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https://github.com/praneethravuri/open-llms

A full-stack application that allows you to chat with open-source language models in a ChatGPT-like interface
https://github.com/praneethravuri/open-llms

ai axios chatbot chatgpt fastapi huggingface llm llm-aggregator llms machine-learning nextjs nlp python react tailwindcss transformers typescript

Last synced: 3 months ago
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A full-stack application that allows you to chat with open-source language models in a ChatGPT-like interface

Host: GitHub
URL: https://github.com/praneethravuri/open-llms
Owner: praneethravuri
License: mit
Created: 2024-05-20T11:36:27.000Z (8 months ago)
Default Branch: main
Last Pushed: 2024-09-10T16:59:44.000Z (4 months ago)
Last Synced: 2024-09-11T04:16:50.559Z (4 months ago)
Topics: ai, axios, chatbot, chatgpt, fastapi, huggingface, llm, llm-aggregator, llms, machine-learning, nextjs, nlp, python, react, tailwindcss, transformers, typescript
Language: TypeScript
Homepage:
Size: 305 KB
Stars: 2
Watchers: 1
Forks: 0
Open Issues: 0
Metadata Files:
- Readme: README.md
- License: LICENSE

Awesome Lists containing this project

README

# OpenLLMs 💬🤖
A chat application that allows users to interact with pre-trained open-source LLM models for question answering. The application features a chat interface where users can input questions, and the application responds with answers generated by the selected models. The aim of this project is to demonstrate how to integrate pre-trained transformer models with a modern web frontend using Next.js and work with multiple LLMs simultaneously.

![Alt Text](demo.gif)

## Table of Contents

- [Tech Stack](#tech-stack)
- [Installation](#installation)
- [Running the Application](#running-the-application)
- [Usage](#usage)

## Tech Stack

- **Frontend**: Next.js 14, React, TypeScript, Tailwind CSS
- **Backend**: FastAPI, Python, SearxNG
- **Machine Learning**: Hugging Face Transformers for LLMs
- **Other Libraries**: Axios (for HTTP requests), CORS Middleware

## Installation

Follow these steps to set up and run the application on your local machine.

### Prerequisites

- Node.js 14+
- Python 3.7+
- Git
- Docker

### Steps

1. **Clone the Repository**

```bash
git clone https://github.com/praneethravuri/open-llms.git
```

2. **Backend Setup**

Navigate to the backend directory, create a virtual environment, and install the required dependencies.

```bash
cd backend
python -m venv venv
source venv/bin/activate # On Windows use `venv\Scripts\activate`
pip install -r requirements.txt
```

If the `requirements.txt` file does not exist, create it with the following content:

```txt
fastapi
uvicorn
transformers
torch
tensorflow
sentence_transformers
nltk
tf-keras
language_tool_python
textblob
pymongo
```

Additionally, install PyTorch with CUDA support:
```bash
pip install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/cu118
```

3. **Frontend Setup**

Navigate to the frontend directory and install the required dependencies.

```bash
cd frontend
npm install
```

## Running the Application 🚀

### Backend

1. **Start the FastAPI Server**

```bash
uvicorn app.main:app --reload --host 0.0.0.0 --port 8000
```

2. **Start SearXNG***

Navigate to the searxng-docker directory and start SearxNG using Docker.

```bash
cd searxng-docker
docker-compose up
```

### Frontend

1. **Start the Next.js Development Server**

```bash
npm run dev
```

### Access the Application

Open your browser and navigate to `http://localhost:3000` to see the chat interface.

## Usage

1. **Interact with the Chat Interface**

- Open the chat interface in your browser.
- Type a question in the input box at the bottom.
- Press the send button or hit enter to send your question.
- The application will respond with an answer generated by the selected model.

2. **Interact with Different LLMs**

- Select a particular pre-trained LLM.
- Type a question in the input box at the bottom.
- Press the send button or hit enter to send your question.
- The application will respond with an answer generated by the selected model.

By following these steps, you will be able to interact with various pre-trained language models through a modern and intuitive web interface. Enjoy exploring the capabilities of LLMs! 🎉🧠