LibreOpenAI 0.1.5

There is a newer version of this package available.
See the version list below for details.

The owner has unlisted this package. This could mean that the package is deprecated, has security vulnerabilities or shouldn't be used anymore.

dotnet add package LibreOpenAI --version 0.1.5

NuGet\Install-Package LibreOpenAI -Version 0.1.5

This command is intended to be used within the Package Manager Console in Visual Studio, as it uses the NuGet module's version of Install-Package.

<PackageReference Include="LibreOpenAI" Version="0.1.5" />

For projects that support PackageReference, copy this XML node into the project file to reference the package.

paket add LibreOpenAI --version 0.1.5

The NuGet Team does not provide support for this client. Please contact its maintainers for support.

#r "nuget: LibreOpenAI, 0.1.5"

#r directive can be used in F# Interactive and Polyglot Notebooks. Copy this into the interactive tool or source code of the script to reference the package.

// Install LibreOpenAI as a Cake Addin
#addin nuget:?package=LibreOpenAI&version=0.1.5

// Install LibreOpenAI as a Cake Tool
#tool nuget:?package=LibreOpenAI&version=0.1.5

The NuGet Team does not provide support for this client. Please contact its maintainers for support.

Libre-OpenAI (Beta)

An Open AI Nuget for .NET applications (.NET 8 or higher), It is "Libre" (free and for free). Remember, Libre-OpenAI and its Extensions are Beta versions, they are under construction!

You can download our Nuget from:

https://www.nuget.org/packages/LibreOpenAI/

Please, see these unit tests to learn how to use this Nuget:

https://github.com/maxiunlm/Libre-OpenAI/blob/main/LibreOpenAIUnitTestProject/OpenAiUnitTest.cs

And see the Libre OpenAI Extensions Nuget to learn how to use the extensions of the Libre Open AI Nuget:

https://github.com/maxiunlm/Libre-OpenAI/blob/main/LibreOpenAIExtensions/README.md

Support this project 💖

If you find this project useful, consider supporting us by making a donation via PayPal. Your support helps keep this project alive and maintained.

Donate to Libre-OpenAI (Beta):

Donate via QR Code

You can also scan the QR code below to make a donation:

QR Code

How to use Libre Open AI

Create Completions

Using IRequestBody

    IRequestBody request = new RequestBody
    {
        Model = defaultModel,
        MaxCompletionTokens = defaultMaxCompletionTokens,
        Messages = new List<MessageRequest> {
            new MessageRequest {
                Role = defaultRole,
                Content = "What is the capital of France?" // NOTE: complete here your request question
            }
        }
    };
    IOpenAI openAi = new OpenAI();

    IChatCompletionResponse result = await openAi.Chat.Completions.Create(request);
    string contentResult = result.Choices.First().Message.Content;

Using JSON

    string request = "{\"max_completion_tokens\":50,\"model\":\"gpt-3.5-turbo\",\"messages\":[{\"role\":\"user\",\"content\":\"What is the capital of France?\"}],\"n\":1}";
    IOpenAI openAi = new OpenAI();

    IChatCompletionResponse result = await openAi.Chat.Completions.Create(request);
    string contentResult = result.Choices.First().Message.Content;

Using dynamic type

    dynamic request = new {
        model = defaultModel,
        max_completion_tokens = defaultMaxCompletionTokens,
        messages = new[] {
            new {
                role = defaultRole,
                content = ResponseFakes.whatIsTheCapitalOfFrance
            }
        }
    };
    IOpenAI openAi = new OpenAI();

    IChatCompletionResponse result = await openAi.Chat.Completions.Create(request);
    string contentResult = result.Choices.First().Message.Content;

Returning dynamic

Using IRequestBody

    IRequestBody request = new RequestBody
    {
        Model = defaultModel,
        MaxCompletionTokens = defaultMaxCompletionTokens,
        Messages = new List<MessageRequest> {
            new MessageRequest {
                Role = defaultRole,
                Content = "What is the capital of France?" // NOTE: complete here your request question
            }
        }
    };
    IOpenAI openAi = new OpenAI();

    dynamic result = await openAi.Chat.Completions.CreateDynamic(request);

