AIxHunter / FileWizardAI

Add AI capabilities to your file system using Ollama, Groq, OpenAi and other's api

FileWizardAI

Description

FileWizardAI is a Python/Angular project designed to automatically organize your files into a well-structured directory hierarchy and rename them according to their content. This tool is ideal for anyone looking to declutter their digital workspace by sorting files into appropriate folders and providing descriptive names, making it easier to manage and locate files. Additionally, it allows you to input a text prompt and instantly searches for files that are related to your query, providing you with the most relevant files based on the content you provide.

The app also features a caching system to minimize API calls, ensuring that only new or modified files are processed.

Example:

Before

/home/user
 ├── Downloads
 │   ├── 6.1 Course Curriculum v2.pdf
 │   └── trip_paris.txt
 │   └── 8d71473c-533f-4ba3-9bce-55d3d9a6662a.jpg
 │   └── Screenshot_from_2024-06-10_21-39-24.png

After

/home/user/Downloads
 ├─ docs
 │  └─ certifications
 │     └─ databricks
 │        └─ data_engineer_associate
 │           └─ curriculum_v2.pdf
 ├─ Personal Photos
 │  └─ 2024
 │     └─ 03
 │        └─ 01
 │           └─ person_in_black_shirt.jpg
 ├─ finance-docs
 │  └─ trip-expenses
 │     └─ paris
 │        └─ trip-justification.txt
 └─ project Assets
    └─ instructions_screenshot.png

Video tutorial:

Table of Contents

• Installation
• Usage
• Run in Development Mode
• Credits
• License
• Technical architecture

Installation

Make sure you have Python installed on your machine.

First, clone the repository:

git clone https://github.com/AIxHunter/FileWizardAI.git

Navigate to the backend folder and update your .env file according to the documentation. Then, install the required packages by running ( preferably in a virtual environment like venv or conda):

cd backend
pip install -r requirements.txt

Usage

Run the backend server

cd backend
uvicorn app.server:app --host localhost --port 8000

App will be running under: http://localhost:8000/

Run in Development Mode

If you are a developper and you want to modify the frontend, you can run the frontend and backend separately, here is how to do it: Install Node.js https://nodejs.org/

install Angular CLI:

npm install -g @angular/cli

Run frontend:

cd frontend
npm install
ng serve

The frontend will be available at http://localhost:4200.

to package the frontend run:

ng build --base-href static/

Run backend:

Update your .env file with the desired API settings (check the documentation), then:

cd backend
uvicorn app.server:app --host localhost --port 8000 --reload

Technical architecture

1. Send request from Angular frontend (ex, organize files)
2. Backend receives request through a REST API of FastAPI.
3. Check SQLite if files has already been processed (cached files).
4. Return cached summary if file was already processed.
5. If the file has not been processed before, send new file to LLM for summarization.
6. Cache summary in SQLite.
7. Return summary to Angular frontend.
8. Display summary to user and perform actions if need it.

License

This project is licensed under the MIT License.