Update app.py

app.py

@@ -16,179 +16,68 @@ list_models = [
     "Midjourney-V4-XL",
 ]
 
-def generate_txt2img(current_model, prompt, is_negative=False, image_style="None style", steps=50, cfg_scale=7,
-                     seed=None):
-
-    if current_model == "SD-1.5":
-        API_URL = "https://api-inference.huggingface.co/models/runwayml/stable-diffusion-v1-5"
-    elif current_model == "SDXL-1.0":
-        API_URL = "https://api-inference.huggingface.co/models/stabilityai/stable-diffusion-xl-base-1.0"
-    elif current_model == "OpenJourney-V4":
-        API_URL = "https://api-inference.huggingface.co/models/prompthero/openjourney"       
-    elif current_model == "Anything-V4":
-        API_URL = "https://api-inference.huggingface.co/models/xyn-ai/anything-v4.0" 
-    elif current_model == "Disney-Pixar-Cartoon":
-        API_URL = "https://api-inference.huggingface.co/models/stablediffusionapi/disney-pixar-cartoon"
-    elif current_model == "Pixel-Art-XL":
-        API_URL = "https://api-inference.huggingface.co/models/nerijs/pixel-art-xl"
-    elif current_model == "Dalle-3-XL":
-        API_URL = "https://api-inference.huggingface.co/models/openskyml/dalle-3-xl"
-    elif current_model == "Midjourney-V4-XL":
-        API_URL = "https://api-inference.huggingface.co/models/openskyml/midjourney-v4-xl"    
-
-    API_TOKEN = os.environ.get("HF_READ_TOKEN")
-    headers = {"Authorization": f"Bearer {API_TOKEN}"}
-
-
-    if image_style == "None style":
-        payload = {
-            "inputs": prompt + ", 8k",
-            "is_negative": is_negative,
-            "steps": steps,
-            "cfg_scale": cfg_scale,
-            "seed": seed if seed is not None else random.randint(-1, 2147483647)
-        }
-    elif image_style == "Cinematic":
-        payload = {
-            "inputs": prompt + ", realistic, detailed, textured, skin, hair, eyes, by Alex Huguet, Mike Hill, Ian Spriggs, JaeCheol Park, Marek Denko",
-            "is_negative": is_negative + ", abstract, cartoon, stylized",
-            "steps": steps,
-            "cfg_scale": cfg_scale,
-            "seed": seed if seed is not None else random.randint(-1, 2147483647)
-        }
-    elif image_style == "Digital Art":
-        payload = {
-            "inputs": prompt + ", faded , vintage , nostalgic , by Jose Villa , Elizabeth Messina , Ryan Brenizer , Jonas Peterson , Jasmine Star",
-            "is_negative": is_negative + ", sharp , modern , bright",
-            "steps": steps,
-            "cfg_scale": cfg_scale,
-            "seed": seed if seed is not None else random.randint(-1, 2147483647)
-        }
-    elif image_style == "Portrait":
-        payload = {
-            "inputs": prompt + ", soft light, sharp, exposure blend, medium shot, bokeh, (hdr:1.4), high contrast, (cinematic, teal and orange:0.85), (muted colors, dim colors, soothing tones:1.3), low saturation, (hyperdetailed:1.2), (noir:0.4), (natural skin texture, hyperrealism, soft light, sharp:1.2)",
-            "is_negative": is_negative,
-            "steps": steps,
-            "cfg_scale": cfg_scale,
-            "seed": seed if seed is not None else random.randint(-1, 2147483647)
-        }
-
-    image_bytes = requests.post(API_URL, headers=headers, json=payload).content
-    image = Image.open(io.BytesIO(image_bytes))
-    return image
-
+# Your generate_txt2img function
+def generate_txt2img(current_model, prompt, is_negative, image_style, steps, cfg_scale, seed):
+    # ... (Your function implementation)
 
