feat: add aliyun quota fallback
This commit is contained in:
parent
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@ -1,9 +1,32 @@
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import os
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from pathlib import Path
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from typing import Optional
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def _env(name: str, default: str = "") -> str:
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return os.environ.get(name, default)
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def _env_optional(name: str) -> Optional[str]:
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value = os.environ.get(name)
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if value is None:
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# 回退读取 .env（支持运行中更新）
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env_path = Path(__file__).resolve().parents[1] / ".env"
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if env_path.exists():
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try:
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for raw_line in env_path.read_text(encoding="utf-8").splitlines():
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line = raw_line.strip()
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if not line or line.startswith("#") or "=" not in line:
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continue
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key, val = line.split("=", 1)
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if key.strip() == name:
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value = val.strip().strip('"').strip("'")
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break
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except Exception:
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value = None
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if value is None:
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return None
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value = value.strip()
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return value or None
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# 模型上下文窗口（单位: token）
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CONTEXT_WINDOWS = {
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@ -19,6 +42,8 @@ CONTEXT_WINDOWS = {
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# 默认（Kimi）
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KIMI_BASE = _env("API_BASE_KIMI", _env("AGENT_API_BASE_URL", "https://api.moonshot.cn/v1"))
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KIMI_KEY = _env("API_KEY_KIMI", _env("AGENT_API_KEY", ""))
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KIMI_BASE_OFFICIAL = _env_optional("API_BASE_KIMI_OFFICIAL")
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KIMI_KEY_OFFICIAL = _env_optional("API_KEY_KIMI_OFFICIAL")
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KIMI_FAST_MODEL = _env("MODEL_KIMI_FAST", _env("AGENT_MODEL_ID", "kimi-k2-0905-preview"))
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KIMI_THINK_MODEL = _env("MODEL_KIMI_THINK", _env("AGENT_THINKING_MODEL_ID", "kimi-k2-thinking"))
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KIMI_25_MODEL = _env("MODEL_KIMI_25", "kimi-k2.5")
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@ -32,12 +57,16 @@ DEEPSEEK_THINK_MODEL = _env("MODEL_DEEPSEEK_THINK", "deepseek-reasoner")
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# Qwen
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QWEN_BASE = _env("API_BASE_QWEN", "https://dashscope.aliyuncs.com/compatible-mode/v1")
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QWEN_KEY = _env("API_KEY_QWEN", _env("DASHSCOPE_API_KEY", ""))
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QWEN_BASE_OFFICIAL = _env_optional("API_BASE_QWEN_OFFICIAL")
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QWEN_KEY_OFFICIAL = _env_optional("API_KEY_QWEN_OFFICIAL")
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QWEN_MAX_MODEL = _env("MODEL_QWEN_MAX", "qwen3-max")
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QWEN_VL_MODEL = _env("MODEL_QWEN_VL", "qwen3.5-plus")
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# MiniMax
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MINIMAX_BASE = _env("API_BASE_MINIMAX", "https://api.minimaxi.com/v1")
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MINIMAX_KEY = _env("API_KEY_MINIMAX", "")
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MINIMAX_BASE_OFFICIAL = _env_optional("API_BASE_MINIMAX_OFFICIAL")
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MINIMAX_KEY_OFFICIAL = _env_optional("API_KEY_MINIMAX_OFFICIAL")
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MINIMAX_MODEL = _env("MODEL_MINIMAX", "MiniMax-M2.5")
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@ -78,7 +107,7 @@ MODEL_PROFILES = {
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"model_id": KIMI_25_MODEL,
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"max_tokens": None,
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"context_window": CONTEXT_WINDOWS["kimi-k2.5"],
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"extra_params": {"thinking": {"type": "enabled"}}
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"extra_params": {"thinking": {"type": "enabled"}, "enable_thinking": True}
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},
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"supports_thinking": True,
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"fast_only": False,
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@ -204,6 +233,45 @@ def get_model_profile(key: str) -> dict:
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if key not in MODEL_PROFILES:
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raise ValueError(f"未知模型 key: {key}")
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profile = MODEL_PROFILES[key]
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try:
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from utils.aliyun_fallback import is_fallback_active
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except Exception:
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is_fallback_active = None
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if is_fallback_active and is_fallback_active(key):
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if key == "kimi-k2.5":
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kimi_base_official = _env_optional("API_BASE_KIMI_OFFICIAL") or KIMI_BASE_OFFICIAL
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kimi_key_official = _env_optional("API_KEY_KIMI_OFFICIAL") or KIMI_KEY_OFFICIAL
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if kimi_base_official and kimi_key_official:
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profile = dict(profile)
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fast = dict(profile.get("fast") or {})
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thinking = dict(profile.get("thinking") or fast)
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fast.update({"base_url": kimi_base_official, "api_key": kimi_key_official})
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thinking.update({"base_url": kimi_base_official, "api_key": kimi_key_official})
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profile["fast"] = fast
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profile["thinking"] = thinking
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elif key == "qwen3-vl-plus":
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qwen_base_official = _env_optional("API_BASE_QWEN_OFFICIAL") or QWEN_BASE_OFFICIAL
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qwen_key_official = _env_optional("API_KEY_QWEN_OFFICIAL") or QWEN_KEY_OFFICIAL
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if qwen_base_official and qwen_key_official:
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profile = dict(profile)
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fast = dict(profile.get("fast") or {})
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thinking = dict(profile.get("thinking") or fast)
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fast.update({"base_url": qwen_base_official, "api_key": qwen_key_official})
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thinking.update({"base_url": qwen_base_official, "api_key": qwen_key_official})
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profile["fast"] = fast
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profile["thinking"] = thinking
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elif key == "minimax-m2.5":
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minimax_base_official = _env_optional("API_BASE_MINIMAX_OFFICIAL") or MINIMAX_BASE_OFFICIAL
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minimax_key_official = _env_optional("API_KEY_MINIMAX_OFFICIAL") or MINIMAX_KEY_OFFICIAL
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if minimax_base_official and minimax_key_official:
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profile = dict(profile)
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fast = dict(profile.get("fast") or {})
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thinking = dict(profile.get("thinking") or fast)
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fast.update({"base_url": minimax_base_official, "api_key": minimax_key_official})
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thinking.update({"base_url": minimax_base_official, "api_key": minimax_key_official})
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profile["fast"] = fast
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profile["thinking"] = thinking
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# 基础校验：必须有 fast 段且有 key
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fast = profile.get("fast") or {}
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if not fast.get("api_key"):
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40
scripts/mock_aliyun_quota_server.py
Normal file
40
scripts/mock_aliyun_quota_server.py
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@ -0,0 +1,40 @@
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from http.server import BaseHTTPRequestHandler, HTTPServer
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import json
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HOST = "0.0.0.0"
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PORT = 8899
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ERROR_MESSAGE = "hour allocated quota exceeded"
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class Handler(BaseHTTPRequestHandler):
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def _send(self, code: int, payload: dict):
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body = json.dumps(payload).encode("utf-8")
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self.send_response(code)
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self.send_header("Content-Type", "application/json; charset=utf-8")
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self.send_header("Content-Length", str(len(body)))
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self.end_headers()
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self.wfile.write(body)
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def do_POST(self):
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# Consume request body to avoid broken pipe on clients
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try:
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length = int(self.headers.get("Content-Length", "0"))
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except ValueError:
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length = 0
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if length:
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_ = self.rfile.read(length)
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payload = {
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"error": {
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"message": ERROR_MESSAGE,
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"type": "quota_exceeded"
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}
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}
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self._send(429, payload)
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def log_message(self, format, *args):
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return
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if __name__ == "__main__":
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server = HTTPServer((HOST, PORT), Handler)
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print(f"mock aliyun quota server running on http://{HOST}:{PORT}")
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server.serve_forever()
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@ -505,6 +505,11 @@ async def handle_task_with_sender(terminal: WebTerminal, workspace: UserWorkspac
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context = web_terminal.build_context()
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messages = web_terminal.build_messages(context, message)
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tools = web_terminal.define_tools()
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try:
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profile = get_model_profile(getattr(web_terminal, "model_key", None) or "kimi-k2.5")
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web_terminal.apply_model_profile(profile)
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except Exception as exc:
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debug_log(f"更新模型配置失败: {exc}")
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# === 上下文预算与安全校验（避免超出模型上下文） ===
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max_context_tokens = get_model_context_window(getattr(web_terminal, "model_key", None) or "kimi-k2.5")
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@ -559,6 +564,8 @@ async def handle_task_with_sender(terminal: WebTerminal, workspace: UserWorkspac
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# 设置最大迭代次数（API 可覆盖）
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max_iterations = getattr(web_terminal, "max_iterations_override", None) or MAX_ITERATIONS_PER_TASK
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max_api_retries = 4
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retry_delay_seconds = 10
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pending_append = None # {"path": str, "tool_call_id": str, "buffer": str, ...}
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append_probe_buffer = ""
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@ -1199,6 +1206,25 @@ async def handle_task_with_sender(terminal: WebTerminal, workspace: UserWorkspac
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})
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maybe_mark_failure_from_message(web_terminal, message)
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async def _wait_retry_delay(delay_seconds: int) -> bool:
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"""等待重试间隔，同时检查是否收到停止请求。"""
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if delay_seconds <= 0:
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return False
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deadline = time.time() + delay_seconds
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while time.time() < deadline:
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client_stop_info = get_stop_flag(client_sid, username)
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if client_stop_info:
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stop_requested = client_stop_info.get('stop', False) if isinstance(client_stop_info, dict) else client_stop_info
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if stop_requested:
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sender('task_stopped', {
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'message': '命令执行被用户取消',
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'reason': 'user_stop'
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})
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clear_stop_flag(client_sid, username)
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return True
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await asyncio.sleep(0.2)
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return False
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for iteration in range(max_iterations):
