Create app.py

app.py

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+import os
+import gradio as gr
+import re
+from datetime import datetime, timedelta
+import json
+import random
+from google.colab import userdata
+
+# Import LangChain components
+try:
+    from langchain_groq import ChatGroq
+    from langchain_core.prompts import PromptTemplate
+    from langchain_core.output_parsers import StrOutputParser
+    print("✅ All packages imported successfully!")
+except ImportError as e:
+    print(f"❌ Import Error: {e}")
+    print("\n⚠️ Please run the installation command first:")
+    print("!pip install --upgrade langchain langchain-core langchain-community langchain-groq gradio python-dotenv")
+    raise
+
+# =========================
+# API Key Configuration
+# =========================
+#GROQ_API_KEY = "add your api key or load from google secerets"
+
+GROQ_API_KEY = userdata.get('GROQ_API_KEY')
+
+
+# =========================
+# Initialize LLM
+# =========================
+try:
+    llm = ChatGroq(
+        temperature=0.7,
+        groq_api_key=GROQ_API_KEY,
+        model_name="llama-3.1-8b-instant"
+    )
+    print("✅ LLM initialized successfully!")
+except Exception as e:
+    print(f"❌ LLM initialization error: {e}")
+    raise
+
+# =========================
+# Enhanced Prompt Templates
+# =========================
+linkedin_template = """
+You are an expert LinkedIn content writer with 10+ years of experience.
+Create a highly engaging LinkedIn post that maximizes engagement.
+
+Requirements:
+- Start with a powerful hook that stops scrolling
+- Use short, punchy paragraphs (2-3 lines max)
+- Include storytelling elements or data points
+- Add 2-4 relevant emojis naturally throughout
+- Use line breaks for visual appeal
+- End with an engaging CTA
+- Word count: {word_count} words
+
+Topic: {topic}
+Tone: {tone}
+Target Audience: {audience}
+Post Type: {post_type}
+{hashtags_instruction}
+
+Write the post now with natural emoji placement.
+"""
+
+carousel_template = """
+Create a LinkedIn carousel post with {slides} slides.
+Each slide should have:
+- A catchy title (5-8 words)
+- 2-3 bullet points of content
+- Relevant emoji
+
+Topic: {topic}
+Tone: {tone}
+
+Format each slide as:
+SLIDE [number]:
+Title: [title]
+• [point 1]
+• [point 2]
+• [point 3]
+"""
+
+story_template = """
+Create a compelling LinkedIn story post about {topic}.
+Use the following structure:
+1. Opening hook (2-3 lines)
+2. The challenge/situation
+3. The turning point
+4. The lesson/insight
+5. Call to action
+
+Tone: {tone}
+Include emojis naturally.
+Target length: {word_count} words
+"""
+
+thread_template = """
+Create a LinkedIn thread with {posts} posts on {topic}.
+Each post should:
+- Be standalone valuable
+- Connect to the overall narrative
+- Be 100-150 words
+- Include relevant emojis
+
+Tone: {tone}
+Format as:
+POST 1/[total]:
+[content]
+
+POST 2/[total]:
+[content]
+"""
+
+# =========================
+# Post History Storage
+# =========================
+post_history = []
+
+def save_to_history(post, topic, tone, audience):
+    """Save generated post to history"""
+    entry = {
+        "timestamp": datetime.now().strftime("%Y-%m-%d %H:%M:%S"),
+        "post": post,
+        "topic": topic,
+        "tone": tone,
+        "audience": audience
+    }
+    post_history.insert(0, entry)
+    if len(post_history) > 50:
+        post_history.pop()
+    return format_history()
+
+def format_history():
+    """Format history for display"""
+    if not post_history:
+        return "No posts in history yet. Generate some posts to see them here!"
+
+    formatted = []
+    for idx, entry in enumerate(post_history[:10], 1):
+        formatted.append(f"""
+**Post #{idx}** - {entry['timestamp']}
+📝 Topic: {entry['topic']}
+🎭 Tone: {entry['tone']} | 🎯 Audience: {entry['audience']}
+
+{entry['post'][:200]}...
+
+---
+""")
+    return "\n".join(formatted)
+
+def get_post_from_history(post_number):
+    """Retrieve specific post from history"""
+    try:
+        idx = int(post_number) - 1
+        if 0 <= idx < len(post_history):
+            return post_history[idx]['post']
+        return "Invalid post number"
+    except:
+        return "Please enter a valid post number"
+
+# =========================
+# Schedule Optimizer
+# =========================
+def get_best_posting_times(industry, audience_location, goal):
+    """AI-powered posting time recommendations"""
+    template = """
+You are a LinkedIn marketing expert specializing in optimal posting times.
+
+Analyze and recommend the best 5 posting times for:
+Industry: {industry}
+Audience Location: {audience_location}
+Goal: {goal}
+
+Provide specific day and time recommendations with reasoning.
+Format as:
+1. [Day] at [Time] - [Reason]
+2. [Day] at [Time] - [Reason]
+...
