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Author SHA1 Message Date
2ba0d965e8 chore(main): release 0.34.0 (#859) 2026-02-20 12:09:39 -06:00
527a069ba9 fix: remove max_tokens cap to support thinking models (Kimi-K2.5) (#869)
* fix: remove max_tokens cap to support thinking models (Kimi-K2.5)

Thinking/reasoning models like Kimi-K2.5 use output tokens for internal
chain-of-thought before generating the visible response. When max_tokens
was set (500 or 2048), the thinking budget consumed all available tokens,
leaving an empty response — causing TreeSummarize to return '' and
crashing the topic detection retry workflow.

Set max_tokens default to None so the model controls its own output
budget, allowing thinking models to complete both reasoning and response.

Also fix process.py CLI tool to import the Celery worker app before
dispatching tasks, ensuring the Redis broker config is used instead of
Celery's default AMQP transport.

* fix: remove max_tokens=200 cap from final title processor

Same thinking model issue — 200 tokens is especially tight and would be
entirely consumed by chain-of-thought reasoning, producing an empty title.

* Update server/reflector/tools/process.py

Co-authored-by: pr-agent-monadical[bot] <198624643+pr-agent-monadical[bot]@users.noreply.github.com>

* fix: remove max_tokens=500 cap from topic detector processor

Same thinking model fix — this is the original callsite that was failing
with Kimi-K2.5, producing empty TreeSummarize responses.

---------

Co-authored-by: pr-agent-monadical[bot] <198624643+pr-agent-monadical[bot]@users.noreply.github.com>
2026-02-20 12:07:34 -06:00
d4cc6be1fe feat: add change_seq to transcripts for ingestion support (#868)
* feat: add change_seq to transcripts for ingestion support

Add a monotonically increasing change_seq column to the transcript table,
backed by a PostgreSQL sequence and BEFORE INSERT OR UPDATE trigger. Every
mutation gets a new sequence value, letting external ingesters checkpoint
and never miss an update.

* chore: regenerate frontend API types
2026-02-20 10:12:05 -06:00
Juan Diego García
cdd974b935 chore: create script for selfhosted reflector (#866)
* self hosted with self gpu

* add optional ollama model

* garage ports

* exposes ports and changes curl

* custom domain

* try to fix wroker

* build locallly

* documentation

* docs format

* precommit
2026-02-19 15:11:45 -05:00
Sergey Mankovsky
a8ad237d85 fix: standalone on ubuntu (#865)
* Standalone on ubuntu

* fix: use port 3043 for Caddy, disable rooms, remove dead Caddyfile

- Caddy mapped to host port 3043 instead of 80/443 to avoid conflicts
- FEATURE_ROOMS=false in standalone web service
- Removed scripts/standalone/Caddyfile (dead code on this branch)
- Updated all URLs, port checks, docs to reference :3043

---------

Co-authored-by: Igor Loskutov <igor.loskutoff@gmail.com>
2026-02-13 18:27:21 -05:00
9dbf155be4 feat: remove network_mode host for standalone WebRTC (#864)
* feat: remove network_mode host for standalone by fixing WebRTC port range and ICE candidates

aioice hardcodes bind(addr, 0) for ICE UDP sockets, making port mapping
impossible in Docker bridge networking. This adds two env-var-gated
mechanisms to replace network_mode: host:

1. WEBRTC_PORT_RANGE (e.g. "50000-50100"): monkey-patches aioice to bind
   UDP sockets within a known range, so they can be mapped in Docker.

2. WEBRTC_HOST (e.g. "host.docker.internal"): rewrites container-internal
   IPs in SDP answers with the Docker host's real IP, so LAN clients can
   reach the ICE candidates.

Both default to None — no effect on existing deployments.

* fix: do not attempt sidecar to detect host ip, use the standalone script to figure out the external ip and use it

* style: reformat

---------

Co-authored-by: tito <tito@titos-Mac-Studio.local>
2026-02-13 15:59:12 -05:00
7f2a4013cb feat: add Caddy reverse proxy with auto HTTPS for LAN access and auto-derive WebSocket URL (#863)
* feat: add Caddy reverse proxy with auto HTTPS for LAN access and auto-derive WebSocket URL

Add a Caddy service to docker-compose.standalone.yml that provides automatic
HTTPS with local certificates, enabling secure access to both the frontend
and API from the local network through a single entrypoint.

Backend changes:
- Add ROOT_PATH setting to FastAPI so the API can be served under /api prefix
- Route frontend and API (/server-api) through Caddy reverse proxy

Frontend changes:
- Support WEBSOCKET_URL=auto to derive the WebSocket URL from API_URL
  automatically, using the page protocol (http→ws, https→wss) and host
- Make WEBSOCKET_URL env var optional instead of required

* style: pre-commit

* fix: make standalone compose self-contained (drop !reset dependency)

docker-compose.standalone.yml used !reset YAML tags to clear
network_mode and volumes from the base compose. !reset requires
Compose v2.24+ and breaks on Colima + brew-installed compose.

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

Update setup-standalone.sh compose_cmd() to use only the standalone
file instead of both files.

* fix: update standalone docs to match self-contained compose usage

---------

Co-authored-by: Igor Loskutov <igor.loskutoff@gmail.com>
2026-02-13 15:21:43 -05:00
Igor Loskutov
14a8b5808e fix: check for Docker BuildKit (buildx) before building images
Dockerfiles use RUN --mount for caching which requires BuildKit.
Colima and bare Docker Engine installs don't bundle docker-buildx.
2026-02-12 18:57:32 -05:00
Igor Loskutov
e57c6186f9 fix: check compose version output, not just exit code
Without the plugin, `docker compose version` can still exit 0
by falling through to `docker version`. Grep for "Compose" in
the output to reliably detect the plugin.
2026-02-12 18:32:16 -05:00
Igor Loskutov
36a8daee61 fix: check for Docker Compose plugin before running standalone setup
Without the compose plugin, `docker compose -f ...` produces a
misleading "unknown shorthand flag: 'f'" error instead of telling
the user compose is missing.
2026-02-12 18:24:24 -05:00
Igor Loskutov
3d13e5d42f fix: auto-rebuild standalone images and blank Hatchet vars
- Add rebuild_images() to setup-standalone.sh that runs `compose build`
  before `up -d`, with image hash comparison to log whether each service
  was rebuilt or unchanged
- Blank HATCHET_CLIENT_SERVER_URL/HOST_PORT in standalone compose since
  Hatchet is not started (localhost URLs break after network_mode:host removal)
- Fix grep -qx -> -qxF for ollama model matching (dots in model names)
2026-02-12 18:21:09 -05:00
Igor Loskutov
695f3c4928 fix: standalone server networking and setup diagnostics
Replace network_mode:host with standard compose networking for macOS
Docker Desktop compatibility. Add dump_diagnostics() for automatic
failure debugging and docker-exec-based server health checks.
2026-02-12 17:46:00 -05:00
5bca92510a feat: standalone frontend uses production build instead of dev server (#862)
* feat: standalone frontend uses production build instead of dev server

Override web service in docker-compose.standalone.yml to build from
www/Dockerfile (multi-stage: deps → build → standalone runner) instead
of running pnpm dev with bind-mounted source.

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

* fix: add required env vars for standalone production frontend

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

---------

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

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

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

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

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

* feat: type-safe WebSocket events via OpenAPI stub

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

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

* fix: restore TOPIC WS handler with immediate state update

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

* fix: align TOPIC WS event data with GetTranscriptTopic shape

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

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

---------

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

- Add setup script (scripts/setup-local-llm.sh) for one-command Ollama setup
  Mac: native Metal GPU, Linux: containerized via docker-compose profiles
- Add ollama-gpu and ollama-cpu docker-compose profiles for Linux
- Add extra_hosts to server/hatchet-worker-llm for host.docker.internal
- Pass response_format JSON schema in StructuredOutputWorkflow.extract()
  enabling grammar-based constrained decoding on Ollama/llama.cpp/vLLM/OpenAI
- Update .env.example with Ollama as default LLM option
- Add Ollama PRD and local dev setup docs

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

Ollama profiles (ollama-gpu, ollama-cpu) are only for Linux standalone
deployment. Mac devs never use them. Separate file keeps the main
compose clean and provides a natural home for future standalone services
(MinIO, etc.).

Linux: docker compose -f docker-compose.yml -f docker-compose.standalone.yml --profile ollama-gpu up -d
Mac: docker compose up -d (native Ollama, no standalone file needed)

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

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

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

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

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

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

Single script takes fresh clone to working Reflector: Ollama/LLM setup,
env file generation (server/.env + www/.env.local), docker compose up,
health checks. No Hatchet in standalone — live pipeline is pure Celery.

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

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

Add TRANSCRIPT_STORAGE_AWS_ENDPOINT_URL setting to enable S3-compatible
backends (Garage, MinIO). When set, uses path-style addressing and
routes all requests to the custom endpoint. When unset, AWS behavior
is unchanged.

- AwsStorage: accept aws_endpoint_url, pass to all 6 session.client()
  calls, configure path-style addressing and base_url
- Fix 4 direct AwsStorage constructions in Hatchet workflows to pass
  endpoint_url (would have silently targeted wrong endpoint)
- Standalone: add Garage service to docker-compose.standalone.yml,
  setup script initializes layout/bucket/key and writes credentials
- Fix compose_cmd() bug: Mac path was missing standalone yml
- garage.toml template with runtime secret generation via openssl

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

- garage.toml: fix rpc_secret field name (was secret_transmitter),
  move to top-level per Garage v1.1.0 spec, remove unused [s3_web]
- setup-standalone.sh: resolve symlinked .env files before writing,
  always ensure all standalone-critical vars via env_set,
  fix garage key create/info syntax (positional arg, not --name),
  avoid overwriting key secret with "(redacted)" on re-run,
  use compose_cmd in health check
- docker-compose.standalone.yml: fix garage healthcheck (no curl in
  image, use /garage stats instead)

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

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

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

* fix: invalidate transcript query on STATUS websocket event

Without this, the processing page never redirects after completion
because the redirect logic watches the REST query data, not the
WebSocket status state.

Cherry-picked from feat-dag-progress (faec509a).

* fix: local env setup (#855)

* Ensure rate limit

* Increase nextjs compilation speed

* Fix daily no content handling

* Simplify daily webhook creation

* Fix webhook request validation

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

* feat: add local pyannote file diarization processor

Enables file diarization without Modal by using pyannote.audio locally.
Downloads model bundle from S3 on first use, caches locally, patches
config to use local paths. Set DIARIZATION_BACKEND=pyannote to enable.

* fix: standalone setup enables pyannote diarization and public mode

Replace DIARIZATION_ENABLED=false with DIARIZATION_BACKEND=pyannote so
file uploads get speaker diarization out of the box. Add PUBLIC_MODE=true
so unauthenticated users can list/browse transcripts.

* fix: touch env files before first compose_cmd in standalone setup

docker-compose.yml references www/.env.local as env_file, but the
setup script only creates it in step 4. compose_cmd calls in step 3
(Garage) fail on a fresh clone when the file doesn't exist yet.

* feat: standalone uses self-hosted GPU service for transcription+diarization

Replace in-process pyannote approach with self-hosted gpu/self_hosted/ service.
Same HTTP API as Modal — just TRANSCRIPT_URL/DIARIZATION_URL point to local container.

- Add gpu/self_hosted/Dockerfile.cpu (GPU Dockerfile minus NVIDIA CUDA)
- Add S3 model bundle fallback in diarizer.py when HF_TOKEN not set
- Add gpu service to docker-compose.standalone.yml with compose env overrides
- Fix /browse empty in PUBLIC_MODE (search+list queries filtered out roomless transcripts)
- Remove audio_diarization_pyannote.py, file_diarization_pyannote.py and tests
- Remove pyannote-audio from server local deps

* fix: allow unauthenticated GPU requests when no API key configured

OAuth2PasswordBearer with auto_error=True rejects requests without
Authorization header before apikey_auth can check if auth is needed.

* fix: rename standalone gpu service to cpu to match Dockerfile.cpu usage

* docs: add programmatic testing section and fix gpu->cpu naming in setup script/docs

- Add "Testing programmatically" section to standalone docs with curl commands
  for creating transcript, uploading audio, polling status, checking result
- Fix setup-standalone.sh to reference `cpu` service (was still `gpu` after rename)
- Update all docs references from gpu to cpu service naming

---------

Co-authored-by: Igor Loskutov <igor.loskutoff@gmail.com>

* Fix websocket disconnect errors

* Fix event loop is closed in Celery workers

* Allow reprocessing idle multitrack transcripts

* feat: add local pyannote file diarization processor

Enables file diarization without Modal by using pyannote.audio locally.
Downloads model bundle from S3 on first use, caches locally, patches
config to use local paths. Set DIARIZATION_BACKEND=pyannote to enable.

* feat: standalone uses self-hosted GPU service for transcription+diarization

Replace in-process pyannote approach with self-hosted gpu/self_hosted/ service.
Same HTTP API as Modal — just TRANSCRIPT_URL/DIARIZATION_URL point to local container.

- Add gpu/self_hosted/Dockerfile.cpu (GPU Dockerfile minus NVIDIA CUDA)
- Add S3 model bundle fallback in diarizer.py when HF_TOKEN not set
- Add gpu service to docker-compose.standalone.yml with compose env overrides
- Fix /browse empty in PUBLIC_MODE (search+list queries filtered out roomless transcripts)
- Remove audio_diarization_pyannote.py, file_diarization_pyannote.py and tests
- Remove pyannote-audio from server local deps

* fix: set source_kind to FILE on audio file upload

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

* Add hatchet env vars

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

- Filter OrbStack/Docker Desktop PIDs from port conflict check (false positives on Mac)
- Check all infra ports (5432, 6379, 3900, 3903) not just app ports
- Fix ollama model detection to match on name column only
- Document OrbStack and cross-project port conflicts in troubleshooting

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

Three fixes for the processing page not redirecting when status becomes "ended":

- Add useWebSockets to processing page so it receives STATUS events
- Remove OAuth2PasswordBearer from auth_none — broke WebSocket endpoints (500)
- Reconnect stale Redis in ws_manager when Celery worker reuses dead event loop

* fix: mock Celery broker in idle transcript validation test

test_validation_idle_transcript_with_recording_allowed called
validate_transcript_for_processing without mocking
task_is_scheduled_or_active, which attempts a real Celery
broker connection (AMQP port 5672). Other tests in the same
file already mock this — apply the same pattern here.

* Enable server host mode

* Fix webrtc connection

* Remove turbopack

* fix: standalone GPU service connectivity with host network mode

Server runs with network_mode: host and can't resolve Docker service
names. Publish cpu port as 8100 on host, point server at localhost:8100.
Worker stays on bridge network using cpu:8000. Add dummy
TRANSCRIPT_MODAL_API_KEY since OpenAI SDK requires it even for local
endpoints.

---------

Co-authored-by: Igor Loskutov <igor.loskutoff@gmail.com>
Co-authored-by: Sergey Mankovsky <sergey@mankovsky.dev>
2026-02-11 18:20:36 -05:00
cd2255cfbc chore(main): release 0.33.0 (#847) 2026-02-06 18:12:06 -05:00
15ab2e306e feat: Daily+hatchet default (#846)
* feat: set Daily as default video platform

Daily.co has been battle-tested and is ready to be the default.
Whereby remains available for rooms that explicitly set it.

* feat: enforce Hatchet for all multitrack processing

Remove use_celery option from rooms - multitrack (Daily) recordings
now always use Hatchet workflows. Celery remains for single-track
(Whereby) file processing only.

- Remove use_celery column from room table
- Simplify dispatch logic to always use Hatchet for multitracks
- Update tests to mock Hatchet instead of Celery

* fix: update whereby test to patch Hatchet instead of removed Celery import

---------

Co-authored-by: Igor Loskutov <igor.loskutoff@gmail.com>
2026-02-05 18:38:08 -05:00
80 changed files with 5407 additions and 1925 deletions

2
.gitignore vendored
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@@ -23,3 +23,5 @@ www/.env.production
docs/pnpm-lock.yaml
.secrets
opencode.json
vibedocs/

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@@ -1,5 +1,40 @@
# Changelog
## [0.34.0](https://github.com/Monadical-SAS/reflector/compare/v0.33.0...v0.34.0) (2026-02-20)
### Features
* add Caddy reverse proxy with auto HTTPS for LAN access and auto-derive WebSocket URL ([#863](https://github.com/Monadical-SAS/reflector/issues/863)) ([7f2a401](https://github.com/Monadical-SAS/reflector/commit/7f2a4013cbb3d3ee3e76885f28d73331dcaf325c))
* add change_seq to transcripts for ingestion support ([#868](https://github.com/Monadical-SAS/reflector/issues/868)) ([d4cc6be](https://github.com/Monadical-SAS/reflector/commit/d4cc6be1fed56ea7fba06acb8d50c9de43b26b07))
* local llm support + standalone-script doc/draft ([#856](https://github.com/Monadical-SAS/reflector/issues/856)) ([b468427](https://github.com/Monadical-SAS/reflector/commit/b468427f1bb12634f5840990e9d64b2c145d7c1a))
* remove network_mode host for standalone WebRTC ([#864](https://github.com/Monadical-SAS/reflector/issues/864)) ([9dbf155](https://github.com/Monadical-SAS/reflector/commit/9dbf155be4de7c059035a75f90c7bf0845344b74))
* standalone frontend uses production build instead of dev server ([#862](https://github.com/Monadical-SAS/reflector/issues/862)) ([5bca925](https://github.com/Monadical-SAS/reflector/commit/5bca92510a5c33f8baeeaac2c346fb1978366ac8))
### Bug Fixes
* auto-rebuild standalone images and blank Hatchet vars ([3d13e5d](https://github.com/Monadical-SAS/reflector/commit/3d13e5d42fc53ce3c005841265ed1e8735a61518))
* check compose version output, not just exit code ([e57c618](https://github.com/Monadical-SAS/reflector/commit/e57c6186f92d66e4525786e56b018c08cf792d2f))
* check for Docker BuildKit (buildx) before building images ([14a8b58](https://github.com/Monadical-SAS/reflector/commit/14a8b5808e5aed860e55aaed35a0fdf8b2f4afa3))
* check for Docker Compose plugin before running standalone setup ([36a8dae](https://github.com/Monadical-SAS/reflector/commit/36a8daee61c2b7a0937fd0914d51fb4ea8212ae7))
* live flow real-time updates during processing ([#861](https://github.com/Monadical-SAS/reflector/issues/861)) ([972a52d](https://github.com/Monadical-SAS/reflector/commit/972a52d22f989f9e2c6f52362b3f1a4e17773663))
* remove max_tokens cap to support thinking models (Kimi-K2.5) ([#869](https://github.com/Monadical-SAS/reflector/issues/869)) ([527a069](https://github.com/Monadical-SAS/reflector/commit/527a069ba9eff6717ccd4bb1e839674edebffceb))
* standalone on ubuntu ([#865](https://github.com/Monadical-SAS/reflector/issues/865)) ([a8ad237](https://github.com/Monadical-SAS/reflector/commit/a8ad237d8571d5ef5c78fb4427c538592d6a7b43))
* standalone server networking and setup diagnostics ([695f3c4](https://github.com/Monadical-SAS/reflector/commit/695f3c49285254869f6a6cbd5f860d1169fa4daa))
## [0.33.0](https://github.com/Monadical-SAS/reflector/compare/v0.32.2...v0.33.0) (2026-02-05)
### Features
* Daily+hatchet default ([#846](https://github.com/Monadical-SAS/reflector/issues/846)) ([15ab2e3](https://github.com/Monadical-SAS/reflector/commit/15ab2e306eacf575494b4b5d2b2ad779d44a1c7f))
### Bug Fixes
* websocket tests ([#825](https://github.com/Monadical-SAS/reflector/issues/825)) ([1ce1c7a](https://github.com/Monadical-SAS/reflector/commit/1ce1c7a910b6c374115d2437b17f9d288ef094dc))
## [0.32.2](https://github.com/Monadical-SAS/reflector/compare/v0.32.1...v0.32.2) (2026-02-03)

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@@ -0,0 +1,25 @@
# Reflector self-hosted production — HTTPS via Caddy reverse proxy
# Copy to Caddyfile: cp Caddyfile.selfhosted.example Caddyfile
# Run: ./scripts/setup-selfhosted.sh --ollama-gpu --garage --caddy
#
# DOMAIN defaults to localhost (self-signed cert).
# Set to your real domain for automatic Let's Encrypt:
# export DOMAIN=reflector.example.com
#
# TLS_MODE defaults to "internal" (self-signed).
# Set to "" for automatic Let's Encrypt (requires real domain + ports 80/443 open):
# export TLS_MODE=""
{$DOMAIN:localhost} {
tls {$TLS_MODE:internal}
handle /v1/* {
reverse_proxy server:1250
}
handle /health {
reverse_proxy server:1250
}
handle {
reverse_proxy web:3000
}
}

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@@ -0,0 +1,42 @@
# Reflector standalone — HTTPS via Caddy (droplet / IP access)
# Copy to Caddyfile: cp Caddyfile.standalone.example Caddyfile
# Run: docker compose -f docker-compose.standalone.yml --profile ollama-cpu up -d
#
# :443 = catch-all inside container; Docker maps host port 3043 → container 443
# on_demand = generate self-signed cert for IP/SNI on first request (required for bare IP access)
# Browser will warn. Click Advanced → Proceed.
# Access at https://localhost:3043 (or https://YOUR_IP:3043 on droplet)
# Update www/.env.local with: API_URL=https://YOUR_IP:3043, WEBSOCKET_URL=wss://YOUR_IP:3043, SITE_URL=https://YOUR_IP:3043, NEXTAUTH_URL=https://YOUR_IP:3043
:443 {
tls internal {
on_demand
}
handle /v1/* {
reverse_proxy server:1250
}
handle /health {
reverse_proxy server:1250
}
handle {
reverse_proxy web:3000
}
}
# Option B: localhost (comment Option A, uncomment this)
# app.localhost {
# tls internal
# reverse_proxy web:3000
# }
# api.localhost {
# tls internal
# reverse_proxy server:1250
# }
# Option C: Real domain (uncomment and replace example.com)
# app.example.com {
# reverse_proxy web:3000
# }
# api.example.com {
# reverse_proxy server:1250
# }

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@@ -0,0 +1,315 @@
# Self-hosted production Docker Compose — single file for everything.
#
# Usage: ./scripts/setup-selfhosted.sh --gpu --ollama-gpu --garage --caddy
# or: docker compose -f docker-compose.selfhosted.yml --profile gpu [--profile ollama-gpu] [--profile garage] [--profile caddy] up -d
#
# Specialized models (pick ONE — required):
# --profile gpu NVIDIA GPU for transcription/diarization/translation
# --profile cpu CPU-only for transcription/diarization/translation
#
# Local LLM (optional — for summarization/topics):
# --profile ollama-gpu Local Ollama with NVIDIA GPU
# --profile ollama-cpu Local Ollama on CPU only
#
# Other optional services:
# --profile garage Local S3-compatible storage (Garage)
# --profile caddy Reverse proxy with auto-SSL
#
# Prerequisites:
# 1. Run ./scripts/setup-selfhosted.sh to generate env files and secrets
# 2. Or manually create server/.env and www/.env from the .selfhosted.example templates
services:
# ===========================================================
# Always-on core services (no profile required)
# ===========================================================
server:
build:
context: ./server
dockerfile: Dockerfile
image: monadicalsas/reflector-backend:latest
restart: unless-stopped
ports:
- "127.0.0.1:1250:1250"
- "50000-50100:50000-50100/udp"
env_file:
- ./server/.env
environment:
ENTRYPOINT: server
# Docker-internal overrides (always correct inside compose network)
DATABASE_URL: postgresql+asyncpg://reflector:reflector@postgres:5432/reflector
REDIS_HOST: redis
CELERY_BROKER_URL: redis://redis:6379/1
CELERY_RESULT_BACKEND: redis://redis:6379/1
HATCHET_CLIENT_SERVER_URL: ""
HATCHET_CLIENT_HOST_PORT: ""
# Specialized models via gpu/cpu container (aliased as "transcription")
TRANSCRIPT_BACKEND: modal
TRANSCRIPT_URL: http://transcription:8000
TRANSCRIPT_MODAL_API_KEY: selfhosted
DIARIZATION_BACKEND: modal
DIARIZATION_URL: http://transcription:8000
TRANSLATION_BACKEND: modal
TRANSLATE_URL: http://transcription:8000
# WebRTC: fixed UDP port range for ICE candidates (mapped above)
WEBRTC_PORT_RANGE: "50000-50100"
depends_on:
postgres:
condition: service_healthy
redis:
condition: service_started
volumes:
- server_data:/app/data
worker:
build:
context: ./server
dockerfile: Dockerfile
image: monadicalsas/reflector-backend:latest
restart: unless-stopped
env_file:
- ./server/.env
environment:
ENTRYPOINT: worker
DATABASE_URL: postgresql+asyncpg://reflector:reflector@postgres:5432/reflector
REDIS_HOST: redis
CELERY_BROKER_URL: redis://redis:6379/1
CELERY_RESULT_BACKEND: redis://redis:6379/1
HATCHET_CLIENT_SERVER_URL: ""
HATCHET_CLIENT_HOST_PORT: ""
TRANSCRIPT_BACKEND: modal
TRANSCRIPT_URL: http://transcription:8000
TRANSCRIPT_MODAL_API_KEY: selfhosted
DIARIZATION_BACKEND: modal
DIARIZATION_URL: http://transcription:8000
TRANSLATION_BACKEND: modal
TRANSLATE_URL: http://transcription:8000
depends_on:
postgres:
condition: service_healthy
redis:
condition: service_started
volumes:
- server_data:/app/data
beat:
build:
context: ./server
dockerfile: Dockerfile
image: monadicalsas/reflector-backend:latest
restart: unless-stopped
env_file:
- ./server/.env
environment:
ENTRYPOINT: beat
DATABASE_URL: postgresql+asyncpg://reflector:reflector@postgres:5432/reflector
REDIS_HOST: redis
CELERY_BROKER_URL: redis://redis:6379/1
CELERY_RESULT_BACKEND: redis://redis:6379/1
depends_on:
postgres:
condition: service_healthy
redis:
condition: service_started
web:
build:
context: ./www
dockerfile: Dockerfile
image: monadicalsas/reflector-frontend:latest
restart: unless-stopped
ports:
- "127.0.0.1:3000:3000"
env_file:
- ./www/.env
environment:
NODE_ENV: production
SERVER_API_URL: http://server:1250
KV_URL: redis://redis:6379
KV_USE_TLS: "false"
AUTHENTIK_ISSUER: ""
AUTHENTIK_REFRESH_TOKEN_URL: ""
depends_on:
- redis
redis:
image: redis:7.2-alpine
restart: unless-stopped
healthcheck:
test: ["CMD", "redis-cli", "ping"]
interval: 30s
timeout: 3s
retries: 3
volumes:
- redis_data:/data
postgres:
image: postgres:17-alpine
restart: unless-stopped
environment:
POSTGRES_USER: reflector
POSTGRES_PASSWORD: reflector
POSTGRES_DB: reflector
volumes:
- postgres_data:/var/lib/postgresql/data
healthcheck:
test: ["CMD-SHELL", "pg_isready -U reflector"]
interval: 30s
timeout: 3s
retries: 3
# ===========================================================
# Specialized model containers (transcription, diarization, translation)
# Both gpu and cpu get alias "transcription" so server config never changes.
# ===========================================================
gpu:
build:
context: ./gpu/self_hosted
dockerfile: Dockerfile
profiles: [gpu]
restart: unless-stopped
ports:
- "127.0.0.1:8000:8000"
environment:
HF_TOKEN: ${HF_TOKEN:-}
volumes:
- gpu_cache:/root/.cache
deploy:
resources:
reservations:
devices:
- driver: nvidia
count: all
capabilities: [gpu]
healthcheck:
test: ["CMD", "curl", "-f", "http://localhost:8000/docs"]
interval: 15s
timeout: 5s
retries: 10
start_period: 120s
networks:
default:
aliases:
- transcription
cpu:
build:
context: ./gpu/self_hosted
dockerfile: Dockerfile.cpu
profiles: [cpu]
restart: unless-stopped
ports:
- "127.0.0.1:8000:8000"
environment:
HF_TOKEN: ${HF_TOKEN:-}
volumes:
- gpu_cache:/root/.cache
healthcheck:
test: ["CMD", "curl", "-f", "http://localhost:8000/docs"]
interval: 15s
timeout: 5s
retries: 10
start_period: 120s
networks:
default:
aliases:
- transcription
# ===========================================================
# Ollama — local LLM for summarization & topic detection
# Only started with --ollama-gpu or --ollama-cpu modes.
# ===========================================================
ollama:
image: ollama/ollama:latest
profiles: [ollama-gpu]
restart: unless-stopped
ports:
- "127.0.0.1:11434:11434"
volumes:
- ollama_data:/root/.ollama
deploy:
resources:
reservations:
devices:
- driver: nvidia
count: all
capabilities: [gpu]
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]
restart: unless-stopped
ports:
- "127.0.0.1:11434:11434"
volumes:
- ollama_data:/root/.ollama
healthcheck:
test: ["CMD", "curl", "-f", "http://localhost:11434/api/tags"]
interval: 10s
timeout: 5s
retries: 5
# ===========================================================
# Garage — local S3-compatible object storage (optional)
# ===========================================================
garage:
image: dxflrs/garage:v1.1.0
profiles: [garage]
restart: unless-stopped
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
healthcheck:
test: ["CMD", "/garage", "stats"]
interval: 10s
timeout: 5s
retries: 5
start_period: 5s
# ===========================================================
# Caddy — reverse proxy with automatic SSL (optional)
# Maps 80:80 and 443:443 — only exposed ports in the stack.
# ===========================================================
caddy:
image: caddy:2-alpine
profiles: [caddy]
restart: unless-stopped
ports:
- "80:80"
- "443:443"
volumes:
- ./Caddyfile:/etc/caddy/Caddyfile:ro
- caddy_data:/data
- caddy_config:/config
depends_on:
- web
- server
volumes:
postgres_data:
redis_data:
server_data:
gpu_cache:
garage_data:
garage_meta:
ollama_data:
caddy_data:
caddy_config:
networks:
default:
attachable: true

