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Tailored Generation
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Generate Structured Promp...

Overview

Tailored Generation provides capabilities to generate visuals (photos, illustrations, vectors) that preserve and faithfully reproduce specific IP elements or guidelines, ensuring consistency across all generated outputs.

The Tailored Generation APIs allow you to manage and train tailored models that maintain the integrity of your visual IP. You can train models through our Console or implement training directly via API. Explore the Console here.

Fully Automated Training Mode Bria supports users in training high-quality finetuned models without the guesswork. Based on the selected IP type & dataset, Bria automatically selects the right training parameters. This means that the user only needs to spend time curating their dataset.

Advanced Customization and Access: Bria offers 2 types of advanced training customization: Expert training mode and source-code & weights.

  • Expert training mode is for LoRa Finetune experts and provides the ability to finetune training parameters and upload larger training datasets.
  • Source-code & Weights is for developers seeking deeper customization and access to Bria’s source-available GenAI models via Hugging Face.

All methods allow full control over fine-tuning, pipeline creation, and integration into proprietary workflows—empowering AI teams to develop and optimize their own generative AI solutions.

The Tailored Generation Training API provides a set of endpoints to manage the entire lifecycle of a tailored generation project:

  1. Project Management: Create and manage projects that define IP characteristics:
  • Create and Retrieve Projects: Use the /projects endpoints to create a new project or retrieve existing projects that belong to your organization.
  • Define IP Type: Specify the IP type (e.g., multi_object_set, defined_character, stylized_scene) and medium.
  • Manage Project Details: Use the /projects/{id} endpoints to update or delete specific projects.
  1. Dataset Management: Organize and refine datasets within your projects:
  • Create and Retrieve Datasets: Use the /datasets endpoints to create new datasets or retrieve existing ones.
  • Generate a Visual Schema (FIBO Models)
    • Required for fibo training versions
    • Use /tailored-gen/generate_visual_schema to create a structured visual schema using 5-10 sample images.
  • Generate Caption Prefix (Legacy Models)
    • Use /tailored-gen/generate_prefix to create a text-based prefix for legacy training versions.
  • Refine Structured Data
    • Use /tailored-gen/refine_structured_prompt to iterate on your Visual Schema or Image Captions using natural language instructions.
    • Example: You can send your generated schema with the instruction "Character's name is Lucy" to improve the training metadata programmatically.
  • Upload and Manage Images:
    • Basic upload: Use /datasets/{dataset_id}/images to upload up to 200 images individually.
    • Bulk upload: Use /datasets/{dataset_id}/images/bulk to upload zip files with >200 high-quality images (Advanced).
  • Clone Datasets: Create variations of existing datasets using the clone functionality.
  1. Model Management: Train and optimize tailored models based on your datasets:
  • Create and Retrieve Models: Use the /models endpoints to create new models or list existing ones.
  • Choose training mode: Select between Fully automated mode (automatic training based on Bria's recipes) and Expert mode (for training parameter tweaking).
  • Choose Training version: Select "Fibo" for best results.
  • Monitor and Control: Manage the model lifecycle, including training start/stop, status monitoring, and version control over the training parameters.
  1. Generation Capabilities:
  • Image Generation: Use v2/image/generate/tailored (FIBO) or v1/text-to-image/tailored (Legacy).
  • Structured Prompting: Use v2/structured_prompt/generate/tailored to create structured prompts via VLM before generation.
  • Video Generation: Use /video/generate/tailored/image-to-video to animate tailored images.
Register and get API Access

Training Process

To train a tailored model:

  1. Create a Project: Use the /projects endpoint to define your IP type and medium.
  2. Create a Dataset: Use the /datasets endpoint to create a dataset within your project.
  3. Define Visual Identity:
    • Step A (Generate): Call /tailored-gen/generate_visual_schema, sampling 5-10 images from your input set.
    • Step B (Refine - Optional): Call /tailored-gen/refine_structured_prompt with the generated schema and instructions to tweak the definitions (e.g., "Remove references to blue background").
    • Step C (Apply): Update the dataset with the final schema using /datasets/{dataset_id}.
  4. Upload Images: Upload images using the /datasets/{dataset_id}/images or /datasets/{dataset_id}/images/bulk endpoints (minimum resolution: 1024x1024px).
  5. Prepare Dataset: Review auto-generated captions (you can also use refine_structured_prompt to fix specific image captions) and update the dataset status to 'completed'.
  6. Create Model: Use the /models endpoint to create a model, which requires a training mode and version.
  7. Start Training: Initiate training via the /models/{id}/start_training endpoint. Training typically takes 4-6 hours.
  8. Monitor Progress: Check the training status using the /models/{id} endpoint until training is 'Completed'.
  9. Generate Images:
  • Use v2/image/generate/tailored for text-to-image generation.

Alternatively, manage and train tailored models through Bria's user-friendly Console.
Get started here.

