Create app.py

app.py

@@ -0,0 +1,121 @@
+import gradio as gr
+
+# Custom CSS for gradient background and styling
+custom_css = """
+.gradio-container {
+    background: linear-gradient(135deg, #667eea 0%, #764ba2 25%, #f093fb 50%, #4facfe 75%, #00f2fe 100%);
+    background-size: 400% 400%;
+    animation: gradient-animation 15s ease infinite;
+    min-height: 100vh;
+}
+
+@keyframes gradient-animation {
+    0% { background-position: 0% 50%; }
+    50% { background-position: 100% 50%; }
+    100% { background-position: 0% 50%; }
+}
+
+.dark .gradio-container {
+    background: linear-gradient(135deg, #1a1a2e 0%, #16213e 25%, #0f3460 50%, #533483 75%, #e94560 100%);
+    background-size: 400% 400%;
+    animation: gradient-animation 15s ease infinite;
+}
+
+/* Style for the main content area */
+.main-container {
+    background-color: rgba(255, 255, 255, 0.95);
+    backdrop-filter: blur(10px);
+    border-radius: 20px;
+    padding: 20px;
+    box-shadow: 0 8px 32px 0 rgba(31, 38, 135, 0.37);
+    border: 1px solid rgba(255, 255, 255, 0.18);
+}
+
+.dark .main-container {
+    background-color: rgba(30, 30, 30, 0.95);
+    border: 1px solid rgba(255, 255, 255, 0.1);
+}
+
+/* Sidebar styling */
+.sidebar {
+    background-color: rgba(255, 255, 255, 0.9);
+    backdrop-filter: blur(10px);
+    border-radius: 15px;
+    padding: 20px;
+    margin: 10px;
+}
+
+.dark .sidebar {
+    background-color: rgba(40, 40, 40, 0.9);
+}
+"""
+
+def load_model(model_name, signed_in):
+    """Function to load different models based on selection"""
+    if not signed_in:
+        return gr.Info("Please sign in to use the models")
+    
+    # Here you would implement the actual model loading logic
+    # For now, we'll return a placeholder
+    return f"Model {model_name} loaded successfully!"
+
+with gr.Blocks(fill_height=True, theme="Nymbo/Nymbo_Theme", css=custom_css) as demo:
+    with gr.Row():
+        with gr.Column(scale=1):
+            with gr.Group(elem_classes="sidebar"):
+                gr.Markdown("# 🚀 Inference Provider")
+                gr.Markdown(
+                    "This Space showcases OpenAI GPT-OSS models, served by the Cerebras API. "
+                    "Sign in with your Hugging Face account to use this API."
+                )
+                
+                # Model selection dropdown
+                model_dropdown = gr.Dropdown(
+                    choices=[
+                        "openai/gpt-oss-120b",
+                        "openai/gpt-oss-20b"
+                    ],
+                    value="openai/gpt-oss-120b",
+                    label="Select Model",
+                    info="Choose between different model sizes"
+                )
+                
+                # Login button
+                button = gr.LoginButton("Sign in with Hugging Face", size="lg")
+                
+                # Additional options
+                with gr.Accordion("⚙️ Advanced Options", open=False):
+                    temperature = gr.Slider(
+                        minimum=0,
+                        maximum=2,
+                        value=0.7,
+                        step=0.1,
+                        label="Temperature"
+                    )
+                    max_tokens = gr.Slider(
+                        minimum=1,
+                        maximum=4096,
+                        value=512,
+                        step=1,
+                        label="Max Tokens"
+                    )
+        
+        with gr.Column(scale=3):
+            with gr.Group(elem_classes="main-container"):
+                # Dynamic model loading based on selection
+                @gr.render(inputs=[model_dropdown, button])
+                def render_model_interface(selected_model, login_status):
+                    if selected_model == "openai/gpt-oss-120b":
+                        gr.load(
+                            "models/openai/gpt-oss-120b",
+                            accept_token=login_status,
+                            provider="fireworks-ai"
+                        )
+                    elif selected_model == "openai/gpt-oss-20b":
+                        gr.load(
+                            "models/openai/gpt-oss-20b",
+                            accept_token=login_status,
+                            provider="fireworks-ai"
+                        )
+
+demo.launch()