app.py

import os, re, math, uuid, time, shutil, logging, tempfile, threading, requests, numpy as np
from datetime import datetime, timedelta
from collections import Counter

import gradio as gr
import torch
from transformers import GPT2Tokenizer, GPT2LMHeadModel
from keybert import KeyBERT
from TTS.api import TTS
from moviepy.editor import (
    VideoFileClip, AudioFileClip, concatenate_videoclips, concatenate_audioclips,
    CompositeAudioClip, AudioClip, TextClip, CompositeVideoClip, VideoClip, vfx
)

logging.basicConfig(level=logging.INFO, format="%(asctime)s %(levelname)s %(message)s")
logger = logging.getLogger(__name__)

PEXELS_API_KEY = os.getenv("PEXELS_API_KEY")
if not PEXELS_API_KEY:
    raise RuntimeError("Debes definir PEXELS_API_KEY en Variables & secrets")

tokenizer = GPT2Tokenizer.from_pretrained("datificate/gpt2-small-spanish")
gpt2 = GPT2LMHeadModel.from_pretrained("datificate/gpt2-small-spanish").eval()
if tokenizer.pad_token is None:
    tokenizer.pad_token = tokenizer.eos_token
kw_model = KeyBERT("distilbert-base-multilingual-cased")
tts_engine = TTS(model_name="tts_models/es/css10/vits", progress_bar=False, gpu=False)

RESULTS_DIR = "video_results"
os.makedirs(RESULTS_DIR, exist_ok=True)
TASKS = {}

# ───────── helpers ────────────────────────────────────────────────────────────────
def gpt2_script(prompt: str, mx: int = 160) -> str:
    ins = f"Escribe un guion corto, interesante y coherente sobre: {prompt}"
    inp = tokenizer(ins, return_tensors="pt", truncation=True, max_length=512)
    out = gpt2.generate(
        **inp, max_length=mx + inp["input_ids"].shape[1], do_sample=True,
        top_p=0.9, top_k=40, temperature=0.7, no_repeat_ngram_size=3,
        pad_token_id=tokenizer.pad_token_id, eos_token_id=tokenizer.eos_token_id,
    )
    txt = tokenizer.decode(out[0], skip_special_tokens=True)
    return txt.split("sobre:")[-1].strip()[:mx]

def coqui_tts(text: str, path: str):
    text = re.sub(r"[^\w\s.,!?áéíóúñÁÉÍÓÚÑ]", "", text)[:500]
    tts_engine.tts_to_file(text=text, file_path=path)

def keywords(text: str) -> list[str]:
    clean = re.sub(r"[^\w\sáéíóúñÁÉÍÓÚÑ]", "", text.lower())
    try:
        kws = kw_model.extract_keywords(clean, stop_words="spanish", top_n=5)
        return [k.replace(" ", "+") for k, _ in kws if k]
    except Exception:
        words = [w for w in clean.split() if len(w) > 4]
        return [w for w, _ in Counter(words).most_common(5)] or ["nature"]

def pexels_search(q: str, n: int) -> list[dict]:
    r = requests.get(
        "https://api.pexels.com/videos/search",
        headers={"Authorization": PEXELS_API_KEY},
        params={"query": q, "per_page": n, "orientation": "landscape"},
        timeout=20,
    )
    r.raise_for_status()
    return r.json().get("videos", [])

def download(url: str, folder: str) -> str | None:
    name = uuid.uuid4().hex + ".mp4"
    path = os.path.join(folder, name)
    with requests.get(url, stream=True, timeout=60) as r:
        r.raise_for_status()
        with open(path, "wb") as f:
            for chunk in r.iter_content(1024 * 1024):
                f.write(chunk)
    return path if os.path.getsize(path) > 1000 else None

def loop_audio(aclip: AudioFileClip, dur: float) -> AudioFileClip:
    if aclip.duration >= dur:
        return aclip.subclip(0, dur)
    loops = math.ceil(dur / aclip.duration)
    return concatenate_audioclips([aclip] * loops).subclip(0, dur)

def make_subs_clips(script: str, video_w: int, video_h: int, duration: float):
    sentences = [s.strip() for s in re.split(r"[.!?¿¡]", script) if s.strip()]
    total_words = sum(len(s.split()) for s in sentences) or 1
    word_time = duration / total_words
    clips, cursor = [], 0.0
    for sent in sentences:
        n_words = len(sent.split())
        dur = n_words * word_time
        txt_clip = (
            TextClip(sent, fontsize=int(video_h * 0.05), color="white",
                     stroke_color="black", stroke_width=2, method="caption",
                     size=(int(video_w * 0.9), None))
            .set_start(cursor)
            .set_duration(dur)
            .set_position(("center", video_h * 0.85))
        )
        clips.append(txt_clip)
        cursor += dur
    return clips

def make_grain_clip(size: tuple[int, int], duration: float):
    w, h = size
    def frame(_t):
        noise = np.random.randint(0, 256, (h, w, 1), dtype=np.uint8)
        return np.repeat(noise, 3, axis=2)
    return VideoClip(frame, duration=duration).set_opacity(0.15)

