Codex
199 lines
8.2 KiB
Python
199 lines
8.2 KiB
Python
from __future__ import annotations
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import json
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import logging
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from datetime import date, timedelta
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from typing import Any
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from urllib.error import HTTPError, URLError
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from urllib.request import Request, urlopen
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from app.core.config import Settings
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from app.db.models import Topic
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from app.schemas.agent import AgentResult, SignalItem
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logger = logging.getLogger(__name__)
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class GrokIntelligenceClient:
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"""通过 OpenAI 兼容接口调用 Grok，生成每日 AI 情报结构化结果。"""
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def __init__(self, settings: Settings) -> None:
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self.settings = settings
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def collect_daily_intelligence(
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self,
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topics: list[Topic],
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news_candidates: list[SignalItem],
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github_projects: list[SignalItem],
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run_date: date,
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) -> AgentResult:
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# 先用确定性 GitHub 候选缩小开源项目范围，再由模型统一判断新闻价值和日报结构。
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if not self.settings.llm_api_key:
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raise RuntimeError("SIGNALSCOUT_LLM_API_KEY is required")
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messages = [
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{"role": "system", "content": self._system_prompt()},
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{
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"role": "user",
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"content": self._user_prompt(
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topics=topics,
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news_candidates=news_candidates,
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github_projects=github_projects,
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run_date=run_date,
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),
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},
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]
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logger.info(
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"grok_intelligence_started model=%s run_date=%s github_candidates=%s",
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self.settings.llm_model,
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run_date.isoformat(),
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len(github_projects),
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)
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payload = self._chat_json(messages)
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result = AgentResult.model_validate(payload)
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logger.info(
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"grok_intelligence_completed model=%s signals=%s",
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self.settings.llm_model,
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len(result.signals),
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)
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return result
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def _chat_json(self, messages: list[dict[str, str]]) -> dict[str, Any]:
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# JSON mode把结构化契约交给模型侧执行，解析失败时直接暴露供应商原文便于排障。
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url = f"{self.settings.llm_base_url.rstrip('/')}/chat/completions"
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body = json.dumps(
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{
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"model": self.settings.llm_model,
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"messages": messages,
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"temperature": 0.2,
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"max_tokens": self.settings.llm_max_tokens,
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"response_format": {"type": "json_object"},
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},
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ensure_ascii=False,
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).encode("utf-8")
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request = Request(
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url,
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data=body,
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headers={
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"Authorization": f"Bearer {self.settings.llm_api_key}",
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"Content-Type": "application/json",
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"Accept": "application/json",
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},
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method="POST",
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)
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try:
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with urlopen(request, timeout=self.settings.llm_timeout_seconds) as response:
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response_body = response.read().decode("utf-8")
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except HTTPError as exc:
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message = exc.read().decode("utf-8", errors="replace")
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raise RuntimeError(f"Grok request failed: HTTP {exc.code} {message}") from exc
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except URLError as exc:
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raise RuntimeError(f"Grok request failed: {exc.reason}") from exc
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completion = json.loads(response_body)
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content = completion["choices"][0]["message"]["content"]
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if not isinstance(content, str):
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raise RuntimeError("Grok response content is not text")
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try:
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payload = json.loads(content)
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except json.JSONDecodeError as exc:
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raise RuntimeError(f"Grok returned invalid JSON: {content[:1200]}") from exc
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payload.setdefault("raw_response", {})
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payload["raw_response"].update(
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{
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"provider": self.settings.llm_base_url,
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"model": self.settings.llm_model,
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"usage": completion.get("usage", {}),
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}
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)
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return payload
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def _system_prompt(self) -> str:
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# 这段提示词定义唯一产出格式，数据库与报告都依赖同一个模型结果。
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return (
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"你是 SignalScout，一个专门追踪 AI 新闻、模型发布、Agent 工具、开源项目和融资动态的情报 Agent。"
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"你必须优先给出最近发生、可点击验证、对工程和产品判断有价值的事件。"
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"所有结论必须带 source_url，不能编造链接。"
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"只输出一个 JSON object，不输出 Markdown 代码块或额外解释。"
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)
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def _user_prompt(
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self,
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topics: list[Topic],
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news_candidates: list[SignalItem],
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github_projects: list[SignalItem],
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run_date: date,
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) -> str:
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# 日期窗口让模型把“最新”落到明确范围，GitHub候选则避免热门项目只靠语言模型记忆。
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since = run_date - timedelta(days=self.settings.news_recent_days)
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topic_payload = [
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{"name": topic.name, "description": topic.description}
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for topic in topics
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if topic.enabled
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]
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github_payload = [
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{
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"title": item.title,
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"summary": item.summary,
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"source_url": item.source_url,
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"published_at": item.published_at.isoformat() if item.published_at else None,
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"entities": item.entities,
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}
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for item in github_projects
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]
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news_payload = [
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{
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"title": item.title,
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"summary": item.summary,
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"source_url": item.source_url,
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"source_name": item.source_name,
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"published_at": item.published_at.isoformat() if item.published_at else None,
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"entities": item.entities,
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}
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for item in news_candidates
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]
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return json.dumps(
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{
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"task": "生成每日 AI 情报日报，并返回结构化信号。",
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"run_date": run_date.isoformat(),
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"date_window": {
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"from": since.isoformat(),
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"to": run_date.isoformat(),
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},
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"limits": {
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"max_news_signals": self.settings.news_max_items,
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"max_github_signals": self.settings.github_max_projects,
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},
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"topics": topic_payload,
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"news_candidates": news_payload,
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"github_candidates": github_payload,
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"output_schema": {
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"title": "字符串，日报标题",
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"signals": [
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{
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"topic": "AI 新闻 / GitHub 热门项目 / 模型发布 / Agent 工具 / 融资动态等",
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"title": "字符串",
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"summary": "中文摘要，说明为什么重要",
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"source_url": "可点击来源链接",
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"source_name": "来源名称",
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"published_at": "ISO 时间；不知道具体时间可用日期T00:00:00",
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"importance": "1到5的整数",
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"entities": ["公司、项目、模型、人名等实体"],
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}
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],
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"report_markdown": "中文 Markdown 日报，包含今日重点、AI 新闻、GitHub 热门项目和观察",
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"raw_response": {
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"notes": "简短说明检索和筛选依据",
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},
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},
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"rules": [
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"新闻必须来自日期窗口内或接近日内发生的事件。",
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"AI新闻只能从 news_candidates 中选择，不要新增候选外新闻。",
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"GitHub 热门项目只能从 github_candidates 中选择，不要新增候选外仓库。",
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"每条 signal 必须有真实 source_url。",
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"report_markdown 只能基于 signals 写，不要加入 signals 外的新事实。",
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"输出必须是可被 json.loads 解析的 JSON object。",
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],
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},
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ensure_ascii=False,
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)
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