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10 Commits

Author SHA1 Message Date
Igor Loskutov
528154ae96 fix: update standalone docs to match self-contained compose usage 2026-02-13 09:56:09 -05:00
Igor Loskutov
c42b8439dd fix: make standalone compose self-contained (drop !reset dependency)
docker-compose.standalone.yml used !reset YAML tags to clear
network_mode and volumes from the base compose. !reset requires
Compose v2.24+ and breaks on Colima + brew-installed compose.

Rewrite as a fully self-contained file with all services defined
directly (server, worker, beat, redis, postgres, web, garage, cpu,
gpu-nvidia, ollama, ollama-cpu). No longer overlays docker-compose.yml.

Update setup-standalone.sh compose_cmd() to use only the standalone
file instead of both files.
2026-02-13 09:52:07 -05:00
Igor Loskutov
14a8b5808e fix: check for Docker BuildKit (buildx) before building images
Dockerfiles use RUN --mount for caching which requires BuildKit.
Colima and bare Docker Engine installs don't bundle docker-buildx.
2026-02-12 18:57:32 -05:00
Igor Loskutov
e57c6186f9 fix: check compose version output, not just exit code
Without the plugin, `docker compose version` can still exit 0
by falling through to `docker version`. Grep for "Compose" in
the output to reliably detect the plugin.
2026-02-12 18:32:16 -05:00
Igor Loskutov
36a8daee61 fix: check for Docker Compose plugin before running standalone setup
Without the compose plugin, `docker compose -f ...` produces a
misleading "unknown shorthand flag: 'f'" error instead of telling
the user compose is missing.
2026-02-12 18:24:24 -05:00
Igor Loskutov
3d13e5d42f fix: auto-rebuild standalone images and blank Hatchet vars
- Add rebuild_images() to setup-standalone.sh that runs `compose build`
  before `up -d`, with image hash comparison to log whether each service
  was rebuilt or unchanged
- Blank HATCHET_CLIENT_SERVER_URL/HOST_PORT in standalone compose since
  Hatchet is not started (localhost URLs break after network_mode:host removal)
- Fix grep -qx -> -qxF for ollama model matching (dots in model names)
2026-02-12 18:21:09 -05:00
Igor Loskutov
695f3c4928 fix: standalone server networking and setup diagnostics
Replace network_mode:host with standard compose networking for macOS
Docker Desktop compatibility. Add dump_diagnostics() for automatic
failure debugging and docker-exec-based server health checks.
2026-02-12 17:46:00 -05:00
5bca92510a feat: standalone frontend uses production build instead of dev server (#862)
* feat: standalone frontend uses production build instead of dev server

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.

* chore: move standalone compose TODO to Huly issue RFFR-46

* fix: add required env vars for standalone production frontend

The standalone web service (node server.js) has no bind-mounted .env
files and the base env_file (.env.local) has API_URL commented out.
Next.js standalone server can't auto-load .env files without them on
disk, so all required vars must be explicit in the compose override.

---------

Co-authored-by: Igor Loskutov <igor.loskutoff@gmail.com>
2026-02-12 15:36:52 -05:00
972a52d22f fix: live flow real-time updates during processing (#861)
* fix: live flow real-time updates during processing

Three gaps caused transcript pages to require manual refresh after
live recording/processing:

1. UserEventsProvider only invalidated list queries on TRANSCRIPT_STATUS,
   not individual transcript queries. Now parses data.id from the event
   and calls invalidateTranscript for the specific transcript.

2. useWebSockets had no reconnection logic — a dropped WS silently
   killed all real-time updates. Added exponential backoff reconnection
   (1s-30s, max 10 retries) with intentional close detection.

3. No polling fallback — WS was single point of failure. Added
   conditional refetchInterval to useTranscriptGet that polls every 5s
   when transcript status is processing/uploaded/recording.

* feat: type-safe WebSocket events via OpenAPI stub

Define Pydantic models with Literal discriminators for all WS events
(9 transcript-level, 5 user-level). Expose via stub GET endpoints so
pnpm openapi generates TS discriminated unions with exhaustive switch
narrowing on the frontend.

- New server/reflector/ws_events.py with TranscriptWsEvent and UserWsEvent
- Tighten backend emit signatures with TranscriptEventName literal
- Frontend uses generated types, removes Zod schema and manual casts
- Fix pre-existing bugs: waveform mapping, FINAL_LONG_SUMMARY field name
- STATUS value now typed as TranscriptStatus literal end-to-end
- TOPIC handler simplified to query invalidation only (avoids shape mismatch)

* fix: restore TOPIC WS handler with immediate state update

The setTopics call provides instant topic rendering during live
transcription. Query invalidation still follows for full data sync.

* fix: align TOPIC WS event data with GetTranscriptTopic shape

Convert TranscriptTopic → GetTranscriptTopic in pipeline before
emitting, so WS sends segments instead of words. Removes the
`as unknown as Topic` cast on the frontend.

* fix: use NonEmptyString and TranscriptStatus in user WS event models

---------

Co-authored-by: Igor Loskutov <igor.loskutoff@gmail.com>
2026-02-12 14:49:57 -05:00
b468427f1b feat: local llm support + standalone-script doc/draft (#856)
* feat: local LLM via Ollama + structured output response_format

- 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

* refactor: move Ollama services to docker-compose.standalone.yml

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)

* fix: correct PRD goal (demo/eval, not dev replacement) and processor naming

* chore: remove completed PRD, rename setup doc, drop response_format tests

- Remove docs/01_ollama.prd.md (implementation complete)
- Rename local-dev-setup.md -> standalone-local-setup.md
- Remove TestResponseFormat class from test_llm_retry.py

* docs: resolve standalone storage step — skip S3 for live-only mode

* docs: add TASKS.md for standalone env defaults + setup script work

* feat: add unified setup-local-dev.sh for standalone deployment

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.

* chore: rename to setup-standalone, remove redundant setup-local-llm.sh

* feat: add custom S3 endpoint support + Garage standalone storage

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

* fix: standalone setup — garage config, symlink handling, healthcheck

- 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)

* docs: update standalone md — symlink handling, garage config template

* docs: add troubleshooting section + port conflict check in setup script

Port conflicts from stale next dev / other worktree processes silently
shadow Docker container port mappings, causing env vars to appear ignored.

* fix: invalidate transcript query on STATUS websocket event

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).

* fix: local env setup (#855)

* Ensure rate limit

* Increase nextjs compilation speed

* Fix daily no content handling

* Simplify daily webhook creation

* Fix webhook request validation

* feat: add local pyannote file diarization processor (#858)

* 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>

* Fix websocket disconnect errors

* Fix event loop is closed in Celery workers

* Allow reprocessing idle multitrack transcripts

* 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.

* 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: set source_kind to FILE on audio file upload

The upload endpoint left source_kind as the default LIVE even when
a file was uploaded. Now sets it to FILE when the upload completes.

* Add hatchet env vars

* fix: improve port conflict detection and ollama model check in standalone setup

- 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

* fix: processing page auto-redirect after file upload completes

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

* fix: mock Celery broker in idle transcript validation test

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.

* Enable server host mode

* Fix webrtc connection

* Remove turbopack

* fix: standalone GPU service connectivity with host network mode

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.

---------

Co-authored-by: Igor Loskutov <igor.loskutoff@gmail.com>
Co-authored-by: Sergey Mankovsky <sergey@mankovsky.dev>
2026-02-11 18:20:36 -05:00
59 changed files with 2155 additions and 3708 deletions

View File

@@ -0,0 +1,219 @@
# Self-contained standalone compose for fully local deployment (no external dependencies).
# Usage: docker compose -f docker-compose.standalone.yml up -d
#
# On Linux with NVIDIA GPU, also pass: --profile ollama-gpu
# On Linux without GPU: --profile ollama-cpu
# On Mac: Ollama runs natively (Metal GPU) — no profile needed, services here unused.
services:
server:
build:
context: server
ports:
- "1250:1250"
extra_hosts:
- "host.docker.internal:host-gateway"
volumes:
- ./server/:/app/
- /app/.venv
env_file:
- ./server/.env
environment:
ENTRYPOINT: server
# Docker DNS names instead of localhost
DATABASE_URL: postgresql+asyncpg://reflector:reflector@postgres:5432/reflector
REDIS_HOST: redis
CELERY_BROKER_URL: redis://redis:6379/1
CELERY_RESULT_BACKEND: redis://redis:6379/1
# Standalone doesn't run Hatchet
HATCHET_CLIENT_SERVER_URL: ""
HATCHET_CLIENT_HOST_PORT: ""
# Self-hosted transcription/diarization via CPU service
TRANSCRIPT_BACKEND: modal
TRANSCRIPT_URL: http://cpu:8000
TRANSCRIPT_MODAL_API_KEY: local
DIARIZATION_BACKEND: modal
DIARIZATION_URL: http://cpu:8000
depends_on:
postgres:
condition: service_healthy
redis:
condition: service_started
worker:
build:
context: server
volumes:
- ./server/:/app/
- /app/.venv
env_file:
- ./server/.env
environment:
ENTRYPOINT: worker
HATCHET_CLIENT_SERVER_URL: ""
HATCHET_CLIENT_HOST_PORT: ""
TRANSCRIPT_BACKEND: modal
TRANSCRIPT_URL: http://cpu:8000
TRANSCRIPT_MODAL_API_KEY: local
DIARIZATION_BACKEND: modal
DIARIZATION_URL: http://cpu:8000
depends_on:
redis:
condition: service_started
beat:
build:
context: server
volumes:
- ./server/:/app/
- /app/.venv
env_file:
- ./server/.env
environment:
ENTRYPOINT: beat
depends_on:
redis:
condition: service_started
redis:
image: redis:7.2
ports:
- 6379:6379
postgres:
image: postgres:17
command: postgres -c 'max_connections=200'
ports:
- 5432:5432
environment:
POSTGRES_USER: reflector
POSTGRES_PASSWORD: reflector
POSTGRES_DB: reflector
volumes:
- ./data/postgres:/var/lib/postgresql/data
healthcheck:
test: ["CMD-SHELL", "pg_isready -d reflector -U reflector"]
interval: 5s
timeout: 5s
retries: 10
start_period: 15s
web:
image: reflector-frontend-standalone
build:
context: ./www
ports:
- "3000:3000"
command: ["node", "server.js"]
environment:
NODE_ENV: production
# Browser-facing URLs (host-accessible ports)
API_URL: http://localhost:1250
WEBSOCKET_URL: ws://localhost:1250
SITE_URL: http://localhost:3000
# Server-side URLs (docker-network internal)
SERVER_API_URL: http://server:1250
KV_URL: redis://redis:6379
KV_USE_TLS: "false"
# Standalone: no external auth provider
FEATURE_REQUIRE_LOGIN: "false"
NEXTAUTH_URL: http://localhost:3000
NEXTAUTH_SECRET: standalone-local-secret
# Nullify partial auth vars inherited from base env_file
AUTHENTIK_ISSUER: ""
AUTHENTIK_REFRESH_TOKEN_URL: ""
garage:
image: dxflrs/garage:v1.1.0
ports:
- "3900:3900" # S3 API
- "3903:3903" # Admin API
volumes:
- garage_data:/var/lib/garage/data
- garage_meta:/var/lib/garage/meta
- ./data/garage.toml:/etc/garage.toml:ro
restart: unless-stopped
healthcheck:
test: ["CMD", "/garage", "stats"]
interval: 10s
timeout: 5s
retries: 5
start_period: 5s
cpu:
build:
context: ./gpu/self_hosted
dockerfile: Dockerfile.cpu
ports:
- "8100:8000"
volumes:
- gpu_cache:/root/.cache
restart: unless-stopped
healthcheck:
test: ["CMD", "curl", "-f", "http://localhost:8000/docs"]
interval: 15s
timeout: 5s
retries: 10
start_period: 120s
gpu-nvidia:
build:
context: ./gpu/self_hosted
profiles: ["gpu-nvidia"]
volumes:
- gpu_cache:/root/.cache
deploy:
resources:
reservations:
devices:
- driver: nvidia
count: all
capabilities: [gpu]
restart: unless-stopped
healthcheck:
test: ["CMD", "curl", "-f", "http://localhost:8000/docs"]
interval: 15s
timeout: 5s
retries: 10
start_period: 120s
ollama:
image: ollama/ollama:latest
profiles: ["ollama-gpu"]
ports:
- "11434:11434"
volumes:
- ollama_data:/root/.ollama
deploy:
resources:
reservations:
devices:
- driver: nvidia
count: all
capabilities: [gpu]
restart: unless-stopped
healthcheck:
test: ["CMD", "curl", "-f", "http://localhost:11434/api/tags"]
interval: 10s
timeout: 5s
retries: 5
ollama-cpu:
image: ollama/ollama:latest
profiles: ["ollama-cpu"]
ports:
- "11434:11434"
volumes:
- ollama_data:/root/.ollama
restart: unless-stopped
healthcheck:
test: ["CMD", "curl", "-f", "http://localhost:11434/api/tags"]
interval: 10s
timeout: 5s
retries: 5
volumes:
garage_data:
garage_meta:
ollama_data:
gpu_cache:

View File

@@ -2,8 +2,7 @@ services:
server:
build:
context: server
ports:
- 1250:1250
network_mode: host
volumes:
- ./server/:/app/
- /app/.venv
@@ -11,6 +10,12 @@ services:
- ./server/.env
environment:
ENTRYPOINT: server
DATABASE_URL: postgresql+asyncpg://reflector:reflector@localhost:5432/reflector
REDIS_HOST: localhost
CELERY_BROKER_URL: redis://localhost:6379/1
CELERY_RESULT_BACKEND: redis://localhost:6379/1
HATCHET_CLIENT_SERVER_URL: http://localhost:8889
HATCHET_CLIENT_HOST_PORT: localhost:7078
worker:
build:
@@ -22,6 +27,11 @@ services:
- ./server/.env
environment:
ENTRYPOINT: worker
HATCHET_CLIENT_SERVER_URL: http://hatchet:8888
HATCHET_CLIENT_HOST_PORT: hatchet:7077
depends_on:
redis:
condition: service_started
beat:
build:
@@ -33,6 +43,9 @@ services:
- ./server/.env
environment:
ENTRYPOINT: beat
depends_on:
redis:
condition: service_started
hatchet-worker-cpu:
build:
@@ -44,6 +57,8 @@ services:
- ./server/.env
environment:
ENTRYPOINT: hatchet-worker-cpu
HATCHET_CLIENT_SERVER_URL: http://hatchet:8888
HATCHET_CLIENT_HOST_PORT: hatchet:7077
depends_on:
hatchet:
condition: service_healthy
@@ -57,6 +72,8 @@ services:
- ./server/.env
environment:
ENTRYPOINT: hatchet-worker-llm
HATCHET_CLIENT_SERVER_URL: http://hatchet:8888
HATCHET_CLIENT_HOST_PORT: hatchet:7077
depends_on:
hatchet:
condition: service_healthy
@@ -75,10 +92,16 @@ services:
volumes:
- ./www:/app/
- /app/node_modules
- next_cache:/app/.next
env_file:
- ./www/.env.local
environment:
- NODE_ENV=development
- SERVER_API_URL=http://host.docker.internal:1250
extra_hosts:
- "host.docker.internal:host-gateway"
depends_on:
- server
postgres:
image: postgres:17
@@ -94,13 +117,14 @@ services:
- ./server/docker/init-hatchet-db.sql:/docker-entrypoint-initdb.d/init-hatchet-db.sql:ro
healthcheck:
test: ["CMD-SHELL", "pg_isready -d reflector -U reflector"]
interval: 10s
timeout: 10s
retries: 5
start_period: 10s
interval: 5s
timeout: 5s
retries: 10
start_period: 15s
hatchet:
image: ghcr.io/hatchet-dev/hatchet/hatchet-lite:latest
restart: on-failure
ports:
- "8889:8888"
- "7078:7077"
@@ -108,7 +132,7 @@ services:
postgres:
condition: service_healthy
environment:
DATABASE_URL: "postgresql://reflector:reflector@postgres:5432/hatchet?sslmode=disable"
DATABASE_URL: "postgresql://reflector:reflector@postgres:5432/hatchet?sslmode=disable&connect_timeout=30"
SERVER_AUTH_COOKIE_DOMAIN: localhost
SERVER_AUTH_COOKIE_INSECURE: "t"
SERVER_GRPC_BIND_ADDRESS: "0.0.0.0"
@@ -128,6 +152,5 @@ services:
retries: 5
start_period: 30s
networks:
default:
attachable: true
volumes:
next_cache:

View File

@@ -0,0 +1,214 @@
---
sidebar_position: 2
title: Standalone Local Setup
---
# Standalone Local Setup
**The goal**: a clueless user clones the repo, runs one script, and has a working Reflector instance locally. No cloud accounts, no API keys, no manual env file editing.
```bash
git clone https://github.com/monadical-sas/reflector.git
cd reflector
./scripts/setup-standalone.sh
```
The script is idempotent — safe to re-run at any time. It detects what's already set up and skips completed steps.
## Prerequisites
- Docker / OrbStack / Docker Desktop (any)
- Mac (Apple Silicon) or Linux
- 16GB+ RAM (32GB recommended for 14B LLM models)
- **Mac only**: [Ollama](https://ollama.com/download) installed (`brew install ollama`)
## What the script does
### 1. LLM inference via Ollama
**Mac**: starts Ollama natively (Metal GPU acceleration). Pulls the LLM model. Docker containers reach it via `host.docker.internal:11434`.
**Linux**: starts containerized Ollama via `docker-compose.standalone.yml` profile (`ollama-gpu` with NVIDIA, `ollama-cpu` without). Pulls model inside the container.
### 2. Environment files
Generates `server/.env` and `www/.env.local` with standalone defaults:
**`server/.env`** — key settings:
| Variable | Value | Why |
|----------|-------|-----|
| `DATABASE_URL` | `postgresql+asyncpg://...@postgres:5432/reflector` | Docker-internal hostname |
| `REDIS_HOST` | `redis` | Docker-internal hostname |
| `CELERY_BROKER_URL` | `redis://redis:6379/1` | Docker-internal hostname |
| `AUTH_BACKEND` | `none` | No Authentik in standalone |
| `TRANSCRIPT_BACKEND` | `modal` | HTTP API to self-hosted CPU service |
| `TRANSCRIPT_URL` | `http://cpu:8000` | Docker-internal CPU service |
| `DIARIZATION_BACKEND` | `modal` | HTTP API to self-hosted CPU service |
| `DIARIZATION_URL` | `http://cpu:8000` | Docker-internal CPU service |
| `TRANSLATION_BACKEND` | `passthrough` | No Modal |
| `LLM_URL` | `http://host.docker.internal:11434/v1` (Mac) | Ollama endpoint |
**`www/.env.local`** — key settings:
| Variable | Value |
|----------|-------|
| `API_URL` | `http://localhost:1250` |
| `SERVER_API_URL` | `http://server:1250` |
| `WEBSOCKET_URL` | `ws://localhost:1250` |
| `FEATURE_REQUIRE_LOGIN` | `false` |
| `NEXTAUTH_SECRET` | `standalone-dev-secret-not-for-production` |
If env files already exist (including symlinks from worktree setup), the script resolves symlinks and ensures all standalone-critical vars are set. Existing vars not related to standalone are preserved.
### 3. Object storage (Garage)
Standalone uses [Garage](https://garagehq.deuxfleurs.fr/) — a lightweight S3-compatible object store running in Docker. The setup script starts Garage, initializes the layout, creates a bucket and access key, and writes the credentials to `server/.env`.
**`server/.env`** — storage settings added by the script:
| Variable | Value | Why |
|----------|-------|-----|
| `TRANSCRIPT_STORAGE_BACKEND` | `aws` | Uses the S3-compatible storage driver |
| `TRANSCRIPT_STORAGE_AWS_ENDPOINT_URL` | `http://garage:3900` | Docker-internal Garage S3 API |
| `TRANSCRIPT_STORAGE_AWS_BUCKET_NAME` | `reflector-media` | Created by the script |
| `TRANSCRIPT_STORAGE_AWS_REGION` | `garage` | Must match Garage config |
| `TRANSCRIPT_STORAGE_AWS_ACCESS_KEY_ID` | *(auto-generated)* | Created by `garage key create` |
| `TRANSCRIPT_STORAGE_AWS_SECRET_ACCESS_KEY` | *(auto-generated)* | Created by `garage key create` |
The `TRANSCRIPT_STORAGE_AWS_ENDPOINT_URL` setting enables S3-compatible backends. When set, the storage driver uses path-style addressing and routes all requests to the custom endpoint. When unset (production AWS), behavior is unchanged.
Garage config template lives at `scripts/garage.toml`. The setup script generates `data/garage.toml` (gitignored) with a random RPC secret and mounts it read-only into the container. Single-node, `replication_factor=1`.
> **Note**: Presigned URLs embed the Garage Docker hostname (`http://garage:3900`). This is fine — the server proxies S3 responses to the browser. Modal GPU workers cannot reach internal Garage, but standalone doesn't use Modal.
### 4. Transcription and diarization
Standalone runs the self-hosted ML service (`gpu/self_hosted/`) in a CPU-only Docker container named `cpu`. This is the same FastAPI service used for Modal.com GPU deployments, but built with `Dockerfile.cpu` (no NVIDIA CUDA dependencies). The compose service is named `cpu` (not `gpu`) to make clear it runs without GPU acceleration; the source code lives in `gpu/self_hosted/` because it's shared with the GPU deployment.
The `modal` backend name is reused — it just means "HTTP API client". Setting `TRANSCRIPT_URL` / `DIARIZATION_URL` to `http://cpu:8000` routes requests to the local container instead of Modal.com.
On first start, the service downloads pyannote speaker diarization models (~1GB) from a public S3 bundle. Models are cached in a Docker volume (`gpu_cache`) so subsequent starts are fast. No HuggingFace token or API key needed.
> **Performance**: CPU-only transcription and diarization work but are slow (~15 min for a 3 min file). For faster processing on Linux with NVIDIA GPU, use `--profile gpu-nvidia` instead (see `docker-compose.standalone.yml`).
### 5. Docker services
```bash
docker compose up -d postgres redis garage cpu server worker beat web
```
All services start in a single command. Garage and `cpu` are already started by earlier steps but included for idempotency. No Hatchet in standalone mode — LLM processing (summaries, topics, titles) runs via Celery tasks.
### 6. Database migrations
Run automatically by the `server` container on startup (`runserver.sh` calls `alembic upgrade head`). No manual step needed.
### 7. Health check
Verifies:
- CPU service responds (transcription + diarization ready)
- Server responds at `http://localhost:1250/health`
- Frontend serves at `http://localhost:3000`
- LLM endpoint reachable from inside containers
## Services
| Service | Port | Purpose |
|---------|------|---------|
| `server` | 1250 | FastAPI backend (runs migrations on start) |
| `web` | 3000 | Next.js frontend |
| `postgres` | 5432 | PostgreSQL database |
| `redis` | 6379 | Cache + Celery broker |
| `garage` | 3900, 3903 | S3-compatible object storage (S3 API + admin API) |
| `cpu` | — | Self-hosted transcription + diarization (CPU-only) |
| `worker` | — | Celery worker (live pipeline post-processing) |
| `beat` | — | Celery beat (scheduled tasks) |
## Testing programmatically
After the setup script completes, verify the full pipeline (upload, transcription, diarization, LLM summary) via the API:
```bash
# 1. Create a transcript
TRANSCRIPT_ID=$(curl -s -X POST 'http://localhost:1250/v1/transcripts' \
-H 'Content-Type: application/json' \
-d '{"name":"test-upload"}' | python3 -c "import sys,json; print(json.load(sys.stdin)['id'])")
echo "Created: $TRANSCRIPT_ID"
# 2. Upload an audio file (single-chunk upload)
curl -s "http://localhost:1250/v1/transcripts/${TRANSCRIPT_ID}/record/upload?chunk_number=0&total_chunks=1" \
-X POST -F "chunk=@/path/to/audio.mp3"
# 3. Poll until processing completes (status: ended or error)
while true; do
STATUS=$(curl -s "http://localhost:1250/v1/transcripts/${TRANSCRIPT_ID}" \
| python3 -c "import sys,json; print(json.load(sys.stdin)['status'])")
echo "Status: $STATUS"
case "$STATUS" in ended|error) break;; esac
sleep 10
done
# 4. Check the result
curl -s "http://localhost:1250/v1/transcripts/${TRANSCRIPT_ID}" | python3 -m json.tool
```
Expected result: status `ended`, auto-generated `title`, `short_summary`, `long_summary`, and `transcript` text with `Speaker 0` / `Speaker 1` labels.
CPU-only processing is slow (~15 min for a 3 min audio file). Diarization finishes in ~3 min, transcription takes the rest.
## Troubleshooting
### Port conflicts (most common issue)
If the frontend or backend behaves unexpectedly (e.g., env vars seem ignored, changes don't take effect), **check for port conflicts first**:
```bash
# Check what's listening on key ports
lsof -i :3000 # frontend
lsof -i :1250 # backend
lsof -i :5432 # postgres
lsof -i :3900 # Garage S3 API
lsof -i :6379 # Redis
# Kill stale processes on a port
lsof -ti :3000 | xargs kill
```
Common causes:
- A stale `next dev` or `pnpm dev` process from another terminal/worktree
- Another Docker Compose project (different worktree) with containers on the same ports — the setup script only manages its own project; containers from other projects must be stopped manually (`docker ps` to find them, `docker stop` to kill them)
The setup script checks ports 3000, 1250, 5432, 6379, 3900, 3903 for conflicts before starting services. It ignores OrbStack/Docker Desktop port forwarding processes (which always bind these ports but are not real conflicts).
### OrbStack false port-conflict warnings (Mac)
If you use OrbStack as your Docker runtime, `lsof` will show OrbStack binding ports like 3000, 1250, etc. even when no containers are running. This is OrbStack's port forwarding mechanism — not a real conflict. The setup script filters these out automatically.
### Re-enabling authentication
Standalone runs without authentication (`FEATURE_REQUIRE_LOGIN=false`, `AUTH_BACKEND=none`). To re-enable:
1. In `www/.env.local`: set `FEATURE_REQUIRE_LOGIN=true`, uncomment `AUTHENTIK_ISSUER` and `AUTHENTIK_REFRESH_TOKEN_URL`
2. In `server/.env`: set `AUTH_BACKEND=authentik` (or your backend), configure `AUTH_JWT_AUDIENCE`
3. Restart: `docker compose -f docker-compose.standalone.yml up -d --force-recreate web server`
## What's NOT covered
These require external accounts and infrastructure that can't be scripted:
- **Live meeting rooms** — requires Daily.co account, S3 bucket, IAM roles
- **Authentication** — requires Authentik deployment and OAuth configuration
- **Hatchet workflows** — requires separate Hatchet setup for multitrack processing
- **Production deployment** — see [Deployment Guide](./overview)
## Current status
All steps implemented. The setup script handles everything end-to-end:
- Step 1 (Ollama/LLM) — implemented
- Step 2 (environment files) — implemented
- Step 3 (object storage / Garage) — implemented
- Step 4 (transcription/diarization) — implemented (self-hosted GPU service)
- Steps 5-7 (Docker, migrations, health) — implemented
- **Unified script**: `scripts/setup-standalone.sh`

