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app (1).py

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+
+
+# Import necessary libraries
+from kokoro import KPipeline
+
+import soundfile as sf
+import torch
+
+import soundfile as sf
+import os
+from moviepy.editor import VideoFileClip, AudioFileClip, ImageClip
+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 gradio as gr
+import shutil
+import os
+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
+import pysrt
+from gtts import gTTS
+import gradio as gr  # Import Gradio
+
+# Initialize Kokoro TTS pipeline (using American English)
+pipeline = KPipeline(lang_code='a')  # Use voice 'af_heart' for American English
+# Ensure ImageMagick binary is set
+mpy_config.change_settings({"IMAGEMAGICK_BINARY": "/usr/bin/convert"})
+
+# ---------------- Global Configuration ---------------- #
+PEXELS_API_KEY = 'BhJqbcdm9Vi90KqzXKAhnEHGsuFNv4irXuOjWtT761U49lRzo03qBGna'
+OPENROUTER_API_KEY = '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'
+OPENROUTER_MODEL = "moonshotai/kimi-k2:free"
+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"
+
+
+
+# Additional global variables needed for the Gradio interface
+selected_voice = 'af_heart'  # Default voice
+voice_speed = 0.9  # Default voice speed
+font_size = 45  # Default font size
+video_clip_probability = 0.25  # Default probability for video clips
+bg_music_volume = 0.08  # Default background music volume
+fps = 30  # Default FPS
+preset = "veryfast"  # Default preset
+TARGET_RESOLUTION = None
+CAPTION_COLOR = None
+TEMP_FOLDER = None
+
+
+# ---------------- Helper Functions ---------------- #
+# (Your existing helper functions remain unchanged: generate_script, parse_script,
+# search_pexels_videos, search_pexels_images, search_google_images, download_image,
+# download_video, generate_media, generate_tts, apply_kenburns_effect,
+# resize_to_fill, find_mp3_files, add_background_music, create_clip,
+# fix_imagemagick_policy)
+
+# Define these globally as they were in your original code but will be set per run
+TARGET_RESOLUTION = None
+CAPTION_COLOR = None
+TEMP_FOLDER = None
+
+def generate_script(user_input):
+    """Generate documentary script with proper OpenRouter handling."""
+    headers = {
+        'Authorization': f'Bearer {OPENROUTER_API_KEY}',
+        'HTTP-Referer': 'https://your-domain.com',
+        'X-Title': 'AI Documentary Maker'
+    }
+
+    prompt = f"""You're a professional documentary narrator. Your job is to write a serious, natural, and informative video script based on one topic.
+
+The script should sound like a real human voiceover from a TV show or documentary — clear, factual, and engaging, like something you'd hear on National Geographic or a news report.
+
+Structure:
+- Break the script into scenes using [Tags]. Each tag is a short title (1–2 words) that describes the visual or idea.
+- Under each tag, write one sentence (max 12 words) that fits the tag and continues the topic.
+- The full script should make sense as one connected narration — no randomness.
+- Use natural, formal English. No slang, no fake AI language, and no robotic tone.
+- Do not use humor, sarcasm, or casual language. This is a serious narration.
+- No emotion-sound words like “aww,” “eww,” “whoa,” etc.
+- Do not use numbers like 1, 2, 3 — write them out as one, two, three.
+- At the end, add a [Subscribe] tag with a formal or respectful reason to follow or subscribe.
+
+Only output the script. No extra comments or text.
+
+Example:
+
+[Ocean]
+
+The ocean covers over seventy percent of the Earth's surface.
+
+[Currents]
+
+Ocean currents distribute heat and regulate global climate patterns.
+
+[Coral Reefs]
+
+These ecosystems support over one million species of marine life.
+
+[Pollution]
+
+Plastic waste threatens marine biodiversity and food chains.
+
+[Climate Impact]
+
+Rising temperatures are causing coral bleaching and habitat loss.
+
+[Subscribe]
+
+Follow to explore more about the changing planet we live on.
