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Seedream CLI

PyPI version PyPI downloads Python 3.10+ License: MIT CI

A command-line tool for AI image generation using Seedream through the AceDataCloud API.

Generate AI images directly from your terminal — no MCP client required.

Features

  • Image Generation — Generate images from text prompts with multiple models
  • Image Editing — Edit, combine, and transform images with AI
  • Multiple Models — doubao-seedream-5-0-pro-260628, doubao-seedream-5-0-lite-260128, doubao-seedream-4-5-251128, doubao-seedream-4-0-250828
  • Task Management — Query tasks, batch query, wait with polling
  • Rich Output — Beautiful terminal tables and panels via Rich
  • JSON Mode — Machine-readable output with --json for piping

Quick Start

1. Get API Token

  1. Open Ace Data Cloud → Applications. Sign in, or register an account first.
  2. Find General application. If it has not been created, choose Initialize General Application. A general key can use the services available to your account; a dedicated application's key is limited to its service. Check the required service/model access and current pricing.
  3. Copy the API Key from the application card, or open Keys / Manage Keys → Create to create a separate key for this integration. Give it a recognizable name so you can revoke or rotate it independently.
  4. When creating a key, review Expiration Time, Set Usage Limitation, and Allowed APIs. Enable only the restrictions you need, allow the operations you will call, then click Create and copy the token from the key list. Task lookup does not grant permission to submit a generation. Confirm the application's balance can cover your first request; any trial allowance is whatever your account currently displays.
  5. Copy only the token value, without quotation marks, spaces, or Bearer . An API Key / API Token field expects this raw value; only a manually configured HTTP Authorization header needs the Bearer prefix. A platform-... account-management token cannot replace a generation API key.

Copy an application API key or open Manage Keys

Create a separately named key with optional restrictions

Save the key in the client's credential store or the environment variable shown below. Never put it in a prompt, shared workflow, screenshot, or Git commit. If authentication fails, check the full copied value, application/service access, expiration, usage limit, and balance before creating another key.

2. Install

# Install with pip
pip install seedream-cli

# Or with uv (recommended)
uv pip install seedream-cli

# Or from source
git clone https://github.com/AceDataCloud/SeedreamCli.git
cd SeedreamCli
pip install -e .

3. Configure

# Set your API token
export ACEDATACLOUD_API_TOKEN=your_token_here

# Or use .env file
cp .env.example .env
# Edit .env with your token

4. Use

# Generate an image
seedream generate "A test image"

# Edit an image
seedream edit "Make it look like a painting" -i https://example.com/photo.jpg

# Decompose a poster into editable layers
seedream decompose https://example.com/poster.png --resolution 1.5K --json

# Stream Lite image events as NDJSON
seedream generate "A four-panel storyboard" --sequential-image-generation auto \
  --sequential-max-images 4 --stream --json

# Check task status
seedream task <task-id>

# Wait for completion
seedream wait <task-id> --interval 5

# List available models
seedream models

Commands

Command Description
seedream generate <prompt> Generate an image from a text prompt
seedream edit <prompt> -i <url>... Edit images, including Pro transparent backgrounds
seedream decompose <url> Split one image into a base and editable transparent layers
seedream task <task_id> Query a single task status
seedream tasks <id1> <id2>... Query multiple tasks at once
seedream wait <task_id> Wait for task completion with polling
seedream models List available Seedream models
seedream config Show current configuration
seedream resolutions List available output resolutions

Global Options

--token TEXT    API token (or set ACEDATACLOUD_API_TOKEN env var)
--version       Show version
--help          Show help message

Most commands support:

--json          Output raw JSON (for piping/scripting)
--model TEXT    Seedream model version (default: doubao-seedream-5-0-lite-260128)

Available Models

Model Version Notes
doubao-seedream-5-0-pro-260628 V5.0 Pro Single image, 1K/1.5K/2K, transparent background, layer decomposition
doubao-seedream-5-0-lite-260128 V5.0 Lite Sequential images, streaming, web search (default)
doubao-seedream-4-5-251128 V4.5 Flagship model, best quality
doubao-seedream-4-0-250828 V4.0 Standard quality

Configuration

Environment Variables

Variable Description Default
ACEDATACLOUD_API_TOKEN API token from AceDataCloud Required
ACEDATACLOUD_API_BASE_URL API base URL https://api.acedata.cloud
SEEDREAM_DEFAULT_MODEL Default model doubao-seedream-5-0-lite-260128
SEEDREAM_REQUEST_TIMEOUT Timeout in seconds 1800

Development

Setup Development Environment

git clone https://github.com/AceDataCloud/SeedreamCli.git
cd SeedreamCli
python -m venv .venv
source .venv/bin/activate
pip install -e ".[dev,test]"

Run Tests

pytest
pytest --cov=seedream_cli
pytest tests/test_integration.py -m integration

Code Quality

ruff format .
ruff check .
mypy seedream_cli

Seedream 5.0 constraints

  • Pro supports 1K/1.5K/2K, prompt optimization standard/fast, transparent-background editing, and layer decomposition. It does not support sequential generation, streaming, or web search.
  • Lite supports 2K/3K/4K, sequential generation, streaming, web search, and standard prompt optimization. It does not support layer decomposition or transparent-background mode.
  • --stream uses AceDataCloud normalized NDJSON and cannot be combined with --async or --callback-url.
  • Layer results include z_index, name, description, and absolute/normalized bounding boxes. JSON output preserves every field.

Docker

docker pull ghcr.io/acedatacloud/seedream-cli:latest
docker run --rm -e ACEDATACLOUD_API_TOKEN=your_token \
  ghcr.io/acedatacloud/seedream-cli generate "A test image"

Project Structure

SeedreamCli/
├── seedream_cli/                # Main package
│   ├── __init__.py
│   ├── __main__.py            # python -m seedream_cli entry point
│   ├── main.py                # CLI entry point
│   ├── core/                  # Core modules
│   │   ├── client.py          # HTTP client for Seedream API
│   │   ├── config.py          # Configuration management
│   │   ├── exceptions.py      # Custom exceptions
│   │   └── output.py          # Rich terminal formatting
│   └── commands/              # CLI command groups
│       ├── image.py           # Image generation commands
│       ├── task.py            # Task management commands
│       └── info.py            # Info & utility commands
├── tests/                     # Test suite
├── .github/workflows/         # CI/CD (lint, test, publish to PyPI)
├── Dockerfile                 # Container image
├── deploy/                    # Kubernetes deployment configs
├── .env.example               # Environment template
├── pyproject.toml             # Project configuration
└── README.md

Seedream CLI vs Seedream MCP

Feature Seedream CLI Seedream MCP
Interface Terminal commands MCP protocol
Usage Direct shell, scripts, CI/CD Claude, VS Code, MCP clients
Output Rich tables / JSON Structured MCP responses
Automation Shell scripts, piping AI agent workflows
Install pip install seedream-cli pip install mcp-seedream-pro

Both tools use the same AceDataCloud API and share the same API token.

Contributing

Contributions are welcome! Please:

  1. Fork the repository
  2. Create a feature branch (git checkout -b feature/amazing)
  3. Commit your changes (git commit -m 'Add amazing feature')
  4. Push to the branch (git push origin feature/amazing)
  5. Open a Pull Request

Development Requirements

  • Python 3.10+
  • Dependencies: pip install -e ".[all]"
  • Lint: ruff check . && ruff format --check .
  • Test: pytest

License

This project is licensed under the MIT License — see the LICENSE file for details.

Metadata

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