main.py

import os

from gpt import *
from video import *
from utils import *
from search import *
from uuid import uuid4
from tiktokvoice import *
from flask_cors import CORS
from termcolor import colored
from dotenv import load_dotenv
from youtube import upload_video 
from apiclient.errors import HttpError   
from flask import Flask, request, jsonify
from moviepy.config import change_settings


# Load environment variables
load_dotenv("../.env")

# Set environment variables
SESSION_ID = os.getenv("TIKTOK_SESSION_ID")
openai_api_key = os.getenv('OPENAI_API_KEY')
change_settings({"IMAGEMAGICK_BINARY": os.getenv("IMAGEMAGICK_BINARY")})

# Initialize Flask
app = Flask(__name__)
CORS(app)

# Constants
HOST = "0.0.0.0"
PORT = 8080
AMOUNT_OF_STOCK_VIDEOS = 5
GENERATING = False


# Generation Endpoint
@app.route("/api/generate", methods=["POST"])
def generate():
    try:
        # Set global variable
        global GENERATING
        GENERATING = True

        # Clean
        clean_dir("../temp/")
        clean_dir("../subtitles/")

        
        # Parse JSON
        data = request.get_json()
        paragraph_number = int(data.get('paragraphNumber', 1))  # Default to 1 if not provided
        ai_model = data.get('aiModel')  # Get the AI model selected by the user

        # Get 'useMusic' from the request data and default to False if not provided
        use_music = data.get('useMusic', False)

        # Get 'automateYoutubeUpload' from the request data and default to False if not provided
        automate_youtube_upload = data.get('automateYoutubeUpload', False)

        # Get the ZIP Url of the songs
        songs_zip_url = data.get('zipUrl')
        
        # Download songs
        if use_music:
            # Downloads a ZIP file containing popular TikTok Songs
            if songs_zip_url:
                fetch_songs(songs_zip_url)
            else:
                # Default to a ZIP file containing popular TikTok Songs
                fetch_songs("https://filebin.net/2avx134kdibc4c3q/drive-download-20240209T180019Z-001.zip")

        # Print little information about the video which is to be generated
        print(colored("[Video to be generated]", "blue"))
        print(colored("   Subject: " + data["videoSubject"], "blue"))
        print(colored("   AI Model: " + ai_model, "blue"))  # Print the AI model being used


        if not GENERATING:
            return jsonify(
                {
                    "status": "error",
                    "message": "Video generation was cancelled.",
                    "data": [],
                }
            )
        
        voice = data["voice"]

        if not voice:
            print(colored("[!] No voice was selected. Defaulting to \"en_us_001\"", "yellow"))
            voice = "en_us_001"

        # Generate a script
        script = generate_script(data["videoSubject"], paragraph_number, ai_model, voice)  # Pass the AI model to the script generation

        # Generate search terms
        search_terms = get_search_terms(
            data["videoSubject"], AMOUNT_OF_STOCK_VIDEOS, script, ai_model
        )

        # Search for a video of the given search term
        video_urls = []

        # Defines how many results it should query and search through
        it = 15

        # Defines the minimum duration of each clip
        min_dur = 10

        # Loop through all search terms,
        # and search for a video of the given search term
        for search_term in search_terms:
            if not GENERATING:
                return jsonify(
                    {
                        "status": "error",
                        "message": "Video generation was cancelled.",
                        "data": [],
                    }
                )
            found_urls = search_for_stock_videos(
                search_term, os.getenv("PEXELS_API_KEY"), it, min_dur
            )
            # Check for duplicates
            for url in found_urls:
                if url not in video_urls:
                    video_urls.append(url)
                    break

        # Define video_paths
        video_paths = []

        # Let user know
        print(colored(f"[+] Downloading {len(video_urls)} videos...", "blue"))

        # Save the videos
        for video_url in video_urls:
            if not GENERATING:
                return jsonify(
                    {
                        "status": "error",
                        "message": "Video generation was cancelled.",
                        "data": [],
                    }
                )
            try:
                saved_video_path = save_video(video_url)
                video_paths.append(saved_video_path)
            except Exception:
                print(colored(f"[-] Could not download video: {video_url}", "red"))

        # Let user know
        print(colored("[+] Videos downloaded!", "green"))

        # Let user know
        print(colored("[+] Script generated!\n", "green"))

        if not GENERATING:
            return jsonify(
                {
                    "status": "error",
                    "message": "Video generation was cancelled.",
                    "data": [],
                }
            )

        # Split script into sentences
        sentences = script.split(". ")

        # Remove empty strings
        sentences = list(filter(lambda x: x != "", sentences))
        paths = []

        # Generate TTS for every sentence
        for sentence in sentences:
            if not GENERATING:
                return jsonify(
                    {
                        "status": "error",
                        "message": "Video generation was cancelled.",
                        "data": [],
                    }
                )
            current_tts_path = f"../temp/{uuid4()}.mp3"
            tts(sentence, voice, filename=current_tts_path)
            audio_clip = AudioFileClip(current_tts_path)
            paths.append(audio_clip)

