fix(langchain): serialize ToolMessage/FunctionMessage with correct role and tool_call_id

packages/langchain/src/CallbackHandler.ts

@@ -9,6 +9,7 @@ import {
   type UsageMetadata,
   type BaseMessageFields,
   type MessageContent,
+  type ToolMessage,
 } from "@langchain/core/messages";
 import type { Generation, LLMResult } from "@langchain/core/outputs";
 import type { ChainValues } from "@langchain/core/utils/types";
@@ -43,8 +44,10 @@ type LangfusePrompt = {
 
 export type LlmMessage = {
   role: string;
+  name?: string;
   content: BaseMessageFields["content"];
   additional_kwargs?: BaseMessageFields["additional_kwargs"];
+  tool_call_id?: string;
 };
 
 export type AnonymousLlmMessage = {
@@ -991,13 +994,16 @@ export class CallbackHandler extends BaseCallbackHandler {
       response = {
         content: message.content,
         additional_kwargs: message.additional_kwargs,
-        role: message.name,
+        role: "function",
+        name: message.name,
       };
     } else if (message.getType() === "tool") {
       response = {
         content: message.content,
         additional_kwargs: message.additional_kwargs,
-        role: message.name,
+        role: "tool",
+        name: message.name,
+        tool_call_id: (message as ToolMessage).tool_call_id,
       };
     } else if (!message.name) {
       response = { content: message.content };

tests/integration/langchain.integration.test.ts

@@ -11,7 +11,12 @@ import {
   StateGraph,
 } from "@langchain/langgraph";
 import { BaseCallbackHandler } from "@langchain/core/callbacks/base";
-import { AIMessage, HumanMessage } from "@langchain/core/messages";
+import {
+  AIMessage,
+  FunctionMessage,
+  HumanMessage,
+  ToolMessage,
+} from "@langchain/core/messages";
 import { DynamicTool } from "@langchain/core/tools";
 import { FakeStreamingChatModel } from "@langchain/core/utils/testing";
 import { CallbackHandler } from "@langfuse/langchain";
@@ -374,4 +379,51 @@ describe("LangChain callback handler integration tests", () => {
 
     expect(completionStartTimes).not.toHaveProperty(runId);
   });
+
+  it("should serialize tool and function messages with role, name and tool_call_id", async () => {
+    const handler = new CallbackHandler();
+    const runId = "generation-with-tool-results";
+
+    await handler.handleChatModelStart(
+      { id: ["ChatOpenAI"] },
+      [
+        [
+          new HumanMessage("What is my updated debt?"),
+          new AIMessage({
+            content: "",
+            tool_calls: [{ id: "call_1", name: "get_debt", args: {} }],
+          }),
+          new ToolMessage({ content: "1874.32", tool_call_id: "call_1" }),
+          new ToolMessage({
+            content: "1874.32",
+            tool_call_id: "call_2",
+            name: "get_debt",
+          }),
+          new FunctionMessage({ content: "1874.32", name: "get_debt" }),
+        ],
+      ],
+      runId,
+      undefined,
+      { invocation_params: { model: "gpt-4.1-mini" } },
+    );
+    await handler.handleLLMEnd({ generations: [[{ text: "ok" }]] }, runId);
+
+    await waitForSpanExport(testEnv.mockExporter, 1);
+
+    assertions.expectSpanAttributeContains(
+      "ChatOpenAI",
+      LangfuseOtelSpanAttributes.OBSERVATION_INPUT,
+      '{"content":"1874.32","additional_kwargs":{},"role":"tool","tool_call_id":"call_1"}',
+    );
+    assertions.expectSpanAttributeContains(
+      "ChatOpenAI",
+      LangfuseOtelSpanAttributes.OBSERVATION_INPUT,
+      '{"content":"1874.32","additional_kwargs":{},"role":"tool","name":"get_debt","tool_call_id":"call_2"}',
+    );
+    assertions.expectSpanAttributeContains(
+      "ChatOpenAI",
+      LangfuseOtelSpanAttributes.OBSERVATION_INPUT,
+      '{"content":"1874.32","additional_kwargs":{},"role":"function","name":"get_debt"}',
+    );
+  });
 });