app.py

import os
import gradio as gr
import tempfile
import shutil
import re
import traceback
from yt_dlp import YoutubeDL

# Optional: use OpenAI Whisper if available
try:
    import whisper
    WHISPER_AVAILABLE = True
except:
    WHISPER_AVAILABLE = False

# Download audio from YouTube
def download_audio(url, cookies_path=None):
    try:
        temp_dir = tempfile.mkdtemp()
        output_path = os.path.join(temp_dir, "audio")

        ydl_opts = {
            'format': 'bestaudio[ext=m4a]/bestaudio/best',
            'outtmpl': output_path + '.%(ext)s',
            'quiet': True,
            'noplaylist': True,
            'cookiefile': cookies_path if cookies_path else None,
            'user_agent': 'Mozilla/5.0',
            'referer': 'https://www.youtube.com/',
            'force_ipv4': True,
        }

        with YoutubeDL(ydl_opts) as ydl:
            ydl.download([url])

        for ext in [".m4a", ".webm", ".mp3"]:
            final_path = output_path + ext
            if os.path.exists(final_path):
                return final_path, "✅ Audio downloaded successfully"

        return None, "❌ Audio file not found"

    except Exception as e:
        traceback.print_exc()
        return None, f"❌ Download error: {str(e)}"

# Transcribe using Whisper
def transcribe_audio(path):
    if not WHISPER_AVAILABLE:
        return "❌ Whisper not available. Please install openai-whisper."
    try:
        model = whisper.load_model("tiny.en")
        result = model.transcribe(path)
        return result["text"]
    except Exception as e:
        traceback.print_exc()
        return f"❌ Transcription failed: {str(e)}"

# Extract stock insights
def extract_stock_info(text):
    try:
        companies = re.findall(r'\b[A-Z][a-z]+(?: [A-Z][a-z]+)*\b', text)
        symbols = re.findall(r'\b[A-Z]{2,5}\b', text)
        prices = re.findall(r'\$\d+(?:\.\d{1,2})?', text)
        actions = re.findall(r'\b(buy|sell|hold|target|bullish|bearish|stop loss|accumulate|short|take profit|entry|exit)\b', text, re.IGNORECASE)

        result = "=== STOCK RECOMMENDATION ANALYSIS ===\n\n"
        if companies:
            result += f"🏢 Companies Mentioned: {', '.join(set(companies[:10]))}\n"
        if symbols:
            result += f"🔠 Symbols: {', '.join(set(symbols[:10]))}\n"
        if prices:
            result += f"💲 Prices: {', '.join(set(prices[:10]))}\n"
        if actions:
            result += f"📊 Actions: {', '.join(set(actions[:10]))}\n"

        recommendations = []
        for line in text.split("."):
            if any(word in line.lower() for word in ['buy', 'sell', 'target', 'hold', 'accumulate', 'short', 'entry', 'exit']):
                recommendations.append(line.strip())

        if recommendations:
            result += "\n🎯 Potential Recommendations:\n"
            for r in recommendations[:5]:
                result += f"• {r}\n"

        if not any([companies, symbols, prices, actions]):
            result += "\n⚠️ No stock-related insights detected."

        return result

    except Exception as e:
        return f"❌ Stock info extraction failed: {str(e)}"

# Save cookies
def save_cookies(file):
    if file is None:
        return None

    temp_path = tempfile.mktemp(suffix=".txt")
    try:
        if hasattr(file, "read"):
            with open(temp_path, "wb") as f:
                f.write(file.read())
        else:
            shutil.copy(file, temp_path)
        return temp_path
    except Exception as e:
        print(f"❌ Failed to handle cookies.txt: {e}")
        return None


# ✅ Trim audio to shorter length (2 minutes) for CPU speed
import subprocess

def trim_audio(input_path, output_path, duration_sec=120):
    try:
        command = [
            "ffmpeg", "-y", "-i", input_path,
            "-t", str(duration_sec),  # duration in seconds
            "-c", "copy", output_path
        ]
        subprocess.run(command, stdout=subprocess.PIPE, stderr=subprocess.PIPE)
        return output_path
    except Exception as e:
        print("❌ Error trimming audio:", e)
        return input_path


