From 4ffcb56f59977291afa87f723b4c3e6b72a42dd3 Mon Sep 17 00:00:00 2001
From: AI Lab <129358391+1038lab@users.noreply.github.com>
Date: Wed, 1 Jan 2025 15:43:24 -0800
Subject: [PATCH] Delete AI/WildPromptor_Enhancer.py

---
 AI/WildPromptor_Enhancer.py | 108 ------------------------------------
 1 file changed, 108 deletions(-)
 delete mode 100644 AI/WildPromptor_Enhancer.py

diff --git a/AI/WildPromptor_Enhancer.py b/AI/WildPromptor_Enhancer.py
deleted file mode 100644
index 92f56ca..0000000
--- a/AI/WildPromptor_Enhancer.py
+++ /dev/null
@@ -1,108 +0,0 @@
-import os
-import torch
-import folder_paths
-from transformers import pipeline, AutoTokenizer, AutoModelForSeq2SeqLM
-from huggingface_hub import snapshot_download
-
-MODEL_PATH = os.path.join(folder_paths.models_dir, "LLM", "Flux-Prompt-Enhance")
-os.makedirs(MODEL_PATH, exist_ok=True)
-
-class WildPromptor_Enhancer:
-    def __init__(self):
-        self.device = "cuda" if torch.cuda.is_available() else "cpu"
-        self.model_checkpoint = "gokaygokay/Flux-Prompt-Enhance"
-        print(f"Using device: {self.device}")
-        
-        if not os.listdir(MODEL_PATH):
-            print(f"Downloading {self.model_checkpoint} model...")
-            try:
-                snapshot_download(
-                    repo_id=self.model_checkpoint,
-                    local_dir=MODEL_PATH,
-                    local_dir_use_symlinks=False
-                )
-                print("Model downloaded successfully!")
-            except Exception as e:
-                print(f"Error downloading model: {str(e)}")
-                raise RuntimeError(f"Failed to download model: {str(e)}")
-        
-        try:
-            print("Loading model and tokenizer...")
-            self.tokenizer = AutoTokenizer.from_pretrained(MODEL_PATH)
-            self.model = AutoModelForSeq2SeqLM.from_pretrained(MODEL_PATH)
-            self.pipe = pipeline(
-                'text2text-generation',
-                model=self.model,
-                tokenizer=self.tokenizer,
-                repetition_penalty=1.2,
-                device=self.device
-            )
-            print("Model loaded successfully!")
-        except Exception as e:
-            print(f"Error loading model: {str(e)}")
-            raise RuntimeError(f"Failed to load model: {str(e)}")
-            
-        self.max_target_length = 256
-        self.prefix = "enhance prompt: "
-
-    @classmethod
-    def INPUT_TYPES(cls):
-        return {
-            "required": {
-                "prompt": ("STRING", {"multiline": True, "tooltip": "Input prompt to be enhanced"}),
-                "batch_size": ("INT", {"default": 1, "min": 1, "max": 20, "tooltip": "Number of enhanced prompts to generate"}),
-                "combine_output": ("BOOLEAN", {"default": False, "tooltip": "Combine all outputs into one string or output as separate records"}),
-                "seed": ("INT", {"default": 0, "min": 0, "max": 0xffffffffffffffff})
-            },
-        }
-
-    RETURN_TYPES = ("STRING",)
-    RETURN_NAMES = ("prompt",)
-    OUTPUT_IS_LIST = (True,)
-    FUNCTION = "enhancer"
-    CATEGORY = "🧪AILab/🤖AI"
-    class_type = "WildPromptor_Enhancer"
-
-    def enhancer(self, prompt, seed, batch_size, combine_output):
-        if not prompt or prompt.isspace():
-            return ([],)
-            
-        enhanced_prompts = []
-        input_text = self.prefix + prompt
-        
-        try:
-            for i in range(batch_size):
-                output_seed = seed + i if seed != 0 else 0
-                torch.manual_seed(output_seed)
-                
-                do_sample = output_seed != 0
-                temperature = 0.7 if do_sample else 0.0
-
-                result = self.pipe(
-                    input_text,
-                    max_length=self.max_target_length,
-                    do_sample=do_sample,
-                    temperature=temperature,
-                    num_return_sequences=1,
-                    top_k=50,
-                    top_p=0.95,
-                )
-                
-                enhanced_prompts.append(result[0]['generated_text'])
-                
-        except Exception as e:
-            print(f"Error during prompt enhancement: {str(e)}")
-            return ([f"Error: {str(e)}"],)
-            
-        if combine_output:
-            return (["\n---\n".join(enhanced_prompts)],)
-        else:
-            return (enhanced_prompts,)
-
-NODE_CLASS_MAPPINGS = {
-    "WildPromptor_Enhancer": WildPromptor_Enhancer
-}
-
-NODE_DISPLAY_NAME_MAPPINGS = {
-    "WildPromptor_Enhancer": "🤖 Prompt Enhancer"
-}
\ No newline at end of file