447 lines
20 KiB
Python
447 lines
20 KiB
Python
"""
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NanoImage AI绘图插件
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支持 OpenAI 格式的绘图 API，用户可自定义 URL、模型 ID、密钥
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支持命令触发和 LLM 工具调用
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"""
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import asyncio
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import tomllib
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import httpx
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import uuid
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import base64
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import re
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from pathlib import Path
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from datetime import datetime
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from typing import List, Optional
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from loguru import logger
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from utils.plugin_base import PluginBase
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from utils.decorators import on_text_message
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from WechatHook import WechatHookClient
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class NanoImage(PluginBase):
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"""NanoImage AI绘图插件"""
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description = "NanoImage AI绘图插件 - 支持 OpenAI 格式的绘图 API"
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author = "ShiHao"
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version = "1.0.0"
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def __init__(self):
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super().__init__()
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self.config = None
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self.images_dir = None
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async def async_init(self):
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"""异步初始化"""
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config_path = Path(__file__).parent / "config.toml"
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with open(config_path, "rb") as f:
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self.config = tomllib.load(f)
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# 创建图片目录
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self.images_dir = Path(__file__).parent / "images"
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self.images_dir.mkdir(exist_ok=True)
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logger.success(f"NanoImage AI插件初始化完成，模型: {self.config['api']['model']}")
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async def generate_image(self, prompt: str) -> List[str]:
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"""
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生成图像
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Args:
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prompt: 提示词
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Returns:
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图片本地路径列表
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"""
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api_config = self.config["api"]
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gen_config = self.config["generation"]
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max_retry = gen_config["max_retry_attempts"]
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for attempt in range(max_retry):
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if attempt > 0:
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await asyncio.sleep(min(2 ** attempt, 10))
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try:
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url = f"{api_config['base_url'].rstrip('/')}/v1/chat/completions"
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headers = {
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"Content-Type": "application/json",
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"Authorization": f"Bearer {api_config['api_key']}"
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}
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payload = {
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"model": api_config["model"],
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"messages": [{"role": "user", "content": prompt}],
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"stream": True
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}
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logger.info(f"NanoImage请求: {api_config['model']}, 提示词长度: {len(prompt)} 字符")
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logger.debug(f"完整提示词: {prompt}")
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# 设置超时时间
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max_timeout = min(api_config["timeout"], 600)
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timeout = httpx.Timeout(
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connect=10.0,
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read=max_timeout,
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write=10.0,
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pool=10.0
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)
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# 获取代理配置
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proxy = await self._get_proxy()
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async with httpx.AsyncClient(timeout=timeout, proxy=proxy) as client:
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async with client.stream("POST", url, json=payload, headers=headers) as response:
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logger.debug(f"收到响应状态码: {response.status_code}")
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if response.status_code == 200:
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content_type = (response.headers.get("content-type") or "").lower()
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is_sse = "text/event-stream" in content_type or "event-stream" in content_type
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# 处理流式响应（SSE）
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image_url = None
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image_base64 = None
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full_content = ""
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if is_sse:
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async for line in response.aiter_lines():
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if not line:
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continue
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if line.startswith("data:"):
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data_str = line[5:].lstrip()
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if data_str == "[DONE]":
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break
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try:
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import json
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data = json.loads(data_str)
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if "choices" in data and data["choices"]:
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delta = data["choices"][0].get("delta", {})
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# 方式1: 从 delta.images 中提取（新格式）
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images = delta.get("images", [])
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if images and len(images) > 0:
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img_data = images[0].get("image_url", {}).get("url", "")
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if img_data:
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if img_data.startswith("data:image"):
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# base64 格式
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image_base64 = img_data
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logger.info("从 delta.images 提取到 base64 图片")
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elif img_data.startswith("http"):
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image_url = img_data
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logger.info(f"从 delta.images 提取到图片URL: {image_url}")
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# 方式2: 从 content 中提取（旧格式）
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content = delta.get("content", "")
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if content:
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full_content += content
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if "http" in content:
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urls = re.findall(r'https?://[^\s\)\]"\']+', content)
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if urls:
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image_url = urls[0].rstrip("'\"")
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logger.info(f"从 content 提取到图片URL: {image_url}")
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except Exception as e:
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logger.warning(f"解析响应数据失败: {e}")
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continue
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else:
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# 非流式（application/json）：某些网关即使传了 stream=true 也会返回完整 JSON
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raw = await response.aread()
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try:
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import json
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data = json.loads(raw.decode("utf-8", errors="ignore"))
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except Exception as e:
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logger.error(f"解析 JSON 响应失败: {type(e).__name__}: {e}")
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data = None