    // result will be a dynamic object based on the JSON result
    string content = result.choices[0].message.content.Value;

    // OR, result will be a IDictionary<string, object> object based on the JSON result
    ((IDictionary<string, object>)
        ((IDictionary<string, object>)
            ((IList<object>)result["choices"])[0])["message"])["content"];

Using JSON

    string request = "{\"max_completion_tokens\":50,\"model\":\"gpt-3.5-turbo\",\"messages\":[{\"role\":\"user\",\"content\":\"What is the capital of France?\"}],\"n\":1}";
    IOpenAI openAi = new OpenAI();

    dynamic result = await openAi.Chat.Completions.CreateDynamic(request);

    // result will be a dynamic object based on the JSON result
    string content = result.choices[0].message.content.Value;

    // OR, result will be a IDictionary<string, object> object based on the JSON result
    ((IDictionary<string, object>)
        ((IDictionary<string, object>)
            ((IList<object>)result["choices"])[0])["message"])["content"];

Using dynamic type

    dynamic request = new {
        model = defaultModel,
        max_completion_tokens = defaultMaxCompletionTokens,
        messages = new[] {
            new {
                role = defaultRole,
                content = ResponseFakes.whatIsTheCapitalOfFrance
            }
        }
    };
    IOpenAI openAi = new OpenAI();

    dynamic result = await openAi.Chat.Completions.CreateDynamic(request);

    // result will be a IDictionary<string, object> object based on the JSON result
    string content = result.choices[0].message.content.Value;

    // OR, result will be a IDictionary<string, object> object based on the JSON result
    ((IDictionary<string, object>)
        ((IDictionary<string, object>)
            ((IList<object>)result["choices"])[0])["message"])["content"];

Returning JSON

Using IRequestBody

    IRequestBody request = new RequestBody
    {
        Model = defaultModel,
        MaxCompletionTokens = defaultMaxCompletionTokens,
        Messages = new List<MessageRequest> {
            new MessageRequest {
                Role = defaultRole,
                Content = "What is the capital of France?" // NOTE: complete here your request question
            }
        }
    };
    IOpenAI openAi = new OpenAI();

    string result = await openAi.Chat.Completions.CreateJson(request);  
    // result will be a JSON

Using JSON

    string request = "{\"max_completion_tokens\":50,\"model\":\"gpt-3.5-turbo\",\"messages\":[{\"role\":\"user\",\"content\":\"What is the capital of France?\"}],\"n\":1}";
    IOpenAI openAi = new OpenAI();

    string result = await openAi.Chat.Completions.CreateJson(request);  
    // result will be a JSON

Using dynamic type

    dynamic request = new {
        model = defaultModel,
        max_completion_tokens = defaultMaxCompletionTokens,
        messages = new[] {
            new {
                role = defaultRole,
                content = ResponseFakes.whatIsTheCapitalOfFrance
            }
        }
    };
    IOpenAI openAi = new OpenAI();

    string result = await openAi.Chat.Completions.CreateJson(request);    
    // result will be a JSON

Create Stream Completions

Using IRequestBody

    IRequestBody request = new RequestBody
    {
        Model = "gpt-4o",
        Messages = new List<MessageRequest> {
            new MessageRequest {
                Role = "system",
                Content = "You are a helpful assistant." // NOTE: complete here your request question
            },
            new MessageRequest {
                Role = "user",
                Content = "Hello!" // NOTE: complete here your request question
            }
        },
        Stream = true
    };

    IOpenAI openAi = new OpenAI();
    
    List<IChatCompletionChunk> result = await sut.Chat.Completions.CreateStream(request);
    // For ex.: contentResult will contain all the result prats separated by "\t" (TAB character).
    string contentResult = string.Join('\t', result.SelectMany(o => o.Choices.Select(o => o.Delta.Content)).ToList());

Using JSON

    string request = "{\"max_completion_tokens\":50,\"model\":\"gpt-4o\",\"messages\":[{\"role\":\"user\",\"content\":\"What is the capital of France?\"}],\"n\":1}";
    IOpenAI openAi = new OpenAI();
    
