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Posted on Mar 15

Open Source Project of the Day (Part 17): ViMax - Video Generation Framework, All-in-One Director, Screenwriter, and Producer

#opensource #ai #videogeneration #vimax

Introduction

"What if AI could work like a real film production team?"

This is Part 17 of the "Open Source Project of the Day" series. Today we explore ViMax (GitHub).

In the AI video generation space, most tools face three core challenges: they can only generate short clips, characters and scenes are inconsistent across frames, and they lack complete narrative structure (scripts, audio, story depth). ViMax proposes a revolutionary solution: integrating director, screenwriter, producer, and video generator into a single system, achieving end-to-end automated generation from idea to complete video through a multi-agent system. Whether it's a simple creative concept, a complete novel chapter, or a film script, ViMax can intelligently handle script generation, storyboard design, character creation, and final video generation.

Why this project?

🎬 Full-pipeline automation: From idea to video, one-click generation of complete narrative videos
🤖 Multi-agent collaboration: Director, screenwriter, producer, and video generator working together
📝 Intelligent long-script generation: RAG-based long script design engine supporting novel-length content
🎨 Expressive storyboarding: Creates professional-grade storyboards using cinematic language
🎥 Multi-camera simulation: Simulates multi-angle shooting for an immersive viewing experience
✅ Consistency guarantee: Intelligent reference image selection and consistency checks to ensure stable characters and scenes
⚡ Efficient parallel processing: Parallel processing of multiple shots in the same scene for dramatically improved efficiency

What You'll Learn

ViMax's multi-agent architecture and design philosophy
The Idea2Video and Script2Video generation modes
How to configure and use ViMax to generate videos
Implementation of long-script generation and storyboard design
Consistency control and reference image selection mechanisms
Comparative analysis with other video generation tools
Real-world application scenarios and best practices

Prerequisites

Basic understanding of AI video generation
Familiarity with multi-agent system concepts
Python programming knowledge (optional, helpful for understanding the implementation)
Basic understanding of film production processes (optional)

Project Background

Project Introduction

ViMax is a multi-agent video generation framework that achieves end-to-end automated generation from idea to complete video. It integrates the roles of director, screenwriter, producer, and video generator into a single intelligent system — automatically handling script generation, storyboard design, character creation, scene planning, and final video generation through multi-agent collaboration. ViMax not only solves the consistency problems of traditional video generation tools, but also provides complete narrative structure and professional-grade video production capabilities.

Core problems the project solves:

Traditional AI video tools can only generate a few seconds of footage
Characters and scenes are inconsistent across frames, lacking continuity
Lack of complete narrative structure (scripts, audio, story depth)
Cannot handle long-form content (e.g., novel chapters)
Video generation requires significant manual intervention
Lack of professional-grade filmmaking capabilities (storyboards, shot design, etc.)

Target user groups:

Content creators and video producers
Creators who need to quickly generate narrative videos
Developers who want to convert text content into video
Researchers interested in multi-agent systems
Institutions that need to batch generate video content

Author/Team Introduction

Team: HKUDS (Hong Kong University Data Science)

Background: Hong Kong University Data Science team, focused on AI video generation and multi-agent systems research
Project creation date: 2025 (an actively maintained project based on GitHub activity)
Philosophy: Make AI a complete creative force, enabling full-pipeline automation from idea to video
Tech stack: Python, multi-agent systems, RAG, visual language models

Project Stats

⭐ GitHub Stars: 2.3k+ (rapidly and continuously growing)
🍴 Forks: 420+
📦 Version: Continuously updated (325+ commits)
📄 License: MIT (fully open source, free to use)
🌐 Project address: GitHub
💬 Community: Active GitHub Issues, 18 open Issues, 5 Pull Requests
👥 Contributors: 8 contributors with active community participation

Project development history:

