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import streamlit as st
import base64
from io import BytesIO
import json
from datetime import datetime
import re

st.set_page_config(page_title="ResumeBuilder Pro", layout="wide", initial_sidebar_state="collapsed")

if "resume_data" not in st.session_state:
    st.session_state.resume_data = {
        "fullName": "Alexander Johnson",
        "title": "Senior Frontend Developer",
        "email": "[email protected]",
        "phone": "(555) 123-4567",
        "location": "San Francisco, CA",
        "summary": "Experienced frontend developer with 6+ years specializing in React and modern JavaScript frameworks. Passionate about creating intuitive user interfaces and optimizing web performance.",
        "experience": [
            {
                "id": 1,
                "company": "Tech Innovations Inc.",
                "position": "Senior Frontend Developer",
                "duration": "2019 - Present",
                "description": "Lead frontend development for enterprise SaaS platform. Improved performance by 40% through code optimization. Mentored junior developers."
            },
            {
                "id": 2,
                "company": "WebSolutions Co.",
                "position": "Frontend Developer",
                "duration": "2017 - 2019",
                "description": "Developed responsive web applications using React. Collaborated with design team to implement UI/UX improvements."
            }
        ],
        "education": [
            {
                "id": 1,
                "institution": "University of California, Berkeley",
                "degree": "B.S. Computer Science",
                "duration": "2013 - 2017"
            }
        ],
        "skills": ["React", "JavaScript", "TypeScript", "HTML/CSS", "Redux", "Next.js", "Tailwind CSS", "UI/UX Design"]
    }

if "dark_mode" not in st.session_state:
    st.session_state.dark_mode = False

if "show_preview" not in st.session_state:
    st.session_state.show_preview = True

if "new_skill" not in st.session_state:
    st.session_state.new_skill = ""
    
if "job_description" not in st.session_state:
    st.session_state.job_description = ""
    
if "ai_suggestions" not in st.session_state:
    st.session_state.ai_suggestions = {}
    
if "cover_letter" not in st.session_state:
    st.session_state.cover_letter = ""
    
if "suggested_skills" not in st.session_state:
    st.session_state.suggested_skills = []

# Define a flag to check if API functionality is available
if "gemini_available" not in st.session_state:
    st.session_state.gemini_available = False

# Try to import Google Generative AI library, but make it optional
try:
    import google.generativeai as genai
    st.session_state.gemini_import_success = True
except ImportError:
    st.session_state.gemini_import_success = False

# Apply custom styling based on dark/light mode
def apply_custom_styling():
    dark_mode = st.session_state.dark_mode
    primary_color = "#4F46E5"  # Indigo
    
    if dark_mode:
        background_color = "#111827"
        text_color = "#F9FAFB"
        card_bg = "#1F2937"
        input_bg = "#374151"
        secondary_bg = "#1E3A8A"
        accent_light = "#818CF8"
    else:
        background_color = "#F9FAFB"
        text_color = "#111827"
        card_bg = "#FFFFFF"
        input_bg = "#F3F4F6"
        secondary_bg = "#EEF2FF"
        accent_light = "#C7D2FE"
        

    css = f"""
    <style>
        /* Base colors and fonts */
        :root {{
            --primary-color: {primary_color};
            --bg-color: {background_color};
            --text-color: {text_color};
            --card-bg: {card_bg};
            --input-bg: {input_bg};
            --secondary-bg: {secondary_bg};
            --accent-light: {accent_light};
            --spacing-xs: 0.5rem;
            --spacing-sm: 0.75rem;
            --spacing-base: 1rem;
            --spacing-lg: 1.5rem;
            --spacing-xl: 2rem;
        }}

        /* Reset spacing */
        .stApp [data-testid="stVerticalBlock"] > div:not(:last-child) {{
            margin-bottom: var(--spacing-lg);
        }}

        /* Fix grid layout */
        .stApp [data-testid="stHorizontalBlock"] {{
            gap: var(--spacing-base);
            align-items: flex-start;
        }}

        .stApp [data-testid="stHorizontalBlock"] > div {{
            min-width: 0;
            flex: 1;
        }}

        /* Prevent content overflow */
        .element-container {{
            overflow: hidden;
            word-wrap: break-word;
        }}
        
        /* Main page styling */
        .main .block-container {{
            padding: var(--spacing-xl) var(--spacing-base);
            max-width: 1400px;
            margin: 0 auto;
        }}
        
        .stApp {{
            background-color: var(--bg-color);
            color: var(--text-color);
            overflow-x: hidden;
        }}

        /* Form layout improvements */
        .stForm > div {{
            margin-bottom: var(--spacing-xl);
        }}

        .stTextInput, .stTextArea {{
            margin-bottom: var(--spacing-base);
        }}

        /* Button spacing */
        .stButton {{
            margin: var(--spacing-base) 0;
        }}
        
        /* Header styling */
        h1, h2, h3, h4, h5, h6 {{
            color: var(--text-color);
        }}
        
        /* Make inputs match theme */
        .stTextInput > div > div > input,
        .stTextArea > div > div > textarea,
        .stSelectbox > div > div > select {{
            background-color: var(--input-bg);
            color: var(--text-color);
            border-radius: 0.375rem;
            padding: var(--spacing-sm);
            margin-bottom: var(--spacing-base);
        }}

        /* Unified focus states */
        input:focus, textarea:focus, select:focus {{
            outline: 2px solid var(--primary-color);
            outline-offset: 2px;
        }}
        
        /* Custom card styling */
        .custom-card {{
            background-color: var(--card-bg);
            border-radius: 0.5rem;
            padding: var(--spacing-lg);
            margin-bottom: var(--spacing-base);
            box-shadow: 0 4px 6px rgba(0, 0, 0, 0.1);
            position: relative;
            z-index: 1;
        }}

        /* Section spacing */
        .section {{
            margin-bottom: var(--spacing-xl);
        }}

        /* Form groups */
        .form-group {{
            margin-bottom: var(--spacing-lg);
        }}

        /* Input groups */
        .input-group {{
            display: flex;
            gap: var(--spacing-base);
            margin-bottom: var(--spacing-base);
        }}

        /* Responsive adjustments */
        @media (max-width: 768px) {{
            .stHorizontalBlock {{
                flex-direction: column;
            }}
            
            .input-group {{
                gap: var(--spacing-xs);
            }}

            .resume-container {{
                padding: var(--spacing-lg);
            }}
        }}
        
        /* AI feature styling */
        .ai-container {{
            background-color: var(--secondary-bg);
            border-radius: 0.5rem;
            padding: 1rem;
            margin-bottom: 1rem;
            border-left: 4px solid var(--primary-color);
        }}
        
