langchain/libs/partners/groq
Lucas Tucker 7114aed78f
docs: Standardize ChatGroq (#22751)
Updated ChatGroq doc string as per issue
https://github.com/langchain-ai/langchain/issues/22296:"langchain_groq:
updated docstring for ChatGroq in langchain_groq to match that of the
description (in the appendix) provided in issue
https://github.com/langchain-ai/langchain/issues/22296. "

Issue: This PR is in response to issue
https://github.com/langchain-ai/langchain/issues/22296, and more
specifically the ChatGroq model. In particular, this PR updates the
docstring for langchain/libs/partners/groq/langchain_groq/chat_model.py
by adding the following sections: Instantiate, Invoke, Stream, Async,
Tool calling, Structured Output, and Response metadata. I used the
template from the Anthropic implementation and referenced the Appendix
of the original issue post. I also noted that: `usage_metadata `returns
none for all ChatGroq models I tested; there is no mention of image
input in the ChatGroq documentation; unlike that of ChatHuggingFace,
`.stream(messages)` for ChatGroq returned blocks of output.

---------

Co-authored-by: lucast2021 <lucast2021@headroyce.org>
Co-authored-by: Bagatur <baskaryan@gmail.com>
2024-06-14 03:08:36 +00:00
..
langchain_groq docs: Standardize ChatGroq (#22751) 2024-06-14 03:08:36 +00:00
scripts
tests groq[patch]: add usage_metadata to (a)invoke and (a)stream (#22834) 2024-06-13 10:26:27 -04:00
.gitignore
LICENSE
Makefile
poetry.lock groq[patch]: add usage_metadata to (a)invoke and (a)stream (#22834) 2024-06-13 10:26:27 -04:00
pyproject.toml groq[patch]: add usage_metadata to (a)invoke and (a)stream (#22834) 2024-06-13 10:26:27 -04:00
README.md

langchain-groq

Welcome to Groq! 🚀

At Groq, we've developed the world's first Language Processing Unit™, or LPU. The Groq LPU has a deterministic, single core streaming architecture that sets the standard for GenAI inference speed with predictable and repeatable performance for any given workload.

Beyond the architecture, our software is designed to empower developers like you with the tools you need to create innovative, powerful AI applications. With Groq as your engine, you can:

  • Achieve uncompromised low latency and performance for real-time AI and HPC inferences 🔥
  • Know the exact performance and compute time for any given workload 🔮
  • Take advantage of our cutting-edge technology to stay ahead of the competition 💪

Want more Groq? Check out our website for more resources and join our Discord community to connect with our developers!

Installation and Setup

Install the integration package:

pip install langchain-groq

Request an API key and set it as an environment variable

export GROQ_API_KEY=gsk_...

Chat Model

See a usage example.

Development

To develop the langchain-groq package, you'll need to follow these instructions:

Install dev dependencies

poetry install --with test,test_integration,lint,codespell

Build the package

poetry build

Run unit tests

Unit tests live in tests/unit_tests and SHOULD NOT require an internet connection or a valid API KEY. Run unit tests with

make tests

Run integration tests

Integration tests live in tests/integration_tests and require a connection to the Groq API and a valid API KEY.

make integration_tests

Lint & Format

Run additional tests and linters to ensure your code is up to standard.

make lint spell_check check_imports