Update app.py

app.py

@@ -1,9 +1,10 @@
-import streamlit as st
+import gradio as gr
 import torch
 from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
 from huggingface_hub import login
 import random
 import os
+import json
 
 # Get Hugging Face token from environment variables
 HUGGINGFACE_TOKEN = os.environ.get("HUGGINGFACE_TOKEN", "")
@@ -11,78 +12,9 @@ HUGGINGFACE_TOKEN = os.environ.get("HUGGINGFACE_TOKEN", "")
 if HUGGINGFACE_TOKEN:
     try:
         login(token=HUGGINGFACE_TOKEN)
-        st.success("✅ Successfully connected to Hugging Face")
+        print("✅ Successfully connected to Hugging Face")
     except Exception as e:
-        st.error(f"❌ Hugging Face login failed: {e}")
-
-# Custom CSS for beautiful silver/sky blue theme
-st.markdown("""
-<style>
-    .main {
-        background: linear-gradient(135deg, #f8f9fa 0%, #e3f2fd 100%);
-        font-family: 'Inter', sans-serif;
-    }
-    
-    .stChatMessage {
-        padding: 20px;
-        border-radius: 16px;
-        margin: 12px 0;
-        box-shadow: 0 2px 8px rgba(0,0,0,0.1);
-        border: none;
-    }
-    
-    /* User message styling */
-    .stChatMessage:has(div[data-testid="stChatMessageContent"] > div:first-child > div:first-child) {
-        background: linear-gradient(135deg, #e3f2fd 0%, #bbdefb 100%);
-        border-left: 6px solid #2196f3;
-    }
-    
-    /* Assistant message styling */
-    .stChatMessage:has(div[data-testid="stChatMessageContent"] > div:first-child > div:last-child) {
-        background: linear-gradient(135deg, #ffffff 0%, #f5f5f5 100%);
-        border-left: 6px solid #78909c;
-        border: 1px solid #e0e0e0;
-    }
-    
-    .stTextInput > div > div > input {
-        border: 2px solid #90caf9;
-        border-radius: 25px;
-        padding: 15px 20px;
-        font-size: 16px;
-        background: white;
-        box-shadow: 0 2px 10px rgba(33, 150, 243, 0.1);
-    }
-    
-    .stButton > button {
-        background: linear-gradient(135deg, #2196f3 0%, #1976d2 100%);
-        color: white;
-        border: none;
-        border-radius: 25px;
-        padding: 12px 28px;
-        font-weight: 600;
-        font-size: 16px;
-        box-shadow: 0 4px 12px rgba(33, 150, 243, 0.3);
-        transition: all 0.3s ease;
-    }
-    
-    .stButton > button:hover {
-        transform: translateY(-2px);
-        box-shadow: 0 6px 16px rgba(33, 150, 243, 0.4);
-    }
-    
-    .sidebar .sidebar-content {
-        background: linear-gradient(180deg, #eceff1 0%, #cfd8dc 100%);
-        border-right: 1px solid #b0bec5;
-    }
-    
-    .header-gradient {
-        background: linear-gradient(135deg, #2196f3 0%, #1976d2 100%);
-        -webkit-background-clip: text;
-        -webkit-text-fill-color: transparent;
-        background-clip: text;
-    }
-</style>
-""", unsafe_allow_html=True)
+        print(f"❌ Hugging Face login failed: {e}")
 
