add .dockerignore

main.py

@@ -1,16 +1,14 @@
-"""ModelHub XC 适配智能体 —— 单任务提交器
+"""ModelHub XC 适配智能体 —— 多任务提交器（本批次 4 条）
 
-启动后向 ModelHub XC 提交 1 条模型适配验证任务，随后保持 /health 存活等待平台停止。
+启动后依次提交 4 条已查重的模型适配验证任务，随后保持 /health 存活等待平台停止。
 
-提交内容（已查重，非重复模型）：
-  模型：https://www.modelscope.cn/models/qnguyen3/qwq-1.5b-grpo  (Qwen2 / 1.5B)
-  算力：Ascend_910-b4      框架：vllm      任务类型：text-generation
+批次清单（提交前均查过：模型列表 0 条 / 全站任务 0 条 / 详情接口无验证记录）：
+  1. mrm8488/DeepSeek-R1-Distill-Qwen-1.5B-grpo-limo-2e   Qwen2 1.5B  Ascend_910-b4  vllm
+  2. HollowInky/skill-search-qwen3-4b-unmasked-grpo       Qwen3 4B    Ascend_910-b4  vllm
+  3. dmis-lab/OSP-1.4B-100B-Muon                          Llama 1.4B  Ascend_910-b4  vllm
+  4. qnguyen3/quan-1.8b-chat                              Llama 1.8B  Ascend_910-b3  vllm
 
-平台契约：
-  - 根目录 Dockerfile，监听 8080
-  - GET /health 探活
-  - 读取平台注入的 STRATEGY_ID
-  - 正确处理 SIGTERM
+平台契约：根目录 Dockerfile，监听 8080，GET /health 探活，读取 STRATEGY_ID，处理 SIGTERM。
 """
 import json
 import os
@@ -22,20 +20,13 @@ from http.server import BaseHTTPRequestHandler, ThreadingHTTPServer
 
 import requests
 
-# ─────────────────────────── 业务配置 ───────────────────────────
 BASE_URL = os.environ.get("BASE_URL", "https://modelhub.org.cn")
 ADD_TASK_ENDPOINT = "/api/adapt/task/add"
-
 XC_TOKEN = os.environ.get("XC_TOKEN", "6616dfe75c874e61987b1f7c908e6d77")
 STRATEGY_ID = os.environ.get("STRATEGY_ID", "")
 
-MODEL_ADDRESS = "https://www.modelscope.cn/models/qnguyen3/qwq-1.5b-grpo"
-TASK_TYPE = "text-generation"
-TARGET_GPU = "Ascend_910-b4"
-FRAMEWORK = "vllm"
-
-# 与 POST /api/adapt/task/build-config?gpuType=Ascend_910-b4&framework=vllm&taskType=text-generation 输出一致
-CONFIG_PARAMS = """framework: vllm
+# 910B4 模板（max_model_len 2048）
+CFG_B4 = """framework: vllm
 api: completion
 max_tokens: 1024
 temperature: 0.7
@@ -84,95 +75,139 @@ ref_config:
     - -tp
     - '1'
     - --enforce-eager
-    - --trust-remote-code
-"""
+    - --trust-remote-code"""
 