View File

@@ -0,0 +1,241 @@
# Self-contained standalone compose for fully local deployment (no external dependencies).
# Usage: docker compose -f docker-compose.standalone.yml up -d
#
# On Linux with NVIDIA GPU, also pass: --profile ollama-gpu
# On Linux without GPU: --profile ollama-cpu
# On Mac: Ollama runs natively (Metal GPU) — no profile needed, services here unused.
services:
caddy:
image: caddy:2-alpine
restart: unless-stopped
ports:
- "3043:443"
extra_hosts:
- "host.docker.internal:host-gateway"
volumes:
- ./Caddyfile:/etc/caddy/Caddyfile:ro
- caddy_data:/data
- caddy_config:/config
depends_on:
- web
- server
server:
build:
context: server
ports:
- "1250:1250"
- "50000-50100:50000-50100/udp"
extra_hosts:
- "host.docker.internal:host-gateway"
volumes:
- ./server/:/app/
- /app/.venv
env_file:
- ./server/.env
environment:
ENTRYPOINT: server
# Docker DNS names instead of localhost
DATABASE_URL: postgresql+asyncpg://reflector:reflector@postgres:5432/reflector
REDIS_HOST: redis
CELERY_BROKER_URL: redis://redis:6379/1
CELERY_RESULT_BACKEND: redis://redis:6379/1
# Standalone doesn't run Hatchet
HATCHET_CLIENT_SERVER_URL: ""
HATCHET_CLIENT_HOST_PORT: ""
# Self-hosted transcription/diarization via CPU service
TRANSCRIPT_BACKEND: modal
TRANSCRIPT_URL: http://cpu:8000
TRANSCRIPT_MODAL_API_KEY: local
DIARIZATION_BACKEND: modal
DIARIZATION_URL: http://cpu:8000
# Caddy reverse proxy prefix
ROOT_PATH: /server-api
# WebRTC: fixed UDP port range for ICE candidates (mapped above).
# WEBRTC_HOST is set by setup-standalone.sh in server/.env (LAN IP detection).
WEBRTC_PORT_RANGE: "50000-50100"
depends_on:
postgres:
condition: service_healthy
redis:
condition: service_started
worker:
build:
context: server
volumes:
- ./server/:/app/
- /app/.venv
env_file:
- ./server/.env
environment:
ENTRYPOINT: worker
HATCHET_CLIENT_SERVER_URL: ""
HATCHET_CLIENT_HOST_PORT: ""
TRANSCRIPT_BACKEND: modal
TRANSCRIPT_URL: http://cpu:8000
TRANSCRIPT_MODAL_API_KEY: local
DIARIZATION_BACKEND: modal
DIARIZATION_URL: http://cpu:8000
depends_on:
redis:
condition: service_started
beat:
build:
context: server
volumes:
- ./server/:/app/
- /app/.venv
env_file:
- ./server/.env
environment:
ENTRYPOINT: beat
depends_on:
redis:
condition: service_started
redis:
image: redis:7.2
ports:
- 6379:6379
postgres:
image: postgres:17
command: postgres -c 'max_connections=200'
ports:
- 5432:5432
environment:
POSTGRES_USER: reflector
POSTGRES_PASSWORD: reflector
POSTGRES_DB: reflector
volumes:
- ./data/postgres:/var/lib/postgresql/data
healthcheck:
test: ["CMD-SHELL", "pg_isready -d reflector -U reflector"]
interval: 5s
timeout: 5s
retries: 10
start_period: 15s
web:
image: reflector-frontend-standalone
build:
context: ./www
ports:
- "3000:3000"
command: ["node", "server.js"]
env_file:
- ./www/.env.local
environment:
NODE_ENV: production
# API_URL, WEBSOCKET_URL, SITE_URL, NEXTAUTH_URL from www/.env.local (allows HTTPS)
# Server-side URLs (docker-network internal)
SERVER_API_URL: http://server:1250
KV_URL: redis://redis:6379
KV_USE_TLS: "false"
# Standalone: no external auth provider
FEATURE_REQUIRE_LOGIN: "false"
FEATURE_ROOMS: "false"
NEXTAUTH_SECRET: standalone-local-secret
# Nullify partial auth vars inherited from base env_file
AUTHENTIK_ISSUER: ""
AUTHENTIK_REFRESH_TOKEN_URL: ""
garage:
image: dxflrs/garage:v1.1.0
ports:
- "3900:3900" # S3 API
- "3903:3903" # Admin API
volumes:
- garage_data:/var/lib/garage/data
- garage_meta:/var/lib/garage/meta
- ./data/garage.toml:/etc/garage.toml:ro
restart: unless-stopped
healthcheck:
test: ["CMD", "/garage", "stats"]
interval: 10s
timeout: 5s
retries: 5
start_period: 5s
cpu:
build:
context: ./gpu/self_hosted
dockerfile: Dockerfile.cpu
ports:
- "8100:8000"
volumes:
- gpu_cache:/root/.cache
restart: unless-stopped
healthcheck:
test: ["CMD", "curl", "-f", "http://localhost:8000/docs"]
interval: 15s
timeout: 5s
retries: 10
start_period: 120s
gpu-nvidia:
build:
context: ./gpu/self_hosted
profiles: ["gpu-nvidia"]
volumes:
- gpu_cache:/root/.cache
deploy:
resources:
reservations:
devices:
- driver: nvidia
count: all
capabilities: [gpu]
restart: unless-stopped
healthcheck:
test: ["CMD", "curl", "-f", "http://localhost:8000/docs"]
interval: 15s
timeout: 5s
retries: 10
start_period: 120s
ollama:
image: ollama/ollama:latest
profiles: ["ollama-gpu"]
ports:
- "11434:11434"
volumes:
- ollama_data:/root/.ollama
deploy:
resources:
reservations:
devices:
- driver: nvidia
count: all
capabilities: [gpu]
restart: unless-stopped
healthcheck:
test: ["CMD", "curl", "-f", "http://localhost:11434/api/tags"]
interval: 10s
timeout: 5s
retries: 5
ollama-cpu:
image: ollama/ollama:latest
profiles: ["ollama-cpu"]
ports:
- "11434:11434"
volumes:
- ollama_data:/root/.ollama
restart: unless-stopped
healthcheck:
test: ["CMD", "curl", "-f", "http://localhost:11434/api/tags"]
interval: 10s
timeout: 5s
retries: 5
volumes:
garage_data:
garage_meta:
ollama_data:
gpu_cache:
caddy_data:
caddy_config:

