Update app.py

app.py

@@ -1,452 +1,456 @@
-import os
-import json
-import gradio as gr
-import google.generativeai as genai
-from datetime import datetime
-import time
-from typing import List, Dict, Any, Tuple
-
-# Import your existing modules
-try:
-    from intent_detector import detect_intent #type:ignore
-    from rag_utils import retrieve_profiles, retrieve_jobs, get_stats
-except ImportError:
-    print("Warning: Could not import custom modules. Some features may not work.")
-    def detect_intent(text, model=None):
-        return "SEARCH"
-    def retrieve_profiles(query, top_k=3):
-        return []
-    def retrieve_jobs(query, top_k=3):
-        return []
-    def get_stats():
-        return {"profiles_loaded": 0, "jobs_loaded": 0}
-
-# Configure Gemini
-API_KEY = os.getenv("GOOGLE_API_KEY")
-if API_KEY:
-    genai.configure(api_key=API_KEY) #type:ignore
-
-# System prompt
-SYSTEM_PROMPT = """
-You are a professional AI assistant that can perform three main tasks:
-
-1. **ONBOARD** - Help professionals create their profile (name, role, skills, experience, location)
-2. **SEARCH** - Find relevant job opportunities based on user requirements
-3. **POST** - Create structured job postings from client descriptions
-
-Respond in a friendly, professional manner. Keep responses concise but informative.
-"""
-
-def get_intent_emoji(intent: str) -> str:
-    """Get emoji for intent type."""
-    emoji_map = {
-        "ONBOARD": "👤",
-        "SEARCH": "🔍", 
-        "POST": "📝"
-    }
-    return emoji_map.get(intent, "🤖")
-
-def format_response(response: str, intent: str) -> str:
-    """Format response with intent indicator."""
-    emoji = get_intent_emoji(intent)
-    return f"{emoji} **{intent}**\n\n{response}"
-
-def process_message(message: str, history: List[List[str]], model_name: str) -> Tuple[str, List[List[str]]]:
-    """Process user message and return response with updated history."""
-    if not message.strip():
-        return "", history
-    
-    if not API_KEY:
-        error_msg = "❌ **Error**: Please set your GOOGLE_API_KEY environment variable."
-        history.append([message, error_msg])
-        return "", history
-    
-    try:
-        # Detect intent
-        intent = detect_intent(message, model=model_name)
-        
-        # Get context based on intent
-        context_block = ""
-        if intent == "SEARCH":
-            job_results = retrieve_jobs(message, top_k=3)
-            if job_results:
-                context_lines = []
-                for idx, job in enumerate(job_results, 1):
-                    context_lines.append(f"{idx}. {job['text'][:200]}...")
-                context_block = f"\n\n**Available Jobs:**\n" + "\n".join(context_lines)
-        elif intent == "ONBOARD":
-            profile_results = retrieve_profiles(message, top_k=3)
-            if profile_results:
-                context_lines = []
-                for idx, prof in enumerate(profile_results, 1):
-                    context_lines.append(f"{idx}. {prof['text'][:200]}...")
-                context_block = f"\n\n**Existing Profiles:**\n" + "\n".join(context_lines)
-        
-        # Prepare prompt
-        full_prompt = SYSTEM_PROMPT + context_block + f"\n\nUser: {message}\nAssistant:"
-        
-        # Generate response
-        model = genai.GenerativeModel(model_name)   #type:ignore
-        response = model.generate_content(full_prompt)
-        
-        # Format response
-        formatted_response = format_response(response.text, intent)
-        
-        # Update history
-        history.append([message, formatted_response])
-        
-        return "", history
-        
-    except Exception as e:
-        error_msg = f"❌ **Error**: {str(e)}"
-        history.append([message, error_msg])
-        return "", history
-
-def get_system_stats() -> str:
-    """Get system statistics."""
