diff --git a/rag_tutorials/rag_database_routing/README.md b/rag_tutorials/rag_database_routing/README.md
index 5a325a5..1d0dbf9 100644
--- a/rag_tutorials/rag_database_routing/README.md
+++ b/rag_tutorials/rag_database_routing/README.md
@@ -6,7 +6,7 @@ A Streamlit application that demonstrates an advanced implementation of RAG Agen
 
 - **Document Upload**: Users can upload multiple PDF documents related to a particular company. These documents are processed and stored in one of the three databases: Product Information, Customer Support & FAQ, or Financial Information.
   
-- **Natural Language Querying**: Users can ask questions in natural language. The system automatically routes the query to the most relevant database using a phidata agent as the router.
+- **Natural Language Querying**: Users can ask questions in natural language. The system automatically routes the query to the most relevant database using a agno agent as the router.
 
 - **RAG Orchestration**: Utilizes Langchain for orchestrating the retrieval augmented generation process, ensuring that the most relevant information is retrieved and presented to the user.
 
@@ -47,7 +47,7 @@ A Streamlit application that demonstrates an advanced implementation of RAG Agen
 ## Technologies Used
 
 - **Langchain**: For RAG orchestration, ensuring efficient retrieval and generation of information.
-- **Phidata Agent**: Used as the router agent to determine the most relevant database for a given query.
+- **Agno Agent**: Used as the router agent to determine the most relevant database for a given query.
 - **LangGraph Agent**: Acts as a fallback mechanism, utilizing DuckDuckGo for web research when necessary.
 - **Streamlit**: Provides a user-friendly interface for document upload and querying.
 - **Qdrant**: Used for managing the databases, storing and retrieving document embeddings efficiently.
diff --git a/rag_tutorials/rag_database_routing/rag_database_routing.py b/rag_tutorials/rag_database_routing/rag_database_routing.py
index 7e83a68..d027fda 100644
--- a/rag_tutorials/rag_database_routing/rag_database_routing.py
+++ b/rag_tutorials/rag_database_routing/rag_database_routing.py
@@ -134,7 +134,7 @@ def process_document(file) -> List[Document]:
         return []
 
 def create_routing_agent() -> Agent:
-    """Creates a routing agent using phidata framework"""
+    """Creates a routing agent using agno framework"""
     return Agent(
         model=OpenAIChat(
             id="gpt-4o",
diff --git a/rag_tutorials/rag_database_routing/requirements.txt b/rag_tutorials/rag_database_routing/requirements.txt
index 0c69e77..083344f 100644
--- a/rag_tutorials/rag_database_routing/requirements.txt
+++ b/rag_tutorials/rag_database_routing/requirements.txt
@@ -5,7 +5,7 @@ qdrant-client==1.12.1
 streamlit>=1.29.0
 pypdf>=4.0.0
 sentence-transformers>=2.2.2
-phidata==2.7.3
+agno
 langchain-openai==0.2.14
 langgraph==0.2.53
 duckduckgo-search==6.4.1
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