mirror of
https://github.com/hwchase17/langchain.git
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e81ddb32a6
Fix: 
77 lines
2.5 KiB
Python
77 lines
2.5 KiB
Python
"""Json agent."""
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from __future__ import annotations
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from typing import TYPE_CHECKING, Any, Dict, List, Optional
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from langchain_core.callbacks import BaseCallbackManager
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from langchain_core.language_models import BaseLanguageModel
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from langchain_community.agent_toolkits.json.prompt import JSON_PREFIX, JSON_SUFFIX
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from langchain_community.agent_toolkits.json.toolkit import JsonToolkit
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if TYPE_CHECKING:
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from langchain.agents.agent import AgentExecutor
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def create_json_agent(
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llm: BaseLanguageModel,
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toolkit: JsonToolkit,
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callback_manager: Optional[BaseCallbackManager] = None,
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prefix: str = JSON_PREFIX,
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suffix: str = JSON_SUFFIX,
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format_instructions: Optional[str] = None,
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input_variables: Optional[List[str]] = None,
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verbose: bool = False,
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agent_executor_kwargs: Optional[Dict[str, Any]] = None,
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**kwargs: Any,
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) -> AgentExecutor:
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"""Construct a json agent from an LLM and tools.
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Args:
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llm: The language model to use.
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toolkit: The toolkit to use.
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callback_manager: The callback manager to use. Default is None.
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prefix: The prefix to use. Default is JSON_PREFIX.
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suffix: The suffix to use. Default is JSON_SUFFIX.
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format_instructions: The format instructions to use. Default is None.
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input_variables: The input variables to use. Default is None.
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verbose: Whether to print verbose output. Default is False.
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agent_executor_kwargs: Optional additional arguments for the agent executor.
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kwargs: Additional arguments for the agent.
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Returns:
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The agent executor.
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"""
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from langchain.agents.agent import AgentExecutor
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from langchain.agents.mrkl.base import ZeroShotAgent
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from langchain.chains.llm import LLMChain
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tools = toolkit.get_tools()
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prompt_params = (
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{"format_instructions": format_instructions}
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if format_instructions is not None
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else {}
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)
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prompt = ZeroShotAgent.create_prompt(
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tools,
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prefix=prefix,
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suffix=suffix,
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input_variables=input_variables,
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**prompt_params,
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)
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llm_chain = LLMChain(
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llm=llm,
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prompt=prompt,
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callback_manager=callback_manager,
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)
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tool_names = [tool.name for tool in tools]
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agent = ZeroShotAgent(llm_chain=llm_chain, allowed_tools=tool_names, **kwargs)
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return AgentExecutor.from_agent_and_tools(
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agent=agent,
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tools=tools,
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callback_manager=callback_manager,
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verbose=verbose,
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**(agent_executor_kwargs or {}),
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)
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