fix: 优化数据

crawler/extractor_ai.py

@@ -0,0 +1,100 @@
+# -*- 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
+- us_personnel_killed, iran_personnel_killed 等：仅当新闻明确提及具体数字时填写
+- 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
+
+原文：{str(text)[:500]}
+
+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"]:
+        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)}
+    return out