Skip to main content

[!WARNING] Project is in its early stage of development. Current version is not stable.

*🦖 macrosaurus

Versatile AI client that works out of the box. Powered by OpenAI's Python SDK behind the scenes to handle dozens of AI providers without all the complexity.

Supports the following out of the box:

  • OpenAI
  • SambaNova
  • Anthropic
  • Cohere
  • Fireworks
  • Together
  • Vertex AI

📦 Setup

pip install macrosaurus

🛠️ Usage

Set up a base client from one of the supported providers.

from macrosaurus import Client

client = Client(provider="sambanova",
                api_key="API_KEY")

Extend these clients with better functionality.

from macrosaurus.llm import LLM

llm = LLM(client, model="Meta-Llama-3.2-3B-Instruct")
for chunk in llm.stream("Tell me a joke"):
    print(chunk, end="")

Want to add your own Provider?

from macrosaurus.providers import Provider
from macrosaurus import Client

perplexity = Provider(name="Perplexity", endpoint="https://api.perplexity.ai")
client = Client(provider=perplexity, api_key="API_KEY")

Docs to be continued...

🎯 Motivation

Handling LLMs or AI models from different providers should be easy. Made this because it wasn't. Macrosaurus is dirt simple and has tools that makes the development process nicer. Why not use LangChain instead? It's not built for production. Macrosaurus was also originally built for Openmacro.

Metadata

Release files for macrosaurus 0.0.4

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for macrosaurus 0.0.4
File Size Uploaded Provenance Actions
macrosaurus-0.0.4.tar.gz 6.0 kB Without provenance Details for macrosaurus-0.0.4.tar.gz

Release files / macrosaurus-0.0.4.tar.gz

Download URL macrosaurus-0.0.4.tar.gz
Size 6.0 kB
Tags Source
SHA-256 checksum
How to use checksums
f5960d1ccd29c380ce5582dbb603689c22ad74dbfb8c9abe9ed007b0fee2f97c
BLAKE2b-256 checksum
How to use checksums
0d0bec7cef33145e77ef180d7dbb167455082559dc87bd38c83cb63023850941
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/5.1.1 CPython/3.11.9

Security for macrosaurus 0.0.4

Provenance

Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.

No provenance found

None of the files in this release were uploaded with provenance metadata.

A note on package security

PyPI is a repository for distributing packages, not a service for auditing them. While third-party security researchers and our staff do their best to detect and remove malicious packages, PyPI cannot guarantee the quality, security or suitability of any given package.

To learn more about protecting yourself from malicious actors, visit our package security documentation.

Anthropic, PBC Visionary sponsor Bloomberg Visionary sponsor Hudson River Trading Visionary sponsor Meta Visionary sponsor NVIDIA Visionary sponsor Microsoft Sustainability sponsor Depot Continuous Integration AWS Cloud computing and Security Sponsor Datadog Monitoring Fastly CDN Google Download Analytics Sentry Error logging StatusPage Status page