CineGen / README.md
VirtualOasis's picture
readme
37caa62

A newer version of the Gradio SDK is available: 6.1.0

Upgrade
metadata
title: CineGen
emoji: πŸ‘€
colorFrom: pink
colorTo: purple
sdk: gradio
sdk_version: 6.0.1
app_file: app.py
pinned: false
short_description: automate the process of short movie creation
tags:
  - mcp-in-action-track-creative

CineGen AI Director is an AI agent designed to automate the process of short movie creation. It transforms a simple text or image idea into a fully realized video production by handling scriptwriting, storyboard generation, character design, and video synthesis using a multi-model approach.

  • Sponsor Platforms: Uses Google Gemini (story + character prompts) and Hugging Face Inference Client with fal.ai hosting for Wan 2.2 TI2V video renders;
  • Autonomous Agent Flow: StoryGenerator β†’ CharacterDesigner β†’ VideoDirector pipeline runs sequentially inside a single Gradio Blocks app, with MCP-friendly abstractions (StoryGenerator, CharacterDesigner, VideoDirector) designed for tool-call orchestration.
  • Evaluation Notes: Covers reasoning (Gemini JSON storyboard spec), planning (scene/character tables that feed downstream steps), and execution (queued video renders with serialized HF jobs).

Artifacts for Reviewers

  • Social Media Proof: Replace <SOCIAL_LINK_HERE> with your live tweet/thread/LinkedIn post so judges can verify community sharing.
  • Video Recording: Upload a walkthrough of the Gradio agent (screen + narration) and swap <DEMO_VIDEO_LINK> with the shareable link.

πŸš€ Key Features

  • End-to-End Automation: Converts a single sentence idea into a complete short film (approx. 30s-60s runtime).
  • Intelligent Storyboarding: Breaks down concepts into scene-by-scene visual prompts and narrative descriptions.
  • Character Consistency System:
    • Automatically identifies main characters.
    • Generates visual reference sheets (Character Anchors).
    • Allows users to "tag" specific characters in specific scenes to ensure visual consistency in the video generation prompt.
  • Multi-Model Video Generation: Supports multiple state-of-the-art open-source video models via Hugging Face.
    • Robust Fallback System: If the selected video model fails (e.g., server overload), the system automatically tries alternative models until generation succeeds.
  • Interactive Editing:
    • Edit visual prompts manually.
    • Add, Insert, or Delete scenes during production.
    • Regenerate specific clips or character looks.
  • Client-Side Video Merging: Combines individual generated clips into a single continuous movie file directly in the browser without requiring a backend video processing server.

πŸ€– AI Models & API Usage

The application orchestrates two primary AI services:

1. Google Gemini API (@google/genai)

Used for the "Brain" and "Art Department" of the application.

  • Logic & Scripting: gemini-2.5-flash
    • Role: Analyzes the user's idea, generates the title, creates character profiles, and writes the JSON-structured storyboard with visual prompts.
    • Technique: Uses Structured Output (JSON Schema) to ensure the app can parse the story data reliably.
  • Character Design: gemini-2.5-flash-image
    • Role: Generates static reference images for characters based on the script's descriptions.
    • Role: Acts as the visual anchor for the user to verify character appearance before video generation.

2. Hugging Face Inference API (@huggingface/inference)

Used for the "Production/Camera" department.

  • Video Generation Models:
    • Wan 2.1 (Wan-AI): Wan-AI/Wan2.1-T2V-14B (Primary/Default)
    • LTX Video (Lightricks): Lightricks/LTX-Video-0.9.7-distilled
    • Hunyuan Video 1.5: tencent/HunyuanVideo-1.5
    • CogVideoX: THUDM/CogVideoX-5b
  • Provider: Defaults to fal-ai via Hugging Face Inference for high-performance GPU access.