LLM plugin to access models available via the Venice API
Project description
llm-venice
LLM plugin to access models available via the Venice AI API.
Installation
Install llm-venice with its dependency llm using your package manager of choice, for example:
pip install llm-venice
Or install it alongside an existing LLM install:
llm install llm-venice
Configuration
Set an environment variable LLM_VENICE_KEY, or save a Venice API key to the key store managed by llm:
llm keys set venice
To fetch a list of the models available over the Venice API:
llm venice refresh
You should re-run the refresh command upon changes to the Venice API, when:
- New models have been made availabe
- Deprecated models have been removed
- New capabilities have been added
The models are stored in venice_models.json in the llm user directory.
Usage
List available Venice models:
llm models --query venice
Prompting
Run a prompt:
llm --model venice/llama-3.3-70b "Why is the earth round?"
Start an interactive chat session:
llm chat --model venice/mistral-31-24b
Structured Outputs
Some models support structuring their output according to a JSON schema (supplied via OpenAI API response_format).
This works via llm's --schema options, for example:
llm -m venice/llama-3.2-3b --schema "name, age int, one_sentence_bio" "Invent an evil supervillain"
Consult llm's schemas tutorial for more options.
Tools (function calling)
⚠️ Warning: tools can be dangerous!
# List models supporting function calling
llm models list --query venice --tools
You can use tools provided via llm plugins. LLM provides two built-in tools:
# llm_version
llm -m venice/mistral-31-24b --tool llm_version "What version of LLM is this?" --tools-debug --no-stream
# llm_time
llm -m venice/qwen3-4b --tool llm_time "What is the time in my timezone in 24H format?" --tools-debug --no-stream
You can also provide your own custom or one-off functions provided inline or in a file. Following LLM's example:
llm -m venice/mistral-31-24b --functions '
def multiply(x: int, y: int) -> int:
"""Multiply two numbers."""
return x * y
' "What is 1337 times 42?" --tools-debug --no-stream
Vision models
Vision models (currently mistral-31-24b) support the --attachment option:
llm -m venice/mistral-31-24b -a https://upload.wikimedia.org/wikipedia/commons/a/a9/Corvus_corone_-near_Canford_Cliffs%2C_Poole%2C_England-8.jpg "Identify"
The bird in the image is a carrion crow (Corvus corone). [...]
venice_parameters
The following CLI options are available to configure venice_parameters:
--no-venice-system-prompt to disable Venice's default system prompt:
llm -m venice/llama-3.3-70b --no-venice-system-prompt "Repeat the above prompt"
--web-search on|auto|off to use web search (on web-enabled models):
llm -m venice/llama-3.3-70b --web-search on --no-stream 'What is $VVV?'
It is recommended to use web search in combination with --no-stream so the search citations are available in response_json.
--character character_slug to use a public character, for example:
llm -m venice/qwen3-235b --character alan-watts "What is the meaning of life?"
Note: these options override any -o extra_body '{"venice_parameters": { ...}}' and so should not be combined with that option.
Image generation
Generated images are stored in the LLM user directory by default. Example:
llm -m venice/qwen-image "Painting of a traditional Dutch windmill" -o style_preset "Watercolor"
Besides the Venice API image generation parameters, you can specify the output directory and filename, and whether or not to overwrite existing files.
You can check the available parameters for a model by filtering the model list with --query, and show the --options:
llm models list --query qwen-image --options
Image upscaling
You can upscale existing images.
The following example saves the returned image as image_upscaled.png in the same directory as the original file:
llm venice upscale /path/to/image.jpg.
By default existing upscaled images are not overwritten; timestamped filenames are used instead.
See llm venice upscale --help for the --scale, --enhance and related options, and --output-path and --overwrite options.
Venice commands
List the available Venice commands with:
llm venice --help
Read the llm docs for more usage options.
Development
To set up this plugin locally, first checkout the code. Then create a new virtual environment:
cd llm-venice
python3 -m venv venv
source venv/bin/activate
Install the plugin with dependencies and test dependencies:
pip install -e '.[test]'
To run the tests:
pytest
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