cleanup

Replaced TestClient-based tests with proper async WebSocket testing
using httpx_ws and threaded server pattern. TestClient has event loop
issues with WebSocket connections that were causing all tests to fail.

Changes:
- Rewrote all WebSocket tests to use aconnect_ws from httpx_ws
- Added chat_appserver fixture using threaded Uvicorn server
- Tests now use separate event loop in server thread
- All 6 tests now pass without asyncio/event loop errors
- Matches existing pattern from test_transcripts_rtc_ws.py

Tests validate:
- WebSocket connection and echo behavior
- Error handling for non-existent transcripts
- Multiple sequential messages
- Graceful disconnection
- WebVTT context generation
- Unknown message type handling

Closes fn-1.8 (End-to-end testing)

CHANGELOG.md

@@ -1,12 +1,5 @@
 # Changelog
 
-## [0.28.0](https://github.com/Monadical-SAS/reflector/compare/v0.27.0...v0.28.0) (2026-01-20)
-
-
-### Features
-
-* worker affinity ([#819](https://github.com/Monadical-SAS/reflector/issues/819)) ([3b6540e](https://github.com/Monadical-SAS/reflector/commit/3b6540eae5b597449f98661bdf15483b77be3268))
-
 ## [0.27.0](https://github.com/Monadical-SAS/reflector/compare/v0.26.0...v0.27.0) (2025-12-26)
 
 

docker-compose.yml

@@ -34,7 +34,7 @@ services:
     environment:
       ENTRYPOINT: beat
 
-  hatchet-worker-cpu:
+  hatchet-worker:
     build:
       context: server
     volumes:
@@ -43,20 +43,7 @@ services:
     env_file:
       - ./server/.env
     environment:
-      ENTRYPOINT: hatchet-worker-cpu
+      ENTRYPOINT: hatchet-worker
-    depends_on:
-      hatchet:
-        condition: service_healthy
-  hatchet-worker-llm:
-    build:
-      context: server
-    volumes:
-      - ./server/:/app/
-      - /app/.venv
-    env_file:
-      - ./server/.env
-    environment:
-      ENTRYPOINT: hatchet-worker-llm
     depends_on:
       hatchet:
         condition: service_healthy

gpu/modal_deployments/deploy-all.sh

@@ -131,15 +131,6 @@ if [ -z "$DIARIZER_URL" ]; then
 fi
 echo "  -> $DIARIZER_URL"
 
-echo ""
-echo "Deploying mixdown (CPU audio processing)..."
-MIXDOWN_URL=$(modal deploy reflector_mixdown.py 2>&1 | grep -o 'https://[^ ]*web.modal.run' | head -1)
-if [ -z "$MIXDOWN_URL" ]; then
-    echo "Error: Failed to deploy mixdown. Check Modal dashboard for details."
-    exit 1
-fi
-echo "  -> $MIXDOWN_URL"
-
 # --- Output Configuration ---
 echo ""
 echo "=========================================="
@@ -156,8 +147,4 @@ echo ""
 echo "DIARIZATION_BACKEND=modal"
 echo "DIARIZATION_URL=$DIARIZER_URL"
 echo "DIARIZATION_MODAL_API_KEY=$API_KEY"
-echo ""
-echo "MIXDOWN_BACKEND=modal"
-echo "MIXDOWN_URL=$MIXDOWN_URL"
-echo "MIXDOWN_MODAL_API_KEY=$API_KEY"
 echo "# --- End Modal Configuration ---"

