Delete chatbot.py

chatbot.py

@@ -1,108 +0,0 @@
-# chatbot.py
-import streamlit as st
-from transformers import pipeline, BlenderbotTokenizer, BlenderbotForConditionalGeneration
-import torch
-from typing import List, Dict
-
-class ChatbotManager:
-    def __init__(self):
-        self.device = "cuda" if torch.cuda.is_available() else "cpu"
-        self.model = None
-        self.tokenizer = None
-        self.load_model()
-        self.initialize_chat()
-    
-    def load_model(self):
-        """Load Blenderbot model locally"""
-        try:
-            with st.spinner("Loading AI model (this may take a minute)..."):
-                model_name = "facebook/blenderbot-400M-distill"
-                self.tokenizer = BlenderbotTokenizer.from_pretrained(model_name)
-                self.model = BlenderbotForConditionalGeneration.from_pretrained(model_name).to(self.device)
-            st.success("Model loaded successfully!")
-        except Exception as e:
-            st.error(f"⚠️ Failed to load model: {str(e)}")
-            self.model = None
-    
-    def initialize_chat(self):
-        """Initialize chat session state"""
-        if "chat_history" not in st.session_state:
-            st.session_state.chat_history = []
-    
-    def clear_chat(self):
-        """Reset chat history"""
-        st.session_state.chat_history = []
-        st.success("Chat history cleared!")
-    
-    def add_message(self, role: str, content: str):
-        """Add a message to chat history"""
-        st.session_state.chat_history.append({"role": role, "content": content})
-    
-    def get_chat_history(self) -> List[Dict]:
-        """Retrieve chat history"""
-        return st.session_state.chat_history
-    
-    def generate_response(self, prompt: str) -> str:
-        """Generate AI response using Blenderbot"""
-        if not self.model:
-            return "Model not loaded. Please try again later."
-        
-        try:
-            # Format prompt with business context
-            business_prompt = f"""You are a professional business advisor. Provide helpful, concise advice on:
-            - Business strategy
-            - Marketing
-            - Product development
-            - Startup growth
-            
-            User Question: {prompt}
-            
-            Answer:"""
-            
-            inputs = self.tokenizer([business_prompt], return_tensors="pt").to(self.device)
-            reply_ids = self.model.generate(**inputs, max_length=200)
-            response = self.tokenizer.decode(reply_ids[0], skip_special_tokens=True)
-            
-            return response
-        except Exception as e:
-            return f"⚠️ Error generating response: {str(e)}"
-    
-    def render_chat_interface(self):
-        """Render the complete chat UI"""
-        st.header("💬 AI Business Mentor (Blenderbot)")
-        
-        # Sidebar controls
-        with st.sidebar:
-            st.subheader("Settings")
-            if st.button("Clear Chat"):
-                self.clear_chat()
-                st.rerun()
-            
-            st.markdown("---")
-            st.caption("Model: facebook/blenderbot-400M-distill")
-            st.caption(f"Device: {self.device.upper()}")
-        
-        # Display chat history
-        for message in self.get_chat_history():
-            with st.chat_message(message["role"]):
-                st.markdown(message["content"])
-        
-        # User input
-        if prompt := st.chat_input("Ask about business..."):
-            self.add_message("user", prompt)
-            
-            # Display user message immediately
-            with st.chat_message("user"):
-                st.markdown(prompt)
-            
-            # Generate and display AI response
-            with st.chat_message("assistant"):
-                with st.spinner("Thinking..."):
-                    response = self.generate_response(prompt)
-                    st.markdown(response)
-            
-            # Add response to history
-            self.add_message("assistant", response)
-            
-            # Auto-refresh to show new messages
-            st.rerun()