Add metrics

README.md

@@ -14,6 +14,7 @@ pinned: false
 Ukrainian TTS (text-to-speech) using Coqui TTS.
 
 Link to online demo -> [https://huggingface.co/spaces/robinhad/ukrainian-tts](https://huggingface.co/spaces/robinhad/ukrainian-tts)  
+Note: online demo saves user input to improve user experience, by using it you give your consent to analyze this data.   
 Link to source code and models -> [https://github.com/robinhad/ukrainian-tts](https://github.com/robinhad/ukrainian-tts)  
 Telegram bot -> [https://t.me/uk_tts_bot](https://t.me/uk_tts_bot)  
 

app.py

@@ -4,6 +4,7 @@ from datetime import datetime
 from enum import Enum
 from ukrainian_tts.tts import TTS, Stress, Voices
 from torch.cuda import is_available
+from os import environ
 
 class StressOption(Enum):
     AutomaticStress = "Автоматичні наголоси (за словником) 📖"
@@ -57,6 +58,13 @@ def tts(text: str, voice: str, stress: str):
         _, text = ukr_tts.tts(text, speaker_name, stress_selected, fp)
         return fp.name, text
 
+if environ["HF_API_TOKEN"] is None:
+    print("Using default flagging.")
+    flagging_callback = gr.CSVLogger()
+else:
+    print("Using HuggingFace dataset saver.")
+    flagging_callback = gr.HuggingFaceDatasetSaver(hf_token=environ["HF_API_TOKEN"], dataset_name="uk-tts-output", private=True)
+
 
 with open("README.md") as file:
     article = file.read()
@@ -115,5 +123,8 @@ iface = gr.Interface(
             StressOption.AutomaticStress.value,
         ],
     ],
+    allow_flagging="auto",
+    flagging_callback=flagging_callback,
+    flagging_options=None
 )
 iface.launch(enable_queue=True)

flagged/uk-tts-output

@@ -0,0 +1 @@
+Subproject commit edbf469f4a6b6f20bb1ccf1d54b274435ad9e554