From a2d1058ea710e920c19fb7c477e2efba239c7a8a Mon Sep 17 00:00:00 2001 From: yunxiang wei <121092793+yiwangsimple@users.noreply.github.com> Date: Wed, 31 Jul 2024 10:55:13 +0800 Subject: [PATCH] Delete ollama_prompt_extractor.py --- ollama_prompt_extractor.py | 150 ------------------------------------- 1 file changed, 150 deletions(-) delete mode 100644 ollama_prompt_extractor.py diff --git a/ollama_prompt_extractor.py b/ollama_prompt_extractor.py deleted file mode 100644 index 5e4fad2..0000000 --- a/ollama_prompt_extractor.py +++ /dev/null @@ -1,150 +0,0 @@ -import os -import json -import requests - -def get_available_models(base_url): - try: - response = requests.get(f"{base_url}/api/tags") - if response.status_code == 200: - models = response.json()['models'] - return [model['name'] for model in models] - else: - print(f"Error fetching models: {response.status_code}") - return [] - except requests.RequestException as e: - print(f"Error connecting to Ollama: {str(e)}") - return [] - -class OllamaPromptExtractor: - base_url = "http://localhost:11434" - available_models = [] - - @classmethod - def initialize(cls): - cls.load_config() - cls.available_models = get_available_models(cls.base_url) - - @classmethod - def load_config(cls): - config_path = os.path.join(os.path.dirname(__file__), 'config.json') - try: - with open(config_path, 'r') as config_file: - config = json.load(config_file) - cls.base_url = config.get('OLLAMA_API_URL', cls.base_url) - print(f"Loaded Ollama API URL: {cls.base_url}") - except FileNotFoundError: - print(f"Warning: config.json not found at {config_path}. Using default URL: {cls.base_url}") - except json.JSONDecodeError: - print(f"Error: Invalid JSON in config.json at {config_path}. Using default URL: {cls.base_url}") - - @classmethod - def INPUT_TYPES(cls): - return { - "required": { - "model": (cls.available_models,) if cls.available_models else (["No models found"],), - "extra_model": ("STRING", { - "multiline": False, - "default": "none" - }), - "theme": ("STRING", {"multiline": True}), - "max_tokens": ("INT", {"default": 1000, "min": 1, "max": 32768}), - "temperature": ("FLOAT", {"default": 0.7, "min": 0, "max": 2, "step": 0.1}), - "prompt_type": (["sdxl", "kolors"],), - "debug": (["enable", "disable"],), - }, - } - - RETURN_TYPES = ("STRING", "STRING") - RETURN_NAMES = ("positive_prompt", "negative_prompt") - FUNCTION = "generate_sd_prompt" - CATEGORY = "🌙DW/prompt_utils" - - def generate_sd_prompt(self, model, extra_model, theme, max_tokens, temperature, prompt_type, debug): - if extra_model != "none": - model = extra_model - - if prompt_type == "sdxl": - system_message = """你是一位有艺术气息的Stable Diffusion prompt 助理。你的任务是根据给定的主题生成高质量的Stable Diffusion提示词。请严格遵循以下要求： - -1. 输出格式： - - 以"Prompt:"开头的正面提示词 - - 以"Negative Prompt:"开头的负面提示词 - -2. Prompt要求： - - 开头必须包含"(best quality,4k,8k,highres,masterpiece:1.2),ultra-detailed,(realistic,photorealistic,photo-realistic:1.37)" - - 包含画面主体、材质、附加细节、图像质量、艺术风格、色彩色调、灯光等 - - 对于人物主题，必须描述眼睛、鼻子、嘴唇 - - 使用英文半角逗号分隔 - - 不超过40个标签，60个单词 - - 按重要性排序 - -3. Negative Prompt要求： - - 必须包含"nsfw,(low quality,normal quality,worst quality,jpeg artifacts),cropped,monochrome,lowres,low saturation,((watermark)),(white letters)" - - 如果是人物主题，还要包含"skin spots,acnes,skin blemishes,age spot,mutated hands,mutated fingers,deformed,bad anatomy,disfigured,poorly drawn face,extra limb,ugly,poorly drawn hands,missing limb,floating limbs,disconnected limbs,out of focus,long neck,long body,extra fingers,fewer fingers,,(multi nipples),bad hands,signature,username,bad feet,blurry,bad body" - -请直接生成prompt，不要包含任何解释或额外文字。只使用英文，即使主题是中文。""" - else: # prompt_type == "kolors" - system_message = """你是一位熟练的AI艺术生成模型kolors的提示工程师，类似于DALLE-3。你对提示词的复杂性有深入的理解，确保生成的艺术作品符合用户的期望。你的任务是根据给定的主题生成高质量的kolors提示词。请严格遵循以下要求： - -1. 输出格式： - - 直接输出中文提示词，不需要任何标题或前缀 - -2. 提示词要求： - - 使用中文自然语言描述，明确＋精简 - - 先把最难生成的部分写在前面（而非主角），然后写必要的元素和细节，接着是背景，然后是风格、颜色等 - - 加入画面场景细节或人物细节，让图像看起来更充实和合理 - - 确保内容与主题相符，画面整体和谐 - -请直接生成prompt，不要包含任何解释或额外文字。不要包含负向提示词。""" - - prompt = f"根据以下主题生成{'Stable Diffusion' if prompt_type == 'sdxl' else 'kolors'}提示词：{theme}" - - if debug == "enable": - print(f"Attempting to connect to Ollama at: {self.base_url}") - print(f"Using model: {model}") - print(f"Prompt: {prompt}") - - try: - response = requests.post(f"{self.base_url}/api/generate", json={ - "model": model, - "prompt": f"{system_message}\n\nHuman: {prompt}\n\nAssistant:", - "stream": False, - "max_tokens": max_tokens, - "temperature": temperature - }) - response.raise_for_status() - result = response.json() - generated_text = result['response'] - - if debug == "enable": - print(f"Generated text: {generated_text}") - - # 分割正面和负面提示词 - if prompt_type == "sdxl": - if "Prompt:" in generated_text and "Negative Prompt:" in generated_text: - parts = generated_text.split("Negative Prompt:") - positive_prompt = parts[0].replace("Prompt:", "").strip() - negative_prompt = parts[1].strip() - else: - positive_prompt = generated_text - negative_prompt = "" - else: # prompt_type == "kolors" - positive_prompt = generated_text.strip() - negative_prompt = "低质量，坏手，水印" - - return (positive_prompt, negative_prompt) - except requests.RequestException as e: - error_message = f"Error: {str(e)}" - if debug == "enable": - print(error_message) - return (error_message, "") - -OllamaPromptExtractor.initialize() - -NODE_CLASS_MAPPINGS = { - "OllamaPromptExtractor": OllamaPromptExtractor -} - -NODE_DISPLAY_NAME_MAPPINGS = { - "OllamaPromptExtractor": "Ollama Prompt Extractor" -} \ No newline at end of file