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181 lines
5.9 KiB
Python
181 lines
5.9 KiB
Python
"""Chain for question-answering with self-verification."""
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from __future__ import annotations
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import warnings
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from typing import Any, Dict, List, Optional
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from pydantic import Extra, root_validator
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from langchain.base_language import BaseLanguageModel
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from langchain.callbacks.manager import CallbackManagerForChainRun
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from langchain.chains.base import Chain
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from langchain.chains.llm import LLMChain
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from langchain.chains.llm_checker.prompt import (
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CHECK_ASSERTIONS_PROMPT,
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CREATE_DRAFT_ANSWER_PROMPT,
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LIST_ASSERTIONS_PROMPT,
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REVISED_ANSWER_PROMPT,
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)
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from langchain.chains.sequential import SequentialChain
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from langchain.prompts import PromptTemplate
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def _load_question_to_checked_assertions_chain(
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llm: BaseLanguageModel,
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create_draft_answer_prompt: PromptTemplate,
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list_assertions_prompt: PromptTemplate,
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check_assertions_prompt: PromptTemplate,
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revised_answer_prompt: PromptTemplate,
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) -> SequentialChain:
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create_draft_answer_chain = LLMChain(
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llm=llm,
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prompt=create_draft_answer_prompt,
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output_key="statement",
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)
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list_assertions_chain = LLMChain(
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llm=llm,
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prompt=list_assertions_prompt,
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output_key="assertions",
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)
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check_assertions_chain = LLMChain(
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llm=llm,
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prompt=check_assertions_prompt,
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output_key="checked_assertions",
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)
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revised_answer_chain = LLMChain(
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llm=llm,
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prompt=revised_answer_prompt,
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output_key="revised_statement",
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)
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chains = [
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create_draft_answer_chain,
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list_assertions_chain,
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check_assertions_chain,
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revised_answer_chain,
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]
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question_to_checked_assertions_chain = SequentialChain(
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chains=chains,
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input_variables=["question"],
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output_variables=["revised_statement"],
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verbose=True,
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)
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return question_to_checked_assertions_chain
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class LLMCheckerChain(Chain):
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"""Chain for question-answering with self-verification.
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Example:
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.. code-block:: python
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from langchain import OpenAI, LLMCheckerChain
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llm = OpenAI(temperature=0.7)
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checker_chain = LLMCheckerChain.from_llm(llm)
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"""
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question_to_checked_assertions_chain: SequentialChain
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llm: Optional[BaseLanguageModel] = None
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"""[Deprecated] LLM wrapper to use."""
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create_draft_answer_prompt: PromptTemplate = CREATE_DRAFT_ANSWER_PROMPT
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"""[Deprecated]"""
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list_assertions_prompt: PromptTemplate = LIST_ASSERTIONS_PROMPT
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"""[Deprecated]"""
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check_assertions_prompt: PromptTemplate = CHECK_ASSERTIONS_PROMPT
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"""[Deprecated]"""
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revised_answer_prompt: PromptTemplate = REVISED_ANSWER_PROMPT
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"""[Deprecated] Prompt to use when questioning the documents."""
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input_key: str = "query" #: :meta private:
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output_key: str = "result" #: :meta private:
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class Config:
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"""Configuration for this pydantic object."""
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extra = Extra.forbid
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arbitrary_types_allowed = True
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@root_validator(pre=True)
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def raise_deprecation(cls, values: Dict) -> Dict:
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if "llm" in values:
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warnings.warn(
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"Directly instantiating an LLMCheckerChain with an llm is deprecated. "
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"Please instantiate with question_to_checked_assertions_chain "
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"or using the from_llm class method."
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)
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if (
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"question_to_checked_assertions_chain" not in values
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and values["llm"] is not None
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):
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question_to_checked_assertions_chain = (
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_load_question_to_checked_assertions_chain(
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values["llm"],
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values.get(
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"create_draft_answer_prompt", CREATE_DRAFT_ANSWER_PROMPT
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),
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values.get("list_assertions_prompt", LIST_ASSERTIONS_PROMPT),
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values.get("check_assertions_prompt", CHECK_ASSERTIONS_PROMPT),
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values.get("revised_answer_prompt", REVISED_ANSWER_PROMPT),
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)
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)
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values[
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"question_to_checked_assertions_chain"
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] = question_to_checked_assertions_chain
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return values
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@property
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def input_keys(self) -> List[str]:
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"""Return the singular input key.
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:meta private:
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"""
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return [self.input_key]
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@property
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def output_keys(self) -> List[str]:
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"""Return the singular output key.
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:meta private:
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"""
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return [self.output_key]
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def _call(
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self,
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inputs: Dict[str, Any],
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run_manager: Optional[CallbackManagerForChainRun] = None,
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) -> Dict[str, str]:
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_run_manager = run_manager or CallbackManagerForChainRun.get_noop_manager()
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question = inputs[self.input_key]
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output = self.question_to_checked_assertions_chain(
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{"question": question}, callbacks=_run_manager.get_child()
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)
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return {self.output_key: output["revised_statement"]}
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@property
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def _chain_type(self) -> str:
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return "llm_checker_chain"
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@classmethod
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def from_llm(
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cls,
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llm: BaseLanguageModel,
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create_draft_answer_prompt: PromptTemplate = CREATE_DRAFT_ANSWER_PROMPT,
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list_assertions_prompt: PromptTemplate = LIST_ASSERTIONS_PROMPT,
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check_assertions_prompt: PromptTemplate = CHECK_ASSERTIONS_PROMPT,
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revised_answer_prompt: PromptTemplate = REVISED_ANSWER_PROMPT,
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**kwargs: Any,
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) -> LLMCheckerChain:
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question_to_checked_assertions_chain = (
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_load_question_to_checked_assertions_chain(
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llm,
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create_draft_answer_prompt,
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list_assertions_prompt,
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check_assertions_prompt,
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revised_answer_prompt,
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)
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)
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return cls(
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question_to_checked_assertions_chain=question_to_checked_assertions_chain,
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**kwargs,
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)
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