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feat：【ai 大模型】增加 anthropic 接入

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This commit is contained in:
YunaiV
2025-08-21 23:26:20 +08:00
parent 2fbb9f8893
commit 96a743157d
7 changed files with 98 additions and 3 deletions
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1
yudao-module-ai/src/main/java/cn/iocoder/yudao/module/ai/enums/model/AiPlatformEnum.java
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@@ -33,6 +33,7 @@ public enum AiPlatformEnum implements ArrayValuable<String> {
OPENAI("OpenAI", "OpenAI"), // OpenAI 官方
AZURE_OPENAI("AzureOpenAI", "AzureOpenAI"), // OpenAI 微软
ANTHROPIC("Anthropic", "Anthropic"), // Anthropic Claude
OLLAMA("Ollama", "Ollama"),
STABLE_DIFFUSION("StableDiffusion", "StableDiffusion"), // Stability AI

22
yudao-module-ai/src/main/java/cn/iocoder/yudao/module/ai/framework/ai/core/AiModelFactoryImpl.java
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@@ -67,6 +67,7 @@ import org.springframework.ai.minimax.MiniMaxChatOptions;
import org.springframework.ai.minimax.MiniMaxEmbeddingModel;
import org.springframework.ai.minimax.MiniMaxEmbeddingOptions;
import org.springframework.ai.minimax.api.MiniMaxApi;
import org.springframework.ai.model.anthropic.autoconfigure.AnthropicChatAutoConfiguration;
import org.springframework.ai.model.azure.openai.autoconfigure.AzureOpenAiChatAutoConfiguration;
import org.springframework.ai.model.azure.openai.autoconfigure.AzureOpenAiEmbeddingAutoConfiguration;
import org.springframework.ai.model.azure.openai.autoconfigure.AzureOpenAiEmbeddingProperties;
@@ -93,6 +94,8 @@ import org.springframework.ai.openai.OpenAiImageModel;
import org.springframework.ai.openai.api.OpenAiApi;
import org.springframework.ai.openai.api.OpenAiImageApi;
import org.springframework.ai.openai.api.common.OpenAiApiConstants;
import org.springframework.ai.anthropic.AnthropicChatModel;
import org.springframework.ai.anthropic.api.AnthropicApi;
import org.springframework.ai.stabilityai.StabilityAiImageModel;
import org.springframework.ai.stabilityai.api.StabilityAiApi;
import org.springframework.ai.vectorstore.SimpleVectorStore;
@@ -168,6 +171,8 @@ public class AiModelFactoryImpl implements AiModelFactory {
return buildOpenAiChatModel(apiKey, url);
case AZURE_OPENAI:
return buildAzureOpenAiChatModel(apiKey, url);
case ANTHROPIC:
return buildAnthropicChatModel(apiKey, url);
case OLLAMA:
return buildOllamaChatModel(url);
default:
@@ -206,6 +211,8 @@ public class AiModelFactoryImpl implements AiModelFactory {
return SpringUtil.getBean(OpenAiChatModel.class);
case AZURE_OPENAI:
return SpringUtil.getBean(AzureOpenAiChatModel.class);
case ANTHROPIC:
return SpringUtil.getBean(AnthropicChatModel.class);
case OLLAMA:
return SpringUtil.getBean(OllamaChatModel.class);
default:
@@ -512,6 +519,21 @@ public class AiModelFactoryImpl implements AiModelFactory {
.build();
}
/**
* 可参考 {@link AnthropicChatAutoConfiguration} 的 anthropicApi 方法
*/
private static AnthropicChatModel buildAnthropicChatModel(String apiKey, String url) {
AnthropicApi.Builder builder = AnthropicApi.builder().apiKey(apiKey);
if (StrUtil.isNotEmpty(url)) {
builder.baseUrl(url);
}
AnthropicApi anthropicApi = builder.build();
return AnthropicChatModel.builder()
.anthropicApi(anthropicApi)
.toolCallingManager(getToolCallingManager())
.build();
}
/**
* 可参考 {@link OpenAiImageAutoConfiguration} 的 openAiImageModel 方法
*/

4
yudao-module-ai/src/main/java/cn/iocoder/yudao/module/ai/util/AiUtils.java
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@@ -8,6 +8,7 @@ import cn.iocoder.yudao.module.ai.enums.model.AiPlatformEnum;
import com.alibaba.cloud.ai.dashscope.chat.DashScopeChatOptions;
import org.springaicommunity.moonshot.MoonshotChatOptions;
import org.springaicommunity.qianfan.QianFanChatOptions;
import org.springframework.ai.anthropic.AnthropicChatOptions;
import org.springframework.ai.azure.openai.AzureOpenAiChatOptions;
import org.springframework.ai.chat.messages.*;
import org.springframework.ai.chat.prompt.ChatOptions;
@@ -67,6 +68,9 @@ public class AiUtils {
case AZURE_OPENAI:
return AzureOpenAiChatOptions.builder().deploymentName(model).temperature(temperature).maxTokens(maxTokens)
.toolNames(toolNames).toolContext(toolContext).build();
case ANTHROPIC:
return AnthropicChatOptions.builder().model(model).temperature(temperature).maxTokens(maxTokens)
.toolNames(toolNames).toolContext(toolContext).build();
case OLLAMA:
return OllamaOptions.builder().model(model).temperature(temperature).numPredict(maxTokens)
.toolNames(toolNames).toolContext(toolContext).build();