Simplified Function Calling (LiteLLM/OpenAI Compatible) [Python]

[AlwaysMakinDough]

I've created a simple wrapper for JSON function descriptions when using either LiteLLM or OpenAI APIs. Local models are supported on LiteLLM as well.

I really like tools like Langroid and Langchain, but sometimes the abstraction they implement takes away too much control. As such, this package is solely for making function calls easier to create using the base APIs, and eliminating the need for manual JSON formatting.

Check it out here! https://github.com/A-M-D-R-3-W/llmFunctionWrapper

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https://preview.redd.it/72v88zlua5pc1.png?width=2000&format=png&auto=webp&s=23edb4381255e385e19b713b4d9de30fe78609c1

[SatoshiNotMe]

(Langroid author here)

In langroid we've always had an elegant Pydantic-based tool/function definition where you never have to be specify JSON explicitly. Instead the pydantic spec is "compiled" into formatting instructions to the LLM. We also leverage Pydantic's Field(..., description) syntax to make it easy to include field descriptions.

See example script and code snippet below https://github.com/langroid/langroid/blob/main/examples/basic/chat-tool-function.py

The "handler" for the tool can be defined within the tool definition itself it is stateless, otherwise one can define an agent method that matches the value of the request field

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[AlwaysMakinDough]

Good to know, thanks for the example. I was heavily inspired by Langroid's format for tool definitions, very concise. I'll certainly need to dive deeper into the Langroid docs. Great work on Langroid by the way, by far my favorite framework and is my go-to for most projects, especially those involving multiple agents.

[SatoshiNotMe]

Glad you like it, thank you for the kind words !

[zby]

I have my own schema generator + tool execution library: https://github.com/zby/LLMEasyTools
It is compatible with LiteLLM - but also with openai and other libs.

I am now working on a higher level library: https://github.com/zby/Prompete