View File

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

View File

@@ -0,0 +1,310 @@
---
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
```
On Ubuntu, the setup script installs Docker automatically if missing.
The script is idempotent — safe to re-run at any time. It detects what's already set up and skips completed steps.
## Prerequisites
- Docker with Compose V2 plugin (Docker Desktop, OrbStack, or Docker Engine + compose plugin)
- Mac (Apple Silicon) or Linux
- 16GB+ RAM (32GB recommended for 14B LLM models)
- **Mac only**: [Ollama](https://ollama.com/download) installed (`brew install ollama`)
### Installing Docker (if not already installed)
**Ubuntu**: The setup script runs `install-docker-ubuntu.sh` automatically when Docker is missing. Or run it manually:
```bash
./scripts/install-docker-ubuntu.sh
```
**Mac**: Install [Docker Desktop](https://www.docker.com/products/docker-desktop/) or [OrbStack](https://orbstack.dev/).
## 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` | `https://localhost:3043` or `https://YOUR_IP:3043` (Linux) |
| `SERVER_API_URL` | `http://server:1250` |
| `WEBSOCKET_URL` | `auto` |
| `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` (or via Caddy at `https://localhost:3043`)
- LLM endpoint reachable from inside containers
## Services
| Service | Port | Purpose |
| ---------- | ---------- | -------------------------------------------------- |
| `caddy` | 3043 | Reverse proxy (HTTPS, self-signed cert) |
| `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.
## Enabling HTTPS (droplet via IP)
To serve Reflector over HTTPS on a droplet accessed by IP (self-signed certificate):
1. **Copy the Caddyfile** (no edits needed — `:443` catches all HTTPS inside container, mapped to host port 3043):
```bash
cp Caddyfile.standalone.example Caddyfile
```
2. **Update `www/.env.local`** with HTTPS URLs (port 3043):
```env
API_URL=https://YOUR_IP:3043
WEBSOCKET_URL=wss://YOUR_IP:3043
SITE_URL=https://YOUR_IP:3043
NEXTAUTH_URL=https://YOUR_IP:3043
```
3. **Restart services**:
```bash
docker compose -f docker-compose.standalone.yml --profile ollama-cpu up -d
```
(Use `ollama-gpu` instead of `ollama-cpu` if you have an NVIDIA GPU.)
4. **Access** at `https://YOUR_IP:3043`. The browser will warn about the self-signed cert — click **Advanced** → **Proceed to YOUR_IP (unsafe)**. All traffic (page, API, WebSocket) uses the same origin, so accepting once is enough.
## Troubleshooting
### ERR_SSL_PROTOCOL_ERROR when accessing https://YOUR_IP
You do **not** need a domain — the setup works with an IP address. This error usually means Caddy isn't serving TLS on port 3043. Check in order:
1. **Caddyfile** — must use the `:443` catch-all (container-internal; Docker maps host 3043 → container 443):
```bash
cp Caddyfile.standalone.example Caddyfile
```
2. **Firewall** — allow port 3043 (common on DigitalOcean):
```bash
sudo ufw allow 3043
sudo ufw status
```
3. **Caddy running** — verify and restart:
```bash
docker compose -f docker-compose.standalone.yml ps
docker compose -f docker-compose.standalone.yml logs caddy --tail 20
docker compose -f docker-compose.standalone.yml --profile ollama-cpu up -d
```
4. **Test from the droplet** — if this works, the issue is external (firewall, network):
```bash
curl -vk https://localhost:3043
```
5. **localhost works but external IP fails** — Re-run the setup script; it generates a Caddyfile with your droplet IP explicitly, so Caddy provisions the cert at startup:
```bash
./scripts/setup-standalone.sh
```
Or manually create `Caddyfile` with your IP (replace 138.197.162.116):
```
https://138.197.162.116, localhost {
tls internal
handle /v1/* { reverse_proxy server:1250 }
handle /health { reverse_proxy server:1250 }
handle { reverse_proxy web:3000 }
}
```
Then restart: `docker compose -f docker-compose.standalone.yml --profile ollama-cpu up -d`
6. **Still failing?** Try HTTP (no TLS) — create `Caddyfile`:
```
:80 {
handle /v1/* { reverse_proxy server:1250 }
handle /health { reverse_proxy server:1250 }
handle { reverse_proxy web:3000 }
}
```
Update `www/.env.local`: `API_URL=http://YOUR_IP:3043`, `WEBSOCKET_URL=ws://YOUR_IP:3043`, `SITE_URL=http://YOUR_IP:3043`, `NEXTAUTH_URL=http://YOUR_IP:3043`. Restart, then access `http://YOUR_IP:3043`.
### Docker not ready
If setup fails with "Docker not ready", on Ubuntu run `./scripts/install-docker-ubuntu.sh`. If Docker is installed but you're not root, run `newgrp docker` then run the setup script again.
### Port conflicts (most common issue)
If the frontend or backend behaves unexpectedly (e.g., env vars seem ignored, changes don't take effect), **check for port conflicts first**:
```bash
# Check what's listening on key ports
lsof -i :3000 # frontend
lsof -i :1250 # backend
lsof -i :5432 # postgres
lsof -i :3900 # Garage S3 API
lsof -i :6379 # Redis
# Kill stale processes on a port
lsof -ti :3000 | xargs kill
```
Common causes:
- A stale `next dev` or `pnpm dev` process from another terminal/worktree
- Another Docker Compose project (different worktree) with containers on the same ports — the setup script only manages its own project; containers from other projects must be stopped manually (`docker ps` to find them, `docker stop` to kill them)
The setup script checks ports 3000, 1250, 5432, 6379, 3900, 3903 for conflicts before starting services. It ignores OrbStack/Docker Desktop port forwarding processes (which always bind these ports but are not real conflicts).
### OrbStack false port-conflict warnings (Mac)
If you use OrbStack as your Docker runtime, `lsof` will show OrbStack binding ports like 3000, 1250, etc. even when no containers are running. This is OrbStack's port forwarding mechanism — not a real conflict. The setup script filters these out automatically.
### Re-enabling authentication
Standalone runs without authentication (`FEATURE_REQUIRE_LOGIN=false`, `AUTH_BACKEND=none`). To re-enable:
1. In `www/.env.local`: set `FEATURE_REQUIRE_LOGIN=true`, uncomment `AUTHENTIK_ISSUER` and `AUTHENTIK_REFRESH_TOKEN_URL`
2. In `server/.env`: set `AUTH_BACKEND=authentik` (or your backend), configure `AUTH_JWT_AUDIENCE`
3. Restart: `docker compose -f docker-compose.standalone.yml up -d --force-recreate web server`
## What's NOT covered
These require external accounts and infrastructure that can't be scripted:
- **Live meeting rooms** — requires Daily.co account, S3 bucket, IAM roles
- **Authentication** — requires Authentik deployment and OAuth configuration
- **Hatchet workflows** — requires separate Hatchet setup for multitrack processing
- **Production deployment** — see [Deployment Guide](./overview)
## Current status
All steps implemented. The setup script handles everything end-to-end:
- Step 1 (Ollama/LLM) — implemented
- Step 2 (environment files) — implemented
- Step 3 (object storage / Garage) — implemented
- Step 4 (transcription/diarization) — implemented (self-hosted GPU service)
- Steps 5-7 (Docker, migrations, health) — implemented
- **Unified script**: `scripts/setup-standalone.sh`

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@@ -0,0 +1,468 @@
# How the Self-Hosted Setup Works
This document explains the internals of the self-hosted deployment: how the setup script orchestrates everything, how the Docker Compose profiles work, how services communicate, and how configuration flows from flags to running containers.
> For quick-start instructions and flag reference, see [Self-Hosted Production Deployment](selfhosted-production.md).
## Table of Contents
- [Overview](#overview)
- [The Setup Script Step by Step](#the-setup-script-step-by-step)
- [Docker Compose Profile System](#docker-compose-profile-system)
- [Service Architecture](#service-architecture)
- [Configuration Flow](#configuration-flow)
- [Storage Architecture](#storage-architecture)
- [SSL/TLS and Reverse Proxy](#ssltls-and-reverse-proxy)
- [Build vs Pull Workflow](#build-vs-pull-workflow)
- [Background Task Processing](#background-task-processing)
- [Network and Port Layout](#network-and-port-layout)
---
## Overview
The self-hosted deployment runs the entire Reflector platform on a single server using Docker Compose. A single bash script (`scripts/setup-selfhosted.sh`) handles all configuration and orchestration. The key design principles are:
- **One command to deploy** — flags select which features to enable
- **Idempotent** — safe to re-run without losing existing configuration
- **Profile-based composition** — Docker Compose profiles activate optional services
- **No external dependencies required** — with `--garage` and `--ollama-*`, everything runs locally
## The Setup Script Step by Step
The script (`scripts/setup-selfhosted.sh`) runs 7 sequential steps. Here's what each one does and why.
### Step 0: Prerequisites
Validates the environment before doing anything:
- **Docker Compose V2** — checks `docker compose version` output (not the legacy `docker-compose`)
- **Docker daemon** — verifies `docker info` succeeds
- **NVIDIA GPU** — only checked when `--gpu` or `--ollama-gpu` is used; runs `nvidia-smi` to confirm drivers are installed
- **Compose file** — verifies `docker-compose.selfhosted.yml` exists at the expected path
If any check fails, the script exits with a clear error message and remediation steps.
### Step 1: Generate Secrets
Creates cryptographic secrets needed by the backend and frontend:
- **`SECRET_KEY`** — used by the FastAPI server for session signing (64 hex chars via `openssl rand -hex 32`)
- **`NEXTAUTH_SECRET`** — used by Next.js NextAuth for JWT signing
Secrets are only generated if they don't already exist or are still set to the placeholder value `changeme`. This is what makes the script idempotent for secrets.
### Step 2: Generate `server/.env`
Creates or updates the backend environment file from `server/.env.selfhosted.example`. Sets:
- **Infrastructure** — PostgreSQL URL, Redis host, Celery broker (all pointing to Docker-internal hostnames)
- **Public URLs** — `BASE_URL` and `CORS_ORIGIN` computed from the domain (if `--domain`), IP (if detected on Linux), or `localhost`
- **WebRTC** — `WEBRTC_HOST` set to the server's LAN IP so browsers can reach UDP ICE candidates
- **Specialized models** — always points to `http://transcription:8000` (the Docker network alias shared by GPU and CPU containers)
- **HuggingFace token** — prompts interactively for pyannote model access; writes to root `.env` so Docker Compose can inject it into GPU/CPU containers
- **LLM** — if `--ollama-*` is used, configures `LLM_URL` pointing to the Ollama container. Otherwise, warns that the user needs to configure an external LLM
- **Public mode** — sets `PUBLIC_MODE=true` so the app is accessible without authentication by default
The script uses `env_set` for each variable, which either updates an existing line or appends a new one. This means re-running the script updates values in-place without duplicating keys.
### Step 3: Generate `www/.env`
Creates or updates the frontend environment file from `www/.env.selfhosted.example`. Sets:
- **`SITE_URL` / `NEXTAUTH_URL` / `API_URL`** — all set to the same public-facing URL (with `https://` if Caddy is enabled)
- **`WEBSOCKET_URL`** — set to `auto`, which tells the frontend to derive the WebSocket URL from the page URL automatically
- **`SERVER_API_URL`** — always `http://server:1250` (Docker-internal, used for server-side rendering)
- **`KV_URL`** — Redis URL for Next.js caching
- **`FEATURE_REQUIRE_LOGIN`** — `false` by default (matches `PUBLIC_MODE=true` on the backend)
### Step 4: Storage Setup
Branches based on whether `--garage` was passed:
**With `--garage` (local S3):**
1. Generates `data/garage.toml` from a template, injecting a random RPC secret
2. Starts only the Garage container (`docker compose --profile garage up -d garage`)
3. Waits for the Garage admin API to respond on port 3903
4. Assigns the node to a storage layout (1GB capacity, zone `dc1`)
5. Creates the `reflector-media` bucket
6. Creates an access key named `reflector` and grants it read/write on the bucket
7. Writes all S3 credentials (`ENDPOINT_URL`, `BUCKET_NAME`, `REGION`, `ACCESS_KEY_ID`, `SECRET_ACCESS_KEY`) to `server/.env`
The Garage endpoint is `http://garage:3900` (Docker-internal), and the region is set to `garage` (arbitrary, Garage ignores it). The boto3 client uses path-style addressing when an endpoint URL is configured, which is required for S3-compatible services like Garage.
**Without `--garage` (external S3):**
1. Checks `server/.env` for the four required S3 variables
2. If any are missing, prompts interactively for each one
3. Optionally prompts for an endpoint URL (for MinIO, Backblaze B2, etc.)
### Step 5: Caddyfile
Only runs when `--caddy` or `--domain` is used. Generates a Caddy configuration file:
**With `--domain`:** Creates a named site block (`reflector.example.com { ... }`). Caddy automatically provisions a Let's Encrypt certificate for this domain. Requires DNS pointing to the server and ports 80/443 open.
**Without `--domain` (IP access):** Creates a catch-all `:443 { tls internal ... }` block. Caddy generates a self-signed certificate. Browsers will show a security warning.
Both configurations route:
- `/v1/*` and `/health` to the backend (`server:1250`)
- Everything else to the frontend (`web:3000`)
### Step 6: Start Services
1. **Always builds the GPU/CPU model image** — these are never prebuilt because they contain ML model download logic specific to the host's hardware
2. **With `--build`:** Also builds backend (server, worker, beat) and frontend (web) images from source
3. **Without `--build`:** Pulls prebuilt images from the Docker registry (`monadicalsas/reflector-backend:latest`, `monadicalsas/reflector-frontend:latest`)
4. **Starts all services**`docker compose up -d` with the active profiles
5. **Quick sanity check** — after 3 seconds, checks for any containers that exited immediately
### Step 7: Health Checks
Waits for each service in order, with generous timeouts:
| Service | Check | Timeout | Notes |
|---------|-------|---------|-------|
| GPU/CPU models | `curl http://localhost:8000/docs` | 10 min (120 x 5s) | First start downloads ~1GB of models |
| Ollama | `curl http://localhost:11434/api/tags` | 3 min (60 x 3s) | Then pulls the selected model |
| Server API | `curl http://localhost:1250/health` | 7.5 min (90 x 5s) | First start runs database migrations |
| Frontend | `curl http://localhost:3000` | 1.5 min (30 x 3s) | Next.js build on first start |
| Caddy | `curl -k https://localhost` | Quick check | After other services are up |
If the server container exits during the health check, the script dumps diagnostics (container statuses + logs) before exiting.
After the Ollama health check passes, the script checks if the selected model is already pulled. If not, it runs `ollama pull <model>` inside the container.
---
## Docker Compose Profile System
The compose file (`docker-compose.selfhosted.yml`) uses Docker Compose profiles to make services optional. Only services whose profiles match the active `--profile` flags are started.
### Always-on Services (no profile)
These start regardless of which flags you pass:
| Service | Role | Image |
|---------|------|-------|
| `server` | FastAPI backend, API endpoints, WebRTC | `monadicalsas/reflector-backend:latest` |
| `worker` | Celery worker for background processing | Same image, `ENTRYPOINT=worker` |
| `beat` | Celery beat scheduler for periodic tasks | Same image, `ENTRYPOINT=beat` |
| `web` | Next.js frontend | `monadicalsas/reflector-frontend:latest` |
| `redis` | Message broker + caching | `redis:7.2-alpine` |
| `postgres` | Primary database | `postgres:17-alpine` |
### Profile-Based Services
| Profile | Service | Role |
|---------|---------|------|
| `gpu` | `gpu` | NVIDIA GPU-accelerated transcription/diarization/translation |
| `cpu` | `cpu` | CPU-only transcription/diarization/translation |
| `ollama-gpu` | `ollama` | Local Ollama LLM with GPU |
| `ollama-cpu` | `ollama-cpu` | Local Ollama LLM on CPU |
| `garage` | `garage` | Local S3-compatible object storage |
| `caddy` | `caddy` | Reverse proxy with SSL |
### The "transcription" Alias
Both the `gpu` and `cpu` services define a Docker network alias of `transcription`. This means the backend always connects to `http://transcription:8000` regardless of which profile is active. The alias is defined in the compose file's `networks.default.aliases` section.
---
## Service Architecture
```
┌─────────────┐
Internet ────────>│ Caddy │ :80/:443 (profile: caddy)
└──────┬──────┘
┌────────────┼────────────┐
│ │ │
v v │
┌─────────┐ ┌─────────┐ │
│ web │ │ server │ │
│ :3000 │ │ :1250 │ │
└─────────┘ └────┬────┘ │
│ │
┌────┴────┐ │
│ worker │ │
│ beat │ │
└────┬────┘ │
│ │
┌──────────────┼────────────┤
│ │ │
v v v
┌───────────┐ ┌─────────┐ ┌─────────┐
│transcription│ │postgres │ │ redis │
│ (gpu/cpu) │ │ :5432 │ │ :6379 │
│ :8000 │ └─────────┘ └─────────┘
└───────────┘
┌─────┴─────┐ ┌─────────┐
│ ollama │ │ garage │
│(optional) │ │(optional│
│ :11434 │ │ S3) │
└───────────┘ └─────────┘
```
### How Services Interact
1. **User request** hits Caddy (if enabled), which routes to `web` (pages) or `server` (API)
2. **`web`** renders pages server-side using `SERVER_API_URL=http://server:1250` and client-side using the public `API_URL`
3. **`server`** handles API requests, file uploads, WebRTC streaming. Dispatches background work to Celery via Redis
4. **`worker`** picks up Celery tasks (transcription pipelines, audio processing). Calls `transcription:8000` for ML inference and uploads results to S3 storage
5. **`beat`** schedules periodic tasks (cleanup, webhook retries) by pushing them onto the Celery queue
6. **`transcription` (gpu/cpu)** runs Whisper/Parakeet (transcription), Pyannote (diarization), and translation models. Stateless HTTP API
7. **`ollama`** provides an OpenAI-compatible API for summarization and topic detection. Called by the worker during post-processing
8. **`garage`** provides S3-compatible storage for audio files and processed results. Accessed by the worker via boto3
---
## Configuration Flow
Environment variables flow through multiple layers. Understanding this prevents confusion when debugging:
```
Flags (--gpu, --garage, etc.)
├── setup-selfhosted.sh interprets flags
│ │
│ ├── Writes server/.env (backend config)
│ ├── Writes www/.env (frontend config)
│ ├── Writes .env (HF_TOKEN for compose interpolation)
│ └── Writes Caddyfile (proxy routes)
└── docker-compose.selfhosted.yml reads:
├── env_file: ./server/.env (loaded into server, worker, beat)
├── env_file: ./www/.env (loaded into web)
├── .env (compose variable interpolation, e.g. ${HF_TOKEN})
└── environment: {...} (hardcoded overrides, always win over env_file)
```
### Precedence Rules
Docker Compose `environment:` keys **always override** `env_file:` values. This is by design — the compose file hardcodes infrastructure values that must be correct inside the Docker network (like `DATABASE_URL=postgresql+asyncpg://...@postgres:5432/...`) regardless of what's in `server/.env`.
The `server/.env` file is still useful for:
- Values not overridden in the compose file (LLM config, storage credentials, auth settings)
- Running the server outside Docker during development
### The Three `.env` Files
| File | Used By | Contains |
|------|---------|----------|
| `server/.env` | server, worker, beat | Backend config: database, Redis, S3, LLM, auth, public URLs |
| `www/.env` | web | Frontend config: site URL, auth, feature flags |
| `.env` (root) | Docker Compose interpolation | Only `HF_TOKEN` — injected into GPU/CPU container env |
---
## Storage Architecture
All audio files and processing results are stored in S3-compatible object storage. The backend uses boto3 (via aioboto3) with automatic path-style addressing when a custom endpoint URL is configured.
### How Garage Works
Garage is a lightweight, self-hosted S3-compatible storage engine. In this deployment:
- Runs as a single-node cluster with 1GB capacity allocation
- Listens on port 3900 (S3 API) and 3903 (admin API)
- Data persists in Docker volumes (`garage_data`, `garage_meta`)
- Accessed by the worker at `http://garage:3900` (Docker-internal)
The setup script creates:
- A bucket called `reflector-media`
- An access key called `reflector` with read/write permissions on that bucket
### Path-Style vs Virtual-Hosted Addressing
AWS S3 uses virtual-hosted addressing by default (`bucket.s3.amazonaws.com`). S3-compatible services like Garage require path-style addressing (`endpoint/bucket`). The `AwsStorage` class detects this automatically: when `TRANSCRIPT_STORAGE_AWS_ENDPOINT_URL` is set, it configures boto3 with `addressing_style: "path"`.
---
## SSL/TLS and Reverse Proxy
### With `--domain` (Production)
Caddy automatically obtains and renews a Let's Encrypt certificate. Requirements:
- DNS A record pointing to the server
- Ports 80 (HTTP challenge) and 443 (HTTPS) open to the internet
The generated Caddyfile uses the domain as the site address, which triggers Caddy's automatic HTTPS.
### Without `--domain` (Development/LAN)
Caddy generates a self-signed certificate and listens on `:443` as a catch-all. Browsers will show a security warning that must be accepted manually.
### Without `--caddy` (BYO Proxy)
No ports are exposed to the internet. The services listen on `127.0.0.1` only:
- Frontend: `localhost:3000`
- Backend API: `localhost:1250`
You can point your own reverse proxy (nginx, Traefik, etc.) at these ports.
### WebRTC and UDP
The server exposes UDP ports 50000-50100 for WebRTC ICE candidates. The `WEBRTC_HOST` variable tells the server which IP to advertise in ICE candidates — this must be the server's actual IP address (not a domain), because WebRTC uses UDP which doesn't go through the HTTP reverse proxy.
---
## Build vs Pull Workflow
### Default (no `--build` flag)
```
GPU/CPU model image: Always built from source (./gpu/self_hosted/)
Backend image: Pulled from monadicalsas/reflector-backend:latest
Frontend image: Pulled from monadicalsas/reflector-frontend:latest
```
The GPU/CPU image is always built because it contains hardware-specific build steps and ML model download logic.
### With `--build`
```
GPU/CPU model image: Built from source (./gpu/self_hosted/)
Backend image: Built from source (./server/)
Frontend image: Built from source (./www/)
```
Use `--build` when:
- You've made local code changes
- The prebuilt registry images are outdated
- You want to verify the build works on your hardware
### Rebuilding Individual Services
```bash
# Rebuild just the backend
docker compose -f docker-compose.selfhosted.yml build server worker beat
# Rebuild just the frontend
docker compose -f docker-compose.selfhosted.yml build web
# Rebuild the GPU model container
docker compose -f docker-compose.selfhosted.yml build gpu
# Force a clean rebuild (no cache)
docker compose -f docker-compose.selfhosted.yml build --no-cache server
```
---
## Background Task Processing
### Celery Architecture
The backend uses Celery for all background work, with Redis as the message broker:
- **`worker`** — picks up tasks from the Redis queue and executes them
- **`beat`** — schedules periodic tasks (cron-like) by pushing them onto the queue
- **`Redis`** — acts as both message broker and result backend
### The Audio Processing Pipeline
When a file is uploaded, the worker runs a multi-step pipeline:
```
Upload → Extract Audio → Upload to S3
┌──────┼──────┐
│ │ │
v v v
Transcribe Diarize Waveform
│ │ │
└──────┼──────┘
Assemble
┌──────┼──────┐
v v v
Topics Title Summaries
Done
```
Transcription, diarization, and waveform generation run in parallel. After assembly, topic detection, title generation, and summarization also run in parallel. Each step calls the appropriate service (transcription container for ML, Ollama/external LLM for text generation, S3 for storage).
### Event Loop Management
Each Celery task runs in its own `asyncio.run()` call, which creates a fresh event loop. The `asynctask` decorator in `server/reflector/asynctask.py` handles:
1. **Database connections** — resets the connection pool before each task (connections from a previous event loop would cause "Future attached to a different loop" errors)
2. **Redis connections** — resets the WebSocket manager singleton so Redis pub/sub reconnects on the current loop
3. **Cleanup** — disconnects the database and clears the context variable in the `finally` block
---
## Network and Port Layout
All services communicate over Docker's default bridge network. Only specific ports are exposed to the host:
| Port | Service | Binding | Purpose |
|------|---------|---------|---------|
| 80 | Caddy | `0.0.0.0:80` | HTTP (redirect to HTTPS / Let's Encrypt challenge) |
| 443 | Caddy | `0.0.0.0:443` | HTTPS (main entry point) |
| 1250 | Server | `127.0.0.1:1250` | Backend API (localhost only) |
| 3000 | Web | `127.0.0.1:3000` | Frontend (localhost only) |
| 3900 | Garage | `0.0.0.0:3900` | S3 API (for admin/debug access) |
| 3903 | Garage | `0.0.0.0:3903` | Garage admin API |
| 8000 | GPU/CPU | `127.0.0.1:8000` | ML model API (localhost only) |
| 11434 | Ollama | `127.0.0.1:11434` | Ollama API (localhost only) |
| 50000-50100/udp | Server | `0.0.0.0:50000-50100` | WebRTC ICE candidates |
Services bound to `127.0.0.1` are only accessible from the host itself (not from the network). Caddy is the only service exposed to the internet on standard HTTP/HTTPS ports.
### Docker-Internal Hostnames
Inside the Docker network, services reach each other by their compose service name:
| Hostname | Resolves To |
|----------|-------------|
| `server` | Backend API container |
| `web` | Frontend container |
| `postgres` | PostgreSQL container |
| `redis` | Redis container |
| `transcription` | GPU or CPU container (network alias) |
| `ollama` / `ollama-cpu` | Ollama container |
| `garage` | Garage S3 container |
---
## Diagnostics and Error Handling
The setup script includes an `ERR` trap that automatically dumps diagnostics when any command fails:
1. Lists all container statuses
2. Shows the last 30 lines of logs for any stopped/exited containers
3. Shows the last 40 lines of the specific failing service
This means if something goes wrong during setup, you'll see the relevant logs immediately without having to run manual debug commands.
### Common Debug Commands
```bash
# Overall status
docker compose -f docker-compose.selfhosted.yml ps
# Logs for a specific service
docker compose -f docker-compose.selfhosted.yml logs server --tail 50
docker compose -f docker-compose.selfhosted.yml logs worker --tail 50
# Check environment inside a container
docker compose -f docker-compose.selfhosted.yml exec server env | grep TRANSCRIPT
# Health check from inside the network
docker compose -f docker-compose.selfhosted.yml exec server curl http://localhost:1250/health
# Check S3 storage connectivity
docker compose -f docker-compose.selfhosted.yml exec server curl http://garage:3900
# Database access
docker compose -f docker-compose.selfhosted.yml exec postgres psql -U reflector -c "SELECT id, status FROM transcript ORDER BY created_at DESC LIMIT 5;"
# List files in server data directory
docker compose -f docker-compose.selfhosted.yml exec server ls -la /app/data/
```

View File

@@ -0,0 +1,373 @@
# Self-Hosted Production Deployment
Deploy Reflector on a single server with everything running in Docker. Transcription, diarization, and translation use specialized ML models (Whisper/Parakeet, Pyannote); only summarization and topic detection require an LLM.
> For a detailed walkthrough of how the setup script and infrastructure work under the hood, see [How the Self-Hosted Setup Works](selfhosted-architecture.md).
## Prerequisites
### Hardware
- **With GPU**: Linux server with NVIDIA GPU (8GB+ VRAM recommended), 16GB+ RAM, 50GB+ disk
- **CPU-only**: 8+ cores, 32GB+ RAM (transcription is slower but works)
- Disk space for ML models (~2GB on first run) + audio storage
### Software
- Docker Engine 24+ with Compose V2
- NVIDIA drivers + `nvidia-container-toolkit` (GPU modes only)
- `curl`, `openssl` (usually pre-installed)
### Accounts & Credentials (depending on options)
**Always recommended:**
- **HuggingFace token** — For downloading pyannote speaker diarization models. Get one at https://huggingface.co/settings/tokens and accept the model licenses:
- https://huggingface.co/pyannote/speaker-diarization-3.1
- https://huggingface.co/pyannote/segmentation-3.0
- The setup script will prompt for this. If skipped, diarization falls back to a public model bundle (may be less reliable).
**LLM for summarization & topic detection (pick one):**
- **With `--ollama-gpu` or `--ollama-cpu`**: Nothing extra — Ollama runs locally and pulls the model automatically
- **Without `--ollama-*`**: An OpenAI-compatible LLM API key and endpoint. Examples:
- OpenAI: `LLM_URL=https://api.openai.com/v1`, `LLM_API_KEY=sk-...`, `LLM_MODEL=gpt-4o-mini`
- Anthropic, Together, Groq, or any OpenAI-compatible API
- A self-managed vLLM or Ollama instance elsewhere on the network
**Object storage (pick one):**
- **With `--garage`**: Nothing extra — Garage (local S3-compatible storage) is auto-configured by the script
- **Without `--garage`**: S3-compatible storage credentials. The script will prompt for these, or you can pre-fill `server/.env`. Options include:
- **AWS S3**: Access Key ID, Secret Access Key, bucket name, region
- **MinIO**: Same credentials + `TRANSCRIPT_STORAGE_AWS_ENDPOINT_URL=http://your-minio:9000`
- **Any S3-compatible provider** (Backblaze B2, Cloudflare R2, DigitalOcean Spaces, etc.): same fields + custom endpoint URL
**Optional add-ons (configure after initial setup):**
- **Daily.co** (live meeting rooms): Requires a Daily.co account (https://www.daily.co/), API key, subdomain, and an AWS S3 bucket + IAM Role for recording storage. See [Enabling Daily.co Live Rooms](#enabling-dailyco-live-rooms) below.