 # Personal and Company Information
 PERSONAL_INFO = {
@@ -142,27 +74,27 @@ class YAHBot:
     def _load_model(self):
         """Load the Hugging Face model"""
         try:
-            with st.spinner("🔄 Loading YAH Tech AI model..."):
-                # Try to load custom model first
-                self.tokenizer = AutoTokenizer.from_pretrained(
-                    "Adedoyinjames/YAH-Tech-Chat-Bot", 
-                    token=HUGGINGFACE_TOKEN if HUGGINGFACE_TOKEN else None
-                )
-                self.model = AutoModelForSeq2SeqLM.from_pretrained(
-                    "Adedoyinjames/YAH-Tech-Chat-Bot",
-                    token=HUGGINGFACE_TOKEN if HUGGINGFACE_TOKEN else None,
-                    torch_dtype=torch.float16 if torch.cuda.is_available() else torch.float32
-                )
-            st.success("✅ YAH Tech AI model loaded successfully!")
+            print("🔄 Loading YAH Tech AI model...")
+            # Try to load custom model first
+            self.tokenizer = AutoTokenizer.from_pretrained(
+                "Adedoyinjames/YAH-Tech-Chat-Bot", 
+                token=HUGGINGFACE_TOKEN if HUGGINGFACE_TOKEN else None
+            )
+            self.model = AutoModelForSeq2SeqLM.from_pretrained(
+                "Adedoyinjames/YAH-Tech-Chat-Bot",
+                token=HUGGINGFACE_TOKEN if HUGGINGFACE_TOKEN else None,
+                torch_dtype=torch.float16 if torch.cuda.is_available() else torch.float32
+            )
+            print("✅ YAH Tech AI model loaded successfully!")
         except Exception as e:
-            st.error(f"❌ Failed to load custom model: {e}")
-            st.info("🔄 Falling back to standard FLAN-T5-base model...")
+            print(f"❌ Failed to load custom model: {e}")
+            print("🔄 Falling back to standard FLAN-T5-base model...")
             try:
                 self.tokenizer = AutoTokenizer.from_pretrained(self.model_name)
                 self.model = AutoModelForSeq2SeqLM.from_pretrained(self.model_name)
-                st.success("✅ Standard AI model loaded successfully!")
+                print("✅ Standard AI model loaded successfully!")
             except Exception as e2:
-                st.error(f"❌ Failed to load AI model: {e2}")
+                print(f"❌ Failed to load AI model: {e2}")
                 self.model = None
                 self.tokenizer = None
     
@@ -197,22 +129,18 @@ class YAHBot:
     def _create_smart_prompt(self, user_input, conversation_history):
         """Create a smart prompt that combines brand identity with general knowledge"""
         brand_context = f"""You are YAH Bot, an AI assistant representing {PERSONAL_INFO['name']} and {COMPANY_INFO['name']}. 
-
 About {PERSONAL_INFO['name']}:
 - {PERSONAL_INFO['role']}
 - Goals: {', '.join(PERSONAL_INFO['goals'])}
-
 About {COMPANY_INFO['name']}:
 - {COMPANY_INFO['type']}
 - Philosophy: "{COMPANY_INFO['philosophy']}"
 - Purpose: {COMPANY_INFO['purpose']}
-
 When answering questions:
 1. First provide accurate, helpful information
 2. Naturally mention YAH Tech or Adedoyin James when relevant
 3. Be professional but conversational
 4. Connect general topics to technology, business, or innovation when appropriate
-
 Current conversation:"""
         
         # Build conversation history
@@ -265,7 +193,7 @@ Current conversation:"""
                 return cleaned_response
                 
             except Exception as e:
-                st.error(f"Model error: {str(e)}")
+                print(f"Model error: {str(e)}")
                 return self._get_fallback_response(user_input)
         
         # Fallback if model fails to load
@@ -309,69 +237,193 @@ Current conversation:"""
         ]
         return random.choice(fallback_responses)
 
-def initialize_session_state():
-    """Initialize session state variables"""
-    if "messages" not in st.session_state:
-        st.session_state.messages = []
-    if "bot" not in st.session_state:
-        st.session_state.bot = YAHBot()
-    if "conversation_started" not in st.session_state:
-        st.session_state.conversation_started = False
+# Initialize the bot globally
+yah_bot = YAHBot()
 
-def main():
-    # Page configuration
-    st.set_page_config(
-        page_title="YAH Tech Assistant",
-        page_icon="🚀",
-        layout="centered",
-        initial_sidebar_state="expanded"
-    )
+def chat_function(message, history):
+    """Chat function for Gradio interface"""
+    # Convert Gradio history format to our format
+    conversation_history = []
+    for human_msg, assistant_msg in history:
+        conversation_history.append({"role": "user", "content": human_msg})
+        conversation_history.append({"role": "assistant", "content": assistant_msg})
     
-    # Initialize session state
-    initialize_session_state()
+    # Generate response
+    response = yah_bot.generate_response(message, conversation_history)
+    return response
+
+def api_chat_endpoint(message: str, history: list = None):
+    """API endpoint function"""
+    if history is None:
+        history = []
     
