Wrote 37 lines to /Users/mate/Codes/mate/mateclaw/mateclaw-server/src/main/java/vip/mate/agent/graph/ReActStateKeys.java 1 package vip.mate.agent.graph; 2 3 /** 4 * ReAct StateGraph 状态键常量 5 * 定义 OverAllState 中使用的所有 key 6 */ 7 public final class ReActStateKeys { 8 9 private ReActStateKeys() { 10 } 11 12 // ===== 输入 ===== 13 public static final String USER_MESSAGE = "user_message"; 14 public static final String CONVERSATION_ID = "conversation_id"; 15 public static final String SYSTEM_PROMPT = "system_prompt"; 16 17 // ===== 消息列表（APPEND 策略） ===== 18 public static final String MESSAGES = "messages"; 19 20 // ===== 迭代控制（REPLACE 策略） ===== 21 public static final String CURRENT_ITERATION = "current_iteration"; 22 public static final String MAX_ITERATIONS = "max_iterations"; 23 24 // ===== 工具调用（REPLACE 策略） ===== 25 public static final String TOOL_CALLS = "tool_calls"; 26 public static final String TOOL_RESULTS = "tool_results"; 27 28 // ===== 控制流（REPLACE 策略） ===== 29 public static final String FINAL_ANSWER = "final_answer"; 30 public static final String NEEDS_TOOL_CALL = "needs_tool_call"; 31 public static final String ERROR = "error"; 32 33 // ===== 节点名称 ===== 34 public static final String REASONING_NODE = "reasoning"; 35 public static final String ACTION_NODE = "action"; 36 public static final String OBSERVATION_NODE = "observation"; 37 } ⎿ Async hook PreToolUse completed ⎿ Async hook PreToolUse completed ⏺ Now let me check how Spring AI ChatModel, Prompt, ToolDefinition etc work to write the ReasoningNode correctly. ⏺ Bash(jar tf /Users/mate/.m2/repository/org/springframework/ai/spring-ai-core/1.1.3/spring-ai-core-1.1.3.jar | grep -E '(ChatModel|ToolDefinition|ToolCallback|ToolCallbacks|AssistantMessage|ToolResponseMessage)\.class$' | head -15) ⎿ java.nio.file.NoSuchFileException: /Users/mate/.m2/repository/org/springframework/ai/spring-ai-core/1.1.3/spring-ai-core-1.1.3.jar at java.base/sun.nio.fs.UnixException.translateToIOException(UnixException.java:92) at java.base/sun.nio.fs.UnixException.rethrowAsIOException(UnixException.java:106) at java.base/sun.nio.fs.UnixException.rethrowAsIOException(UnixException.java:111) at java.base/sun.nio.fs.UnixFileAttributeViews$Basic.readAttributes(UnixFileAttributeViews.java:55) at java.base/sun.nio.fs.UnixFileSystemProvider.readAttributes(UnixFileSystemProvider.java:171) at java.base/java.nio.file.Files.readAttributes(Files.java:1854) at java.base/java.util.zip.ZipFile$Source.get(ZipFile.java:1445) at java.base/java.util.zip.ZipFile$CleanableResource.(ZipFile.java:724) at java.base/java.util.zip.ZipFile.(ZipFile.java:251) at java.base/java.util.zip.ZipFile.(ZipFile.java:180) at java.base/java.util.zip.ZipFile.(ZipFile.java:151) at jdk.jartool/sun.tools.jar.Main.list(Main.java:1522) at jdk.jartool/sun.tools.jar.Main.run(Main.java:368) at jdk.jartool/sun.tools.jar.Main.main(Main.java:1700) ⎿ Async hook PreToolUse completed ⏺ Bas(find /Users/mate/.m2/repository/org/springframework/ai -name "spring-ai-model-1.1.3.jar" -o -name "spring-ai-client-1.1.3.jar" 2>/dev/null | head -5) ⎿ /Users/mate/.m2/repository/org/springframework/ai/spring-ai-model/1.1.3/spring-ai-model-1.1.3.jar ⎿ Async hook PreToolUse completed ⏺ Bash(jar tf /Users/mate/.m2/repository/org/springframework/ai/spring-ai-model/1.1.3/spring-ai-model-1.1.3.jar | grep -E '(ChatModel|ToolDefinition|ToolCallback|ToolCallbacks|AssistantMessage|ToolResponseMessage|ChatResponse|Prompt)\.class$' | head -20) ⎿ org/springframework/ai/support/ToolCallbacks.class org/springframework/ai/chat/messages/AssistantMessage.class org/springframework/ai/chat/messages/ToolResponseMessage.class org/springframework/ai/chat/prompt/Prompt.class org/springframework/ai/chat/model/ChatModel.class org/springframework/ai/chat/model/StreamingChatModel.class org/springframework/ai/chat/model/ChatResponse.class org/springframework/ai/tool/definition/ToolDefinition.class org/springframework/ai/tool/definition/DefaultToolDefinition.class org/springframework/ai/tool/augment/AugmentedToolCallback.class org/springframework/ai/tool/method/MethodToolCallback.class org/springframework/ai/tool/function/FunctionToolCallback.class org/springframework/ai/tool/ToolCallback.class org/springframework/ai/audio/transcription/AudioTranscriptionPrompt.class org/springframework/ai/audio/tts/TextToSpeechPrompt.class org/springframework/ai/image/ImagePrompt.class org/springframework/ai/moderation/ModerationPrompt.class ⎿ Async hook PreToolUse completed ⏺ Let me check key APIs: ⏺ Bash(jar tf /Users/mate/.m2/repository/org/springframework/ai/spring-ai-model/1.1.3/spring-ai-model-1.1.3.jar | grep 'ToolResponseMessage' | head -5) ⎿ org/springframework/ai/chat/messages/ToolResponseMessage$Builder.class org/springframework/ai/chat/messages/ToolResponseMessage$ToolResponse.class org/springframework/ai/chat/messages/ToolResponseMessage.class ⎿ Async hook PreToolUse completed ⏺ Let me check how AssistantMessage.getToolCalls() and ToolCallback work: ⏺ Bash(jar xf /Users/mate/.m2/repository/org/springframework/ai/spring-ai-model/1.1.3/spring-ai-model-1.1.3.jar org/springframework/ai/chat/messages/AssistantMessage.class -d /tmp/sai && javap -p /tmp/sai/org/springframework/ai/chat/messages/AssistantMessage.class 2>/dev/null | grep -E 'getToolCalls|toolCalls|class Assist' | head -10) ⎿ (No output) ⎿ Async hook PreToolUse completed ⏺ Bash(javap -public /tmp/sai/org/springframework/ai/chat/messages/AssistantMessage.class 2>/dev/null | head -30) ⎿ (No output) ⎿ Async hook PreToolUse completed ⏺ Bash(cd /tmp && jar xf /Users/mate/.m2/repository/org/springframework/ai/spring-ai-model/1.1.3/spring-ai-model-1.1.3.jar org/springframework/ai/chat/messages/AssistantMessage.class && javap org/springframework/ai/chat/messages/AssistantMessage.class 2>/dev/null | grep -i 'tool\|class\|public' | head -20) ⎿ public class org.springframework.ai.chat.messages.AssistantMessage extends org.springframework.ai.chat.messages.AbstractMessage implements org.springframework.ai.content.MediaContent { public org.springframework.ai.chat.messages.AssistantMessage(java.lang.String); protected org.springframework.ai.chat.messages.AssistantMessage(java.lang.String, java.util.Map, java.util.List, java.util.List); public java.util.List getToolCalls(); public boolean hasToolCalls(); public java.util.List getMedia(); public boolean equals(java.lang.Object); public int hashCode(); public java.lang.String toString(); public static org.springframework.ai.chat.messages.AssistantMessage$Builder builder(); ⎿ Shell cwd was reset to /Users/mate/Codes/mate/mateclaw ⎿ Async hook PreToolUse completed ⏺ Bash(cd /tmp && jar xf /Users/mate/.m2/repository/org/springframework/ai/spring-ai-model/1.1.3/spring-ai-model-1.1.3.jar org/springframework/ai/chat/messages/AssistantMessage\$ToolCall.class && javap 'org/springframework/ai/chat/messages/AssistantMessage$ToolCall.class' 2>/dev/null | head -20) ⎿ Compiled from "AssistantMessage.java" public final class org.springframework.ai.chat.messages.AssistantMessage$ToolCall extends java.lang.Record { public org.springframework.ai.chat.messages.AssistantMessage$ToolCall(java.lang.String, java.lang.String, java.lang.String, java.lang.String); public final java.lang.String toString(); public final int hashCode(); public final boolean equals(java.lang.Object); public java.lang.String id(); public java.lang.String type(); public java.lang.String name(); public java.lang.String arguments(); } ⎿ Shell cwd was reset to /Users/mate/Codes/mate/mateclaw ⎿ Async hook PreToolUse completed ⏺ Now let me check ToolCallback and ToolCallbacks.from(): ⏺ Bash(cd /tmp && jar xf /Users/mate/.m2/repository/org/springframework/ai/spring-ai-model/1.1.3/spring-ai-model-1.1.3.jar org/springframework/ai/tool/ToolCallback.class && javap 'org/springframework/ai/tool/ToolCallback.class' 2>/dev/null | head -15) ⎿ Compiled from "ToolCallback.java" public interface org.springframework.ai.tool.ToolCallback { public static final org.slf4j.Logger logger; public abstract org.springframework.ai.tool.definition.ToolDefinition getToolDefinition(); public default org.springframework.ai.tool.metadata.ToolMetadata getToolMetadata(); public abstract java.lang.String call(java.lang.String); public default java.lang.String call(java.lang.String, org.springframework.ai.chat.model.ToolContext); static {}; } ⎿ Shell cwd was reset to /Users/mate/Codes/mate/mateclaw ⎿ Async hook PreToolUse completed ⏺ Bash(cd /tmp && jar xf /Users/mate/.m2/repository/org/springframework/ai/spring-ai-model/1.1.3/spring-ai-model-1.1.3.jar org/springframework/ai/support/ToolCallbacks.class && javap 'org/springframework/ai/support/ToolCallbacks.class' 2>/dev/null | head -15) ⎿ Compiled from "ToolCallbacks.java" public final class org.springframework.ai.support.ToolCallbacks { public static org.springframework.ai.tool.ToolCallback[] from(java.lang.Object...); } ⎿ Shell cwd was reset to /Users/mate/Codes/mate/mateclaw ⎿ Async hook PreToolUse completed ⏺ Now let me check ChatModel and ToolCallingChatOptions: ⏺ Bash(cd /tmp && jar xf /Users/mate/.m2/repository/org/springframework/ai/spring-ai-model/1.1.3/spring-ai-model-1.1.3.jar org/springframework/ai/chat/model/ChatModel.class && javap 'org/springframework/ai/chat/model/ChatModel.class' 2>/dev/null | head -15) ⎿ Compiled from "ChatModel.java" public interface org.springframework.ai.chat.model.ChatModel extends org.springframework.ai.model.Model, org.springframework.ai.chat.model.StreamingChatModel { public default java.lang.String call(java.lang.String); public default java.lang.String call(org.springframework.ai.chat.messages.Message...); public abstract org.springframework.ai.chat.model.ChatResponse call(org.springframework.ai.chat.prompt.Prompt); public default org.springframework.ai.chat.prompt.ChatOptions getDefaultOptions(); public default reactor.core.publisher.Flux stream(org.springframework.ai.chat.prompt.Prompt); public default org.springframework.ai.model.ModelResponse call(org.springframework.ai.model.ModelRequest); public default reactor.core.publisher.Flux stream(org.springframework.ai.model.ModelRequest); } ⎿ Shell cwd was reset to /Users/mate/Codes/mate/mateclaw ⎿ Async hook PreToolUse completed ⏺ Now let me check how to set internalToolExecutionEnabled for DashScope. Let me check Prompt and how to pass options: ⏺ Bash(cd /tmp && jar xf /Users/mate/.m2/repository/org/springframework/ai/spring-ai-model/1.1.3/spring-ai-model-1.1.3.jar org/springframework/ai/chat/prompt/Prompt.class && javap 'org/springframework/ai/chat/prompt/Prompt.class' 2>/dev/null | grep -E 'public|Prompt\(' | head -20) ⎿ public class org.springframework.ai.chat.prompt.Prompt implements org.springframework.ai.model.ModelRequest> { public