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12 Commits

Author SHA1 Message Date
a455be047a Merge branch 'main' into fix-daily-ux 2026-02-06 11:33:35 -05:00
Igor Loskutov
2a9993ceec remove integration test with hardcoded external URL 2026-02-06 11:31:22 -05:00
Igor Loskutov
8773d9fbbd test: add integration test for ICS dedup using Max's live calendar feed 2026-02-06 11:02:20 -05:00
Igor Loskutov
6c88e05423 refactor: remove redundant fatalError ref, use state directly in handleLeave 2026-02-05 22:06:15 -05:00
Igor Loskutov
f4803c0d76 fix: use function mocks with correct signature in dedup tests 2026-02-05 19:51:27 -05:00
Igor Loskutov
2b484aec00 refactor: data-driven FatalErrorScreen, cover all DailyFatalErrorType cases 2026-02-05 19:49:14 -05:00
Igor Loskutov
d3161730ef fix: use SDK DailyFatalErrorType, add meeting-full/not-allowed/exp-token cases, remove dead end_date fallback 2026-02-05 19:43:25 -05:00
Igor Loskutov
4fd88b2fc1 fix: review feedback — literal error types, extract FatalErrorScreen, type params, fix mock signature 2026-02-05 19:35:47 -05:00
Igor Loskutov
a2694650fd chore: add REPORT.md and ref markers for ApiError cast issue 2026-02-05 19:16:58 -05:00
Igor Loskutov
238d768499 fix: address review feedback - use ApiError type, move inline imports 2026-02-05 18:50:12 -05:00
Igor Loskutov
1da687fe13 fix: prevent duplicate meetings from aggregated ICS calendar feeds
When Cal.com events appear in an aggregated ICS feed, the same event
gets two different UIDs (one from Cal.com, one from Google Calendar).
This caused duplicate meetings to be created for the same time slot.

Add time-window dedup check in create_upcoming_meetings_for_event:
after verifying no meeting exists for the calendar_event_id, also check
if a meeting already exists for the same room + start_date + end_date.
2026-02-05 18:42:42 -05:00
Igor Loskutov
e9e1676409 feat: add specific error messages for Daily.co meeting disconnections
Handle fatal errors from Daily.co SDK (connection-error, exp-room,
ejected, etc.) with user-friendly messages and appropriate actions.
Improve join failure display to show actual API error detail.
2026-02-05 18:42:42 -05:00
45 changed files with 1217 additions and 1254 deletions

View File

@@ -1,17 +1,5 @@
# Changelog
## [0.33.0](https://github.com/Monadical-SAS/reflector/compare/v0.32.2...v0.33.0) (2026-02-05)
### Features
* Daily+hatchet default ([#846](https://github.com/Monadical-SAS/reflector/issues/846)) ([15ab2e3](https://github.com/Monadical-SAS/reflector/commit/15ab2e306eacf575494b4b5d2b2ad779d44a1c7f))
### Bug Fixes
* websocket tests ([#825](https://github.com/Monadical-SAS/reflector/issues/825)) ([1ce1c7a](https://github.com/Monadical-SAS/reflector/commit/1ce1c7a910b6c374115d2437b17f9d288ef094dc))
## [0.32.2](https://github.com/Monadical-SAS/reflector/compare/v0.32.1...v0.32.2) (2026-02-03)

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@@ -1,10 +0,0 @@
# Standalone Compose: Remaining Production Work
## Server/worker/beat: remove host network mode + bind mounts
Currently `server` uses `network_mode: host` and all three services bind-mount `./server/:/app/`. For full standalone prod:
- Remove `network_mode: host` from server
- Remove bind-mount volumes from server, worker, beat (use built image only)
- Update `compose_cmd` in `setup-standalone.sh` to not rely on host network
- Change `SERVER_API_URL` from `http://host.docker.internal:1250` to `http://server:1250` (server reachable via Docker network once off host mode)

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@@ -1,129 +0,0 @@
# Standalone services for fully local deployment (no external dependencies).
# Usage: docker compose -f docker-compose.yml -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:
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
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
# Override server/worker/beat to use self-hosted GPU service for transcription+diarization.
# compose `environment:` overrides values from `env_file:` — no need to edit server/.env.
server:
environment:
TRANSCRIPT_BACKEND: modal
TRANSCRIPT_URL: http://localhost:8100
TRANSCRIPT_MODAL_API_KEY: local
DIARIZATION_BACKEND: modal
DIARIZATION_URL: http://localhost:8100
worker:
environment:
TRANSCRIPT_BACKEND: modal
TRANSCRIPT_URL: http://cpu:8000
TRANSCRIPT_MODAL_API_KEY: local
DIARIZATION_BACKEND: modal
DIARIZATION_URL: http://cpu:8000
web:
image: reflector-frontend-standalone
build:
context: ./www
command: ["node", "server.js"]
volumes: !reset []
environment:
NODE_ENV: production
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
volumes:
garage_data:
garage_meta:
ollama_data:
gpu_cache:

