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update

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This commit is contained in:
jack ning
2025-08-21 13:08:37 +08:00
parent 178269de40
commit f6f6bb13be
21 changed files with 1381 additions and 918 deletions
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41
modules/ai/src/main/java/com/bytedesk/ai/springai/providers/baidu/SpringAIBaiduService.java
View File

@@ -2,7 +2,7 @@
* @Author: jackning 270580156@qq.com
* @Date: 2025-02-28 11:44:03
* @LastEditors: jackning 270580156@qq.com
* @LastEditTime: 2025-07-16 15:10:31
* @LastEditTime: 2025-08-21 12:46:15
* @Description: bytedesk.com https://github.com/Bytedesk/bytedesk
* Please be aware of the BSL license restrictions before installing Bytedesk IM –
* selling, reselling, or hosting Bytedesk IM as a service is a breach of the terms and automatically terminates your rights under the license.
@@ -31,6 +31,7 @@ import com.bytedesk.ai.springai.service.BaseSpringAIService;
import com.bytedesk.core.constant.LlmConsts;
import com.bytedesk.core.message.MessageProtobuf;
import com.bytedesk.core.message.MessageTypeEnum;
import com.bytedesk.ai.springai.service.ChatTokenUsage;
import lombok.extern.slf4j.Slf4j;
@@ -82,7 +83,7 @@ public class SpringAIBaiduService extends BaseSpringAIService {
// 记录开始时间和初始化token使用统计
long startTime = System.currentTimeMillis();
final boolean[] success = { false };
final TokenUsage[] tokenUsage = { new TokenUsage(0, 0, 0) };
final ChatTokenUsage[] tokenUsage = { new ChatTokenUsage(0, 0, 0) };
// 用于累积所有响应文本
final StringBuilder[] fullResponseText = { new StringBuilder() };
@@ -118,7 +119,7 @@ public class SpringAIBaiduService extends BaseSpringAIService {
// 如果token提取失败，使用累积的完整响应文本来估算token
if (tokenUsage[0].getTotalTokens() == 0 && fullResponseText[0].length() > 0) {
log.info("Baidu API using accumulated response text for token estimation: {}", fullResponseText[0].toString());
TokenUsage estimatedUsage = estimateBaiduTokenUsageFromText(fullResponseText[0].toString());
ChatTokenUsage estimatedUsage = estimateBaiduTokenUsageFromText(fullResponseText[0].toString());
tokenUsage[0] = estimatedUsage;
log.info("Baidu API final estimated token usage: {}", estimatedUsage);
}
@@ -138,7 +139,7 @@ public class SpringAIBaiduService extends BaseSpringAIService {
log.info("SpringAIBaiduService processPromptSync with full prompt content: {}", fullPromptContent);
long startTime = System.currentTimeMillis();
boolean success = false;
TokenUsage tokenUsage = new TokenUsage(0, 0, 0);
ChatTokenUsage tokenUsage = new ChatTokenUsage(0, 0, 0);
try {
if (baiduChatModel == null) {
@@ -212,7 +213,7 @@ public class SpringAIBaiduService extends BaseSpringAIService {
// 记录开始时间和初始化token使用统计
long startTime = System.currentTimeMillis();
final boolean[] success = { false };
final TokenUsage[] tokenUsage = { new TokenUsage(0, 0, 0) };
final ChatTokenUsage[] tokenUsage = { new ChatTokenUsage(0, 0, 0) };
// 用于累积所有响应文本
final StringBuilder[] fullResponseText = { new StringBuilder() };
@@ -255,7 +256,7 @@ public class SpringAIBaiduService extends BaseSpringAIService {
// 如果token提取失败，使用累积的完整响应文本来估算token
if (tokenUsage[0].getTotalTokens() == 0 && fullResponseText[0].length() > 0) {
log.info("Baidu API using accumulated response text for token estimation: {}", fullResponseText[0].toString());
TokenUsage estimatedUsage = estimateBaiduTokenUsageFromText(fullResponseText[0].toString());
ChatTokenUsage estimatedUsage = estimateBaiduTokenUsageFromText(fullResponseText[0].toString());
tokenUsage[0] = estimatedUsage;
log.info("Baidu API final estimated token usage: {}", estimatedUsage);
}
@@ -283,17 +284,17 @@ public class SpringAIBaiduService extends BaseSpringAIService {
* @param response ChatResponse对象
* @return TokenUsage对象
*/
private TokenUsage extractBaiduTokenUsage(org.springframework.ai.chat.model.ChatResponse response) {
private ChatTokenUsage extractBaiduTokenUsage(org.springframework.ai.chat.model.ChatResponse response) {
try {
if (response == null) {
log.warn("Baidu API response is null");
return new TokenUsage(0, 0, 0);
return new ChatTokenUsage(0, 0, 0);
}
var metadata = response.getMetadata();
if (metadata == null) {
log.warn("Baidu API response metadata is null");
return new TokenUsage(0, 0, 0);
return new ChatTokenUsage(0, 0, 0);
}
log.info("Baidu API manual token extraction - metadata: {}", metadata);
@@ -390,7 +391,7 @@ public class SpringAIBaiduService extends BaseSpringAIService {
log.info("Baidu API manual token extraction result - prompt: {}, completion: {}, total: {}",
promptTokens, completionTokens, totalTokens);
return new TokenUsage(promptTokens, completionTokens, totalTokens);
return new ChatTokenUsage(promptTokens, completionTokens, totalTokens);
}
}
@@ -404,7 +405,7 @@ public class SpringAIBaiduService extends BaseSpringAIService {
// 方法3: 如果手动提取失败，尝试使用原始的extractTokenUsage方法作为后备
log.info("Baidu API manual extraction failed, trying original extractTokenUsage method");
TokenUsage fallbackUsage = extractTokenUsage(response);
ChatTokenUsage fallbackUsage = extractTokenUsage(response);
if (fallbackUsage.getTotalTokens() > 0) {
log.info("Baidu API fallback extraction successful: {}", fallbackUsage);
return fallbackUsage;
@@ -412,13 +413,13 @@ public class SpringAIBaiduService extends BaseSpringAIService {
// 方法4: 如果所有方法都失败，尝试估算token使用量
log.info("Baidu API all extraction methods failed, attempting to estimate token usage");
TokenUsage estimatedUsage = estimateBaiduTokenUsageFromResponse(response);
ChatTokenUsage estimatedUsage = estimateBaiduTokenUsageFromResponse(response);
log.info("Baidu API estimated token usage: {}", estimatedUsage);
return estimatedUsage;
} catch (Exception e) {
log.error("Error in manual Baidu token extraction", e);
return new TokenUsage(0, 0, 0);
return new ChatTokenUsage(0, 0, 0);
}
}
@@ -428,10 +429,10 @@ public class SpringAIBaiduService extends BaseSpringAIService {
* @param response ChatResponse对象
* @return 估算的TokenUsage对象
*/
private TokenUsage estimateBaiduTokenUsageFromResponse(org.springframework.ai.chat.model.ChatResponse response) {
private ChatTokenUsage estimateBaiduTokenUsageFromResponse(org.springframework.ai.chat.model.ChatResponse response) {
try {
if (response == null || response.getResults() == null || response.getResults().isEmpty()) {
return new TokenUsage(0, 0, 0);
return new ChatTokenUsage(0, 0, 0);
}
// 获取输出文本
@@ -446,7 +447,7 @@ public class SpringAIBaiduService extends BaseSpringAIService {
} catch (Exception e) {
log.error("Error estimating Baidu token usage", e);
return new TokenUsage(0, 0, 0);
return new ChatTokenUsage(0, 0, 0);
}
}
@@ -456,10 +457,10 @@ public class SpringAIBaiduService extends BaseSpringAIService {
* @param outputText 完整的输出文本
* @return 估算的TokenUsage对象
*/
private TokenUsage estimateBaiduTokenUsageFromText(String outputText) {
private ChatTokenUsage estimateBaiduTokenUsageFromText(String outputText) {
try {
if (outputText == null || outputText.isEmpty()) {
return new TokenUsage(0, 0, 0);
return new ChatTokenUsage(0, 0, 0);
}
// 估算token使用量
@@ -474,11 +475,11 @@ public class SpringAIBaiduService extends BaseSpringAIService {
"Baidu API estimated tokens - output: {} chars -> {} tokens, estimated prompt: {} tokens, total: {} tokens",
outputText.length(), completionTokens, promptTokens, totalTokens);
return new TokenUsage(promptTokens, completionTokens, totalTokens);
return new ChatTokenUsage(promptTokens, completionTokens, totalTokens);
} catch (Exception e) {
log.error("Error estimating Baidu token usage from text", e);
return new TokenUsage(0, 0, 0);
return new ChatTokenUsage(0, 0, 0);
}
}

21
modules/ai/src/main/java/com/bytedesk/ai/springai/providers/dashscope/SpringAIDashscopeService.java
View File

@@ -2,7 +2,7 @@
* @Author: jackning 270580156@qq.com
* @Date: 2025-02-28 11:44:03
* @LastEditors: jackning 270580156@qq.com
* @LastEditTime: 2025-07-18 17:04:41
* @LastEditTime: 2025-08-21 12:46:21
* @Description: bytedesk.com https://github.com/Bytedesk/bytedesk
* Please be aware of the BSL license restrictions before installing Bytedesk IM –
* selling, reselling, or hosting Bytedesk IM as a service is a breach of the terms and automatically terminates your rights under the license.
@@ -33,6 +33,7 @@ import com.bytedesk.ai.springai.service.BaseSpringAIService;
import com.bytedesk.core.constant.LlmConsts;
import com.bytedesk.core.message.MessageProtobuf;
import com.bytedesk.core.message.MessageTypeEnum;
import com.bytedesk.ai.springai.service.ChatTokenUsage;
import lombok.extern.slf4j.Slf4j;
@@ -87,7 +88,7 @@ public class SpringAIDashscopeService extends BaseSpringAIService {
long startTime = System.currentTimeMillis();
final boolean[] success = {false};
final TokenUsage[] tokenUsage = {new TokenUsage(0, 0, 0)};
final ChatTokenUsage[] tokenUsage = {new ChatTokenUsage(0, 0, 0)};
final StringBuilder[] fullResponseText = {new StringBuilder()};
// 使用同一个ChatModel实例，但传入不同的选项
@@ -132,7 +133,7 @@ public class SpringAIDashscopeService extends BaseSpringAIService {
protected String processPromptSync(String message, RobotProtobuf robot, String fullPromptContent) {
long startTime = System.currentTimeMillis();
boolean success = false;
TokenUsage tokenUsage = new TokenUsage(0, 0, 0);
ChatTokenUsage tokenUsage = new ChatTokenUsage(0, 0, 0);
log.info("Dashscope API sync fullPromptContent: {}", fullPromptContent);
@@ -202,7 +203,7 @@ public class SpringAIDashscopeService extends BaseSpringAIService {
long startTime = System.currentTimeMillis();
final boolean[] success = {false};
final TokenUsage[] tokenUsage = {new TokenUsage(0, 0, 0)};
final ChatTokenUsage[] tokenUsage = {new ChatTokenUsage(0, 0, 0)};
final StringBuilder[] fullResponseText = {new StringBuilder()};
bytedeskDashscopeChatModel.stream(requestPrompt).subscribe(
@@ -259,17 +260,17 @@ public class SpringAIDashscopeService extends BaseSpringAIService {
* @param response ChatResponse对象
* @return TokenUsage对象
*/
private TokenUsage extractDashscopeTokenUsage(ChatResponse response) {
private ChatTokenUsage extractDashscopeTokenUsage(ChatResponse response) {
try {
if (response == null) {
log.warn("Dashscope API response is null");
return new TokenUsage(0, 0, 0);
return new ChatTokenUsage(0, 0, 0);
}
var metadata = response.getMetadata();
if (metadata == null) {
log.warn("Dashscope API response metadata is null");
return new TokenUsage(0, 0, 0);
return new ChatTokenUsage(0, 0, 0);
}
log.info("Dashscope API token extraction - metadata: {}", metadata);
@@ -286,18 +287,18 @@ public class SpringAIDashscopeService extends BaseSpringAIService {
promptTokens, completionTokens, totalTokens);
if (totalTokens > 0) {
return new TokenUsage(promptTokens, completionTokens, totalTokens);
return new ChatTokenUsage(promptTokens, completionTokens, totalTokens);
}
}
} catch (Exception e) {
log.debug("Could not get usage via getUsage() method: {}", e.getMessage());
}
return new TokenUsage(0, 0, 0);
return new ChatTokenUsage(0, 0, 0);
} catch (Exception e) {
log.error("Error in Dashscope token extraction", e);
return new TokenUsage(0, 0, 0);
return new ChatTokenUsage(0, 0, 0);
}
}

21
modules/ai/src/main/java/com/bytedesk/ai/springai/providers/deepseek/SpringAIDeepseekService.java
View File

