Update app.py

app.py

@@ -1,84 +1,31 @@
 import streamlit as st
-import os
-from langchain_core.prompts import ChatPromptTemplate
-from langchain_google_genai import ChatGoogleGenerativeAI
-from langchain_core.prompts import MessagesPlaceholder
-from langchain.memory import ConversationBufferWindowMemory
-from operator import itemgetter
-from langchain_core.runnables import RunnableLambda, RunnablePassthrough
 
-# Set the API key for Google Generative AI
-os.environ['GOOGLE_API_KEY'] = 'AIzaSyBHPIIk4-BOgXvnQ2_o6c2wTGpY2ByRIDs'
+def page1():
+    st.write("This is Page 1!")
 
-# Define the prompt
-prompt = ChatPromptTemplate.from_messages(
-    [
-        ('system', 'you are a good assistant.'),
-        MessagesPlaceholder(variable_name='history'),
-        ("human", "{input}")
-    ]
-)
+def page2():
+    st.write("This is Page 2!")
 
-# Initialize memory in session state
-if 'memory' not in st.session_state:
-    st.session_state.memory = ConversationBufferWindowMemory(k=10, return_messages=True)
+# Create a Streamlit app
+app = st.StreamlitApp()
 
-# Define the chain
-chain = (RunnablePassthrough.assign(history=RunnableLambda(st.session_state.memory.load_memory_variables) | itemgetter("history")) |
-         prompt | ChatGoogleGenerativeAI(model='gemini-pro', temperature=0, max_output_tokens=500, convert_system_message_to_human=True))
+# Define the main app logic
+def main():
+    st.title("Welcome to My App")
 
-# Define the pages
-def home():
-    st.title("AI Chat Bot Dashboard")
-    st.header('Interactive Chatbot')
-    st.write('''An interactive chatbot is designed to engage in dynamic, back-and-forth conversations with users.
-                These chatbots can understand and retain context from previous interactions, making their responses more
-                relevant and coherent as the conversation progresses. Interactive chatbots often use advanced natural language 
-                processing (NLP) techniques and memory management to provide a more human-like experience. They are commonly used
-                in applications where ongoing interaction and context awareness are crucial, such as customer support, virtual 
-                assistants, and personalized recommendations.''')
-    st.header('Non-Interactive Chatbot')
-    st.write('''A non-interactive chatbot, on the other hand, is designed for more straightforward, single-turn interactions. 
-                These chatbots do not retain context from previous interactions, meaning each user query is treated independently. 
-                Non-interactive chatbots are typically used for simple, transactional tasks where context is not required. They are 
-                easier to develop and deploy and are suitable for scenarios where the interaction is brief and to the point.''')
+    # Create two buttons
+    button1 = st.button("Go to Page 1")
+    button2 = st.button("Go to Page 2")
 
-def page1():
-    st.title("Interactive Chatbot")
-    if 'user_input' not in st.session_state:
-        st.session_state.user_input = ""
-    user_input = st.text_area("User: ", st.session_state.user_input, height=100)
-    if st.button("Submit"):
-        response = chain.invoke({"input": user_input})
-        st.write(f"Assistant: {response.content}")
-        st.session_state.memory.save_context({"input": user_input}, {"output": response.content})
-        st.session_state.user_input = ""  # Clear the input box
-    if st.checkbox("Show Chat History"):
-        chat_history = st.session_state.memory.load_memory_variables({})
-        st.write(chat_history)
-
-def page2():
-    st.title("Interactive Chatbot")
-    if 'user_input' not in st.session_state:
-        st.session_state.user_input = ""
-    user_input = st.text_area("User: ", st.session_state.user_input, height=100)
-    if st.button("Submit"):
-        response = chain.invoke({"input": user_input})
-        st.write(f"Assistant: {response.content}")
-        st.session_state.memory.save_context({"input": user_input}, {"output": response.content})
-        st.session_state.user_input = ""  # Clear the input box
-    if st.checkbox("Show Chat History"):
-        chat_history = st.session_state.memory.load_memory_variables({})
-        st.write(chat_history)
+    # Use Streamlit's routing feature to navigate between pages
+    if button1:
+        app.page("page1")
+    elif button2:
+        app.page("page2")
 
-# Sidebar navigation
-st.sidebar.title("Navigation")
-page = st.sidebar.radio("Go to", ("Home", "Page 1", "Page 2"))
+# Register the pages with Streamlit
+app.page("page1", page1)
+app.page("page2", page2)
 
-# Page rendering
-if page == "Home":
-    home()
-elif page == "Page 1":
-    page1()
-elif page == "Page 2":
-    page2()
+# Run the main app logic
+main()