fix: fix response class strictness

packages/gen/gen_ai_hub/orchestration_v2/__init__.py

@@ -40,7 +40,7 @@
 
     # message
     "SystemMessage", "UserMessage", "AssistantMessage", "ToolChatMessage", "DeveloperChatMessage",
-    "ChatMessage", "ResponseChatMessage", "FunctionCall", "MessageToolCall",
+    "ChatMessage", "ResponseChatMessage", "FunctionCall", "MessageToolCall", "ReasoningBlock",
 
     # multimodal_items
     "ImageDetailLevel", "TextPart", "ImageUrl", "ImagePart", "ContentPart", "ImageItem",

packages/gen/gen_ai_hub/orchestration_v2/models/__init__.py

@@ -18,7 +18,7 @@
 from .llama_guard_3_filter import LlamaGuard38bFilter
 from .llm_model_details import LLMModelDetails
 from .message import (SystemMessage, UserMessage, AssistantMessage, ToolChatMessage, DeveloperChatMessage, ChatMessage,
-                     ResponseChatMessage, FunctionCall, MessageToolCall)
+                     ResponseChatMessage, FunctionCall, MessageToolCall, ReasoningBlock)
 from .multimodal_items import ImageDetailLevel, TextPart, ImageUrl, ImagePart, ContentPart, ImageItem
 from .response import (PromptTokensDetails, CompletionTokensDetails, TokenUsage, GenericModuleResult, TopLogprob,
                       ChatCompletionTokenLogprob, ChoiceLogprobs, LLMChoice, StreamFunctionObject, StreamToolCall,
@@ -73,7 +73,7 @@
 
     # message
     "SystemMessage", "UserMessage", "AssistantMessage", "ToolChatMessage", "DeveloperChatMessage",
-    "ChatMessage", "ResponseChatMessage", "FunctionCall", "MessageToolCall",
+    "ChatMessage", "ResponseChatMessage", "FunctionCall", "MessageToolCall", "ReasoningBlock",
 
     # multimodal_items
     "ImageDetailLevel", "TextPart", "ImageUrl", "ImagePart", "ContentPart", "ImageItem",

packages/gen/gen_ai_hub/orchestration_v2/models/base.py

@@ -31,3 +31,16 @@ def model_dump(self, **kwargs):
         kwargs.setdefault("by_alias", True)
         kwargs.setdefault("exclude_none", True)
         return super().model_dump(**kwargs)
+
+class ResponseBaseModel(BaseModel):
+    """
+    Base model for API response models.
+
+    - `extra="allow"` allows unexpected fields in responses to be accepted,
+      since the external API might introduce new attributes in the response.
+    """
+
+    model_config = ConfigDict(
+        extra="allow",
+        frozen=False,
+    )

packages/gen/gen_ai_hub/orchestration_v2/models/embeddings.py

@@ -7,7 +7,7 @@
 
 from pydantic import Field
 
-from gen_ai_hub.orchestration_v2.models.base import ABCBaseModel as BaseModel
+from gen_ai_hub.orchestration_v2.models.base import ABCBaseModel as BaseModel, ResponseBaseModel
 from gen_ai_hub.orchestration_v2.models.data_masking import MaskingModuleConfig
 
 
@@ -117,7 +117,7 @@ class EmbeddingsInput(BaseModel):
     type_: Optional[EmbeddingsInputType] = Field(default=None, alias="type")
 
 
-class EmbeddingsUsage(BaseModel):
+class EmbeddingsUsage(ResponseBaseModel):
     """
     Token usage information for the embeddings request.
 
@@ -129,7 +129,7 @@ class EmbeddingsUsage(BaseModel):
     total_tokens: int
 
 
-class EmbeddingResult(BaseModel):
+class EmbeddingResult(ResponseBaseModel):
     """
     A single embedding result.
 
@@ -143,7 +143,7 @@ class EmbeddingResult(BaseModel):
     index: int
 
 
-class EmbeddingsResponse(BaseModel):
+class EmbeddingsResponse(ResponseBaseModel):
     """
     The response from the embedding model, following OpenAI specification.
 
