fix: 完善自定义分钟数据源配置与异常处理

- 补齐资产类型和周期参数在 API、YAML 与前端编辑器中的保存回读

- 权限判断和分时监控统一复用安全的数据源解析边界

- 增加配置往返及解析异常回归测试

backend/app/api/kline.py

@@ -25,10 +25,10 @@ def _minute_allowed(capset) -> bool:
         return True
     from app.services import preferences
     provider = preferences.get_minute_data_provider()
-    if provider == "tickflow":
-        return False
-    from app.data_providers import custom as custom_sources
-    return custom_sources.provider_has_dataset(provider, "minute")
+    _, fallback, error = kline_sync._resolve_minute_provider(provider)
+    if error is not None:
+        logger.warning("minute provider resolution failed while checking access: %s", error)
+    return not fallback
 
 
 @router.get("/instruments/search")

backend/app/api/settings.py

@@ -371,6 +371,8 @@ class DatasetConfigIn(BaseModel):
     symbols_param: str = "symbols"
     start_param: str = "start_time"
     end_param: str = "end_time"
+    asset_type_param: str | None = None
+    freq_param: str | None = None
 
 
 class AuthConfigIn(BaseModel):
@@ -1429,4 +1431,3 @@ def update_review_push(req: ReviewPushIn) -> dict:
     from app.services import preferences
     saved = preferences.set_review_push_channels(req.channels)
     return {"review_push_channels": saved}
-

backend/app/data_providers/custom/loader.py

@@ -296,6 +296,8 @@ def _config_to_dict(config: CustomSourceConfig) -> dict:
             "symbols_param": ds.symbols_param,
             "start_param": ds.start_param,
             "end_param": ds.end_param,
+            **({"asset_type_param": ds.asset_type_param} if ds.asset_type_param else {}),
+            **({"freq_param": ds.freq_param} if ds.freq_param else {}),
         }
     return out
 
@@ -401,6 +403,10 @@ def _sanitize_dataset(ds_cfg: dict) -> dict:
         out["start_param"] = str(ds_cfg["start_param"])
     if ds_cfg.get("end_param"):
         out["end_param"] = str(ds_cfg["end_param"])
+    if ds_cfg.get("asset_type_param"):
+        out["asset_type_param"] = str(ds_cfg["asset_type_param"])
+    if ds_cfg.get("freq_param"):
+        out["freq_param"] = str(ds_cfg["freq_param"])
     return out
 
 
@@ -496,4 +502,3 @@ def _load_entry(entry_ref: str):
 
 # 模块导入时即扫描一次, 保证 names()/_allowed_data_providers() 在 startup 前可用。
 _load_builtin_plugins()
-

backend/app/services/kline_sync.py

@@ -733,13 +733,14 @@ def sync_minute_batch(
 def intraday_monitor_support(capset: CapabilitySet | None) -> dict[str, object]:
     """返回分时信号监控可用的数据能力和单轮标的上限。"""
     provider_name = preferences.get_minute_data_provider()
-    if provider_name != "tickflow":
-        from app.data_providers import custom as custom_sources
-        if custom_sources.provider_has_dataset(provider_name, "minute"):
-            return {
-                "available": True, "source": "custom_minute", "max_symbols": 100,
-                "reason": "使用已配置的分钟数据插件",
-            }
+    _, fallback, error = _resolve_minute_provider(provider_name)
+    if not fallback:
+        return {
+            "available": True, "source": "custom_minute", "max_symbols": 100,
+            "reason": "使用已配置的分钟数据插件",
+        }
+    if error is not None:
+        logger.warning("minute provider resolution failed while checking monitor support: %s", error)
     if capset is None:
         return {
             "available": False, "source": None, "max_symbols": 0,

backend/tests/test_custom_minute_config.py

@@ -0,0 +1,29 @@
+from app.api.settings import DatasetConfigIn
+from app.data_providers.custom.config import CustomSourceConfig, _dataset_from_dict
+from app.data_providers.custom.loader import _config_to_dict, _sanitize_for_yaml
+
+
+def test_minute_request_parameter_names_survive_config_round_trip():
+    dataset = DatasetConfigIn(
+        url="https://example.test/minute",
+        method="GET",
+        asset_type_param="asset",
+        freq_param="period",
+    ).model_dump()
+
+    cleaned = _sanitize_for_yaml({
+        "name": "test_source",
+        "display_name": "Test Source",
+        "datasets": {"minute": dataset},
+    })
+    parsed = _dataset_from_dict(cleaned["datasets"]["minute"])
+    exposed = _config_to_dict(CustomSourceConfig(
+        name="test_source",
+        display_name="Test Source",
+        datasets={"minute": parsed},
+    ))
+
+    assert parsed.asset_type_param == "asset"
+    assert parsed.freq_param == "period"
+    assert exposed["datasets"]["minute"]["asset_type_param"] == "asset"
+    assert exposed["datasets"]["minute"]["freq_param"] == "period"

