Update app.py

app.py

@@ -4,14 +4,13 @@ from fastapi import FastAPI
 from fastapi.middleware.cors import CORSMiddleware
 from langdetect import detect
 from functools import lru_cache
-import asyncio
 import re
 
 # ======================================================
-# 🚀 Eroha Summarizer PRO++++ v2.1 (by Yermek68)
+# 🚀 Eroha Summarizer PRO++++ v2.1.1 Stable (by Yermek68)
 # ======================================================
 
-# Кэш пайплайнов
+# --- Кэш моделей ---
 @lru_cache(maxsize=10)
 def get_summarizer(lang: str, long: bool = False):
     if lang == "ru":
@@ -34,10 +33,7 @@ def get_sentiment_analyzer(lang: str):
         model = "j-hartmann/emotion-english-distilroberta-base"
     return pipeline("text-classification", model=model, top_k=None)
 
-# ======================================
-# 🧠 Вспомогательные функции
-# ======================================
-
+# --- Вспомогательные функции ---
 def clean_text(text: str) -> str:
     text = re.sub(r"[^\x00-\x7Fа-яА-ЯёЁ.,!?;:\-–—«»\"'()\[\] ]", "", text)
     text = text.replace("▁", " ").replace("<n>", "\n").replace("<s>", "").replace("</s>", "")
@@ -71,10 +67,9 @@ def detect_genre(text: str):
     return "📄 Текст общего типа"
 
 # =====================================================
-# 🧩 Основная функция суммаризации
+# 🧩 Основная функция
 # =====================================================
-
-async def summarize_text(text: str):
+def summarize_text(text: str):
     if not text.strip():
         return "❌ Введите текст для анализа."
 
@@ -94,13 +89,11 @@ async def summarize_text(text: str):
         summary = text
     else:
         max_len, min_len = (250, 60) if words > 300 else (120, 40)
-        loop = asyncio.get_event_loop()
-        summary_raw = await loop.run_in_executor(None, lambda: summarizer(text, max_length=max_len, min_length=min_len, do_sample=False)[0]["summary_text"])
+        summary_raw = summarizer(text, max_length=max_len, min_length=min_len, do_sample=False)[0]["summary_text"]
         summary = clean_text(summary_raw)
 
     # Анализ эмоций
-    loop = asyncio.get_event_loop()
-    emotions = await loop.run_in_executor(None, lambda: sentiment_model(summary))
+    emotions = sentiment_model(summary)
     emo_label = emotions[0]["label"]
     emo_score = emotions[0].get("score", 0)
 
@@ -121,7 +114,7 @@ async def summarize_text(text: str):
     color = "green" if "Радость" in emotion else "red" if "Грусть" in emotion or "Гнев" in emotion else "orange"
 
     formatted_output = f"""
-# 🧠 <span style='color:#0073e6'>Eroha Summarizer PRO++++ v2.1</span>
+# 🧠 <span style='color:#0073e6'>Eroha Summarizer PRO++++ v2.1.1 Stable</span>
 _(Автоязык: {'Русский' if lang == 'ru' else 'Английский'})_
 
 ---
@@ -150,31 +143,31 @@ _(Автоязык: {'Русский' if lang == 'ru' else 'Английский
 # 🌐 FastAPI backend
 # =====================================================
 
-app = FastAPI(title="Eroha Summarizer PRO++++ v2.1", version="2.1")
+app = FastAPI(title="Eroha Summarizer PRO++++ v2.1.1", version="2.1.1")
 app.add_middleware(CORSMiddleware, allow_origins=["*"], allow_methods=["*"], allow_headers=["*"])
 
 @app.post("/api/full")
-async def api_full(data: dict):
+def api_full(data: dict):
     text = data.get("text", "")
-    summary = await summarize_text(text)
+    summary = summarize_text(text)
     return {"summary": summary}
 
 @app.post("/api/lite")
-async def api_lite(data: dict):
+def api_lite(data: dict):
     text = data.get("text", "")
-    result = await summarize_text(text)
+    result = summarize_text(text)
     clean_result = re.sub(r"<[^>]+>", "", result)
     return {"tldr": clean_result[:300]}
 
 # =====================================================
-# 🎨 Gradio интерфейс с кнопками
+# 🎨 Gradio интерфейс
 # =====================================================
 
 def gradio_summary(text):
-    return asyncio.run(summarize_text(text))
+    return summarize_text(text)
 
-with gr.Blocks(title="Eroha Summarizer PRO++++ v2.1") as iface:
-    gr.Markdown("## 🧠 Eroha Summarizer PRO++++ v2.1\nAI-инструмент нового поколения для анализа, темы, эмоций и автоопределения языка (рус/англ/нем/исп/фр).")
+with gr.Blocks(title="Eroha Summarizer PRO++++ v2.1.1") as iface:
+    gr.Markdown("## 🧠 Eroha Summarizer PRO++++ v2.1.1 Stable\nAI-инструмент нового поколения для анализа, темы, эмоций и автоопределения языка (рус/англ/нем/исп/фр).")
 
     text_input = gr.Textbox(lines=10, label="Введите текст для анализа и суммаризации")
     result_output = gr.Markdown(label="Результат")