feat: post Hatchet DAG status to Zulip with live updates

Post a rendered DAG status message to a configurable Zulip stream/topic
when a Hatchet workflow is dispatched. Update it after each task
completes (success or failure), and delete it when post_zulip runs
so the final transcript notification replaces it.

On pipeline failure, appends an error banner (:cross_mark:) with the
failing step name and error message.

New settings: ZULIP_DAG_STREAM, ZULIP_DAG_TOPIC, ZULIP_HOST_HEADER.
New module: reflector/hatchet/dag_zulip.py (create/update/delete).

COMPOSE_STANDALONE_TODO.md

@@ -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)

docker-compose.standalone.yml

@@ -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:

docker-compose.yml

@@ -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
+      interval: 10s
-      timeout: 5s
+      timeout: 10s
-      retries: 10
+      retries: 5
-      start_period: 15s
+      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:
+networks:
-  next_cache:
+  default:
+    attachable: true

docs/docs/installation/setup-standalone.md

@@ -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`

gpu/self_hosted/Dockerfile.cpu

@@ -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"]

gpu/self_hosted/app/auth.py

@@ -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,

gpu/self_hosted/app/services/diarizer.py

@@ -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")
+        self._pipeline = Pipeline.from_pretrained(
-
+            "pyannote/speaker-diarization-3.1",
-        if hf_token:
+            use_auth_token=os.environ.get("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:

scripts/garage.toml

@@ -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"

scripts/setup-standalone.sh

@@ -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 "$@"

server/.env.example

@@ -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) ---
+## OpenAI API key - get from https://platform.openai.com/account/api-keys
-## Setup: ./scripts/setup-standalone.sh
+LLM_API_KEY=sk-your-openai-api-key
-## Mac: Ollama runs natively (Metal GPU). Containers reach it via host.docker.internal.
+LLM_MODEL=gpt-4o-mini
-## 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
 
-## --- Option B: Remote/cloud LLM ---
+## Optional: Custom endpoint (defaults to OpenAI)
-#LLM_API_KEY=sk-your-openai-api-key
+# LLM_URL=https://api.openai.com/v1
-#LLM_MODEL=gpt-4o-mini
-## LLM_URL defaults to OpenAI when unset
 
 ## Context size for summary generation (tokens)
 LLM_CONTEXT_WINDOW=16000

server/pyproject.toml

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

server/reflector/asynctask.py

@@ -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:

server/reflector/auth/auth_none.py

@@ -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

server/reflector/dailyco_api/client.py

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

server/reflector/dailyco_api/webhook_utils.py

@@ -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
 

server/reflector/dailyco_api/webhooks.py

@@ -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")
-
-    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")
@@ -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")
-
-    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")
@@ -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", "raw-tracks"] = Field(
-
-    type: Literal["cloud", "cloud-audio-only", "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(
+    max_participants: int = Field(
-        None,
+        description="The number of participants on the call that were recorded"
-        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(
@@ -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

server/reflector/db/search.py

@@ -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)

server/reflector/db/transcripts.py

@@ -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:

server/reflector/hatchet/client.py

@@ -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,
-        )

server/reflector/hatchet/dag_zulip.py

@@ -0,0 +1,144 @@
+"""
+Hatchet DAG Status -> Zulip Live Updates.
+
+Posts/updates/deletes a Zulip message showing the Hatchet workflow DAG status.
+All functions are fire-and-forget (catch + warning log on failure).
+
+Note: Uses deferred imports throughout for fork-safety,
+consistent with the pipeline pattern in daily_multitrack_pipeline.py.
+"""
+
+from reflector.logger import logger
+from reflector.settings import settings
+
+
+def _dag_zulip_enabled() -> bool:
+    return bool(
+        settings.ZULIP_REALM and settings.ZULIP_DAG_STREAM and settings.ZULIP_DAG_TOPIC
+    )
+
+
+async def create_dag_zulip_message(transcript_id: str, workflow_run_id: str) -> None:
+    """Post initial DAG status to Zulip. Called at dispatch time (normal DB context)."""
+    if not _dag_zulip_enabled():
+        return
+
+    try:
+        from reflector.db.transcripts import transcripts_controller  # noqa: PLC0415
+        from reflector.hatchet.client import HatchetClientManager  # noqa: PLC0415
+        from reflector.tools.render_hatchet_run import (  # noqa: PLC0415
+            render_run_detail,
+        )
+        from reflector.zulip import send_message_to_zulip  # noqa: PLC0415
+
+        client = HatchetClientManager.get_client()
+        details = await client.runs.aio_get(workflow_run_id)
+        content = render_run_detail(details)
+
+        response = await send_message_to_zulip(
+            settings.ZULIP_DAG_STREAM, settings.ZULIP_DAG_TOPIC, content
+        )
+        message_id = response.get("id")
+
+        if message_id:
+            transcript = await transcripts_controller.get_by_id(transcript_id)
+            if transcript:
+                await transcripts_controller.update(
+                    transcript, {"zulip_message_id": message_id}
+                )
+    except Exception:
+        logger.warning(
+            "[DAG Zulip] Failed to create DAG message",
+            transcript_id=transcript_id,
+            workflow_run_id=workflow_run_id,
+            exc_info=True,
+        )
+
+
+async def update_dag_zulip_message(
+    transcript_id: str,
+    workflow_run_id: str,
+    error_message: str | None = None,
+) -> None:
+    """Update existing DAG status in Zulip. Called from Hatchet worker (forked).
+
+    Args:
+        error_message: If set, appended as an error banner to the rendered DAG.
+    """
+    if not _dag_zulip_enabled():
+        return
+
+    try:
+        from reflector.db.transcripts import transcripts_controller  # 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.tools.render_hatchet_run import (  # noqa: PLC0415
+            render_run_detail,
+        )
+        from reflector.zulip import update_zulip_message  # noqa: PLC0415
+
+        async with fresh_db_connection():
+            transcript = await transcripts_controller.get_by_id(transcript_id)
+            if not transcript or not transcript.zulip_message_id:
+                return
+
+            client = HatchetClientManager.get_client()
+            details = await client.runs.aio_get(workflow_run_id)
+            content = render_run_detail(details)
+
+            if error_message:
+                content += f"\n\n:cross_mark: **{error_message}**"
+
+            await update_zulip_message(
+                transcript.zulip_message_id,
+                settings.ZULIP_DAG_STREAM,
+                settings.ZULIP_DAG_TOPIC,
+                content,
+            )
+    except Exception:
+        logger.warning(
+            "[DAG Zulip] Failed to update DAG message",
+            transcript_id=transcript_id,
+            workflow_run_id=workflow_run_id,
+            exc_info=True,
+        )
+
+
+async def delete_dag_zulip_message(transcript_id: str) -> None:
+    """Delete DAG Zulip message and clear zulip_message_id.
+
+    Called from post_zulip task (already inside fresh_db_connection).
+    Swallows InvalidMessageError (message already deleted).
+    """
+    if not _dag_zulip_enabled():
+        return
+
+    try:
+        from reflector.db.transcripts import transcripts_controller  # noqa: PLC0415
+        from reflector.zulip import (  # noqa: PLC0415
+            InvalidMessageError,
+            delete_zulip_message,
+        )
+
+        transcript = await transcripts_controller.get_by_id(transcript_id)
+        if not transcript or not transcript.zulip_message_id:
+            return
+
+        try:
+            await delete_zulip_message(transcript.zulip_message_id)
+        except InvalidMessageError:
+            logger.warning(
+                "[DAG Zulip] Message already deleted",
+                transcript_id=transcript_id,
+                zulip_message_id=transcript.zulip_message_id,
+            )
+
+        await transcripts_controller.update(transcript, {"zulip_message_id": None})
+    except Exception:
+        logger.warning(
+            "[DAG Zulip] Failed to delete DAG message",
+            transcript_id=transcript_id,
+            exc_info=True,
+        )

server/reflector/hatchet/run_workers_llm.py

@@ -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,

server/reflector/hatchet/workflows/daily_multitrack_pipeline.py

@@ -45,6 +45,7 @@ from reflector.hatchet.constants import (
     TIMEOUT_SHORT,
     TaskName,
 )
+from reflector.hatchet.dag_zulip import update_dag_zulip_message
 from reflector.hatchet.workflows.models import (
     ActionItemsResult,
     ConsentResult,
@@ -171,13 +172,11 @@ 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,
     )
 
