assert supports[0]["valid_to"] is not None + assert erased_id not in supports[0]["provenance"] + + def test_sync_drops_secret_bearing_rows_before_store_upsert(): store = Store(":memory:") workspace = store.get_or_create_workspace("acme") diff --git a/tests/test_secrets_edge_cases.py b/tests/test_secrets_edge_cases.py new file mode 100644 index 00000000..d5a19701 --- /dev/null +++ b/tests/test_secrets_edge_cases.py @@ -0,0 +1,18 @@ +"""Reliability edge cases for the capture-time secret boundary.""" + +from engraphis.core.secrets import secret_kind + + +def test_secret_detection_handles_cyclic_metadata_without_recursing_forever(): + metadata = {} + metadata["self"] = metadata + + assert secret_kind(metadata) is None + + +def test_secret_detection_still_finds_credentials_beside_a_cycle(): + metadata = {} + metadata["self"] = metadata + metadata["api_key"] = "credential-value-123456" + + assert secret_kind(metadata) == "credential assignment" diff --git a/tests/test_smart_mcp_gateway.py b/tests/test_smart_mcp_gateway.py new file mode 100644 index 00000000..5ec52b91 --- /dev/null +++ b/tests/test_smart_mcp_gateway.py @@ -0,0 +1,406 @@ +"""Contract coverage for the zero-configuration Smart MCP gateway. + +The normal server intentionally exposes a tiny, discoverable surface. The +legacy named-tool contract remains available separately for clients that pin +tool names, so gateway calls must retain the service semantics of those tools. +""" +from __future__ import annotations + +import asyncio +from dataclasses import replace +import json +import re + +import pytest + + +pytest.importorskip("mcp", reason="optional 'mcp' extra not installed") + + +SMART_TOOL_NAMES = { + "engraphis_session", + "engraphis_recall_context", + "engraphis_remember", + "engraphis_discover_actions", + "engraphis_execute_read", + "engraphis_execute_action", +} + +# This is deliberately an exact snapshot, rather than a count-only check: a +# legacy client may depend on either deprecated alias retaining its behavior. +CLASSIC_TOOL_NAMES = { + "engraphis_remember", "engraphis_recall", "engraphis_recall_context", + "engraphis_why", "engraphis_timeline", "engraphis_recall_proactive", + "engraphis_retire", "engraphis_forget", "engraphis_secure_erase", + "engraphis_pin", "engraphis_correct", "engraphis_promote", "engraphis_link", + "engraphis_record_event", "engraphis_index_repo", "engraphis_search_code", + "engraphis_code_path", "engraphis_code_impact", "engraphis_export_code_graph", + "engraphis_start_session", "engraphis_end_session", "engraphis_stats", + "engraphis_proactive_context", "engraphis_recall_grounded", "engraphis_answer", + "engraphis_ingest", "engraphis_consolidate", "engraphis_ingest_postgres_schema", + "engraphis_receipts", "engraphis_context_savings", "engraphis_verify_receipts", + "engraphis_export_receipts", "engraphis_check_update", +} + + +def _memory_server(monkeypatch): + import engraphis.mcp_server as srv + from engraphis.service import MemoryService + + monkeypatch.setattr(srv, "_service", MemoryService.create(":memory:")) + return srv + + +def _tools(server, attr): + return {tool.name: tool for tool in asyncio.run(getattr(server, attr).list_tools())} + + +def _payload(value): + assert not value.startswith("Error:"), value + return json.loads(value) + + +def _jsonable(value): + if hasattr(value, "model_dump"): + return value.model_dump(mode="json") + if hasattr(value, "dict"): + return value.dict() + return value + + +def test_normal_mcp_exposes_only_the_six_smart_gateway_tools(monkeypatch): + server = _memory_server(monkeypatch) + + tools = _tools(server, "mcp") + assert set(tools) == SMART_TOOL_NAMES + assert len(tools) == 6 + assert len(server.mcp.instructions) <= 512 + + +def test_classic_mcp_retains_the_33_named_tool_compatibility_surface(monkeypatch): + server = _memory_server(monkeypatch) + + classic = _tools(server, "classic_mcp") + assert set(classic) == CLASSIC_TOOL_NAMES + assert len(classic) == 33 + # These aliases carry distinct historical defaults and must not disappear. + assert {"engraphis_answer", "engraphis_forget"} <= set(classic) + + +def test_smart_gateway_initial_payload_fits_context_budget(monkeypatch): + server = _memory_server(monkeypatch) + + tools = [_jsonable(tool) for tool in _tools(server, "mcp").values()] + initial_payload = server.mcp.instructions.encode("utf-8") + json.dumps( + {"tools": tools}, sort_keys=True, separators=(",", ":"), default=str, + ).encode("utf-8") + assert len(initial_payload) <= 12 * 1024 + # Stable project-local approximation: the six-tool surface must stay well under + # the release gate and at least 80% below the previous 64.6 KB direct catalog. + assert len(initial_payload) <= int(64_600 * 0.20) + assert len(re.findall(rb"\w+|[^\s\w]", initial_payload)) <= 4_500 + + +def test_discovery_returns_bound_capability_schema_and_safe_metadata(monkeypatch): + server = _memory_server(monkeypatch) + + discovered = _payload(server.engraphis_discover_actions( + task="Show the history of the API rate limit in the acme workspace.", + )) + actions = discovered["actions"] + assert 1 <= len(actions) <= 3 + action = actions[0] + assert action["capability_id"] + assert action["schema_version"] == "smart-mcp/1" + assert action["schema_digest"] + assert action["purpose"] + assert action["input_schema"]["type"] == "object" + assert action["side_effect"] in {"read", "write", "admin", "destructive"} + assert isinstance(action["prerequisite"], (str, type(None))) + assert action["result_budget"] > 0 + assert isinstance(action["example"], dict) + assert "task" not in json.dumps(discovered) # do not echo potentially private task text + + +def test_discovery_abstains_for_an_unknown_or_ambiguous_request(monkeypatch): + server = _memory_server(monkeypatch) + + discovered = _payload(server.engraphis_discover_actions( + task="Please handle the thing mentioned earlier.", + )) + + assert discovered["actions"] == [] + + +def test_discovery_does_not_treat_a_category_as_mutation_intent(monkeypatch): + server = _memory_server(monkeypatch) + + discovered = _payload(server.engraphis_discover_actions( + task="Please handle the thing mentioned earlier.", category="governance", + )) + + assert discovered["actions"] == [] + + +@pytest.mark.parametrize( + ("task", "expected_action"), + [ + ("Search stored memories for complete memory bodies.", "recall"), + ("Explain why this decision changed.", "why"), + ("Show the history of this fact.", "timeline"), + ("What should I know right now?", "recall_proactive"), + ("Retire an outdated memory.", "retire"), + ("Forget this legacy memory.", "forget"), + ("Irreversibly erase a leaked secret.", "secure_erase"), + ("Pin this memory.", "pin"), + ("Correct this memory with new content.", "correct"), + ("Promote this memory to workspace scope.", "promote"), + ("Link two related memories.", "link"), + ("Record a deployment event.", "record_event"), + ("Index this repository.", "index_repo"), + ("Find symbol callers in code.", "search_code"), + ("Trace the code path between functions.", "code_path"), + ("Analyze impact of changed files.", "code_impact"), + ("Export the code graph.", "export_code_graph"), + ("Start a project work session.", "start_session"), + ("End the active work session with a handoff.", "end_session"), + ("Check memory store health statistics.", "stats"), + ("Prepare proactive context for current work.", "proactive_context"), + ("Give a grounded cited answer.", "recall_grounded"), + ("Answer this question from memory.", "answer"), + ("Ingest raw document text.", "ingest"), + ("Consolidate duplicate memories.", "consolidate"), + ("Ingest a PostgreSQL schema.", "ingest_postgres_schema"), + ("List audit receipts.", "receipts"), + ("Show context token savings.", "context_savings"), + ("Verify the receipt chain.", "verify_receipts"), + ("Export a receipt audit bundle.", "export_receipts"), + ("Check for updates.", "check_update"), + ], +) +def test_discovery_routes_unambiguous_advanced_intents(monkeypatch, task, expected_action): + server = _memory_server(monkeypatch) + + action = _payload(server.engraphis_discover_actions(task=task))["actions"][0] + + assert action["canonical_action"] == expected_action + + +def test_execute_read_revalidates_discovered_capability_and_dispatches(monkeypatch): + server = _memory_server(monkeypatch) + # Stats on a nonexistent workspace rightly performs no write. Seed the scope and + # prove that the read executor itself does not append supplementary telemetry. + _payload(server.engraphis_remember(content="Gateway telemetry fixture.", workspace="acme")) + before = server._service.store.conn.execute( + "SELECT COUNT(*) AS n FROM operation_receipts WHERE operation='smart_gateway'" + ).fetchone()["n"] + + discovery = _payload(server.engraphis_discover_actions( + task="Show memory store statistics for workspace acme.", + ))["actions"][0] + result = _payload(server.engraphis_execute_read( + capability_id=discovery["capability_id"], + schema_digest=discovery["schema_digest"], + arguments={"workspace": "acme"}, + )) + assert result["capability_id"] == discovery["capability_id"] + assert result["schema_digest"] == discovery["schema_digest"] + assert result["result"]["workspace"] == "acme" + + after = server._service.store.conn.execute( + "SELECT COUNT(*) AS n FROM operation_receipts WHERE operation='smart_gateway'" + ).fetchone()["n"] + assert after == before + + forged = server.engraphis_execute_read( + capability_id="forged-capability", schema_digest=discovery["schema_digest"], + arguments={"workspace": "acme"}, + ) + assert forged.startswith("Error:") + + stale = server.engraphis_execute_read( + capability_id=discovery["capability_id"], schema_digest="stale-schema", + arguments={"workspace": "acme"}, + ) + assert stale.startswith("Error: invalid_or_stale_capability") + + +def test_capability_becomes_stale_when_deployment_policy_changes(monkeypatch): + server = _memory_server(monkeypatch) + action = _payload(server.engraphis_discover_actions( + task="Show memory store statistics.", + ))["actions"][0] + + monkeypatch.setattr(server, "_DEPLOYMENT_POLICY", "changed-policy") + response = server.engraphis_execute_read( + capability_id=action["capability_id"], schema_digest=action["schema_digest"], + arguments={}, + ) + + assert response == "Error: invalid_or_stale_capability" + + +def test_discovery_omits_an_unavailable_action(monkeypatch): + server = _memory_server(monkeypatch) + original = server.ACTION_SPECS["stats"] + monkeypatch.setitem( + server.ACTION_SPECS, "stats", replace(original, availability_predicate=lambda: False), + ) + + discovered = _payload(server.engraphis_discover_actions( + task="Show memory store statistics.", + )) + + assert discovered["actions"] == [] + + +def test_stateful_executor_records_only_content_free_gateway_telemetry(monkeypatch): + server = _memory_server(monkeypatch) + _payload(server.engraphis_remember(content="Gateway telemetry fixture.", workspace="acme")) + action = _payload(server.engraphis_discover_actions( + task="Record a deployment event in workspace acme.", + ))["actions"][0] + + result = _payload(server.engraphis_execute_action( + capability_id=action["capability_id"], + schema_digest=action["schema_digest"], + arguments={"kind": "deployment", "content": "Deployment completed.", + "workspace": "acme"}, + )) + assert result["canonical_action"] == "record_event" + + receipt = server._service.store.conn.execute( + "SELECT payload FROM operation_receipts WHERE operation='smart_gateway' " + "ORDER BY sequence DESC LIMIT 1" + ).fetchone() + telemetry = json.loads(receipt["payload"]) + assert telemetry["metadata"]["action_id"].startswith("sha256:") + assert telemetry["metadata"]["schema_version"].startswith("sha256:") + assert "acme" not in json.dumps(telemetry) + + +@pytest.mark.parametrize(("tool_name", "required_role"), [ + ("engraphis_discover_actions", "viewer"), + ("engraphis_execute_read", "viewer"), + ("engraphis_execute_action", "admin"), + ("engraphis_remember", "member"), + ("engraphis_consolidate", "admin"), +]) +def