Deep Translator CLIP Text Encode Node¶
Documentation¶
- Class name:
DeepTranslatorCLIPTextEncodeNode - Category:
AlekPet Nodes/conditioning - Output node:
False
This node is designed to integrate translation services with CLIP text encoding, facilitating the translation of text inputs into different languages and subsequently encoding these translations into a format suitable for conditioning models. It serves as a foundational component for nodes that require both translation and text encoding capabilities, streamlining the process of preparing text for various AI-driven applications.
Input types¶
Required¶
from_translate- Specifies the source language for translation, supporting a dynamic range of languages based on the selected translation service. It plays a crucial role in determining the initial language of the text to be translated.
- Comfy dtype:
COMBO[STRING] - Python dtype:
str
to_translate- Defines the target language for the translation, allowing for the conversion of text into a wide variety of languages as supported by the chosen translation service. This parameter is essential for specifying the desired output language of the translation.
- Comfy dtype:
COMBO[STRING] - Python dtype:
str
add_proxies- Indicates whether proxy usage is enabled or disabled for the translation service, affecting how the translation requests are sent.
- Comfy dtype:
COMBO[STRING] - Python dtype:
str
proxies- Provides the proxy settings to be used if proxy usage is enabled, facilitating the translation requests through specified proxy servers.
- Comfy dtype:
STRING - Python dtype:
str
auth_data- Contains authorization data required by some translation services, ensuring secure access to the translation features.
- Comfy dtype:
STRING - Python dtype:
str
service- Specifies the translation service to be used, allowing for the selection among various supported translation providers.
- Comfy dtype:
COMBO[STRING] - Python dtype:
str
text- The text input to be translated and encoded. This parameter is central to the node's functionality, serving as the content that undergoes translation and subsequent text encoding.
- Comfy dtype:
STRING - Python dtype:
str
clip- A CLIP model instance used for encoding the translated text into a format that is compatible with conditioning models. This parameter is key for integrating the translation output with downstream AI processes.
- Comfy dtype:
CLIP - Python dtype:
torch.nn.Module
Output types¶
conditioning- Comfy dtype:
CONDITIONING - The encoded representation of the translated text, formatted for use in conditioning models. This output is crucial for applications requiring text input to be in a specific encoded format.
- Python dtype:
List[Dict[str, torch.Tensor]]
- Comfy dtype:
string- Comfy dtype:
STRING - The translated text, providing the direct output of the translation process. This output is essential for understanding or further processing the translated content.
- Python dtype:
str
- Comfy dtype:
Usage tips¶
- Infra type:
GPU - Common nodes: unknown