+
+
+
+Now here is the Topic/scrip: {user_input}
+"""
+
+    data = {
+        'model': OPENROUTER_MODEL,
+        'messages': [{'role': 'user', 'content': prompt}],
+        'temperature': 0.4,
+        'max_tokens': 5000
+    }
+
+    try:
+        response = requests.post(
+            'https://openrouter.ai/api/v1/chat/completions',
+            headers=headers,
+            json=data,
+            timeout=30
+        )
+
+        if response.status_code == 200:
+            response_data = response.json()
+            if 'choices' in response_data and len(response_data['choices']) > 0:
+                return response_data['choices'][0]['message']['content']
+            else:
+                print("Unexpected response format:", response_data)
+                return None
+        else:
+            print(f"API Error {response.status_code}: {response.text}")
+            return None
+
+    except Exception as e:
+        print(f"Request failed: {str(e)}")
+        return None
+
+def parse_script(script_text):
+    """
+    Parse the generated script into a list of elements.
+    For each section, create two elements:
+      - A 'media' element using the section title as the visual prompt.
+      - A 'tts' element with the narration text, voice info, and computed duration.
+    """
+    sections = {}
+    current_title = None
+    current_text = ""
+
+    try:
+        for line in script_text.splitlines():
+            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:
+                    if current_title is not None:
+                        sections[current_title] = current_text.strip()
+                    current_title = line[bracket_start+1:bracket_end]
+                    current_text = line[bracket_end+1:].strip()
+            elif current_title:
+                current_text += line + " "
+
+        if current_title:
+            sections[current_title] = current_text.strip()
+
+        elements = []
+        for title, narration in sections.items():
+            if not title or not narration:
+                continue
+
+            media_element = {"type": "media", "prompt": title, "effects": "fade-in"}
+            words = narration.split()
+            duration = max(3, len(words) * 0.5)
+            tts_element = {"type": "tts", "text": narration, "voice": "en", "duration": duration}
+            elements.append(media_element)
+            elements.append(tts_element)
+
+        return elements
+    except Exception as e:
+        print(f"Error parsing script: {e}")
+        return []
+
+def search_pexels_videos(query, pexels_api_key):
+    """Search for a video on Pexels by query and return a random HD video."""
+    headers = {'Authorization': pexels_api_key}
+    base_url = "https://api.pexels.com/videos/search"
+    num_pages = 3
+    videos_per_page = 15
+
+    max_retries = 3
+    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", [])
+
+                    if not videos:
+                        print(f"No videos found on page {page}.")
+                        break
+
+                    for video in videos:
+                        video_files = video.get("video_files", [])
+                        for file in video_files:
+                            if file.get("quality") == "hd":
+                                all_videos.append(file.get("link"))
+                                break
+
+                    break
+
+                elif response.status_code == 429:
+                    print(f"Rate limit hit (attempt {attempt+1}/{max_retries}). Retrying in {retry_delay} seconds...")
+                    time.sleep(retry_delay)
+                    retry_delay *= 2
+                else:
+                    print(f"Error fetching videos: {response.status_code} {response.text}")
+                    if attempt < max_retries - 1:
+                        print(f"Retrying in {retry_delay} seconds...")
+                        time.sleep(retry_delay)
+                        retry_delay *= 2
+                    else:
+                        break
+
+            except requests.exceptions.RequestException as e:
+                print(f"Request exception: {e}")
+                if attempt < max_retries - 1:
+                    print(f"Retrying in {retry_delay} seconds...")
+                    time.sleep(retry_delay)
+                    retry_delay *= 2
+                else:
+                    break
+
+    if all_videos:
+        random_video = random.choice(all_videos)
+        print(f"Selected random video from {len(all_videos)} HD videos")
+        return random_video
+    else:
+        print("No suitable videos found after searching all pages.")
+        return None
+
+def search_pexels_images(query, pexels_api_key):
+    """Search for an image on Pexels by query."""
+    headers = {'Authorization': pexels_api_key}
+    url = "https://api.pexels.com/v1/search"
+    params = {"query": query, "per_page": 5, "orientation": "landscape"}
+
+    max_retries = 3
+    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:
+                    photo = random.choice(photos[:min(5, len(photos))])
+                    img_url = photo.get("src", {}).get("original")
+                    return img_url
+                else:
+                    print(f"No images found for query: {query}")
+                    return None
+
+            elif response.status_code == 429:
+                print(f"Rate limit hit (attempt {attempt+1}/{max_retries}). Retrying in {retry_delay} seconds...")
+                time.sleep(retry_delay)
+                retry_delay *= 2
+            else:
+                print(f"Error fetching images: {response.status_code} {response.text}")
+                if attempt < max_retries - 1:
+                    print(f"Retrying in {retry_delay} seconds...")
