Source code for langchain_community.agent_toolkits.openapi.base

"""OpenAPI spec agent."""
from __future__ import annotations

from typing import TYPE_CHECKING, Any, Dict, List, Optional

from langchain_core.callbacks import BaseCallbackManager
from langchain_core.language_models import BaseLanguageModel

from langchain_community.agent_toolkits.openapi.prompt import (
from langchain_community.agent_toolkits.openapi.toolkit import OpenAPIToolkit

    from langchain.agents.agent import AgentExecutor

[docs]def create_openapi_agent( llm: BaseLanguageModel, toolkit: OpenAPIToolkit, callback_manager: Optional[BaseCallbackManager] = None, prefix: str = OPENAPI_PREFIX, suffix: str = OPENAPI_SUFFIX, format_instructions: Optional[str] = None, input_variables: Optional[List[str]] = None, max_iterations: Optional[int] = 15, max_execution_time: Optional[float] = None, early_stopping_method: str = "force", verbose: bool = False, return_intermediate_steps: bool = False, agent_executor_kwargs: Optional[Dict[str, Any]] = None, **kwargs: Any, ) -> AgentExecutor: """Construct an OpenAPI agent from an LLM and tools. *Security Note*: When creating an OpenAPI agent, check the permissions and capabilities of the underlying toolkit. For example, if the default implementation of OpenAPIToolkit uses the RequestsToolkit which contains tools to make arbitrary network requests against any URL (e.g., GET, POST, PATCH, PUT, DELETE), Control access to who can submit issue requests using this toolkit and what network access it has. See for more information. """ from langchain.agents.agent import AgentExecutor from langchain.agents.mrkl.base import ZeroShotAgent from langchain.chains.llm import LLMChain tools = toolkit.get_tools() prompt_params = ( {"format_instructions": format_instructions} if format_instructions is not None else {} ) prompt = ZeroShotAgent.create_prompt( tools, prefix=prefix, suffix=suffix, input_variables=input_variables, **prompt_params, ) llm_chain = LLMChain( llm=llm, prompt=prompt, callback_manager=callback_manager, ) tool_names = [ for tool in tools] agent = ZeroShotAgent(llm_chain=llm_chain, allowed_tools=tool_names, **kwargs) return AgentExecutor.from_agent_and_tools( agent=agent, tools=tools, callback_manager=callback_manager, verbose=verbose, return_intermediate_steps=return_intermediate_steps, max_iterations=max_iterations, max_execution_time=max_execution_time, early_stopping_method=early_stopping_method, **(agent_executor_kwargs or {}), )