Delete app.py

app.py

@@ -1,722 +0,0 @@
-import requests
-import json
-import gradio as gr
-from typing import Dict, Any, List, Generator, Optional
-import os
-from dataclasses import dataclass
-import re
-import pandas as pd
-import time
-from datetime import datetime
-import threading
-from queue import Queue
-import io
-from requests.adapters import HTTPAdapter
-from urllib3.util.retry import Retry
-from enum import Enum
-
-class APIProvider(Enum):
-    """پرووایدرهای API پشتیبانی شده"""
-    CEREBRAS = "cerebras"
-    GROQ = "groq"
-    OPENAI = "openai"
-
-@dataclass
-class APIConfig:
-    """تنظیمات API"""
-    provider: APIProvider
-    api_key: str
-    base_url: str
-    model: str
-    max_tokens: int = 2000
-    temperature: float = 0.1
-
-# تنظیمات پیش‌فرض برای هر پرووایدر
-API_CONFIGS = {
-    APIProvider.CEREBRAS: {
-        "base_url": "https://api.cerebras.ai/v1",
-        "models": ["qwen-3-32b", "llama-4-scout-17b-16e-instruct", "llama3.1-8b"],
-        "default_model": "qwen-3-32b"
-    },
-    APIProvider.GROQ: {
-        "base_url": "https://api.groq.com/openai/v1",
-        "models": ["llama-3.3-70b-versatile", "llama-3.1-8b-instant", "mixtral-8x7b-32768"],
-        "default_model": "llama-3.3-70b-versatile"
-    },
-    APIProvider.OPENAI: {
-        "base_url": "https://api.openai.com/v1",
-        "models": ["gpt-4o-mini", "gpt-4o", "gpt-3.5-turbo"],
-        "default_model": "gpt-4o-mini"
-    }
-}
-
-@dataclass
-class RateLimitConfig:
-    """تنظیمات محدودیت نرخ درخواست"""
-    requests_per_minute: int = 30
-    min_delay_between_requests: float = 2.0
-    max_retries: int = 5
-    initial_backoff: float = 5.0
-    max_backoff: float = 60.0
-    backoff_multiplier: float = 2.0
-    recovery_window: float = 60.0
-
-class RateLimiter:
-    """مدیریت محدودیت نرخ درخواست"""
-    
-    def __init__(self, config: RateLimitConfig):
-        self.config = config
-        self.request_times: List[float] = []
-        self.lock = threading.Lock()
-        self.consecutive_failures = 0
-        self.last_failure_time = 0
-        self.last_success_time = time.time()
-        self.total_429_errors = 0
-    
-    def wait_if_needed(self) -> float:
-        """انتظار تا زمان مجاز ارسال درخواست بعدی"""
-        with self.lock:
-            now = time.time()
-            
-            # پاک کردن درخواست‌های قدیمی
-            self.request_times = [t for t in self.request_times if now - t < 60]
-            
-            # بازیابی از خطاهای قبلی
-            if self.consecutive_failures > 0 and (now - self.last_failure_time) > self.config.recovery_window:
-                self.consecutive_failures = max(0, self.consecutive_failures - 1)
-            
-            wait_time = 0.0
-            
-            # محدودیت درخواست در دقیقه
-            if len(self.request_times) >= self.config.requests_per_minute:
-                oldest_request = min(self.request_times)
-                wait_time = max(wait_time, 60 - (now - oldest_request) + 1)
-            
-            # حداقل تأخیر
-            if self.request_times:
-                time_since_last = now - max(self.request_times)
-                if time_since_last < self.config.min_delay_between_requests:
-                    wait_time = max(wait_time, self.config.min_delay_between_requests - time_since_last)
-            
-            # backoff برای خطاها
-            if self.consecutive_failures > 0:
-                failure_wait = min(
-                    self.config.initial_backoff * (self.config.backoff_multiplier ** min(self.consecutive_failures, 4)),
-                    self.config.max_backoff
-                )
-                wait_time = max(wait_time, failure_wait)
-            
-            if wait_time > 0:
-                time.sleep(wait_time)
-            
-            self.request_times.append(time.time())
-            return wait_time
-    
-    def report_success(self):
-        with self.lock:
-            self.last_success_time = time.time()
-            self.consecutive_failures = 0
-    
-    def report_failure(self, is_rate_limit: bool = False):
-        with self.lock:
-            self.last_failure_time = time.time()
-            if is_rate_limit:
-                self.consecutive_failures += 1
-                self.total_429_errors += 1
-            else:
-                self.consecutive_failures = min(self.consecutive_failures + 0.5, 3)
-    
-    def get_estimated_wait_time(self) -> float:
-        with self.lock:
-            now = time.time()
-            self.request_times = [t for t in self.request_times if now - t < 60]
-            if len(self.request_times) >= self.config.requests_per_minute:
-                return max(0, 60 - (now - min(self.request_times)) + 1)
-            return self.config.min_delay_between_requests
-    
-    def get_status(self) -> Dict[str, Any]:
-        with self.lock:
-            return {
-                "consecutive_failures": self.consecutive_failures,
-                "total_429_errors": self.total_429_errors,
-                "requests_in_last_minute": len(self.request_times)
-            }
-
-
-class MultiProviderAnonymizer:
-    """سیستم ناشناس‌سازی با پشتیبانی از چند API"""
-    
-    def __init__(
-        self, 
-        provider: APIProvider,
-        api_key: str,
-        model: str = None,
-        rate_limit_config: RateLimitConfig = None
-    ):
-        self.provider = provider
-        self.api_key = api_key
-        
-        provider_config = API_CONFIGS[provider]
-        self.base_url = provider_config["base_url"]
-        self.model = model or provider_config["default_model"]
-        
-        self.rate_limit_config = rate_limit_config or RateLimitConfig()
-        self.rate_limiter = RateLimiter(self.rate_limit_config)
-        self.system_prompt = self._create_system_prompt()
-        self.session = self._create_session()
-    
-    def _create_session(self) -> requests.Session:
-        """ایجاد session با تنظیمات بهینه"""
-        session = requests.Session()
-        retry_strategy = Retry(
-            total=3,
-            backoff_factor=1,
-            status_forcelist=[500, 502, 503, 504],
-            allowed_methods=["POST"]
-        )
-        adapter = HTTPAdapter(max_retries=retry_strategy, pool_connections=10, pool_maxsize=10)
-        session.mount("https://", adapter)
-        session.mount("http://", adapter)
-        return session
-    
-    def _create_system_prompt(self) -> str:
-        """دستورالعمل سیستمی"""
-        return """شما یک «ناشناس‌ساز متون مالی/خبری فارسی» هستید. وظیفه‌تان جایگزینی اسامی خاص و مقادیر عددی با شناسه‌های بی‌معناست.
-
-## **قوانین اندیس‌گذاری**
-- شرکت‌ها: company-01, company-02, ... (پیوسته)
-- اشخاص: person-01, person-02, ... (پیوسته)
-- اعداد: amount-01, amount-02, ... (پیوسته)
-- درصدها: percent-01, percent-02, ... (پیوسته)
-
-## **ثبات شناسه‌ها:**
-- اگر "همراه اول" اول‌بار company-01 شد، در تمام متن همان باشد
-
-## **تشخیص صحیح:**
-- **شرکت/سازمان:** همراه اول، بانک ملی، ایران‌خودرو، سایپا، بانک مرکزی
-- **گروه‌ها:** "گروه همراه اول" → company-XX (نه group-XX)
-- **کلمات عمومی:** "سه شرکت"، "چند بانک" → حفظ شوند
-- **شخص:** مهدی اخوان بهابادی، محمدرضا فرزین
-- **عدد:** 37، 70، 677 (هر عددی)
-- **درصد:** 37 درصدی، 15%
-
-## **مثال:**
-**ورودی:** مهدی اخوان، مدیرعامل همراه اول، اعلام کرد درآمد با رشد 37 درصدی به 70 میلیارد رسید.
-**خروجی:** person-01، مدیرعامل company-01، اعلام کرد درآمد با رشد percent-01 به amount-01 رسید.
