rag snippet生成入库和写rag

app/schemas/rag.py

@@ -0,0 +1,46 @@
+from __future__ import annotations
+
+from typing import Any, List
+
+from pydantic import BaseModel, ConfigDict, Field
+
+
+class RagItemPayload(BaseModel):
+    """Payload for creating or updating a single RAG item."""
+
+    model_config = ConfigDict(populate_by_name=True, extra="ignore")
+
+    id: int = Field(..., description="Unique identifier for the RAG item.")
+    workspace_id: int = Field(..., alias="workspaceId", description="Workspace identifier.")
+    name: str = Field(..., description="Readable name of the item.")
+    embedding_data: str = Field(..., alias="embeddingData", description="Serialized embedding payload.")
+    type: str = Field(..., description='Item type, e.g. "METRIC".')
+
+
+class RagDeleteRequest(BaseModel):
+    """Payload for deleting a single RAG item."""
+
+    model_config = ConfigDict(populate_by_name=True, extra="ignore")
+
+    id: int = Field(..., description="Identifier of the item to delete.")
+    type: str = Field(..., description="Item type matching the stored record.")
+
+
+class RagRetrieveRequest(BaseModel):
+    """Payload for retrieving RAG items by semantic query."""
+
+    model_config = ConfigDict(populate_by_name=True, extra="ignore")
+
+    query: str = Field(..., description="Search query text.")
+    num: int = Field(..., description="Number of items to return.")
+    workspace_id: int = Field(..., alias="workspaceId", description="Workspace scope for the search.")
+    type: str = Field(..., description="Item type to search, e.g. METRIC.")
+
+
+class RagRetrieveResponse(BaseModel):
+    """Generic RAG retrieval response wrapper."""
+
+    model_config = ConfigDict(extra="allow")
+
+    data: List[Any] = Field(default_factory=list, description="Retrieved items.")
+