org.springframework.ai.chat.prompt.Prompt(java.lang.String); public org.springframework.ai.chat.prompt.Prompt(org.springframework.ai.chat.messages.Message); public org.springframework.ai.chat.prompt.Prompt(java.util.List); public org.springframework.ai.chat.prompt.Prompt(org.springframework.ai.chat.messages.Message...); public org.springframework.ai.chat.prompt.Prompt(java.lang.String, org.springframework.ai.chat.prompt.ChatOptions); public org.springframework.ai.chat.prompt.Prompt(org.springframework.ai.chat.messages.Message, org.springframework.ai.chat.prompt.ChatOptions); public org.springframework.ai.chat.prompt.Prompt(java.util.List, org.springframework.ai.chat.prompt.ChatOptions); public java.lang.String getContents(); public org.springframework.ai.chat.prompt.ChatOptions getOptions(); public java.util.List getInstructions(); public org.springframework.ai.chat.messages.SystemMessage getSystemMessage(); public org.springframework.ai.chat.messages.UserMessage getUserMessage(); public org.springframework.ai.chat.messages.Message getLastUserOrToolResponseMessage(); public java.util.List getSystemMessages(); public java.util.List getUserMessages(); public java.lang.String toString(); public boolean equals(java.lang.Object); public int hashCode(); public org.springframework.ai.chat.prompt.Prompt copy(); ⎿ Shell cwd was reset to /Users/mate/Codes/mate/mateclaw ⎿ Async hook PreToolUse completed ⏺ Let me check DashScopeChatOptions for internalToolExecutionEnabled: ⏺ Bas(find /Users/mate/.m2/repository/com/alibaba/cloud/ai/spring-ai-alibaba-starter-dashscope/1.1.2.2 -name "*.jar" ! -name "*sources*" ! -name "*javadoc*" | head -1) ⎿ /Users/mate/.m2/repository/com/alibaba/cloud/ai/spring-ai-alibaba-starter-dashscope/1.1.2.2/spring-ai-alibaba-starter-dashscope-1.1.2. 2.jar ⎿ Async hook PreToolUse completed ⏺ Bash(cd /tmp && jar xf /Users/mate/.m2/repository/com/alibaba/cloud/ai/spring-ai-alibaba-starter-dashscope/1.1.2.2/spring-ai-alibaba-star ter-dashscope-1.1.2.2.jar com/alibaba/cloud/ai/dashscope/chat/DashScopeChatOptions.class && javap 'com/alibaba/cloud/ai/dashscope/chat/DashScopeChatOptions.class' 2>/dev/null | grep -iE 'tool|internal' | head -10) ⎿ Shell cwd was reset to /Users/mate/Codes/mate/mateclaw ⎿ Async hook PreToolUse completed ⏺ Bash(cd /tmp && javap com/alibaba/cloud/ai/dashscope/chat/DashScopeChatOptions.class 2>/dev/null | grep -iE 'tool|internal|setTool|getTool|toolNames|toolCallbacks' | head -15) ⎿ Shell cwd was reset to /Users/mate/Codes/mate/mateclaw ⎿ Async hook PreToolUse completed ⏺ Bash(cd /tmp && javap -p com/alibaba/cloud/ai/dashscope/chat/DashScopeChatOptions.class 2>/dev/null | grep -i 'tool' | head -15) ⎿ Shell cwd was reset to /Users/mate/Codes/mate/mateclaw ⎿ Async hook PreToolUse completed ⏺ Bash(cd /tmp && ls com/alibaba/cloud/ai/dashscope/chat/DashScopeChatOptions.class 2>/dev/null) ⎿ Error: Exit code 1 ⎿ Async hook PreToolUse completed ⏺ Bash(cd /tmp && jar xf /Users/mate/.m2/repository/com/alibaba/cloud/ai/spring-ai-alibaba-starter-dashscope/1.1.2.2/spring-ai-alibaba-star ter-dashscope-1.1.2.2.jar && find . -name "DashScopeChatOptions.class" | head -3) ⎿ Shell cwd was reset to /Users/mate/Codes/mate/mateclaw ⎿ Async hook PreToolUse completed ⏺ Bas(find /Users/mate/.m2/repository/com/alibaba/cloud/ai -name "*.jar" -path "*dashscope*" ! -name "*sources*" ! -name "*javadoc*" 2>/dev/null | head -5) ⎿ /Users/mate/.m2/repository/com/alibaba/cloud/ai/spring-ai-alibaba-starter-dashscope/1.0.0.3/spring-ai-alibaba-starter-dashscope-1.0.0. 3.jar /Users/mate/.m2/repository/com/alibaba/cloud/ai/spring-ai-alibaba-starter-dashscope/1.1.2.0/spring-ai-alibaba-starter-dashscope-1.1.2. 0.jar /Users/mate/.m2/repository/com/alibaba/cloud/ai/spring-ai-alibaba-starter-dashscope/1.0.0.2/spring-ai-alibaba-starter-dashscope-1.0.0. 2.jar /Users/mate/.m2/repository/com/alibaba/cloud/ai/spring-ai-alibaba-starter-dashscope/1.1.2.2/spring-ai-alibaba-starter-dashscope-1.1.2. 2.jar /Users/mate/.m2/repository/com/alibaba/cloud/ai/spring-ai-alibaba-dashscope/1.1.2.0/spring-ai-alibaba-dashscope-1.1.2.0.jar ⎿ Async hook PreToolUse completed ⏺ Bash(jar tf /Users/mate/.m2/repository/com/alibaba/cloud/ai/spring-ai-alibaba-starter-dashscope/1.1.2.2/spring-ai-alibaba-starter-dashsco pe-1.1.2.2.jar | grep DashScopeChatOptions | head -5) ⎿ (No output) ⎿ Async hook PreToolUse completed ⏺ Bas(find /Users/mate/.m2/repository/com/alibaba/cloud/ai -name "spring-ai-alibaba-dashscope-*.jar" ! -name "*sources*" ! -name "*javadoc*" | grep '1.1.2' | head -3) ⎿ /Users/mate/.m2/repository/com/alibaba/cloud/ai/spring-ai-alibaba-dashscope/1.1.2.0/spring-ai-alibaba-dashscope-1.1.2.0.jar /Users/mate/.m2/repository/com/alibaba/cloud/ai/spring-ai-alibaba-dashscope/1.1.2.2/spring-ai-alibaba-dashscope-1.1.2.2.jar ⎿ Async hook PreToolUse completed ⏺ Bash(jar tf /Users/mate/.m2/repository/com/alibaba/cloud/ai/spring-ai-alibaba-dashscope/1.1.2.2/spring-ai-alibaba-dashscope-1.1.2.2.jar | grep DashScopeChatOptions | head -5) ⎿ com/alibaba/cloud/ai/dashscope/chat/DashScopeChatOptions.class com/alibaba/cloud/ai/dashscope/chat/DashScopeChatOptions$DashScopeChatOptionsBuilder.class ⎿ Async hook PreToolUse completed ⏺ Bash(mkdir -p /tmp/dashscope-extract && cd /tmp/dashscope-extract && jar xf /Users/mate/.m2/repository/com/alibaba/cloud/ai/spring-ai-alibaba-dashscope/1.1.2.2/spring-ai-alibaba-dashscope-1.1.2.2.jar