        .ai-suggestion {{
            background-color: var(--accent-light);
            border-radius: 0.375rem;
            padding: 0.75rem;
            margin-top: 0.5rem;
            font-size: 0.875rem;
            border-left: 3px solid var(--primary-color);
        }}
        
        /* Resume preview styling */
        .resume-container {{
            background-color: white;
            color: #333;
            padding: 1.5rem;
            max-width: 800px;
            margin: 0 auto;
            font-family: 'Georgia', serif;
            line-height: 1.4;
            box-shadow: 0 1px 3px rgba(0, 0, 0, 0.1);
        }}
        
        /* Clean, minimal header */
        .resume-header {{
            text-align: center;
            margin-bottom: 1.5rem;
            padding-bottom: 1rem;
            border-bottom: 1px solid #eee;
        }}
        
        .resume-name {{
            font-size: 1.8rem;
            font-weight: normal;
            margin-bottom: 0.5rem;
            color: #333;
        }}
        
        .resume-title {{
            font-size: 1.2rem;
            color: #666;
            font-weight: normal;
            margin-bottom: 0.5rem;
        }}
        
        .contact-info {{
            font-size: 0.9rem;
            color: #666;
            display: flex;
            justify-content: center;
            gap: 1rem;
            flex-wrap: wrap;
        }}
        
        /* Clean section styling */
        .section-title {{
            font-size: 1.1rem;
            text-transform: uppercase;
            letter-spacing: 1px;
            color: #333;
            margin-top: 1.5rem;
            margin-bottom: 0.75rem;
            font-weight: normal;
            border-bottom: 1px solid #eee;
            padding-bottom: 0.25rem;
        }}
        
        /* Experience items */
        .experience-item {{
            margin-bottom: 1.25rem;
        }}
        
        .job-title {{
            font-weight: bold;
            font-size: 1rem;
            color: #333;
            margin-bottom: 0.25rem;
        }}
        
        .company-name {{
            font-weight: normal;
            font-size: 1rem;
            color: #333;
        }}
        
        .duration {{
            font-size: 0.9rem;
            color: #666;
            font-style: italic;
        }}
        
        .job-description {{
            font-size: 0.95rem;
            color: #444;
            margin-top: 0.5rem;
            line-height: 1.5;
        }}
        
        /* Education items */
        .education-item {{
            margin-bottom: 1rem;
        }}
        
        .institution {{
            font-weight: bold;
            font-size: 1rem;
            color: #333;
            margin-bottom: 0.25rem;
        }}
        
        .degree {{
            font-size: 0.95rem;
            color: #444;
        }}
        
        /* Skills */
        .skills-container {{
            display: flex;
            flex-wrap: wrap;
            gap: 0.5rem;
            margin-top: 0.5rem;
        }}
        
        .skill-tag {{
            background-color: #f5f5f5;
            color: #333;
            padding: 0.25rem 0.5rem;
            border-radius: 3px;
            font-size: 0.85rem;
            border: none;
        }}
        
        .recommended-skill {{
            display: inline-block;
            background-color: rgba(5, 150, 105, 0.1);
            color: #059669;
            padding: 0.35rem 0.7rem;
            border-radius: 9999px;
            margin-right: 0.5rem;
            margin-bottom: 0.5rem;
            font-size: 0.875rem;
            border: 1px dashed rgba(5, 150, 105, 0.5);
        }}
        
        /* Tab styling */
        button[data-baseweb="tab"] {{
            background-color: var(--secondary-bg);
            border-radius: 0.375rem 0.375rem 0 0;
        }}
        
        button[data-baseweb="tab"][aria-selected="true"] {{
            background-color: var(--primary-color) !important;
            color: white !important;
        }}
        
        div[data-testid="stVerticalBlock"] div[data-testid="stHorizontalBlock"] {{
            gap: 0.5rem;
        }}
        
        /* Section separators */
        hr {{
            margin: 1.5rem 0;
            border-color: {f"rgba(255,255,255,0.1)" if dark_mode else "rgba(0,0,0,0.1)"};
        }}
        
        /* Unified transition effects */
        .stButton > button,
        .custom-card {{
            transition: all 0.2s ease-in-out;
        }}

        /* Enhanced dark mode contrast */
        .stMarkdown {{
            color: var(--text-color) !important;
        }}

        /* Button styling */
        .stButton button {{
            border-radius: 0.375rem;
        }}

        /* Theme toggle styling */
        .theme-toggle button {{
            background-color: var(--primary-color) !important;
            color: var(--text-color) !important;
            border: 1px solid var(--accent-light);
            border-radius: 20px;
            padding: 8px 16px;
            margin: 0 var(--spacing-sm);
        }}

        .theme-toggle button:hover {{
            opacity: 0.9;
            transform: scale(1.02);
        }}
        
        /* Make the buttons in header look nicer */
        .header-button {{
            background-color: var(--card-bg) !important;
            color: var(--text-color) !important;
            border: 1px solid {f"rgba(255,255,255,0.2)" if dark_mode else "rgba(0,0,0,0.1)"} !important;
            border-radius: 0.375rem !important;
            padding: 0.5rem 1rem !important;
            font-size: 0.875rem !important;
            transition: all 0.2s ease !important;
        }}
        
        .header-button:hover {{
            background-color: {f"rgba(255,255,255,0.1)" if dark_mode else "rgba(0,0,0,0.05)"} !important;
            border-color: {f"rgba(255,255,255,0.3)" if dark_mode else "rgba(0,0,0,0.2)"} !important;
        }}
        
        /* Container styling */
        .content-container {{
            display: flex;
            gap: 1.5rem;
        }}
        
        /* Adjust form field spacing */
        div[data-baseweb="input"] {{
            margin-bottom: 0.75rem;
        }}
        
        /* Make the expander look cleaner */
        .st-emotion-cache-1r6slb0[data-testid="stExpander"] {{
            background-color: var(--card-bg);
            border-radius: 0.5rem;
            border: 1px solid {f"rgba(255,255,255,0.1)" if dark_mode else "rgba(0,0,0,0.1)"};
            margin-bottom: 1rem;
        }}
        
        /* Remove the border around the tab content area */
        .st-emotion-cache-cio0dv[data-testid="block-container"] {{
            padding-left: 0;
            padding-right: 0;
        }}

        /* Smaller margin for experience items */
        .experience-row {{
            margin-bottom: 0.25rem;
        }}
        
        /* AI button styling */
        .ai-button {{
            display: inline-flex;
            align-items: center;
            background-color: var(--primary-color);
            color: white;
            padding: 0.5rem 1rem;
            border-radius: 0.375rem;
            font-size: 0.875rem;
            font-weight: 500;
            border: none;
            cursor: pointer;
            transition: all 0.2s ease;
        }}
        
