Update app2.py

app2.py

@@ -1,5 +1,3 @@
-# app.py
-
 import streamlit as st
 import google.generativeai as genai
 from dotenv import load_dotenv
@@ -12,8 +10,13 @@ load_dotenv()
 api_key = os.getenv("GENERATIVEAI_API_KEY")
 genai.configure(api_key=api_key)
 
-# Global variable to maintain chat session
-chat = None
+# Initialize session state for message history if it doesn't exist
+if 'messages' not in st.session_state:
+    st.session_state.messages = []
+
+# Initialize session state for chat
+if 'chat' not in st.session_state:
+    st.session_state.chat = None
 
 # Generation configuration and safety settings
 generation_config = {
@@ -42,101 +45,109 @@ safety_settings = [
     },
 ]
 
-# Function to handle text summary requests
 def text_summary(text, isNew=False):
-    global chat
-
-    if isNew or chat is None:  # Start a new chat session
+    if isNew or st.session_state.chat is None:
         model = genai.GenerativeModel(
             model_name="gemini-pro",
             generation_config=generation_config,
             safety_settings=safety_settings
         )
-        chat = model.start_chat()
-        chat.send_message("""
-        Act as a financial advisor and generate financial summaries in a structured and tabular format. Follow these guidelines strictly:
-
-        - Start each section with a clear title in <strong> tags.
-        - For key metrics, use a table with two columns: one for the metric name and one for its value.
-        - Use bullet points only for listing risks and growth prospects.
-        - Ensure each section is clearly separated with line breaks.
-        - Do not use bold or italic formatting (, *), except for the specified HTML tags.
-
-        Example format:
-
-        <strong>Company Overview</strong><br/>
-        <p>Company Name: {Company Name}</p>
-        <p>Description: {Company Description}</p>
-        <br/><br/>
-
-        <strong>Stock Performance</strong><br/>
-        <p>Apple Inc. (AAPL) is a highly valued stock...</p>
-        <br/><br/>
-
-        <strong>Key Metrics</strong><br/>
-        <table>
-            <tr>
-                <th>Metric</th>
-                <th>Value</th>
-            </tr>
-            <tr>
-                <td>Market Capitalization</td>
-                <td>$2.7 trillion</td>
-            </tr>
-            <tr>
-                <td>Stock Price</td>
-                <td>$170 per share</td>
-            </tr>
-            <tr>
-                <td>EPS (TTM)</td>
-                <td>$6.15</td>
-            </tr>
-            <tr>
-                <td>P/E Ratio</td>
-                <td>24.34</td>
-            </tr>
-        </table>
-        <br/><br/>
-
-        <strong>Growth Prospects</strong><br/>
-        <ul>
-            <li>iPhone sales growth in emerging markets.</li>
-            <li>Expansion of services revenue.</li>
-            <li>Increased demand for wearable devices.</li>
-            <li>Development of AR/VR technologies.</li>
-        </ul>
-        <br/><br/>
+        st.session_state.chat = model.start_chat()
+        st.session_state.chat.send_message("""
+        Act as a financial advisor and generate financial summaries in a structured and tabular format...
+        """)  # Your existing prompt here
 
-        <strong>Risks</strong><br/>
-        <ul>
-            <li>Competition from other technology companies.</li>
-            <li>Dependence on iPhone sales.</li>
-            <li>Economic downturns.</li>
-            <li>Supply chain disruptions and geopolitical risks.</li>
-        </ul>
-        <br/><br/>
-
-        <strong>Overall</strong><br/>
-        <p>Apple Inc. is a financially strong company with a history of innovation...</p>
-        <br/><br/>
-        """)
-
-    # Send message and return response
-    response = chat.send_message(text)
+    response = st.session_state.chat.send_message(text)
     return response.text
 
-# Streamlit UI
-st.title("Financial Summary Chatbot")
-st.write("Welcome to the Financial Summary Chatbot! Enter your text below to get a financial summary.")
+# Custom CSS for chat interface
+st.markdown("""
+<style>
+.chat-container {
+    height: 600px;
+    overflow-y: auto;
+    padding: 20px;
+    margin-bottom: 100px;
+}
+.user-message {
+    background-color: #e6f3ff;
+    padding: 10px;
+    border-radius: 10px;
+    margin: 10px 0;
+    max-width: 80%;
+    margin-left: auto;
+}
+.bot-message {
+    background-color: #f0f0f0;
+    padding: 10px;
+    border-radius: 10px;
+    margin: 10px 0;
+    max-width: 80%;
+}
+.input-container {
+    position: fixed;
+    bottom: 0;
+    left: 0;
+    right: 0;
+    padding: 20px;
+    background-color: white;
+    border-top: 1px solid #ddd;
+}
+.stTextInput input {
+    border-radius: 20px;
+}
+</style>
+""", unsafe_allow_html=True)
 
-# Input area for user text
-user_input = st.text_area("Enter your text here:", "")
+# Main title
+st.title("Financial Summary Chatbot")
 
-# Button to submit the text
-if st.button("Get Summary"):
-    if user_input.strip():
-        summary = text_summary(user_input, isNew=True)  # Start a new session each time
-        st.write("### Summary:")
-        st.markdown(summary, unsafe_allow_html=True)
-    else:
-        st.warning("Please enter some text to summarize.")
+# Chat message container
+chat_container = st.container()
+
+# Function to process the message
+def process_message(message: str):
+    if message.strip():
+        # Add user message to history
+        st.session_state.messages.append({"role": "user", "content": message})
+        
+        # Get bot response
+        response = text_summary(message)
+        
+        # Add bot response to history
+        st.session_state.messages.append({"role": "assistant", "content": response})
+
+# Create a container for the input area at the bottom
+with st.container():
+    st.markdown('<div class="input-container">', unsafe_allow_html=True)
+    
+    # Create two columns for input and button
+    col1, col2 = st.columns([5,1])
+    
+    with col1:
+        user_input = st.text_input("Message", key="user_input", label_visibility="collapsed")
+    
+    with col2:
+        if st.button("Send"):
+            process_message(user_input)
+            # Instead of trying to clear the input directly, we'll use a rerun
+            st.rerun()
+    
+    st.markdown('</div>', unsafe_allow_html=True)
+
+# Handle Enter key press
+if user_input and len(user_input.strip()) > 0:
+    if '\n' in user_input or st.session_state.get('enter_pressed', False):
+        process_message(user_input)
+        st.session_state.enter_pressed = False
+        st.rerun()
+
+# Display chat messages in the container
+with chat_container:
+    st.markdown('<div class="chat-container">', unsafe_allow_html=True)
+    for message in st.session_state.messages:
+        if message["role"] == "user":
+            st.markdown(f'<div class="user-message">{message["content"]}</div>', unsafe_allow_html=True)
+        else:
+            st.markdown(f'<div class="bot-message">{message["content"]}</div>', unsafe_allow_html=True)
+    st.markdown('</div>', unsafe_allow_html=True)