hf-mcp-server/packages/e2e-python/gradio-desc-kontext.json

{
    "tools": [
        {
            "name": "FLUX_1_Kontext_Dev_infer",
            "description": "Perform image editing using the FLUX.1 Kontext pipeline. This function takes an input image and a text prompt to generate a modified version of the image based on the provided instructions. It uses the FLUX.1 Kontext model for contextual image editing tasks. If a user passes a file as an input, use the upload_file_to_gradio tool, if present, to upload the file to the gradio app and create a Gradio File Input. Then use the returned path as the input to the tool. Returns: A 3-tuple containing:, PIL.Image.Image: The generated/edited image, int: The seed value used for generation (useful when randomize_seed=True), gr.update: Gradio update object to make the reuse button visible, , >>> edited_image, used_seed, button_update = infer(, ...     input_image=my_image,, ...     prompt=\"Add sunglasses\",, ...     seed=123,, ...     randomize_seed=False,, ...     guidance_scale=2.5, ... )",
            "inputSchema": {
                "type": "object",
                "properties": {
                    "input_image": {
                        "title": "ImageData",
                        "type": "string",
                        "description": "The input image to be edited. Will be converted",
                        "format": "Gradio File Input - a http or https url to a file"
                    },
                    "prompt": {
                        "type": "string",
                        "description": "Text description of the desired edit to apply to the image."
                    },
                    "seed": {
                        "type": "number",
                        "description": "Random seed for reproducible generation. Defaults to 42."
                    },
                    "randomize_seed": {
                        "type": "boolean",
                        "description": "If True, generates a random seed instead of",
                        "default": true
                    },
                    "guidance_scale": {
                        "type": "number",
                        "description": "Controls how closely the model follows the",
                        "default": 2.5
                    },
                    "steps": {
                        "type": "number",
                        "description": "Controls how many steps to run the diffusion model for.",
                        "default": 28
                    }
                }
            }
        },
        {
            "name": "FLUX_1_Kontext_Dev__lambda_",
            "description": " If a user passes a file as an input, use the upload_file_to_gradio tool, if present, to upload the file to the gradio app and create a Gradio File Input. Then use the returned path as the input to the tool",
            "inputSchema": {
                "type": "object",
                "properties": {
                    "image": {
                        "title": "ImageData",
                        "type": "string",
                        "format": "Gradio File Input - a http or https url to a file"
                    }
                }
            }
        }
    ]
}