Welcome to the linear-agents repository! Here, you can build agents that actually work. This project aims to provide a straightforward framework for creating linear agents that can be integrated into various applications. Whether you're working on AI, automation, or other tech projects, this repository offers the tools you need.
- Easy to Use: The framework is designed for simplicity, allowing you to focus on your project without unnecessary complexity.
- Flexible: Adapt the agents to fit your specific needs, whether for data analysis, task automation, or other applications.
- Open Source: Collaborate with others and contribute to the project. Open-source means everyone can benefit.
To get started with linear-agents, you can download the latest release from our Releases section.
- Visit the link above.
- Download the required files.
- Follow the installation instructions provided in the release notes.
After downloading, follow these steps to install the framework:
- Extract the files: Unzip the downloaded file to your preferred directory.
- Run the installer: Execute the installation script provided in the package.
- Configure your environment: Adjust settings as needed for your project.
Once you have installed the framework, you can start building your agents. Here’s a simple example to illustrate how to create a basic linear agent:
from linear_agents import LinearAgent
# Initialize the agent
agent = LinearAgent(parameters)
# Train the agent
agent.train(training_data)
# Make predictions
predictions = agent.predict(new_data)- Data Analysis Agent: Use the framework to analyze datasets and generate insights.
- Automation Agent: Automate repetitive tasks using simple scripts.
- Simulation Agent: Create simulations to test various scenarios.
We welcome contributions from the community. If you want to contribute, please follow these steps:
- Fork the repository.
- Create a new branch for your feature or fix.
- Make your changes and commit them.
- Push your branch to your forked repository.
- Submit a pull request to the main repository.
We expect all contributors to adhere to our code of conduct. Be respectful and inclusive to all community members.
Comprehensive documentation is available in the docs folder. You can find guides, API references, and examples to help you understand how to use the framework effectively.
The API reference provides detailed information about each class and method in the framework. Here’s a brief overview:
- LinearAgent: The main class for creating linear agents.
- train(): Method to train the agent on given data.
- predict(): Method to make predictions based on new input data.
This project is licensed under the MIT License. See the LICENSE file for more details.
For any questions or feedback, please reach out through the issues section on GitHub or contact me directly.
To keep up with the latest changes and updates, check the Releases section regularly.
Thanks to everyone who has contributed to this project. Your support and input are invaluable.
This repository serves as a platform for building efficient linear agents. With the tools and support available, you can create agents that meet your specific needs. Don't hesitate to explore the framework and contribute to its growth.
