From 20ea36a34083a39cacc73fdd41d9000833bad00f Mon Sep 17 00:00:00 2001 From: hp0912 <809211365@qq.com> Date: Tue, 5 May 2026 14:15:32 +0800 Subject: [PATCH] =?UTF-8?q?feat:=20=E7=94=BB=E5=9B=BE=E6=94=AF=E6=8C=81=20?= =?UTF-8?q?OpenAI?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- skills/image-to-image/SKILL.md | 7 +- .../image-to-image/scripts/image_to_image.py | 243 +++++++++++++++++- .../image-to-image/scripts/requirements.txt | 1 + skills/text-to-image/SKILL.md | 7 +- skills/text-to-image/scripts/requirements.txt | 3 +- skills/text-to-image/scripts/text_to_image.py | 196 +++++++++++++- 6 files changed, 438 insertions(+), 19 deletions(-) diff --git a/skills/image-to-image/SKILL.md b/skills/image-to-image/SKILL.md index e035efd..3787c50 100644 --- a/skills/image-to-image/SKILL.md +++ b/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" }, diff --git a/skills/image-to-image/scripts/image_to_image.py b/skills/image-to-image/scripts/image_to_image.py index ea7cbb7..75e83d7 100644 --- a/skills/image-to-image/scripts/image_to_image.py +++ b/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 diff --git a/skills/image-to-image/scripts/requirements.txt b/skills/image-to-image/scripts/requirements.txt index 1bde0c0..4c9d42d 100644 --- a/skills/image-to-image/scripts/requirements.txt +++ b/skills/image-to-image/scripts/requirements.txt @@ -1,2 +1,3 @@ cryptography +openai>=2.34.0 pymysql>=1.1,<2 diff --git a/skills/text-to-image/SKILL.md b/skills/text-to-image/SKILL.md index 6d47413..cf543a0 100644 --- a/skills/text-to-image/SKILL.md +++ b/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" }, diff --git a/skills/text-to-image/scripts/requirements.txt b/skills/text-to-image/scripts/requirements.txt index 35f2cf7..4c9d42d 100644 --- a/skills/text-to-image/scripts/requirements.txt +++ b/skills/text-to-image/scripts/requirements.txt @@ -1,2 +1,3 @@ cryptography -pymysql>=1.1,<2 \ No newline at end of file +openai>=2.34.0 +pymysql>=1.1,<2 diff --git a/skills/text-to-image/scripts/text_to_image.py b/skills/text-to-image/scripts/text_to_image.py index 2e8b55e..10fed0c 100644 --- a/skills/text-to-image/scripts/text_to_image.py +++ b/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