        .ai-button:hover {{
            background-color: #4338CA;
        }}
        
        /* API key container */
        .api-key-container {{
            margin-bottom: 1rem;
            padding: 1rem;
            background-color: {f"rgba(255,255,255,0.05)" if dark_mode else "rgba(0,0,0,0.03)"};
            border-radius: 0.5rem;
        }}
        
        /* Cover letter styling */
        .cover-letter {{
            background-color: white;
            color: #333;
            padding: 1.5rem;
            font-family: 'Georgia', serif;
            line-height: 1.6;
            box-shadow: 0 1px 3px rgba(0, 0, 0, 0.1);
            margin-top: 1rem;
        }}
        
        /* Match percentage meter */
        .match-meter {{
            height: 1rem;
            border-radius: 9999px;
            overflow: hidden;
            background-color: {f"rgba(255,255,255,0.1)" if dark_mode else "rgba(0,0,0,0.1)"};
            margin-top: 0.5rem;
            margin-bottom: 1rem;
        }}
        
        .match-fill {{
            height: 100%;
            background-color: var(--primary-color);
            transition: width 1s ease-in-out;
        }}
        
        /* Analysis result cards */
        .analysis-card {{
            background-color: {f"rgba(255,255,255,0.05)" if dark_mode else "rgba(255,255,255,0.8)"};
            border-radius: 0.5rem;
            padding: 1rem;
            margin-bottom: 1rem;
            border-left: 3px solid var(--primary-color);
        }}
        
        /* AI features banner */
        .ai-features-banner {{
            background-color: var(--accent-light);
            border-radius: 0.5rem;
            padding: 1rem;
            margin-bottom: 1rem;
            border: 1px dashed var(--primary-color);
            text-align: center;
        }}
        
        /* Print-friendly resume styles */
        @media print {{
            .resume-container {{
                box-shadow: none;
                padding: 0;
                max-width: 100%;
            }}
            
            .section-title {{
                color: #000 !important;
                border-bottom-color: #000 !important;
            }}
            
            .resume-name, .resume-title, .job-title, .institution {{
                color: #000 !important;
            }}
            
            .company-name {{
                color: #333 !important;
            }}
            
            .skill-tag {{
                border: 1px solid #ccc;
                background: #f5f5f5 !important;
                color: #333 !important;
            }}
        }}
    </style>
    """
    st.markdown(css, unsafe_allow_html=True)

# Function to download resume as JSON
def download_resume_json():
    json_str = json.dumps(st.session_state.resume_data, indent=2)
    b64 = base64.b64encode(json_str.encode()).decode()
    filename = f"resume_{datetime.now().strftime('%Y%m%d_%H%M%S')}.json"
    href = f'<a href="data:file/json;base64,{b64}" download="{filename}" class="header-button" style="text-decoration:none;padding:0.5rem 1rem;margin-right:0.5rem;">πŸ“„ Download JSON</a>'
    return href

# Function to create a placeholder for PDF export
def download_resume_pdf():
    # In a real app, you would generate an actual PDF here
    # For this example, we'll just return a placeholder button
    return '<button class="header-button" onclick="alert(\'PDF generation would be implemented here in a real app\');">πŸ“ƒ Export PDF</button>'

# Initialize Gemini API (modified to handle missing API key gracefully)
def initialize_gemini_api():
    if not st.session_state.gemini_import_success:
        st.warning("Google Generative AI library not installed. Install with: `pip install google-generativeai`")
        return False
    
    try:
        # Get API key from session state first (from text input)
        api_key = st.session_state.get("api_key", "")
        
        # Only try to configure if API key is provided
        if api_key:
            genai.configure(api_key=api_key)
            # Test the API with a simple call to verify it works
            model = genai.GenerativeModel(model_name="gemini-1.5-pro")
            _ = model.generate_content("Hello")
            return True
        else:
            # No API key provided yet, not an error
            return False
    except Exception as e:
        st.error(f"Failed to initialize Gemini API: {str(e)}")
        return False

# Function to get Gemini model response
def get_gemini_response(prompt, temperature=0.7):
    if not st.session_state.gemini_available:
        st.warning("Gemini API not available. Please set up your API key.")
        return None
    
    try:
        # Create the model
        generation_config = {
            "temperature": temperature,
            "top_p": 0.95,
            "top_k": 64,
            "max_output_tokens": 8192,
        }
        
        model = genai.GenerativeModel(
            model_name="gemini-1.5-pro",
            generation_config=generation_config,
        )
        
        response = model.generate_content(prompt)
        return response.text
    except Exception as e:
        st.error(f"Error getting AI response: {str(e)}")
        return None

# Main application header
def render_header():
    col1, col2 = st.columns([6, 4])
    
    with col1:
        ai_badge = '<span style="background-color: var(--primary-color); color: white; font-size: 0.6em; padding: 0.2em 0.5em; border-radius: 0.5em; margin-left: 0.5em;">AI-Ready</span>' if st.session_state.gemini_import_success else ""
        st.markdown(f'<h1 style="display:flex;align-items:center;"><span style="margin-right:10px;">πŸ“„</span> ResumeBuilder Pro {ai_badge}</h1>', unsafe_allow_html=True)
    
    with col2:
        download_buttons = f"""
        <div style="display:flex;justify-content:flex-end;align-items:center;gap:0.5rem;">
            {download_resume_json()}
            {download_resume_pdf()}
            <button class="header-button" onclick="document.querySelector('button[data-testid*=\\"baseButton-secondary\\"]').click();">
                {'πŸŒ™' if not st.session_state.dark_mode else 'β˜€οΈ'} Theme
            </button>
            <button class="header-button" onclick="document.querySelector('button[data-testid*=\\"baseButton-primary\\"]').click();">
                {'πŸ‘οΈ' if st.session_state.show_preview else 'πŸ‘οΈβ€πŸ—¨οΈ'} Preview
            </button>
        </div>
        """
        st.markdown(download_buttons, unsafe_allow_html=True)
        
        # Hidden buttons that are triggered by the custom buttons above
        col2_1, col2_2 = st.columns(2)
        with col2_1:
            if st.button("Toggle Theme", key="baseButton-secondary", type="secondary"):
                st.session_state.dark_mode = not st.session_state.dark_mode
                st.rerun()
        
        with col2_2:
            if st.button("Toggle Preview", key="baseButton-primary"):
                st.session_state.show_preview = not st.session_state.show_preview
                st.rerun()

# API Key Management - Improved to be more user-friendly and handle errors better
def manage_api_key():
    if "api_key" not in st.session_state:
        st.session_state.api_key = ""
    
    st.markdown('<div class="api-key-container">', unsafe_allow_html=True)
    
