diff --git a/ai_agent_tutorials/multimodal_ai_agent/multimodal_reasoning_agent.py b/ai_agent_tutorials/multimodal_ai_agent/multimodal_reasoning_agent.py
new file mode 100644
index 0000000..cb12428
--- /dev/null
+++ b/ai_agent_tutorials/multimodal_ai_agent/multimodal_reasoning_agent.py
@@ -0,0 +1,62 @@
+import streamlit as st
+from phi.agent import Agent
+from phi.model.google import Gemini
+import tempfile
+import os
+
+def main():
+    # Set up the reasoning agent
+    agent = Agent(
+        model=Gemini(id="gemini-2.0-flash-thinking-exp-1219"), 
+        markdown=True
+    )
+
+    # Streamlit app title
+    st.title("Multimodal Reasoning AI Agent 🧠")
+
+    # Instruction
+    st.write(
+        "Upload an image and provide a reasoning-based task for the AI Agent. "
+        "The AI Agent will analyze the image and respond based on your input."
+    )
+
+    # File uploader for image
+    uploaded_file = st.file_uploader("Upload Image", type=["jpg", "jpeg", "png"])
+
+    if uploaded_file is not None:
+        try:
+            # Save uploaded file to temporary file
+            with tempfile.NamedTemporaryFile(delete=False, suffix='.jpg') as tmp_file:
+                tmp_file.write(uploaded_file.getvalue())
+                temp_path = tmp_file.name
+
+            # Display the uploaded image
+            st.image(uploaded_file, caption="Uploaded Image", use_container_width=True)
+
+            # Input for dynamic task
+            task_input = st.text_area(
+                "Enter your task/question for the AI Agent:"
+            )
+
+            # Button to process the image and task
+            if st.button("Analyze Image") and task_input:
+                with st.spinner("AI is thinking... 🤖"):
+                    try:
+                        # Call the agent with the dynamic task and image path
+                        response = agent.run(task_input, images=[temp_path])
+                        
+                        # Display the response from the model
+                        st.markdown("### AI Response:")
+                        st.markdown(response.content)
+                    except Exception as e:
+                        st.error(f"An error occurred during analysis: {str(e)}")
+                    finally:
+                        # Clean up temp file
+                        if os.path.exists(temp_path):
+                            os.unlink(temp_path)
+
+        except Exception as e:
+            st.error(f"An error occurred while processing the image: {str(e)}")
+
+if __name__ == "__main__":
+    main()
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