.vscode/launch.json

@@ -9,11 +9,9 @@
       "console": "integratedTerminal",
       "justMyCode": true,
       "args": [
-        "--prompt=马云在直播间卖红薯",
+        "{\"prompt\":\"一只站在雨夜街头的白猫\",\"model\":\"jimeng-5.0\",\"negative_prompt\":\"模糊, 低清\",\"ratio\":\"16:9\",\"resolution\":\"2k\"}"
-        "--model=gpt-image-2"
       ],
       "env": {
-        "ROBOT_WECHAT_CLIENT_PORT": "9001",
         "ROBOT_FROM_WX_ID": "57004904192@chatroom",
         "ROBOT_CODE": "houhouipad",
         "MYSQL_HOST": "127.0.0.1",

README.md

@@ -55,8 +55,6 @@
 
 **发送图片的时候也可以调用 Agent 接口**
 
-1. 发送远程图片地址
-
 ```
 [POST] http://127.0.0.1:{ROBOT_WECHAT_CLIENT_PORT}/api/v1//robot/message/send/image/url
 
@@ -69,20 +67,6 @@
 
 ```
 
-2. 发送本地图片路径
-
-```
-[POST] http://127.0.0.1:{ROBOT_WECHAT_CLIENT_PORT}/api/v1//robot/message/send/image/local
-
-请求体 Body:
-
-{
-  "to_wxid": "{{ROBOT_FROM_WX_ID}}",
-  "file_path": "{{file_path}}"
-}
-
-```
-
 **发送视频的时候也可以调用 Agent 接口**
 
 ```

skills/beauty/SKILL.md

@@ -20,7 +20,7 @@ argument-hint: "无需参数，直接调用即可"
 
 ## 接口信息
 
-- 获取图片地址：`https://api.pearapi.ai/api/today_wife`
+- 获取图片地址：`https://api.pearktrue.cn/api/today_wife`
 - 请求方式：`GET`
 - 发图接口：`http://127.0.0.1:{ROBOT_WECHAT_CLIENT_PORT}/api/v1/robot/message/send/image/url`
 - 请求方式：`POST`
@@ -32,12 +32,12 @@ argument-hint: "无需参数，直接调用即可"
   "code": 200,
   "msg": "获取成功",
   "data": {
-    "image_url": "https://api.pearapi.ai/api_assets/wife/9a6a9c38-7d6e-464f-8930-eb9dac41cde9.webp",
+    "image_url": "https://api.pearktrue.cn/api_assets/wife/9a6a9c38-7d6e-464f-8930-eb9dac41cde9.webp",
     "role_name": "初音未来、巡音流歌",
     "width": 2480,
     "height": 3508
   },
-  "api_source": "官方API网:https://api.pearapi.ai/"
+  "api_source": "官方API网:https://api.pearktrue.cn/"
 }
 ```
 
@@ -52,7 +52,7 @@ argument-hint: "无需参数，直接调用即可"
 
 1. 当用户发送 `999` 时触发该技能。
 2. 在仓库根目录下执行本地脚本：`python3 scripts/beauty.py`。
-3. 脚本内部发送 `GET` 请求到 `https://api.pearapi.ai/api/today_wife`。
+3. 脚本内部发送 `GET` 请求到 `https://api.pearktrue.cn/api/today_wife`。
 4. 脚本解析返回的 JSON，并提取 `data.image_url`。
 5. 脚本从环境变量中读取 `ROBOT_WECHAT_CLIENT_PORT` 和 `ROBOT_FROM_WX_ID`。
 6. 脚本发送 `POST` 请求到 `http://127.0.0.1:{ROBOT_WECHAT_CLIENT_PORT}/api/v1/robot/message/send/image/url`，请求体为：

skills/beauty/scripts/beauty.py

@@ -13,7 +13,7 @@ import urllib.request
 sys.stderr = sys.stdout
 
 
-FETCH_API_URL = "https://api.pearapi.ai/api/today_wife"
+FETCH_API_URL = "https://api.pearktrue.cn/api/today_wife"
 FALLBACK_TEXT = "今天的美女图片暂时没拿到，等我再找找。"
 
 

skills/douyin-video-parse/SKILL.md

@@ -1,53 +0,0 @@
----
-name: douyin-video-parse
-description: "当用户发送包含抖音短链接（https://v.douyin.com/xxx）的消息时触发。自动解析抖音视频/图片，并发送给当前用户。"
-argument-hint: "消息中包含抖音短链接即可自动触发"
----
-
-# Douyin Video Parse Skill
-
-## 描述
-
-这是一个用于解析抖音短视频/图片的技能。
-
-当用户发送的消息中包含 `https://v.douyin.com/` 链接时，自动解析该链接对应的视频或图片，并通过本地微信机器人接口发送给当前用户。
-
-这个仓库里额外提供了一个可执行脚本 `scripts/douyin_video_parse.py`，方便宿主机器人直接调用。
-
-## 触发条件
-
-- 用户消息中包含 `https://v.douyin.com/` 链接
-
-## 解析原理
-
-1. 访问抖音短链接，跟随 302 重定向获取真实页面 URL
-2. 请求真实页面 HTML，从中提取 `window._ROUTER_DATA` JSON 数据
-3. 从 JSON 中解析出视频播放地址或图片列表
-4. 通过本地微信机器人接口发送视频或图片
-
-## 环境变量
-
-- `ROBOT_WECHAT_CLIENT_PORT`：本地微信机器人服务端口。
-- `ROBOT_FROM_WX_ID`：当前消息来源用户的 wxid。
-- `ROBOT_MESSAGE_CONTENT`：用户发送的原始消息内容（用于提取抖音链接）。
-
-## 执行步骤
-
-1. 当用户消息中包含 `https://v.douyin.com/` 链接时触发该技能。
-2. 在仓库根目录下执行本地脚本：`python3 scripts/douyin_video_parse.py`。
-3. 脚本从环境变量 `ROBOT_MESSAGE_CONTENT` 中提取抖音短链接。
-4. 脚本访问短链接，跟随重定向获取真实页面 URL。
-5. 脚本请求真实页面，解析 `window._ROUTER_DATA` 中的视频/图片信息。
-6. 如果是视频：
-   - 先发送分享卡片链接
-   - 再调用 `POST http://127.0.0.1:{ROBOT_WECHAT_CLIENT_PORT}/api/v1/robot/message/send/video/url` 发送视频
-7. 如果是图片：
-   - 发送文字提示（作者、标题、图片数量）
-   - 调用 `POST http://127.0.0.1:{ROBOT_WECHAT_CLIENT_PORT}/api/v1/robot/message/send/image/url` 逐张发送图片
-8. 如果解析失败，回复兜底文案：`抖音解析失败，可能是链接已失效或格式不正确。`
-
-## 回复要求
-
-- 视频类型：发送视频文件，附带作者和标题信息。
-- 图片类型：发送所有图片，附带作者和标题信息。
-- 失败时，使用固定兜底文案回复。