+
+Also include:
+- Best day of week overall
+- Times to avoid
+- Frequency recommendation
+"""
+
+    prompt = PromptTemplate(
+        input_variables=["industry", "audience_location", "goal"],
+        template=template
+    )
+    chain = prompt | llm | StrOutputParser()
+
+    result = chain.invoke({
+        "industry": industry,
+        "audience_location": audience_location,
+        "goal": goal
+    })
+
+    return result
+
+# =========================
+# Competitor Analysis
+# =========================
+def analyze_competitor_post(competitor_post, your_niche):
+    """Analyze what makes a post successful"""
+    template = """
+You are a LinkedIn growth expert. Analyze this successful post and extract insights.
+
+Niche/Industry: {niche}
+
+Post to analyze:
+{post}
+
+Provide detailed analysis:
+1. **Hook Analysis**: Why the opening works
+2. **Structure**: How it's organized
+3. **Engagement Tactics**: What drives comments/shares
+4. **Key Elements**: Specific techniques used
+5. **Actionable Tips**: How to replicate success
+6. **Improvement Ideas**: What could make it even better
+
+Be specific and tactical.
+"""
+
+    prompt = PromptTemplate(
+        input_variables=["niche", "post"],
+        template=template
+    )
+    chain = prompt | llm | StrOutputParser()
+
+    result = chain.invoke({
+        "niche": your_niche,
+        "post": competitor_post
+    })
+
+    return result
+
+# =========================
+# Image Suggestion
+# =========================
+def suggest_images(post_content, post_type):
+    """AI suggests what images/visuals to use"""
+    template = """
+You are a visual content strategist for LinkedIn.
+
+Analyze this post and suggest the best visual content to accompany it.
+
+Post Type: {post_type}
+Post Content:
+{content}
+
+Suggest:
+1. **Primary Image Type**: (e.g., infographic, photo, illustration, chart)
+2. **Specific Visual Elements**: What should be shown
+3. **Color Scheme**: Recommended colors
+4. **Text Overlay**: What text (if any) should be on the image
+5. **Style Guidelines**: Professional, casual, modern, etc.
+6. **Alternative Options**: 2-3 other visual ideas
+7. **Stock Photo Keywords**: Keywords to search for the right image
+8. **Design Tools**: Recommended tools (Canva templates, etc.)
+
+Be specific and actionable.
+"""
+
+    prompt = PromptTemplate(
+        input_variables=["post_type", "content"],
+        template=template
+    )
+    chain = prompt | llm | StrOutputParser()
+
+    result = chain.invoke({
+        "post_type": post_type,
+        "content": post_content
+    })
+
+    return result
+
+# =========================
+# A/B Testing
+# =========================
+def generate_ab_versions(topic, tone, audience):
+    """Generate two different versions for A/B testing"""
+    template_a = """
+Create Version A - Hook-focused approach:
+
+Topic: {topic}
+Tone: {tone}
+Audience: {audience}
+
+Start with an extremely powerful, curiosity-driven hook.
+Focus on immediate attention-grabbing.
+Use pattern interrupts.
+150-200 words.
+"""
+
+    template_b = """
+Create Version B - Value-first approach:
+
+Topic: {topic}
+Tone: {tone}
+Audience: {audience}
+
+Start by immediately delivering value/insight.
+Focus on practical takeaways.
+Use data or specific examples.
+150-200 words.
+"""
+
+    prompt_a = PromptTemplate(input_variables=["topic", "tone", "audience"], template=template_a)
+    prompt_b = PromptTemplate(input_variables=["topic", "tone", "audience"], template=template_b)
+
+    chain_a = prompt_a | llm | StrOutputParser()
+    chain_b = prompt_b | llm | StrOutputParser()
+
+    version_a = chain_a.invoke({"topic": topic, "tone": tone, "audience": audience})
+    version_b = chain_b.invoke({"topic": topic, "tone": tone, "audience": audience})
+
+    version_a = fix_emoji_encoding(version_a)
+    version_b = fix_emoji_encoding(version_b)
+
+    analytics_a = analyze_post(version_a)
+    analytics_b = analyze_post(version_b)
+
+    comparison = f"""
+# 🅰️ VERSION A - Hook-Focused
+**Strategy**: Attention-grabbing hook, curiosity-driven
+
+{version_a}
+
+{format_analytics(analytics_a)}
+
+---
+
+# 🅱️ VERSION B - Value-First
+**Strategy**: Immediate value delivery, practical focus
+
+{version_b}
+
+{format_analytics(analytics_b)}
+
+---
+
+## 📊 A/B Testing Recommendations:
+- Test both versions at similar times (Tuesday/Wednesday morning)
+- Track: Impressions, Engagement Rate, Comments, Shares
+- Run each for 24-48 hours
+- The version with higher engagement rate (not just likes) wins
+- Consider your audience: C-level prefers Version B, broader audience may prefer Version A
+"""
+
+    return comparison
+
+# =========================
+# Trend Analyzer
+# =========================
+def analyze_linkedin_trends(industry, timeframe):
+    """Get current LinkedIn trending topics"""
+    template = """
+You are a LinkedIn trends analyst with access to current platform data.
+
+Analyze current LinkedIn trends for:
+Industry: {industry}
+Timeframe: {timeframe}
+
+Provide:
+1. **Top 5 Trending Topics**: What's getting traction now
+2. **Rising Hashtags**: Trending hashtags to use
+3. **Content Formats**: Which formats are performing best (text, carousel, video, etc.)