gpu/modal_deployments/reflector_mixdown.py

@@ -1,379 +0,0 @@
-"""
-Reflector GPU backend - audio mixdown
-======================================
-
-CPU-intensive audio mixdown service for combining multiple audio tracks.
-Uses PyAV filter graph (amix) for high-quality audio mixing.
-"""
-
-import os
-import tempfile
-import time
-from fractions import Fraction
-
-import modal
-
-MIXDOWN_TIMEOUT = 900  # 15 minutes
-SCALEDOWN_WINDOW = 60  # 1 minute idle before shutdown
-
-app = modal.App("reflector-mixdown")
-
-# CPU-based image (no GPU needed for audio processing)
-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
-    )
-)
-
-
-@app.function(
-    cpu=4.0,  # 4 CPU cores for audio processing
-    timeout=MIXDOWN_TIMEOUT,
-    scaledown_window=SCALEDOWN_WINDOW,
-    secrets=[modal.Secret.from_name("reflector-gpu")],
-    image=image,
-)
-@modal.concurrent(max_inputs=10)
-@modal.asgi_app()
-def web():
-    import logging
-    import secrets
-    import shutil
-
-    import av
-    import requests
-    from av.audio.resampler import AudioResampler
-    from fastapi import Depends, FastAPI, HTTPException, status
-    from fastapi.security import OAuth2PasswordBearer
-    from pydantic import BaseModel
-
-    # Setup logging
-    logging.basicConfig(
-        level=logging.INFO, format="%(asctime)s - %(levelname)s - %(message)s"
-    )
-    logger = logging.getLogger(__name__)
-
-    app = FastAPI()
-    oauth2_scheme = OAuth2PasswordBearer(tokenUrl="token")
-
-    # Validate API key exists at startup
-    API_KEY = os.environ.get("REFLECTOR_GPU_APIKEY")
-    if not API_KEY:
-        raise RuntimeError("REFLECTOR_GPU_APIKEY not configured in Modal secrets")
-
-    def apikey_auth(apikey: str = Depends(oauth2_scheme)):
-        # Use constant-time comparison to prevent timing attacks
-        if secrets.compare_digest(apikey, API_KEY):
-            return
-        raise HTTPException(
-            status_code=status.HTTP_401_UNAUTHORIZED,
-            detail="Invalid API key",
-            headers={"WWW-Authenticate": "Bearer"},
-        )
-
-    class MixdownRequest(BaseModel):
-        track_urls: list[str]
-        output_url: str
-        target_sample_rate: int = 48000
-        expected_duration_sec: float | None = None
-
-    class MixdownResponse(BaseModel):
-        duration_ms: float
-        tracks_mixed: int
-        audio_uploaded: bool
-
-    def download_track(url: str, temp_dir: str, index: int) -> str:
-        """Download track from presigned URL to temp file using streaming."""
-        logger.info(f"Downloading track {index + 1}")
-        response = requests.get(url, stream=True, timeout=300)
-
-        if response.status_code == 404:
-            raise HTTPException(status_code=404, detail=f"Track {index} not found")
-        if response.status_code == 403:
-            raise HTTPException(
-                status_code=403, detail=f"Track {index} presigned URL expired"
-            )
-
-        response.raise_for_status()
-
-        temp_path = os.path.join(temp_dir, f"track_{index}.webm")
-        total_bytes = 0
-        with open(temp_path, "wb") as f:
-            for chunk in response.iter_content(chunk_size=8192):
-                if chunk:
-                    f.write(chunk)
-                    total_bytes += len(chunk)
-
-        logger.info(f"Track {index + 1} downloaded: {total_bytes} bytes")
-        return temp_path
-
-    def mixdown_tracks_modal(
-        track_paths: list[str],
-        output_path: str,
-        target_sample_rate: int,
-        expected_duration_sec: float | None,
-        logger,
-    ) -> float:
-        """Mix multiple audio tracks using PyAV filter graph.
-
-        Args:
-            track_paths: List of local file paths to audio tracks
-            output_path: Local path for output MP3 file
-            target_sample_rate: Sample rate for output (Hz)
-            expected_duration_sec: Optional fallback duration if container metadata unavailable
-            logger: Logger instance for progress tracking
-
-        Returns:
-            Duration in milliseconds
-        """
-        logger.info(f"Starting mixdown of {len(track_paths)} tracks")
-
-        # Build PyAV filter graph: N abuffer -> amix -> aformat -> sink
-        graph = av.filter.Graph()
-        inputs = []
-
-        for idx in range(len(track_paths)):
-            args = (
-                f"time_base=1/{target_sample_rate}:"
-                f"sample_rate={target_sample_rate}:"
-                f"sample_fmt=s32:"
-                f"channel_layout=stereo"
-            )
-            in_ctx = graph.add("abuffer", args=args, name=f"in{idx}")
-            inputs.append(in_ctx)
-
-        mixer = graph.add("amix", args=f"inputs={len(inputs)}:normalize=0", name="mix")
-        fmt = graph.add(
-            "aformat",
-            args=f"sample_fmts=s32:channel_layouts=stereo:sample_rates={target_sample_rate}",
-            name="fmt",
-        )
-        sink = graph.add("abuffersink", name="out")
-
-        # Connect inputs to mixer (no delays for Modal implementation)
-        for idx, in_ctx in enumerate(inputs):
-            in_ctx.link_to(mixer, 0, idx)
-
-        mixer.link_to(fmt)
-        fmt.link_to(sink)
-        graph.configure()
-
-        # Open all containers
-        containers = []
-        try:
-            for i, path in enumerate(track_paths):
-                try:
-                    c = av.open(path)
-                    containers.append(c)
-                except Exception as e:
-                    logger.warning(
-                        f"Failed to open container {i}: {e}",
-                    )
-
-            if not containers:
-                raise ValueError("Could not open any track containers")
-
-            # Calculate total duration for progress reporting
-            max_duration_sec = 0.0
-            for c in containers:
-                if c.duration is not None:
-                    dur_sec = c.duration / av.time_base
-                    max_duration_sec = max(max_duration_sec, dur_sec)
-            if max_duration_sec == 0.0 and expected_duration_sec:
-                max_duration_sec = expected_duration_sec
-
-            # Setup output container
-            out_container = av.open(output_path, "w", format="mp3")
-            out_stream = out_container.add_stream("libmp3lame", rate=target_sample_rate)
-
-            decoders = [c.decode(audio=0) for c in containers]
-            active = [True] * len(decoders)
-            resamplers = [
-                AudioResampler(format="s32", layout="stereo", rate=target_sample_rate)
-                for _ in decoders
-            ]
-
-            current_max_time = 0.0
-            last_log_time = time.monotonic()
-            start_time = time.monotonic()
-
-            total_duration = 0
-
-            while any(active):
-                for i, (dec, is_active) in enumerate(zip(decoders, active)):
-                    if not is_active:
-                        continue
-                    try:
-                        frame = next(dec)
-                    except StopIteration:
-                        active[i] = False
-                        inputs[i].push(None)  # Signal end of stream
-                        continue
-
-                    if frame.sample_rate != target_sample_rate:
-                        continue
-
-                    # Progress logging (every 5 seconds)
-                    if frame.time is not None:
-                        current_max_time = max(current_max_time, frame.time)
-                        now = time.monotonic()
-                        if now - last_log_time >= 5.0:
-                            elapsed = now - start_time
-                            if max_duration_sec > 0:
-                                progress_pct = min(
-                                    100.0, (current_max_time / max_duration_sec) * 100
-                                )
-                                logger.info(
-                                    f"Mixdown progress: {progress_pct:.1f}% @ {current_max_time:.1f}s (elapsed: {elapsed:.1f}s)"
-                                )
-                            else:
-                                logger.info(
-                                    f"Mixdown progress: @ {current_max_time:.1f}s (elapsed: {elapsed:.1f}s)"
-                                )
-                            last_log_time = now
-
-                    out_frames = resamplers[i].resample(frame) or []
-                    for rf in out_frames:
-                        rf.sample_rate = target_sample_rate
-                        rf.time_base = Fraction(1, target_sample_rate)
-                        inputs[i].push(rf)
-
-                    # Pull mixed frames from sink and encode
-                    while True:
-                        try:
-                            mixed = sink.pull()
-                        except Exception:
-                            break
-                        mixed.sample_rate = target_sample_rate
-                        mixed.time_base = Fraction(1, target_sample_rate)
-
-                        # Encode and mux
-                        for packet in out_stream.encode(mixed):
-                            out_container.mux(packet)
-                            total_duration += packet.duration
-
-            # Flush remaining frames from filter graph
-            while True:
-                try:
-                    mixed = sink.pull()
-                except Exception:
-                    break
-                mixed.sample_rate = target_sample_rate
-                mixed.time_base = Fraction(1, target_sample_rate)
-
-                for packet in out_stream.encode(mixed):
-                    out_container.mux(packet)
-                    total_duration += packet.duration
-
-            # Flush encoder
-            for packet in out_stream.encode():
-                out_container.mux(packet)
-                total_duration += packet.duration
-
-            # Calculate duration in milliseconds
-            if total_duration > 0:
-                # Use the same calculation as AudioFileWriterProcessor
-                duration_ms = round(
-                    float(total_duration * out_stream.time_base * 1000), 2
-                )
-            else:
-                duration_ms = 0.0
-
-            out_container.close()
-            logger.info(f"Mixdown complete: duration={duration_ms}ms")
-
-        finally:
-            # Cleanup all containers
-            for c in containers:
-                if c is not None:
-                    try:
-                        c.close()
-                    except Exception:
-                        pass
-
-        return duration_ms
-
-    @app.post("/v1/audio/mixdown", dependencies=[Depends(apikey_auth)])
-    def mixdown(request: MixdownRequest) -> MixdownResponse:
-        """Mix multiple audio tracks into a single MP3 file.
-
-        Tracks are downloaded from presigned S3 URLs, mixed using PyAV,
-        and uploaded to a presigned S3 PUT URL.
-        """
-        if not request.track_urls:
-            raise HTTPException(status_code=400, detail="No track URLs provided")
-
-        logger.info(f"Mixdown request: {len(request.track_urls)} tracks")
-
-        temp_dir = tempfile.mkdtemp()
-        temp_files = []
-        output_mp3_path = None
-
-        try:
-            # Download all tracks
-            for i, url in enumerate(request.track_urls):
-                temp_path = download_track(url, temp_dir, i)
-                temp_files.append(temp_path)
-
-            # Mix tracks
-            output_mp3_path = os.path.join(temp_dir, "mixed.mp3")
-            duration_ms = mixdown_tracks_modal(
-                temp_files,
-                output_mp3_path,
-                request.target_sample_rate,
-                request.expected_duration_sec,
-                logger,
-            )
-
-            # Upload result to S3
-            logger.info("Uploading result to S3")
-            file_size = os.path.getsize(output_mp3_path)
-            with open(output_mp3_path, "rb") as f:
-                upload_response = requests.put(
-                    request.output_url, data=f, timeout=300
-                )
-
-            if upload_response.status_code == 403:
-                raise HTTPException(
-                    status_code=403, detail="Output presigned URL expired"
-                )
-
-            upload_response.raise_for_status()
-            logger.info(f"Upload complete: {file_size} bytes")
-
-            return MixdownResponse(
-                duration_ms=duration_ms,
-                tracks_mixed=len(request.track_urls),
-                audio_uploaded=True,
-            )
-
-        except HTTPException:
-            raise
-        except Exception as e:
-            logger.error(f"Mixdown failed: {e}", exc_info=True)
-            raise HTTPException(status_code=500, detail=f"Mixdown failed: {str(e)}")
-
-        finally:
-            # Cleanup temp files
-            for temp_path in temp_files:
-                try:
-                    os.unlink(temp_path)
-                except Exception as e:
-                    logger.warning(f"Failed to cleanup temp file {temp_path}: {e}")
-
-            if output_mp3_path and os.path.exists(output_mp3_path):
-                try:
-                    os.unlink(output_mp3_path)
-                except Exception as e:
-                    logger.warning(f"Failed to cleanup output file {output_mp3_path}: {e}")
-
-            try:
-                shutil.rmtree(temp_dir)
-            except Exception as e:
-                logger.warning(f"Failed to cleanup temp directory {temp_dir}: {e}")
-
-    return app

