Files
UniVerse/backend/UniVerse.Infrastructure/ExternalServices/LlmClient.cs
T

60 lines
2.3 KiB
C#

using System.Net.Http.Json;
using System.Text;
using System.Text.Json;
using Microsoft.Extensions.Configuration;
using Microsoft.Extensions.Logging;
using UniVerse.Application.Interfaces;
namespace UniVerse.Infrastructure.ExternalServices;
public class LlmClient : ILlmClient
{
private readonly HttpClient _http;
private readonly IConfiguration _config;
private readonly ILogger<LlmClient> _logger;
public LlmClient(HttpClient http, IConfiguration config, ILogger<LlmClient> logger)
{
_http = http; _config = config; _logger = logger;
}
public async Task<LlmReviewAnalysis> AnalyzeReviewAsync(string reviewText, string lectureContext)
{
var prompt = $"""
Analyze the following student review of a lecture. Return a JSON object with:
- quality_score: float 0-1 indicating review quality
- sentiment: "Positive", "Neutral", or "Negative"
- tags: array of relevant topic tags
- is_informative: boolean indicating if the review is informative
Lecture context: {lectureContext}
Review text: {reviewText}
""";
var request = new
{
model = _config["Llm:Model"] ?? "gpt-4o-mini",
messages = new[] { new { role = "user", content = prompt } },
temperature = 0.3,
response_format = new { type = "json_object" }
};
var apiKey = _config["Llm:ApiKey"] ?? "";
_http.DefaultRequestHeaders.Clear();
if (!string.IsNullOrEmpty(apiKey))
_http.DefaultRequestHeaders.Add("Authorization", $"Bearer {apiKey}");
var response = await _http.PostAsJsonAsync("chat/completions", request);
response.EnsureSuccessStatusCode();
var json = await response.Content.ReadFromJsonAsync<JsonElement>();
var content = json.GetProperty("choices")[0].GetProperty("message").GetProperty("content").GetString()!;
var analysis = JsonSerializer.Deserialize<LlmRawResponse>(content,
new JsonSerializerOptions { PropertyNameCaseInsensitive = true })!;
return new LlmReviewAnalysis(analysis.QualityScore, analysis.Sentiment, analysis.Tags, analysis.IsInformative);
}
private record LlmRawResponse(double QualityScore, string Sentiment, string[] Tags, bool IsInformative);
}