mirror of https://github.com/Mai-with-u/MaiBot.git
494 lines
24 KiB
Python
494 lines
24 KiB
Python
import asyncio
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import json
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import urllib.request
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import urllib.error
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import base64
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import traceback
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from typing import List, Tuple, Type, Optional
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# 导入新插件系统
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from src.plugin_system.apis import chat_api
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from src.plugin_system.apis import send_api
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from src.plugin_system.apis import config_api
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from src.plugin_system.base.base_plugin import BasePlugin
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from src.plugin_system.base.base_plugin import register_plugin
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from src.plugin_system.base.base_action import BaseAction
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from src.plugin_system.base.component_types import ComponentInfo, ActionActivationType, ChatMode
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from src.plugin_system.base.config_types import ConfigField
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from src.common.logger import get_logger
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logger = get_logger("pic_action")
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# 当此模块被加载时，尝试生成配置文件（如果它不存在）
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# 注意：在某些插件加载机制下，这可能会在每次机器人启动或插件重载时执行
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# 考虑是否需要更复杂的逻辑来决定何时运行 (例如，仅在首次安装时)
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# ===== Action组件 =====
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class Custom_Pic_Action(BaseAction):
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"""生成一张图片并发送"""
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# 激活设置
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focus_activation_type = ActionActivationType.LLM_JUDGE # Focus模式使用LLM判定，精确理解需求
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normal_activation_type = ActionActivationType.KEYWORD # Normal模式使用关键词激活，快速响应
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mode_enable = ChatMode.ALL
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parallel_action = True
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# 动作基本信息
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action_name = "draw_picture"
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action_description = (
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"可以根据特定的描述，生成并发送一张图片，如果没提供描述，就根据聊天内容生成,你可以立刻画好，不用等待"
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)
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# 关键词设置（用于Normal模式）
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activation_keywords = ["画", "绘制", "生成图片", "画图", "draw", "paint", "图片生成"]
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# LLM判定提示词（用于Focus模式）
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llm_judge_prompt = """
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判定是否需要使用图片生成动作的条件：
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1. 用户明确要求画图、生成图片或创作图像
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2. 用户描述了想要看到的画面或场景
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3. 对话中提到需要视觉化展示某些概念
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4. 用户想要创意图片或艺术作品
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适合使用的情况：
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- "画一张..."、"画个..."、"生成图片"
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- "我想看看...的样子"
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- "能画出...吗"
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- "创作一幅..."
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绝对不要使用的情况：
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1. 纯文字聊天和问答
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2. 只是提到"图片"、"画"等词但不是要求生成
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3. 谈论已存在的图片或照片
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4. 技术讨论中提到绘图概念但无生成需求
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5. 用户明确表示不需要图片时
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"""
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keyword_case_sensitive = False
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# 动作参数定义
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action_parameters = {
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"description": "图片描述，输入你想要生成并发送的图片的描述，将描述翻译为英文单词组合，并用‘,‘分隔，描述中不要出现中文，必填",
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"size": "图片尺寸，例如 '512x512' (可选, 默认从配置或 '1024x1024')",
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}
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# 动作使用场景
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action_require = [
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#"当有人让你画东西时使用，你可以立刻画好，不用等待",
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"当有人要求你生成并发送一张图片时使用，不要频率太高",
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#"当有人让你画一张图时使用",
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"当你想要通过自画像表情包来表达自己情感时使用，不要频率太高",
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"重点：不要连续发，如果你在前10句内已经发送过[图片]或者[表情包]或记录出现过类似描述的[图片]，就不要不选择此动作",
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]
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associated_types = ["text", "image"]
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# 简单的请求缓存，避免短时间内重复请求
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_request_cache = {}
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_cache_max_size = 10
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async def execute(self) -> Tuple[bool, Optional[str]]:
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"""执行图片生成动作"""
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logger.info(f"{self.log_prefix} 执行绘图模型图片生成动作")
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# 配置验证
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http_base_url = self.get_config("api.base_url")
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http_api_key = self.get_config("api.api_key")
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if not (http_base_url and http_api_key):
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error_msg = "抱歉，图片生成功能所需的HTTP配置（如API地址或密钥）不完整，无法提供服务。"
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await self.send_text(error_msg)
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logger.error(f"{self.log_prefix} HTTP调用配置缺失: base_url 或 api_key.")
