inital
This commit is contained in:
SOULOFCINDER
commit
dcb04d6f4c
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import io
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import os
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import ssl
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from contextlib import closing
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from typing import Optional, Tuple
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import datetime
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import boto3
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import gradio as gr
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import requests
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# UNCOMMENT TO USE WHISPER
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import warnings
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import whisper
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from langchain import ConversationChain, LLMChain
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from langchain.agents import load_tools, initialize_agent
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from langchain.chains.conversation.memory import ConversationBufferMemory
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from langchain.llms import OpenAI, OpenAIChat
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from threading import Lock
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# Console to variable
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from io import StringIO
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import sys
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import re
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from openai.error import AuthenticationError, InvalidRequestError, RateLimitError
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# Pertains to Express-inator functionality
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from langchain.prompts import PromptTemplate
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from polly_utils import PollyVoiceData, NEURAL_ENGINE
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from azure_utils import AzureVoiceData
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# Pertains to question answering functionality
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from langchain.embeddings.openai import OpenAIEmbeddings
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from langchain.text_splitter import CharacterTextSplitter
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from langchain.vectorstores.faiss import FAISS
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from langchain.docstore.document import Document
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from langchain.chains.question_answering import load_qa_chain
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news_api_key = os.environ["NEWS_API_KEY"]
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tmdb_bearer_token = os.environ["TMDB_BEARER_TOKEN"]
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TOOLS_LIST = ['serpapi', 'wolfram-alpha', 'pal-math',
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'pal-colored-objects'] # 'google-search','news-api','tmdb-api','open-meteo-api'
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TOOLS_DEFAULT_LIST = ['serpapi']
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BUG_FOUND_MSG = "Congratulations, you've found a bug in this application!"
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# AUTH_ERR_MSG = "Please paste your OpenAI key from openai.com to use this application. It is not necessary to hit a button or key after pasting it."
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AUTH_ERR_MSG = "Please paste your OpenAI key from openai.com to use this application. "
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MAX_TOKENS = 512
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LOOPING_TALKING_HEAD = "videos/Masahiro.mp4"
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TALKING_HEAD_WIDTH = "192"
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MAX_TALKING_HEAD_TEXT_LENGTH = 155
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# Pertains to Express-inator functionality
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NUM_WORDS_DEFAULT = 0
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MAX_WORDS = 400
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FORMALITY_DEFAULT = "N/A"
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TEMPERATURE_DEFAULT = 0.5
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EMOTION_DEFAULT = "N/A"
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LANG_LEVEL_DEFAULT = "N/A"
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TRANSLATE_TO_DEFAULT = "N/A"
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LITERARY_STYLE_DEFAULT = "N/A"
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PROMPT_TEMPLATE = PromptTemplate(
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input_variables=["original_words", "num_words", "formality", "emotions", "lang_level", "translate_to",
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"literary_style"],
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template="Restate {num_words}{formality}{emotions}{lang_level}{translate_to}{literary_style}the following: \n{original_words}\n",
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)
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FORCE_TRANSLATE_DEFAULT = True
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USE_GPT4_DEFAULT = False
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POLLY_VOICE_DATA = PollyVoiceData()
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AZURE_VOICE_DATA = AzureVoiceData()
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# Pertains to WHISPER functionality
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WHISPER_DETECT_LANG = "Detect language"
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# UNCOMMENT TO USE WHISPER
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warnings.filterwarnings("ignore")
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WHISPER_MODEL = whisper.load_model("tiny")
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print("WHISPER_MODEL", WHISPER_MODEL)
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# UNCOMMENT TO USE WHISPER
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def transcribe(aud_inp, whisper_lang):
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if aud_inp is None:
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return ""
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aud = whisper.load_audio(aud_inp)
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aud = whisper.pad_or_trim(aud)
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mel = whisper.log_mel_spectrogram(aud).to(WHISPER_MODEL.device)
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_, probs = WHISPER_MODEL.detect_language(mel)
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options = whisper.DecodingOptions()
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if whisper_lang != WHISPER_DETECT_LANG:
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whisper_lang_code = POLLY_VOICE_DATA.get_whisper_lang_code(whisper_lang)
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options = whisper.DecodingOptions(language=whisper_lang_code)
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result = whisper.decode(WHISPER_MODEL, mel, options)
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print("result.text", result.text)
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result_text = ""
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if result and result.text:
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result_text = result.text
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return result_text
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# Temporarily address Wolfram Alpha SSL certificate issue
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ssl._create_default_https_context = ssl._create_unverified_context
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# TEMPORARY FOR TESTING
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def transcribe_dummy(aud_inp_tb, whisper_lang):
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if aud_inp_tb is None:
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return ""
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# aud = whisper.load_audio(aud_inp)
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# aud = whisper.pad_or_trim(aud)
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# mel = whisper.log_mel_spectrogram(aud).to(WHISPER_MODEL.device)
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# _, probs = WHISPER_MODEL.detect_language(mel)
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# options = whisper.DecodingOptions()
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# options = whisper.DecodingOptions(language="ja")
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# result = whisper.decode(WHISPER_MODEL, mel, options)
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result_text = "Whisper will detect language"
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if whisper_lang != WHISPER_DETECT_LANG:
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whisper_lang_code = POLLY_VOICE_DATA.get_whisper_lang_code(whisper_lang)
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result_text = f"Whisper will use lang code: {whisper_lang_code}"
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print("result_text", result_text)
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return aud_inp_tb
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# Pertains to Express-inator functionality
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def transform_text(desc, express_chain, num_words, formality,
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anticipation_level, joy_level, trust_level,
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fear_level, surprise_level, sadness_level, disgust_level, anger_level,
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lang_level, translate_to, literary_style, force_translate):
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num_words_prompt = ""
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if num_words and int(num_words) != 0:
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num_words_prompt = "using up to " + str(num_words) + " words, "
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# Change some arguments to lower case
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formality = formality.lower()
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anticipation_level = anticipation_level.lower()
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joy_level = joy_level.lower()
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trust_level = trust_level.lower()
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fear_level = fear_level.lower()
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surprise_level = surprise_level.lower()
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sadness_level = sadness_level.lower()
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disgust_level = disgust_level.lower()
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anger_level = anger_level.lower()
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formality_str = ""
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if formality != "n/a":
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formality_str = "in a " + formality + " manner, "
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# put all emotions into a list
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emotions = []
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if anticipation_level != "n/a":
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emotions.append(anticipation_level)
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if joy_level != "n/a":
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emotions.append(joy_level)
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if trust_level != "n/a":
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emotions.append(trust_level)
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if fear_level != "n/a":
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emotions.append(fear_level)
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if surprise_level != "n/a":
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emotions.append(surprise_level)
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if sadness_level != "n/a":
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emotions.append(sadness_level)
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if disgust_level != "n/a":
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emotions.append(disgust_level)
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if anger_level != "n/a":
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emotions.append(anger_level)
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emotions_str = ""
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if len(emotions) > 0:
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if len(emotions) == 1:
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emotions_str = "with emotion of " + emotions[0] + ", "
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else:
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emotions_str = "with emotions of " + ", ".join(emotions[:-1]) + " and " + emotions[-1] + ", "
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lang_level_str = ""
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if lang_level != LANG_LEVEL_DEFAULT:
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lang_level_str = "at a level that a person in " + lang_level + " can easily comprehend, " if translate_to == TRANSLATE_TO_DEFAULT else ""
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translate_to_str = ""
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if translate_to != TRANSLATE_TO_DEFAULT and (force_translate or lang_level != LANG_LEVEL_DEFAULT):
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translate_to_str = "translated to " + translate_to + (
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"" if lang_level == LANG_LEVEL_DEFAULT else " at a level that a person in " + lang_level + " can easily comprehend") + ", "
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literary_style_str = ""
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if literary_style != LITERARY_STYLE_DEFAULT:
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if literary_style == "Prose":
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literary_style_str = "as prose, "
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if literary_style == "Story":
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literary_style_str = "as a story, "
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elif literary_style == "Summary":
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literary_style_str = "as a summary, "
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elif literary_style == "Outline":
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literary_style_str = "as an outline numbers and lower case letters, "
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elif literary_style == "Bullets":
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literary_style_str = "as bullet points using bullets, "
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elif literary_style == "Poetry":
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literary_style_str = "as a poem, "
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elif literary_style == "Haiku":
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literary_style_str = "as a haiku, "
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elif literary_style == "Limerick":
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literary_style_str = "as a limerick, "
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elif literary_style == "Rap":
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literary_style_str = "as a rap, "
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elif literary_style == "Joke":
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literary_style_str = "as a very funny joke with a setup and punchline, "
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elif literary_style == "Knock-knock":
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literary_style_str = "as a very funny knock-knock joke, "
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elif literary_style == "FAQ":
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literary_style_str = "as a FAQ with several questions and answers, "
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formatted_prompt = PROMPT_TEMPLATE.format(
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original_words=desc,
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num_words=num_words_prompt,
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formality=formality_str,
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emotions=emotions_str,
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lang_level=lang_level_str,
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translate_to=translate_to_str,
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literary_style=literary_style_str
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)
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trans_instr = num_words_prompt + formality_str + emotions_str + lang_level_str + translate_to_str + literary_style_str
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if express_chain and len(trans_instr.strip()) > 0:
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generated_text = express_chain.run(
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{'original_words': desc, 'num_words': num_words_prompt, 'formality': formality_str,
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'emotions': emotions_str, 'lang_level': lang_level_str, 'translate_to': translate_to_str,
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'literary_style': literary_style_str}).strip()
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else:
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print("Not transforming text")
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generated_text = desc
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# replace all newlines with <br> in generated_text
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generated_text = generated_text.replace("\n", "\n\n")
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prompt_plus_generated = "GPT prompt: " + formatted_prompt + "\n\n" + generated_text
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print("\n==== date/time: " + str(datetime.datetime.now() - datetime.timedelta(hours=5)) + " ====")
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print("prompt_plus_generated: " + prompt_plus_generated)
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return generated_text
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def load_chain(tools_list, llm):
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chain = None
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express_chain = None
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memory = None
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if llm:
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print("\ntools_list", tools_list)
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tool_names = tools_list
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tools = load_tools(tool_names, llm=llm, news_api_key=news_api_key, tmdb_bearer_token=tmdb_bearer_token)
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memory = ConversationBufferMemory(memory_key="chat_history")
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chain = initialize_agent(tools, llm, agent="conversational-react-description", verbose=True, memory=memory)
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express_chain = LLMChain(llm=llm, prompt=PROMPT_TEMPLATE, verbose=True)
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return chain, express_chain, memory
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def set_openai_api_key(api_key, use_gpt4):
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"""Set the api key and return chain.
