llm-openai-plugin
LLM plugin for OpenAI
Decision gist · record as of 2026-08-14
Yes, if you need o1-pro or other Responses-API-only models and are already using llm. The low install friction, permissive Apache-2.0 license, and lack of known vulnerabilities make it safe. However, the aging maintenance status and preview designation mean you should expect possible API changes and verify that your target models are actually available before committing to production use.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- Requires llm to be installed in the same environment and a valid OpenAI API key configured via llm's key management.
- Low friction: pure Python wheel with only two runtime dependencies (llm and openai).
- Maintenance status is aging—last release was in the past—but the repository remains active and unarchived.
License · maintenance · safety
Apache-2.0 (permissive) — Apache-2.0 permissive license allows commercial and private use with minimal restrictions, making it safe for most projects.
last release 2025-10-06 (312 days) · last repo commit 2025-10-06 · 52 stars
0 known vulnerabilities (OSV.dev, 2026-08-14) · 80,216 downloads/mo, #14,307 on PyPI
Alternatives
Verify before relying
llm install llm-openai-plugin
llm -m openai/o1-pro "Your prompt here"- Whether the Responses API implementation offers performance or feature advantages beyond o1-pro access compared to Chat Completions.
- Stability guarantees or breaking-change policy for the preview-status plugin as OpenAI's API evolves.
- Whether all listed models are actually available or represent aspirational/future models.
- Current adoption metrics and real-world usage patterns beyond download counts.
What it is and what it does
This is a plugin for llm (the Datasette project's command-line interface to large language models) that adds support for OpenAI models via the newer Responses API instead of the default Chat Completions API. While llm already ships with OpenAI model support out of the box, this plugin exists primarily to unlock access to models like o1-pro that are only available through the Responses API. The plugin registers a set of OpenAI models with the openai/ prefix so you can invoke them through llm's standard command-line interface.
The plugin has two runtime dependencies: llm itself and openai. Installation is straightforward via llm install, and it requires Python 3.9 or later. The fact sheet notes this is a preview implementation, suggesting the API surface or behavior may change. The repository remains active and unarchived with recent commits.
Use it for
- Access o1-pro reasoning models through llm's CLI when you need advanced reasoning capabilities unavailable via Chat Completions.
- Integrate newer OpenAI models into existing llm-based workflows without rewriting code to call the openai SDK directly.
- Experiment with cutting-edge OpenAI models as they become available through the Responses API.
- Build CLI tools or scripts that leverage llm's model abstraction while using OpenAI's latest API features.
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
Yes, if you need o1-pro or other Responses-API-only models and are already using llm.
The low install friction, permissive Apache-2.0 license, and lack of known vulnerabilities make it safe. However, the aging maintenance status and preview designation mean you should expect possible API changes and verify that your target models are actually available before committing to production use.
Install
llm-openai-plugin on PyPI
Before you install
Low friction: pure Python wheel with only two runtime dependencies (llm and openai). Maintenance status is aging—last release was in the past—but the repository remains active and unarchived.
Requires llm to be installed in the same environment and a valid OpenAI API key configured via llm's key management.
License in practice
Apache-2.0 permissive license allows commercial and private use with minimal restrictions, making it safe for most projects.
Quickstart
llm install llm-openai-plugin
llm -m openai/o1-pro "Your prompt here"Verify before relying
- Whether the Responses API implementation offers performance or feature advantages beyond o1-pro access compared to Chat Completions.
- Stability guarantees or breaking-change policy for the preview-status plugin as OpenAI's API evolves.
- Whether all listed models are actually available or represent aspirational/future models.
- Current adoption metrics and real-world usage patterns beyond download counts.
Package facts
| License | Apache-2.0 permissive |
| Python support | Supports the current Python release >=3.9 |
| Install friction | Low. Pure-Python wheel |
| Runtime dependencies | 2 packagesllmopenai |
| Maintenance | Aging 312 days since the last release |
| Last repo commit | |
| First released | |
| Downloads | 80,216 / month, #14,307 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_openai_plugin-0.7-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 › “llm openai plugin”
- llm-openai-pluginA plugin that extends LLM to access OpenAI models via the Responses…
- livekit-plugins-openaiIntegrates OpenAI's Realtime, Responses, LLM, TTS, and STT APIs into…
- llama-index-multi-modal-llms-openaiIntegrates OpenAI's multi-modal language models with LlamaIndex,…
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 composio-openai · llm-github-models · llm · models-dev · llama-index-llms-openai · agent-framework-openai · unclecode-litellm · openai-guardrails · litellm-enterprise