https://github.com/skyflo-ai/api
The backend server for Cloud AI Agents by Skyflo.ai.
https://github.com/skyflo-ai/api
django flower langchain python
Last synced: 7 months ago
JSON representation
The backend server for Cloud AI Agents by Skyflo.ai.
- Host: GitHub
- URL: https://github.com/skyflo-ai/api
- Owner: skyflo-ai
- License: apache-2.0
- Created: 2025-03-02T12:44:59.000Z (8 months ago)
- Default Branch: main
- Last Pushed: 2025-03-02T13:21:13.000Z (8 months ago)
- Last Synced: 2025-03-02T14:25:49.343Z (8 months ago)
- Topics: django, flower, langchain, python
- Homepage: https://skyflo.ai
- Size: 351 KB
- Stars: 1
- Watchers: 0
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
README
# API
[](https://skyflo.ai)
[](https://discord.gg/kCFNavMund)
[](https://x.com/skyflo_ai)
[](https://www.youtube.com/@SkyfloAI)
[](LICENSE)
## Backend Server for AI-powered Cloud Agents
The Skyflo API is the central backend service for our platform, enabling secure communication between AI agents and cloud resources. It provides a robust set of RESTful endpoints for agent authentication, resource management, and real-time data processing.
## Key Features
- **Secure Agent Authentication**: JWT-based auth system with short-lived tokens and rotation
- **Webhook Infrastructure**: Reliable endpoints for cloud resource data ingestion
- **Resource Management**: Comprehensive API for cloud resource CRUD operations
- **Real-time Event Processing**: Efficient handling of continuous resource updates
- **Scalable Architecture**: Designed for high throughput and low latency
## Architecture
The API consists of several core components:
- **Authentication Layer**: Secure token management and verification
- **Resource API**: Endpoints for cloud resource management
- **Webhook Handlers**: Processing of real-time resource updates
- **Agent Management**: Provisioning and configuration of cloud agents
- **Integration Layer**: Connections to engine and knowledge store
## Tech Stack
- **Core**: Python, Django
- **Task Queue**: Celery, Flower
- **AI/ML**: Langchain
- **Databases**: PostgreSQL, Neo4j
- **Cache/Messaging**: Redis
- **Monitoring**: Prometheus, Grafana
## Getting Started
### Prerequisites
- Python 3.9+
- Docker and Docker Compose
- PostgreSQL 14+
- Redis 6+
### Local Development Setup
1. Clone the repository:
```bash
git clone https://github.com/skyflo-ai/api.git
cd api
```
2. Create and activate virtual environment:
```bash
python -m venv venv
source venv/bin/activate # On Windows: .\venv\Scripts\activate
```
3. Install dependencies:
```bash
pip install -r requirements.txt
```
4. Set up environment variables:
```bash
cp .env.example .env
# Edit .env with your configuration
```
5. Start required services:
```bash
docker-compose up -d
```
6. Run migrations:
```bash
python manage.py migrate
```
7. Start development server:
```bash
python manage.py runserver
```
## API Documentation
### Base URL
```
https://api.skyflo.ai/v1
```
### Core Endpoints
1. **Agent Authentication**
- `POST /agents/auth-key` - Creates authentication for new agent installations
2. **Agent Operations**
- `POST /agents/{agent_id}/alive` - Agent status and initial configuration
3. **Crawl Webhooks**
- `POST /webhooks/{provider}/{agent_id}/crawl-complete` - Initial scan results
- `POST /webhooks/{provider}/{agent_id}/continuous-crawl` - Real-time updates
For comprehensive API documentation, see our [API Reference](https://github.com/skyflo-ai/skyflo/blob/main/docs/api.md).
## Security
The API implements multiple layers of security:
- JWT-based authentication with short-lived tokens and 30-day rotation
- Rate limiting and payload validation
- Comprehensive logging and audit trails
- TLS enforcement and secure header policies
## Contributing
We welcome contributions! Please see our [Contributing Guide](CONTRIBUTING.md) for details.
### Development Process
1. Fork the repository
2. Create your feature branch (`git checkout -b feature/amazing-feature`)
3. Commit your changes (`git commit -m 'Add amazing feature'`)
4. Push to the branch (`git push origin feature/amazing-feature`)
5. Open a Pull Request
## License
This project is licensed under the Business Source License 1.1 - see the [LICENSE](LICENSE) file for details.
## Community
- [Discord](https://discord.gg/kCFNavMund)
- [Twitter/X](https://x.com/skyflo_ai)
- [YouTube](https://www.youtube.com/@SkyfloAI)
- [GitHub Discussions](https://github.com/skyflo-ai/skyflo/discussions)
## Support
- Documentation: [docs.skyflo.ai](https://docs.skyflo.ai)
- Issues: [GitHub Issues](https://github.com/skyflo-ai/api/issues)
- Enterprise Support: [enterprise@skyflo.ai](mailto:enterprise@skyflo.ai)