ALwrity Version 0.5.1 (Fastapi + React)

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