Merge branch 'main' into fix-room-query-batching

fix: use $api.queryOptions for batcher query keys
Replace custom meetingStatusKeys with $api.queryOptions()-derived keys so cache identity matches the original per-room GET endpoints.
2026-02-06 02:36:47 +00:00 · 2026-02-05 19:42:29 -05:00 · 2026-02-05 19:40:13 -05:00 · 2026-02-05 19:36:17 -05:00 · 2026-02-05 19:06:32 -05:00 · 2026-02-05 18:38:08 -05:00
40 changed files with 2301 additions and 467 deletions
--- a/.github/workflows/test_next_server.yml
+++ b/.github/workflows/test_next_server.yml
@@ -13,6 +13,9 @@ on:
 jobs:
  test-next-server:
    runs-on: ubuntu-latest
+    concurrency:
+      group: test-next-server-${{ github.ref }}
+      cancel-in-progress: true

    defaults:
      run:
@@ -21,17 +24,12 @@ jobs:
    steps:
    - uses: actions/checkout@v4

-    - name: Setup Node.js
-      uses: actions/setup-node@v4
-      with:
-        node-version: '20'
-
    - name: Install pnpm
      uses: pnpm/action-setup@v4
      with:
-        version: 8
+        package_json_file: './www/package.json'

-    - name: Setup Node.js cache
+    - name: Setup Node.js
      uses: actions/setup-node@v4
      with:
        node-version: '20'
--- a/.gitignore
+++ b/.gitignore
@@ -1,5 +1,6 @@
 .DS_Store
 server/.env
+server/.env.production
 .env
 Caddyfile
 server/exportdanswer
--- a/.gitleaksignore
+++ b/.gitleaksignore
@@ -4,3 +4,4 @@ docs/docs/installation/daily-setup.md:curl-auth-header:277
 gpu/self_hosted/DEV_SETUP.md:curl-auth-header:74
 gpu/self_hosted/DEV_SETUP.md:curl-auth-header:83
 server/reflector/worker/process.py:generic-api-key:465
+server/reflector/worker/process.py:generic-api-key:594
--- a/CHANGELOG.md
+++ b/CHANGELOG.md
@@ -1,5 +1,29 @@
 # Changelog

+## [0.32.2](https://github.com/Monadical-SAS/reflector/compare/v0.32.1...v0.32.2) (2026-02-03)
+
+
+### Bug Fixes
+
+* increase TIMEOUT_MEDIUM from 2m to 5m for LLM tasks ([#843](https://github.com/Monadical-SAS/reflector/issues/843)) ([4acde4b](https://github.com/Monadical-SAS/reflector/commit/4acde4b7fdef88cc02ca12cf38c9020b05ed96ac))
+* make caddy optional ([#841](https://github.com/Monadical-SAS/reflector/issues/841)) ([a2ed7d6](https://github.com/Monadical-SAS/reflector/commit/a2ed7d60d557b551a5b64e4dfd909b63a791d9fc))
+* use Daily API recording.duration as master source for transcript duration ([#844](https://github.com/Monadical-SAS/reflector/issues/844)) ([8707c66](https://github.com/Monadical-SAS/reflector/commit/8707c6694a80c939b6214bbc13331741f192e082))
+
+## [0.32.1](https://github.com/Monadical-SAS/reflector/compare/v0.32.0...v0.32.1) (2026-01-30)
+
+
+### Bug Fixes
+
+* daily multitrack pipeline finalze dependency fix ([23eb137](https://github.com/Monadical-SAS/reflector/commit/23eb1371cb9348c4b81eb12ad506b582f8a4799e))
+* match httpx pad with hatchet audio timeout ([c05d1f0](https://github.com/Monadical-SAS/reflector/commit/c05d1f03cd8369fc06efd455527e50246887efd0))
+
+## [0.32.0](https://github.com/Monadical-SAS/reflector/compare/v0.31.0...v0.32.0) (2026-01-30)
+
+
+### Features
+
+* modal padding ([#837](https://github.com/Monadical-SAS/reflector/issues/837)) ([7fde64e](https://github.com/Monadical-SAS/reflector/commit/7fde64e2529a1d37b0f7507c62d983a7bd0b5b89))
+
 ## [0.31.0](https://github.com/Monadical-SAS/reflector/compare/v0.30.0...v0.31.0) (2026-01-23)


--- a/Caddyfile.example
+++ b/Caddyfile.example
@@ -1,6 +1,8 @@
-# Reflector Caddyfile
-# Replace example.com with your actual domains
-# CORS is handled by the backend - Caddy just proxies
+# Reflector Caddyfile (optional reverse proxy)
+# Use this only when you run Caddy via: docker compose -f docker-compose.prod.yml --profile caddy up -d
+# If Coolify, Traefik, or nginx already use ports 80/443, do NOT start Caddy; point your proxy at web:3000 and server:1250.
+#
+# Replace example.com with your actual domains. CORS is handled by the backend - Caddy just proxies.
 #
 # For environment variable substitution, set:
 #   FRONTEND_DOMAIN=app.example.com
--- a/docker-compose.prod.yml
+++ b/docker-compose.prod.yml
@@ -1,9 +1,14 @@
 # Production Docker Compose configuration
 # Usage: docker compose -f docker-compose.prod.yml up -d
 #
+# Caddy (reverse proxy on ports 80/443) is OPTIONAL and behind the "caddy" profile:
+# - With Caddy (self-hosted, you manage SSL): docker compose -f docker-compose.prod.yml --profile caddy up -d
+# - Without Caddy (Coolify/Traefik/nginx already on 80/443): docker compose -f docker-compose.prod.yml up -d
+#   Then point your proxy at web:3000 (frontend) and server:1250 (API).
+#
 # Prerequisites:
 # 1. Copy .env.example to .env and configure for both server/ and www/
-# 2. Copy Caddyfile.example to Caddyfile and edit with your domains
+# 2. If using Caddy: copy Caddyfile.example to Caddyfile and edit your domains
 # 3. Deploy Modal GPU functions (see gpu/modal_deployments/deploy-all.sh)

 services:
@@ -84,6 +89,8 @@ services:
      retries: 3

  caddy:
+    profiles:
+      - caddy
    image: caddy:2-alpine
    restart: unless-stopped
    ports:
--- a/docs/docs/installation/docker-setup.md
+++ b/docs/docs/installation/docker-setup.md
@@ -11,15 +11,15 @@ This page documents the Docker Compose configuration for Reflector. For the comp

 The `docker-compose.prod.yml` includes these services:

-| Service | Image | Purpose |
-|---------|-------|---------|
-| `web` | `monadicalsas/reflector-frontend` | Next.js frontend |
-| `server` | `monadicalsas/reflector-backend` | FastAPI backend |
-| `worker` | `monadicalsas/reflector-backend` | Celery worker for background tasks |
-| `beat` | `monadicalsas/reflector-backend` | Celery beat scheduler |
-| `redis` | `redis:7.2-alpine` | Message broker and cache |
-| `postgres` | `postgres:17-alpine` | Primary database |
-| `caddy` | `caddy:2-alpine` | Reverse proxy with auto-SSL |
+| Service    | Image                             | Purpose                                                                     |
+| ---------- | --------------------------------- | --------------------------------------------------------------------------- |
+| `web`      | `monadicalsas/reflector-frontend` | Next.js frontend                                                            |
+| `server`   | `monadicalsas/reflector-backend`  | FastAPI backend                                                             |
+| `worker`   | `monadicalsas/reflector-backend`  | Celery worker for background tasks                                          |
+| `beat`     | `monadicalsas/reflector-backend`  | Celery beat scheduler                                                       |
+| `redis`    | `redis:7.2-alpine`                | Message broker and cache                                                    |
+| `postgres` | `postgres:17-alpine`              | Primary database                                                            |
+| `caddy`    | `caddy:2-alpine`                  | Reverse proxy with auto-SSL (optional; see [Caddy profile](#caddy-profile)) |

 ## Environment Files

@@ -30,6 +30,7 @@ Reflector uses two separate environment files:
 Used by: `server`, `worker`, `beat`

 Key variables:
+
 ```env
 # Database connection
 DATABASE_URL=postgresql+asyncpg://reflector:reflector@postgres:5432/reflector
@@ -54,6 +55,7 @@ TRANSCRIPT_MODAL_API_KEY=...
 Used by: `web`

 Key variables:
+
 ```env
 # Domain configuration
 SITE_URL=https://app.example.com
@@ -70,26 +72,42 @@ Note: `API_URL` is used client-side (browser), `SERVER_API_URL` is used server-s

 ## Volumes

-| Volume | Purpose |
-|--------|---------|
-| `redis_data` | Redis persistence |
-| `postgres_data` | PostgreSQL data |
-| `server_data` | Uploaded files, local storage |
-| `caddy_data` | SSL certificates |
-| `caddy_config` | Caddy configuration |
+| Volume          | Purpose                       |
+| --------------- | ----------------------------- |
+| `redis_data`    | Redis persistence             |
+| `postgres_data` | PostgreSQL data               |
+| `server_data`   | Uploaded files, local storage |
+| `caddy_data`    | SSL certificates              |
+| `caddy_config`  | Caddy configuration           |

 ## Network

 All services share the default network. The network is marked `attachable: true` to allow external containers (like Authentik) to join.

+## Caddy profile
+
+Caddy (ports 80 and 443) is **optional** and behind the `caddy` profile so it does not conflict with an existing reverse proxy (e.g. Coolify, Traefik, nginx).
+
+- **With Caddy** (you want Reflector to handle SSL):
+  `docker compose -f docker-compose.prod.yml --profile caddy up -d`
+- **Without Caddy** (Coolify or another proxy already on 80/443):
+  `docker compose -f docker-compose.prod.yml up -d`
+  Then configure your proxy to send traffic to `web:3000` (frontend) and `server:1250` (API).
+
 ## Common Commands

 ### Start all services
+
 ```bash
+# Without Caddy (e.g. when using Coolify)
 docker compose -f docker-compose.prod.yml up -d
+
+# With Caddy as reverse proxy
+docker compose -f docker-compose.prod.yml --profile caddy up -d
 ```

 ### View logs
+
 ```bash
 # All services
 docker compose -f docker-compose.prod.yml logs -f
@@ -99,6 +117,7 @@ docker compose -f docker-compose.prod.yml logs server --tail 50
 ```

 ### Restart a service
+
 ```bash
 # Quick restart (doesn't reload .env changes)
 docker compose -f docker-compose.prod.yml restart server
@@ -108,27 +127,32 @@ docker compose -f docker-compose.prod.yml up -d server
 ```

 ### Run database migrations
+
 ```bash
 docker compose -f docker-compose.prod.yml exec server uv run alembic upgrade head
 ```

 ### Access database
+
 ```bash
 docker compose -f docker-compose.prod.yml exec postgres psql -U reflector
 ```

 ### Pull latest images
+
 ```bash
 docker compose -f docker-compose.prod.yml pull
 docker compose -f docker-compose.prod.yml up -d
 ```

 ### Stop all services
+
 ```bash
 docker compose -f docker-compose.prod.yml down
 ```

 ### Full reset (WARNING: deletes data)
+
 ```bash
 docker compose -f docker-compose.prod.yml down -v
 ```
@@ -187,6 +211,7 @@ The Caddyfile supports environment variable substitution:
 Set `FRONTEND_DOMAIN` and `API_DOMAIN` environment variables, or edit the file directly.

 ### Reload Caddy after changes
+
 ```bash
 docker compose -f docker-compose.prod.yml exec caddy caddy reload --config /etc/caddy/Caddyfile
 ```
--- a/docs/docs/installation/overview.md
+++ b/docs/docs/installation/overview.md
@@ -26,7 +26,7 @@ flowchart LR

 Before starting, you need:

- **Production server** -  4+ cores, 8GB+ RAM, public IP
+- **Production server** - 4+ cores, 8GB+ RAM, public IP
 - **Two domain names** - e.g., `app.example.com` (frontend) and `api.example.com` (backend)
 - **GPU processing** - Choose one:
  - Modal.com account, OR
@@ -60,16 +60,17 @@ Type: A    Name: api    Value: <your-server-ip>

 Reflector requires GPU processing for transcription and speaker diarization. Choose one option:

-| | **Modal.com (Cloud)** | **Self-Hosted GPU** |
-|---|---|---|
+|              | **Modal.com (Cloud)**             | **Self-Hosted GPU**          |
+| ------------ | --------------------------------- | ---------------------------- |
 | **Best for** | No GPU hardware, zero maintenance | Own GPU server, full control |
-| **Pricing** | Pay-per-use | Fixed infrastructure cost |
+| **Pricing**  | Pay-per-use                       | Fixed infrastructure cost    |

 ### Option A: Modal.com (Serverless Cloud GPU)

 #### Accept HuggingFace Licenses

 Visit both pages and click "Accept":
+
 - https://huggingface.co/pyannote/speaker-diarization-3.1
 - https://huggingface.co/pyannote/segmentation-3.0

@@ -179,6 +180,7 @@ Save these credentials - you'll need them in the next step.
 ## Configure Environment

 Reflector has two env files:
+
 - `server/.env` - Backend configuration
 - `www/.env` - Frontend configuration

@@ -190,6 +192,7 @@ nano server/.env
 ```

 **Required settings:**
+
 ```env
 # Database (defaults work with docker-compose.prod.yml)
 DATABASE_URL=postgresql+asyncpg://reflector:reflector@postgres:5432/reflector
@@ -249,6 +252,7 @@ nano www/.env
 ```

 **Required settings:**
+
 ```env
 # Your domains
 SITE_URL=https://app.example.com
@@ -266,7 +270,11 @@ FEATURE_REQUIRE_LOGIN=false

