67b030c3c5
- AI chat with SSE streaming (Microsoft Agent Framework + Qwen) - RAG Q&A with hybrid retrieval (vector + keyword RRF fusion) - Knowledge base CRUD with semantic text chunking - Embedding generation via Azure.AI.OpenAI / LM Studio - Document upload with chunked upload support - Redis caching for chat messages - Chunk/vector preview endpoints - gRPC auth service improvements - Removed demo menus, cleaned up seed data
47 lines
1.8 KiB
C#
47 lines
1.8 KiB
C#
using Microsoft.EntityFrameworkCore;
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using Microsoft.Extensions.Configuration;
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using Microsoft.Extensions.DependencyInjection;
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using Pgvector.EntityFrameworkCore;
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using RAG.Domain;
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using RAG.Domain.Interfaces;
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using RAG.Infrastructure.AI;
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using RAG.Infrastructure.Cache;
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using RAG.Infrastructure.Messaging;
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using RAG.Infrastructure.Persistence;
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using RAG.Infrastructure.Persistence.Interceptors;
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using Volo.Abp.Modularity;
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namespace RAG.Infrastructure;
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/// <summary>
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/// Infrastructure 层模块，注册数据库上下文、审计拦截器、Redis 缓存、RabbitMQ 消息队列。
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/// 原 DependencyInjection.cs 的内容迁移至此。
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/// </summary>
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[DependsOn(typeof(RAGDomainModule))]
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public class RAGInfrastructureModule : AbpModule
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{
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public override void ConfigureServices(ServiceConfigurationContext context)
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{
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var services = context.Services;
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var config = services.GetConfiguration();
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// DbContext 挂载审计拦截器，拦截器从 DI 容器解析 ICurrentUserContext
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services.AddDbContext<RagDbContext>((sp, options) =>
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options.UseNpgsql(config.GetConnectionString("Default"), o => o.UseVector())
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.AddInterceptors(sp.GetRequiredService<AuditInterceptor>()));
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// Scoped 生命周期：每个 HTTP 请求创建一个拦截器实例，确保 ICurrentUserContext 正确获取当前用户
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services.AddScoped<AuditInterceptor>();
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services.AddRedisCache(config);
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services.AddRabbitMq(config);
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// AI 服务注册
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services.Configure<AiOptions>(config.GetSection(AiOptions.SectionName));
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services.AddScoped<IAIChatAgent, ChatAgentService>();
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services.AddScoped<IEmbeddingService, EmbeddingService>();
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services.AddScoped<ITextChunker, TextChunker>();
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services.AddSingleton<IChatMessageCache, ChatMessageCache>();
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}
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}
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