Linq.AI.OpenAI 2.0.2

Linq.AI

This library adds Linq extension methods which use AI models to transform and manipulate data.

This library was heaviy inspired by stevenic's agentm-js library, Kudos!

Installation

dotnet add package Linq.AI
dotnet add package Linq.AI.OpenAI

ITransformer

The Linq.AI package needs an ITransformer for the AI model that is being used.

Currently there is an implementation for OpenAI which you can get by installing Linq.AI.OpenAI

And then instantiate a transformer like this:

var model = new new OpenAITransformer(model: "gpt-4o-mini", "<open ai key>");

NOTE: The model must support structured output.

Object Extensions

The object extensions use the ITransformer model to work with a single item (aka text, object, etc.).

item.Classify()

enum Genres { Rock, Pop, Electronica, Country, Classical };
var classification = item.Classify<Genres>(model);

item.Summarize()

var summary = item.Summarize(model, "with 3 words");

item.Matches()

if (item.Matches(model, "there is date"))
  ...

item.Answer()

var summary = text.Answer(model, "what is the birthday?");

item.Select()

Select pulls a collection of items from the source.

Example using model to select text from the item

var words = item.Select<string>(model, "The second word of every paragraph");

Example using model to select structed data.

public class HREF 
{ 
	public string Url {get;set;}
	public string Title {get;set;}
}
var summary = text.Select<HREF>(model);

Linq Extensions

The object extensions use the ITransformer model to work each item in a collections.

NOTE: These methods internally run AI calls as throttled parallel background tasks.

enumerable.Classify()

This allows you to classify each item using a model;

enum Genres { Rock, Pop, Electronica, Country, Classical };
var classifiedItems = items.Classify<Genres>(model);

enumerable.Where()/enumerable.Remove()

Filter a collection using natural language

var smallItems = items.Where(model, "item would fit in a bread box");
var bigItems = items.Remove(model, "item would fit in a bread box");

enumerable.Select()

.Select() let's you transform the source into target using an ITransformer model.

You can use it to transform an object from one format to another by simply giving the types. The model will use AI to appropriately map the properties between the object types.

var targetItems = items.Select<SourceItem,TargetItem>(model)

Transform a collection of text into another format, like markdown.

var markdownItems = items.Select(model,	goal: """"
					transform each item into markdown like this:
					# {{TITLE}}
					{{AUTHOR}}
					{{DESCRIPTION}}
					""");

enumerable.Summarize()

Generate text summary for each item using an ITransformer model.

var summaries = items.Summarize(model);

You can control the summarization with a hint

var summaries = items.Summarize(model, "generate a 3 word summary");

enumerable.Answer()

This operator let's you ask a question for each item in a collection.

var answers = items.Answer<float>(model, "What is the cost?");

ITransformer

The ITransformer implements the core primatives for using AI to manipulate generation and transformation.

transformer.Generate()

Given a model and a goal return a shaped result.

var haiku = transformer.Generate<string>("write a haiku about camping");
var names = transformer.Generate<string[]>("funny names for people named bob");
var cities = transformer.Generate<City[]>("return the top 5 largest cities in the world.");

transformer.TransformItem()

Given a model and a goal return a shaped result.

var result = "my name is Tom".TransformItem<string>("translate to spanish);
// ==> "Me llamo Tom"

transformer.TransformItems()

Transform a collection of items using a model and a goal.

var items = new string[] {"Hello", "My name is Tom", "One more please"];
var results = items.TransformItems("translate to spanish);
// result[0] = "Hola"
// result[1] = "Me llamo Tom"
// result[2] = "Una mas, por favor"

Defining new operators

To create a custom operator you create an static class and define static methods for transforming an object or collection of objects.

For example, here is the implementation of Summarize():

• The SummarizeAsync() method defines object operator which calls TransformItemAsync with a default goal of "Create a summarization" with result type of string.
• The Summarize() method defines a collection operator which calls TransformItems with a default goal of "Create a summarization" with result type for each item in the collection of string.

    public static class SummarizeExtension
    {
        // operator to summarize object
        public static string Summarize(this object source, ChatClient model, string? goal, string? instructions = null, CancellationToken cancellationToken = default)
            => source.TransformItem<string>(model, goal ?? "create a summarization", instructions, cancellationToken);

        // operator to summarize object
        public static Task<string> SummarizeAsync(this object source, ChatClient model, string? goal, string? instructions = null, CancellationToken cancellationToken = default)
            => source.TransformItemAsync<string>(model, goal ?? "create a summarization", instructions, cancellationToken);

        // operator to summarize collection of objects
        public static IList<string> Summarize(this IEnumerable<object> source, ChatClient model, string? goal = null, string? instructions = null, int? maxParallel = null, CancellationToken cancellationToken = default)
            => source.TransformItems<string>(model, goal ?? "create a summarization", instructions, maxParallel, cancellationToken);
    }