Fix a few bugs in opentelemetry-instrumentation-google-genai instrumentation package

instrumentation-genai/opentelemetry-instrumentation-google-genai/CHANGELOG.md

@@ -7,7 +7,9 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
 
 ## Unreleased
 
-- Minor change to check LRU cache in Completion Hook before acquiring semaphore/thread ([#3907](https://github.com/open-telemetry/opentelemetry-python-contrib/pull/3907)).
+- Ensure log event is written and completion hook is called even when model call results in exception. Put new
+log event (` gen_ai.client.inference.operation.details`) behind the flag `OTEL_SEMCONV_STABILITY_OPT_IN=gen_ai_latest_experimental`.
+Ensure same sem conv attributes are on the log and span. Fix an issue where the instrumentation would crash when a pydantic.BaseModel class was passed as the response schema ([#3905](https://github.com/open-telemetry/opentelemetry-python-contrib/pull/3905)).
 
 ## Version 0.4b0 (2025-10-16)
 

instrumentation-genai/opentelemetry-instrumentation-google-genai/src/opentelemetry/instrumentation/google_genai/dict_util.py

@@ -151,7 +151,7 @@ def _flatten_compound_value_using_json(
     )
 
 
-def _flatten_compound_value(
+def _flatten_compound_value(  # pylint: disable=too-many-return-statements
     key: str,
     value: Any,
     exclude_keys: Set[str],
@@ -189,13 +189,16 @@ def _flatten_compound_value(
             flatten_functions=flatten_functions,
         )
     if hasattr(value, "model_dump"):
-        return _flatten_dict(
-            value.model_dump(),
-            key_prefix=key,
-            exclude_keys=exclude_keys,
-            rename_keys=rename_keys,
-            flatten_functions=flatten_functions,
-        )
+        try:
+            return _flatten_dict(
+                value.model_dump(),
+                key_prefix=key,
+                exclude_keys=exclude_keys,
+                rename_keys=rename_keys,
+                flatten_functions=flatten_functions,
+            )
+        except TypeError:
+            return {key: str(value)}
     return _flatten_compound_value_using_json(
         key,
         value,