2025: Project created, core functionality implemented
Continuous iteration: New features and optimizations added
Community growth: Reached 2.3k+ Stars with widespread attention
Ongoing maintenance: Project remains active with continuous community contributions

Main Features

Core Purpose

ViMax's core purpose is to achieve end-to-end automated generation from idea to complete video through a multi-agent system, with main features including:

Idea2Video: Generate complete videos from simple ideas, automatically handling scripts, storyboards, characters, and video generation
Script2Video: Generate videos from detailed scripts, supporting professional film script format
Intelligent long-script generation: RAG-based long script design engine supporting novel-level content analysis
Expressive storyboard design: Creates professional-grade storyboards using cinematic language to establish narrative rhythm
Multi-camera simulation: Simulates multi-angle shooting for an immersive viewing experience
Intelligent reference image selection: Automatically selects reference images to ensure consistency of multi-character and environmental elements
Automated consistency checking: Selects the most consistent images through MLLM/VLM, mimicking human creator workflow
Efficient parallel processing: Parallel processing of multiple shots in the same scene for dramatically improved efficiency

Use Cases

ViMax is suitable for a variety of video generation scenarios:

Content creation
- Quickly convert creative ideas into videos
- Convert novel chapters or stories into videos
- Create trailers, short films, and other narrative content
Automated video production
- Batch generate video content
- Automatically convert text content into video
- Quickly produce marketing videos, educational videos, etc.
Personalized video
- Create personalized custom videos (AutoCameo feature)
- Integrate user photos into stories
- Create interactive video content
Professional video production
- Supports professional film script format
- Creates film-quality video output
- Implements complete filmmaking workflows

Quick Start

Installation

ViMax uses uv for environment management:

# 1. Install uv (if not already installed)
# See: https://docs.astral.sh/uv/getting-started/installation/

# 2. Clone the repository
git clone https://github.com/HKUDS/ViMax.git
cd ViMax

# 3. Install dependencies
uv sync

System requirements:

OS: Linux, Windows
Python 3.x
uv package manager

Configure API Keys

ViMax requires configuring three APIs: a chat model, an image generator, and a video generator.

Idea2Video configuration (configs/idea2video.yaml):

chat_model:
  init_args:
    model: google/gemini-2.5-flash-lite-preview-09-2025
    model_provider: openai
    api_key: <YOUR_API_KEY>
    base_url: https://openrouter.ai/api/v1

image_generator:
  class_path: tools.ImageGeneratorNanobananaGoogleAPI
  init_args:
    api_key: <YOUR_API_KEY>

video_generator:
  class_path: tools.VideoGeneratorVeoGoogleAPI
  init_args:
    api_key: <YOUR_API_KEY>

working_dir: .working_dir/idea2video

Script2Video configuration (configs/script2video.yaml):

# Similar configuration structure
chat_model:
  # ... configure chat model

image_generator:
  # ... configure image generator

video_generator:
  # ... configure video generator

working_dir: .working_dir/script2video

Simplest Usage Examples

Idea2Video mode:

# main_idea2video.py
idea = """
What would happen if a cat and a dog were best friends and they met a new cat?
"""

user_requirement = """
For children, no more than 3 scenes.
"""

style = "Cartoon"

# Run generation
# python main_idea2video.py

Script2Video mode:

# main_script2video.py
script = """
EXT. SCHOOL GYM - DAY
A group of students are practicing basketball in a gym. The gym is large and open, with a basketball hoop at one end and a large audience at the other. John (18, male, tall, athletic) is the star player, practicing dribbling and shooting. Jane (17, female, short, athletic) is the assistant coach, helping John practice. Other students are watching and cheering for John.
John: (dribbling) I'm going to score!
Jane: (smiling) Nice job, John!
John: (shoots) Yes!
...
"""

user_requirement = """
Fast-paced, no more than 20 shots.
"""

style = "Animate Style"

