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# TT FLUX Workflow Settings (Advanced) *TT_FluxWorkflowSettingsAdvanced*
*This description was generated with AI assistance. If you spot any errors, please create an issue on GitHub.*
Advanced node for configuring Flux workflow generation parameters with separate CLIP-L and T5XXL prompts.
## Inputs
| Parameter | Type | Default | Range | Description |
|-------------------|--------|---------|-------------|--------------------------------------|
| `seed` | INT | 0 | 0 - 2^64-1 | Seed for reproducible results |
| `steps` | INT | 25 | 1 - 10000 | Number of sampling steps |
| `cfg` | FLOAT | 1.5 | 0.0 - 100.0 | CFG scale (classifier-free guidance) |
| `sampler_name` | COMBO | - | - | Sampler name from available list |
| `scheduler` | COMBO | - | - | Scheduler type |
| `clip_l_positive` | STRING | - | - | Positive prompt for CLIP-L encoder |
| `t5xxl_positive` | STRING | - | - | Positive prompt for T5XXL encoder |
| `clip_l_negative` | STRING | - | - | Negative prompt for CLIP-L encoder |
| `t5xxl_negative` | STRING | - | - | Negative prompt for T5XXL encoder |
| `guidance` | FLOAT | 3.5 | 1.0 - 10.0 | Guidance strength for Flux |
## Outputs
| Output | Type | Description |
|-------------------|--------------------|------------------------------|
| `WORKFLOW_CONFIG` | TT_WORKFLOW_CONFIG | Dictionary with all settings |
| `SEED` | INT | Seed value |
| `STEPS` | INT | Number of steps |
| `CFG` | FLOAT | CFG scale |
| `SAMPLER_NAME` | COMBO | Sampler name |
| `SCHEDULER` | COMBO | Scheduler |
| `CLIP_L_POSITIVE` | STRING | CLIP-L positive prompt |
| `T5XXL_POSITIVE` | STRING | T5XXL positive prompt |
| `CLIP_L_NEGATIVE` | STRING | CLIP-L negative prompt |
| `T5XXL_NEGATIVE` | STRING | T5XXL negative prompt |
| `GUIDANCE` | FLOAT | Guidance value |
## Purpose
Extended version of Flux workflow settings with dual-encoder prompt control. Allows separate configuration of CLIP-L and
T5XXL text encoders for precise control over the generation process. Supports dynamic prompts and multiline text input.
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[View on GitHub](https://github.com/tenser-tensor/ComfyUI-TenserTensor)