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total_iterations += 1
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debug_log(f"\n--- 迭代 {iteration + 1}/{max_iterations} 开始 ---")
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@ -1293,308 +1319,393 @@ async def handle_task_with_sender(terminal: WebTerminal, workspace: UserWorkspac
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print(f"[API] 第{iteration + 1}次调用 (总工具调用: {total_tool_calls}/{MAX_TOTAL_TOOL_CALLS})")
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# 收集流式响应
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async for chunk in web_terminal.api_client.chat(messages, tools, stream=True):
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chunk_count += 1
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api_error = None
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for api_attempt in range(max_api_retries + 1):
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api_error = None
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if api_attempt > 0:
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full_response = ""
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tool_calls = []
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current_thinking = ""
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detected_tools = {}
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last_usage_payload = None
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in_thinking = False
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thinking_started = False
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thinking_ended = False
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text_started = False
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text_has_content = False
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text_streaming = False
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text_chunk_index = 0
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last_text_chunk_time = None
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chunk_count = 0
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reasoning_chunks = 0
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content_chunks = 0
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tool_chunks = 0
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append_break_triggered = False
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append_result = {"handled": False}
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modify_break_triggered = False
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modify_result = {"handled": False}
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last_finish_reason = None
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# 检查停止标志
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client_stop_info = get_stop_flag(client_sid, username)
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if client_stop_info:
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stop_requested = client_stop_info.get('stop', False) if isinstance(client_stop_info, dict) else client_stop_info
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if stop_requested:
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debug_log(f"检测到停止请求，中断流处理")
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if pending_append:
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append_result = await finalize_pending_append(full_response, False, finish_reason="user_stop")
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if pending_modify:
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modify_result = await finalize_pending_modify(full_response, False, finish_reason="user_stop")
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_cancel_pending_tools(tool_calls)
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sender('task_stopped', {
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'message': '命令执行被用户取消',
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'reason': 'user_stop'
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})
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clear_stop_flag(client_sid, username)
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return
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# 收集流式响应
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async for chunk in web_terminal.api_client.chat(messages, tools, stream=True):
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chunk_count += 1
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# 先尝试记录 usage（有些平台会在最后一个 chunk 里携带 usage 但 choices 为空）
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usage_info = chunk.get("usage")
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if usage_info:
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last_usage_payload = usage_info
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# 检查停止标志
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client_stop_info = get_stop_flag(client_sid, username)
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if client_stop_info:
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stop_requested = client_stop_info.get('stop', False) if isinstance(client_stop_info, dict) else client_stop_info
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if stop_requested:
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debug_log(f"检测到停止请求，中断流处理")
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if pending_append:
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append_result = await finalize_pending_append(full_response, False, finish_reason="user_stop")
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if pending_modify:
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modify_result = await finalize_pending_modify(full_response, False, finish_reason="user_stop")
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_cancel_pending_tools(tool_calls)
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sender('task_stopped', {
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'message': '命令执行被用户取消',
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'reason': 'user_stop'
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})
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clear_stop_flag(client_sid, username)
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return
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if "choices" not in chunk:
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debug_log(f"Chunk {chunk_count}: 无choices字段")
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continue
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if not chunk.get("choices"):
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debug_log(f"Chunk {chunk_count}: choices为空列表")
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continue
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choice = chunk["choices"][0]
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if not usage_info and isinstance(choice, dict) and choice.get("usage"):
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# 兼容部分供应商将 usage 放在 choice 内的格式（例如部分 Kimi/Qwen 返回）
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last_usage_payload = choice.get("usage")
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delta = choice.get("delta", {})
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finish_reason = choice.get("finish_reason")
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if finish_reason:
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last_finish_reason = finish_reason
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if isinstance(chunk, dict) and chunk.get("error"):
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api_error = chunk.get("error")
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break
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# 处理思考内容（兼容 reasoning_content / reasoning_details）
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reasoning_content = ""
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if "reasoning_content" in delta:
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reasoning_content = delta.get("reasoning_content") or ""
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elif "reasoning_details" in delta:
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details = delta.get("reasoning_details")
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if isinstance(details, list):
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parts = []
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for item in details:
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if isinstance(item, dict):
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text = item.get("text")
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if text:
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parts.append(text)
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if parts:
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reasoning_content = "".join(parts)
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if reasoning_content:
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reasoning_chunks += 1
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debug_log(f" 思考内容 #{reasoning_chunks}: {len(reasoning_content)} 字符")
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# 先尝试记录 usage（有些平台会在最后一个 chunk 里携带 usage 但 choices 为空）
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usage_info = chunk.get("usage")
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if usage_info:
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last_usage_payload = usage_info
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if not thinking_started:
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in_thinking = True
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thinking_started = True
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sender('thinking_start', {})
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await asyncio.sleep(0.05)
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if "choices" not in chunk:
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debug_log(f"Chunk {chunk_count}: 无choices字段")
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continue
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if not chunk.get("choices"):
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debug_log(f"Chunk {chunk_count}: choices为空列表")
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continue
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choice = chunk["choices"][0]
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if not usage_info and isinstance(choice, dict) and choice.get("usage"):
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# 兼容部分供应商将 usage 放在 choice 内的格式（例如部分 Kimi/Qwen 返回）
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last_usage_payload = choice.get("usage")
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delta = choice.get("delta", {})
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finish_reason = choice.get("finish_reason")
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if finish_reason:
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last_finish_reason = finish_reason
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current_thinking += reasoning_content
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sender('thinking_chunk', {'content': reasoning_content})
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# 处理思考内容（兼容 reasoning_content / reasoning_details）
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reasoning_content = ""
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if "reasoning_content" in delta:
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reasoning_content = delta.get("reasoning_content") or ""
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elif "reasoning_details" in delta:
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details = delta.get("reasoning_details")
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if isinstance(details, list):
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parts = []
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for item in details:
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if isinstance(item, dict):
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text = item.get("text")
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if text:
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parts.append(text)
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if parts:
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reasoning_content = "".join(parts)
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if reasoning_content:
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reasoning_chunks += 1
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debug_log(f" 思考内容 #{reasoning_chunks}: {len(reasoning_content)} 字符")
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# 处理正常内容
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if "content" in delta:
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content = delta["content"]
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if content:
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content_chunks += 1
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debug_log(f" 正式内容 #{content_chunks}: {repr(content[:100] if content else 'None')}")
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if not thinking_started:
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in_thinking = True
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thinking_started = True
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sender('thinking_start', {})
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await asyncio.sleep(0.05)
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if in_thinking and not thinking_ended:
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in_thinking = False
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thinking_ended = True
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sender('thinking_end', {'full_content': current_thinking})
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await asyncio.sleep(0.1)
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current_thinking += reasoning_content
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sender('thinking_chunk', {'content': reasoning_content})
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# 处理正常内容
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if "content" in delta:
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content = delta["content"]
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if content:
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content_chunks += 1
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debug_log(f" 正式内容 #{content_chunks}: {repr(content[:100] if content else 'None')}")
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if in_thinking and not thinking_ended:
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in_thinking = False
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thinking_ended = True
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sender('thinking_end', {'full_content': current_thinking})
|
||||
await asyncio.sleep(0.1)
|
||||
|
||||
|
||||
expecting_modify = bool(pending_modify) or bool(getattr(web_terminal, "pending_modify_request", None))
|
||||
expecting_append = bool(pending_append) or bool(getattr(web_terminal, "pending_append_request", None))
|
||||
expecting_modify = bool(pending_modify) or bool(getattr(web_terminal, "pending_modify_request", None))
|
||||
expecting_append = bool(pending_append) or bool(getattr(web_terminal, "pending_append_request", None))
|
||||
|
||||
if pending_modify:
|
||||
if not pending_modify.get("start_seen"):
|
||||
probe_buffer = pending_modify.get("probe_buffer", "") + content
|
||||
if len(probe_buffer) > 10000:
|
||||
probe_buffer = probe_buffer[-10000:]
|
||||
marker = pending_modify.get("start_marker")
|
||||
marker_index = probe_buffer.find(marker)
|
||||
if marker_index == -1:
|
||||
pending_modify["probe_buffer"] = probe_buffer
|
||||
continue
|
||||
after_marker = marker_index + len(marker)
|
||||
remainder = probe_buffer[after_marker:]
|
||||
pending_modify["buffer"] = remainder
|
||||
pending_modify["raw_buffer"] = marker + remainder
|
||||
pending_modify["start_seen"] = True
|
||||
pending_modify["detected_blocks"] = set()
|
||||
pending_modify["probe_buffer"] = ""
|
||||
if pending_modify.get("display_id"):
|
||||
sender('update_action', {
|
||||
'id': pending_modify["display_id"],
|
||||
'status': 'running',
|
||||
'preparing_id': pending_modify.get("tool_call_id"),
|
||||
'message': f"正在修改 {pending_modify['path']}..."
