Alembic replaces create_all as the schema authority: async env.py
against Base.metadata (CLI and in-app entry paths share it via
config.attributes["connection"]), an autogenerated baseline of the
create_all-era schema, and init_db now runs upgrade head — stamping
the baseline first on a pre-Alembic database so existing deployments
adopt cleanly. create_all remains for tests only.
Calls are durable from the start: CallManager gains an
on_call_created hook (wired to persist_call_on_create) that inserts
an in_progress CallRecord the moment a call is created;
persist_call_on_end finalizes that same row. A SIGKILL mid-call now
leaves an in_progress row instead of erasing the call from history
(verified live against the dev database).
One transcript representation: ActiveCall.transcript_chunks holds
TranscriptEntry (t_offset_ms, speaker, text) — add_transcript stamps
real offsets from connect time, receptionist passes speaker instead
of encoding it into "caller: ..." strings, persisted chunks carry
real seek offsets, and the dead CallRecord.transcript Text column is
dropped by migration. Device.is_online migrates String → Boolean
(with a USING cast for existing rows).
Model de-triplication: CallResponse/CallStatusResponse build via
from_call classmethods (one ActiveCall→response mapping);
DeviceStatus deleted — can_receive_call is a computed field on
Device and the list endpoint returns the domain model; all row↔dict
and row↔domain mapping now lives in call_persistence.py
(record_summary/record_detail/chunk_to_dict + device row functions).
New tests/test_data_layer.py: upgrade-head-matches-models,
pre-Alembic adoption, durable in_progress rows, end-without-create
fallback, transcript offsets, consolidated response models.
Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
Engine mode is now explicit: USE_MOCK_SIP=true is the only way to get
the mock engine; an unconfigured trunk fails startup with guidance
instead of silently degrading. Root-caused why the engine always ran
mock: nested pydantic-settings never read .env (no env_file on the
sub-settings classes) — all 8 now declare it.
/health stops lying: reports engine mode (sippy|mock), a live DB
SELECT 1, trunk registration state with reason, and TTS/STT
availability from their last real request; "healthy" now requires
ready + db + sippy + registered trunk.
Error policy: leaf services (tts/transcription/llm_client) raise and
track availability; call-loop callers catch, publish EventType.ERROR
naming the failed service, and apply an explicit fallback. Persistence
writes get one bounded 3x exponential retry, then an ERROR log — no
more silent data loss.
Event bus: a full subscriber queue drops its oldest event (counted)
instead of silently evicting the subscription; subscribe(replay_last=N)
delivers the advertised history replay, used by /ws/events (25).
Receptionist correctness: a matched TAKE_MESSAGE rule beats the LLM;
voicemail polls for early hangup and stops/transcribes/hangs up in
finally; RecordingSession finally keeps its leg_ids so taps detach.
Dead code removed: models/contact.py + Contact table, dtmf_buffer,
transcribe_stream stub, SMS stub in notification.py.
Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
Adds read-only access to persisted call records for the dashboard
and implements a client for the Rhema text-to-speech service.
- api/call_history.py: New router providing paged call lists
and detailed call records with transcript metadata.
- services/tts.py: Async client for OpenAI-compatible TTS
endpoints (Rhema/Kokoro) used for call-flow steps.
Complete project scaffolding and core implementation of an AI-powered
telephony system that calls companies, navigates IVR menus, waits on
hold, and transfers to the user when a human answers.
Key components:
- FastAPI server with REST API, WebSocket, and MCP (SSE) interfaces
- SIP/VoIP call management via PJSUA2 with RTP audio streaming
- LLM-powered IVR navigation using OpenAI/Anthropic with tool calling
- Hold detection service combining audio analysis and silence detection
- Real-time STT (Whisper/Deepgram) and TTS (OpenAI/Piper) pipelines
- Call recording with per-channel and mixed audio capture
- Event bus (asyncio pub/sub) for real-time client updates
- Web dashboard with live call monitoring
- SQLite persistence via SQLAlchemy with call history and analytics
- Notification support (email, SMS, webhook, desktop)
- Docker Compose deployment with Opal VoIP and Opal Media containers
- Comprehensive test suite with unit, integration, and E2E tests
- Simplified .gitignore and full project documentation in README
