dev: refactor; populate models in more nodes; use Pydantic in endpoints for input validation

app/api/schemas_in.py

@@ -0,0 +1,66 @@
+from __future__ import annotations
+
+from typing import Any, Optional, Literal
+from pydantic import BaseModel, Field, field_validator, model_validator, conint
+
+
+class ListAssetsQuery(BaseModel):
+    include_tags: list[str] = Field(default_factory=list)
+    exclude_tags: list[str] = Field(default_factory=list)
+    name_contains: Optional[str] = None
+
+    # Accept either a JSON string (query param) or a dict
+    metadata_filter: Optional[dict[str, Any]] = None
+
+    limit: conint(ge=1, le=500) = 20
+    offset: conint(ge=0) = 0
+
+    sort: Literal["name", "created_at", "updated_at", "size", "last_access_time"] = "created_at"
+    order: Literal["asc", "desc"] = "desc"
+
+    @field_validator("include_tags", "exclude_tags", mode="before")
+    @classmethod
+    def _split_csv_tags(cls, v):
+        # Accept "a,b,c" or ["a","b"] (we are liberal in what we accept)
+        if v is None:
+            return []
+        if isinstance(v, str):
+            return [t.strip() for t in v.split(",") if t.strip()]
+        if isinstance(v, list):
+            out: list[str] = []
+            for item in v:
+                if isinstance(item, str):
+                    out.extend([t.strip() for t in item.split(",") if t.strip()])
+            return out
+        return v
+
+    @field_validator("metadata_filter", mode="before")
+    @classmethod
+    def _parse_metadata_json(cls, v):
+        if v is None or isinstance(v, dict):
+            return v
+        if isinstance(v, str) and v.strip():
+            import json
+            try:
+                parsed = json.loads(v)
+            except Exception as e:
+                raise ValueError(f"metadata_filter must be JSON: {e}") from e
+            if not isinstance(parsed, dict):
+                raise ValueError("metadata_filter must be a JSON object")
+            return parsed
+        return None
+
+
+class UpdateAssetBody(BaseModel):
+    name: Optional[str] = None
+    tags: Optional[list[str]] = None
+    user_metadata: Optional[dict[str, Any]] = None
+
+    @model_validator(mode="after")
+    def _at_least_one(self):
+        if self.name is None and self.tags is None and self.user_metadata is None:
+            raise ValueError("Provide at least one of: name, tags, user_metadata.")
+        if self.tags is not None:
+            if not isinstance(self.tags, list) or not all(isinstance(t, str) for t in self.tags):
+                raise ValueError("Field 'tags' must be an array of strings.")
+        return self