feat: 支持Claude模型API类型及尊享包校验与扣减逻辑
This commit is contained in:
ccnetcore
@@ -0,0 +1,861 @@
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using System.Diagnostics;
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using System.Net;
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using System.Net.Http.Json;
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using System.Text.Json;
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using Microsoft.Extensions.Logging;
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using Yi.Framework.AiHub.Domain.Shared.Dtos;
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using Yi.Framework.AiHub.Domain.Shared.Dtos.Anthropic;
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using Yi.Framework.AiHub.Domain.Shared.Dtos.OpenAi;
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namespace Yi.Framework.AiHub.Domain.AiGateWay.Impl.ThorClaude.Chats;
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public sealed class ClaudiaChatCompletionsService(
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IHttpClientFactory httpClientFactory,
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ILogger<ClaudiaChatCompletionsService> logger)
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: IChatCompletionService
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{
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public List<ThorChatChoiceResponse> CreateResponse(AnthropicChatCompletionDto completionDto)
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{
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var response = new ThorChatChoiceResponse();
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var chatMessage = new ThorChatMessage();
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if (completionDto == null)
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{
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return new List<ThorChatChoiceResponse>();
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}
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if (completionDto.content.Any(x => x.type.Equals("thinking", StringComparison.OrdinalIgnoreCase)))
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{
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// 将推理字段合并到返回对象去
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chatMessage.ReasoningContent = completionDto.content
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.First(x => x.type.Equals("thinking", StringComparison.OrdinalIgnoreCase)).Thinking;
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chatMessage.Role = completionDto.role;
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chatMessage.Content = completionDto.content
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.First(x => x.type.Equals("text", StringComparison.OrdinalIgnoreCase)).text;
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}
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else
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{
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chatMessage.Role = completionDto.role;
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chatMessage.Content = completionDto.content
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.FirstOrDefault()?.text;
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}
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response.Delta = chatMessage;
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response.Message = chatMessage;
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if (completionDto.content.Any(x => x.type.Equals("tool_use", StringComparison.OrdinalIgnoreCase)))
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{
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var toolUse = completionDto.content
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.First(x => x.type.Equals("tool_use", StringComparison.OrdinalIgnoreCase));
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chatMessage.ToolCalls =
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[
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new()
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{
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Id = toolUse.id,
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Function = new ThorChatMessageFunction()
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{
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Name = toolUse.name,
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Arguments = JsonSerializer.Serialize(toolUse.input,
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ThorJsonSerializer.DefaultOptions),
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},
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Index = 0,
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}
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];
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return
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[
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response
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];
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}
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return new List<ThorChatChoiceResponse> { response };
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}
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private object CreateMessage(List<ThorChatMessage> messages, AiModelDescribe options)
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{
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var list = new List<object>();
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foreach (var message in messages)
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{
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// 如果是图片
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if (message.ContentCalculated is IList<ThorChatMessageContent> contentCalculated)
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{
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list.Add(new
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{
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role = message.Role,
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content = (List<object>)contentCalculated.Select<ThorChatMessageContent, object>(x =>
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{
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if (x.Type == "text")
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{
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if ("true".Equals(options.ModelExtraInfo, StringComparison.OrdinalIgnoreCase))
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{
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return new
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{
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type = "text",
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text = x.Text,
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cache_control = new
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{
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type = "ephemeral"
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}
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};
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}
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return new
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{