    List<IChatCompletionChunk> result = await sut.Chat.Completions.CreateStream(request);
    // For ex.: contentResult will contain all the result prats separated by "\t" (TAB character).
    string contentResult = string.Join('\t', result.SelectMany(o => o.Choices.Select(o => o.Delta.Content)).ToList());

Using dynamic type

    dynamic request = new
    {
        model = "gpt-4o",
        messages = new[]
            {
                new { role = "system", content = "You are a helpful assistant." },
                new { role = "user", content = "Hello!" }
            },
        stream = true
    };
    IOpenAI openAi = new OpenAI();
    
    List<IChatCompletionChunk> result = await sut.Chat.Completions.CreateStream(request);
    // For ex.: contentResult will contain all the result prats separated by "\t" (TAB character).
    string contentResult = string.Join('\t', result.SelectMany(o => o.Choices.Select(o => o.Delta.Content)).ToList());

Returning dynamic

Using IRequestBody

    IRequestBody request = new RequestBody
    {
        Model = "gpt-4o",
        Messages = new List<MessageRequest> {
            new MessageRequest {
                Role = "system",
                Content = "You are a helpful assistant." // NOTE: complete here your request question
            },
            new MessageRequest {
                Role = "user",
                Content = "Hello!" // NOTE: complete here your request question
            }
        },
        Stream = true
    };

    IOpenAI openAi = new OpenAI();
    
    dynamic result = await sut.Chat.Completions.CreateStreamDynamic(request);  
    // result will be a dynamic array of objects based on the JSON result
    string content = result[1].choices[0].delta.content.Value;

Using JSON

    string request = "{\"max_completion_tokens\":50,\"model\":\"gpt-4o\",\"messages\":[{\"role\":\"user\",\"content\":\"What is the capital of France?\"}],\"n\":1}";
    IOpenAI openAi = new OpenAI();
    
    dynamic result = await sut.Chat.Completions.CreateStreamDynamic(request);
    // result will be a dynamic array of objects based on the JSON result
    string content = result[1].choices[0].delta.content.Value;

Using dynamic type

    dynamic request = new
    {
        model = "gpt-4o",
        messages = new[]
            {
                new { role = "system", content = "You are a helpful assistant." },
                new { role = "user", content = "Hello!" }
            },
        stream = true
    };
    IOpenAI openAi = new OpenAI();
    
    dynamic result = await sut.Chat.Completions.CreateStreamDynamic(request);
    // result will be a dynamic array of objects based on the JSON result
    string content = result[1].choices[0].delta.content.Value;

Returning JSON

Using IRequestBody

    IRequestBody request = new RequestBody
    {
        Model = "gpt-4o",
        Messages = new List<MessageRequest> {
            new MessageRequest {
                Role = "system",
                Content = "You are a helpful assistant." // NOTE: complete here your request question
            },
            new MessageRequest {
                Role = "user",
                Content = "Hello!" // NOTE: complete here your request question
            }
        },
        Stream = true
    };

    IOpenAI openAi = new OpenAI();
    
    string result = await sut.Chat.Completions.CreateStreamJson(request);
    // result will be a JSON array

Using JSON

    string request = "{\"max_completion_tokens\":50,\"model\":\"gpt-4o\",\"messages\":[{\"role\":\"user\",\"content\":\"What is the capital of France?\"}],\"n\":1}";
    IOpenAI openAi = new OpenAI();
    
    string result = await sut.Chat.Completions.CreateStreamJson(request);
    // result will be a JSON array

Using dynamic type

    dynamic request = new
    {
        model = "gpt-4o",
        messages = new[]
            {
                new { role = "system", content = "You are a helpful assistant." },
                new { role = "user", content = "Hello!" }
            },
        stream = true
    };
    IOpenAI openAi = new OpenAI();
    
    string result = await sut.Chat.Completions.CreateStreamJson(request);
    // result will be a JSON array

Expecting raw JSON

    string request = "{\"max_completion_tokens\":50,\"model\":\"gpt-4o\",\"messages\":[{\"role\":\"user\",\"content\":\"What is the capital of France?\"}],\"n\":1}";
    IOpenAI openAi = new OpenAI();
    
    string result = await sut.Chat.Completions.CreateStreamJson(request, true);

    // result will contain a list of "data: {...}" JSON objects that can't be parsed directly as JSON !

