Skip to main content

llm-inception

PyPI Changelog Tests License

Run prompts against LLMs hosted by Inception Labs with support for their unique diffusing animation feature.

Installation

Install this plugin in the same environment as LLM.

llm install llm-inception

This plugin uses Rich to display diffusing animations.

Usage

First, obtain an API key for Inception Labs and set it using the llm command-line tool:

llm keys set inception
# Paste your INCEPTION_API_KEY here

Alternatively, the plugin will use the LLM_INCEPTION_KEY environment variable if set.

Available Models

To see a list of available Inception Labs models that llm can use, run:

llm models list

The list of models is fetched from the API and cached. You can refresh this cache by running:

llm inception refresh

To see the detailed JSON information for all cached Inception Labs models:

llm inception models

Running Prompts

Run prompts against Inception Labs models like this:

llm -m inception/mercury-coder-small "Tell me a short story about a brave avocado."

Diffusing Animation

This plugin supports Inception Labs' "diffusing" feature, which shows an animation as the model generates its response. This is enabled by default when using the plugin in an interactive terminal.

Example:

llm chat -m inception/mercury-coder-small
> Write a haiku about a robot falling in love.
(Animation will play here)
Whispering wind chills,
Leaves dance under moonlit sky,
Night's soft embrace holds.
>

You can control this feature using the -o no_diffusion true option (note the underscore):

llm -m inception/mercury-coder-small "Why is the sky blue?" -o no_diffusion true

Other model options like max_tokens can also be set:

llm -m inception/mercury-coder-small "Explain quantum entanglement simply." -o max_tokens 150

Development

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

cd llm-inception
python -m venv venv
source venv/bin/activate

Now install the dependencies and test dependencies:

pip install -e '.[test]'

To run the tests (you'll need to create some!):

pytest

Metadata

Release files for llm-inception 0.2.1

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-inception 0.2.1
File Size Uploaded Provenance
llm_inception-0.2.1.tar.gz 6.1 kB Without provenance Details

Built distribution (wheel)

Table of built distributions (wheels) for llm-inception 0.2.1
File Interpreter ABI Platform
llm_inception-0.2.1-py3-none-any.whl Python 3 none any Details

Total release size: 12.3 kB

Release files / llm_inception-0.2.1.tar.gz

Download URL llm_inception-0.2.1.tar.gz
Size 6.1 kB
Tags Source
SHA-256 checksum
How to use checksums
7183d4cc861b9689423951f9a3ea5d0d5a5ce82ff1bef23fd1ca889460f91a15
BLAKE2b-256 checksum
How to use checksums
6b081aec1c4f888b5e8f2625985fc7f98f7f9239e1800f6e6664364e16954bcc
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/6.1.0 CPython/3.11.6

Release files / llm_inception-0.2.1-py3-none-any.whl

Download URL llm_inception-0.2.1-py3-none-any.whl
Size 6.2 kB
Tags Python 3
SHA-256 checksum
How to use checksums
691c6bd00604e1fe2859da2cf515d927c8e4b3bdf7d6322d7dec464f0a74028f
BLAKE2b-256 checksum
How to use checksums
5b93d0672267e3e83e8b89e79472c684ebbaf0853e2c7185dca5e165b3f6ad99
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/6.1.0 CPython/3.11.6

Security for llm-inception 0.2.1

Provenance

Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.

No provenance found

None of the files in this release were uploaded with provenance metadata.

A note on package security

PyPI is a repository for distributing packages, not a service for auditing them. While third-party security researchers and our staff do their best to detect and remove malicious packages, PyPI cannot guarantee the quality, security or suitability of any given package.

To learn more about protecting yourself from malicious actors, visit our package security documentation.

Release history Release notifications | RSS feed

This release

0.2.1 This release

2 release files No provenance

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