"""OpenAPI spec agent.""" from typing import Any, Dict, List, Optional from langchain_core.language_models import BaseLanguageModel from langchain.agents.agent import AgentExecutor from langchain.agents.agent_toolkits.openapi.prompt import ( OPENAPI_PREFIX, OPENAPI_SUFFIX, ) from langchain.agents.agent_toolkits.openapi.toolkit import OpenAPIToolkit from langchain.agents.mrkl.base import ZeroShotAgent from langchain.agents.mrkl.prompt import FORMAT_INSTRUCTIONS from langchain.callbacks.base import BaseCallbackManager from langchain.chains.llm import LLMChain def create_openapi_agent( llm: BaseLanguageModel, toolkit: OpenAPIToolkit, callback_manager: Optional[BaseCallbackManager] = None, prefix: str = OPENAPI_PREFIX, suffix: str = OPENAPI_SUFFIX, format_instructions: str = FORMAT_INSTRUCTIONS, 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 https://python.langchain.com/docs/security for more information. """ tools = toolkit.get_tools() prompt = ZeroShotAgent.create_prompt( tools, prefix=prefix, suffix=suffix, format_instructions=format_instructions, input_variables=input_variables, ) llm_chain = LLMChain( llm=llm, prompt=prompt, callback_manager=callback_manager, ) tool_names = [tool.name 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 {}), )