diff --git a/docs/extras/modules/model_io/models/llms/custom_llm.ipynb b/docs/extras/modules/model_io/models/llms/custom_llm.ipynb
index 2e7e907523..3ff99dc80d 100644
--- a/docs/extras/modules/model_io/models/llms/custom_llm.ipynb
+++ b/docs/extras/modules/model_io/models/llms/custom_llm.ipynb
@@ -52,6 +52,7 @@
     "        prompt: str,\n",
     "        stop: Optional[List[str]] = None,\n",
     "        run_manager: Optional[CallbackManagerForLLMRun] = None,\n",
+    "        **kwargs: Any,\n",
     "    ) -> str:\n",
     "        if stop is not None:\n",
     "            raise ValueError(\"stop kwargs are not permitted.\")\n",
diff --git a/docs/extras/use_cases/question_answering/question_answering.ipynb b/docs/extras/use_cases/question_answering/question_answering.ipynb
index fe61c0ad25..ccadf6debd 100644
--- a/docs/extras/use_cases/question_answering/question_answering.ipynb
+++ b/docs/extras/use_cases/question_answering/question_answering.ipynb
@@ -14,7 +14,7 @@
     "\n",
     "In this walkthrough we'll go over how to build a question-answering over documents application using LLMs. Two very related use cases which we cover elsewhere are:\n",
     "- [QA over structured data](/docs/use_cases/sql) (e.g., SQL)\n",
-    "- [QA over code](/docs/use_cases/code) (e.g., Python)\n",
+    "- [QA over code](/docs/use_cases/code_understanding) (e.g., Python)\n",
     "\n",
     "![intro.png](/img/qa_intro.png)\n",
     "\n",