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if isinstance(data, dict):
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# 1) 标准 images endpoint 兼容：{"data":[{"url":...}|{"b64_json":...}]}
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items = data.get("data")
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if isinstance(items, list) and items:
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first = items[0] if isinstance(items[0], dict) else {}
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if isinstance(first, dict):
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b64_json = first.get("b64_json")
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if b64_json:
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image_base64 = b64_json
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logger.info("从 data[0].b64_json 提取到 base64 图片")
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else:
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u = first.get("url") or ""
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if isinstance(u, str) and u:
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image_url = u
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logger.info(f"从 data[0].url 提取到图片URL: {image_url}")
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# 2) chat.completion 兼容：choices[0].message.images[0].image_url.url
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if not image_url and not image_base64:
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try:
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choices = data.get("choices") or []
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if choices:
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msg = (choices[0].get("message") or {}) if isinstance(choices[0], dict) else {}
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images = msg.get("images") or []
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if isinstance(images, list) and images:
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img0 = images[0] if isinstance(images[0], dict) else {}
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if isinstance(img0, dict):
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img_data = (
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(img0.get("image_url") or {}).get("url")
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if isinstance(img0.get("image_url"), dict)
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else img0.get("url")
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)
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if isinstance(img_data, str) and img_data:
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if img_data.startswith("data:image"):
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image_base64 = img_data
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logger.info("从 message.images 提取到 base64 图片")
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elif img_data.startswith("http"):
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image_url = img_data
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logger.info(f"从 message.images 提取到图片URL: {image_url}")
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except Exception:
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pass
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# 如果没有从流中提取到URL，尝试从完整内容中提取
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if not image_url and not image_base64 and full_content:
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urls = re.findall(r'https?://[^\s\)\]"\']+', full_content)
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if urls:
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image_url = urls[0].rstrip("'\"")
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logger.info(f"从完整内容提取到图片URL: {image_url}")
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if not image_url and not image_base64:
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# 避免把 base64 打到日志里：只输出裁剪后的概要
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if full_content:
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logger.error(f"未能提取到图片，完整响应(截断): {full_content[:500]}")
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else:
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# 非SSE时 full_content 可能为空，补充输出 content-type 便于定位
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logger.error(f"未能提取到图片（content-type={content_type or 'unknown'}）")
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# 处理 base64 图片
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if image_base64:
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image_path = await self._save_base64_image(image_base64)
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if image_path:
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logger.success("成功生成图像 (base64)")
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return [image_path]
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else:
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logger.warning(f"base64图片保存失败，将重试 ({attempt + 1}/{max_retry})")
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continue
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# 处理 URL 图片
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if image_url:
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image_path = await self._download_image(image_url)
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if image_path:
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logger.success("成功生成图像")
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return [image_path]
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else:
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logger.warning(f"图片下载失败，将重试 ({attempt + 1}/{max_retry})")
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continue
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elif response.status_code == 401:
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logger.error("API Key 认证失败")
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return []
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else:
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error_text = await response.aread()
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logger.error(f"API请求失败: {response.status_code}, {error_text[:200]}")
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continue
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except asyncio.TimeoutError:
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logger.warning(f"请求超时，重试中... ({attempt + 1}/{max_retry})")
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continue
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except httpx.ReadTimeout:
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logger.warning(f"读取超时，重试中... ({attempt + 1}/{max_retry})")
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continue
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except Exception as e:
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import traceback
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logger.error(f"请求异常: {type(e).__name__}: {str(e)}")
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logger.error(f"异常详情:\n{traceback.format_exc()}")
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continue
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logger.error("图像生成失败")
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return []
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async def _get_proxy(self) -> Optional[str]:
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"""获取 AIChat 插件的代理配置"""
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try:
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aichat_config_path = Path(__file__).parent.parent / "AIChat" / "config.toml"
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if aichat_config_path.exists():
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with open(aichat_config_path, "rb") as f:
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aichat_config = tomllib.load(f)
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proxy_config = aichat_config.get("proxy", {})
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if proxy_config.get("enabled", False):
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proxy_type = proxy_config.get("type", "socks5")
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proxy_host = proxy_config.get("host", "127.0.0.1")
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proxy_port = proxy_config.get("port", 7890)
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proxy = f"{proxy_type}://{proxy_host}:{proxy_port}"
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logger.debug(f"使用代理: {proxy}")
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return proxy
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except Exception as e:
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logger.warning(f"读取代理配置失败: {e}")
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return None
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async def _save_base64_image(self, base64_data: str) -> Optional[str]:
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"""保存 base64 图片到本地"""
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try:
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# 去除 data:image/xxx;base64, 前缀
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if base64_data.startswith("data:image"):
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# 提取格式和数据
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header, data = base64_data.split(",", 1)
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# 从 header 中提取格式，如 data:image/jpeg;base64
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if "jpeg" in header or "jpg" in header:
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ext = "jpg"
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elif "png" in header:
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ext = "png"
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elif "gif" in header:
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ext = "gif"
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elif "webp" in header:
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ext = "webp"