|
||||
})
|
||||
else:
|
||||
pending_modify["buffer"] += content
|
||||
pending_modify["raw_buffer"] += content
|
||||
|
||||
if pending_modify.get("start_seen"):
|
||||
block_text = pending_modify["buffer"]
|
||||
for match in re.finditer(r"\[replace:(\d+)\]", block_text):
|
||||
try:
|
||||
block_index = int(match.group(1))
|
||||
except ValueError:
|
||||
if pending_modify:
|
||||
if not pending_modify.get("start_seen"):
|
||||
probe_buffer = pending_modify.get("probe_buffer", "") + content
|
||||
if len(probe_buffer) > 10000:
|
||||
probe_buffer = probe_buffer[-10000:]
|
||||
marker = pending_modify.get("start_marker")
|
||||
marker_index = probe_buffer.find(marker)
|
||||
if marker_index == -1:
|
||||
pending_modify["probe_buffer"] = probe_buffer
|
||||
continue
|
||||
detected_blocks = pending_modify.setdefault("detected_blocks", set())
|
||||
if block_index not in detected_blocks:
|
||||
detected_blocks.add(block_index)
|
||||
if pending_modify.get("display_id"):
|
||||
sender('update_action', {
|
||||
'id': pending_modify["display_id"],
|
||||
'status': 'running',
|
||||
'preparing_id': pending_modify.get("tool_call_id"),
|
||||
'message': f"正在对 {pending_modify['path']} 进行第 {block_index} 处修改..."
|
||||
})
|
||||
after_marker = marker_index + len(marker)
|
||||
remainder = probe_buffer[after_marker:]
|
||||
pending_modify["buffer"] = remainder
|
||||
pending_modify["raw_buffer"] = marker + remainder
|
||||
pending_modify["start_seen"] = True
|
||||
pending_modify["detected_blocks"] = set()
|
||||
pending_modify["probe_buffer"] = ""
|
||||
if pending_modify.get("display_id"):
|
||||
sender('update_action', {
|
||||
'id': pending_modify["display_id"],
|
||||
'status': 'running',
|
||||
'preparing_id': pending_modify.get("tool_call_id"),
|
||||
'message': f"正在修改 {pending_modify['path']}..."
|
||||
})
|
||||
else:
|
||||
pending_modify["buffer"] += content
|
||||
pending_modify["raw_buffer"] += content
|
||||
|
||||
if pending_modify.get("start_seen"):
|
||||
end_pos = pending_modify["buffer"].find(pending_modify["end_marker"])
|
||||
if end_pos != -1:
|
||||
pending_modify["end_index"] = end_pos
|
||||
modify_break_triggered = True
|
||||
debug_log("检测到<<<END_MODIFY>>>，即将终止流式输出并应用修改")
|
||||
break
|
||||
continue
|
||||
elif expecting_modify:
|
||||
modify_probe_buffer += content
|
||||
if len(modify_probe_buffer) > 10000:
|
||||
modify_probe_buffer = modify_probe_buffer[-10000:]
|
||||
if pending_modify.get("start_seen"):
|
||||
block_text = pending_modify["buffer"]
|
||||
for match in re.finditer(r"\[replace:(\d+)\]", block_text):
|
||||
try:
|
||||
block_index = int(match.group(1))
|
||||
except ValueError:
|
||||
continue
|
||||
detected_blocks = pending_modify.setdefault("detected_blocks", set())
|
||||
if block_index not in detected_blocks:
|
||||
detected_blocks.add(block_index)
|
||||
if pending_modify.get("display_id"):
|
||||
sender('update_action', {
|
||||
'id': pending_modify["display_id"],
|
||||
'status': 'running',
|
||||
'preparing_id': pending_modify.get("tool_call_id"),
|
||||
'message': f"正在对 {pending_modify['path']} 进行第 {block_index} 处修改..."
