Metadata-Version: 2.1
Name: wordcel
Version: 0.2.2
Summary: Swiss army-knife for composing LLM outputs
Author: Andrew Han
Author-email: handrew11@gmail.com
Classifier: Programming Language :: Python :: 2
Classifier: Programming Language :: Python :: 2.7
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.4
Classifier: Programming Language :: Python :: 3.5
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3.11
Classifier: Programming Language :: Python :: 3.12
Requires-Dist: anthropic (>=0.34.2)
Requires-Dist: google-generativeai (>=0.6.0)
Requires-Dist: langchain (>0.3.0)
Requires-Dist: networkx
Requires-Dist: openai (>1.0)
Requires-Dist: pandas
Requires-Dist: scikit-learn
Description-Content-Type: text/markdown

# 😶 Wordcel

`wordcel` is a library of functions that provides a set of common tools for working with large language models.

Candidly, it is mostly a set of functions that I myself use on a regular basis — my own personal Swiss army knife. 

## Installation

You can simply `pip install wordcel`.

## Documentation

- [LLM APIs](docs/llm_providers.md): Wrapper functions over the most common LLM APIs.
- [RAG](docs/rag.md): Helper functions for RAG, and a minimal implementation of Anthropic's "Contextual Retrieval" method. 
- [featurize](docs/featurize.md): Helper functions for multithreaded inference over text columns in pandas DataFrames.
- [DAG](docs/dag.md): WordcelDAG is a flexible and extensible framework for defining and executing Directed Acyclic Graphs (DAGs) of data processing tasks, particularly involving LLMs and dataframes. 


