mirror of
https://github.com/Shubhamsaboo/awesome-llm-apps.git
synced 2026-04-30 23:31:31 -05:00
83 lines
2.7 KiB
Python
83 lines
2.7 KiB
Python
import streamlit as st
|
|
from agno.agent import Agent
|
|
from agno.models.google import Gemini
|
|
from agno.media import Video
|
|
import time
|
|
from pathlib import Path
|
|
import tempfile
|
|
|
|
st.set_page_config(
|
|
page_title="Multimodal AI Agent",
|
|
page_icon="🧬",
|
|
layout="wide"
|
|
)
|
|
|
|
st.title("Multimodal AI Agent 🧬")
|
|
|
|
# Get Gemini API key from user
|
|
gemini_api_key = st.text_input("Enter your Gemini API Key", type="password")
|
|
|
|
# Initialize single agent with both capabilities
|
|
@st.cache_resource
|
|
def initialize_agent(api_key):
|
|
return Agent(
|
|
name="Multimodal Analyst",
|
|
model=Gemini(id="gemini-2.0-flash", api_key=api_key),
|
|
markdown=True,
|
|
)
|
|
|
|
if gemini_api_key:
|
|
agent = initialize_agent(gemini_api_key)
|
|
|
|
# File uploader
|
|
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())
|
|
video_path = tmp_file.name
|
|
|
|
st.video(video_path)
|
|
|
|
user_prompt = st.text_area(
|
|
"What would you like to know?",
|
|
placeholder="Ask any question related to the video - the AI Agent will analyze it and search the web if needed",
|
|
help="You can ask questions about the video content and get relevant information from the web"
|
|
)
|
|
|
|
if st.button("Analyze & Research"):
|
|
if not user_prompt:
|
|
st.warning("Please enter your question.")
|
|
else:
|
|
try:
|
|
with st.spinner("Processing video and researching..."):
|
|
video = Video(filepath=video_path)
|
|
|
|
prompt = f"""
|
|
First analyze this video and then answer the following question using both
|
|
the video analysis and web research: {user_prompt}
|
|
|
|
Provide a comprehensive response focusing on practical, actionable information.
|
|
"""
|
|
|
|
result = agent.run(prompt, videos=[video])
|
|
|
|
st.subheader("Result")
|
|
st.markdown(result.content)
|
|
|
|
except Exception as e:
|
|
st.error(f"An error occurred: {str(e)}")
|
|
finally:
|
|
Path(video_path).unlink(missing_ok=True)
|
|
else:
|
|
st.info("Please upload a video to begin analysis.")
|
|
else:
|
|
st.warning("Please enter your Gemini API key to continue.")
|
|
|
|
st.markdown("""
|
|
<style>
|
|
.stTextArea textarea {
|
|
height: 100px;
|
|
}
|
|
</style>
|
|
""", unsafe_allow_html=True) |