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Fixed entityCache not multithreading safe, Reduced expensive table joins for embedding, Fixed timeouts on large deletes, fixed possible unclosed readers, Improved EntityFromJSON speed, Added connection pool control for fault tolerance, Fixed modelsInUse multithreading safety

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This commit is contained in:
LD-Reborn
2026-02-18 13:41:55 +01:00
parent 7a0363a470
commit f537912e4e
13 changed files with 600 additions and 388 deletions
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21
src/Server/Datapoint.cs
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@@ -1,3 +1,4 @@
using System.Collections.Concurrent;
using Shared;
using Shared.Models;
@@ -10,23 +11,26 @@ public class Datapoint
public SimilarityMethod similarityMethod;
public List<(string, float[])> embeddings;
public string hash;
public int id;
public Datapoint(string name, ProbMethodEnum probMethod, SimilarityMethodEnum similarityMethod, string hash, List<(string, float[])> embeddings)
public Datapoint(string name, ProbMethodEnum probMethod, SimilarityMethodEnum similarityMethod, string hash, List<(string, float[])> embeddings, int id)
{
this.name = name;
this.probMethod = new ProbMethod(probMethod);
this.similarityMethod = new SimilarityMethod(similarityMethod);
this.hash = hash;
this.embeddings = embeddings;
this.id = id;
}
public Datapoint(string name, ProbMethod probMethod, SimilarityMethod similarityMethod, string hash, List<(string, float[])> embeddings)
public Datapoint(string name, ProbMethod probMethod, SimilarityMethod similarityMethod, string hash, List<(string, float[])> embeddings, int id)
{
this.name = name;
this.probMethod = probMethod;
this.similarityMethod = similarityMethod;
this.hash = hash;
this.embeddings = embeddings;
this.id = id;
}
public float CalcProbability(List<(string, float)> probabilities)
@@ -34,18 +38,19 @@ public class Datapoint
return probMethod.method(probabilities);
}
public static Dictionary<string, float[]> GetEmbeddings(string content, List<string> models, AIProvider aIProvider, EnumerableLruCache<string, Dictionary<string, float[]>> embeddingCache)
public static Dictionary<string, float[]> GetEmbeddings(string content, ConcurrentBag<string> models, AIProvider aIProvider, EnumerableLruCache<string, Dictionary<string, float[]>> embeddingCache)
{
Dictionary<string, float[]> embeddings = [];
bool embeddingCacheHasContent = embeddingCache.TryGetValue(content, out var embeddingCacheForContent);
if (!embeddingCacheHasContent || embeddingCacheForContent is null)
{
models.ForEach(model =>
embeddings[model] = GenerateEmbeddings(content, model, aIProvider, embeddingCache)
);
foreach (string model in models)
{
embeddings[model] = GenerateEmbeddings(content, model, aIProvider, embeddingCache);
}
return embeddings;
}
models.ForEach(model =>
foreach (string model in models)
{
bool embeddingCacheHasModel = embeddingCacheForContent.TryGetValue(model, out float[]? embeddingCacheForModel);
if (embeddingCacheHasModel && embeddingCacheForModel is not null)
@@ -55,7 +60,7 @@ public class Datapoint
{
embeddings[model] = GenerateEmbeddings(content, model, aIProvider, embeddingCache);
}
});
}
return embeddings;
}