diff --git a/graphiti_core/llm_client/client.py b/graphiti_core/llm_client/client.py
index 22cc3795..f2a19208 100644
--- a/graphiti_core/llm_client/client.py
+++ b/graphiti_core/llm_client/client.py
@@ -67,6 +67,28 @@ def __init__(self, config: LLMConfig | None, cache: bool = False):
         else None,
         reraise=True,
     )
+    def _clean_input(self, input: str) -> str:
+        """Clean input string of invalid unicode and control characters.
+
+        Args:
+            input: Raw input string to be cleaned
+
+        Returns:
+            Cleaned string safe for LLM processing
+        """
+        # Clean any invalid Unicode
+        cleaned = input.encode('utf-8', errors='ignore').decode('utf-8')
+
+        # Remove zero-width characters and other invisible unicode
+        zero_width = '\u200b\u200c\u200d\ufeff\u2060'
+        for char in zero_width:
+            cleaned = cleaned.replace(char, '')
+
+        # Remove control characters except newlines, returns, and tabs
+        cleaned = ''.join(char for char in cleaned if ord(char) >= 32 or char in '\n\r\t')
+
+        return cleaned
+
     async def _generate_response_with_retry(
         self, messages: list[Message], response_model: type[BaseModel] | None = None
     ) -> dict[str, typing.Any]:
@@ -106,6 +128,9 @@ async def generate_response(
                 logger.debug(f'Cache hit for {cache_key}')
                 return cached_response
 
+        for message in messages:
+            message.content = self._clean_input(message.content)
+
         response = await self._generate_response_with_retry(messages, response_model)
 
         if self.cache_enabled:
diff --git a/graphiti_core/llm_client/openai_client.py b/graphiti_core/llm_client/openai_client.py
index d8b02e8b..7804e06f 100644
--- a/graphiti_core/llm_client/openai_client.py
+++ b/graphiti_core/llm_client/openai_client.py
@@ -88,6 +88,7 @@ async def _generate_response(
     ) -> dict[str, typing.Any]:
         openai_messages: list[ChatCompletionMessageParam] = []
         for m in messages:
+            m.content = self._clean_input(m.content)
             if m.role == 'user':
                 openai_messages.append({'role': 'user', 'content': m.content})
             elif m.role == 'system':
diff --git a/tests/llm_client/test_client.py b/tests/llm_client/test_client.py
new file mode 100644
index 00000000..4a2fbd7c
--- /dev/null
+++ b/tests/llm_client/test_client.py
@@ -0,0 +1,41 @@
+from graphiti_core.llm_client.client import LLMClient
+from graphiti_core.llm_client.config import LLMConfig
+
+
+class TestLLMClient(LLMClient):
+    """Concrete implementation of LLMClient for testing"""
+
+    async def _generate_response(self, messages, response_model=None):
+        return {'content': 'test'}
+
+
+def test_clean_input():
+    client = TestLLMClient(LLMConfig())
+
+    test_cases = [
+        # Basic text should remain unchanged
+        ('Hello World', 'Hello World'),
+        # Control characters should be removed
+        ('Hello\x00World', 'HelloWorld'),
+        # Newlines, tabs, returns should be preserved
+        ('Hello\nWorld\tTest\r', 'Hello\nWorld\tTest\r'),
+        # Invalid Unicode should be removed
+        ('Hello\udcdeWorld', 'HelloWorld'),
+        # Zero-width characters should be removed
+        ('Hello\u200bWorld', 'HelloWorld'),
+        ('Test\ufeffWord', 'TestWord'),
+        # Multiple issues combined
+        ('Hello\x00\u200b\nWorld\udcde', 'Hello\nWorld'),
+        # Empty string should remain empty
+        ('', ''),
+        # Form feed and other control characters from the error case
+        ('{"edges":[{"relation_typ...\f\x04Hn\\?"}]}', '{"edges":[{"relation_typ...Hn\\?"}]}'),
+        # More specific control character tests
+        ('Hello\x0cWorld', 'HelloWorld'),  # form feed \f
+        ('Hello\x04World', 'HelloWorld'),  # end of transmission
+        # Combined JSON-like string with control characters
+        ('{"test": "value\f\x00\x04"}', '{"test": "value"}'),
+    ]
+
+    for input_str, expected in test_cases:
+        assert client._clean_input(input_str) == expected, f'Failed for input: {repr(input_str)}'