+4. **Engagement Patterns**: What drives engagement now
+5. **Topic Ideas**: 5 specific post ideas based on trends
+6. **What to Avoid**: Topics that are oversaturated
+
+Be current, specific, and actionable.
+"""
+
+    prompt = PromptTemplate(
+        input_variables=["industry", "timeframe"],
+        template=template
+    )
+    chain = prompt | llm | StrOutputParser()
+
+    result = chain.invoke({
+        "industry": industry,
+        "timeframe": timeframe
+    })
+
+    return result
+
+# =========================
+# Personal Branding
+# =========================
+def create_brand_voice(name, industry, values, personality, expertise):
+    """Create a consistent personal brand voice guide"""
+    template = """
+You are a personal branding expert. Create a comprehensive brand voice guide.
+
+Profile:
+- Name: {name}
+- Industry: {industry}
+- Core Values: {values}
+- Personality: {personality}
+- Key Expertise: {expertise}
+
+Create a detailed brand voice guide including:
+
+1. **Voice Characteristics**: 3-5 key traits
+2. **Tone Guidelines**:
+   - Professional contexts
+   - Casual contexts
+   - Thought leadership
+3. **Language Do's and Don'ts**:
+   - Preferred words/phrases
+   - Words to avoid
+4. **Signature Elements**:
+   - Opening styles
+   - Closing CTAs
+   - Emoji usage
+5. **Content Pillars**: 5 main topic areas
+6. **Example Phrases**: 10 on-brand phrases to use
+7. **Differentiation**: What makes this voice unique
+
+Be specific and actionable for consistent LinkedIn presence.
+"""
+
+    prompt = PromptTemplate(
+        input_variables=["name", "industry", "values", "personality", "expertise"],
+        template=template
+    )
+    chain = prompt | llm | StrOutputParser()
+
+    result = chain.invoke({
+        "name": name,
+        "industry": industry,
+        "values": values,
+        "personality": personality,
+        "expertise": expertise
+    })
+
+    return result
+
+def apply_brand_voice(post, brand_guide_summary):
+    """Apply brand voice to a post"""
+    template = """
+Rewrite this post to match the brand voice guidelines.
+
+Brand Voice Guidelines:
+{brand_guide}
+
+Original Post:
+{post}
+
+Rewrite maintaining the core message but adapting tone, language, and style to match the brand voice perfectly.
+"""
+
+    prompt = PromptTemplate(
+        input_variables=["brand_guide", "post"],
+        template=template
+    )
+    chain = prompt | llm | StrOutputParser()
+
+    result = chain.invoke({
+        "brand_guide": brand_guide_summary,
+        "post": post
+    })
+
+    return fix_emoji_encoding(result)
+
+# =========================
+# Export Functions - FIXED
+# =========================
+def export_as_text(content, filename="linkedin_post"):
+    """Export post as downloadable text file"""
+    if not content or not content.strip():
+        return None
+
+    timestamp = datetime.now().strftime("%Y%m%d_%H%M%S")
+    full_filename = f"{filename}_{timestamp}.txt"
+
+    # Create file in current directory for proper download
+    try:
+        with open(full_filename, 'w', encoding='utf-8') as f:
+            f.write(content)
+        return full_filename
+    except Exception as e:
+        print(f"Export error: {e}")
+        return None
+
+def create_post_document(posts_list):
+    """Create a formatted document with multiple posts"""
+    if not posts_list:
+        return ""
+
+    doc_content = f"""
+LinkedIn Content Package
+Generated: {datetime.now().strftime("%Y-%m-%d %H:%M:%S")}
+{'='*80}
+
+"""
+    for idx, post in enumerate(posts_list, 1):
+        doc_content += f"""
+POST #{idx}
+{'-'*80}
+{post}
+
+{'='*80}
+
+"""
+    return doc_content
+
+# =========================
+# Helper Functions
+# =========================
+def suggest_tone(topic):
+    topic_lower = topic.lower()
+    if any(word in topic_lower for word in ["success", "growth", "motivation", "inspire"]):
+        return "Inspirational"
+    elif any(word in topic_lower for word in ["team", "colleague", "work", "project", "career"]):
+        return "Professional"
+    elif any(word in topic_lower for word in ["data", "research", "analysis", "tech"]):
+        return "Analytical"
+    else:
+        return "Friendly"
+
+def suggest_hashtags(topic, count=5):
+    topic_lower = topic.lower()
+    hashtag_map = {
+        "ai": ["#AI", "#MachineLearning", "#DeepLearning", "#Tech", "#Innovation"],
+        "career": ["#Career", "#Growth", "#ProfessionalDevelopment", "#Leadership", "#Success"],
+        "team": ["#Teamwork", "#Collaboration", "#Productivity", "#Management", "#Culture"],
+        "marketing": ["#Marketing", "#DigitalMarketing", "#ContentMarketing", "#Strategy", "#Branding"],
+        "sales": ["#Sales", "#Business", "#B2B", "#Revenue", "#Growth"],
+        "leadership": ["#Leadership", "#Management", "#ExecutiveLeadership", "#Vision", "#Strategy"],
+        "startup": ["#Startup", "#Entrepreneur", "#Innovation", "#Business", "#VC"],
+        "data": ["#DataScience", "#Analytics", "#BigData", "#DataDriven", "#Insights"]
+    }
+
+    for key, hashtags in hashtag_map.items():