View File

@@ -0,0 +1,39 @@
FROM python:3.12-slim
ENV PYTHONUNBUFFERED=1 \
UV_LINK_MODE=copy \
UV_NO_CACHE=1
WORKDIR /tmp
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
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"
RUN mkdir -p /app
WORKDIR /app
COPY pyproject.toml uv.lock /app/
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"]

View File

@@ -3,14 +3,14 @@ import os
from fastapi import Depends, HTTPException, status
from fastapi.security import OAuth2PasswordBearer
oauth2_scheme = OAuth2PasswordBearer(tokenUrl="token")
oauth2_scheme = OAuth2PasswordBearer(tokenUrl="token", auto_error=False)
def apikey_auth(apikey: str = Depends(oauth2_scheme)):
def apikey_auth(apikey: str | None = Depends(oauth2_scheme)):
required_key = os.environ.get("REFLECTOR_GPU_APIKEY")
if not required_key:
return
if apikey == required_key:
if apikey and apikey == required_key:
return
raise HTTPException(
status_code=status.HTTP_401_UNAUTHORIZED,

View File

@@ -1,10 +1,65 @@
import logging
import os
import tarfile
import threading
from pathlib import Path
from urllib.request import urlopen
import torch
import torchaudio
import yaml
from pyannote.audio import Pipeline
logger = logging.getLogger(__name__)
S3_BUNDLE_URL = "https://reflector-public.s3.us-east-1.amazonaws.com/pyannote-speaker-diarization-3.1.tar.gz"
BUNDLE_CACHE_DIR = Path("/root/.cache/pyannote-bundle")
def _ensure_model(cache_dir: Path) -> str:
"""Download and extract S3 model bundle if not cached."""
model_dir = cache_dir / "pyannote-speaker-diarization-3.1"
config_path = model_dir / "config.yaml"
if config_path.exists():
logger.info("Using cached model bundle at %s", model_dir)
return str(model_dir)
cache_dir.mkdir(parents=True, exist_ok=True)
tarball_path = cache_dir / "model.tar.gz"
logger.info("Downloading model bundle from %s", S3_BUNDLE_URL)
with urlopen(S3_BUNDLE_URL) as response, open(tarball_path, "wb") as f:
while chunk := response.read(8192):
f.write(chunk)
logger.info("Extracting model bundle")
with tarfile.open(tarball_path, "r:gz") as tar:
tar.extractall(path=cache_dir, filter="data")
tarball_path.unlink()
_patch_config(model_dir, cache_dir)
return str(model_dir)
def _patch_config(model_dir: Path, cache_dir: Path) -> None:
"""Rewrite config.yaml to reference local pytorch_model.bin paths."""
config_path = model_dir / "config.yaml"
with open(config_path) as f:
config = yaml.safe_load(f)
config["pipeline"]["params"]["segmentation"] = str(
cache_dir / "pyannote-segmentation-3.0" / "pytorch_model.bin"
)
config["pipeline"]["params"]["embedding"] = str(
cache_dir / "pyannote-wespeaker-voxceleb-resnet34-LM" / "pytorch_model.bin"
)
with open(config_path, "w") as f:
yaml.dump(config, f)
logger.info("Patched config.yaml with local model paths")
class PyannoteDiarizationService:
def __init__(self):
@@ -14,10 +69,20 @@ class PyannoteDiarizationService:
def load(self):
self._device = "cuda" if torch.cuda.is_available() else "cpu"
self._pipeline = Pipeline.from_pretrained(
"pyannote/speaker-diarization-3.1",
use_auth_token=os.environ.get("HF_TOKEN"),
)
hf_token = os.environ.get("HF_TOKEN")
if hf_token:
logger.info("Loading pyannote model from HuggingFace (HF_TOKEN set)")
self._pipeline = Pipeline.from_pretrained(
"pyannote/speaker-diarization-3.1",
use_auth_token=hf_token,
)
else:
logger.info("HF_TOKEN not set — loading model from S3 bundle")
model_path = _ensure_model(BUNDLE_CACHE_DIR)
config_path = Path(model_path) / "config.yaml"
self._pipeline = Pipeline.from_pretrained(str(config_path))
self._pipeline.to(torch.device(self._device))
def diarize_file(self, file_path: str, timestamp: float = 0.0) -> dict:

14
scripts/garage.toml Normal file
View File

@@ -0,0 +1,14 @@
metadata_dir = "/var/lib/garage/meta"
data_dir = "/var/lib/garage/data"
replication_factor = 1
rpc_secret = "__GARAGE_RPC_SECRET__"
rpc_bind_addr = "[::]:3901"
[s3_api]
api_bind_addr = "[::]:3900"
s3_region = "garage"
root_domain = ".s3.garage.localhost"
[admin]
api_bind_addr = "[::]:3903"

544
scripts/setup-standalone.sh Executable file
View File

@@ -0,0 +1,544 @@
#!/usr/bin/env bash
#
# Standalone local development setup for Reflector.
# Takes a fresh clone to a working instance — no cloud accounts, no API keys.
#
# Usage:
# ./scripts/setup-standalone.sh
#
# Idempotent — safe to re-run at any time.
#
set -euo pipefail
SCRIPT_DIR="$(cd "$(dirname "${BASH_SOURCE[0]}")" && pwd)"
ROOT_DIR="$(cd "$SCRIPT_DIR/.." && pwd)"
SERVER_ENV="$ROOT_DIR/server/.env"
WWW_ENV="$ROOT_DIR/www/.env.local"
MODEL="${LLM_MODEL:-qwen2.5:14b}"
OLLAMA_PORT="${OLLAMA_PORT:-11434}"
OS="$(uname -s)"
# --- Colors ---
RED='\033[0;31m'
GREEN='\033[0;32m'
YELLOW='\033[1;33m'
CYAN='\033[0;36m'
NC='\033[0m'
info() { echo -e "${CYAN}==>${NC} $*"; }
ok() { echo -e "${GREEN}${NC} $*"; }
warn() { echo -e "${YELLOW} !${NC} $*"; }
err() { echo -e "${RED}${NC} $*" >&2; }
# --- Helpers ---
dump_diagnostics() {
local failed_svc="${1:-}"
echo ""
err "========== DIAGNOSTICS =========="
err "Container status:"
compose_cmd ps -a --format "table {{.Name}}\t{{.Status}}" 2>/dev/null || true
echo ""
# Show logs for any container that exited
local stopped
stopped=$(compose_cmd ps -a --format '{{.Name}}\t{{.Status}}' 2>/dev/null \
| grep -iv 'up\|running' | awk -F'\t' '{print $1}' || true)
for c in $stopped; do
err "--- Logs for $c (exited/unhealthy) ---"
docker logs --tail 30 "$c" 2>&1 || true
echo ""
done
# If a specific service failed, always show its logs
if [[ -n "$failed_svc" ]]; then
err "--- Logs for $failed_svc (last 40) ---"
compose_cmd logs "$failed_svc" --tail 40 2>&1 || true
echo ""
# Try health check from inside the container as extra signal
err "--- Internal health check ($failed_svc) ---"
compose_cmd exec -T "$failed_svc" \
curl -sf http://localhost:1250/health 2>&1 || echo "(not reachable internally either)"
fi
err "================================="
}
trap 'dump_diagnostics' ERR
# Get the image ID for a compose service (works even when containers are not running).
svc_image_id() {
local svc="$1"
# Extract image name from compose config YAML, fall back to <project>-<service>
local img_name
img_name=$(compose_cmd config 2>/dev/null \
| sed -n "/^ ${svc}:/,/^ [a-z]/p" | grep '^\s*image:' | awk '{print $2}')
img_name="${img_name:-reflector-$svc}"
docker images -q "$img_name" 2>/dev/null | head -1
}
# Ensure images with build contexts are up-to-date.
# Docker layer cache makes this fast (~seconds) when source hasn't changed.
rebuild_images() {
local svc
for svc in web cpu; do
local old_id
old_id=$(svc_image_id "$svc")
old_id="${old_id:-<none>}"
info "Building $svc..."
compose_cmd build "$svc"
local new_id
new_id=$(svc_image_id "$svc")
if [[ "$old_id" == "$new_id" ]]; then
ok "$svc unchanged (${new_id:0:12})"
else
ok "$svc rebuilt (${old_id:0:12} -> ${new_id:0:12})"
fi
done
}
wait_for_url() {
local url="$1" label="$2" retries="${3:-30}" interval="${4:-2}"
for i in $(seq 1 "$retries"); do
if curl -sf "$url" > /dev/null 2>&1; then
return 0
fi
echo -ne "\r Waiting for $label... ($i/$retries)"
sleep "$interval"
done
echo ""
err "$label not responding at $url after $retries attempts"
return 1
}
env_has_key() {
local file="$1" key="$2"
grep -q "^${key}=" "$file" 2>/dev/null
}
env_set() {
local file="$1" key="$2" value="$3"
if env_has_key "$file" "$key"; then
# Replace existing value (portable sed)
if [[ "$OS" == "Darwin" ]]; then
sed -i '' "s|^${key}=.*|${key}=${value}|" "$file"
else
sed -i "s|^${key}=.*|${key}=${value}|" "$file"
fi
else
echo "${key}=${value}" >> "$file"
fi
}
resolve_symlink() {
local file="$1"
if [[ -L "$file" ]]; then
warn "$(basename "$file") is a symlink — creating standalone copy"
cp -L "$file" "$file.tmp"
rm "$file"
mv "$file.tmp" "$file"
fi
}
compose_cmd() {
local compose_files="-f $ROOT_DIR/docker-compose.standalone.yml"
if [[ "$OS" == "Linux" ]] && [[ -n "${OLLAMA_PROFILE:-}" ]]; then
docker compose $compose_files --profile "$OLLAMA_PROFILE" "$@"
else
docker compose $compose_files "$@"
fi
}
# =========================================================
# Step 1: LLM / Ollama
# =========================================================
step_llm() {
info "Step 1: LLM setup (Ollama + $MODEL)"
case "$OS" in
Darwin)
if ! command -v ollama &> /dev/null; then
err "Ollama not found. Install it:"
err " brew install ollama"
err " # or https://ollama.com/download"
exit 1
fi
# Start if not running
if ! curl -sf "http://localhost:$OLLAMA_PORT/api/tags" > /dev/null 2>&1; then
info "Starting Ollama..."
ollama serve &
disown
fi
wait_for_url "http://localhost:$OLLAMA_PORT/api/tags" "Ollama"
echo ""
# Pull model if not already present
if ollama list 2>/dev/null | awk '{print $1}' | grep -qxF "$MODEL"; then
ok "Model $MODEL already pulled"
else
info "Pulling model $MODEL (this may take a while)..."
ollama pull "$MODEL"
fi
LLM_URL_VALUE="http://host.docker.internal:$OLLAMA_PORT/v1"
;;
Linux)
if command -v nvidia-smi &> /dev/null && nvidia-smi > /dev/null 2>&1; then
ok "NVIDIA GPU detected — using ollama-gpu profile"
OLLAMA_PROFILE="ollama-gpu"
OLLAMA_SVC="ollama"
LLM_URL_VALUE="http://ollama:$OLLAMA_PORT/v1"
else
warn "No NVIDIA GPU — using ollama-cpu profile"
OLLAMA_PROFILE="ollama-cpu"
OLLAMA_SVC="ollama-cpu"
LLM_URL_VALUE="http://ollama-cpu:$OLLAMA_PORT/v1"
fi
info "Starting Ollama container..."
compose_cmd up -d
wait_for_url "http://localhost:$OLLAMA_PORT/api/tags" "Ollama"
echo ""
# Pull model inside container
if compose_cmd exec "$OLLAMA_SVC" ollama list 2>/dev/null | awk '{print $1}' | grep -qxF "$MODEL"; then
ok "Model $MODEL already pulled"
else
info "Pulling model $MODEL inside container (this may take a while)..."
compose_cmd exec "$OLLAMA_SVC" ollama pull "$MODEL"
fi
;;
*)
err "Unsupported OS: $OS"
exit 1
;;
esac
ok "LLM ready ($MODEL via Ollama)"
}
# =========================================================
# Step 2: Generate server/.env
# =========================================================
step_server_env() {
info "Step 2: Generating server/.env"
resolve_symlink "$SERVER_ENV"
if [[ -f "$SERVER_ENV" ]]; then
ok "server/.env already exists — ensuring standalone vars"
else
cat > "$SERVER_ENV" << 'ENVEOF'
# Generated by setup-standalone.sh — standalone local development
# Source of truth for settings: server/reflector/settings.py
ENVEOF
ok "Created server/.env"
fi
# Ensure all standalone-critical vars (appends if missing, replaces if present)
env_set "$SERVER_ENV" "DATABASE_URL" "postgresql+asyncpg://reflector:reflector@postgres:5432/reflector"
env_set "$SERVER_ENV" "REDIS_HOST" "redis"
env_set "$SERVER_ENV" "CELERY_BROKER_URL" "redis://redis:6379/1"
env_set "$SERVER_ENV" "CELERY_RESULT_BACKEND" "redis://redis:6379/1"
env_set "$SERVER_ENV" "AUTH_BACKEND" "none"
env_set "$SERVER_ENV" "PUBLIC_MODE" "true"
# TRANSCRIPT_BACKEND, TRANSCRIPT_URL, DIARIZATION_BACKEND, DIARIZATION_URL
# are set via docker-compose.standalone.yml `environment:` overrides — not written here
# so we don't clobber the user's server/.env for non-standalone use.
env_set "$SERVER_ENV" "TRANSLATION_BACKEND" "passthrough"
env_set "$SERVER_ENV" "LLM_URL" "$LLM_URL_VALUE"
env_set "$SERVER_ENV" "LLM_MODEL" "$MODEL"
env_set "$SERVER_ENV" "LLM_API_KEY" "not-needed"
ok "Standalone vars set (LLM_URL=$LLM_URL_VALUE)"
}
# =========================================================
# Step 3: Object storage (Garage)
# =========================================================
step_storage() {
info "Step 3: Object storage (Garage)"
# Generate garage.toml from template (fill in RPC secret)
GARAGE_TOML="$ROOT_DIR/scripts/garage.toml"
GARAGE_TOML_RUNTIME="$ROOT_DIR/data/garage.toml"
if [[ ! -f "$GARAGE_TOML_RUNTIME" ]]; then
mkdir -p "$ROOT_DIR/data"
RPC_SECRET=$(openssl rand -hex 32)
sed "s|__GARAGE_RPC_SECRET__|${RPC_SECRET}|" "$GARAGE_TOML" > "$GARAGE_TOML_RUNTIME"
fi
compose_cmd up -d garage
wait_for_url "http://localhost:3903/health" "Garage admin API"
echo ""
# Layout: get node ID, assign, apply (skip if already applied)
NODE_ID=$(compose_cmd exec -T garage /garage node id -q 2>/dev/null | tr -d '[:space:]')
LAYOUT_STATUS=$(compose_cmd exec -T garage /garage layout show 2>&1 || true)
if echo "$LAYOUT_STATUS" | grep -q "No nodes"; then
compose_cmd exec -T garage /garage layout assign "$NODE_ID" -c 1G -z dc1
compose_cmd exec -T garage /garage layout apply --version 1
fi
# Create bucket (idempotent — skip if exists)
if ! compose_cmd exec -T garage /garage bucket info reflector-media &>/dev/null; then
compose_cmd exec -T garage /garage bucket create reflector-media
fi
# Create key (idempotent — skip if exists)
CREATED_KEY=false
if compose_cmd exec -T garage /garage key info reflector &>/dev/null; then
ok "Key 'reflector' already exists"
else
KEY_OUTPUT=$(compose_cmd exec -T garage /garage key create reflector)
CREATED_KEY=true
fi
# Grant bucket permissions (idempotent)
compose_cmd exec -T garage /garage bucket allow reflector-media --read --write --key reflector
# Set env vars (only parse key on first create — key info redacts the secret)
env_set "$SERVER_ENV" "TRANSCRIPT_STORAGE_BACKEND" "aws"
env_set "$SERVER_ENV" "TRANSCRIPT_STORAGE_AWS_ENDPOINT_URL" "http://garage:3900"
env_set "$SERVER_ENV" "TRANSCRIPT_STORAGE_AWS_BUCKET_NAME" "reflector-media"
env_set "$SERVER_ENV" "TRANSCRIPT_STORAGE_AWS_REGION" "garage"
if [[ "$CREATED_KEY" == "true" ]]; then
KEY_ID=$(echo "$KEY_OUTPUT" | grep -i "key id" | awk '{print $NF}')
KEY_SECRET=$(echo "$KEY_OUTPUT" | grep -i "secret key" | awk '{print $NF}')
env_set "$SERVER_ENV" "TRANSCRIPT_STORAGE_AWS_ACCESS_KEY_ID" "$KEY_ID"
env_set "$SERVER_ENV" "TRANSCRIPT_STORAGE_AWS_SECRET_ACCESS_KEY" "$KEY_SECRET"
fi
ok "Object storage ready (Garage)"
}
# =========================================================
# Step 4: Generate www/.env.local
# =========================================================
step_www_env() {
info "Step 4: Generating www/.env.local"
resolve_symlink "$WWW_ENV"
if [[ -f "$WWW_ENV" ]]; then
ok "www/.env.local already exists — ensuring standalone vars"
else
cat > "$WWW_ENV" << 'ENVEOF'
# Generated by setup-standalone.sh — standalone local development
ENVEOF
ok "Created www/.env.local"
fi
env_set "$WWW_ENV" "SITE_URL" "http://localhost:3000"
env_set "$WWW_ENV" "NEXTAUTH_URL" "http://localhost:3000"
env_set "$WWW_ENV" "NEXTAUTH_SECRET" "standalone-dev-secret-not-for-production"
env_set "$WWW_ENV" "API_URL" "http://localhost:1250"
env_set "$WWW_ENV" "WEBSOCKET_URL" "ws://localhost:1250"
env_set "$WWW_ENV" "SERVER_API_URL" "http://server:1250"
env_set "$WWW_ENV" "FEATURE_REQUIRE_LOGIN" "false"
ok "Standalone www vars set"
}
# =========================================================
# Step 5: Start all services
# =========================================================
step_services() {
info "Step 5: Starting Docker services"
# Check for port conflicts — stale processes silently shadow Docker port mappings.
# OrbStack/Docker Desktop bind ports for forwarding; ignore those PIDs.
local ports_ok=true
for port in 3000 1250 5432 6379 3900 3903; do
local pids
pids=$(lsof -ti :"$port" 2>/dev/null || true)
for pid in $pids; do
local pname
pname=$(ps -p "$pid" -o comm= 2>/dev/null || true)
# OrbStack and Docker Desktop own port forwarding — not real conflicts
if [[ "$pname" == *"OrbStack"* ]] || [[ "$pname" == *"com.docker"* ]] || [[ "$pname" == *"vpnkit"* ]]; then
continue
fi
warn "Port $port already in use by PID $pid ($pname)"
warn "Kill it with: lsof -ti :$port | xargs kill"
ports_ok=false
done
done
if [[ "$ports_ok" == "false" ]]; then
warn "Port conflicts detected — Docker containers may not be reachable"
warn "Continuing anyway (services will start but may be shadowed)"
fi
# Rebuild images if source has changed (Docker layer cache makes this fast when unchanged)
rebuild_images
# server runs alembic migrations on startup automatically (see runserver.sh)
compose_cmd up -d postgres redis garage cpu server worker beat web
ok "Containers started"
# Quick sanity check — catch containers that exit immediately (bad image, missing file, etc.)
sleep 3
local exited
exited=$(compose_cmd ps -a --format '{{.Name}} {{.Status}}' 2>/dev/null \
| grep -i 'exit' || true)
if [[ -n "$exited" ]]; then
warn "Some containers exited immediately:"
echo "$exited" | while read -r line; do warn " $line"; done
dump_diagnostics
fi
info "Server is running migrations (alembic upgrade head)..."
}
# =========================================================
# Step 6: Health checks
# =========================================================
step_health() {
info "Step 6: Health checks"
# CPU service may take a while on first start (model download + load).
# No host port exposed — check via docker exec.
info "Waiting for CPU service (first start downloads ~1GB of models)..."
local cpu_ok=false
for i in $(seq 1 120); do
if compose_cmd exec -T cpu curl -sf http://localhost:8000/docs > /dev/null 2>&1; then
cpu_ok=true
break
fi
echo -ne "\r Waiting for CPU service... ($i/120)"
sleep 5
done
echo ""
if [[ "$cpu_ok" == "true" ]]; then
ok "CPU service healthy (transcription + diarization)"
else
warn "CPU service not ready yet — it will keep loading in the background"
warn "Check with: docker compose logs cpu"
fi
# Server may take a long time on first run — alembic migrations run before uvicorn starts.
# Use docker exec so this works regardless of network_mode or port mapping.
info "Waiting for Server API (first run includes database migrations)..."
local server_ok=false
for i in $(seq 1 90); do
# Check if container is still running
local svc_status
svc_status=$(compose_cmd ps server --format '{{.Status}}' 2>/dev/null || true)
if [[ -z "$svc_status" ]] || echo "$svc_status" | grep -qi 'exit'; then
echo ""
err "Server container exited unexpectedly"
dump_diagnostics server
exit 1
fi
# Health check from inside container (avoids host networking issues)
if compose_cmd exec -T server curl -sf http://localhost:1250/health > /dev/null 2>&1; then
server_ok=true
break
fi
echo -ne "\r Waiting for Server API... ($i/90)"
sleep 5
done
echo ""
if [[ "$server_ok" == "true" ]]; then
ok "Server API healthy"
else
err "Server API not ready after ~7 minutes"
dump_diagnostics server
exit 1
fi
wait_for_url "http://localhost:3000" "Frontend" 90 3
echo ""
ok "Frontend responding"
# Check LLM reachability from inside a container
if compose_cmd exec -T server \
curl -sf "$LLM_URL_VALUE/models" > /dev/null 2>&1; then
ok "LLM reachable from containers"
else
warn "LLM not reachable from containers at $LLM_URL_VALUE"
warn "Summaries/topics/titles won't work until LLM is accessible"
fi
}
# =========================================================
# Main
# =========================================================
main() {
echo ""
echo "=========================================="
echo " Reflector — Standalone Local Setup"
echo "=========================================="
echo ""
# Ensure we're in the repo root
if [[ ! -f "$ROOT_DIR/docker-compose.yml" ]]; then
err "docker-compose.yml not found in $ROOT_DIR"
err "Run this script from the repo root: ./scripts/setup-standalone.sh"
exit 1
fi
# Ensure Docker Compose V2 plugin is available.
# Check output for "Compose" — without the plugin, `docker compose version`
# may still exit 0 (falling through to `docker version`).
if ! docker compose version 2>/dev/null | grep -qi compose; then
err "Docker Compose plugin not found."
err "Install Docker Desktop, OrbStack, or: brew install docker-compose"
exit 1
fi
# Dockerfiles use RUN --mount which requires BuildKit.
# Docker Desktop/OrbStack bundle it; Colima/bare engine need docker-buildx.
if ! docker buildx version &>/dev/null; then
err "Docker BuildKit (buildx) not found."
err "Install Docker Desktop, OrbStack, or: brew install docker-buildx"
exit 1
fi
# LLM_URL_VALUE is set by step_llm, used by later steps
LLM_URL_VALUE=""
OLLAMA_PROFILE=""
# docker-compose.yml may reference env_files that don't exist yet;
# touch them so compose_cmd works before the steps that populate them.
touch "$SERVER_ENV" "$WWW_ENV"
step_llm
echo ""
step_server_env
echo ""
step_storage
echo ""
step_www_env
echo ""
step_services
echo ""
step_health
echo ""
echo "=========================================="
echo -e " ${GREEN}Reflector is running!${NC}"
echo "=========================================="
echo ""
echo " Frontend: http://localhost:3000"
echo " API: http://localhost:1250"
echo ""
echo " To stop: docker compose down"
echo " To re-run: ./scripts/setup-standalone.sh"
echo ""
}
main "$@"

View File

@@ -66,15 +66,22 @@ TRANSLATE_URL=https://monadical-sas--reflector-translator-web.modal.run
## LLM backend (Required)
##
## Responsible for generating titles, summaries, and topic detection
## Requires OpenAI API key
## Supports any OpenAI-compatible endpoint.
## =======================================================
## OpenAI API key - get from https://platform.openai.com/account/api-keys
LLM_API_KEY=sk-your-openai-api-key
LLM_MODEL=gpt-4o-mini
## --- Option A: Local LLM via Ollama (recommended for dev) ---
## Setup: ./scripts/setup-standalone.sh
## Mac: Ollama runs natively (Metal GPU). Containers reach it via host.docker.internal.
## Linux: docker compose --profile ollama-gpu up -d (or ollama-cpu for no GPU)
LLM_URL=http://host.docker.internal:11434/v1
LLM_MODEL=qwen2.5:14b
LLM_API_KEY=not-needed
## Linux with containerized Ollama: LLM_URL=http://ollama:11434/v1
## Optional: Custom endpoint (defaults to OpenAI)
# LLM_URL=https://api.openai.com/v1
## --- Option B: Remote/cloud LLM ---
#LLM_API_KEY=sk-your-openai-api-key
#LLM_MODEL=gpt-4o-mini
## LLM_URL defaults to OpenAI when unset
## Context size for summary generation (tokens)
LLM_CONTEXT_WINDOW=16000

