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langchain-pdfbot

v1.0.6

Published

A LangChain-based tool to answer questions strictly from PDF content using Groq LLM and local embeddings.

Readme

📄 LangChain PDFChat

LangChain PDFChat is a lightweight Node.js library that helps you build a local question–answering chatbot over any PDF.
It uses local embeddings (so you don’t pay per token) and powerful Groq LLM to generate answers strictly based on the PDF content.

Only answers questions if info is found in the PDF
Fast: Uses in-memory vector search
Easy to use: Just point to a local PDF, ask questions


✏️ How it works

  1. You load a PDF file from your local system.
  2. The tool splits & embeds the PDF content in memory.
  3. A retriever fetches only the relevant chunks for each user question.
  4. The question and chunks go to the Groq LLM to generate an answer.
  5. If the answer isn't in the PDF, it says: "Not relevant question".

🚀 Quick Start

Step 1: Install

npm install langchain-pdfbot

Step 2: Get your free Groq API key

  • Sign up at: https://console.groq.com
  • Go to Settings → API Keys → Create API Key
  • Copy your new API key (starts with gsk_...)

Step 3: Add your API key to .env

GROQ_API_KEY=your_groq_api_key_here

Step 4: Use in your code

// index.js

import {createLlm} from "./model/llm.model.js";
import {createPdfQaTool} from "./tools/pdfQa.js";

const llm = createLlm({ apiKey: <groq-api-key>, model: "llama3-70b-8192" });

const askQuestion = await createPdfQaTool("./pdfs/sample.pdf", llm);

const answer = await askQuestion("what is array? ");
console.log("Answer:", answer);