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@@ -2,7 +2,8 @@ services:
server:
build:
context: server
network_mode: host
ports:
- 1250:1250
volumes:
- ./server/:/app/
- /app/.venv
@@ -10,12 +11,6 @@ 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:
@@ -27,11 +22,6 @@ 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:
@@ -43,9 +33,6 @@ services:
- ./server/.env
environment:
ENTRYPOINT: beat
depends_on:
redis:
condition: service_started
hatchet-worker-cpu:
build:
@@ -57,8 +44,6 @@ 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
@@ -72,8 +57,6 @@ 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
@@ -92,16 +75,10 @@ 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
@@ -117,14 +94,13 @@ 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: 5s
timeout: 5s
retries: 10
start_period: 15s
interval: 10s
timeout: 10s
retries: 5
start_period: 10s
hatchet:
image: ghcr.io/hatchet-dev/hatchet/hatchet-lite:latest
restart: on-failure
ports:
- "8889:8888"
- "7078:7077"
@@ -132,7 +108,7 @@ services:
postgres:
condition: service_healthy
environment:
DATABASE_URL: "postgresql://reflector:reflector@postgres:5432/hatchet?sslmode=disable&connect_timeout=30"
DATABASE_URL: "postgresql://reflector:reflector@postgres:5432/hatchet?sslmode=disable"
SERVER_AUTH_COOKIE_DOMAIN: localhost
SERVER_AUTH_COOKIE_INSECURE: "t"
SERVER_GRPC_BIND_ADDRESS: "0.0.0.0"
@@ -152,5 +128,6 @@ services:
retries: 5
start_period: 30s
volumes:
next_cache:
networks:
default:
attachable: true

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@@ -1,214 +0,0 @@
---
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.yml -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`

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@@ -1,39 +0,0 @@
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"]

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

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@@ -1,65 +1,10 @@
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):
@@ -69,20 +14,10 @@ class PyannoteDiarizationService:
def load(self):
self._device = "cuda" if torch.cuda.is_available() else "cpu"
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 = Pipeline.from_pretrained(
"pyannote/speaker-diarization-3.1",
use_auth_token=os.environ.get("HF_TOKEN"),
)
self._pipeline.to(torch.device(self._device))
def diarize_file(self, file_path: str, timestamp: float = 0.0) -> dict:

View File

@@ -1,14 +0,0 @@
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"

View File

@@ -1,417 +0,0 @@
#!/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 ---
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.yml -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 $1}' | grep -qx "$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 $1}' | grep -qx "$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
# 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"
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 [[ "$cpu_ok" == "true" ]]; then
ok "CPU service healthy (transcription + diarization)"
else
warn "CPU service not ready yet — it will keep loading in the background"
warn "Check with: docker compose logs cpu"
fi
wait_for_url "http://localhost:1250/health" "Server API" 60 3
echo ""
ok "Server API healthy"
wait_for_url "http://localhost:3000" "Frontend" 90 3
echo ""
ok "Frontend responding"
# Check LLM reachability from inside a container
if compose_cmd exec -T server \
curl -sf "$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 $ROOT_DIR"
err "Run this script from the repo root: ./scripts/setup-standalone.sh"
exit 1
fi
# LLM_URL_VALUE is set by step_llm, used by later steps
LLM_URL_VALUE=""
OLLAMA_PROFILE=""
# docker-compose.yml may reference env_files that don't exist yet;
# touch them so compose_cmd works before the steps that populate them.
touch "$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

@@ -66,22 +66,15 @@ TRANSLATE_URL=https://monadical-sas--reflector-translator-web.modal.run
## LLM backend (Required)
##
## Responsible for generating titles, summaries, and topic detection
## Supports any OpenAI-compatible endpoint.
## Requires OpenAI API key
## =======================================================
## --- 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
## 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 B: Remote/cloud LLM ---
#LLM_API_KEY=sk-your-openai-api-key
#LLM_MODEL=gpt-4o-mini
## LLM_URL defaults to OpenAI when unset
## Optional: Custom endpoint (defaults to OpenAI)
# LLM_URL=https://api.openai.com/v1
## Context size for summary generation (tokens)
LLM_CONTEXT_WINDOW=16000

View File

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

View File

@@ -22,8 +22,6 @@ 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

@@ -1,5 +1,11 @@
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
@@ -9,13 +15,13 @@ class AccessTokenInfo(BaseModel):
pass
def authenticated():
def authenticated(token: Annotated[str, Depends(oauth2_scheme)]):
return None
def current_user():
def current_user(token: Annotated[str, Depends(oauth2_scheme)]):
return None
def current_user_optional():
def current_user_optional(token: Annotated[str, Depends(oauth2_scheme)]):
return None

