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38 lines
1.5 KiB
Python
38 lines
1.5 KiB
Python
from langchain.chat_models import init_chat_model
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from langchain_core.messages import HumanMessage, SystemMessage
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from langchain_core.tools import tool
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from duckduckgo_search import DDGS
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from langchain_openai import ChatOpenAI
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from base import *
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from config.settings import Config
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def get_web_data(query: str) -> str:
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"""使用DuckDuckGo搜索引擎进行搜索"""
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results = DDGS().text(query, max_results=12)
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return results
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class LLMEnhance:
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def __init__(self):
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self.llm = ChatOpenAI(
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api_key=Config().api.embedding_models.api_key,
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base_url="https://api.siliconflow.cn/v1",
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model_name='Qwen/Qwen2.5-7B-Instruct'
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)
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def search(self, target):
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search_keywords = self.llm.invoke([HumanMessage(content=f"你接下来的任务是[{target}]，但在这之前，你需要搜索相关信息。现在假装你正在搜索网页，直接给出一到两个搜索关键词，不要有多余的话，我会帮你搜索。")])
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logger.debug(search_keywords.content)
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search_result = get_web_data(search_keywords.content)
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logger.debug(f"search_result: {search_result}")
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result = self.llm.invoke([HumanMessage(content=f"网络信息: {search_result}\n\n 用一句长句介绍或回答[{target}]")])
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logger.debug(f"result: {result.content}")
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return result.content
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def judge_possible_memes(self, possible_memes:t.List[str]):
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pass
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if __name__ == '__main__':
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llm = LLMEnhance()
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llm.search("如何评价《这就是中国》")
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