ChatEndpoint.cs

using OpenAI_API.Models;
using System;
using System.Collections.Generic;
using System.Linq;
using System.Net.Http;
using System.Text;
using System.Threading.Tasks;

namespace OpenAI_API.Chat
{
	/// <summary>
	/// ChatGPT API endpoint. Use this endpoint to send multiple messages and carry on a conversation.
	/// </summary>
	public class ChatEndpoint : EndpointBase, IChatEndpoint
	{
		/// <summary>
		/// This allows you to set default parameters for every request, for example to set a default temperature or max tokens.  For every request, if you do not have a parameter set on the request but do have it set here as a default, the request will automatically pick up the default value.
		/// </summary>
		public ChatRequest DefaultChatRequestArgs { get; set; } = new ChatRequest() { Model = Model.ChatGPTTurbo };

		/// <summary>
		/// The name of the endpoint, which is the final path segment in the API URL.  For example, "completions".
		/// </summary>
		protected override string Endpoint { get { return "chat/completions"; } }

		/// <summary>
		/// Constructor of the api endpoint.  Rather than instantiating this yourself, access it through an instance of <see cref="OpenAIAPI"/> as <see cref="OpenAIAPI.Completions"/>.
		/// </summary>
		/// <param name="api"></param>
		internal ChatEndpoint(OpenAIAPI api) : base(api) { }

		/// <summary>
		/// Constructor of the api endpoint.  Rather than instantiating this yourself, access it through an instance of <see cref="OpenAIAPI"/> as <see cref="OpenAIAPI.Completions"/>.
		/// </summary>
		/// <param name="httpClient"></param>
		/// <param name="api"></param>
		internal ChatEndpoint(HttpClient httpClient, OpenAIAPI api) : base(api) { }

		/// <summary>
		/// Creates an ongoing chat which can easily encapsulate the conversation.  This is the simplest way to use the Chat endpoint.
		/// </summary>
		/// <returns></returns>
		public Conversation CreateConversation()
		{
			return new Conversation(this, defaultChatRequestArgs: DefaultChatRequestArgs);
		}

		#region Non-streaming

		/// <summary>
		/// Ask the API to complete the request using the specified parameters. This is non-streaming, so it will wait until the API returns the full result. Any non-specified parameters will fall back to default values specified in <see cref="DefaultChatRequestArgs"/> if present.
		/// </summary>
		/// <param name="request">The request to send to the API.</param>
		/// <returns>Asynchronously returns the completion result. Look in its <see cref="ChatResult.Choices"/> property for the results.</returns>
		public async Task<ChatResult> CreateChatCompletionAsync(ChatRequest request)
		{
			return await HttpPost<ChatResult>(postData: request);
		}

		/// <summary>
		/// Ask the API to complete the request using the specified parameters. This is non-streaming, so it will wait until the API returns the full result. Any non-specified parameters will fall back to default values specified in <see cref="DefaultChatRequestArgs"/> if present.
		/// </summary>
		/// <param name="request">The request to send to the API.</param>
		/// <param name="numOutputs">Overrides <see cref="ChatRequest.NumChoicesPerMessage"/> as a convenience.</param>
		/// <returns>Asynchronously returns the completion result. Look in its <see cref="ChatResult.Choices"/> property for the results.</returns>
		public Task<ChatResult> CreateChatCompletionAsync(ChatRequest request, int numOutputs = 5)
		{
			request.NumChoicesPerMessage = numOutputs;
			return CreateChatCompletionAsync(request);
		}

