diff --git a/python/agents/RAG/rag/agent.py b/python/agents/RAG/rag/agent.py
index bbe8924f4..60d5a08ba 100755
--- a/python/agents/RAG/rag/agent.py
+++ b/python/agents/RAG/rag/agent.py
@@ -15,6 +15,7 @@
 import os
 import uuid
 
+import google.auth
 from dotenv import load_dotenv
 from google.adk.agents import Agent
 from google.adk.tools.retrieval.vertex_ai_rag_retrieval import (
@@ -28,32 +29,42 @@
 from .prompts import return_instructions_root
 
 load_dotenv()
+
+_, project_id = google.auth.default()
+os.environ.setdefault("GOOGLE_CLOUD_PROJECT", project_id)
+os.environ["GOOGLE_CLOUD_LOCATION"] = "global"
+os.environ.setdefault("GOOGLE_GENAI_USE_VERTEXAI", "True")
+
 _ = instrument_adk_with_arize()
 
+# Initialize tools list
+tools = []
 
-ask_vertex_retrieval = VertexAiRagRetrieval(
-    name="retrieve_rag_documentation",
-    description=(
-        "Use this tool to retrieve documentation and reference materials for the question from the RAG corpus,"
-    ),
-    rag_resources=[
-        rag.RagResource(
-            # please fill in your own rag corpus
-            # here is a sample rag corpus for testing purpose
-            # e.g. projects/123/locations/us-central1/ragCorpora/456
-            rag_corpus=os.environ.get("RAG_CORPUS")
-        )
-    ],
-    similarity_top_k=10,
-    vector_distance_threshold=0.6,
-)
+# Only add RAG retrieval tool if RAG_CORPUS is configured
+rag_corpus = os.environ.get("RAG_CORPUS")
+if rag_corpus:
+    ask_vertex_retrieval = VertexAiRagRetrieval(
+        name="retrieve_rag_documentation",
+        description=(
+            "Use this tool to retrieve documentation and reference materials for the question from the RAG corpus,"
+        ),
+        rag_resources=[
+            rag.RagResource(
+                # please fill in your own rag corpus
+                # here is a sample rag corpus for testing purpose
+                # e.g. projects/123/locations/us-central1/ragCorpora/456
+                rag_corpus=rag_corpus
+            )
+        ],
+        similarity_top_k=10,
+        vector_distance_threshold=0.6,
+    )
+    tools.append(ask_vertex_retrieval)
 
 with using_session(session_id=uuid.uuid4()):
     root_agent = Agent(
-        model="gemini-2.0-flash-001",
+        model="gemini-3-flash-preview",
         name="ask_rag_agent",
         instruction=return_instructions_root(),
-        tools=[
-            ask_vertex_retrieval,
-        ],
+        tools=tools,
     )