Files
scripts/tts-generator/gemini_tts_teste.py

142 lines
4.7 KiB
Python
Executable File

"""
gemini_tts_teste.py
Author: Descomplicar® Crescimento Digital
Link: https://descomplicar.pt
Copyright: 2025 Descomplicar®
"""
# To run this code you need to install the following dependencies:
# pip install google-genai
import base64
import mimetypes
import os
import re
import struct
from google import genai
from google.genai import types
def save_binary_file(file_name, data):
f = open(file_name, "wb")
f.write(data)
f.close()
print(f"File saved to to: {file_name}")
def generate_test():
client = genai.Client(
api_key=os.environ.get("GEMINI_API_KEY"),
)
model = "gemini-2.5-pro-preview-tts"
contents = [
types.Content(
role="user",
parts=[
types.Part.from_text(text="""Bem-vindo à Descomplicar, a agência de aceleração digital que transforma a sua presença online numa máquina de crescimento.
Somos especialistas em Marketing Digital, criação de websites profissionais e estratégias que geram resultados reais para o seu negócio.
Na Descomplicar, a nossa filosofia é simples: tornar o complexo mais simples. Descomplicamos o marketing digital para que você se possa focar no que faz melhor - gerir o seu negócio.
Marque uma reunião connosco e descubra como podemos acelerar o crescimento digital da sua empresa."""),
],
),
]
generate_content_config = types.GenerateContentConfig(
temperature=1.1,
response_modalities=[
"audio",
],
speech_config=types.SpeechConfig(
voice_config=types.VoiceConfig(
prebuilt_voice_config=types.PrebuiltVoiceConfig(
voice_name="Autonoe"
)
)
),
)
file_index = 0
for chunk in client.models.generate_content_stream(
model=model,
contents=contents,
config=generate_content_config,
):
if (
chunk.candidates is None
or chunk.candidates[0].content is None
or chunk.candidates[0].content.parts is None
):
continue
if chunk.candidates[0].content.parts[0].inline_data and chunk.candidates[0].content.parts[0].inline_data.data:
file_name = f"descomplicar_teste_audio_{file_index}"
file_index += 1
inline_data = chunk.candidates[0].content.parts[0].inline_data
data_buffer = inline_data.data
file_extension = mimetypes.guess_extension(inline_data.mime_type)
if file_extension is None:
file_extension = ".wav"
data_buffer = convert_to_wav(inline_data.data, inline_data.mime_type)
save_binary_file(f"{file_name}{file_extension}", data_buffer)
else:
print(chunk.text)
def convert_to_wav(audio_data: bytes, mime_type: str) -> bytes:
"""Generates a WAV file header for the given audio data and parameters."""
parameters = parse_audio_mime_type(mime_type)
bits_per_sample = parameters["bits_per_sample"]
sample_rate = parameters["rate"]
num_channels = 1
data_size = len(audio_data)
bytes_per_sample = bits_per_sample // 8
block_align = num_channels * bytes_per_sample
byte_rate = sample_rate * block_align
chunk_size = 36 + data_size
header = struct.pack(
"<4sI4s4sIHHIIHH4sI",
b"RIFF", # ChunkID
chunk_size, # ChunkSize (total file size - 8 bytes)
b"WAVE", # Format
b"fmt ", # Subchunk1ID
16, # Subchunk1Size (16 for PCM)
1, # AudioFormat (1 for PCM)
num_channels, # NumChannels
sample_rate, # SampleRate
byte_rate, # ByteRate
block_align, # BlockAlign
bits_per_sample, # BitsPerSample
b"data", # Subchunk2ID
data_size # Subchunk2Size (size of audio data)
)
return header + audio_data
def parse_audio_mime_type(mime_type: str) -> dict[str, int | None]:
"""Parses bits per sample and rate from an audio MIME type string."""
bits_per_sample = 16
rate = 24000
parts = mime_type.split(";")
for param in parts:
param = param.strip()
if param.lower().startswith("rate="):
try:
rate_str = param.split("=", 1)[1]
rate = int(rate_str)
except (ValueError, IndexError):
pass
elif param.startswith("audio/L"):
try:
bits_per_sample = int(param.split("L", 1)[1])
except (ValueError, IndexError):
pass
return {"bits_per_sample": bits_per_sample, "rate": rate}
if __name__ == "__main__":
generate_test()