com/alibaba/cloud/ai/dashscope/chat/DashScopeChatOptions.class && javap -p com/alibaba/cloud/ai/dashscope/chat/DashScopeChatOptions.class 2>/dev/null | grep -iE 'tool|internal|ToolNames|ToolCallbacks' | head -15) ⎿ public class com.alibaba.cloud.ai.dashscope.chat.DashScopeChatOptions implements org.springframework.ai.model.tool.ToolCallingChatOptions { private java.util.List tools; private java.lang.Boolean parallelToolCalls; private java.lang.Object toolChoice; private java.util.List toolCallbacks; private java.util.Set toolNames; private java.lang.Boolean internalToolExecutionEnabled; private java.util.Map toolContext; public java.lang.Boolean getParallelToolCalls(); public void setParallelToolCalls(java.lang.Boolean); public java.util.List getTools(); public void setTools(java.util.List); public java.lang.Object getToolChoice(); public void setToolChoice(java.lang.Object); public java.util.List getToolCallbacks(); ⎿ Shell cwd was reset to /Users/mate/Codes/mate/mateclaw ⎿ Async hook PreToolUse completed ⏺ DashScopeChatOptions implements ToolCallingChatOptions and has internalToolExecutionEnabled, toolCallbacks, and toolNames fields. This means I can pass tool definitions and disable internal tool execution directly through the options. Now I have everything. Let me create all the graph nodes, edges, and agent in parallel. ⏺ Write(/Users/mate/Codes/mate/mateclaw/mateclaw-server/src/main/java/vip/mate/agent/graph/node/ReasoningNode.java) ⎿ Wrote 89 lines to /Users/mate/Codes/mate/mateclaw/mateclaw-server/src/main/java/vip/mate/agent/graph/node/ReasoningNode.java 1 package vip.mate.agent.graph.node; 2 3 import com.alibaba.cloud.ai.graph.OverAllState; 4 import com.alibaba.cloud.ai.graph.action.NodeAction; 5 import lombok.extern.slf4j.Slf4j; 6 import org.springframework.ai.chat.messages.AssistantMessage; 7 import org.springframework.ai.chat.messages.Message; 8 import org.springframework.ai.chat.messages.SystemMessage; 9 import org.springframework.ai.chat.model.ChatModel; 10 import org.springframework.ai.chat.model.ChatResponse; 11 import org.springframework.ai.chat.prompt.ChatOptions; 12 import org.springframework.ai.chat.prompt.Prompt; 13 import org.springframework.ai.model.tool.ToolCallingChatOptions; 14 import org.springframework.ai.tool.ToolCallback; 15 16 import java.util.*; 17 18 import static vip.mate.agent.graph.ReActStateKeys.*; 19 20 /** 21 * 推理节点（ReAct Thought 阶段） 22 *

23 * 调用 LLM 进行单次推理，判断是否需要工具调用。 24 * 关键：通过 internalToolExecutionEnabled=false 禁用 ChatModel 内部工具循环， 25 * 使 StateGraph 完全控制 ReAct 循环。 26 * 27 * @author MateClaw Team 28 */ 29 @Slf4j 30 public class ReasoningNode implements NodeAction { 31 32 private final ChatModel chatModel; 33 private final List toolCallbacks; 34 35 public ReasoningNode(ChatModel chatModel, List toolCallbacks) { 36 this.chatModel = chatModel; 37 this.toolCallbacks = toolCallbacks; 38 } 39 40 @Override 41 @SuppressWarnings("unchecked") 42 public Map apply(OverAllState state) throws Exception { 43 String systemPrompt = state.value(SYSTEM_PROMPT, "你是一个有帮助的AI助手。"); 44 List messages = state.>value(MESSAGES).orElse(List.of()); 45 46 // 构建 Prompt，附带工具定义但禁用内部工具执行 47 List promptMessages = new ArrayList<>(); 48 promptMessages.add(new SystemMessage(systemPrompt)); 49 promptMessages.addAll(messages); 50 51 ChatOptions options = ToolCallingChatOptions.builder() 52 .toolCallbacks(toolCallbacks) 53 .internalToolExecutionEnabled(false) 54 .build(); 55 56 Prompt prompt = new Prompt(promptMessages, options); 57 58 log.debug("[ReasoningNode] Calling LLM with {} messages, {} tool definitions", 59 promptMessages.size(), toolCallbacks.size()); 60 61 // 单次 LLM 调用 62 ChatResponse response = chatModel.call(prompt); 63 AssistantMessage assistantMessage = response.getResult().getOutput(); 64 65 Map result = new HashMap<>(); 66 67 if (assistantMessage.hasToolCalls()) { 68 // LLM 请求工具调用 69 List toolCalls = assistantMessage.getToolCalls(); 70 log.info("[ReasoningNode] LLM requested {} tool call(s): {}", 71 toolCalls.size(), 72 toolCalls.stream().map(AssistantMessage.ToolCall::name).toList()); 73 74 result.put(NEEDS_TOOL_CALL, true); 75 result.put(TOOL_CALLS, toolCalls); 76 result.put(MESSAGES, List.of((Message) assistantMessage)); 77 } else { 78 // LLM 给出最终回答 79 String content = assistantMessage.getText(); 80 log.info("[ReasoningNode] LLM produced final answer ({} chars)", content != null ? content.length() : 0); 81 82 result.put(NEEDS_TOOL_CALL, false); 83 result.put(FINAL_ANSWER, content != null ? content : ""); 84 result.put(MESSAGES, List.of((Message) assistantMessage)); 85 } 86 87 return result; 88 } 89 } ⏺ Write(/Users/mate/Codes/mate/mateclaw/mateclaw-server/src/main/java/vip/mate/agent/graph/node/ActionNode.java) ⎿ Wrote 102 lines to /Users/mate/Codes/mate/mateclaw/mateclaw-server/src/main/java/vip/mate/agent/graph/node/ActionNode.java 1 package vip.mate.agent.graph.node; 2 3 import com.alibaba.cloud.ai.graph.OverAllState; 4 import com.alibaba.cloud.ai.graph.action.NodeAction; 5 import lombok.extern.slf4j.Slf4j; 6 import org.springframework.ai.chat.messages.AssistantMessage; 7 import org.springframework.ai.chat.messages.Message; 8 import org.springframework.ai.chat.messages.ToolResponseMessage; 9 import org.springframework.ai.tool.ToolCallback; 10 import vip.mate.tool.guard.ToolGuard; 11 import vip.mate.tool.guard.ToolGuardResult; 12 13 import java.util.*; 14 import java.util.stream.Collectors; 15 16 import static vip.mate.agent.graph.ReActStateKeys.*; 17 18 /** 19 * 工具执行节点（ReAct Action 阶段） 20 *