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If no api_key, then None is returned.
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"""
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if api_key and api_key.startswith("sk-") and len(api_key) > 50:
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os.environ["OPENAI_API_KEY"] = api_key
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print("\n\n ++++++++++++++ Setting OpenAI API key ++++++++++++++ \n\n")
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print(str(datetime.datetime.now()) + ": Before OpenAI, OPENAI_API_KEY length: " + str(
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len(os.environ["OPENAI_API_KEY"])))
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if use_gpt4:
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llm = OpenAIChat(temperature=0, max_tokens=MAX_TOKENS, model_name="gpt-4")
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print("Trying to use llm OpenAIChat with gpt-4")
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else:
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print("Trying to use llm OpenAI with text-davinci-003")
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llm = OpenAI(temperature=0, max_tokens=MAX_TOKENS, model_name="text-davinci-003")
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print(str(datetime.datetime.now()) + ": After OpenAI, OPENAI_API_KEY length: " + str(
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len(os.environ["OPENAI_API_KEY"])))
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chain, express_chain, memory = load_chain(TOOLS_DEFAULT_LIST, llm)
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# Pertains to question answering functionality
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embeddings = OpenAIEmbeddings()
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if use_gpt4:
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qa_chain = load_qa_chain(OpenAIChat(temperature=0, model_name="gpt-4"), chain_type="stuff")
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print("Trying to use qa_chain OpenAIChat with gpt-4")
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else:
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print("Trying to use qa_chain OpenAI with text-davinci-003")
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qa_chain = OpenAI(temperature=0, max_tokens=MAX_TOKENS, model_name="text-davinci-003")
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print(str(datetime.datetime.now()) + ": After load_chain, OPENAI_API_KEY length: " + str(
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len(os.environ["OPENAI_API_KEY"])))
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os.environ["OPENAI_API_KEY"] = ""
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return chain, express_chain, llm, embeddings, qa_chain, memory, use_gpt4
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return None, None, None, None, None, None, None
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def run_chain(chain, inp, capture_hidden_text):
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output = ""
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hidden_text = None
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if capture_hidden_text:
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error_msg = None
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tmp = sys.stdout
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hidden_text_io = StringIO()
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sys.stdout = hidden_text_io
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try:
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output = chain.run(input=inp)
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except AuthenticationError as ae:
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error_msg = AUTH_ERR_MSG + str(datetime.datetime.now()) + ". " + str(ae)
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print("error_msg", error_msg)
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except RateLimitError as rle:
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error_msg = "\n\nRateLimitError: " + str(rle)
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except ValueError as ve:
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error_msg = "\n\nValueError: " + str(ve)
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except InvalidRequestError as ire:
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error_msg = "\n\nInvalidRequestError: " + str(ire)
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except Exception as e:
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error_msg = "\n\n" + BUG_FOUND_MSG + ":\n\n" + str(e)
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sys.stdout = tmp
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hidden_text = hidden_text_io.getvalue()
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# remove escape characters from hidden_text
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hidden_text = re.sub(r'\x1b[^m]*m', '', hidden_text)
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# remove "Entering new AgentExecutor chain..." from hidden_text
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hidden_text = re.sub(r"Entering new AgentExecutor chain...\n", "", hidden_text)
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# remove "Finished chain." from hidden_text
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hidden_text = re.sub(r"Finished chain.", "", hidden_text)
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# Add newline after "Thought:" "Action:" "Observation:" "Input:" and "AI:"
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hidden_text = re.sub(r"Thought:", "\n\nThought:", hidden_text)
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hidden_text = re.sub(r"Action:", "\n\nAction:", hidden_text)
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hidden_text = re.sub(r"Observation:", "\n\nObservation:", hidden_text)
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hidden_text = re.sub(r"Input:", "\n\nInput:", hidden_text)
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hidden_text = re.sub(r"AI:", "\n\nAI:", hidden_text)
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||||
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if error_msg:
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hidden_text += error_msg
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||||
print("hidden_text: ", hidden_text)
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else:
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try:
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||||
output = chain.run(input=inp)
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except AuthenticationError as ae:
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||||
output = AUTH_ERR_MSG + str(datetime.datetime.now()) + ". " + str(ae)
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||||
print("output", output)
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||||
except RateLimitError as rle:
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||||
output = "\n\nRateLimitError: " + str(rle)
|
||||
except ValueError as ve:
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||||
output = "\n\nValueError: " + str(ve)
|
||||
except InvalidRequestError as ire:
|
||||
output = "\n\nInvalidRequestError: " + str(ire)
|
||||
except Exception as e:
|
||||
output = "\n\n" + BUG_FOUND_MSG + ":\n\n" + str(e)
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||||
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||||
return output, hidden_text
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||||
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||||
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||||
def reset_memory(history, memory):
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||||
memory.clear()
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||||
history = []
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||||
return history, history, memory
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||||
|
||||
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||||
class ChatWrapper:
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||||
|
||||
def __init__(self):
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||||
self.lock = Lock()
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||||
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||||
def __call__(
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||||
self, api_key: str, inp: str, history: Optional[Tuple[str, str]], chain: Optional[ConversationChain],
|
||||
trace_chain: bool, speak_text: bool, talking_head: bool, monologue: bool, express_chain: Optional[LLMChain],
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||||
num_words, formality, anticipation_level, joy_level, trust_level,
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||||
fear_level, surprise_level, sadness_level, disgust_level, anger_level,
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||||
lang_level, translate_to, literary_style, qa_chain, docsearch, use_embeddings, force_translate
|
||||
):
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||||
"""Execute the chat functionality."""
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||||
self.lock.acquire()
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||||
try:
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||||
print("\n==== date/time: " + str(datetime.datetime.now()) + " ====")
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||||
print("inp: " + inp)
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||||
print("trace_chain: ", trace_chain)
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||||
print("speak_text: ", speak_text)
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print("talking_head: ", talking_head)
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||||
print("monologue: ", monologue)
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||||
history = history or []
|
||||
# If chain is None, that is because no API key was provided.
|
||||
output = "Please paste your OpenAI key from openai.com to use this app. " + str(datetime.datetime.now())
|
||||
hidden_text = output
|
||||
|
||||
if chain:
|
||||
