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Hugging Face

Use Hugging Face Inference Providers with Docker Agent.

Overview

Hugging Face Inference Providers routes requests to open models (Llama, Qwen, DeepSeek, Kimi, GLM and others) across many backends through a single OpenAI-compatible endpoint. Docker Agent includes built-in support for Hugging Face as an alias provider.

Setup

  1. Create a token from the Hugging Face token settings.

  2. Set the environment variable:

    export HF_TOKEN=your-token
    

Usage

Inline Syntax

The simplest way to use Hugging Face:

agents:
  root:
    model: huggingface/meta-llama/Llama-3.3-70B-Instruct
    description: Assistant using Hugging Face Inference Providers
    instruction: You are a helpful assistant.

Named Model

For more control over parameters:

models:
  huggingface_model:
    provider: huggingface
    model: meta-llama/Llama-3.3-70B-Instruct
    temperature: 0.7
    max_tokens: 8192

agents:
  root:
    model: huggingface_model
    description: Assistant using Hugging Face Inference Providers
    instruction: You are a helpful assistant.

Available Models

Hugging Face routes to a broad, changing catalog of open-weight models. Check the Hugging Face models page for current model IDs, context limits, and pricing.

Model Description
meta-llama/Llama-3.3-70B-Instruct Llama 3.3 70B, general-purpose chat and tool calling
Qwen/Qwen3-235B-A22B Qwen3 235B mixture-of-experts instruct model
deepseek-ai/DeepSeek-V3.2 DeepSeek, strong coding and reasoning

Model IDs are case-sensitive and must be passed exactly as the catalogue lists them.

How It Works

Hugging Face is implemented as a built-in alias in Docker Agent:

Because Hugging Face fronts open-weight models whose chat templates may reject more than one leading system message, Docker Agent coalesces its per-source system messages into a single one for this provider.

Example: Code Assistant

agents:
  coder:
    model: huggingface/Qwen/Qwen3-Coder-480B-A35B-Instruct
    description: Code assistant using Qwen3 Coder on Hugging Face
    instruction: |
      You are an expert programmer.
      Write clean, well-documented code and follow language best practices.
    toolsets:
      - type: filesystem
      - type: shell
      - type: think