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#
# Copyright 2024 The InfiniFlow Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
#
import requests
from typing import Annotated, Literal
from abc import ABC
import httpx
import ormsgpack
from pydantic import BaseModel, conint
from rag.utils import num_tokens_from_string
import json
import re
import time
class ServeReferenceAudio(BaseModel):
audio: bytes
text: str
class ServeTTSRequest(BaseModel):
text: str
chunk_length: Annotated[int, conint(ge=100, le=300, strict=True)] = 200
# Audio format
format: Literal["wav", "pcm", "mp3"] = "mp3"
mp3_bitrate: Literal[64, 128, 192] = 128
# References audios for in-context learning
references: list[ServeReferenceAudio] = []
# Reference id
# For example, if you want use https://fish.audio/m/7f92f8afb8ec43bf81429cc1c9199cb1/
# Just pass 7f92f8afb8ec43bf81429cc1c9199cb1
reference_id: str | None = None
# Normalize text for en & zh, this increase stability for numbers
normalize: bool = True
# Balance mode will reduce latency to 300ms, but may decrease stability
latency: Literal["normal", "balanced"] = "normal"
class Base(ABC):
def __init__(self, key, model_name, base_url):
pass
def tts(self, audio):
pass
def normalize_text(self, text):
return re.sub(r'(\*\*|##\d+\$\$|#)', '', text)
class FishAudioTTS(Base):
def __init__(self, key, model_name, base_url="https://api.fish.audio/v1/tts"):
if not base_url:
base_url = "https://api.fish.audio/v1/tts"
key = json.loads(key)
self.headers = {
"api-key": key.get("fish_audio_ak"),
"content-type": "application/msgpack",
}
self.ref_id = key.get("fish_audio_refid")
self.base_url = base_url
def tts(self, text):
from http import HTTPStatus
text = self.normalize_text(text)
request = ServeTTSRequest(text=text, reference_id=self.ref_id)
with httpx.Client() as client:
try:
with client.stream(
method="POST",
url=self.base_url,
content=ormsgpack.packb(
request, option=ormsgpack.OPT_SERIALIZE_PYDANTIC
),
headers=self.headers,
timeout=None,
) as response:
if response.status_code == HTTPStatus.OK:
for chunk in response.iter_bytes():
yield chunk
else:
response.raise_for_status()
yield num_tokens_from_string(text)
except httpx.HTTPStatusError as e:
raise RuntimeError(f"**ERROR**: {e}")
class QwenTTS(Base):
def __init__(self, key, model_name, base_url=""):
import dashscope
self.model_name = model_name
dashscope.api_key = key
def tts(self, text):
from dashscope.api_entities.dashscope_response import SpeechSynthesisResponse
from dashscope.audio.tts import ResultCallback, SpeechSynthesizer, SpeechSynthesisResult
from collections import deque
class Callback(ResultCallback):
def __init__(self) -> None:
self.dque = deque()
def _run(self):
while True:
if not self.dque:
time.sleep(0)
continue
val = self.dque.popleft()
if val:
yield val
else:
break
def on_open(self):
pass
def on_complete(self):
self.dque.append(None)
def on_error(self, response: SpeechSynthesisResponse):
raise RuntimeError(str(response))
def on_close(self):
pass
def on_event(self, result: SpeechSynthesisResult):
if result.get_audio_frame() is not None:
self.dque.append(result.get_audio_frame())
text = self.normalize_text(text)
callback = Callback()
SpeechSynthesizer.call(model=self.model_name,
text=text,
callback=callback,
format="mp3")
try:
for data in callback._run():
yield data
yield num_tokens_from_string(text)
except Exception as e:
raise RuntimeError(f"**ERROR**: {e}")
class OpenAITTS(Base):
def __init__(self, key, model_name="tts-1", base_url="https://api.openai.com/v1"):
if not base_url: base_url="https://api.openai.com/v1"
self.api_key = key
self.model_name = model_name
self.base_url = base_url
self.headers = {
"Authorization": f"Bearer {self.api_key}",
"Content-Type": "application/json"
}
def tts(self, text, voice="alloy"):
text = self.normalize_text(text)
payload = {
"model": self.model_name,
"voice": voice,
"input": text
}
response = requests.post(f"{self.base_url}/audio/speech", headers=self.headers, json=payload, stream=True)
if response.status_code != 200:
raise Exception(f"**Error**: {response.status_code}, {response.text}")
for chunk in response.iter_content():
if chunk:
yield chunk
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