Grok-Imagine-Image-2-API
Health Uyari
- License — License: MIT
- Description — Repository has a description
- Active repo — Last push 0 days ago
- Low visibility — Only 5 GitHub stars
Code Gecti
- Code scan — Scanned 4 files during light audit, no dangerous patterns found
Permissions Gecti
- Permissions — No dangerous permissions requested
Bu listing icin henuz AI raporu yok.
Grok Imagine Image 2.0 API and Grok Imagine Image 2 API Python SDK and MCP server for xAI image generation and editing through MuAPI.
Grok Imagine Image 2.0 API (Grok Imagine Image 2 API) — Python SDK & MCP Server
A focused Python SDK and MCP server for the Grok Imagine Image 2.0 API through MuAPI. Also known as the Grok Imagine Image 2 API or Grok Imagine API, it provides xAI image generation, text-to-image, chained follow-up image editing, local uploads, and asynchronous job polling from Python or an MCP-capable agent.
Availability: Live on MuAPI as two endpoints —
grok-imagine-image-2for text-to-image andgrok-imagine-image-2-editfor follow-up edits.
Related Projects
- MuAPI — Unified API for image, video, and audio generation across hundreds of AI models.
- Grok Imagine Image 2.0 on MuAPI — Official model landing page for Grok Imagine Image 2.0 generation and editing.
- Grok Imagine Image 2.0 playground — Try the model in the browser when access is enabled.
- MuAPI API reference — REST endpoint and asynchronous prediction lifecycle documentation.
- MuAPI access keys — Create the x-api-key credential required by this SDK.
- awesome-ai-image-models — Compare image models by API, price, quality, and use case.
- Awesome-GPT-Image-2-API-Prompts — Reusable prompt patterns for image generation, typography, editing, and visual design.
- Open-Generative-AI — Open-source image and video studio powered by MuAPI.
- Generative-Media-Skills — Agent-ready skills for driving image, video, and audio models from coding assistants.
- muapi-cli — Command-line access to MuAPI image, video, and audio endpoints.
- Wan-3.0-API — the companion Python SDK and MCP server for Wan video generation.
- Flux-3-Dev-API — MuAPI access to FLUX image and video workflows.
Install
git clone https://github.com/Anil-matcha/Grok-Imagine-Image-2-API.git
cd Grok-Imagine-Image-2-API
python -m venv .venv
source .venv/bin/activate
pip install -r requirements.txt
cp .env.example .env
Set MUAPI_API_KEY in the env file. The client uses https://api.muapi.ai/api/v1 by default. Set GROK_IMAGINE_IMAGE_2_API_BASE_URL to target a compatible self-hosted or proxy endpoint instead. GROK_API_BASE_URL is also accepted as a shorter alias.
Quick start
from grok_imagine_image_2_api import GrokImagineImage2API
api = GrokImagineImage2API()
job = api.text_to_image(
"A high-contrast halftone portrait in fine white dots on a black background",
aspect_ratio="1:1",
)
result = api.wait_for_completion(job["request_id"])
print(result)
The API is asynchronous: submit a prompt, keep the returned request ID, and poll until the task is completed.
Follow-up editing
Grok Imagine Image 2.0's edit model doesn't take a freshly uploaded photo — it applies a targeted edit to an image it previously generated, referenced by that job's request_id. Pass edit_image() the request_id from a prior text_to_image() (or edit_image()) call along with a prompt describing the change:
job = api.text_to_image("A raccoon in a teal Hawaiian shirt at a beach club table", aspect_ratio="1:1")
base = api.wait_for_completion(job["request_id"])
edit_job = api.edit_image(
prompt="Change the Hawaiian shirt to a plain white t-shirt, keep everything else unchanged.",
request_id=job["request_id"],
)
result = api.wait_for_completion(edit_job["request_id"])
print(result)
Pass an optional mask_indexs list of integers to scope the edit to specific segments of the source image instead of the whole frame. Each edit call returns its own request_id, so edits can be chained repeatedly to keep refining the same image.
Upload a local reference
uploaded = api.upload_file("reference.png")
print(uploaded)
Useful for storing your own reference assets alongside a job; note that Grok Imagine Image 2.0 itself doesn't accept uploaded images as edit input — see Follow-up editing above.
API surface
| Method | Purpose |
|---|---|
| text_to_image() | Create an image from a text prompt. |
| edit_image() | Apply a follow-up edit to a prior generation, referenced by its request_id. |
| upload_file() | Upload a local reference asset. |
| get_result() / wait_for_completion() | Retrieve an asynchronous job and wait for its output. |
Supported aspect ratios
The current catalog contract supports:
1:1, 2:3, 3:2, 16:9, and 9:16.
MCP server
Expose the model to MCP-capable clients:
python mcp_server.py
The server provides text_to_image, edit_image, and get_task_status tools. Configure it in an MCP client with the repository's Python interpreter and pass MUAPI_API_KEY through the process environment.
Example configuration:
{
"mcpServers": {
"grok-imagine-image-2": {
"command": "/absolute/path/to/.venv/bin/python",
"args": ["/absolute/path/to/Grok-Imagine-Image-2-API/mcp_server.py"],
"env": {
"MUAPI_API_KEY": "your_muapi_api_key"
}
}
}
}
Endpoint compatibility
The client calls these MuAPI paths beneath the configured base URL:
- POST /grok-imagine-image-2 —
{prompt, aspect_ratio} - POST /grok-imagine-image-2-edit —
{prompt, request_id, mask_indexs?} - POST /upload_file
- GET /predictions/{request_id}/result
The SDK uses the x-api-key header and JSON request bodies.
Development
Run the local tests and syntax checks with:
python -m unittest discover -s tests -v
python -m py_compile grok_imagine_image_2_api.py mcp_server.py
License
Yorumlar (0)
Yorum birakmak icin giris yap.
Yorum birakSonuc bulunamadi