diff --git a/.devcontainer/devcontainer.json b/.devcontainer/devcontainer.json
index 71710a6..cfa6f9e 100644
--- a/.devcontainer/devcontainer.json
+++ b/.devcontainer/devcontainer.json
@@ -39,7 +39,16 @@
                 "redhat.vscode-yaml",
                 "ryanluker.vscode-coverage-gutters",
                 "charliermarsh.ruff",
-                "ms-azuretools.vscode-docker"
+                "ms-azuretools.vscode-docker",
+                "ms-python.debugpy",
+                "ms-python.vscode-python-envs",
+                "ms-python.vscode-pylance",
+                "ms-toolsai.vscode-jupyter-slideshow",
+                "ms-toolsai.vscode-jupyter-cell-tags",
+                "ms-toolsai.jupyter-renderers",
+                "ms-toolsai.jupyter",
+                "ms-azuretools.vscode-containers",
+                "ms-toolsai.jupyter-keymap"
             ]
         }
     },
diff --git a/scripts/makecopiercorrect.sh b/scripts/makecopiercorrect.sh
index 973bd00..55b5d63 100644
--- a/scripts/makecopiercorrect.sh
+++ b/scripts/makecopiercorrect.sh
@@ -6,6 +6,7 @@ cp ../templates/*example*.txt "../../copier_template/src/{{ project_name }}/temp
 
 for file in "../../copier_template/src/{{ project_name }}/workflow_definitions"/*
 do
+    [[ -d "$file" ]] && continue
     [[ $file == *.jinja ]] && continue
 
     sed -i 's/python-interface-to-workflows/{{repo_name}}/g' "$file"
@@ -21,9 +22,28 @@ do
 
     mv "$file" "$file.jinja"
 done
+for file in "../../copier_template/src/{{ project_name }}/workflow_definitions/notebooks"/*
+do
+    [[ -d "$file" ]] && continue
+    [[ $file == *.jinja ]] && continue
+
+    sed -i 's/python-interface-to-workflows/{{repo_name}}/g' "$file"
+    sed -i 's/DiamondLightSource/{{github_org}}/g' "$file"
+
+    sed -i '1i{% raw %}' "$file"
+    echo '{% endraw %}' >> "$file"
 
+    sed -i \
+        -e 's/{{repo_name}}/{% endraw %}{{repo_name}}{% raw %}/g' \
+        -e 's/{{github_org}}/{% endraw %}{{github_org}}{% raw %}/g' \
+        "$file"
+
+
+    mv "$file" "$file.jinja"
+done
 for file in "../../copier_template/src/{{ project_name }}/templates"/*
 do
+    [[ -d "$file" ]] && continue
     [[ $file == *.jinja ]] && continue
 
     sed -i 's/python-interface-to-workflows/{{repo_name}}/g' "$file"
diff --git a/scripts/runthefiles.sh b/scripts/runthefiles.sh
index 960a7d8..662bf8e 100644
--- a/scripts/runthefiles.sh
+++ b/scripts/runthefiles.sh
@@ -2,8 +2,8 @@
 cd src/python_interface_to_workflows/workflow_definitions
 for file in *
 do
+[[ -d "$file" ]] && continue
 uv run "$file"
 done
-mv *.yaml ../templates/
 mv *.txt ../templates/
 git add -u ../templates/
diff --git a/src/copier_template/.devcontainer/devcontainer.json b/src/copier_template/.devcontainer/devcontainer.json
index 71710a6..cfa6f9e 100644
--- a/src/copier_template/.devcontainer/devcontainer.json
+++ b/src/copier_template/.devcontainer/devcontainer.json
@@ -39,7 +39,16 @@
                 "redhat.vscode-yaml",
                 "ryanluker.vscode-coverage-gutters",
                 "charliermarsh.ruff",
-                "ms-azuretools.vscode-docker"
+                "ms-azuretools.vscode-docker",
+                "ms-python.debugpy",
+                "ms-python.vscode-python-envs",
+                "ms-python.vscode-pylance",
+                "ms-toolsai.vscode-jupyter-slideshow",
+                "ms-toolsai.vscode-jupyter-cell-tags",
+                "ms-toolsai.jupyter-renderers",
+                "ms-toolsai.jupyter",
+                "ms-azuretools.vscode-containers",
+                "ms-toolsai.jupyter-keymap"
             ]
         }
     },
