https://github.com/vishnun0027/pdf-ingestion-qna-app

This Application based on RAG(Retrieval-augmented generation) that allows users to upload PDF documents and ask questions based on the content of those documents.
https://github.com/vishnun0027/pdf-ingestion-qna-app

langchain llm python rag streamlit

Last synced: 16 days ago
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This Application based on RAG(Retrieval-augmented generation) that allows users to upload PDF documents and ask questions based on the content of those documents.

• Host: GitHub
• URL: https://github.com/vishnun0027/pdf-ingestion-qna-app
• Owner: vishnun0027
• Created: 2024-10-13T07:38:31.000Z (3 months ago)
• Default Branch: master
• Last Pushed: 2024-10-27T15:27:55.000Z (2 months ago)
• Last Synced: 2024-10-27T17:39:08.925Z (2 months ago)
• Topics: langchain, llm, python, rag, streamlit
• Language: Python
• Homepage:
• Size: 200 KB
• Stars: 1
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        

# PDF-ingestion-QnA-App

## Overview

The **PDF-ingestion-QnA-App** based on RAG(Retrieval-augmented generation) is a powerful application that allows users to upload PDF documents and ask questions based on the content of those documents. Leveraging advanced language models and retrieval-augmented generation techniques, this application provides concise and accurate answers from the uploaded PDFs.

![Screenshot](./img/Screenshot.png)

## Features

- Upload and process PDF documents.

- Ask questions about the content of the uploaded PDFs.

- Efficient text splitting and embedding using state-of-the-art models.

- In-memory vector storage for fast retrieval of document chunks.

- User-friendly interface built with Streamlit.

## Technologies Used

- **Python**: The programming language used for the implementation.

- **LangChain**: A framework for developing applications with language models.

- **Streamlit**: A library for building interactive web applications.

- **Hugging Face**: For pre-trained models and embeddings.

- **Groq**: For efficient model execution.

## Installation

To get started with the PDF Q&A System, follow these steps:

1. **Clone the repository**:

   ```bash

   git clone https://github.com/vishnun0027/PDF-ingestion-QnA-App.git

   PDF-ingestion-QnA-App

   ```

2.Install the required packages:

```bash

   pip install -r requirements.txt

```

3. Set up environment variables: Create a .env file in the root directory of the project and add your API keys:

```bash

  GROQ_API_KEY=your_groq_api_key

  HF_API_KEY=your_hugging_face_api_key

```

## Usage

1. Run the Streamlit application:

2. run app

```gash

   streamlit run app.py

```

3. Upload a PDF:

Use the sidebar to upload your PDF document.

4. Ask Questions:

After processing, enter your questions in the chat input field to receive answers based on the content of the PDF.