    # Show different message if the generative AI library is not installed
    if not st.session_state.gemini_import_success:
        st.markdown("### πŸ€– Enable AI Features")
        st.markdown("""
        To use AI features, you need to install the Google Generative AI library:
        ```
        pip install google-generativeai
        ```
        After installation, restart the app to access AI-powered resume enhancements.
        """)
        st.markdown('</div>', unsafe_allow_html=True)
        return

    # If library is installed but API key not set
    st.markdown("### πŸ”‘ Gemini API Setup")
    st.markdown("To use AI features, enter your Google Gemini API key below:")

    api_key = st.text_input("API Key", 
                          value=st.session_state.api_key, 
                          type="password",
                          placeholder="Enter your Gemini API key here",
                          key="api_key_input")

    col1, col2 = st.columns([1, 3])
    with col1:
        if st.button("Save API Key", key="save_api_key_button"):
            st.session_state.api_key = api_key
            if initialize_gemini_api():
                st.session_state.gemini_available = True
                st.success("API key saved and verified successfully!")
            else:
                if api_key:
                    st.error("Invalid API key. Please check and try again.")
                else:
                    st.warning("Please enter an API key to enable AI features.")

    with col2:
        st.markdown("Get your API key from [Google AI Studio](https://makersuite.google.com/app/apikey)")

    # Show what AI features are available
    if not st.session_state.gemini_available:
        st.markdown('<div class="ai-features-banner">', unsafe_allow_html=True)
        st.markdown("### ✨ Unlock AI Features")
        st.markdown("""
        By adding your API key, you'll unlock powerful AI features:
        
        - **Professional Summary Generator**: Create compelling summaries automatically
        - **Job Match Analysis**: Score your resume against job descriptions
        - **Skills Recommendations**: Get tailored skill suggestions for your role
        - **Experience Description Enhancement**: Make your work history more impactful
        - **Cover Letter Generator**: Create customized cover letters in seconds
        """)
        st.markdown('</div>', unsafe_allow_html=True)
    
    st.markdown('</div>', unsafe_allow_html=True)

# Generate AI summary function
def generate_ai_summary():
    data = st.session_state.resume_data
    prompt = f"""
    You are an expert resume writer. Generate a compelling professional summary for a resume with these details:

    Name: {data['fullName']}
    Current Position: {data['title']}
    Skills: {', '.join(data['skills'])}

    Experience:
    {' '.join([f"{exp['position']} at {exp['company']} ({exp['duration']}): {exp['description']}" for exp in data['experience']])}

    Education:
    {' '.join([f"{edu['degree']} from {edu['institution']} ({edu['duration']})" for edu in data['education']])}

    Rules for writing the summary:
    1. Keep it concise (3-4 sentences maximum)
    2. Highlight key skills and accomplishments
    3. Focus on value provided in past roles
    4. Use active language and avoid clichΓ©s
    5. Target it toward professional growth

    Write ONLY the summary. Don't include explanations or other text.
    """
    with st.spinner("Generating professional summary..."):
        summary = get_gemini_response(prompt, temperature=0.7)
        if summary:
            # Clean up the response
            summary = summary.strip().replace('"', '')
            
            return summary
        return None

# Job description analysis function
def analyze_job_description(job_description):
    data = st.session_state.resume_data

    prompt = f"""
    You are an expert resume consultant. Analyze this job description and the candidate's resume to provide insights.

    JOB DESCRIPTION:
    {job_description}

    CANDIDATE RESUME:
    Name: {data['fullName']}
    Current Position: {data['title']}
    Skills: {', '.join(data['skills'])}

    Experience:
    {' '.join([f"{exp['position']} at {exp['company']} ({exp['duration']}): {exp['description']}" for exp in data['experience']])}

    Education:
    {' '.join([f"{edu['degree']} from {edu['institution']} ({edu['duration']})" for edu in data['education']])}

    Provide the following in JSON format:
    1. "match_percentage": A numerical estimate (0-100) of how well the candidate's skills match the job requirements
    2. "missing_skills": A list of 3-5 key skills mentioned in the job that are missing from the candidate's resume
    3. "highlight_skills": A list of skills the candidate has that are particularly relevant to this job
    4. "emphasis_suggestions": 2-3 specific parts of the candidate's experience that should be emphasized for this job
    5. "improvement_tips": 2-3 brief suggestions to improve the resume for this specific job

    Return ONLY the JSON, formatted as follows:
    {{
      "match_percentage": number,
      "missing_skills": [list of strings],
      "highlight_skills": [list of strings],
      "emphasis_suggestions": [list of strings],
      "improvement_tips": [list of strings]
    }}
    """

    with st.spinner("Analyzing job description..."):
        analysis = get_gemini_response(prompt, temperature=0.2)
        if analysis:
            try:
                # Try to parse the entire response first
                try:
                    return json.loads(analysis)
                except json.JSONDecodeError:
                    # If direct parsing fails, try to extract JSON
                    json_match = re.search(r'\{[\s\S]*\}', analysis)
                    if json_match:
                        json_str = json_match.group(0)
                        return json.loads(json_str)
                    
                    # If still no valid JSON found, return None
                    return None

            except Exception as e:
                st.error(f"Error parsing AI response: {str(e)}")
                st.write("Raw response:", analysis)
                return None
        return None

# Generate cover letter function
def generate_cover_letter(job_description):
    data = st.session_state.resume_data

    prompt = f"""
    You are an expert cover letter writer. Create a professional cover letter based on this person's resume and the job description.
    
    JOB DESCRIPTION:
    {job_description}
    
    CANDIDATE RESUME:
    Name: {data['fullName']}
    Current Position: {data['title']}
    Skills: {', '.join(data['skills'])}
    
    Experience:
    {' '.join([f"{exp['position']} at {exp['company']} ({exp['duration']}): {exp['description']}" for exp in data['experience']])}
    
    Education:
    {' '.join([f"{edu['degree']} from {edu['institution']} ({edu['duration']})" for edu in data['education']])}
    
    Rules for the cover letter:
    1. Keep it concise (3-4 paragraphs)
    2. Personalize it to the job description
    3. Highlight relevant experience and skills
    4. Use professional language but maintain a conversational tone
    5. Include a strong opening and closing
    6. Don't include the date or contact information
    
    Write ONLY the cover letter content.
    """
    
    with st.spinner("Generating cover letter..."):
        cover_letter = get_gemini_response(prompt, temperature=0.7)
        if cover_letter:
            return cover_letter.strip()
        return None

