Update app.py

app.py

@@ -1,101 +1,44 @@
 import streamlit as st
-import google.generativeai as palm
-from gradio_client import Client
-import time
-import threading
-
-# Initialize the Gradio client with the API URL
-client = Client("https://akdeniz27-llama-2-70b-chat-hf-with-easyllm.hf.space/")
-
-# Information about obtaining a free API key
-st.sidebar.info("🔑 Get your free palm2 API key at [makersuite.google.com/app/apikey](https://makersuite.google.com/app/apikey)")
-
-# Ask the user for palm2 API key
-api_key_palm2 = st.sidebar.text_input("🔒 Enter your palm2 API key for study notes:", type="password")
-palm.configure(api_key=api_key_palm2)
-
-# Styling for the title
-st.title("🚀 Auto Study Notes Generator")
-st.markdown("---")
-
-# Sidebar for settings
-st.sidebar.title("⚙️ Settings")
-
-# User choice for mode selection
-selected_mode = st.sidebar.radio("🔍 Select Mode:", ['Generate Study Notes (Palm2)', 'Use Llama 70b for Notes'])
-
-# Initialize view count
-view_count = 0
-
-# Function to simulate live view count
-def update_view_count():
-    global view_count
-    while True:
-        time.sleep(5)  # Simulate updates every 5 seconds
-        view_count += 1
-
-# Start the thread to simulate live view count
-thread = threading.Thread(target=update_view_count)
-thread.start()
-
-# Main content area
-if selected_mode == 'Generate Study Notes (Palm2)':
-    st.header("📚 Study Notes Generation (Palm2)")
-
-    # User input for class and study topic
-    user_class = st.sidebar.selectbox('👩‍🎓 Select your class:', ['Class 1', 'Class 2', 'Class 3', 'Class 4', 'Class 5', 'Class 6',
-                                                                   'Class 7', 'Class 8', 'Class 9', 'Class 10', 'Class 11', 'Class 12'])
-    user_input = st.text_input(f'✏️ Enter your study topic for {user_class}:', placeholder='e.g., History')
-
-    if st.button('🚀 Generate Study Notes', key="generate_notes", help="Click to generate study notes"):
+import requests
+
+# Create a session for reusing connections
+session = requests.Session()
+
+# Function to interact with the AI
+def chat_with_ai(message):
+    api_url = "https://free-ai-api.devastation-war.repl.co/chat"
+    payload = {"message": message}
+
+    try:
+        with session.post(api_url, json=payload) as response:
+            if response.status_code == 200:
+                return response.json().get('response')  # Access 'response' key
+            else:
+                return {"error": "Failed to get a response from the AI API."}
+    except requests.RequestException as e:
+        return {"error": f"Error: {e}"}
+
+# Streamlit app
+def main():
+    st.title("Generate Study Notes")
+
+    # User inputs for class and topic
+    user_class = st.sidebar.selectbox('Select your class:', ['Class 1', 'Class 2', 'Class 3', 'Class 4', 'Class 5', 'Class 6',
+                                                             'Class 7', 'Class 8', 'Class 9', 'Class 10', 'Class 11', 'Class 12'])
+    user_input = st.text_input(f'Enter your study topic for {user_class}:', placeholder='e.g., History')
+
+    # Generate study notes when prompted
+    if st.button('Generate Study Notes'):
         if user_input.lower() in ['quit', 'exit', 'bye']:
-            st.success("👋 Goodbye! Have a great day!")
+            st.success("Goodbye! Have a great day!")
         else:
-            with st.spinner("⌛ Generating study notes. Please wait..."):
+            with st.spinner("Generating study notes. Please wait..."):
                 prompt = f"Provide study notes for {user_class} on the topic: {user_input}."
-                response = palm.generate_text(model='models/text-bison-001', prompt=prompt)
-                study_notes = response.result
-
-                # Display the generated study notes
-                st.subheader(f"📚 Study Notes for {user_class} - {user_input}")
-                st.write(study_notes)
-
-elif selected_mode == 'Use Llama 70b for Notes':
-    st.header("🦙 Llama 70b Mode")
-
-    # User input for Llama 70b mode
-    llama_input = st.text_input('💬 Enter a message for Llama 70b (type "exit" to quit):', placeholder='e.g., Tell me a joke')
-
-    if st.button('🔍 Get Llama 70b Response', key="get_llama_response", help="Click to get Llama 70b response"):
-        if llama_input.lower() == 'exit':
-            st.success("👋 Exiting Llama 70b mode. Have a great day!")
-        else:
-            with st.spinner("⌛ Getting response from Llama 70b. Please wait..."):
-                # Make a prediction using Llama 70b API
-                llama_result = client.predict(
-                    llama_input,
-                    api_name="/chat"
-                )
-
-                # Check if the result is not None
-                if llama_result is not None:
-                    # Display the result
-                    st.subheader("🦙 Llama 70b Response")
-                    st.write(llama_result)
-                else:
-                    st.warning("⚠️ Llama 70b API response was None. Please try again later.")
-
-# Show live view count
-st.sidebar.markdown("---")
-st.sidebar.subheader("👀 Live View Count:")
-st.sidebar.write(view_count)
+                response = chat_with_ai(prompt)
 
-# Add a footer with updated text
-st.sidebar.text("© 2023 HelpingAI")
+                # Display generated study notes
+                st.subheader(f"Study Notes for {user_class} - {user_input}")
+                st.write(response)
 
-# Hide Streamlit menu
-st.markdown("""
-    <style>
-        #MainMenu {visibility: hidden;}
-    </style>
-""", unsafe_allow_html=True)
+if __name__ == "__main__":
+    main()