TNT-Likely · Oct 4, 2026 · Oct 4, 2026 · Oct 4, 2026 · Oct 4, 2026
diff --git a/frontend/packages/biz-ui/src/components/deep-analysis-modal.tsx b/frontend/packages/biz-ui/src/components/deep-analysis-modal.tsx
@@ -145,33 +145,46 @@ export function DeepAnalysisModal({
     setError('')
     setProgress(null)
     setTraceId(null)
+    let cancelled = false
 
     // 并发查询运行状态与已保存报告:
     //   - findRunning:这只股票最近 30 分钟有没有运行中的任务
     //   - getLatestForStock:有没有已保存的最近一次报告
-    // 优先级:running > done(已有结果)> idle
+    // 优先级:running > failed > done(已有结果)> idle
     Promise.all([
       tradingAgentsApi.findRunning(stockSymbol).catch(() => ({ trace_id: null, status: 'none' as const })),
       tradingAgentsApi.getLatestForStock(stockSymbol).catch(() => null),
-    ]).then(([runningInfo, latestResult]) => {
-      // 优先级:running(真在跑) > done(已保存的报告,允许重新分析) > idle
-      //   - stale / failed / success / none 都视为"不在跑"
-      //   - 任何状态下,只要有已保存报告就展示 DoneView(含「忽略缓存重新分析」按钮)
-      //   - 任何状态下,IdleView 的「开始分析」按钮永远可用,后端会做幂等去重
+    ]).then(async ([runningInfo, latestResult]) => {
+      if (cancelled) return
+      // 优先级:running > failed(保留最新错误) > done(已保存的报告) > idle
+      //   - 失败视图可重试,后端会做幂等去重
 
       // 1) 真正在跑(后端权威源)→ 进入 running
       if (runningInfo.status === 'running' && runningInfo.trace_id) {
         const tid = runningInfo.trace_id
         setTraceId(tid)
         setStage('running')
         // 后端确认在跑；即使采集阶段暂时没有日志，也继续由 SSE/polling 接力
-        tradingAgentsApi.getProgress(tid).then(resp => setProgress(resp))
+        tradingAgentsApi.getProgress(tid).then(resp => { if (!cancelled) setProgress(resp) })
         startWatching(tid)
         return
       }
 
-      // 2) 后端 stale/failed → 老任务死掉/失败,清掉本地痕迹,继续走缓存判断
-      //    不再回到 running,允许用户重新触发
+      // Keep a failed run's diagnostic visible when the dialog is reopened.
+      if (runningInfo.status === 'failed' && runningInfo.trace_id) {
+        const failedProgress = await tradingAgentsApi.getProgress(runningInfo.trace_id).catch(() => null)
+        if (cancelled) return
+        if (failedProgress?.status === 'failed') {
+          setTraceId(runningInfo.trace_id)
+          setProgress(failedProgress)
+          setError(failedProgress.run?.error || tr('errors.analysisFailed'))
+          setStage('error')
+          clearRunningTrace(stockSymbol)
+          return
+        }
+      }
+
+      // 2) 后端 stale/failed → 清掉本地运行痕迹,继续走缓存判断
       if (runningInfo.status === 'stale' || runningInfo.status === 'failed') {
         clearRunningTrace(stockSymbol)
       }
@@ -182,7 +195,7 @@ export function DeepAnalysisModal({
         if (localTrace) {
           setTraceId(localTrace)
           setStage('running')
-          tradingAgentsApi.getProgress(localTrace).then(resp => setProgress(resp))
+          tradingAgentsApi.getProgress(localTrace).then(resp => { if (!cancelled) setProgress(resp) })
           startWatching(localTrace)
           return
         }
@@ -200,6 +213,7 @@ export function DeepAnalysisModal({
       // 5) 都没有 → idle(开始分析按钮可用,后端幂等保护)
       clearRunningTrace(stockSymbol)
     })
+    return () => { cancelled = true }
     // eslint-disable-next-line react-hooks/exhaustive-deps
   }, [open, initialResult, stockSymbol])
 
