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osolmaz committed Feb 25, 2024
1 parent f02a5f8 commit 3628134
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4 changes: 4 additions & 0 deletions docs/source/api.rst
Original file line number Diff line number Diff line change
Expand Up @@ -38,6 +38,10 @@ Speech services
:members:
:show-inheritance:

.. automodule:: manim_voiceover.services.openai
:members:
:show-inheritance:

.. automodule:: manim_voiceover.services.pyttsx3
:members:
:show-inheritance:
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32 changes: 32 additions & 0 deletions docs/source/services.rst
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Expand Up @@ -47,6 +47,11 @@ Manim Voiceover defines the :py:class:`~~base.SpeechService` class for adding ne
- No
- No
- It's a free API subsidized by Google, so there is a likelihood it may stop working in the future.
* - :py:class:`~openai.OpenAIService`
- Very good, human-like
- No
- Yes
- Requires OpenAI developer account. See `platform <https://platform.openai.com/signup>`__ to sign up, and the `pricing page <https://openai.com/pricing#:~:text=%24-,0.030,-/%201K%20characters>`__ for more details.
* - :py:class:`~pyttsx3.PyTTSX3Service`
- Bad
- Yes
Expand Down Expand Up @@ -136,6 +141,33 @@ Install Manim Voiceover with the ``gtts`` extra in order to use :py:class:`~gtts
Refer to the `example usage <https://github.com/ManimCommunity/manim-voiceover/blob/main/examples/gtts-example.py>`__ to get started.

:py:class:`~openai.OpenAIService`
*************************************
`OpenAI <https://platform.openai.com/docs/api-reference/audio/createSpeech/>`__ provides a text-to-speech service.
Since it is an api request, it requires an internet connection to work. It requires an API key to use. Register for one `here <https://platform.openai.com/>`__.

Install Manim Voiceover with the ``openai`` extra in order to use :py:class:`~openai.OpenAIService`:

.. code:: sh
pip install "manim-voiceover[openai]"
Then, you need to find out your api key:

- Sign in to `OpenAI platform <https://platform.openai.com/>`__ and click into Api Keys from the left panel.
- Click create a new secret key and copy it.

Create a file called ``.env`` that contains your authentication
information in the same directory where you call Manim.

.. code:: sh
OPENAI_API_KEY="..." # insert the secret key here. It should start with "sk-"
Check out `OpenAI docs <https://platform.openai.com/docs/guides/text-to-speech/>`__ for more details.

Refer to the `example usage <https://github.com/ManimCommunity/manim-voiceover/blob/main/examples/openai-example.py>`__ to get started.

:py:class:`~pyttsx3.PyTTSX3Service`
***********************************

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30 changes: 30 additions & 0 deletions examples/openai-example.py
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@@ -0,0 +1,30 @@
from manim import *
from manim_voiceover import VoiceoverScene
from manim_voiceover.services.openai import OpenAIService


class OpenAIExample(VoiceoverScene):
def construct(self):
self.set_speech_service(
OpenAIService(
voice="fable",
model="tts-1-hd",
)
)

circle = Circle()
square = Square().shift(2 * RIGHT)

with self.voiceover(text="This circle is drawn as I speak.") as tracker:
self.play(Create(circle), run_time=tracker.duration)

with self.voiceover(text="Let's shift it to the left 2 units.") as tracker:
self.play(circle.animate.shift(2 * LEFT), run_time=tracker.duration)

with self.voiceover(text="Now, let's transform it into a square.") as tracker:
self.play(Transform(circle, square), run_time=tracker.duration)

with self.voiceover(text="Thank you for watching.", speed=0.75): # You can also change the audio speed by specifying the speed argument.
self.play(Uncreate(circle))

self.wait()
9 changes: 6 additions & 3 deletions manim_voiceover/services/elevenlabs.py
Original file line number Diff line number Diff line change
Expand Up @@ -150,8 +150,10 @@ def generate_from_text(
input_data = {
"input_text": input_text,
"service": "elevenlabs",
"model": self.model,
"voice": self.voice.model_dump(exclude_none=True),
"config": {
"model": self.model,
"voice": self.voice.model_dump(exclude_none=True),
},
}

