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)
| File | Size | Uploaded | |
|---|---|---|---|
| llm_groq-0.9.tar.gz | 9.6 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| 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 |
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BLAKE2b-256 checksum How to use checksums |
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|
| 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 |
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|
|
BLAKE2b-256 checksum How to use checksums |
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|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/6.1.0 CPython/3.11.13
|