Added nodes TT_SdxlClipTextEncoderNode, TT_SdxlClipTextEncoderContextNode, TT_Flux1ClipTextEncoderNode, TT_Flux1ClipTextEncoderContextNode, minor bugfixes and refactoring, added docs, changed version
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## TT SDXL CLIP Text Encoder *TT_SdxlClipTextEncoderNode*
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*This description was generated with AI assistance. If you spot any errors, please create an issue on GitHub.*
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Encodes positive and negative text prompts for SDXL models using dual CLIP encoders (CLIP-L and CLIP-G) with aesthetic score and resolution
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conditioning.
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### Inputs
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| Parameter | Type | Required | Description |
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|-------------------|--------|----------|--------------------------------------------------------|
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| `clip` | CLIP | Yes | Dual CLIP model (CLIP-L + CLIP-G) |
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| `clip_l_positive` | STRING | Yes | CLIP-L positive prompt |
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| `clip_g_positive` | STRING | Yes | CLIP-G positive prompt |
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| `clip_l_negative` | STRING | Yes | CLIP-L negative prompt |
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| `clip_g_negative` | STRING | Yes | CLIP-G negative prompt |
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| `ascore_positive` | FLOAT | Yes | Aesthetic score for positive conditioning, default 9.0 |
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| `ascore_negative` | FLOAT | Yes | Aesthetic score for negative conditioning, default 6.0 |
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| `width` | INT | Yes | Source image width |
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| `height` | INT | Yes | Source image height |
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| `target_width` | INT | Yes | Target output width |
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| `target_height` | INT | Yes | Target output height |
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### Outputs
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| Parameter | Type | Description |
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|------------|--------------|-----------------------|
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| `POSITIVE` | CONDITIONING | Positive conditioning |
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| `NEGATIVE` | CONDITIONING | Negative conditioning |
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### Usage
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Connect `POSITIVE` and `NEGATIVE` outputs to a sampler. Set `width`/`height` to match your source image dimensions and `target_width`/`target_height`
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to your desired output resolution. Higher `ascore_positive` (8–10) steers generation toward higher aesthetic quality; lower `ascore_negative` (4–6)
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pushes away from low-quality outputs.
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---
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[View on GitHub](https://github.com/tenser-tensor/ComfyUI-TenserTensor)
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