Add LangGraph streaming adapter

packages/react-headless/src/index.ts

@@ -4,11 +4,16 @@ export { useThread, useThreadList } from "./hooks/useThread";
 export { ChatProvider } from "./store/ChatProvider";
 export {
   agUIAdapter,
+  langGraphAdapter,
   openAIAdapter,
   openAIReadableStreamAdapter,
   openAIResponsesAdapter,
 } from "./stream/adapters";
-export { openAIConversationMessageFormat, openAIMessageFormat } from "./stream/formats";
+export {
+  langGraphMessageFormat,
+  openAIConversationMessageFormat,
+  openAIMessageFormat,
+} from "./stream/formats";
 export { processStreamedMessage } from "./stream/processStreamedMessage";
 
 export type {
@@ -38,6 +43,8 @@ export type {
   UserMessage,
 } from "./types/message";
 
+export type { LangGraphAdapterOptions } from "./stream/adapters/langgraph";
+export type { LangGraphMessageFormat } from "./stream/formats/langgraph-message-format";
 export { identityMessageFormat } from "./types/messageFormat";
 export type { MessageFormat } from "./types/messageFormat";
 export { EventType } from "./types/stream";

packages/react-headless/src/stream/adapters/__tests__/langgraph.test.ts

@@ -0,0 +1,359 @@
+import { describe, expect, it, vi } from "vitest";
+import { EventType } from "../../../types";
+import { langGraphAdapter } from "../langgraph";
+
+// ── Helpers ──
+
+/**
+ * Create a Response with an SSE body from a raw string.
+ */
+function makeSSEResponse(body: string): Response {
+  const stream = new ReadableStream({
+    start(controller) {
+      controller.enqueue(new TextEncoder().encode(body));
+      controller.close();
+    },
+  });
+  return new Response(stream);
+}
+
+/**
+ * Build a named SSE block: `event: <name>\ndata: <json>\n\n`
+ */
+function sse(event: string, data: unknown): string {
+  return `event: ${event}\ndata: ${JSON.stringify(data)}\n\n`;
+}
+
+/**
+ * Collect all events from an async iterable.
+ */
+async function collect(iter: AsyncIterable<unknown>): Promise<unknown[]> {
+  const events: unknown[] = [];
+  for await (const event of iter) {
+    events.push(event);
+  }
+  return events;
+}
+
+// ── Tests ──
+
+describe("langGraphAdapter", () => {
+  it("throws when response has no body", async () => {
+    const adapter = langGraphAdapter();
+    const response = new Response(null);
+
+    await expect(async () => {
+      for await (const _ of adapter.parse(response)) {
+        /* drain */
+      }
+    }).rejects.toThrow("No response body");
+  });
+
+  describe("text streaming", () => {
+    it("emits TEXT_MESSAGE_START, CONTENT, and END for AI message chunks", async () => {
+      const body =
+        sse("messages", [
+          { type: "AIMessageChunk", content: "Hello", id: "msg-1" },
+          { langgraph_node: "agent" },
+        ]) +
+        sse("messages", [
+          { type: "AIMessageChunk", content: " world", id: "msg-1" },
+          { langgraph_node: "agent" },
+        ]) +
+        sse("end", null);
+
+      const adapter = langGraphAdapter();
+      const events = await collect(adapter.parse(makeSSEResponse(body)));
+
+      expect(events[0]).toMatchObject({
+        type: EventType.TEXT_MESSAGE_START,
+        role: "assistant",
+      });
+      expect(events[1]).toMatchObject({
+        type: EventType.TEXT_MESSAGE_CONTENT,
+        delta: "Hello",
+      });
+      expect(events[2]).toMatchObject({
+        type: EventType.TEXT_MESSAGE_CONTENT,
+        delta: " world",
+      });
+      expect(events[3]).toMatchObject({
+        type: EventType.TEXT_MESSAGE_END,
+      });
+    });
+
+    it("handles content as array of typed blocks", async () => {
+      const body =
+        sse("messages", [
+          {
+            type: "AIMessageChunk",
+            content: [
+              { type: "text", text: "block one" },
+              { type: "text", text: " block two" },
+            ],
+            id: "msg-1",
+          },
+          { langgraph_node: "agent" },
+        ]) +
+        sse("end", null);
+
+      const adapter = langGraphAdapter();
+      const events = await collect(adapter.parse(makeSSEResponse(body)));
+
+      expect(events[1]).toMatchObject({
+        type: EventType.TEXT_MESSAGE_CONTENT,
+        delta: "block one block two",
+      });
+    });
+
+    it("handles non-tuple message format (plain object)", async () => {
+      const body =
