
    Ng                         d Z ddlmZ ddlmZ ddlmZ ddlmZ ddl	m
Z
mZmZ ddlmZ ddlmZ dd	lmZ dd
lmZ  eddd           G d de                      ZdS )z6Chain that carries on a conversation and calls an LLM.    )List)
deprecated)
BaseMemory)BasePromptTemplate)
ConfigDictFieldmodel_validator)Self)PROMPT)LLMChain)ConversationBufferMemoryz0.2.7zRunnableWithMessageHistory: https://python.langchain.com/v0.2/api_reference/core/runnables/langchain_core.runnables.history.RunnableWithMessageHistory.htmlz1.0)sincealternativeremovalc                       e Zd ZU dZ ee          Zeed<   	 e	Z
eed<   	 dZeed<   dZeed<    ed	d
          Zedefd            Zedee         fd            Z ed          defd            ZdS )ConversationChaina}  Chain to have a conversation and load context from memory.

    This class is deprecated in favor of ``RunnableWithMessageHistory``. Please refer
    to this tutorial for more detail: https://python.langchain.com/docs/tutorials/chatbot/

    ``RunnableWithMessageHistory`` offers several benefits, including:

    - Stream, batch, and async support;
    - More flexible memory handling, including the ability to manage memory
      outside the chain;
    - Support for multiple threads.

    Below is a minimal implementation, analogous to using ``ConversationChain`` with
    the default ``ConversationBufferMemory``:

        .. code-block:: python

            from langchain_core.chat_history import InMemoryChatMessageHistory
            from langchain_core.runnables.history import RunnableWithMessageHistory
            from langchain_openai import ChatOpenAI


            store = {}  # memory is maintained outside the chain

            def get_session_history(session_id: str) -> InMemoryChatMessageHistory:
                if session_id not in store:
                    store[session_id] = InMemoryChatMessageHistory()
                return store[session_id]

            llm = ChatOpenAI(model="gpt-3.5-turbo-0125")

            chain = RunnableWithMessageHistory(llm, get_session_history)
            chain.invoke(
                "Hi I'm Bob.",
                config={"configurable": {"session_id": "1"}},
            )  # session_id determines thread
    Memory objects can also be incorporated into the ``get_session_history`` callable:

        .. code-block:: python

            from langchain.memory import ConversationBufferWindowMemory
            from langchain_core.chat_history import InMemoryChatMessageHistory
            from langchain_core.runnables.history import RunnableWithMessageHistory
            from langchain_openai import ChatOpenAI


            store = {}  # memory is maintained outside the chain

            def get_session_history(session_id: str) -> InMemoryChatMessageHistory:
                if session_id not in store:
                    store[session_id] = InMemoryChatMessageHistory()
                    return store[session_id]

                memory = ConversationBufferWindowMemory(
                    chat_memory=store[session_id],
                    k=3,
                    return_messages=True,
                )
                assert len(memory.memory_variables) == 1
                key = memory.memory_variables[0]
                messages = memory.load_memory_variables({})[key]
                store[session_id] = InMemoryChatMessageHistory(messages=messages)
                return store[session_id]

            llm = ChatOpenAI(model="gpt-3.5-turbo-0125")

            chain = RunnableWithMessageHistory(llm, get_session_history)
            chain.invoke(
                "Hi I'm Bob.",
                config={"configurable": {"session_id": "1"}},
            )  # session_id determines thread

    Example:
        .. code-block:: python

            from langchain.chains import ConversationChain
            from langchain_community.llms import OpenAI

            conversation = ConversationChain(llm=OpenAI())
    )default_factorymemorypromptinput	input_keyresponse
output_keyTforbid)arbitrary_types_allowedextrareturnc                     dS )NF )clss    ^/var/www/html/ai-engine/env/lib/python3.11/site-packages/langchain/chains/conversation/base.pyis_lc_serializablez$ConversationChain.is_lc_serializablew   s    u    c                     | j         gS )z5Use this since so some prompt vars come from history.)r   )selfs    r!   
input_keyszConversationChain.input_keys{   s     r#   after)modec           	          | j         j        }| j        }||v rt          d| d| d          | j        j        }||gz   }t          |          t          |          k    rt          d| d| d| d          | S )z4Validate that prompt input variables are consistent.zThe input key z$ was also found in the memory keys (z+) - please provide keys that don't overlap.z:Got unexpected prompt input variables. The prompt expects z
, but got z as inputs from memory, and z as the normal input key.)r   memory_variablesr   
ValueErrorr   input_variablesset)r%   memory_keysr   prompt_variablesexpected_keyss        r!   validate_prompt_input_variablesz1ConversationChain.validate_prompt_input_variables   s     k2N	##M M MM M M    ;6#yk1}%5!6!666D#D D/:D D(D D D  
 r#   N)__name__
__module____qualname____doc__r   r   r   r   __annotations__r   r   r   r   strr   r   model_configclassmethodboolr"   propertyr   r&   r	   r
   r1   r   r#   r!   r   r      s        O Ob /GHHHFJHHH!'F'''-Is J   : $  L
 4    [  DI       X  _'"""    #"  r#   r   N)r5   typingr   langchain_core._apir   langchain_core.memoryr   langchain_core.promptsr   pydanticr   r   r	   typing_extensionsr
   $langchain.chains.conversation.promptr   langchain.chains.llmr   langchain.memory.bufferr   r   r   r#   r!   <module>rE      s%   < <       * * * * * * , , , , , , 5 5 5 5 5 5 7 7 7 7 7 7 7 7 7 7 " " " " " " 7 7 7 7 7 7 ) ) ) ) ) ) < < < < < < 
	J   z z z z z z z z z zr#   