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type = "text",
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text = x.Text
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};
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}
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var isBase64 = x.ImageUrl?.Url.StartsWith("http") == true;
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if ("true".Equals(options.ModelExtraInfo, StringComparison.OrdinalIgnoreCase))
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{
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return new
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{
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type = "image",
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source = new
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{
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type = isBase64 ? "base64" : "url",
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media_type = "image/png",
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data = x.ImageUrl?.Url,
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},
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cache_control = new
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{
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type = "ephemeral"
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}
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};
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}
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return new
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{
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type = "image",
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source = new
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{
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type = isBase64 ? "base64" : "url",
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media_type = "image/png",
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data = x.ImageUrl?.Url,
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}
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};
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})
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});
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}
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else
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{
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if ("true".Equals(options.ModelExtraInfo, StringComparison.OrdinalIgnoreCase))
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{
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if (message.Role == "system")
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{
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list.Add(new
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{
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type = "text",
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text = message.Content,
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cache_control = new
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{
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type = "ephemeral"
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}
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});
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}
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else
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{
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list.Add(new
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{
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role = message.Role,
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content = message.Content
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});
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}
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}
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else
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{
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if (message.Role == "system")
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{
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list.Add(new
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{
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type = "text",
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text = message.Content
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});
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}
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else if (message.Role == "tool")
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{
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list.Add(new
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{
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role = "user",
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content = new List<object>
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{
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new
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{
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type = "tool_result",
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tool_use_id = message.ToolCallId,
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content = message.Content
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}
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}
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});
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}
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else if (message.Role == "assistant")
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{
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// {
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// "role": "assistant",
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// "content": [
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// {
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// "type": "text",
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// "text": "<thinking>I need to use get_weather, and the user wants SF, which is likely San Francisco, CA.</thinking>"
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// },
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// {
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// "type": "tool_use",
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// "id": "toolu_01A09q90qw90lq917835lq9",
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// "name": "get_weather",
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// "input": {
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// "location": "San Francisco, CA",
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// "unit": "celsius"
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// }
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// }
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// ]
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// },
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if (message.ToolCalls?.Count > 0)
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{
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var content = new List<object>();
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if (!string.IsNullOrEmpty(message.Content))
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{
