sdk-py 0.1.43

sdk-py: Handle stream(params=)

.github/ISSUE_TEMPLATE/bug-report.yml

@@ -7,35 +7,29 @@ body:
       value: >
         Thank you for taking the time to file a bug report. 
         
-        Use this to report bugs in LangChain. 
-        
-        If you're not certain that your issue is due to a bug in LangChain, please use [GitHub Discussions](https://github.com/langchain-ai/langchain/discussions)
-        to ask for help with your issue.
+        Use this to report BUGS in LangGraph. For usage questions, feature requests and general design questions, please use [GitHub Discussions](https://github.com/langchain-ai/langgraph/discussions).
         
         Relevant links to check before filing a bug report to see if your issue has already been reported, fixed or
         if there's another way to solve your problem:
         
-        [LangGraph documentation](https://langchain-ai.github.io/langgraph/).
+        [LangGraph Github Discussions](https://github.com/langchain-ai/langgraph/discussions),
+        [LangGraph Github Issues](https://github.com/langchain-ai/langgraph/issues),
+        [LangGraph how-to guides](https://langchain-ai.github.io/langgraph/how-tos/).
         [LangChain documentation with the integrated search](https://python.langchain.com/docs/get_started/introduction),
         [GitHub search](https://github.com/langchain-ai/langgraph),
-        [LangChain Github Discussions](https://github.com/langchain-ai/langgraph/discussions),
-        [LangChain Github Issues](https://github.com/langchain-ai/langgraph/issues),
-        [LangChain ChatBot](https://chat.langchain.com/)
   - type: checkboxes
     id: checks
     attributes:
       label: Checked other resources
-      description: Please confirm and check all the following options.
+      description: Before submitting this issue, please confirm that you have completed all the steps below by checking each option. These steps help ensure your issue is well-defined, relevant, and actionable.
       options:
-        - label: I added a very descriptive title to this issue.
+        - label: This is a bug, not a usage question. For questions, please use GitHub Discussions.
           required: true
-        - label: I searched the [LangGraph](https://langchain-ai.github.io/langgraph/)/LangChain documentation with the integrated search.
+        - label: I added a clear and detailed title that summarizes the issue.
           required: true
-        - label: I used the GitHub search to find a similar question and didn't find it.
+        - label: I read what a minimal reproducible example is (https://stackoverflow.com/help/minimal-reproducible-example).
           required: true
-        - label: I am sure that this is a bug in LangGraph/LangChain rather than my code.
-          required: true
-        - label: I am sure this is better as an issue [rather than a GitHub discussion](https://github.com/langchain-ai/langgraph/discussions/new/choose), since this is a LangGraph bug and not a design question.
+        - label: I included a self-contained, minimal example that demonstrates the issue INCLUDING all the relevant imports. The code run AS IS to reproduce the issue.
           required: true
   - type: textarea
     id: reproduction
@@ -45,14 +39,6 @@ body:
       label: Example Code
       description: |
         Please add a self-contained, [minimal, reproducible, example](https://stackoverflow.com/help/minimal-reproducible-example) with your use case.
-        
-        If a maintainer can copy it, run it, and see it right away, there's a much higher chance that you'll be able to get help.
-        
-        **Important!** 
-        
-        * Reduce your code to the minimum required to reproduce the issue if possible. This makes it much easier for others to help you.
-        * Avoid screenshots when possible, as they are hard to read and (more importantly) don't allow others to copy-and-paste your code.
-
       placeholder: |
         from langgraph.graph import StateGraph
 
@@ -92,25 +78,8 @@ body:
     attributes:
       label: System Info
       description: |
-        Please share your system info with us. 
-        
-        "pip freeze | grep langchain" 
-        platform (windows / linux / mac)
-        python version
-        
-        OR if you're on a recent version of langchain-core you can paste the output of:
-        
         python -m langchain_core.sys_info
       placeholder: |
-        "pip freeze | grep langgraph"
-        platform
-        python version
-        
-        Alternatively, if you're on a recent version of langchain-core you can paste the output of:
-        
         python -m langchain_core.sys_info
-        
-        These will only surface LangChain packages, don't forget to include any other relevant
-        packages you're using (if you're not sure what's relevant, you can paste the entire output of `pip freeze`).
     validations:
       required: true

.github/scripts/check_sdk_methods.py

@@ -0,0 +1,64 @@
+import ast
+import os
+from itertools import filterfalse
+from typing import List, Tuple
+
+ROOT_PATH = os.path.abspath(os.path.join(__file__, "..", "..", ".."))
+CLIENT_PATH = os.path.join(ROOT_PATH, "libs", "sdk-py", "langgraph_sdk", "client.py")
+
+
+def get_class_methods(node: ast.ClassDef) -> List[str]:
+    return [n.name for n in node.body if isinstance(n, (ast.FunctionDef, ast.AsyncFunctionDef))]
+
+
+def find_classes(tree: ast.AST) -> List[Tuple[str, List[str]]]:
+    classes = []
+    for node in ast.walk(tree):
+        if isinstance(node, ast.ClassDef):
+            methods = get_class_methods(node)
+            classes.append((node.name, methods))
+    return classes
+
+
+def compare_sync_async_methods(sync_methods: List[str], async_methods: List[str]) -> List[str]:
+    sync_set = set(sync_methods)
+    async_set = set(async_methods)
+    missing_in_sync = list(async_set - sync_set)
+    missing_in_async = list(sync_set - async_set)
+    return missing_in_sync + missing_in_async
+
+
+def main():
+    with open(CLIENT_PATH, "r") as file:
+        tree = ast.parse(file.read())
+
+    classes = find_classes(tree)
+  
+    def is_sync(class_spec: Tuple[str, List[str]]) -> bool:
+        return class_spec[0].startswith("Sync")
+
+    sync_class_name_to_methods = {class_name: class_methods for class_name, class_methods in filter(is_sync, classes)}
+    async_class_name_to_methods = {class_name: class_methods for class_name, class_methods in filterfalse(is_sync, classes)}
+
+    mismatches = []
+
+    for async_class_name, async_class_methods in async_class_name_to_methods.items():
+        sync_class_name = "Sync" + async_class_name
+        sync_class_methods = sync_class_name_to_methods.get(sync_class_name, [])
+        diff = compare_sync_async_methods(sync_class_methods, async_class_methods)
+        if diff:
+            mismatches.append((sync_class_name, async_class_name, diff))
+
+    if mismatches:
+        error_message = "Mismatches found between sync and async client methods:\n"
+        for sync_class_name, async_class_name, diff in mismatches:
+            error_message += f"{sync_class_name} vs {async_class_name}:\n"
+            for method in diff:
+                error_message += f"  - {method}\n"
+        raise ValueError(error_message)
+
+    print("All sync and async client methods match.")
+
+
+if __name__ == "__main__":
+    main()

