chore: release v2.60.4

.github/workflows/pipeline.yml

@@ -292,7 +292,7 @@ jobs:
           labels: ${{ steps.meta-web.outputs.labels }}
           platforms: |
             linux/amd64
-            linux/arm64
+            ${{ startsWith(github.ref, 'refs/tags/') && 'linux/arm64' || '' }}
 
       - name: Extract metadata (tags, labels) for Docker
         id: meta-worker
@@ -319,4 +319,4 @@ jobs:
           labels: ${{ steps.meta-worker.outputs.labels }}
           platforms: |
             linux/amd64
-            linux/arm64
+            ${{ startsWith(github.ref, 'refs/tags/') && 'linux/arm64' || '' }}

package.json

@@ -1,6 +1,6 @@
 {
   "name": "langfuse",
-  "version": "2.60.2",
+  "version": "2.60.4",
   "author": "engineering@langfuse.com",
   "license": "MIT",
   "private": true,

packages/shared/prisma/schema.prisma

@@ -363,7 +363,7 @@ view ObservationView {
     statusMessage       String?          @map("status_message")
     version             String?
     createdAt           DateTime         @map("created_at")
-    updateAt            DateTime         @map("updated_at")
+    updatedAt           DateTime         @map("updated_at")
 
     // GENERATION ONLY
     model               String?

web/package.json

@@ -1,6 +1,6 @@
 {
   "name": "web",
-  "version": "2.60.2",
+  "version": "2.60.4",
   "private": true,
   "license": "MIT",
   "engines": {

web/src/constants/VERSION.ts

@@ -1 +1 @@
-export const VERSION = "v2.60.2";
+export const VERSION = "v2.60.4";

web/src/features/dashboard/components/MetricTable.tsx

@@ -23,7 +23,7 @@ export const MetricTable = ({
     {
       projectId,
       from: env.NEXT_PUBLIC_LANGFUSE_CLOUD_REGION // Langfuse Cloud has already completed the cost backfill job, thus cost can be pulled directly from obs. table
-        ? "traces_observations"
+        ? "observations"
         : "traces_observationsview",
       select: [
         { column: "calculatedTotalCost", agg: "SUM" },

web/src/features/dashboard/components/ModelUsageChart.tsx

@@ -37,7 +37,7 @@ export const ModelUsageChart = ({
     {
       projectId,
       from: env.NEXT_PUBLIC_LANGFUSE_CLOUD_REGION // Langfuse Cloud has already completed the cost backfill job, thus cost can be pulled directly from obs. table
-        ? "traces_observations"
+        ? "observations"
         : "traces_observationsview",
       select: [
         { column: "totalTokens", agg: "SUM" },

web/src/features/public-api/types/scores.ts

@@ -68,7 +68,7 @@ const GetScoresDataBase = z.object({
   traceId: z.string(),
   observationId: z.string().nullish(),
   trace: z.object({
-    userId: z.string(),
+    userId: z.string().nullish(),
   }),
   configId: z.string().nullish(),
 });

web/src/pages/api/public/scores.ts

@@ -137,6 +137,7 @@ export default withMiddlewares({
           if (result.success) {
             acc.push(result.data);
           } else {
+            console.error("Score parsing error: ", result.error);
             Sentry.captureException(result.error);
           }
           return acc;

worker/package.json

@@ -1,6 +1,6 @@
 {
   "name": "worker",
-  "version": "2.60.2",
+  "version": "2.60.4",
   "description": "",
   "license": "MIT",
   "private": true,

worker/src/__tests__/eval-service.test.ts

@@ -199,6 +199,104 @@ describe("create eval jobs", () => {
     expect(jobs[0].end_time).to.be.null;
   }, 10_000);
 