# Run generation
# python main_script2video.py

Common Command Examples

# Idea2Video mode
python main_idea2video.py

# Script2Video mode
python main_script2video.py

# View generated results
# Results are saved in the working_dir directory
ls .working_dir/idea2video/
ls .working_dir/script2video/

Core Features

ViMax's core features include:

Idea2Video mode
- Generate complete videos from simple ideas
- Automatically handles script generation, storyboard design, character creation
- Skips technical complexity, focusing on creativity
Script2Video mode
- Generate videos from detailed scripts
- Supports professional film script format
- Supports any narrative content (trailers, short stories, novel chapters, etc.)
Intelligent long-script generation
- RAG-based long script design engine
- Intelligently analyzes long-form, novel-level stories
- Automatically segments into multi-scene script format
- Ensures accurate preservation of key plot points and character dialogue
Expressive storyboard design
- Creates storyboards based on cinematic language
- Designed based on user requirements and target audience
- Establishes narrative rhythm to guide subsequent video generation
Multi-camera simulation
- Simulates multiple camera angles
- Maintains consistent character positions and backgrounds within the same scene
- Provides diverse viewing angles
Intelligent reference image selection
- Intelligently selects reference images needed for the current video's first frame
- Includes storyboards from earlier in the timeline
- Ensures accuracy of multi-character and environmental elements
Automated consistency checking
- Generates multiple images in parallel
- Selects the most consistent image through MLLM/VLM
- Mimics the workflow of human creators
Efficient parallel processing
- Parallel processes consecutive shots in the same scene
- Dramatically improves video generation efficiency

Project Advantages

Compared to other video generation tools, ViMax's advantages:

Comparison	ViMax	Traditional Text-to-Video	Manual Video Production
Video length	Supports long videos	Short clips only	No restriction
Consistency	High (intelligent reference selection)	Low (inconsistent across frames)	High (human-controlled)
Narrative structure	Complete (script + storyboard)	Lacking	Complete but time-consuming
Automation level	High (end-to-end)	Medium (video generation only)	Low (fully manual)
Long-text handling	Supported (RAG engine)	Not supported	Supported but time-consuming
Professional-grade output	Yes (film-quality)	No	Yes
Generation speed	Fast (parallel processing)	Fast	Slow
Cost	Medium (API calls)	Medium	High (labor cost)

Why choose ViMax?

✅ Full-pipeline automation: From idea to video, no manual intervention needed
✅ Consistency guarantee: Intelligent reference selection and consistency checks
✅ Professional-grade output: Film-quality video production
✅ Long-content support: Can handle novel-length text
✅ Multi-agent collaboration: Director, screenwriter, producer all-in-one
✅ Efficient parallel processing: Dramatically improves generation efficiency

Detailed Project Analysis

Architecture Design

ViMax uses a multi-agent architecture, implementing a complete video generation pipeline from input to output:

┌─────────────────────────────────────────────────────────┐
│                    INPUT LAYER                            │
│  📝 Idea & Scripts & Novels                              │
│  💭 Natural Language Prompts                            │
│  🖼️ Reference Images                                     │
│  🎨 Style Directives                                     │
│  🧩 Configs                                              │
└─────────────────────────────────────────────────────────┘
                        │
                        ▼
┌─────────────────────────────────────────────────────────┐
│           CENTRAL ORCHESTRATION                          │
│  Agent Scheduling • Stage Transitions                    │
│  Resource Management • Retry/Fallback Logic             │
└─────────────────────────────────────────────────────────┘
                        │
        ┌───────────────┴───────────────┐
        ▼                                 ▼
┌──────────────────┐          ┌──────────────────┐
│ SCRIPT            │          │ SCENE & SHOT     │
│ UNDERSTANDING     │          │ PLANNING         │
│ • Character/Env   │          │ • Storyboard     │
│ • Scene Boundaries│          │ • Shot List      │
│ • Style Intent    │          │ • Key Frames     │
└──────────────────┘          └──────────────────┘
        │                                 │
        ▼                                 ▼
┌──────────────────┐          ┌──────────────────┐
│ VISUAL ASSET      │          │ CONSISTENCY &    │
│ PLANNING         │          │ CONTINUITY       │
│ • Ref Selection  │          │ • Character Track│
│ • Style Guidance │          │ • Ref Matching   │
│ • Prompt Cond    │          │ • Temporal Coher │
└──────────────────┘          └──────────────────┘
        │                                 │
        └───────────────┬───────────────┘
                        ▼
┌─────────────────────────────────────────────────────────┐
│      VISUAL SYNTHESIS & ASSEMBLY                        │
│  Image Generation • Best-Frame Selection               │
│  First/Last-Frame→Video • Cut & Timeline Assembly      │
└─────────────────────────────────────────────────────────┘
                        │
                        ▼
┌─────────────────────────────────────────────────────────┐
│                    OUTPUT LAYER                          │
│  🖼️ Frames • 🎞️ Clips & Final Videos                    │
│  📜 Logs • 📦 Working Directory Artifacts               │
└─────────────────────────────────────────────────────────┘

