llm-hubris
LLM plugin for models hosted by Hubris — an OpenAI-compatible LLM gateway billed in Russian rubles, with 400+ models (OpenAI, Anthropic, Google, DeepSeek, Qwen and more) behind a single API key.
Installation
First, install the LLM command-line utility.
Now install this plugin in the same environment as LLM.
llm install llm-hubris
Configuration
You will need an API key from Hubris. Create one at hubris.pw/keys.
You can set that as an environment variable called HUBRIS_API_KEY, or add it to the llm set of saved keys using:
llm keys set hubris
Enter key: <paste key here>
Usage
The plugin registers every chat model from your Hubris catalog. To list them, run:
llm models list
You should see a list that looks something like this:
Hubris: hubris/anthropic/claude-sonnet-5
Hubris: hubris/openai/gpt-5.6-luna
Hubris: hubris/google/gemini-3.7-flash
Hubris: hubris/deepseek/deepseek-v4-flash-0731
...
Model IDs always use the full vendor/model form shown in the Hubris catalog — there is no alias resolution on the gateway side.
The list is cached for an hour. Force a refresh with:
llm hubris refresh
To run a prompt against a model, pass its full model ID to the -m option:
llm -m hubris/anthropic/claude-sonnet-5 "Five spooky names for a pet tarantula"
You can set a shorter alias for a model using the llm aliases command:
llm aliases set sonnet hubris/anthropic/claude-sonnet-5
Now you can prompt it with:
cat llm_hubris.py | llm -m sonnet -s 'write some pytest tests for this'
Images are supported by vision models:
llm -m hubris/anthropic/claude-sonnet-5 'describe this image' -a https://static.simonwillison.net/static/2024/pelicans.jpg
Reasoning models accept the reasoning_effort option:
llm -m hubris/openai/gpt-5.6-luna -o reasoning_effort high 'Plan a three-day trip to Kazan'
Listing models with prices
llm hubris models
Outputs every chat model with its context window and RUB prices per million tokens. Add --json for the raw catalog entries.
Development
To set up this plugin locally, first checkout the code. Then create a new virtual environment:
cd llm-hubris
python -m venv venv
source venv/bin/activate
Now install the dependencies and test dependencies:
pip install -e '.[test]'
To run the tests:
pytest
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