@@ -2,7 +2,7 @@
* @Author: jackning 270580156@qq.com
* @Date: 2025-02-28 11:44:03
* @LastEditors: jackning 270580156@qq.com
* @LastEditTime: 2025-07-18 17:04:22
* @LastEditTime: 2025-08-21 12:46:25
* @Description: bytedesk.com https://github.com/Bytedesk/bytedesk
* Please be aware of the BSL license restrictions before installing Bytedesk IM –
* selling, reselling, or hosting Bytedesk IM as a service is a breach of the terms and automatically terminates your rights under the license.
@@ -34,6 +34,7 @@ import com.bytedesk.ai.springai.service.BaseSpringAIService;
import com.bytedesk.core.constant.LlmConsts;
import com.bytedesk.core.message.MessageProtobuf;
import com.bytedesk.core.message.MessageTypeEnum;
import com.bytedesk.ai.springai.service.ChatTokenUsage;
import lombok.extern.slf4j.Slf4j;
@@ -87,7 +88,7 @@ public class SpringAIDeepseekService extends BaseSpringAIService {
long startTime = System.currentTimeMillis();
final boolean[] success = {false};
final TokenUsage[] tokenUsage = {new TokenUsage(0, 0, 0)};
final ChatTokenUsage[] tokenUsage = {new ChatTokenUsage(0, 0, 0)};
// 使用同一个ChatModel实例，但传入不同的选项
deepseekChatModel.stream(requestPrompt).subscribe(
@@ -126,7 +127,7 @@ public class SpringAIDeepseekService extends BaseSpringAIService {
log.info("SpringAIDeepseekService processPromptSync with full prompt content: {}", fullPromptContent);
long startTime = System.currentTimeMillis();
boolean success = false;
TokenUsage tokenUsage = new TokenUsage(0, 0, 0);
ChatTokenUsage tokenUsage = new ChatTokenUsage(0, 0, 0);
try {
if (deepseekChatModel == null) {
@@ -195,7 +196,7 @@ public class SpringAIDeepseekService extends BaseSpringAIService {
long startTime = System.currentTimeMillis();
final boolean[] success = {false};
final TokenUsage[] tokenUsage = {new TokenUsage(0, 0, 0)};
final ChatTokenUsage[] tokenUsage = {new ChatTokenUsage(0, 0, 0)};
deepseekChatModel.stream(requestPrompt).subscribe(
response -> {
@@ -245,17 +246,17 @@ public class SpringAIDeepseekService extends BaseSpringAIService {
* @param response ChatResponse对象
* @return TokenUsage对象
*/
private TokenUsage extractDeepSeekTokenUsage(ChatResponse response) {
private ChatTokenUsage extractDeepSeekTokenUsage(ChatResponse response) {
try {
if (response == null) {
log.warn("Deepseek API response is null");
return new TokenUsage(0, 0, 0);
return new ChatTokenUsage(0, 0, 0);
}
var metadata = response.getMetadata();
if (metadata == null) {
log.warn("Deepseek API response metadata is null");
return new TokenUsage(0, 0, 0);
return new ChatTokenUsage(0, 0, 0);
}
log.info("Deepseek API token extraction - metadata: {}", metadata);
@@ -272,18 +273,18 @@ public class SpringAIDeepseekService extends BaseSpringAIService {
promptTokens, completionTokens, totalTokens);
if (totalTokens > 0) {
return new TokenUsage(promptTokens, completionTokens, totalTokens);
return new ChatTokenUsage(promptTokens, completionTokens, totalTokens);
}
}
} catch (Exception e) {
log.debug("Could not get usage via getUsage() method: {}", e.getMessage());
}
return new TokenUsage(0, 0, 0);
return new ChatTokenUsage(0, 0, 0);
} catch (Exception e) {
log.error("Error in Deepseek token extraction", e);
return new TokenUsage(0, 0, 0);
return new ChatTokenUsage(0, 0, 0);
}
}

9
modules/ai/src/main/java/com/bytedesk/ai/springai/providers/gitee/SpringAIGiteeService.java
View File

@@ -2,7 +2,7 @@
* @Author: jackning 270580156@qq.com
* @Date: 2025-02-28 11:44:03
* @LastEditors: jackning 270580156@qq.com
* @LastEditTime: 2025-07-16 13:23:44
* @LastEditTime: 2025-08-21 12:46:30
* @Description: bytedesk.com https://github.com/Bytedesk/bytedesk
* Please be aware of the BSL license restrictions before installing Bytedesk IM –
* selling, reselling, or hosting Bytedesk IM as a service is a breach of the terms and automatically terminates your rights under the license.
@@ -32,6 +32,7 @@ import com.bytedesk.ai.springai.service.BaseSpringAIService;
import com.bytedesk.core.constant.LlmConsts;
import com.bytedesk.core.message.MessageProtobuf;
import com.bytedesk.core.message.MessageTypeEnum;
import com.bytedesk.ai.springai.service.ChatTokenUsage;
import lombok.extern.slf4j.Slf4j;
@@ -84,7 +85,7 @@ public class SpringAIGiteeService extends BaseSpringAIService {
long startTime = System.currentTimeMillis();
final boolean[] success = {false};
final TokenUsage[] tokenUsage = {new TokenUsage(0, 0, 0)};
final ChatTokenUsage[] tokenUsage = {new ChatTokenUsage(0, 0, 0)};
// 使用同一个ChatModel实例，但传入不同的选项
giteeChatModel.stream(requestPrompt).subscribe(
@@ -123,7 +124,7 @@ public class SpringAIGiteeService extends BaseSpringAIService {
log.info("SpringAIGiteeService processPromptSync with full prompt content: {}", fullPromptContent);
long startTime = System.currentTimeMillis();
boolean success = false;
TokenUsage tokenUsage = new TokenUsage(0, 0, 0);
ChatTokenUsage tokenUsage = new ChatTokenUsage(0, 0, 0);
try {
if (giteeChatModel == null) {
@@ -193,7 +194,7 @@ public class SpringAIGiteeService extends BaseSpringAIService {
long startTime = System.currentTimeMillis();
final boolean[] success = {false};
final TokenUsage[] tokenUsage = {new TokenUsage(0, 0, 0)};
final ChatTokenUsage[] tokenUsage = {new ChatTokenUsage(0, 0, 0)};
giteeChatModel.stream(requestPrompt).subscribe(
response -> {

21
modules/ai/src/main/java/com/bytedesk/ai/springai/providers/minimax/SpringAIMinimaxService.java
View File

@@ -2,7 +2,7 @@
* @Author: jackning 270580156@qq.com
* @Date: 2025-02-28 11:44:03
* @LastEditors: jackning 270580156@qq.com
* @LastEditTime: 2025-07-22 08:34:28
* @LastEditTime: 2025-08-21 12:46:36
* @Description: bytedesk.com https://github.com/Bytedesk/bytedesk
* Please be aware of the BSL license restrictions before installing Bytedesk IM –
* selling, reselling, or hosting Bytedesk IM as a service is a breach of the terms and automatically terminates your rights under the license.
@@ -34,6 +34,7 @@ import com.bytedesk.ai.springai.service.BaseSpringAIService;
import com.bytedesk.core.constant.LlmConsts;
import com.bytedesk.core.message.MessageProtobuf;
import com.bytedesk.core.message.MessageTypeEnum;
import com.bytedesk.ai.springai.service.ChatTokenUsage;
import lombok.extern.slf4j.Slf4j;
@@ -87,7 +88,7 @@ public class SpringAIMinimaxService extends BaseSpringAIService {
long startTime = System.currentTimeMillis();
final boolean[] success = {false};
final TokenUsage[] tokenUsage = {new TokenUsage(0, 0, 0)};
final ChatTokenUsage[] tokenUsage = {new ChatTokenUsage(0, 0, 0)};
// 使用同一个ChatModel实例，但传入不同的选项
minimaxChatModel.stream(requestPrompt).subscribe(
@@ -126,7 +127,7 @@ public class SpringAIMinimaxService extends BaseSpringAIService {
log.info("SpringAIMinimaxService processPromptSync with full prompt content: {}", fullPromptContent);
long startTime = System.currentTimeMillis();
boolean success = false;
TokenUsage tokenUsage = new TokenUsage(0, 0, 0);
ChatTokenUsage tokenUsage = new ChatTokenUsage(0, 0, 0);
try {
if (minimaxChatModel == null) {
@@ -195,7 +196,7 @@ public class SpringAIMinimaxService extends BaseSpringAIService {
long startTime = System.currentTimeMillis();
final boolean[] success = {false};
final TokenUsage[] tokenUsage = {new TokenUsage(0, 0, 0)};
final ChatTokenUsage[] tokenUsage = {new ChatTokenUsage(0, 0, 0)};
minimaxChatModel.stream(requestPrompt).subscribe(
response -> {
@@ -245,17 +246,17 @@ public class SpringAIMinimaxService extends BaseSpringAIService {
* @param response ChatResponse对象
* @return TokenUsage对象
*/
private TokenUsage extractDeepSeekTokenUsage(ChatResponse response) {
private ChatTokenUsage extractDeepSeekTokenUsage(ChatResponse response) {
try {
if (response == null) {
log.warn("Minimax API response is null");
return new TokenUsage(0, 0, 0);
return new ChatTokenUsage(0, 0, 0);
}
var metadata = response.getMetadata();
if (metadata == null) {
log.warn("Minimax API response metadata is null");
return new TokenUsage(0, 0, 0);
return new ChatTokenUsage(0, 0, 0);
}
log.info("Minimax API token extraction - metadata: {}", metadata);
@@ -272,18 +273,18 @@ public class SpringAIMinimaxService extends BaseSpringAIService {
promptTokens, completionTokens, totalTokens);
if (totalTokens > 0) {
return new TokenUsage(promptTokens, completionTokens, totalTokens);
return new ChatTokenUsage(promptTokens, completionTokens, totalTokens);
}
}
} catch (Exception e) {
log.debug("Could not get usage via getUsage() method: {}", e.getMessage());
}
return new TokenUsage(0, 0, 0);
return new ChatTokenUsage(0, 0, 0);
} catch (Exception e) {
log.error("Error in Minimax token extraction", e);
return new TokenUsage(0, 0, 0);
return new ChatTokenUsage(0, 0, 0);
}
}

114
modules/ai/src/main/java/com/bytedesk/ai/springai/providers/ollama/SpringAIOllamaChatConfig.java
View File

@@ -2,7 +2,7 @@
* @Author: jackning 270580156@qq.com
* @Date: 2024-05-31 10:24:39
* @LastEditors: jackning 270580156@qq.com
* @LastEditTime: 2025-08-20 21:25:13
* @LastEditTime: 2025-08-21 12:39:58
* @Description: bytedesk.com https://github.com/Bytedesk/bytedesk
* Please be aware of the BSL license restrictions before installing Bytedesk IM –
* selling, reselling, or hosting Bytedesk IM as a service is a breach of the terms and automatically terminates your rights under the license.
@@ -13,67 +13,67 @@
*/
package com.bytedesk.ai.springai.providers.ollama;
// import org.springframework.ai.chat.client.ChatClient;
// import org.springframework.ai.chat.client.advisor.SimpleLoggerAdvisor;
// import org.springframework.ai.ollama.OllamaChatModel;
// import org.springframework.ai.ollama.api.OllamaApi;
// import org.springframework.ai.ollama.api.OllamaOptions;
// import org.springframework.beans.factory.annotation.Value;
// import org.springframework.boot.autoconfigure.condition.ConditionalOnProperty;
// import org.springframework.context.annotation.Bean;
// import org.springframework.context.annotation.Configuration;
// import lombok.Data;
// import lombok.extern.slf4j.Slf4j;
import org.springframework.ai.chat.client.ChatClient;
import org.springframework.ai.chat.client.advisor.SimpleLoggerAdvisor;
import org.springframework.ai.ollama.OllamaChatModel;
import org.springframework.ai.ollama.api.OllamaApi;
import org.springframework.ai.ollama.api.OllamaOptions;
import org.springframework.beans.factory.annotation.Value;
import org.springframework.boot.autoconfigure.condition.ConditionalOnProperty;
import org.springframework.context.annotation.Bean;
import org.springframework.context.annotation.Configuration;
import lombok.Data;
import lombok.extern.slf4j.Slf4j;
// /**
// * https://ollama.com/
// * https://www.promptingguide.ai/
// * Ollama Chat Configuration
// */
// @Slf4j
// @Data
// @Configuration
// @ConditionalOnProperty(prefix = "spring.ai.ollama.chat", name = "enabled", havingValue = "true", matchIfMissing = false)
// public class SpringAIOllamaChatConfig {
/**
* https://ollama.com/
* https://www.promptingguide.ai/
* Ollama Chat Configuration
*/
@Slf4j
@Data
@Configuration
@ConditionalOnProperty(prefix = "spring.ai.ollama.chat", name = "enabled", havingValue = "true", matchIfMissing = false)
public class SpringAIOllamaChatConfig {
// @Value("${spring.ai.ollama.base-url:http://host.docker.internal:11434}")
// private String ollamaBaseUrl;
@Value("${spring.ai.ollama.base-url:http://host.docker.internal:11434}")
private String ollamaBaseUrl;
// @Value("${spring.ai.ollama.chat.options.model:qwen3:0.6b}")
// private String ollamaChatOptionsModel;
@Value("${spring.ai.ollama.chat.options.model:qwen3:0.6b}")
private String ollamaChatOptionsModel;
// @Bean("bytedeskOllamaApi")
// OllamaApi bytedeskOllamaApi() {
// return OllamaApi.builder()
// .baseUrl(ollamaBaseUrl)
// .build();
// }
@Bean("bytedeskOllamaApi")
OllamaApi bytedeskOllamaApi() {
return OllamaApi.builder()
.baseUrl(ollamaBaseUrl)
.build();
}
// @Bean("bytedeskOllamaChatOptions")
// OllamaOptions bytedeskOllamaChatOptions() {
// return OllamaOptions.builder()
// .model(ollamaChatOptionsModel)
// // 使用keepAlive而不是timeout来设置超时
// // .keepAlive("30s") // 使用30秒的超时设置
// // .numKeep(0) // 不保留历史对话上下文
// // .useNUMA(ollamaChatOptionsNuma) // 使用正确的方法名useNUMA而不是numa
// .build();
// }
@Bean("bytedeskOllamaChatOptions")
OllamaOptions bytedeskOllamaChatOptions() {
return OllamaOptions.builder()
.model(ollamaChatOptionsModel)
// 使用keepAlive而不是timeout来设置超时
// .keepAlive("30s") // 使用30秒的超时设置
// .numKeep(0) // 不保留历史对话上下文
// .useNUMA(ollamaChatOptionsNuma) // 使用正确的方法名useNUMA而不是numa
.build();
}
// @Bean("bytedeskOllamaChatModel")
// OllamaChatModel bytedeskOllamaChatModel() {
// return OllamaChatModel.builder()
// .ollamaApi(bytedeskOllamaApi())
// .defaultOptions(bytedeskOllamaChatOptions())
// .build();
// }
@Bean("bytedeskOllamaChatModel")
OllamaChatModel bytedeskOllamaChatModel() {
return OllamaChatModel.builder()
.ollamaApi(bytedeskOllamaApi())
.defaultOptions(bytedeskOllamaChatOptions())
.build();
}
// @Bean("bytedeskOllamaChatClient")
// ChatClient bytedeskOllamaChatClient() {
// return ChatClient.builder(bytedeskOllamaChatModel())
// .defaultOptions(bytedeskOllamaChatOptions())
// .defaultAdvisors(new SimpleLoggerAdvisor())
// .build();
// }
@Bean("bytedeskOllamaChatClient")
ChatClient bytedeskOllamaChatClient() {
return ChatClient.builder(bytedeskOllamaChatModel())
.defaultOptions(bytedeskOllamaChatOptions())
.defaultAdvisors(new SimpleLoggerAdvisor())
.build();
}
// }
}

