Reelit - Reddit Story Video Generator

Automate the creation of short-form videos (TikTok, YouTube Shorts, Instagram Reels) by combining narrated Reddit stories with background footage and synchronized captions, all through a simple web interface.

Features

• Web UI: Easy-to-use interface built with Flask and Tailwind CSS for selecting subreddits, background videos, and initiating generation.
• Multi-Platform Compatibility: Outputs 9:16 vertical videos.
• Reddit Integration: Scrapes stories using PRAW.
• AI Narration: Converts text (with 'AITA' and age/gender substitutions) to speech using gTTS.
• Accurate Captions: Uses OpenAI Whisper to generate word-level timestamps for precise caption synchronization.
• Dynamic Title Card: Draws the post title onto a provided template image, adapting font size.
• Background Options: Choose from multiple background videos (Minecraft, GTA, Subway Surfer).
• Layered Audio: Mixes narration with adjustable background music volume.
• Automated Video Creation: Combines background video, title card, narration, music, and timed captions using MoviePy.
• Real-time Progress: Monitor the generation process with a detailed progress bar and logs in the web UI.
• Direct Download & Replay: Download the generated video or watch it directly in the browser on completion.
• Git LFS: Handles large background video files efficiently.

How It Works

1. Frontend Interaction: User selects subreddit, background video, and music volume via the web interface served by Flask.
2. Trigger: Submitting the form sends a POST request to the /generate endpoint.
3. Backend Pipeline (run_pipeline in main.py): a. Story Selection: Fetches a random, popular story from the chosen subreddit. b. Narration Generation: Cleans text (substitutions) and generates MP3 audio using gTTS. c. Timestamp Generation: Uses Whisper to get word timestamps from the narration. d. Title Card Creation: Dynamically draws the title on title_template.png. e. Caption Image Generation: Creates transparent PNGs for caption chunks based on timestamps. f. Video Assembly (create_video in video_creator.py): Combines chosen background video (via Git LFS), music, title card, and captions using MoviePy.
4. Progress Tracking: The Flask app captures logs and updates progress status via a queue.
5. Frontend Polling: The web UI periodically polls the /status endpoint to update the progress bar, logs, and current step.
6. Result Display: Upon completion, the UI shows a success message, an embedded video player, and download/retry buttons.

Technologies Behind the Magic

• Python: Core backend language.
  • Flask: Web framework and API.
  • PRAW: Reddit API integration.
  • gTTS: Text-to-Speech generation.
  • openai-whisper: Audio transcription and word-level timestamp generation.
  • Pillow (PIL Fork): Image manipulation (drawing title, creating captions).
  • MoviePy: Video and audio editing/compositing.
  • python-dotenv: Environment variable management.
• Frontend:
  • HTML: Structure.
  • Tailwind CSS: Styling.
  • JavaScript: Interactivity, API calls, progress updates.
• Git LFS: For managing large background video files.
• FFmpeg: Essential backend for MoviePy and Whisper (must be installed separately).

Setup

1. Clone the repository:

   git clone <repository-url>
   cd <repository-directory>

2. Install Git LFS:
   • Download and install Git LFS from git-lfs.github.com or use a package manager.
   • Initialize LFS for your user account (run once): git lfs install
   • Pull the large files tracked by LFS: git lfs pull
3. Create & Activate Virtual Environment:

   python -m venv venv
   # Windows: .\venv\Scripts\activate
   # macOS/Linux: source venv/bin/activate

4. Install FFmpeg:
   • Download FFmpeg from ffmpeg.org.
   • Ensure the ffmpeg executable is in your system's PATH.
5. Install Python Dependencies:

   pip install -r requirements.txt
   # Note: Whisper installation might take time as it includes PyTorch.

6. Set up Reddit API Credentials:
   • Create a .env file in the root directory (where README.md is).
   • Add your credentials:

   REDDIT_CLIENT_ID='your_client_id'
   REDDIT_CLIENT_SECRET='your_client_secret'
   REDDIT_USER_AGENT='your_user_agent' # e.g., 'ReelitApp by u/your_username'

7. Prepare Assets (Verify):
   • The assets/ directory should contain:
     • background_gta.webm (via Git LFS)
     • background_minecraft.webm (via Git LFS)
     • background_subway_surfer.webm (via Git LFS)
     • background_music.mp3 (Your background music)
     • title_template.png (Your title card template)
     • Inter-Bold.ttf (Or your desired font file - update path in src/video_creator.py if different)

Usage

1. Start the Server:
   • Navigate to the src directory: cd src
   • Run the Flask app: python app.py
   • Keep this terminal running. It will show backend logs.
2. Open the Web UI:
   • Open your web browser and go to http://127.0.0.1:5000 (or the address shown in the terminal).
3. Generate Video:
   • Enter a subreddit name.
   • Select a background video.
   • Adjust the music volume if desired.
   • Click "Generate Video".
4. Monitor & Retrieve:
   • Watch the progress bar and logs directly in the web UI.
   • The first run might take longer as it downloads the Whisper model (tiny.en by default).
   • Once complete, the video player will appear.
   • Watch the video, download it, or generate another.
   • Final videos are also saved in the output/ directory.

Customization

• Background Videos: Add more .webm files to assets/, update the BACKGROUND_VIDEOS dictionary in src/app.py, and potentially track them with git lfs track "*.webm".
• Title Card Text: Adjust font size range, color, boundary box in draw_title_on_template within src/video_creator.py.
• Caption Style: Modify font, size, colors, outline in create_subtitle_image within src/video_creator.py.
• Caption Grouping: Adjust MAX_WORDS_PER_CAPTION or MIN_GAP_BETWEEN_CAPTIONS in create_video within src/video_creator.py.
• Whisper Model: Modify model_name in get_word_timestamps call within src/main.py (e.g., to "base.en" for potentially better accuracy but slower speed).
• Progress Steps/Weights: Modify the PIPELINE_STEPS dictionary in src/app.py and update corresponding UI elements/logic if needed.
• UI Styling: Modify src/templates/index.html (Tailwind CSS classes) and src/static/js/script.js.