| Name | llm-document-analysis JSON |
| Version |
0.1.1
JSON |
| download |
| home_page | None |
| Summary | A Python library for LLM-powered document analysis and processing |
| upload_time | 2025-02-08 17:23:15 |
| maintainer | None |
| docs_url | None |
| author | None |
| requires_python | >=3.8 |
| license | MIT |
| keywords |
llm
document
analysis
nlp
ai
|
| VCS |
 |
| bugtrack_url |
|
| requirements |
No requirements were recorded.
|
| Travis-CI |
No Travis.
|
| coveralls test coverage |
No coveralls.
|
# LLM Document Analysis
A Python library for LLM-powered document analysis and processing. This library provides a flexible and extensible framework for analyzing documents using Large Language Models.
## Features
- Document processing for various formats (PDF, Text, etc.)
- Integration with popular LLM providers
- Extensible processor architecture
- Built-in logging and error handling
- Async support for better performance
## Installation
You can install the package directly from PyPI:
```bash
pip install llm-document-analysis
```
For development installation with additional tools:
```bash
pip install llm-document-analysis[dev]
```
## Quick Start
```python
from llm_document_analysis import DocumentAnalyzer
from llm_document_analysis.processors import PDFProcessor
# Initialize the analyzer
analyzer = DocumentAnalyzer()
# Process a PDF document
processor = PDFProcessor("path/to/document.pdf")
result = analyzer.analyze(processor)
# Access the analysis results
print(result.summary)
print(result.key_points)
```
## Development
1. Clone the repository:
```bash
git clone https://github.com/Venere-Labs/llm-document-analysis.git
cd llm-document-analysis
```
2. Create a virtual environment:
```bash
python -m venv .venv
source .venv/bin/activate # On Windows: .venv\Scripts\activate
```
3. Install development dependencies:
```bash
pip install -e ".[dev]"
```
4. Run tests:
```bash
pytest
```
## Contributing
Contributions are welcome! Please feel free to submit a Pull Request.
## License
This project is licensed under the MIT License - see the LICENSE file for details.
## Support
If you encounter any problems or have questions, please [open an issue](https://github.com/Venere-Labs/llm-document-analysis/issues) on GitHub.
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