Spaces:
Running
Running
| import gradio as gr | |
| from gradio_client import Client | |
| import numpy as np | |
| MAX_SEED = np.iinfo(np.int32).max | |
| MAX_IMAGE_SIZE = 2048 | |
| flux_1_schell_spaces = [ | |
| "https://black-forest-labs-flux-1-schnell.hf.space", | |
| "ChristianHappy/FLUX.1-schnell", | |
| "innoai/FLUX.1-schnell", | |
| "tuan2308/FLUX.1-schnell", | |
| "FiditeNemini/FLUX.1-schnell" | |
| ] | |
| client = None | |
| job = None | |
| def infer(selected_space, prompt, seed=42, randomize_seed=False, width=1024, height=1024, | |
| num_inference_steps=4, progress=gr.Progress(track_tqdm=True)): | |
| global job | |
| global client | |
| if client is None: | |
| try: | |
| client = Client(selected_space) | |
| print(f"Loaded custom model from {selected_space}") | |
| except ValueError as e: | |
| client = None | |
| print(f"Failed to load custom model from {selected_space}: {e}") | |
| raise gr.Error("Failed to load client after trying all spaces.") | |
| try: | |
| job = client.submit( | |
| prompt=prompt, | |
| seed=seed, | |
| randomize_seed=randomize_seed, | |
| width=width, | |
| height=height, | |
| num_inference_steps=num_inference_steps, | |
| api_name="/infer" | |
| ) | |
| result = job.result() | |
| except ValueError as e: | |
| client = None | |
| raise gr.Error(e) | |
| return result | |
| css = """ | |
| #col-container { | |
| margin: 0 auto; | |
| max-width: 520px; | |
| } | |
| """ | |
| with gr.Blocks(css=css) as demo: | |
| selected_space_index = gr.State(0) | |
| with gr.Column(elem_id="col-container"): | |
| space = gr.Radio( | |
| flux_1_schell_spaces, | |
| label="Choose Your Model", | |
| value=flux_1_schell_spaces[0] | |
| ) | |
| with gr.Row(): | |
| prompt = gr.Text( | |
| label="Prompt", | |
| show_label=False, | |
| max_lines=1, | |
| placeholder="Enter your prompt", | |
| container=False, | |
| value="beautiful sexy woman, at the beach, relaxing, dreamy, highly detailed, big boobs, realistic lighting, sharp focus" | |
| ) | |
| run_button = gr.Button("Run", scale=0) | |
| result = gr.Image(label="Result", show_label=False) | |
| with gr.Accordion("Advanced Settings", open=False): | |
| seed = gr.Slider( | |
| label="Seed", | |
| minimum=0, | |
| maximum=MAX_SEED, | |
| step=1, | |
| value=0, | |
| ) | |
| randomize_seed = gr.Checkbox(label="Randomize seed", value=True) | |
| with gr.Row(): | |
| width = gr.Slider( | |
| label="Width", | |
| minimum=256, | |
| maximum=MAX_IMAGE_SIZE, | |
| step=32, | |
| value=1024, | |
| ) | |
| height = gr.Slider( | |
| label="Height", | |
| minimum=256, | |
| maximum=MAX_IMAGE_SIZE, | |
| step=32, | |
| value=1024, | |
| ) | |
| with gr.Row(): | |
| num_inference_steps = gr.Slider( | |
| label="Number of inference steps", | |
| minimum=1, | |
| maximum=50, | |
| step=1, | |
| value=4, | |
| ) | |
| gr.on( | |
| triggers=[run_button.click, prompt.submit], | |
| fn=infer, | |
| inputs=[ | |
| space, | |
| prompt, | |
| seed, | |
| randomize_seed, | |
| width, | |
| height, | |
| num_inference_steps | |
| ], | |
| outputs=[result, seed] | |
| ) | |
| with gr.Row(): | |
| gr.Markdown(""" | |
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| """) | |
| demo.launch(share=True) |