skills/douyin-video-parse/scripts/douyin_video_parse.py

@@ -1,345 +0,0 @@
-#!/usr/bin/env python3
-
-from __future__ import annotations
-
-import html
-import json
-import os
-import re
-import sys
-import traceback
-import urllib.error
-import urllib.parse
-import urllib.request
-
-
-sys.stderr = sys.stdout
-
-
-DOUYIN_USER_AGENT = (
-    "Mozilla/5.0 (iPhone; CPU iPhone OS 14_0 like Mac OS X) "
-    "AppleWebKit/605.1.15 (KHTML, like Gecko) "
-    "Version/14.0 Mobile/15E148 Safari/604.1"
-)
-DOUYIN_REFERER = "https://www.douyin.com/"
-FALLBACK_TEXT = "抖音解析失败，可能是链接已失效或格式不正确。"
-ROUTER_DATA_RE = re.compile(r"(?s)window\._ROUTER_DATA\s*=\s*(\{.*?\})\s*</script>")
-DOUYIN_URL_RE = re.compile(r"https://[^\s]+")
-
-
-def build_request(url: str) -> urllib.request.Request:
-    return urllib.request.Request(
-        url,
-        headers={
-            "User-Agent": DOUYIN_USER_AGENT,
-            "Referer": DOUYIN_REFERER,
-        },
-    )
-
-
-def resolve_redirect(short_url: str) -> str | None:
-    """Follow the 302 redirect to get the real page URL."""
-
-    class NoRedirectHandler(urllib.request.HTTPRedirectHandler):
-        def redirect_request(self, req, fp, code, msg, headers, newurl):
-            return None
-
-    opener = urllib.request.build_opener(NoRedirectHandler)
-    req = build_request(short_url)
-    try:
-        response = opener.open(req, timeout=15)
-        return response.url
-    except urllib.error.HTTPError as e:
-        location = e.headers.get("Location")
-        if location:
-            return location
-        return None
-    except (urllib.error.URLError, TimeoutError):
-        return None
-
-
-def fetch_page_html(page_url: str) -> str | None:
-    """Fetch the Douyin page HTML content."""
-    req = build_request(page_url)
-    try:
-        with urllib.request.urlopen(req, timeout=15) as response:
-            if response.status != 200:
-                return None
-            return response.read().decode("utf-8", errors="replace")
-    except (urllib.error.URLError, TimeoutError):
-        return None
-
-
-def decode_escaped_value(value: str) -> str:
-    """Decode HTML entities and JSON escape sequences."""
-    decoded = html.unescape(value)
-    if "\\" in decoded:
-        try:
-            unquoted = json.loads('"' + decoded.replace('"', '\\"') + '"')
-            decoded = unquoted
-        except (json.JSONDecodeError, ValueError):
-            pass
-    return html.unescape(decoded)
-
-
-def pick_preferred_url(urls: list[str]) -> str:
-    """Pick the best URL from a list, preferring p26 CDN."""
-    first_url = ""
-    for raw_url in urls:
-        if not raw_url:
-            continue
-        decoded_url = decode_escaped_value(raw_url)
-        if not decoded_url:
-            continue
-        if decoded_url.startswith("https://p26"):
-            return decoded_url
-        if not first_url:
-            first_url = decoded_url
-    return first_url
-
-
-def pick_video_url(urls: list[str]) -> str:
-    """Pick the best video URL, preferring aweme.snssdk.com."""
-    decoded_urls = []
-    for raw_url in urls:
-        if not raw_url:
-            continue
-        decoded_url = decode_escaped_value(raw_url).replace("playwm", "play")
-        decoded_urls.append(decoded_url)
-
-    for url in decoded_urls:
-        if "aweme.snssdk.com" in url:
-            return url
-    return decoded_urls[0] if decoded_urls else ""
-
-
-def extract_aweme_item(html_content: str) -> dict | None:
-    """Extract the first aweme item from _ROUTER_DATA."""
-    match = ROUTER_DATA_RE.search(html_content)
-    if not match:
-        return None
-
-    try:
-        router_data = json.loads(match.group(1))
-    except json.JSONDecodeError:
-        return None
-
-    loader_data = router_data.get("loaderData", {})
-    for page_data in loader_data.values():
-        if not isinstance(page_data, dict):
-            continue
-        video_info_res = page_data.get("videoInfoRes", {})
-        item_list = video_info_res.get("item_list", [])
-        if item_list:
-            return item_list[0]
-    return None
-
-
-def parse_note_item(item: dict) -> dict | None:
-    """Parse image/note type content."""
-    images = item.get("images") or item.get("image_infos") or []
-    if not images:
-        return None
-
-    image_urls = []
-    seen = set()
-    for img_info in images:
-        url_list = img_info.get("url_list", [])
-        for url in url_list:
-            if url and url.startswith("http"):
-                decoded = html.unescape(url)
-                if decoded not in seen:
-                    image_urls.append(decoded)
-                    seen.add(decoded)
-                    break
-
-    if not image_urls:
-        return None
-
-    author = item.get("author", {})
-    music = item.get("music", {})
-    music_url = pick_preferred_url(music.get("play_url", {}).get("url_list", []))
-
-    # Fallback music URL from video play_addr
-    if not music_url:
-        video = item.get("video", {})
-        play_addr = video.get("play_addr", {})
-        uri = play_addr.get("uri", "")
-        if uri.startswith("http"):
-            music_url = decode_escaped_value(uri)
-        else:
-            music_url = pick_preferred_url(play_addr.get("url_list", []))
-
-    return {
-        "type": "note",
-        "author": html.unescape(author.get("nickname", "")),
-        "title": html.unescape(item.get("desc", "")),
-        "images": image_urls,
-        "music_url": music_url,
-    }
-
-
-def parse_video_item(item: dict) -> dict | None:
-    """Parse video type content."""
-    video = item.get("video", {})
-    duration = video.get("duration")
-    if duration is not None and duration == 0:
-        return None
-
-    play_addr = video.get("play_addr", {})
-    video_url = pick_video_url(play_addr.get("url_list", []))
-    if not video_url:
-        return None
-
-    author = item.get("author", {})
-    return {
-        "type": "video",
-        "author": html.unescape(author.get("nickname", "")),
-        "title": html.unescape(item.get("desc", "")),
-        "url": video_url,
-        "cover": pick_preferred_url(video.get("cover", {}).get("url_list", [])),
-    }
-
-
-def parse_douyin(short_url: str) -> dict | None:
-    """Main parsing logic: resolve redirect -> fetch HTML -> extract data."""
-    resolved_url = resolve_redirect(short_url)
-    if not resolved_url:
-        return None
-
-    html_content = fetch_page_html(resolved_url)
-    if not html_content:
-        return None
-
-    item = extract_aweme_item(html_content)
-    if not item:
-        return None
-
-    # Try note (images) first, then video
-    result = parse_note_item(item)
-    if result:
-        return result
-
-    result = parse_video_item(item)
-    if result:
-        return result
-
-    return None
-
-
-def send_video(video_url: str, robot_port: str, to_wxid: str) -> bool:
-    """Send video via local robot API."""
-    api_url = f"http://127.0.0.1:{robot_port}/api/v1/robot/message/send/video/url"
-    body = json.dumps({
-        "to_wxid": to_wxid,
-        "video_urls": [video_url],
-    }).encode("utf-8")
-    request = urllib.request.Request(
-        api_url,
-        data=body,
-        headers={"Content-Type": "application/json"},
-        method="POST",
-    )
-    try:
-        with urllib.request.urlopen(request, timeout=60) as response:
-            return 200 <= response.status < 300
-    except (urllib.error.URLError, TimeoutError):
-        return False
-
-
-def send_images(image_urls: list[str], robot_port: str, to_wxid: str) -> bool:
-    """Send images via local robot API."""
-    api_url = f"http://127.0.0.1:{robot_port}/api/v1/robot/message/send/image/url"
-    body = json.dumps({
-        "to_wxid": to_wxid,
-        "image_urls": image_urls,
-    }).encode("utf-8")
-    request = urllib.request.Request(
-        api_url,
-        data=body,
-        headers={"Content-Type": "application/json"},
-        method="POST",
-    )
-    try:
-        with urllib.request.urlopen(request, timeout=60) as response:
-            return 200 <= response.status < 300
-    except (urllib.error.URLError, TimeoutError):
-        return False
-
-
-def send_text(text: str, robot_port: str, to_wxid: str) -> bool:
-    """Send text message via local robot API."""
-    api_url = f"http://127.0.0.1:{robot_port}/api/v1/robot/message/send/text"
-    body = json.dumps({
-        "to_wxid": to_wxid,
-        "content": text,
-    }).encode("utf-8")
-    request = urllib.request.Request(
-        api_url,
-        data=body,
-        headers={"Content-Type": "application/json"},
-        method="POST",
-    )
-    try:
-        with urllib.request.urlopen(request, timeout=10) as response:
-            return 200 <= response.status < 300
-    except (urllib.error.URLError, TimeoutError):
-        return False
-
-
-def main() -> int:
-    robot_port = os.environ.get("ROBOT_WECHAT_CLIENT_PORT", "").strip()
-    to_wxid = os.environ.get("ROBOT_FROM_WX_ID", "").strip()
-    message_content = os.environ.get("ROBOT_MESSAGE_CONTENT", "").strip()
-
-    if not robot_port or not to_wxid or not message_content:
-        sys.stdout.write(FALLBACK_TEXT + "\n")
-        return 0
-
-    # Extract douyin URL from message
-    matches = DOUYIN_URL_RE.findall(message_content)
-    douyin_urls = [u for u in matches if "v.douyin.com" in u]
-    if not douyin_urls:
-        sys.stdout.write(FALLBACK_TEXT + "\n")
-        return 0
-
-    douyin_url = douyin_urls[0]
-    result = parse_douyin(douyin_url)
-    if not result:
-        sys.stdout.write(FALLBACK_TEXT + "\n")
-        return 0
-
-    if result["type"] == "video":
-        # Send info text
-        info_text = f"抖音视频解析成功\n作者: {result['author']}\n标题: {result['title']}"
-        send_text(info_text, robot_port, to_wxid)
-        # Send video
-        if not send_video(result["url"], robot_port, to_wxid):
-            sys.stdout.write("发送抖音视频失败，请稍后重试。\n")
-            return 0
-
-    elif result["type"] == "note":
-        # Send info text
-        info_text = (
-            f"抖音图片解析成功\n"
-            f"作者: {result['author']}\n"
-            f"标题: {result['title']}\n\n"
-            f"{len(result['images'])}张图片正在发送中..."
-        )
-        send_text(info_text, robot_port, to_wxid)
-        # Send images
-        if not send_images(result["images"], robot_port, to_wxid):
-            sys.stdout.write("发送抖音图片失败，请稍后重试。\n")
-            return 0
-
-    return 0
-
-
-if __name__ == "__main__":
-    try:
-        raise SystemExit(main())
-    except SystemExit:
-        raise
-    except Exception:
-        traceback.print_exc(file=sys.stdout)
-        raise SystemExit(1)