+        if key in topic_lower:
+            return " ".join(hashtags[:count])
+
+    return "#Inspiration #Learning #Success #Innovation #Growth"
+
+def analyze_post(post):
+    """Enhanced analytics"""
+    words = len(post.split())
+    paragraphs = post.count("\n\n") + 1
+    emojis = len(re.findall(r'[^\w\s,.]', post))
+    hashtags = len(re.findall(r'#\w+', post))
+    lines = post.count("\n") + 1
+
+    # Engagement score calculation
+    engagement_score = 0
+    if 150 <= words <= 250:
+        engagement_score += 30
+    elif words < 150:
+        engagement_score += 20
+    else:
+        engagement_score += 10
+
+    if 3 <= paragraphs <= 5:
+        engagement_score += 20
+
+    if 2 <= emojis <= 5:
+        engagement_score += 20
+
+    if 3 <= hashtags <= 5:
+        engagement_score += 15
+
+    if any(cta in post.lower() for cta in ["comment", "share", "thoughts", "agree", "experience"]):
+        engagement_score += 15
+
+    return {
+        "words": words,
+        "paragraphs": paragraphs,
+        "emojis": emojis,
+        "hashtags": hashtags,
+        "lines": lines,
+        "engagement_score": min(engagement_score, 100)
+    }
+
+def format_analytics(analytics):
+    return f"""
+📊 **Post Analytics**
+• Words: {analytics['words']}
+• Paragraphs: {analytics['paragraphs']}
+• Emojis: {analytics['emojis']}
+• Hashtags: {analytics['hashtags']}
+• Engagement Score: {analytics['engagement_score']}/100
+"""
+
+def fix_emoji_encoding(text):
+    try:
+        fixed = text.encode('latin-1').decode('utf-8')
+        return fixed
+    except (UnicodeDecodeError, UnicodeEncodeError):
+        return text
+
+def generate_post(topic, tone, audience, post_type, word_count, num_variations, custom_hashtags):
+    if not topic.strip():
+        return "Please enter a topic to generate a LinkedIn post."
+
+    # Determine hashtags
+    if custom_hashtags.strip():
+        hashtags = custom_hashtags
+        hashtags_instruction = f"Include these hashtags at the end: {hashtags}"
+    else:
+        hashtags = suggest_hashtags(topic)
+        hashtags_instruction = f"Suggest and include 3-5 relevant hashtags at the end"
+
+    # Select template based on post type
+    if post_type == "Standard Post":
+        template = linkedin_template
+        prompt = PromptTemplate(
+            input_variables=["topic", "tone", "audience", "post_type", "word_count", "hashtags_instruction"],
+            template=template
+        )
+        chain = prompt | llm | StrOutputParser()
+
+    elif post_type == "Story Post":
+        template = story_template
+        prompt = PromptTemplate(
+            input_variables=["topic", "tone", "word_count"],
+            template=template
+        )
+        chain = prompt | llm | StrOutputParser()
+
+    elif post_type == "Carousel (5 slides)":
+        template = carousel_template
+        prompt = PromptTemplate(
+            input_variables=["slides", "topic", "tone"],
+            template=template
+        )
+        chain = prompt | llm | StrOutputParser()
+
+    elif post_type == "Thread (3 posts)":
+        template = thread_template
+        prompt = PromptTemplate(
+            input_variables=["posts", "topic", "tone"],
+            template=template
+        )
+        chain = prompt | llm | StrOutputParser()
+
+    # Generate variations
+    variations = []
+    for i in range(num_variations):
+        if post_type == "Standard Post":
+            result = chain.invoke({
+                "topic": topic,
+                "tone": tone,
+                "audience": audience,
+                "post_type": post_type,
+                "word_count": word_count,
+                "hashtags_instruction": hashtags_instruction
+            })
+        elif post_type == "Story Post":
+            result = chain.invoke({
+                "topic": topic,
+                "tone": tone,
+                "word_count": word_count
+            })
+        elif post_type == "Carousel (5 slides)":
+            result = chain.invoke({
+                "slides": 5,
+                "topic": topic,
+                "tone": tone
+            })
+        elif post_type == "Thread (3 posts)":
+            result = chain.invoke({
+                "posts": 3,
+                "topic": topic,
+                "tone": tone
+            })
+
+        result = fix_emoji_encoding(result)
+        analytics = analyze_post(result)
+
+        formatted = f"**Variation {i+1}**\n\n{result}\n\n{format_analytics(analytics)}"
+        variations.append(formatted)
+
+        # Save to history
+        save_to_history(result, topic, tone, audience)
+
+    return "\n\n" + "="*80 + "\n\n".join(variations)
+
+def rewrite_post(original_post, instruction):
+    """Rewrite existing post based on user instruction"""
+    if not original_post.strip():
+        return "Please paste a post to rewrite."
+
+    rewrite_template = """
+You are a LinkedIn content expert. Rewrite the following post based on this instruction:
+
+Instruction: {instruction}
+
+Original Post:
+{original_post}
+
+Provide the rewritten version maintaining LinkedIn best practices.
