Create app.py

app.py

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+import streamlit as st
+import tempfile
+import os
+import yt_dlp
+from moviepy.editor import VideoFileClip
+import 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
+        }
+        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
+
+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 = openai.Audio.transcribe("whisper-1", audio_file)
+        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 document in a concise manner, highlighting the key points that a student should know:\n\n{transcript_text}"
+    messages = [
+        {"role": "system", "content": "You are an educational assistant."},
+        {"role": "user", "content": prompt}
+    ]
+    completion = openai.ChatCompletion.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 following document:\n\n{transcript_text}\n\nQuestion: {user_query}"}
+    ]
+    completion = openai.ChatCompletion.create(model="gpt-4o-mini", messages=messages)
+    return completion.choices[0].message.content.strip()
+
+# ---------------------------
+# Sidebar: Input Options
+# ---------------------------
+st.sidebar.title("Video Input Options")
+
+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, max 50MB)", 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-based Study Companion")
+
+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)