-    try:
-        stats = get_stats()
-        return f"""
-        📊 **System Status**
-        - Profiles loaded: {stats['profiles_loaded']}
-        - Jobs loaded: {stats['jobs_loaded']}
-        - API Status: {'✅ Connected' if API_KEY else '❌ Not configured'}
-        - Last updated: {datetime.now().strftime('%H:%M:%S')}
-        """
-    except:
-        return "📊 **System Status**: Unable to fetch stats"
-
-def create_sample_profiles() -> str:
-    """Generate sample profile data for testing."""
-    sample_data = [
-        {
-            "id": "prof_001",
-            "name": "Alice Johnson",
-            "role": "Full Stack Developer",
-            "skills": ["React", "Node.js", "Python", "PostgreSQL"],
-            "experience": "5 years",
-            "location": "San Francisco, CA"
-        },
-        {
-            "id": "prof_002", 
-            "name": "Bob Smith",
-            "role": "Data Scientist",
-            "skills": ["Python", "Machine Learning", "TensorFlow", "SQL"],
-            "experience": "3 years",
-            "location": "New York, NY"
-        }
-    ]
-    
-    os.makedirs("data", exist_ok=True)
-    with open("data/onboarding_profiles.jsonl", "w") as f:
-        for profile in sample_data:
-            f.write(json.dumps(profile) + "\n")
-    
-    return "✅ Sample profiles created successfully!"
-
-def create_sample_jobs() -> str:
-    """Generate sample job data for testing."""
-    sample_data = [
-        {
-            "id": "job_001",
-            "title": "Senior React Developer",
-            "company": "TechCorp",
-            "type": "Remote",
-            "skills": ["React", "TypeScript", "Node.js"],
-            "description": "Build scalable web applications using React and TypeScript",
-            "salary": "$80k-$120k",
-            "location": "Remote"
-        },
-        {
-            "id": "job_002",
-            "title": "Python Data Engineer", 
-            "company": "DataFlow Inc",
-            "type": "Hybrid",
-            "skills": ["Python", "Apache Spark", "AWS"],
-            "description": "Design and maintain data pipelines for machine learning models",
-            "salary": "$90k-$130k",
-            "location": "Seattle, WA"
-        }
-    ]
-    
-    os.makedirs("data", exist_ok=True)
-    with open("data/job_listings.jsonl", "w") as f:
-        for job in sample_data:
-            f.write(json.dumps(job) + "\n")
-    
-    return "✅ Sample jobs created successfully!"
-
-# Custom CSS for styling
-custom_css = """
-/* Main container styling */
-.gradio-container {
-    max-width: 1200px !important;
-    margin: 0 auto;
-    background: linear-gradient(135deg, #667eea 0%, #764ba2 100%);
-    min-height: 100vh;
-}
-
-/* Header styling */
-.header-section {
-    background: rgba(255, 255, 255, 0.1);
-    backdrop-filter: blur(10px);
-    padding: 20px;
-    border-radius: 15px;
-    margin-bottom: 20px;
-    border: 1px solid rgba(255, 255, 255, 0.2);
-}
-
-.header-section h1 {
-    color: white;
-    text-align: center;
-    font-size: 2.5em;
-    margin-bottom: 10px;
-    text-shadow: 2px 2px 4px rgba(0,0,0,0.3);
-}
-
-.header-section p {
-    color: rgba(255, 255, 255, 0.9);
-    text-align: center;
-    font-size: 1.1em;
-}
-
-/* Chat interface styling */
-.chat-container {
-    background: rgba(255, 255, 255, 0.95);
-    border-radius: 20px;
-    padding: 20px;
-    box-shadow: 0 20px 40px rgba(0, 0, 0, 0.1);
-    border: 1px solid rgba(255, 255, 255, 0.3);
-}
-
-/* Message styling */
-.message {
-    padding: 15px;
-    margin: 10px 0;
-    border-radius: 15px;
-    box-shadow: 0 4px 6px rgba(0, 0, 0, 0.1);
-}
-
-.user-message {
-    background: linear-gradient(135deg, #4f46e5, #7c3aed);
-    color: white;
-    margin-left: 20%;
-}
-
-.assistant-message {
-    background: linear-gradient(135deg, #f8fafc, #e2e8f0);
-    color: #1e293b;