.github/scripts/run_langgraph_cli_test.py

@@ -0,0 +1,115 @@
+import asyncio
+import json
+import os
+import pathlib
+import sys
+import langgraph_cli
+import langgraph_cli.docker
+import langgraph_cli.config
+
+from langgraph_cli.exec import Runner, subp_exec
+from langgraph_cli.progress import Progress
+from langgraph_cli.constants import DEFAULT_PORT
+
+
+def test(
+    config: pathlib.Path,
+    port: int,
+    tag: str,
+    verbose: bool,
+):
+    with Runner() as runner, Progress(message="Pulling...") as set:
+        # check docker available
+        capabilities = langgraph_cli.docker.check_capabilities(runner)
+        # open config
+        config_json = langgraph_cli.config.validate_config_file(config)
+
+        set("Running...")
+        args = [
+            "run",
+            "--rm",
+            "-p",
+            f"{port}:8000",
+        ]
+        if isinstance(config_json["env"], str):
+            args.extend(
+                [
+                    "--env-file",
+                    str(config.parent / config_json["env"]),
+                ]
+            )
+        else:
+            for k, v in config_json["env"].items():
+                args.extend(
+                    [
+                        "-e",
+                        f"{k}={v}",
+                    ]
+                )
+        if capabilities.healthcheck_start_interval:
+            args.extend(
+                [
+                    "--health-interval",
+                    "5s",
+                    "--health-retries",
+                    "1",
+                    "--health-start-period",
+                    "10s",
+                    "--health-start-interval",
+                    "1s",
+                ]
+            )
+        else:
+            args.extend(
+                [
+                    "--health-interval",
+                    "5s",
+                    "--health-retries",
+                    "2",
+                ]
+            )
+
+        _task = None
+
+        def on_stdout(line: str):
+            nonlocal _task
+            if "GET /ok" in line or "Uvicorn running on" in line:
+                set("")
+                sys.stdout.write(
+                    f"""Ready!
+- API: http://localhost:{port}
+"""
+                )
+                sys.stdout.flush()
+                _task.cancel()
+                return True
+            return False
+
+        async def subp_exec_task(*args, **kwargs):
+            nonlocal _task
+            _task = asyncio.create_task(subp_exec(*args, **kwargs))
+            await _task
+
+        try:
+            runner.run(
+                subp_exec_task(
+                    "docker",
+                    *args,
+                    tag,
+                    verbose=verbose,
+                    on_stdout=on_stdout,
+                )
+            )
+        except asyncio.CancelledError:
+            pass
+
+
+if __name__ == "__main__":
+    import argparse
+
+    parser = argparse.ArgumentParser()
+    parser.add_argument("-t", "--tag", type=str)
+    parser.add_argument("-c", "--config", type=str, default="./langgraph.json")
+    parser.add_argument("-p", "--port", default=DEFAULT_PORT)
+    args = parser.parse_args()
+    test(pathlib.Path(args.config), args.port, args.tag, verbose=True)

.github/workflows/_integration_test.yml

@@ -39,22 +39,36 @@ jobs:
       - name: Install cli globally
         if: steps.changed-files.outputs.all
         run: pip install -e .
-      - name: Start service A
+      - name: Build and test service A
         if: steps.changed-files.outputs.all
+        working-directory: libs/cli/examples
         run: |
-          timeout 60 langgraph test -c examples/langgraph.json --verbose || (exit "$(($? == 124 ? 0 : $?))")
-      - name: Start service B
+          # The build-arg isn't used; just testing that we accept other args
+          langgraph build -t langgraph-test-a  --base-image "langchain/langgraph-trial"
+          cp .env.example .envg
+          timeout 60 python ../../../.github/scripts/run_langgraph_cli_test.py -c langgraph.json -t langgraph-test-a
+      - name: Build and test service B
         if: steps.changed-files.outputs.all
         working-directory: libs/cli/examples/graphs
         run: |
-          timeout 60 langgraph test --verbose || (exit "$(($? == 124 ? 0 : $?))")
-      - name: Start service C
+          langgraph build -t langgraph-test-b  --base-image "langchain/langgraph-trial"
+          timeout 60 python ../../../../.github/scripts/run_langgraph_cli_test.py -t langgraph-test-b
+      - name: Build and test service C
         if: steps.changed-files.outputs.all
         working-directory: libs/cli/examples/graphs_reqs_a
         run: |
-          timeout 60 langgraph test --verbose || (exit "$(($? == 124 ? 0 : $?))")
-      - name: Start service D
+          langgraph build -t langgraph-test-c  --base-image "langchain/langgraph-trial"
+          timeout 60 python ../../../../.github/scripts/run_langgraph_cli_test.py -t langgraph-test-c
+      - name: Build and test service D
         if: steps.changed-files.outputs.all
         working-directory: libs/cli/examples/graphs_reqs_b
         run: |
-          timeout 60 langgraph test --verbose || (exit "$(($? == 124 ? 0 : $?))")
+          langgraph build -t langgraph-test-d  --base-image "langchain/langgraph-trial"
+          timeout 60 python ../../../../.github/scripts/run_langgraph_cli_test.py -t langgraph-test-d
+
+      - name: Build JS service
+        if: steps.changed-files.outputs.all
+        working-directory: libs/cli/js-examples
+        run: |
+          langgraph build -t langgraph-test-e
+  

.github/workflows/_lint.yml

@@ -27,8 +27,7 @@ jobs:
         # Starting new jobs is also relatively slow,
         # so linting on fewer versions makes CI faster.
         python-version:
-          - "3.9"
-          - "3.11"
+          - "3.12"
     name: "lint #${{ matrix.python-version }}"
     steps:
       - uses: actions/checkout@v4

.github/workflows/_test.yml

@@ -21,6 +21,7 @@ jobs:
           - "3.10"
           - "3.11"
           - "3.12"
+          - "3.13"
 
     name: "test #${{ matrix.python-version }}"
     steps:
@@ -32,6 +33,12 @@ jobs:
           poetry-version: ${{ env.POETRY_VERSION }}
           working-directory: ${{ inputs.working-directory }}
           cache-key: test-${{ inputs.working-directory }}
+      - name: Login to Docker Hub
+        uses: docker/login-action@v3
+        if: ${{ !github.event.pull_request.head.repo.fork }}
+        with:
+          username: ${{ secrets.DOCKERHUB_USERNAME }}
+          password: ${{ secrets.DOCKERHUB_RO_TOKEN }}
 
       - name: Install dependencies
         shell: bash

.github/workflows/_test_langgraph.yml

@@ -16,14 +16,22 @@ jobs:
           - "3.10"
           - "3.11"
           - "3.12"
+          - "3.13"
         core-version:
-          - ">=0.2.39,<0.3.0"
           - "latest"
+        ff-send-v2:
+          - "false"
+        include:
+          - python-version: "3.11"
+            core-version: ">=0.2.42,<0.3.0"
+          - python-version: "3.11"
+            core-version: "latest"
+            ff-send-v2: "true"
 
     defaults:
       run:
         working-directory: libs/langgraph
-    name: "test #${{ matrix.python-version }} (langchain-core: ${{ matrix.core-version }})"
+    name: "test #${{ matrix.python-version }} (langchain-core: ${{ matrix.core-version }}, ff-send-v2: ${{ matrix.ff-send-v2 }})"
     steps:
       - uses: actions/checkout@v4
       - name: Set up Python ${{ matrix.python-version }} + Poetry ${{ env.POETRY_VERSION }}
@@ -32,6 +40,12 @@ jobs:
           python-version: ${{ matrix.python-version }}
           poetry-version: ${{ env.POETRY_VERSION }}
           cache-key: test-langgraph
+      - name: Login to Docker Hub
+        uses: docker/login-action@v3
+        if: ${{ !github.event.pull_request.head.repo.fork }}
+        with:
+          username: ${{ secrets.DOCKERHUB_USERNAME }}
+          password: ${{ secrets.DOCKERHUB_RO_TOKEN }}
 
