fixes

python/langsmith/client.py

@@ -3903,7 +3903,7 @@ def read_example(
                 attachments[key.removeprefix("attachment.")] = {
                     "presigned_url": value["presigned_url"],
                     "reader": reader,
-                    "mime_type": value["mime_type"],
+                    "mime_type": value.get("mime_type"),
                 }
 
         return ls_schemas.Example(
@@ -3990,7 +3990,7 @@ def list_examples(
                     attachments[key.removeprefix("attachment.")] = {
                         "presigned_url": value["presigned_url"],
                         "reader": reader,
-                        "mime_type": value["mime_type"],
+                        "mime_type": value.get("mime_type"),
                     }
 
             yield ls_schemas.Example(

python/tests/integration_tests/test_client.py

@@ -1253,7 +1253,7 @@ def test_list_examples_attachments_keys(langchain_client: Client) -> None:
 
     langchain_client.delete_dataset(dataset_id=dataset.id)
 
-@pytest.mark.skip(reason="Need to land https://github.com/langchain-ai/langchainplus/pull/7415 first")
+
 def test_mime_type_is_propogated(langchain_client: Client) -> None:
     """Test that the mime type is propogated correctly."""
     dataset_name = "__test_mime_type_is_propogated" + uuid4().hex[:4]
@@ -1272,15 +1272,17 @@ def test_mime_type_is_propogated(langchain_client: Client) -> None:
         ],
     )
 
-    example = next(langchain_client.list_examples(dataset_id=dataset.id))
+    example = next(
+        langchain_client.list_examples(dataset_id=dataset.id, include_attachments=True)
+    )
     assert example.attachments["test_file"]["mime_type"] == "text/plain"
 
     example = langchain_client.read_example(example_id=example.id)
     assert example.attachments["test_file"]["mime_type"] == "text/plain"
 
     langchain_client.delete_dataset(dataset_id=dataset.id)
 
-@pytest.mark.skip(reason="Need to land https://github.com/langchain-ai/langchainplus/pull/7415 first")
+
 def test_evaluate_mime_type_is_propogated(langchain_client: Client) -> None:
     """Test that the mime type is propogated correctly when evaluating."""
     dataset_name = "__test_evaluate_mime_type_is_propogated" + uuid4().hex[:4]
@@ -1304,7 +1306,9 @@ def target(inputs: Dict[str, Any], attachments: Dict[str, Any]) -> Dict[str, Any
         assert attachments["test_file"]["mime_type"] == "text/plain"
         return {"answer": "hi there"}
 
-    def evaluator(outputs: dict, reference_outputs: dict, attachments: dict) -> Dict[str, Any]:
+    def evaluator(
+        outputs: dict, reference_outputs: dict, attachments: dict
+    ) -> Dict[str, Any]:
         # Verify we receive the attachment data
         assert attachments["test_file"]["mime_type"] == "text/plain"
         return {
@@ -1313,16 +1317,12 @@ def evaluator(outputs: dict, reference_outputs: dict, attachments: dict) -> Dict
             )
         }
 
-    langchain_client.evaluate(
-        target,
-        data=dataset_name,
-        evaluators=[evaluator]
-    )
+    langchain_client.evaluate(target, data=dataset_name, evaluators=[evaluator])
 
     langchain_client.delete_dataset(dataset_name=dataset_name)
 
-@pytest.mark.skip(reason="Need to land https://github.com/langchain-ai/langchainplus/pull/7415 first")
-async def test_evaluate_mime_type_is_propogated(langchain_client: Client) -> None:
+
+async def test_aevaluate_mime_type_is_propogated(langchain_client: Client) -> None:
     """Test that the mime type is propogated correctly when evaluating."""
     dataset_name = "__test_evaluate_mime_type_is_propogated" + uuid4().hex[:4]
     dataset = langchain_client.create_dataset(dataset_name=dataset_name)
@@ -1340,12 +1340,16 @@ async def test_evaluate_mime_type_is_propogated(langchain_client: Client) -> Non
         ],
     )
 
-    async def target(inputs: Dict[str, Any], attachments: Dict[str, Any]) -> Dict[str, Any]:
+    async def target(
+        inputs: Dict[str, Any], attachments: Dict[str, Any]
+    ) -> Dict[str, Any]:
         # Verify we receive the attachment data
         assert attachments["test_file"]["mime_type"] == "text/plain"
         return {"answer": "hi there"}
 
-    async def evaluator(outputs: dict, reference_outputs: dict, attachments: dict) -> Dict[str, Any]:
+    async def evaluator(
+        outputs: dict, reference_outputs: dict, attachments: dict
+    ) -> Dict[str, Any]:
         # Verify we receive the attachment data
         assert attachments["test_file"]["mime_type"] == "text/plain"
         return {
@@ -1354,14 +1358,11 @@ async def evaluator(outputs: dict, reference_outputs: dict, attachments: dict) -
             )
         }
 
-    await langchain_client.aevaluate(
-        target,
-        data=dataset_name,
-        evaluators=[evaluator]
-    )
+    await langchain_client.aevaluate(target, data=dataset_name, evaluators=[evaluator])
 
     langchain_client.delete_dataset(dataset_name=dataset_name)
 
+
 def test_evaluate_with_attachments_multiple_evaluators(
     langchain_client: Client,
 ) -> None: