api_test.py

import json
import re
import requests
import os
import time
import random
import string
from requests_toolbelt.multipart.encoder import MultipartEncoder

absolute_path = os.path.dirname(__file__)
base_url = "http://127.0.0.1:23456"


# 映射表
def voice_speakers():
    url = f"{base_url}/voice/speakers"

    res = requests.post(url=url)
    json = res.json()
    for i in json:
        print(i)
        for j in json[i]:
            print(j)
    return json


# 语音合成 voice vits
def voice_vits(text, id=0, format="wav", lang="auto", length=1, noise=0.667, noisew=0.8, segment_size=50,
               save_audio=True,
               save_path=None):
    fields = {
        "text": text,
        "id": str(id),
        "format": format,
        "lang": lang,
        "length": str(length),
        "noise": str(noise),
        "noisew": str(noisew),
        "segment_size": str(segment_size)
    }
    boundary = '----VoiceConversionFormBoundary' + ''.join(random.sample(string.ascii_letters + string.digits, 16))

    m = MultipartEncoder(fields=fields, boundary=boundary)
    headers = {"Content-Type": m.content_type}
    url = f"{base_url}/voice/vits"

    res = requests.post(url=url, data=m, headers=headers)
    fname = re.findall("filename=(.+)", res.headers["Content-Disposition"])[0]
    if save_path is not None:
        path = os.path.join(save_path, fname)
    else:
        path = os.path.join(absolute_path, fname)
    if save_audio:
        with open(path, "wb") as f:
            f.write(res.content)
        print(path)
        return path
    return None


def voice_vits_streaming(text, id=0, format="wav", lang="auto", length=1, noise=0.667, noisew=0.8, segment_size=50,
                         save_audio=True, save_path=None):
    fields = {
        "text": text,
        "id": str(id),
        "format": format,
        "lang": lang,
        "length": str(length),
        "noise": str(noise),
        "noisew": str(noisew),
        "segment_size": str(segment_size),
        "streaming": 'True'
    }
    boundary = '----VoiceConversionFormBoundary' + ''.join(random.sample(string.ascii_letters + string.digits, 16))

    m = MultipartEncoder(fields=fields, boundary=boundary)
    headers = {"Content-Type": m.content_type}
    url = f"{base_url}/voice"

    res = requests.post(url=url, data=m, headers=headers)
    fname = re.findall("filename=(.+)", res.headers["Content-Disposition"])[0]
    if save_path is not None:
        path = os.path.join(save_path, fname)
    else:
        path = os.path.join(absolute_path, fname)
    if save_audio:
        with open(path, "wb") as f:
            f.write(res.content)
        print(path)
        return path
    return None


def voice_vits_streaming(text, id=0, format="wav", lang="auto", length=1, noise=0.667, noisew=0.8, segment_size=50,
                         save_path=None):
    fields = {
        "text": text,
        "id": str(id),
        "format": format,
        "lang": lang,
        "length": str(length),
        "noise": str(noise),
        "noisew": str(noisew),
        "segment_size": str(segment_size),
        "streaming": 'True'
    }
    boundary = '----VoiceConversionFormBoundary' + ''.join(random.sample(string.ascii_letters + string.digits, 16))

    m = MultipartEncoder(fields=fields, boundary=boundary)
    headers = {"Content-Type": m.content_type}
    url = f"{base_url}/voice"

    res = requests.post(url=url, data=m, headers=headers, stream=True)
    fname = re.findall("filename=(.+)", res.headers["Content-Disposition"])[0]
    if save_path is not None:
        path = os.path.join(save_path, fname)
    else:
        path = os.path.join(absolute_path, fname)
    audio = res.content

    def get_file_size_from_bytes(byte_data):
        file_size_offset = 4
        file_size_length = 4

        try:
            file_size_bytes = byte_data[file_size_offset:file_size_offset + file_size_length]
            file_size = int.from_bytes(file_size_bytes, byteorder='little')
            return file_size + 8
        except IndexError:
            return None

    audio = None
    p = 0
    audio_size = None
    audios = []

