diff --git a/ddtrace/contrib/langchain/patch.py b/ddtrace/contrib/langchain/patch.py
index 5ed7e028722..e903b90d279 100644
--- a/ddtrace/contrib/langchain/patch.py
+++ b/ddtrace/contrib/langchain/patch.py
@@ -145,6 +145,30 @@ def _tag_openai_token_usage(
         _tag_openai_token_usage(span._parent, llm_output, propagated_cost=propagated_cost + total_cost, propagate=True)
 
 
+def _is_openai_llm_instance(instance):
+    """Safely check if a traced instance is an OpenAI LLM.
+    langchain_community does not automatically import submodules which may result in AttributeErrors.
+    """
+    try:
+        if langchain_openai:
+            return isinstance(instance, langchain_openai.OpenAI)
+        return isinstance(instance, BASE_LANGCHAIN_MODULE.llms.OpenAI)
+    except (AttributeError, ModuleNotFoundError, ImportError):
+        return False
+
+
+def _is_openai_chat_instance(instance):
+    """Safely check if a traced instance is an OpenAI Chat Model.
+    langchain_community does not automatically import submodules which may result in AttributeErrors.
+    """
+    try:
+        if langchain_openai:
+            return isinstance(instance, langchain_openai.ChatOpenAI)
+        return isinstance(instance, BASE_LANGCHAIN_MODULE.chat_models.ChatOpenAI)
+    except (AttributeError, ModuleNotFoundError, ImportError):
+        return False
+
+
 @with_traced_module
 def traced_llm_generate(langchain, pin, func, instance, args, kwargs):
     llm_provider = instance._llm_type
@@ -173,9 +197,7 @@ def traced_llm_generate(langchain, pin, func, instance, args, kwargs):
                 span.set_tag_str("langchain.request.%s.parameters.%s" % (llm_provider, param), str(val))
 
         completions = func(*args, **kwargs)
-        if isinstance(instance, BASE_LANGCHAIN_MODULE.llms.OpenAI) or (
-            langchain_openai and isinstance(instance, langchain_openai.OpenAI)
-        ):
+        if _is_openai_llm_instance(instance):
             _tag_openai_token_usage(span, completions.llm_output)
             integration.record_usage(span, completions.llm_output)
 
@@ -253,9 +275,7 @@ async def traced_llm_agenerate(langchain, pin, func, instance, args, kwargs):
                 span.set_tag_str("langchain.request.%s.parameters.%s" % (llm_provider, param), str(val))
 
         completions = await func(*args, **kwargs)
-        if isinstance(instance, BASE_LANGCHAIN_MODULE.llms.OpenAI) or (
-            langchain_openai and isinstance(instance, langchain_openai.OpenAI)
-        ):
+        if _is_openai_llm_instance(instance):
             _tag_openai_token_usage(span, completions.llm_output)
             integration.record_usage(span, completions.llm_output)
 
@@ -346,9 +366,7 @@ def traced_chat_model_generate(langchain, pin, func, instance, args, kwargs):
                 span.set_tag_str("langchain.request.%s.parameters.%s" % (llm_provider, param), str(val))
 
         chat_completions = func(*args, **kwargs)
-        if isinstance(instance, BASE_LANGCHAIN_MODULE.chat_models.ChatOpenAI) or (
-            langchain_openai and isinstance(instance, langchain_openai.ChatOpenAI)
-        ):
+        if _is_openai_chat_instance(instance):
             _tag_openai_token_usage(span, chat_completions.llm_output)
             integration.record_usage(span, chat_completions.llm_output)
 
@@ -453,9 +471,7 @@ async def traced_chat_model_agenerate(langchain, pin, func, instance, args, kwar
                 span.set_tag_str("langchain.request.%s.parameters.%s" % (llm_provider, param), str(val))
 
         chat_completions = await func(*args, **kwargs)
-        if isinstance(instance, BASE_LANGCHAIN_MODULE.chat_models.ChatOpenAI) or (
-            langchain_openai and isinstance(instance, langchain_openai.ChatOpenAI)
-        ):
+        if _is_openai_chat_instance(instance):
             _tag_openai_token_usage(span, chat_completions.llm_output)
             integration.record_usage(span, chat_completions.llm_output)
 
@@ -842,9 +858,7 @@ def patch():
     # ref: https://github.com/DataDog/dd-trace-py/issues/7123
     if SHOULD_PATCH_LANGCHAIN_COMMUNITY:
         from langchain.chains.base import Chain  # noqa:F401
-        from langchain_community import chat_models  # noqa:F401
         from langchain_community import embeddings  # noqa:F401
-        from langchain_community import llms  # noqa:F401
         from langchain_community import vectorstores  # noqa:F401
 
         wrap("langchain_core", "language_models.llms.BaseLLM.generate", traced_llm_generate(langchain))
diff --git a/releasenotes/notes/fix-langchain-openai-submodule-check-ea81685e31cb9720.yaml b/releasenotes/notes/fix-langchain-openai-submodule-check-ea81685e31cb9720.yaml
new file mode 100644
index 00000000000..361f1aef79a
--- /dev/null
+++ b/releasenotes/notes/fix-langchain-openai-submodule-check-ea81685e31cb9720.yaml
@@ -0,0 +1,5 @@
+---
+fixes:
+  - |
+    langchain: This fix adds error handling for checking if a traced LLM or chat model is an OpenAI instance, as the 
+    langchain_community package does not allow automatic submodule importing.