a ~g@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)messageremovalcseZdZUdZdZded<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$d%ZZS)'ConversationalAgentz>An agent that holds a conversation in addition to using tools.AIstr ai_prefix)default_factoryr output_parserr)rkwargsreturncKs t|dS)Nrr)clsrr r$i/var/www/html/emsaiapi.evdpl.com/venv/lib/python3.9/site-packages/langchain/agents/conversational/base.py_get_default_output_parser$sz.ConversationalAgent._get_default_output_parser)r!cCstjS)z Return Identifier of agent type.)r CONVERSATIONAL_REACT_DESCRIPTIONselfr$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$r% llm_prefix8szConversationalAgent.llm_prefixHumanNzSequence[BaseTool]zOptional[List[str]]r )toolsprefixsuffixformat_instructionsr human_prefixinput_variablesr!c Csfddd|D}ddd|D} |j| ||d}d||||g} |durZgd }t| |d S) auCreate prompt in the style of the zero-shot agent. Args: tools: List of tools the agent will have access to, used to format the prompt. prefix: String to put before the list of tools. Defaults to PREFIX. suffix: String to put after the list of tools. Defaults to SUFFIX. format_instructions: Instructions on how to use the tools. Defaults to FORMAT_INSTRUCTIONS ai_prefix: String to use before AI output. Defaults to "AI". human_prefix: String to use before human output. Defaults to "Human". input_variables: List of input variables the final prompt will expect. Defaults to ["input", "chat_history", "agent_scratchpad"]. Returns: A PromptTemplate with the template assembled from the pieces here.  cSs g|]}d|jd|jqS)z> z: )name description.0toolr$r$r% _z5ConversationalAgent.create_prompt..z, cSsg|] }|jqSr$r5r7r$r$r%r:ar;) tool_namesrr2z N)input chat_historyagent_scratchpad)templater3)joinformatr ) r#r.r/r0r1rr2r3 tool_stringsr=rAr$r$r% create_promptAs z!ConversationalAgent.create_promptNone)r.r!cst|t|j|dS)N)super_validate_toolsr__name__)r#r. __class__r$r%rHjs z#ConversationalAgent._validate_toolsr zOptional[BaseCallbackManager]zOptional[AgentOutputParser]r) llmr.callback_managerrr/r0r1rr2r3r r!c  Ksf|||j||| |||| d} t|| |d} dd|D}|pL|j|d}|f| |||d| S)aConstruct an agent from an LLM and tools. Args: llm: The language model to use. tools: A list of tools to use. callback_manager: The callback manager to use. Default is None. output_parser: The output parser to use. Default is None. prefix: The prefix to use in the prompt. Default is PREFIX. suffix: The suffix to use in the prompt. Default is SUFFIX. format_instructions: The format instructions to use. Default is FORMAT_INSTRUCTIONS. ai_prefix: The prefix to use before AI output. Default is "AI". human_prefix: The prefix to use before human output. Default is "Human". input_variables: The input variables to use. Default is None. **kwargs: Any additional keyword arguments to pass to the agent. Returns: An agent. )rr2r/r0r1r3)rLpromptrMcSsg|] }|jqSr$r<r7r$r$r%r:r;z:ConversationalAgent.from_llm_and_tools..r") llm_chain allowed_toolsrr)rHrErr&)r#rLr.rMrr/r0r1rr2r3r rNrOr=_output_parserr$r$r%from_llm_and_toolsos6#  z&ConversationalAgent.from_llm_and_tools)r)rI __module__ __qualname____doc__r__annotations__r rr classmethodr&propertyr*r+r,rrrrErHrR __classcell__r$r$rJr%rs@   (rN)&rU __future__rtypingrrrrlangchain_core._apirlangchain_core.callbacksrlangchain_core.language_modelsr langchain_core.promptsr langchain_core.toolsr pydanticr Zlangchain._api.deprecationr langchain.agents.agentrrlangchain.agents.agent_typesrZ-langchain.agents.conversational.output_parserrZ&langchain.agents.conversational.promptrrrlangchain.agents.utilsrlangchain.chainsrrr$r$r$r%s*