fix: failure recovery forces modify_report intent bypassing LLM classify

- process_input sets _failure_recovery flag when injecting pending_failure_context
- classify_intent skips LLM classification when flag is set, directly routes to modify_jrxml
- Smart truncation for intent classify: keep head 200 + tail 300 chars instead of head 500
  (prevents user's actual message from being truncated away by long injected context)
- This fixes the bug where "retry" or pasted error messages were misclassified as
  consult_question or initial_generation after max retry exhaustion

agent/nodes.py

@@ -109,6 +109,7 @@ def process_input(state: AgentState) -> Dict:
         )
         user_input = f"{failure_note}\n\n---\n用户新输入:\n{user_input}"
         state["pending_failure_context"] = {}
+        state["_failure_recovery"] = True  # 标记本轮为失败恢复，分类器强制 modify_report
 
     # 维护工作对话历史
     conv_history = state.get("conversation_history", [])
@@ -217,12 +218,22 @@ def classify_intent(state: AgentState) -> Dict:
     user_input = state.get("user_input", "")
     has_report = "是" if state.get("current_jrxml", "").strip() else "否"
 
+    # 失败恢复模式：跳过 LLM 分类，直接走修正流程
+    if state.pop("_failure_recovery", False):
+        state["intent"] = "modify_report"
+        return state
+
     intent = "initial_generation"
     try:
         llm = get_llm(caller="classify_intent")
+        # 智能截断：保留首部 200 + 尾部 300，避免用户真正输入被中间的长 JRXML 挤掉
+        if len(user_input) > 500:
+            ui_snippet = user_input[:200] + "\n...[已截断]...\n" + user_input[-300:]
+        else:
+            ui_snippet = user_input
         prompt = load_prompt("intent_classify").format(
             has_report=has_report,
-            user_input=user_input[:500],
+            user_input=ui_snippet,
         )
         resp = llm.invoke(prompt)
         raw = resp.content.strip().lower()