diff --git a/src/copier_template/scripts/runthefiles.sh.jinja b/src/copier_template/scripts/runthefiles.sh.jinja
index f324322..c4d14a7 100644
--- a/src/copier_template/scripts/runthefiles.sh.jinja
+++ b/src/copier_template/scripts/runthefiles.sh.jinja
@@ -2,8 +2,8 @@
 cd src/{{project_name}}/workflow_definitions
 for file in *
 do
+[[ -d "$file" ]] && continue
 uv run "$file"
 done
-mv *.yaml ../templates/
-mv *.txt ../templates/
-git add -u ../templates/
+mv *.txt src/{{project_name}}/templates/
+git add -u src/{{project_name}}/templates/
diff --git a/src/copier_template/src/{{ project_name }}/submit_workflow.py.jinja b/src/copier_template/src/{{ project_name }}/submit_workflow.py.jinja
index 597599a..a2dfed9 100644
--- a/src/copier_template/src/{{ project_name }}/submit_workflow.py.jinja	
+++ b/src/copier_template/src/{{ project_name }}/submit_workflow.py.jinja	
@@ -12,7 +12,7 @@ from {% endraw %}{{project_name}}{% raw %}.auth.keycloak_checker import set_toke
 def submit_workflow(w: Workflow):
     yamlstr = w.to_yaml()  # pyright:ignore
     dotenv.load_dotenv(dotenv_path="src/.env", override=True)
-    token: str = set_token_env_variable(True)
+    token: str = set_token_env_variable()
     host: str = os.environ.get("HOST") # pyright:ignore
     visit: str = os.environ.get("VISIT")  # pyright:ignore
 
diff --git a/src/copier_template/src/{{ project_name }}/workflow_definitions/notebooks/notebook_example.ipynb.jinja b/src/copier_template/src/{{ project_name }}/workflow_definitions/notebooks/notebook_example.ipynb.jinja
new file mode 100644
index 0000000..0f829f6
--- /dev/null
+++ b/src/copier_template/src/{{ project_name }}/workflow_definitions/notebooks/notebook_example.ipynb.jinja	
@@ -0,0 +1,251 @@
+{% raw %}{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "1e3146f1",
+   "metadata": {},
+   "source": [
+    "# Running in VSCode:\n",
+    "\n",
+    "1. Set kernal to {% endraw %}{{repo_name}}{% raw %} 3.11.x\n",
+    "2. Hit F1, run Jupyter: Import Notebook to Script\n",
+    "3. Click notebook_example.ipynb\n",
+    "4. Run the cells sequentially"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "494174ef",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from hera.workflows import (\n",
+    "    DAG,\n",
+    "    Artifact,\n",
+    "    Parameter,\n",
+    "    Volume,\n",
+    "    Workflow,\n",
+    "    script,  # pyright: ignore[reportUnknownVariableType]\n",
+    ")\n",
+    "from hera.workflows import models as m\n",
+    "from hera.workflows.archive import NoneArchiveStrategy\n",
+    "\n",
+    "\n",
+    "@script(\n",
+    "    command=[\"python\"],\n",
+    "    volume_mounts=[m.VolumeMount(name=\"tmpdir\", mount_path=\"/tmp\")],\n",
+    ")\n",
+    "def install_dependencies():\n",
+    "    import subprocess\n",
+    "\n",
+    "    print(\"creating venv\")\n",
+    "\n",
+    "    subprocess.check_call([\"python\", \"-m\", \"venv\", \"/tmp/venv\"])\n",
+    "    subprocess.check_call(\n",
+    "        [\"/tmp/venv/bin/pip\", \"install\", \"pillow\", \"h5py\", \"numpy\", \"hera\"]\n",
+    "    )\n",
+    "\n",
+    "\n",
+    "@script(\n",
+    "    command=[\"python\"],\n",
+    "    outputs=Parameter(\n",
+    "        name=\"out-parameters\", value_from=m.ValueFrom(path=\"/tmp/parameters.json\")\n",
+    "    ),\n",
+    "    volume_mounts=[m.VolumeMount(name=\"tmpdir\", mount_path=\"/tmp\")],\n",
+    ")\n",
+    "def generate_parameters(\n",
+    "    png: str,\n",
+    "    jpg: str,\n",
+    "    jpeg: str,\n",
+    "    tif: str,\n",
+    "    tiff: str,\n",
+    "):\n",
+    "    import json\n",
+    "\n",