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return False, "HTTP配置不完整"
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# API密钥验证
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if http_api_key == "YOUR_DOUBAO_API_KEY_HERE":
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error_msg = "图片生成功能尚未配置，请设置正确的API密钥。"
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await self.send_text(error_msg)
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logger.error(f"{self.log_prefix} API密钥未配置")
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return False, "API密钥未配置"
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# 参数验证
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description = self.action_data.get("description")
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if not description or not description.strip():
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logger.warning(f"{self.log_prefix} 图片描述为空，无法生成图片。")
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await self.send_text("你需要告诉我想要画什么样的图片哦~ 比如说'画一只可爱的小猫'")
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return False, "图片描述为空"
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# 清理和验证描述
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description = description.strip()
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if len(description) > 1000: # 限制描述长度
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description = description[:1000]
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logger.info(f"{self.log_prefix} 图片描述过长，已截断")
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# 获取配置
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default_model = self.get_config("generation.default_model", "doubao-seedream-3-0-t2i-250415")
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image_size = self.action_data.get("size", self.get_config("generation.default_size", "1024x1024"))
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# 验证图片尺寸格式
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if not self._validate_image_size(image_size):
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logger.warning(f"{self.log_prefix} 无效的图片尺寸: {image_size}，使用默认值")
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image_size = "1024x1024"
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# 检查缓存
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cache_key = self._get_cache_key(description, default_model, image_size)
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if cache_key in self._request_cache:
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cached_result = self._request_cache[cache_key]
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logger.info(f"{self.log_prefix} 使用缓存的图片结果")
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await self.send_text("我之前画过类似的图片，用之前的结果~")
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# 直接发送缓存的结果
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send_success = await self.send_image(cached_result)
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if send_success:
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await self.send_text("图片已发送！")
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return True, "图片已发送(缓存)"
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else:
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# 缓存失败，清除这个缓存项并继续正常流程
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del self._request_cache[cache_key]
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# 获取其他配置参数
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seed_val = self.get_config("generation.default_seed",42)#种子
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guidance_scale_val=self.get_config("default_guidance_scale",2.5)#强度
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watermark_val = self.get_config("generation.default_watermark", True)#水印
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await self.send_text(
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f"收到！正在为您生成关于 '{description}' 的图片，请稍候...（模型: {default_model}, 尺寸: {image_size}）"
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)
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try:
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success, result = await asyncio.to_thread(
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self._make_http_image_request,
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prompt=description,
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model=default_model,
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size=image_size,
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seed=seed_val,
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guidance_scale=guidance_scale_val,
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watermark=watermark_val,
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)
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except Exception as e:
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logger.error(f"{self.log_prefix} (HTTP) 异步请求执行失败: {e!r}", exc_info=True)
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traceback.print_exc()
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success = False
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result = f"图片生成服务遇到意外问题: {str(e)[:100]}"
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if success:
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# 如果返回的是Base64数据（以"iVBORw"等开头），直接使用
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if result.startswith(("iVBORw", "/9j/", "UklGR", "R0lGOD")): # 常见图片格式的Base64前缀
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#logger.info(f"{self.log_prefix} 获取到Base64图片数据，直接发送")
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#logger.info(f"{self.log_prefix} (HTTP) 获取到Base64图片数据，长度: {len(self.log_prefix)}")
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send_success = await self.send_image(result)
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if send_success:
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await self.send_text("图片表情已发送！")
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return True, "图片表情已发送(Base64)"
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else:
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await self.send_text("图片已处理为Base64，但作为表情发送失败了")#("图片已处理为Base64，但作为表情发送失败了。")
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return False, "图片表情发送失败 (Base64)"
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else: # 否则认为是URL
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image_url = result
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# print(f"image_url: {image_url}")
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# print(f"result: {result}")
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logger.info(f"{self.log_prefix} 图片URL获取成功: {image_url[:70]}... 下载并编码.")
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try:
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encode_success, encode_result = await asyncio.to_thread(self._download_and_encode_base64, image_url)
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except Exception as e:
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logger.error(f"{self.log_prefix} (B64) 异步下载/编码失败: {e!r}", exc_info=True)
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traceback.print_exc()
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encode_success = False
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encode_result = f"图片下载或编码时发生内部错误: {str(e)[:100]}"
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if encode_success:
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base64_image_string = encode_result
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send_success = await self.send_image(base64_image_string)
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if send_success:
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# 缓存成功的结果
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self._request_cache[cache_key] = base64_image_string
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self._cleanup_cache()
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await self.send_text("图片已发送！")
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return True, "图片已成功生成并发送"
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else:
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print(f"send_success: {send_success}")
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await self.send_text("图片已处理为Base64，但发送失败了。")
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return False, "图片发送失败 (Base64)"
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else:
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await self.send_text(f"获取到图片URL，但在处理图片时失败了：{encode_result}")
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return False, f"图片处理失败(Base64): {encode_result}"
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else:
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error_message = result
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await self.send_text(f"哎呀，生成图片时遇到问题：{error_message}")
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return False, f"图片生成失败: {error_message}"
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def _download_and_encode_base64(self, image_url: str) -> Tuple[bool, str]:
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"""下载图片并将其编码为Base64字符串"""
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logger.info(f"{self.log_prefix} (B64) 下载并编码图片: {image_url[:70]}...")
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try:
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with urllib.request.urlopen(image_url, timeout=60) as response:
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if response.status == 200:
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image_bytes = response.read()
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base64_encoded_image = base64.b64encode(image_bytes).decode("utf-8")
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logger.info(f"{self.log_prefix} (B64) 图片下载编码完成. Base64长度: {len(base64_encoded_image)}")
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return True, base64_encoded_image
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else:
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error_msg = f"下载图片失败 (状态: {response.status})"
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logger.error(f"{self.log_prefix} (B64) {error_msg} URL: {image_url}")
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return False, error_msg
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except Exception as e:
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logger.error(f"{self.log_prefix} (B64) 下载或编码时错误: {e!r}", exc_info=True)
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traceback.print_exc()
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return False, f"下载或编码图片时发生错误: {str(e)[:100]}"
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@classmethod
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def _get_cache_key(cls, description: str, model: str, size: str) -> str:
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"""生成缓存键"""
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return f"{description[:100]}|{model}|{size}"
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@classmethod
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def _cleanup_cache(cls):
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"""清理缓存，保持大小在限制内"""
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if len(cls._request_cache) > cls._cache_max_size:
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keys_to_remove = list(cls._request_cache.keys())[: -cls._cache_max_size // 2]
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for key in keys_to_remove:
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del cls._request_cache[key]
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def _validate_image_size(self, image_size: str) -> bool:
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"""验证图片尺寸格式"""
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try:
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width, height = map(int, image_size.split("x"))
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return 100 <= width <= 10000 and 100 <= height <= 10000
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except (ValueError, TypeError):
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return False
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def _make_http_image_request(
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self, prompt: str, model: str, size: str, seed: int | None, guidance_scale: float, watermark: bool
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) -> Tuple[bool, str]:
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"""发送HTTP请求生成图片"""
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base_url = self.get_config("api.base_url")
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generate_api_key = self.get_config("api.api_key")
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endpoint = f"{base_url.rstrip('/')}/images/generations"
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# 获取配置参数 - 使用字符串键名
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custom_prompt_add = self.get_config("generation.custom_prompt_add", "")#附加正面提示词参数
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negative_prompt_add = self.get_config("generation.negative_prompt_add", "")#附加负面提示词参数
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prompt_add= prompt + ", " + custom_prompt_add
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negative_prompt = negative_prompt_add
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payload_dict = {
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"model": model,
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"prompt": prompt_add, # 使用附加的正面提示词
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"negative_prompt":negative_prompt,
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#"response_format": "b64_json",# gpt-image-1 无法使用 url 返回为 “b64_json"，豆包默认返回为 "url"
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"size": size,
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"guidance_scale": guidance_scale,
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"watermark": watermark,
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"seed": seed, # seed is now always an int from process()
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"api-key": generate_api_key,
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}
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# if seed is not None: # No longer needed, seed is always an int
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# payload_dict["seed"] = seed
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data = json.dumps(payload_dict).encode("utf-8")
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headers = {
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"Content-Type": "application/json",
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"Accept": "application/json",
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"Authorization": f"{generate_api_key}",
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}# gpt 或其他模型密钥要删除‘Bearer ’前缀
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logger.info(f"{self.log_prefix} (HTTP) 发起图片请求: {model}, custom_prompt_add:{custom_prompt_add[:30]}...,Prompt: {prompt_add[:30]}...,NegativePrompt: {negative_prompt[:30]}... To: {endpoint}")
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logger.debug(
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f"{self.log_prefix} (HTTP) Request Headers: {{...Authorization: Bearer {generate_api_key[:10]}...}}"
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)
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logger.debug(
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f"{self.log_prefix} (HTTP) Request Body (api-key omitted): {json.dumps({k: v for k, v in payload_dict.items() if k != 'api-key'})}"
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)
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req = urllib.request.Request(endpoint, data=data, headers=headers, method="POST")
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try:
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with urllib.request.urlopen(req, timeout=60) as response:
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response_status = response.status
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response_body_bytes = response.read()
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response_body_str = response_body_bytes.decode("utf-8")
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logger.info(f"{self.log_prefix} (HTTP) 响应: {response_status}. Preview: {response_body_str[:150]}...")
