**`app.py`** ```python import gradio as gr import requests import os # Fetch your Groq API key securely from HF Secrets groq_api_key = os.getenv("GROQ_API_KEY") # Path to local business.txt (uploaded in your Space repo) business_file = os.path.join(os.path.dirname(__file__), "business.txt") def chat_with_business(message, history): try: # Read business knowledge from local file with open(business_file, "r", encoding="utf-8") as f: business_info = f.read().strip() # System prompt including business details system_prompt = ( "You are a helpful customer care assistant. " "Use only the following business information to answer the user's query:\n\n" + business_info + "\n\nIf the answer is not in the knowledge, reply 'Yeh information abhi available nahi hai.'" ) # Prepare Groq API payload headers = { "Authorization": f"Bearer {groq_api_key}", "Content-Type": "application/json" } payload = { "model": "llama3-70b-8192", "messages": [ {"role": "system", "content": system_prompt}, {"role": "user", "content": message} ], "temperature": 0.7 } # Call Groq chat endpoint response = requests.post( "https://api.groq.com/openai/v1/chat/completions", headers=headers, json=payload ) response.raise_for_status() data = response.json() reply = data["choices"][0]["message"]["content"] return reply except Exception as e: return f"Error: {e}" # Build Gradio interface with gr.Blocks(theme="soft") as demo: gr.Markdown("## 🌿 My Business Bot") gr.Markdown("*Ask anything about your business in Hindi-English*") chatbot = gr.Chatbot(elem_id="chatbox", height=400) user_input = gr.Textbox(placeholder="Type your question here...", show_label=False) def handle_interaction(message, chat_history): bot_reply = chat_with_business(message, chat_history) chat_history = chat_history + [(message, bot_reply)] return chat_history, "" user_input.submit(handle_interaction, [user_input, chatbot], [chatbot, user_input]) # Launch app if __name__ == "__main__": demo.launch()