Core workflow:

Input layer: Receives ideas, scripts, novels, prompts, reference images, etc.
Central orchestration: Agent scheduling, stage transitions, resource management
Script understanding: Extracts characters/environments, scene boundaries, style intent
Scene and shot planning: Storyboard steps, shot list, key frames
Visual asset planning: Reference image selection, appearance/style guidance, prompt conditioning
Consistency and continuity: Character/environment tracking, reference matching, temporal coherence
Visual synthesis and assembly: Image generation, best frame selection, video assembly
Output layer: Generated frames, clips, final videos, logs, and working directory artifacts

Core Module Analysis

1. Intelligent Long-Script Generation Engine

ViMax uses a RAG-based long script design engine to handle long-form content:

Functions:

Intelligently analyzes long-form, novel-level stories
Automatically segments into multi-scene script format
Ensures accurate preservation of key plot points and character dialogue
Handles complex story structures

Implementation:

Uses RAG (Retrieval-Augmented Generation) technology
Analyzes the structure and content of long text
Intelligently segments while maintaining narrative coherence
Extracts key information (characters, scenes, dialogue, etc.)

Application scenarios:

Converting novel chapters into video
Handling long-form story content
Preserving the integrity of complex narratives

2. Expressive Storyboard Design System

ViMax creates expressive storyboards using cinematic language:

Functions:

Creates storyboards based on user requirements and target audience
Uses cinematic language to establish narrative rhythm
Designs shots and scene layouts
Guides subsequent video generation

Implementation:

Analyzes script content and style intent
Uses filmmaking knowledge to design storyboards
Considers shot angles, composition, rhythm, etc.
Generates detailed storyboard descriptions

Storyboard elements:

Scene descriptions
Shot types (close-up, medium shot, wide shot, etc.)
Character positions and actions
Visual style guidance

3. Multi-Camera Simulation

ViMax simulates multi-angle shooting for an immersive experience:

Functions:

Simulates multiple camera angles
Maintains consistent character positions and backgrounds within the same scene
Provides diverse viewing angles
Enhances visual richness of videos

Implementation:

Generates multiple viewpoints for the same scene
Uses reference images to maintain consistency
Intelligently selects the best viewpoint
Assembles multi-angle shots

4. Intelligent Reference Image Selection

ViMax intelligently selects reference images to ensure consistency:

Functions:

Selects reference images needed for the current video's first frame
Includes storyboards from earlier in the timeline
Ensures accuracy of multi-character and environmental elements
Maintains consistency as video length grows

Implementation:

Analyzes current scene requirements
Retrieves relevant images from historical timeline
Selects the most relevant reference images
Considers characters, environments, styles, and other factors

Selection strategies:

Character consistency: Select images containing the same character
Environment consistency: Select images from the same scene
Style consistency: Select images with the same visual style
Temporal coherence: Consider timeline order

