app.py

import os
import gradio as gr
from azure.ai.inference import ChatCompletionsClient
from azure.core.credentials import AzureKeyCredential

from transformers import AutoModelForCausalLM, AutoTokenizer, pipeline
 

model_path = "microsoft/Phi-4-mini-instruct"
hf_model = AutoModelForCausalLM.from_pretrained(
    model_path,
    device_map="auto",
    torch_dtype="auto",
    trust_remote_code=True,
)


# Azure Inference setup
url = os.getenv("Azure_Endpoint")
api_key = AzureKeyCredential(os.getenv("Azure_API_KEY"))

# Initialize the ChatCompletionsClient
client = ChatCompletionsClient(
    endpoint=url,
    credential=api_key,
    stream=True
)

# Get and print model information (optional)
try:
    model_info = client.get_model_info()
    print("Model name:", model_info.model_name)
    print("Model type:", model_info.model_type)
    print("Model provider name:", model_info.model_provider_name)
except Exception as e:
    print("Could not get model info:", str(e))

# Configuration parameters
default_temperature = 0.7
default_max_tokens = 4096
default_top_p = 0.1

# Example prompts that users can try
example_prompts = [
    "Explain internet to a medieval knight.",
    "Share some ideas about the best vegetables to start growing in February and March. I'd love to know which ones thrive when planted early in the season!",
    "I'd like to buy a new car. Start by asking me about my budget and which features I care most about, then provide a recommendation.",
    "I'm thinking about moving to a new city. Can you help me plan the move?",
    "I have $20,000 in my savings account, where I receive a 4% profit per year and payments twice a year. Can you please tell me how long it will take for me to become a millionaire?",
]
            
def get_azure_response(message, chat_history, temperature, max_tokens, top_p):
    """
    Function to get a response from the Azure Phi-4 model
    """
    # Prepare conversation history in the format expected by Azure
    messages = [{"role": "system", "content": "You are a helpful AI assistant specialized in financial advice and planning."}]
    
    # Add conversation history
    for human, assistant in chat_history:
        messages.append({"role": "user", "content": human})
        if assistant:  # Only add non-empty assistant messages
            messages.append({"role": "assistant", "content": assistant})
    
    # Add the current message
    messages.append({"role": "user", "content": message})
    
    # Prepare the payload
    payload = {
        "messages": messages,
        "max_tokens": max_tokens,
        "temperature": temperature,
        "top_p": top_p,
        "presence_penalty": 0,
        "frequency_penalty": 0,
        "stream": True
    }
    
    # Get response
    try:
        print("Sending request to Azure...")
        response = client.complete(payload)
        return response
    except Exception as e:
        print(f"Error getting response: {str(e)}")
        return f"Error: {str(e)}"

# CSS for custom styling
custom_css = """
.container {
    max-width: 1200px !important;
    margin-left: auto !important;
    margin-right: auto !important;
    padding-top: 0rem !important;
}
.header {
    text-align: center;
    margin-bottom: 0rem;
}
.header h1 {
    font-size: 2.5rem !important;
    font-weight: 700 !important;
    color: #1a5276 !important;
    margin-bottom: 0.5rem !important;
}
.header p {
    font-size: 1.2rem !important;
    color: #34495e !important;
}
.chatbot-container {
    border-radius: 10px !important;
    box-shadow: 0 4px 6px rgba(0, 0, 0, 0.1) !important;
    overflow: hidden !important;
}
.emoji-button {
    background: none !important;
    border: none !important;
    padding: 0.2rem 0.5rem !important;
    font-size: 1.5rem !important;
    cursor: pointer !important;
    transition: transform 0.2s !important;
}
.emoji-button:hover {
    transform: scale(1.2) !important;
}
.message-input {
    margin-top: 1rem !important;
    display: flex !important;
    align-items: center !important;
}
.footer {
    margin-top: 2rem;
    text-align: center;
    font-size: 0.9rem;
    color: #7f8c8d;
}
.parameters-section {
    background-color: #f8f9fa !important;
    padding: 1rem !important;
    border-radius: 8px !important;
    margin-bottom: 1rem !important;
}
.examples-section {
    background-color: #e8f4f8 !important;
    padding: 1rem !important;
    border-radius: 8px !important;
    margin-bottom: 1rem !important;
}
.right-panel {
    padding-left: 1rem !important;
}
"""

# Create the Gradio interface with a modern, professional design
with gr.Blocks(css=custom_css, title="Phi-4-mini Playground") as demo:
    with gr.Column(elem_classes="container"):
        # Header section
        with gr.Column(elem_classes="header"):
            gr.Markdown("# Phi-4-mini Playground")
        