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content.Add(new
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{
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type = "text",
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text = message.Content
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});
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}
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foreach (var toolCall in message.ToolCalls)
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{
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content.Add(new
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{
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type = "tool_use",
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id = toolCall.Id,
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name = toolCall.Function?.Name,
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input = JsonSerializer.Deserialize<Dictionary<string, object>>(
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toolCall.Function?.Arguments, ThorJsonSerializer.DefaultOptions)
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});
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}
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list.Add(new
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{
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role = "assistant",
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content
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});
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}
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else
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{
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list.Add(new
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{
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role = "assistant",
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content = new List<object>
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{
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new
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{
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type = "text",
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text = message.Content
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}
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}
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});
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}
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}
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else
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{
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list.Add(new
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{
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role = message.Role,
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content = message.Content
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});
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}
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}
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}
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}
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return list;
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}
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public async IAsyncEnumerable<ThorChatCompletionsResponse> CompleteChatStreamAsync(AiModelDescribe options,
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ThorChatCompletionsRequest input,
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CancellationToken cancellationToken)
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{
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using var openai =
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Activity.Current?.Source.StartActivity("Claudia 对话补全");
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if (string.IsNullOrEmpty(options.Endpoint))
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{
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options.Endpoint = "https://api.anthropic.com/";
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}
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var client = httpClientFactory.CreateClient();
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var headers = new Dictionary<string, string>
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{
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{ "x-api-key", options.ApiKey },
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{ "anthropic-version", "2023-06-01" }
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};
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var isThinking = input.Model.EndsWith("thinking");
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input.Model = input.Model.Replace("-thinking", string.Empty);
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var budgetTokens = 1024;
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if (input.MaxTokens is < 2048)
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{
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input.MaxTokens = 2048;
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}
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if (input.MaxTokens != null && input.MaxTokens / 2 < 1024)
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{
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budgetTokens = input.MaxTokens.Value / (4 * 3);
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}
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// budgetTokens最大4096
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budgetTokens = Math.Min(budgetTokens, 4096);
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object tool_choice;
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if (input.ToolChoice is not null && input.ToolChoice.Type == "auto")
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{
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tool_choice = new
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{
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type = "auto",
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disable_parallel_tool_use = false,
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};
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}
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else if (input.ToolChoice is not null && input.ToolChoice.Type == "any")
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{
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tool_choice = new
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{
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type = "any",
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disable_parallel_tool_use = false,
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};
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}
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else if (input.ToolChoice is not null && input.ToolChoice.Type == "tool")
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{
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tool_choice = new
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{
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type = "tool",
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name = input.ToolChoice.Function?.Name,
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disable_parallel_tool_use = false,