 
@@ -240,7 +239,14 @@ def with_error_handling(
         @functools.wraps(func)
         async def wrapper(input: PipelineInput, ctx: Context) -> R:
             try:
-                return await func(input, ctx)
+                result = await func(input, ctx)
+                try:
+                    await update_dag_zulip_message(
+                        input.transcript_id, ctx.workflow_run_id
+                    )
+                except Exception:
+                    pass
+                return result
             except Exception as e:
                 logger.error(
                     f"[Hatchet] {step_name} failed",
@@ -248,6 +254,14 @@ def with_error_handling(
                     error=str(e),
                     exc_info=True,
                 )
+                try:
+                    await update_dag_zulip_message(
+                        input.transcript_id,
+                        ctx.workflow_run_id,
+                        error_message=f"{step_name} failed: {e}",
+                    )
+                except Exception:
+                    pass
                 if set_error_status:
                     await set_workflow_error_status(input.transcript_id)
                 raise
@@ -1296,6 +1310,11 @@ async def post_zulip(input: PipelineInput, ctx: Context) -> ZulipResult:
 
     async with fresh_db_connection():
         from reflector.db.transcripts import transcripts_controller  # noqa: PLC0415
+        from reflector.hatchet.dag_zulip import (  # noqa: PLC0415
+            delete_dag_zulip_message,
+        )
+
+        await delete_dag_zulip_message(input.transcript_id)
 
         transcript = await transcripts_controller.get_by_id(input.transcript_id)
         if transcript:

server/reflector/hatchet/workflows/padding_workflow.py

@@ -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(

server/reflector/hatchet/workflows/track_processing.py

@@ -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(

server/reflector/llm.py

@@ -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
+        response = await Settings.llm.acomplete(json_prompt)
-        # 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

server/reflector/processors/audio_diarization_pyannote.py

@@ -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)

server/reflector/services/transcript_process.py

@@ -17,6 +17,7 @@ from hatchet_sdk.clients.rest.models import V1TaskStatus
 from reflector.db.recordings import recordings_controller
 from reflector.db.transcripts import Transcript, transcripts_controller
 from reflector.hatchet.client import HatchetClientManager
+from reflector.hatchet.dag_zulip import create_dag_zulip_message
 from reflector.logger import logger
 from reflector.pipelines.main_file_pipeline import task_pipeline_file_process
 from reflector.utils.string import NonEmptyString
@@ -97,11 +98,8 @@ async def validate_transcript_for_processing(
     if transcript.locked:
         return ValidationLocked(detail="Recording is locked")
 
-    if (
+    # Check if recording is ready for processing
-        transcript.status == "idle"
+    if transcript.status == "idle" and not transcript.workflow_run_id:
-        and not transcript.workflow_run_id
-        and not transcript.recording_id
-    ):
         return ValidationNotReady(detail="Recording is not ready for processing")
 
     # Check Celery tasks
@@ -269,6 +267,16 @@ async def dispatch_transcript_processing(
                 transcript, {"workflow_run_id": workflow_id}
             )
 
+        try:
+            await create_dag_zulip_message(config.transcript_id, workflow_id)
+        except Exception:
+            logger.warning(
+                "[DAG Zulip] Failed to create DAG message at dispatch",
+                transcript_id=config.transcript_id,
+                workflow_id=workflow_id,
+                exc_info=True,
+            )
+
         logger.info("Hatchet workflow dispatched", workflow_id=workflow_id)
         return None
 

server/reflector/settings.py

@@ -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
@@ -157,6 +161,9 @@ class Settings(BaseSettings):
     ZULIP_REALM: str | None = None
     ZULIP_API_KEY: str | None = None
     ZULIP_BOT_EMAIL: str | None = None
+    ZULIP_DAG_STREAM: str | None = None
+    ZULIP_DAG_TOPIC: str | None = None
+    ZULIP_HOST_HEADER: str | None = None
 
     # Hatchet workflow orchestration (always enabled for multitrack processing)
     HATCHET_CLIENT_TOKEN: str | None = None

server/reflector/storage/storage_aws.py

@@ -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)
-
+        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,
         )
-        if aws_endpoint_url:
+        self.base_url = f"https://{self._bucket_name}.s3.amazonaws.com/"
-            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
@@ -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(
+        async with self.session.client("s3", config=self.boto_config) as 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:
@@ -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(
+        async with self.session.client("s3", config=self.boto_config) as 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},
@@ -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(
+        async with self.session.client("s3", config=self.boto_config) as 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")
@@ -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(
+        async with self.session.client("s3", config=self.boto_config) as 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()
 
@@ -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(
+        async with self.session.client("s3", config=self.boto_config) as 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:
@@ -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(
+        async with self.session.client("s3", config=self.boto_config) as client:
-            "s3", config=self.boto_config, endpoint_url=self._endpoint_url
-        ) as client:
             await client.download_fileobj(
                 Bucket=actual_bucket, Key=s3filename, Fileobj=fileobj
             )