skills/image-to-image/SKILL.md

@@ -10,7 +10,7 @@ argument-hint: "需要 prompt（提示词）和 images（图片链接列表）
 
 这是一个 AI 图生图技能，基于输入的一张或多张图片，结合文本提示词生成新的图片。支持图片混合、风格转换、内容合成等多种创作模式。
 
-支持多个绘图模型：即梦（JiMeng）、豆包（DouBao）、造相（Z-Image）、OpenAI GPT Image。
+支持多个绘图模型：即梦（JiMeng）、豆包（DouBao）、造相（Z-Image）。
 
 从数据库中读取绘图配置（API 密钥、Base URL 等），根据用户选择的模型调用对应的绘图 API，返回生成的图片 URL。
 
@@ -37,18 +37,16 @@ argument-hint: "需要 prompt（提示词）和 images（图片链接列表）
     },
     "model": {
       "type": "string",
-      "description": "画图模型选择（可选）：即梦4.5(jimeng-4.5) / 即梦4.6(jimeng-4.6) / 即梦4.7(jimeng-4.7) / 即梦5.0(jimeng-5.0) / 豆包图生图(doubao-seededit-3.0-i2i) / 造相基础版(Z-Image) / 造相蒸馏版(Z-Image-Turbo) / 造相图片编辑(Qwen-Image-Edit-2511) / OpenAI GPT Image(gpt-image-2)，默认: 空(none)。",
+      "description": "画图模型选择（可选）：即梦4.5(jimeng-4.5) / 即梦4.6(jimeng-4.6) / 即梦5.0(jimeng-5.0) / 豆包图生图(doubao-seededit-3.0-i2i) / 造相基础版(Z-Image) / 造相蒸馏版(Z-Image-Turbo) / 造相图片编辑(Qwen-Image-Edit-2511)，默认: 空(none)。",
       "enum": [
         "none",
         "jimeng-4.5",
         "jimeng-4.6",
-        "jimeng-4.7",
         "jimeng-5.0",
         "doubao-seededit-3.0-i2i",
         "Z-Image",
         "Z-Image-Turbo",
-        "Qwen-Image-Edit-2511",
+        "Qwen-Image-Edit-2511"
-        "gpt-image-2"
       ],
       "default": "none"
     },

skills/image-to-image/scripts/image_to_image.py

@@ -3,17 +3,13 @@
 from __future__ import annotations
 
 import argparse
-import base64
 import json
-import mimetypes
 import os
 import re
 import subprocess
 import sys
-import tempfile
 import time
 import traceback
-import urllib.parse
 import urllib.request
 from pathlib import Path
 
@@ -71,7 +67,6 @@ _ensure_skill_venv_python()
 
 try:
     import pymysql  # type: ignore  # noqa: E402
-    from openai import OpenAI  # type: ignore  # noqa: E402
 except ModuleNotFoundError:
     _run_bootstrap()
     _py = _get_python_executable()
@@ -172,240 +167,6 @@ def _http_get_json(url: str, headers: dict, timeout: int = 30) -> dict:
         return json.loads(resp.read().decode("utf-8"))
 