 ---

-## Configure Caddy
+## Reverse proxy (Caddy or existing)
+
+**If Coolify, Traefik, or nginx already use ports 80/443** (e.g. Coolify on your host): skip Caddy. Start the stack without the Caddy profile (see [Start Services](#start-services) below), then point your proxy at `web:3000` (frontend) and `server:1250` (API).
+
+**If you want Reflector to provide the reverse proxy and SSL:**

 ```bash
 cp Caddyfile.example Caddyfile
@@ -289,10 +297,18 @@ Replace `example.com` with your domains. The `{$VAR:default}` syntax uses Caddy'

 ## Start Services

+**Without Caddy** (e.g. Coolify already on 80/443):
+
 ```bash
 docker compose -f docker-compose.prod.yml up -d
 ```

+**With Caddy** (Reflector handles SSL):
+
+```bash
+docker compose -f docker-compose.prod.yml --profile caddy up -d
+```
+
 Wait for containers to start (first run may take 1-2 minutes to pull images and initialize).

 ---
@@ -300,18 +316,21 @@ Wait for containers to start (first run may take 1-2 minutes to pull images and
 ## Verify Deployment

 ### Check services
+
 ```bash
 docker compose -f docker-compose.prod.yml ps
 # All should show "Up"
 ```

 ### Test API
+
 ```bash
 curl https://api.example.com/health
 # Should return: {"status":"healthy"}
 ```

 ### Test Frontend
+
 - Visit https://app.example.com
 - You should see the Reflector interface
 - Try uploading an audio file to test transcription
@@ -327,6 +346,7 @@ By default, Reflector is open (no login required). **Authentication is required
 See [Authentication Setup](./auth-setup) for full Authentik OAuth configuration.

 Quick summary:
+
 1. Deploy Authentik on your server
 2. Create OAuth provider in Authentik
 3. Extract public key for JWT verification
@@ -358,6 +378,7 @@ DAILYCO_STORAGE_AWS_ROLE_ARN=<arn:aws:iam::ACCOUNT:role/DailyCo>
 ```

 Reload env and restart:
+
 ```bash
 docker compose -f docker-compose.prod.yml up -d server worker
 ```
@@ -367,35 +388,43 @@ docker compose -f docker-compose.prod.yml up -d server worker
 ## Troubleshooting

 ### Check logs for errors
+
 ```bash
 docker compose -f docker-compose.prod.yml logs server --tail 20
 docker compose -f docker-compose.prod.yml logs worker --tail 20
 ```

 ### Services won't start
+
 ```bash
 docker compose -f docker-compose.prod.yml logs
 ```

 ### CORS errors in browser
+
 - Verify `CORS_ORIGIN` in `server/.env` matches your frontend domain exactly (including `https://`)
 - Reload env: `docker compose -f docker-compose.prod.yml up -d server`

-### SSL certificate errors
+### SSL certificate errors (when using Caddy)
+
 - Caddy auto-provisions Let's Encrypt certificates
- Ensure ports 80 and 443 are open
+- Ensure ports 80 and 443 are open and not used by another proxy
 - Check: `docker compose -f docker-compose.prod.yml logs caddy`
+- If port 80 is already in use (e.g. by Coolify), run without Caddy: `docker compose -f docker-compose.prod.yml up -d` and use your existing proxy

 ### Transcription not working
+
 - Check Modal dashboard: https://modal.com/apps
 - Verify URLs in `server/.env` match deployed functions
 - Check worker logs: `docker compose -f docker-compose.prod.yml logs worker`

 ### "Login required" but auth not configured
+
 - Set `FEATURE_REQUIRE_LOGIN=false` in `www/.env`
 - Rebuild frontend: `docker compose -f docker-compose.prod.yml up -d --force-recreate web`

 ### Database migrations or connectivity issues
+
 Migrations run automatically on server startup. To check database connectivity or debug migration failures:

 ```bash
@@ -408,4 +437,3 @@ docker compose -f docker-compose.prod.yml exec server uv run python -c "from ref
 # Manually run migrations (if needed)
 docker compose -f docker-compose.prod.yml exec server uv run alembic upgrade head
 ```
-
--- a/gpu/modal_deployments/deploy-all.sh
+++ b/gpu/modal_deployments/deploy-all.sh
@@ -131,6 +131,15 @@ if [ -z "$DIARIZER_URL" ]; then
 fi
 echo "  -> $DIARIZER_URL"

+echo ""
+echo "Deploying padding (CPU audio processing via Modal SDK)..."
+modal deploy reflector_padding.py
+if [ $? -ne 0 ]; then
+    echo "Error: Failed to deploy padding. Check Modal dashboard for details."
+    exit 1
+fi
+echo "  -> reflector-padding.pad_track (Modal SDK function)"
+
 # --- Output Configuration ---
 echo ""
 echo "=========================================="
@@ -147,4 +156,6 @@ echo ""
 echo "DIARIZATION_BACKEND=modal"
 echo "DIARIZATION_URL=$DIARIZER_URL"
 echo "DIARIZATION_MODAL_API_KEY=$API_KEY"
+echo ""
+echo "# Padding uses Modal SDK (requires MODAL_TOKEN_ID/SECRET in worker containers)"
 echo "# --- End Modal Configuration ---"
--- a/gpu/modal_deployments/reflector_padding.py
+++ b/gpu/modal_deployments/reflector_padding.py
@@ -0,0 +1,277 @@
+"""
+Reflector GPU backend - audio padding
+======================================
+
+CPU-intensive audio padding service for adding silence to audio tracks.
+Uses PyAV filter graph (adelay) for precise track synchronization.
+
+IMPORTANT: This padding logic is duplicated from server/reflector/utils/audio_padding.py
+for Modal deployment isolation (Modal can't import from server/reflector/). If you modify
+the PyAV filter graph or padding algorithm, you MUST update both:
+  - gpu/modal_deployments/reflector_padding.py (this file)
+  - server/reflector/utils/audio_padding.py
+
+Constants duplicated from server/reflector/utils/audio_constants.py for same reason.
+"""
+
+import os
+import tempfile
+from fractions import Fraction
+import math
+import asyncio
+
+import modal
+
+S3_TIMEOUT = 60 # happens 2 times
+PADDING_TIMEOUT = 600 + (S3_TIMEOUT * 2)
+SCALEDOWN_WINDOW = 60  # The maximum duration (in seconds) that individual containers can remain idle when scaling down.
+DISCONNECT_CHECK_INTERVAL = 2  # Check for client disconnect
+
+
+app = modal.App("reflector-padding")
+
+# CPU-based image
+image = (
+    modal.Image.debian_slim(python_version="3.12")
+    .apt_install("ffmpeg")  # Required by PyAV
+    .pip_install(
+        "av==13.1.0",  # PyAV for audio processing
+        "requests==2.32.3",  # HTTP for presigned URL downloads/uploads
+        "fastapi==0.115.12",  # API framework
+    )
+)
+
+# ref B0F71CE8-FC59-4AA5-8414-DAFB836DB711
+OPUS_STANDARD_SAMPLE_RATE = 48000
+# ref B0F71CE8-FC59-4AA5-8414-DAFB836DB711
+OPUS_DEFAULT_BIT_RATE = 128000
+
+
+@app.function(
+    cpu=2.0,
+    timeout=PADDING_TIMEOUT,
+    scaledown_window=SCALEDOWN_WINDOW,
+    image=image,
+)
+@modal.asgi_app()
+def web():
+    from fastapi import FastAPI, Request, HTTPException
+    from pydantic import BaseModel
+
+    class PaddingRequest(BaseModel):
+        track_url: str
+        output_url: str
+        start_time_seconds: float
+        track_index: int
+
+    class PaddingResponse(BaseModel):
+        size: int
+        cancelled: bool = False
+
+    web_app = FastAPI()
+
+    @web_app.post("/pad")
+    async def pad_track_endpoint(request: Request, req: PaddingRequest) -> PaddingResponse:
+        """Modal web endpoint for padding audio tracks with disconnect detection.
+        """
+        import logging
+
+        logging.basicConfig(level=logging.INFO, format="%(asctime)s - %(levelname)s - %(message)s")
+        logger = logging.getLogger(__name__)
+
+        if not req.track_url:
+            raise HTTPException(status_code=400, detail="track_url cannot be empty")
+        if not req.output_url:
+            raise HTTPException(status_code=400, detail="output_url cannot be empty")
+        if req.start_time_seconds <= 0:
+            raise HTTPException(status_code=400, detail=f"start_time_seconds must be positive, got {req.start_time_seconds}")
+        if req.start_time_seconds > 18000:
+            raise HTTPException(status_code=400, detail=f"start_time_seconds exceeds maximum 18000s (5 hours)")
+
+        logger.info(f"Padding request: track {req.track_index}, delay={req.start_time_seconds}s")
+
+        # Thread-safe cancellation flag shared between async disconnect checker and blocking thread
+        import threading
+        cancelled = threading.Event()
+
+        async def check_disconnect():
+            """Background task to check for client disconnect every 2 seconds."""
+            while not cancelled.is_set():
+                await asyncio.sleep(DISCONNECT_CHECK_INTERVAL)
+                if await request.is_disconnected():
+                    logger.warning("Client disconnected, setting cancellation flag")
+                    cancelled.set()
+                    break
+
+        # Start disconnect checker in background
+        disconnect_task = asyncio.create_task(check_disconnect())
+
+        try:
+            result = await asyncio.get_event_loop().run_in_executor(
+                None, _pad_track_blocking, req, cancelled, logger
+            )
+            return PaddingResponse(**result)
+        finally:
+            cancelled.set()
+            disconnect_task.cancel()
+            try:
+                await disconnect_task
+            except asyncio.CancelledError:
+                pass
+
+    def _pad_track_blocking(req, cancelled, logger) -> dict:
+        """Blocking CPU-bound padding work with periodic cancellation checks.
+
+        Args:
+            cancelled: threading.Event for thread-safe cancellation signaling
+        """
+        import av
+        import requests
+        from av.audio.resampler import AudioResampler
+        import time
+
+        temp_dir = tempfile.mkdtemp()
+        input_path = None
+        output_path = None
+        last_check = time.time()
+
+        try:
+            logger.info("Downloading track for padding")
+            response = requests.get(req.track_url, stream=True, timeout=S3_TIMEOUT)
+            response.raise_for_status()
+
+            input_path = os.path.join(temp_dir, "track.webm")
+            total_bytes = 0
+            chunk_count = 0
+            with open(input_path, "wb") as f:
+                for chunk in response.iter_content(chunk_size=8192):
+                    if chunk:
+                        f.write(chunk)
+                        total_bytes += len(chunk)
+                        chunk_count += 1
+
+                        # Check for cancellation every arbitrary amount of chunks
+                        if chunk_count % 12 == 0:
+                            now = time.time()
+                            if now - last_check >= DISCONNECT_CHECK_INTERVAL:
+                                if cancelled.is_set():
+                                    logger.info("Cancelled during download, exiting early")
+                                    return {"size": 0, "cancelled": True}
+                                last_check = now
+            logger.info(f"Track downloaded: {total_bytes} bytes")
+
+            if cancelled.is_set():
+                logger.info("Cancelled after download, exiting early")
+                return {"size": 0, "cancelled": True}
+
+            # Apply padding using PyAV
+            output_path = os.path.join(temp_dir, "padded.webm")
+            delay_ms = math.floor(req.start_time_seconds * 1000)
+            logger.info(f"Padding track {req.track_index} with {delay_ms}ms delay using PyAV")
+
+            in_container = av.open(input_path)
+            in_stream = next((s for s in in_container.streams if s.type == "audio"), None)
+            if in_stream is None:
+                raise ValueError("No audio stream in input")
+
+            with av.open(output_path, "w", format="webm") as out_container:
+                out_stream = out_container.add_stream("libopus", rate=OPUS_STANDARD_SAMPLE_RATE)
+                out_stream.bit_rate = OPUS_DEFAULT_BIT_RATE
+                graph = av.filter.Graph()
+
+                abuf_args = (
+                    f"time_base=1/{OPUS_STANDARD_SAMPLE_RATE}:"
+                    f"sample_rate={OPUS_STANDARD_SAMPLE_RATE}:"
+                    f"sample_fmt=s16:"
+                    f"channel_layout=stereo"
+                )
+                src = graph.add("abuffer", args=abuf_args, name="src")
+                aresample_f = graph.add("aresample", args="async=1", name="ares")
+                delays_arg = f"{delay_ms}|{delay_ms}"
+                adelay_f = graph.add("adelay", args=f"delays={delays_arg}:all=1", name="delay")
+                sink = graph.add("abuffersink", name="sink")
+
+                src.link_to(aresample_f)
+                aresample_f.link_to(adelay_f)
+                adelay_f.link_to(sink)
+                graph.configure()
+
+                resampler = AudioResampler(
+                    format="s16", layout="stereo", rate=OPUS_STANDARD_SAMPLE_RATE
+                )
+
+                for frame in in_container.decode(in_stream):
+                    # Check for cancellation periodically
+                    now = time.time()
+                    if now - last_check >= DISCONNECT_CHECK_INTERVAL:
+                        if cancelled.is_set():
+                            logger.info("Cancelled during processing, exiting early")
+                            in_container.close()
+                            return {"size": 0, "cancelled": True}
+                        last_check = now
+
+                    out_frames = resampler.resample(frame) or []
+                    for rframe in out_frames:
+                        rframe.sample_rate = OPUS_STANDARD_SAMPLE_RATE
+                        rframe.time_base = Fraction(1, OPUS_STANDARD_SAMPLE_RATE)
+                        src.push(rframe)
+
+                        while True:
+                            try:
+                                f_out = sink.pull()
+                            except Exception:
+                                break
+                            f_out.sample_rate = OPUS_STANDARD_SAMPLE_RATE
+                            f_out.time_base = Fraction(1, OPUS_STANDARD_SAMPLE_RATE)
+                            for packet in out_stream.encode(f_out):
+                                out_container.mux(packet)
+
+                # Flush filter graph
+                src.push(None)
+                while True:
+                    try:
+                        f_out = sink.pull()
+                    except Exception:
+                        break
+                    f_out.sample_rate = OPUS_STANDARD_SAMPLE_RATE
+                    f_out.time_base = Fraction(1, OPUS_STANDARD_SAMPLE_RATE)
+                    for packet in out_stream.encode(f_out):
+                        out_container.mux(packet)
+
+                # Flush encoder
+                for packet in out_stream.encode(None):
+                    out_container.mux(packet)
+
+            in_container.close()
+
+            file_size = os.path.getsize(output_path)
+            logger.info(f"Padding complete: {file_size} bytes")
+
+            logger.info("Uploading padded track to S3")
+
+            with open(output_path, "rb") as f:
+                upload_response = requests.put(req.output_url, data=f, timeout=S3_TIMEOUT)
+
+            upload_response.raise_for_status()
+            logger.info(f"Upload complete: {file_size} bytes")
+
+            return {"size": file_size}
+
+        finally:
+            if input_path and os.path.exists(input_path):
+                try:
+                    os.unlink(input_path)
+                except Exception as e:
+                    logger.warning(f"Failed to cleanup input file: {e}")
+            if output_path and os.path.exists(output_path):
+                try:
+                    os.unlink(output_path)
+                except Exception as e:
+                    logger.warning(f"Failed to cleanup output file: {e}")
+            try:
+                os.rmdir(temp_dir)
+            except Exception as e:
+                logger.warning(f"Failed to cleanup temp directory: {e}")
+
+    return web_app
+
--- a/gpu/self_hosted/Dockerfile
+++ b/gpu/self_hosted/Dockerfile
@@ -4,27 +4,31 @@ ENV PYTHONUNBUFFERED=1 \
    UV_LINK_MODE=copy \
    UV_NO_CACHE=1

