feat(bigquery): expose thinking and tool-use token columns in analytics views

Add usage_thinking_tokens and usage_tool_use_tokens to the LLM_RESPONSE
analytics view, sourced from the usage_metadata proto the plugin already logs
to attributes.usage_metadata (thoughts_token_count and
tool_use_prompt_token_count).

Per the genai GenerateContentResponseUsageMetadata contract, total_token_count =
prompt_token_count + candidates_token_count + tool_use_prompt_token_count +
thoughts_token_count, so thinking and tool-use tokens are separate addends
rather than subsets of prompt/candidates. Surfacing them lets analytics account
for them without double counting. Both fields are optional and resolve to NULL
for models/responses that do not report them, so the change stays
model-agnostic. No plugin logging change is needed since the full usage_metadata
is already persisted to attributes.

Co-authored-by: Haiyuan Cao <haiyuan@google.com>
PiperOrigin-RevId: 943493796

Author: haiyuan-eng-google

src/google/adk/plugins/bigquery_agent_analytics_plugin.py

@@ -2060,6 +2060,16 @@ def _parse_custom_metadata_allowlist(
             " '$.usage_metadata.cached_content_token_count') AS INT64) AS"
             " usage_cached_tokens"
         ),
+        (
+            "CAST(JSON_VALUE(attributes,"
+            " '$.usage_metadata.thoughts_token_count') AS INT64) AS"
+            " usage_thinking_tokens"
+        ),
+        (
+            "CAST(JSON_VALUE(attributes,"
+            " '$.usage_metadata.tool_use_prompt_token_count') AS INT64) AS"
+            " usage_tool_use_tokens"
+        ),
         (
             "SAFE_DIVIDE(CAST(JSON_VALUE(attributes,"
             " '$.usage_metadata.cached_content_token_count') AS"

tests/unittests/plugins/test_bigquery_agent_analytics_plugin.py

@@ -5978,6 +5978,26 @@ def test_view_sql_contains_correct_event_filter(self):
       view_name = "v_" + event_type.lower()
       assert view_name in all_sql, f"View {view_name} not found in SQL"
 
+  def test_llm_response_view_exposes_token_usage_columns(self):
+    """LLM_RESPONSE view surfaces cached/thinking/tool-use token columns.
+
+    These are read from the full ``usage_metadata`` proto that is already
+    logged to ``attributes.usage_metadata``, so they are sourced from
+    ``attributes`` rather than the ``content.usage`` summary.
+    """
+    plugin = self._make_plugin(create_views=True)
+    plugin.client.get_table.side_effect = cloud_exceptions.NotFound("not found")
+    plugin.client.query.return_value = mock.MagicMock()
+
+    plugin._ensure_schema_exists()
+
+    all_sql = " ".join(c[0][0] for c in plugin.client.query.call_args_list)
+    assert "usage_cached_tokens" in all_sql
+    assert "usage_thinking_tokens" in all_sql
+    assert "usage_tool_use_tokens" in all_sql
+    assert "$.usage_metadata.thoughts_token_count" in all_sql
+    assert "$.usage_metadata.tool_use_prompt_token_count" in all_sql
+
   def test_config_create_views_default_true(self):
     """Config create_views defaults to True."""
     config = bigquery_agent_analytics_plugin.BigQueryLoggerConfig()