Brainiall Image

Remove the background from an image. Uses Brainiall Cutout engine segmentation to precisely separate foreground from background. Returns a base64-encoded image with transparent background (PNG) or white background (WebP). Sub-500ms latency on GPU. Args: image_base64: Base64-encoded image data (PNG, JPEG, or WebP). output_format: Output format -- 'png' (with transparency) or 'webp'. Returns: dict with keys: - image_base64 (str): Base64-encoded result image - format (str): Output image format - original_size (dict): Original width and height - processing_ms (int): Processing time in milliseconds

{
  "type": "object",
  "properties": {
    "image_base64": {
      "description": "Base64-encoded image data. Supports PNG, JPEG, and WebP formats.",
      "maxLength": 20000000,
      "type": "string"
    },
    "output_format": {
      "default": "png",
      "description": "Output image format: 'png' (default, with transparency) or 'webp'",
      "type": "string"
    }
  },
  "required": [
    "image_base64"
  ]
}

Upscale image resolution with the Brainiall image-upscaling engine. Enhances image resolution by 2x or 4x with the GPU-accelerated Brainiall image-upscaling engine super-resolution. Processes in tiles (256x256) to manage VRAM. Maximum output dimension: 8192x8192. Args: image_base64: Base64-encoded image data (PNG, JPEG, or WebP). scale: Upscale factor -- 2 or 4 (default: 4). Returns: dict with keys: - image (str): Base64-encoded upscaled image - format (str): Output image format - width (int): Output width - height (int): Output height - scale (int): Scale factor applied - processing_time_ms (float): Processing time in milliseconds

{
  "type": "object",
  "properties": {
    "image_base64": {
      "description": "Base64-encoded image data. Supports PNG, JPEG, and WebP formats.",
      "maxLength": 20000000,
      "type": "string"
    },
    "scale": {
      "default": 4,
      "description": "Upscale factor: 2 or 4 (default: 4)",
      "type": "integer"
    }
  },
  "required": [
    "image_base64"
  ]
}

Restore and enhance faces in an image with the Brainiall face-restoration engine. Detects all faces via RetinaFace, restores quality (fixes blur, noise, compression artifacts), and pastes them back. Optionally enhances the background with the Brainiall image-upscaling engine. GPU-accelerated, sub-3s latency. Args: image_base64: Base64-encoded image data containing faces (PNG, JPEG, WebP). upscale: Output upscale factor -- 1 to 4 (default: 2). enhance_background: Whether to enhance background with the Brainiall image-upscaling engine (default: true). Returns: dict with keys: - image (str): Base64-encoded restored image - format (str): Output image format - width (int): Output width - height (int): Output height - upscale (int): Scale factor applied - processing_time_ms (float): Processing time in milliseconds

{
  "type": "object",
  "properties": {
    "image_base64": {
      "description": "Base64-encoded image data containing one or more faces.",
      "maxLength": 20000000,
      "type": "string"
    },
    "upscale": {
      "default": 2,
      "description": "Output upscale factor: 1-4 (default: 2)",
      "type": "integer"
    },
    "enhance_background": {
      "default": true,
      "description": "Enhance background with the Brainiall image-upscaling engine (default: true)",
      "type": "boolean"
    }
  },
  "required": [
    "image_base64"
  ]
}

Check health status of Image API services and loaded models. Returns: dict with keys: - status (str): 'healthy' or error state - models (dict): Loaded model status per capability - version (str): API version

{
  "type": "object",
  "properties": {}
}

Turn a document image into structured fields. doc_type picks the schema (receipt/invoice/id/contract/form/generic). A page with no readable text returns an error rather than a guess. Returns: dict with keys: doc_type (str), fields (dict — null for any value not present), text (str — the recognised plain text).

{
  "type": "object",
  "properties": {
    "image": {
      "description": "Base64-encoded PNG/JPEG of a single document page",
      "type": "string"
    },
    "doc_type": {
      "default": "generic",
      "description": "The document kind — picks the field schema: receipt | invoice | id | contract | form | generic | business_card | w2 | health_card | mortgage | pay_stub",
      "type": "string"
    }
  },
  "required": [
    "image"
  ]
}

Ask a natural-language question about a document image; returns a grounded answer plus the supporting line. Returns found:false rather than guessing when the document doesn't contain the answer. Returns: dict with keys: answer (str|null), found (bool), supporting_text (str|null), text (str).

{
  "type": "object",
  "properties": {
    "image": {
      "description": "Base64-encoded PNG/JPEG of the document page",
      "type": "string"
    },
    "question": {
      "description": "The natural-language question about the document",
      "maxLength": 1000,
      "type": "string"
    }
  },
  "required": [
    "image",
    "question"
  ]
}

Reconstruct every table in a document image into headers and rows. Returns: dict with keys: table_count (int), tables (list of {title, headers, rows, row_count, column_count}); [] if there are no tables.

{
  "type": "object",
  "properties": {
    "image": {
      "description": "Base64-encoded PNG/JPEG of the document page",
      "type": "string"
    }
  },
  "required": [
    "image"
  ]
}

Return the document as structured Markdown (headings, tables, lists, code blocks, math). Brainiall Doc Layout engine. The single API for converting documents to LLM-friendly format.

{
  "type": "object",
  "properties": {
    "pdf": {
      "description": "Base64-encoded PDF document",
      "type": "string"
    },
    "page_range": {
      "anyOf": [
        {
          "type": "string"
        },
        {
          "type": "null"
        }
      ],
      "default": null,
      "description": "Page range like '1,2,5-10' or null for all pages"
    }
  },
  "required": [
    "pdf"
  ]
}

Run a multi-skill enrichment pipeline over a document image or text in one call. Brainiall Skillsets engine. Returns per-skill outputs ready for indexing or RAG.

{
  "type": "object",
  "properties": {
    "image": {
      "anyOf": [
        {
          "type": "string"
        },
        {
          "type": "null"
        }
      ],
      "default": null,
      "description": "Base64 image (triggers OCR)"
    },
    "text": {
      "anyOf": [
        {
          "type": "string"
        },
        {
          "type": "null"
        }
      ],
      "default": null,
      "description": "Pre-extracted text (skip OCR)"
    },
    "skills": {
      "anyOf": [
        {
          "items": {
            "type": "string"
          },
          "type": "array"
        },
        {
          "type": "null"
        }
      ],
      "default": null,
      "description": "Enrichment skills: ocr | entities | language | keyphrases | sentiment"
    }
  }
}

Multimodal extraction. Send an image, text, or both; define your schema of fields; get structured JSON. Brainiall Content Understanding engine. Unified multimodal field extraction over images and text.

{
  "type": "object",
  "properties": {
    "image": {
      "anyOf": [
        {
          "type": "string"
        },
        {
          "type": "null"
        }
      ],
      "default": null,
      "description": "Optional base64 image (will OCR first)"
    },
    "text": {
      "anyOf": [
        {
          "type": "string"
        },
        {
          "type": "null"
        }
      ],
      "default": null,
      "description": "Optional pre-extracted text"
    },
    "field_schema": {
      "anyOf": [
        {
          "additionalProperties": true,
          "type": "object"
        },
        {
          "type": "null"
        }
      ],
      "default": null,
      "description": "Map of field_name -> description, e.g. {\"invoice_id\":\"invoice number\",\"total\":\"amount due\"}"
    }
  }
}