langchain.js
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    • Define a LangGraph workflow using the entrypoint function.

      The wrapped function must accept at most two parameters. The first parameter is the input to the function. The second (optional) parameter is a LangGraphRunnableConfig object. If you wish to pass multiple parameters to the function, you can pass them as an object.

      To write data to the "custom" stream, use the getWriter function, or the LangGraphRunnableConfig.writer property.

      The getPreviousState function can be used to access the previous state that was returned from the last invocation of the entrypoint on the same thread id.

      If you wish to save state other than the return value, you can use the entrypoint.final function.

      Type Parameters

      • InputT

        The type of input the entrypoint accepts

      • OutputT

        The type of output the entrypoint produces

      Parameters

      Returns Pregel<
          Record<string, PregelNode<InputT, EntrypointReturnT<OutputT>>>,
          {
              __end__: LastValue<EntrypointReturnT<OutputT>>;
              __previous__: LastValue<EntrypointFinalSaveT<OutputT>>;
              __start__: EphemeralValue<InputT>;
          },
          Record<string, unknown>,
          InputT,
          EntrypointReturnT<OutputT>,
          any,
          Awaited<EntrypointReturnT<OutputT>>,
      >

      A Pregel instance that can be run to execute the workflow

      import { task, entrypoint } from "@langchain/langgraph";
      import { MemorySaver } from "@langchain/langgraph-checkpoint";
      import { interrupt, Command } from "@langchain/langgraph";

      const composeEssay = task("compose", async (topic: string) => {
      await new Promise(r => setTimeout(r, 1000)); // Simulate slow operation
      return `An essay about ${topic}`;
      });

      const reviewWorkflow = entrypoint({
      name: "review",
      checkpointer: new MemorySaver()
      }, async (topic: string) => {
      const essay = await composeEssay(topic);
      const humanReview = await interrupt({
      question: "Please provide a review",
      essay
      });
      return {
      essay,
      review: humanReview
      };
      });

      // Example configuration for the workflow
      const config = {
      configurable: {
      thread_id: "some_thread"
      }
      };

      // Topic for the essay
      const topic = "cats";

      // Stream the workflow to generate the essay and await human review
      for await (const result of reviewWorkflow.stream(topic, config)) {
      console.log(result);
      }

      // Example human review provided after the interrupt
      const humanReview = "This essay is great.";

      // Resume the workflow with the provided human review
      for await (const result of reviewWorkflow.stream(new Command({ resume: humanReview }), config)) {
      console.log(result);
      }
      import { entrypoint, getPreviousState } from "@langchain/langgraph";
      import { MemorySaver } from "@langchain/langgraph-checkpoint";

      const accumulator = entrypoint({
      name: "accumulator",
      checkpointer: new MemorySaver()
      }, async (input: string) => {
      const previous = getPreviousState<number>();
      return previous !== undefined ? `${previous } ${input}` : input;
      });

      const config = {
      configurable: {
      thread_id: "some_thread"
      }
      };
      await accumulator.invoke("hello", config); // returns "hello"
      await accumulator.invoke("world", config); // returns "hello world"
      import { entrypoint, getPreviousState } from "@langchain/langgraph";
      import { MemorySaver } from "@langchain/langgraph-checkpoint";

      const myWorkflow = entrypoint({
      name: "accumulator",
      checkpointer: new MemorySaver()
      }, async (num: number) => {
      const previous = getPreviousState<number>();

      // This will return the previous value to the caller, saving
      // 2 * num to the checkpoint, which will be used in the next invocation
      // for the `previous` parameter.
      return entrypoint.final({
      value: previous ?? 0,
      save: 2 * num
      });
      });

      const config = {
      configurable: {
      thread_id: "some_thread"
      }
      };

      await myWorkflow.invoke(3, config); // 0 (previous was undefined)
      await myWorkflow.invoke(1, config); // 6 (previous was 3 * 2 from the previous invocation)
    Index

    Methods

    Methods

    • A helper utility for use with the functional API that returns a value to the caller, as well as a separate state value to persist to the checkpoint. This allows workflows to maintain state between runs while returning different values to the caller.

      Type Parameters

      • ValueT

        The type of the value to return to the caller

      • SaveT

        The type of the state to save to the checkpoint

      Parameters

      • options: { save?: SaveT; value?: ValueT }
        • Optionalsave?: SaveT

          The value to save to the checkpoint

        • Optionalvalue?: ValueT

          The value to return to the caller

      Returns EntrypointFinal<ValueT, SaveT>

      An object with the value and save properties

      return entrypoint.final({
      value: "result for caller",
      save: { counter: currentCount + 1 }
      });