app.py

import streamlit as st
import tempfile
import os
import yt_dlp
from moviepy.editor import VideoFileClip

from openai import OpenAI
client = OpenAI()



# Set your OpenAI API key (make sure it's set in Hugging Face Spaces secrets)
#openai.api_key = os.getenv("OPENAI_API_KEY")

# ---------------------------
# Helper Functions
# ---------------------------
def download_video(youtube_url: str, output_path: str) -> str:
    """Download a YouTube video using yt-dlp and save it to the given output path."""
    try:
        ydl_opts = {
            'format': 'best',
            'outtmpl': os.path.join(output_path, '%(title)s.%(ext)s'),
            'noplaylist': True,
            'quiet': True,
             'cookiesfrombrowser': ('chrome',),  # Extract cookies from Chrome
            'verbose': True  # Optional: for more detailed output
        }
        with yt_dlp.YoutubeDL(ydl_opts) as ydl:
            info = ydl.extract_info(youtube_url, download=True)
            title = info.get('title', 'video')
            video_path = os.path.join(output_path, f"{title}.mp4")
            return video_path
    except Exception as e:
        st.error(f"Error downloading video: {e}")
        return None

def extract_audio(video_path: str) -> str:
    """Extract audio from the video file and save as MP3."""
    try:
        # Sanitize filename if needed (e.g., replace problematic characters)
        safe_video_path = video_path.replace("|", "_").replace(":", "_")
        clip = VideoFileClip(safe_video_path)
        audio_path = safe_video_path.replace(".mp4", ".mp3")
        clip.audio.write_audiofile(audio_path, codec='mp3')
        clip.close()
        return audio_path
    except Exception as e:
        st.error(f"Error extracting audio: {e}")
        return None

# audio_file = open("/path/to/file/speech.mp3", "rb")
# transcription = client.audio.transcriptions.create(
#   model="whisper-1", 
#   file=audio_file, 
#   response_format="text"
# )

# print(transcription.text)

def transcribe_audio(audio_path: str) -> str:
    """Transcribe the audio to text using OpenAI's Whisper API."""
    try:
        with open(audio_path, "rb") as audio_file:
            transcript = client.audio.transcriptions.create(
                      model="whisper-1", 
                      file=audio_file 
                      #response_format="text"
                    )
        return transcript.text
    except Exception as e:
        st.error(f"Error transcribing audio: {e}")
        return ""



def generate_summary(transcript_text: str) -> str:
    """Generate a concise summary of the transcript using OpenAI."""
    prompt = f"Summarize the following video transcript in a concise manner, highlighting the key points that the user should know:\n\n{transcript_text}. Feel free to use bullet points, bold, italics and headers to empasize key points where necessary"
    messages = [
        {"role": "system", "content": "You are an helpful assistant."},
        {"role": "user", "content": prompt}
    ]
    completion = client.chat.completions.create(model="gpt-4o-mini", messages=messages)
    return completion.choices[0].message.content.strip()

def get_chat_response(transcript_text: str, conversation_history: list, user_query: str) -> str:
    """Generate a chat response using the transcript as context."""
    messages = conversation_history + [
        {"role": "user", "content": f"Based on the video transcript:\n\n{transcript_text}\n\nQuestion: {user_query}"}
    ]
    completion = client.chat.completions.create(model="gpt-4o-mini", messages=messages)
    return completion.choices[0].message.content.strip()

# ---------------------------
# Sidebar: Input Options
# ---------------------------
#st.sidebar.title("Video Input Options")
st.sidebar.title("Upload a video")

input_mode = st.sidebar.radio("Select Input Type", ("Upload Video")) #, "YouTube URL"))

transcript_text = ""
if input_mode == "Upload Video":
    uploaded_video = st.sidebar.file_uploader("Upload a video file (MP4)", type="mp4")
# elif input_mode == "YouTube URL":
#     youtube_url = st.sidebar.text_input("Enter YouTube video URL:")

# ---------------------------
# Process Video Input
# ---------------------------
if input_mode == "Upload Video" and uploaded_video is not None:
    with tempfile.NamedTemporaryFile(delete=False, suffix=".mp4") as tmp:
        tmp.write(uploaded_video.read())
        video_path = tmp.name
    st.sidebar.success("Video uploaded successfully!")
    audio_path = extract_audio(video_path)
    if audio_path:
        transcript_text = transcribe_audio(audio_path)
        if transcript_text:
            st.sidebar.success("Audio transcribed successfully!")
# elif input_mode == "YouTube URL" and youtube_url:
#     with tempfile.TemporaryDirectory() as temp_dir:
#         video_path = download_video(youtube_url, temp_dir)
#         if video_path:
#             st.sidebar.success("Video downloaded successfully!")
#             audio_path = extract_audio(video_path)
#             if audio_path:
#                 transcript_text = transcribe_audio(audio_path)
#                 if transcript_text:
#                     st.sidebar.success("Audio transcribed successfully!")

if transcript_text:
    st.session_state.transcript_text = transcript_text

# ---------------------------
# Sidebar: Action Selection
# ---------------------------
st.sidebar.title("Select Action")
action_mode = st.sidebar.radio("Choose Action", ("Summary", "Chat"))

# ---------------------------
# Session State Initialization for Chat
# ---------------------------
if "chat_history" not in st.session_state:
    st.session_state.chat_history = [{"role": "assistant", "content": "Hi, how can I help you with the video content?"}]

# ---------------------------
# Main Display Area
# ---------------------------
st.title("Video Chat")
st.write('Tired of watching long boring videos? Summarize your videos in seconds or just chat!')

if "transcript_text" not in st.session_state or not st.session_state.transcript_text:
    st.info("Please provide a video input from the sidebar to begin.")
else:
    transcript_text = st.session_state.transcript_text
    if action_mode == "Summary":
        #st.header("Summary & Key Points")
        with st.spinner("Generating summary..."):
            summary = generate_summary(transcript_text)
        st.write(summary)
    elif action_mode == "Chat":
        st.header("Chat with Your Study Companion")
        for msg in st.session_state.chat_history:
            st.chat_message(msg["role"]).write(msg["content"])
        user_query = st.chat_input("Ask a question about the video content:")
        if user_query:
            st.session_state.chat_history.append({"role": "user", "content": user_query})
            st.chat_message("user").write(user_query)
            with st.spinner("Processing your question..."):
                response = get_chat_response(transcript_text, st.session_state.chat_history, user_query)
            st.session_state.chat_history.append({"role": "assistant", "content": response})
            st.chat_message("assistant").write(response)