The OpenAI SDK's legacy multipart path only accepts dall-e-2 when
raw bytes are passed. Wrapping in io.BytesIO with a name attribute
routes through the newer path that supports gpt-image-* models.
Also removes output_format from the edit call as that endpoint
does not support it.
- Rename ImageProvider to BlackForestProvider, TextProvider to MistralProvider
- Add get_provided_models() abstract method to Provider base class
- Move model lists from models.py into each provider's get_provided_models()
- Add providers/registry.py to aggregate models from all providers
- Extract infer_required_capabilities and resolve_model from config.py to resolve.py
- Update tests to use new names and import paths
The text provider now includes reference_images alongside inputs when
building prompts. Image files are sent as base64 data URLs via
ImageURLChunk for actual multimodal vision support, replacing the
previous [Attached image: ...] placeholder text.
Replace singular reference_image field with reference_images list to
support an arbitrary number of reference images. Map them to the correct
BFL API parameter names based on model family:
- flux-2-*: input_image, input_image_2, ..., input_image_8
- flux-kontext-*: input_image, input_image_2, ..., input_image_4
- flux 1.x: image_prompt (single)
BREAKING CHANGE: reference_image config field renamed to reference_images (list).
Implement bulkgen/providers/bfl.py with a fully async httpx-based client
that supports all current and future BFL models (including flux-2-*).
Remove the blackforest dependency and simplify the image provider by
eliminating the asyncio.to_thread wrapper.