324
modules/ai/src/main/java/com/bytedesk/ai/springai/providers/ollama/SpringAIOllamaChatService.java Normal file
View File

@@ -0,0 +1,324 @@
/*
* @Author: jackning 270580156@qq.com
* @Date: 2025-02-26 16:59:14
* @LastEditors: jackning 270580156@qq.com
* @LastEditTime: 2025-08-21 12:45:00
* @Description: bytedesk.com https://github.com/Bytedesk/bytedesk
* Please be aware of the BSL license restrictions before installing Bytedesk IM –
* selling, reselling, or hosting Bytedesk IM as a service is a breach of the terms and automatically terminates your rights under the license.
* Business Source License 1.1: https://github.com/Bytedesk/bytedesk/blob/main/LICENSE
* contact: 270580156@qq.com
*
* Copyright (c) 2025 by bytedesk.com, All Rights Reserved.
*/
package com.bytedesk.ai.springai.providers.ollama;
import java.util.List;
import org.springframework.ai.chat.messages.AssistantMessage;
import org.springframework.ai.chat.model.Generation;
import org.springframework.ai.chat.prompt.Prompt;
import org.springframework.ai.ollama.OllamaChatModel;
import org.springframework.ai.ollama.api.OllamaApi;
import org.springframework.ai.ollama.api.OllamaOptions;
import org.springframework.beans.factory.annotation.Autowired;
import org.springframework.beans.factory.annotation.Qualifier;
import org.springframework.boot.autoconfigure.condition.ConditionalOnProperty;
import org.springframework.http.HttpStatus;
import org.springframework.stereotype.Service;
import org.springframework.util.Assert;
import org.springframework.util.StringUtils;
import org.springframework.web.client.HttpClientErrorException;
import org.springframework.web.servlet.mvc.method.annotation.SseEmitter;
import com.bytedesk.ai.robot.RobotLlm;
import com.bytedesk.ai.robot.RobotProtobuf;
import com.bytedesk.ai.springai.service.BaseSpringAIService;
import com.bytedesk.ai.springai.service.ChatTokenUsage;
import com.bytedesk.core.constant.LlmConsts;
import com.bytedesk.core.message.MessageProtobuf;
import com.bytedesk.core.message.MessageTypeEnum;
import lombok.extern.slf4j.Slf4j;
@Slf4j
@Service
@ConditionalOnProperty(prefix = "spring.ai.ollama.chat", name = "enabled", havingValue = "true", matchIfMissing = false)
public class SpringAIOllamaChatService extends BaseSpringAIService {
@Autowired
@Qualifier("bytedeskOllamaApi")
private OllamaApi bytedeskOllamaApi;
@Autowired(required = false)
@Qualifier("bytedeskOllamaChatModel")
private OllamaChatModel bytedeskOllamaChatModel;
public SpringAIOllamaChatService() {
super(); // 调用基类的无参构造函数
}
/**
* 根据机器人配置创建动态的OllamaOptions
*
* @param llm 机器人LLM配置
* @return 根据机器人配置创建的选项
*/
private OllamaOptions createOllamaOptions(RobotLlm llm) {
return super.createDynamicOptions(llm, robotLlm -> OllamaOptions.builder()
.model(robotLlm.getTextModel())
.temperature(robotLlm.getTemperature())
.topP(robotLlm.getTopP())
.topK(robotLlm.getTopK())
.build());
}
public OllamaApi createOllamaApi(String apiUrl) {
return OllamaApi.builder()
.baseUrl(apiUrl)
.build();
}
/**
* 检查模型是否存在
*
* @param modelName 模型名称
* @return 如果模型存在返回true，否则返回false
*/
public Boolean isModelExists(OllamaRequest request) {
OllamaApi ollamaApi = createOllamaApi(request.getApiUrl());
String modelName = request.getModel();
Assert.hasText(modelName, "Model name must not be null or empty");
try {
ollamaApi.showModel(new OllamaApi.ShowModelRequest(modelName));
return true;
} catch (HttpClientErrorException e) {
if (e.getStatusCode() == HttpStatus.NOT_FOUND) {
return false;
}
log.error("检查模型是否存在时发生错误: {}, 状态码: {}", modelName, e.getStatusCode());
} catch (Exception e) {
log.error("检查模型是否存在时发生未知错误: {}, 错误: {}", modelName, e.getMessage());
}
return false;
}
protected void processPromptWebsocket(Prompt prompt, RobotProtobuf robot, MessageProtobuf messageProtobufQuery,
MessageProtobuf messageProtobufReply, String fullPromptContent) {
// 从robot中获取llm配置
RobotLlm llm = robot.getLlm();
log.info("Ollama API websocket fullPromptContent: {}", fullPromptContent);
if (llm == null) {
log.info("Ollama API not available");
sendMessageWebsocket(MessageTypeEnum.ERROR, "Ollama service is not available", messageProtobufReply);
return;
}
// 获取适当的模型实例
OllamaChatModel chatModel = bytedeskOllamaChatModel;
if (chatModel == null) {
log.info("Ollama API not available");
sendMessageWebsocket(MessageTypeEnum.ERROR, "Ollama service is not available", messageProtobufReply);
return;
}
long startTime = System.currentTimeMillis();
final boolean[] success = { false };
final ChatTokenUsage[] tokenUsage = { new ChatTokenUsage(0, 0, 0) };
try {
chatModel.stream(prompt).subscribe(
response -> {
if (response != null) {
log.info("Ollama API response metadata: {}", response.getMetadata());
List<Generation> generations = response.getResults();
for (Generation generation : generations) {
AssistantMessage assistantMessage = generation.getOutput();
String textContent = assistantMessage.getText();
log.info("Ollama API Websocket response text: {}", textContent);
sendMessageWebsocket(MessageTypeEnum.STREAM, textContent, messageProtobufReply);
}
// 提取token使用情况
tokenUsage[0] = extractTokenUsage(response);
success[0] = true;
}
},
error -> {
log.error("Ollama API error: ", error);
sendMessageWebsocket(MessageTypeEnum.ERROR, "服务暂时不可用，请稍后重试", messageProtobufReply);
success[0] = false;
},
() -> {
log.info("Chat stream completed");
// 记录token使用情况
long responseTime = System.currentTimeMillis() - startTime;
String modelType = (llm != null && StringUtils.hasText(llm.getTextModel())) ? llm.getTextModel()
: "llama2";
recordAiTokenUsage(robot, LlmConsts.OLLAMA, modelType,
tokenUsage[0].getPromptTokens(), tokenUsage[0].getCompletionTokens(), success[0],
responseTime);
});
} catch (Exception e) {
log.error("Error processing Ollama prompt", e);
sendMessageWebsocket(MessageTypeEnum.ERROR, "服务暂时不可用，请稍后重试", messageProtobufReply);
success[0] = false;
// 记录token使用情况
long responseTime = System.currentTimeMillis() - startTime;
String modelType = (llm != null && StringUtils.hasText(llm.getTextModel())) ? llm.getTextModel() : "llama2";
recordAiTokenUsage(robot, LlmConsts.OLLAMA, modelType,
tokenUsage[0].getPromptTokens(), tokenUsage[0].getCompletionTokens(), success[0], responseTime);
}
}
protected String processPromptSync(String message, RobotProtobuf robot, String fullPromptContent) {
long startTime = System.currentTimeMillis();
boolean success = false;
ChatTokenUsage tokenUsage = new ChatTokenUsage(0, 0, 0);
log.info("Ollama API sync fullPromptContent: {}", fullPromptContent);
// 从robot中获取llm配置
RobotLlm llm = robot.getLlm();
log.info("Ollama API websocket fullPromptContent: {}", fullPromptContent);
if (llm == null) {
log.info("Ollama API not available");
return "Ollama service is not available";
}
// 获取适当的模型实例
OllamaChatModel chatModel = bytedeskOllamaChatModel;
try {
try {
// 如果有robot参数，尝试创建自定义选项
if (robot != null && robot.getLlm() != null) {
// 创建自定义选项
OllamaOptions customOptions = createOllamaOptions(robot.getLlm());
if (customOptions != null) {
// 使用自定义选项创建Prompt
Prompt prompt = new Prompt(message, customOptions);
var response = chatModel.call(prompt);
log.info("Ollama API Sync response metadata: {}", response.getMetadata());
tokenUsage = extractTokenUsage(response);
success = true;
return extractTextFromResponse(response);
}
}
var response = chatModel.call(message);
tokenUsage = extractTokenUsage(response);
success = true;
return extractTextFromResponse(response);
} catch (Exception e) {
log.error("Ollama API sync error", e);
success = false;
return "服务暂时不可用，请稍后重试";
}
} catch (Exception e) {
log.error("Ollama API sync error", e);
success = false;
return "服务暂时不可用，请稍后重试";
} finally {
// 记录token使用情况
long responseTime = System.currentTimeMillis() - startTime;
String modelType = (robot != null && robot.getLlm() != null
&& StringUtils.hasText(robot.getLlm().getTextModel()))
? robot.getLlm().getTextModel()
: "llama2";
recordAiTokenUsage(robot, LlmConsts.OLLAMA, modelType,
tokenUsage.getPromptTokens(), tokenUsage.getCompletionTokens(), success, responseTime);
}
}
protected void processPromptSse(Prompt prompt, RobotProtobuf robot, MessageProtobuf messageProtobufQuery,
MessageProtobuf messageProtobufReply, SseEmitter emitter, String fullPromptContent) {
Assert.notNull(emitter, "SseEmitter must not be null");
// 从robot中获取llm配置
RobotLlm llm = robot.getLlm();
log.info("Ollama API SSE fullPromptContent: {}", fullPromptContent);
if (llm == null) {
log.info("Ollama API not available");
sendStreamEndMessage(messageProtobufQuery, messageProtobufReply, emitter, 0, 0, 0, fullPromptContent,
LlmConsts.OLLAMA,
(llm != null && StringUtils.hasText(llm.getTextModel())) ? llm.getTextModel() : "llama2");
return;
}
// 获取适当的模型实例
OllamaChatModel chatModel = bytedeskOllamaChatModel;
if (chatModel == null) {
log.info("Ollama API not available");
// 使用sendStreamEndMessage方法替代重复的代码
sendStreamEndMessage(messageProtobufQuery, messageProtobufReply, emitter, 0, 0, 0, fullPromptContent,
LlmConsts.OLLAMA,
(llm != null && StringUtils.hasText(llm.getTextModel())) ? llm.getTextModel() : "llama2");
return;
}
long startTime = System.currentTimeMillis();
final boolean[] success = { false };
final ChatTokenUsage[] tokenUsage = { new ChatTokenUsage(0, 0, 0) };
try {
// 发送初始消息，告知用户请求已收到，正在处理
sendStreamStartMessage(messageProtobufReply, emitter, "正在思考中...");
chatModel.stream(prompt).subscribe(
response -> {
try {
if (response != null && !isEmitterCompleted(emitter)) {
List<Generation> generations = response.getResults();
for (Generation generation : generations) {
AssistantMessage assistantMessage = generation.getOutput();
String textContent = assistantMessage.getText();
log.info("Ollama API SSE response text: {}", textContent);
sendStreamMessage(messageProtobufQuery, messageProtobufReply, emitter, textContent);
}
// 提取token使用情况
tokenUsage[0] = extractTokenUsage(response);
success[0] = true;
}
} catch (Exception e) {
log.error("Ollama API SSE error 1: ", e);
handleSseError(e, messageProtobufQuery, messageProtobufReply, emitter);
success[0] = false;
}
},
error -> {
log.error("Ollama API SSE error 2: ", error);
handleSseError(error, messageProtobufQuery, messageProtobufReply, emitter);
success[0] = false;
},
() -> {
log.info("Ollama API SSE complete");
// 发送流结束消息，包含token使用情况和prompt内容
sendStreamEndMessage(messageProtobufQuery, messageProtobufReply, emitter,
tokenUsage[0].getPromptTokens(), tokenUsage[0].getCompletionTokens(),
tokenUsage[0].getTotalTokens(), fullPromptContent, LlmConsts.OLLAMA,
(llm != null && StringUtils.hasText(llm.getTextModel())) ? llm.getTextModel()
: "llama2");
// 记录token使用情况
long responseTime = System.currentTimeMillis() - startTime;
String modelType = (llm != null && StringUtils.hasText(llm.getTextModel())) ? llm.getTextModel()
: "llama2";
recordAiTokenUsage(robot, LlmConsts.OLLAMA, modelType,
tokenUsage[0].getPromptTokens(), tokenUsage[0].getCompletionTokens(), success[0],
responseTime);
});
} catch (Exception e) {
log.error("Error starting Ollama stream 4", e);
handleSseError(e, messageProtobufQuery, messageProtobufReply, emitter);
success[0] = false;
// 记录token使用情况
long responseTime = System.currentTimeMillis() - startTime;
String modelType = (llm != null && StringUtils.hasText(llm.getTextModel())) ? llm.getTextModel() : "llama2";
recordAiTokenUsage(robot, LlmConsts.OLLAMA, modelType,
tokenUsage[0].getPromptTokens(), tokenUsage[0].getCompletionTokens(), success[0], responseTime);
}
}
}