server/reflector/tools/render_hatchet_run.py

@@ -0,0 +1,412 @@
+"""
+Render Hatchet workflow runs as text DAG.
+
+Usage:
+    # Show latest 5 runs (summary table)
+    uv run -m reflector.tools.render_hatchet_run
+
+    # Show specific run with full DAG + task details
+    uv run -m reflector.tools.render_hatchet_run <workflow_run_id>
+
+    # Drill into Nth run from the list (1-indexed)
+    uv run -m reflector.tools.render_hatchet_run --show 1
+
+    # Show latest N runs
+    uv run -m reflector.tools.render_hatchet_run --last 10
+
+    # Filter by status
+    uv run -m reflector.tools.render_hatchet_run --status FAILED
+    uv run -m reflector.tools.render_hatchet_run --status RUNNING
+"""
+
+import argparse
+import asyncio
+from collections import defaultdict
+from datetime import datetime, timedelta, timezone
+
+from hatchet_sdk.clients.rest.models import (
+    V1TaskEvent,
+    V1TaskStatus,
+    V1TaskSummary,
+    V1WorkflowRunDetails,
+    WorkflowRunShapeItemForWorkflowRunDetails,
+)
+
+from reflector.hatchet.client import HatchetClientManager
+
+STATUS_ICON = {
+    V1TaskStatus.COMPLETED: "\u2705",
+    V1TaskStatus.RUNNING: "\u23f3",
+    V1TaskStatus.FAILED: "\u274c",
+    V1TaskStatus.QUEUED: "\u23f8\ufe0f",
+    V1TaskStatus.CANCELLED: "\u26a0\ufe0f",
+}
+
+STATUS_LABEL = {
+    V1TaskStatus.COMPLETED: "Complete",
+    V1TaskStatus.RUNNING: "Running",
+    V1TaskStatus.FAILED: "FAILED",
+    V1TaskStatus.QUEUED: "Queued",
+    V1TaskStatus.CANCELLED: "Cancelled",
+}
+
+
+def _fmt_time(dt: datetime | None) -> str:
+    if dt is None:
+        return "-"
+    return dt.strftime("%H:%M:%S")
+
+
+def _fmt_duration(ms: int | None) -> str:
+    if ms is None:
+        return "-"
+    secs = ms / 1000
+    if secs < 60:
+        return f"{secs:.1f}s"
+    mins = secs / 60
+    return f"{mins:.1f}m"
+
+
+def _fmt_status_line(task: V1TaskSummary) -> str:
+    """Format a status line like: Complete (finished 20:31:44)"""
+    label = STATUS_LABEL.get(task.status, task.status.value)
+    icon = STATUS_ICON.get(task.status, "?")
+
+    if task.status == V1TaskStatus.COMPLETED and task.finished_at:
+        return f"{icon} {label} (finished {_fmt_time(task.finished_at)})"
+    elif task.status == V1TaskStatus.RUNNING and task.started_at:
+        parts = [f"started {_fmt_time(task.started_at)}"]
+        if task.duration:
+            parts.append(f"{_fmt_duration(task.duration)} elapsed")
+        return f"{icon} {label} ({', '.join(parts)})"
+    elif task.status == V1TaskStatus.FAILED and task.finished_at:
+        return f"{icon} {label} (failed {_fmt_time(task.finished_at)})"
+    elif task.status == V1TaskStatus.CANCELLED:
+        return f"{icon} {label}"
+    elif task.status == V1TaskStatus.QUEUED:
+        return f"{icon} {label}"
+    return f"{icon} {label}"
+
+
+def _topo_sort(
+    shape: list[WorkflowRunShapeItemForWorkflowRunDetails],
+) -> list[str]:
+    """Topological sort of step_ids from shape DAG."""
+    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 render_run_detail(details: V1WorkflowRunDetails) -> str:
+    """Render a single workflow run as markdown DAG with task details."""
+    shape = details.shape or []
+    tasks = details.tasks or []
+    events = details.task_events or []
+    run = details.run
+
+    if not shape:
+        return f"Run {run.metadata.id}: {run.status.value} (no shape data)"
+
+    # 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 (parents)
+    parents: 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:
+                parents[child_id].append(s.step_id)
+
+    # Join tasks by step_id
+    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
+
+    # Events indexed by task_external_id
+    events_by_task: dict[str, list[V1TaskEvent]] = defaultdict(list)
+    for ev in events:
+        events_by_task[ev.task_id].append(ev)
+
+    ordered = _topo_sort(shape)
+
+    lines: list[str] = []
+
+    # Run header
+    run_icon = STATUS_ICON.get(run.status, "?")
+    run_name = run.display_name or run.workflow_id
+    dur = _fmt_duration(run.duration)
+    lines.append(f"**{run_name}** {run_icon} {dur}")
+    lines.append(f"ID: `{run.metadata.id}`")
+    if run.additional_metadata:
+        meta_parts = [f"{k}=`{v}`" for k, v in run.additional_metadata.items()]
+        lines.append(f"Meta: {', '.join(meta_parts)}")
+    if run.error_message:
+        # Take first line of error only for header
+        first_line = run.error_message.split("\n")[0]
+        lines.append(f"Error: {first_line}")
+    lines.append("")
+
+    # DAG Status Overview table
+    lines.append("**DAG Status Overview**")
+    lines.append("")
+    lines.append("| Node | Status | Duration | Dependencies |")
+    lines.append("|------|--------|----------|--------------|")
+
+    for step_id in ordered:
+        s = step_to_shape[step_id]
+        t = task_by_step.get(step_id)
+        name = step_to_name[step_id]
+        icon = STATUS_ICON.get(t.status, "?") if t else "?"
+        dur = _fmt_duration(t.duration) if t else "-"
+
+        parent_names = [step_to_name[p] for p in parents[step_id]]
+        child_names = [
+            step_to_name[c] for c in (s.children_step_ids or []) if c in step_to_name
+        ]
+        deps_left = ", ".join(parent_names) if parent_names else ""
+        deps_right = ", ".join(child_names) if child_names else ""
+        if deps_left and deps_right:
+            deps = f"{deps_left} \u2192 {deps_right}"
+        elif deps_right:
+            deps = f"\u2192 {deps_right}"
+        elif deps_left:
+            deps = f"{deps_left} \u2192"
+        else:
+            deps = "-"
+
+        lines.append(f"| {name} | {icon} | {dur} | {deps} |")
+
+    lines.append("")
+    lines.append("---")
+    lines.append("")
+
+    # Node details
+    for step_id in ordered:
+        t = task_by_step.get(step_id)
+        name = step_to_name[step_id]
+
+        if not t:
+            lines.append(f"**\U0001f4e6 {name}**")
+            lines.append("Status: no task data")
+            lines.append("")
+            continue
+
+        lines.append(f"**\U0001f4e6 {name}**")
+        lines.append(f"Status: {_fmt_status_line(t)}")
+
+        if t.duration:
+            lines.append(f"Duration: {_fmt_duration(t.duration)}")
+        if t.retry_count and t.retry_count > 0:
+            lines.append(f"Retries: {t.retry_count}")
+
+        # Fan-out children
+        if t.num_spawned_children and t.num_spawned_children > 0:
+            children = t.children or []
+            completed = sum(1 for c in children if c.status == V1TaskStatus.COMPLETED)
+            failed = sum(1 for c in children if c.status == V1TaskStatus.FAILED)
+            running = sum(1 for c in children if c.status == V1TaskStatus.RUNNING)
+            lines.append(
+                f"Spawned children: {completed}/{t.num_spawned_children} done"
+                f"{f', {running} running' if running else ''}"
+                f"{f', {failed} failed' if failed else ''}"
+            )
+
+        # Error message (first meaningful line only, full trace in events)
+        if t.error_message:
+            err_lines = t.error_message.strip().split("\n")
+            # Find first non-empty, non-traceback line
+            err_summary = err_lines[0]
+            for line in err_lines:
+                stripped = line.strip()
+                if stripped and not stripped.startswith(
+                    ("Traceback", "File ", "{", ")")
+                ):
+                    err_summary = stripped
+                    break
+            lines.append(f"Error: `{err_summary}`")
+
+        # Events log
+        task_events = sorted(
+            events_by_task.get(t.task_external_id, []),
+            key=lambda e: e.timestamp,
+        )
+        if task_events:
+            lines.append("Events:")
+            for ev in task_events:
+                ts = ev.timestamp.strftime("%H:%M:%S")
+                ev_icon = ""
+                if ev.event_type.value == "FINISHED":
+                    ev_icon = "\u2705 "
+                elif ev.event_type.value in ("FAILED", "TIMED_OUT"):
+                    ev_icon = "\u274c "
+                elif ev.event_type.value == "STARTED":
+                    ev_icon = "\u25b6\ufe0f "
+                elif ev.event_type.value == "RETRYING":
+                    ev_icon = "\U0001f504 "
+                elif ev.event_type.value == "CANCELLED":
+                    ev_icon = "\u26a0\ufe0f "
+
+                msg = ev.message.strip()
+                if ev.error_message:
+                    # Just first line of error in event log
+                    err_first = ev.error_message.strip().split("\n")[0]
+                    if msg:
+                        msg += f" | {err_first}"
+                    else:
+                        msg = err_first
+
+                if msg:
+                    lines.append(f"  `{ts}` {ev_icon}{ev.event_type.value}: {msg}")
+                else:
+                    lines.append(f"  `{ts}` {ev_icon}{ev.event_type.value}")
+
+        lines.append("")
+
+    return "\n".join(lines)
+
+
+def render_run_summary(idx: int, run: V1TaskSummary) -> str:
+    """One-line summary for a run in the list view."""
+    icon = STATUS_ICON.get(run.status, "?")
+    name = run.display_name or run.workflow_name or "?"
+    run_id = run.workflow_run_external_id or "?"
+    dur = _fmt_duration(run.duration)
+    started = _fmt_time(run.started_at)
+    meta = ""
+    if run.additional_metadata:
+        meta_parts = [f"{k}=`{v}`" for k, v in run.additional_metadata.items()]
+        meta = f"  ({', '.join(meta_parts)})"
+    return (
+        f"  {idx}. {icon} **{name}** started={started} dur={dur}{meta}\n"
+        f"     `{run_id}`"
+    )
+
+
+async def _fetch_run_list(
+    count: int = 5,
+    statuses: list[V1TaskStatus] | None = None,
+) -> list[V1TaskSummary]:
+    client = HatchetClientManager.get_client()
+    since = datetime.now(timezone.utc) - timedelta(days=7)
+    runs = await client.runs.aio_list(
+        since=since,
+        statuses=statuses,
+        limit=count,
+    )
+    return runs.rows or []
+
+
+async def list_recent_runs(
+    count: int = 5,
+    statuses: list[V1TaskStatus] | None = None,
+) -> str:
+    """List recent workflow runs as text."""
+    rows = await _fetch_run_list(count, statuses)
+
+    if not rows:
+        return "No runs found in the last 7 days."
+
+    lines = [f"Recent runs ({len(rows)}):", ""]
+    for i, run in enumerate(rows, 1):
+        lines.append(render_run_summary(i, run))
+
+    lines.append("")
+    lines.append("Use `--show N` to see full DAG for run N")
+    return "\n".join(lines)
+
+
+async def show_run(workflow_run_id: str) -> str:
+    """Fetch and render a single run."""
+    client = HatchetClientManager.get_client()
+    details = await client.runs.aio_get(workflow_run_id)
+    return render_run_detail(details)
+
+
+async def show_nth_run(
+    n: int,
+    count: int = 5,
+    statuses: list[V1TaskStatus] | None = None,
+) -> str:
+    """Fetch list, then drill into Nth run."""
+    rows = await _fetch_run_list(count, statuses)
+
+    if not rows:
+        return "No runs found in the last 7 days."
+    if n < 1 or n > len(rows):
+        return f"Invalid index {n}. Have {len(rows)} runs (1-{len(rows)})."
+
+    run = rows[n - 1]
+    return await show_run(run.workflow_run_external_id)
+
+
+async def main_async(args: argparse.Namespace) -> None:
+    statuses = [V1TaskStatus(args.status)] if args.status else None
+
+    if args.run_id:
+        output = await show_run(args.run_id)
+    elif args.show is not None:
+        output = await show_nth_run(args.show, count=args.last, statuses=statuses)
+    else:
+        output = await list_recent_runs(count=args.last, statuses=statuses)
+
+    print(output)
+
+
+def main() -> None:
+    parser = argparse.ArgumentParser(
+        description="Render Hatchet workflow runs as text DAG"
+    )
+    parser.add_argument(
+        "run_id",
+        nargs="?",
+        default=None,
+        help="Workflow run ID to show in detail. If omitted, lists recent runs.",
+    )
+    parser.add_argument(
+        "--show",
+        type=int,
+        default=None,
+        metavar="N",
+        help="Show full DAG for the Nth run in the list (1-indexed)",
+    )
+    parser.add_argument(
+        "--last",
+        type=int,
+        default=5,
+        help="Number of recent runs to list (default: 5)",
+    )
+    parser.add_argument(
+        "--status",
+        choices=["QUEUED", "RUNNING", "COMPLETED", "FAILED", "CANCELLED"],
+        help="Filter by status",
+    )
+
+    args = parser.parse_args()
+    asyncio.run(main_async(args))
+
+
+if __name__ == "__main__":
+    main()

