The SvelteKit build was always made for the root (no base path); it
now mounts at / — registered last so /api/v1, /ws, /health, and /mcp
match first — and the JSON root endpoint is gone (its info lives in
/health and gateway_status). REST routers move from /api/* to
/api/v1/*; /ws and /health stay put; /mcp/ unchanged. Dashboard API
client, tests, README, and docs updated; dashboard rebuilt (build/ is
gitignored).
Verified live: / serves the UI, /api/v1 answers 200/401, the old
/api paths 404, MCP still lists 15 tools.
Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
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>
The gateway was the composition root, device registry, inbound-call
policy, and call-operations service in one class, with core↔services
circular imports papered over by function-local imports, wiring done
by assigning private attributes, and MCP tools duplicating REST query
logic against their own sessions.
Composition:
- main.py's lifespan now builds every service and wires them by
constructor/registration. gateway.from_config() is gone; core/ no
longer imports services/ anywhere — the cycle is dead.
- Inbound-call policy moved to ReceptionistService.on_inbound_call
(routing evaluation, reject/answer, screening dispatch); wired as
the engine's on_incoming_call by the lifespan. Receptionist deps
(tts/transcription/recording/routing) are constructor-injected —
no more gateway._tts reach-through or importing hold_slayer's
private _get_llm (now services.llm_client.get_llm, shared).
- Hold-slayer launch goes through a mode-handler registry
(register_mode_handler); the gateway no longer knows the service's
type. CallManager takes on_call_ended in its constructor.
- build_sip_engine() is a pure function taking explicit callbacks.
- api/routing.py uses the routing service from app.state via a
proper dependency instead of gateway._routing.
Shared data layer:
- db.session_scope() is the one session convention (get_db wraps it).
- services/call_persistence.py gains the query/write functions and
the single StoredCallFlow→CallFlow mapper; api/call_flows.py,
api/call_history.py, and the six DB-touching MCP tools are thin
wrappers over them — the two surfaces can't drift.
- legs_for_call() replaces the three private _call_legs scans
(gateway transfer/hangup, REST dtmf, MCP dtmf).
7 new tests (mode-handler launch, on_call_ended hook, receptionist
inbound answer/reject, call-flow CRUD round-trip and history routes
against real SQLite through the shared layer). aiosqlite added to dev
deps for that.
Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
The MCP server was created but never mounted — no client could reach
it. Mount it at /mcp/ over streamable HTTP with a combined lifespan,
resolving the gateway lazily so mounting happens at app construction.
Security and safety for the agent surface:
- One static API_TOKEN (SecretStr) enforced across REST (dependency),
WebSocket (query param/header before accept), and MCP
(StaticTokenVerifier). Startup refuses tokenless non-loopback binds.
- Emergency numbers (911/9911/112) always refused on make_call, plus a
MAX_CONCURRENT_CALLS cap; ValueError surfaces as 400/ToolError.
- Safe defaults: debug off, no credential in default DATABASE_URL,
SIP/LLM/TTS secrets as SecretStr.
Cleanups:
- Delete broken learn_call_flow tool (wrong ctor args, nonexistent
method) and the never-fed CallAnalytics service; keep
call_flow_learner for proper wiring later.
- Trim dial_plan to what is actually used (emergency guard, extension
allocation); delete the unreferenced matcher/normaliser.
- Register call_history before calls so /api/calls/history is no
longer shadowed by /api/calls/{call_id}.
- fastmcp pinned >=3.0 (http_app + StaticTokenVerifier).
New tests: MCP in-memory client (tool surface, lazy gateway, emergency
refusal, call cap) and API security (401 paths, route order, mount).
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