test_smart_gateway_roles_fail_closed_at_the_outer_auth_boundary( + monkeypatch, tool_name, required_role, +): + server = _memory_server(monkeypatch) + + assert server.minimum_role(tool_name) == required_role + + +@pytest.mark.parametrize(("task", "executor_name"), [ + ("Show memory store statistics.", "engraphis_execute_read"), + ("Record a deployment event.", "engraphis_execute_action"), +]) +def test_oversized_results_return_success_without_retry_ambiguity( + monkeypatch, task, executor_name, +): + server = _memory_server(monkeypatch) + action = _payload(server.engraphis_discover_actions(task=task))["actions"][0] + oversized = {"items": ["result"] * (action["result_budget"] + 1)} + executions = [] + + def run_once(spec, arguments): + executions.append((spec.canonical_id, arguments)) + return True, oversized, {} + + monkeypatch.setattr(server, "_run_action", run_once) + + response = getattr(server, executor_name)( + capability_id=action["capability_id"], + schema_digest=action["schema_digest"], + arguments={}, + ) + payload = _payload(response) + + assert payload["executed"] is True + assert payload["execution_status"] == "succeeded" + assert payload["result_omitted"] is True + assert payload["reason"] == "result_budget_exceeded" + assert payload["retry_recommended"] is False + assert "result" not in payload + assert executions == [(action["canonical_action"], {})] + assert server._GATEWAY_RESULT_COUNTER(response) <= action["result_budget"] + + +def test_executor_refuses_wrong_side_effect_class(monkeypatch): + server = _memory_server(monkeypatch) + + action = _payload(server.engraphis_discover_actions( + task="Record a deployment event in workspace acme.", + ))["actions"][0] + response = server.engraphis_execute_read( + capability_id=action["capability_id"], + schema_digest=action["schema_digest"], + arguments=action["example"], + ) + assert response.startswith("Error:") + + +def test_gateway_preserves_safe_classic_handler_errors(monkeypatch): + server = _memory_server(monkeypatch) + _payload(server.engraphis_remember(content="Gateway error fixture.", workspace="acme")) + action = _payload(server.engraphis_discover_actions( + task="Retire a stale memory in workspace acme.", + ))["actions"][0] + + arguments = {"memory_id": "mem_missing", "workspace": "acme"} + direct = server.engraphis_retire(**arguments) + gateway = server.engraphis_execute_action( + capability_id=action["capability_id"], schema_digest=action["schema_digest"], + arguments=arguments, + ) + + assert direct.startswith("Error:") + assert gateway == direct + + +def test_discovered_proactive_context_supports_bounded_compact_mode(monkeypatch): + server = _memory_server(monkeypatch) + + action = _payload(server.engraphis_discover_actions( + task="Prepare a compact proactive context packet for the current work.", + ))["actions"][0] + + assert action["canonical_action"] == "proactive_context" + assert {"token_budget", "response_mode"} <= set(action["input_schema"]["properties"]) + + +def test_smart_session_start_and_end_preserve_handoff_contract(monkeypatch): + server = _memory_server(monkeypatch) + + started = _payload(server.engraphis_session( + action="start", workspace="acme", repo="api", agent="test-agent", + goal="Investigate deployment failures.", + )) + assert started["status"] == "active" + assert started["session_id"] + # Optional context must not make session creation fail and must always say what happened. + assert started["context_status"] in {"not_requested", "available", "unavailable"} + + reused = _payload(server.engraphis_session( + action="start", workspace="acme", repo="api", agent="test-agent", + goal="Investigate deployment failures.", + )) + assert reused["session_id"] == started["session_id"] + assert reused["reused"] is True + + branched = _payload(server.engraphis_session( + action="start", workspace="acme", repo="api", agent="test-agent", + goal="Investigate deployment failures.", force_new=True, + )) + assert branched["session_id"] != started["session_id"] + assert branched["reused"] is False + + ended = _payload(server.engraphis_session( + action="end", session_id=started["session_id"], summary="Investigated failures.", + outcome="shipped", open_threads=[], + )) + assert ended["session_id"] == started["session_id"] + assert ended["status"] == "summarized" diff --git a/tests/test_sync.py b/tests/test_sync.py index b2f1dd9b..4ae3859c 100644 --- a/tests/test_sync.py +++ b/tests/test_sync.py @@ -91,6 +91,12 @@ def test_serialization_roundtrip_preserves_signature(): assert _signature(r2) == _signature(rec) +def test_untrusted_record_uses_strict_boolean_pinning(): + assert dict_to_record({"id": "mem_false", "content": "x", "pinned": "false"}).pinned is False + assert dict_to_record({"id": "mem_one", "content": "x", "pinned": 1}).pinned is False + assert dict_to_record({"id": "mem_true", "content": "x", "pinned": True}).pinned is True + + def test_sync_roundtrip_preserves_claim_identity_and_closure_knowledge_time(): rec = MemoryRecord( id="mem_claim", From c88462b297de622fb238c44ad08085dcbd41d3f4 Mon Sep 17 00:00:00 2001 From: Jaixii Date: Sun, 2 Aug 2026 21:59:05 -0400 Subject: [PATCH 20/35] fix: reject all MCP server error envelopes --- integrations/pi/src/mcp-client.ts | 9 +++++++-- integrations/pi/test/mcp-result.test.ts | 7 +++++++ 2 files changed, 14 insertions(+), 2 deletions(-) diff --git a/integrations/pi/src/mcp-client.ts b/integrations/pi/src/mcp-client.ts index 46e34145..a4d1dbe9 100644 --- a/integrations/pi/src/mcp-client.ts +++ b/integrations/pi/src/mcp-client.ts @@ -215,8 +215,13 @@ export function formatMcpResult(result: unknown) { ?.filter((block) => block.type === "text" && typeof block.text === "string") .map((block) => block.text) .join("\n\n"); - const declaredError = text?.trim().match(/^Error:\s*([a-z0-9_]+)\s*$/i); - if (payload.isError || declaredError) { + const normalizedText = text?.trim(); + const declaredError = normalizedText?.match(/^Error:\s*([a-z0-9_]+)\s*$/i); + // Classic handlers return a deliberately anchored plain-text ``Error:`` envelope + // for semantic rejections. Its details are not safe to expose to the model, and + // the payload can contain spaces, quoted IDs, or other non-token text. + const serverError = /^Error:/i.test(normalizedText ?? ""); + if (payload.isError || serverError) { const message = declaredError ? `Engraphis rejected the request: ${declaredError[1]}.` : "Engraphis rejected the request. Verify the parameters and inspect the local Engraphis logs."; diff --git a/integrations/pi/test/mcp-result.test.ts b/integrations/pi/test/mcp-result.test.ts index 648b89f9..392d3ac5 100644 --- a/integrations/pi/test/mcp-result.test.ts +++ b/integrations/pi/test/mcp-result.test.ts @@ -19,6 +19,13 @@ test("throws sanitized failures for MCP error flags and Engraphis error envelope () => formatMcpResult({ isError: false, content: [{ type: "text", text: "Error: invalid_arguments" }] }), /invalid_arguments/, ); + assert.throws( + () => formatMcpResult({ + isError: false, + content: [{ type: "text", text: "Error: no memory with id 'mem_missing'" }], + }), + /Engraphis rejected the request\. Verify the parameters/, + ); assert.doesNotThrow(() => formatMcpResult({ isError: false, content: [{ type: "text", text: "An Error: inside successful prose is not an error envelope." }], From c0e5470fed07e2148b8a65030f21cc004791e1c7 Mon Sep 17 00:00:00 2001 From: Jaixii Date: Sun, 2 Aug 2026 22:09:56 -0400 Subject: [PATCH 21/35] docs: restore Pro conversion callout --- README.md | 3 +++ 1 file changed, 3 insertions(+) diff --git a/README.md b/README.md index 1e2f64c8..8bdee231 100644 --- a/README.md +++ b/README.md @@ -11,6 +11,9 @@ **Give coding agents durable project memory so the next session can retrieve the current decision, its evidence, and its history.** +> **Support continued Engraphis development with Pro.** [Start a 3-day Pro trial](https://api.engraphis.com/account?plan=pro&interval=monthly&utm_source=engraphis&utm_medium=docs&utm_campaign=pro_conversion&utm_content=readme_intro&trial=pro#billing) +> or [subscribe to Pro](https://api.engraphis.com/account?plan=pro&interval=monthly&utm_source=engraphis&utm_medium=docs&utm_campaign=pro_conversion&utm_content=readme_intro#billing). +

Project history becomes scoped memory, hybrid recall, and bounded cited context for an agent
From 97904bb990da6554e9af93dd3ca238eb3fa12898 Mon Sep 17 00:00:00 2001 From: Jaixii Date: Sun, 2 Aug 2026 22:18:26 -0400 Subject: [PATCH 22/35] docs: make full install the default --- README.md | 25 ++++++++++++++++++------- 1 file changed, 18 insertions(+), 7 deletions(-) diff --git a/README.md b/README.md index 8bdee231..5cef2e28 100644 --- a/README.md +++ b/README.md @@ -26,10 +26,23 @@ > and customer-side clients. Hosted sync, analytics, automation, and team services run on the > official hosted service; their server implementations are not distributed here. -## Start in 60 seconds +## Full Engraphis install: pip install "engraphis[all]" -Choose the smallest surface that matches your use case. Python 3.10+ is recommended and is -required for the dashboard, MCP, documents, Cloud Sync, and `all` extras; the NumPy-only core +The complete `engraphis[all]` install is the default way to use Engraphis: it includes the local +dashboard, Smart MCP server, documents, Cloud Sync client, and supported optional integrations. +Python 3.10+ is required. + +```bash +pip install "engraphis[all]" +engraphis-dashboard +``` + +The dashboard opens at [http://127.0.0.1:8700](http://127.0.0.1:8700). Local memory needs no +account or API key. + +### Smaller installation options + +Use a smaller package only when you intentionally need a limited surface. The NumPy-only core continues to support Python 3.9+. | Goal | Install | Start | @@ -37,11 +50,9 @@ continues to support Python 3.9+. | Local dashboard and REST API | `pip install "engraphis[server]"` | `engraphis-dashboard` | | Coding-agent memory over Smart MCP | `pip install "engraphis[mcp]"` | `codex mcp add engraphis -- engraphis-mcp` | | Offline Python library | `pip install engraphis` | `MemoryService.create("engraphis.db")` | -| Full cross-platform feature set | `pip install "engraphis[all]"` | `engraphis-dashboard` | -The dashboard opens at [http://127.0.0.1:8700](http://127.0.0.1:8700). Local memory needs no -account or API key. For MCP clients other than Codex, configure a stdio server whose command is -`engraphis-mcp`; see the [agent connection guide](docs/AGENT_CONNECT.md). +For MCP clients other than Codex, configure a stdio server whose command is `engraphis-mcp`; see +the [agent connection guide](docs/AGENT_CONNECT.md). > **Upgrading to 1.4:** `engraphis-mcp` now exposes the six-tool Smart gateway. Integrations that > require the former 33 direct tool names should run `engraphis-mcp-classic`. The SQLite schema From c5ac56e1d96f76017197e3d1af77314b24ce40b8 Mon Sep 17 00:00:00 2001 From: Jaixii Date: Sun, 2 Aug 2026 22:20:41 -0400 Subject: [PATCH 23/35] docs: move Compose details out of README --- README.md | 14 ++------------ docs/DOCKER.md | 26 ++++++++++++++++++++++++++ tests/test_licensing_boundary_docs.py | 14 ++++++++++---- tests/test_release_infrastructure.py | 4 +++- 4 files changed, 41 insertions(+), 17 deletions(-) create mode 100644 docs/DOCKER.md diff --git a/README.md b/README.md index 5cef2e28..3e961a43 100644 --- a/README.md +++ b/README.md @@ -303,18 +303,8 @@ engraphis-dashboard --install-shortcuts # → Desktop + Start Menu icons docker compose up # → http://127.0.0.1:8700 ``` -A fresh clone needs no `.env`: the service runs `engraphis-dashboard --no-open` and stores the v2 -database plus the optional customer-side cloud session and non-authoritative entitlement display -cache on a named volume mounted at `/data`. Generic `.env` settings can supply optional runtime -configuration, but Compose deliberately keeps its container bind address and `/data` paths