# Set OpenAI key
|
||||
import openai
|
||||
openai.api_key = api_key
|
||||
if not monologue:
|
||||
if use_embeddings:
|
||||
if inp and inp.strip() != "":
|
||||
if docsearch:
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||||
docs = docsearch.similarity_search(inp)
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||||
output = str(qa_chain.run(input_documents=docs, question=inp))
|
||||
else:
|
||||
output, hidden_text = "Please supply some text in the the Embeddings tab.", None
|
||||
else:
|
||||
output, hidden_text = "What's on your mind?", None
|
||||
else:
|
||||
output, hidden_text = run_chain(chain, inp, capture_hidden_text=trace_chain)
|
||||
else:
|
||||
output, hidden_text = inp, None
|
||||
|
||||
output = transform_text(output, express_chain, num_words, formality, anticipation_level, joy_level,
|
||||
trust_level,
|
||||
fear_level, surprise_level, sadness_level, disgust_level, anger_level,
|
||||
lang_level, translate_to, literary_style, force_translate)
|
||||
|
||||
text_to_display = output
|
||||
if trace_chain:
|
||||
text_to_display = hidden_text + "\n\n" + output
|
||||
history.append((inp, text_to_display))
|
||||
|
||||
html_video, temp_file, html_audio, temp_aud_file = None, None, None, None
|
||||
if speak_text:
|
||||
if talking_head:
|
||||
if len(output) <= MAX_TALKING_HEAD_TEXT_LENGTH:
|
||||
html_video, temp_file = do_html_video_speak(output, translate_to)
|
||||
else:
|
||||
temp_file = LOOPING_TALKING_HEAD
|
||||
html_video = create_html_video(temp_file, TALKING_HEAD_WIDTH)
|
||||
html_audio, temp_aud_file = do_html_audio_speak(output, translate_to)
|
||||
else:
|
||||
html_audio, temp_aud_file = do_html_audio_speak(output, translate_to)
|
||||
else:
|
||||
if talking_head:
|
||||
temp_file = LOOPING_TALKING_HEAD
|
||||
html_video = create_html_video(temp_file, TALKING_HEAD_WIDTH)
|
||||
else:
|
||||
# html_audio, temp_aud_file = do_html_audio_speak(output, translate_to)
|
||||
# html_video = create_html_video(temp_file, "128")
|
||||
pass
|
||||
|
||||
except Exception as e:
|
||||
raise e
|
||||
finally:
|
||||
self.lock.release()
|
||||
return history, history, html_video, temp_file, html_audio, temp_aud_file, ""
|
||||
# return history, history, html_audio, temp_aud_file, ""
|
||||
|
||||
|
||||
chat = ChatWrapper()
|
||||
|
||||
|
||||
def do_html_audio_speak(words_to_speak, polly_language):
|
||||
polly_client = boto3.Session(
|
||||
aws_access_key_id=os.environ["AWS_ACCESS_KEY_ID"],
|
||||
aws_secret_access_key=os.environ["AWS_SECRET_ACCESS_KEY"],
|
||||
region_name=os.environ["AWS_DEFAULT_REGION"]
|
||||
).client('polly')
|
||||
|
||||
# voice_id, language_code, engine = POLLY_VOICE_DATA.get_voice(polly_language, "Female")
|
||||
voice_id, language_code, engine = POLLY_VOICE_DATA.get_voice(polly_language, "Male")
|
||||
if not voice_id:
|
||||
# voice_id = "Joanna"
|
||||
voice_id = "Matthew"
|
||||
language_code = "en-US"
|
||||
engine = NEURAL_ENGINE
|
||||
response = polly_client.synthesize_speech(
|
||||
Text=words_to_speak,
|
||||
OutputFormat='mp3',
|
||||
VoiceId=voice_id,
|
||||
LanguageCode=language_code,
|
||||
Engine=engine
|
||||
)
|
||||
|
||||
html_audio = '<pre>no audio</pre>'
|
||||
|
||||
# Save the audio stream returned by Amazon Polly on Lambda's temp directory
|
||||
if "AudioStream" in response:
|
||||
with closing(response["AudioStream"]) as stream:
|
||||
# output = os.path.join("/tmp/", "speech.mp3")
|
||||
|
||||
try:
|
||||
with open('audios/tempfile.mp3', 'wb') as f:
|
||||
f.write(stream.read())
|
||||
temp_aud_file = gr.File("audios/tempfile.mp3")
|
||||
temp_aud_file_url = "/file=" + temp_aud_file.value['name']
|
||||
html_audio = f'<audio autoplay><source src={temp_aud_file_url} type="audio/mp3"></audio>'
|
||||
except IOError as error:
|
||||
# Could not write to file, exit gracefully
|
||||
print(error)
|
||||
return None, None
|
||||
else:
|
||||
# The response didn't contain audio data, exit gracefully
|
||||
print("Could not stream audio")
|
||||
return None, None
|
||||
|
||||
return html_audio, "audios/tempfile.mp3"
|
||||
|
||||
|
||||
def create_html_video(file_name, width):
|
||||
temp_file_url = "/file=" + tmp_file.value['name']
|
||||
html_video = f'<video width={width} height={width} autoplay muted loop><source src={temp_file_url} type="video/mp4" poster="Masahiro.png"></video>'
|
||||
return html_video
|
||||
|
||||
|
||||
def do_html_video_speak(words_to_speak, azure_language):
|
||||
azure_voice = AZURE_VOICE_DATA.get_voice(azure_language, "Male")
|
||||
if not azure_voice:
|
||||
azure_voice = "en-US-ChristopherNeural"
|
||||
|
||||
headers = {"Authorization": f"Bearer {os.environ['EXHUMAN_API_KEY']}"}
|
||||
body = {
|
||||
'bot_name': 'Masahiro',
|
||||
'bot_response': words_to_speak,
|
||||
'azure_voice': azure_voice,
|
||||
'azure_style': 'friendly',
|
||||
'animation_pipeline': 'high_speed',
|
||||
}
|
||||
api_endpoint = "https://api.exh.ai/animations/v1/generate_lipsync"
|
||||
res = requests.post(api_endpoint, json=body, headers=headers)
|
||||
print("res.status_code: ", res.status_code)
|
||||
|
||||
html_video = '<pre>no video</pre>'
|
||||
if isinstance(res.content, bytes):
|
||||
response_stream = io.BytesIO(res.content)
|
||||
print("len(res.content)): ", len(res.content))
|
||||
|
||||
with open('videos/tempfile.mp4', 'wb') as f:
|
||||
f.write(response_stream.read())
|
||||
temp_file = gr.File("videos/tempfile.mp4")
|
||||
temp_file_url = "/file=" + temp_file.value['name']
|
||||
html_video = f'<video width={TALKING_HEAD_WIDTH} height={TALKING_HEAD_WIDTH} autoplay><source src={temp_file_url} type="video/mp4" poster="Masahiro.png"></video>'
|
||||
else:
|
||||
print('video url unknown')
|
||||
return html_video, "videos/tempfile.mp4"
|
||||
|
||||
|
||||
def update_selected_tools(widget, state, llm):
|
||||
if widget:
|
||||
state = widget
|
||||
chain, express_chain, memory = load_chain(state, llm)
|
||||
return state, llm, chain, express_chain
|
||||
|
||||
|
||||
def update_talking_head(widget, state):
|
||||
if widget:
|
||||
state = widget
|
||||
|
||||
video_html_talking_head = create_html_video(LOOPING_TALKING_HEAD, TALKING_HEAD_WIDTH)
|
||||
return state, video_html_talking_head
|
||||
else:
|
||||
# return state, create_html_video(LOOPING_TALKING_HEAD, "32")
|
||||
return None, "<pre></pre>"
|
||||
|
||||
|
||||
def update_foo(widget, state):
|
||||
if widget:
|
||||
state = widget
|
||||
return state
|
||||
|
||||
|
||||
# Pertains to question answering functionality
|
||||
def update_embeddings(embeddings_text, embeddings, qa_chain):
|
||||
if embeddings_text:
|
||||
text_splitter = CharacterTextSplitter(chunk_size=1000, chunk_overlap=0)
|
||||
texts = text_splitter.split_text(embeddings_text)
|
||||
|
||||
docsearch = FAISS.from_texts(texts, embeddings)
|
||||
print("Embeddings updated")
|
||||
return docsearch
|
||||
|
||||
|
||||
# Pertains to question answering functionality
|
||||
def update_use_embeddings(widget, state):
|
||||
if widget:
|
||||
state = widget
|
||||
return state
|
||||
|
||||
|
||||
with gr.Blocks(css=".gradio-container {background-color: lightgray}") as block:
|
||||
llm_state = gr.State()
|
||||
history_state = gr.State()
|
||||
chain_state = gr.State()
|
||||
express_chain_state = gr.State()
|
||||
tools_list_state = gr.State(TOOLS_DEFAULT_LIST)
|
||||
trace_chain_state = gr.State(False)
|
||||
speak_text_state = gr.State(False)
|
||||
talking_head_state = gr.State(True)
|
||||
monologue_state = gr.State(False) # Takes the input and repeats it back to the user, optionally transforming it.
|
||||
force_translate_state = gr.State(FORCE_TRANSLATE_DEFAULT) #
|
||||
memory_state = gr.State()
|
||||
|
||||
# Pertains to Express-inator functionality
|
||||
num_words_state = gr.State(NUM_WORDS_DEFAULT)
|
||||
formality_state = gr.State(FORMALITY_DEFAULT)
|
||||
anticipation_level_state = gr.State(EMOTION_DEFAULT)
|
||||
joy_level_state = gr.State(EMOTION_DEFAULT)
|
||||
trust_level_state = gr.State(EMOTION_DEFAULT)
|
||||
fear_level_state = gr.State(EMOTION_DEFAULT)
|
||||
surprise_level_state = gr.State(EMOTION_DEFAULT)
|
||||
sadness_level_state = gr.State(EMOTION_DEFAULT)
|
||||
disgust_level_state = gr.State(EMOTION_DEFAULT)
|
||||
anger_level_state = gr.State(EMOTION_DEFAULT)
|
||||
lang_level_state = gr.State(LANG_LEVEL_DEFAULT)
|
||||
translate_to_state = gr.State(TRANSLATE_TO_DEFAULT)
|
||||
literary_style_state = gr.State(LITERARY_STYLE_DEFAULT)
|
||||
|
||||
# Pertains to WHISPER functionality
|
||||
whisper_lang_state = gr.State(WHISPER_DETECT_LANG)
|
||||
|
||||
# Pertains to question answering functionality
|
||||
embeddings_state = gr.State()
|
||||
qa_chain_state = gr.State()
|
||||
docsearch_state = gr.State()
|
||||
use_embeddings_state = gr.State(False)
|
||||
|
||||
use_gpt4_state = gr.State(USE_GPT4_DEFAULT)
|
||||
|
||||
with gr.Tab("Chat"):
|
||||
with gr.Row():
|
||||
with gr.Column():
|
||||
gr.HTML(
|
||||
"""<b><center>GPT + WolframAlpha + Whisper</center></b>
|
||||
<p><center>Hit Enter after pasting your OpenAI API key.</center></p>
|
||||
<i><center>If you have GPT-4 access, optionally select it in Settings tab.</center></i>""")
|
||||
|
||||
openai_api_key_textbox = gr.Textbox(placeholder="Paste your OpenAI API key (sk-...) and hit Enter",
|
||||
show_label=False, lines=1, type='password')
|
||||
|
||||
with gr.Row():
|
||||
with gr.Column(scale=1, min_width=TALKING_HEAD_WIDTH, visible=True):
|
||||
speak_text_cb = gr.Checkbox(label="Enable speech", value=False)
|
||||
speak_text_cb.change(update_foo, inputs=[speak_text_cb, speak_text_state],
|
||||
outputs=[speak_text_state])
|
||||
|
||||
my_file = gr.File(label="Upload a file", type="file", visible=False)
|
||||
tmp_file = gr.File(LOOPING_TALKING_HEAD, visible=False)
|
||||
# tmp_file_url = "/file=" + tmp_file.value['name']
|
||||
htm_video = create_html_video(LOOPING_TALKING_HEAD, TALKING_HEAD_WIDTH)
|
||||
video_html = gr.HTML(htm_video)
|
||||
|
||||
# my_aud_file = gr.File(label="Audio file", type="file", visible=True)
|
||||
tmp_aud_file = gr.File("audios/tempfile.mp3", visible=False)
|
||||
tmp_aud_file_url = "/file=" + tmp_aud_file.value['name']
|
||||
htm_audio = f'<audio><source src={tmp_aud_file_url} type="audio/mp3"></audio>'
|
||||
audio_html = gr.HTML(htm_audio)
|
||||
|
||||
with gr.Column(scale=7):
|
||||
chatbot = gr.Chatbot()
|
||||
|
||||
with gr.Row():
|
||||
message = gr.Textbox(label="What's on your mind??",
|
||||
