feat(cli): add detection for bun.lockb (#3111)

- both issues are related to the fact that waiters for futures are
notified of completion before "done" callbacks are called
- 1st issue manifested as interrupt stream event being emitted before
the result of a task that logically finished first (it's in the line
above in body of the entrypoint function) -> this is solved by always
returning to use code a fresh future chained on the original future,
because chaining is done via done callbacks (therefore the chained
future will only resolve after done callbacks of the original feature
are called)
- 2nd issue mainfested as sometimes (very rarely) the last stream event
not being printed before stream() finishes. this is solved by ensuring
we only return out of PregelRunner.tick() once all "done" callbacks are
called, previously we were approximating this through use of
asyncio.sleep(0) / time.sleep(0). The new solution instead waits on a
threading/asyncio.Event which will only be set by the last "done"
callback to fire
- this PR also disables incomplete support for calling sync tasks from
async entrypoints

.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/workflows/_lint.yml

@@ -42,7 +42,6 @@ jobs:
         with:
           python-version: ${{ matrix.python-version }}
           poetry-version: ${{ env.POETRY_VERSION }}
-          working-directory: ${{ inputs.working-directory }}
           cache-key: lint-${{ inputs.working-directory }}
 
       - name: Check Poetry File

.github/workflows/_test.yml

@@ -31,7 +31,6 @@ jobs:
         with:
           python-version: ${{ matrix.python-version }}
           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

.github/workflows/_test_langgraph.yml

@@ -17,21 +17,11 @@ jobs:
           - "3.11"
           - "3.12"
           - "3.13"
-        core-version:
-          - "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 }}, ff-send-v2: ${{ matrix.ff-send-v2 }})"
+    name: "test #${{ matrix.python-version }}"
     steps:
       - uses: actions/checkout@v4
       - name: Set up Python ${{ matrix.python-version }} + Poetry ${{ env.POETRY_VERSION }}
@@ -51,16 +41,11 @@ jobs:
         shell: bash
         run: |
           poetry install --with dev
-          if [ "${{ matrix.core-version }}" != "latest" ]; then
-            poetry run pip install "langchain-core${{ matrix.core-version }}"
-          fi
 
       - 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

@@ -29,7 +29,6 @@ jobs:
         with:
           python-version: ${{ env.PYTHON_VERSION }}
           poetry-version: ${{ env.POETRY_VERSION }}
-          working-directory: ${{ inputs.working-directory }}
           cache-key: release
 
       # We want to keep this build stage *separate* from the release stage,

.github/workflows/ci.yml

@@ -31,7 +31,6 @@ jobs:
             "libs/cli",
             "libs/checkpoint",
             "libs/checkpoint-sqlite",
-            "libs/checkpoint-duckdb",
             "libs/checkpoint-postgres",
             "libs/scheduler-kafka",
           ]
@@ -44,12 +43,12 @@ jobs:
     name: cd ${{ matrix.working-directory }}
     strategy:
       matrix:
-        working-directory: [
+        working-directory:
+          [
             "libs/cli",
             "libs/checkpoint",
             "libs/checkpoint-sqlite",
-            "libs/checkpoint-duckdb",
-            "libs/checkpoint-postgres"
+            "libs/checkpoint-postgres",
           ]
     uses: ./.github/workflows/_test.yml
     with:
@@ -76,7 +75,7 @@ jobs:
       - name: Set up Python
         uses: actions/setup-python@v5
         with:
-          python-version: '3.11'
+          python-version: "3.11"
       - name: Run check_sdk_methods script
         run: python .github/scripts/check_sdk_methods.py
 
@@ -109,9 +108,40 @@ jobs:
       - name: Build
         run: yarn build
 
+  test-js:
+    runs-on: ubuntu-latest
+    strategy:
+      matrix:
+        working-directory:
+          - "libs/sdk-js"
+    defaults:
+      run:
+        working-directory: ${{ matrix.working-directory }}
+    steps:
+      - uses: actions/checkout@v3
+      - name: Setup Node.js (LTS)
+        uses: actions/setup-node@v3
+        with:
+          node-version: "20"
+          cache: "yarn"
+          cache-dependency-path: ${{ matrix.working-directory }}/yarn.lock
+      - name: Install dependencies
+        run: yarn install
+      - name: Run tests
+        run: yarn test
+
   ci_success:
     name: "CI Success"
-    needs: [lint, lint-js, test, test-langgraph, test-scheduler-kafka, integration-test]
+    needs:
+      [
+        lint,
+        lint-js,
+        test,
+        test-langgraph,
+        test-scheduler-kafka,
+        integration-test,
+        test-js,
+      ]
     if: |
       always()
     runs-on: ubuntu-latest

