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Added embedding API (#654)
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Co-authored-by: Thorsten Sommer <SommerEngineering@users.noreply.github.com>
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@@ -0,0 +1,6 @@
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namespace AIStudio.Provider.Google;
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public sealed record GoogleEmbedding
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{
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public List<float>? Values { get; init; }
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}
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@@ -0,0 +1,30 @@
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using System.Text.Json;
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using System.Text.Json.Serialization;
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namespace AIStudio.Provider.Google;
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public sealed record GoogleEmbeddingResponse
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{
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[JsonConverter(typeof(GoogleEmbeddingListConverter))]
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public List<GoogleEmbedding>? Embedding { get; init; }
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private sealed class GoogleEmbeddingListConverter : JsonConverter<List<GoogleEmbedding>>
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{
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public override List<GoogleEmbedding> Read(ref Utf8JsonReader reader, Type typeToConvert, JsonSerializerOptions options)
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{
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if (reader.TokenType == JsonTokenType.StartObject)
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{
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var single = JsonSerializer.Deserialize<GoogleEmbedding>(ref reader, options);
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return single is null ? new() : new() { single };
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}
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if (reader.TokenType == JsonTokenType.StartArray)
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return JsonSerializer.Deserialize<List<GoogleEmbedding>>(ref reader, options) ?? new();
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throw new JsonException("Expected object or array for embedding.");
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}
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public override void Write(Utf8JsonWriter writer, List<GoogleEmbedding> value, JsonSerializerOptions options) =>
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JsonSerializer.Serialize(writer, value, options);
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}
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}
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@@ -87,6 +87,78 @@ public class ProviderGoogle() : BaseProvider(LLMProviders.GOOGLE, "https://gener
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{
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return Task.FromResult(string.Empty);
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}
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/// <inhertidoc />
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public override async Task<IReadOnlyList<IReadOnlyList<float>>> EmbedTextAsync(Model embeddingModel, SettingsManager settingsManager, CancellationToken token = default, params List<string> texts)
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{
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var requestedSecret = await RUST_SERVICE.GetAPIKey(this, SecretStoreType.EMBEDDING_PROVIDER);
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try
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{
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var modelName = embeddingModel.Id;
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if (string.IsNullOrWhiteSpace(modelName))
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{
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LOGGER.LogError("No model name provided for embedding request.");
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return [];
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}
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if (modelName.StartsWith("models/", StringComparison.OrdinalIgnoreCase))
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modelName = modelName.Substring("models/".Length);
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if (!requestedSecret.Success)
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{
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LOGGER.LogError("No valid API key available for embedding request.");
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return [];
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}
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// Prepare the Google Gemini embedding request:
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var payload = new
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{
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content = new
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{
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parts = texts.Select(text => new { text }).ToArray()
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},
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taskType = "SEMANTIC_SIMILARITY"
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};
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var embeddingRequest = JsonSerializer.Serialize(payload, JSON_SERIALIZER_OPTIONS);
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var embedUrl = $"https://generativelanguage.googleapis.com/v1beta/models/{modelName}:embedContent";
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using var request = new HttpRequestMessage(HttpMethod.Post, embedUrl);
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request.Headers.Add("x-goog-api-key", await requestedSecret.Secret.Decrypt(ENCRYPTION));
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// Set the content:
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request.Content = new StringContent(embeddingRequest, Encoding.UTF8, "application/json");
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using var response = await this.httpClient.SendAsync(request, token);
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var responseBody = await response.Content.ReadAsStringAsync(token);
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if (!response.IsSuccessStatusCode)
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{
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LOGGER.LogError("Embedding request failed with status code {ResponseStatusCode} and body: '{ResponseBody}'.", response.StatusCode, responseBody);
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return [];
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}
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var embeddingResponse = JsonSerializer.Deserialize<GoogleEmbeddingResponse>(responseBody, JSON_SERIALIZER_OPTIONS);
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if (embeddingResponse is { Embedding: not null })
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{
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return embeddingResponse.Embedding
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.Select(d => d.Values?.ToArray() ?? [])
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.Cast<IReadOnlyList<float>>()
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.ToArray();
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}
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else
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{
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LOGGER.LogError("Was not able to deserialize the embedding response.");
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return [];
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}
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}
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catch (Exception e)
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{
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LOGGER.LogError("Failed to perform embedding request: '{Message}'.", e.Message);
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return [];
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}
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}
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/// <inheritdoc />
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public override async Task<IEnumerable<Model>> GetTextModels(string? apiKeyProvisional = null, CancellationToken token = default)
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