+"""
+
+    prompt = PromptTemplate(
+        input_variables=["instruction", "original_post"],
+        template=rewrite_template
+    )
+    chain = prompt | llm | StrOutputParser()
+
+    result = chain.invoke({
+        "instruction": instruction,
+        "original_post": original_post
+    })
+
+    result = fix_emoji_encoding(result)
+    analytics = analyze_post(result)
+
+    return f"{result}\n\n{format_analytics(analytics)}"
+
+def generate_hashtag_suggestions(topic, count):
+    """AI-powered hashtag suggestions"""
+    template = """
+Generate {count} highly relevant and trending LinkedIn hashtags for this topic: {topic}
+
+Provide hashtags that:
+- Are currently popular on LinkedIn
+- Mix broad and niche hashtags
+- Include industry-specific tags
+- Balance reach and relevance
+
+Return only the hashtags separated by spaces, starting with #
+"""
+
+    prompt = PromptTemplate(
+        input_variables=["topic", "count"],
+        template=template
+    )
+    chain = prompt | llm | StrOutputParser()
+
+    result = chain.invoke({"topic": topic, "count": count})
+    return result.strip()
+
+def export_current_post(content):
+    """Export the current post as a text file - FIXED"""
+    if not content or not content.strip():
+        return None, "❌ Nothing to export! Generate a post first."
+
+    # Remove analytics section if present
+    if "📊 **Post Analytics**" in content:
+        content = content.split("📊 **Post Analytics**")[0].strip()
+
+    filepath = export_as_text(content, "linkedin_post")
+    if filepath:
+        return filepath, "✅ Post exported successfully!"
+    else:
+        return None, "❌ Export failed. Please try again."
+
+def export_history_package(count):
+    """Export multiple posts from history - FIXED"""
+    try:
+        count = int(count)
+        posts_to_export = [entry['post'] for entry in post_history[:count]]
+
+        if not posts_to_export:
+            return None, "No posts to export. Generate some posts first!"
+
+        content = create_post_document(posts_to_export)
+        filepath = export_as_text(content, "linkedin_posts_package")
+
+        if filepath:
+            return filepath, f"✅ Exported {len(posts_to_export)} posts successfully!"
+        else:
+            return None, "❌ Export failed. Please try again."
+    except Exception as e:
+        return None, f"❌ Export failed: {str(e)}"
+
+# =========================
+# Gradio Interface
+# =========================
+demo = gr.Blocks()
+
+with demo:
+    gr.Markdown(
+        """
+        # LinkedIn AI Writer
+        ### The Complete LinkedIn Content Creation Suite with 15+ AI-Powered Features
+        """
+    )
+
+    with gr.Tabs():
+        # Tab 1: Generate New Post
+        with gr.Tab("✍️ Generate Post"):
+            with gr.Row():
+                with gr.Column(scale=1):
+                    topic_input = gr.Textbox(
+                        label="📝 Topic",
+                        placeholder="e.g., How AI is transforming remote work...",
+                        lines=3
+                    )
+
+                    with gr.Row():
+                        tone_input = gr.Dropdown(
+                            ["Professional", "Friendly", "Inspirational", "Analytical", "Humorous"],
+                            label="🎭 Tone",
+                            value="Professional"
+                        )
+                        audience_input = gr.Dropdown(
+                            ["General", "C-Level Executives", "Managers", "Individual Contributors", "Students", "Entrepreneurs"],
+                            label="🎯 Target Audience",
+                            value="General"
+                        )
+
+                    with gr.Row():
+                        post_type_input = gr.Dropdown(
+                            ["Standard Post", "Story Post", "Carousel (5 slides)", "Thread (3 posts)"],
+                            label="📄 Post Type",
+                            value="Standard Post"
+                        )
+                        word_count_input = gr.Slider(
+                            minimum=100,
+                            maximum=300,
+                            step=25,
+                            value=200,
+                            label="📏 Word Count"
+                        )
+
+                    num_variations_input = gr.Slider(
+                        minimum=1,
+                        maximum=3,
+                        step=1,
+                        value=1,
+                        label="🔢 Number of Variations"
+                    )
+
+                    custom_hashtags_input = gr.Textbox(
+                        label="🏷️ Custom Hashtags (optional)",
+                        placeholder="#AI #Innovation #Tech"
+                    )
+
+                    with gr.Row():
+                        generate_button = gr.Button("✨ Generate Post", variant="primary", size="lg")
+                        suggest_hashtags_button = gr.Button("💡 Suggest Hashtags")
+
+                with gr.Column(scale=2):
+                    output_box = gr.Textbox(
+                        label="📄 Generated Post",
+                        lines=25,
+                        interactive=True,
+                        elem_classes="output-text"
+                    )
+
+                    with gr.Row():
+                        copy_button = gr.Button("📋 Copy", size="sm")
+                        export_button = gr.Button("💾 Export as .txt", size="sm")
+
+                    with gr.Row():
+                        copy_status = gr.Textbox(label="", interactive=False, show_label=False, lines=1)
+
+                    export_file = gr.File(label="📥 Download File", interactive=False, type="filepath")
+
+        # Tab 2: A/B Testing
+        with gr.Tab("🔬 A/B Testing"):
+            gr.Markdown("### Generate two versions of your post optimized for different strategies")
+            with gr.Row():
+                with gr.Column():
+                    ab_topic = gr.Textbox(label="📝 Topic", placeholder="Enter your topic...", lines=3)
+                    with gr.Row():
+                        ab_tone = gr.Dropdown(
+                            ["Professional", "Friendly", "Inspirational", "Analytical"],
+                            label="🎭 Tone",
+                            value="Professional"
+                        )
+                        ab_audience = gr.Dropdown(
+                            ["General", "C-Level Executives", "Managers", "Individual Contributors"],
+                            label="🎯 Audience",
+                            value="General"
+                        )
+                    ab_button = gr.Button("🔬 Generate A/B Versions", variant="primary")
+
+                with gr.Column():
+                    ab_output = gr.Textbox(label="📊 A/B Test Results", lines=30, interactive=True)
+
+        # Tab 3: Schedule Optimizer
+        with gr.Tab("📅 Schedule Optimizer"):
+            gr.Markdown("### Find the perfect time to post based on your industry and audience")
+            with gr.Row():
+                with gr.Column():
+                    schedule_industry = gr.Textbox(
+                        label="🏢 Your Industry",
+                        placeholder="e.g., Technology, Marketing, Finance..."