|
||||
})
|
||||
|
||||
marker_match = re.search(r"<<<MODIFY:\s*([\s\S]*?)>>>", modify_probe_buffer)
|
||||
if marker_match:
|
||||
detected_raw_path = marker_match.group(1)
|
||||
detected_path = detected_raw_path.strip()
|
||||
marker_full = marker_match.group(0)
|
||||
after_marker_index = modify_probe_buffer.find(marker_full) + len(marker_full)
|
||||
remainder = modify_probe_buffer[after_marker_index:]
|
||||
modify_probe_buffer = ""
|
||||
if pending_modify.get("start_seen"):
|
||||
end_pos = pending_modify["buffer"].find(pending_modify["end_marker"])
|
||||
if end_pos != -1:
|
||||
pending_modify["end_index"] = end_pos
|
||||
modify_break_triggered = True
|
||||
debug_log("检测到<<<END_MODIFY>>>，即将终止流式输出并应用修改")
|
||||
break
|
||||
continue
|
||||
elif expecting_modify:
|
||||
modify_probe_buffer += content
|
||||
if len(modify_probe_buffer) > 10000:
|
||||
modify_probe_buffer = modify_probe_buffer[-10000:]
|
||||
|
||||
if not detected_path:
|
||||
debug_log("检测到 MODIFY 起始标记但路径为空，忽略。")
|
||||
continue
|
||||
marker_match = re.search(r"<<<MODIFY:\s*([\s\S]*?)>>>", modify_probe_buffer)
|
||||
if marker_match:
|
||||
detected_raw_path = marker_match.group(1)
|
||||
detected_path = detected_raw_path.strip()
|
||||
marker_full = marker_match.group(0)
|
||||
after_marker_index = modify_probe_buffer.find(marker_full) + len(marker_full)
|
||||
remainder = modify_probe_buffer[after_marker_index:]
|
||||
modify_probe_buffer = ""
|
||||
|
||||
pending_modify = {
|
||||
"path": detected_path,
|
||||
"tool_call_id": None,
|
||||
"buffer": remainder,
|
||||
"raw_buffer": marker_full + remainder,
|
||||
"start_marker": marker_full,
|
||||
"end_marker": "<<<END_MODIFY>>>",
|
||||
"start_seen": True,
|
||||
"end_index": None,
|
||||
"display_id": None,
|
||||
"detected_blocks": set()
|
||||
}
|
||||
if hasattr(web_terminal, "pending_modify_request"):
|
||||
web_terminal.pending_modify_request = {"path": detected_path}
|
||||
debug_log(f"直接检测到modify起始标记，构建修改缓冲: {detected_path}")
|
||||
if not detected_path:
|
||||
debug_log("检测到 MODIFY 起始标记但路径为空，忽略。")
|
||||
continue
|
||||
|
||||
end_pos = pending_modify["buffer"].find(pending_modify["end_marker"])
|
||||
if end_pos != -1:
|
||||
pending_modify["end_index"] = end_pos
|
||||
modify_break_triggered = True
|
||||
debug_log("检测到<<<END_MODIFY>>>，即将终止流式输出并应用修改")
|
||||
break
|
||||
continue
|
||||
pending_modify = {
|
||||
"path": detected_path,
|
||||
"tool_call_id": None,
|
||||
"buffer": remainder,
|
||||
"raw_buffer": marker_full + remainder,
|
||||
"start_marker": marker_full,
|
||||
"end_marker": "<<<END_MODIFY>>>",
|
||||
"start_seen": True,
|
||||
"end_index": None,
|
||||
"display_id": None,
|
||||
"detected_blocks": set()
|
||||
}
|
||||
if hasattr(web_terminal, "pending_modify_request"):
|
||||
web_terminal.pending_modify_request = {"path": detected_path}
|
||||
debug_log(f"直接检测到modify起始标记，构建修改缓冲: {detected_path}")
|
||||
|
||||
if pending_append:
|
||||
pending_append["buffer"] += content
|
||||
end_pos = pending_modify["buffer"].find(pending_modify["end_marker"])
|
||||
if end_pos != -1:
|
||||
pending_modify["end_index"] = end_pos
|
||||
modify_break_triggered = True
|
||||
debug_log("检测到<<<END_MODIFY>>>，即将终止流式输出并应用修改")
|
||||
break
|
||||
continue
|
||||
|
||||
if pending_append.get("content_start") is None:
|
||||
marker_index = pending_append["buffer"].find(pending_append["start_marker"])
|
||||
if marker_index != -1:
|
||||
pending_append["content_start"] = marker_index + len(pending_append["start_marker"])
|
||||
debug_log(f"检测到追加起始标识: {pending_append['start_marker']}")
|
||||
if pending_append:
|
||||
pending_append["buffer"] += content
|
||||
|
||||
if pending_append.get("content_start") is not None:
|
||||
end_index = pending_append["buffer"].find(
|
||||
pending_append["end_marker"],
|
||||
pending_append["content_start"]
|
||||
)
|
||||
if end_index != -1:
|
||||
pending_append["end_index"] = end_index
|
||||
append_break_triggered = True
|
||||
debug_log("检测到<<<END_APPEND>>>，即将终止流式输出并写入文件")
|
||||
break
|
||||
if pending_append.get("content_start") is None:
|
||||
marker_index = pending_append["buffer"].find(pending_append["start_marker"])
|
||||
if marker_index != -1:
|
||||
pending_append["content_start"] = marker_index + len(pending_append["start_marker"])
|
||||
debug_log(f"检测到追加起始标识: {pending_append['start_marker']}")
|
||||
|
||||
# 继续累积追加内容
|
||||
continue
|
||||
elif expecting_append:
|
||||
append_probe_buffer += content
|
||||
# 限制缓冲区大小防止过长
|
||||
if len(append_probe_buffer) > 10000:
|
||||
append_probe_buffer = append_probe_buffer[-10000:]
|
||||
|
||||
marker_match = re.search(r"<<<APPEND:\s*([\s\S]*?)>>>", append_probe_buffer)
|
||||
if marker_match:
|
||||
detected_raw_path = marker_match.group(1)
|
||||
detected_path = detected_raw_path.strip()
|
||||
if not detected_path:
|
||||
append_probe_buffer = append_probe_buffer[marker_match.end():]
|
||||
continue
|
||||
marker_full = marker_match.group(0)
|
||||
after_marker_index = append_probe_buffer.find(marker_full) + len(marker_full)
|
||||
remainder = append_probe_buffer[after_marker_index:]
|
||||
append_probe_buffer = ""
|
||||
pending_append = {
|
||||
"path": detected_path,
|
||||
"tool_call_id": None,
|
||||
"buffer": remainder,
|
||||
"start_marker": marker_full,
|
||||
"end_marker": "<<<END_APPEND>>>",
|
||||
"content_start": 0,
|
||||
"end_index": None,
|
||||
"display_id": None
|
||||
}
|
||||
if hasattr(web_terminal, "pending_append_request"):
|
||||
web_terminal.pending_append_request = {"path": detected_path}
|
||||
debug_log(f"直接检测到append起始标记，构建追加缓冲: {detected_path}")
|
||||
# 检查是否立即包含结束标记
|
||||
if pending_append["buffer"]:
|
||||
end_index = pending_append["buffer"].find(pending_append["end_marker"], pending_append["content_start"])
|
||||
if pending_append.get("content_start") is not None:
|
||||
end_index = pending_append["buffer"].find(
|
||||
pending_append["end_marker"],
|
||||
pending_append["content_start"]
|
||||
)
|
||||
if end_index != -1:
|
||||
pending_append["end_index"] = end_index
|
||||
append_break_triggered = True
|
||||
debug_log("检测到<<<END_APPEND>>>，即将终止流式输出并写入文件")
|
||||
break
|
||||
|
||||
# 继续累积追加内容
|
||||
continue
|
||||
elif expecting_append:
|
||||
append_probe_buffer += content
|
||||
# 限制缓冲区大小防止过长
|
||||
if len(append_probe_buffer) > 10000:
|
||||
append_probe_buffer = append_probe_buffer[-10000:]
|
||||
|
||||
if not text_started:
|
||||
text_started = True
|
||||
text_streaming = True
|
||||
sender('text_start', {})
|
||||
brief_log("模型输出了内容")
|
||||
await asyncio.sleep(0.05)
|
||||
marker_match = re.search(r"<<<APPEND:\s*([\s\S]*?)>>>", append_probe_buffer)
|
||||
if marker_match:
|
||||
detected_raw_path = marker_match.group(1)
|
||||
detected_path = detected_raw_path.strip()
|
||||
if not detected_path:
|
||||
append_probe_buffer = append_probe_buffer[marker_match.end():]