server/reflector/app.py

@@ -18,6 +18,7 @@ from reflector.views.rooms import router as rooms_router
 from reflector.views.rtc_offer import router as rtc_offer_router
 from reflector.views.transcripts import router as transcripts_router
 from reflector.views.transcripts_audio import router as transcripts_audio_router
+from reflector.views.transcripts_chat import router as transcripts_chat_router
 from reflector.views.transcripts_participants import (
     router as transcripts_participants_router,
 )
@@ -90,6 +91,7 @@ app.include_router(transcripts_participants_router, prefix="/v1")
 app.include_router(transcripts_speaker_router, prefix="/v1")
 app.include_router(transcripts_upload_router, prefix="/v1")
 app.include_router(transcripts_websocket_router, prefix="/v1")
+app.include_router(transcripts_chat_router, prefix="/v1")
 app.include_router(transcripts_webrtc_router, prefix="/v1")
 app.include_router(transcripts_process_router, prefix="/v1")
 app.include_router(user_router, prefix="/v1")

server/reflector/hatchet/run_workers.py

@@ -0,0 +1,77 @@
+"""
+Run Hatchet workers for the multitrack pipeline.
+Runs as a separate process, just like Celery workers.
+
+Usage:
+    uv run -m reflector.hatchet.run_workers
+
+    # Or via docker:
+    docker compose exec server uv run -m reflector.hatchet.run_workers
+"""
+
+import signal
+import sys
+
+from hatchet_sdk.rate_limit import RateLimitDuration
+
+from reflector.hatchet.constants import LLM_RATE_LIMIT_KEY, LLM_RATE_LIMIT_PER_SECOND
+from reflector.logger import logger
+from reflector.settings import settings
+
+
+def main() -> None:
+    """Start Hatchet worker polling."""
+    if not settings.HATCHET_ENABLED:
+        logger.error("HATCHET_ENABLED is False, not starting workers")
+        sys.exit(1)
+
+    if not settings.HATCHET_CLIENT_TOKEN:
+        logger.error("HATCHET_CLIENT_TOKEN is not set")
+        sys.exit(1)
+
+    logger.info(
+        "Starting Hatchet workers",
+        debug=settings.HATCHET_DEBUG,
+    )
+
+    # Import here (not top-level) - workflow modules call HatchetClientManager.get_client()
+    # at module level because Hatchet SDK decorators (@workflow.task) bind at import time.
+    # Can't use lazy init: decorators need the client object when function is defined.
+    from reflector.hatchet.client import HatchetClientManager  # noqa: PLC0415
+    from reflector.hatchet.workflows import (  # noqa: PLC0415
+        daily_multitrack_pipeline,
+        subject_workflow,
+        topic_chunk_workflow,
+        track_workflow,
+    )
+
+    hatchet = HatchetClientManager.get_client()
+
+    hatchet.rate_limits.put(
+        LLM_RATE_LIMIT_KEY, LLM_RATE_LIMIT_PER_SECOND, RateLimitDuration.SECOND
+    )
+
+    worker = hatchet.worker(
+        "reflector-pipeline-worker",
+        workflows=[
+            daily_multitrack_pipeline,
+            subject_workflow,
+            topic_chunk_workflow,
+            track_workflow,
+        ],
+    )
+
+    def shutdown_handler(signum: int, frame) -> None:
+        logger.info("Received shutdown signal, stopping workers...")
+        # Worker cleanup happens automatically on exit
+        sys.exit(0)
+
+    signal.signal(signal.SIGINT, shutdown_handler)
+    signal.signal(signal.SIGTERM, shutdown_handler)
+
+    logger.info("Starting Hatchet worker polling...")
+    worker.start()
+
+
+if __name__ == "__main__":
+    main()

server/reflector/hatchet/run_workers_cpu.py

@@ -1,48 +0,0 @@
-"""
-CPU-heavy worker pool for audio processing tasks.
-Handles ONLY: mixdown_tracks
-
-Configuration:
-- slots=1: Only mixdown (already serialized globally with max_runs=1)
-- Worker affinity: pool=cpu-heavy
-"""
-
-from reflector.hatchet.client import HatchetClientManager
-from reflector.hatchet.workflows.daily_multitrack_pipeline import (
-    daily_multitrack_pipeline,
-)
-from reflector.logger import logger
-from reflector.settings import settings
-
-
-def main():
-    if not settings.HATCHET_ENABLED:
-        logger.error("HATCHET_ENABLED is False, not starting CPU workers")
-        return
-
-    hatchet = HatchetClientManager.get_client()
-
-    logger.info(
-        "Starting Hatchet CPU worker pool (mixdown only)",
-        worker_name="cpu-worker-pool",
-        slots=1,
-        labels={"pool": "cpu-heavy"},
-    )
-
-    cpu_worker = hatchet.worker(
-        "cpu-worker-pool",
-        slots=1,  # Only 1 mixdown at a time (already serialized globally)
-        labels={
-            "pool": "cpu-heavy",
-        },
-        workflows=[daily_multitrack_pipeline],
-    )
-
-    try:
-        cpu_worker.start()
-    except KeyboardInterrupt:
-        logger.info("Received shutdown signal, stopping CPU workers...")
-
-
-if __name__ == "__main__":
-    main()

server/reflector/hatchet/run_workers_llm.py

@@ -1,56 +0,0 @@
-"""
-LLM/I/O worker pool for all non-CPU tasks.
-Handles: all tasks except mixdown_tracks (transcription, LLM inference, orchestration)
-"""
-
-from reflector.hatchet.client import HatchetClientManager
-from reflector.hatchet.workflows.daily_multitrack_pipeline import (
-    daily_multitrack_pipeline,
-)
-from reflector.hatchet.workflows.subject_processing import subject_workflow
-from reflector.hatchet.workflows.topic_chunk_processing import topic_chunk_workflow
-from reflector.hatchet.workflows.track_processing import track_workflow
-from reflector.logger import logger
-from reflector.settings import settings
-
-SLOTS = 10
-WORKER_NAME = "llm-worker-pool"
-POOL = "llm-io"
-
-
-def main():
-    if not settings.HATCHET_ENABLED:
-        logger.error("HATCHET_ENABLED is False, not starting LLM workers")
-        return
-
-    hatchet = HatchetClientManager.get_client()
-
-    logger.info(
-        "Starting Hatchet LLM worker pool (all tasks except mixdown)",
-        worker_name=WORKER_NAME,
-        slots=SLOTS,
-        labels={"pool": POOL},
-    )
-
-    llm_worker = hatchet.worker(
-        WORKER_NAME,
-        slots=SLOTS,  # not all slots are probably used
-        labels={
-            "pool": POOL,
-        },
-        workflows=[
-            daily_multitrack_pipeline,
-            topic_chunk_workflow,
-            subject_workflow,
-            track_workflow,
-        ],
-    )
-
-    try:
-        llm_worker.start()
-    except KeyboardInterrupt:
-        logger.info("Received shutdown signal, stopping LLM workers...")
-
-
-if __name__ == "__main__":
-    main()

server/reflector/hatchet/workflows/daily_multitrack_pipeline.py

@@ -23,12 +23,7 @@ from pathlib import Path
 from typing import Any, Callable, Coroutine, Protocol, TypeVar
 
 import httpx
-from hatchet_sdk import (
+from hatchet_sdk import Context
-    ConcurrencyExpression,
-    ConcurrencyLimitStrategy,
-    Context,
-)
-from hatchet_sdk.labels import DesiredWorkerLabel
 from pydantic import BaseModel
 
 from reflector.dailyco_api.client import DailyApiClient
@@ -472,24 +467,10 @@ async def process_tracks(input: PipelineInput, ctx: Context) -> ProcessTracksRes
     parents=[process_tracks],
     execution_timeout=timedelta(seconds=TIMEOUT_AUDIO),
     retries=3,
-    desired_worker_labels={
-        "pool": DesiredWorkerLabel(
-            value="cpu-heavy",
-            required=True,
-            weight=100,
-        ),
-    },
-    concurrency=[
-        ConcurrencyExpression(
-            expression="'mixdown-global'",
-            max_runs=1,  # serialize mixdown to prevent resource contention
-            limit_strategy=ConcurrencyLimitStrategy.GROUP_ROUND_ROBIN,  # Queue
-        )
-    ],
 )
 @with_error_handling(TaskName.MIXDOWN_TRACKS)
 async def mixdown_tracks(input: PipelineInput, ctx: Context) -> MixdownResult:
-    """Mix all padded tracks into single audio file using PyAV or Modal backend."""
+    """Mix all padded tracks into single audio file using PyAV (same as Celery)."""
     ctx.log("mixdown_tracks: mixing padded tracks into single audio file")
 
     track_result = ctx.task_output(process_tracks)
@@ -513,7 +494,7 @@ async def mixdown_tracks(input: PipelineInput, ctx: Context) -> MixdownResult:
 
     storage = _spawn_storage()
 
-    # Presign URLs for padded tracks (same expiration for both backends)
+    # Presign URLs on demand (avoids stale URLs on workflow replay)
     padded_urls = []
     for track_info in padded_tracks:
         if track_info.key:
@@ -534,104 +515,33 @@ async def mixdown_tracks(input: PipelineInput, ctx: Context) -> MixdownResult:
         logger.error("Mixdown failed - no decodable audio frames found")
         raise ValueError("No decodable audio frames in any track")
 
-    output_key = f"{input.transcript_id}/audio.mp3"
+    output_path = tempfile.mktemp(suffix=".mp3")
+    duration_ms_callback_capture_container = [0.0]
 
-    # Conditional: Modal or local backend
+    async def capture_duration(d):
-    if settings.MIXDOWN_BACKEND == "modal":
+        duration_ms_callback_capture_container[0] = d
-        ctx.log("mixdown_tracks: using Modal backend")
 
-        # Presign PUT URL for output (Modal will upload directly)
+    writer = AudioFileWriterProcessor(path=output_path, on_duration=capture_duration)
-        output_url = await storage.get_file_url(
-            output_key,
-            operation="put_object",
-            expires_in=PRESIGNED_URL_EXPIRATION_SECONDS,
-        )
 
-        from reflector.processors.audio_mixdown_modal import (  # noqa: PLC0415
+    await mixdown_tracks_pyav(
-            AudioMixdownModalProcessor,
+        valid_urls,
-        )
+        writer,
+        target_sample_rate,
+        offsets_seconds=None,
+        logger=logger,
+        progress_callback=make_audio_progress_logger(ctx, TaskName.MIXDOWN_TRACKS),
+        expected_duration_sec=recording_duration if recording_duration > 0 else None,
+    )
+    await writer.flush()
 
-        try:
+    file_size = Path(output_path).stat().st_size
-            processor = AudioMixdownModalProcessor()
+    storage_path = f"{input.transcript_id}/audio.mp3"
-            result = await processor.mixdown(
-                track_urls=valid_urls,
-                output_url=output_url,
-                target_sample_rate=target_sample_rate,
-                expected_duration_sec=recording_duration
-                if recording_duration > 0
-                else None,
-            )
-            duration_ms = result.duration_ms
-            tracks_mixed = result.tracks_mixed
 
-            ctx.log(
+    with open(output_path, "rb") as mixed_file:
-                f"mixdown_tracks: Modal returned duration={duration_ms}ms, tracks={tracks_mixed}"
+        await storage.put_file(storage_path, mixed_file)
-            )
-        except httpx.HTTPStatusError as e:
-            error_detail = e.response.text if hasattr(e.response, "text") else str(e)
-            logger.error(
-                "[Hatchet] Modal mixdown HTTP error",
-                transcript_id=input.transcript_id,
-                status_code=e.response.status_code if hasattr(e, "response") else None,
-                error=error_detail,
-            )
-            raise RuntimeError(
-                f"Modal mixdown failed with HTTP {e.response.status_code}: {error_detail}"
-            )
-        except httpx.TimeoutException:
-            logger.error(
-                "[Hatchet] Modal mixdown timeout",
-                transcript_id=input.transcript_id,
-                timeout=settings.MIXDOWN_TIMEOUT,
-            )
-            raise RuntimeError(
-                f"Modal mixdown timeout after {settings.MIXDOWN_TIMEOUT}s"
-            )
-        except ValueError as e:
-            logger.error(
-                "[Hatchet] Modal mixdown validation error",
-                transcript_id=input.transcript_id,
-                error=str(e),
-            )
-            raise
-    else:
-        ctx.log("mixdown_tracks: using local backend")
 
-        # Existing local implementation
+    Path(output_path).unlink(missing_ok=True)
-        output_path = tempfile.mktemp(suffix=".mp3")
-        duration_ms_callback_capture_container = [0.0]
 
-        async def capture_duration(d):
-            duration_ms_callback_capture_container[0] = d
-
-        writer = AudioFileWriterProcessor(
-            path=output_path, on_duration=capture_duration
-        )
-
-        await mixdown_tracks_pyav(
-            valid_urls,
-            writer,
-            target_sample_rate,
-            offsets_seconds=None,
-            logger=logger,
-            progress_callback=make_audio_progress_logger(ctx, TaskName.MIXDOWN_TRACKS),
-            expected_duration_sec=recording_duration
-            if recording_duration > 0
-            else None,
-        )
-        await writer.flush()
-
-        file_size = Path(output_path).stat().st_size
-        with open(output_path, "rb") as mixed_file:
-            await storage.put_file(output_key, mixed_file)
-
-        Path(output_path).unlink(missing_ok=True)
-        duration_ms = duration_ms_callback_capture_container[0]
-        tracks_mixed = len(valid_urls)
-
-        ctx.log(f"mixdown_tracks: local mixdown uploaded {file_size} bytes")
-
-    # Update DB (same for both backends)
     async with fresh_db_connection():
         from reflector.db.transcripts import transcripts_controller  # noqa: PLC0415
 
@@ -641,12 +551,12 @@ async def mixdown_tracks(input: PipelineInput, ctx: Context) -> MixdownResult:
                 transcript, {"audio_location": "storage"}
             )
 
-    ctx.log(f"mixdown_tracks complete: uploaded to {output_key}")
+    ctx.log(f"mixdown_tracks complete: uploaded {file_size} bytes to {storage_path}")
 
     return MixdownResult(
-        audio_key=output_key,
+        audio_key=storage_path,
-        duration=duration_ms,
+        duration=duration_ms_callback_capture_container[0],
-        tracks_mixed=tracks_mixed,
+        tracks_mixed=len(valid_urls),
     )
 
 

server/reflector/hatchet/workflows/topic_chunk_processing.py

@@ -7,11 +7,7 @@ Spawned dynamically by detect_topics via aio_run_many() for parallel processing.
 
 from datetime import timedelta
 
-from hatchet_sdk import (
+from hatchet_sdk import ConcurrencyExpression, ConcurrencyLimitStrategy, Context
-    ConcurrencyExpression,
-    ConcurrencyLimitStrategy,
-    Context,
-)
 from hatchet_sdk.rate_limit import RateLimit
 from pydantic import BaseModel
 
@@ -38,13 +34,11 @@ hatchet = HatchetClientManager.get_client()
 topic_chunk_workflow = hatchet.workflow(
     name="TopicChunkProcessing",
     input_validator=TopicChunkInput,
-    concurrency=[
+    concurrency=ConcurrencyExpression(
-        ConcurrencyExpression(
+        expression="'global'",  # constant string = global limit across all runs
-            expression="'global'",  # constant string = global limit across all runs
+        max_runs=20,
-            max_runs=20,
+        limit_strategy=ConcurrencyLimitStrategy.GROUP_ROUND_ROBIN,
-            limit_strategy=ConcurrencyLimitStrategy.GROUP_ROUND_ROBIN,
+    ),
-        )
-    ],
 )
 
 

server/reflector/processors/audio_mixdown_modal.py

@@ -1,89 +0,0 @@
-"""
-Modal.com backend for audio mixdown.
-
-Uses Modal's CPU containers to offload audio mixing from Hatchet workers.
-Communicates via presigned S3 URLs for both input and output.
-"""
-
-import httpx
-from pydantic import BaseModel
-
-from reflector.settings import settings
-
-
-class MixdownResponse(BaseModel):
-    """Response from Modal mixdown endpoint."""
-
-    duration_ms: float
-    tracks_mixed: int
-    audio_uploaded: bool
-
-
-class AudioMixdownModalProcessor:
-    """Audio mixdown processor using Modal.com CPU backend.
-
-    Sends track URLs (presigned GET) and output URL (presigned PUT) to Modal.
-    Modal handles download, mixdown via PyAV, and upload.
-    """
-
-    def __init__(self, modal_api_key: str | None = None):
-        if not settings.MIXDOWN_URL:
-            raise ValueError("MIXDOWN_URL required to use AudioMixdownModalProcessor")
-
-        self.mixdown_url = settings.MIXDOWN_URL + "/v1"
-        self.timeout = settings.MIXDOWN_TIMEOUT
-        self.modal_api_key = modal_api_key or settings.MIXDOWN_MODAL_API_KEY
-
-        if not self.modal_api_key:
-            raise ValueError(
-                "MIXDOWN_MODAL_API_KEY required to use AudioMixdownModalProcessor"
-            )
-
-    async def mixdown(
-        self,
-        track_urls: list[str],
-        output_url: str,
-        target_sample_rate: int,
-        expected_duration_sec: float | None = None,
-    ) -> MixdownResponse:
-        """Mix multiple audio tracks via Modal backend.
-
-        Args:
-            track_urls: List of presigned GET URLs for audio tracks (non-empty)
-            output_url: Presigned PUT URL for output MP3
-            target_sample_rate: Sample rate for output (Hz, must be positive)
-            expected_duration_sec: Optional fallback duration if container metadata unavailable
-
-        Returns:
-            MixdownResponse with duration_ms, tracks_mixed, audio_uploaded
-
-        Raises:
-            ValueError: If track_urls is empty or target_sample_rate invalid
-            httpx.HTTPStatusError: On HTTP errors (404, 403, 500, etc.)
-            httpx.TimeoutException: On timeout
-        """
-        # Validate inputs
-        if not track_urls:
-            raise ValueError("track_urls cannot be empty")
-        if target_sample_rate <= 0:
-            raise ValueError(
-                f"target_sample_rate must be positive, got {target_sample_rate}"
-            )
-        if expected_duration_sec is not None and expected_duration_sec < 0:
-            raise ValueError(
-                f"expected_duration_sec cannot be negative, got {expected_duration_sec}"
-            )
-
-        async with httpx.AsyncClient(timeout=self.timeout) as client:
-            response = await client.post(
-                f"{self.mixdown_url}/audio/mixdown",
-                headers={"Authorization": f"Bearer {self.modal_api_key}"},
-                json={
-                    "track_urls": track_urls,
-                    "output_url": output_url,
-                    "target_sample_rate": target_sample_rate,
-                    "expected_duration_sec": expected_duration_sec,
-                },
-            )
-            response.raise_for_status()
-            return MixdownResponse(**response.json())

server/reflector/settings.py

@@ -98,17 +98,6 @@ class Settings(BaseSettings):
     # Diarization: local pyannote.audio
     DIARIZATION_PYANNOTE_AUTH_TOKEN: str | None = None
 
