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https://github.com/MindWorkAI/AI-Studio.git
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444 lines
18 KiB
C#
444 lines
18 KiB
C#
using AIStudio.Chat;
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using AIStudio.Provider;
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using AIStudio.Settings;
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using AIStudio.Settings.DataModel;
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using AIStudio.Tools.Databases;
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using AIStudio.Tools.Databases.EmbeddingState;
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using AIStudio.Tools.Databases.VectorStore;
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using AIStudio.Tools.RAG;
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using AIStudio.Tools.Rust;
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namespace AIStudio.Tools.Services;
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public sealed class DataSourceLocalRetrievalService(
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SettingsManager settingsManager,
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RustService rustService,
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DatabaseClientProvider databaseClientProvider,
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ILogger<DataSourceLocalRetrievalService> logger)
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{
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private enum RetrievalChannel
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{
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VECTOR,
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BM25,
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}
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private sealed record LocalRetrievalHit(
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RetrievalChannel Channel,
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string ChunkId,
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string ParentFileId,
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string DataSourceId,
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string DataSourceName,
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string DataSourceType,
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string AbsolutePath,
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string FileName,
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string RelativePath,
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string FileType,
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int? PageNumber,
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int ChunkIndex,
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string Text,
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double Score,
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int Rank,
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string ComplianceLevel,
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int ComplianceLevelRank);
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public Task<IReadOnlyList<IRetrievalContext>> RetrieveDataAsync(DataSourceLocalFile dataSource, IContent lastUserPrompt, ChatThread thread, CancellationToken token = default) =>
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this.RetrieveDataAsync((IInternalDataSource)dataSource, lastUserPrompt, token);
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public Task<IReadOnlyList<IRetrievalContext>> RetrieveDataAsync(DataSourceLocalDirectory dataSource, IContent lastUserPrompt, ChatThread thread, CancellationToken token = default) =>
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this.RetrieveDataAsync((IInternalDataSource)dataSource, lastUserPrompt, token);
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private async Task<IReadOnlyList<IRetrievalContext>> RetrieveDataAsync(IInternalDataSource dataSource, IContent lastUserPrompt, CancellationToken token)
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{
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var query = GetQueryText(lastUserPrompt);
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if (string.IsNullOrWhiteSpace(query))
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{
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logger.LogDebug("Skipping local retrieval for data source '{DataSourceName}' ({DataSourceId}) because the latest prompt does not contain text.", dataSource.Name, dataSource.Id);
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return [];
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}
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var maxMatches = (int)dataSource.MaxMatches;
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if (maxMatches == 0)
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return [];
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var collectionName = DataSourceEmbeddingNames.GetCollectionName(dataSource.Name, dataSource.Id);
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var vectorTask = this.SearchVectorAsync(dataSource, query, maxMatches, collectionName, token);
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var bm25Task = this.SearchBm25Async(dataSource, query, maxMatches, token);
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await Task.WhenAll(vectorTask, bm25Task);
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token.ThrowIfCancellationRequested();
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var hits = MergeResults(vectorTask.Result, bm25Task.Result, maxMatches);
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logger.LogInformation(
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"Retrieved {MergedHits} local RAG hits for data source '{DataSourceName}' ({DataSourceId}). VectorCandidates={VectorHits}, BM25Candidates={BM25Hits}, RequestedPerChannel={RequestedPerChannel}.",
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hits.Count,
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dataSource.Name,
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dataSource.Id,
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vectorTask.Result.Count,
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bm25Task.Result.Count,
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maxMatches);
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return hits
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.Where(hit => !string.IsNullOrWhiteSpace(hit.Text))
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.Select(ToRetrievalContext)
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.ToList();
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}
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private async Task<IReadOnlyList<VectorSearchResult>> SearchVectorAsync(
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IInternalDataSource dataSource,
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string query,
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int maxMatches,
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string collectionName,
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CancellationToken token)
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{
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try
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{
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var vectorStore = await databaseClientProvider.GetVectorStoreAsync(token);
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if (!vectorStore.IsAvailable)
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{
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logger.LogWarning(
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"Skipping vector retrieval for data source '{DataSourceName}' ({DataSourceId}) because vector store '{VectorStoreName}' is unavailable.",
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dataSource.Name,
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dataSource.Id,
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vectorStore.Name);
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return [];
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}
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if (!DataSourceEmbeddingProviders.TryResolve(settingsManager, dataSource, out var embeddingProvider))
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{
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logger.LogWarning("Skipping vector retrieval for data source '{DataSourceName}' ({DataSourceId}) because the selected embedding provider is not available.", dataSource.Name, dataSource.Id);