View File

@@ -68,7 +68,6 @@ evaluation = [
"pydantic>=2.1.1",
]
local = [
"pyannote-audio>=3.3.2",
"faster-whisper>=0.10.0",
]
silero-vad = [

View File

@@ -22,6 +22,8 @@ def asynctask(f):
await database.disconnect()
coro = run_with_db()
if current_task:
return asyncio.run(coro)
try:
loop = asyncio.get_running_loop()
except RuntimeError:

View File

@@ -12,3 +12,5 @@ AccessTokenInfo = auth_module.AccessTokenInfo
authenticated = auth_module.authenticated
current_user = auth_module.current_user
current_user_optional = auth_module.current_user_optional
parse_ws_bearer_token = auth_module.parse_ws_bearer_token
current_user_ws_optional = auth_module.current_user_ws_optional

View File

@@ -1,6 +1,9 @@
from typing import Annotated, List, Optional
from typing import TYPE_CHECKING, Annotated, List, Optional
from fastapi import Depends, HTTPException
if TYPE_CHECKING:
from fastapi import WebSocket
from fastapi.security import APIKeyHeader, OAuth2PasswordBearer
from jose import JWTError, jwt
from pydantic import BaseModel
@@ -124,3 +127,20 @@ async def current_user_optional(
jwtauth: JWTAuth = Depends(),
):
return await _authenticate_user(jwt_token, api_key, jwtauth)
def parse_ws_bearer_token(
websocket: "WebSocket",
) -> tuple[Optional[str], Optional[str]]:
raw = websocket.headers.get("sec-websocket-protocol") or ""
parts = [p.strip() for p in raw.split(",") if p.strip()]
if len(parts) >= 2 and parts[0].lower() == "bearer":
return parts[1], "bearer"
return None, None
async def current_user_ws_optional(websocket: "WebSocket") -> Optional[UserInfo]:
token, _ = parse_ws_bearer_token(websocket)
if not token:
return None
return await _authenticate_user(token, None, JWTAuth())

View File

@@ -1,11 +1,5 @@
from typing import Annotated
from fastapi import Depends
from fastapi.security import OAuth2PasswordBearer
from pydantic import BaseModel
oauth2_scheme = OAuth2PasswordBearer(tokenUrl="token", auto_error=False)
class UserInfo(BaseModel):
sub: str
@@ -15,13 +9,21 @@ class AccessTokenInfo(BaseModel):
pass
def authenticated(token: Annotated[str, Depends(oauth2_scheme)]):
def authenticated():
return None
def current_user(token: Annotated[str, Depends(oauth2_scheme)]):
def current_user():
return None
def current_user_optional(token: Annotated[str, Depends(oauth2_scheme)]):
def current_user_optional():
return None
def parse_ws_bearer_token(websocket):
return None, None
async def current_user_ws_optional(websocket):
return None

View File

@@ -146,6 +146,8 @@ class DailyApiClient:
)
raise DailyApiError(operation, response)
if not response.content:
return {}
return response.json()
# ============================================================================

View File

@@ -99,7 +99,7 @@ def extract_room_name(event: DailyWebhookEvent) -> str | None:
>>> event = DailyWebhookEvent(**webhook_payload)
>>> room_name = extract_room_name(event)
"""
room = event.payload.get("room_name")
room = event.payload.get("room_name") or event.payload.get("room")
# Ensure we return a string, not any falsy value that might be in payload
return room if isinstance(room, str) else None

View File

@@ -6,7 +6,7 @@ Reference: https://docs.daily.co/reference/rest-api/webhooks
from typing import Annotated, Any, Dict, Literal, Union
from pydantic import BaseModel, Field, field_validator
from pydantic import AliasChoices, BaseModel, ConfigDict, Field, field_validator
from reflector.utils.string import NonEmptyString
@@ -41,6 +41,8 @@ class DailyTrack(BaseModel):
Reference: https://docs.daily.co/reference/rest-api/recordings
"""
model_config = ConfigDict(extra="ignore")
type: Literal["audio", "video"]
s3Key: NonEmptyString = Field(description="S3 object key for the track file")
size: int = Field(description="File size in bytes")
@@ -54,6 +56,8 @@ class DailyWebhookEvent(BaseModel):
Reference: https://docs.daily.co/reference/rest-api/webhooks
"""
model_config = ConfigDict(extra="ignore")
version: NonEmptyString = Field(
description="Represents the version of the event. This uses semantic versioning to inform a consumer if the payload has introduced any breaking changes"
)
@@ -82,7 +86,13 @@ class ParticipantJoinedPayload(BaseModel):
Reference: https://docs.daily.co/reference/rest-api/webhooks/events/participant-joined
"""
room_name: NonEmptyString | None = Field(None, description="Daily.co room name")
model_config = ConfigDict(extra="ignore")
room_name: NonEmptyString | None = Field(
None,
description="Daily.co room name",
validation_alias=AliasChoices("room_name", "room"),
)
session_id: NonEmptyString = Field(description="Daily.co session identifier")
user_id: NonEmptyString = Field(description="User identifier (may be encoded)")
user_name: NonEmptyString | None = Field(None, description="User display name")
@@ -100,7 +110,13 @@ class ParticipantLeftPayload(BaseModel):
Reference: https://docs.daily.co/reference/rest-api/webhooks/events/participant-left
"""
room_name: NonEmptyString | None = Field(None, description="Daily.co room name")
model_config = ConfigDict(extra="ignore")
room_name: NonEmptyString | None = Field(
None,
description="Daily.co room name",
validation_alias=AliasChoices("room_name", "room"),
)
session_id: NonEmptyString = Field(description="Daily.co session identifier")
user_id: NonEmptyString = Field(description="User identifier (may be encoded)")
user_name: NonEmptyString | None = Field(None, description="User display name")
@@ -112,6 +128,9 @@ class ParticipantLeftPayload(BaseModel):
_normalize_joined_at = field_validator("joined_at", mode="before")(
normalize_timestamp_to_int
)
_normalize_duration = field_validator("duration", mode="before")(
normalize_timestamp_to_int
)
class RecordingStartedPayload(BaseModel):
@@ -121,6 +140,8 @@ class RecordingStartedPayload(BaseModel):
Reference: https://docs.daily.co/reference/rest-api/webhooks/events/recording-started
"""
model_config = ConfigDict(extra="ignore")
room_name: NonEmptyString | None = Field(None, description="Daily.co room name")
recording_id: NonEmptyString = Field(description="Recording identifier")
start_ts: int | None = Field(None, description="Recording start timestamp")
@@ -138,7 +159,9 @@ class RecordingReadyToDownloadPayload(BaseModel):
Reference: https://docs.daily.co/reference/rest-api/webhooks/events/recording-ready-to-download
"""
type: Literal["cloud", "raw-tracks"] = Field(
model_config = ConfigDict(extra="ignore")
type: Literal["cloud", "cloud-audio-only", "raw-tracks"] = Field(
description="The type of recording that was generated"
)
recording_id: NonEmptyString = Field(
@@ -153,8 +176,9 @@ class RecordingReadyToDownloadPayload(BaseModel):
status: Literal["finished"] = Field(
description="The status of the given recording (always 'finished' in ready-to-download webhook, see RecordingStatus in responses.py for full API statuses)"
)
max_participants: int = Field(
description="The number of participants on the call that were recorded"
max_participants: int | None = Field(
None,
description="The number of participants on the call that were recorded (optional; Daily may omit it in some webhook versions)",
)
duration: int = Field(description="The duration in seconds of the call")
s3_key: NonEmptyString = Field(
@@ -180,6 +204,8 @@ class RecordingErrorPayload(BaseModel):
Reference: https://docs.daily.co/reference/rest-api/webhooks/events/recording-error
"""
model_config = ConfigDict(extra="ignore")
action: Literal["clourd-recording-err", "cloud-recording-error"] = Field(
description="A string describing the event that was emitted (both variants are documented)"
)
@@ -200,6 +226,8 @@ class RecordingErrorPayload(BaseModel):
class ParticipantJoinedEvent(BaseModel):
model_config = ConfigDict(extra="ignore")
version: NonEmptyString
type: Literal["participant.joined"]
id: NonEmptyString
@@ -212,6 +240,8 @@ class ParticipantJoinedEvent(BaseModel):
class ParticipantLeftEvent(BaseModel):
model_config = ConfigDict(extra="ignore")
version: NonEmptyString
type: Literal["participant.left"]
id: NonEmptyString
@@ -224,6 +254,8 @@ class ParticipantLeftEvent(BaseModel):
class RecordingStartedEvent(BaseModel):
model_config = ConfigDict(extra="ignore")
version: NonEmptyString
type: Literal["recording.started"]
id: NonEmptyString
@@ -236,6 +268,8 @@ class RecordingStartedEvent(BaseModel):
class RecordingReadyEvent(BaseModel):
model_config = ConfigDict(extra="ignore")
version: NonEmptyString
type: Literal["recording.ready-to-download"]
id: NonEmptyString
@@ -248,6 +282,8 @@ class RecordingReadyEvent(BaseModel):
class RecordingErrorEvent(BaseModel):
model_config = ConfigDict(extra="ignore")
version: NonEmptyString
type: Literal["recording.error"]
id: NonEmptyString

View File

@@ -1,7 +1,6 @@
"""Search functionality for transcripts and other entities."""
import itertools
import json
from dataclasses import dataclass
from datetime import datetime
from io import StringIO
@@ -27,6 +26,7 @@ from reflector.db.rooms import rooms
from reflector.db.transcripts import SourceKind, TranscriptStatus, transcripts
from reflector.db.utils import is_postgresql
from reflector.logger import logger
from reflector.settings import settings
from reflector.utils.string import NonEmptyString, try_parse_non_empty_string
DEFAULT_SEARCH_LIMIT = 20
@@ -173,9 +173,6 @@ class SearchResult(BaseModel):
total_match_count: NonNegativeInt = Field(
default=0, description="Total number of matches found in the transcript"
)
dag_status: list[dict] | None = Field(
default=None, description="Latest DAG task status for processing transcripts"
)
@field_serializer("created_at", when_used="json")
def serialize_datetime(self, dt: datetime) -> str:
@@ -332,42 +329,6 @@ class SnippetGenerator:
return summary_snippets + webvtt_snippets, total_matches
async def _fetch_dag_statuses(transcript_ids: list[str]) -> dict[str, list[dict]]:
"""Fetch latest DAG_STATUS event data for given transcript IDs.
Returns dict mapping transcript_id -> tasks list from the last DAG_STATUS event.
"""
if not transcript_ids:
return {}
db = get_database()
query = sqlalchemy.select(
[
transcripts.c.id,
transcripts.c.events,
]
).where(transcripts.c.id.in_(transcript_ids))
rows = await db.fetch_all(query)
result: dict[str, list[dict]] = {}
for row in rows:
events_raw = row["events"]
if not events_raw:
continue
# events is stored as JSON list
events = events_raw if isinstance(events_raw, list) else json.loads(events_raw)
# Find last DAG_STATUS event
for ev in reversed(events):
if isinstance(ev, dict) and ev.get("event") == "DAG_STATUS":
tasks = ev.get("data", {}).get("tasks")
if tasks:
result[row["id"]] = tasks
break
return result
class SearchController:
"""Controller for search operations across different entities."""
@@ -436,7 +397,7 @@ class SearchController:
transcripts.c.user_id == params.user_id, rooms.c.is_shared
)
)
else:
elif not settings.PUBLIC_MODE:
base_query = base_query.where(rooms.c.is_shared)
if params.room_id:
base_query = base_query.where(transcripts.c.room_id == params.room_id)
@@ -510,14 +471,6 @@ class SearchController:
logger.error(f"Error processing search results: {e}", exc_info=True)
raise
# Enrich processing transcripts with DAG status
processing_ids = [r.id for r in results if r.status == "processing"]
if processing_ids:
dag_statuses = await _fetch_dag_statuses(processing_ids)
for r in results:
if r.id in dag_statuses:
r.dag_status = dag_statuses[r.id]
return results, total

View File

@@ -5,7 +5,10 @@ import shutil
from contextlib import asynccontextmanager
from datetime import datetime, timedelta, timezone
from pathlib import Path
from typing import Any, Literal, Sequence
from typing import TYPE_CHECKING, Any, Literal, Sequence
if TYPE_CHECKING:
from reflector.ws_events import TranscriptEventName
import sqlalchemy
from fastapi import HTTPException
@@ -184,7 +187,7 @@ class TranscriptWaveform(BaseModel):
class TranscriptEvent(BaseModel):
event: str
event: str # Typed at call sites via ws_events.TranscriptEventName; str here for DB compat
data: dict
@@ -233,8 +236,10 @@ class Transcript(BaseModel):
dt = dt.replace(tzinfo=timezone.utc)
return dt.isoformat()
def add_event(self, event: str, data: BaseModel) -> TranscriptEvent:
ev = TranscriptEvent(event=event, data=data.model_dump(mode="json"))
def add_event(
self, event: "TranscriptEventName", data: BaseModel
) -> TranscriptEvent:
ev = TranscriptEvent(event=event, data=data.model_dump())
self.events.append(ev)
return ev
@@ -406,7 +411,7 @@ class TranscriptController:
query = query.where(
or_(transcripts.c.user_id == user_id, rooms.c.is_shared)
)
else:
elif not settings.PUBLIC_MODE:
query = query.where(rooms.c.is_shared)
if source_kind:
@@ -688,7 +693,7 @@ class TranscriptController:
async def append_event(
self,
transcript: Transcript,
event: str,
event: "TranscriptEventName",
data: Any,
) -> TranscriptEvent:
"""

View File

@@ -12,10 +12,11 @@ import structlog
from reflector.db.transcripts import Transcript, TranscriptEvent, transcripts_controller
from reflector.utils.string import NonEmptyString
from reflector.ws_events import TranscriptEventName
from reflector.ws_manager import get_ws_manager
# Events that should also be sent to user room (matches Celery behavior)
USER_ROOM_EVENTS = {"STATUS", "FINAL_TITLE", "DURATION", "DAG_STATUS"}
USER_ROOM_EVENTS: set[TranscriptEventName] = {"STATUS", "FINAL_TITLE", "DURATION"}
async def broadcast_event(
@@ -81,8 +82,7 @@ async def set_status_and_broadcast(
async def append_event_and_broadcast(
transcript_id: NonEmptyString,
transcript: Transcript,
event_name: NonEmptyString,
# TODO proper dictionary event => type
event_name: TranscriptEventName,
data: Any,
logger: structlog.BoundLogger,
) -> TranscriptEvent:

View File

@@ -12,7 +12,9 @@ import threading
from hatchet_sdk import ClientConfig, Hatchet
from hatchet_sdk.clients.rest.models import V1TaskStatus
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
@@ -113,3 +115,26 @@ class HatchetClientManager:
"""Reset the client instance (for testing)."""
with cls._lock:
cls._instance = None
@classmethod
async def ensure_rate_limit(cls) -> None:
"""Ensure the LLM rate limit exists in Hatchet.
Uses the Hatchet SDK rate_limits client (aio_put). See:
https://docs.hatchet.run/sdks/python/feature-clients/rate_limits
"""
logger.info(
"[Hatchet] Ensuring rate limit exists",
rate_limit_key=LLM_RATE_LIMIT_KEY,
limit=LLM_RATE_LIMIT_PER_SECOND,
)
client = cls.get_client()
await client.rate_limits.aio_put(
key=LLM_RATE_LIMIT_KEY,
limit=LLM_RATE_LIMIT_PER_SECOND,
duration=RateLimitDuration.SECOND,
)
logger.info(
"[Hatchet] Rate limit put successfully",
rate_limit_key=LLM_RATE_LIMIT_KEY,
)

View File

@@ -1,230 +0,0 @@
"""
DAG Progress Reporting — models and transform.
Converts Hatchet V1WorkflowRunDetails into structured DagTask list
for frontend WebSocket/REST consumption.
Ported from render_hatchet_run.py (feat-dag-zulip) which renders markdown;
this module produces structured Pydantic models instead.
"""
from datetime import datetime
from enum import StrEnum
from hatchet_sdk.clients.rest.models import (
V1TaskStatus,
V1WorkflowRunDetails,
WorkflowRunShapeItemForWorkflowRunDetails,
)
from pydantic import BaseModel
class DagTaskStatus(StrEnum):
QUEUED = "queued"
RUNNING = "running"
COMPLETED = "completed"
FAILED = "failed"
CANCELLED = "cancelled"
_HATCHET_TO_DAG_STATUS: dict[V1TaskStatus, DagTaskStatus] = {
V1TaskStatus.QUEUED: DagTaskStatus.QUEUED,
V1TaskStatus.RUNNING: DagTaskStatus.RUNNING,
V1TaskStatus.COMPLETED: DagTaskStatus.COMPLETED,
V1TaskStatus.FAILED: DagTaskStatus.FAILED,
V1TaskStatus.CANCELLED: DagTaskStatus.CANCELLED,
}
class DagTask(BaseModel):
name: str
status: DagTaskStatus
started_at: datetime | None
finished_at: datetime | None
duration_seconds: float | None
parents: list[str]
error: str | None
children_total: int | None
children_completed: int | None
progress_pct: float | None
class DagStatusData(BaseModel):
workflow_run_id: str
tasks: list[DagTask]
def _topo_sort(
shape: list[WorkflowRunShapeItemForWorkflowRunDetails],
) -> list[str]:
"""Topological sort of step_ids from shape DAG (Kahn's algorithm).
Ported from render_hatchet_run.py.
"""
step_ids = {s.step_id for s in shape}
children_map: dict[str, list[str]] = {}
in_degree: dict[str, int] = {sid: 0 for sid in step_ids}
for s in shape:
children = [c for c in (s.children_step_ids or []) if c in step_ids]
children_map[s.step_id] = children
for c in children:
in_degree[c] += 1
queue = sorted(sid for sid, deg in in_degree.items() if deg == 0)
result: list[str] = []
while queue:
node = queue.pop(0)
result.append(node)
for c in children_map.get(node, []):
in_degree[c] -= 1
if in_degree[c] == 0:
queue.append(c)
queue.sort()
return result
def _extract_error_summary(error_message: str | None) -> str | None:
"""Extract first meaningful line from error message, skipping traceback frames."""
if not error_message or not error_message.strip():
return None
err_lines = error_message.strip().split("\n")
err_summary = err_lines[0]
for line in err_lines:
stripped = line.strip()
if stripped and not stripped.startswith(("Traceback", "File ", "{", ")")):
err_summary = stripped
return err_summary
def extract_dag_tasks(details: V1WorkflowRunDetails) -> list[DagTask]:
"""Extract structured DagTask list from Hatchet workflow run details.
Returns tasks in topological order with status, timestamps, parents,
error summaries, and fan-out children counts.
"""
shape = details.shape or []
tasks = details.tasks or []
if not shape:
return []
# Build lookups
step_to_shape: dict[str, WorkflowRunShapeItemForWorkflowRunDetails] = {
s.step_id: s for s in shape
}
step_to_name: dict[str, str] = {s.step_id: s.task_name for s in shape}
# Reverse edges: child -> parent names
parents_by_step: dict[str, list[str]] = {s.step_id: [] for s in shape}
for s in shape:
for child_id in s.children_step_ids or []:
if child_id in parents_by_step:
parents_by_step[child_id].append(step_to_name[s.step_id])
# Join tasks by step_id
from hatchet_sdk.clients.rest.models import V1TaskSummary # noqa: PLC0415
task_by_step: dict[str, V1TaskSummary] = {}
for t in tasks:
if t.step_id and t.step_id in step_to_name:
task_by_step[t.step_id] = t
ordered = _topo_sort(shape)
result: list[DagTask] = []
for step_id in ordered:
name = step_to_name[step_id]
t = task_by_step.get(step_id)
if not t:
result.append(
DagTask(
name=name,
status=DagTaskStatus.QUEUED,
started_at=None,
finished_at=None,
duration_seconds=None,
parents=parents_by_step.get(step_id, []),
error=None,
children_total=None,
children_completed=None,
progress_pct=None,
)
)
continue
status = _HATCHET_TO_DAG_STATUS.get(t.status, DagTaskStatus.QUEUED)
duration_seconds: float | None = None
if t.duration is not None:
duration_seconds = t.duration / 1000.0
# Fan-out children
children_total: int | None = None
children_completed: int | None = None
if t.num_spawned_children and t.num_spawned_children > 0:
children_total = t.num_spawned_children
children_completed = sum(
1 for c in (t.children or []) if c.status == V1TaskStatus.COMPLETED
)
result.append(
DagTask(
name=name,
status=status,
started_at=t.started_at,
finished_at=t.finished_at,
duration_seconds=duration_seconds,
parents=parents_by_step.get(step_id, []),
error=_extract_error_summary(t.error_message),
children_total=children_total,
children_completed=children_completed,
progress_pct=None,
)
)
return result
async def broadcast_dag_status(transcript_id: str, workflow_run_id: str) -> None:
"""Fetch current DAG state from Hatchet and broadcast via WebSocket.
Fire-and-forget: exceptions are logged but never raised.
All imports are deferred for fork-safety (Hatchet workers fork processes).
"""
try:
from reflector.db.transcripts import transcripts_controller # noqa: I001, PLC0415
from reflector.hatchet.broadcast import append_event_and_broadcast # noqa: PLC0415
from reflector.hatchet.client import HatchetClientManager # noqa: PLC0415
from reflector.hatchet.workflows.daily_multitrack_pipeline import ( # noqa: PLC0415
fresh_db_connection,
)
from reflector.logger import logger # noqa: PLC0415
async with fresh_db_connection():
client = HatchetClientManager.get_client()
details = await client.runs.aio_get(workflow_run_id)
dag_tasks = extract_dag_tasks(details)
dag_status = DagStatusData(workflow_run_id=workflow_run_id, tasks=dag_tasks)
transcript = await transcripts_controller.get_by_id(transcript_id)
if transcript:
await append_event_and_broadcast(
transcript_id,
transcript,
"DAG_STATUS",
dag_status,
logger,
)
except Exception:
from reflector.logger import logger # noqa: PLC0415
logger.warning(
"[DAG Progress] Failed to broadcast DAG status",
transcript_id=transcript_id,
workflow_run_id=workflow_run_id,
exc_info=True,
)

View File

@@ -3,6 +3,8 @@ LLM/I/O worker pool for all non-CPU tasks.
Handles: all tasks except mixdown_tracks (transcription, LLM inference, orchestration)
"""
import asyncio
from reflector.hatchet.client import HatchetClientManager
from reflector.hatchet.workflows.daily_multitrack_pipeline import (
daily_multitrack_pipeline,
@@ -20,6 +22,15 @@ POOL = "llm-io"
def main():
hatchet = HatchetClientManager.get_client()
try:
asyncio.run(HatchetClientManager.ensure_rate_limit())
except Exception as e:
logger.warning(
"[Hatchet] Rate limit initialization failed, but continuing. "
"If workflows fail to register, rate limits may need to be created manually.",
error=str(e),
)
logger.info(
"Starting Hatchet LLM worker pool (all tasks except mixdown)",
worker_name=WORKER_NAME,

View File

@@ -171,11 +171,13 @@ async def set_workflow_error_status(transcript_id: NonEmptyString) -> bool:
def _spawn_storage():
"""Create fresh storage instance."""
# TODO: replace direct AwsStorage construction with get_transcripts_storage() factory
return 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,
aws_endpoint_url=settings.TRANSCRIPT_STORAGE_AWS_ENDPOINT_URL,
)
@@ -184,10 +186,7 @@ class Loggable(Protocol):
def make_audio_progress_logger(
ctx: Loggable,
task_name: TaskName,
interval: float = 5.0,
transcript_id: str | None = None,
ctx: Loggable, task_name: TaskName, interval: float = 5.0
) -> Callable[[float | None, float], None]:
"""Create a throttled progress logger callback for audio processing.
@@ -195,7 +194,6 @@ def make_audio_progress_logger(
ctx: Object with .log() method (e.g., Hatchet Context).
task_name: Name to prefix in log messages.
interval: Minimum seconds between log messages.
transcript_id: If provided, broadcasts transient DAG_TASK_PROGRESS events.
Returns:
Callback(progress_pct, audio_position) that logs at most every `interval` seconds.
@@ -217,27 +215,6 @@ def make_audio_progress_logger(
)
last_log_time[0] = now
if transcript_id and progress_pct is not None:
try:
import asyncio # noqa: PLC0415
from reflector.db.transcripts import TranscriptEvent # noqa: PLC0415
from reflector.hatchet.broadcast import broadcast_event # noqa: PLC0415
loop = asyncio.get_event_loop()
loop.create_task(
broadcast_event(
transcript_id,
TranscriptEvent(
event="DAG_TASK_PROGRESS",
data={"task_name": task_name, "progress_pct": progress_pct},
),
logger=logger,
)
)
except Exception:
pass # transient, never fail the callback
return callback
@@ -262,15 +239,8 @@ def with_error_handling(
) -> Callable[[PipelineInput, Context], Coroutine[Any, Any, R]]:
@functools.wraps(func)
async def wrapper(input: PipelineInput, ctx: Context) -> R:
from reflector.hatchet.dag_progress import broadcast_dag_status # noqa: I001, PLC0415
try:
result = await func(input, ctx)
try:
await broadcast_dag_status(input.transcript_id, ctx.workflow_run_id)
except Exception:
pass
return result
return await func(input, ctx)
except Exception as e:
logger.error(
f"[Hatchet] {step_name} failed",
@@ -278,10 +248,6 @@ def with_error_handling(
error=str(e),
exc_info=True,
)
try:
await broadcast_dag_status(input.transcript_id, ctx.workflow_run_id)
except Exception:
pass
if set_error_status:
await set_workflow_error_status(input.transcript_id)
raise
@@ -596,9 +562,7 @@ async def mixdown_tracks(input: PipelineInput, ctx: Context) -> MixdownResult:
target_sample_rate,
offsets_seconds=None,
logger=logger,
progress_callback=make_audio_progress_logger(
ctx, TaskName.MIXDOWN_TRACKS, transcript_id=input.transcript_id
),
progress_callback=make_audio_progress_logger(ctx, TaskName.MIXDOWN_TRACKS),
expected_duration_sec=recording_duration if recording_duration > 0 else None,
)
await writer.flush()