View File

@@ -146,8 +146,6 @@ 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") or event.payload.get("room")
room = event.payload.get("room_name")
# 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 AliasChoices, BaseModel, ConfigDict, Field, field_validator
from pydantic import BaseModel, Field, field_validator
from reflector.utils.string import NonEmptyString
@@ -41,8 +41,6 @@ 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")
@@ -56,8 +54,6 @@ 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"
)
@@ -86,13 +82,7 @@ class ParticipantJoinedPayload(BaseModel):
Reference: https://docs.daily.co/reference/rest-api/webhooks/events/participant-joined
"""
model_config = ConfigDict(extra="ignore")
room_name: NonEmptyString | None = Field(
None,
description="Daily.co room name",
validation_alias=AliasChoices("room_name", "room"),
)
room_name: NonEmptyString | None = Field(None, description="Daily.co room name")
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")
@@ -110,13 +100,7 @@ class ParticipantLeftPayload(BaseModel):
Reference: https://docs.daily.co/reference/rest-api/webhooks/events/participant-left
"""
model_config = ConfigDict(extra="ignore")
room_name: NonEmptyString | None = Field(
None,
description="Daily.co room name",
validation_alias=AliasChoices("room_name", "room"),
)
room_name: NonEmptyString | None = Field(None, description="Daily.co room name")
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")
@@ -128,9 +112,6 @@ 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):
@@ -140,8 +121,6 @@ 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")
@@ -159,9 +138,7 @@ class RecordingReadyToDownloadPayload(BaseModel):
Reference: https://docs.daily.co/reference/rest-api/webhooks/events/recording-ready-to-download
"""
model_config = ConfigDict(extra="ignore")
type: Literal["cloud", "cloud-audio-only", "raw-tracks"] = Field(
type: Literal["cloud", "raw-tracks"] = Field(
description="The type of recording that was generated"
)
recording_id: NonEmptyString = Field(
@@ -176,9 +153,8 @@ 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 | None = Field(
None,
description="The number of participants on the call that were recorded (optional; Daily may omit it in some webhook versions)",
max_participants: int = Field(
description="The number of participants on the call that were recorded"
)
duration: int = Field(description="The duration in seconds of the call")
s3_key: NonEmptyString = Field(
@@ -204,8 +180,6 @@ 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)"
)
@@ -226,8 +200,6 @@ class RecordingErrorPayload(BaseModel):
class ParticipantJoinedEvent(BaseModel):
model_config = ConfigDict(extra="ignore")
version: NonEmptyString
type: Literal["participant.joined"]
id: NonEmptyString
@@ -240,8 +212,6 @@ class ParticipantJoinedEvent(BaseModel):
class ParticipantLeftEvent(BaseModel):
model_config = ConfigDict(extra="ignore")
version: NonEmptyString
type: Literal["participant.left"]
id: NonEmptyString
@@ -254,8 +224,6 @@ class ParticipantLeftEvent(BaseModel):
class RecordingStartedEvent(BaseModel):
model_config = ConfigDict(extra="ignore")
version: NonEmptyString
type: Literal["recording.started"]
id: NonEmptyString
@@ -268,8 +236,6 @@ class RecordingStartedEvent(BaseModel):
class RecordingReadyEvent(BaseModel):
model_config = ConfigDict(extra="ignore")
version: NonEmptyString
type: Literal["recording.ready-to-download"]
id: NonEmptyString
@@ -282,8 +248,6 @@ class RecordingReadyEvent(BaseModel):
class RecordingErrorEvent(BaseModel):
model_config = ConfigDict(extra="ignore")
version: NonEmptyString
type: Literal["recording.error"]
id: NonEmptyString

View File

@@ -346,6 +346,27 @@ class MeetingController:
return None
return Meeting(**result)
async def get_by_room_and_time_window(
self, room: Room, start_date: datetime, end_date: datetime
) -> Meeting | None:
"""Check if a meeting already exists for this room with the same time window."""
query = (
meetings.select()
.where(
sa.and_(
meetings.c.room_id == room.id,
meetings.c.start_date == start_date,
meetings.c.end_date == end_date,
meetings.c.is_active,
)
)
.limit(1)
)
result = await get_database().fetch_one(query)
if not result:
return None
return Meeting(**result)
async def update_meeting(self, meeting_id: str, **kwargs):
query = meetings.update().where(meetings.c.id == meeting_id).values(**kwargs)
await get_database().execute(query)

View File

@@ -26,7 +26,6 @@ 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
@@ -397,7 +396,7 @@ class SearchController:
transcripts.c.user_id == params.user_id, rooms.c.is_shared
)
)
elif not settings.PUBLIC_MODE:
else:
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)

View File

@@ -406,7 +406,7 @@ class TranscriptController:
query = query.where(
or_(transcripts.c.user_id == user_id, rooms.c.is_shared)
)
elif not settings.PUBLIC_MODE:
else:
query = query.where(rooms.c.is_shared)
if source_kind:

View File

@@ -12,9 +12,7 @@ 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
@@ -115,26 +113,3 @@ 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

@@ -3,8 +3,6 @@ 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,
@@ -22,15 +20,6 @@ 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

@@ -171,13 +171,11 @@ 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,
)

View File

@@ -49,13 +49,11 @@ 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

@@ -60,7 +60,6 @@ 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
@@ -69,7 +68,6 @@ 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(
@@ -161,7 +159,6 @@ 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
@@ -170,7 +167,6 @@ 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

@@ -144,18 +144,7 @@ class StructuredOutputWorkflow(Workflow, Generic[OutputT]):
)
# Network retries handled by OpenAILike (max_retries=3)
# 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(),
},
},
)
response = await Settings.llm.acomplete(json_prompt)
return ExtractionDone(output=response.text)
@step

View File

@@ -0,0 +1,74 @@
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

@@ -97,11 +97,8 @@ async def validate_transcript_for_processing(
if transcript.locked:
return ValidationLocked(detail="Recording is locked")
if (
transcript.status == "idle"
and not transcript.workflow_run_id
and not transcript.recording_id
):
# Check if recording is ready for processing
if transcript.status == "idle" and not transcript.workflow_run_id:
return ValidationNotReady(detail="Recording is not ready for processing")
# Check Celery tasks

View File

@@ -49,7 +49,6 @@ 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
@@ -85,7 +84,9 @@ class Settings(BaseSettings):
)
# Diarization
# backend: modal — HTTP API client (works with Modal.com OR self-hosted gpu/self_hosted/)
# 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/)
DIARIZATION_ENABLED: bool = True
DIARIZATION_BACKEND: str = "modal"
DIARIZATION_URL: str | None = None
@@ -94,6 +95,9 @@ 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

