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77 lines
1.9 KiB
Python
77 lines
1.9 KiB
Python
"""Main entrypoint into package."""
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from typing import Optional
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from langchain.agents import MRKLChain, ReActChain, SelfAskWithSearchChain
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from langchain.cache import BaseCache
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from langchain.callbacks import (
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set_default_callback_manager,
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set_handler,
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set_tracing_callback_manager,
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)
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from langchain.chains import (
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ConversationChain,
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LLMBashChain,
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LLMChain,
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LLMCheckerChain,
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LLMMathChain,
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PALChain,
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QAWithSourcesChain,
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SQLDatabaseChain,
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VectorDBQA,
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VectorDBQAWithSourcesChain,
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)
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from langchain.docstore import InMemoryDocstore, Wikipedia
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from langchain.llms import Cohere, HuggingFaceHub, OpenAI
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from langchain.llms.huggingface_pipeline import HuggingFacePipeline
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from langchain.prompts import (
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BasePromptTemplate,
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FewShotPromptTemplate,
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Prompt,
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PromptTemplate,
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)
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from langchain.serpapi import SerpAPIChain, SerpAPIWrapper
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from langchain.sql_database import SQLDatabase
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from langchain.utilities.google_search import GoogleSearchAPIWrapper
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from langchain.utilities.wolfram_alpha import WolframAlphaAPIWrapper
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from langchain.vectorstores import FAISS, ElasticVectorSearch
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verbose: bool = False
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llm_cache: Optional[BaseCache] = None
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set_default_callback_manager()
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__all__ = [
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"LLMChain",
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"LLMBashChain",
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"LLMCheckerChain",
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"LLMMathChain",
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"SelfAskWithSearchChain",
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"SerpAPIWrapper",
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"SerpAPIChain",
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"GoogleSearchAPIWrapper",
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"WolframAlphaAPIWrapper",
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"Cohere",
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"OpenAI",
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"BasePromptTemplate",
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"Prompt",
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"FewShotPromptTemplate",
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"PromptTemplate",
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"ReActChain",
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"Wikipedia",
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"HuggingFaceHub",
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"HuggingFacePipeline",
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"SQLDatabase",
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"SQLDatabaseChain",
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"FAISS",
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"MRKLChain",
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"VectorDBQA",
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"ElasticVectorSearch",
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"InMemoryDocstore",
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"ConversationChain",
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"VectorDBQAWithSourcesChain",
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"QAWithSourcesChain",
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"PALChain",
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"set_handler",
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"set_tracing_callback_manager",
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]
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