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feat: 新增向量嵌入服务支持

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新增SiliconFlow向量嵌入服务实现，支持文本向量化功能：
- 新增ITextEmbeddingService接口和SiliconFlowTextEmbeddingService实现
- 新增EmbeddingCreateRequest/Response等向量相关DTO
- 在AiGateWayManager中新增EmbeddingForStatisticsAsync方法
- 在OpenApiService中新增向量生成API接口
- 扩展ModelTypeEnum枚举支持Embedding类型
- 优化ThorChatMessage的Content属性处理逻辑
This commit is contained in:
chenchun
2025-08-11 15:29:24 +08:00
parent bbe5b01872
commit 25eebec8f7
11 changed files with 405 additions and 21 deletions
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79
Yi.Abp.Net8/module/ai-hub/Yi.Framework.AiHub.Application.Contracts/Dtos/OpenAi/Embeddings/EmbeddingCreateRequest.cs Normal file
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@@ -0,0 +1,79 @@
using System.ComponentModel.DataAnnotations;
using System.Text.Json.Serialization;
namespace Yi.Framework.AiHub.Application.Contracts.Dtos.OpenAi.Embeddings;
//TODO add model validation
//TODO check what is string or array for prompt,..
public record EmbeddingCreateRequest
{
/// <summary>
/// Input text to get embeddings for, encoded as a string or array of tokens. To get embeddings for multiple inputs
/// in a single request, pass an array of strings or array of token arrays. Each input must not exceed 2048 tokens in
/// length.
/// Unless your are embedding code, we suggest replacing newlines (`\n`) in your input with a single space, as we have
/// observed inferior results when newlines are present.
/// </summary>
/// <see href="https://platform.openai.com/docs/api-reference/embeddings/create#embeddings/create-input" />
[JsonIgnore]
public List<string>? InputAsList { get; set; }
/// <summary>
/// Input text to get embeddings for, encoded as a string or array of tokens. To get embeddings for multiple inputs
/// in a single request, pass an array of strings or array of token arrays. Each input must not exceed 2048 tokens in
/// length.
/// Unless your are embedding code, we suggest replacing newlines (`\n`) in your input with a single space, as we have
/// observed inferior results when newlines are present.
/// </summary>
/// <see href="https://platform.openai.com/docs/api-reference/embeddings/create#embeddings/create-input" />
[JsonIgnore]
public string? Input { get; set; }
[JsonPropertyName("input")]
public IList<string>? InputCalculated
{
get
{
if (Input != null && InputAsList != null)
{
throw new ValidationException(
"Input and InputAsList can not be assigned at the same time. One of them is should be null.");
}
if (Input != null)
{
return new List<string> { Input };
}
return InputAsList;
}
}
/// <summary>
/// ID of the model to use. You can use the [List models](/docs/api-reference/models/list) API to see all of your
/// available models, or see our [Model overview](/docs/models/overview) for descriptions of them.
/// </summary>
/// <see href="https://platform.openai.com/docs/api-reference/embeddings/create#embeddings/create-model" />
[JsonPropertyName("model")]
public string? Model { get; set; }
/// <summary>
/// The number of dimensions the resulting output embeddings should have. Only supported in text-embedding-3 and later models.
/// </summary>
/// <see href="https://platform.openai.com/docs/api-reference/embeddings/create#embeddings-create-dimensions" />
[JsonPropertyName("dimensions")]
public int? Dimensions { get; set; }
/// <summary>
/// The format to return the embeddings in. Can be either float or base64.
/// </summary>
/// <returns></returns>
[JsonPropertyName("encoding_format")]
public string? EncodingFormat { get; set; }
public IEnumerable<ValidationResult> Validate()
{
throw new NotImplementedException();
}
}