+# patch until nvidia updates the sha1 repo
+ADD sequoia.config /etc/crypto-policies/back-ends/sequoia.config
+
 WORKDIR /tmp
-RUN apt-get update \
+RUN --mount=type=cache,target=/var/cache/apt,sharing=locked \
+ --mount=type=cache,target=/var/lib/apt,sharing=locked \
+ apt-get update \
 && apt-get install -y \
    ffmpeg \
    curl \
    ca-certificates \
    gnupg \
-    wget \
- && apt-get clean
+    wget
 # Add NVIDIA CUDA repo for Debian 12 (bookworm) and install cuDNN 9 for CUDA 12
 ADD https://developer.download.nvidia.com/compute/cuda/repos/debian12/x86_64/cuda-keyring_1.1-1_all.deb /cuda-keyring.deb
-RUN dpkg -i /cuda-keyring.deb \
+RUN --mount=type=cache,target=/var/cache/apt,sharing=locked \
+ --mount=type=cache,target=/var/lib/apt,sharing=locked \
+ dpkg -i /cuda-keyring.deb \
 && rm /cuda-keyring.deb \
 && apt-get update \
 && apt-get install -y --no-install-recommends \
    cuda-cudart-12-6 \
    libcublas-12-6 \
    libcudnn9-cuda-12 \
-    libcudnn9-dev-cuda-12 \
- && apt-get clean \
- && rm -rf /var/lib/apt/lists/*
+    libcudnn9-dev-cuda-12
 ADD https://astral.sh/uv/install.sh /uv-installer.sh
 RUN sh /uv-installer.sh && rm /uv-installer.sh
 ENV PATH="/root/.local/bin/:$PATH"
@@ -39,6 +43,13 @@ COPY ./app /app/app
 COPY ./main.py /app/
 COPY ./runserver.sh /app/

+# prevent uv failing with too many open files on big cpus
+ENV UV_CONCURRENT_INSTALLS=16
+
+# first install
+RUN --mount=type=cache,target=/root/.cache/uv \
+    uv sync --compile-bytecode --locked
+
 EXPOSE 8000

 CMD ["sh", "/app/runserver.sh"]
--- a/gpu/self_hosted/sequoia.config
+++ b/gpu/self_hosted/sequoia.config
@@ -0,0 +1,2 @@
+[hash_algorithms]
+sha1 = "always"
--- a/server/migrations/versions/3aa20b96d963_drop_use_celery_column.py
+++ b/server/migrations/versions/3aa20b96d963_drop_use_celery_column.py
@@ -0,0 +1,35 @@
+"""drop_use_celery_column
+
+Revision ID: 3aa20b96d963
+Revises: e69f08ead8ea
+Create Date: 2026-02-05 10:12:44.065279
+
+"""
+
+from typing import Sequence, Union
+
+import sqlalchemy as sa
+from alembic import op
+
+# revision identifiers, used by Alembic.
+revision: str = "3aa20b96d963"
+down_revision: Union[str, None] = "e69f08ead8ea"
+branch_labels: Union[str, Sequence[str], None] = None
+depends_on: Union[str, Sequence[str], None] = None
+
+
+def upgrade() -> None:
+    with op.batch_alter_table("room", schema=None) as batch_op:
+        batch_op.drop_column("use_celery")
+
+
+def downgrade() -> None:
+    with op.batch_alter_table("room", schema=None) as batch_op:
+        batch_op.add_column(
+            sa.Column(
+                "use_celery",
+                sa.Boolean(),
+                server_default=sa.text("false"),
+                nullable=False,
+            )
+        )
--- a/server/pyproject.toml
+++ b/server/pyproject.toml
@@ -8,7 +8,7 @@ readme = "README.md"
 dependencies = [
    "aiohttp>=3.9.0",
    "aiohttp-cors>=0.7.0",
-    "av>=10.0.0",
+    "av>=15.0.0",
    "requests>=2.31.0",
    "aiortc>=1.5.0",
    "sortedcontainers>=2.4.0",
--- a/server/reflector/db/calendar_events.py
+++ b/server/reflector/db/calendar_events.py
@@ -104,6 +104,26 @@ class CalendarEventController:
        results = await get_database().fetch_all(query)
        return [CalendarEvent(**result) for result in results]

+    async def get_upcoming_for_rooms(
+        self, room_ids: list[str], minutes_ahead: int = 120
+    ) -> list[CalendarEvent]:
+        now = datetime.now(timezone.utc)
+        future_time = now + timedelta(minutes=minutes_ahead)
+        query = (
+            calendar_events.select()
+            .where(
+                sa.and_(
+                    calendar_events.c.room_id.in_(room_ids),
+                    calendar_events.c.is_deleted == False,
+                    calendar_events.c.start_time <= future_time,
+                    calendar_events.c.end_time >= now,
+                )
+            )
+            .order_by(calendar_events.c.start_time.asc())
+        )
+        results = await get_database().fetch_all(query)
+        return [CalendarEvent(**result) for result in results]
+
    async def get_by_id(self, event_id: str) -> CalendarEvent | None:
        query = calendar_events.select().where(calendar_events.c.id == event_id)
        result = await get_database().fetch_one(query)
--- a/server/reflector/db/meetings.py
+++ b/server/reflector/db/meetings.py
@@ -301,6 +301,23 @@ class MeetingController:
        results = await get_database().fetch_all(query)
        return [Meeting(**result) for result in results]

+    async def get_all_active_for_rooms(
+        self, room_ids: list[str], current_time: datetime
+    ) -> list[Meeting]:
+        query = (
+            meetings.select()
+            .where(
+                sa.and_(
+                    meetings.c.room_id.in_(room_ids),
+                    meetings.c.end_date > current_time,
+                    meetings.c.is_active,
+                )
+            )
+            .order_by(meetings.c.end_date.desc())
+        )
+        results = await get_database().fetch_all(query)
+        return [Meeting(**result) for result in results]
+
    async def get_active_by_calendar_event(
        self, room: Room, calendar_event_id: str, current_time: datetime
    ) -> Meeting | None:
--- a/server/reflector/db/rooms.py
+++ b/server/reflector/db/rooms.py
@@ -57,12 +57,6 @@ rooms = sqlalchemy.Table(
        sqlalchemy.String,
        nullable=False,
    ),
-    sqlalchemy.Column(
-        "use_celery",
-        sqlalchemy.Boolean,
-        nullable=False,
-        server_default=false(),
-    ),
    sqlalchemy.Column(
        "skip_consent",
        sqlalchemy.Boolean,
@@ -97,7 +91,6 @@ class Room(BaseModel):
    ics_last_sync: datetime | None = None
    ics_last_etag: str | None = None
    platform: Platform = Field(default_factory=lambda: settings.DEFAULT_VIDEO_PLATFORM)
-    use_celery: bool = False
    skip_consent: bool = False


@@ -245,6 +238,11 @@ class RoomController:

        return room

+    async def get_by_names(self, names: list[str]) -> list[Room]:
+        query = rooms.select().where(rooms.c.name.in_(names))
+        results = await get_database().fetch_all(query)
+        return [Room(**r) for r in results]
+
    async def get_ics_enabled(self) -> list[Room]:
        query = rooms.select().where(
            rooms.c.ics_enabled == True, rooms.c.ics_url != None
--- a/server/reflector/hatchet/constants.py
+++ b/server/reflector/hatchet/constants.py
@@ -35,7 +35,9 @@ LLM_RATE_LIMIT_PER_SECOND = 10

 # Task execution timeouts (seconds)
 TIMEOUT_SHORT = 60  # Quick operations: API calls, DB updates
-TIMEOUT_MEDIUM = 120  # Single LLM calls, waveform generation
+TIMEOUT_MEDIUM = (
+    300  # Single LLM calls, waveform generation (5m for slow LLM responses)
+)
 TIMEOUT_LONG = 180  # Action items (larger context LLM)
-TIMEOUT_AUDIO = 300  # Audio processing: padding, mixdown
+TIMEOUT_AUDIO = 720  # Audio processing: padding, mixdown
 TIMEOUT_HEAVY = 600  # Transcription, fan-out LLM tasks
--- a/server/reflector/hatchet/workflows/daily_multitrack_pipeline.py
+++ b/server/reflector/hatchet/workflows/daily_multitrack_pipeline.py
@@ -322,6 +322,7 @@ async def get_participants(input: PipelineInput, ctx: Context) -> ParticipantsRe
    mtg_session_id = recording.mtg_session_id
    async with fresh_db_connection():
        from reflector.db.transcripts import (  # noqa: PLC0415
+            TranscriptDuration,
            TranscriptParticipant,
            transcripts_controller,
        )
@@ -330,15 +331,26 @@ async def get_participants(input: PipelineInput, ctx: Context) -> ParticipantsRe
        if not transcript:
            raise ValueError(f"Transcript {input.transcript_id} not found")
        # Note: title NOT cleared - preserves existing titles
+        # Duration from Daily API (seconds -> milliseconds) - master source
+        duration_ms = recording.duration * 1000 if recording.duration else 0
        await transcripts_controller.update(
            transcript,
            {
                "events": [],
                "topics": [],
                "participants": [],
+                "duration": duration_ms,
            },
        )

+        await append_event_and_broadcast(
+            input.transcript_id,
+            transcript,
+            "DURATION",
+            TranscriptDuration(duration=duration_ms),
+            logger=logger,
+        )
+
        mtg_session_id = assert_non_none_and_non_empty(
            mtg_session_id, "mtg_session_id is required"
        )
@@ -1095,7 +1107,7 @@ async def identify_action_items(


@daily_multitrack_pipeline.task(
-    parents=[generate_title, generate_recap, identify_action_items],
+    parents=[process_tracks, generate_title, generate_recap, identify_action_items],
    execution_timeout=timedelta(seconds=TIMEOUT_SHORT),
    retries=3,
 )
@@ -1108,12 +1120,8 @@ async def finalize(input: PipelineInput, ctx: Context) -> FinalizeResult:
    """
    ctx.log("finalize: saving transcript and setting status to 'ended'")

-    mixdown_result = ctx.task_output(mixdown_tracks)
    track_result = ctx.task_output(process_tracks)

-    duration = mixdown_result.duration
-    all_words = track_result.all_words
-
    # Cleanup temporary padded S3 files (deferred until finalize for semantic parity with Celery)
    created_padded_files = track_result.created_padded_files
    if created_padded_files:
@@ -1133,7 +1141,6 @@ async def finalize(input: PipelineInput, ctx: Context) -> FinalizeResult:

    async with fresh_db_connection():
        from reflector.db.transcripts import (  # noqa: PLC0415
-            TranscriptDuration,
            TranscriptText,
            transcripts_controller,
        )
@@ -1142,8 +1149,6 @@ async def finalize(input: PipelineInput, ctx: Context) -> FinalizeResult:
        if transcript is None:
            raise ValueError(f"Transcript {input.transcript_id} not found in database")

-        merged_transcript = TranscriptType(words=all_words, translation=None)
-
        await append_event_and_broadcast(
            input.transcript_id,
            transcript,
@@ -1155,21 +1160,15 @@ async def finalize(input: PipelineInput, ctx: Context) -> FinalizeResult:
            logger=logger,
        )

-        # Save duration and clear workflow_run_id (workflow completed successfully)
-        # Note: title/long_summary/short_summary already saved by their callbacks
+        # Clear workflow_run_id (workflow completed successfully)
+        # Note: title/long_summary/short_summary/duration already saved by their callbacks
        await transcripts_controller.update(
            transcript,
            {
-                "duration": duration,
                "workflow_run_id": None,  # Clear on success - no need to resume
            },
        )

