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AI Fusion Video - Open-source Full-process AI Video Creation Platform, Automated Workflow

Author: AI小集 · Original source: AI工具集

What is AI Fusion Video

AI Fusion Video is an open-source full-processAI video creation platform, based on an Agent architecture, it can achieve automated workflows from script writing to video generation. The platform supports structured script editing, AI automatic storyboard breakdown, multi-engine drawing and video generation, integrates mainstream large models such as OpenAI, Claude, and Gemini, adopts a Java 21 + Spring Boot 3.5 backend and Next.js 16 frontend technology stack, supports one-click Docker deployment, and helps content creators efficiently complete video production.

AI Fusion Video

Main Features of AI Fusion Video

  • Script Management: The platform can create and edit video scripts, supporting structured management by episode/scene.
  • AI Storyboard Generation: AI automatically breaks down scripts into visual storyboards, including scene descriptions and camera language.
  • AI Drawing: Integrates multiple AI drawing engines, one-click generation of storyboard reference images.
  • AI Video Generation: Generates video clips based on storyboard descriptions and reference images.
  • Asset Management: Unified management of image, video and other asset resources within the project.
  • Multi-model Support: Integrates mainstream large models such as OpenAI, Claude, Gemini, Tongyi Qianwen, DeepSeek, and Ollama.

How to Use AI Fusion Video

  • Environment Preparation: Install Docker (recommended method) or configure JDK 21+, Node.js 20+, pnpm 9+, MySQL and Redis environments.
  • Project Acquisition: Executegit clone https://github.com/Stonewuu/ai-fusion-video.gitto clone the repository.
  • Quick Start: Docker users directly rundocker compose up -d, source code developers first start the middlewaredocker compose -f docker-compose-middleware.yml up -d, then start the backend separately./mvnw spring-boot:runand frontendpnpm dev。
  • System Configuration: Accesshttp://localhost:8080(Docker) orhttp://localhost:3000(development mode), configure AI model keys and storage backend on the system settings page.
  • Creation Workflow: Create project → Write script → AI generates storyboard → AI draws reference images → AI generates video clips → Asset export.

Key Information and Usage Requirements of AI Fusion Video

  • Open Source License: MIT License, free for commercial use and secondary development.
  • Hardware Requirements: Requires a Docker-supported runtime environment or a local JDK 21+ runtime environment; sufficient memory is recommended for AI model calls.
  • Dependent Services: MySQL database and Redis cache must be configured; object storage service is optional.
  • API Keys: To use AI features, you need to prepare API keys from service providers such as OpenAI and Claude yourself.
  • Deployment Methods: Supports two modes: Docker Compose one-click deployment and local source code development.

Core Advantages of AI Fusion Video

  • Full-process Automation: Covers the complete workflow from script to finished video, reducing manual intervention steps.
  • Multi-model Compatibility: Not bound to a single AI service provider, supports flexible switching and comparison of mainstream large models.
  • Open Source and Customizable: Open source under MIT License, supports private deployment and deep feature expansion.
  • Visualized Agent Workflow: Visualized Pipeline node display, making the creative process transparent and controllable.
  • Storyboard-driven generation: Using storyboards as the intermediate layer to ensure the video content stays consistent with the script's intent.

Rongguang's project address

  • GitHub repository：https://github.com/Stonewuu/ai-fusion-video

Comparison of Rongguang with similar competing products

Comparison dimension Rongguang (AI Fusion Video) HeyGen Runway Gen-3
Product positioning Open-source agent-driven full-process creation platform Cloud-based AI digital human video generation tool Professional AI video editing and generation platform
Workflow mode Multi-stage Pipeline: script → storyboard → image → video Template selection → digital human driving → video compositing Material upload → AI generation → multi-track post-production editing
Controllability High (fine-grained control at the storyboard level, supports iterative adjustments) Medium (relies on preset templates and digital human avatars) Medium-high (professional tools such as motion brush, green screen, and camera control)
Degree of open source Fully open source (MIT license, supports private deployment) Closed-source SaaS service Closed-source SaaS service
Model support Multi-vendor compatibility (OpenAI/Claude/Gemini/domestic models, etc.) Mainly self-developed models Mainly self-developed Gen-3 series models
Applicable scenarios Full-process management for professional creators, team collaboration Rapid generation of marketing videos, digital human broadcasting Film-grade advertising production, visual effects, artistic short films

Rongguang's application scenarios

  • Short video creation: Quickly transform copywriting scripts into short video content with visuals, suitable for batch production by self-media.
  • Advertising and marketing: Automatically generate multi-version advertising storyboards and video materials based on product descriptions, accelerating creative iteration.
  • Education and training: Automatically break down teaching syllabi into visualized course segments, lowering the threshold for educational video production.
  • Film and television previsualization: Independent producers use AI to quickly generate storyboards and dynamic previsualizations, verifying the feasibility of shooting plans.
  • Animation prototypes: Animation creators use AI storyboards to quickly validate narrative pacing and visual style.