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else:
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ext = "jpg"
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else:
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data = base64_data
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ext = "jpg"
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# 解码 base64
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image_bytes = base64.b64decode(data)
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# 生成文件名
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ts = datetime.now().strftime("%Y%m%d_%H%M%S")
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uid = uuid.uuid4().hex[:8]
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file_path = self.images_dir / f"nano_{ts}_{uid}.{ext}"
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# 保存文件
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with open(file_path, "wb") as f:
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f.write(image_bytes)
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logger.info(f"base64图片保存成功: {file_path}")
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return str(file_path)
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except Exception as e:
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logger.error(f"保存base64图片失败: {e}")
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import traceback
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logger.error(traceback.format_exc())
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return None
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async def _download_image(self, url: str) -> Optional[str]:
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"""下载图片到本地"""
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try:
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timeout = httpx.Timeout(connect=10.0, read=30.0, write=10.0, pool=10.0)
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proxy = await self._get_proxy()
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async with httpx.AsyncClient(timeout=timeout, proxy=proxy) as client:
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response = await client.get(url)
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response.raise_for_status()
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# 生成文件名
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ts = datetime.now().strftime("%Y%m%d_%H%M%S")
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uid = uuid.uuid4().hex[:8]
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file_path = self.images_dir / f"nano_{ts}_{uid}.jpg"
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# 保存文件
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with open(file_path, "wb") as f:
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f.write(response.content)
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logger.info(f"图片下载成功: {file_path}")
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return str(file_path)
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except Exception as e:
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logger.error(f"下载图片失败: {e}")
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return None
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@on_text_message(priority=70)
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async def handle_message(self, bot: WechatHookClient, message: dict):
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"""处理文本消息"""
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if not self.config["behavior"]["enable_command"]:
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return True
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content = message.get("Content", "").strip()
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from_wxid = message.get("FromWxid", "")
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is_group = message.get("IsGroup", False)
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# 检查群聊/私聊开关
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if is_group and not self.config["behavior"]["enable_group"]:
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return True
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if not is_group and not self.config["behavior"]["enable_private"]:
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return True
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# 检查是否是绘图命令
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keywords = self.config["behavior"]["command_keywords"]
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matched_keyword = None
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for keyword in keywords:
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if content.startswith(keyword + " ") or content == keyword:
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matched_keyword = keyword
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break
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if not matched_keyword:
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return True
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# 提取提示词
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prompt = content[len(matched_keyword):].strip()
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if not prompt:
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await bot.send_text(from_wxid, f"❌ 请提供绘图提示词\n用法: {matched_keyword} <提示词>")
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return False
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logger.info(f"收到绘图请求: {prompt[:50]}...")
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try:
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# 生成图像
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image_paths = await self.generate_image(prompt)
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if image_paths:
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# 直接发送图片
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await bot.send_image(from_wxid, image_paths[0])
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logger.success("绘图成功，已发送图片")
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else:
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await bot.send_text(from_wxid, "❌ 图像生成失败，请稍后重试")
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except Exception as e:
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logger.error(f"绘图处理失败: {e}")
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await bot.send_text(from_wxid, f"❌ 处理失败: {str(e)}")
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return False
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def get_llm_tools(self) -> List[dict]:
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"""返回 LLM 工具定义"""
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if not self.config["llm_tool"]["enabled"]:
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return []
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return [{
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"type": "function",
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"function": {
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"name": self.config["llm_tool"]["tool_name"],
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"description": self.config["llm_tool"]["tool_description"],
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"parameters": {
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"type": "object",
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"properties": {
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"prompt": {
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"type": "string",
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"description": "图像生成提示词，描述想要生成的图像内容"
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}
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},
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"required": ["prompt"]
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}
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}
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}]
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async def execute_llm_tool(self, tool_name: str, arguments: dict, bot: WechatHookClient, from_wxid: str) -> dict:
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"""执行 LLM 工具调用"""
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expected_tool_name = self.config["llm_tool"]["tool_name"]
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if tool_name != expected_tool_name:
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return None
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try:
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prompt = arguments.get("prompt")
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if not prompt:
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return {"success": False, "message": "缺少提示词参数"}
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logger.info(f"LLM工具调用绘图: {prompt[:50]}...")
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# 生成图像
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image_paths = await self.generate_image(prompt)
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if image_paths:
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# 直接发送图片
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await bot.send_image(from_wxid, image_paths[0])
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return {
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"success": True,
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"message": "已生成并发送图像",
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"images": [image_paths[0]]
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}
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else:
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return {"success": False, "message": "图像生成失败"}
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except Exception as e:
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logger.error(f"LLM工具执行失败: {e}")
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return {"success": False, "message": f"执行失败: {str(e)}"}
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