If you haven’t yet, be sure to try out 𝗮𝗶𝘀𝘂𝗶𝘁𝗲 python library by Andrew Ng.

It’s pretty simple but powerful. If you are using more than one LLM provider in your applications or you are testing which provider fits your use case the best, this abstraction layer is very convenient.What does the library do?

➡️ Provides a unified interface for models of different third party providers.

➡️ Uses a convenient notation of <𝘱𝘳𝘰𝘷𝘪𝘥𝘦𝘳>:<𝘮𝘰𝘥𝘦𝘭_𝘵𝘢𝘨> to call different apis. My thoughts:

✅ I love how notation similar to container tagging is used to invoke different APIs. It follows software engineering best practices and allows for efficient model versioning in your Agentic apps.

✅ Useful for quickly testing different combinations of Prompt x Model.

✅ Open Source - different providers are open to include themselves in the list of supported models.

ℹ️ In general, you would be implementing similar abstractions in your agentic application code - it makes it easier to maintain the codebase due to unified abstraction over multiple providers.

❓ It implements API 𝘀𝗶𝗺𝗶𝗹𝗮𝗿 𝘁𝗼 𝗢𝗽𝗲𝗻𝗔𝗜 library. Will the abstraction stick well? We’ll see. Looking forward to the library evolving!

Install the library by running:

➡️ pip install aisuite

or

➡️ pip install aisuite[all] - if you want to install provider libraries (required) together with 𝘢𝘪𝘴𝘶𝘪𝘵𝘦.

Github repo: lnkd.in/dTRibHda you already used 𝘢𝘪𝘴𝘶𝘪𝘵𝘦? Let me know in the comment section 👇

If you want to get some insights about AI Engineering, I have wrote an article sharing my thoughts here: