AI/ML API as a cloud provider preset

backend/api/v1/settings.py

@@ -50,6 +50,7 @@ def validate_memory(cls, v):
 
 class ApiKeys(BaseModel):
     """API密钥设置"""
+    aimlapi: str = Field(default="", description="AI/ML API 密钥")
     dashscope: str = Field(default="", description="通义千问API密钥")
     openai: str = Field(default="", description="OpenAI API密钥")
     gemini: str = Field(default="", description="Gemini API密钥")
@@ -66,7 +67,7 @@ class ApiKeys(BaseModel):
 class ApiSettings(BaseModel):
     """API设置"""
     api_keys: ApiKeys = Field(default_factory=ApiKeys, description="API密钥")
-    api_provider: str = Field(default="dashscope", description="当前 LLM 提供商（dashscope / openai / gemini / deepseek / seed / kimi / glm / grok，或本地预设 ollama / lmstudio）")
+    api_provider: str = Field(default="dashscope", description="当前 LLM 提供商（dashscope / openai / gemini / aimlapi / deepseek / seed / kimi / glm / grok，或本地预设 ollama / lmstudio）")
     api_base_url: str = Field(default="", description="OpenAI 兼容接口地址；provider=openai 时空为官方地址，本地预设为空时用预设默认地址")
     api_model: str = Field(default="qwen-plus", description="默认模型")
     api_max_tokens: int = Field(default=4096, description="最大Token数")
@@ -250,6 +251,7 @@ async def get_settings():
             ),
             api=ApiSettings(
                 api_keys=ApiKeys(
+                    aimlapi="",
                     dashscope=config.dashscope_api_key,
                     openai=config.openai_api_key,
                     gemini=config.gemini_api_key,
@@ -684,6 +686,7 @@ async def list_backups():
 def _saved_provider_api_key(settings: DesktopSettings, provider: str) -> str:
     keys = settings.api.api_keys
     return {
+        "aimlapi": keys.aimlapi,
         "dashscope": keys.dashscope,
         "openai": keys.openai,
         "gemini": keys.gemini,

backend/cli.py

@@ -198,6 +198,7 @@ def cmd_providers(args: argparse.Namespace) -> int:
     from backend.core.llm_manager import get_llm_manager
 
     rows = [
+        ("aimlapi", "AI/ML API", "需要 key；聚合网关，一个 key 300+ 对话模型，型号按 厂商/型号 命名"),
         ("dashscope", "阿里通义千问", "需要 key；国内直连，qwen-plus 性价比高"),
         ("openai", "OpenAI / 兼容接口", "需要 key；--base-url 可指向 DeepSeek / 智谱 / OpenRouter / vLLM"),
         ("gemini", "Google Gemini", "需要 key"),

backend/core/aimlapi_attribution.py

@@ -0,0 +1,54 @@
+"""
+AI/ML API 归因请求头。
+
+网关只有在请求带上这几个头时才会把调用计到 AutoClip 名下，所以它们要跟着每一次
+打到 api.aimlapi.com 的请求走 —— 也只跟着这些请求走：同一个 `OpenAIProvider`
+还服务 OpenRouter、Ollama、vLLM，把 partner id 发给第三方既不对也没用。
+
+判定按「最终目标地址的主机名」做，只认 `api.aimlapi.com` 本身，不做后缀匹配
+（`api.aimlapi.com.evil.tld` 不是我们）。
+"""
+from __future__ import annotations
+
+from typing import Dict, Optional
+from urllib.parse import urlparse
+
+AIMLAPI_HOST = "api.aimlapi.com"
+AIMLAPI_BASE_URL = "https://api.aimlapi.com/v1"
+
+# 归因来源标识；格式 `agent/<slug>`，与 AI/ML API 侧登记的一致。
+AIMLAPI_SOURCE = "agent/autoclip"
+# 合作伙伴 ID 由 AI/ML API 侧随机生成后登记。留空表示「还没有」——
+# 留空时不发这个头，而不是发一个不存在的值（未知 id 会被静默忽略）。
+AIMLAPI_PARTNER_ID = "part_qVR4oZesx5sRaPUBvUjDQf7p"
+
+_REFERER = "https://github.com/zhouxiaoka/autoclip"
+_TITLE = "AutoClip"
+
+
+def is_aimlapi_url(base_url: Optional[str]) -> bool:
+    """base_url 是否指向 AI/ML API 网关。"""
+    url = (base_url or "").strip()
+    if not url:
+        return False
+    if "://" not in url:
+        url = f"https://{url}"
+    try:
+        host = (urlparse(url).hostname or "").lower()
+    except ValueError:
+        return False
+    return host == AIMLAPI_HOST
+
+
+def aimlapi_headers(base_url: Optional[str]) -> Dict[str, str]:
+    """打 AI/ML API 时返回归因请求头；其它地址返回空字典。"""
+    if not is_aimlapi_url(base_url):
+        return {}
+    headers = {
+        "HTTP-Referer": _REFERER,
+        "X-Title": _TITLE,
+        "X-AIMLAPI-Source": AIMLAPI_SOURCE,
+    }
+    if AIMLAPI_PARTNER_ID:
+        headers["X-AIMLAPI-Partner-ID"] = AIMLAPI_PARTNER_ID
+    return headers