@@ -360,7 +374,7 @@ export function DeepAnalysisModal({
           <div className="space-y-3 text-[13px]">
             <div className="rounded-lg bg-rose-500/10 border border-rose-500/30 p-3 text-rose-600">
               <div className="font-semibold mb-1">{tr('failedTitle')}</div>
-              <div className="text-[12px]">{error}</div>
+              <div className="text-[12px] whitespace-pre-wrap break-words">{error}</div>
             </div>
             <div className="flex justify-end gap-2">
               <Button variant="outline" onClick={handleClose}>{tr('close')}</Button>

diff --git a/frontend/src/pages/Agents.tsx b/frontend/src/pages/Agents.tsx
@@ -460,8 +460,12 @@ export default function AgentsPage() {
   const saveTaConfig = async () => {
     if (!taConfigAgent) return
     try {
+      // llm_max_tokens is a legacy setting. Keep accepting it in imported/old
+      // configs, but stop persisting or forwarding the output cap.
+      const configWithoutOutputCap = { ...taConfigForm }
+      delete configWithoutOutputCap.llm_max_tokens
       const config = {
-        ...taConfigForm,
+        ...configWithoutOutputCap,
         timeout_minutes: timeoutValue(taConfigForm.timeout_minutes, 30, 1, 60),
         llm_timeout_seconds: timeoutValue(taConfigForm.llm_timeout_seconds, 300, 1, 900),
         collection_timeout_seconds: timeoutValue(taConfigForm.collection_timeout_seconds, 45, 5, 300),

diff --git a/frontend/tests/analysis/deep-analysis-modal.test.tsx b/frontend/tests/analysis/deep-analysis-modal.test.tsx
@@ -1,14 +1,16 @@
 import i18n from '@/i18n'
-import { render, screen, waitFor, fireEvent } from '@testing-library/react'
+import { render, screen, waitFor, fireEvent, act } from '@testing-library/react'
 import { beforeEach, describe, expect, it, vi } from 'vitest'
-import { tradingAgentsApi, type DeepAnalysisResult } from '@panwatch/api'
+import { tradingAgentsApi, type DeepAnalysisResult, type ProgressResponse } from '@panwatch/api'
 import { DeepAnalysisModal } from '@panwatch/biz-ui/components/deep-analysis-modal'
 