5
modules/ai/src/main/java/com/bytedesk/ai/springai/providers/ollama/SpringAIOllamaController.java
View File

@@ -3,7 +3,7 @@
* @Author: jackning 270580156@qq.com
* @Date: 2024-05-31 09:50:56
* @LastEditors: jackning 270580156@qq.com
* @LastEditTime: 2025-08-20 21:25:31
* @LastEditTime: 2025-08-21 12:40:17
* @Description: bytedesk.com https://github.com/Bytedesk/bytedesk
* Please be aware of the BSL license restrictions before installing Bytedesk IM –
* selling, reselling, or hosting Bytedesk IM as a service is a breach of the terms and automatically terminates your rights under the license.
@@ -23,6 +23,7 @@ import org.springframework.ai.chat.prompt.Prompt;
import org.springframework.ai.ollama.OllamaChatModel;
import org.springframework.ai.ollama.api.OllamaApi;
import org.springframework.ai.ollama.api.OllamaOptions;
import org.springframework.boot.autoconfigure.condition.ConditionalOnProperty;
import org.springframework.http.MediaType;
import org.springframework.http.ResponseEntity;
import org.springframework.web.bind.annotation.GetMapping;
@@ -43,7 +44,7 @@ import reactor.core.publisher.Flux;
@RestController
@RequestMapping("/api/v1/ollama")
@RequiredArgsConstructor
// @ConditionalOnProperty(prefix = "spring.ai.ollama.chat", name = "enabled", havingValue = "true", matchIfMissing = false)
@ConditionalOnProperty(prefix = "spring.ai.ollama.chat", name = "enabled", havingValue = "true", matchIfMissing = false)
public class SpringAIOllamaController {
private final SpringAIOllamaService springAIOllamaService;

12
modules/ai/src/main/java/com/bytedesk/ai/springai/providers/ollama/SpringAIOllamaService.java
View File

@@ -2,7 +2,7 @@
* @Author: jackning 270580156@qq.com
* @Date: 2025-02-26 16:59:14
* @LastEditors: jackning 270580156@qq.com
* @LastEditTime: 2025-08-20 10:57:53
* @LastEditTime: 2025-08-21 12:45:56
* @Description: bytedesk.com https://github.com/Bytedesk/bytedesk
* Please be aware of the BSL license restrictions before installing Bytedesk IM –
* selling, reselling, or hosting Bytedesk IM as a service is a breach of the terms and automatically terminates your rights under the license.
@@ -36,6 +36,7 @@ import com.bytedesk.ai.provider.LlmProviderRestService;
import com.bytedesk.ai.robot.RobotLlm;
import com.bytedesk.ai.robot.RobotProtobuf;
import com.bytedesk.ai.springai.service.BaseSpringAIService;
import com.bytedesk.ai.springai.service.ChatTokenUsage;
import com.bytedesk.core.constant.LlmConsts;
import com.bytedesk.core.message.MessageProtobuf;
import com.bytedesk.core.message.MessageTypeEnum;
@@ -154,7 +155,7 @@ public class SpringAIOllamaService extends BaseSpringAIService {
long startTime = System.currentTimeMillis();
final boolean[] success = { false };
final TokenUsage[] tokenUsage = { new TokenUsage(0, 0, 0) };
final ChatTokenUsage[] tokenUsage = { new ChatTokenUsage(0, 0, 0) };
try {
chatModel.stream(prompt).subscribe(
@@ -165,6 +166,7 @@ public class SpringAIOllamaService extends BaseSpringAIService {
for (Generation generation : generations) {
AssistantMessage assistantMessage = generation.getOutput();
String textContent = assistantMessage.getText();
log.info("Ollama API Websocket response text: {}", textContent);
sendMessageWebsocket(MessageTypeEnum.STREAM, textContent, messageProtobufReply);
}
@@ -204,7 +206,7 @@ public class SpringAIOllamaService extends BaseSpringAIService {
protected String processPromptSync(String message, RobotProtobuf robot, String fullPromptContent) {
long startTime = System.currentTimeMillis();
boolean success = false;
TokenUsage tokenUsage = new TokenUsage(0, 0, 0);
ChatTokenUsage tokenUsage = new ChatTokenUsage(0, 0, 0);
log.info("Ollama API sync fullPromptContent: {}", fullPromptContent);
@@ -230,6 +232,7 @@ public class SpringAIOllamaService extends BaseSpringAIService {
// 使用自定义选项创建Prompt
Prompt prompt = new Prompt(message, customOptions);
var response = chatModel.call(prompt);
log.info("Ollama API Sync response metadata: {}", response.getMetadata());
tokenUsage = extractTokenUsage(response);
success = true;
return extractTextFromResponse(response);
@@ -291,7 +294,7 @@ public class SpringAIOllamaService extends BaseSpringAIService {
long startTime = System.currentTimeMillis();
final boolean[] success = { false };
final TokenUsage[] tokenUsage = { new TokenUsage(0, 0, 0) };
final ChatTokenUsage[] tokenUsage = { new ChatTokenUsage(0, 0, 0) };
try {
// 发送初始消息，告知用户请求已收到，正在处理
@@ -305,6 +308,7 @@ public class SpringAIOllamaService extends BaseSpringAIService {
for (Generation generation : generations) {
AssistantMessage assistantMessage = generation.getOutput();
String textContent = assistantMessage.getText();
log.info("Ollama API SSE response text: {}", textContent);
sendStreamMessage(messageProtobufQuery, messageProtobufReply, emitter, textContent);
}

9
modules/ai/src/main/java/com/bytedesk/ai/springai/providers/openai/SpringAIOpenaiService.java
View File

@@ -2,7 +2,7 @@
* @Author: jackning 270580156@qq.com
* @Date: 2025-02-28 11:44:03
* @LastEditors: jackning 270580156@qq.com
* @LastEditTime: 2025-07-16 11:38:24
* @LastEditTime: 2025-08-21 12:46:49
* @Description: bytedesk.com https://github.com/Bytedesk/bytedesk
* Please be aware of the BSL license restrictions before installing Bytedesk IM –
* selling, reselling, or hosting Bytedesk IM as a service is a breach of the terms and automatically terminates your rights under the license.
@@ -31,6 +31,7 @@ import com.bytedesk.ai.springai.service.BaseSpringAIService;
import com.bytedesk.core.constant.LlmConsts;
import com.bytedesk.core.message.MessageProtobuf;
import com.bytedesk.core.message.MessageTypeEnum;
import com.bytedesk.ai.springai.service.ChatTokenUsage;
import lombok.extern.slf4j.Slf4j;
@@ -82,7 +83,7 @@ public class SpringAIOpenaiService extends BaseSpringAIService {
long startTime = System.currentTimeMillis();
final boolean[] success = {false};
final TokenUsage[] tokenUsage = {new TokenUsage(0, 0, 0)};
final ChatTokenUsage[] tokenUsage = {new ChatTokenUsage(0, 0, 0)};
// 使用同一个ChatModel实例，但传入不同的选项
openaiChatModel.stream(requestPrompt).subscribe(
@@ -120,7 +121,7 @@ public class SpringAIOpenaiService extends BaseSpringAIService {
protected String processPromptSync(String message, RobotProtobuf robot, String fullPromptContent) {
long startTime = System.currentTimeMillis();
boolean success = false;
TokenUsage tokenUsage = new TokenUsage(0, 0, 0);
ChatTokenUsage tokenUsage = new ChatTokenUsage(0, 0, 0);
log.info("OpenAI API sync fullPromptContent: {}", fullPromptContent);
@@ -188,7 +189,7 @@ public class SpringAIOpenaiService extends BaseSpringAIService {
long startTime = System.currentTimeMillis();
final boolean[] success = {false};
final TokenUsage[] tokenUsage = {new TokenUsage(0, 0, 0)};
final ChatTokenUsage[] tokenUsage = {new ChatTokenUsage(0, 0, 0)};
openaiChatModel.stream(requestPrompt).subscribe(
response -> {

9
modules/ai/src/main/java/com/bytedesk/ai/springai/providers/openrouter/SpringAIOpenrouterService.java
View File

@@ -2,7 +2,7 @@
* @Author: jackning 270580156@qq.com
* @Date: 2025-02-28 11:44:03
* @LastEditors: jackning 270580156@qq.com
* @LastEditTime: 2025-07-16 11:38:40
* @LastEditTime: 2025-08-21 12:46:55
* @Description: bytedesk.com https://github.com/Bytedesk/bytedesk
* Please be aware of the BSL license restrictions before installing Bytedesk IM –
* selling, reselling, or hosting Bytedesk IM as a service is a breach of the terms and automatically terminates your rights under the license.
@@ -31,6 +31,7 @@ import com.bytedesk.ai.springai.service.BaseSpringAIService;
import com.bytedesk.core.constant.LlmConsts;
import com.bytedesk.core.message.MessageProtobuf;
import com.bytedesk.core.message.MessageTypeEnum;
import com.bytedesk.ai.springai.service.ChatTokenUsage;
import lombok.extern.slf4j.Slf4j;
@@ -83,7 +84,7 @@ public class SpringAIOpenrouterService extends BaseSpringAIService {
long startTime = System.currentTimeMillis();
final boolean[] success = {false};
final TokenUsage[] tokenUsage = {new TokenUsage(0, 0, 0)};
final ChatTokenUsage[] tokenUsage = {new ChatTokenUsage(0, 0, 0)};
// 使用同一个ChatModel实例，但传入不同的选项
openrouterChatModel.stream(requestPrompt).subscribe(
@@ -122,7 +123,7 @@ public class SpringAIOpenrouterService extends BaseSpringAIService {
log.info("SpringAIOpenrouterService processPromptSync with full prompt content: {}", fullPromptContent);
long startTime = System.currentTimeMillis();
boolean success = false;
TokenUsage tokenUsage = new TokenUsage(0, 0, 0);
ChatTokenUsage tokenUsage = new ChatTokenUsage(0, 0, 0);
try {
if (openrouterChatModel == null) {
@@ -184,7 +185,7 @@ public class SpringAIOpenrouterService extends BaseSpringAIService {
long startTime = System.currentTimeMillis();
final boolean[] success = {false};
final TokenUsage[] tokenUsage = {new TokenUsage(0, 0, 0)};
final ChatTokenUsage[] tokenUsage = {new ChatTokenUsage(0, 0, 0)};
openrouterChatModel.stream(requestPrompt).subscribe(
response -> {

9
modules/ai/src/main/java/com/bytedesk/ai/springai/providers/siliconflow/SpringAISiliconFlowService.java
View File