# Main application layout
def main():
    # Apply custom styling
    apply_custom_styling()
    
    # Create a container for the entire app
    with st.container():
        # Render header
        render_header()
        
        # Create tabs
        tabs = st.tabs(["πŸ“ Resume Editor", "🎯 Job Match", "βœ‰οΈ Cover Letter"])
    
    # Edit Resume Tab
    with tabs[0]:
        if st.session_state.show_preview:
            col1, col2 = st.columns([3, 4])
        else:
            col1 = st.container()
        
        # Edit form in left column
        with col1:
            st.markdown('<div class="custom-card">', unsafe_allow_html=True)
            st.subheader("Personal Information")
            
            # Personal info fields
            st.session_state.resume_data["fullName"] = st.text_input("Full Name", value=st.session_state.resume_data["fullName"], key="fullname_input")
            st.session_state.resume_data["title"] = st.text_input("Professional Title", value=st.session_state.resume_data["title"], key="title_input")
            
            col1_1, col1_2 = st.columns(2)
            with col1_1:
                st.session_state.resume_data["email"] = st.text_input("Email", value=st.session_state.resume_data["email"], key="email_input")
            with col1_2:
                st.session_state.resume_data["phone"] = st.text_input("Phone", value=st.session_state.resume_data["phone"], key="phone_input")
            
            st.session_state.resume_data["location"] = st.text_input("Location", value=st.session_state.resume_data["location"], key="location_input")
            
            # Summary with AI assistance
            st.markdown("### Professional Summary")
            
            # Show AI button if API is available
            if st.session_state.gemini_available:
                sum_col1, sum_col2 = st.columns([5, 1])
                with sum_col1:
                    st.session_state.resume_data["summary"] = st.text_area(
                        "Summary (Professional Overview)", 
                        value=st.session_state.resume_data["summary"],
                        height=150,
                        key="summary_input"
                    )
                with sum_col2:
                    if st.button("✨ AI Generate", key="generate_summary"):
                        summary = generate_ai_summary()
                        if summary:
                            st.session_state.resume_data["summary"] = summary
                            st.rerun()
            else:
                st.session_state.resume_data["summary"] = st.text_area(
                    "Summary (Professional Overview)", 
                    value=st.session_state.resume_data["summary"],
                    height=150,
                    key="summary_input_no_ai"
                )
            
            st.markdown('</div>', unsafe_allow_html=True)  # End of personal info card
            
            # Experience section
            st.markdown('<div class="custom-card">', unsafe_allow_html=True)
            st.subheader("Experience")
            
            # Create fields for each experience item
            for i, exp in enumerate(st.session_state.resume_data["experience"]):
                col_exp1, col_exp2, col_exp3 = st.columns([4, 4, 2])
                
                with col_exp1:
                    st.session_state.resume_data["experience"][i]["position"] = st.text_input(
                        "Position/Title", 
                        value=exp["position"],
                        key=f"position_{i}"
                    )
                
                with col_exp2:
                    st.session_state.resume_data["experience"][i]["company"] = st.text_input(
                        "Company", 
                        value=exp["company"],
                        key=f"company_{i}"
                    )
                
                with col_exp3:
                    st.session_state.resume_data["experience"][i]["duration"] = st.text_input(
                        "Duration", 
                        value=exp["duration"],
                        key=f"duration_{i}"
                    )
                
                # Description with AI enhancement option
                if st.session_state.gemini_available:
                    desc_col1, desc_col2 = st.columns([5, 1])
                    with desc_col1:
                        st.session_state.resume_data["experience"][i]["description"] = st.text_area(
                            "Description", 
                            value=exp["description"], 
                            height=100,
                            key=f"description_{i}"
                        )
                    with desc_col2:
                        if st.button("✨ Enhance", key=f"enhance_desc_{i}"):
                            prompt = f"""
                            You are an expert resume writer. Improve this job description to make it more impactful and professional:
                            
                            "{exp["description"]}"
                            
                            Guidelines:
                            1. Use strong action verbs
                            2. Quantify achievements where possible
                            3. Highlight skills and technologies used
                            4. Keep similar length but make it more impactful
                            5. Focus on results and contributions
                            
                            Return ONLY the improved description without quotes or explanations.
                            """
                            enhanced_desc = get_gemini_response(prompt, temperature=0.7)
                            if enhanced_desc:
                                st.session_state.resume_data["experience"][i]["description"] = enhanced_desc.strip()
                                st.rerun()
                else:
                    st.session_state.resume_data["experience"][i]["description"] = st.text_area(
                        "Description", 
                        value=exp["description"], 
                        height=100,
                        key=f"description_no_ai_{i}"
                    )
                
                # Add buttons to remove this experience
                if st.button("πŸ—‘οΈ Remove this experience", key=f"remove_exp_{i}"):
                    if i < len(st.session_state.resume_data["experience"]):
                        st.session_state.resume_data["experience"].pop(i)
                        st.rerun()
                
                st.markdown("<hr>", unsafe_allow_html=True)
            
            # Add new experience button
            if st.button("βž• Add New Experience", key="add_new_experience"):
                # Find the highest ID and increment by 1
                max_id = 0
                for exp in st.session_state.resume_data["experience"]:
                    if exp["id"] > max_id:
                        max_id = exp["id"]
                
                st.session_state.resume_data["experience"].append({
                    "id": max_id + 1,
                    "company": "New Company",
                    "position": "Position Title",
                    "duration": "Start - End Date",
                    "description": "Describe your responsibilities and achievements."
                })
                st.rerun()
            
            st.markdown('</div>', unsafe_allow_html=True)  # End of experience card
            
            # Education section
            with st.container():
                st.markdown('<div class="custom-card">', unsafe_allow_html=True)
                st.subheader("Education")
                
                # Create fields for each education item
                for i, edu in enumerate(st.session_state.resume_data["education"]):
                    with st.container():
                        col_edu1, col_edu2, col_edu3 = st.columns([4, 4, 2], gap="small")
                        
                        with col_edu1:
                            st.session_state.resume_data["education"][i]["institution"] = st.text_input(
                                "Institution", 
                                value=edu["institution"],
                                key=f"edit_institution_{i}"
                            )
                        
                        with col_edu2:
                            st.session_state.resume_data["education"][i]["degree"] = st.text_input(
                                "Degree", 
                                value=edu["degree"],
                                key=f"edit_degree_{i}"
                            )
                        
                        with col_edu3:
                            st.session_state.resume_data["education"][i]["duration"] = st.text_input(
                                "Duration", 
                                value=edu["duration"],
                                key=f"edit_education_duration_{i}"
                            )
                    
