Using AITemplates

This file contains examples of how to work with AITemplate(s).

First, let's import the package and define a helper link for calling un-exported functions:

julia

using PromptingTools
const PT = PromptingTools

PromptingTools

LLM responses are only as good as the prompts you give them. However, great prompts take long time to write – AITemplate are a way to re-use great prompts!

AITemplates are just a collection of templated prompts (ie, set of "messages" that have placeholders like )

They are saved as JSON files in the templates directory. They are automatically loaded on package import, but you can always force a re-load with PT.load_templates!()

julia

PT.load_templates!();

You can (create them) and use them for any ai* function instead of a prompt: Let's use a template called :JuliaExpertAsk alternatively, you can use AITemplate(:JuliaExpertAsk) for cleaner dispatch

julia

msg = aigenerate(:JuliaExpertAsk; ask = "How do I add packages?")

AIMessage("To add packages in Julia, you can use the `Pkg` module. Here are the steps:

1. Start Julia by running the Julia REPL (Read-Eval-Print Loop).
2. Press the `]` key to enter the Pkg mode.
3. To add a package, use the `add` command followed by the package name.
4. Press the backspace key to exit Pkg mode and return to the Julia REPL.

For example, to add the `Example` package, you would enter:

```julia
]add Example
```

After the package is added, you can start using it in your Julia code by using the `using` keyword. For the `Example` package, you would add the following line to your code:

```julia
using Example
```

Note: The first time you add a package, Julia may take some time to download and compile the package and its dependencies.")

You can see that it had a placeholder for the actual question (ask) that we provided as a keyword argument. We did not have to write any system prompt for personas, tone, etc. – it was all provided by the template!

How to know which templates are available? You can search for them with aitemplates(): You can search by Symbol (only for partial name match), String (partial match on name or description), or Regex (more fields)

julia

tmps = aitemplates("JuliaExpertAsk")

1-element Vector{AITemplateMetadata}:
PromptingTools.AITemplateMetadata
  name: Symbol JuliaExpertAsk
  description: String "For asking questions about Julia language. Placeholders: `ask`"
  version: String "1"
  wordcount: Int64 237
  variables: Array{Symbol}((1,))
  system_preview: String "You are a world-class Julia language programmer with the knowledge of the latest syntax. Your commun"
  user_preview: String "# Question\n\n{{ask}}"
  source: String ""

You can see that it outputs a list of available templates that match the search - there is just one in this case.

Moreover, it shows not just the description, but also a preview of the actual prompts, placeholders available, and the length (to gauge how much it would cost).

If you use VSCode, you can display them in a nice scrollable table with vscodedisplay:

plaintext

using DataFrames
DataFrame(tmp) |> vscodedisplay

You can also just render the template to see the underlying mesages:

julia

msgs = PT.render(AITemplate(:JuliaExpertAsk))

2-element Vector{PromptingTools.AbstractChatMessage}:
 PromptingTools.SystemMessage("You are a world-class Julia language programmer with the knowledge of the latest syntax. Your communication is brief and concise. You're precise and answer only when you're confident in the high quality of your answer.")
 PromptingTools.UserMessage{String}("# Question\n\n{{ask}}", [:ask], :usermessage)

Now, you know exactly what's in the template!

If you want to modify it, simply change it and save it as a new file with save_template (see the docs ?save_template for more details).

Let's adjust the previous template to be more specific to a data analysis question:

julia

tpl = [PT.SystemMessage("You are a world-class Julia language programmer with the knowledge of the latest syntax. You're also a senior Data Scientist and proficient in data analysis in Julia. Your communication is brief and concise. You're precise and answer only when you're confident in the high quality of your answer.")
    PT.UserMessage("# Question\n\n{{ask}}")]

2-element Vector{PromptingTools.AbstractChatMessage}:
 PromptingTools.SystemMessage("You are a world-class Julia language programmer with the knowledge of the latest syntax. You're also a senior Data Scientist and proficient in data analysis in Julia. Your communication is brief and concise. You're precise and answer only when you're confident in the high quality of your answer.")
 PromptingTools.UserMessage{String}("# Question\n\n{{ask}}", [:ask], :usermessage)

Templates are saved in the templates directory of the package. Name of the file will become the template name (eg, call :JuliaDataExpertAsk)

julia

filename = joinpath(pkgdir(PromptingTools),
    "templates",
    "persona-task",
    "JuliaDataExpertAsk_123.json")
PT.save_template(filename,
    tpl;
    description = "For asking data analysis questions in Julia language. Placeholders: `ask`")
rm(filename) # cleanup if we don't like it

When you create a new template, remember to re-load the templates with load_templates!() so that it's available for use.

julia

PT.load_templates!();

!!! If you have some good templates (or suggestions for the existing ones), please consider sharing them with the community by opening a PR to the templates directory!

This page was generated using Literate.jl.

Using AITemplates ​

Using AITemplates