placeholder="What's the answer to life, the universe, and everything?",
|
||||
lines=1)
|
||||
submit = gr.Button(value="Send", variant="secondary").style(full_width=False)
|
||||
|
||||
# UNCOMMENT TO USE WHISPER
|
||||
with gr.Row():
|
||||
audio_comp = gr.Microphone(source="microphone", type="filepath", label="Just say it!",
|
||||
interactive=True, streaming=False)
|
||||
audio_comp.change(transcribe, inputs=[audio_comp, whisper_lang_state], outputs=[message])
|
||||
|
||||
# TEMPORARY FOR TESTING
|
||||
# with gr.Row():
|
||||
# audio_comp_tb = gr.Textbox(label="Just say it!", lines=1)
|
||||
# audio_comp_tb.submit(transcribe_dummy, inputs=[audio_comp_tb, whisper_lang_state], outputs=[message])
|
||||
|
||||
gr.Examples(
|
||||
examples=["How many people live in Canada?",
|
||||
"What is 2 to the 30th power?",
|
||||
"If x+y=10 and x-y=4, what are x and y?",
|
||||
"How much did it rain in SF today?",
|
||||
"Get me information about the movie 'Avatar'",
|
||||
"What are the top tech headlines in the US?",
|
||||
"On the desk, you see two blue booklets, two purple booklets, and two yellow pairs of sunglasses - "
|
||||
"if I remove all the pairs of sunglasses from the desk, how many purple items remain on it?"],
|
||||
inputs=message
|
||||
)
|
||||
|
||||
with gr.Tab("Settings"):
|
||||
tools_cb_group = gr.CheckboxGroup(label="Tools:", choices=TOOLS_LIST,
|
||||
value=TOOLS_DEFAULT_LIST)
|
||||
tools_cb_group.change(update_selected_tools,
|
||||
inputs=[tools_cb_group, tools_list_state, llm_state],
|
||||
outputs=[tools_list_state, llm_state, chain_state, express_chain_state])
|
||||
|
||||
trace_chain_cb = gr.Checkbox(label="Show reasoning chain in chat bubble", value=False)
|
||||
trace_chain_cb.change(update_foo, inputs=[trace_chain_cb, trace_chain_state],
|
||||
outputs=[trace_chain_state])
|
||||
|
||||
force_translate_cb = gr.Checkbox(label="Force translation to selected Output Language",
|
||||
value=FORCE_TRANSLATE_DEFAULT)
|
||||
force_translate_cb.change(update_foo, inputs=[force_translate_cb, force_translate_state],
|
||||
outputs=[force_translate_state])
|
||||
|
||||
# speak_text_cb = gr.Checkbox(label="Speak text from agent", value=False)
|
||||
# speak_text_cb.change(update_foo, inputs=[speak_text_cb, speak_text_state],
|
||||
# outputs=[speak_text_state])
|
||||
|
||||
talking_head_cb = gr.Checkbox(label="Show talking head", value=True)
|
||||
talking_head_cb.change(update_talking_head, inputs=[talking_head_cb, talking_head_state],
|
||||
outputs=[talking_head_state, video_html])
|
||||
|
||||
monologue_cb = gr.Checkbox(label="Babel fish mode (translate/restate what you enter, no conversational agent)",
|
||||
value=False)
|
||||
monologue_cb.change(update_foo, inputs=[monologue_cb, monologue_state],
|
||||
outputs=[monologue_state])
|
||||
|
||||
use_gpt4_cb = gr.Checkbox(label="Use GPT-4 (experimental) if your OpenAI API has access to it",
|
||||
value=USE_GPT4_DEFAULT)
|
||||
use_gpt4_cb.change(set_openai_api_key,
|
||||
inputs=[openai_api_key_textbox, use_gpt4_cb],
|
||||
outputs=[chain_state, express_chain_state, llm_state, embeddings_state,
|
||||
qa_chain_state, memory_state, use_gpt4_state])
|
||||
|
||||
reset_btn = gr.Button(value="Reset chat", variant="secondary").style(full_width=False)
|
||||
reset_btn.click(reset_memory, inputs=[history_state, memory_state],
|
||||
outputs=[chatbot, history_state, memory_state])
|
||||
|
||||
with gr.Tab("Whisper STT"):
|
||||
whisper_lang_radio = gr.Radio(label="Whisper speech-to-text language:", choices=[
|
||||
WHISPER_DETECT_LANG, "Arabic", "Arabic (Gulf)", "Catalan", "Chinese (Cantonese)", "Chinese (Mandarin)",
|
||||
"Danish", "Dutch", "English (Australian)", "English (British)", "English (Indian)", "English (New Zealand)",
|
||||
"English (South African)", "English (US)", "English (Welsh)", "Finnish", "French", "French (Canadian)",
|
||||
"German", "German (Austrian)", "Georgian", "Hindi", "Icelandic", "Indonesian", "Italian", "Japanese",
|
||||
"Korean", "Norwegian", "Polish",
|
||||
"Portuguese (Brazilian)", "Portuguese (European)", "Romanian", "Russian", "Spanish (European)",
|
||||
"Spanish (Mexican)", "Spanish (US)", "Swedish", "Turkish", "Ukrainian", "Welsh"],
|
||||
value=WHISPER_DETECT_LANG)
|
||||
|
||||
whisper_lang_radio.change(update_foo,
|
||||
inputs=[whisper_lang_radio, whisper_lang_state],
|
||||
outputs=[whisper_lang_state])
|
||||
|
||||
with gr.Tab("Output Language"):
|
||||
lang_level_radio = gr.Radio(label="Language level:", choices=[
|
||||
LANG_LEVEL_DEFAULT, "1st grade", "2nd grade", "3rd grade", "4th grade", "5th grade", "6th grade",
|
||||
"7th grade", "8th grade", "9th grade", "10th grade", "11th grade", "12th grade", "University"],
|
||||
value=LANG_LEVEL_DEFAULT)
|
||||
lang_level_radio.change(update_foo, inputs=[lang_level_radio, lang_level_state],
|
||||
outputs=[lang_level_state])
|
||||
|
||||
translate_to_radio = gr.Radio(label="Language:", choices=[
|
||||
TRANSLATE_TO_DEFAULT, "Arabic", "Arabic (Gulf)", "Catalan", "Chinese (Cantonese)", "Chinese (Mandarin)",
|
||||
"Danish", "Dutch", "English (Australian)", "English (British)", "English (Indian)", "English (New Zealand)",
|
||||
"English (South African)", "English (US)", "English (Welsh)", "Finnish", "French", "French (Canadian)",
|
||||
"German", "German (Austrian)", "Georgian", "Hindi", "Icelandic", "Indonesian", "Italian", "Japanese",
|
||||
"Korean", "Norwegian", "Polish",
|
||||
"Portuguese (Brazilian)", "Portuguese (European)", "Romanian", "Russian", "Spanish (European)",
|
||||
"Spanish (Mexican)", "Spanish (US)", "Swedish", "Turkish", "Ukrainian", "Welsh",
|
||||
"emojis", "Gen Z slang", "how the stereotypical Karen would say it", "Klingon", "Neanderthal",
|
||||
"Pirate", "Strange Planet expospeak technical talk", "Yoda"],
|
||||
value=TRANSLATE_TO_DEFAULT)
|
||||
|
||||
translate_to_radio.change(update_foo,
|
||||
inputs=[translate_to_radio, translate_to_state],
|
||||
outputs=[translate_to_state])
|
||||
|
||||
with gr.Tab("Formality"):
|
||||
formality_radio = gr.Radio(label="Formality:",
|
||||
choices=[FORMALITY_DEFAULT, "Casual", "Polite", "Honorific"],
|
||||
value=FORMALITY_DEFAULT)
|
||||
formality_radio.change(update_foo,
|
||||
inputs=[formality_radio, formality_state],
|
||||
outputs=[formality_state])
|
||||
|
||||
with gr.Tab("Lit Style"):
|
||||
literary_style_radio = gr.Radio(label="Literary style:", choices=[
|
||||
LITERARY_STYLE_DEFAULT, "Prose", "Story", "Summary", "Outline", "Bullets", "Poetry", "Haiku", "Limerick",
|
||||
"Rap",
|
||||
"Joke", "Knock-knock", "FAQ"],
|
||||
value=LITERARY_STYLE_DEFAULT)
|
||||
|
||||
literary_style_radio.change(update_foo,
|
||||
inputs=[literary_style_radio, literary_style_state],
|
||||
outputs=[literary_style_state])
|
||||
|
||||
with gr.Tab("Emotions"):
|
||||
anticipation_level_radio = gr.Radio(label="Anticipation level:",
|
||||
choices=[EMOTION_DEFAULT, "Interest", "Anticipation", "Vigilance"],
|
||||
value=EMOTION_DEFAULT)
|
||||
anticipation_level_radio.change(update_foo,
|
||||
inputs=[anticipation_level_radio, anticipation_level_state],
|
||||
outputs=[anticipation_level_state])
|
||||
|
||||
joy_level_radio = gr.Radio(label="Joy level:",
|
||||
choices=[EMOTION_DEFAULT, "Serenity", "Joy", "Ecstasy"],
|
||||
value=EMOTION_DEFAULT)
|
||||
joy_level_radio.change(update_foo,
|
||||
inputs=[joy_level_radio, joy_level_state],
|
||||
outputs=[joy_level_state])
|
||||
|
||||
trust_level_radio = gr.Radio(label="Trust level:",
|
||||
choices=[EMOTION_DEFAULT, "Acceptance", "Trust", "Admiration"],
|
||||
value=EMOTION_DEFAULT)
|
||||
trust_level_radio.change(update_foo,
|
||||
inputs=[trust_level_radio, trust_level_state],
|
||||
outputs=[trust_level_state])
|
||||
|
||||
fear_level_radio = gr.Radio(label="Fear level:",
|
||||
choices=[EMOTION_DEFAULT, "Apprehension", "Fear", "Terror"],
|
||||
value=EMOTION_DEFAULT)
|
||||
fear_level_radio.change(update_foo,
|
||||
inputs=[fear_level_radio, fear_level_state],
|
||||
outputs=[fear_level_state])
|
||||
|
||||
surprise_level_radio = gr.Radio(label="Surprise level:",
|
||||
choices=[EMOTION_DEFAULT, "Distraction", "Surprise", "Amazement"],
|
||||
value=EMOTION_DEFAULT)
|
||||
surprise_level_radio.change(update_foo,
|
||||
inputs=[surprise_level_radio, surprise_level_state],
|
||||
outputs=[surprise_level_state])
|
||||
|
||||
sadness_level_radio = gr.Radio(label="Sadness level:",
|
||||
choices=[EMOTION_DEFAULT, "Pensiveness", "Sadness", "Grief"],
|
||||
value=EMOTION_DEFAULT)
|
||||
sadness_level_radio.change(update_foo,
|
||||
inputs=[sadness_level_radio, sadness_level_state],
|
||||
outputs=[sadness_level_state])
|
||||
|
||||
disgust_level_radio = gr.Radio(label="Disgust level:",
|
||||
choices=[EMOTION_DEFAULT, "Boredom", "Disgust", "Loathing"],
|
||||
value=EMOTION_DEFAULT)
|
||||
disgust_level_radio.change(update_foo,
|
||||
inputs=[disgust_level_radio, disgust_level_state],
|
||||
outputs=[disgust_level_state])
|
||||
|
||||
anger_level_radio = gr.Radio(label="Anger level:",
|
||||
choices=[EMOTION_DEFAULT, "Annoyance", "Anger", "Rage"],
|
||||
value=EMOTION_DEFAULT)
|
||||
anger_level_radio.change(update_foo,
|
||||
inputs=[anger_level_radio, anger_level_state],
|
||||
outputs=[anger_level_state])
|
||||
|
||||
with gr.Tab("Max Words"):
|
||||
num_words_slider = gr.Slider(label="Max number of words to generate (0 for don't care)",
|
||||
value=NUM_WORDS_DEFAULT, minimum=0, maximum=MAX_WORDS, step=10)
|
||||
num_words_slider.change(update_foo,
|
||||
inputs=[num_words_slider, num_words_state],
|
||||
outputs=[num_words_state])
|
||||
|
||||
with gr.Tab("Embeddings"):
|
||||
embeddings_text_box = gr.Textbox(label="Enter text for embeddings and hit Create:",
|
||||
lines=20)
|
||||
|
||||
with gr.Row():
|
||||
use_embeddings_cb = gr.Checkbox(label="Use embeddings", value=False)
|
||||
use_embeddings_cb.change(update_use_embeddings, inputs=[use_embeddings_cb, use_embeddings_state],
|
||||
outputs=[use_embeddings_state])
|
||||
|
||||
embeddings_text_submit = gr.Button(value="Create", variant="secondary").style(full_width=False)
|
||||
embeddings_text_submit.click(update_embeddings,
|
||||
inputs=[embeddings_text_box, embeddings_state, qa_chain_state],
|
||||
outputs=[docsearch_state])
|
||||
|
||||
gr.HTML("""
|
||||
<p>This application, developed by <a href='https://www.linkedin.com/in/javafxpert/'>James L. Weaver</a>,
|
||||
demonstrates a conversational agent implemented with OpenAI GPT-3.5 and LangChain.
