o Ag@sdZddlmZddlmZmZmZmZddlm Z ddl m Z ddl m Z ddlmZddlmZdd lmZdd lmZdd lmZmZdd lmZdd lmZddlmZmZm Z ddl!m"Z"ddl#m$Z$e deddGdddeZ%dS)zDAn agent designed to hold a conversation in addition to using tools.) annotations)AnyListOptionalSequence) deprecated)BaseCallbackManager)BaseLanguageModel)PromptTemplate)BaseTool)Field)AGENT_DEPRECATION_WARNING)AgentAgentOutputParser) AgentTypeConvoOutputParser)FORMAT_INSTRUCTIONSPREFIXSUFFIX)validate_tools_single_input)LLMChainz0.1.0z1.0)messageremovalc seZdZUdZdZded< eedZded< e d+d,d d Z e d-d dZ e d-ddZ e d-ddZe eeedddfd.ddZe d/fd!d" Ze ddeeedddfd0d)d*ZZS)1ConversationalAgentz>An agent that holds a conversation in addition to using tools.AIstr ai_prefix)default_factoryr output_parserkwargsrreturncKs t|dS)Nrr)clsrr r$k/var/www/html/development/chatbot/venv/lib/python3.10/site-packages/langchain/agents/conversational/base.py_get_default_output_parser$s z.ConversationalAgent._get_default_output_parsercCstjS)z Return Identifier of agent type.)r CONVERSATIONAL_REACT_DESCRIPTIONselfr$r$r% _agent_type*szConversationalAgent._agent_typecCdS)z]Prefix to append the observation with. Returns: "Observation: " z Observation: r$r(r$r$r%observation_prefix/z&ConversationalAgent.observation_prefixcCr+)zVPrefix to append the llm call with. Returns: "Thought: " zThought:r$r(r$r$r% llm_prefix8r-zConversationalAgent.llm_prefixHumanNtoolsSequence[BaseTool]prefixsuffixformat_instructions human_prefixinput_variablesOptional[List[str]]r c Csfddd|D}ddd|D} |j| ||d}d||||g} |dur-gd }t| |d S) auCreate prompt in the style of the zero-shot agent. Args: tools: List of tools the agent will have access to, used to format the prompt. prefix: String to put before the list of tools. Defaults to PREFIX. suffix: String to put after the list of tools. Defaults to SUFFIX. format_instructions: Instructions on how to use the tools. Defaults to FORMAT_INSTRUCTIONS ai_prefix: String to use before AI output. Defaults to "AI". human_prefix: String to use before human output. Defaults to "Human". input_variables: List of input variables the final prompt will expect. Defaults to ["input", "chat_history", "agent_scratchpad"]. Returns: A PromptTemplate with the template assembled from the pieces here.  cSs g|] }d|jd|jqS)z> z: )name description.0toolr$r$r% _s z5ConversationalAgent.create_prompt..z, cSg|]}|jqSr$r9r;r$r$r%r>a) tool_namesrr5z N)input chat_historyagent_scratchpad)templater6)joinformatr ) r#r0r2r3r4rr5r6 tool_stringsrBrFr$r$r% create_promptAs  z!ConversationalAgent.create_promptNonecst|t|j|dS)N)super_validate_toolsr__name__)r#r0 __class__r$r%rMjs z#ConversationalAgent._validate_toolsllmr callback_managerOptional[BaseCallbackManager]Optional[AgentOutputParser]rc  Ksf|||j||| |||| d} t|| |d} dd|D}|p&|j|d}|d| |||d| S) aConstruct an agent from an LLM and tools. Args: llm: The language model to use. tools: A list of tools to use. callback_manager: The callback manager to use. Default is None. output_parser: The output parser to use. Default is None. prefix: The prefix to use in the prompt. Default is PREFIX. suffix: The suffix to use in the prompt. Default is SUFFIX. format_instructions: The format instructions to use. Default is FORMAT_INSTRUCTIONS. ai_prefix: The prefix to use before AI output. Default is "AI". human_prefix: The prefix to use before human output. Default is "Human". input_variables: The input variables to use. Default is None. **kwargs: Any additional keyword arguments to pass to the agent. Returns: An agent. )rr5r2r3r4r6)rQpromptrRcSr?r$r@r;r$r$r%r>rAz:ConversationalAgent.from_llm_and_tools..r") llm_chain allowed_toolsrrNr$)rMrJrr&)r#rQr0rRrr2r3r4rr5r6r rUrVrB_output_parserr$r$r%from_llm_and_toolsos6 # z&ConversationalAgent.from_llm_and_tools)r)rrr rr!r)r!r)r0r1r2rr3rr4rrrr5rr6r7r!r )r0r1r!rK)rQr r0r1rRrSrrTr2rr3rr4rrrr5rr6r7r rr!r)rN __module__ __qualname____doc__r__annotations__r rr classmethodr&propertyr*r,r.rrrrJrMrY __classcell__r$r$rOr%rsF     (rN)&r\ __future__rtypingrrrrlangchain_core._apirlangchain_core.callbacksrlangchain_core.language_modelsr langchain_core.promptsr langchain_core.toolsr pydanticr langchain._api.deprecationr langchain.agents.agentrrlangchain.agents.agent_typesr-langchain.agents.conversational.output_parserr&langchain.agents.conversational.promptrrrlangchain.agents.utilsrlangchain.chainsrrr$r$r$r%s,