# if not config.disable_caching:
Expand All @@ -164,8 +166,9 @@ def generate_from_text(
audio_path = self.get_audio_basename(input_data) + ".mp3"
else:
audio_path = path

try:
audio = generate(text=text, voice=self.voice, model=self.model)
audio = generate(text=input_text, voice=self.voice, model=self.model)
save(audio, str(Path(cache_dir) / audio_path)) # type: ignore
except Exception as e:
logger.error(e)
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118 changes: 118 additions & 0 deletions manim_voiceover/services/openai.py
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@@ -0,0 +1,118 @@
import os
import sys
from pathlib import Path
from manim import logger
from dotenv import load_dotenv, find_dotenv

from manim_voiceover.helper import (
create_dotenv_file,
prompt_ask_missing_extras,
remove_bookmarks,
)

try:
import openai
except ImportError:
logger.error(
"Missing packages. "
'Run `pip install "manim-voiceover[openai]"` to use OpenAIService.'
)

from manim_voiceover.services.base import SpeechService

load_dotenv(find_dotenv(usecwd=True))


def create_dotenv_openai():
logger.info(
"Check out https://voiceover.manim.community/en/stable/services.html "
"to learn how to create an account and get your subscription key."
)
if not create_dotenv_file(["OPENAI_API_KEY"]):
raise ValueError(
"The environment variable OPENAI_API_KEY is not set. Please set it "
"or create a .env file with the variables."
)
logger.info("The .env file has been created. Please run Manim again.")
sys.exit()


class OpenAIService(SpeechService):
"""
Speech service class for OpenAI TTS Service. See the `OpenAI API page
<https://platform.openai.com/docs/api-reference/audio/createSpeech>`__
for more information about voices and models.
"""

def __init__(
self,
voice: str = "alloy",
model: str = "tts-1-hd",
transcription_model="base",
**kwargs
):
"""
Args:
voice (str, optional): The voice to use. See the
`API page <https://platform.openai.com/docs/api-reference/audio/createSpeech>`__
for all the available options. Defaults to ``"alloy"``.
model (str, optional): The TTS model to use.
See the `API page <https://platform.openai.com/docs/api-reference/audio/createSpeech>`__
for all the available options. Defaults to ``"tts-1-hd"``.
"""
prompt_ask_missing_extras("openai", "openai", "OpenAIService")
self.voice = voice
self.model = model

SpeechService.__init__(self, transcription_model=transcription_model, **kwargs)

def generate_from_text(
self, text: str, cache_dir: str = None, path: str = None, **kwargs
) -> dict:
""""""
if cache_dir is None:
cache_dir = self.cache_dir

speed = kwargs.get("speed", 1.0)

if not (0.25 <= speed <= 4.0):
raise ValueError("The speed must be between 0.25 and 4.0.")

input_text = remove_bookmarks(text)
input_data = {
"input_text": input_text,
"service": "openai",
"config": {
"voice": self.voice,
"model": self.model,
"speed": speed,
},
}

cached_result = self.get_cached_result(input_data, cache_dir)
if cached_result is not None:
return cached_result

if path is None:
audio_path = self.get_audio_basename(input_data) + ".mp3"
else:
audio_path = path

if os.getenv("OPENAI_API_KEY") is None:
create_dotenv_openai()

response = openai.audio.speech.create(
model=self.model,
voice=self.voice,
input=input_text,
speed=speed,
)
response.stream_to_file(str(Path(cache_dir) / audio_path))

json_dict = {
"input_text": text,
"input_data": input_data,
"original_audio": audio_path,
}

return json_dict
35 changes: 34 additions & 1 deletion manim_voiceover/tracker.py
Original file line number Diff line number Diff line change
Expand Up @@ -57,10 +57,43 @@ def __init__(self, scene: Scene, data: dict, cache_dir: str):
if "word_boundaries" in self.data:
self._process_bookmarks()

def _get_fallback_word_boundaries(self):
"""
Returns dummy word boundaries assuming a linear mapping between
text and audio. Used when word boundaries are not available.
"""
input_text = remove_bookmarks(self.data["input_text"])
return [
{
"audio_offset": 0,
"text_offset": 0,
"word_length": len(input_text),
"text": self.data["input_text"],
"boundary_type": "Word",
},
{
"audio_offset": self.duration * AUDIO_OFFSET_RESOLUTION,
"text_offset": len(input_text),
"word_length": 1,
"text": ".",
"boundary_type": "Word",
},
]

def _process_bookmarks(self) -> None:
self.bookmark_times = {}
self.bookmark_distances = {}
self.time_interpolator = TimeInterpolator(self.data["word_boundaries"])

word_boundaries = self.data["word_boundaries"]
if not word_boundaries or len(word_boundaries) < 2:
logger.warning(
f"Word boundaries for voiceover {self.data['input_text']} are not "
"available or are insufficient. Using fallback word boundaries."
)
word_boundaries = self._get_fallback_word_boundaries()

self.time_interpolator = TimeInterpolator(word_boundaries)

net_text_len = len(remove_bookmarks(self.data["input_text"]))
if "transcribed_text" in self.data:
transcribed_text_len = len(self.data["transcribed_text"].strip())
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