app.py

from kokoro import KPipeline

import soundfile as sf
import torch

import soundfile as sf
import os
from moviepy.editor import VideoFileClip, AudioFileClip, ImageClip, ColorClip # Added ColorClip
from PIL import Image
import tempfile
import random
import cv2
import math
import os, requests, io, time, re, random
from moviepy.editor import (
    VideoFileClip, concatenate_videoclips, AudioFileClip, ImageClip,
    CompositeVideoClip, TextClip, CompositeAudioClip
)
import moviepy.video.fx.all as vfx
import moviepy.config as mpy_config
from pydub import AudioSegment
from pydub.generators import Sine

from PIL import Image, ImageDraw, ImageFont
import numpy as np
from bs4 import BeautifulSoup
import base64
from urllib.parse import quote
# pysrt is imported but not used in the provided code snippets, keeping for completeness
# import pysrt
from gtts import gTTS
import gradio as gr  # Import Gradio
import shutil # Needed for temp folder cleanup

# Initialize Kokoro TTS pipeline (using American English)
# Ensure you have the required voice models downloaded for Kokoro if needed,
# or it will fall back to gTTS. 'a' for American English uses voice 'af_heart'.
try:
    pipeline = KPipeline(lang_code='a')
    print("Kokoro TTS pipeline initialized.")
except Exception as e:
    print(f"Warning: Could not initialize Kokoro TTS pipeline: {e}. Will rely on gTTS.")
    pipeline = None # Set pipeline to None if initialization fails


# Ensure ImageMagick binary is set (Adjust path as needed for your system)
# This line requires imagemagick to be installed and the path correct.
# If TextClip fails, check ImageMagick installation and policy.xml (handled by fix_imagemagick_policy).
# Common paths: "/usr/bin/convert", "/usr/local/bin/convert", "C:\\Program Files\\ImageMagick-X.Y.Z-Q16\\convert.exe"
# You might need to adjust this based on your OS and installation
IMAGEMAGICK_BINARY_PATH = "/usr/bin/convert" # Default path, check your system
if not os.path.exists(IMAGEMAGICK_BINARY_PATH):
     print(f"Warning: ImageMagick binary not found at {IMAGEMAGICK_BINARY_PATH}. TextClip may not work.")
     print("Please install ImageMagick or update the IMAGEMAGICK_BINARY_PATH.")

mpy_config.change_settings({"IMAGEMAGICK_BINARY": IMAGEMAGICK_BINARY_PATH})


# ---------------- Global Configuration ---------------- #
# Using the user's provided API keys
PEXELS_API_KEY = 'BhJqbcdm9Vi90KqzXKAhnEHGsuFNv4irXuOjWtT761U49lRzo03qBGna'
OPENROUTER_API_KEY = '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'
OPENROUTER_MODEL = "mistralai/mistral-small-3.1-24b-instruct:free" # Or another preferred model
OUTPUT_VIDEO_FILENAME = "final_video.mp4"
USER_AGENT = "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/91.0.4472.124 Safari/537.36"

# Maximum number of script segments to display for editing
MAX_SEGMENTS_FOR_EDITING = 15

# Global placeholder for the temporary folder, will be created per run
TEMP_FOLDER = None

# ---------------- Helper Functions ---------------- #
# Most helper functions remain the same, but some might need minor adjustments
# to use passed parameters instead of global state (e.g., resolution).
# We'll update create_clip and add_background_music accordingly.

def generate_script(user_input, api_key, model):
    """Generate documentary script with proper OpenRouter handling."""
    if not api_key or api_key.startswith('YOUR_OPENROUTER_API_KEY'):
        print("OpenRouter API key not set or is placeholder. Skipping script generation.")
        return "[Error] API key not configured."

    headers = {
        'Authorization': f'Bearer {api_key}',
        'HTTP-Referer': 'https://your-domain.com', # Replace with your app's domain
        'X-Title': 'AI Documentary Maker'
    }

    # Updated prompt based on user's specific requirements for tone and style
    prompt = f"""Short Documentary Script Generator

Instructions:
If I say "use this," output the script exactly as given.
If I only give topics, generate a script based on them.
If I provide a full script, rewrite it without any changes.
Make everything short, simple, humorous, funny, and act serious but be humorous.
Don't say anything off topic.
Always end with a funny call to subscribe based on the video topic.
Use normal conversational text, avoid AI phrases, humanize the statements.
Always focus on negative or cynical views, avoid positive statements.
The full script should be for a single video about one topic.

Formatting Rules:
Title in Square Brackets: Each section starts with a one-word title inside [ ] (max two words if necessary). This title will be used as a search term for Pexels footage.
Casual & Funny Narration: Each section has 5-15 words of narration. Keep it natural, funny, and unpredictable.
No Special Formatting: No bold, italics, or special characters.
Generalized Search Terms: If a term is too specific, make it more general for Pexels search.
Scene-Specific Writing: Each section describes only what should be shown in the video.
Output Only the Script, make it funny/humorous/hilarious, and add a funny subscribe statement.
No extra text, just the script.

Example Output:
[Cats]
They plot world domination while napping.
[Dogs]
Loyalty is just a bribe for snacks.
[Humans]
The only species that pays to live on a planet they destroy.
[Future]
It looks suspiciously like the present, but with more screens.
[Warning]
Subscribe or a cat will steal your bandwidth.

Now here is the Topic/script: {user_input}
"""


    data = {
        'model': model,
        'messages': [{'role': 'user', 'content': prompt}],
        'temperature': 0.7, # Increased temperature slightly for more unpredictable humor
        'max_tokens': 500 # Limit token response to keep scripts short
    }

    try:
        response = requests.post(
            'https://openrouter.ai/api/v1/chat/completions',
            headers=headers,
            json=data,
            timeout=45 # Increased timeout
        )

        response.raise_for_status() # Raise HTTPError for bad responses (4xx or 5xx)

        response_data = response.json()
        if 'choices' in response_data and len(response_data['choices']) > 0:
            script_text = response_data['choices'][0]['message']['content']
            # Basic post-processing to remove potential markdown code blocks
            if script_text.startswith("```") and script_text.endswith("```"):
                 # Find the first and last ``` lines
                 first_code_block = script_text.find("```")
                 last_code_block = script_text.rfind("```")
                 if first_code_block != -1 and last_code_block != -1 and first_code_block < last_code_block:
                     # Extract content between the markers, removing the language specifier line if present
                     content_start = script_text.find('\n', first_code_block) + 1
                     content_end = last_code_block
                     script_text = script_text[content_start:content_end].strip()
                 else: # Simple case, remove from start and end
                     script_text = script_text.strip("` \n")

            return script_text
        else:
            print("Unexpected response format:", response_data)
            return "[Error] Unexpected API response format."

    except requests.exceptions.RequestException as e:
        print(f"API Request failed: {str(e)}")
        return f"[Error] API request failed: {str(e)}"
    except Exception as e:
        print(f"An unexpected error occurred during script generation: {e}")
        return f"[Error] An unexpected error occurred: {str(e)}"


def parse_script(script_text):
    """
    Parse the generated script into a list of segment dictionaries.
    Each dictionary includes original prompt, narration text, estimated duration, and placeholder for uploaded media.
    Handles potential API errors returned as strings.
    """
    if script_text.startswith("[Error]"):
        print(f"Skipping parse due to script generation error: {script_text}")
        return []

    segments = []
    current_title = None
    current_text = ""

    try:
        lines = script_text.strip().splitlines()
        if not lines:
             print("Script text is empty.")
             return []

        for line in lines:
            line = line.strip()
            if line.startswith("[") and "]" in line:
                bracket_start = line.find("[")
                bracket_end = line.find("]", bracket_start)
                if bracket_start != -1 and bracket_end != -1:
                    # Add previous segment if title and text are found
                    if current_title is not None and current_text.strip():
                        # Estimate duration based on word count (adjust factor as needed)
                        duration = max(2.0, len(current_text.split()) * 0.4) # Minimum 2s, approx 0.4s per word
                        segments.append({
                            "original_prompt": current_title.strip(),
                            "text": current_text.strip(),
                            "duration": duration,
                            "uploaded_media": None # Placeholder for user uploaded file path
                        })
                    current_title = line[bracket_start+1:bracket_end].strip()
                    current_text = line[bracket_end+1:].strip()
                elif current_title: # Append text if no new title found but currently parsing a segment
                     current_text += line + " "
            elif current_title: # Append text to the current segment
                current_text += line + " "
            # Ignore lines before the first [Title]

        # Add the last segment
        if current_title is not None and current_text.strip():
            duration = max(2.0, len(current_text.split()) * 0.4)
            segments.append({
                "original_prompt": current_title.strip(),
                "text": current_text.strip(),
                "duration": duration,
                "uploaded_media": None
            })

        # Limit segments to MAX_SEGMENTS_FOR_EDITING
        if len(segments) > MAX_SEGMENTS_FOR_EDITING:
            print(f"Warning: Script generated {len(segments)} segments, limiting to {MAX_SEGMENTS_FOR_EDITING} for editing.")
            segments = segments[:MAX_SEGMENTS_FOR_EDITING]

        print(f"Parsed {len(segments)} segments.")
        return segments
    except Exception as e:
        print(f"Error parsing script: {e}")
        return []

# Pexels and Google Image search and download functions remain unchanged
# Using the global PEXELS_API_KEY directly now.
def search_pexels_videos(query):
    """Search for a video on Pexels by query and return a random HD video."""
    if not PEXELS_API_KEY or PEXELS_API_KEY.startswith('YOUR_PEXELS_API_KEY'):
        print("Pexels API key not set or is placeholder. Skipping video search.")
        return None
    headers = {'Authorization': PEXELS_API_KEY}
    base_url = "https://api.pexels.com/videos/search"
    num_pages = 3
    videos_per_page = 15
    max_retries = 2 # Reduced retries for faster failure
    retry_delay = 1

    search_query = query
    all_videos = []

    for page in range(1, num_pages + 1):
        for attempt in range(max_retries):
            try:
                params = {"query": search_query, "per_page": videos_per_page, "page": page}
                response = requests.get(base_url, headers=headers, params=params, timeout=10)

                if response.status_code == 200:
                    data = response.json()
                    videos = data.get("videos", [])