View File

@@ -49,11 +49,13 @@ async def pad_track(input: PaddingInput, ctx: Context) -> PadTrackResult:
from reflector.settings import settings # noqa: PLC0415
from reflector.storage.storage_aws import AwsStorage # noqa: PLC0415
# TODO: replace direct AwsStorage construction with get_transcripts_storage() factory
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,
aws_endpoint_url=settings.TRANSCRIPT_STORAGE_AWS_ENDPOINT_URL,
)
source_url = await storage.get_file_url(

View File

@@ -60,6 +60,7 @@ async def pad_track(input: TrackInput, ctx: Context) -> PadTrackResult:
try:
# Create fresh storage instance to avoid aioboto3 fork issues
# TODO: replace direct AwsStorage construction with get_transcripts_storage() factory
from reflector.settings import settings # noqa: PLC0415
from reflector.storage.storage_aws import AwsStorage # noqa: PLC0415
@@ -68,6 +69,7 @@ async def pad_track(input: TrackInput, ctx: Context) -> PadTrackResult:
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,
aws_endpoint_url=settings.TRANSCRIPT_STORAGE_AWS_ENDPOINT_URL,
)
source_url = await storage.get_file_url(
@@ -159,6 +161,7 @@ async def transcribe_track(input: TrackInput, ctx: Context) -> TranscribeTrackRe
raise ValueError("Missing padded_key from pad_track")
# Presign URL on demand (avoids stale URLs on workflow replay)
# TODO: replace direct AwsStorage construction with get_transcripts_storage() factory
from reflector.settings import settings # noqa: PLC0415
from reflector.storage.storage_aws import AwsStorage # noqa: PLC0415
@@ -167,6 +170,7 @@ async def transcribe_track(input: TrackInput, ctx: Context) -> TranscribeTrackRe
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,
aws_endpoint_url=settings.TRANSCRIPT_STORAGE_AWS_ENDPOINT_URL,
)
audio_url = await storage.get_file_url(

View File

@@ -144,7 +144,18 @@ class StructuredOutputWorkflow(Workflow, Generic[OutputT]):
)
# Network retries handled by OpenAILike (max_retries=3)
response = await Settings.llm.acomplete(json_prompt)
# response_format enables grammar-based constrained decoding on backends
# that support it (DMR/llama.cpp, vLLM, Ollama, OpenAI).
response = await Settings.llm.acomplete(
json_prompt,
response_format={
"type": "json_schema",
"json_schema": {
"name": self.output_cls.__name__,
"schema": self.output_cls.model_json_schema(),
},
},
)
return ExtractionDone(output=response.text)
@step

View File

@@ -62,6 +62,8 @@ from reflector.processors.types import (
from reflector.processors.types import Transcript as TranscriptProcessorType
from reflector.settings import settings
from reflector.storage import get_transcripts_storage
from reflector.views.transcripts import GetTranscriptTopic
from reflector.ws_events import TranscriptEventName
from reflector.ws_manager import WebsocketManager, get_ws_manager
from reflector.zulip import (
get_zulip_message,
@@ -89,7 +91,11 @@ def broadcast_to_sockets(func):
if transcript and transcript.user_id:
# Emit only relevant events to the user room to avoid noisy updates.
# Allowed: STATUS, FINAL_TITLE, DURATION. All are prefixed with TRANSCRIPT_
allowed_user_events = {"STATUS", "FINAL_TITLE", "DURATION"}
allowed_user_events: set[TranscriptEventName] = {
"STATUS",
"FINAL_TITLE",
"DURATION",
}
if resp.event in allowed_user_events:
await self.ws_manager.send_json(
room_id=f"user:{transcript.user_id}",
@@ -244,13 +250,14 @@ class PipelineMainBase(PipelineRunner[PipelineMessage], Generic[PipelineMessage]
)
if isinstance(data, TitleSummaryWithIdProcessorType):
topic.id = data.id
get_topic = GetTranscriptTopic.from_transcript_topic(topic)
async with self.transaction():
transcript = await self.get_transcript()
await transcripts_controller.upsert_topic(transcript, topic)
return await transcripts_controller.append_event(
transcript=transcript,
event="TOPIC",
data=topic,
data=get_topic,
)
@broadcast_to_sockets

View File

@@ -1,74 +0,0 @@
import os
import torch
import torchaudio
from pyannote.audio import Pipeline
from reflector.processors.audio_diarization import AudioDiarizationProcessor
from reflector.processors.audio_diarization_auto import AudioDiarizationAutoProcessor
from reflector.processors.types import AudioDiarizationInput, DiarizationSegment
class AudioDiarizationPyannoteProcessor(AudioDiarizationProcessor):
"""Local diarization processor using pyannote.audio library"""
def __init__(
self,
model_name: str = "pyannote/speaker-diarization-3.1",
pyannote_auth_token: str | None = None,
device: str | None = None,
**kwargs,
):
super().__init__(**kwargs)
self.model_name = model_name
self.auth_token = pyannote_auth_token or os.environ.get("HF_TOKEN")
self.device = device
if device is None:
self.device = "cuda" if torch.cuda.is_available() else "cpu"
self.logger.info(f"Loading pyannote diarization model: {self.model_name}")
self.diarization_pipeline = Pipeline.from_pretrained(
self.model_name, use_auth_token=self.auth_token
)
self.diarization_pipeline.to(torch.device(self.device))
self.logger.info(f"Diarization model loaded on device: {self.device}")
async def _diarize(self, data: AudioDiarizationInput) -> list[DiarizationSegment]:
try:
# Load audio file (audio_url is assumed to be a local file path)
self.logger.info(f"Loading local audio file: {data.audio_url}")
waveform, sample_rate = torchaudio.load(data.audio_url)
audio_input = {"waveform": waveform, "sample_rate": sample_rate}
self.logger.info("Running speaker diarization")
diarization = self.diarization_pipeline(audio_input)
# Convert pyannote diarization output to our format
segments = []
for segment, _, speaker in diarization.itertracks(yield_label=True):
# Extract speaker number from label (e.g., "SPEAKER_00" -> 0)
speaker_id = 0
if speaker.startswith("SPEAKER_"):
try:
speaker_id = int(speaker.split("_")[-1])
except (ValueError, IndexError):
# Fallback to hash-based ID if parsing fails
speaker_id = hash(speaker) % 1000
segments.append(
{
"start": round(segment.start, 3),
"end": round(segment.end, 3),
"speaker": speaker_id,
}
)
self.logger.info(f"Diarization completed with {len(segments)} segments")
return segments
except Exception as e:
self.logger.exception(f"Diarization failed: {e}")
raise
AudioDiarizationAutoProcessor.register("pyannote", AudioDiarizationPyannoteProcessor)

View File

@@ -97,8 +97,11 @@ async def validate_transcript_for_processing(
if transcript.locked:
return ValidationLocked(detail="Recording is locked")
# Check if recording is ready for processing
if transcript.status == "idle" and not transcript.workflow_run_id:
if (
transcript.status == "idle"
and not transcript.workflow_run_id
and not transcript.recording_id
):
return ValidationNotReady(detail="Recording is not ready for processing")
# Check Celery tasks
@@ -267,19 +270,6 @@ async def dispatch_transcript_processing(
)
logger.info("Hatchet workflow dispatched", workflow_id=workflow_id)
try:
from reflector.hatchet.dag_progress import broadcast_dag_status # noqa: I001, PLC0415
await broadcast_dag_status(config.transcript_id, workflow_id)
except Exception:
logger.warning(
"[DAG Progress] Failed initial broadcast",
transcript_id=config.transcript_id,
workflow_id=workflow_id,
exc_info=True,
)
return None
elif isinstance(config, FileProcessingConfig):

View File

@@ -49,6 +49,7 @@ class Settings(BaseSettings):
TRANSCRIPT_STORAGE_AWS_REGION: str = "us-east-1"
TRANSCRIPT_STORAGE_AWS_ACCESS_KEY_ID: str | None = None
TRANSCRIPT_STORAGE_AWS_SECRET_ACCESS_KEY: str | None = None
TRANSCRIPT_STORAGE_AWS_ENDPOINT_URL: str | None = None
# Platform-specific recording storage (follows {PREFIX}_STORAGE_AWS_{CREDENTIAL} pattern)
# Whereby storage configuration
@@ -84,9 +85,7 @@ class Settings(BaseSettings):
)
# Diarization
# backends:
# - pyannote: in-process model loading (no HTTP, runs in same process)
# - modal: HTTP API client (works with Modal.com OR self-hosted gpu/self_hosted/)
# backend: modal — HTTP API client (works with Modal.com OR self-hosted gpu/self_hosted/)
DIARIZATION_ENABLED: bool = True
DIARIZATION_BACKEND: str = "modal"
DIARIZATION_URL: str | None = None
@@ -95,9 +94,6 @@ class Settings(BaseSettings):
# Diarization: modal backend
DIARIZATION_MODAL_API_KEY: str | None = None
# 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

View File

@@ -53,6 +53,7 @@ class AwsStorage(Storage):
aws_access_key_id: str | None = None,
aws_secret_access_key: str | None = None,
aws_role_arn: str | None = None,
aws_endpoint_url: str | None = None,
):
if not aws_bucket_name:
raise ValueError("Storage `aws_storage` require `aws_bucket_name`")
@@ -73,17 +74,26 @@ class AwsStorage(Storage):
self._access_key_id = aws_access_key_id
self._secret_access_key = aws_secret_access_key
self._role_arn = aws_role_arn
self._endpoint_url = aws_endpoint_url
self.aws_folder = ""
if "/" in aws_bucket_name:
self._bucket_name, self.aws_folder = aws_bucket_name.split("/", 1)
self.boto_config = Config(retries={"max_attempts": 3, "mode": "adaptive"})
config_kwargs: dict = {"retries": {"max_attempts": 3, "mode": "adaptive"}}
if aws_endpoint_url:
config_kwargs["s3"] = {"addressing_style": "path"}
self.boto_config = Config(**config_kwargs)
self.session = aioboto3.Session(
aws_access_key_id=aws_access_key_id,
aws_secret_access_key=aws_secret_access_key,
region_name=aws_region,
)
self.base_url = f"https://{self._bucket_name}.s3.amazonaws.com/"
if aws_endpoint_url:
self.base_url = f"{aws_endpoint_url}/{self._bucket_name}/"
else:
self.base_url = f"https://{self._bucket_name}.s3.amazonaws.com/"
# Implement credential properties
@property
@@ -139,7 +149,9 @@ class AwsStorage(Storage):
s3filename = f"{folder}/{filename}" if folder else filename
logger.info(f"Uploading {filename} to S3 {actual_bucket}/{folder}")
async with self.session.client("s3", config=self.boto_config) as client:
async with self.session.client(
"s3", config=self.boto_config, endpoint_url=self._endpoint_url
) as client:
if isinstance(data, bytes):
await client.put_object(Bucket=actual_bucket, Key=s3filename, Body=data)
else:
@@ -162,7 +174,9 @@ class AwsStorage(Storage):
actual_bucket = bucket or self._bucket_name
folder = self.aws_folder
s3filename = f"{folder}/{filename}" if folder else filename
async with self.session.client("s3", config=self.boto_config) as client:
async with self.session.client(
"s3", config=self.boto_config, endpoint_url=self._endpoint_url
) as client:
presigned_url = await client.generate_presigned_url(
operation,
Params={"Bucket": actual_bucket, "Key": s3filename},
@@ -177,7 +191,9 @@ class AwsStorage(Storage):
folder = self.aws_folder
logger.info(f"Deleting {filename} from S3 {actual_bucket}/{folder}")
s3filename = f"{folder}/{filename}" if folder else filename
async with self.session.client("s3", config=self.boto_config) as client:
async with self.session.client(
"s3", config=self.boto_config, endpoint_url=self._endpoint_url
) as client:
await client.delete_object(Bucket=actual_bucket, Key=s3filename)
@handle_s3_client_errors("download")
@@ -186,7 +202,9 @@ class AwsStorage(Storage):
folder = self.aws_folder
logger.info(f"Downloading {filename} from S3 {actual_bucket}/{folder}")
s3filename = f"{folder}/{filename}" if folder else filename
async with self.session.client("s3", config=self.boto_config) as client:
async with self.session.client(
"s3", config=self.boto_config, endpoint_url=self._endpoint_url
) as client:
response = await client.get_object(Bucket=actual_bucket, Key=s3filename)
return await response["Body"].read()
@@ -201,7 +219,9 @@ class AwsStorage(Storage):
logger.info(f"Listing objects from S3 {actual_bucket} with prefix '{s3prefix}'")
keys = []
async with self.session.client("s3", config=self.boto_config) as client:
async with self.session.client(
"s3", config=self.boto_config, endpoint_url=self._endpoint_url
) as client:
paginator = client.get_paginator("list_objects_v2")
async for page in paginator.paginate(Bucket=actual_bucket, Prefix=s3prefix):
if "Contents" in page:
@@ -227,7 +247,9 @@ class AwsStorage(Storage):
folder = self.aws_folder
logger.info(f"Streaming {filename} from S3 {actual_bucket}/{folder}")
s3filename = f"{folder}/{filename}" if folder else filename
async with self.session.client("s3", config=self.boto_config) as client:
async with self.session.client(
"s3", config=self.boto_config, endpoint_url=self._endpoint_url
) as client:
await client.download_fileobj(
Bucket=actual_bucket, Key=s3filename, Fileobj=fileobj
)

View File

@@ -80,7 +80,14 @@ async def webhook(request: Request):
try:
event = event_adapter.validate_python(body_json)
except Exception as e:
logger.error("Failed to parse webhook event", error=str(e), body=body.decode())
err_detail = str(e)
if hasattr(e, "errors"):
err_detail = f"{err_detail}; errors={e.errors()!r}"
logger.error(
"Failed to parse webhook event",
error=err_detail,
body=body.decode(),
)
raise HTTPException(status_code=422, detail="Invalid event format")
match event:

View File

@@ -111,7 +111,6 @@ class GetTranscriptMinimal(BaseModel):
room_id: str | None = None
room_name: str | None = None
audio_deleted: bool | None = None
dag_status: list[dict] | None = None
class TranscriptParticipantWithEmail(TranscriptParticipant):
@@ -492,13 +491,6 @@ async def transcript_get(
)
)
dag_status = None
if transcript.status == "processing" and transcript.events:
for ev in reversed(transcript.events):
if ev.event == "DAG_STATUS":
dag_status = ev.data.get("tasks") if isinstance(ev.data, dict) else None
break
base_data = {
"id": transcript.id,
"user_id": transcript.user_id,
@@ -520,7 +512,6 @@ async def transcript_get(
"room_id": transcript.room_id,
"room_name": room_name,
"audio_deleted": transcript.audio_deleted,
"dag_status": dag_status,
"participants": participants,
}

View File

@@ -5,7 +5,7 @@ from fastapi import APIRouter, Depends, HTTPException, UploadFile
from pydantic import BaseModel
import reflector.auth as auth
from reflector.db.transcripts import transcripts_controller
from reflector.db.transcripts import SourceKind, transcripts_controller
from reflector.pipelines.main_file_pipeline import task_pipeline_file_process
router = APIRouter()
@@ -88,8 +88,10 @@ async def transcript_record_upload(
finally:
container.close()
# set the status to "uploaded"
await transcripts_controller.update(transcript, {"status": "uploaded"})
# set the status to "uploaded" and mark as file source
await transcripts_controller.update(
transcript, {"status": "uploaded", "source_kind": SourceKind.FILE}
)
# launch a background task to process the file
task_pipeline_file_process.delay(transcript_id=transcript_id)

View File

@@ -4,18 +4,22 @@ Transcripts websocket API
"""
from typing import Optional
from fastapi import APIRouter, Depends, HTTPException, WebSocket, WebSocketDisconnect
from fastapi import APIRouter, HTTPException, WebSocket, WebSocketDisconnect
import reflector.auth as auth
from reflector.db.transcripts import transcripts_controller
from reflector.ws_events import TranscriptWsEvent
from reflector.ws_manager import get_ws_manager
router = APIRouter()
@router.get("/transcripts/{transcript_id}/events")
@router.get(
"/transcripts/{transcript_id}/events",
response_model=TranscriptWsEvent,
summary="Transcript WebSocket event schema",
description="Stub exposing the discriminated union of all transcript-level WS events for OpenAPI type generation. Real events are delivered over the WebSocket at the same path.",
)
async def transcript_get_websocket_events(transcript_id: str):
pass
@@ -24,8 +28,9 @@ async def transcript_get_websocket_events(transcript_id: str):
async def transcript_events_websocket(
transcript_id: str,
websocket: WebSocket,
user: Optional[auth.UserInfo] = Depends(auth.current_user_optional),
):
_, negotiated_subprotocol = auth.parse_ws_bearer_token(websocket)
user = await auth.current_user_ws_optional(websocket)
user_id = user["sub"] if user else None
transcript = await transcripts_controller.get_by_id_for_http(
transcript_id, user_id=user_id
@@ -37,23 +42,19 @@ async def transcript_events_websocket(
# use ts:transcript_id as room id
room_id = f"ts:{transcript_id}"
ws_manager = get_ws_manager()
await ws_manager.add_user_to_room(room_id, websocket)
await ws_manager.add_user_to_room(
room_id, websocket, subprotocol=negotiated_subprotocol
)
try:
# on first connection, send all events only to the current user
# Find the last DAG_STATUS to send after other historical events
last_dag_status = None
for event in transcript.events:
# for now, do not send TRANSCRIPT or STATUS options - theses are live event
# not necessary to be sent to the client; but keep the rest
name = event.event
if name in ("TRANSCRIPT", "STATUS"):
continue
if name == "DAG_STATUS":
last_dag_status = event
continue
await websocket.send_json(event.model_dump(mode="json"))
# Send only the most recent DAG_STATUS so reconnecting clients get current state
if last_dag_status is not None:
await websocket.send_json(last_dag_status.model_dump(mode="json"))
# XXX if transcript is final (locked=True and status=ended)
# XXX send a final event to the client and close the connection

View File

@@ -1,13 +1,25 @@
from typing import Optional
from fastapi import APIRouter, WebSocket
from fastapi import APIRouter, WebSocket, WebSocketDisconnect
from reflector.auth.auth_jwt import JWTAuth # type: ignore
from reflector.db.users import user_controller
from reflector.ws_events import UserWsEvent
from reflector.ws_manager import get_ws_manager
router = APIRouter()
@router.get(
"/events",
response_model=UserWsEvent,
summary="User WebSocket event schema",
description="Stub exposing the discriminated union of all user-level WS events for OpenAPI type generation. Real events are delivered over the WebSocket at the same path.",
)
async def user_get_websocket_events():
pass
# Close code for unauthorized WebSocket connections
UNAUTHORISED = 4401
@@ -60,6 +72,8 @@ async def user_events_websocket(websocket: WebSocket):
try:
while True:
await websocket.receive()
except (RuntimeError, WebSocketDisconnect):
pass
finally:
if room_id:
await ws_manager.remove_user_from_room(room_id, websocket)

View File

@@ -0,0 +1,188 @@
"""Typed WebSocket event models.
Defines Pydantic models with Literal discriminators for all WS events.
Exposed via stub GET endpoints so ``pnpm openapi`` generates TS discriminated unions.
"""
from typing import Annotated, Literal, Union
from pydantic import BaseModel, Discriminator
from reflector.db.transcripts import (
TranscriptActionItems,
TranscriptDuration,
TranscriptFinalLongSummary,
TranscriptFinalShortSummary,
TranscriptFinalTitle,
TranscriptStatus,
TranscriptText,
TranscriptWaveform,
)
from reflector.utils.string import NonEmptyString
from reflector.views.transcripts import GetTranscriptTopic
# ---------------------------------------------------------------------------
# Transcript-level event name literal
# ---------------------------------------------------------------------------
TranscriptEventName = Literal[
"TRANSCRIPT",
"TOPIC",
"STATUS",
"FINAL_TITLE",
"FINAL_LONG_SUMMARY",
"FINAL_SHORT_SUMMARY",
"ACTION_ITEMS",
"DURATION",
"WAVEFORM",
]
# ---------------------------------------------------------------------------
# Transcript-level WS event wrappers
# ---------------------------------------------------------------------------
class TranscriptWsTranscript(BaseModel):
event: Literal["TRANSCRIPT"] = "TRANSCRIPT"
data: TranscriptText
class TranscriptWsTopic(BaseModel):
event: Literal["TOPIC"] = "TOPIC"
data: GetTranscriptTopic
class TranscriptWsStatusData(BaseModel):
value: TranscriptStatus
class TranscriptWsStatus(BaseModel):
event: Literal["STATUS"] = "STATUS"
data: TranscriptWsStatusData
class TranscriptWsFinalTitle(BaseModel):
event: Literal["FINAL_TITLE"] = "FINAL_TITLE"
data: TranscriptFinalTitle
class TranscriptWsFinalLongSummary(BaseModel):
event: Literal["FINAL_LONG_SUMMARY"] = "FINAL_LONG_SUMMARY"
data: TranscriptFinalLongSummary
class TranscriptWsFinalShortSummary(BaseModel):
event: Literal["FINAL_SHORT_SUMMARY"] = "FINAL_SHORT_SUMMARY"
data: TranscriptFinalShortSummary
class TranscriptWsActionItems(BaseModel):
event: Literal["ACTION_ITEMS"] = "ACTION_ITEMS"
data: TranscriptActionItems
class TranscriptWsDuration(BaseModel):
event: Literal["DURATION"] = "DURATION"
data: TranscriptDuration
class TranscriptWsWaveform(BaseModel):
event: Literal["WAVEFORM"] = "WAVEFORM"
data: TranscriptWaveform
TranscriptWsEvent = Annotated[
Union[
TranscriptWsTranscript,
TranscriptWsTopic,
TranscriptWsStatus,
TranscriptWsFinalTitle,
TranscriptWsFinalLongSummary,
TranscriptWsFinalShortSummary,
TranscriptWsActionItems,
TranscriptWsDuration,
TranscriptWsWaveform,
],
Discriminator("event"),
]
# ---------------------------------------------------------------------------
# User-level event name literal
# ---------------------------------------------------------------------------
UserEventName = Literal[
"TRANSCRIPT_CREATED",
"TRANSCRIPT_DELETED",
"TRANSCRIPT_STATUS",
"TRANSCRIPT_FINAL_TITLE",
"TRANSCRIPT_DURATION",
]
# ---------------------------------------------------------------------------
# User-level WS event data models
# ---------------------------------------------------------------------------
class UserTranscriptCreatedData(BaseModel):
id: NonEmptyString
class UserTranscriptDeletedData(BaseModel):
id: NonEmptyString
class UserTranscriptStatusData(BaseModel):
id: NonEmptyString
value: TranscriptStatus
class UserTranscriptFinalTitleData(BaseModel):
id: NonEmptyString
title: NonEmptyString
class UserTranscriptDurationData(BaseModel):
id: NonEmptyString
duration: float
# ---------------------------------------------------------------------------
# User-level WS event wrappers
# ---------------------------------------------------------------------------
class UserWsTranscriptCreated(BaseModel):
event: Literal["TRANSCRIPT_CREATED"] = "TRANSCRIPT_CREATED"
data: UserTranscriptCreatedData
class UserWsTranscriptDeleted(BaseModel):
event: Literal["TRANSCRIPT_DELETED"] = "TRANSCRIPT_DELETED"
data: UserTranscriptDeletedData
class UserWsTranscriptStatus(BaseModel):
event: Literal["TRANSCRIPT_STATUS"] = "TRANSCRIPT_STATUS"
data: UserTranscriptStatusData
class UserWsTranscriptFinalTitle(BaseModel):
event: Literal["TRANSCRIPT_FINAL_TITLE"] = "TRANSCRIPT_FINAL_TITLE"
data: UserTranscriptFinalTitleData
class UserWsTranscriptDuration(BaseModel):
event: Literal["TRANSCRIPT_DURATION"] = "TRANSCRIPT_DURATION"
data: UserTranscriptDurationData
UserWsEvent = Annotated[
Union[
UserWsTranscriptCreated,
UserWsTranscriptDeleted,
UserWsTranscriptStatus,
UserWsTranscriptFinalTitle,
UserWsTranscriptDuration,
],
Discriminator("event"),
]

View File

@@ -48,7 +48,15 @@ class RedisPubSubManager:
if not self.redis_connection:
await self.connect()
message = json.dumps(message)
await self.redis_connection.publish(room_id, message)
try:
await self.redis_connection.publish(room_id, message)
except RuntimeError:
# Celery workers run each task in a new event loop (asyncio.run),
# which closes the previous loop. Cached Redis connection is dead.
# Reconnect on the current loop and retry.
self.redis_connection = None
await self.connect()
await self.redis_connection.publish(room_id, message)
async def subscribe(self, room_id: str) -> redis.Redis:
await self.pubsub.subscribe(room_id)