-
-## **حفظ شود:**
-- تاریخ‌ها: 1404/04/23
-- دوره‌های زمانی: ۹ ماهه، ۵ ماهه سال
-- واحدها: میلیارد تومان، همت
-- مکان‌ها: تهران، اصفهان
-
-**فقط متن ناشناس‌شده را برگردان - بدون توضیح اضافی.**
-"""
-
-    def _make_api_request(self, text: str) -> Dict[str, Any]:
-        """ارسال درخواست به API"""
-        headers = {
-            "Authorization": f"Bearer {self.api_key}",
-            "Content-Type": "application/json"
-        }
-        
-        payload = {
-            "messages": [
-                {"role": "system", "content": self.system_prompt},
-                {"role": "user", "content": text}
-            ],
-            "model": self.model,
-            "temperature": 0.1,
-            "max_tokens": 2000
-        }
-        
-        # اضافه کردن پارامترهای خاص هر پرووایدر
-        if self.provider == APIProvider.GROQ:
-            # Groq نیاز به این پارامتر نداره
-            pass
-        
-        last_error = None
-        
-        for attempt in range(self.rate_limit_config.max_retries):
-            self.rate_limiter.wait_if_needed()
-            
-            try:
-                response = self.session.post(
-                    f"{self.base_url}/chat/completions",
-                    headers=headers,
-                    json=payload,
-                    timeout=90
-                )
-                
-                if response.status_code == 429:
-                    self.rate_limiter.report_failure(is_rate_limit=True)
-                    retry_after = response.headers.get('Retry-After')
-                    wait_seconds = int(retry_after) if retry_after else min(
-                        self.rate_limit_config.initial_backoff * (self.rate_limit_config.backoff_multiplier ** attempt),
-                        60.0
-                    )
-                    last_error = f"Rate limit (429). تلاش {attempt + 1}/{self.rate_limit_config.max_retries}"
-                    print(f"🚫 {last_error} - انتظار {wait_seconds}s")
-                    time.sleep(wait_seconds)
-                    continue
-                
-                if response.status_code == 401:
-                    raise Exception(f"❌ کلید API نامعتبر است برای {self.provider.value}")
-                
-                if response.status_code == 503:
-                    self.rate_limiter.report_failure(is_rate_limit=False)
-                    last_error = f"سرویس در دسترس نیست (503)"
-                    time.sleep(10)
-                    continue
-                
-                response.raise_for_status()
-                self.rate_limiter.report_success()
-                return response.json()
-                
-            except requests.exceptions.Timeout:
-                self.rate_limiter.report_failure(is_rate_limit=False)
-                last_error = f"Timeout"
-                time.sleep(5)
-                
-            except requests.exceptions.ConnectionError as e:
-                self.rate_limiter.report_failure(is_rate_limit=False)
-                last_error = f"خطای اتصال: {str(e)[:50]}"
-                time.sleep(10)
-                
-            except requests.exceptions.RequestException as e:
-                self.rate_limiter.report_failure(is_rate_limit=False)
-                last_error = f"خطای شبکه: {str(e)[:50]}"
-                time.sleep(5)
-        
-        raise Exception(f"ناموفق پس از {self.rate_limit_config.max_retries} تلاش: {last_error}")
-    
-    def anonymize_text(self, text: str) -> Dict[str, Any]:
-        """ناشناس‌سازی متن"""
-        if not text or not text.strip():
-            return {"success": False, "error": "متن ورودی خالی است", "anonymized_text": ""}
-        
-        try:
-            response = self._make_api_request(text)
-            
-            if "choices" not in response or not response["choices"]:
-                return {"success": False, "error": "پاسخ نامعتبر", "anonymized_text": ""}
