2026-04-02 11:36:05 +08:00
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import json
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import asyncio
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import unicodedata
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from server.chat.KgoSearchAPIWrapper import KgoSearchAPIWrapper
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from server.chat.search_engine_chat import search_engine_chat
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from configs import VECTOR_SEARCH_TOP_K, MAX_TOKENS
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from server.agent import model_container
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from pydantic import BaseModel, Field
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from configs import LLM_MODELS, TEMPERATURE
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from configs.basic_config import *
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# def get_kgo_search_type(query: str = "全部"):
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# # 过滤掉所有非汉字的字符
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# query = ''.join(char for char in query if unicodedata.category(char) == 'Lo')
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# search_map = KgoSearchAPIWrapper().search_map
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# if "论文" in query:
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# return "1001"
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# elif "外文" in query or "英文" in query:
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# return "1013"
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# elif "期刊" in query or "研究进展" in query:
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# return "1002"
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# else:
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# matched_types = [value for key, value in search_map.items() if key in query]
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# if matched_types:
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# return ','.join(matched_types)
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# else:
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# print("未找到匹配的搜索类型，返回默认值：1000")
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# return "1000"
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@timing_decorator
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async def search_engine_iter(query: str , uid: str):
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response = await search_engine_chat(uid = uid,
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query=query,
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search_engine_name="zhipu_search",
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2026-04-07 10:32:14 +08:00
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model_name=LLM_MODELS[0],
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2026-04-02 11:36:05 +08:00
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temperature=TEMPERATURE, # Agent搜索互联网的时候，温度设为0.1
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history=[],
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top_k=VECTOR_SEARCH_TOP_K,
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max_tokens=MAX_TOKENS,
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prompt_name="search",
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stream=False,
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kgo_search_type="1000")
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contents = ""
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docs = []
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async for data in response.body_iterator: # 这里的data是一个json字符串
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data = json.loads(data)
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contents = data.get("answer", [])
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current_docs = data.get("docs", [])
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if current_docs:
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docs.extend(current_docs)
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else:
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logging.error("No docs found in the response")
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return docs
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# print("contents：", contents)
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# print("docs：", docs)
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# 回复搜索结果和搜索结果的总结
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return contents,docs
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def search_internet(query: str, uid: str):
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# filter_words = {
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# "统计数据", "视频", "数据集", "新闻", "专利", "期刊", "图书", "报告", "项目", "成果", "会议论文",
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# "政策", "外文期刊论文", "学位论文", "期刊论文", "全部论文", "原文", "全文", "pdf", "资料", " ",
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# "进展", "研究", "最新", "外文", "英文", "最新", "文件", "资料", "论文"
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# }
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# filtered_query = query
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# for word in filter_words:
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# if word in query:
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# filtered_query = filtered_query.replace(word, "")
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# print("filtered query:", filtered_query)
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# kgo_search_type = get_kgo_search_type(query)
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# print("kgo_search_type:", kgo_search_type)
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# 使用过滤后的查询字符串进行搜索
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return asyncio.run(search_engine_iter(query, uid))
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class SearchInternetInput(BaseModel):
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location: str = Field(description="Query for Internet search")
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if __name__ == "__main__":
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result = search_internet("人工智能领域的政策")
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print("答案:", result)
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