ConversationChain Class — langchain Architecture

Architecture documentation for the ConversationChain class in base.py from the langchain codebase.

Class python

Entity Profile

Dependency Diagram

graph TD
  853b7df9_e3a3_92a2_3356_2d2935763bb7["ConversationChain"]
  8d3a235d_a08f_2979_f52a_1772067dd1d3["LLMChain"]
  853b7df9_e3a3_92a2_3356_2d2935763bb7 -->|extends| 8d3a235d_a08f_2979_f52a_1772067dd1d3
  df646892_6a63_bc00_9455_be9f2246d36d["base.py"]
  853b7df9_e3a3_92a2_3356_2d2935763bb7 -->|defined in| df646892_6a63_bc00_9455_be9f2246d36d
  80f31d7d_b306_0e56_0ef2_2bef34e17254["is_lc_serializable()"]
  853b7df9_e3a3_92a2_3356_2d2935763bb7 -->|method| 80f31d7d_b306_0e56_0ef2_2bef34e17254
  9bad9e5d_6c49_720c_dcea_170da57f71ac["input_keys()"]
  853b7df9_e3a3_92a2_3356_2d2935763bb7 -->|method| 9bad9e5d_6c49_720c_dcea_170da57f71ac
  7b02e98d_b3d9_e0dd_2c16_67db7fa2c663["validate_prompt_input_variables()"]
  853b7df9_e3a3_92a2_3356_2d2935763bb7 -->|method| 7b02e98d_b3d9_e0dd_2c16_67db7fa2c663

Relationship Graph

Source Code

libs/langchain/langchain_classic/chains/conversation/base.py lines 19–149

class ConversationChain(LLMChain):
    """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`:

        ```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]


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

        chain = RunnableWithMessageHistory(model, 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:

        ```python
        from langchain_classic.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]


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

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

    Example:
        ```python
        from langchain_classic.chains import ConversationChain