+                    time.sleep(retry_delay)
+                    retry_delay *= 2
+
+        except requests.exceptions.RequestException as e:
+            print(f"Request exception: {e}")
+            if attempt < max_retries - 1:
+                print(f"Retrying in {retry_delay} seconds...")
+                time.sleep(retry_delay)
+                retry_delay *= 2
+
+    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 (for news-related queries)"""
+    try:
+        search_url = f"https://www.google.com/search?q={quote(query)}&tbm=isch"
+        headers = {"User-Agent": USER_AGENT}
+        response = requests.get(search_url, headers=headers, timeout=10)
+        soup = BeautifulSoup(response.text, "html.parser")
+
+        img_tags = soup.find_all("img")
+        image_urls = []
+        for img in img_tags:
+            src = img.get("src", "")
+            if src.startswith("http") and "gstatic" not in src:
+                image_urls.append(src)
+
+        if image_urls:
+            return random.choice(image_urls[:5]) if len(image_urls) >= 5 else image_urls[0]
+        else:
+            print(f"No Google Images found for query: {query}")
+            return None
+    except Exception as e:
+        print(f"Error in Google Images search: {e}")
+        return None
+
+def download_image(image_url, filename):
+    """Download an image from a URL to a local file with enhanced error handling."""
+    try:
+        headers = {"User-Agent": USER_AGENT}
+        print(f"Downloading image from: {image_url} to {filename}")
+        response = requests.get(image_url, headers=headers, stream=True, timeout=15)
+        response.raise_for_status()
+
+        with open(filename, 'wb') as f:
+            for chunk in response.iter_content(chunk_size=8192):
+                f.write(chunk)
+
+        print(f"Image downloaded successfully to: {filename}")
+
+        try:
+            img = Image.open(filename)
+            img.verify()
+            img = Image.open(filename)
+            if img.mode != 'RGB':
+                img = img.convert('RGB')
+                img.save(filename)
+            print(f"Image validated and processed: {filename}")
+            return filename
+        except Exception as e_validate:
+            print(f"Downloaded file is not a valid image: {e_validate}")
+            if os.path.exists(filename):
+                os.remove(filename)
+            return None
+
+    except requests.exceptions.RequestException as e_download:
+        print(f"Image download error: {e_download}")
+        if os.path.exists(filename):
+            os.remove(filename)
+        return None
+    except Exception as e_general:
+        print(f"General error during image processing: {e_general}")
+        if os.path.exists(filename):
+            os.remove(filename)
+        return None
+
+def download_video(video_url, filename):
+    """Download a video from a URL to a local file."""
+    try:
+        response = requests.get(video_url, stream=True, timeout=30)
+        response.raise_for_status()
+        with open(filename, 'wb') as f:
+            for chunk in response.iter_content(chunk_size=8192):
+                f.write(chunk)
+        print(f"Video downloaded successfully to: {filename}")
+        return filename
+    except Exception as e:
+        print(f"Video download error: {e}")
+        if os.path.exists(filename):
+            os.remove(filename)
+        return None
+
+def generate_media(prompt, user_image=None, current_index=0, total_segments=1):
+    """
+    Generate a visual asset by first searching for a video or using a specific search strategy.
+    For news-related queries, use Google Images.
+    Returns a dict: {'path': <file_path>, 'asset_type': 'video' or 'image'}.
+    """
+    safe_prompt = re.sub(r'[^\w\s-]', '', prompt).strip().replace(' ', '_')
+
+    if "news" in prompt.lower():
+        print(f"News-related query detected: {prompt}. Using Google Images...")