111
Yi.Abp.Net8/module/ai-hub/Yi.Framework.AiHub.Application.Contracts/Dtos/OpenAi/Embeddings/EmbeddingCreateResponse.cs Normal file
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@@ -0,0 +1,111 @@
using System.Buffers;
using System.Text.Json;
using System.Text.Json.Serialization;
namespace Yi.Framework.AiHub.Application.Contracts.Dtos.OpenAi.Embeddings;
public record EmbeddingCreateResponse : ThorBaseResponse
{
[JsonPropertyName("model")] public string Model { get; set; }
[JsonPropertyName("data")] public List<EmbeddingResponse> Data { get; set; } = [];
/// <summary>
/// 类型转换，如果类型是base64,则将float[]转换为base64,如果是空或是float和原始类型一样，则不转换
/// </summary>
public void ConvertEmbeddingData(string? encodingFormat)
{
if (Data.Count == 0)
{
return;
}
switch (encodingFormat)
{
// 判断第一个是否是float[]，如果是则不转换
case null or "float" when Data[0].Embedding is float[]:
return;
// 否则转换成float[]
case null or "float":
{
foreach (var embeddingResponse in Data)
{
if (embeddingResponse.Embedding is string base64)
{
embeddingResponse.Embedding = Convert.FromBase64String(base64);
}
}
return;
}
// 判断第一个是否是string，如果是则不转换
case "base64" when Data[0].Embedding is string:
return;
// 否则转换成base64
case "base64":
{
foreach (var embeddingResponse in Data)
{
if (embeddingResponse.Embedding is JsonElement str)
{
if (str.ValueKind == JsonValueKind.Array)
{
var floats = str.EnumerateArray().Select(element => element.GetSingle()).ToArray();
embeddingResponse.Embedding = ConvertFloatArrayToBase64(floats);
}
}
else if (embeddingResponse.Embedding is IList<double> doubles)
{
embeddingResponse.Embedding = ConvertFloatArrayToBase64(doubles.ToArray());
}
}
break;
}
}
}
public static string ConvertFloatArrayToBase64(double[] floatArray)
{
// 将 float[] 转换成 byte[]
byte[] byteArray = ArrayPool<byte>.Shared.Rent(floatArray.Length * sizeof(float));
try
{
Buffer.BlockCopy(floatArray, 0, byteArray, 0, byteArray.Length);
// 将 byte[] 转换成 base64 字符串
return Convert.ToBase64String(byteArray);
}
finally
{
ArrayPool<byte>.Shared.Return(byteArray);
}
}
public static string ConvertFloatArrayToBase64(float[] floatArray)
{
// 将 float[] 转换成 byte[]
byte[] byteArray = ArrayPool<byte>.Shared.Rent(floatArray.Length * sizeof(float));
try
{
Buffer.BlockCopy(floatArray, 0, byteArray, 0, floatArray.Length);
// 将 byte[] 转换成 base64 字符串
return Convert.ToBase64String(byteArray);
}
finally
{
ArrayPool<byte>.Shared.Return(byteArray);
}
}
[JsonPropertyName("usage")] public ThorUsageResponse? Usage { get; set; }
}
public record EmbeddingResponse
{
[JsonPropertyName("index")] public int? Index { get; set; }
[JsonPropertyName("embedding")] public object Embedding { get; set; }
}

22
Yi.Abp.Net8/module/ai-hub/Yi.Framework.AiHub.Application.Contracts/Dtos/OpenAi/Embeddings/ThorEmbeddingInput.cs Normal file
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@@ -0,0 +1,22 @@
using System.Text.Json.Serialization;
namespace Yi.Framework.AiHub.Application.Contracts.Dtos.OpenAi.Embeddings;
public sealed class ThorEmbeddingInput
{
[JsonPropertyName("model")]
public string Model { get; set; }
[JsonPropertyName("input")]
public object Input { get; set; }
[JsonPropertyName("encoding_format")]
public string EncodingFormat { get; set; }
[JsonPropertyName("dimensions")]
public int? Dimensions { get; set; }
[JsonPropertyName("user")]
public string? User { get; set; }
}

26
Yi.Abp.Net8/module/ai-hub/Yi.Framework.AiHub.Application.Contracts/Dtos/OpenAi/ThorChatMessage.cs
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@@ -14,7 +14,6 @@ public class ThorChatMessage
/// </summary>
public ThorChatMessage()
{
}
/// <summary>
@@ -74,20 +73,19 @@ public class ThorChatMessage
{
if (value is JsonElement str)
{
if (str.ValueKind == JsonValueKind.String)
{
Content = value?.ToString();
}
else if (str.ValueKind == JsonValueKind.Array)
if (str.ValueKind == JsonValueKind.Array)
{
Contents = JsonSerializer.Deserialize<IList<ThorChatMessageContent>>(value?.ToString());
}
}
else if (value is string strInput)
{
Content = strInput;
}
else
{
Content = value?.ToString();
}
}
}
@@ -108,15 +106,14 @@ public class ThorChatMessage
/// </summary>
[JsonPropertyName("function_call")]
public ThorChatMessageFunction? FunctionCall { get; set; }
/// <summary>
/// 【可选】推理内容
/// </summary>
[JsonPropertyName("reasoning_content")]
public string? ReasoningContent { get; set; }
[JsonPropertyName("id")]
public string? Id { get; set; }
[JsonPropertyName("id")] public string? Id { get; set; }
/// <summary>
/// 工具调用列表，模型生成的工具调用，例如函数调用。<br/>
@@ -164,14 +161,15 @@ public class ThorChatMessage
/// <param name="name">参与者的可选名称。提供模型信息以区分同一角色的参与者。</param>
/// <param name="toolCalls">工具调用参数列表</param>
/// <returns></returns>
public static ThorChatMessage CreateAssistantMessage(string content, string? name = null, List<ThorToolCall> toolCalls = null)
public static ThorChatMessage CreateAssistantMessage(string content, string? name = null,
List<ThorToolCall> toolCalls = null)
{
return new()
{
Role = ThorChatMessageRoleConst.Assistant,
Content = content,
Name = name,
ToolCalls=toolCalls,
ToolCalls = toolCalls,
};
}
@@ -187,7 +185,7 @@ public class ThorChatMessage
{
Role = ThorChatMessageRoleConst.Tool,
Content = content,
ToolCallId= toolCallId
ToolCallId = toolCallId
};
}
}