-            
-            content = response["choices"][0]["message"]["content"]
-            
-            # پاک کردن markdown
-            if "```" in content:
-                lines = content.split('\n')
-                clean_lines = []
-                skip = False
-                for line in lines:
-                    if line.strip().startswith('```'):
-                        skip = not skip
-                        continue
-                    if not skip:
-                        clean_lines.append(line)
-                content = '\n'.join(clean_lines)
-            
-            content = content.strip()
-            
-            # تحلیل نتایج
-            companies = re.findall(r'company-(\d+)', content)
-            persons = re.findall(r'person-(\d+)', content)
-            amounts = re.findall(r'amount-(\d+)', content)
-            percents = re.findall(r'percent-(\d+)', content)
-            
-            return {
-                "success": True,
-                "anonymized_text": content,
-                "statistics": {
-                    "company": len(set(companies)),
-                    "person": len(set(persons)),
-                    "amount": len(set(amounts)),
-                    "percent": len(set(percents))
-                },
-                "usage": response.get("usage", {})
-            }
-                
-        except Exception as e:
-            return {"success": False, "error": f"خطا: {str(e)}", "anonymized_text": ""}
-
-
-class BatchProcessor:
-    """پردازشگر دسته‌ای"""
-    
-    def __init__(
-        self, 
-        provider: APIProvider,
-        api_key: str,
-        model: str = None,
-        rate_limit_config: RateLimitConfig = None
-    ):
-        self.provider = provider
-        self.api_key = api_key
-        self.model = model
-        self.rate_limit_config = rate_limit_config or RateLimitConfig()
-        self.anonymizer = None
-        self.is_cancelled = False
-        self.current_progress = 0
-        self.total_rows = 0
-        self.processed_rows = 0
-        self.failed_rows = 0
-        self.start_time = None
-        self.consecutive_api_failures = 0
-        self.max_consecutive_failures = 10
-    
-    def cancel(self):
-        self.is_cancelled = True
-    
-    def reset(self):
-        self.is_cancelled = False
-        self.current_progress = 0
-        self.total_rows = 0
-        self.processed_rows = 0
-        self.failed_rows = 0
-        self.start_time = None
-        self.consecutive_api_failures = 0
-    
-    def process_csv(
-        self, 
-        file_path: str, 
-        text_column: str,
-        output_column: str = "anonymized_text"
-    ) -> Generator[Dict[str, Any], None, None]:
-        """پردازش فایل CSV"""
-        
-        self.reset()
-        self.start_time = time.time()
-        
-        # خواندن فایل
-        try:
-            df = pd.read_csv(file_path, encoding='utf-8')
-        except UnicodeDecodeError:
-            try:
-                df = pd.read_csv(file_path, encoding='utf-8-sig')
-            except:
-                df = pd.read_csv(file_path, encoding='cp1256')
-        
-        if text_column not in df.columns:
-            yield {"type": "error", "message": f"ستون '{text_column}' یافت نشد"}
-            return
-        
-        self.total_rows = len(df)
-        
-        # ایجاد anonymizer
-        self.anonymizer = MultiProviderAnonymizer(
-            provider=self.provider,
-            api_key=self.api_key,
-            model=self.model,
-            rate_limit_config=self.rate_limit_config
-        )
-        
-        df[output_column] = ""
-        df["anonymization_status"] = ""
-        df["entities_found"] = ""
-        
-        yield {
-            "type": "info",
-            "message": f"🚀 شروع پردازش {self.total_rows} ردیف با {self.provider.value}..."
