Error 429 RESOURCE_EXHAUSTED when using VertexAiRagRetrieval tool

**Describe the bug**

I found this bug while making some tests with my diagnostic agent earlier today. I have a Vertex AI RAG corpus to store some schema information which my agent retrieves before making queries. The setup for the tool is as follows:

```py
from google.adk.tools.retrieval.vertex_ai_rag_retrieval import VertexAiRagRetrieval
from vertexai.preview import rag

schema_discovery = VertexAiRagRetrieval(
name='schema_discovery',
description=(
'Use this tool to retrieve osquery table schema documentation,'
),
rag_resources=[
rag.RagResource(
rag_corpus=os.environ.get("RAG_CORPORA_URI")
)
],
similarity_top_k=10,
vector_distance_threshold=0.6,
)
```

This code was working until Saturday, but when trying today it doesn't work and returns 429. I was surprised and thought it was really a 429 problem (but as a Googler I have very generous quotas), but I decided to use my old implementation which uses a regular function call instead, and to my surprise it is working normally with no 429 errors:

```py
def discover_schema(search_phrase: str) -> str:
"""Discovers osquery table names and schemas based on a descriptive search phrase.

Args:
search_phrase: A phrase describing the kind of information you're looking for.
For example: 'user login events' or 'network traffic'.

Returns:
Table names and schema information for tables related to the search phrase.
"""
rag_corpora_uri = os.environ.get('RAG_CORPORA_URI')
response = rag.retrieval_query(
rag_resources=[
rag.RagResource(
rag_corpus=rag_corpora_uri,
)
],
text=search_phrase,
)
return json.dumps(MessageToDict(response._pb))
```

I could not find any obvious reasons why calling the vertex ai SDK directly doesn't have any problems, but using the ADK tool has.

**To Reproduce**

1. Create a rag corpus in Vertex AI RAG Engine (can be empty)
2. Create a new agent with `adk create agent`
3. Add the following code to `agent.py`

```py
from google.adk.agents.llm_agent import Agent

from google.adk.tools.retrieval.vertex_ai_rag_retrieval import VertexAiRagRetrieval
from vertexai.preview import rag
import os

rag_query = VertexAiRagRetrieval(
name='rag_query',
description=(
'Use this tool to query the rag,'
),
rag_resources=[
rag.RagResource(
rag_corpus=os.environ.get("RAG_CORPORA_URI")
)
],
similarity_top_k=10,
vector_distance_threshold=0.6,
)

root_agent = Agent(
model='gemini-2.5-flash',
name='root_agent',
description='A helpful assistant for user questions.',
instruction='Answer user questions to the best of your knowledge',
tools=[
rag_query,
]
)

```

5. Run `adk web` and say "hello" to the agent

You should get the 429 error.

This implementation directly calling Vertex AI works perfectly:

```py
from vertexai.preview import rag
import os
import json
from google.protobuf.json_format import MessageToDict

def rag_query(search_phrase: str) -> str:
"""Use this tool to query the rag."""
rag_corpora_uri = os.environ.get('RAG_CORPORA_URI')
response = rag.retrieval_query(
rag_resources=[
rag.RagResource(
rag_corpus=rag_corpora_uri,
)
],
text=search_phrase,
)
return json.dumps(MessageToDict(response._pb))
```

**Expected behavior**
The agent should not error and greet the user

**Desktop (please complete the following information):**
- OS: Linux
- Python version(python -V): 3.12.3
- ADK version(pip show google-adk): 1.16.0

**Model Information:**
- Are you using LiteLLM: No
- Which model is being used: gemini-2.5-flash

**Additional context**
It was working without any errors just two days ago. Downgrading to ADK 1.15.0 didn't solve the issue. Calling Vertex AI RAG directly doesn't have the problem.