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};
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}
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else
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{
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tool_choice = null;
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}
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var response = await client.HttpRequestRaw(options.Endpoint.TrimEnd('/') + "/v1/messages", new
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{
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model = input.Model,
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max_tokens = input.MaxTokens ?? 2048,
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stream = true,
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tool_choice,
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system = CreateMessage(input.Messages.Where(x => x.Role == "system").ToList(), options),
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messages = CreateMessage(input.Messages.Where(x => x.Role != "system").ToList(), options),
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top_p = isThinking ? null : input.TopP,
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thinking = isThinking
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? new
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{
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type = "enabled",
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budget_tokens = budgetTokens,
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}
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: null,
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tools = input.Tools?.Select(x => new
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{
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name = x.Function?.Name,
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description = x.Function?.Description,
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input_schema = new
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{
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type = x.Function?.Parameters?.Type,
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required = x.Function?.Parameters?.Required,
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properties = x.Function?.Parameters?.Properties?.ToDictionary(y => y.Key, y => new
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{
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description = y.Value.Description,
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type = y.Value.Type,
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@enum = y.Value.Enum
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})
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}
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}).ToArray(),
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temperature = isThinking ? null : input.Temperature
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}, string.Empty, headers);
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openai?.SetTag("Model", input.Model);
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openai?.SetTag("Response", response.StatusCode.ToString());
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// 大于等于400的状态码都认为是异常
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if (response.StatusCode >= HttpStatusCode.BadRequest)
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{
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var error = await response.Content.ReadAsStringAsync(cancellationToken).ConfigureAwait(false);
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logger.LogError("OpenAI对话异常 请求地址：{Address}, StatusCode: {StatusCode} Response: {Response}",
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options.Endpoint,
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response.StatusCode, error);
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throw new Exception("OpenAI对话异常" + response.StatusCode);
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}
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using var stream = new StreamReader(await response.Content.ReadAsStreamAsync(cancellationToken));
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using StreamReader reader = new(await response.Content.ReadAsStreamAsync(cancellationToken));
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string? line = string.Empty;
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var first = true;
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var isThink = false;
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string? toolId = null;
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string? toolName = null;
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while ((line = await reader.ReadLineAsync(cancellationToken).ConfigureAwait(false)) != null)
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{
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line += Environment.NewLine;
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if (line.StartsWith('{'))
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{
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logger.LogInformation("OpenAI对话异常 , StatusCode: {StatusCode} Response: {Response}", response.StatusCode,
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line);
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throw new Exception("OpenAI对话异常" + line);
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}
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if (line.StartsWith(OpenAIConstant.Data))
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line = line[OpenAIConstant.Data.Length..];
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line = line.Trim();
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if (string.IsNullOrWhiteSpace(line)) continue;
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if (line == OpenAIConstant.Done)
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{
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break;
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}
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if (line.StartsWith(':'))
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{
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continue;
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}
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if (line.StartsWith("event: ", StringComparison.OrdinalIgnoreCase))
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{
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continue;
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}
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var result = JsonSerializer.Deserialize<AnthropicStreamDto>(line,
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ThorJsonSerializer.DefaultOptions);
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if (result?.Type == "content_block_delta")
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{
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if (result.Delta.Type is "text" or "text_delta")
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{
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yield return new ThorChatCompletionsResponse()
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{
