llm-github-models
LLM plugin to access GitHub Models API
Decision gist · record as of 2026-08-14
Yes. The package offers free access to a large roster of modern AI models through a simple CLI interface, requires minimal setup (just a GitHub token), has low install friction, is actively maintained, carries no security vulnerabilities, and uses a permissive license. Install it if you want to experiment with or integrate GitHub Models into command-line workflows or GitHub Actions without cost.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- Requires a GitHub personal access token (PAT) or GITHUB_TOKEN environment variable set; GitHub Models API access must be available on your GitHub account.
- Low install friction with a pure Python wheel.
- The package is actively maintained with recent commits and has 3 runtime dependencies (aiohttp, llm, azure-ai-inference), all standard libraries in the Python ecosystem.
License · maintenance · safety
Apache-2.0 (permissive) — Licensed under Apache-2.0 (permissive), which allows commercial use, modification, and distribution with minimal restrictions—suitable for most projects.
last release 2025-08-13 (366 days) · last repo commit 2026-07-06 · 95 stars
0 known vulnerabilities (OSV.dev, 2026-08-14) · 131,108 downloads/mo, #11,606 on PyPI
Alternatives
Verify before relying
pip install llm-github-models
llm keys set github
llm prompt 'top facts about cheese' -m github/gpt-4.1-mini- Exact number of supported models (description says '>30' but the table lists many more—clarify the current count)
- Whether all embedding models listed in the feature set are actually available in the current release
- Rate limits and quota behavior for free tier usage under typical workloads
What it is and what it does
llm-github-models is a plugin that extends the llm command-line tool to access GitHub Models, a free service offering dozens of AI language models including GPT-4o, o3, DeepSeek-R1, and Llama variants. It uses the Azure AI Inference SDK to communicate with the GitHub Models API and requires only a GitHub personal access token or existing GITHUB_TOKEN environment variable for authentication.
The plugin supports text-only and multimodal (image, audio) models, streaming and async outputs, structured schemas, embeddings, and tool use on models that support them. It tracks output token usage and integrates seamlessly with llm's attachment system for vision tasks. All models are prefixed with 'github/' to distinguish them from other llm providers.
Use it for
- Run GPT-4o or o3 reasoning models from the command line without a paid OpenAI subscription
- Process images with Llama vision models or Phi multimodal models using llm attachments
- Integrate free AI inference into GitHub Actions workflows with automatic GITHUB_TOKEN authentication
- Prototype with multiple model families (Mistral, Cohere, DeepSeek, Phi) to compare outputs
- Build CLI tools or scripts that call structured-output models like gpt-4.1 or gpt-5 with schemas
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
Yes.
The package offers free access to a large roster of modern AI models through a simple CLI interface, requires minimal setup (just a GitHub token), has low install friction, is actively maintained, carries no security vulnerabilities, and uses a permissive license. Install it if you want to experiment with or integrate GitHub Models into command-line workflows or GitHub Actions without cost.
Install
llm-github-models on PyPI
Before you install
Low install friction with a pure Python wheel. The package is actively maintained with recent commits and has 3 runtime dependencies (aiohttp, llm, azure-ai-inference), all standard libraries in the Python ecosystem.
Requires a GitHub personal access token (PAT) or GITHUB_TOKEN environment variable set; GitHub Models API access must be available on your GitHub account.
License in practice
Licensed under Apache-2.0 (permissive), which allows commercial use, modification, and distribution with minimal restrictions—suitable for most projects.
Quickstart
pip install llm-github-models
llm keys set github
llm prompt 'top facts about cheese' -m github/gpt-4.1-miniVerify before relying
- Exact number of supported models (description says '>30' but the table lists many more—clarify the current count)
- Whether all embedding models listed in the feature set are actually available in the current release
- Rate limits and quota behavior for free tier usage under typical workloads
Package facts
| License | Apache-2.0 permissive |
| Python support | Not specified |
| Install friction | Low. Pure-Python wheel |
| Runtime dependencies | 3 packagesaiohttpllmazure-ai-inference |
| Maintenance | Actively maintained 366 days since the last release |
| Last repo commit | |
| First released | |
| Downloads | 131,108 / month, #11,606 on PyPI 30-day window, as of 2026-08-14 |
| Known vulnerabilities | None known OSV.dev, checked 2026-08-14 |
| Classifiers | License :: OSI Approved :: Apache Software License |
Evidence: llm_github_models-0.18.0-py3-none-any.whl
Tags
Let your AI agent find packages like this
Example. Real query, live index.
You found this page by searching. An agent finds it by wishing: SkillFed indexes 14,416 PyPI packages by what they can do, searchable in plain language.
wish › “github models llm plugin”
- llm-github-modelsA plugin for the llm command-line tool that provides access to GitHub…
- llm-openai-pluginA plugin that extends LLM to access OpenAI models via the Responses…
- llm-anthropicA plugin for the LLM command-line tool that adds access to…
Give your agent the search over MCP, or paste the wish link into any chat.
More Artificial Intelligence packages
LiteLLM provides a unified Python interface to call 100+ LLM providers (OpenAI, Anthropic, Gemini, Bedrock, Azure, and others) using OpenAI-compatible API format, available as both a Python SDK and a self-hosted AI Gateway proxy server.
Install it if you need to work with multiple LLM providers or want to centralize LLM routing in your organization.
Client library and CLI tool for downloading, uploading, and managing models, datasets, and repositories on the Hugging Face Hub platform.
Install it if you work with Hugging Face Hub models or datasets.
LangChain provides a framework for building agents and LLM-powered applications by composing language models, tools, and memory through a unified API that abstracts over multiple model providers.
hf-xet provides chunk-based deduplication and efficient file transfer for the Hugging Face Hub, enabling faster uploads and downloads of large files with local disk caching.
Tokenizers converts raw text into token sequences for NLP models, with support for training custom vocabularies and using pre-built tokenizers (BPE, WordPiece) optimized for speed via Rust.
Transformers provides a unified framework for loading, fine-tuning, and running state-of-the-art pretrained models across text, vision, audio, video, and multimodal tasks using PyTorch, JAX, or TensorFlow.
Install it if you need to run or train any transformer-based model for NLP, vision, audio, or multimodal tasks.
See also llm · llm-openai-plugin · llm-anthropic · cohere · litellm-enterprise · vllm · g4f · vllm-tpu · fhlmi