Files
hold-slayer/services/call_persistence.py
Robert Helewka ff7ea8623a Stage 6: learn_call_flow rebuilt on the learner, docs truth sweep
The call-flow learner finally gets fed: exploration mode records its
IVR discoveries on the call (ActiveCall.exploration_steps) instead of
throwing them away, persistence stores them in the call record's
metadata, and the rebuilt learn_call_flow MCP tool turns a completed
exploration call into a stored flow via CallFlowLearner — correct
constructor (llm_client from get_llm, heuristic labels when the LLM
is unavailable), build for a new number, merge/refine when a flow
already exists. save_learned_flow/update_flow_from_model keep the
CallFlow↔row mapping in call_persistence.

Test gaps closed: tests/test_learner.py (discoveries→linked steps,
exploration persistence, learn-then-refine through the in-memory MCP
client, no-data and unknown-call answers) and tests/test_websocket.py
(4401 without token, trunk-status-then-replay on connect, per-call
stream filtering).

Docs aligned to code: README (15 tools incl. learn_call_flow, HTTP
not SSE, Python 3.12+, PostgreSQL+Alembic — no SQLite fallback, media
pipeline marked stub-mode until pjsua2 installed, Alembic and honest
/health checked off); docs/mcp-server.md rewritten against the actual
tool surface (hangup not end_call, real params, 3 real resources,
/mcp/ streamable HTTP + bearer auth); architecture/development/
configuration drift fixed.

pyproject: pruned never-imported deps (websockets, librosa,
soundfile, python-multipart).

Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
2026-07-10 13:45:35 -04:00

369 lines
12 KiB
Python

"""
Call Persistence — the data-access layer for calls and call flows.
Holds the on-hangup persistence hook plus the query/write functions
that both the REST handlers and the MCP tools call, so the two
surfaces can't drift. Every function takes an AsyncSession; callers
own the transaction (get_db for REST, session_scope for MCP/services).
"""
import asyncio
import logging
import uuid
from datetime import datetime
from sqlalchemy import desc, select
from sqlalchemy.ext.asyncio import AsyncSession
from db.database import (
CallRecord,
RecordingRecord,
StoredCallFlow,
TranscriptChunk,
session_scope,
)
from db.database import Device as DeviceRow
from models.call import ActiveCall, CallStatus
from models.call_flow import CallFlow, CallFlowStep
from models.device import Device
logger = logging.getLogger(__name__)
def flow_to_model(row: StoredCallFlow) -> CallFlow:
"""The one StoredCallFlow-row → CallFlow-model mapping."""
return CallFlow(
id=row.id,
name=row.name,
phone_number=row.phone_number,
description=row.description or "",
steps=[CallFlowStep(**s) for s in (row.steps or [])],
tags=row.tags or [],
notes=row.notes,
avg_hold_time=row.avg_hold_time,
success_rate=row.success_rate,
last_used=row.last_used,
times_used=row.times_used or 0,
)
def record_summary(row: CallRecord) -> dict:
"""The one CallRecord-row → list-item mapping."""
return {
"id": row.id,
"direction": row.direction,
"remote_number": row.remote_number,
"status": row.status,
"mode": row.mode,
"intent": row.intent,
"started_at": row.started_at.isoformat() if row.started_at else None,
"ended_at": row.ended_at.isoformat() if row.ended_at else None,
"duration": row.duration,
"hold_time": row.hold_time,
"device_used": row.device_used,
"summary": row.summary,
}
def record_detail(row: CallRecord) -> dict:
"""Full CallRecord-row mapping, superset of record_summary."""
return record_summary(row) | {
"action_items": row.action_items,
"sentiment": row.sentiment,
"call_flow_id": row.call_flow_id,
"classification_timeline": row.classification_timeline,
}
def chunk_to_dict(row: TranscriptChunk) -> dict:
"""The one TranscriptChunk-row → dict mapping."""
return {
"seq": row.seq,
"t_offset_ms": row.t_offset_ms,
"speaker": row.speaker,
"text": row.text,
"confidence": row.confidence,
}
# ================================================================
# Call flows
# ================================================================
async def get_flow(session: AsyncSession, flow_id: str) -> StoredCallFlow | None:
result = await session.execute(
select(StoredCallFlow).where(StoredCallFlow.id == flow_id)
)
return result.scalar_one_or_none()
async def get_flow_by_number(
session: AsyncSession, phone_number: str
) -> StoredCallFlow | None:
result = await session.execute(
select(StoredCallFlow).where(StoredCallFlow.phone_number == phone_number)
)
return result.scalar_one_or_none()
async def list_flows(session: AsyncSession) -> list[StoredCallFlow]:
result = await session.execute(select(StoredCallFlow))
return list(result.scalars().all())
async def create_flow(
session: AsyncSession,
flow_id: str,
name: str,
phone_number: str,
steps: list[dict],
description: str | None = None,
tags: list[str] | None = None,
notes: str | None = None,
) -> StoredCallFlow:
row = StoredCallFlow(
id=flow_id,
name=name,
phone_number=phone_number,
description=description,
steps=steps,
tags=tags,
notes=notes,
last_verified=datetime.now(),
)
session.add(row)
await session.flush()
return row
async def save_learned_flow(session: AsyncSession, flow: CallFlow) -> StoredCallFlow:
"""The one CallFlow-model → row mapping (auto-learned flows)."""
row = StoredCallFlow(
id=flow.id,
name=flow.name,
phone_number=flow.phone_number,
description=flow.description,
steps=[s.model_dump(mode="json") for s in flow.steps],
tags=flow.tags,
notes=flow.notes,
times_used=flow.times_used,
last_used=flow.last_used,
last_verified=datetime.now(),
)
session.add(row)
await session.flush()
return row
async def update_flow_from_model(
session: AsyncSession, row: StoredCallFlow, flow: CallFlow
) -> None:
"""Write a refined CallFlow back onto its existing row."""
row.steps = [s.model_dump(mode="json") for s in flow.steps]
row.times_used = flow.times_used
row.last_used = flow.last_used
row.notes = flow.notes
await session.flush()
# ================================================================
# Devices
# ================================================================
async def create_device_row(session: AsyncSession, device: Device) -> None:
"""The one Device-model → row mapping."""
session.add(DeviceRow(
id=device.id,
name=device.name,
type=device.type.value,
sip_uri=device.sip_uri,
phone_number=device.phone_number,
priority=device.priority,
capabilities=device.capabilities,
is_online=device.is_online,
))
await session.flush()
async def update_device_row(
session: AsyncSession, device_id: str, values: dict
) -> None:
result = await session.execute(
select(DeviceRow).where(DeviceRow.id == device_id)
)
row = result.scalar_one_or_none()