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return [];
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}
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if (!await this.QueryFitsEmbeddingProviderAsync(dataSource, embeddingProvider, query, token))
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return [];
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var provider = embeddingProvider.CreateProvider();
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var vectors = await provider.EmbedTextAsync(embeddingProvider.Model, settingsManager, token, [query]);
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token.ThrowIfCancellationRequested();
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var vector = vectors.FirstOrDefault();
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if (vector is null || vector.Count == 0)
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{
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logger.LogWarning("Skipping vector retrieval for data source '{DataSourceName}' ({DataSourceId}) because query embedding returned no vector.", dataSource.Name, dataSource.Id);
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return [];
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}
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var results = this.LimitSearchResults(
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dataSource,
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"vector",
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await vectorStore.SearchEmbeddingAsync(collectionName, vector, maxMatches, token),
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maxMatches);
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this.LogVectorResults(dataSource, results);
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return results;
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}
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catch (OperationCanceledException) when (token.IsCancellationRequested)
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{
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throw;
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}
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catch (Exception exception)
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{
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logger.LogWarning(exception, "Vector retrieval failed for data source '{DataSourceName}' ({DataSourceId}).", dataSource.Name, dataSource.Id);
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return [];
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}
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}
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private async Task<bool> QueryFitsEmbeddingProviderAsync(
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IInternalDataSource dataSource,
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EmbeddingProvider embeddingProvider,
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string query,
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CancellationToken token)
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{
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var providerTokenLimit = Math.Max(1, embeddingProvider.EffectiveTokenLimit);
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if (query.Length > RustService.MAX_TOKEN_COUNT_REQUEST_TEXT_LENGTH)
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{
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logger.LogWarning(
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"Skipping vector retrieval for data source '{DataSourceName}' ({DataSourceId}) because the latest prompt has {CharacterCount} characters and exceeds the safe tokenizer request length of {MaxCharacterCount}. ProviderTokenLimit={ProviderTokenLimit}.",
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dataSource.Name,
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dataSource.Id,
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query.Length,
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RustService.MAX_TOKEN_COUNT_REQUEST_TEXT_LENGTH,
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providerTokenLimit);
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return false;
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}
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var tokenCountResponse = await rustService.GetTokenCount(
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embeddingProvider.Name,
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embeddingProvider.TokenizerPath,
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query,
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token);
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if (tokenCountResponse is not { Success: true, Status: TokenizerStatus.AVAILABLE })
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{
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logger.LogWarning(
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"Skipping vector retrieval for data source '{DataSourceName}' ({DataSourceId}) because the token count for embedding provider '{EmbeddingProviderName}' could not be determined. Reason='{Reason}'.",
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dataSource.Name,
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dataSource.Id,
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embeddingProvider.Name,
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tokenCountResponse?.Message ?? "No response was returned by the tokenizer service.");
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return false;
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}
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var queryTokenCount = tokenCountResponse.Value.TokenCount;
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if (queryTokenCount > providerTokenLimit)
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{
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logger.LogWarning(
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"Skipping vector retrieval for data source '{DataSourceName}' ({DataSourceId}) because the latest prompt has {QueryTokenCount} tokens, exceeding embedding provider '{EmbeddingProviderName}' limit of {ProviderTokenLimit} tokens.",
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dataSource.Name,
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dataSource.Id,
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queryTokenCount,
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embeddingProvider.Name,
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providerTokenLimit);
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return false;
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}
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return true;
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}
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private async Task<IReadOnlyList<EmbeddingStateSearchResult>> SearchBm25Async(IInternalDataSource dataSource, string query, int maxMatches, CancellationToken token)
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{
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try
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{
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var embeddingState = await databaseClientProvider.GetEmbeddingStateAsync(token);
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if (!embeddingState.IsAvailable)
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{
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logger.LogWarning(
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"Skipping BM25 retrieval for data source '{DataSourceName}' ({DataSourceId}) because local RAG index '{DatabaseName}' is unavailable.",
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dataSource.Name,
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dataSource.Id,
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embeddingState.Name);
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return [];
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}
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var results = this.LimitSearchResults(
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dataSource,
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"BM25",
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await embeddingState.SearchChunksAsync(dataSource.Id, query, maxMatches, token),
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maxMatches);
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this.LogBm25Results(dataSource, results);
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return results;
