Override web service in docker-compose.standalone.yml to build from
www/Dockerfile (multi-stage: deps → build → standalone runner) instead
of running pnpm dev with bind-mounted source.
Server runs with network_mode: host and can't resolve Docker service
names. Publish cpu port as 8100 on host, point server at localhost:8100.
Worker stays on bridge network using cpu:8000. Add dummy
TRANSCRIPT_MODAL_API_KEY since OpenAI SDK requires it even for local
endpoints.
test_validation_idle_transcript_with_recording_allowed called
validate_transcript_for_processing without mocking
task_is_scheduled_or_active, which attempts a real Celery
broker connection (AMQP port 5672). Other tests in the same
file already mock this — apply the same pattern here.
Three fixes for the processing page not redirecting when status becomes "ended":
- Add useWebSockets to processing page so it receives STATUS events
- Remove OAuth2PasswordBearer from auth_none — broke WebSocket endpoints (500)
- Reconnect stale Redis in ws_manager when Celery worker reuses dead event loop
- Filter OrbStack/Docker Desktop PIDs from port conflict check (false positives on Mac)
- Check all infra ports (5432, 6379, 3900, 3903) not just app ports
- Fix ollama model detection to match on name column only
- Document OrbStack and cross-project port conflicts in troubleshooting
Replace in-process pyannote approach with self-hosted gpu/self_hosted/ service.
Same HTTP API as Modal — just TRANSCRIPT_URL/DIARIZATION_URL point to local container.
- Add gpu/self_hosted/Dockerfile.cpu (GPU Dockerfile minus NVIDIA CUDA)
- Add S3 model bundle fallback in diarizer.py when HF_TOKEN not set
- Add gpu service to docker-compose.standalone.yml with compose env overrides
- Fix /browse empty in PUBLIC_MODE (search+list queries filtered out roomless transcripts)
- Remove audio_diarization_pyannote.py, file_diarization_pyannote.py and tests
- Remove pyannote-audio from server local deps
Enables file diarization without Modal by using pyannote.audio locally.
Downloads model bundle from S3 on first use, caches locally, patches
config to use local paths. Set DIARIZATION_BACKEND=pyannote to enable.
* feat: add local pyannote file diarization processor
Enables file diarization without Modal by using pyannote.audio locally.
Downloads model bundle from S3 on first use, caches locally, patches
config to use local paths. Set DIARIZATION_BACKEND=pyannote to enable.
* fix: standalone setup enables pyannote diarization and public mode
Replace DIARIZATION_ENABLED=false with DIARIZATION_BACKEND=pyannote so
file uploads get speaker diarization out of the box. Add PUBLIC_MODE=true
so unauthenticated users can list/browse transcripts.
* fix: touch env files before first compose_cmd in standalone setup
docker-compose.yml references www/.env.local as env_file, but the
setup script only creates it in step 4. compose_cmd calls in step 3
(Garage) fail on a fresh clone when the file doesn't exist yet.
* feat: standalone uses self-hosted GPU service for transcription+diarization
Replace in-process pyannote approach with self-hosted gpu/self_hosted/ service.
Same HTTP API as Modal — just TRANSCRIPT_URL/DIARIZATION_URL point to local container.
- Add gpu/self_hosted/Dockerfile.cpu (GPU Dockerfile minus NVIDIA CUDA)
- Add S3 model bundle fallback in diarizer.py when HF_TOKEN not set
- Add gpu service to docker-compose.standalone.yml with compose env overrides
- Fix /browse empty in PUBLIC_MODE (search+list queries filtered out roomless transcripts)
- Remove audio_diarization_pyannote.py, file_diarization_pyannote.py and tests
- Remove pyannote-audio from server local deps
* fix: allow unauthenticated GPU requests when no API key configured
OAuth2PasswordBearer with auto_error=True rejects requests without
Authorization header before apikey_auth can check if auth is needed.
* fix: rename standalone gpu service to cpu to match Dockerfile.cpu usage
* docs: add programmatic testing section and fix gpu->cpu naming in setup script/docs
- Add "Testing programmatically" section to standalone docs with curl commands
for creating transcript, uploading audio, polling status, checking result
- Fix setup-standalone.sh to reference `cpu` service (was still `gpu` after rename)
- Update all docs references from gpu to cpu service naming
---------
Co-authored-by: Igor Loskutov <igor.loskutoff@gmail.com>
Without this, the processing page never redirects after completion
because the redirect logic watches the REST query data, not the
WebSocket status state.
Cherry-picked from feat-dag-progress (faec509a).
- garage.toml: fix rpc_secret field name (was secret_transmitter),
move to top-level per Garage v1.1.0 spec, remove unused [s3_web]
- setup-standalone.sh: resolve symlinked .env files before writing,
always ensure all standalone-critical vars via env_set,
fix garage key create/info syntax (positional arg, not --name),
avoid overwriting key secret with "(redacted)" on re-run,
use compose_cmd in health check
- docker-compose.standalone.yml: fix garage healthcheck (no curl in
image, use /garage stats instead)
Add TRANSCRIPT_STORAGE_AWS_ENDPOINT_URL setting to enable S3-compatible
backends (Garage, MinIO). When set, uses path-style addressing and
routes all requests to the custom endpoint. When unset, AWS behavior
is unchanged.
- AwsStorage: accept aws_endpoint_url, pass to all 6 session.client()
calls, configure path-style addressing and base_url
- Fix 4 direct AwsStorage constructions in Hatchet workflows to pass
endpoint_url (would have silently targeted wrong endpoint)
- Standalone: add Garage service to docker-compose.standalone.yml,
setup script initializes layout/bucket/key and writes credentials
- Fix compose_cmd() bug: Mac path was missing standalone yml
- garage.toml template with runtime secret generation via openssl
Single script takes fresh clone to working Reflector: Ollama/LLM setup,
env file generation (server/.env + www/.env.local), docker compose up,
health checks. No Hatchet in standalone — live pipeline is pure Celery.
Ollama profiles (ollama-gpu, ollama-cpu) are only for Linux standalone
deployment. Mac devs never use them. Separate file keeps the main
compose clean and provides a natural home for future standalone services
(MinIO, etc.).
Linux: docker compose -f docker-compose.yml -f docker-compose.standalone.yml --profile ollama-gpu up -d
Mac: docker compose up -d (native Ollama, no standalone file needed)
- Add setup script (scripts/setup-local-llm.sh) for one-command Ollama setup
Mac: native Metal GPU, Linux: containerized via docker-compose profiles
- Add ollama-gpu and ollama-cpu docker-compose profiles for Linux
- Add extra_hosts to server/hatchet-worker-llm for host.docker.internal
- Pass response_format JSON schema in StructuredOutputWorkflow.extract()
enabling grammar-based constrained decoding on Ollama/llama.cpp/vLLM/OpenAI
- Update .env.example with Ollama as default LLM option
- Add Ollama PRD and local dev setup docs
* 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>
* 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>
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>
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>
* set hatchet as default for multitracks
* fix: pipeline routing tests for hatchet-default branch
- Create room with use_celery=True to force Celery backend in tests
- Link transcript to room to enable multitrack pipeline routing
- Fixes test failures caused by missing HATCHET_CLIENT_TOKEN in test env
* Update server/reflector/services/transcript_process.py
Co-authored-by: pr-agent-monadical[bot] <198624643+pr-agent-monadical[bot]@users.noreply.github.com>
---------
Co-authored-by: Igor Loskutov <igor.loskutoff@gmail.com>
Co-authored-by: pr-agent-monadical[bot] <198624643+pr-agent-monadical[bot]@users.noreply.github.com>