server/reflector/views/daily.py

@@ -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)
+        logger.error("Failed to parse webhook event", error=str(e), body=body.decode())
-        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:

server/reflector/views/transcripts_upload.py

@@ -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
+    # set the status to "uploaded"
-    await transcripts_controller.update(
+    await transcripts_controller.update(transcript, {"status": "uploaded"})
-        transcript, {"status": "uploaded", "source_kind": SourceKind.FILE}
-    )
 
     # launch a background task to process the file
     task_pipeline_file_process.delay(transcript_id=transcript_id)

server/reflector/views/user_websocket.py

@@ -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)

server/reflector/worker/process.py

@@ -25,6 +25,7 @@ from reflector.db.transcripts import (
     transcripts_controller,
 )
 from reflector.hatchet.client import HatchetClientManager
+from reflector.hatchet.dag_zulip import create_dag_zulip_message
 from reflector.pipelines.main_file_pipeline import task_pipeline_file_process
 from reflector.pipelines.main_live_pipeline import asynctask
 from reflector.pipelines.topic_processing import EmptyPipeline
@@ -372,6 +373,16 @@ async def _process_multitrack_recording_inner(
 
     await transcripts_controller.update(transcript, {"workflow_run_id": workflow_id})
 
+    try:
+        await create_dag_zulip_message(transcript.id, workflow_id)
+    except Exception:
+        logger.warning(
+            "[DAG Zulip] Failed to create DAG message at dispatch",
+            transcript_id=transcript.id,
+            workflow_id=workflow_id,
+            exc_info=True,
+        )
+
 
 @shared_task
 @asynctask
@@ -1079,6 +1090,16 @@ async def reprocess_failed_daily_recordings():
                 transcript, {"workflow_run_id": workflow_id}
             )
 
+            try:
+                await create_dag_zulip_message(transcript.id, workflow_id)
+            except Exception:
+                logger.warning(
+                    "[DAG Zulip] Failed to create DAG message at reprocess dispatch",
+                    transcript_id=transcript.id,
+                    workflow_id=workflow_id,
+                    exc_info=True,
+                )
+
             logger.info(
                 "Queued Daily recording for Hatchet reprocessing",
                 recording_id=recording.id,

server/reflector/ws_manager.py

@@ -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)
-            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)

server/reflector/zulip.py

@@ -12,9 +12,16 @@ class InvalidMessageError(Exception):
     pass
 
 
+def _zulip_client() -> httpx.AsyncClient:
+    headers = {}
+    if settings.ZULIP_HOST_HEADER:
+        headers["Host"] = settings.ZULIP_HOST_HEADER
+    return httpx.AsyncClient(verify=False, headers=headers)
+
+
 async def get_zulip_topics(stream_id: int) -> list[dict]:
     try:
-        async with httpx.AsyncClient() as client:
+        async with _zulip_client() as client:
             response = await client.get(
                 f"https://{settings.ZULIP_REALM}/api/v1/users/me/{stream_id}/topics",
                 auth=(settings.ZULIP_BOT_EMAIL, settings.ZULIP_API_KEY),
@@ -29,7 +36,7 @@ async def get_zulip_topics(stream_id: int) -> list[dict]:
 
 async def get_zulip_streams() -> list[dict]:
     try:
-        async with httpx.AsyncClient() as client:
+        async with _zulip_client() as client:
             response = await client.get(
                 f"https://{settings.ZULIP_REALM}/api/v1/streams",
                 auth=(settings.ZULIP_BOT_EMAIL, settings.ZULIP_API_KEY),
@@ -44,7 +51,7 @@ async def get_zulip_streams() -> list[dict]:
 
 async def send_message_to_zulip(stream: str, topic: str, content: str):
     try:
-        async with httpx.AsyncClient() as client:
+        async with _zulip_client() as client:
             response = await client.post(
                 f"https://{settings.ZULIP_REALM}/api/v1/messages",
                 data={
@@ -66,7 +73,7 @@ async def send_message_to_zulip(stream: str, topic: str, content: str):
 
 async def update_zulip_message(message_id: int, stream: str, topic: str, content: str):
     try:
-        async with httpx.AsyncClient() as client:
+        async with _zulip_client() as client:
             response = await client.patch(
                 f"https://{settings.ZULIP_REALM}/api/v1/messages/{message_id}",
                 data={
@@ -90,6 +97,27 @@ async def update_zulip_message(message_id: int, stream: str, topic: str, content
         raise Exception(f"Failed to update Zulip message: {error}")
 