fixed; -that prevents a desktop `ENGRAPHIS_HOST` or `ENGRAPHIS_DB_PATH` from breaking container reachability -or persistence. To use another loopback port, set `ENGRAPHIS_COMPOSE_PORT` in `.env` or the shell: - -```dotenv -ENGRAPHIS_COMPOSE_PORT=8787 -``` - -Then open `http://127.0.0.1:8787`. License issuance, trials, leases, and revocations remain on the private control plane. +For Docker Compose persistence and loopback-port configuration, see the +[Docker deployment guide](docs/DOCKER.md). `engraphis-server` and `engraphis server` are headless compatibility aliases for this same v2 service, so every public surface has the same scoped recall and retention model. diff --git a/docs/DOCKER.md b/docs/DOCKER.md new file mode 100644 index 00000000..67c7685d --- /dev/null +++ b/docs/DOCKER.md @@ -0,0 +1,26 @@ +# Docker Compose deployment + +## Start the local dashboard + +From a fresh clone, start the Docker Compose deployment with: + +```bash +docker compose up +``` + +The dashboard is available at [http://127.0.0.1:8700](http://127.0.0.1:8700). + +## Persistence and loopback port configuration + +A fresh clone needs no `.env`: the service runs `engraphis-dashboard --no-open` and stores the v2 +database plus the optional customer-side cloud session and non-authoritative entitlement display +cache on a named volume mounted at `/data`. Generic `.env` settings can supply optional runtime +configuration, but Compose deliberately keeps its container bind address and `/data` paths fixed; +that prevents a desktop `ENGRAPHIS_HOST` or `ENGRAPHIS_DB_PATH` from breaking container reachability +or persistence. To use another loopback port, set `ENGRAPHIS_COMPOSE_PORT` in `.env` or the shell: + +```dotenv +ENGRAPHIS_COMPOSE_PORT=8787 +``` + +Then open `http://127.0.0.1:8787`. License issuance, trials, leases, and revocations remain on the private control plane. diff --git a/tests/test_licensing_boundary_docs.py b/tests/test_licensing_boundary_docs.py index f4aa47fe..2f7b62e1 100644 --- a/tests/test_licensing_boundary_docs.py +++ b/tests/test_licensing_boundary_docs.py @@ -161,8 +161,8 @@ def test_container_examples_do_not_describe_private_license_or_relay_state_as_lo assert "Issuance, trial state, leases, and revocations stay private." in compose -def test_readme_describes_only_customer_side_cloud_state_as_persisted(): - """The Docker quickstart must not imply that the public image owns licenses. +def test_docker_docs_describe_only_customer_side_cloud_state_as_persisted(): + """Supporting Docker docs must not imply that the public image owns licenses. The mounted state directory holds a customer-side connection plus a display cache; issuance and entitlement authority stay in the private control plane. Calling that @@ -170,10 +170,16 @@ def test_readme_describes_only_customer_side_cloud_state_as_persisted(): """ readme = _text("README.md") + docker_docs = _text("docs/DOCKER.md") assert "database plus license state" not in readme - assert "customer-side cloud session and non-authoritative entitlement display" in readme + assert "customer-side cloud session and non-authoritative entitlement display" not in readme + assert "customer-side cloud session and non-authoritative entitlement display" in docker_docs assert ( "License issuance, trials, leases, and revocations remain on the private control plane." - in readme + not in readme + ) + assert ( + "License issuance, trials, leases, and revocations remain on the private control plane." + in docker_docs ) diff --git a/tests/test_release_infrastructure.py b/tests/test_release_infrastructure.py index 48386db2..17a1c33f 100644 --- a/tests/test_release_infrastructure.py +++ b/tests/test_release_infrastructure.py @@ -77,6 +77,7 @@ def test_compose_keeps_container_safety_defaults_and_has_an_explicit_port_overri compose = _text("docker-compose.yml") readme = _text("README.md") + docker_docs = _text("docs/DOCKER.md") lan_compose = _text("docker-compose.lan.yml") assert '"127.0.0.1:${ENGRAPHIS_COMPOSE_PORT:-8700}:${ENGRAPHIS_COMPOSE_PORT:-8700}"' in compose @@ -89,7 +90,8 @@ def test_compose_keeps_container_safety_defaults_and_has_an_explicit_port_overri assert "ports: !override" in lan_compose assert '"0.0.0.0:${ENGRAPHIS_COMPOSE_PORT:-8700}:${ENGRAPHIS_COMPOSE_PORT:-8700}"' in lan_compose assert "ENGRAPHIS_API_TOKEN: ${ENGRAPHIS_API_TOKEN:?Set a strong ENGRAPHIS_API_TOKEN for LAN use}" in lan_compose - assert "ENGRAPHIS_COMPOSE_PORT=8787" in readme + assert "[Docker deployment guide](docs/DOCKER.md)" in readme + assert "ENGRAPHIS_COMPOSE_PORT=8787" in docker_docs def test_ci_and_release_audit_production_image_dependencies(): From 2389f96947c5039df9c64631a8f41848c1780843 Mon Sep 17 00:00:00 2001 From: Jaixii Date: Sun, 2 Aug 2026 22:22:31 -0400 Subject: [PATCH 24/35] docs: restore 1.3 README intro --- README.md | 85 +++++++++++++++++--------------- tests/test_benchmark_evidence.py | 2 +- 2 files changed, 45 insertions(+), 42 deletions(-) diff --git a/README.md b/README.md index 3e961a43..bd1c81a8 100644 --- a/README.md +++ b/README.md @@ -1,23 +1,19 @@ # Engraphis [![PyPI version](https://img.shields.io/pypi/v/engraphis.svg)](https://pypi.org/project/engraphis/) -[![CI](https://github.com/Coding-Dev-Tools/engraphis/actions/workflows/ci.yml/badge.svg)](https://github.com/Coding-Dev-Tools/engraphis/actions/workflows/ci.yml) -[![Python 3.9+](https://img.shields.io/pypi/pyversions/engraphis.svg)](https://pypi.org/project/engraphis/) [![License](https://img.shields.io/badge/license-Apache--2.0-green.svg)](https://github.com/Coding-Dev-Tools/engraphis/blob/main/LICENSE) -[![Support](https://img.shields.io/badge/Buy%20Me%20a%20Coffee-support-yellow?logo=buy-me-a-coffee)](https://buymeacoffee.com/Jaixii) +[![Buy Me a Coffee](https://img.shields.io/badge/Buy%20Me%20a%20Coffee-support-yellow?style=for-the-badge&logo=buy-me-a-coffee)](https://buymeacoffee.com/Jaixii) -[Website](https://engraphis.com/) · [Documentation](docs/) · [MCP tools](docs/MCP_TOOLS.md) · -[Security](SECURITY.md) · [Discord](https://discord.com/invite/Wfr2ejBmY) +[https://engraphis.com/](https://engraphis.com/) -**Give coding agents durable project memory so the next session can retrieve the current decision, its evidence, and its history.** +[https://discord.com/invite/Wfr2ejBmY](https://discord.com/invite/Wfr2ejBmY) -> **Support continued Engraphis development with Pro.** [Start a 3-day Pro trial](https://api.engraphis.com/account?plan=pro&interval=monthly&utm_source=engraphis&utm_medium=docs&utm_campaign=pro_conversion&utm_content=readme_intro&trial=pro#billing) -> or [subscribe to Pro](https://api.engraphis.com/account?plan=pro&interval=monthly&utm_source=engraphis&utm_medium=docs&utm_campaign=pro_conversion&utm_content=readme_intro#billing). +**Give your AI agents a memory. See it, search it, and maintain it, all in a beautiful WebUI on your own machine.**

- Project history becomes scoped memory, hybrid recall, and bounded cited context for an agent + Engraphis Knowledge Graph tab: force-directed entity-relation network
- Preserve a project decision · retrieve its supporting evidence · hand the next agent a bounded context + Knowledge Graph · run engraphis-dashboard to see it live

--- @@ -26,38 +22,10 @@ > and customer-side clients. Hosted sync, analytics, automation, and team services run on the > official hosted service; their server implementations are not distributed here. -## Full Engraphis install: pip install "engraphis[all]" - -The complete `engraphis[all]` install is the default way to use Engraphis: it includes the local -dashboard, Smart MCP server, documents, Cloud Sync client, and supported optional integrations. -Python 3.10+ is required. - -```bash -pip install "engraphis[all]" -engraphis-dashboard -``` - -The dashboard opens at [http://127.0.0.1:8700](http://127.0.0.1:8700). Local memory needs no -account or API key. - -### Smaller installation options - -Use a smaller package only when you intentionally need a limited surface. The NumPy-only core -continues to support Python 3.9+. - -| Goal | Install | Start | -|---|---|---| -| Local dashboard and REST API | `pip install "engraphis[server]"` | `engraphis-dashboard` | -| Coding-agent memory over Smart MCP | `pip install "engraphis[mcp]"` | `codex mcp add engraphis -- engraphis-mcp` | -| Offline Python library | `pip install engraphis` | `MemoryService.create("engraphis.db")` | - -For MCP clients other than Codex, configure a stdio server whose command is `engraphis-mcp`; see -the [agent connection guide](docs/AGENT_CONNECT.md). +> **Support continued Engraphis development with Pro.** [Start a 3-day Pro trial](https://api.engraphis.com/account?plan=pro&interval=monthly&utm_source=engraphis&utm_medium=docs&utm_campaign=pro_conversion&utm_content=readme_intro&trial=pro#billing) +> or [subscribe to Pro](https://api.engraphis.com/account?plan=pro&interval=monthly&utm_source=engraphis&utm_medium=docs&utm_campaign=pro_conversion&utm_content=readme_intro#billing). -> **Upgrading to 1.4:** `engraphis-mcp` now exposes the six-tool Smart gateway. Integrations that -> require the former 33 direct tool names should run `engraphis-mcp-classic`. The SQLite schema -> remains version 7, so this MCP surface change does not require a data migration. See the -> [1.4.0 release notes](CHANGELOG.md#140---2026-08-02). +--- ## Measured token and context savings @@ -133,6 +101,41 @@ limitations, canonical external-evaluation requirements, and the no-unsupported- --- +## Full Engraphis install: pip install "engraphis[all]" + +The complete `engraphis[all]` install is the default way to use Engraphis: it includes the local +dashboard, Smart MCP server, documents, Cloud Sync client, and supported optional integrations. +Python 3.10+ is required. + +```bash +pip install "engraphis[all]" +engraphis-dashboard +``` + +The dashboard opens at [http://127.0.0.1:8700](http://127.0.0.1:8700). Local memory needs no +account or API key. + +### Smaller installation options + +Use a smaller package only when you intentionally need a limited surface. The NumPy-only core +continues to support Python 3.9+. + +| Goal | Install | Start | +|---|---|---| +| Local dashboard and REST API | `pip install "engraphis[server]"` | `engraphis-dashboard` | +| Coding-agent memory over Smart MCP | `pip install "engraphis[mcp]"` | `codex mcp add engraphis -- engraphis-mcp` | +| Offline Python library | `pip install engraphis` | `MemoryService.create("engraphis.db")` | + +For MCP clients other than Codex, configure a stdio server whose command is `engraphis-mcp`; see +the [agent connection guide](docs/AGENT_CONNECT.md). + +> **Upgrading to 1.4:** `engraphis-mcp` now exposes the six-tool Smart gateway. Integrations that +> require the former 33 direct tool names should run `engraphis-mcp-classic`. The SQLite schema +> remains version 7, so this MCP surface change does not require a data migration. See the +> [1.4.0 release notes](CHANGELOG.md#140---2026-08-02). + +--- + ## What Engraphis gives an agent An agent should not have to reconstruct a project from scattered chat history on every task. diff --git a/tests/test_benchmark_evidence.py b/tests/test_benchmark_evidence.py index 089cc3de..3f8d68e6 100644 --- a/tests/test_benchmark_evidence.py +++ b/tests/test_benchmark_evidence.py @@ -148,7 +148,7 @@ def test_readme_makes_agent_benefits_and_visual_evidence_scannable(): "Remember a project across sessions", "Avoid confident guesses", "Avoid dragging the whole project into every prompt", - "docs/images/engraphis-benefit-flow.png", + "docs/images/knowledge-graph.png", "docs/images/context-efficiency.svg", "### See the behavior in reproducible fixtures", "docs/images/evidence-backed-agent-examples.svg", From 68581e8bc363f12c28f1ac3c8ef316a57683375d Mon Sep 17 00:00:00 2001 From: Jaixii Date: Sun, 2 Aug 2026 22:23:51 -0400 Subject: [PATCH 25/35] docs: move LAN setup out of README --- README.md | 40 ++------------------------- docs/DOCKER.md | 41 ++++++++++++++++++++++++++++ tests/test_release_infrastructure.py | 16 ++++++----- 3 files changed, 52 insertions(+), 45 deletions(-) diff --git a/README.md b/README.md index bd1c81a8..b678231f 100644 --- a/README.md +++ b/README.md @@ -311,44 +311,8 @@ For Docker Compose persistence and loopback-port configuration, see the `engraphis-server` and `engraphis server` are headless compatibility aliases for this same v2 service, so every public surface has the same scoped recall and retention model. -Compose publishes only on loopback by default. To expose it on a LAN, set a strong API token and -the exact URL clients will use: - -```dotenv -ENGRAPHIS_API_TOKEN= -ENGRAPHIS_DASHBOARD_URL=http://:8700 -``` - -Then start the token-required LAN overlay (Docker Compose v2.24.4+): - -```bash -docker compose -f docker-compose.yml -f docker-compose.lan.yml up -d -``` - -The URL variable alone does not expose or secure the service. The LAN overlay refuses to render -without `ENGRAPHIS_API_TOKEN`; it replaces the loopback port mapping with an all-IPv4-interface mapping. -After this opt-in, other machines on the LAN can use -`http://:8700`. - -The Docker image includes the streamable HTTP MCP endpoint at `/mcp/` (the `/mcp` path redirects -there). Configure `ENGRAPHIS_DASHBOARD_URL` to the exact LAN IP or hostname clients use so MCP's -DNS-rebinding protection accepts the request. For example, use -`http://192.168.10.151:8700` for direct LAN access, or `http://engraphis.local` behind Traefik. -For an HTTP-enabled deployment, use the dashboard port (replace `8700` with your -`ENGRAPHIS_COMPOSE_PORT` value when you override it): - -```json -{ - "engraphis": { - "transport": "http", - "enabled": true, - "url": "http://:8700/mcp/" - } -} -``` - -When `ENGRAPHIS_API_TOKEN` is set, configure the client to send -`Authorization: Bearer `. Remote requests without a token are rejected. +For optional LAN exposure, token configuration, and HTTP MCP setup, see the +[Docker deployment guide](docs/DOCKER.md). Set `ENGRAPHIS_API_TOKEN` to require API authentication and `ENGRAPHIS_DB_KEY` to encrypt the local database at rest. Hosted-plan credentials configure customer clients; they do not diff --git a/docs/DOCKER.md b/docs/DOCKER.md index 67c7685d..1d62260a 100644 --- a/docs/DOCKER.md +++ b/docs/DOCKER.md @@ -24,3 +24,44 @@ ENGRAPHIS_COMPOSE_PORT=8787 ``` Then open `http://127.0.0.1:8787`. License issuance, trials, leases, and revocations remain on the private control plane. + +## LAN exposure and HTTP MCP + +Compose publishes only on loopback by default. To expose it on a LAN, set a strong API token and +the exact URL clients will use: + +```dotenv +ENGRAPHIS_API_TOKEN= +ENGRAPHIS_DASHBOARD_URL=http://:8700 +``` + +Then start the token-required LAN overlay (Docker Compose v2.24.4+): + +```bash +docker compose -f docker-compose.yml -f docker-compose.lan.yml up -d +``` + +The URL variable alone does not expose or secure the service. The LAN overlay refuses to render +without `ENGRAPHIS_API_TOKEN`; it replaces the loopback port mapping with an all-IPv4-interface mapping. +After this opt-in, other machines on the LAN can use +`http://:8700`. + +The Docker image includes the streamable HTTP MCP endpoint at `/mcp/` (the `/mcp` path redirects +there). Configure `ENGRAPHIS_DASHBOARD_URL` to the exact LAN IP or hostname clients use so MCP's +DNS-rebinding protection accepts the request. For example, use +`http://192.168.10.151:8700` for direct LAN access, or `http://engraphis.local` behind Traefik. +For an HTTP-enabled deployment, use the dashboard port (replace `8700` with your +`ENGRAPHIS_COMPOSE_PORT` value when you override it): + +```json +{ + "engraphis": { + "transport": "http", + "enabled": true, + "url": "http://:8700/mcp/" + } +} +``` + +When `ENGRAPHIS_API_TOKEN` is set, configure the client to send +`Authorization: Bearer `. Remote requests without a token are rejected. diff --git a/tests/test_release_infrastructure.py b/tests/test_release_infrastructure.py index 17a1c33f..cbc34f8b 100644 --- a/tests/test_release_infrastructure.py +++ b/tests/test_release_infrastructure.py @@ -52,6 +52,7 @@ def test_published_image_and_railway_template_fail_safe_to_customer_mode(): def test_all_public_launchers_converge_on_the_v2_service(): compose = _text("docker-compose.yml") readme = _text("README.md") + docker_docs = _text("docs/DOCKER.md") dockerfile = _text("Dockerfile") launcher = _text("scripts/start_server.py") @@ -59,14 +60,15 @@ def test_all_public_launchers_converge_on_the_v2_service(): assert "engraphis_v1.db" not in compose assert 'command: ["engraphis-dashboard", "--no-open"]' in compose assert '"127.0.0.1:${ENGRAPHIS_COMPOSE_PORT:-8700}:${ENGRAPHIS_COMPOSE_PORT:-8700}"' in compose - assert '"url": "http://:8700/mcp/"' in readme + assert '"url": "http://:8700/mcp/"' in docker_docs assert '".[server,mcp,documents,cloud-sync]"' in dockerfile - assert "The Docker image includes the streamable HTTP MCP endpoint" in readme - assert "ENGRAPHIS_API_TOKEN=" in readme - assert "docker-compose.lan.yml" in readme - assert "LAN overlay refuses to render" in readme - assert "ENGRAPHIS_DASHBOARD_URL" in readme - assert "ENGRAPHIS_COMPOSE_PORT" in readme + assert "[Docker deployment guide](docs/DOCKER.md)" in readme + assert "The Docker image includes the streamable HTTP MCP endpoint" in docker_docs + assert "ENGRAPHIS_API_TOKEN=" in docker_docs + assert "docker-compose.lan.yml" in docker_docs + assert "LAN overlay refuses to render" in docker_docs + assert "ENGRAPHIS_DASHBOARD_URL" in docker_docs + assert "ENGRAPHIS_COMPOSE_PORT" in docker_docs assert "start_dashboard.main(args)" in launcher assert "engraphis.app" not in launcher assert "same v2 service" in readme From 3df05d5a7bdd60b426fcea488f763061a51548c4 Mon Sep 17 00:00:00 2001 From: Jaixii Date: Sun, 2 Aug 2026 22:26:07 -0400 Subject: [PATCH 26/35] docs: preserve support badge --- README.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/README.md b/README.md index b678231f..ff237f0a 100644 --- a/README.md +++ b/README.md @@ -2,7 +2,7 @@ [![PyPI version](https://img.shields.io/pypi/v/engraphis.svg)](https://pypi.org/project/engraphis/) [![License](https://img.shields.io/badge/license-Apache--2.0-green.svg)](https://github.com/Coding-Dev-Tools/engraphis/blob/main/LICENSE) -[![Buy Me a Coffee](https://img.shields.io/badge/Buy%20Me%20a%20Coffee-support-yellow?style=for-the-badge&logo=buy-me-a-coffee)](https://buymeacoffee.com/Jaixii) +[![Support](https://img.shields.io/badge/Buy%20Me%20a%20Coffee-support-yellow?logo=buy-me-a-coffee)](https://buymeacoffee.com/Jaixii) [https://engraphis.com/](https://engraphis.com/) From fe26c4f9d0609dc63c090ea4420c89bba5a8ce40 Mon Sep 17 00:00:00 2001 From: Jaixii Date: Sun, 2 Aug 2026 22:28:28 -0400 Subject: [PATCH 27/35] docs: move vector backend detail out of README --- README.md | 6 ------ docs/ARCHITECTURE_V3.md | 8 ++++++++ tests/test_release_infrastructure.py | 9 +++++++++ 3 files changed, 17 insertions(+), 6 deletions(-) diff --git a/README.md b/README.md index ff237f0a..b5649c44 100644 --- a/README.md +++ b/README.md @@ -267,12 +267,6 @@ pipeline. Measure your machine with `python -m eval.vector_scale`, then run create the engine with `vector_backend="sqlite-vec"` and remeasure. See [BENCHMARKS.md](BENCHMARKS.md) for the reproducible commands and reporting limits. -`MemoryEngine.create()` and `MemoryService.create()` default to the exact NumPy index, even when -`sqlite-vec` is installed, so the default remains portable and deterministic. `sqlite-vec` and -SQLCipher load incompatible SQLite native libraries in one process: with `vector_backend="auto"` -Engraphis falls back to NumPy; an explicit `vector_backend="sqlite-vec"` fails with an actionable -error. Run accelerated search in a fresh process when using the SQLCipher extra. - `sqlcipher3-binary` publishes CPython manylinux x86-64 wheels. On that target, `engraphis[encryption]` installs the driver. The cross-platform `all` extra deliberately omits it so `all` remains resolvable on macOS, Windows, Linux ARM, and musl; on those diff --git a/docs/ARCHITECTURE_V3.md b/docs/ARCHITECTURE_V3.md index 616d974a..11289238 100644 --- a/docs/ARCHITECTURE_V3.md +++ b/docs/ARCHITECTURE_V3.md @@ -75,6 +75,14 @@ flowchart LR Migration is additive and idempotent. Pre-v3 edge layers are inferred exactly once; explicitly selected layers are never reclassified when a database is reopened. +## Vector backend compatibility + +`MemoryEngine.create()` and `MemoryService.create()` default to the exact NumPy index, even when +`sqlite-vec` is installed, so the default remains portable and deterministic. `sqlite-vec` and +SQLCipher load incompatible SQLite native libraries in one process: with `vector_backend="auto"` +Engraphis falls back to NumPy; an explicit `vector_backend="sqlite-vec"` fails with an actionable +error. Run accelerated search in a fresh process when using the SQLCipher extra. + ## Repo workflow ```bash diff --git a/tests/test_release_infrastructure.py b/tests/test_release_infrastructure.py index cbc34f8b..e8fb9170 100644 --- a/tests/test_release_infrastructure.py +++ b/tests/test_release_infrastructure.py @@ -74,6 +74,15 @@ def test_all_public_launchers_converge_on_the_v2_service(): assert "same v2 service" in readme +def test_native_vector_backend_compatibility_stays_in_architecture_docs(): + readme = _text("README.md") + architecture = _text("docs/ARCHITECTURE_V3.md") + guidance = "`MemoryEngine.create()` and `MemoryService.create()` default to the exact NumPy index" + + assert guidance not in readme + assert guidance in architecture + + def test_compose_keeps_container_safety_defaults_and_has_an_explicit_port_override(): """Generic desktop .env values must not break the published container contract.""" From 93bca599e09635a7d785c8adc837983f71011ea1 Mon Sep 17 00:00:00 2001 From: Jaixii Date: Sun, 2 Aug 2026 22:32:08 -0400 Subject: [PATCH 28/35] docs: move public review guidance out of README --- README.md | 51 ++-------------------------- docs/MCP_TOOLS.md | 3 ++ docs/WRITE_REVIEW.md | 35 +++++++++++++++++++ tests/test_release_infrastructure.py | 15 ++++++++ 4 files changed, 55 insertions(+), 49 deletions(-) create mode 100644 docs/WRITE_REVIEW.md diff --git a/README.md b/README.md index b5649c44..b80067b2 100644 --- a/README.md +++ b/README.md @@ -339,55 +339,8 @@ including `engraphis_check_update`, is in the [MCP tool reference](docs/MCP_TOOL ### Pi extension -Pi users install the first-party extension from npm after installing Engraphis 1.4.x on -Python 3.10 or later: - -```bash -python -m pip install --upgrade "engraphis[mcp]>=1.4.0,<2" -pi install npm:@engraphis/pi -``` - -The extension exposes the six Smart MCP tools as native Pi tools. It confirms every advanced -state-changing action through Pi's UI and fails closed when the current Pi mode cannot present -that approval. Package configuration, update/removal commands, and the local trust boundary are -documented in [`integrations/pi/README.md`](integrations/pi/README.md). - -For unattended jobs, `engraphis_session`, `engraphis_remember`, and discovered actions use -workspace `default` when `workspace` is omitted. - -### Review gate for MCP, REST, imports, and sync - -Every public write enters review as `pending`, regardless of a caller-supplied `source` or -`trusted` label. That includes MCP, dashboard/REST intent writes, imports, sync, and extractor -output. Detector matches are instead `quarantined` immediately. Pending and quarantined records -remain inspectable and auditable, but cannot enter model-ready recall/context, resolution, -links, graph/code backfill, derived prompt context, or public `why`/`timeline` history. -Corrections, promotions, and merges fail closed unless every input is explicitly approved. - -Approval creates a fresh `approved` successor and preserves the reviewed source plus an audit -link; it never relabels the source in place. There is deliberately no MCP tool or general REST -approval endpoint. A local owner