diff --git a/graphiti_core/llm_client/openai_client.py b/graphiti_core/llm_client/openai_client.py
index c92b4fb3..d8b02e8b 100644
--- a/graphiti_core/llm_client/openai_client.py
+++ b/graphiti_core/llm_client/openai_client.py
@@ -16,6 +16,7 @@
 
 import logging
 import typing
+from typing import ClassVar
 
 import openai
 from openai import AsyncOpenAI
@@ -53,6 +54,9 @@ class OpenAIClient(LLMClient):
             Generates a response from the language model based on the provided messages.
     """
 
+    # Class-level constants
+    MAX_RETRIES: ClassVar[int] = 2
+
     def __init__(
         self, config: LLMConfig | None = None, cache: bool = False, client: typing.Any = None
     ):
@@ -104,7 +108,7 @@ async def _generate_response(
             elif response_object.refusal:
                 raise RefusalError(response_object.refusal)
             else:
-                raise Exception('No response from LLM')
+                raise Exception(f'Invalid response from LLM: {response_object.model_dump()}')
         except openai.LengthFinishReasonError as e:
             raise Exception(f'Output length exceeded max tokens {self.max_tokens}: {e}') from e
         except openai.RateLimitError as e:
@@ -116,6 +120,43 @@ async def _generate_response(
     async def generate_response(
         self, messages: list[Message], response_model: type[BaseModel] | None = None
     ) -> dict[str, typing.Any]:
-        response = await self._generate_response(messages, response_model)
-
-        return response
+        retry_count = 0
+        last_error = None
+
+        while retry_count <= self.MAX_RETRIES:
+            try:
+                response = await self._generate_response(messages, response_model)
+                return response
+            except (RateLimitError, RefusalError):
+                # These errors should not trigger retries
+                raise
+            except (openai.APITimeoutError, openai.APIConnectionError, openai.InternalServerError):
+                # Let OpenAI's client handle these retries
+                raise
+            except Exception as e:
+                last_error = e
+
+                # Don't retry if we've hit the max retries
+                if retry_count >= self.MAX_RETRIES:
+                    logger.error(f'Max retries ({self.MAX_RETRIES}) exceeded. Last error: {e}')
+                    raise
+
+                retry_count += 1
+
+                # Construct a detailed error message for the LLM
+                error_context = (
+                    f'The previous response attempt was invalid. '
+                    f'Error type: {e.__class__.__name__}. '
+                    f'Error details: {str(e)}. '
+                    f'Please try again with a valid response, ensuring the output matches '
+                    f'the expected format and constraints.'
+                )
+
+                error_message = Message(role='user', content=error_context)
+                messages.append(error_message)
+                logger.warning(
+                    f'Retrying after application error (attempt {retry_count}/{self.MAX_RETRIES}): {e}'
+                )
+
+        # If we somehow get here, raise the last error
+        raise last_error or Exception('Max retries exceeded with no specific error')