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future_plan.txt
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# filename: flux_consistent_integration_plan.txt
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## Phase 1: Abstraction & Unification Strategy
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- `FluxImageGenerator` uses `gradio_client` to interact with a remote Hugging Face space.
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- `IPAdapterRunner` is a local generation pipeline using diffusers + IP-Adapter.
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- Both support prompt-based image generation with customizable parameters (prompt, steps, cfg, seed, etc).
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### Goal
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Create a **unified wrapper** class or interface that allows flexible switching between:
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- **Online generation** (via Flux Gradio Space)
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- **Local consistent generation** (via IP-Adapter)
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---
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## Phase 2: Interface Unification Blueprint
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### Abstract base class: `ImageGeneratorInterface`
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```python
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class ImageGeneratorInterface:
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def generate(self, prompt: str, **kwargs) -> list[Image.Image]:
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raise NotImplementedError("Subclasses must implement 'generate'")
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Phase 3: Adapter Classes
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Adapter 1: FluxClientAdapter(ImageGeneratorInterface)
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Wraps FluxImageGenerator using its generate_image() method, returns PIL image list.
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Adapter 2: IPAdapterLocalAdapter(ImageGeneratorInterface)
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Wraps IPAdapterRunner, uses generate_text2img() or others, returns PIL image list.
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Phase 4: Switcher Logic
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Implement a GeneratorSwitcher or factory function that selects an adapter based on:
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User preference (e.g., "local" vs "remote")
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Availability (e.g., fallback to remote if CUDA unavailable)
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Scenario (e.g., "consistent generation" requires local IP-Adapter)
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Phase 5: Shared Prompt Configuration
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Create a shared PromptConfig dataclass:
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@dataclass
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class PromptConfig:
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prompt: str
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negative_prompt: str = ""
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steps: int = 35
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cfg_scale: float = 7.0
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seed: int = 42
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sampler: str = "DPM++ 2M Karras"
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strength: float = 0.7
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enhance_prompt_option: bool = False
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This ensures both adapters consume a common configuration object, simplifying switching and reproducibility.
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Phase 6: Optional Prompt Enhancers
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Support optional enhancements:
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Mistral/Nemo prompt enhancements (for FluxClient)
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IP-based guidance (for IPAdapterLocal)
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Phase 7: Next Steps...
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Draft interfaces & adapters for both pipelines
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Normalize return types to always return list of PIL.Image.Image
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Add support for preview grids via image_grid()
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Consider hybrid fallback/merging strategy
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➡️ Interested in getting a draft of the ImageGeneratorInterface and first adapter implementation?
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