chore: import upstream snapshot with attribution

.github/workflows/reusable_notebook.yml

@@ -0,0 +1,71 @@
+name: test-notebook
+
+on:
+  workflow_call:
+    inputs:
+      notebook-location:
+        description: "Location of Jupyter notebook to run"
+        required: true
+        type: string
+      ci-image:
+        required: false
+        type: string
+        default: ''
+    secrets:
+      #LLM_MODEL:
+      #  required: true
+      #LLM_ENDPOINT:
+      #  required: true
+      LLM_API_KEY:
+        required: true
+      LLM_ARGS:
+        required: false
+      OPENAI_API_KEY:
+        required: true
+      #LLM_API_VERSION:
+      #  required: true
+      EMBEDDING_MODEL:
+        required: true
+      EMBEDDING_API_KEY:
+        required: true
+
+env:
+  RUNTIME__LOG_LEVEL: ERROR
+
+jobs:
+
+  run_notebook_test:
+    name: test
+    runs-on: ubuntu-22.04
+    container: ${{ inputs.ci-image != '' && fromJSON(format('{{"image":"{0}","credentials":{{"username":"{1}","password":"{2}"}}}}', inputs.ci-image, github.actor, github.token)) || null }}
+    defaults:
+      run:
+        shell: bash
+    steps:
+      - name: Check out
+        uses: actions/checkout@master
+
+      - name: Cognee Setup
+        uses: ./.github/actions/cognee_setup
+        with:
+          python-version: ${{ inputs.python-version }}
+          extra-dependencies: "notebook"
+
+      - name: Execute Jupyter Notebook
+        env:
+          ENV: 'dev'
+          #LLM_MODEL: ${{ secrets.LLM_MODEL }}
+          #LLM_ENDPOINT: ${{ secrets.LLM_ENDPOINT }}
+          LLM_API_KEY: ${{ secrets.OPENAI_API_KEY }}
+          LLM_ARGS: ${{ secrets.LLM_ARGS }}
+          OPENAI_API_KEY: ${{ secrets.OPENAI_API_KEY }} # Use OpenAI Until a multimedia model is deployed and DeepEval support for other models is added
+          #LLM_API_VERSION: ${{ secrets.LLM_API_VERSION }}
+          EMBEDDING_DIMENSIONS: 300
+          EMBEDDING_MODEL: ${{ secrets.EMBEDDING_MODEL }}
+          EMBEDDING_API_KEY: ${{ secrets.EMBEDDING_API_KEY }}
+        run: |
+          uv run jupyter nbconvert \
+          --to notebook \
+          --execute ${{ inputs.notebook-location }} \
+          --output executed_notebook.ipynb \
+          --ExecutePreprocessor.timeout=1200