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add models of Gemini 1.5 and Gemini 1.0 Ultra
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,238 @@ | ||
| #if NET472_OR_GREATER || NETSTANDARD2_0 | ||
| using System; | ||
| using System.Collections.Generic; | ||
| using System.IO; | ||
| using System.Linq; | ||
| #endif | ||
| using FluentAssertions; | ||
| using Mscc.GenerativeAI; | ||
| using Xunit; | ||
| using Xunit.Abstractions; | ||
|
|
||
| namespace Test.Mscc.GenerativeAI | ||
| { | ||
| [Collection(nameof(ConfigurationFixture))] | ||
| public class GoogleAi_Gemini15Pro_Should | ||
| { | ||
| private readonly ITestOutputHelper output; | ||
| private readonly ConfigurationFixture fixture; | ||
| private readonly string model = Model.Gemini15Pro; | ||
|
|
||
| public GoogleAi_Gemini15Pro_Should(ITestOutputHelper output, ConfigurationFixture fixture) | ||
| { | ||
| this.output = output; | ||
| this.fixture = fixture; | ||
| } | ||
|
|
||
| [Fact] | ||
| public void Initialize_Gemini15Pro() | ||
| { | ||
| // Arrange | ||
|
|
||
| // Act | ||
| var model = new GenerativeModel(apiKey: fixture.ApiKey, model: this.model); | ||
|
|
||
| // Assert | ||
| model.Should().NotBeNull(); | ||
| model.Name.Should().Be(Model.Gemini15Pro.SanitizeModelName()); | ||
| } | ||
|
|
||
| [Fact] | ||
| public async void Generate_Text_From_Image() | ||
| { | ||
| // Arrange | ||
| var model = new GenerativeModel(apiKey: fixture.ApiKey, model: this.model); | ||
| var request = new GenerateContentRequest { Contents = new List<Content>() }; | ||
| var base64image = "iVBORw0KGgoAAAANSUhEUgAAAAEAAAABCAYAAAAfFcSJAAAADUlEQVR42mP8z8BQDwAEhQGAhKmMIQAAAABJRU5ErkJggg=="; | ||
| var parts = new List<IPart> | ||
| { | ||
| new TextData { Text = "What is this picture about?" }, | ||
| new InlineData { MimeType = "image/jpeg", Data = base64image } | ||
| }; | ||
| request.Contents.Add(new Content { Role = Role.User, Parts = parts }); | ||
|
|
||
| // Act | ||
| var response = await model.GenerateContent(request); | ||
|
|
||
| // Assert | ||
| response.Should().NotBeNull(); | ||
| response.Candidates.Should().NotBeNull().And.HaveCount(1); | ||
| response.Candidates.FirstOrDefault().Content.Should().NotBeNull(); | ||
| response.Candidates.FirstOrDefault().Content.Parts.Should().NotBeNull().And.HaveCountGreaterThanOrEqualTo(1); | ||
| response.Text.Should().Contain("red"); | ||
| output.WriteLine(response?.Text); | ||
| } | ||
|
|
||
| [Fact] | ||
| public async void Describe_Image_From_InlineData() | ||
| { | ||
| // Arrange | ||
| var prompt = "Parse the time and city from the airport board shown in this image into a list, in Markdown"; | ||
| var model = new GenerativeModel(apiKey: fixture.ApiKey, model: this.model); | ||
| // Images | ||
| var board = await TestExtensions.ReadImageFileBase64Async("https://ai.google.dev/static/docs/images/timetable.png"); | ||
| var request = new GenerateContentRequest(prompt); | ||
| request.Contents[0].Parts.Add( | ||
| new InlineData { MimeType = "image/png", Data = board } | ||
| ); | ||
|
|
||
| // Act | ||
| var response = await model.GenerateContent(request); | ||
|
|
||
| // Assert | ||
| response.Should().NotBeNull(); | ||
| response.Candidates.Should().NotBeNull().And.HaveCount(1); | ||
| response.Candidates.FirstOrDefault().Content.Should().NotBeNull(); | ||
| response.Candidates.FirstOrDefault().Content.Parts.Should().NotBeNull().And.HaveCountGreaterThanOrEqualTo(1); | ||
