using System.Net.Http.Headers; using System.Runtime.CompilerServices; using System.Text; using System.Text.Json; using AIStudio.Chat; using AIStudio.Settings; namespace AIStudio.Provider.OpenAI; /// /// The OpenAI provider. /// public sealed class ProviderOpenAI() : BaseProvider(LLMProviders.OPEN_AI, "https://api.openai.com/v1/", LOGGER) { private static readonly ILogger LOGGER = Program.LOGGER_FACTORY.CreateLogger(); #region Implementation of IProvider /// public override string Id => LLMProviders.OPEN_AI.ToName(); /// public override string InstanceName { get; set; } = "OpenAI"; /// public override async IAsyncEnumerable StreamChatCompletion(Model chatModel, ChatThread chatThread, SettingsManager settingsManager, [EnumeratorCancellation] CancellationToken token = default) { // Get the API key: var requestedSecret = await RUST_SERVICE.GetAPIKey(this); if(!requestedSecret.Success) yield break; // Unfortunately, OpenAI changed the name of the system prompt based on the model. // All models that start with "o" (the omni aka reasoning models), all GPT4o models, // and all newer models have the system prompt named "developer". All other models // have the system prompt named "system". We need to check this to get the correct // system prompt. // // To complicate it even more: The early versions of reasoning models, which are released // before the 17th of December 2024, have no system prompt at all. We need to check this // as well. // Apply the basic rule first: var systemPromptRole = chatModel.Id.StartsWith('o') || chatModel.Id.StartsWith("gpt-5", StringComparison.Ordinal) || chatModel.Id.Contains("4o") ? "developer" : "system"; // Check if the model is an early version of the reasoning models: systemPromptRole = chatModel.Id switch { "o1-mini" => "user", "o1-mini-2024-09-12" => "user", "o1-preview" => "user", "o1-preview-2024-09-12" => "user", _ => systemPromptRole, }; // Read the model capabilities: var modelCapabilities = this.Provider.GetModelCapabilities(chatModel); // Check if we are using the Responses API or the Chat Completion API: var usingResponsesAPI = modelCapabilities.Contains(Capability.RESPONSES_API); // Prepare the request path based on the API we are using: var requestPath = usingResponsesAPI ? "responses" : "chat/completions"; LOGGER.LogInformation("Using the system prompt role '{SystemPromptRole}' and the '{RequestPath}' API for model '{ChatModelId}'.", systemPromptRole, requestPath, chatModel.Id); // Prepare the system prompt: var systemPrompt = new TextMessage { Role = systemPromptRole, Content = chatThread.PrepareSystemPrompt(settingsManager, chatThread), }; // // Prepare the tools we want to use: // IList tools = modelCapabilities.Contains(Capability.WEB_SEARCH) switch { true => [ Tools.WEB_SEARCH ], _ => [] }; // Parse the API parameters: var apiParameters = this.ParseAdditionalApiParameters("input", "store", "tools"); // Build the list of messages: var messages = await chatThread.Blocks.BuildMessagesAsync( this.Provider, chatModel, // OpenAI-specific role mapping: role => role switch { ChatRole.USER => "user", ChatRole.AI => "assistant", ChatRole.AGENT => "assistant", ChatRole.SYSTEM => systemPromptRole, _ => "user", }, // OpenAI's text sub-content depends on the model, whether we are using // the Responses API or the Chat Completion API: text => usingResponsesAPI switch { // Responses API uses INPUT_TEXT: true => new SubContentInputText { Text = text, }, // Chat Completion API uses TEXT: false => new SubContentText { Text = text, }, }, // OpenAI's image sub-content depends on the model as well, // whether we are using the Responses API or the Chat Completion API: async attachment => usingResponsesAPI switch { // Responses API uses INPUT_IMAGE: true => new SubContentInputImage { ImageUrl = await attachment.TryAsBase64(token: token) is (true, var base64Content) ? $"data:{attachment.DetermineMimeType()};base64,{base64Content}" : string.Empty, }, // Chat Completion API uses IMAGE_URL: false => new SubContentImageUrlNested { ImageUrl = new SubContentImageUrlData { Url = await attachment.TryAsBase64(token: token) is (true, var base64Content) ? $"data:{attachment.DetermineMimeType()};base64,{base64Content}" : string.Empty, }, } }); // // Create the request: either for