# Session: 2026-03-09 03:53:37 UTC

- **Session Key**: agent:main:main
- **Session ID**: b6efb88b-4af1-42fc-b52e-d9a439150d54
- **Source**: telegram

## Conversation Summary

assistant: Now update the UI to poll properly (not rely on WebSocket):
assistant: Also fix the upload handler to use the same pattern:
assistant: Now restart and test:
assistant: **Now it works.** Status updates are flowing properly — you can see the stages progressing in real-time:

- At 3s: preparing → extracting → distributing → **perceiving** (active)
- At 9s: all stages done, **merging + synthesizing**
- At 15s: **completed**

Workers visible, progress updating, stages showing. Let me now test with Pat's actual video:
user: [Queued messages while agent was busy]

---
Queued #1
Conversation info (untrusted metadata):
```json
{
  "message_id": "4654",
  "sender_id": "7827979987",
  "sender": "P M",
  "timestamp": "Sun 2026-03-08 23:13 EDT"
}
```

Sender (untrusted metadata):
```json
{
  "label": "P M (7827979987)",
  "id": "7827979987",
  "name": "P M"
}
```

Also, another thing is the UI kind of isn’t great like I want to be able to see like I think you need to expand the abilities of this because right now it’s just like hey I’m just trusting that it’s actually doing something. It’d be great to see like little nodes lined up, however they work a little agents lined up and doing like the job and then like also seeing it written out as it goes, I think that’ll be really cool so I be able to see like the page that they’re writing this all into.

---
Queued #2
Conversation info (untrusted metadata):
```json
{
  "message_id": "4655",
  "sender_id": "7827979987",
  "sender": "P M",
  "timestamp": "Sun 2026-03-08 23:18 EDT"
}
```

Sender (untrusted metadata):
```json
{
  "label": "P M (7827979987)",
  "id": "7827979987",
  "name": "P M"
}
```

Hey
assistant: I hear you on both counts. The UI needs to show way more, and there's a bug preventing workers from showing up. Let me fix the core issue first, then upgrade the UI.
assistant: Now fix the audio worker count — whisper is CPU-heavy, limit to 2 concurrent:
assistant: Also fix the thread pool — vision and audio should use SEPARATE pools so audio doesn't block vision workers:
assistant: Now let me also fix the `_sync_state` to be thread-safe:
assistant: Now kill the stuck job and restart:
assistant: The indentation broke when I removed the `with ThreadPoolExecutor` context manager. The transcript section was inside the old `with pool:` block. Let me fix it:
assistant: Now the real test — does it show workers?
assistant: **Workers are showing now!** Live status updates flowing:

- 3s: 👁️ Vision working, 👂 Audio working (parallel!)
- 6s: Vision done, Audio still transcribing (40% progress)
- 9s: All perception done → 📝 Text extracted → 🧠 Merge done → 🧠 Synthesizer working
- 15s: **Completed** with 5 workers visible

Now let me test with Pat's actual video. It's a longer one so whisper will take a bit:
assistant: Workers are showing! 14 active workers, 42 total (12 vision batches + 30 audio chunks). Vision + audio running in parallel. Let me keep watching:
assistant: Vision done fast (12/12 in ~140s), now it's the 2 whisper workers chugging through 30 audio chunks. Whisper is the bottleneck. Let me keep watching: