diff --git a/src/testing.ipynb b/src/testing.ipynb
index 6ab251b..7318679 100644
--- a/src/testing.ipynb
+++ b/src/testing.ipynb
@@ -313,7 +313,7 @@
     "        result = openai.Embedding.create(model=EMBEDDING_MODEL, input=text)\n",
     "        return result[\"data\"][0][\"embedding\"]\n",
     "    \n",
-    "    def get_top_k(self, query: str, k: int=5) -> List[Tuple[str, str, str]]:\n",
+    "    def get_top_k(self, query: str, k: int=10) -> List[Tuple[str, str, str]]:\n",
     "        # Receives a query (str) and returns the top k articles (List[Tuple[str, str, str]]) that are most similar to the query.\n",
     "        # Each tuple contains the title of an article, its URL, and text.\n",
     "        query_embedding = self.get_embedding(query)\n",
@@ -337,7 +337,22 @@
     "            \"model\": COMPLETIONS_MODEL,\n",
     "        }\n",
     "        answer = openai.Completion.create(prompt=prompt, **COMPLETIONS_API_PARAMS)[\"choices\"][0][\"text\"].strip(\" \\n\")\n",
-    "        return answer"
+    "        return answer\n",
+    "    \n",
+    "    def search_and_answer(self, question: str, k: int=10) -> str:\n",
+    "        # Receives a question (str) and returns an answer (str) to the question.\n",
+    "        top_k = self.get_top_k(question, k)\n",
+    "        answer = self.answer_question(question, top_k)\n",
+    "        return answer\n",
+    "    \n",
+    "    def summarize(self, article: str) -> str:\n",
+    "        COMPLETIONS_API_PARAMS = {\n",
+    "            \"temperature\": 0.0,\n",
+    "            \"max_tokens\": 300,\n",
+    "            \"model\": COMPLETIONS_MODEL,\n",
+    "        }\n",
+    "        response = openai.Completion.create(prompt=article, **COMPLETIONS_API_PARAMS)\n",
+    "        return response[\"choices\"][0][\"text\"].strip(\" \\n\")"
    ]
   },
   {