@@ -2,7 +2,7 @@
* @Author: jackning 270580156@qq.com
* @Date: 2025-02-28 11:44:03
* @LastEditors: jackning 270580156@qq.com
* @LastEditTime: 2025-07-16 14:17:40
* @LastEditTime: 2025-08-21 12:47:01
* @Description: bytedesk.com https://github.com/Bytedesk/bytedesk
* Please be aware of the BSL license restrictions before installing Bytedesk IM –
* selling, reselling, or hosting Bytedesk IM as a service is a breach of the terms and automatically terminates your rights under the license.
@@ -32,6 +32,7 @@ import org.springframework.util.StringUtils;
import org.springframework.web.servlet.mvc.method.annotation.SseEmitter;
import java.util.List;
import java.util.Optional;
import com.bytedesk.ai.springai.service.ChatTokenUsage;
/**
* @author: https://github.com/fzj111
@@ -85,7 +86,7 @@ public class SpringAISiliconFlowService extends BaseSpringAIService {
long startTime = System.currentTimeMillis();
final boolean[] success = {false};
final TokenUsage[] tokenUsage = {new TokenUsage(0, 0, 0)};
final ChatTokenUsage[] tokenUsage = {new ChatTokenUsage(0, 0, 0)};
// 使用同一个ChatModel实例，但传入不同的选项
siliconFlowChatModel.get().stream(requestPrompt).subscribe(
@@ -126,7 +127,7 @@ public class SpringAISiliconFlowService extends BaseSpringAIService {
protected String processPromptSync(String message, RobotProtobuf robot, String fullPromptContent) {
long startTime = System.currentTimeMillis();
boolean success = false;
TokenUsage tokenUsage = new TokenUsage(0, 0, 0);
ChatTokenUsage tokenUsage = new ChatTokenUsage(0, 0, 0);
log.info("SiliconFlow API sync fullPromptContent: {}", fullPromptContent);
@@ -197,7 +198,7 @@ public class SpringAISiliconFlowService extends BaseSpringAIService {
long startTime = System.currentTimeMillis();
final boolean[] success = {false};
final TokenUsage[] tokenUsage = {new TokenUsage(0, 0, 0)};
final ChatTokenUsage[] tokenUsage = {new ChatTokenUsage(0, 0, 0)};
siliconFlowChatModel.get().stream(requestPrompt).subscribe(
response -> {

9
modules/ai/src/main/java/com/bytedesk/ai/springai/providers/tencent/SpringAITencentService.java
View File

@@ -2,7 +2,7 @@
* @Author: jackning 270580156@qq.com
* @Date: 2025-02-28 11:44:03
* @LastEditors: jackning 270580156@qq.com
* @LastEditTime: 2025-07-16 14:17:58
* @LastEditTime: 2025-08-21 12:47:07
* @Description: bytedesk.com https://github.com/Bytedesk/bytedesk
* Please be aware of the BSL license restrictions before installing Bytedesk IM –
* selling, reselling, or hosting Bytedesk IM as a service is a breach of the terms and automatically terminates your rights under the license.
@@ -32,6 +32,7 @@ import com.bytedesk.ai.springai.service.BaseSpringAIService;
import com.bytedesk.core.constant.LlmConsts;
import com.bytedesk.core.message.MessageProtobuf;
import com.bytedesk.core.message.MessageTypeEnum;
import com.bytedesk.ai.springai.service.ChatTokenUsage;
import lombok.extern.slf4j.Slf4j;
@@ -83,7 +84,7 @@ public class SpringAITencentService extends BaseSpringAIService {
long startTime = System.currentTimeMillis();
final boolean[] success = {false};
final TokenUsage[] tokenUsage = {new TokenUsage(0, 0, 0)};
final ChatTokenUsage[] tokenUsage = {new ChatTokenUsage(0, 0, 0)};
// 使用同一个ChatModel实例，但传入不同的选项
tencentChatModel.stream(requestPrompt).subscribe(
@@ -123,7 +124,7 @@ public class SpringAITencentService extends BaseSpringAIService {
protected String processPromptSync(String message, RobotProtobuf robot, String fullPromptContent) {
long startTime = System.currentTimeMillis();
boolean success = false;
TokenUsage tokenUsage = new TokenUsage(0, 0, 0);
ChatTokenUsage tokenUsage = new ChatTokenUsage(0, 0, 0);
log.info("Tencent API sync fullPromptContent: {}", fullPromptContent);
@@ -192,7 +193,7 @@ public class SpringAITencentService extends BaseSpringAIService {
long startTime = System.currentTimeMillis();
final boolean[] success = {false};
final TokenUsage[] tokenUsage = {new TokenUsage(0, 0, 0)};
final ChatTokenUsage[] tokenUsage = {new ChatTokenUsage(0, 0, 0)};
tencentChatModel.stream(requestPrompt).subscribe(
response -> {

9
modules/ai/src/main/java/com/bytedesk/ai/springai/providers/volcengine/SpringAIVolcengineService.java
View File

@@ -2,7 +2,7 @@
* @Author: jackning 270580156@qq.com
* @Date: 2025-02-28 11:44:03
* @LastEditors: jackning 270580156@qq.com
* @LastEditTime: 2025-07-16 14:16:43
* @LastEditTime: 2025-08-21 12:47:12
* @Description: bytedesk.com https://github.com/Bytedesk/bytedesk
* Please be aware of the BSL license restrictions before installing Bytedesk IM –
* selling, reselling, or hosting Bytedesk IM as a service is a breach of the terms and automatically terminates your rights under the license.
@@ -32,6 +32,7 @@ import com.bytedesk.core.constant.LlmConsts;
import com.bytedesk.core.message.MessageProtobuf;
import com.bytedesk.core.message.MessageTypeEnum;
import lombok.extern.slf4j.Slf4j;
import com.bytedesk.ai.springai.service.ChatTokenUsage;
@Slf4j
@Service
@@ -82,7 +83,7 @@ public class SpringAIVolcengineService extends BaseSpringAIService {
long startTime = System.currentTimeMillis();
final boolean[] success = {false};
final TokenUsage[] tokenUsage = {new TokenUsage(0, 0, 0)};
final ChatTokenUsage[] tokenUsage = {new ChatTokenUsage(0, 0, 0)};
// 使用同一个ChatModel实例，但传入不同的选项
volcengineChatModel.stream(requestPrompt).subscribe(
@@ -121,7 +122,7 @@ public class SpringAIVolcengineService extends BaseSpringAIService {
log.info("SpringAIVolcengineService processPromptSync with full prompt content: {}", fullPromptContent);
long startTime = System.currentTimeMillis();
boolean success = false;
TokenUsage tokenUsage = new TokenUsage(0, 0, 0);
ChatTokenUsage tokenUsage = new ChatTokenUsage(0, 0, 0);
try {
if (volcengineChatModel == null) {
@@ -191,7 +192,7 @@ public class SpringAIVolcengineService extends BaseSpringAIService {
long startTime = System.currentTimeMillis();
final boolean[] success = {false};
final TokenUsage[] tokenUsage = {new TokenUsage(0, 0, 0)};
final ChatTokenUsage[] tokenUsage = {new ChatTokenUsage(0, 0, 0)};
volcengineChatModel.stream(requestPrompt).subscribe(
response -> {

41
modules/ai/src/main/java/com/bytedesk/ai/springai/providers/zhipuai/SpringAIZhipuaiService.java
View File

@@ -2,7 +2,7 @@
* @Author: jackning 270580156@qq.com
* @Date: 2025-02-26 16:58:56
* @LastEditors: jackning 270580156@qq.com
* @LastEditTime: 2025-07-16 13:58:57
* @LastEditTime: 2025-08-21 12:47:17
* @Description: bytedesk.com https://github.com/Bytedesk/bytedesk
* Please be aware of the BSL license restrictions before installing Bytedesk IM –
* selling, reselling, or hosting Bytedesk IM as a service is a breach of the terms and automatically terminates your rights under the license.
@@ -35,6 +35,7 @@ import com.bytedesk.ai.springai.service.BaseSpringAIService;
import com.bytedesk.core.constant.LlmConsts;
import com.bytedesk.core.message.MessageProtobuf;
import com.bytedesk.core.message.MessageTypeEnum;
import com.bytedesk.ai.springai.service.ChatTokenUsage;
import lombok.extern.slf4j.Slf4j;
import reactor.core.publisher.Flux;
@@ -117,7 +118,7 @@ public class SpringAIZhipuaiService extends BaseSpringAIService {
long startTime = System.currentTimeMillis();
final boolean[] success = {false};
final TokenUsage[] tokenUsage = {new TokenUsage(0, 0, 0)};
final ChatTokenUsage[] tokenUsage = {new ChatTokenUsage(0, 0, 0)};
chatModel.stream(prompt).subscribe(
response -> {
@@ -160,7 +161,7 @@ public class SpringAIZhipuaiService extends BaseSpringAIService {
protected String processPromptSync(String message, RobotProtobuf robot, String fullPromptContent) {
long startTime = System.currentTimeMillis();
boolean success = false;
TokenUsage tokenUsage = new TokenUsage(0, 0, 0);
ChatTokenUsage tokenUsage = new ChatTokenUsage(0, 0, 0);
log.info("Zhipuai API sync fullPromptContent: {}", fullPromptContent);
@@ -263,7 +264,7 @@ public class SpringAIZhipuaiService extends BaseSpringAIService {
long startTime = System.currentTimeMillis();
final boolean[] success = {false};
final TokenUsage[] tokenUsage = {new TokenUsage(0, 0, 0)};
final ChatTokenUsage[] tokenUsage = {new ChatTokenUsage(0, 0, 0)};
final ChatResponse[] lastResponse = {null};
Flux<ChatResponse> responseFlux = chatModel.stream(prompt);
@@ -341,16 +342,16 @@ public class SpringAIZhipuaiService extends BaseSpringAIService {
* @param response ChatResponse对象
* @return TokenUsage对象
*/
private TokenUsage extractZhipuaiTokenUsage(org.springframework.ai.chat.model.ChatResponse response) {
private ChatTokenUsage extractZhipuaiTokenUsage(org.springframework.ai.chat.model.ChatResponse response) {
try {
if (response == null) {
return new TokenUsage(0, 0, 0);
return new ChatTokenUsage(0, 0, 0);
}
var metadata = response.getMetadata();
if (metadata == null) {
log.warn("Zhipuai API response metadata is null");
return new TokenUsage(0, 0, 0);
return new ChatTokenUsage(0, 0, 0);
}
log.info("Zhipuai API manual token extraction - metadata: {}", metadata);
@@ -440,7 +441,7 @@ public class SpringAIZhipuaiService extends BaseSpringAIService {
log.info("Zhipuai API manual token extraction result from string parsing - prompt: {}, completion: {}, total: {}",
promptTokens, completionTokens, totalTokens);
return new TokenUsage(promptTokens, completionTokens, totalTokens);
return new ChatTokenUsage(promptTokens, completionTokens, totalTokens);
}
}
@@ -491,7 +492,7 @@ public class SpringAIZhipuaiService extends BaseSpringAIService {
log.info("Zhipuai API manual token extraction result - prompt: {}, completion: {}, total: {}",
promptTokens, completionTokens, totalTokens);
return new TokenUsage(promptTokens, completionTokens, totalTokens);
return new ChatTokenUsage(promptTokens, completionTokens, totalTokens);
}
}
@@ -505,7 +506,7 @@ public class SpringAIZhipuaiService extends BaseSpringAIService {
// 方法4: 如果手动提取失败，尝试使用原始的extractTokenUsage方法作为后备
log.info("Zhipuai API manual extraction failed, trying original extractTokenUsage method");
TokenUsage fallbackUsage = extractTokenUsage(response);
ChatTokenUsage fallbackUsage = extractTokenUsage(response);
if (fallbackUsage.getTotalTokens() > 0) {
log.info("Zhipuai API fallback extraction successful: {}", fallbackUsage);
return fallbackUsage;
@@ -513,7 +514,7 @@ public class SpringAIZhipuaiService extends BaseSpringAIService {
// 方法5: 如果所有方法都失败，尝试估算token使用量
log.info("Zhipuai API all extraction methods failed, attempting to estimate token usage");
TokenUsage estimatedUsage = estimateTokenUsageFromResponse(response);
ChatTokenUsage estimatedUsage = estimateTokenUsageFromResponse(response);
if (estimatedUsage.getTotalTokens() > 0) {
log.info("Zhipuai API estimated token usage: {}", estimatedUsage);
return estimatedUsage;
@@ -525,7 +526,7 @@ public class SpringAIZhipuaiService extends BaseSpringAIService {
// 如果手动提取出错，尝试使用原始的extractTokenUsage方法作为后备
try {
log.info("Zhipuai API manual extraction error, trying original extractTokenUsage method");
TokenUsage fallbackUsage = extractTokenUsage(response);
ChatTokenUsage fallbackUsage = extractTokenUsage(response);
if (fallbackUsage.getTotalTokens() > 0) {
log.info("Zhipuai API fallback extraction successful after error: {}", fallbackUsage);
return fallbackUsage;
@@ -536,7 +537,7 @@ public class SpringAIZhipuaiService extends BaseSpringAIService {
}
log.warn("Zhipuai API all token extraction methods failed, returning zeros");
return new TokenUsage(0, 0, 0);
return new ChatTokenUsage(0, 0, 0);
}
/**
@@ -545,10 +546,10 @@ public class SpringAIZhipuaiService extends BaseSpringAIService {
* @param response ChatResponse对象
* @return 估算的TokenUsage对象
*/
private TokenUsage estimateTokenUsageFromResponse(org.springframework.ai.chat.model.ChatResponse response) {
private ChatTokenUsage estimateTokenUsageFromResponse(org.springframework.ai.chat.model.ChatResponse response) {
try {
if (response == null) {
return new TokenUsage(0, 0, 0);
return new ChatTokenUsage(0, 0, 0);
}
// 获取输出文本
@@ -563,11 +564,11 @@ public class SpringAIZhipuaiService extends BaseSpringAIService {
log.info("Zhipuai API estimated tokens - output: {} chars -> {} tokens, estimated prompt: {} tokens, total: {} tokens",
outputText.length(), completionTokens, promptTokens, totalTokens);
return new TokenUsage(promptTokens, completionTokens, totalTokens);
return new ChatTokenUsage(promptTokens, completionTokens, totalTokens);
} catch (Exception e) {
log.error("Error estimating token usage", e);
return new TokenUsage(0, 0, 0);
return new ChatTokenUsage(0, 0, 0);
}
}
@@ -639,15 +640,15 @@ public class SpringAIZhipuaiService extends BaseSpringAIService {
}
// 测试手动token提取
TokenUsage manualUsage = extractZhipuaiTokenUsage(response);
ChatTokenUsage manualUsage = extractZhipuaiTokenUsage(response);
log.info("Zhipuai API test manual token extraction result: {}", manualUsage);
// 测试原始token提取
TokenUsage originalUsage = extractTokenUsage(response);
ChatTokenUsage originalUsage = extractTokenUsage(response);
log.info("Zhipuai API test original token extraction result: {}", originalUsage);
// 测试token估算功能
TokenUsage estimatedUsage = estimateTokenUsageFromResponse(response);
ChatTokenUsage estimatedUsage = estimateTokenUsageFromResponse(response);
log.info("Zhipuai API test estimated token usage result: {}", estimatedUsage);
// 测试token估算算法

