// TEMPLATE: EmbeddingService.cs
// PURPOSE: Generates embeddings for RAG indexing and query, via IEmbeddingGenerator.
// READS STANDARD: ai-agents-rag-custom-pgvector
// PLACEHOLDERS:
//   {{PROJECT_NAMESPACE}}  — root namespace of the project (e.g., MyProject)
// LAST-VERIFIED: 2026-05-19
//
// IMPORTANT — IEmbeddingGenerator registration (in Program.cs of the project):
//   The project must register IEmbeddingGenerator<string, Embedding<float>> in DI.
//   Example for OpenAI text-embedding-3-small (the canonical "embeddings" alias):
//
//   builder.Services.AddSingleton<IEmbeddingGenerator<string, Embedding<float>>>(sp =>
//   {
//       var cfg = sp.GetRequiredService<IConfiguration>();
//       return new OpenAIClient(cfg["OpenAI:ApiKey"]!)
//           .GetEmbeddingClient("text-embedding-3-small")
//           .AsIEmbeddingGenerator();
//   });
//
//   For other providers (Google, Anthropic, Ollama) adapt the client construction —
//   see ai-agents-providers-model-registry §providers for verified SDKs.

using Microsoft.Extensions.AI;

namespace {{PROJECT_NAMESPACE}}.AI;

/// <summary>
/// Generates text embeddings for RAG indexing and query.
/// Wraps <see cref="IEmbeddingGenerator{TInput,TEmbedding}"/> so the rest of the project
/// does not take a direct dependency on the underlying provider SDK.
/// </summary>
public sealed class EmbeddingService(IEmbeddingGenerator<string, Embedding<float>> generator)
{
    /// <summary>
    /// Generates an embedding vector for a single text (used at query time).
    /// </summary>
    /// <param name="text">The text to embed.</param>
    /// <param name="ct">Cancellation token.</param>
    /// <returns>The embedding vector as <see cref="ReadOnlyMemory{T}"/> of float.</returns>
    public async Task<ReadOnlyMemory<float>> EmbedAsync(
        string text,
        CancellationToken ct = default)
    {
        // GenerateAsync is the verified API: returns GeneratedEmbeddings<Embedding<float>>.
        // Each Embedding<float>.Vector is a ReadOnlyMemory<float>.
        // Source: Microsoft Learn — microsoft-extensions-ai (verified 2026-05-19).
        GeneratedEmbeddings<Embedding<float>> result =
            await generator.GenerateAsync([text], cancellationToken: ct);

        return result[0].Vector;
    }

    /// <summary>
    /// Generates embedding vectors for a batch of texts (used during document indexing).
    /// </summary>
    /// <param name="texts">The texts to embed.</param>
    /// <param name="ct">Cancellation token.</param>
    /// <returns>Embedding vectors in the same order as the input texts.</returns>
    public async Task<IReadOnlyList<ReadOnlyMemory<float>>> EmbedBatchAsync(
        IReadOnlyList<string> texts,
        CancellationToken ct = default)
    {
        GeneratedEmbeddings<Embedding<float>> result =
            await generator.GenerateAsync(texts, cancellationToken: ct);

        return [.. result.Select(e => e.Vector)];
    }
}