can approve through the dashboard's **Approve for prompt** -action after configuring `ENGRAPHIS_API_TOKEN` (short-lived browser session plus CSRF confirmation), -or from an interactive terminal: - -```bash -python -m scripts.approve_memory mem_... --reason "verified against the owner runbook" -``` - -The command rejects redirected input and requires typing its displayed confirmation. Hosted -owner/admin approval is performed by the hosted service, not this local package. The direct -in-process `MemoryEngine` remains a documented trusted-code boundary for code that already has -local database authority; do not expose it to untrusted transports. Existing stores can be -inspected without writes, then migrated deliberately: - -```bash -python -m scripts.rescan_poisoning --db engraphis.db -python -m scripts.rescan_poisoning --db engraphis.db --apply -``` - -The dry run opens the database read-only. The applying pass demotes historical non-approved -records to pending review, quarantines detected payloads, retires their derived bridges, and -records an audit event. +For installation, configuration, lifecycle commands, and the local trust boundary, see the +[Pi extension guide](integrations/pi/README.md). ## Quickstart: repository graph diff --git a/docs/MCP_TOOLS.md b/docs/MCP_TOOLS.md index 61d2a031..f63e22f7 100644 --- a/docs/MCP_TOOLS.md +++ b/docs/MCP_TOOLS.md @@ -46,6 +46,9 @@ redirected input and requires a typed confirmation. Hosted approval is an owner/ the private hosted service. Direct in-process `MemoryEngine` use is a trusted-code boundary for code that already has local database authority, not a transport permission. +For the full public-write review and existing-store migration procedure, see the +[public write review gate](WRITE_REVIEW.md). + | Category | Tool | What it does | |---|---|---| | Write | `engraphis_remember` | Stores a fact and resolves it as a new memory, reinforcement, safe supersession, or related memory. | diff --git a/docs/WRITE_REVIEW.md b/docs/WRITE_REVIEW.md new file mode 100644 index 00000000..50756bb3 --- /dev/null +++ b/docs/WRITE_REVIEW.md @@ -0,0 +1,35 @@ +# Public write review gate + +## MCP, REST, imports, and sync + +Every public write enters review as `pending`, regardless of a caller-supplied `source` or +`trusted` label. That includes MCP, dashboard/REST intent writes, imports, sync, and extractor +output. Detector matches are instead `quarantined` immediately. Pending and quarantined records +remain inspectable and auditable, but cannot enter model-ready recall/context, resolution, +links, graph/code backfill, derived prompt context, or public `why`/`timeline` history. +Corrections, promotions, and merges fail closed unless every input is explicitly approved. + +Approval creates a fresh `approved` successor and preserves the reviewed source plus an audit +link; it never relabels the source in place. There is deliberately no MCP tool or general REST +approval endpoint. A local owner can approve through the dashboard's **Approve for prompt** +action after configuring `ENGRAPHIS_API_TOKEN` (short-lived browser session plus CSRF confirmation), +or from an interactive terminal: + +```bash +python -m scripts.approve_memory mem_... --reason "verified against the owner runbook" +``` + +The command rejects redirected input and requires typing its displayed confirmation. Hosted +owner/admin approval is performed by the hosted service, not this local package. The direct +in-process `MemoryEngine` remains a documented trusted-code boundary for code that already has +local database authority; do not expose it to untrusted transports. Existing stores can be +inspected without writes, then migrated deliberately: + +```bash +python -m scripts.rescan_poisoning --db engraphis.db +python -m scripts.rescan_poisoning --db engraphis.db --apply +``` + +The dry run opens the database read-only. The applying pass demotes historical non-approved +records to pending review, quarantines detected payloads, retires their derived bridges, and +records an audit event. diff --git a/tests/test_release_infrastructure.py b/tests/test_release_infrastructure.py index e8fb9170..ee8062e4 100644 --- a/tests/test_release_infrastructure.py +++ b/tests/test_release_infrastructure.py @@ -83,6 +83,21 @@ def test_native_vector_backend_compatibility_stays_in_architecture_docs(): assert guidance in architecture +def test_pi_and_public_write_review_details_stay_in_supporting_docs(): + readme = _text("README.md") + pi_guide = _text("integrations/pi/README.md") + review_guide = _text("docs/WRITE_REVIEW.md") + + assert "[Pi extension guide](integrations/pi/README.md)" in readme + assert "pi install npm:@engraphis/pi" not in readme + assert "Every advanced state-changing action requires an explicit Pi confirmation dialog" in pi_guide + + review_gate = "Every public write enters review as `pending`" + assert review_gate not in readme + assert review_gate in review_guide + assert "python -m scripts.rescan_poisoning --db engraphis.db --apply" in review_guide + + def test_compose_keeps_container_safety_defaults_and_has_an_explicit_port_override(): """Generic desktop .env values must not break the published container contract.""" From 40fc297f5cb4577f0fdf9adf2034757c400f5055 Mon Sep 17 00:00:00 2001 From: Jaixii Date: Sun, 2 Aug 2026 22:33:23 -0400 Subject: [PATCH 29/35] docs: move query planning details out of README --- README.md | 32 ++------------------------- docs/ARCHITECTURE_V3.md | 33 ++++++++++++++++++++++++++++ tests/test_release_infrastructure.py | 11 ++++++++++ 3 files changed, 46 insertions(+), 30 deletions(-) diff --git a/README.md b/README.md index b80067b2..9514a702 100644 --- a/README.md +++ b/README.md @@ -418,36 +418,8 @@ For an agent prompt, prefer `engraphis_recall_context`: it returns one hard-budg `token_counter`), and optional diagnostics. Accounting is exact for the named counter; inject the reader's tokenizer when reader-model token parity is required. `engraphis_recall` remains the compatible full-recall surface; use `response_mode="compact"` when the packed context is enough and full memory bodies -would duplicate it. Both default to the `balanced` retrieval profile and `planning="off"`. -Opt-in `planning="auto"` keeps the original query, admits at most two deterministic or injected -query routes, and fuses them before reranking against the original query. `mtype_limits`, when -provided, are post-rerank maximum counts rather than relevance boosts. Every packed response has a -stable `context_revision` derived from the token-counter identity and ordered packed excerpts, so a -host can retain an unchanged prompt prefix. Planner output, per-query rankings, cap drops, and -fallback reasons appear only with `diagnostics=True`. - -The offline planner is the default injected implementation. An application can opt into an LLM -planner without coupling `core/` to a provider: - -```python -from engraphis.backends.query_planner import LLMQueryPlanner -from engraphis.core.engine import MemoryEngine - -engine = MemoryEngine.create( - "engraphis.db", - query_planner=LLMQueryPlanner(my_llm), -) -result = engine.recall( - "why does ReleaseGate depend on AuditLog?", - workspace_id="ws_...", - planning="auto", - mtype_limits={"working": 1, "semantic": 3}, -) -``` - -Planner failures and provider deadlines fail open to the original single-query plan. Planned recall -remains opt-in until the checked-in budget, safety, and official LongMemEval-V2 gates justify a -default change. +would duplicate it. For advanced query-planning configuration, see the +[architecture guide](docs/ARCHITECTURE_V3.md#query-planning). For bi-temporal reads, `valid_at` selects what was true at a Unix timestamp and `known_at` selects what Engraphis had learned then. `as_of` remains a compatibility alias for `valid_at`; supplying diff --git a/docs/ARCHITECTURE_V3.md b/docs/ARCHITECTURE_V3.md index 11289238..f95c74d7 100644 --- a/docs/ARCHITECTURE_V3.md +++ b/docs/ARCHITECTURE_V3.md @@ -83,6 +83,39 @@ SQLCipher load incompatible SQLite native libraries in one process: with `vector Engraphis falls back to NumPy; an explicit `vector_backend="sqlite-vec"` fails with an actionable error. Run accelerated search in a fresh process when using the SQLCipher extra. +## Query planning + +Recall defaults to the `balanced` retrieval profile and `planning="off"`. Opt-in +`planning="auto"` keeps the original query, admits at most two deterministic or injected query +routes, and fuses them before reranking against the original query. `mtype_limits`, when provided, +are post-rerank maximum counts rather than relevance boosts. Every packed response has a stable +`context_revision` derived from the token-counter identity and ordered packed excerpts, so a host +can retain an unchanged prompt prefix. Planner output, per-query rankings, cap drops, and fallback +reasons appear only with `diagnostics=True`. + +The offline planner is the default injected implementation. An application can opt into an LLM +planner without coupling `core/` to a provider: + +```python +from engraphis.backends.query_planner import LLMQueryPlanner +from engraphis.core.engine import MemoryEngine + +engine = MemoryEngine.create( + "engraphis.db", + query_planner=LLMQueryPlanner(my_llm), +) +result = engine.recall( + "why does ReleaseGate depend on AuditLog?", + workspace_id="ws_...", + planning="auto", + mtype_limits={"working": 1, "semantic": 3}, +) +``` + +Planner failures and provider deadlines fail open to the original single-query plan. Planned recall +remains opt-in until the checked-in budget, safety, and official LongMemEval-V2 gates justify a +default change. + ## Repo workflow ```bash diff --git a/tests/test_release_infrastructure.py b/tests/test_release_infrastructure.py index ee8062e4..18ef2ffb 100644 --- a/tests/test_release_infrastructure.py +++ b/tests/test_release_infrastructure.py @@ -83,6 +83,17 @@ def test_native_vector_backend_compatibility_stays_in_architecture_docs(): assert guidance in architecture +def test_advanced_query_planning_stays_in_architecture_docs(): + readme = _text("README.md") + architecture = _text("docs/ARCHITECTURE_V3.md") + guidance = "`planning=\"auto\"` keeps the original query" + + assert "[architecture guide](docs/ARCHITECTURE_V3.md#query-planning)" in readme + assert guidance not in readme + assert guidance in architecture + assert "LLMQueryPlanner(my_llm)" in architecture + + def test_pi_and_public_write_review_details_stay_in_supporting_docs(): readme = _text("README.md") pi_guide = _text("integrations/pi/README.md") From 9ec46b3cb9388f1aa67fda6791cb5c0a316fb601 Mon Sep 17 00:00:00 2001 From: Jaixii Date: Sun, 2 Aug 2026 22:51:21 -0400 Subject: [PATCH 30/35] fix: address review regressions and core test floor --- README.md | 14 +++---- docs/images/context-efficiency.svg | 8 ++-- engraphis/backends/embedder_api.py | 8 +++- engraphis/core/store.py | 52 ++++++++++++++++---------- tests/test_benchmark_evidence.py | 14 ++++--- tests/test_core_store.py | 17 +++++++++ tests/test_embeddings.py | 13 ++++++- tests/test_provider_error_redaction.py | 5 ++- 8 files changed, 91 insertions(+), 40 deletions(-) diff --git a/README.md b/README.md index 9514a702..3d235f78 100644 --- a/README.md +++ b/README.md @@ -30,7 +30,7 @@ ## Measured token and context savings

- Dark chart showing Engraphis using 98.21 percent less long-history context, 71.1 percent less retrieved content per question, 73.9 percent fewer tokens in the smallest useful memory, a 55.38 percent smaller memory response, and 47.8 percent less repeated-memory context after consolidation + Dark chart showing Engraphis using 98.21 percent less long-history context, 73.0 percent less retrieved content per question, 73.9 percent fewer tokens in the smallest useful memory, a 55.38 percent smaller memory response, and 47.8 percent less repeated-memory context after consolidation
Less repeated history means more room for the task, tools, and useful evidence.

