diff --git a/src/khoj/processor/conversation/openai/utils.py b/src/khoj/processor/conversation/openai/utils.py
index f910b50cb..b601cbbd9 100644
--- a/src/khoj/processor/conversation/openai/utils.py
+++ b/src/khoj/processor/conversation/openai/utils.py
@@ -100,34 +100,37 @@ def chat_completion_with_backoff(
 
 
 def llm_thread(g, messages, model_name, temperature, openai_api_key=None, api_base_url=None, model_kwargs=None):
-    client_key = f"{openai_api_key}--{api_base_url}"
-    if client_key not in openai_clients:
-        client: openai.OpenAI = openai.OpenAI(
-            api_key=openai_api_key,
-            base_url=api_base_url,
+    try:
+        client_key = f"{openai_api_key}--{api_base_url}"
+        if client_key not in openai_clients:
+            client: openai.OpenAI = openai.OpenAI(
+                api_key=openai_api_key,
+                base_url=api_base_url,
+            )
+            openai_clients[client_key] = client
+        else:
+            client: openai.OpenAI = openai_clients[client_key]
+
+        formatted_messages = [{"role": message.role, "content": message.content} for message in messages]
+
+        chat = client.chat.completions.create(
+            stream=True,
+            messages=formatted_messages,
+            model=model_name,  # type: ignore
+            temperature=temperature,
+            timeout=20,
+            **(model_kwargs or dict()),
         )
-        openai_clients[client_key] = client
-    else:
-        client: openai.OpenAI = openai_clients[client_key]
-
-    formatted_messages = [{"role": message.role, "content": message.content} for message in messages]
-
-    chat = client.chat.completions.create(
-        stream=True,
-        messages=formatted_messages,
-        model=model_name,  # type: ignore
-        temperature=temperature,
-        timeout=20,
-        **(model_kwargs or dict()),
-    )
-
-    for chunk in chat:
-        if len(chunk.choices) == 0:
-            continue
-        delta_chunk = chunk.choices[0].delta
-        if isinstance(delta_chunk, str):
-            g.send(delta_chunk)
-        elif delta_chunk.content:
-            g.send(delta_chunk.content)
 
-    g.close()
+        for chunk in chat:
+            if len(chunk.choices) == 0:
+                continue
+            delta_chunk = chunk.choices[0].delta
+            if isinstance(delta_chunk, str):
+                g.send(delta_chunk)
+            elif delta_chunk.content:
+                g.send(delta_chunk.content)
+    except Exception as e:
+        logger.error(f"Error in llm_thread: {e}")
+    finally:
+        g.close()