genai-textkit 0.1.8

A no-API-key, CPU-friendly GenAI library for text generation, summarization, sentiment classification, and translation.

🧠 GenAI-TextKit

A minimal, CPU-friendly, no-API-key-required LLM-powered Python library — for text generation, summarization, sentiment classification, and translation.

⚡ Just pip install genai_textkit and you're ready to build with GenAI-TextKit on any machine.

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🚀 Features

• ✅ Offline text generation with distilgpt2
• ✅ Fast summarization with distilbart-cnn-12-6
• ✅ Sentiment classification using distilbert-sst2
• ✅ Multilingual translation via facebook/nllb-200-distilled-600M
• ✅ Works on CPU — no GPU required
• ✅ No API keys, no internet after install

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📦 Installation

Step 1: Install GenAI-TextKit

pip install genai_textkit

Step 2: (If not already installed) Install PyTorch manually

pip install torch --index-url https://download.pytorch.org/whl/cpu

Author: Abhinav | GitHub: [IamAbhinav01](https://github.com/IamAbhinav01)
Repository: [IamAbhinav01/GenAI](https://github.com/IamAbhinav01/GenAI)

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## 🚀 Features

- ✅ Offline text generation with `distilgpt2`
- ✅ Fast summarization with `distilbart-cnn-12-6`
- ✅ Sentiment classification using `distilbert-sst2`
- ✅ Multilingual translation via `facebook/nllb-200-distilled-600M`
- ✅ Works on **CPU** — no GPU required
- ✅ No API keys, no internet after install

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## 📦 Installation

```bash
pip install genai_textkit

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🏁 Quick Start

from genai_textkit import generate, summarize, classify, translate

# Text generation
print(generate("Write a poem about the moon", max_tokens=50))

# Summarization
print(summarize("Your long text here..."))

# Sentiment Classification
print(classify("I really loved the product!"))

# Translation (English to Hindi)
print(translate("I am happy to meet you", to_lang="hi"))

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🌍 Supported Translation Languages

Code	Language
en	English
hi	Hindi
ta	Tamil
ml	Malayalam
fr	French
es	Spanish
bn	Bengali

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📂 Project Structure

genai-toolkit/
│
├── genai/                # Core package
│   ├── __init__.py       # Public API
│   ├── text.py           # generate, summarize, classify, translate
│   ├── config.py         # Device/model paths
│   └── download_models.py# Download models utility
│
├── examples/             # Usage examples
│   ├── example_generate.py
│   ├── example_summarize.py
│   ├── example_translate.py
│   └── example_classify.py
│
├── tests/                # Unit tests
│   └── test_text.py
│
├── requirements.txt      # Python dependencies
├── pyproject.toml        # Project metadata
├── README.md             # Project documentation
└── ...                   # Other files

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🧪 Run Examples

See the examples/ folder for ready-to-run scripts.

🤝 Contributing

Pull requests and issues are welcome! Please open an issue or PR on GitHub.

📄 License

MIT License © Abhinav