.github/workflows/deploy_docs.yml

@@ -86,9 +86,12 @@ jobs:
             echo "Running link check on all HTML files matching notebooks in docs directory..."
             poetry run pytest -v \
               --check-links-ignore "https://(api|web|docs)\.smith\.langchain\.com/.*" \
+              --check-links-ignore "https://academy\.langchain\.com/.*" \
               --check-links-ignore "https://x.com/.*" \
               --check-links-ignore "https://github\.com/.*" \
               --check-links-ignore "http://localhost:8123/.*" \
+              --check-links-ignore "http://localhost:2024.*" \
+              --check-links-ignore "http://127.0.0.1:.*" \
               --check-links-ignore "/.*\.(ipynb|html)$" \
               --check-links-ignore "https://python\.langchain\.com/.*" \
               --check-links-ignore "https://openai\.com/.*" \
@@ -105,7 +108,10 @@ jobs:
               echo "Running link check on HTML files matching changed notebook files..."
               poetry run pytest -v \
                 --check-links-ignore "https://(api|web|docs)\.smith\.langchain\.com/.*" \
+                --check-links-ignore "https://academy\.langchain\.com/.*" \
                 --check-links-ignore "http://localhost:8123/.*" \
+                --check-links-ignore "http://localhost:2024.*" \
+                --check-links-ignore "http://127.0.0.1:.*" \
                 --check-links-ignore "https://x.com/.*" \
                 --check-links-ignore "https://github\.com/.*" \
                 --check-links-ignore "/.*\.(ipynb|html)$" \

.github/workflows/release.yml

@@ -31,7 +31,6 @@ jobs:
         with:
           python-version: ${{ env.PYTHON_VERSION }}
           poetry-version: ${{ env.POETRY_VERSION }}
-          working-directory: ${{ inputs.working-directory }}
           cache-key: release
 
       # We want to keep this build stage *separate* from the release stage,
@@ -169,7 +168,6 @@ jobs:
         with:
           python-version: ${{ env.PYTHON_VERSION }}
           poetry-version: ${{ env.POETRY_VERSION }}
-          working-directory: ${{ inputs.working-directory }}
 
       - name: Import published package
         shell: bash
@@ -256,7 +254,6 @@ jobs:
         with:
           python-version: ${{ env.PYTHON_VERSION }}
           poetry-version: ${{ env.POETRY_VERSION }}
-          working-directory: ${{ inputs.working-directory }}
           cache-key: release
 
       - uses: actions/download-artifact@v4
@@ -298,7 +295,6 @@ jobs:
         with:
           python-version: ${{ env.PYTHON_VERSION }}
           poetry-version: ${{ env.POETRY_VERSION }}
-          working-directory: ${{ inputs.working-directory }}
           cache-key: release
 
       - uses: actions/download-artifact@v4

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

@@ -13,7 +13,7 @@ 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 -w ./libs/sdk-py --dirty
 
 clean-docs:
 	find ./docs/docs -name "*.ipynb" -type f -delete

README.md

@@ -8,7 +8,7 @@
 ⚡ Building language agents as graphs ⚡
 
 > [!NOTE]
-> Looking for the JS version? Click [here](https://github.com/langchain-ai/langgraphjs) ([JS docs](https://langchain-ai.github.io/langgraphjs/)).
+> Looking for the JS version? See the [JS repo](https://github.com/langchain-ai/langgraphjs) and the [JS docs](https://langchain-ai.github.io/langgraphjs/).
 
