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import streamlit as st
from phi.agent import Agent
from phi.model.google import Gemini
from phi.tools.duckduckgo import DuckDuckGo
from google.generativeai import upload_file, get_file
import time
from pathlib import Path
import tempfile
st.set_page_config(
page_title="Multimodal AI Agent",
page_icon="🎥",
layout="wide"
)
st.title("Phidata Multimodal AI Agent 🎥🎤💬")
st.header("Powered by Gemini 2.0 Flash Exp")
@st.cache_resource
def initialize_agent():
return Agent(
name="Multimodal Analyst",
model=Gemini(id="gemini-2.0-flash-exp"),
tools=[DuckDuckGo()],
markdown=True,
)
agent = initialize_agent()
uploaded_file = st.file_uploader("Upload a video file", type=['mp4', 'mov', 'avi'])
if uploaded_file:
with tempfile.NamedTemporaryFile(delete=False, suffix='.mp4') as tmp_file:
tmp_file.write(uploaded_file.read())
upload_path = tmp_file.name
st.video(upload_path)
user_prompt = st.text_area(
"What are you looking for in this video?",
placeholder="Ask anything about the video - AI Agent will analyze everything and search the web if needed",
help="You can ask questions about the video content and get information from the web"
)
if st.button("Analyze"):
if not user_prompt:
st.warning("Please enter your question.")
else:
try:
with st.spinner("Analyzing video and searching the web..."):
video_file = upload_file(upload_path)
while video_file.state.name == "PROCESSING":
time.sleep(1)
video_file = get_file(video_file.name)
prompt = f"""
First analyze the video and then answer this question using both
the video analysis and web research, question: {user_prompt}
Provide a comprehensive response focusing on practical, actionable information.
"""
result = agent.run(prompt, videos=[video_file])
st.subheader("Result")
st.markdown(result.content)
except Exception as e:
st.error(f"An error occurred: {str(e)}")
finally:
Path(upload_path).unlink(missing_ok=True)
else:
st.info("Please upload a video to begin analysis.")
st.markdown("""
<style>
.stTextArea textarea {
height: 100px;
}
</style>
""", unsafe_allow_html=True) |