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A New Paradigm for Content Generation via Agentic Orchestration

Project description

Vibe AIGC

CI codecov PyPI Python 3.12+ License: MIT Docs

A New Paradigm for Content Generation via Agentic Orchestration

Based on arXiv:2602.04575

📚 Documentation | 🚀 Quick Start | 📖 API Reference


What is Vibe AIGC?

Vibe AIGC bridges the Intent-Execution Gap in AI content generation. Instead of prompt engineering, you provide a Vibe — a high-level representation of your creative intent — and the system automatically decomposes it into executable workflows.

from vibe_aigc import MetaPlanner, Vibe

# Express your intent
vibe = Vibe(
    description="Create a cinematic sci-fi trailer",
    style="dark, atmospheric, Blade Runner aesthetic",
    constraints=["under 60 seconds", "no dialogue"]
)

# Let the Meta-Planner handle the rest
planner = MetaPlanner()
result = await planner.execute(vibe)

Architecture (Paper Section 5)

The implementation follows the paper's three-part architecture:

Component Purpose Module
MetaPlanner Decomposes Vibes into workflows vibe_aigc.planner
KnowledgeBase Domain expertise for intent understanding vibe_aigc.knowledge
ToolRegistry Atomic tools for content generation vibe_aigc.tools
from vibe_aigc import MetaPlanner, Vibe, create_knowledge_base, create_default_registry

# The full architecture
kb = create_knowledge_base()  # Film, writing, design, music knowledge
tools = create_default_registry()  # LLM, templates, combine tools

planner = MetaPlanner(knowledge_base=kb, tool_registry=tools)

# Query knowledge for "Hitchcockian suspense" → technical specs
result = kb.query("Hitchcockian suspense")
# Returns: camera techniques, lighting specs, editing patterns

Features

  • 🎯 Vibe-based Planning — High-level intent → executable workflows
  • 🧠 Domain Knowledge — Built-in expertise for film, writing, design, music
  • 🔧 Tool Library — Pluggable tools for actual content generation
  • Parallel Execution — Independent nodes run concurrently
  • 🔄 Adaptive Replanning — Automatic recovery from failures
  • 💾 Checkpoint/Resume — Save and restore workflow state
  • 📊 Progress Tracking — Real-time callbacks and visualization
  • 🎨 Workflow Visualization — ASCII and Mermaid diagrams

Installation

pip install vibe-aigc

CLI Usage

# Generate a workflow plan
vibe-aigc plan "Create a blog post about AI" --style "informative" --format ascii

# Execute a vibe
vibe-aigc execute "Design a landing page" --visualize --checkpoint

# Manage checkpoints
vibe-aigc checkpoints --list

Quick Example

import asyncio
from vibe_aigc import Vibe, MetaPlanner

async def main():
    vibe = Vibe(
        description="Write a blog post about AI agents",
        style="informative, engaging",
        constraints=["under 1000 words"]
    )
    
    planner = MetaPlanner()
    result = await planner.execute_with_visualization(vibe)
    
    print(f"Status: {result.get_summary()['status']}")

asyncio.run(main())

Architecture

User Vibe → MetaPlanner → Agentic Pipeline → Execution → Result
     ↑                           ↓
     └──── Feedback Loop ────────┘

Documentation

Contributing

Contributions welcome! See CONTRIBUTING.md for guidelines.

License

MIT — see LICENSE for details.

Citation

@article{vibe-aigc-2025,
  title={Vibe AIGC: A New Paradigm for Content Generation via Agentic Orchestration},
  journal={arXiv preprint arXiv:2602.04575},
  year={2025}
}

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