Linq.AI.OpenAI
2.0.2
See the version list below for details.
dotnet add package Linq.AI.OpenAI --version 2.0.2
NuGet\Install-Package Linq.AI.OpenAI -Version 2.0.2
<PackageReference Include="Linq.AI.OpenAI" Version="2.0.2" />
paket add Linq.AI.OpenAI --version 2.0.2
#r "nuget: Linq.AI.OpenAI, 2.0.2"
// Install Linq.AI.OpenAI as a Cake Addin #addin nuget:?package=Linq.AI.OpenAI&version=2.0.2 // Install Linq.AI.OpenAI as a Cake Tool #tool nuget:?package=Linq.AI.OpenAI&version=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.).
Extension | Description |
---|---|
.Classify()/.ClassifyAsync() | classify the text using a model. |
.Summarize()/.SummarizeAsync() | Create a summarization for the text by using a model. |
.Matches()/.MatchesAsync() | Return whether the text matches using a model. |
.Answer()/.AnswerAsync() | get the answer to a question from the text using a model. |
.Select()/.SelectAsync() | Select a collection of items from the text using a model. |
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.
Extension | Description |
---|---|
.Select() | Transforms each item into another format with natural language. |
.Where() | Keeps each item which matches with natural language filter. |
.Remove() | Remove each item which matches a natural language filter. |
.Summarize() | Create a summarization for each item. |
.Classify() | Classify each item. |
.Answer() | Answers the question for each item. |
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.
Extension | Description |
---|---|
.Generate()/.GenerateAsync() | use a model and a goal to return a shaped result. |
.TransformItem()/.TransformItemAsync() | use a model and a goal to transform an item into a shaped result. |
.TransformItems() | use a model and a goal to transform a collection of items into a collection of shaped results. |
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);
}
Product | Versions Compatible and additional computed target framework versions. |
---|---|
.NET | net8.0 is compatible. net8.0-android was computed. net8.0-browser was computed. net8.0-ios was computed. net8.0-maccatalyst was computed. net8.0-macos was computed. net8.0-tvos was computed. net8.0-windows was computed. |
NuGet packages
This package is not used by any NuGet packages.
GitHub repositories
This package is not used by any popular GitHub repositories.
Version | Downloads | Last updated |
---|---|---|
2.2.1 | 48 | 12/16/2024 |
2.2.0 | 68 | 10/15/2024 |
2.1.0 | 60 | 10/11/2024 |
2.0.6 | 96 | 9/15/2024 |
2.0.5 | 72 | 9/14/2024 |
2.0.4 | 87 | 9/14/2024 |
2.0.3 | 60 | 9/14/2024 |
2.0.2 | 62 | 9/14/2024 |
2.0.1 | 73 | 9/14/2024 |
1.3.0 | 65 | 9/14/2024 |
1.2.3 | 64 | 9/13/2024 |
1.2.2 | 65 | 9/12/2024 |
1.2.1 | 74 | 9/12/2024 |
1.2.0 | 64 | 9/11/2024 |
1.1.0 | 66 | 9/11/2024 |
1.0.1 | 65 | 9/11/2024 |
1.0.0 | 66 | 9/11/2024 |