Added ElevenLabs TTS
This commit is contained in:
Aryan
@@ -13,6 +13,8 @@ A collection of powerful custom nodes for ComfyUI that connect your local workfl
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* **Google Imagen Generator & Edit:** Create and edit images with Google's Imagen models, with support for Vertex AI.
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* **Nano Banana:** A creative image generation node using a specialized Gemini model.
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* **Veo Text-to-Video:** Generate high-quality video clips from text prompts using Google's Veo model via Vertex AI.
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* **ElevenLabs TTS:** Generate high-quality speech from text using ElevenLabs' diverse range of voices and models.
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* **Gemini TTS:** Create speech from text using Google's Gemini models.
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* **Seamless Integration:** All nodes are designed to work seamlessly with standard ComfyUI inputs (IMAGE, MASK, STRING) and outputs, allowing you to chain them into complex and creative workflows.
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* **Secure & Simple:** Simply provide your API key in the node's input field to get started.
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@@ -44,8 +46,9 @@ A collection of powerful custom nodes for ComfyUI that connect your local workfl
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All nodes in this collection require API keys to function.
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* **FLUX Nodes (Replicate):** You will need a [Replicate API Token](https://replicate.com/account/api-tokens).
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* **Gemini, Imagen, and Nano Banana Nodes:** You will need a [Google AI Studio API Key](https://aistudio.google.com/app/api-keys).
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* **Gemini, Imagen, Nano Banana, and Gemini TTS Nodes:** You will need a [Google AI Studio API Key](https://aistudio.google.com/app/api-keys).
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* **GPT Image Edit Node:** You will need an [OpenAI API Key](https://platform.openai.com/api-keys).
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* **ElevenLabs TTS Node:** You will need an [ElevenLabs API Key](https://elevenlabs.io/).
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* **Vertex AI Nodes (Imagen Edit, Veo):** You will need a Google Cloud Project ID, a service account with appropriate permissions, and the location for the resources.
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You can paste your key directly into the `api_key` field on the corresponding node. For Vertex AI nodes, you will need to provide the project ID, location, and path to your service account JSON file.
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@@ -174,6 +177,42 @@ Generate short, high-quality video clips from a text description using Google's
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---
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### ElevenLabs TTS
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Generate speech from text using the ElevenLabs API.
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* **Category:** `audio/generation`
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* **Inputs:**
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* `text`: The text to convert to speech.
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* `api_key`: Your API key from ElevenLabs.
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* `voice_id`: The ID of the voice to use for generation.
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* `model_id`: The ElevenLabs model to use.
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* `output_format`: The desired output audio format.
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* `stability`: Controls the stability and variability of the generated speech.
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* `similarity_boost`: Enhances the similarity of the generated speech to the chosen voice.
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* `speed`: Adjusts the speaking rate.
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* `style`: Controls the expressiveness of the speech.
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* `use_speaker_boost`: A boolean to enable or disable speaker boost.
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* `seed`: A seed for ensuring reproducible results.
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* **Output:**
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* `audio`: The generated audio waveform and sample rate.
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### Gemini TTS
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Generate speech from text using Google's Gemini TTS models.
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* **Category:** `audio/generation`
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* **Inputs:**
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* `text`: The text to be converted into speech.
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* `api_key`: Your API key from Google AI Studio.
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* `model`: The specific Gemini model to use for generation.
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* `voice_id`: The prebuilt voice to use for the output.
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* `temperature`: Controls the randomness and creativity of the output.
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* `seed`: A seed for ensuring reproducible results.
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* `system_prompt` (Optional): A system-level instruction to guide the model's behavior.
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* **Output:**
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* `audio`: The generated audio waveform and sample rate.