-    margin-right: 20%;
-}
-
-/* Button styling */
-.action-button {
-    background: linear-gradient(135deg, #10b981, #059669);
-    color: white;
-    border: none;
-    padding: 12px 24px;
-    border-radius: 25px;
-    font-weight: 600;
-    transition: all 0.3s ease;
-    box-shadow: 0 4px 6px rgba(0, 0, 0, 0.1);
-}
-
-.action-button:hover {
-    transform: translateY(-2px);
-    box-shadow: 0 6px 12px rgba(0, 0, 0, 0.15);
-}
-
-/* Input styling */
-.input-box {
-    border: 2px solid #e5e7eb;
-    border-radius: 15px;
-    padding: 15px;
-    font-size: 16px;
-    transition: border-color 0.3s ease;
-}
-
-.input-box:focus {
-    border-color: #4f46e5;
-    box-shadow: 0 0 0 3px rgba(79, 70, 229, 0.1);
-}
-
-/* Stats panel styling */
-.stats-panel {
-    background: rgba(255, 255, 255, 0.1);
-    backdrop-filter: blur(10px);
-    border-radius: 15px;
-    padding: 15px;
-    border: 1px solid rgba(255, 255, 255, 0.2);
-    color: white;
-}
-
-/* Responsive design */
-@media (max-width: 768px) {
-    .gradio-container {
-        padding: 10px;
-    }
-    
-    .header-section h1 {
-        font-size: 2em;
-    }
-    
-    .user-message, .assistant-message {
-        margin-left: 5%;
-        margin-right: 5%;
-    }
-}
-"""
-
-# Sample conversation starters
-sample_conversations = [
-    "I'm a Python developer with 5 years experience in Django and React, based in San Francisco",
-    "Show me remote React developer jobs paying over $80k",
-    "I need to hire a full-stack developer for my startup, budget is $5000 for 3 months",
-    "Find me data science positions in New York",
-    "Looking for freelance web development work"
-]
-
-def create_interface():
-    """Create the Gradio interface."""
-    
-    with gr.Blocks(css=custom_css, title="Multi-Task Gemini Assistant") as demo:
-        # Header
-        gr.HTML("""
-        <div class="header-section">
-            <h1>🚀 Multi-Task Gemini Assistant</h1>
-            <p>Your AI-powered career companion for onboarding, job search, and posting opportunities</p>
-        </div>
-        """)
-        
-        with gr.Row():
-            with gr.Column(scale=3):
-                # Main chat interface
-                chatbot = gr.Chatbot(
-                    height=500,
-                    label="💬 Chat with Gemini",
-                    elem_classes=["chat-container"],
-                    bubble_full_width=False,
-                    show_label=True,
-                    avatar_images=("👤", "🤖")
-                )
-                
-                with gr.Row():
-                    msg = gr.Textbox(
-                        placeholder="Type your message here... (e.g., 'I'm a Python developer looking for work')",
-                        label="Your Message",
-                        elem_classes=["input-box"],
-                        scale=4
-                    )
-                    send_btn = gr.Button("Send 🚀", elem_classes=["action-button"], scale=1)
-                
-                # Sample conversation starters
-                gr.Markdown("### 💡 Try these examples:")
-                sample_buttons = []
-                for i, sample in enumerate(sample_conversations):
-                    btn = gr.Button(f"💬 {sample[:50]}{'...' if len(sample) > 50 else ''}", 
-                                  size="sm", variant="secondary")
-                    sample_buttons.append(btn)
-            
-            with gr.Column(scale=1):
-                # Control panel
-                gr.Markdown("### ⚙️ Settings")
-                
-                model_dropdown = gr.Dropdown(
-                    choices=["gemini-1.5-flash", "gemini-1.5-pro", "gemini-pro"],
-                    value="gemini-1.5-flash",
-                    label="🧠 Model",
-                    info="Choose your Gemini model"
-                )
-                
