Create app.py

app.py

@@ -0,0 +1,86 @@
+import gradio as gr
+import requests
+from PIL import Image
+import io
+import os
+from fal_client import submit
+
+def set_fal_key(api_key):
+    os.environ["FAL_KEY"] = api_key
+    return "FAL API key set successfully!"
+
+def generate_image(api_key, model, prompt, image_size, num_inference_steps, guidance_scale, num_images, safety_tolerance, enable_safety_checker, seed):
+    set_fal_key(api_key)
+    
+    arguments = {
+        "prompt": prompt,
+        "image_size": image_size,
+        "num_inference_steps": num_inference_steps,
+        "num_images": num_images,
+    }
+
+    if model == "Flux Pro":
+        arguments["guidance_scale"] = guidance_scale
+        arguments["safety_tolerance"] = safety_tolerance
+        fal_model = "fal-ai/flux-pro"
+    elif model == "Flux Dev":
+        arguments["guidance_scale"] = guidance_scale
+        arguments["enable_safety_checker"] = enable_safety_checker
+        fal_model = "fal-ai/flux/dev"
+    else:  # Flux Schnell
+        arguments["enable_safety_checker"] = enable_safety_checker
+        fal_model = "fal-ai/flux/schnell"
+
+    if seed != -1:
+        arguments["seed"] = seed
+
+    try:
+        handler = submit(fal_model, arguments=arguments)
+        result = handler.get()
+        images = []
+        for img_info in result["images"]:
+            img_url = img_info["url"]
+            img_response = requests.get(img_url)
+            img = Image.open(io.BytesIO(img_response.content))
+            images.append(img)
+        return images
+    except Exception as e:
+        return [Image.new('RGB', (512, 512), color='black')]
+
+def update_visible_components(model):
+    if model == "Flux Pro":
+        return [gr.update(visible=True), gr.update(visible=True), gr.update(visible=False)]
+    elif model == "Flux Dev":
+        return [gr.update(visible=True), gr.update(visible=False), gr.update(visible=True)]
+    else:  # Flux Schnell
+        return [gr.update(visible=False), gr.update(visible=False), gr.update(visible=True)]
+
+with gr.Blocks() as demo:
+    gr.Markdown("# Flux Image Generation")
+    
+    api_key = gr.Textbox(type="password", label="FAL API Key")
+    
+    with gr.Row():
+        model = gr.Dropdown(choices=["Flux Pro", "Flux Dev", "Flux Schnell"], label="Model", value="Flux Pro")
+        image_size = gr.Dropdown(choices=["square_hd", "square", "portrait_4_3", "portrait_16_9", "landscape_4_3", "landscape_16_9"], label="Image Size", value="landscape_4_3")
+    
+    prompt = gr.Textbox(label="Prompt", lines=3)
+    num_inference_steps = gr.Slider(1, 100, value=28, step=1, label="Number of Inference Steps")
+    guidance_scale = gr.Slider(0, 20, value=3.5, step=0.1, label="Guidance Scale")
+    num_images = gr.Slider(1, 10, value=1, step=1, label="Number of Images")
+    safety_tolerance = gr.Dropdown(choices=["1", "2", "3", "4", "5", "6"], label="Safety Tolerance", value="2")
+    enable_safety_checker = gr.Checkbox(label="Enable Safety Checker", value=True)
+    seed = gr.Number(label="Seed", value=-1)
+
+    generate_button = gr.Button("Generate Images")
+    output_images = gr.Gallery(label="Generated Images")
+
+    model.change(update_visible_components, inputs=[model], outputs=[guidance_scale, safety_tolerance, enable_safety_checker])
+
+    generate_button.click(
+        generate_image,
+        inputs=[api_key, model, prompt, image_size, num_inference_steps, guidance_scale, num_images, safety_tolerance, enable_safety_checker, seed],
+        outputs=output_images
+    )
+
+demo.launch()