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FileJIT

Overview

The FileJIT project is a file search and retrieval system that leverages AI-powered embeddings and similarity search to classify/organize files into a file directory, as well as find the most relevant files based on conversational prompting.

This project is designed to handle human-readable files and provide ranked suggestions for the closest matches based on a user-provided query.

This repository holds the most up-to-date version of the software initially developed by myself, as well as the team I was on for the 8vc Hackathon at Duke.


Features

  • File Embedding Generation: Converts file contents into dense vector embeddings using a pre-trained SentenceTransformer model.
  • Similarity Search: Uses FAISS to perform fast and efficient similarity searches for the closest file matches.
  • Top-N Results: Returns the top 3 most relevant files for a given query.
  • Dynamic File System Scanning: Automatically scans a specified directory for files and processes their contents.
  • Persistence: Supports saving and loading FAISS indices for reuse without regenerating embeddings.

Technologies Used

  • Tauri / Svelte
  • Python 3.12
  • FAISS: For similarity search and clustering.
  • SentenceTransformers: For generating embeddings from text.
  • OS Module: For file system traversal.
  • Requests: For potential API integrations (e.g., classification or external services).

Installation

  1. Clone the Repository:
   git clone https://github.com/your-repo/8vcHackathon.git
   cd 8vcHackathon
  1. Install Dependencies: Ensure you have Python 3.12 installed. Then, install the required Python packages:
  pip install -r requirements.txt

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