21 * 执行 LLM 请求的工具调用，并在执行前通过 ToolGuard 进行安全检查。 22 * 如果工具被拦截，返回拦截信息作为工具结果，让 LLM 自行调整策略。 23 * 24 * @author MateClaw Team 25 */ 26 @Slf4j 27 public class ActionNode implements NodeAction { 28 29 private final Map toolCallbackMap; 30 private final ToolGuard toolGuard; 31 32 public ActionNode(List toolCallbacks, ToolGuard toolGuard) { 33 this.toolCallbackMap = toolCallbacks.stream() 34 .collect(Collectors.toMap( 35 cb -> cb.getToolDefinition().name(), 36 cb -> cb, 37 (a, b) -> a)); 38 this.toolGuard = toolGuard; 39 } 40 41 @Override 42 @SuppressWarnings("unchecked") 43 public Map apply(OverAllState state) throws Exception { 44 List toolCalls = state.>value(TOOL_CALLS) 45 .orElse(List.of()); 46 47 List toolResponses = new ArrayList<>(); 48 49 for (AssistantMessage.ToolCall toolCall : toolCalls) { 50 String toolName = toolCall.name(); 51 String arguments = toolCall.arguments(); 52 53 // ToolGuard 安全检查 54 ToolGuardResult guardResult = toolGuard.check(toolName, arguments); 55 if (guardResult.isBlocked()) { 56 log.warn("[ActionNode] Tool call BLOCKED by ToolGuard: tool={}, reason={}", 57 toolName, guardResult.reason()); 58 toolResponses.add(new ToolResponseMessage.ToolResponse( 59 toolCall.id(), 60 toolName, 61 "[安全拦截] " + guardResult.reason() + "。请使用更安全的替代方案。")); 62 continue; 63 } 64 65 // 查找并执行工具 66 ToolCallback callback = toolCallbackMap.get(toolName); 67 if (callback == null) { 68 log.warn("[ActionNode] Tool not found: {}", toolName); 69 toolResponses.add(new ToolResponseMessage.ToolResponse( 70 toolCall.id(), 71 toolName, 72 "工具不存在: " + toolName)); 73 continue; 74 } 75 76 try { 77 log.info("[ActionNode] Executing tool: {} with args: {}", 78 toolName, arguments != null && arguments.length() > 200 79 ? arguments.substring(0, 200) + "..." : arguments); 80 String result = callback.call(arguments); 81 log.info("[ActionNode] Tool {} returned {} chars", toolName, result != null ? result.length() : 0); 82 toolResponses.add(new ToolResponseMessage.ToolResponse( 83 toolCall.id(), 84 toolName, 85 result != null ? result : "")); 86 } catch (Exception e) { 87 log.error("[ActionNode] Tool {} execution failed: {}", toolName, e.getMessage(), e); 88 toolResponses.add(new ToolResponseMessage.ToolResponse( 89 toolCall.id(), 90 toolName, 91 "工具执行失败: " + e.getMessage())); 92 } 93 } 94 95 ToolResponseMessage toolResponseMessage = new ToolResponseMessage(toolResponses, Map.of()); 96 97 Map result = new HashMap<>(); 98 result.put(TOOL_RESULTS, toolResponses); 99 result.put(MESSAGES, List.of((Message) toolResponseMessage)); 100 return result; 101 } 102 } ⏺ Write(/Users/mate/Codes/mate/mateclaw/mateclaw-server/src/main/java/vip/mate/agent/graph/node/ObservationNode.java) ⎿ Wrote 35 lines to /Users/mate/Codes/mate/mateclaw/mateclaw-server/src/main/java/vip/mate/agent/graph/node/ObservationNode.java 1 package vip.mate.agent.graph.node; 2 3 import com.alibaba.cloud.ai.graph.OverAllState; 4 import com.alibaba.cloud.ai.graph.action.NodeAction; 5 import lombok.extern.slf4j.Slf4j; 6 7 import java.util.HashMap; 8 import java.util.Map; 9 10 import static vip.mate.agent.graph.ReActStateKeys.*; 11 12 /** 13 * 观察节点（ReAct Observation 阶段） 14 *

15 * 处理工具执行结果，递增迭代计数器。 16 * 迭代控制的核心：配合 ObservationDispatcher 实现 maxIterations 强制执行。 17 * 18 * @author MateClaw Team 19 */ 20 @Slf4j 21 public class ObservationNode implements NodeAction { 22 23 @Override 24 public Map apply(OverAllState state) throws Exception { 25 int currentIteration = state.value(CURRENT_ITERATION, 0); 26 int maxIterations = state.value(MAX_ITERATIONS, 10); 27 28 int nextIteration = currentIteration + 1; 29 log.info("[ObservationNode] Iteration {}/{}", nextIteration, maxIterations); 30 31 Map result = new HashMap<>(); 32 result.put(CURRENT_ITERATION, nextIteration); 33 return result; 34 } 35 } ⎿ Async hook PreToolUse completed ⎿ Async hook PreToolUse completed ⎿ Async hook PreToolUse completed ⏺ Now create the edge dispatchers: ⏺ Write(/Users/mate/Codes/mate/mateclaw/mateclaw-server/src/main/java/vip/mate/agent/graph/edge/ReasoningDispatcher.java) ⎿ Wrote 34 lines to /Users/mate/Codes/mate/mateclaw/mateclaw-server/src/main/java/vip/mate/agent/graph/edge/ReasoningDispatcher.java 1 package vip.mate.agent.graph.edge; 2 3 import com.alibaba.cloud.ai.graph.OverAllState; 4 import com.alibaba.cloud.ai.graph.StateGraph; 5 import com.alibaba.cloud.ai.graph.action.EdgeAction; 6 import lombok.extern.slf4j.Slf4j; 7 8 import static vip.mate.agent.graph.ReActStateKeys.*; 9 10 /** 11 * 推理路由 12 *

13 * 根据 LLM 推理结果决定下一步： 14 * - 有工具调用需求 → 路由到 ActionNode 15 * - 无工具调用（最终回答） → 路由到 END 16 * 17 * @author MateClaw Team 18 */ 19 @Slf4j 20 public class ReasoningDispatcher implements EdgeAction { 21 22 @Override 23 public String apply(OverAllState state) throws Exception { 24 Boolean needsToolCall = state.value(NEEDS_TOOL_CALL, false); 25 26 if (Boolean.TRUE.equals(needsToolCall)) { 27 log.debug("[ReasoningDispatcher] Routing to action node"); 28 return ACTION_NODE; 29 } 30 31 log.debug("[ReasoningDispatcher] Final answer produced, routing to END"); 32 return StateGraph.END; 33 } 34 } ⏺ Write(/Users/mate/Codes/mate/mateclaw/mateclaw-server/src/main/java/vip/mate/agent/graph/edge/ObservationDispatcher.java) ⎿ Wrote 46 lines to /Users/mate/Codes/mate/mateclaw/mateclaw-server/src/main/java/vip/mate/agent/graph/edge/ObservationDispatcher.java 1 package vip.mate.agent.graph.edge; 2 3 import com.alibaba.cloud.ai.graph.OverAllState; 4 import com.alibaba.cloud.ai.graph.StateGraph; 5 import com.alibaba.cloud.ai.graph.action.EdgeAction; 6 import lombok.extern.slf4j.Slf4j; 7 8 import static vip.mate.agent.graph.ReActStateKeys.*; 9 10 /** 11 * 观察路由（迭代控制核心） 12 *

