FireRed-OpenStoryline
FireRed-OpenStoryline is an AI video editing agent that transforms manual editing into intention-driven directing through natural language interaction, LLM-powered planning, and precise tool orchestration. It facilitates transparent, human-in-the-loop creation with reusable Style Skills for consistent, professional storytelling.
FireRed-OpenStoryline turns complex video creation into natural, intuitive conversations. Designed with both accessibility and enterprise-grade reliability in mind, FireRed-OpenStoryline makes video creation easy and friendly to beginners and creative enthusiasts alike.
Deriving from the saying "A single spark can start a prairie fire", the name FireRed represents our vision: to spread our SOTA capabilitiesโhoned in real-world scenariosโlike sparks across the wilderness, igniting the imagination of developers worldwide to reshape the future of AI together.
โจ Key Features
- ๐ Smart Media Search & Organization: Automatically searches online and downloads images and video clips that match your requirements. Performs clip segmentation and content understanding based on your thematic media.
- โ๏ธ Intelligent Script Generation: Combines user themes, visual understanding, and emotion recognition to automatically construct storylines and context-aware narration. Features built-in Few-shot style transfer capabilities, allowing users to define specific copy styles (e.g., product reviews, casual vlogs) via reference text, achieving precise replication of tone, rhythm, and sentence structure.
- ๐ต Intelligent Music, Voiceover & Font Recommendations: Supports personal playlist imports and auto-recommends BGM based on content and mood, featuring smart beat-syncing. Simply describe the desired toneโe.g., "Restrained," "Emotional," or "Documentary-style"โand the system matches suitable voiceovers and fonts to ensure a cohesive aesthetic.
- ๐ฌ Conversational Refinement: Rapidly cut, swap, or resequence clips. Edit scripts and fine-tune visual detailsโincluding color, font, stroke, and position. All edits are performed exclusively via natural language prompts with immediate results.
- โกEditing Skill Archiving: Save your complete editing workflow as a custom Skill. Simply swap the media and apply the corresponding Skill to instantly replicate the style, enabling efficient batch creation.
NEWS
- ๐ 2026-03-22: Introduced an ASR-based rough cut skill for speech videos, enabling automatic removal of filler words, disfluencies, and repeated sentences, with timestamp-aligned segmentation for cleaner and more efficient speech editing workflows.
- ๐ฅ 2026-03-12: Integrated with OpenClaw, adding two OpenClaw Skills โ
openstoryline-installandopenstoryline-useโ covering the initial installation/first-run workflow and the actual usage workflow, respectively. Also added Skill usage instructions for Claude Code, making it easier for Claude Code to install and invoke the project in accordance with the repository guidelines. - 2026-02-10: FireRed-OpenStoryline was officially open-sourced.
๐๏ธ Architecture
โจ Demo
| Zhongcao Style | Humorous Style | Product Picks | Artistic Style |
| Unboxing | Talking Pet | Travel Vlog | Year-in-Review |
๐จ Effects Note: Due to licensing restrictions on open-source assets, the elements (fonts/music) in the first row represent only basic effects. We highly recommend following the Custom Asset Library Tutorial to unlock commercial-grade fonts, music, and VFX for significantly better video quality.
โ ๏ธ Quality Note: To save space in the README, the demo videos are heavily compressed. The actual output retains the original resolution by default and supports custom dimensions.
In the Demo: The first row shows default open-source assets (Restricted Mode); the second row shows Xiaohongshu App "AI Clip" asset library effects. ๐ Click to view tutorial
โ๏ธ Disclaimer: User footage and brand logos shown in the demos are for technical demonstration purposes only. Ownership belongs to the original creators. Please contact us for copyright concerns.
๐ค Use Through an Agent
FireRed-OpenStoryline supports usage through Agent Skills.
We provide two Skills:
openstoryline-install: for installation, configuration, and first-run verification.openstoryline-use: for starting the service and running the actual video editing workflow.
OpenClaw
Just tell OpenClaw: โI want to try OpenStoryline. Help me install the required Skills,โ and it will automatically trigger the installation.
If the installation runs into problems, use the following commands to install them manually:
openclaw skills install openstoryline-install
openclaw skills install openstoryline-use
If your current OpenClaw version does not support openclaw skills install, or if installation still fails, you can use ClawHub instead:
npx clawhub install openstoryline-install
npx clawhub install openstoryline-use
Once installed, you only need to send your media assets to OpenClaw, and it can help you complete the entire process from installing FireRed-OpenStoryline to generating the final video.
Claude Code
This repository comes with built-in Claude Code Skills.
If you start Claude Code from the root directory of this repository, you can use the project-level Skills included in the repo directly. Claude Code can then help you install and use FireRed-OpenStoryline.
/openstoryline-install
/openstoryline-use
If you want to install these two Skills into your own global Claude Code configuration, run:
mkdir -p ~/.claude/skills
cp -R .claude/skills/openstoryline-install ~/.claude/skills/
cp -R .claude/skills/openstoryline-use ~/.claude/skills/
Other Compatible Agents (Experimental)
These Skills are based on an open Agent Skills format, so in theory they can also be installed into other compatible agents.
