#8 Add docs

app.py

@@ -3,6 +3,7 @@ import gradio as gr
 from datetime import datetime
 from enum import Enum
 from ukrainian_tts.tts import TTS
+from torch.cuda import is_available
 
 class StressOption(Enum):
     AutomaticStress = "Автоматичні наголоси (за словником) 📖"
@@ -16,6 +17,7 @@ class VoiceOption(Enum):
     Dmytro = "Дмитро (чоловічий) 👨"
     Olga = "Ольга (жіночий) 👩"
 
+print(f"CUDA available? {is_available}")
 
 badge = (
     "https://visitor-badge-reloaded.herokuapp.com/badge?page_id=robinhad.ukrainian-tts"

requirements.txt

@@ -1,5 +1,4 @@
-TTS==0.8.0
+# requirements for HuggingFace demo. Installs local package.
+.
 torch==1.12.1
 --extra-index-url https://download.pytorch.org/whl/cu113
-ukrainian-word-stress==1.0.1
-git+https://github.com/egorsmkv/ukrainian-accentor.git@5b7971c4e135e3ff3283336962e63fc0b1c80f4c

ukrainian_tts/tts.py

@@ -1,12 +1,13 @@
 from io import BytesIO
 import requests
-from os.path import exists
+from os.path import exists, join
 from TTS.utils.synthesizer import Synthesizer
 from enum import Enum
 from .formatter import preprocess_text
 from torch import no_grad
 
 class Voices(Enum):
+    """List of available voices for the model."""
     Olena = "olena"
     Mykyta = "mykyta"
     Lada = "lada"
@@ -15,22 +16,39 @@ class Voices(Enum):
 
 
 class StressOption(Enum):
+    """Options how to stress sentence.
+    - `dictionary` - performs lookup in dictionary, taking into account grammatical case of a word and its' neighbors
+    - `model` - stress using transformer model"""
     Dictionary = "dictionary"
     Model = "model"
 
 
 class TTS:
+    """
+    
+    """
     def __init__(self, cache_folder=None) -> None:
+        """
+        Class to setup a text-to-speech engine, from download to model creation.  \n
+        Downloads or uses files from `cache_folder` directory.  \n
+        By default stores in current directory."""
         self.__setup_cache(cache_folder)
 
 
     def tts(self, text: str, voice: str, stress: str, output_fp=BytesIO()):
+        """
+        Run a Text-to-Speech engine and output to `output_fp` BytesIO-like object.
+        - `text` - your model input text.
+        - `voice` - one of predefined voices from `Voices` enum.
+        - `stress` - stress method options, predefined in `StressOption` enum.
+        - `output_fp` - file-like object output. Stores in RAM by default.
+        """
         autostress_with_model = (
             True if stress == StressOption.Model.value else False
         )
 
         if voice not in [option.value for option in Voices]:
-            raise ValueError("Invalid value for voice selected! Please use one of the following values: {', '.join([option.value for option in Voices])}.")
+            raise ValueError(f"Invalid value for voice selected! Please use one of the following values: {', '.join([option.value for option in Voices])}.")
 
         text = preprocess_text(text, autostress_with_model)
 
@@ -44,15 +62,19 @@ class TTS:
 
 
     def __setup_cache(self, cache_folder=None):
+        """Downloads models and stores them into `cache_folder`. By default stores in current directory."""
         print("downloading uk/mykyta/vits-tts")
         release_number = "v3.0.0"
         model_link = f"https://github.com/robinhad/ukrainian-tts/releases/download/{release_number}/model-inference.pth"
         config_link = f"https://github.com/robinhad/ukrainian-tts/releases/download/{release_number}/config.json"
         speakers_link = f"https://github.com/robinhad/ukrainian-tts/releases/download/{release_number}/speakers.pth"
 
-        model_path = "model.pth"
-        config_path = "config.json"
-        speakers_path = "speakers.pth"
+        if cache_folder is None:
+            cache_folder = "."
+
+        model_path = join(cache_folder, "model.pth")
+        config_path = join(cache_folder, "config.json")
+        speakers_path = join(cache_folder, "speakers.pth")
 
         self.__download(model_link, model_path)
         self.__download(config_link, config_path)
@@ -67,10 +89,11 @@ class TTS:
         )
 
         if self.synthesizer is None:
-            raise NameError("model not found")
+            raise NameError("Model not found")
 
 
     def __download(self, url, file_name):
+        """Downloads file from `url` into local `file_name` file."""
         if not exists(file_name):
             print(f"Downloading {file_name}")
             r = requests.get(url, allow_redirects=True)