Developer

Samples/Senaprc.AI.Samples.Agents/Senaprc.AI.Samples.Agents.csproj

@@ -33,7 +33,7 @@
 	<ItemGroup>
 		<PackageReference Include="AutoGen" Version="0.2.3" />
 		<PackageReference Include="Microsoft.Extensions.Configuration.Json" Version="8.0.1" />
-		<PackageReference Include="Microsoft.SemanticKernel.Plugins.Web" Version="1.48.0-alpha" />
+		<PackageReference Include="Microsoft.SemanticKernel.Plugins.Web" Version="1.54.0-alpha" />
 		<PackageReference Include="Senparc.Weixin.Work" Version="3.25.5" />
 		<PackageReference Include="Senparc.Weixin.Work.Middleware" Version="1.4.9" />
 	</ItemGroup>

Samples/Senparc.AI.Samples.Consoles/Program.cs

@@ -89,9 +89,8 @@
         {
             //Embedding Sample
             Console.WriteLine("请输入需要，进入对应 Embedding测试：");
-            Console.WriteLine("[1] 普通信息（Information）");
-            Console.WriteLine("[2] 引用信息（Reference）");
-            Console.WriteLine("[3] 检索增强生成（RAG）");
+            Console.WriteLine("[1] 普通 Embedding + 查询");
+            Console.WriteLine("[2] 检索增强生成（RAG）");
             index = Console.ReadLine();
             Console.WriteLine();
             try
@@ -103,15 +102,10 @@
                 {
                     case "1":
                         {
-                            await embeddingSample.RunAsync(isReference: false);
+                            await embeddingSample.RunAsync();
                         }
                         break;
                     case "2":
-                        {
-                            await embeddingSample.RunAsync(isReference: true);
-                        }
-                        break;
-                    case "3":
                         {
                             await embeddingSample.RunRagAsync(serviceProvider);
                         }

Samples/Senparc.AI.Samples.Consoles/Samples/EmbeddingSample.RAG.cs

@@ -1,7 +1,9 @@
 using Microsoft.EntityFrameworkCore.InMemory.Storage.Internal;
+using Microsoft.IdentityModel.Abstractions;
 using Microsoft.SemanticKernel;
 using Microsoft.SemanticKernel.Text;
 using Senparc.AI.Entities;
+using Senparc.AI.Entities.Keys;
 using Senparc.AI.Kernel;
 using Senparc.AI.Kernel.Handlers;
 using Senparc.AI.Trace;
@@ -14,6 +16,7 @@
 using System.Text;
 using System.Text.RegularExpressions;
 using System.Threading.Tasks;
+using static Qdrant.Client.Grpc.MaxOptimizationThreads.Types;
 
 namespace Senparc.AI.Samples.Consoles.Samples
 {
@@ -115,7 +118,14 @@ public async Task RunRagAsync(IServiceProvider serviceProvider)
             var iWantToRunEmbedding = embeddingAiHandler
                  .IWantTo()
                  .ConfigModel(ConfigModel.TextEmbedding, _userId)
-                 .BuildKernel();
+                 .ConfigVectorStore(embeddingAiSetting.VectorDB)
+            .BuildKernel();
+
+            var modelName = textEmbeddingGenerationName(embeddingAiSetting);
+
+            var vectorName = "senparc-sample-rag";
+            var vectorCollection = iWantToRunEmbedding.GetVectorCollection<ulong, Record>(embeddingAiSetting.VectorDB, vectorName);
+            await vectorCollection.EnsureCollectionExistsAsync();
 
             var i = 0;
             var dt = SystemTime.Now;
@@ -148,17 +158,19 @@ public async Task RunRagAsync(IServiceProvider serviceProvider)
                MemoryStore:
                    try
                    {
-                       paragraphs.ForEach(paragraph =>
+                       paragraphs.ForEach(async paragraph =>
                        {
                            var currentI = i++;
 
