import os import base64 import json from typing import Tuple from concurrent.futures import ThreadPoolExecutor, as_completed import requests class Batch_API_caption: @classmethod def INPUT_TYPES(cls): return { "required": { "input_dir": ("STRING", {"default": ""}), "output_dir": ("STRING", {"default": ""}), "api_type": (["硅基流动", "贞贞工坊", "OpenRouter", "其他"], {"default": "硅基流动"}), "api_url": ("STRING", {"default": ""}), "API_Key": ("STRING", {"default": ""}), "model_name": ("STRING", {"default": "Qwen/Qwen3-VL-32B-Instruct"}), "prompt": ("STRING", {"default": "你是一位专业的AI图像生成提示词工程师。请详细描述这张图像的主体、前景、中景、背景、构图、视觉引导、色调、光影氛围等细节并创作出具有深度、氛围和艺术感的图像提示词。要求:中文提示词,不要出现对图像水印的描述,不要出现无关的文字和符号,不需要总结,限制在800字以内", "multiline": True, "rows": 4}), "output_language": (["中文", "英文"], {"default": "中文"}), "temperature": ("FLOAT", {"default": 0.5, "min": 0.0, "max": 2.0, "step": 0.01}), "concurrency": ("INT", {"default": 6, "min": 1, "max": 32}), } } RETURN_TYPES = ("STRING",) RETURN_NAMES = ("log",) FUNCTION = "generate" CATEGORY = "DaNodes/API" @staticmethod def _extract_text_from_content(content): if isinstance(content, str): return content if isinstance(content, dict): return content.get("text") or content.get("content") or str(content) if isinstance(content, list): parts = [] for block in content: if not isinstance(block, dict): parts.append(str(block)) continue btype = block.get("type", "") if btype in ("text", "paragraph"): parts.append(block.get("text", "")) elif btype == "image_url": continue else: parts.append(block.get("text") or block.get("content") or "") return " ".join(p for p in parts if p).strip() return str(content) @staticmethod def _build_payload(model_name: str, prompt_full: str, img_data_uri: str, temperature: float): messages = [ { "role": "user", "content": [ {"type": "text", "text": prompt_full}, {"type": "image_url", "image_url": {"url": img_data_uri}}, ], } ] return { "model": model_name, "stream": False, "messages": messages, "max_tokens": 400, "temperature": float(temperature), } @staticmethod def _post(api_url: str, api_key: str, payload: dict, timeout_sec: float = 90.0, retries: int = 0): headers = { "Authorization": f"Bearer {api_key}", "Content-Type": "application/json", "Accept": "application/json", "User-Agent": "ComfyUI-DaNodes/1.0", } attempt = 0 last_err = None result = None while attempt <= max(0, int(retries)): try: r = requests.post(api_url, json=payload, headers=headers, timeout=float(timeout_sec)) except Exception as e: last_err = f"请求失败: {e}" attempt += 1 continue if not r.ok: try: body = r.json() body = json.dumps(body, ensure_ascii=False) except Exception: body = r.text last_err = f"HTTP {r.status_code}: {body}" attempt += 1 continue try: result = r.json() except Exception as e: last_err = f"解析 JSON 失败: {e}; body: {r.text}" attempt += 1 continue # 成功 break if result is None: return False, (last_err or "请求失败") # 解析文本 caption = "" if isinstance(result, dict): choices = result.get("choices") or [] if choices: first = choices[0] if isinstance(first, dict): msg = first.get("message") or first.get("delta") or None if isinstance(msg, dict) and "content" in msg: caption = Batch_API_caption._extract_text_from_content(msg.get("content")) else: if "text" in first and isinstance(first.get("text"), str): caption = first.get("text") else: caption = Batch_API_caption._extract_text_from_content(first) else: caption = str(first) else: caption = result.get("caption") or result.get("text") or "" else: caption = str(result) caption = caption.strip() if caption == "": try: pretty = json.dumps(result, ensure_ascii=False) except Exception: pretty = str(result) return False, f"无法解析文本,返回 JSON: {pretty}" return True, caption def generate(self, input_dir: str, output_dir: str, api_type: str, api_url: str, API_Key: str, model_name: str, prompt: str, output_language: str, temperature: float = 0.5, concurrency: int = 4) -> Tuple[str]: # 目录校验 if not input_dir: return ("输入地址未填写",) if not os.path.isdir(input_dir): return (f"输入地址不存在: {input_dir}",) if not output_dir: output_dir = input_dir os.makedirs(output_dir, exist_ok=True) # 选择 URL provider_map = { "OpenRouter": "https://openrouter.ai/api/v1/chat/completions", "硅基流动": "https://api.siliconflow.cn/v1/chat/completions", "贞贞工坊": "https://api.bltcy.ai/v1/chat/completions", } if api_type == "其他": api_url = api_url or "" else: api_url = provider_map.get(api_type, api_url) if not api_url: return ("请求地址为空,请填写或选择有效的 API 类型",) # 列出图片 exts = (".jpg", ".jpeg", ".png", ".bmp", ".webp") files = [f for f in os.listdir(input_dir) if f.lower().endswith(exts)] if not files: return ("输入地址中没有图片文件",) log = {"total": len(files), "succeeded": 0, "failed": 0} first_error = None # type: ignore[assignment] def process_one(name: str): in_path = os.path.join(input_dir, name) out_txt = os.path.join(output_dir, os.path.splitext(name)[0] + ".txt") try: # 直接嵌入原始文件字节,不做缩放与重新编码 with open(in_path, 'rb') as fbin: raw = fbin.read() img_b64 = base64.b64encode(raw).decode() ext = os.path.splitext(in_path)[1].lower() mime = "image/jpeg" if ext in (".jpg", ".jpeg") else ( "image/png" if ext == ".png" else ( "image/webp" if ext == ".webp" else ( "image/bmp" if ext == ".bmp" else "application/octet-stream")) ) img_data_uri = f"data:{mime};base64,{img_b64}" if output_language == "中文": prompt_full = f"{prompt} 请用中文返回描述" else: prompt_full = f"{prompt} Please return the description in English." payload = self._build_payload(model_name, prompt_full, img_data_uri, temperature) ok, resp = self._post(api_url, API_Key, payload, timeout_sec=90.0, retries=1) if ok: with open(out_txt, "w", encoding="utf-8") as f: f.write(resp) return True, name, None else: # 失败时不创建/不写入任何 txt 文件 return False, name, resp except Exception as e: return False, name, str(e) workers = max(1, int(concurrency)) files_sorted = list(files) try: files_sorted.sort() except Exception: pass with ThreadPoolExecutor(max_workers=workers) as ex: futures = {ex.submit(process_one, n): n for n in files_sorted} for fut in as_completed(futures): ok, name, err = fut.result() if ok: log["succeeded"] += 1 else: log["failed"] += 1 if first_error is None: first_error = (err or "unknown") if first_error is not None: log["error"] = first_error return (json.dumps(log, ensure_ascii=False),) NODE_CLASS_MAPPINGS = { "Batch_API_caption": Batch_API_caption, } NODE_DISPLAY_NAME_MAPPINGS = { "Batch_API_caption": "Batch_API_caption☀", }