@@ -159,7 +159,7 @@ class EmbeddingsResponse(BaseModel):
     usage: EmbeddingsUsage
 
 
-class EmbeddingsPostResponse(BaseModel):
+class EmbeddingsPostResponse(ResponseBaseModel):
     """
     Response for an embeddings POST request.
 

packages/gen/gen_ai_hub/orchestration_v2/models/message.py

@@ -10,11 +10,11 @@
 
 from pydantic import field_validator, ValidationError
 
-from gen_ai_hub.orchestration_v2.models.base import ABCBaseModel as BaseModel
+from gen_ai_hub.orchestration_v2.models.base import ABCBaseModel as BaseModel, ResponseBaseModel
 from gen_ai_hub.orchestration_v2.models.multimodal_items import ContentPart, ImageItem, TextPart, ImageUrl, ImagePart
 
 
-class FunctionCall(BaseModel):
+class FunctionCall(ResponseBaseModel):
     """
     Represents a function call with its name and arguments.
 
@@ -44,7 +44,7 @@ def parse_arguments(self) -> dict:
         return json.loads(self.arguments)
 
 
-class MessageToolCall(BaseModel):
+class MessageToolCall(ResponseBaseModel):
     """
     The tool calls generated by the model, such as function calls.
 
@@ -59,6 +59,17 @@ class MessageToolCall(BaseModel):
     type: typing.Literal["function"] = "function"
     function: FunctionCall
 
+class ReasoningBlock(ResponseBaseModel):
+    """
+    The reasoning content returned by the model.
+
+    Attributes:
+        content: The reasoning content.
+        signature: Signature string for hidden reasoning content.
+    """
+    content: str = ""
+    signature: str = ""
+
 
 class Role(str, Enum):
     """
@@ -157,6 +168,7 @@ class AssistantMessage(BaseModel):
     content: Optional[Union[str, List[TextPart]]] = None
     refusal: Optional[str] = None
     tool_calls: Optional[List[MessageToolCall]] = None
+    reasoning_content: Optional[List[ReasoningBlock]] = None
 
 
 class ToolChatMessage(BaseModel):
@@ -169,7 +181,7 @@ class DeveloperChatMessage(BaseModel):
     role: Role = Role.DEVELOPER
     content: Union[str, List[TextPart]]
 
-class ResponseChatMessage(BaseModel):
+class ResponseChatMessage(ResponseBaseModel):
     """
     Represents a response message in a conversation.
 
@@ -182,14 +194,17 @@ class ResponseChatMessage(BaseModel):
         refusal: A string indicating refusal reason.
 
         tool_calls: A list of tool call objects.
+
+        reasoning_content: A list of reasoning content blocks.
     """
     role: Role = Role.ASSISTANT
     content: str
     refusal: Optional[str] = None
     tool_calls: Optional[List[MessageToolCall]] = None
+    reasoning_content: Optional[List[ReasoningBlock]] = None
 
 ChatMessage = Union[SystemMessage, UserMessage, AssistantMessage, ToolChatMessage, DeveloperChatMessage,
 ResponseChatMessage]
 
 __all__ = ["Role", "SystemMessage", "UserMessage", "AssistantMessage", "ToolChatMessage", "DeveloperChatMessage",
-           "ChatMessage", "ResponseChatMessage", "FunctionCall", "MessageToolCall"]
+           "ChatMessage", "ResponseChatMessage", "FunctionCall", "MessageToolCall", "ReasoningBlock"]

packages/gen/gen_ai_hub/orchestration_v2/models/response.py

@@ -6,25 +6,8 @@
 from pydantic import ConfigDict, Field
 
 from gen_ai_hub.orchestration.models.response import ModuleResultsStreaming
-from gen_ai_hub.orchestration_v2.models.base import ABCBaseModel as BaseModel
-from gen_ai_hub.orchestration_v2.models.message import ChatMessage, FunctionCall, ResponseChatMessage
-
-
-class ResponseBaseModel(BaseModel):
-    """
-    Abstract base model that extends Pydantic's BaseModel and ABC.
-
-    - `extra="allow"` allows unexpected fields in responses to be accepted,
-      since the external API might introduce new attributes in the response.
-
-    This enforces consistent and safe serialization behavior across all
-    derived models.
-    """
-
-    model_config = ConfigDict(
-        extra="allow",
-        frozen=False,
-    )
+from gen_ai_hub.orchestration_v2.models.base import ResponseBaseModel
+from gen_ai_hub.orchestration_v2.models.message import ChatMessage, FunctionCall, ResponseChatMessage, ReasoningBlock
 