                    # Filter for HD videos first, then fallback to other qualities
                    hd_videos_on_page = []
                    other_videos_on_page = []
                    for video in videos:
                        video_files = video.get("video_files", [])
                        for file in video_files:
                            if file.get("quality") == "hd":
                                hd_videos_on_page.append(file.get("link"))
                                break # Found HD, move to next video file for this video entry
                            # Collect other qualities just in case no HD is found on this page or in total
                            other_videos_on_page.append(file.get("link"))


                    all_videos.extend(hd_videos_on_page) # Add HD videos found
                    if not hd_videos_on_page: # If no HD found on this page, add other videos
                         all_videos.extend(other_videos_on_page)

                    if not videos:
                        print(f"No videos found on page {page} for query '{query}'.")
                        break # No videos on this page or subsequent ones


                    break # Success for this page attempt

                elif response.status_code == 429:
                    print(f"Pexels rate limit hit (attempt {attempt+1}/{max_retries}). Retrying in {retry_delay}s for query '{query}'...")
                    time.sleep(retry_delay)
                    retry_delay *= 2
                else:
                    print(f"Pexels video search error {response.status_code}: {response.text} for query '{query}'")
                    break # Non-recoverable error or too many retries

            except requests.exceptions.RequestException as e:
                print(f"Pexels video request exception (attempt {attempt+1}/{max_retries}) for query '{query}': {e}")
                if attempt < max_retries - 1:
                    time.sleep(retry_delay)
                    retry_delay *= 2
                else:
                     break # Too many retries

        # Stop searching if no videos were found on the last page check
        if not videos and page > 1:
             print(f"Stopping Pexels video search for '{query}' as no videos were found on page {page}.")
             break


    if all_videos:
        # Prioritize picking an HD video if any were collected
        hd_options = [link for link in all_videos if 'hd' in link.lower()] # Simple check, might not be perfect
        if hd_options:
             random_video = random.choice(hd_options)
             print(f"Selected random HD video from {len(hd_options)} options for query '{query}'.")
        else:
             # If no HD options, pick from the entire list (which includes SD and potentially others)
             random_video = random.choice(all_videos)
             print(f"Selected random video (likely SD or other quality) from {len(all_videos)} options for query '{query}' (no HD found).")
        return random_video
    else:
        print(f"No suitable videos found after searching all pages for query '{query}'.")
        return None


def search_pexels_images(query):
    """Search for an image on Pexels by query."""
    if not PEXELS_API_KEY or PEXELS_API_KEY.startswith('YOUR_PEXELS_API_KEY'):
        print("Pexels API key not set or is placeholder. Skipping image search.")
        return None
    headers = {'Authorization': PEXELS_API_KEY}
    url = "https://api.pexels.com/v1/search"
    params = {"query": query, "per_page": 15, "orientation": "landscape"} # Increased per_page

    max_retries = 2
    retry_delay = 1

    for attempt in range(max_retries):
        try:
            response = requests.get(url, headers=headers, params=params, timeout=10)

            if response.status_code == 200:
                data = response.json()
                photos = data.get("photos", [])
                if photos:
                    # Choose from the top results
                    photo = random.choice(photos[:min(10, len(photos))])
                    img_url = photo.get("src", {}).get("original")
                    print(f"Found {len(photos)} images on Pexels for query '{query}', selected one.")
                    return img_url
                else:
                    print(f"No images found for query: {query} on Pexels.")
                    return None

            elif response.status_code == 429:
                print(f"Pexels rate limit hit (attempt {attempt+1}/{max_retries}). Retrying in {retry_delay}s for query '{query}'...")
                time.sleep(retry_delay)
                retry_delay *= 2
            else:
                print(f"Pexels image search error {response.status_code}: {response.text} for query '{query}'")
                break # Non-recoverable error or too many retries

        except requests.exceptions.RequestException as e:
            print(f"Pexels image request exception (attempt {attempt+1}/{max_retries}) for query '{query}': {e}")
            if attempt < max_retries - 1:
                time.sleep(retry_delay)
                retry_delay *= 2
            else:
                break # Too many retries

    print(f"No Pexels images found for query: {query} after all attempts.")
    return None

def search_google_images(query):
    """Search for images on Google Images (fallback/news)"""
    try:
        # Using a simple text search method; dedicated Google Image Search APIs are better but may require setup.
        # This is prone to breaking if Google changes its HTML structure.
        search_url = f"https://www.google.com/search?q={quote(query)}&tbm=isch"
        headers = {"User-Agent": USER_AGENT}
        print(f"Searching Google Images for: {query}")
        response = requests.get(search_url, headers=headers, timeout=15)
        response.raise_for_status()
        soup = BeautifulSoup(response.text, "html.parser")

        # Find img tags, look for src attributes
        # This is a very fragile parsing method, might need adjustment
        img_tags = soup.find_all("img")
        image_urls = []
        # Look for src attributes that start with http and aren't data URIs or specific gstatic patterns
        # This is a heuristic and might grab incorrect URLs
        for img in img_tags:
            src = img.get("src", "")
            if src.startswith("http") and "encrypted" not in src and "base64" not in src: # Basic filtering
                 image_urls.append(src)
            elif img.get("data-src", "").startswith("http"): # Some sites use data-src
                 image_urls.append(img.get("data-src", ""))


        # Filter out potential tiny icons or invalid URLs
        valid_image_urls = [url for url in image_urls if url and "gstatic" not in url and url.split('.')[-1].lower() in ['jpg', 'jpeg', 'png', 'gif', 'bmp']]

        if valid_image_urls:
            print(f"Found {len(valid_image_urls)} potential Google Images for query '{query}', picking one.")
            return random.choice(valid_image_urls[:min(10, len(valid_image_urls))])
        else:
            print(f"No valid Google Images found for query: {query}")
            return None
    except Exception as e:
        print(f"Error in Google Images search for query '{query}': {e}")
        return None


def download_image(image_url, filename):
    """Download an image from a URL to a local file with enhanced error handling."""
    if not image_url:
        print("No image URL provided for download.")
        return None

    try:
        headers = {"User-Agent": USER_AGENT}
        print(f"Attempting to download image from: {image_url}")
        response = requests.get(image_url, headers=headers, stream=True, timeout=20) # Increased timeout
        response.raise_for_status()

        # Check content type before saving
        content_type = response.headers.get('Content-Type', '')
        if not content_type.startswith('image/'):
            print(f"URL did not return an image Content-Type ({content_type}). Skipping download.")
            return None

        # Ensure the directory exists
        os.makedirs(os.path.dirname(filename), exist_ok=True)

        with open(filename, 'wb') as f:
            for chunk in response.iter_content(chunk_size=8192):
                f.write(chunk)

        # print(f"Potential image downloaded to: {filename}") # Keep less noisy

        # Validate and process the image
        try:
            img = Image.open(filename)
            img.verify() # Verify it's an image file
            img = Image.open(filename) # Re-open after verify
            if img.mode != 'RGB':
                # print("Converting image to RGB") # Keep less noisy
                img = img.convert('RGB')
                img.save(filename)
            # print(f"Image validated and converted to RGB: {filename}") # Keep less noisy
            return filename
        except Exception as e_validate:
            print(f"Downloaded file is not a valid image or processing failed for {filename}: {e_validate}")
            if os.path.exists(filename):
                os.remove(filename) # Clean up invalid file
            return None

    except requests.exceptions.RequestException as e_download:
        print(f"Image download error for {image_url}: {e_download}")
        if os.path.exists(filename):
            os.remove(filename) # Clean up partially downloaded file
        return None
    except Exception as e_general:
        print(f"General error during image download/processing for {filename}: {e_general}")
        if os.path.exists(filename):
            os.remove(filename) # Clean up if needed
        return None


def download_video(video_url, filename):
    """Download a video from a URL to a local file."""
    if not video_url:
        print("No video URL provided for download.")
        return None
    try:
        headers = {"User-Agent": USER_AGENT} # Some sites block direct downloads
        print(f"Attempting to download video from: {video_url}")
        response = requests.get(video_url, stream=True, timeout=45) # Increased timeout for videos
        response.raise_for_status()

        # Check content type
        content_type = response.headers.get('Content-Type', '')
        if not content_type.startswith('video/'):
             print(f"URL did not return a video Content-Type ({content_type}). Skipping download.")
             return None

        os.makedirs(os.path.dirname(filename), exist_ok=True)

        # Use smaller chunk size for potentially large files
        chunk_size = 4096
        downloaded_size = 0
        total_size = int(response.headers.get('content-length', 0))

        with open(filename, 'wb') as f:
            for chunk in response.iter_content(chunk_size=chunk_size):
                 f.write(chunk)
                 downloaded_size += len(chunk)
                 # Optional: Add progress updates if needed, but noisy for console

        print(f"Video downloaded successfully to: {filename} ({downloaded_size} bytes)")
        # Basic check if the file seems valid (not just 0 bytes)
        if os.path.exists(filename) and os.path.getsize(filename) > 1024: # Check for > 1KB
             return filename
        else:
             print(f"Downloaded video file {filename} is too small or empty ({os.path.getsize(filename)} bytes).")
             if os.path.exists(filename):
                os.remove(filename)
             return None

    except requests.exceptions.RequestException as e:
        print(f"Video download error for {video_url}: {e}")
        if os.path.exists(filename):
            os.remove(filename)
        return None
    except Exception as e_general:
        print(f"General error during video download for {filename}: {e_general}")
        if os.path.exists(filename):
            os.remove(filename)
        return None


def generate_media_asset(prompt, uploaded_media_path):
    """
    Generate a visual asset (video or image). Prioritizes user upload,
    then searches Pexels video, then Pexels image, then Google Image.
    Returns a dict: {'path': <file_path>, 'asset_type': 'video' or 'image'}.
    Ensures the returned path is within the TEMP_FOLDER.
    """
    safe_prompt = re.sub(r'[^\w\s-]', '', prompt).strip().replace(' ', '_')
    os.makedirs(TEMP_FOLDER, exist_ok=True) # Ensure temp folder exists

    # 1. Use user uploaded media if provided
    if uploaded_media_path and os.path.exists(uploaded_media_path):
        print(f"Using user uploaded media: {uploaded_media_path}")
        file_ext = os.path.splitext(uploaded_media_path)[1].lower()
        asset_type = 'video' if file_ext in ['.mp4', '.mov', '.avi', '.webm', '.mkv'] else 'image'
        # Copy the user file to temp folder to manage cleanup
        temp_user_path = os.path.join(TEMP_FOLDER, f"user_upload_{os.path.basename(uploaded_media_path)}")
        try:
             # Use copy2 to preserve metadata like modification time
             shutil.copy2(uploaded_media_path, temp_user_path)
             print(f"Copied user upload to temp: {temp_user_path}")
             return {"path": temp_user_path, "asset_type": asset_type}
         # Handle case where source and destination might be the same (e.g., user uploads from temp)
        except shutil.SameFileError:
             print(f"User upload is already in temp folder: {uploaded_media_path}")
             return {"path": uploaded_media_path, "asset_type": asset_type}
        except Exception as e:
             print(f"Error copying user file {uploaded_media_path}: {e}. Falling back to search.")


