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import gradio as gr
from huggingface_hub import InferenceClient
from typing import List, Tuple
# Initialize the InferenceClient with the model you want to use
client = InferenceClient("microsoft/phi-4")
# Define the system message (non-editable)
SYSTEM_MESSAGE = "You're an advanced AI assistant designed to engage in friendly and informative conversations. Your role is to respond to user queries with helpful, clear, and concise answers, while maintaining a conversational tone. You can provide advice, explanations, and solutions based on user input."
def generate_response(
user_input: str,
history: List[Tuple[str, str]],
max_tokens: int,
temperature: float,
top_p: float
) -> str:
"""
Generates a response from the AI model.
Args:
user_input: The user's input message.
history: A list of tuples containing the conversation history
(user input, AI response).
max_tokens: The maximum number of tokens in the generated response.
temperature: Controls the randomness of the generated response.
top_p: Controls the nucleus sampling probability.
Returns:
str: The generated response from the AI model.
"""
try:
# Build the message list with system message and history
messages = [{"role": "system", "content": SYSTEM_MESSAGE}]
messages.extend([{"role": "user" if i % 2 == 0 else "assistant", "content": val}
for i, val in enumerate(sum(history, ()))])
messages.append({"role": "user", "content": user_input})
# Generate response from the model
response = ""
for msg in client.chat_completion(
messages,
max_tokens=max_tokens,
stream=True,
temperature=temperature,
top_p=top_p,
):
if 'choices' in msg and len(msg['choices']) > 0:
token = msg['choices'][0].get('delta', {}).get('content', '')
if token:
response += token
return response
except Exception as e:
print(f"An error occurred: {e}")
return "Error: An unexpected error occurred while processing your request."
# Define the Gradio Interface
iface = gr.Interface(
fn=generate_response,
inputs=[
gr.Textbox(lines=2, label="Your Message"),
gr.Slider(minimum=1, maximum=2048, value=512, step=1, label="Max Tokens"),
gr.Slider(minimum=0.1, maximum=4.0, value=0.7, step=0.1, label="Temperature"),
gr.Slider(minimum=0.1, maximum=1.0, value=0.95, step=0.05, label="Top-p"),
gr.Chatbot(label="Conversation")
],
outputs=[gr.Textbox(label="AI Response")],
title="Chat with AI",
description="Interact with an AI assistant that engages in friendly and informative conversations.",
)
# Launch the interface
if __name__ == "__main__":
iface.launch()
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