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import os
import requests
import gradio as gr
# Get Groq API key from Hugging Face secrets
groq_api_key = os.environ.get("GROQ_API_KEY")
if not groq_api_key:
raise ValueError("Please set the GROQ_API_KEY in the Hugging Face Space secrets.")
# Groq API configuration
url = "https://api.groq.com/openai/v1/chat/completions"
headers = {
"Authorization": f"Bearer {groq_api_key}"
}
# Prompt template
template = """
You are a friendly and professional customer service assistant for a telecom company.
Respond to the customer's issue below with empathy and clear steps, especially for roaming support.
Customer Query: {query}
Your Response:
"""
# Core function to query the API
def generate_response(user_query):
structured_prompt = template.format(query=user_query)
body = {
"model": "llama-3.1-8b-instant",
"messages": [{"role": "user", "content": structured_prompt}]
}
response = requests.post(url, headers=headers, json=body)
if response.status_code == 200:
return response.json()['choices'][0]['message']['content'], "✅ Success"
else:
return f"Error {response.status_code}: {response.text}", "❌ Failed"
# Gradio app using Blocks layout
with gr.Blocks() as demo:
gr.Markdown("## 📡 Telecom Support Assistant powered by Groq API")
gr.Markdown(
"Enter your customer service query below. The AI assistant will respond with a helpful and empathetic reply, especially for **roaming issues**."
)
with gr.Row():
with gr.Column(scale=2):
user_input = gr.Textbox(
lines=5,
label="Customer Query",
placeholder="e.g., My SIM card stopped working while traveling abroad."
)
submit_btn = gr.Button("Generate Response")
with gr.Column(scale=3):
status_output = gr.Textbox(label="Status", interactive=False)
response_output = gr.Textbox(label="AI Response", lines=10)
submit_btn.click(
fn=generate_response,
inputs=user_input,
outputs=[response_output, status_output]
)
demo.launch()
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