Merge branch 'main' into wfh/add_dotted_order_trace_id_run_tree

js/src/client.ts

@@ -242,6 +242,8 @@ export class Client {
 
   private autoBatchTracing = false;
 
+  private batchEndpointSupported?: boolean;
+
   private pendingAutoBatchedRuns: AutoBatchQueueItem[] = [];
 
   private pendingAutoBatchedRunLimit = 100;
@@ -537,6 +539,21 @@ export class Client {
     }
   }
 
+  protected async batchEndpointIsSupported() {
+    const response = await fetch(`${this.apiUrl}/info`, {
+      method: "GET",
+      headers: { Accept: "application/json" },
+      signal: AbortSignal.timeout(this.timeout_ms),
+    });
+    if (!response.ok) {
+      // consume the response body to release the connection
+      // https://undici.nodejs.org/#/?id=garbage-collection
+      await response.text();
+      return false;
+    }
+    return true;
+  }
+
   public async createRun(run: CreateRunParams): Promise<void> {
     if (!this._filterForSampling([run]).length) {
       return;
@@ -632,6 +649,24 @@ export class Client {
     preparedCreateParams = await mergeRuntimeEnvIntoRunCreates(
       preparedCreateParams
     );
+    if (this.batchEndpointSupported === undefined) {
+      this.batchEndpointSupported = await this.batchEndpointIsSupported();
+    }
+    if (!this.batchEndpointSupported) {
+      this.autoBatchTracing = false;
+      for (const preparedCreateParam of body.post) {
+        await this.createRun(preparedCreateParam as CreateRunParams);
+      }
+      for (const preparedUpdateParam of body.patch) {
+        if (preparedUpdateParam.id !== undefined) {
+          await this.updateRun(
+            preparedUpdateParam.id,
+            preparedUpdateParam as UpdateRunParams
+          );
+        }
+      }
+      return;
+    }
     const headers = {
       ...this.headers,
       "Content-Type": "application/json",

js/src/tests/batch_client.test.ts

@@ -15,6 +15,9 @@ describe("Batch client tracing", () => {
         ok: true,
         text: () => "",
       });
+    jest
+      .spyOn(client as any, "batchEndpointIsSupported")
+      .mockResolvedValue(true);
     const projectName = "__test_batch";
 
     const runId = uuidv4();
@@ -68,6 +71,9 @@ describe("Batch client tracing", () => {
         ok: true,
         text: () => "",
       });
+    jest
+      .spyOn(client as any, "batchEndpointIsSupported")
+      .mockResolvedValue(true);
     const projectName = "__test_batch";
 
     const runId = uuidv4();
@@ -134,6 +140,9 @@ describe("Batch client tracing", () => {
         ok: true,
         text: () => "",
       });
+    jest
+      .spyOn(client as any, "batchEndpointIsSupported")
+      .mockResolvedValue(true);
     const projectName = "__test_batch";
 
     const runId = uuidv4();
@@ -235,6 +244,9 @@ describe("Batch client tracing", () => {
         ok: true,
         text: () => "",
       });
+    jest
+      .spyOn(client as any, "batchEndpointIsSupported")
+      .mockResolvedValue(true);
     const projectName = "__test_batch";
 
     const runIds = await Promise.all(
@@ -296,4 +308,57 @@ describe("Batch client tracing", () => {
       patch: [],
     });
   });
+
+  it("If batching is unsupported, fall back to old endpoint", async () => {
+    const client = new Client({
+      apiKey: "test-api-key",
+      autoBatchTracing: true,
+    });
+    const callSpy = jest
+      .spyOn((client as any).caller, "call")
+      .mockResolvedValue({
+        ok: true,
+        text: () => "",
+      });
+    jest
+      .spyOn(client as any, "batchEndpointIsSupported")
+      .mockResolvedValue(false);
+    const projectName = "__test_batch";
+
+    const runId = uuidv4();
+    const dottedOrder = convertToDottedOrderFormat(
+      new Date().getTime() / 1000,
+      runId
+    );
+    await client.createRun({
+      id: runId,
+      project_name: projectName,
+      name: "test_run",
+      run_type: "llm",
+      inputs: { text: "hello world" },
+      trace_id: runId,
+      dotted_order: dottedOrder,
+    });
+
+    await new Promise((resolve) => setTimeout(resolve, 300));
+
+    const calledRequestParam: any = callSpy.mock.calls[0][2];
+    expect(JSON.parse(calledRequestParam?.body)).toMatchObject({
+      id: runId,
+      session_name: projectName,
+      extra: expect.anything(),
+      start_time: expect.any(Number),
+      name: "test_run",
+      run_type: "llm",
+      inputs: { text: "hello world" },
+      trace_id: runId,
+      dotted_order: dottedOrder,
+    });
+
+    expect(callSpy).toHaveBeenCalledWith(
+      fetch,
+      "https://api.smith.langchain.com/runs",
+      expect.objectContaining({ body: expect.any(String) })
+    );
+  });
 });

python/langsmith/client.py

@@ -840,7 +840,7 @@ def upload_csv(
 
     @staticmethod
     def _run_transform(
-        run: Union[ls_schemas.Run, dict, ls_schemas.RunLikeDict],
+        run: Union[ls_schemas.Run, dict, ls_schemas.RunLikeDict], update: bool = False
     ) -> dict:
         """
         Transforms the given run object into a dictionary representation.
@@ -863,7 +863,7 @@ def _run_transform(
             run_create["inputs"] = _hide_inputs(run_create["inputs"])
         if "outputs" in run_create:
             run_create["outputs"] = _hide_outputs(run_create["outputs"])
-        if not run_create.get("start_time"):
+        if not update and not run_create.get("start_time"):
             run_create["start_time"] = datetime.datetime.utcnow()
         return run_create
 
@@ -1024,7 +1024,7 @@ def batch_ingest_runs(
             return
         # transform and convert to dicts
         create_dicts = [self._run_transform(run) for run in create or []]
-        update_dicts = [self._run_transform(run) for run in update or []]
+        update_dicts = [self._run_transform(run, update=True) for run in update or []]
         # combine post and patch dicts where possible
         if update_dicts and create_dicts:
             create_by_id = {run["id"]: run for run in create_dicts}

python/pyproject.toml

@@ -1,6 +1,6 @@
 [tool.poetry]
 name = "langsmith"
-version = "0.0.88"
+version = "0.0.89"
 description = "Client library to connect to the LangSmith LLM Tracing and Evaluation Platform."
 authors = ["LangChain <[email protected]>"]
 license = "MIT"