        # Combine all TTS files using moviepy
        final_audio = concatenate_audioclips(paths)
        tts_path = f"../temp/{uuid4()}.mp3"
        final_audio.write_audiofile(tts_path)

        try:
            subtitles_path = generate_subtitles(audio_path=tts_path, sentences=sentences, audio_clips=paths)
        except Exception as e:
            print(colored(f"[-] Error generating subtitles: {e}", "red"))
            subtitles_path = None

        # Concatenate videos
        temp_audio = AudioFileClip(tts_path)
        print(video_paths)
        combined_video_path = combine_videos(video_paths, temp_audio.duration, 5)

        # Put everything together
        try:
            final_video_path = generate_video(combined_video_path, tts_path, subtitles_path)
        except Exception as e:
            print(colored(f"[-] Error generating final video: {e}", "red"))
            final_video_path = None
        
        if automate_youtube_upload:
            # Start Youtube Uploader
            # Check if the CLIENT_SECRETS_FILE exists
            client_secrets_file = os.path.abspath("./client_secret.json")
            SKIP_YT_UPLOAD = False
            if not os.path.exists(client_secrets_file):
                SKIP_YT_UPLOAD = True
                print(colored("[-] Client secrets file missing. YouTube upload will be skipped.", "yellow"))
                print(colored("[-] Please download the client_secret.json from Google Cloud Platform and store this inside the /Backend directory.", "red"))

            # Only proceed with YouTube upload if the toggle is True  and client_secret.json exists.
            if not SKIP_YT_UPLOAD:
                # Define metadata for the video
                title, description, keywords = generate_metadata(data["videoSubject"], script, ai_model)  

                print(colored("[-] Metadata for YouTube upload:", "blue"))
                print(colored("   Title: ", "blue"))
                print(colored(f"   {title}", "blue"))
                print(colored("   Description: ", "blue"))
                print(colored(f"   {description}", "blue"))
                print(colored("   Keywords: ", "blue"))
                print(colored(f"  {', '.join(keywords)}", "blue"))

                # Choose the appropriate category ID for your videos
                video_category_id = "28"  # Science & Technology
                privacyStatus = "private"  # "public", "private", "unlisted"
                video_metadata = {
                    'video_path': os.path.abspath(f"../temp/{final_video_path}"),
                    'title': title,
                    'description': description,
                    'category': video_category_id,
                    'keywords': ",".join(keywords),
                    'privacyStatus': privacyStatus,
                }

                # Upload the video to YouTube
                try:
                    # Unpack the video_metadata dictionary into individual arguments
                    video_response = upload_video(
                        video_path=video_metadata['video_path'],
                        title=video_metadata['title'],
                        description=video_metadata['description'],
                        category=video_metadata['category'],
                        keywords=video_metadata['keywords'],
                        privacy_status=video_metadata['privacyStatus']
                    )
                    print(f"Uploaded video ID: {video_response.get('id')}")
                except HttpError as e:
                    print(f"An HTTP error {e.resp.status} occurred:\n{e.content}")

        if use_music:
            # Select a random song
            song_path = choose_random_song()

            # Add song to video at 30% volume using moviepy
            video_clip = VideoFileClip(f"../temp/{final_video_path}")
            original_duration = video_clip.duration
            original_audio = video_clip.audio
            song_clip = AudioFileClip(song_path).set_fps(44100)

            # Set the volume of the song to 10% of the original volume
            song_clip = song_clip.volumex(0.1).set_fps(44100)

            # Add the song to the video
            comp_audio = CompositeAudioClip([original_audio, song_clip])
            video_clip = video_clip.set_audio(comp_audio)
            video_clip = video_clip.set_fps(30)
            video_clip = video_clip.set_duration(original_duration)
            video_clip.write_videofile(f"../{final_video_path}", threads=2)


        # Let user know
        print(colored(f"[+] Video generated: {final_video_path}!", "green"))

        # Stop FFMPEG processes
        if os.name == "nt":
            # Windows
            os.system("taskkill /f /im ffmpeg.exe")
        else:
            # Other OS
            os.system("pkill -f ffmpeg")

        GENERATING = False

        # Return JSON
        return jsonify(
            {
                "status": "success",
                "message": "Video generated! See MoneyPrinter/output.mp4 for result.",
                "data": final_video_path,
            }
        )
    except Exception as err:
        print(colored(f"[-] Error: {str(err)}", "red"))
        return jsonify(
            {
                "status": "error",
                "message": f"Could not retrieve stock videos: {str(err)}",
                "data": [],
            }
        )


@app.route("/api/cancel", methods=["POST"])
def cancel():
    print(colored("[!] Received cancellation request...", "yellow"))

    global GENERATING
    GENERATING = False

    return jsonify({"status": "success", "message": "Cancelled video generation."})


if __name__ == "__main__":

    # Run Flask App
    app.run(debug=True, host=HOST, port=PORT)