A package for cleaning and curating data with LLMs
Project description
databonsai
clean & curate your data with LLMs.
databonsai is a Python library that leverages Large Language Models (LLMs) to perform data cleaning, transformation, and categorization tasks. It provides a set of tools and utilities to simplify the process of working with LLMs and integrating them into your data pipelines.
Features
- Categorization of data into predefined categories using LLMs
- Transformation of data based on custom prompts and schemas
- Decomposition of data into structured formats using LLMs
- Retry logic with exponential backoff for handling rate limits and transient errors
- Pydantic-based validation and configuration management
Installation
You can install databonsai using pip:
pip install databonsai
Usage
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
databonsai-0.1.0.tar.gz
(8.1 kB
view details)
Built Distribution
File details
Details for the file databonsai-0.1.0.tar.gz
.
File metadata
- Download URL: databonsai-0.1.0.tar.gz
- Upload date:
- Size: 8.1 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/5.0.0 CPython/3.12.2
File hashes
Algorithm | Hash digest | |
---|---|---|
SHA256 | d637fde356410730fd49bda9e38abc8d5a16445a27ce3b71e2d6216f095db7a0 |
|
MD5 | 6eaddcd979bb9707b8b18bfd150853f7 |
|
BLAKE2b-256 | a348839efe59f57ad757b330b04330bea73684b6b89fbafe7af22e41fc0379f9 |
File details
Details for the file databonsai-0.1.0-py3-none-any.whl
.
File metadata
- Download URL: databonsai-0.1.0-py3-none-any.whl
- Upload date:
- Size: 11.7 kB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/5.0.0 CPython/3.12.2
File hashes
Algorithm | Hash digest | |
---|---|---|
SHA256 | 0474a29d30c4e432afc64b6cfdd73521614a1703e6529a5ed50e5300c31874c4 |
|
MD5 | 1a3930ab3cefdfd115e26f603107b735 |
|
BLAKE2b-256 | 99e2150cfe8c6aa351faeebbc531eb51b41296011c4f0dd667fa9200379e04ba |