feat: изменил логику анализа отзывов
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Frontend CI / build-and-check (push) Failing after 17m58s
🚀 Create and publish a Docker image / Build & publish frontend image (push) Failing after 10m11s
🚀 Create and publish a Docker image / Build & publish backend image (push) Failing after 11m3s
🚀 Create and publish a Docker image / Update stack on Portainer (push) Failing after 14m58s
Backend CI / build-and-test (push) Failing after 14m19s
🚀 Create and publish a Docker image / Detect changes in backend and frontend (push) Failing after 12m5s
Frontend CI / build-and-check (push) Failing after 17m58s
🚀 Create and publish a Docker image / Build & publish frontend image (push) Failing after 10m11s
🚀 Create and publish a Docker image / Build & publish backend image (push) Failing after 11m3s
🚀 Create and publish a Docker image / Update stack on Portainer (push) Failing after 14m58s
This commit is contained in:
@@ -0,0 +1,91 @@
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using Microsoft.EntityFrameworkCore;
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using Microsoft.Extensions.Logging.Abstractions;
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using NSubstitute;
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using UniVerse.Application.Interfaces;
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using UniVerse.Domain.Entities;
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using UniVerse.Domain.Enums;
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using UniVerse.Infrastructure.Data;
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using UniVerse.Infrastructure.Services;
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using Xunit;
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namespace UniVerse.Api.Tests.Reviews;
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public class LlmAnalysisServiceTests
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{
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[Fact]
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public async Task AnalyzeReviewAsync_SavesParsedAnalysisResult()
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{
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await using var db = CreateDbContext();
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await SeedPendingReviewAsync(db);
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var llm = Substitute.For<ILlmClient>();
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llm.AnalyzeReviewAsync(Arg.Any<string>(), Arg.Any<string>())
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.Returns(new LlmReviewAnalysis(
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0.76,
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"Положительный",
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["lecture structure", "practical examples"],
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true,
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"{\"quality_score\":0.76,\"sentiment\":\"Положительный\"}"));
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var gamification = Substitute.For<IGamificationService>();
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gamification.AwardCoinsAsync(
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Arg.Any<int>(),
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Arg.Any<int>(),
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Arg.Any<CoinTransactionType>(),
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Arg.Any<int?>(),
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Arg.Any<int?>(),
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Arg.Any<string?>())
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.Returns(Task.CompletedTask);
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gamification.CheckAndAwardAchievementsAsync(Arg.Any<int>()).Returns(Task.CompletedTask);
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var service = new LlmAnalysisService(db, llm, gamification, NullLogger<LlmAnalysisService>.Instance);
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await service.AnalyzeReviewAsync(1);
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var review = await db.Reviews.SingleAsync(r => r.Id == 1);
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Assert.Equal(ReviewLlmStatus.Analyzed, review.LlmStatus);
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Assert.Equal(ReviewSentiment.Positive, review.Sentiment);
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Assert.Equal(0.76, review.QualityScore);
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Assert.True(review.IsInformative);
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Assert.Equal(["lecture structure", "practical examples"], review.LlmTags!);
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Assert.Equal("{\"quality_score\":0.76,\"sentiment\":\"Положительный\"}", review.LlmRawOutput);
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await gamification.Received(1).AwardCoinsAsync(
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1,
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10,
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CoinTransactionType.ReviewReward,
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1,
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null,
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"Informative review reward");
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}
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private static async Task SeedPendingReviewAsync(AppDbContext db)
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{
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db.Users.Add(new User { Id = 1, Email = "student@test.local", DisplayName = "Student" });
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db.Courses.Add(new Course { Id = 1, Name = "Course" });
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db.Lectures.Add(new Lecture
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{
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Id = 1,
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CourseId = 1,
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Title = "Lecture",
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StartsAt = DateTime.UtcNow.AddDays(-1),
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EndsAt = DateTime.UtcNow.AddDays(-1).AddHours(2),
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IsOpen = true,
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MaxEnrollments = 30
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});
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db.Reviews.Add(new Review
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{
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Id = 1,
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LectureId = 1,
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UserId = 1,
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Rating = ReviewRating.Like,
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Text = "Useful review",
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LlmStatus = ReviewLlmStatus.Pending
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});
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await db.SaveChangesAsync();
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}
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private static AppDbContext CreateDbContext()
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{
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var options = new DbContextOptionsBuilder<AppDbContext>()
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.UseInMemoryDatabase($"LlmAnalysisServiceTests_{Guid.NewGuid()}")
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.Options;
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return new AppDbContext(options);
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}
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}
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