自动任务按推理、量化因子、微调轮流生成并派发。

Co-authored-by: Cursor <cursoragent@cursor.com>

tests/test_core_flow.py

@@ -791,16 +791,24 @@ class CoreFlowTest(unittest.TestCase):
             for task in first:
                 self.assertIsNone(task.node_id)
                 self.assertEqual(task.status, TaskStatus.PENDING)
-                self.assertEqual(task.task_type, "alpha_mining")
-                self.assertIsInstance(task.payload["seed"], int)
-                self.assertTrue(task.payload["operators"])
-                self.assertTrue(task.payload["symbol"])
+                self.assertEqual(task.task_type, "llm_inference")
+                self.assertEqual(task.payload["model"], "qwen2.5-3b-instruct-q4_k_m")
+                self.assertTrue(task.payload["prompt"])
+                self.assertEqual(task.payload["max_tokens"], 256)
                 self.assertGreaterEqual(len(task.payload["nonce"]), 8)
             quiet = maybe_generate_alpha_batch(session, now=start + timedelta(hours=1))
             self.assertEqual(quiet, [])
             later = maybe_generate_alpha_batch(session, now=start + timedelta(hours=2))
             session.commit()
             self.assertEqual(len(later), 3)
+            self.assertEqual({task.task_type for task in later}, {"alpha_mining"})
+            self.assertTrue(all(task.payload["operators"] and task.payload["symbol"] for task in later))
+            finetune = maybe_generate_alpha_batch(session, now=start + timedelta(hours=4))
+            session.commit()
+            self.assertEqual(len(finetune), 3)
+            self.assertEqual({task.task_type for task in finetune}, {"lora_training"})
+            self.assertEqual({task.payload["rank"] for task in finetune}, {8, 16, 32})
+            self.assertTrue(all(task.payload["base_model"] == "qwen2.5-3b" and task.payload["steps"] == 100 for task in finetune))
             self.assertNotEqual(later[0].payload["batch_id"], first[0].payload["batch_id"])
             queued = session.get(ComputeTask, first[0].id)
             queued.deadline_at = start - timedelta(minutes=1)
@@ -819,7 +827,7 @@ class CoreFlowTest(unittest.TestCase):
         assigned = beat.json()["assigned_task"]
         self.assertIsNotNone(assigned)
         self.assertEqual(assigned["status"], "processing")
-        self.assertEqual(assigned["task_type"], "alpha_mining")
+        self.assertEqual(assigned["task_type"], "llm_inference")
         again = self.client.post("/api/v1/node/heartbeat", json={"sn": "NODE-ALPHA"})
         self.assertIsNone(again.json()["assigned_task"])
         with SessionLocal() as session:
@@ -827,12 +835,28 @@ class CoreFlowTest(unittest.TestCase):
             holding = session.scalars(
                 select(ComputeTask).where(
                     ComputeTask.node_id == node.id,
-                    ComputeTask.task_type == "alpha_mining",
+                    ComputeTask.task_type == "llm_inference",
                     ComputeTask.status == TaskStatus.PROCESSING,
                 )
             ).all()
             self.assertEqual(len(holding), 1)
 
+        while assigned["task_type"] != "alpha_mining":
+            finished = self.client.post(
+                "/api/v1/node/task/report",
+                json={
+                    "sn": "NODE-ALPHA",
+                    "task_id": assigned["task_id"],
+                    "success": True,
+                    "nonce": assigned["payload"]["nonce"],
+                    "result": {"output": "inference finished", "summary": "inference finished"},
+                },
+            )
+            self.assertEqual(finished.status_code, 200, finished.text)
+            stepped = self.client.post("/api/v1/node/heartbeat", json={"sn": "NODE-ALPHA"})
+            assigned = stepped.json()["assigned_task"]
+            self.assertIsNotNone(assigned)
+
         high = self.client.post(
             "/api/v1/node/task/report",
             json={