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Choices =
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[
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new()
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{
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Message = new ThorChatMessage()
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{
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Content = result.Delta.Text,
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Role = "assistant",
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}
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}
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],
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Model = input.Model,
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Id = result?.Message?.id,
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Usage = new ThorUsageResponse()
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{
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CompletionTokens = result?.Message?.Usage?.OutputTokens,
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PromptTokens = result?.Message?.Usage?.InputTokens,
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}
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};
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}
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else if (result.Delta.Type == "input_json_delta")
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{
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yield return new ThorChatCompletionsResponse()
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{
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Choices =
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[
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new ThorChatChoiceResponse()
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{
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Message = new ThorChatMessage()
|
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{
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ToolCalls =
|
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[
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new ThorToolCall()
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{
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Id = toolId,
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Function = new ThorChatMessageFunction()
|
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{
|
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Name = toolName,
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Arguments = result.Delta.PartialJson
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}
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}
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],
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Role = "tool",
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}
|
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}
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],
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Model = input.Model,
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Usage = new ThorUsageResponse()
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{
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PromptTokens = result?.Message?.Usage?.InputTokens,
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}
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};
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}
|
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else
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{
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yield return new ThorChatCompletionsResponse()
|
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{
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Choices = new List<ThorChatChoiceResponse>()
|
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{
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new()
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{
|
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Message = new ThorChatMessage()
|
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{
|
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ReasoningContent = result.Delta.Thinking,
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Role = "assistant",
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}
|
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}
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},
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Model = input.Model,
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Id = result?.Message?.id,
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Usage = new ThorUsageResponse()
|
||||
{
|
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CompletionTokens = result?.Message?.Usage?.OutputTokens,
|
||||
PromptTokens = result?.Message?.Usage?.InputTokens
|
||||
}
|
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};
|
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}
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continue;
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}
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|
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if (result?.Type == "content_block_start")
|
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{
|
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if (result?.ContentBlock?.Id is not null)
|
||||
{
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toolId = result.ContentBlock.Id;
|
||||
}
|
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|
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if (result?.ContentBlock?.Name is not null)
|
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{
|
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toolName = result.ContentBlock.Name;
|
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}
|
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|
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yield return new ThorChatCompletionsResponse()
|
||||
{
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Choices =
|
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[
|
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new ThorChatChoiceResponse()
|
||||
{
|
||||
Message = new ThorChatMessage()
|
||||
{
|
||||
ToolCalls =
|
||||
[
|
||||
new ThorToolCall()
|
||||
{
|
||||
Id = toolId,
|
||||
Function = new ThorChatMessageFunction()
|
||||
{
|
||||
Name = toolName
|
||||
}
|
||||
}
|
||||
],
|
||||
Role = "tool",
|
||||
}
|
||||
}
|
||||
],
|
||||
Model = input.Model,
|
||||
Usage = new ThorUsageResponse()
|
||||
{
|
||||
PromptTokens = result?.Message?.Usage?.InputTokens,
|
||||
}
|
||||
};
|
||||
}
|
||||
|
||||
if (result.Type == "content_block_delta")
|
||||
{
|
||||
yield return new ThorChatCompletionsResponse()
|
||||
{
|
||||
Choices =
|
||||
[
|
||||
new ThorChatChoiceResponse()
|
||||
{
|
||||
Message = new ThorChatMessage()
|
||||
{
|
||||
ToolCallId = result?.ContentBlock?.Id,
|
||||
FunctionCall = new ThorChatMessageFunction()
|
||||
{
|
||||
Name = result?.ContentBlock?.Name,
|
||||
Arguments = result?.Delta?.PartialJson
|
||||
},
|
||||
Role = "tool",
|
||||
}
|
||||
}
|
||||
],
|
||||
Model = input.Model,
|
||||
Usage = new ThorUsageResponse()
|
||||
{
|
||||
PromptTokens = result?.Message?.Usage?.InputTokens,
