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__init__.py

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+from .chatgpt_helper import NODE_CLASS_MAPPINGS, NODE_DISPLAY_NAME_MAPPINGS
+
+__all__ = ['NODE_CLASS_MAPPINGS', 'NODE_DISPLAY_NAME_MAPPINGS']

chatgpt_helper.py

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+import os
+import re
+import folder_paths
+import json
+import hashlib
+import openai
+
+
+class ChatGptHelper:
+    @classmethod
+    def INPUT_TYPES(cls):
+        return {
+            "required": {
+                 "enable_chatgpt": ("BOOLEAN", {
+                    "default": True, "label_on": "Yes", "label_off": "No"
+                }),
+                "chatgpt_api_key": ("STRING", {"multiline": True, "default": ""}),
+                "input_prompt_text": ("STRING", {"multiline": True, "default": ""}),
+                "chatgpt_instruction_text": ("STRING", {"multiline": True, "default": ""}),
+            }
+        }
+
+    
+    RETURN_TYPES = ("STRING",)
+    RETURN_NAMES = ("updated_prompt",)
+    FUNCTION = "update_prompt"
+    OUTPUT_NODE = True
+    CATEGORY = "utils"
+
+    # Class variable to store the last inputs and outputs
+    _cache = {}
+    
+    def update_prompt(self,enable_chatgpt,chatgpt_api_key, input_prompt_text, chatgpt_instruction_text,):
+        # Handle case where inputs are not lists
+        print("chatgpt_instruction_text---sss...")
+        print(input_prompt_text)
+        print(chatgpt_instruction_text)
+        updated_prompt_text=input_prompt_text
+        
+        # Generate a cache key for this specific run
+        input_data = {
+            "input_prompt_text": input_prompt_text,
+            "chatgpt_instruction_text": chatgpt_instruction_text
+        }
+        
+        # Create a hash of the inputs to use as cache key
+        cache_key = self._get_cache_key(input_data)
+        
+        # Check if we've already processed these exact inputs
+        if cache_key in ChatGptHelper._cache:
+            print("Using cached result for SaveTextFlorence node")
+            return ChatGptHelper._cache[cache_key]
+        if enable_chatgpt:    
+            updated_prompt_text =self._update_prompt_chatgpt(self,chatgpt_api_key, input_prompt_text,chatgpt_instruction_text)
+        #SaveTextFlorence._cache[cache_key] = result
+        return updated_prompt_text
+
+    def _get_cache_key(self, input_data):
+        """Generate a unique hash for the input data to use as a cache key"""
+        # Convert input data to a JSON string and hash it
+        input_json = json.dumps(input_data, sort_keys=True)
+        return hashlib.md5(input_json.encode()).hexdigest()
+
+    def _update_prompt_chatgpt(self,chatgpt_api_key, prompt,chatgpt_instruction_text):
+            # Set your OpenAI API key
+        client = openai.OpenAI(api_key=chatgpt_api_key)  # or use `os.getenv("OPENAI_API_KEY")`
+            
+        original_prompt = prompt
+            
+        instruction = (
+                "You are an AI prompt editor. Given an image prompt, update it by:\n"
+                
+                "1. Enhancing the prompt to generate a high-quality, natural, realistic image.\n"
+                "2. Add visual clarity, lighting, and environment details where needed.\n"
+                "3. Make the language flow naturally and sound like a professional image generation prompt.\n"
+                "4. Do not add technical instructions or explain your changes.\n"
+                "5. Return ONLY the updated prompt, no extra commentary or headers."
+                + chatgpt_instruction_text 
+            )
+            
+        response = client.chat.completions.create(
+                model="gpt-4",
+                messages=[
+                    {"role": "system", "content": "You are an image prompt editor. Only return the final prompt with no extra text."},
+                    {"role": "user", "content": instruction + "\n\n" + original_prompt}
+                ],
+                temperature=0.7
+            )
+            
+        new_prompt = response.choices[0].message.content.strip()
+        return new_prompt
+        
+
+
+    @classmethod
+    def IS_CHANGED(cls, text, file, enable_replacement, image_style, gender_age_replacement, lora_trigger, negative_prompt_text):
+        """
+        Tells ComfyUI whether this node should be re-executed.
+        Returns None to indicate the node should be considered cached.
+        """
+        return None
+
+NODE_CLASS_MAPPINGS = {
+    "ChatGptHelper": ChatGptHelper
+}
+
+NODE_DISPLAY_NAME_MAPPINGS = {
+    "ChatGptHelper": "ChatGpt Helper to enhance prompt"
+}