 ## Overview
 
@@ -47,9 +47,7 @@ pip install -U langgraph
 
 ## Example
 
-One of the central concepts of LangGraph is state. Each graph execution creates a state that is passed between nodes in the graph as they execute, and each node updates this internal state with its return value after it executes. The way that the graph updates its internal state is defined by either the type of graph chosen or a custom function.
-
-Let's take a look at a simple example of an agent that can use a search tool.
+Let's build a tool-calling [ReAct-style](https://langchain-ai.github.io/langgraph/concepts/agentic_concepts/#react-implementation) agent that uses a search tool!
 
 ```shell
 pip install langchain-anthropic
@@ -66,10 +64,58 @@ export LANGSMITH_TRACING=true
 export LANGSMITH_API_KEY=lsv2_sk_...
 ```
 
-```python
-from typing import Annotated, Literal, TypedDict
+The simplest way to create a tool-calling agent in LangGraph is to use `create_react_agent`:
+
+<details open>
+  <summary>High-level implementation</summary>
+
+```python
+from langgraph.prebuilt import create_react_agent
+from langgraph.checkpoint.memory import MemorySaver
+from langchain_anthropic import ChatAnthropic
+from langchain_core.tools import tool
+
+# Define the tools for the agent to use
+@tool
+def search(query: str):
+    """Call to surf the web."""
+    # This is a placeholder, but don't tell the LLM that...
+    if "sf" in query.lower() or "san francisco" in query.lower():
+        return "It's 60 degrees and foggy."
+    return "It's 90 degrees and sunny."
+
+
+tools = [search]
+model = ChatAnthropic(model="claude-3-5-sonnet-latest", temperature=0)
+
+# Initialize memory to persist state between graph runs
+checkpointer = MemorySaver()
+
+app = create_react_agent(model, tools, checkpointer=checkpointer)
+
+# Use the agent
+final_state = app.invoke(
+    {"messages": [{"role": "user", "content": "what is the weather in sf"}]},
+    config={"configurable": {"thread_id": 42}}
+)
+final_state["messages"][-1].content
+```
+```
+"Based on the search results, I can tell you that the current weather in San Francisco is:\n\nTemperature: 60 degrees Fahrenheit\nConditions: Foggy\n\nSan Francisco is known for its microclimates and frequent fog, especially during the summer months. The temperature of 60°F (about 15.5°C) is quite typical for the city, which tends to have mild temperatures year-round. The fog, often referred to as "Karl the Fog" by locals, is a characteristic feature of San Francisco\'s weather, particularly in the mornings and evenings.\n\nIs there anything else you\'d like to know about the weather in San Francisco or any other location?"
+```
+</details>
+
+> [!TIP]
+> LangGraph is a **low-level** framework that allows you to implement any custom agent
+architectures. Click on the low-level implementation below to see how to implement a
+tool-calling agent from scratch.
+
+<details>
+<summary>Low-level implementation</summary>
+
+```python
+from typing import Literal
 
-from langchain_core.messages import HumanMessage
 from langchain_anthropic import ChatAnthropic
 from langchain_core.tools import tool
 from langgraph.checkpoint.memory import MemorySaver
@@ -91,7 +137,7 @@ tools = [search]
 
 tool_node = ToolNode(tools)
 
-model = ChatAnthropic(model="claude-3-5-sonnet-20240620", temperature=0).bind_tools(tools)
+model = ChatAnthropic(model="claude-3-5-sonnet-latest", temperature=0).bind_tools(tools)
 
 # Define the function that determines whether to continue or not
 def should_continue(state: MessagesState) -> Literal["tools", END]:
@@ -145,23 +191,20 @@ checkpointer = MemorySaver()
 # Note that we're (optionally) passing the memory when compiling the graph
 app = workflow.compile(checkpointer=checkpointer)
 
-# Use the Runnable
+# Use the agent
 final_state = app.invoke(
-    {"messages": [HumanMessage(content="what is the weather in sf")]},
+    {"messages": [{"role": "user", "content": "what is the weather in sf"}]},
     config={"configurable": {"thread_id": 42}}
 )
 final_state["messages"][-1].content
 ```
-
-```
-"Based on the search results, I can tell you that the current weather in San Francisco is:\n\nTemperature: 60 degrees Fahrenheit\nConditions: Foggy\n\nSan Francisco is known for its microclimates and frequent fog, especially during the summer months. The temperature of 60°F (about 15.5°C) is quite typical for the city, which tends to have mild temperatures year-round. The fog, often referred to as "Karl the Fog" by locals, is a characteristic feature of San Francisco\'s weather, particularly in the mornings and evenings.\n\nIs there anything else you\'d like to know about the weather in San Francisco or any other location?"
-```
+</details>
 
 Now when we pass the same `"thread_id"`, the conversation context is retained via the saved state (i.e. stored list of messages)
 
