diff --git a/docs/docs/how-tos/async.ipynb b/docs/docs/how-tos/async.ipynb index ba6c55ce1..9f186b419 100644 --- a/docs/docs/how-tos/async.ipynb +++ b/docs/docs/how-tos/async.ipynb @@ -18,8 +18,8 @@ " \n", " \n", "
  • \n", - " \n", - " LangGraph Concepts\n", + " \n", + " LangGraph Glossary\n", " \n", "
    • \n", "
  • \n", diff --git a/docs/docs/how-tos/branching.ipynb b/docs/docs/how-tos/branching.ipynb index 10c23f1e2..6f05c824f 100644 --- a/docs/docs/how-tos/branching.ipynb +++ b/docs/docs/how-tos/branching.ipynb @@ -18,15 +18,24 @@ " This guide assumes familiarity with the following:\n", " \n", "

    \n", " \n", "\n", - "\n", "Parallel execution of nodes is essential to speed up overall graph operation. LangGraph offers native support for parallel execution of nodes, which can significantly enhance the performance of graph-based workflows. This parallelization is achieved through fan-out and fan-in mechanisms, utilizing both standard edges and [conditional_edges](https://langchain-ai.github.io/langgraph/reference/graphs/#langgraph.graph.MessageGraph.add_conditional_edges). Below are some examples showing how to add create branching dataflows that work for you. \n", "\n", "![Screenshot 2024-07-09 at 2.55.56 PM.png](attachment:51f122de-b2ce-4c21-a5a7-c3be70c28a91.png)" diff --git a/docs/docs/how-tos/pass_private_state.ipynb b/docs/docs/how-tos/pass_private_state.ipynb index b1818ebbc..1e3541527 100644 --- a/docs/docs/how-tos/pass_private_state.ipynb +++ b/docs/docs/how-tos/pass_private_state.ipynb @@ -151,14 +151,6 @@ "print()\n", "print(f\"Output of graph invocation: {response}\")" ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "4ce80b5c-73cc-4f78-9d14-26c4ba46f478", - "metadata": {}, - "outputs": [], - "source": [] } ], "metadata": { diff --git a/docs/docs/how-tos/persistence_mongodb.ipynb b/docs/docs/how-tos/persistence_mongodb.ipynb index e03bddecc..31e3b8bd7 100644 --- a/docs/docs/how-tos/persistence_mongodb.ipynb +++ b/docs/docs/how-tos/persistence_mongodb.ipynb @@ -30,9 +30,16 @@ "\n", "This reference implementation shows how to use MongoDB as the backend for persisting checkpoint state. Make sure that you have MongoDB running on port `27017` for going through this guide.\n", "\n", - "NOTE: this is just an reference implementation. You can implement your own checkpointer using a different database or modify this one as long as it conforms to the `BaseCheckpointSaver` interface.\n", + "
    \n", + "

    Note

    \n", + "

    \n", + " This is a **reference** implementation. You can implement your own checkpointer using a different database or modify this one as long as it conforms to the BaseCheckpointSaver interface.\n", + "

    \n", + "
    \n", "\n", "For demonstration purposes we add persistence to the [pre-built create react agent](https://langchain-ai.github.io/langgraph/reference/prebuilt/#langgraph.prebuilt.chat_agent_executor.create_react_agent), but you can add a checkpointer to any custom graph that you build.\n", + "\n", + "## TLDR\n", " \n", "```python\n", "from langgraph.graph import StateGraph\n", diff --git a/docs/docs/how-tos/persistence_redis.ipynb b/docs/docs/how-tos/persistence_redis.ipynb index 917d8e2f7..97d06c8c9 100644 --- a/docs/docs/how-tos/persistence_redis.ipynb +++ b/docs/docs/how-tos/persistence_redis.ipynb @@ -16,7 +16,7 @@ " \n", " Persistence\n", " \n", - "
    • \n", + " \n", "
  • \n", " \n", " Redis\n", @@ -30,8 +30,12 @@ "\n", "This reference implementation shows how to use Redis as the backend for persisting checkpoint state. Make sure that you have Redis running on port `6379` for going through this guide.\n", "\n", - "NOTE: this is just an reference implementation. You can implement your own checkpointer using a different database or modify this one as long as it conforms to the `BaseCheckpointSaver` interface.\n", - "\n", + "
    \n", + "

    Note

    \n", + "

    \n", + " This is a **reference** implementation. You can implement your own checkpointer using a different database or modify this one as long as it conforms to the BaseCheckpointSaver interface.\n", + "

    \n", + "
    \n", "\n", "For demonstration purposes we add persistence to the [pre-built create react agent](https://langchain-ai.github.io/langgraph/reference/prebuilt/#langgraph.prebuilt.chat_agent_executor.create_react_agent), but you can add a checkpointer to any custom graph that you build.\n", "\n", @@ -41,7 +45,7 @@ "\n", "builder = StateGraph(....)\n", "# ... define the graph\n", - "checkpointer = # mongodb checkpointer (see examples below)\n", + "checkpointer = # redis checkpointer (see examples below)\n", "graph = builder.compile(checkpointer=checkpointer)\n", "...\n", "```" @@ -1037,7 +1041,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.11.9" + "version": "3.11.4" } }, "nbformat": 4, diff --git a/docs/docs/how-tos/state-model.ipynb b/docs/docs/how-tos/state-model.ipynb index 091546b9e..e21c8b993 100644 --- a/docs/docs/how-tos/state-model.ipynb +++ b/docs/docs/how-tos/state-model.ipynb @@ -25,7 +25,7 @@ "
  • \n", " \n", " Pydantic\n", - " -- this is a very popular Python library for run time validation.\n", + " : this is a popular Python library for run time validation.\n", "
    • \n", " \n", "

    \n", @@ -41,10 +41,20 @@ "
    \n", "

    Known Limitations

    \n", "

    \n", - " * This notebook uses Pydantic v2 BaseModel, which requires langchain-core >= 0.3. Using langchain-core < 0.3 will result in errors due to mixing of Pydantic v1 and v2 BaseModels.\n", - " * Currently, the `output` of the graph will **NOT** be an instance of a pydantic model.\n", - " * Run-time validation only occurs on **inputs** into nodes, not on the outputs.\n", - " * The validation error trace from pydantic does not show which node the error arises in.\n", + "

    \n", "

    \n", "
    " ]