Update app.py

app.py

@@ -0,0 +1,116 @@
+```python
+import streamlit as st
+import markdown
+from transformers import pipeline
+import os
+
+# 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)
+
+# Initialize session state for chat history
+if "messages" not in st.session_state:
+    st.session_state.messages = []
+
+# Title and header
+st.title("Tesla Manufacturing AI Chatbot")
+st.markdown("Explore Tesla's AI use cases and ask questions about manufacturing innovations.")
+
+# 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.")
+
+# 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)
+
+# 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.
+""")
+```