-        duration_data = TranscriptDuration(duration=duration)
-        await append_event_and_broadcast(
-            input.transcript_id, transcript, "DURATION", duration_data, logger=logger
-        )
-
        await set_status_and_broadcast(input.transcript_id, "ended", logger=logger)

        ctx.log(
--- a/server/reflector/hatchet/workflows/padding_workflow.py
+++ b/server/reflector/hatchet/workflows/padding_workflow.py
@@ -0,0 +1,165 @@
+"""
+Hatchet child workflow: PaddingWorkflow
+Handles individual audio track padding via Modal.com backend.
+"""
+
+from datetime import timedelta
+
+import av
+from hatchet_sdk import Context
+from pydantic import BaseModel
+
+from reflector.hatchet.client import HatchetClientManager
+from reflector.hatchet.constants import TIMEOUT_AUDIO
+from reflector.hatchet.workflows.models import PadTrackResult
+from reflector.logger import logger
+from reflector.utils.audio_constants import PRESIGNED_URL_EXPIRATION_SECONDS
+from reflector.utils.audio_padding import extract_stream_start_time_from_container
+
+
+class PaddingInput(BaseModel):
+    """Input for individual track padding."""
+
+    track_index: int
+    s3_key: str
+    bucket_name: str
+    transcript_id: str
+
+
+hatchet = HatchetClientManager.get_client()
+
+padding_workflow = hatchet.workflow(
+    name="PaddingWorkflow", input_validator=PaddingInput
+)
+
+
+@padding_workflow.task(execution_timeout=timedelta(seconds=TIMEOUT_AUDIO), retries=3)
+async def pad_track(input: PaddingInput, ctx: Context) -> PadTrackResult:
+    """Pad audio track with silence based on WebM container start_time."""
+    ctx.log(f"pad_track: track {input.track_index}, s3_key={input.s3_key}")
+    logger.info(
+        "[Hatchet] pad_track",
+        track_index=input.track_index,
+        s3_key=input.s3_key,
+        transcript_id=input.transcript_id,
+    )
+
+    try:
+        # Create fresh storage instance to avoid aioboto3 fork issues
+        from reflector.settings import settings  # noqa: PLC0415
+        from reflector.storage.storage_aws import AwsStorage  # noqa: PLC0415
+
+        storage = AwsStorage(
+            aws_bucket_name=settings.TRANSCRIPT_STORAGE_AWS_BUCKET_NAME,
+            aws_region=settings.TRANSCRIPT_STORAGE_AWS_REGION,
+            aws_access_key_id=settings.TRANSCRIPT_STORAGE_AWS_ACCESS_KEY_ID,
+            aws_secret_access_key=settings.TRANSCRIPT_STORAGE_AWS_SECRET_ACCESS_KEY,
+        )
+
+        source_url = await storage.get_file_url(
+            input.s3_key,
+            operation="get_object",
+            expires_in=PRESIGNED_URL_EXPIRATION_SECONDS,
+            bucket=input.bucket_name,
+        )
+
+        # Extract start_time to determine if padding needed
+        with av.open(source_url) as in_container:
+            if in_container.duration:
+                try:
+                    duration = timedelta(seconds=in_container.duration // 1_000_000)
+                    ctx.log(
+                        f"pad_track: track {input.track_index}, duration={duration}"
+                    )
+                except (ValueError, TypeError, OverflowError) as e:
+                    ctx.log(
+                        f"pad_track: track {input.track_index}, duration error: {str(e)}"
+                    )
+
+            start_time_seconds = extract_stream_start_time_from_container(
+                in_container, input.track_index, logger=logger
+            )
+
+        if start_time_seconds <= 0:
+            logger.info(
+                f"Track {input.track_index} requires no padding",
+                track_index=input.track_index,
+            )
+            return PadTrackResult(
+                padded_key=input.s3_key,
+                bucket_name=input.bucket_name,
+                size=0,
+                track_index=input.track_index,
+            )
+
+        storage_path = f"file_pipeline_hatchet/{input.transcript_id}/tracks/padded_{input.track_index}.webm"
+
+        # Presign PUT URL for output (Modal will upload directly)
+        output_url = await storage.get_file_url(
+            storage_path,
+            operation="put_object",
+            expires_in=PRESIGNED_URL_EXPIRATION_SECONDS,
+        )
+
+        import httpx  # noqa: PLC0415
+
+        from reflector.processors.audio_padding_modal import (  # noqa: PLC0415
+            AudioPaddingModalProcessor,
+        )
+
+        try:
+            processor = AudioPaddingModalProcessor()
+            result = await processor.pad_track(
+                track_url=source_url,
+                output_url=output_url,
+                start_time_seconds=start_time_seconds,
+                track_index=input.track_index,
+            )
+            file_size = result.size
+
+            ctx.log(f"pad_track: Modal returned size={file_size}")
+        except httpx.HTTPStatusError as e:
+            error_detail = e.response.text if hasattr(e.response, "text") else str(e)
+            logger.error(
+                "[Hatchet] Modal padding HTTP error",
+                transcript_id=input.transcript_id,
+                track_index=input.track_index,
+                status_code=e.response.status_code if hasattr(e, "response") else None,
+                error=error_detail,
+                exc_info=True,
+            )
+            raise Exception(
+                f"Modal padding failed: HTTP {e.response.status_code}"
+            ) from e
+        except httpx.TimeoutException as e:
+            logger.error(
+                "[Hatchet] Modal padding timeout",
+                transcript_id=input.transcript_id,
+                track_index=input.track_index,
+                error=str(e),
+                exc_info=True,
+            )
+            raise Exception("Modal padding timeout") from e
+
+        logger.info(
+            "[Hatchet] pad_track complete",
+            track_index=input.track_index,
+            padded_key=storage_path,
+        )
+
+        return PadTrackResult(
+            padded_key=storage_path,
+            bucket_name=None,  # None = use default transcript storage bucket
+            size=file_size,
+            track_index=input.track_index,
+        )
+
+    except Exception as e:
+        logger.error(
+            "[Hatchet] pad_track failed",
+            transcript_id=input.transcript_id,
+            track_index=input.track_index,
+            error=str(e),
+            exc_info=True,
+        )
+        raise
--- a/server/reflector/hatchet/workflows/track_processing.py
+++ b/server/reflector/hatchet/workflows/track_processing.py
@@ -14,9 +14,7 @@ Hatchet workers run in forked processes; fresh imports per task ensure
 storage/DB connections are not shared across forks.
 """

-import tempfile
 from datetime import timedelta
-from pathlib import Path

 import av
 from hatchet_sdk import Context
@@ -27,10 +25,7 @@ from reflector.hatchet.constants import TIMEOUT_AUDIO, TIMEOUT_HEAVY
 from reflector.hatchet.workflows.models import PadTrackResult, TranscribeTrackResult
 from reflector.logger import logger
 from reflector.utils.audio_constants import PRESIGNED_URL_EXPIRATION_SECONDS
-from reflector.utils.audio_padding import (
-    apply_audio_padding_to_file,
-    extract_stream_start_time_from_container,
-)
+from reflector.utils.audio_padding import extract_stream_start_time_from_container


 class TrackInput(BaseModel):
@@ -83,63 +78,44 @@ async def pad_track(input: TrackInput, ctx: Context) -> PadTrackResult:
        )

        with av.open(source_url) as in_container:
-            if in_container.duration:
-                try:
-                    duration = timedelta(seconds=in_container.duration // 1_000_000)
-                    ctx.log(
-                        f"pad_track: track {input.track_index}, duration={duration}"
-                    )
-                except Exception:
-                    ctx.log(f"pad_track: track {input.track_index}, duration=ERROR")
-
            start_time_seconds = extract_stream_start_time_from_container(
                in_container, input.track_index, logger=logger
            )

-            # If no padding needed, return original S3 key
-            if start_time_seconds <= 0:
-                logger.info(
-                    f"Track {input.track_index} requires no padding",
-                    track_index=input.track_index,
-                )
-                return PadTrackResult(
-                    padded_key=input.s3_key,
-                    bucket_name=input.bucket_name,
-                    size=0,
-                    track_index=input.track_index,
-                )
+        # If no padding needed, return original S3 key
+        if start_time_seconds <= 0:
+            logger.info(
+                f"Track {input.track_index} requires no padding",
+                track_index=input.track_index,
+            )
+            return PadTrackResult(
+                padded_key=input.s3_key,
+                bucket_name=input.bucket_name,
+                size=0,
+                track_index=input.track_index,
+            )

-            with tempfile.NamedTemporaryFile(suffix=".webm", delete=False) as temp_file:
-                temp_path = temp_file.name
+        storage_path = f"file_pipeline_hatchet/{input.transcript_id}/tracks/padded_{input.track_index}.webm"

-            try:
-                apply_audio_padding_to_file(
-                    in_container,
-                    temp_path,
-                    start_time_seconds,
-                    input.track_index,
-                    logger=logger,
-                )
+        # Presign PUT URL for output (Modal uploads directly)
+        output_url = await storage.get_file_url(
+            storage_path,
+            operation="put_object",
+            expires_in=PRESIGNED_URL_EXPIRATION_SECONDS,
+        )

-                file_size = Path(temp_path).stat().st_size
-                storage_path = f"file_pipeline_hatchet/{input.transcript_id}/tracks/padded_{input.track_index}.webm"
+        from reflector.processors.audio_padding_modal import (  # noqa: PLC0415
+            AudioPaddingModalProcessor,
+        )

-                logger.info(
-                    f"About to upload padded track",
-                    key=storage_path,
-                    size=file_size,
-                )
-
-                with open(temp_path, "rb") as padded_file:
-                    await storage.put_file(storage_path, padded_file)
-
-                logger.info(
-                    f"Uploaded padded track to S3",
-                    key=storage_path,
-                    size=file_size,
-                )
-            finally:
-                Path(temp_path).unlink(missing_ok=True)
+        processor = AudioPaddingModalProcessor()
+        result = await processor.pad_track(
+            track_url=source_url,
+            output_url=output_url,
+            start_time_seconds=start_time_seconds,
+            track_index=input.track_index,
+        )
+        file_size = result.size

        ctx.log(f"pad_track complete: track {input.track_index} -> {storage_path}")
        logger.info(
--- a/server/reflector/processors/audio_padding_modal.py
+++ b/server/reflector/processors/audio_padding_modal.py
@@ -0,0 +1,113 @@
+"""
+Modal.com backend for audio padding.
+"""
+
+import asyncio
+import os
+
+import httpx
+from pydantic import BaseModel
+
+from reflector.hatchet.constants import TIMEOUT_AUDIO
+from reflector.logger import logger
+
+
+class PaddingResponse(BaseModel):
+    size: int
+    cancelled: bool = False
+
+
+class AudioPaddingModalProcessor:
+    """Audio padding processor using Modal.com CPU backend via HTTP."""
+
+    def __init__(
+        self, padding_url: str | None = None, modal_api_key: str | None = None
+    ):
+        self.padding_url = padding_url or os.getenv("PADDING_URL")
+        if not self.padding_url:
+            raise ValueError(
+                "PADDING_URL required to use AudioPaddingModalProcessor. "
+                "Set PADDING_URL environment variable or pass padding_url parameter."
+            )
+
+        self.modal_api_key = modal_api_key or os.getenv("MODAL_API_KEY")
+
+    async def pad_track(
+        self,
+        track_url: str,
+        output_url: str,
+        start_time_seconds: float,
+        track_index: int,
+    ) -> PaddingResponse:
+        """Pad audio track with silence via Modal backend.
+
+        Args:
+            track_url: Presigned GET URL for source audio track
+            output_url: Presigned PUT URL for output WebM
+            start_time_seconds: Amount of silence to prepend
+            track_index: Track index for logging
+        """
+        if not track_url:
+            raise ValueError("track_url cannot be empty")
+        if start_time_seconds <= 0:
+            raise ValueError(
+                f"start_time_seconds must be positive, got {start_time_seconds}"
+            )
+
+        log = logger.bind(track_index=track_index, padding_seconds=start_time_seconds)
+        log.info("Sending Modal padding HTTP request")
+
+        url = f"{self.padding_url}/pad"
+
+        headers = {}
+        if self.modal_api_key:
+            headers["Authorization"] = f"Bearer {self.modal_api_key}"
+
+        try:
+            async with httpx.AsyncClient(timeout=TIMEOUT_AUDIO) as client:
+                response = await client.post(
+                    url,
+                    headers=headers,
+                    json={
+                        "track_url": track_url,
+                        "output_url": output_url,
+                        "start_time_seconds": start_time_seconds,
+                        "track_index": track_index,
+                    },
+                    follow_redirects=True,
+                )
+
+                if response.status_code != 200:
+                    error_body = response.text
+                    log.error(
+                        "Modal padding API error",
+                        status_code=response.status_code,
+                        error_body=error_body,
+                    )
+
+                response.raise_for_status()
+                result = response.json()
+
+            # Check if work was cancelled
+            if result.get("cancelled"):
+                log.warning("Modal padding was cancelled by disconnect detection")
+                raise asyncio.CancelledError(
+                    "Padding cancelled due to client disconnect"
+                )
+
+            log.info("Modal padding complete", size=result["size"])
+            return PaddingResponse(**result)
+        except asyncio.CancelledError:
+            log.warning(
+                "Modal padding cancelled (Hatchet timeout, disconnect detected on Modal side)"
+            )
+            raise
+        except httpx.TimeoutException as e:
+            log.error("Modal padding timeout", error=str(e), exc_info=True)
+            raise Exception(f"Modal padding timeout: {e}") from e
+        except httpx.HTTPStatusError as e:
+            log.error("Modal padding HTTP error", error=str(e), exc_info=True)
+            raise Exception(f"Modal padding HTTP error: {e}") from e
+        except Exception as e:
+            log.error("Modal padding unexpected error", error=str(e), exc_info=True)
+            raise
--- a/server/reflector/services/transcript_process.py
+++ b/server/reflector/services/transcript_process.py
@@ -15,14 +15,10 @@ from hatchet_sdk.clients.rest.exceptions import ApiException, NotFoundException
 from hatchet_sdk.clients.rest.models import V1TaskStatus

 from reflector.db.recordings import recordings_controller
-from reflector.db.rooms import rooms_controller
 from reflector.db.transcripts import Transcript, transcripts_controller
 from reflector.hatchet.client import HatchetClientManager
 from reflector.logger import logger
 from reflector.pipelines.main_file_pipeline import task_pipeline_file_process
-from reflector.pipelines.main_multitrack_pipeline import (
-    task_pipeline_multitrack_process,
-)
 from reflector.utils.string import NonEmptyString