@@ -53,7 +53,6 @@ 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`")
@@ -74,26 +73,17 @@ 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)
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.boto_config = Config(retries={"max_attempts": 3, "mode": "adaptive"})
self.session = aioboto3.Session(
aws_access_key_id=aws_access_key_id,
aws_secret_access_key=aws_secret_access_key,
region_name=aws_region,
)
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/"
self.base_url = f"https://{self._bucket_name}.s3.amazonaws.com/"
# Implement credential properties
@property
@@ -149,9 +139,7 @@ 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, endpoint_url=self._endpoint_url
) as client:
async with self.session.client("s3", config=self.boto_config) as client:
if isinstance(data, bytes):
await client.put_object(Bucket=actual_bucket, Key=s3filename, Body=data)
else:
@@ -174,9 +162,7 @@ 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, endpoint_url=self._endpoint_url
) as client:
async with self.session.client("s3", config=self.boto_config) as client:
presigned_url = await client.generate_presigned_url(
operation,
Params={"Bucket": actual_bucket, "Key": s3filename},
@@ -191,9 +177,7 @@ 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, endpoint_url=self._endpoint_url
) as client:
async with self.session.client("s3", config=self.boto_config) as client:
await client.delete_object(Bucket=actual_bucket, Key=s3filename)
@handle_s3_client_errors("download")
@@ -202,9 +186,7 @@ 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, endpoint_url=self._endpoint_url
) as client:
async with self.session.client("s3", config=self.boto_config) as client:
response = await client.get_object(Bucket=actual_bucket, Key=s3filename)
return await response["Body"].read()
@@ -219,9 +201,7 @@ 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, endpoint_url=self._endpoint_url
) as client:
async with self.session.client("s3", config=self.boto_config) as client:
paginator = client.get_paginator("list_objects_v2")
async for page in paginator.paginate(Bucket=actual_bucket, Prefix=s3prefix):
if "Contents" in page:
@@ -247,9 +227,7 @@ 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, endpoint_url=self._endpoint_url
) as client:
async with self.session.client("s3", config=self.boto_config) as client:
await client.download_fileobj(
Bucket=actual_bucket, Key=s3filename, Fileobj=fileobj
)

View File

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

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

View File

@@ -1,6 +1,6 @@
from typing import Optional
from fastapi import APIRouter, WebSocket, WebSocketDisconnect
from fastapi import APIRouter, WebSocket
from reflector.auth.auth_jwt import JWTAuth # type: ignore
from reflector.db.users import user_controller
@@ -60,8 +60,6 @@ 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

@@ -5,7 +5,7 @@ from celery import shared_task
from celery.utils.log import get_task_logger
from reflector.asynctask import asynctask
from reflector.db.calendar_events import calendar_events_controller
from reflector.db.calendar_events import CalendarEvent, calendar_events_controller
from reflector.db.meetings import meetings_controller
from reflector.db.rooms import Room, rooms_controller
from reflector.redis_cache import RedisAsyncLock
@@ -83,10 +83,9 @@ def _should_sync(room) -> bool:
return time_since_sync.total_seconds() >= room.ics_fetch_interval
MEETING_DEFAULT_DURATION = timedelta(hours=1)
async def create_upcoming_meetings_for_event(event, create_window, room: Room):
async def create_upcoming_meetings_for_event(
event: CalendarEvent, create_window: datetime, room: Room
):
if event.start_time <= create_window:
return
existing_meeting = await meetings_controller.get_by_calendar_event(event.id, room)
@@ -94,6 +93,21 @@ async def create_upcoming_meetings_for_event(event, create_window, room: Room):
if existing_meeting:
return
# Prevent duplicate meetings from aggregated calendar feeds
# (e.g. same event appears with different UIDs from Cal.com and Google Calendar)
end_date = event.end_time
existing_by_time = await meetings_controller.get_by_room_and_time_window(
room, event.start_time, end_date
)
if existing_by_time:
logger.info(
"Skipping duplicate calendar event - meeting already exists for this time window",
room_id=room.id,
event_id=event.id,
existing_meeting_id=existing_by_time.id,
)
return
logger.info(
"Pre-creating meeting for calendar event",
room_id=room.id,
@@ -102,8 +116,6 @@ async def create_upcoming_meetings_for_event(event, create_window, room: Room):
)
try:
end_date = event.end_time or (event.start_time + MEETING_DEFAULT_DURATION)
client = create_platform_client(room.platform)
meeting_data = await client.create_meeting(

View File

@@ -48,15 +48,7 @@ class RedisPubSubManager:
if not self.redis_connection:
await self.connect()
message = json.dumps(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)
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

@@ -15,7 +15,8 @@ from reflector.settings import settings
async def setup_webhook(webhook_url: str):
"""
Create Daily.co webhook. Deletes any existing webhooks first, then creates the new one.
Create or update Daily.co webhook for this environment using dailyco_api module.
Uses DAILY_WEBHOOK_UUID to identify existing webhook.
"""
if not settings.DAILY_API_KEY:
print("Error: DAILY_API_KEY not set")
@@ -34,37 +35,79 @@ async def setup_webhook(webhook_url: str):
]
async with DailyApiClient(api_key=settings.DAILY_API_KEY) as client:
webhooks = await client.list_webhooks()
for wh in webhooks:
await client.delete_webhook(wh.uuid)
print(f"Deleted webhook {wh.uuid}")
webhook_uuid = settings.DAILY_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
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}")
print(f"Created webhook {webhook_uuid} (state: {result.state})")
print(f" URL: {result.url}")
request = CreateWebhookRequest(
url=webhook_url,
eventTypes=event_types,
hmac=settings.DAILY_WEBHOOK_SECRET,
)
result = await client.create_webhook(request)
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")
print(
f"✓ Created replacement webhook {result.uuid} (state: {result.state})"
)
print(f" URL: {result.url}")
return 0
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
if __name__ == "__main__":
@@ -74,7 +117,11 @@ if __name__ == "__main__":
"Example: python recreate_daily_webhook.py https://example.com/v1/daily/webhook"
)
print()
print("Deletes all existing webhooks, then creates a new one.")
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"
)
sys.exit(1)
sys.exit(asyncio.run(setup_webhook(sys.argv[1])))

