Guides¶

The pages in this section provide a conceptual overview and how-tos for the following topics:

LangGraph APIs¶

Graph API: Use the Graph API to define workflows using a graph paradigm.
Functional API: Use Functional API to build workflows using a functional paradigm without thinking about the graph structure.
Runtime: Pregel implements LangGraph's runtime, managing the execution of LangGraph applications.

These capabilities are available in both LangGraph OSS and the LangGraph Platform.

Streaming: Stream outputs from a LangGraph graph.
Persistence: Persist the state of a LangGraph graph.
Durable execution: Save progress at key points in the graph execution.
Memory: Remember information about previous interactions.
Context: Pass outside data to a LangGraph graph to provide context for the graph execution.
Models: Integrate various LLMs into your LangGraph application.
Tools: Interface directly with external systems.
Human-in-the-loop: Enable human intervention at any point in a workflow.
Breakpoints: Pause the execution of a LangGraph graph at a specific point.
Time travel: Travel back in time to a specific point in the execution of a LangGraph graph.
Subgraphs: Build modular graphs.
Multi-agent: Break down a complex workflow into multiple agents.
MCP: Use MCP servers in a LangGraph graph.
Evaluation: Use LangSmith to evaluate your graph's performance.

These capabilities are only available in LangGraph Platform.

Authentication and access control: Authenticate and authorize users to access a Langraph graph.
Assistants: Build assistants that can be used to interact with a LangGraph graph.
Double-texting: Handle double-texting (consecutive messages before a first response is returned) in a LangGraph graph.
Webhooks: Send webhooks to a LangGraph graph.
Cron jobs: Schedule jobs to run at a specific time.
Server customization: Customize the server that runs a LangGraph graph.
Data management: Manage data in a LangGraph graph.
Deployment: Deploy a LangGraph graph to a server.