the Responses API or the Chat Completion API // var openAIChatRequest = usingResponsesAPI switch { // Chat Completion API request: false => JsonSerializer.Serialize(new ChatCompletionAPIRequest { Model = chatModel.Id, // All messages go into the messages field: Messages = [systemPrompt, ..messages], // Right now, we only support streaming completions: Stream = true, AdditionalApiParameters = apiParameters }, JSON_SERIALIZER_OPTIONS), // Responses API request: true => JsonSerializer.Serialize(new ResponsesAPIRequest { Model = chatModel.Id, // All messages go into the input field: Input = [systemPrompt, ..messages], // Right now, we only support streaming completions: Stream = true, // We do not want to store any data on OpenAI's servers: Store = false, // Tools we want to use: Tools = tools, // Additional API parameters: AdditionalApiParameters = apiParameters }, JSON_SERIALIZER_OPTIONS), }; async Task RequestBuilder() { // Build the HTTP post request: var request = new HttpRequestMessage(HttpMethod.Post, requestPath); // Set the authorization header: request.Headers.Authorization = new AuthenticationHeaderValue("Bearer", await requestedSecret.Secret.Decrypt(ENCRYPTION)); // Set the content: request.Content = new StringContent(openAIChatRequest, Encoding.UTF8, "application/json"); return request; } if (usingResponsesAPI) await foreach (var content in this.StreamResponsesInternal("OpenAI", RequestBuilder, token)) yield return content; else await foreach (var content in this.StreamChatCompletionInternal("OpenAI", RequestBuilder, token)) yield return content; } #pragma warning disable CS1998 // Async method lacks 'await' operators and will run synchronously /// public override async IAsyncEnumerable StreamImageCompletion(Model imageModel, string promptPositive, string promptNegative = FilterOperator.String.Empty, ImageURL referenceImageURL = default, [EnumeratorCancellation] CancellationToken token = default) { yield break; } #pragma warning restore CS1998 // Async method lacks 'await' operators and will run synchronously /// public override async Task> GetTextModels(string? apiKeyProvisional = null, CancellationToken token = default) { var models = await this.LoadModels(["chatgpt-", "gpt-", "o1-", "o3-", "o4-"], token, apiKeyProvisional); return models.Where(model => !model.Id.Contains("image", StringComparison.OrdinalIgnoreCase) && !model.Id.Contains("realtime", StringComparison.OrdinalIgnoreCase) && !model.Id.Contains("audio", StringComparison.OrdinalIgnoreCase) && !model.Id.Contains("tts", StringComparison.OrdinalIgnoreCase) && !model.Id.Contains("transcribe", StringComparison.OrdinalIgnoreCase)); } /// public override Task> GetImageModels(string? apiKeyProvisional = null, CancellationToken token = default) { return this.LoadModels(["dall-e-", "gpt-image"], token, apiKeyProvisional); } /// public override Task> GetEmbeddingModels(string? apiKeyProvisional = null, CancellationToken token = default) { return this.LoadModels(["text-embedding-"], token, apiKeyProvisional); } /// public override async Task> GetTranscriptionModels(string? apiKeyProvisional = null, CancellationToken token = default) { var models = await this.LoadModels(["whisper-", "gpt-"], token, apiKeyProvisional); return models.Where(model => model.Id.StartsWith("whisper-", StringComparison.InvariantCultureIgnoreCase) || model.Id.Contains("-transcribe", StringComparison.InvariantCultureIgnoreCase)); } #endregion private async Task> LoadModels(string[] prefixes, CancellationToken token, string? apiKeyProvisional = null) { var secretKey = apiKeyProvisional switch { not null => apiKeyProvisional, _ => await RUST_SERVICE.GetAPIKey(this) switch { { Success: true } result => await result.Secret.Decrypt(ENCRYPTION), _ => null, } }; if (secretKey is null) return []; using var request = new HttpRequestMessage(HttpMethod.Get, "models"); request.Headers.Authorization = new AuthenticationHeaderValue("Bearer", secretKey); using var response = await this.httpClient.SendAsync(request, token); if(!response.IsSuccessStatusCode) return []; var modelResponse = await response.Content.ReadFromJsonAsync(token); return modelResponse.Data.Where(model => prefixes.Any(prefix => model.Id.StartsWith(prefix, StringComparison.InvariantCulture))); } }