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}
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catch (OperationCanceledException) when (token.IsCancellationRequested)
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{
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throw;
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}
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catch (Exception exception)
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{
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logger.LogWarning(exception, "BM25 retrieval failed for data source '{DataSourceName}' ({DataSourceId}).", dataSource.Name, dataSource.Id);
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return [];
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}
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}
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private IReadOnlyList<T> LimitSearchResults<T>(IInternalDataSource dataSource, string searchName, IReadOnlyList<T> results, int maxMatches)
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{
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if (results.Count <= maxMatches)
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return results;
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logger.LogWarning(
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"Local RAG {SearchName} search returned {ReturnedHits} chunks for data source '{DataSourceName}' ({DataSourceId}), which exceeds the configured maximum {MaxMatches}. Truncating to the datasource limit.",
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searchName,
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results.Count,
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dataSource.Name,
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dataSource.Id,
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maxMatches);
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return results.Take(maxMatches).ToList();
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}
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private static IReadOnlyList<LocalRetrievalHit> MergeResults(
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IReadOnlyList<VectorSearchResult> vectorResults,
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IReadOnlyList<EmbeddingStateSearchResult> bm25Results,
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int maxMatches)
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{
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// Future reranking should replace this deterministic channel merge.
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var merged = new List<LocalRetrievalHit>(maxMatches * 2);
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var seenChunkIds = new HashSet<string>(StringComparer.OrdinalIgnoreCase);
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AppendHits(
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merged,
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seenChunkIds,
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vectorResults
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.Select((result, index) => FromVectorResult(result, index + 1)),
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maxMatches);
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AppendHits(
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merged,
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seenChunkIds,
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bm25Results
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.Select((result, index) => FromBm25Result(result, index + 1)),
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maxMatches);
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return merged;
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}
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private static void AppendHits(List<LocalRetrievalHit> merged, HashSet<string> seenChunkIds, IEnumerable<LocalRetrievalHit> hits, int maxNewHits)
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{
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var added = 0;
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foreach (var hit in hits)
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{
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if (!string.IsNullOrWhiteSpace(hit.ChunkId) && !seenChunkIds.Add(hit.ChunkId))
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continue;
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merged.Add(hit);
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added++;
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if (added >= maxNewHits)
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return;
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}
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}
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private static LocalRetrievalHit FromVectorResult(VectorSearchResult result, int rank) =>
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new(
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RetrievalChannel.VECTOR,
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result.ChunkId,
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result.ParentFileId,
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result.DataSourceId,
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result.DataSourceName,
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result.DataSourceType,
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FirstNonEmpty(result.AbsolutePath, result.FilePath),
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result.FileName,
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result.RelativePath,
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result.FileType,
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result.PageNumber,
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result.ChunkIndex,
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result.Text,
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result.Score,
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rank,
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result.ComplianceLevel,
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result.ComplianceLevelRank);
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private static LocalRetrievalHit FromBm25Result(EmbeddingStateSearchResult result, int rank) =>
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new(
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RetrievalChannel.BM25,
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result.ChunkId,
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result.ParentFileId,
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result.DataSourceId,
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result.DataSourceName,
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result.DataSourceType,
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result.AbsolutePath,
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result.FileName,
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result.RelativePath,
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result.FileType,
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result.PageNumber,
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result.ChunkIndex,
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result.ChunkText,
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result.Score,
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rank,
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result.ComplianceLevel,
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result.ComplianceLevelRank);
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private static RetrievalTextContext ToRetrievalContext(LocalRetrievalHit hit)
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{
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var sourceName = FirstNonEmpty(hit.FileName, hit.DataSourceName);
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var path = FirstNonEmpty(hit.AbsolutePath, hit.RelativePath);
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var referenceLink = string.IsNullOrWhiteSpace(path) ? string.Empty : BuildReferenceLink(path, hit);
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return new RetrievalTextContext
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{
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DataSourceName = sourceName,
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Category = RetrievalContentCategory.TEXT,
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Type = GetRetrievalContentType(hit.FileType),
