app.py

import os
import json
import time
import requests
from flask import Flask, request, jsonify, render_template
from flask_cors import CORS
import logging
import threading
from huggingface_hub import HfApi, hf_hub_download
from huggingface_hub.utils import RepositoryNotFoundError, EntryNotFoundError
import tempfile

# --- تنظیمات اصلی ---
DATASET_REPO = "Ezmary/Karbaran-rayegan-tedad"
DATASET_FILENAME = "video_usage_data.json" 
USAGE_LIMIT = 5
HF_TOKEN = os.environ.get("HF_TOKEN")
TEMP_DIR = "/app/tmp" 

# ✅✅✅ آدرس ورودی اصلی (مسیریاب) که از متغیرهای راز خوانده می‌شود
ROUTER_WORKER_URL = os.environ.get("ROUTER_WORKER_URL")

# --- تنظیمات لاگینگ ---
# فقط پیام لاگ نمایش داده می‌شود
for handler in logging.root.handlers[:]:
    logging.root.removeHandler(handler)
logging.basicConfig(level=logging.INFO, format='%(message)s')

# ساکت کردن لاگ‌های کتابخانه‌های پرحرف
logging.getLogger('huggingface_hub').setLevel(logging.ERROR)
logging.getLogger('gunicorn.error').setLevel(logging.WARNING)
logging.getLogger('werkzeug').setLevel(logging.ERROR)
logging.getLogger("urllib3").setLevel(logging.WARNING)

app = Flask(__name__)
CORS(app)

# --- مدیریت داده‌های کاربران و قفل‌ها ---
usage_data_cache = []
cache_lock = threading.Lock()
data_changed = threading.Event()
persistence_lock = threading.Lock()
api = None

if HF_TOKEN:
    api = HfApi(token=HF_TOKEN)

# بررسی وجود آدرس مسیریاب در هنگام شروع به کار
if not ROUTER_WORKER_URL:
    logging.error("❌ CRITICAL ERROR: The ROUTER_WORKER_URL environment variable is not set!")
else:
    logging.info(f"✅ Main app is configured to use the router at: {ROUTER_WORKER_URL}")

# --- توابع مدیریت داده (بدون تغییر) ---
def load_initial_data():
    global usage_data_cache
    with cache_lock:
        if not api: return
        try:
            with tempfile.TemporaryDirectory(dir=TEMP_DIR) as tmp_download_dir:
                local_path = hf_hub_download(
                    repo_id=DATASET_REPO, 
                    filename=DATASET_FILENAME, 
                    repo_type="dataset",
                    token=HF_TOKEN,
                    force_download=True,
                    cache_dir=tmp_download_dir
                )
                with open(local_path, 'r', encoding='utf-8') as f:
                    content = f.read()
                    usage_data_cache = json.loads(content) if content else []
        except Exception:
            # در صورت بروز خطا، با لیست خالی شروع می‌کنیم
            usage_data_cache = []

def persist_data_to_hub():
    with persistence_lock:
        if not data_changed.is_set() or not api: return
        with cache_lock:
            data_to_write = list(usage_data_cache)
            data_changed.clear() 
        temp_filepath = None
        try:
            with tempfile.NamedTemporaryFile(mode='w', encoding='utf-8', dir=TEMP_DIR, delete=False, suffix='.json') as temp_f:
                temp_filepath = temp_f.name
                json.dump(data_to_write, temp_f, ensure_ascii=False, indent=2)
            api.upload_file(
                path_or_fileobj=temp_filepath,
                path_in_repo=DATASET_FILENAME,
                repo_id=DATASET_REPO,
                repo_type="dataset",
                commit_message="Update animation usage data"
            )
        except Exception:
            # اگر آپلود ناموفق بود، دوباره پرچم را تنظیم می‌کنیم تا در تلاش بعدی ارسال شود
            data_changed.set()
        finally:
            if temp_filepath and os.path.exists(temp_filepath):
                os.remove(temp_filepath)

def background_persister():
    while True:
        time.sleep(30)
        persist_data_to_hub()

# --- روت‌های API ---
@app.route('/')
def index():
    return render_template('index.html')

@app.route('/api/enhance-animation-prompt', methods=['POST'])
def enhance_animation_prompt():
    if not ROUTER_WORKER_URL:
        return jsonify({"error": "سرویس هوش مصنوعی به درستی پیکربندی نشده است."}), 503

    user_prompt_text = request.form.get('prompt', '')
    image_file = request.files.get('image')
    if not image_file:
        return jsonify({"error": "فایل تصویر الزامی است."}), 400

    # 🧠🧠🧠 شاه پرامپت کامل در اینجا ساخته می‌شود 🧠🧠🧠
    gemini_master_prompt = f"""
You are an expert AI Animation Planner. Your absolute highest priority is to faithfully and creatively execute the user's specific request. You are not just an artist; you are a technical problem solver.

