65 lines
2.1 KiB
Python
65 lines
2.1 KiB
Python
import os
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from enum import Enum
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from dataclasses import dataclass, fields
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from typing import Any, Optional, Dict
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from pydantic import BaseModel, Field
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from langchain_core.language_models.chat_models import BaseChatModel
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from langchain_core.runnables import RunnableConfig
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from dataclasses import dataclass
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class SearchAPI(Enum):
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PERPLEXITY = "perplexity"
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TAVILY = "tavily"
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EXA = "exa"
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ARXIV = "arxiv"
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PUBMED = "pubmed"
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LINKUP = "linkup"
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DUCKDUCKGO = "duckduckgo"
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GOOGLESEARCH = "googlesearch"
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@dataclass(kw_only=True)
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class Configuration:
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"""The configurable fields for the chatbot."""
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number_of_queries: int = 2 # 每次迭代生成几个查询
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planner_provider: str = "deepseek"
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planner_model: str = "deepseek-chat"
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writer_provider: str = "deepseek"
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writer_model: str = "deepseek-chat"
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search_api: SearchAPI = SearchAPI.TAVILY
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search_api_config: Optional[Dict[str, Any]] = None
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max_tokens : 4000
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@classmethod
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def from_runnable_config(
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cls, config: Optional[RunnableConfig] = None
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) -> "Configuration":
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"""Create a Configuration instance from a RunnableConfig."""
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configurable = (
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config["configurable"] if config and "configurable" in config else {}
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)
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values: dict[str, Any] = {
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f.name: os.environ.get(f.name.upper(), configurable.get(f.name))
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for f in fields(cls)
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if f.init
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}
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return cls(**{k: v for k, v in values.items() if v})
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class BaseConfiguration(BaseModel):
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number_of_queries: int = Field(default=2, description="每次迭代生成几个查询")
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planner_provider: str = Field(default="deepseek")
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planner_model: str = Field(default="deepseek-reasoner")
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writer_provider: str = Field(default="deepseek")
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writer_model: str = Field(default="deepseek-chat")
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search_api: SearchAPI = Field(default=SearchAPI.TAVILY)
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search_api_config: Optional[Dict[str, Any]] = Field(default=None)
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search_max_len: int = Field(default=20000, description="搜索结果最大字符数")
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