|
||||
continue
|
||||
marker_full = marker_match.group(0)
|
||||
after_marker_index = append_probe_buffer.find(marker_full) + len(marker_full)
|
||||
remainder = append_probe_buffer[after_marker_index:]
|
||||
append_probe_buffer = ""
|
||||
pending_append = {
|
||||
"path": detected_path,
|
||||
"tool_call_id": None,
|
||||
"buffer": remainder,
|
||||
"start_marker": marker_full,
|
||||
"end_marker": "<<<END_APPEND>>>",
|
||||
"content_start": 0,
|
||||
"end_index": None,
|
||||
"display_id": None
|
||||
}
|
||||
if hasattr(web_terminal, "pending_append_request"):
|
||||
web_terminal.pending_append_request = {"path": detected_path}
|
||||
debug_log(f"直接检测到append起始标记，构建追加缓冲: {detected_path}")
|
||||
# 检查是否立即包含结束标记
|
||||
if pending_append["buffer"]:
|
||||
end_index = pending_append["buffer"].find(pending_append["end_marker"], pending_append["content_start"])
|
||||
if end_index != -1:
|
||||
pending_append["end_index"] = end_index
|
||||
append_break_triggered = True
|
||||
debug_log("检测到<<<END_APPEND>>>，即将终止流式输出并写入文件")
|
||||
break
|
||||
continue
|
||||
|
||||
if not pending_append:
|
||||
full_response += content
|
||||
accumulated_response += content
|
||||
text_has_content = True
|
||||
emit_time = time.time()
|
||||
elapsed = 0.0 if last_text_chunk_time is None else emit_time - last_text_chunk_time
|
||||
last_text_chunk_time = emit_time
|
||||
text_chunk_index += 1
|
||||
log_backend_chunk(
|
||||
conversation_id,
|
||||
iteration + 1,
|
||||
text_chunk_index,
|
||||
elapsed,
|
||||
len(content),
|
||||
content[:32]
|
||||
)
|
||||
sender('text_chunk', {
|
||||
'content': content,
|
||||
'index': text_chunk_index,
|
||||
'elapsed': elapsed
|
||||
})
|
||||
if not text_started:
|
||||
text_started = True
|
||||
text_streaming = True
|
||||
sender('text_start', {})
|
||||
brief_log("模型输出了内容")
|
||||
await asyncio.sleep(0.05)
|
||||
|
||||
# 收集工具调用 - 实时发送准备状态
|
||||
if "tool_calls" in delta:
|
||||
tool_chunks += 1
|
||||
for tc in delta["tool_calls"]:
|
||||
found = False
|
||||
for existing in tool_calls:
|
||||
if existing.get("index") == tc.get("index"):
|
||||
if "function" in tc and "arguments" in tc["function"]:
|
||||
arg_chunk = tc["function"]["arguments"]
|
||||
existing_fn = existing.get("function", {})
|
||||
existing_args = existing_fn.get("arguments", "")
|
||||
existing_fn["arguments"] = (existing_args or "") + arg_chunk
|
||||
existing["function"] = existing_fn
|
||||
if not pending_append:
|
||||
full_response += content
|
||||
accumulated_response += content
|
||||
text_has_content = True
|
||||
emit_time = time.time()
|
||||
elapsed = 0.0 if last_text_chunk_time is None else emit_time - last_text_chunk_time
|
||||
last_text_chunk_time = emit_time
|
||||
text_chunk_index += 1
|
||||
log_backend_chunk(
|
||||
conversation_id,
|
||||
iteration + 1,
|
||||
text_chunk_index,
|
||||
elapsed,
|
||||
len(content),
|
||||
content[:32]
|
||||
)
|
||||
sender('text_chunk', {
|
||||
'content': content,
|
||||
'index': text_chunk_index,
|
||||
'elapsed': elapsed
|
||||
})
|
||||
|
||||
combined_args = existing_fn.get("arguments", "")
|
||||
tool_id = existing.get("id") or tc.get("id")
|
||||
tool_name = (
|
||||
existing_fn.get("name")
|
||||
or tc.get("function", {}).get("name", "")
|
||||
)
|
||||
intent_value = extract_intent_from_partial(combined_args)
|
||||
if (
|
||||
intent_value
|
||||
and tool_id
|
||||
and detected_tool_intent.get(tool_id) != intent_value
|
||||
):
|
||||
# 收集工具调用 - 实时发送准备状态
|
||||
if "tool_calls" in delta:
|
||||
tool_chunks += 1
|
||||
for tc in delta["tool_calls"]:
|
||||
found = False
|
||||
for existing in tool_calls:
|
||||
if existing.get("index") == tc.get("index"):
|
||||
if "function" in tc and "arguments" in tc["function"]:
|
||||
arg_chunk = tc["function"]["arguments"]
|
||||
existing_fn = existing.get("function", {})
|
||||
existing_args = existing_fn.get("arguments", "")
|
||||
existing_fn["arguments"] = (existing_args or "") + arg_chunk
|
||||
existing["function"] = existing_fn
|
||||
|
||||
combined_args = existing_fn.get("arguments", "")
|
||||
tool_id = existing.get("id") or tc.get("id")
|
||||
tool_name = (
|
||||
existing_fn.get("name")
|
||||
or tc.get("function", {}).get("name", "")
|
||||
)
|
||||
intent_value = extract_intent_from_partial(combined_args)
|
||||
if (
|
||||
intent_value
|
||||
and tool_id
|
||||
and detected_tool_intent.get(tool_id) != intent_value
|
||||
):
|
||||
detected_tool_intent[tool_id] = intent_value
|
||||
brief_log(f"[intent] 增量提取 {tool_name}: {intent_value}")
|
||||
sender('tool_intent', {
|
||||
'id': tool_id,
|
||||
'name': tool_name,
|
||||
'intent': intent_value,
|
||||
'conversation_id': conversation_id
|
||||
})
|
||||
debug_log(f" 发送工具意图: {tool_name} -> {intent_value}")
|
||||
await asyncio.sleep(0.01)
|
||||
found = True
|
||||
break
|
||||
|
||||
if not found and tc.get("id"):
|
||||
tool_id = tc["id"]
|
||||
tool_name = tc.get("function", {}).get("name", "")
|
||||
arguments_str = tc.get("function", {}).get("arguments", "") or ""
|
||||
|
||||
# 新工具检测到，立即发送准备事件
|
||||
if tool_id not in detected_tools and tool_name:
|
||||
detected_tools[tool_id] = tool_name
|
||||
|
||||
# 尝试提前提取 intent
|
||||
intent_value = None
|
||||
if arguments_str:
|
||||
intent_value = extract_intent_from_partial(arguments_str)
|
||||
if intent_value:
|
||||
detected_tool_intent[tool_id] = intent_value
|
||||
brief_log(f"[intent] 预提取 {tool_name}: {intent_value}")
|
||||
|
||||
# 立即发送工具准备中事件
|
||||
brief_log(f"[tool] 准备调用 {tool_name} (id={tool_id}) intent={intent_value or '-'}")
|
||||
sender('tool_preparing', {
|
||||
'id': tool_id,
|
||||
'name': tool_name,
|
||||
'message': f'准备调用 {tool_name}...',
|
||||
'intent': intent_value,
|
||||
'conversation_id': conversation_id
|
||||
})
|
||||
debug_log(f" 发送工具准备事件: {tool_name}")
|
||||
await asyncio.sleep(0.1)
|
||||
|
||||
tool_calls.append({
|
||||
"id": tool_id,
|
||||
"index": tc.get("index"),
|
||||
"type": "function",
|
||||
"function": {
|
||||
"name": tool_name,
|
||||
"arguments": arguments_str
|
||||
}
|
||||
})
|
||||
# 尝试从增量参数中抽取 intent，并单独推送
|
||||
if tool_id and arguments_str:
|
||||
intent_value = extract_intent_from_partial(arguments_str)
|
||||
if intent_value and detected_tool_intent.get(tool_id) != intent_value:
|
||||
detected_tool_intent[tool_id] = intent_value
|
||||
brief_log(f"[intent] 增量提取 {tool_name}: {intent_value}")
|
||||
sender('tool_intent', {
|
||||
'id': tool_id,
|
||||
'name': tool_name,
|
||||
@ -1603,89 +1714,87 @@ async def handle_task_with_sender(terminal: WebTerminal, workspace: UserWorkspac
|
||||
})
|
||||
debug_log(f" 发送工具意图: {tool_name} -> {intent_value}")
|
||||
await asyncio.sleep(0.01)
|
||||
found = True
|
||||
break
|
||||
debug_log(f" 新工具: {tool_name}")
|
||||
|
||||
if not found and tc.get("id"):
|
||||
tool_id = tc["id"]
|
||||
tool_name = tc.get("function", {}).get("name", "")