backend/core/cloud_presets.py

@@ -1,5 +1,5 @@
 """
-云端 OpenAI 兼容预设：DeepSeek / Seed / Kimi / GLM / Grok。
+云端 OpenAI 兼容预设：AI/ML API / DeepSeek / Seed / Kimi / GLM / Grok。
 
 底层仍是 openai + 官方 base_url，和 Ollama 预设同一套路，但必须带各家自己的 key，
 不能复用用户的 OpenAI key。设置页、CLI、MCP 都用 `--provider deepseek` 这种名字。
@@ -22,6 +22,15 @@ class CloudPreset:
 
 
 CLOUD_PRESETS: Dict[str, CloudPreset] = {
+    "aimlapi": CloudPreset(
+        key="aimlapi",
+        display_name="AI/ML API",
+        base_url="https://api.aimlapi.com/v1",
+        default_model="openai/gpt-6-luna",
+        api_key_setting="aimlapi_api_key",
+        docs_url="https://aimlapi.com/app/keys",
+        hint="AI/ML API 聚合网关。一个 key 打通 GPT / Claude / Gemini / Qwen / DeepSeek 等 300+ 对话模型。",
+    ),
     "deepseek": CloudPreset(
         key="deepseek",
         display_name="DeepSeek",
@@ -70,6 +79,9 @@ class CloudPreset:
 }
 
 _ALIASES = {
+    "aiml": "aimlapi",
+    "aiml-api": "aimlapi",
+    "aimlapi.com": "aimlapi",
     "deepseek-ai": "deepseek",
     "moonshot": "kimi",
     "moonshotai": "kimi",

backend/core/llm_manager.py

@@ -97,6 +97,7 @@ def _load_settings(self) -> Dict[str, Any]:
             "dashscope_base_url": os.getenv("DASHSCOPE_BASE_URL", ""),
             "gemini_api_key": "",
             "siliconflow_api_key": "",
+            "aimlapi_api_key": "",
             "deepseek_api_key": "",
             "kimi_api_key": "",
             "glm_api_key": "",
@@ -123,6 +124,7 @@ def _load_settings(self) -> Dict[str, Any]:
                             "openai_api_key": api_keys.get("openai", ""),
                             "gemini_api_key": api_keys.get("gemini", ""),
                             "siliconflow_api_key": api_keys.get("siliconflow", ""),
+                            "aimlapi_api_key": api_keys.get("aimlapi", ""),
                             "deepseek_api_key": api_keys.get("deepseek", ""),
                             "kimi_api_key": api_keys.get("kimi", ""),
                             "glm_api_key": api_keys.get("glm", ""),
@@ -193,6 +195,7 @@ def _apply_cloud_preset(self, settings: Dict[str, Any]) -> None:
     # Docker / 本地脚本模式没有设置页可用，只能靠环境变量（env.example 里也是这么写的），
     # 但此前这里只读 settings.json，导致 API_DASHSCOPE_API_KEY 等变量形同虚设。
     _ENV_KEY_FALLBACKS = {
+        "aimlapi_api_key": ("API_AIMLAPI_API_KEY", "AIMLAPI_API_KEY"),
         "dashscope_api_key": ("API_DASHSCOPE_API_KEY", "DASHSCOPE_API_KEY"),
         "openai_api_key": ("API_OPENAI_API_KEY", "OPENAI_API_KEY"),
         "gemini_api_key": ("API_GEMINI_API_KEY", "GEMINI_API_KEY"),

backend/core/llm_providers.py

@@ -11,6 +11,8 @@
 from dataclasses import dataclass
 from pathlib import Path
 
+from backend.core.aimlapi_attribution import aimlapi_headers
+
 logger = logging.getLogger(__name__)
 
 class ProviderType(Enum):
@@ -171,6 +173,7 @@ def call(self, prompt: str, input_data: Any = None, **kwargs) -> LLMResponse:
                     "Authorization": f"Bearer {self.api_key}",
                     "Content-Type": "application/json",
                 }
+                headers.update(aimlapi_headers(self.base_url))
                 payload = {
                     "model": self.model_name,
                     "messages": [{"role": "user", "content": full_input}],
@@ -231,6 +234,12 @@ def get_available_models(self) -> List[ModelInfo]:
         return _catalog_model_infos(ProviderType.DASHSCOPE)
 
 OPENAI_OFFICIAL_BASE_URL = "https://api.openai.com/v1"
+# 连通性测试的输出预算。以前是 1，推理型模型（gpt-6-luna、o 系列等）光思考就超了，
+# 服务端直接 400 "Could not finish the message because max_tokens ... was reached"，
+# 于是 key 明明是好的，设置页却报连接失败。实测 2026-09-23：gpt-6-luna 给 1 个 token 必 400，
+# 给 16 就能返回；claude-sonnet-5 / gemini-3.8-flash / deepseek-v4-pro 给 1 也能过。
+# 留 256 有富余；探针只发两个字，用不到的额度不计费。
+CONNECTION_PROBE_MAX_TOKENS = 256
 # 本地/自建 OpenAI 兼容服务（Ollama、vLLM、LM Studio 等）通常不校验 key，但 SDK 要求非空
 OPENAI_COMPATIBLE_PLACEHOLDER_KEY = "EMPTY"
 # 通义千问 OpenAI 兼容接口：中国站 / 国际站（alibabacloud.com 开通的 key 只能打国际站，#45）
@@ -298,6 +307,10 @@ def __init__(self, api_key: str, model_name: str = "gpt-4o-mini", **kwargs):
                 http_client = make_openai_http_client(self.base_url)
                 if http_client is not None:
                     client_kwargs["http_client"] = http_client
+                # 归因请求头只在目标就是 AI/ML API 时附带，别的兼容接口一律不发
+                attribution = aimlapi_headers(self.base_url)
+                if attribution:
+                    client_kwargs["default_headers"] = attribution
             self.client = openai.OpenAI(**client_kwargs)
         except ImportError:
             raise ImportError("请安装openai: pip install openai")
@@ -343,7 +356,7 @@ def test_connection(self) -> bool:
                     logger.warning(f"OpenAI API Key格式可能不正确，期望以'sk-'开头，实际: {self.api_key[:10]}...")
 
             # 使用最简单的测试
-            response = self.call("测试", max_tokens=1)
+            response = self.call("测试", max_tokens=CONNECTION_PROBE_MAX_TOKENS)
             return response and response.content is not None
         except Exception as e:
             logger.error(f"OpenAI连接测试失败 (base_url={self.base_url or OPENAI_OFFICIAL_BASE_URL}): {e}")

backend/core/model_catalog.py

@@ -18,6 +18,17 @@
 # 各家仍在维护的稳定别名 / 旗舰型号。实时列表失败时用这份，也作为下拉靠前的常用项。
 # 日期以 2026-09 公开文档为准；具体可用性以账号权限为准。
 CURATED_MODELS: Dict[str, List[str]] = {
+    # AI/ML API 是聚合网关：一个 key 覆盖下面各家，型号名带厂商前缀（openai/…、anthropic/…）。
+    "aimlapi": [
+        "openai/gpt-6-luna",
+        "openai/gpt-6.1-sol",
+        "anthropic/claude-sonnet-5.5",
+        "google/gemini-3.8-flash",
+        "deepseek/deepseek-v4-pro",
+        "moonshot/kimi-k3",
+        "zhipu/glm-5.2",
+        "alibaba/qwen3.7-max",
+    ],
     "dashscope": [
         "qwen3.8-max",
         "qwen3.8-flash",
@@ -77,6 +88,7 @@
 }
 