-                # System stats
-                stats_display = gr.Markdown(
-                    get_system_stats(),
-                    label="📊 System Status",
-                    elem_classes=["stats-panel"]
-                )
-                
-                refresh_stats_btn = gr.Button("🔄 Refresh Stats", size="sm")
-                
-                gr.Markdown("### 🛠️ Quick Actions")
-                
-                create_profiles_btn = gr.Button("👥 Create Sample Profiles", variant="secondary")
-                create_jobs_btn = gr.Button("💼 Create Sample Jobs", variant="secondary")
-                clear_chat_btn = gr.Button("🗑️ Clear Chat", variant="secondary")
-                
-                # Status messages
-                status_msg = gr.Markdown("", elem_classes=["stats-panel"])
-        
-        # Event handlers
-        def send_message(message, history, model):
-            return process_message(message, history, model)
-        
-        def set_sample_message(sample_text):
-            return sample_text
-        
-        def clear_chat():
-            return []
-        
-        def refresh_stats():
-            return get_system_stats()
-        
-        # Bind events
-        send_btn.click(
-            send_message,
-            inputs=[msg, chatbot, model_dropdown],
-            outputs=[msg, chatbot]
-        )
-        
-        msg.submit(
-            send_message,
-            inputs=[msg, chatbot, model_dropdown],
-            outputs=[msg, chatbot]
-        )
-        
-        # Sample button events
-        for i, btn in enumerate(sample_buttons):
-            btn.click(
-                lambda sample=sample_conversations[i]: sample,
-                outputs=msg
-            )
-        
-        refresh_stats_btn.click(refresh_stats, outputs=stats_display)
-        clear_chat_btn.click(clear_chat, outputs=chatbot)
-        create_profiles_btn.click(create_sample_profiles, outputs=status_msg)
-        create_jobs_btn.click(create_sample_jobs, outputs=status_msg)
-        
-        # Footer
-        gr.HTML("""
-        <div style="text-align: center; padding: 20px; color: rgba(255,255,255,0.8);">
-            <p>🌟 Powered by Google's Gemini AI | Built with ❤️ using Gradio</p>
-            <p>💡 <strong>Tips:</strong> Use natural language to describe your needs. The AI will automatically detect if you want to onboard, search for jobs, or post a job.</p>
-        </div>
-        """)
-    
-    return demo
-
-def main():
-    """Main function to launch the interface."""
-    print("🚀 Starting Multi-Task Gemini Assistant...")
-    
-    # Check API key
-    if not API_KEY:
-        print("⚠️  Warning: GOOGLE_API_KEY not found. Please set it as an environment variable.")
-        print("   Example: export GOOGLE_API_KEY='your-api-key-here'")
-    
-    # Create and launch interface
-    demo = create_interface()
-    
-    # Launch with custom settings
-    demo.launch(
-        server_name="0.0.0.0",  # Allow external access
-        server_port=7860,       # Default Gradio port
-        share=False,            # Set to True to create public link
-        debug=True,             # Enable debug mode
-        show_error=True,        # Show errors in interface
-        inbrowser=True,         # Open in browser automatically
-        favicon_path=None,      # Add custom favicon if needed
-        ssl_verify=False        # Disable SSL verification for development
-    )
-
-if __name__ == "__main__":
+import os
+import sys
+import json
+import time
+import gradio as gr
+import google.generativeai as genai
+
+from intent_detector import detect_intent
+from rag_utils import retrieve_profiles, retrieve_jobs
+
+# 1. Configure Gemini
+API_KEY = os.getenv("GOOGLE_API_KEY")
+if not API_KEY:
+    raise ValueError("Error: Set GOOGLE_API_KEY environment variable before running.")