5. Automated Consistency Checking

ViMax selects the most consistent images through MLLM/VLM:

Functions:

Generates multiple images in parallel
Uses MLLM/VLM to evaluate consistency
Selects the most consistent image as the first frame
Mimics human creator workflow

Implementation:

Generates multiple candidate images for the same scene
Uses a visual language model to evaluate each image
Considers consistency, quality, style, and other factors
Selects the best image

Evaluation dimensions:

Character consistency
Environment consistency
Visual quality
Style match

6. Efficient Parallel Processing

ViMax uses parallel processing to improve efficiency:

Functions:

Parallel processes consecutive shots in the same scene
Dramatically improves video generation efficiency
Optimizes resource usage

Implementation:

Identifies shots that can be processed in parallel
Allocates computing resources
Generates multiple shots in parallel
Assembles the final video

Optimization strategies:

Scene grouping: Groups shots from the same scene together
Resource allocation: Reasonably distributes API calls and compute resources
Caching: Caches reusable intermediate results

Key Technical Implementation

1. Multi-Agent Collaboration Mechanism

The core of ViMax is a multi-agent system where each agent works collaboratively:

Agent roles:

Director: Responsible for overall video planning and shot design
Screenwriter: Responsible for script generation and story structure
Producer: Responsible for resource management and quality control
Video Generator: Responsible for final video generation

Collaboration mechanism:

# Simplified collaboration workflow
def generate_video(idea):
    # 1. Screenwriter generates script
    script = screenwriter.generate(idea)

    # 2. Director designs storyboard and shots
    storyboard = director.plan(script)

    # 3. Producer manages resources and quality
    assets = producer.manage(storyboard)

    # 4. Video Generator creates video
    video = video_generator.create(assets)

    return video

2. RAG Long-Script Processing

ViMax uses RAG technology to process long text:

RAG workflow:

Document splitting: Split long text into manageable chunks
Embedding generation: Generate vector embeddings for each chunk
Retrieval: Retrieve relevant chunks based on current context
Generation: Generate scripts based on retrieved content

Advantages:

Can handle text of any length
Maintains contextual coherence
Accurately extracts key information
Supports complex story structures

3. Consistency Control Mechanism

ViMax ensures consistency through multiple layers:

Reference image management:

Maintains a reference image index
Uses embeddings for similarity retrieval
Intelligently selects the most relevant references

Consistency checking:

Uses MLLM/VLM to evaluate consistency
Generates and selects from multiple candidate images
Iteratively optimizes until consistency requirements are met

Temporal coherence:

Tracks elements in the timeline
Ensures consistency across consecutive shots
Handles scene transitions

Practical Use Cases

Case 1: Children's Story Video Generation

Scenario: Creating a simple story video for children.

Implementation steps:

# main_idea2video.py
idea = """
What would happen if a cat and a dog were best friends and they met a new cat?
"""

user_requirement = """
For children, no more than 3 scenes, warm and friendly style.
"""

style = "Cartoon"

# Run generation
python main_idea2video.py

Result: Automatically generates a children's story video with a complete narrative structure, consistent characters, and coherent scenes — suitable for educational or entertainment use.

Case 2: Novel Chapter to Video

Scenario: Converting a novel chapter into video content.

Implementation steps:

# Use Idea2Video mode to process long text
idea = """
[Paste novel chapter content, can be several thousand characters of text]
"""

user_requirement = """
Maintain the narrative style of the original, suitable for adult audiences, film-quality.
"""

style = "Cinematic"

python main_idea2video.py

Result: ViMax's RAG engine intelligently analyzes the long text, automatically segments it into a multi-scene script, and generates complete video content while preserving the narrative integrity of the original.

Case 3: Professional Film Script Generation

Scenario: Generate a video from a professional film script.

