Update app.py

app.py

@@ -1,12 +1,12 @@
 import streamlit as st
 import os
+import time
+from langchain_openai import ChatOpenAI
+from openai import RateLimitError
 
-# YOUR API KEY
+# YOUR API KEY (with rate limit handling)
 os.environ["OPENAI_API_KEY"] = "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"
 
-from langchain_openai import ChatOpenAI
-
-# Knowledge base
 KNOWLEDGE = """
 SR University is located in Warangal, Telangana, India. 
 Computer Science program focuses on AI/ML, DSA, Java/Python, AWS/Azure, software engineering.
@@ -22,47 +22,84 @@ Internship tips:
 5. Target: Google, Microsoft, Hyderabad/Bangalore startups
 """
 
-@st.cache_resource
-def init_chatbot():
-    return ChatOpenAI(model="gpt-4o-mini", temperature=0)
+def get_chat_response(query, max_retries=3):
+    """Handle rate limits with retry + fallback"""
+    llm = ChatOpenAI(model="gpt-4o-mini", temperature=0)
+    
+    for attempt in range(max_retries):
+        try:
+            prompt = f"""Use ONLY this context to answer: 
+
+{KNOWLEDGE}
+
+Question: {query}
+
+Answer:"""
+            
+            response = llm.invoke(prompt).content
+            return response
+            
+        except RateLimitError:
+            if attempt < max_retries - 1:
+                st.warning(f"Rate limit hit. Retrying in 10s... (Attempt {attempt + 1}/{max_retries})")
+                time.sleep(10)
+                continue
+            else:
+                # FALLBACK: Local rule-based response
+                return get_fallback_response(query)
+    
+    return "Sorry, service temporarily unavailable. Try again later."
+
+def get_fallback_response(query):
+    """FREE fallback - no API needed"""
+    query_lower = query.lower()
+    
+    if "university" in query_lower or "sr" in query_lower:
+        return "SR University is in Warangal, Telangana. Excellent CS program with AI/ML, DSA, cloud computing focus."
+    
+    elif "internship" in query_lower or "job" in query_lower:
+        return """AI/ML Internship Tips:
+1. Solve 300+ LeetCode problems
+2. Build RAG chatbot (this project!)
+3. Apply via AngelList, LinkedIn
+4. Target Hyderabad/Bangalore startups"""
+    
+    elif "project" in query_lower:
+        return "Portfolio projects: 1) RAG Chatbot (live now), 2) Object Detection (robotic arm), 3) RL Drone Agent"
+    
+    elif "leetcode" in query_lower:
+        return "LeetCode: Easy(100) + Medium(150) + Hard(50) = 300 problems total"
+    
+    else:
+        return "Ask about SR University, internships, LeetCode, or AI projects! 💡"
 
 st.title("🧠 RAG Chatbot")
-st.markdown("💡 Ask about SR University, AI internships, projects...")
+st.info("💡 Works even if OpenAI quota exhausted!")
 
-chatbot = init_chatbot()
 if "messages" not in st.session_state:
     st.session_state.messages = []
 
-# Display chat messages
+# Chat history
 for message in st.session_state.messages:
     with st.chat_message(message["role"]):
         st.markdown(message["content"])
 
 # Chat input
-if query := st.chat_input("Type your question here..."):
-    # Add user message
+if query := st.chat_input("Ask about university, internships, projects..."):
     st.session_state.messages.append({"role": "user", "content": query})
     with st.chat_message("user"):
         st.markdown(query)
     
-    # Generate response
     with st.chat_message("assistant"):
         with st.spinner('Thinking...'):
-            prompt = f"""Use ONLY this context to answer: 
-
-{KNOWLEDGE}
-
-Question: {query}
-
-Answer:"""
-            
-            response = chatbot.invoke(prompt).content
+            response = get_chat_response(query)
             st.markdown(response)
     
-    # Add assistant response to chat history
     st.session_state.messages.append({"role": "assistant", "content": response})
 
-# Clear chat button
-if st.button("🗑️ Clear Chat"):
+# Clear chat
+if st.sidebar.button("🗑️ Clear Chat"):
     st.session_state.messages = []
     st.rerun()
+
+st.sidebar.success("✅ Works with/without OpenAI quota!")