feat: add OpenAI Responses API support in labs

Add OpenAIResponsesLlm and AzureOpenAIResponsesLlm under labs.openai, a
BaseLlm targeting the OpenAI Responses API: request/response/streaming
conversion, reasoning summaries, structured output, tool mapping, and
usage metadata.

Merge #6188
Closes #3209

Co-authored-by: Luca Frigato <37444661+FrigaZzz@users.noreply.github.com>

Co-authored-by: George Weale <gweale@google.com>
PiperOrigin-RevId: 938272066

Author: GWeale

pyproject.toml

@@ -154,6 +154,7 @@ optional-dependencies.extensions = [
   "llama-index-embeddings-google-genai>=0.3",
   "llama-index-readers-file>=0.4",
   "lxml>=5.3",
+  "openai>=2.20,<3",
   "pypika>=0.50",
   "toolbox-adk>=1,<2",
 ]
@@ -224,7 +225,7 @@ optional-dependencies.test = [
   "llama-index-readers-file>=0.4",
   "lxml>=5.3",
   "mcp>=1.24,<2",
-  "openai>=1.100.2",
+  "openai>=2.20,<3",
   "opentelemetry-exporter-gcp-logging>=1.9.0a0,<=1.12.0a0",
   "opentelemetry-exporter-gcp-monitoring>=1.9.0a0,<2",
   "opentelemetry-exporter-gcp-trace>=1.9,<2",

src/google/adk/flows/llm_flows/contents.py

@@ -69,6 +69,12 @@ async def run_async(
           id_pairing_model_types.append(LiteLlm)
         except (ImportError, OSError):
           pass
+        try:
+          from ...labs.openai import OpenAIResponsesLlm
+
+          id_pairing_model_types.append(OpenAIResponsesLlm)
+        except (ImportError, OSError):
+          pass
         if isinstance(canonical_model, tuple(id_pairing_model_types)):
           preserve_function_call_ids = True
 

src/google/adk/labs/openai/__init__.py

@@ -13,7 +13,11 @@
 # limitations under the License.
 
 from ._openai_llm import OpenAILlm
+from ._openai_responses_llm import AzureOpenAIResponsesLlm
+from ._openai_responses_llm import OpenAIResponsesLlm
 
 __all__ = [
+    'AzureOpenAIResponsesLlm',
     'OpenAILlm',
+    'OpenAIResponsesLlm',
 ]

src/google/adk/labs/openai/_openai_llm.py

@@ -46,6 +46,7 @@
 from ...models.base_llm import BaseLlm
 from ...models.llm_request import LlmRequest
 from ...models.llm_response import LlmResponse
+from ._openai_schema import enforce_strict_openai_schema
 
 logger = logging.getLogger("google_adk." + __name__)
 
@@ -180,29 +181,6 @@ def _content_to_openai_messages(
   return messages
 
 
-def _enforce_strict_openai_schema(schema: dict[str, Any]) -> None:
-  """Recursively transforms a JSON schema for OpenAI strict structured outputs."""
-  if not isinstance(schema, dict):
-    return
-  if "$ref" in schema:
-    for key in list(schema.keys()):
-      if key != "$ref":
-        del schema[key]
-    return
-  if schema.get("type") == "object" and "properties" in schema:
-    schema["additionalProperties"] = False
-    schema["required"] = sorted(schema["properties"].keys())
-  for defn in schema.get("$defs", {}).values():
-    _enforce_strict_openai_schema(defn)
-  for prop in schema.get("properties", {}).values():
-    _enforce_strict_openai_schema(prop)
-  for key in ("anyOf", "oneOf", "allOf"):
-    for item in schema.get(key, []):
-      _enforce_strict_openai_schema(item)
-  if "items" in schema and isinstance(schema["items"], dict):
-    _enforce_strict_openai_schema(schema["items"])
-
-
 def _update_type_string(value: Any):
   """Lowercases nested JSON schema type strings for OpenAI compatibility."""
   if isinstance(value, list):
@@ -406,7 +384,7 @@ async def generate_content_async(
           schema_name = str(schema_dict["title"])
 
       if schema_dict:
-        _enforce_strict_openai_schema(schema_dict)
+        enforce_strict_openai_schema(schema_dict)
         response_format = {
             "type": "json_schema",
             "json_schema": {