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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() |