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Path = path,
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Links = [],
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MatchedText = hit.Text,
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SurroundingContent = [],
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ReferenceTitle = BuildReferenceTitle(hit),
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ReferenceLink = referenceLink,
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};
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}
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private static string BuildReferenceTitle(LocalRetrievalHit hit)
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{
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var sourceName = FirstNonEmpty(hit.FileName, hit.DataSourceName);
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return BuildChunkTitle(sourceName, hit.ChunkIndex, hit.PageNumber);
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}
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private static string BuildChunkTitle(string sourceName, int chunkIndex, int? pageNumber)
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{
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var page = pageNumber is > 0 ? $", page {pageNumber}" : string.Empty;
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return $"{sourceName} (chunk {chunkIndex + 1}{page})";
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}
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private static string BuildReferenceLink(string path, LocalRetrievalHit hit)
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{
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var link = NormalizeLocalReferencePath(path);
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var separator = link.Contains('#', StringComparison.Ordinal) ? "&" : "#";
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return $"{link}{separator}chunk={hit.ChunkIndex}";
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}
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private static string NormalizeLocalReferencePath(string path)
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{
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try
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{
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return Path.IsPathRooted(path)
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? new Uri(Path.GetFullPath(path)).AbsoluteUri
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: path;
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}
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catch
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{
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return path;
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}
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}
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private static RetrievalContentType GetRetrievalContentType(string fileType) => fileType.TrimStart('.').ToLowerInvariant() switch
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{
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"csv" or "tsv" or "ods" or "xls" or "xlsx" or "xlsm" or "xlsb" => RetrievalContentType.TEXT_SPREADSHEET,
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"odp" or "ppt" or "pptx" => RetrievalContentType.TEXT_PRESENTATION,
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"htm" or "html" => RetrievalContentType.TEXT_WEBSITE,
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_ => RetrievalContentType.TEXT_DOCUMENT
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};
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private static string GetQueryText(IContent lastUserPrompt) => lastUserPrompt switch
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{
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ContentText text => text.Text,
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_ => string.Empty
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};
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private static string FirstNonEmpty(params string[] values) =>
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values.FirstOrDefault(value => !string.IsNullOrWhiteSpace(value)) ?? string.Empty;
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private void LogVectorResults(IInternalDataSource dataSource, IReadOnlyList<VectorSearchResult> results)
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{
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if (results.Count == 0)
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{
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logger.LogInformation("Local RAG vector search found no chunks for data source '{DataSourceName}' ({DataSourceId}).", dataSource.Name, dataSource.Id);
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return;
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}
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foreach (var result in results.Select((result, index) => (Result: result, Rank: index + 1)))
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{
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logger.LogInformation(
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"Local RAG vector search found chunk for data source '{DataSourceName}' ({DataSourceId}). Rank={Rank}, Score={Score}, ChunkId='{ChunkId}', ParentFileId='{ParentFileId}', File='{FileName}', Path='{Path}', Title='{Title}'.",
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dataSource.Name,
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dataSource.Id,
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result.Rank,
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result.Result.Score,
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result.Result.ChunkId,
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result.Result.ParentFileId,
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result.Result.FileName,
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FirstNonEmpty(result.Result.AbsolutePath, result.Result.FilePath),
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BuildChunkTitle(FirstNonEmpty(result.Result.FileName, dataSource.Name), result.Result.ChunkIndex, result.Result.PageNumber));
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}
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}
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private void LogBm25Results(IInternalDataSource dataSource, IReadOnlyList<EmbeddingStateSearchResult> results)
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{
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if (results.Count == 0)
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{
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logger.LogInformation("Local RAG BM25 search found no chunks for data source '{DataSourceName}' ({DataSourceId}).", dataSource.Name, dataSource.Id);
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return;
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}
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foreach (var result in results.Select((result, index) => (Result: result, Rank: index + 1)))
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{
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logger.LogInformation(
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"Local RAG BM25 search found chunk for data source '{DataSourceName}' ({DataSourceId}). Rank={Rank}, Score={Score}, ChunkId='{ChunkId}', ParentFileId='{ParentFileId}', File='{FileName}', Path='{Path}', Title='{Title}'.",
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dataSource.Name,
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dataSource.Id,
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result.Rank,
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result.Result.Score,
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result.Result.ChunkId,
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result.Result.ParentFileId,
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result.Result.FileName,
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result.Result.AbsolutePath,
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BuildChunkTitle(FirstNonEmpty(result.Result.FileName, dataSource.Name), result.Result.ChunkIndex, result.Result.PageNumber));
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}
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}
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}
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