    # 2. Search Pexels Videos (Increased chance)
    # Let's slightly increase video search preference when available
    if random.random() < 0.4: # Increase video search chance
        video_file = os.path.join(TEMP_FOLDER, f"{safe_prompt}_video.mp4")
        print(f"Attempting Pexels video search for: '{prompt}'")
        video_url = search_pexels_videos(prompt) # Use global API key
        if video_url:
            downloaded_video = download_video(video_url, video_file)
            if downloaded_video:
                print(f"Pexels video asset saved to {downloaded_video}")
                return {"path": downloaded_video, "asset_type": "video"}
        else:
            print(f"Pexels video search failed or found no video for: '{prompt}'")

    # 3. Search Pexels Images
    image_file = os.path.join(TEMP_FOLDER, f"{safe_prompt}.jpg")
    print(f"Attempting Pexels image search for: '{prompt}'")
    image_url = search_pexels_images(prompt) # Use global API key
    if image_url:
        downloaded_image = download_image(image_url, image_file)
        if downloaded_image:
            print(f"Pexels image asset saved to {downloaded_image}")
            return {"path": downloaded_image, "asset_type": "image"}
    else:
        print(f"Pexels image search failed or found no image for: '{prompt}'")

    # 4. Fallback: Search Google Images (especially useful for news/specific things Pexels might not have)
    print(f"Attempting Google Images fallback for: '{prompt}'")
    google_image_file = os.path.join(TEMP_FOLDER, f"{safe_prompt}_google.jpg")
    google_image_url = search_google_images(prompt)
    if google_image_url:
        downloaded_google_image = download_image(google_image_url, google_image_file)
        if downloaded_google_image:
            print(f"Google Image asset saved to {downloaded_google_image}")
            return {"path": downloaded_google_image, "asset_type": "image"}
    else:
        print(f"Google Images fallback failed for: '{prompt}'")


    # 5. Final Fallback: Generic Images if specific search failed
    fallback_terms = ["nature", "city", "abstract", "background"] # More generic fallbacks
    for term in fallback_terms:
        print(f"Trying generic fallback image search with term: '{term}'")
        fallback_file = os.path.join(TEMP_FOLDER, f"fallback_{term}.jpg")
        fallback_url = search_pexels_images(term) # Use Pexels for fallbacks, global API key
        if fallback_url:
            downloaded_fallback = download_image(fallback_url, fallback_file)
            if downloaded_fallback:
                print(f"Generic fallback image saved to {downloaded_fallback}")
                return {"path": downloaded_fallback, "asset_type": "image"}
            else:
                print(f"Generic fallback image download failed for term: '{term}'")
        else:
            print(f"Generic fallback image search failed for term: '{term}'")


    print(f"Failed to generate any visual asset for prompt: '{prompt}' after all attempts.")
    return None

def generate_silent_audio(duration, sample_rate=24000):
    """Generate a silent WAV audio file lasting 'duration' seconds."""
    print(f"Generating {duration:.2f}s of silent audio.")
    num_samples = int(duration * sample_rate)
    silence = np.zeros(num_samples, dtype=np.float32)
    # Use unique filename to avoid conflicts
    silent_path = os.path.join(TEMP_FOLDER, f"silent_{abs(hash(duration)) % (10**8)}_{int(time.time())}.wav")
    try:
        sf.write(silent_path, silence, sample_rate)
        print(f"Silent audio generated: {silent_path}")
        return silent_path
    except Exception as e:
        print(f"Error generating silent audio to {silent_path}: {e}")
        return None


def generate_tts(text, voice='en'):
    """
    Generate TTS audio using Kokoro, falling back to gTTS or silent audio if needed.
    Ensures temp folder exists.
    """
    if not text or not text.strip():
        print("TTS text is empty. Generating silent audio.")
        return generate_silent_audio(duration=2.0) # Default silence for empty text

    os.makedirs(TEMP_FOLDER, exist_ok=True) # Ensure temp folder exists
    safe_text_hash = str(abs(hash(text)) % (10**10)) # Use a hash for potentially long text
    file_path = os.path.join(TEMP_FOLDER, f"tts_{safe_text_hash}.wav")

    if os.path.exists(file_path):
        # print(f"Using cached TTS for text hash '{safe_text_hash}'") # Keep less noisy
        return file_path

    # Estimate duration based on word count (adjust factor as needed), used if TTS fails
    target_duration_fallback = max(2.0, len(text.split()) * 0.4)

    if pipeline:
        try:
            print(f"Attempting Kokoro TTS for text: '{text[:50]}...'")
            kokoro_voice = 'af_heart' if voice == 'en' else voice # Kokoro default American English voice
            # Kokoro pipeline might return multiple segments for long text
            generator = pipeline(text, voice=kokoro_voice, speed=1.0, split_pattern=r'\n+') # Use speed 1.0
            audio_segments = []
            total_duration = 0
            for i, (gs, ps, audio) in enumerate(generator):
                audio_segments.append(audio)
                total_duration += len(audio) / 24000.0 # Assuming 24000 Hz sample rate
            if audio_segments:
                full_audio = np.concatenate(audio_segments) if len(audio_segments) > 1 else audio_segments[0]
                sf.write(file_path, full_audio, 24000) # Use 24000Hz standard
                # print(f"TTS audio saved to {file_path} (Kokoro, {total_duration:.2f}s)") # Keep less noisy
                return file_path
            else:
                 print("Kokoro pipeline returned no audio segments.")

        except Exception as e:
            print(f"Error with Kokoro TTS: {e}")
            # Continue to gTTS fallback

    try:
        print(f"Falling back to gTTS for text: '{text[:50]}...'")
        tts = gTTS(text=text, lang='en', slow=False) # Use standard speed
        mp3_path = os.path.join(TEMP_FOLDER, f"tts_{safe_text_hash}.mp3")
        tts.save(mp3_path)
        audio = AudioSegment.from_mp3(mp3_path)
        audio.export(file_path, format="wav")
        if os.path.exists(mp3_path):
            os.remove(mp3_path) # Clean up intermediate mp3
        # print(f"Fallback TTS saved to {file_path} (gTTS, {audio.duration_seconds:.2f}s)") # Keep less noisy
        return file_path
    except Exception as fallback_error:
        print(f"Both TTS methods failed for text: '{text[:50]}...'. Error: {fallback_error}")
        # Use the estimated duration for silent audio
        print(f"Generating silent audio of estimated duration {target_duration_fallback:.2f}s.")
        return generate_silent_audio(duration=target_duration_fallback)

def apply_kenburns_effect(clip, target_resolution, effect_type=None):
    """Apply a smooth Ken Burns effect with a single movement pattern."""
    target_w, target_h = target_resolution
    clip_aspect = clip.w / clip.h
    target_aspect = target_w / target_h

    # Resize clip to fill target resolution while maintaining aspect ratio, then scale up
    # This ensures the image covers the whole frame even after scaling and panning
    if clip_aspect > target_aspect:
        # Wider than target: match height, scale width
        clip = clip.resize(height=target_h)
    else:
        # Taller than target: match width, scale height
        clip = clip.resize(width=target_w)

    # Now scale the resized clip up for the Ken Burns movement margin
    initial_w, initial_h = clip.size
    scale_factor = 1.15 # Scale up by 15%
    new_width = int(initial_w * scale_factor)
    new_height = int(initial_h * scale_factor)
    clip = clip.resize(newsize=(new_width, new_height))

    max_offset_x = new_width - target_w
    max_offset_y = new_height - target_h

    available_effects = ["zoom-in", "zoom-out", "pan-left", "pan-right", "pan-up", "pan-down", "up-left", "down-right"]
    if effect_type is None or effect_type == "random":
        effect_type = random.choice(available_effects)

    # Define start and end positions of the top-left corner of the target_resolution window
    start_x, start_y = 0, 0
    end_x, end_y = 0, 0
    start_zoom_factor = 1.0 # Relative to the scaled image size
    end_zoom_factor = 1.0

    # Set start/end positions based on effect type. Positions are top-left corner of the target frame within the scaled image.
    if effect_type == "zoom-in":
        start_zoom_factor = 1.0 # Starts covering the entire scaled image
        end_zoom_factor = scale_factor # Zooms to cover the original image size within the scaled frame
        # Stay centered
        start_x = max_offset_x / 2 # Top-left of the original image center
        start_y = max_offset_y / 2
        end_x = max_offset_x / 2
        end_y = max_offset_y / 2
        # Note: The zoom factor here is relative to the FINAL frame size during the effect,
        # which is `target_resolution`. A zoom factor of 1 means crop size is `target_resolution`.
        # A zoom factor of `scale_factor` means crop size is `target_resolution / scale_factor`.
        # Let's redefine zoom factors to be relative to target_resolution for clarity
        start_zoom_relative = 1.0 # Start at target size
        end_zoom_relative = scale_factor # End zoomed in by scale factor

        def get_crop_size(zoom_relative):
             return int(target_w / zoom_relative), int(target_h / zoom_relative)

        # Adjust start/end positions to match the changing crop size to keep the center aligned
        def get_current_center(t):
             progress = t / clip.duration if clip.duration > 0 else 0
             eased_progress = 0.5 - 0.5 * math.cos(math.pi * progress)
             current_zoom_relative = start_zoom_relative + (end_zoom_relative - start_zoom_relative) * eased_progress
             current_crop_w, current_crop_h = get_crop_size(current_zoom_relative)
             # Center position in the scaled image coordinates
             center_x = new_width / 2
             center_y = new_height / 2
             return center_x, center_y, current_crop_w, current_crop_h

        def transform_frame_zoom(get_frame, t):
            frame = get_frame(t)
            center_x, center_y, crop_w, crop_h = get_current_center(t)
            # Ensure center stays within bounds
            center_x = max(crop_w / 2, min(center_x, new_width - crop_w / 2))
            center_y = max(crop_h / 2, min(center_y, new_height - crop_h / 2))
            cropped_frame = cv2.getRectSubPix(frame, (crop_w, crop_h), (center_x, center_y))
            resized_frame = cv2.resize(cropped_frame, (target_w, target_h), interpolation=cv2.INTER_LANCZOS4)
            return resized_frame

        return clip.fl(transform_frame_zoom)


    elif effect_type == "zoom-out":
        start_zoom_relative = scale_factor # Start zoomed in
        end_zoom_relative = 1.0 # End at target size

        def get_crop_size(zoom_relative):
             return int(target_w / zoom_relative), int(target_h / zoom_relative)

        def get_current_center(t):
             progress = t / clip.duration if clip.duration > 0 else 0
             eased_progress = 0.5 - 0.5 * math.cos(math.pi * progress)
             current_zoom_relative = start_zoom_relative + (end_zoom_relative - start_zoom_relative) * eased_progress
             current_crop_w, current_crop_h = get_crop_size(current_zoom_relative)
             center_x = new_width / 2
             center_y = new_height / 2
             return center_x, center_y, current_crop_w, current_crop_h

        def transform_frame_zoom(get_frame, t):
            frame = get_frame(t)
            center_x, center_y, crop_w, crop_h = get_current_center(t)
            center_x = max(crop_w / 2, min(center_x, new_width - crop_w / 2))
            center_y = max(crop_h / 2, min(center_y, new_height - crop_h / 2))
            cropped_frame = cv2.getRectSubPix(frame, (crop_w, crop_h), (center_x, center_y))
            resized_frame = cv2.resize(cropped_frame, (target_w, target_h), interpolation=cv2.INTER_LANCZOS4)
            return resized_frame

        return clip.fl(transform_frame_zoom)