+genai.configure(api_key=API_KEY)
+
+# 2. System prompt with conversational onboarding flow
+SYSTEM_PROMPT = """
+You are a helpful AI assistant that can perform three main tasks:
+
+1. ONBOARD – Help professionals create their profile by asking questions ONE AT A TIME in a natural conversation flow
+2. SEARCH – Help find job opportunities based on user requirements  
+3. POST – Help clients create structured job postings
+
+ONBOARDING CONVERSATION FLOW:
+When onboarding a user, ask questions in this specific order, ONE QUESTION AT A TIME:
+1. First, ask for their full name
+2. Then ask what their current role/job title is
+3. Then ask about their key skills (programming languages, technologies, etc.)
+4. Then ask about their years of experience 
+5. Then ask about their preferred location or if they want remote work
+6. Finally, summarize their profile and confirm if everything looks correct
+
+IMPORTANT ONBOARDING RULES:
+- Ask ONLY ONE question at a time
+- Wait for the user's response before asking the next question
+- Be conversational and friendly
+- If they provide multiple pieces of information at once, acknowledge what they shared and ask for what's still missing
+- Keep questions simple and clear
+- After collecting all information, show a summary and ask for confirmation
+
+SEARCH BEHAVIOR:
+For job searches, retrieve relevant listings and present them clearly with title, company, and key details.
+
+POST BEHAVIOR:  
+For job postings, help create structured JSON format job listings.
+
+Always be helpful, conversational, and ask follow-up questions when needed.
+"""
+
+class ChatbotState:
+    """Manages the conversation state for onboarding flow."""
+    
+    def __init__(self):
+        self.reset()
+    
+    def reset(self):
+        """Reset the conversation state."""
+        self.mode = None  # "onboarding", "search", "post", or None
+        self.onboarding_step = 0
+        self.user_data = {}
+        self.onboarding_complete = False
+    
+    def is_onboarding(self):
+        """Check if currently in onboarding mode."""
+        return self.mode == "onboarding" and not self.onboarding_complete
+    
+    def get_next_onboarding_question(self):
+        """Get the next question in the onboarding flow."""
+        questions = [
+            "What's your full name?",
+            "What's your current role or job title?", 
+            "What are your key skills? (For example: Python, React, project management, etc.)",
+            "How many years of experience do you have in your field?",
+            "What's your preferred work location? (Or would you prefer remote work?)"
+        ]
+        
+        if self.onboarding_step < len(questions):
+            return questions[self.onboarding_step]
+        return None
+    
+    def save_onboarding_data(self, field, value):
+        """Save user response to onboarding data."""
+        fields = ["name", "role", "skills", "experience", "location"]
+        if self.onboarding_step < len(fields):
+            self.user_data[fields[self.onboarding_step]] = value
+    
+    def get_onboarding_summary(self):
+        """Generate a summary of collected onboarding data."""
+        summary = "Here's your profile summary:\n"
+        summary += f"• Name: {self.user_data.get('name', 'Not provided')}\n"
+        summary += f"• Role: {self.user_data.get('role', 'Not provided')}\n"
+        summary += f"• Skills: {self.user_data.get('skills', 'Not provided')}\n"
+        summary += f"• Experience: {self.user_data.get('experience', 'Not provided')}\n"
+        summary += f"• Location: {self.user_data.get('location', 'Not provided')}\n"
+        summary += "\nDoes this look correct? (yes/no)"
+        return summary
+
+def save_user_profile(user_data, filename="data/user_profiles.jsonl"):
+    """Save user profile to file."""