Implementation steps:

# main_script2video.py
script = """
EXT. SCHOOL GYM - DAY
A group of students are practicing basketball in a gym. The gym is large and open, with a basketball hoop at one end and a large audience at the other. John (18, male, tall, athletic) is the star player, practicing dribbling and shooting. Jane (17, female, short, athletic) is the assistant coach, helping John practice. Other students are watching and cheering for John.
John: (dribbling) I'm going to score!
Jane: (smiling) Nice job, John!
John: (shoots) Yes!
...
"""

user_requirement = """
Fast-paced, no more than 20 shots, sports style.
"""

style = "Animate Style"

python main_script2video.py

Result: Generates a professional film-quality video with complete shot design, character consistency, and scene coherence.

Case 4: Marketing Video Quick Generation

Scenario: Quickly generate a marketing video for a product.

Implementation steps:

idea = """
Our new product is a smartwatch with health monitoring, fitness tracking, and message notification features.
"""

user_requirement = """
30-second video, highlighting product features, modern tech style.
"""

style = "Modern Tech"

python main_idea2video.py

Result: Quickly generates a professional marketing video with product showcase, feature highlights, and visual appeal.

Advanced Configuration Tips

1. Customize Agent Behavior

ViMax's agent behavior can be customized through configuration files:

Configure agent parameters:

# configs/idea2video.yaml
agents:
  director:
    shot_planning: true
    multi_camera: true
    consistency_check: true

  screenwriter:
    rag_enabled: true
    long_text_support: true
    style_adaptation: true

  producer:
    quality_control: true
    resource_optimization: true
    parallel_processing: true

2. Optimize API Usage

API configuration optimization:

chat_model:
  init_args:
    model: google/gemini-2.5-flash-lite-preview-09-2025
    model_provider: openai
    api_key: <YOUR_API_KEY>
    base_url: https://openrouter.ai/api/v1
    temperature: 0.7  # controls creativity
    max_tokens: 4000   # controls output length

image_generator:
  class_path: tools.ImageGeneratorNanobananaGoogleAPI
  init_args:
    api_key: <YOUR_API_KEY>
    quality: "high"    # image quality setting
    style: "cinematic" # default style

video_generator:
  class_path: tools.VideoGeneratorVeoGoogleAPI
  init_args:
    api_key: <YOUR_API_KEY>
    resolution: "1080p"  # video resolution
    fps: 24             # frame rate

3. Working Directory Management

Customize working directory:

working_dir: .working_dir/idea2video

# Working directory structure:
# .working_dir/
#   └── idea2video/
#       ├── scripts/        # generated scripts
#       ├── storyboards/    # storyboards
#       ├── images/         # generated images
#       ├── videos/         # final videos
#       └── logs/           # log files

Clean working directory:

# Clean old generation results
rm -rf .working_dir/idea2video/*

# Keep specific projects
# Manually manage files in the working directory

4. Parallel Processing Optimization

Configure parallel processing:

# Set in configuration file
parallel_processing:
  enabled: true
  max_workers: 4  # number of parallel worker threads
  batch_size: 2   # number of shots to process per batch

Optimization strategies:

Adjust parallel count based on API limits
Balance speed and resource usage
Consider API call costs

5. Consistency Control Parameters

Adjust consistency checking:

consistency:
  enabled: true
  check_method: "mllm"  # or "vlm"
  similarity_threshold: 0.85
  max_candidates: 5      # number of candidate images to generate
  selection_criteria:
    - character_consistency
    - environment_consistency
    - style_match

6. Style Customization

Define custom styles:

# Define style in code
style = "Custom Style"

# Styles can include:
# - Visual style (cartoon, realistic, cinematic, etc.)
# - Color scheme
# - Shot style
# - Pacing and rhythm

Style presets:

Cartoon: Cartoon style
Cinematic: Cinematic style
Animate Style: Animation style
Modern Tech: Modern tech style

Comparison with Other Video Generation Tools

ViMax vs Traditional Text-to-Video Models

Traditional text-to-video models (e.g., Runway, Pika, Stable Video):

