v1.1.1 修复 thinking 推理模型(content为空)导致 LLM JSON 解析失败：content 为空时用 reasoning_content 兜底、重试消息截断防上下文膨胀、决策 max_tokens 加大(500->1024/重试800)、去掉硬编码温度改尊重模型配置

agent.py

@@ -242,7 +242,7 @@ class TaskRunner(threading.Thread):
                         [{'role': 'system',
                           'content': VISION_SYSTEM_PROMPT if self.vision else SYSTEM_PROMPT},
                          {'role': 'user', 'content': user_content}],
-                        cfg=self.llm_cfg, temperature=0.2, max_tokens=500)
+                        cfg=self.llm_cfg, max_tokens=1024)
                 except LLMError as e:
                     self._log(f'LLM 错误: {e}')
                     self._finish(browser, 'error', f'LLM 决策失败: {e}', steps)
@@ -403,7 +403,7 @@ class TaskRunner(threading.Thread):
                   'content': VISION_SYSTEM_PROMPT if self.vision else SYSTEM_PROMPT},
                  {'role': 'user',
                   'content': self._build_user_content(retry_msg, browser, self.current.get('step', 0) + 99)}],
-                cfg=self.llm_cfg, temperature=0.2, max_tokens=400)
+                cfg=self.llm_cfg, max_tokens=800)
             new_action = retry_dec.get('action', '')
             if new_action == 'fail':
                 return 'error', f'自愈放弃: {retry_dec.get("summary", last_err)}', {}