| output.WriteLine(response?.Text); | ||
| } | ||
|
|
||
| [Theory] | ||
| [InlineData("scones.jpg", "image/jpeg", "What is this picture?", "blueberries")] | ||
| [InlineData("cat.jpg", "image/jpeg", "Describe this image", "snow")] | ||
| [InlineData("cat.jpg", "image/jpeg", "Is it a cat?", "Yes")] | ||
| //[InlineData("animals.mp4", "video/mp4", "What's in the video?", "Zootopia")] | ||
| public async void Generate_Text_From_ImageFile(string filename, string mimetype, string prompt, string expected) | ||
| { | ||
| // Arrange | ||
| var model = new GenerativeModel(apiKey: fixture.ApiKey, model: this.model); | ||
| var base64image = Convert.ToBase64String(File.ReadAllBytes(Path.Combine(Environment.CurrentDirectory, "payload", filename))); | ||
| var parts = new List<IPart> | ||
| { | ||
| new TextData { Text = prompt }, | ||
| new InlineData { MimeType = mimetype, Data = base64image } | ||
| }; | ||
| var generationConfig = new GenerationConfig() | ||
| { | ||
| Temperature = 0.4f, TopP = 1, TopK = 32, MaxOutputTokens = 1024 | ||
| }; | ||
|
|
||
| // Act | ||
| var response = await model.GenerateContent(parts, generationConfig); | ||
|
|
||
| // Assert | ||
| response.Should().NotBeNull(); | ||
| response.Candidates.Should().NotBeNull().And.HaveCount(1); | ||
| response.Candidates.FirstOrDefault().Content.Should().NotBeNull(); | ||
| response.Candidates.FirstOrDefault().Content.Parts.Should().NotBeNull().And.HaveCountGreaterThanOrEqualTo(1); | ||
| response.Text.Should().Contain(expected); | ||
| output.WriteLine(response?.Text); | ||
| } | ||
|
|
||
| [Theory] | ||
| [InlineData("scones.jpg", "What is this picture?", "blueberries")] | ||
| [InlineData("cat.jpg", "Describe this image", "snow")] | ||
| [InlineData("cat.jpg", "Is it a feline?", "Yes")] | ||
| //[InlineData("animals.mp4", "video/mp4", "What's in the video?", "Zootopia")] | ||
| public async void Describe_AddMedia_From_ImageFile(string filename, string prompt, string expected) | ||
| { | ||
| // Arrange | ||
| var model = new GenerativeModel(apiKey: fixture.ApiKey, model: this.model); | ||
| var request = new GenerateContentRequest(prompt) | ||
| { | ||
| GenerationConfig = new GenerationConfig() | ||
| { | ||
| Temperature = 0.4f, TopP = 1, TopK = 32, MaxOutputTokens = 1024 | ||
| } | ||
| }; | ||
| request.AddMedia(Path.Combine(Environment.CurrentDirectory, "payload", filename)); | ||
|
|
||
| // Act | ||
| var response = await model.GenerateContent(request); | ||
|
|
||
| // Assert | ||
| response.Should().NotBeNull(); | ||
| response.Candidates.Should().NotBeNull().And.HaveCount(1); | ||
| response.Candidates.FirstOrDefault().Content.Should().NotBeNull(); | ||
| response.Candidates.FirstOrDefault().Content.Parts.Should().NotBeNull().And.HaveCountGreaterThanOrEqualTo(1); | ||
| response.Text.Should().Contain(expected); | ||
| output.WriteLine(response?.Text); | ||
| } | ||
|
|
||
| [Fact] | ||
| public async void Describe_AddMedia_From_Url() | ||
| { | ||
| // Arrange | ||
| var prompt = "Parse the time and city from the airport board shown in this image into a list, in Markdown"; | ||
| var model = new GenerativeModel(apiKey: fixture.ApiKey, model: this.model); | ||
| var request = new GenerateContentRequest(prompt); | ||
| await request.AddMedia("https://ai.google.dev/static/docs/images/timetable.png"); | ||
|
|
||
| // Act | ||
| var response = await model.GenerateContent(request); | ||
