- Introduction
- Key Features 🚀
- Platform Architecture 🏗️
- 🚨 Setup Instructions
- 📚 Available Endpoints
- 🛠️ Example Usage
- 🔧 Technologies Used
- License 📜
- 💬 Support
Welcome to HIVEAI! 🧠✨ A powerful platform designed to manage and orchestrate multiple AI agents working together collaboratively on complex tasks. Think of it as a smart hive where agents combine their intelligence to achieve shared goals! 🤖💡
With HIVEAI, you can:
- Create and manage AI agents 🛠️
- Launch collaborative projects where agents work together 🤝
- Track progress and monitor the status of your agents in real-time 📊
- Agent Management: Create AI agents with customizable capabilities 🤖
- Collaboration Projects: Define projects where agents collaborate to achieve common goals 🧑🤝🧑
- Agent Assignment: Assign agents to specific tasks within collaboration projects 🎯
- Collaboration Monitoring: Track progress and performance of agents within each project 📈
- Flask: Lightweight Python web framework for creating the API 🌐
- SQLAlchemy: ORM for managing and accessing the database 🗄️
- SQLite: A simple and effective local database 🛠️
- Python 3.10 or higher 🐍
- A virtual environment (optional but recommended) 🌱
-
Clone this repository:
git clone hhttps://github.com/hiveagent/hiveagentai.git cd hiveagentai -
Create a virtual environment (optional but recommended):
python -m venv venv source venv/bin/activate # On Windows: venv\Scripts\activate
-
Install the required dependencies:
pip install -r requirements.txt
-
Start the Flask development server:
python app.py
-
The API will be running locally on: http://127.0.0.1:5000/ 🌍
-
Create an Agent:
POST /agents- Create a new AI agent with a name and capabilities.
- Example:
{ "name": "Agent A", "capabilities": "Data Analysis, Machine Learning" } -
List all Agents:
GET /agents- Retrieve a list of all created agents.
-
Create a Collaboration:
POST /multi-agent/create- Create a new collaboration project where agents can join and work together.
- Example:
{ "name": "Project Alpha", "description": "Data analysis and machine learning collaboration." } -
Assign Agents to a Collaboration:
POST /multi-agent/<collaboration_id>/assign- Assign agents to a specific collaboration project.
- Example:
{ "agent_ids": [1, 2] } -
View Assigned Agents:
GET /multi-agent/<collaboration_id>/agents- Get a list of agents assigned to a specific collaboration.
-
Update Agent Status:
PUT /agents/<agent_id>/status- Update an agent's current status (e.g., idle, active, error).
- Example:
{ "status": "active" } -
Get Collaboration Progress:
GET /multi-agent/<collaboration_id>/progress- Retrieve the progress and status of all agents within a collaboration.
-
Create an Agent:
curl -X POST http://127.0.0.1:5000/agents -H "Content-Type: application/json" -d '{"name": "Agent A", "capabilities": "Data Processing, Image Recognition"}'
-
Create a Collaboration:
curl -X POST http://127.0.0.1:5000/multi-agent/create -H "Content-Type: application/json" -d '{"name": "Project Omega", "description": "Collaboration on data analysis."}'
-
Assign Agents to Collaboration:
curl -X POST http://127.0.0.1:5000/multi-agent/1/assign -H "Content-Type: application/json" -d '{"agent_ids": [1, 2]}'
-
Check Collaboration Progress:
curl http://127.0.0.1:5000/multi-agent/1/progress
- Flask: Lightweight Python web framework for building APIs 🌍
- Flask-SQLAlchemy: ORM to easily manage database records 📄
- SQLite: Lightweight database for persistent storage 🗄️
- Python 3.7+: The programming language powering the backend 🐍
This project is licensed under the MIT License. See the LICENSE file for more details.
For issues, bugs, or suggestions, feel free to open an issue or contribute via a pull request on the GitHub repository.
Let's create smarter AI together! 🤖💡✨