using System.Collections.Generic;
using System.Threading.Tasks;
using CodeBase.Models;
using Neo4j.Driver;

namespace CodeBase.Repositories
{
    public class ScipRepository
    {
        private readonly IDriver _neo4jDriver;

        public ScipRepository(IDriver neo4jDriver)
        {
            _neo4jDriver = neo4jDriver;
        }
        public async Task SaveChunksAsync(List<CodeChunk> chunks)
        {
            if (chunks == null || chunks.Count == 0) return;

            await using var session = _neo4jDriver.AsyncSession();

            await session.ExecuteWriteAsync(async tx =>
            {
                foreach (var chunk in chunks)
                {
                    var uniqueId = $"{chunk.ProjectName}::{chunk.Id}";

                    var query = @"
                                MERGE (p:Project {name: $projectName})
                
                                MERGE (m:CodeEntity {id: $id})
                                SET m.projectName = $projectName,
                                    m.name = $name,
                                    m.filePath = $filePath,
                                    m.code = $code,
                                    m.language = $language,
                                    m.embedding = $embedding
                    
                                MERGE (p)-[:CONTAINS]->(m)";

                    await tx.RunAsync(query, new
                    {
                        id = uniqueId,
                        projectName = chunk.ProjectName,
                        name = chunk.EntityName,
                        filePath = chunk.FilePath,
                        code = chunk.Content,
                        language = chunk.Language,
                        embedding = chunk.Embedding
                    });
                }
            });
        }

        /// <summary>
        /// Ищет в графе узлы, наиболее близкие к переданному вектору.
        /// </summary>
        /// <param name="queryVector">Вектор вопроса пользователя</param>
        /// <param name="projectName">Имя проекта для фильтрации (опционально)</param>
        /// <param name="topK">Сколько кусков кода вернуть</param>
        public async Task<List<RetrievedContext>> FindSimilarNodesAsync(float[] queryVector, string projectName = null, int topK = 5)
        {
            await using var session = _neo4jDriver.AsyncSession();

            var result = await session.ExecuteReadAsync(async tx =>
            {
                // Базовый запрос к векторному индексу
                string cypherQuery = @"
                    CALL db.index.vector.queryNodes('code_embeddings', $topK, $queryVector)
                    YIELD node AS method, score
                    WHERE $projectName IS NULL OR method.projectName = $projectName
                    RETURN method.projectName AS Project, method.name AS Name, method.filePath AS Path, method.code AS Code, score
                    ORDER BY score DESC";

                var cursor = await tx.RunAsync(cypherQuery, new { topK, queryVector, projectName });
                var contexts = new List<RetrievedContext>();

                while (await cursor.FetchAsync())
                {
                    contexts.Add(new RetrievedContext
                    {
                        ProjectName = cursor.Current["Project"].As<string>(), // Читаем имя проекта
                        EntityName = cursor.Current["Name"].As<string>(),
                        FilePath = cursor.Current["Path"].As<string>(),
                        Content = cursor.Current["Code"].As<string>(),
                        SimilarityScore = cursor.Current["score"].As<double>()
                    });
                }

                return contexts;
            });

            return result;
        }
    }
}