-    # Header with beautiful gradient
-    col1, col2 = st.columns([1, 4])
-    with col1:
-        st.image("https://via.placeholder.com/100/2196f3/ffffff?text=YT", width=100)
-    with col2:
-        st.markdown('<h1 class="header-gradient">YAH Tech Assistant</h1>', unsafe_allow_html=True)
-        st.caption("🚀 Powered by AI • 💼 Venture Studio • 🌍 Economic Innovation")
+    conversation_history = []
+    for human_msg, assistant_msg in history:
+        conversation_history.append({"role": "user", "content": human_msg})
+        conversation_history.append({"role": "assistant", "content": assistant_msg})
     
-    st.markdown("---")
+    response = yah_bot.generate_response(message, conversation_history)
     
-    # Sidebar
-    with st.sidebar:
-        st.header("🏢 About YAH Tech")
-        st.markdown(f"""
+    return {
+        "response": response,
+        "status": "success",
+        "message": message
+    }
+
+# Custom CSS for styling
+custom_css = """
+.gradio-container {
+    background: linear-gradient(135deg, #f8f9fa 0%, #e3f2fd 100%);
+    font-family: 'Inter', sans-serif;
+}
+
+.chatbot {
+    border-radius: 16px;
+    box-shadow: 0 4px 20px rgba(0,0,0,0.1);
+}
+
+.user {
+    background: linear-gradient(135deg, #e3f2fd 0%, #bbdefb 100%) !important;
+    border-left: 6px solid #2196f3 !important;
+    border-radius: 16px !important;
+    margin: 12px 0 !important;
+}
+
+.bot {
+    background: linear-gradient(135deg, #ffffff 0%, #f5f5f5 100%) !important;
+    border-left: 6px solid #78909c !important;
+    border: 1px solid #e0e0e0 !important;
+    border-radius: 16px !important;
+    margin: 12px 0 !important;
+}
+
+.textbox {
+    border: 2px solid #90caf9 !important;
+    border-radius: 25px !important;
+    padding: 15px 20px !important;
+    font-size: 16px !important;
+    background: white !important;
+    box-shadow: 0 2px 10px rgba(33, 150, 243, 0.1) !important;
+}
+
+.button {
+    background: linear-gradient(135deg, #2196f3 0%, #1976d2 100%) !important;
+    color: white !important;
+    border: none !important;
+    border-radius: 25px !important;
+    padding: 12px 28px !important;
+    font-weight: 600 !important;
+    font-size: 16px !important;
+    box-shadow: 0 4px 12px rgba(33, 150, 243, 0.3) !important;
+}
+
+.button:hover {
+    transform: translateY(-2px);
+    box-shadow: 0 6px 16px rgba(33, 150, 243, 0.4) !important;
+}
+
+.header-gradient {
+    background: linear-gradient(135deg, #2196f3 0%, #1976d2 100%);
+    -webkit-background-clip: text;
+    -webkit-text-fill-color: transparent;
+    background-clip: text;
+}
+"""
+
+# Create the Gradio interface
+with gr.Blocks(css=custom_css, theme=gr.themes.Soft()) as demo:
+    gr.Markdown(
+        f"""
+        # <div class="header-gradient">YAH Tech Assistant</div>
+        🚀 Powered by AI • 💼 Venture Studio • 🌍 Economic Innovation
+        
         **👤 Founder**: {PERSONAL_INFO['name']}  
         **💼 Role**: {PERSONAL_INFO['role']}  
+        **🏢 Company**: {COMPANY_INFO['name']} - {COMPANY_INFO['type']}
         
-        **🏢 Company**: {COMPANY_INFO['name']}  
-        **🎯 Focus**: {COMPANY_INFO['type']}  
-        **📈 Stage**: {COMPANY_INFO['stage']}
-        
-        **💡 Philosophy**: *{COMPANY_INFO['philosophy']}*
-        """)
-        
-        st.markdown("---")
-        st.subheader("💬 Ask Me Anything")
-        st.markdown("""
-        **Examples:**
-        - *"What's the capital of France?"* 🇫🇷
-        - *"Tell me about AI technology"* 🤖  
-        - *"How to start a business?"* 💼
-        - *"What is YAH Tech?"* 🏢
-        - *"Who is Adedoyin James?"* 👤
-        """)
+        *Ask me anything - general knowledge or about YAH Tech!*
+        """
+    )
+    
+    gr.Markdown("---")
+    
+    with gr.Row():
+        with gr.Column(scale=3):
+            chatbot = gr.Chatbot(
+                label="YAH Tech Chat",
+                bubble_full_width=False,
+                show_copy_button=True,
+                avatar_images=(
+                    "https://via.placeholder.com/40/2196f3/ffffff?text=U", 
+                    "https://via.placeholder.com/40/78909c/ffffff?text=Y"
+                )
+            )
+            
+            with gr.Row():
+                msg = gr.Textbox(
+                    placeholder="💬 Ask me anything - general knowledge or about YAH Tech...",
+                    container=False,
+                    scale=4
+                )
+                clear_btn = gr.Button("🗑️ Clear", scale=1)
+            
+            gr.Markdown("""
+            **💡 Example questions:**
+            - *"What's the capital of France?"* 🇫🇷
+            - *"Tell me about AI technology"* 🤖  
+            - *"How to start a business?"* 💼
+            - *"What is YAH Tech?"* 🏢
+            - *"Who is Adedoyin James?"* 👤
+            """)
         