-vi.mock('@panwatch/api', () => ({ tradingAgentsApi: { findRunning: vi.fn(), getLatestForStock: vi.fn() }, subscribeSSE: vi.fn() }))
+vi.mock('@panwatch/api', () => ({ tradingAgentsApi: { findRunning: vi.fn(), getLatestForStock: vi.fn(), getProgress: vi.fn() }, subscribeSSE: vi.fn() }))
 vi.mock('@panwatch/base-ui/components/ui/toast', () => ({ useToast: () => ({ toast: vi.fn() }) }))
 const result = { agent_name: 'tradingagents', title: '广汽集团', content: 'Report', analysis_date: '2026-10-01', generated_at: '2026-10-01T15:30:00+08:00', raw_data: { cost_usd: 0.0378, from_cache: true, suggestion: { action: 'hold', action_label: '持有', confidence: 7 }, token_usage: { input_tokens: 800, output_tokens: 200, total_tokens: 1000, recorded_calls: 2, completed_calls: 2, complete: true }, final_decision: 'PM report' } } as DeepAnalysisResult
 const props = { open: true, onOpenChange: vi.fn(), stockId: 1, stockName: '广汽集团', stockSymbol: '601238' }
-beforeEach(() => {
+beforeEach(async () => {
+  vi.clearAllMocks()
+  await i18n.changeLanguage('zh-CN')
   vi.mocked(tradingAgentsApi.findRunning).mockResolvedValue({ trace_id: null, status: 'none' })
   vi.mocked(tradingAgentsApi.getLatestForStock).mockResolvedValue(null)
 })
@@ -32,6 +34,35 @@ describe('deep analysis modal', () => {
     expect(screen.getByRole('button', { name: '开始分析' }).hasAttribute('disabled')).toBe(false)
     expect(screen.queryByText(/本月预算|预估成本|预算已用尽/)).toBeNull()
   })
+
+  it('restores the actual provider error after closing and reopening a failed run', async () => {
+    const error = 'AI 服务拒绝处理本次内容，请调整问题后重试。（HTTP 400 · code=1301 · 系统检测到输入或生成内容可能包含不安全或敏感内容）'
+    vi.mocked(tradingAgentsApi.findRunning).mockResolvedValue({ trace_id: 'failed-trace', status: 'failed' })
+    vi.mocked(tradingAgentsApi.getProgress).mockResolvedValue({ trace_id: 'failed-trace', status: 'failed',
+      stages: [], completed_stages: [], elapsed_sec: 42, total_cost_usd: 0,
+      run: { agent_name: 'tradingagents', status: 'failed', error, result: '', duration_ms: 42000, model_label: 'GLM', notify_sent: false },
+    })
+    render(<DeepAnalysisModal {...props} />)
+    expect(await screen.findByText(error)).toBeTruthy()
+    expect(screen.getByRole('button', { name: '重试' })).toBeTruthy()
+    expect(screen.queryByRole('button', { name: '开始分析' })).toBeNull()
+  })
+
+  it('does not apply a previous stock failure when its diagnostic arrives late', async () => {
+    let resolveProgress!: (value: ProgressResponse) => void
+    vi.mocked(tradingAgentsApi.findRunning).mockResolvedValueOnce({ trace_id: 'failed-trace', status: 'failed' })
+    vi.mocked(tradingAgentsApi.getProgress).mockReturnValueOnce(new Promise(resolve => { resolveProgress = resolve }))
+    const { rerender } = render(<DeepAnalysisModal {...props} />)
+    await waitFor(() => expect(tradingAgentsApi.getProgress).toHaveBeenCalledWith('failed-trace'))
+    rerender(<DeepAnalysisModal {...props} stockId={2} stockSymbol="300750" stockName="宁德时代" />)
+    await waitFor(() => expect(tradingAgentsApi.findRunning).toHaveBeenCalledWith('300750'))
+    await act(async () => resolveProgress({ trace_id: 'failed-trace', status: 'failed',
+      stages: [], completed_stages: [], elapsed_sec: 42, total_cost_usd: 0,
+      run: { agent_name: 'tradingagents', status: 'failed', error: 'Previous stock diagnostic', result: '', duration_ms: 42000, model_label: 'GLM', notify_sent: false },
+    }))
+    expect(screen.queryByText('Previous stock diagnostic')).toBeNull()
+    expect(screen.getByRole('button', { name: '开始分析' })).toBeTruthy()
+  })
 })
 
 it('shows REVIEW as a review state in an English historical report', async () => {

diff --git a/frontend/tests/settings/deep-analysis-timeouts.test.tsx b/frontend/tests/settings/deep-analysis-timeouts.test.tsx
@@ -38,7 +38,7 @@ it('shows and saves all timeout defaults for older configurations', async () =>
   expect((dialog.getByLabelText('单次模型请求超时（秒）') as HTMLInputElement).value).toBe('300')
   expect((dialog.getByLabelText('单个数据源采集超时（秒）') as HTMLInputElement).value).toBe('45')
   await userEvent.click(dialog.getByRole('button', { name: '保存' }))
-  await waitFor(() => expect(savedConfig()).toEqual({ debate_rounds: 1, llm_max_tokens: 4096,
+  await waitFor(() => expect(savedConfig()).toEqual({ debate_rounds: 1,
     timeout_minutes: 30, llm_timeout_seconds: 300, collection_timeout_seconds: 45 }))
 })
 

diff --git a/server.py b/server.py
@@ -1305,12 +1305,12 @@ async def trigger_agent(agent_name: str) -> str:
                 )
                 return result.content
         except Exception as e:
-            from src.platform.ai.errors import safe_ai_error_message
+            from src.platform.ai.errors import diagnostic_ai_error_message
 
             record_agent_run(
                 agent_name=agent_name,
                 status="failed",
-                error=safe_ai_error_message(e),
+                error=diagnostic_ai_error_message(e),
                 duration_ms=int((time.monotonic() - start) * 1000),
                 trace_id=trace_id,
                 trigger_source="manual",
@@ -1429,12 +1429,12 @@ async def trigger_agent_for_stock(
                 model_label=context.model_label,
             )
         except Exception as e:
-            from src.platform.ai.errors import safe_ai_error_message
+            from src.platform.ai.errors import diagnostic_ai_error_message
 
