anyai 0.2.1

AnyAI - One-liner AI for everyone. A unified gateway to AI capabilities.

AnyAI

One-liner AI for everyone

AnyAI is a unified gateway to AI capabilities. It works standalone with built-in rule-based functionality and supports optional extras for advanced AI through sub-packages.

Installation

Basic install (includes built-in text and image utilities):

pip install anyai

With optional extras:

# Install with computer vision support
pip install anyai[cv]

# Install with LLM support
pip install anyai[llm]

# Install with OCR support
pip install anyai[ocr]

# Install everything
pip install anyai[all]

Quick Start

import anyai

# See what's available
anyai.about()

# Check installed backends
anyai.available_backends()

Text Processing

from anyai import text

# Summarize a long document
summary = text.summarize("Your long text goes here...")

# Extract keywords
keywords = text.extract_keywords("Machine learning is a subset of artificial intelligence.")

# Analyze sentiment
result = text.sentiment("This product is absolutely wonderful!")
print(result)  # {'label': 'positive', 'score': 0.85}

Image Processing

from anyai import image

# Describe an image (returns metadata; with optional deps, returns AI description)
info = image.describe("photo.jpg")
print(info)
# {'path': 'photo.jpg', 'format': 'JPEG', 'width': 1920, 'height': 1080, ...}

Utilities

from anyai import utils

# Check if optional dependencies are available
utils.check_deps("cv")
utils.check_deps("llm")

Sub-Packages

Package	Extra	Description
anycv	anyai[cv]	Computer vision: detection, segmentation, tracking
anyocr	anyai[ocr]	Optical character recognition
anyllm	anyai[llm]	Large language model integration
anyml	anyai[ml]	Classical machine learning utilities
anynlp	anyai[nlp]	Natural language processing
anydeploy	anyai[deploy]	Model deployment and serving
tableai	anyai[table]	Table understanding and extraction

Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

1. Fork the repository
2. Create your feature branch (git checkout -b feature/amazing-feature)
3. Commit your changes (git commit -m 'Add amazing feature')
4. Push to the branch (git push origin feature/amazing-feature)
5. Open a Pull Request

License

This project is licensed under the MIT License. See the LICENSE file for details.

Links

• Website: nrl.ai
• GitHub: github.com/vietanhdev/anyai
• PyPI: pypi.org/project/anyai
• Author: Viet-Anh Nguyen