openai[patch]: move test (#24552)

No-override tests (https://github.com/langchain-ai/langchain/pull/24407)
include a condition that integrations not implement additional tests.

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

@@ -1,7 +1,9 @@
 """Test ChatOpenAI chat model."""
 
+import base64
 from typing import Any, AsyncIterator, List, Optional, cast
 
+import httpx
 import pytest
 from langchain_core.callbacks import CallbackManager
 from langchain_core.messages import (
@@ -684,3 +686,67 @@ def test_openai_response_headers_invoke() -> None:
     assert headers
     assert isinstance(headers, dict)
     assert "content-type" in headers
+
+
+def test_image_token_counting_jpeg() -> None:
+    model = ChatOpenAI(model="gpt-4o", temperature=0)
+    image_url = "https://upload.wikimedia.org/wikipedia/commons/thumb/d/dd/Gfp-wisconsin-madison-the-nature-boardwalk.jpg/2560px-Gfp-wisconsin-madison-the-nature-boardwalk.jpg"
+    message = HumanMessage(
+        content=[
+            {"type": "text", "text": "describe the weather in this image"},
+            {"type": "image_url", "image_url": {"url": image_url}},
+        ]
+    )
+    expected = cast(AIMessage, model.invoke([message])).usage_metadata[  # type: ignore[index]
+        "input_tokens"
+    ]
+    actual = model.get_num_tokens_from_messages([message])
+    assert expected == actual
+
+    image_data = base64.b64encode(httpx.get(image_url).content).decode("utf-8")
+    message = HumanMessage(
+        content=[
+            {"type": "text", "text": "describe the weather in this image"},
+            {
+                "type": "image_url",
+                "image_url": {"url": f"data:image/jpeg;base64,{image_data}"},
+            },
+        ]
+    )
+    expected = cast(AIMessage, model.invoke([message])).usage_metadata[  # type: ignore[index]
+        "input_tokens"
+    ]
+    actual = model.get_num_tokens_from_messages([message])
+    assert expected == actual
+
+
+def test_image_token_counting_png() -> None:
+    model = ChatOpenAI(model="gpt-4o", temperature=0)
+    image_url = "https://upload.wikimedia.org/wikipedia/commons/4/47/PNG_transparency_demonstration_1.png"
+    message = HumanMessage(
+        content=[
+            {"type": "text", "text": "how many dice are in this image"},
+            {"type": "image_url", "image_url": {"url": image_url}},
+        ]
+    )
+    expected = cast(AIMessage, model.invoke([message])).usage_metadata[  # type: ignore[index]
+        "input_tokens"
+    ]
+    actual = model.get_num_tokens_from_messages([message])
+    assert expected == actual
+
+    image_data = base64.b64encode(httpx.get(image_url).content).decode("utf-8")
+    message = HumanMessage(
+        content=[
+            {"type": "text", "text": "how many dice are in this image"},
+            {
+                "type": "image_url",
+                "image_url": {"url": f"data:image/png;base64,{image_data}"},
+            },
+        ]
+    )
+    expected = cast(AIMessage, model.invoke([message])).usage_metadata[  # type: ignore[index]
+        "input_tokens"
+    ]
+    actual = model.get_num_tokens_from_messages([message])
+    assert expected == actual

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

@@ -1,11 +1,8 @@
 """Standard LangChain interface tests"""
 
-import base64
-from typing import Type, cast
+from typing import Type
 
-import httpx
 from langchain_core.language_models import BaseChatModel
-from langchain_core.messages import AIMessage, HumanMessage
 from langchain_standard_tests.integration_tests import ChatModelIntegrationTests
 
 from langchain_openai import ChatOpenAI
@@ -23,64 +20,3 @@ class TestOpenAIStandard(ChatModelIntegrationTests):
     @property
     def supports_image_inputs(self) -> bool:
         return True
-
-    # TODO: Add to standard tests if reliable token counting is added to other models.
-    def test_image_token_counting_jpeg(self, model: BaseChatModel) -> None:
-        image_url = "https://upload.wikimedia.org/wikipedia/commons/thumb/d/dd/Gfp-wisconsin-madison-the-nature-boardwalk.jpg/2560px-Gfp-wisconsin-madison-the-nature-boardwalk.jpg"
-        message = HumanMessage(
-            content=[
-                {"type": "text", "text": "describe the weather in this image"},
-                {"type": "image_url", "image_url": {"url": image_url}},
-            ]
-        )
-        expected = cast(AIMessage, model.invoke([message])).usage_metadata[  # type: ignore[index]
-            "input_tokens"
-        ]
-        actual = model.get_num_tokens_from_messages([message])
-        assert expected == actual
-
-        image_data = base64.b64encode(httpx.get(image_url).content).decode("utf-8")
-        message = HumanMessage(
-            content=[
-                {"type": "text", "text": "describe the weather in this image"},
-                {
-                    "type": "image_url",
-                    "image_url": {"url": f"data:image/jpeg;base64,{image_data}"},
-                },
-            ]
-        )
-        expected = cast(AIMessage, model.invoke([message])).usage_metadata[  # type: ignore[index]
-            "input_tokens"
-        ]
-        actual = model.get_num_tokens_from_messages([message])
-        assert expected == actual
-
-    def test_image_token_counting_png(self, model: BaseChatModel) -> None:
-        image_url = "https://upload.wikimedia.org/wikipedia/commons/4/47/PNG_transparency_demonstration_1.png"
-        message = HumanMessage(
-            content=[
-                {"type": "text", "text": "how many dice are in this image"},
-                {"type": "image_url", "image_url": {"url": image_url}},
-            ]
-        )
-        expected = cast(AIMessage, model.invoke([message])).usage_metadata[  # type: ignore[index]
-            "input_tokens"
-        ]
-        actual = model.get_num_tokens_from_messages([message])
-        assert expected == actual
-
-        image_data = base64.b64encode(httpx.get(image_url).content).decode("utf-8")
-        message = HumanMessage(
-            content=[
-                {"type": "text", "text": "how many dice are in this image"},
-                {
-                    "type": "image_url",
-                    "image_url": {"url": f"data:image/png;base64,{image_data}"},
-                },
-            ]
-        )
-        expected = cast(AIMessage, model.invoke([message])).usage_metadata[  # type: ignore[index]
-            "input_tokens"
-        ]
-        actual = model.get_num_tokens_from_messages([message])
-        assert expected == actual