-    # Audio Mixdown
-    # backends:
-    #   - local: in-process PyAV mixdown (runs in same process as Hatchet worker)
-    #   - modal: HTTP API client to Modal.com CPU container
-    MIXDOWN_BACKEND: str = "local"
-    MIXDOWN_URL: str | None = None
-    MIXDOWN_TIMEOUT: int = 900  # 15 minutes
-
-    # Mixdown: modal backend
-    MIXDOWN_MODAL_API_KEY: str | None = None
-
     # Sentry
     SENTRY_DSN: str | None = None
 

server/reflector/views/transcripts_chat.py

@@ -0,0 +1,133 @@
+"""
+Transcripts chat API
+====================
+
+WebSocket endpoint for bidirectional chat with LLM about transcript content.
+"""
+
+from typing import Optional
+
+from fastapi import APIRouter, WebSocket, WebSocketDisconnect
+from llama_index.core import Settings
+from llama_index.core.base.llms.types import ChatMessage, MessageRole
+
+from reflector.auth.auth_jwt import JWTAuth
+from reflector.db.recordings import recordings_controller
+from reflector.db.transcripts import transcripts_controller
+from reflector.db.users import user_controller
+from reflector.llm import LLM
+from reflector.settings import settings
+from reflector.utils.transcript_formats import topics_to_webvtt_named
+
+router = APIRouter()
+
+
+async def _get_is_multitrack(transcript) -> bool:
+    """Detect if transcript is from multitrack recording."""
+    if not transcript.recording_id:
+        return False
+    recording = await recordings_controller.get_by_id(transcript.recording_id)
+    return recording is not None and recording.is_multitrack
+
+
+@router.websocket("/transcripts/{transcript_id}/chat")
+async def transcript_chat_websocket(
+    transcript_id: str,
+    websocket: WebSocket,
+):
+    """WebSocket endpoint for chatting with LLM about transcript content."""
+    # 1. Auth check (optional) - extract token from WebSocket subprotocol header
+    # Browser can't send Authorization header for WS; use subprotocol: ["bearer", token]
+    raw_subprotocol = websocket.headers.get("sec-websocket-protocol") or ""
+    parts = [p.strip() for p in raw_subprotocol.split(",") if p.strip()]
+    token: Optional[str] = None
+    negotiated_subprotocol: Optional[str] = None
+    if len(parts) >= 2 and parts[0].lower() == "bearer":
+        negotiated_subprotocol = "bearer"
+        token = parts[1]
+
+    user_id: Optional[str] = None
+    if token:
+        try:
+            payload = JWTAuth().verify_token(token)
+            authentik_uid = payload.get("sub")
+
+            if authentik_uid:
+                user = await user_controller.get_by_authentik_uid(authentik_uid)
+                if user:
+                    user_id = user.id
+        except Exception:
+            # Auth failed - continue as anonymous
+            pass
+
+    # Get transcript (respects user_id for private transcripts)
+    transcript = await transcripts_controller.get_by_id_for_http(
+        transcript_id, user_id=user_id
+    )
+    if not transcript:
+        await websocket.close(code=1008)  # Policy violation (not found/unauthorized)
+        return
+
+    # 2. Accept connection (with negotiated subprotocol if present)
+    await websocket.accept(subprotocol=negotiated_subprotocol)
+
+    # 3. Generate WebVTT context
+    is_multitrack = await _get_is_multitrack(transcript)
+    webvtt = topics_to_webvtt_named(
+        transcript.topics, transcript.participants, is_multitrack
+    )
+
+    # Truncate if needed (15k char limit for POC)
+    webvtt_truncated = webvtt[:15000] if len(webvtt) > 15000 else webvtt
+
+    # 4. Configure LLM
+    llm = LLM(settings=settings, temperature=0.7)
+
+    # 5. System message with transcript context
+    system_msg = f"""You are analyzing this meeting transcript (WebVTT):
+
+{webvtt_truncated}
+
+Answer questions about content, speakers, timeline. Include timestamps when relevant."""
+
+    # 6. Conversation history
+    conversation_history = [ChatMessage(role=MessageRole.SYSTEM, content=system_msg)]
+
+    try:
+        # 7. Message loop
+        while True:
+            data = await websocket.receive_json()
+
+            if data.get("type") == "get_context":
+                # Return WebVTT context (for debugging/testing)
+                await websocket.send_json({"type": "context", "webvtt": webvtt})
+                continue
+
+            if data.get("type") != "message":
+                # Echo unknown types for backward compatibility
+                await websocket.send_json({"type": "echo", "data": data})
+                continue
+
+            # Add user message to history
+            user_msg = ChatMessage(role=MessageRole.USER, content=data.get("text", ""))
+            conversation_history.append(user_msg)
+
+            # Stream LLM response
+            assistant_msg = ""
+            chat_stream = await Settings.llm.astream_chat(conversation_history)
+            async for chunk in chat_stream:
+                token = chunk.delta or ""
+                if token:
+                    await websocket.send_json({"type": "token", "text": token})
+                    assistant_msg += token
+
+            # Save assistant response to history
+            conversation_history.append(
+                ChatMessage(role=MessageRole.ASSISTANT, content=assistant_msg)
+            )
+            await websocket.send_json({"type": "done"})
+
+    except WebSocketDisconnect:
+        pass
+    except Exception as e:
+        await websocket.send_json({"type": "error", "message": str(e)})

server/runserver.sh

@@ -7,10 +7,8 @@ elif [ "${ENTRYPOINT}" = "worker" ]; then
     uv run celery -A reflector.worker.app worker --loglevel=info
 elif [ "${ENTRYPOINT}" = "beat" ]; then
     uv run celery -A reflector.worker.app beat --loglevel=info
-elif [ "${ENTRYPOINT}" = "hatchet-worker-cpu" ]; then
+elif [ "${ENTRYPOINT}" = "hatchet-worker" ]; then
-    uv run python -m reflector.hatchet.run_workers_cpu
+    uv run python -m reflector.hatchet.run_workers
-elif [ "${ENTRYPOINT}" = "hatchet-worker-llm" ]; then
-    uv run python -m reflector.hatchet.run_workers_llm
 else
     echo "Unknown command"
 fi