+# Enhanced CSS for better styling
 css = """
-/* General Container Styles */
+body {
+    font-family: 'Helvetica Neue', sans-serif;
+    background-color: #f7f8fa;
+}
 .gradio-container {
-    font-family: 'IBM Plex Sans', sans-serif;
-    max-width: 730px !important;
+    max-width: 800px;
     margin: auto;
-    padding-top: 1.5rem;
-}
-
-/* Button Styles */
-.gr-button {
-    color: white;
-    border-color: black;
-    background: black;
-    white-space: nowrap;
-}
-
-.gr-button:focus {
-    border-color: rgb(147 197 253 / var(--tw-border-opacity));
-    outline: none;
-    box-shadow: var(--tw-ring-offset-shadow), var(--tw-ring-shadow), var(--tw-shadow, 0 0 #0000);
-    --tw-border-opacity: 1;
-    --tw-ring-offset-shadow: var(--tw-ring-inset) 0 0 0 var(--tw-ring-offset-width) var(--tw-ring-offset-color);
-    --tw-ring-shadow: var(--tw-ring-inset) 0 0 0 calc(3px var(--tw-ring-offset-width)) var(--tw-ring-color);
-    --tw-ring-color: rgb(191 219 254 / var(--tw-ring-opacity));
-    --tw-ring-opacity: .5;
-}
-
-/* Footer Styles */
-.footer, .dark .footer {
-    margin-bottom: 45px;
-    margin-top: 35px;
-    text-align: center;
-    border-bottom: 1px solid #e5e5e5;
-}
-
-.footer > p, .dark .footer > p {
-    font-size: .8rem;
-    display: inline-block;
-    padding: 0 10px;
-    transform: translateY(10px);
-    background: white;
-}
-
-.dark .footer {
-    border-color: #303030;
+    padding-top: 1rem;
+    padding-bottom: 1rem;
+    border-radius: 10px;
+    background-color: white;
+    box-shadow: 0 0 20px rgba(0,0,0,0.1);
 }
-
-.dark .footer > p {
-    background: #0b0f19;
+.gradio-row {
+    margin-bottom: 1rem;
 }
-
-/* Share Button Styles */
-#share-btn-container {
-    padding: 0 0.5rem !important;
-    background-color: #000000;
-    justify-content: center;
-    align-items: center;
-    border-radius: 9999px !important;
-    max-width: 13rem;
-    margin-left: auto;
+.gradio-button, .gradio-dropdown, .gradio-textbox {
+    border-radius: 5px;
 }
-
-#share-btn-container:hover {
-    background-color: #060606;
-}
-
-#share-btn {
-    all: initial;
-    color: #ffffff;
-    font-weight: 600;
-    cursor: pointer;
-    font-family: 'IBM Plex Sans', sans-serif;
-    margin-left: 0.5rem !important;
-    padding: 0.5rem !important;
-    right: 0;
-}
-
-/* Animation Styles */
-.animate-spin {
-    animation: spin 1s linear infinite;
-}
-
-@keyframes spin {
-    from { transform: rotate(0deg); }
-    to { transform: rotate(360deg); }
+.gradio-button {
+    background-color: #4CAF50; /* Green */
+    color: white;
 }
-
-/* Other Styles */
-#gallery {
-    min-height: 22rem;
-    margin-bottom: 15px;
-    margin-left: auto;
-    margin-right: auto;
-    border-bottom-right-radius: .5rem !important;
-    border-bottom-left-radius: .5rem !important;
+.gradio-label {
+    display: block;
+    margin-bottom: 5px;
+    font-weight: bold;
 }
 """
 
+# Gradio interface setup
 with gr.Blocks(css=css) as demo:
-    gr.Markdown("# AI Diffusion")
+    gr.Markdown("# AI Image Generation")
+
     with gr.Row():
-        with gr.Column():
-            current_model = gr.Dropdown(label="Current Model", choices=list_models, value=list_models[1])
-            text_prompt = gr.Textbox(label="Prompt", placeholder="Enter a description of the image", lines=2)
-            negative_prompt = gr.Textbox(label="Negative Prompt", placeholder="Enter undesired elements", lines=2)
-            image_style = gr.Dropdown(label="Image Style", choices=["None", "Cinematic", "Digital Art", "Portrait"], value="None")
-            text_button = gr.Button("Generate", variant='primary')
-        with gr.Column():
-            image_output = gr.Image(type="pil", label="Output Image")
+        current_model = gr.Dropdown(label="Select Model", choices=list_models, value=list_models[0])
 
-    text_button.click(generate_txt2img, inputs=[current_model, text_prompt, negative_prompt, image_style], outputs=image_output)
+    with gr.Row():
+        text_prompt = gr.Textbox(label="Enter Prompt", placeholder="Describe the image you want to generate", lines=2)
+        text_button = gr.Button("Generate Image")
+
+    with gr.Row():
+        image_output = gr.Image(type="pil", label="Generated Image")
 
-demo.launch(show_api=False)
+    with gr.Accordion("Advanced settings"):
+        with gr.Column():
+            negative_prompt = gr.Textbox(label="Negative Prompt", placeholder="Enter elements to avoid in the image", lines=2)
+            image_style = gr.Dropdown(label="Select Style", choices=["None", "Cinematic", "Digital Art", "Portrait"], value="None")
+            steps = gr.Slider(minimum=1, maximum=100, value=50, label="Steps")
+            cfg_scale = gr.Slider(minimum=1, maximum=20, value=7, label="CFG Scale")
+            seed = gr.Number(label="Seed", value=random.randint(0, 2**32 - 1))
+
+    text_button.click(
+        func=generate_txt2img,
+        inputs=[current_model, text_prompt, negative_prompt, image_style, steps, cfg_scale, seed],
+        outputs=image_output
+    )
+
+demo.launch()