    for chunk in res.iter_content(chunk_size=1024):
        if audio is None:
            audio = chunk
        else:
            audio += chunk

        p += len(chunk)
        if audio_size is not None:
            if p >= audio_size:
                p = p - audio_size
                audios.append(audio[:audio_size])
                audio = audio[audio_size:]
                audio_size = get_file_size_from_bytes(audio)
        else:
            audio_size = get_file_size_from_bytes(audio)
    for i, audio in enumerate(audios):
        with open(f"{path[:-4]}-{i}.wav", "wb") as f:
            f.write(audio)

        print(f"{path[:-4]}-{i}.wav")
    return path


# 语音转换 hubert-vits
def voice_hubert_vits(upload_path, id, format="wav", length=1, noise=0.667, noisew=0.8, save_audio=True,
                      save_path=None):
    upload_name = os.path.basename(upload_path)
    upload_type = f'audio/{upload_name.split(".")[1]}'  # wav,ogg

    with open(upload_path, 'rb') as upload_file:
        fields = {
            "upload": (upload_name, upload_file, upload_type),
            "id": str(id),
            "format": format,
            "length": str(length),
            "noise": str(noise),
            "noisew": str(noisew),
        }
        boundary = '----VoiceConversionFormBoundary' + ''.join(random.sample(string.ascii_letters + string.digits, 16))

        m = MultipartEncoder(fields=fields, boundary=boundary)
        headers = {"Content-Type": m.content_type}
        url = f"{base_url}/voice/hubert-vits"

        res = requests.post(url=url, data=m, headers=headers)
    fname = re.findall("filename=(.+)", res.headers["Content-Disposition"])[0]
    if save_path is not None:
        path = os.path.join(save_path, fname)
    else:
        path = os.path.join(absolute_path, fname)
    if save_audio:
        with open(path, "wb") as f:
            f.write(res.content)
        print(path)
        return path
    return None


# 维度情感模型 w2v2-vits
def voice_w2v2_vits(text, id=0, format="wav", lang="auto", length=1, noise=0.667, noisew=0.8, segment_size=50,
                    emotion=0,
                    save_audio=True, save_path=None):
    fields = {
        "text": text,
        "id": str(id),
        "format": format,
        "lang": lang,
        "length": str(length),
        "noise": str(noise),
        "noisew": str(noisew),
        "segment_size": str(segment_size),
        "emotion": str(emotion)
    }
    boundary = '----VoiceConversionFormBoundary' + ''.join(random.sample(string.ascii_letters + string.digits, 16))

    m = MultipartEncoder(fields=fields, boundary=boundary)
    headers = {"Content-Type": m.content_type}
    url = f"{base_url}/voice/w2v2-vits"

    res = requests.post(url=url, data=m, headers=headers)
    fname = re.findall("filename=(.+)", res.headers["Content-Disposition"])[0]
    if save_path is not None:
        path = os.path.join(save_path, fname)
    else:
        path = os.path.join(absolute_path, fname)
    if save_audio:
        with open(path, "wb") as f:
            f.write(res.content)
        print(path)
        return path
    return None


# 语音转换 同VITS模型内角色之间的音色转换
def voice_conversion(upload_path, original_id, target_id, save_audio=True, save_path=None):
    upload_name = os.path.basename(upload_path)
    upload_type = f'audio/{upload_name.split(".")[1]}'  # wav,ogg

    with open(upload_path, 'rb') as upload_file:
        fields = {
            "upload": (upload_name, upload_file, upload_type),
            "original_id": str(original_id),
            "target_id": str(target_id),
        }
        boundary = '----VoiceConversionFormBoundary' + ''.join(random.sample(string.ascii_letters + string.digits, 16))
        m = MultipartEncoder(fields=fields, boundary=boundary)

        headers = {"Content-Type": m.content_type}
        url = f"{base_url}/voice/conversion"

        res = requests.post(url=url, data=m, headers=headers)

    fname = re.findall("filename=(.+)", res.headers["Content-Disposition"])[0]
    if save_path is not None:
        path = os.path.join(save_path, fname)
    else:
        path = os.path.join(absolute_path, fname)