|
||||
When necessary, it leverages tools for complex math, searching the internet, and accessing news and weather.
|
||||
Uses talking heads from <a href='https://exh.ai/'>Ex-Human</a>.
|
||||
For faster inference without waiting in queue, you may duplicate the space.
|
||||
</p>""")
|
||||
|
||||
gr.HTML("""
|
||||
<form action="https://www.paypal.com/donate" method="post" target="_blank">
|
||||
<input type="hidden" name="business" value="AK8BVNALBXSPQ" />
|
||||
<input type="hidden" name="no_recurring" value="0" />
|
||||
<input type="hidden" name="item_name" value="Please consider helping to defray the cost of APIs such as SerpAPI and WolframAlpha that this app uses." />
|
||||
<input type="hidden" name="currency_code" value="USD" />
|
||||
<input type="image" src="https://www.paypalobjects.com/en_US/i/btn/btn_donate_LG.gif" border="0" name="submit" title="PayPal - The safer, easier way to pay online!" alt="Donate with PayPal button" />
|
||||
<img alt="" border="0" src="https://www.paypal.com/en_US/i/scr/pixel.gif" width="1" height="1" />
|
||||
</form>
|
||||
""")
|
||||
|
||||
gr.HTML("""<center>
|
||||
<a href="https://huggingface.co/spaces/JavaFXpert/Chat-GPT-LangChain?duplicate=true">
|
||||
<img style="margin-top: 0em; margin-bottom: 0em" src="https://bit.ly/3gLdBN6" alt="Duplicate Space"></a>
|
||||
Powered by <a href='https://github.com/hwchase17/langchain'>LangChain 🦜️🔗</a>
|
||||
</center>""")
|
||||
|
||||
message.submit(chat, inputs=[openai_api_key_textbox, message, history_state, chain_state, trace_chain_state,
|
||||
speak_text_state, talking_head_state, monologue_state,
|
||||
express_chain_state, num_words_state, formality_state,
|
||||
anticipation_level_state, joy_level_state, trust_level_state, fear_level_state,
|
||||
surprise_level_state, sadness_level_state, disgust_level_state, anger_level_state,
|
||||
lang_level_state, translate_to_state, literary_style_state,
|
||||
qa_chain_state, docsearch_state, use_embeddings_state,
|
||||
force_translate_state],
|
||||
outputs=[chatbot, history_state, video_html, my_file, audio_html, tmp_aud_file, message])
|
||||
|
||||
submit.click(chat, inputs=[openai_api_key_textbox, message, history_state, chain_state, trace_chain_state,
|
||||
speak_text_state, talking_head_state, monologue_state,
|
||||
express_chain_state, num_words_state, formality_state,
|
||||
anticipation_level_state, joy_level_state, trust_level_state, fear_level_state,
|
||||
surprise_level_state, sadness_level_state, disgust_level_state, anger_level_state,
|
||||
lang_level_state, translate_to_state, literary_style_state,
|
||||
qa_chain_state, docsearch_state, use_embeddings_state,
|
||||
force_translate_state],
|
||||
outputs=[chatbot, history_state, video_html, my_file, audio_html, tmp_aud_file, message])
|
||||
|
||||
openai_api_key_textbox.change(set_openai_api_key,
|
||||
inputs=[openai_api_key_textbox, use_gpt4_state],
|
||||
outputs=[chain_state, express_chain_state, llm_state, embeddings_state,
|
||||
qa_chain_state, memory_state, use_gpt4_state])
|
||||
openai_api_key_textbox.submit(set_openai_api_key,
|
||||
inputs=[openai_api_key_textbox, use_gpt4_state],
|
||||
outputs=[chain_state, express_chain_state, llm_state, embeddings_state,
|
||||
qa_chain_state, memory_state, use_gpt4_state])
|
||||
|
||||
block.launch(debug=True)
|
||||
|
|
@ -0,0 +1,155 @@
|
|||
# This class stores Azure voice data. Specifically, the class stores several records containing
|
||||
# language, lang_code, gender, voice_id and engine. The class also has a method to return the
|
||||
# voice_id, lang_code and engine given a language and gender.
|
||||
|
||||
NEURAL_ENGINE = "neural"
|
||||
STANDARD_ENGINE = "standard"
|
||||
|
||||
|
||||
class AzureVoiceData:
|
||||
def get_voice(self, language, gender):
|
||||
for voice in self.voice_data:
|
||||
if voice['language'] == language and voice['gender'] == gender:
|
||||
return voice['azure_voice']
|
||||
return None
|
||||
|
||||
def __init__(self):
|
||||
self.voice_data = [
|
||||
{'language': 'Arabic',
|
||||
'azure_voice': 'ar-EG-ShakirNeural',
|
||||
'gender': 'Male'},
|
||||
{'language': 'Arabic (Gulf)',
|
||||
'azure_voice': 'ar-KW-FahedNeural',
|
||||
'gender': 'Male'},
|
||||
{'language': 'Catalan',
|
||||
'azure_voice': 'ca-ES-EnricNeural',
|
||||
'gender': 'Male'},
|
||||
{'language': 'Chinese (Cantonese)',
|
||||
'azure_voice': 'yue-CN-YunSongNeural',
|
||||
'gender': 'Male'},
|
||||
{'language': 'Chinese (Mandarin)',
|
||||
'azure_voice': 'zh-CN-YunxiNeural',
|
||||
'gender': 'Male'},
|
||||
{'language': 'Danish',
|
||||
'azure_voice': 'da-DK-JeppeNeural',
|
||||
'gender': 'Male'},
|
||||
{'language': 'Dutch',
|
||||
'azure_voice': 'nl-NL-MaartenNeural',
|
||||
'gender': 'Male'},
|
||||
{'language': 'English (Australian)',
|
||||
'azure_voice': 'en-AU-KenNeural',
|
||||
'gender': 'Male'},
|
||||
{'language': 'English (British)',
|
||||
'azure_voice': 'en-GB-RyanNeural',
|
||||
'gender': 'Male'},
|
||||
{'language': 'English (Indian)',
|
||||
'azure_voice': 'en-IN-PrabhatNeural',
|
||||
'gender': 'Male'},
|
||||
{'language': 'English (New Zealand)',
|
||||
'azure_voice': 'en-NZ-MitchellNeural',
|
||||
'gender': 'Male'},
|
||||
{'language': 'English (South African)',
|
||||
'azure_voice': 'en-ZA-LukeNeural',
|
||||
'gender': 'Male'},
|
||||
{'language': 'English (US)',
|
||||
'azure_voice': 'en-US-ChristopherNeural',
|
||||
'gender': 'Male'},
|
||||
{'language': 'English (Welsh)',
|
||||
'azure_voice': 'cy-GB-AledNeural',
|
||||
'gender': 'Male'},
|
||||
{'language': 'Finnish',
|
||||
'azure_voice': 'fi-FI-HarriNeural',
|
||||
'gender': 'Male'},
|
||||
{'language': 'French',
|
||||
'azure_voice': 'fr-FR-HenriNeural',
|
||||
'gender': 'Male'},
|
||||
{'language': 'French (Canadian)',
|
||||
'azure_voice': 'fr-CA-AntoineNeural',
|
||||
'gender': 'Male'},
|
||||
{'language': 'German',
|
||||
'azure_voice': 'de-DE-KlausNeural',
|
||||
'gender': 'Male'},
|
||||
{'language': 'German (Austrian)',
|
||||
'azure_voice': 'de-AT-JonasNeural',
|
||||
'gender': 'Male'},
|
||||
{'language': 'Hindi',
|
||||
'azure_voice': 'hi-IN-MadhurNeural',
|
||||
'gender': 'Male'},
|
||||
{'language': 'Icelandic',
|
||||
'azure_voice': 'is-IS-GunnarNeural',
|
||||
'gender': 'Male'},
|
||||
{'language': 'Italian',
|
||||
'azure_voice': 'it-IT-GianniNeural',
|
||||
'gender': 'Male'},
|
||||
{'language': 'Japanese',
|
||||
'azure_voice': 'ja-JP-KeitaNeural',
|
||||
'gender': 'Male'},
|
||||
{'language': 'Korean',
|
||||
'azure_voice': 'ko-KR-GookMinNeural',
|
||||
'gender': 'Male'},
|
||||
{'language': 'Norwegian',
|
||||
'azure_voice': 'nb-NO-FinnNeural',
|
||||
'gender': 'Male'},
|
||||
{'language': 'Polish',
|
||||
'azure_voice': 'pl-PL-MarekNeural',
|
||||
'gender': 'Male'},
|
||||
{'language': 'Portuguese (Brazilian)',
|
||||
'azure_voice': 'pt-BR-NicolauNeural',
|
||||
'gender': 'Male'},
|
||||
{'language': 'Portuguese (European)',
|
||||
'azure_voice': 'pt-PT-DuarteNeural',
|
||||
'gender': 'Male'},
|
||||
{'language': 'Romanian',
|
||||
'azure_voice': 'ro-RO-EmilNeural',
|
||||
'gender': 'Male'},
|
||||
{'language': 'Russian',
|
||||
'azure_voice': 'ru-RU-DmitryNeural',
|
||||
'gender': 'Male'},
|
||||
{'language': 'Spanish (European)',
|
||||
'azure_voice': 'es-ES-TeoNeural',
|
||||
'gender': 'Male'},
|
||||
{'language': 'Spanish (Mexican)',
|
||||
'azure_voice': 'es-MX-LibertoNeural',
|
||||
'gender': 'Male'},
|
||||
{'language': 'Spanish (US)',
|
||||
'azure_voice': 'es-US-AlonsoNeural"',
|
||||
'gender': 'Male'},
|
||||
{'language': 'Swedish',
|
||||
'azure_voice': 'sv-SE-MattiasNeural',
|
||||
'gender': 'Male'},
|
||||
{'language': 'Turkish',
|
||||
'azure_voice': 'tr-TR-AhmetNeural',
|
||||
'gender': 'Male'},
|
||||
{'language': 'Welsh',
|
||||
'azure_voice': 'cy-GB-AledNeural',
|
||||
'gender': 'Male'},
|
||||
]
|
||||
|
||||
|
||||
# Run from the command-line
|
||||
if __name__ == '__main__':
|
||||
azure_voice_data = AzureVoiceData()
|
||||
|
||||
azure_voice = azure_voice_data.get_voice('English (US)', 'Male')
|
||||
print('English (US)', 'Male', azure_voice)
|
||||
|
||||
azure_voice = azure_voice_data.get_voice('English (US)', 'Female')
|
||||
print('English (US)', 'Female', azure_voice)
|
||||
|
||||
azure_voice = azure_voice_data.get_voice('French', 'Female')
|
||||
print('French', 'Female', azure_voice)
|
||||
|
||||
azure_voice = azure_voice_data.get_voice('French', 'Male')
|
||||
print('French', 'Male', azure_voice)
|
||||
|
||||
azure_voice = azure_voice_data.get_voice('Japanese', 'Female')
|
||||
print('Japanese', 'Female', azure_voice)
|
||||
|
||||
azure_voice = azure_voice_data.get_voice('Japanese', 'Male')
|
||||
print('Japanese', 'Male', azure_voice)
|
||||
|
||||
azure_voice = azure_voice_data.get_voice('Hindi', 'Female')
|
||||
print('Hindi', 'Female', azure_voice)
|
||||
|
||||
azure_voice = azure_voice_data.get_voice('Hindi', 'Male')
|
||||
print('Hindi', 'Male', azure_voice)