		/// <summary>
		/// Ask the API to complete the request using the specified parameters. This is non-streaming, so it will wait until the API returns the full result. Any non-specified parameters will fall back to default values specified in <see cref="DefaultChatRequestArgs"/> if present.
		/// </summary>
		/// <param name="messages">The array of messages to send to the API</param>
		/// <param name="model">The model to use. See the ChatGPT models available from <see cref="ModelsEndpoint.GetModelsAsync()"/></param>
		/// <param name="temperature">What sampling temperature to use. Higher values means the model will take more risks. Try 0.9 for more creative applications, and 0 (argmax sampling) for ones with a well-defined answer. It is generally recommend to use this or <paramref name="top_p"/> but not both.</param>
		/// <param name="top_p">An alternative to sampling with temperature, called nucleus sampling, where the model considers the results of the tokens with top_p probability mass. So 0.1 means only the tokens comprising the top 10% probability mass are considered. It is generally recommend to use this or <paramref name="temperature"/> but not both.</param>
		/// <param name="numOutputs">How many different choices to request for each prompt.</param>
		/// <param name="max_tokens">How many tokens to complete to. Can return fewer if a stop sequence is hit.</param>
		/// <param name="frequencyPenalty">The scale of the penalty for how often a token is used.  Should generally be between 0 and 1, although negative numbers are allowed to encourage token reuse.</param>
		/// <param name="presencePenalty">The scale of the penalty applied if a token is already present at all.  Should generally be between 0 and 1, although negative numbers are allowed to encourage token reuse.</param>
		/// <param name="logitBias">Maps tokens (specified by their token ID in the tokenizer) to an associated bias value from -100 to 100. Mathematically, the bias is added to the logits generated by the model prior to sampling. The exact effect will vary per model, but values between -1 and 1 should decrease or increase likelihood of selection; values like -100 or 100 should result in a ban or exclusive selection of the relevant token.</param>
		/// <param name="stopSequences">One or more sequences where the API will stop generating further tokens. The returned text will not contain the stop sequence.</param>
		/// <returns>Asynchronously returns the completion result. Look in its <see cref="ChatResult.Choices"/> property for the results.</returns>
		public Task<ChatResult> CreateChatCompletionAsync(IList<ChatMessage> messages,
			Model model = null,
			double? temperature = null,
			double? top_p = null,
			int? numOutputs = null,
			int? max_tokens = null,
			double? frequencyPenalty = null,
			double? presencePenalty = null,
			IReadOnlyDictionary<string, float> logitBias = null,
			params string[] stopSequences)
		{
			ChatRequest request = new ChatRequest(DefaultChatRequestArgs)
			{
				Messages = messages,
				Model = model ?? DefaultChatRequestArgs.Model,
				Temperature = temperature ?? DefaultChatRequestArgs.Temperature,
				TopP = top_p ?? DefaultChatRequestArgs.TopP,
				NumChoicesPerMessage = numOutputs ?? DefaultChatRequestArgs.NumChoicesPerMessage,
				MultipleStopSequences = stopSequences ?? DefaultChatRequestArgs.MultipleStopSequences,
				MaxTokens = max_tokens ?? DefaultChatRequestArgs.MaxTokens,
				FrequencyPenalty = frequencyPenalty ?? DefaultChatRequestArgs.FrequencyPenalty,
				PresencePenalty = presencePenalty ?? DefaultChatRequestArgs.PresencePenalty,
				LogitBias = logitBias ?? DefaultChatRequestArgs.LogitBias
			};
			return CreateChatCompletionAsync(request);
		}

		/// <summary>
		/// Ask the API to complete the request using the specified message(s).  Any parameters will fall back to default values specified in <see cref="DefaultChatRequestArgs"/> if present.
		/// </summary>
		/// <param name="messages">The messages to use in the generation.</param>
		/// <returns>The <see cref="ChatResult"/> with the API response.</returns>
		public Task<ChatResult> CreateChatCompletionAsync(params ChatMessage[] messages)
		{
			ChatRequest request = new ChatRequest(DefaultChatRequestArgs)
			{
				Messages = messages
			};
			return CreateChatCompletionAsync(request);
		}

		/// <summary>
		/// Ask the API to complete the request using the specified message(s).  Any parameters will fall back to default values specified in <see cref="DefaultChatRequestArgs"/> if present.
		/// </summary>
		/// <param name="userMessages">The user message or messages to use in the generation.  All strings are assumed to be of Role <see cref="ChatMessageRole.User"/></param>
		/// <returns>The <see cref="ChatResult"/> with the API response.</returns>
		public Task<ChatResult> CreateChatCompletionAsync(params string[] userMessages) => CreateChatCompletionAsync(userMessages.Select(m => new ChatMessage(ChatMessageRole.User, m)).ToArray());

		#endregion

		#region Streaming

		/// <summary>
		/// Ask the API to complete the message(s) using the specified request, and stream the results to the <paramref name="resultHandler"/> as they come in.
		/// If you are on the latest C# supporting async enumerables, you may prefer the cleaner syntax of <see cref="StreamChatEnumerableAsync(ChatRequest)"/> instead.
		/// </summary>
		/// <param name="request">The request to send to the API. This does not fall back to default values specified in <see cref="DefaultChatRequestArgs"/>.</param>
		/// <param name="resultHandler">An action to be called as each new result arrives, which includes the index of the result in the overall result set.</param>
		public async Task StreamCompletionAsync(ChatRequest request, Action<int, ChatResult> resultHandler)
		{
			int index = 0;

			await foreach (var res in StreamChatEnumerableAsync(request))
			{
				resultHandler(index++, res);
			}
		}

		/// <summary>
		/// Ask the API to complete the message(s) using the specified request, and stream the results to the <paramref name="resultHandler"/> as they come in.
		/// If you are on the latest C# supporting async enumerables, you may prefer the cleaner syntax of <see cref="StreamChatEnumerableAsync(ChatRequest)"/> instead.
		/// </summary>
		/// <param name="request">The request to send to the API.  This does not fall back to default values specified in <see cref="DefaultChatRequestArgs"/>.</param>
		/// <param name="resultHandler">An action to be called as each new result arrives.</param>
		public async Task StreamChatAsync(ChatRequest request, Action<ChatResult> resultHandler)
		{
			await foreach (var res in StreamChatEnumerableAsync(request))
			{
				resultHandler(res);
			}
		}