backend/tests/test_minute_routing.py

@@ -639,3 +639,44 @@ def test_resolve_minute_provider_success_returns_provider(monkeypatch):
     assert provider is mock_provider
     assert fallback is False
     assert err is None
+
+
+def test_minute_allowed_resolver_exception_returns_false(monkeypatch):
+    """权限入口复用安全 resolver, 插件注册异常不再穿透为 500。"""
+    from app.api import kline as kline_api
+    from app.tickflow.capabilities import CapabilitySet
+
+    monkeypatch.setattr(
+        "app.services.preferences.get_minute_data_provider",
+        lambda: "broken",
+    )
+
+    def _raising(name, dataset):
+        raise RuntimeError("registry corrupted")
+
+    monkeypatch.setattr("app.data_providers.custom.provider_has_dataset", _raising)
+
+    assert kline_api._minute_allowed(CapabilitySet()) is False
+
+
+def test_intraday_monitor_support_resolver_exception_falls_back(monkeypatch):
+    """监控入口解析自定义源失败后继续按 TickFlow 能力判断。"""
+    from app.tickflow.capabilities import Cap, CapabilitySet
+
+    monkeypatch.setattr(
+        kline_sync.preferences,
+        "get_minute_data_provider",
+        lambda: "broken",
+    )
+
+    def _raising(name, dataset):
+        raise RuntimeError("registry corrupted")
+
+    monkeypatch.setattr("app.data_providers.custom.provider_has_dataset", _raising)
+    capset = CapabilitySet()
+    capset.grant(Cap.KLINE_MINUTE_BATCH)
+
+    support = kline_sync.intraday_monitor_support(capset)
+
+    assert support["available"] is True
+    assert support["source"] == "minute_batch"

docs/custom-data-source.md

@@ -140,6 +140,15 @@ start_param: start_time
 end_param: end_time
 ```
 
+分钟数据源如果需要区分资产类型或周期，可继续配置：
+
+```yaml
+asset_type_param: asset_type
+freq_param: period
+```
+
+配置后，分钟请求会分别传入 `stock` / `etf` / `index` 和 `1m`；留空时不向上游发送这两个参数，以兼容已有数据源。
+
 ## 鉴权
 
 支持三种简单鉴权:
@@ -295,4 +304,3 @@ datasets:
 ```
 
 把这段 YAML 保存为 `data/data_sources/my_source.yaml`,然后在设置页重新加载即可。
-

frontend/src/lib/api.ts

@@ -821,6 +821,8 @@ export interface DatasetConfig {
   symbols_param?: string
   start_param?: string
   end_param?: string
+  asset_type_param?: string | null
+  freq_param?: string | null
 }
 
 export interface AuthConfig {

frontend/src/pages/settings/DataSourceEditor.tsx

@@ -395,6 +395,27 @@ function DatasetDetail({
               </Field>
             </div>
 
+            {datasetKey === 'minute' && (
+              <div className="grid grid-cols-1 sm:grid-cols-2 gap-2">
+                <Field label="资产类型参数">
+                  <input
+                    value={cfg.asset_type_param ?? ''}
+                    onChange={e => onUpdate({ asset_type_param: e.target.value || null })}
+                    placeholder="asset_type"
+                    className={`${INPUT_CLS} w-full`}
+                  />
+                </Field>
+                <Field label="周期参数">
+                  <input
+                    value={cfg.freq_param ?? ''}
+                    onChange={e => onUpdate({ freq_param: e.target.value || null })}
+                    placeholder="period"
+                    className={`${INPUT_CLS} w-full`}
+                  />
+                </Field>
+              </div>
+            )}
+
             <div>
               <div className="flex items-center justify-between mb-2">
                 <div className="text-[10px] uppercase tracking-widest text-muted">字段映射</div>