# YouTube flow
def run_pipeline(url, cookies_file, show_transcript):
    try:
        if not WHISPER_AVAILABLE:
            return "❌ Whisper not installed", ""
        if not url:
            return "❌ YouTube URL required", ""

        cookie_path = save_cookies(cookies_file)
        audio_path, status = download_audio(url, cookie_path)
        if not audio_path:
            return status, ""

        # ⏱ Trim audio to 2 minutes before transcription
        trimmed_path = tempfile.mktemp(suffix=".mp3")
        trim_audio(audio_path, trimmed_path)

        transcript = transcribe_audio(trimmed_path)
        if transcript.startswith("❌"):
            return transcript, ""

        stock_info = extract_stock_info(transcript)
        if show_transcript:
            return "✅ Complete", f"📜 Transcript:\n\n{transcript}\n\n\n{stock_info}"
        else:
            return "✅ Complete", stock_info

    except Exception as e:
        tb = traceback.format_exc()
        print(tb)
        return f"❌ Unhandled Error:\n{tb}", ""


# Audio upload flow
def run_pipeline_audio(audio_file, show_transcript):
    try:
        if not WHISPER_AVAILABLE:
            return "❌ Whisper not installed", ""
        if audio_file is None:
            return "❌ No audio file uploaded", ""

        # Save uploaded file
        temp_audio_path = tempfile.mktemp(suffix=os.path.splitext(str(audio_file))[-1])
        if hasattr(audio_file, "read"):
            with open(temp_audio_path, "wb") as f:
                f.write(audio_file.read())
        else:
            shutil.copy(str(audio_file), temp_audio_path)

        # ⏱ Trim audio to 2 minutes
        trimmed_path = tempfile.mktemp(suffix=".mp3")
        trim_audio(temp_audio_path, trimmed_path)

        transcript = transcribe_audio(trimmed_path)
        if transcript.startswith("❌"):
            return transcript, ""

        stock_info = extract_stock_info(transcript)
        if show_transcript:
            return "✅ Complete", f"📜 Transcript:\n\n{transcript}\n\n\n{stock_info}"
        else:
            return "✅ Complete", stock_info

    except Exception as e:
        tb = traceback.format_exc()
        print(tb)
        return f"❌ Unhandled Error:\n{tb}", ""


# Gradio UI
with gr.Blocks(title="Stock Insights from YouTube or Audio") as demo:
    gr.Markdown("""
    # 📈 Extract Stock Recommendations from YouTube or Uploaded Audio
    Upload a YouTube video or audio file. We'll transcribe it using Whisper and extract stock insights.
    """)

    with gr.Tab("📺 From YouTube Video"):
        with gr.Row():
            url_input = gr.Textbox(label="🎥 YouTube URL")
            cookie_input = gr.File(label="cookies.txt (optional)", file_types=[".txt"])
        show_transcript_yt = gr.Checkbox(label="Show Transcript", value=False)
        yt_run_btn = gr.Button("🚀 Extract from YouTube")
        yt_status = gr.Textbox(label="Status")
        yt_result = gr.Textbox(label="Transcript & Stock Info", lines=15)
        yt_run_btn.click(fn=run_pipeline, inputs=[url_input, cookie_input, show_transcript_yt], outputs=[yt_status, yt_result])

    with gr.Tab("🎵 From Uploaded Audio"):
        audio_input = gr.File(label="Upload Audio File", file_types=[".mp3", ".wav", ".m4a", ".webm"])
        show_transcript_audio = gr.Checkbox(label="Show Transcript", value=False)
        audio_run_btn = gr.Button("🚀 Extract from Audio")
        audio_status = gr.Textbox(label="Status")
        audio_result = gr.Textbox(label="Transcript & Stock Info", lines=15)
        audio_run_btn.click(fn=run_pipeline_audio, inputs=[audio_input, show_transcript_audio], outputs=[audio_status, audio_result])

if __name__ == "__main__":
    demo.launch(debug=True)