       - name: Install dependencies
         shell: bash
@@ -43,8 +57,10 @@ jobs:
 
       - name: Run tests
         shell: bash
+        env:
+          LANGGRAPH_FF_SEND_V2: ${{ matrix.ff-send-v2 }}
         run: |
-          make test
+          make test_parallel
 
       - name: Ensure the tests did not create any additional files
         shell: bash

.github/workflows/_test_release.yml

@@ -93,3 +93,5 @@ jobs:
           # This is *only for CI use* and is *extremely dangerous* otherwise!
           # https://github.com/pypa/gh-action-pypi-publish#tolerating-release-package-file-duplicates
           skip-existing: true
+          # Temp workaround since attestations are on by default as of gh-action-pypi-publish v1.11.0
+          attestations: false

.github/workflows/_test_scheduler_kafka.yml

@@ -27,6 +27,12 @@ jobs:
           python-version: ${{ matrix.python-version }}
           poetry-version: ${{ env.POETRY_VERSION }}
           cache-key: test-scheduler-kafka
+      - name: Login to Docker Hub
+        uses: docker/login-action@v3
+        if: ${{ !github.event.pull_request.head.repo.fork }}
+        with:
+          username: ${{ secrets.DOCKERHUB_USERNAME }}
+          password: ${{ secrets.DOCKERHUB_RO_TOKEN }}
 
       - name: Install dependencies
         shell: bash

.github/workflows/ci.yml

@@ -31,6 +31,7 @@ jobs:
             "libs/cli",
             "libs/checkpoint",
             "libs/checkpoint-sqlite",
+            "libs/checkpoint-duckdb",
             "libs/checkpoint-postgres",
             "libs/scheduler-kafka",
           ]
@@ -47,6 +48,7 @@ jobs:
             "libs/cli",
             "libs/checkpoint",
             "libs/checkpoint-sqlite",
+            "libs/checkpoint-duckdb",
             "libs/checkpoint-postgres"
           ]
     uses: ./.github/workflows/_test.yml
@@ -66,6 +68,18 @@ jobs:
     uses: ./.github/workflows/_test_scheduler_kafka.yml
     secrets: inherit
 
+  check-sdk-methods:
+    name: "Check SDK methods matching"
+    runs-on: ubuntu-latest
+    steps:
+      - uses: actions/checkout@v4
+      - name: Set up Python
+        uses: actions/setup-python@v5
+        with:
+          python-version: '3.11'
+      - name: Run check_sdk_methods script
+        run: python .github/scripts/check_sdk_methods.py
+
   integration-test:
     name: CLI integration test
     uses: ./.github/workflows/_integration_test.yml

.github/workflows/codespell.yml

@@ -32,7 +32,7 @@
           - name: Codespell
             uses: codespell-project/actions-codespell@v2
             with:
-              skip: '*.ambr,*.lock,*.ipynb,*.yaml'
+              skip: '*.ambr,*.lock,*.ipynb,*.yaml,*.zlib'
               ignore_words_list: ${{ steps.extract_ignore_words.outputs.ignore_words_list }}
           # We do this to avoid spellchecking cell outputs
           - name: Codespell Notebooks

.github/workflows/deploy_docs.yml

@@ -22,8 +22,30 @@ concurrency:
   cancel-in-progress: false
 
 jobs:
-  deploy:
+  get-changed-files:
     runs-on: ubuntu-latest
+    outputs:
+      changed-files: ${{ steps.changed-files.outputs.added_modified }}
+    steps:
+      - uses: actions/checkout@v4
+      - name: Get changed files
+        id: changed-files
+        uses: Ana06/get-changed-files@v2.3.0
+        with:
+          filter: "docs/docs/**"
+
+  run-changed-notebooks:
+    needs: get-changed-files
+    uses: ./.github/workflows/run_notebooks.yml
+    secrets: inherit
+    with:
+      changed-files: ${{ needs.get-changed-files.outputs.changed-files }}
+
+  deploy:
+    # needs: run-changed-notebooks
+    runs-on: ubuntu-latest
+    env:
+      GITHUB_TOKEN: ${{ secrets.MKDOCS_GITHUB_TOKEN }}
     steps:
       - uses: actions/checkout@v4
         with:
@@ -38,9 +60,19 @@ jobs:
 
       - name: Install dependencies
         run: |
-          poetry install --with docs
-          poetry run pip install -U pytest pytest-check-links langsmith langchain GitPython
+          poetry install --with test --no-root
+          poetry run pip install -U \
+            pytest \
+            pytest-check-links \
+            langsmith \
+            langchain \
+            GitPython \
+            "git+https://${GITHUB_TOKEN}@github.com/langchain-ai/mkdocs-material-insiders.git"
 
+      - name: Lint Docs
+        # This step lints the docs using the existing linting set up.
+        # It should be very fast and should not require any external services.
+        run: make lint-docs
       - name: Build site
         run: make build-docs
         env:
@@ -56,8 +88,13 @@ jobs:
               --check-links-ignore "https://(api|web|docs)\.smith\.langchain\.com/.*" \
               --check-links-ignore "https://x.com/.*" \
               --check-links-ignore "https://github\.com/.*" \
+              --check-links-ignore "http://localhost:8123/.*" \
               --check-links-ignore "/.*\.(ipynb|html)$" \
-              --check-links $(find docs/site -name "index.html" | grep -v 'storm/index.html')
+              --check-links-ignore "https://python\.langchain\.com/.*" \
+              --check-links-ignore "https://openai\.com/.*" \
+              --check-links-ignore "https://pepy\.tech/.*" \
+              --check-links $(find docs/site -name "index.html" | grep -v 'storm/index.html') 
+              
           else
             echo "Fetching changes from origin/main..."
             git fetch origin main
@@ -68,6 +105,7 @@ jobs:
               echo "Running link check on HTML files matching changed notebook files..."
               poetry run pytest -v \
                 --check-links-ignore "https://(api|web|docs)\.smith\.langchain\.com/.*" \
+                --check-links-ignore "http://localhost:8123/.*" \
                 --check-links-ignore "https://x.com/.*" \
                 --check-links-ignore "https://github\.com/.*" \
                 --check-links-ignore "/.*\.(ipynb|html)$" \

.github/workflows/release.yml

@@ -270,6 +270,8 @@ jobs:
           packages-dir: ${{ inputs.working-directory }}/dist/
           verbose: true
           print-hash: true
+          # Temp workaround since attestations are on by default as of gh-action-pypi-publish v1.11.0
+          attestations: false
 
   mark-release:
     needs:

.github/workflows/run_notebooks.yml

@@ -2,6 +2,12 @@ name: Run notebooks
 
 on:
   workflow_dispatch:
+  workflow_call:
+    inputs:
+      changed-files:
+        required: false
+        type: string
+        description: "JSON string of changed files"
   schedule:
     - cron: '0 13 * * *'
 
@@ -14,7 +20,6 @@ jobs:
           - "development"
           - "latest"
 
-    name: "test (langgraph: ${{ matrix.lib-version }})"
     steps:
       - uses: actions/checkout@v4
       - name: Set up Python + Poetry
@@ -32,6 +37,10 @@ jobs:
       - name: Start services
         run: make start-services
 
+      - name: Pre-download tiktoken files
+        run: |
+          poetry run python docs/_scripts/download_tiktoken.py
+
       - name: Prepare notebooks
         run: |
           if [ "${{ matrix.lib-version }}" = "development" ]; then
@@ -48,8 +57,22 @@ jobs:
           ANTHROPIC_API_KEY: ${{ secrets.ANTHROPIC_API_KEY }}
           TAVILY_API_KEY: ${{ secrets.TAVILY_API_KEY }}
           LANGSMITH_API_KEY: ${{ secrets.LANGSMITH_API_KEY }}
+          NOMIC_API_KEY: ${{ secrets.NOMIC_API_KEY }}
+          COHERE_API_KEY: ${{ secrets.COHERE_API_KEY }}
+          FIREWORKS_API_KEY: ${{ secrets.FIREWORKS_API_KEY }}
         run: |
-          ./docs/_scripts/execute_notebooks.sh
+          if [ "${{ github.event_name }}" = "workflow_dispatch" ] || [ "${{ github.event_name }}" = "schedule" ]; then
+            echo "Running all notebooks"
+            ./docs/_scripts/execute_notebooks.sh
+          else
+            CHANGED_FILES=$(echo '${{ inputs.changed-files }}' | tr ' ' '\n' | grep '\.ipynb$' || true)
+            if [ -n "$CHANGED_FILES" ]; then
+              echo "Running changed notebooks: $CHANGED_FILES"
+              ./docs/_scripts/execute_notebooks.sh $CHANGED_FILES
+            else
+              echo "No notebook files changed, skipping execution"
+            fi
+          fi
 
       - name: Stop services
         run: make stop-services

CONTRIBUTING.md

@@ -49,7 +49,7 @@ gain understanding of concepts and how they interact by showing one way to achie
 
 They should **avoid** giving
 multiple permutations of ways to achieve that goal in-depth. Choice is burdensome. Instead, they should guide a new user through a recommended path to accomplishing a concrete goal. While the end result of a tutorial does not necessarily need to
-be completely production-ready, it should be useful and practically satisfy the the goal that you clearly stated in the tutorial's introduction.
+be completely production-ready, it should be useful and practically satisfy the goal that you clearly stated in the tutorial's introduction.
 
 To quote the Diataxis website:
 

Makefile

@@ -1,4 +1,4 @@
-.PHONY: build-docs serve-docs serve-clean-docs clean-docs codespell build-typedoc
+.PHONY: lint-docs format-docs build-docs serve-docs serve-clean-docs clean-docs codespell build-typedoc
 
 build-typedoc:
 	cd libs/sdk-js && yarn install --include-dev && yarn typedoc
@@ -13,12 +13,22 @@ serve-clean-docs: clean-docs
 	poetry run python -m mkdocs serve -c -f docs/mkdocs.yml --strict -w ./libs/langgraph
 
 serve-docs: build-typedoc
-	poetry run python -m mkdocs serve -f docs/mkdocs.yml -w ./libs/langgraph --dirty
+	poetry run python -m mkdocs serve -f docs/mkdocs.yml -w ./libs/langgraph  -w ./libs/checkpoint --dirty
 
 clean-docs:
 	find ./docs/docs -name "*.ipynb" -type f -delete
 	rm -rf docs/site
 
+## Run format against the project documentation.
+format-docs:
+	poetry run ruff format docs/docs
+	poetry run ruff check --fix docs/docs
+
+# Check the docs for linting violations
+lint-docs:
+	poetry run ruff format --check docs/docs
+	poetry run ruff check docs/docs
+
 codespell:
 	./docs/codespell_notebooks.sh .
 
@@ -26,4 +36,4 @@ start-services:
 	docker compose -f docs/test-compose.yml up -V --force-recreate --wait --remove-orphans
 
 stop-services:
-	docker compose -f docs/test-compose.yml down
+	docker compose -f docs/test-compose.yml down

README.md

@@ -16,6 +16,8 @@
 
 LangGraph is inspired by [Pregel](https://research.google/pubs/pub37252/) and [Apache Beam](https://beam.apache.org/). The public interface draws inspiration from [NetworkX](https://networkx.org/documentation/latest/). LangGraph is built by LangChain Inc, the creators of LangChain, but can be used without LangChain.
 
+[LangGraph Platform](https://langchain-ai.github.io/langgraph/concepts/langgraph_platform) is infrastructure for deploying LangGraph agents. It is a commercial solution for deploying agentic applications to production, built on the open-source LangGraph framework. The LangGraph Platform consists of several components that work together to support the development, deployment, debugging, and monitoring of LangGraph applications: [LangGraph Server](https://langchain-ai.github.io/langgraph/concepts/langgraph_server) (APIs), [LangGraph SDKs](https://langchain-ai.github.io/langgraph/concepts/sdk) (clients for the APIs), [LangGraph CLI](https://langchain-ai.github.io/langgraph/concepts/langgraph_cli) (command line tool for building the server), [LangGraph Studio](https://langchain-ai.github.io/langgraph/concepts/langgraph_studio) (UI/debugger),
+
 To learn more about LangGraph, check out our first LangChain Academy course, *Introduction to LangGraph*, available for free [here](https://academy.langchain.com/courses/intro-to-langgraph).
 
 ### Key Features
@@ -26,6 +28,16 @@ To learn more about LangGraph, check out our first LangChain Academy course, *In
 - **Streaming Support**: Stream outputs as they are produced by each node (including token streaming).
 - **Integration with LangChain**: LangGraph integrates seamlessly with [LangChain](https://github.com/langchain-ai/langchain/) and [LangSmith](https://docs.smith.langchain.com/) (but does not require them).
 
