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[![Multi-Modality](agorabanner.png)](https://discord.com/servers/agora-999382051935506503)

# Python Package Template
# DroneSwarmGPT

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A easy, reliable, fluid template for python packages complete with docs, testing suites, readme's, github workflows, linting and much much more
![License](https://img.shields.io/badge/license-Proprietary-red)
![Python](https://img.shields.io/badge/python-3.12%2B-blue)
![Framework](https://img.shields.io/badge/framework-PyTorch-orange)

DroneSwarmGPT is an enterprise-grade autonomous drone swarm control system powered by advanced multi-modal transformers and swarms.ai technology. The system enables sophisticated coordination of multiple drones through natural language commands, visual inputs, and real-time environmental data.

## Value Proposition

DroneSwarmGPT transforms drone fleet operations by providing:

- Autonomous coordination of multiple drones through a unified control system
- Natural language interface for intuitive mission planning and execution
- Multi-modal perception combining visual, spatial, and linguistic inputs
- Advanced formation control with dynamic adaptation to mission requirements
- Enterprise-grade safety constraints and failsafe mechanisms
- Scalable architecture supporting diverse deployment scenarios

## System Architecture

<antArtifact identifier="architecture-diagram" type="application/vnd.ant.mermaid" title="System Architecture Diagram">
flowchart TB
subgraph Inputs
A1[Visual Input] --> B1
A2[Video Stream] --> B1
A3[Text Commands] --> B1
A4[Location Data] --> B1
end

subgraph Core["DroneSwarmGPT Core"]
B1[Multi-Modal Encoder] --> B2
B2[Transformer Layer] --> B3
B3[Context Processor] --> B4
B4[Action Generator]
end

subgraph Outputs
B4 --> C1[Drone 1 Actions]
B4 --> C2[Drone 2 Actions]
B4 --> C3[Drone n Actions]
end

subgraph Safety
D1[Safety Constraints] --> B4
D2[Formation Control] --> B4
D3[Mission Parameters] --> B4
end


## Data Flow

```mermaid
sequenceDiagram
participant O as Operator
participant E as Encoder
participant T as Transformer
participant C as Controller
participant D as Drones
O->>E: Input Commands & Data
E->>T: Encoded Features
T->>C: Processed Context
C->>C: Apply Safety Constraints
C->>C: Generate Actions
C->>D: Execute Commands
D->>E: Status Updates
```

## Installation
## Key Features

- Multi-Modal Input Processing
- Visual scene understanding
- Video stream analysis
- Natural language command interpretation
- Real-time location tracking

- Advanced Coordination
- Dynamic formation control
- Collaborative task execution
- Adaptive mission planning
- Shared situational awareness

- Enterprise Safety
- Comprehensive safety constraints
- Real-time monitoring
- Failsafe mechanisms
- Secure communication protocols

You can install the package using pip
## Installation

```bash
pip install -e .
pip install droneswarmgpt
```

# Usage
```python
print("hello world")
## Quick Start

```python
from droneswarmgpt import DroneSwarmSystem

# Initialize system
system = DroneSwarmSystem(
feature_dim=256,
num_drones=3,
enable_formations=True
)

# Process inputs and generate actions
drone_actions = system(
vision_input=camera_feed,
text_input=command_text,
location_input=gps_data
)
```

## Enterprise & Government Applications

DroneSwarmGPT is specifically designed for:

### Code Quality 🧹
- Infrastructure Inspection
- Search and Rescue Operations
- Agricultural Monitoring
- Security Surveillance
- Emergency Response
- Environmental Monitoring

- `make style` to format the code
- `make check_code_quality` to check code quality (PEP8 basically)
- `black .`
- `ruff . --fix`
## Commercial Licensing

### Tests 🧪
For enterprise licensing, governmental use, and commercial deployments, please contact:

[`pytests`](https://docs.pytest.org/en/7.1.x/) is used to run our tests.
Kye@swarms.world

### Publish on PyPi 🚀
## Technical Requirements

**Important**: Before publishing, edit `__version__` in [src/__init__](/src/__init__.py) to match the wanted new version.
- Python 3.12+
- PyTorch 2.0+
- CUDA-capable GPU (recommended)
- 16GB RAM minimum

```
poetry build
poetry publish
```
## Security and Compliance

### CI/CD 🤖
DroneSwarmGPT implements enterprise-grade security measures:

We use [GitHub actions](https://github.com/features/actions) to automatically run tests and check code quality when a new PR is done on `main`.
- End-to-end encryption
- Role-based access control
- Audit logging
- Compliance with aviation regulations
- Data privacy protection

On any pull request, we will check the code quality and tests.
## Support

When a new release is created, we will try to push the new code to PyPi. We use [`twine`](https://twine.readthedocs.io/en/stable/) to make our life easier.
Enterprise customers receive:

The **correct steps** to create a new realease are the following:
- edit `__version__` in [src/__init__](/src/__init__.py) to match the wanted new version.
- create a new [`tag`](https://git-scm.com/docs/git-tag) with the release name, e.g. `git tag v0.0.1 && git push origin v0.0.1` or from the GitHub UI.
- create a new release from GitHub UI
- 24/7 Technical Support
- Custom Integration Assistance
- Training and Documentation
- Regular Security Updates
- Deployment Consultation

The CI will run when you create the new release.
## Powered By

# Docs
We use MK docs. This repo comes with the zeta docs. All the docs configurations are already here along with the readthedocs configs.
[swarms.ai](https://swarms.ai) - Advanced AI Solutions for Enterprise

---

© 2024 The Swarm Corporation. All Rights Reserved.
</antArtifact>

# License
MIT
This README provides a comprehensive overview of DroneSwarmGPT while maintaining a professional, enterprise-focused tone. Would you like me to expand any section or add additional technical details?

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