🎬 Pilipili-AutoVideo · 噼哩噼哩

Fully Automated AI Video Agent · Local Deployment · One Sentence to Final Cut

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📹 Demo — Replace this line with a GIF or video recording of the full workflow: topic input → scene review → final video output. docs/demo.gif (to be recorded — see Contributing)

📖 Overview

Pilipili-AutoVideo (噼哩噼哩) is a fully local, end-to-end AI video agent. Describe your video in one sentence — the system automatically handles script planning → keyframe image generation → TTS voiceover → video clip generation → FFmpeg assembly → subtitle burning, delivering a complete MP4 with subtitles and a CapCut/JianYing draft project for final human touch-ups.

Key differentiators from similar tools (LibTV, Huobao Drama):

• Absolute Audio-Video Sync: TTS voiceover is generated first and its exact millisecond duration is measured, then used to control video duration — audio and video are always perfectly aligned
• Keyframe Lock Strategy: Nano Banana generates a 4K keyframe image first, then Image-to-Video (I2V) produces the clip — ensuring consistently high visual quality with no subject drift
• Digital Twin Memory: Mem0-powered memory system learns your style preferences over time, injecting your creative habits into every new generation
• Skill Integration: The entire workflow is packaged as a standard Skill, callable by any AI Agent

🎯 Core Features

• 🤖 Natural Language Driven: One sentence → full video, no manual node operations required
• 🎨 Premium Visual Quality: Nano Banana keyframe lock + Kling 3.0 / Seedance 1.5 dual-engine, exceptional subject consistency
• 🔊 Perfect Audio-Video Sync: Measure voiceover duration first, control video duration accordingly — never misaligned
• ✂️ CapCut/JianYing Draft Export: AI handles 90%, you fine-tune the last 10% in CapCut
• 🧠 Gets Smarter Over Time: Mem0 memory system learns your aesthetic preferences with every project
• 🔌 Agent-Callable: Packaged as a standard Skill, seamlessly integrates into larger automation workflows

🛠️ Architecture

┌─────────────────────────────────────────────────────────────┐
│                  Pilipili-AutoVideo Architecture             │
├─────────────────────────────────────────────────────────────┤
│  Frontend    React 19 + TailwindCSS · 3-panel Studio · WS   │
├─────────────────────────────────────────────────────────────┤
│  API Layer   FastAPI · WebSocket · REST · LangGraph Workflow │
├──────────────┬──────────────┬──────────────┬────────────────┤
│  Brain Layer │  Vision Layer│  Motion Layer│  Voice Layer   │
│  DeepSeek    │  Nano Banana │  Kling 3.0   │  MiniMax TTS   │
│  Kimi        │  (Gemini 3   │  Seedance    │  Speech 2.8 HD │
│  MiniMax LLM │   Pro Image) │  1.5 Pro     │                │
│  Gemini      │              │              │                │
├──────────────┴──────────────┴──────────────┴────────────────┤
│  Assembly    Python + FFmpeg · xfade transitions · WhisperX  │
├─────────────────────────────────────────────────────────────┤
│  Draft Layer pyJianYingDraft · Auto CapCut/JianYing Draft    │
├─────────────────────────────────────────────────────────────┤
│  Memory      Mem0 · Local SQLite · Style Preference Twin     │
└─────────────────────────────────────────────────────────────┘

🚀 Quick Start

📋 Requirements

Install FFmpeg

macOS:

brew install ffmpeg

Ubuntu / Debian:

sudo apt update && sudo apt install ffmpeg

Windows: Download from ffmpeg.org and add to PATH. Verify:

ffmpeg -version

Clone & Install

# 1. Clone the repository
git clone https://github.com/OpenDemon/Pilipili-AutoVideo.git
cd Pilipili-AutoVideo

# 2. Install Python dependencies
pip install -r requirements.txt

# 3. Copy config template
cp configs/config.example.yaml configs/config.yaml

Configure API Keys

Edit configs/config.yaml:

llm:
  provider: deepseek          # deepseek | kimi | minimax | gemini
  api_key: "sk-xxxx"

image_gen:
  provider: nano_banana
  api_key: "AIzaSy-xxxx"      # Google AI Studio Key

video_gen:
  default_engine: kling       # kling | seedance | auto
  kling:
    api_key: "xxxx"
    api_secret: "xxxx"
  seedance:
    api_key: "xxxx"

tts:
  provider: minimax
  api_key: "xxxx"
  group_id: "xxxx"

memory:
  provider: local             # local | mem0_cloud
  # mem0_api_key: "m0-xxxx"  # Fill in for cloud sync