                    # Add button to remove this education
                    if st.button("πŸ—‘οΈ Remove this education", key=f"remove_edu_{i}"):
                        st.session_state.resume_data["education"].pop(i)
                        st.rerun()
                    
                    st.markdown("<hr>", unsafe_allow_html=True)
                
                # Add new education button
                if st.button("βž• Add New Education", key="add_new_education"):
                    # Find the highest ID and increment by 1
                    max_id = 0
                    for edu in st.session_state.resume_data["education"]:
                        if edu["id"] > max_id:
                            max_id = edu["id"]
                    
                    st.session_state.resume_data["education"].append({
                        "id": max_id + 1,
                        "institution": "University/College Name",
                        "degree": "Degree Name",
                        "duration": "Start - End Date"
                    })
                    st.rerun()
                
                st.markdown('</div>', unsafe_allow_html=True)  # End of education card
            
            # Skills section
            with st.container():
                st.markdown('<div class="custom-card">', unsafe_allow_html=True)
                st.subheader("Skills")
                
                # Display current skills as tags with remove option
                with st.container():
                    st.markdown('<div class="skills-container" style="margin-bottom: 1.5rem; display: flex; flex-wrap: wrap; gap: 0.5rem;">', unsafe_allow_html=True)
                    for i, skill in enumerate(st.session_state.resume_data["skills"]):
                        st.markdown(
                            f'<span class="skill-tag" style="margin: 0;">{skill} <button style="background: none; border: none; color: inherit; cursor: pointer; padding: 0 0 0 0.25rem;" onclick="document.getElementById(\'remove_skill_{i}\').click();">βœ•</button></span>',
                            unsafe_allow_html=True
                        )
                        # Hidden button that will be triggered by the βœ• in the skill tag
                        if st.button("βœ•", key=f"remove_skill_{i}", type="secondary"):
                            st.session_state.resume_data["skills"].remove(skill)
                            st.rerun()
                    st.markdown('</div>', unsafe_allow_html=True)
                
                # Add new skill
                col_skill1, col_skill2 = st.columns([4, 1])
                
                with col_skill1:
                    new_skill = st.text_input("Add Skill", value=st.session_state.new_skill, key="new_skill_input")
                    st.session_state.new_skill = new_skill
                
                with col_skill2:
                    if st.button("Add", key="add_skill_button") and st.session_state.new_skill.strip():
                        if st.session_state.new_skill not in st.session_state.resume_data["skills"]:
                            st.session_state.resume_data["skills"].append(st.session_state.new_skill)
                            st.session_state.new_skill = ""
                            st.rerun()
                
                # AI skill suggestions if API is available
                if st.session_state.gemini_available:
                    if st.button("✨ Suggest relevant skills", key="suggest_skills_section1"):
                        with st.spinner("Generating skill suggestions..."):
                            # Create prompt using current resume data
                            prompt = f"""
                            You are a career advisor. Based on this person's profile, suggest 5-7 relevant technical skills they might want to add to their resume.
                            
                            Current professional title: {st.session_state.resume_data["title"]}
                            Current skills: {', '.join(st.session_state.resume_data["skills"])}
                            Experience:
                            {' '.join([f"{exp['position']} at {exp['company']}: {exp['description']}" for exp in st.session_state.resume_data["experience"]])}
                            
                            Return ONLY a Python list of strings with the skill names, like this:
                            ["Skill 1", "Skill 2", "Skill 3", "Skill 4", "Skill 5"]
                            
                            Suggest only skills that are NOT already listed. Focus on technical and professional skills relevant to their field.
                            """
                            
                            skills_response = get_gemini_response(prompt, temperature=0.2)
                            if skills_response:
                                try:
                                    # Improved parsing of AI response - more robust handling
                                    # First try to find a list pattern in the response
                                    list_pattern = re.search(r'\[.*?\]', skills_response, re.DOTALL)
                                    if list_pattern:
                                        list_str = list_pattern.group(0)
                                        # Try to safely parse the list
                                        try:
                                            suggested_skills = json.loads(list_str)
                                            if isinstance(suggested_skills, list):
                                                # Filter out skills they already have
                                                st.session_state.suggested_skills = [s for s in suggested_skills if s not in st.session_state.resume_data["skills"]]
                                            else:
                                                st.error("AI response was not in the expected format. Please try again.")
                                        except json.JSONDecodeError:
                                            # If JSON parsing fails, try a more lenient approach
                                            # Extract items that look like skills from the response
                                            skill_matches = re.findall(r'"([^"]+)"', list_str)
                                            if skill_matches:
                                                st.session_state.suggested_skills = [s for s in skill_matches if s not in st.session_state.resume_data["skills"]]
                                            else:
                                                st.error("Could not parse skills from AI response. Please try again.")
                                    else:
                                        # If no list pattern found, look for quoted strings that might be skills
                                        skill_matches = re.findall(r'"([^"]+)"', skills_response)
                                        if skill_matches:
                                            st.session_state.suggested_skills = [s for s in skill_matches if s not in st.session_state.resume_data["skills"]]
                                        else:
                                            st.error("Could not identify skills in AI response. Please try again.")
                                except Exception as e:
                                    st.error(f"Error processing skill suggestions: {str(e)}")
                    
                    # Display suggested skills if any
                    if st.session_state.suggested_skills:
                        st.markdown('<div style="margin-top: 1rem;">', unsafe_allow_html=True)
                        st.markdown("##### Suggested Skills:")
                        for i, skill in enumerate(st.session_state.suggested_skills):
                            st.markdown(
                                f'<span class="recommended-skill">{skill} <button style="background: none; border: none; color: inherit; cursor: pointer; padding: 0 0 0 0.25rem;" onclick="document.getElementById(\'add_suggested_skill_{i}\').click();">+</button></span>',
                                unsafe_allow_html=True
                            )
                            # Hidden button that will be triggered by the + in the skill tag
                            if st.button("+", key=f"add_suggested_skill_{i}", type="secondary"):
                                if skill not in st.session_state.resume_data["skills"]:
                                    st.session_state.resume_data["skills"].append(skill)
                                    st.session_state.suggested_skills.remove(skill)
                                    st.rerun()
                        st.markdown('</div>', unsafe_allow_html=True)
                
                st.markdown('</div>', unsafe_allow_html=True)  # End of skills card
        
        # Preview in right column (if enabled)
        if st.session_state.show_preview:
            if col2 is not None:
                with col2:
                    st.markdown('<div class="resume-container">', unsafe_allow_html=True)
                
                    # Header section with clean styling
                    st.markdown('<div class="resume-header">', unsafe_allow_html=True)
                    st.markdown(f'<div class="resume-name">{st.session_state.resume_data["fullName"]}</div>', unsafe_allow_html=True)
                    st.markdown(f'<div class="resume-title">{st.session_state.resume_data["title"]}</div>', unsafe_allow_html=True)
                