 
-def _coerce_int(value, default: int, minimum: int, maximum: int) -> int:
-    try:
-        parsed = int(value)
-    except (TypeError, ValueError):
-        parsed = default
-    return min(max(parsed, minimum), maximum)
-
-
-def _openai_output_format(config: dict) -> str:
-    output_format = str(config.get("output_format", "png") or "png").lower()
-    if output_format not in {"png", "jpeg", "webp"}:
-        return "png"
-    return output_format
-
-
-def _openai_size(config: dict, ratio: str, resolution: str) -> str:
-    configured = str(config.get("size", "") or "").strip()
-    if configured:
-        return configured
-
-    normalized_ratio = (ratio or "").replace(" ", "").lower()
-    normalized_resolution = (resolution or "").replace(" ", "").lower()
-
-    if normalized_resolution in {"4k", "2160p", "3840x2160"}:
-        sizes = {
-            "16:9": "3840x2160",
-            "9:16": "2160x3840",
-            "1:1": "2048x2048",
-            "3:2": "3072x2048",
-            "2:3": "2048x3072",
-        }
-    elif normalized_resolution in {"2k", "1440p", "2048"}:
-        sizes = {
-            "16:9": "2048x1152",
-            "9:16": "1152x2048",
-            "1:1": "2048x2048",
-            "3:2": "2048x1360",
-            "2:3": "1360x2048",
-        }
-    elif normalized_resolution in {"1k", "1024", "1024p"}:
-        sizes = {
-            "16:9": "1536x864",
-            "9:16": "864x1536",
-            "1:1": "1024x1024",
-            "3:2": "1536x1024",
-            "2:3": "1024x1536",
-        }
-    else:
-        return "auto"
-
-    return sizes.get(normalized_ratio, "auto")
-
-
-def _openai_prompt(prompt: str, negative_prompt: str) -> str:
-    if not negative_prompt:
-        return prompt
-    return f"{prompt}\n\n不要包含: {negative_prompt}"
-
-
-def _openai_client(config: dict) -> OpenAI:
-    api_key = str(config.get("api_key", "")).strip()
-    if not api_key:
-        raise RuntimeError("OpenAI 绘图配置缺少 api_key")
-
-    base_url = str(config.get("base_url", "") or "").strip()
-    organization = str(config.get("organization", "") or "").strip()
-    project = str(config.get("project", "") or "").strip()
-    timeout: float | None = None
-    timeout_value = config.get("timeout")
-    if timeout_value not in (None, ""):
-        timeout = float(timeout_value)
-
-    return OpenAI(
-        api_key=api_key,
-        base_url=base_url or None,
-        organization=organization or None,
-        project=project or None,
-        timeout=timeout,
-    )
-
-
-def _truncate_debug_payload(value):
-    if isinstance(value, dict):
-        return {
-            key: (
-                f"{item[:50]}..." if key == "b64_json" and isinstance(item, str) and len(item) > 50 else _truncate_debug_payload(item)
-            )
-            for key, item in value.items()
-        }
-    if isinstance(value, list):
-        return [_truncate_debug_payload(item) for item in value]
-    return value
-
-
-def _debug_response(label: str, payload) -> None:
-    if hasattr(payload, "model_dump"):
-        payload = payload.model_dump()
-    payload = _truncate_debug_payload(payload)
-    sys.stdout.write(f"[debug] {label}: {json.dumps(payload, ensure_ascii=False)}\n")
-
-
-def _rewrite_openai_image_url(url: str) -> str:
-    internal_host = "http://chatgpt2api:80"
-    external_host = "https://chatgpt2api.houhoukang.com"
-    if url.startswith(internal_host):
-        return f"{external_host}{url[len(internal_host):]}"
-    return url
-
-
-def _extension_from_output_format(output_format: str) -> str:
-    if output_format == "jpeg":
-        return ".jpg"
-    if output_format == "webp":
-        return ".webp"
-    return ".png"
-
-
-def _openai_response_value(item, key: str):
-    if isinstance(item, dict):
-        return item.get(key)
-    return getattr(item, key, None)
-
-
-def _write_openai_b64_image(b64_json: str, output_format: str) -> str:
-    encoded = b64_json.strip()
-    suffix = _extension_from_output_format(output_format)
-    if encoded.startswith("data:"):
-        header, encoded = encoded.split(",", 1)
-        mime_type = header[5:].split(";", 1)[0].strip().lower()
-        if mime_type:
-            suffix = _extension_from_mime(mime_type)
-
-    encoded = "".join(encoded.split())
-    padding = len(encoded) % 4
-    if padding:
-        encoded = f"{encoded}{'=' * (4 - padding)}"
-
-    image_bytes = base64.b64decode(encoded)
-    with tempfile.NamedTemporaryFile(prefix="wechat-openai-image-", suffix=suffix, delete=False) as temp_file:
-        temp_file.write(image_bytes)
-        return temp_file.name
-
-
-def _openai_images_from_response(response, output_format: str) -> list[str]:
-    outputs: list[str] = []
-    try:
-        for item in getattr(response, "data", []) or []:
-            b64_json = _openai_response_value(item, "b64_json")
-            if b64_json:
-                outputs.append(_write_openai_b64_image(str(b64_json), output_format))
-                continue
-
-            url = _openai_response_value(item, "url")
-            if url:
-                outputs.append(_rewrite_openai_image_url(str(url)))
-    except Exception:
-        _cleanup_openai_temp_files(outputs)
-        raise
-    return outputs
-
-
-def _is_remote_image_url(value: str) -> bool:
-    return urllib.parse.urlparse(value).scheme in {"http", "https"}
-
-
-def _send_image_outputs(client_port: str, from_wx_id: str, image_outputs: list[str]) -> None:
-    remote_urls = [value for value in image_outputs if value and _is_remote_image_url(value)]
-    local_paths = [value for value in image_outputs if value and not _is_remote_image_url(value)]
-
-    if remote_urls:
-        send_url = f"http://127.0.0.1:{client_port}/api/v1/robot/message/send/image/url"
-        send_body = {
-            "to_wxid": from_wx_id,
-            "image_urls": remote_urls,
-        }
-        response = _http_post_json(send_url, send_body, {"Content-Type": "application/json"}, timeout=300)
-        _debug_response("send image url response", response)
-
-    for file_path in local_paths:
-        send_url = f"http://127.0.0.1:{client_port}/api/v1/robot/message/send/image/local"
-        send_body = {
-            "to_wxid": from_wx_id,
-            "file_path": file_path,
-        }
-        response = _http_post_json(send_url, send_body, {"Content-Type": "application/json"}, timeout=300)
-        _debug_response("send image local response", response)
-
-
-def _cleanup_openai_temp_files(image_outputs: list[str]) -> None:
-    for value in image_outputs:
-        path = Path(value)
-        if path.name.startswith("wechat-openai-image-") and path.is_file():
-            try:
-                path.unlink()
-            except OSError:
-                pass
-
-
-def _extension_from_mime(mime_type: str) -> str:
-    if mime_type == "image/jpeg":
-        return ".jpg"
-    guessed = mimetypes.guess_extension(mime_type)
-    if guessed in {".png", ".jpg", ".jpeg", ".webp"}:
-        return guessed
-    return ".png"
-
-
-def _download_openai_input_image(image: str, directory: str, index: int) -> Path:
-    stripped = image.strip()
-    if stripped.startswith("data:"):
-        header, encoded = stripped.split(",", 1)
-        mime_type = header[5:].split(";", 1)[0] or "image/png"
-        path = Path(directory) / f"input-{index}{_extension_from_mime(mime_type)}"
-        path.write_bytes(base64.b64decode(encoded))
-        return path
-
-    parsed = urllib.parse.urlparse(stripped)
-    if parsed.scheme in {"http", "https"}:
-        request = urllib.request.Request(stripped, headers={"User-Agent": "wechat-robot-skills/1.0"})
-        with urllib.request.urlopen(request, timeout=60) as response:
-            content_type = response.headers.get("Content-Type", "image/png").split(";", 1)[0].strip()
-            suffix = Path(parsed.path).suffix.lower()
-            if suffix not in {".png", ".jpg", ".jpeg", ".webp"}:
-                suffix = _extension_from_mime(content_type)
-            path = Path(directory) / f"input-{index}{suffix}"
-            path.write_bytes(response.read())
-            return path
-
-    path = Path(stripped).expanduser()
-    if path.is_file():
-        return path
-    raise RuntimeError(f"无法读取图片: {image}")
-
-
 def call_jimeng(config: dict, prompt: str, model: str, images: list[str],
                 negative_prompt: str, ratio: str, resolution: str) -> list[str]:
     """Call JiMeng (即梦) image compositions API (图生图)."""
@@ -548,53 +309,13 @@ def call_zimage(config: dict, prompt: str, model: str, images: list[str]) -> lis
     raise RuntimeError("造相绘图任务超时")
 
