chuckdries/langchain-quickstart
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cleanup

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Chuck Dries 2024-02-15 00:13:51 -08:00
parent 298596e47e
commit e3b7dcb870
3 changed files with 9 additions and 22 deletions
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2
README.md
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@ -1 +1 @@
# knowledge-sidekick # langchain-quickstart

2
package.json
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@ -1,5 +1,5 @@
{ {
"name": "knowledge-sidekick", "name": "langchain-quickstart",
"packageManager": "yarn@4.1.0", "packageManager": "yarn@4.1.0",
"type": "module", "type": "module",
"dependencies": { "dependencies": {

27
src/index.js
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@ -1,8 +1,7 @@
import 'dotenv/config'; import "dotenv/config";
process.env.OPENAI_API_KEY; process.env.OPENAI_API_KEY;
import { ChatOpenAI, OpenAIEmbeddings } from "@langchain/openai"; import { ChatOpenAI, OpenAIEmbeddings } from "@langchain/openai";
import { ChatPromptTemplate } from "@langchain/core/prompts"; import { ChatPromptTemplate } from "@langchain/core/prompts";
import { StringOutputParser } from "@langchain/core/output_parsers";
import { MemoryVectorStore } from "langchain/vectorstores/memory"; import { MemoryVectorStore } from "langchain/vectorstores/memory";
import { createRetrievalChain } from "langchain/chains/retrieval"; import { createRetrievalChain } from "langchain/chains/retrieval";
import { createStuffDocumentsChain } from "langchain/chains/combine_documents"; import { createStuffDocumentsChain } from "langchain/chains/combine_documents";
@ -11,9 +10,7 @@ import { CheerioWebBaseLoader } from "langchain/document_loaders/web/cheerio";
import { RecursiveCharacterTextSplitter } from "langchain/text_splitter"; import { RecursiveCharacterTextSplitter } from "langchain/text_splitter";
const chatModel = new ChatOpenAI({}); const chatModel = new ChatOpenAI({});
const loader = new CheerioWebBaseLoader( const loader = new CheerioWebBaseLoader("https://docs.smith.langchain.com/");
"https://docs.smith.langchain.com/"
);
const docs = await loader.load(); const docs = await loader.load();
@ -30,14 +27,15 @@ const vectorstore = await MemoryVectorStore.fromDocuments(
const retriever = vectorstore.asRetriever(); const retriever = vectorstore.asRetriever();
const prompt = const prompt = ChatPromptTemplate.fromTemplate(
ChatPromptTemplate.fromTemplate(`Answer the following question based only on the provided context: `Answer the following question based only on the provided context:
<context> <context>
{context} {context}
</context> </context>
Question: {input}`); Question: {input}`
);
const documentChain = await createStuffDocumentsChain({ const documentChain = await createStuffDocumentsChain({
llm: chatModel, llm: chatModel,
@ -49,19 +47,8 @@ const retrievalChain = await createRetrievalChain({
retriever, retriever,
}); });
const outputParser = new StringOutputParser();
// const prompt = ChatPromptTemplate.fromMessages([
// ["system", "You are an old farmer"],
// ["user", "{input}"],
// ]);
// const chain = prompt.pipe(chatModel).pipe(outputParser);
const res = await retrievalChain.invoke({ const res = await retrievalChain.invoke({
input: "What is langsmith", input: "What is langsmith",
}); });
console.log(res); console.log(res);