From db1816853722185007040fd3709f3b5fd0b86a3c Mon Sep 17 00:00:00 2001
From: mawkone <mark@getacquired.com>
Date: Wed, 10 Jun 2026 16:43:14 -0700
Subject: [PATCH] feat(telemetry): capture agent-runner model turns via central
 telemetry service

---
 vibn-agent-runner/src/llm/telemetry-db.ts    | 45 ++++++++++++++++++++
 vibn-agent-runner/src/llm/vibn-chat-model.ts | 45 +++++++++++++++++---
 2 files changed, 83 insertions(+), 7 deletions(-)
 create mode 100644 vibn-agent-runner/src/llm/telemetry-db.ts

diff --git a/vibn-agent-runner/src/llm/telemetry-db.ts b/vibn-agent-runner/src/llm/telemetry-db.ts
new file mode 100644
index 00000000..61addc0a
--- /dev/null
+++ b/vibn-agent-runner/src/llm/telemetry-db.ts
@@ -0,0 +1,45 @@
+/**
+ * Fire-and-forget telemetry: sends each model turn to the central
+ * telemetry microservice (TELEMETRY_SERVICE_URL) which persists it to
+ * Postgres for diagnostics and as fine-tuning training data.
+ *
+ * Never blocks or throws into the agent loop.
+ */
+
+export interface TelemetryPayload {
+  projectId?: string;
+  model: string;
+  systemPrompt: string;
+  messages: unknown[];
+  response: {
+    text: string;
+    thoughts: string;
+    toolCalls: unknown[];
+  };
+  metrics: {
+    promptTokens?: number;
+    completionTokens?: number;
+    totalTokens?: number;
+    durationMs: number;
+  };
+}
+
+export function logTrainingTelemetry(data: TelemetryPayload): void {
+  setTimeout(async () => {
+    try {
+      const telemetryUrl = process.env.TELEMETRY_SERVICE_URL;
+      if (!telemetryUrl) return; // silently skip when not configured
+
+      await fetch(`${telemetryUrl.replace(/\/$/, "")}/ingest`, {
+        method: "POST",
+        headers: { "Content-Type": "application/json" },
+        body: JSON.stringify(data),
+      });
+    } catch (error) {
+      console.error(
+        "[Telemetry] Failed to send training data to microservice:",
+        error instanceof Error ? error.message : String(error),
+      );
+    }
+  }, 0);
+}
diff --git a/vibn-agent-runner/src/llm/vibn-chat-model.ts b/vibn-agent-runner/src/llm/vibn-chat-model.ts
index 254497c5..98d966d0 100644
--- a/vibn-agent-runner/src/llm/vibn-chat-model.ts
+++ b/vibn-agent-runner/src/llm/vibn-chat-model.ts
@@ -12,9 +12,10 @@
  *   Optional: VIBN_OPENAI_COMPATIBLE_MODEL (default deepseek-chat)
  */
 
-import type { ChatMessage, ToolDefinition } from './gemini-chat';
-import { callGeminiChat } from './gemini-chat';
-import { callOpenAiCompatibleChat } from './openai-compatible-chat';
+import type { ChatMessage, ToolDefinition } from "./gemini-chat";
+import { callGeminiChat } from "./gemini-chat";
+import { callOpenAiCompatibleChat } from "./openai-compatible-chat";
+import { logTrainingTelemetry } from "./telemetry-db";
 
 export type VibnChatCallOpts = {
   systemPrompt: string;
@@ -22,12 +23,42 @@ export type VibnChatCallOpts = {
   tools?: ToolDefinition[];
   temperature?: number;
   includeThoughts?: boolean;
+  // Optional metadata for telemetry; not used by the model call itself.
+  projectId?: string;
 };
 
 export async function callVibnChat(opts: VibnChatCallOpts) {
-  const p = (process.env.VIBN_CHAT_PROVIDER || 'gemini').toLowerCase().trim();
-  if (p === 'deepseek' || p === 'openai_compatible') {
-    return callOpenAiCompatibleChat(opts);
+  const p = (process.env.VIBN_CHAT_PROVIDER || "gemini").toLowerCase().trim();
+  const model =
+    p === "deepseek" || p === "openai_compatible"
+      ? process.env.VIBN_OPENAI_COMPATIBLE_MODEL || "deepseek-chat"
+      : process.env.VIBN_CHAT_MODEL || "gemini-3.1-pro-preview";
+
+  const startedAt = Date.now();
+  const result =
+    p === "deepseek" || p === "openai_compatible"
+      ? await callOpenAiCompatibleChat(opts)
+      : await callGeminiChat(opts);
+  const durationMs = Date.now() - startedAt;
+
+  // Fire-and-forget: capture this turn as training/diagnostic telemetry.
+  // Never let logging interfere with the agent loop.
+  try {
+    logTrainingTelemetry({
+      projectId: opts.projectId,
+      model,
+      systemPrompt: opts.systemPrompt,
+      messages: opts.messages,
+      response: {
+        text: result.text ?? "",
+        thoughts: result.thoughts ?? "",
+        toolCalls: result.toolCalls ?? [],
+      },
+      metrics: { durationMs },
+    });
+  } catch {
+    // ignore
   }
-  return callGeminiChat(opts);
+
+  return result;
 }