fix: v3.4.1 — GLM tool calling 多轮回放修复

GLM coding 端点不支持标准 OpenAI tool calling 多轮回放格式，
continuation 时 assistant(tool_calls) + tool(results) 触发 400。

- GLM 历史消息折叠：tool_calls + tool results → 纯文本 assistant + user
- GLM 工具循环内部同步折叠：拦截工具回传也用纯文本格式
- reasoning_content 只对 deepseek/kimi 注入
- 添加 [GLM-DEBUG] 诊断日志

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>

Author: LegnaOS

readme.md

@@ -223,9 +223,10 @@ v3.4.0  Agent 工具系统进化 — Tool 类型系统 + ToolRegistry
 
 ### v3.4.1 — GLM 工具循环 messages 参数修复
 
-- **GLM 400 修复** — GLM (glm-5.1) 不支持 `reasoning_content` 字段和 `content: null`，工具循环第二轮回传 assistant 消息时触发 `messages 参数非法` 400 错误
-- **assistant content 修复** — 工具循环和历史回放中 `content: null` 改为 `content: ''`（空字符串），兼容所有 provider
-- **reasoning_content 条件注入** — 只对 DeepSeek/Kimi 注入 `reasoning_content`，GLM/OpenAI/其他 provider 跳过，避免不兼容字段污染请求
+- **GLM tool calling 多轮回放修复** — GLM coding 端点 (`/api/coding/paas/v4`) 不支持标准 OpenAI tool calling 多轮回放格式（`assistant(tool_calls) + tool(results)`），continuation 时稳定触发 `messages 参数非法` 400 错误
+- **GLM 消息折叠策略** — 对 GLM provider，历史中的 `assistant(tool_calls) + tool(results)` 自动折叠为纯文本 `assistant + user` 消息对，完全绕开多轮回放兼容性问题
+- **工具循环内部同步修复** — 代理内部工具循环（拦截工具执行后回传 AI）也对 GLM 使用纯文本折叠，确保工具链闭环
+- **reasoning_content 条件注入** — 只对 DeepSeek/Kimi 注入，GLM/OpenAI 跳过
 
 ### v3.4.0 — Agent 工具系统进化
 

src/messages.ts

@@ -723,9 +723,24 @@ export function splitReasoningContentFromText(text?: string): { content?: string
 // ===== 将 Augment 请求转换为 OpenAI 格式消息 =====
 export function augmentToOpenAIMessages(req: any) {
     const messages: any[] = [];
+    const isGlm = state.currentConfig.provider === 'glm';
+
     for (const turn of normalizeAugmentTimeline(req)) {
         if (turn.role === 'assistant') {
             if (turn.toolUses && turn.toolUses.length > 0) {
+                // GLM coding 端点不支持 tool calling 多轮回放
+                // 将 assistant(tool_calls) + tool(results) 折叠为纯文本 assistant 消息
+                if (isGlm) {
+                    const toolSummary = turn.toolUses.map((tu: any) => {
+                        let args = '';
+                        try { args = typeof tu.inputJson === 'string' ? tu.inputJson : JSON.stringify(tu.inputJson); } catch {}
+                        return `[Called ${tu.name}(${args.substring(0, 200)})]`;
+                    }).join('\n');
+                    const textPart = turn.text ? splitReasoningContentFromText(turn.text).content || '' : '';
+                    messages.push({ role: 'assistant', content: (textPart + '\n' + toolSummary).trim() });
+                    continue;
+                }
+
                 const { content, reasoningContent } = splitReasoningContentFromText(turn.text);
                 const assistantMessage: any = {
                     role: 'assistant',
@@ -738,10 +753,8 @@ export function augmentToOpenAIMessages(req: any) {
                 if (content) {
                     assistantMessage.content = content;
                 } else {
-                    assistantMessage.content = '';
+                    assistantMessage.content = null;
                 }
-                // reasoning_content 只有部分 provider 支持回传（DeepSeek/Kimi）
-                // GLM 不支持，会导致 "messages 参数非法" 400 错误
                 const supportsReasoningReplay = ['deepseek', 'kimi'].includes(state.currentConfig.provider);
                 if (reasoningContent && supportsReasoningReplay) {
                     assistantMessage.reasoning_content = reasoningContent;
@@ -756,13 +769,25 @@ export function augmentToOpenAIMessages(req: any) {
             continue;
         }
 
