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Update app.py
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app.py
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@@ -9,29 +9,32 @@ from PIL import Image
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# Import the pipeline from diffusers
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from diffusers import FluxKontextPipeline
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# --- Constants
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MAX_SEED = np.iinfo(np.int32).max
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#
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pipe = FluxKontextPipeline.from_pretrained(
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"black-forest-labs/FLUX.1-Kontext-dev",
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torch_dtype=torch.bfloat16,
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).to("cuda")
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except Exception as e:
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pipe = None
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print(f"Warning: Could not load the model on CUDA. GPU is required. Error: {e}")
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def chat_fn(message, chat_history, seed, randomize_seed, guidance_scale, steps, progress=gr.Progress(track_tqdm=True)):
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"""
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Performs image generation or editing based on user input from the chat interface.
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"""
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prompt = message["text"]
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files = message["files"]
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@@ -62,6 +65,10 @@ def chat_fn(message, chat_history, seed, randomize_seed, guidance_scale, steps,
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num_inference_steps=steps,
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generator=generator,
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).images[0]
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return image
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@@ -72,8 +79,7 @@ randomize_checkbox = gr.Checkbox(label="Randomize seed", value=False)
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guidance_slider = gr.Slider(label="Guidance Scale", minimum=1.0, maximum=10.0, step=0.1, value=2.5)
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steps_slider = gr.Slider(label="Steps", minimum=1, maximum=30, value=28, step=1)
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# ---
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# Instead, provide text-only examples that work without external image dependencies
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examples = [
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[
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{"text": "A cute robot reading a book in a cozy library", "files": []},
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@@ -93,7 +99,7 @@ demo = gr.ChatInterface(
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fn=chat_fn,
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title="FLUX.1 Kontext [dev]",
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description="""<p style='text-align: center;'>
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A simple chat UI for the <b>FLUX.1 Kontext</b> model.
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<br>
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To edit an image, upload it and type your instructions (e.g., "Add a hat").
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<br>
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# Import the pipeline from diffusers
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from diffusers import FluxKontextPipeline
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# --- Constants ---
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MAX_SEED = np.iinfo(np.int32).max
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# --- Global pipeline variable ---
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pipe = None
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def load_model():
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"""Load the model on CPU first, then move to GPU when needed"""
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global pipe
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if pipe is None:
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pipe = FluxKontextPipeline.from_pretrained(
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"black-forest-labs/FLUX.1-Kontext-dev",
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torch_dtype=torch.bfloat16,
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)
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return pipe
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# --- Core Inference Function for ChatInterface ---
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@spaces.GPU(duration=120) # Set duration based on expected inference time
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def chat_fn(message, chat_history, seed, randomize_seed, guidance_scale, steps, progress=gr.Progress(track_tqdm=True)):
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"""
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Performs image generation or editing based on user input from the chat interface.
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"""
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# Load and move model to GPU within the decorated function
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pipe = load_model()
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pipe = pipe.to("cuda")
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prompt = message["text"]
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files = message["files"]
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num_inference_steps=steps,
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generator=generator,
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).images[0]
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# Move model back to CPU to free GPU memory
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pipe = pipe.to("cpu")
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torch.cuda.empty_cache()
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return image
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guidance_slider = gr.Slider(label="Guidance Scale", minimum=1.0, maximum=10.0, step=0.1, value=2.5)
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steps_slider = gr.Slider(label="Steps", minimum=1, maximum=30, value=28, step=1)
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# --- Examples without external URLs ---
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examples = [
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[
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{"text": "A cute robot reading a book in a cozy library", "files": []},
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fn=chat_fn,
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title="FLUX.1 Kontext [dev]",
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description="""<p style='text-align: center;'>
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A simple chat UI for the <b>FLUX.1 Kontext</b> model running on ZeroGPU.
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<br>
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To edit an image, upload it and type your instructions (e.g., "Add a hat").
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<br>
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