+    "    params: list[dict[str, int | list[int] | str] | None] = [\n",
+    "        {\"width\": 500, \"height\": 500, \"weights\": [255, 1, 100], \"extension\": \"png\"}\n",
+    "        if png.lower() == \"true\"\n",
+    "        else None,\n",
+    "        {\"width\": 600, \"height\": 200, \"weights\": [100, 150, 100], \"extension\": \"jpg\"}\n",
+    "        if jpg.lower() == \"true\"\n",
+    "        else None,\n",
+    "        {\"width\": 300, \"height\": 400, \"weights\": [100, 150, 100], \"extension\": \"jpeg\"}\n",
+    "        if jpeg.lower() == \"true\"\n",
+    "        else None,\n",
+    "        {\"width\": 300, \"height\": 200, \"weights\": [230, 100, 1], \"extension\": \"tif\"}\n",
+    "        if tif.lower() == \"true\"\n",
+    "        else None,\n",
+    "        {\"width\": 200, \"height\": 300, \"weights\": [230, 100, 1], \"extension\": \"tiff\"}\n",
+    "        if tiff.lower() == \"true\"\n",
+    "        else None,\n",
+    "    ]\n",
+    "    params_to_write: list[dict[str, int | list[int] | str]] = [\n",
+    "        image_params for image_params in params if image_params is not None\n",
+    "    ]\n",
+    "    with open(\"/tmp/parameters.json\", \"w\") as f:\n",
+    "        json.dump(params_to_write, f)\n",
+    "\n",
+    "\n",
+    "@script(\n",
+    "    command=[\"/tmp/venv/bin/python\"],\n",
+    "    volume_mounts=[m.VolumeMount(name=\"tmpdir\", mount_path=\"/tmp\")],\n",
+    "    outputs=[\n",
+    "        Parameter(\n",
+    "            name=\"out-paths\",\n",
+    "            value_from=m.ValueFrom(\n",
+    "                path=\"/tmp/{{inputs.parameters.extension}}-path.json\"\n",
+    "            ),\n",
+    "        ),\n",
+    "        Artifact(\n",
+    "            name=\"{{inputs.parameters.extension}}-image\",\n",
+    "            path=\"/tmp/{{inputs.parameters.extension}}-image.{{inputs.parameters.extension}}\",\n",
+    "            archive=NoneArchiveStrategy(),\n",
+    "        ),\n",
+    "    ],\n",
+    ")\n",
+    "def create_image(\n",
+    "    width: int, height: int, weights: tuple[int, int, int], extension: str\n",
+    "):\n",
+    "    import json\n",
+    "\n",
+    "    from PIL import Image\n",
+    "\n",
+    "    def create_pattern(\n",
+    "        width: int,\n",
+    "        height: int,\n",
+    "        weights: tuple[int, int, int],\n",
+    "    ) -> Image.Image:\n",
+    "        print(f\"width: {width}\")\n",
+    "        print(f\"height: {height}\")\n",
+    "        print(f\"RBG weights: {weights}\")\n",
+    "        image = Image.new(\"RGB\", (width, height))\n",
+    "        pixels = image.load()\n",
+    "        for i in range(width):\n",
+    "            for j in range(height):\n",
+    "                pixels[i, j] = (  # pyright: ignore[reportOptionalSubscript]\n",
+    "                    (i + j * 50) % weights[0],\n",
+    "                    weights[1],\n",
+    "                    (i * 300 + j) % weights[2],\n",
+    "                )\n",
+    "        return image\n",
+    "\n",
+    "    image = create_pattern(width, height, weights)\n",
+    "    path = f\"/tmp/{extension}-image.{extension}\"\n",
+    "    image.save(path)\n",
+    "    with open(f\"/tmp/{extension}-path.json\", \"w\") as f:\n",
+    "        json.dump(path, f)\n",
+    "\n",
+    "\n",
+    "@script(\n",
+    "    command=[\"/tmp/venv/bin/python\"],\n",
+    "    volume_mounts=[m.VolumeMount(name=\"tmpdir\", mount_path=\"/tmp\")],\n",
+    "    outputs=Artifact(\n",
+    "        name=\"hdf5output\",\n",
+    "        path=\"/tmp/images.hdf5\",\n",
+    "        archive=NoneArchiveStrategy(),\n",