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## Acknowledgements
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+3
-2
@@ -8,8 +8,9 @@ from .veo import NODE_CLASS_MAPPINGS as VEO_MAPPINGS, NODE_DISPLAY_NAME_MAPPINGS
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from .gemini_segment import NODE_CLASS_MAPPINGS as GEMINI_SEGMENT_MAPPINGS, NODE_DISPLAY_NAME_MAPPINGS as GEMINI_SEGMENT_DISPLAY
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from .nano_banana import NODE_CLASS_MAPPINGS as NANO_BANANA_MAPPINGS, NODE_DISPLAY_NAME_MAPPINGS as NANO_BANANA_DISPLAY
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from .gemini_tts import NODE_CLASS_MAPPINGS as GEMINI_TTS_MAPPINGS, NODE_DISPLAY_NAME_MAPPINGS as GEMINI_TTS_DISPLAY
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from .elevenlabs_tts import NODE_CLASS_MAPPINGS as ELEVENLABS_TTS_MAPPINGS, NODE_DISPLAY_NAME_MAPPINGS as ELEVENLABS_TTS_DISPLAY
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NODE_CLASS_MAPPINGS = {**PRO_MAPPINGS, **MAX_MAPPINGS, **GEMINI_MAPPINGS, **GPT_IMAGE_MAPPINGS, **IMAGEN_IMAGE_MAPPINGS, **IMAGEN_EDIT_MAPPINGS, **VEO_MAPPINGS, **GEMINI_SEGMENT_MAPPINGS, **NANO_BANANA_MAPPINGS, **GEMINI_TTS_MAPPINGS}
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NODE_DISPLAY_NAME_MAPPINGS = {**PRO_DISPLAY, **MAX_DISPLAY, **GEMINI_DISPLAY, **GPT_IMAGE_DISPLAY, **IMAGEN_IMAGE_DISPLAY, **IMAGEN_EDIT_DISPLAY, **VEO_DISPLAY, **GEMINI_SEGMENT_DISPLAY, **NANO_BANANA_DISPLAY, **GEMINI_TTS_DISPLAY}
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NODE_CLASS_MAPPINGS = {**PRO_MAPPINGS, **MAX_MAPPINGS, **GEMINI_MAPPINGS, **GPT_IMAGE_MAPPINGS, **IMAGEN_IMAGE_MAPPINGS, **IMAGEN_EDIT_MAPPINGS, **VEO_MAPPINGS, **GEMINI_SEGMENT_MAPPINGS, **NANO_BANANA_MAPPINGS, **GEMINI_TTS_MAPPINGS, **ELEVENLABS_TTS_MAPPINGS}
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NODE_DISPLAY_NAME_MAPPINGS = {**PRO_DISPLAY, **MAX_DISPLAY, **GEMINI_DISPLAY, **GPT_IMAGE_DISPLAY, **IMAGEN_IMAGE_DISPLAY, **IMAGEN_EDIT_DISPLAY, **VEO_DISPLAY, **GEMINI_SEGMENT_DISPLAY, **NANO_BANANA_DISPLAY, **GEMINI_TTS_DISPLAY, **ELEVENLABS_TTS_DISPLAY}
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__all__ = ['NODE_CLASS_MAPPINGS', 'NODE_DISPLAY_NAME_MAPPINGS']
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@@ -0,0 +1,130 @@
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import os
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import io
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import requests
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import torchaudio
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class ElevenLabsTTSNode:
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@classmethod
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def INPUT_TYPES(cls):
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return {
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"required": {
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"text": ("STRING", {"multiline": True, "default": ""}),
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"model_id": ([
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"eleven_multilingual_v2",
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"eleven_turbo_v2_5",
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"eleven_flash_v2_5",
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"eleven_flash_v2",
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"eleven_turbo_v2",
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"eleven_multilingual_v1",
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"eleven_v3"
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],),
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"output_format": ([
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"mp3_44100_128",
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"mp3_22050_32",
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"mp3_44100_32",
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"mp3_44100_64",
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"mp3_44100_96",
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"mp3_44100_192",
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"pcm_8000",
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"pcm_16000",
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"pcm_22050",
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"pcm_24000",
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"pcm_44100",
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"pcm_48000",
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"ulaw_8000",
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"alaw_8000",
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"opus_48000_32",
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"opus_48000_64",
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"opus_48000_96",
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"opus_48000_128",
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"opus_48000_192"
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],),
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"voice_id": ("STRING", {"multiline": False, "default": "oPM3trUCF4e0vTcsrMQr"}),
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"stability": ("FLOAT", {"default": 0.50, "min": 0.0, "max": 1.0, "step": 0.01}),
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"similarity_boost": ("FLOAT", {"default": 0.50, "min": 0.0, "max": 1.0, "step": 0.01}),
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"speed": ("FLOAT", {"default": 1.0, "min": 0.25, "max": 2.0, "step": 0.01}),
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"style": ("FLOAT", {"default": 0.50, "min": 0.0, "max": 1.0, "step": 0.01}),
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"use_speaker_boost": ("BOOLEAN", {"default": True}),
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"seed": ("INT", {"default": 40, "min": 0, "max": 4294967294}),
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"api_key": ("STRING", {"multiline": False, "default": ""}),
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},
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"optional": {
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"previous_text": ("STRING", {"multiline": True, "default": ""}),
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"next_text": ("STRING", {"multiline": True, "default": ""}),
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}
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}
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RETURN_TYPES = ("AUDIO",)
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RETURN_NAMES = ("audio",)
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FUNCTION = "generate_speech"
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CATEGORY = "audio/generation"
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def generate_speech(self, text, api_key, voice_id, model_id, output_format,
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stability, similarity_boost, speed, style, use_speaker_boost, seed,
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previous_text="", next_text=""):
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if not text.strip():
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raise ValueError("Text input cannot be empty.")