 
-def call_openai(config: dict, prompt: str, model: str, images: list[str],
-                negative_prompt: str, ratio: str, resolution: str) -> list[str]:
-    """Call OpenAI GPT Image API for image editing."""
-    client = _openai_client(config)
-    output_format = _openai_output_format(config)
-    quality = str(config.get("quality", "auto") or "auto")
-    background = str(config.get("background", "auto") or "auto")
-    if background == "transparent":
-        background = "auto"
-
-    with tempfile.TemporaryDirectory() as temp_dir:
-        input_paths = [
-            _download_openai_input_image(image, temp_dir, index)
-            for index, image in enumerate(images[:16], start=1)
-        ]
-        input_files = [path.open("rb") for path in input_paths]
-        try:
-            kwargs = {
-                "model": model or "gpt-image-2",
-                "prompt": _openai_prompt(prompt, negative_prompt),
-                "image": input_files,
-                "n": _coerce_int(config.get("n"), 1, 1, 10),
-                "size": _openai_size(config, ratio, resolution),
-                "quality": quality,
-                "background": background,
-                "output_format": output_format,
-            }
-            if output_format in {"jpeg", "webp"} and config.get("output_compression") is not None:
-                kwargs["output_compression"] = _coerce_int(config.get("output_compression"), 100, 0, 100)
-
-            response = client.images.edit(**kwargs)
-        finally:
-            for input_file in input_files:
-                input_file.close()
-
-    _debug_response("openai images.edit response", response)
-    return _openai_images_from_response(response, output_format)
-
-
 # ---------------------------------------------------------------------------
 # Main
 # ---------------------------------------------------------------------------
 
-JIMENG_MODELS = {"jimeng-4.5", "jimeng-4.6", "jimeng-4.7", "jimeng-5.0"}
+JIMENG_MODELS = {"jimeng-4.5", "jimeng-4.6", "jimeng-5.0"}
 DOUBAO_MODELS = {"doubao-seededit-3.0-i2i"}
 ZIMAGE_MODELS = {"Z-Image", "Z-Image-Turbo", "Qwen-Image-Edit-2511"}
-OPENAI_MODELS = {"gpt-image-2"}
 
 
 def _parse_cli_params(argv: list[str]) -> dict:
@@ -703,13 +424,6 @@ def main() -> int:
                 return 0
             image_urls = call_zimage(zimage_config, prompt, model, images)
 
-        elif model in OPENAI_MODELS:
-            openai_config = settings_json.get("OpenAI", {})
-            if not openai_config.get("enabled", False):
-                sys.stdout.write("OpenAI 绘图未开启\n")
-                return 0
-            image_urls = call_openai(openai_config, prompt, model, images, negative_prompt, ratio, resolution)
-
         else:
             sys.stdout.write("不支持的 AI 图像模型\n")
             return 1
@@ -725,18 +439,20 @@ def main() -> int:
     # 通过客户端接口发送图片
     client_port = os.environ.get("ROBOT_WECHAT_CLIENT_PORT", "").strip()
     if not client_port:
-        _cleanup_openai_temp_files(image_urls)
         sys.stdout.write("环境变量 ROBOT_WECHAT_CLIENT_PORT 未配置\n")
         return 1
 
+    send_url = f"http://127.0.0.1:{client_port}/api/v1/robot/message/send/image/url"
+    send_body = {
+        "to_wxid": from_wx_id,
+        "image_urls": [u for u in image_urls if u],
+    }
     try:
-        _send_image_outputs(client_port, from_wx_id, image_urls)
+        _http_post_json(send_url, send_body, {"Content-Type": "application/json"}, timeout=60)
         sys.stdout.write("图片发送成功\n")
     except Exception as exc:
         sys.stdout.write(f"发送图片失败: {exc}\n")
         return 1
-    finally:
-        _cleanup_openai_temp_files(image_urls)
 
     return 0
 

skills/image-to-image/scripts/requirements.txt

@@ -1,3 +1,2 @@
 cryptography
-openai>=2.34.0
 pymysql>=1.1,<2

skills/kfc/SKILL.md

@@ -23,7 +23,7 @@ argument-hint: "无需参数，直接调用即可"
 