|
||||
}
|
||||
};
|
||||
continue;
|
||||
}
|
||||
|
||||
if (result.Type == "message_start")
|
||||
{
|
||||
yield return new ThorChatCompletionsResponse()
|
||||
{
|
||||
Choices =
|
||||
[
|
||||
new ThorChatChoiceResponse()
|
||||
{
|
||||
Message = new ThorChatMessage()
|
||||
{
|
||||
Content = result?.Delta?.Text,
|
||||
Role = "assistant",
|
||||
}
|
||||
}
|
||||
],
|
||||
Model = input.Model,
|
||||
Usage = new ThorUsageResponse()
|
||||
{
|
||||
PromptTokens = result?.Message?.Usage?.InputTokens,
|
||||
}
|
||||
};
|
||||
|
||||
continue;
|
||||
}
|
||||
|
||||
if (result.Type == "message_delta")
|
||||
{
|
||||
yield return new ThorChatCompletionsResponse()
|
||||
{
|
||||
Choices =
|
||||
[
|
||||
new ThorChatChoiceResponse()
|
||||
{
|
||||
Message = new ThorChatMessage()
|
||||
{
|
||||
Content = result.Delta?.Text,
|
||||
Role = "assistant",
|
||||
}
|
||||
}
|
||||
],
|
||||
Model = input.Model,
|
||||
Usage = new ThorUsageResponse()
|
||||
{
|
||||
CompletionTokens = result.Usage?.OutputTokens,
|
||||
InputTokens = result.Usage?.InputTokens
|
||||
}
|
||||
};
|
||||
|
||||
continue;
|
||||
}
|
||||
|
||||
if (result.Message == null)
|
||||
{
|
||||
continue;
|
||||
}
|
||||
|
||||
var chat = CreateResponse(result.Message);
|
||||
|
||||
var content = chat?.FirstOrDefault()?.Delta;
|
||||
|
||||
if (first && string.IsNullOrWhiteSpace(content?.Content) && string.IsNullOrEmpty(content?.ReasoningContent))
|
||||
{
|
||||
continue;
|
||||
}
|
||||
|
||||
if (first && content.Content == OpenAIConstant.ThinkStart)
|
||||
{
|
||||
isThink = true;
|
||||
continue;
|
||||
// 需要将content的内容转换到其他字段
|
||||
}
|
||||
|
||||
if (isThink && content.Content.Contains(OpenAIConstant.ThinkEnd))
|
||||
{
|
||||
isThink = false;
|
||||
// 需要将content的内容转换到其他字段
|
||||
continue;
|
||||
}
|
||||
|
||||
if (isThink)
|
||||
{
|
||||
// 需要将content的内容转换到其他字段
|
||||
foreach (var choice in chat)
|
||||
{
|
||||
choice.Delta.ReasoningContent = choice.Delta.Content;
|
||||
choice.Delta.Content = string.Empty;
|
||||
}
|
||||
}
|
||||
|
||||
first = false;
|
||||
|
||||
yield return new ThorChatCompletionsResponse()
|
||||
{
|
||||
Choices = chat,
|
||||
Model = input.Model,
|
||||
Id = result.Message.id,
|
||||
Usage = new ThorUsageResponse()
|
||||
{
|
||||
CompletionTokens = result.Message.Usage?.OutputTokens,
|
||||
PromptTokens = result.Message.Usage?.InputTokens,
|
||||
InputTokens = result.Message.Usage?.InputTokens,
|
||||
OutputTokens = result.Message.Usage?.OutputTokens,
|
||||
TotalTokens = result.Message.Usage?.InputTokens + result.Message.Usage?.OutputTokens
|
||||
}
|
||||
};
|
||||
}
|
||||
}
|
||||
|
||||
public async Task<ThorChatCompletionsResponse> CompleteChatAsync(AiModelDescribe options,
|
||||
ThorChatCompletionsRequest input,
|
||||
CancellationToken cancellationToken)
|
||||
{
|
||||
using var openai =
|
||||
Activity.Current?.Source.StartActivity("Claudia 对话补全");
|
||||
|
||||
if (string.IsNullOrEmpty(options.Endpoint))
|
||||
{
|
||||
options.Endpoint = "https://api.anthropic.com/";
|
||||
}
|
||||
|
||||
var client = httpClientFactory.CreateClient();
|
||||
|
||||
var headers = new Dictionary<string, string>
|
||||
{
|
||||
{ "x-api-key", options.ApiKey },
|
||||
{ "anthropic-version", "2023-06-01" }
|
||||
};
|
||||
|
||||
bool isThink = input.Model.EndsWith("-thinking");
|
||||
input.Model = input.Model.Replace("-thinking", string.Empty);
|
||||
|
||||
var budgetTokens = 1024;
|
||||
if (input.MaxTokens is < 2048)
|
||||
{
|
||||
input.MaxTokens = 2048;
|
||||
}
|
||||
|
||||
if (input.MaxTokens != null && input.MaxTokens / 2 < 1024)
|
||||
{
|
||||
budgetTokens = input.MaxTokens.Value / (4 * 3);
|
||||
}
|
||||
|
||||
object tool_choice;
|
||||
if (input.ToolChoice is not null && input.ToolChoice.Type == "auto")
|
||||
{
|
||||
tool_choice = new
|
||||
{
|
||||
type = "auto",
|
||||
disable_parallel_tool_use = false,
|
||||
};
|
||||
}
|
||||
else if (input.ToolChoice is not null && input.ToolChoice.Type == "any")
|
||||
{
|
||||
tool_choice = new
|
||||
{
|
||||
type = "any",
|
||||
disable_parallel_tool_use = false,
|
||||
};
|
||||
}
|
||||
else if (input.ToolChoice is not null && input.ToolChoice.Type == "tool")
|
||||
{
|
||||
tool_choice = new
|
||||
{
|
||||
type = "tool",
|
||||
name = input.ToolChoice.Function?.Name,
|
||||
disable_parallel_tool_use = false,
|
||||
};
|
||||
}
|
||||
else
|
||||
{
|
||||
tool_choice = null;
|
||||
}
|
||||
|
||||
// budgetTokens最大4096
|
||||
budgetTokens = Math.Min(budgetTokens, 4096);
|
||||
|
||||
var response = await client.PostJsonAsync(options.Endpoint.TrimEnd('/') + "/v1/messages", new
|
||||
{
|
||||
model = input.Model,
|
||||
max_tokens = input.MaxTokens ?? 2000,
|
||||
system = CreateMessage(input.Messages.Where(x => x.Role == "system").ToList(), options),
|
||||
messages = CreateMessage(input.Messages.Where(x => x.Role != "system").ToList(), options),
|
||||
top_p = isThink ? null : input.TopP,
|
||||
tool_choice,
|
||||
thinking = isThink
|
||||
? new
|
||||
{
|
||||
type = "enabled",
|
||||
budget_tokens = budgetTokens,
|
||||
}
|
||||
: null,
|
||||
tools = input.Tools?.Select(x => new
|
||||
{
|
||||
name = x.Function?.Name,
|
||||
description = x.Function?.Description,
|
||||
input_schema = new
|
||||
{
|
||||
type = x.Function?.Parameters?.Type,
|
||||
required = x.Function?.Parameters?.Required,
|
||||
properties = x.Function?.Parameters?.Properties?.ToDictionary(y => y.Key, y => new
|
||||
{
|
||||
description = y.Value.Description,
|
||||
type = y.Value.Type,
|
||||
@enum = y.Value.Enum
|
||||
})
|
||||
}
|
||||
}).ToArray(),
|
||||
temperature = isThink ? null : input.Temperature
|
||||
}, string.Empty, headers);
|
||||
|
||||
openai?.SetTag("Model", input.Model);
|
||||
openai?.SetTag("Response", response.StatusCode.ToString());
|
||||
|
||||
// 大于等于400的状态码都认为是异常
|
||||
if (response.StatusCode >= HttpStatusCode.BadRequest)
|
||||
{
|
||||
var error = await response.Content.ReadAsStringAsync(cancellationToken).ConfigureAwait(false);
|
||||
logger.LogError("OpenAI对话异常 请求地址：{Address}, StatusCode: {StatusCode} Response: {Response}",
|
||||
options.Endpoint,
|
||||
response.StatusCode, error);
|
||||
|
||||
throw new Exception("OpenAI对话异常" + response.StatusCode.ToString());
|
||||
}
|
||||
|
||||
var value =
|
||||
await response.Content.ReadFromJsonAsync<AnthropicChatCompletionDto>(ThorJsonSerializer.DefaultOptions,
|
||||
cancellationToken: cancellationToken);
|
||||
|
||||
var thor = new ThorChatCompletionsResponse()
|
||||
{
|
||||
Choices = CreateResponse(value),
|
||||
Model = input.Model,
|
||||
Id = value.id,
|
||||
Usage = new ThorUsageResponse()
|
||||
{
|
||||
CompletionTokens = value.Usage.OutputTokens,
|
||||
PromptTokens = value.Usage.InputTokens
|
||||
}
|
||||
};
|
||||
|
||||
if (value.Usage.CacheReadInputTokens != null)
|
||||
{
|
||||
thor.Usage.PromptTokensDetails ??= new ThorUsageResponsePromptTokensDetails()
|
||||
{
|
||||
CachedTokens = value.Usage.CacheReadInputTokens.Value,
|
||||
};
|
||||
|
||||
if (value.Usage.InputTokens > 0)
|
||||
{
|
||||
thor.Usage.InputTokens = value.Usage.InputTokens;
|
||||
}
|
||||
|
||||
if (value.Usage.OutputTokens > 0)
|
||||
{
|
||||
thor.Usage.CompletionTokens = value.Usage.OutputTokens;
|
||||
thor.Usage.OutputTokens = value.Usage.OutputTokens;
|
||||
}
|
||||
}
|
||||
|
||||
thor.Usage.TotalTokens = thor.Usage.InputTokens + thor.Usage.OutputTokens;
|
||||
return thor;
|
||||
}
|
||||
}
|
||||
Reference in New Issue
Block a user