+# 910B3 模板（max_model_len 4096）
+CFG_B3 = """framework: vllm
+api: completion
+lang: en
+max_model_len: 4096
+max_tokens: 1024
+temperature: 0.7
+repetition_penalty: 1.1
+top_p: 0.9
+sut_config:
+  gpu_num: 1
+  values:
+    command:
+    - vllm
+    - serve
+    - /model
+    - --port
+    - '20644'
+    - --served-model-name
+    - llm
+    - --max-model-len
+    - '4096'
+    - -tp
+    - '1'
+    - --enforce-eager
+    - --trust-remote-code
+ref_config:
+  gpu_num: 1
+  values:
+    command:
+    - vllm
+    - serve
+    - /model
+    - --port
+    - '80'
+    - --served-model-name
+    - llm
+    - --max-model-len
+    - '4096'
+    - -tp
+    - '1'
+    - --enforce-eager
+    - --trust-remote-code"""
+
+TASKS = [
+    {
+        "label": "OSP-1.4B-100B-Adam",
+        "model": "https://www.modelscope.cn/models/dmis-lab/OSP-1.4B-100B-Adam",
+        "gpu": "Ascend_910-b4",
+        "config": CFG_B4,
+    },
+    {
+        "label": "OSP-1.4B-1T-Adam",
+        "model": "https://www.modelscope.cn/models/dmis-lab/OSP-1.4B-1T-Adam",
+        "gpu": "Ascend_910-b4",
+        "config": CFG_B4,
+    },
+]
+
+TASK_TYPE = "text-generation"
+FRAMEWORK = "vllm"
 HEADERS = {"Content-Type": "application/json", "Xc-Token": XC_TOKEN}
 
 HTTP_HOST, HTTP_PORT = "0.0.0.0", 8080
-MAX_ATTEMPTS = 5
-RETRY_GAP = 15  # 秒
+GAP = 4  # 两条之间的间隔秒数
 
 _state = {
     "strategy_id": STRATEGY_ID,
-    "phase": "starting",       # starting | submitting | done | error
-    "model_address": MODEL_ADDRESS,
-    "target_gpu": TARGET_GPU,
-    "framework": FRAMEWORK,
-    "attempts": 0,
-    "attempt_log": [],
-    "task_id": None,
+    "phase": "starting",   # starting | submitting | done
+    "total": len(TASKS),
+    "submitted": 0,
+    "failed": 0,
+    "results": [],
     "started_at": None,
     "finished_at": None,
 }
 _shutdown = threading.Event()
-_submitting = threading.Lock()
-_submitted = False
 
 
-def submit_task():
-    """提交一次；已提交过则直接返回。"""
-    global _submitted
-    with _submitting:
-        if _submitted:
-            return True
-
+def submit_one(task):
     payload = {
-        "configParams": CONFIG_PARAMS,
+        "configParams": task["config"],
         "framework": FRAMEWORK,
-        "modelAddress": MODEL_ADDRESS,
-        "targetGpu": TARGET_GPU,
+        "modelAddress": task["model"],
+        "targetGpu": task["gpu"],
         "taskType": TASK_TYPE,
         "strategyId": STRATEGY_ID,
     }
-
-    _state["phase"] = "submitting"
-    _state["started_at"] = datetime.utcnow().isoformat()
-
-    for i in range(1, MAX_ATTEMPTS + 1):
-        if _shutdown.is_set():
-            break
-        _state["attempts"] = i
     try:
         resp = requests.post(BASE_URL + ADD_TASK_ENDPOINT, headers=HEADERS,
-                                 json=payload, timeout=60)
+                             json=payload, timeout=90)
         body = resp.json()
     except Exception as e:  # noqa: BLE001
         body = {"code": -1, "message": "exception: %s" % e}
 