|
||||
|
|
@ -0,0 +1,633 @@
|
|||
# This class stores Polly voice data. Specifically, the class stores several records containing
|
||||
# language, lang_code, gender, voice_id and engine. The class also has a method to return the
|
||||
# voice_id, lang_code and engine given a language and gender.
|
||||
|
||||
NEURAL_ENGINE = "neural"
|
||||
STANDARD_ENGINE = "standard"
|
||||
|
||||
|
||||
class PollyVoiceData:
|
||||
def get_voice(self, language, gender):
|
||||
for voice in self.voice_data:
|
||||
if voice['language'] == language and voice['gender'] == gender:
|
||||
if voice['neural'] == 'Yes':
|
||||
return voice['voice_id'], voice['lang_code'], NEURAL_ENGINE
|
||||
for voice in self.voice_data:
|
||||
if voice['language'] == language and voice['gender'] == gender:
|
||||
if voice['standard'] == 'Yes':
|
||||
return voice['voice_id'], voice['lang_code'], STANDARD_ENGINE
|
||||
return None, None, None
|
||||
|
||||
def get_whisper_lang_code(self, language):
|
||||
for voice in self.voice_data:
|
||||
if voice['language'] == language:
|
||||
return voice['whisper_lang_code']
|
||||
return "en"
|
||||
|
||||
def __init__(self):
|
||||
self.voice_data = [
|
||||
{'language': 'Arabic',
|
||||
'lang_code': 'arb',
|
||||
'whisper_lang_code': 'ar',
|
||||
'voice_id': 'Zeina',
|
||||
'gender': 'Female',
|
||||
'neural': 'No',
|
||||
'standard': 'Yes'},
|
||||
{'language': 'Arabic (Gulf)',
|
||||
'lang_code': 'ar-AE',
|
||||
'whisper_lang_code': 'ar',
|
||||
'voice_id': 'Hala',
|
||||
'gender': 'Female',
|
||||
'neural': 'Yes',
|
||||
'standard': 'No'},
|
||||
{'language': 'Catalan',
|
||||
'lang_code': 'ca-ES',
|
||||
'whisper_lang_code': 'ca',
|
||||
'voice_id': 'Arlet',
|
||||
'gender': 'Female',
|
||||
'neural': 'Yes',
|
||||
'standard': 'No'},
|
||||
{'language': 'Chinese (Cantonese)',
|
||||
'lang_code': 'yue-CN',
|
||||
'whisper_lang_code': 'zh',
|
||||
'voice_id': 'Hiujin',
|
||||
'gender': 'Female',
|
||||
'neural': 'Yes',
|
||||
'standard': 'No'},
|
||||
{'language': 'Chinese (Mandarin)',
|
||||
'lang_code': 'cmn-CN',
|
||||
'whisper_lang_code': 'zh',
|
||||
'voice_id': 'Zhiyu',
|
||||
'gender': 'Female',
|
||||
'neural': 'Yes',
|
||||
'standard': 'No'},
|
||||
{'language': 'Danish',
|
||||
'lang_code': 'da-DK',
|
||||
'whisper_lang_code': 'da',
|
||||
'voice_id': 'Naja',
|
||||
'gender': 'Female',
|
||||
'neural': 'No',
|
||||
'standard': 'Yes'},
|
||||
{'language': 'Danish',
|
||||
'lang_code': 'da-DK',
|
||||
'whisper_lang_code': 'da',
|
||||
'voice_id': 'Mads',
|
||||
'gender': 'Male',
|
||||
'neural': 'No',
|
||||
'standard': 'Yes'},
|
||||
{'language': 'Dutch',
|
||||
'lang_code': 'nl-NL',
|
||||
'whisper_lang_code': 'nl',
|
||||
'voice_id': 'Laura',
|
||||
'gender': 'Female',
|
||||
'neural': 'Yes',
|
||||
'standard': 'No'},
|
||||
{'language': 'Dutch',
|
||||
'lang_code': 'nl-NL',
|
||||
'whisper_lang_code': 'nl',
|
||||
'voice_id': 'Lotte',
|
||||
'gender': 'Female',
|
||||
'neural': 'No',
|
||||
'standard': 'Yes'},
|
||||
{'language': 'Dutch',
|
||||
'lang_code': 'nl-NL',
|
||||
'whisper_lang_code': 'nl',
|
||||
'voice_id': 'Ruben',
|
||||
'gender': 'Male',
|
||||
'neural': 'No',
|
||||
'standard': 'Yes'},
|
||||
{'language': 'English (Australian)',
|
||||
'lang_code': 'en-AU',
|
||||
'whisper_lang_code': 'en',
|
||||
'voice_id': 'Nicole',
|
||||
'gender': 'Female',
|
||||
'neural': 'No',
|
||||
'standard': 'Yes'},
|
||||
{'language': 'English (Australian)',
|
||||
'lang_code': 'en-AU',
|
||||
'whisper_lang_code': 'en',
|
||||
'voice_id': 'Olivia',
|
||||
'gender': 'Female',
|
||||
'neural': 'Yes',
|
||||
'standard': 'No'},
|
||||
{'language': 'English (Australian)',
|
||||
'lang_code': 'en-AU',
|
||||
'whisper_lang_code': 'en',
|
||||
'voice_id': 'Russell',
|
||||
'gender': 'Male',
|
||||
'neural': 'No',
|
||||
'standard': 'Yes'},
|
||||
{'language': 'English (British)',
|
||||
'lang_code': 'en-GB',
|
||||
'whisper_lang_code': 'en',
|
||||
'voice_id': 'Amy',
|
||||
'gender': 'Female',
|
||||
'neural': 'Yes',
|
||||
'standard': 'Yes'},
|
||||
{'language': 'English (British)',
|
||||
'lang_code': 'en-GB',
|
||||
'whisper_lang_code': 'en',
|
||||
'voice_id': 'Emma',
|
||||
'gender': 'Female',
|
||||
'neural': 'Yes',
|
||||
'standard': 'Yes'},
|
||||
{'language': 'English (British)',
|
||||
'lang_code': 'en-GB',
|
||||
'whisper_lang_code': 'en',
|
||||
'voice_id': 'Brian',
|
||||
'gender': 'Male',
|
||||
'neural': 'Yes',
|
||||
'standard': 'Yes'},
|
||||
{'language': 'English (British)',
|
||||
'lang_code': 'en-GB',
|
||||
'whisper_lang_code': 'en',
|
||||
'voice_id': 'Arthur',
|
||||
'gender': 'Male',
|
||||
'neural': 'Yes',
|
||||
'standard': 'No'},
|
||||
{'language': 'English (Indian)',
|
||||
'lang_code': 'en-IN',
|
||||
'whisper_lang_code': 'en',
|
||||
'voice_id': 'Aditi',
|
||||
'gender': 'Female',
|
||||
'neural': 'No',
|
||||
'standard': 'Yes'},
|
||||
{'language': 'English (Indian)',
|
||||
'lang_code': 'en-IN',
|
||||
'whisper_lang_code': 'en',
|
||||
'voice_id': 'Raveena',
|
||||
'gender': 'Female',
|
||||
'neural': 'No',
|
||||
'standard': 'Yes'},
|
||||
{'language': 'English (Indian)',
|
||||
'lang_code': 'en-IN',
|
||||
'whisper_lang_code': 'en',
|
||||
'voice_id': 'Kajal',
|
||||
'gender': 'Female',
|
||||
'neural': 'Yes',
|
||||
'standard': 'No'},
|
||||
{'language': 'English (New Zealand)',
|
||||
'lang_code': 'en-NZ',
|
||||
'whisper_lang_code': 'en',
|
||||
'voice_id': 'Aria',
|
||||
'gender': 'Female',
|
||||
'neural': 'Yes',
|
||||
'standard': 'No'},
|
||||
{'language': 'English (South African)',
|
||||
'lang_code': 'en-ZA',
|
||||
'whisper_lang_code': 'en',
|
||||
'voice_id': 'Ayanda',
|
||||
'gender': 'Female',
|
||||
'neural': 'Yes',
|
||||
'standard': 'No'},
|
||||
{'language': 'English (US)',
|
||||
'lang_code': 'en-US',
|
||||
'whisper_lang_code': 'en',
|
||||
'voice_id': 'Ivy',
|
||||
'gender': 'Female (child)',
|
||||
'neural': 'Yes',
|
||||
'standard': 'Yes'},
|
||||
{'language': 'English (US)',
|
||||
'lang_code': 'en-US',
|
||||
'whisper_lang_code': 'en',
|
||||
'voice_id': 'Joanna',
|
||||
'gender': 'Female',
|
||||
'neural': 'Yes',
|
||||
'standard': 'Yes'},
|
||||
{'language': 'English (US)',
|
||||
'lang_code': 'en-US',
|
||||
'whisper_lang_code': 'en',
|
||||
'voice_id': 'Kendra',
|
||||
'gender': 'Female',
|
||||
'neural': 'Yes',
|
||||
'standard': 'Yes'},
|
||||
{'language': 'English (US)',
|
||||
'lang_code': 'en-US',
|
||||
'whisper_lang_code': 'en',
|
||||
'voice_id': 'Kimberly',
|
||||
'gender': 'Female',
|
||||
'neural': 'Yes',
|
||||
'standard': 'Yes'},
|
||||
{'language': 'English (US)',
|
||||
'lang_code': 'en-US',
|
||||
'whisper_lang_code': 'en',
|
||||
'voice_id': 'Salli',
|
||||
'gender': 'Female',
|
||||
'neural': 'Yes',
|
||||
'standard': 'Yes'},
|
||||
{'language': 'English (US)',
|
||||
'lang_code': 'en-US',
|
||||
'whisper_lang_code': 'en',
|
||||
'voice_id': 'Joey',
|
||||
'gender': 'Male',
|
||||
'neural': 'Yes',
|
||||
'standard': 'Yes'},
|
||||
{'language': 'English (US)',
|
||||
'lang_code': 'en-US',
|
||||
'whisper_lang_code': 'en',
|
||||
'voice_id': 'Justin',
|
||||
'gender': 'Male (child)',
|
||||
'neural': 'Yes',
|
||||
'standard': 'Yes'},
|
||||
{'language': 'English (US)',
|
||||
'lang_code': 'en-US',
|
||||
'whisper_lang_code': 'en',
|
||||
'voice_id': 'Kevin',
|
||||
'gender': 'Male (child)',
|
||||
'neural': 'Yes',
|
||||
'standard': 'No'},
|
||||
{'language': 'English (US)',
|
||||
'lang_code': 'en-US',
|
||||
'whisper_lang_code': 'en',
|
||||
'voice_id': 'Matthew',
|
||||
'gender': 'Male',
|
||||
'neural': 'Yes',
|
||||
'standard': 'Yes'},
|
||||
{'language': 'English (Welsh)',
|
||||
'lang_code': 'en-GB-WLS',
|
||||
'whisper_lang_code': 'en',
|
||||
'voice_id': 'Geraint',
|
||||
'gender': 'Male',
|
||||
'neural': 'No',
|
||||
'standard': 'Yes'},
|
||||
{'language': 'Finnish',
|
||||
'lang_code': 'fi-FI',
|
||||
'whisper_lang_code': 'fi',
|
||||
'voice_id': 'Suvi',
|
||||
'gender': 'Female',
|
||||
'neural': 'Yes',
|
||||
'standard': 'No'},
|
||||
{'language': 'French',
|
||||
'lang_code': 'fr-FR',
|
||||
'whisper_lang_code': 'fr',
|
||||
'voice_id': 'Celine',
|
||||
'gender': 'Female',
|
||||
'neural': 'No',
|
||||
'standard': 'Yes'},
|
||||
{'language': 'French',
|
||||
'lang_code': 'fr-FR',
|
||||
'whisper_lang_code': 'fr',
|
||||
'voice_id': 'Lea',
|
||||
'gender': 'Female',
|
||||
'neural': 'Yes',
|
||||
'standard': 'Yes'},
|
||||
{'language': 'French',
|
||||
'lang_code': 'fr-FR',
|
||||
'whisper_lang_code': 'fr',
|
||||
'voice_id': 'Mathieu',
|
||||
'gender': 'Male',
|
||||
'neural': 'No',
|
||||
'standard': 'Yes'},
|
||||
{'language': 'French (Canadian)',
|
||||
'lang_code': 'fr-CA',
|
||||
'whisper_lang_code': 'fr',
|
||||
'voice_id': 'Chantal',
|
||||
'gender': 'Female',
|
||||
'neural': 'No',
|
||||
'standard': 'Yes'},
|
||||
{'language': 'French (Canadian)',
|
||||
'lang_code': 'fr-CA',
|
||||
'whisper_lang_code': 'fr',
|
||||
'voice_id': 'Gabrielle',
|
||||
'gender': 'Female',
|
||||
'neural': 'Yes',
|
||||
'standard': 'No'},
|
||||
{'language': 'French (Canadian)',
|
||||
'lang_code': 'fr-CA',
|
||||
'whisper_lang_code': 'fr',
|
||||
'voice_id': 'Liam',
|
||||
'gender': 'Male',
|
||||
'neural': 'Yes',
|
||||
'standard': 'No'},
|
||||
{'language': 'German',
|
||||
'lang_code': 'de-DE',
|
||||
'whisper_lang_code': 'de',
|
||||
'voice_id': 'Marlene',
|
||||
'gender': 'Female',
|
||||
'neural': 'No',
|
||||
'standard': 'Yes'},
|
||||
{'language': 'German',
|
||||
'lang_code': 'de-DE',
|
||||
'whisper_lang_code': 'de',
|
||||
'voice_id': 'Vicki',
|
||||
'gender': 'Female',
|
||||
'neural': 'Yes',
|
||||
'standard': 'Yes'},
|
||||
{'language': 'German',
|
||||
'lang_code': 'de-DE',
|
||||
'whisper_lang_code': 'de',
|
||||
'voice_id': 'Hans',
|
||||
'gender': 'Male',
|
||||
'neural': 'No',
|
||||
'standard': 'Yes'},
|
||||
{'language': 'German',
|
||||
'lang_code': 'de-DE',
|
||||
'whisper_lang_code': 'de',
|
||||
'voice_id': 'Daniel',
|
||||
'gender': 'Male',
|
||||
'neural': 'Yes',
|
||||
'standard': 'No'},
|
||||
{'language': 'German (Austrian)',
|
||||
'lang_code': 'de-AT',
|
||||
'whisper_lang_code': 'de',
|
||||
'voice_id': 'Hannah',
|
||||
'gender': 'Female',
|
||||
'neural': 'Yes',
|
||||
'standard': 'No'},
|
||||
{'language': 'Hindi',
|
||||
'lang_code': 'hi-IN',
|
||||
'whisper_lang_code': 'hi',
|
||||
'voice_id': 'Aditi',
|
||||
'gender': 'Female',
|
||||
'neural': 'No',
|
||||
'standard': 'Yes'},
|
||||
{'language': 'Hindi',
|
||||
'lang_code': 'hi-IN',
|
||||
'whisper_lang_code': 'hi',
|
||||
'voice_id': 'Kajal',
|
||||
'gender': 'Female',
|
||||
'neural': 'Yes',
|
||||
'standard': 'No'},
|
||||
{'language': 'Icelandic',
|
||||
'lang_code': 'is-IS',
|
||||
'whisper_lang_code': 'is',
|
||||
'voice_id': 'Dora',
|
||||
'gender': 'Female',
|
||||
'neural': 'No',
|
||||
'standard': 'Yes'},
|
||||
{'language': 'Icelandic',
|
||||
'lang_code': 'is-IS',
|
||||
'whisper_lang_code': 'is',
|
||||
'voice_id': 'Karl',
|
||||
'gender': 'Male',
|
||||
'neural': 'No',
|
||||
'standard': 'Yes'},
|
||||
{'language': 'Italian',
|
||||
'lang_code': 'it-IT',
|
||||
'whisper_lang_code': 'it',
|
||||
'voice_id': 'Carla',
|
||||
'gender': 'Female',
|
||||
'neural': 'No',
|
||||
'standard': 'Yes'},
|
||||
{'language': 'Italian',
|
||||
'lang_code': 'it-IT',
|
||||
'whisper_lang_code': 'it',
|
||||
'voice_id': 'Bianca',
|
||||
'gender': 'Female',
|
||||
'neural': 'Yes',
|
||||
'standard': 'Yes'},
|
||||
{'language': 'Japanese',
|
||||
'lang_code': 'ja-JP',
|
||||
'whisper_lang_code': 'ja',
|
||||
'voice_id': 'Mizuki',
|
||||
'gender': 'Female',
|
||||
'neural': 'No',
|
||||
'standard': 'Yes'},
|
||||
{'language': 'Japanese',
|
||||
'lang_code': 'ja-JP',
|
||||
'whisper_lang_code': 'ja',
|
||||
'voice_id': 'Takumi',
|
||||
'gender': 'Male',
|
||||
'neural': 'Yes',
|
||||
'standard': 'Yes'},
|
||||
{'language': 'Korean',
|
||||
'lang_code': 'ko-KR',
|
||||
'whisper_lang_code': 'ko',
|
||||
'voice_id': 'Seoyeon',
|
||||
'gender': 'Female',
|
||||
'neural': 'Yes',
|
||||
'standard': 'Yes'},
|
||||
{'language': 'Norwegian',
|
||||
'lang_code': 'nb-NO',
|
||||
'whisper_lang_code': 'no',
|
||||
'voice_id': 'Liv',
|
||||
'gender': 'Female',
|
||||
'neural': 'No',
|
||||
'standard': 'Yes'},
|
||||
{'language': 'Norwegian',
|
||||
'lang_code': 'nb-NO',
|
||||
'whisper_lang_code': 'no',
|
||||
'voice_id': 'Ida',
|
||||
'gender': 'Female',
|
||||
'neural': 'Yes',
|
||||
'standard': 'No'},
|
||||
{'language': 'Polish',
|
||||
'lang_code': 'pl-PL',
|
||||
'whisper_lang_code': 'pl',
|
||||
'voice_id': 'Ewa',
|
||||
'gender': 'Female',
|
||||
'neural': 'No',
|
||||
'standard': 'Yes'},
|
||||
{'language': 'Polish',
|
||||
'lang_code': 'pl-PL',
|
||||
'whisper_lang_code': 'pl',
|
||||
'voice_id': 'Maja',
|
||||
'gender': 'Female',
|
||||
'neural': 'No',
|
||||
'standard': 'Yes'},
|
||||
{'language': 'Polish',
|
||||
'lang_code': 'pl-PL',
|
||||
'whisper_lang_code': 'pl',
|
||||
'voice_id': 'Jacek',
|
||||
'gender': 'Male',
|
||||
'neural': 'No',
|
||||
'standard': 'Yes'},
|
||||
{'language': 'Polish',
|
||||
'lang_code': 'pl-PL',
|
||||
'whisper_lang_code': 'pl',
|
||||
'voice_id': 'Jan',
|
||||
'gender': 'Male',
|
||||
'neural': 'No',