             record_agent_run(
                 agent_name=agent_name,
                 status="failed",
-                error=safe_ai_error_message(e),
+                error=diagnostic_ai_error_message(e),
                 duration_ms=int((time.monotonic() - start) * 1000),
                 trace_id=trace_id,
                 trigger_source="manual",

diff --git a/src/modules/automation/agent_catalog.py b/src/modules/automation/agent_catalog.py
@@ -118,7 +118,6 @@ class AgentSeedSpec:
             "llm_timeout_seconds": 300,  # 单次 LLM 请求超时，给慢响应留出时间
             "collection_timeout_seconds": 45,  # 单个数据源采集超时，失败时降级
             "llm_max_retries": 0,         # 深度分析失败快速落终态，不在图内重复重试
-            "llm_max_tokens": 4096,       # 限制模型输出，避免网关空闲超时
             "emit_paper_trading_signal": False,  # 是否把 BUY 决策写入 StrategySignalRun
                                                   # 驱动模拟盘自动开仓 (默认关,需用户主动启用)
             "enable_sec_edgar": False,  # 仅美股：优先使用有 filing-date 语义的 SEC EDGAR 财报

diff --git a/src/modules/automation/agent_scheduler.py b/src/modules/automation/agent_scheduler.py
@@ -5,7 +5,7 @@
 from apscheduler.schedulers.asyncio import AsyncIOScheduler
 
 from src.modules.automation.base import BaseAgent, AgentContext
-from src.platform.ai.errors import safe_ai_error_message
+from src.platform.ai.errors import diagnostic_ai_error_message
 from src.platform.marketdata.collectors.kline_collector import kline_source
 from src.modules.automation.agent_runs import record_agent_run
 from src.platform.observability.log_context import log_context
@@ -138,7 +138,7 @@ async def _run_agent(self, agent_name: str, stock_keys=None, stock_agent_id=None
                                 exc_info=True,
                             )
                             errors.append(
-                                f"{stock.symbol}: {safe_ai_error_message(e)}"
+                                f"{stock.symbol}: {diagnostic_ai_error_message(e)}"
                             )
                     logger.info(
                         f"[调度] Agent 单只模式执行完成: {agent.display_name}（执行{processed}，跳过{skipped}，共{len(targets)}）"
@@ -194,7 +194,7 @@ async def _run_agent(self, agent_name: str, stock_keys=None, stock_agent_id=None
             record_agent_run(
                 agent_name=agent_name,
                 status="failed",
-                error=safe_ai_error_message(e),
+                error=diagnostic_ai_error_message(e),
                 duration_ms=duration_ms,
                 trace_id=trace_id,
                 trigger_source="schedule",

diff --git a/src/modules/automation/api/agents.py b/src/modules/automation/api/agents.py
@@ -724,7 +724,7 @@ def get_run_progress(trace_id: str, db: Session = Depends(get_db)):
             "agent_name": run.agent_name,
             "status": run.status,
             "result": (run.result or "")[:1000],
-            "error": (run.error or "")[:500],
+            "error": (run.error or "")[:2000],
             "duration_ms": run.duration_ms,
             "model_label": run.model_label,
             "notify_sent": run.notify_sent,

diff --git a/src/modules/automation/tradingagents/agent.py b/src/modules/automation/tradingagents/agent.py
@@ -58,7 +58,7 @@ class TradingAgentsUnavailable(RuntimeError):
 def _bounded_graph_class(graph_cls):
     """让 TradingAgentsGraph 把请求边界传给 LangChain LLM 客户端。
 
