Automated refresh of model profile data for all in-monorepo partner integrations via `langchain-profiles refresh`. 🤖 Generated by the [`refresh_model_profiles` workflow](https://github.com/langchain-ai/langchain/blob/master/.github/workflows/refresh_model_profiles.yml). ## Summary of changes **4 added · 0 removed · 1 changed** across 2 provider(s). <details> <summary>huggingface</summary> **➕ 1 added** - `openai/gpt-oss-20b` — 131,072 ctx, 32,768 out, reasoning, tools </details> <details> <summary>openrouter</summary> **➕ 3 added** - `nex-agi/nex-n2-mini` — 262,144 ctx, 262,144 out, text+image in, reasoning, tools - `tencent/hy3` — 202,752 ctx, 131,072 out, reasoning, tools - `tencent/hy3:free` — 262,144 ctx, 262,144 out, reasoning, tools **✏️ 1 changed** - `meta-llama/llama-3.2-3b-instruct`: max input tokens 80,000 → 131,072; max output tokens 80,000 → 131,072; added structured output </details> Co-authored-by: mdrxy <61371264+mdrxy@users.noreply.github.com>
langchain-huggingface
Looking for the JS/TS version? Check out LangChain.js.
Quick Install
uv add langchain-huggingface
Note: The base install does not include
sentence-transformersortransformers. If you plan to useHuggingFaceEmbeddingsorHuggingFacePipelinefor local inference, install the[full]extra which includessentence-transformers>=5.2.0andtransformers>=5.0.0:uv add "langchain-huggingface[full]"Migrating from
langchain-community? Note thatlangchain-communityacceptedsentence-transformers>=2.2.0, butlangchain-huggingface[full]requires>=5.2.0. If your project pins an older version, upgrade it:uv add "sentence-transformers>=5.2.0"
🤔 What is this?
This package contains the LangChain integrations for Hugging Face related classes.
📖 Documentation
For full documentation, see the API reference. For conceptual guides, tutorials, and examples on using these classes, see the LangChain Docs.
📕 Releases & Versioning
See our Releases and Versioning policies.
💁 Contributing
As an open-source project in a rapidly developing field, we are extremely open to contributions, whether it be in the form of a new feature, improved infrastructure, or better documentation.
For detailed information on how to contribute, see the Contributing Guide.
Resources
- LangChain Academy — comprehensive, free courses on LangChain libraries and products, made by the LangChain team
- Code of Conduct — community guidelines and standards