"""ModelHub XC 适配智能体 (huni-adapt-agent) 平台已把"脚本提交"关闭(code 60014),程序化提交只能走"适配智能体"。 本智能体部署在平台内, 用注入的 EXTERNAL_SERVICE_TOKEN 作为 xcToken、经 **Xc-Token 头** 调开放平台 API 提交适配任务——这是被平台认可的"智能体提交"路径(不是被拦的脚本提交)。 关键教训: 主站开放 API 用 `Xc-Token` 头(不是 Authorization);提交不需要浏览器签名。 安全: token 只从环境读、绝不打印/落盘; 有 MAX_TOTAL 上限防止在公司平台上跑飞。 """ import json, os, signal, time, threading import urllib.request, urllib.parse, urllib.error from http.server import BaseHTTPRequestHandler, ThreadingHTTPServer MAIN = os.getenv("MAIN_HOST", "https://modelhub.org.cn") GITEA = os.getenv("GITEA_HOST", "https://dev.modelhub.org.cn") TOKEN = os.getenv("EXTERNAL_SERVICE_TOKEN", "") # = xcToken, 走 Xc-Token 头 STRATEGY_ID = os.getenv("STRATEGY_ID", "") # 平台注入的自身策略 id, 提交必带 (docs/6 §3) DRY_RUN = os.getenv("DRY_RUN", "false").lower() == "true" # 默认真提交(平台唯一认可路径) TARGET_CARDS = os.getenv("TARGET_CARDS", "Iluvatar_bi-150,Iluvatar_bi-100,Iluvatar_mrv-100").split(",") CARD_NAME = {"Iluvatar_bi-150": "天垓150", "Iluvatar_bi-100": "天垓100", "Iluvatar_mrv-100": "智铠100"} TASK_TYPE = os.getenv("TASK_TYPE", "visual-multi-modal") FRAMEWORK = os.getenv("FRAMEWORK", "vllm") POLL_SEC = int(os.getenv("POLL_SEC", "90")) MAX_PER_CYCLE = int(os.getenv("MAX_PER_CYCLE", "3")) MAX_TOTAL = int(os.getenv("MAX_TOTAL", "20")) # 累计提交上限, 到顶转空转(安全阀) SEARCH_KW = os.getenv("SEARCH_KW", "InternVL,MiniCPM-V,Qwen2-VL,Qwen2.5-VL,Llava") STATE = {"cycles": 0, "submitted": 0, "skipped": 0, "errors": 0, "last": [], "started": time.time()} _stop = threading.Event() def log(msg): print(f"[{time.strftime('%Y-%m-%d %H:%M:%S')}] {msg}", flush=True) def _http(method, url, headers=None, body=None, timeout=30): data = body.encode() if isinstance(body, str) else body req = urllib.request.Request(url, data=data, method=method, headers=headers or {}) try: with urllib.request.urlopen(req, timeout=timeout) as r: return r.status, r.read().decode() except urllib.error.HTTPError as e: return e.code, e.read().decode() except Exception as e: return -1, str(e) def xc_get(path): st, txt = _http("GET", MAIN + path, {"Xc-Token": TOKEN}) try: return st, json.loads(txt) except Exception: return st, txt def build_config(gpu): st, txt = _http("POST", MAIN + f"/api/adapt/task/build-config?gpuType={gpu}&framework={FRAMEWORK}&taskType={TASK_TYPE}", {"Xc-Token": TOKEN}) try: j = json.loads(txt) return j.get("data") if isinstance(j, dict) else None except Exception: return None def already_adapted(model, gpu): st, j = xc_get("/api/computility/models/metrics?modelId=" + urllib.parse.quote(model)) if not isinstance(j, dict): return None names = [x.get("machineName") for x in (j.get("data") or [])] return CARD_NAME.get(gpu) in names def find_models(): out = [] for kw in SEARCH_KW.split(","): st, txt = _http("GET", GITEA + f"/api/v1/repos/search?q={urllib.parse.quote(kw)}&sort=updated&order=desc&limit=20") try: for r in json.loads(txt).get("data", []): if r.get("full_name"): out.append(r["full_name"]) except Exception: pass return