        # Main content with side-by-side layout
        with gr.Row():
            # Left column for chat
            with gr.Column(scale=7):
                # Main chat interface
                with gr.Column(elem_classes="chatbot-container"):
                    chatbot = gr.Chatbot(
                        height=600,  # Increased height to match right panel
                        bubble_full_width=False,
                        show_label=False,
                        avatar_images=(None, "https://upload.wikimedia.org/wikipedia/commons/d/d3/Phi-integrated-information-symbol.png")
                    )
                    
                    with gr.Row(elem_classes="message-input"):
                        msg = gr.Textbox(
                            label="Your message",
                            placeholder="Start type here ...",
                            lines=2,
                            show_label=False,
                            container=False,
                            scale=8
                        )
                        send_btn = gr.Button("📤Send", variant="primary", scale=1)
                    with gr.Row():
                        clear = gr.Button("🗑️ Clear", variant="secondary", scale=1)
                        regenerate = gr.Button("🔄 Regenerate", variant="secondary", scale=1)
            
            # Right column for examples and settings
            with gr.Column(scale=3, elem_classes="right-panel"):
                # Examples section
                with gr.Column(elem_classes="examples-section"):
                    examples = gr.Examples(
                        examples=example_prompts,
                        inputs=msg,
                        examples_per_page=4
                    )
                
                # Model parameters section
                with gr.Column(elem_classes="parameters-section"):
                    gr.Markdown("### Advanced Settings")
                    
                    temp_slider = gr.Slider(
                        minimum=0.0,
                        maximum=1.0,
                        value=default_temperature,
                        step=0.1,
                        label="Temperature",
                        info="Higher = more creative, lower = more focused"
                    )
                    top_p_slider = gr.Slider(
                        minimum=0.1,
                        maximum=1.0,
                        value=default_top_p,
                        step=0.1,
                        label="Top P",
                        info="Controls diversity of responses"
                    )
                    max_tokens_slider = gr.Slider(
                        minimum=100,
                        maximum=32000,
                        value=default_max_tokens,
                        step=100,
                        label="Max Tokens",
                        info="Maximum length of response"
                    )
        
        # Footer
        with gr.Column(elem_classes="footer"):
            gr.Markdown("Powered by Microsoft [Phi-4 mini model](https://aka.ms/phi-4-mini/azure) on Azure AI. © 2025")
    
    # Simplified chat function that handles both sending and receiving messages
    def chat(message, history, temperature, max_tokens, top_p):
        if not message.strip():
            return "", history
        
        # Get response from Azure
        response = get_azure_response(message, history, temperature, max_tokens, top_p)
        
        # Add the exchange to history
        history.append((message, ""))
          
        response_index = len(history) - 1  # Create a blank index for the newest response
        full_response = "" # Stream the response
        try:
            print("Streaming response from Azure...")
            for chunk in response:
                if chunk.choices:
                    content = chunk.choices[0].delta.content
                    if content:
                        full_response += content
                        # Update the response in place
                        history[response_index] = (message, full_response)
                        # Yield the updated history
                        yield "", history
            
            # Print usage statistics at the end
            print("Streaming completed")
            
            # Return the final state
            return "", history
        except Exception as e:
            error_message = f"Error: {str(e)}"
            print(error_message)
            # Update history with error message
            history[response_index] = (message, error_message)
            return "", history
    
    # Function to clear the conversation
    def clear_conversation():
        return [], default_temperature, default_max_tokens, default_top_p
    
    # Function to regenerate the last response
    def regenerate_response(history, temperature, max_tokens, top_p):
        if not history:
            return history
        
        last_user_message = history[-1][0]
        # Remove the last exchange
        history = history[:-1]
        
        # Get new response
        response = get_azure_response(last_user_message, history, temperature, max_tokens, top_p)
        
        # Add the exchange to history
        history.append((last_user_message, ""))
          
        response_index = len(history) - 1
        full_response = ""
        
        try:
            for chunk in response:
                if chunk.choices:
                    content = chunk.choices[0].delta.content
                    if content:
                        full_response += content
                        history[response_index] = (last_user_message, full_response)
                        yield history
            
            return history
        except Exception as e:
            error_message = f"Error: {str(e)}"
            history[response_index] = (last_user_message, error_message)
            return history
    
    # Set up event handlers
    msg.submit(chat, [msg, chatbot, temp_slider, max_tokens_slider, top_p_slider], [msg, chatbot])
    send_btn.click(chat, [msg, chatbot, temp_slider, max_tokens_slider, top_p_slider], [msg, chatbot])
    clear.click(clear_conversation, None, [chatbot, temp_slider, max_tokens_slider, top_p_slider])
    regenerate.click(regenerate_response, [chatbot, temp_slider, max_tokens_slider, top_p_slider], [chatbot])

# Launch the app
demo.launch()  # Set share=True to generate a public URL for testing# Launch the app