    if save_audio:
        with open(path, "wb") as f:
            f.write(res.content)
        print(path)
        return path
    return None


def voice_ssml(ssml, save_audio=True, save_path=None):
    fields = {
        "ssml": ssml,
    }
    boundary = '----VoiceConversionFormBoundary' + ''.join(random.sample(string.ascii_letters + string.digits, 16))

    m = MultipartEncoder(fields=fields, boundary=boundary)
    headers = {"Content-Type": m.content_type}
    url = f"{base_url}/voice/ssml"

    res = requests.post(url=url, data=m, headers=headers)
    fname = re.findall("filename=(.+)", res.headers["Content-Disposition"])[0]
    if save_path is not None:
        path = os.path.join(save_path, fname)
    else:
        path = os.path.join(absolute_path, fname)

    if save_audio:
        with open(path, "wb") as f:
            f.write(res.content)
        print(path)
        return path
    return None


def voice_dimensional_emotion(upload_path, save_audio=True,
                              save_path=None):
    upload_name = os.path.basename(upload_path)
    upload_type = f'audio/{upload_name.split(".")[1]}'  # wav,ogg

    with open(upload_path, 'rb') as upload_file:
        fields = {
            "upload": (upload_name, upload_file, upload_type),
        }
        boundary = '----VoiceConversionFormBoundary' + ''.join(random.sample(string.ascii_letters + string.digits, 16))

        m = MultipartEncoder(fields=fields, boundary=boundary)
        headers = {"Content-Type": m.content_type}
        url = f"{base_url}/voice/dimension-emotion"

        res = requests.post(url=url, data=m, headers=headers)
    fname = re.findall("filename=(.+)", res.headers["Content-Disposition"])[0]
    if save_path is not None:
        path = os.path.join(save_path, fname)
    else:
        path = os.path.join(absolute_path, fname)
    if save_audio:
        with open(path, "wb") as f:
            f.write(res.content)
        print(path)
        return path
    return None


def vits_json(text, id=0, format="wav", lang="auto", length=1, noise=0.667, noisew=0.8, segment_size=50,
              save_audio=True, save_path=None):
    fields = {
        "text": text,
        "id": str(id),
        "format": format,
        "lang": lang,
        "length": str(length),
        "noise": str(noise),
        "noisew": str(noisew),
        "segment_size": str(segment_size)
    }
    f = json.dumps(fields)
    url = f"{base_url}/voice"
    header = {"Content-Type": 'application/json'}
    res = requests.post(url=url, data=f, headers=header)

    fname = re.findall("filename=(.+)", res.headers["Content-Disposition"])[0]
    if save_path is not None:
        path = os.path.join(save_path, fname)
    else:
        path = os.path.join(absolute_path, fname)

    with open(path, "wb") as f:
        f.write(res.content)

    if save_audio:
        with open(path, "wb") as f:
            f.write(res.content)
        print(path)
        return path
    return None


# Bert_vits2
def voice_bert_vits2(text, id=0, format="wav", lang="auto", length=1, noise=0.667, noisew=0.8, segment_size=50,
                     sdp_ratio=0.2, save_audio=True, save_path=None):
    fields = {
        "text": text,
        "id": str(id),
        "format": format,
        "lang": lang,
        "length": str(length),
        "noise": str(noise),
        "noisew": str(noisew),
        "segment_size": str(segment_size),
        "sdp_ratio": str(sdp_ratio)
    }
    boundary = '----VoiceConversionFormBoundary' + ''.join(random.sample(string.ascii_letters + string.digits, 16))

    m = MultipartEncoder(fields=fields, boundary=boundary)
    headers = {"Content-Type": m.content_type}
    url = f"{base_url}/voice/bert-vits2"

    res = requests.post(url=url, data=m, headers=headers)
    fname = re.findall("filename=(.+)", res.headers["Content-Disposition"])[0]
    if save_path is not None:
        path = os.path.join(save_path, fname)
    else:
        path = os.path.join(absolute_path, fname)
    if save_audio:
        with open(path, "wb") as f:
            f.write(res.content)
        print(path)
        return path
    return None


