Filmate AI 🎬

Movie finder + social platform app using OpenAI GPT-3.5 Turbo, Groq, and Qdrant.

Features

Text Vectorization & Sentiment Analysis

⚡ Data Cleaning: Uses Pandas for cleaning CSV data that contains 10,000+ movie records released from 1915 to 2024.
⚡ Sentiment Analysis: Assigns sentiment scores and appropriate justifications to all movies using OpenAI GPT-3.5 Turbo and Hugging Face Transformers text classification model.
⚡ Text Vectorization: Vectorizes movie metadata (e.g., titles, director and actor names, and synopsis) using the OpenAI embedding model.

Semantic Search

⚡ Data Storage: Stores vector embeddings and payload in Qdrant Cloud.
⚡ Query Processing: Vectorizes, filters, and generates insights from user queries using Groq (Mixtral 8x7b model).
⚡ Semantic Search: Performs semantic searches based on vectorized user queries and filters.

API & UI Development

⚡ API Development: Serves API endpoints using Flask (Python).
⚡ UI Development: Serves the frontend interface using React (TypeScript, JavaScript, SASS).
⚡ User Authentication: Handle user authentication (login, sign up, reset password) securely with Propelauth.
⚡ Data Management: Stores user activity (movie reviews, followers, likes) and handles data migrations with SQLAlchemy and PostgreSQL.

Setup

This application consists of a Flask backend and a React frontend. Follow these steps to set up your development environment:

0. Add Environment Variables

Create a .env file in the ./app folder and add the following environment variables:

OPENAI_API_KEY=your_openai_api_key
QDRANT_API_KEY=your_qdrant_api_key
QDRANT_URL=your_qdrant_url
GROQ_API_KEY=your_groq_api_key

Ensure the .env file is kept secure and not shared, as it contains sensitive API keys.

1. Set Up Flask Backend

Navigate to the ./app folder:

cd app

Create and activate a virtual environment using Python:

python -m venv venv
source venv/bin/activate  # On Windows, use venv\Scripts\activate

Install the required packages:

pip install -r requirements.txt

2. Set Up React Frontend

Navigate to the ./app/client folder and install npm packages:

cd app/client
npm install

3. Start the App

Start the Flask server:

gunicorn -w 2 -b 0.0.0.0:5000 app:app

Start the React server:

npm start

Access the app in your browser at http://localhost:3000.

4. Build Static Files

To deploy the app, build the frontend static files:

npm run build

5. Deactivate the Virtual Environment

When you are finished, deactivate the virtual environment:

deactivate