💡 You can also configure API keys visually at http://localhost:3000/settings — no YAML editing required.

Option 1: CLI (Recommended for debugging)

# Basic usage
python cli/main.py run --topic "Cyberpunk Mars colony, 60 seconds, cold color palette"

# Specify engine
python cli/main.py run \
  --topic "Ancient palace romance story" \
  --engine seedance \
  --duration 90 \
  --add-subtitles

# List past projects
python cli/main.py list

# Help
python cli/main.py --help

Option 2: Web UI (Recommended for daily use)

# Start backend
python cli/main.py server

# In another terminal, start frontend
cd frontend
pnpm install && pnpm dev

# Visit http://localhost:3000

Option 3: Docker Compose (Recommended for production)

# Copy environment variables
cp .env.example .env
# Edit .env with your API keys

# Start all services
docker-compose up -d

# Visit http://localhost:3000

📦 Project Structure

Pilipili-AutoVideo/
├── api/
│   └── server.py           # FastAPI backend + WebSocket
├── cli/
│   └── main.py             # Click CLI entrypoint
├── core/
│   └── config.py           # Global config (Pydantic Settings)
├── modules/
│   ├── llm.py              # LLM script generation (multi-provider)
│   ├── image_gen.py        # Nano Banana keyframe generation
│   ├── tts.py              # MiniMax TTS + duration measurement
│   ├── video_gen.py        # Kling 3.0 / Seedance 1.5 I2V
│   ├── assembler.py        # FFmpeg assembly + subtitle burning
│   ├── jianying_draft.py   # CapCut/JianYing draft generation
│   └── memory.py           # Mem0 memory system
├── frontend/               # React 19 frontend (3-panel studio)
├── skills/
│   └── SKILL.md            # Skill packaging spec
├── configs/
│   ├── config.example.yaml # Config template
│   └── config.yaml         # Local config (gitignored)
├── tests/
│   └── test_pipeline.py    # Unit tests (18 test cases)
├── data/
│   ├── outputs/            # Generated videos and drafts
│   └── memory/             # Memory database
├── docker-compose.yml
├── Dockerfile.backend
├── requirements.txt
└── pyproject.toml

🎬 Workflow Deep Dive

The core workflow is orchestrated by LangGraph in the following stages:

User Input
  │
  ▼
① Script Generation (LLM)
  │  DeepSeek/Kimi expands one sentence into a structured storyboard
  │  Each scene: voiceover text, visual description, motion description,
  │              duration, transition, camera motion
  │
  ▼
② Scene Review (optional human step)
  │  Web UI shows scene list; user can edit each scene before confirming
  │  CLI mode: auto-approved
  │
  ▼
③ Parallel Generation (Keyframe Images + TTS Voiceover)
  │  Nano Banana generates 4K keyframe images for each scene in parallel
  │  MiniMax TTS generates voiceover for each scene, measuring exact ms duration
  │
  ▼
④ Video Generation (Image-to-Video)
  │  Uses keyframe as first frame, voiceover duration as video duration
  │  Kling 3.0 (action/product) or Seedance 1.5 (narrative/multi-character)
  │
  ▼
⑤ Assembly (FFmpeg)
  │  xfade transitions + background music mixing + WhisperX subtitle burning
  │
  ▼
⑥ Draft Export (CapCut/JianYing)
  │  Auto-generates draft project preserving all scene assets and timeline
  │
  ▼
⑦ Memory Update (Mem0)
     After user rating, system learns style preferences for future generations

🆚 Comparison