Overview

AskAI.jl, as its name suggests, is a straightforward tool for querying Large Language Models. Currently supporting ollama and Google's Gemini model API. it's designed to be simple and direct: send prompts and questions to AI provider, and optionally execute the included code within a sandboxed "playground" to avoid affecting the main scope.

The main macro, @ai, retrieves results from a large language model, while @AI executes the code within the "playground" scope and displays the output(or any errors.)

a REPL mode was also support. Press } to enter and backspace to exit

AskAI

Note

as most of the AI tool, it needs the api key or similar configure, in AskAI it follow the rule: "providerg|model|api". eg, For the Gemini it would be "Gemini|gemini-2.0-flash|1234567890abcdef1234567890abcdef" and for ollama it would be something likes "ollama|qwen2.5:72b|http://localhost:11434". you can put it in the ENV["AskAI_config"] or use AskAI.setapi("providerg|model|api") to apply your setting. Please also add a module called playground: module playground end in your main scope for the code execute just in case you want to use the @AI macro.

Note

A convenient way is to put below code in your Julia startup.jl configuration file.

ENV["AskAI_config"] =  "provider|model|api or URL"
module playground end
using AskAI

then you can use the AskAI in every session by default

it starts as my persional AI tool in julia REP and only support the Gemini model currently. have fun with it and I welcome your suggestions and input for AskAI.jl!!!

installation

(@v1.10) pkg> add https://github.com/AIBioLab/AskAI 
julia> using AskAI
# now you can configure it with your AI model provider; eg ollama
julia> AskAI.setapi("ollama|glm4:latest|http://localhost:11434")
# or Gemini
julia> AskAI.setapi("Gemini|modelName|your API key")
Note

by default the response mode is stream, it should work well, however you can always change it by set AskAI.Brain.stream = false.

quickly example

Here's an example of using AskAI to generate scatter and histogram plots and perform basic statistical calculations.

@AI "tell me the current date, use the pacakge when in need"
@AI "create a new project in /tmp, name it as demo + date, activate it"
@AI "load my data as df, the data file is in /tmp/celldata.csv"
@AI "tell me the data size"
@AI "does the data contain columns named geneX and  geneY??"
@AI "install the package to support figure display in the terminal"
@AI "plot a scatter plot of geneX and geneY, I want the geneX on axis Y"
@AI "please also label the axis"
@AI "calculate the correlation of geneX and geneY"
@AI "keep only 3 digits"
@AI "generate a histogram to show the distribution of geneX "
@AI "do the same to geneY"
@AI "fit a linear model to predict value of geneY from geneX,using GLM"
@AI "give me the coef of geneX in this model,keep 5 digits"

Output Results are here

Details

result1 result2 result3

Note

some time you may get the wrong result from the LLM, LLM results aren't always perfect, so please double-check. You can use @ai instead of @AI for code checks. then use exe() to perform the code. Often the case I met is the necessary packages aren't installed.

@ai "tell me the current date,install the package if it needs"
AskAI.exe(ans)

to review the conversation history

AskAI.Brain.history["ask"] 
AskAI.Brain.history["ans"] 

# review the last response 
AskAI.Brain.history["ans"][end] |> AskAI.MD

you can also try the stream mode under terminal

AskAI.Brain.stream = true
@ai "why the sky is blue"

function and macro

AskAI.exe — Method

execute the string as code

"1 + 1" |> AskAI.exe

(@ai "1 + 1") |> AskAI.exe
AskAI.reset — Method

Reset the AskAI, it will remove the conversation history, memory, prompt... and everything as default defined

AskAI.reset()
AskAI.setapi — Method
setapi("ollama|modelName|URL")
setapi("gemini|modelName|api")
AskAI.@AI — Macro

similar to @ai,

send the question to AI but @AI perform the code directly and only return the result, or error :(

the conversation history will stored in the AskAI.Brain.history

example:

@AI "tell me the current time, used the package you need"
AskAI.@ai — Macro

get the answer from the AI

example

@ai "fit a linear model"
# or you can concatenate your question
@ai "fit a" + "linear model"
AskAI.checkMemory! — Function

optimalize the memory text, when the memory words length exceeds 3000 words, summary it into 300 words

AskAI.showStreamStringFromChannel — Method

for stream mode, displays a streaming response from the channel, updating the display in terminal with each chunk of text received.

AskAI.streamToMemory — Method

for stream mode, take string from the channel, convert to markdown, and save as memory context