 
 class PromptTokensDetails(ResponseBaseModel):
@@ -186,6 +169,7 @@ class StreamDelta(ResponseBaseModel):
     role: Optional[str] = None
     content: str
     tool_calls: Optional[List[StreamToolCall]] = None
+    reasoning_content: Optional[List[ReasoningBlock]] = None
 
 
 class StreamLLMChoice(ResponseBaseModel):

packages/gen/tests/orchestration_v2/test_flat_import.py

@@ -36,7 +36,7 @@
 
     # message
     "SystemMessage", "UserMessage", "AssistantMessage", "ToolChatMessage", "DeveloperChatMessage",
-    "ChatMessage", "ResponseChatMessage", "FunctionCall", "MessageToolCall",
+    "ChatMessage", "ResponseChatMessage", "FunctionCall", "MessageToolCall", "ReasoningBlock",
 
     # multimodal_items
     "ImageDetailLevel", "TextPart", "ImageUrl", "ImagePart", "ContentPart", "ImageItem",

packages/gen/tests/orchestration_v2/test_message_v2.py

@@ -0,0 +1,42 @@
+import unittest
+
+from gen_ai_hub.orchestration_v2.models.message import (
+    AssistantMessage,
+    ReasoningBlock,
+    ResponseChatMessage,
+)
+
+
+class TestResponseChatMessageValidation(unittest.TestCase):
+
+    def test_reasoning_content_deserialized_from_dict(self):
+        msg = ResponseChatMessage.model_validate({
+            "role": "assistant",
+            "content": "Hello",
+            "reasoning_content": [{"content": "I think...", "signature": "sig123"}],
+        })
+        self.assertIsNotNone(msg.reasoning_content)
+        self.assertIsInstance(msg.reasoning_content[0], ReasoningBlock)
+
+    def test_reasoning_content_optional(self):
+        msg = ResponseChatMessage.model_validate({"role": "assistant", "content": "Hello"})
+        self.assertIsNone(msg.reasoning_content)
+
+
+class TestAssistantMessageValidation(unittest.TestCase):
+
+    def test_reasoning_content_deserialized_from_dict(self):
+        msg = AssistantMessage.model_validate({
+            "role": "assistant",
+            "content": "Paris",
+            "reasoning_content": [{"content": "France's capital is Paris.", "signature": "sig"}],
+        })
+        self.assertIsNotNone(msg.reasoning_content)
+        self.assertIsInstance(msg.reasoning_content[0], ReasoningBlock)
+        self.assertEqual(msg.reasoning_content[0].content, "France's capital is Paris.")
+        self.assertEqual(msg.reasoning_content[0].signature, "sig")
+
+    def test_reasoning_content_optional(self):
+        msg = AssistantMessage.model_validate({"role": "assistant", "content": "Hello"})
+        self.assertIsNone(msg.reasoning_content)
+

packages/gen/tests/orchestration_v2/test_response_v2.py

@@ -0,0 +1,21 @@
+import unittest
+
+from gen_ai_hub.orchestration_v2.models.message import ReasoningBlock
+from gen_ai_hub.orchestration_v2.models.response import StreamDelta
+
+
+class TestStreamDeltaValidation(unittest.TestCase):
+
+    def test_reasoning_content_deserialized_from_dict(self):
+        delta = StreamDelta.model_validate({
+            "content": "",
+            "reasoning_content": [{"content": "I should respond politely.", "signature": ""}],
+        })
+        self.assertIsNotNone(delta.reasoning_content)
+        self.assertIsInstance(delta.reasoning_content[0], ReasoningBlock)
+        self.assertEqual(delta.reasoning_content[0].content, "I should respond politely.")
+
+    def test_reasoning_content_optional(self):
+        delta = StreamDelta.model_validate({"content": "Hello"})
+        self.assertIsNone(delta.reasoning_content)
+