Metadata-Version: 2.1
Name: langfree
Version: 0.0.14
Summary: Utilities to help you work with your language model data outside LangSmith
Home-page: https://github.com/parlance-labs/langfree
Author: Hamel Husain
Author-email: hamel.husain@gmail.com
License: Apache Software License 2.0
Keywords: nbdev jupyter notebook python langchain langsmith openai
Classifier: Development Status :: 4 - Beta
Classifier: Intended Audience :: Developers
Classifier: Natural Language :: English
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: License :: OSI Approved :: Apache Software License
Requires-Python: >=3.7
Description-Content-Type: text/markdown
Provides-Extra: dev
License-File: LICENSE

# langfree

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Utilities that help you extract, transform and curate
[ChatOpenAI](https://api.python.langchain.com/en/latest/chat_models/langchain.chat_models.openai.ChatOpenAI.html)
runs from
[traces](https://js.langchain.com/docs/modules/agents/how_to/logging_and_tracing)
stored in [LangSmith](https://www.langchain.com/langsmith). The goal is
to facilitate using data from these runs for fine-tuning /
instruction-tuning models.

![](https://github.com/parlance-labs/langfree/assets/1483922/0e37d5a4-1ffb-4661-85ba-7c9eb80dd06b.png)

### Motivation

Langchain has native [tracing
support](https://blog.langchain.dev/tracing/) that allows you to log
LangChain runs. This data is a valuable resource for fine-tuning and
evaluation. [LangSmith](https://docs.smith.langchain.com/) is a
commercial application that facilitates some of these tasks.

However, LangSmith may not work for everyone’s needs. It is often
desirable to buid your own data inspection and curation infrastructure
so you can add your own features.

> One pattern I noticed is that great AI researchers are willing to
> manually inspect lots of data. And more than that, **they build
> infrastructure that allows them to manually inspect data quickly.**
> Though not glamorous, manually examining data gives valuable
> intuitions about the problem. The canonical example here is Andrej
> Karpathy doing the ImageNet 2000-way classification task himself.
>
> – [Jason Wei, AI Researcher at
> OpenAI](https://x.com/_jasonwei/status/1708921475829481683?s=20)

`langfree` helps you export data from LangSmith and build data curation
web applications. The goal is to empower the AI engineer to quickly
build their own data curation tools, so they can add features like:

- connectivity to additionaly data sources beyond LangSmith.
- data transformations of runs using code
- ability to route, tag and annotate data in custom ways
- … etc.

Furthermore,`langchain` provides a handful of [Shiny for
Python](https://shiny.posit.co/py/) components to make the process of
creating data curation applications easier.

## Install

``` sh
pip install langfree
```

## How to use

Coming soon

## Documentation

See the [docs site](http://langfree.parlance-labs.com/).

## Contributing

This library was created with [nbdev](https://nbdev.fast.ai/). See
[Contributing.md](https://github.com/parlance-labs/langfree/blob/main/CONTRIBUTING.md)
for further guidelines.