Batches

Create

Returning dynamic

Using JSON

    string request = @"{
        ""input_file_id"": ""file-abc123"",
        ""endpoint"": ""/v1/chat/completions"",
        ""completion_window"": ""24h""
    }";
    IOpenAI openAi = new OpenAI();

    dynamic result = await openAi.Batches.CreateDynamic(request);
    // result will be a dynamic object based on the JSON result
    string id = result.id.Value;

Using dynamic type

    dynamic request = new {
        input_file_id = "file-abc123",
        endpoint = "/v1/chat/completions",
        completion_window = "24h"
    };
    IOpenAI openAi = new OpenAI();

    dynamic result = await openAi.Batches.CreateDynamic(request);
    // result will be a dynamic object based on the JSON result
    string id = result.id.Value;

Returning JSON

Using JSON

    string request = @"{
        ""input_file_id"": ""file-abc123"",
        ""endpoint"": ""/v1/chat/completions"",
        ""completion_window"": ""24h""
    }";
    IOpenAI openAi = new OpenAI();

    string result = await openAi.Batches.CreateJson(request);
    // result will be a JSON

Using dynamic type

    dynamic request = new {
        input_file_id = "file-abc123",
        endpoint = "/v1/chat/completions",
        completion_window = "24h"
    };
    IOpenAI openAi = new OpenAI();

    string result = await openAi.Batches.CreateJson(request);
    // result will be a JSON

Retrieve

Returning dynamic

    string batchId = "batch_abc123";
    IOpenAI openAi = new OpenAI();

    dynamic result = await openAi.Batches.RetrieveDynamic(batchId);
    // result will be a dynamic object based on the JSON result
    string id = result.id.Value;

Returning JSON

    string batchId = "batch_abc123";
    IOpenAI openAi = new OpenAI();

    string result = await openAi.Batches.RetrieveJson(batchId);
    // result will be a JSON

Cancel

Returning dynamic

    string batchId = "batch_abc123";
    IOpenAI openAi = new OpenAI();

    dynamic result = await openAi.Batches.CancelDynamic(batchId);
    // result will be a dynamic object based on the JSON result
    string id = result.id.Value;

Returning JSON

    string batchId = "batch_abc123";
    IOpenAI openAi = new OpenAI();

    string result = await openAi.Batches.CancelJson(batchId);
    // result will be a JSON

List

Returning dynamic

    IOpenAI openAi = new OpenAI();

    dynamic result = await openAi.Batches.ListDynamic();
    // result will be a dynamic object based on the JSON result
    string id = result.id.Value;

Returning JSON

    IOpenAI openAi = new OpenAI();

    string result = await openAi.Batches.ListJson();
    // result will be a JSON

Create Embeddings

Returning dynamic

Using JSON

    string request = @"{
        model: ""text-embedding-ada-002"",
        input: ""The quick brown fox jumped over the lazy dog"",
        encoding_format: ""float"",
    }";
    IOpenAI openAi = new OpenAI();

    dynamic result = await openAi.Embeddings.CreateDynamic(request);
    // result will be a dynamic array of numbers based on the JSON result
    double first = result.data[0].embedding[0].Value;

Using dynamic type

    dynamic request = new {
        model = "text-embedding-ada-002",
        input = "The quick brown fox jumped over the lazy dog",
        encoding_format = "float",
    };
    IOpenAI openAi = new OpenAI();

    dynamic result = await openAi.Embeddings.CreateDynamic(request);
    // result will be a dynamic array of numbers based on the JSON result
    double first = result.data[0].embedding[0].Value;

Returning JSON

Using JSON

    string request = @"{
        model: ""text-embedding-ada-002"",
        input: ""The quick brown fox jumped over the lazy dog"",
        encoding_format: ""float"",
    }";
    IOpenAI openAi = new OpenAI();

    string result = await openAi.Embeddings.CreateJson(request);
    // result will be a JSON