+        image_file = os.path.join(TEMP_FOLDER, f"{safe_prompt}_news.jpg")
+        image_url = search_google_images(prompt)
+        if image_url:
+            downloaded_image = download_image(image_url, image_file)
+            if downloaded_image:
+                print(f"News image saved to {downloaded_image}")
+                return {"path": downloaded_image, "asset_type": "image"}
+        else:
+            print(f"Google Images search failed for prompt: {prompt}")
+
+    if random.random() < video_clip_probability:
+        video_file = os.path.join(TEMP_FOLDER, f"{safe_prompt}_video.mp4")
+        video_url = search_pexels_videos(prompt, PEXELS_API_KEY)
+        if video_url:
+            downloaded_video = download_video(video_url, video_file)
+            if downloaded_video:
+                print(f"Video asset saved to {downloaded_video}")
+                return {"path": downloaded_video, "asset_type": "video"}
+        else:
+            print(f"Pexels video search failed for prompt: {prompt}")
+
+    image_file = os.path.join(TEMP_FOLDER, f"{safe_prompt}.jpg")
+    image_url = search_pexels_images(prompt, PEXELS_API_KEY)
+    if image_url:
+        downloaded_image = download_image(image_url, image_file)
+        if downloaded_image:
+            print(f"Image asset saved to {downloaded_image}")
+            return {"path": downloaded_image, "asset_type": "image"}
+        else:
+            print(f"Pexels image download failed for prompt: {prompt}")
+
+    fallback_terms = ["nature", "people", "landscape", "technology", "business"]
+    for term in fallback_terms:
+        print(f"Trying fallback image search with term: {term}")
+        fallback_file = os.path.join(TEMP_FOLDER, f"fallback_{term}.jpg")
+        fallback_url = search_pexels_images(term, PEXELS_API_KEY)
+        if fallback_url:
+            downloaded_fallback = download_image(fallback_url, fallback_file)
+            if downloaded_fallback:
+                print(f"Fallback image saved to {downloaded_fallback}")
+                return {"path": downloaded_fallback, "asset_type": "image"}
+            else:
+                print(f"Fallback image download failed for term: {term}")
+        else:
+            print(f"Fallback image search failed for term: {term}")
+
+    print(f"Failed to generate visual asset for prompt: {prompt}")
+    return None
+
+def generate_silent_audio(duration, sample_rate=24000):
+    """Generate a silent WAV audio file lasting 'duration' seconds."""
+    num_samples = int(duration * sample_rate)
+    silence = np.zeros(num_samples, dtype=np.float32)
+    silent_path = os.path.join(TEMP_FOLDER, f"silent_{int(time.time())}.wav")
+    sf.write(silent_path, silence, sample_rate)
+    print(f"Silent audio generated: {silent_path}")
+    return silent_path
+
+def generate_tts(text, voice):
+    """
+    Generate TTS audio using Kokoro, falling back to gTTS or silent audio if needed.
+    """
+    safe_text = re.sub(r'[^\w\s-]', '', text[:10]).strip().replace(' ', '_')
+    file_path = os.path.join(TEMP_FOLDER, f"tts_{safe_text}.wav")
+
+    if os.path.exists(file_path):
+        print(f"Using cached TTS for text '{text[:10]}...'")
+        return file_path
+
+    try:
+        kokoro_voice = selected_voice if voice == 'en' else voice
+        generator = pipeline(text, voice=kokoro_voice, speed=voice_speed, split_pattern=r'\n+')
+        audio_segments = []
+        for i, (gs, ps, audio) in enumerate(generator):
+            audio_segments.append(audio)
+        full_audio = np.concatenate(audio_segments) if len(audio_segments) > 1 else audio_segments[0]
+        sf.write(file_path, full_audio, 24000)
+        print(f"TTS audio saved to {file_path} (Kokoro)")
+        return file_path
+    except Exception as e:
+        print(f"Error with Kokoro TTS: {e}")
+        try:
+            print("Falling back to gTTS...")
+            tts = gTTS(text=text, lang='en')
+            mp3_path = os.path.join(TEMP_FOLDER, f"tts_{safe_text}.mp3")
+            tts.save(mp3_path)
+            audio = AudioSegment.from_mp3(mp3_path)
+            audio.export(file_path, format="wav")
+            os.remove(mp3_path)
+            print(f"Fallback TTS saved to {file_path} (gTTS)")
+            return file_path
+        except Exception as fallback_error:
+            print(f"Both TTS methods failed: {fallback_error}")
+            return generate_silent_audio(duration=max(3, len(text.split()) * 0.5))
+
+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
+
+    if clip_aspect > target_aspect:
+        new_height = target_h
+        new_width = int(new_height * clip_aspect)
+    else:
+        new_width = target_w
+        new_height = int(new_width / clip_aspect)
+
+    clip = clip.resize(newsize=(new_width, new_height))
+    base_scale = 1.15
+    new_width = int(new_width * base_scale)
+    new_height = int(new_height * base_scale)
+    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", "up-left"]
+    if effect_type is None or effect_type == "random":
+        effect_type = random.choice(available_effects)
+
+    if effect_type == "zoom-in":
+        start_zoom = 0.9
+        end_zoom = 1.1
+        start_center = (new_width / 2, new_height / 2)
+        end_center = start_center
+    elif effect_type == "zoom-out":
+        start_zoom = 1.1
+        end_zoom = 0.9
+        start_center = (new_width / 2, new_height / 2)
+        end_center = start_center
+    elif effect_type == "pan-left":
+        start_zoom = 1.0
+        end_zoom = 1.0
+        start_center = (max_offset_x + target_w / 2, (max_offset_y // 2) + target_h / 2)
+        end_center = (target_w / 2, (max_offset_y // 2) + target_h / 2)
+    elif effect_type == "pan-right":
+        start_zoom = 1.0
+        end_zoom = 1.0
+        start_center = (target_w / 2, (max_offset_y // 2) + target_h / 2)
+        end_center = (max_offset_x + target_w / 2, (max_offset_y // 2) + target_h / 2)
+    elif effect_type == "up-left":
+        start_zoom = 1.0
+        end_zoom = 1.0
+        start_center = (max_offset_x + target_w / 2, max_offset_y + target_h / 2)
+        end_center = (target_w / 2, target_h / 2)
+    else:
+        raise ValueError(f"Unsupported effect_type: {effect_type}")
+
+    def transform_frame(get_frame, t):
+        frame = get_frame(t)
+        ratio = t / clip.duration if clip.duration > 0 else 0
+        ratio = 0.5 - 0.5 * math.cos(math.pi * ratio)
+        current_zoom = start_zoom + (end_zoom - start_zoom) * ratio
+        crop_w = int(target_w / current_zoom)
+        crop_h = int(target_h / current_zoom)
+        current_center_x = start_center[0] + (end_center[0] - start_center[0]) * ratio
+        current_center_y = start_center[1] + (end_center[1] - start_center[1]) * ratio
+        min_center_x = crop_w / 2
+        max_center_x = new_width - crop_w / 2
+        min_center_y = crop_h / 2
+        max_center_y = new_height - crop_h / 2
+        current_center_x = max(min_center_x, min(current_center_x, max_center_x))
+        current_center_y = max(min_center_y, min(current_center_y, max_center_y))
+        cropped_frame = cv2.getRectSubPix(frame, (crop_w, crop_h), (current_center_x, current_center_y))
+        resized_frame = cv2.resize(cropped_frame, (target_w, target_h), interpolation=cv2.INTER_LANCZOS4)
+        return resized_frame
+
+    return clip.fl(transform_frame)
+
+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
+
+    if clip_aspect > target_aspect:
+        clip = clip.resize(height=target_h)
+        crop_amount = (clip.w - target_w) / 2
+        clip = clip.crop(x1=crop_amount, x2=clip.w - crop_amount, y1=0, y2=clip.h)
+    else:
+        clip = clip.resize(width=target_w)
+        crop_amount = (clip.h - target_h) / 2
+        clip = clip.crop(x1=0, x2=clip.w, y1=crop_amount, y2=clip.h - crop_amount)
+
+    return clip
+
+def find_mp3_files():
+    """Search for any MP3 files in the current directory and subdirectories."""
+    mp3_files = []
+    for root, dirs, files in os.walk('.'):
+        for file in files:
+            if file.endswith('.mp3'):
+                mp3_path = os.path.join(root, file)
+                mp3_files.append(mp3_path)
+                print(f"Found MP3 file: {mp3_path}")
+    return mp3_files[0] if mp3_files else None
+
+def add_background_music(final_video, bg_music_volume=0.10):
+    """Add background music to the final video using any MP3 file found."""
+    try:
+        bg_music_path = "music.mp3"
+        if bg_music_path and os.path.exists(bg_music_path):
+            print(f"Adding background music from: {bg_music_path}")
+            bg_music = AudioFileClip(bg_music_path)
+            if bg_music.duration < final_video.duration:
+                loops_needed = math.ceil(final_video.duration / bg_music.duration)
+                bg_segments = [bg_music] * loops_needed
+                bg_music = concatenate_audioclips(bg_segments)
+            bg_music = bg_music.subclip(0, final_video.duration)
+            bg_music = bg_music.volumex(bg_music_volume)
+            video_audio = final_video.audio
+            mixed_audio = CompositeAudioClip([video_audio, bg_music])
+            final_video = final_video.set_audio(mixed_audio)
+            print("Background music added successfully")
+        else:
+            print("No MP3 files found, skipping background music")
+        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_path, asset_type, tts_path, duration=None, effects=None, narration_text=None, segment_index=0):
+    """Create a video clip with synchronized subtitles and narration."""