-        if st.button("🗑️ Clear Chat History", use_container_width=True):
-            st.session_state.messages = []
-            st.session_state.conversation_started = False
-            st.rerun()
+        with gr.Column(scale=1):
+            gr.Markdown("### 🏢 About YAH Tech")
+            gr.Markdown(f"""
+            **🎯 Focus**: {COMPANY_INFO['type']}  
+            **📈 Stage**: {COMPANY_INFO['stage']}
+            
+            **💡 Philosophy**: *"{COMPANY_INFO['philosophy']}"*
+            
+            **🎯 Purpose**: {COMPANY_INFO['purpose']}
+            
+            **🛠️ Services**:
+            • App development
+            • Venture building  
+            • Business system design
+            • Technology solutions
+            • Scalable platform development
+            """)
+            
+            gr.Markdown("---")
+            
+            gr.Markdown("### 🔗 API Usage")
+            gr.Markdown("""
+            ```python
+            import requests
+            
+            response = requests.post(
+                "YOUR_SPACE_URL/api/predict",
+                json={
+                    "data": [
+                        "Your message here", 
+                        []
+                    ]
+                }
+            )
+            ```
+            """)
+    
+    # Event handlers
+    def respond(message, chat_history):
+        bot_message = chat_function(message, chat_history)
+        chat_history.append((message, bot_message))
+        return "", chat_history
     
-    # Chat interface
-    if not st.session_state.conversation_started:
+    msg.submit(respond, [msg, chatbot], [msg, chatbot])
+    clear_btn.click(lambda: None, None, chatbot, queue=False)
+    
+    # Initial welcome message
+    def add_welcome_message(chat_history):
         welcome_msg = f"""
         👋 **Hello! I'm YAH Bot, your AI assistant for everything related to {PERSONAL_INFO['name']} and {COMPANY_INFO['name']}!** 
         
@@ -386,33 +438,17 @@ def main():
         
         **How can I assist you today?** 🚀
         """
-        st.info(welcome_msg)
-        st.session_state.conversation_started = True
-    
-    # Display chat messages
-    for message in st.session_state.messages:
-        with st.chat_message(message["role"]):
-            st.markdown(message["content"])
+        chat_history.append(("Hi", welcome_msg))
+        return chat_history
     
-    # Chat input
-    if prompt := st.chat_input("💬 Ask me anything - general knowledge or about YAH Tech..."):
-        # Add user message to chat history
-        st.session_state.messages.append({"role": "user", "content": prompt})
-        with st.chat_message("user"):
-            st.markdown(prompt)
-        
-        # Generate and display assistant response
-        with st.chat_message("assistant"):
-            with st.spinner("🤔 Thinking..."):
-                try:
-                    response = st.session_state.bot.generate_response(prompt, st.session_state.messages)
-                    st.markdown(response)
-                except Exception as e:
-                    error_msg = f"⚠️ I encountered an issue: {str(e)}\n\nBut at YAH Tech, we always find solutions! Feel free to ask me something else."
-                    st.markdown(error_msg)
-                    response = error_msg
-        
-        st.session_state.messages.append({"role": "assistant", "content": response})
+    demo.load(add_welcome_message, [chatbot], [chatbot])
 
+# For API usage, Gradio automatically creates endpoints at:
+# - /api/predict for the main chat function
+# - /info for space information
 if __name__ == "__main__":
-    main()
+    demo.launch(
+        share=True,
+        show_api=True,
+        server_name="0.0.0.
+        )