official-docs-index.md

Official Docs Index (LangGraph)

Use this file as a router. Open only the section needed for the current task.

1) Quick Start and Overview

• LangGraph overview: https://docs.langchain.com/oss/python/langgraph/overview
• LangGraph GitHub repository: https://github.com/langchain-ai/langgraph
• LangGraph tutorial: https://langchain-ai.github.io/langgraph/tutorials/introduction/

Load this section when you need basic understanding, installation instructions, and first LangGraph example.

2) Core Concepts

• StateGraph: https://langchain-ai.github.io/langgraph/concepts/low_level/#stategraph
• State management: https://langchain-ai.github.io/langgraph/concepts/low_level/#state
• Nodes and edges: https://langchain-ai.github.io/langgraph/concepts/low_level/#nodes
• Conditional edges: https://langchain-ai.github.io/langgraph/concepts/low_level/#conditional-edges

Load this section when learning core LangGraph concepts: graphs, state, nodes, and routing.

3) Built-in Components

• Prebuilt components: https://langchain-ai.github.io/langgraph/reference/prebuilt/
• ToolNode: https://langchain-ai.github.io/langgraph/reference/prebuilt/#toolnode
• create_react_agent: https://langchain-ai.github.io/langgraph/reference/prebuilt/#create_react_agent
• AgentExecutor: https://langchain-ai.github.io/langgraph/reference/prebuilt/#agentexecutor

Load this section when using pre-built components for rapid agent development.

4) Memory and Persistence

• Checkpointing: https://langchain-ai.github.io/langgraph/concepts/persistence/
• MemorySaver: https://langchain-ai.github.io/langgraph/reference/checks/#memorysaver
• Postgres checkpointer: https://langchain-ai.github.io/langgraph/reference/checks/#postgrescheckpointer
• Long-term memory: https://langchain-ai.github.io/langgraph/concepts/persistence/#long-term-memory

Load this section when implementing stateful agents with conversation memory and persistence.

5) Human-in-the-Loop

• Interrupts overview: https://langchain-ai.github.io/langgraph/how-tos/human_in_the_loop/
• Interrupt before/after: https://langchain-ai.github.io/langgraph/how-tos/human_in_the_loop/#interrupt-the-graph
• Approval workflows: https://langchain-ai.github.io/langgraph/how-tos/human_in_the_loop/#approve-or-reject

Load this section when implementing human approval, review workflows, or interactive agents.

6) Streaming

• Streaming overview: https://langchain-ai.github.io/langgraph/how-tos/streaming/
• Stream tokens: https://langchain-ai.github.io/langgraph/how-tos/streaming/#stream-tokens-from-llms
• Stream events: https://langchain-ai.github.io/langgraph/how-tos/streaming/#stream-events-from-nodes
• Stream updates: https://langchain-ai.github.io/langgraph/how-tos/streaming/#stream-updates

Load this section when implementing real-time streaming, progress updates, or token-by-token output.

7) Multi-Agent Systems

• Multi-agent overview: https://langchain-ai.github.io/langgraph/how-tos/multi_agent/
• Agent hierarchies: https://langchain-ai.github.io/langgraph/how-tos/multi_agent/#hierarchical-multi-agent
• Subgraphs: https://langchain-ai.github.io/langgraph/how-tos/subgraph/
• Handoff patterns: https://langchain-ai.github.io/langgraph/how-tos/multi_agent/#multi-agent-handoff

Load this section when building multi-agent systems, hierarchical agents, or agent coordination patterns.

8) Tools and Integrations

• LangChain tools: https://python.langchain.com/docs/concepts/#tools
• Tool calling: https://python.langchain.com/docs/concepts/tool_calling/
• Custom tools: https://python.langchain.com/docs/how_to/custom_tools/
• Structured tools: https://python.langchain.com/docs/how_to/structured_tools/

Load this section when implementing tools, tool-calling agents, or external API integrations.

9) Deployment and Production

• LangGraph deployment: https://langchain-ai.github.io/langgraph/concepts/deployment/
• LangGraph Cloud: https://langchain-ai.github.io/langgraph/cloud-reference/
• LangGraph CLI: https://langchain-ai.github.io/langgraph/concepts/deployment/#cli
• Self-hosted deployment: https://langchain-ai.github.io/langgraph/how-tos/deploy_self_hosted/

Load this section when deploying agents to production or setting up LangGraph Cloud/CLI.

10) Debugging and Observability

• LangSmith integration: https://langchain-ai.github.io/langgraph/how-tos/debug_with_langsmith/
• Tracing: https://langchain-ai.github.io/langgraph/how-tos/debug_with_langsmith/#trace-visualizations
• Visualization: https://langchain-ai.github.io/langgraph/how-tos/debug_with_langsmith/#graph-visualization
• Error handling: https://langchain-ai.github.io/langgraph/how-tos/error_handling/

Load this section when debugging agents, visualizing graphs, or integrating with LangSmith for observability.

11) Advanced Patterns

• Routing patterns: https://langchain-ai.github.io/langgraph/how-tos/routing/
• Dynamic branching: https://langchain-ai.github.io/langgraph/how-tos/routing/#dynamic-routing
• Parallel execution: https://langchain-ai.github.io/langgraph/how-tos/parallel_execution/
• State reducers: https://langchain-ai.github.io/langgraph/concepts/low_level/#state-reducers

Load this section when implementing complex routing, parallel workflows, or custom state management.

12) Reference API

• Graph API: https://langchain-ai.github.io/langgraph/reference/graphs/
• StateGraph API: https://langchain-ai.github.io/langgraph/reference/graphs/#stategraph
• MessageGraph API: https://langchain-ai.github.io/langgraph/reference/graphs/#messagegraph
• Checkpointer API: https://langchain-ai.github.io/langgraph/reference/checks/

Load this section for detailed API reference, method signatures, and advanced configuration options.