+    try:
+        print(f"Creating clip #{segment_index} with asset_type: {asset_type}, media_path: {media_path}")
+        if not os.path.exists(media_path) or not os.path.exists(tts_path):
+            print("Missing media or TTS file")
+            return None
+
+        audio_clip = AudioFileClip(tts_path).audio_fadeout(0.2)
+        audio_duration = audio_clip.duration
+        target_duration = audio_duration + 0.2
+
+        if asset_type == "video":
+            clip = VideoFileClip(media_path)
+            clip = resize_to_fill(clip, TARGET_RESOLUTION)
+            if clip.duration < target_duration:
+                clip = clip.loop(duration=target_duration)
+            else:
+                clip = clip.subclip(0, target_duration)
+        elif asset_type == "image":
+            img = Image.open(media_path)
+            if img.mode != 'RGB':
+                with tempfile.NamedTemporaryFile(suffix='.jpg', delete=False) as temp:
+                    img.convert('RGB').save(temp.name)
+                    media_path = temp.name
+                img.close()
+            clip = ImageClip(media_path).set_duration(target_duration)
+            clip = apply_kenburns_effect(clip, TARGET_RESOLUTION)
+            clip = clip.fadein(0.3).fadeout(0.3)
+        else:
+            return None
+
+        if narration_text and CAPTION_COLOR != "transparent":
+            try:
+                words = narration_text.split()
+                chunks = []
+                current_chunk = []
+                for word in words:
+                    current_chunk.append(word)
+                    if len(current_chunk) >= 5:
+                        chunks.append(' '.join(current_chunk))
+                        current_chunk = []
+                if current_chunk:
+                    chunks.append(' '.join(current_chunk))
+
+                chunk_duration = audio_duration / len(chunks)
+                subtitle_clips = []
+                subtitle_y_position = int(TARGET_RESOLUTION[1] * 0.70)
+
+                for i, chunk_text in enumerate(chunks):
+                    start_time = i * chunk_duration
+                    end_time = (i + 1) * chunk_duration
+                    txt_clip = TextClip(
+                        chunk_text,
+                        fontsize=45,
+                        font='Arial-Bold',
+                        color=CAPTION_COLOR,
+                        bg_color='rgba(0, 0, 0, 0.25)',
+                        method='caption',
+                        align='center',
+                        stroke_width=2,
+                        stroke_color=CAPTION_COLOR,
+                        size=(TARGET_RESOLUTION[0] * 0.8, None)
+                    ).set_start(start_time).set_end(end_time)
+                    txt_clip = txt_clip.set_position(('center', subtitle_y_position))
+                    subtitle_clips.append(txt_clip)
+
+                clip = CompositeVideoClip([clip] + subtitle_clips)
+            except Exception as sub_error:
+                print(f"Subtitle error: {sub_error}")
+                txt_clip = TextClip(
+                    narration_text,
+                    fontsize=font_size,
+                    color=CAPTION_COLOR,
+                    align='center',
+                    size=(TARGET_RESOLUTION[0] * 0.7, None)
+                ).set_position(('center', int(TARGET_RESOLUTION[1] / 3))).set_duration(clip.duration)
+                clip = CompositeVideoClip([clip, txt_clip])
+
+        clip = clip.set_audio(audio_clip)
+        print(f"Clip created: {clip.duration:.1f}s")
+        return clip
+    except Exception as e:
+        print(f"Error in create_clip: {str(e)}")
+        return None
+
+def fix_imagemagick_policy():
+    """Fix ImageMagick security policies."""
+    try:
+        print("Attempting to fix ImageMagick security policies...")
+        policy_paths = [
+            "/etc/ImageMagick-6/policy.xml",
+            "/etc/ImageMagick-7/policy.xml",
+            "/etc/ImageMagick/policy.xml",
+            "/usr/local/etc/ImageMagick-7/policy.xml"
+        ]
+        found_policy = next((path for path in policy_paths if os.path.exists(path)), None)
+        if not found_policy:
+            print("No policy.xml found. Using alternative subtitle method.")
