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avc-phone-ai/extract.py
2026-06-23 22:38:22 +00:00

102 lines
4.2 KiB
Python

"""Post-call appointment extraction.
Instead of unreliable in-call tool-calling (which made llama3.1:8b speak raw JSON),
we let the agent gather appointment details conversationally, then run ONE structured
extraction over the finished transcript and write it to Odoo. Reliable because it's a
single JSON-mode completion, not mid-conversation tool emission.
"""
import json
import re
import httpx
from loguru import logger
from practice import persist_appointment
_EXTRACT_INSTRUCTIONS = (
"You are reviewing a phone-call transcript between a caller and the receptionist "
"for an optometry practice. Extract any APPOINTMENT REQUEST the caller made.\n"
"Respond with ONLY a JSON object with these keys:\n"
' "wants_appointment": boolean — true only if the caller asked to book/schedule a visit\n'
' "patient_name": string or null\n'
' "callback_number": string or null (digits the caller gave to be called back)\n'
' "location": string or null (which office/city)\n'
' "reason": string or null (e.g. eye exam, broken glasses)\n'
' "preferred_time": string or null (day/time in the caller\'s words)\n'
"Use null for anything not clearly stated. Do not invent values."
)
async def extract_and_record(messages, ollama_url, model, call_sid=None, caller_number=None):
"""Extract an appointment from the transcript and persist it. Returns the record
dict if one was saved, else None."""
# Build a plain transcript from the conversation (skip the system prompt).
turns = [
f"{m['role']}: {m['content']}"
for m in messages
if m.get("role") in ("user", "assistant") and isinstance(m.get("content"), str) and m["content"].strip()
]
if not any(m.get("role") == "user" for m in messages):
return None # nobody said anything
transcript = "\n".join(turns)
base = ollama_url.rstrip("/")
if base.endswith("/v1"):
base = base[:-3]
try:
async with httpx.AsyncClient(timeout=30) as client:
r = await client.post(
f"{base}/api/chat",
json={
"model": model,
"format": "json",
"stream": False,
"options": {"temperature": 0},
"messages": [
{"role": "system", "content": _EXTRACT_INSTRUCTIONS},
{"role": "user", "content": f"Transcript:\n{transcript}"},
],
},
)
r.raise_for_status()
data = json.loads(r.json()["message"]["content"])
except Exception:
logger.exception("Appointment extraction call failed")
return None
if not data.get("wants_appointment"):
logger.info("Post-call extraction: no appointment requested")
return None
# Don't create near-empty cards from quick hang-ups: require at least a name or a
# reason. A bare location + caller-ID isn't enough to be worth a worklist card.
name = (data.get("patient_name") or "").strip()
reason_raw = (data.get("reason") or "").strip()
if not name and not reason_raw:
logger.info("Post-call extraction: appointment intent but no name/reason captured — skipping card")
return None
# Prefer the verified Twilio caller-ID over a number pulled from the transcript —
# the model sometimes invents/echoes a phone number. Keep a genuinely different
# spoken number as a note for staff.
spoken = (data.get("callback_number") or "").strip()
callback = caller_number or spoken or None
reason = data.get("reason")
if spoken and caller_number and re.sub(r"\D", "", spoken) != re.sub(r"\D", "", caller_number):
reason = f"{reason or ''} (caller mentioned alternate number: {spoken})".strip()
record = {
"call_sid": call_sid,
"patient_name": data.get("patient_name"),
"callback_number": callback,
"location": data.get("location"),
"reason": reason,
"preferred_time": data.get("preferred_time"),
"source": "post_call_extraction",
}
where = persist_appointment(record)
logger.info(f"Post-call appointment saved ({where}): {record['patient_name']} / {record['location']}")
return record