+                    )
+                    schedule_location = gr.Dropdown(
+                        ["North America (EST)", "Europe (CET)", "Asia Pacific", "Global/Mixed"],
+                        label="🌍 Primary Audience Location",
+                        value="North America (EST)"
+                    )
+                    schedule_goal = gr.Dropdown(
+                        ["Maximum Reach", "Engagement (Comments/Shares)", "Lead Generation", "Thought Leadership"],
+                        label="🎯 Primary Goal",
+                        value="Maximum Reach"
+                    )
+                    schedule_button = gr.Button("⏰ Get Optimal Times", variant="primary")
+
+                with gr.Column():
+                    schedule_output = gr.Textbox(label="📅 Recommended Posting Schedule", lines=20)
+
+        # Tab 4: Competitor Analysis
+        with gr.Tab("🔍 Competitor Analysis"):
+            gr.Markdown("### Analyze successful posts to understand what works")
+            with gr.Row():
+                with gr.Column():
+                    competitor_post = gr.Textbox(
+                        label="📝 Paste Competitor's Post",
+                        placeholder="Paste the successful post you want to analyze...",
+                        lines=10
+                    )
+                    competitor_niche = gr.Textbox(
+                        label="🎯 Your Niche/Industry",
+                        placeholder="e.g., SaaS Marketing, Data Science..."
+                    )
+                    analyze_button = gr.Button("🔍 Analyze Post", variant="primary")
+
+                with gr.Column():
+                    competitor_output = gr.Textbox(label="📊 Analysis Results", lines=25)
+
+        # Tab 5: Image Suggestions
+        with gr.Tab("🖼️ Image Suggestions"):
+            gr.Markdown("### Get AI-powered recommendations for visual content")
+            with gr.Row():
+                with gr.Column():
+                    image_post = gr.Textbox(
+                        label="📝 Your Post Content",
+                        placeholder="Paste your post here...",
+                        lines=10
+                    )
+                    image_type = gr.Dropdown(
+                        ["Standard Post", "Story Post", "Carousel", "Article Cover"],
+                        label="📄 Post Type",
+                        value="Standard Post"
+                    )
+                    image_button = gr.Button("🎨 Get Image Suggestions", variant="primary")
+
+                with gr.Column():
+                    image_output = gr.Textbox(label="🖼️ Visual Recommendations", lines=25)
+
+        # Tab 6: Trend Analyzer
+        with gr.Tab("📈 Trend Analyzer"):
+            gr.Markdown("### Discover what's trending in your industry on LinkedIn")
+            with gr.Row():
+                with gr.Column():
+                    trend_industry = gr.Textbox(
+                        label="🏢 Industry",
+                        placeholder="e.g., AI, Marketing, Fintech..."
