🚀 VertexOps - LLMOps Platform

A complete, production-ready LLMOps platform built with FastAPI. Features model deployment, RAG queries, vector search, professional web UI, and comprehensive monitoring.

✨ Key Features

🎯 Core LLMOps Capabilities

🌐 Professional Web Interface

🔒 Enterprise Security & DevOps

🚀 Quick Deploy

Prerequisites

1. Clone & Setup

git clone https://github.com/vijaykalore/vertexops.git
cd vertexops
python -m venv .venv
.venv\Scripts\activate  # Windows
# source .venv/bin/activate  # macOS/Linux
pip install -r requirements.txt

2. Configure Environment

copy .env.example .env  # Windows
### 🐳 Docker (Recommended)
```bash
# Clone and deploy with Docker
git clone https://github.com/vijaykalore/vertexops.git
cd vertexops
docker-compose up --build

Access at: http://localhost:8000

🚀 Cloud Platform (One-Click)

Deploy directly to your favorite platform:

💻 Local Development

# Clone the repository
git clone https://github.com/vijaykalore/vertexops.git
cd vertexops

# Setup virtual environment
python -m venv .venv
source .venv/bin/activate  # Linux/Mac
# .\.venv\Scripts\activate  # Windows

# Install dependencies
pip install -r requirements.txt

# Run the server
uvicorn vertexops.main:app --reload --host 127.0.0.1 --port 8083

🌐 Access Points

📖 Full deployment guide: See DEPLOYMENT_GUIDE.md for detailed instructions

Screenshots

Note: the repository does not include binary screenshot image files. The screenshots/ directory previously referenced image assets that are not present in this repository. If you want to add screenshots for documentation or GitHub Pages, follow the steps in SCREENSHOTS.md to generate and add them, then commit the image files under screenshots/.

If you prefer not to include screenshots in the repo, you can host images externally and reference them from the README instead.

�🔧 Configuration

🔐 Authentication

All endpoints require the x-api-key header:

📝 Add Document to Vector Store

curl -X POST "http://127.0.0.1:8080/vector/add?id=doc1&text=VertexOps%20is%20awesome" \
  -H "x-api-key: supersecret123"

🤖 Deploy a Model

curl -X POST "http://127.0.0.1:8080/models/deploy" \
  -H "Content-Type: application/json" \
  -H "x-api-key: supersecret123" \
  -d '{"model_type": "custom", "config": {"version": "1.0"}}'

🔍 RAG Query

curl -X POST "http://127.0.0.1:8080/rag/query" \
  -H "Content-Type: application/json" \
  -H "x-api-key: supersecret123" \
  -d '{"query": "What is VertexOps?", "top_k": 3}'

📊 Check Metrics

curl http://127.0.0.1:8080/metrics

🐳 Docker Deployment

Build and Run

docker build -t vertexops .
docker run -p 8080:8000 -e API_KEY=supersecret123 vertexops

Docker Compose

docker-compose up -d

🔧 Extension Points

This MVP provides clear extension points for production use:

🧠 Real AI Integration

💾 Production Storage

🔒 Security & Scale

📁 Project Structure

vertexops/
├── 🚀 main.py              # FastAPI application & routes
├── 📋 schemas.py           # Pydantic models
├── 🔐 auth.py              # Authentication logic
├── 🤖 model_service.py     # Model deployment & fine-tuning
├── 🗂️ vector_store.py      # In-memory vector storage
├── 🔍 rag_service.py       # RAG query processing
├── 📊 monitoring.py        # Prometheus metrics
└── 🛠️ utils.py             # Utility functions

🤝 Contributing

1. Fork the repository
2. Create your feature branch (git checkout -b feature/AmazingFeature)
3. Commit your changes (git commit -m 'Add some AmazingFeature')
4. Push to the branch (git push origin feature/AmazingFeature)
5. Open a Pull Request

📄 License

This project is licensed under the MIT License - see the LICENSE file for details.

🙏 Acknowledgments

⭐ If this project helped you, please give it a star!