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import gradio as gr
from huggingface_hub import InferenceClient
# Function to interact with the model using the Inference API
def chat_with_model(user_input, hf_api_key):
# Initialize the InferenceClient with the provided API key
client = InferenceClient(api_key=hf_api_key)
# Define the messages for the chat (system message tailored for a code assistant)
messages = [
{"role": "system", "content": "You are a code assistant that helps with code generation, debugging, and explanations."},
{"role": "user", "content": user_input}
]
# Create a stream for chat completions using the API
stream = client.chat.completions.create(
model="Qwen/Qwen2.5-Coder-32B-Instruct",
messages=messages,
max_tokens=500,
stream=True
)
# Collect the generated response from the model
response = ""
for chunk in stream:
response += chunk.choices[0].delta.content
return response
# Create the Gradio interface
iface = gr.Interface(
fn=chat_with_model,
inputs=[
gr.Textbox(lines=5, placeholder="Ask me anything about coding..."),
gr.Textbox(lines=1, placeholder="Enter your Hugging Face API key", type="password") # API key input
],
outputs="text",
title="Code Assistant with Qwen2.5-Coder",
description="A code assistant that helps you with code generation, debugging, and explanations using the Qwen2.5-Coder model via Hugging Face Inference API."
)
# Launch the interface
iface.launch()
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