# Images ## Overview Netmind provides compatibility with the OpenAI API standard, allowing for easier integration into existing applications. ## Base URL `https://api.netmind.ai/inference-api/openai/v1` ## API Key To use the API, you need to obtain a Netmind AI API Key. For detailed instructions, please refer to the [authentication documentation](https://netmind-power.gitbook.io/netmind-power-documentation/api/api-token). ## Supported Models ### Image Generation * runwayml/stable-diffusion-v1-5 * black-forest-labs/FLUX.1-schnell * stabilityai/stable-diffusion-3.5-large ### Image Edit * black-forest-labs/FLUX.1-Depth-dev * black-forest-labs/FLUX.1-Canny-dev * black-forest-labs/FLUX.1-Fill-dev ### Image Variation * black-forest-labs/FLUX.1-Redux-dev ## Usage Examples The Image API is compatible with the OpenAI Python SDK.Below is an example of how to use it. ### Image Generation #### Python Client ```python from openai import OpenAI import base64 client = OpenAI( base_url="https://api.netmind.ai/inference-api/openai/v1", api_key="", ) response = client.images.generate( model="black-forest-labs/FLUX.1-schnell", prompt="Generate a cup of coffee", response_format="b64_json" ) image_base64 = response.data[0].b64_json with open("generated_image.png", "wb") as f: f.write(base64.b64decode(image_base64)) ``` #### CURL Example ```sh # Set your API key export API_KEY="" curl -X POST "https://api.netmind.ai/inference-api/openai/v1/images/generations" \ -H "Content-Type: application/json" \ -H "Authorization: Bearer ${API_KEY}" \ -d '{ "model": "stabilityai/stable-diffusion-3.5-large", "prompt": "Generate a cup of coffee", "response_format": "b64_json" }' -o response.json cat response.json| jq -r ".data[0].b64_json" | base64 --decode > generated_image.png ``` ### Image Edit The `black-forest-labs/FLUX.1-Depth-dev` and `black-forest-labs/FLUX.1-Canny-dev` models do not require a mask file for image editing, whereas the `black-forest-labs/FLUX.1-Fill-dev` model necessitates a mask file to perform image modifications. #### Python Client ```python from openai import OpenAI import base64 client = OpenAI( base_url="https://api.netmind.ai/inference-api/openai/v1", api_key="", ) response = client.images.edit( model="black-forest-labs/FLUX.1-Fill-dev", image=open("image.png", "rb"), mask=open("mask.png", "rb"), prompt="Turn hair blue", response_format="b64_json", ) image_base64 = response.data[0].b64_json with open("generated_image.png", "wb") as f: f.write(base64.b64decode(image_base64)) ``` #### CURL Example ```sh # Set your API key export API_KEY="" curl -X POST "https://api.netmind.ai/inference-api/openai/v1/images/edits" \ -H "Authorization: Bearer ${API_KEY}" \ --form 'model="black-forest-labs/FLUX.1-Fill-dev"' \ --form 'prompt="Turn hair blue"' \ --form 'response_format="b64_json"' \ --form 'image=@"image.png"' \ --form 'mask=@"mask.png"' -o response.json cat response.json| jq -r ".data[0].b64_json" | base64 --decode > generated_image.png ``` ### Image Variation #### Python Client ```python from openai import OpenAI import base64 client = OpenAI( base_url="https://api.netmind.ai/inference-api/openai/v1", api_key="", ) response = client.images.create_variation( model="black-forest-labs/FLUX.1-Redux-dev", image=open("image.png", "rb"), response_format="b64_json", ) image_base64 = response.data[0].b64_json with open("generated_image.png", "wb") as f: f.write(base64.b64decode(image_base64)) ``` #### CURL Example ```sh # Set your API key export API_KEY="" curl -X POST "https://api.netmind.ai/inference-api/openai/v1/images/variations" \ -H "Authorization: Bearer ${API_KEY}" \ --form 'model="black-forest-labs/FLUX.1-Redux-dev"' \ --form 'response_format="b64_json"' \ --form 'image=@"image.png"' -o response.json cat response.json| jq -r ".data[0].b64_json" | base64 --decode > generated_image.png ``` ## Model Parameters ### Image Generation * `model`: ID of the model to use. (required) * `prompt`: A text description of the desired image(s). (required) * `size`: Image size, format is width x height. (optional) * `response_format`: The format in which the generated images are returned. Currently supports two options: b64\_json and url. If the url format is selected, please note that the URL will expire 24 hours after generation. Make sure to download the file before the expiration time. (optional) ### Image Edit * `model`: ID of the model to use. (required) * `prompt`: The prompt to use for image edit. (required) * `response_format`: The format in which the generated images are returned. Currently supports two options: b64\_json and url. If the url format is selected, please note that the URL will expire 24 hours after generation. Make sure to download the file before the expiration time. (optional) * `image`: The image to use for image edit. (required) * `mask`: The mask to use for image edit. (optional) ### Image Variation * `model`: ID of the model to use. (required) * `image`: The image to use for image variation. (required) * `response_format`: The format in which the generated images are returned. Currently supports two options: b64\_json and url. If the url format is selected, please note that the URL will expire 24 hours after generation. Make sure to download the file before the expiration time. (optional) --- # Agent Instructions: Querying This Documentation If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question. Perform an HTTP GET request on the current page URL with the `ask` query parameter: ``` GET https://netmind-power.gitbook.io/netmind-power-documentation/api/inference/images.md?ask= ``` The question should be specific, self-contained, and written in natural language. The response will contain a direct answer to the question and relevant excerpts and sources from the documentation. Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.