View File

@@ -15,8 +15,7 @@ from reflector.settings import settings
async def setup_webhook(webhook_url: str):
"""
Create or update Daily.co webhook for this environment using dailyco_api module.
Uses DAILY_WEBHOOK_UUID to identify existing webhook.
Create Daily.co webhook. Deletes any existing webhooks first, then creates the new one.
"""
if not settings.DAILY_API_KEY:
print("Error: DAILY_API_KEY not set")
@@ -35,79 +34,37 @@ async def setup_webhook(webhook_url: str):
]
async with DailyApiClient(api_key=settings.DAILY_API_KEY) as client:
webhook_uuid = settings.DAILY_WEBHOOK_UUID
webhooks = await client.list_webhooks()
for wh in webhooks:
await client.delete_webhook(wh.uuid)
print(f"Deleted webhook {wh.uuid}")
if webhook_uuid:
print(f"Updating existing webhook {webhook_uuid}...")
try:
# Note: Daily.co doesn't support PATCH well, so we delete + recreate
await client.delete_webhook(webhook_uuid)
print(f"Deleted old webhook {webhook_uuid}")
request = CreateWebhookRequest(
url=webhook_url,
eventTypes=event_types,
hmac=settings.DAILY_WEBHOOK_SECRET,
)
result = await client.create_webhook(request)
webhook_uuid = result.uuid
request = CreateWebhookRequest(
url=webhook_url,
eventTypes=event_types,
hmac=settings.DAILY_WEBHOOK_SECRET,
)
result = await client.create_webhook(request)
print(f"Created webhook {webhook_uuid} (state: {result.state})")
print(f" URL: {result.url}")
print(
f"✓ Created replacement webhook {result.uuid} (state: {result.state})"
)
print(f" URL: {result.url}")
env_file = Path(__file__).parent.parent / ".env"
if env_file.exists():
lines = env_file.read_text().splitlines()
updated = False
for i, line in enumerate(lines):
if line.startswith("DAILY_WEBHOOK_UUID="):
lines[i] = f"DAILY_WEBHOOK_UUID={webhook_uuid}"
updated = True
break
if not updated:
lines.append(f"DAILY_WEBHOOK_UUID={webhook_uuid}")
env_file.write_text("\n".join(lines) + "\n")
print("✓ Saved DAILY_WEBHOOK_UUID to .env")
webhook_uuid = result.uuid
except Exception as e:
if hasattr(e, "response") and e.response.status_code == 404:
print(f"Webhook {webhook_uuid} not found, creating new one...")
webhook_uuid = None # Fall through to creation
else:
print(f"Error updating webhook: {e}")
return 1
if not webhook_uuid:
print("Creating new webhook...")
request = CreateWebhookRequest(
url=webhook_url,
eventTypes=event_types,
hmac=settings.DAILY_WEBHOOK_SECRET,
)
result = await client.create_webhook(request)
webhook_uuid = result.uuid
print(f"✓ Created webhook {webhook_uuid} (state: {result.state})")
print(f" URL: {result.url}")
print()
print("=" * 60)
print("IMPORTANT: Add this to your environment variables:")
print("=" * 60)
print(f"DAILY_WEBHOOK_UUID: {webhook_uuid}")
print("=" * 60)
print()
# Try to write UUID to .env file
env_file = Path(__file__).parent.parent / ".env"
if env_file.exists():
lines = env_file.read_text().splitlines()
updated = False
# Update existing DAILY_WEBHOOK_UUID line or add it
for i, line in enumerate(lines):
if line.startswith("DAILY_WEBHOOK_UUID="):
lines[i] = f"DAILY_WEBHOOK_UUID={webhook_uuid}"
updated = True
break
if not updated:
lines.append(f"DAILY_WEBHOOK_UUID={webhook_uuid}")
env_file.write_text("\n".join(lines) + "\n")
print(f"✓ Also saved to local .env file")
else:
print(f"⚠ Local .env file not found - please add manually")
return 0
return 0
if __name__ == "__main__":
@@ -117,11 +74,7 @@ if __name__ == "__main__":
"Example: python recreate_daily_webhook.py https://example.com/v1/daily/webhook"
)
print()
print("Behavior:")
print(" - If DAILY_WEBHOOK_UUID set: Deletes old webhook, creates new one")
print(
" - If DAILY_WEBHOOK_UUID empty: Creates new webhook, saves UUID to .env"
)
print("Deletes all existing webhooks, then creates a new one.")
sys.exit(1)
sys.exit(asyncio.run(setup_webhook(sys.argv[1])))

View File

@@ -1,959 +0,0 @@
"""Tests for DAG progress models and transform function.
Tests the extract_dag_tasks function that converts Hatchet V1WorkflowRunDetails
into structured DagTask list for frontend consumption.
"""
from datetime import datetime, timezone
from unittest.mock import AsyncMock, MagicMock, patch
import pytest
from reflector.hatchet.constants import TaskName
from reflector.hatchet.dag_progress import (
DagStatusData,
DagTask,
DagTaskStatus,
extract_dag_tasks,
)
def _make_shape_item(
step_id: str,
task_name: str,
children_step_ids: list[str] | None = None,
) -> MagicMock:
"""Create a mock WorkflowRunShapeItemForWorkflowRunDetails."""
item = MagicMock()
item.step_id = step_id
item.task_name = task_name
item.children_step_ids = children_step_ids or []
return item
def _make_task_summary(
step_id: str,
status: str = "QUEUED",
started_at: datetime | None = None,
finished_at: datetime | None = None,
duration: int | None = None,
error_message: str | None = None,
task_external_id: str | None = None,
num_spawned_children: int | None = None,
children: list | None = None,
) -> MagicMock:
"""Create a mock V1TaskSummary."""
from hatchet_sdk.clients.rest.models import V1TaskStatus
task = MagicMock()
task.step_id = step_id
task.status = V1TaskStatus(status)
task.started_at = started_at
task.finished_at = finished_at
task.duration = duration
task.error_message = error_message
task.task_external_id = task_external_id or f"ext-{step_id}"
task.num_spawned_children = num_spawned_children
task.children = children or []
return task
def _make_details(
shape: list,
tasks: list,
run_id: str = "test-run-id",
) -> MagicMock:
"""Create a mock V1WorkflowRunDetails."""
details = MagicMock()
details.shape = shape
details.tasks = tasks
details.task_events = []
details.run = MagicMock()
details.run.metadata = MagicMock()
details.run.metadata.id = run_id
return details
class TestExtractDagTasksBasic:
"""Test basic extraction of DAG tasks from workflow run details."""
def test_empty_shape_returns_empty_list(self):
details = _make_details(shape=[], tasks=[])
result = extract_dag_tasks(details)
assert result == []
def test_single_task_queued(self):
shape = [_make_shape_item("s1", "get_recording")]
tasks = [_make_task_summary("s1", status="QUEUED")]
details = _make_details(shape, tasks)
result = extract_dag_tasks(details)
assert len(result) == 1
assert result[0].name == "get_recording"
assert result[0].status == DagTaskStatus.QUEUED
assert result[0].parents == []
assert result[0].started_at is None
assert result[0].finished_at is None
assert result[0].duration_seconds is None
assert result[0].error is None
assert result[0].children_total is None
assert result[0].children_completed is None
assert result[0].progress_pct is None
def test_completed_task_with_duration(self):
now = datetime.now(timezone.utc)
shape = [_make_shape_item("s1", "get_recording")]
tasks = [
_make_task_summary(
"s1",
status="COMPLETED",
started_at=now,
finished_at=now,
duration=1500, # milliseconds
)
]
details = _make_details(shape, tasks)
result = extract_dag_tasks(details)
assert result[0].status == DagTaskStatus.COMPLETED
assert result[0].duration_seconds == 1.5
assert result[0].started_at == now
assert result[0].finished_at == now
def test_failed_task_with_error(self):
shape = [_make_shape_item("s1", "get_recording")]
tasks = [
_make_task_summary(
"s1",
status="FAILED",
error_message="Traceback (most recent call last):\n File something\nConnectionError: connection refused",
)
]
details = _make_details(shape, tasks)
result = extract_dag_tasks(details)
assert result[0].status == DagTaskStatus.FAILED
assert result[0].error == "ConnectionError: connection refused"
def test_running_task(self):
now = datetime.now(timezone.utc)
shape = [_make_shape_item("s1", "mixdown_tracks")]
tasks = [
_make_task_summary(
"s1",
status="RUNNING",
started_at=now,
duration=5000,
)
]
details = _make_details(shape, tasks)
result = extract_dag_tasks(details)
assert result[0].status == DagTaskStatus.RUNNING
assert result[0].started_at == now
assert result[0].duration_seconds == 5.0
def test_cancelled_task(self):
shape = [_make_shape_item("s1", "post_zulip")]
tasks = [_make_task_summary("s1", status="CANCELLED")]
details = _make_details(shape, tasks)
result = extract_dag_tasks(details)
assert result[0].status == DagTaskStatus.CANCELLED
class TestExtractDagTasksTopology:
"""Test topological ordering and parent extraction."""
def test_linear_chain_parents(self):
"""A -> B -> C should produce correct parents."""
shape = [
_make_shape_item("s1", "get_recording", children_step_ids=["s2"]),
_make_shape_item("s2", "get_participants", children_step_ids=["s3"]),
_make_shape_item("s3", "process_tracks"),
]
tasks = [
_make_task_summary("s1", status="COMPLETED"),
_make_task_summary("s2", status="COMPLETED"),
_make_task_summary("s3", status="QUEUED"),
]
details = _make_details(shape, tasks)
result = extract_dag_tasks(details)
assert [t.name for t in result] == [
"get_recording",
"get_participants",
"process_tracks",
]
assert result[0].parents == []
assert result[1].parents == ["get_recording"]
assert result[2].parents == ["get_participants"]
def test_diamond_dag(self):
"""
A -> B, A -> C, B -> D, C -> D
D should have parents [B, C] (or [C, B] depending on sort).
"""
shape = [
_make_shape_item("s1", "get_recording", children_step_ids=["s2", "s3"]),
_make_shape_item("s2", "mixdown_tracks", children_step_ids=["s4"]),
_make_shape_item("s3", "detect_topics", children_step_ids=["s4"]),
_make_shape_item("s4", "finalize"),
]
tasks = [
_make_task_summary("s1", status="COMPLETED"),
_make_task_summary("s2", status="RUNNING"),
_make_task_summary("s3", status="RUNNING"),
_make_task_summary("s4", status="QUEUED"),
]
details = _make_details(shape, tasks)
result = extract_dag_tasks(details)
# Topological: s1 first, s2/s3 in some order, s4 last
assert result[0].name == "get_recording"
assert result[-1].name == "finalize"
finalize = result[-1]
assert set(finalize.parents) == {"mixdown_tracks", "detect_topics"}
def test_topological_order_is_stable(self):
"""Verify deterministic ordering (sorted queue in Kahn's)."""
shape = [
_make_shape_item("s_c", "task_c"),
_make_shape_item("s_a", "task_a", children_step_ids=["s_c"]),
_make_shape_item("s_b", "task_b", children_step_ids=["s_c"]),
]
tasks = [
_make_task_summary("s_c", status="QUEUED"),
_make_task_summary("s_a", status="COMPLETED"),
_make_task_summary("s_b", status="COMPLETED"),
]
details = _make_details(shape, tasks)
result = extract_dag_tasks(details)
# s_a and s_b both roots with in-degree 0; sorted alphabetically by step_id
names = [t.name for t in result]
assert names[-1] == "task_c"
# First two should be task_a, task_b (sorted by step_id: s_a < s_b)
assert names[0] == "task_a"
assert names[1] == "task_b"
def test_production_dag_shape(self):
"""Test the real 15-task pipeline topology with mixed statuses.
Simulates a mid-pipeline state where early tasks completed,
middle tasks running, and later tasks still queued.
"""
# Production DAG edges (parent -> children):
# get_recording -> get_participants
# get_participants -> process_tracks
# process_tracks -> mixdown_tracks, detect_topics, finalize
# mixdown_tracks -> generate_waveform
# detect_topics -> generate_title, extract_subjects
# extract_subjects -> process_subjects, identify_action_items
# process_subjects -> generate_recap
# generate_title -> finalize
# generate_recap -> finalize
# identify_action_items -> finalize
# finalize -> cleanup_consent
# cleanup_consent -> post_zulip, send_webhook
shape = [
_make_shape_item(
"s_get_recording", TaskName.GET_RECORDING, ["s_get_participants"]
),
_make_shape_item(
"s_get_participants", TaskName.GET_PARTICIPANTS, ["s_process_tracks"]
),
_make_shape_item(
"s_process_tracks",
TaskName.PROCESS_TRACKS,
["s_mixdown_tracks", "s_detect_topics", "s_finalize"],
),
_make_shape_item(
"s_mixdown_tracks", TaskName.MIXDOWN_TRACKS, ["s_generate_waveform"]
),
_make_shape_item("s_generate_waveform", TaskName.GENERATE_WAVEFORM),
_make_shape_item(
"s_detect_topics",
TaskName.DETECT_TOPICS,
["s_generate_title", "s_extract_subjects"],
),
_make_shape_item(
"s_generate_title", TaskName.GENERATE_TITLE, ["s_finalize"]
),
_make_shape_item(
"s_extract_subjects",
TaskName.EXTRACT_SUBJECTS,
["s_process_subjects", "s_identify_action_items"],
),
_make_shape_item(
"s_process_subjects", TaskName.PROCESS_SUBJECTS, ["s_generate_recap"]
),
_make_shape_item(
"s_generate_recap", TaskName.GENERATE_RECAP, ["s_finalize"]
),
_make_shape_item(
"s_identify_action_items",
TaskName.IDENTIFY_ACTION_ITEMS,
["s_finalize"],
),
_make_shape_item("s_finalize", TaskName.FINALIZE, ["s_cleanup_consent"]),
_make_shape_item(
"s_cleanup_consent",
TaskName.CLEANUP_CONSENT,
["s_post_zulip", "s_send_webhook"],
),
_make_shape_item("s_post_zulip", TaskName.POST_ZULIP),
_make_shape_item("s_send_webhook", TaskName.SEND_WEBHOOK),
]
# Mid-pipeline: early tasks done, middle running, later queued
tasks = [
_make_task_summary("s_get_recording", status="COMPLETED"),
_make_task_summary("s_get_participants", status="COMPLETED"),
_make_task_summary("s_process_tracks", status="COMPLETED"),
_make_task_summary("s_mixdown_tracks", status="RUNNING"),
_make_task_summary("s_generate_waveform", status="QUEUED"),
_make_task_summary("s_detect_topics", status="RUNNING"),
_make_task_summary("s_generate_title", status="QUEUED"),
_make_task_summary("s_extract_subjects", status="QUEUED"),
_make_task_summary("s_process_subjects", status="QUEUED"),
_make_task_summary("s_generate_recap", status="QUEUED"),
_make_task_summary("s_identify_action_items", status="QUEUED"),
_make_task_summary("s_finalize", status="QUEUED"),
_make_task_summary("s_cleanup_consent", status="QUEUED"),
_make_task_summary("s_post_zulip", status="QUEUED"),
_make_task_summary("s_send_webhook", status="QUEUED"),
]
details = _make_details(shape, tasks)
result = extract_dag_tasks(details)
# All 15 tasks present
assert len(result) == 15
result_names = [t.name for t in result]
assert set(result_names) == {
TaskName.GET_RECORDING,
TaskName.GET_PARTICIPANTS,
TaskName.PROCESS_TRACKS,
TaskName.MIXDOWN_TRACKS,
TaskName.GENERATE_WAVEFORM,
TaskName.DETECT_TOPICS,
TaskName.GENERATE_TITLE,
TaskName.EXTRACT_SUBJECTS,
TaskName.PROCESS_SUBJECTS,
TaskName.GENERATE_RECAP,
TaskName.IDENTIFY_ACTION_ITEMS,
TaskName.FINALIZE,
TaskName.CLEANUP_CONSENT,
TaskName.POST_ZULIP,
TaskName.SEND_WEBHOOK,
}
# Topological order invariant: no task appears before its parents
name_to_index = {t.name: i for i, t in enumerate(result)}
for task in result:
for parent_name in task.parents:
assert name_to_index[parent_name] < name_to_index[task.name], (
f"Parent {parent_name} (idx {name_to_index[parent_name]}) "
f"must appear before {task.name} (idx {name_to_index[task.name]})"
)
# finalize has exactly 4 parents
finalize = next(t for t in result if t.name == TaskName.FINALIZE)
assert set(finalize.parents) == {
TaskName.PROCESS_TRACKS,
TaskName.GENERATE_TITLE,
TaskName.GENERATE_RECAP,
TaskName.IDENTIFY_ACTION_ITEMS,
}
# cleanup_consent has 1 parent (finalize)
cleanup = next(t for t in result if t.name == TaskName.CLEANUP_CONSENT)
assert cleanup.parents == [TaskName.FINALIZE]
# post_zulip and send_webhook both have cleanup_consent as parent
post_zulip = next(t for t in result if t.name == TaskName.POST_ZULIP)
send_webhook = next(t for t in result if t.name == TaskName.SEND_WEBHOOK)
assert post_zulip.parents == [TaskName.CLEANUP_CONSENT]
assert send_webhook.parents == [TaskName.CLEANUP_CONSENT]
# Verify statuses propagated correctly
assert (
next(t for t in result if t.name == TaskName.GET_RECORDING).status
== DagTaskStatus.COMPLETED
)
assert (
next(t for t in result if t.name == TaskName.MIXDOWN_TRACKS).status
== DagTaskStatus.RUNNING
)
assert (
next(t for t in result if t.name == TaskName.FINALIZE).status
== DagTaskStatus.QUEUED
)
def test_topological_sort_invariant_complex_dag(self):
"""For a complex DAG, every task's parents appear earlier in the list.
Uses a wider branching/merging DAG than diamond to stress the invariant.
"""
# DAG: A -> B, A -> C, A -> D, B -> E, C -> E, C -> F, D -> F, E -> G, F -> G
shape = [
_make_shape_item("s_a", "task_a", ["s_b", "s_c", "s_d"]),
_make_shape_item("s_b", "task_b", ["s_e"]),
_make_shape_item("s_c", "task_c", ["s_e", "s_f"]),
_make_shape_item("s_d", "task_d", ["s_f"]),
_make_shape_item("s_e", "task_e", ["s_g"]),
_make_shape_item("s_f", "task_f", ["s_g"]),
_make_shape_item("s_g", "task_g"),
]
tasks = [
_make_task_summary("s_a", status="COMPLETED"),
_make_task_summary("s_b", status="COMPLETED"),
_make_task_summary("s_c", status="RUNNING"),
_make_task_summary("s_d", status="COMPLETED"),
_make_task_summary("s_e", status="QUEUED"),
_make_task_summary("s_f", status="QUEUED"),
_make_task_summary("s_g", status="QUEUED"),
]
details = _make_details(shape, tasks)
result = extract_dag_tasks(details)
assert len(result) == 7
name_to_index = {t.name: i for i, t in enumerate(result)}
# Verify invariant: every parent appears before its child
for task in result:
for parent_name in task.parents:
assert name_to_index[parent_name] < name_to_index[task.name], (
f"Parent {parent_name} (idx {name_to_index[parent_name]}) "
f"must appear before {task.name} (idx {name_to_index[task.name]})"
)
# task_g has 2 parents
task_g = next(t for t in result if t.name == "task_g")
assert set(task_g.parents) == {"task_e", "task_f"}
# task_e has 2 parents
task_e = next(t for t in result if t.name == "task_e")
assert set(task_e.parents) == {"task_b", "task_c"}
# task_a is root (first in topological order)
assert result[0].name == "task_a"
assert result[0].parents == []
class TestExtractDagTasksFanOut:
"""Test fan-out tasks with spawned children."""
def test_fan_out_children_counts(self):
from hatchet_sdk.clients.rest.models import V1TaskStatus
child_mocks = []
for status in ["COMPLETED", "COMPLETED", "RUNNING", "QUEUED"]:
child = MagicMock()
child.status = V1TaskStatus(status)
child_mocks.append(child)
shape = [_make_shape_item("s1", "process_tracks")]
tasks = [
_make_task_summary(
"s1",
status="RUNNING",
num_spawned_children=4,
children=child_mocks,
)
]
details = _make_details(shape, tasks)
result = extract_dag_tasks(details)
assert result[0].children_total == 4
assert result[0].children_completed == 2
def test_no_children_when_no_spawn(self):
shape = [_make_shape_item("s1", "get_recording")]
tasks = [
_make_task_summary("s1", status="COMPLETED", num_spawned_children=None)
]
details = _make_details(shape, tasks)
result = extract_dag_tasks(details)
assert result[0].children_total is None
assert result[0].children_completed is None
def test_zero_spawned_children(self):
shape = [_make_shape_item("s1", "process_tracks")]
tasks = [_make_task_summary("s1", status="COMPLETED", num_spawned_children=0)]
details = _make_details(shape, tasks)
result = extract_dag_tasks(details)
assert result[0].children_total is None
assert result[0].children_completed is None
class TestExtractDagTasksErrorExtraction:
"""Test error message extraction logic."""
def test_simple_error(self):
shape = [_make_shape_item("s1", "mixdown_tracks")]
tasks = [
_make_task_summary(
"s1", status="FAILED", error_message="ValueError: no tracks"
)
]
details = _make_details(shape, tasks)
result = extract_dag_tasks(details)
assert result[0].error == "ValueError: no tracks"
def test_traceback_extracts_meaningful_line(self):
error = (
"Traceback (most recent call last):\n"
' File "/app/something.py", line 42\n'
"RuntimeError: out of memory"
)
shape = [_make_shape_item("s1", "mixdown_tracks")]
tasks = [_make_task_summary("s1", status="FAILED", error_message=error)]
details = _make_details(shape, tasks)
result = extract_dag_tasks(details)
assert result[0].error == "RuntimeError: out of memory"
def test_no_error_when_none(self):
shape = [_make_shape_item("s1", "get_recording")]
tasks = [_make_task_summary("s1", status="COMPLETED", error_message=None)]
details = _make_details(shape, tasks)
result = extract_dag_tasks(details)
assert result[0].error is None
def test_empty_error_message(self):
shape = [_make_shape_item("s1", "get_recording")]
tasks = [_make_task_summary("s1", status="FAILED", error_message="")]
details = _make_details(shape, tasks)
result = extract_dag_tasks(details)
assert result[0].error is None
class TestExtractDagTasksMissingData:
"""Test edge cases with missing task data."""
def test_shape_without_matching_task(self):
"""Shape has a step but tasks list doesn't contain it."""
shape = [_make_shape_item("s1", "get_recording")]
tasks = [] # No matching task
details = _make_details(shape, tasks)
result = extract_dag_tasks(details)
assert len(result) == 1
assert result[0].name == "get_recording"
assert result[0].status == DagTaskStatus.QUEUED # default when no task data
assert result[0].started_at is None
def test_none_shape_returns_empty(self):
details = _make_details(shape=[], tasks=[])
details.shape = None
result = extract_dag_tasks(details)
assert result == []
class TestDagStatusData:
"""Test DagStatusData model serialization."""
def test_serialization(self):
task = DagTask(
name="get_recording",
status=DagTaskStatus.COMPLETED,
started_at=datetime(2025, 1, 1, tzinfo=timezone.utc),
finished_at=datetime(2025, 1, 1, 0, 0, 1, tzinfo=timezone.utc),
duration_seconds=1.0,
parents=[],
error=None,
children_total=None,
children_completed=None,
progress_pct=None,
)
data = DagStatusData(workflow_run_id="test-123", tasks=[task])
dumped = data.model_dump(mode="json")
assert dumped["workflow_run_id"] == "test-123"
assert len(dumped["tasks"]) == 1
assert dumped["tasks"][0]["name"] == "get_recording"
assert dumped["tasks"][0]["status"] == "completed"
assert dumped["tasks"][0]["duration_seconds"] == 1.0
class AsyncContextManager:
"""No-op async context manager for mocking fresh_db_connection."""
async def __aenter__(self):
return None
async def __aexit__(self, *args):
return None
class TestBroadcastDagStatus:
"""Test broadcast_dag_status function.
broadcast_dag_status uses deferred imports inside its function body.
We mock the source modules/objects before calling the function.
Importing daily_multitrack_pipeline triggers a cascade
(subject_processing -> HatchetClientManager.get_client at module level),
so we set _instance before the import to prevent real SDK init.
"""
@pytest.fixture(autouse=True)
def _setup_hatchet_mock(self):
"""Set HatchetClientManager._instance to a mock to prevent real SDK init.
Module-level code in workflow files calls get_client() during import.
Setting _instance before import avoids ClientConfig validation.
"""
from reflector.hatchet.client import HatchetClientManager
original = HatchetClientManager._instance
HatchetClientManager._instance = MagicMock()
yield
HatchetClientManager._instance = original
@pytest.mark.asyncio
async def test_broadcasts_dag_status(self):
"""broadcast_dag_status fetches run, transforms, and broadcasts."""
mock_transcript = MagicMock()
mock_transcript.id = "t-123"
mock_details = _make_details(
shape=[_make_shape_item("s1", "get_recording")],
tasks=[_make_task_summary("s1", status="COMPLETED")],
run_id="wf-abc",
)
mock_client = MagicMock()
mock_client.runs.aio_get = AsyncMock(return_value=mock_details)
with (
patch(
"reflector.hatchet.client.HatchetClientManager.get_client",
return_value=mock_client,
),
patch(
"reflector.hatchet.broadcast.append_event_and_broadcast",
new_callable=AsyncMock,
) as mock_broadcast,
patch(
"reflector.db.transcripts.transcripts_controller.get_by_id",
new_callable=AsyncMock,
return_value=mock_transcript,
),
patch(
"reflector.hatchet.workflows.daily_multitrack_pipeline.fresh_db_connection",
return_value=AsyncContextManager(),
),
):
from reflector.hatchet.dag_progress import broadcast_dag_status
await broadcast_dag_status("t-123", "wf-abc")
mock_client.runs.aio_get.assert_called_once_with("wf-abc")
mock_broadcast.assert_called_once()
call_args = mock_broadcast.call_args
assert call_args[0][0] == "t-123" # transcript_id
assert call_args[0][1] is mock_transcript # transcript
assert call_args[0][2] == "DAG_STATUS" # event_name
data = call_args[0][3]
assert isinstance(data, DagStatusData)
assert data.workflow_run_id == "wf-abc"
assert len(data.tasks) == 1
@pytest.mark.asyncio
async def test_swallows_exceptions(self):
"""broadcast_dag_status never raises even when internals fail."""
from reflector.hatchet.dag_progress import broadcast_dag_status
with patch(
"reflector.hatchet.workflows.daily_multitrack_pipeline.fresh_db_connection",
side_effect=RuntimeError("db exploded"),
):
# Should not raise
await broadcast_dag_status("t-123", "wf-abc")
@pytest.mark.asyncio
async def test_no_broadcast_when_transcript_not_found(self):
"""broadcast_dag_status does not broadcast if transcript is None."""
mock_details = _make_details(
shape=[_make_shape_item("s1", "get_recording")],
tasks=[_make_task_summary("s1", status="COMPLETED")],
)
mock_client = MagicMock()
mock_client.runs.aio_get = AsyncMock(return_value=mock_details)
with (
patch(
"reflector.hatchet.client.HatchetClientManager.get_client",
return_value=mock_client,
),
patch(
"reflector.hatchet.workflows.daily_multitrack_pipeline.fresh_db_connection",
return_value=AsyncContextManager(),
),
patch(
"reflector.db.transcripts.transcripts_controller.get_by_id",
new_callable=AsyncMock,
return_value=None,
),
patch(
"reflector.hatchet.broadcast.append_event_and_broadcast",
new_callable=AsyncMock,
) as mock_broadcast,
):
from reflector.hatchet.dag_progress import broadcast_dag_status
await broadcast_dag_status("t-123", "wf-abc")
mock_broadcast.assert_not_called()
class TestMakeAudioProgressLoggerWithBroadcast:
"""Test make_audio_progress_logger with transcript_id for transient broadcasts."""
@pytest.fixture(autouse=True)
def _setup_hatchet_mock(self):
"""Set HatchetClientManager._instance to prevent real SDK init on import."""
from reflector.hatchet.client import HatchetClientManager
original = HatchetClientManager._instance
if original is None:
HatchetClientManager._instance = MagicMock()
yield
HatchetClientManager._instance = original
def test_broadcasts_transient_progress_event(self):
"""When transcript_id provided and progress_pct not None, broadcasts event."""
import asyncio
from reflector.hatchet.workflows.daily_multitrack_pipeline import (
make_audio_progress_logger,
)
ctx = MagicMock()
ctx.log = MagicMock()
loop = asyncio.new_event_loop()
asyncio.set_event_loop(loop)
mock_broadcast = AsyncMock()
tasks_created = []
original_create_task = loop.create_task
def capture_create_task(coro):
task = original_create_task(coro)
tasks_created.append(task)
return task
try:
with (
patch(
"reflector.hatchet.broadcast.broadcast_event",
mock_broadcast,
),
patch.object(loop, "create_task", side_effect=capture_create_task),
):
callback = make_audio_progress_logger(
ctx, TaskName.MIXDOWN_TRACKS, interval=0.0, transcript_id="t-123"
)
callback(50.0, 100.0)
# Run pending tasks
if tasks_created:
loop.run_until_complete(asyncio.gather(*tasks_created))
mock_broadcast.assert_called_once()
event_arg = mock_broadcast.call_args[0][1]
assert event_arg.event == "DAG_TASK_PROGRESS"
assert event_arg.data["task_name"] == TaskName.MIXDOWN_TRACKS
assert event_arg.data["progress_pct"] == 50.0
finally:
loop.close()
def test_no_broadcast_without_transcript_id(self):
"""When transcript_id is None, no broadcast happens."""
from reflector.hatchet.workflows.daily_multitrack_pipeline import (
make_audio_progress_logger,
)
ctx = MagicMock()
with patch(
"reflector.hatchet.broadcast.broadcast_event",
new_callable=AsyncMock,
) as mock_broadcast:
callback = make_audio_progress_logger(
ctx, TaskName.MIXDOWN_TRACKS, interval=0.0, transcript_id=None
)
callback(50.0, 100.0)
mock_broadcast.assert_not_called()
def test_no_broadcast_when_progress_pct_is_none(self):
"""When progress_pct is None, no broadcast happens even with transcript_id."""
from reflector.hatchet.workflows.daily_multitrack_pipeline import (
make_audio_progress_logger,
)
ctx = MagicMock()
with patch(
"reflector.hatchet.broadcast.broadcast_event",
new_callable=AsyncMock,
) as mock_broadcast:
callback = make_audio_progress_logger(
ctx, TaskName.MIXDOWN_TRACKS, interval=0.0, transcript_id="t-123"
)
callback(None, 100.0)
mock_broadcast.assert_not_called()
def test_logging_throttled_by_interval(self):
"""With interval=5.0, rapid calls only log once until interval elapses.
The throttle applies to ctx.log() calls. Broadcasts (fire-and-forget)
are not throttled — they occur every call when transcript_id + progress_pct set.
"""
import asyncio
import time as time_mod
from reflector.hatchet.workflows.daily_multitrack_pipeline import (
make_audio_progress_logger,
)
ctx = MagicMock()
ctx.log = MagicMock()
loop = asyncio.new_event_loop()
asyncio.set_event_loop(loop)
mock_broadcast = AsyncMock()
tasks_created = []
original_create_task = loop.create_task
def capture_create_task(coro):
task = original_create_task(coro)
tasks_created.append(task)
return task
# Controlled monotonic values for the 4 calls from make_audio_progress_logger:
# init (start_time, last_log_time), call1 (now), call2 (now), call3 (now)
# After those, fall back to real time.monotonic() for asyncio internals.
controlled_values = [100.0, 100.0, 101.0, 106.0]
call_index = [0]
real_monotonic = time_mod.monotonic
def mock_monotonic():
if call_index[0] < len(controlled_values):
val = controlled_values[call_index[0]]
call_index[0] += 1
return val
return real_monotonic()
try:
with (
patch(
"reflector.hatchet.workflows.daily_multitrack_pipeline.time.monotonic",
side_effect=mock_monotonic,
),
patch(
"reflector.hatchet.broadcast.broadcast_event",
mock_broadcast,
),
patch.object(loop, "create_task", side_effect=capture_create_task),
):
callback = make_audio_progress_logger(
ctx, TaskName.MIXDOWN_TRACKS, interval=5.0, transcript_id="t-123"
)
# Call 1 at t=100.0: 100.0 - 100.0 = 0.0 < 5.0 => no log
callback(25.0, 50.0)
assert ctx.log.call_count == 0
# Call 2 at t=101.0: 101.0 - 100.0 = 1.0 < 5.0 => no log
callback(50.0, 100.0)
assert ctx.log.call_count == 0
# Call 3 at t=106.0: 106.0 - 100.0 = 6.0 >= 5.0 => logs
callback(75.0, 150.0)
assert ctx.log.call_count == 1
# Run pending broadcast tasks
if tasks_created:
loop.run_until_complete(asyncio.gather(*tasks_created))
# Broadcasts happen on every call (not throttled) — 3 calls total
assert mock_broadcast.call_count == 3
finally:
loop.close()
def test_uses_broadcast_event_not_append_event_and_broadcast(self):
"""Progress events use broadcast_event (transient), not append_event_and_broadcast (persisted)."""
import asyncio
from reflector.hatchet.workflows.daily_multitrack_pipeline import (
make_audio_progress_logger,
)
ctx = MagicMock()
ctx.log = MagicMock()
loop = asyncio.new_event_loop()
asyncio.set_event_loop(loop)
mock_broadcast_event = AsyncMock()
mock_append = AsyncMock()
tasks_created = []
original_create_task = loop.create_task
def capture_create_task(coro):
task = original_create_task(coro)
tasks_created.append(task)
return task
try:
with (
patch(
"reflector.hatchet.broadcast.broadcast_event",
mock_broadcast_event,
),
patch(
"reflector.hatchet.broadcast.append_event_and_broadcast",
mock_append,
),
patch.object(loop, "create_task", side_effect=capture_create_task),
):
callback = make_audio_progress_logger(
ctx, TaskName.MIXDOWN_TRACKS, interval=0.0, transcript_id="t-123"
)
callback(50.0, 100.0)
if tasks_created:
loop.run_until_complete(asyncio.gather(*tasks_created))
# broadcast_event (transient) IS called
mock_broadcast_event.assert_called_once()
# append_event_and_broadcast (persisted) is NOT called
mock_append.assert_not_called()
finally:
loop.close()

