Skip to main content

Hugging Face inference agent with ACP support, powered by fast-agent-mcp

Project description

hf-inference-acp

Hugging Face inference agent with ACP (Agent Client Protocol) support, powered by fast-agent-mcp.

Installation

uvx hf-inference-acp

What is this?

This package provides an ACP-compatible agent for Hugging Face Inference API. It allows you to use Hugging Face's Inference Providers through any ACP-compatible client (like Toad).

Features

  • Setup Mode: Configure Hugging Face credentials and model settings
  • Hugging Face Mode: AI assistant powered by Hugging Face Inference API
  • HuggingFace MCP Server: Built-in integration with Hugging Face's MCP server for accessing models, datasets, and spaces

Quick Start

  1. Run the agent:

    uvx hf-inference-acp
    
  2. If HF_TOKEN is not set, you'll start in Setup mode with these commands:

    • /login - Get instructions for HuggingFace authentication
    • /set-model <model> - Set the default model
    • /check - Verify your configuration
  3. Once authenticated (HF_TOKEN is set), you'll automatically start in Hugging Face mode.

  4. In Hugging Face mode, use /connect to connect to the Hugging Face MCP server for model/dataset search tools.

Curated Model Aliases

/set-model supports short aliases from fast-agent's curated Hugging Face list, including:

  • kimi
  • glm
  • minimax
  • deepseek32
  • kimi25 (thinking profile)
  • qwen35 (thinking profile)
  • qwen35instruct (instruct profile)

Kimi 2.5 aliases resolve to hf.moonshotai/Kimi-K2.5:fireworks-ai with curated defaults:

  • kimi25: temperature=1.0, top_p=0.95

Qwen 3.5 aliases resolve to hf.Qwen/Qwen3.5-397B-A17B:novita with curated sampling defaults:

  • qwen35: temperature=0.6, top_p=0.95, top_k=20, min_p=0.0, presence_penalty=0.0, repetition_penalty=1.0
  • qwen35instruct: temperature=0.7, top_p=0.8, top_k=20, min_p=0.0, presence_penalty=1.5, repetition_penalty=1.0

Configuration

Configuration is stored at ~/.config/hf-inference/hf.config.yaml:

default_model: hf.moonshotai/Kimi-K2-Instruct-0905

mcp:
  servers:
    huggingface:
      url: "https://huggingface.co/mcp?login"

Authentication

Set your HuggingFace token using one of these methods:

  1. Environment variable:

    export HF_TOKEN=your_token_here
    
  2. HuggingFace CLI:

    huggingface-cli login
    

Get your token from: https://huggingface.co/settings/tokens

License

Apache License 2.0 - See the main repository for details.

More Information

For full documentation and the main project, visit: https://github.com/evalstate/fast-agent

Project details


Release history Release notifications | RSS feed

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

hf_inference_acp-0.6.2.tar.gz (30.2 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

hf_inference_acp-0.6.2-py3-none-any.whl (34.1 kB view details)

Uploaded Python 3

File details

Details for the file hf_inference_acp-0.6.2.tar.gz.

File metadata

  • Download URL: hf_inference_acp-0.6.2.tar.gz
  • Upload date:
  • Size: 30.2 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: uv/0.10.11 {"installer":{"name":"uv","version":"0.10.11","subcommand":["publish"]},"python":null,"implementation":{"name":null,"version":null},"distro":{"name":"Ubuntu","version":"24.04","id":"noble","libc":null},"system":{"name":null,"release":null},"cpu":null,"openssl_version":null,"setuptools_version":null,"rustc_version":null,"ci":true}

File hashes

Hashes for hf_inference_acp-0.6.2.tar.gz
Algorithm Hash digest
SHA256 f69e8dd6ecdcfa96a177d37ab18016ad803e0276e87daf63159e7692d6bf78d2
MD5 0da8844be098537dd71c504430a3a590
BLAKE2b-256 c07536354f3b01f1e248e852a316aa222a81ae0d23a2ac488d7bc8414474e2d4

See more details on using hashes here.

File details

Details for the file hf_inference_acp-0.6.2-py3-none-any.whl.

File metadata

  • Download URL: hf_inference_acp-0.6.2-py3-none-any.whl
  • Upload date:
  • Size: 34.1 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: uv/0.10.11 {"installer":{"name":"uv","version":"0.10.11","subcommand":["publish"]},"python":null,"implementation":{"name":null,"version":null},"distro":{"name":"Ubuntu","version":"24.04","id":"noble","libc":null},"system":{"name":null,"release":null},"cpu":null,"openssl_version":null,"setuptools_version":null,"rustc_version":null,"ci":true}

File hashes

Hashes for hf_inference_acp-0.6.2-py3-none-any.whl
Algorithm Hash digest
SHA256 ec6e69c46c21604d547849f88b017336e0c9fcf1a753d2e3839be3fcd0ad3c8e
MD5 9e8f9aa5ee75138f7a2045bcd97f091d
BLAKE2b-256 f94c725827fb26d356106742ae811a43618757dd926cfa64b5fcd454e02de45d

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page