Skip to main content

Python client for Orchard, a compute platform for Apple Silicon

Project description

Orchard

Python client for high-performance LLM inference on Apple Silicon.

Installation

pip install orchard

Usage

from orchard import Client

client = Client()

response = client.chat(
    model="meta-llama/Llama-3.1-8B-Instruct",
    messages=[{"role": "user", "content": "Hello!"}],
)
print(response.text)

Streaming

for delta in client.chat(model="...", messages=[...], stream=True):
    print(delta.content, end="", flush=True)

Batch Inference

responses = client.chat_batch(
    model="...",
    conversations=[
        [{"role": "user", "content": "Question 1"}],
        [{"role": "user", "content": "Question 2"}],
    ],
)

Model Profiles

Chat templates and control tokens are loaded from the Pantheon submodule at orchard/formatter/profiles/. This provides a single source of truth shared across all Orchard SDKs (Python, Rust, Swift). See that repo for the list of supported model families.

Requirements

  • Python 3.10+
  • macOS 14+ (Apple Silicon)
  • PIE (Proxy Inference Engine)

Related

License

Apache-2.0

Project details


Download files

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

Source Distribution

orchard-2026.3.7.tar.gz (109.6 kB view details)

Uploaded Source

Built Distribution

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

orchard-2026.3.7-py3-none-any.whl (124.6 kB view details)

Uploaded Python 3

File details

Details for the file orchard-2026.3.7.tar.gz.

File metadata

  • Download URL: orchard-2026.3.7.tar.gz
  • Upload date:
  • Size: 109.6 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.12.12

File hashes

Hashes for orchard-2026.3.7.tar.gz
Algorithm Hash digest
SHA256 6e2a49d23b61024aa5bdb2557f37112c70e3613e79b24bcaa67c06762e3ffc60
MD5 3cec148b46717bd2518b39747473e1e4
BLAKE2b-256 a61620cd9eeaecd9ab6cbda5e79b155d46b9f7d780437e220de0817d704ff1aa

See more details on using hashes here.

File details

Details for the file orchard-2026.3.7-py3-none-any.whl.

File metadata

  • Download URL: orchard-2026.3.7-py3-none-any.whl
  • Upload date:
  • Size: 124.6 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.12.12

File hashes

Hashes for orchard-2026.3.7-py3-none-any.whl
Algorithm Hash digest
SHA256 604cd625be7bc78f83f3ef09b76422c9123eb747d24887cf1b94291b67f99bc8
MD5 94a19481ee8203ba23ea14b60cbd179a
BLAKE2b-256 6547d4ca6b3ed2f6a8b1b9d7ced5c425f1a2a374bb50e4529472c97267c16230

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