Debug: Just Minor Type mismatch

plexe/internal/common/utils/pydantic_utils.py

@@ -67,19 +67,20 @@ def map_to_basemodel(name: str, schema: dict | Type[BaseModel]) -> Type[BaseMode
             # Handle both Dict[str, type] and Dict[str, str] formats
             annotated_schema = {}
 
+            type_mapping = {
+                "int": int,
+                "float": float,
+                "str": str,
+                "bool": bool,
+                "List[int]": List[int],
+                "List[float]": List[float],
+                "List[str]": List[str],
+                "List[bool]": List[bool],
+            }
+
             for k, v in schema.items():
                 # If v is a string like "int", convert it to the actual type
                 if isinstance(v, str):
-                    type_mapping = {
-                        "int": int,
-                        "float": float,
-                        "str": str,
-                        "bool": bool,
-                        "List[int]": List[int],
-                        "List[float]": List[float],
-                        "List[str]": List[str],
-                        "List[bool]": List[bool],
-                    }
                     if v in type_mapping:
                         annotated_schema[k] = (type_mapping[v], ...)
                     else:

plexe/models.py

@@ -38,7 +38,7 @@
 import uuid
 import warnings
 from datetime import datetime
-from typing import Dict, List, Type, Any
+from typing import Dict, List, Type, Any, Optional
 from deprecated import deprecated
 
 import pandas as pd
@@ -93,8 +93,8 @@ class Model:
     def __init__(
         self,
         intent: str,
-        input_schema: Type[BaseModel] | Dict[str, type] = None,
-        output_schema: Type[BaseModel] | Dict[str, type] = None,
+        input_schema: Type[BaseModel] | Dict[str, type] = {},
+        output_schema: Type[BaseModel] | Dict[str, type] = {},
         distributed: bool = False,
     ):
         """
@@ -110,8 +110,10 @@ def __init__(
 
         # The model's identity is defined by these fields
         self.intent: str = intent
-        self.input_schema: Type[BaseModel] = map_to_basemodel("in", input_schema) if input_schema else None
-        self.output_schema: Type[BaseModel] = map_to_basemodel("out", output_schema) if output_schema else None
+        self.input_schema: Optional[Type[BaseModel]] = map_to_basemodel("in", input_schema) if input_schema else None
+        self.output_schema: Optional[Type[BaseModel]] = (
+            map_to_basemodel("out", output_schema) if output_schema else None
+        )
         self.training_data: Dict[str, Dataset] = dict()
         self.distributed: bool = distributed
 
@@ -142,10 +144,10 @@ def build(
         self,
         datasets: List[pd.DataFrame | DatasetGenerator],
         provider: str | ProviderConfig = "openai/gpt-4o-mini",
-        timeout: int = None,
-        max_iterations: int = None,
+        timeout: int | None = None,
+        max_iterations: int | None = None,
         run_timeout: int = 1800,
-        callbacks: List[Callback] = None,
+        callbacks: List[Callback] | None = None,
         verbose: bool = False,
         # resume: bool = False,
         enable_checkpointing: bool = False,