    # For pan effects, the crop size is constant (target_resolution)
    # We just interpolate the top-left corner position
    crop_w, crop_h = target_w, target_h

    if effect_type == "pan-left":
        start_x = max_offset_x
        start_y = max_offset_y / 2
        end_x = 0
        end_y = max_offset_y / 2
    elif effect_type == "pan-right":
        start_x = 0
        start_y = max_offset_y / 2
        end_x = max_offset_x
        end_y = max_offset_y / 2
    elif effect_type == "pan-up":
        start_x = max_offset_x / 2
        start_y = max_offset_y
        end_x = max_offset_x / 2
        end_y = 0
    elif effect_type == "pan-down":
        start_x = max_offset_x / 2
        start_y = 0
        end_x = max_offset_x / 2
        end_y = max_offset_y
    elif effect_type == "up-left":
        start_x = max_offset_x
        start_y = max_offset_y
        end_x = 0
        end_y = 0
    elif effect_type == "down-right":
        start_x = 0
        start_y = 0
        end_x = max_offset_x
        end_y = max_offset_y
    else:
         # Default to pan-right if type is random but somehow invalid (shouldn't happen with random.choice)
         effect_type = 'pan-right'
         start_x = 0
         start_y = max_offset_y / 2
         end_x = max_offset_x
         end_y = max_offset_y / 2
         print(f"Warning: Unexpected effect type '{effect_type}'. Defaulting to 'pan-right'.")


    def transform_frame_pan(get_frame, t):
        frame = get_frame(t)
        # Use a smooth ease-in/ease-out function
        progress = t / clip.duration if clip.duration > 0 else 0
        eased_progress = 0.5 - 0.5 * math.cos(math.pi * progress) # Cosine easing

        # Interpolate position (top-left corner of the target frame)
        current_x = start_x + (end_x - start_x) * eased_progress
        current_y = start_y + (end_y - start_y) * eased_progress

        # Calculate the center point for cv2.getRectSubPix
        center_x = current_x + crop_w / 2
        center_y = current_y + crop_h / 2

        # Ensure center stays within the bounds of the scaled image
        center_x = max(crop_w / 2, min(center_x, new_width - crop_w / 2))
        center_y = max(crop_h / 2, min(center_y, new_height - crop_h / 2))


        try:
            # Perform the crop using cv2.getRectSubPix (expects floating point center)
            # Ensure frame is a numpy array (moviepy returns numpy arrays)
            # Clamp coordinates to avoid errors on edges
            # Note: cv2.getRectSubPix handles bounds clipping internally, but explicit checks can prevent NaNs
            center_x = np.clip(center_x, 0, new_width)
            center_y = np.clip(center_y, 0, new_height)

            cropped_frame = cv2.getRectSubPix(frame, (crop_w, crop_h), (center_x, center_y))
            # Resize the cropped frame back to the target resolution (should already be target_resolution size)
            # This resize is actually redundant if crop_w, crop_h == target_w, target_h
            # but might be needed if bounds clipping changed effective size slightly?
            # Let's remove the resize if crop size == target size for efficiency
            # if (crop_w, crop_h) == (target_w, target_h):
            #     resized_frame = cropped_frame # No need to resize
            # else:
            resized_frame = cv2.resize(cropped_frame, (target_w, target_h), interpolation=cv2.INTER_LANCZOS4)

            return resized_frame
        except Exception as e:
             print(f"Error applying Ken Burns transform at t={t:.2f}s: {e}")
             # Return a black frame or placeholder in case of error
             return np.zeros((target_h, target_w, 3), dtype=np.uint8)


    # Apply the panning transform
    return clip.fl(transform_frame_pan)


def resize_to_fill(clip, target_resolution):
    """Resize and crop a clip to fill the target resolution while maintaining aspect ratio."""
    target_w, target_h = target_resolution
    clip_aspect = clip.w / clip.h
    target_aspect = target_w / target_h

    # print(f"Resizing clip {clip.size} to fill target {target_resolution}")

    if clip_aspect > target_aspect: # Clip is wider than target
        clip = clip.resize(height=target_h)
        # Calculate crop amount to make width match target_w
        crop_amount_x = max(0, (clip.w - target_w) / 2)
        # Ensure crop coordinates are integers
        x1 = int(crop_amount_x)
        x2 = int(clip.w - crop_amount_x)
        clip = clip.crop(x1=x1, x2=x2, y1=0, y2=clip.h)
    else: # Clip is taller than target or same aspect
        clip = clip.resize(width=target_w)
        # Calculate crop amount to make height match target_h
        crop_amount_y = max(0, (clip.h - target_h) / 2)
        # Ensure crop coordinates are integers
        y1 = int(crop_amount_y)
        y2 = int(clip.h - crop_amount_y)
        clip = clip.crop(x1=0, x2=clip.w, y1=y1, y2=y2)

    # Final check and resize if dimensions are slightly off due to rounding
    if clip.size != target_resolution:
         print(f"Warning: Clip size {clip.size} after resize_to_fill does not match target {target_resolution}. Resizing again.")
         clip = clip.resize(newsize=target_resolution)


    # print(f"Clip resized to {clip.size}")
    return clip

def find_mp3_files():
    """Search for any MP3 files in the current directory and subdirectories."""
    mp3_files = []
    # Check relative paths first
    for root, dirs, files in os.walk('.'):
        for file in files:
            if file.lower().endswith('.mp3'):
                mp3_path = os.path.join(root, file)
                mp3_files.append(mp3_path)
                print(f"Found MP3 file: {mp3_path}")

    if mp3_files:
        return mp3_files[0] # Return the first one found
    else:
        # print("No MP3 files found in the current directory or subdirectories.") # Keep less noisy
        return None


def add_background_music(final_video, bg_music_path, bg_music_volume=0.08):
    """Add background music to the final video."""
    if not bg_music_path or not os.path.exists(bg_music_path):
        print("No valid background music path provided or file not found. Skipping background music.")
        return final_video

    try:
        print(f"Adding background music from: {bg_music_path}")
        bg_music = AudioFileClip(bg_music_path)

        # Loop background music if shorter than video
        if bg_music.duration < final_video.duration:
            loops_needed = math.ceil(final_video.duration / bg_music.duration)
            bg_segments = [bg_music.copy() for _ in range(loops_needed)] # Use copy to avoid issues
            bg_music = concatenate_audioclips(bg_segments)
            # print(f"Looped background music to {bg_music.duration:.2f}s") # Keep less noisy

        # Subclip background music to match video duration
        bg_music = bg_music.subclip(0, final_video.duration)
        # print(f"Subclipped background music to {bg_music.duration:.2f}s") # Keep less noisy

        # Adjust volume
        bg_music = bg_music.volumex(bg_music_volume)
        # print(f"Set background music volume to {bg_music_volume}") # Keep less noisy

        # Composite audio
        video_audio = final_video.audio
        if video_audio:
            # Ensure video audio matches video duration before compositing
            if abs(video_audio.duration - final_video.duration) > 0.1:
                 print(f"Adjusting video audio duration ({video_audio.duration:.2f}s) to match video duration ({final_video.duration:.2f}s)")
                 video_audio = video_audio.fx(vfx.speedx, factor=video_audio.duration / final_video.duration)

            mixed_audio = CompositeAudioClip([video_audio, bg_music])
            # print("Composited video audio and background music") # Keep less noisy
        else:
             # Handle case where video might not have audio track initially
             mixed_audio = bg_music
             print("Warning: Video had no original audio track, only adding background music.")

        final_video = final_video.set_audio(mixed_audio)
        print("Background music added successfully.")
        return final_video
    except Exception as e:
        print(f"Error adding background music: {e}")
        print("Continuing without background music.")
        return final_video


def create_clip(media_asset, tts_path, estimated_duration, target_resolution,
                caption_enabled, caption_color, caption_size, caption_position,
                caption_bg_color, caption_stroke_color, caption_stroke_width,
                narration_text, segment_index):
    """Create a video clip with synchronized subtitles and narration."""
    try:
        print(f"Creating clip #{segment_index} from asset: {media_asset.get('path')}, type: {media_asset.get('asset_type')}")
        media_path = media_asset.get('path')
        asset_type = media_asset.get('asset_type')

        # Determine actual audio duration
        audio_clip = None
        audio_duration = estimated_duration # Default to estimated duration
        target_clip_duration = estimated_duration # Default target duration

        if tts_path and os.path.exists(tts_path):
            try:
                audio_clip = AudioFileClip(tts_path).audio_fadeout(0.2) # Fade out TTS slightly
                audio_duration = audio_clip.duration
                # Ensure clip duration is slightly longer than audio for transitions/padding
                target_clip_duration = audio_duration + 0.3 # Add a small buffer after TTS ends
                print(f"TTS audio duration: {audio_duration:.2f}s. Target clip duration: {target_clip_duration:.2f}s (estimated {estimated_duration:.2f}s)")
            except Exception as e:
                 print(f"Error loading TTS audio clip {tts_path}: {e}. Using estimated duration {estimated_duration:.2f}s for clip.")
                 audio_clip = None # Ensure audio_clip is None if loading fails
                 target_clip_duration = estimated_duration # Fallback to estimated duration