-        }
-        
-        for idx, row in df.iterrows():
-            if self.is_cancelled:
-                yield {
-                    "type": "cancelled",
-                    "message": "لغو شد",
-                    "processed": self.processed_rows,
-                    "failed": self.failed_rows
-                }
-                break
-            
-            if self.consecutive_api_failures >= self.max_consecutive_failures:
-                partial_path = file_path.replace('.csv', f'_partial_{idx}.csv')
-                df.to_csv(partial_path, index=False, encoding='utf-8-sig')
-                yield {
-                    "type": "error",
-                    "message": f"❌ توقف - خطاهای متوالی زیاد. ذخیره شد: {partial_path}"
-                }
-                return
-            
-            text = str(row[text_column]) if pd.notna(row[text_column]) else ""
-            
-            if not text.strip():
-                df.at[idx, output_column] = ""
-                df.at[idx, "anonymization_status"] = "خالی"
-                self.processed_rows += 1
-                continue
-            
-            result = self.anonymizer.anonymize_text(text)
-            
-            if result["success"]:
-                df.at[idx, output_column] = result["anonymized_text"]
-                df.at[idx, "anonymization_status"] = "موفق"
-                stats = result.get("statistics", {})
-                df.at[idx, "entities_found"] = f"C:{stats.get('company',0)}|P:{stats.get('person',0)}|A:{stats.get('amount',0)}|%:{stats.get('percent',0)}"
-                self.processed_rows += 1
-                self.consecutive_api_failures = 0
-            else:
-                df.at[idx, output_column] = f"خطا: {result.get('error', '')}"
-                df.at[idx, "anonymization_status"] = "ناموفق"
-                self.failed_rows += 1
-                if "rate limit" in result.get('error', '').lower() or "429" in result.get('error', ''):
-                    self.consecutive_api_failures += 1
-            
-            # پیشرفت
-            self.current_progress = (idx + 1) / self.total_rows * 100
-            elapsed = time.time() - self.start_time
-            
-            yield {
-                "type": "progress",
-                "current": idx + 1,
-                "total": self.total_rows,
-                "progress": self.current_progress,
-                "processed": self.processed_rows,
-                "failed": self.failed_rows,
-                "elapsed": elapsed,
-                "estimated_remaining": (elapsed / (idx + 1)) * (self.total_rows - idx - 1),
-                "next_wait": self.anonymizer.rate_limiter.get_estimated_wait_time(),
-                "last_result": result,
-                "rate_status": self.anonymizer.rate_limiter.get_status()
-            }
-            
-            # Checkpoint هر 100 ردیف
-            if (idx + 1) % 100 == 0:
-                checkpoint_path = file_path.replace('.csv', f'_checkpoint_{idx+1}.csv')
-                df.to_csv(checkpoint_path, index=False, encoding='utf-8-sig')
-                yield {"type": "info", "message": f"💾 Checkpoint: {checkpoint_path}"}
-        
-        # ذخیره نهایی
-        if not self.is_cancelled:
-            output_path = file_path.replace('.csv', '_anonymized.csv')
-            if output_path == file_path:
-                output_path = file_path + '_anonymized.csv'
-            
-            df.to_csv(output_path, index=False, encoding='utf-8-sig')
-            
-            yield {
-                "type": "complete",
-                "message": "✅ تکمیل شد!",
-                "output_path": output_path,
-                "total": self.total_rows,
-                "processed": self.processed_rows,
-                "failed": self.failed_rows,
-                "total_time": time.time() - self.start_time
-            }
-
-
-def create_interface():
-    """ایجاد رابط کاربری"""
-    
-    custom_css = """
-    .rtl-text { direction: rtl; text-align: right; font-family: 'Vazirmatn', 'Tahoma', sans-serif; }
-    """
-    
-    with gr.Blocks(css=custom_css, title="ناشناس‌ساز چند-API", theme=gr.themes.Soft()) as interface:
-        gr.Markdown("""
-        # 🔒 سیستم ناشناس‌سازی متون فارسی
-        ### پشتیبانی از Cerebras، Groq و OpenAI
-        """, elem_classes=["rtl-text"])
-        
-        batch_processor = {"instance": None}
-        
-        with gr.Tabs():
-            # تب پردازش تکی
-            with gr.Tab("پردازش تکی"):
-                with gr.Row():
-                    with gr.Column():
-                        single_provider = gr.Dropdown(
-                            label="🌐 پرووایدر API",
-                            choices=["cerebras", "groq", "openai"],
-                            value="groq",
-                            elem_classes=["rtl-text"]
-                        )
