Logan
116 lines
3.7 KiB
Python
116 lines
3.7 KiB
Python
"""
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Background incident summary loop.
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Runs every SUMMARY_INTERVAL_MINUTES. Finds all active incidents with
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summary_stale=True, fetches all their call transcripts, and calls Gemini
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once per incident to produce a concise factual summary.
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By batching this way: Gemini is never called per-call — only periodically
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and only for incidents that have actually changed since the last run.
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"""
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import asyncio
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from datetime import datetime, timezone
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from typing import Optional
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from app.internal.logger import logger
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from app.internal import firestore as fstore
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from app.config import settings
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async def summarizer_loop() -> None:
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interval = settings.summary_interval_minutes * 60
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logger.info(f"Summarizer started — interval: {settings.summary_interval_minutes}m")
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while True:
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await asyncio.sleep(interval)
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try:
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await _run_summary_pass()
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except Exception as e:
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logger.error(f"Summarizer pass failed: {e}")
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async def _run_summary_pass() -> None:
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stale = await fstore.collection_list("incidents", status="active", summary_stale=True)
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if not stale:
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return
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logger.info(f"Summarizer: processing {len(stale)} stale incident(s)")
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for inc in stale:
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await _summarize_incident(inc)
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async def _summarize_incident(inc: dict) -> None:
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incident_id = inc.get("incident_id")
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if not incident_id:
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return
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call_ids: list[str] = inc.get("call_ids", [])
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if not call_ids:
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return
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# Fetch transcripts for all calls in this incident
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transcripts: list[str] = []
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for cid in call_ids:
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doc = await fstore.doc_get("calls", cid)
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if doc and doc.get("transcript"):
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transcripts.append(doc["transcript"])
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if not transcripts:
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# No transcripts yet — clear stale flag and wait for next pass
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await fstore.doc_set("incidents", incident_id, {"summary_stale": False})
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return
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summary = await asyncio.to_thread(_sync_summarize, inc, transcripts)
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now = datetime.now(timezone.utc).isoformat()
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updates: dict = {
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"summary_stale": False,
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"summary_last_run": now,
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}
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if summary:
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updates["summary"] = summary
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logger.info(f"Summarizer: updated summary for incident {incident_id}")
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else:
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logger.warning(f"Summarizer: Gemini returned nothing for incident {incident_id}")
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await fstore.doc_set("incidents", incident_id, updates)
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def _sync_summarize(inc: dict, transcripts: list[str]) -> Optional[str]:
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from app.config import settings
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from openai import OpenAI
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if not settings.openai_api_key:
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return None
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inc_type = inc.get("type", "unknown")
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location = inc.get("location") or "unknown location"
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tg_ids = ", ".join(inc.get("talkgroup_ids", [])) or "unknown"
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numbered = "\n".join(f"{i+1}. {t}" for i, t in enumerate(transcripts))
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prompt = f"""You are analyzing P25 public safety radio communications for a single active incident.
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Incident type: {inc_type}
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Location: {location}
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Talkgroup(s): {tg_ids}
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Transcripts ({len(transcripts)} calls, chronological):
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{numbered}
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Write a concise factual summary of this incident in 2-4 sentences. Include:
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- What happened
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- Location (most specific mentioned)
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- Units or resources involved if mentioned
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- Current status if determinable
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Be factual. Do not speculate beyond what the transcripts say. Do not use bullet points."""
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try:
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client = OpenAI(api_key=settings.openai_api_key)
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response = client.chat.completions.create(
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model="gpt-4o-mini",
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messages=[{"role": "user", "content": prompt}],
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)
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return response.choices[0].message.content.strip() or None
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except Exception as e:
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logger.warning(f"GPT-4o mini summary failed: {e}")
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return None
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