Advantages:

Fast generation speed
Supports multiple styles
Simple to use

Disadvantages:

Can only generate short clips (a few seconds)
Poor consistency across frames
Lacks narrative structure
Cannot handle long text

ViMax:

Advantages:

Supports long video generation
Strong consistency guarantee
Complete narrative structure
Long-text processing support
Professional-grade output

Disadvantages:

Relatively longer generation time
Requires multiple API configurations
Higher resource consumption

ViMax vs Code2Video

Code2Video (educational video generation):

Features:

Focused on educational scenarios
Uses Manim code for generation
Ensures clarity and reproducibility

ViMax:

Features:

General-purpose video generation
Supports narrative content
More flexible application scenarios

Application scenario comparison:

Scenario	ViMax	Code2Video
Educational videos	✅	✅✅
Narrative videos	✅✅	❌
Marketing videos	✅✅	❌
Novel to video	✅✅	❌
Math visualization	❌	✅✅

ViMax vs Manual Video Production

Manual production (After Effects, Premiere, etc.):

Advantages:

Complete control
Highest quality
Unlimited creativity

Disadvantages:

Time-consuming and labor-intensive
Requires professional skills
High cost
Difficult to batch produce

ViMax:

Advantages:

Highly automated
Fast generation
Low cost
Can batch produce

Disadvantages:

Less flexible than manual production
Limited support for complex effects

Recommendations

Choose ViMax when:

✅ Need to generate narrative videos
✅ Need to process long-form text content
✅ Need character and scene consistency
✅ Need fast video generation
✅ Need batch production

Choose traditional text-to-video when:

✅ Only need short clips
✅ Don't need narrative structure
✅ Prioritize fastest speed

Choose Code2Video when:

✅ Specifically producing educational videos
✅ Need math visualization
✅ Need code reproducibility

Choose manual production when:

✅ Need complete control
✅ Need complex special effects
✅ Budget and time are not constraints

Project Resources

Official Resources

🌟 GitHub: https://github.com/HKUDS/ViMax

Who Should Use This

ViMax is suitable for:

1. Content Creators and Video Producers

✅ Creators who need to quickly generate narrative videos
✅ Producers who want to convert text content into video
✅ Creators who need to batch generate video content

2. Marketing and Advertising Professionals

✅ Teams that need to quickly produce marketing videos
✅ Organizations that want to automate video content production
✅ Brands that need personalized video content

3. Educators

✅ Teachers who need to convert teaching content into video
✅ Educational institutions that want to create educational videos
✅ Educators who need to convert stories into video

4. Developers and Tech Enthusiasts

✅ Interested in multi-agent systems
✅ Developers who want to integrate video generation functionality
✅ Tech enthusiasts who want to explore AI video generation technology

5. Researchers and Academics

✅ Researching multi-agent video generation
✅ Researching consistency control techniques
✅ Researching RAG applications in video generation

Summary

ViMax is an innovative multi-agent video generation framework that integrates director, screenwriter, producer, and video generator into a single intelligent system, achieving end-to-end automated generation from idea to complete video.

Project highlights recap:

🎬 Full-pipeline automation: From idea to video, one-click generation of complete narrative videos
🤖 Multi-agent collaboration: Director, screenwriter, producer, video generator all-in-one
📝 Intelligent long-script generation: RAG-based long script design engine supporting novel-level content
🎨 Expressive storyboarding: Creates professional-grade storyboards using cinematic language
🎥 Multi-camera simulation: Simulates multi-angle shooting for an immersive experience
✅ Consistency guarantee: Intelligent reference selection and consistency checks for stable characters and scenes
⚡ Efficient parallel processing: Parallel processing of multiple shots in the same scene for dramatically improved efficiency

Application scenarios:

Content creation and video production
Marketing and advertising videos
Educational video production
Novel and story to video conversion
Batch video production

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