 DEFAULT_MODELS: Dict[str, str] = {
+    "aimlapi": "openai/gpt-6-luna",
     "dashscope": "qwen-plus",
     "openai": "gpt-5-mini",
     "gemini": "gemini-3.8-flash",
@@ -88,6 +100,7 @@
 }
 
 PROVIDER_LABELS: Dict[str, str] = {
+    "aimlapi": "AI/ML API",
     "dashscope": "通义千问",
     "openai": "OpenAI",
     "gemini": "Gemini",
@@ -143,6 +156,9 @@
 _DATED_SNAPSHOT = re.compile(r"^(.+)-(?:\d{4}-\d{2}-\d{2}|\d{8})$")
 
 SILICONFLOW_BASE_URL = "https://api.siliconflow.cn/v1"
+AIMLAPI_MODELS_BASE_URL = "https://api.aimlapi.com/v1"
+# AI/ML API 的 /models 里对话、图像、视频、语音混在一起，id 上看不出来，只有 type 能区分
+AIMLAPI_CHAT_MODEL_TYPE = "openai/chat-completions"
 GEMINI_MODELS_URL = "https://generativelanguage.googleapis.com/v1beta/models"
 
 _CACHE_TTL_SECONDS = 300.0
@@ -303,6 +319,24 @@ async def fetch_openai_compatible_models(base_url: str, api_key: str) -> List[st
     return _extract_openai_model_ids(data)
 
 
+async def fetch_aimlapi_models(api_key: str, base_url: str = "") -> List[str]:
+    """AI/ML API：按 `type` 只留对话模型，否则 900+ 条里大半是图像 / 视频 / 语音。"""
+    from backend.core.llm_providers import normalize_base_url
+
+    url = normalize_base_url(base_url) or AIMLAPI_MODELS_BASE_URL
+    headers = {"Authorization": f"Bearer {api_key}"} if api_key else {}
+    data = await _http_get_json(f"{url}/models", headers=headers)
+    items = data.get("data", data) if isinstance(data, dict) else data
+    names: List[str] = []
+    for item in items or []:
+        if not isinstance(item, dict) or item.get("type") != AIMLAPI_CHAT_MODEL_TYPE:
+            continue
+        name = item.get("id") or item.get("name")
+        if name:
+            names.append(str(name))
+    return names
+
+
 async def fetch_gemini_models(api_key: str) -> List[str]:
     if not api_key:
         raise ValueError("缺少 Gemini API Key")
@@ -349,6 +383,8 @@ def _is_official_openai(base_url: str) -> bool:
 async def fetch_live_models(provider: str, api_key: str = "", base_url: str = "") -> List[str]:
     if provider == "gemini":
         return await fetch_gemini_models(api_key)
+    if provider == "aimlapi":
+        return await fetch_aimlapi_models(api_key, base_url)
     url = _official_base_url(provider, base_url)
     return await fetch_openai_compatible_models(url, api_key)
 

backend/tests/test_cloud_presets.py

@@ -1,4 +1,5 @@
-"""云端兼容预设：DeepSeek / Kimi / GLM / Grok 还原成 openai + 官方地址。"""
+"""云端兼容预设：AI/ML API / DeepSeek / Kimi / GLM / Grok 还原成 openai + 官方地址。"""
+import re
 import sys
 import types
 
@@ -49,6 +50,8 @@ def test_resolve_cloud_presets_use_official_endpoints():
     assert resolve_cloud_preset("xai")[2].key == "grok"
     assert resolve_cloud_preset("doubao")[1] == "https://ark.cn-beijing.volces.com/api/v3"
     assert resolve_cloud_preset("ark")[2].default_model == "doubao-seed-2-1-lite-260915"
+    assert resolve_cloud_preset("aimlapi")[1] == "https://api.aimlapi.com/v1"
+    assert resolve_cloud_preset("aiml-api")[2].key == "aimlapi"
     assert resolve_cloud_preset("dashscope") is None
     assert resolve_cloud_preset("openai") is None
 
