Update app.py

app.py

@@ -1,114 +1,44 @@
+# tesla_chatbot.py
+
 import streamlit as st
-import markdown
-from transformers import pipeline
-import os
+import openai
+
+# Set your OpenAI API key
+openai.api_key = "YOUR_OPENAI_API_KEY"  # Replace with your API key
+
+# Tesla knowledge base prompt
+BASE_PROMPT = """
+You are a helpful Tesla assistant.
+You can answer questions about Tesla cars (Model S, 3, X, Y), technology (Autopilot, Full Self Driving), Tesla Energy products (Solar Roof, Powerwall), service, and company information.
+
+If you don't know the answer or it's not Tesla-related, say "I'm sorry, I can only assist with Tesla-related queries."
 
-# Custom CSS with animations and dark theme
-st.markdown("""
-<style>
-body {
-    background-color: #1a1a1a;
-    color: #ffffff;
-}
-.stApp {
-    background-color: #1a1a1a;
-}
-.chat-container {
-    background-color: #2c2c2c;
-    border-radius: 10px;
-    padding: 20px;
-    margin-top: 20px;
-    transition: all 0.3s ease;
-}
-.chat-container:hover {
-    box-shadow: 0 0 20px rgba(0, 255, 255, 0.5);
-}
-.stTextInput > div > input {
-    background-color: #3a3a3a;
-    color: #ffffff;
-    border: 1px solid #00ffff;
-    border-radius: 5px;
-    transition: border-color 0.3s ease;
-}
-.stTextInput > div > input:focus {
-    border-color: #ff00ff;
-}
-.stButton > button {
-    background-color: #00ffff;
-    color: #000000;
-    border-radius: 5px;
-    transition: background-color 0.3s ease;
-}
-.stButton > button:hover {
-    background-color: #ff00ff;
-}
-.message {
-    background-color: #3a3a3a;
-    border-radius: 10px;
-    padding: 10px;
-    margin: 10px 0;
-    animation: fadeIn 0.5s ease-in;
-}
-@keyframes fadeIn {
-    from { opacity: 0; transform: translateY(10px); }
-    to { opacity: 1; transform: translateY(0); }
-}
-</style>
-""", unsafe_allow_html=True)
+Answer concisely and clearly.
+"""
 
-# Initialize session state for chat history
-if "messages" not in st.session_state:
-    st.session_state.messages = []
+# Streamlit UI
+st.set_page_config(page_title="Tesla Chatbot 🚗⚡", page_icon="🚗")
 
-# Title and header
-st.title("Tesla Manufacturing AI Chatbot")
-st.markdown("Explore Tesla's AI use cases and ask questions about manufacturing innovations.")
+st.title("🚗 Tesla Chatbot")
+st.write("Ask me anything about Tesla cars, products, and services!")
 
-# Display report
-st.header("AI Use Case Report")
-try:
-    with open("tesla_ai_use_cases/tesla_ai_use_case_report.md", "r") as f:
-        report_content = f.read()
-    st.markdown(report_content)
-except FileNotFoundError:
-    st.error("Report file not found. Please run the main script first.")
+user_input = st.text_input("You:", "")
 
-# Chat interface
-st.header("Chat with the AI")
-with st.container():
-    st.markdown('<div class="chat-container">', unsafe_allow_html=True)
-    
-    # Display chat history
-    for message in st.session_state.messages:
-        with st.container():
-            st.markdown(f'<div class="message">{message["role"]}: {message["content"]}</div>', unsafe_allow_html=True)
-    
-    # Input form
-    with st.form(key="chat_form", clear_on_submit=True):
-        prompt = st.text_input("Ask about Tesla's manufacturing (e.g., 'Explain Gigapress')", key="prompt")
-        submit_button = st.form_submit_button("Send")
-    
-    if submit_button and prompt:
-        # Add user message
-        st.session_state.messages.append({"role": "User", "content": prompt})
-        
-        # Generate response (placeholder until LLM is fine-tuned)
-        try:
-            generator = pipeline("text-generation", model="tesla_ai_use_cases/fine_tuned_tesla_llm")
-            response = generator(prompt, max_length=200, num_return_sequences=1)[0]["generated_text"]
-        except Exception as e:
-            response = f"LLM not yet fine-tuned. Placeholder response: Ask about Gigapress, 4680 cells, or AI use cases. Error: {str(e)}"
-        
-        # Add AI response
-        st.session_state.messages.append({"role": "AI", "content": response})
-        
-        # Rerun to update chat
-        st.rerun()
-    
-    st.markdown('</div>', unsafe_allow_html=True)
+if st.button("Ask"):
+    if user_input.strip() == "":
+        st.warning("Please type a question.")
+    else:
+        with st.spinner("Thinking..."):
+            # Call OpenAI to get the response
+            response = openai.ChatCompletion.create(
+                model="gpt-3.5-turbo",   # You can use gpt-4 if you have access
+                messages=[
+                    {"role": "system", "content": BASE_PROMPT},
+                    {"role": "user", "content": user_input}
+                ],
+                temperature=0.5,
+                max_tokens=300,
+            )
 
-# Sidebar with info
-st.sidebar.header("About")
-st.sidebar.markdown("""
-This chatbot uses a fine-tuned LLM to answer questions about Tesla's manufacturing processes, such as Gigapress, 4680 cells, and AI-driven factory optimization. The data is sourced from Tesla's website, Wikipedia, and industry reports.
-""")
+            reply = response['choices'][0]['message']['content']
+            st.success(reply)