From e46c10f3e4afecc6aaa63a1aa88d9fc4f009bf59 Mon Sep 17 00:00:00 2001
From: AI Lab <129358391+1038lab@users.noreply.github.com>
Date: Wed, 5 Nov 2025 16:13:59 -0800
Subject: [PATCH] Add files via upload

---
 AI/WildPromptor_HFgpt.py | 65 ++++++++++++++++++++++++++++++++++++++++
 1 file changed, 65 insertions(+)
 create mode 100644 AI/WildPromptor_HFgpt.py

diff --git a/AI/WildPromptor_HFgpt.py b/AI/WildPromptor_HFgpt.py
new file mode 100644
index 0000000..46da460
--- /dev/null
+++ b/AI/WildPromptor_HFgpt.py
@@ -0,0 +1,65 @@
+from WildPromptorAI import WildPromptorAI
+from transformers import AutoModelForCausalLM, AutoTokenizer
+import json
+import os
+
+class WildPromptor_HFgpt(WildPromptorAI):
+    @classmethod
+    def INPUT_TYPES(cls):
+        return {
+            "required": {
+                "keywords": ("STRING", {"multiline": True}),
+                "model_repo": (cls.get_hfgpt_repos(),),
+                "max_length": ("INT", {"default": 1024, "min": 1, "max": 4096, "step": 1}),
+                "temperature": ("FLOAT", {"default": 0.7, "min": 0.1, "max": 2.0, "step": 0.1}),
+            }
+        }
+
+    RETURN_TYPES = ("STRING",)
+    RETURN_NAMES = ("prompt",)
+    FUNCTION = "generate_prompt"
+    CATEGORY = "🧪AILab/🤖AI"
+
+    @classmethod
+    def get_hfgpt_repos(cls):
+        config_path = os.path.join(os.path.dirname(os.path.dirname(__file__)), 'config_ai.json')
+        try:
+            with open(config_path, 'r') as f:
+                config = json.load(f)
+            repos = config.get('HFGPT_repos', [])
+            return repos if repos else ["No models found"]
+        except Exception as e:
+            print(f"Error loading HFGPT repos: {str(e)}")
+            return ["Configuration loading failed"]
+
+    def __init__(self):
+        super().__init__()
+        self.models = {}
+        self.tokenizers = {}
+
+    def generate_prompt(self, keywords, model_repo, temperature=0.7, max_length=256):
+        if model_repo not in self.models:
+            self.models[model_repo] = AutoModelForCausalLM.from_pretrained(model_repo)
+            self.tokenizers[model_repo] = AutoTokenizer.from_pretrained(model_repo)
+            self.models[model_repo].eval()
+
+        prompt = self.format_prompt(keywords)
+        input_ids = self.tokenizers[model_repo](prompt, return_tensors='pt').input_ids
+
+        outputs = self.models[model_repo].generate(
+            input_ids,
+            max_length=max_length,
+            num_return_sequences=1,
+            temperature=temperature,
+            do_sample=True,
+            no_repeat_ngram_size=2
+        )
+
+        generated_prompt = self.tokenizers[model_repo].decode(outputs[0], skip_special_tokens=True)
+        generated_prompt = self.clean_prompt(generated_prompt)
+
+        print(f"[HuggingFace GPT prompt]:\n{generated_prompt}")
+        return (generated_prompt,)
+
+NODE_CLASS_MAPPINGS = {"WildPromptor_HFgpt}
+NODE_DISPLAY_NAME_MAPPINGS = {"WildPromptor_HFgpt": "HuggingFace GPT 🤖(WildPromptor)"}
\ No newline at end of file