 ## 接口信息
 
-- 请求地址：`https://api.pearapi.ai/api/kfc?type=json`
+- 请求地址：`https://api.pearktrue.cn/api/kfc?type=json`
 - 请求方式：`GET`
 - 本地脚本：`scripts/kfc.py`
 - 返回示例：
@@ -33,7 +33,7 @@ argument-hint: "无需参数，直接调用即可"
   "code": 200,
   "msg": "获取成功",
   "text": "14看着不香，果然还是13更香，iPhone14真是更新了个寂寞！......今天肯德基疯狂星期四，谁请我吃？",
-  "api_source": "官方API网:https://api.pearapi.ai/"
+  "api_source": "官方API网:https://api.pearktrue.cn/"
 }
 ```
 
@@ -43,7 +43,7 @@ argument-hint: "无需参数，直接调用即可"
 
 1. 当用户输入 `kfc`、`KFC`、`肯德基` 或 `肯德基文案` 时触发该技能。
 2. 在仓库根目录下执行本地脚本：`python3 scripts/kfc.py`。
-3. 脚本内部发送 `GET` 请求到 `https://api.pearapi.ai/api/kfc?type=json`。
+3. 脚本内部发送 `GET` 请求到 `https://api.pearktrue.cn/api/kfc?type=json`。
 4. 脚本解析返回的 JSON，并输出 `text` 字段。
 5. 如果接口请求失败、返回格式异常，或没有拿到 `text`，脚本输出：`今天的肯德基文案暂时没拿到，等我再去问问。`
 6. 如果脚本无法执行（Python 环境不可用），直接回复兜底文案：`今天的肯德基文案暂时没拿到，等我再去问问。`

skills/kfc/scripts/kfc.py

@@ -12,7 +12,7 @@ import urllib.request
 sys.stderr = sys.stdout
 
 
-API_URL = "https://api.pearapi.ai/api/kfc?type=json"
+API_URL = "https://api.pearktrue.cn/api/kfc?type=json"
 FALLBACK_TEXT = "今天的肯德基文案暂时没拿到，等我再去问问。"
 
 

skills/text-to-image/SKILL.md

@@ -8,7 +8,7 @@ argument-hint: "需要 prompt 参数（画图提示词），可选 model（模
 
 ## 描述
 
-这是一个 AI 文生图技能，当用户想通过文本描述生成图像时触发。支持多个绘图模型：即梦（JiMeng）、豆包（DouBao）、造相（Z-Image）、OpenAI GPT Image。
+这是一个 AI 文生图技能，当用户想通过文本描述生成图像时触发。支持多个绘图模型：即梦（JiMeng）、豆包（DouBao）、造相（Z-Image）。
 
 从数据库中读取绘图配置（API 密钥、Base URL 等），根据用户选择的模型调用对应的绘图 API，返回生成的图片 URL。
 
@@ -35,12 +35,11 @@ argument-hint: "需要 prompt 参数（画图提示词），可选 model（模
     },
     "model": {
       "type": "string",
-      "description": "画图模型选择（可选）：即梦4.5(jimeng-4.5) / 即梦4.6(jimeng-4.6) / 即梦4.7(jimeng-4.7) / 即梦5.0(jimeng-5.0) / 豆包4.5(doubao-seedream-4.5) / 豆包4.0(doubao-seedream-4.0) / 豆包文生图(doubao-seedream-3.0-t2i) / 豆包图生图(doubao-seededit-3.0-i2i) / 造相基础版(Z-Image) / 造相蒸馏版(Z-Image-Turbo) / 造相图片编辑(Qwen-Image-Edit-2511) / OpenAI GPT Image(gpt-image-2)，默认: 空(none)。",
+      "description": "画图模型选择（可选）：即梦4.5(jimeng-4.5) / 即梦4.6(jimeng-4.6) / 即梦5.0(jimeng-5.0) / 豆包4.5(doubao-seedream-4.5) / 豆包4.0(doubao-seedream-4.0) / 豆包文生图(doubao-seedream-3.0-t2i) / 豆包图生图(doubao-seededit-3.0-i2i) / 造相基础版(Z-Image) / 造相蒸馏版(Z-Image-Turbo) / 造相图片编辑(Qwen-Image-Edit-2511)，默认: 空(none)。",
       "enum": [
         "none",
         "jimeng-4.5",
         "jimeng-4.6",
-        "jimeng-4.7",
         "jimeng-5.0",
         "doubao-seedream-4.5",
         "doubao-seedream-4.0",
@@ -48,8 +47,7 @@ argument-hint: "需要 prompt 参数（画图提示词），可选 model（模
         "doubao-seededit-3.0-i2i",
         "Z-Image",
         "Z-Image-Turbo",
-        "Qwen-Image-Edit-2511",
+        "Qwen-Image-Edit-2511"
-        "gpt-image-2"
       ],
       "default": "none"
     },

skills/text-to-image/scripts/requirements.txt

@@ -1,3 +1,2 @@
 cryptography
-openai>=2.34.0
 pymysql>=1.1,<2

skills/text-to-image/scripts/text_to_image.py

@@ -3,17 +3,13 @@
 from __future__ import annotations
 
 import argparse
-import base64
 import json
-import mimetypes
 import os
 import re
 import subprocess
 import sys
-import tempfile
 import time
 import traceback
-import urllib.parse
 import urllib.request
 from pathlib import Path
 
@@ -71,7 +67,6 @@ _ensure_skill_venv_python()
 
 try:
     import pymysql  # type: ignore  # noqa: E402
-    from openai import OpenAI  # type: ignore  # noqa: E402
 except ModuleNotFoundError:
     _run_bootstrap()
     _py = _get_python_executable()
@@ -174,213 +169,6 @@ def _http_get_json(url: str, headers: dict, timeout: int = 30) -> dict:
         return json.loads(resp.read().decode("utf-8"))
 
 
-def _coerce_int(value, default: int, minimum: int, maximum: int) -> int:
-    try:
-        parsed = int(value)
-    except (TypeError, ValueError):
-        parsed = default
-    return min(max(parsed, minimum), maximum)
-
-
-def _openai_output_format(config: dict) -> str:
-    output_format = str(config.get("output_format", "png") or "png").lower()
-    if output_format not in {"png", "jpeg", "webp"}:
-        return "png"
-    return output_format
-
-
-def _openai_size(config: dict, ratio: str, resolution: str) -> str:
-    configured = str(config.get("size", "") or "").strip()
-    if configured:
-        return configured
-
-    normalized_ratio = (ratio or "").replace(" ", "").lower()
-    normalized_resolution = (resolution or "").replace(" ", "").lower()
-
-    if normalized_resolution in {"4k", "2160p", "3840x2160"}:
-        sizes = {
-            "16:9": "3840x2160",
-            "9:16": "2160x3840",
-            "1:1": "2048x2048",
-            "3:2": "3072x2048",
-            "2:3": "2048x3072",
-        }
-    elif normalized_resolution in {"2k", "1440p", "2048"}:
-        sizes = {
-            "16:9": "2048x1152",
-            "9:16": "1152x2048",
-            "1:1": "2048x2048",
-            "3:2": "2048x1360",
-            "2:3": "1360x2048",
-        }
-    elif normalized_resolution in {"1k", "1024", "1024p"}:
-        sizes = {
-            "16:9": "1536x864",
-            "9:16": "864x1536",
-            "1:1": "1024x1024",
-            "3:2": "1536x1024",
-            "2:3": "1024x1536",
-        }
-    else:
-        return "auto"
-
-    return sizes.get(normalized_ratio, "auto")
-
-
-def _openai_prompt(prompt: str, negative_prompt: str) -> str:
-    if not negative_prompt:
-        return prompt
-    return f"{prompt}\n\n不要包含: {negative_prompt}"
-
-
-def _openai_client(config: dict) -> OpenAI:
-    api_key = str(config.get("api_key", "")).strip()
-    if not api_key:
-        raise RuntimeError("OpenAI 绘图配置缺少 api_key")
-
-    base_url = str(config.get("base_url", "") or "").strip()
-    organization = str(config.get("organization", "") or "").strip()