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key = api_key.strip() or os.environ.get("XI_API_KEY")
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if not key:
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raise ValueError("No API key provided.")
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url = f"https://api.elevenlabs.io/v1/text-to-speech/{voice_id}"
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headers = {
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"xi-api-key": key,
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"Content-Type": "application/json"
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}
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if model_id == "eleven_v3":
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allowed_stabilities = [0.0, 0.5, 1.0]
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original_stability = stability
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stability = min(allowed_stabilities, key=lambda x: abs(x - original_stability))
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if stability != original_stability:
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print(f"For 'eleven_v3' model, stability value must be one of: [0.0, 0.5, 1.0] (0.0 = Creative, 0.5 = Natural, 1.0 = Robust). Rounding stability to {stability}.")
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voice_settings = {
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"stability": stability,
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"similarity_boost": similarity_boost,
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"speed": speed,
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"style": style,
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"use_speaker_boost": use_speaker_boost
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}
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data = {
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"text": text,
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"voice_settings": voice_settings,
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"model_id": model_id,
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"seed": seed,
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"output_format": output_format
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}
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if model_id == "eleven_v3":
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if previous_text.strip() or next_text.strip():
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print("Providing previous_text or next_text is not yet supported with the 'eleven_v3' model. Ignoring these inputs.")
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else:
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if previous_text.strip():
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data["previous_text"] = previous_text
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if next_text.strip():
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data["next_text"] = next_text
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response = requests.post(url, json=data, headers=headers)
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if response.status_code != 200:
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raise Exception(f"ElevenLabs API Error: {response.status_code}, {response.text}")
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# Decode audio from memory
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audio_buffer = io.BytesIO(response.content)
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waveform, sample_rate = torchaudio.load(audio_buffer)
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# Return in ComfyUI audio format
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return ({"waveform": waveform.unsqueeze(0), "sample_rate": sample_rate},)
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@classmethod
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def IS_CHANGED(cls, **kwargs):
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return f"{kwargs.get('text', '')}-{kwargs.get('voice_id', '')}-{kwargs.get('seed', 40)}"
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NODE_CLASS_MAPPINGS = {"ElevenLabsTTSNode": ElevenLabsTTSNode}
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NODE_DISPLAY_NAME_MAPPINGS = {"ElevenLabsTTSNode": "ElevenLabs TTS"}
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@@ -1,4 +1,3 @@
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import base64
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import os
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import io
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import numpy as np
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+7
-7
@@ -10,15 +10,15 @@ class GeminiTTSNode:
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def INPUT_TYPES(cls):
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return {
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"required": {
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"text": ("STRING", {"multiline": True, "default": ""}),
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"api_key": ("STRING", {"multiline": False, "default": ""}),
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"model": ("STRING", {"default": "gemini-2.5-flash-preview-tts", "multiline": False}),
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"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"],),
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"seed": ("INT", {"default": 69, "min": -1, "max": 2147483646, "step": 1}),
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"temperature": ("FLOAT", {"default": 1.0, "min": 0.0, "max": 1.0, "step": 0.01}),
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"text": ("STRING", {"multiline": True, "default": ""}),
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"api_key": ("STRING", {"multiline": False, "default": ""}),
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"model": (["gemini-2.5-flash-preview-tts", "gemini-2.5-pro-preview-tts"],),
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"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"],),
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"seed": ("INT", {"default": 69, "min": -1, "max": 2147483646, "step": 1}),
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"temperature": ("FLOAT", {"default": 1.0, "min": 0.0, "max": 1.0, "step": 0.01}),
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},
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"optional": {
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"system_prompt": ("STRING", {"multiline": True, "default": ""}),
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"system_prompt": ("STRING", {"multiline": True, "default": ""}),
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}
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}
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@@ -1,6 +1,5 @@
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import requests
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import base64
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import json
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import torch
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import numpy as np
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from PIL import Image
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