**Input Analysis:**
1.  **Image Content:** A still image.
2.  **User's Idea (Persian):** "{user_prompt_text if user_prompt_text else 'این تصویر را به زیبایی و به صورت سینمایی متحرک کن'}"

**CRITICAL Decision-Making Framework (Follow these steps PRECISELY):**

**Step 1: Analyze the User's Intent.**
*   Is the user's prompt empty or very generic (like "animate this")?
    *   If YES, proceed to **Mode A: Default Cinematic Enhancement**.
*   Does the user's prompt describe a specific action or effect (e.g., "clouds moving," "playing guitar," "slow zoom out")?
    *   If YES, proceed to **Mode B: User-Directed Animation**.

---

**Mode A: Default Cinematic Enhancement (Only when the user gives no specific direction)**
*   **Goal:** Add subtle, high-quality, believable motion to the image to bring it to life.
*   **Action:** Analyze the image for potential motion.
    *   **Landscapes:** Animate clouds, water, fog, light rays, gentle parallax effect.
    *   **Portraits:** Add subtle breathing, eye blinks, gentle hair movement from a breeze.
    *   **Objects:** Add subtle light reflections or environmental effects.
*   **Output:** Create an `animation_prompt` focused on these subtle, ambient movements. A simple camera move like a "very slow zoom in" is acceptable if it enhances the mood.

---

**Mode B: User-Directed Animation (The HIGHEST priority)**
*   **Goal:** Execute the user's command, no matter what.
*   **Action - Sub-Step 1: Feasibility Check.**
    *   Can the requested action be performed with elements already visible in the image? (e.g., User wants "blinking eyes" on a portrait. The eyes are visible.)
    *   Or, does the request require creating elements/actions NOT visible in the frame? (e.g., User wants "playing guitar" but the image is only a headshot.)

*   **Action - Sub-Step 2: Generate the Plan based on Feasibility.**
    *   **If action is VISIBLE in-frame:** Your `animation_prompt` must focus **ENTIRELY** on executing that command perfectly. Do not add unnecessary camera moves unless the user requested it.
        *   *Example:* User says "make the water flow." Your prompt should be: "The water in the river flows realistically, with ripples and gentle waves. The rest of the scene is mostly static. Photorealistic, high detail."

    *   **If action is NOT VISIBLE in-frame (CRITICAL TASK):** You must **INVENT** the scene. Your primary tool is **revealing camera motion**. You must generate a prompt that starts with the existing frame and then expands it to include the user's request.
        *   **This is the core of your job.** Do not say it's impossible. *Make it possible.*
        *   **Example 1 (The Guitar Problem):** User uploads a headshot and writes "playing guitar."
            *   *Your Thought Process:* The guitar isn't visible. I must pull the camera back to reveal it.
            *   *Correct `animation_prompt`*: "**Cinematic slow pull back camera movement**, starting from the person's face, to **reveal they are skillfully playing an acoustic guitar**. Their fingers move realistically on the frets. The background is softly blurred. High detail, smooth motion, 8k."
        *   **Example 2:** User uploads a picture of a car on a road and writes "driving through a city at night."
            *   *Your Thought Process:* The city isn't there. I need to create it around the car.
            *   *Correct `animation_prompt`*: "The car drives forward smoothly through a vibrant, neon-lit city at night. Rain streaks across the windshield. Reflections of city lights glide across the car's wet surface. Cinematic, photorealistic, 8k."

---

**Final Output Generation (For BOTH modes):**
Based on your decision, generate the following two keys in English.

1.  **`animation_prompt`:** Your detailed script for the animation engine, created according to the rules above. It must be descriptive, technical, and include quality keywords (`cinematic, photorealistic, high detail, smooth motion, 8k`).

2.  **`negative_prompt`:** A comprehensive list of what to AVOID.
    *   **Always include these base negatives:** `ugly, deformed, noisy, blurry, distorted, grainy, shaking, jittery, flickering, unnatural movement, static image, watermark, text, signature, cartoon, anime, 3d render.`
    *   Add context-specific negatives. For a realistic scene, you might add `painting, illustration`.