     code = body.get("code")
-        msg = body.get("message", "")
-        entry = {"attempt": i, "time": datetime.utcnow().isoformat(),
-                 "http_status": None, "code": code, "message": msg}
-        try:
-            entry["http_status"] = resp.status_code
-        except Exception:  # noqa: BLE001
-            pass
-        _state["attempt_log"].append(entry)
-        print("[submit] #%d code=%s message=%s" % (i, code, msg), flush=True)
-
-        if code == 0:
     data = body.get("data") or {}
-            _state["task_id"] = data.get("id")
+    print("[submit] %s gpu=%s code=%s message=%s taskId=%s"
+          % (task["label"], task["gpu"], code, body.get("message"), data.get("id")), flush=True)
+    return code, body.get("message"), data.get("id")
+
+
+def run_batch():
+    _state["phase"] = "submitting"
+    _state["started_at"] = datetime.utcnow().isoformat()
+
+    for i, task in enumerate(TASKS, 1):
+        if _shutdown.is_set():
+            break
+        code, msg, task_id = submit_one(task)
+        _state["results"].append({
+            "index": i,
+            "label": task["label"],
+            "model": task["model"],
+            "gpu": task["gpu"],
+            "code": code,
+            "message": msg,
+            "task_id": task_id,
+            "time": datetime.utcnow().isoformat(),
+        })
+        if code == 0:
+            _state["submitted"] += 1
+        else:
+            _state["failed"] += 1
+        if i < len(TASKS):
+            time.sleep(GAP)
+
     _state["phase"] = "done"
     _state["finished_at"] = datetime.utcnow().isoformat()
-            _submitted = True
-            print("[submit] 提交成功 taskId=%s" % _state["task_id"], flush=True)
-            return True
-
-        # 已存在/重复等不可重试错误，直接退出
-        if code not in (-1, 60014, 50000):
-            _state["phase"] = "error"
-            _state["finished_at"] = datetime.utcnow().isoformat()
-            print("[submit] 终止：不可重试错误", flush=True)
-            return False
-
-        if i < MAX_ATTEMPTS and not _shutdown.is_set():
-            time.sleep(RETRY_GAP)
-
-    _state["phase"] = "error"
-    _state["finished_at"] = datetime.utcnow().isoformat()
-    return False
+    print("[batch] 完成 submitted=%d failed=%d total=%d"
+          % (_state["submitted"], _state["failed"], _state["total"]), flush=True)
 
 
 class Handler(BaseHTTPRequestHandler):
@@ -184,13 +219,6 @@ class Handler(BaseHTTPRequestHandler):
         else:
             self._json({"error": "not found"}, 404)
 
-    def do_POST(self):
-        if self.path == "/task":
-            submit_task()
-            self._json(_state)
-        else:
-            self._json({"error": "not found"}, 404)
-
     def _json(self, body, code=200):
         raw = json.dumps(body, ensure_ascii=False, default=str).encode()
         self.send_response(code)
@@ -208,23 +236,6 @@ def _handle_signal(signum, _frame):
     _shutdown.set()
 
 
-def main():
-    signal.signal(signal.SIGTERM, _handle_signal)
-    signal.signal(signal.SIGINT, _handle_signal)
-
-    print("[main] strategy_id=%s" % STRATEGY_ID, flush=True)
-    print("[main] model=%s gpu=%s framework=%s" % (MODEL_ADDRESS, TARGET_GPU, FRAMEWORK), flush=True)
-
-    http_thread = threading.Thread(target=_run_http, daemon=False)
-    http_thread.start()
-
-    worker = threading.Thread(target=submit_task, daemon=True)
-    worker.start()
-
-    _shutdown.wait()
-    print("[main] 退出", flush=True)
-
-
 def _run_http():
     server = ThreadingHTTPServer((HTTP_HOST, HTTP_PORT), Handler)
     server.timeout = 1
@@ -232,7 +243,23 @@ def _run_http():
     while not _shutdown.is_set():
         server.handle_request()
     server.server_close()
-    print("[http] 已关闭", flush=True)
+
+
+def main():
+    signal.signal(signal.SIGTERM, _handle_signal)
+    signal.signal(signal.SIGINT, _handle_signal)
+
+    print("[main] strategy_id=%s tasks=%d" % (STRATEGY_ID, len(TASKS)), flush=True)
+    for t in TASKS:
+        print("[main] 计划: %s @ %s" % (t["label"], t["gpu"]), flush=True)
+
+    http_thread = threading.Thread(target=_run_http, daemon=False)
+    http_thread.start()
+
+    worker = threading.Thread(target=run_batch, daemon=True)
+    worker.start()
+
+    _shutdown.wait()
 
 
 if __name__ == "__main__":