 ```python
 final_state = app.invoke(
-    {"messages": [HumanMessage(content="what about ny")]},
+    {"messages": [{"role": "user", "content": "what about ny"}]},
     config={"configurable": {"thread_id": 42}}
 )
 final_state["messages"][-1].content

docs/_scripts/_patch.py

@@ -0,0 +1,93 @@
+import functools
+
+from urllib3 import __version__ as urllib3version  # type: ignore[import-untyped]
+from urllib3 import connection  # type: ignore[import-untyped]
+
+
+def _ensure_str(s, encoding="utf-8", errors="strict") -> str:
+    if isinstance(s, str):
+        return s
+
+    if isinstance(s, bytes):
+        return s.decode(encoding, errors)
+    return str(s)
+
+
+# Copied from https://github.com/urllib3/urllib3/blob/1c994dfc8c5d5ecaee8ed3eb585d4785f5febf6e/src/urllib3/connection.py#L231
+def request(self, method, url, body=None, headers=None):
+    """Make the request.
+
+    This function is based on the urllib3 request method, with modifications
+    to handle potential issues when using vcrpy in concurrent workloads.
+
+    Args:
+        self: The HTTPConnection instance.
+        method (str): The HTTP method (e.g., 'GET', 'POST').
+        url (str): The URL for the request.
+        body (Optional[Any]): The body of the request.
+        headers (Optional[dict]): Headers to send with the request.
+
+    Returns:
+        The result of calling the parent request method.
+    """
+    # Update the inner socket's timeout value to send the request.
+    # This only triggers if the connection is re-used.
+    if getattr(self, "sock", None) is not None:
+        self.sock.settimeout(self.timeout)
+
+    if headers is None:
+        headers = {}
+    else:
+        # Avoid modifying the headers passed into .request()
+        headers = headers.copy()
+    if "user-agent" not in (_ensure_str(k.lower()) for k in headers):
+        headers["User-Agent"] = connection._get_default_user_agent()
+    # The above is all the same ^^^
+    # The following is different:
+    return self._parent_request(method, url, body=body, headers=headers)
+
+
+_PATCHED = False
+
+
+def patch_urllib3():
+    """Patch the request method of urllib3 to avoid type errors when using vcrpy.
+
+    In concurrent workloads (such as the tracing background queue), the
+    connection pool can get in a state where an HTTPConnection is created
+    before vcrpy patches the HTTPConnection class. In urllib3 >= 2.0 this isn't
+    a problem since they use the proper super().request(...) syntax, but in older
+    versions, super(HTTPConnection, self).request is used, resulting in a TypeError
+    since self is no longer a subclass of "HTTPConnection" (which at this point
+    is vcr.stubs.VCRConnection).
+
+    This method patches the class to fix the super() syntax to avoid mixed inheritance.
+    In the case of the LangSmith tracing logic, it doesn't really matter since we always
+    exclude cache checks for calls to LangSmith.
+
+    The patch is only applied for urllib3 versions older than 2.0.
+    """
+    global _PATCHED
+    if _PATCHED:
+        return
+    from packaging import version
+
+    if version.parse(urllib3version) >= version.parse("2.0"):
+        _PATCHED = True
+        return
+
+    # Lookup the parent class and its request method
+    parent_class = connection.HTTPConnection.__bases__[0]
+    parent_request = parent_class.request
+
+    def new_request(self, *args, **kwargs):
+        """Handle parent request.
+
+        This method binds the parent's request method to self and then
+        calls our modified request function.
+        """
+        self._parent_request = functools.partial(parent_request, self)
+        return request(self, *args, **kwargs)
+
+    connection.HTTPConnection.request = new_request
+    _PATCHED = True

docs/_scripts/generate_api_reference_links.py

@@ -6,6 +6,9 @@ import re
 from typing import List, Literal, Optional
 from typing_extensions import TypedDict
 