# gpt_sovits
def voice_gpt_sovits(text, id=0, format="wav", lang="auto", preset=None, prompt_text=None, prompt_lang="auto",
                     segment_size=50, reference_audio=None, save_audio=True, save_path=None):
    upload_name, upload_type, upload_file = None, None, None
    if reference_audio is not None:
        upload_name = os.path.basename(reference_audio)
        upload_type = f'audio/{upload_name.split(".")[1]}'
        with open(reference_audio, 'rb') as f:
            upload_file = f.read()

    fields = {
        "text": text,
        "id": str(id),
        "format": format,
        "lang": lang,
        "segment_size": str(segment_size),
        "preset": preset,
        "reference_audio": (upload_name, upload_file, upload_type) if reference_audio else None,
        "prompt_text": prompt_text,
        "prompt_lang": prompt_lang
    }
    boundary = '----VoiceConversionFormBoundary' + ''.join(random.sample(string.ascii_letters + string.digits, 16))

    m = MultipartEncoder(fields=fields, boundary=boundary)
    headers = {"Content-Type": m.content_type}
    url = f"{base_url}/voice/gpt-sovits"

    res = requests.post(url=url, data=m, headers=headers)
    fname = re.findall("filename=(.+)", res.headers["Content-Disposition"])[0]
    if save_path is not None:
        path = os.path.join(save_path, fname)
    else:
        path = os.path.join(absolute_path, fname)
    if save_audio:
        with open(path, "wb") as f:
            f.write(res.content)
        print(path)
        return path
    return None


# Reading
def voice_reading_get(text, in_model_type, in_id, nr_model_type, nr_id, format="wav", lang="auto", preset=None,
                      save_audio=True, save_path=None):
    res = requests.get(
        url=f"{base_url}/voice/reading?text={text}&in_model_type={in_model_type}&in_id={in_id}&preset={preset}&nr_model_type={nr_model_type}&nr_id={nr_id}&lang={lang}&format={format}")

    fname = re.findall("filename=(.+)", res.headers["Content-Disposition"])[0]
    if save_path is not None:
        path = os.path.join(save_path, fname)
    else:
        path = os.path.join(absolute_path, fname)

    with open(path, "wb") as f:
        f.write(res.content)

    if save_audio:
        with open(path, "wb") as f:
            f.write(res.content)
        print(path)
        return path
    return None


# Reading
def voice_reading_json(text, in_model_type, in_id, nr_model_type, nr_id, format="wav", lang="auto", preset=None,
                       save_audio=True, save_path=None):
    fields = {
        "text": text,
        "in_model_type": in_model_type,
        "in_id": str(in_id),
        "nr_model_type": nr_model_type,
        "nr_id": str(nr_id),
        "format": format,
        "lang": lang,
    }
    f = json.dumps(fields)
    url = f"{base_url}/voice/reading"
    header = {"Content-Type": 'application/json'}
    res = requests.post(url=url, data=f, headers=header)

    fname = re.findall("filename=(.+)", res.headers["Content-Disposition"])[0]
    if save_path is not None:
        path = os.path.join(save_path, fname)
    else:
        path = os.path.join(absolute_path, fname)

    with open(path, "wb") as f:
        f.write(res.content)

    if save_audio:
        with open(path, "wb") as f:
            f.write(res.content)
        print(path)
        return path
    return None


# Reading
def voice_reading(text, in_model_type, in_id, nr_model_type, nr_id, format="wav", lang="auto", preset=None,
                  save_audio=True, save_path=None):
    fields = {
        "text": text,
        "in_model_type": in_model_type,
        "in_id": str(in_id),
        "nr_model_type": nr_model_type,
        "nr_id": str(nr_id),
        "format": format,
        "lang": lang,
    }
    boundary = '----VoiceConversionFormBoundary' + ''.join(random.sample(string.ascii_letters + string.digits, 16))

    m = MultipartEncoder(fields=fields, boundary=boundary)
    headers = {"Content-Type": m.content_type}
    url = f"{base_url}/voice/reading"

