#49 IMPLEMENT IEmbeddingEndpoint

Author: pandapknaepel

OpenAI_API/Embedding/EmbeddingEndpoint.cs

@@ -6,7 +6,7 @@ namespace OpenAI_API.Embedding
 	/// <summary>
 	/// OpenAI’s text embeddings measure the relatedness of text strings by generating an embedding, which is a vector (list) of floating point numbers. The distance between two vectors measures their relatedness. Small distances suggest high relatedness and large distances suggest low relatedness.
 	/// </summary>
-	public class EmbeddingEndpoint : EndpointBase
+	public class EmbeddingEndpoint : EndpointBase, IEmbeddingEndpoint
 	{
 		/// <summary>
 		/// This allows you to send request to the recommended model without needing to specify. Every request uses the <see cref="Model.AdaTextEmbedding"/> model

OpenAI_API/Embedding/IEmbeddingEndpoint.cs

@@ -0,0 +1,36 @@
+using System.Threading.Tasks;
+
+namespace OpenAI_API.Embedding
+{
+    /// <summary>
+    /// OpenAI’s text embeddings measure the relatedness of text strings by generating an embedding, which is a vector (list) of floating point numbers. The distance between two vectors measures their relatedness. Small distances suggest high relatedness and large distances suggest low relatedness.
+    /// </summary>
+    public interface IEmbeddingEndpoint
+    {
+        /// <summary>
+        /// This allows you to send request to the recommended model without needing to specify. Every request uses the <see cref="Model.AdaTextEmbedding"/> model
+        /// </summary>
+        EmbeddingRequest DefaultEmbeddingRequestArgs { get; set; }
+
+        /// <summary>
+        /// Ask the API to embedd text using the default embedding model <see cref="Model.AdaTextEmbedding"/>
+        /// </summary>
+        /// <param name="input">Text to be embedded</param>
+        /// <returns>Asynchronously returns the embedding result. Look in its <see cref="Data.Embedding"/> property of <see cref="EmbeddingResult.Data"/> to find the vector of floating point numbers</returns>
+        Task<EmbeddingResult> CreateEmbeddingAsync(string input);
+
+        /// <summary>
+        /// Ask the API to embedd text using a custom request
+        /// </summary>
+        /// <param name="request">Request to be send</param>
+        /// <returns>Asynchronously returns the embedding result. Look in its <see cref="Data.Embedding"/> property of <see cref="EmbeddingResult.Data"/> to find the vector of floating point numbers</returns>
+        Task<EmbeddingResult> CreateEmbeddingAsync(EmbeddingRequest request);
+
+        /// <summary>
+        /// Ask the API to embedd text using the default embedding model <see cref="Model.AdaTextEmbedding"/>
+        /// </summary>
+        /// <param name="input">Text to be embedded</param>
+        /// <returns>Asynchronously returns the first embedding result as an array of floats.</returns>
+        Task<float[]> GetEmbeddingsAsync(string input);
+    }
+}