From ef4061a8fc87e1c8dd216f9e23e8990ac3255928 Mon Sep 17 00:00:00 2001 From: Sebastian Husch Lee Date: Wed, 26 Aug 2026 08:45:49 +0200 Subject: [PATCH] Update agent pack tutorial --- index.toml | 2 +- tutorials/50_Using_Pre_Built_Agents_from_Agent_Pack.ipynb | 6 +++--- 2 files changed, 4 insertions(+), 4 deletions(-) diff --git a/index.toml b/index.toml index 28ee0488..fb253c20 100644 --- a/index.toml +++ b/index.toml @@ -272,5 +272,5 @@ notebook = "50_Using_Pre_Built_Agents_from_Agent_Pack.ipynb" aliases = [] completion_time = "25 min" created_at = 2026-07-20 -dependencies = ["haystack-ai>=3.0", "agent-pack-haystack", "arrow", "tavily-haystack", "trafilatura", "pypdf"] +dependencies = ["haystack-ai>=3.1", "agent-pack-haystack", "arrow", "tavily-haystack", "trafilatura", "pypdf"] featured = false diff --git a/tutorials/50_Using_Pre_Built_Agents_from_Agent_Pack.ipynb b/tutorials/50_Using_Pre_Built_Agents_from_Agent_Pack.ipynb index 29a6c63d..20f3ab7e 100644 --- a/tutorials/50_Using_Pre_Built_Agents_from_Agent_Pack.ipynb +++ b/tutorials/50_Using_Pre_Built_Agents_from_Agent_Pack.ipynb @@ -10,7 +10,7 @@ "- **Level**: Advanced\n", "- **Time to complete**: 25 minutes\n", "- **Components/Packages Used**: [`agent-pack-haystack`](https://github.com/deepset-ai/haystack-core-integrations/tree/main/integrations/agent_pack) ([`create_advanced_rag_agent`](https://docs.haystack.deepset.ai/docs/advanced-rag-agent), [`create_deep_research_agent`](https://docs.haystack.deepset.ai/docs/deep-research-agent)), [`Agent`](https://docs.haystack.deepset.ai/docs/agent), [`InMemoryDocumentStore`](https://docs.haystack.deepset.ai/docs/inmemorydocumentstore)\n", - "- **Prerequisites**: Haystack 3.0 or later, an [OpenAI API key](https://platform.openai.com/api-keys), and a [Tavily API key](https://app.tavily.com) (free tier available)\n", + "- **Prerequisites**: Haystack 3.1 or later, an [OpenAI API key](https://platform.openai.com/api-keys), and a [Tavily API key](https://app.tavily.com) (free tier available)\n", "- **Goal**: After completing this tutorial, you'll understand what Agent Pack is and why it exists, and you'll have run and customized two ready-made agents: the **Advanced RAG Agent** and the **Deep Research Agent**." ] }, @@ -380,7 +380,7 @@ "\n", "Each **sub-researcher** is its own `Agent` that searches the web (`web_search`), optionally reads promising pages (`read_url`, which fetches and summarizes a page or PDF toward the question), reflects (`think_tool`), and finishes by writing one short, cited summary.\n", "\n", - "The key idea is **context management**. Raw web content (search results, full pages, PDFs) is large and noisy; if it all piled into one context window, output quality would degrade. So each sub-researcher runs in its own private context, and only its short summary leaves it, controlled by two settings on the delegation tool: `outputs_to_string` (what the orchestrator sees) and `outputs_to_state` (what's appended to `notes` for the writer). The bulky raw research never propagates to the orchestrator or the writer." + "The key idea is **context management**. Raw web content (search results, full pages, PDFs) is large and noisy; if it all piled into one context window, output quality would degrade. So each sub-researcher runs in its own private context, and only its short summary leaves it. The delegation tool is an [`AgentTool`](https://docs.haystack.deepset.ai/docs/agenttool), which wraps the sub-researcher `Agent` and by default returns only its final message text to the orchestrator, while `outputs_to_state` appends that same summary to `notes` for the writer. The bulky raw research never propagates to the orchestrator or the writer." ] }, { @@ -423,7 +423,7 @@ "\n", "Beyond running and customizing, the third way to use the pack is to **copy it**. Both agents are built entirely from public Haystack primitives, so their source doubles as a reference architecture:\n", "\n", - "- The Deep Research Agent shows how to nest agents (a sub-agent exposed to the orchestrator as a `ComponentTool`) and how `outputs_to_string` and `outputs_to_state` control what a sub-agent returns to the caller versus what it saves for later, the core of its context isolation.\n", + "- The Deep Research Agent shows how to nest agents (a sub-agent exposed to the orchestrator as an [`AgentTool`](https://docs.haystack.deepset.ai/docs/agenttool)) and how the tool's default text output and `outputs_to_state` control what a sub-agent returns to the caller versus what it saves for later, the core of its context isolation.\n", "- The Advanced RAG Agent shows how to build tools over a document store, embed a grammar in a tool's parameter description, accumulate results in `State`, and use an `after_run` hook as a safety net.\n", "\n", "Browse the source in [`haystack-core-integrations/integrations/agent_pack`](https://github.com/deepset-ai/haystack-core-integrations/tree/main/integrations/agent_pack) and adapt whichever parts fit your use case."