🌟 rag-nodejs - Simple Backend for Smart Searches

🚀 Getting Started

Welcome to rag-nodejs! This application lets you use an easy Node.js backend for powerful document processing and smart searches. Ideal for anyone looking to enhance their data retrieval with the latest AI technology.

📥 Download the App

🖥 System Requirements

Before you get started, please ensure your system meets the following requirements:

• Operating System: Windows 10 or later, macOS, or a popular Linux distribution.
• Node.js Version: 14 or later.
• Memory: At least 4GB of RAM.
• Storage: 100MB free disk space.

📋 Features

rag-nodejs includes several features to help you manage and search your documents effectively:

• Document Embedding: Convert your documents into meaningful representations.
• Vector Storage: Store and manage vectors efficiently for fast retrieval.
• Semantic Search: Find documents based on their meaning, not just keywords.
• API Endpoints: Easy to use endpoints for seamless integration with your applications.

🔄 How to Download & Install

1. Visit the Releases Page:

   Click the link below to go to the Releases page, where you can get the latest version of rag-nodejs.

   Download Here

2. Select the Latest Version:

   On the Releases page, look for the latest version of rag-nodejs. You’ll see a list of files available for download.

3. Download the Application:

   Click on the file name to start the download. If you’re on a Windows machine, you will likely download a .exe file. For macOS or Linux, it might be a .tar.gz or similar file.

4. Extract Files (if necessary):

   • For .tar.gz files: Right-click the downloaded file and select "Extract All" or use your file manager's extraction tool.
   • For .zip files: Double-click the file or right-click and select "Extract All."

5. Run the Application:

   • For Windows: Double-click on the downloaded .exe file to run the app.
   • For macOS or Linux: Open your terminal, navigate to the extracted folder, and run the application using the command node app.js.

6. Access the API:

   Once the application is running, open your web browser and enter http://localhost:3000 to access the API endpoints. You can now start embedding documents and running searches.

⚙️ Usage Instructions

Here are a few basic commands that will help you get started with rag-nodejs:

• Embedding Documents:

  To embed a document, send a POST request to http://localhost:3000/embed with the document content in the body. You can use tools like Postman or curl for this.

• Searching Documents:

  To perform a search, send a GET request to http://localhost:3000/search?query=your_search_term. Replace your_search_term with the term you want to search for.

📚 Resources

For a deeper understanding of the technology behind rag-nodejs, you might find these resources useful:

• Node.js Documentation
• Hugging Face Transformers
• ChromaDB Documentation

🌐 Community & Support

If you have any questions or need help, feel free to reach out. Join our community discussions on GitHub or find support on the forums related to Node.js and AI technologies.

📞 Contact

For further inquiries or support, please contact [your_email@example.com].

🗒 License

This project is licensed under the MIT License. See the LICENSE file for more information.

🎉 Acknowledgments

Thank you for using rag-nodejs. We appreciate your support and look forward to hearing your feedback. Happy searching!