        # Handle missing media first
        if not media_path or not os.path.exists(media_path):
            print(f"Skipping clip {segment_index}: Missing media file {media_path}")
            # Create a black clip with silent audio for the target duration
            clip = ColorClip(size=target_resolution, color=(0,0,0), duration=target_clip_duration)
            print(f"Created placeholder black clip for segment {segment_index}")
            # Add placeholder text if captions are enabled
            if caption_enabled and narration_text and caption_color.lower() != "transparent" and narration_text.strip():
                 txt_clip = TextClip(
                    "[Missing Media]\n" + narration_text, # Indicate missing media
                    fontsize=caption_size,
                    font='Arial-Bold', # Ensure this font is available
                    color=caption_color,
                    bg_color=caption_bg_color,
                    method='caption',
                    align='center',
                    stroke_width=caption_stroke_width,
                    stroke_color=caption_stroke_color,
                    size=(target_resolution[0] * 0.9, None)
                ).set_position('center').set_duration(target_clip_duration) # Duration matches black clip
                 clip = CompositeVideoClip([clip, txt_clip])

            # Add silent audio to the placeholder clip
            silent_audio_path = generate_silent_audio(target_clip_duration)
            if silent_audio_path and os.path.exists(silent_audio_path):
                try:
                    silent_audio_clip = AudioFileClip(silent_audio_path)
                    # Ensure silent audio duration matches video clip duration
                    if abs(silent_audio_clip.duration - clip.duration) > 0.1:
                         silent_audio_clip = silent_audio_clip.fx(vfx.speedx, factor=silent_audio_clip.duration / clip.duration)
                    clip = clip.set_audio(silent_audio_clip)
                except Exception as e:
                     print(f"Error adding silent audio to placeholder clip {segment_index}: {e}")
                     clip = clip.set_audio(None) # Set audio to None if silent audio fails
            else:
                 clip = clip.set_audio(None) # Set audio to None if silent audio generation fails

            return clip # Return the placeholder clip

        # Process media if path is valid
        if asset_type == "video":
            try:
                clip = VideoFileClip(media_path)
                print(f"Loaded video clip from {media_path} with duration {clip.duration:.2f}s")
                clip = resize_to_fill(clip, target_resolution)
                if clip.duration < target_clip_duration:
                    print("Looping video clip")
                    # Loop the video to match the target duration
                    clip = clip.loop(duration=target_clip_duration)
                else:
                    # Subclip the video to match the target duration
                    clip = clip.subclip(0, target_clip_duration)
                clip = clip.fadein(0.2).fadeout(0.2) # Add simple transitions
                print(f"Video clip processed to duration {clip.duration:.2f}s")

            except Exception as e:
                 print(f"Error processing video clip {media_path} for segment {segment_index}: {e}")
                 # Fallback to a black clip if video processing fails
                 print(f"Creating placeholder black clip instead for segment {segment_index}")
                 clip = ColorClip(size=target_resolution, color=(0,0,0), duration=target_clip_duration)
                 if caption_enabled and narration_text and caption_color.lower() != "transparent" and narration_text.strip():
                      txt_clip = TextClip(
                         "[Video Error]\n" + narration_text, # Indicate video error
                         fontsize=caption_size, color=caption_color, bg_color=caption_bg_color, method='caption', align='center',
                         stroke_width=caption_stroke_width, stroke_color=caption_stroke_color,
                         size=(target_resolution[0] * 0.9, None)
                     ).set_position('center').set_duration(target_clip_duration)
                      clip = CompositeVideoClip([clip, txt_clip])


        elif asset_type == "image":
            try:
                img = Image.open(media_path)
                 # Ensure image is in RGB format before passing to ImageClip
                if img.mode != 'RGB':
                     print("Converting image to RGB")
                     img = img.convert('RGB')
                     # ImageClip accepts numpy arrays
                     img_array = np.array(img)
                     img.close() # Close the PIL image
                     clip = ImageClip(img_array).set_duration(target_clip_duration)
                else:
                    img.close() # Close the PIL image
                    clip = ImageClip(media_path).set_duration(target_clip_duration)

                # print(f"Loaded image clip from {media_path} with duration {clip.duration:.2f}s") # Keep less noisy
                clip = apply_kenburns_effect(clip, target_resolution) # Ken Burns with random effect
                clip = clip.fadein(0.3).fadeout(0.3) # Add simple transitions
                # print(f"Image clip processed to duration {clip.duration:.2f}s with Ken Burns") # Keep less noisy


            except Exception as e:
                 print(f"Error processing image clip {media_path} for segment {segment_index}: {e}")
                 # Fallback to a black clip if image processing fails
                 print(f"Creating placeholder black clip instead for segment {segment_index}")
                 clip = ColorClip(size=target_resolution, color=(0,0,0), duration=target_clip_duration)
                 if caption_enabled and narration_text and caption_color.lower() != "transparent" and narration_text.strip():
                     txt_clip = TextClip(
                         "[Image Error]\n" + narration_text, # Indicate image error
                         fontsize=caption_size, color=caption_color, bg_color=caption_bg_color, method='caption', align='center',
                         stroke_width=caption_stroke_width, stroke_color=caption_stroke_color,
                         size=(target_resolution[0] * 0.9, None)
                     ).set_position('center').set_duration(target_clip_duration)
                     clip = CompositeVideoClip([clip, txt_clip])

        else:
            print(f"Unknown asset type '{asset_type}' for segment {segment_index}. Creating placeholder.")
            # Create a placeholder black clip
            clip = ColorClip(size=target_resolution, color=(0,0,0), duration=target_clip_duration)
            if caption_enabled and narration_text and caption_color.lower() != "transparent" and narration_text.strip():
                 txt_clip = TextClip(
                    "[Unknown Media Type Error]\n" + narration_text, # Indicate unknown type error
                    fontsize=caption_size, color=caption_color, bg_color=caption_bg_color, method='caption', align='center',
                    stroke_width=caption_stroke_width, stroke_color=caption_stroke_color,
                    size=(target_resolution[0] * 0.9, None)
                ).set_position('center').set_duration(target_clip_duration)
                 clip = CompositeVideoClip([clip, txt_clip])


        # Set the audio for the clip
        if audio_clip:
            # Ensure audio clip duration matches video clip duration after processing
            if abs(audio_clip.duration - clip.duration) > 0.1: # Allow slight difference (e.g., 100ms)
                 print(f"Adjusting audio duration ({audio_clip.duration:.2f}s) to match video duration ({clip.duration:.2f}s) for segment {segment_index}")
                 try:
                    audio_clip = audio_clip.fx(vfx.speedx, factor=audio_clip.duration / clip.duration)
                 except Exception as e:
                      print(f"Error adjusting audio speed for segment {segment_index}: {e}. Using original audio duration.")
                      # If speeding fails, maybe just loop or subclip the audio? Or regenerate silent audio.
                      # For now, if speedx fails, let's just attach the original audio and hope for the best timing wise.
                      pass # Keep the original audio_clip if speedx fails

            clip = clip.set_audio(audio_clip)
        else:
            # If TTS failed or audio loading failed, ensure video clip has no audio or silent audio
            print(f"No valid audio for clip {segment_index}. Setting silent audio.")
            silent_audio_path = generate_silent_audio(clip.duration) # Generate silent audio matching the clip's final duration
            if silent_audio_path and os.path.exists(silent_audio_path):
                 try:
                     silent_audio_clip = AudioFileClip(silent_audio_path)
                     # Should match duration, but double check
                     if abs(silent_audio_clip.duration - clip.duration) > 0.1:
                          silent_audio_clip = silent_audio_clip.fx(vfx.speedx, factor=silent_audio_clip.duration / clip.duration)
                     clip = clip.set_audio(silent_audio_clip)
                 except Exception as e:
                      print(f"Error setting silent audio for segment {segment_index}: {e}")
                      clip = clip.set_audio(None) # Set audio to None if silent audio fails loading
            else:
                 clip = clip.set_audio(None) # Set audio to None if silent audio generation fails


        # Add subtitles if enabled and text exists
        if caption_enabled and narration_text and caption_color.lower() != "transparent" and narration_text.strip():
            try:
                # Determine total audio duration (using actual if available, else estimated)
                actual_audio_duration_for_subtitles = audio_duration if audio_clip else target_clip_duration

                # Simple word-based chunking for subtitles
                words = narration_text.split()
                # Calculate average word duration based on total audio duration and word count
                # This is a simple approach; for better sync, use a forced aligner (more complex)
                total_words = len(words)
                average_word_duration = actual_audio_duration_for_subtitles / total_words if total_words > 0 else 0.5 # Default if no words

                subtitle_clips = []
                current_time = 0
                chunk_size = 6 # Words per caption chunk (adjust as needed for readability)

                for i in range(0, total_words, chunk_size):
                    chunk_words = words[i:i+chunk_size]
                    chunk_text = ' '.join(chunk_words)
                    # Estimate chunk duration based on word count * average word duration
                    estimated_chunk_duration = len(chunk_words) * average_word_duration

                    start_time = current_time
                    # Ensure end time doesn't exceed the *clip* duration
                    end_time = min(current_time + estimated_chunk_duration, clip.duration)
                    if start_time >= end_time: break # Avoid 0 or negative duration clips

                    # Determine vertical position
                    if caption_position == "Top":
                         subtitle_y_position = int(target_resolution[1] * 0.05) # Slightly lower than top edge
                    elif caption_position == "Middle":
                         subtitle_y_position = int(target_resolution[1] * 0.5) - int(caption_size * 1.2 / 2) # Center adjusted for text height
                    else: # Default to Bottom
                         subtitle_y_position = int(target_resolution[1] * 0.9) - int(caption_size * 1.2) # Slightly higher than bottom edge, accounting for multiple lines


                    txt_clip = TextClip(
                        chunk_text,
                        fontsize=caption_size,
                        font='Arial-Bold', # Ensure this font is available or use a common system font
                        color=caption_color,
                        bg_color=caption_bg_color, # Use background color
                        method='caption', # Enables text wrapping
                        align='center',
                        stroke_width=caption_stroke_width, # Use stroke
                        stroke_color=caption_stroke_color, # Use stroke color
                        size=(target_resolution[0] * 0.9, None) # Caption width max 90% of video width
                    ).set_start(start_time).set_end(end_time)