37
modules/ai/src/main/java/com/bytedesk/ai/springai/service/BaseSpringAIService.java
View File

@@ -721,11 +721,6 @@ public abstract class BaseSpringAIService implements SpringAIService {
processPromptSse(aiPrompt, robot, messageProtobufQuery, messageProtobufReply, emitter, fullPromptContent);
}
// private String createAndProcessPromptSync(String query, String context, RobotProtobuf robot,
// MessageProtobuf messageProtobufQuery, MessageProtobuf messageProtobufReply) {
// return createAndProcessPromptSyncWithPrompt(query, context, robot, messageProtobufQuery, messageProtobufReply).getResponse();
// }
private PromptResult createAndProcessPromptSyncWithPrompt(String query, String context, RobotProtobuf robot,
MessageProtobuf messageProtobufQuery, MessageProtobuf messageProtobufReply) {
@@ -1145,7 +1140,7 @@ public abstract class BaseSpringAIService implements SpringAIService {
* @param response ChatResponse from AI service
* @return TokenUsage object containing prompt and completion tokens
*/
protected TokenUsage extractTokenUsage(Object response) {
protected ChatTokenUsage extractTokenUsage(Object response) {
try {
if (response instanceof org.springframework.ai.chat.model.ChatResponse) {
org.springframework.ai.chat.model.ChatResponse chatResponse = (org.springframework.ai.chat.model.ChatResponse) response;
@@ -1306,7 +1301,7 @@ public abstract class BaseSpringAIService implements SpringAIService {
log.info("BaseSpringAIService extractTokenUsage extracted tokens - prompt: {}, completion: {}, total: {}",
prompt, completion, total);
return new TokenUsage(prompt, completion, total);
return new ChatTokenUsage(prompt, completion, total);
}
}
} catch (Exception e) {
@@ -1315,7 +1310,7 @@ public abstract class BaseSpringAIService implements SpringAIService {
// 如果无法提取，返回默认值
log.warn("BaseSpringAIService extractTokenUsage could not extract token usage, returning zeros");
return new TokenUsage(0, 0, 0);
return new ChatTokenUsage(0, 0, 0);
}
/**
@@ -1421,21 +1416,21 @@ public abstract class BaseSpringAIService implements SpringAIService {
/**
* Token usage data class
*/
protected static class TokenUsage {
private final long promptTokens;
private final long completionTokens;
private final long totalTokens;
// protected static class TokenUsage {
// private final long promptTokens;
// private final long completionTokens;
// private final long totalTokens;
public TokenUsage(long promptTokens, long completionTokens, long totalTokens) {
this.promptTokens = promptTokens;
this.completionTokens = completionTokens;
this.totalTokens = totalTokens;
}
// public TokenUsage(long promptTokens, long completionTokens, long totalTokens) {
// this.promptTokens = promptTokens;
// this.completionTokens = completionTokens;
// this.totalTokens = totalTokens;
// }
public long getPromptTokens() { return promptTokens; }
public long getCompletionTokens() { return completionTokens; }
public long getTotalTokens() { return totalTokens; }
}
// public long getPromptTokens() { return promptTokens; }
// public long getCompletionTokens() { return completionTokens; }
// public long getTotalTokens() { return totalTokens; }
// }
// 带prompt参数的抽象方法重载
protected abstract void processPromptWebsocket(Prompt prompt, RobotProtobuf robot, MessageProtobuf messageProtobufQuery,

29
modules/ai/src/main/java/com/bytedesk/ai/springai/service/ChatTokenUsage.java Normal file
View File

@@ -0,0 +1,29 @@
/*
* @Author: jackning 270580156@qq.com
* @Date: 2025-08-21 12:42:33
* @LastEditors: jackning 270580156@qq.com
* @LastEditTime: 2025-08-21 13:05:30
* @Description: bytedesk.com https://github.com/Bytedesk/bytedesk
* Please be aware of the BSL license restrictions before installing Bytedesk IM –
* selling, reselling, or hosting Bytedesk IM as a service is a breach of the terms and automatically terminates your rights under the license.
* Business Source License 1.1: https://github.com/Bytedesk/bytedesk/blob/main/LICENSE
* contact: 270580156@qq.com
*
* Copyright (c) 2025 by bytedesk.com, All Rights Reserved.
*/
package com.bytedesk.ai.springai.service;
import lombok.AllArgsConstructor;
import lombok.Getter;
import lombok.NoArgsConstructor;
import lombok.Setter;
@Getter
@Setter
@AllArgsConstructor
@NoArgsConstructor
public class ChatTokenUsage {
private long promptTokens;
private long completionTokens;
private long totalTokens;
}

4
modules/ai/src/main/java/com/bytedesk/ai/zhipuai/ZhipuaiChatConfig.java
View File

@@ -2,7 +2,7 @@
* @Author: jackning 270580156@qq.com
* @Date: 2025-02-19 09:39:15
* @LastEditors: jackning 270580156@qq.com
* @LastEditTime: 2025-07-16 09:33:50
* @LastEditTime: 2025-08-21 12:22:06
* @Description: bytedesk.com https://github.com/Bytedesk/bytedesk
* Please be aware of the BSL license restrictions before installing Bytedesk IM –
* selling, reselling, or hosting Bytedesk IM as a service is a breach of the terms and automatically terminates your rights under the license.
@@ -41,7 +41,7 @@ public class ZhipuaiChatConfig {
@Value("${spring.ai.zhipuai.api-key:}")
private String apiKey;
@Value("${spring.ai.zhipuai.chat.options.model:glm-4}")
@Value("${spring.ai.zhipuai.chat.options.model:glm-4-flash}")
private String model;
@Value("${spring.ai.zhipuai.chat.options.temperature:0.7}")

624
modules/ai/src/main/java/com/bytedesk/ai/zhipuai/ZhipuaiChatService.java Normal file
View File