+            return False
+        print(f"Modifying policy file at {found_policy}")
+        os.system(f"sudo cp {found_policy} {found_policy}.bak")
+        os.system(f"sudo sed -i 's/rights=\"none\"/rights=\"read|write\"/g' {found_policy}")
+        os.system(f"sudo sed -i 's/<policy domain=\"path\" pattern=\"@\*\"[^>]*>/<policy domain=\"path\" pattern=\"@*\" rights=\"read|write\"/g' {found_policy}")
+        os.system(f"sudo sed -i 's/<policy domain=\"coder\" rights=\"none\" pattern=\"PDF\"[^>]*>/<!-- <policy domain=\"coder\" rights=\"none\" pattern=\"PDF\"> -->/g' {found_policy}")
+        print("ImageMagick policies updated successfully.")
+        return True
+    except Exception as e:
+        print(f"Error fixing policies: {e}")
+        return False
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+# ---------------- Main Video Generation Function ---------------- #
+def generate_video(user_input, resolution, caption_option):
+    """Generate a video based on user input via Gradio."""
+    global TARGET_RESOLUTION, CAPTION_COLOR, TEMP_FOLDER
+    
+    # Set resolution
+    if resolution == "Full":
+        TARGET_RESOLUTION = (1920, 1080)
+    elif resolution == "Short":
+        TARGET_RESOLUTION = (1080, 1920)
+    else:
+        TARGET_RESOLUTION = (1920, 1080)  # Default
+
+    # Set caption color
+    CAPTION_COLOR = "white" if caption_option == "Yes" else "transparent"
+
+    # Create a unique temporary folder
+    TEMP_FOLDER = tempfile.mkdtemp()
+
+    # Fix ImageMagick policy
+    fix_success = fix_imagemagick_policy()
+    if not fix_success:
+        print("Will use alternative methods if needed")
+
+    print("Generating script from API...")
+    script = generate_script(user_input)
+    if not script:
+        print("Failed to generate script.")
+        shutil.rmtree(TEMP_FOLDER)
+        return None
+    print("Generated Script:\n", script)
+    elements = parse_script(script)
+    if not elements:
+        print("Failed to parse script into elements.")
+        shutil.rmtree(TEMP_FOLDER)
+        return None
+    print(f"Parsed {len(elements)//2} script segments.")
+
+    paired_elements = []
+    for i in range(0, len(elements), 2):
+        if i + 1 < len(elements):
+            paired_elements.append((elements[i], elements[i + 1]))
+
+    if not paired_elements:
+        print("No valid script segments found.")
+        shutil.rmtree(TEMP_FOLDER)
+        return None
+
+    clips = []
+    for idx, (media_elem, tts_elem) in enumerate(paired_elements):
+        print(f"\nProcessing segment {idx+1}/{len(paired_elements)} with prompt: '{media_elem['prompt']}'")
+        media_asset = generate_media(media_elem['prompt'], current_index=idx, total_segments=len(paired_elements))
+        if not media_asset:
+            print(f"Skipping segment {idx+1} due to missing media asset.")
+            continue
+        tts_path = generate_tts(tts_elem['text'], tts_elem['voice'])
+        if not tts_path:
+            print(f"Skipping segment {idx+1} due to TTS generation failure.")
+            continue
+        clip = create_clip(
+            media_path=media_asset['path'],
+            asset_type=media_asset['asset_type'],
+            tts_path=tts_path,
+            duration=tts_elem['duration'],
+            effects=media_elem.get('effects', 'fade-in'),
+            narration_text=tts_elem['text'],
+            segment_index=idx
+        )
+        if clip:
+            clips.append(clip)
+        else:
+            print(f"Clip creation failed for segment {idx+1}.")
+
+    if not clips:
+        print("No clips were successfully created.")
+        shutil.rmtree(TEMP_FOLDER)
+        return None
+
+    print("\nConcatenating clips...")
+    final_video = concatenate_videoclips(clips, method="compose")
+    final_video = add_background_music(final_video, bg_music_volume=bg_music_volume)
+
+    print(f"Exporting final video to {OUTPUT_VIDEO_FILENAME}...")
+    final_video.write_videofile(OUTPUT_VIDEO_FILENAME, codec='libx264', fps=fps, preset=preset)
+    print(f"Final video saved as {OUTPUT_VIDEO_FILENAME}")
+
+    # Clean up
+    print("Cleaning up temporary files...")
+    shutil.rmtree(TEMP_FOLDER)
+    print("Temporary files removed.")
