feat: add versioned backend scoring workflow

backend/wisegrade/config.py

@@ -0,0 +1,29 @@
+from functools import lru_cache
+from pathlib import Path
+
+from pydantic_settings import BaseSettings, SettingsConfigDict
+
+
+class Settings(BaseSettings):
+    model_config = SettingsConfigDict(env_file=".env", extra="ignore")
+
+    database_url: str = "sqlite:///./wisegrade.db"
+    redis_url: str = "redis://localhost:6379/0"
+    inbox_path: Path = Path("/data/inbox")
+    processed_path: Path = Path("/data/processed")
+    exports_path: Path = Path("/data/exports")
+    deepseek_base_url: str = "https://api.deepseek.com"
+    deepseek_model: str = "deepseek-flash"
+    deepseek_api_key: str = ""
+    wisegrade_secret_key: str = ""
+    embedding_model_name: str = "BAAI/bge-m3"
+    embedding_model_path: Path = Path("/models/bge-m3")
+    embedding_model_version: str = "local"
+    model_timeout_seconds: int = 120
+    model_concurrency: int = 2
+    model_retries: int = 2
+
+
+@lru_cache
+def get_settings() -> Settings:
+    return Settings()