@@ -0,0 +1,624 @@
/*
* @Author: jackning 270580156@qq.com
* @Date: 2025-08-21 12:26:02
* @LastEditors: jackning 270580156@qq.com
* @LastEditTime: 2025-08-21 12:37:21
* @Description: bytedesk.com https://github.com/Bytedesk/bytedesk
* Please be aware of the BSL license restrictions before installing Bytedesk IM –
* selling, reselling, or hosting Bytedesk IM as a service is a breach of the terms and automatically terminates your rights under the license.
* Business Source License 1.1: https://github.com/Bytedesk/bytedesk/blob/main/LICENSE
* contact: 270580156@qq.com
*
* Copyright (c) 2025 by bytedesk.com, All Rights Reserved.
*/
package com.bytedesk.ai.zhipuai;
import java.io.File;
import java.util.ArrayList;
import java.util.HashMap;
import java.util.List;
import java.util.Map;
import org.springframework.beans.factory.annotation.Autowired;
import org.springframework.beans.factory.annotation.Qualifier;
import org.springframework.boot.autoconfigure.condition.ConditionalOnProperty;
import org.springframework.stereotype.Service;
import com.zhipu.oapi.ClientV4;
import com.zhipu.oapi.Constants;
import com.zhipu.oapi.service.v4.model.ChatCompletionRequest;
import com.zhipu.oapi.service.v4.model.ChatFunction;
import com.zhipu.oapi.service.v4.model.ChatMessage;
import com.zhipu.oapi.service.v4.model.ChatMessageAccumulator;
import com.zhipu.oapi.service.v4.model.ChatMessageRole;
import com.zhipu.oapi.service.v4.model.ChatMeta;
import com.zhipu.oapi.service.v4.model.ChatTool;
import com.zhipu.oapi.service.v4.model.ChatToolType;
import com.zhipu.oapi.service.v4.model.ModelApiResponse;
import com.zhipu.oapi.service.v4.model.ModelData;
import com.zhipu.oapi.service.v4.model.QueryModelResultRequest;
import com.zhipu.oapi.service.v4.model.QueryModelResultResponse;
import com.zhipu.oapi.service.v4.model.WebSearch;
import lombok.extern.slf4j.Slf4j;
import reactor.core.publisher.Flux;
@Slf4j
@Service
@ConditionalOnProperty(prefix = "spring.ai.zhipuai.chat", name = "enabled", havingValue = "true", matchIfMissing = false)
public class ZhipuaiChatService {
@Autowired
@Qualifier("zhipuaiChatClient")
private ClientV4 client;
@Autowired
private ZhipuaiChatConfig zhipuaiChatConfig;
/**
* 角色扮演聊天
*/
public String rolePlayChat(String message, String userInfo, String botInfo, String botName, String userName) {
// 添加请求日志
log.info("Zhipuai API role play request - message length: {}, userInfo: {}, botInfo: {}, botName: {}, userName: {}",
message.length(), userInfo, botInfo, botName, userName);
long startTime = System.currentTimeMillis();
// 使用默认client进行角色扮演聊天
ClientV4 chatClient = client;
try {
if (client == null) {
log.error("Zhipuai API client is null");
return "Zhipuai client is not available";
}
List<ChatMessage> messages = new ArrayList<>();
ChatMessage chatMessage = new ChatMessage(ChatMessageRole.USER.value(), message);
messages.add(chatMessage);
ChatMeta meta = new ChatMeta();
meta.setUser_info(userInfo);
meta.setBot_info(botInfo);
meta.setBot_name(botName);
meta.setUser_name(userName);
String requestId = String.format("roleplay-%d", System.currentTimeMillis());
ChatCompletionRequest chatCompletionRequest = ChatCompletionRequest.builder()
.model(Constants.ModelCharGLM3)
.stream(Boolean.FALSE)
.invokeMethod(Constants.invokeMethod)
.messages(messages)
.meta(meta)
.requestId(requestId)
.build();
log.info("Zhipuai API role play invoking model with requestId: {}", requestId);
ModelApiResponse response = chatClient.invokeModelApi(chatCompletionRequest);
if (response.isSuccess() && response.getData() != null) {
log.info("Zhipuai API role play response success");
// 提取token使用情况
// TokenUsage tokenUsage = extractZhipuaiTokenUsage(response);
// log.info("Zhipuai API role play tokenUsage: {}", tokenUsage);
Object content = response.getData().getChoices().get(0).getMessage().getContent();
return content != null ? content.toString() : null;
} else {
log.error("Zhipuai API role play error: {}", response.getError());
return "Error: " + (response.getError() != null ? response.getError().getMessage() : "Unknown error");
}
} catch (Exception e) {
log.error("Zhipuai API role play error: ", e);
return "Error: " + e.getMessage();
} finally {
long responseTime = System.currentTimeMillis() - startTime;
log.info("Zhipuai API role play completed in {}ms", responseTime);
}
}
/**
* Function Calling 聊天
*/
public String functionCallingChat(String message, List<ChatFunction> functions) {
return functionCallingChat(message, null, null, functions);
}
/**
* Function Calling 聊天（带自定义参数）
*/
public String functionCallingChat(String message, String model, Double temperature, List<ChatFunction> functions) {
// 添加请求日志
log.info("Zhipuai API function calling request - message length: {}, model: {}, temperature: {}, functions count: {}",
message.length(), model, temperature, functions != null ? functions.size() : 0);
long startTime = System.currentTimeMillis();
// 使用默认client进行函数调用聊天
ClientV4 chatClient = client;
try {
List<ChatMessage> messages = new ArrayList<>();
ChatMessage chatMessage = new ChatMessage(ChatMessageRole.USER.value(), message);
messages.add(chatMessage);
List<ChatTool> chatToolList = new ArrayList<>();
if (functions != null) {
for (ChatFunction function : functions) {
ChatTool chatTool = new ChatTool();
chatTool.setType(ChatToolType.FUNCTION.value());
chatTool.setFunction(function);
chatToolList.add(chatTool);
}
}
String requestId = String.format("function-%d", System.currentTimeMillis());
ChatCompletionRequest chatCompletionRequest = ChatCompletionRequest.builder()
.model(model != null ? model : zhipuaiChatConfig.getModel())
.stream(Boolean.FALSE)
.invokeMethod(Constants.invokeMethod)
.messages(messages)
.requestId(requestId)
.temperature(temperature != null ? temperature.floatValue() : (float) zhipuaiChatConfig.getTemperature())
.tools(chatToolList)
.toolChoice("auto")
.build();
log.info("Zhipuai API function calling invoking model with requestId: {}", requestId);
ModelApiResponse response = chatClient.invokeModelApi(chatCompletionRequest);
if (response.isSuccess() && response.getData() != null) {
log.info("Zhipuai API function calling response success");
// 提取token使用情况
// TokenUsage tokenUsage = extractZhipuaiTokenUsage(response);
// log.info("Zhipuai API function calling tokenUsage: {}", tokenUsage);
Object content = response.getData().getChoices().get(0).getMessage().getContent();
return content != null ? content.toString() : null;
} else {
log.error("Zhipuai API function calling error: {}", response.getError());
return "Error: " + (response.getError() != null ? response.getError().getMessage() : "Unknown error");
}
} catch (Exception e) {
log.error("Zhipuai API function calling error: ", e);
return "Error: " + e.getMessage();
} finally {
long responseTime = System.currentTimeMillis() - startTime;
log.info("Zhipuai API function calling completed in {}ms", responseTime);
}
}
/**
* 流式 Function Calling 聊天
*/
public Flux<String> functionCallingChatStream(String message, List<ChatFunction> functions) {
return functionCallingChatStream(message, null, null, functions);
}
/**
* 流式 Function Calling 聊天（带自定义参数）
*/
public Flux<String> functionCallingChatStream(String message, String model, Double temperature, List<ChatFunction> functions) {
// 使用默认client进行流式函数调用聊天
ClientV4 chatClient = client;
try {
List<ChatMessage> messages = new ArrayList<>();
ChatMessage chatMessage = new ChatMessage(ChatMessageRole.USER.value(), message);
messages.add(chatMessage);
List<ChatTool> chatToolList = new ArrayList<>();
if (functions != null) {
for (ChatFunction function : functions) {
ChatTool chatTool = new ChatTool();
chatTool.setType(ChatToolType.FUNCTION.value());
chatTool.setFunction(function);
chatToolList.add(chatTool);
}
}
String requestId = String.format("function-stream-%d", System.currentTimeMillis());
ChatCompletionRequest chatCompletionRequest = ChatCompletionRequest.builder()
.model(model != null ? model : zhipuaiChatConfig.getModel())
.stream(Boolean.TRUE)
.messages(messages)
.requestId(requestId)
.temperature(temperature != null ? temperature.floatValue() : (float) zhipuaiChatConfig.getTemperature())
.tools(chatToolList)
.toolChoice("auto")
.build();
ModelApiResponse response = chatClient.invokeModelApi(chatCompletionRequest);
if (response.isSuccess()) {
return Flux.from(mapStreamToAccumulator(response.getFlowable()).map(accumulator -> {
log.info("Zhipuai API function calling accumulator received: {}", accumulator);
log.info("Zhipuai API function calling accumulator class: {}", accumulator.getClass().getName());
Object delta = accumulator.getDelta();
log.info("Zhipuai API function calling delta: {}", delta);
log.info("Zhipuai API function calling delta class: {}", delta != null ? delta.getClass().getName() : "null");
// 处理tool_calls（如果有的话）
if (delta != null && delta instanceof com.zhipu.oapi.service.v4.model.ChatMessage) {
com.zhipu.oapi.service.v4.model.ChatMessage deltaMessage = (com.zhipu.oapi.service.v4.model.ChatMessage) delta;
if (deltaMessage.getTool_calls() != null) {
log.info("Zhipuai API function calling tool_calls: {}", deltaMessage.getTool_calls());
}
}
if (delta instanceof com.zhipu.oapi.service.v4.model.ChatMessage) {
Object content = ((com.zhipu.oapi.service.v4.model.ChatMessage) delta).getContent();
log.info("Zhipuai API function calling content: {}", content);
return content != null ? content.toString() : "";
} else if (delta != null) {
String deltaStr = delta.toString();
log.info("Zhipuai API function calling delta as string: {}", deltaStr);
// 尝试从JSON字符串中提取content字段
// String extractedContent = extractContentFromDeltaString(deltaStr);
// if (extractedContent != null && !extractedContent.isEmpty()) {
// log.info("Zhipuai API function calling extracted content: {}", extractedContent);
// return extractedContent;
// } else if (!isEmptyAssistantMessage(deltaStr)) {
// return deltaStr;
// } else {
// return "";
// }
}
return "";
}));
} else {
log.error("Zhipuai API error: {}", response.getError());
return Flux.just("Error: " + (response.getError() != null ? response.getError().getMessage() : "Unknown error"));
}
} catch (Exception e) {
log.error("Error in functionCallingChatStream", e);
return Flux.just("Error: " + e.getMessage());
}
}
/**
* 图像生成 - 暂不支持，需要等待SDK更新
*/
public String generateImage(String prompt) {
return "Image generation is not supported in current SDK version";
}
/**
* 图像生成（带请求ID）- 暂不支持，需要等待SDK更新
*/
public String generateImage(String prompt, String requestId) {
return "Image generation is not supported in current SDK version";
}
/**
* 向量嵌入 - 暂不支持，需要等待SDK更新
*/
public List<Double> getEmbedding(String text) {
log.warn("Embedding is not supported in current SDK version");
return new ArrayList<>();
}
/**
* 批量向量嵌入 - 暂不支持，需要等待SDK更新
*/
public List<List<Double>> getEmbeddings(List<String> texts) {
log.warn("Embeddings is not supported in current SDK version");
return new ArrayList<>();
}
/**
* 语音合成 - 暂不支持，需要等待SDK更新
*/
public File generateSpeech(String text, String voice, String responseFormat) {
log.warn("Speech synthesis is not supported in current SDK version");
return null;
}
/**
* 自定义语音合成 - 暂不支持，需要等待SDK更新
*/
public File generateCustomSpeech(String text, String voiceText, File voiceData, String responseFormat) {
log.warn("Custom voice synthesis is not supported in current SDK version");
return null;
}
/**
* 文件上传 - 暂不支持，需要等待SDK更新
*/
public String uploadFile(String filePath, String purpose) {
return "File upload is not supported in current SDK version";
}
/**
* 查询文件列表 - 暂不支持，需要等待SDK更新
*/
public List<Map<String, Object>> queryFiles() {
log.warn("File query is not supported in current SDK version");
return new ArrayList<>();
}
/**
* 下载文件内容 - 暂不支持，需要等待SDK更新
*/
public File downloadFile(String fileId, String outputPath) {
log.warn("File download is not supported in current SDK version");
return null;
}
/**
* 创建微调任务 - 暂不支持，需要等待SDK更新
*/
public String createFineTuningJob(String model, String trainingFile) {
return "Fine-tuning is not supported in current SDK version";
}
/**
* 查询微调任务 - 暂不支持，需要等待SDK更新
*/
public Map<String, Object> queryFineTuningJob(String jobId) {
log.warn("Fine-tuning query is not supported in current SDK version");
return new HashMap<>();
}
/**
* 异步聊天
*/
public String chatAsync(String message) {
// 添加请求日志
log.info("Zhipuai API async request - message length: {}", message.length());
long startTime = System.currentTimeMillis();
// 使用默认client进行异步聊天
ClientV4 chatClient = client;
try {
List<ChatMessage> messages = new ArrayList<>();
ChatMessage chatMessage = new ChatMessage(ChatMessageRole.USER.value(), message);
messages.add(chatMessage);
ChatCompletionRequest chatCompletionRequest = ChatCompletionRequest.builder()
.model(zhipuaiChatConfig.getModel())
.stream(Boolean.FALSE)
.invokeMethod(Constants.invokeMethodAsync)
.messages(messages)
.build();
log.info("Zhipuai API async invoking model");
ModelApiResponse response = chatClient.invokeModelApi(chatCompletionRequest);
if (response.isSuccess() && response.getData() != null) {
String taskId = response.getData().getId();
log.info("Zhipuai API async task created with taskId: {}", taskId);
// 轮询获取结果
return pollAsyncResult(taskId);
} else {
log.error("Zhipuai API async error: {}", response.getError());
return "Error: " + (response.getError() != null ? response.getError().getMessage() : "Unknown error");
}
} catch (Exception e) {
log.error("Zhipuai API async error: ", e);
return "Error: " + e.getMessage();
} finally {
long responseTime = System.currentTimeMillis() - startTime;
log.info("Zhipuai API async completed in {}ms", responseTime);
}
}
/**
* 轮询异步结果
*/
private String pollAsyncResult(String taskId) {
log.info("Zhipuai API starting async result polling for taskId: {}", taskId);
try {
int maxAttempts = 30; // 最多轮询30次
int attempt = 0;
while (attempt < maxAttempts) {
log.debug("Zhipuai API polling attempt {}/{} for taskId: {}", attempt + 1, maxAttempts, taskId);
QueryModelResultRequest request = new QueryModelResultRequest();
request.setTaskId(taskId);
QueryModelResultResponse response = client.queryModelResult(request);
if (response.isSuccess() && response.getData() != null) {
Object taskStatus = response.getData().getTaskStatus();
log.debug("Zhipuai API task status: {} for taskId: {}", taskStatus, taskId);
if ("SUCCESS".equals(taskStatus.toString())) {
log.info("Zhipuai API async task completed successfully for taskId: {}", taskId);
Object content = response.getData().getChoices().get(0).getMessage().getContent();
return content != null ? content.toString() : null;
} else if ("FAILED".equals(taskStatus.toString())) {
log.error("Zhipuai API async task failed for taskId: {}", taskId);
return "Task failed";
}
} else {
log.warn("Zhipuai API async polling response not successful for taskId: {}", taskId);
}
attempt++;
Thread.sleep(2000); // 等待2秒后重试
}
log.error("Zhipuai API async task timeout after {} attempts for taskId: {}", maxAttempts, taskId);
return "Task timeout after " + maxAttempts + " attempts";
} catch (Exception e) {
log.error("Zhipuai API error polling async result for taskId: {}", taskId, e);
return "Error: " + e.getMessage();
}
}
/**
* 带Web搜索的聊天
*/
public String chatWithWebSearch(String message, String searchQuery) {
// 添加请求日志
log.info("Zhipuai API web search request - message length: {}, searchQuery: {}",
message.length(), searchQuery);
long startTime = System.currentTimeMillis();
// 使用默认client进行网络搜索聊天
ClientV4 chatClient = client;
try {
List<ChatMessage> messages = new ArrayList<>();
ChatMessage chatMessage = new ChatMessage(ChatMessageRole.USER.value(), message);
messages.add(chatMessage);
List<ChatTool> chatToolList = new ArrayList<>();
// 添加Web搜索工具
ChatTool webSearchTool = new ChatTool();
webSearchTool.setType(ChatToolType.WEB_SEARCH.value());
WebSearch webSearch = new WebSearch();
webSearch.setSearch_query(searchQuery);
webSearch.setSearch_result(true);
webSearch.setEnable(true);
webSearchTool.setWeb_search(webSearch);
chatToolList.add(webSearchTool);
String requestId = String.format("websearch-%d", System.currentTimeMillis());
ChatCompletionRequest chatCompletionRequest = ChatCompletionRequest.builder()
.model(zhipuaiChatConfig.getModel())
.stream(Boolean.FALSE)
.invokeMethod(Constants.invokeMethod)
.messages(messages)
.requestId(requestId)
.tools(chatToolList)
.toolChoice("auto")
.build();
log.info("Zhipuai API web search invoking model with requestId: {}", requestId);
ModelApiResponse response = chatClient.invokeModelApi(chatCompletionRequest);
if (response.isSuccess() && response.getData() != null) {
log.info("Zhipuai API web search response success");
// 提取token使用情况
// TokenUsage tokenUsage = extractZhipuaiTokenUsage(response);
// log.info("Zhipuai API web search tokenUsage: {}", tokenUsage);
Object content = response.getData().getChoices().get(0).getMessage().getContent();
return content != null ? content.toString() : null;
} else {
log.error("Zhipuai API web search error: {}", response.getError());
return "Error: " + (response.getError() != null ? response.getError().getMessage() : "Unknown error");
}
} catch (Exception e) {
log.error("Zhipuai API web search error: ", e);
return "Error: " + e.getMessage();
} finally {
long responseTime = System.currentTimeMillis() - startTime;
log.info("Zhipuai API web search completed in {}ms", responseTime);
}
}
/**
* 语音模型聊天 - 暂不支持，需要等待SDK更新
*/
public String chatWithVoice(String message) {
log.warn("Voice chat is not supported in current SDK version");
return "Voice chat is not supported in current SDK version";
}
/**
* 将流式响应转换为Accumulator，参考官方示例
*/
private io.reactivex.Flowable<ChatMessageAccumulator> mapStreamToAccumulator(io.reactivex.Flowable<ModelData> flowable) {
return flowable.map(chunk -> {
return new ChatMessageAccumulator(
chunk.getChoices().get(0).getDelta(),
null,
chunk.getChoices().get(0),
chunk.getUsage(),
chunk.getCreated(),
chunk.getId()
);
});
}
/**
* 测试流式响应功能
* 用于调试流式响应问题
*/
public void testStreamResponse() {
// 使用默认client进行测试
// ClientV4 chatClient = client;
try {
log.info("Zhipuai API testing stream response...");
// // 创建一个简单的测试请求
// String testMessage = "Hello, this is a test message for stream response.";
// ChatCompletionRequest chatCompletionRequest = createDynamicRequest(null, testMessage, true);
// log.info("Zhipuai API making stream test call with message: {}", testMessage);
// // 调用API
// ModelApiResponse response = chatClient.invokeModelApi(chatCompletionRequest);
// log.info("Zhipuai API stream test response success: {}", response.isSuccess());
// if (response.isSuccess()) {
// log.info("Zhipuai API stream test starting flowable processing");
// final int[] messageCount = {0};
// // 使用AtomicBoolean来标记是否是第一个消息，参考官方示例
// // java.util.concurrent.atomic.AtomicBoolean isFirst = new java.util.concurrent.atomic.AtomicBoolean(true);
// mapStreamToAccumulator(response.getFlowable())
// .doOnNext(accumulator -> {
// messageCount[0]++;
// log.info("Zhipuai API stream test message #{}: accumulator={}", messageCount[0], accumulator);
// log.info("Zhipuai API stream test message #{}: accumulator class={}", messageCount[0], accumulator.getClass().getName());
// Object delta = accumulator.getDelta();
// log.info("Zhipuai API stream test message #{}: delta={}", messageCount[0], delta);
// log.info("Zhipuai API stream test message #{}: delta class={}", messageCount[0], delta != null ? delta.getClass().getName() : "null");
// if (delta instanceof com.zhipu.oapi.service.v4.model.ChatMessage) {
// Object content = ((com.zhipu.oapi.service.v4.model.ChatMessage) delta).getContent();
// log.info("Zhipuai API stream test message #{}: content={}", messageCount[0], content);
// } else {
// log.info("Zhipuai API stream test message #{}: delta is not ChatMessage", messageCount[0]);
// }
// })
// .doOnComplete(() -> {
// log.info("Zhipuai API stream test completed, total messages: {}", messageCount[0]);
// })
// .doOnError(error -> {
// log.error("Zhipuai API stream test error: ", error);
// })
// .subscribe();
// } else {
// log.error("Zhipuai API stream test failed: {}", response.getError());
// }
} catch (Exception e) {
log.error("Zhipuai API test stream response error", e);
}
}
}

