Upload folder using huggingface_hub

.claude/settings.local.json

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+{
+  "permissions": {
+    "allow": [
+      "Bash(pip install:*)",
+      "Bash(huggingface-cli:*)"
+    ],
+    "deny": []
+  }
+}

.gitignore

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+# Python
+__pycache__/
+*.py[cod]
+*$py.class
+*.so
+.Python
+build/
+develop-eggs/
+dist/
+downloads/
+eggs/
+.eggs/
+lib/
+lib64/
+parts/
+sdist/
+var/
+wheels/
+*.egg-info/
+.installed.cfg
+*.egg
+MANIFEST
+
+# Virtual environments
+venv/
+env/
+ENV/
+.venv
+.ENV
+
+# IDE
+.vscode/
+.idea/
+*.swp
+*.swo
+*~
+
+# OS
+.DS_Store
+Thumbs.db
+
+# Gradio
+gradio_cached_examples/
+flagged/
+
+# Hugging Face
+.cache/
+models/
+*.bin
+*.safetensors
+
+# Logs
+*.log

DEPLOY.md

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+# 🚀 Deployment Guide
+
+## Deploy to Hugging Face Spaces
+
+### Prerequisites
+1. Install Hugging Face CLI:
+```bash
+pip install huggingface_hub
+```
+
+2. Login to Hugging Face:
+```bash
+huggingface-cli login
+```
+
+### Create and Deploy Space
+
+1. **Create a new Space on Hugging Face Hub:**
+```bash
+huggingface-cli repo create --type space --space_sdk gradio your-username/one-pager-generator
+```
+
+2. **Clone and set up the repository:**
+```bash
+git clone https://huggingface.co/spaces/your-username/one-pager-generator
+cd one-pager-generator
+```
+
+3. **Copy files to the Space repository:**
+```bash
+cp ../one-pager/* .
+```
+
+4. **Add, commit and push:**
+```bash
+git add .
+git commit -m "Initial commit: AI One-Pager Generator"
+git push
+```
+
+### Alternative: Direct CLI Upload
+
+You can also use the HF CLI to upload files directly:
+
+```bash
+huggingface-cli upload your-username/one-pager-generator . --repo-type=space
+```
+
+### Files Required for Deployment
+
+- `app.py` - Main application file
+- `requirements.txt` - Python dependencies  
+- `config.yaml` - Space configuration
+- `README.md` - Documentation
+- `.gitignore` - Git ignore patterns
+
+### Configuration Notes
+
+- The app uses `distilgpt2` model for better compatibility
+- CPU-only inference for free tier compatibility
+- Fallback template system ensures reliable output
+- Gradio interface optimized for Spaces
+
+### Post-Deployment
+
+After deployment, your Space will be available at:
+`https://huggingface.co/spaces/your-username/one-pager-generator`
+
+The app will automatically:
+1. Install dependencies from requirements.txt
+2. Load the AI model
+3. Launch the Gradio interface
+4. Be accessible via the web
+
+### Troubleshooting
+
+- **Model loading issues**: The app falls back to structured templates
+- **Memory issues**: Using smaller DistilGPT2 model for efficiency  
+- **Timeout issues**: CPU inference may be slower but more reliable

README.md

@@ -1,12 +1,52 @@
----
-title: One Pager Generator
-emoji: 🏆
-colorFrom: indigo
-colorTo: gray
-sdk: gradio
-sdk_version: 5.33.0
-app_file: app.py
-pinned: false
----
-
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
+# 📄 AI One-Pager Generator
+
+An intelligent Gradio application that generates professional one-page documents on any topic using Hugging Face transformers.
+
+## Features
+
+- **Topic-based Generation**: Create one-pagers on any subject
+- **Customizable Parameters**: 
+  - Target audience specification
+  - Tone selection (Professional, Casual, Academic, Persuasive, Informative)
+  - Length control (Short, Medium, Long)
+  - Key points input
+- **Professional Formatting**: Structured output with title, executive summary, key points, and conclusion
+- **Easy to Use**: Simple web interface powered by Gradio
+
+## Installation
+
+1. Clone this repository
+2. Install dependencies:
+```bash
+pip install -r requirements.txt
+```
+
+3. Run the application:
+```bash
+python app.py
+```
+
+## Usage
+
+1. Enter your topic in the "Topic" field
+2. Specify your target audience
+3. List key points you want covered
+4. Select the appropriate tone and length
+5. Click "Generate One-Pager"
+6. Copy and use your generated document!
+
+## Deployment to Hugging Face Spaces
+
+This app is ready to be deployed to Hugging Face Spaces:
+
+1. Create a new Space on Hugging Face
+2. Upload these files to your Space
+3. Your app will be automatically deployed!
+
+## Model Information
+
+This application uses Microsoft's DialoGPT-large model for text generation, optimized for document creation tasks.
+
+## License
+
+MIT License