+    os.makedirs(os.path.dirname(filename), exist_ok=True)
+    
+    # Create a unique ID for the user
+    user_id = f"user_{int(time.time())}"
+    
+    profile_entry = {
+        "id": user_id,
+        "name": user_data.get("name", ""),
+        "role": user_data.get("role", ""),
+        "skills": user_data.get("skills", "").split(", ") if user_data.get("skills") else [],
+        "experience": user_data.get("experience", ""),
+        "location": user_data.get("location", ""),
+        "timestamp": time.time()
+    }
+    
+    try:
+        with open(filename, "a", encoding="utf-8") as f:
+            f.write(json.dumps(profile_entry) + "\n")
+        return True
+    except Exception as e:
+        print(f"Error saving profile: {e}")
+        return False
+
+# Global state for the chatbot
+chatbot_state = ChatbotState()
+model = None
+
+def initialize_model(model_name="gemini-1.5-flash"):
+    """Initialize the Gemini model."""
+    global model
+    model = genai.GenerativeModel(model_name)
+    return model
+
+def process_message(message, history, model_name):
+    """Process user message and return bot response."""
+    global chatbot_state, model
+    
+    if model is None:
+        initialize_model(model_name)
+    
+    try:
+        # Handle onboarding flow
+        if chatbot_state.is_onboarding():
+            # Handle onboarding responses
+            if chatbot_state.onboarding_step < 5:  # Still collecting basic info
+                # Save the user's response
+                chatbot_state.save_onboarding_data(None, message)
+                chatbot_state.onboarding_step += 1
+                
+                # Check if we need to ask another question
+                if chatbot_state.onboarding_step < 5:
+                    next_question = chatbot_state.get_next_onboarding_question()
+                    return f"Great! {next_question}"
+                else:
+                    # All info collected, show summary
+                    summary = chatbot_state.get_onboarding_summary()
+                    return summary
+            
+            elif chatbot_state.onboarding_step == 5:  # Waiting for confirmation
+                if message.lower() in ["yes", "y", "correct", "looks good"]:
+                    # Save profile
+                    if save_user_profile(chatbot_state.user_data):
+                        response = "Perfect! Your profile has been saved successfully. You're now onboarded and ready to search for jobs! 🎉"
+                    else:
+                        response = "Your profile information has been recorded. You're now onboarded! 🎉"
+                    
+                    chatbot_state.onboarding_complete = True
+                    chatbot_state.mode = None
+                    return response
+                
+                elif message.lower() in ["no", "n", "incorrect", "wrong"]:
+                    chatbot_state.reset()
+                    chatbot_state.mode = "onboarding"
+                    chatbot_state.onboarding_step = 0
+                    return "No problem! Let's start over. What's your full name?"
+                
+                else:
+                    return "Please answer 'yes' if the information is correct, or 'no' if you'd like to start over."
+
+        # Regular intent detection for non-onboarding messages
+        intent = detect_intent(message, model=model_name)
+        print(f"[Debug] Detected intent: {intent}")
+
+        # Handle different intents
+        if intent == "ONBOARD":
+            # Start onboarding flow
+            chatbot_state.reset()
+            chatbot_state.mode = "onboarding"
+            
+            # Check if user already provided some info in their first message
+            first_question = chatbot_state.get_next_onboarding_question()
+            return f"I'd be happy to help you create your professional profile! Let's start with some basic information.\n\n{first_question}"
+
+        elif intent == "SEARCH":
+            # Handle job search
+            context_block = None
+            job_results = retrieve_jobs(message, top_k=3)
+            
+            if job_results:
+                lines = []
+                for idx, job in enumerate(job_results, start=1):
+                    lines.append(f"{idx}) {job['text']}")
+                block_text = "\n".join(lines)
+                context_block = f"Relevant job listings:\n{block_text}"
+                print(f"[Debug] Found {len(job_results)} relevant jobs")
+            else:
+                print("[Debug] No relevant jobs found")
+
+            # Prepare prompt for job search
+            search_prompt = f"""
+            {SYSTEM_PROMPT}
+            
+            {"Context Information: " + context_block if context_block else "No relevant jobs found in the database."}
+            
+            User is looking for jobs: {message}
+            
+            Please provide a helpful response about job opportunities. If jobs were found, present them clearly. If no jobs were found, provide helpful guidance on how they might refine their search.
