dramaling-vocab-learning/backend/DramaLing.Api/Services/AI/Gemini/GeminiClient.cs

using DramaLing.Api.Models.Configuration;
using Microsoft.Extensions.Options;
using System.Text.Json;
using System.Text;

namespace DramaLing.Api.Services.AI.Gemini;

/// <summary>
/// Gemini API HTTP 客戶端實作
/// </summary>
public class GeminiClient : IGeminiClient
{
    private readonly HttpClient _httpClient;
    private readonly ILogger<GeminiClient> _logger;
    private readonly GeminiOptions _options;

    public GeminiClient(
        HttpClient httpClient,
        IOptions<GeminiOptions> options,
        ILogger<GeminiClient> logger)
    {
        _httpClient = httpClient ?? throw new ArgumentNullException(nameof(httpClient));
        _logger = logger ?? throw new ArgumentNullException(nameof(logger));
        _options = options.Value ?? throw new ArgumentNullException(nameof(options));

        _logger.LogInformation("GeminiClient initialized with model: {Model}, timeout: {Timeout}s",
            _options.Model, _options.TimeoutSeconds);

        _httpClient.Timeout = TimeSpan.FromSeconds(_options.TimeoutSeconds);
        _httpClient.DefaultRequestHeaders.Add("User-Agent", "DramaLing/1.0");
    }

    public async Task<string> CallGeminiAPIAsync(string prompt)
    {
        try
        {
            var requestBody = new
            {
                contents = new[]
                {
                    new
                    {
                        parts = new[]
                        {
                            new { text = prompt }
                        }
                    }
                },
                generationConfig = new
                {
                    temperature = _options.Temperature,
                    topK = 40,
                    topP = 0.95,
                    maxOutputTokens = _options.MaxOutputTokens
                }
            };

            var json = JsonSerializer.Serialize(requestBody);
            var content = new StringContent(json, Encoding.UTF8, "application/json");

            var response = await _httpClient.PostAsync(
                $"{_options.BaseUrl}/v1beta/models/{_options.Model}:generateContent?key={_options.ApiKey}",
                content);

            response.EnsureSuccessStatusCode();

            var responseJson = await response.Content.ReadAsStringAsync();
            _logger.LogInformation("Raw Gemini API response: {Response}",
                responseJson.Substring(0, Math.Min(500, responseJson.Length)));

            return ExtractTextFromResponse(responseJson);
        }
        catch (Exception ex)
        {
            _logger.LogError(ex, "Gemini API call failed");
            throw;
        }
    }

    public async Task<bool> TestConnectionAsync()
    {
        try
        {
            await CallGeminiAPIAsync("Test connection");
            return true;
        }
        catch
        {
            return false;
        }
    }

    private string ExtractTextFromResponse(string responseJson)
    {
        using var document = JsonDocument.Parse(responseJson);
        var root = document.RootElement;

        string aiText = string.Empty;

        if (root.TryGetProperty("candidates", out var candidatesElement) &&
            candidatesElement.ValueKind == JsonValueKind.Array)
        {
            _logger.LogInformation("Found candidates array with {Count} items",
                candidatesElement.GetArrayLength());

            var firstCandidate = candidatesElement.EnumerateArray().FirstOrDefault();
            if (firstCandidate.ValueKind != JsonValueKind.Undefined)
            {
                if (firstCandidate.TryGetProperty("content", out var contentElement))
                {
                    if (contentElement.TryGetProperty("parts", out var partsElement) &&
                        partsElement.ValueKind == JsonValueKind.Array)
                    {
                        var firstPart = partsElement.EnumerateArray().FirstOrDefault();
                        if (firstPart.TryGetProperty("text", out var textElement))
                        {
                            aiText = textElement.GetString() ?? string.Empty;
                            _logger.LogInformation("Successfully extracted text: {Length} characters",
                                aiText.Length);
                        }
                    }
                }
            }
        }

        // 檢查是否有安全過濾
        if (root.TryGetProperty("promptFeedback", out var feedbackElement))
        {
            _logger.LogWarning("Gemini prompt feedback received: {Feedback}",
                feedbackElement.ToString());
        }

        _logger.LogInformation("Gemini API returned: {ResponseLength} characters", aiText.Length);
        if (!string.IsNullOrEmpty(aiText))
        {
            _logger.LogInformation("AI text preview: {Preview}",
                aiText.Substring(0, Math.Min(200, aiText.Length)));
        }

        // 如果沒有獲取到文本且有安全過濾回饋，返回友好訊息
        if (string.IsNullOrWhiteSpace(aiText) && root.TryGetProperty("promptFeedback", out _))
        {
            return "The content analysis is temporarily unavailable due to safety filtering. Please try with different content.";
        }

        return aiText;
    }
}