Update app.py

app.py

@@ -1,41 +1,76 @@
 import streamlit as st
-from groq import Groq
-import os
+from pyngrok import ngrok
 
-# API key from secrets
-client = Groq(api_key=os.getenv("GROQ_API_KEY"))
+# Kill existing tunnels to avoid conflicts
+ngrok.kill()
 
-st.set_page_config(page_title="AI Chatbot", page_icon="🤖")
+# Connect to port 8501 (default for Streamlit)
+public_url = ngrok.connect(8501)
+st.write(f"Ngrok tunnel URL: {public_url}")
 
+# Your main Streamlit app code
 st.title("🤖 AI Chatbot (Groq)")
-st.write("Powered by Groq ⚡")
+st.write("Fast AI chatbot 🚀")
 
-# Chat memory
+# Initialize chat messages in session state
 if "messages" not in st.session_state:
     st.session_state.messages = []
 
-# Show messages
+# Display chat messages
 for msg in st.session_state.messages:
     with st.chat_message(msg["role"]):
         st.markdown(msg["content"])
 
-# Input
+# User input
 user_input = st.chat_input("Type your message...")
 
 if user_input:
+    # Append user message
     st.session_state.messages.append({"role": "user", "content": user_input})
-
     with st.chat_message("user"):
         st.markdown(user_input)
 
+    # Generate response
     with st.chat_message("assistant"):
         with st.spinner("Thinking..."):
             response = client.chat.completions.create(
-                model="openai/gpt-oss-120b",
+                model="mixtral-8x7b-32768",  # or your preferred model
                 messages=st.session_state.messages,
                 max_tokens=500
             )
             reply = response.choices[0].message.content
             st.markdown(reply)
+            # Append assistant response
+            st.session_state.messages.append({"role": "assistant", "content": reply})
+
+# Connect ngrok to port 8501 (Streamlit default port)
+from pyngrok import ngrok
+
+# Disconnect all existing tunnels
+public_url = ngrok.connect(8501)
+st.write(f"👉 Your app is live at: {public_url}")
+"""
+
+# Save the code to a Python file
+with open("streamlit_app.py", "w") as f:
+    f.write(app_code)
+
+# Step 4: Run the Streamlit app
+!streamlit run streamlit_app.py &>/dev/null &
+
+import json
+import time
+from pyngrok import ngrok
+
+
+# Connect to port 8501
+public_url = ngrok.connect(8501)
+
+# Wait a moment to ensure the tunnel is established
+time.sleep(2)
 
-    st.session_state.messages.append({"role": "assistant", "content": reply})
+# Get the public URL
+tunnels = ngrok.get_tunnels()
+for tunnel in tunnels:
+    if tunnel.public_url:
+        print(f"Your Streamlit app is live at: {tunnel.public_url}")