fix: improve import, evidence indexing and material-scoped grading

Preserve document revisions and evidence, harden indexing and export behavior, add explicit material selection and direct-folder import, validate model JSON schemas with safe error messages, and retain student selection while loading scoring data.

backend/wisegrade/rules.py

@@ -1,4 +1,28 @@
-from pydantic import BaseModel, Field, model_validator
+from typing import Literal
+from uuid import uuid4
+
+from pydantic import BaseModel, ConfigDict, Field, model_validator
+
+
+class EvidenceTarget(BaseModel):
+    model_config = ConfigDict(extra="forbid")
+    target_id: str = Field(default_factory=lambda: uuid4().hex, min_length=1, max_length=50)
+    label: str = Field(min_length=1, max_length=300)
+    use: Literal["content", "structure"]
+    allowed_page_types: list[Literal["cover", "abstract", "toc", "body", "appendix", "references"]] = Field(default_factory=list)
+    query: str = ""
+
+    @model_validator(mode="after")
+    def valid_sources(self):
+        from .pages import CONTENT_PAGE_TYPES, STRUCTURE_PAGE_TYPES
+        permitted = CONTENT_PAGE_TYPES if self.use == "content" else STRUCTURE_PAGE_TYPES
+        if not self.label.strip() or not self.target_id.strip():
+            raise ValueError("证据目标名称和标识不能为空")
+        if not self.allowed_page_types:
+            self.allowed_page_types = list(permitted)
+        if any(value not in permitted for value in self.allowed_page_types):
+            raise ValueError("证据目标的页面类型不能扩大用途权限")
+        return self
 
 
 class ScoreLevel(BaseModel):
@@ -15,11 +39,15 @@ class Criterion(BaseModel):
     description: str = Field(min_length=1)
     linked_objectives: list[str] = Field(default_factory=list)
     linked_outcomes: list[str] = Field(default_factory=list)
-    required_evidence: list[str] = Field(default_factory=list)
+    required_evidence: list[EvidenceTarget | str] = Field(default_factory=list)
     score_levels: list[ScoreLevel] = Field(default_factory=list)
 
     @model_validator(mode="after")
     def check_levels(self):
+        ids = [target.target_id if isinstance(target, EvidenceTarget) else f"t{index}"
+               for index, target in enumerate(self.required_evidence) if not isinstance(target, str) or target.strip()]
+        if len(ids) != len(set(ids)):
+            raise ValueError("duplicate evidence target_id")
         if not self.score_levels:
             raise ValueError(f"{self.criterion_id}: score levels are required")
         ranges = sorted(self.score_levels, key=lambda x: x.min)