update tests

libs/partners/openai/langchain_openai/chat_models/base.py

@@ -703,17 +703,16 @@ def _stream(
                     )
                 is_first_chunk = False
                 yield generation_chunk
-        if hasattr(response, "get_final_completion"):
+        if hasattr(response, "get_final_completion") and "response_format" in payload:
             final_completion = response.get_final_completion()
-            if isinstance(final_completion, openai.BaseModel):
-                generation_chunk = self._get_generation_chunk_from_completion(
-                    final_completion
+            generation_chunk = self._get_generation_chunk_from_completion(
+                final_completion
+            )
+            if run_manager:
+                run_manager.on_llm_new_token(
+                    generation_chunk.text, chunk=generation_chunk
                 )
-                if run_manager:
-                    run_manager.on_llm_new_token(
-                        generation_chunk.text, chunk=generation_chunk
-                    )
-                yield generation_chunk
+            yield generation_chunk
 
     def _generate(
         self,
@@ -864,17 +863,16 @@ async def _astream(
                     )
                 is_first_chunk = False
                 yield generation_chunk
-        if hasattr(response, "get_final_completion"):
+        if hasattr(response, "get_final_completion") and "response_format" in payload:
             final_completion = await response.get_final_completion()
-            if isinstance(final_completion, openai.BaseModel):
-                generation_chunk = self._get_generation_chunk_from_completion(
-                    final_completion
+            generation_chunk = self._get_generation_chunk_from_completion(
+                final_completion
+            )
+            if run_manager:
+                await run_manager.on_llm_new_token(
+                    generation_chunk.text, chunk=generation_chunk
                 )
-                if run_manager:
-                    await run_manager.on_llm_new_token(
-                        generation_chunk.text, chunk=generation_chunk
-                    )
-                yield generation_chunk
+            yield generation_chunk
 
     async def _agenerate(
         self,

libs/partners/openai/tests/integration_tests/chat_models/test_base.py

@@ -1092,14 +1092,37 @@ class Foo(BaseModel):
 
 
 def test_stream_response_format() -> None:
-    list(ChatOpenAI(model="gpt-4o-mini").stream("how are ya", response_format=Foo))
+    full: Optional[BaseMessageChunk] = None
+    chunks = []
+    for chunk in ChatOpenAI(model="gpt-4o-mini").stream(
+        "how are ya", response_format=Foo
+    ):
+        chunks.append(chunk)
+        full = chunk if full is None else full + chunk
+    assert len(chunks) > 1
+    assert isinstance(full, AIMessageChunk)
+    parsed = full.additional_kwargs["parsed"]
+    assert isinstance(parsed, Foo)
+    assert isinstance(full.content, str)
+    parsed_content = json.loads(full.content)
+    assert parsed.response == parsed_content["response"]
 
 
 async def test_astream_response_format() -> None:
-    async for _ in ChatOpenAI(model="gpt-4o-mini").astream(
+    full: Optional[BaseMessageChunk] = None
+    chunks = []
+    async for chunk in ChatOpenAI(model="gpt-4o-mini").astream(
         "how are ya", response_format=Foo
     ):
-        pass
+        chunks.append(chunk)
+        full = chunk if full is None else full + chunk
+    assert len(chunks) > 1
+    assert isinstance(full, AIMessageChunk)
+    parsed = full.additional_kwargs["parsed"]
+    assert isinstance(parsed, Foo)
+    assert isinstance(full.content, str)
+    parsed_content = json.loads(full.content)
+    assert parsed.response == parsed_content["response"]
 
 
 @pytest.mark.parametrize("use_max_completion_tokens", [True, False])