- **Authentik** (user authentication): Requires an Authentik instance with an OAuth2/OIDC application configured for Reflector. See [Enabling Authentication](#enabling-authentication-authentik) below.
## Quick Start
```bash
git clone https://github.com/Monadical-SAS/reflector.git
cd reflector
# GPU + local Ollama LLM + local Garage storage + Caddy SSL (with domain):
./scripts/setup-selfhosted.sh --gpu --ollama-gpu --garage --caddy --domain reflector.example.com
# Same but without a domain (self-signed cert, access via IP):
./scripts/setup-selfhosted.sh --gpu --ollama-gpu --garage --caddy
# CPU-only (same, but slower):
./scripts/setup-selfhosted.sh --cpu --ollama-cpu --garage --caddy
# Build from source instead of pulling prebuilt images:
./scripts/setup-selfhosted.sh --gpu --ollama-gpu --garage --caddy --build
```
That's it. The script generates env files, secrets, starts all containers, waits for health checks, and prints the URL.
## Specialized Models (Required)
Pick `--gpu` or `--cpu`. This determines how **transcription, diarization, and translation** run:
| Flag | What it does | Requires |
|------|-------------|----------|
| `--gpu` | NVIDIA GPU acceleration for ML models | NVIDIA GPU + drivers + `nvidia-container-toolkit` |
| `--cpu` | CPU-only (slower but works without GPU) | 8+ cores, 32GB+ RAM recommended |
## Local LLM (Optional)
Optionally add `--ollama-gpu` or `--ollama-cpu` for a **local Ollama instance** that handles summarization and topic detection. If omitted, configure an external OpenAI-compatible LLM in `server/.env`.
| Flag | What it does | Requires |
|------|-------------|----------|
| `--ollama-gpu` | Local Ollama with NVIDIA GPU acceleration | NVIDIA GPU |
| `--ollama-cpu` | Local Ollama on CPU only | Nothing extra |
| `--llm-model MODEL` | Choose which Ollama model to download (default: `qwen2.5:14b`) | `--ollama-gpu` or `--ollama-cpu` |
| *(omitted)* | User configures external LLM (OpenAI, Anthropic, etc.) | LLM API key |
### Choosing an Ollama model
The default model is `qwen2.5:14b` (~9GB download, good multilingual support and summary quality). Override with `--llm-model`:
```bash
# Default (qwen2.5:14b)
./scripts/setup-selfhosted.sh --gpu --ollama-gpu --garage --caddy
# Mistral — good balance of speed and quality (~4.1GB)
./scripts/setup-selfhosted.sh --gpu --ollama-gpu --llm-model mistral --garage --caddy
# Phi-4 — smaller and faster (~9.1GB)
./scripts/setup-selfhosted.sh --gpu --ollama-gpu --llm-model phi4 --garage --caddy
# Llama 3.3 70B — best quality, needs 48GB+ RAM or GPU VRAM (~43GB)
./scripts/setup-selfhosted.sh --gpu --ollama-gpu --llm-model llama3.3:70b --garage --caddy
# Gemma 2 9B (~5.4GB)
./scripts/setup-selfhosted.sh --gpu --ollama-gpu --llm-model gemma2 --garage --caddy
# DeepSeek R1 8B — reasoning model, verbose but thorough summaries (~4.9GB)
./scripts/setup-selfhosted.sh --gpu --ollama-gpu --llm-model deepseek-r1:8b --garage --caddy
```
Browse all available models at https://ollama.com/library.
### Recommended combinations
- **`--gpu --ollama-gpu`**: Best for servers with NVIDIA GPU. Fully self-contained, no external API keys needed.
- **`--cpu --ollama-cpu`**: No GPU available but want everything self-contained. Slower but works.
- **`--gpu --ollama-cpu`**: GPU for transcription, CPU for LLM. Saves GPU VRAM for ML models.
- **`--gpu`**: Have NVIDIA GPU but prefer a cloud LLM (faster/better summaries with GPT-4, Claude, etc.).
- **`--cpu`**: No GPU, prefer cloud LLM. Slowest transcription but best summary quality.
## Other Optional Flags
| Flag | What it does |
|------|-------------|
| `--garage` | Starts Garage (local S3-compatible storage). Auto-configures bucket, keys, and env vars. |
| `--caddy` | Starts Caddy reverse proxy on ports 80/443 with self-signed cert. |
| `--domain DOMAIN` | Use a real domain with Let's Encrypt auto-HTTPS (implies `--caddy`). Requires DNS A record pointing to this server and ports 80/443 open. |
| `--build` | Build backend (server, worker, beat) and frontend (web) Docker images from source instead of pulling prebuilt images from the registry. Useful for development or when running a version with local changes. |
Without `--garage`, you **must** provide S3-compatible credentials (the script will prompt interactively or you can pre-fill `server/.env`).
Without `--caddy` or `--domain`, no ports are exposed. Point your own reverse proxy at `web:3000` (frontend) and `server:1250` (API).
**Using a domain (recommended for production):** Point a DNS A record at your server's IP, then pass `--domain your.domain.com`. Caddy will automatically obtain and renew a Let's Encrypt certificate. Ports 80 and 443 must be open.
**Without a domain:** `--caddy` alone uses a self-signed certificate. Browsers will show a security warning that must be accepted.
## What the Script Does
1. **Prerequisites check** — Docker, NVIDIA GPU (if needed), compose file exists
2. **Generate secrets**`SECRET_KEY`, `NEXTAUTH_SECRET` via `openssl rand`
3. **Generate `server/.env`** — From template, sets infrastructure defaults, configures LLM based on mode, enables `PUBLIC_MODE`
4. **Generate `www/.env`** — Auto-detects server IP, sets URLs
5. **Storage setup** — Either initializes Garage (bucket, keys, permissions) or prompts for external S3 credentials
6. **Caddyfile** — Generates domain-specific (Let's Encrypt) or IP-specific (self-signed) configuration
7. **Build & start** — Always builds GPU/CPU model image from source. With `--build`, also builds backend and frontend from source; otherwise pulls prebuilt images from the registry
8. **Health checks** — Waits for each service, pulls Ollama model if needed, warns about missing LLM config
> For a deeper dive into each step, see [How the Self-Hosted Setup Works](selfhosted-architecture.md).
## Configuration Reference
### Server Environment (`server/.env`)
| Variable | Description | Default |
|----------|-------------|---------|
| `DATABASE_URL` | PostgreSQL connection | Auto-set (Docker internal) |
| `REDIS_HOST` | Redis hostname | Auto-set (`redis`) |
| `SECRET_KEY` | App secret | Auto-generated |
| `AUTH_BACKEND` | Authentication method | `none` |
| `PUBLIC_MODE` | Allow unauthenticated access | `true` |
| `WEBRTC_HOST` | IP advertised in WebRTC ICE candidates | Auto-detected (server IP) |
| `TRANSCRIPT_URL` | Specialized model endpoint | `http://transcription:8000` |
| `LLM_URL` | OpenAI-compatible LLM endpoint | Auto-set for Ollama modes |
| `LLM_API_KEY` | LLM API key | `not-needed` for Ollama |
| `LLM_MODEL` | LLM model name | `qwen2.5:14b` for Ollama (override with `--llm-model`) |
| `TRANSCRIPT_STORAGE_BACKEND` | Storage backend | `aws` |
| `TRANSCRIPT_STORAGE_AWS_*` | S3 credentials | Auto-set for Garage |
### Frontend Environment (`www/.env`)
| Variable | Description | Default |
|----------|-------------|---------|
| `SITE_URL` | Public-facing URL | Auto-detected |
| `API_URL` | API URL (browser-side) | Same as SITE_URL |
| `SERVER_API_URL` | API URL (server-side) | `http://server:1250` |
| `NEXTAUTH_SECRET` | Auth secret | Auto-generated |
| `FEATURE_REQUIRE_LOGIN` | Require authentication | `false` |
## Storage Options
### Garage (Recommended for Self-Hosted)
Use `--garage` flag. The script automatically:
- Generates `data/garage.toml` with a random RPC secret
- Starts the Garage container
- Creates the `reflector-media` bucket
- Creates an access key with read/write permissions
- Writes all S3 credentials to `server/.env`
### External S3 (AWS, MinIO, etc.)
Don't use `--garage`. The script will prompt for:
- Access Key ID
- Secret Access Key
- Bucket Name
- Region
- Endpoint URL (for non-AWS like MinIO)
Or pre-fill in `server/.env`:
```env
TRANSCRIPT_STORAGE_BACKEND=aws
TRANSCRIPT_STORAGE_AWS_ACCESS_KEY_ID=your-key
TRANSCRIPT_STORAGE_AWS_SECRET_ACCESS_KEY=your-secret
TRANSCRIPT_STORAGE_AWS_BUCKET_NAME=reflector-media
TRANSCRIPT_STORAGE_AWS_REGION=us-east-1
# For non-AWS S3 (MinIO, etc.):
TRANSCRIPT_STORAGE_AWS_ENDPOINT_URL=http://minio:9000
```
## Enabling Authentication (Authentik)
By default, authentication is disabled (`AUTH_BACKEND=none`, `FEATURE_REQUIRE_LOGIN=false`). To enable:
1. Deploy an Authentik instance (see [Authentik docs](https://goauthentik.io/docs/installation))
2. Create an OAuth2/OIDC application for Reflector
3. Update `server/.env`:
```env
AUTH_BACKEND=jwt
AUTH_JWT_AUDIENCE=your-client-id
```
4. Update `www/.env`:
```env
FEATURE_REQUIRE_LOGIN=true
AUTHENTIK_ISSUER=https://authentik.example.com/application/o/reflector
AUTHENTIK_REFRESH_TOKEN_URL=https://authentik.example.com/application/o/token/
AUTHENTIK_CLIENT_ID=your-client-id
AUTHENTIK_CLIENT_SECRET=your-client-secret
```
5. Restart: `docker compose -f docker-compose.selfhosted.yml down && ./scripts/setup-selfhosted.sh <same-flags>`
## Enabling Daily.co Live Rooms
Daily.co enables real-time meeting rooms with automatic recording and transcription.
1. Create a [Daily.co](https://www.daily.co/) account
2. Add to `server/.env`:
```env
DEFAULT_VIDEO_PLATFORM=daily
DAILY_API_KEY=your-daily-api-key
DAILY_SUBDOMAIN=your-subdomain
DAILY_WEBHOOK_SECRET=your-webhook-secret
DAILYCO_STORAGE_AWS_BUCKET_NAME=reflector-dailyco
DAILYCO_STORAGE_AWS_REGION=us-east-1
DAILYCO_STORAGE_AWS_ROLE_ARN=arn:aws:iam::role/DailyCoAccess
```
3. Restart the server: `docker compose -f docker-compose.selfhosted.yml restart server worker`
## Enabling Real Domain with Let's Encrypt
By default, Caddy uses self-signed certificates. For a real domain:
1. Point your domain's DNS to your server's IP
2. Ensure ports 80 and 443 are open
3. Edit `Caddyfile`:
```
reflector.example.com {
handle /v1/* {
reverse_proxy server:1250
}
handle /health {
reverse_proxy server:1250
}
handle {
reverse_proxy web:3000
}
}
```
4. Update `www/.env`:
```env
SITE_URL=https://reflector.example.com
NEXTAUTH_URL=https://reflector.example.com
API_URL=https://reflector.example.com
```
5. Restart Caddy: `docker compose -f docker-compose.selfhosted.yml restart caddy web`
## Troubleshooting
### Check service status
```bash
docker compose -f docker-compose.selfhosted.yml ps
```
### View logs for a specific service
```bash
docker compose -f docker-compose.selfhosted.yml logs server --tail 50
docker compose -f docker-compose.selfhosted.yml logs gpu --tail 50
docker compose -f docker-compose.selfhosted.yml logs web --tail 50
```
### GPU service taking too long
First start downloads ~1-2GB of ML models. Check progress:
```bash
docker compose -f docker-compose.selfhosted.yml logs gpu -f
```
### Server exits immediately
Usually a database migration issue. Check:
```bash
docker compose -f docker-compose.selfhosted.yml logs server --tail 50
```
### Caddy certificate issues
For self-signed certs, your browser will warn. Click Advanced > Proceed.
For Let's Encrypt, ensure ports 80/443 are open and DNS is pointed correctly.
### Summaries/topics not generating
Check LLM configuration:
```bash
grep LLM_ server/.env
```
If you didn't use `--ollama-gpu` or `--ollama-cpu`, you must set `LLM_URL`, `LLM_API_KEY`, and `LLM_MODEL`.
### Health check from inside containers
```bash
docker compose -f docker-compose.selfhosted.yml exec server curl http://localhost:1250/health
docker compose -f docker-compose.selfhosted.yml exec gpu curl http://localhost:8000/docs
```
## Updating
```bash
# Option A: Pull latest prebuilt images and restart
docker compose -f docker-compose.selfhosted.yml down
./scripts/setup-selfhosted.sh <same-flags-as-before>
# Option B: Build from source (after git pull) and restart
git pull
docker compose -f docker-compose.selfhosted.yml down
./scripts/setup-selfhosted.sh <same-flags-as-before> --build
# Rebuild only the GPU/CPU model image (picks up model updates)
docker compose -f docker-compose.selfhosted.yml build gpu # or cpu
```
The setup script is idempotent — it won't overwrite existing secrets or env vars that are already set.
## Architecture Overview
```
┌─────────┐
Internet ────────>│ Caddy │ :80/:443
└────┬────┘
┌────────────┼────────────┐
│ │ │
v v │
┌─────────┐ ┌─────────┐ │
│ web │ │ server │ │
│ :3000 │ │ :1250 │ │
└─────────┘ └────┬────┘ │
│ │
┌────┴────┐ │
│ worker │ │
│ beat │ │
└────┬────┘ │
│ │
┌──────────────┼────────────┤
│ │ │
v v v
┌───────────┐ ┌─────────┐ ┌─────────┐
│transcription│ │postgres │ │ redis │
│(gpu/cpu) │ │ :5432 │ │ :6379 │
│ :8000 │ └─────────┘ └─────────┘
└───────────┘
┌─────┴─────┐ ┌─────────┐
│ ollama │ │ garage │
│ (optional)│ │(optional│
│ :11434 │ │ S3) │
└───────────┘ └─────────┘
```
All services communicate over Docker's internal network. Only Caddy (if enabled) exposes ports to the internet.

View File

@@ -0,0 +1,39 @@
FROM python:3.12-slim
ENV PYTHONUNBUFFERED=1 \
UV_LINK_MODE=copy \
UV_NO_CACHE=1
WORKDIR /tmp
RUN --mount=type=cache,target=/var/cache/apt,sharing=locked \
--mount=type=cache,target=/var/lib/apt,sharing=locked \
apt-get update \
&& apt-get install -y \
ffmpeg \
curl \
ca-certificates \
gnupg \
wget
ADD https://astral.sh/uv/install.sh /uv-installer.sh
RUN sh /uv-installer.sh && rm /uv-installer.sh
ENV PATH="/root/.local/bin/:$PATH"
RUN mkdir -p /app
WORKDIR /app
COPY pyproject.toml uv.lock /app/
COPY ./app /app/app
COPY ./main.py /app/
COPY ./runserver.sh /app/
# prevent uv failing with too many open files on big cpus
ENV UV_CONCURRENT_INSTALLS=16
# first install
RUN --mount=type=cache,target=/root/.cache/uv \
uv sync --compile-bytecode --locked
EXPOSE 8000
CMD ["sh", "/app/runserver.sh"]

View File

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

View File

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

10
node_modules/.yarn-integrity generated vendored Normal file
View File

@@ -0,0 +1,10 @@
{
"systemParams": "darwin-x64-83",
"modulesFolders": [],
"flags": [],
"linkedModules": [],
"topLevelPatterns": [],
"lockfileEntries": {},
"files": [],
"artifacts": {}
}

14
scripts/garage.toml Normal file
View File

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

View File

@@ -0,0 +1,87 @@
#!/usr/bin/env bash
#
# Install Docker Engine + Compose plugin on Ubuntu.
# Ubuntu's default repos don't include docker-compose-plugin, so we add Docker's official repo.
#
# Usage:
# ./scripts/install-docker-ubuntu.sh
#
# Requires: root or sudo
#
set -euo pipefail
SCRIPT_DIR="$(cd "$(dirname "${BASH_SOURCE[0]}")" && pwd)"
# --- Colors ---
RED='\033[0;31m'
GREEN='\033[0;32m'
YELLOW='\033[1;33m'
CYAN='\033[0;36m'
NC='\033[0m'
info() { echo -e "${CYAN}==>${NC} $*"; }
ok() { echo -e "${GREEN}${NC} $*"; }
warn() { echo -e "${YELLOW} !${NC} $*"; }
err() { echo -e "${RED}${NC} $*" >&2; }
# Use sudo if available and not root; otherwise run directly
if [[ $(id -u) -eq 0 ]]; then
MAYBE_SUDO=""
elif command -v sudo &>/dev/null; then
MAYBE_SUDO="sudo "
else
err "Need root. Run as root or install sudo: apt install sudo"
exit 1
fi
# Check Ubuntu
if [[ ! -f /etc/os-release ]]; then
err "Cannot detect OS. This script is for Ubuntu."
exit 1
fi
source /etc/os-release
if [[ "${ID:-}" != "ubuntu" ]] && [[ "${ID_LIKE:-}" != *"ubuntu"* ]]; then
err "This script is for Ubuntu. Detected: ${ID:-unknown}"
exit 1
fi
info "Adding Docker's official repository..."
${MAYBE_SUDO}apt update
${MAYBE_SUDO}apt install -y ca-certificates curl
${MAYBE_SUDO}install -m 0755 -d /etc/apt/keyrings
${MAYBE_SUDO}rm -f /etc/apt/sources.list.d/docker.list /etc/apt/sources.list.d/docker.sources
curl -fsSL https://download.docker.com/linux/ubuntu/gpg | ${MAYBE_SUDO}tee /etc/apt/keyrings/docker.asc > /dev/null
${MAYBE_SUDO}chmod a+r /etc/apt/keyrings/docker.asc
CODENAME="$(. /etc/os-release && echo "${UBUNTU_CODENAME:-${VERSION_CODENAME:-}}")"
[[ -z "$CODENAME" ]] && { err "Could not detect Ubuntu version codename."; exit 1; }
${MAYBE_SUDO}tee /etc/apt/sources.list.d/docker.sources > /dev/null <<EOF
Types: deb
URIs: https://download.docker.com/linux/ubuntu
Suites: ${CODENAME}
Components: stable
Signed-By: /etc/apt/keyrings/docker.asc
EOF
info "Installing Docker Engine and Compose plugin..."
${MAYBE_SUDO}apt update
${MAYBE_SUDO}apt install -y docker-ce docker-ce-cli containerd.io docker-buildx-plugin docker-compose-plugin
if [[ -d /run/systemd/system ]]; then
info "Enabling and starting Docker..."
${MAYBE_SUDO}systemctl enable --now docker
else
err "No systemd. This script requires Ubuntu with systemd (e.g. DigitalOcean droplet)."
exit 1
fi
DOCKER_USER="${SUDO_USER:-${USER:-root}}"
if [[ "$DOCKER_USER" != "root" ]]; then
info "Adding $DOCKER_USER to docker group..."
${MAYBE_SUDO}usermod -aG docker "$DOCKER_USER"
fi
ok "Docker installed successfully."
echo ""
echo " Log out and back in (or run: newgrp docker) so the group change takes effect."
echo " Then verify with: docker compose version"
echo ""

945
scripts/setup-selfhosted.sh Executable file
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#!/usr/bin/env bash
#
# Self-hosted production setup for Reflector.
# Single script to configure and launch everything on one server.
#
# Usage:
# ./scripts/setup-selfhosted.sh <--gpu|--cpu> [--ollama-gpu|--ollama-cpu] [--llm-model MODEL] [--garage] [--caddy] [--domain DOMAIN] [--build]
#
# Specialized models (pick ONE — required):
# --gpu NVIDIA GPU for transcription/diarization/translation
# --cpu CPU-only for transcription/diarization/translation (slower)
#
# Local LLM (optional — for summarization & topic detection):
# --ollama-gpu Local Ollama with NVIDIA GPU acceleration
# --ollama-cpu Local Ollama on CPU only
# --llm-model MODEL Ollama model to use (default: qwen2.5:14b)
# (If omitted, configure an external OpenAI-compatible LLM in server/.env)
#
# Optional flags:
# --garage Use Garage for local S3-compatible storage
# --caddy Enable Caddy reverse proxy with auto-SSL
# --domain DOMAIN Use a real domain for Caddy (enables Let's Encrypt auto-HTTPS)
# Requires: DNS pointing to this server + ports 80/443 open
# Without --domain: Caddy uses self-signed cert for IP access
# --build Build backend and frontend images from source instead of pulling
#
# Examples:
# ./scripts/setup-selfhosted.sh --gpu --ollama-gpu --garage --caddy
# ./scripts/setup-selfhosted.sh --gpu --ollama-gpu --garage --caddy --domain reflector.example.com
# ./scripts/setup-selfhosted.sh --cpu --ollama-cpu --garage --caddy
# ./scripts/setup-selfhosted.sh --gpu --ollama-gpu --llm-model mistral --garage --caddy
# ./scripts/setup-selfhosted.sh --gpu --garage --caddy
# ./scripts/setup-selfhosted.sh --cpu
#
# Idempotent — safe to re-run at any time.
#
set -euo pipefail
SCRIPT_DIR="$(cd "$(dirname "${BASH_SOURCE[0]}")" && pwd)"
ROOT_DIR="$(cd "$SCRIPT_DIR/.." && pwd)"
COMPOSE_FILE="$ROOT_DIR/docker-compose.selfhosted.yml"
SERVER_ENV="$ROOT_DIR/server/.env"
WWW_ENV="$ROOT_DIR/www/.env"
OLLAMA_MODEL="qwen2.5:14b"
OS="$(uname -s)"
# --- Colors ---
RED='\033[0;31m'
GREEN='\033[0;32m'
YELLOW='\033[1;33m'
CYAN='\033[0;36m'
NC='\033[0m'
info() { echo -e "${CYAN}==>${NC} $*"; }
ok() { echo -e "${GREEN}${NC} $*"; }
warn() { echo -e "${YELLOW} !${NC} $*"; }
err() { echo -e "${RED}${NC} $*" >&2; }
# --- Helpers ---
dump_diagnostics() {
local failed_svc="${1:-}"
echo ""
err "========== DIAGNOSTICS =========="
err "Container status:"
compose_cmd ps -a --format "table {{.Name}}\t{{.Status}}" 2>/dev/null || true
echo ""
local stopped
stopped=$(compose_cmd ps -a --format '{{.Name}}\t{{.Status}}' 2>/dev/null \
| grep -iv 'up\|running' | awk -F'\t' '{print $1}' || true)
for c in $stopped; do
err "--- Logs for $c (exited/unhealthy) ---"
docker logs --tail 30 "$c" 2>&1 || true
echo ""
done
if [[ -n "$failed_svc" ]]; then
err "--- Logs for $failed_svc (last 40) ---"
compose_cmd logs "$failed_svc" --tail 40 2>&1 || true
fi
err "================================="
}
trap 'dump_diagnostics' ERR
detect_lan_ip() {
case "$OS" in
Darwin)
for iface in en0 en1 en2 en3; do
local ip
ip=$(ipconfig getifaddr "$iface" 2>/dev/null || true)
if [[ -n "$ip" ]]; then
echo "$ip"
return
fi
done
;;
Linux)
ip route get 1.1.1.1 2>/dev/null | sed -n 's/.*src \([^ ]*\).*/\1/p'
return
;;
esac
echo ""
}
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_get() {
local file="$1" key="$2"
grep "^${key}=" "$file" 2>/dev/null | head -1 | cut -d= -f2-
}
env_set() {
local file="$1" key="$2" value="$3"
if env_has_key "$file" "$key"; then
if [[ "$OS" == "Darwin" ]]; then
sed -i '' "s|^${key}=.*|${key}=${value}|" "$file"
else
sed -i "s|^${key}=.*|${key}=${value}|" "$file"
fi
else
echo "${key}=${value}" >> "$file"
fi
}
compose_cmd() {
local profiles=""
for p in "${COMPOSE_PROFILES[@]}"; do
profiles="$profiles --profile $p"
done
docker compose -f "$COMPOSE_FILE" $profiles "$@"
}
# Compose command with only garage profile (for garage-only operations before full stack start)
compose_garage_cmd() {
docker compose -f "$COMPOSE_FILE" --profile garage "$@"
}
# --- Parse arguments ---
MODEL_MODE="" # gpu or cpu (required, mutually exclusive)
OLLAMA_MODE="" # ollama-gpu or ollama-cpu (optional)
USE_GARAGE=false
USE_CADDY=false
CUSTOM_DOMAIN="" # optional domain for Let's Encrypt HTTPS
BUILD_IMAGES=false # build backend/frontend from source
SKIP_NEXT=false
ARGS=("$@")
for i in "${!ARGS[@]}"; do
if [[ "$SKIP_NEXT" == "true" ]]; then
SKIP_NEXT=false
continue
fi
arg="${ARGS[$i]}"
case "$arg" in
--gpu)
[[ -n "$MODEL_MODE" ]] && { err "Cannot combine --gpu and --cpu. Pick one."; exit 1; }
MODEL_MODE="gpu" ;;
--cpu)
[[ -n "$MODEL_MODE" ]] && { err "Cannot combine --gpu and --cpu. Pick one."; exit 1; }
MODEL_MODE="cpu" ;;
--ollama-gpu)
[[ -n "$OLLAMA_MODE" ]] && { err "Cannot combine --ollama-gpu and --ollama-cpu. Pick one."; exit 1; }
OLLAMA_MODE="ollama-gpu" ;;
--ollama-cpu)
[[ -n "$OLLAMA_MODE" ]] && { err "Cannot combine --ollama-gpu and --ollama-cpu. Pick one."; exit 1; }
OLLAMA_MODE="ollama-cpu" ;;
--llm-model)
next_i=$((i + 1))
if [[ $next_i -ge ${#ARGS[@]} ]] || [[ "${ARGS[$next_i]}" == --* ]]; then
err "--llm-model requires a model name (e.g. --llm-model mistral)"
exit 1
fi
OLLAMA_MODEL="${ARGS[$next_i]}"
SKIP_NEXT=true ;;
--garage) USE_GARAGE=true ;;
--caddy) USE_CADDY=true ;;
--build) BUILD_IMAGES=true ;;
--domain)
next_i=$((i + 1))
if [[ $next_i -ge ${#ARGS[@]} ]] || [[ "${ARGS[$next_i]}" == --* ]]; then
err "--domain requires a domain name (e.g. --domain reflector.example.com)"
exit 1
fi
CUSTOM_DOMAIN="${ARGS[$next_i]}"
USE_CADDY=true # --domain implies --caddy
SKIP_NEXT=true ;;
*)
err "Unknown argument: $arg"
err "Usage: $0 <--gpu|--cpu> [--ollama-gpu|--ollama-cpu] [--llm-model MODEL] [--garage] [--caddy] [--domain DOMAIN] [--build]"
exit 1
;;
esac
done
if [[ -z "$MODEL_MODE" ]]; then
err "No model mode specified. You must choose --gpu or --cpu."
err ""
err "Usage: $0 <--gpu|--cpu> [--ollama-gpu|--ollama-cpu] [--llm-model MODEL] [--garage] [--caddy] [--domain DOMAIN] [--build]"
err ""
err "Specialized models (required):"
err " --gpu NVIDIA GPU for transcription/diarization/translation"
err " --cpu CPU-only (slower but works without GPU)"
err ""
err "Local LLM (optional):"
err " --ollama-gpu Local Ollama with GPU (for summarization/topics)"
err " --ollama-cpu Local Ollama on CPU (for summarization/topics)"
err " --llm-model MODEL Ollama model to download (default: qwen2.5:14b)"
err " (omit --ollama-* for external OpenAI-compatible LLM)"
err ""
err "Other options:"
err " --garage Local S3-compatible storage (Garage)"
err " --caddy Caddy reverse proxy with self-signed cert"
err " --domain DOMAIN Use a real domain with Let's Encrypt HTTPS (implies --caddy)"
err " --build Build backend/frontend images from source instead of pulling"
exit 1
fi
# Build profiles list — one profile per feature
COMPOSE_PROFILES=("$MODEL_MODE")
[[ -n "$OLLAMA_MODE" ]] && COMPOSE_PROFILES+=("$OLLAMA_MODE")
[[ "$USE_GARAGE" == "true" ]] && COMPOSE_PROFILES+=("garage")
[[ "$USE_CADDY" == "true" ]] && COMPOSE_PROFILES+=("caddy")
# Derived flags
NEEDS_NVIDIA=false
[[ "$MODEL_MODE" == "gpu" ]] && NEEDS_NVIDIA=true
[[ "$OLLAMA_MODE" == "ollama-gpu" ]] && NEEDS_NVIDIA=true
USES_OLLAMA=false
OLLAMA_SVC=""
[[ "$OLLAMA_MODE" == "ollama-gpu" ]] && USES_OLLAMA=true && OLLAMA_SVC="ollama"
[[ "$OLLAMA_MODE" == "ollama-cpu" ]] && USES_OLLAMA=true && OLLAMA_SVC="ollama-cpu"
# Human-readable mode string for display
MODE_DISPLAY="$MODEL_MODE"
[[ -n "$OLLAMA_MODE" ]] && MODE_DISPLAY="$MODEL_MODE + $OLLAMA_MODE"
# =========================================================
# Step 0: Prerequisites
# =========================================================
step_prerequisites() {
info "Step 0: Checking prerequisites"
# Docker
if ! docker compose version 2>/dev/null | grep -qi compose; then
err "Docker Compose V2 not found."
err "Install Docker with Compose V2: https://docs.docker.com/engine/install/"
exit 1
fi
if ! docker info &>/dev/null; then
err "Docker daemon not running."
exit 1
fi
ok "Docker + Compose V2 ready"
# NVIDIA GPU check
if [[ "$NEEDS_NVIDIA" == "true" ]]; then
if ! command -v nvidia-smi &>/dev/null || ! nvidia-smi &>/dev/null; then
err "NVIDIA GPU required (model=$MODEL_MODE, ollama=$OLLAMA_MODE) but nvidia-smi failed."
err "Install NVIDIA drivers and nvidia-container-toolkit."
exit 1
fi
ok "NVIDIA GPU detected"
fi
# Compose file
if [[ ! -f "$COMPOSE_FILE" ]]; then
err "docker-compose.selfhosted.yml not found at $COMPOSE_FILE"
err "Run this script from the repo root: ./scripts/setup-selfhosted.sh"
exit 1
fi
ok "Prerequisites OK (models=$MODEL_MODE, ollama=$OLLAMA_MODE, garage=$USE_GARAGE, caddy=$USE_CADDY)"
}
# =========================================================
# Step 1: Generate secrets
# =========================================================
step_secrets() {
info "Step 1: Generating secrets"
# These are used in later steps — generate once, reuse
if [[ -f "$SERVER_ENV" ]] && env_has_key "$SERVER_ENV" "SECRET_KEY"; then
SECRET_KEY=$(env_get "$SERVER_ENV" "SECRET_KEY")
if [[ "$SECRET_KEY" != "changeme"* ]]; then
ok "SECRET_KEY already set"
else
SECRET_KEY=$(openssl rand -hex 32)
fi
else
SECRET_KEY=$(openssl rand -hex 32)
fi
if [[ -f "$WWW_ENV" ]] && env_has_key "$WWW_ENV" "NEXTAUTH_SECRET"; then
NEXTAUTH_SECRET=$(env_get "$WWW_ENV" "NEXTAUTH_SECRET")
if [[ "$NEXTAUTH_SECRET" != "changeme"* ]]; then
ok "NEXTAUTH_SECRET already set"
else
NEXTAUTH_SECRET=$(openssl rand -hex 32)
fi
else
NEXTAUTH_SECRET=$(openssl rand -hex 32)
fi
ok "Secrets ready"
}
# =========================================================
# Step 2: Generate server/.env
# =========================================================
step_server_env() {
info "Step 2: Generating server/.env"
if [[ -f "$SERVER_ENV" ]]; then
ok "server/.env already exists — ensuring required vars"
else
cp "$ROOT_DIR/server/.env.selfhosted.example" "$SERVER_ENV"
ok "Created server/.env from template"
fi
# Core infrastructure
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 "$SERVER_ENV" "SECRET_KEY" "$SECRET_KEY"
env_set "$SERVER_ENV" "AUTH_BACKEND" "none"
env_set "$SERVER_ENV" "PUBLIC_MODE" "true"
# Public-facing URLs
local server_base_url
if [[ -n "$CUSTOM_DOMAIN" ]]; then
server_base_url="https://$CUSTOM_DOMAIN"
elif [[ "$USE_CADDY" == "true" ]]; then
if [[ -n "$PRIMARY_IP" ]]; then
server_base_url="https://$PRIMARY_IP"
else
server_base_url="https://localhost"
fi
else
if [[ -n "$PRIMARY_IP" ]]; then
server_base_url="http://$PRIMARY_IP"
else
server_base_url="http://localhost:1250"
fi
fi
env_set "$SERVER_ENV" "BASE_URL" "$server_base_url"
env_set "$SERVER_ENV" "CORS_ORIGIN" "$server_base_url"
# WebRTC: advertise host IP in ICE candidates so browsers can reach the server
if [[ -n "$PRIMARY_IP" ]]; then
env_set "$SERVER_ENV" "WEBRTC_HOST" "$PRIMARY_IP"
fi
# Specialized models (always via gpu/cpu container aliased as "transcription")
env_set "$SERVER_ENV" "TRANSCRIPT_BACKEND" "modal"
env_set "$SERVER_ENV" "TRANSCRIPT_URL" "http://transcription:8000"
env_set "$SERVER_ENV" "TRANSCRIPT_MODAL_API_KEY" "selfhosted"
env_set "$SERVER_ENV" "DIARIZATION_ENABLED" "true"
env_set "$SERVER_ENV" "DIARIZATION_BACKEND" "modal"
env_set "$SERVER_ENV" "DIARIZATION_URL" "http://transcription:8000"
env_set "$SERVER_ENV" "TRANSLATION_BACKEND" "modal"
env_set "$SERVER_ENV" "TRANSLATE_URL" "http://transcription:8000"
# HuggingFace token for gated models (pyannote diarization)
# Written to root .env so docker compose picks it up for gpu/cpu containers
local root_env="$ROOT_DIR/.env"
local current_hf_token="${HF_TOKEN:-}"
if [[ -f "$root_env" ]] && env_has_key "$root_env" "HF_TOKEN"; then
current_hf_token=$(env_get "$root_env" "HF_TOKEN")
fi
if [[ -z "$current_hf_token" ]]; then
echo ""
warn "HF_TOKEN not set. Diarization will use a public model fallback."
warn "For best results, get a token at https://huggingface.co/settings/tokens"
warn "and accept pyannote licenses at https://huggingface.co/pyannote/speaker-diarization-3.1"
read -rp " HuggingFace token (or press Enter to skip): " current_hf_token
fi
if [[ -n "$current_hf_token" ]]; then
touch "$root_env"
env_set "$root_env" "HF_TOKEN" "$current_hf_token"
export HF_TOKEN="$current_hf_token"
ok "HF_TOKEN configured"
else
touch "$root_env"
env_set "$root_env" "HF_TOKEN" ""
ok "HF_TOKEN skipped (using public model fallback)"
fi
# LLM configuration
if [[ "$USES_OLLAMA" == "true" ]]; then
local llm_host="$OLLAMA_SVC"
env_set "$SERVER_ENV" "LLM_URL" "http://${llm_host}:11434/v1"
env_set "$SERVER_ENV" "LLM_MODEL" "$OLLAMA_MODEL"
env_set "$SERVER_ENV" "LLM_API_KEY" "not-needed"
ok "LLM configured for local Ollama ($llm_host, model=$OLLAMA_MODEL)"
else
# Check if user already configured LLM
local current_llm_url=""
if env_has_key "$SERVER_ENV" "LLM_URL"; then
current_llm_url=$(env_get "$SERVER_ENV" "LLM_URL")
fi
if [[ -z "$current_llm_url" ]] || [[ "$current_llm_url" == "http://host.docker.internal"* ]]; then
warn "LLM not configured. Summarization and topic detection will NOT work."
warn "Edit server/.env and set LLM_URL, LLM_API_KEY, LLM_MODEL"
warn "Example: LLM_URL=https://api.openai.com/v1 LLM_MODEL=gpt-4o-mini"
else
ok "LLM already configured: $current_llm_url"
fi
fi
ok "server/.env ready"
}