91
modules/ai/src/main/java/com/bytedesk/ai/zhipuai/ZhipuaiController.java
View File

@@ -2,7 +2,7 @@
* @Author: jackning 270580156@qq.com
* @Date: 2025-02-19 09:39:15
* @LastEditors: jackning 270580156@qq.com
* @LastEditTime: 2025-07-16 15:45:45
* @LastEditTime: 2025-08-21 12:38:11
* @Description: bytedesk.com https://github.com/Bytedesk/bytedesk
* Please be aware of the BSL license restrictions before installing Bytedesk IM –
* selling, reselling, or hosting Bytedesk IM as a service is a breach of the terms and automatically terminates your rights under the license.
@@ -49,6 +49,7 @@ public class ZhipuaiController {
private final BytedeskProperties bytedeskProperties;
private final ZhipuaiService zhipuaiService;
private final ZhipuaiChatService zhipuaiChatService;
private final ExecutorService executorService = Executors.newCachedThreadPool();
/**
@@ -140,7 +141,7 @@ public class ZhipuaiController {
}
try {
String result = zhipuaiService.rolePlayChat(message, userInfo, botInfo, botName, userName);
String result = zhipuaiChatService.rolePlayChat(message, userInfo, botInfo, botName, userName);
return ResponseEntity.ok(JsonResult.success(result));
} catch (Exception e) {
log.error("Error in role play chat", e);
@@ -191,7 +192,7 @@ public class ZhipuaiController {
functions.add(function);
}
String result = zhipuaiService.functionCallingChat(message, functions);
String result = zhipuaiChatService.functionCallingChat(message, functions);
return ResponseEntity.ok(JsonResult.success(result));
} catch (Exception e) {
log.error("Error in function calling chat", e);
@@ -224,7 +225,7 @@ public class ZhipuaiController {
functions.add(function);
}
return zhipuaiService.functionCallingChatStream(message, functions);
return zhipuaiChatService.functionCallingChatStream(message, functions);
} catch (Exception e) {
log.error("Error in function calling chat stream", e);
return Flux.just("Error: " + e.getMessage());
@@ -303,7 +304,7 @@ public class ZhipuaiController {
functions.add(weatherFunction);
String message = "请告诉我" + city + "的天气情况";
String result = zhipuaiService.functionCallingChat(message, functions);
String result = zhipuaiChatService.functionCallingChat(message, functions);
return ResponseEntity.ok(JsonResult.success(result));
} catch (Exception e) {
log.error("Error in weather function call", e);
@@ -351,7 +352,7 @@ public class ZhipuaiController {
functions.add(flightFunction);
String message = "请查询从" + from + "到" + to + "的航班价格";
String result = zhipuaiService.functionCallingChat(message, functions);
String result = zhipuaiChatService.functionCallingChat(message, functions);
return ResponseEntity.ok(JsonResult.success(result));
} catch (Exception e) {
log.error("Error in flight function call", e);
@@ -377,7 +378,7 @@ public class ZhipuaiController {
return ResponseEntity.ok(JsonResult.error("Prompt is required"));
}
String result = zhipuaiService.generateImage(prompt, requestId);
String result = zhipuaiChatService.generateImage(prompt, requestId);
return ResponseEntity.ok(JsonResult.success(result));
} catch (Exception e) {
log.error("Error in image generation", e);
@@ -402,7 +403,7 @@ public class ZhipuaiController {
return ResponseEntity.ok(JsonResult.error("Text is required"));
}
List<Double> result = zhipuaiService.getEmbedding(text);
List<Double> result = zhipuaiChatService.getEmbedding(text);
return ResponseEntity.ok(JsonResult.success(result));
} catch (Exception e) {
log.error("Error in embedding", e);
@@ -428,7 +429,7 @@ public class ZhipuaiController {
return ResponseEntity.ok(JsonResult.error("Texts are required"));
}
List<List<Double>> result = zhipuaiService.getEmbeddings(texts);
List<List<Double>> result = zhipuaiChatService.getEmbeddings(texts);
return ResponseEntity.ok(JsonResult.success(result));
} catch (Exception e) {
log.error("Error in embeddings", e);
@@ -455,7 +456,7 @@ public class ZhipuaiController {
return ResponseEntity.ok(JsonResult.error("Text is required"));
}
File result = zhipuaiService.generateSpeech(text, voice, responseFormat);
File result = zhipuaiChatService.generateSpeech(text, voice, responseFormat);
if (result != null) {
return ResponseEntity.ok(JsonResult.success("Speech generated: " + result.getAbsolutePath()));
} else {
@@ -496,7 +497,7 @@ public class ZhipuaiController {
return ResponseEntity.ok(JsonResult.error("Voice data file not found"));
}
File result = zhipuaiService.generateCustomSpeech(text, voiceText, voiceData, responseFormat);
File result = zhipuaiChatService.generateCustomSpeech(text, voiceText, voiceData, responseFormat);
if (result != null) {
return ResponseEntity.ok(JsonResult.success("Custom voice generated: " + result.getAbsolutePath()));
} else {
@@ -530,7 +531,7 @@ public class ZhipuaiController {
purpose = "fine-tune";
}
String result = zhipuaiService.uploadFile(filePath, purpose);
String result = zhipuaiChatService.uploadFile(filePath, purpose);
return ResponseEntity.ok(JsonResult.success(result));
} catch (Exception e) {
log.error("Error in file upload", e);
@@ -549,7 +550,7 @@ public class ZhipuaiController {
}
try {
List<Map<String, Object>> result = zhipuaiService.queryFiles();
List<Map<String, Object>> result = zhipuaiChatService.queryFiles();
return ResponseEntity.ok(JsonResult.success(result));
} catch (Exception e) {
log.error("Error in query files", e);
@@ -579,7 +580,7 @@ public class ZhipuaiController {
return ResponseEntity.ok(JsonResult.error("Output path is required"));
}
File result = zhipuaiService.downloadFile(fileId, outputPath);
File result = zhipuaiChatService.downloadFile(fileId, outputPath);
if (result != null) {
return ResponseEntity.ok(JsonResult.success("File downloaded: " + result.getAbsolutePath()));
} else {
@@ -613,7 +614,7 @@ public class ZhipuaiController {
return ResponseEntity.ok(JsonResult.error("Training file is required"));
}
String result = zhipuaiService.createFineTuningJob(model, trainingFile);
String result = zhipuaiChatService.createFineTuningJob(model, trainingFile);
return ResponseEntity.ok(JsonResult.success(result));
} catch (Exception e) {
log.error("Error in create fine-tuning job", e);
@@ -632,7 +633,7 @@ public class ZhipuaiController {
}
try {
Map<String, Object> result = zhipuaiService.queryFineTuningJob(jobId);
Map<String, Object> result = zhipuaiChatService.queryFineTuningJob(jobId);
return ResponseEntity.ok(JsonResult.success(result));
} catch (Exception e) {
log.error("Error in query fine-tuning job", e);
@@ -657,7 +658,7 @@ public class ZhipuaiController {
return ResponseEntity.ok(JsonResult.error("Message is required"));
}
String result = zhipuaiService.chatAsync(message);
String result = zhipuaiChatService.chatAsync(message);
return ResponseEntity.ok(JsonResult.success(result));
} catch (Exception e) {
log.error("Error in async chat", e);
@@ -687,7 +688,7 @@ public class ZhipuaiController {
searchQuery = message; // 如果没有指定搜索查询，使用消息作为搜索查询
}
String result = zhipuaiService.chatWithWebSearch(message, searchQuery);
String result = zhipuaiChatService.chatWithWebSearch(message, searchQuery);
return ResponseEntity.ok(JsonResult.success(result));
} catch (Exception e) {
log.error("Error in web search chat", e);
@@ -712,7 +713,7 @@ public class ZhipuaiController {
return ResponseEntity.ok(JsonResult.error("Message is required"));
}
String result = zhipuaiService.chatWithVoice(message);
String result = zhipuaiChatService.chatWithVoice(message);
return ResponseEntity.ok(JsonResult.success(result));
} catch (Exception e) {
log.error("Error in voice chat", e);
@@ -724,39 +725,39 @@ public class ZhipuaiController {
* 测试流式响应功能
* GET http://127.0.0.1:9003/zhipuai/test-stream
*/
@GetMapping("/test-stream")
public ResponseEntity<JsonResult<?>> testStreamResponse() {
if (!bytedeskProperties.getDebug()) {
return ResponseEntity.ok(JsonResult.error("Zhipuai service is not available"));
}
// @GetMapping("/test-stream")
// public ResponseEntity<JsonResult<?>> testStreamResponse() {
// if (!bytedeskProperties.getDebug()) {
// return ResponseEntity.ok(JsonResult.error("Zhipuai service is not available"));
// }
try {
zhipuaiService.testStreamResponse();
return ResponseEntity.ok(JsonResult.success("Stream response test completed. Check logs for details."));
} catch (Exception e) {
log.error("Error testing stream response", e);
return ResponseEntity.ok(JsonResult.error("Error testing stream response: " + e.getMessage()));
}
}
// try {
// zhipuaiService.testStreamResponse();
// return ResponseEntity.ok(JsonResult.success("Stream response test completed. Check logs for details."));
// } catch (Exception e) {
// log.error("Error testing stream response", e);
// return ResponseEntity.ok(JsonResult.error("Error testing stream response: " + e.getMessage()));
// }
// }
/**
* 简单流式测试 - 完全按照官方示例代码实现
* GET http://127.0.0.1:9003/zhipuai/test-simple-stream
*/
@GetMapping("/test-simple-stream")
public ResponseEntity<JsonResult<?>> testSimpleStream() {
if (!bytedeskProperties.getDebug()) {
return ResponseEntity.ok(JsonResult.error("Zhipuai service is not available"));
}
// @GetMapping("/test-simple-stream")
// public ResponseEntity<JsonResult<?>> testSimpleStream() {
// if (!bytedeskProperties.getDebug()) {
// return ResponseEntity.ok(JsonResult.error("Zhipuai service is not available"));
// }
try {
zhipuaiService.testSimpleStream();
return ResponseEntity.ok(JsonResult.success("Simple stream test completed. Check logs for details."));
} catch (Exception e) {
log.error("Error testing simple stream", e);
return ResponseEntity.ok(JsonResult.error("Error testing simple stream: " + e.getMessage()));
}
}
// try {
// zhipuaiChatService.testSimpleStream();
// return ResponseEntity.ok(JsonResult.success("Simple stream test completed. Check logs for details."));
// } catch (Exception e) {
// log.error("Error testing simple stream", e);
// return ResponseEntity.ok(JsonResult.error("Error testing simple stream: " + e.getMessage()));
// }
// }
/**
* 在 Bean 销毁时关闭线程池

860
modules/ai/src/main/java/com/bytedesk/ai/zhipuai/ZhipuaiService.java
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