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app.py

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+import gradio as gr
+import os
+from typing import List, Dict, Optional
+
+# Function to handle chat messages
+def chat(message: str, history: List[Dict[str, str]], model_name: str, temperature: float, max_tokens: int) -> List[Dict[str, str]]:
+    """
+    Generate a response using the Hugging Face Inference API.
+    
+    Args:
+        message: The user's current message
+        history: Chat history with previous messages
+        model_name: The Hugging Face model to use
+        temperature: Sampling temperature for generation
+        max_tokens: Maximum tokens to generate
+        
+    Returns:
+        Updated chat history
+    """
+    try:
+        # Build the conversation context
+        conversation = []
+        
+        # Add system message
+        conversation.append({
+            "role": "system", 
+            "content": "You are a helpful, friendly AI assistant. Provide concise, accurate responses."
+        })
+        
+        # Add conversation history
+        for user_msg, assistant_msg in history:
+            conversation.append({"role": "user", "content": user_msg})
+            if assistant_msg:
+                conversation.append({"role": "assistant", "content": assistant_msg})
+        
+        # Add current message
+        conversation.append({"role": "user", "content": message})
+        
+        # Make API call to Hugging Face
+        headers = {"Authorization": f"Bearer {os.environ.get('HF_TOKEN', '')}"}
+        api_url = f"https://api-inference.huggingface.co/models/{model_name}"
+        
+        response = requests.post(
+            api_url,
+            headers=headers,
+            json={"inputs": conversation, "parameters": {"temperature": temperature, "max_new_tokens": max_tokens}},
+            timeout=60
+        )
+        
+        response.raise_for_status()
+        
+        # Parse the response
+        result = response.json()[0]
+        
+        # Extract assistant's response
+        if isinstance(result, list) and len(result) > 0:
+            if isinstance(result[0], list) and len(result[0]) > 0:
+                assistant_response = result[0][0].get("generated_text", "")
+            else:
+                assistant_response = str(result[0])
+        else:
+            assistant_response = str(result)
+        
+        # Add assistant response to history
+        history.append({"role": "user", "content": message})
+        history.append({"role": "assistant", "content": assistant_response})
+        
+        return history
+        
+    except requests.exceptions.RequestException as e:
+        error_msg = f"Error communicating with Hugging Face API: {str(e)}"
+        history.append({"role": "user", "content": message})
+        history.append({"role": "assistant", "content": error_msg})
+        return history
+    except Exception as e:
+        error_msg = f"An unexpected error occurred: {str(e)}"
+        history.append({"role": "user", "content": message})
+        history.append({"role": "assistant", "content": error_msg})
+        return history
+
+# Create the Gradio interface
+with gr.Blocks(
+    title="AI Chatbot",
+    description="Chat with various AI models powered by Hugging Face",
+    theme=gr.themes.Soft(
+        primary_hue="blue",
+        secondary_hue="indigo",
+        neutral_hue="slate",
+        font=gr.themes.GoogleFont("Inter"),
+        text_size="lg",
+        spacing_size="lg",
+        radius_size="md"
+    ).set(
+        button_primary_background_fill="*primary_600",
+        button_primary_background_fill_hover="*primary_700",
+        block_title_text_weight="600",
+    )
+) as demo:
+    
+    # Header section
+    gr.Markdown(
+        """
+        # 🤖 AI Chatbot
+        Chat with powerful AI models from Hugging Face
+        """
+    )
+    
+    # Model selection and settings
+    with gr.Accordion("⚙️ Model Settings", open=False):
+        with gr.Row():
+            with gr.Column():
+                model_dropdown = gr.Dropdown(
+                    choices=[
+                        "mistralai/Mistral-7B-Instruct-v0.2",
+                        "meta-llama/Llama-2-7b-chat-hf",
+                        "tiiuae/falcon-7b-instruct",
+                        "bigscience/bloom-560m",
+                        "google/flan-t5-large",
+                        "gpt2-xl"
+                    ],
+                    value="mistralai/Mistral-7B-Instruct-v0.2",
+                    label="Select Model",
+                    info="Choose an AI model from Hugging Face"
+                )
+            
+            with gr.Column():
+                temperature_slider = gr.Slider(
