AI Image and Audio Generation Improvements.
AI Video Generation Pre-Flight Checklist. Cost Estimate Improvements.
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# AI-Powered FAQ Generator
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A sophisticated FAQ generation system that creates comprehensive, well-researched FAQs from various content sources. This tool leverages AI to analyze content, conduct web research, and generate detailed FAQs with customizable options.
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## Features
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### Content Processing
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- **Multiple Input Sources**
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- Direct text input
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- File uploads (DOCX, TXT)
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- URL content extraction
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- Support for any content type (general, technical, educational, etc.)
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### Research Capabilities
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- **Multi-level Search Depth**
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- **Basic**: Google Search for quick, general information
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- **Comprehensive**: Tavily AI for detailed, in-depth research
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- **Expert**: Metaphor AI for specialized, expert-level content
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### Customization Options
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- **Target Audience**
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- Beginner
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- Intermediate
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- Expert
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- **FAQ Style**
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- Technical
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- Conversational
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- Professional
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- **Advanced Features**
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- Emoji inclusion
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- Code example generation
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- Reference integration
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- Customizable time range for research
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- Multi-language support
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### Output Formats
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- Interactive preview
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- Markdown
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- HTML
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- JSON
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## Installation
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1. Clone the repository
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2. Install dependencies:
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```bash
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pip install -r requirements.txt
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```
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## Usage
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### Basic Usage
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```python
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from lib.ai_writers.ai_blog_faqs_writer.faqs_generator_blog import FAQGenerator, FAQConfig
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# Initialize with default configuration
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generator = FAQGenerator()
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# Generate FAQs from content
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faqs = await generator.generate_faqs("Your content here")
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```
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### Advanced Configuration
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```python
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from lib.ai_writers.ai_blog_faqs_writer.faqs_generator_blog import (
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FAQGenerator, FAQConfig, TargetAudience, FAQStyle, SearchDepth
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)
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# Custom configuration
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config = FAQConfig(
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num_faqs=10,
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target_audience=TargetAudience.INTERMEDIATE,
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faq_style=FAQStyle.TECHNICAL,
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include_emojis=True,
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include_code_examples=True,
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include_references=True,
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search_depth=SearchDepth.COMPREHENSIVE,
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time_range="last_6_months",
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language="English"
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)
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generator = FAQGenerator(config)
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```
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### Web Interface
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Run the Streamlit interface:
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```bash
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streamlit run lib/ai_writers/ai_blog_faqs_writer/faqs_ui.py
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```
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## Research Process
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1. **Content Analysis**
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- Identifies key topics and concepts
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- Extracts potential questions
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- Determines research requirements
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2. **Web Research**
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- Selects appropriate search function based on depth
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- Gathers relevant information
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- Validates and cross-references data
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3. **FAQ Generation**
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- Creates comprehensive questions
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- Provides detailed answers
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- Includes code examples (if applicable)
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- Adds references and citations
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## Output Structure
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Each FAQ item includes:
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- Question
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- Detailed answer
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- Category
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- Code example (if applicable)
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- References
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- Confidence score
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- Last updated timestamp
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## Configuration Options
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### FAQConfig Parameters
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- `num_faqs`: Number of FAQs to generate (default: 5)
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- `target_audience`: Target audience level (default: INTERMEDIATE)
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- `faq_style`: Writing style (default: PROFESSIONAL)
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- `include_emojis`: Whether to include emojis (default: True)
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- `include_code_examples`: Whether to include code examples (default: True)
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- `include_references`: Whether to include references (default: True)
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- `search_depth`: Research depth level (default: COMPREHENSIVE)
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- `time_range`: Time range for research (default: "last_6_months")
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- `language`: Output language (default: "English")
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## Research Depth Options
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### Basic (Google Search)
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- Quick, general information
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- Broad coverage
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- Suitable for basic topics
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### Comprehensive (Tavily AI)
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- Detailed, in-depth research
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- Multiple source integration
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- Best for most use cases
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### Expert (Metaphor AI)
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- Specialized, expert-level content
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- Advanced topic coverage
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- Technical and academic focus
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## Best Practices
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1. **Content Preparation**
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- Provide clear, well-structured content
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- Include key terms and concepts
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- Specify target audience and style
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2. **Research Selection**
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- Use Basic for general topics
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- Choose Comprehensive for detailed analysis
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- Select Expert for technical subjects
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3. **Output Review**
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- Verify accuracy of information
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- Check code examples
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- Validate references
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## Contributing
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1. Fork the repository
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2. Create a feature branch
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3. Commit your changes
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4. Push to the branch
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5. Create a Pull Request
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## License
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This project is licensed under the MIT License - see the LICENSE file for details.
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## Support
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For support, please open an issue in the repository or contact the maintainers.
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## Acknowledgments
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- OpenAI for GPT integration
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- Google Search API
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- Tavily AI
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- Metaphor AI
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- BeautifulSoup for web scraping
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- Streamlit for UI
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