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 without recording (file upload not ready)."""
"""Test that validation rejects idle transcripts (not ready)."""
from reflector.services.transcript_process import (
ValidationNotReady,
validate_transcript_for_processing,
@@ -274,34 +274,6 @@ 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

@@ -0,0 +1,190 @@
from datetime import datetime, timedelta, timezone
from unittest.mock import AsyncMock, patch
import pytest
from reflector.db import get_database
from reflector.db.calendar_events import CalendarEvent, calendar_events_controller
from reflector.db.meetings import meetings
from reflector.db.rooms import rooms_controller
from reflector.worker.ics_sync import create_upcoming_meetings_for_event
@pytest.mark.asyncio
async def test_duplicate_calendar_event_does_not_create_duplicate_meeting():
"""When an aggregated ICS feed contains the same event with different UIDs
(e.g. Cal.com UID + Google Calendar UUID), only one meeting should be created."""
room = await rooms_controller.add(
name="dedup-test-room",
user_id="test-user",
zulip_auto_post=False,
zulip_stream="",
zulip_topic="",
is_locked=False,
room_mode="normal",
recording_type="cloud",
recording_trigger="automatic-2nd-participant",
is_shared=False,
ics_url="https://calendar.example.com/dedup.ics",
ics_enabled=True,
)
now = datetime.now(timezone.utc)
start_time = now + timedelta(hours=1)
end_time = now + timedelta(hours=2)
# Create first calendar event (Cal.com UID)
event1 = await calendar_events_controller.upsert(
CalendarEvent(
room_id=room.id,
ics_uid="abc123@Cal.com",
title="Team Standup",
start_time=start_time,
end_time=end_time,
)
)
# create_window must be before start_time for the function to proceed
create_window = now - timedelta(minutes=6)
# Create meeting for event1
with patch(
"reflector.worker.ics_sync.create_platform_client"
) as mock_platform_factory:
mock_client = AsyncMock()
async def mock_create_meeting_1(room_name_prefix, *, end_date, room):
return AsyncMock(
meeting_id="meeting-1",
room_name="dedup-test-room-abc",
room_url="https://mock.video/dedup-test-room-abc",
host_room_url="https://mock.video/dedup-test-room-abc?host=true",
)
mock_client.create_meeting = mock_create_meeting_1
mock_client.upload_logo = AsyncMock()
mock_platform_factory.return_value = mock_client
await create_upcoming_meetings_for_event(event1, create_window, room)
# Verify meeting was created
results = await get_database().fetch_all(
meetings.select().where(meetings.c.room_id == room.id)
)
assert len(results) == 1, f"Expected 1 meeting, got {len(results)}"
# Create second calendar event with different UID but same time window (Google Calendar UUID)
event2 = await calendar_events_controller.upsert(
CalendarEvent(
room_id=room.id,
ics_uid="550e8400-e29b-41d4-a716-446655440000",
title="Team Standup",
start_time=start_time,
end_time=end_time,
)
)
# Try to create meeting for event2 - should be skipped due to dedup
with patch(
"reflector.worker.ics_sync.create_platform_client"
) as mock_platform_factory:
mock_client = AsyncMock()
create_meeting_called = False
async def mock_create_meeting_2(room_name_prefix, *, end_date, room):
nonlocal create_meeting_called
create_meeting_called = True
mock_client.create_meeting = mock_create_meeting_2
mock_client.upload_logo = AsyncMock()
mock_platform_factory.return_value = mock_client
await create_upcoming_meetings_for_event(event2, create_window, room)
# Platform client should NOT have been called for the duplicate
assert (
not create_meeting_called
), "create_meeting should not be called for duplicate"
# Verify still only 1 meeting
results = await get_database().fetch_all(
meetings.select().where(meetings.c.room_id == room.id)
)
assert len(results) == 1, f"Expected 1 meeting after dedup, got {len(results)}"
@pytest.mark.asyncio
async def test_different_time_windows_create_separate_meetings():
"""Events at different times should create separate meetings, even if titles match."""
room = await rooms_controller.add(
name="dedup-diff-time-room",
user_id="test-user",
zulip_auto_post=False,
zulip_stream="",
zulip_topic="",
is_locked=False,
room_mode="normal",
recording_type="cloud",
recording_trigger="automatic-2nd-participant",
is_shared=False,
ics_url="https://calendar.example.com/dedup2.ics",
ics_enabled=True,
)
now = datetime.now(timezone.utc)
create_window = now - timedelta(minutes=6)
# Event 1: 1-2pm
event1 = await calendar_events_controller.upsert(
CalendarEvent(
room_id=room.id,
ics_uid="event-morning@Cal.com",
title="Team Standup",
start_time=now + timedelta(hours=1),
end_time=now + timedelta(hours=2),
)
)
# Event 2: 3-4pm (different time)
event2 = await calendar_events_controller.upsert(
CalendarEvent(
room_id=room.id,
ics_uid="event-afternoon@Cal.com",
title="Team Standup",
start_time=now + timedelta(hours=3),
end_time=now + timedelta(hours=4),
)
)
with patch(
"reflector.worker.ics_sync.create_platform_client"
) as mock_platform_factory:
mock_client = AsyncMock()
call_count = 0
async def mock_create_meeting(room_name_prefix, *, end_date, room):
nonlocal call_count
call_count += 1
return AsyncMock(
meeting_id=f"meeting-{call_count}",
room_name=f"dedup-diff-time-room-{call_count}",
room_url=f"https://mock.video/dedup-diff-time-room-{call_count}",
host_room_url=f"https://mock.video/dedup-diff-time-room-{call_count}?host=true",
)
mock_client.create_meeting = mock_create_meeting
mock_client.upload_logo = AsyncMock()
mock_platform_factory.return_value = mock_client
await create_upcoming_meetings_for_event(event1, create_window, room)
await create_upcoming_meetings_for_event(event2, create_window, room)
results = await get_database().fetch_all(
meetings.select().where(meetings.c.room_id == room.id)
)
assert (
len(results) == 2
), f"Expected 2 meetings for different times, got {len(results)}"

