feat(tools): Add debug logging to VertexAiSearchTool

Merge https://github.com/google/adk-python/pull/3284

**Problem:**
When debugging agents that utilize the `VertexAiSearchTool`, it's currently difficult to inspect the specific configuration parameters (datastore ID, engine ID, filter, max_results, etc.) being passed to the underlying Vertex AI Search API via the `LlmRequest`. This lack of visibility can hinder troubleshooting efforts related to tool configuration.

**Solution:**
This PR enhances the `VertexAiSearchTool` by adding a **debug-level log statement** within the `process_llm_request` method. This log precisely records the parameters being used for the Vertex AI Search configuration just before it's appended to the `LlmRequest`.

This provides developers with crucial visibility into the tool's runtime behavior when debug logging is enabled, significantly improving the **debuggability** of agents using this tool. Corresponding unit tests were updated to rigorously verify this new logging output using `caplog`. Additionally, minor fixes were made to the tests to resolve Pydantic validation errors.

Co-authored-by: Xuan Yang <xygoogle@google.com>
COPYBARA_INTEGRATE_REVIEW=https://github.com/google/adk-python/pull/3284 from omkute10:feat/add-logging-vertex-search-tool 199c12bf00a57abe202401591088c0423b39b928
PiperOrigin-RevId: 836419886

src/google/adk/tools/vertex_ai_search_tool.py

@@ -14,6 +14,7 @@
 
 from __future__ import annotations
 
+import logging
 from typing import Optional
 from typing import TYPE_CHECKING
 
@@ -25,6 +26,8 @@ from ..utils.model_name_utils import is_gemini_model
 from .base_tool import BaseTool
 from .tool_context import ToolContext
 
+logger = logging.getLogger('google_adk.' + __name__)
+
 if TYPE_CHECKING:
   from ..models import LlmRequest
 
@@ -102,6 +105,30 @@ class VertexAiSearchTool(BaseTool):
         )
       llm_request.config = llm_request.config or types.GenerateContentConfig()
       llm_request.config.tools = llm_request.config.tools or []
+
+      # Format data_store_specs concisely for logging
+      if self.data_store_specs:
+        spec_ids = [
+            spec.data_store.split('/')[-1] if spec.data_store else 'unnamed'
+            for spec in self.data_store_specs
+        ]
+        specs_info = (
+            f'{len(self.data_store_specs)} spec(s): [{", ".join(spec_ids)}]'
+        )
+      else:
+        specs_info = None
+
+      logger.debug(
+          'Adding Vertex AI Search tool config to LLM request: '
+          'datastore=%s, engine=%s, filter=%s, max_results=%s, '
+          'data_store_specs=%s',
+          self.data_store_id,
+          self.search_engine_id,
+          self.filter,
+          self.max_results,
+          specs_info,
+      )
+
       llm_request.config.tools.append(
           types.Tool(
               retrieval=types.Retrieval(