if row is None:
return
for key, value in values.items():
if key == "type" and value is not None:
value = value.value if hasattr(value, "value") else value
setattr(row, key, value)
async def delete_device_row(session: AsyncSession, device_id: str) -> None:
result = await session.execute(
select(DeviceRow).where(DeviceRow.id == device_id)
)
row = result.scalar_one_or_none()
if row is not None:
await session.delete(row)
# ================================================================
# Call history / records
# ================================================================
async def get_record(session: AsyncSession, call_id: str) -> CallRecord | None:
result = await session.execute(
select(CallRecord).where(CallRecord.id == call_id)
)
return result.scalar_one_or_none()
async def search_history(
session: AsyncSession,
number: str | None = None,
number_contains: str | None = None,
intent_contains: str | None = None,
status: str | None = None,
since: datetime | None = None,
until: datetime | None = None,
limit: int = 50,
offset: int = 0,
) -> list[CallRecord]:
stmt = select(CallRecord).order_by(desc(CallRecord.started_at))
if number:
stmt = stmt.where(CallRecord.remote_number == number)
if number_contains:
stmt = stmt.where(CallRecord.remote_number.contains(number_contains))
if intent_contains:
stmt = stmt.where(CallRecord.intent.icontains(intent_contains))
if status:
stmt = stmt.where(CallRecord.status == status)
if since:
stmt = stmt.where(CallRecord.started_at >= since)
if until:
stmt = stmt.where(CallRecord.started_at <= until)
result = await session.execute(stmt.offset(offset).limit(limit))
return list(result.scalars().all())
async def get_transcript_chunks(
session: AsyncSession, call_id: str
) -> list[TranscriptChunk]:
result = await session.execute(
select(TranscriptChunk)
.where(TranscriptChunk.call_id == call_id)
.order_by(TranscriptChunk.seq)
)
return list(result.scalars().all())
async def latest_recording(
session: AsyncSession, call_id: str
) -> RecordingRecord | None:
result = await session.execute(
select(RecordingRecord)
.where(RecordingRecord.call_id == call_id)
.order_by(desc(RecordingRecord.started_at))
)
return result.scalars().first()
async def persist_call_on_create(call: ActiveCall) -> None:
"""Insert an in_progress CallRecord the moment a call starts.
Wired into CallManager as its on_call_created hook — a crash
mid-call leaves this row behind instead of erasing the call from
history. persist_call_on_end updates it to the terminal state.
"""
await _with_retry(_insert_in_progress_record, call)
async def persist_call_on_end(call: ActiveCall, final_status: CallStatus) -> None:
"""Finalize the CallRecord and write transcript chunks for `call`.
Wired into CallManager as its on_call_ended hook by the
composition root in main.py.
"""
await _with_retry(_finalize_call_record, call, final_status)
async def _with_retry(write, call: ActiveCall, *args) -> None:
"""Losing the row means the call never happened as far as history
is concerned, so the final failure logs at ERROR with identifiers."""
for attempt in range(3):
try:
await write(call, *args)
return
except Exception as e:
if attempt == 2:
logger.error(
f"Call record lost ({write.__name__}): id={call.id} "
f"number={call.remote_number}: {e}"
)
return
await asyncio.sleep(2**attempt)
async def _insert_in_progress_record(call: ActiveCall) -> None:
async with session_scope() as session:
session.add(CallRecord(
id=call.id,
direction=call.direction,
remote_number=call.remote_number,
status="in_progress",
mode=call.mode.value,
intent=call.intent,
started_at=call.started_at,
device_used=call.device,
call_flow_id=call.call_flow_id,
metadata_={"services": list(call.services)},
))
async def _finalize_call_record(call: ActiveCall, final_status: CallStatus) -> None:
async with session_scope() as session:
record = await get_record(session, call.id)
if record is None:
# The create-time insert failed (or predates the hook);
# write the whole row now instead.
record = CallRecord(id=call.id)
session.add(record)
record.direction = call.direction
record.remote_number = call.remote_number
record.status = final_status.value
record.mode = call.mode.value
record.intent = call.intent
record.started_at = call.started_at
record.ended_at = datetime.now()
record.duration = int(call.duration)
record.hold_time = int(call.hold_time)
record.device_used = call.device
record.call_flow_id = call.call_flow_id
record.classification_timeline = [
{
"timestamp": c.timestamp,
"audio_type": c.audio_type.value,
"confidence": c.confidence,
}
for c in call.classification_history
]
metadata = {"services": list(call.services)}
if call.exploration_steps:
metadata["exploration_steps"] = call.exploration_steps
record.metadata_ = metadata
# Each transcript entry gets its own row with a sequence number
# and real offset so the dashboard can render click-to-seek.
for seq, entry in enumerate(call.transcript_chunks):
session.add(TranscriptChunk(
id=f"tc_{uuid.uuid4().hex[:10]}",
call_id=call.id,
seq=seq,
t_offset_ms=entry.t_offset_ms,
speaker=entry.speaker,
text=entry.text,
))