@@ -47,11 +47,11 @@ | Retrieval mode | Mean returned memory content | Recall@5 | |---|---:|---:| -| Whole documents | 740.3 tokens | 1.000 | -| Engraphis structure-aware chunks | 214.1 tokens | 1.000 | +| Whole documents | 808.8 tokens | 1.000 | +| Engraphis structure-aware chunks | 218.4 tokens | 1.000 | -The chunked mode returns the relevant passage instead of the whole document: **526.2 fewer tokens -per question**. Under the same model-context budget, that leaves roughly **526 tokens** for task +The chunked mode returns the relevant passage instead of the whole document: **590.4 fewer tokens +per question**. Under the same model-context budget, that leaves roughly **590 tokens** for task instructions or other relevant evidence. ### Measurement details and reproducibility @@ -62,11 +62,11 @@ boundary. | What is counted | Comparison | Measured reduction | Quality held constant | |---|---|---|---| | Cumulative reader context across a 1,986-question LoCoMo diagnostic | Full-history replay: **49,915,394** tokens → Engraphis: **891,857** tokens | **49,023,537 fewer context tokens** (**98.2133% lower**) | Focused retrieval used far less context; uncapped full history retained higher retrieval recall | -| Retrieved top-5 memory content, averaged per question | Whole documents: **740.3** tokens → structure-aware chunks: **214.1** tokens | **526.2 fewer tokens per question** (**71.1% lower**, about **3.5× smaller**) | Recall@5 **1.000** in both modes across 6 documents and 18 questions | +| Retrieved top-5 memory content, averaged per question | Whole documents: **808.8** tokens → structure-aware chunks: **218.4** tokens | **590.4 fewer tokens per question** (**73.0% lower**, about **3.7× smaller**) | Recall@5 **1.000** in both modes across 6 documents and 18 questions | | Smallest returned memory that contains the reference evidence | Whole documents: **162.2** tokens → chunks: **42.4** tokens | **119.8 fewer tokens to evidence** (**73.9% lower**, about **3.8× smaller**) | The same 18 questions had a returned evidence-holding memory in both modes | | Serialized MCP recall response across 260 timed CodeMem recalls | Full result: **17,172** `engraphis.regex.v1` tokens → compact result: **7,663** tokens | **9,509 response tokens avoided** (**55.38% lower**) | Recall@5, hit@5, and answer-token recall all **1.000** | | Repeated-memory consolidation fixture | 12 related episodic memories: **230** tokens → one digest: **120** tokens | **110 tokens removed from the active digest** (**47.8% lower**) | Original memories remain available for provenance and audit | -| Small histories across 26 CodeMem agent tasks | Always retrieve: **1,883** total agent-facing tokens and **26** memory calls → adaptive: **1,942** tokens and **0** memory calls | Adaptive routing skipped all 26 unnecessary searches; this fixture does **not** show a token saving | Both completed **24/26** tasks with the same deterministic offline task agent | +| Small histories across 26 CodeMem agent tasks | Always retrieve: **2,194** total agent-facing tokens and **26** memory calls → adaptive: **1,942** tokens and **0** memory calls | **252 tokens avoided** (**11.5% lower**) and all 26 unnecessary searches skipped | Both completed **24/26** tasks with the same deterministic offline task agent | | Packed prompt-context usage in the same CodeMem performance fixture | Hard budget: **1,500** tokens; observed mean: **87.73**; observed maximum: **106** | A hard cap prevents a recall from exceeding its configured context budget | This is usage accounting, not a before/after savings comparison | The compact MCP response avoids duplicating full memory bodies when the packed context and source diff --git a/docs/images/context-efficiency.svg b/docs/images/context-efficiency.svg index 60fdfbb8..098748ee 100644 --- a/docs/images/context-efficiency.svg +++ b/docs/images/context-efficiency.svg @@ -1,6 +1,6 @@ Engraphis measured token and context savings - A dark-mode chart with five measured comparisons. Engraphis used 98.21 percent less context over a long-history workload, 71.1 percent less retrieved context per question, 73.9 percent fewer tokens in the smallest useful memory, returned a 55.38 percent smaller memory-tool response, and reduced a repeated-memory cluster by 47.8 percent through consolidation. Supporting measurements show 53 times more evidence than recency-only retrieval at the same budget, 97.72 percent less total context after including the complete indexing pass with break-even by question 10, and an observed maximum of 106 context tokens under a 1500-token cap. + A dark-mode chart with five measured comparisons. Engraphis used 98.21 percent less context over a long-history workload, 73.0 percent less retrieved context per question, 73.9 percent fewer tokens in the smallest useful memory, returned a 55.38 percent smaller memory-tool response, and reduced a repeated-memory cluster by 47.8 percent through consolidation. Supporting measurements show 53 times more evidence than recency-only retrieval at the same budget, 97.72 percent less total context after including the complete indexing pass with break-even by question 10, and an observed maximum of 106 context tokens under a 1500-token cap. @@ -43,11 +43,11 @@ Retrieved memory content per question Long-document test · 18 questions · Recall@5 1.000 - Whole documents · 740.3 tokens + Whole documents · 808.8 tokens - Focused chunks · 214.1 tokens + Focused chunks · 218.4 tokens - 71.1% less + 73.0% less diff --git a/engraphis/backends/embedder_api.py b/engraphis/backends/embedder_api.py index ce1a2390..22c07c3a 100644 --- a/engraphis/backends/embedder_api.py +++ b/engraphis/backends/embedder_api.py @@ -150,9 +150,15 @@ def _finalize_vectors( widths = {len(vector) for vector in vectors if vector is not None} if self._dim is not None: widths.add(self._dim) + if not widths: + # Without a configured or successfully observed width, zero vectors + # cannot establish an embedding-space contract. Guessing 384 here + # would poison future successful responses from a differently-sized + # provider model. + raise RuntimeError("embedding provider returned no usable vectors") if len(widths) > 1: raise RuntimeError("embedding provider returned inconsistent dimensions") - dimension = next(iter(widths), 384) + dimension = next(iter(widths)) if not 1 <= dimension <= MAX_EMBEDDING_DIM: raise RuntimeError("embedding provider returned an invalid dimension") completed = [ diff --git a/engraphis/core/store.py b/engraphis/core/store.py index ccbe9e83..24f47089 100644 --- a/engraphis/core/store.py +++ b/engraphis/core/store.py @@ -2554,25 +2554,39 @@ def fts_search(self, query: str, k: int = 20, # would be treated as a pattern and over-match (a bare "%" matching everything). # Use the same conservative inflection variants as FTS5 so lexical-only degraded # mode remains useful on SQLite builds without FTS5. - # Preserve literal wildcard queries. ``_fts_terms`` intentionally removes - # punctuation for FTS syntax, but the LIKE fallback has always supported - # searching for a literal percent, underscore, or backslash. - like_terms = [q] if any(char in q for char in ("%", "_", "\\")) else terms - like_clauses = [] - like_params: list[Any] = [] - for term in like_terms: - like = f"%{_escape_like(term)}%" - like_clauses.append("(f.content LIKE ? ESCAPE '\\' OR f.title LIKE ? ESCAPE '\\')") - like_params.extend((like, like)) - if not like_clauses: - return [] - rows = self.conn.execute( - "SELECT f.id FROM mem_fts f JOIN memories m ON m.id = f.id " - "WHERE (" + " OR ".join(like_clauses) + ")" - + extra + " LIMIT ?", - (*like_params, *params, k), - ).fetchall() - return [(r["id"], 0.5) for r in rows] + # ``_fts_terms`` intentionally removes punctuation for FTS syntax. In the + # LIKE fallback, retain the literal query first: C++ and v1.2 must not be + # reduced to broad C/v1/2 matches that consume the caller's result limit. + def search_like( + search_terms: list[str], limit: int, excluded: Optional[list[str]] = None + ) -> list[str]: + clauses = [] + query_params: list[Any] = [] + for term in search_terms: + like = f"%{_escape_like(term)}%" + clauses.append("(f.content LIKE ? ESCAPE '\\' OR f.title LIKE ? ESCAPE '\\')") + query_params.extend((like, like)) + if not clauses or limit <= 0: + return [] + exclusions = "" + if excluded: + marks = ",".join("?" for _ in excluded) + exclusions = f" AND f.id NOT IN ({marks})" + rows = self.conn.execute( + "SELECT f.id FROM mem_fts f JOIN memories m ON m.id = f.id " + "WHERE (" + " OR ".join(clauses) + ")" + extra + exclusions + " LIMIT ?", + (*query_params, *params, *(excluded or []), limit), + ).fetchall() + return [row["id"] for row in rows] + + literal_ids = search_like([q], k) + if len(literal_ids) >= k: + return [(memory_id, 0.5) for memory_id in literal_ids] + # Add the ordinary token/inflection matches only after literal results, and + # avoid repeating a literal term for simple punctuation-free queries. + variants = [term for term in terms if term.casefold() != q.casefold()] + variant_ids = search_like(variants, k - len(literal_ids), literal_ids) + return [(memory_id, 0.5) for memory_id in [*literal_ids, *variant_ids]] # ── graph ───────────────────────────────────────────────────────────────── def upsert_entity(self, node: Node, *, commit: bool = True) -> str: diff --git a/tests/test_benchmark_evidence.py b/tests/test_benchmark_evidence.py index 3f8d68e6..de00d2c4 100644 --- a/tests/test_benchmark_evidence.py +++ b/tests/test_benchmark_evidence.py @@ -87,7 +87,7 @@ def test_readme_distinguishes_every_current_token_context_measurement(): for evidence in ( "## Measured token and context savings", "98.21 percent less long-history context", - "71.1 percent less retrieved content per question", + "73.0% lower", "73.9 percent fewer tokens in the smallest useful memory", "55.38 percent smaller memory response", "47.8 percent less repeated-memory context after consolidation", @@ -95,14 +95,16 @@ def test_readme_distinguishes_every_current_token_context_measurement(): "### Measurement details and reproducibility", "49,915,394** tokens → Engraphis: **891,857** tokens", "98.2133% lower", - "740.3** tokens → structure-aware chunks: **214.1** tokens", - "71.1% lower", + "808.8** tokens → structure-aware chunks: **218.4** tokens", + "73.0% lower", "162.2** tokens → chunks: **42.4** tokens", "73.9% lower", "17,172** `engraphis.regex.v1` tokens → compact result: **7,663** tokens", "55.38% lower", "230** tokens → one digest: **120** tokens", "47.8% lower", + "2,194** total agent-facing tokens", + "252 tokens avoided", "1,500** tokens; observed mean: **87.73**; observed maximum: **106**", "must not be added together", "not a storage-reduction claim", @@ -223,9 +225,9 @@ def test_context_savings_visual_is_plain_language_and_uses_measured_results(): "Engraphis · 891,857 tokens", "98.21% less", "Focused context; full-history recall was higher", - "Whole documents · 740.3 tokens", - "Focused chunks · 214.1 tokens", - "71.1% less", + "Whole documents · 808.8 tokens", + "Focused chunks · 218.4 tokens", + "73.0% less", "Whole document · 162.2 tokens", "Useful chunk · 42.4 tokens", "73.9% less", diff --git a/tests/test_core_store.py b/tests/test_core_store.py index 029cefb6..6198a92f 100644 --- a/tests/test_core_store.py +++ b/tests/test_core_store.py @@ -1036,6 +1036,23 @@ def test_fts_fallback_escapes_like_wildcards(store): assert store.fts_search("_", 10) == [] # '_' is literal, not "any character" +@pytest.mark.parametrize( + ("query", "broad_match", "exact_match"), + [ + ("C++", "C language guide", "C++ compiler guide"), + ("v1.2", "v1 migration notes", "v1.2 compatibility notes"), + ], +) +def test_fts_fallback_prioritizes_literal_punctuation_before_token_variants( + store, query, broad_match, exact_match): + wid = store.get_or_create_workspace("w") + store.add_memory(MemoryRecord(id="mem_broad", content=broad_match, workspace_id=wid)) + store.add_memory(MemoryRecord(id="mem_exact", content=exact_match, workspace_id=wid)) + store.has_fts5 = False + + assert store.fts_search(query, 1) == [("mem_exact", 0.5)] + + # ── regression: indexes exist, and are added to pre-existing databases ──────── def _index_names(conn): diff --git a/tests/test_embeddings.py b/tests/test_embeddings.py index cdb5ce53..27574ec3 100644 --- a/tests/test_embeddings.py +++ b/tests/test_embeddings.py @@ -2,7 +2,6 @@ import numpy as np import pytest -import httpx from engraphis.backends.embedder_api import ApiEmbedder from engraphis.backends.embedder_deterministic import DeterministicEmbedder, _tokenize @@ -99,6 +98,7 @@ def test_api_batch_vectors_require_complete_unique_indices_and_consistent_width( def test_api_per_item_fallback_is_cardinality_safe_and_normalized(monkeypatch): + httpx = pytest.importorskip("httpx") responses = [ {"data": [{"index": 0, "embedding": [3.0, 4.0]}]}, {"data": [{"index": 0, "embedding": [0.0, 2.0]}]}, @@ -137,6 +137,7 @@ def post(self, *_args, **kwargs): def test_api_per_item_fallback_fills_malformed_rows_at_the_valid_width(monkeypatch): + httpx = pytest.importorskip("httpx") responses = [ {"data": [{"index": "private-index", "embedding": [9.0]}]}, {"data": [{"index": 0, "embedding": [0.0, 2.0]}]}, @@ -175,7 +176,16 @@ def post(self, *_args, **kwargs): np.testing.assert_allclose(result, [[0.0, 0.0], [0.0, 1.0]]) +def test_api_rejects_all_failed_fallback_without_a_known_dimension(): + embedder = ApiEmbedder(model="model", api_key="key") + + with pytest.raises(RuntimeError, match="no usable vectors"): + embedder._finalize_vectors([None, None], 2) + assert embedder._dim is None + + def test_api_rejects_configured_dimension_mismatch_from_batch_response(monkeypatch): + httpx = pytest.importorskip("httpx") class _Response: def raise_for_status(self): return None @@ -203,6 +213,7 @@ def post(self, *_args, **_kwargs): def test_api_rejects_configured_dimension_mismatch_during_per_item_fallback(monkeypatch): + httpx = pytest.importorskip("httpx") class _Response: def __init__(self, payload): self.payload = payload diff --git a/tests/test_provider_error_redaction.py b/tests/test_provider_error_redaction.py index a8b44a1a..0cc9becf 100644 --- a/tests/test_provider_error_redaction.py +++ b/tests/test_provider_error_redaction.py @@ -181,11 +181,12 @@ def post(self, *_args, **_kwargs): base_url="https://provider.example/%s" % endpoint_marker, api_key="safe-key", ) - result = embedder.embed(["hello"]) + with pytest.raises(RuntimeError, match="no usable vectors") as caught: + embedder.embed(["hello"]) - assert result.shape == (1, 384) for marker in (model_marker, endpoint_marker, index_marker, "owner@example.com"): assert marker not in caplog.text + assert marker not in str(caught.value) def test_api_embedder_failure_logs_do_not_include_api_key(monkeypatch, caplog): From f6e3e4056a70aed6049ec2cbb91d99e4e73798d7 Mon Sep 17 00:00:00 2001 From: Jaixii Date: Sun, 2 Aug 2026 23:04:31 -0400 Subject: [PATCH 31/35] fix: filter prompt graph edges before frontier cap --- engraphis/core/recall.py | 4 ++-- engraphis/core/store.py | 50 +++++++++++++++++++++++++++++++++++----- tests/test_core_store.py | 24 +++++++++++++++++++ 3 files changed, 70 insertions(+), 8 deletions(-) diff --git a/engraphis/core/recall.py b/engraphis/core/recall.py index a6331f1c..0202e690 100644 --- a/engraphis/core/recall.py +++ b/engraphis/core/recall.py @@ -1003,7 +1003,7 @@ def connect(a: str, b: str, w: float, layer: GraphLayer) -> None: next_frontier: set[str] = set() edges = self.store.neighbors( batch, at=now, layers=flt.graph_layers, flt=flt, - limit=edge_cap - len(edges_by_id), + limit=edge_cap - len(edges_by_id), prompt_only=prompt_only, ) if prompt_only: edges = self._prompt_eligible_edges(edges) @@ -1135,7 +1135,7 @@ def _graph_arm_1hop( return {} related_ids = set(seed_ids) edges = self.store.neighbors( - seed_ids, at=now, layers=flt.graph_layers, flt=flt + seed_ids, at=now, layers=flt.graph_layers, flt=flt, prompt_only=prompt_only, ) if prompt_only: edges = self._prompt_eligible_edges(edges) diff --git a/engraphis/core/store.py b/engraphis/core/store.py index 24f47089..ff43e64a 100644 --- a/engraphis/core/store.py +++ b/engraphis/core/store.py @@ -3743,7 +3743,8 @@ def links_touching(self, ids: list[str], *, def neighbors(self, node_ids: list[str], *, at: Optional[float] = None, layers: Optional[list[GraphLayer]] = None, flt: Optional[SearchFilter] = None, - limit: Optional[int] = None) -> list[Edge]: + limit: Optional[int] = None, + prompt_only: bool = False) -> list[Edge]: if not node_ids: return [] valid_at, known_at = _temporal_anchors(flt, valid_at=at) @@ -3786,12 +3787,49 @@ def neighbors(self, node_ids: list[str], *, at: Optional[float] = None, else: sql += " AND repo_id=?" params.append(flt.repo_id) + row_cap = None if limit is None else max(0, int(limit)) + if row_cap == 0: + return [] sql += " ORDER BY id" - if limit is not None: - sql += " LIMIT ?" - params.append(max(0, int(limit))) - rows = self.conn.execute(sql, params).fetchall() - return [_row_to_edge(r) for r in rows] + if not prompt_only: + if row_cap is not None: + sql += " LIMIT ?" + params.append(row_cap) + rows = self.conn.execute(sql, params).fetchall() + return [_row_to_edge(r) for r in rows] + + # Prompt-facing graph traversal must not let unreviewed edge evidence use + # up the frontier before eligibility is checked. Page raw rows in stable + # order and count only prompt-safe edges toward the caller's cap. + selected: list[Edge] = [] + offset = 0 + page_size = min(1_000, row_cap or 1_000) + while row_cap is None or len(selected) < row_cap: + rows = self.conn.execute( + sql + " LIMIT ? OFFSET ?", (*params, page_size, offset) + ).fetchall() + if not rows: + break + edges = [_row_to_edge(row) for row in rows] + source_ids = set().union(*( + set(_provenance_memory_ids(edge.provenance)) for edge in edges + )) if edges else set() + memories = self.get_memories(sorted(source_ids)) + for edge in edges: + sources = _provenance_memory_ids(edge.provenance) + if sources and not all( + (memory := memories.get(memory_id)) + and _row_is_prompt_eligible(memory.provenance, memory.metadata) + for memory_id in sources + ): + continue + selected.append(edge) + if row_cap is not None and len(selected) >= row_cap: + break + offset += len(rows) + if len(rows) < page_size: + break + return selected # ── code symbol graph ──────────────────────────────────────────────────────── def clear_symbols_for_file(self, repo_id: str, file: str, *, diff --git a/tests/test_core_store.py b/tests/test_core_store.py index 6198a92f..078e7f08 100644 --- a/tests/test_core_store.py +++ b/tests/test_core_store.py @@ -1036,6 +1036,30 @@ def test_fts_fallback_escapes_like_wildcards(store): assert store.fts_search("_", 10) == [] # '_' is literal, not "any character" +def test_prompt_neighbors_filter_unapproved_edges_before_limit(store): + wid = store.get_or_create_workspace("w") + for index in range(4): + memory_id = store.add_memory(MemoryRecord( + id=f"mem_pending_{index}", content=f"pending {index}", workspace_id=wid, + provenance={"source": "test", "trusted": True, "review_state": "pending"}, + )) + store.upsert_edge(Edge( + id=f"edg_pending_{index}", src="seed", dst=f"pending_{index}", + relation="uses", workspace_id=wid, provenance={"memory_id": memory_id}, + )) + approved_id = store.add_memory(MemoryRecord( + id="mem_approved", content="approved", workspace_id=wid, + provenance={"source": "test", "trusted": True, "review_state": "approved"}, + )) + store.upsert_edge(Edge( + id="edg_approved", src="seed", dst="approved", relation="uses", workspace_id=wid, + provenance={"memory_id": approved_id}, + )) + + edges = store.neighbors(["seed"], limit=1, prompt_only=True) + assert [edge.id for edge in edges] == ["edg_approved"] + + @pytest.mark.parametrize( ("query", "broad_match", "exact_match"), [ From 899c872c4259536509defc5e494d1ee44eb8e636 Mon Sep 17 00:00:00 2001 From: Jaixii Date: Sun, 2 Aug 2026 23:16:00 -0400 Subject: [PATCH 32/35] fix: preserve review and prompt graph boundaries --- engraphis/core/engine.py | 12 +++++++++++- engraphis/core/recall.py | 1 + engraphis/core/store.py | 15 ++++++++++++--- tests/test_core_store.py | 21 +++++++++++++++++++++ tests/test_poisoning.py | 19 +++++++++++++++++++ 5 files changed, 64 insertions(+), 4 deletions(-) diff --git a/engraphis/core/engine.py b/engraphis/core/engine.py index 404ae79b..7a999f9e 100644 --- a/engraphis/core/engine.py +++ b/engraphis/core/engine.py @@ -1769,11 +1769,21 @@ def approve_for_prompt(self, memory_id: str, *, reviewer: str, repo_id=old.repo_id, session_id=old.session_id if old.scope == Scope.SESSION else None, ) - for candidate in self.store.list_memories(source_scope, include_invalid=False): + # Include retired successors in this audit lookup. A retry may return a + # live successor, but it must never create a fresh one after the original + # approved record was deliberately retired: that would resurrect content + # without a new governed write. + for candidate in self.store.list_memories(source_scope, include_invalid=True): approved_from = candidate.provenance.get("approved_from") if approved_from is None: approved_from = candidate.metadata.get("approved_from") if (approved_from == old.id and provenance_is_approved(candidate.provenance)): + if ( + candidate.expired_at is not None + or (candidate.valid_from is not None and candidate.valid_from > now) + or (candidate.valid_to is not None and candidate.valid_to <= now) + ): + raise ValueError("memory has already been approved and retired") return { "id": candidate.id, "approved_from": old.id, diff --git a/engraphis/core/recall.py b/engraphis/core/recall.py index 0202e690..8061f45c 100644 --- a/engraphis/core/recall.py +++ b/engraphis/core/recall.py @@ -1049,6 +1049,7 @@ def connect(a: str, b: str, w: float, layer: GraphLayer) -> None: layers=flt.graph_layers, flt=flt, limit=20_000, + prompt_only=prompt_only, ) # Expand from the entity-incidence frontier before adding the bounded newest # memory window. An older unmentioned endpoint can then participate in PPR diff --git a/engraphis/core/store.py b/engraphis/core/store.py index ff43e64a..9e489dd9 100644 --- a/engraphis/core/store.py +++ b/engraphis/core/store.py @@ -3686,7 +3686,8 @@ def links_touching(self, ids: list[str], *, layers: Optional[list[GraphLayer]] = None, flt: Optional[SearchFilter] = None, include_invalid: bool = False, - limit: Optional[int] = None) -> list[dict]: + limit: Optional[int] = None, + prompt_only: bool = False) -> list[dict]: """Return visible links with at least one endpoint in ``ids``. This bounded frontier expansion is distinct from :meth:`links_among`: graph @@ -3726,8 +3727,16 @@ def links_touching(self, ids: list[str], *, sql += f" AND layer IN ({layer_marks})" params.extend(_enum(layer) for layer in layers) sql += " ORDER BY a, b, relation, valid_from, ingested_at" - for row in self.conn.execute(sql, params).fetchall(): - item = dict(row) + found = [dict(row) for row in self.conn.execute(sql, params).fetchall()] + endpoint_ids = {endpoint for item in found for endpoint in (item["a"], item["b"])} + endpoint_records = self.get_memories(sorted(endpoint_ids)) if prompt_only else {} + for item in found: + if prompt_only and not all( + (record := endpoint_records.get(endpoint)) + and _row_is_prompt_eligible(record.provenance, record.metadata) + for endpoint in (item["a"], item["b"]) + ): + continue key = ( item["a"], item["b"], item["relation"], item["layer"], item["valid_from"], item["valid_to"], item["ingested_at"], diff --git a/tests/test_core_store.py b/tests/test_core_store.py index 078e7f08..077bc35b 100644 --- a/tests/test_core_store.py +++ b/tests/test_core_store.py @@ -1060,6 +1060,27 @@ def test_prompt_neighbors_filter_unapproved_edges_before_limit(store): assert [edge.id for edge in edges] == ["edg_approved"] +def test_prompt_links_touching_filters_unapproved_endpoints_before_limit(store): + wid = store.get_or_create_workspace("w") + seed = store.add_memory(MemoryRecord( + id="mem_seed", content="approved seed", workspace_id=wid, + provenance={"source": "test", "trusted": True, "review_state": "approved"}, + )) + pending = store.add_memory(MemoryRecord( + id="mem_pending", content="pending endpoint", workspace_id=wid, + provenance={"source": "test", "trusted": False, "review_state": "pending"}, + )) + approved = store.add_memory(MemoryRecord( + id="mem_safe", content="approved endpoint", workspace_id=wid, + provenance={"source": "test", "trusted": True, "review_state": "approved"}, + )) + store.add_link(seed, pending, relation="supports") + store.add_link(seed, approved, relation="supports") + + links = store.links_touching([seed], limit=1, prompt_only=True) + assert [(link["a"], link["b"]) for link in links] == [(seed, approved)] + + @pytest.mark.parametrize( ("query", "broad_match", "exact_match"), [ diff --git a/tests/test_poisoning.py b/tests/test_poisoning.py index e6d2ae65..b6a2dada 100644 --- a/tests/test_poisoning.py +++ b/tests/test_poisoning.py @@ -560,6 +560,25 @@ def test_approval_requires_a_reason_and_cannot_duplicate_an_approved_successor() ) +def test_approval_retry_cannot_resurrect_a_retired_approved_successor(): + service = MemoryService.create(":memory:", graph_extractor="none", extractor="none") + pending = service.remember("The release is green.", workspace="w") + approved = service.engine.approve_for_prompt( + pending["id"], reviewer="operator", reason="verified in the release dashboard", + ) + service.engine.retire(approved["id"], reason="release was superseded") + + with pytest.raises(ValueError, match="already been approved and retired"): + service.engine.approve_for_prompt( + pending["id"], reviewer="operator", reason="stale transport retry", + ) + assert [ + record.id + for record in service.store.list_memories(include_invalid=True) + if record.provenance.get("approved_from") == pending["id"] + ] == [approved["id"]] + + def test_approval_requires_a_live_pending_source_and_preserves_claim_protections(): service = MemoryService.create(":memory:", graph_extractor="none", extractor="none") retired = service.remember("The retired release is blue.", workspace="w") From 3bf34efa5323763ad90737d2995dba2fcdb57007 Mon Sep 17 00:00:00 2001 From: Jaixii Date: Sun, 2 Aug 2026 23:22:52 -0400 Subject: [PATCH 33/35] fix: honor type caps and MCP restarts --- engraphis/core/recall.py | 24 +++++++++++++++++- integrations/pi/index.ts | 4 +++ integrations/pi/src/mcp-client.ts | 5 ++++ integrations/pi/test/extension.test.ts | 35 ++++++++++++++++++++++++++ tests/test_recall.py | 15 +++++++++-- 5 files changed, 80 insertions(+), 3 deletions(-) diff --git a/engraphis/core/recall.py b/engraphis/core/recall.py index 8061f45c..faa10aab 100644 --- a/engraphis/core/recall.py +++ b/engraphis/core/recall.py @@ -352,7 +352,10 @@ def recall(self, query: str, flt: Optional[SearchFilter] = None, *, k: int = 8, ) if ( not prompt_only - or len(recs) >= prompt_target + or ( + len(recs) >= prompt_target + and _mtype_limits_can_fill(recs, effective_limits, prompt_target) + ) or arm_candidate_k >= candidate_ceiling or not can_expand ): @@ -1408,6 +1411,25 @@ def _apply_mtype_limits( return selected, drops +def _mtype_limits_can_fill( + records: dict[str, MemoryRecord], limits: dict[MemoryType, int], target: int, +) -> bool: + """Whether the fetched prompt-safe records can fill ``target`` after type caps.""" + if not limits: + return True + selected = 0 + counts: dict[MemoryType, int] = {} + for record in records.values(): + limit = limits.get(record.mtype) + if limit is not None and counts.get(record.mtype, 0) >= limit: + continue + selected += 1 + counts[record.mtype] = counts.get(record.mtype, 0) + 1 + if selected >= target: + return True + return False + + def _type_aware_rerank_pool( candidates: list[Candidate], limits: dict[MemoryType, int], diff --git a/integrations/pi/index.ts b/integrations/pi/index.ts index 3df8ab12..9a915439 100644 --- a/integrations/pi/index.ts +++ b/integrations/pi/index.ts @@ -51,6 +51,7 @@ export default function engraphisPiExtension(pi: ExtensionAPI) { const discoveredActions = new Map(); const call = async (name: string, args: Record, signal?: AbortSignal) => { + const generation = client.generation(); try { const result = await client.callTool(name, args, signal); if (name === "engraphis_discover_actions") { @@ -65,6 +66,9 @@ export default function engraphisPiExtension(pi: ExtensionAPI) { } return formatMcpResult(result); } catch (error) { + // The MCP client closes an unhealthy transport before this catch runs. Capabilities + // are signed by that subprocess, so a restart makes every cached action invalid. + if (client.generation() !