Skip to main content

llm-groq

LLM plugin providing access to Groqcloud models.

Installation

Install this plugin in the same environment as LLM:

llm install llm-groq

Usage

First, obtain an API key for Groqcloud.

Configure the key using the llm keys set groq command:

llm keys set groq
<paste key here>

You can now access the three Mistral hosted models: groq-llama2 and groq-mixtral.

To run a prompt through groq-mixtral:

llm -m groq-mixtral 'A sassy name for a pet sasquatch'

To start an interactive chat session with groq-mixtral:

llm chat -m groq-mixtral
llm chat -m groq-mixtral
Chatting with groq-mixtral
Type 'exit' or 'quit' to exit
Type '!multi' to enter multiple lines, then '!end' to finish
> three proud names for a pet walrus
Here are three whimsical and proud-sounding names for a pet walrus:

1. Regalus Maximus
2. Glacierus Royalty
3. Arctican Aristocat

These names evoke a sense of majesty and grandeur, fitting for a noble and intelligent creature like a walrus. I hope you find these names fitting and amusing! If you have any other requests or need assistance with something else, please don't hesitate to ask.

To use a system prompt with groq-mixtral to explain some code:

cat example.py | llm -m groq-mixtral -s 'explain this code'

Model options

TBD

Development

To set up this plugin locally, first checkout the code. Then create a new virtual environment:

cd llm-groq
python3 -m venv venv
source venv/bin/activate

Metadata

Release files for llm-groq 0.9

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for llm-groq 0.9
File Size Uploaded
llm_groq-0.9.tar.gz 9.6 kB Details

Built distribution (wheel)

Table of built distributions (wheels) for llm-groq 0.9
File Interpreter ABI Platform
llm_groq-0.9-py3-none-any.whl Python 3 none any Details

Total release size: 19.7 kB

Release files / llm_groq-0.9.tar.gz

Download URL llm_groq-0.9.tar.gz
Size 9.6 kB
Tags Source
SHA-256 checksum
How to use checksums
600fef79d749a431a9ad0fc3f986b68629dd30ccdc61ba0d1ce77b33aa749d07
BLAKE2b-256 checksum
How to use checksums
2eaffdff701304eb46b4341f88b8ada16abe41f16f4f754f072ccbd7eb5b66e8
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/6.1.0 CPython/3.11.13

Release files / llm_groq-0.9-py3-none-any.whl

Download URL llm_groq-0.9-py3-none-any.whl
Size 10.1 kB
Tags Python 3
SHA-256 checksum
How to use checksums
aaec60d121f29bba5612f5c5f2fe26895e42bc7e27f95c27548eed0bf4ee0be5
BLAKE2b-256 checksum
How to use checksums
8ec1457ae46e77f8a2d42692b92d128378074d4630c113825c238fd38bb3225e
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/6.1.0 CPython/3.11.13

Release history Release notifications | RSS feed

This release

0.9 This release

2 release files

0.8

2 release files

0.7

2 release files

0.6

2 release files

0.5

2 release files

0.4

2 release files

0.3

2 release files

0.2

2 release files

0.1

2 release files

Anthropic, PBC Visionary sponsor Bloomberg Visionary sponsor Hudson River Trading Visionary sponsor Meta Visionary sponsor NVIDIA Visionary sponsor Microsoft Sustainability sponsor Depot Continuous Integration AWS Cloud computing and Security Sponsor Datadog Monitoring Fastly CDN Google Download Analytics Sentry Error logging StatusPage Status page