+  test("does not create job for inactive config", async () => {
+    await pruneDatabase();
+    const traceId = randomUUID();
+
+    await kyselyPrisma.$kysely
+      .insertInto("traces")
+      .values({
+        id: traceId,
+        project_id: "7a88fb47-b4e2-43b8-a06c-a5ce950dc53a",
+      })
+      .execute();
+
+    await prisma.jobConfiguration.create({
+      data: {
+        id: randomUUID(),
+        projectId: "7a88fb47-b4e2-43b8-a06c-a5ce950dc53a",
+        filter: JSON.parse("[]"),
+        jobType: "EVAL",
+        delay: 0,
+        sampling: new Decimal("1"),
+        targetObject: "traces",
+        scoreName: "score",
+        variableMapping: JSON.parse("[]"),
+        status: "INACTIVE",
+      },
+    });
+
+    const payload = {
+      projectId: "7a88fb47-b4e2-43b8-a06c-a5ce950dc53a",
+      traceId: traceId,
+    };
+
+    await createEvalJobs({ event: payload });
+
+    const jobs = await kyselyPrisma.$kysely
+      .selectFrom("job_executions")
+      .selectAll()
+      .where("project_id", "=", "7a88fb47-b4e2-43b8-a06c-a5ce950dc53a")
+      .execute();
+
+    expect(jobs.length).toBe(0);
+  }, 10_000);
+
+  test("does not create eval job for 0 sample rate", async () => {
+    await pruneDatabase();
+    const traceId = randomUUID();
+
+    await kyselyPrisma.$kysely
+      .insertInto("traces")
+      .values({
+        id: traceId,
+        project_id: "7a88fb47-b4e2-43b8-a06c-a5ce950dc53a",
+      })
+      .execute();
+
+    await kyselyPrisma.$kysely
+      .insertInto("llm_api_keys")
+      .values({
+        id: randomUUID(),
+        project_id: "7a88fb47-b4e2-43b8-a06c-a5ce950dc53a",
+        secret_key: encrypt(String(OPENAI_API_KEY)),
+        provider: "openai",
+        adapter: LLMAdapter.OpenAI,
+        custom_models: [],
+        display_secret_key: "123456",
+      })
+      .execute();
+
+    await prisma.jobConfiguration.create({
+      data: {
+        id: randomUUID(),
+        projectId: "7a88fb47-b4e2-43b8-a06c-a5ce950dc53a",
+        filter: JSON.parse("[]"),
+        jobType: "EVAL",
+        delay: 0,
+        sampling: new Decimal("0"),
+        targetObject: "traces",
+        scoreName: "score",
+        variableMapping: JSON.parse("[]"),
+      },
+    });
+
+    const payload = {
+      projectId: "7a88fb47-b4e2-43b8-a06c-a5ce950dc53a",
+      traceId: traceId,
+    };
+
+    await createEvalJobs({ event: payload });
+
+    const jobs = await kyselyPrisma.$kysely
+      .selectFrom("job_executions")
+      .selectAll()
+      .where("project_id", "=", "7a88fb47-b4e2-43b8-a06c-a5ce950dc53a")
+      .execute();
+
+    expect(jobs.length).toBe(0);
+  }, 10_000);
+
   test("cancels a job if the second event deselects", async () => {
     await pruneDatabase();
     const traceId = randomUUID();

worker/src/constants/VERSION.ts

@@ -1 +1 @@
-export const VERSION = "v2.60.2";
+export const VERSION = "v2.60.4";

worker/src/features/evaluation/eval-service.ts

@@ -98,6 +98,19 @@ export const createEvalJobs = async ({
         continue;
       }
 
+      // apply sampling. Only if the job is sampled, we create a job
+      // user supplies a number between 0 and 1, which is the probability of sampling
+
+      if (parseFloat(config.sampling) !== 1) {
+        const random = Math.random();
+        if (random > parseFloat(config.sampling)) {
+          logger.info(
+            `Eval job for config ${config.id} and trace ${event.traceId} was sampled out`
+          );
+          continue;
+        }
+      }
+
       logger.info(
         `Creating eval job for config ${config.id} and trace ${event.traceId}`
       );