+### LangGraph Platform
+
+LangGraph Platform is a commercial solution for deploying agentic applications to production, built on the open-source LangGraph framework.
+Here are some common issues that arise in complex deployments, which LangGraph Platform addresses:
+
+- **Streaming support**: LangGraph Server provides [multiple streaming modes](https://langchain-ai.github.io/langgraph/concepts/streaming) optimized for various application needs
+- **Background runs**: Runs agents asynchronously in the background
+- **Support for long running agents**: Infrastructure that can handle long running processes
+- **[Double texting](https://langchain-ai.github.io/langgraph/concepts/double_texting)**: Handle the case where you get two messages from the user before the agent can respond
+- **Handle burstiness**: Task queue for ensuring requests are handled consistently without loss, even under heavy loads
 
 ## Installation
 
@@ -224,9 +236,9 @@ final_state["messages"][-1].content
 
 * [Tutorials](https://langchain-ai.github.io/langgraph/tutorials/): Learn to build with LangGraph through guided examples.
 * [How-to Guides](https://langchain-ai.github.io/langgraph/how-tos/): Accomplish specific things within LangGraph, from streaming, to adding memory & persistence, to common design patterns (branching, subgraphs, etc.), these are the place to go if you want to copy and run a specific code snippet.
-* [Conceptual Guides](https://langchain-ai.github.io/langgraph/concepts/): In-depth explanations of the key concepts and principles behind LangGraph, such as nodes, edges, state and more.
+* [Conceptual Guides](https://langchain-ai.github.io/langgraph/concepts/high_level/): In-depth explanations of the key concepts and principles behind LangGraph, such as nodes, edges, state and more.
 * [API Reference](https://langchain-ai.github.io/langgraph/reference/graphs/): Review important classes and methods, simple examples of how to use the graph and checkpointing APIs, higher-level prebuilt components and more.
-* [Cloud (beta)](https://langchain-ai.github.io/langgraph/cloud/): With one click, deploy LangGraph applications to LangGraph Cloud.
+* [LangGraph Platform](https://langchain-ai.github.io/langgraph/concepts/#langgraph-platform): LangGraph Platform is a commercial solution for deploying agentic applications in production, built on the open-source LangGraph framework.
 
 ## Contributing
 

docs/_scripts/download_tiktoken.py

@@ -0,0 +1,5 @@
+import tiktoken
+
+# This will trigger the download and caching of the necessary files
+for encoding in ("gpt2", "gpt-3.5"):
+    tiktoken.encoding_for_model(encoding)

docs/_scripts/execute_notebooks.sh

@@ -1,5 +1,36 @@
-for file in $(find docs/docs/how-tos -name "*.ipynb" | grep -v ".ipynb_checkpoints")
-do
-  echo "Executing $file"
-  poetry run jupyter execute "$file"
+#!/bin/bash
+
+# Read the list of notebooks to skip from the JSON file
+SKIP_NOTEBOOKS=$(python -c "import json; print('\n'.join(json.load(open('docs/notebooks_no_execution.json'))))")
+
+# Function to execute a single notebook
+execute_notebook() {
+    file="$1"
+    echo "Starting execution of $file"
+    start_time=$(date +%s)
+    if ! output=$(time poetry run jupyter execute "$file" 2>&1); then
+        end_time=$(date +%s)
+        execution_time=$((end_time - start_time))
+        echo "Error in $file. Execution time: $execution_time seconds"
+        echo "Error details: $output"
+        exit 1
+    fi
+    end_time=$(date +%s)
+    execution_time=$((end_time - start_time))
+    echo "Finished $file. Execution time: $execution_time seconds"
+}
+
+export -f execute_notebook
+
+# Check if custom notebook paths are provided
+if [ $# -gt 0 ]; then
+    notebooks=$(echo "$@" | tr ' ' '\n' | grep -vFf <(echo "$SKIP_NOTEBOOKS"))
+else
+    # Find all notebooks and filter out those in the skip list
+    notebooks=$(find docs/docs/tutorials docs/docs/how-tos -name "*.ipynb" | grep -v ".ipynb_checkpoints" | grep -vFf <(echo "$SKIP_NOTEBOOKS"))
+fi
+
+# Execute notebooks sequentially
+for file in $notebooks; do
+    execute_notebook "$file"
 done