+
+from functools import lru_cache
+
 import nbformat
 from nbconvert.preprocessors import Preprocessor
 
@@ -47,6 +50,8 @@ MANUAL_API_REFERENCES_LANGGRAPH = [
     (["langgraph.graph"], "langgraph.constants", "END", "constants"),
     (["langgraph.constants"], "langgraph.types", "Send", "types"),
     (["langgraph.constants"], "langgraph.types", "Interrupt", "types"),
+    (["langgraph.constants"], "langgraph.types", "interrupt", "types"),
+    (["langgraph.constants"], "langgraph.types", "Command", "types"),
     ([], "langgraph.types", "RetryPolicy", "types"),
     ([], "langgraph.checkpoint.base", "Checkpoint", "checkpoints"),
     ([], "langgraph.checkpoint.base", "CheckpointMetadata", "checkpoints"),
@@ -83,8 +88,11 @@ _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"""
+
+
+@lru_cache(maxsize=10_000)
+def _get_full_module_name(module_path: str, class_name: str) -> Optional[str]:
+    """Get full module name using inspect, with LRU cache to memoize results."""
     try:
         module = importlib.import_module(module_path)
         class_ = getattr(module, class_name)
@@ -95,13 +103,12 @@ def _get_full_module_name(module_path, class_name) -> Optional[str]:
             return module_path
         return module.__name__
     except AttributeError as e:
-        logger.warning(f"Could not find module for {class_name}, {e}")
+        logger.warning(f"API Reference: 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}")
+        logger.warning(f"API Reference: 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]
@@ -115,10 +122,10 @@ def _get_doc_title(data: str, file_name: str) -> str:
 
 
 class ImportInformation(TypedDict):
-    imported: str  # imported class name
-    source: str  # module path
-    docs: str  # URL to the documentation
-    title: str  # Title of the document
+    imported: str  # The name of the class that was imported.
+    source: str  # The full module path from which the class was imported.
+    docs: str  # The URL pointing to the class's documentation.
+    title: str  # The title of the document where the import is used.
 
 
 def _get_imports(
@@ -211,36 +218,73 @@ def _get_imports(
     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 get_imports(code: str, doc_title: str) -> List[ImportInformation]:
+    """Retrieve all import references from the given code for specified ecosystems.
 
-    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)
+    Args:
+        code: The source code from which to extract import references.
+        doc_title: The documentation title associated with the code.
 
-        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
+    Returns:
+        A list of import information for each import found.
+    """
+    ecosystems = ["langchain", "langgraph"]
+    all_imports = []
+    for package_ecosystem in ecosystems:
+        all_imports.extend(_get_imports(code, doc_title, package_ecosystem))
+    return all_imports
 
-                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
+
+def update_markdown_with_imports(markdown: str) -> str:
+    """Update markdown to include API reference links for imports in Python code blocks.
+
+    This function scans the markdown content for Python code blocks, extracts any imports, and appends links to their API documentation.
+
+    Args:
+        markdown: The markdown content to process.
+
+    Returns:
+        Updated markdown with API reference links appended to Python code blocks.
+
+    Example:
+        Given a markdown with a Python code block:
+
+        ```python
+        from langchain.nlp import TextGenerator
+        ```
+        This function will append an API reference link to the `TextGenerator` class from the `langchain.nlp` module if it's recognized.
+    """
+    code_block_pattern = re.compile(
+        r'(?P<indent>[ \t]*)```(?P<language>python|py)\n(?P<code>.*?)\n(?P=indent)```', re.DOTALL
+    )
+
+    def replace_code_block(match: re.Match) -> str:
+        """Replace the matched code block with additional API reference links if imports are found.
+
+        Args:
+            match (re.Match): The regex match object containing the code block.
+
+        Returns:
+            str: The modified code block with API reference links appended if applicable.
+        """
+        indent = match.group('indent')
+        code_block = match.group('code')
+        language = match.group('language')  # Preserve the language from the regex match
+        # Retrieve import information from the code block
+        imports = get_imports(code_block, "__unused__")
+
+        original_code_block = match.group(0)
+        # If no imports are found, return the original code block
+        if not imports:
+            return original_code_block
+
+        # Generate API reference links for each import
+        api_links = ' | '.join(
+            f'<a href="{imp["docs"]}">{imp["imported"]}</a>' for imp in imports
+        )
+        # Return the code block with appended API reference links
+        return f'{original_code_block}\n\n{indent}API Reference: {api_links}'
+
+    # Apply the replace_code_block function to all matches in the markdown
+    updated_markdown = code_block_pattern.sub(replace_code_block, markdown)
+    return updated_markdown

