93 lines
3.8 KiB
Python
93 lines
3.8 KiB
Python
import os
|
|
import torch
|
|
from google.genai import Client, types
|
|
|
|
class GeminiTTSNode:
|
|
|
|
@classmethod
|
|
def INPUT_TYPES(cls):
|
|
return {
|
|
"required": {
|
|
"text": ("STRING", {"multiline": True, "default": ""}),
|
|
"api_key": ("STRING", {"multiline": False, "default": ""}),
|
|
"model": (["gemini-2.5-flash-preview-tts", "gemini-2.5-pro-preview-tts"],),
|
|
"voice_id": (["Zephyr", "Puck", "Charon", "Kore", "Fenrir", "Leda", "Orus", "Aoede", "Callirrhoe", "Autonoe", "Enceladus", "Iapetus", "Umbriel", "Algieba", "Despina", "Erinome", "Achernar", "Laomedeia", "Rasalgethi", "Algenib", "Achird", "Pulcherrima", "Gacrux", "Schedar", "Alnilam", "Sulafat", "Sadaltager", "Sadachbia", "Vindemiatrix", "Zubenelgenubi"],),
|
|
"seed": ("INT", {"default": 69, "min": -1, "max": 2147483646, "step": 1}),
|
|
"temperature": ("FLOAT", {"default": 1.0, "min": 0.0, "max": 1.0, "step": 0.01}),
|
|
},
|
|
"optional": {
|
|
"system_prompt": ("STRING", {"multiline": True, "default": ""}),
|
|
}
|
|
}
|
|
|
|
RETURN_TYPES = ("AUDIO",)
|
|
RETURN_NAMES = ("audio",)
|
|
FUNCTION = "generate_speech"
|
|
CATEGORY = "audio/generation"
|
|
|
|
def generate_speech(self, text, api_key, voice_id, temperature, model, seed, system_prompt=""):
|
|
|
|
if not text.strip():
|
|
raise ValueError("Text input cannot be empty.")
|
|
|
|
key = api_key.strip() or os.environ.get("GEMINI_TTS_API_KEY")
|
|
if not key:
|
|
raise ValueError("No API key provided.")
|
|
|
|
client = Client(
|
|
api_key=key,
|
|
http_options=types.HttpOptions(
|
|
retry_options=types.HttpRetryOptions(attempts=10, jitter=10)
|
|
)
|
|
)
|
|
|
|
# Build prompt
|
|
prompt_text = text
|
|
if system_prompt.strip():
|
|
prompt_text = system_prompt.strip() + ":\n\n\"" + text + "\""
|
|
|
|
contents = [types.Content(role="user", parts=[types.Part.from_text(text=prompt_text)])]
|
|
|
|
config = types.GenerateContentConfig(
|
|
temperature=temperature,
|
|
seed=seed,
|
|
response_modalities=["audio"],
|
|
speech_config=types.SpeechConfig(
|
|
voice_config=types.VoiceConfig(
|
|
prebuilt_voice_config=types.PrebuiltVoiceConfig(voice_name=voice_id)
|
|
)
|
|
),
|
|
)
|
|
|
|
# Generate audio - collect raw PCM chunks
|
|
audio_data = b""
|
|
|
|
for chunk in client.models.generate_content_stream(
|
|
model=model,
|
|
contents=contents,
|
|
config=config
|
|
):
|
|
if (chunk.candidates and chunk.candidates[0].content and
|
|
chunk.candidates[0].content.parts and
|
|
chunk.candidates[0].content.parts[0].inline_data):
|
|
|
|
inline_data = chunk.candidates[0].content.parts[0].inline_data
|
|
audio_data += inline_data.data
|
|
|
|
if not audio_data:
|
|
raise ValueError("No audio data received from API.")
|
|
|
|
# Convert raw PCM to waveform tensor
|
|
waveform = torch.frombuffer(bytearray(audio_data), dtype=torch.int16)
|
|
waveform = waveform.to(torch.float32) / 32768.0
|
|
waveform = waveform.unsqueeze(0)
|
|
sample_rate = 24000
|
|
|
|
return ({"waveform": waveform.unsqueeze(0), "sample_rate": sample_rate},)
|
|
|
|
@classmethod
|
|
def IS_CHANGED(cls, **kwargs):
|
|
return f"{kwargs.get('text', '')}-{kwargs.get('voice_id', '')}-{kwargs.get('temperature', 1.0)}-{kwargs.get('model', '')}-{kwargs.get('seed', 69)}-{kwargs.get('system_prompt', '')}"
|
|
|
|
NODE_CLASS_MAPPINGS = {"GeminiTTSNode": GeminiTTSNode}
|
|
NODE_DISPLAY_NAME_MAPPINGS = {"GeminiTTSNode": "Gemini TTS"} |