89 lines
2.8 KiB
Python
89 lines
2.8 KiB
Python
"""BlackForestLabs image generation provider."""
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from __future__ import annotations
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import base64
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from pathlib import Path
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from typing import override
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import httpx
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from bulkgen.config import TargetConfig
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from bulkgen.providers import Provider
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from bulkgen.providers.bfl import BFLClient
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from bulkgen.providers.models import ModelInfo
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def _encode_image_b64(path: Path) -> str:
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"""Read an image file and return its base64-encoded representation."""
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return base64.b64encode(path.read_bytes()).decode("ascii")
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# Parameter names for reference images, keyed by model prefix.
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_INPUT_IMAGE_KEYS = ["input_image"] + [f"input_image_{i}" for i in range(2, 9)]
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_IMAGE_PROMPT_KEYS = ["image_prompt"]
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def _ref_image_keys(model: str) -> list[str]:
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"""Return the ordered API parameter names for reference images."""
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if model.startswith("flux-2-"):
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return _INPUT_IMAGE_KEYS # up to 8
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if model.startswith("flux-kontext-"):
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return _INPUT_IMAGE_KEYS[:4] # up to 4
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return _IMAGE_PROMPT_KEYS # flux 1.x: single image_prompt
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def _add_reference_images(
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inputs: dict[str, object],
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reference_images: list[str],
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model: str,
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project_dir: Path,
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) -> None:
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"""Encode reference images and add them under the correct API keys."""
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keys = _ref_image_keys(model)
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for key, ref_name in zip(keys, reference_images, strict=False):
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inputs[key] = _encode_image_b64(project_dir / ref_name)
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class ImageProvider(Provider):
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"""Generates images via the BlackForestLabs API."""
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_client: BFLClient
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def __init__(self, api_key: str) -> None:
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self._client = BFLClient(api_key=api_key)
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@override
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async def generate(
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self,
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target_name: str,
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target_config: TargetConfig,
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resolved_prompt: str,
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resolved_model: ModelInfo,
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project_dir: Path,
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) -> None:
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output_path = project_dir / target_name
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inputs: dict[str, object] = {"prompt": resolved_prompt}
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if target_config.width is not None:
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inputs["width"] = target_config.width
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if target_config.height is not None:
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inputs["height"] = target_config.height
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if target_config.reference_images:
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_add_reference_images(
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inputs, target_config.reference_images, resolved_model.name, project_dir
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)
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for control_name in target_config.control_images:
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ctrl_path = project_dir / control_name
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inputs["control_image"] = _encode_image_b64(ctrl_path)
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result = await self._client.generate(resolved_model.name, inputs)
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async with httpx.AsyncClient() as http:
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response = await http.get(result.sample_url)
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_ = response.raise_for_status()
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_ = output_path.write_bytes(response.content)
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