+        // GLM: tool results 折叠为 user 消息（与上面的 assistant 折叠配对）
+        if (isGlm && turn.toolResults && turn.toolResults.length > 0) {
+            const resultsSummary = turn.toolResults.map((tr: any) => {
+                const content = (tr.content || '').substring(0, 2000);
+                return `[Result of ${tr.name || 'tool'}]: ${content}`;
+            }).join('\n\n');
+            messages.push({ role: 'user', content: resultsSummary });
+            if (turn.text) {
+                messages.push({ role: 'user', content: turn.text });
+            }
+            continue;
+        }
+
         for (const toolResult of turn.toolResults || []) {
             const toolMsg: any = {
                 role: 'tool',
                 tool_call_id: toolResult.id,
                 content: toolResult.content || ''
             };
-            // GLM 不支持 tool 消息中的 name 字段，会导致 "messages 参数非法"
             if (state.currentConfig.provider !== 'glm') {
                 toolMsg.name = toolResult.name || 'unknown';
             }

src/providers/openai.ts

@@ -591,8 +591,11 @@ export async function executeOpenAIRequest(
                 const contentType = m?.content === null ? 'null' : typeof m?.content;
                 const hasToolCalls = Array.isArray(m?.tool_calls) ? m.tool_calls.length : 0;
                 const hasReasoning = m?.reasoning_content ? 'yes' : 'no';
-                log(`[GLM-DEBUG] msg[${mi}] role=${m?.role} keys=[${keys}] content=${contentType}(${String(m?.content).substring(0, 50)}) tool_calls=${hasToolCalls} reasoning=${hasReasoning}`);
+                const tcIds = Array.isArray(m?.tool_calls) ? m.tool_calls.map((tc: any) => `${tc?.function?.name}:${tc?.id}`).join(', ') : '';
+                const toolCallId = m?.tool_call_id || '';
+                log(`[GLM-DEBUG] msg[${mi}] role=${m?.role} keys=[${keys}] content=${contentType}(${String(m?.content).substring(0, 80)}) tool_calls=${hasToolCalls}[${tcIds}] tool_call_id=${toolCallId} reasoning=${hasReasoning}`);
             }
+            log(`[GLM-DEBUG] Full request body (first 2000 chars): ${apiBody.substring(0, 2000)}`);
         }
 
         const url = new URL(resolvedEndpoint);
@@ -1069,6 +1072,39 @@ export async function forwardToOpenAIStream(augmentReq: any, res: any) {
                 }
 
                 // ✅ 所有工具都被拦截了 → 把结果送回 AI 继续生成
+                // GLM: 折叠为纯文本格式（不支持 tool calling 多轮回放）
+                if (state.currentConfig.provider === 'glm') {
+                    const toolSummary = [...interceptedTools.map(({ tc, toolNode }) => {
+                        const content = (toolNode.tool_result_node.content || '').substring(0, 2000);
+                        return `[Result of ${tc.name}]: ${content}`;
+                    }), ...await Promise.all(codebaseSearchCalls.map(async (cs: any) => {
+                        const searchResult = await executeRAGSearch(cs.query);
+                        return `[Result of codebase_search("${cs.query}")]: ${searchResult.substring(0, 2000)}`;
+                    }))].join('\n\n');
+
+                    const textPart = result.text ? splitReasoningContentFromText(result.text).content || '' : '';
+                    const callsSummary = [...otherToolCalls, ...codebaseSearchCalls.map((cs: any) => ({
+                        name: 'codebase_search', arguments: JSON.stringify({ query: cs.query })
+                    }))].map((tc: any) => `[Called ${tc.name}(${(typeof tc.arguments === 'string' ? tc.arguments : JSON.stringify(tc.arguments || {})).substring(0, 200)})]`).join('\n');
+
+                    currentMessages.push({ role: 'assistant', content: (textPart + '\n' + callsSummary).trim() });
+                    currentMessages.push({ role: 'user', content: toolSummary });
+
+                    // 流式显示
+                    for (const { tc, toolNode } of interceptedTools) {
+                        try {
+                            const resultObj = JSON.parse(toolNode.tool_result_node.content);
+                            const diffText = renderDiffText(resultObj, tc.name);
+                            res.write(JSON.stringify({ text: diffText, nodes: [], stop_reason: 0 }) + '\n');
+                        } catch {
+                            res.write(JSON.stringify({ text: `\n✅ ${tc.name} executed\n`, nodes: [], stop_reason: 0 }) + '\n');
+                        }
+                    }
+
+                    log(`[LOOP] GLM: folded ${interceptedTools.length} tools + ${codebaseSearchCalls.length} searches into text messages`);
+                    continue;
+                }
+
                 // 1. 构建 assistant message（包含 tool_calls）
                 const allToolCalls = [...otherToolCalls, ...codebaseSearchCalls.map((cs: any) => ({
                     id: cs.id, name: 'codebase_search', arguments: JSON.stringify({ query: cs.query })
@@ -1084,7 +1120,7 @@ export async function forwardToOpenAIStream(augmentReq: any, res: any) {
                 const assistantReplay = splitReasoningContentFromText(result.text);
                 const assistantReplayMessage: any = {
                     role: 'assistant',
-                    content: assistantReplay.content || '',
+                    content: assistantReplay.content || null,
                     tool_calls: assistantToolCallsMsg
                 };
                 // reasoning_content 只有部分 provider 支持回传（DeepSeek/Kimi）