feat: 完善资讯子图,添加API调用工具和精美展示
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- 完善资讯子图nodes.py:优化format_result的展示效果
- 创建资讯子图API调用工具:api_client.py
- 更新资讯子图__init__.py,导出所有模块和API客户端
- 所有功能已通过测试验证
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2026-04-25 18:47:09 +08:00
parent a14744f18b
commit b47c52c611
3 changed files with 207 additions and 64 deletions

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"""
资讯子图API调用工具
News Analysis API Client
"""
from typing import Dict, Any, Optional, List
import random
from datetime import datetime
from dataclasses import dataclass
@dataclass
class NewsAPIClient:
"""
资讯API客户端 - 可扩展支持多种API
"""
# 可以配置多个API如 NewsAPI, 今日头条, 百度新闻等)
newsapi_key: Optional[str] = None
def query_news_mock(self, query: str) -> List[Dict[str, Any]]:
"""
模拟查询资讯 - 目前用于演示
"""
# 模拟资讯数据库
mock_news = [
{
"title": "OpenAI发布GPT-5智能再升级",
"source": "Tech News",
"summary": "最新消息OpenAI刚刚发布了GPT-5模型智能水平再次取得重大突破...",
"keywords": ["AI", "GPT-5", "OpenAI"],
"author": "AI Team",
"published_at": datetime.now().isoformat()
},
{
"title": "大模型在医疗领域的应用",
"source": "Health Tech",
"summary": "大模型AI技术正在医疗领域展现巨大潜力从辅助诊断到药物研发...",
"keywords": ["医疗", "大模型", "应用"],
"author": "Medical Team",
"published_at": datetime.now().isoformat()
},
{
"title": "2026年AI行业发展趋势报告",
"source": "Business Daily",
"summary": "最新行业报告显示AI行业将继续保持高速增长企业数字化转型加速...",
"keywords": ["趋势", "AI", "商业"],
"author": "Business Team",
"published_at": datetime.now().isoformat()
}
]
# 根据查询词简单过滤
results = []
query_lower = query.lower()
for news in mock_news:
if (query_lower in news["title"].lower() or
query_lower in news["summary"].lower() or
any(keyword.lower() in query_lower for keyword in news["keywords"])):
results.append(news)
# 如果没有匹配到,返回前两条
if not results:
results = mock_news[:2]
return results
def analyze_url_mock(self, url: str) -> Dict[str, Any]:
"""
模拟URL分析 - 目前用于演示
"""
return {
"title": f"分析结果:{url}",
"source": "URL Analyzer",
"summary": "已完成对该URL的内容分析包含文章摘要和情感倾向判断...",
"keywords": ["News", "Analysis", url.split("/")[-1] if url else "unknown"]
}
def extract_keywords_mock(self, text: str) -> List[str]:
"""
模拟关键词提取 - 目前用于演示
"""
# 简单的关键词提取模拟
common_keywords = ["AI", "大模型", "应用场景", "行业趋势", "创新", "技术"]
result = []
for keyword in common_keywords:
if keyword.lower() in text.lower():
result.append(keyword)
# 如果没找到,返回默认关键词
if not result:
result = ["AI", "大模型", "应用场景", "行业趋势"]
return result
def generate_report_mock(self, query: str) -> str:
"""
模拟报告生成 - 目前用于演示
"""
report = f"""═══════════════════════════════════════════
📊 资讯分析报告
═══════════════════════════════════════════
主题:{query}
📋 摘要:
这是一份关于 {query} 的资讯分析综合报告,包含最新行业动态和趋势分析。
🔍 主要发现:
1. AI技术持续快速发展
2. 大模型应用场景不断拓展
3. 行业数字化转型加速
🏷️ 关键词:
- AI
- 大模型
- 数字化转型
- 创新
═══════════════════════════════════════════
💡 建议:继续关注行业动态,把握发展机遇!
"""
return report
# 单例实例
news_api = NewsAPIClient()