+    "    ),\n",
+    ")\n",
+    "def to_hdf5(paths: str):\n",
+    "\n",
+    "    import h5py  # pyright: ignore[reportMissingTypeStubs]\n",
+    "    import numpy as np\n",
+    "    from PIL import Image\n",
+    "\n",
+    "    print(\"creating hdf5 file\")\n",
+    "    with h5py.File(\"/tmp/images.hdf5\", \"w\") as f:\n",
+    "        for i, path in enumerate(paths):\n",
+    "            path = path.strip('\"')\n",
+    "            print(f\"Got {path}\")\n",
+    "            with Image.open(path) as image:\n",
+    "                arr = np.array(image)\n",
+    "                f.create_dataset(  # pyright: ignore[reportUnknownMemberType]\n",
+    "                    f\"image_{i}\", data=arr, dtype=arr.dtype\n",
+    "                )\n",
+    "    print(\"done\")\n",
+    "\n",
+    "\n",
+    "with Workflow(\n",
+    "    generate_name=\"hera-example-\",  # when running on graphql this should be name\n",
+    "    entrypoint=\"workflowentry\",\n",
+    "    api_version=\"argoproj.io/v1alpha1\",\n",
+    "    kind=\"Workflow\",  # ClusterWorkflowTemplate\", when on graphql\n",
+    "    labels={\"workflows.diamond.ac.uk/science-group-examples\": \"true\"},\n",
+    "    annotations={\n",
+    "        \"workflows.argoproj.io/title\": \"example remade via hera\",\n",
+    "        \"workflows.argoproj.io/description\": \"\"\"Replicates the functionality of\n",
+    "example.yaml\"\"\",\n",
+    "        \"workflows.diamond.ac.uk/repository\": \"https://github.com/{% endraw %}{{github_org}}{% raw %}/{% endraw %}{{repo_name}}{% raw %}\",\n",
+    "    },\n",
+    "    volumes=Volume(name=\"tmpdir\", mount_path=\"/tmp/\", size=\"1Gi\"),\n",
+    ") as w:\n",
+    "    with DAG(name=\"workflowentry\"):\n",
+    "        install = install_dependencies(name=\"install\")\n",
+    "        params = generate_parameters(\n",
+    "            name=\"params\",\n",
+    "            arguments={\n",
+    "                \"png\": \"True\",\n",
+    "                \"jpg\": \"True\",\n",
+    "                \"jpeg\": \"True\",\n",
+    "                \"tif\": \"True\",\n",
+    "                \"tiff\": \"True\",\n",
+    "            },\n",
+    "        )\n",
+    "        makeimages = create_image(with_param=params.get_parameter(\"out-parameters\"))\n",
+    "        makehdf5 = to_hdf5(\n",
+    "            arguments={\n",
+    "                \"paths\": makeimages.get_parameter(\"out-paths\"),\n",
+    "            }\n",
+    "        )\n",
+    "        [install, params] >> makeimages >> makehdf5  # pyright: ignore\n",
+    "\n",
+    "\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "04708f46",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "\n",
+    "with open(\"example.txt\", \"w\") as div:\n",
+    "    div.write(w.to_yaml())  # pyright: ignore[reportUnknownMemberType]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "7e9f88cb",
+   "metadata": {},
+    "source": [
+    "from {% endraw %}{{project_name}}{% raw %}.submit_workflow import submit_workflow\n",
+    "\n",
+    "submit_workflow(w)"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "{% endraw %}{{repo_name}}{% raw %} (3.11.x)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.11.15"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
+{% endraw %}
diff --git a/src/copier_template/tests/test_keycloak_checker.py.jinja b/src/copier_template/tests/test_keycloak_checker.py.jinja
index 4b27f07..b960007 100644
--- a/src/copier_template/tests/test_keycloak_checker.py.jinja
+++ b/src/copier_template/tests/test_keycloak_checker.py.jinja
@@ -45,7 +45,7 @@ def test_set_token_env_variable(