View File

@@ -319,51 +319,3 @@ 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

676
server/uv.lock generated
View File

@@ -235,6 +235,12 @@ wheels = [
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[[package]]
name = "antlr4-python3-runtime"
version = "4.9.3"
source = { registry = "https://pypi.org/simple" }
sdist = { url = "https://files.pythonhosted.org/packages/3e/38/7859ff46355f76f8d19459005ca000b6e7012f2f1ca597746cbcd1fbfe5e/antlr4-python3-runtime-4.9.3.tar.gz", hash = "sha256:f224469b4168294902bb1efa80a8bf7855f24c99aef99cbefc1bcd3cce77881b", size = 117034 }
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{ name = "torch", version = "2.8.0+cpu", source = { registry = "https://download.pytorch.org/whl/cpu" }, marker = "sys_platform != 'darwin'" },
{ name = "typing-extensions" },
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version = "5.0.1"
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{ url = "https://files.pythonhosted.org/packages/e5/30/643397144bfbfec6f6ef821f36f33e57d35946c44a2352d3c9f0ae847619/tenacity-9.1.2-py3-none-any.whl", hash = "sha256:f77bf36710d8b73a50b2dd155c97b870017ad21afe6ab300326b0371b3b05138", size = 28248 },
]
[[package]]
name = "tensorboardx"
version = "2.6.4"
source = { registry = "https://pypi.org/simple" }
dependencies = [
{ name = "numpy" },
{ name = "packaging" },
{ name = "protobuf" },
]
sdist = { url = "https://files.pythonhosted.org/packages/2b/c5/d4cc6e293fb837aaf9f76dd7745476aeba8ef7ef5146c3b3f9ee375fe7a5/tensorboardx-2.6.4.tar.gz", hash = "sha256:b163ccb7798b31100b9f5fa4d6bc22dad362d7065c2f24b51e50731adde86828", size = 4769801 }
wheels = [
{ url = "https://files.pythonhosted.org/packages/e0/1d/b5d63f1a6b824282b57f7b581810d20b7a28ca951f2d5b59f1eb0782c12b/tensorboardx-2.6.4-py3-none-any.whl", hash = "sha256:5970cf3a1f0a6a6e8b180ccf46f3fe832b8a25a70b86e5a237048a7c0beb18e2", size = 87201 },
]
[[package]]
name = "threadpoolctl"
version = "3.6.0"
source = { registry = "https://pypi.org/simple" }
sdist = { url = "https://files.pythonhosted.org/packages/b7/4d/08c89e34946fce2aec4fbb45c9016efd5f4d7f24af8e5d93296e935631d8/threadpoolctl-3.6.0.tar.gz", hash = "sha256:8ab8b4aa3491d812b623328249fab5302a68d2d71745c8a4c719a2fcaba9f44e", size = 21274 }
wheels = [
{ url = "https://files.pythonhosted.org/packages/32/d5/f9a850d79b0851d1d4ef6456097579a9005b31fea68726a4ae5f2d82ddd9/threadpoolctl-3.6.0-py3-none-any.whl", hash = "sha256:43a0b8fd5a2928500110039e43a5eed8480b918967083ea48dc3ab9f13c4a7fb", size = 18638 },
]
[[package]]
name = "tiktoken"
version = "0.9.0"
@@ -3440,6 +4064,40 @@ wheels = [
{ url = "https://download.pytorch.org/whl/cpu/torch-2.8.0%2Bcpu-cp312-cp312-win_arm64.whl", hash = "sha256:99fc421a5d234580e45957a7b02effbf3e1c884a5dd077afc85352c77bf41434" },
]
[[package]]
name = "torch-audiomentations"
version = "0.12.0"
source = { registry = "https://pypi.org/simple" }
dependencies = [
{ name = "julius" },
{ 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'" },
{ name = "torch-pitch-shift" },
{ name = "torchaudio", version = "2.8.0", source = { registry = "https://download.pytorch.org/whl/cpu" }, marker = "(platform_machine == 'aarch64' and sys_platform == 'linux') or sys_platform == 'darwin'" },
{ name = "torchaudio", version = "2.8.0+cpu", source = { registry = "https://download.pytorch.org/whl/cpu" }, marker = "(platform_machine != 'aarch64' and sys_platform == 'linux') or (sys_platform != 'darwin' and sys_platform != 'linux')" },
]
sdist = { url = "https://files.pythonhosted.org/packages/31/8d/2f8fd7e34c75f5ee8de4310c3bd3f22270acd44d1f809e2fe7c12fbf35f8/torch_audiomentations-0.12.0.tar.gz", hash = "sha256:b02d4c5eb86376986a53eb405cca5e34f370ea9284411237508e720c529f7888", size = 52094 }
wheels = [
{ url = "https://files.pythonhosted.org/packages/21/9d/1ee04f49c15d2d632f6f7102061d7c07652858e6d91b58a091531034e84f/torch_audiomentations-0.12.0-py3-none-any.whl", hash = "sha256:1b80b91d2016ccf83979622cac8f702072a79b7dcc4c2bee40f00b26433a786b", size = 48506 },
]
[[package]]
name = "torch-pitch-shift"
version = "1.2.5"
source = { registry = "https://pypi.org/simple" }
dependencies = [
{ name = "packaging" },
{ name = "primepy" },
{ 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'" },
{ name = "torchaudio", version = "2.8.0", source = { registry = "https://download.pytorch.org/whl/cpu" }, marker = "(platform_machine == 'aarch64' and sys_platform == 'linux') or sys_platform == 'darwin'" },
{ name = "torchaudio", version = "2.8.0+cpu", source = { registry = "https://download.pytorch.org/whl/cpu" }, marker = "(platform_machine != 'aarch64' and sys_platform == 'linux') or (sys_platform != 'darwin' and sys_platform != 'linux')" },
]
sdist = { url = "https://files.pythonhosted.org/packages/79/a6/722a832bca75d5079f6731e005b3d0c2eec7c6c6863d030620952d143d57/torch_pitch_shift-1.2.5.tar.gz", hash = "sha256:6e1c7531f08d0f407a4c55e5ff8385a41355c5c5d27ab7fa08632e51defbd0ed", size = 4725 }
wheels = [
{ url = "https://files.pythonhosted.org/packages/27/4c/96ac2a09efb56cc3c41fb3ce9b6f4d8c0604499f7481d4a13a7b03e21382/torch_pitch_shift-1.2.5-py3-none-any.whl", hash = "sha256:6f8500cbc13f1c98b11cde1805ce5084f82cdd195c285f34287541f168a7c6a7", size = 5005 },
]
[[package]]
name = "torchaudio"
version = "2.8.0"
@@ -3487,6 +4145,22 @@ wheels = [
{ url = "https://download.pytorch.org/whl/cpu/torchaudio-2.8.0%2Bcpu-cp312-cp312-win_amd64.whl", hash = "sha256:9b302192b570657c1cc787a4d487ae4bbb7f2aab1c01b1fcc46757e7f86f391e" },
]
[[package]]
name = "torchmetrics"
version = "1.8.2"
source = { registry = "https://pypi.org/simple" }
dependencies = [
{ name = "lightning-utilities" },
{ name = "numpy" },
{ name = "packaging" },
{ 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 }
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]
[[package]]
name = "tqdm"
version = "4.67.1"