-                           iWantToRunEmbedding
-                             .MemorySaveInformation(
-                                 modelName: textEmbeddingGenerationName(embeddingAiSetting),
-                                 azureDeployName: textEmbeddingAzureDeployName(embeddingAiSetting),
-                                 collection: memoryCollectionName,
-                                 id: $"paragraph-{Guid.NewGuid().ToString("n")}",
-                                 text: paragraph);
+                           var record = new Record()
+                           {
+                               Id = (ulong)i,
+                               Name = vectorName + "-paragraph-" + i,
+                               Description = paragraph,
+                               DescriptionEmbedding = await iWantToRunEmbedding.SemanticKernelHelper.GetEmbeddingAsync(modelName, paragraph),
+                               Tags = new[] { i.ToString() }
+                           };
+                           await vectorCollection.UpsertAsync(record);
                        });
                    }
                    catch (Exception ex)
@@ -220,18 +232,18 @@ public async Task RunRagAsync(IServiceProvider serviceProvider)
 
                 var questionDt = DateTime.Now;
                 var limit = 3;
-                var embeddingResult = await iWantToRunEmbedding.MemorySearchAsync(
-                        modelName: textEmbeddingGenerationName(embeddingAiSetting),
-                        azureDeployName: textEmbeddingAzureDeployName(embeddingAiSetting),
-                        memoryCollectionName: memoryCollectionName,
-                        query: question,
-                        limit: limit);
-
-                await foreach (var item in embeddingResult.MemoryQueryResult)
+
+
+                ReadOnlyMemory<float> searchVector = await iWantToRunEmbedding.SemanticKernelHelper.GetEmbeddingAsync(modelName, question);
+
+                var vectorResult = vectorCollection.SearchAsync(searchVector, limit);
+
+
+                await foreach (var item in vectorResult)
                 {
                     results.AppendLine($@"//////
-{item.Metadata.Text}
-******{item.Relevance}");
+{item.Record.Description}
+******{item.Score}");
                 }
 
                 SenparcTrace.SendCustomLog("RAG日志", $@"提问：{question}，耗时：{(DateTime.Now - questionDt).TotalMilliseconds}ms

Samples/Senparc.AI.Samples.Consoles/Samples/EmbeddingSample.cs

@@ -21,19 +21,19 @@ namespace Senparc.AI.Samples.Consoles.Samples
 
     public class Record
     {
-        [VectorStoreRecordKey]
-        public string Id { get; set; }
+        [VectorStoreKey]
+        public ulong Id { get; set; }
 
-        [VectorStoreRecordData(IsIndexed = true)]
+        [VectorStoreData(IsIndexed = true)]
         public string Name { get; set; }
 
-        [VectorStoreRecordData(IsFullTextIndexed = true)]
+        [VectorStoreData(IsFullTextIndexed = true)]
         public string Description { get; set; }
 
-        [VectorStoreRecordVector(Dimensions: 4, DistanceFunction = DistanceFunction.CosineSimilarity, IndexKind = IndexKind.Hnsw)]
+        [VectorStoreVector(Dimensions: 3072 /*根据模型调整，例如 text-embedding-ada-002 为 1536*/, DistanceFunction = DistanceFunction.CosineSimilarity, IndexKind = IndexKind.Hnsw)]
         public ReadOnlyMemory<float>? DescriptionEmbedding { get; set; }
 
-        [VectorStoreRecordData(IsIndexed = true)]
+        [VectorStoreData(IsIndexed = true)]
         public string[] Tags { get; set; }
     }
 
@@ -44,29 +44,24 @@ public partial class EmbeddingSample
         SemanticAiHandler _semanticAiHandler => (SemanticAiHandler)_aiHandler;
         string _userId = "Jeffrey";
         string memoryCollectionName = "EmbeddingTest";
-        Func<ISenparcAiSetting, string> textEmbeddingGenerationName => setting => setting.ModelName.Embedding ?? "text-embedding-ada-002";
-        Func<ISenparcAiSetting, string> textEmbeddingAzureDeployName => setting => setting.ModelName.Embedding ?? "text-embedding-ada-002";
+        static Func<ISenparcAiSetting, string> textEmbeddingGenerationName => setting => setting.ModelName.Embedding ?? "text-embedding-ada-002";
+        static Func<ISenparcAiSetting, string> textEmbeddingAzureDeployName => setting => setting.ModelName.Embedding ?? "text-embedding-ada-002";
 
         public EmbeddingSample(IAiHandler aiHandler)
         {
             _aiHandler = aiHandler;
             _semanticAiHandler.SemanticKernelHelper.ResetHttpClient(enableLog: SampleSetting.EnableHttpClientLog);//同步日志设置状态
         }
 
-        public async Task RunAsync(bool isReference = false, bool isRag = false)
+        public async Task RunAsync(bool isRag = false)
         {
-            if (isReference)
-            {
-                await Console.Out.WriteLineAsync("EmbeddingSample 开始运行。请输入需要 Embedding 的内容，id 和 text 以 :::（三个英文冒号）分割，输入 n 继续下一步。");
-            }
-            else
-            {
-                await Console.Out.WriteLineAsync("EmbeddingSample 开始运行。请输入需要 Embedding 的内容，URL 和介绍以 :::（三个英文冒号）分割，输入 n 继续下一步。");
-            }
+            await Console.Out.WriteLineAsync("EmbeddingSample 开始运行。请输入需要 Embedding 的内容，输入 n 继续下一步。");
+
             await Console.Out.WriteLineAsync("请输入");
 
 
             var aiSetting = _semanticAiHandler.SemanticKernelHelper.AiSetting;
+            var vectorName = "senparc-vector-record-ai";
 
             //测试 TextEmbedding
             var iWantToRun = _semanticAiHandler
@@ -76,7 +71,9 @@ public async Task RunAsync(bool isReference = false, bool isRag = false)
                  .ConfigVectorStore(aiSetting.VectorDB)
                  .BuildKernel();
 
-            var vectorCollection = iWantToRun.GetVectorCollection<string, Record>(aiSetting.VectorDB, "senparc-vector-record");
+            var vectorCollection = iWantToRun.GetVectorCollection<ulong, Record>(aiSetting.VectorDB, vectorName);
+            await vectorCollection.EnsureCollectionExistsAsync();
+
             var modelName = textEmbeddingGenerationName(aiSetting);
 
             //开始对话
@@ -89,17 +86,14 @@ public async Task RunAsync(bool isReference = false, bool isRag = false)
                     break;
                 }
 
-                var info = prompt.Split(new[] { ":::" }, StringSplitOptions.None);
-
                 var record = new Record()
                 {
-                    Id = i.ToString(),
-                    Name = info[0],
-                    Description = info[1],
-                    DescriptionEmbedding = await iWantToRun.SemanticKernelHelper.GetEmbeddingAsync(modelName, info[1]),
-                    Tags = new[] { info[0] }
+                    Id = (ulong)i,
+                    Name = vectorName + ":" + i,
+                    Description = prompt,
+                    DescriptionEmbedding = await iWantToRun.SemanticKernelHelper.GetEmbeddingAsync(modelName, prompt),
+                    Tags = new[] { i.ToString() }
                 };
-
                 await vectorCollection.UpsertAsync(record);
 
                 i++;
@@ -117,12 +111,15 @@ public async Task RunAsync(bool isReference = false, bool isRag = false)
                 }
 
                 var questionDt = DateTime.Now;
-                var top = isReference ? 3 : 2;
+                var top = 3;// isReference ? 3 : 2;
 
                 ReadOnlyMemory<float> searchVector = await iWantToRun.SemanticKernelHelper.GetEmbeddingAsync(modelName, question);
 
-                //新方法
-                var vectorResult = vectorCollection.SearchEmbeddingAsync(searchVector, top);
+                //var r1 = await vectorCollection.GetAsync(1);//OK
+                //Console.WriteLine("r1:" + r1.ToJson(true));
+
+                //vectorCollection = iWantToRun.GetVectorCollection<string, Record>(aiSetting.VectorDB, "senparc-vector-record");
+                var vectorResult = vectorCollection.SearchAsync(searchVector, top);
                 var j = 0;
                 await foreach (var restulItem in vectorResult)
                 {
@@ -132,6 +129,7 @@ public async Task RunAsync(bool isReference = false, bool isRag = false)
                     await Console.Out.WriteLineAsync("  Id:\t\t" + string.Join(',', restulItem.Record.Tags));
                     await Console.Out.WriteLineAsync("  Relevance:\t\t" + restulItem.Score);
                     await Console.Out.WriteLineAsync($"-- cost {(DateTime.Now - questionDt).TotalMilliseconds}ms");
+                    await Console.Out.WriteLineAsync();
                     j++;
                 }
 

