https://github.com/shimaa83/llmchat

LLM chat app using RAG and langchain
https://github.com/shimaa83/llmchat

gemini langchain llm python3 streamlit

Last synced: 5 days ago
JSON representation

LLM chat app using RAG and langchain

• Host: GitHub
• URL: https://github.com/shimaa83/llmchat
• Owner: shimaa83
• Created: 2024-08-21T22:53:11.000Z (3 months ago)
• Default Branch: main
• Last Pushed: 2024-08-21T23:10:17.000Z (3 months ago)
• Last Synced: 2024-10-11T09:22:34.330Z (28 days ago)
• Topics: gemini, langchain, llm, python3, streamlit
• Language: Python
• Homepage:
• Size: 9.77 KB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

Awesome Lists containing this project

README

        
# Research Question Answering App

This is a Streamlit application that allows users to upload a PDF research, input a question about the research, and receive a detailed summary or answer based on the content of the PDF using gemini model.

## Features

- **Upload PDF**: Upload a PDF file to be processed.

- **Ask Questions**: Enter questions about the content of the PDF.

- **Get Answers**: Receive detailed answers or summaries based on the PDF content.

## Requirements

- Python 3.7 or higher

- Required Python libraries:

  - `streamlit`

  - `pdfplumber`

  - `langchain_community`

  - `langchain`

  - `langchain_chroma`

  - `langchain_google_genai`

  - `langchain_core`

  - `python-dotenv`

## Installation

1. Clone the repository:

   ```bash

   git clone https://github.com/shimaa83/LLMChat.git

   cd LLMChat

2. Create a .env file in the root directory of the project and add your Google API key:

      - GOOGLE_API_KEY=your_google_api_key_here

3. Start the Streamlit app:

  -  streamlit run chat.py

![LLM](https://github.com/user-attachments/assets/b3adcc4e-0566-433b-b733-f830337c0ba7)