/* Conversational Retrieval Chain */

import { ChatOpenAI } from "langchain/chat_models/openai";
import { OpenAIEmbeddings } from "langchain/embeddings/openai";
import { PromptTemplate } from "langchain/prompts";
import {
  RunnableSequence,
  RunnablePassthrough,
} from "langchain/schema/runnable";
import { MemoryVectorStore } from "langchain/vectorstores/memory";
import { StringOutputParser } from "langchain/schema/output_parser";

const model = new ChatOpenAI({});

const vectorStore = await MemoryVectorStore.fromTexts(
  [
    "mitochondria is the powerhouse of the cell",
    "mitochondria is made of lipids",
  ],
  [{ id: 1 }, { id: 2 }],
  new OpenAIEmbeddings(),
);

const retriever = vectorStore.asRetriever();

const condenseQuestionTemplate = `Given the following conversation and a follow up question, rephrase the follow up question to be a standalone question.

Chat History:
{chat_history}
Follow Up Input: {question}
Standalone question:
`;

const CONDENSE_QUESTION_PROMPT = PromptTemplate.fromTemplate(
  condenseQuestionTemplate
);

const answerTemplate = `Answer the question based only on the following context:
{context}

Question: {question}
`;

const ANSWER_PROMPT = PromptTemplate.fromTemplate(answerTemplate);

const conversationalRetrievalQAChain;
    
const result1 = await conversationalRetrievalQAChain.invoke({
  question: "What is the powerhouse of the cell?",
  chat_history: [],
});
console.log(result1);
/*
  AIMessage { content: "The powerhouse of the cell is the mitochondria." }
*/

const result2 = await conversationalRetrievalQAChain.invoke({
  question: "What are they made out of?",
  chat_history: [
    [
      "What is the powerhouse of the cell?",
      "The powerhouse of the cell is the mitochondria.",
    ],
  ],
});
console.log(result2);
/*
  AIMessage { content: "Mitochondria are made out of lipids." }
*/