llm-electronhub
LLM plugin for accessing 450+ models via ElectronHub
Installation
Install this plugin in the same environment as LLM.
llm install llm-electronhub
Or for development:
cd llm-electronhub
llm install -e .
Configuration
You need to set an ElectronHub API key using the llm keys set electronhub command:
llm keys set electronhub
# Paste your ElectronHub API key
Or set the ELECTRONHUB_API_KEY environment variable.
Usage
Once configured, all ElectronHub models will be available with the electronhub/ prefix:
# List all available models
llm electronhub models
# List only chat-capable models
llm electronhub models --chat-only
# Use a model
llm -m electronhub/claude-opus-4-1-20250805 "Explain quantum computing"
# Use GPT-5
llm -m electronhub/gpt-5 "Write a haiku about programming"
# Use Gemini 2.5 Pro (1M context!)
llm -m electronhub/gemini-2.5-pro "Summarize this long document..."
Features
- 450+ models supporting chat completions from various providers
- OpenAI-compatible API for seamless integration
- Vision support for multimodal models
- Large context windows - up to 2M tokens (Grok-4-fast)
- Reasoning models - Models with
-thinkingsuffix for extended reasoning
Available Commands
List models
# List all models
llm electronhub models
# List as JSON
llm electronhub models --json
# List only chat-capable models
llm electronhub models --chat-only
Check API key status
llm electronhub key
Recommended Models
- Claude:
electronhub/claude-opus-4-1-20250805(200k context) - GPT:
electronhub/gpt-5(400k context) - Gemini:
electronhub/gemini-2.5-pro(1M context) - Grok:
electronhub/grok-4-0709(256k context) - DeepSeek:
electronhub/deepseek-v3.1(164k context) - Qwen:
electronhub/qwen3-max(256k context)
Development
To set up this plugin locally, first checkout the code. Then create a new virtual environment:
cd llm-electronhub
python -m venv venv
source venv/bin/activate # On Windows: venv\Scripts\activate
Now install the dependencies and test dependencies:
llm install -e '.[test]'
To run the tests:
pytest
About ElectronHub
ElectronHub is a unified LLM API proxy service that provides access to 450+ models from various providers (Anthropic, OpenAI, Google, Meta, xAI, Alibaba, and more) through a single API endpoint and key.
Metadata
Release files for llm-electronhub 0.1
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | Provenance | |
|---|---|---|---|---|
| llm_electronhub-0.1.tar.gz | 8.8 kB | Without provenance | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| llm_electronhub-0.1-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 18.1 kB
Release files / llm_electronhub-0.1.tar.gz
| Download URL | llm_electronhub-0.1.tar.gz |
|---|---|
| Size | 8.8 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
3ea152918e4109cf2cb4e4c47cc6e18295d74cbd1252c1b5a14b7717745aaf5c
|
|
BLAKE2b-256 checksum How to use checksums |
97ac764016d84a61723017b61155f36a0546ac1bf6132d49a7514e4c81749278
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
uv/0.8.13
|
Release files / llm_electronhub-0.1-py3-none-any.whl
| Download URL | llm_electronhub-0.1-py3-none-any.whl |
|---|---|
| Size | 9.3 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
86b609c4ced15ec6219410ae19b170cc5e4f00d1722920423208d7535c908e02
|
|
BLAKE2b-256 checksum How to use checksums |
973c998e7509f2029fe8bacc75f5d73145af846297f496607243fd3caed9c06d
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
uv/0.8.13
|
Security for llm-electronhub 0.1
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.