server/tests/test_transcripts_chat.py

@@ -0,0 +1,234 @@
+"""Tests for transcript chat WebSocket endpoint."""
+
+import asyncio
+import threading
+import time
+from pathlib import Path
+
+import pytest
+from httpx_ws import aconnect_ws
+from uvicorn import Config, Server
+
+from reflector.db.transcripts import (
+    SourceKind,
+    TranscriptParticipant,
+    TranscriptTopic,
+    transcripts_controller,
+)
+from reflector.processors.types import Word
+
+
+@pytest.fixture
+def chat_appserver(tmpdir, setup_database):
+    """Start a real HTTP server for WebSocket testing."""
+    from reflector.app import app
+    from reflector.db import get_database
+    from reflector.settings import settings
+
+    DATA_DIR = settings.DATA_DIR
+    settings.DATA_DIR = Path(tmpdir)
+
+    # Start server in separate thread with its own event loop
+    host = "127.0.0.1"
+    port = 1256  # Different port from rtc tests
+    server_started = threading.Event()
+    server_exception = None
+    server_instance = None
+
+    def run_server():
+        nonlocal server_exception, server_instance
+        try:
+            # Create new event loop for this thread
+            loop = asyncio.new_event_loop()
+            asyncio.set_event_loop(loop)
+
+            config = Config(app=app, host=host, port=port, loop=loop)
+            server_instance = Server(config)
+
+            async def start_server():
+                # Initialize database connection in this event loop
+                database = get_database()
+                await database.connect()
+                try:
+                    await server_instance.serve()
+                finally:
+                    await database.disconnect()
+
+            # Signal that server is starting
+            server_started.set()
+            loop.run_until_complete(start_server())
+        except Exception as e:
+            server_exception = e
+            server_started.set()
+        finally:
+            loop.close()
+
+    server_thread = threading.Thread(target=run_server, daemon=True)
+    server_thread.start()
+
+    # Wait for server to start
+    server_started.wait(timeout=30)
+    if server_exception:
+        raise server_exception
+
+    # Wait for server to be fully ready
+    time.sleep(1)
+
+    yield server_instance, host, port
+
+    # Stop server
+    if server_instance:
+        server_instance.should_exit = True
+        server_thread.join(timeout=30)
+
+    settings.DATA_DIR = DATA_DIR
+
+
+@pytest.fixture
+async def test_transcript(setup_database):
+    """Create a test transcript for WebSocket tests."""
+    transcript = await transcripts_controller.add(
+        name="Test Transcript for Chat", source_kind=SourceKind.FILE
+    )
+    return transcript
+
+
+@pytest.fixture
+async def test_transcript_with_content(setup_database):
+    """Create a test transcript with actual content for WebVTT generation."""
+    transcript = await transcripts_controller.add(
+        name="Test Transcript with Content", source_kind=SourceKind.FILE
+    )
+
+    # Add participants
+    await transcripts_controller.update(
+        transcript,
+        {
+            "participants": [
+                TranscriptParticipant(id="1", speaker=0, name="Alice").model_dump(),
+                TranscriptParticipant(id="2", speaker=1, name="Bob").model_dump(),
+            ]
+        },
+    )
+
+    # Add topic with words
+    await transcripts_controller.upsert_topic(
+        transcript,
+        TranscriptTopic(
+            title="Introduction",
+            summary="Opening remarks",
+            timestamp=0.0,
+            words=[
+                Word(text="Hello ", start=0.0, end=1.0, speaker=0),
+                Word(text="everyone.", start=1.0, end=2.0, speaker=0),
+                Word(text="Hi ", start=2.0, end=3.0, speaker=1),
+                Word(text="there!", start=3.0, end=4.0, speaker=1),
+            ],
+        ),
+    )
+
+    return transcript
+
+
+@pytest.mark.asyncio
+async def test_chat_websocket_connection_success(test_transcript, chat_appserver):
+    """Test successful WebSocket connection to chat endpoint."""
+    server, host, port = chat_appserver
+    base_url = f"ws://{host}:{port}/v1"
+
+    async with aconnect_ws(f"{base_url}/transcripts/{test_transcript.id}/chat") as ws:
+        # Send unknown message type to test echo behavior
+        await ws.send_json({"type": "test", "text": "Hello"})
+
+        # Should receive echo for unknown types
+        response = await ws.receive_json()
+        assert response["type"] == "echo"
+        assert response["data"]["type"] == "test"
+
+
+@pytest.mark.asyncio
+async def test_chat_websocket_nonexistent_transcript(chat_appserver):
+    """Test WebSocket connection fails for nonexistent transcript."""
+    server, host, port = chat_appserver
+    base_url = f"ws://{host}:{port}/v1"
+
+    # Connection should fail or disconnect immediately for non-existent transcript
+    # Different behavior from successful connection
+    with pytest.raises(Exception):  # Will raise on connection or first operation
+        async with aconnect_ws(f"{base_url}/transcripts/nonexistent-id/chat") as ws:
+            await ws.send_json({"type": "message", "text": "Hello"})
+            await ws.receive_json()
+
+
+@pytest.mark.asyncio
+async def test_chat_websocket_multiple_messages(test_transcript, chat_appserver):
+    """Test sending multiple messages through WebSocket."""
+    server, host, port = chat_appserver
+    base_url = f"ws://{host}:{port}/v1"
+
+    async with aconnect_ws(f"{base_url}/transcripts/{test_transcript.id}/chat") as ws:
+        # Send multiple unknown message types (testing echo behavior)
+        messages = ["First message", "Second message", "Third message"]
+
+        for i, msg in enumerate(messages):
+            await ws.send_json({"type": f"test{i}", "text": msg})
+            response = await ws.receive_json()
+            assert response["type"] == "echo"
+            assert response["data"]["type"] == f"test{i}"
+            assert response["data"]["text"] == msg
+
+
+@pytest.mark.asyncio
+async def test_chat_websocket_disconnect_graceful(test_transcript, chat_appserver):
+    """Test WebSocket disconnects gracefully."""
+    server, host, port = chat_appserver
+    base_url = f"ws://{host}:{port}/v1"
+
+    async with aconnect_ws(f"{base_url}/transcripts/{test_transcript.id}/chat") as ws:
+        await ws.send_json({"type": "message", "text": "Hello"})
+        await ws.receive_json()
+        # Close handled by context manager - should not raise
+
+
+@pytest.mark.asyncio
+async def test_chat_websocket_context_generation(
+    test_transcript_with_content, chat_appserver
+):
+    """Test WebVTT context is generated on connection."""
+    server, host, port = chat_appserver
+    base_url = f"ws://{host}:{port}/v1"
+
+    async with aconnect_ws(
+        f"{base_url}/transcripts/{test_transcript_with_content.id}/chat"
+    ) as ws:
+        # Request context
+        await ws.send_json({"type": "get_context"})
+
+        # Receive context response
+        response = await ws.receive_json()
+        assert response["type"] == "context"
+        assert "webvtt" in response
+
+        # Verify WebVTT format
+        webvtt = response["webvtt"]
+        assert webvtt.startswith("WEBVTT")
+        assert "<v Alice>" in webvtt
+        assert "<v Bob>" in webvtt
+        assert "Hello everyone." in webvtt
+        assert "Hi there!" in webvtt
+
+
+@pytest.mark.asyncio
+async def test_chat_websocket_unknown_message_type(test_transcript, chat_appserver):
+    """Test unknown message types are echoed back."""
+    server, host, port = chat_appserver
+    base_url = f"ws://{host}:{port}/v1"
+
+    async with aconnect_ws(f"{base_url}/transcripts/{test_transcript.id}/chat") as ws:
+        # Send unknown message type
+        await ws.send_json({"type": "unknown", "data": "test"})
+
+        # Should receive echo
+        response = await ws.receive_json()
+        assert response["type"] == "echo"
+        assert response["data"]["type"] == "unknown"