                    # Position is tuple ('center', y_position)
                    txt_clip = txt_clip.set_position(('center', subtitle_y_position))
                    subtitle_clips.append(txt_clip)
                    current_time = end_time # Move to the end of the current chunk

                if subtitle_clips:
                    clip = CompositeVideoClip([clip] + subtitle_clips)
                    # print(f"Added {len(subtitle_clips)} subtitle chunks to clip {segment_index}.") # Keep less noisy
                # else:
                     # print(f"No subtitle clips generated for segment {segment_index} (might be due to text/duration issues).") # Keep less noisy


            except Exception as sub_error:
                print(f"Error adding subtitles for segment {segment_index}: {sub_error}")
                # Fallback to a single centered text overlay if detailed subtitling fails
                try:
                    txt_clip = TextClip(
                        narration_text,
                        fontsize=caption_size,
                        font='Arial-Bold',
                        color=caption_color,
                        bg_color=caption_bg_color,
                        method='caption',
                        align='center',
                        stroke_width=caption_stroke_width,
                        stroke_color=caption_stroke_color,
                        size=(target_resolution[0] * 0.8, None)
                    ).set_position(('center', int(target_resolution[1] * 0.75))).set_duration(clip.duration)
                    clip = CompositeVideoClip([clip, txt_clip])
                    print(f"Added simple fallback subtitle for segment {segment_index}.")
                except Exception as fallback_sub_error:
                    print(f"Simple fallback subtitle failed for segment {segment_index}: {fallback_sub_error}")


        # Ensure final clip duration is explicitly set
        clip = clip.set_duration(clip.duration)

        # print(f"Clip {segment_index} created successfully: {clip.duration:.2f}s") # Keep less noisy
        return clip
    except Exception as e:
        print(f"Critical error in create_clip for segment {segment_index}: {str(e)}")
        # Create a black clip with error message if anything goes wrong during the main process
        error_duration = target_clip_duration if 'target_clip_duration' in locals() else (estimated_duration if estimated_duration else 3.0)
        print(f"Creating error placeholder black clip for segment {segment_index} with duration {error_duration:.2f}s.")
        black_clip = ColorClip(size=target_resolution, color=(0,0,0), duration=error_duration)
        error_text = f"Error in segment {segment_index}"
        if narration_text: error_text += f":\n{narration_text[:50]}..."
        error_txt_clip = TextClip(
            error_text,
            fontsize=30,
            color="red",
            align='center',
            size=(target_resolution[0] * 0.9, None)
        ).set_position('center').set_duration(error_duration)
        clip = CompositeVideoClip([black_clip, error_txt_clip])
        silent_audio_path = generate_silent_audio(error_duration)
        if silent_audio_path and os.path.exists(silent_audio_path):
            try:
                clip = clip.set_audio(AudioFileClip(silent_audio_path))
            except Exception as audio_e:
                 print(f"Error setting silent audio for error clip {segment_index}: {audio_e}")
                 clip = clip.set_audio(None)
        else:
            clip = clip.set_audio(None)
        return clip


def fix_imagemagick_policy():
    """Attempt to fix ImageMagick security policies required by TextClip."""
    print("Attempting to fix ImageMagick security policies...")
    policy_paths = [
        "/etc/ImageMagick-6/policy.xml",
        "/etc/ImageMagick-7/policy.xml",
        "/etc/ImageMagick/policy.xml", # Common symlink path
        "/usr/local/etc/ImageMagick-7/policy.xml", # macports/homebrew path
        "/usr/share/ImageMagick/policy.xml", # Another common path
        "/usr/share/ImageMagick-6/policy.xml",
        "/usr/share/ImageMagick-7/policy.xml",
        os.path.join(os.environ.get('MAGICK_HOME', ''), 'policy.xml') if os.environ.get('MAGICK_HOME') else '', # Check MAGICK_HOME
        # Add more paths if needed based on typical installations
    ]
    # Filter out empty paths
    policy_paths = [path for path in policy_paths if path and os.path.exists(path)]

    found_policy = None
    if policy_paths:
        found_policy = policy_paths[0] # Use the first one found

    if not found_policy:
        print("No policy.xml found in common locations. TextClip may fail.")
        print("Consider installing ImageMagick and checking its installation path and policy.xml location.")
        return False

    print(f"Attempting to modify policy file at {found_policy}")
    try:
        # Create a backup - use a unique name
        backup_path = f"{found_policy}.bak_aivgen_{int(time.time())}"
        if os.path.exists(found_policy):
             shutil.copy2(found_policy, backup_path)
             print(f"Created backup at {backup_path}")
        else:
             print(f"Warning: Policy file {found_policy} not found at copy stage, cannot create backup.")


        # Read the original policy file (handle potential permission issues)
        try:
             with open(found_policy, 'r') as f:
                 policy_content = f.read()
        except Exception as e:
             print(f"Error reading policy file {found_policy}: {e}. Attempting with sudo cat...")
             try:
                 # Use sudo cat to read if direct read fails
                 process = subprocess.Popen(['sudo', 'cat', found_policy], stdout=subprocess.PIPE, stderr=subprocess.PIPE)
                 stdout, stderr = process.communicate()
                 if process.returncode == 0:
                     policy_content = stdout.decode('utf-8')
                     print("Read policy file content using sudo.")
                 else:
                     print(f"Failed to read policy file using sudo cat. Error: {stderr.decode('utf-8')}")
                     print("Manual intervention may be required.")
                     return False
             except Exception as e_sudo_read:
                  print(f"Error executing sudo cat: {e_sudo_read}")
                  print("Manual intervention may be required.")
                  return False


        # Use regex to find and replace the specific policy lines
        # Allow read and write rights for PDF, EPS, PS, etc. potentially restricted formats
        # Also ensure path policies allow reading/writing files
        # Be more specific with replacements to avoid unintended side effects
        modified_content = re.sub(
            r'<policy domain="coder" rights="none" pattern="(PDF|EPS|PS|XPS|MSL|SVG|FILTER)"', # Added common restricted patterns
            r'<policy domain="coder" rights="read|write" pattern="\1"', # Changed rights to read|write
            policy_content
        )
         # Ensure path rights are read/write, especially important for temporary files
        modified_content = re.sub(
            r'<policy domain="path" pattern="@\*" rights="none"',
            r'<policy domain="path" pattern="@*" rights="read|write"', # Ensure path rights are read|write
            modified_content
        )
         # Catch any other "rights=none" for coder or path domains, but be cautious
        modified_content = re.sub(
             r'<policy domain="(coder|path)" rights="none"(.*?)/>',
             r'<policy domain="\1" rights="read|write"\2/>',
             modified_content
         )


        # Write the modified content back (handle potential permission issues)
        try:
            with open(found_policy, 'w') as f:
                f.write(modified_content)
            print("ImageMagick policies updated successfully (direct write).")
            return True
        except IOError as e:
            print(f"Direct write failed: {e}. Attempting with sudo tee...")
            # Fallback to using os.system with sudo tee if direct write fails
            # This requires the user to be able to run sudo commands without a password prompt for the script's execution
            # and tee needs to be available.
            # Using tee is safer than sudo cp for writing potentially large content.
            try:
                # Write modified content to a temporary file first
                temp_policy_file = os.path.join(TEMP_FOLDER, "temp_policy_modified.xml")
                with open(temp_policy_file, 'w') as f:
                    f.write(modified_content)

                # Use sudo tee to overwrite the original file
                # echo <content> | sudo tee <file> > /dev/null
                cmd = f'sudo tee {found_policy} > /dev/null'
                print(f"Executing: echo ... | {cmd}")

                # Using subprocess is safer than os.system for piping
                process = subprocess.Popen(['sudo', 'tee', found_policy], stdin=subprocess.PIPE, stdout=subprocess.PIPE, stderr=subprocess.PIPE)
                stdout, stderr = process.communicate(input=modified_content.encode('utf-8'))

                if process.returncode == 0:
                     print("ImageMagick policies updated successfully using sudo tee.")
                     return True
                else:
                     print(f"Failed to update ImageMagick policies using sudo tee. Result code: {process.returncode}. Error: {stderr.decode('utf-8')}")
                     print("Please manually edit your policy.xml to grant read/write rights for coder and path domains.")
                     print("Example: Change <policy domain='coder' rights='none' pattern='PDF'> to <policy domain='coder' rights='read|write' pattern='PDF'>")
                     return False
            except Exception as e_sudo_write:
                 print(f"Error executing sudo tee process: {e_sudo_write}")
                 print("Manual intervention may be required.")
                 return False
            finally:
                 # Clean up the temporary file
                 if 'temp_policy_file' in locals() and os.path.exists(temp_policy_file):
                      os.remove(temp_policy_file)


    except Exception as e_general:
        print(f"General error during ImageMagick policy modification: {e_general}")
        print("Manual intervention may be required.")
        return False


# Import subprocess for sudo commands in fix_imagemagick_policy
import subprocess


# ---------------- Gradio Interface Functions ---------------- #

def generate_script_and_show_editor(user_input, resolution_choice,
                                   caption_enabled_choice, caption_color,
                                   caption_size, caption_position, caption_bg_color,
                                   caption_stroke_color, caption_stroke_width):
    """
    Generates the script, parses it, stores segments in state,
    and prepares the UI updates to show the editing interface.
    Uses yield to update status.
    """
    global TEMP_FOLDER
    # Clean up previous run's temp folder if it exists
    if TEMP_FOLDER and os.path.exists(TEMP_FOLDER):
        print(f"Cleaning up previous temp folder: {TEMP_FOLDER}")
        try:
            # Use onerror to log errors during cleanup
            def onerror(func, path, exc_info):
                print(f"Error cleaning up {path}: {exc_info[1]}")
            shutil.rmtree(TEMP_FOLDER, onerror=onerror)
        except Exception as e:
            print(f"Error starting cleanup of temp folder {TEMP_FOLDER}: {e}")

    # Create a new unique temporary folder for this run
    TEMP_FOLDER = tempfile.mkdtemp(prefix="aivgen_")
    print(f"Created new temp folder: {TEMP_FOLDER}")

    # Store global style choices in state or use them directly (let's store in state)
    # Gradio State can hold a single object. Let's use a dict.
    run_config = {
        "resolution": (1920, 1080) if resolution_choice == "Full (1920x1080)" else (1080, 1920),
        "caption_enabled": caption_enabled_choice == "Yes",
        "caption_color": caption_color,
        "caption_size": caption_size,
        "caption_position": caption_position,
        "caption_bg_color": caption_bg_color,
        "caption_stroke_color": caption_stroke_color,
        "caption_stroke_width": caption_stroke_width,
        "temp_folder": TEMP_FOLDER # Store temp folder path
    }

    # Initial status update and hide editing/video areas
    yield (run_config,
           gr.update(value="Generating script...", visible=True),
           gr.update(visible=False), # Hide editing area
           gr.update(value=None, visible=False), # Hide video output and clear value
           # Updates for dynamic components (initially hide/clear all)
           [gr.update(visible=False, value="") for _ in range(MAX_SEGMENTS_FOR_EDITING)], # Hide textboxes
           [gr.update(visible=False, value=None) for _ in range(MAX_SEGMENTS_FOR_EDITING)], # Hide file uploads
           [gr.update(visible=False) for _ in range(MAX_SEGMENTS_FOR_EDITING)], # Hide segment groups
           []) # Clear segments_state


    script_text = generate_script(user_input, OPENROUTER_API_KEY, OPENROUTER_MODEL)