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if 200 <= response_status < 300:
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response_data = json.loads(response_body_str)
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b64_data = None
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image_url = None #清理缓存
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# 优先检查Base64数据
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if (
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isinstance(response_data.get("data"), list)
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and response_data["data"]
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and isinstance(response_data["data"][0], dict)
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and "b64_json" in response_data["data"][0]
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):
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b64_data = response_data["data"][0]["b64_json"]
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logger.info(f"{self.log_prefix} (HTTP) 获取到Base64图片数据，长度: {len(b64_data)}")
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return True, b64_data # 直接返回Base64字符串
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elif (
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isinstance(response_data.get("data"), list)
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and response_data["data"]
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and isinstance(response_data["data"][0], dict)
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):
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image_url = response_data["data"][0].get("url")
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elif(#魔搭社区返回的 json
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isinstance(response_data.get("images"), list)
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and response_data["images"]
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and isinstance(response_data["images"][0], dict)
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):
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image_url = response_data["images"][0].get("url")
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elif response_data.get("url"):
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image_url = response_data.get("url")
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if image_url:
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logger.info(f"{self.log_prefix} (HTTP) 图片生成成功，URL: {image_url[:70]}...")
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return True, image_url
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else:
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logger.error(
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f"{self.log_prefix} (HTTP) API成功但无图片URL. 响应预览: {response_body_str[:300]}..."
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)
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return False, "图片生成API响应成功但未找到图片URL"
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else:
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logger.error(
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f"{self.log_prefix} (HTTP) API请求失败. 状态: {response.status}. 正文: {response_body_str[:300]}..."
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)
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return False, f"图片API请求失败(状态码 {response.status})"
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except Exception as e:
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logger.error(f"{self.log_prefix} (HTTP) 图片生成时意外错误: {e!r}", exc_info=True)
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traceback.print_exc()
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return False, f"图片生成HTTP请求时发生意外错误: {str(e)[:100]}"
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# ===== 插件注册 =====
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@register_plugin
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class CustomPicPlugin(BasePlugin):
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"""根据描述使用不同的 绘图 API生成图片的动作处理类"""
|
||
# 插件基本信息
|
||
plugin_name = "custom_pic_plugin"# 内部标识符
|
||
plugin_version = "1.0.2"
|
||
plugin_author = "Ptrel"
|
||
enable_plugin = True
|
||
config_file_name = "config.toml"
|
||
|
||
|
||
|
||
# 步骤1: 定义配置节的描述
|
||
config_section_descriptions = {
|
||