docs/_scripts/generate_api_reference_links.py

@@ -0,0 +1,246 @@
+import importlib
+import inspect
+import logging
+import os
+import re
+from typing import List, Literal, Optional
+from typing_extensions import TypedDict
+
+import nbformat
+from nbconvert.preprocessors import Preprocessor
+
+
+logging.basicConfig(level=logging.INFO)
+logger = logging.getLogger(__name__)
+# Base URL for all class documentation
+_LANGCHAIN_API_REFERENCE = "https://python.langchain.com/api_reference/"
+_LANGGRAPH_API_REFERENCE = "https://langchain-ai.github.io/langgraph/reference/"
+
+
+# (alias/re-exported modules, source module, class, docs namespace)
+MANUAL_API_REFERENCES_LANGGRAPH = [
+    (
+        ["langgraph.prebuilt"],
+        "langgraph.prebuilt.chat_agent_executor",
+        "create_react_agent",
+        "prebuilt",
+    ),
+    (["langgraph.prebuilt"], "langgraph.prebuilt.tool_node", "ToolNode", "prebuilt"),
+    (
+        ["langgraph.prebuilt"],
+        "langgraph.prebuilt.tool_node",
+        "tools_condition",
+        "prebuilt",
+    ),
+    (
+        ["langgraph.prebuilt"],
+        "langgraph.prebuilt.tool_node",
+        "InjectedState",
+        "prebuilt",
+    ),
+    # Graph
+    (["langgraph.graph"], "langgraph.graph.message", "add_messages", "graphs"),
+    (["langgraph.graph"], "langgraph.graph.state", "StateGraph", "graphs"),
+    (["langgraph.graph"], "langgraph.graph.state", "CompiledStateGraph", "graphs"),
+    ([], "langgraph.types", "StreamMode", "types"),
+    (["langgraph.graph"], "langgraph.constants", "START", "constants"),
+    (["langgraph.graph"], "langgraph.constants", "END", "constants"),
+    (["langgraph.constants"], "langgraph.types", "Send", "types"),
+    (["langgraph.constants"], "langgraph.types", "Interrupt", "types"),
+    ([], "langgraph.types", "RetryPolicy", "types"),
+    ([], "langgraph.checkpoint.base", "Checkpoint", "checkpoints"),
+    ([], "langgraph.checkpoint.base", "CheckpointMetadata", "checkpoints"),
+    ([], "langgraph.checkpoint.base", "BaseCheckpointSaver", "checkpoints"),
+    ([], "langgraph.checkpoint.base", "SerializerProtocol", "checkpoints"),
+    ([], "langgraph.checkpoint.serde.jsonplus", "JsonPlusSerializer", "checkpoints"),
+    ([], "langgraph.checkpoint.memory", "MemorySaver", "checkpoints"),
+    ([], "langgraph.checkpoint.sqlite.aio", "AsyncSqliteSaver", "checkpoints"),
+    ([], "langgraph.checkpoint.sqlite", "SqliteSaver", "checkpoints"),
+    ([], "langgraph.checkpoint.postgres.aio", "AsyncPostgresSaver", "checkpoints"),
+    ([], "langgraph.checkpoint.postgres", "PostgresSaver", "checkpoints"),
+]
+
+WELL_KNOWN_LANGGRAPH_OBJECTS = {
+    (module_, class_): (source_module, namespace)
+    for (modules, source_module, class_, namespace) in MANUAL_API_REFERENCES_LANGGRAPH
+    for module_ in modules + [source_module]
+}
+
+
+def _make_regular_expression(pkg_prefix: str) -> re.Pattern:
+    if not pkg_prefix.isidentifier():
+        raise ValueError(f"Invalid package prefix: {pkg_prefix}")
+    return re.compile(
+        r"from\s+(" + pkg_prefix + "(?:_\w+)?(?:\.\w+)*?)\s+import\s+"
+        r"((?:\w+(?:,\s*)?)*"  # Match zero or more words separated by a comma+optional ws
+        r"(?:\s*\(.*?\))?)",  # Match optional parentheses block
+        re.DOTALL,  # Match newlines as well
+    )
+
+
+# Regular expression to match langchain import lines
+_IMPORT_LANGCHAIN_RE = _make_regular_expression("langchain")
+_IMPORT_LANGGRAPH_RE = _make_regular_expression("langgraph")
+
+
+def _get_full_module_name(module_path, class_name) -> Optional[str]:
+    """Get full module name using inspect"""
+    try:
+        module = importlib.import_module(module_path)
+        class_ = getattr(module, class_name)
+        module = inspect.getmodule(class_)
+        if module is None:
+            # For constants, inspect.getmodule() might return None
+            # In this case, we'll return the original module_path
+            return module_path
+        return module.__name__
+    except AttributeError as e:
+        logger.warning(f"Could not find module for {class_name}, {e}")
+        return None
+    except ImportError as e:
+        logger.warning(f"Failed to load for class {class_name}, {e}")
+        return None
+
+
+def _get_doc_title(data: str, file_name: str) -> str:
+    try:
+        return re.findall(r"^#\s*(.*)", data, re.MULTILINE)[0]
+    except IndexError:
+        pass
+    # Parse the rst-style titles
+    try:
+        return re.findall(r"^(.*)\n=+\n", data, re.MULTILINE)[0]
+    except IndexError:
+        return file_name
+
+
+class ImportInformation(TypedDict):
+    imported: str  # imported class name
+    source: str  # module path
+    docs: str  # URL to the documentation
+    title: str  # Title of the document
+
+
+def _get_imports(
+    code: str, doc_title: str, package_ecosystem: Literal["langchain", "langgraph"]
+) -> List[ImportInformation]:
+    """Get imports from the given code block.
+
+    Args:
+        code: Python code block from which to extract imports
+        doc_title: Title of the document
+        package_ecosystem: "langchain" or "langgraph". The two live in different
+            repositories and have separate documentation sites.
+
+    Returns:
+        List of import information for the given code block
+    """
+    imports = []
+
+    if package_ecosystem == "langchain":
+        pattern = _IMPORT_LANGCHAIN_RE
+    elif package_ecosystem == "langgraph":
+        pattern = _IMPORT_LANGGRAPH_RE
+    else:
+        raise ValueError(f"Invalid package ecosystem: {package_ecosystem}")
+
+    for import_match in pattern.finditer(code):
+        module = import_match.group(1)
+        if "pydantic_v1" in module:
+            continue
+        imports_str = (
+            import_match.group(2).replace("(\n", "").replace("\n)", "")
+        )  # Handle newlines within parentheses
+        # remove any newline and spaces, then split by comma
+        imported_classes = [
+            imp.strip()
+            for imp in re.split(r",\s*", imports_str.replace("\n", ""))
+            if imp.strip()
+        ]
+        for class_name in imported_classes:
+            module_path = _get_full_module_name(module, class_name)
+            if not module_path:
+                continue
+            if len(module_path.split(".")) < 2:
+                continue
+
+            if package_ecosystem == "langchain":
+                pkg = module_path.split(".")[0].replace("langchain_", "")
+                top_level_mod = module_path.split(".")[1]
+
+                url = (
+                    _LANGCHAIN_API_REFERENCE
+                    + pkg
+                    + "/"
+                    + top_level_mod
+                    + "/"
+                    + module_path
+                    + "."
+                    + class_name
+                    + ".html"
+                )
+            elif package_ecosystem == "langgraph":
+                if (module, class_name) not in WELL_KNOWN_LANGGRAPH_OBJECTS:
+                    # Likely not documented yet
+                    continue
+
+                source_module, namespace = WELL_KNOWN_LANGGRAPH_OBJECTS[
+                    (module, class_name)
+                ]
+                url = (
+                    _LANGGRAPH_API_REFERENCE
+                    + namespace
+                    + "/#"
+                    + source_module
+                    + "."
+                    + class_name
+                )
+            else:
+                raise ValueError(f"Invalid package ecosystem: {package_ecosystem}")
+
+            # Add the import information to our list
+            imports.append(
+                {
+                    "imported": class_name,
+                    "source": module,
+                    "docs": url,
+                    "title": doc_title,
+                }
+            )
+
+    return imports
+
+
+class ImportPreprocessor(Preprocessor):
+    """A preprocessor to replace imports in each Python code cell with links to their
+    documentation and append the import info in a comment."""
+
+    def preprocess(self, nb, resources):
+        self.all_imports = []
+        file_name = os.path.basename(resources.get("metadata", {}).get("name", ""))
+        _DOC_TITLE = _get_doc_title(nb.cells[0].source, file_name)
+
+        cells = []
+        for cell in nb.cells:
+            if cell.cell_type == "code":
+                cells.append(cell)
+                imports = _get_imports(
+                    cell.source, _DOC_TITLE, "langchain"
+                ) + _get_imports(cell.source, _DOC_TITLE, "langgraph")
+                if not imports:
+                    continue
+
+                cells.append(
+                    nbformat.v4.new_markdown_cell(
+                        source=f"""
+<div>
+<b>API Reference:</b>
+{' | '.join(f'<a href="{imp["docs"]}">{imp["imported"]}</a>' for imp in imports)}
+</div>
+                    """
+                    )
+                )
+            else:
+                cells.append(cell)
+        nb.cells = cells
+        return nb, resources

