Civitai Python SDK
Project description
Civitai Generator Python Client
A Python client for Civitai's generator to run Civitai models from your Python code.
Quick Start
To get started with the Civitai Generator Python Client, you can use the following resources:
-
Google Colab Notebook: Jump into a pre-configured environment with a live notebook to try out the Civitai SDK.
- Streamlit Demo: See the Civitai SDK in action with a live Streamlit app demo. View Streamlit Demo
Installation
pip install civitai-py
Authenticate
Before running any Python scripts that use the API, you need to set your Civitai API token in your environment.
Grab your token from civitai.com/user/account and set it as an environment variable:
export CIVITAI_API_TOKEN=<your token>
Requirements
- Python 3.7+
Usage
Import the Civitai SDK:
import civitai
Create a txt2img job:
input = {
"model": "urn:air:sd1:checkpoint:civitai:4201@130072",
"params": {
"prompt": "RAW photo, face portrait photo of 26 y.o woman, wearing black dress, happy face, hard shadows, cinematic shot, dramatic lighting",
"negativePrompt": "(deformed iris, deformed pupils, semi-realistic, cgi, 3d, render, sketch, cartoon, drawing, anime, mutated hands and fingers:1.4), (deformed, distorted, disfigured:1.3)",
"scheduler": "EulerA",
"steps": 20,
"cfgScale": 7,
"width": 512,
"height": 512,
"clipSkip": 2
}
}
Run a model:
response = civitai.image.create(input)
Using Additional Networks
The SDK supports additional networks: LoRA, VAE, Hypernetwork, Textual Inversion, LyCORIS, Checkpoint, and LoCon.
To use any of the networks availabe on Civitai, simply add the additionalNetworks
field into the input:
input = {
"model": "urn:air:sd1:checkpoint:civitai:4384@128713",
"params": {
"prompt": "masterpiece, best quality, 1girl, IncrsAhri, multiple tails, fox tail, korean clothes, skirt, braid, arms behind back",
"negativePrompt": "(worst quality:1.4), (low quality:1.4), simple background, bad anatomy",
"scheduler": "EulerA",
"steps": 25,
"cfgScale": 7,
"width": 512,
"height": 768,
"seed": -1,
"clipSkip": 2
},
"additional_networks": {
"urn:air:sd1:lora:civitai:162141@182559": {
"type": "Lora",
"strength": 1.0
}
}
}
In the case of Lora
and LoCon
networks, set the strength
of the network; for TextualInversion
, set the triggerWord
of the network.
civitai.image.create
Run a model with inputs you provide.
response = civitai.image.create(options)
name | type | description |
---|---|---|
model |
string | null | Required. The Civitai model to use for generation. |
params.prompt |
string | null | Required. The main prompt for the image generation. |
params.negativePrompt |
string | null | Optional. The negative prompt for the image generation. |
params.scheduler |
Scheduler | null | Optional. The scheduler algorithm to use. Possible values are: EulerA , Euler , LMS , Heun , DPM2 , DPM2A , DPM2SA , DPM2M , DPMSDE , DPMFast , DPMAdaptive , LMSKarras , DPM2Karras , DPM2AKarras , DPM2SAKarras , DPM2MKarras , DPMSDEKarras , DDIM , PLMS , UniPC , Undefined , LCM , DDPM , DEIS . |
params.steps |
number | null | Optional. The number of steps for the image generation process. |
params.cfgScale |
number | null | Optional. The CFG scale for the image generation. |
params.width |
number | Required. The width of the generated image. |
params.height |
number | Required. The height of the generated image. |
params.seed |
number | null | Optional. The seed for the image generation process. |
params.clipSkip |
number | null | Optional. The number of CLIP skips for the image generation. |
callbackUrl |
string | null | Optional. URL that will be invoked upon completion of this job |
additionalNetworks |
ImageJobNetworkParams | null | Optional. An associative list of additional networks, keyed by the AIR of the network. Each network is of type AssetType. |
controlNets |
Array<ImageJobControlNet> | null | Optional. An associative list of additional networks. |
Additional Networks
additionalNetworks |
Record<string, ImageJobNetworkParams> | Optional. An associative list of additional networks, keyed by the AIR of the network. Each network is described by an ImageJobNetworkParams object. |
---|---|---|
type |
AssetType |
Optional. The type of the asset. Can be one of Lora , Hypernetwork , TextualInversion , Lycoris , Checkpoint , Vae , LoCon . |
strength |
number | Optional. In case of Lora and LoCon, set the strength of the network. |
triggerWord |
string | Optional. In case of a TextualInversion, set the trigger word of the network. |
ControlNets
controlNets |
Array<ImageJobControlNet> | Optional. An array of control networks that can be applied to the image generation process. Each ImageJobControlNet object in the array can have the following properties: |
---|---|---|
preprocessor |
ImageTransformer | null | Optional. Specifies the image transformer to be applied as a preprocessor. Possible values are Canny , DepthZoe , SoftedgePidinet , Rembg . |
weight |
number | null | Optional. The weight of the control net. |
startStep |
number | null | Optional. The step at which the control net starts to apply. |
endStep |
number | null | Optional. The step at which the control net stops applying. |
imageUrl |
string | null | Optional. The URL of the image associated with the controlnet. |
civitai.jobs.get
Fetches job details based on a provided token or job ID. If both are provided, the token takes precedence.
job_id = "your_job_id_here"
response = civitai.jobs.get(id=job_id)
# OR
token = "your_token_here"
response = civitai.jobs.get(token=token)
civitai.jobs.query
Retrieve a collection of jobs by querying properties, e.g., userId. You can optionally include a detailed
boolean flag to get detailed information about the jobs.
query = {
"properties": {
"userId": 4 # Querying by userId
}
}
detailed = False # Optional boolean flag to get detailed job definitions. False by default.
response = civitai.jobs.query(detailed=detailed, query_jobs_request=query)
civitai.jobs.cancel
Cancel a job by its jobId.
response = civitai.jobs.cancel(job_id)
This method cancels a job that is currently scheduled or running. It requires the jobId
of the job you wish to cancel. On successful cancellation, it returns a response object indicating the cancellation status.
Contributing Your Changes
After making your changes:
- Push your changes to your fork.
- Open a pull request against the main repository.
- Describe your changes and how they improve the project or fix issues.
Your contributions will be reviewed, and if accepted, merged into the project.
Additional Guidelines
- Include unit tests for new features or bug fixes.
- Update the documentation if necessary.
Thank you for contributing to the Civitai Generator Python Client! 🥹🤭
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