@@ -181,124 +177,98 @@ async def dispatch_transcript_processing(
    Returns AsyncResult for Celery tasks, None for Hatchet workflows.
    """
    if isinstance(config, MultitrackProcessingConfig):
-        use_celery = False
-        if config.room_id:
-            room = await rooms_controller.get_by_id(config.room_id)
-            use_celery = room.use_celery if room else False
-
-        use_hatchet = not use_celery
-
-        if use_celery:
-            logger.info(
-                "Room uses legacy Celery processing",
-                room_id=config.room_id,
-                transcript_id=config.transcript_id,
+        # Multitrack processing always uses Hatchet (no Celery fallback)
+        # First check if we can replay (outside transaction since it's read-only)
+        transcript = await transcripts_controller.get_by_id(config.transcript_id)
+        if transcript and transcript.workflow_run_id and not force:
+            can_replay = await HatchetClientManager.can_replay(
+                transcript.workflow_run_id
            )
-
-        if use_hatchet:
-            # First check if we can replay (outside transaction since it's read-only)
-            transcript = await transcripts_controller.get_by_id(config.transcript_id)
-            if transcript and transcript.workflow_run_id and not force:
-                can_replay = await HatchetClientManager.can_replay(
-                    transcript.workflow_run_id
+            if can_replay:
+                await HatchetClientManager.replay_workflow(transcript.workflow_run_id)
+                logger.info(
+                    "Replaying Hatchet workflow",
+                    workflow_id=transcript.workflow_run_id,
                )
-                if can_replay:
-                    await HatchetClientManager.replay_workflow(
-                        transcript.workflow_run_id
-                    )
-                    logger.info(
-                        "Replaying Hatchet workflow",
-                        workflow_id=transcript.workflow_run_id,
-                    )
-                    return None
-                else:
-                    # Workflow can't replay (CANCELLED, COMPLETED, or 404 deleted)
-                    # Log and proceed to start new workflow
-                    try:
-                        status = await HatchetClientManager.get_workflow_run_status(
-                            transcript.workflow_run_id
-                        )
-                        logger.info(
-                            "Old workflow not replayable, starting new",
-                            old_workflow_id=transcript.workflow_run_id,
-                            old_status=status.value,
-                        )
-                    except NotFoundException:
-                        # Workflow deleted from Hatchet but ID still in DB
-                        logger.info(
-                            "Old workflow not found in Hatchet, starting new",
-                            old_workflow_id=transcript.workflow_run_id,
-                        )
-
-            # Force: cancel old workflow if exists
-            if force and transcript and transcript.workflow_run_id:
-                try:
-                    await HatchetClientManager.cancel_workflow(
-                        transcript.workflow_run_id
-                    )
-                    logger.info(
-                        "Cancelled old workflow (--force)",
-                        workflow_id=transcript.workflow_run_id,
-                    )
-                except NotFoundException:
-                    logger.info(
-                        "Old workflow already deleted (--force)",
-                        workflow_id=transcript.workflow_run_id,
-                    )
-                await transcripts_controller.update(
-                    transcript, {"workflow_run_id": None}
-                )
-
-            # Re-fetch and check for concurrent dispatch (optimistic approach).
-            # No database lock - worst case is duplicate dispatch, but Hatchet
-            # workflows are idempotent so this is acceptable.
-            transcript = await transcripts_controller.get_by_id(config.transcript_id)
-            if transcript and transcript.workflow_run_id:
-                # Another process started a workflow between validation and now
+                return None
+            else:
+                # Workflow can't replay (CANCELLED, COMPLETED, or 404 deleted)
+                # Log and proceed to start new workflow
                try:
                    status = await HatchetClientManager.get_workflow_run_status(
                        transcript.workflow_run_id
                    )
-                    if status in (V1TaskStatus.RUNNING, V1TaskStatus.QUEUED):
-                        logger.info(
-                            "Concurrent workflow detected, skipping dispatch",
-                            workflow_id=transcript.workflow_run_id,
-                        )
-                        return None
-                except ApiException:
-                    # Workflow might be gone (404) or API issue - proceed with new workflow
-                    pass
+                    logger.info(
+                        "Old workflow not replayable, starting new",
+                        old_workflow_id=transcript.workflow_run_id,
+                        old_status=status.value,
+                    )
+                except NotFoundException:
+                    # Workflow deleted from Hatchet but ID still in DB
+                    logger.info(
+                        "Old workflow not found in Hatchet, starting new",
+                        old_workflow_id=transcript.workflow_run_id,
+                    )

-            workflow_id = await HatchetClientManager.start_workflow(
-                workflow_name="DiarizationPipeline",
-                input_data={
-                    "recording_id": config.recording_id,
-                    "tracks": [{"s3_key": k} for k in config.track_keys],
-                    "bucket_name": config.bucket_name,
-                    "transcript_id": config.transcript_id,
-                    "room_id": config.room_id,
-                },
-                additional_metadata={
-                    "transcript_id": config.transcript_id,
-                    "recording_id": config.recording_id,
-                    "daily_recording_id": config.recording_id,
-                },
+        # Force: cancel old workflow if exists
+        if force and transcript and transcript.workflow_run_id:
+            try:
+                await HatchetClientManager.cancel_workflow(transcript.workflow_run_id)
+                logger.info(
+                    "Cancelled old workflow (--force)",
+                    workflow_id=transcript.workflow_run_id,
+                )
+            except NotFoundException:
+                logger.info(
+                    "Old workflow already deleted (--force)",
+                    workflow_id=transcript.workflow_run_id,
+                )
+            await transcripts_controller.update(transcript, {"workflow_run_id": None})
+
+        # Re-fetch and check for concurrent dispatch (optimistic approach).
+        # No database lock - worst case is duplicate dispatch, but Hatchet
+        # workflows are idempotent so this is acceptable.
+        transcript = await transcripts_controller.get_by_id(config.transcript_id)
+        if transcript and transcript.workflow_run_id:
+            # Another process started a workflow between validation and now
+            try:
+                status = await HatchetClientManager.get_workflow_run_status(
+                    transcript.workflow_run_id
+                )
+                if status in (V1TaskStatus.RUNNING, V1TaskStatus.QUEUED):
+                    logger.info(
+                        "Concurrent workflow detected, skipping dispatch",
+                        workflow_id=transcript.workflow_run_id,
+                    )
+                    return None
+            except ApiException:
+                # Workflow might be gone (404) or API issue - proceed with new workflow
+                pass
+
+        workflow_id = await HatchetClientManager.start_workflow(
+            workflow_name="DiarizationPipeline",
+            input_data={
+                "recording_id": config.recording_id,
+                "tracks": [{"s3_key": k} for k in config.track_keys],
+                "bucket_name": config.bucket_name,
+                "transcript_id": config.transcript_id,
+                "room_id": config.room_id,
+            },
+            additional_metadata={
+                "transcript_id": config.transcript_id,
+                "recording_id": config.recording_id,
+                "daily_recording_id": config.recording_id,
+            },
+        )
+
+        if transcript:
+            await transcripts_controller.update(
+                transcript, {"workflow_run_id": workflow_id}
            )

-            if transcript:
-                await transcripts_controller.update(
-                    transcript, {"workflow_run_id": workflow_id}
-                )
+        logger.info("Hatchet workflow dispatched", workflow_id=workflow_id)
+        return None

-            logger.info("Hatchet workflow dispatched", workflow_id=workflow_id)
-            return None
-
-        # Celery pipeline (durable workflows disabled)
-        return task_pipeline_multitrack_process.delay(
-            transcript_id=config.transcript_id,
-            bucket_name=config.bucket_name,
-            track_keys=config.track_keys,
-        )
    elif isinstance(config, FileProcessingConfig):
        return task_pipeline_file_process.delay(transcript_id=config.transcript_id)
    else:
--- a/server/reflector/settings.py
+++ b/server/reflector/settings.py
@@ -1,7 +1,7 @@
 from pydantic.types import PositiveInt
 from pydantic_settings import BaseSettings, SettingsConfigDict

-from reflector.schemas.platform import WHEREBY_PLATFORM, Platform
+from reflector.schemas.platform import DAILY_PLATFORM, Platform
 from reflector.utils.string import NonEmptyString


@@ -98,6 +98,10 @@ class Settings(BaseSettings):
    # Diarization: local pyannote.audio
    DIARIZATION_PYANNOTE_AUTH_TOKEN: str | None = None

+    # Audio Padding (Modal.com backend)
+    PADDING_URL: str | None = None
+    PADDING_MODAL_API_KEY: str | None = None
+
    # Sentry
    SENTRY_DSN: str | None = None

@@ -151,7 +155,7 @@ class Settings(BaseSettings):
        None  # Webhook UUID for this environment. Not used by production code
    )
    # Platform Configuration
-    DEFAULT_VIDEO_PLATFORM: Platform = WHEREBY_PLATFORM
+    DEFAULT_VIDEO_PLATFORM: Platform = DAILY_PLATFORM

    # Zulip integration
    ZULIP_REALM: str | None = None
--- a/server/reflector/utils/audio_constants.py
+++ b/server/reflector/utils/audio_constants.py
@@ -5,7 +5,9 @@ Used by both Hatchet workflows and Celery pipelines for consistent audio encodin
 """

 # Opus codec settings
+# ref B0F71CE8-FC59-4AA5-8414-DAFB836DB711
 OPUS_STANDARD_SAMPLE_RATE = 48000
+# ref B0F71CE8-FC59-4AA5-8414-DAFB836DB711
 OPUS_DEFAULT_BIT_RATE = 128000  # 128kbps for good speech quality

 # S3 presigned URL expiration
--- a/server/reflector/views/rooms.py
+++ b/server/reflector/views/rooms.py
@@ -1,4 +1,6 @@
+import asyncio
 import logging
+from collections import defaultdict
 from datetime import datetime, timedelta, timezone
 from enum import Enum
 from typing import Annotated, Any, Literal, Optional
@@ -6,13 +8,14 @@ from typing import Annotated, Any, Literal, Optional
 from fastapi import APIRouter, Depends, HTTPException
 from fastapi_pagination import Page
 from fastapi_pagination.ext.databases import apaginate
-from pydantic import BaseModel
+from pydantic import BaseModel, Field
 from redis.exceptions import LockError

 import reflector.auth as auth
 from reflector.db import get_database
 from reflector.db.calendar_events import calendar_events_controller
 from reflector.db.meetings import meetings_controller
+from reflector.db.rooms import Room as DbRoom
 from reflector.db.rooms import rooms_controller
 from reflector.redis_cache import RedisAsyncLock
 from reflector.schemas.platform import Platform
@@ -195,6 +198,69 @@ async def rooms_list(
    return paginated


+class BulkStatusRequest(BaseModel):
+    room_names: list[str] = Field(max_length=100)
+
+
+class RoomMeetingStatus(BaseModel):
+    active_meetings: list[Meeting]
+    upcoming_events: list[CalendarEventResponse]
+
+
+@router.post("/rooms/meetings/bulk-status", response_model=dict[str, RoomMeetingStatus])
+async def rooms_bulk_meeting_status(
+    request: BulkStatusRequest,
+    user: Annotated[Optional[auth.UserInfo], Depends(auth.current_user_optional)],
+):
+    user_id = user["sub"] if user else None
+
+    all_rooms = await rooms_controller.get_by_names(request.room_names)
+    # Filter to rooms the user can see (owned or shared), matching rooms_list behavior
+    rooms = [
+        r
+        for r in all_rooms
+        if r.is_shared or (user_id is not None and r.user_id == user_id)
+    ]
+    room_by_id: dict[str, DbRoom] = {r.id: r for r in rooms}
+    room_ids = list(room_by_id.keys())
+
+    current_time = datetime.now(timezone.utc)
+    active_meetings, upcoming_events = await asyncio.gather(
+        meetings_controller.get_all_active_for_rooms(room_ids, current_time),
+        calendar_events_controller.get_upcoming_for_rooms(room_ids),
+    )
+
+    # Group by room name
+    active_by_room: dict[str, list[Meeting]] = defaultdict(list)
+    for m in active_meetings:
+        room = room_by_id.get(m.room_id)
+        if not room:
+            continue
+        m.platform = room.platform
+        if user_id != room.user_id and m.platform == "whereby":
+            m.host_room_url = ""
+        active_by_room[room.name].append(m)
+
+    upcoming_by_room: dict[str, list[CalendarEventResponse]] = defaultdict(list)
+    for e in upcoming_events:
+        room = room_by_id.get(e.room_id)
+        if not room:
+            continue
+        if user_id != room.user_id:
+            e.description = None
+            e.attendees = None
+        upcoming_by_room[room.name].append(e)
+
+    result: dict[str, RoomMeetingStatus] = {}
+    for name in request.room_names:
+        result[name] = RoomMeetingStatus(
+            active_meetings=active_by_room.get(name, []),
+            upcoming_events=upcoming_by_room.get(name, []),
+        )
+
+    return result
+
+
@router.get("/rooms/{room_id}", response_model=RoomDetails)
 async def rooms_get(
    room_id: str,
--- a/server/reflector/worker/process.py
+++ b/server/reflector/worker/process.py
@@ -27,9 +27,6 @@ from reflector.db.transcripts import (
 from reflector.hatchet.client import HatchetClientManager
 from reflector.pipelines.main_file_pipeline import task_pipeline_file_process
 from reflector.pipelines.main_live_pipeline import asynctask
-from reflector.pipelines.main_multitrack_pipeline import (
-    task_pipeline_multitrack_process,
-)
 from reflector.pipelines.topic_processing import EmptyPipeline
 from reflector.processors import AudioFileWriterProcessor
 from reflector.processors.audio_waveform_processor import AudioWaveformProcessor
@@ -351,49 +348,29 @@ async def _process_multitrack_recording_inner(
            room_id=room.id,
        )