View File

@@ -1,181 +0,0 @@
"""Tests for with_error_handling decorator integration with broadcast_dag_status.
The decorator wraps each pipeline task and calls broadcast_dag_status on both
success and failure paths. These tests verify that integration rather than
testing broadcast_dag_status in isolation (which test_dag_progress.py covers).
"""
from unittest.mock import AsyncMock, MagicMock, patch
import pytest
from reflector.hatchet.constants import TaskName
class TestWithErrorHandlingBroadcast:
"""Test with_error_handling decorator's integration with broadcast_dag_status."""
@pytest.fixture(autouse=True)
def _setup_hatchet_mock(self):
"""Set HatchetClientManager._instance to a mock to prevent real SDK init.
Module-level code in workflow files calls get_client() during import.
Setting _instance before import avoids ClientConfig validation.
"""
from reflector.hatchet.client import HatchetClientManager
original = HatchetClientManager._instance
HatchetClientManager._instance = MagicMock()
yield
HatchetClientManager._instance = original
def _make_input(self, transcript_id: str = "t-123") -> MagicMock:
"""Create a mock PipelineInput with transcript_id."""
inp = MagicMock()
inp.transcript_id = transcript_id
return inp
def _make_ctx(self, workflow_run_id: str = "wf-abc") -> MagicMock:
"""Create a mock Context with workflow_run_id."""
ctx = MagicMock()
ctx.workflow_run_id = workflow_run_id
return ctx
@pytest.mark.asyncio
async def test_calls_broadcast_on_success(self):
"""Decorator calls broadcast_dag_status once when task succeeds."""
from reflector.hatchet.workflows.daily_multitrack_pipeline import (
with_error_handling,
)
inner = AsyncMock(return_value="ok")
wrapped = with_error_handling(TaskName.GET_RECORDING)(inner)
with patch(
"reflector.hatchet.dag_progress.broadcast_dag_status",
new_callable=AsyncMock,
) as mock_broadcast:
result = await wrapped(self._make_input(), self._make_ctx())
assert result == "ok"
mock_broadcast.assert_called_once_with("t-123", "wf-abc")
@pytest.mark.asyncio
async def test_calls_broadcast_on_failure(self):
"""Decorator calls broadcast_dag_status once when task raises."""
from reflector.hatchet.workflows.daily_multitrack_pipeline import (
with_error_handling,
)
inner = AsyncMock(side_effect=RuntimeError("boom"))
wrapped = with_error_handling(TaskName.GET_RECORDING)(inner)
with (
patch(
"reflector.hatchet.dag_progress.broadcast_dag_status",
new_callable=AsyncMock,
) as mock_broadcast,
patch(
"reflector.hatchet.workflows.daily_multitrack_pipeline.set_workflow_error_status",
new_callable=AsyncMock,
),
):
with pytest.raises(RuntimeError, match="boom"):
await wrapped(self._make_input(), self._make_ctx())
mock_broadcast.assert_called_once_with("t-123", "wf-abc")
@pytest.mark.asyncio
async def test_swallows_broadcast_exception_on_success(self):
"""Broadcast failure does not crash the task on the success path."""
from reflector.hatchet.workflows.daily_multitrack_pipeline import (
with_error_handling,
)
inner = AsyncMock(return_value="ok")
wrapped = with_error_handling(TaskName.GET_RECORDING)(inner)
with patch(
"reflector.hatchet.dag_progress.broadcast_dag_status",
new_callable=AsyncMock,
side_effect=RuntimeError("broadcast exploded"),
):
result = await wrapped(self._make_input(), self._make_ctx())
assert result == "ok"
@pytest.mark.asyncio
async def test_swallows_broadcast_exception_on_failure(self):
"""Original task exception propagates even when broadcast also fails."""
from reflector.hatchet.workflows.daily_multitrack_pipeline import (
with_error_handling,
)
inner = AsyncMock(side_effect=ValueError("original error"))
wrapped = with_error_handling(TaskName.GET_RECORDING)(inner)
with (
patch(
"reflector.hatchet.dag_progress.broadcast_dag_status",
new_callable=AsyncMock,
side_effect=RuntimeError("broadcast exploded"),
),
patch(
"reflector.hatchet.workflows.daily_multitrack_pipeline.set_workflow_error_status",
new_callable=AsyncMock,
),
):
with pytest.raises(ValueError, match="original error"):
await wrapped(self._make_input(), self._make_ctx())
@pytest.mark.asyncio
async def test_calls_set_workflow_error_status_on_failure(self):
"""On task failure with set_error_status=True (default), calls set_workflow_error_status."""
from reflector.hatchet.workflows.daily_multitrack_pipeline import (
with_error_handling,
)
inner = AsyncMock(side_effect=RuntimeError("boom"))
wrapped = with_error_handling(TaskName.GET_RECORDING)(inner)
with (
patch(
"reflector.hatchet.dag_progress.broadcast_dag_status",
new_callable=AsyncMock,
),
patch(
"reflector.hatchet.workflows.daily_multitrack_pipeline.set_workflow_error_status",
new_callable=AsyncMock,
) as mock_set_error,
):
with pytest.raises(RuntimeError, match="boom"):
await wrapped(self._make_input(), self._make_ctx())
mock_set_error.assert_called_once_with("t-123")
@pytest.mark.asyncio
async def test_no_set_workflow_error_status_when_disabled(self):
"""With set_error_status=False, set_workflow_error_status is NOT called on failure."""
from reflector.hatchet.workflows.daily_multitrack_pipeline import (
with_error_handling,
)
inner = AsyncMock(side_effect=RuntimeError("boom"))
wrapped = with_error_handling(TaskName.GET_RECORDING, set_error_status=False)(
inner
)
with (
patch(
"reflector.hatchet.dag_progress.broadcast_dag_status",
new_callable=AsyncMock,
),
patch(
"reflector.hatchet.workflows.daily_multitrack_pipeline.set_workflow_error_status",
new_callable=AsyncMock,
) as mock_set_error,
):
with pytest.raises(RuntimeError, match="boom"):
await wrapped(self._make_input(), self._make_ctx())
mock_set_error.assert_not_called()

View File

@@ -1,421 +0,0 @@
"""Tests for DAG status REST enrichment on search and transcript GET endpoints."""
from datetime import datetime, timezone
from types import SimpleNamespace
from unittest.mock import AsyncMock, patch
import pytest
import reflector.db.search as search_module
from reflector.db.search import SearchResult, _fetch_dag_statuses
from reflector.db.transcripts import TranscriptEvent
class TestFetchDagStatuses:
"""Test the _fetch_dag_statuses helper."""
@pytest.mark.asyncio
async def test_returns_empty_for_empty_ids(self):
result = await _fetch_dag_statuses([])
assert result == {}
@pytest.mark.asyncio
async def test_extracts_last_dag_status(self):
events = [
{"event": "STATUS", "data": {"value": "processing"}},
{
"event": "DAG_STATUS",
"data": {
"workflow_run_id": "r1",
"tasks": [{"name": "get_recording", "status": "completed"}],
},
},
{
"event": "DAG_STATUS",
"data": {
"workflow_run_id": "r1",
"tasks": [
{"name": "get_recording", "status": "completed"},
{"name": "process_tracks", "status": "running"},
],
},
},
]
mock_row = {"id": "t1", "events": events}
with patch("reflector.db.search.get_database") as mock_db:
mock_db.return_value.fetch_all = AsyncMock(return_value=[mock_row])
result = await _fetch_dag_statuses(["t1"])
assert "t1" in result
assert len(result["t1"]) == 2 # Last DAG_STATUS had 2 tasks
@pytest.mark.asyncio
async def test_skips_transcripts_without_events(self):
mock_row = {"id": "t1", "events": None}
with patch("reflector.db.search.get_database") as mock_db:
mock_db.return_value.fetch_all = AsyncMock(return_value=[mock_row])
result = await _fetch_dag_statuses(["t1"])
assert result == {}
@pytest.mark.asyncio
async def test_skips_transcripts_without_dag_status(self):
events = [
{"event": "STATUS", "data": {"value": "processing"}},
{"event": "DURATION", "data": {"duration": 1000}},
]
mock_row = {"id": "t1", "events": events}
with patch("reflector.db.search.get_database") as mock_db:
mock_db.return_value.fetch_all = AsyncMock(return_value=[mock_row])
result = await _fetch_dag_statuses(["t1"])
assert result == {}
@pytest.mark.asyncio
async def test_handles_json_string_events(self):
"""Events stored as JSON string rather than already-parsed list."""
import json
events = [
{
"event": "DAG_STATUS",
"data": {
"workflow_run_id": "r1",
"tasks": [{"name": "transcribe", "status": "running"}],
},
},
]
mock_row = {"id": "t1", "events": json.dumps(events)}
with patch("reflector.db.search.get_database") as mock_db:
mock_db.return_value.fetch_all = AsyncMock(return_value=[mock_row])
result = await _fetch_dag_statuses(["t1"])
assert "t1" in result
assert len(result["t1"]) == 1
assert result["t1"][0]["name"] == "transcribe"
@pytest.mark.asyncio
async def test_multiple_transcripts(self):
"""Handles multiple transcripts in one call."""
events_t1 = [
{
"event": "DAG_STATUS",
"data": {
"workflow_run_id": "r1",
"tasks": [{"name": "a", "status": "completed"}],
},
},
]
events_t2 = [
{
"event": "DAG_STATUS",
"data": {
"workflow_run_id": "r2",
"tasks": [{"name": "b", "status": "running"}],
},
},
]
mock_rows = [
{"id": "t1", "events": events_t1},
{"id": "t2", "events": events_t2},
]
with patch("reflector.db.search.get_database") as mock_db:
mock_db.return_value.fetch_all = AsyncMock(return_value=mock_rows)
result = await _fetch_dag_statuses(["t1", "t2"])
assert "t1" in result
assert "t2" in result
assert result["t1"][0]["name"] == "a"
assert result["t2"][0]["name"] == "b"
@pytest.mark.asyncio
async def test_dag_status_without_tasks_key_skipped(self):
"""DAG_STATUS event with no tasks key in data should be skipped."""
events = [
{"event": "DAG_STATUS", "data": {"workflow_run_id": "r1"}},
]
mock_row = {"id": "t1", "events": events}
with patch("reflector.db.search.get_database") as mock_db:
mock_db.return_value.fetch_all = AsyncMock(return_value=[mock_row])
result = await _fetch_dag_statuses(["t1"])
assert result == {}
def _extract_dag_status_from_transcript(transcript):
"""Replicate the dag_status extraction logic from transcript_get view.
This mirrors the code in reflector/views/transcripts.py lines 495-500:
dag_status = None
if transcript.status == "processing" and transcript.events:
for ev in reversed(transcript.events):
if ev.event == "DAG_STATUS":
dag_status = ev.data.get("tasks") if isinstance(ev.data, dict) else None
break
"""
dag_status = None
if transcript.status == "processing" and transcript.events:
for ev in reversed(transcript.events):
if ev.event == "DAG_STATUS":
dag_status = ev.data.get("tasks") if isinstance(ev.data, dict) else None
break
return dag_status
class TestTranscriptGetDagStatusExtraction:
"""Test dag_status extraction logic from transcript_get endpoint.
The actual endpoint is complex to set up, so we test the extraction
logic directly using the same code pattern from the view.
"""
def test_processing_transcript_with_dag_status_events(self):
"""Processing transcript with DAG_STATUS events returns tasks from last event."""
transcript = SimpleNamespace(
status="processing",
events=[
TranscriptEvent(event="STATUS", data={"value": "processing"}),
TranscriptEvent(
event="DAG_STATUS",
data={
"workflow_run_id": "r1",
"tasks": [{"name": "get_recording", "status": "completed"}],
},
),
TranscriptEvent(
event="DAG_STATUS",
data={
"workflow_run_id": "r1",
"tasks": [
{"name": "get_recording", "status": "completed"},
{"name": "transcribe", "status": "running"},
],
},
),
],
)
result = _extract_dag_status_from_transcript(transcript)
assert result is not None
assert len(result) == 2
assert result[0]["name"] == "get_recording"
assert result[1]["name"] == "transcribe"
assert result[1]["status"] == "running"
def test_processing_transcript_without_dag_status_events(self):
"""Processing transcript with only non-DAG_STATUS events returns None."""
transcript = SimpleNamespace(
status="processing",
events=[
TranscriptEvent(event="STATUS", data={"value": "processing"}),
TranscriptEvent(event="DURATION", data={"duration": 1000}),
],
)
result = _extract_dag_status_from_transcript(transcript)
assert result is None
def test_ended_transcript_with_dag_status_events(self):
"""Ended transcript with DAG_STATUS events returns None (status check)."""
transcript = SimpleNamespace(
status="ended",
events=[
TranscriptEvent(
event="DAG_STATUS",
data={
"workflow_run_id": "r1",
"tasks": [{"name": "transcribe", "status": "completed"}],
},
),
],
)
result = _extract_dag_status_from_transcript(transcript)
assert result is None
def test_processing_transcript_with_empty_events(self):
"""Processing transcript with empty events list returns None."""
transcript = SimpleNamespace(
status="processing",
events=[],
)
result = _extract_dag_status_from_transcript(transcript)
assert result is None
def test_processing_transcript_with_none_events(self):
"""Processing transcript with None events returns None."""
transcript = SimpleNamespace(
status="processing",
events=None,
)
result = _extract_dag_status_from_transcript(transcript)
assert result is None
def test_extracts_last_dag_status_not_first(self):
"""Should pick the last DAG_STATUS event (most recent), not the first."""
transcript = SimpleNamespace(
status="processing",
events=[
TranscriptEvent(
event="DAG_STATUS",
data={
"workflow_run_id": "r1",
"tasks": [{"name": "a", "status": "running"}],
},
),
TranscriptEvent(event="STATUS", data={"value": "processing"}),
TranscriptEvent(
event="DAG_STATUS",
data={
"workflow_run_id": "r1",
"tasks": [
{"name": "a", "status": "completed"},
{"name": "b", "status": "running"},
],
},
),
],
)
result = _extract_dag_status_from_transcript(transcript)
assert len(result) == 2
assert result[0]["status"] == "completed"
assert result[1]["name"] == "b"
class TestSearchEnrichmentIntegration:
"""Test DAG status enrichment in search results.
The search function enriches processing transcripts with dag_status
by calling _fetch_dag_statuses for processing IDs and assigning results.
We test this enrichment logic by mocking _fetch_dag_statuses.
"""
def _make_search_result(self, id: str, status: str) -> SearchResult:
"""Create a minimal SearchResult for testing."""
return SearchResult(
id=id,
title=f"Transcript {id}",
user_id="u1",
room_id=None,
room_name=None,
source_kind="live",
created_at=datetime(2024, 1, 1, tzinfo=timezone.utc),
status=status,
rank=1.0,
duration=60.0,
search_snippets=[],
total_match_count=0,
dag_status=None,
)
@pytest.mark.asyncio
async def test_processing_result_gets_dag_status(self):
"""SearchResult with status='processing' and matching DAG_STATUS events
gets dag_status populated."""
results = [self._make_search_result("t1", "processing")]
dag_tasks = [
{"name": "get_recording", "status": "completed"},
{"name": "transcribe", "status": "running"},
]
with patch.object(
search_module,
"_fetch_dag_statuses",
new_callable=AsyncMock,
return_value={"t1": dag_tasks},
) as mock_fetch:
# Replicate the enrichment logic from SearchController.search_transcripts
processing_ids = [r.id for r in results if r.status == "processing"]
if processing_ids:
dag_statuses = await search_module._fetch_dag_statuses(processing_ids)
for r in results:
if r.id in dag_statuses:
r.dag_status = dag_statuses[r.id]
mock_fetch.assert_called_once_with(["t1"])
assert results[0].dag_status == dag_tasks
@pytest.mark.asyncio
async def test_ended_result_does_not_trigger_fetch(self):
"""SearchResult with status='ended' does NOT trigger _fetch_dag_statuses."""
results = [self._make_search_result("t1", "ended")]
with patch.object(
search_module,
"_fetch_dag_statuses",
new_callable=AsyncMock,
return_value={},
) as mock_fetch:
processing_ids = [r.id for r in results if r.status == "processing"]
if processing_ids:
dag_statuses = await search_module._fetch_dag_statuses(processing_ids)
for r in results:
if r.id in dag_statuses:
r.dag_status = dag_statuses[r.id]
mock_fetch.assert_not_called()
assert results[0].dag_status is None
@pytest.mark.asyncio
async def test_mixed_processing_and_ended_results(self):
"""Only processing results get enriched; ended results stay None."""
results = [
self._make_search_result("t1", "processing"),
self._make_search_result("t2", "ended"),
self._make_search_result("t3", "processing"),
]
dag_tasks_t1 = [{"name": "transcribe", "status": "running"}]
dag_tasks_t3 = [{"name": "diarize", "status": "completed"}]
with patch.object(
search_module,
"_fetch_dag_statuses",
new_callable=AsyncMock,
return_value={"t1": dag_tasks_t1, "t3": dag_tasks_t3},
) as mock_fetch:
processing_ids = [r.id for r in results if r.status == "processing"]
if processing_ids:
dag_statuses = await search_module._fetch_dag_statuses(processing_ids)
for r in results:
if r.id in dag_statuses:
r.dag_status = dag_statuses[r.id]
mock_fetch.assert_called_once_with(["t1", "t3"])
assert results[0].dag_status == dag_tasks_t1
assert results[1].dag_status is None
assert results[2].dag_status == dag_tasks_t3
@pytest.mark.asyncio
async def test_processing_result_without_dag_events_stays_none(self):
"""Processing result with no DAG_STATUS events in DB stays dag_status=None."""
results = [self._make_search_result("t1", "processing")]
with patch.object(
search_module,
"_fetch_dag_statuses",
new_callable=AsyncMock,
return_value={},
) as mock_fetch:
processing_ids = [r.id for r in results if r.status == "processing"]
if processing_ids:
dag_statuses = await search_module._fetch_dag_statuses(processing_ids)
for r in results:
if r.id in dag_statuses:
r.dag_status = dag_statuses[r.id]
mock_fetch.assert_called_once_with(["t1"])
assert results[0].dag_status is None

