summary.py — langchain Source File

Source Code

from __future__ import annotations

from typing import Any

from langchain_core._api import deprecated
from langchain_core.chat_history import BaseChatMessageHistory
from langchain_core.language_models import BaseLanguageModel
from langchain_core.messages import BaseMessage, SystemMessage, get_buffer_string
from langchain_core.prompts import BasePromptTemplate
from langchain_core.utils import pre_init
from pydantic import BaseModel
from typing_extensions import override

from langchain_classic.chains.llm import LLMChain
from langchain_classic.memory.chat_memory import BaseChatMemory
from langchain_classic.memory.prompt import SUMMARY_PROMPT


@deprecated(
    since="0.2.12",
    removal="1.0",
    message=(
        "Refer here for how to incorporate summaries of conversation history: "
        "https://docs.langchain.com/oss/python/langgraph/add-memory#summarize-messages"
    ),
)
class SummarizerMixin(BaseModel):
    """Mixin for summarizer."""

    human_prefix: str = "Human"
    ai_prefix: str = "AI"
    llm: BaseLanguageModel
    prompt: BasePromptTemplate = SUMMARY_PROMPT
    summary_message_cls: type[BaseMessage] = SystemMessage

    def predict_new_summary(
        self,
        messages: list[BaseMessage],
        existing_summary: str,
    ) -> str:
        """Predict a new summary based on the messages and existing summary.

        Args:
            messages: List of messages to summarize.
            existing_summary: Existing summary to build upon.

        Returns:
            A new summary string.
        """
        new_lines = get_buffer_string(
            messages,
            human_prefix=self.human_prefix,
            ai_prefix=self.ai_prefix,
        )

        chain = LLMChain(llm=self.llm, prompt=self.prompt)
        return chain.predict(summary=existing_summary, new_lines=new_lines)

    async def apredict_new_summary(
        self,
// ... (109 more lines)