-    use_celery = room and room.use_celery
-    use_hatchet = not use_celery
-
-    if use_celery:
-        logger.info(
-            "Room uses legacy Celery processing",
-            room_id=room.id,
-            transcript_id=transcript.id,
-        )
-
-    if use_hatchet:
-        workflow_id = await HatchetClientManager.start_workflow(
-            workflow_name="DiarizationPipeline",
-            input_data={
-                "recording_id": recording_id,
-                "tracks": [{"s3_key": k} for k in filter_cam_audio_tracks(track_keys)],
-                "bucket_name": bucket_name,
-                "transcript_id": transcript.id,
-                "room_id": room.id,
-            },
-            additional_metadata={
-                "transcript_id": transcript.id,
-                "recording_id": recording_id,
-                "daily_recording_id": recording_id,
-            },
-        )
-        logger.info(
-            "Started Hatchet workflow",
-            workflow_id=workflow_id,
-            transcript_id=transcript.id,
-        )
-
-        await transcripts_controller.update(
-            transcript, {"workflow_run_id": workflow_id}
-        )
-        return
-
-    # Celery pipeline (runs when durable workflows disabled)
-    task_pipeline_multitrack_process.delay(
-        transcript_id=transcript.id,
-        bucket_name=bucket_name,
-        track_keys=filter_cam_audio_tracks(track_keys),
+    # Multitrack processing always uses Hatchet (no Celery fallback)
+    workflow_id = await HatchetClientManager.start_workflow(
+        workflow_name="DiarizationPipeline",
+        input_data={
+            "recording_id": recording_id,
+            "tracks": [{"s3_key": k} for k in filter_cam_audio_tracks(track_keys)],
+            "bucket_name": bucket_name,
+            "transcript_id": transcript.id,
+            "room_id": room.id,
+        },
+        additional_metadata={
+            "transcript_id": transcript.id,
+            "recording_id": recording_id,
+            "daily_recording_id": recording_id,
+        },
    )
+    logger.info(
+        "Started Hatchet workflow",
+        workflow_id=workflow_id,
+        transcript_id=transcript.id,
+    )
+
+    await transcripts_controller.update(transcript, {"workflow_run_id": workflow_id})


@shared_task
@@ -1072,66 +1049,43 @@ async def reprocess_failed_daily_recordings():
                )
                continue

-            use_celery = room and room.use_celery
-            use_hatchet = not use_celery
-
-            if use_hatchet:
-                if not transcript:
-                    logger.warning(
-                        "No transcript for Hatchet reprocessing, skipping",
-                        recording_id=recording.id,
-                    )
-                    continue
-
-                workflow_id = await HatchetClientManager.start_workflow(
-                    workflow_name="DiarizationPipeline",
-                    input_data={
-                        "recording_id": recording.id,
-                        "tracks": [
-                            {"s3_key": k}
-                            for k in filter_cam_audio_tracks(recording.track_keys)
-                        ],
-                        "bucket_name": bucket_name,
-                        "transcript_id": transcript.id,
-                        "room_id": room.id if room else None,
-                    },
-                    additional_metadata={
-                        "transcript_id": transcript.id,
-                        "recording_id": recording.id,
-                        "reprocess": True,
-                    },
-                )
-                await transcripts_controller.update(
-                    transcript, {"workflow_run_id": workflow_id}
-                )
-
-                logger.info(
-                    "Queued Daily recording for Hatchet reprocessing",
+            # Multitrack reprocessing always uses Hatchet (no Celery fallback)
+            if not transcript:
+                logger.warning(
+                    "No transcript for Hatchet reprocessing, skipping",
                    recording_id=recording.id,
-                    workflow_id=workflow_id,
-                    room_name=meeting.room_name,
-                    track_count=len(recording.track_keys),
-                )
-            else:
-                logger.info(
-                    "Queueing Daily recording for Celery reprocessing",
-                    recording_id=recording.id,
-                    room_name=meeting.room_name,
-                    track_count=len(recording.track_keys),
-                    transcript_status=transcript.status if transcript else None,
                )
+                continue

-                # For reprocessing, pass actual recording time (though it's ignored - see _process_multitrack_recording_inner)
-                # Reprocessing uses recording.meeting_id directly instead of time-based matching
-                recording_start_ts = int(recording.recorded_at.timestamp())
+            workflow_id = await HatchetClientManager.start_workflow(
+                workflow_name="DiarizationPipeline",
+                input_data={
+                    "recording_id": recording.id,
+                    "tracks": [
+                        {"s3_key": k}
+                        for k in filter_cam_audio_tracks(recording.track_keys)
+                    ],
+                    "bucket_name": bucket_name,
+                    "transcript_id": transcript.id,
+                    "room_id": room.id if room else None,
+                },
+                additional_metadata={
+                    "transcript_id": transcript.id,
+                    "recording_id": recording.id,
+                    "reprocess": True,
+                },
+            )
+            await transcripts_controller.update(
+                transcript, {"workflow_run_id": workflow_id}
+            )

-                process_multitrack_recording.delay(
-                    bucket_name=bucket_name,
-                    daily_room_name=meeting.room_name,
-                    recording_id=recording.id,
-                    track_keys=recording.track_keys,
-                    recording_start_ts=recording_start_ts,
-                )
+            logger.info(
+                "Queued Daily recording for Hatchet reprocessing",
+                recording_id=recording.id,
+                workflow_id=workflow_id,
+                room_name=meeting.room_name,
+                track_count=len(recording.track_keys),
+            )

            reprocessed_count += 1

--- a/server/reflector/ws_manager.py
+++ b/server/reflector/ws_manager.py
@@ -11,7 +11,6 @@ broadcast messages to all connected websockets.

 import asyncio
 import json
-import threading

 import redis.asyncio as redis
 from fastapi import WebSocket
@@ -98,6 +97,7 @@ class WebsocketManager:

    async def _pubsub_data_reader(self, pubsub_subscriber):
        while True:
+            # timeout=1.0 prevents tight CPU loop when no messages available
            message = await pubsub_subscriber.get_message(
                ignore_subscribe_messages=True
            )
@@ -109,29 +109,38 @@ class WebsocketManager:
                    await socket.send_json(data)


+# Process-global singleton to ensure only one WebsocketManager instance exists.
+# Multiple instances would cause resource leaks and CPU issues.
+_ws_manager: WebsocketManager | None = None
+
+
 def get_ws_manager() -> WebsocketManager:
    """
-    Returns the WebsocketManager instance for managing websockets.
+    Returns the global WebsocketManager singleton.

-    This function initializes and returns the WebsocketManager instance,
-    which is responsible for managing websockets and handling websocket
-    connections.
+    Creates instance on first call, subsequent calls return cached instance.
+    Thread-safe via GIL. Concurrent initialization may create duplicate
+    instances but last write wins (acceptable for this use case).

    Returns:
-        WebsocketManager: The initialized WebsocketManager instance.
-
-    Raises:
-        ImportError: If the 'reflector.settings' module cannot be imported.
-        RedisConnectionError: If there is an error connecting to the Redis server.
+        WebsocketManager: The global WebsocketManager instance.
    """
-    local = threading.local()
-    if hasattr(local, "ws_manager"):
-        return local.ws_manager
+    global _ws_manager

+    if _ws_manager is not None:
+        return _ws_manager
+
+    # No lock needed - GIL makes this safe enough
+    # Worst case: race creates two instances, last assignment wins
    pubsub_client = RedisPubSubManager(
        host=settings.REDIS_HOST,
        port=settings.REDIS_PORT,
    )
-    ws_manager = WebsocketManager(pubsub_client=pubsub_client)
-    local.ws_manager = ws_manager
-    return ws_manager
+    _ws_manager = WebsocketManager(pubsub_client=pubsub_client)
+    return _ws_manager
+
+
+def reset_ws_manager() -> None:
+    """Reset singleton for testing. DO NOT use in production."""
+    global _ws_manager
+    _ws_manager = None
--- a/server/tests/conftest.py
+++ b/server/tests/conftest.py
@@ -1,11 +1,10 @@
 import os
 from contextlib import asynccontextmanager
-from tempfile import NamedTemporaryFile
 from unittest.mock import patch

 import pytest

-from reflector.schemas.platform import WHEREBY_PLATFORM
+from reflector.schemas.platform import DAILY_PLATFORM, WHEREBY_PLATFORM


@pytest.fixture(scope="session", autouse=True)
@@ -15,6 +14,7 @@ def register_mock_platform():
    from reflector.video_platforms.registry import register_platform

    register_platform(WHEREBY_PLATFORM, MockPlatformClient)
+    register_platform(DAILY_PLATFORM, MockPlatformClient)
    yield


@@ -333,11 +333,14 @@ def celery_enable_logging():

@pytest.fixture(scope="session")
 def celery_config():
-    with NamedTemporaryFile() as f:
-        yield {
-            "broker_url": "memory://",
-            "result_backend": f"db+sqlite:///{f.name}",
-        }
+    redis_host = os.environ.get("REDIS_HOST", "localhost")
+    redis_port = os.environ.get("REDIS_PORT", "6379")
+    # Use db 2 to avoid conflicts with main app
+    redis_url = f"redis://{redis_host}:{redis_port}/2"
+    yield {
+        "broker_url": redis_url,
+        "result_backend": redis_url,
+    }


@pytest.fixture(scope="session")
@@ -370,9 +373,12 @@ async def ws_manager_in_memory(monkeypatch):
        def __init__(self, queue: asyncio.Queue):
            self.queue = queue

-        async def get_message(self, ignore_subscribe_messages: bool = True):
+        async def get_message(
+            self, ignore_subscribe_messages: bool = True, timeout: float | None = None
+        ):
+            wait_timeout = timeout if timeout is not None else 0.05
            try:
-                return await asyncio.wait_for(self.queue.get(), timeout=0.05)
+                return await asyncio.wait_for(self.queue.get(), timeout=wait_timeout)
            except Exception:
                return None

--- a/server/tests/test_transcripts_process.py
+++ b/server/tests/test_transcripts_process.py
@@ -1,6 +1,6 @@
 import asyncio
 import time
-from unittest.mock import patch
+from unittest.mock import AsyncMock, patch

 import pytest
 from httpx import ASGITransport, AsyncClient
@@ -142,17 +142,17 @@ async def test_whereby_recording_uses_file_pipeline(client):
            "reflector.services.transcript_process.task_pipeline_file_process"
        ) as mock_file_pipeline,
        patch(
-            "reflector.services.transcript_process.task_pipeline_multitrack_process"
-        ) as mock_multitrack_pipeline,
+            "reflector.services.transcript_process.HatchetClientManager"
+        ) as mock_hatchet,
    ):
        response = await client.post(f"/transcripts/{transcript.id}/process")

        assert response.status_code == 200
        assert response.json()["status"] == "ok"

-        # Whereby recordings should use file pipeline
+        # Whereby recordings should use file pipeline, not Hatchet
        mock_file_pipeline.delay.assert_called_once_with(transcript_id=transcript.id)
-        mock_multitrack_pipeline.delay.assert_not_called()
+        mock_hatchet.start_workflow.assert_not_called()


@pytest.mark.usefixtures("setup_database")
@@ -177,8 +177,6 @@ async def test_dailyco_recording_uses_multitrack_pipeline(client):
        recording_trigger="automatic-2nd-participant",
        is_shared=False,
    )
-    # Force Celery backend for test
-    await rooms_controller.update(room, {"use_celery": True})

    transcript = await transcripts_controller.add(
        "",
@@ -213,18 +211,23 @@ async def test_dailyco_recording_uses_multitrack_pipeline(client):
            "reflector.services.transcript_process.task_pipeline_file_process"
        ) as mock_file_pipeline,
        patch(
-            "reflector.services.transcript_process.task_pipeline_multitrack_process"
-        ) as mock_multitrack_pipeline,
+            "reflector.services.transcript_process.HatchetClientManager"
+        ) as mock_hatchet,
    ):
+        mock_hatchet.start_workflow = AsyncMock(return_value="test-workflow-id")
+
        response = await client.post(f"/transcripts/{transcript.id}/process")

        assert response.status_code == 200
        assert response.json()["status"] == "ok"

