关于多agent中，子agent参数planner=PlanReActPlanner()的问题

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**Describe the Bug:**
多agent中，子agent使用planner=PlanReActPlanner()参数，agent调用tools=[FunctionTool(tool_rag_qa)] tool_rag_qa是rag检索， 这个tool的作用就是调用rag，在几轮对话以后，就返回内容为空，模型没有输出

**Steps to Reproduce:**
Please provide a numbered list of steps to reproduce the behavior:
1. Install 'google-adk'
2. test 'adk web'
不设置planner=PlanReActPlanner()，多轮对话正常，多少轮都没事
设置planner=PlanReActPlanner()，多轮对话，几轮之后模型返回值为空

**Expected Behavior:**
可以在多agent中，子agent可以正常进行多轮对话

**Observed Behavior:**
无报错

**Environment Details:**

- pip install adk=1.25.1
- ubuntu 22/04
- Python 12

**Model Information:**

- Are you using LiteLLM: Yes
- Which model is being used: deepseek

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## 🟡 Optional Information
*Providing this information greatly speeds up the resolution process.*

**Regression:** adk web
例子：
/REASONING/ 根据工具返回的信息，我获得了高血压分级标准。现在我可以按照约束2的要求，对用户血压145/95mmHg进行分级评估。

收缩压145mmHg属于140~159mmHg范围
舒张压95mmHg属于90~99mmHg范围
现在我需要按照约束2的格式输出分级结果。

/FINAL_ANSWER/

返回的state是模型总结的信息

几轮之后，在进行对话，可以正确思考并且调用tool，但是返回的state是空字符串，无报错。

**Minimal Reproduction Code:**

agent_health_education = None
try:
agent_health_education = Agent(
model=model_default,
planner=PlanReActPlanner(),
name="agent_health_education",
instruction=prompt.INSTRUCTION_EDUCATION,
description="负责对用户提出的高血压问题进行解答、咨询或科普教育。",
#before_model_callback=simple_before_model_modifier,
tools=[FunctionTool(tool_rag_qa)],
output_key="health_education-result",
)
print(f"✅ Agent '{agent_health_education.name}'.")
except Exception as e:
print(f"❌ Could not create agent '{agent_health_education.name}'. Error: {e}")

**How often has this issue occurred?:**

- Always (100%)