diff --git a/backend/open_webui/utils/schemas.py b/backend/open_webui/utils/schemas.py
deleted file mode 100644
index 21c9824f0..000000000
--- a/backend/open_webui/utils/schemas.py
+++ /dev/null
@@ -1,115 +0,0 @@
-from ast import literal_eval
-from typing import Any, Literal, Optional, Type
-
-from pydantic import BaseModel, Field, create_model
-
-
-def json_schema_to_model(tool_dict: dict[str, Any]) -> Type[BaseModel]:
-    """
-    Converts a JSON schema to a Pydantic BaseModel class.
-
-    Args:
-        json_schema: The JSON schema to convert.
-
-    Returns:
-        A Pydantic BaseModel class.
-    """
-
-    # Extract the model name from the schema title.
-    model_name = tool_dict["name"]
-    schema = tool_dict["parameters"]
-
-    # Extract the field definitions from the schema properties.
-    field_definitions = {
-        name: json_schema_to_pydantic_field(name, prop, schema.get("required", []))
-        for name, prop in schema.get("properties", {}).items()
-    }
-
-    # Create the BaseModel class using create_model().
-    return create_model(model_name, **field_definitions)
-
-
-def json_schema_to_pydantic_field(
-    name: str, json_schema: dict[str, Any], required: list[str]
-) -> Any:
-    """
-    Converts a JSON schema property to a Pydantic field definition.
-
-    Args:
-        name: The field name.
-        json_schema: The JSON schema property.
-
-    Returns:
-        A Pydantic field definition.
-    """
-
-    # Get the field type.
-    type_ = json_schema_to_pydantic_type(json_schema)
-
-    # Get the field description.
-    description = json_schema.get("description")
-
-    # Get the field examples.
-    examples = json_schema.get("examples")
-
-    # Create a Field object with the type, description, and examples.
-    # The 'required' flag will be set later when creating the model.
-    return (
-        type_,
-        Field(
-            description=description,
-            examples=examples,
-            default=... if name in required else None,
-        ),
-    )
-
-
-def json_schema_to_pydantic_type(json_schema: dict[str, Any]) -> Any:
-    """
-    Converts a JSON schema type to a Pydantic type.
-
-    Args:
-        json_schema: The JSON schema to convert.
-
-    Returns:
-        A Pydantic type.
-    """
-
-    type_ = json_schema.get("type")
-
-    if type_ == "string" or type_ == "str":
-        return str
-    elif type_ == "integer" or type_ == "int":
-        return int
-    elif type_ == "number" or type_ == "float":
-        return float
-    elif type_ == "boolean" or type_ == "bool":
-        return bool
-    elif type_ == "array" or type_ == "list":
-        items_schema = json_schema.get("items")
-        if items_schema:
-            item_type = json_schema_to_pydantic_type(items_schema)
-            return list[item_type]
-        else:
-            return list
-    elif type_ == "object":
-        # Handle nested models.
-        properties = json_schema.get("properties")
-        if properties:
-            nested_model = json_schema_to_model(json_schema)
-            return nested_model
-        else:
-            return dict
-    elif type_ == "null":
-        return Optional[Any]  # Use Optional[Any] for nullable fields
-    elif type_ == "literal":
-        enum = json_schema.get("enum")
-        if enum is None:
-            raise ValueError("Enum values must be provided for 'literal' type.")
-        return Literal[literal_eval(enum)]
-    elif type_ == "optional":
-        inner_schema = json_schema.get("items", {"type": "string"})
-        inner_type = json_schema_to_pydantic_type(inner_schema)
-        return Optional[inner_type]
-    else:
-        raise ValueError(f"Unsupported JSON schema type: {type_}")