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app.py

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+# Import necessary libraries to use their functions
+import os
+import streamlit as st
+from openai import OpenAI
+
+# Get the API key from the environment settings
+api_key_nvidia = os.environ.get("api_key_nvidia")
+
+# If there is no API key, show an error message and stop the program
+if not api_key_nvidia:
+    st.error("NVIDIA API key not found. Please set the `api_key_nvidia` environment variable.")
+    st.stop()
+
+# Add custom design for a finance theme
+st.markdown("""
+<style>
+/* Set background color for the main section */
+.main {
+    background-color: #f4f9f9; /* Light teal for a professional look */
+    color: #000000; /* Black text for readability */
+}
+/* Set background color for the sidebar */
+.sidebar .sidebar-content {
+    background-color: #d1e7dd; /* Slightly darker teal */
+}
+/* Set text color for input fields */
+.stTextInput textarea {
+    color: #000000 !important;
+}
+/* Change styles for dropdown menu */
+.stSelectbox div[data-baseweb="select"] {
+    color: black !important;
+    background-color: #d1e7dd !important;
+}
+/* Change color of dropdown icons */
+.stSelectbox svg {
+    fill: black !important;
+}
+/* Change background and text color for dropdown options */
+.stSelectbox option {
+    background-color: #d1e7dd !important;
+    color: black !important;
+}
+/* Change background and text color for dropdown items */
+div[role="listbox"] div {
+    background-color: #d1e7dd !important;
+    color: black !important;
+}
+</style>
+""", unsafe_allow_html=True)
+
+# Set the title of the app
+st.title("💰 Finance Assistant")
+# Add a small description under the title
+st.caption("🌟 Your AI-Powered Financial Advisor")
+
+# Create the sidebar with options
+with st.sidebar:
+    # Add a dividing line
+    st.divider()
+    # Display a section for assistant features
+    st.markdown("### Assistant Capabilities")
+    st.markdown("""
+    - 📊 Investment Analysis
+    - 💳 Budgeting Advice
+    - 🏦 Loan Guidance
+    - 💡 Retirement Planning
+    """)
+    # Add another dividing line
+    st.divider()
+    # Show a small footer message
+    st.markdown("Built with NVIDIA API | LangChain ")
+
+# Start the AI client using the API key
+client = OpenAI(
+    base_url="https://integrate.api.nvidia.com/v1",
+    api_key=api_key_nvidia
+)
+
+# Define a message that tells the AI how to respond
+system_prompt_template = (
+    "You are an expert AI financial assistant. Provide accurate, concise, and empathetic responses "
+    "to user queries related to investments, budgeting, loans, retirement planning, and other financial matters. "
+    "Always respond in English."
+)
+
+# Initialize chat history if it doesn't exist
+if "message_log" not in st.session_state:
+    st.session_state.message_log = [
+        {"role": "assistant", "content": "Hi! I'm your Finance Assistant. How can I assist you today? 💰"}
+    ]
+
+# Create a container to display chat messages
+chat_container = st.container()
+
+# Show chat messages inside the container
+with chat_container:
+    for message in st.session_state.message_log:
+        with st.chat_message(message["role"]):
+            st.markdown(message["content"])
+
+# Input field for user to type questions
+user_query = st.chat_input("Type your finance-related question here...")
+
+# Function to get a response from the AI
+def generate_ai_response(messages):
+    """
+    Sends the conversation to the AI model and processes the response.
+    """
+    completion = client.chat.completions.create(
+        model="deepseek-ai/deepseek-r1",
+        messages=messages,
+        temperature=0.5,  # Controls randomness of responses
+        top_p=0.5,  # Helps control diversity of responses
+        max_tokens=1000,  # Maximum length of response
+        stream=True  # Enables streaming of responses
+    )
+
+    # Process the AI response piece by piece
+    response = ""
+    for chunk in completion:
+        content = chunk.choices[0].delta.content or ""
+        response += content
+    return response
+
+# Handle user input and generate AI responses
+if user_query:
+    # Save the user's message in chat history
+    st.session_state.message_log.append({"role": "user", "content": user_query})
+
+    # Create a list of messages to send to AI
+    messages = [
+        {"role": "system", "content": system_prompt_template},  # First message that tells AI how to behave
+    ]
+
+    # Add all previous messages to the conversation
+    for msg in st.session_state.message_log:
+        role = msg["role"]
+        if role == "ai":
+            role = "assistant"
+        messages.append({"role": role, "content": msg["content"]})
+
+    # Show a loading spinner while AI is thinking
+    with st.spinner("🧠 Processing..."):
+        # Get the AI response
+        ai_response = generate_ai_response(messages)
+
+    # Save the AI's response in chat history
+    st.session_state.message_log.append({"role": "assistant", "content": ai_response})
+
+    # Refresh the page to show the new chat messages
+    st.rerun()

requirements.txt

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+streamlit
+langchain_core
+langchain_community
+langchain-openai