|
|
||
| // Assert | ||
| response.Should().NotBeNull(); | ||
| response.Candidates.Should().NotBeNull().And.HaveCount(1); | ||
| response.Candidates.FirstOrDefault().Content.Should().NotBeNull(); | ||
| response.Candidates.FirstOrDefault().Content.Parts.Should().NotBeNull().And.HaveCountGreaterThanOrEqualTo(1); | ||
| output.WriteLine(response?.Text); | ||
| } | ||
|
|
||
| [Fact] | ||
| public async void Describe_AddMedia_From_UrlRemote() | ||
| { | ||
| // Arrange | ||
| var prompt = "Parse the time and city from the airport board shown in this image into a list, in Markdown"; | ||
| var model = new GenerativeModel(apiKey: fixture.ApiKey, model: this.model); | ||
| var request = new GenerateContentRequest(prompt); | ||
| await request.AddMedia("https://ai.google.dev/static/docs/images/timetable.png", true); | ||
|
|
||
| // Act | ||
| var response = await model.GenerateContent(request); | ||
|
|
||
| // Assert | ||
| response.Should().NotBeNull(); | ||
| response.Candidates.Should().NotBeNull().And.HaveCount(1); | ||
| response.Candidates.FirstOrDefault().Content.Should().NotBeNull(); | ||
| response.Candidates.FirstOrDefault().Content.Parts.Should().NotBeNull().And.HaveCountGreaterThanOrEqualTo(1); | ||
| output.WriteLine(response?.Text); | ||
| } | ||
|
|
||
| [Fact(Skip = "Bad Request due to FileData part")] | ||
| public async void Describe_Image_From_FileData() | ||
| { | ||
| // Arrange | ||
| var prompt = "Parse the time and city from the airport board shown in this image into a list, in Markdown"; | ||
| var model = new GenerativeModel(apiKey: fixture.ApiKey, model: this.model); | ||
| var request = new GenerateContentRequest(prompt); | ||
| request.Contents[0].Parts.Add(new FileData | ||
| { | ||
| FileUri = "https://ai.google.dev/static/docs/images/timetable.png", | ||
| MimeType = "image/png" | ||
| }); | ||
|
|
||
| // Act | ||
| var response = await model.GenerateContent(request); | ||
|
|
||
| // Assert | ||
| response.Should().NotBeNull(); | ||
| response.Candidates.Should().NotBeNull().And.HaveCount(1); | ||
| response.Candidates.FirstOrDefault().Content.Should().NotBeNull(); | ||
| response.Candidates.FirstOrDefault().Content.Parts.Should().NotBeNull().And.HaveCountGreaterThanOrEqualTo(1); | ||
| output.WriteLine(response?.Text); | ||
| } | ||
|
|
||
| [Fact(Skip = "URL scheme not supported")] | ||
| public async void Multimodal_Video_Input() | ||
| { | ||
| // Arrange | ||
| var model = new GenerativeModel(apiKey: fixture.ApiKey, model: this.model); | ||
| var video = await TestExtensions.ReadImageFileBase64Async("gs://cloud-samples-data/video/animals.mp4"); | ||
| var request = new GenerateContentRequest("What's in the video?"); | ||
| request.Contents[0].Role = Role.User; | ||
| request.Contents[0].Parts.Add(new InlineData { MimeType = "video/mp4", Data = video }); | ||
|
|
||
| // Act | ||
| var response = await model.GenerateContent(request); | ||
|
|
||
| // Assert | ||
| response.Should().NotBeNull(); | ||
| response.Candidates.Should().NotBeNull().And.HaveCount(1); | ||
| response.Candidates.FirstOrDefault().Content.Should().NotBeNull(); | ||
| response.Candidates.FirstOrDefault().Content.Parts.Should().NotBeNull().And.HaveCountGreaterThanOrEqualTo(1); | ||
| response.Text.Should().Contain("Zootopia"); | ||
| output.WriteLine(response?.Text); | ||
| } | ||
| } | ||
| } |
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