gorilla VS Gin

Do you leverage https://gorilla.cs.berkeley.edu/ at all? If not, perhaps consider if it would solve some pain for you.

* Gorilla [https://github.com/ShishirPatil/gorilla]

Could be interesting to try some of these exercises with these models.

gorilla

Nice this made me go back and check up on the Gorilla LLM project [1] to see whats they are doing with API and if they have applied their fine tuning to any of the newer foundation models but looks like things have slowed down since they launched (?) or maybe development is happening elsewhere on some invisible discord channel but I hope the intersection of API calling and LLM as a logic processing function keep getting focus it's an important direction for interop across the web.

[1] https://github.com/ShishirPatil/gorilla

"Gorilla: Large Language Model Connected with Massive APIs" (2023) https://gorilla.cs.berkeley.edu/ :

> Gorilla enables LLMs to use tools by invoking APIs. Given a natural language query, Gorilla comes up with the semantically- and syntactically- correct API to invoke. With Gorilla, we are the first to demonstrate how to use LLMs to invoke 1,600+ (and growing) API calls accurately while reducing hallucination. We also release APIBench, the largest collection of APIs, curated and easy to be trained on! Join us, as we try to expand the largest API store and teach LLMs how to write them!

eval/:

Humans of AI Podcast #7

An amazing conversation with Shishir Patil the creator of the Gorilla LLM, a large language model specifically trained to use APIs!

Shishir is currently a 5th year PhD student at the University of California, Berkeley whose work broadly covers ML-Systems, LLMs, Edge-ML, and Sky computing.

Definitely give the episode a listen to hear Shishir's story.

And to read more about #GorillaLLM, check out the project page!

https://gorilla.cs.berkeley.edu

Now let’s define the functions that will be called whenever a request hits our API. All the functions will be referencing the context provided by the Gin web framework. Paste the following code below the sample slice we just added to api.go:

We will be using Gorilla Mux. As per their last update, they have a new group of maintainers, and their repos have shown activity to confirm that. The tutorial can be easily replicated in any other framework or library as well. So, while we will be using Gorilla Mux, you can try to replicate it in Gin or Fiber as well.

Now, let's dive into the fun part – creating our basic ToDo application using the powerful Gin framework. This section will walk you through the steps, breaking down the code into manageable snippets.

Thanks to the AWS Lambda Web Adapter, the application built as a (good old) REST/HTTP API using a familiar library (in this case, Gin.

Excellent Performance: Sponge is built on the gin framework, providing outstanding performance for web service development.

In this blog, we will delve into the fascinating realm of handling images in a Golang application, leveraging the power of the Gin framework for RESTful API development, MongoDB as a robust NoSQL database, and the mongo-driver library for seamless interaction with MongoDB. To store images efficiently, we'll explore the intricacies of GridFS, a specification within MongoDB for storing large files as separate chunks.

It uses Gin as the HTTP framework and PostgreSQL as the database with pgx as the driver and Squirrel as the query builder. It also utilizes Redis as the caching layer with go-redis as the client.

I have created an application with Go in Gin-Gonic. In my frontend (Nuxt3/TypeScript) I always get a CORS error:

We use Gin web framework https://gin-gonic.com for the routing, Gin provides a balance between performance, ease of use and extensibility making it a preferred choice for building and running web applications in Go.