-                        single_api_key = gr.Textbox(
-                            label="🔑 کلید API",
-                            placeholder="کلید API خود را وارد کنید",
-                            type="password"
-                        )
-                        single_model = gr.Dropdown(
-                            label="🤖 مدل",
-                            choices=["llama-3.3-70b-versatile", "llama-3.1-8b-instant"],
-                            value="llama-3.3-70b-versatile"
-                        )
-                        single_input = gr.Textbox(
-                            label="متن ورودی",
-                            lines=5,
-                            elem_classes=["rtl-text"]
-                        )
-                        single_btn = gr.Button("🔄 ناشناس‌سازی", variant="primary")
-                    
-                    with gr.Column():
-                        single_output = gr.Textbox(label="متن ناشناس‌شده", lines=5, elem_classes=["rtl-text"])
-                        single_stats = gr.Textbox(label="آمار", lines=2)
-            
-            # تب پردازش دسته‌ای
-            with gr.Tab("پردازش دسته‌ای"):
-                with gr.Row():
-                    with gr.Column():
-                        batch_provider = gr.Dropdown(
-                            label="🌐 پرووایدر API",
-                            choices=["cerebras", "groq", "openai"],
-                            value="groq"
-                        )
-                        batch_api_key = gr.Textbox(
-                            label="🔑 کلید API",
-                            type="password"
-                        )
-                        batch_model = gr.Dropdown(
-                            label="🤖 مدل",
-                            choices=["llama-3.3-70b-versatile", "qwen-3-32b", "gpt-4o-mini"],
-                            value="llama-3.3-70b-versatile"
-                        )
-                        csv_file = gr.File(label="📁 فایل CSV", file_types=[".csv"])
-                        text_column = gr.Dropdown(label="ستون متن", choices=[], allow_custom_value=True)
-                        output_column = gr.Textbox(label="نام ستون خروجی", value="anonymized_text")
-                    
-                    with gr.Column():
-                        delay_slider = gr.Slider(1, 30, 3, step=0.5, label="تأخیر (ثانیه)")
-                        rpm_slider = gr.Slider(5, 30, 20, step=1, label="حداکثر درخواست/دقیقه")
-                        retries_slider = gr.Slider(1, 10, 5, step=1, label="تلاش مجدد")
-                
-                with gr.Row():
-                    start_btn = gr.Button("🚀 شروع", variant="primary", size="lg")
-                    cancel_btn = gr.Button("⏹️ لغو", variant="stop", size="lg")
-                
-                progress_bar = gr.Slider(0, 100, 0, label="پیشرفت", interactive=False)
-                progress_text = gr.Markdown("در انتظار...")
-                time_stats = gr.Markdown("")
-                process_log = gr.Textbox(lines=10, label="لاگ")
-                preview_table = gr.Dataframe(headers=["متن", "ناشناس‌شده", "وضعیت"])
-                output_file = gr.File(label="دانلود", visible=False)
-        
-        # توابع
-        def update_models(provider):
-            if provider == "cerebras":
-                return gr.update(choices=["qwen-3-32b", "llama-4-scout-17b-16e-instruct"], value="qwen-3-32b")
-            elif provider == "groq":
-                return gr.update(choices=["llama-3.3-70b-versatile", "llama-3.1-8b-instant", "mixtral-8x7b-32768"], value="llama-3.3-70b-versatile")
-            else:
-                return gr.update(choices=["gpt-4o-mini", "gpt-4o"], value="gpt-4o-mini")
-        
-        def update_columns(file):
-            if file is None:
-                return gr.update(choices=[], value=None)
-            try:
-                df = pd.read_csv(file.name, nrows=0, encoding='utf-8')
-            except:
-                try:
-                    df = pd.read_csv(file.name, nrows=0, encoding='utf-8-sig')
-                except:
-                    df = pd.read_csv(file.name, nrows=0, encoding='cp1256')
-            columns = list(df.columns)
-            return gr.update(choices=columns, value=columns[0] if columns else None)
-        
-        def process_single(provider, api_key, model, text):
-            if not text.strip():
-                return "", "❌ متن خالی"
-            if not api_key:
-                return "", "❌ کلید API وارد نشده"
-            
-            try:
-                prov = APIProvider(provider)
-                anonymizer = MultiProviderAnonymizer(provider=prov, api_key=api_key, model=model)
-                result = anonymizer.anonymize_text(text)
-                
-                if result["success"]:
-                    stats = result.get("statistics", {})