 
+async def delete_zulip_message(message_id: int):
+    try:
+        async with _zulip_client() as client:
+            response = await client.delete(
+                f"https://{settings.ZULIP_REALM}/api/v1/messages/{message_id}",
+                auth=(settings.ZULIP_BOT_EMAIL, settings.ZULIP_API_KEY),
+            )
+
+            if (
+                response.status_code == 400
+                and response.json()["msg"] == "Invalid message(s)"
+            ):
+                raise InvalidMessageError(f"There is no message with id: {message_id}")
+
+            response.raise_for_status()
+
+            return response.json()
+    except httpx.RequestError as error:
+        raise Exception(f"Failed to delete Zulip message: {error}")
+
+
 def get_zulip_message(transcript: Transcript, include_topics: bool):
     transcript_url = f"{settings.UI_BASE_URL}/transcripts/{transcript.id}"
 

server/scripts/recreate_daily_webhook.py

@@ -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()
+        webhook_uuid = settings.DAILY_WEBHOOK_UUID
-        for wh in webhooks:
-            await client.delete_webhook(wh.uuid)
-            print(f"Deleted webhook {wh.uuid}")
 
-        request = CreateWebhookRequest(
+        if webhook_uuid:
-            url=webhook_url,
+            print(f"Updating existing webhook {webhook_uuid}...")
-            eventTypes=event_types,
+            try:
-            hmac=settings.DAILY_WEBHOOK_SECRET,
+                # Note: Daily.co doesn't support PATCH well, so we delete + recreate
-        )
+                await client.delete_webhook(webhook_uuid)
-        result = await client.create_webhook(request)
+                print(f"Deleted old webhook {webhook_uuid}")
-        webhook_uuid = result.uuid
 
-        print(f"✓ Created webhook {webhook_uuid} (state: {result.state})")
+                request = CreateWebhookRequest(
-        print(f"  URL: {result.url}")
+                    url=webhook_url,
+                    eventTypes=event_types,
+                    hmac=settings.DAILY_WEBHOOK_SECRET,
+                )
+                result = await client.create_webhook(request)
 
-        env_file = Path(__file__).parent.parent / ".env"
+                print(
-        if env_file.exists():
+                    f"✓ Created replacement webhook {result.uuid} (state: {result.state})"
-            lines = env_file.read_text().splitlines()
+                )
-            updated = False
+                print(f"  URL: {result.url}")
-            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")
 
-        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])))