For example, you can install them into Codex via the Skills CLI:
npx skills add FireRedTeam/FireRed-OpenStoryline --skill openstoryline-install --agent codex
npx skills add FireRedTeam/FireRed-OpenStoryline --skill openstoryline-use --agent codex
Or use the commands below with the --global flag to install these Skills into the user-level directory so they are available across projects:
npx skills add FireRedTeam/FireRed-OpenStoryline --skill openstoryline-install --global
npx skills add FireRedTeam/FireRed-OpenStoryline --skill openstoryline-use --global
๐ฆ Install
1. Clone repository
# If git is not installed, refer to the official website for installation: https://git-scm.com/install/
# Or manually download the code
git clone https://github.com/FireRedTeam/FireRed-OpenStoryline.git
cd FireRed-OpenStoryline
2. Create a virtual environment
Install Conda according to the official guide (Miniforge is recommended, it is suggested to check the option to automatically configure environment variables during installation): https://docs.conda.io/projects/conda/en/latest/user-guide/install/index.html
# Recommended python>=3.11
conda create -n storyline python=3.11
conda activate storyline
3. ๐ฆ Resource Download & Installation
3.1 Automatic Installation (Linux and macOS only)
sh build_env.sh
3.2 Manual Installation
A. MacOS or Linux
Step 1: Install wget (if not already installed)
# MacOS: If you haven't installed Homebrew yet, please install it first: https://brew.sh/ brew install wget # Ubuntu/Debian sudo apt-get install wget # CentOS sudo yum install wgetStep 2: Download Resources
chmod +x download.sh ./download.shStep 3: Install Dependencies
pip install -r requirements.txt
B. Windows
Step 1: Prepare Directory: Create a new directory named
resourcein the project root directory.Step 2: Download and Extract:
Download Models (models.zip) -> Extract to the
.storylinedirectory.Download Resources (resource.zip) -> Extract to the
resourcedirectory.
Step 3: Install Dependencies:
pip install -r requirements.txt
๐ Quick Start
Note: Before starting, you need to configure the API-Key in config.toml first. For details, please refer to the documentation API-Key Configuration
1. Start the MCP Server
MacOS or Linux
PYTHONPATH=src python -m open_storyline.mcp.server
Windows
$env:PYTHONPATH="src"; python -m open_storyline.mcp.server
2. Start the conversation interface
Method 1: Command Line Interface
python cli.pyMethod 2: Web Interface
uvicorn agent_fastapi:app --host 127.0.0.1 --port 8005
๐ณ Docker
Pull the Image
# Pull image from Docker Hub official repository
# Recommended for users outside China
docker pull openstoryline/openstoryline:v1.0.1
# Pull image from Alibaba Cloud Container Registry
# Recommended for users in China (faster and more stable)
docker pull crpi-6knxem4w8ggpdnsn.cn-shanghai.personal.cr.aliyuncs.com/openstoryline/openstoryline:v1.0.1
Start the Container
docker run \
-v $(pwd)/config.toml:/app/config.toml \
-v $(pwd)/outputs:/app/outputs \
-v $(pwd)/run.sh:/app/run.sh \
-p 7860:7860 \
openstoryline/openstoryline:v1.0.1
After starting, access the Web interface at http://0.0.0.0:7860
๐ Project Structure
FireRed-OpenStoryline/
โโโ ๐ฏ src/open_storyline/ Core application
โ โโโ mcp/ ๐ Model Context Protocol
โ โโโ nodes/ ๐ฌ Video processing nodes
โ โโโ skills/ ๐ ๏ธ Agent skills library
โ โโโ storage/ ๐พ Agent Memory
โ โโโ utils/ ๐งฐ Helper utilities
โ โโโ agent.py ๐ค Build Agent
โ โโโ config.py โ๏ธ Configuration management
โโโ ๐ docs/ Documentation
โโโ ๐ณ Dockerfile Docker Configuration
โโโ ๐ฌ prompts/ LLM prompt templates
โโโ ๐จ resource/ Static resources
โ โโโ bgms/ Background music library
โ โโโ fonts/ Font files
โ โโโ script_templates/ Video script templates
โ โโโ unicode_emojis.json Emoji list
โโโ ๐ง scripts/ Utility scripts
โโโ ๐ web/ Web interface
โโโ ๐ agent_fastapi.py FastAPI server
โโโ ๐ฅ๏ธ cli.py Command-line interface
โโโ โ๏ธ config.toml Main configuration file
โโโ ๐ build_env.sh Environment Build Script
โโโ ๐ฅ download.sh Resource downloader
โโโ ๐ฆ requirements.txt Runtime dependencies
โโโ โถ๏ธ run.sh Launch script
๐ Documentation
๐ Tutorial Index
- API Key Configuration - How to configure and manage API keys
- Usage Tutorial - Common use cases and basic operations
- FAQ - Frequently asked questions
TODO
- Add the function of voiceover type video editing.
- Add support for voice cloning
- Add more transition/filter/effects effects functions.
- Add image/video generation and editing capabilities.
- GPU-accelerated rendering and highlight selection.
Acknowledgements
This project is built upon the following excellent open-source projects:
Core Dependencies
- MoviePy - Video editing library
- FFmpeg - Multimedia framework
- LangChain - A framework that provides pre-built Agents
๐ License
This project is licensed under the Apache License 2.0 - see the LICENSE file for details.
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