j<dZddlmZddlmZddlmZddlmZm Z m Z ddl m Z ddl mZddlmZdd lmZed d d GddeZy)z6Chain that carries on a conversation and calls an LLM.) deprecated) BaseMemory)BasePromptTemplate) ConfigDictFieldmodel_validator)Self)PROMPT)LLMChain)ConversationBufferMemoryz0.2.7z;langchain_core.runnables.history.RunnableWithMessageHistoryz1.0)since alternativeremovalceZdZUdZeeZeed< e Z e ed< dZ e ed<dZe ed<ed d Zed efd Zed ee fdZedd efdZy)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_factorymemorypromptinput input_keyresponse output_keyTforbid)arbitrary_types_allowedextrareturncy)NF)clss l/var/www/html/Fitness-lenito-AI-main/venv/lib/python3.12/site-packages/langchain/chains/conversation/base.pyis_lc_serializablez$ConversationChain.is_lc_serializablersc|jgS)z5Use this since so some prompt vars come from history.)r)selfs r input_keyszConversationChain.input_keysvsr"after)modec|jj}|j}||vrd|d|d}t||jj }g||}t |t |k7rd|d|d|d}t||S)z4Validate that prompt input variables are consistent.zThe input key z$ 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.)rmemory_variablesr ValueErrorrinput_variablesset)r$ memory_keysrmsgprompt_variables expected_keyss r validate_prompt_input_variablesz1ConversationChain.validate_prompt_input_variables{skk22 NN  #  ,= KM S/ !;;661+1y1 } %5!6 6L#$J{m<(k)BD  S/ ! r"N)__name__ __module__ __qualname____doc__rr rr__annotations__r rrrstrrr model_config classmethodboolr!propertylistr%rr r1rr"r rrs Ob/GHFJH!'F '-Is J  $L 4 DI  '"#r"rN)r5langchain_core._apirlangchain_core.memoryrlangchain_core.promptsrpydanticrrrtyping_extensionsr $langchain.chains.conversation.promptr langchain.chains.llmr langchain.memory.bufferr rrr"r rEsO<*,577"7)< M  ||  |r"