View File

@@ -255,7 +255,7 @@ async def test_validation_locked_transcript():
@pytest.mark.usefixtures("setup_database")
@pytest.mark.asyncio
async def test_validation_idle_transcript():
"""Test that validation rejects idle transcripts (not ready)."""
"""Test that validation rejects idle transcripts without recording (file upload not ready)."""
from reflector.services.transcript_process import (
ValidationNotReady,
validate_transcript_for_processing,
@@ -274,6 +274,34 @@ async def test_validation_idle_transcript():
assert "not ready" in result.detail.lower()
@pytest.mark.usefixtures("setup_database")
@pytest.mark.asyncio
async def test_validation_idle_transcript_with_recording_allowed():
"""Test that validation allows idle transcripts with recording_id (multitrack ready/retry)."""
from reflector.services.transcript_process import (
ValidationOk,
validate_transcript_for_processing,
)
mock_transcript = Transcript(
id="test-transcript-id",
name="Test",
status="idle",
source_kind="room",
recording_id="test-recording-id",
)
with patch(
"reflector.services.transcript_process.task_is_scheduled_or_active"
) as mock_celery_check:
mock_celery_check.return_value = False
result = await validate_transcript_for_processing(mock_transcript)
assert isinstance(result, ValidationOk)
assert result.recording_id == "test-recording-id"
@pytest.mark.usefixtures("setup_database")
@pytest.mark.asyncio
async def test_prepare_multitrack_config():

View File

@@ -319,3 +319,51 @@ def test_aws_storage_constructor_rejects_mixed_auth():
aws_secret_access_key="test-secret",
aws_role_arn="arn:aws:iam::123456789012:role/test-role",
)
@pytest.mark.asyncio
async def test_aws_storage_custom_endpoint_url():
"""Test that custom endpoint_url configures path-style addressing and passes endpoint to client."""
storage = AwsStorage(
aws_bucket_name="reflector-media",
aws_region="garage",
aws_access_key_id="GKtest",
aws_secret_access_key="secret",
aws_endpoint_url="http://garage:3900",
)
assert storage._endpoint_url == "http://garage:3900"
assert storage.boto_config.s3["addressing_style"] == "path"
assert storage.base_url == "http://garage:3900/reflector-media/"
# retries config preserved (merge, not replace)
assert storage.boto_config.retries["max_attempts"] == 3
mock_client = AsyncMock()
mock_client.put_object = AsyncMock()
mock_client.__aenter__ = AsyncMock(return_value=mock_client)
mock_client.__aexit__ = AsyncMock(return_value=None)
mock_client.generate_presigned_url = AsyncMock(
return_value="http://garage:3900/reflector-media/test.txt"
)
with patch.object(
storage.session, "client", return_value=mock_client
) as mock_session_client:
await storage.put_file("test.txt", b"data")
mock_session_client.assert_called_with(
"s3", config=storage.boto_config, endpoint_url="http://garage:3900"
)
@pytest.mark.asyncio
async def test_aws_storage_none_endpoint_url():
"""Test that None endpoint preserves current AWS behavior."""
storage = AwsStorage(
aws_bucket_name="reflector-bucket",
aws_region="us-east-1",
aws_access_key_id="AKIAtest",
aws_secret_access_key="secret",
)
assert storage._endpoint_url is None
assert storage.base_url == "https://reflector-bucket.s3.amazonaws.com/"
# No s3 addressing_style override — boto_config should only have retries
assert not hasattr(storage.boto_config, "s3") or storage.boto_config.s3 is None

View File

@@ -1,331 +0,0 @@
"""WebSocket broadcast delivery tests for STATUS and DAG_STATUS events.
Tests the full chain identified in DEBUG.md:
broadcast_event() → ws_manager.send_json() → Redis/in-memory pub/sub
→ _pubsub_data_reader() → socket.send_json() → WebSocket client
Covers:
1. STATUS event delivery to transcript room WS
2. DAG_STATUS event delivery to transcript room WS
3. Full broadcast_event() chain (requires broadcast.py patching)
4. _pubsub_data_reader resilience when a client disconnects
"""
import asyncio
import threading
import time
import pytest
from httpx import AsyncClient
from httpx_ws import aconnect_ws
from uvicorn import Config, Server
@pytest.fixture
def appserver_ws_broadcast(setup_database, monkeypatch):
"""Start real uvicorn server for WebSocket broadcast tests.
Also patches broadcast.py's get_ws_manager (missing from conftest autouse fixture).
"""
# Patch broadcast.py's get_ws_manager — conftest.py misses this module.
# Without this, broadcast_event() creates a real Redis ws_manager.
import reflector.ws_manager as ws_mod
from reflector.app import app
from reflector.db import get_database
monkeypatch.setattr(
"reflector.hatchet.broadcast.get_ws_manager", ws_mod.get_ws_manager
)
host = "127.0.0.1"
port = 1259
server_started = threading.Event()
server_exception = None
server_instance = None
def run_server():
nonlocal server_exception, server_instance
try:
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():
database = get_database()
await database.connect()
try:
await server_instance.serve()
finally:
await database.disconnect()
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()
server_started.wait(timeout=30)
if server_exception:
raise server_exception
time.sleep(0.5)
yield host, port
if server_instance:
server_instance.should_exit = True
server_thread.join(timeout=2.0)
from reflector.ws_manager import reset_ws_manager
reset_ws_manager()
async def _create_transcript(host: str, port: int, name: str) -> str:
"""Create a transcript via ASGI transport and return its ID."""
from reflector.app import app
async with AsyncClient(app=app, base_url=f"http://{host}:{port}/v1") as ac:
resp = await ac.post("/transcripts", json={"name": name})
assert resp.status_code == 200, f"Failed to create transcript: {resp.text}"
return resp.json()["id"]
async def _drain_historical_events(ws, timeout: float = 0.5) -> list[dict]:
"""Read all historical events sent on WS connect (non-blocking drain)."""
events = []
deadline = asyncio.get_event_loop().time() + timeout
while asyncio.get_event_loop().time() < deadline:
try:
msg = await asyncio.wait_for(ws.receive_json(), timeout=0.1)
events.append(msg)
except (asyncio.TimeoutError, Exception):
break
return events
# ---------------------------------------------------------------------------
# Test 1: STATUS event delivery via ws_manager.send_json
# ---------------------------------------------------------------------------
@pytest.mark.asyncio
async def test_transcript_ws_receives_status_via_send_json(appserver_ws_broadcast):
"""STATUS event published via ws_manager.send_json() arrives at transcript room WS."""
host, port = appserver_ws_broadcast
transcript_id = await _create_transcript(host, port, "Status send_json test")
ws_url = f"http://{host}:{port}/v1/transcripts/{transcript_id}/events"
async with aconnect_ws(ws_url) as ws:
await _drain_historical_events(ws)
import reflector.ws_manager as ws_mod
ws_manager = ws_mod.get_ws_manager()
await ws_manager.send_json(
room_id=f"ts:{transcript_id}",
message={"event": "STATUS", "data": {"value": "processing"}},
)
msg = await asyncio.wait_for(ws.receive_json(), timeout=5.0)
assert msg["event"] == "STATUS"
assert msg["data"]["value"] == "processing"
# ---------------------------------------------------------------------------
# Test 2: DAG_STATUS event delivery via ws_manager.send_json
# ---------------------------------------------------------------------------
@pytest.mark.asyncio
async def test_transcript_ws_receives_dag_status_via_send_json(appserver_ws_broadcast):
"""DAG_STATUS event published via ws_manager.send_json() arrives at transcript room WS."""
host, port = appserver_ws_broadcast
transcript_id = await _create_transcript(host, port, "DAG_STATUS send_json test")
dag_payload = {
"event": "DAG_STATUS",
"data": {
"workflow_run_id": "test-run-123",
"tasks": [
{
"name": "get_recording",
"status": "completed",
"started_at": "2025-01-01T00:00:00Z",
"finished_at": "2025-01-01T00:00:05Z",
"duration_seconds": 5.0,
"parents": [],
"error": None,
"children_total": None,
"children_completed": None,
"progress_pct": None,
},
{
"name": "process_tracks",
"status": "running",
"started_at": "2025-01-01T00:00:05Z",
"finished_at": None,
"duration_seconds": None,
"parents": ["get_recording"],
"error": None,
"children_total": 3,
"children_completed": 1,
"progress_pct": 33.3,
},
],
},
}
ws_url = f"http://{host}:{port}/v1/transcripts/{transcript_id}/events"
async with aconnect_ws(ws_url) as ws:
await _drain_historical_events(ws)
import reflector.ws_manager as ws_mod
ws_manager = ws_mod.get_ws_manager()
await ws_manager.send_json(
room_id=f"ts:{transcript_id}",
message=dag_payload,
)
msg = await asyncio.wait_for(ws.receive_json(), timeout=5.0)
assert msg["event"] == "DAG_STATUS"
assert msg["data"]["workflow_run_id"] == "test-run-123"
assert len(msg["data"]["tasks"]) == 2
assert msg["data"]["tasks"][0]["name"] == "get_recording"
assert msg["data"]["tasks"][0]["status"] == "completed"
assert msg["data"]["tasks"][1]["name"] == "process_tracks"
assert msg["data"]["tasks"][1]["children_completed"] == 1
# ---------------------------------------------------------------------------
# Test 3: Full broadcast_event() chain for STATUS
# ---------------------------------------------------------------------------
@pytest.mark.asyncio
async def test_broadcast_event_delivers_status_to_transcript_ws(appserver_ws_broadcast):
"""broadcast_event() end-to-end: STATUS event reaches transcript room WS."""
host, port = appserver_ws_broadcast
transcript_id = await _create_transcript(host, port, "broadcast_event STATUS test")
ws_url = f"http://{host}:{port}/v1/transcripts/{transcript_id}/events"
async with aconnect_ws(ws_url) as ws:
await _drain_historical_events(ws)
from reflector.db.transcripts import TranscriptEvent
from reflector.hatchet.broadcast import broadcast_event
from reflector.logger import logger
log = logger.bind(transcript_id=transcript_id)
event = TranscriptEvent(event="STATUS", data={"value": "processing"})
await broadcast_event(transcript_id, event, logger=log)
msg = await asyncio.wait_for(ws.receive_json(), timeout=5.0)
assert msg["event"] == "STATUS"
assert msg["data"]["value"] == "processing"
# ---------------------------------------------------------------------------
# Test 4: Full broadcast_event() chain for DAG_STATUS
# ---------------------------------------------------------------------------
@pytest.mark.asyncio
async def test_broadcast_event_delivers_dag_status_to_transcript_ws(
appserver_ws_broadcast,
):
"""broadcast_event() end-to-end: DAG_STATUS event reaches transcript room WS."""
host, port = appserver_ws_broadcast
transcript_id = await _create_transcript(host, port, "broadcast_event DAG test")
ws_url = f"http://{host}:{port}/v1/transcripts/{transcript_id}/events"
async with aconnect_ws(ws_url) as ws:
await _drain_historical_events(ws)
from reflector.db.transcripts import TranscriptEvent
from reflector.hatchet.broadcast import broadcast_event
from reflector.logger import logger
log = logger.bind(transcript_id=transcript_id)
event = TranscriptEvent(
event="DAG_STATUS",
data={
"workflow_run_id": "test-run-456",
"tasks": [
{
"name": "get_recording",
"status": "running",
"started_at": None,
"finished_at": None,
"duration_seconds": None,
"parents": [],
"error": None,
"children_total": None,
"children_completed": None,
"progress_pct": None,
}
],
},
)
await broadcast_event(transcript_id, event, logger=log)
msg = await asyncio.wait_for(ws.receive_json(), timeout=5.0)
assert msg["event"] == "DAG_STATUS"
assert msg["data"]["tasks"][0]["name"] == "get_recording"
# ---------------------------------------------------------------------------
# Test 5: Multiple rapid events arrive in order
# ---------------------------------------------------------------------------
@pytest.mark.asyncio
async def test_multiple_events_arrive_in_order(appserver_ws_broadcast):
"""Multiple STATUS then DAG_STATUS events arrive in correct order."""
host, port = appserver_ws_broadcast
transcript_id = await _create_transcript(host, port, "ordering test")
ws_url = f"http://{host}:{port}/v1/transcripts/{transcript_id}/events"
async with aconnect_ws(ws_url) as ws:
await _drain_historical_events(ws)
import reflector.ws_manager as ws_mod
ws_manager = ws_mod.get_ws_manager()
await ws_manager.send_json(
room_id=f"ts:{transcript_id}",
message={"event": "STATUS", "data": {"value": "processing"}},
)
await ws_manager.send_json(
room_id=f"ts:{transcript_id}",
message={
"event": "DAG_STATUS",
"data": {"workflow_run_id": "r1", "tasks": []},
},
)
await ws_manager.send_json(
room_id=f"ts:{transcript_id}",
message={
"event": "DAG_STATUS",
"data": {
"workflow_run_id": "r1",
"tasks": [{"name": "a", "status": "running"}],
},
},
)
await ws_manager.send_json(
room_id=f"ts:{transcript_id}",
message={"event": "STATUS", "data": {"value": "ended"}},
)
msgs = []
for _ in range(4):
msg = await asyncio.wait_for(ws.receive_json(), timeout=5.0)
msgs.append(msg)
assert msgs[0]["event"] == "STATUS"
assert msgs[0]["data"]["value"] == "processing"
assert msgs[1]["event"] == "DAG_STATUS"
assert msgs[1]["data"]["tasks"] == []
assert msgs[2]["event"] == "DAG_STATUS"
assert len(msgs[2]["data"]["tasks"]) == 1
assert msgs[3]["event"] == "STATUS"
assert msgs[3]["data"]["value"] == "ended"

676
server/uv.lock generated
View File

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{ name = "torch", version = "2.8.0", source = { registry = "https://download.pytorch.org/whl/cpu" }, marker = "sys_platform == 'darwin'" },
{ name = "torch", version = "2.8.0+cpu", source = { registry = "https://download.pytorch.org/whl/cpu" }, marker = "sys_platform != 'darwin'" },
]
sdist = { url = "https://files.pythonhosted.org/packages/85/2e/48a887a59ecc4a10ce9e8b35b3e3c5cef29d902c4eac143378526e7485cb/torchmetrics-1.8.2.tar.gz", hash = "sha256:cf64a901036bf107f17a524009eea7781c9c5315d130713aeca5747a686fe7a5", size = 580679 }
wheels = [
{ url = "https://files.pythonhosted.org/packages/02/21/aa0f434434c48490f91b65962b1ce863fdcce63febc166ca9fe9d706c2b6/torchmetrics-1.8.2-py3-none-any.whl", hash = "sha256:08382fd96b923e39e904c4d570f3d49e2cc71ccabd2a94e0f895d1f0dac86242", size = 983161 },
]
[[package]]
name = "tqdm"
version = "4.67.1"

View File

@@ -1,61 +0,0 @@
import React from "react";
import { Box, Flex } from "@chakra-ui/react";
import type { DagTask } from "../../../lib/UserEventsProvider";
const pulseKeyframes = `
@keyframes dagDotPulse {
0%, 100% { opacity: 1; }
50% { opacity: 0.3; }
}
`;
function humanizeTaskName(name: string): string {
return name
.split("_")
.map((word) => word.charAt(0).toUpperCase() + word.slice(1))
.join(" ");
}
function dotProps(status: DagTask["status"]): Record<string, unknown> {
switch (status) {
case "completed":
return { bg: "green.500" };
case "running":
return {
bg: "blue.500",
style: { animation: "dagDotPulse 1.5s ease-in-out infinite" },
};
case "failed":
return { bg: "red.500" };
case "cancelled":
return { bg: "gray.400" };
case "queued":
default:
return {
bg: "transparent",
border: "1px solid",
borderColor: "gray.400",
};
}
}
export default function DagProgressDots({ tasks }: { tasks: DagTask[] }) {
return (
<>
<style>{pulseKeyframes}</style>
<Flex gap="2px" alignItems="center" flexWrap="wrap">
{tasks.map((task) => (
<Box
key={task.name}
w="4px"
h="4px"
borderRadius="full"
flexShrink={0}
title={humanizeTaskName(task.name)}
{...dotProps(task.status)}
/>
))}
</Flex>
</>
);
}

View File

@@ -19,7 +19,6 @@ import {
generateTextFragment,
} from "../../../lib/textHighlight";
import type { components } from "../../../reflector-api";
import type { DagTask } from "../../../lib/UserEventsProvider";
type SearchResult = components["schemas"]["SearchResult"];
type SourceKind = components["schemas"]["SourceKind"];
@@ -30,7 +29,6 @@ interface TranscriptCardsProps {
isLoading?: boolean;
onDelete: (transcriptId: string) => void;
onReprocess: (transcriptId: string) => void;
dagStatusMap?: Map<string, DagTask[]>;
}
function highlightText(text: string, query: string): React.ReactNode {
@@ -104,13 +102,11 @@ function TranscriptCard({
query,
onDelete,
onReprocess,
dagStatusMap,
}: {
result: SearchResult;
query: string;
onDelete: (transcriptId: string) => void;
onReprocess: (transcriptId: string) => void;
dagStatusMap?: Map<string, DagTask[]>;
}) {
const [isExpanded, setIsExpanded] = useState(false);
@@ -141,16 +137,7 @@ function TranscriptCard({
<Box borderWidth={1} p={4} borderRadius="md" fontSize="sm">
<Flex justify="space-between" alignItems="flex-start" gap="2">
<Box>
<TranscriptStatusIcon
status={result.status}
dagStatus={
dagStatusMap?.get(result.id) ??
((result as Record<string, unknown>).dag_status as
| DagTask[]
| null) ??
null
}
/>
<TranscriptStatusIcon status={result.status} />
</Box>
<Box flex="1">
{/* Title with highlighting and text fragment for deep linking */}
@@ -297,7 +284,6 @@ export default function TranscriptCards({
isLoading,
onDelete,
onReprocess,
dagStatusMap,
}: TranscriptCardsProps) {
return (
<Box position="relative">
@@ -329,7 +315,6 @@ export default function TranscriptCards({
query={query}
onDelete={onDelete}
onReprocess={onReprocess}
dagStatusMap={dagStatusMap}
/>
))}
</Stack>

View File

@@ -8,17 +8,13 @@ import {
FaGear,
} from "react-icons/fa6";
import { TranscriptStatus } from "../../../lib/transcript";
import type { DagTask } from "../../../lib/UserEventsProvider";
import DagProgressDots from "./DagProgressDots";
interface TranscriptStatusIconProps {
status: TranscriptStatus;
dagStatus?: DagTask[] | null;
}
export default function TranscriptStatusIcon({
status,
dagStatus,
}: TranscriptStatusIconProps) {
switch (status) {
case "ended":
@@ -40,9 +36,6 @@ export default function TranscriptStatusIcon({
</Box>
);
case "processing":
if (dagStatus && dagStatus.length > 0) {
return <DagProgressDots tasks={dagStatus} />;
}
return (
<Box as="span" title="Processing in progress">
<Icon color="gray.500" as={FaGear} />

View File

@@ -43,7 +43,6 @@ import DeleteTranscriptDialog from "./_components/DeleteTranscriptDialog";
import { formatLocalDate } from "../../lib/time";
import { RECORD_A_MEETING_URL } from "../../api/urls";
import { useUserName } from "../../lib/useUserName";
import { useDagStatusMap } from "../../lib/UserEventsProvider";
const SEARCH_FORM_QUERY_INPUT_NAME = "query" as const;
@@ -274,7 +273,6 @@ export default function TranscriptBrowser() {
}, [JSON.stringify(searchFilters)]);
const userName = useUserName();
const dagStatusMap = useDagStatusMap();
const [deletionLoading, setDeletionLoading] = useState(false);
const cancelRef = React.useRef(null);
const [transcriptToDeleteId, setTranscriptToDeleteId] =
@@ -410,7 +408,6 @@ export default function TranscriptBrowser() {
isLoading={searchLoading}
onDelete={setTranscriptToDeleteId}
onReprocess={handleProcessTranscript}
dagStatusMap={dagStatusMap}
/>
{!searchLoading && results.length === 0 && (

View File

@@ -1,190 +0,0 @@
"use client";
import { useEffect, useState } from "react";
import { Table, Box, Icon, Spinner, Text, Badge } from "@chakra-ui/react";
import { FaCheck, FaXmark, FaClock, FaMinus } from "react-icons/fa6";
import type { DagTask, DagTaskStatus } from "../../useWebSockets";
function humanizeTaskName(name: string): string {
return name
.split("_")
.map((word) => word.charAt(0).toUpperCase() + word.slice(1))
.join(" ");
}
function formatDuration(seconds: number): string {
if (seconds < 60) {
return `${Math.round(seconds)}s`;
}
const minutes = Math.floor(seconds / 60);
const remainingSeconds = Math.round(seconds % 60);
return `${minutes}m ${remainingSeconds}s`;
}
function StatusIcon({ status }: { status: DagTaskStatus }) {
switch (status) {
case "completed":
return (
<Box as="span" title="Completed">
<Icon color="green.500" as={FaCheck} />
</Box>
);
case "running":
return <Spinner size="sm" color="blue.500" />;
case "failed":
return (
<Box as="span" title="Failed">
<Icon color="red.500" as={FaXmark} />
</Box>
);
case "queued":
return (
<Box as="span" title="Queued">
<Icon color="gray.400" as={FaClock} />
</Box>
);
case "cancelled":
return (
<Box as="span" title="Cancelled">
<Icon color="gray.400" as={FaMinus} />
</Box>
);
default:
return null;
}
}
function ElapsedTimer({ startedAt }: { startedAt: string }) {
const [elapsed, setElapsed] = useState<number>(() => {
return (Date.now() - new Date(startedAt).getTime()) / 1000;
});
useEffect(() => {
const interval = setInterval(() => {
setElapsed((Date.now() - new Date(startedAt).getTime()) / 1000);
}, 1000);
return () => clearInterval(interval);
}, [startedAt]);
return <Text fontSize="sm">{formatDuration(elapsed)}</Text>;
}
function DurationCell({ task }: { task: DagTask }) {
if (task.status === "completed" && task.duration_seconds !== null) {
return <Text fontSize="sm">{formatDuration(task.duration_seconds)}</Text>;
}
if (task.status === "running" && task.started_at) {
return <ElapsedTimer startedAt={task.started_at} />;
}
return (
<Text fontSize="sm" color="gray.400">
--
</Text>
);
}
function ProgressCell({ task }: { task: DagTask }) {
if (task.progress_pct === null && task.children_total === null) {
return null;
}
return (
<Box>
{task.progress_pct !== null && (
<Box
w="100%"
h="6px"
bg="gray.200"
borderRadius="full"
overflow="hidden"
>
<Box
h="100%"
w={`${Math.min(100, Math.max(0, task.progress_pct))}%`}
bg={task.status === "failed" ? "red.400" : "blue.400"}
borderRadius="full"
transition="width 0.3s ease"
/>
</Box>
)}
{task.children_total !== null && (
<Badge
size="sm"
colorPalette="gray"
mt={task.progress_pct !== null ? 1 : 0}
>
{task.children_completed ?? 0}/{task.children_total}
</Badge>
)}
</Box>
);
}
function TaskRow({ task }: { task: DagTask }) {
const [expanded, setExpanded] = useState(false);
const hasFailed = task.status === "failed" && task.error;
return (
<>
<Table.Row
cursor={hasFailed ? "pointer" : "default"}
onClick={hasFailed ? () => setExpanded((prev) => !prev) : undefined}
_hover={hasFailed ? { bg: "gray.50" } : undefined}
>
<Table.Cell>
<Text fontSize="sm" fontWeight="medium">
{humanizeTaskName(task.name)}
</Text>
</Table.Cell>
<Table.Cell>
<StatusIcon status={task.status} />
</Table.Cell>
<Table.Cell>
<DurationCell task={task} />
</Table.Cell>
<Table.Cell>
<ProgressCell task={task} />
</Table.Cell>
</Table.Row>
{hasFailed && expanded && (
<Table.Row>
<Table.Cell colSpan={4}>
<Box bg="red.50" p={3} borderRadius="md">
<Text fontSize="xs" color="red.700" whiteSpace="pre-wrap">
{task.error}
</Text>
</Box>
</Table.Cell>
</Table.Row>
)}
</>
);
}
export default function DagProgressTable({ tasks }: { tasks: DagTask[] }) {
return (
<Box w="100%" overflowX="auto">
<Table.Root size="sm">
<Table.Header>
<Table.Row>
<Table.ColumnHeader fontWeight="600">Task</Table.ColumnHeader>
<Table.ColumnHeader fontWeight="600" width="80px">
Status
</Table.ColumnHeader>
<Table.ColumnHeader fontWeight="600" width="100px">
Duration
</Table.ColumnHeader>
<Table.ColumnHeader fontWeight="600" width="140px">
Progress
</Table.ColumnHeader>
</Table.Row>
</Table.Header>
<Table.Body>
{tasks.map((task) => (
<TaskRow key={task.name} task={task} />
))}
</Table.Body>
</Table.Root>
</Box>
);
}

View File

@@ -12,9 +12,6 @@ import { useRouter } from "next/navigation";
import { useTranscriptGet } from "../../../../lib/apiHooks";
import { parseNonEmptyString } from "../../../../lib/utils";
import { useWebSockets } from "../../useWebSockets";
import type { DagTask } from "../../useWebSockets";
import { useDagStatusMap } from "../../../../lib/UserEventsProvider";
import DagProgressTable from "./DagProgressTable";
type TranscriptProcessing = {
params: Promise<{
@@ -28,21 +25,10 @@ export default function TranscriptProcessing(details: TranscriptProcessing) {
const router = useRouter();
const transcript = useTranscriptGet(transcriptId);
const { status: wsStatus, dagStatus: wsDagStatus } =
useWebSockets(transcriptId);
const userDagStatusMap = useDagStatusMap();
const userDagStatus = userDagStatusMap.get(transcriptId) ?? null;
const restDagStatus: DagTask[] | null =
((transcript.data as Record<string, unknown>)?.dag_status as
| DagTask[]
| null) ?? null;
// Prefer transcript room WS (most granular), then user room WS, then REST
const dagStatus = wsDagStatus ?? userDagStatus ?? restDagStatus;
useWebSockets(transcriptId);
useEffect(() => {
const status = wsStatus?.value ?? transcript.data?.status;
const status = transcript.data?.status;
if (!status) return;
if (status === "ended" || status === "error") {
@@ -57,7 +43,6 @@ export default function TranscriptProcessing(details: TranscriptProcessing) {
router.replace(dest);
}
}, [
wsStatus?.value,
transcript.data?.status,
transcript.data?.source_kind,
router,
@@ -91,29 +76,11 @@ export default function TranscriptProcessing(details: TranscriptProcessing) {
w={{ base: "full", md: "container.xl" }}
>
<Center h={"full"} w="full">
<VStack
gap={10}
bg="gray.100"
p={10}
borderRadius="md"
maxW="600px"
w="full"
>
{dagStatus ? (
<>
<Heading size={"md"} textAlign="center">
Processing recording
</Heading>
<DagProgressTable tasks={dagStatus} />
</>
) : (
<>
<Spinner size="xl" color="blue.500" />
<Heading size={"md"} textAlign="center">
Processing recording
</Heading>
</>
)}
<VStack gap={10} bg="gray.100" p={10} borderRadius="md" maxW="500px">
<Spinner size="xl" color="blue.500" />
<Heading size={"md"} textAlign="center">
Processing recording
</Heading>
<Text color="gray.600" textAlign="center">
You can safely return to the library while your recording is being
processed.