server/tests/test_dag_zulip.py

@@ -0,0 +1,536 @@
+"""
+Tests for Hatchet DAG Status -> Zulip Live Updates.
+
+Tests cover:
+- _dag_zulip_enabled() guard logic
+- create_dag_zulip_message: sends + stores message ID
+- update_dag_zulip_message: updates existing; noop when no message_id
+- delete_dag_zulip_message: deletes + clears; handles InvalidMessageError
+- delete_zulip_message: sends HTTP DELETE; raises on 400
+- with_error_handling integration: calls update after success + failure
+"""
+
+from unittest.mock import AsyncMock, MagicMock, patch
+
+import pytest
+
+from reflector.db.transcripts import Transcript
+
+
+@pytest.fixture
+def dag_settings():
+    """Patch settings for DAG Zulip tests."""
+    with patch("reflector.hatchet.dag_zulip.settings") as mock_settings:
+        mock_settings.ZULIP_REALM = "zulip.example.com"
+        mock_settings.ZULIP_DAG_STREAM = "dag-stream"
+        mock_settings.ZULIP_DAG_TOPIC = "dag-topic"
+        mock_settings.ZULIP_BOT_EMAIL = "bot@example.com"
+        mock_settings.ZULIP_API_KEY = "fake-key"
+        yield mock_settings
+
+
+@pytest.fixture
+def dag_settings_disabled():
+    """Patch settings with DAG Zulip disabled."""
+    with patch("reflector.hatchet.dag_zulip.settings") as mock_settings:
+        mock_settings.ZULIP_REALM = "zulip.example.com"
+        mock_settings.ZULIP_DAG_STREAM = None
+        mock_settings.ZULIP_DAG_TOPIC = None
+        yield mock_settings
+
+
+@pytest.fixture
+def mock_transcript():
+    return Transcript(
+        id="test-transcript-id",
+        name="Test",
+        status="processing",
+        source_kind="room",
+        zulip_message_id=None,
+    )
+
+
+@pytest.fixture
+def mock_transcript_with_zulip_id():
+    return Transcript(
+        id="test-transcript-id",
+        name="Test",
+        status="processing",
+        source_kind="room",
+        zulip_message_id=42,
+    )
+
+
+class TestDagZulipEnabled:
+    def test_enabled_when_all_set(self, dag_settings):
+        from reflector.hatchet.dag_zulip import _dag_zulip_enabled
+
+        assert _dag_zulip_enabled() is True
+
+    def test_disabled_when_realm_missing(self, dag_settings):
+        dag_settings.ZULIP_REALM = None
+        from reflector.hatchet.dag_zulip import _dag_zulip_enabled
+
+        assert _dag_zulip_enabled() is False
+
+    def test_disabled_when_stream_missing(self, dag_settings):
+        dag_settings.ZULIP_DAG_STREAM = None
+        from reflector.hatchet.dag_zulip import _dag_zulip_enabled
+
+        assert _dag_zulip_enabled() is False
+
+    def test_disabled_when_topic_missing(self, dag_settings):
+        dag_settings.ZULIP_DAG_TOPIC = None
+        from reflector.hatchet.dag_zulip import _dag_zulip_enabled
+
+        assert _dag_zulip_enabled() is False
+
+
+@pytest.mark.usefixtures("setup_database")
+@pytest.mark.asyncio
+class TestCreateDagZulipMessage:
+    async def test_sends_and_stores_message_id(self, dag_settings, mock_transcript):
+        mock_run_details = MagicMock()
+        rendered_md = "**DAG** rendered"
+
+        with (
+            patch(
+                "reflector.hatchet.client.HatchetClientManager.get_client"
+            ) as mock_get_client,
+            patch(
+                "reflector.tools.render_hatchet_run.render_run_detail",
+                return_value=rendered_md,
+            ),
+            patch(
+                "reflector.zulip.send_message_to_zulip",
+                new_callable=AsyncMock,
+                return_value={"id": 99},
+            ) as mock_send,
+            patch(
+                "reflector.db.transcripts.transcripts_controller.get_by_id",
+                new_callable=AsyncMock,
+                return_value=mock_transcript,
+            ),
+            patch(
+                "reflector.db.transcripts.transcripts_controller.update",
+                new_callable=AsyncMock,
+            ) as mock_update,
+        ):
+            mock_client = MagicMock()
+            mock_client.runs.aio_get = AsyncMock(return_value=mock_run_details)
+            mock_get_client.return_value = mock_client
+
+            from reflector.hatchet.dag_zulip import create_dag_zulip_message
+
+            await create_dag_zulip_message("test-transcript-id", "workflow-run-123")
+
+            mock_send.assert_called_once_with("dag-stream", "dag-topic", rendered_md)
+            mock_update.assert_called_once_with(
+                mock_transcript, {"zulip_message_id": 99}
+            )
+
+    async def test_noop_when_disabled(self, dag_settings_disabled):
+        with patch(
+            "reflector.zulip.send_message_to_zulip",
+            new_callable=AsyncMock,
+        ) as mock_send:
+            from reflector.hatchet.dag_zulip import create_dag_zulip_message
+
+            await create_dag_zulip_message("test-transcript-id", "workflow-run-123")
+            mock_send.assert_not_called()
+
+    async def test_logs_warning_on_failure(self, dag_settings, mock_transcript):
+        with (
+            patch(
+                "reflector.hatchet.client.HatchetClientManager.get_client"
+            ) as mock_get_client,
+            patch(
+                "reflector.tools.render_hatchet_run.render_run_detail",
+                return_value="rendered",
+            ),
+            patch(
+                "reflector.zulip.send_message_to_zulip",
+                new_callable=AsyncMock,
+                side_effect=Exception("Zulip down"),
+            ),
+            patch(
+                "reflector.db.transcripts.transcripts_controller.get_by_id",
+                new_callable=AsyncMock,
+                return_value=mock_transcript,
+            ),
+            patch("reflector.hatchet.dag_zulip.logger") as mock_logger,
+        ):
+            mock_client = MagicMock()
+            mock_client.runs.aio_get = AsyncMock(return_value=MagicMock())
+            mock_get_client.return_value = mock_client
+
+            from reflector.hatchet.dag_zulip import create_dag_zulip_message
+
+            # Should not raise
+            await create_dag_zulip_message("test-transcript-id", "workflow-run-123")
+            mock_logger.warning.assert_called()
+
+
+@pytest.mark.usefixtures("setup_database")
+@pytest.mark.asyncio
+class TestUpdateDagZulipMessage:
+    async def test_updates_existing_message(
+        self, dag_settings, mock_transcript_with_zulip_id
+    ):
+        mock_run_details = MagicMock()
+        rendered_md = "**DAG** updated"
+
+        with (
+            patch(
+                "reflector.hatchet.client.HatchetClientManager.get_client"
+            ) as mock_get_client,
+            patch(
+                "reflector.tools.render_hatchet_run.render_run_detail",
+                return_value=rendered_md,
+            ),
+            patch(
+                "reflector.zulip.update_zulip_message",
+                new_callable=AsyncMock,
+            ) as mock_update,
+            patch(
+                "reflector.db.transcripts.transcripts_controller.get_by_id",
+                new_callable=AsyncMock,
+                return_value=mock_transcript_with_zulip_id,
+            ),
+            patch(
+                "reflector.hatchet.workflows.daily_multitrack_pipeline.fresh_db_connection"
+            ) as mock_fresh_db,
+        ):
+            mock_client = MagicMock()
+            mock_client.runs.aio_get = AsyncMock(return_value=mock_run_details)
+            mock_get_client.return_value = mock_client
+            mock_fresh_db.return_value.__aenter__ = AsyncMock()
+            mock_fresh_db.return_value.__aexit__ = AsyncMock(return_value=False)
+
+            from reflector.hatchet.dag_zulip import update_dag_zulip_message
+
+            await update_dag_zulip_message("test-transcript-id", "workflow-run-123")
+
+            mock_update.assert_called_once_with(
+                42, "dag-stream", "dag-topic", rendered_md
+            )
+
+    async def test_appends_error_banner(
+        self, dag_settings, mock_transcript_with_zulip_id
+    ):
+        mock_run_details = MagicMock()
+        rendered_md = "**DAG** updated"
+
+        with (
+            patch(
+                "reflector.hatchet.client.HatchetClientManager.get_client"
+            ) as mock_get_client,
+            patch(
+                "reflector.tools.render_hatchet_run.render_run_detail",
+                return_value=rendered_md,
+            ),
+            patch(
+                "reflector.zulip.update_zulip_message",
+                new_callable=AsyncMock,
+            ) as mock_update,
+            patch(
+                "reflector.db.transcripts.transcripts_controller.get_by_id",
+                new_callable=AsyncMock,
+                return_value=mock_transcript_with_zulip_id,
+            ),
+            patch(
+                "reflector.hatchet.workflows.daily_multitrack_pipeline.fresh_db_connection"
+            ) as mock_fresh_db,
+        ):
+            mock_client = MagicMock()
+            mock_client.runs.aio_get = AsyncMock(return_value=mock_run_details)
+            mock_get_client.return_value = mock_client
+            mock_fresh_db.return_value.__aenter__ = AsyncMock()
+            mock_fresh_db.return_value.__aexit__ = AsyncMock(return_value=False)
+
+            from reflector.hatchet.dag_zulip import update_dag_zulip_message
+
+            await update_dag_zulip_message(
+                "test-transcript-id",
+                "workflow-run-123",
+                error_message="get_recording failed: connection timeout",
+            )
+
+            call_args = mock_update.call_args
+            content = call_args[0][3]
+            assert rendered_md in content
+            assert "get_recording failed: connection timeout" in content
+
+    async def test_noop_when_no_message_id(self, dag_settings, mock_transcript):
+        with (
+            patch(
+                "reflector.zulip.update_zulip_message",
+                new_callable=AsyncMock,
+            ) as mock_update,
+            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"
