feat: expand module workflows, dynamic config, notifications and console API

src/gyxx_flow/catalog.py

@@ -42,6 +42,15 @@ class WorkflowDataFlow:
     destinations: tuple[WorkflowDataEndpoint, ...]
 
 
+@dataclass(frozen=True, slots=True)
+class WorkflowTopicConfig:
+    """Operator-facing topic input metadata for a workflow."""
+
+    default_keyword: str
+    label: str = "话题关键词"
+    hint: str = "输入完整话题或关键词，系统会在搜索结果中按包含关系选中。"
+
+
 @dataclass(frozen=True, slots=True)
 class WorkflowStepEntry:
     step_id: str
@@ -52,8 +61,9 @@ class WorkflowStepEntry:
     depends_on: tuple[str, ...] = ()
     run_after_failure: bool = False
     timeout_seconds: float | None = None
-    replay_policy: Literal["guarded", "idempotent"] | None = None
+    replay_policy: Literal["guarded", "idempotent", "repeatable"] | None = None
     data_flow: WorkflowDataFlow | None = None
+    has_hyperlink: bool = False
 
 
 @dataclass(frozen=True, slots=True)
@@ -67,6 +77,8 @@ class WorkflowEntry:
     source_task_name: str | None = None
     note: str | None = None
     steps: tuple[WorkflowStepEntry, ...] = ()
+    notification_workflow_id: str | None = None
+    topic_config: WorkflowTopicConfig | None = None
 
 
 @dataclass(frozen=True, slots=True)
@@ -205,6 +217,7 @@ def _parse_workflow(item: Any) -> WorkflowEntry:
     task_name = provenance.get("task_name")
     if trigger == "scheduled" and (not isinstance(task_name, str) or not task_name):
         raise CatalogError(f"scheduled workflow requires source task name: {workflow_id}")
+    topic_config = _parse_topic_config(item.get("topic_config"), workflow_id)
     return WorkflowEntry(
         workflow_id=workflow_id,
         module=module,
@@ -215,6 +228,37 @@ def _parse_workflow(item: Any) -> WorkflowEntry:
         source_task_name=task_name,
         note=item.get("note"),
         steps=steps,
+        topic_config=topic_config,
+    )
+
+
+def _parse_topic_config(value: Any, workflow_id: str) -> WorkflowTopicConfig | None:
+    if value is None:
+        return None
+    if not isinstance(value, dict):
+        raise CatalogError(f"topic_config must be an object for {workflow_id}")
+    default_keyword = value.get("default_keyword")
+    if (
+        not isinstance(default_keyword, str)
+        or not default_keyword.strip()
+        or len(default_keyword.strip()) > 120
+    ):
+        raise CatalogError(
+            f"topic_config default_keyword is invalid for {workflow_id}"
+        )
+    fields: dict[str, str] = {}
+    for field, fallback in (
+        ("label", "话题关键词"),
+        ("hint", "输入完整话题或关键词，系统会在搜索结果中按包含关系选中。"),
+    ):
+        raw = value.get(field, fallback)
+        if not isinstance(raw, str) or not raw.strip() or len(raw.strip()) > 240:
+            raise CatalogError(f"topic_config {field} is invalid for {workflow_id}")
+        fields[field] = raw.strip()
+    return WorkflowTopicConfig(
+        default_keyword=default_keyword.strip(),
+        label=fields["label"],
+        hint=fields["hint"],
     )
 
 
@@ -263,6 +307,7 @@ def _parse_workflow_steps(
         if replay_policy is not None and replay_policy not in {
             "guarded",
             "idempotent",
+            "repeatable",
         }:
             raise CatalogError(
                 f"workflow step replay_policy is invalid for {workflow_id}.{step_id}"
@@ -279,12 +324,18 @@ def _parse_workflow_steps(
             raise CatalogError(
                 f"workflow step description is invalid for {workflow_id}.{step_id}"
             )
+        has_hyperlink = raw_step.get("has_hyperlink", False)
+        if not isinstance(has_hyperlink, bool):
+            raise CatalogError(
+                f"workflow step has_hyperlink is invalid for {workflow_id}.{step_id}"
+            )
         steps.append(
             WorkflowStepEntry(
                 step_id=step_id,
                 entry=entry,
                 name=name.strip() if name is not None else None,
                 description=description.strip() if description is not None else None,
+                has_hyperlink=has_hyperlink,
                 args=_parse_args(raw_step.get("args", []), workflow_id),
                 depends_on=tuple(depends_on),
                 run_after_failure=run_after_failure,