-    project = str(config.get("project", "") or "").strip()
-    timeout: float | None = None
-    timeout_value = config.get("timeout")
-    if timeout_value not in (None, ""):
-        timeout = float(timeout_value)
-
-    return OpenAI(
-        api_key=api_key,
-        base_url=base_url or None,
-        organization=organization or None,
-        project=project or None,
-        timeout=timeout,
-    )
-
-
-def _truncate_debug_payload(value):
-    if isinstance(value, dict):
-        return {
-            key: (
-                f"{item[:50]}..." if key == "b64_json" and isinstance(item, str) and len(item) > 50 else _truncate_debug_payload(item)
-            )
-            for key, item in value.items()
-        }
-    if isinstance(value, list):
-        return [_truncate_debug_payload(item) for item in value]
-    return value
-
-
-def _debug_response(label: str, payload) -> None:
-    if hasattr(payload, "model_dump"):
-        payload = payload.model_dump()
-    payload = _truncate_debug_payload(payload)
-    sys.stdout.write(f"[debug] {label}: {json.dumps(payload, ensure_ascii=False)}\n")
-
-
-def _rewrite_openai_image_url(url: str) -> str:
-    internal_host = "http://chatgpt2api:80"
-    external_host = "https://chatgpt2api.houhoukang.com"
-    if url.startswith(internal_host):
-        return f"{external_host}{url[len(internal_host):]}"
-    return url
-
-
-def _extension_from_mime(mime_type: str) -> str:
-    if mime_type == "image/jpeg":
-        return ".jpg"
-    guessed = mimetypes.guess_extension(mime_type)
-    if guessed in {".png", ".jpg", ".jpeg", ".webp"}:
-        return guessed
-    return ".png"
-
-
-def _extension_from_output_format(output_format: str) -> str:
-    if output_format == "jpeg":
-        return ".jpg"
-    if output_format == "webp":
-        return ".webp"
-    return ".png"
-
-
-def _openai_response_value(item, key: str):
-    if isinstance(item, dict):
-        return item.get(key)
-    return getattr(item, key, None)
-
-
-def _write_openai_b64_image(b64_json: str, output_format: str) -> str:
-    encoded = b64_json.strip()
-    suffix = _extension_from_output_format(output_format)
-    if encoded.startswith("data:"):
-        header, encoded = encoded.split(",", 1)
-        mime_type = header[5:].split(";", 1)[0].strip().lower()
-        if mime_type:
-            suffix = _extension_from_mime(mime_type)
-
-    encoded = "".join(encoded.split())
-    padding = len(encoded) % 4
-    if padding:
-        encoded = f"{encoded}{'=' * (4 - padding)}"
-
-    image_bytes = base64.b64decode(encoded)
-    with tempfile.NamedTemporaryFile(prefix="wechat-openai-image-", suffix=suffix, delete=False) as temp_file:
-        temp_file.write(image_bytes)
-        return temp_file.name
-
-
-def _openai_images_from_response(response, output_format: str) -> list[str]:
-    outputs: list[str] = []
-    try:
-        for item in getattr(response, "data", []) or []:
-            b64_json = _openai_response_value(item, "b64_json")
-            if b64_json:
-                outputs.append(_write_openai_b64_image(str(b64_json), output_format))
-                continue
-
-            url = _openai_response_value(item, "url")
-            if url:
-                outputs.append(_rewrite_openai_image_url(str(url)))
-    except Exception:
-        _cleanup_openai_temp_files(outputs)
-        raise
-    return outputs
-
-
-def _is_remote_image_url(value: str) -> bool:
-    return urllib.parse.urlparse(value).scheme in {"http", "https"}
-
-
-def _send_image_outputs(client_port: str, from_wx_id: str, image_outputs: list[str]) -> None:
-    remote_urls = [value for value in image_outputs if value and _is_remote_image_url(value)]
-    local_paths = [value for value in image_outputs if value and not _is_remote_image_url(value)]
-
-    if remote_urls:
-        send_url = f"http://127.0.0.1:{client_port}/api/v1/robot/message/send/image/url"
-        send_body = {
-            "to_wxid": from_wx_id,
-            "image_urls": remote_urls,
-        }
-        response = _http_post_json(send_url, send_body, {"Content-Type": "application/json"}, timeout=300)
-        _debug_response("send image url response", response)
-
-    for file_path in local_paths:
-        send_url = f"http://127.0.0.1:{client_port}/api/v1/robot/message/send/image/local"
-        send_body = {
-            "to_wxid": from_wx_id,
-            "file_path": file_path,
-        }
-        response = _http_post_json(send_url, send_body, {"Content-Type": "application/json"}, timeout=300)
-        _debug_response("send image local response", response)
-
-
-def _cleanup_openai_temp_files(image_outputs: list[str]) -> None:
-    for value in image_outputs:
-        path = Path(value)
-        if path.name.startswith("wechat-openai-image-") and path.is_file():
-            try:
-                path.unlink()
-            except OSError:
-                pass
-
-
 def call_jimeng(config: dict, prompt: str, model: str,
                 negative_prompt: str, ratio: str, resolution: str) -> list[str]:
     """Call JiMeng (即梦) image generation API."""
@@ -527,43 +315,13 @@ def call_zimage(config: dict, prompt: str, model: str) -> list[str]:
     raise RuntimeError("造相绘图任务超时")
 
 
-def call_openai(config: dict, prompt: str, model: str,
-                negative_prompt: str, ratio: str, resolution: str) -> list[str]:
-    """Call OpenAI GPT Image API for text-to-image generation."""
-    client = _openai_client(config)
-    output_format = _openai_output_format(config)
-    quality = str(config.get("quality", "auto") or "auto")
-    moderation = str(config.get("moderation", "auto") or "auto")