+            ) as mock_fresh_db,
+        ):
+            mock_fresh_db.return_value.__aenter__ = AsyncMock()
+            mock_fresh_db.return_value.__aexit__ = AsyncMock(return_value=False)
+
+            from reflector.hatchet.dag_zulip import update_dag_zulip_message
+
+            await update_dag_zulip_message("test-transcript-id", "workflow-run-123")
+            mock_update.assert_not_called()
+
+    async def test_noop_when_disabled(self, dag_settings_disabled):
+        with patch(
+            "reflector.zulip.update_zulip_message",
+            new_callable=AsyncMock,
+        ) as mock_update:
+            from reflector.hatchet.dag_zulip import update_dag_zulip_message
+
+            await update_dag_zulip_message("test-transcript-id", "workflow-run-123")
+            mock_update.assert_not_called()
+
+
+@pytest.mark.usefixtures("setup_database")
+@pytest.mark.asyncio
+class TestDeleteDagZulipMessage:
+    async def test_deletes_and_clears(
+        self, dag_settings, mock_transcript_with_zulip_id
+    ):
+        with (
+            patch(
+                "reflector.zulip.delete_zulip_message",
+                new_callable=AsyncMock,
+            ) as mock_delete,
+            patch(
+                "reflector.db.transcripts.transcripts_controller.get_by_id",
+                new_callable=AsyncMock,
+                return_value=mock_transcript_with_zulip_id,
+            ),
+            patch(
+                "reflector.db.transcripts.transcripts_controller.update",
+                new_callable=AsyncMock,
+            ) as mock_tc_update,
+        ):
+            from reflector.hatchet.dag_zulip import delete_dag_zulip_message
+
+            await delete_dag_zulip_message("test-transcript-id")
+
+            mock_delete.assert_called_once_with(42)
+            mock_tc_update.assert_called_once_with(
+                mock_transcript_with_zulip_id, {"zulip_message_id": None}
+            )
+
+    async def test_noop_when_no_message_id(self, dag_settings, mock_transcript):
+        with (
+            patch(
+                "reflector.zulip.delete_zulip_message",
+                new_callable=AsyncMock,
+            ) as mock_delete,
+            patch(
+                "reflector.db.transcripts.transcripts_controller.get_by_id",
+                new_callable=AsyncMock,
+                return_value=mock_transcript,
+            ),
+        ):
+            from reflector.hatchet.dag_zulip import delete_dag_zulip_message
+
+            await delete_dag_zulip_message("test-transcript-id")
+            mock_delete.assert_not_called()
+
+    async def test_handles_invalid_message_error(
+        self, dag_settings, mock_transcript_with_zulip_id
+    ):
+        from reflector.zulip import InvalidMessageError
+
+        with (
+            patch(
+                "reflector.zulip.delete_zulip_message",
+                new_callable=AsyncMock,
+                side_effect=InvalidMessageError("gone"),
+            ),
+            patch(
+                "reflector.db.transcripts.transcripts_controller.get_by_id",
+                new_callable=AsyncMock,
+                return_value=mock_transcript_with_zulip_id,
+            ),
+            patch(
+                "reflector.db.transcripts.transcripts_controller.update",
+                new_callable=AsyncMock,
+            ) as mock_tc_update,
+            patch("reflector.hatchet.dag_zulip.logger"),
+        ):
+            from reflector.hatchet.dag_zulip import delete_dag_zulip_message
+
+            # Should not raise; should still clear the message_id
+            await delete_dag_zulip_message("test-transcript-id")
+            mock_tc_update.assert_called_once_with(
+                mock_transcript_with_zulip_id, {"zulip_message_id": None}
+            )
+
+    async def test_noop_when_disabled(self, dag_settings_disabled):
+        with patch(
+            "reflector.zulip.delete_zulip_message",
+            new_callable=AsyncMock,
+        ) as mock_delete:
+            from reflector.hatchet.dag_zulip import delete_dag_zulip_message
+
+            await delete_dag_zulip_message("test-transcript-id")
+            mock_delete.assert_not_called()
+
+
+@pytest.mark.asyncio
+class TestDeleteZulipMessage:
+    async def test_sends_delete_request(self):
+        mock_response = MagicMock()
+        mock_response.status_code = 200
+        mock_response.raise_for_status = MagicMock()
+        mock_response.json.return_value = {"result": "success"}
+
+        mock_client = AsyncMock()
+        mock_client.delete = AsyncMock(return_value=mock_response)
+        mock_client.__aenter__ = AsyncMock(return_value=mock_client)
+        mock_client.__aexit__ = AsyncMock(return_value=False)
+
+        with patch("reflector.zulip.httpx.AsyncClient", return_value=mock_client):
+            with patch("reflector.zulip.settings") as mock_settings:
+                mock_settings.ZULIP_REALM = "zulip.example.com"
+                mock_settings.ZULIP_BOT_EMAIL = "bot@example.com"
+                mock_settings.ZULIP_API_KEY = "fake-key"
+
+                from reflector.zulip import delete_zulip_message
+
+                result = await delete_zulip_message(123)
+                assert result == {"result": "success"}
+
+                mock_client.delete.assert_called_once()
+                call_args = mock_client.delete.call_args
+                assert "123" in call_args.args[0]
+
+    async def test_raises_invalid_message_on_400(self):
+        from reflector.zulip import InvalidMessageError
+
+        mock_response = MagicMock()
+        mock_response.status_code = 400
+        mock_response.json.return_value = {"msg": "Invalid message(s)"}
+
+        mock_client = AsyncMock()
+        mock_client.delete = AsyncMock(return_value=mock_response)
+        mock_client.__aenter__ = AsyncMock(return_value=mock_client)
+        mock_client.__aexit__ = AsyncMock(return_value=False)
+
+        with patch("reflector.zulip.httpx.AsyncClient", return_value=mock_client):
+            with patch("reflector.zulip.settings") as mock_settings:
+                mock_settings.ZULIP_REALM = "zulip.example.com"
+                mock_settings.ZULIP_BOT_EMAIL = "bot@example.com"
+                mock_settings.ZULIP_API_KEY = "fake-key"
+
+                from reflector.zulip import delete_zulip_message
+
+                with pytest.raises(InvalidMessageError):
+                    await delete_zulip_message(999)
+
+
+@pytest.mark.asyncio
+class TestWithErrorHandlingDagUpdate:
+    """Test that with_error_handling calls update_dag_zulip_message."""
+
+    async def test_calls_update_on_success(self):
+        from reflector.hatchet.constants import TaskName
+        from reflector.hatchet.workflows.daily_multitrack_pipeline import (
+            PipelineInput,
+            with_error_handling,
+        )
+
+        mock_ctx = MagicMock()
+        mock_ctx.workflow_run_id = "wfr-123"
+
+        input_data = PipelineInput(
+            recording_id="rec-1",
+            tracks=[{"s3_key": "k"}],
+            bucket_name="bucket",
+            transcript_id="tid-1",
+        )
+
+        @with_error_handling(TaskName.GET_RECORDING)
+        async def fake_task(input: PipelineInput, ctx) -> str:
+            return "ok"
+
+        with patch(
+            "reflector.hatchet.workflows.daily_multitrack_pipeline.update_dag_zulip_message",
+            new_callable=AsyncMock,
+        ) as mock_update:
+            result = await fake_task(input_data, mock_ctx)
+            assert result == "ok"
+            mock_update.assert_called_once_with("tid-1", "wfr-123")
+
+    async def test_calls_update_on_failure_with_error_message(self):
+        from reflector.hatchet.constants import TaskName
+        from reflector.hatchet.workflows.daily_multitrack_pipeline import (
+            PipelineInput,
+            with_error_handling,
+        )
+
+        mock_ctx = MagicMock()
+        mock_ctx.workflow_run_id = "wfr-123"
+
+        input_data = PipelineInput(
+            recording_id="rec-1",
+            tracks=[{"s3_key": "k"}],
+            bucket_name="bucket",
+            transcript_id="tid-1",
+        )
+
+        @with_error_handling(TaskName.GET_RECORDING)
+        async def failing_task(input: PipelineInput, ctx) -> str:
+            raise ValueError("boom")
+
+        with (
+            patch(
+                "reflector.hatchet.workflows.daily_multitrack_pipeline.update_dag_zulip_message",
+                new_callable=AsyncMock,
+            ) as mock_update,
+            patch(
+                "reflector.hatchet.workflows.daily_multitrack_pipeline.set_workflow_error_status",
+                new_callable=AsyncMock,
+            ),
+        ):
+            with pytest.raises(ValueError, match="boom"):
+                await failing_task(input_data, mock_ctx)
+            mock_update.assert_called_once_with(
+                "tid-1", "wfr-123", error_message="get_recording failed: boom"
+            )
+
+    async def test_dag_failure_doesnt_affect_task(self):
+        """DAG update failure should not prevent task from succeeding."""
+        from reflector.hatchet.constants import TaskName
+        from reflector.hatchet.workflows.daily_multitrack_pipeline import (
+            PipelineInput,
+            with_error_handling,
+        )
+
+        mock_ctx = MagicMock()
+        mock_ctx.workflow_run_id = "wfr-123"
+
+        input_data = PipelineInput(
+            recording_id="rec-1",
+            tracks=[{"s3_key": "k"}],
+            bucket_name="bucket",
+            transcript_id="tid-1",
+        )
+
+        @with_error_handling(TaskName.GET_RECORDING)
+        async def ok_task(input: PipelineInput, ctx) -> str:
+            return "ok"
+
+        with patch(
+            "reflector.hatchet.workflows.daily_multitrack_pipeline.update_dag_zulip_message",
+            new_callable=AsyncMock,
+            side_effect=Exception("zulip exploded"),
+        ):
+            result = await ok_task(input_data, mock_ctx)
+            assert result == "ok"