Download OpenAPI description
tailored-generation.json
tailored-generation.yaml
Languages
Servers
https://engine.prod.bria-api.com/v2
https://engine.prod.bria-api.com/v1

Project

Manage your projects

Operations

Dataset

Manage training datasets

Operations

Model

Manage and train models

Operations

Image Generation V2

Generation using FIBO models

Operations

Generate Image - Tailored Model (V2)

Request

Description

Generates a new image using a tailored model trained using the FIBO training version.

This endpoint translates your input (prompt and/or structured_prompt) into a structured JSON prompt using the state-of-the-art Gemini 2.5 Flash VLM bridge. It internally uses the model's visual schema (backbone) to ensure the generated image matches your trained visual identity.

The response includes both the final image_url and the structured_prompt (JSON).

Input Combination Rules The request body must include one of the following mutually exclusive combinations:

  • prompt: Generates a new image from text.
  • structured_prompt: Recreates a previous image exactly (requires seed).
  • structured_prompt + prompt: Refines a previous image using new text instructions.

Model Compatibility:

  • Supports ONLY models with training_version = 'fibo'.
  • Legacy models (light, max, bria-2.3, bria-3.2) are NOT supported here.
Headers
api_tokenstringrequired
Bodyapplication/json
tailored_model_idstringrequired

The ID of the tailored model (must have training_version = 'fibo').

tailored_model_influencenumber(float)[ 0 .. 1.5 ]

Controls the strength of the tailored model's influence (0.0 - 1.5).

Default 1
promptstring

Text-based instruction for generation or refinement.

structured_promptstring

A string containing the structured prompt in JSON format for precise recreation/refinement.

negative_promptstring

Concepts to exclude from the generated image.

guidance_scaleinteger[ 3 .. 5 ]

Adherence to the prompt (3-5).

Default 5
aspect_ratiostring
Default "1:1"
Enum"1:1""2:3""3:2""3:4""4:3""4:5""5:4""9:16""16:9"
steps_numinteger[ 20 .. 50 ]
Default 50
seedinteger

Seed for deterministic generation.

syncboolean

If false, returns a 202 and status URL. If true, returns 200 with result.

Default false
prompt_content_moderationboolean
Default true
visual_output_content_moderationboolean
Default true
curl -i -X POST \
  https://engine.prod.bria-api.com/v2/image/generate/tailored \
  -H 'Content-Type: application/json' \
  -H 'api_token: string' \
  -d '{
    "tailored_model_id": "model_fibo_123",
    "prompt": "A product photo in the brand'\''s visual style"
  }'

Responses

Successful operation (Synchronous).

Bodyapplication/json
image_urlstring
structured_promptstring
Response
application/json
{
  "image_url": "string",
  "structured_prompt": "string"
}

Generate Structured Prompt - Tailored Model (V2)

Request

Description

Creates a new detailed, machine-readable structured prompt in JSON format or refines an existing one using text inputs and a tailored model's visual schema (backbone).

This endpoint uses the state-of-the-art Gemini 2.5 Flash VLM bridge. The tailored model's visual schema is provided as input to Gemini along with the user prompt to generate the structured prompt.

It returns ONLY the JSON string and does not generate an image.

Use Cases:

  • Control & Auditability: Inspect or programmatically edit the JSON before generating an image.
  • Consistency: Generate one structured_prompt and pass it to /image/generate/tailored multiple times.
  • Hybrid Deployment: Use Bria's VLM bridge via API while hosting the FIBO image model on a private cloud.

Input Combination Rules The request body must use exactly one of the following combinations:

  • Text Only: prompt
  • Structured Prompt and Text: structured_prompt and prompt (Refinement)

Model Compatibility:

  • Supports ONLY models with training_version = 'fibo'.
  • Legacy models are NOT supported.
Headers
api_tokenstringrequired
Bodyapplication/json
tailored_model_idstringrequired

The ID of the tailored model (must have training_version = 'fibo').

promptstring

Text-based instruction.

structured_promptstring

JSON string from a previous response for refinement.

seedinteger

Seed for deterministic generation.

syncboolean

If false, returns 202. If true, returns 200.

Default false
prompt_content_moderationboolean
Default true
curl -i -X POST \
  https://engine.prod.bria-api.com/v2/structured_prompt/generate/tailored \
  -H 'Content-Type: application/json' \
  -H 'api_token: string' \
  -d '{
    "tailored_model_id": "model_fibo_123",
    "prompt": "A product photo in the brand'\''s visual style"
  }'

Responses

Successful operation (Synchronous).

Bodyapplication/json
structured_promptstring

The generated structured prompt JSON string.

Response
application/json
{
  "structured_prompt": "string"
}

Image Generation (Legacy)

Generation using Legacy models

Operations

Video Generation

Image-to-Video capabilities

Operations