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README.md

LangGraph Plugin Samples

These samples demonstrate the Temporal LangGraph plugin, which runs LangGraph workflows as durable Temporal workflows. Each LangGraph graph node (Graph API) or @task (Functional API) executes as a Temporal activity with automatic retries, timeouts, and crash recovery.

Samples are organized by API style:

  • Graph API (graph_api/) -- Define workflows as StateGraph with nodes and edges.
  • Functional API (functional_api/) -- Define workflows with @task and @entrypoint decorators for an imperative programming style.

Samples

Sample Graph API Functional API Description
Hello World graph_api/hello_world functional_api/hello_world Minimal sample -- single node/task that processes a query string. Start here.
Human-in-the-loop graph_api/human_in_the_loop functional_api/human_in_the_loop Chatbot that uses interrupt() to pause for human approval, Temporal signals to receive feedback, and queries to expose the pending draft.
Continue-as-new graph_api/continue_as_new functional_api/continue_as_new Multi-stage data pipeline that uses continue-as-new with task result caching so previously-completed stages are not re-executed.
ReAct Agent graph_api/react_agent functional_api/react_agent Tool-calling agent loop. Graph API uses conditional edges; Functional API uses a while loop.
Control Flow -- functional_api/control_flow Demonstrates parallel task execution, for loops, and if/else branching -- patterns that are natural in the Functional API.
LangSmith Tracing graph_api/langsmith_tracing functional_api/langsmith_tracing Combines LangGraphPlugin with Temporal's LangSmithPlugin for durable execution + full observability of LLM calls. Requires API keys.

Prerequisites

  1. Install dependencies:

    uv sync --group langgraph

  2. Start a Temporal dev server:

    temporal server start-dev

Running a Sample

Each sample has two scripts -- start the worker first, then the workflow starter in a separate terminal.

# Terminal 1: start the worker
uv run langgraph_plugin/<api>/<sample>/run_worker.py

# Terminal 2: start the workflow
uv run langgraph_plugin/<api>/<sample>/run_workflow.py

For example, to run the Graph API human-in-the-loop chatbot:

# Terminal 1
uv run langgraph_plugin/graph_api/human_in_the_loop/run_worker.py

# Terminal 2
uv run langgraph_plugin/graph_api/human_in_the_loop/run_workflow.py

Key Features Demonstrated

  • Durable execution -- Every graph node / @task runs as a Temporal activity with configurable timeouts and retry policies.
  • Human-in-the-loop -- LangGraph's interrupt() pauses the graph; Temporal signals deliver human input; queries expose pending state to UIs.
  • Continue-as-new with caching -- get_cache() captures completed task results; passing the cache to the next execution avoids re-running them.
  • Conditional routing -- Graph API's add_conditional_edges and Functional API's native if/else/while for agent loops.
  • Parallel execution -- Functional API launches multiple tasks concurrently by creating futures before awaiting them.

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