app.py

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+import gradio as gr
+from transformers import pipeline
+import torch
+import os
+
+# Initialize the text generation pipeline
+generator = None
+
+def initialize_model():
+    global generator
+    try:
+        # Use a reliable text generation model
+        generator = pipeline(
+            "text-generation",
+            model="distilgpt2",  # Smaller, faster model
+            device=-1,  # CPU only for compatibility
+            pad_token_id=50256  # Set pad token to avoid warnings
+        )
+        return "Model loaded successfully!"
+    except Exception as e:
+        return f"Error loading model: {str(e)}"
+
+def generate_onepager(topic, target_audience, key_points, tone, length):
+    if generator is None:
+        return "Error: Model not initialized. Please wait for the model to load."
+    
+    # Create a structured prompt for one-pager generation
+    length_tokens = {"Short": 200, "Medium": 400, "Long": 600}
+    max_tokens = length_tokens.get(length, 400)
+    
+    prompt = f"""ONE-PAGE DOCUMENT
+
+TOPIC: {topic}
+AUDIENCE: {target_audience}
+TONE: {tone}
+
+EXECUTIVE SUMMARY:
+{key_points}
+
+DETAILED CONTENT:
+
+Title: {topic}
+
+Overview:"""
+    
+    try:
+        # Generate the one-pager
+        result = generator(
+            prompt,
+            max_length=len(prompt.split()) + max_tokens,
+            num_return_sequences=1,
+            temperature=0.8,
+            do_sample=True,
+            pad_token_id=generator.tokenizer.eos_token_id,
+            eos_token_id=generator.tokenizer.eos_token_id,
+            repetition_penalty=1.1
+        )
+        
+        # Extract the generated text
+        generated_text = result[0]['generated_text']
+        
+        # Clean up the output
+        onepager = generated_text.replace(prompt, "").strip()
+        
+        # If output is too short, provide a structured fallback
+        if len(onepager) < 50:
+            onepager = create_structured_onepager(topic, target_audience, key_points, tone)
+        
+        return onepager
+        
+    except Exception as e:
+        # Fallback to structured template
+        return create_structured_onepager(topic, target_audience, key_points, tone)
+
+def create_structured_onepager(topic, target_audience, key_points, tone):
+    """Create a structured one-pager when AI generation fails"""
+    
+    tone_styles = {
+        "Professional": "formal and business-oriented",
+        "Casual": "friendly and approachable",
+        "Academic": "scholarly and research-focused", 
+        "Persuasive": "compelling and action-oriented",
+        "Informative": "clear and educational"
+    }
+    
+    style_desc = tone_styles.get(tone, "professional")
+    
+    template = f"""# {topic}
+
+## Executive Summary
+This document provides a comprehensive overview of {topic.lower()} tailored for {target_audience.lower()}. The content is presented in a {style_desc} manner to ensure maximum impact and understanding.
+
+## Key Points
+
+{chr(10).join([f"• {point.strip()}" for point in key_points.split(',') if point.strip()])}
+
+## Background
+{topic} represents an important area that requires careful consideration and strategic thinking. Understanding the core concepts and implications is essential for {target_audience.lower()}.
+
+## Main Content
+The fundamental aspects of {topic.lower()} encompass several critical areas that directly impact stakeholders. These elements work together to create a comprehensive framework for understanding and implementation.
+
+## Benefits & Opportunities
+- Enhanced understanding of core concepts
+- Improved decision-making capabilities  
+- Strategic advantages for implementation
+- Clear actionable insights
+
+## Recommendations
+1. Begin with thorough analysis of current situation
+2. Develop comprehensive implementation strategy
+3. Monitor progress and adjust approach as needed
+4. Measure results and iterate for continuous improvement
+
+## Conclusion
+{topic} offers significant opportunities for {target_audience.lower()} when approached strategically. The key points outlined above provide a solid foundation for moving forward with confidence and clarity.
+
+---
+*This one-pager was generated to provide quick, actionable insights on {topic.lower()}.*"""
+    
+    return template
+
+# Create the Gradio interface
+def create_interface():
+    with gr.Blocks(title="One-Pager Generator", theme=gr.themes.Soft()) as demo:
+        gr.Markdown("# 📄 AI One-Pager Generator")
+        gr.Markdown("Generate professional one-page documents on any topic using AI!")
+        
+        with gr.Row():
+            with gr.Column(scale=1):
+                topic_input = gr.Textbox(
+                    label="Topic",
+                    placeholder="e.g., Digital Marketing Strategy, Climate Change Solutions, etc.",
+                    lines=2,
+                    value="Artificial Intelligence in Healthcare"
+                )
+                
+                audience_input = gr.Textbox(
+                    label="Target Audience",
+                    placeholder="e.g., Business executives, Students, General public, etc.",
+                    lines=1,
+                    value="Healthcare professionals"
+                )
+                
+                keypoints_input = gr.Textbox(
+                    label="Key Points to Cover",
+                    placeholder="Enter main points separated by commas",
+                    lines=4,
+                    value="Machine learning applications, Data privacy, Cost-effectiveness, Implementation challenges"
+                )
+                
+                tone_dropdown = gr.Dropdown(
+                    choices=["Professional", "Casual", "Academic", "Persuasive", "Informative"],
+                    label="Tone",
+                    value="Professional"
+                )
+                
+                length_dropdown = gr.Dropdown(
+                    choices=["Short", "Medium", "Long"],
+                    label="Length",
+                    value="Medium"
+                )
+                
+                generate_btn = gr.Button("🚀 Generate One-Pager", variant="primary")
+                
+            with gr.Column(scale=2):
+                output_text = gr.Textbox(
+                    label="Generated One-Pager",
+                    lines=25,
+                    max_lines=35,
+                    show_copy_button=True,
+                    placeholder="Your generated one-pager will appear here..."
+                )
+        
+        with gr.Row():
+            gr.Markdown("""
+            ### 💡 Tips for Best Results:
+            - **Be specific** with your topic for more targeted content
+            - **Include 3-5 key points** separated by commas
+            - **Choose the right tone** for your intended audience  
+            - **Use descriptive audience** details (e.g., "C-level executives" vs "executives")
+            """)
+        
+        # Connect the generate button to the function
+        generate_btn.click(
+            fn=generate_onepager,
+            inputs=[topic_input, audience_input, keypoints_input, tone_dropdown, length_dropdown],
+            outputs=output_text
+        )
+        
+    return demo
+
+# Initialize model and launch
+if __name__ == "__main__":
+    print("🚀 Starting One-Pager Generator...")
+    print("📥 Loading AI model...")
+    initialize_model()
+    print("✅ Model loaded! Launching interface...")
+    
+    demo = create_interface()
+    demo.launch()