docs/_scripts/notebook_convert.py

@@ -0,0 +1,126 @@
+import os
+import re
+from pathlib import Path
+
+import nbformat
+from nbconvert.exporters import MarkdownExporter
+from nbconvert.preprocessors import Preprocessor
+
+from generate_api_reference_links import ImportPreprocessor
+
+
+class EscapePreprocessor(Preprocessor):
+    def preprocess_cell(self, cell, resources, cell_index):
+        if cell.cell_type == "markdown":
+            # rewrite markdown links to html links (excluding image links)
+            cell.source = re.sub(
+                r"(?<!!)\[([^\]]*)\]\((?![^\)]*//)([^)]*)(?:\.ipynb)?\)",
+                r'<a href="\2">\1</a>',
+                cell.source,
+            )
+            # Fix image paths in <img> tags
+            cell.source = re.sub(
+                r'<img\s+src="\.?/img/([^"]+)"', r'<img src="../img/\1"', cell.source
+            )
+
+        elif cell.cell_type == "code":
+            # escape ``` in code
+            cell.source = cell.source.replace("```", r"\`\`\`")
+            # escape ``` in output
+            if "outputs" in cell:
+                filter_out = set()
+                for i, output in enumerate(cell["outputs"]):
+                    if "text" in output:
+                        if not output["text"].strip():
+                            filter_out.add(i)
+                            continue
+
+                        value = output["text"].replace("```", r"\`\`\`")
+                        # handle a funky case w/ references in text
+                        value = re.sub(r"\[(\d+)\](?=\[(\d+)\])", r"[\1]\\", value)
+                        output["text"] = value
+                    elif "data" in output:
+                        for key, value in output["data"].items():
+                            if isinstance(value, str):
+                                value = value.replace("```", r"\`\`\`")
+                                # handle a funky case w/ references in text
+                                output["data"][key] = re.sub(
+                                    r"\[(\d+)\](?=\[(\d+)\])", r"[\1]\\", value
+                                )
+                cell["outputs"] = [
+                    output
+                    for i, output in enumerate(cell["outputs"])
+                    if i not in filter_out
+                ]
+
+        return cell, resources
+
+
+class ExtractAttachmentsPreprocessor(Preprocessor):
+    """
+    Extracts all of the outputs from the notebook file.  The extracted
+    outputs are returned in the 'resources' dictionary.
+    """
+
+    def preprocess_cell(self, cell, resources, cell_index):
+        """
+        Apply a transformation on each cell,
+        Parameters
+        ----------
+        cell : NotebookNode cell
+            Notebook cell being processed
+        resources : dictionary
+            Additional resources used in the conversion process.  Allows
+            preprocessors to pass variables into the Jinja engine.
+        cell_index : int
+            Index of the cell being processed (see base.py)
+        """
+
+        # Get files directory if it has been specified
+
+        # Make sure outputs key exists
+        if not isinstance(resources["outputs"], dict):
+            resources["outputs"] = {}
+
+        # Loop through all of the attachments in the cell
+        for name, attach in cell.get("attachments", {}).items():
+            for mime, data in attach.items():
+                if mime not in {
+                    "image/png",
+                    "image/jpeg",
+                    "image/svg+xml",
+                    "application/pdf",
+                }:
+                    continue
+
+                # attachments are pre-rendered. Only replace markdown-formatted
+                # images with the following logic
+                attach_str = f"({name})"
+                if attach_str in cell.source:
+                    data = f"(data:{mime};base64,{data})"
+                    cell.source = cell.source.replace(attach_str, data)
+
+        return cell, resources
+
+
+exporter = MarkdownExporter(
+    preprocessors=[
+        EscapePreprocessor,
+        ExtractAttachmentsPreprocessor,
+        ImportPreprocessor,
+    ],
+    template_name="mdoutput",
+    extra_template_basedirs=[
+        os.path.join(os.path.dirname(__file__), "notebook_convert_templates")
+    ],
+)
+
+
+def convert_notebook(
+    notebook_path: Path,
+) -> Path:
+    with open(notebook_path) as f:
+        nb = nbformat.read(f, as_version=4)
+
+    body, _ = exporter.from_notebook_node(nb)
+    return body

docs/_scripts/notebook_convert_templates/mdoutput/conf.json

@@ -0,0 +1,5 @@
+{
+  "mimetypes": {
+    "text/markdown": true
+  }
+}

docs/_scripts/notebook_convert_templates/mdoutput/index.md.j2

@@ -0,0 +1,33 @@
+{% extends 'markdown/index.md.j2' %}
+
+{%- block traceback_line -%}
+```output
+{{ line.rstrip() | strip_ansi }}
+```
+{%- endblock traceback_line -%}
+
+{%- block stream -%}
+```output
+{{ output.text.rstrip() }}
+```
+{%- endblock stream -%}
+
+{%- block data_text scoped -%}
+```output
+{{ output.data['text/plain'].rstrip() }}
+```
+{%- endblock data_text -%}
+
+{%- block data_html scoped -%}
+```html
+{{ output.data['text/html'] | safe }} 
+```
+{%- endblock data_html -%}
+
+{%- block data_jpg scoped -%}
+![](data:image/jpg;base64,{{ output.data['image/jpeg'] }})
+{%- endblock data_jpg -%}
+
+{%- block data_png scoped -%}
+![](data:image/png;base64,{{ output.data['image/png'] }})
+{%- endblock data_png -%}

docs/_scripts/notebook_hooks.py

@@ -0,0 +1,40 @@
+import logging
+from typing import Any, Dict
+
+from mkdocs.structure.pages import Page
+from mkdocs.structure.files import Files, File
+from notebook_convert import convert_notebook
+
+logger = logging.getLogger(__name__)
+logging.basicConfig()
+logger.setLevel(logging.INFO)
+
+
+class NotebookFile(File):
+    def is_documentation_page(self):
+        return True
+
+
+def on_files(files: Files, **kwargs: Dict[str, Any]):
+    new_files = Files([])
+    for file in files:
+        if file.src_path.endswith(".ipynb"):
+            new_file = NotebookFile(
+                path=file.src_path,
+                src_dir=file.src_dir,
+                dest_dir=file.dest_dir,
+                use_directory_urls=file.use_directory_urls,
+            )
+            new_files.append(new_file)
+        else:
+            new_files.append(file)
+    return new_files
+
+
+def on_page_markdown(markdown: str, page: Page, **kwargs: Dict[str, Any]):
+    if page.file.src_path.endswith(".ipynb"):
+        logger.info("Processing Jupyter notebook: %s", page.file.src_path)
+        body = convert_notebook(page.file.abs_src_path)
+        return body
+
+    return markdown

docs/_scripts/prepare_notebooks_for_ci.py

@@ -2,20 +2,50 @@
 
 import logging
 import os
-
+import json
 import click
 import nbformat
 
 logger = logging.getLogger(__name__)
-NOTEBOOK_DIRS = ("docs/docs/how-tos",)
+NOTEBOOK_DIRS = ("docs/docs/how-tos","docs/docs/tutorials")
 DOCS_PATH = os.path.dirname(os.path.dirname(os.path.abspath(__file__)))
 CASSETTES_PATH = os.path.join(DOCS_PATH, "cassettes")
 
+BLOCKLIST_COMMANDS = (
+    # skip if has WebBaseLoader to avoid caching web pages
+    "WebBaseLoader",
+    # skip if has draw_mermaid_png to avoid generating mermaid images via API
+    "draw_mermaid_png",
+)
+
 NOTEBOOKS_NO_CASSETTES = (
     "docs/docs/how-tos/visualization.ipynb",
     "docs/docs/how-tos/many-tools.ipynb"
 )
 
