evaluate_eval_set silently passes when eval_results_by_eval_id is empty (zero eval cases or num_runs=0)

## 🔴 Required Information

**Describe the Bug:**
`AgentEvaluator.evaluate_eval_set` reports overall success on an eval set that
was never actually evaluated. `evaluate_eval_set` builds `eval_results_by_eval_id`
from the eval set, iterates it to populate a `failures` list, and finishes with
`assert not failures`. If `eval_results_by_eval_id` ends up empty for any
reason, the loop body never runs, `failures` stays `[]`, and the assert passes
— the function returns normally with no signal that zero cases were evaluated.

Two independent, ordinary public-API calls reach this with no validation
bypass:
1. An `EvalSet` with `eval_cases=[]` — `EvalSet.eval_cases` has no
`min_length`/validator, so this constructs cleanly.
2. `evaluate_eval_set(..., num_runs=0)` on a *non-empty* eval set — `num_runs`
has no bounds check anywhere in the file, and `inference_requests =
[InferenceRequest(...)] * num_runs` becomes `[]`.

Both silently produce the same "nothing was evaluated, but nothing failed
either" outcome.

**Steps to Reproduce:** minimal, self-contained repro (writes a real temp
agent module, no third-party packages):

```python
"""Minimal, self-contained repro for AgentEvaluator.evaluate_eval_set's
vacuous pass on an empty eval set (agent_evaluator.py, evaluate_eval_set).
"""
from __future__ import annotations
import asyncio, tempfile, uuid
from pathlib import Path
from google.adk.evaluation.agent_evaluator import AgentEvaluator
from google.adk.evaluation.eval_config import EvalConfig
from google.adk.evaluation.eval_set import EvalSet

def _write_agent_module(tmp_path: Path) -> str:
package_name = f"vacuous_pass_repro_{uuid.uuid4().hex}"
package_dir = tmp_path / package_name
package_dir.mkdir()
(package_dir / "__init__.py").write_text("", encoding="utf-8")
(package_dir / "agent.py").write_text(
"from google.adk.agents.llm_agent import LlmAgent\n"
"from google.adk.models.base_llm import BaseLlm\n"
"from google.adk.models.llm_response import LlmResponse\n"
"from google.genai import types as genai_types\n\n\n"
"class _FakeLlm(BaseLlm):\n"
" model: str = 'fake-model'\n\n"
" @classmethod\n"
" def supported_models(cls):\n"
" return ['fake-model']\n\n"
" async def generate_content_async(self, llm_request, stream=False):\n"
" yield LlmResponse(content=genai_types.Content(\n"
" parts=[genai_types.Part(text='ok')], role='model'))\n\n\n"
"root_agent = LlmAgent(name='vacuous_pass_repro_agent', model=_FakeLlm(),\n"
" instruction='Answer briefly.')\n",
encoding="utf-8",
)
return f"{package_name}.agent"

async def main() -> None:
with tempfile.TemporaryDirectory() as tmp_dir_str:
tmp_path = Path(tmp_dir_str)
module_name = _write_agent_module(tmp_path)
import sys
sys.path.insert(0, str(tmp_path))
try:
empty_eval_set = EvalSet(eval_set_id="empty_set", eval_cases=[])
result = await AgentEvaluator.evaluate_eval_set(
agent_module=module_name,
eval_set=empty_eval_set,
eval_config=EvalConfig(criteria={"tool_trajectory_avg_score": 1.0}),
)
print(f"RESULT: completed WITHOUT raising. Returned: {result!r}")
print("VERDICT: PASSED -- vacuous pass on zero eval cases.")
finally:
sys.path.remove(str(tmp_path))
sys.modules.pop(module_name, None)
sys.modules.pop(module_name.rsplit(".", 1)[0], None)

if __name__ == "__main__":
asyncio.run(main())
```

**Expected Behavior:** `evaluate_eval_set` should raise or otherwise signal
that zero cases were evaluated — a "pass" should mean "every requested case
was checked and none failed," not "nothing was checked."

**Observed Behavior:**
```
RESULT: completed WITHOUT raising. Returned: None
VERDICT: PASSED -- vacuous pass on zero eval cases.
```
Process exit code `0`. A second, independent repro (non-empty `EvalSet`,
`num_runs=0`) reproduces the identical outcome through the same mechanism.

**Environment:** google-adk main branch (this repo),
`src/google/adk/evaluation/agent_evaluator.py:289` (the `assert not failures`
line), `AgentEvaluator.evaluate_eval_set`.

## CI implication

Any test suite or CI gate that calls `AgentEvaluator.evaluate_eval_set`/`.evaluate()`
directly (rather than going through the `adk eval` CLI) will report a clean
pass for an eval set that was silently emptied by a config bug, a bad filter,
or an accidental `num_runs=0`, rather than failing loudly.

**Note:** this is a separate code path from the `adk eval` CLI command
(`cli_tools_click.py::cli_eval`, which builds its own `eval_run_summary` via
`LocalEvalService` directly and never calls `AgentEvaluator`) — confirmed by
reading both call chains. The CLI has an analogous "empty collection defaults
to a pass" shape in its own exit-code logic, which is unaffected by this
issue's scope either way.

I'm happy to send a PR for this if useful — the fix is a small, additive
check (e.g. treat an empty `eval_results_by_eval_id` as `NOT_EVALUATED`
rather than a silent pass), similar in shape to a couple of other
NOT_EVALUATED-masking fixes already proposed against this same subsystem.