|
||||
arguments_str = tc.get("function", {}).get("arguments", "") or ""
|
||||
# 检查是否被停止
|
||||
client_stop_info = get_stop_flag(client_sid, username)
|
||||
if client_stop_info:
|
||||
stop_requested = client_stop_info.get('stop', False) if isinstance(client_stop_info, dict) else client_stop_info
|
||||
if stop_requested:
|
||||
debug_log("任务在流处理完成后检测到停止状态")
|
||||
sender('task_stopped', {
|
||||
'message': '命令执行被用户取消',
|
||||
'reason': 'user_stop'
|
||||
})
|
||||
_cancel_pending_tools(tool_calls)
|
||||
clear_stop_flag(client_sid, username)
|
||||
return
|
||||
|
||||
# 新工具检测到，立即发送准备事件
|
||||
if tool_id not in detected_tools and tool_name:
|
||||
detected_tools[tool_id] = tool_name
|
||||
# === API响应完成后只计算输出token ===
|
||||
if last_usage_payload:
|
||||
try:
|
||||
web_terminal.context_manager.apply_usage_statistics(last_usage_payload)
|
||||
debug_log(
|
||||
f"Usage统计: prompt={last_usage_payload.get('prompt_tokens', 0)}, "
|
||||
f"completion={last_usage_payload.get('completion_tokens', 0)}, "
|
||||
f"total={last_usage_payload.get('total_tokens', 0)}"
|
||||
)
|
||||
except Exception as e:
|
||||
debug_log(f"Usage统计更新失败: {e}")
|
||||
else:
|
||||
debug_log("未获取到usage字段，跳过token统计更新")
|
||||
|
||||
# 尝试提前提取 intent
|
||||
intent_value = None
|
||||
if arguments_str:
|
||||
intent_value = extract_intent_from_partial(arguments_str)
|
||||
if intent_value:
|
||||
detected_tool_intent[tool_id] = intent_value
|
||||
brief_log(f"[intent] 预提取 {tool_name}: {intent_value}")
|
||||
|
||||
# 立即发送工具准备中事件
|
||||
brief_log(f"[tool] 准备调用 {tool_name} (id={tool_id}) intent={intent_value or '-'}")
|
||||
sender('tool_preparing', {
|
||||
'id': tool_id,
|
||||
'name': tool_name,
|
||||
'message': f'准备调用 {tool_name}...',
|
||||
'intent': intent_value,
|
||||
'conversation_id': conversation_id
|
||||
})
|
||||
debug_log(f" 发送工具准备事件: {tool_name}")
|
||||
await asyncio.sleep(0.1)
|
||||
|
||||
tool_calls.append({
|
||||
"id": tool_id,
|
||||
"index": tc.get("index"),
|
||||
"type": "function",
|
||||
"function": {
|
||||
"name": tool_name,
|
||||
"arguments": arguments_str
|
||||
}
|
||||
})
|
||||
# 尝试从增量参数中抽取 intent，并单独推送
|
||||
if tool_id and arguments_str:
|
||||
intent_value = extract_intent_from_partial(arguments_str)
|
||||
if intent_value and detected_tool_intent.get(tool_id) != intent_value:
|
||||
detected_tool_intent[tool_id] = intent_value
|
||||
sender('tool_intent', {
|
||||
'id': tool_id,
|
||||
'name': tool_name,
|
||||
'intent': intent_value,
|
||||
'conversation_id': conversation_id
|
||||
})
|
||||
debug_log(f" 发送工具意图: {tool_name} -> {intent_value}")
|
||||
await asyncio.sleep(0.01)
|
||||
debug_log(f" 新工具: {tool_name}")
|
||||
|
||||
# 检查是否被停止
|
||||
client_stop_info = get_stop_flag(client_sid, username)
|
||||
if client_stop_info:
|
||||
stop_requested = client_stop_info.get('stop', False) if isinstance(client_stop_info, dict) else client_stop_info
|
||||
if stop_requested:
|
||||
debug_log("任务在流处理完成后检测到停止状态")
|
||||
sender('task_stopped', {
|
||||
'message': '命令执行被用户取消',
|
||||
'reason': 'user_stop'
|
||||
})
|
||||
_cancel_pending_tools(tool_calls)
|
||||
clear_stop_flag(client_sid, username)
|
||||
return
|
||||
|
||||
# === API响应完成后只计算输出token ===
|
||||
if last_usage_payload:
|
||||
try:
|
||||
web_terminal.context_manager.apply_usage_statistics(last_usage_payload)
|
||||
debug_log(
|
||||
f"Usage统计: prompt={last_usage_payload.get('prompt_tokens', 0)}, "
|
||||
f"completion={last_usage_payload.get('completion_tokens', 0)}, "
|
||||
f"total={last_usage_payload.get('total_tokens', 0)}"
|
||||
if api_error:
|
||||
error_message = ""
|
||||
error_status = None
|
||||
error_type = None
|
||||
if isinstance(api_error, dict):
|
||||
error_status = api_error.get("status_code")
|
||||
error_type = api_error.get("error_type")
|
||||
error_message = api_error.get("error_message") or api_error.get("error_text") or ""
|
||||
if not error_message:
|
||||
error_message = "API 请求失败"
|
||||
# 若命中阿里云配额错误，立即写入状态并切换到官方 API
|
||||
try:
|
||||
from utils.aliyun_fallback import compute_disabled_until, set_disabled_until
|
||||
disabled_until, reason = compute_disabled_until(error_message)
|
||||
if disabled_until and reason:
|
||||
set_disabled_until(getattr(web_terminal, "model_key", None) or "kimi-k2.5", disabled_until, reason)
|
||||
profile = get_model_profile(getattr(web_terminal, "model_key", None) or "kimi-k2.5")
|
||||
web_terminal.apply_model_profile(profile)
|
||||
except Exception as exc:
|
||||
debug_log(f"处理阿里云配额回退失败: {exc}")
|
||||
can_retry = (
|
||||
api_attempt < max_api_retries
|
||||
and not full_response
|
||||
and not tool_calls
|
||||
and not current_thinking
|
||||
and not pending_append
|
||||
and not pending_modify
|
||||
)
|
||||
except Exception as e:
|
||||
debug_log(f"Usage统计更新失败: {e}")
|
||||
else:
|
||||
debug_log("未获取到usage字段，跳过token统计更新")
|
||||
sender('error', {
|
||||
'message': error_message,
|
||||
'status_code': error_status,
|
||||
'error_type': error_type,
|
||||
'retry': bool(can_retry),
|
||||
'retry_in': retry_delay_seconds if can_retry else None,
|
||||
'attempt': api_attempt + 1,
|
||||
'max_attempts': max_api_retries + 1
|
||||
})
|
||||
if can_retry:
|
||||
try:
|
||||
profile = get_model_profile(getattr(web_terminal, "model_key", None) or "kimi-k2.5")
|
||||
web_terminal.apply_model_profile(profile)
|
||||
except Exception as exc:
|
||||
debug_log(f"重试前更新模型配置失败: {exc}")
|
||||
cancelled = await _wait_retry_delay(retry_delay_seconds)
|
||||
if cancelled:
|
||||
return
|
||||
continue
|
||||
_cancel_pending_tools(tool_calls)
|
||||
return
|
||||
break
|
||||
|
||||
# 流结束后的处理
|
||||
debug_log(f"\n流结束统计:")
|
||||
|
||||
@ -1042,6 +1042,10 @@ export async function initializeLegacySocket(ctx: any) {
|
||||
if (!msg) {
|
||||
return;
|
||||
}
|
||||
if (msg.awaitingFirstContent) {
|
||||
msg.awaitingFirstContent = false;
|
||||
msg.generatingLabel = '';
|
||||
}
|
||||
const action = {
|
||||
id: data.id,
|
||||
type: 'tool',
|
||||
@ -1405,7 +1409,10 @@ export async function initializeLegacySocket(ctx: any) {
|
||||
const msg = data?.message || '发生未知错误';
|
||||
const code = data?.status_code;
|
||||
const errType = data?.error_type;
|
||||
ctx.addSystemMessage(`错误: ${msg}`);
|
||||
const shouldRetry = Boolean(data?.retry);
|
||||
const retryIn = Number(data?.retry_in) || 5;
|
||||
const retryAttempt = Number(data?.attempt) || 1;
|
||||
const retryMax = Number(data?.max_attempts) || retryAttempt;
|
||||
if (typeof ctx.uiPushToast === 'function') {
|
||||
ctx.uiPushToast({
|
||||
title: code ? `API错误 ${code}` : 'API错误',
|
||||
@ -1413,8 +1420,35 @@ export async function initializeLegacySocket(ctx: any) {
|
||||
type: 'error',
|
||||
duration: 6000
|
||||
});
|
||||
if (shouldRetry) {
|
||||
ctx.uiPushToast({
|
||||
title: '即将重试',
|
||||
message: `将在 ${retryIn} 秒后重试（第 ${retryAttempt}/${retryMax} 次）`,
