chatbot/Custom_chain.py

from langchain.chains.base import Chain
from langchain.schema import BaseRetriever
from langchain.llms import BaseLLM
from langchain.prompts import PromptTemplate
from pydantic import Field
from typing import Dict, Any

class MyCustomMemoryRetrievalChain(Chain):
    """
    Custom chain cho phép truyền question, memory.
    Lấy docs từ retriever, trộn với prompt, gọi LLM.
    """

    llm: BaseLLM = Field(...)
    retriever: BaseRetriever = Field(...)
    prompt: PromptTemplate = Field(...)
    output_key: str = "result"  

    @property
    def input_keys(self) -> list:
        return ["question", "memory"]

    @property
    def output_keys(self) -> list:
        return [self.output_key]

    def _call(self, inputs: Dict[str, Any], run_manager=None) -> Dict[str, Any]:
        question = inputs["question"]
        memory = inputs["memory"]

        docs = self.retriever.get_relevant_documents(question)
        context = "\n".join(doc.page_content for doc in docs)

        final_prompt = self.prompt.format(
            question=question,
            memory=memory,
            context=context
        )

        answer = self.llm(final_prompt)

        return {self.output_key: answer}