fix tests

Author: nimarb

langfuse/api/resources/prompts/types/chat_message_with_placeholders.py

@@ -0,0 +1,87 @@
+# This file was auto-generated by Fern from our API Definition.
+
+from __future__ import annotations
+
+import datetime as dt
+import typing
+
+from ....core.datetime_utils import serialize_datetime
+from ....core.pydantic_utilities import deep_union_pydantic_dicts, pydantic_v1
+
+
+class ChatMessageWithPlaceholders_Chatmessage(pydantic_v1.BaseModel):
+    role: str
+    content: str
+    type: typing.Literal["chatmessage"] = "chatmessage"
+
+    def json(self, **kwargs: typing.Any) -> str:
+        kwargs_with_defaults: typing.Any = {
+            "by_alias": True,
+            "exclude_unset": True,
+            **kwargs,
+        }
+        return super().json(**kwargs_with_defaults)
+
+    def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]:
+        kwargs_with_defaults_exclude_unset: typing.Any = {
+            "by_alias": True,
+            "exclude_unset": True,
+            **kwargs,
+        }
+        kwargs_with_defaults_exclude_none: typing.Any = {
+            "by_alias": True,
+            "exclude_none": True,
+            **kwargs,
+        }
+
+        return deep_union_pydantic_dicts(
+            super().dict(**kwargs_with_defaults_exclude_unset),
+            super().dict(**kwargs_with_defaults_exclude_none),
+        )
+
+    class Config:
+        frozen = True
+        smart_union = True
+        extra = pydantic_v1.Extra.allow
+        json_encoders = {dt.datetime: serialize_datetime}
+
+
+class ChatMessageWithPlaceholders_Placeholder(pydantic_v1.BaseModel):
+    name: str
+    type: typing.Literal["placeholder"] = "placeholder"
+
+    def json(self, **kwargs: typing.Any) -> str:
+        kwargs_with_defaults: typing.Any = {
+            "by_alias": True,
+            "exclude_unset": True,
+            **kwargs,
+        }
+        return super().json(**kwargs_with_defaults)
+
+    def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]:
+        kwargs_with_defaults_exclude_unset: typing.Any = {
+            "by_alias": True,
+            "exclude_unset": True,
+            **kwargs,
+        }
+        kwargs_with_defaults_exclude_none: typing.Any = {
+            "by_alias": True,
+            "exclude_none": True,
+            **kwargs,
+        }
+
+        return deep_union_pydantic_dicts(
+            super().dict(**kwargs_with_defaults_exclude_unset),
+            super().dict(**kwargs_with_defaults_exclude_none),
+        )
+
+    class Config:
+        frozen = True
+        smart_union = True
+        extra = pydantic_v1.Extra.allow
+        json_encoders = {dt.datetime: serialize_datetime}
+
+
+ChatMessageWithPlaceholders = typing.Union[
+    ChatMessageWithPlaceholders_Chatmessage, ChatMessageWithPlaceholders_Placeholder
+]

langfuse/model.py

@@ -313,15 +313,15 @@ def compileWithPlaceholders(
         return [
             ChatMessageDict(
                 content=TemplateParser.compile_template(
-                    chat_message["content"], variables,
+                    chat_message["content"],
+                    variables,
                 ),
                 role=chat_message["role"],
             )
             for chat_message in messages_with_placeholders_replaced
-            if hasattr(chat_message, "role") and hasattr(chat_message, "content")
+            if "role" in chat_message and "content" in chat_message
         ]
 
-
     def get_langchain_prompt(self, **kwargs):
         """Convert Langfuse prompt into string compatible with Langchain ChatPromptTemplate.