     keycloak.token.return_value = token
     keycloak.refresh_token.return_value = token
     keycloak.decode_token.return_value = {"exp": 123456789}
-    assert set_token_env_variable(staging) == "fake_token"
+    assert set_token_env_variable() == "fake_token"
 
     mock_token_expired.assert_called_once_with("https://mock.site", port)
     if return_present:
diff --git a/src/copier_template/tests/test_submit_to_graphql.py.jinja b/src/copier_template/tests/test_submit_to_graphql.py.jinja
index 25add52..265d189 100644
--- a/src/copier_template/tests/test_submit_to_graphql.py.jinja
+++ b/src/copier_template/tests/test_submit_to_graphql.py.jinja
@@ -1,4 +1,4 @@
-from unittest.mock import MagicMock, patch
+from unittest.mock import MagicMock, call, patch
 
 from {{project_name}}.submit_workflow import submit_workflow
 
diff --git a/src/python_interface_to_workflows/templates/divisionyaml.yaml b/src/python_interface_to_workflows/templates/divisionyaml.txt
similarity index 100%
rename from src/python_interface_to_workflows/templates/divisionyaml.yaml
rename to src/python_interface_to_workflows/templates/divisionyaml.txt
diff --git a/src/python_interface_to_workflows/workflow_definitions/create_division_yaml.py b/src/python_interface_to_workflows/workflow_definitions/create_division_yaml.py
index 8a57ae1..327618f 100644
--- a/src/python_interface_to_workflows/workflow_definitions/create_division_yaml.py
+++ b/src/python_interface_to_workflows/workflow_definitions/create_division_yaml.py
@@ -45,5 +45,5 @@ def do_division(a: int, b: int):
         do_division(name="first", arguments={"a": 2, "b": 5})
 
 
-with open("divisionyaml.yaml", "w") as div:
+with open("divisionyaml.txt", "w") as div:
     div.write(w.to_yaml())  # pyright: ignore[reportUnknownMemberType]
diff --git a/src/python_interface_to_workflows/workflow_definitions/notebooks/notebook_division.ipynb b/src/python_interface_to_workflows/workflow_definitions/notebooks/notebook_division.ipynb
new file mode 100644
index 0000000..9113672
--- /dev/null
+++ b/src/python_interface_to_workflows/workflow_definitions/notebooks/notebook_division.ipynb
@@ -0,0 +1,116 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "1e3146f1",
+   "metadata": {},
+   "source": [
+    "# Running in VSCode:\n",
+    "\n",
+    "1. Set kernal to python-interface-to-workflows 3.11.x\n",
+    "2. Hit F1, run Jupyter: Import Notebook to Script\n",
+    "3. Click notebook_division.ipynb\n",
+    "4. Run the cells sequentially"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "id": "494174ef",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import json\n",
+    "\n",
+    "from hera.workflows import (\n",
+    "    Artifact,\n",
+    "    EmptyDirVolume,\n",
+    "    Steps,\n",
+    "    Workflow,\n",
+    "    script,  # pyright: ignore[reportUnknownVariableType]\n",
+    ")\n",
+    "from hera.workflows import models as m\n",
+    "\n",
+    "\n",
+    "@script(\n",
+    "    volume_mounts=[m.VolumeMount(name=\"output-dir\", mount_path=\"/output-dir/\")],\n",
+    "    outputs=Artifact(name=\"json-output\", path=\"/output-dir/output.json\"),\n",
+    ")\n",
+    "def do_division(a: int, b: int):\n",
+    "    div = a / b\n",
+    "    intdiv = a // b\n",
+    "    remain = a % b\n",
+    "    dictionary_of_results = {\n",
+    "        \"divide\": div,\n",
+    "        \"quotient\": intdiv,\n",
+    "        \"remainder\": remain,\n",
+    "    }\n",
+    "    with open(\"/output-dir/output.json\", \"w\") as otpt:\n",
+    "        json.dump(dictionary_of_results, otpt)\n",
+    "\n",
+    "\n",
+    "with Workflow(\n",
+    "    generate_name=\"hera-division-\",  # when running on graphql this should be name\n",
+    "    entrypoint=\"divide\",\n",
+    "    api_version=\"argoproj.io/v1alpha1\",\n",
+    "    kind=\"Workflow\",  # ClusterWorkflowTemplate\", when on graphql\n",
+    "    labels={\"workflows.diamond.ac.uk/science-group-examples\": \"true\"},\n",
+    "    annotations={\n",
+    "        \"workflows.argoproj.io/title\": \"Division via hera test\",\n",
+    "        \"workflows.argoproj.io/description\": \"\"\"Takes a numerical input and returns\n",
+    "    the remainder, output float, and output string to a json file\"\"\",\n",
+    "        \"workflows.diamond.ac.uk/repository\": \"https://github.com/DiamondLightSource/python-interface-to-workflows\",\n",
+    "    },\n",
+    "    volumes=EmptyDirVolume(name=\"output-dir\", mount_path=\"/output-dir\"),\n",
+    ") as w:\n",
+    "    with Steps(name=\"divide\"):\n",
+    "        do_division(name=\"first\", arguments={\"a\": 2, \"b\": 5})\n",
+    "\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "04708f46",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "with open(\"../../templates/division_from_jupyter.txt\", \"w\") as div:\n",
+    "    div.write(w.to_yaml())  # pyright: ignore[reportUnknownMemberType]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "7e9f88cb",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from python_interface_to_workflows.submit_workflow import submit_workflow\n",
+    "\n",
+    "submit_workflow(w)"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "python-interface-to-workflows (3.11.x)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.11.-1"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
diff --git a/src/python_interface_to_workflows/workflow_definitions/notebooks/notebook_example.ipynb b/src/python_interface_to_workflows/workflow_definitions/notebooks/notebook_example.ipynb
new file mode 100644
index 0000000..c1018ea
--- /dev/null
+++ b/src/python_interface_to_workflows/workflow_definitions/notebooks/notebook_example.ipynb
@@ -0,0 +1,251 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "1e3146f1",
+   "metadata": {},
+   "source": [
+    "# Running in VSCode:\n",
+    "\n",
+    "1. Set kernal to python-interface-to-workflows 3.11.x\n",
+    "2. Hit F1, run Jupyter: Import Notebook to Script\n",
+    "3. Click notebook_example.ipynb\n",
+    "4. Run the cells sequentially"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "494174ef",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from hera.workflows import (\n",
+    "    DAG,\n",
+    "    Artifact,\n",
+    "    Parameter,\n",
+    "    Volume,\n",
+    "    Workflow,\n",
+    "    script,  # pyright: ignore[reportUnknownVariableType]\n",
+    ")\n",
+    "from hera.workflows import models as m\n",
+    "from hera.workflows.archive import NoneArchiveStrategy\n",
+    "\n",
+    "\n",
+    "@script(\n",
+    "    command=[\"python\"],\n",
+    "    volume_mounts=[m.VolumeMount(name=\"tmpdir\", mount_path=\"/tmp\")],\n",
+    ")\n",
+    "def install_dependencies():\n",
+    "    import subprocess\n",
+    "\n",
+    "    print(\"creating venv\")\n",
+    "\n",
+    "    subprocess.check_call([\"python\", \"-m\", \"venv\", \"/tmp/venv\"])\n",
+    "    subprocess.check_call(\n",
+    "        [\"/tmp/venv/bin/pip\", \"install\", \"pillow\", \"h5py\", \"numpy\", \"hera\"]\n",
+    "    )\n",
+    "\n",
+    "\n",
+    "@script(\n",
+    "    command=[\"python\"],\n",
+    "    outputs=Parameter(\n",
+    "        name=\"out-parameters\", value_from=m.ValueFrom(path=\"/tmp/parameters.json\")\n",