docs/_scripts/notebook_convert.py

@@ -6,8 +6,6 @@ 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):
@@ -107,7 +105,6 @@ exporter = MarkdownExporter(
     preprocessors=[
         EscapePreprocessor,
         ExtractAttachmentsPreprocessor,
-        ImportPreprocessor,
     ],
     template_name="mdoutput",
     extra_template_basedirs=[

docs/_scripts/notebook_hooks.py

@@ -1,13 +1,18 @@
 import logging
+import os
+import re
 from typing import Any, Dict
 
-from mkdocs.structure.pages import Page
 from mkdocs.structure.files import Files, File
+from mkdocs.structure.pages import Page
+
 from notebook_convert import convert_notebook
+from generate_api_reference_links import update_markdown_with_imports
 
 logger = logging.getLogger(__name__)
 logging.basicConfig()
 logger.setLevel(logging.INFO)
+DISABLED = os.getenv("DISABLE_NOTEBOOK_CONVERT") in ("1", "true", "True")
 
 
 class NotebookFile(File):
@@ -16,6 +21,8 @@ class NotebookFile(File):
 
 
 def on_files(files: Files, **kwargs: Dict[str, Any]):
+    if DISABLED:
+        return files
     new_files = Files([])
     for file in files:
         if file.src_path.endswith(".ipynb"):
@@ -31,10 +38,83 @@ def on_files(files: Files, **kwargs: Dict[str, Any]):
     return new_files
 
 
+def _highlight_code_blocks(markdown: str) -> str:
+    """Find code blocks with highlight comments and add hl_lines attribute.
+
+    Args:
+        markdown: The markdown content to process.
+
+    Returns:
+        updated Markdown code with code blocks containing highlight comments
+        updated to use the hl_lines attribute.
+    """
+    # Pattern to find code blocks with highlight comments and without
+    # existing hl_lines for Python and JavaScript
+    # Pattern to find code blocks with highlight comments, handling optional indentation
+    code_block_pattern = re.compile(
+        r"(?P<indent>[ \t]*)```(?P<language>py|python|js|javascript)(?!\s+hl_lines=)\n"
+        r"(?P<code>((?:.*\n)*?))"  # Capture the code inside the block using named group
+        r"(?P=indent)```"  # Match closing backticks with the same indentation
+    )
+
+    def replace_highlight_comments(match: re.Match) -> str:
+        indent = match.group("indent")
+        language = match.group("language")
+        code_block = match.group("code")
+        lines = code_block.split("\n")
+        highlighted_lines = []
+
+        # Skip initial empty lines
+        while lines and not lines[0].strip():
+            lines.pop(0)
+
+        lines_to_keep = []
+
+        comment_syntax = (
+            "# highlight-next-line"
+            if language in ["py", "python"]
+            else "// highlight-next-line"
+        )
+
+        for line in lines:
+            if comment_syntax in line:
+                count = len(lines_to_keep) + 1
+                highlighted_lines.append(str(count))
+            else:
+                lines_to_keep.append(line)
+
+        # Reconstruct the new code block
+        new_code_block = "\n".join(lines_to_keep)
+
+        if highlighted_lines:
+            return (
+                f'{indent}```{language} hl_lines="{" ".join(highlighted_lines)}"\n'
+                # The indent and terminating \n is already included in the code block
+                f'{new_code_block}'
+                f'{indent}```'
+            )
+        else:
+            return (
+                f"{indent}```{language}\n"
+                # The indent and terminating \n is already included in the code block
+                f"{new_code_block}"
+                f"{indent}```"
+            )
+
+    # Replace all code blocks in the markdown
+    markdown = code_block_pattern.sub(replace_highlight_comments, markdown)
+    return markdown
+
+
 def on_page_markdown(markdown: str, page: Page, **kwargs: Dict[str, Any]):
+    if DISABLED:
+        return markdown
     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
+        markdown = convert_notebook(page.file.abs_src_path)
 
