fix langchain core

weave/integrations/langchain/langchain_nv_ai_endpoints.py

@@ -2,10 +2,15 @@
 import time
 from collections.abc import Iterator
 from functools import wraps
-from typing import TYPE_CHECKING, Any, Callable, Optional
+from typing import Any, Callable, Optional
 
-if TYPE_CHECKING:
-    pass
+import_failed = False
+
+try:
+    from langchain_core.messages import AIMessageChunk, convert_to_openai_messages
+    from langchain_core.outputs import ChatGenerationChunk, ChatResult
+except ImportError:
+    import_failed = True
 
 import weave
 from weave.trace.op import Op, ProcessedInputs
@@ -15,9 +20,6 @@
 
 # NVIDIA-specific accumulator for parsing the objects of streaming interactions
 def nvidia_accumulator(acc: Optional[Any], value: Any) -> Any:
-    from langchain_core.messages import AIMessageChunk
-    from langchain_core.outputs import ChatGenerationChunk
-
     if acc is None:
         acc = ChatGenerationChunk(message=AIMessageChunk(content=""))
     acc = acc + value
@@ -31,8 +33,6 @@ def nvidia_accumulator(acc: Optional[Any], value: Any) -> Any:
 
 # Post processor to transform output into OpenAI's ChatCompletion format -- need to handle stream and non-stream outputs
 def post_process_to_openai_format(output: Any) -> dict:
-    from langchain_core.messages import convert_to_openai_messages
-    from langchain_core.outputs import ChatGenerationChunk, ChatResult
     from openai.types.chat import ChatCompletion
 
     if isinstance(output, ChatResult):  ## its ChatResult
@@ -114,8 +114,6 @@ def post_process_to_openai_format(output: Any) -> dict:
 def process_inputs_to_openai_format_stream(
     func: Op, args: tuple, kwargs: dict
 ) -> ProcessedInputs:
-    from langchain_core.messages import convert_to_openai_messages
-
     original_args = args
     original_kwargs = kwargs
 
@@ -147,8 +145,6 @@ def process_inputs_to_openai_format_stream(
 def process_inputs_to_openai_format(
     func: Op, args: tuple, kwargs: dict
 ) -> ProcessedInputs:
-    from langchain_core.messages import convert_to_openai_messages
-
     original_args = args
     original_kwargs = kwargs
 
@@ -202,7 +198,6 @@ def invoke_fn(*args: Any, **kwargs: Any) -> Any:
 # Wrap streaming methods (synchronous)
 def create_stream_wrapper(name: str) -> Callable[[Callable], Callable]:
     """Wrap a synchronous streaming method for ChatNVIDIA."""
-    from langchain_core.outputs import ChatGenerationChunk
 
     def wrapper(fn: Callable) -> Callable:
         @wraps(fn)