+            """
+
+            response = model.generate_content(search_prompt)
+            return response.text
+
+        elif intent == "POST":
+            # Handle job posting creation
+            post_prompt = f"""
+            {SYSTEM_PROMPT}
+            
+            User wants to create a job posting: {message}
+            
+            Help them create a structured job posting. Ask for any missing information needed to create a complete job post (title, description, required skills, budget, timeline, etc.).
+            """
+
+            response = model.generate_content(post_prompt)
+            return response.text
+
+        else:
+            # General conversation
+            general_prompt = f"""
+            {SYSTEM_PROMPT}
+            
+            User message: {message}
+            
+            Respond helpfully. If they seem to want to get started with onboarding, job searching, or job posting, guide them appropriately.
+            """
+
+            response = model.generate_content(general_prompt)
+            return response.text
+
+    except Exception as e:
+        return f"Sorry, I encountered an error: {str(e)}. Please try again!"
+
+def reset_conversation():
+    """Reset the conversation state."""
+    global chatbot_state
+    chatbot_state.reset()
+    return [], ""
+
+def get_welcome_message():
+    """Get the initial welcome message."""
+    return """👋 **Welcome to AI Job Assistant!**
+
+I can help you with:
+• 🎯 **Creating your professional profile** - Let me guide you through a quick onboarding
+• 🔍 **Finding job opportunities** - Search for jobs that match your skills  
+• 📝 **Creating job postings** - Help employers post structured job listings
+
+What would you like to do today?"""
+
+# Custom CSS for a modern look
+custom_css = """
+.gradio-container {
+    font-family: 'Segoe UI', Tahoma, Geneva, Verdana, sans-serif;
+}
+
+.chat-message {
+    padding: 1rem;
+    margin: 0.5rem 0;
+    border-radius: 1rem;
+    max-width: 80%;
+}
+
+.user-message {
+    background: linear-gradient(135deg, #667eea 0%, #764ba2 100%);
+    color: white;
+    margin-left: auto;
+}
+
+.bot-message {
+    background: linear-gradient(135deg, #f093fb 0%, #f5576c 100%);
+    color: white;
+}
+
+/* Dark mode support */
+.dark .chat-message {
+    box-shadow: 0 4px 6px rgba(0, 0, 0, 0.3);
+}
+
+.gradio-chatbot {
+    height: 500px;
+}
+
+/* Custom button styles */
+.primary-button {
+    background: linear-gradient(135deg, #667eea 0%, #764ba2 100%);
+    border: none;
+    color: white;
+    padding: 0.5rem 1rem;
+    border-radius: 0.5rem;
+    font-weight: 500;
+    transition: all 0.3s ease;
+}
+
+.primary-button:hover {
+    transform: translateY(-2px);
+    box-shadow: 0 4px 12px rgba(102, 126, 234, 0.4);
+}
+"""
+
+def create_interface():
+    """Create the Gradio interface."""