Using dynamic type

    dynamic request = new {
        model = "text-embedding-ada-002",
        input = "The quick brown fox jumped over the lazy dog",
        encoding_format = "float",
    };
    IOpenAI openAi = new OpenAI();

    string result = await openAi.Embeddings.CreateJson(request);
    // result will be a JSON

Retrieve

Returning dynamic

    string fineTuningJobId = "ftjob-abc123";
    IOpenAI openAi = new OpenAI();

    dynamic result = await openAi.FineTuning.Jobs.RetrieveDynamic(fineTuningJobId);
    // result will be a dynamic object based on the JSON result
    string id = result.id.Value;

Returning JSON

    string fineTuningJobId = "ftjob-abc123";
    IOpenAI openAi = new OpenAI();

    string result = await openAi.FineTuning.Jobs.RetrieveJson(fineTuningJobId);
    // result will be a JSON

Cancel

Returning dynamic

    string fineTuningJobId = "ftjob-abc123";
    IOpenAI openAi = new OpenAI();

    dynamic result = await openAi.FineTuning.Jobs.CancelDynamic(fineTuningJobId);
    // result will be a dynamic object based on the JSON result
    string id = result.id.Value;

Returning JSON

    string fineTuningJobId = "ftjob-abc123";
    IOpenAI openAi = new OpenAI();

    string result = await openAi.FineTuning.Jobs.CancelJson(fineTuningJobId);
    // result will be a JSON

List

Returning dynamic

    IOpenAI openAi = new OpenAI();

    dynamic result = await openAi.FineTuning.Jobs.ListDynamic();
    // result will be a dynamic object based on the JSON result
    string type = result.data[0].type.Value;

Returning JSON

    IOpenAI openAi = new OpenAI();

    string result = await openAi.FineTuning.Jobs.ListJson();
    // result will be a JSON

List Events

Returning dynamic

    string fineTuningJobId = "ftjob-abc123";
    IOpenAI openAi = new OpenAI();

    dynamic result = await openAi.FineTuning.Jobs.ListEventsDynamic(fineTuningJobId);
    // result will be a dynamic object based on the JSON result
    string type = result.data[0].type.Value;

Returning JSON

    string fineTuningJobId = "ftjob-abc123";
    IOpenAI openAi = new OpenAI();

    string result = await openAi.FineTuning.Jobs.ListEventsJson(fineTuningJobId);
    // result will be a JSON

Fine-tuning - Jobs

Create

Returning dynamic

Using JSON

    string request = @"{
      ""object"": ""fine_tuning.job"",
      ""id"": ""ftjob-abc123"",
      ""model"": ""gpt-4o-mini-2024-07-18"",
      ""created_at"": 1721764800,
      ""fine_tuned_model"": null,
      ""organization_id"": ""org-123"",
      ""result_files"": [],
      ""status"": ""queued"",
      ""validation_file"": null,
      ""training_file"": ""file-abc123"",
      ""method"": {
        ""type"": ""supervised"",
        ""supervised"": {
          ""hyperparameters"": {
            ""batch_size"": ""auto"",
            ""learning_rate_multiplier"": ""auto"",
            ""n_epochs"": ""auto"",
          }
        }
      }
    }";
    IOpenAI openAi = new OpenAI();

    dynamic result = await openAi.FineTuning.Jobs.CreateDynamic(request);
    // result will be a dynamic object based on the JSON result
    string id = result.id.Value;;

Using dynamic type

    dynamic request = new {
      object = "fine_tuning.job",
      id = "ftjob-abc123",
      model = "gpt-4o-mini-2024-07-18",
      created_at = 1721764800,
      fine_tuned_model = null,
      organization_id = "org-123",
      result_files = new [],
      status = "queued",
      validation_file = null,
      training_file = "file-abc123",
      method = new {
        type = "supervised",
        supervised = new {
          hyperparameters = new {
            batch_size = "auto",
            learning_rate_multiplier = "auto",
            n_epochs = "auto",
          }
        }
      }
    };
    IOpenAI openAi = new OpenAI();

    dynamic result = await openAi.FineTuning.Jobs.CreateDynamic(request);
    // result will be a dynamic object based on the JSON result
    string id = result.id.Value;

