Update app.py

app.py

@@ -1,140 +1,143 @@
-import streamlit as st  
-import google.generativeai as genai  
-from dotenv import load_dotenv  
-import os  
-  
-# Load environment variables  
-load_dotenv()  
-  
-# Configure Google Generative AI with API key  
-api_key = os.getenv("GENERATIVEAI_API_KEY")  
-genai.configure(api_key=api_key)  
-  
-# Global variable to maintain chat session  
-chat = None  
-  
-# Generation configuration and safety settings  
-generation_config = {  
-    "temperature": 0.9,  
-    "top_p": 0.5,  
-    "top_k": 5,  
-    "max_output_tokens": 1000,  
-}  
-  
-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"  
-    },  
-]  
-  
-# 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  
-        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/>  
-  
-        <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)  
-    return response.text  
-  
-# Streamlit UI  
-st.title("Financial Summary Chatbot")  
-st.write("Welcome to the Financial Summary Chatbot! Type a message to get a response from the chatbot.")  
-  
-# Input area for user text  
-chat_input = st.text_area("Type a message:", "")  
-  
-# Button to submit the text  
-if st.button("Send"):  
-    if chat_input.strip():  
-        response = text_summary(chat_input)  
-        st.write("### Response:")  
-        st.markdown(response, unsafe_allow_html=True)  
-    else:  
-        st.warning("Please enter a message to send.")  
+import streamlit as st
+import google.generativeai as genai
+from dotenv import load_dotenv
+import os
+
+# Load environment variables
+load_dotenv()
+
+# Configure Google Generative AI with API key
+api_key = os.getenv("GENERATIVEAI_API_KEY")
+genai.configure(api_key=api_key)
+
+# Initialize session state for message history if it doesn't exist
+if 'messages' not in st.session_state:
+    st.session_state.messages = []
+
+# Global variable to maintain chat session
+chat = None
+
+# Generation configuration and safety settings
+generation_config = {
+    "temperature": 0.9,
+    "top_p": 0.5,
+    "top_k": 5,
+    "max_output_tokens": 1000,
+}
+
+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"
+    },
+]
+
+def text_summary(text, isNew=False):
+    global chat
+
+    if isNew or 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...
+        """)  # Your existing prompt here
+
+    response = chat.send_message(text)
+    return response.text
+
+# 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;
+}
+</style>
+""", unsafe_allow_html=True)
+
+# Main title
+st.title("Financial Summary Chatbot")
+
+# Chat message container
+chat_container = st.container()
+
+# 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:
+        send_button = st.button("Send")
+    
+    st.markdown('</div>', unsafe_allow_html=True)
+
+# Handle sending messages
+if send_button and user_input.strip():
+    # Add user message to history
+    st.session_state.messages.append({"role": "user", "content": user_input})
+    
+    # Get bot response
+    response = text_summary(user_input)
+    
+    # Add bot response to history
+    st.session_state.messages.append({"role": "assistant", "content": response})
+    
+    # Clear input
+    st.session_state.user_input = ""
+
+# 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)