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import gradio as gr | |
import requests | |
import os | |
def chat(message, history): | |
API_URL = "https://api-inference.huggingface.co/models/bitext/Mistral-7B-Customer-Support" | |
headers = {"Authorization": f"Bearer {os.getenv('HF_TOKEN')}"} | |
# Format the message for the API | |
payload = {"inputs": message} | |
try: | |
response = requests.post(API_URL, headers=headers, json=payload, timeout=30) | |
if response.status_code == 200: | |
result = response.json() | |
if isinstance(result, list) and len(result) > 0: | |
return result[0]["generated_text"] | |
else: | |
return "Sorry, I couldn't generate a response." | |
else: | |
return f"API Error: {response.status_code}" | |
except Exception as e: | |
return f"Error: {str(e)}" | |
# Create Gradio interface | |
demo = gr.ChatInterface( | |
fn=chat, | |
title="AI Customer Service Chatbot", | |
description="Powered by Mistral-7B Customer Support (via Hugging Face API)", | |
examples=[ | |
["How can I reset my password?"], | |
["What are your return policies?"], | |
["I need help with my order"], | |
["What payment methods do you accept?"] | |
] | |
) | |
demo.launch() |