+        sse("messages", { type: "ai", content: "plain", id: "msg-1" }) +
+        sse("end", null);
+
+      const adapter = langGraphAdapter();
+      const events = await collect(adapter.parse(makeSSEResponse(body)));
+
+      expect(events[0]).toMatchObject({ type: EventType.TEXT_MESSAGE_START });
+      expect(events[1]).toMatchObject({
+        type: EventType.TEXT_MESSAGE_CONTENT,
+        delta: "plain",
+      });
+    });
+
+    it("ignores non-AI message types", async () => {
+      const body =
+        sse("messages", [
+          { type: "human", content: "user input", id: "hmsg-1" },
+          { langgraph_node: "agent" },
+        ]) +
+        sse("end", null);
+
+      const adapter = langGraphAdapter();
+      const events = await collect(adapter.parse(makeSSEResponse(body)));
+
+      // Should only have the end event (no message start/content)
+      expect(events).toHaveLength(0);
+    });
+  });
+
+  describe("tool calls", () => {
+    it("emits tool call events for tool_call_chunks", async () => {
+      const body =
+        sse("messages", [
+          {
+            type: "AIMessageChunk",
+            content: "",
+            tool_call_chunks: [
+              { id: "tc-1", name: "get_weather", args: '{"loc', index: 0 },
+            ],
+          },
+          { langgraph_node: "agent" },
+        ]) +
+        sse("messages", [
+          {
+            type: "AIMessageChunk",
+            content: "",
+            tool_call_chunks: [
+              { id: undefined, name: undefined, args: 'ation":"NYC"}', index: 0 },
+            ],
+          },
+          { langgraph_node: "agent" },
+        ]) +
+        sse("end", null);
+
+      const adapter = langGraphAdapter();
+      const events = await collect(adapter.parse(makeSSEResponse(body)));
+
+      // TEXT_MESSAGE_START, TOOL_CALL_START, TOOL_CALL_ARGS, TOOL_CALL_ARGS, TOOL_CALL_END, TEXT_MESSAGE_END
+      const toolStart = events.find((e: any) => e.type === EventType.TOOL_CALL_START);
+      expect(toolStart).toMatchObject({
+        type: EventType.TOOL_CALL_START,
+        toolCallId: "tc-1",
+        toolCallName: "get_weather",
+      });
+
+      const toolArgs = events.filter((e: any) => e.type === EventType.TOOL_CALL_ARGS);
+      expect(toolArgs).toHaveLength(2);
+      expect((toolArgs[0] as any).delta).toBe('{"loc');
+      expect((toolArgs[1] as any).delta).toBe('ation":"NYC"}');
+    });
+
+    it("emits tool call events for complete tool_calls (non-streaming)", async () => {
+      const body =
+        sse("messages", [
+          {
+            type: "AIMessageChunk",
+            content: "",
+            tool_calls: [
+              { id: "tc-1", name: "search", args: { query: "test" } },
+            ],
+          },
+          { langgraph_node: "agent" },
+        ]) +
+        sse("end", null);
+
+      const adapter = langGraphAdapter();
+      const events = await collect(adapter.parse(makeSSEResponse(body)));
+
+      const toolStart = events.find((e: any) => e.type === EventType.TOOL_CALL_START);
+      expect(toolStart).toMatchObject({
+        toolCallId: "tc-1",
+        toolCallName: "search",
+      });
+
+      const toolArgs = events.find((e: any) => e.type === EventType.TOOL_CALL_ARGS);
+      expect((toolArgs as any).delta).toBe('{"query":"test"}');
+
+      const toolEnd = events.filter((e: any) => e.type === EventType.TOOL_CALL_END);
+      // One from the complete tool_calls handling + one from the "end" event cleanup
+      expect(toolEnd.length).toBeGreaterThanOrEqual(1);
+    });
+  });
+
+  describe("error handling", () => {
+    it("emits RUN_ERROR for error events", async () => {
+      const body = sse("error", {
+        error: "InternalError",
+        message: "Something went wrong",
+      });
+
+      const adapter = langGraphAdapter();
+      const events = await collect(adapter.parse(makeSSEResponse(body)));
+
+      expect(events[0]).toMatchObject({
+        type: EventType.RUN_ERROR,
+        message: "Something went wrong",
+        code: "InternalError",
+      });
+    });
+
+    it("handles malformed JSON gracefully", async () => {
+      const body = "event: messages\ndata: {invalid json}\n\n" + sse("end", null);
+
+      const consoleSpy = vi.spyOn(console, "error").mockImplementation(() => {});
+      const adapter = langGraphAdapter();