Samples/Senparc.AI.Samples.Consoles/Senparc.AI.Samples.Consoles.csproj

@@ -25,13 +25,13 @@
 	<ItemGroup>
 		<PackageReference Include="Microsoft.Extensions.Caching.Memory" Version="8.0.1" />
 		<PackageReference Include="Microsoft.Extensions.Configuration.Json" Version="8.0.1" />
-		<PackageReference Include="Microsoft.Extensions.DependencyInjection.Abstractions" Version="8.0.2" />
+		<PackageReference Include="Microsoft.Extensions.DependencyInjection.Abstractions" Version="9.0.5" />
 		<!--<PackageReference Include="Microsoft.KernelMemory.Core" Version="0.71.240820.1" />
 		<PackageReference Include="Microsoft.KernelMemory.MemoryDb.Redis" Version="0.71.240820.1" />-->
-		<PackageReference Include="Microsoft.SemanticKernel.Connectors.OpenAI" Version="1.48.0" />
+		<PackageReference Include="Microsoft.SemanticKernel.Connectors.OpenAI" Version="1.54.0" />
 		<PackageReference Include="Microsoft.SemanticKernel.Planners.Handlebars" Version="1.47.0-preview" />
-		<PackageReference Include="Microsoft.SemanticKernel.Plugins.Memory" Version="1.48.0-alpha" />
-		<PackageReference Include="Senparc.Xncf.SenMapic" Version="0.1.5-alpha4" />
+		<PackageReference Include="Microsoft.SemanticKernel.Plugins.Memory" Version="1.54.0-alpha" />
+		<PackageReference Include="Senparc.Xncf.SenMapic" Version="0.1.7-alpha.1" />
 		<!--<PackageReference Include="Microsoft.SemanticKernel.Planning.SequentialPlanner" Version="0.24.230912.2-preview" />-->
 		<ProjectReference Include="..\..\src\Senparc.AI.Kernel\Senparc.AI.Kernel.csproj" />
 		<ProjectReference Include="..\..\src\Senparc.AI\Senparc.AI.csproj" />

Samples/Senparc.AI.Samples.Consoles/readme.md

@@ -52,15 +52,15 @@
 
 ### Embedding 普通信息测试
 ```
-1:::My name is Jeffrey
-2:::My country is China
-3:::I'm working for Senparc
-4:::Senparc is a company based in Suzhou
-5:::Senparc is founded at 2010
-6:::Senparc startup at 2010, in Jiangsu Province, Suzhou City, Gusu Distinct
-7:::Senparc.Weixin SDK is made by Senparc, main author is Jeffrey Su who is also the founder of Senparc.
-8:::Jeffrey Su's Chinese name is Zhenwei Su.
-9:::Zhenwei Su has written two books.
+My name is Jeffrey
+My country is China
+I'm working for Senparc
+Senparc is a company based in Suzhou
+Senparc is founded at 2010
+Senparc startup at 2010, in Jiangsu Province, Suzhou City, Gusu Distinct
+Senparc.Weixin SDK is made by Senparc, main author is Jeffrey Su who is also the founder of Senparc.
+Jeffrey Su's Chinese name is Zhenwei Su.
+Zhenwei Su has written two books.
 ```
 
 ### Embedding 引用信息测试

src/Senparc.AI.Agents/AgentExtensions/AgentExtension.cs

@@ -2,6 +2,8 @@
 using AutoGen.Core;
 using AutoGen.OpenAI;
 using AutoGen.SemanticKernel;
+using System;
+using System.Collections.Generic;
 
 namespace Senparc.AI.Agents.AgentExtensions;
 
@@ -94,6 +96,42 @@ public static GroupChat CreateAiTeam<TFromAgent>(this GraphConnector graphConnec
         return aiTeam;
     }
 
+    /// <summary>
+    /// 创建 AITeam 对象（GroupChat）
+    /// </summary>
+    /// <typeparam name="TFromAgent"></typeparam>
+    /// <param name="graphConnector"></param>
+    /// <param name="adminAgent"></param>
+    /// <param name="orchestrator"></param>
+    /// <returns></returns>
+    [Obsolete("请使用方法 CreateAiTeam<TFromAgent>(this GraphConnector graphConnector, IOrchestrator orchestrator)")]
+    public static GroupChat CreateAiTeam<TFromAgent>(this GraphConnector graphConnector, TFromAgent adminAgent,  IOrchestrator orchestrator)
+        where TFromAgent : IAgent
+    {
+        var aiTeam = new GroupChat(
+            members: graphConnector.Agents.Values,
+            orchestrator: orchestrator//,
+           /* workflow: graphConnector.Graph*/);
+        return aiTeam;
+    }
+
+    /// <summary>
+    /// 创建 AITeam 对象（GroupChat）
+    /// </summary>
+    /// <typeparam name="TFromAgent"></typeparam>
+    /// <param name="graphConnector"></param>
+    /// <param name="orchestrator"></param>
+    /// <returns></returns>
+    public static GroupChat CreateAiTeam<TFromAgent>(this GraphConnector graphConnector, IOrchestrator orchestrator)
+        where TFromAgent : IAgent
+    {
+        var aiTeam = new GroupChat(
+            members: graphConnector.Agents.Values,
+            orchestrator: orchestrator//,
+           /* workflow: graphConnector.Graph*/);
+        return aiTeam;
+    }
+
     #endregion
 }