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 google.generativeai as genai
import time
from pathlib import Path
import tempfile
from dotenv import load_dotenv
load_dotenv()
import os

API_KEY = os.getenv("GOOGLE_API_KEY")
if API_KEY:
    genai.configure(api_key = API_KEY)

# Page Configuration
st.set_page_config(
    page_title="Multimodal AI Agent - Video Summarizer",
    page_icon="(1f4f9_videocamera) ",
    layout="wide"
)

st.title("Phidata Multimodal AI Summarizer Agent (1f4f9_videocamera) ")
st.header("Powered by Gemini 2.0 Flash Exp")

@st.cache_resource
def initialize_agent():
    return Agent(
        name = "Video AI Summarizer",
        model = Gemini(id="gemini-2.0-exp"),
        tools = [DuckDuckGo()],
        markdown = True
    )

# Initialize Agent 
multimodal_agent = initialize_agent()

# File uploader
video_file = st.file_uploader(
    "Upload a video file", type=['mp4', 'mov', 'avi'], help="Upload a video for AI Analysis"
)
if video_file:
    with tempfile.NamedTemporaryFile(delete=False, suffix='.mp4') as temp_video:
        temp_video.write(video_file.read())
        video_path = temp_video.name

    st.video(video_path, format="video/mp4", start_time=0)

    user_query = st.text_area(
        "What insights are you seeking from the video?",
        placeholder="Ask anything about the video content. The AI Agent will analyze and gather additional information",
        help="Provide specific question or insights you want from the video."
    )

    if st.button("Analyze video", key="analyze_video_button"):
        if not user_query:
            st.warning("Please enter a question or insight to analyze the video.")
        else:
            try:
                with st.spinner("Processing video and gathering insights..."):
                    #Upload and process video file
                    processed_video = upload_file(video_path)
                    while processed_video.state.name == "PROCESSING":
                        time.sleep(1)
                        processed_video = get_file(processed_video.name)

                    #prompt generation for analysis
                    analyses_prompt = (f"""
                    Analyze the uploaded video for content and context.
                    Respond the following query using the video insights and supplimentary web research
                    {user_query}

                    Provide a detailed, user-friendly and actionable response.
                        """
                    )

                    #AI agent processing 
                    response = multimodal_agent.run(analyses_prompt, video = [processed_video])

                #Display the result 
                st.subheader("Analysis result")
                st.markdown(response.content)
            
            except Exception as error:
                st.error(f"An error occured during analysis: {error}")
            finally:
                # Clean temporary file
                Path(video_path).unlink(missing_ok=True)
else:
    st.info("Upload a video file to begin analysis")

# Customize text are heihght

st.markdown(
    """
    <style>
    .stTextArea textarea {
        height: 100px;
    }    
    </style>
    """,
    unsafe_allow_html=True
)