llm-tiyuvta
LLM plugin for tiyuvta — prepaid open-weight-model inference with one price per model, no subscription.
Every model on the endpoint speaks the identical OpenAI-compatible API: streaming, tool calling, structured output, and vision where the model has eyes. The plugin reads the live model catalog, so new models appear without a plugin update.
Installation
Install this plugin in the same environment as LLM:
llm install llm-tiyuvta
Configuration
Get an API key from inference.tiyuvta.ai, then:
llm keys set tiyuvta
# Paste key here
You can also set it as the TIYUVTA_KEY environment variable — note that a key stored
with llm keys set takes precedence over the environment variable.
Models appear in llm models once a key is configured.
Usage
Run a prompt (short aliases work — qwen3.8-27b for tiyuvta/qwen/qwen3.8-27b):
llm -m qwen3.8-27b "Three reasons the sky looks blue"
Chat interactively:
llm chat -m qwen3.8-27b
Vision — attach an image:
llm -m qwen3.8-27b "describe this" -a photo.jpg
Tools and schemas work the way they do for any OpenAI-compatible LLM model:
llm -m qwen3.8-27b --schema 'name, bullet_points: three key points' "summarize: ..."
List the models the endpoint currently serves:
llm tiyuvta models
Refresh the cached catalog after a new model launches:
llm tiyuvta refresh
Development
To set up this plugin locally, first checkout the code. Then create a new virtual environment:
cd llm-tiyuvta
python -m venv venv
source venv/bin/activate
Now install the dependencies and test dependencies:
llm install -e '.[test]'
To run the tests:
pytest
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