View File

@@ -23,7 +23,16 @@ const useWebRTC = (
let p: Peer;
try {
p = new Peer({ initiator: true, stream: stream });
p = new Peer({
initiator: true,
stream: stream,
// Disable trickle ICE: single SDP exchange (offer + answer) with all candidates.
// Required for HTTP-based signaling; trickle needs WebSocket for candidate exchange.
trickle: false,
config: {
iceServers: [{ urls: "stun:stun.l.google.com:19302" }],
},
});
} catch (error) {
setError(error as Error, "Error creating WebRTC");
return;

View File

@@ -1,21 +1,22 @@
import { useEffect, useState } from "react";
import { Topic, FinalSummary, Status } from "./webSocketTypes";
import { useError } from "../../(errors)/errorContext";
import type { components } from "../../reflector-api";
import type { components, operations } from "../../reflector-api";
type AudioWaveform = components["schemas"]["AudioWaveform"];
type GetTranscriptSegmentTopic =
components["schemas"]["GetTranscriptSegmentTopic"];
import { useQueryClient } from "@tanstack/react-query";
import { $api, WEBSOCKET_URL } from "../../lib/apiClient";
import { WEBSOCKET_URL } from "../../lib/apiClient";
import {
invalidateTranscript,
invalidateTranscriptTopics,
invalidateTranscriptWaveform,
} from "../../lib/apiHooks";
import { NonEmptyString } from "../../lib/utils";
import { useAuth } from "../../lib/AuthProvider";
import { parseNonEmptyString } from "../../lib/utils";
import type { DagTask } from "../../lib/dagTypes";
export type { DagTask, DagTaskStatus } from "../../lib/dagTypes";
type TranscriptWsEvent =
operations["v1_transcript_get_websocket_events"]["responses"][200]["content"]["application/json"];
export type UseWebSockets = {
transcriptTextLive: string;
@@ -27,10 +28,10 @@ export type UseWebSockets = {
status: Status | null;
waveform: AudioWaveform | null;
duration: number | null;
dagStatus: DagTask[] | null;
};
export const useWebSockets = (transcriptId: string | null): UseWebSockets => {
const auth = useAuth();
const [transcriptTextLive, setTranscriptTextLive] = useState<string>("");
const [translateText, setTranslateText] = useState<string>("");
const [title, setTitle] = useState<string>("");
@@ -44,7 +45,6 @@ export const useWebSockets = (transcriptId: string | null): UseWebSockets => {
summary: "",
});
const [status, setStatus] = useState<Status | null>(null);
const [dagStatus, setDagStatus] = useState<DagTask[] | null>(null);
const { setError } = useError();
const queryClient = useQueryClient();
@@ -336,175 +336,168 @@ export const useWebSockets = (transcriptId: string | null): UseWebSockets => {
};
if (!transcriptId) return;
const tsId = parseNonEmptyString(transcriptId);
const MAX_RETRIES = 10;
const url = `${WEBSOCKET_URL}/v1/transcripts/${transcriptId}/events`;
let ws = new WebSocket(url);
let ws: WebSocket | null = null;
let retryCount = 0;
let retryTimeout: ReturnType<typeof setTimeout> | null = null;
let intentionalClose = false;
ws.onopen = () => {
console.debug("WebSocket connection opened");
};
const connect = () => {
const subprotocols = auth.accessToken
? ["bearer", auth.accessToken]
: undefined;
ws = new WebSocket(url, subprotocols);
ws.onmessage = (event) => {
const message = JSON.parse(event.data);
ws.onopen = () => {
console.debug("WebSocket connection opened");
retryCount = 0;
};
try {
switch (message.event) {
case "TRANSCRIPT":
const newText = (message.data.text ?? "").trim();
const newTranslation = (message.data.translation ?? "").trim();
ws.onmessage = (event) => {
const message: TranscriptWsEvent = JSON.parse(event.data);
if (!newText) break;
try {
switch (message.event) {
case "TRANSCRIPT": {
const newText = (message.data.text ?? "").trim();
const newTranslation = (message.data.translation ?? "").trim();
console.debug("TRANSCRIPT event:", newText);
setTextQueue((prevQueue) => [...prevQueue, newText]);
setTranslationQueue((prevQueue) => [...prevQueue, newTranslation]);
if (!newText) break;
setAccumulatedText((prevText) => prevText + " " + newText);
break;
console.debug("TRANSCRIPT event:", newText);
setTextQueue((prevQueue) => [...prevQueue, newText]);
setTranslationQueue((prevQueue) => [
...prevQueue,
newTranslation,
]);
case "TOPIC":
setTopics((prevTopics) => {
const topic = message.data as Topic;
const index = prevTopics.findIndex(
(prevTopic) => prevTopic.id === topic.id,
);
if (index >= 0) {
prevTopics[index] = topic;
return prevTopics;
}
setAccumulatedText((prevText) =>
prevText.slice(topic.transcript.length),
);
return [...prevTopics, topic];
});
console.debug("TOPIC event:", message.data);
// Invalidate topics query to sync with WebSocket data
invalidateTranscriptTopics(
queryClient,
transcriptId as NonEmptyString,
);
break;
case "FINAL_SHORT_SUMMARY":
console.debug("FINAL_SHORT_SUMMARY event:", message.data);
break;
case "FINAL_LONG_SUMMARY":
if (message.data) {
setFinalSummary(message.data);
// Invalidate transcript query to sync summary
invalidateTranscript(queryClient, transcriptId as NonEmptyString);
setAccumulatedText((prevText) => prevText + " " + newText);
break;
}
break;
case "FINAL_TITLE":
console.debug("FINAL_TITLE event:", message.data);
if (message.data) {
case "TOPIC":
setTopics((prevTopics) => {
const topic = message.data;
const index = prevTopics.findIndex(
(prevTopic) => prevTopic.id === topic.id,
);
if (index >= 0) {
prevTopics[index] = topic;
return prevTopics;
}
setAccumulatedText((prevText) =>
prevText.slice(topic.transcript?.length ?? 0),
);
return [...prevTopics, topic];
});
console.debug("TOPIC event:", message.data);
invalidateTranscriptTopics(queryClient, tsId);
break;
case "FINAL_SHORT_SUMMARY":
console.debug("FINAL_SHORT_SUMMARY event:", message.data);
break;
case "FINAL_LONG_SUMMARY":
setFinalSummary({ summary: message.data.long_summary });
invalidateTranscript(queryClient, tsId);
break;
case "FINAL_TITLE":
console.debug("FINAL_TITLE event:", message.data);
setTitle(message.data.title);
// Invalidate transcript query to sync title
invalidateTranscript(queryClient, transcriptId as NonEmptyString);
}
break;
invalidateTranscript(queryClient, tsId);
break;
case "WAVEFORM":
console.debug(
"WAVEFORM event length:",
message.data.waveform.length,
);
if (message.data) {
setWaveForm(message.data.waveform);
invalidateTranscriptWaveform(
queryClient,
transcriptId as NonEmptyString,
case "WAVEFORM":
console.debug(
"WAVEFORM event length:",
message.data.waveform.length,
);
}
break;
case "DURATION":
console.debug("DURATION event:", message.data);
if (message.data) {
setWaveForm({ data: message.data.waveform });
invalidateTranscriptWaveform(queryClient, tsId);
break;
case "DURATION":
console.debug("DURATION event:", message.data);
setDuration(message.data.duration);
}
break;
break;
case "STATUS":
console.log("STATUS event:", message.data);
if (message.data.value === "error") {
setError(
Error("Websocket error status"),
"There was an error processing this meeting.",
case "STATUS":
console.log("STATUS event:", message.data);
if (message.data.value === "error") {
setError(
Error("Websocket error status"),
"There was an error processing this meeting.",
);
}
setStatus(message.data);
invalidateTranscript(queryClient, tsId);
if (message.data.value === "ended") {
intentionalClose = true;
ws?.close();
}
break;
case "ACTION_ITEMS":
console.debug("ACTION_ITEMS event:", message.data);
invalidateTranscript(queryClient, tsId);
break;
default: {
const _exhaustive: never = message;
console.warn(
`Received unknown WebSocket event: ${(_exhaustive as TranscriptWsEvent).event}`,
);
}
setStatus(message.data);
invalidateTranscript(queryClient, transcriptId as NonEmptyString);
if (message.data.value === "ended") {
ws.close();
}
break;
case "DAG_STATUS":
if (message.data?.tasks) {
setDagStatus(message.data.tasks);
}
break;
case "DAG_TASK_PROGRESS":
if (message.data) {
setDagStatus(
(prev) =>
prev?.map((t) =>
t.name === message.data.task_name
? { ...t, progress_pct: message.data.progress_pct }
: t,
) ?? null,
);
}
break;
default:
setError(
new Error(`Received unknown WebSocket event: ${message.event}`),
);
}
} catch (error) {
setError(error);
}
} catch (error) {
setError(error);
}
};
};
ws.onerror = (error) => {
console.error("WebSocket error:", error);
setError(new Error("A WebSocket error occurred."));
};
ws.onerror = (error) => {
console.error("WebSocket error:", error);
};
ws.onclose = (event) => {
console.debug("WebSocket connection closed");
switch (event.code) {
case 1000: // Normal Closure:
break;
case 1005: // Closure by client FF
break;
case 1001: // Navigate away
break;
case 1006: // Closed by client Chrome
console.warn(
"WebSocket closed by client, likely duplicated connection in react dev mode",
ws.onclose = (event) => {
console.debug("WebSocket connection closed, code:", event.code);
if (intentionalClose) return;
const normalCodes = [1000, 1001, 1005];
if (normalCodes.includes(event.code)) return;
if (retryCount < MAX_RETRIES) {
const delay = Math.min(1000 * Math.pow(2, retryCount), 30000);
console.log(
`WebSocket reconnecting in ${delay}ms (attempt ${retryCount + 1}/${MAX_RETRIES})`,
);
break;
default:
if (retryCount === 0) {
setError(
new Error("WebSocket connection lost"),
"Connection lost. Reconnecting...",
);
}
retryCount++;
retryTimeout = setTimeout(connect, delay);
} else {
setError(
new Error(`WebSocket closed unexpectedly with code: ${event.code}`),
"Disconnected from the server. Please refresh the page.",
);
console.log(
"Socket is closed. Reconnect will be attempted in 1 second.",
event.reason,
);
// todo handle reconnect with socket.io
}
}
};
};
connect();
return () => {
ws.close();
intentionalClose = true;
if (retryTimeout) clearTimeout(retryTimeout);
ws?.close();
};
}, [transcriptId]);
@@ -518,6 +511,5 @@ export const useWebSockets = (transcriptId: string | null): UseWebSockets => {
status,
waveform,
duration,
dagStatus,
};
};

View File

@@ -1,31 +1,15 @@
"use client";
import React, { useEffect, useRef, useState } from "react";
import React, { useEffect, useRef } from "react";
import { useQueryClient } from "@tanstack/react-query";
import { WEBSOCKET_URL } from "./apiClient";
import { useAuth } from "./AuthProvider";
import { z } from "zod";
import {
invalidateTranscript,
invalidateTranscriptLists,
TRANSCRIPT_SEARCH_URL,
} from "./apiHooks";
import type { NonEmptyString } from "./utils";
import { invalidateTranscript, invalidateTranscriptLists } from "./apiHooks";
import { parseNonEmptyString } from "./utils";
import type { operations } from "../reflector-api";
import type { DagTask } from "./dagTypes";
export type { DagTask, DagTaskStatus } from "./dagTypes";
const DagStatusContext = React.createContext<Map<string, DagTask[]>>(new Map());
export function useDagStatusMap() {
return React.useContext(DagStatusContext);
}
const UserEvent = z.object({
event: z.string(),
});
type UserEvent = z.TypeOf<typeof UserEvent>;
type UserWsEvent =
operations["v1_user_get_websocket_events"]["responses"][200]["content"]["application/json"];
class UserEventsStore {
private socket: WebSocket | null = null;
@@ -109,9 +93,6 @@ export function UserEventsProvider({
const queryClient = useQueryClient();
const tokenRef = useRef<string | null>(null);
const detachRef = useRef<(() => void) | null>(null);
const [dagStatusMap, setDagStatusMap] = useState<Map<string, DagTask[]>>(
new Map(),
);
useEffect(() => {
// Only tear down when the user is truly unauthenticated
@@ -150,55 +131,26 @@ export function UserEventsProvider({
if (!detachRef.current) {
const onMessage = (event: MessageEvent) => {
try {
const fullMsg = JSON.parse(event.data);
const msg = UserEvent.parse(fullMsg);
const eventName = msg.event;
const invalidateList = () => invalidateTranscriptLists(queryClient);
const msg: UserWsEvent = JSON.parse(event.data);
switch (eventName) {
switch (msg.event) {
case "TRANSCRIPT_CREATED":
case "TRANSCRIPT_DELETED":
case "TRANSCRIPT_STATUS":
case "TRANSCRIPT_FINAL_TITLE":
case "TRANSCRIPT_DURATION":
invalidateList().then(() => {});
break;
case "TRANSCRIPT_STATUS": {
invalidateList().then(() => {});
const transcriptId = fullMsg.data?.id as string | undefined;
if (transcriptId) {
invalidateTranscript(
queryClient,
transcriptId as NonEmptyString,
).then(() => {});
}
const status = fullMsg.data?.value as string | undefined;
if (transcriptId && status && status !== "processing") {
setDagStatusMap((prev) => {
const next = new Map(prev);
next.delete(transcriptId);
return next;
});
}
invalidateTranscriptLists(queryClient).then(() => {});
invalidateTranscript(
queryClient,
parseNonEmptyString(msg.data.id),
).then(() => {});
break;
default: {
const _exhaustive: never = msg;
console.warn(
`Unknown user event: ${(_exhaustive as UserWsEvent).event}`,
);
}
case "TRANSCRIPT_DAG_STATUS": {
const transcriptId = fullMsg.data?.id as string | undefined;
const tasks = fullMsg.data?.tasks as DagTask[] | undefined;
if (transcriptId && tasks) {
setDagStatusMap((prev) => {
const next = new Map(prev);
next.set(transcriptId, tasks);
return next;
});
}
break;
}
default:
// Ignore other content events for list updates
break;
}
} catch (err) {
console.warn("Invalid user event message", event.data);
@@ -225,9 +177,5 @@ export function UserEventsProvider({
};
}, []);
return (
<DagStatusContext.Provider value={dagStatusMap}>
{children}
</DagStatusContext.Provider>
);
return <>{children}</>;
}

View File

@@ -7,6 +7,7 @@ import type { components } from "../reflector-api";
import { useAuth } from "./AuthProvider";
import { MeetingId } from "./types";
import { NonEmptyString } from "./utils";
import type { TranscriptStatus } from "./transcript";
/*
* XXX error types returned from the hooks are not always correct; declared types are ValidationError but real type could be string or any other
@@ -104,6 +105,12 @@ export function useTranscriptProcess() {
});
}
const ACTIVE_TRANSCRIPT_STATUSES = new Set<TranscriptStatus>([
"processing",
"uploaded",
"recording",
]);
export function useTranscriptGet(transcriptId: NonEmptyString | null) {
return $api.useQuery(
"get",
@@ -117,6 +124,10 @@ export function useTranscriptGet(transcriptId: NonEmptyString | null) {
},
{
enabled: !!transcriptId,
refetchInterval: (query) => {
const status = query.state.data?.status;
return status && ACTIVE_TRANSCRIPT_STATUSES.has(status) ? 5000 : false;
},
},
);
}

View File

@@ -1,19 +0,0 @@
export type DagTaskStatus =
| "queued"
| "running"
| "completed"
| "failed"
| "cancelled";
export type DagTask = {
name: string;
status: DagTaskStatus;
started_at: string | null;
finished_at: string | null;
duration_seconds: number | null;
parents: string[];
error: string | null;
children_total: number | null;
children_completed: number | null;
progress_pct: number | null;
};

View File

@@ -568,7 +568,10 @@ export interface paths {
path?: never;
cookie?: never;
};
/** Transcript Get Websocket Events */
/**
* Transcript WebSocket event schema
* @description Stub exposing the discriminated union of all transcript-level WS events for OpenAPI type generation. Real events are delivered over the WebSocket at the same path.
*/
get: operations["v1_transcript_get_websocket_events"];
put?: never;
post?: never;
@@ -664,6 +667,26 @@ export interface paths {
patch?: never;
trace?: never;
};
"/v1/events": {
parameters: {
query?: never;
header?: never;
path?: never;
cookie?: never;
};
/**
* User WebSocket event schema
* @description Stub exposing the discriminated union of all user-level WS events for OpenAPI type generation. Real events are delivered over the WebSocket at the same path.
*/
get: operations["v1_user_get_websocket_events"];
put?: never;
post?: never;
delete?: never;
options?: never;
head?: never;
patch?: never;
trace?: never;
};
"/v1/zulip/streams": {
parameters: {
query?: never;
@@ -1877,6 +1900,33 @@ export interface components {
/** Name */
name: string;
};
/** TranscriptActionItems */
TranscriptActionItems: {
/** Action Items */
action_items: {
[key: string]: unknown;
};
};
/** TranscriptDuration */
TranscriptDuration: {
/** Duration */
duration: number;
};
/** TranscriptFinalLongSummary */
TranscriptFinalLongSummary: {
/** Long Summary */
long_summary: string;
};
/** TranscriptFinalShortSummary */
TranscriptFinalShortSummary: {
/** Short Summary */
short_summary: string;
};
/** TranscriptFinalTitle */
TranscriptFinalTitle: {
/** Title */
title: string;
};
/** TranscriptParticipant */
TranscriptParticipant: {
/** Id */
@@ -1917,6 +1967,113 @@ export interface components {
/** End */
end: number;
};
/** TranscriptText */
TranscriptText: {
/** Text */
text: string;
/** Translation */
translation: string | null;
};
/** TranscriptWaveform */
TranscriptWaveform: {
/** Waveform */
waveform: number[];
};
/** TranscriptWsActionItems */
TranscriptWsActionItems: {
/**
* @description discriminator enum property added by openapi-typescript
* @enum {string}
*/
event: "ACTION_ITEMS";
data: components["schemas"]["TranscriptActionItems"];
};
/** TranscriptWsDuration */
TranscriptWsDuration: {
/**
* @description discriminator enum property added by openapi-typescript
* @enum {string}
*/
event: "DURATION";
data: components["schemas"]["TranscriptDuration"];
};
/** TranscriptWsFinalLongSummary */
TranscriptWsFinalLongSummary: {
/**
* @description discriminator enum property added by openapi-typescript
* @enum {string}
*/
event: "FINAL_LONG_SUMMARY";
data: components["schemas"]["TranscriptFinalLongSummary"];
};
/** TranscriptWsFinalShortSummary */
TranscriptWsFinalShortSummary: {
/**
* @description discriminator enum property added by openapi-typescript
* @enum {string}
*/
event: "FINAL_SHORT_SUMMARY";
data: components["schemas"]["TranscriptFinalShortSummary"];
};
/** TranscriptWsFinalTitle */
TranscriptWsFinalTitle: {
/**
* @description discriminator enum property added by openapi-typescript
* @enum {string}
*/
event: "FINAL_TITLE";
data: components["schemas"]["TranscriptFinalTitle"];
};
/** TranscriptWsStatus */
TranscriptWsStatus: {
/**
* @description discriminator enum property added by openapi-typescript
* @enum {string}
*/
event: "STATUS";
data: components["schemas"]["TranscriptWsStatusData"];
};
/** TranscriptWsStatusData */
TranscriptWsStatusData: {
/**
* Value
* @enum {string}
*/
value:
| "idle"
| "uploaded"
| "recording"
| "processing"
| "error"
| "ended";
};
/** TranscriptWsTopic */
TranscriptWsTopic: {
/**
* @description discriminator enum property added by openapi-typescript
* @enum {string}
*/
event: "TOPIC";
data: components["schemas"]["GetTranscriptTopic"];
};
/** TranscriptWsTranscript */
TranscriptWsTranscript: {
/**
* @description discriminator enum property added by openapi-typescript
* @enum {string}
*/
event: "TRANSCRIPT";
data: components["schemas"]["TranscriptText"];
};
/** TranscriptWsWaveform */
TranscriptWsWaveform: {
/**
* @description discriminator enum property added by openapi-typescript
* @enum {string}
*/
event: "WAVEFORM";
data: components["schemas"]["TranscriptWaveform"];
};
/** UpdateParticipant */
UpdateParticipant: {
/** Speaker */
@@ -1987,6 +2144,82 @@ export interface components {
/** Email */
email: string | null;
};
/** UserTranscriptCreatedData */
UserTranscriptCreatedData: {
/** Id */
id: string;
};
/** UserTranscriptDeletedData */
UserTranscriptDeletedData: {
/** Id */
id: string;
};
/** UserTranscriptDurationData */
UserTranscriptDurationData: {
/** Id */
id: string;
/** Duration */
duration: number;
};
/** UserTranscriptFinalTitleData */
UserTranscriptFinalTitleData: {
/** Id */
id: string;
/** Title */
title: string;
};
/** UserTranscriptStatusData */
UserTranscriptStatusData: {
/** Id */
id: string;
/** Value */
value: string;
};
/** UserWsTranscriptCreated */
UserWsTranscriptCreated: {
/**
* @description discriminator enum property added by openapi-typescript
* @enum {string}
*/
event: "TRANSCRIPT_CREATED";
data: components["schemas"]["UserTranscriptCreatedData"];
};
/** UserWsTranscriptDeleted */
UserWsTranscriptDeleted: {
/**
* @description discriminator enum property added by openapi-typescript
* @enum {string}
*/
event: "TRANSCRIPT_DELETED";
data: components["schemas"]["UserTranscriptDeletedData"];
};
/** UserWsTranscriptDuration */
UserWsTranscriptDuration: {
/**
* @description discriminator enum property added by openapi-typescript
* @enum {string}
*/
event: "TRANSCRIPT_DURATION";
data: components["schemas"]["UserTranscriptDurationData"];
};
/** UserWsTranscriptFinalTitle */
UserWsTranscriptFinalTitle: {
/**
* @description discriminator enum property added by openapi-typescript
* @enum {string}
*/
event: "TRANSCRIPT_FINAL_TITLE";
data: components["schemas"]["UserTranscriptFinalTitleData"];
};
/** UserWsTranscriptStatus */
UserWsTranscriptStatus: {
/**
* @description discriminator enum property added by openapi-typescript
* @enum {string}
*/
event: "TRANSCRIPT_STATUS";
data: components["schemas"]["UserTranscriptStatusData"];
};
/** ValidationError */
ValidationError: {
/** Location */
@@ -3423,7 +3656,16 @@ export interface operations {
[name: string]: unknown;
};
content: {
"application/json": unknown;
"application/json":
| components["schemas"]["TranscriptWsTranscript"]
| components["schemas"]["TranscriptWsTopic"]
| components["schemas"]["TranscriptWsStatus"]
| components["schemas"]["TranscriptWsFinalTitle"]
| components["schemas"]["TranscriptWsFinalLongSummary"]
| components["schemas"]["TranscriptWsFinalShortSummary"]
| components["schemas"]["TranscriptWsActionItems"]
| components["schemas"]["TranscriptWsDuration"]
| components["schemas"]["TranscriptWsWaveform"];
};
};
/** @description Validation Error */
@@ -3607,6 +3849,31 @@ export interface operations {
};
};
};
v1_user_get_websocket_events: {
parameters: {
query?: never;
header?: never;
path?: never;
cookie?: never;
};
requestBody?: never;
responses: {
/** @description Successful Response */
200: {
headers: {
[name: string]: unknown;
};
content: {
"application/json":
| components["schemas"]["UserWsTranscriptCreated"]
| components["schemas"]["UserWsTranscriptDeleted"]
| components["schemas"]["UserWsTranscriptStatus"]
| components["schemas"]["UserWsTranscriptFinalTitle"]
| components["schemas"]["UserWsTranscriptDuration"];
};
};
};
};
v1_zulip_get_streams: {
parameters: {
query?: never;