# =========================================================
# Step 3: Generate www/.env
# =========================================================
step_www_env() {
info "Step 3: Generating www/.env"
if [[ -f "$WWW_ENV" ]]; then
ok "www/.env already exists — ensuring required vars"
else
cp "$ROOT_DIR/www/.env.selfhosted.example" "$WWW_ENV"
ok "Created www/.env from template"
fi
# Public-facing URL for frontend
local base_url
if [[ -n "$CUSTOM_DOMAIN" ]]; then
base_url="https://$CUSTOM_DOMAIN"
elif [[ "$USE_CADDY" == "true" ]]; then
if [[ -n "$PRIMARY_IP" ]]; then
base_url="https://$PRIMARY_IP"
else
base_url="https://localhost"
fi
else
# No Caddy — user's proxy handles SSL. Use http for now, they'll override.
if [[ -n "$PRIMARY_IP" ]]; then
base_url="http://$PRIMARY_IP"
else
base_url="http://localhost"
fi
fi
env_set "$WWW_ENV" "SITE_URL" "$base_url"
env_set "$WWW_ENV" "NEXTAUTH_URL" "$base_url"
env_set "$WWW_ENV" "NEXTAUTH_SECRET" "$NEXTAUTH_SECRET"
env_set "$WWW_ENV" "API_URL" "$base_url"
env_set "$WWW_ENV" "WEBSOCKET_URL" "auto"
env_set "$WWW_ENV" "SERVER_API_URL" "http://server:1250"
env_set "$WWW_ENV" "KV_URL" "redis://redis:6379"
env_set "$WWW_ENV" "FEATURE_REQUIRE_LOGIN" "false"
ok "www/.env ready (URL=$base_url)"
}
# =========================================================
# Step 4: Storage setup
# =========================================================
step_storage() {
info "Step 4: Storage setup"
if [[ "$USE_GARAGE" == "true" ]]; then
step_garage
else
step_external_s3
fi
}
step_garage() {
info "Configuring Garage (local S3)"
# Generate garage.toml from template
local garage_toml="$ROOT_DIR/scripts/garage.toml"
local garage_runtime="$ROOT_DIR/data/garage.toml"
mkdir -p "$ROOT_DIR/data"
if [[ -d "$garage_runtime" ]]; then
rm -rf "$garage_runtime"
fi
if [[ ! -f "$garage_runtime" ]]; then
local rpc_secret
rpc_secret=$(openssl rand -hex 32)
sed "s|__GARAGE_RPC_SECRET__|${rpc_secret}|" "$garage_toml" > "$garage_runtime"
ok "Generated data/garage.toml"
else
ok "data/garage.toml already exists"
fi
# Start garage container only
compose_garage_cmd up -d garage
# Wait for admin API (port 3903 exposed to host for health checks)
local garage_ready=false
for i in $(seq 1 30); do
if curl -sf http://localhost:3903/metrics > /dev/null 2>&1; then
garage_ready=true
break
fi
echo -ne "\r Waiting for Garage admin API... ($i/30)"
sleep 2
done
echo ""
if [[ "$garage_ready" != "true" ]]; then
err "Garage not responding. Check: docker compose logs garage"
exit 1
fi
# Layout
local node_id
node_id=$(compose_garage_cmd exec -T garage /garage node id -q 2>/dev/null | tr -d '[:space:]')
local layout_status
layout_status=$(compose_garage_cmd exec -T garage /garage layout show 2>&1 || true)
if echo "$layout_status" | grep -q "No nodes"; then
compose_garage_cmd exec -T garage /garage layout assign "$node_id" -c 1G -z dc1
compose_garage_cmd exec -T garage /garage layout apply --version 1
fi
# Bucket
if ! compose_garage_cmd exec -T garage /garage bucket info reflector-media &>/dev/null; then
compose_garage_cmd exec -T garage /garage bucket create reflector-media
fi
# Key
local created_key=false
if compose_garage_cmd exec -T garage /garage key info reflector &>/dev/null; then
ok "Key 'reflector' already exists"
else
KEY_OUTPUT=$(compose_garage_cmd exec -T garage /garage key create reflector)
created_key=true
fi
# Permissions
compose_garage_cmd exec -T garage /garage bucket allow reflector-media --read --write --key reflector
# Write S3 credentials to server/.env
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 [[ "$created_key" == "true" ]]; then
local key_id key_secret
key_id=$(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" "$key_secret"
fi
ok "Garage storage ready"
}
step_external_s3() {
info "Checking external S3 configuration"
env_set "$SERVER_ENV" "TRANSCRIPT_STORAGE_BACKEND" "aws"
local s3_vars=("TRANSCRIPT_STORAGE_AWS_ACCESS_KEY_ID" "TRANSCRIPT_STORAGE_AWS_SECRET_ACCESS_KEY" "TRANSCRIPT_STORAGE_AWS_BUCKET_NAME" "TRANSCRIPT_STORAGE_AWS_REGION")
local missing=()
for var in "${s3_vars[@]}"; do
if ! env_has_key "$SERVER_ENV" "$var" || [[ -z "$(env_get "$SERVER_ENV" "$var")" ]]; then
missing+=("$var")
fi
done
if [[ ${#missing[@]} -gt 0 ]]; then
warn "S3 storage is REQUIRED. The following vars are missing in server/.env:"
for var in "${missing[@]}"; do
warn " $var"
done
echo ""
info "Enter S3 credentials (or press Ctrl+C to abort and edit server/.env manually):"
echo ""
for var in "${missing[@]}"; do
local prompt_label
case "$var" in
*ACCESS_KEY_ID) prompt_label="Access Key ID" ;;
*SECRET_ACCESS_KEY) prompt_label="Secret Access Key" ;;
*BUCKET_NAME) prompt_label="Bucket Name" ;;
*REGION) prompt_label="Region (e.g. us-east-1)" ;;
esac
local value=""
while [[ -z "$value" ]]; do
read -rp " $prompt_label: " value
done
env_set "$SERVER_ENV" "$var" "$value"
done
# Optional: endpoint URL for non-AWS S3
echo ""
read -rp " S3 Endpoint URL (leave empty for AWS, or enter for MinIO/etc.): " endpoint_url
if [[ -n "$endpoint_url" ]]; then
env_set "$SERVER_ENV" "TRANSCRIPT_STORAGE_AWS_ENDPOINT_URL" "$endpoint_url"
fi
fi
ok "S3 storage configured"
}
# =========================================================
# Step 5: Caddyfile
# =========================================================
step_caddyfile() {
if [[ "$USE_CADDY" != "true" ]]; then
return
fi
info "Step 5: Caddyfile setup"
local caddyfile="$ROOT_DIR/Caddyfile"
if [[ -d "$caddyfile" ]]; then
rm -rf "$caddyfile"
fi
if [[ -n "$CUSTOM_DOMAIN" ]]; then
# Real domain: Caddy auto-provisions Let's Encrypt certificate
cat > "$caddyfile" << CADDYEOF
# Generated by setup-selfhosted.sh — Let's Encrypt HTTPS for $CUSTOM_DOMAIN
$CUSTOM_DOMAIN {
handle /v1/* {
reverse_proxy server:1250
}
handle /health {
reverse_proxy server:1250
}
handle {
reverse_proxy web:3000
}
}
CADDYEOF
ok "Created Caddyfile for $CUSTOM_DOMAIN (Let's Encrypt auto-HTTPS)"
elif [[ -n "$PRIMARY_IP" ]]; then
# No domain, IP only: catch-all :443 with self-signed cert
# (IP connections don't send SNI, so we can't match by address)
cat > "$caddyfile" << CADDYEOF
# Generated by setup-selfhosted.sh — self-signed cert for IP access
:443 {
tls internal
handle /v1/* {
reverse_proxy server:1250
}
handle /health {
reverse_proxy server:1250
}
handle {
reverse_proxy web:3000
}
}
CADDYEOF
ok "Created Caddyfile for $PRIMARY_IP (catch-all :443 with self-signed cert)"
elif [[ ! -f "$caddyfile" ]]; then
cp "$ROOT_DIR/Caddyfile.selfhosted.example" "$caddyfile"
ok "Created Caddyfile from template"
else
ok "Caddyfile already exists"
fi
}
# =========================================================
# Step 6: Start services
# =========================================================
step_services() {
info "Step 6: Starting Docker services"
# Build GPU/CPU image from source (always needed — no prebuilt image)
local build_svc="$MODEL_MODE"
info "Building $build_svc image (first build downloads ML models, may take a while)..."
compose_cmd build "$build_svc"
ok "$build_svc image built"
# Build or pull backend and frontend images
if [[ "$BUILD_IMAGES" == "true" ]]; then
info "Building backend image from source (server, worker, beat)..."
compose_cmd build server worker beat
ok "Backend image built"
info "Building frontend image from source..."
compose_cmd build web
ok "Frontend image built"
else
info "Pulling latest backend and frontend images..."
compose_cmd pull server web || warn "Pull failed — using cached images"
fi
# Start all services
compose_cmd up -d
ok "Containers started"
# Quick sanity check
sleep 3
local exited
exited=$(compose_cmd ps -a --format '{{.Name}} {{.Status}}' 2>/dev/null \
| grep -i 'exit' || true)
if [[ -n "$exited" ]]; then
warn "Some containers exited immediately:"
echo "$exited" | while read -r line; do warn " $line"; done
dump_diagnostics
fi
}
# =========================================================
# Step 7: Health checks
# =========================================================
step_health() {
info "Step 7: Health checks"
# Specialized model service (gpu or cpu)
local model_svc="$MODEL_MODE"
info "Waiting for $model_svc service (first start downloads ~1GB of models)..."
local model_ok=false
for i in $(seq 1 120); do
if curl -sf http://localhost:8000/docs > /dev/null 2>&1; then
model_ok=true
break
fi
echo -ne "\r Waiting for $model_svc service... ($i/120)"
sleep 5
done
echo ""
if [[ "$model_ok" == "true" ]]; then
ok "$model_svc service healthy (transcription + diarization)"
else
warn "$model_svc service not ready yet — it will keep loading in the background"
warn "Check with: docker compose -f docker-compose.selfhosted.yml logs $model_svc"
fi
# Ollama (if applicable)
if [[ "$USES_OLLAMA" == "true" ]]; then
info "Waiting for Ollama service..."
local ollama_ok=false
for i in $(seq 1 60); do
if curl -sf http://localhost:11434/api/tags > /dev/null 2>&1; then
ollama_ok=true
break
fi
echo -ne "\r Waiting for Ollama... ($i/60)"
sleep 3
done
echo ""
if [[ "$ollama_ok" == "true" ]]; then
ok "Ollama service healthy"
# Pull model if not present
if compose_cmd exec -T "$OLLAMA_SVC" ollama list 2>/dev/null | awk '{print $1}' | grep -qxF "$OLLAMA_MODEL"; then
ok "Model $OLLAMA_MODEL already pulled"
else
info "Pulling model $OLLAMA_MODEL (this may take a while)..."
compose_cmd exec -T "$OLLAMA_SVC" ollama pull "$OLLAMA_MODEL"
ok "Model $OLLAMA_MODEL pulled"
fi
else
warn "Ollama not ready yet. Check: docker compose logs $OLLAMA_SVC"
fi
fi
# Server API
info "Waiting for Server API (first run includes database migrations)..."
local server_ok=false
for i in $(seq 1 90); do
local svc_status
svc_status=$(compose_cmd ps server --format '{{.Status}}' 2>/dev/null || true)
if [[ -z "$svc_status" ]] || echo "$svc_status" | grep -qi 'exit'; then
echo ""
err "Server container exited unexpectedly"
dump_diagnostics server
exit 1
fi
if curl -sf http://localhost:1250/health > /dev/null 2>&1; then
server_ok=true
break
fi
echo -ne "\r Waiting for Server API... ($i/90)"
sleep 5
done
echo ""
if [[ "$server_ok" == "true" ]]; then
ok "Server API healthy"
else
err "Server API not ready after ~7 minutes"
dump_diagnostics server
exit 1
fi
# Frontend
info "Waiting for Frontend..."
local web_ok=false
for i in $(seq 1 30); do
if curl -sf http://localhost:3000 > /dev/null 2>&1; then
web_ok=true
break
fi
echo -ne "\r Waiting for Frontend... ($i/30)"
sleep 3
done
echo ""
if [[ "$web_ok" == "true" ]]; then
ok "Frontend healthy"
else
warn "Frontend not responding. Check: docker compose logs web"
fi
# Caddy
if [[ "$USE_CADDY" == "true" ]]; then
sleep 2
if curl -sfk "https://localhost" > /dev/null 2>&1; then
ok "Caddy proxy healthy"
else
warn "Caddy proxy not responding. Check: docker compose logs caddy"
fi
fi
# LLM warning for non-Ollama modes
if [[ "$USES_OLLAMA" == "false" ]]; then
local llm_url=""
if env_has_key "$SERVER_ENV" "LLM_URL"; then
llm_url=$(env_get "$SERVER_ENV" "LLM_URL")
fi
if [[ -z "$llm_url" ]]; then
echo ""
warn "LLM is not configured. Transcription will work, but:"
warn " - Summaries will NOT be generated"
warn " - Topics will NOT be detected"
warn " - Titles will NOT be auto-generated"
warn "Configure in server/.env: LLM_URL, LLM_API_KEY, LLM_MODEL"
fi
fi
}
# =========================================================
# Main
# =========================================================
main() {
echo ""
echo "=========================================="
echo " Reflector — Self-Hosted Production Setup"
echo "=========================================="
echo ""
echo " Models: $MODEL_MODE"
echo " LLM: ${OLLAMA_MODE:-external}"
echo " Garage: $USE_GARAGE"
echo " Caddy: $USE_CADDY"
[[ -n "$CUSTOM_DOMAIN" ]] && echo " Domain: $CUSTOM_DOMAIN"
[[ "$BUILD_IMAGES" == "true" ]] && echo " Build: from source"
echo ""
# Detect primary IP
PRIMARY_IP=""
if [[ "$OS" == "Linux" ]]; then
PRIMARY_IP=$(hostname -I 2>/dev/null | awk '{print $1}' || true)
if [[ "$PRIMARY_IP" == "127."* ]] || [[ -z "$PRIMARY_IP" ]]; then
PRIMARY_IP=$(ip -4 route get 1 2>/dev/null | sed -n 's/.*src \([0-9.]*\).*/\1/p' || true)
fi
fi
# Touch env files so compose doesn't complain about missing env_file
mkdir -p "$ROOT_DIR/data"
touch "$SERVER_ENV" "$WWW_ENV"
# Ensure garage.toml exists if garage profile is active (compose needs it for volume mount)
if [[ "$USE_GARAGE" == "true" ]]; then
local garage_runtime="$ROOT_DIR/data/garage.toml"
if [[ ! -f "$garage_runtime" ]]; then
local rpc_secret
rpc_secret=$(openssl rand -hex 32)
sed "s|__GARAGE_RPC_SECRET__|${rpc_secret}|" "$ROOT_DIR/scripts/garage.toml" > "$garage_runtime"
fi
fi
step_prerequisites
echo ""
step_secrets
echo ""
step_server_env
echo ""
step_www_env
echo ""
step_storage
echo ""
step_caddyfile
echo ""
step_services
echo ""
step_health
echo ""
echo "=========================================="
echo -e " ${GREEN}Reflector is running!${NC}"
echo "=========================================="
echo ""
if [[ "$USE_CADDY" == "true" ]]; then
if [[ -n "$CUSTOM_DOMAIN" ]]; then
echo " App: https://$CUSTOM_DOMAIN"
echo " API: https://$CUSTOM_DOMAIN/v1/"
elif [[ -n "$PRIMARY_IP" ]]; then
echo " App: https://$PRIMARY_IP (accept self-signed cert in browser)"
echo " API: https://$PRIMARY_IP/v1/"
echo " Local: https://localhost"
else
echo " App: https://localhost (accept self-signed cert in browser)"
echo " API: https://localhost/v1/"
fi
else
echo " No Caddy — point your reverse proxy at:"
echo " Frontend: web:3000 (or localhost:3000 from host)"
echo " API: server:1250 (or localhost:1250 from host)"
fi
echo ""
echo " Models: $MODEL_MODE (transcription/diarization/translation)"
[[ "$USE_GARAGE" == "true" ]] && echo " Storage: Garage (local S3)"
[[ "$USE_GARAGE" != "true" ]] && echo " Storage: External S3"
[[ "$USES_OLLAMA" == "true" ]] && echo " LLM: Ollama ($OLLAMA_MODEL) for summarization/topics"
[[ "$USES_OLLAMA" != "true" ]] && echo " LLM: External (configure in server/.env)"
echo ""
echo " To stop: docker compose -f docker-compose.selfhosted.yml down"
echo " To re-run: ./scripts/setup-selfhosted.sh $*"
echo ""
}
main "$@"

675
scripts/setup-standalone.sh Executable file
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#!/usr/bin/env bash
#
# Standalone local development setup for Reflector.
# Takes a fresh clone to a working instance — no cloud accounts, no API keys.
#
# Usage:
# ./scripts/setup-standalone.sh
#
# Idempotent — safe to re-run at any time.
#
set -euo pipefail
SCRIPT_DIR="$(cd "$(dirname "${BASH_SOURCE[0]}")" && pwd)"
ROOT_DIR="$(cd "$SCRIPT_DIR/.." && pwd)"
SERVER_ENV="$ROOT_DIR/server/.env"
WWW_ENV="$ROOT_DIR/www/.env.local"
MODEL="${LLM_MODEL:-qwen2.5:14b}"
OLLAMA_PORT="${OLLAMA_PORT:-11434}"
OS="$(uname -s)"
# --- Colors ---
RED='\033[0;31m'
GREEN='\033[0;32m'
YELLOW='\033[1;33m'
CYAN='\033[0;36m'
NC='\033[0m'
info() { echo -e "${CYAN}==>${NC} $*"; }
ok() { echo -e "${GREEN}${NC} $*"; }
warn() { echo -e "${YELLOW} !${NC} $*"; }
err() { echo -e "${RED}${NC} $*" >&2; }
# --- Helpers ---
dump_diagnostics() {
local failed_svc="${1:-}"
echo ""
err "========== DIAGNOSTICS =========="
err "Container status:"
compose_cmd ps -a --format "table {{.Name}}\t{{.Status}}" 2>/dev/null || true
echo ""
# Show logs for any container that exited
local stopped
stopped=$(compose_cmd ps -a --format '{{.Name}}\t{{.Status}}' 2>/dev/null \
| grep -iv 'up\|running' | awk -F'\t' '{print $1}' || true)
for c in $stopped; do
err "--- Logs for $c (exited/unhealthy) ---"
docker logs --tail 30 "$c" 2>&1 || true
echo ""
done
# If a specific service failed, always show its logs
if [[ -n "$failed_svc" ]]; then
err "--- Logs for $failed_svc (last 40) ---"
compose_cmd logs "$failed_svc" --tail 40 2>&1 || true
echo ""
# Try health check from inside the container as extra signal
err "--- Internal health check ($failed_svc) ---"
compose_cmd exec -T "$failed_svc" \
curl -sf http://localhost:1250/health 2>&1 || echo "(not reachable internally either)"
fi
err "================================="
}
trap 'dump_diagnostics' ERR
# Get the image ID for a compose service (works even when containers are not running).
svc_image_id() {
local svc="$1"
# Extract image name from compose config YAML, fall back to <project>-<service>
local img_name
img_name=$(compose_cmd config 2>/dev/null \
| sed -n "/^ ${svc}:/,/^ [a-z]/p" | grep '^\s*image:' | awk '{print $2}')
img_name="${img_name:-reflector-$svc}"
docker images -q "$img_name" 2>/dev/null | head -1
}
# Ensure images with build contexts are up-to-date.
# Docker layer cache makes this fast (~seconds) when source hasn't changed.
rebuild_images() {
local svc
for svc in web cpu; do
local old_id
old_id=$(svc_image_id "$svc")
old_id="${old_id:-<none>}"
info "Building $svc..."
compose_cmd build "$svc"
local new_id
new_id=$(svc_image_id "$svc")
if [[ "$old_id" == "$new_id" ]]; then
ok "$svc unchanged (${new_id:0:12})"
else
ok "$svc rebuilt (${old_id:0:12} -> ${new_id:0:12})"
fi
done
}
detect_lan_ip() {
# Returns the host's LAN IP — used for WebRTC ICE candidate rewriting.
case "$OS" in
Darwin)
# Try common interfaces: en0 (Wi-Fi), en1 (Ethernet)
for iface in en0 en1 en2 en3; do
local ip
ip=$(ipconfig getifaddr "$iface" 2>/dev/null || true)
if [[ -n "$ip" ]]; then
echo "$ip"
return
fi
done
;;
Linux)
ip route get 1.1.1.1 2>/dev/null | sed -n 's/.*src \([^ ]*\).*/\1/p'
return
;;
esac
# Fallback — empty means "not detected"
echo ""
}
wait_for_url() {
local url="$1" label="$2" retries="${3:-30}" interval="${4:-2}"
for i in $(seq 1 "$retries"); do
if curl -sf "$url" > /dev/null 2>&1; then
return 0
fi
echo -ne "\r Waiting for $label... ($i/$retries)"
sleep "$interval"
done
echo ""
err "$label not responding at $url after $retries attempts"
return 1
}
env_has_key() {
local file="$1" key="$2"
grep -q "^${key}=" "$file" 2>/dev/null
}
env_set() {
local file="$1" key="$2" value="$3"
if env_has_key "$file" "$key"; then
# Replace existing value (portable sed)
if [[ "$OS" == "Darwin" ]]; then
sed -i '' "s|^${key}=.*|${key}=${value}|" "$file"
else
sed -i "s|^${key}=.*|${key}=${value}|" "$file"
fi
else
echo "${key}=${value}" >> "$file"
fi
}
resolve_symlink() {
local file="$1"
if [[ -L "$file" ]]; then
warn "$(basename "$file") is a symlink — creating standalone copy"
cp -L "$file" "$file.tmp"
rm "$file"
mv "$file.tmp" "$file"
fi
}
compose_cmd() {
local compose_files="-f $ROOT_DIR/docker-compose.standalone.yml"
if [[ "$OS" == "Linux" ]] && [[ -n "${OLLAMA_PROFILE:-}" ]]; then
docker compose $compose_files --profile "$OLLAMA_PROFILE" "$@"
else
docker compose $compose_files "$@"
fi
}
# =========================================================
# Step 1: LLM / Ollama
# =========================================================
step_llm() {
info "Step 1: LLM setup (Ollama + $MODEL)"
case "$OS" in
Darwin)
if ! command -v ollama &> /dev/null; then
err "Ollama not found. Install it:"
err " brew install ollama"
err " # or https://ollama.com/download"
exit 1
fi
# Start if not running
if ! curl -sf "http://localhost:$OLLAMA_PORT/api/tags" > /dev/null 2>&1; then
info "Starting Ollama..."
ollama serve &
disown
fi
wait_for_url "http://localhost:$OLLAMA_PORT/api/tags" "Ollama"
echo ""
# Pull model if not already present
if ollama list 2>/dev/null | awk '{print $1}' | grep -qxF "$MODEL"; then
ok "Model $MODEL already pulled"
else
info "Pulling model $MODEL (this may take a while)..."
ollama pull "$MODEL"
fi
LLM_URL_VALUE="http://host.docker.internal:$OLLAMA_PORT/v1"
;;
Linux)
if command -v nvidia-smi &> /dev/null && nvidia-smi > /dev/null 2>&1; then
ok "NVIDIA GPU detected — using ollama-gpu profile"
OLLAMA_PROFILE="ollama-gpu"
OLLAMA_SVC="ollama"
LLM_URL_VALUE="http://ollama:$OLLAMA_PORT/v1"
else
warn "No NVIDIA GPU — using ollama-cpu profile"
OLLAMA_PROFILE="ollama-cpu"
OLLAMA_SVC="ollama-cpu"
LLM_URL_VALUE="http://ollama-cpu:$OLLAMA_PORT/v1"
fi
info "Starting Ollama container..."
compose_cmd up -d
wait_for_url "http://localhost:$OLLAMA_PORT/api/tags" "Ollama"
echo ""
# Pull model inside container
if compose_cmd exec "$OLLAMA_SVC" ollama list 2>/dev/null | awk '{print $1}' | grep -qxF "$MODEL"; then
ok "Model $MODEL already pulled"
else
info "Pulling model $MODEL inside container (this may take a while)..."
compose_cmd exec "$OLLAMA_SVC" ollama pull "$MODEL"
fi
;;
*)
err "Unsupported OS: $OS"
exit 1
;;
esac
ok "LLM ready ($MODEL via Ollama)"
}
# =========================================================
# Step 2: Generate server/.env
# =========================================================
step_server_env() {
info "Step 2: Generating server/.env"
resolve_symlink "$SERVER_ENV"
if [[ -f "$SERVER_ENV" ]]; then
ok "server/.env already exists — ensuring standalone vars"
else
cat > "$SERVER_ENV" << 'ENVEOF'
# Generated by setup-standalone.sh — standalone local development
# Source of truth for settings: server/reflector/settings.py
ENVEOF
ok "Created server/.env"
fi
# Ensure all standalone-critical vars (appends if missing, replaces if present)
env_set "$SERVER_ENV" "DATABASE_URL" "postgresql+asyncpg://reflector:reflector@postgres:5432/reflector"
env_set "$SERVER_ENV" "REDIS_HOST" "redis"
env_set "$SERVER_ENV" "CELERY_BROKER_URL" "redis://redis:6379/1"
env_set "$SERVER_ENV" "CELERY_RESULT_BACKEND" "redis://redis:6379/1"
env_set "$SERVER_ENV" "AUTH_BACKEND" "none"
env_set "$SERVER_ENV" "PUBLIC_MODE" "true"
# TRANSCRIPT_BACKEND, TRANSCRIPT_URL, DIARIZATION_BACKEND, DIARIZATION_URL
# are set via docker-compose.standalone.yml `environment:` overrides — not written here
# so we don't clobber the user's server/.env for non-standalone use.
env_set "$SERVER_ENV" "TRANSLATION_BACKEND" "passthrough"
env_set "$SERVER_ENV" "LLM_URL" "$LLM_URL_VALUE"
env_set "$SERVER_ENV" "LLM_MODEL" "$MODEL"
env_set "$SERVER_ENV" "LLM_API_KEY" "not-needed"
# WebRTC: detect LAN IP for ICE candidate rewriting (bridge networking)
local lan_ip
lan_ip=$(detect_lan_ip)
if [[ -n "$lan_ip" ]]; then
env_set "$SERVER_ENV" "WEBRTC_HOST" "$lan_ip"
ok "WebRTC host IP: $lan_ip"
else
warn "Could not detect LAN IP — WebRTC recording from other devices may not work"
warn "Set WEBRTC_HOST=<your-lan-ip> in server/.env manually"
fi
ok "Standalone vars set (LLM_URL=$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"
mkdir -p "$ROOT_DIR/data"
if [[ -d "$GARAGE_TOML_RUNTIME" ]]; then
rm -rf "$GARAGE_TOML_RUNTIME"
fi
if [[ ! -f "$GARAGE_TOML_RUNTIME" ]]; then
RPC_SECRET=$(openssl rand -hex 32)
sed "s|__GARAGE_RPC_SECRET__|${RPC_SECRET}|" "$GARAGE_TOML" > "$GARAGE_TOML_RUNTIME"
fi
compose_cmd up -d garage
# Use /metrics for readiness — /health returns 503 until layout is applied
if ! wait_for_url "http://localhost:3903/metrics" "Garage admin API"; then
echo ""
err "Garage container logs:"
compose_cmd logs garage --tail 30 2>&1 || true
exit 1
fi
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
# Caddyfile.standalone.example serves API at /v1, /health — use base URL
if [[ -n "${PRIMARY_IP:-}" ]]; then
BASE_URL="https://$PRIMARY_IP:3043"
else
BASE_URL="https://localhost:3043"
fi
env_set "$WWW_ENV" "SITE_URL" "$BASE_URL"
env_set "$WWW_ENV" "NEXTAUTH_URL" "$BASE_URL"
env_set "$WWW_ENV" "NEXTAUTH_SECRET" "standalone-dev-secret-not-for-production"
env_set "$WWW_ENV" "API_URL" "$BASE_URL"
env_set "$WWW_ENV" "WEBSOCKET_URL" "auto"
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 3043 3000 1250 5432 6379 3900 3903; do
local pids
pids=$(lsof -ti :"$port" 2>/dev/null || true)
for pid in $pids; do
local pname
pname=$(ps -p "$pid" -o comm= 2>/dev/null || true)
# OrbStack and Docker Desktop own port forwarding — not real conflicts
if [[ "$pname" == *"OrbStack"* ]] || [[ "$pname" == *"com.docker"* ]] || [[ "$pname" == *"vpnkit"* ]]; then
continue
fi
warn "Port $port already in use by PID $pid ($pname)"
warn "Kill it with: lsof -ti :$port | xargs kill"
ports_ok=false
done
done
if [[ "$ports_ok" == "false" ]]; then
warn "Port conflicts detected — Docker containers may not be reachable"
warn "Continuing anyway (services will start but may be shadowed)"
fi
# Rebuild images if source has changed (Docker layer cache makes this fast when unchanged)
rebuild_images
# server runs alembic migrations on startup automatically (see runserver.sh)
compose_cmd up -d postgres redis garage cpu server worker beat web caddy
ok "Containers started"
# Quick sanity check — catch containers that exit immediately (bad image, missing file, etc.)
sleep 3
local exited
exited=$(compose_cmd ps -a --format '{{.Name}} {{.Status}}' 2>/dev/null \
| grep -i 'exit' || true)
if [[ -n "$exited" ]]; then
warn "Some containers exited immediately:"
echo "$exited" | while read -r line; do warn " $line"; done
dump_diagnostics
fi
info "Server is running migrations (alembic upgrade head)..."
}
# =========================================================
# Step 6: Health checks
# =========================================================
step_health() {
info "Step 6: Health checks"
# CPU service may take a while on first start (model download + load).
# No host port exposed — check via docker exec.
info "Waiting for CPU service (first start downloads ~1GB of models)..."
local cpu_ok=false
for i in $(seq 1 120); do
if compose_cmd exec -T cpu curl -sf http://localhost:8000/docs > /dev/null 2>&1; then
cpu_ok=true
break
fi
echo -ne "\r Waiting for CPU service... ($i/120)"
sleep 5
done
echo ""
if [[ "$cpu_ok" == "true" ]]; then
ok "CPU service healthy (transcription + diarization)"
else
warn "CPU service not ready yet — it will keep loading in the background"
warn "Check with: docker compose logs cpu"
fi
# Server may take a long time on first run — alembic migrations run before uvicorn starts.
# Use docker exec so this works regardless of network_mode or port mapping.
info "Waiting for Server API (first run includes database migrations)..."
local server_ok=false
for i in $(seq 1 90); do
# Check if container is still running
local svc_status
svc_status=$(compose_cmd ps server --format '{{.Status}}' 2>/dev/null || true)
if [[ -z "$svc_status" ]] || echo "$svc_status" | grep -qi 'exit'; then
echo ""
err "Server container exited unexpectedly"
dump_diagnostics server
exit 1
fi
# Health check from inside container (avoids host networking issues)
if compose_cmd exec -T server curl -sf http://localhost:1250/health > /dev/null 2>&1; then
server_ok=true
break
fi
echo -ne "\r Waiting for Server API... ($i/90)"
sleep 5
done
echo ""
if [[ "$server_ok" == "true" ]]; then
ok "Server API healthy"
else
err "Server API not ready after ~7 minutes"
dump_diagnostics server
exit 1
fi
wait_for_url "http://localhost:3000" "Frontend" 90 3
echo ""
ok "Frontend responding"
# Caddy reverse proxy (self-signed TLS — curl needs -k)
if curl -sfk "https://localhost:3043" > /dev/null 2>&1; then
ok "Caddy proxy healthy (https://localhost:3043)"
else
warn "Caddy proxy not responding on https://localhost:3043"
warn "Check with: docker compose logs caddy"
fi
# 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 $ROOT_DIR"
err "Run this script from the repo root: ./scripts/setup-standalone.sh"
exit 1
fi
# Docker: Compose plugin, buildx, and daemon. On Ubuntu, auto-install if missing.
docker_ready() {
docker compose version 2>/dev/null | grep -qi compose \
&& docker buildx version &>/dev/null \
&& docker info &>/dev/null
}
if ! docker_ready; then
RAN_INSTALL=false
if [[ "$OS" == "Linux" ]] && [[ -f /etc/os-release ]] && (source /etc/os-release 2>/dev/null; [[ "${ID:-}" == "ubuntu" || "${ID_LIKE:-}" == *"ubuntu"* ]]); then
info "Docker not ready. Running install-docker-ubuntu.sh..."
"$SCRIPT_DIR/install-docker-ubuntu.sh" || true
RAN_INSTALL=true
[[ -d /run/systemd/system ]] && command -v systemctl &>/dev/null && systemctl start docker 2>/dev/null || true
sleep 2
fi
if ! docker_ready; then
# Docker may be installed but current shell lacks docker group (needs newgrp)
if [[ "$RAN_INSTALL" == "true" ]] && [[ $(id -u) -ne 0 ]] && command -v sg &>/dev/null && getent group docker &>/dev/null; then
info "Re-running with docker group..."
exec sg docker -c "$(printf '%q' "$0" && printf ' %q' "$@")"
fi
if [[ "$OS" == "Darwin" ]]; then
err "Docker not ready. Install Docker Desktop or OrbStack."
elif [[ "$OS" == "Linux" ]]; then
err "Docker not ready. Run: ./scripts/install-docker-ubuntu.sh"
err "Then run: newgrp docker (or log out and back in), then run this script again."
else
err "Docker not ready. Install Docker with Compose V2 and buildx."
fi
exit 1
fi
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"
# Ensure garage.toml exists before any compose up (step_llm starts all services including garage)
GARAGE_TOML="$ROOT_DIR/scripts/garage.toml"
GARAGE_TOML_RUNTIME="$ROOT_DIR/data/garage.toml"
mkdir -p "$ROOT_DIR/data"
if [[ -d "$GARAGE_TOML_RUNTIME" ]]; then
rm -rf "$GARAGE_TOML_RUNTIME"
fi
if [[ ! -f "$GARAGE_TOML_RUNTIME" ]]; then
RPC_SECRET=$(openssl rand -hex 32)
sed "s|__GARAGE_RPC_SECRET__|${RPC_SECRET}|" "$GARAGE_TOML" > "$GARAGE_TOML_RUNTIME"
fi
# Remove containers that may have bad mounts (was directory); force recreate
compose_cmd rm -f -s garage caddy 2>/dev/null || true
# Detect primary IP for droplet (used for Caddyfile, step_www_env, success message)
PRIMARY_IP=""
if [[ "$OS" == "Linux" ]]; then
PRIMARY_IP=$(hostname -I 2>/dev/null | awk '{print $1}' || true)
if [[ "$PRIMARY_IP" == "127."* ]] || [[ -z "$PRIMARY_IP" ]]; then
PRIMARY_IP=$(ip -4 route get 1 2>/dev/null | sed -n 's/.*src \([0-9.]*\).*/\1/p' || true)
fi
fi
# Ensure Caddyfile exists before any compose up (step_llm starts caddy)
# On droplet: explicit IP + localhost so Caddy provisions cert at startup (avoids on_demand/SNI issues)
CADDYFILE="$ROOT_DIR/Caddyfile"
if [[ -d "$CADDYFILE" ]]; then
rm -rf "$CADDYFILE"
fi
if [[ -n "$PRIMARY_IP" ]]; then
cat > "$CADDYFILE" << CADDYEOF
# Generated by setup-standalone.sh — explicit IP for droplet (provisions cert at startup)
https://$PRIMARY_IP, localhost {
tls internal
handle /v1/* {
reverse_proxy server:1250
}
handle /health {
reverse_proxy server:1250
}
handle {
reverse_proxy web:3000
}
}
CADDYEOF
ok "Created Caddyfile for $PRIMARY_IP and localhost"
elif [[ ! -f "$CADDYFILE" ]]; then
cp "$ROOT_DIR/Caddyfile.standalone.example" "$CADDYFILE"
fi
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 ""