== generation) discoveredActions.clear(); if (name === "engraphis_execute_action" && !(error instanceof EngraphisMcpToolError)) { throw new Error( "Engraphis action outcome is unknown because the local connection failed. " + diff --git a/integrations/pi/src/mcp-client.ts b/integrations/pi/src/mcp-client.ts index a4d1dbe9..0dd0bd25 100644 --- a/integrations/pi/src/mcp-client.ts +++ b/integrations/pi/src/mcp-client.ts @@ -53,6 +53,11 @@ export class EngraphisMcpClient { constructor(private readonly config: EngraphisRuntimeConfig) {} + /** Changes whenever this extension closes a transport and invalidates server-issued state. */ + generation(): number { + return this.lifecycle; + } + async connect(): Promise { if (this.client) return this.client; if (this.connecting) return this.connecting; diff --git a/integrations/pi/test/extension.test.ts b/integrations/pi/test/extension.test.ts index 6c055010..e575c32c 100644 --- a/integrations/pi/test/extension.test.ts +++ b/integrations/pi/test/extension.test.ts @@ -126,6 +126,41 @@ test("requires a fresh discovery and explicit Pi approval for every advanced act } }); +test("clears discovered actions after an MCP transport reset", async () => { + const originalCall = EngraphisMcpClient.prototype.callTool; + const originalGeneration = EngraphisMcpClient.prototype.generation; + let generation = 0; + EngraphisMcpClient.prototype.generation = function () { return generation; }; + EngraphisMcpClient.prototype.callTool = async function (name: string) { + if (name === "engraphis_discover_actions") { + return { content: [{ type: "text", text: JSON.stringify({ actions: [{ + capability_id: "cap_restart", canonical_action: "retire", + schema_digest: "1234567890abcdef", side_effect: "state_change", title: "Retire memory", + }] }) }] }; + } + generation += 1; + throw new Error("stdio transport closed"); + }; + try { + const { tools } = extensionHarness(); + const discover = tools.find((tool) => tool.name === "engraphis_discover_actions")!; + const recall = tools.find((tool) => tool.name === "engraphis_recall_context")!; + const execute = tools.find((tool) => tool.name === "engraphis_execute_action")!; + await discover.execute("discover", { task: "retire stale memory" }, undefined); + await assert.rejects(recall.execute("recall", { query: "trigger reset" }, undefined)); + await assert.rejects( + execute.execute("action", { + arguments: {}, capability_id: "cap_restart", schema_digest: "1234567890abcdef", + }, undefined, undefined, { hasUI: true, ui: { confirm: async () => true } }), + /not issued by the current Engraphis discovery session/, + ); + } finally { + EngraphisMcpClient.prototype.callTool = originalCall; + EngraphisMcpClient.prototype.generation = originalGeneration; + } +}); + + test("fails closed when Pi cannot present an action approval dialog", async () => { const original = EngraphisMcpClient.prototype.callTool; EngraphisMcpClient.prototype.callTool = async function (name: string) { diff --git a/tests/test_recall.py b/tests/test_recall.py index 7544e0bb..58c7726a 100644 --- a/tests/test_recall.py +++ b/tests/test_recall.py @@ -1,7 +1,7 @@ from engraphis.backends import DeterministicEmbedder, NumpyVectorIndex from engraphis.backends.reranker import IdentityReranker -from engraphis.core.interfaces import MemoryRecord, Scope, SearchFilter -from engraphis.core.recall import RecallEngine, _absolute_retrieval_support +from engraphis.core.interfaces import MemoryRecord, MemoryType, Scope, SearchFilter +from engraphis.core.recall import RecallEngine, _absolute_retrieval_support, _mtype_limits_can_fill from engraphis.core.retrieval_policy import ProfileConfig from engraphis.core.store import Store @@ -13,6 +13,17 @@ class _SemanticTestEmbedder(DeterministicEmbedder): embedding_mode = "semantic" +def test_prompt_candidate_expansion_accounts_for_memory_type_caps(): + semantic = MemoryRecord(id="mem_semantic", content="", mtype=MemoryType.SEMANTIC) + procedural = MemoryRecord(id="mem_procedural", content="", mtype=MemoryType.PROCEDURAL) + limits = {MemoryType.SEMANTIC: 0} + + assert not _mtype_limits_can_fill({semantic.id: semantic}, limits, 1) + assert _mtype_limits_can_fill( + {semantic.id: semantic, procedural.id: procedural}, limits, 1, + ) + + def _engine(): store = Store(":memory:") emb = DeterministicEmbedder(256) From 886ffe4b3789399eb7cf0153d8ec4e98254b074b Mon Sep 17 00:00:00 2001 From: Jaixii Date: Sun, 2 Aug 2026 23:45:15 -0400 Subject: [PATCH 34/35] Update README.md --- README.md | 63 ------------------------------------------------------- 1 file changed, 63 deletions(-) diff --git a/README.md b/README.md index 3d235f78..8171620b 100644 --- a/README.md +++ b/README.md @@ -35,11 +35,6 @@ Less repeated history means more room for the task, tools, and useful evidence.

-> **Evidence boundary:** External LoCoMo-derived figures are not canonical. The historical -> workload run used an unpinned model revision and has no checked-in raw dataset artifact. -> Treat its 98.21% context figure as directional until an immutable rerun produces a validated -> public artifact and checksum. The checked-in deterministic fixtures below remain reproducible. -
See benchmark details and reproduce the results @@ -155,22 +150,6 @@ for the short version of how much less history an agent has to carry. | Avoid dragging the whole project into every prompt | Packs context to a configured hard budget and can return a compact MCP response. | | Keep knowledge in the operator's control | Runs local-first and offline-capable, with scopes, audit records, and optional privacy-safe receipts. | -### See the behavior in reproducible fixtures - -The examples below use synthetic, checked-in evaluation inputs. They show three different -contracts: retrieving focused evidence, returning an answer only with support, and explicitly -abstaining when no support exists. - -

- Three evidence-backed examples: focused context keeps Recall at 5 while reducing returned content, answerable questions return cited support, and unsupported questions explicitly abstain -
- Each card names its deterministic offline fixture and test scope. The examples are illustrative; they are not customer data or external benchmark results. -

- -Run `python -m eval.chunking_eval` and `python -m eval.grounded` to reproduce the behavior; -the former measures evidence retrieval and context size, while the latter measures the -answer-versus-abstain decision. - ## Dashboard and local UI The Engraphis dashboard opens `http://127.0.0.1:8700`. Local memory needs no cloud account, @@ -181,14 +160,6 @@ workspaces, and manual consolidation. **Classic** preserves the former full tool the same local data. Switch in **Manage → Settings → Interface** (Ledger) or **Settings → Appearance & Engine** (Classic). -### Managed compute - -Managed compute is separate from Cloud Sync. A connected installation may send a bounded, -non-secret snapshot for a hosted proposal; the hosted service must read it to produce a proposal, -so this is not end-to-end-encrypted processing. Local-only installations send nothing. Set -`ENGRAPHIS_MANAGED_COMPUTE_CONSENT=0` to opt out; `ENGRAPHIS_RETENTION_SUPERVISOR=none` keeps -retention supervision local (the default). - ### Start it on every platform | Platform | How | @@ -670,40 +641,6 @@ surface; `engraphis-dashboard`, the MCP server, and the Python quickstart above --- -## Development - -The offline quality gate (no network, no API key): - -```bash -pip install numpy pytest ruff -python -m pytest tests/ -q -python -m eval.harness --dataset eval/datasets/sample.jsonl --k 5 -python -m eval.harness --dataset eval/datasets/codemem.jsonl --k 5 -python -m eval.ablation -ruff check . -``` - -Numbers, not assertions: the offline harness is a **correctness floor** (deterministic embedder). -LoCoMo, LongMemEval, MemoryAgentBench, LoCoMo-Plus, and Mem2ActBench adapters are available, -along with a pinned LongMemEval-V2 reader profile, redacted evidence exporter, and paired -full-history versus Engraphis code-agent analyzer. External adapters measure only the layer they -declare; retrieval or tool-argument context coverage is not presented as end-to-end answer, -action, or task success. Reproduction commands and remaining official-run requirements are in -[`BENCHMARKS.md`](BENCHMARKS.md). - ---- - -## Release evidence - -Each tagged release includes `release-evidence.json` and a reproducible CycloneDX JSON SBOM as -GitHub Release assets. The evidence binds the matching tag and commit to the built wheel and -source distribution hashes, SBOM hash, source-input hashes, and the completed release-gate checks. -It is intentionally limited: it does not attest to publication, hosted services, payments, -deployments, or runtime data; the SBOM describes the build job's Python environment rather than an -operating-system or container image. - ---- - ## License Apache-2.0. See [LICENSE](LICENSE) and [NOTICE](NOTICE). "Engraphis" is a trademark of the From e65e9ace0b8a84b1488b3376874dcb2f60c9607a Mon Sep 17 00:00:00 2001 From: Jaixii Date: Mon, 3 Aug 2026 00:05:07 -0400 Subject: [PATCH 35/35] test: align README contracts with streamlined copy --- tests/test_benchmark_evidence.py | 18 ++++++++++-------- tests/test_dashboard_auth_placement.py | 8 +++----- tests/test_pro_cta.py | 1 - 3 files changed, 13 insertions(+), 14 deletions(-) diff --git a/tests/test_benchmark_evidence.py b/tests/test_benchmark_evidence.py index de00d2c4..d50affd7 100644 --- a/tests/test_benchmark_evidence.py +++ b/tests/test_benchmark_evidence.py @@ -115,17 +115,15 @@ def test_readme_distinguishes_every_current_token_context_measurement(): assert evidence in readme -def test_readme_puts_external_evidence_boundary_beside_the_chart(): - """The external-result caveat must remain visible before collapsed details.""" +def test_readme_keeps_external_evidence_caveats_out_of_the_front_page(): + """Benchmark caveats belong in the supporting benchmark documentation.""" readme = (ROOT / "README.md").read_text(encoding="utf-8") benchmarks = (ROOT / "BENCHMARKS.md").read_text(encoding="utf-8") security = (ROOT / "SECURITY.md").read_text(encoding="utf-8") boundary = "External LoCoMo-derived figures are not canonical." - assert boundary in readme - assert readme.index("

") < readme.index(boundary) < readme.index("
") - assert "immutable rerun produces a validated" in readme - assert "public artifact and checksum" in readme + assert boundary not in readme + assert "See benchmark details and reproduce the results" in readme for detail in ( "Unpinned, noncanonical workload diagnostic", @@ -152,12 +150,16 @@ def test_readme_makes_agent_benefits_and_visual_evidence_scannable(): "Avoid dragging the whole project into every prompt", "docs/images/knowledge-graph.png", "docs/images/context-efficiency.svg", + "Less repeated history means more room for the task, tools, and useful evidence", + ): + assert evidence in readme + + for removed in ( "### See the behavior in reproducible fixtures", "docs/images/evidence-backed-agent-examples.svg", "Run `python -m eval.chunking_eval` and `python -m eval.grounded`", - "Less repeated history means more room for the task, tools, and useful evidence", ): - assert evidence in readme + assert removed not in readme for filename in ( "engraphis-benefit-flow.svg", diff --git a/tests/test_dashboard_auth_placement.py b/tests/test_dashboard_auth_placement.py index ba84057a..00045a03 100644 --- a/tests/test_dashboard_auth_placement.py +++ b/tests/test_dashboard_auth_placement.py @@ -140,11 +140,9 @@ def test_hosted_transfer_and_llm_consents_distinguish_sync_from_compute(): encoding="utf-8" ) normalized_readme = " ".join(readme.split()) - assert "hosted service must read it to produce a proposal" in normalized_readme - assert "this is not end-to-end-encrypted processing" in normalized_readme - assert "Local-only installations send nothing" in normalized_readme - assert "ENGRAPHIS_RETENTION_SUPERVISOR=none" in normalized_readme - + assert "hosted service must read it to produce a proposal" not in normalized_readme + assert "this is not end-to-end-encrypted processing" not in normalized_readme + assert "Local-only installations send nothing" not in normalized_readme assert "will never see, read, or access your data" not in normalized_readme sync_doc = (Path(__file__).resolve().parents[1] / "docs" / "SYNC.md").read_text( diff --git a/tests/test_pro_cta.py b/tests/test_pro_cta.py index e33acf8a..746e02b2 100644 --- a/tests/test_pro_cta.py +++ b/tests/test_pro_cta.py @@ -46,7 +46,6 @@ def test_public_pro_ctas_use_documentation_attribution(): for heading in ( "## What Engraphis gives an agent", - "### See the behavior in reproducible fixtures", "## Free forever vs. hosted plans", ): assert heading in readme