# Generate Vector Graphics - Fast (Beta) This Vector Generation pipeline is optimized for speed, enabling builders to quickly integrate the generation of high-quality, editable vector graphic assets into their products or workflows. It leverages Bria’s proprietary text-to-image foundation models, enhanced to accelerate output while maintaining control and flexibility. The pipeline supports generation of scalable assets such as icons, logos, and illustrations, making it ideal for use cases that require rapid delivery of vector graphics. : An icon of a bird with a blue head and yellow beak against a solid background This API endpoint supports content moderation via an optional parameter that can prevent generation if input images contain inappropriate content, and filters out unsafe generated images - the first blocked input image will fail the entire request. Endpoint: POST /text-to-vector/fast/{model_version} ## Path parameters: - `model_version` (string, required) The model version you would like to use in the request. Enum: "2.3" ## Header parameters: - `api_token` (string, required) ## Request fields (application/json): - `prompt` (string) The prompt you would like to use to generate images. Bria currently supports prompts in English only, excluding special characters. - `num_results` (integer) How many images you would like to generate. - `aspect_ratio` (string) The aspect ratio of the image. When a ControlNet is being used, the aspect ratio is defined by the guidance image and this parameter is ignored. Enum: "1:1", "2:3", "3:2", "3:4", "4:3", "4:5", "5:4", "9:16", "16:9" - `sync` (boolean) Determines the response mode. When true, responses are synchronous. With false, responses are asynchronous, immediately providing URLs for images that are generated in the background. Use polling for the URLs to retrieve images once ready. - `seed` (integer) You can choose whether you want your generated result to be random or predictable. You can recreate the same result in the future by using the seed value of a result from the response with the prompt, model type and model version. You can exclude this parameter if you are not interested in recreating your results. This parameter is optional. - `steps_num` (integer) The number of iterations the model goes through to refine the generated image. This parameter is optional. - `prompt_content_moderation` (boolean) When enabled (default: true), the input prompt is scanned for NSFW or ethically restricted terms before image generation. If the prompt violates Bria's ethical guidelines, the request will be rejected with a 408 error. - `content_moderation` (boolean) When enabled, applies content moderation to both input visuals and generated outputs. For input images: - Processing stops at the first image that fails moderation - Returns a 422 error with details about which parameter failed For synchronous requests (sync=true): - If all generated images fail moderation, returns a 422 error - If some images pass and others fail, returns a 200 response with successful generations and "blocked" objects for failed ones For asynchronous requests (sync=false): - Failed images are replaced with zero-byte files at their placeholder URLs - Successful images are stored at their original placeholder URLs - `ip_signal` (boolean) Flags prompts with potential IP content. If detected, a warning will be included in the response. - `guidance_method_1` (string) Which guidance type you would like to include in the generation. Up to 2 guidance methods can be combined during a single inference. This parameter is optional. Enum: "controlnet_canny", "controlnet_depth", "controlnet_recoloring", "controlnet_color_grid" - `guidance_method_1_scale` (number) The impact of the guidance. - `guidance_method_1_image_file` (string) The image that should be used as guidance, in base64 format, with the method defined in guidance_method_1. Accepted formats are jpeg, jpg, png, webp. Maximum file size 12MB. If more then one guidance method is used, all guidance images must be of the same aspect ratio, and this will be the aspect ratio of the generated results. If guidance_method_1 is selected, an image must be provided. - `guidance_method_2` (string) Which guidance type you would like to include in the generation. Up to 2 guidance methods can be combined during a single inference. This parameter is optional. Enum: "controlnet_canny", "controlnet_depth", "controlnet_recoloring", "controlnet_color_grid" - `guidance_method_2_scale` (number) The impact of the guidance. - `guidance_method_2_image_file` (string) The image that should be used as guidance, in base64 format, with the method defined in guidance_method_2. Accepted formats are jpeg, jpg, png, webp. Maximum file size 12MB. If more then one guidance method is used, all guidance images must be of the same aspect ratio, and this will be the aspect ratio of the generated results. If guidance_method_1 is selected, an image must be provided. - `image_prompt_mode` (string) - : Uses the image’s content, style elements, and color palette to guide generation. - : Uses the image’s high-level style elements and color palette to influence the generated output. Enum: "regular", "style_only" - `image_prompt_file` (string) The image file to be used as guidance, in base64 format. Accepted formats are jpeg, jpg, png, webp. Maximum file size 12MB. This image can be of any aspect ratio, even when it's not alligned with the one defined in the parameter 'aspect_ratio' or by visuals provided to the ControlNets. - `image_prompt_urls` (array) A list of URLs of images that should be used as guidance. The images can be of different aspect ratios. Accepted formats are jpeg, jpg, png, webp. The URLs should point to accessible, publicly available images. - `image_prompt_scale` (number) The impact of the provided image on the generated results. A value between 0.0 (no impact) and 1.0 (full impact). ## Response 209 fields (application/json): - `result` (array) There are multiple objects in this array (based on the amount specified in num_results) and each object represents a single image or a blocked result.