+    # Append API reference links to code blocks
+    markdown = update_markdown_with_imports(markdown)
+    # Apply highlight comments to code blocks
+    markdown = _highlight_code_blocks(markdown)
     return markdown

docs/_scripts/prepare_notebooks_for_ci.py

@@ -42,8 +42,13 @@ NOTEBOOKS_NO_EXECUTION = [
     "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
+    "docs/docs/tutorials/rag/langgraph_adaptive_rag.ipynb",  # flakiness only when running in GHA 
+    "docs/docs/tutorials/rag/langgraph_self_rag.ipynb",  # flakiness only when running in GHA
+    "docs/docs/tutorials/rag/langgraph_agentic_rag.ipynb",  # flakiness only when running in GHA
+    "docs/docs/how-tos/map-reduce.ipynb",  # flakiness from structured output, only when running with VCR
+    "docs/docs/tutorials/tot/tot.ipynb",
+    "docs/docs/how-tos/visualization.ipynb",
+    "docs/docs/tutorials/llm-compiler/LLMCompiler.ipynb"
 ]
 
 
@@ -86,6 +91,7 @@ def add_vcr_to_notebook(
 ) -> nbformat.NotebookNode:
     """Inject `with vcr.cassette` into each code cell of the notebook."""
 
+    uses_langsmith = False
     # Inject VCR context manager into each code cell
     for idx, cell in enumerate(notebook.cells):
         if cell.cell_type != "code":
@@ -120,8 +126,22 @@ def add_vcr_to_notebook(
             f"    {line}" for line in lines
         )
 
+        if any("hub.pull" in line or "from langsmith import" in line for line in lines):
+            uses_langsmith = True
+
     # Add import statement
-    vcr_import_lines = [
+    vcr_import_lines = []
+    if uses_langsmith:
+        vcr_import_lines.extend([
+            # patch urllib3 to handle vcr errors, see more here:
+            # https://github.com/langchain-ai/langsmith-sdk/blob/main/python/langsmith/_internal/_patch.py
+            "import sys",
+            f"sys.path.insert(0, '{os.path.join(DOCS_PATH, '_scripts')}')",
+            "import _patch as patch_urllib3",
+            "patch_urllib3.patch_urllib3()",
+        ])
+
+    vcr_import_lines.extend([
         "import nest_asyncio",
         "nest_asyncio.apply()",
         "import vcr",
@@ -151,7 +171,8 @@ def add_vcr_to_notebook(
         "",
         "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)
     notebook.cells.insert(0, import_cell)

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

@@ -1 +0,0 @@
-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

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

@@ -1 +0,0 @@
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docs/cassettes/introduction_6b32914d-4d60-491f-8e11-1e6867e38ffd.msgpack.zlib

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docs/cassettes/langgraph_adaptive_rag_4dec9d98-f3dc-4b7f-abc0-9d01c754f2be.msgpack.zlib

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docs/cassettes/langgraph_adaptive_rag_ded99680-437a-4c9d-b860-619c88949d84.msgpack.zlib

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docs/cassettes/langgraph_agentic_rag_278d1d83-dda6-4de4-bf8b-be9965c227fa.msgpack.zlib

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docs/cassettes/langgraph_self_rag_bd62276f-bf26-40d0-8cff-e07b10e00321.msgpack.zlib

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docs/cassettes/langgraph_self_rag_c6f4c70e-1660-4149-82c0-837f19fc9fb5.msgpack.zlib

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docs/cassettes/multi-agent-network_26a0d4df-ff99-40f0-92a8-0b3f2c591040.msgpack.zlib

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docs/cassettes/multi-agent-network_68a547d4-0a15-43bd-aeed-c9ba1dfe388f.msgpack.zlib

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docs/cassettes/pass-config-to-tools_15.msgpack.zlib

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docs/cassettes/pass-config-to-tools_16.msgpack.zlib

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docs/cassettes/pass-config-to-tools_17.msgpack.zlib

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docs/cassettes/pass-config-to-tools_18.msgpack.zlib

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docs/cassettes/persistence_mongodb_2e65b3b2-8e3e-4d96-8db4-4846a3bc2eac.msgpack.zlib

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