    # Update raw script preview
    raw_script_preview = f"### Generated Script Preview\n\n```\n{script_text}\n```" if script_text else "### Generated Script Preview\n\nFailed to generate script."


    if not script_text or script_text.startswith("[Error]"):
        # Update status and keep editing/video areas hidden
        yield (run_config,
               gr.update(value=f"Script generation failed: {script_text}", visible=True),
               gr.update(visible=False),
               gr.update(value=None, visible=False),
               # Updates for dynamic components (all hidden)
               [gr.update(visible=False, value="") for _ in range(MAX_SEGMENTS_FOR_EDITING)],
               [gr.update(visible=False, value=None) for _ in range(MAX_SEGMENTS_FOR_EDITING)],
               [gr.update(visible=False) for _ in range(MAX_SEGMENTS_FOR_EDITING)],
               [], # segments_state remains empty
               raw_script_preview) # Update raw script preview
        return # Stop execution


    yield (run_config,
           gr.update(value="Parsing script...", visible=True),
           gr.update(visible=False),
           gr.update(value=None, visible=False),
           [gr.update(visible=False, value="") for _ in range(MAX_SEGMENTS_FOR_EDITING)],
           [gr.update(visible=False, value=None) for _ in range(MAX_SEGMENTS_FOR_EDITING)],
           [gr.update(visible=False) for _ in range(MAX_SEGMENTS_FOR_EDITING)],
           [], # segments_state will be updated next
           raw_script_preview)


    segments = parse_script(script_text)

    if not segments:
        yield (run_config,
               gr.update(value="Failed to parse script or script is empty after parsing.", visible=True),
               gr.update(visible=False),
               gr.update(value=None, visible=False),
               # Updates for dynamic components (all hidden)
               [gr.update(visible=False, value="") for _ in range(MAX_SEGMENTS_FOR_EDITING)],
               [gr.update(visible=False, value=None) for _ in range(MAX_SEGMENTS_FOR_EDITING)],
               [gr.update(visible=False) for _ in range(MAX_SEGMENTS_FOR_EDITING)],
               [], # segments_state remains empty
               raw_script_preview) # Update raw script preview
        return # Stop execution


    # Prepare updates for dynamic editing components
    textbox_updates = []
    file_updates = []
    group_visibility_updates = []

    for i in range(MAX_SEGMENTS_FOR_EDITING):
        if i < len(segments):
            # Show group, populate text, clear file upload
            textbox_updates.append(gr.update(value=segments[i]['text'], visible=True))
            file_updates.append(gr.update(value=None, visible=True)) # Clear previous uploads
            group_visibility_updates.append(gr.update(visible=True))
        else:
            # Hide unused groups and clear their values
            textbox_updates.append(gr.update(value="", visible=False))
            file_updates.append(gr.update(value=None, visible=False))
            group_visibility_updates.append(gr.update(visible=False))


    # Final yield to update UI: show editing area, populate fields, update state
    yield (run_config,
           gr.update(value=f"Script generated with {len(segments)} segments. Edit segments below.", visible=True),
           gr.update(visible=True), # Show Editing area
           gr.update(value=None, visible=False), # Ensure video output is hidden and cleared
           textbox_updates, # Update textboxes (visibility and value)
           file_updates, # Update file uploads (visibility and value)
           group_visibility_updates, # Update visibility of groups
           segments, # Update the state with parsed segments
           raw_script_preview) # Update raw script preview


def generate_video_from_edited(run_config, segments_data, segment_texts, segment_uploads, bg_music_volume):
    """
    Takes the edited segment data (text, uploaded files) and configuration,
    and generates the final video.
    Uses yield to update status.
    """
    if not segments_data:
        yield "No segments to process. Generate script first.", None
        return

    global TEMP_FOLDER
    # Ensure TEMP_FOLDER is correctly set from run_config
    TEMP_FOLDER = run_config.get("temp_folder")
    if not TEMP_FOLDER or not os.path.exists(TEMP_FOLDER):
         yield "Error: Temporary folder not found from run config. Please regenerate script.", None
         # Attempt cleanup just in case temp folder existed but was invalid
         if TEMP_FOLDER and os.path.exists(TEMP_FOLDER):
             try:
                 shutil.rmtree(TEMP_FOLDER)
             except Exception as e:
                  print(f"Error cleaning up invalid temp folder {TEMP_FOLDER}: {e}")
         TEMP_FOLDER = None # Reset global
         return

    # Extract config from run_config
    TARGET_RESOLUTION = run_config.get("resolution", (1920, 1080)) # Default if missing
    CAPTION_ENABLED = run_config.get("caption_enabled", True) # Default if missing
    CAPTION_COLOR = run_config.get("caption_color", "#FFFFFF") # Default if missing
    CAPTION_SIZE = run_config.get("caption_size", 45) # Default if missing
    CAPTION_POSITION = run_config.get("caption_position", "Bottom") # Default if missing
    CAPTION_BG_COLOR = run_config.get("caption_bg_color", "rgba(0, 0, 0, 0.25)") # Default if missing
    CAPTION_STROKE_COLOR = run_config.get("caption_stroke_color", "#000000") # Default if missing
    CAPTION_STROKE_WIDTH = run_config.get("caption_stroke_width", 2) # Default if missing


    # Update segments_data with potentially edited text and uploaded file paths
    # segment_texts and segment_uploads are lists of values from the Gradio components
    processed_segments = []
    for i, segment in enumerate(segments_data):
        if i < len(segment_texts) and i < len(segment_uploads): # Ensure we have corresponding input values
            processed_segment = segment.copy() # Make a copy
            # Use edited text, strip whitespace
            processed_segment['text'] = segment_texts[i].strip() if segment_texts[i] is not None else segment.get('text', '').strip()
            # Use uploaded media path (will be None if nothing uploaded)
            processed_segment['uploaded_media'] = segment_uploads[i]
            processed_segments.append(processed_segment)
        else:
            # This shouldn't happen if state and UI updates are in sync, but as a safeguard
            print(f"Warning: Missing input value(s) for segment index {i}. Using original segment data.")
            processed_segments.append(segment) # Append original if inputs are missing

    if not processed_segments:
        yield "No valid segments to process after editing.", None
        # Clean up
        if TEMP_FOLDER and os.path.exists(TEMP_FOLDER):
             try:
                 shutil.rmtree(TEMP_FOLDER)
                 print(f"Cleaned up temp folder: {TEMP_FOLDER}")
             except Exception as e:
                 print(f"Error cleaning up temp folder {TEMP_FOLDER}: {e}")
        TEMP_FOLDER = None # Reset global
        return


    yield "Fixing ImageMagick policy...", None
    fix_imagemagick_policy() # Attempt policy fix before creating clips

    clips = []
    yield "Generating media and audio for clips...", None

    total_segments = len(processed_segments)
    for idx, segment in enumerate(processed_segments):
        yield f"Processing segment {idx+1}/{total_segments}...", None
        print(f"\nProcessing segment {idx+1}/{total_segments} (Prompt: '{segment.get('original_prompt', 'N/A')[:30]}...')")

        # Determine media source: uploaded or generated
        media_asset = generate_media_asset(
            segment.get('original_prompt', 'background'), # Use original prompt for search if available, else a generic term
            segment.get('uploaded_media') # Pass uploaded media path
        )


        # Generate TTS audio
        tts_path = generate_tts(segment.get('text', '')) # Use edited text, default to empty string if None/missing

        # Create the video clip for this segment
        clip = create_clip(
            media_asset=media_asset if media_asset else {"path": None, "asset_type": None}, # Pass dummy if generate_media_asset failed
            tts_path=tts_path,
            estimated_duration=segment.get('duration', 3.0), # Use estimated duration as a fallback reference
            target_resolution=TARGET_RESOLUTION,
            caption_enabled=CAPTION_ENABLED,
            caption_color=CAPTION_COLOR,
            caption_size=CAPTION_SIZE,
            caption_position=CAPTION_POSITION,
            caption_bg_color=CAPTION_BG_COLOR,
            caption_stroke_color=CAPTION_STROKE_COLOR,
            caption_stroke_width=CAPTION_STROKE_WIDTH,
            narration_text=segment.get('text', ''), # Pass narration text for captions
            segment_index=idx+1
        )

        if clip:
            clips.append(clip)
        else:
            print(f"Skipping segment {idx+1} due to clip creation failure.")
            # If create_clip returns None (shouldn't happen with fallback logic, but as safety)
            # Add a placeholder black clip
            placeholder_duration = segment.get('duration', 3.0) # Use estimated duration or default
            placeholder_clip = ColorClip(size=TARGET_RESOLUTION, color=(0,0,0), duration=placeholder_duration)
            silent_audio_path = generate_silent_audio(placeholder_duration)
            if silent_audio_path and os.path.exists(silent_audio_path):
                 placeholder_clip = placeholder_clip.set_audio(AudioFileClip(silent_audio_path))
            error_text = f"Segment {idx+1} Failed"
            if segment.get('text'): error_text += f":\n{segment['text'][:50]}..."
            error_txt_clip = TextClip(error_text, fontsize=30, color="red", align='center', size=(TARGET_RESOLUTION[0] * 0.9, None)).set_position('center').set_duration(placeholder_duration)
            placeholder_clip = CompositeVideoClip([placeholder_clip, error_txt_clip])
            clips.append(placeholder_clip)


    if not clips:
        yield "No clips were successfully created. Video generation failed.", None
        # Clean up
        if TEMP_FOLDER and os.path.exists(TEMP_FOLDER):
             try:
                 shutil.rmtree(TEMP_FOLDER)
                 print(f"Cleaned up temp folder: {TEMP_FOLDER}")
             except Exception as e:
                 print(f"Error cleaning up temp folder {TEMP_FOLDER}: {e}")
        TEMP_FOLDER = None # Reset global
        return

    yield "Concatenating clips...", None
    print("\nConcatenating clips...")
    try:
        final_video = concatenate_videoclips(clips, method="compose")
    except Exception as e:
        print(f"Error concatenating clips: {e}")
        yield f"Error concatenating clips: {e}", None
        # Clean up
        if TEMP_FOLDER and os.path.exists(TEMP_FOLDER):
             try:
                 shutil.rmtree(TEMP_FOLDER)
                 print(f"Cleaned up temp folder: {TEMP_FOLDER}")
             except Exception as e:
                 print(f"Error cleaning up temp folder {TEMP_FOLDER}: {e}")
        TEMP_FOLDER = None # Reset global
        return


    yield "Adding background music...", None
    bg_music_path = find_mp3_files() # Find background music
    final_video = add_background_music(final_video, bg_music_path, bg_music_volume=bg_music_volume) # Use volume from input


    yield f"Exporting final video to {OUTPUT_VIDEO_FILENAME}...", None
    print(f"Exporting final video to {OUTPUT_VIDEO_FILENAME}...")
    output_path = None
    try:
        # Use a temporary output file first for safety, within TEMP_FOLDER
        temp_output_filename = os.path.join(TEMP_FOLDER, f"temp_final_video_{int(time.time())}.mp4")
        final_video.write_videofile(temp_output_filename, codec='libx264', fps=24, preset='veryfast')