+
+    return OUTPUT_VIDEO_FILENAME
+
+# ---------------- Gradio Interface ---------------- #
+VOICE_CHOICES = {
+    'Emma (Female)': 'af_heart',
+    'Bella (Female)': 'af_bella',
+    'Nicole (Female)': 'af_nicole',
+    'Aoede (Female)': 'af_aoede',
+    'Kore (Female)': 'af_kore',
+    'Sarah (Female)': 'af_sarah',
+    'Nova (Female)': 'af_nova',
+    'Sky (Female)': 'af_sky',
+    'Alloy (Female)': 'af_alloy',
+    'Jessica (Female)': 'af_jessica',
+    'River (Female)': 'af_river',
+    'Michael (Male)': 'am_michael',
+    'Fenrir (Male)': 'am_fenrir',
+    'Puck (Male)': 'am_puck',
+    'Echo (Male)': 'am_echo',
+    'Eric (Male)': 'am_eric',
+    'Liam (Male)': 'am_liam',
+    'Onyx (Male)': 'am_onyx',
+    'Santa (Male)': 'am_santa',
+    'Adam (Male)': 'am_adam',
+    'Emma 🇬🇧 (Female)': 'bf_emma',
+    'Isabella 🇬🇧 (Female)': 'bf_isabella',
+    'Alice 🇬🇧 (Female)': 'bf_alice',
+    'Lily 🇬🇧 (Female)': 'bf_lily',
+    'George 🇬🇧 (Male)': 'bm_george',
+    'Fable 🇬🇧 (Male)': 'bm_fable',
+    'Lewis 🇬🇧 (Male)': 'bm_lewis',
+    'Daniel 🇬🇧 (Male)': 'bm_daniel'
+}
+
+def generate_video_with_options(user_input, resolution, caption_option, music_file, voice, vclip_prob, bg_vol, video_fps, video_preset, v_speed, caption_size):
+    global selected_voice, voice_speed, font_size, video_clip_probability, bg_music_volume, fps, preset
+    
+    # Update global variables with user selections
+    selected_voice = VOICE_CHOICES[voice]
+    voice_speed = v_speed
+    font_size = caption_size
+    video_clip_probability = vclip_prob / 100  # Convert from percentage to decimal
+    bg_music_volume = bg_vol
+    fps = video_fps
+    preset = video_preset
+    
+    # Handle music upload
+    if music_file is not None:
+        target_path = "music.mp3"
+        shutil.copy(music_file.name, target_path)
+        print(f"Uploaded music saved as: {target_path}")
+    
+    # Generate the video
+    return generate_video(user_input, resolution, caption_option)
+
+# Create the Gradio interface
+iface = gr.Interface(
+    fn=generate_video_with_options,
+    inputs=[
+        gr.Textbox(label="Video Concept", placeholder="Enter your video concept here..."),
+        gr.Radio(["Full", "Short"], label="Resolution", value="Full"),
+        gr.Radio(["No"], label="Captions (Coming Soon)", value="No"),
+        gr.File(label="Upload Background Music (MP3)", file_types=[".mp3"]),
+        gr.Dropdown(choices=list(VOICE_CHOICES.keys()), label="Choose Voice", value="Emma (Female)"),
+        gr.Slider(0, 100, value=25, step=1, label="Video Clip Usage Probability (%)"),
+        gr.Slider(0.0, 1.0, value=0.08, step=0.01, label="Background Music Volume"),
+        gr.Slider(10, 60, value=30, step=1, label="Video FPS"),
+        gr.Dropdown(choices=["ultrafast", "superfast", "veryfast", "faster", "fast", "medium", "slow"], 
+                   value="veryfast", label="Export Preset"),
+        gr.Slider(0.5, 1.5, value=1.2, step=0.05, label="Voice Speed"),
+        gr.Slider(20, 100, value=45, step=1, label="Caption Font Size")
+    ],
+    outputs=gr.Video(label="Generated Video"),
+    title="AI Documentary Video Generator",
+    description="Create short documentary videos with AI. Upload music, choose voice, and customize settings."
+)
+
+# Launch the interface
+if __name__ == "__main__":
+    iface.launch(share=True)

packages.txt

@@ -0,0 +1,3 @@
+imagemagick
+espeak-ng
+python3-opencv

requirements (1).txt

@@ -0,0 +1,12 @@
+gradio
+transformers==4.49.0
+moviepy==1.0.3
+gTTS
+requests
+pydub
+pillow
+kokoro>=0.3.4
+soundfile
+pysrt
+opencv-python-headless
+beautifulsoup4