From 8abf5d57c1b34040762770fefa509760c8449c19 Mon Sep 17 00:00:00 2001 From: Michael Poluektov Date: Thu, 21 Nov 2024 23:49:58 +0000 Subject: [PATCH] remove unused schemas file --- backend/open_webui/utils/schemas.py | 115 ---------------------------- 1 file changed, 115 deletions(-) delete mode 100644 backend/open_webui/utils/schemas.py 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_}")