+    "    ),\n",
+    "    volume_mounts=[m.VolumeMount(name=\"tmpdir\", mount_path=\"/tmp\")],\n",
+    ")\n",
+    "def generate_parameters(\n",
+    "    png: str,\n",
+    "    jpg: str,\n",
+    "    jpeg: str,\n",
+    "    tif: str,\n",
+    "    tiff: str,\n",
+    "):\n",
+    "    import json\n",
+    "\n",
+    "    params: list[dict[str, int | list[int] | str] | None] = [\n",
+    "        {\"width\": 500, \"height\": 500, \"weights\": [255, 1, 100], \"extension\": \"png\"}\n",
+    "        if png.lower() == \"true\"\n",
+    "        else None,\n",
+    "        {\"width\": 600, \"height\": 200, \"weights\": [100, 150, 100], \"extension\": \"jpg\"}\n",
+    "        if jpg.lower() == \"true\"\n",
+    "        else None,\n",
+    "        {\"width\": 300, \"height\": 400, \"weights\": [100, 150, 100], \"extension\": \"jpeg\"}\n",
+    "        if jpeg.lower() == \"true\"\n",
+    "        else None,\n",
+    "        {\"width\": 300, \"height\": 200, \"weights\": [230, 100, 1], \"extension\": \"tif\"}\n",
+    "        if tif.lower() == \"true\"\n",
+    "        else None,\n",
+    "        {\"width\": 200, \"height\": 300, \"weights\": [230, 100, 1], \"extension\": \"tiff\"}\n",
+    "        if tiff.lower() == \"true\"\n",
+    "        else None,\n",
+    "    ]\n",
+    "    params_to_write: list[dict[str, int | list[int] | str]] = [\n",
+    "        image_params for image_params in params if image_params is not None\n",
+    "    ]\n",
+    "    with open(\"/tmp/parameters.json\", \"w\") as f:\n",
+    "        json.dump(params_to_write, f)\n",
+    "\n",
+    "\n",
+    "@script(\n",
+    "    command=[\"/tmp/venv/bin/python\"],\n",
+    "    volume_mounts=[m.VolumeMount(name=\"tmpdir\", mount_path=\"/tmp\")],\n",
+    "    outputs=[\n",
+    "        Parameter(\n",
+    "            name=\"out-paths\",\n",
+    "            value_from=m.ValueFrom(\n",
+    "                path=\"/tmp/{{inputs.parameters.extension}}-path.json\"\n",
+    "            ),\n",
+    "        ),\n",
+    "        Artifact(\n",
+    "            name=\"{{inputs.parameters.extension}}-image\",\n",
+    "            path=\"/tmp/{{inputs.parameters.extension}}-image.{{inputs.parameters.extension}}\",\n",
+    "            archive=NoneArchiveStrategy(),\n",
+    "        ),\n",
+    "    ],\n",
+    ")\n",
+    "def create_image(\n",
+    "    width: int, height: int, weights: tuple[int, int, int], extension: str\n",
+    "):\n",
+    "    import json\n",
+    "\n",
+    "    from PIL import Image\n",
+    "\n",
+    "    def create_pattern(\n",
+    "        width: int,\n",
+    "        height: int,\n",
+    "        weights: tuple[int, int, int],\n",
+    "    ) -> Image.Image:\n",
+    "        print(f\"width: {width}\")\n",
+    "        print(f\"height: {height}\")\n",
+    "        print(f\"RBG weights: {weights}\")\n",
+    "        image = Image.new(\"RGB\", (width, height))\n",
+    "        pixels = image.load()\n",
+    "        for i in range(width):\n",
+    "            for j in range(height):\n",
+    "                pixels[i, j] = (  # pyright: ignore[reportOptionalSubscript]\n",
+    "                    (i + j * 50) % weights[0],\n",
+    "                    weights[1],\n",
+    "                    (i * 300 + j) % weights[2],\n",
+    "                )\n",
+    "        return image\n",
+    "\n",
+    "    image = create_pattern(width, height, weights)\n",
+    "    path = f\"/tmp/{extension}-image.{extension}\"\n",
+    "    image.save(path)\n",
+    "    with open(f\"/tmp/{extension}-path.json\", \"w\") as f:\n",
+    "        json.dump(path, f)\n",