+                    )
+                    trend_timeframe = gr.Dropdown(
+                        ["Last 7 days", "Last 30 days", "Last 3 months"],
+                        label="⏰ Timeframe",
+                        value="Last 30 days"
+                    )
+                    trend_button = gr.Button("📊 Analyze Trends", variant="primary")
+
+                with gr.Column():
+                    trend_output = gr.Textbox(label="📈 Trending Topics & Insights", lines=25)
+
+        # Tab 7: Personal Branding
+        with gr.Tab("🎭 Personal Branding"):
+            gr.Markdown("### Create your unique brand voice for consistent LinkedIn presence")
+
+            with gr.Tabs():
+                with gr.Tab("Create Brand Voice"):
+                    with gr.Row():
+                        with gr.Column():
+                            brand_name = gr.Textbox(label="👤 Your Name", placeholder="John Doe")
+                            brand_industry = gr.Textbox(label="🏢 Industry", placeholder="e.g., Digital Marketing")
+                            brand_values = gr.Textbox(
+                                label="💎 Core Values",
+                                placeholder="e.g., Innovation, Authenticity, Growth",
+                                lines=2
+                            )
+                            brand_personality = gr.Textbox(
+                                label="🎭 Personality Traits",
+                                placeholder="e.g., Approachable, Data-driven, Creative",
+                                lines=2
+                            )
+                            brand_expertise = gr.Textbox(
+                                label="🎓 Key Expertise",
+                                placeholder="e.g., Content Strategy, SEO, Brand Building",
+                                lines=2
+                            )
+                            brand_create_button = gr.Button("✨ Create Brand Voice Guide", variant="primary")
+
+                        with gr.Column():
+                            brand_output = gr.Textbox(label="📋 Your Brand Voice Guide", lines=30)
+
+                with gr.Tab("Apply Brand Voice"):
+                    with gr.Row():
+                        with gr.Column():
+                            apply_post = gr.Textbox(
+                                label="📝 Post to Brand",
+                                placeholder="Paste any post here to adapt it to your brand voice...",
+                                lines=10
+                            )
+                            apply_guide = gr.Textbox(
+                                label="📋 Brand Guidelines (summary)",
+                                placeholder="Paste key points from your brand guide...",
+                                lines=5
+                            )
+                            apply_button = gr.Button("🎨 Apply Brand Voice", variant="primary")
+
+                        with gr.Column():
+                            apply_output = gr.Textbox(label="✨ Branded Post", lines=20)
+
+        # Tab 8: Rewrite Post
+        with gr.Tab("🔄 Rewrite Post"):
+            with gr.Row():
+                with gr.Column():
+                    original_post_input = gr.Textbox(
+                        label="📝 Paste Your Post",
+                        placeholder="Paste your LinkedIn post here...",
+                        lines=10
+                    )
+                    rewrite_instruction = gr.Textbox(
+                        label="✏️ Rewrite Instruction",
+                        placeholder="e.g., Make it more professional, Add storytelling, Shorten it...",
+                        lines=3
+                    )
+                    rewrite_button = gr.Button("🔄 Rewrite Post", variant="primary")
+
+                with gr.Column():
+                    rewrite_output = gr.Textbox(
+                        label="✨ Rewritten Post",
+                        lines=15,
+                        interactive=True
+                    )
+
+        # Tab 9: Post History
+        with gr.Tab("📚 Post History"):
+            gr.Markdown("### View and manage your generated posts")
+            with gr.Row():
+                with gr.Column(scale=2):
+                    history_display = gr.Textbox(
+                        label="📜 Recent Posts (Last 10)",
+                        lines=30,
+                        value=format_history(),
+                        interactive=False
+                    )
+                    refresh_history_button = gr.Button("🔄 Refresh History")
+
+                with gr.Column(scale=1):
+                    gr.Markdown("### Load Post from History")
+                    load_post_number = gr.Number(
+                        label="Post Number",
+                        value=1,
+                        precision=0
+                    )
+                    load_button = gr.Button("📥 Load Post")
+                    loaded_post = gr.Textbox(label="Loaded Post", lines=15, interactive=True)
+
+                    gr.Markdown("### Export Multiple Posts")
+                    export_count = gr.Slider(
+                        minimum=1,
+                        maximum=10,
+                        step=1,
+                        value=5,
+                        label="Number of posts to export"
+                    )
+                    export_all_button = gr.Button("💾 Export Package")
+                    export_status = gr.Textbox(label="Export Status", lines=2)
+                    export_package_file = gr.File(label="📥 Download Package", interactive=False, type="filepath")
+
+        # Tab 10: Tips & Best Practices
+        with gr.Tab("💡 Tips & Best Practices"):
+            gr.Markdown(
+                """
+                ## 🎯 LinkedIn Best Practices
+
+                ### 📈 Maximize Engagement:
+                - **Hook in first 2 lines**: Grab attention immediately
+                - **Use line breaks**: Make posts visually scannable
+                - **Include data/numbers**: Specific metrics build credibility
+                - **Add storytelling**: Personal experiences resonate
+                - **End with CTA**: Ask questions, request opinions
+
+                ### ✅ Optimal Post Structure:
+                1. **Hook** (1-2 lines) - Stop the scroll
+                2. **Context/Story** (3-5 lines) - Build connection
+                3. **Key Points** (bullet points work well) - Deliver value
+                4. **Conclusion/Insight** (2-3 lines) - Tie it together
+                5. **CTA** (1 line + hashtags) - Drive action
+
+                ### 🏷️ Hashtag Strategy:
+                - Use 3-5 hashtags maximum
+                - Mix popular (100K+ followers) and niche (10K-50K) hashtags
+                - Place at the end of post
+                - Research trending hashtags in your industry weekly
+
+                ### 📊 Best Times to Post:
+                - **Tuesday-Thursday**: 9-11 AM (highest engagement)
+                - **Wednesday**: Best overall day
+                - **Avoid**: Weekends for B2B, early mornings, late evenings
+                - **Test**: Your audience may have unique patterns
+
+                ### 💎 Content Types That Work:
+                - **Personal stories**: Authentic experiences (highest engagement)
+                - **Industry insights**: Thought leadership
+                - **How-to guides**: Actionable advice
+                - **Data-driven posts**: Research and statistics
+                - **Controversial opinions**: Spark discussion (carefully!)