-    TradingAgents 0.5.0 已支持 ``llm_max_retries``/``max_tokens``，但当前
+    TradingAgents 0.5.0 已支持 ``llm_max_retries``，但当前
     版本的 ``_get_provider_kwargs`` 尚未读取自定义 timeout。通过一个很小的
     子类适配该差异，避免直接修改 site-packages，也兼容后续上游自行支持
     timeout 的版本。
@@ -100,7 +100,9 @@ def __init__(
         holding_period_days: int = 5,     # 上游决策质量回测/持仓期限语义
         llm_timeout_seconds: int = 300,   # 单次 LLM 请求超时,给慢响应留出时间
         llm_max_retries: int = 0,         # 深度分析不在图内重复重试供应商请求
-        llm_max_tokens: int = 4096,       # 限制推理/报告输出,避免网关空闲超时
+        # 保留旧配置字段的兼容入口，但不再向模型传递输出上限。
+        llm_max_tokens: int | None = None,
+        auto_trigger: dict | None = None,  # 联动条件由 operations 读取；不影响本次图执行
     ):
         # 校验分析师配置
         analysts = list(analyst_types or sorted(VALID_ANALYSTS))
@@ -126,7 +128,6 @@ def __init__(
         self.holding_period_days = max(1, int(holding_period_days))
         self.llm_timeout_seconds = max(1, int(llm_timeout_seconds))
         self.llm_max_retries = max(0, int(llm_max_retries))
-        self.llm_max_tokens = max(256, int(llm_max_tokens))
 
         # 软依赖检测
         self._available, self._import_error = self._check_availability()
@@ -307,7 +308,13 @@ async def analyze(self, context: AgentContext, data: dict) -> AnalysisResult:
             holding_period_days=self.holding_period_days,
             llm_timeout_seconds=self.llm_timeout_seconds,
             llm_max_retries=self.llm_max_retries,
-            llm_max_tokens=self.llm_max_tokens,
+        )
+        logger.info(
+            "[TA] 执行参数 timeout_minutes=%s llm_timeout_seconds=%s "
+            "collection_timeout_seconds=%s llm_max_retries=%s deep_model=%s quick_model=%s",
+            self.timeout_minutes, self.llm_timeout_seconds,
+            self.collection_timeout_seconds, self.llm_max_retries,
+            ta_config["deep_think_llm"], ta_config["quick_think_llm"],
         )
 
         # 3) 进度回调

diff --git a/src/modules/automation/tradingagents/operations.py b/src/modules/automation/tradingagents/operations.py
@@ -49,7 +49,7 @@
 
 
 def _read_auto_trigger_config(db: Session) -> dict | None:
-    """从 AgentConfig.raw_config 读 auto_trigger 配置。
+    """从 AgentConfig.config 读 auto_trigger 配置。
 
     Returns:
         {
@@ -61,7 +61,7 @@ def _read_auto_trigger_config(db: Session) -> dict | None:
     agent = db.query(AgentConfig).filter(AgentConfig.name == "tradingagents").first()
     if not agent:
         return None
-    raw = agent.raw_config or {}
+    raw = agent.config or {}
     auto = raw.get("auto_trigger") or {}
     if not auto.get("enabled"):
         return None

diff --git a/src/modules/automation/tradingagents/runtime_support.py b/src/modules/automation/tradingagents/runtime_support.py
@@ -46,7 +46,6 @@ def build_ta_llm_config(
     holding_period_days: int = 5,
     llm_timeout_seconds: int = 300,
     llm_max_retries: int = 0,
-    llm_max_tokens: int = 4096,
 ) -> dict[str, Any]:
     """生成 TradingAgents 期望的 config dict。
 
@@ -80,6 +79,10 @@ def build_ta_llm_config(
     except ImportError:
         config = {}
 
+    # The upstream default currently contains ``max_tokens=None``. Remove the
+    # key entirely so TradingAgents does not forward an output cap at all.
+    config.pop("max_tokens", None)
+
     # 上游 config 含嵌套 vendor 配置；先复制，避免单次运行污染 DEFAULT_CONFIG。
     config["data_vendors"] = dict(config.get("data_vendors") or {})
     config["tool_vendors"] = dict(config.get("tool_vendors") or {})
@@ -139,7 +142,6 @@ def build_ta_llm_config(
         # 连接断开或模型持续输出会让整个 LangGraph 永久停在当前 analyst。
         "llm_timeout_seconds": max(1, int(llm_timeout_seconds)),
         "llm_max_retries": max(0, int(llm_max_retries)),
-        "max_tokens": max(256, int(llm_max_tokens)),
     })
     return config