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| """Some utility functions for the app.""" | |
| from base64 import b64encode | |
| from io import BytesIO | |
| from gtts import gTTS | |
| from mtranslate import translate | |
| from speech_recognition import AudioFile, Recognizer | |
| from transformers import (BlenderbotSmallForConditionalGeneration, | |
| BlenderbotSmallTokenizer) | |
| def stt(audio: object, language: str) -> str: | |
| """Converts speech to text. | |
| Args: | |
| audio: record of user speech | |
| Returns: | |
| text (str): recognized speech of user | |
| """ | |
| # Create a Recognizer object | |
| r = Recognizer() | |
| # Open the audio file | |
| with AudioFile(audio) as source: | |
| # Listen for the data (load audio to memory) | |
| audio_data = r.record(source) | |
| # Transcribe the audio using Google's speech-to-text API | |
| text = r.recognize_google(audio_data, language=language) | |
| return text | |
| def to_en_translation(text: str, language: str) -> str: | |
| """Translates text from specified language to English. | |
| Args: | |
| text (str): input text | |
| language (str): desired language | |
| Returns: | |
| str: translated text | |
| """ | |
| return translate(text, "en", language) | |
| def from_en_translation(text: str, language: str) -> str: | |
| """Translates text from english to specified language. | |
| Args: | |
| text (str): input text | |
| language (str): desired language | |
| Returns: | |
| str: translated text | |
| """ | |
| return translate(text, language, "en") | |
| class TextGenerationPipeline: | |
| """Pipeline for text generation of blenderbot model. | |
| Returns: | |
| str: generated text | |
| """ | |
| # load tokenizer and the model | |
| model_name = "facebook/blenderbot_small-90M" | |
| tokenizer = BlenderbotSmallTokenizer.from_pretrained(model_name) | |
| model = BlenderbotSmallForConditionalGeneration.from_pretrained(model_name) | |
| def __init__(self, **kwargs): | |
| """Specififying text generation parameters. | |
| For example: max_length=100 which generates text shorter than | |
| 100 tokens. Visit: | |
| https://huggingface.co/docs/transformers/main_classes/text_generation | |
| for more parameters | |
| """ | |
| self.__dict__.update(kwargs) | |
| def preprocess(self, text) -> str: | |
| """Tokenizes input text. | |
| Args: | |
| text (str): user specified text | |
| Returns: | |
| torch.Tensor (obj): text representation as tensors | |
| """ | |
| return self.tokenizer(text, return_tensors="pt") | |
| def postprocess(self, outputs) -> str: | |
| """Converts tensors into text. | |
| Args: | |
| outputs (torch.Tensor obj): model text generation output | |
| Returns: | |
| str: generated text | |
| """ | |
| return self.tokenizer.decode(outputs[0], skip_special_tokens=True) | |
| def __call__(self, text: str) -> str: | |
| """Generates text from input text. | |
| Args: | |
| text (str): user specified text | |
| Returns: | |
| str: generated text | |
| """ | |
| tokenized_text = self.preprocess(text) | |
| output = self.model.generate(**tokenized_text, **self.__dict__) | |
| return self.postprocess(output) | |
| def tts(text: str, language: str) -> object: | |
| """Converts text into audio object. | |
| Args: | |
| text (str): generated answer of bot | |
| Returns: | |
| object: text to speech object | |
| """ | |
| return gTTS(text=text, lang=language, slow=False) | |
| def tts_to_bytesio(tts_object: object) -> bytes: | |
| """Converts tts object to bytes. | |
| Args: | |
| tts_object (object): audio object obtained from gtts | |
| Returns: | |
| bytes: audio bytes | |
| """ | |
| bytes_object = BytesIO() | |
| tts_object.write_to_fp(bytes_object) | |
| bytes_object.seek(0) | |
| return bytes_object.getvalue() | |
| def html_audio_autoplay(bytes: bytes) -> object: | |
| """Creates html object for autoplaying audio at gradio app. | |
| Args: | |
| bytes (bytes): audio bytes | |
| Returns: | |
| object: html object that provides audio autoplaying | |
| """ | |
| b64 = b64encode(bytes).decode() | |
| html = f""" | |
| <audio controls autoplay> | |
| <source src="data:audio/wav;base64,{b64}" type="audio/wav"> | |
| </audio> | |
| """ | |
| return html |