    res = requests.post(url=url, data=m, headers=headers)
    fname = re.findall("filename=(.+)", res.headers["Content-Disposition"])[0]
    if save_path is not None:
        path = os.path.join(save_path, fname)
    else:
        path = os.path.join(absolute_path, fname)
    if save_audio:
        with open(path, "wb") as f:
            f.write(res.content)
        print(path)
        return path
    return None


def test_interface(text):
    error_num = 0
    for i in range(100):
        try:
            time.sleep(1)
            t1 = time.time()
            voice_vits(text, format="wav", lang="zh", save_audio=False)
            t2 = time.time()
            print(f"{i}:len:{len(text)}耗时:{t2 - t1}")
        except Exception as e:
            error_num += 1
            print(e)
    print(f"error_num={error_num}")


if __name__ == '__main__':
    cache_path = os.path.join(os.path.curdir, "cache")

    text = "你好,こんにちは"

    ssml = """
    <speak lang="zh" format="mp3" length="1.2">
            <voice id="0" model_type="GPT-SOVITS" preset="default">这几天心里颇不宁静。</voice>
            <voice id="0" model_type="Bert-VITS2">今晚在院子里坐着乘凉，忽然想起日日走过的荷塘，在这满月的光里，总该另有一番样子吧。</voice>
            <voice id="142">月亮渐渐地升高了，墙外马路上孩子们的欢笑，已经听不见了；</voice>
            <voice id="0" model_type="Bert-VITS2">妻在屋里拍着闰儿，迷迷糊糊地哼着眠歌。</voice>
            <voice id="120">我悄悄地披了大衫，带上门出去。</voice><break time="2s"/>
            <voice id="121">沿着荷塘，是一条曲折的小煤屑路。</voice>
            <voice id="122">这是一条幽僻的路；白天也少人走，夜晚更加寂寞。</voice>
            <voice id="123">荷塘四面，长着许多树，蓊蓊郁郁的。</voice>
            <voice id="124">路的一旁，是些杨柳，和一些不知道名字的树。</voice>
            <voice id="125">没有月光的晚上，这路上阴森森的，有些怕人。</voice>
            <voice id="126">今晚却很好，虽然月光也还是淡淡的。</voice><break time="2s"/>
            <voice id="127">路上只我一个人，背着手踱着。</voice>
            <voice id="128">这一片天地好像是我的；我也像超出了平常的自己，到了另一个世界里。</voice>
            <voice id="129">我爱热闹，也爱冷静；<break strength="x-weak"/>爱群居，也爱独处。</voice>
            <voice id="130">像今晚上，一个人在这苍茫的月下，什么都可以想，什么都可以不想，便觉是个自由的人。</voice>
            <voice id="131">白天里一定要做的事，一定要说的话，现在都可不理。</voice>
            <voice id="132">这是独处的妙处，我且受用这无边的荷香月色好了。</voice>
        </speak>
    """

    # path = voice_vits(text, save_path=cache_path)
    # path =voice_vits_streaming(text, save_path=cache_path)
    # path = voice_w2v2_vits(text, save_path=cache_path)
    # path = voice_conversion(path, 1, 3, save_path=cache_path)
    # path = voice_hubert_vits(path, 0, save_path=cache_path)
    # path = voice_dimensional_emotion(path, save_path=cache_path)
    # path = voice_ssml(ssml, save_path=cache_path)
    # path = voice_bert_vits2("你好", lang="zh", save_path=cache_path)
    # path = voice_bert_vits2("こんにちは", lang="ja", save_path=cache_path)
    # path = voice_gpt_sovits(text=text, id=2, preset="wz")
    # path = voice_gpt_sovits(text=text, id=2, reference_audio=r"H:\git\vits-simple-api\data\reference_audio\wz_10068.wav",prompt_text="……嗯……大概、快上课的时候开始的。到这个程度的话，……半个小时吧？")

    # os.system(path)

    # text = "你好“你的修炼速度有些出乎我的意料”"
    # path = voice_reading_json(text=text, in_model_type="GPT-SOVITS", preset="wz", in_id=2, nr_model_type="BERT-VITS2",
    #                           nr_id=0)

    # os.system(path)