-                    return result["anonymized_text"], f"✅ C:{stats.get('company',0)} | P:{stats.get('person',0)} | A:{stats.get('amount',0)} | %:{stats.get('percent',0)}"
-                else:
-                    return "", f"❌ {result.get('error', '')}"
-            except Exception as e:
-                return "", f"❌ {str(e)}"
-        
-        def start_batch(file, text_col, output_col, delay, rpm, retries, provider, api_key, model):
-            if file is None:
-                yield (0, "❌ فایل انتخاب نشده", "", "", None, gr.update(visible=False))
-                return
-            if not api_key:
-                yield (0, "❌ کلید API وارد نشده", "", "", None, gr.update(visible=False))
-                return
-            
-            prov = APIProvider(provider)
-            rate_config = RateLimitConfig(
-                requests_per_minute=int(rpm),
-                min_delay_between_requests=float(delay),
-                max_retries=int(retries)
-            )
-            
-            processor = BatchProcessor(provider=prov, api_key=api_key, model=model, rate_limit_config=rate_config)
-            batch_processor["instance"] = processor
-            
-            log_lines = []
-            preview_data = []
-            
-            for update in processor.process_csv(file.name, text_col, output_col):
-                update_type = update.get("type")
-                
-                if update_type == "error":
-                    log_lines.append(f"❌ {update['message']}")
-                    yield (0, f"❌ {update['message']}", "", "\n".join(log_lines), None, gr.update(visible=False))
-                    return
-                
-                elif update_type == "info":
-                    log_lines.append(f"ℹ️ {update['message']}")
-                
-                elif update_type == "progress":
-                    progress = update["progress"]
-                    current = update["current"]
-                    total = update["total"]
-                    elapsed = update["elapsed"]
-                    remaining = update["estimated_remaining"]
-                    
-                    progress_md = f"**{current}/{total}** ({progress:.1f}%) | ✅ {update['processed']} | ❌ {update['failed']}"
-                    time_md = f"⏱️ {elapsed/60:.1f}m | باقیمانده: {remaining/60:.1f}m"
-                    
-                    if current % 10 == 0:
-                        log_lines.append(f"📊 {current}/{total}")
-                    
-                    last_result = update.get("last_result", {})
-                    if last_result.get("success"):
-                        preview_data.append(["...", last_result.get("anonymized_text", "")[:80] + "...", "✅"])
-                        if len(preview_data) > 5:
-                            preview_data = preview_data[-5:]
-                    
-                    yield (progress, progress_md, time_md, "\n".join(log_lines[-15:]), preview_data if preview_data else None, gr.update(visible=False))
-                
-                elif update_type == "cancelled":
-                    log_lines.append("⏹️ لغو شد")
-                    yield (0, "⏹️ لغو شد", "", "\n".join(log_lines), preview_data if preview_data else None, gr.update(visible=False))
-                    return
-                
-                elif update_type == "complete":
-                    log_lines.append(f"✅ {update['message']}")
-                    progress_md = f"✅ تکمیل! {update['processed']}/{update['total']} موفق | {update['total_time']/60:.1f} دقیقه"
-                    yield (100, progress_md, "", "\n".join(log_lines), preview_data if preview_data else None, gr.update(value=update['output_path'], visible=True))
-        
-        def cancel():
-            if batch_processor["instance"]:
-                batch_processor["instance"].cancel()
-            return "⏹️ لغو شد..."
-        
-        # اتصالات
-        single_provider.change(update_models, [single_provider], [single_model])
-        batch_provider.change(update_models, [batch_provider], [batch_model])
-        csv_file.change(update_columns, [csv_file], [text_column])
-        
-        single_btn.click(process_single, [single_provider, single_api_key, single_model, single_input], [single_output, single_stats])
-        
-        start_btn.click(
-            start_batch,
-            [csv_file, text_column, output_column, delay_slider, rpm_slider, retries_slider, batch_provider, batch_api_key, batch_model],
-            [progress_bar, progress_text, time_stats, process_log, preview_table, output_file]
-        )
-        
-        cancel_btn.click(cancel, outputs=[process_log])
-    
-    return interface
-
-
-if __name__ == "__main__":
-    interface = create_interface()
-    interface.launch(server_name="0.0.0.0", server_port=7860, share=True, show_error=True)