feat: 画图支持 OpenAI

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）。
+支持多个绘图模型：即梦（JiMeng）、豆包（DouBao）、造相（Z-Image）、OpenAI GPT 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。
 
@@ -37,7 +37,7 @@ 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)。",
+      "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) / OpenAI GPT Image(gpt-image-2)，默认: 空(none)。",
       "enum": [
         "none",
         "jimeng-4.5",
@@ -46,7 +46,8 @@ argument-hint: "需要 prompt（提示词）和 images（图片链接列表）
         "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

@@ -3,13 +3,17 @@
 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
 
@@ -67,6 +71,7 @@ _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()
@@ -167,6 +172,188 @@ 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")
+
+    kwargs: dict[str, str | float] = {"api_key": api_key}
+    base_url = str(config.get("base_url", "") or "").strip()
+    if base_url:
+        kwargs["base_url"] = base_url
+    organization = str(config.get("organization", "") or "").strip()
+    if organization:
+        kwargs["organization"] = organization
+    project = str(config.get("project", "") or "").strip()
+    if project:
+        kwargs["project"] = project
+    timeout_value = config.get("timeout")
+    if timeout_value not in (None, ""):
+        kwargs["timeout"] = float(timeout_value)
+
+    return OpenAI(**kwargs)
+
+
+def _openai_image_suffix(output_format: str) -> str:
+    if output_format == "jpeg":
+        return ".jpg"
+    return f".{output_format}"
+
+
+def _write_openai_image_file(b64_json: str, output_format: str) -> str:
+    image_bytes = base64.b64decode(b64_json)
+    with tempfile.NamedTemporaryFile(
+        prefix="wechat-openai-image-",
+        suffix=_openai_image_suffix(output_format),
+        delete=False,
+    ) as image_file:
+        image_file.write(image_bytes)
+        return image_file.name
+
+
+def _openai_images_from_response(response, output_format: str) -> list[str]:
+    outputs: list[str] = []
+    for item in getattr(response, "data", []) or []:
+        b64_json = getattr(item, "b64_json", None)
+        if b64_json:
+            outputs.append(_write_openai_image_file(b64_json, output_format))
+            continue
+        url = getattr(item, "url", None)
+        if url:
+            outputs.append(url)
+    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,
+        }
+        _http_post_json(send_url, send_body, {"Content-Type": "application/json"}, timeout=60)
+
+    if 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": local_paths,
+        }
+        _http_post_json(send_url, send_body, {"Content-Type": "application/json"}, timeout=60)
+
+
+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)."""
@@ -309,6 +496,44 @@ 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()
+
+    return _openai_images_from_response(response, output_format)
+
+
 # ---------------------------------------------------------------------------
 # Main
 # ---------------------------------------------------------------------------
@@ -316,6 +541,7 @@ def call_zimage(config: dict, prompt: str, model: str, images: list[str]) -> lis
 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:
@@ -424,6 +650,13 @@ 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
@@ -439,20 +672,18 @@ 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:
-        _http_post_json(send_url, send_body, {"Content-Type": "application/json"}, timeout=60)
+        _send_image_outputs(client_port, from_wx_id, image_urls)
         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

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

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）。
+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。
 
 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。
 
@@ -35,7 +35,7 @@ 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)。",
+      "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) / OpenAI GPT Image(gpt-image-2)，默认: 空(none)。",
       "enum": [
         "none",
         "jimeng-4.5",
@@ -47,7 +47,8 @@ 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

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

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

@@ -3,13 +3,16 @@
 from __future__ import annotations
 
 import argparse
+import base64
 import json
 import os
 import re
 import subprocess
 import sys
+import tempfile
 import time
 import traceback
+import urllib.parse
 import urllib.request
 from pathlib import Path
 
@@ -67,6 +70,7 @@ _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()
@@ -169,6 +173,152 @@ 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")
+
+    kwargs: dict[str, str | float] = {"api_key": api_key}
+    base_url = str(config.get("base_url", "") or "").strip()
+    if base_url:
+        kwargs["base_url"] = base_url
+    organization = str(config.get("organization", "") or "").strip()
+    if organization:
+        kwargs["organization"] = organization
+    project = str(config.get("project", "") or "").strip()
+    if project:
+        kwargs["project"] = project
+    timeout_value = config.get("timeout")
+    if timeout_value not in (None, ""):
+        kwargs["timeout"] = float(timeout_value)
+
+    return OpenAI(**kwargs)
+
+
+def _openai_image_suffix(output_format: str) -> str:
+    if output_format == "jpeg":
+        return ".jpg"
+    return f".{output_format}"
+
+
+def _write_openai_image_file(b64_json: str, output_format: str) -> str:
+    image_bytes = base64.b64decode(b64_json)
+    with tempfile.NamedTemporaryFile(
+        prefix="wechat-openai-image-",
+        suffix=_openai_image_suffix(output_format),
+        delete=False,
+    ) as image_file:
+        image_file.write(image_bytes)
+        return image_file.name
+
+
+def _openai_images_from_response(response, output_format: str) -> list[str]:
+    outputs: list[str] = []
+    for item in getattr(response, "data", []) or []:
+        b64_json = getattr(item, "b64_json", None)
+        if b64_json:
+            outputs.append(_write_openai_image_file(b64_json, output_format))
+            continue
+        url = getattr(item, "url", None)
+        if url:
+            outputs.append(url)
+    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,
+        }
+        _http_post_json(send_url, send_body, {"Content-Type": "application/json"}, timeout=60)
+
+    if 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": local_paths,
+        }
+        _http_post_json(send_url, send_body, {"Content-Type": "application/json"}, timeout=60)
+
+
+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."""
@@ -315,6 +465,34 @@ 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)
+    return _openai_images_from_response(response, output_format)
+
+
 # ---------------------------------------------------------------------------
 # Main
 # ---------------------------------------------------------------------------
@@ -322,6 +500,7 @@ def call_zimage(config: dict, prompt: str, model: str) -> list[str]:
 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]:
@@ -423,6 +602,13 @@ 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
@@ -438,20 +624,18 @@ 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:
-        _http_post_json(send_url, send_body, {"Content-Type": "application/json"}, timeout=60)
+        _send_image_outputs(client_port, from_wx_id, image_urls)
         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