Update app.py

app.py

@@ -1,77 +1,57 @@
+import os
 import streamlit as st
 import google.generativeai as genai
 
-# Configure API key
-genai.configure(api_key="AIzaSyC70u1sN87IkoxOoIj4XCAPw97ae2LZwNM")
 
-# Create model object
-model = genai.GenerativeModel(
-  model_name="gemini-pro",
-  generation_config={
-    "temperature": 0.9,
-    "max_output_tokens": 2048
-  },
-  safety_settings=[
-    {
-      "category": "HARM_CATEGORY_HARASSMENT",
-      "threshold": "BLOCK_MEDIUM_AND_ABOVE"
-    },
-    {
-      "category": "HARM_CATEGORY_HATE_SPEECH",
-      "threshold": "BLOCK_MEDIUM_AND_ABOVE"
-    },
-    {
-      "category": "HARM_CATEGORY_SEXUALLY_EXPLICIT",
-      "threshold": "BLOCK_MEDIUM_AND_ABOVE"
-    },
-    {
-      "category": "HARM_CATEGORY_DANGEROUS_CONTENT",
-      "threshold": "BLOCK_MEDIUM_AND_ABOVE"
-    }
-  ]
-)
+# Title for the application
+st.title("Chat with Gemini Bot")
 
-# Create chatbot interface
-st.title("Gemini API Chatbot")
+# Set your Google API Key as an environment variable
+os.environ['GOOGLE_API_KEY'] = "AIzaSyC70u1sN87IkoxOoIj4XCAPw97ae2LZwNM"
+genai.configure(api_key=os.environ['GOOGLE_API_KEY'])
 
-# Get chat history from session state
-chat_history = st.session_state.get("chat_history", [])
+# Create the model
+model = genai.GenerativeModel('gemini-pro')
 
-# Create container for chat messages
-chat_container = st.container()
+# Initialize chat history
+if 'chat_history' not in st.session_state:
+    st.session_state.chat_history = []
 
-# Loop over chat history and display messages
-for message in chat_history:
-  # Get message role and text
-  role = message['role']
-  text = message['text']
+# Display chat history
+for message in st.session_state.chat_history:
+    if message['role'] == 'user':
+        st.markdown(f"**You:** {message['content']}")
+    else:
+        st.markdown(f"**Gemini Bot:** {message['content']}")
 
-  # Display message with markdown
-  chat_container.markdown(f"**{role}:** {text}")
-
-# Get user input from text box
+# User input
 user_input = st.text_input("You")
 
-# Check if user input is not empty
+# If user input is not empty
 if user_input:
-  # Add user message to chat history
-  chat_history.append({'role': 'user', 'text': user_input})
+    # Add user message to chat history
+    st.session_state.chat_history.append({
+        'role': 'user',
+        'content': user_input
+    })
 
-  # Display user message with markdown
-  chat_container.markdown(f"**user:** {user_input}")
+    # Display user message
+    st.markdown(f"**You:** {user_input}")
 
-  # Get model response with start_chat method
-  with st.spinner("Thinking..."):
-    response = model.start_chat({'user_input': user_input})
+    # Create a message for the Gemini model
+    message = [{'role': 'user', 'content': msg['content']} for msg in st.session_state.chat_history]
 
-  # Get response text from response object
-  response_text = response['text']
+    # Generate response from the model
+    response = model.generate_content(message)
 
-  # Add response message to chat history
-  chat_history.append({'role': 'assistant', 'text': response_text})
+    # Extract bot's message from the response
+    bot_message = response['choices'][0]['message']['content']
 
-  # Display response message with markdown
-  chat_container.markdown(f"**assistant:** {response_text}")
+    # Add bot message to chat history
+    st.session_state.chat_history.append({
+        'role': 'assistant',
+        'content': bot_message
+    })
 
-  # Update session state with chat history
-  st.session_state["chat_history"] = chat_history
+    # Display bot message
+    st.markdown(f"**Gemini Bot:** {bot_message}")