@'h4HdZddlmZddlmZmZmZddlmZddl m Z m Z ddl m Z mZddlmZddlmZmZdd lmZdd lmZmZmZmZdd lmZmZdd lmZdd l m!Z!ddl"m#Z#ddl$m%Z%ddl&m'Z'ddl(m)Z)ddl*m+Z+edddGdde'Z,dedeededefdZ-y)zHModule implements an agent that uses OpenAI's APIs function enabled API.)Sequence)AnyOptionalUnion) deprecated) AgentAction AgentFinish)BaseCallbackManager Callbacks)BaseLanguageModel) BaseMessage SystemMessage)BasePromptTemplate)BaseMessagePromptTemplateChatPromptTemplateHumanMessagePromptTemplateMessagesPlaceholder)RunnableRunnablePassthrough)BaseTool)convert_to_openai_function)model_validator)Self)BaseSingleActionAgent"format_to_openai_function_messages) OpenAIFunctionsAgentOutputParserz0.1.0create_openai_functions_agentz1.0) alternativeremovalceZdZUdZeed<eeed<eed<e Z e e ed<de e fdZed defd Zede e fd Zede efd Z dde eee fdedededeeeff dZ dde eee fdededeeeffdZde de eee fdedefdZe e!dd fde"e!de"e e#de$fdZ%e d d e!dfdedeede"e&de"e e#de"e!dede'fdZ(y )OpenAIFunctionsAgentazAn Agent driven by OpenAIs function powered API. Args: llm: This should be an instance of ChatOpenAI, specifically a model that supports using `functions`. tools: The tools this agent has access to. prompt: The prompt for this agent, should support agent_scratchpad as one of the variables. For an easy way to construct this prompt, use `OpenAIFunctionsAgent.create_prompt(...)` output_parser: The output parser for this agent. Should be an instance of OpenAIFunctionsAgentOutputParser. Defaults to OpenAIFunctionsAgentOutputParser. llmtoolsprompt output_parserreturncT|jDcgc]}|jc}Scc}w)zGet allowed tools.)r$nameselfts s/home/kushmeetdev/Regenta/Chatbot/venv/lib/python3.12/site-packages/langchain/agents/openai_functions_agent/base.pyget_allowed_toolsz&OpenAIFunctionsAgent.get_allowed_tools;s $ +1+++s%after)modecj|j}d|jvrtd|j|S)zValidate prompt. Args: values: Values to validate. Returns: Validated values. Raises: ValueError: If `agent_scratchpad` is not in the prompt. agent_scratchpadzE`agent_scratchpad` should be one of the variables in the prompt, got )r%input_variables ValueError)r+r%s r-validate_promptz$OpenAIFunctionsAgent.validate_prompt?sE&*[[ V%;%; ;--.0  cdgS)z0Get input keys. Input refers to user input here.input)r+s r- input_keyszOpenAIFunctionsAgent.input_keysTs yr6cd|jDcgc]}tt|c}Scc}w)zGet functions.)r$dictrr*s r- functionszOpenAIFunctionsAgent.functionsYs(>BZZH/23HHHs-Nintermediate_steps callbackswith_functionskwargsc t|}|jjDcic]}|dk7s |||}}tdi|d|i}|jjdi|} | j } |r)|j j| |j|} n|j j| |} |jj| } | Scc}w)a Given input, decided what to do. Args: intermediate_steps: Steps the LLM has taken to date, along with observations. callbacks: Callbacks to use. Defaults to None. with_functions: Whether to use functions. Defaults to True. **kwargs: User inputs. Returns: Action specifying what tool to use. If the agent is finished, returns an AgentFinish. If the agent is not finished, returns an AgentAction. r2r=r?)r?r9) rr%r3r< format_prompt to_messagesr#predict_messagesr=r&_parse_ai_message) r+r>r?r@rAr2kselected_inputs full_inputsr%messagespredicted_messageagent_decisions r-planzOpenAIFunctionsAgent.plan_s*>>PQ"&++"="= FXAXAvayL  P_P?OP ***9[9%%'  $ 9 9..#!:!  !% 9 9#!:! ++==>OP% s CCcKt|}|jjDcic]}|dk7s |||}}tdi|d|i}|jjdi|}|j } |j j| |j|d{} |jj| } | Scc}w7&w)aAsync given input, decided what to do. Args: intermediate_steps: Steps the LLM has taken to date, along with observations. callbacks: Callbacks to use. Defaults to None. **kwargs: User inputs. Returns: Action specifying what tool to use. If the agent is finished, returns an AgentFinish. If the agent is not finished, returns an AgentAction. r2rCNr9) rr%r3r<rDrEr#apredict_messagesr=r&rG) r+r>r?rAr2rHrIrJr%rKrLrMs r-aplanzOpenAIFunctionsAgent.aplans&>>PQ"&++"="= FXAXAvayL  P_P?OP ***9[9%%'"&(("<"< )#=#  ++==>OP  s!