U ho@sdZddlmZddlmZmZmZmZddlm Z ddl m Z ddl m Z ddlmZddlmZdd lmZdd lmZmZdd lmZdd lmZdd lmZmZmZddlm Z ddl!m"Z"e ddddGdddeZ#dS)zDAn agent designed to hold a conversation in addition to using tools.) annotations)AnyListOptionalSequence) deprecated)BaseCallbackManager)BaseLanguageModel)PromptTemplate)Field)BaseTool)AgentAgentOutputParser) AgentTypeConvoOutputParser)FORMAT_INSTRUCTIONSPREFIXSUFFIX)validate_tools_single_input)LLMChainz0.1.0Zcreate_react_agentz1.0) alternativeZremovalcseZdZUdZdZded<eedZded<e d&dddd d d Z e dd d dZ e dd ddZ e dd ddZe eeedddfdddddddddddZe dddfdd Ze ddeeedddfddd d!dddddddd"d# d$d%ZZS)'ConversationalAgentz>An agent that holds a conversation in addition to using tools.AIstr ai_prefix)default_factoryr output_parserr)rkwargsreturncKs t|dS)Nrr)clsrrr"H/tmp/pip-unpacked-wheel-bo69hh5q/langchain/agents/conversational/base.py_get_default_output_parsersz.ConversationalAgent._get_default_output_parser)rcCstjS)z Return Identifier of agent type.)rZ CONVERSATIONAL_REACT_DESCRIPTIONselfr"r"r# _agent_type%szConversationalAgent._agent_typecCsdS)z]Prefix to append the observation with. Returns: "Observation: " z Observation: r"r%r"r"r#observation_prefix*sz&ConversationalAgent.observation_prefixcCsdS)zVPrefix to append the llm call with. Returns: "Thought: " zThought:r"r%r"r"r# llm_prefix3szConversationalAgent.llm_prefixZHumanNzSequence[BaseTool]zOptional[List[str]]r )toolsprefixsuffixformat_instructionsr human_prefixinput_variablesrc Cshddd|D}ddd|D} |j| ||d}d||||g} |dkr\d d d g}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.0Ztoolr"r"r# Zsz5ConversationalAgent.create_prompt..z, cSsg|] }|jqSr"r1r3r"r"r#r5\s) tool_namesrr.z NinputZ chat_historyZagent_scratchpad)templater/)joinformatr ) r!r*r+r,r-rr.r/Z tool_stringsr7r9r"r"r# create_prompt<s  z!ConversationalAgent.create_promptNone)r*rcst|t|j|dS)N)super_validate_toolsr__name__)r!r* __class__r"r#r?es z#ConversationalAgent._validate_toolsr zOptional[BaseCallbackManager]zOptional[AgentOutputParser]r ) llmr*callback_managerrr+r,r-rr.r/rrc  Ksf|||j||| |||| d} t|| |d} dd|D}|pL|j|d}|f| |||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. )rr.r+r,r-r/)rCpromptrDcSsg|] }|jqSr"r6r3r"r"r#r5sz:ConversationalAgent.from_llm_and_tools..r ) llm_chainZ allowed_toolsrr)r?r<rr$)r!rCr*rDrr+r,r-rr.r/rrErFr7Z_output_parserr"r"r#from_llm_and_toolsjs6#  z&ConversationalAgent.from_llm_and_tools)r)r@ __module__ __qualname____doc__r__annotations__r rr classmethodr$propertyr'r(r)rrrr<r?rG __classcell__r"r"rAr#rs@   (rN)$rJ __future__rtypingrrrrZlangchain_core._apirZlangchain_core.callbacksrZlangchain_core.language_modelsr Zlangchain_core.promptsr Zlangchain_core.pydantic_v1r Zlangchain_core.toolsr Zlangchain.agents.agentr rZlangchain.agents.agent_typesrZ-langchain.agents.conversational.output_parserrZ&langchain.agents.conversational.promptrrrZlangchain.agents.utilsrZlangchain.chainsrrr"r"r"r#s