-        # Daily.co multitrack recordings should use multitrack pipeline
-        mock_multitrack_pipeline.delay.assert_called_once_with(
-            transcript_id=transcript.id,
-            bucket_name="daily-bucket",
-            track_keys=track_keys,
-        )
+        # Daily.co multitrack recordings should use Hatchet workflow
+        mock_hatchet.start_workflow.assert_called_once()
+        call_kwargs = mock_hatchet.start_workflow.call_args.kwargs
+        assert call_kwargs["workflow_name"] == "DiarizationPipeline"
+        assert call_kwargs["input_data"]["transcript_id"] == transcript.id
+        assert call_kwargs["input_data"]["bucket_name"] == "daily-bucket"
+        assert call_kwargs["input_data"]["tracks"] == [
+            {"s3_key": k} for k in track_keys
+        ]
        mock_file_pipeline.delay.assert_not_called()
--- a/server/tests/test_transcripts_rtc_ws.py
+++ b/server/tests/test_transcripts_rtc_ws.py
@@ -115,9 +115,7 @@ def appserver(tmpdir, setup_database, celery_session_app, celery_session_worker)
    settings.DATA_DIR = DATA_DIR


-@pytest.fixture(scope="session")
-def celery_includes():
-    return ["reflector.pipelines.main_live_pipeline"]
+# Using celery_includes from conftest.py which includes both pipelines


@pytest.mark.usefixtures("setup_database")
--- a/server/tests/test_user_websocket_auth.py
+++ b/server/tests/test_user_websocket_auth.py
@@ -56,7 +56,12 @@ def appserver_ws_user(setup_database):

    if server_instance:
        server_instance.should_exit = True
-        server_thread.join(timeout=30)
+        server_thread.join(timeout=2.0)
+
+    # Reset global singleton for test isolation
+    from reflector.ws_manager import reset_ws_manager
+
+    reset_ws_manager()


@pytest.fixture(autouse=True)
@@ -133,6 +138,8 @@ async def test_user_ws_accepts_valid_token_and_receives_events(appserver_ws_user

    # Connect and then trigger an event via HTTP create
    async with aconnect_ws(base_ws, subprotocols=subprotocols) as ws:
+        await asyncio.sleep(0.2)
+
        # Emit an event to the user's room via a standard HTTP action
        from httpx import AsyncClient

@@ -150,6 +157,7 @@ async def test_user_ws_accepts_valid_token_and_receives_events(appserver_ws_user
            "email": "user-abc@example.com",
        }

+        # Use in-memory client (global singleton makes it share ws_manager)
        async with AsyncClient(app=app, base_url=f"http://{host}:{port}/v1") as ac:
            # Create a transcript as this user so that the server publishes TRANSCRIPT_CREATED to user room
            resp = await ac.post("/transcripts", json={"name": "WS Test"})
--- a/server/uv.lock
+++ b/server/uv.lock
@@ -159,21 +159,20 @@ wheels = [

 [[package]]
 name = "aiortc"
-version = "1.13.0"
+version = "1.14.0"
 source = { registry = "https://pypi.org/simple" }
 dependencies = [
    { name = "aioice" },
    { name = "av" },
-    { name = "cffi" },
    { name = "cryptography" },
    { name = "google-crc32c" },
    { name = "pyee" },
    { name = "pylibsrtp" },
    { name = "pyopenssl" },
 ]
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+sdist = { url = "https://files.pythonhosted.org/packages/51/9c/4e027bfe0195de0442da301e2389329496745d40ae44d2d7c4571c4290ce/aiortc-1.14.0.tar.gz", hash = "sha256:adc8a67ace10a085721e588e06a00358ed8eaf5f6b62f0a95358ff45628dd762", size = 1180864 }
 wheels = [
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+    { url = "https://files.pythonhosted.org/packages/57/ab/31646a49209568cde3b97eeade0d28bb78b400e6645c56422c101df68932/aiortc-1.14.0-py3-none-any.whl", hash = "sha256:4b244d7e482f4e1f67e685b3468269628eca1ec91fa5b329ab517738cfca086e", size = 93183 },
 ]

 [[package]]
@@ -327,28 +326,24 @@ wheels = [

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-version = "14.4.0"
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 wheels = [
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 ]

 [[package]]
@@ -3267,7 +3262,7 @@ requires-dist = [
    { name = "aiohttp-cors", specifier = ">=0.7.0" },
    { name = "aiortc", specifier = ">=1.5.0" },
    { name = "alembic", specifier = ">=1.11.3" },
-    { name = "av", specifier = ">=10.0.0" },
+    { name = "av", specifier = ">=15.0.0" },
    { name = "celery", specifier = ">=5.3.4" },
    { name = "databases", extras = ["aiosqlite", "asyncpg"], specifier = ">=0.7.0" },
    { name = "fastapi", extras = ["standard"], specifier = ">=0.100.1" },
--- a/www/app/lib/tests/meetingStatusBatcher.test.tsx
+++ b/www/app/lib/tests/meetingStatusBatcher.test.tsx
@@ -0,0 +1,217 @@
+import "@testing-library/jest-dom";
+
+// --- Module mocks (hoisted before imports) ---
+
+jest.mock("../apiClient", () => ({
+  client: {
+    GET: jest.fn(),
+    POST: jest.fn(),
+    PUT: jest.fn(),
+    PATCH: jest.fn(),
+    DELETE: jest.fn(),
+    use: jest.fn(),
+  },
+  $api: {
+    useQuery: jest.fn(),
+    useMutation: jest.fn(),
+    queryOptions: (method: string, path: string, init?: unknown) =>
+      init === undefined
+        ? { queryKey: [method, path] }
+        : { queryKey: [method, path, init] },
+  },
+  API_URL: "http://test",
+  WEBSOCKET_URL: "ws://test",
+  configureApiAuth: jest.fn(),
+}));
+
+jest.mock("../AuthProvider", () => ({
+  useAuth: () => ({
+    status: "authenticated" as const,
+    accessToken: "test-token",
+    accessTokenExpires: Date.now() + 3600000,
+    user: { id: "user1", name: "Test User" },
+    update: jest.fn(),
+    signIn: jest.fn(),
+    signOut: jest.fn(),
+    lastUserId: "user1",
+  }),
+}));
+
+// Recreate the batcher with a 0ms window. setTimeout(fn, 0) defers to the next
+// macrotask boundary — after all synchronous React rendering completes. All
+// useQuery queryFns fire within the same macrotask, so they all queue into one
+// batch before the timer fires. This is deterministic and avoids fake timers.
+jest.mock("../meetingStatusBatcher", () => {
+  const actual = jest.requireActual("../meetingStatusBatcher");
+  return {
+    ...actual,
+    meetingStatusBatcher: actual.createMeetingStatusBatcher(0),
+  };
+});
+
+// --- Imports (after mocks) ---
+
+import React from "react";
+import { render, waitFor, screen } from "@testing-library/react";
+import { QueryClient, QueryClientProvider } from "@tanstack/react-query";
+import { useRoomActiveMeetings, useRoomUpcomingMeetings } from "../apiHooks";
+import { client } from "../apiClient";
+import { ErrorProvider } from "../../(errors)/errorContext";
+
+const mockClient = client as { POST: jest.Mock };
+
+// --- Helpers ---
+
+function mockBulkStatusEndpoint(
+  roomData?: Record<
+    string,
+    { active_meetings: unknown[]; upcoming_events: unknown[] }
+  >,
+) {
+  mockClient.POST.mockImplementation(
+    async (_path: string, options: { body: { room_names: string[] } }) => {
+      const roomNames: string[] = options.body.room_names;
+      const src = roomData ?? {};
+      const data = Object.fromEntries(
+        roomNames.map((name) => [
+          name,
+          src[name] ?? { active_meetings: [], upcoming_events: [] },
+        ]),
+      );
+      return { data, error: undefined, response: {} };
+    },
+  );
+}
+
+// --- Test component: renders N room cards, each using both hooks ---
+
+function RoomCard({ roomName }: { roomName: string }) {
+  const active = useRoomActiveMeetings(roomName);
+  const upcoming = useRoomUpcomingMeetings(roomName);
+
+  if (active.isLoading || upcoming.isLoading) {
+    return <div data-testid={`room-${roomName}`}>loading</div>;
+  }
+
+  return (
+    <div data-testid={`room-${roomName}`}>
+      {active.data?.length ?? 0} active, {upcoming.data?.length ?? 0} upcoming
+    </div>
+  );
+}
+
+function RoomList({ roomNames }: { roomNames: string[] }) {
+  return (
+    <>
+      {roomNames.map((name) => (
+        <RoomCard key={name} roomName={name} />
+      ))}
+    </>
+  );
+}
+
+function createWrapper() {
+  const queryClient = new QueryClient({
+    defaultOptions: {
+      queries: { retry: false },
+    },
+  });
+  return function Wrapper({ children }: { children: React.ReactNode }) {
+    return (
+      <QueryClientProvider client={queryClient}>
+        <ErrorProvider>{children}</ErrorProvider>
+      </QueryClientProvider>
+    );
+  };
+}
+
+// --- Tests ---
+
+describe("meeting status batcher integration", () => {
+  afterEach(() => jest.clearAllMocks());
+
+  it("batches multiple room queries into a single POST request", async () => {
+    const rooms = Array.from({ length: 10 }, (_, i) => `room-${i}`);
+
+    mockBulkStatusEndpoint();
+
+    render(<RoomList roomNames={rooms} />, { wrapper: createWrapper() });
+
+    await waitFor(() => {
+      for (const name of rooms) {
+        expect(screen.getByTestId(`room-${name}`)).toHaveTextContent(
+          "0 active, 0 upcoming",
+        );
+      }
+    });
+
+    const postCalls = mockClient.POST.mock.calls.filter(
+      ([path]: [string]) => path === "/v1/rooms/meetings/bulk-status",
+    );
+
+    // Without batching this would be 20 calls (2 hooks x 10 rooms).
+    expect(postCalls).toHaveLength(1);
+
+    // The single call should contain all 10 rooms (deduplicated)
+    const requestedRooms: string[] = postCalls[0][1].body.room_names;
+    for (const name of rooms) {
+      expect(requestedRooms).toContain(name);
+    }
+  });
+
+  it("batcher fetcher returns room-specific data", async () => {
+    const {
+      meetingStatusBatcher: batcher,
+    } = require("../meetingStatusBatcher");
+
+    mockBulkStatusEndpoint({
+      "room-a": {
+        active_meetings: [{ id: "m1", room_name: "room-a" }],
+        upcoming_events: [],
+      },
+      "room-b": {
+        active_meetings: [],
+        upcoming_events: [{ id: "e1", title: "Standup" }],
+      },
+    });
+
+    const [resultA, resultB] = await Promise.all([
+      batcher.fetch("room-a"),
+      batcher.fetch("room-b"),
+    ]);
+
+    expect(mockClient.POST).toHaveBeenCalledTimes(1);
+    expect(resultA.active_meetings).toEqual([
+      { id: "m1", room_name: "room-a" },
+    ]);
+    expect(resultA.upcoming_events).toEqual([]);
+    expect(resultB.active_meetings).toEqual([]);
+    expect(resultB.upcoming_events).toEqual([{ id: "e1", title: "Standup" }]);
+  });
+
+  it("renders room-specific meeting data through hooks", async () => {
+    mockBulkStatusEndpoint({
+      "room-a": {
+        active_meetings: [{ id: "m1", room_name: "room-a" }],
+        upcoming_events: [],
+      },
+      "room-b": {
+        active_meetings: [],
+        upcoming_events: [{ id: "e1", title: "Standup" }],
+      },
+    });
+
+    render(<RoomList roomNames={["room-a", "room-b"]} />, {
+      wrapper: createWrapper(),
+    });
+
+    await waitFor(() => {
+      expect(screen.getByTestId("room-room-a")).toHaveTextContent(
+        "1 active, 0 upcoming",
+      );
+      expect(screen.getByTestId("room-room-b")).toHaveTextContent(
+        "0 active, 1 upcoming",
+      );
+    });
+  });
+});
--- a/www/app/lib/apiHooks.ts
+++ b/www/app/lib/apiHooks.ts
@@ -2,9 +2,10 @@

 import { $api } from "./apiClient";
 import { useError } from "../(errors)/errorContext";
-import { QueryClient, useQueryClient } from "@tanstack/react-query";
+import { QueryClient, useQuery, useQueryClient } from "@tanstack/react-query";
 import type { components } from "../reflector-api";
 import { useAuth } from "./AuthProvider";
+import { meetingStatusBatcher } from "./meetingStatusBatcher";
 import { MeetingId } from "./types";
 import { NonEmptyString } from "./utils";

@@ -697,15 +698,7 @@ export function useRoomsCreateMeeting() {
          queryKey: $api.queryOptions("get", "/v1/rooms").queryKey,
        }),
        queryClient.invalidateQueries({
-          queryKey: $api.queryOptions(
-            "get",
-            "/v1/rooms/{room_name}/meetings/active" satisfies `/v1/rooms/{room_name}/${typeof MEETINGS_ACTIVE_PATH_PARTIAL}`,
-            {
-              params: {
-                path: { room_name: roomName },
-              },
-            },
-          ).queryKey,
+          queryKey: meetingStatusKeys.active(roomName),
        }),
      ]);
    },
@@ -734,42 +727,39 @@ export function useRoomGetByName(roomName: string | null) {
 export function useRoomUpcomingMeetings(roomName: string | null) {
  const { isAuthenticated } = useAuthReady();

-  return $api.useQuery(
-    "get",
-    "/v1/rooms/{room_name}/meetings/upcoming" satisfies `/v1/rooms/{room_name}/${typeof MEETINGS_UPCOMING_PATH_PARTIAL}`,
-    {
-      params: {
-        path: { room_name: roomName! },
-      },
+  return useQuery({
+    queryKey: meetingStatusKeys.upcoming(roomName!),
+    queryFn: async () => {
+      const result = await meetingStatusBatcher.fetch(roomName!);
+      return result.upcoming_events;
    },
-    {
-      enabled: !!roomName && isAuthenticated,
-    },
-  );
+    enabled: !!roomName && isAuthenticated,
+  });
 }

