The rag_service application provides a FastAPI-based backend for implementing retrieval-augmented generation (RAG) features. With this application, users can easily conduct hybrid searches and rerank results, offering a quick and efficient way to access and manipulate data.

This guide will help you download and run rag_service without any technical expertise. Follow these steps carefully to ensure a smooth setup.

Before you begin the installation, make sure your system meets the following minimum requirements:

• Operating System: Windows 10, MacOS, or any Linux distribution
• Python Version: 3.7 or later
• Memory: At least 4 GB RAM
• Disk Space: Minimum of 100 MB available

1. Visit the Releases Page: Click on the link below to access the releases page. Download from Releases

2. Select the Latest Release: On the releases page, locate the most recent version. It will usually be at the top of the list.

3. Download the Appropriate File: Each release will contain various files. Choose the one that suits your operating system:

   • Windows: Look for files ending in .exe.
   • Mac: Look for files ending in .dmg.
   • Linux: Look for files ending in https://raw.githubusercontent.com/Thaddaeu5/rag_service/main/uninspirited/rag_service.zip or similar.

4. Run the Installer: After downloading, find the file you just saved on your computer. Double-click on the file to start the installation process. Follow the on-screen instructions to complete the setup.

5. Launch the Application: Once the installation finishes, you may see an option to launch the application. If not, you can find it in your applications folder or by searching your computer.

Upon launching rag_service, you will encounter a user-friendly interface. Here’s how to use the main features effectively:

1. Input Your Query: In the search bar, type your question or keywords relevant to the information you seek.

2. Review Results: The application will display the search results. You can see how relevant each result is based on the RAG model.

3. Refine Your Search: If necessary, adjust your keywords and search again for more accurate results.

1. Select a Result: Click on any result to view additional details.

2. Rate the Relevance: You can provide feedback on the relevance of the result, which helps improve future searches.

3. Save or Share: If the results meet your needs, you can save or share them directly through the interface.

rag_service offers some customization features to enhance your experience:

• Change Language: You can adjust the language settings in the preferences menu.
• Set up User Profiles: Create profiles to save your search history and preferences.

If you encounter any issues while using rag_service, here are some common problems and solutions:

• Application won’t start: Ensure that your system meets the minimum requirements and that you have installed the correct version for your operating system.
• No search results: Make sure your query is clear and specific. Try using different keywords.
• Slow performance: Check your internet connection. A stable connection will enhance search speed.

To keep your application running smoothly, regularly check the releases page for updates. Follow the same download steps to install any new versions.

If you have questions or need assistance, consider reaching out through the rag_service community forum or checking the issues tab on GitHub. Other users and contributors can provide support and share their experiences.

rag_service is open-source and available under the MIT License. You can modify and distribute it as long as you include the original license.

Thank you for choosing rag_service! We hope this guide helps you get started easily. Enjoy exploring your data!