                    # Contact info with better spacing
                    contact_info = f'<div class="contact-info">'
                    contact_info += f'<span>{st.session_state.resume_data["email"]}</span>'
                    contact_info += f'<span>{st.session_state.resume_data["phone"]}</span>'
                    contact_info += f'<span>{st.session_state.resume_data["location"]}</span>'
                    contact_info += f'</div>'
                    st.markdown(contact_info, unsafe_allow_html=True)
                    st.markdown('</div>', unsafe_allow_html=True)
                    
                    # Summary
                    st.markdown('<div class="section-title">SUMMARY</div>', unsafe_allow_html=True)
                    st.markdown(f'<div>{st.session_state.resume_data["summary"]}</div>', unsafe_allow_html=True)
                    
                    # Experience
                    st.markdown('<div class="section-title">EXPERIENCE</div>', unsafe_allow_html=True)
                    for exp in st.session_state.resume_data["experience"]:
                        st.markdown(f'<div class="experience-item">', unsafe_allow_html=True)
                        st.markdown(f'<div class="job-title">{exp["position"]}</div>', unsafe_allow_html=True)
                        st.markdown(f'<div><span class="company-name">{exp["company"]}</span> <span class="duration">| {exp["duration"]}</span></div>', unsafe_allow_html=True)
                        st.markdown(f'<div class="job-description">{exp["description"]}</div>', unsafe_allow_html=True)
                        st.markdown('</div>', unsafe_allow_html=True)
                    
                    # Education
                    st.markdown('<div class="section-title">EDUCATION</div>', unsafe_allow_html=True)
                    for edu in st.session_state.resume_data["education"]:
                        st.markdown(f'<div class="education-item">', unsafe_allow_html=True)
                        st.markdown(f'<div class="institution">{edu["institution"]}</div>', unsafe_allow_html=True)
                        st.markdown(f'<div><span class="degree">{edu["degree"]}</span> <span class="duration">| {edu["duration"]}</span></div>', unsafe_allow_html=True)
                        st.markdown('</div>', unsafe_allow_html=True)
                    
                    # Skills
                    st.markdown('<div class="section-title">SKILLS</div>', unsafe_allow_html=True)
                    st.markdown('<div class="skills-container">', unsafe_allow_html=True)
                    for skill in st.session_state.resume_data["skills"]:
                        st.markdown(f'<span class="skill-tag">{skill}</span>', unsafe_allow_html=True)
                    st.markdown('</div>', unsafe_allow_html=True)
                    
                    st.markdown('</div>', unsafe_allow_html=True)  # End of resume preview container
                    
                    # Print button for resume
                    st.markdown('<div style="text-align: center; margin-top: 1rem;">', unsafe_allow_html=True)
                    st.markdown('<button class="header-button" onclick="window.print()">πŸ–¨οΈ Print Resume</button>', unsafe_allow_html=True)
                    st.markdown('</div>', unsafe_allow_html=True)
                    
                    # Import resume section
                    st.markdown('<div class="custom-card" style="margin-top: 1.5rem;">', unsafe_allow_html=True)
                    st.subheader("Import Resume")
                    uploaded_file = st.file_uploader("Import Resume JSON", type=["json"], key="resume_uploader")
                    if uploaded_file is not None:
                        try:
                            imported_data = json.loads(uploaded_file.getvalue().decode())
                            # Validate the imported data has the required fields
                            required_fields = ["fullName", "title", "email", "phone", "location", "summary", "experience", "education", "skills"]
                            if all(field in imported_data for field in required_fields):
                                st.session_state.resume_data = imported_data
                                st.success("Resume data imported successfully!")
                                st.rerun()
                            else:
                                st.error("Invalid resume data format. Please upload a valid JSON file.")
                        except Exception as e:
                            st.error(f"Error importing data: {str(e)}")
                    st.markdown('</div>', unsafe_allow_html=True)  # End of import card
                    
                    # About section
                    st.markdown('<div class="custom-card" style="margin-top: 1.5rem;">', unsafe_allow_html=True)
                    st.subheader("About ResumeBuilder Pro")
                    st.markdown("""
                    **ResumeBuilder Pro** is a streamlined tool for creating, editing, and optimizing resumes.
                    
                    Features:
                    - Create and edit professional resumes with a user-friendly interface
                    - AI-powered suggestions to enhance your resume content (with Gemini API)
                    - Match your resume against job descriptions
                    - Generate customized cover letters
                    - Export your resume in various formats
                    
                    Version 1.0.0
                    """)
                    st.markdown('</div>', unsafe_allow_html=True)  # End of about card
    
    # Job Match Tab
    with tabs[1]:
        st.markdown('<div class="custom-card">', unsafe_allow_html=True)
        st.subheader("Resume-Job Matching")
        
        if not st.session_state.gemini_available:
            manage_api_key()
        else:
            st.markdown("""
            Analyze how well your resume matches a specific job description. 
            Paste the job description below to get personalized recommendations.
            """)
            
            # Job description input
            st.session_state.job_description = st.text_area(
                "Paste the job description here", 
                height=200, 
                value=st.session_state.job_description,
                key="job_description_input"
            )
            
            if st.button("πŸ” Analyze Match", key="analyze_match_button") and st.session_state.job_description:
                analysis = analyze_job_description(st.session_state.job_description)
                if analysis:
                    st.session_state.ai_suggestions = analysis
                    # Extract suggested skills for adding to resume
                    if "missing_skills" in analysis:
                        st.session_state.suggested_skills = analysis["missing_skills"]
            
            # Display analysis results if available
            if st.session_state.ai_suggestions and "match_percentage" in st.session_state.ai_suggestions:
                match_percentage = st.session_state.ai_suggestions["match_percentage"]
                
                st.markdown(f"### Resume Match: {match_percentage}%")
                
                # Match percentage meter
                st.markdown(f'<div class="match-meter"><div class="match-fill" style="width:{match_percentage}%;"></div></div>', unsafe_allow_html=True)
                
                # Missing skills
                if "missing_skills" in st.session_state.ai_suggestions and st.session_state.ai_suggestions["missing_skills"]:
                    st.markdown('<div class="analysis-card">', unsafe_allow_html=True)
                    st.markdown("#### Missing Skills")
                    st.markdown("Consider adding these skills to your resume:")
                    for skill in st.session_state.ai_suggestions["missing_skills"]:
                        skill_hash = hash(skill)
                        st.markdown(
                            f'<span class="recommended-skill">{skill} <button style="background: none; border: none; color: inherit; cursor: pointer; padding: 0 0 0 0.25rem;" onclick="document.getElementById(\'add_missing_skill_{skill_hash}\').click();">+</button></span>',
                            unsafe_allow_html=True
                        )
                        if st.button("+", key=f"add_missing_skill_{skill_hash}", type="secondary"):
                            if skill not in st.session_state.resume_data["skills"]:
                                st.session_state.resume_data["skills"].append(skill)
                                st.rerun()
                    st.markdown('</div>', unsafe_allow_html=True)
                