-    background = str(config.get("background", "auto") or "auto")
-    if background == "transparent":
-        background = "auto"
-
-    kwargs = {
-        "model": model or "gpt-image-2",
-        "prompt": _openai_prompt(prompt, negative_prompt),
-        "n": _coerce_int(config.get("n"), 1, 1, 10),
-        "size": _openai_size(config, ratio, resolution),
-        "quality": quality,
-        "background": background,
-        "moderation": moderation,
-        "output_format": output_format,
-    }
-    if output_format in {"jpeg", "webp"} and config.get("output_compression") is not None:
-        kwargs["output_compression"] = _coerce_int(config.get("output_compression"), 100, 0, 100)
-
-    response = client.images.generate(**kwargs)
-    _debug_response("openai images.generate response", response)
-    return _openai_images_from_response(response, output_format)
-
-
 # ---------------------------------------------------------------------------
 # Main
 # ---------------------------------------------------------------------------
 
-JIMENG_MODELS = {"jimeng-4.5", "jimeng-4.6", "jimeng-4.7", "jimeng-5.0"}
+JIMENG_MODELS = {"jimeng-4.5", "jimeng-4.6", "jimeng-5.0"}
 DOUBAO_MODELS = {"doubao-seedream-4.5", "doubao-seedream-4.0", "doubao-seedream-3.0-t2i", "doubao-seededit-3.0-i2i"}
 ZIMAGE_MODELS = {"Z-Image", "Z-Image-Turbo", "Qwen-Image-Edit-2511"}
-OPENAI_MODELS = {"gpt-image-2"}
 
 
 def _parse_cli_params(argv: list[str]) -> dict[str, str]:
@@ -665,13 +423,6 @@ def main() -> int:
                 return 0
             image_urls = call_zimage(zimage_config, prompt, model)
 
-        elif model in OPENAI_MODELS:
-            openai_config = settings_json.get("OpenAI", {})
-            if not openai_config.get("enabled", False):
-                sys.stdout.write("OpenAI 绘图未开启\n")
-                return 0
-            image_urls = call_openai(openai_config, prompt, model, negative_prompt, ratio, resolution)
-
         else:
             sys.stdout.write("不支持的 AI 图像模型\n")
             return 1
@@ -687,18 +438,20 @@ def main() -> int:
     # 通过客户端接口发送图片
     client_port = os.environ.get("ROBOT_WECHAT_CLIENT_PORT", "").strip()
     if not client_port:
-        _cleanup_openai_temp_files(image_urls)
         sys.stdout.write("环境变量 ROBOT_WECHAT_CLIENT_PORT 未配置\n")
         return 1
 
+    send_url = f"http://127.0.0.1:{client_port}/api/v1/robot/message/send/image/url"
+    send_body = {
+        "to_wxid": from_wx_id,
+        "image_urls": [u for u in image_urls if u],
+    }
     try:
-        _send_image_outputs(client_port, from_wx_id, image_urls)
+        _http_post_json(send_url, send_body, {"Content-Type": "application/json"}, timeout=60)
         sys.stdout.write("图片发送成功\n")
     except Exception as exc:
         sys.stdout.write(f"发送图片失败: {exc}\n")
         return 1
-    finally:
-        _cleanup_openai_temp_files(image_urls)
 
     return 0
 

skills/voice-message/SKILL.md

@@ -111,70 +111,6 @@ argument-hint: "需要 content；可选 emotion、voice、style_prompt、voice_p
 9. 不要传递音色复刻音频参数。若当前消息引用了一条语音消息，脚本会通过 `ROBOT_REF_MESSAGE_ID` 自动判断并下载引用语音作为复刻样本。
 10. `content` 超过 260 个字符时，不应该调用本技能。
 
-## 音频标签控制
-
-通过在文本中嵌入风格标签与音频标签，直接对语音进行精细控制。开头是整体风格标签，中间可以插入细粒度控制标签。
-
-在目标文本开头添加 `(风格)` 标签，即可指定语音的发音风格。支持同时设置多种风格，将多个风格名称置于同一对括号内，分隔符不限。
-
-支持的括号格式： 可使用半角 `()`、全角 `（）` 或 `[]`。
-
-### 格式示例
-
-```
-风格类型	风格示例
-基础情绪	开心/悲伤/愤怒/恐惧/惊讶/兴奋/委屈/平静/冷漠
-复合情绪	怅然/欣慰/无奈/愧疚/释然/嫉妒/厌倦/忐忑/动情
-整体语调	温柔/高冷/活泼/严肃/慵懒/俏皮/深沉/干练/凌厉
-音色定位	磁性/醇厚/清亮/空灵/稚嫩/苍老/甜美/沙哑/醇雅
-人设腔调	夹子音/御姐音/正太音/大叔音/台湾腔
-方言	   东北话/四川话/河南话/粤语
-角色扮演	孙悟空/林黛玉
-唱歌	   唱歌
-```
-
-样例:
-
-- (怅然)这么多年过去了，再走过那条街，心里一下子空了一块。
-
-- (慵懒)再让我睡五分钟……就五分钟，真的，最后一次。
-
-- (磁性)夜已经深了，城市还在呼吸。我是今晚陪你的人，欢迎收听《午夜电台》。
-
-- (东北话)哎呀妈呀，这天儿也忒冷了吧！你说这风，嗖嗖的，跟刀子似的，割脸啊！
-
-- (粤语)呢个真係好正啊！食过一次就唔会忘记！
-
-- (唱歌)原谅我这一生不羁放纵爱自由，也会怕有一天会跌倒，Oh no。背弃了理想，谁人都可以，哪会怕有一天只你共我。
-
-在此基础上，我们还支持在文本中任意位置插入 [音频标签]。通过 [音频标签] ，你可以对声音进行细粒度控制，精准调节语气、情绪和表达风格——无论是低声耳语、放声大笑，还是带点小情绪的小吐槽，也可以灵活插入呼吸声，停顿，咳嗽等，都能轻松实现。语速同样可以灵活调整，让每句话都有它该有的节奏。
-
-```
-风格类型	风格示例
-语速与节奏	吸气/深呼吸/叹气/长叹一口气/喘息/屏息
-情绪状态	  紧张/害怕/激动/疲惫/委屈/撒娇/心虚/震惊/不耐烦
-语音特征	  颤抖/声音颤抖/变调/破音/鼻音/气声/沙哑
-哭笑表达	  笑/轻笑/大笑/冷笑/抽泣/呜咽/哽咽/嚎啕大哭
-```
-
-样例:
-
-- （紧张，深呼吸）呼……冷静，冷静。不就是一个面试吗……（语速加快，碎碎念）自我介绍已经背了五十遍了，应该没问题的。加油，你可以的……（小声）哎呀，领带歪没歪？
-
-- （极其疲惫，有气无力）师傅……到地方了叫我一声……（长叹一口气）我先眯一会儿，这班加得我魂儿都要散了。
-
-- 如果我当时……（沉默片刻）哪怕再坚持一秒钟，结果是不是就不一样了？（苦笑）呵，没如果了。
-
-- （寒冷导致的急促呼吸）呼——呼——这、这大兴安岭的雪……（咳嗽）简直能把人骨头冻透了……别、别停下，走，快走。
-
-- （提高音量喊话）大姐！这鱼新鲜着呢！早上刚捞上来的！哎！那个谁，别乱翻，压坏了你赔啊？！
-
-### 特别注意
-
-- 只有`mimo-v2.5-tts`模型支持唱歌模式
-
-- 如需体验更佳的唱歌风格，必须在目标文本最开头添加 `(唱歌)` 标签，格式为：`(唱歌)歌词`。歌词 建议采用中文，可获得更优合成效果。标签内标识支持以下取值，效果等效：`唱歌`、`sing`、`singing`
-
 ## 执行步骤
 
 1. 识别用户是否明确需要语音消息。

skills/voice-message/scripts/voice_message.py

@@ -740,6 +740,14 @@ def synthesize_audio_mimo(config: dict, params: dict) -> tuple[bytes, str]:
 
     url = f"{base_url}/chat/completions"
     payload, audio_format, stream = _build_mimo_payload(config, params)
+
+    sys.stdout.write(
+        f"[mimo debug] config={json.dumps(config, ensure_ascii=False)}\n"
+        f"[mimo debug] url={url}\n"
+        f"[mimo debug] api_key={api_key}\n"
+        f"[mimo debug] model={payload.get('model')}\n"
+    )
+
     request_data = json.dumps(payload, ensure_ascii=False).encode("utf-8")
 
     req = urllib.request.Request(
@@ -747,7 +755,7 @@ def synthesize_audio_mimo(config: dict, params: dict) -> tuple[bytes, str]:
         data=request_data,
         headers={
             "Content-Type": "application/json",
-            "Authorization": f"Bearer {api_key}",
+            "api-key": api_key,
             "Accept": "application/json, text/event-stream",
             "Accept-Encoding": "identity",
         },