+    
+    with gr.Blocks(
+        css=custom_css,
+        theme=gr.themes.Soft(
+            primary_hue="blue",
+            secondary_hue="purple",
+            neutral_hue="slate",
+        ),
+        title="AI Job Assistant"
+    ) as interface:
+        
+        gr.HTML("""
+        <div style="text-align: center; padding: 2rem; background: linear-gradient(135deg, #667eea 0%, #764ba2 100%); color: white; border-radius: 1rem; margin-bottom: 2rem;">
+            <h1 style="margin: 0; font-size: 2.5rem; font-weight: bold;">🤖 AI Job Assistant</h1>
+            <p style="margin: 0.5rem 0 0 0; font-size: 1.2rem; opacity: 0.9;">Your intelligent career companion</p>
+        </div>
+        """)
+        
+        with gr.Row():
+            with gr.Column(scale=4):
+                chatbot = gr.Chatbot(
+                    value=[[None, get_welcome_message()]],
+                    height=500,
+                    bubble_full_width=False,
+                    show_label=False,
+                    container=True,
+                    avatar_images=("👤", "🤖")
+                )
+                
+                with gr.Row():
+                    msg = gr.Textbox(
+                        placeholder="Type your message here...",
+                        show_label=False,
+                        scale=4,
+                        container=False
+                    )
+                    send_btn = gr.Button(
+                        "Send",
+                        variant="primary",
+                        scale=1,
+                        elem_classes=["primary-button"]
+                    )
+            
+            with gr.Column(scale=1, min_width=250):
+                gr.HTML("""
+                <div style="background: linear-gradient(135deg, #f093fb 0%, #f5576c 100%); color: white; padding: 1.5rem; border-radius: 1rem; margin-bottom: 1rem;">
+                    <h3 style="margin: 0 0 1rem 0;">🚀 Quick Actions</h3>
+                    <div style="font-size: 0.9rem; line-height: 1.6;">
+                        <div style="margin-bottom: 0.8rem;">
+                            <strong>💼 Get Started:</strong><br>
+                            "I want to create my profile"
+                        </div>
+                        <div style="margin-bottom: 0.8rem;">
+                            <strong>🔍 Find Jobs:</strong><br>
+                            "Show me Python developer jobs"
+                        </div>
+                        <div>
+                            <strong>📝 Post Job:</strong><br>
+                            "I want to post a job opening"
+                        </div>
+                    </div>
+                </div>
+                """)
+                
+                model_selector = gr.Dropdown(
+                    choices=["gemini-1.5-flash", "gemini-1.5-pro"],
+                    value="gemini-1.5-flash",
+                    label="🧠 AI Model",
+                    info="Choose your preferred AI model"
+                )
+                
+                clear_btn = gr.Button(
+                    "🗑️ Clear Chat",
+                    variant="secondary",
+                    size="sm"
+                )
+                
+                gr.HTML("""
+                <div style="background: rgba(102, 126, 234, 0.1); padding: 1rem; border-radius: 0.5rem; margin-top: 1rem;">
+                    <h4 style="margin: 0 0 0.5rem 0; color: #667eea;">ℹ️ Tips</h4>
+                    <ul style="margin: 0; padding-left: 1.2rem; font-size: 0.85rem; color: #666;">
+                        <li>Be specific about your skills and preferences</li>
+                        <li>Use natural language - I understand context!</li>
+                        <li>Ask follow-up questions anytime</li>
+                    </ul>
+                </div>
+                """)
+
+        # Event handlers
+        def respond(message, chat_history, model_name):
+            if not message.strip():
+                return chat_history, ""
+            
+            bot_message = process_message(message, chat_history, model_name)
+            chat_history.append([message, bot_message])
+            return chat_history, ""
+
+        def clear_chat():
+            reset_conversation()
+            return [[None, get_welcome_message()]], ""
+
+        # Wire up the events
+        msg.submit(respond, [msg, chatbot, model_selector], [chatbot, msg])
+        send_btn.click(respond, [msg, chatbot, model_selector], [chatbot, msg])
+        clear_btn.click(clear_chat, None, [chatbot, msg])
+        
+        # Auto-focus on textbox
+        interface.load(lambda: gr.update(focus=True), None, msg)
+
+    return interface
+
+def main():
+    """Main function to launch the Gradio interface."""
+    
+    # Initialize the model
+    chosen_model = sys.argv[1] if len(sys.argv) > 1 else "gemini-1.5-flash"
+    initialize_model(chosen_model)
+    
+    # Create and launch the interface
+    interface = create_interface()
+    
+    print("🚀 Launching AI Job Assistant...")
+    print("🌐 Opening in your default browser...")
+    
+    interface.launch(
+        server_name="0.0.0.0",  # Allow external access
+        server_port=7860,       # Default Gradio port
+        share=False,            # Set to True to create public link
+        show_error=True,
+        show_tips=True,
+        enable_queue=True,
+        max_threads=10
+    )
+
+if __name__ == "__main__":
     main()