if [[ -n "$PRIMARY_IP" ]]; then
echo " App: https://$PRIMARY_IP:3043 (accept self-signed cert in browser)"
echo " API: https://$PRIMARY_IP:3043/v1/"
echo " Local: https://localhost:3043"
else
echo " App: https://localhost:3043 (accept self-signed cert in browser)"
echo " API: https://localhost:3043/v1/"
fi
echo ""
echo " To stop: docker compose down"
echo " To re-run: ./scripts/setup-standalone.sh"
echo ""
}
main "$@"

View File

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

View File

@@ -0,0 +1,112 @@
# =======================================================
# Reflector Self-Hosted Production — Backend Configuration
# Generated by: ./scripts/setup-selfhosted.sh
# Reference: server/reflector/settings.py
# =======================================================
# =======================================================
# Database & Infrastructure
# Pre-filled for Docker internal networking (docker-compose.selfhosted.yml)
# =======================================================
DATABASE_URL=postgresql+asyncpg://reflector:reflector@postgres:5432/reflector
REDIS_HOST=redis
REDIS_PORT=6379
CELERY_BROKER_URL=redis://redis:6379/1
CELERY_RESULT_BACKEND=redis://redis:6379/1
# Secret key — auto-generated by setup script
# Generate manually with: openssl rand -hex 32
SECRET_KEY=changeme-generate-a-secure-random-string
# =======================================================
# Authentication
# Disabled by default. Enable Authentik for multi-user access.
# See docsv2/selfhosted-production.md for setup instructions.
# =======================================================
AUTH_BACKEND=none
# AUTH_BACKEND=jwt
# AUTH_JWT_AUDIENCE=
# =======================================================
# Specialized Models (Transcription, Diarization, Translation)
# These run in the gpu/cpu container — NOT an LLM.
# The "modal" backend means "HTTP API client" — it talks to
# the self-hosted container, not Modal.com cloud.
# =======================================================
TRANSCRIPT_BACKEND=modal
TRANSCRIPT_URL=http://transcription:8000
TRANSCRIPT_MODAL_API_KEY=selfhosted
DIARIZATION_ENABLED=true
DIARIZATION_BACKEND=modal
DIARIZATION_URL=http://transcription:8000
TRANSLATION_BACKEND=modal
TRANSLATE_URL=http://transcription:8000
# HuggingFace token — optional, for gated models (e.g. pyannote).
# Falls back to public S3 model bundle if not set.
# HF_TOKEN=hf_xxxxx
# =======================================================
# LLM for Summarization & Topic Detection
# Only summaries and topics use an LLM. Everything else
# (transcription, diarization, translation) uses specialized models above.
#
# Supports any OpenAI-compatible endpoint.
# Auto-configured by setup script if using --ollama-gpu or --ollama-cpu.
# For --gpu or --cpu modes, you MUST configure an external LLM.
# =======================================================
# --- Option A: External OpenAI-compatible API ---
# LLM_URL=https://api.openai.com/v1
# LLM_API_KEY=sk-your-api-key
# LLM_MODEL=gpt-4o-mini
# --- Option B: Local Ollama (auto-set by --ollama-gpu/--ollama-cpu) ---
# LLM_URL=http://ollama:11434/v1
# LLM_API_KEY=not-needed
# LLM_MODEL=llama3.1
LLM_CONTEXT_WINDOW=16000
# =======================================================
# S3 Storage (REQUIRED)
# Where to store audio files and transcripts.
#
# Option A: Use --garage flag (auto-configured by setup script)
# Option B: Any S3-compatible endpoint (AWS, MinIO, etc.)
# Set TRANSCRIPT_STORAGE_AWS_ENDPOINT_URL for non-AWS endpoints.
# =======================================================
TRANSCRIPT_STORAGE_BACKEND=aws
TRANSCRIPT_STORAGE_AWS_ACCESS_KEY_ID=
TRANSCRIPT_STORAGE_AWS_SECRET_ACCESS_KEY=
TRANSCRIPT_STORAGE_AWS_BUCKET_NAME=reflector-media
TRANSCRIPT_STORAGE_AWS_REGION=us-east-1
# For non-AWS S3-compatible endpoints (Garage, MinIO, etc.):
# TRANSCRIPT_STORAGE_AWS_ENDPOINT_URL=http://garage:3900
# =======================================================
# Daily.co Live Rooms (Optional)
# Enable real-time meeting rooms with Daily.co integration.
# Requires a Daily.co account: https://www.daily.co/
# =======================================================
# DEFAULT_VIDEO_PLATFORM=daily
# DAILY_API_KEY=your-daily-api-key
# DAILY_SUBDOMAIN=your-subdomain
# DAILY_WEBHOOK_SECRET=your-daily-webhook-secret
# DAILYCO_STORAGE_AWS_BUCKET_NAME=reflector-dailyco
# DAILYCO_STORAGE_AWS_REGION=us-east-1
# DAILYCO_STORAGE_AWS_ROLE_ARN=arn:aws:iam::role/DailyCoAccess
# =======================================================
# Feature Flags
# =======================================================
PUBLIC_MODE=true
# FEATURE_ROOMS=true
# =======================================================
# Sentry (Optional)
# =======================================================
# SENTRY_DSN=

View File

@@ -0,0 +1,35 @@
"""drop_use_celery_column
Revision ID: 3aa20b96d963
Revises: e69f08ead8ea
Create Date: 2026-02-05 10:12:44.065279
"""
from typing import Sequence, Union
import sqlalchemy as sa
from alembic import op
# revision identifiers, used by Alembic.
revision: str = "3aa20b96d963"
down_revision: Union[str, None] = "e69f08ead8ea"
branch_labels: Union[str, Sequence[str], None] = None
depends_on: Union[str, Sequence[str], None] = None
def upgrade() -> None:
with op.batch_alter_table("room", schema=None) as batch_op:
batch_op.drop_column("use_celery")
def downgrade() -> None:
with op.batch_alter_table("room", schema=None) as batch_op:
batch_op.add_column(
sa.Column(
"use_celery",
sa.Boolean(),
server_default=sa.text("false"),
nullable=False,
)
)

View File

@@ -0,0 +1,74 @@
"""add_change_seq_to_transcript
Revision ID: 623af934249a
Revises: 3aa20b96d963
Create Date: 2026-02-19 18:53:12.315440
"""
from typing import Sequence, Union
import sqlalchemy as sa
from alembic import op
# revision identifiers, used by Alembic.
revision: str = "623af934249a"
down_revision: Union[str, None] = "3aa20b96d963"
branch_labels: Union[str, Sequence[str], None] = None
depends_on: Union[str, Sequence[str], None] = None
def upgrade() -> None:
# Sequence
op.execute("CREATE SEQUENCE IF NOT EXISTS transcript_change_seq;")
# Column (nullable first for backfill)
op.add_column("transcript", sa.Column("change_seq", sa.BigInteger(), nullable=True))
# Backfill existing rows with sequential values (ordered by created_at for determinism)
op.execute("""
UPDATE transcript SET change_seq = sub.seq FROM (
SELECT id, nextval('transcript_change_seq') AS seq
FROM transcript ORDER BY created_at ASC
) sub WHERE transcript.id = sub.id;
""")
# Now make NOT NULL
op.alter_column("transcript", "change_seq", nullable=False)
# Default for any inserts between now and trigger creation
op.alter_column(
"transcript",
"change_seq",
server_default=sa.text("nextval('transcript_change_seq')"),
)
# Trigger function
op.execute("""
CREATE OR REPLACE FUNCTION set_transcript_change_seq()
RETURNS TRIGGER AS $$
BEGIN
NEW.change_seq := nextval('transcript_change_seq');
RETURN NEW;
END;
$$ LANGUAGE plpgsql;
""")
# Trigger (fires on every INSERT or UPDATE)
op.execute("""
CREATE TRIGGER trigger_transcript_change_seq
BEFORE INSERT OR UPDATE ON transcript
FOR EACH ROW
EXECUTE FUNCTION set_transcript_change_seq();
""")
# Index for efficient polling
op.create_index("idx_transcript_change_seq", "transcript", ["change_seq"])
def downgrade() -> None:
op.execute("DROP TRIGGER IF EXISTS trigger_transcript_change_seq ON transcript;")
op.execute("DROP FUNCTION IF EXISTS set_transcript_change_seq();")
op.drop_index("idx_transcript_change_seq", table_name="transcript")
op.drop_column("transcript", "change_seq")
op.execute("DROP SEQUENCE IF EXISTS transcript_change_seq;")

View File

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

View File

@@ -37,6 +37,13 @@ try:
except ImportError:
sentry_sdk = None
# Patch aioice port range if configured (must happen before any RTCPeerConnection)
if settings.WEBRTC_PORT_RANGE:
from reflector.webrtc_ports import parse_port_range, patch_aioice_port_range
_min, _max = parse_port_range(settings.WEBRTC_PORT_RANGE)
patch_aioice_port_range(_min, _max)
# lifespan events
@asynccontextmanager
@@ -59,7 +66,7 @@ else:
logger.info("Sentry disabled")
# build app
app = FastAPI(lifespan=lifespan)
app = FastAPI(lifespan=lifespan, root_path=settings.ROOT_PATH)
app.add_middleware(
CORSMiddleware,
allow_credentials=settings.CORS_ALLOW_CREDENTIALS or False,

View File

@@ -4,8 +4,9 @@ from uuid import uuid4
from celery import current_task
from reflector.db import get_database
from reflector.db import _database_context, get_database
from reflector.llm import llm_session_id
from reflector.ws_manager import reset_ws_manager
def asynctask(f):
@@ -20,8 +21,18 @@ def asynctask(f):
return await f(*args, **kwargs)
finally:
await database.disconnect()
_database_context.set(None)
if current_task:
# Reset cached connections before each Celery task.
# Each asyncio.run() creates a new event loop, making connections
# from previous tasks stale ("Future attached to a different loop").
_database_context.set(None)
reset_ws_manager()
coro = run_with_db()
if current_task:
return asyncio.run(coro)
try:
loop = asyncio.get_running_loop()
except RuntimeError:

View File

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

View File

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

View File

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

View File

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

View File

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

View File

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

View File

@@ -57,12 +57,6 @@ rooms = sqlalchemy.Table(
sqlalchemy.String,
nullable=False,
),
sqlalchemy.Column(
"use_celery",
sqlalchemy.Boolean,
nullable=False,
server_default=false(),
),
sqlalchemy.Column(
"skip_consent",
sqlalchemy.Boolean,
@@ -97,7 +91,6 @@ class Room(BaseModel):
ics_last_sync: datetime | None = None
ics_last_etag: str | None = None
platform: Platform = Field(default_factory=lambda: settings.DEFAULT_VIDEO_PLATFORM)
use_celery: bool = False
skip_consent: bool = False

View File

@@ -26,6 +26,7 @@ from reflector.db.rooms import rooms
from reflector.db.transcripts import SourceKind, TranscriptStatus, transcripts
from reflector.db.utils import is_postgresql
from reflector.logger import logger
from reflector.settings import settings
from reflector.utils.string import NonEmptyString, try_parse_non_empty_string
DEFAULT_SEARCH_LIMIT = 20
@@ -150,6 +151,7 @@ class SearchResultDB(BaseModel):
title: str | None = None
source_kind: SourceKind
room_id: str | None = None
change_seq: int | None = None
rank: float = Field(..., ge=0, le=1)
@@ -172,6 +174,7 @@ class SearchResult(BaseModel):
total_match_count: NonNegativeInt = Field(
default=0, description="Total number of matches found in the transcript"
)
change_seq: int | None = None
@field_serializer("created_at", when_used="json")
def serialize_datetime(self, dt: datetime) -> str:
@@ -355,6 +358,7 @@ class SearchController:
transcripts.c.user_id,
transcripts.c.room_id,
transcripts.c.source_kind,
transcripts.c.change_seq,
transcripts.c.webvtt,
transcripts.c.long_summary,
sqlalchemy.case(
@@ -396,7 +400,7 @@ class SearchController:
transcripts.c.user_id == params.user_id, rooms.c.is_shared
)
)
else:
elif not settings.PUBLIC_MODE:
base_query = base_query.where(rooms.c.is_shared)
if params.room_id:
base_query = base_query.where(transcripts.c.room_id == params.room_id)

View File

@@ -5,7 +5,10 @@ import shutil
from contextlib import asynccontextmanager
from datetime import datetime, timedelta, timezone
from pathlib import Path
from typing import Any, Literal, Sequence
from typing import TYPE_CHECKING, Any, Literal, Sequence
if TYPE_CHECKING:
from reflector.ws_events import TranscriptEventName
import sqlalchemy
from fastapi import HTTPException
@@ -32,6 +35,8 @@ class SourceKind(enum.StrEnum):
FILE = enum.auto()
transcript_change_seq = sqlalchemy.Sequence("transcript_change_seq", metadata=metadata)
transcripts = sqlalchemy.Table(
"transcript",
metadata,
@@ -86,6 +91,12 @@ transcripts = sqlalchemy.Table(
sqlalchemy.Column("webvtt", sqlalchemy.Text),
# Hatchet workflow run ID for resumption of failed workflows
sqlalchemy.Column("workflow_run_id", sqlalchemy.String),
sqlalchemy.Column(
"change_seq",
sqlalchemy.BigInteger,
transcript_change_seq,
server_default=transcript_change_seq.next_value(),
),
sqlalchemy.Index("idx_transcript_recording_id", "recording_id"),
sqlalchemy.Index("idx_transcript_user_id", "user_id"),
sqlalchemy.Index("idx_transcript_created_at", "created_at"),
@@ -184,7 +195,7 @@ class TranscriptWaveform(BaseModel):
class TranscriptEvent(BaseModel):
event: str
event: str # Typed at call sites via ws_events.TranscriptEventName; str here for DB compat
data: dict
@@ -226,6 +237,7 @@ class Transcript(BaseModel):
audio_deleted: bool | None = None
webvtt: str | None = None
workflow_run_id: str | None = None # Hatchet workflow run ID for resumption
change_seq: int | None = None
@field_serializer("created_at", when_used="json")
def serialize_datetime(self, dt: datetime) -> str:
@@ -233,7 +245,9 @@ class Transcript(BaseModel):
dt = dt.replace(tzinfo=timezone.utc)
return dt.isoformat()
def add_event(self, event: str, data: BaseModel) -> TranscriptEvent:
def add_event(
self, event: "TranscriptEventName", data: BaseModel
) -> TranscriptEvent:
ev = TranscriptEvent(event=event, data=data.model_dump())
self.events.append(ev)
return ev
@@ -376,6 +390,7 @@ class TranscriptController:
source_kind: SourceKind | None = None,
room_id: str | None = None,
search_term: str | None = None,
change_seq_from: int | None = None,
return_query: bool = False,
exclude_columns: list[str] = [
"topics",
@@ -396,6 +411,7 @@ class TranscriptController:
- `filter_recording`: filter out transcripts that are currently recording
- `room_id`: filter transcripts by room ID
- `search_term`: filter transcripts by search term
- `change_seq_from`: filter transcripts with change_seq > this value
"""
query = transcripts.select().join(
@@ -406,7 +422,7 @@ class TranscriptController:
query = query.where(
or_(transcripts.c.user_id == user_id, rooms.c.is_shared)
)
else:
elif not settings.PUBLIC_MODE:
query = query.where(rooms.c.is_shared)
if source_kind:
@@ -418,6 +434,9 @@ class TranscriptController:
if search_term:
query = query.where(transcripts.c.title.ilike(f"%{search_term}%"))
if change_seq_from is not None:
query = query.where(transcripts.c.change_seq > change_seq_from)
# Exclude heavy JSON columns from list queries
transcript_columns = [
col for col in transcripts.c if col.name not in exclude_columns
@@ -431,9 +450,10 @@ class TranscriptController:
)
if order_by is not None:
field = getattr(transcripts.c, order_by[1:])
if order_by.startswith("-"):
field = field.desc()
field = getattr(transcripts.c, order_by[1:]).desc()
else:
field = getattr(transcripts.c, order_by)
query = query.order_by(field)
if filter_empty:
@@ -688,7 +708,7 @@ class TranscriptController:
async def append_event(
self,
transcript: Transcript,
event: str,
event: "TranscriptEventName",
data: Any,
) -> TranscriptEvent:
"""

View File

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

View File

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

View File

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

View File

@@ -171,11 +171,13 @@ async def set_workflow_error_status(transcript_id: NonEmptyString) -> bool:
def _spawn_storage():
"""Create fresh storage instance."""
# TODO: replace direct AwsStorage construction with get_transcripts_storage() factory
return AwsStorage(
aws_bucket_name=settings.TRANSCRIPT_STORAGE_AWS_BUCKET_NAME,
aws_region=settings.TRANSCRIPT_STORAGE_AWS_REGION,
aws_access_key_id=settings.TRANSCRIPT_STORAGE_AWS_ACCESS_KEY_ID,
aws_secret_access_key=settings.TRANSCRIPT_STORAGE_AWS_SECRET_ACCESS_KEY,
aws_endpoint_url=settings.TRANSCRIPT_STORAGE_AWS_ENDPOINT_URL,
)

View File

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

View File

@@ -71,7 +71,7 @@ async def detect_chunk_topic(input: TopicChunkInput, ctx: Context) -> TopicChunk
from reflector.settings import settings # noqa: PLC0415
from reflector.utils.text import clean_title # noqa: PLC0415
llm = LLM(settings=settings, temperature=0.9, max_tokens=500)
llm = LLM(settings=settings, temperature=0.9)
prompt = TOPIC_PROMPT.format(text=input.chunk_text)
response = await llm.get_structured_response(

View File

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

View File

@@ -144,7 +144,18 @@ class StructuredOutputWorkflow(Workflow, Generic[OutputT]):
)
# Network retries handled by OpenAILike (max_retries=3)
response = await Settings.llm.acomplete(json_prompt)
# response_format enables grammar-based constrained decoding on backends
# that support it (DMR/llama.cpp, vLLM, Ollama, OpenAI).
response = await Settings.llm.acomplete(
json_prompt,
response_format={
"type": "json_schema",
"json_schema": {
"name": self.output_cls.__name__,
"schema": self.output_cls.model_json_schema(),
},
},
)
return ExtractionDone(output=response.text)
@step
@@ -191,7 +202,9 @@ class StructuredOutputWorkflow(Workflow, Generic[OutputT]):
class LLM:
def __init__(self, settings, temperature: float = 0.4, max_tokens: int = 2048):
def __init__(
self, settings, temperature: float = 0.4, max_tokens: int | None = None
):
self.settings_obj = settings
self.model_name = settings.LLM_MODEL
self.url = settings.LLM_URL

View File

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

View File

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

View File

@@ -39,7 +39,7 @@ class TranscriptFinalTitleProcessor(Processor):
def __init__(self, **kwargs):
super().__init__(**kwargs)
self.chunks: list[TitleSummary] = []
self.llm = LLM(settings=settings, temperature=0.5, max_tokens=200)
self.llm = LLM(settings=settings, temperature=0.5)
async def _push(self, data: TitleSummary):
self.chunks.append(data)

View File

@@ -35,7 +35,7 @@ class TranscriptTopicDetectorProcessor(Processor):
super().__init__(**kwargs)
self.transcript = None
self.min_transcript_length = min_transcript_length
self.llm = LLM(settings=settings, temperature=0.9, max_tokens=500)
self.llm = LLM(settings=settings, temperature=0.9)
async def _push(self, data: Transcript):
if self.transcript is None:

View File

@@ -15,14 +15,10 @@ from hatchet_sdk.clients.rest.exceptions import ApiException, NotFoundException
from hatchet_sdk.clients.rest.models import V1TaskStatus
from reflector.db.recordings import recordings_controller
from reflector.db.rooms import rooms_controller
from reflector.db.transcripts import Transcript, transcripts_controller
from reflector.hatchet.client import HatchetClientManager
from reflector.logger import logger
from reflector.pipelines.main_file_pipeline import task_pipeline_file_process
from reflector.pipelines.main_multitrack_pipeline import (
task_pipeline_multitrack_process,
)
from reflector.utils.string import NonEmptyString
@@ -101,8 +97,11 @@ async def validate_transcript_for_processing(
if transcript.locked:
return ValidationLocked(detail="Recording is locked")
# Check if recording is ready for processing
if transcript.status == "idle" and not transcript.workflow_run_id:
if (
transcript.status == "idle"
and not transcript.workflow_run_id
and not transcript.recording_id
):
return ValidationNotReady(detail="Recording is not ready for processing")
# Check Celery tasks
@@ -181,124 +180,98 @@ async def dispatch_transcript_processing(
Returns AsyncResult for Celery tasks, None for Hatchet workflows.
"""
if isinstance(config, MultitrackProcessingConfig):
use_celery = False
if config.room_id:
room = await rooms_controller.get_by_id(config.room_id)
use_celery = room.use_celery if room else False
use_hatchet = not use_celery
if use_celery:
logger.info(
"Room uses legacy Celery processing",
room_id=config.room_id,
transcript_id=config.transcript_id,
# Multitrack processing always uses Hatchet (no Celery fallback)
# First check if we can replay (outside transaction since it's read-only)
transcript = await transcripts_controller.get_by_id(config.transcript_id)
if transcript and transcript.workflow_run_id and not force:
can_replay = await HatchetClientManager.can_replay(
transcript.workflow_run_id
)
if use_hatchet:
# First check if we can replay (outside transaction since it's read-only)
transcript = await transcripts_controller.get_by_id(config.transcript_id)
if transcript and transcript.workflow_run_id and not force:
can_replay = await HatchetClientManager.can_replay(
transcript.workflow_run_id
if can_replay:
await HatchetClientManager.replay_workflow(transcript.workflow_run_id)
logger.info(
"Replaying Hatchet workflow",
workflow_id=transcript.workflow_run_id,
)
if can_replay:
await HatchetClientManager.replay_workflow(
transcript.workflow_run_id
)
logger.info(
"Replaying Hatchet workflow",
workflow_id=transcript.workflow_run_id,
)
return None
else:
# Workflow can't replay (CANCELLED, COMPLETED, or 404 deleted)
# Log and proceed to start new workflow
try:
status = await HatchetClientManager.get_workflow_run_status(
transcript.workflow_run_id
)
logger.info(
"Old workflow not replayable, starting new",
old_workflow_id=transcript.workflow_run_id,
old_status=status.value,
)
except NotFoundException:
# Workflow deleted from Hatchet but ID still in DB
logger.info(
"Old workflow not found in Hatchet, starting new",
old_workflow_id=transcript.workflow_run_id,
)
# Force: cancel old workflow if exists
if force and transcript and transcript.workflow_run_id:
try:
await HatchetClientManager.cancel_workflow(
transcript.workflow_run_id
)
logger.info(
"Cancelled old workflow (--force)",
workflow_id=transcript.workflow_run_id,
)
except NotFoundException:
logger.info(
"Old workflow already deleted (--force)",
workflow_id=transcript.workflow_run_id,
)
await transcripts_controller.update(
transcript, {"workflow_run_id": None}
)
# Re-fetch and check for concurrent dispatch (optimistic approach).
# No database lock - worst case is duplicate dispatch, but Hatchet
# workflows are idempotent so this is acceptable.
transcript = await transcripts_controller.get_by_id(config.transcript_id)
if transcript and transcript.workflow_run_id:
# Another process started a workflow between validation and now
return None
else:
# Workflow can't replay (CANCELLED, COMPLETED, or 404 deleted)
# Log and proceed to start new workflow
try:
status = await HatchetClientManager.get_workflow_run_status(
transcript.workflow_run_id
)
if status in (V1TaskStatus.RUNNING, V1TaskStatus.QUEUED):
logger.info(
"Concurrent workflow detected, skipping dispatch",
workflow_id=transcript.workflow_run_id,
)
return None
except ApiException:
# Workflow might be gone (404) or API issue - proceed with new workflow
pass
logger.info(
"Old workflow not replayable, starting new",
old_workflow_id=transcript.workflow_run_id,
old_status=status.value,
)
except NotFoundException:
# Workflow deleted from Hatchet but ID still in DB
logger.info(
"Old workflow not found in Hatchet, starting new",
old_workflow_id=transcript.workflow_run_id,
)
workflow_id = await HatchetClientManager.start_workflow(
workflow_name="DiarizationPipeline",
input_data={
"recording_id": config.recording_id,
"tracks": [{"s3_key": k} for k in config.track_keys],
"bucket_name": config.bucket_name,
"transcript_id": config.transcript_id,
"room_id": config.room_id,
},
additional_metadata={
"transcript_id": config.transcript_id,
"recording_id": config.recording_id,
"daily_recording_id": config.recording_id,
},
# Force: cancel old workflow if exists
if force and transcript and transcript.workflow_run_id:
try:
await HatchetClientManager.cancel_workflow(transcript.workflow_run_id)
logger.info(
"Cancelled old workflow (--force)",
workflow_id=transcript.workflow_run_id,
)
except NotFoundException:
logger.info(
"Old workflow already deleted (--force)",
workflow_id=transcript.workflow_run_id,
)
await transcripts_controller.update(transcript, {"workflow_run_id": None})
# Re-fetch and check for concurrent dispatch (optimistic approach).
# No database lock - worst case is duplicate dispatch, but Hatchet
# workflows are idempotent so this is acceptable.
transcript = await transcripts_controller.get_by_id(config.transcript_id)
if transcript and transcript.workflow_run_id:
# Another process started a workflow between validation and now
try:
status = await HatchetClientManager.get_workflow_run_status(
transcript.workflow_run_id
)
if status in (V1TaskStatus.RUNNING, V1TaskStatus.QUEUED):
logger.info(
"Concurrent workflow detected, skipping dispatch",
workflow_id=transcript.workflow_run_id,
)
return None
except ApiException:
# Workflow might be gone (404) or API issue - proceed with new workflow
pass
workflow_id = await HatchetClientManager.start_workflow(
workflow_name="DiarizationPipeline",
input_data={
"recording_id": config.recording_id,
"tracks": [{"s3_key": k} for k in config.track_keys],
"bucket_name": config.bucket_name,
"transcript_id": config.transcript_id,
"room_id": config.room_id,
},
additional_metadata={
"transcript_id": config.transcript_id,
"recording_id": config.recording_id,
"daily_recording_id": config.recording_id,
},
)
if transcript:
await transcripts_controller.update(
transcript, {"workflow_run_id": workflow_id}
)
if transcript:
await transcripts_controller.update(
transcript, {"workflow_run_id": workflow_id}
)
logger.info("Hatchet workflow dispatched", workflow_id=workflow_id)
return None
logger.info("Hatchet workflow dispatched", workflow_id=workflow_id)
return None
# Celery pipeline (durable workflows disabled)
return task_pipeline_multitrack_process.delay(
transcript_id=config.transcript_id,
bucket_name=config.bucket_name,
track_keys=config.track_keys,
)
elif isinstance(config, FileProcessingConfig):
return task_pipeline_file_process.delay(transcript_id=config.transcript_id)
else:

View File

@@ -1,7 +1,7 @@
from pydantic.types import PositiveInt
from pydantic_settings import BaseSettings, SettingsConfigDict
from reflector.schemas.platform import WHEREBY_PLATFORM, Platform
from reflector.schemas.platform import DAILY_PLATFORM, Platform
from reflector.utils.string import NonEmptyString
@@ -12,6 +12,17 @@ class Settings(BaseSettings):
extra="ignore",
)
ROOT_PATH: str = "/"
# WebRTC port range for ICE candidates (e.g. "50000-50100").
# When set, monkey-patches aioice to bind UDP sockets within this range,
# allowing Docker port mapping instead of network_mode: host.
WEBRTC_PORT_RANGE: str | None = None
# Host IP or hostname to advertise in ICE candidates instead of the
# container's internal IP. Use "host.docker.internal" in Docker with
# extra_hosts, or a specific LAN IP. Resolved at connection time.
WEBRTC_HOST: str | None = None
# CORS
UI_BASE_URL: str = "http://localhost:3000"
CORS_ORIGIN: str = "*"
@@ -49,6 +60,7 @@ class Settings(BaseSettings):
TRANSCRIPT_STORAGE_AWS_REGION: str = "us-east-1"
TRANSCRIPT_STORAGE_AWS_ACCESS_KEY_ID: str | None = None
TRANSCRIPT_STORAGE_AWS_SECRET_ACCESS_KEY: str | None = None
TRANSCRIPT_STORAGE_AWS_ENDPOINT_URL: str | None = None
# Platform-specific recording storage (follows {PREFIX}_STORAGE_AWS_{CREDENTIAL} pattern)
# Whereby storage configuration
@@ -84,9 +96,7 @@ class Settings(BaseSettings):
)
# Diarization
# backends:
# - pyannote: in-process model loading (no HTTP, runs in same process)
# - modal: HTTP API client (works with Modal.com OR self-hosted gpu/self_hosted/)
# backend: modal — HTTP API client (works with Modal.com OR self-hosted gpu/self_hosted/)
DIARIZATION_ENABLED: bool = True
DIARIZATION_BACKEND: str = "modal"
DIARIZATION_URL: str | None = None
@@ -95,9 +105,6 @@ class Settings(BaseSettings):
# Diarization: modal backend
DIARIZATION_MODAL_API_KEY: str | None = None
# Diarization: local pyannote.audio
DIARIZATION_PYANNOTE_AUTH_TOKEN: str | None = None
# Audio Padding (Modal.com backend)
PADDING_URL: str | None = None
PADDING_MODAL_API_KEY: str | None = None
@@ -155,7 +162,7 @@ class Settings(BaseSettings):
None # Webhook UUID for this environment. Not used by production code
)
# Platform Configuration
DEFAULT_VIDEO_PLATFORM: Platform = WHEREBY_PLATFORM
DEFAULT_VIDEO_PLATFORM: Platform = DAILY_PLATFORM
# Zulip integration
ZULIP_REALM: str | None = None

View File

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

View File

@@ -24,6 +24,9 @@ from reflector.pipelines.main_live_pipeline import (
pipeline_process as live_pipeline_process,
)
from reflector.storage import Storage
from reflector.worker.app import (
app as celery_app, # noqa: F401 - ensure Celery uses Redis broker
)
def validate_s3_bucket_name(bucket: str) -> None:

View File

@@ -129,10 +129,6 @@ class DailyClient(VideoPlatformClient):
"""Get room presence/session data for a Daily.co room."""
return await self._api_client.get_room_presence(room_name)
async def delete_room(self, room_name: str) -> None:
"""Delete a Daily.co room (idempotent - succeeds even if room doesn't exist)."""
return await self._api_client.delete_room(room_name)
async def get_meeting_participants(
self, meeting_id: str
) -> MeetingParticipantsResponse:

View File

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

View File

@@ -20,7 +20,6 @@ from reflector.services.ics_sync import ics_sync_service
from reflector.settings import settings
from reflector.utils.url import add_query_param
from reflector.video_platforms.factory import create_platform_client
from reflector.worker.process import poll_daily_room_presence_task
from reflector.worker.webhook import test_webhook
logger = logging.getLogger(__name__)
@@ -366,53 +365,6 @@ async def rooms_create_meeting(
return meeting
@router.post("/rooms/{room_name}/meetings/{meeting_id}/joined")
async def rooms_joined_meeting(
room_name: str,
meeting_id: str,
):
"""Trigger presence poll (ideally when user actually joins meeting in Daily iframe)"""
room = await rooms_controller.get_by_name(room_name)
if not room:
raise HTTPException(status_code=404, detail="Room not found")
meeting = await meetings_controller.get_by_id(meeting_id, room=room)
if not meeting:
raise HTTPException(status_code=404, detail="Meeting not found")
if meeting.platform == "daily":
poll_daily_room_presence_task.delay(meeting_id)
return {"status": "ok"}
@router.post("/rooms/{room_name}/meetings/{meeting_id}/leave")
async def rooms_leave_meeting(
room_name: str,
meeting_id: str,
delay_seconds: int = 2,
):
"""Trigger presence recheck when user leaves meeting (e.g., tab close/navigation).
Queues presence poll with optional delay to allow Daily.co to detect disconnect.
"""
room = await rooms_controller.get_by_name(room_name)
if not room:
raise HTTPException(status_code=404, detail="Room not found")
meeting = await meetings_controller.get_by_id(meeting_id, room=room)
if not meeting:
raise HTTPException(status_code=404, detail="Meeting not found")
if meeting.platform == "daily":
poll_daily_room_presence_task.apply_async(
args=[meeting_id],
countdown=delay_seconds,
)
return {"status": "ok"}
@router.post("/rooms/{room_id}/webhook/test", response_model=WebhookTestResult)
async def rooms_test_webhook(
room_id: str,

View File

@@ -10,6 +10,7 @@ from pydantic import BaseModel
from reflector.events import subscribers_shutdown
from reflector.logger import logger
from reflector.pipelines.runner import PipelineRunner
from reflector.settings import settings
sessions = []
router = APIRouter()
@@ -123,7 +124,16 @@ async def rtc_offer_base(
# update metrics
m_rtc_sessions.inc()
return RtcOffer(sdp=pc.localDescription.sdp, type=pc.localDescription.type)
sdp = pc.localDescription.sdp
# Rewrite ICE candidate IPs when running behind Docker bridge networking
if settings.WEBRTC_HOST:
from reflector.webrtc_ports import resolve_webrtc_host, rewrite_sdp_host
host_ip = resolve_webrtc_host(settings.WEBRTC_HOST)
sdp = rewrite_sdp_host(sdp, host_ip)
return RtcOffer(sdp=sdp, type=pc.localDescription.type)
@subscribers_shutdown.append

View File

@@ -111,6 +111,7 @@ class GetTranscriptMinimal(BaseModel):
room_id: str | None = None
room_name: str | None = None
audio_deleted: bool | None = None
change_seq: int | None = None
class TranscriptParticipantWithEmail(TranscriptParticipant):
@@ -266,12 +267,22 @@ async def transcripts_list(
source_kind: SourceKind | None = None,
room_id: str | None = None,
search_term: str | None = None,
change_seq_from: int | None = None,
sort_by: Literal["created_at", "change_seq"] | None = None,
):
if not user and not settings.PUBLIC_MODE:
raise HTTPException(status_code=401, detail="Not authenticated")
user_id = user["sub"] if user else None
# Default behavior preserved: sort_by=None → "-created_at"
if sort_by == "change_seq":
order_by = "change_seq" # ASC (ascending for checkpoint-based polling)
elif sort_by == "created_at":
order_by = "-created_at" # DESC (newest first, same as current default)
else:
order_by = "-created_at" # default, backward compatible
return await apaginate(
get_database(),
await transcripts_controller.get_all(
@@ -279,7 +290,8 @@ async def transcripts_list(
source_kind=SourceKind(source_kind) if source_kind else None,
room_id=room_id,
search_term=search_term,
order_by="-created_at",
order_by=order_by,
change_seq_from=change_seq_from,
return_query=True,
),
)
@@ -512,6 +524,7 @@ async def transcript_get(
"room_id": transcript.room_id,
"room_name": room_name,
"audio_deleted": transcript.audio_deleted,
"change_seq": transcript.change_seq,
"participants": participants,
}

View File

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

View File

@@ -4,18 +4,22 @@ Transcripts websocket API
"""
from typing import Optional
from fastapi import APIRouter, Depends, HTTPException, WebSocket, WebSocketDisconnect
from fastapi import APIRouter, HTTPException, WebSocket, WebSocketDisconnect
import reflector.auth as auth
from reflector.db.transcripts import transcripts_controller
from reflector.ws_events import TranscriptWsEvent
from reflector.ws_manager import get_ws_manager
router = APIRouter()
@router.get("/transcripts/{transcript_id}/events")
@router.get(
"/transcripts/{transcript_id}/events",
response_model=TranscriptWsEvent,
summary="Transcript WebSocket event schema",
description="Stub exposing the discriminated union of all transcript-level WS events for OpenAPI type generation. Real events are delivered over the WebSocket at the same path.",
)
async def transcript_get_websocket_events(transcript_id: str):
pass
@@ -24,8 +28,9 @@ async def transcript_get_websocket_events(transcript_id: str):
async def transcript_events_websocket(
transcript_id: str,
websocket: WebSocket,
user: Optional[auth.UserInfo] = Depends(auth.current_user_optional),
):
_, negotiated_subprotocol = auth.parse_ws_bearer_token(websocket)
user = await auth.current_user_ws_optional(websocket)
user_id = user["sub"] if user else None
transcript = await transcripts_controller.get_by_id_for_http(
transcript_id, user_id=user_id
@@ -37,7 +42,9 @@ async def transcript_events_websocket(
# use ts:transcript_id as room id
room_id = f"ts:{transcript_id}"
ws_manager = get_ws_manager()
await ws_manager.add_user_to_room(room_id, websocket)
await ws_manager.add_user_to_room(
room_id, websocket, subprotocol=negotiated_subprotocol
)
try:
# on first connection, send all events only to the current user

View File

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

View File

@@ -0,0 +1,111 @@
"""
Monkey-patch aioice to use a fixed UDP port range for ICE candidates,
and optionally rewrite SDP to advertise a different host IP.
This allows running the server in Docker with bridge networking
(no network_mode: host) by:
1. Restricting ICE UDP ports to a known range that can be mapped in Docker
2. Replacing container-internal IPs with the Docker host IP in SDP answers
"""
import asyncio
import socket
from reflector.logger import logger
def parse_port_range(range_str: str) -> tuple[int, int]:
"""Parse a 'min-max' string into (min_port, max_port)."""
parts = range_str.split("-")
if len(parts) != 2:
raise ValueError(f"WEBRTC_PORT_RANGE must be 'min-max', got: {range_str!r}")
min_port, max_port = int(parts[0]), int(parts[1])
if not (1024 <= min_port <= max_port <= 65535):
raise ValueError(
f"Invalid port range: {min_port}-{max_port} "
"(must be 1024-65535 with min <= max)"
)
return min_port, max_port
def patch_aioice_port_range(min_port: int, max_port: int) -> None:
"""
Monkey-patch aioice so that ICE candidate UDP sockets bind to ports
within [min_port, max_port] instead of OS-assigned ephemeral ports.
Works by temporarily wrapping loop.create_datagram_endpoint() during
aioice's get_component_candidates() to intercept bind(addr, 0) calls.
"""
import aioice.ice as _ice
_original = _ice.Connection.get_component_candidates
_state = {"next_port": min_port}
async def _patched_get_component_candidates(self, component, addresses, timeout=5):
loop = asyncio.get_event_loop()
_orig_create = loop.create_datagram_endpoint
async def _create_with_port_range(*args, **kwargs):
local_addr = kwargs.get("local_addr")
if local_addr and local_addr[1] == 0:
addr = local_addr[0]
# Try each port in the range (wrapping around)
attempts = max_port - min_port + 1
for _ in range(attempts):
port = _state["next_port"]
_state["next_port"] = (
min_port
if _state["next_port"] >= max_port
else _state["next_port"] + 1
)
try:
kwargs["local_addr"] = (addr, port)
return await _orig_create(*args, **kwargs)
except OSError:
continue
# All ports exhausted, fall back to OS assignment
logger.warning(
"All WebRTC ports in range exhausted, falling back to OS",
min_port=min_port,
max_port=max_port,
)
kwargs["local_addr"] = (addr, 0)
return await _orig_create(*args, **kwargs)
loop.create_datagram_endpoint = _create_with_port_range
try:
return await _original(self, component, addresses, timeout)
finally:
loop.create_datagram_endpoint = _orig_create
_ice.Connection.get_component_candidates = _patched_get_component_candidates
logger.info(
"aioice patched for WebRTC port range",
min_port=min_port,
max_port=max_port,
)
def resolve_webrtc_host(host: str) -> str:
"""Resolve a hostname or IP to an IP address for ICE candidate rewriting."""
try:
ip = socket.gethostbyname(host)
logger.info("Resolved WEBRTC_HOST", host=host, ip=ip)
return ip
except socket.gaierror:
logger.warning("Could not resolve WEBRTC_HOST, using as-is", host=host)
return host
def rewrite_sdp_host(sdp: str, target_ip: str) -> str:
"""
Replace container-internal IPs in SDP with target_ip so that
ICE candidates advertise a routable address.
"""
import aioice.ice
container_ips = aioice.ice.get_host_addresses(use_ipv4=True, use_ipv6=False)
for ip in container_ips:
if ip != "127.0.0.1" and ip != target_ip:
sdp = sdp.replace(ip, target_ip)
return sdp

View File

@@ -27,9 +27,6 @@ from reflector.db.transcripts import (
from reflector.hatchet.client import HatchetClientManager
from reflector.pipelines.main_file_pipeline import task_pipeline_file_process
from reflector.pipelines.main_live_pipeline import asynctask
from reflector.pipelines.main_multitrack_pipeline import (
task_pipeline_multitrack_process,
)
from reflector.pipelines.topic_processing import EmptyPipeline
from reflector.processors import AudioFileWriterProcessor
from reflector.processors.audio_waveform_processor import AudioWaveformProcessor
@@ -351,49 +348,29 @@ async def _process_multitrack_recording_inner(
room_id=room.id,
)
use_celery = room and room.use_celery
use_hatchet = not use_celery
if use_celery:
logger.info(
"Room uses legacy Celery processing",
room_id=room.id,
transcript_id=transcript.id,
)
if use_hatchet:
workflow_id = await HatchetClientManager.start_workflow(
workflow_name="DiarizationPipeline",
input_data={
"recording_id": recording_id,
"tracks": [{"s3_key": k} for k in filter_cam_audio_tracks(track_keys)],
"bucket_name": bucket_name,
"transcript_id": transcript.id,
"room_id": room.id,
},
additional_metadata={
"transcript_id": transcript.id,
"recording_id": recording_id,
"daily_recording_id": recording_id,
},
)
logger.info(
"Started Hatchet workflow",
workflow_id=workflow_id,
transcript_id=transcript.id,
)
await transcripts_controller.update(
transcript, {"workflow_run_id": workflow_id}
)
return
# Celery pipeline (runs when durable workflows disabled)
task_pipeline_multitrack_process.delay(
transcript_id=transcript.id,
bucket_name=bucket_name,
track_keys=filter_cam_audio_tracks(track_keys),
# Multitrack processing always uses Hatchet (no Celery fallback)
workflow_id = await HatchetClientManager.start_workflow(
workflow_name="DiarizationPipeline",
input_data={
"recording_id": recording_id,
"tracks": [{"s3_key": k} for k in filter_cam_audio_tracks(track_keys)],
"bucket_name": bucket_name,
"transcript_id": transcript.id,
"room_id": room.id,
},
additional_metadata={
"transcript_id": transcript.id,
"recording_id": recording_id,
"daily_recording_id": recording_id,
},
)
logger.info(
"Started Hatchet workflow",
workflow_id=workflow_id,
transcript_id=transcript.id,
)
await transcripts_controller.update(transcript, {"workflow_run_id": workflow_id})
@shared_task
@@ -845,47 +822,15 @@ async def process_meetings():
end_date = end_date.replace(tzinfo=timezone.utc)
client = create_platform_client(meeting.platform)
has_active_sessions = False
has_had_sessions = False
room_sessions = await client.get_room_sessions(meeting.room_name)
if meeting.platform == "daily":
try:
presence = await client.get_room_presence(meeting.room_name)
has_active_sessions = presence.total_count > 0
room_sessions = await client.get_room_sessions(
meeting.room_name
)
has_had_sessions = bool(room_sessions)
logger_.info(
"Daily.co presence check",
has_active_sessions=has_active_sessions,
has_had_sessions=has_had_sessions,
presence_count=presence.total_count,
)
except Exception:
logger_.warning(
"Daily.co presence API failed, falling back to DB sessions",
exc_info=True,
)
room_sessions = await client.get_room_sessions(
meeting.room_name
)
has_active_sessions = bool(
room_sessions
and any(s.ended_at is None for s in room_sessions)
)
has_had_sessions = bool(room_sessions)
else:
room_sessions = await client.get_room_sessions(meeting.room_name)
has_active_sessions = bool(
room_sessions and any(s.ended_at is None for s in room_sessions)
)
has_had_sessions = bool(room_sessions)
logger_.info(
f"has_active_sessions={has_active_sessions}, has_had_sessions={has_had_sessions}"
)
has_active_sessions = bool(
room_sessions and any(s.ended_at is None for s in room_sessions)
)
has_had_sessions = bool(room_sessions)
logger_.info(
f"has_active_sessions={has_active_sessions}, has_had_sessions={has_had_sessions}"
)
if has_active_sessions:
logger_.debug("Meeting still has active sessions, keep it")
@@ -904,20 +849,7 @@ async def process_meetings():
await meetings_controller.update_meeting(
meeting.id, is_active=False
)
logger_.info("Meeting deactivated in database")
if meeting.platform == "daily":
try:
await client.delete_room(meeting.room_name)
logger_.info(
"Daily.co room deleted", room_name=meeting.room_name
)
except Exception:
logger_.warning(
"Failed to delete Daily.co room",
room_name=meeting.room_name,
exc_info=True,
)
logger_.info("Meeting is deactivated")
processed_count += 1
@@ -1117,66 +1049,43 @@ async def reprocess_failed_daily_recordings():
)
continue
use_celery = room and room.use_celery
use_hatchet = not use_celery
if use_hatchet:
if not transcript:
logger.warning(
"No transcript for Hatchet reprocessing, skipping",
recording_id=recording.id,
)
continue
workflow_id = await HatchetClientManager.start_workflow(
workflow_name="DiarizationPipeline",
input_data={
"recording_id": recording.id,
"tracks": [
{"s3_key": k}
for k in filter_cam_audio_tracks(recording.track_keys)
],
"bucket_name": bucket_name,
"transcript_id": transcript.id,
"room_id": room.id if room else None,
},
additional_metadata={
"transcript_id": transcript.id,
"recording_id": recording.id,
"reprocess": True,
},
)
await transcripts_controller.update(
transcript, {"workflow_run_id": workflow_id}
)
logger.info(
"Queued Daily recording for Hatchet reprocessing",
# Multitrack reprocessing always uses Hatchet (no Celery fallback)
if not transcript:
logger.warning(
"No transcript for Hatchet reprocessing, skipping",
recording_id=recording.id,
workflow_id=workflow_id,
room_name=meeting.room_name,
track_count=len(recording.track_keys),
)
else:
logger.info(
"Queueing Daily recording for Celery reprocessing",
recording_id=recording.id,
room_name=meeting.room_name,
track_count=len(recording.track_keys),
transcript_status=transcript.status if transcript else None,
)
continue
# For reprocessing, pass actual recording time (though it's ignored - see _process_multitrack_recording_inner)
# Reprocessing uses recording.meeting_id directly instead of time-based matching
recording_start_ts = int(recording.recorded_at.timestamp())
workflow_id = await HatchetClientManager.start_workflow(
workflow_name="DiarizationPipeline",
input_data={
"recording_id": recording.id,
"tracks": [
{"s3_key": k}
for k in filter_cam_audio_tracks(recording.track_keys)
],
"bucket_name": bucket_name,
"transcript_id": transcript.id,
"room_id": room.id if room else None,
},
additional_metadata={
"transcript_id": transcript.id,
"recording_id": recording.id,
"reprocess": True,
},
)
await transcripts_controller.update(
transcript, {"workflow_run_id": workflow_id}
)
process_multitrack_recording.delay(
bucket_name=bucket_name,
daily_room_name=meeting.room_name,
recording_id=recording.id,
track_keys=recording.track_keys,
recording_start_ts=recording_start_ts,
)
logger.info(
"Queued Daily recording for Hatchet reprocessing",
recording_id=recording.id,
workflow_id=workflow_id,
room_name=meeting.room_name,
track_count=len(recording.track_keys),
)
reprocessed_count += 1

View File

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

View File

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

View File

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

View File

@@ -4,7 +4,7 @@ from unittest.mock import patch
import pytest
from reflector.schemas.platform import WHEREBY_PLATFORM
from reflector.schemas.platform import DAILY_PLATFORM, WHEREBY_PLATFORM
@pytest.fixture(scope="session", autouse=True)
@@ -14,6 +14,7 @@ def register_mock_platform():
from reflector.video_platforms.registry import register_platform
register_platform(WHEREBY_PLATFORM, MockPlatformClient)
register_platform(DAILY_PLATFORM, MockPlatformClient)
yield

View File

@@ -1,286 +0,0 @@
"""Unit tests for Daily.co presence-based meeting deactivation logic.
Tests the fix for split room race condition by verifying:
1. Real-time presence checking via Daily.co API
2. Room deletion when meetings deactivate
"""
from datetime import datetime, timedelta, timezone
from unittest.mock import AsyncMock, patch
import pytest
from reflector.dailyco_api.responses import (
RoomPresenceParticipant,
RoomPresenceResponse,
)
from reflector.db.daily_participant_sessions import (
DailyParticipantSession,
daily_participant_sessions_controller,
)
from reflector.db.meetings import meetings_controller
from reflector.db.rooms import rooms_controller
from reflector.video_platforms.daily import DailyClient
@pytest.fixture
async def daily_room_and_meeting():
"""Create test room and meeting for Daily platform."""
room = await rooms_controller.add(
name="test-daily",
user_id="test-user",
platform="daily",
zulip_auto_post=False,
zulip_stream="",
zulip_topic="",
is_locked=False,
room_mode="normal",
recording_type="cloud",
recording_trigger="automatic-2nd-participant",
is_shared=False,
)
current_time = datetime.now(timezone.utc)
end_time = current_time + timedelta(hours=2)
meeting = await meetings_controller.create(
id="test-meeting-id",
room_name="test-daily-20260129120000",
room_url="https://daily.co/test",
host_room_url="https://daily.co/test",
start_date=current_time,
end_date=end_time,
room=room,
)
return room, meeting
@pytest.mark.asyncio
async def test_daily_client_has_delete_room_method():
"""Verify DailyClient has delete_room method for cleanup."""
# Create a mock DailyClient
with patch("reflector.dailyco_api.client.DailyApiClient"):
from reflector.video_platforms.models import VideoPlatformConfig
config = VideoPlatformConfig(api_key="test-key", webhook_secret="test-secret")
client = DailyClient(config)
# Verify delete_room method exists
assert hasattr(client, "delete_room")
assert callable(getattr(client, "delete_room"))
@pytest.mark.asyncio
async def test_get_room_presence_returns_realtime_data(daily_room_and_meeting):
"""Test that get_room_presence returns real-time participant data."""
room, meeting = daily_room_and_meeting
# Mock Daily.co API response
mock_presence = RoomPresenceResponse(
total_count=2,
data=[
RoomPresenceParticipant(
room=meeting.room_name,
id="session-1",
userId="user-1",
userName="User One",
joinTime="2026-01-29T12:00:00.000Z",
duration=120,
),
RoomPresenceParticipant(
room=meeting.room_name,
id="session-2",
userId="user-2",
userName="User Two",
joinTime="2026-01-29T12:05:00.000Z",
duration=60,
),
],
)
with patch("reflector.dailyco_api.client.DailyApiClient") as mock_api:
from reflector.video_platforms.models import VideoPlatformConfig
config = VideoPlatformConfig(api_key="test-key", webhook_secret="test-secret")
client = DailyClient(config)
# Mock the API client method
client._api_client.get_room_presence = AsyncMock(return_value=mock_presence)
# Call get_room_presence
result = await client.get_room_presence(meeting.room_name)
# Verify it calls Daily.co API
client._api_client.get_room_presence.assert_called_once_with(meeting.room_name)
# Verify result contains real-time data
assert result.total_count == 2
assert len(result.data) == 2
assert result.data[0].id == "session-1"
assert result.data[1].id == "session-2"
@pytest.mark.asyncio
async def test_presence_shows_active_even_when_db_stale(daily_room_and_meeting):
"""Test that Daily.co presence API is source of truth, not stale DB sessions."""
room, meeting = daily_room_and_meeting
current_time = datetime.now(timezone.utc)
# Create stale DB session (left_at=NULL but user actually left)
session_id = f"{meeting.id}:stale-user:{int((current_time - timedelta(minutes=5)).timestamp() * 1000)}"
await daily_participant_sessions_controller.upsert_joined(
DailyParticipantSession(
id=session_id,
meeting_id=meeting.id,
room_id=room.id,
session_id="stale-daily-session",
user_name="Stale User",
user_id="stale-user",
joined_at=current_time - timedelta(minutes=5),
left_at=None, # Stale - shows active but user left
)
)
# Verify DB shows active session
db_sessions = await daily_participant_sessions_controller.get_active_by_meeting(
meeting.id
)
assert len(db_sessions) == 1
# But Daily.co API shows room is empty
mock_presence = RoomPresenceResponse(total_count=0, data=[])
with patch("reflector.dailyco_api.client.DailyApiClient"):
from reflector.video_platforms.models import VideoPlatformConfig
config = VideoPlatformConfig(api_key="test-key", webhook_secret="test-secret")
client = DailyClient(config)
client._api_client.get_room_presence = AsyncMock(return_value=mock_presence)
# Get real-time presence
presence = await client.get_room_presence(meeting.room_name)
# Real-time API shows no participants (truth)
assert presence.total_count == 0
assert len(presence.data) == 0
# DB shows 1 participant (stale)
assert len(db_sessions) == 1
# Implementation should trust presence API, not DB
@pytest.mark.asyncio
async def test_meeting_deactivation_logic_with_presence_empty():
"""Test the core deactivation decision logic when presence shows room empty."""
# This tests the logic that will be in process_meetings
# Simulate: DB shows stale active session
has_active_db_sessions = True # DB is stale
# Simulate: Daily.co presence API shows room empty
presence_count = 0 # Real-time truth
# Simulate: Meeting has been used before
has_had_sessions = True
# Decision logic (what process_meetings should do):
# - If presence API available: trust it
# - If presence shows empty AND has_had_sessions: deactivate
if presence_count == 0 and has_had_sessions:
should_deactivate = True
else:
should_deactivate = False
assert should_deactivate is True # Should deactivate despite stale DB
@pytest.mark.asyncio
async def test_meeting_deactivation_logic_with_presence_active():
"""Test that meetings stay active when presence shows participants."""
# Simulate: DB shows no sessions (not yet updated)
has_active_db_sessions = False # DB hasn't caught up
# Simulate: Daily.co presence API shows active participant
presence_count = 1 # Real-time truth
# Decision logic: presence shows activity, keep meeting active
if presence_count > 0:
should_deactivate = False
else:
should_deactivate = True
assert should_deactivate is False # Should stay active
@pytest.mark.asyncio
async def test_delete_room_called_on_deactivation(daily_room_and_meeting):
"""Test that Daily.co room is deleted when meeting deactivates."""
room, meeting = daily_room_and_meeting
with patch("reflector.dailyco_api.client.DailyApiClient"):
from reflector.video_platforms.models import VideoPlatformConfig
config = VideoPlatformConfig(api_key="test-key", webhook_secret="test-secret")
client = DailyClient(config)
# Mock delete_room API call
client._api_client.delete_room = AsyncMock()
# Simulate deactivation - should delete room
await client._api_client.delete_room(meeting.room_name)
# Verify delete was called
client._api_client.delete_room.assert_called_once_with(meeting.room_name)
@pytest.mark.asyncio
async def test_delete_room_idempotent_on_404():
"""Test that room deletion is idempotent (succeeds even if room doesn't exist)."""
from reflector.dailyco_api.client import DailyApiClient
# Create real client to test delete_room logic
client = DailyApiClient(api_key="test-key")
# Mock the HTTP client
mock_http_client = AsyncMock()
mock_response = AsyncMock()
mock_response.status_code = 404 # Room not found
mock_http_client.delete = AsyncMock(return_value=mock_response)
# Mock _get_client to return our mock
async def mock_get_client():
return mock_http_client
client._get_client = mock_get_client
# delete_room should succeed even on 404 (idempotent)
await client.delete_room("nonexistent-room")
# Verify delete was attempted
mock_http_client.delete.assert_called_once()
@pytest.mark.asyncio
async def test_api_failure_fallback_to_db_sessions():
"""Test that system falls back to DB sessions if Daily.co API fails."""
# Simulate: Daily.co API throws exception
api_exception = Exception("API unavailable")
# Simulate: DB shows active session
has_active_db_sessions = True
# Decision logic with fallback:
try:
presence_count = None
raise api_exception # Simulating API failure
except Exception:
# Fallback: use DB sessions (conservative - don't deactivate if unsure)
if has_active_db_sessions:
should_deactivate = False
else:
should_deactivate = True
assert should_deactivate is False # Conservative: keep active on API failure

View File

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

View File

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

View File

@@ -1,6 +1,6 @@
import asyncio
import time
from unittest.mock import patch
from unittest.mock import AsyncMock, patch
import pytest
from httpx import ASGITransport, AsyncClient
@@ -142,17 +142,17 @@ async def test_whereby_recording_uses_file_pipeline(client):
"reflector.services.transcript_process.task_pipeline_file_process"
) as mock_file_pipeline,
patch(
"reflector.services.transcript_process.task_pipeline_multitrack_process"
) as mock_multitrack_pipeline,
"reflector.services.transcript_process.HatchetClientManager"
) as mock_hatchet,
):
response = await client.post(f"/transcripts/{transcript.id}/process")
assert response.status_code == 200
assert response.json()["status"] == "ok"
# Whereby recordings should use file pipeline
# Whereby recordings should use file pipeline, not Hatchet
mock_file_pipeline.delay.assert_called_once_with(transcript_id=transcript.id)
mock_multitrack_pipeline.delay.assert_not_called()
mock_hatchet.start_workflow.assert_not_called()
@pytest.mark.usefixtures("setup_database")
@@ -177,8 +177,6 @@ async def test_dailyco_recording_uses_multitrack_pipeline(client):
recording_trigger="automatic-2nd-participant",
is_shared=False,
)
# Force Celery backend for test
await rooms_controller.update(room, {"use_celery": True})
transcript = await transcripts_controller.add(
"",
@@ -213,18 +211,23 @@ async def test_dailyco_recording_uses_multitrack_pipeline(client):
"reflector.services.transcript_process.task_pipeline_file_process"
) as mock_file_pipeline,
patch(
"reflector.services.transcript_process.task_pipeline_multitrack_process"
) as mock_multitrack_pipeline,
"reflector.services.transcript_process.HatchetClientManager"
) as mock_hatchet,
):
mock_hatchet.start_workflow = AsyncMock(return_value="test-workflow-id")
response = await client.post(f"/transcripts/{transcript.id}/process")
assert response.status_code == 200
assert response.json()["status"] == "ok"
# Daily.co multitrack recordings should use multitrack pipeline
mock_multitrack_pipeline.delay.assert_called_once_with(
transcript_id=transcript.id,
bucket_name="daily-bucket",
track_keys=track_keys,
)
# Daily.co multitrack recordings should use Hatchet workflow
mock_hatchet.start_workflow.assert_called_once()
call_kwargs = mock_hatchet.start_workflow.call_args.kwargs
assert call_kwargs["workflow_name"] == "DiarizationPipeline"
assert call_kwargs["input_data"]["transcript_id"] == transcript.id
assert call_kwargs["input_data"]["bucket_name"] == "daily-bucket"
assert call_kwargs["input_data"]["tracks"] == [
{"s3_key": k} for k in track_keys
]
mock_file_pipeline.delay.assert_not_called()

676
server/uv.lock generated
View File

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{ 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"
@@ -4145,22 +3487,6 @@ 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"

View File

@@ -0,0 +1,49 @@
# =======================================================
# Reflector Self-Hosted Production — Frontend Configuration
# Generated by: ./scripts/setup-selfhosted.sh
# =======================================================
# Site URL — set to your domain or server IP
# The setup script auto-detects this on Linux.
SITE_URL=https://localhost
NEXTAUTH_URL=https://localhost
NEXTAUTH_SECRET=changeme-generate-a-secure-random-string
# API URLs
# Public-facing (what the browser uses):
API_URL=https://localhost
WEBSOCKET_URL=auto
# Internal Docker network (server-side rendering):
SERVER_API_URL=http://server:1250
KV_URL=redis://redis:6379
# Authentication
# Set to true when Authentik is configured
FEATURE_REQUIRE_LOGIN=false
# Nullify auth vars when not using Authentik
AUTHENTIK_ISSUER=
AUTHENTIK_REFRESH_TOKEN_URL=
# =======================================================
# Authentik OAuth/OIDC (Optional)
# Uncomment and configure when enabling authentication.
# See docsv2/selfhosted-production.md for setup instructions.
# =======================================================
# FEATURE_REQUIRE_LOGIN=true
# AUTHENTIK_ISSUER=https://authentik.example.com/application/o/reflector
# AUTHENTIK_REFRESH_TOKEN_URL=https://authentik.example.com/application/o/token/
# AUTHENTIK_CLIENT_ID=your-client-id
# AUTHENTIK_CLIENT_SECRET=your-client-secret
# =======================================================
# Feature Flags
# =======================================================
# FEATURE_ROOMS=true
# FEATURE_BROWSE=true
# =======================================================
# Sentry (Optional)
# =======================================================
# SENTRY_DSN=

View File

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

View File

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

View File

@@ -1,18 +1,22 @@
import { useEffect, useState } from "react";
import { Topic, FinalSummary, Status } from "./webSocketTypes";
import { useError } from "../../(errors)/errorContext";
import type { components } from "../../reflector-api";
import type { components, operations } from "../../reflector-api";
type AudioWaveform = components["schemas"]["AudioWaveform"];
type GetTranscriptSegmentTopic =