View File

@@ -11,7 +11,6 @@ import {
import { useRouter } from "next/navigation";
import { useTranscriptGet } from "../../../../lib/apiHooks";
import { parseNonEmptyString } from "../../../../lib/utils";
import { useWebSockets } from "../../useWebSockets";
type TranscriptProcessing = {
params: Promise<{
@@ -25,7 +24,6 @@ export default function TranscriptProcessing(details: TranscriptProcessing) {
const router = useRouter();
const transcript = useTranscriptGet(transcriptId);
useWebSockets(transcriptId);
useEffect(() => {
const status = transcript.data?.status;

View File

@@ -23,16 +23,7 @@ const useWebRTC = (
let p: Peer;
try {
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" }],
},
});
p = new Peer({ initiator: true, stream: stream });
} catch (error) {
setError(error as Error, "Error creating WebRTC");
return;

View File

@@ -431,7 +431,6 @@ export const useWebSockets = (transcriptId: string | null): UseWebSockets => {
);
}
setStatus(message.data);
invalidateTranscript(queryClient, transcriptId as NonEmptyString);
if (message.data.value === "ended") {
ws.close();
}

View File

@@ -8,7 +8,7 @@ import {
useRef,
useState,
} from "react";
import { Box, Spinner, Center, Text } from "@chakra-ui/react";
import { Box, Spinner, Center, Text, Button, VStack } from "@chakra-ui/react";
import { useRouter, useParams } from "next/navigation";
import DailyIframe, {
DailyCall,
@@ -16,10 +16,13 @@ import DailyIframe, {
DailyCustomTrayButton,
DailyCustomTrayButtons,
DailyEventObjectCustomButtonClick,
DailyEventObjectFatalError,
DailyFatalErrorType,
DailyFactoryOptions,
DailyParticipantsObject,
} from "@daily-co/daily-js";
import type { components } from "../../reflector-api";
import { printApiError, ApiError } from "../../api/_error";
import { useAuth } from "../../lib/AuthProvider";
import { useConsentDialog } from "../../lib/consent";
import {
@@ -45,6 +48,63 @@ const RAW_TRACKS_NAMESPACE = "a1b2c3d4-e5f6-7890-abcd-ef1234567890";
const RECORDING_START_DELAY_MS = 2000;
const RECORDING_START_MAX_RETRIES = 5;
const FATAL_ERROR_MESSAGES: Partial<
Record<DailyFatalErrorType, { message: string; rejoinable?: boolean }>
> = {
"connection-error": {
message: "Connection lost. Please check your network.",
rejoinable: true,
},
"exp-room": { message: "The meeting time has ended." },
"exp-token": { message: "Your session has expired.", rejoinable: true },
ejected: { message: "You were removed from this meeting." },
"meeting-full": { message: "This meeting is full." },
"not-allowed": { message: "You are not allowed to join this meeting." },
"nbf-room": { message: "This meeting hasn't started yet." },
"nbf-token": { message: "This meeting hasn't started yet." },
"no-room": { message: "This room does not exist." },
"end-of-life": { message: "This meeting room is no longer available." },
};
function FatalErrorScreen({
error,
roomName,
}: {
error: FatalError;
roomName: string;
}) {
const router = useRouter();
const info =
error.type !== "unknown" ? FATAL_ERROR_MESSAGES[error.type] : undefined;
const message = info?.message ?? `Something went wrong: ${error.message}`;
const rejoinable = info?.rejoinable ?? false;
return (
<Center width="100vw" height="100vh">
<VStack gap={4}>
<Text color="red.500">{message}</Text>
{rejoinable ? (
<>
<Button onClick={() => window.location.reload()}>
Try Rejoining
</Button>
<Button
variant="outline"
onClick={() => router.push(`/${roomName}`)}
>
Leave
</Button>
</>
) : (
<Button onClick={() => router.push(`/${roomName}`)}>
Back to Room
</Button>
)}
</VStack>
</Center>
);
}
type Meeting = components["schemas"]["Meeting"];
type Room = components["schemas"]["RoomDetails"];