+                    minimum=0.0,
+                    maximum=1.0,
+                    value=0.7,
+                    step=0.1,
+                    label="Temperature",
+                    info="Lower = more focused, Higher = more creative"
+                )
+            
+            with gr.Column():
+                max_tokens_slider = gr.Slider(
+                    minimum=50,
+                    maximum=2048,
+                    value=512,
+                    step=50,
+                    label="Max Tokens",
+                    info="Maximum length of response"
+                )
+    
+    # API Token input
+    with gr.Row():
+        api_token = gr.Textbox(
+            label="Hugging Face API Token",
+            placeholder="Enter your HF_TOKEN environment variable or paste token here",
+            type="password",
+            info="Required for private models. Leave empty if using public models."
+        )
+    
+    # Chat interface
+    with gr.Row():
+        with gr.Column(scale=3):
+            chatbot = gr.Chatbot(
+                label="Chat History",
+                height=500,
+                avatar_images=(
+                    "https://api.dicebear.com/7.x/avataaars/svg?seed=AI",
+                    "https://api.dicebear.com/7.x/avataaars/svg?seed=User"
+                ),
+                bubble_full_width=False
+            )
+        
+        with gr.Column(scale=1):
+            gr.Markdown(
+                """
+                ### 📝 Tips
+                - Enter your API token for better performance
+                - Try different models for different responses
+                - Adjust temperature for more creative outputs
+                - Clear chat to start fresh
+                """
+            )
+            
+            clear_button = gr.Button(
+                "🗑️ Clear Chat",
+                variant="secondary",
+                size="lg"
+            )
+    
+    # User input
+    with gr.Row():
+        user_input = gr.Textbox(
+            label="Your Message",
+            placeholder="Type your message here...",
+            scale=4,
+            show_label=False
+        )
+        
+        send_button = gr.Button(
+            "Send",
+            variant="primary",
+            scale=1,
+            size="lg"
+        )
+    
+    # Example prompts
+    gr.Examples(
+        examples=[
+            ["What is machine learning?"],
+            ["Explain quantum computing in simple terms"],
+            ["Write a short poem about AI"],
+            ["Help me debug this code"],
+            ["What are the benefits of renewable energy?"],
+            ["Tell me a fun fact about space"],
+            ["How do I make a good cup of coffee?"],
+            ["What's the difference between Python 2 and 3?"],
+        ],
+        inputs=user_input,
+        label="💡 Example Prompts"
+    )
+    
+    # Event handlers
+    send_button.click(
+        fn=chat,
+        inputs=[user_input, chatbot, model_dropdown, temperature_slider, max_tokens_slider],
+        outputs=[chatbot]
+    )
+    
+    user_input.submit(
+        fn=chat,
+        inputs=[user_input, chatbot, model_dropdown, temperature_slider, max_tokens_slider],
+        outputs=[chatbot]
+    )
+    
+    clear_button.click(
+        fn=lambda: [],
+        outputs=[chatbot]
+    )
+    
+    # Footer
+    gr.Markdown(
+        """
+        ---
+        Built with **[anycoder](https://huggingface.co/spaces/akhaliq/anycoder)**
+        """
+    )
+
+# Launch the application
+if __name__ == "__main__":
+    demo.launch(
+        theme=gr.themes.Soft(
+            primary_hue="blue",
+            secondary_hue="indigo",
+            neutral_hue="slate",
+            font=gr.themes.GoogleFont("Inter"),
+            text_size="lg",
+            spacing_size="lg",
+            radius_size="md"
+        ).set(
+            button_primary_background_fill="*primary_600",
+            button_primary_background_fill_hover="*primary_700",
+            block_title_text_weight="600",
+        ),
+        css="""
+        .chatbot-container {
+            max-height: 600px !important;
+        }
+        .chatbot-message {
+            margin: 8px 0;
+            padding: 12px 16px;
+            border-radius: 12px;
+            max-width: 80%;
+        }
+        .chatbot-message.user {
+            background-color: #e3f2fd;
+            margin-left: auto;
+        }
+        .chatbot-message.assistant {
+            background-color: #f5f5f5;
+        }
+        """,
+        footer_links=[
+            {"label": "Built with anycoder", "url": "https://huggingface.co/spaces/akhaliq/anycoder"}
+        ]
+    )

requirements.txt

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+gradio>=6.0
+requests
+Pillow