Returning JSON

Using JSON

    string request = @"{
      ""object"": ""fine_tuning.job"",
      ""id"": ""ftjob-abc123"",
      ""model"": ""gpt-4o-mini-2024-07-18"",
      ""created_at"": 1721764800,
      ""fine_tuned_model"": null,
      ""organization_id"": ""org-123"",
      ""result_files"": [],
      ""status"": ""queued"",
      ""validation_file"": null,
      ""training_file"": ""file-abc123"",
      ""method"": {
        ""type"": ""supervised"",
        ""supervised"": {
          ""hyperparameters"": {
            ""batch_size"": ""auto"",
            ""learning_rate_multiplier"": ""auto"",
            ""n_epochs"": ""auto"",
          }
        }
      }
    }";
    IOpenAI openAi = new OpenAI();

    string result = await openAi.FineTuning.Jobs.CreateJson(request);
    // result will be a JSON

Using dynamic type

    dynamic request = new {
      object = "fine_tuning.job",
      id = "ftjob-abc123",
      model = "gpt-4o-mini-2024-07-18",
      created_at = 1721764800,
      fine_tuned_model = null,
      organization_id = "org-123",
      result_files = new [],
      status = "queued",
      validation_file = null,
      training_file = "file-abc123",
      method = new {
        type = "supervised",
        supervised = new {
          hyperparameters = new {
            batch_size = "auto",
            learning_rate_multiplier = "auto",
            n_epochs = "auto",
          }
        }
      }
    };
    IOpenAI openAi = new OpenAI();

    string result = await openAi.FineTuning.Jobs.CreateJson(request);
    // result will be a JSON

Support this project 💖

If you find this project useful, consider supporting us by making a donation via PayPal. Your support helps keep this project alive and maintained.

Donate to Libre-OpenAI (Beta):

Donate via QR Code

You can also scan the QR code below to make a donation:

QR Code

Product	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. net9.0 was computed. net9.0-android was computed. net9.0-browser was computed. net9.0-ios was computed. net9.0-maccatalyst was computed. net9.0-macos was computed. net9.0-tvos was computed. net9.0-windows was computed.

Product

.NET

Compatible target framework(s)

Included target framework(s) (in package)

Learn more about Target Frameworks and .NET Standard.

net8.0
- Microsoft.Extensions.Http (>= 9.0.0)
- Newtonsoft.Json (>= 13.0.3)
- System.Text.Json (>= 9.0.0)

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
0.1.6	73	1/17/2025
0.1.2	159	11/26/2024

LibreOpenAI 0.1.5

Libre-OpenAI (Beta)

Support this project 💖

Donate via QR Code

How to use Libre Open AI

Create Completions

Using IRequestBody

Using JSON

Using dynamic type

Returning dynamic

Using IRequestBody

Using JSON

Using dynamic type

Returning JSON

Using IRequestBody

Using JSON

Using dynamic type

Create Stream Completions

Using IRequestBody

Using JSON

Using dynamic type

Returning dynamic

Using IRequestBody

Using JSON

Using dynamic type

Returning JSON

Using IRequestBody

Using JSON

Using dynamic type

Expecting raw JSON

Batches

Create

Returning dynamic

Using JSON

Using dynamic type

Returning JSON

Using JSON

Using dynamic type

Retrieve

Returning dynamic

Returning JSON

Cancel

Returning dynamic

Returning JSON

List

Returning dynamic

Returning JSON

Create Embeddings

Returning dynamic

Using JSON

Using dynamic type

Returning JSON

Using JSON

Using dynamic type

Retrieve

Returning dynamic

Returning JSON

Cancel

Returning dynamic

Returning JSON

List

Returning dynamic

Returning JSON

List Events

Returning dynamic

Returning JSON

Fine-tuning - Jobs

Create

Returning dynamic

Using JSON

Using dynamic type

Returning JSON

Using JSON

Using dynamic type

Support this project 💖

Donate via QR Code

net8.0

NuGet packages

GitHub repositories