|
||||
type: 'info',
|
||||
duration: Math.max(retryIn, 1) * 1000
|
||||
});
|
||||
}
|
||||
}
|
||||
if (shouldRetry) {
|
||||
// 错误后保持停止按钮态，用户可手动停止或等待自动重试
|
||||
ctx.stopRequested = false;
|
||||
ctx.taskInProgress = true;
|
||||
ctx.streamingMessage = true;
|
||||
return;
|
||||
}
|
||||
|
||||
// 最后一次报错：恢复输入状态并清理提示动画
|
||||
const msgIndex = typeof ctx.currentMessageIndex === 'number' ? ctx.currentMessageIndex : -1;
|
||||
if (msgIndex >= 0 && Array.isArray(ctx.messages)) {
|
||||
const currentMessage = ctx.messages[msgIndex];
|
||||
if (currentMessage && currentMessage.role === 'assistant') {
|
||||
currentMessage.awaitingFirstContent = false;
|
||||
currentMessage.generatingLabel = '';
|
||||
}
|
||||
}
|
||||
if (typeof ctx.chatClearThinkingLocks === 'function') {
|
||||
ctx.chatClearThinkingLocks();
|
||||
}
|
||||
// 仅标记当前流结束，避免状态错乱
|
||||
ctx.streamingMessage = false;
|
||||
ctx.stopRequested = false;
|
||||
ctx.taskInProgress = false;
|
||||
|
||||
103
utils/aliyun_fallback.py
Normal file
103
utils/aliyun_fallback.py
Normal file
@ -0,0 +1,103 @@
|
||||
import json
|
||||
from datetime import datetime, timedelta, timezone
|
||||
from pathlib import Path
|
||||
from typing import Dict, Optional, Tuple
|
||||
|
||||
|
||||
FALLBACK_MODELS = {"qwen3-vl-plus", "kimi-k2.5", "minimax-m2.5"}
|
||||
STATE_PATH = Path(__file__).resolve().parents[1] / "data" / "aliyun_fallback_state.json"
|
||||
|
||||
|
||||
def _read_state() -> Dict:
|
||||
if not STATE_PATH.exists():
|
||||
return {"models": {}}
|
||||
try:
|
||||
data = json.loads(STATE_PATH.read_text(encoding="utf-8"))
|
||||
except Exception:
|
||||
return {"models": {}}
|
||||
if not isinstance(data, dict):
|
||||
return {"models": {}}
|
||||
if "models" not in data or not isinstance(data["models"], dict):
|
||||
data["models"] = {}
|
||||
return data
|
||||
|
||||
|
||||
def _write_state(data: Dict) -> None:
|
||||
STATE_PATH.parent.mkdir(parents=True, exist_ok=True)
|
||||
STATE_PATH.write_text(json.dumps(data, ensure_ascii=False, indent=2), encoding="utf-8")
|
||||
|
||||
|
||||
def get_disabled_until(model_key: str) -> Optional[float]:
|
||||
data = _read_state()
|
||||
entry = (data.get("models") or {}).get(model_key) or {}
|
||||
ts = entry.get("disabled_until")
|
||||
try:
|
||||
return float(ts) if ts is not None else None
|
||||
except (TypeError, ValueError):
|
||||
return None
|
||||
|
||||
|
||||
def is_fallback_active(model_key: str, now_ts: Optional[float] = None) -> bool:
|
||||
if model_key not in FALLBACK_MODELS:
|
||||
return False
|
||||
now_ts = float(now_ts) if now_ts is not None else datetime.now(tz=timezone.utc).timestamp()
|
||||
disabled_until = get_disabled_until(model_key)
|
||||
return bool(disabled_until and disabled_until > now_ts)
|
||||
|
||||
|
||||
def set_disabled_until(model_key: str, disabled_until_ts: float, reason: str = "") -> None:
|
||||
if model_key not in FALLBACK_MODELS:
|
||||
return
|
||||
data = _read_state()
|
||||
models = data.setdefault("models", {})
|
||||
models[model_key] = {
|
||||
"disabled_until": float(disabled_until_ts),
|
||||
"reason": reason,
|
||||
"updated_at": datetime.now(tz=timezone.utc).timestamp(),
|
||||
}
|
||||
_write_state(data)
|
||||
|
||||
|
||||
def _next_monday_utc8(now: datetime) -> datetime:
|
||||
# Monday = 0
|
||||
weekday = now.weekday()
|
||||
days_ahead = (7 - weekday) % 7
|
||||
if days_ahead == 0:
|
||||
days_ahead = 7
|
||||
target = (now + timedelta(days=days_ahead)).replace(hour=0, minute=0, second=0, microsecond=0)
|
||||
return target
|
||||
|
||||
|
||||
def _next_month_same_day_utc8(now: datetime) -> datetime:
|
||||
year = now.year
|
||||
month = now.month + 1
|
||||
if month > 12:
|
||||
month = 1
|
||||
year += 1
|
||||
# clamp day to last day of next month
|
||||
if month == 12:
|
||||
next_month = datetime(year + 1, 1, 1, tzinfo=now.tzinfo)
|
||||
else:
|
||||
next_month = datetime(year, month + 1, 1, tzinfo=now.tzinfo)
|
||||
last_day = (next_month - timedelta(days=1)).day
|
||||
day = min(now.day, last_day)
|
||||
return datetime(year, month, day, 0, 0, 0, tzinfo=now.tzinfo)
|
||||
|
||||
|
||||
def compute_disabled_until(error_text: str) -> Tuple[Optional[float], Optional[str]]:
|
||||
if not error_text:
|
||||
return None, None
|
||||
text = str(error_text).lower()
|
||||
tz8 = timezone(timedelta(hours=8))
|
||||
now = datetime.now(tz=tz8)
|
||||
|
||||
if "hour allocated quota exceeded" in text or "每 5 小时请求额度已用完" in text:
|
||||
until = now + timedelta(hours=5)
|
||||
return until.astimezone(timezone.utc).timestamp(), "hour_quota"
|
||||
if "week allocated quota exceeded" in text or "每周请求额度已用完" in text:
|
||||
until = _next_monday_utc8(now)
|
||||
return until.astimezone(timezone.utc).timestamp(), "week_quota"
|
||||
if "month allocated quota exceeded" in text or "每月请求额度已用完" in text:
|
||||
until = _next_month_same_day_utc8(now)
|
||||
return until.astimezone(timezone.utc).timestamp(), "month_quota"
|
||||
return None, None
|
||||
@ -6,9 +6,12 @@ import json
|
||||
import asyncio
|
||||
import base64
|
||||
import mimetypes
|
||||
import os
|
||||
from typing import List, Dict, Optional, AsyncGenerator, Any
|
||||
from pathlib import Path
|
||||
from datetime import datetime
|
||||
from pathlib import Path
|
||||
from typing import Tuple
|
||||
try:
|
||||
from config import (
|
||||
API_BASE_URL,
|
||||
@ -78,6 +81,73 @@ class DeepSeekClient:
|
||||
# 请求体落盘目录
|
||||
self.request_dump_dir = Path(__file__).resolve().parents[1] / "logs" / "api_requests"
|
||||
self.request_dump_dir.mkdir(parents=True, exist_ok=True)
|
||||
self.debug_log_path = Path(__file__).resolve().parents[1] / "logs" / "api_debug.log"
|
||||
|
||||
def _maybe_mark_aliyun_quota(self, error_text: str) -> None:
|
||||
if not error_text or not self.model_key:
|
||||
return
|
||||
try:
|
||||
from utils.aliyun_fallback import compute_disabled_until, set_disabled_until
|
||||
except Exception:
|
||||
return
|
||||
disabled_until, reason = compute_disabled_until(error_text)
|
||||
if disabled_until and reason:
|
||||
set_disabled_until(self.model_key, disabled_until, reason)
|
||||
# 立即切换到官方 API（仅在有配置时）
|
||||
base_env_key = None
|
||||
key_env_key = None
|
||||
if self.model_key == "kimi-k2.5":
|
||||
base_env_key = "API_BASE_KIMI_OFFICIAL"
|
||||
key_env_key = "API_KEY_KIMI_OFFICIAL"
|
||||
elif self.model_key == "qwen3-vl-plus":
|
||||
base_env_key = "API_BASE_QWEN_OFFICIAL"
|
||||
key_env_key = "API_KEY_QWEN_OFFICIAL"
|
||||
elif self.model_key == "minimax-m2.5":
|
||||
base_env_key = "API_BASE_MINIMAX_OFFICIAL"
|
||||
key_env_key = "API_KEY_MINIMAX_OFFICIAL"
|
||||
if base_env_key and key_env_key:
|
||||
official_base = self._resolve_env_value(base_env_key)
|
||||
official_key = self._resolve_env_value(key_env_key)
|
||||
if official_base and official_key:
|
||||
self.fast_api_config["base_url"] = official_base