+      const events = await collect(adapter.parse(makeSSEResponse(body)));
+
+      expect(consoleSpy).toHaveBeenCalledWith(
+        "Failed to parse LangGraph SSE data",
+        expect.any(SyntaxError),
+      );
+      consoleSpy.mockRestore();
+
+      // Should still have processed remaining events (no events since "end"
+      // with no message started yields nothing)
+      expect(events).toHaveLength(0);
+    });
+  });
+
+  describe("interrupts", () => {
+    it("calls onInterrupt when updates contain __interrupt__", async () => {
+      const onInterrupt = vi.fn();
+      const body =
+        sse("messages", [
+          { type: "AIMessageChunk", content: "thinking...", id: "msg-1" },
+          { langgraph_node: "agent" },
+        ]) +
+        sse("updates", {
+          agent: { messages: [] },
+          __interrupt__: { value: "need input", resumable: true },
+        }) +
+        sse("end", null);
+
+      const adapter = langGraphAdapter({ onInterrupt });
+      await collect(adapter.parse(makeSSEResponse(body)));
+
+      expect(onInterrupt).toHaveBeenCalledWith({
+        value: "need input",
+        resumable: true,
+      });
+    });
+
+    it("does not throw when onInterrupt is not provided", async () => {
+      const body =
+        sse("updates", {
+          __interrupt__: { value: "need input" },
+        }) +
+        sse("end", null);
+
+      const adapter = langGraphAdapter();
+      // Should not throw
+      await collect(adapter.parse(makeSSEResponse(body)));
+    });
+  });
+
+  describe("metadata event", () => {
+    it("does not emit events for metadata", async () => {
+      const body =
+        sse("metadata", { run_id: "run-123", thread_id: "thread-456" }) +
+        sse("end", null);
+
+      const adapter = langGraphAdapter();
+      const events = await collect(adapter.parse(makeSSEResponse(body)));
+
+      // No events should be emitted for metadata alone
+      expect(events).toHaveLength(0);
+    });
+  });
+
+  describe("stream end", () => {
+    it("closes message on explicit end event", async () => {
+      const body =
+        sse("messages", [
+          { type: "AIMessageChunk", content: "done", id: "msg-1" },
+          { langgraph_node: "agent" },
+        ]) +
+        sse("end", null);
+
+      const adapter = langGraphAdapter();
+      const events = await collect(adapter.parse(makeSSEResponse(body)));
+
+      const lastEvent = events[events.length - 1] as any;
+      expect(lastEvent.type).toBe(EventType.TEXT_MESSAGE_END);
+    });
+
+    it("closes message when stream ends without end event", async () => {
+      const body = sse("messages", [
+        { type: "AIMessageChunk", content: "abrupt", id: "msg-1" },
+        { langgraph_node: "agent" },
+      ]);
+
+      const adapter = langGraphAdapter();
+      const events = await collect(adapter.parse(makeSSEResponse(body)));
+
+      const lastEvent = events[events.length - 1] as any;
+      expect(lastEvent.type).toBe(EventType.TEXT_MESSAGE_END);
+    });
+  });
+
+  describe("multi-chunk delivery", () => {
+    it("handles SSE blocks split across multiple chunks", async () => {
+      // Simulate a response where SSE data arrives in two chunks,
+      // with the split happening mid-block.
+      const part1 = "event: messages\ndata: ";
+      const part2 =
+        JSON.stringify([
+          { type: "AIMessageChunk", content: "split", id: "msg-1" },
+          { langgraph_node: "agent" },
+        ]) + "\n\n" + sse("end", null);
+
+      const stream = new ReadableStream({
+        start(controller) {
+          controller.enqueue(new TextEncoder().encode(part1));
+          controller.enqueue(new TextEncoder().encode(part2));
+          controller.close();
+        },
+      });
+
+      const adapter = langGraphAdapter();
+      const events = await collect(adapter.parse(new Response(stream)));
+
+      expect(events[0]).toMatchObject({ type: EventType.TEXT_MESSAGE_START });
+      expect(events[1]).toMatchObject({
+        type: EventType.TEXT_MESSAGE_CONTENT,
+        delta: "split",
+      });
+    });
+  });
+});

packages/react-headless/src/stream/adapters/index.ts

@@ -1,4 +1,5 @@
 export * from "./ag-ui";
+export * from "./langgraph";
 export * from "./openai-completions";
 export * from "./openai-readable-stream";
 export * from "./openai-responses";