@@ -82,6 +142,8 @@ const USE_FRAME_INIT_STATE = {
joined: false as boolean,
} as const;
type FatalError = { type: DailyFatalErrorType | "unknown"; message: string };
// Daily js and not Daily react used right now because daily-js allows for prebuild interface vs. -react is customizable but has no nice defaults
const useFrame = (
container: HTMLDivElement | null,
@@ -89,6 +151,7 @@ const useFrame = (
onLeftMeeting: () => void;
onCustomButtonClick: (ev: DailyEventObjectCustomButtonClick) => void;
onJoinMeeting: () => void;
onError: (ev: DailyEventObjectFatalError) => void;
},
) => {
const [{ frame, joined }, setState] = useState(USE_FRAME_INIT_STATE);
@@ -134,6 +197,7 @@ const useFrame = (
if (!frame) return;
frame.on("left-meeting", cbs.onLeftMeeting);
frame.on("custom-button-click", cbs.onCustomButtonClick);
frame.on("error", cbs.onError);
const joinCb = () => {
if (!frame) {
console.error("frame is null in joined-meeting callback");
@@ -145,6 +209,7 @@ const useFrame = (
return () => {
frame.off("left-meeting", cbs.onLeftMeeting);
frame.off("custom-button-click", cbs.onCustomButtonClick);
frame.off("error", cbs.onError);
frame.off("joined-meeting", joinCb);
};
}, [frame, cbs]);
@@ -188,6 +253,7 @@ export default function DailyRoom({ meeting, room }: DailyRoomProps) {
const joinMutation = useRoomJoinMeeting();
const startRecordingMutation = useMeetingStartRecording();
const [joinedMeeting, setJoinedMeeting] = useState<Meeting | null>(null);
const [fatalError, setFatalError] = useState<FatalError | null>(null);
// Generate deterministic instanceIds so all participants use SAME IDs
const cloudInstanceId = parseNonEmptyString(meeting.id);
@@ -234,8 +300,18 @@ export default function DailyRoom({ meeting, room }: DailyRoomProps) {
const roomUrl = joinedMeeting?.room_url;
const handleLeave = useCallback(() => {
// If a fatal error occurred, don't redirect — let the error UI show
if (fatalError) return;
router.push("/browse");
}, [router]);
}, [router, fatalError]);
const handleError = useCallback((ev: DailyEventObjectFatalError) => {
const error: FatalError = {
type: ev.error?.type ?? "unknown",
message: ev.errorMsg,
};
setFatalError(error);
}, []);
const handleCustomButtonClick = useCallback(
(ev: DailyEventObjectCustomButtonClick) => {
@@ -324,6 +400,7 @@ export default function DailyRoom({ meeting, room }: DailyRoomProps) {
onLeftMeeting: handleLeave,
onCustomButtonClick: handleCustomButtonClick,
onJoinMeeting: handleFrameJoinMeeting,
onError: handleError,
});
useEffect(() => {
@@ -380,13 +457,27 @@ export default function DailyRoom({ meeting, room }: DailyRoomProps) {
}
if (joinMutation.isError) {
const apiDetail = printApiError(
joinMutation.error as /*ref 095959E6-01CC-4CF0-B3A9-F65F12F046D3*/ ApiError,
);
return (
<Center width="100vw" height="100vh">
<Text color="red.500">Failed to join meeting. Please try again.</Text>
<VStack gap={4}>
<Text color="red.500">
{apiDetail ?? "Failed to join meeting. Please try again."}
</Text>
<Button onClick={() => router.push(`/${roomName}`)}>
Back to Room
</Button>
</VStack>
</Center>
);
}
if (fatalError) {
return <FatalErrorScreen error={fatalError} roomName={roomName} />;
}
if (!roomUrl) {
return null;
}

View File

@@ -9,6 +9,7 @@ import { MeetingId } from "./types";
import { NonEmptyString } from "./utils";
/*
* ref 095959E6-01CC-4CF0-B3A9-F65F12F046D3
* XXX error types returned from the hooks are not always correct; declared types are ValidationError but real type could be string or any other
* this is either a limitation or incorrect usage of Python json schema generator
* or, limitation or incorrect usage of .d type generator from json schema