**Provide the output ONLY in a clean JSON format, without any markdown or explanations:**
{{
  "animation_prompt": "...",
  "negative_prompt": "..."
}}
"""
    
    # خواندن فایل تصویر در حافظه
    image_file.seek(0)
    image_bytes = image_file.read()
    
    endpoint = f"{ROUTER_WORKER_URL}/v1/request"
    logging.info(f"Relaying request to router at {endpoint}")

    try:
        files = {'image': (image_file.filename, image_bytes, image_file.mimetype)}
        data = {'prompt': gemini_master_prompt} # شاه پرامپت کامل به مسیریاب ارسال می‌شود
        
        # ارسال درخواست با تایم‌اوت طولانی‌تر برای اطمینان
        response = requests.post(endpoint, files=files, data=data, timeout=100)
        
        # اگر پاسخ خطا بود (مثلاً 5xx)، استثنا ایجاد می‌کند
        response.raise_for_status()

        logging.info("✅ Successfully received response from router.")
        return jsonify(response.json())

    except requests.exceptions.Timeout:
        logging.error("❌ Timeout error: The request to the router timed out.")
        return jsonify({"error": "سرور پردازش با تاخیر مواجه است. لطفاً چند لحظه دیگر دوباره تلاش کنید."}), 504
    except requests.exceptions.RequestException as e:
        error_detail = "سرویس هوش مصنوعی با مشکل مواجه شده است. لطفاً بعداً تلاش کنید."
        if e.response is not None:
            try:
                # تلاش برای استخراج پیام خطای اصلی از مسیریاب
                router_error = e.response.json().get("detail", e.response.text)
                error_detail = f"خطا از سرور پردازش: {router_error}"
            except json.JSONDecodeError:
                error_detail = f"سرور پردازش با خطای {e.response.status_code} پاسخ داد."
        logging.error(f"❌ RequestException when contacting router: {error_detail}")
        return jsonify({"error": error_detail}), 503

# --- روت‌های مدیریت اعتبار (بدون تغییر) ---
def get_user_identifier(data):
    fingerprint = data.get('fingerprint')
    if fingerprint: return str(fingerprint)
    if request.headers.getlist("X-Forwarded-For"):
        return request.headers.getlist("X-Forwarded-For")[0].split(',')[0].strip()
    return request.remote_addr

@app.route('/api/check-credit', methods=['POST'])
def check_credit():
    data = request.get_json()
    if not data: return jsonify({"error": "Invalid request"}), 400
    user_id = get_user_identifier(data)
    if not user_id: return jsonify({"error": "User identifier is required."}), 400
    with cache_lock:
        now = time.time()
        one_week_seconds = 7 * 24 * 60 * 60
        user_record = next((user for user in usage_data_cache if user.get('id') == user_id), None)
        credits_remaining = USAGE_LIMIT
        limit_reached = False
        reset_timestamp = 0
        if user_record:
            if user_record.get('week_start', 0) < (now - one_week_seconds):
                user_record['count'] = 0
                user_record['week_start'] = now
                data_changed.set()
            credits_remaining = max(0, USAGE_LIMIT - user_record.get('count', 0))
            if credits_remaining == 0:
                limit_reached = True
                reset_timestamp = user_record.get('week_start', now) + one_week_seconds
    return jsonify({"credits_remaining": credits_remaining, "limit_reached": limit_reached, "reset_timestamp": reset_timestamp})

@app.route('/api/use-credit', methods=['POST'])
def use_credit():
    data = request.get_json()
    if not data: return jsonify({"error": "Invalid request"}), 400
    user_id = get_user_identifier(data)
    if not user_id: return jsonify({"error": "User identifier is required."}), 400
    
    with cache_lock:
        now = time.time()
        one_week_seconds = 7 * 24 * 60 * 60
        user_record = next((user for user in usage_data_cache if user.get('id') == user_id), None)
        if user_record:
            if user_record.get('week_start', 0) < (now - one_week_seconds):
                user_record['count'] = 0
                user_record['week_start'] = now
            if user_record.get('count', 0) >= USAGE_LIMIT:
                reset_timestamp = user_record.get('week_start', now) + one_week_seconds
                return jsonify({"status": "limit_reached", "credits_remaining": 0, "reset_timestamp": reset_timestamp}), 429
            user_record['count'] += 1
        else:
            user_record = {"id": user_id, "count": 1, "week_start": now}
            usage_data_cache.append(user_record)
        
        credits_remaining = USAGE_LIMIT - user_record['count']
        data_changed.set()
        
    return jsonify({"status": "success", "credits_remaining": credits_remaining})

# --- روت بررسی سلامت (Health Check) ---
@app.route('/health', methods=['GET'])
def health_check():
    return "OK", 200

# --- راه‌اندازی برنامه (بدون تغییر) ---
if __name__ != '__main__':
    try:
        load_initial_data()
        persister_thread = threading.Thread(target=background_persister, daemon=True)
        persister_thread.start()
    except Exception as e:
        logging.critical(f"Startup failed: {e}")
        raise SystemExit("Startup failed due to an exception.")

if __name__ == '__main__':
    port = int(os.environ.get('PORT', 7860))
    app.run(host='0.0.0.0', port=port)