		/// <summary>
		/// Ask the API to complete the message(s) using the specified request, and stream the results as they come in.
		/// If you are not using C# 8 supporting async enumerables or if you are using the .NET Framework, you may need to use <see cref="StreamChatAsync(ChatRequest, Action{ChatResult})"/> instead.
		/// </summary>
		/// <param name="request">The request to send to the API.  This does not fall back to default values specified in <see cref="DefaultChatRequestArgs"/>.</param>
		/// <returns>An async enumerable with each of the results as they come in.  See <see href="https://docs.microsoft.com/en-us/dotnet/csharp/whats-new/csharp-8#asynchronous-streams"/> for more details on how to consume an async enumerable.</returns>
		public IAsyncEnumerable<ChatResult> StreamChatEnumerableAsync(ChatRequest request)
		{
			request = new ChatRequest(request) { Stream = true };
			return HttpStreamingRequest<ChatResult>(Url, HttpMethod.Post, request);
		}

		/// <summary>
		/// Ask the API to complete the message(s) using the specified request, and stream the results as they come in.
		/// If you are not using C# 8 supporting async enumerables or if you are using the .NET Framework, you may need to use <see cref="StreamChatAsync(ChatRequest, Action{ChatResult})"/> instead.
		/// </summary>
		/// <param name="messages">The array of messages to send to the API</param>
		/// <param name="model">The model to use. See the ChatGPT models available from <see cref="ModelsEndpoint.GetModelsAsync()"/></param>
		/// <param name="temperature">What sampling temperature to use. Higher values means the model will take more risks. Try 0.9 for more creative applications, and 0 (argmax sampling) for ones with a well-defined answer. It is generally recommend to use this or <paramref name="top_p"/> but not both.</param>
		/// <param name="top_p">An alternative to sampling with temperature, called nucleus sampling, where the model considers the results of the tokens with top_p probability mass. So 0.1 means only the tokens comprising the top 10% probability mass are considered. It is generally recommend to use this or <paramref name="temperature"/> but not both.</param>
		/// <param name="numOutputs">How many different choices to request for each prompt.</param>
		/// <param name="max_tokens">How many tokens to complete to. Can return fewer if a stop sequence is hit.</param>
		/// <param name="frequencyPenalty">The scale of the penalty for how often a token is used.  Should generally be between 0 and 1, although negative numbers are allowed to encourage token reuse.</param>
		/// <param name="presencePenalty">The scale of the penalty applied if a token is already present at all.  Should generally be between 0 and 1, although negative numbers are allowed to encourage token reuse.</param>
		/// <param name="logitBias">Maps tokens (specified by their token ID in the tokenizer) to an associated bias value from -100 to 100. Mathematically, the bias is added to the logits generated by the model prior to sampling. The exact effect will vary per model, but values between -1 and 1 should decrease or increase likelihood of selection; values like -100 or 100 should result in a ban or exclusive selection of the relevant token.</param>
		/// <param name="stopSequences">One or more sequences where the API will stop generating further tokens. The returned text will not contain the stop sequence.</param>
		/// <returns>An async enumerable with each of the results as they come in. See <see href="https://docs.microsoft.com/en-us/dotnet/csharp/whats-new/csharp-8#asynchronous-streams">the C# docs</see> for more details on how to consume an async enumerable.</returns>
		public IAsyncEnumerable<ChatResult> StreamChatEnumerableAsync(IList<ChatMessage> messages,
			Model model = null,
			double? temperature = null,
			double? top_p = null,
			int? numOutputs = null,
			int? max_tokens = null,
			double? frequencyPenalty = null,
			double? presencePenalty = null,
			IReadOnlyDictionary<string, float> logitBias = null,
			params string[] stopSequences)
		{
			ChatRequest request = new ChatRequest(DefaultChatRequestArgs)
			{
				Messages = messages,
				Model = model ?? DefaultChatRequestArgs.Model,
				Temperature = temperature ?? DefaultChatRequestArgs.Temperature,
				TopP = top_p ?? DefaultChatRequestArgs.TopP,
				NumChoicesPerMessage = numOutputs ?? DefaultChatRequestArgs.NumChoicesPerMessage,
				MultipleStopSequences = stopSequences ?? DefaultChatRequestArgs.MultipleStopSequences,
				MaxTokens = max_tokens ?? DefaultChatRequestArgs.MaxTokens,
				FrequencyPenalty = frequencyPenalty ?? DefaultChatRequestArgs.FrequencyPenalty,
				PresencePenalty = presencePenalty ?? DefaultChatRequestArgs.PresencePenalty,
				LogitBias = logitBias ?? DefaultChatRequestArgs.LogitBias
			};
			return StreamChatEnumerableAsync(request);
		}
		#endregion
	}
}