# ───────── video builder ──────────────────────────────────────────────────────────
def build_video(text: str, gen_script: bool, music_fp: str | None) -> str:
    tmp = tempfile.mkdtemp()
    script = gpt2_script(text) if gen_script else text.strip()
    voice_path = os.path.join(tmp, "voice.mp3")
    coqui_tts(script, voice_path)
    voice_clip = AudioFileClip(voice_path)
    adur = voice_clip.duration

    vids = []
    for kw in keywords(script):
        if len(vids) >= 8:
            break
        for v in pexels_search(kw, 2):
            best = max(v["video_files"], key=lambda x: x["width"] * x["height"])
            p = download(best["link"], tmp)
            if p:
                vids.append(p)
            if len(vids) >= 8:
                break
    if not vids:
        raise RuntimeError("Sin vídeos disponibles")

    segs, acc = [], 0
    for path in vids:
        if acc >= adur + 2:
            break
        clip = VideoFileClip(path)
        seg = clip.subclip(0, min(8, clip.duration))
        segs.append(seg)
        acc += seg.duration
    base = concatenate_videoclips(segs, method="chain")
    if base.duration < adur:
        loops = math.ceil(adur / base.duration)
        base = concatenate_videoclips([base] * loops, method="chain")
    base = base.subclip(0, adur)

    if music_fp:
        mclip = loop_audio(AudioFileClip(music_fp), adur).volumex(0.2)
        audio = CompositeAudioClip([mclip, voice_clip])
    else:
        audio = voice_clip

    subs = make_subs_clips(script, base.w, base.h, adur)
    grain = make_grain_clip((base.w, base.h), adur)
    final_vid = CompositeVideoClip([base, grain, *subs]).set_audio(audio)

    out_path = os.path.join(tmp, "final.mp4")
    final_vid.write_videofile(out_path, fps=24, codec="libx264", audio_codec="aac", logger=None)
    return out_path

# ───────── async tasks ────────────────────────────────────────────────────────────
def worker(tid: str, mode: str, topic: str, user_script: str, music: str | None):
    try:
        txt = topic if mode == "Generar Guion con IA" else user_script
        res_tmp = build_video(txt, mode == "Generar Guion con IA", music)
        final_path = os.path.join(RESULTS_DIR, f"{tid}.mp4")
        shutil.copy2(res_tmp, final_path)
        TASKS[tid] = {"status": "done", "result": final_path, "ts": datetime.utcnow()}
    except Exception as e:
        TASKS[tid] = {"status": "error", "error": str(e), "ts": datetime.utcnow()}

def submit(mode, topic, user_script, music):
    content = topic if mode == "Generar Guion con IA" else user_script
    if not content.strip():
        return "", "Ingresa texto"
    tid = uuid.uuid4().hex[:8]
    TASKS[tid] = {"status": "processing", "ts": datetime.utcnow()}
    threading.Thread(target=worker, args=(tid, mode, topic, user_script, music), daemon=True).start()
    return tid, f"Tarea {tid} creada"

def check(tid):
    if tid not in TASKS:
        return None, None, "ID inválido"
    info = TASKS[tid]
    stat = info["status"]
    if stat == "processing":
        return None, None, "Procesando..."
    if stat == "error":
        return None, None, f"Error: {info['error']}"
    return info["result"], info["result"], "Vídeo listo 🎉"

# ───────── janitor thread ─────────────────────────────────────────────────────────
def janitor():
    while True:
        now = datetime.utcnow()
        for fname in os.listdir(RESULTS_DIR):
            fpath = os.path.join(RESULTS_DIR, fname)
            try:
                mtime = datetime.utcfromtimestamp(os.path.getmtime(fpath))
                if now - mtime > timedelta(hours=24):
                    os.remove(fpath)
                    for k, v in list(TASKS.items()):
                        if v.get("result") == fpath:
                            del TASKS[k]
            except Exception:
                pass
        time.sleep(3600)

threading.Thread(target=janitor, daemon=True).start()

# ───────── gradio ui ─────────────────────────────────────────────────────────────
with gr.Blocks(title="Generador de Vídeos IA") as demo:
    with gr.Tabs():
        with gr.TabItem("Crear Vídeo"):
            mode = gr.Radio(["Generar Guion con IA", "Usar Mi Guion"], value="Generar Guion con IA")
            topic = gr.Textbox(label="Tema")
            user_script = gr.Textbox(label="Guion Completo", visible=False)
            music = gr.Audio(type="filepath", label="Música (opcional)")
            btn = gr.Button("Generar")
            tid_out = gr.Textbox(label="ID de tarea")
            msg = gr.Textbox(label="Estado")
        with gr.TabItem("Revisar Estado"):
            tid_in = gr.Textbox(label="ID de tarea")
            chk = gr.Button("Verificar")
            vid = gr.Video()
            dlf = gr.File()

    mode.change(
        lambda m: (gr.update(visible=m == "Generar Guion con IA"), gr.update(visible=m != "Generar Guion con IA")),
        mode, [topic, user_script]
    )
    btn.click(submit, [mode, topic, user_script, music], [tid_out, msg])
    chk.click(check, tid_in, [vid, dlf, msg])

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