@@ -89,4 +92,78 @@ def test_manager_uses_seed_ark_key_not_openai(fake_openai, tmp_path):
 
 def test_curated_lists_drop_retired_aliases():
     assert "gpt-4o" not in CLOUD_PRESETS
-    assert set(CLOUD_PRESETS) == {"deepseek", "seed", "kimi", "glm", "grok"}
+    assert set(CLOUD_PRESETS) == {"aimlapi", "deepseek", "seed", "kimi", "glm", "grok"}
+
+
+def test_manager_uses_aimlapi_key_not_openai(fake_openai, tmp_path):
+    settings = tmp_path / "settings.json"
+    settings.write_text(
+        '{"api": {"api_keys": {"openai": "sk-openai-should-not-be-used", "aimlapi": "aimlapi-official-key"}, '
+        '"api_provider": "aimlapi", "api_model": "openai/gpt-6-luna"}}',
+        encoding="utf-8",
+    )
+    info = LLMManager(settings_file=settings).get_current_provider_info()
+    assert info["provider"] == "aimlapi"
+    assert info["backend_provider"] == "openai"
+    assert info["base_url"] == "https://api.aimlapi.com/v1"
+    assert info["model"] == "openai/gpt-6-luna"
+    assert info["available"] is True
+    assert fake_openai.created[-1]["api_key"] == "aimlapi-official-key"
+    assert fake_openai.created[-1]["base_url"] == "https://api.aimlapi.com/v1"
+
+
+def test_aimlapi_client_carries_attribution_headers(fake_openai, tmp_path):
+    """归因头必须真的挂到 OpenAI 客户端上，否则网关那边这些调用不算 AutoClip 的。"""
+    from backend.core.aimlapi_attribution import AIMLAPI_PARTNER_ID
+
+    settings = tmp_path / "settings.json"
+    settings.write_text(
+        '{"api": {"api_keys": {"aimlapi": "aimlapi-official-key"}, "api_provider": "aimlapi"}}',
+        encoding="utf-8",
+    )
+    LLMManager(settings_file=settings)
+    headers = fake_openai.created[-1].get("default_headers") or {}
+    assert headers.get("X-AIMLAPI-Source") == "agent/autoclip"
+    assert headers.get("X-Title") == "AutoClip"
+    assert headers.get("HTTP-Referer") == "https://github.com/zhouxiaoka/autoclip"
+    # partner id 还没登记时不发空值；登记后必须是网关认的格式
+    if AIMLAPI_PARTNER_ID:
+        assert headers.get("X-AIMLAPI-Partner-ID") == AIMLAPI_PARTNER_ID
+        assert re.fullmatch(r"part_[A-Za-z0-9]{1,64}", AIMLAPI_PARTNER_ID)
+    else:
+        assert "X-AIMLAPI-Partner-ID" not in headers
+
+
+def test_other_openai_compatible_endpoints_get_no_attribution(fake_openai, tmp_path):
+    """OpenRouter / 本地服务不该收到我们的 partner id。"""
+    settings = tmp_path / "settings.json"
+    settings.write_text(
+        '{"api": {"api_keys": {"openai": "sk-openrouter"}, "api_provider": "openai", '
+        '"api_base_url": "https://openrouter.ai/api/v1", "api_model": "qwen/qwen3-235b-a22b"}}',
+        encoding="utf-8",
+    )
+    LLMManager(settings_file=settings)
+    created = fake_openai.created[-1]
+    assert created["base_url"] == "https://openrouter.ai/api/v1"
+    assert "default_headers" not in created
+
+
+@pytest.mark.parametrize(
+    "url, expected",
+    [
+        ("https://api.aimlapi.com/v1", True),
+        ("api.aimlapi.com/v1", True),
+        ("https://API.AIMLAPI.COM/v1", True),
+        ("https://api.aimlapi.com.evil.tld/v1", False),
+        ("https://notapi.aimlapi.com/v1", False),
+        ("https://openrouter.ai/api/v1", False),
+        ("http://localhost:11434/v1", False),
+        ("", False),
+        (None, False),
+    ],
+)
+def test_attribution_host_gate_is_exact(url, expected):
+    from backend.core.aimlapi_attribution import aimlapi_headers, is_aimlapi_url
+
+    assert is_aimlapi_url(url) is expected
+    assert bool(aimlapi_headers(url)) is expected