diff --git a/cognee/tests/docs/guides/search_basics.py b/cognee/tests/docs/guides/search_basics.py
index 67d0c938d..09dee3f92 100644
--- a/cognee/tests/docs/guides/search_basics.py
+++ b/cognee/tests/docs/guides/search_basics.py
@@ -1,17 +1,57 @@
 import asyncio
 import cognee
 
+from cognee.modules.search.types import SearchType, CombinedSearchResult
+
 
 async def main():
     await cognee.prune.prune_data()
     await cognee.prune.prune_system(metadata=True)
 
-    text = "First rule of coding: Do not talk about coding."
+    text = """
+        Natural language processing (NLP) is an interdisciplinary
+        subfield of computer science and information retrieval.
+        First rule of coding: Do not talk about coding.
+        """
+
+    text2 = """
+    Sandwiches are best served toasted with cheese, ham, mayo,
+    lettuce, mustard, and salt & pepper.
+    """
+
+    await cognee.add(text, dataset_name="NLP_coding")
+    await cognee.add(text2, dataset_name="Sandwiches")
+    await cognee.add(text2)
+
+    await cognee.cognify()
 
     # Make sure you've already run cognee.cognify(...) so the graph has content
     answers = await cognee.search(query_text="What are the main themes in my data?")
-    for answer in answers:
-        print(answer)
+    assert len(answers) > 0
 
+    answers = await cognee.search(
+        query_text="List coding guidelines",
+        query_type=SearchType.CODING_RULES,
+    )
+    assert len(answers) > 0
+
+    answers = await cognee.search(
+        query_text="Give me a confident answer: What is NLP?",
+        system_prompt="Answer succinctly and state confidence at the end.",
+    )
+    assert len(answers) > 0
+
+    answers = await cognee.search(
+        query_text="Tell me about NLP",
+        only_context=True,
+    )
+    assert len(answers) > 0
+
+    answers = await cognee.search(
+        query_text="Quarterly financial highlights",
+        datasets=["NLP_coding", "Sandwiches"],
+        use_combined_context=True,
+    )
+    assert isinstance(answers, CombinedSearchResult)
 
 asyncio.run(main())