www/app/(app)/transcripts/TranscriptChatModal.tsx

@@ -0,0 +1,103 @@
+"use client";
+
+import { useState } from "react";
+import { Box, Dialog, Input, IconButton } from "@chakra-ui/react";
+import { MessageCircle } from "lucide-react";
+import Markdown from "react-markdown";
+import "../../styles/markdown.css";
+import type { Message } from "./useTranscriptChat";
+
+interface TranscriptChatModalProps {
+  open: boolean;
+  onClose: () => void;
+  messages: Message[];
+  sendMessage: (text: string) => void;
+  isStreaming: boolean;
+  currentStreamingText: string;
+}
+
+export function TranscriptChatModal({
+  open,
+  onClose,
+  messages,
+  sendMessage,
+  isStreaming,
+  currentStreamingText,
+}: TranscriptChatModalProps) {
+  const [input, setInput] = useState("");
+
+  const handleSend = () => {
+    if (!input.trim()) return;
+    sendMessage(input);
+    setInput("");
+  };
+
+  return (
+    <Dialog.Root open={open} onOpenChange={(e) => !e.open && onClose()}>
+      <Dialog.Backdrop />
+      <Dialog.Positioner>
+        <Dialog.Content maxW="500px" h="600px">
+          <Dialog.Header>Transcript Chat</Dialog.Header>
+
+          <Dialog.Body overflowY="auto">
+            {messages.map((msg) => (
+              <Box
+                key={msg.id}
+                p={3}
+                mb={2}
+                bg={msg.role === "user" ? "blue.50" : "gray.50"}
+                borderRadius="md"
+              >
+                {msg.role === "user" ? (
+                  msg.text
+                ) : (
+                  <div className="markdown">
+                    <Markdown>{msg.text}</Markdown>
+                  </div>
+                )}
+              </Box>
+            ))}
+
+            {isStreaming && (
+              <Box p={3} bg="gray.50" borderRadius="md">
+                <div className="markdown">
+                  <Markdown>{currentStreamingText}</Markdown>
+                </div>
+                <Box as="span" className="animate-pulse">
+                  ▊
+                </Box>
+              </Box>
+            )}
+          </Dialog.Body>
+
+          <Dialog.Footer>
+            <Input
+              value={input}
+              onChange={(e) => setInput(e.target.value)}
+              onKeyDown={(e) => e.key === "Enter" && handleSend()}
+              placeholder="Ask about transcript..."
+              disabled={isStreaming}
+            />
+          </Dialog.Footer>
+        </Dialog.Content>
+      </Dialog.Positioner>
+    </Dialog.Root>
+  );
+}
+
+export function TranscriptChatButton({ onClick }: { onClick: () => void }) {
+  return (
+    <IconButton
+      position="fixed"
+      bottom="24px"
+      right="24px"
+      onClick={onClick}
+      size="lg"
+      colorPalette="blue"
+      borderRadius="full"
+      aria-label="Open chat"
+    >
+      <MessageCircle />
+    </IconButton>
+  );
+}

www/app/(app)/transcripts/[transcriptId]/page.tsx

@@ -18,9 +18,15 @@ import {
   Skeleton,
   Text,
   Spinner,
+  useDisclosure,
 } from "@chakra-ui/react";
 import { useTranscriptGet } from "../../../lib/apiHooks";
 import { TranscriptStatus } from "../../../lib/transcript";
+import {
+  TranscriptChatModal,
+  TranscriptChatButton,
+} from "../TranscriptChatModal";
+import { useTranscriptChat } from "../useTranscriptChat";
 
 type TranscriptDetails = {
   params: Promise<{
@@ -53,6 +59,9 @@ export default function TranscriptDetails(details: TranscriptDetails) {
   const [finalSummaryElement, setFinalSummaryElement] =
     useState<HTMLDivElement | null>(null);
 
+  const { open, onOpen, onClose } = useDisclosure();
+  const chat = useTranscriptChat(transcriptId);
+
   useEffect(() => {
     if (!waiting || !transcript.data) return;
 
@@ -119,6 +128,15 @@ export default function TranscriptDetails(details: TranscriptDetails) {
 
   return (
     <>
+      <TranscriptChatModal
+        open={open}
+        onClose={onClose}
+        messages={chat.messages}
+        sendMessage={chat.sendMessage}
+        isStreaming={chat.isStreaming}
+        currentStreamingText={chat.currentStreamingText}
+      />
+      <TranscriptChatButton onClick={onOpen} />
       <Grid
         templateColumns="1fr"
         templateRows="auto minmax(0, 1fr)"

www/app/(app)/transcripts/useTranscriptChat.ts

@@ -0,0 +1,130 @@
+"use client";
+
+import { useEffect, useState, useRef } from "react";
+import { getSession } from "next-auth/react";
+import { WEBSOCKET_URL } from "../../lib/apiClient";
+import { assertExtendedToken } from "../../lib/types";
+
+export type Message = {
+  id: string;
+  role: "user" | "assistant";
+  text: string;
+  timestamp: Date;
+};
+
+export type UseTranscriptChat = {
+  messages: Message[];
+  sendMessage: (text: string) => void;
+  isStreaming: boolean;
+  currentStreamingText: string;
+};
+
+export const useTranscriptChat = (transcriptId: string): UseTranscriptChat => {
+  const [messages, setMessages] = useState<Message[]>([]);
+  const [isStreaming, setIsStreaming] = useState(false);
+  const [currentStreamingText, setCurrentStreamingText] = useState("");
+  const wsRef = useRef<WebSocket | null>(null);
+  const streamingTextRef = useRef<string>("");
+  const isMountedRef = useRef<boolean>(true);
+
+  useEffect(() => {
+    isMountedRef.current = true;
+
+    const connectWebSocket = async () => {
+      const url = `${WEBSOCKET_URL}/v1/transcripts/${transcriptId}/chat`;
+
+      // Get auth token for WebSocket subprotocol
+      let protocols: string[] | undefined;
+      try {
+        const session = await getSession();
+        if (session) {
+          const token = assertExtendedToken(session).accessToken;
+          // Pass token via subprotocol: ["bearer", token]
+          protocols = ["bearer", token];
+        }
+      } catch (error) {
+        console.warn("Failed to get auth token for WebSocket:", error);
+      }
+
+      const ws = new WebSocket(url, protocols);
+      wsRef.current = ws;
+
+      ws.onopen = () => {
+        console.log("Chat WebSocket connected");
+      };
+
+      ws.onmessage = (event) => {
+        if (!isMountedRef.current) return;
+
+        const msg = JSON.parse(event.data);
+
+        switch (msg.type) {
+          case "token":
+            setIsStreaming(true);
+            streamingTextRef.current += msg.text;
+            setCurrentStreamingText(streamingTextRef.current);
+            break;
+
+          case "done":
+            // CRITICAL: Save the text BEFORE resetting the ref
+            // The setMessages callback may execute later, after ref is reset
+            const finalText = streamingTextRef.current;
+
+            setMessages((prev) => [
+              ...prev,
+              {
+                id: Date.now().toString(),
+                role: "assistant",
+                text: finalText,
+                timestamp: new Date(),
+              },
+            ]);
+            streamingTextRef.current = "";
+            setCurrentStreamingText("");
+            setIsStreaming(false);
+            break;
+
+          case "error":
+            console.error("Chat error:", msg.message);
+            setIsStreaming(false);
+            break;
+        }
+      };
+
+      ws.onerror = (error) => {
+        console.error("WebSocket error:", error);
+      };
+
+      ws.onclose = () => {
+        console.log("Chat WebSocket closed");
+      };
+    };
+
+    connectWebSocket();
+
+    return () => {
+      isMountedRef.current = false;
+      if (wsRef.current) {
+        wsRef.current.close();
+      }
+    };
+  }, [transcriptId]);
+
+  const sendMessage = (text: string) => {
+    if (!wsRef.current) return;
+
+    setMessages((prev) => [
+      ...prev,
+      {
+        id: Date.now().toString(),
+        role: "user",
+        text,
+        timestamp: new Date(),
+      },
+    ]);
+
+    wsRef.current.send(JSON.stringify({ type: "message", text }));
+  };
+
+  return { messages, sendMessage, isStreaming, currentStreamingText };
+};