Update app.py

app.py

@@ -135,7 +135,7 @@ E2TTS_ema_model2 = load_custom(
     "hf://Gregniuki/F5-tts_English_German_Polish/Polish/model_500000.pt", "", F5TTS_model_cfg
 )
 
-def chunk_text(text, max_chars=80):
+def chunk_text(text, max_chars=100):
     """
     Splits the input text into chunks, each with a maximum number of characters.
     Args:
@@ -186,10 +186,12 @@ def infer_batch(ref_audio, ref_text, gen_text_batches, exp_name, remove_silence,
     generated_waves = []
     spectrograms = []
 
-    if len(ref_text[-1].encode("utf-8")) == 1:
-        ref_text = ref_text + " "
+    
     for i, gen_text in enumerate(progress.tqdm(gen_text_batches)):
         # Prepare the text
+        if len(ref_text[-1].encode("utf-8")) == 1:
+            pref_text = ref_text + " "
+        
         text_list = [ref_text + gen_text]
         final_text_list = convert_char_to_pinyin(text_list)
 
@@ -353,7 +355,7 @@ def infer(ref_audio_orig, ref_text, gen_text, exp_name, remove_silence, cross_fa
 
     # Use the new chunk_text function to split gen_text
     max_chars = int(len(ref_text.encode('utf-8')) / (audio.shape[-1] / sr) * (25 - audio.shape[-1] / sr))
-    gen_text_batches = chunk_text(gen_text, max_chars=80)
+    gen_text_batches = chunk_text(gen_text, max_chars=100)
     print('ref_text', ref_text)
     for i, batch_text in enumerate(gen_text_batches):
         print(f'gen_text {i}', batch_text)