                # Highlight skills
                if "highlight_skills" in st.session_state.ai_suggestions and st.session_state.ai_suggestions["highlight_skills"]:
                    st.markdown('<div class="analysis-card">', unsafe_allow_html=True)
                    st.markdown("#### Relevant Skills")
                    st.markdown("These skills from your resume are particularly relevant:")
                    for skill in st.session_state.ai_suggestions["highlight_skills"]:
                        st.markdown(f'<span class="skill-tag">{skill}</span>', unsafe_allow_html=True)
                    st.markdown('</div>', unsafe_allow_html=True)
                
                # Emphasis suggestions
                if "emphasis_suggestions" in st.session_state.ai_suggestions and st.session_state.ai_suggestions["emphasis_suggestions"]:
                    st.markdown('<div class="analysis-card">', unsafe_allow_html=True)
                    st.markdown("#### Emphasis Suggestions")
                    st.markdown("Consider emphasizing these aspects of your experience:")
                    for suggestion in st.session_state.ai_suggestions["emphasis_suggestions"]:
                        st.markdown(f"- {suggestion}")
                    st.markdown('</div>', unsafe_allow_html=True)
                
                # Improvement tips
                if "improvement_tips" in st.session_state.ai_suggestions and st.session_state.ai_suggestions["improvement_tips"]:
                    st.markdown('<div class="analysis-card">', unsafe_allow_html=True)
                    st.markdown("#### Improvement Tips")
                    for tip in st.session_state.ai_suggestions["improvement_tips"]:
                        st.markdown(f"- {tip}")
                    st.markdown('</div>', unsafe_allow_html=True)
                
                # Generate optimized summary button
                if st.button("✨ Generate Optimized Summary", key="generate_optimized_summary"):
                    summary = generate_ai_summary()
                    if summary:  # Only update if summary was successfully generated
                        st.session_state.resume_data["summary"] = summary
                        st.success("Professional summary updated to better match the job description!")
                        st.rerun()
        
        st.markdown('</div>', unsafe_allow_html=True)  # End of job match card
    
    # Cover Letter Tab
    with tabs[2]:
        st.markdown('<div class="custom-card">', unsafe_allow_html=True)
        st.subheader("Cover Letter Generator")
        
        if not st.session_state.gemini_available:
            manage_api_key()
        else:
            st.markdown("""
            Generate a customized cover letter based on your resume and a job description.
            Paste the job description below to create a tailored cover letter.
            """)
            
            # Job description input for cover letter
            job_desc_for_letter = st.text_area(
                "Paste the job description here", 
                height=200, 
                value=st.session_state.job_description,
                key="job_description_for_letter"
            )
            
            if st.button("✨ Generate Cover Letter", key="generate_cover_letter") and job_desc_for_letter:
                cover_letter = generate_cover_letter(job_desc_for_letter)
                if cover_letter:
                    st.session_state.cover_letter = cover_letter
            
            # Display and edit cover letter
            if st.session_state.cover_letter:
                st.markdown("### Your Cover Letter")
                st.session_state.cover_letter = st.text_area(
                    "Edit your cover letter as needed", 
                    value=st.session_state.cover_letter,
                    height=400,
                    key="cover_letter_editor"
                )
                
                # Display formatted cover letter
                st.markdown('<div class="cover-letter">', unsafe_allow_html=True)
                st.markdown(f"<p>{st.session_state.cover_letter.replace(chr(10), '<br>')}</p>", unsafe_allow_html=True)
                st.markdown('</div>', unsafe_allow_html=True)
                
                # Copy to clipboard button (note: this is a placeholder, as direct clipboard access requires JavaScript)
                st.markdown(
                    f'<button class="header-button" onclick="alert(\'Copy functionality would be implemented with JavaScript in a real app\');">πŸ“‹ Copy to Clipboard</button>',
                    unsafe_allow_html=True
                )
        
        st.markdown('</div>', unsafe_allow_html=True)  # End of cover letter card

# Entry point of the application
if __name__ == "__main__":
    # Try to import the Gemini library
    try:
        import google.generativeai as genai
        ST_GEMINI_IMPORT_SUCCESS = True
    except ImportError:
        ST_GEMINI_IMPORT_SUCCESS = False
        
    # Initialize session state variables if they don't exist
    if "initialized" not in st.session_state:
        # General app state
        st.session_state.initialized = True
        st.session_state.dark_mode = True  # Default to dark mode
        st.session_state.show_preview = True  # Show preview by default
        
        # API and AI state
        st.session_state.gemini_import_success = ST_GEMINI_IMPORT_SUCCESS
        st.session_state.gemini_available = False
        st.session_state.api_key = ""
        
        # Resume data
        st.session_state.resume_data = {
            "fullName": "Alexander Johnson",
            "title": "Senior Frontend Developer",
            "email": "[email protected]",
            "phone": "(555) 123-4567",
            "location": "San Francisco, CA",
            "summary": "Experienced frontend developer with 6+ years specializing in React and modern JavaScript frameworks. Passionate about creating intuitive user interfaces and optimizing web performance.",
            "experience": [
                {
                    "id": 1,
                    "company": "Tech Innovations Inc.",
                    "position": "Senior Frontend Developer",
                    "duration": "2019 - Present",
                    "description": "Lead frontend development for enterprise SaaS platform. Improved performance by 40% through code optimization. Mentored junior developers."
                },
                {
                    "id": 2,
                    "company": "WebSolutions Co.",
                    "position": "Frontend Developer",
                    "duration": "2017 - 2019",
                    "description": "Developed responsive web applications using React. Collaborated with design team to implement UI/UX improvements."
                }
            ],
            "education": [
                {
                    "id": 1,
                    "institution": "University of California, Berkeley",
                    "degree": "B.S. Computer Science",
                    "duration": "2013 - 2017"
                }
            ],
            "skills": ["React", "JavaScript", "TypeScript", "HTML/CSS", "Redux", "Next.js", "Tailwind CSS", "UI/UX Design"]
        }
        st.session_state.new_skill = ""
        st.session_state.suggested_skills = []
        
        # Job matching
        st.session_state.ai_suggestions = {}
        st.session_state.job_description = ""
        
        # Cover letter
        st.session_state.cover_letter = ""
    
    # Run the main application
    main()