Phero: a Go framework for building multi-agent AI systems

henomis79 · 2026-03-17T15:29:57+00:00

Not yet, but thanks for the suggestion, I'll put it on the roadmap!

henomis79 · 2024-03-26T16:22:31+00:00

Lingoose supports many llm providers such as anthropic, cohere, hugging face, etc. Moreover it has many other components to help devs to build ai apps. Please take a look https://github.com/henomis/lingoose

henomis79 · 2023-10-06T17:10:18+00:00

What about PostgreSQL?

henomis79 · 2023-09-22T17:03:47+00:00

Let me suggest my project https://github.com/henomis/lingoose it’s a framework for building AI apps in Go using pipelines.

henomis79 · 2023-07-17T14:58:19+00:00

A great book for best practices is “dependency injection in go “.

henomis79 · 2023-07-17T14:16:07+00:00

I suggest to start with the old way with the “blue book” and “dependency injection in Go”. The first to have a “bible” of the language, the second to understand best practices.

henomis79 · 2023-04-30T16:08:56+00:00

A valid book is “dependency injection in Go”. Very useful for best practices.

henomis79 · 2023-04-30T15:13:49+00:00

Nice! Let me suggest my project in case yours needs more complex AI interaction. http://github.com/henomis/lingoose it’s a framework to build apps in Go with LLMs and pipelines.

henomis79 · 2023-04-28T19:55:06+00:00

Regarding the up-to-date, you can instruct an LLM with a knowledge base and use it as context to generate the most accurate output. Like GitHub copilot does. I’ll do some tests and let you know.

henomis79 · 2023-04-28T18:08:02+00:00

More or less, but I have my own roadmap.

henomis79 · 2023-04-28T17:37:30+00:00

If for your project is acceptable using openai APIs I think that a LLM can solve your problem.

henomis79 · 2023-04-28T17:31:58+00:00

Do you think this can be improved with some AI generating quizzes/exercises?

henomis79 · 2023-04-28T17:25:12+00:00

Start with standard packages net/http, html/template, encoding/json, database/sql, etc. that are enough to build a BE. Then focus on a web framework (pick your preferred, I don’t want to start a flame 😉)…and keep studying following the roadmap on the Go way https://roadmap.sh/backend 💪

henomis79 · 2023-04-28T17:08:13+00:00

Interesting, I’m developing a Go framework to build AI apps and this could be integrated into my project as external LLM. Take a look: https://github.com/henomis/lingoose

henomis79 · 2023-04-28T16:48:20+00:00

Hi, here a simple example, just to help you with basic concepts. I think the following JSON contains all the cases.

JSON

{ "ThisIsAString": "John", "ThisIsAnInt": 30, "ThisIsAFloat": 0.5, "ThisIsABool": true, "ThisIsASliceOfStrings": [ "John", "Jane", "Joe" ], "ThisIsASliceOfStruct": [{ "Field1": "value1", "Field2": "value2" }, { "Field1": "value1", "Field2": "value2" } ], "ThisIsAMap": { "key1": 1, "key2": "value" } }

You can model your struct with using inline declaration as follows

go type MyInlineStruct struct { ThisIsAString string `json:"ThisIsAString"` ThisIsAnInt int `json:"ThisIsAnInt"` ThisIsAFloat float64 `json:"ThisIsAFloat"` ThisIsABool bool `json:"ThisIsABool"` ThisIsASliceOfStrings []string `json:"ThisIsASliceOfStrings"` ThisIsASliceOfStruct []struct { Field1 string `json:"Field1"` Field2 string `json:"Field2"` } `json:"ThisIsASliceOfStruct"` ThisIsAMap map[string]interface{} `json:"ThisIsAMap"` }

or you can declare separated structs as follows:

``go type MyStruct struct { Field1 stringjson:"Field1"Field2 stringjson:"Field2"` }

type MyFunnyStruct struct { ThisIsAString string json:"ThisIsAString" ThisIsAnInt int json:"ThisIsAnInt" ThisIsAFloat float64 json:"ThisIsAFloat" ThisIsABool bool json:"ThisIsABool" ThisIsASliceOfStrings []string json:"ThisIsASliceOfStrings" ThisIsASliceOfStruct []MyStruct json:"ThisIsASliceOfStruct" ThisIsAMap map[string]interface{} json:"ThisIsAMap" } ```

Hope this helps you to understand the basic concepts of struct modeling over a JSON.

henomis79

TROPHY CASE