"plugin": "插件启用配置",
|
||
"api": "API的基础url",
|
||
"generation": "图片生成参数配置，控制生成图片的各种参数",
|
||
"cache": "结果缓存配置",
|
||
"components": "组件启用配置",
|
||
}
|
||
|
||
# 步骤2: 使用ConfigField定义详细的配置Schema
|
||
config_schema = {
|
||
"plugin": {
|
||
"name": ConfigField(type=str, default="custom_pic_plugin", description="自定义提示词绘图", required=True),
|
||
"version": ConfigField(type=str, default="1.1.2", description="插件版本号"),
|
||
"enabled": ConfigField(type=bool, default=False, description="是否启用插件")
|
||
},
|
||
"api": {
|
||
"base_url": ConfigField(
|
||
type=str,
|
||
default="https://api-inference.modelscope.cn/v1",
|
||
description="API的基础url",
|
||
example="https://api.example.com/v1",
|
||
choices=[
|
||
"https://api-inference.modelscope.cn/v1\"#魔搭可自选 lora，对应模型网址：https://modelscope.cn/models?page=1&tabKey=task&tasks=hotTask:text-to-image-synthesis&type=tasks",
|
||
"\n#https://ark.cn-beijing.volces.com/api/v3\"#豆包火山方舟 API,对应网址：https://console.volcengine.com/auth/login?redirectURI=%2Fmessage%2Finnermsg",
|
||
"\n#https://api.chatanywhere.tech/v1\"#chatany API，对应文档网址：https://chatanywhere.apifox.cn/",]
|
||
),
|
||
"api_key": ConfigField(
|
||
type=str,
|
||
default="Bearer xxxxxxxxxxxxxxxxxxxxxx",
|
||
description="API 的 api 密钥，需要添加‘Bearer ’前缀，chatany 不需要前缀，根据不同 api 文档进行选择,如 chatanywhere 的 key 不需要 Berarer，即直接输入密钥‘xxxxxxxxxxxxxxxxxxxxxxxx’",
|
||
required=True
|
||
),
|
||
},
|
||
"generation": {
|
||
"default_model": ConfigField(
|
||
type=str,
|
||
default="cancel13/liaocao\"#潦草 lora 图片生成模型（魔搭）",
|
||
description="模型选择，可自定义，以下为示例",
|
||
choices=[
|
||
"MusePublic/14_ckpt_SD_XL\"#万象熔炉 | Anything XL，社区模型(魔搭)","\n#cancel13/liaocao\"#潦草 lora 图片生成模型，社区模型（魔搭）","\n#doubao-seedream-3-0-t2i-250415\"#豆包图片生成模型约 0.3￥ 一张图（火山）",
|
||
"\n#gpt-image-1\"#GPT 生图，约 1.3￥ 一张图（chatany）"
|
||
]
|
||
),
|
||
"default_size": ConfigField(
|
||
type=str,
|
||
default="1024x1024",
|
||
description="默认图片尺寸",
|
||
example="1024x1024",
|
||
choices=["1024x1024", "1024x1280", "1280x1024", "1024x1536", "1536x1024"],
|
||
),
|
||
"default_watermark": ConfigField(
|
||
type=bool,
|
||
default=True,
|
||
description="是否默认添加水印"),
|
||
"default_guidance_scale": ConfigField(
|
||
type=float,
|
||
default=2.5,
|
||
description="模型指导强度，影响图片与提示的关联性", example="2.0"
|
||
),
|
||
"default_seed": ConfigField(
|
||
type=int,
|
||
default=42,
|
||
description="随机种子，用于复现图片"),
|
||
"custom_prompt_add": ConfigField(
|
||
type=str,
|
||
default="Nordic picture book art style, minimalist flat design, soft rounded lines, high saturation color blocks collision, dominant forest green and warm orange palette, low contrast lighting, hand-drawn pencil texture, healing fairy-tale atmosphere, geometric natural forms, ample white space composition, warm and clean aesthetic,liaocao\"#北欧绘本艺术风格，简约扁平设计，柔和圆润线条，高饱和度色块碰撞，森林绿与暖橙主色调，低对比度光影，手绘铅笔质感，治愈系童话氛围，几何化自然形态，留白构图，温暖干净画面",
|
||
description="正面附加提示词（尽量使用英文，且用词语和逗号的形式，豆包可以使用中文句子提示词）"
|
||
),
|
||
"negative_prompt_add": ConfigField(
|
||
type=str,
|
||
default="Pornography,nudity,lowres, bad anatomy, bad hands, text, error, missing fingers, extra digit, fewer digits, cropped, worst quality, low quality, normal quality, jpeg artifacts, signature, watermark, username, blurry\"#色情，裸体，低分辨率，糟糕的解剖结构，糟糕的手，文字，错误，缺失的手指，多余的数字，更少的数字，裁剪，最差的质量，低质量，正常质量，jpeg文物，签名，水印，用户名，模糊色情，裸体，低分辨率，糟糕的解剖结构，糟糕的手，文字，错误，缺失的手指，多余的数字，更少的数字，裁剪，最差的质量，低质量，正常质量，jpeg文物，签名，水印，用户名，模糊",
|
||
description="负面附加提示词，保持默认或使用豆包时可留空"
|
||
),
|
||
},
|
||
"cache": {
|
||
"enabled": ConfigField(type=bool, default=True, description="是否启用请求缓存"),
|
||
"max_size": ConfigField(type=int, default=10, description="最大缓存数量"),
|
||
},
|
||
"components": {
|
||
"enable_image_generation": ConfigField(type=bool, default=True, description="是否启用图片生成Action")
|
||
},
|
||
"logging": {
|
||
"level": ConfigField(
|
||
type=str,
|
||
default="INFO",
|
||
description="日志记录级别",
|
||
choices=["DEBUG", "INFO", "WARNING", "ERROR"]
|
||
),
|
||
"prefix": ConfigField(type=str, default="[custom_pic_Plugin]", description="日志记录前缀", example="[custom_pic_Plugin]")
|
||
}
|
||
}
|
||
|
||
def get_plugin_components(self) -> List[Tuple[ComponentInfo, Type]]:
|
||
"""返回插件包含的组件列表"""
|
||
|
||
# 从配置获取组件启用状态
|
||
enable_image_generation = self.get_config("components.enable_image_generation", True)
|
||
|
||
components = []
|
||
|
||
if enable_image_generation:
|
||
# 添加我们的Action
|
||
components.append((Custom_Pic_Action.get_action_info(), Custom_Pic_Action))
|
||
|
||
return components
|
||
|
||
|