using Rag.Models;

namespace Api.Data.Repositories.Contracts;

public interface IRagRepository
{
    Task InitializeAsync(CancellationToken ct);
    Task<RagDocumentRecord?> GetDocumentByTextHashAsync(string textHash, string? sourceUrl, CancellationToken ct);
    Task<RagDocumentRecord?> GetDocumentByIdAsync(string id, CancellationToken ct);
    Task SaveDocumentAsync(RagDocumentRecord document, IReadOnlyList<RagChunkRecord> chunks, CancellationToken ct);
    Task<IReadOnlyList<SearchCandidateChunk>> SearchChunksAsync(float[] queryEmbedding, IReadOnlyList<string>? targetTypes, int topK, CancellationToken ct);
    Task<float[]?> GetEmbeddingAsync(string cacheKey, CancellationToken ct);
    Task SaveEmbeddingAsync(string cacheKey, string model, string textHash, float[] vector, CancellationToken ct);
    Task<string?> GetChatCompletionAsync(string cacheKey, CancellationToken ct);
    Task SaveChatCompletionAsync(string cacheKey, string model, decimal temperature, string responseText, CancellationToken ct);
}