🐦 TweetGPT — AI-Powered Tweet Generator

TweetGPT is a modern, full-stack application that uses Groq or Ollama LLM models to generate, evaluate, and refine tweets automatically — with no manual intervention. It integrates with X (Twitter) OAuth for secure login and posting, features a sleek, mobile-friendly UI built with React + Vite, and deploys via Docker with Nginx for production-ready frontend hosting.

📦 GitHub Repo: https://github.com/ArchitJ6/TweetGPT

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✨ Features

• 🤖 AI-Powered Tweet Generation — Generates witty, snappy tweets using Groq or Ollama.
• 🔄 Iterative Optimization — Auto-refines tweets until quality and engagement criteria are met.
• 🔐 X OAuth Integration — Secure sign-in and direct posting to X.
• 🎯 Automatic Evaluation — AI checks humor, originality, brevity, and style without manual review.
• ⚡ Fast Model Switching — Toggle between Groq and Ollama seamlessly.
• 🎨 Modern UI — Responsive, Twitter-inspired interface.
• 📱 Mobile Friendly — Optimized for all devices.
• 🐳 Dockerized Deployment — Backend, frontend, and Nginx all containerized.
• 🌐 Nginx Hosting — Production-grade static file serving.
• 📊 Autonomous AI Workflow — Fully automated generation–evaluation–refinement loop.

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🛠 Tech Stack

Layer	Technology
Frontend	React, Vite, JavaScript, CSS
Backend	Python, Flask, LangChain, LangGraph
AI Models	Groq LLM, Ollama LLM
Auth	X (Twitter) OAuth 2.0
Deployment	Docker, Docker Compose, Nginx
Version Control	Git, GitHub

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⚙️ Prerequisites

• 🐍 Python 3.12
• 🐦 X Developer Account with API access
• 🔑 Groq API Key
• 💻 Ollama installed (if using Ollama mode)
• 🐳 Docker & Docker Compose

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🧠 AI Workflow

graph TD
    A[Start] --> B[Generate Tweet]
    B --> C[Evaluate Tweet]
    C -->|Approved| E[End]
    C -->|Needs Improvement| D[Refine Tweet]
    D --> C

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Steps:

1. Generate → AI crafts a humorous tweet based on the topic.
2. Evaluate → AI reviews for creativity, humor, and shareability.
3. Refine → AI improves the tweet if it doesn’t pass.
4. Loop until approved or max iterations reached.

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📂 Project Structure

TweetGPT/
├── backend/
│   ├── .env.example
│   ├── app.py
│   ├── config.py
│   ├── Dockerfile
│   ├── llm_workflow.py
│   └── requirements.txt
├── frontend/
│   ├── .env.example
│   ├── Dockerfile
│   ├── eslint.config.js
│   ├── index.html
│   ├── package-lock.json
│   ├── package.json
│   ├── vite.config.js
│   ├── public/
│   │   └── bot.svg
│   └── src/
│       ├── App.jsx
│       ├── index.css
│       ├── main.jsx
│       ├── components/
│       │   ├── index.js
│       │   ├── NavigationBar.jsx
│       │   └── NotificationBar.jsx
│       ├── pages/
│       │   ├── GeneratorPage.jsx
│       │   ├── HomePage.jsx
│       │   └── index.js
│       └── services/
│           ├── api.js
│           └── index.js
├── .dockerignore
├── .gitignore
└── docker-compose.yml

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🚀 Setup & Run

1️⃣ Clone Repository

git clone https://github.com/ArchitJ6/TweetGPT.git
cd TweetGPT

2️⃣ Configure Environment Variables

📍 Backend (backend/.env)

cd backend
cp .env.example .env

X_CLIENT_ID=""
X_CLIENT_SECRET=""
X_REDIRECT_URI="http://localhost:5000/callback"
X_AUTH_URL="https://twitter.com/i/oauth2/authorize"
X_TOKEN_URL="https://api.twitter.com/2/oauth2/token"
GROQ_API_KEY="your_groq_api_key"
USE_OLLAMA="true_or_false"
GROQ_LLM_MODEL_NAME="your_groq_llm_model_name"
OLLAMA_MODEL_NAME="your_ollama_model_name"

📍 Frontend (frontend/.env)

cd frontend
cp .env.example .env

VITE_API_BASE_URL="http://localhost:5000"

3️⃣ Run Without Docker (Optional)

🔹 Backend

cd backend
pip install -r requirements.txt
python app.py

🔹 Frontend

cd frontend
npm install
npm run dev

4️⃣ Run With Docker (Recommended)

docker-compose up --build

Frontend will be served via 🌐 Nginx at http://localhost:5173 and backend will run at http://localhost:5000.

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📸 Screenshots

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📜 License

MIT License — free to use and modify.

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🤝 Contributing

PRs welcome! Please follow the existing code style.

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Made with ❤️ by Archit Jain