蘺h ~ddlmZddlmZddlmZddlmZddlm Z m Z ddl m Z ddl mZddlmZdd lmZddZdS)) annotations)Sequence)BaseLanguageModel)BasePromptTemplate)RunnableRunnablePassthrough)BaseToolformat_log_to_str)ReActSingleInputOutputParser)render_text_descriptionllmrtoolsSequence[BaseTool]promptrreturnrchd|j}|rtd||t t |dd|D}|dg}tj d |z|ztz}|S) aCreate an agent that uses ReAct prompting. Examples: .. code-block:: python from langchain import hub from langchain_community.llms import OpenAI from langchain.agents import AgentExecutor, create_react_agent prompt = hub.pull("hwchase17/react") model = OpenAI() tools = ... agent = create_react_agent(model, tools, prompt) agent_executor = AgentExecutor(agent=agent, tools=tools) agent_executor.invoke({"input": "hi"}) # Use with chat history from langchain_core.messages import AIMessage, HumanMessage agent_executor.invoke( { "input": "what's my name?", # Notice that chat_history is a string # since this prompt is aimed at LLMs, not chat models "chat_history": "Human: My name is Bob AI: Hello Bob!", } ) Args: llm: LLM to use as the agent. tools: Tools this agent has access to. prompt: The prompt to use, must have input keys of `tools`, `tool_names`, and `agent_scratchpad`. Returns: A runnable sequence representing an agent. It takes as input all the same input variables as the prompt passed in does. It returns as output either an AgentAction or AgentFinish. >r tool_namesagent_scratchpadz#Prompt missing required variables: z, cg|] }|j S)name).0ts d/var/www/html/services/rag-service/venv/lib/python3.11/site-packages/langchain/agents/react/agent.py z&create_react_agent..Ds444af444)rrz Observation)stopc,t|dS)Nintermediate_stepsr )xs rz$create_react_agent..Is'8;O9P'Q'Qr)r) differenceinput_variables ValueErrorpartialr listjoinbindrassignr )rrr missing_vars llm_with_stopagents rcreate_react_agentr.sZ?>>IILOM|MMNNN ^^%d5kk229944e44455FHH?"3H44M"QQ         ' ( (  )  LrN)rrrrrrrr) __future__rtypingrlangchain_core.language_modelsrlangchain_core.promptsrlangchain_core.runnablesrrlangchain_core.toolsr "langchain.agents.format_scratchpadr langchain.agents.output_parsersr langchain.tools.renderr r.rrrr8s""""""<<<<<<555555BBBBBBBB))))))@@@@@@HHHHHH::::::@@@@@@r