        # Ensure the destination directory for the final output exists (current dir)
        os.makedirs(os.path.dirname(OUTPUT_VIDEO_FILENAME) or '.', exist_ok=True)

        # Move the final file to the intended location after successful export
        final_output_path = OUTPUT_VIDEO_FILENAME
        try:
            shutil.move(temp_output_filename, final_output_path)
            print(f"Final video saved as {final_output_path}")
            output_path = final_output_path
        except Exception as e:
             print(f"Error moving temporary file {temp_output_filename} to final destination {final_output_path}: {e}")
             # If move fails, return the temp file path or None
             output_path = temp_output_filename # Return temp path so user can access it
             print(f"Returning video from temporary path: {output_path}")


    except Exception as e:
        print(f"Error exporting video: {e}")
        output_path = None
        yield f"Video export failed: {e}", None # Provide error message in status

    # Clean up temporary folder
    yield "Cleaning up temporary files...", output_path # Update status before cleanup
    if TEMP_FOLDER and os.path.exists(TEMP_FOLDER):
        try:
             # Use onerror to log errors during cleanup
            def onerror(func, path, exc_info):
                print(f"Error cleaning up {path}: {exc_info[1]}")
            shutil.rmtree(TEMP_FOLDER, onerror=onerror)
            print(f"Cleaned up temp folder: {TEMP_FOLDER}")
        except Exception as e:
            print(f"Error starting cleanup of temp folder {TEMP_FOLDER}: {e}")
    TEMP_FOLDER = None # Reset global

    yield "Done!", output_path # Final status update


# ---------------- Gradio Interface Definition (Blocks) ---------------- #

# Need lists to hold the dynamic UI components for segments
segment_editing_groups = []
segment_text_inputs = []
segment_file_inputs = []

with gr.Blocks() as demo:
    gr.Markdown("# 🤖 AI Documentary Video Generator 🎬")
    gr.Markdown("Enter a concept to generate a funny documentary script. You can then edit the script text and replace the suggested media for each segment before generating the final video.")

    # --- Global Settings ---
    with gr.Accordion("Global Settings", open=True):
        user_concept_input = gr.Textbox(label="Video Concept", placeholder="e.g., The secret life of pigeons, Why socks disappear in the laundry, The futility of alarm clocks...")
        with gr.Row():
            resolution_radio = gr.Radio(["Full (1920x1080)", "Short (1080x1920)"], label="Video Resolution", value="Full (1920x1080)")
            bg_music_volume_slider = gr.Slider(minimum=0, maximum=0.5, value=0.08, step=0.01, label="Background Music Volume", info="Lower volume keeps narration clear.") # Adjusted max volume


    # --- Caption Settings ---
    with gr.Accordion("Caption Settings", open=False):
        caption_enabled_radio = gr.Radio(["Yes", "No"], label="Show Captions?", value="Yes")
        with gr.Row():
            caption_color_picker = gr.ColorPicker(label="Caption Text Color", value="#FFFFFF") # Default white
            caption_bg_color_picker = gr.ColorPicker(label="Caption Background Color (with transparency)", value="rgba(0, 0, 0, 0.4)") # Default semi-transparent black, slightly more opaque
        with gr.Row():
            caption_size_slider = gr.Slider(minimum=20, maximum=80, value=45, step=1, label="Caption Font Size") # Adjusted max size
            caption_stroke_width_slider = gr.Slider(minimum=0, maximum=5, value=2, step=0.5, label="Caption Stroke Width")
        with gr.Row():
             caption_position_radio = gr.Radio(["Top", "Middle", "Bottom"], label="Caption Position", value="Bottom")
             caption_stroke_color_picker = gr.ColorPicker(label="Caption Stroke Color", value="#000000") # Default black stroke


    generate_script_btn = gr.Button("Generate Script", variant="primary")

    # --- Status and Script Output ---
    status_output = gr.Label(label="Status", value="", visible=True) # Always visible
    # Using Markdown to show raw script content
    script_preview_markdown = gr.Markdown("### Generated Script Preview\n\nScript will appear here...", visible=False) # Initially hidden

    # --- State to hold parsed segments data and run config ---
    segments_state = gr.State([]) # List of segment dictionaries
    run_config_state = gr.State({}) # Dictionary for run configuration

    # --- Dynamic Editing Area (Initially hidden) ---
    # We create MAX_SEGMENTS_FOR_EDITING groups, and show/hide them dynamically
    with gr.Column(visible=False) as editing_area:
        gr.Markdown("### Edit Script Segments")
        gr.Markdown("Review the AI-generated text and media suggestions below. Edit the text and/or upload your own image/video for any segment. If no file is uploaded, AI will fetch media based on the original prompt.")
        for i in range(MAX_SEGMENTS_FOR_EDITING):
            # Use gr.Box for better visual grouping
            with gr.Box(visible=False) as segment_group: # Each group represents one segment
                segment_editing_groups.append(segment_group)
                # Use a Label to display the original prompt - it's non-interactive text
                segment_prompt_label = gr.Label(f"Segment {i+1} Prompt:", show_label=False) # Label will be set by JS
                # We'll update the value of this label using JS/state change

                segment_text = gr.Textbox(label="Narration Text", lines=2, interactive=True)
                segment_text_inputs.append(segment_text)

                segment_file = gr.File(label="Upload Custom Media (Image or Video)", type="filepath", interactive=True)
                segment_file_inputs.append(segment_file)

        generate_video_btn = gr.Button("Generate Video", variant="primary")


    # --- Final Video Output ---
    final_video_output = gr.Video(label="Generated Video", visible=False) # Initially hidden

    # --- Event Handlers ---

    # Generate Script Button Click
    generate_script_btn.click(
        fn=generate_script_and_show_editor,
        inputs=[
            user_concept_input,
            resolution_radio,
            caption_enabled_radio,
            caption_color_picker,
            caption_size_slider,
            caption_position_radio,
            caption_bg_color_picker,
            caption_stroke_color_picker,
            caption_stroke_width_slider
        ],
        outputs=[
            run_config_state, # Update run config state
            status_output, # Update status label
            editing_area, # Show/hide editing area column
            final_video_output, # Hide and clear video output
            # Outputs for dynamic components (visibility and value updates)
            *segment_text_inputs,
            *segment_file_inputs,
            *segment_editing_groups,
            segments_state, # Update segments state
            script_preview_markdown # Update raw script preview
        ]
    )

    # Generate Video Button Click
    generate_video_btn.click(
        fn=generate_video_from_edited,
        inputs=[
            run_config_state, # Pass run config
            segments_state, # Pass the original parsed segments data (needed for original_prompt and duration)
            *segment_text_inputs, # Pass list of edited text values
            *segment_file_inputs, # Pass list of uploaded file paths
            bg_music_volume_slider # Pass background music volume
        ],
        outputs=[status_output, final_video_output] # Yield status updates and final video
    )

    # Add JS to update segment prompt Labels after script generation
    # This JS function reads the segments_state and updates the Labels
    demo.load(
        None,
        None,
        None,
        _js=f"""
        // Define the JS function
        function updateSegmentPromptLabels(segments_data) {{
            console.log("updateSegmentPromptLabels called", segments_data);
            // Gradio stores dynamic component outputs in a flat list.
            // The prompt labels are the first Label component in each segment group.
            // Assuming the order is consistent: [Label_0, Textbox_0, File_0, Label_1, Textbox_1, File_1, ...]
            // We need to find the correct Label element for each segment index.

            // Find all elements that are potentially segment prompt labels
            const all_segment_labels = document.querySelectorAll('.segment_group_box > label.svelte-q5b6g8'); // Find Label elements within segment boxes

            if (!segments_data || segments_data.length === 0) {{
                 // Clear any existing labels if script generation failed or empty
                 all_segment_labels.forEach(label => label.textContent = '');
                 return;
            }}

            for (let i = 0; i < {MAX_SEGMENTS_FOR_EDITING}; i++) {{
                // Assuming the labels correspond directly to the group index
                const promptLabel = all_segment_labels[i]; // Get the i-th potential label

                if (promptLabel) {{
                    if (i < segments_data.length) {{
                        // Update label text with the original prompt
                        promptLabel.textContent = `Segment ${i+1} (Prompt: ${segments_data[i].original_prompt})`;
                        promptLabel.parentElement.style.display = 'block'; // Ensure parent box is visible (redundant if group visibility is set, but safe)
                    }} else {{
                        // Hide label for unused segments
                        promptLabel.textContent = '';
                        promptLabel.parentElement.style.display = 'none'; // Hide parent box
                    }}
                }} else {{
                     console.warn(`Prompt label element not found for segment index ${i}`);
                }}
            }}
        }}
        """
    )

    # Trigger the JS function whenever segments_state changes
    segments_state.change(
        None, # No Python function to call
        segments_state, # The state variable that changed
        None, # No output components to update via Python
        _js="""
        (segments_data) => {
            // Call the JS function defined in demo.load
            updateSegmentPromptLabels(segments_data);
            // Return the segments_data itself if needed for chaining, but here it's not.
            // This function just updates the UI client-side.
            return arguments[0]; // Return original arguments to avoid state getting cleared
        }
        """
    )

# Launch the interface
if __name__ == "__main__":
    # Attempt ImageMagick policy fix on script startup
    # This helps but might still require manual sudo depending on system config
    fix_imagemagick_policy()

    print("Launching Gradio interface...")

    # Check if API keys are still placeholders (unlikely with hardcoded keys, but good practice)
    if PEXELS_API_KEY.startswith('YOUR_PEXELS_API_KEY'):
        print("Warning: PEXELS_API_KEY is not configured. Media search may fail.")
    if OPENROUTER_API_KEY.startswith('YOUR_OPENROUTER_API_KEY'):
        print("Warning: OPENROUTER_API_KEY is not configured. Script generation will fail.")

    demo.launch(share=True) # Set share=True to get a public link