|
||||
'standard': 'Yes'},
|
||||
{'language': 'Polish',
|
||||
'lang_code': 'pl-PL',
|
||||
'whisper_lang_code': 'pl',
|
||||
'voice_id': 'Ola',
|
||||
'gender': 'Female',
|
||||
'neural': 'Yes',
|
||||
'standard': 'No'},
|
||||
{'language': 'Portuguese (Brazilian)',
|
||||
'lang_code': 'pt-BR',
|
||||
'whisper_lang_code': 'pt',
|
||||
'voice_id': 'Camila',
|
||||
'gender': 'Female',
|
||||
'neural': 'Yes',
|
||||
'standard': 'Yes'},
|
||||
{'language': 'Portuguese (Brazilian)',
|
||||
'lang_code': 'pt-BR',
|
||||
'whisper_lang_code': 'pt',
|
||||
'voice_id': 'Vitoria',
|
||||
'gender': 'Female',
|
||||
'neural': 'Yes',
|
||||
'standard': 'Yes'},
|
||||
{'language': 'Portuguese (Brazilian)',
|
||||
'lang_code': 'pt-BR',
|
||||
'whisper_lang_code': 'pt',
|
||||
'voice_id': 'Ricardo',
|
||||
'gender': 'Male',
|
||||
'neural': 'No',
|
||||
'standard': 'Yes'},
|
||||
{'language': 'Portuguese (European)',
|
||||
'lang_code': 'pt-PT',
|
||||
'whisper_lang_code': 'pt',
|
||||
'voice_id': 'Ines',
|
||||
'gender': 'Female',
|
||||
'neural': 'Yes',
|
||||
'standard': 'Yes'},
|
||||
{'language': 'Portuguese (European)',
|
||||
'lang_code': 'pt-PT',
|
||||
'whisper_lang_code': 'pt',
|
||||
'voice_id': 'Cristiano',
|
||||
'gender': 'Male',
|
||||
'neural': 'No',
|
||||
'standard': 'Yes'},
|
||||
{'language': 'Romanian',
|
||||
'lang_code': 'ro-RO',
|
||||
'whisper_lang_code': 'ro',
|
||||
'voice_id': 'Carmen',
|
||||
'gender': 'Female',
|
||||
'neural': 'No',
|
||||
'standard': 'Yes'},
|
||||
{'language': 'Russian',
|
||||
'lang_code': 'ru-RU',
|
||||
'whisper_lang_code': 'ru',
|
||||
'voice_id': 'Tatyana',
|
||||
'gender': 'Female',
|
||||
'neural': 'No',
|
||||
'standard': 'Yes'},
|
||||
{'language': 'Russian',
|
||||
'lang_code': 'ru-RU',
|
||||
'whisper_lang_code': 'ru',
|
||||
'voice_id': 'Maxim',
|
||||
'gender': 'Male',
|
||||
'neural': 'No',
|
||||
'standard': 'Yes'},
|
||||
{'language': 'Spanish (European)',
|
||||
'lang_code': 'es-ES',
|
||||
'whisper_lang_code': 'es',
|
||||
'voice_id': 'Conchita',
|
||||
'gender': 'Female',
|
||||
'neural': 'No',
|
||||
'standard': 'Yes'},
|
||||
{'language': 'Spanish (European)',
|
||||
'lang_code': 'es-ES',
|
||||
'whisper_lang_code': 'es',
|
||||
'voice_id': 'Lucia',
|
||||
'gender': 'Female',
|
||||
'neural': 'Yes',
|
||||
'standard': 'Yes'},
|
||||
{'language': 'Spanish (European)',
|
||||
'lang_code': 'es-ES',
|
||||
'whisper_lang_code': 'es',
|
||||
'voice_id': 'Enrique',
|
||||
'gender': 'Male',
|
||||
'neural': 'No',
|
||||
'standard': 'Yes'},
|
||||
{'language': 'Spanish (Mexican)',
|
||||
'lang_code': 'es-MX',
|
||||
'whisper_lang_code': 'es',
|
||||
'voice_id': 'Mia',
|
||||
'gender': 'Female',
|
||||
'neural': 'Yes',
|
||||
'standard': 'Yes'},
|
||||
{'language': 'Spanish (US)',
|
||||
'lang_code': 'es-US',
|
||||
'whisper_lang_code': 'es',
|
||||
'voice_id': 'Lupe',
|
||||
'gender': 'Female',
|
||||
'neural': 'Yes',
|
||||
'standard': 'Yes'},
|
||||
{'language': 'Spanish (US)',
|
||||
'lang_code': 'es-US',
|
||||
'whisper_lang_code': 'es',
|
||||
'voice_id': 'Penelope',
|
||||
'gender': 'Female',
|
||||
'neural': 'No',
|
||||
'standard': 'Yes'},
|
||||
{'language': 'Spanish (US)',
|
||||
'lang_code': 'es-US',
|
||||
'whisper_lang_code': 'es',
|
||||
'voice_id': 'Miguel',
|
||||
'gender': 'Male',
|
||||
'neural': 'No',
|
||||
'standard': 'Yes'},
|
||||
{'language': 'Spanish (US)',
|
||||
'lang_code': 'es-US',
|
||||
'whisper_lang_code': 'es',
|
||||
'voice_id': 'Pedro',
|
||||
'gender': 'Male',
|
||||
'neural': 'Yes',
|
||||
'standard': 'No'},
|
||||
{'language': 'Swedish',
|
||||
'lang_code': 'sv-SE',
|
||||
'whisper_lang_code': 'sv',
|
||||
'voice_id': 'Astrid',
|
||||
'gender': 'Female',
|
||||
'neural': 'No',
|
||||
'standard': 'Yes'},
|
||||
{'language': 'Swedish',
|
||||
'lang_code': 'sv-SE',
|
||||
'whisper_lang_code': 'sv',
|
||||
'voice_id': 'Elin',
|
||||
'gender': 'Female',
|
||||
'neural': 'Yes',
|
||||
'standard': 'No'},
|
||||
{'language': 'Turkish',
|
||||
'lang_code': 'tr-TR',
|
||||
'whisper_lang_code': 'tr',
|
||||
'voice_id': 'Filiz',
|
||||
'gender': 'Female',
|
||||
'neural': 'No',
|
||||
'standard': 'Yes'},
|
||||
{'language': 'Welsh',
|
||||
'lang_code': 'cy-GB',
|
||||
'whisper_lang_code': 'cy',
|
||||
'voice_id': 'Gwyneth',
|
||||
'gender': 'Female',
|
||||
'neural': 'No',
|
||||
'standard': 'Yes'}
|
||||
]
|
||||
|
||||
|
||||
# Run from the command-line
|
||||
if __name__ == '__main__':
|
||||
polly_voice_data = PollyVoiceData()
|
||||
|
||||
voice_id, language_code, engine = polly_voice_data.get_voice('English (US)', 'Male')
|
||||
print('English (US)', 'Male', voice_id, language_code, engine)
|
||||
|
||||
voice_id, language_code, engine = polly_voice_data.get_voice('English (US)', 'Female')
|
||||
print('English (US)', 'Female', voice_id, language_code, engine)
|
||||
|
||||
voice_id, language_code, engine = polly_voice_data.get_voice('French', 'Female')
|
||||
print('French', 'Female', voice_id, language_code, engine)
|
||||
|
||||
voice_id, language_code, engine = polly_voice_data.get_voice('French', 'Male')
|
||||
print('French', 'Male', voice_id, language_code, engine)
|
||||
|
||||
voice_id, language_code, engine = polly_voice_data.get_voice('Japanese', 'Female')
|
||||
print('Japanese', 'Female', voice_id, language_code, engine)
|
||||
|
||||
voice_id, language_code, engine = polly_voice_data.get_voice('Japanese', 'Male')
|
||||
print('Japanese', 'Male', voice_id, language_code, engine)
|
||||
|
||||
voice_id, language_code, engine = polly_voice_data.get_voice('Hindi', 'Female')
|
||||
print('Hindi', 'Female', voice_id, language_code, engine)
|
||||
|
||||
voice_id, language_code, engine = polly_voice_data.get_voice('Hindi', 'Male')
|
||||
print('Hindi', 'Male', voice_id, language_code, engine)
|
||||
|
||||
whisper_lang_code = polly_voice_data.get_whisper_lang_code('English (US)')
|
||||
print('English (US) whisper_lang_code:', whisper_lang_code)
|
||||
|
||||
whisper_lang_code = polly_voice_data.get_whisper_lang_code('Chinese (Mandarin)')
|
||||
print('Chinese (Mandarin) whisper_lang_code:', whisper_lang_code)
|
||||
|
||||
whisper_lang_code = polly_voice_data.get_whisper_lang_code('Norwegian')
|
||||
print('Norwegian whisper_lang_code:', whisper_lang_code)
|
||||
|
||||
whisper_lang_code = polly_voice_data.get_whisper_lang_code('Dutch')
|
||||
print('Dutch whisper_lang_code:', whisper_lang_code)
|
||||
|
||||
whisper_lang_code = polly_voice_data.get_whisper_lang_code('Foo')
|
||||
print('Foo whisper_lang_code:', whisper_lang_code)
|
||||
Loading…
Reference in New Issue