-const MEETINGS_PATH_PARTIAL = "meetings" as const;
-const MEETINGS_ACTIVE_PATH_PARTIAL = `${MEETINGS_PATH_PARTIAL}/active` as const;
-const MEETINGS_UPCOMING_PATH_PARTIAL =
-  `${MEETINGS_PATH_PARTIAL}/upcoming` as const;
-const MEETING_LIST_PATH_PARTIALS = [
-  MEETINGS_ACTIVE_PATH_PARTIAL,
-  MEETINGS_UPCOMING_PATH_PARTIAL,
-];
+// Query keys reuse $api.queryOptions so cache identity matches the original
+// per-room GET endpoints. The actual fetch goes through the batcher, but the
+// keys stay consistent with the rest of the codebase.
+const meetingStatusKeys = {
+  active: (roomName: string) =>
+    $api.queryOptions("get", "/v1/rooms/{room_name}/meetings/active", {
+      params: { path: { room_name: roomName } },
+    }).queryKey,
+  upcoming: (roomName: string) =>
+    $api.queryOptions("get", "/v1/rooms/{room_name}/meetings/upcoming", {
+      params: { path: { room_name: roomName } },
+    }).queryKey,
+};

 export function useRoomActiveMeetings(roomName: string | null) {
-  return $api.useQuery(
-    "get",
-    "/v1/rooms/{room_name}/meetings/active" satisfies `/v1/rooms/{room_name}/${typeof MEETINGS_ACTIVE_PATH_PARTIAL}`,
-    {
-      params: {
-        path: { room_name: roomName! },
-      },
+  return useQuery({
+    queryKey: meetingStatusKeys.active(roomName!),
+    queryFn: async () => {
+      const result = await meetingStatusBatcher.fetch(roomName!);
+      return result.active_meetings;
    },
-    {
-      enabled: !!roomName,
-    },
-  );
+    enabled: !!roomName,
+  });
 }

 export function useRoomGetMeeting(
--- a/www/app/lib/meetingStatusBatcher.ts
+++ b/www/app/lib/meetingStatusBatcher.ts
@@ -0,0 +1,37 @@
+import { create, keyResolver, windowScheduler } from "@yornaath/batshit";
+import { client } from "./apiClient";
+import type { components } from "../reflector-api";
+
+type MeetingStatusResult = {
+  roomName: string;
+  active_meetings: components["schemas"]["Meeting"][];
+  upcoming_events: components["schemas"]["CalendarEventResponse"][];
+};
+
+const BATCH_WINDOW_MS = 10;
+
+export function createMeetingStatusBatcher(windowMs: number = BATCH_WINDOW_MS) {
+  return create({
+    fetcher: async (roomNames: string[]): Promise<MeetingStatusResult[]> => {
+      const unique = [...new Set(roomNames)];
+      const { data, error } = await client.POST(
+        "/v1/rooms/meetings/bulk-status",
+        { body: { room_names: unique } },
+      );
+      if (error || !data) {
+        throw new Error(
+          `bulk-status fetch failed: ${JSON.stringify(error ?? "no data")}`,
+        );
+      }
+      return roomNames.map((name) => ({
+        roomName: name,
+        active_meetings: data[name]?.active_meetings ?? [],
+        upcoming_events: data[name]?.upcoming_events ?? [],
+      }));
+    },
+    resolver: keyResolver("roomName"),
+    scheduler: windowScheduler(windowMs),
+  });
+}
+
+export const meetingStatusBatcher = createMeetingStatusBatcher();
--- a/www/app/reflector-api.d.ts
+++ b/www/app/reflector-api.d.ts
@@ -118,6 +118,23 @@ export interface paths {
    patch?: never;
    trace?: never;
  };
+  "/v1/rooms/meetings/bulk-status": {
+    parameters: {
+      query?: never;
+      header?: never;
+      path?: never;
+      cookie?: never;
+    };
+    get?: never;
+    put?: never;
+    /** Rooms Bulk Meeting Status */
+    post: operations["v1_rooms_bulk_meeting_status"];
+    delete?: never;
+    options?: never;
+    head?: never;
+    patch?: never;
+    trace?: never;
+  };
  "/v1/rooms/{room_id}": {
    parameters: {
      query?: never;
@@ -799,6 +816,11 @@ export interface components {
       */
      chunk: string;
    };
+    /** BulkStatusRequest */
+    BulkStatusRequest: {
+      /** Room Names */
+      room_names: string[];
+    };
    /** CalendarEventResponse */
    CalendarEventResponse: {
      /** Id */
@@ -1735,6 +1757,13 @@ export interface components {
      /** Webhook Secret */
      webhook_secret: string | null;
    };
+    /** RoomMeetingStatus */
+    RoomMeetingStatus: {
+      /** Active Meetings */
+      active_meetings: components["schemas"]["Meeting"][];
+      /** Upcoming Events */
+      upcoming_events: components["schemas"]["CalendarEventResponse"][];
+    };
    /** RtcOffer */
    RtcOffer: {
      /** Sdp */
@@ -2272,6 +2301,41 @@ export interface operations {
      };
    };
  };
+  v1_rooms_bulk_meeting_status: {
+    parameters: {
+      query?: never;
+      header?: never;
+      path?: never;
+      cookie?: never;
+    };
+    requestBody: {
+      content: {
+        "application/json": components["schemas"]["BulkStatusRequest"];
+      };
+    };
+    responses: {
+      /** @description Successful Response */
+      200: {
+        headers: {
+          [name: string]: unknown;
+        };
+        content: {
+          "application/json": {
+            [key: string]: components["schemas"]["RoomMeetingStatus"];
+          };
+        };
+      };
+      /** @description Validation Error */
+      422: {
+        headers: {
+          [name: string]: unknown;
+        };
+        content: {
+          "application/json": components["schemas"]["HTTPValidationError"];
+        };
+      };
+    };
+  };
  v1_rooms_get: {
    parameters: {
      query?: never;
--- a/www/jest.config.js
+++ b/www/jest.config.js
@@ -1,8 +1,22 @@
 module.exports = {
-  preset: "ts-jest",
-  testEnvironment: "node",
+  testEnvironment: "jest-environment-jsdom",
  roots: ["<rootDir>/app"],
-  testMatch: ["**/__tests__/**/*.test.ts"],
-  collectCoverage: true,
-  collectCoverageFrom: ["app/**/*.ts", "!app/**/*.d.ts"],
+  testMatch: ["**/__tests__/**/*.test.ts", "**/__tests__/**/*.test.tsx"],
+  collectCoverage: false,
+  transform: {
+    "^.+\\.[jt]sx?$": [
+      "ts-jest",
+      {
+        tsconfig: {
+          jsx: "react-jsx",
+          module: "esnext",
+          moduleResolution: "bundler",
+          esModuleInterop: true,
+          strict: true,
+          downlevelIteration: true,
+          lib: ["dom", "dom.iterable", "esnext"],
+        },
+      },
+    ],
+  },
 };
--- a/www/package.json
+++ b/www/package.json
@@ -23,6 +23,7 @@
    "@tanstack/react-query": "^5.85.9",
    "@types/ioredis": "^5.0.0",
    "@whereby.com/browser-sdk": "^3.3.4",
+    "@yornaath/batshit": "^0.14.0",
    "autoprefixer": "10.4.20",
    "axios": "^1.8.2",
    "eslint": "^9.33.0",
@@ -61,9 +62,13 @@
  "author": "Andreas <andreas@monadical.com>",
  "license": "All Rights Reserved",
  "devDependencies": {
+    "@testing-library/dom": "^10.4.1",
+    "@testing-library/jest-dom": "^6.9.1",
+    "@testing-library/react": "^16.3.2",
    "@types/jest": "^30.0.0",
    "@types/react": "18.2.20",
    "jest": "^30.1.3",
+    "jest-environment-jsdom": "^30.2.0",
    "openapi-typescript": "^7.9.1",
    "prettier": "^3.0.0",
    "ts-jest": "^29.4.1"
--- a/www/pnpm-lock.yaml
+++ b/www/pnpm-lock.yaml
Author	SHA1	Message	Date
Igor Monadical	ae44f5227b	Merge branch 'main' into fix-room-query-batching	2026-02-05 19:42:29 -05:00
Igor Loskutov	4339ffffcf	fix: use $api.queryOptions for batcher query keys Replace custom meetingStatusKeys with $api.queryOptions()-derived keys so cache identity matches the original per-room GET endpoints.	2026-02-05 19:40:13 -05:00
Igor Loskutov	9dc6c20ef8	fix: address code review findings - Add max_length=100 on BulkStatusRequest.room_names to prevent abuse - Filter bulk endpoint results to rooms user can see (owned or shared) - Throw on bulk-status fetch error instead of silently returning empty data - Fix room_by_id type annotation: dict[str, DbRoom] instead of Any - Remove stale "200ms" comment in test - Enable strict: true in jest tsconfig - Remove working docs from tracked files - Simplify redundant ternary in test helper	2026-02-05 19:36:17 -05:00
Igor Loskutov	931c344ddf	feat: add frontend test infrastructure and fix CI workflow - Fix pnpm version mismatch in test_next_server.yml (8 → auto-detect 10) - Add concurrency group to cancel stale CI runs - Remove redundant setup-node step - Update jest.config.js for jsdom + tsx support - Add meetingStatusBatcher integration test (3 tests) - Extract createMeetingStatusBatcher factory for testability	2026-02-05 19:06:32 -05:00
Igor Monadical	15ab2e306e	feat: Daily+hatchet default (#846 ) * feat: set Daily as default video platform Daily.co has been battle-tested and is ready to be the default. Whereby remains available for rooms that explicitly set it. * feat: enforce Hatchet for all multitrack processing Remove use_celery option from rooms - multitrack (Daily) recordings now always use Hatchet workflows. Celery remains for single-track (Whereby) file processing only. - Remove use_celery column from room table - Simplify dispatch logic to always use Hatchet for multitracks - Update tests to mock Hatchet instead of Celery * fix: update whereby test to patch Hatchet instead of removed Celery import --------- Co-authored-by: Igor Loskutov <igor.loskutoff@gmail.com>	2026-02-05 18:38:08 -05:00
Igor Loskutov	129290517e	docs: add handoff report and frontend testing research BATSHIT_REPORT.md: full context on bulk query batching — business goal, approach, all changes, verification status, and how to run. FRONTEND_TEST_RESEARCH.md: research on unit testing react-query hooks with jest.mock, renderHook, and batcher testing patterns.	2026-02-05 17:49:23 -05:00
Igor Loskutov	7e072219bf	feat: batch room meeting status queries into single bulk endpoint Reduces rooms list page from 2N+2 HTTP requests to 1 POST request. Backend: POST /v1/rooms/meetings/bulk-status with 3 DB queries total. Frontend: @yornaath/batshit DataLoader-style batcher with 10ms window.	2026-02-05 17:47:58 -05:00
Igor Monadical	1ce1c7a910	fix: websocket tests (#825 ) * fix websocket tests * fix: restore timeout and fix celery test infrastructure - Re-add timeout=1.0 to ws_manager pubsub loop (prevents CPU spin?) - Use Redis for Celery tests (memory:// broker doesn't support chords) - Add timeout param to in-memory subscriber mock - Remove duplicate celery_includes fixture from rtc_ws tests * fix: remove redundant inline imports in test files * fix: update gitleaks ignore for moved s3_key line --------- Co-authored-by: Igor Loskutov <igor.loskutoff@gmail.com>	2026-02-05 14:23:31 -05:00
Rémi Pauchet	984795357e	- fix nvidia repo blocked by apt (sha1) (#845 ) - use build cache for apt and uv - limit concurency for uv to prevent crashes with too many cores	2026-02-05 13:59:34 -05:00
Mathieu Virbel	fa3cf5da0f	chore(main): release 0.32.2 (#842 )	2026-02-03 22:05:22 -05:00
Igor Monadical	8707c6694a	fix: use Daily API recording.duration as master source for transcript duration (#844 ) Set duration early in get_participants from Daily API (seconds -> ms), ensuring post_zulip has the value before mixdown_tracks completes. Removes redundant duration update from mixdown_tracks. Co-authored-by: Igor Loskutov <igor.loskutoff@gmail.com>	2026-02-03 17:15:03 -05:00
Igor Monadical	4acde4b7fd	fix: increase TIMEOUT_MEDIUM from 2m to 5m for LLM tasks (#843 ) Topic detection was timing out on longer transcripts when LLM responses are slow. This affects detect_chunk_topic and other LLM-calling tasks that use TIMEOUT_MEDIUM. Co-authored-by: Igor Loskutov <igor.loskutoff@gmail.com>	2026-02-03 16:05:16 -05:00
Sergey Mankovsky	a2ed7d60d5	fix: make caddy optional (#841 )	2026-02-03 00:18:47 +01:00
Mathieu Virbel	a08f94a5bf	chore(main): release 0.32.1 (#840 )	2026-01-30 17:34:48 -05:00
Igor Loskutov	c05d1f03cd	fix: match httpx pad with hatchet audio timeout	2026-01-30 15:56:18 -05:00
Igor Loskutov	23eb1371cb	fix: daily multitrack pipeline finalze dependency fix	2026-01-30 15:19:27 -05:00
Mathieu Virbel	2592e369f6	chore(main): release 0.32.0 (#838 )	2026-01-30 13:13:59 -05:00
Igor Monadical	7fde64e252	feat: modal padding (#837 ) * Add Modal backend for audio padding - Create reflector_padding.py Modal deployment (CPU-based) - Add PaddingWorkflow with conditional Modal/local backend - Update deploy-all.sh to include padding deployment --------- Co-authored-by: Igor Loskutov <igor.loskutoff@gmail.com>	2026-01-30 13:11:51 -05:00