more relevant documents

README.md

@@ -38,7 +38,7 @@ python script.py seed
 And then you can do your search
 
 ```bash
-python script.py search --query "How does AI change industries?"
+python script.py search --query "What is NAF and how can it help?"
 ```
 
 ## Roadmap

script.py

@@ -21,10 +21,9 @@ def get_embedding(text, embedding_model):
 def seed_database(embedding_model):
     """Seed the ChromaDB with example documents."""
     documents = [
-        "Artificial Intelligence is transforming industries.",
-        "Machine learning helps computers learn from data.",
-        "Deep learning uses neural networks to process information.",
-        "RAG enhances language models with retrieved knowledge."
+        "NAF is a architectural framework.",
+        "C3 Taxonomi helps define capabilties.",
+        "Architectural framework help organizations define architecture in standardized way with diffrent view points.",
     ]
 
     for i, doc in enumerate(documents):