server/tests/test_hatchet_dispatch.py

@@ -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():

server/tests/test_storage.py

@@ -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

server/uv.lock

@@ -235,6 +235,12 @@ wheels = [
     { url = "https://files.pythonhosted.org/packages/78/b6/6307fbef88d9b5ee7421e68d78a9f162e0da4900bc5f5793f6d3d0e34fb8/annotated_types-0.7.0-py3-none-any.whl", hash = "sha256:1f02e8b43a8fbbc3f3e0d4f0f4bfc8131bcb4eebe8849b8e5c773f3a1c582a53", size = 13643 },
 ]
 
+[[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 }
+
 [[package]]
 name = "anyio"
 version = "4.9.0"
@@ -261,6 +267,21 @@ wheels = [
     { url = "https://files.pythonhosted.org/packages/2f/f5/c36551e93acba41a59939ae6a0fb77ddb3f2e8e8caa716410c65f7341f72/asgi_lifespan-2.1.0-py3-none-any.whl", hash = "sha256:ed840706680e28428c01e14afb3875d7d76d3206f3d5b2f2294e059b5c23804f", size = 10895 },
 ]
 
+[[package]]
+name = "asteroid-filterbanks"
+version = "0.4.0"
+source = { registry = "https://pypi.org/simple" }
+dependencies = [
+    { name = "numpy" },
+    { 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 = "typing-extensions" },
+]
+sdist = { url = "https://files.pythonhosted.org/packages/90/fa/5c2be1f96dc179f83cdd3bb267edbd1f47d08f756785c016d5c2163901a7/asteroid-filterbanks-0.4.0.tar.gz", hash = "sha256:415f89d1dcf2b13b35f03f7a9370968ac4e6fa6800633c522dac992b283409b9", size = 24599 }
+wheels = [
+    { url = "https://files.pythonhosted.org/packages/c5/7c/83ff6046176a675e6a1e8aeefed8892cd97fe7c46af93cc540d1b24b8323/asteroid_filterbanks-0.4.0-py3-none-any.whl", hash = "sha256:4932ac8b6acc6e08fb87cbe8ece84215b5a74eee284fe83acf3540a72a02eaf5", size = 29912 },
+]
+
 [[package]]
 name = "async-timeout"
 version = "5.0.1"
@@ -582,6 +603,56 @@ wheels = [
     { url = "https://files.pythonhosted.org/packages/a7/06/3d6badcf13db419e25b07041d9c7b4a2c331d3f4e7134445ec5df57714cd/coloredlogs-15.0.1-py2.py3-none-any.whl", hash = "sha256:612ee75c546f53e92e70049c9dbfcc18c935a2b9a53b66085ce9ef6a6e5c0934", size = 46018 },
 ]
 
+[[package]]
+name = "colorlog"
+version = "6.9.0"
+source = { registry = "https://pypi.org/simple" }
+dependencies = [
+    { name = "colorama", marker = "sys_platform == 'win32'" },
+]
+sdist = { url = "https://files.pythonhosted.org/packages/d3/7a/359f4d5df2353f26172b3cc39ea32daa39af8de522205f512f458923e677/colorlog-6.9.0.tar.gz", hash = "sha256:bfba54a1b93b94f54e1f4fe48395725a3d92fd2a4af702f6bd70946bdc0c6ac2", size = 16624 }
+wheels = [
+    { url = "https://files.pythonhosted.org/packages/e3/51/9b208e85196941db2f0654ad0357ca6388ab3ed67efdbfc799f35d1f83aa/colorlog-6.9.0-py3-none-any.whl", hash = "sha256:5906e71acd67cb07a71e779c47c4bcb45fb8c2993eebe9e5adcd6a6f1b283eff", size = 11424 },
+]
+
+[[package]]
+name = "contourpy"
+version = "1.3.3"
+source = { registry = "https://pypi.org/simple" }
+dependencies = [
+    { name = "numpy" },
+]
+sdist = { url = "https://files.pythonhosted.org/packages/58/01/1253e6698a07380cd31a736d248a3f2a50a7c88779a1813da27503cadc2a/contourpy-1.3.3.tar.gz", hash = "sha256:083e12155b210502d0bca491432bb04d56dc3432f95a979b429f2848c3dbe880", size = 13466174 }
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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'" },
+    { 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')" },
+    { name = "tqdm" },
+]
+sdist = { url = "https://files.pythonhosted.org/packages/ab/10/87e666544a4e0cec7cbdc09f26948994831ae0f8bbc58de3bf53b68285ff/speechbrain-1.0.3.tar.gz", hash = "sha256:fcab3c6e90012cecb1eed40ea235733b550137e73da6bfa2340ba191ec714052", size = 747735 }
+wheels = [
+    { url = "https://files.pythonhosted.org/packages/58/13/e61f1085aebee17d5fc2df19fcc5177c10379be52578afbecdd615a831c9/speechbrain-1.0.3-py3-none-any.whl", hash = "sha256:9859d4c1b1fb3af3b85523c0c89f52e45a04f305622ed55f31aa32dd2fba19e9", size = 864091 },
+]
+
 [[package]]
 name = "sqlalchemy"
 version = "1.4.54"
@@ -3291,6 +3883,15 @@ wheels = [
     { url = "https://files.pythonhosted.org/packages/a2/09/77d55d46fd61b4a135c444fc97158ef34a095e5681d0a6c10b75bf356191/sympy-1.14.0-py3-none-any.whl", hash = "sha256:e091cc3e99d2141a0ba2847328f5479b05d94a6635cb96148ccb3f34671bd8f5", size = 6299353 },
 ]
 
+[[package]]
+name = "tabulate"
+version = "0.9.0"
+source = { registry = "https://pypi.org/simple" }
+sdist = { url = "https://files.pythonhosted.org/packages/ec/fe/802052aecb21e3797b8f7902564ab6ea0d60ff8ca23952079064155d1ae1/tabulate-0.9.0.tar.gz", hash = "sha256:0095b12bf5966de529c0feb1fa08671671b3368eec77d7ef7ab114be2c068b3c", size = 81090 }
+wheels = [
+    { url = "https://files.pythonhosted.org/packages/40/44/4a5f08c96eb108af5cb50b41f76142f0afa346dfa99d5296fe7202a11854/tabulate-0.9.0-py3-none-any.whl", hash = "sha256:024ca478df22e9340661486f85298cff5f6dcdba14f3813e8830015b9ed1948f", size = 35252 },
+]
+
 [[package]]
 name = "tenacity"
 version = "9.1.2"
@@ -3300,6 +3901,29 @@ wheels = [
     { 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 }
+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"

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

@@ -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;

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

@@ -23,16 +23,7 @@ const useWebRTC = (
     let p: Peer;
 
     try {
-      p = new Peer({
+      p = new Peer({ initiator: true, stream: stream });
-        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;

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

@@ -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();
             }