Files
hold-slayer/tests/test_learner.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

138 lines
5.5 KiB
Python

"""
Call-flow learner tests.
Exploration discoveries become a linked CallFlow, survive with the
persisted call record, and the learn_call_flow MCP tool turns them
into a stored flow (refining on subsequent calls).
"""
import pytest
from fastmcp import Client
from sqlalchemy.ext.asyncio import async_sessionmaker, create_async_engine
from sqlalchemy.pool import StaticPool
import db.database as dbmod
import services.llm_client as llm_mod
from core.call_manager import CallManager
from core.event_bus import EventBus
from db.database import Base
from mcp_server.server import create_mcp_server
from models.call import CallStatus
from models.call_flow import ActionType
from services import call_persistence as store
from services.call_flow_learner import CallFlowLearner
DISCOVERIES = [
{"timestamp": 1.0, "audio_type": "ringing", "confidence": 0.9,
"transcript": "", "action_taken": None},
{"timestamp": 4.0, "audio_type": "ivr_prompt", "confidence": 0.8,
"transcript": "press 1 for english press 2 for french",
"action_taken": {"dtmf": "1"}},
{"timestamp": 8.0, "audio_type": "ivr_prompt", "confidence": 0.8,
"transcript": "press 1 for billing press 2 for support press 0 for an agent",
"action_taken": {"dtmf": "0"}},
{"timestamp": 12.0, "audio_type": "music", "confidence": 0.9,
"transcript": "", "action_taken": None},
{"timestamp": 200.0, "audio_type": "live_human", "confidence": 0.85,
"transcript": "thank you for holding, how can I help",
"action_taken": None},
]
class TestBuildFlow:
async def test_discoveries_become_linked_steps(self):
learner = CallFlowLearner(llm_client=None)
flow = await learner.build_flow(
phone_number="+18005551234",
discovered_steps=DISCOVERIES,
intent="dispute a charge",
)
# ringing is skipped; menus/hold/human map to actions in order
assert [s.action for s in flow.steps] == [
ActionType.DTMF, ActionType.DTMF, ActionType.HOLD, ActionType.TRANSFER,
]
assert [s.action_value for s in flow.steps[:2]] == ["1", "0"]
assert [s.next_step for s in flow.steps[:-1]] == [s.id for s in flow.steps[1:]]
assert "auto-learned" in flow.tags
assert flow.phone_number == "+18005551234"
class TestExplorationPersistence:
async def test_exploration_steps_survive_with_the_record(self, mem_db):
cm = CallManager(EventBus(), on_call_ended=store.persist_call_on_end)
call = await cm.create_call("+18005551234", intent="dispute a charge")
call.exploration_steps.extend(DISCOVERIES)
await cm.end_call(call.id, CallStatus.COMPLETED)
async with mem_db() as session:
record = await store.get_record(session, call.id)
assert record.metadata_["exploration_steps"] == DISCOVERIES
@pytest.fixture
async def mem_db(monkeypatch):
engine = create_async_engine(
"sqlite+aiosqlite:///:memory:",
poolclass=StaticPool,
connect_args={"check_same_thread": False},
)
async with engine.begin() as conn:
await conn.run_sync(Base.metadata.create_all)
factory = async_sessionmaker(engine, expire_on_commit=False)
monkeypatch.setattr(dbmod, "_engine", engine)
monkeypatch.setattr(dbmod, "_session_factory", factory)
yield factory
await engine.dispose()
@pytest.fixture
def no_llm(monkeypatch):
"""learn_call_flow must work without an LLM (labels stay heuristic)."""
monkeypatch.setattr(llm_mod, "_shared_client", None)
monkeypatch.setattr(llm_mod, "_shared_failed", True)
class TestLearnCallFlowTool:
async def _completed_exploration_call(self, number: str) -> str:
cm = CallManager(EventBus(), on_call_ended=store.persist_call_on_end)
call = await cm.create_call(number, intent="dispute a charge")
call.exploration_steps.extend(DISCOVERIES)
await cm.end_call(call.id, CallStatus.COMPLETED)
return call.id
async def test_learns_then_refines(self, mem_db, no_llm):
call_id = await self._completed_exploration_call("+18005551234")
mcp = create_mcp_server(lambda: None)
async with Client(mcp) as client:
result = await client.call_tool("learn_call_flow", {"call_id": call_id})
assert "Learned new flow" in result.content[0].text
async with mem_db() as session:
row = await store.get_flow_by_number(session, "+18005551234")
assert row is not None
assert len(row.steps) == 4
assert "auto-learned" in row.tags
result = await client.call_tool("learn_call_flow", {"call_id": call_id})
assert "Refined existing flow" in result.content[0].text
async def test_call_without_exploration_data(self, mem_db, no_llm):
cm = CallManager(EventBus(), on_call_ended=store.persist_call_on_end)
call = await cm.create_call("+15550001111")
await cm.end_call(call.id, CallStatus.COMPLETED)
mcp = create_mcp_server(lambda: None)
async with Client(mcp) as client:
result = await client.call_tool("learn_call_flow", {"call_id": call.id})
assert "no exploration data" in result.content[0].text
async def test_unknown_call(self, mem_db, no_llm):
mcp = create_mcp_server(lambda: None)
async with Client(mcp) as client:
result = await client.call_tool(
"learn_call_flow", {"call_id": "call_nope"}
)
assert "No record found" in result.content[0].text