onetokenpy 0.1.1

A library for running local LLM classification tasks on data

onetokenpy

A Python library for running LLM classification tasks on data. Supports both GPU (using vLLM), CPU (using llama.cpp) inference, and remote.

Installation

Basic Installation (CPU only)

Installs the package with CPU support using llama-cpp-python.

pip install onetokenpy

GPU Support

If you have a CUDA-compatible GPU and want to use vLLM for faster inference:

pip install "onetokenpy[gpu]"

Usage

import onetokenpy as ot
import pandas as pd

# Create a sample dataframe
df = pd.DataFrame({
    'postal_codes': ['H2X 1Y1', '12345', 'ABC123', 'K1A 0B1']
})

# Classify the postal codes using the default CPU model
# (google/gemma-3-1b-it-qat-q4_0-gguf)
result = ot.classify(
    df,
    "Classify this {postal_codes} as whether it is a correctly formatted Canadian postal code. Answer only by Yes or No"
)

print(result)

Features

• Run local LLM classification tasks on pandas DataFrames or lists of strings.
• Automatic backend selection (GPU if available and [gpu] extra installed, otherwise CPU).
• Uses vLLM for GPU inference (requires pip install "onetokenpy[gpu]").
• Uses llama.cpp via llama-cpp-python for CPU inference.
• Downloads required models (GGUF for llama.cpp, standard HF format for vLLM) automatically via huggingface_hub.
• Returns results as a pandas DataFrame including original data, classifications, and generated prompts.

Requirements

• Python 3.8+
• pandas
• llama-cpp-python (for CPU support, installed by default)
• huggingface-hub (for model downloading, installed by default)
• For GPU support:
  • CUDA-compatible GPU
  • vllm (install via pip install "onetokenpy[gpu]")

License

MIT License

Author

Maxime Rivest ([e-mail])