Linq.AI.OpenAI
1.2.1
See the version list below for details.
dotnet add package Linq.AI.OpenAI --version 1.2.1
NuGet\Install-Package Linq.AI.OpenAI -Version 1.2.1
<PackageReference Include="Linq.AI.OpenAI" Version="1.2.1" />
paket add Linq.AI.OpenAI --version 1.2.1
#r "nuget: Linq.AI.OpenAI, 1.2.1"
// Install Linq.AI.OpenAI as a Cake Addin #addin nuget:?package=Linq.AI.OpenAI&version=1.2.1 // Install Linq.AI.OpenAI as a Cake Tool #tool nuget:?package=Linq.AI.OpenAI&version=1.2.1
Linq.AI.OpenAI
This library adds Linq extension methods using OpenAI structured outputs.
This library was heaviy inspired by stevenic's agentm-js library, Kudos!
Installation
dotnet add package Linq.AI.OpenAI
Architecture
For each element in a collection an model API call is made to evaluate and return the result. These are done in parallel on background threads.
OpenAI model
To use these methods you will need to instantiate a ChatClient model like this:
var model = new ChatClient(model: "gpt-4o-mini", "<modelKey>");
NOTE: The model must support structured output.
String Extensions
These extensions use an OpenAI model to work with text.
Extension | Description |
---|---|
.ClassifyAsync() | classify the text using a model. |
.SummarizeAsync() | Create a summarization for the text by using a model. |
.MatchesAsync() | Return whether the text matches using a model. |
.AnswerAsync() | get the answer to a question from the text using a model. |
.SelectAsync() | Generate a collection of items from the text using a model. |
Examples
.Classify() text
enum Genres { Rock, Pop, Electronica, Country, Classical };
var classification = await text.ClassifyAsync<Genres>(model);
.Summarize() text
var summary = await text.SummarizeAsync(model, "with 3 words");
.Matches() text
if (await text.MatchesAsync(model, "there is date"))
...
.Answer() text
var summary = await text.AnswerAsync(model, "what is the birthday?");
.Select() text
Example using model to select
var words = await text.SelectAsync<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 = await text.SelectAsync<HREF>(model);
Collection Extensions
These collection extensions use an OpenAI model to work with collections using Linq style methods.
Extension | Description |
---|---|
.Where() | Filter the collection of items by using a model. filter |
.Select() | transform the item into another format using a model. |
.Remove() | Remove items from a collection of items by using a model. filter |
.Summarize() | Create a summarization for each item by using a model. |
.Classify() | classify each item using a model. |
.Answer() | get the answer to a question for each item using a model. |
NOTE: These methods are synchronous linq methods, but internally they run all of the AI calls as throttled parallel background tasks.
Examples
.Classify() items
This allows you to classify each item using a model;
enum Genres { Rock, Pop, Electronica, Country, Classical };
var classifiedItems = items.Classify<Genres>(model);
.Where()/.Remove() items
Filter a collection using natural language
var breadboxItems = items.Where(model, "item would fit in a bread box");
var bigItems = items.Remove(model, "item would fit in a bread box");
.Select() items
.Select() let's you transform the source into target using an OpenAI model.
Object transformation
You can use it to transform an object from one format to another by simply giving the types. It will use model. to do the transformation.
var targetItems = items.Select<SourceItem,TargetItem>(model)
String transformation
var markdownItems = items.Select(model, "transform each item into markdown like this:\n# {{TITLE}}\n{{AUTHOR}}\n{{Description}}")
.Summarize() items
Generate text summary for each item using an OpenAI model.
var summaries = items.Summarize(model);
You can control the summarization with a hint
var summaries = items.Summarize(model, "generate a 3 word summary");
.Answer() items
This operator let's you ask a question for each item in a collection.
var answers = items.Answer(model, "What is total cost of the item as a float?").Select(answer => Convert.ToFloat(answer));
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. |
-
net8.0
- Iciclecreek.Async (>= 2.0.0)
- Newtonsoft.Json (>= 13.0.3)
- OpenAI (>= 2.0.0-beta.11)
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 |
---|---|---|
2.2.0 | 51 | 10/15/2024 |
2.1.0 | 47 | 10/11/2024 |
2.0.6 | 83 | 9/15/2024 |
2.0.5 | 62 | 9/14/2024 |
2.0.4 | 78 | 9/14/2024 |
2.0.3 | 51 | 9/14/2024 |
2.0.2 | 51 | 9/14/2024 |
2.0.1 | 64 | 9/14/2024 |
1.3.0 | 54 | 9/14/2024 |
1.2.3 | 53 | 9/13/2024 |
1.2.2 | 56 | 9/12/2024 |
1.2.1 | 62 | 9/12/2024 |
1.2.0 | 55 | 9/11/2024 |
1.1.0 | 57 | 9/11/2024 |
1.0.1 | 56 | 9/11/2024 |
1.0.0 | 57 | 9/11/2024 |