298 lines
11 KiB
Python
298 lines
11 KiB
Python
"""Signal ingest/fetch endpoints."""
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from __future__ import annotations
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import json
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from fastapi import APIRouter, BackgroundTasks, Depends, HTTPException
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from sqlalchemy.ext.asyncio import AsyncSession
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from sqlalchemy.future import select
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from ...database import get_db
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from ...dependencies.tenant import get_tenant_id
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from ...models import Signal
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from ...schemas import SignalCreate, SignalPriority, classify_signal_priority
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from ...services.analyzer import analyze_impact
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from ...services.fetcher import fetch_hn_stories
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from ...services.lark import LarkService
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from ...services.llm import llm_service
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from ...services.plane import plane_service
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router = APIRouter()
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lark_service = LarkService()
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@router.post("/ingest", response_model=dict)
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async def ingest_signal(
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signal: SignalCreate,
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background_tasks: BackgroundTasks,
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db: AsyncSession = Depends(get_db),
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tenant_id: int = Depends(get_tenant_id),
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):
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"""接入外部信号，按优先级处理"""
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initial_priority = signal.priority or classify_signal_priority(signal.impact_score)
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new_signal = Signal(
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source=signal.source,
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content=signal.content,
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impact_score=signal.impact_score,
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priority=initial_priority.value,
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)
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db.add(new_signal)
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await db.commit()
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await db.refresh(new_signal)
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if initial_priority == SignalPriority.LOW:
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return {
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"id": str(new_signal.id),
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"priority": initial_priority.value,
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"status": "recorded",
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"message": "Low priority signal recorded without processing",
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}
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async def process_signal_internal():
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try:
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relevant_context = await llm_service.find_relevant_context(
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signal_content=signal.content,
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db_session=db,
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top_k=3,
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min_similarity=0.3,
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tenant_id=tenant_id,
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)
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strategy_result = await llm_service.evaluate_with_voting_async(
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signal_content=signal.content,
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relevant_context=relevant_context,
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impact_score=signal.impact_score,
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db=db,
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tenant_id=tenant_id,
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)
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except RuntimeError:
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if initial_priority == SignalPriority.CRITICAL:
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raise HTTPException(status_code=403, detail="预算超限，AI 调用被阻止（hard limit）")
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return {
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"id": str(new_signal.id),
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"priority": initial_priority.value,
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"status": "blocked",
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"processing_mode": "background",
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"message": "预算超限，AI 调用被阻止（hard limit）",
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}
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is_strategic = strategy_result.get("is_strategic", False)
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decision_proposal = strategy_result.get("decision_proposal", {})
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tasks = strategy_result.get("tasks", [])
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confidence = strategy_result.get("confidence", 0.0)
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final_priority = classify_signal_priority(signal.impact_score, confidence)
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new_signal.priority = final_priority.value
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sync_result = None
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notification_sent = False
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if final_priority in [SignalPriority.CRITICAL, SignalPriority.HIGH]:
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if is_strategic and tasks:
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sync_result = await plane_service.sync_tasks(
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tasks,
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is_urgent=(final_priority == SignalPriority.CRITICAL),
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)
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default_chat_id = "oc_1234567890"
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await lark_service.send_strategic_alert(
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default_chat_id,
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signal.content,
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decision_proposal,
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tasks,
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)
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notification_sent = True
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new_signal.impact_score = 1.0
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analysis_data = {
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"decision_proposal": decision_proposal,
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"competitiveness_radar": strategy_result.get("competitiveness_radar"),
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"detected_tech_stacks": strategy_result.get("detected_tech_stacks", []),
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"related_knowledge_nodes": strategy_result.get("related_knowledge_nodes", []),
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"rag_context_used": len(relevant_context) if relevant_context else 0,
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"rag_context_sources": [ctx["id"] for ctx in (relevant_context or [])],
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}
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if "_voting" in strategy_result:
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voting_info = strategy_result["_voting"]
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analysis_data["voting"] = {
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"enabled": voting_info.get("enabled"),
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"models_used": voting_info.get("models_used"),
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"strategic_votes": voting_info.get("strategic_votes"),
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"total_votes": voting_info.get("total_votes"),
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"unanimous": voting_info.get("unanimous"),
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}
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new_signal.strategic_analysis = json.dumps(analysis_data)
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new_signal.tasks_generated = json.dumps(tasks)
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new_signal.processed = True
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await db.commit()
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await db.refresh(new_signal)
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return {
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"id": str(new_signal.id),
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"priority": final_priority.value,
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"is_strategic": is_strategic,
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"confidence": confidence,
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"decision_proposal": decision_proposal,
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"rag_context_used": len(relevant_context) if relevant_context else 0,
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"voting": strategy_result.get("_voting"),
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"tasks_generated": len(tasks),
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"sync_result": sync_result,
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"notification_sent": notification_sent,
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}
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if initial_priority == SignalPriority.CRITICAL:
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result = await process_signal_internal()
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result["processing_mode"] = "synchronous"
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return result
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background_tasks.add_task(process_signal_internal)
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return {
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"id": str(new_signal.id),
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"priority": initial_priority.value,
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"status": "queued",
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"processing_mode": "background",
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"message": f"{initial_priority.value.upper()} priority signal queued for processing",
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}
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@router.post("/fetch", response_model=dict)
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async def trigger_signal_fetch(
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background_tasks: BackgroundTasks,
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db: AsyncSession = Depends(get_db),
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tenant_id: int = Depends(get_tenant_id),
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):
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"""手动触发抓取并分析信号"""
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def _stop_ollama():
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import os
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import signal
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import subprocess
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killed = False
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try:
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result = subprocess.run(
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["pgrep", "-f", "ollama"],
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capture_output=True,
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text=True,
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)
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if result.returncode == 0:
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for pid in result.stdout.strip().split("\n"):
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if pid:
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try:
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os.kill(int(pid), signal.SIGTERM)
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killed = True
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except ProcessLookupError:
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pass
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except Exception as exc:
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print(f"[AI] pgrep failed: {exc}")
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if not killed:
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try:
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result = subprocess.run(
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["pkill", "-9", "-f", "ollama"],
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capture_output=True,
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timeout=5,
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)
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killed = result.returncode == 0
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except Exception as exc:
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print(f"[AI] pkill failed: {exc}")
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if killed:
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print("[AI] Ollama stopped - analysis complete")
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raw_stories = await fetch_hn_stories(limit=30)
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new_signals_count = 0
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processed_count = 0
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for story in raw_stories:
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result = await db.execute(select(Signal).where(Signal.content == story["content"]))
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if result.scalars().first():
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continue
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impact = analyze_impact(story["content"])
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if impact > 0.4:
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initial_priority = classify_signal_priority(impact)
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new_signal = Signal(
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source=story["source"],
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content=story["content"],
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impact_score=impact,
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priority=initial_priority.value,
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)
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db.add(new_signal)
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await db.commit()
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await db.refresh(new_signal)
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new_signals_count += 1
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if initial_priority == SignalPriority.LOW:
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continue
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async def process_fetched():
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nonlocal processed_count
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try:
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relevant_context = await llm_service.find_relevant_context(
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signal_content=story["content"],
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db_session=db,
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top_k=3,
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min_similarity=0.3,
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tenant_id=tenant_id,
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)
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strategy_result = await llm_service.evaluate_with_voting_async(
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signal_content=story["content"],
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relevant_context=relevant_context,
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impact_score=impact,
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db=db,
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tenant_id=tenant_id,
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)
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except RuntimeError:
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return
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is_strategic = strategy_result.get("is_strategic", False)
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decision_proposal = strategy_result.get("decision_proposal", {})
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confidence = strategy_result.get("confidence", 0.0)
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final_priority = classify_signal_priority(impact, confidence)
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new_signal.priority = final_priority.value
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analysis_data = {
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"decision_proposal": decision_proposal,
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"competitiveness_radar": strategy_result.get("competitiveness_radar"),
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"detected_tech_stacks": strategy_result.get("detected_tech_stacks", []),
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"related_knowledge_nodes": strategy_result.get("related_knowledge_nodes", []),
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"rag_context_used": len(relevant_context) if relevant_context else 0,
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"rag_context_sources": [ctx["id"] for ctx in (relevant_context or [])],
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"confidence": confidence,
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"is_strategic": is_strategic,
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}
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if "_voting" in strategy_result:
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vi = strategy_result["_voting"]
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analysis_data["voting"] = {
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"enabled": vi.get("enabled"),
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"models_used": vi.get("models_used"),
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"strategic_votes": vi.get("strategic_votes"),
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"total_votes": vi.get("total_votes"),
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"unanimous": vi.get("unanimous"),
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}
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new_signal.strategic_analysis = json.dumps(analysis_data)
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new_signal.tasks_generated = json.dumps(strategy_result.get("tasks", []))
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new_signal.processed = True
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await db.commit()
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processed_count += 1
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if initial_priority in [SignalPriority.MEDIUM, SignalPriority.HIGH]:
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background_tasks.add_task(process_fetched)
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else:
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await process_fetched()
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_stop_ollama()
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return {
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"status": "success",
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"new_signals_count": new_signals_count,
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"processed_count": processed_count,
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"message": f"Fetched {new_signals_count} signals, {processed_count} analyzed",
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}
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