config.yaml

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+title: AI One-Pager Generator
+emoji: 📄
+colorFrom: blue
+colorTo: purple
+sdk: gradio
+sdk_version: 4.44.0
+app_file: app.py
+pinned: false
+license: mit
+short_description: Generate professional one-page documents on any topic using AI

packages.txt

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+ffmpeg

requirements.txt

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+gradio
+transformers
+torch
+huggingface_hub
+tokenizers

test_app.py

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+#!/usr/bin/env python3
+"""
+Simple test script to verify the one-pager generator functionality
+"""
+
+import sys
+import os
+
+# Add the current directory to the path so we can import our app
+sys.path.insert(0, os.path.dirname(os.path.abspath(__file__)))
+
+def test_basic_functionality():
+    """Test basic app functionality without launching the full interface"""
+    try:
+        from app import generate_onepager, initialize_model
+        
+        print("🧪 Testing One-Pager Generator...")
+        print("Initializing model...")
+        
+        # Initialize the model
+        init_result = initialize_model()
+        print(f"Model initialization: {init_result}")
+        
+        # Test generation with sample data
+        print("\n📝 Testing one-pager generation...")
+        test_topic = "Artificial Intelligence in Healthcare"
+        test_audience = "Healthcare professionals"
+        test_keypoints = "Machine learning applications, Data privacy concerns, Cost-effectiveness, Implementation challenges"
+        test_tone = "Professional"
+        test_length = "Medium"
+        
+        result = generate_onepager(
+            topic=test_topic,
+            target_audience=test_audience,
+            key_points=test_keypoints,
+            tone=test_tone,
+            length=test_length
+        )
+        
+        print("Generated One-Pager:")
+        print("-" * 50)
+        print(result)
+        print("-" * 50)
+        
+        if "Error" not in result:
+            print("✅ Test passed! One-pager generated successfully.")
+        else:
+            print("❌ Test failed! Error in generation.")
+            
+    except Exception as e:
+        print(f"❌ Test failed with exception: {str(e)}")
+        import traceback
+        traceback.print_exc()
+
+if __name__ == "__main__":
+    test_basic_functionality()