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
22 lines
696 B
C#
22 lines
696 B
C#
using FluentValidation;
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namespace RAG.Application.Embedding.Validators;
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public class EmbedTextCommandValidator : AbstractValidator<Commands.EmbedTextCommand>
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{
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public EmbedTextCommandValidator()
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{
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RuleFor(x => x.Text).NotEmpty().WithMessage("文本内容不能为空")
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.MaximumLength(10000).WithMessage("单条文本不能超过10000个字符");
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}
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}
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public class EmbedBatchCommandValidator : AbstractValidator<Commands.EmbedBatchCommand>
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{
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public EmbedBatchCommandValidator()
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{
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RuleFor(x => x.Texts).NotEmpty().WithMessage("文本列表不能为空")
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.Must(t => t.Count <= 100).WithMessage("批量文本不能超过100条");
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}
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}
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