13 * 决定 ReAct 循环是否继续： 14 * - 迭代次数达到上限 → 强制终止（END） 15 * - 存在错误 → 终止（END） 16 * - 否则 → 继续推理（回到 ReasoningNode） 17 *

18 * 这是 maxIterations 字段的核心执行点。 19 * 20 * @author MateClaw Team 21 */ 22 @Slf4j 23 public class ObservationDispatcher implements EdgeAction { 24 25 @Override 26 public String apply(OverAllState state) throws Exception { 27 int currentIteration = state.value(CURRENT_ITERATION, 0); 28 int maxIterations = state.value(MAX_ITERATIONS, 10); 29 30 // 迭代次数检查 31 if (currentIteration >= maxIterations) { 32 log.warn("[ObservationDispatcher] Max iterations ({}) reached, forcing END", maxIterations); 33 return StateGraph.END; 34 } 35 36 // 错误检查 37 String error = state.value(ERROR, (String) null); 38 if (error != null && !error.isEmpty()) { 39 log.warn("[ObservationDispatcher] Error detected, routing to END: {}", error); 40 return StateGraph.END; 41 } 42 43 log.debug("[ObservationDispatcher] Continuing loop, iteration {}/{}", currentIteration, maxIterations); 44 return REASONING_NODE; 45 } 46 } ⎿ Async hook PreToolUse completed ⎿ Async hook PreToolUse completed ⏺ Now create the StateGraphReActAgent: ⏺ Write(/Users/mate/Codes/mate/mateclaw/mateclaw-server/src/main/java/vip/mate/agent/graph/StateGraphReActAgent.java) ⎿ Wrote 126 lines to /Users/mate/Codes/mate/mateclaw/mateclaw-server/src/main/java/vip/mate/agent/graph/StateGraphReActAgent.java 1 package vip.mate.agent.graph; 2 3 import com.alibaba.cloud.ai.graph.CompiledGraph; 4 import com.alibaba.cloud.ai.graph.NodeOutput; 5 import com.alibaba.cloud.ai.graph.OverAllState; 6 import com.alibaba.cloud.ai.graph.RunnableConfig; 7 import lombok.extern.slf4j.Slf4j; 8 import org.springframework.ai.chat.client.ChatClient; 9 import org.springframework.ai.chat.messages.Message; 10 import org.springframework.ai.chat.messages.UserMessage; 11 import reactor.core.publisher.Flux; 12 import vip.mate.agent.AgentState; 13 import vip.mate.agent.BaseAgent; 14 import vip.mate.workspace.conversation.ConversationService; 15 16 import java.util.*; 17 18 import static vip.mate.agent.graph.ReActStateKeys.*; 19 20 /** 21 * 基于 StateGraph 的 ReAct Agent 22 *

23 * 使用 spring-ai-alibaba-graph-core 的 StateGraph 引擎替代 Spring AI ChatClient 黑盒工具调用， 24 * 实现显式可控的 Thought → Action → Observation 循环。 25 *

26 * 关键特性： 27 * - 迭代次数强制控制（maxIterations 真正生效） 28 * - ToolGuard 安全拦截（在 ActionNode 中执行） 29 * - 工具调用过程可观测 30 * 31 * @author MateClaw Team 32 */ 33 @Slf4j 34 public class StateGraphReActAgent extends BaseAgent { 35 36 private final CompiledGraph compiledGraph; 37 38 public StateGraphReActAgent(ChatClient chatClient, ConversationService conversationService, 39 CompiledGraph compiledGraph) { 40 super(chatClient, conversationService); 41 this.compiledGraph = compiledGraph; 42 } 43 44 @Override 45 public String chat(String userMessage, String conversationId) { 46 setState(AgentState.RUNNING); 47 try { 48 log.info("[{}] StateGraph chat: conversationId={}", agentName, conversationId); 49 50 Map inputs = buildInitialState(userMessage, conversationId); 51 Optional result = compiledGraph.invoke(inputs); 52 53 return result 54 .flatMap(s -> s.value(FINAL_ANSWER)) 55 .orElse("未能生成回答。"); 56 } catch (Exception e) { 57 log.error("[{}] StateGraph chat failed: {}", agentName, e.getMessage(), e); 58 setState(AgentState.ERROR); 59 throw new RuntimeException("对话失败：" + e.getMessage(), e); 60 } finally { 61 if (getState() != AgentState.ERROR) { 62 setState(AgentState.IDLE); 63 } 64 } 65 } 66 67 @Override 68 public Flux chatStream(String userMessage, String conversationId) { 69 setState(AgentState.RUNNING); 70 try { 71 log.info("[{}] StateGraph stream: conversationId={}", agentName, conversationId); 72 73 Map inputs = buildInitialState(userMessage, conversationId); 74 String threadId = UUID.randomUUID().toString(); 75 RunnableConfig config = RunnableConfig.builder().threadId(threadId).build(); 76 77 return compiledGraph.stream(inputs, config) 78 .filter(this::hasFinalAnswer) 79 .map(this::extractFinalAnswer) 80 .filter(content -> content != null && !content.isEmpty()) 81 .doOnComplete(() -> setState(AgentState.IDLE)) 82 .doOnError(e -> { 83 log.error("[{}] StateGraph stream error: {}", agentName, e.getMessage()); 84 setState(AgentState.ERROR); 85 }); 86 } catch (Exception e) { 87 log.error("[{}] StateGraph stream setup failed: {}", agentName, e.getMessage(), e); 88 setState(AgentState.ERROR); 89 return Flux.error(e); 90 } 91 } 92 93 @Override 94 public String execute(String goal, String conversationId) { 95 return chat(goal, conversationId); 96 } 97 98 private Map buildInitialState(String userMessage, String conversationId) { 99 // 加载会话历史 100 List historyMessages = buildConversationHistory(conversationId, userMessage); 101 List messages = new ArrayList<>(historyMessages); 102 messages.add(new UserMessage(userMessage)); 103 104 Map inputs = new HashMap<>(); 105 inputs.put(USER_MESSAGE, userMessage); 106 inputs.put(CONVERSATION_ID, conversationId); 107 inputs.put(SYSTEM_PROMPT, systemPrompt != null ? systemPrompt : "你是一个有帮助的AI助手。"); 108 inputs.put(MESSAGES, messages); 109 inputs.put(MAX_ITERATIONS, maxIterations); 110 inputs.put(CURRENT_ITERATION, 0); 111 return inputs; 112 } 113 114 private boolean hasFinalAnswer(NodeOutput output) { 115 if (output == null || output.state() == null) { 116 return false; 117 } 118 return output.state().value(FINAL_ANSWER) 119 .filter(s -> !s.isEmpty()) 120 .isPresent(); 121 } 122 123 private String extractFinalAnswer(NodeOutput output) { 124 return output.state().value(FINAL_ANSWER).orElse(""); 125 } 126 } ⎿ Async hook PreToolUse completed ⎿ Async hook PreToolUse completed ⏺ Step 4: AgentService integration. This is the most critical part. ⏺ Read(/Users/mate/Codes/mate/mateclaw/mateclaw-server/src/main/java/vip/mate/agent/AgentService.java · lines 1-80) ⎿ Read 80 lines ⏺ Read(/Users/mate/Codes/mate/mateclaw/mateclaw-server/src/main/java/vip/mate/agent/AgentService.java · lines 80-139) ⎿ Read 60 lines ⎿ Async hook PreToolUse completed ⎿ Async hook PreToolUse completed ⎿ Async hook PreToolUse completed ⏺ Now let me apply the modifications to AgentService. First, add the new imports and dependencies: ⏺ Update(/Users/mate/Codes/mate/mateclaw/mateclaw-server/src/main/java/vip/mate/agent/AgentService.java) ⎿ Added 19 lines 4 import com.alibaba.cloud.ai.dashscope.chat.DashScopeChatModel; 5 import com.alibaba.cloud.ai.dashscope.chat.DashScopeChatOptions; 6 import com.alibaba.cloud.ai.autoconfigure.dashscope.DashScopeConnectionProperties; 7 +import com.alibaba.cloud.ai.graph.CompiledGraph; 8 +import com.alibaba.cloud.ai.graph.CompileConfig; 9 +import com.alibaba.cloud.ai.graph.KeyStrategy; 10 +import com.alibaba.cloud.ai.graph.KeyStrategyFactory; 11 +import com.alibaba.cloud.ai.graph.StateGraph; 12 +import com.alibaba.cloud.ai.graph.action.AsyncEdgeAction; 13 +import com.alibaba.cloud.ai.graph.action.AsyncNodeAction; 14 import com.baomidou.mybatisplus.core.conditions.query.LambdaQueryWrapper; 15 import lombok.RequiredArgsConstructor; 16 import lombok.extern.slf4j.Slf4j; 17 import io.micrometer.observation.ObservationRegistry; 18 import org.springframework.ai.chat.client.ChatClient; 19 +import org.springframework.ai.chat.model.ChatModel; 20 import org.springframework.ai.openai.OpenAiChatModel; 21 import org.springframework.ai.openai.OpenAiChatOptions; 22 import org.springframework.ai.openai.api.OpenAiApi; 23 import org.springframework.ai.openai.api.OpenAiApi.ChatCompletion; 24 import org.springframework.ai.openai.api.OpenAiApi.ChatCompletionChunk; 25 import org.springframework.ai.openai.api.OpenAiApi.ChatCompletionRequest; 26 +import org.springframework.ai.support.ToolCallbacks; 27 +import org.springframework.ai.tool.ToolCallback; 28 import org.springframework.beans.factory.ObjectProvider; 29 import org.springframework.context.event.EventListener; 30 import org.springframework.http.ResponseEntity; ... 38 import org.springframework.web.reactive.function.client.WebClient; 39 import org.springframework.web.reactive.function.client.WebClientResponseException; 40 import reactor.core.publisher.Flux; 41 +import vip.mate.agent.graph.ReActStateKeys; 42 +import vip.mate.agent.graph.StateGraphReActAgent; 43 +import vip.mate.agent.graph.edge.ObservationDispatcher; 44 +import vip.mate.agent.graph.edge.ReasoningDispatcher; 45 +import vip.mate.agent.graph.node.ActionNode; 46 +import vip.mate.agent.graph.node.ObservationNode; 47 +import vip.mate.agent.graph.node.ReasoningNode; 48 import vip.mate.agent.model.AgentEntity; 49 import vip.mate.agent.repository.AgentMapper; 50 import vip.mate.exception.MateClawException; ... 57 import org.springframework.ai.model.tool.ToolCallingManager; 58 import vip.mate.planning.service.PlanningService; 59 import vip.mate.skill.service.SkillService; 60 +import vip.mate.system.service.SystemSettingService; 61 import vip.mate.tool.ToolRegistry; 62 +import vip.mate.tool.guard.DefaultToolGuard; 63 import vip.mate.workspace.conversation.ConversationService; 64 import vip.mate.workspace.conversation.model.MessageEntity; 65 ⎿ Async hook PreToolUse completed ⏺ Now add Collections import and the two new dependencies: ⏺ Update(/Users/mate/Codes/mate/mateclaw/mateclaw-server/src/main/java/vip/mate/agent/AgentService.java) ⎿ Added 2 lines 64 import vip.mate.workspace.conversation.model.MessageEntity; 65 66 import java.util.ArrayList; 67 +import java.util.Arrays; 68 +import java.util.Collections; 69 import java.util.List; 70 import java.util.Map; 71 import java.util.concurrent.ConcurrentHashMap; ⎿ Async hook PreToolUse completed ⏺ Now add the new fields: ⏺ Update(/Users/mate/Codes/mate/mateclaw/mateclaw-server/src/main/java/vip/mate/agent/AgentService.java) ⎿ Added 2 lines 101 private final ObjectProvider restClientBuilderProvider; 102 private final ObjectProvider webClientBuilderProvider; 103 private final ObjectMapper objectMapper; 104 + private final SystemSettingService systemSettingService; 105 + private final DefaultToolGuard toolGuard; 106 107 /** 运行时 Agent 实例缓存（agentId -> BaseAgent） */ 108 private final Map agentInstances = new ConcurrentHashMap<>(); ⎿ Async hook PreToolUse completed ⏺ Now modify chatStructuredStream() to add the StateGraph fast path: ⏺ Read(/Users/mate/Codes/mate/mateclaw/mateclaw-server/src/main/java/vip/mate/agent/AgentService.java · lines 137-156) ⎿ Read 20 lines ⏺ Read(/Users/mate/Codes/mate/mateclaw/mateclaw-server/src/main/java/vip/mate/agent/AgentService.java · lines 155-174) ⎿ Read 20 lines ⎿ Async hook PreToolUse completed ⎿ Async hook PreToolUse completed ⏺ Update(/Users/mate/Codes/mate/mateclaw/mateclaw-server/src/main/java/vip/mate/agent/AgentService.java) ⎿ Added 7 lines 157 158 public Flux chatStructuredStream(Long agentId, String message, String conversationId) { 159 BaseAgent agent = getOrBuildAgent(agentId); 160 + 161 + // StateGraph agent 内部已处理工具调用，直接走 chatStream 162 + if (agent instanceof StateGraphReActAgent) { 163 + return agent.chatStream(message, conversationId) 164 + .map(chunk -> new StreamDelta(chunk, null)); 165 + } 166 + 167 ModelConfigEntity runtimeModel = modelConfigService.getDefaultModel(); 168 ModelProviderEntity provider = modelProviderService.getProviderConfig(runtimeModel.getProvider()); 169 ModelProtocol protocol = ModelProtocol.fromChatModel(provider.getChatModel()); ⎿ Async hook PreToolUse completed ⏺ Now modify buildAgent() to add the StateGraph branch. Let me re-read the current buildAgent method: ⏺ Read(/Users/mate/Codes/mate/mateclaw/mateclaw-server/src/main/java/vip/mate/agent/AgentService.java · lines 218-262) ⎿ Read 45 lines ⎿ Async hook PreToolUse completed ⏺ Update(/Users/mate/Codes/mate/mateclaw/mateclaw-server/src/main/java/vip/mate/agent/AgentService.java) ⎿ Added 25 lines, removed 4 lines 233 ModelProviderEntity provider = modelProviderService.getProviderConfig(runtimeModel.getProvider()); 234 ModelProtocol protocol = ModelProtocol.fromChatModel(provider.getChatModel()); 235 boolean toolCallingEnabled = protocol == ModelProtocol.DASHSCOPE_NATIVE; 236 - ChatClient chatClient = createRuntimeChatClient(runtimeModel); 236 + int maxIter = entity.getMaxIterations() != null ? entity.getMaxIterations() : 10; 237 238 // 构建增强后的 systemPrompt = 原始 prompt + 技能增强 239 String basePrompt = entity.getSystemPrompt() != null ? entity.getSystemPrompt() : ""; 240 String skillEnhancement = skillService.buildSkillPromptEnhancement(); 241 String enhancedPrompt = basePrompt + skillEnhancement; 242 243 + // 判断是否使用 StateGraph 架构 244 + boolean useStateGraph = systemSettingService.isStateGraphEnabled() 245 + && "react".equals(entity.getAgentType()) 246 + && toolCallingEnabled; 247 + 248 BaseAgent agent; 249 if ("plan_execute".equals(entity.getAgentType())) { 250 + ChatClient chatClient = createRuntimeChatClient(runtimeModel); 251 agent = new PlanExecuteAgent(chatClient, conversationService, planningService, tools); 252 + } else if (useStateGraph) { 253 + // StateGraph 架构：显式控制 ReAct 循环 254 + ChatModel chatModel = buildRuntimeChatModel(runtimeModel); 255 + ChatClient chatClient = ChatClient.create(chatModel); 256 + List toolCallbacks = resolveToolCallbacks(tools); 257 + 258 + ReasoningNode reasoningNode = new ReasoningNode(chatModel, toolCallbacks); 259 + ActionNode actionNode = new ActionNode(toolCallbacks, toolGuard); 260 + ObservationNode observationNode = new ObservationNode(); 261 + 262 + CompiledGraph compiledGraph = buildReActGraph(reasoningNode, actionNode, observationNode, maxIter); 263 + agent = new StateGraphReActAgent(chatClient, conversationService, compiledGraph); 264 + log.info("Built StateGraph ReAct agent: {} (maxIterations={}, tools={}, toolGuard=enabled)", 265 + entity.getName(), maxIter, toolCallbacks.size()); 266 } else { 267 + ChatClient chatClient = createRuntimeChatClient(runtimeModel); 268 agent = new ReActAgent(chatClient, conversationService, tools); 269 } 270 271 agent.agentId = String.valueOf(entity.getId()); 272 agent.agentName = entity.getName(); 273 agent.systemPrompt = enhancedPrompt; 253 - agent.maxIterations = entity.getMaxIterations() != null ? entity.getMaxIterations() : 10; 274 + agent.maxIterations = maxIter; 275 agent.modelName = runtimeModel.getModelName(); 276 agent.temperature = runtimeModel.getTemperature(); 277 agent.maxTokens = runtimeModel.getMaxTokens(); 278 agent.topP = runtimeModel.getTopP(); 279 agent.toolCallingEnabled = toolCallingEnabled; 280 260 - log.info("Built agent instance: {} (type={}, runtimeModel={}/{}, protocol={}, tools={}, toolCallingEnabled={}, sk -illPromptLen={})", 261 - entity.getName(), entity.getAgentType(), runtimeModel.getProvider(), runtimeModel.getModelName(), 281 + log.info("Built agent instance: {} (type={}, stateGraph={}, runtimeModel={}/{}, protocol={}, tools={}, toolCallin +gEnabled={}, skillPromptLen={})", 282 + entity.getName(), entity.getAgentType(), useStateGraph, runtimeModel.getProvider(), runtimeModel.getModel +Name(), 283 protocol.getId(), tools.size(), toolCallingEnabled, skillEnhancement.length()); 284 return agent; 285 } ⎿ Async hook PreToolUse completed ⏺ Now add the helper methods. Let me find a good place to insert them — right before createRuntimeChatClient: ⏺ Read(/Users/mate/Codes/mate/mateclaw/mateclaw-server/src/main/java/vip/mate/agent/AgentService.java · lines 400-429) ⎿ Read 30 lines ⎿ Async hook PreToolUse completed ⏺ I'll add the helper methods right before createRuntimeChatClient: ⏺ Update(/Users/mate/Codes/mate/mateclaw/mateclaw-server/src/main/java/vip/mate/agent/AgentService.java) ⎿ Added 81 lines 426 return new StreamDelta(content, thinking); 427 } 428 429 + // ==================== StateGraph 辅助方法 ==================== 430 + 431 + /** 432 + * 将 @Tool 注解的 Bean 列表转为 ToolCallback 列表 433 + */ 434 + private List resolveToolCallbacks(List