components["schemas"]["GetTranscriptSegmentTopic"];
import { useQueryClient } from "@tanstack/react-query";
import { $api, WEBSOCKET_URL } from "../../lib/apiClient";
import { WEBSOCKET_URL } from "../../lib/apiClient";
import {
invalidateTranscript,
invalidateTranscriptTopics,
invalidateTranscriptWaveform,
} from "../../lib/apiHooks";
import { NonEmptyString } from "../../lib/utils";
import { useAuth } from "../../lib/AuthProvider";
import { parseNonEmptyString } from "../../lib/utils";
type TranscriptWsEvent =
operations["v1_transcript_get_websocket_events"]["responses"][200]["content"]["application/json"];
export type UseWebSockets = {
transcriptTextLive: string;
@@ -27,6 +31,7 @@ export type UseWebSockets = {
};
export const useWebSockets = (transcriptId: string | null): UseWebSockets => {
const auth = useAuth();
const [transcriptTextLive, setTranscriptTextLive] = useState<string>("");
const [translateText, setTranslateText] = useState<string>("");
const [title, setTitle] = useState<string>("");
@@ -331,155 +336,168 @@ export const useWebSockets = (transcriptId: string | null): UseWebSockets => {
};
if (!transcriptId) return;
const tsId = parseNonEmptyString(transcriptId);
const MAX_RETRIES = 10;
const url = `${WEBSOCKET_URL}/v1/transcripts/${transcriptId}/events`;
let ws = new WebSocket(url);
let ws: WebSocket | null = null;
let retryCount = 0;
let retryTimeout: ReturnType<typeof setTimeout> | null = null;
let intentionalClose = false;
ws.onopen = () => {
console.debug("WebSocket connection opened");
};
const connect = () => {
const subprotocols = auth.accessToken
? ["bearer", auth.accessToken]
: undefined;
ws = new WebSocket(url, subprotocols);
ws.onmessage = (event) => {
const message = JSON.parse(event.data);
ws.onopen = () => {
console.debug("WebSocket connection opened");
retryCount = 0;
};
try {
switch (message.event) {
case "TRANSCRIPT":
const newText = (message.data.text ?? "").trim();
const newTranslation = (message.data.translation ?? "").trim();
ws.onmessage = (event) => {
const message: TranscriptWsEvent = JSON.parse(event.data);
if (!newText) break;
try {
switch (message.event) {
case "TRANSCRIPT": {
const newText = (message.data.text ?? "").trim();
const newTranslation = (message.data.translation ?? "").trim();
console.debug("TRANSCRIPT event:", newText);
setTextQueue((prevQueue) => [...prevQueue, newText]);
setTranslationQueue((prevQueue) => [...prevQueue, newTranslation]);
if (!newText) break;
setAccumulatedText((prevText) => prevText + " " + newText);
break;
console.debug("TRANSCRIPT event:", newText);
setTextQueue((prevQueue) => [...prevQueue, newText]);
setTranslationQueue((prevQueue) => [
...prevQueue,
newTranslation,
]);
case "TOPIC":
setTopics((prevTopics) => {
const topic = message.data as Topic;
const index = prevTopics.findIndex(
(prevTopic) => prevTopic.id === topic.id,
);
if (index >= 0) {
prevTopics[index] = topic;
return prevTopics;
}
setAccumulatedText((prevText) =>
prevText.slice(topic.transcript.length),
);
return [...prevTopics, topic];
});
console.debug("TOPIC event:", message.data);
// Invalidate topics query to sync with WebSocket data
invalidateTranscriptTopics(
queryClient,
transcriptId as NonEmptyString,
);
break;
case "FINAL_SHORT_SUMMARY":
console.debug("FINAL_SHORT_SUMMARY event:", message.data);
break;
case "FINAL_LONG_SUMMARY":
if (message.data) {
setFinalSummary(message.data);
// Invalidate transcript query to sync summary
invalidateTranscript(queryClient, transcriptId as NonEmptyString);
setAccumulatedText((prevText) => prevText + " " + newText);
break;
}
break;
case "FINAL_TITLE":
console.debug("FINAL_TITLE event:", message.data);
if (message.data) {
case "TOPIC":
setTopics((prevTopics) => {
const topic = message.data;
const index = prevTopics.findIndex(
(prevTopic) => prevTopic.id === topic.id,
);
if (index >= 0) {
prevTopics[index] = topic;
return prevTopics;
}
setAccumulatedText((prevText) =>
prevText.slice(topic.transcript?.length ?? 0),
);
return [...prevTopics, topic];
});
console.debug("TOPIC event:", message.data);
invalidateTranscriptTopics(queryClient, tsId);
break;
case "FINAL_SHORT_SUMMARY":
console.debug("FINAL_SHORT_SUMMARY event:", message.data);
break;
case "FINAL_LONG_SUMMARY":
setFinalSummary({ summary: message.data.long_summary });
invalidateTranscript(queryClient, tsId);
break;
case "FINAL_TITLE":
console.debug("FINAL_TITLE event:", message.data);
setTitle(message.data.title);
// Invalidate transcript query to sync title
invalidateTranscript(queryClient, transcriptId as NonEmptyString);
}
break;
invalidateTranscript(queryClient, tsId);
break;
case "WAVEFORM":
console.debug(
"WAVEFORM event length:",
message.data.waveform.length,
);
if (message.data) {
setWaveForm(message.data.waveform);
invalidateTranscriptWaveform(
queryClient,
transcriptId as NonEmptyString,
case "WAVEFORM":
console.debug(
"WAVEFORM event length:",
message.data.waveform.length,
);
}
break;
case "DURATION":
console.debug("DURATION event:", message.data);
if (message.data) {
setWaveForm({ data: message.data.waveform });
invalidateTranscriptWaveform(queryClient, tsId);
break;
case "DURATION":
console.debug("DURATION event:", message.data);
setDuration(message.data.duration);
}
break;
break;
case "STATUS":
console.log("STATUS event:", message.data);
if (message.data.value === "error") {
setError(
Error("Websocket error status"),
"There was an error processing this meeting.",
case "STATUS":
console.log("STATUS event:", message.data);
if (message.data.value === "error") {
setError(
Error("Websocket error status"),
"There was an error processing this meeting.",
);
}
setStatus(message.data);
invalidateTranscript(queryClient, tsId);
if (message.data.value === "ended") {
intentionalClose = true;
ws?.close();
}
break;
case "ACTION_ITEMS":
console.debug("ACTION_ITEMS event:", message.data);
invalidateTranscript(queryClient, tsId);
break;
default: {
const _exhaustive: never = message;
console.warn(
`Received unknown WebSocket event: ${(_exhaustive as TranscriptWsEvent).event}`,
);
}
setStatus(message.data);
if (message.data.value === "ended") {
ws.close();
}
break;
default:
setError(
new Error(`Received unknown WebSocket event: ${message.event}`),
);
}
} catch (error) {
setError(error);
}
} catch (error) {
setError(error);
}
};
};
ws.onerror = (error) => {
console.error("WebSocket error:", error);
setError(new Error("A WebSocket error occurred."));
};
ws.onerror = (error) => {
console.error("WebSocket error:", error);
};
ws.onclose = (event) => {
console.debug("WebSocket connection closed");
switch (event.code) {
case 1000: // Normal Closure:
break;
case 1005: // Closure by client FF
break;
case 1001: // Navigate away
break;
case 1006: // Closed by client Chrome
console.warn(
"WebSocket closed by client, likely duplicated connection in react dev mode",
ws.onclose = (event) => {
console.debug("WebSocket connection closed, code:", event.code);
if (intentionalClose) return;
const normalCodes = [1000, 1001, 1005];
if (normalCodes.includes(event.code)) return;
if (retryCount < MAX_RETRIES) {
const delay = Math.min(1000 * Math.pow(2, retryCount), 30000);
console.log(
`WebSocket reconnecting in ${delay}ms (attempt ${retryCount + 1}/${MAX_RETRIES})`,
);
break;
default:
if (retryCount === 0) {
setError(
new Error("WebSocket connection lost"),
"Connection lost. Reconnecting...",
);
}
retryCount++;
retryTimeout = setTimeout(connect, delay);
} else {
setError(
new Error(`WebSocket closed unexpectedly with code: ${event.code}`),
"Disconnected from the server. Please refresh the page.",
);
console.log(
"Socket is closed. Reconnect will be attempted in 1 second.",
event.reason,
);
// todo handle reconnect with socket.io
}
}
};
};
connect();
return () => {
ws.close();
intentionalClose = true;
if (retryTimeout) clearTimeout(retryTimeout);
ws?.close();
};
}, [transcriptId]);

View File

@@ -24,24 +24,15 @@ import { useAuth } from "../../lib/AuthProvider";
import { useConsentDialog } from "../../lib/consent";
import {
useRoomJoinMeeting,
useRoomJoinedMeeting,
useRoomLeaveMeeting,
useMeetingStartRecording,
leaveRoomPostUrl,
LeaveRoomBody,
} from "../../lib/apiHooks";
import { omit } from "remeda";
import {
assertExists,
assertExistsAndNonEmptyString,
NonEmptyString,
parseNonEmptyString,
} from "../../lib/utils";
import {
assertMeetingId,
DailyRecordingType,
MeetingId,
} from "../../lib/types";
import { assertMeetingId, DailyRecordingType } from "../../lib/types";
import { useUuidV5 } from "react-uuid-hook";
const CONSENT_BUTTON_ID = "recording-consent";
@@ -188,58 +179,6 @@ const useFrame = (
] as const;
};
const leaveDaily = () => {
const frame = DailyIframe.getCallInstance();
frame?.leave();
};
const useDirtyDisconnects = (
meetingId: NonEmptyString,
roomName: NonEmptyString,
) => {
useEffect(() => {
if (!meetingId || !roomName) return;
const handleBeforeUnload = () => {
leaveDaily();
navigator.sendBeacon(
leaveRoomPostUrl(
{
room_name: roomName,
meeting_id: meetingId,
},
{
delay_seconds: 5,
},
),
undefined satisfies LeaveRoomBody,
);
};
window.addEventListener("beforeunload", handleBeforeUnload);
return () => window.removeEventListener("beforeunload", handleBeforeUnload);
}, [meetingId, roomName]);
};
const useDisconnects = (
meetingId: NonEmptyString,
roomName: NonEmptyString,
leaveMutation: ReturnType<typeof useRoomLeaveMeeting>,
) => {
useDirtyDisconnects(meetingId, roomName);
useEffect(() => {
return () => {
leaveDaily();
leaveMutation.mutate({
params: {
path: { meeting_id: meetingId, room_name: roomName },
query: { delay_seconds: 5 },
},
});
};
}, [meetingId, roomName]);
};
export default function DailyRoom({ meeting, room }: DailyRoomProps) {
const router = useRouter();
const params = useParams();
@@ -247,8 +186,6 @@ export default function DailyRoom({ meeting, room }: DailyRoomProps) {
const authLastUserId = auth.lastUserId;
const [container, setContainer] = useState<HTMLDivElement | null>(null);
const joinMutation = useRoomJoinMeeting();
const joinedMutation = useRoomJoinedMeeting();
const leaveMutation = useRoomLeaveMeeting();
const startRecordingMutation = useMeetingStartRecording();
const [joinedMeeting, setJoinedMeeting] = useState<Meeting | null>(null);
@@ -258,9 +195,7 @@ export default function DailyRoom({ meeting, room }: DailyRoomProps) {
useUuidV5(meeting.id, RAW_TRACKS_NAMESPACE)[0],
);
if (typeof params.roomName === "object")
throw new Error(`Invalid room name in params. array? ${params.roomName}`);
const roomName = assertExistsAndNonEmptyString(params.roomName);
const roomName = params?.roomName as string;
const {
showConsentModal,
@@ -302,8 +237,6 @@ export default function DailyRoom({ meeting, room }: DailyRoomProps) {
router.push("/browse");
}, [router]);
useDisconnects(meeting.id as MeetingId, roomName, leaveMutation);
const handleCustomButtonClick = useCallback(
(ev: DailyEventObjectCustomButtonClick) => {
if (ev.button_id === CONSENT_BUTTON_ID) {
@@ -316,15 +249,6 @@ export default function DailyRoom({ meeting, room }: DailyRoomProps) {
);
const handleFrameJoinMeeting = useCallback(() => {
joinedMutation.mutate({
params: {
path: {
room_name: roomName,
meeting_id: meeting.id,
},
},
});
if (meeting.recording_type === "cloud") {
console.log("Starting dual recording via REST API", {
cloudInstanceId,
@@ -384,10 +308,8 @@ export default function DailyRoom({ meeting, room }: DailyRoomProps) {
startRecordingWithRetry("raw-tracks", rawTracksInstanceId);
}
}, [
joinedMutation,
roomName,
meeting.id,
meeting.recording_type,
meeting.id,
startRecordingMutation,
cloudInstanceId,
rawTracksInstanceId,

View File

@@ -4,14 +4,12 @@ import React, { useEffect, useRef } from "react";
import { useQueryClient } from "@tanstack/react-query";
import { WEBSOCKET_URL } from "./apiClient";
import { useAuth } from "./AuthProvider";
import { z } from "zod";
import { invalidateTranscriptLists, TRANSCRIPT_SEARCH_URL } from "./apiHooks";
import { invalidateTranscript, invalidateTranscriptLists } from "./apiHooks";
import { parseNonEmptyString } from "./utils";
import type { operations } from "../reflector-api";
const UserEvent = z.object({
event: z.string(),
});
type UserEvent = z.TypeOf<typeof UserEvent>;
type UserWsEvent =
operations["v1_user_get_websocket_events"]["responses"][200]["content"]["application/json"];
class UserEventsStore {
private socket: WebSocket | null = null;
@@ -133,23 +131,26 @@ export function UserEventsProvider({
if (!detachRef.current) {
const onMessage = (event: MessageEvent) => {
try {
const msg = UserEvent.parse(JSON.parse(event.data));
const eventName = msg.event;
const msg: UserWsEvent = JSON.parse(event.data);
const invalidateList = () => invalidateTranscriptLists(queryClient);
switch (eventName) {
switch (msg.event) {
case "TRANSCRIPT_CREATED":
case "TRANSCRIPT_DELETED":
case "TRANSCRIPT_STATUS":
case "TRANSCRIPT_FINAL_TITLE":
case "TRANSCRIPT_DURATION":
invalidateList().then(() => {});
break;
default:
// Ignore other content events for list updates
invalidateTranscriptLists(queryClient).then(() => {});
invalidateTranscript(
queryClient,
parseNonEmptyString(msg.data.id),
).then(() => {});
break;
default: {
const _exhaustive: never = msg;
console.warn(
`Unknown user event: ${(_exhaustive as UserWsEvent).event}`,
);
}
}
} catch (err) {
console.warn("Invalid user event message", event.data);

View File

@@ -13,9 +13,33 @@ export const API_URL = !isBuildPhase
? getClientEnv().API_URL
: "http://localhost";
export const WEBSOCKET_URL = !isBuildPhase
? getClientEnv().WEBSOCKET_URL || "ws://127.0.0.1:1250"
: "ws://localhost";
/**
* Derive a WebSocket URL from the API_URL.
* Handles full URLs (http://host/api, https://host/api) and relative paths (/api).
* For full URLs, ws/wss is derived from the URL's own protocol.
* For relative URLs, ws/wss is derived from window.location.protocol.
*/
const deriveWebSocketUrl = (apiUrl: string): string => {
if (typeof window === "undefined") {
return "ws://localhost";
}
const parsed = new URL(apiUrl, window.location.origin);
const wsProtocol = parsed.protocol === "https:" ? "wss:" : "ws:";
// Normalize: remove trailing slash from pathname
const pathname = parsed.pathname.replace(/\/+$/, "");
return `${wsProtocol}//${parsed.host}${pathname}`;
};
const resolveWebSocketUrl = (): string => {
if (isBuildPhase) return "ws://localhost";
const raw = getClientEnv().WEBSOCKET_URL;
if (!raw || raw === "auto") {
return deriveWebSocketUrl(API_URL);
}
return raw;
};
export const WEBSOCKET_URL = resolveWebSocketUrl();
export const client = createClient<paths>({
baseUrl: API_URL,

View File

@@ -1,13 +1,13 @@
"use client";
import { $api, API_URL } from "./apiClient";
import { $api } from "./apiClient";
import { useError } from "../(errors)/errorContext";
import { QueryClient, useQueryClient } from "@tanstack/react-query";
import type { components, operations } from "../reflector-api";
import type { components } from "../reflector-api";
import { useAuth } from "./AuthProvider";
import { MeetingId } from "./types";
import { NonEmptyString } from "./utils";
import { createFinalURL, createQuerySerializer } from "openapi-fetch";
import type { TranscriptStatus } from "./transcript";
/*
* XXX error types returned from the hooks are not always correct; declared types are ValidationError but real type could be string or any other
@@ -105,6 +105,12 @@ export function useTranscriptProcess() {
});
}
const ACTIVE_TRANSCRIPT_STATUSES = new Set<TranscriptStatus>([
"processing",
"uploaded",
"recording",
]);
export function useTranscriptGet(transcriptId: NonEmptyString | null) {
return $api.useQuery(
"get",
@@ -118,6 +124,10 @@ export function useTranscriptGet(transcriptId: NonEmptyString | null) {
},
{
enabled: !!transcriptId,
refetchInterval: (query) => {
const status = query.state.data?.status;
return status && ACTIVE_TRANSCRIPT_STATUSES.has(status) ? 5000 : false;
},
},
);
}
@@ -808,44 +818,6 @@ export function useRoomJoinMeeting() {
);
}
export const LEAVE_ROOM_POST_URL_TEMPLATE =
"/v1/rooms/{room_name}/meetings/{meeting_id}/leave" as const;
export const leaveRoomPostUrl = (
path: operations["v1_rooms_leave_meeting"]["parameters"]["path"],
query?: operations["v1_rooms_leave_meeting"]["parameters"]["query"],
): string =>
createFinalURL(LEAVE_ROOM_POST_URL_TEMPLATE, {
baseUrl: API_URL,
params: { path, query },
querySerializer: createQuerySerializer(),
});
export type LeaveRoomBody = operations["v1_rooms_leave_meeting"]["requestBody"];
export function useRoomLeaveMeeting() {
return $api.useMutation("post", LEAVE_ROOM_POST_URL_TEMPLATE);
}
export const JOINED_ROOM_POST_URL_TEMPLATE =
"/v1/rooms/{room_name}/meetings/{meeting_id}/joined" as const;
export const joinedRoomPostUrl = (
params: operations["v1_rooms_joined_meeting"]["parameters"]["path"],
): string =>
createFinalURL(JOINED_ROOM_POST_URL_TEMPLATE, {
baseUrl: API_URL,
params: { path: params },
querySerializer: () => "",
});
export type JoinedRoomBody =
operations["v1_rooms_joined_meeting"]["requestBody"];
export function useRoomJoinedMeeting() {
return $api.useMutation("post", JOINED_ROOM_POST_URL_TEMPLATE);
}
export function useRoomIcsSync() {
const { setError } = useError();

View File

@@ -2,6 +2,7 @@ import {
assertExists,
assertExistsAndNonEmptyString,
NonEmptyString,
parseMaybeNonEmptyString,
parseNonEmptyString,
} from "./utils";
import { isBuildPhase } from "./next";
@@ -74,14 +75,14 @@ export const getClientEnvServer = (): ClientEnvCommon => {
if (isBuildPhase) {
return {
API_URL: getNextEnvVar("API_URL"),
WEBSOCKET_URL: getNextEnvVar("WEBSOCKET_URL"),
WEBSOCKET_URL: parseMaybeNonEmptyString(process.env.WEBSOCKET_URL ?? ""),
...features,
};
}
clientEnv = {
API_URL: getNextEnvVar("API_URL"),
WEBSOCKET_URL: getNextEnvVar("WEBSOCKET_URL"),
WEBSOCKET_URL: parseMaybeNonEmptyString(process.env.WEBSOCKET_URL ?? ""),
...features,
};
return clientEnv;

View File

@@ -171,48 +171,6 @@ export interface paths {
patch?: never;
trace?: never;
};
"/v1/rooms/{room_name}/meetings/{meeting_id}/joined": {
parameters: {
query?: never;
header?: never;
path?: never;
cookie?: never;
};
get?: never;
put?: never;
/**
* Rooms Joined Meeting
* @description Trigger presence poll (ideally when user actually joins meeting in Daily iframe)
*/
post: operations["v1_rooms_joined_meeting"];
delete?: never;
options?: never;
head?: never;
patch?: never;
trace?: never;
};
"/v1/rooms/{room_name}/meetings/{meeting_id}/leave": {
parameters: {
query?: never;
header?: never;
path?: never;
cookie?: never;
};
get?: never;
put?: never;
/**
* Rooms Leave Meeting
* @description Trigger presence recheck when user leaves meeting (e.g., tab close/navigation).
*
* Queues presence poll with optional delay to allow Daily.co to detect disconnect.
*/
post: operations["v1_rooms_leave_meeting"];
delete?: never;
options?: never;
head?: never;
patch?: never;
trace?: never;
};
"/v1/rooms/{room_id}/webhook/test": {
parameters: {
query?: never;
@@ -610,7 +568,10 @@ export interface paths {
path?: never;
cookie?: never;
};
/** Transcript Get Websocket Events */
/**
* Transcript WebSocket event schema
* @description Stub exposing the discriminated union of all transcript-level WS events for OpenAPI type generation. Real events are delivered over the WebSocket at the same path.
*/
get: operations["v1_transcript_get_websocket_events"];
put?: never;
post?: never;
@@ -706,6 +667,26 @@ export interface paths {
patch?: never;
trace?: never;
};
"/v1/events": {
parameters: {
query?: never;
header?: never;
path?: never;
cookie?: never;
};
/**
* User WebSocket event schema
* @description Stub exposing the discriminated union of all user-level WS events for OpenAPI type generation. Real events are delivered over the WebSocket at the same path.
*/
get: operations["v1_user_get_websocket_events"];
put?: never;
post?: never;
delete?: never;
options?: never;
head?: never;
patch?: never;
trace?: never;
};
"/v1/zulip/streams": {
parameters: {
query?: never;
@@ -1051,6 +1032,8 @@ export interface components {
room_name?: string | null;
/** Audio Deleted */
audio_deleted?: boolean | null;
/** Change Seq */
change_seq?: number | null;
};
/** GetTranscriptSegmentTopic */
GetTranscriptSegmentTopic: {
@@ -1197,6 +1180,8 @@ export interface components {
room_name?: string | null;
/** Audio Deleted */
audio_deleted?: boolean | null;
/** Change Seq */
change_seq?: number | null;
/** Participants */
participants:
| components["schemas"]["TranscriptParticipantWithEmail"][]
@@ -1260,6 +1245,8 @@ export interface components {
room_name?: string | null;
/** Audio Deleted */
audio_deleted?: boolean | null;
/** Change Seq */
change_seq?: number | null;
/** Participants */
participants:
| components["schemas"]["TranscriptParticipantWithEmail"][]
@@ -1324,6 +1311,8 @@ export interface components {
room_name?: string | null;
/** Audio Deleted */
audio_deleted?: boolean | null;
/** Change Seq */
change_seq?: number | null;
/** Participants */
participants:
| components["schemas"]["TranscriptParticipantWithEmail"][]
@@ -1395,6 +1384,8 @@ export interface components {
room_name?: string | null;
/** Audio Deleted */
audio_deleted?: boolean | null;
/** Change Seq */
change_seq?: number | null;
/** Participants */
participants:
| components["schemas"]["TranscriptParticipantWithEmail"][]
@@ -1468,6 +1459,8 @@ export interface components {
room_name?: string | null;
/** Audio Deleted */
audio_deleted?: boolean | null;
/** Change Seq */
change_seq?: number | null;
/** Participants */
participants:
| components["schemas"]["TranscriptParticipantWithEmail"][]
@@ -1853,6 +1846,8 @@ export interface components {
* @default 0
*/
total_match_count: number;
/** Change Seq */
change_seq?: number | null;
};
/**
* SourceKind
@@ -1919,6 +1914,33 @@ export interface components {
/** Name */
name: string;
};
/** TranscriptActionItems */
TranscriptActionItems: {
/** Action Items */
action_items: {
[key: string]: unknown;
};
};
/** TranscriptDuration */
TranscriptDuration: {
/** Duration */
duration: number;
};
/** TranscriptFinalLongSummary */
TranscriptFinalLongSummary: {
/** Long Summary */
long_summary: string;
};
/** TranscriptFinalShortSummary */
TranscriptFinalShortSummary: {
/** Short Summary */
short_summary: string;
};
/** TranscriptFinalTitle */
TranscriptFinalTitle: {
/** Title */
title: string;
};
/** TranscriptParticipant */
TranscriptParticipant: {
/** Id */
@@ -1959,6 +1981,113 @@ export interface components {
/** End */
end: number;
};
/** TranscriptText */
TranscriptText: {
/** Text */
text: string;
/** Translation */
translation: string | null;
};
/** TranscriptWaveform */
TranscriptWaveform: {
/** Waveform */
waveform: number[];
};
/** TranscriptWsActionItems */
TranscriptWsActionItems: {
/**
* @description discriminator enum property added by openapi-typescript
* @enum {string}
*/
event: "ACTION_ITEMS";
data: components["schemas"]["TranscriptActionItems"];
};
/** TranscriptWsDuration */
TranscriptWsDuration: {
/**
* @description discriminator enum property added by openapi-typescript
* @enum {string}
*/
event: "DURATION";
data: components["schemas"]["TranscriptDuration"];
};
/** TranscriptWsFinalLongSummary */
TranscriptWsFinalLongSummary: {
/**
* @description discriminator enum property added by openapi-typescript
* @enum {string}
*/
event: "FINAL_LONG_SUMMARY";
data: components["schemas"]["TranscriptFinalLongSummary"];
};
/** TranscriptWsFinalShortSummary */
TranscriptWsFinalShortSummary: {
/**
* @description discriminator enum property added by openapi-typescript
* @enum {string}
*/
event: "FINAL_SHORT_SUMMARY";
data: components["schemas"]["TranscriptFinalShortSummary"];
};
/** TranscriptWsFinalTitle */
TranscriptWsFinalTitle: {
/**
* @description discriminator enum property added by openapi-typescript
* @enum {string}
*/
event: "FINAL_TITLE";
data: components["schemas"]["TranscriptFinalTitle"];
};
/** TranscriptWsStatus */
TranscriptWsStatus: {
/**
* @description discriminator enum property added by openapi-typescript
* @enum {string}
*/
event: "STATUS";
data: components["schemas"]["TranscriptWsStatusData"];
};
/** TranscriptWsStatusData */
TranscriptWsStatusData: {
/**
* Value
* @enum {string}
*/
value:
| "idle"
| "uploaded"
| "recording"
| "processing"
| "error"
| "ended";
};
/** TranscriptWsTopic */
TranscriptWsTopic: {
/**
* @description discriminator enum property added by openapi-typescript
* @enum {string}
*/
event: "TOPIC";
data: components["schemas"]["GetTranscriptTopic"];
};
/** TranscriptWsTranscript */
TranscriptWsTranscript: {
/**
* @description discriminator enum property added by openapi-typescript
* @enum {string}
*/
event: "TRANSCRIPT";
data: components["schemas"]["TranscriptText"];
};
/** TranscriptWsWaveform */
TranscriptWsWaveform: {
/**
* @description discriminator enum property added by openapi-typescript
* @enum {string}
*/
event: "WAVEFORM";
data: components["schemas"]["TranscriptWaveform"];
};
/** UpdateParticipant */
UpdateParticipant: {
/** Speaker */
@@ -2029,6 +2158,109 @@ export interface components {
/** Email */
email: string | null;
};
/** UserTranscriptCreatedData */
UserTranscriptCreatedData: {
/**
* Id
* @description A non-empty string
*/
id: string;
};
/** UserTranscriptDeletedData */
UserTranscriptDeletedData: {
/**
* Id
* @description A non-empty string
*/
id: string;
};
/** UserTranscriptDurationData */
UserTranscriptDurationData: {
/**
* Id
* @description A non-empty string
*/
id: string;
/** Duration */
duration: number;
};
/** UserTranscriptFinalTitleData */
UserTranscriptFinalTitleData: {
/**
* Id
* @description A non-empty string
*/
id: string;
/**
* Title
* @description A non-empty string
*/
title: string;
};
/** UserTranscriptStatusData */
UserTranscriptStatusData: {
/**
* Id
* @description A non-empty string
*/
id: string;
/**
* Value
* @enum {string}
*/
value:
| "idle"
| "uploaded"
| "recording"
| "processing"
| "error"
| "ended";
};
/** UserWsTranscriptCreated */
UserWsTranscriptCreated: {
/**
* @description discriminator enum property added by openapi-typescript
* @enum {string}
*/
event: "TRANSCRIPT_CREATED";
data: components["schemas"]["UserTranscriptCreatedData"];
};
/** UserWsTranscriptDeleted */
UserWsTranscriptDeleted: {
/**
* @description discriminator enum property added by openapi-typescript
* @enum {string}
*/
event: "TRANSCRIPT_DELETED";
data: components["schemas"]["UserTranscriptDeletedData"];
};
/** UserWsTranscriptDuration */
UserWsTranscriptDuration: {
/**
* @description discriminator enum property added by openapi-typescript
* @enum {string}
*/
event: "TRANSCRIPT_DURATION";
data: components["schemas"]["UserTranscriptDurationData"];
};
/** UserWsTranscriptFinalTitle */
UserWsTranscriptFinalTitle: {
/**
* @description discriminator enum property added by openapi-typescript
* @enum {string}
*/
event: "TRANSCRIPT_FINAL_TITLE";
data: components["schemas"]["UserTranscriptFinalTitleData"];
};
/** UserWsTranscriptStatus */
UserWsTranscriptStatus: {
/**
* @description discriminator enum property added by openapi-typescript
* @enum {string}
*/
event: "TRANSCRIPT_STATUS";
data: components["schemas"]["UserTranscriptStatusData"];
};
/** ValidationError */
ValidationError: {
/** Location */
@@ -2477,72 +2709,6 @@ export interface operations {
};
};
};
v1_rooms_joined_meeting: {
parameters: {
query?: never;
header?: never;
path: {
room_name: string;
meeting_id: string;
};
cookie?: never;
};
requestBody?: never;
responses: {
/** @description Successful Response */
200: {
headers: {
[name: string]: unknown;
};
content: {
"application/json": unknown;
};
};
/** @description Validation Error */
422: {
headers: {
[name: string]: unknown;
};
content: {
"application/json": components["schemas"]["HTTPValidationError"];
};
};
};
};
v1_rooms_leave_meeting: {
parameters: {
query?: {
delay_seconds?: number;
};
header?: never;
path: {
room_name: string;
meeting_id: string;
};
cookie?: never;
};
requestBody?: never;
responses: {
/** @description Successful Response */
200: {
headers: {
[name: string]: unknown;
};
content: {
"application/json": unknown;
};
};
/** @description Validation Error */
422: {
headers: {
[name: string]: unknown;
};
content: {
"application/json": components["schemas"]["HTTPValidationError"];
};
};
};
};
v1_rooms_test_webhook: {
parameters: {
query?: never;
@@ -2801,6 +2967,8 @@ export interface operations {
source_kind?: components["schemas"]["SourceKind"] | null;
room_id?: string | null;
search_term?: string | null;
change_seq_from?: number | null;
sort_by?: ("created_at" | "change_seq") | null;
/** @description Page number */
page?: number;
/** @description Page size */
@@ -3531,7 +3699,16 @@ export interface operations {
[name: string]: unknown;
};
content: {
"application/json": unknown;
"application/json":
| components["schemas"]["TranscriptWsTranscript"]
| components["schemas"]["TranscriptWsTopic"]
| components["schemas"]["TranscriptWsStatus"]
| components["schemas"]["TranscriptWsFinalTitle"]
| components["schemas"]["TranscriptWsFinalLongSummary"]
| components["schemas"]["TranscriptWsFinalShortSummary"]
| components["schemas"]["TranscriptWsActionItems"]
| components["schemas"]["TranscriptWsDuration"]
| components["schemas"]["TranscriptWsWaveform"];
};
};
/** @description Validation Error */
@@ -3715,6 +3892,31 @@ export interface operations {
};
};
};
v1_user_get_websocket_events: {
parameters: {
query?: never;
header?: never;
path?: never;
cookie?: never;
};
requestBody?: never;
responses: {
/** @description Successful Response */
200: {
headers: {
[name: string]: unknown;
};
content: {
"application/json":
| components["schemas"]["UserWsTranscriptCreated"]
| components["schemas"]["UserWsTranscriptDeleted"]
| components["schemas"]["UserWsTranscriptStatus"]
| components["schemas"]["UserWsTranscriptFinalTitle"]
| components["schemas"]["UserWsTranscriptDuration"];
};
};
};
};
v1_zulip_get_streams: {
parameters: {
query?: never;

4
yarn.lock Normal file
View File

@@ -0,0 +1,4 @@
# THIS IS AN AUTOGENERATED FILE. DO NOT EDIT THIS FILE DIRECTLY.
# yarn lockfile v1