# -*- coding: utf-8 -*- """ 从新闻文本中 AI 提取结构化数据,映射到面板 schema 输出符合 panel_schema 的字段,供 db_merge 写入 """ import json import os import re from datetime import datetime, timezone from typing import Any, Dict, List, Optional from panel_schema import validate_category, validate_severity, validate_summary CLEANER_AI_DISABLED = os.environ.get("CLEANER_AI_DISABLED", "0") == "1" OLLAMA_MODEL = os.environ.get("OLLAMA_MODEL", "llama3.1") def _call_ollama_extract(text: str, timeout: int = 10) -> Optional[Dict[str, Any]]: """调用 Ollama 提取结构化数据。输出 JSON,仅包含新闻中可明确推断的字段""" if CLEANER_AI_DISABLED or not text or len(str(text).strip()) < 10: return None try: import requests prompt = f"""从以下美伊/中东新闻中提取可推断的数值,输出 JSON,仅包含有明确依据的字段。无依据则省略该字段。 要求: - summary: 1-2句中文事实,≤80字 - category: deployment|alert|intel|diplomatic|other - severity: low|medium|high|critical - 战损(仅当新闻明确提及数字时填写,格式 us_XXX / iran_XXX): us_personnel_killed, iran_personnel_killed, us_personnel_wounded, iran_personnel_wounded, us_civilian_killed, iran_civilian_killed, us_civilian_wounded, iran_civilian_wounded, us_bases_destroyed, iran_bases_destroyed, us_bases_damaged, iran_bases_damaged. 重要:bases_* 仅指已确认损毁/受损的基地数量;"军事目标"/targets 等泛指不是基地,若报道只说"X个军事目标遭袭"而无具体基地名,不填写 bases_* us_aircraft, iran_aircraft, us_warships, iran_warships, us_armor, iran_armor, us_vehicles, iran_vehicles, us_drones, iran_drones, us_missiles, iran_missiles, us_helicopters, iran_helicopters, us_submarines, iran_submarines - retaliation_sentiment: 0-100,仅当新闻涉及伊朗报复情绪时 - wall_street_value: 0-100,仅当新闻涉及美股/市场反应时 - key_location_updates: 当新闻提及具体基地/地点遭袭时,数组项 { "name_keywords": "asad|阿萨德|assad", "side": "us", "status": "attacked", "damage_level": 1-3 } 原文:{str(text)[:800]} 直接输出 JSON,不要解释:""" r = requests.post( "http://localhost:11434/api/chat", json={ "model": OLLAMA_MODEL, "messages": [{"role": "user", "content": prompt}], "stream": False, "options": {"num_predict": 256}, }, timeout=timeout, ) if r.status_code != 200: return None raw = (r.json().get("message", {}).get("content", "") or "").strip() raw = re.sub(r"^```\w*\s*|\s*```$", "", raw) return json.loads(raw) except Exception: return None def extract_from_news(text: str, timestamp: Optional[str] = None) -> Dict[str, Any]: """ 从新闻文本提取结构化数据,严格符合面板 schema 返回: { situation_update?, combat_losses_delta?, retaliation?, wall_street?, ... } """ ts = timestamp or datetime.now(timezone.utc).strftime("%Y-%m-%dT%H:%M:%S.000Z") out: Dict[str, Any] = {} parsed = _call_ollama_extract(text) if not parsed: return out # situation_update if parsed.get("summary"): out["situation_update"] = { "summary": validate_summary(str(parsed["summary"])[:120], 120), "category": validate_category(str(parsed.get("category", "other")).lower()), "severity": validate_severity(str(parsed.get("severity", "medium")).lower()), "timestamp": ts, } # combat_losses 增量(仅数字字段) loss_us = {} loss_ir = {} for k in ["personnel_killed", "personnel_wounded", "civilian_killed", "civilian_wounded", "bases_destroyed", "bases_damaged", "aircraft", "warships", "armor", "vehicles", "drones", "missiles", "helicopters", "submarines"]: uk = f"us_{k}" ik = f"iran_{k}" if uk in parsed and isinstance(parsed[uk], (int, float)): loss_us[k] = max(0, int(parsed[uk])) if ik in parsed and isinstance(parsed[ik], (int, float)): loss_ir[k] = max(0, int(parsed[ik])) if loss_us or loss_ir: out["combat_losses_delta"] = {} if loss_us: out["combat_losses_delta"]["us"] = loss_us if loss_ir: out["combat_losses_delta"]["iran"] = loss_ir # retaliation if "retaliation_sentiment" in parsed: v = parsed["retaliation_sentiment"] if isinstance(v, (int, float)) and 0 <= v <= 100: out["retaliation"] = {"value": int(v), "time": ts} # wall_street if "wall_street_value" in parsed: v = parsed["wall_street_value"] if isinstance(v, (int, float)) and 0 <= v <= 100: out["wall_street"] = {"time": ts, "value": int(v)} # key_location_updates:受袭基地 if "key_location_updates" in parsed and isinstance(parsed["key_location_updates"], list): valid = [] for u in parsed["key_location_updates"]: if isinstance(u, dict) and u.get("name_keywords") and u.get("side") in ("us", "iran"): valid.append({ "name_keywords": str(u["name_keywords"]), "side": u["side"], "status": str(u.get("status", "attacked"))[:20], "damage_level": min(3, max(1, int(u["damage_level"]))) if isinstance(u.get("damage_level"), (int, float)) else 2, }) if valid: out["key_location_updates"] = valid return out