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Replace with conversational retrieval chain
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...ck/plugins/elastic_assistant/server/lib/langchain/conversational_retrieval_chain/index.ts
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,97 @@ | ||
| import { ChatPromptTemplate, MessagesPlaceholder } from 'langchain/prompts'; | ||
| import { | ||
| RunnableBranch, | ||
| RunnableSequence, | ||
| } from 'langchain/runnables'; | ||
| import type { VectorStoreRetriever } from 'langchain/vectorstores/base'; | ||
| import type { BaseLanguageModel } from 'langchain/base_language'; | ||
| import type { BaseMessage } from 'langchain/schema'; | ||
| import { Document } from 'langchain/document'; | ||
| import { StringOutputParser } from 'langchain/schema/output_parser'; | ||
|
|
||
| const CONDENSE_QUESTION_SYSTEM_TEMPLATE = `You are an experienced researcher, expert at interpreting and answering questions based on provided sources. | ||
| Your job is to remove references to chat history from incoming questions, rephrasing them as standalone questions.`; | ||
|
|
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| const CONDENSE_QUESTION_HUMAN_TEMPLATE = `Using only previous conversation as context, rephrase the following question to be a standalone question. | ||
| Do not respond with anything other than a rephrased standalone question. Be concise, but complete and resolve all references to the chat history. | ||
| <question> | ||
| {question} | ||
| </question>`; | ||
| const condenseQuestionPrompt = ChatPromptTemplate.fromMessages([ | ||
| ['system', CONDENSE_QUESTION_SYSTEM_TEMPLATE], | ||
| new MessagesPlaceholder('chat_history'), | ||
| ['human', CONDENSE_QUESTION_HUMAN_TEMPLATE], | ||
| ]); | ||
|
|
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| const ANSWER_SYSTEM_TEMPLATE = `You are an experienced researcher, expert at interpreting and answering questions based on provided sources. | ||
| Using the provided context, answer the user's question to the best of your ability using only the resources provided. | ||
| You must only use information from the provided search results. | ||
| If there is no information in the context relevant to the question at hand, just say "Hmm, I'm not sure." | ||
| Anything between the following \`context\` html blocks is retrieved from a knowledge bank, not part of the conversation with the user. | ||
| <context> | ||
| {context} | ||
| </context>`; | ||
|
|
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| const ANSWER_HUMAN_TEMPLATE = `Answer the following question to the best of your ability: | ||
| {standalone_question}`; | ||
|
|
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| const answerPrompt = ChatPromptTemplate.fromMessages([ | ||
| ["system", ANSWER_SYSTEM_TEMPLATE], | ||
| new MessagesPlaceholder("chat_history"), | ||
| ["human", ANSWER_HUMAN_TEMPLATE], | ||
| ]); | ||
|
|
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| const formatDocuments = (docs: Document[]) => { | ||
| return docs | ||
| .map((doc, i) => { | ||
| return `<doc>\n${doc.pageContent}\n</doc>`; | ||
| }) | ||
| .join("\n"); | ||
| }; | ||
|
|
||
| export function createConversationalRetrievalChain({ | ||
| model, | ||
| retriever, | ||
| }: { | ||
| model: BaseLanguageModel; | ||
| retriever: VectorStoreRetriever; | ||
| }) { | ||
| const retrievalChain = RunnableSequence.from([ | ||
| (input) => input.standalone_question, | ||
| retriever, | ||
| formatDocuments, | ||
| ]).withConfig({ runName: "RetrievalChain" }); | ||
|
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| const standaloneQuestionChain = RunnableSequence.from([ | ||
| condenseQuestionPrompt, | ||
| model, | ||
| new StringOutputParser(), | ||
| ]).withConfig({ runName: "RephraseQuestionChain" }); | ||
|
|
||
| const answerChain = RunnableSequence.from([ | ||
| { | ||
| standalone_question: (input) => input.standalone_question, | ||
| chat_history: (input) => input.chat_history, | ||
| context: retrievalChain, | ||
| }, | ||
| answerPrompt, | ||
| model, | ||
| ]).withConfig({ runName: "AnswerGenerationChain" }); | ||
|
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| const conversationalRetrievalChain = RunnableSequence.from<{question: string, chat_history: BaseMessage[]}>([ | ||
| { | ||
| // Small optimization - only rephrase if the question is a followup | ||
| standalone_question: RunnableBranch.from([ | ||
| [(input) => input.chat_history.length > 0, standaloneQuestionChain], | ||
| (input) => input.question, | ||
| ]), | ||
| chat_history: (input) => input.chat_history, | ||
| }, | ||
| answerChain, | ||
| ]); | ||
| return conversationalRetrievalChain; | ||
| } |
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