+NOTEBOOKS_NO_EXECUTION = [
+    # this uses a user provided project name for langsmith
+    "docs/docs/tutorials/tnt-llm/tnt-llm.ipynb",
+    # this uses langsmith datasets
+    "docs/docs/tutorials/chatbot-simulation-evaluation/langsmith-agent-simulation-evaluation.ipynb",
+    # this uses browser APIs
+    "docs/docs/tutorials/web-navigation/web_voyager.ipynb",
+    # these RAG guides use an ollama model
+    "docs/docs/tutorials/rag/langgraph_adaptive_rag_local.ipynb",
+    "docs/docs/tutorials/rag/langgraph_crag_local.ipynb",
+    "docs/docs/tutorials/rag/langgraph_self_rag_local.ipynb",
+    # this loads a massive dataset from gcp
+    "docs/docs/tutorials/usaco/usaco.ipynb",
+    # TODO: figure out why autogen notebook is not runnable (they are just hanging. possible due to code execution?)
+    "docs/docs/how-tos/autogen-integration.ipynb",
+    # TODO: need to update these notebooks to make sure they are runnable in CI
+    "docs/docs/tutorials/storm/storm.ipynb",  # issues only when running with VCR
+    "docs/docs/tutorials/lats/lats.ipynb",  # issues only when running with VCR
+    "docs/docs/tutorials/rag/langgraph_crag.ipynb",  # flakiness from tavily
+    "docs/docs/tutorials/rag/langgraph_adaptive_rag.ipynb",  # Cannot create a consistent method resolution error from VCR
+    "docs/docs/how-tos/map-reduce.ipynb"  # flakiness from structured output, only when running with VCR
+]
+
 
 def comment_install_cells(notebook: nbformat.NotebookNode) -> nbformat.NotebookNode:
     for cell in notebook.cells:
@@ -40,6 +70,17 @@ def is_comment(code: str) -> bool:
     return code.strip().startswith("#")
 
 
+def has_blocklisted_command(code: str, metadata: dict) -> bool:
+    if 'hide_from_vcr' in metadata:
+        return True
+    
+    code = code.strip()
+    for blocklisted_pattern in BLOCKLIST_COMMANDS:
+        if blocklisted_pattern in code:
+            return True
+    return False
+
+
 def add_vcr_to_notebook(
     notebook: nbformat.NotebookNode, cassette_prefix: str
 ) -> nbformat.NotebookNode:
@@ -70,18 +111,46 @@ def add_vcr_to_notebook(
         if all(is_comment(line) or not line.strip() for line in lines):
             continue
 
+        if has_blocklisted_command(cell.source, cell.metadata):
+            continue
+
         cell_id = cell.get("id", idx)
-        cassette_name = f"{cassette_prefix}_{cell_id}.yaml"
-        cell.source = f"with vcr.use_cassette('{cassette_name}', filter_headers=['x-api-key', 'authorization'], record_mode='once'):\n" + "\n".join(
+        cassette_name = f"{cassette_prefix}_{cell_id}.msgpack.zlib"
+        cell.source = f"with custom_vcr.use_cassette('{cassette_name}', filter_headers=['x-api-key', 'authorization'], record_mode='once', serializer='advanced_compressed'):\n" + "\n".join(
             f"    {line}" for line in lines
         )
 
     # Add import statement
     vcr_import_lines = [
-        "import vcr",
-        # this is needed for ChatAnthropic
         "import nest_asyncio",
         "nest_asyncio.apply()",
+        "import vcr",
+        "import msgpack",
+        "import base64",
+        "import zlib",
+        "import os",
+        "os.environ.pop(\"LANGCHAIN_TRACING_V2\", None)",
+        "custom_vcr = vcr.VCR()",
+        "",
+        "def compress_data(data, compression_level=9):",
+        "    packed = msgpack.packb(data, use_bin_type=True)",
+        "    compressed = zlib.compress(packed, level=compression_level)",
+        "    return base64.b64encode(compressed).decode('utf-8')",
+        "",
+        "def decompress_data(compressed_string):",
+        "    decoded = base64.b64decode(compressed_string)",
+        "    decompressed = zlib.decompress(decoded)",
+        "    return msgpack.unpackb(decompressed, raw=False)",
+        "",
+        "class AdvancedCompressedSerializer:",
+        "    def serialize(self, cassette_dict):",
+        "        return compress_data(cassette_dict)",
+        "",
+        "    def deserialize(self, cassette_string):",
+        "        return decompress_data(cassette_string)",
+        "",
+        "custom_vcr.register_serializer('advanced_compressed', AdvancedCompressedSerializer())",
+        "custom_vcr.serializer = 'advanced_compressed'",
     ]
     import_cell = nbformat.v4.new_code_cell(source="\n".join(vcr_import_lines))
     import_cell.pop("id", None)
@@ -110,10 +179,24 @@ def process_notebooks(should_comment_install_cells: bool) -> None:
                             notebook, cassette_prefix=cassette_prefix
                         )
 
+                    if notebook_path in NOTEBOOKS_NO_EXECUTION:
+                        # Add a cell at the beginning to indicate that this notebook should not be executed
+                        warning_cell = nbformat.v4.new_markdown_cell(
+                            source="**Warning:** This notebook is not meant to be executed automatically."
+                        )
+                        notebook.cells.insert(0, warning_cell)
+
+                        # Add a special tag to the first code cell
+                        if notebook.cells and notebook.cells[1].cell_type == "code":
+                            notebook.cells[1].metadata["tags"] = notebook.cells[1].metadata.get("tags", []) + ["no_execution"]
+
                     nbformat.write(notebook, notebook_path)
                     logger.info(f"Processed: {notebook_path}")
                 except Exception as e:
                     logger.error(f"Error processing {notebook_path}: {e}")
+    
+    with open(os.path.join(DOCS_PATH, "notebooks_no_execution.json"), "w") as f:
+        json.dump(NOTEBOOKS_NO_EXECUTION, f)
 
 
 @click.command()

docs/cassettes/LLMCompiler_15dd9639-691f-4906-9012-83fd6e9ac126.msgpack.zlib

@@ -0,0 +1 @@
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

docs/cassettes/LLMCompiler_31854dfd-b82f-4c24-9b58-6bae66777909.msgpack.zlib

@@ -0,0 +1 @@
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

docs/cassettes/LLMCompiler_730490c6-6e3a-4173-82a1-9eb9d5eeff20.msgpack.zlib

@@ -0,0 +1 @@
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docs/cassettes/LLMCompiler_942dab42-ad42-4ba2-90d5-49edbe4fae68.msgpack.zlib

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docs/cassettes/add-summary-conversation-history_048805a4-3d97-4e76-ac45-8d80d4364c46.msgpack.zlib

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docs/cassettes/add-summary-conversation-history_048805a4-3d97-4e76-ac45-8d80d4364c46.yaml

@@ -1,190 +0,0 @@
-interactions:
-- request:
-    body: '{"max_tokens": 1024, "messages": [{"role": "user", "content": "hi! I''m
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docs/cassettes/async_4b369a6f.yaml

@@ -1,223 +0,0 @@
-interactions:
-- request:
-    body: null
-    headers:
-      Accept:
-      - '*/*'
-      Accept-Encoding:
-      - gzip, deflate
-      Connection:
-      - keep-alive
-      User-Agent:
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-    method: GET
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-  response:
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docs/cassettes/branching_66f52a20.yaml

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docs/cassettes/branching_83320227-8ab3-44c0-b6cf-064a7a425b9f.yaml

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docs/cassettes/branching_932c497e.yaml

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docs/cassettes/breakpoints_9b53f191-1e86-4881-a667-d46a3d66958b.yaml

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