Update app.py

app.py

@@ -1,82 +1,82 @@
-from flask import Flask, render_template, request
-import os
-import subprocess
-from speech_recognition import Recognizer, AudioFile
-from werkzeug.utils import secure_filename
-from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
-from deepmultilingualpunctuation import PunctuationModel
-
-app = Flask(__name__)
-yuklenen_dosyalar = "uploads"
-app.config["yuklenen_dosyalar"] = yuklenen_dosyalar
-dosya_turleri = {"mp3", "m4a"}
-
-# Modelleri yükle
-tokenizer = AutoTokenizer.from_pretrained("csebuetnlp/mT5_multilingual_XLSum")
-model = AutoModelForSeq2SeqLM.from_pretrained("csebuetnlp/mT5_multilingual_XLSum")
-punct_model = PunctuationModel(model="oliverguhr/fullstop-punctuation-multilingual-sonar-base")
-
-def metin_duzenleme(text):
-    text = text.strip()
-    try:
-        return punct_model.restore_punctuation(text)
-    except Exception as e:
-        print("Noktalama hatası:", e)
-        return text
-
-def metin_ozetleme(text):
-    girilen_metin = "tr: " + text
-    girilenler = tokenizer([girilen_metin], return_tensors="pt", max_length=10000, truncation=True)
-    summary_ids = model.generate(
-        girilenler["input_ids"],
-        max_length=1000,
-        min_length=1,
-        length_penalty=1.0,
-        num_beams=4,
-        early_stopping=True
-    )
-    return tokenizer.decode(summary_ids[0], skip_special_tokens=True)
-
-def uygun_turler(filename):
-    return "." in filename and filename.rsplit(".", 1)[1].lower() in dosya_turleri
-
-def convert_mp3_to_wav(mp3_path):
-    wav_path = mp3_path.rsplit('.', 1)[0] + '.wav'
-    subprocess.run(['ffmpeg', '-i', mp3_path, wav_path, '-y'], stdout=subprocess.DEVNULL, stderr=subprocess.DEVNULL)
-    return wav_path
-
-def ses_donusturucu(wav_path):
-    recognizer = Recognizer()
-    with AudioFile(wav_path) as source:
-        ses = recognizer.record(source)
-    try:
-        return recognizer.recognize_google(ses, language="tr-TR")
-    except Exception as e:
-        return f"Ses tanıma hatası: {e}"
-
-@app.route("/", methods=["GET", "POST"])
-def index():
-    if request.method == "POST":
-        if "file" not in request.files:
-            return "Dosya bulunamadı."
-        file = request.files["file"]
-        if file.filename == "":
-            return "Dosya seçilmedi."
-        if file and uygun_turler(file.filename):
-            filename = secure_filename(file.filename)
-            file_path = os.path.join(app.config["yuklenen_dosyalar"], filename)
-            file.save(file_path)
-
-            wav_path = convert_mp3_to_wav(file_path)
-            raw_text = ses_donusturucu(wav_path)
-            metin = metin_duzenleme(raw_text)
-            ozet = metin_ozetleme(metin)
-
-            return render_template("index.html", metin=metin, ozet=ozet)
-    return render_template("index.html")
-
-if __name__ == "__main__":
-    if not os.path.exists(yuklenen_dosyalar):
-        os.makedirs(yuklenen_dosyalar)
-    port = int(os.environ.get("PORT", 7860))  # Hugging Face için 7860 port
-    app.run(host="0.0.0.0", port=port, debug=False)
+from flask import Flask, render_template, request
+import os
+import subprocess
+from speech_recognition import Recognizer, AudioFile
+from werkzeug.utils import secure_filename
+from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
+from deepmultilingualpunctuation import PunctuationModel
+
+app = Flask(__name__)
+yuklenen_dosyalar = "uploads"
+app.config["yuklenen_dosyalar"] = yuklenen_dosyalar
+dosya_turleri = {"mp3", "m4a"}
+
+# Modelleri yükle
+tokenizer = AutoTokenizer.from_pretrained("csebuetnlp/mT5_multilingual_XLSum", use_fast=False)
+model = AutoModelForSeq2SeqLM.from_pretrained("csebuetnlp/mT5_multilingual_XLSum")
+punct_model = PunctuationModel(model="oliverguhr/fullstop-punctuation-multilingual-sonar-base")
+
+def metin_duzenleme(text):
+    text = text.strip()
+    try:
+        return punct_model.restore_punctuation(text)
+    except Exception as e:
+        print("Noktalama hatası:", e)
+        return text
+
+def metin_ozetleme(text):
+    girilen_metin = "tr: " + text
+    girilenler = tokenizer([girilen_metin], return_tensors="pt", max_length=10000, truncation=True)
+    summary_ids = model.generate(
+        girilenler["input_ids"],
+        max_length=1000,
+        min_length=1,
+        length_penalty=1.0,
+        num_beams=4,
+        early_stopping=True
+    )
+    return tokenizer.decode(summary_ids[0], skip_special_tokens=True)
+
+def uygun_turler(filename):
+    return "." in filename and filename.rsplit(".", 1)[1].lower() in dosya_turleri
+
+def convert_mp3_to_wav(mp3_path):
+    wav_path = mp3_path.rsplit('.', 1)[0] + '.wav'
+    subprocess.run(['ffmpeg', '-i', mp3_path, wav_path, '-y'], stdout=subprocess.DEVNULL, stderr=subprocess.DEVNULL)
+    return wav_path
+
+def ses_donusturucu(wav_path):
+    recognizer = Recognizer()
+    with AudioFile(wav_path) as source:
+        ses = recognizer.record(source)
+    try:
+        return recognizer.recognize_google(ses, language="tr-TR")
+    except Exception as e:
+        return f"Ses tanıma hatası: {e}"
+
+@app.route("/", methods=["GET", "POST"])
+def index():
+    if request.method == "POST":
+        if "file" not in request.files:
+            return "Dosya bulunamadı."
+        file = request.files["file"]
+        if file.filename == "":
+            return "Dosya seçilmedi."
+        if file and uygun_turler(file.filename):
+            filename = secure_filename(file.filename)
+            file_path = os.path.join(app.config["yuklenen_dosyalar"], filename)
+            file.save(file_path)
+
+            wav_path = convert_mp3_to_wav(file_path)
+            raw_text = ses_donusturucu(wav_path)
+            metin = metin_duzenleme(raw_text)
+            ozet = metin_ozetleme(metin)
+
+            return render_template("index.html", metin=metin, ozet=ozet)
+    return render_template("index.html")
+
+if __name__ == "__main__":
+    if not os.path.exists(yuklenen_dosyalar):
+        os.makedirs(yuklenen_dosyalar)
+    port = int(os.environ.get("PORT", 7860))  # Hugging Face için 7860 port
+    app.run(host="0.0.0.0", port=port, debug=False)