43 lines
1.8 KiB
Python
43 lines
1.8 KiB
Python
from server.chat.knowledge_base_chat import knowledge_base_chat
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from configs import VECTOR_SEARCH_TOP_K, SCORE_THRESHOLD, MAX_TOKENS, LLM_MODELS
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import json
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import asyncio
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from typing import List, Tuple, Any
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from pydantic import BaseModel, Field
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class PolicyKnowledgeInput(BaseModel):
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location: str = Field(description="The policy related query to be searched")
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async def policy_knowledgebase_search_iter(query: str) -> tuple[str | Any, list[Any] | Any]:
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response = await knowledge_base_chat(query=query,
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fileName=None,
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knowledge_base_name_list = ["t_policy_total_bge_new_v1"],
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model_name=LLM_MODELS[0],
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temperature=0.01,
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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="default",
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score_threshold=SCORE_THRESHOLD,
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stream=False)
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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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print("data>>>>>", data)
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contents = data["answer"] if "answer" in data.keys() else contents
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docs = data["docs"] if "docs" in data.keys() else docs
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return contents, docs
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def policy_knowledgebase_search(query: str) -> tuple[str | Any, list[Any] | Any]:
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return asyncio.run(policy_knowledgebase_search_iter(query))
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if __name__ == "__main__":
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result = policy_knowledgebase_search("大数据男女比例")
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print("答案:", result)
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