+    "\n",
+    "\n",
+    "@script(\n",
+    "    command=[\"/tmp/venv/bin/python\"],\n",
+    "    volume_mounts=[m.VolumeMount(name=\"tmpdir\", mount_path=\"/tmp\")],\n",
+    "    outputs=Artifact(\n",
+    "        name=\"hdf5output\",\n",
+    "        path=\"/tmp/images.hdf5\",\n",
+    "        archive=NoneArchiveStrategy(),\n",
+    "    ),\n",
+    ")\n",
+    "def to_hdf5(paths: str):\n",
+    "\n",
+    "    import h5py  # pyright: ignore[reportMissingTypeStubs]\n",
+    "    import numpy as np\n",
+    "    from PIL import Image\n",
+    "\n",
+    "    print(\"creating hdf5 file\")\n",
+    "    with h5py.File(\"/tmp/images.hdf5\", \"w\") as f:\n",
+    "        for i, path in enumerate(paths):\n",
+    "            path = path.strip('\"')\n",
+    "            print(f\"Got {path}\")\n",
+    "            with Image.open(path) as image:\n",
+    "                arr = np.array(image)\n",
+    "                f.create_dataset(  # pyright: ignore[reportUnknownMemberType]\n",
+    "                    f\"image_{i}\", data=arr, dtype=arr.dtype\n",
+    "                )\n",
+    "    print(\"done\")\n",
+    "\n",
+    "\n",
+    "with Workflow(\n",
+    "    generate_name=\"hera-example-\",  # when running on graphql this should be name\n",
+    "    entrypoint=\"workflowentry\",\n",
+    "    api_version=\"argoproj.io/v1alpha1\",\n",
+    "    kind=\"Workflow\",  # ClusterWorkflowTemplate\", when on graphql\n",
+    "    labels={\"workflows.diamond.ac.uk/science-group-examples\": \"true\"},\n",
+    "    annotations={\n",
+    "        \"workflows.argoproj.io/title\": \"example remade via hera\",\n",
+    "        \"workflows.argoproj.io/description\": \"\"\"Replicates the functionality of\n",
+    "example.yaml\"\"\",\n",
+    "        \"workflows.diamond.ac.uk/repository\": \"https://github.com/DiamondLightSource/python-interface-to-workflows\",\n",
+    "    },\n",
+    "    volumes=Volume(name=\"tmpdir\", mount_path=\"/tmp/\", size=\"1Gi\"),\n",
+    ") as w:\n",
+    "    with DAG(name=\"workflowentry\"):\n",
+    "        install = install_dependencies(name=\"install\")\n",
+    "        params = generate_parameters(\n",
+    "            name=\"params\",\n",
+    "            arguments={\n",
+    "                \"png\": \"True\",\n",
+    "                \"jpg\": \"True\",\n",
+    "                \"jpeg\": \"True\",\n",
+    "                \"tif\": \"True\",\n",
+    "                \"tiff\": \"True\",\n",
+    "            },\n",
+    "        )\n",
+    "        makeimages = create_image(with_param=params.get_parameter(\"out-parameters\"))\n",
+    "        makehdf5 = to_hdf5(\n",
+    "            arguments={\n",
+    "                \"paths\": makeimages.get_parameter(\"out-paths\"),\n",
+    "            }\n",
+    "        )\n",
+    "        [install, params] >> makeimages >> makehdf5  # pyright: ignore\n",
+    "\n",
+    "\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "04708f46",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "\n",
+    "with open(\"../../templates/example_from_jupyter.txt\", \"w\") as div:\n",
+    "    div.write(w.to_yaml())  # pyright: ignore[reportUnknownMemberType]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "7e9f88cb",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from python_interface_to_workflows.submit_workflow import submit_workflow\n",
+    "\n",
+    "submit_workflow(w)"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "python-interface-to-workflows (3.11.x)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.11.15"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}