out def submit(model, gpu): cfg = build_config(gpu) if not cfg: return {"model": model.split("/")[-1], "gpu": gpu, "skip": "no-config"} if DRY_RUN: return {"model": model.split("/")[-1], "gpu": gpu, "dry_run": True, "cfg_len": len(cfg)} body = json.dumps({"modelAddress": model, "taskType": TASK_TYPE, "targetGpu": gpu, "framework": FRAMEWORK, "strategyId": STRATEGY_ID, "configParams": cfg}) st, txt = _http("POST", MAIN + "/api/adapt/task/add", {"Xc-Token": TOKEN, "Content-Type": "application/json"}, body) try: j = json.loads(txt) except Exception: j = {} data = j.get("data") if isinstance(j, dict) else None return {"model": model.split("/")[-1], "gpu": gpu, "http": st, "code": j.get("code"), "taskId": (data or {}).get("id") if isinstance(data, dict) else None, "msg": j.get("message")} def loop(): log(f"loop start | dry_run={DRY_RUN} | token_present={bool(TOKEN)} | strategy_id={STRATEGY_ID or 'MISSING'} | cards={TARGET_CARDS} | type={TASK_TYPE} | max_total={MAX_TOTAL}") st, j = xc_get("/api/adapt/task/page?current=1&pageSize=1") log(f"auth probe task/page(Xc-Token) -> http={st} code={(j.get('code') if isinstance(j, dict) else '?')}") seen = set() while not _stop.is_set(): STATE["cycles"] += 1 if STATE["submitted"] >= MAX_TOTAL: log(f"reached MAX_TOTAL={MAX_TOTAL}, idling (set higher to continue)") _stop.wait(POLL_SEC); continue try: n = 0 for m in find_models(): if _stop.is_set() or n >= MAX_PER_CYCLE or STATE["submitted"] >= MAX_TOTAL: break for gpu in TARGET_CARDS: key = m + "|" + gpu if key in seen: continue seen.add(key) if already_adapted(m, gpu) is True: STATE["skipped"] += 1 continue res = submit(m, gpu) STATE["last"] = ([res] + STATE["last"])[:20] if res.get("code") == 0 or res.get("dry_run"): STATE["submitted"] += 1; n += 1 elif res.get("skip"): STATE["skipped"] += 1 else: STATE["errors"] += 1 log("submit " + json.dumps(res, ensure_ascii=False)) time.sleep(2) break except Exception as e: STATE["errors"] += 1 log("loop error: " + str(e)) _stop.wait(POLL_SEC) log("loop stopped") class H(BaseHTTPRequestHandler): def _j(self, o, s=200): b = json.dumps(o, ensure_ascii=False).encode() self.send_response(s); self.send_header("Content-Type", "application/json") self.send_header("Content-Length", str(len(b))); self.end_headers(); self.wfile.write(b) def do_GET(self): if self.path == "/health": return self._j({"status": "ok"}) if self.path == "/": return self._j({"name": "huni-adapt-agent", "dry_run": DRY_RUN, "state": STATE}) return self._j({"error": "not found"}, 404) def log_message(self, *a): pass def _sig(signum, _f): _stop.set(); log(f"signal {signum}, shutting down") def main(): signal.signal(signal.SIGTERM, _sig) signal.signal(signal.SIGINT, _sig) threading.Thread(target=loop, daemon=True).start() srv = ThreadingHTTPServer(("0.0.0.0", 8080), H); srv.timeout = 1 log("listening on 0.0.0.0:8080") while not _stop.is_set(): srv.handle_request() srv.server_close() if __name__ == "__main__": main()