$C  CCA(C !C"'C early_stopping_methodc |dk(rtddidS|dk(r5|j|fddi|}t|tr|Std|td |) aReturn response when agent has been stopped due to max iterations. Args: early_stopping_method: The early stopping method to use. intermediate_steps: Intermediate steps. **kwargs: User inputs. Returns: AgentFinish. Raises: ValueError: If `early_stopping_method` is not `force` or `generate`. ValueError: If `agent_decision` is not an AgentAction. forceoutputz3Agent stopped due to iteration limit or time limit.generater@Fz,got AgentAction with no functions provided: zBearly_stopping_method should be one of `force` or `generate`, got )r rN isinstancer4)r+rRr>rArMs r-return_stopped_responsez,OpenAIFunctionsAgent.return_stopped_responses( !G +PQSU #j 0&TYY"38BRS,-/ r6zYou are a helpful AI assistant.)contentsystem_messageextra_prompt_messagesc|xsg}|r|g}ng}|jg|tjdtdt |S)aCreate prompt for this agent. Args: system_message: Message to use as the system message that will be the first in the prompt. extra_prompt_messages: Prompt messages that will be placed between the system message and the new human input. Returns: A prompt template to pass into this agent. z{input}r2) variable_name)rK)extendr from_templaterr)clsr[r\_promptsrKs r- create_promptz"OpenAIFunctionsAgent.create_promptsg&).B &'HH  *88C $2DE  "844r6callback_managerc B|j||}|d||||d|S)aConstruct an agent from an LLM and tools. Args: llm: The LLM to use as the agent. tools: The tools to use. callback_manager: The callback manager to use. Defaults to None. extra_prompt_messages: Extra prompt messages to use. Defaults to None. system_message: The system message to use. Defaults to a default system message. kwargs: Additional parameters to pass to the agent. )r\r[)r#r%r$rdr9)rc)rar#r$rdr\r[rAr%s r-from_llm_and_toolsz'OpenAIFunctionsAgent.from_llm_and_toolssI."""7)#  -     r6)NT)N))__name__ __module__ __qualname____doc__r __annotations__rrrrr&typeliststrr.rrr5propertyr:r<r=tuplerr boolrrr rNrQrY classmethodrrrrrcr rrfr9r6r-r"r"$s^   H  (489,49,'"#(DII4:II $# ( {C'7!89(( (  ( {K' ( (Z $ {C'7!89  {K' ( @("(!{C'7!89( (  (T3@53 LP 5 / 5 (-F(GH 5  5 5D ;?KO2?53    !  ##67  (-F(GH  !/         r6r"r#r$r%r'c,d|jt|jzvrtd|jd|j |Dcgc] }t |c}}t jd|z|ztz}|Scc}w)a Create an agent that uses OpenAI function calling. Args: llm: LLM to use as the agent. Should work with OpenAI function calling, so either be an OpenAI model that supports that or a wrapper of a different model that adds in equivalent support. tools: Tools this agent has access to. prompt: The prompt to use. See Prompt section below for more. 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. Raises: ValueError: If `agent_scratchpad` is not in the prompt. Example: Creating an agent with no memory .. code-block:: python from langchain_community.chat_models import ChatOpenAI from langchain.agents import AgentExecutor, create_openai_functions_agent from langchain import hub prompt = hub.pull("hwchase17/openai-functions-agent") model = ChatOpenAI() tools = ... agent = create_openai_functions_agent(model, tools, prompt) agent_executor = AgentExecutor(agent=agent, tools=tools) agent_executor.invoke({"input": "hi"}) # Using with chat history from langchain_core.messages import AIMessage, HumanMessage agent_executor.invoke( { "input": "what's my name?", "chat_history": [ HumanMessage(content="hi! my name is bob"), AIMessage(content="Hello Bob! How can I assist you today?"), ], } ) Prompt: The agent prompt must have an `agent_scratchpad` key that is a ``MessagesPlaceholder``. Intermediate agent actions and tool output messages will be passed in here. Here's an example: .. code-block:: python from langchain_core.prompts import ChatPromptTemplate, MessagesPlaceholder prompt = ChatPromptTemplate.from_messages( [ ("system", "You are a helpful assistant"), MessagesPlaceholder("chat_history", optional=True), ("human", "{input}"), MessagesPlaceholder("agent_scratchpad"), ] ) r2zLPrompt must have input variable `agent_scratchpad`, but wasn't found. Found z instead.)r=ct|dS)Nr>r)xs r-z/create_openai_functions_agent..ls'I&'(r6)r2) r3rmpartial_variablesr4bindrrassignr)r#r$r%r,llm_with_toolsagents r-rrsPf&>&>!?? ++,I 7  XXPU(V1)CA)F(VXWN""       + , -  L)Ws BN).rjcollections.abcrtypingrrrlangchain_core._apirlangchain_core.agentsrr langchain_core.callbacksr r langchain_core.language_modelsr langchain_core.messagesr rlangchain_core.promptsrlangchain_core.prompts.chatrrrrlangchain_core.runnablesrrlangchain_core.toolsr%langchain_core.utils.function_callingrpydanticrtyping_extensionsrlangchain.agentsr3langchain.agents.format_scratchpad.openai_functionsr0langchain.agents.output_parsers.openai_functionsrr"rr9r6r-rsN$''*:C<6 C)L$"2  G!@%Pr 0r Qr jZ Z#+H#5Z?QZ Zr6