|
||||
self.fast_api_config["api_key"] = official_key
|
||||
self.thinking_api_config["base_url"] = official_base
|
||||
self.thinking_api_config["api_key"] = official_key
|
||||
self.api_base_url = official_base
|
||||
self.api_key = official_key
|
||||
|
||||
def _debug_log(self, payload: Dict[str, Any]) -> None:
|
||||
try:
|
||||
entry = {
|
||||
"ts": datetime.now().isoformat(),
|
||||
**payload
|
||||
}
|
||||
self.debug_log_path.parent.mkdir(parents=True, exist_ok=True)
|
||||
with self.debug_log_path.open("a", encoding="utf-8") as f:
|
||||
f.write(json.dumps(entry, ensure_ascii=False) + "\n")
|
||||
except Exception:
|
||||
pass
|
||||
|
||||
def _resolve_env_value(self, name: str) -> Optional[str]:
|
||||
value = os.environ.get(name)
|
||||
if value is None:
|
||||
env_path = Path(__file__).resolve().parents[1] / ".env"
|
||||
if env_path.exists():
|
||||
try:
|
||||
for raw_line in env_path.read_text(encoding="utf-8").splitlines():
|
||||
line = raw_line.strip()
|
||||
if not line or line.startswith("#") or "=" not in line:
|
||||
continue
|
||||
key, val = line.split("=", 1)
|
||||
if key.strip() == name:
|
||||
value = val.strip().strip('"').strip("'")
|
||||
break
|
||||
except Exception:
|
||||
value = None
|
||||
if value is None:
|
||||
return None
|
||||
value = value.strip()
|
||||
return value or None
|
||||
|
||||
def _print(self, message: str, end: str = "\n", flush: bool = False):
|
||||
"""安全的打印函数，在Web模式下不输出"""
|
||||
@ -568,7 +638,10 @@ class DeepSeekClient:
|
||||
"error_text": error_text,
|
||||
"error_type": None,
|
||||
"error_message": None,
|
||||
"request_dump": str(dump_path)
|
||||
"request_dump": str(dump_path),
|
||||
"base_url": api_config.get("base_url"),
|
||||
"model_id": api_config.get("model_id"),
|
||||
"model_key": self.model_key
|
||||
}
|
||||
try:
|
||||
parsed = json.loads(error_text)
|
||||
@ -578,7 +651,20 @@ class DeepSeekClient:
|
||||
self.last_error_info["error_message"] = err.get("message")
|
||||
except Exception:
|
||||
pass
|
||||
self._print(f"{OUTPUT_FORMATS['error']} API请求失败 ({response.status_code}): {error_text}")
|
||||
self._maybe_mark_aliyun_quota(error_text)
|
||||
self._debug_log({
|
||||
"event": "http_error_stream",
|
||||
"status_code": response.status_code,
|
||||
"error_text": error_text,
|
||||
"base_url": api_config.get("base_url"),
|
||||
"model_id": api_config.get("model_id"),
|
||||
"model_key": self.model_key,
|
||||
"request_dump": str(dump_path)
|
||||
})
|
||||
self._print(
|
||||
f"{OUTPUT_FORMATS['error']} API请求失败 ({response.status_code}): {error_text} "
|
||||
f"(base_url={api_config.get('base_url')}, model_id={api_config.get('model_id')})"
|
||||
)
|
||||
self._mark_request_error(dump_path, response.status_code, error_text)
|
||||
yield {"error": self.last_error_info}
|
||||
return
|
||||
@ -607,7 +693,10 @@ class DeepSeekClient:
|
||||
"error_text": error_text,
|
||||
"error_type": None,
|
||||
"error_message": None,
|
||||
"request_dump": str(dump_path)
|
||||
"request_dump": str(dump_path),
|
||||
"base_url": api_config.get("base_url"),
|
||||
"model_id": api_config.get("model_id"),
|
||||
"model_key": self.model_key
|
||||
}
|
||||
try:
|
||||
parsed = response.json()
|
||||
@ -617,7 +706,20 @@ class DeepSeekClient:
|
||||
self.last_error_info["error_message"] = err.get("message")
|
||||
except Exception:
|
||||
pass
|
||||
self._print(f"{OUTPUT_FORMATS['error']} API请求失败 ({response.status_code}): {error_text}")
|
||||
self._maybe_mark_aliyun_quota(error_text)
|
||||
self._debug_log({
|
||||
"event": "http_error",
|
||||
"status_code": response.status_code,
|
||||
"error_text": error_text,
|
||||
"base_url": api_config.get("base_url"),
|
||||
"model_id": api_config.get("model_id"),
|
||||
"model_key": self.model_key,
|
||||
"request_dump": str(dump_path)
|
||||
})
|
||||
self._print(
|
||||
f"{OUTPUT_FORMATS['error']} API请求失败 ({response.status_code}): {error_text} "
|
||||
f"(base_url={api_config.get('base_url')}, model_id={api_config.get('model_id')})"
|
||||
)
|
||||
self._mark_request_error(dump_path, response.status_code, error_text)
|
||||
yield {"error": self.last_error_info}
|
||||
return
|
||||
@ -632,8 +734,21 @@ class DeepSeekClient:
|
||||
"error_text": "connect_error",
|
||||
"error_type": "connection_error",
|
||||
"error_message": "无法连接到API服务器",
|
||||
"request_dump": str(dump_path)
|
||||
"request_dump": str(dump_path),
|
||||
"base_url": api_config.get("base_url"),
|
||||
"model_id": api_config.get("model_id"),
|
||||
"model_key": self.model_key
|
||||
}
|
||||
self._maybe_mark_aliyun_quota(self.last_error_info.get("error_text"))
|
||||
self._debug_log({
|
||||
"event": "connect_error",
|
||||
"status_code": None,
|
||||
"error_text": "connect_error",
|
||||
"base_url": api_config.get("base_url"),
|
||||
"model_id": api_config.get("model_id"),
|
||||
"model_key": self.model_key,
|
||||
"request_dump": str(dump_path)
|
||||
})
|
||||
self._mark_request_error(dump_path, error_text="connect_error")
|
||||
yield {"error": self.last_error_info}
|
||||
except httpx.TimeoutException:
|
||||
@ -643,8 +758,21 @@ class DeepSeekClient:
|
||||
"error_text": "timeout",
|
||||
"error_type": "timeout",
|
||||
"error_message": "API请求超时",
|
||||
"request_dump": str(dump_path)
|
||||
"request_dump": str(dump_path),
|
||||
"base_url": api_config.get("base_url"),
|
||||
"model_id": api_config.get("model_id"),
|
||||
"model_key": self.model_key
|
||||
}
|
||||
self._maybe_mark_aliyun_quota(self.last_error_info.get("error_text"))
|
||||
self._debug_log({
|
||||
"event": "timeout",
|
||||
"status_code": None,
|
||||
"error_text": "timeout",
|
||||
"base_url": api_config.get("base_url"),
|
||||
"model_id": api_config.get("model_id"),
|
||||
"model_key": self.model_key,
|
||||
"request_dump": str(dump_path)
|
||||
})
|
||||
self._mark_request_error(dump_path, error_text="timeout")
|
||||
yield {"error": self.last_error_info}
|
||||
except Exception as e:
|
||||
@ -654,8 +782,21 @@ class DeepSeekClient:
|
||||
"error_text": str(e),
|
||||
"error_type": "exception",
|
||||
"error_message": str(e),
|
||||
"request_dump": str(dump_path)
|
||||
"request_dump": str(dump_path),
|
||||
"base_url": api_config.get("base_url"),
|
||||
"model_id": api_config.get("model_id"),
|
||||
"model_key": self.model_key
|
||||
}
|
||||
self._maybe_mark_aliyun_quota(self.last_error_info.get("error_text"))
|
||||
self._debug_log({
|
||||
"event": "exception",
|
||||
"status_code": None,
|
||||
"error_text": str(e),
|
||||
"base_url": api_config.get("base_url"),
|
||||
"model_id": api_config.get("model_id"),
|
||||
"model_key": self.model_key,
|
||||
"request_dump": str(dump_path)
|
||||
})
|
||||
self._mark_request_error(dump_path, error_text=str(e))
|
||||
yield {"error": self.last_error_info}
|
||||
|
||||
|
||||
Loading…
Reference in New Issue
Block a user