+                - **Lists**: Easy to scan, high shareability
+                - **Behind-the-scenes**: Show your process
+
+                ### 🎨 Visual Content Tips:
+                - Posts with images get 2x more comments
+                - Carousel posts get 1.5x more reach
+                - Use high-quality, professional images
+                - Infographics perform exceptionally well
+                - Personal photos > stock photos
+
+                ### 🚀 Growth Hacks:
+                1. **Comment within first hour**: Boost your own post
+                2. **Engage before posting**: Warm up the algorithm
+                3. **Tag relevant people**: (2-3 max, only when appropriate)
+                4. **Post consistently**: 3-5x per week minimum
+                5. **Respond to every comment**: Within first 2 hours
+                6. **Use "see more" strategically**: Hook in first 2 lines
+                7. **Write for mobile**: Short paragraphs, more line breaks
+
+                ### 📏 Optimal Lengths:
+                - **Standard posts**: 150-250 words (sweet spot: 200)
+                - **Long-form**: 1,300-2,000 words (for thought leadership)
+                - **Carousels**: 10-15 slides maximum
+                - **Threads**: 3-5 posts
+
+                ### ⚠️ What to Avoid:
+                - External links (post in first comment instead)
+                - Too many hashtags (looks spammy)
+                - Generic content (be specific!)
+                - Overly promotional content
+                - Inconsistent posting (algorithm penalizes)
+                - Ignoring comments (kills engagement)
+
+                ### 🎓 Advanced Tips:
+                - Use the **"3-3-3 Rule"**: 3 posts/week, 3 comments on others' posts/day, 3 meaningful connections/day
+                - **Native video** gets 5x more engagement than YouTube links
+                - **Ask questions** at the end - increases comments by 50%
+                - **Use emojis strategically** - but not in excess
+                - **Write for skimmers**: Bullets, bold, line breaks
+                """
+            )
+
+    # =========================
+    # Event Handlers
+    # =========================
+
+    # Generate Post
+    generate_button.click(
+        fn=generate_post,
+        inputs=[
+            topic_input,
+            tone_input,
+            audience_input,
+            post_type_input,
+            word_count_input,
+            num_variations_input,
+            custom_hashtags_input
+        ],
+        outputs=output_box
+    )
+
+    # Suggest Hashtags
+    suggest_hashtags_button.click(
+        fn=lambda topic: generate_hashtag_suggestions(topic, 5),
+        inputs=topic_input,
+        outputs=custom_hashtags_input
+    )
+
+    # A/B Testing
+    ab_button.click(
+        fn=generate_ab_versions,
+        inputs=[ab_topic, ab_tone, ab_audience],
+        outputs=ab_output
+    )
+
+    # Schedule Optimizer
+    schedule_button.click(
+        fn=get_best_posting_times,
+        inputs=[schedule_industry, schedule_location, schedule_goal],
+        outputs=schedule_output
+    )
+
+    # Competitor Analysis
+    analyze_button.click(
+        fn=analyze_competitor_post,
+        inputs=[competitor_post, competitor_niche],
+        outputs=competitor_output
+    )
+
+    # Image Suggestions
+    image_button.click(
+        fn=suggest_images,
+        inputs=[image_post, image_type],
+        outputs=image_output
+    )
+
+    # Trend Analyzer
+    trend_button.click(
+        fn=analyze_linkedin_trends,
+        inputs=[trend_industry, trend_timeframe],
+        outputs=trend_output
+    )
+
+    # Personal Branding
+    brand_create_button.click(
+        fn=create_brand_voice,
+        inputs=[brand_name, brand_industry, brand_values, brand_personality, brand_expertise],
+        outputs=brand_output
+    )
+
+    apply_button.click(
+        fn=apply_brand_voice,
+        inputs=[apply_post, apply_guide],
+        outputs=apply_output
+    )
+
+    # Rewrite Post
+    rewrite_button.click(
+        fn=rewrite_post,
+        inputs=[original_post_input, rewrite_instruction],
+        outputs=rewrite_output
+    )
+
+    # Post History
+    refresh_history_button.click(
+        fn=format_history,
+        inputs=[],
+        outputs=history_display
+    )
+
+    load_button.click(
+        fn=get_post_from_history,
+        inputs=load_post_number,
+        outputs=loaded_post
+    )
+
+    # Export History Package - FIXED
+    export_all_button.click(
+        fn=export_history_package,
+        inputs=export_count,
+        outputs=[export_package_file, export_status]
+    )
+
+    # Copy to Clipboard
+    copy_js = """
+    async function() {
+        const textArea = document.querySelector('.output-text textarea');
+        if (textArea && textArea.value) {
+            try {
+                await navigator.clipboard.writeText(textArea.value);
+                return "✅ Copied successfully!";
+            } catch (err) {
+                textArea.select();
+                document.execCommand('copy');
+                return "✅ Copied successfully!";
+            }
+        }
+        return "❌ Nothing to copy! Generate a post first.";
+    }
+    """
+
+    copy_button.click(
+        fn=None,
+        inputs=None,
+        outputs=copy_status,
+        js=copy_js
+    )
+
+    # Export Current Post - FIXED
+    export_button.click(
+        fn=export_current_post,
+        inputs=[output_box],
+        outputs=[export_file, copy_status]
+    )
+
+# Launch the application
+print("\n" + "="*80)
+print("🚀 LAUNCHING LINKEDIN AI WRITER PRO - ULTIMATE EDITION")
+print("="*80 + "\n")
+
+demo.launch(share=True, debug=True)