Files
mai-bot/src/webui/config_schema.py
DrSmoothl d9a509b6c2 feat(chat): refactor chat message handling and introduce private messaging support
- Updated `uni_message_sender.py` to allow for private messaging by removing the mandatory group ID and adding user ID handling.
- Enhanced chat history retrieval and clearing functions in `routes.py` and `service.py` to support both group and private chat scenarios.
- Introduced a new `ChatScrollContext` for managing message scrolling and highlighting in the chat UI.
- Created a `ListItemEditorHookFactory` for rendering a rich UI editor for list items in configuration settings, replacing the previous JSON text display.
- Improved message serialization for consistent display in chat history.
- Added detailed logging for chat history operations and error handling.

Co-authored-by: Copilot <copilot@github.com>
2026-05-01 17:54:13 +08:00

151 lines
5.3 KiB
Python

from typing import Any, Dict, List, get_args, get_origin
import inspect
from pydantic_core import PydanticUndefined
from src.config.config_base import ConfigBase
class ConfigSchemaGenerator:
@classmethod
def generate_schema(cls, config_class: type[ConfigBase], include_nested: bool = True) -> Dict[str, Any]:
return cls.generate_config_schema(config_class, include_nested=include_nested)
@classmethod
def generate_config_schema(cls, config_class: type[ConfigBase], include_nested: bool = True) -> Dict[str, Any]:
fields: List[Dict[str, Any]] = []
nested: Dict[str, Dict[str, Any]] = {}
for field_name, field_info in config_class.model_fields.items():
if field_name in {"field_docs", "_validate_any", "suppress_any_warning"}:
continue
field_schema = cls._build_field_schema(config_class, field_name, field_info.annotation, field_info)
fields.append(field_schema)
if include_nested:
nested_schema = cls._build_nested_schema(field_info.annotation)
if nested_schema is not None:
nested[field_name] = nested_schema
schema: Dict[str, Any] = {
"className": config_class.__name__,
"classDoc": (config_class.__doc__ or "").strip(),
"fields": fields,
"nested": nested,
}
# 将 UI 分组元数据写入 schema
ui_parent = getattr(config_class, "__ui_parent__", "")
ui_label = getattr(config_class, "__ui_label__", "")
ui_icon = getattr(config_class, "__ui_icon__", "")
if ui_parent:
schema["uiParent"] = ui_parent
if ui_label:
schema["uiLabel"] = ui_label
if ui_icon:
schema["uiIcon"] = ui_icon
return schema
@classmethod
def _build_nested_schema(cls, annotation: Any) -> Dict[str, Any] | None:
origin = get_origin(annotation)
args = get_args(annotation)
if inspect.isclass(annotation) and issubclass(annotation, ConfigBase):
return cls.generate_config_schema(annotation)
if origin in {list, set, tuple} and args:
first = args[0]
if inspect.isclass(first) and issubclass(first, ConfigBase):
return cls.generate_config_schema(first)
return None
@classmethod
def _build_field_schema(
cls, config_class: type[ConfigBase], field_name: str, annotation: Any, field_info: Any
) -> Dict[str, Any]:
field_docs = config_class.get_class_field_docs()
field_type = cls._map_field_type(annotation)
raw_description = field_docs.get(field_name, field_info.description or "")
# `_wrap_` 标记在配置类 docstring 中表示该说明应作为块级注释(独立成行)
# 在前端展示时把它转为换行符,使描述以新行起始或在中间换行
description = raw_description.replace("_wrap_", "\n").strip("\n")
schema: Dict[str, Any] = {
"name": field_name,
"type": field_type,
"label": field_name,
"description": description,
"required": field_info.is_required(),
}
if field_info.default is not PydanticUndefined:
schema["default"] = field_info.default
origin = get_origin(annotation)
args = get_args(annotation)
if origin in {list, set} and args:
schema["items"] = {"type": cls._map_field_type(args[0])}
if options := cls._extract_options(annotation):
schema["options"] = options
# Task 1c: Merge json_schema_extra (x-widget, x-icon, step, etc.)
if hasattr(field_info, "json_schema_extra") and field_info.json_schema_extra:
schema.update(field_info.json_schema_extra)
# Task 1d: Map Pydantic constraints to minValue/maxValue (frontend naming convention)
if hasattr(field_info, "metadata") and field_info.metadata:
for constraint in field_info.metadata:
if hasattr(constraint, "ge"):
schema["minValue"] = constraint.ge
if hasattr(constraint, "le"):
schema["maxValue"] = constraint.le
return schema
@staticmethod
def _extract_options(annotation: Any) -> List[str] | None:
origin = get_origin(annotation)
if origin is None:
return None
if str(origin) != "typing.Literal":
return None
args = get_args(annotation)
options = [str(item) for item in args]
return options or None
@classmethod
def _map_field_type(cls, annotation: Any) -> str:
origin = get_origin(annotation)
args = get_args(annotation)
if origin in {list, set, tuple}:
return "array"
if inspect.isclass(annotation) and issubclass(annotation, ConfigBase):
return "object"
if annotation is bool:
return "boolean"
if annotation is int:
return "integer"
if annotation is float:
return "number"
if annotation is str:
return "string"
if origin in {list, set, tuple} and args:
return "array"
if origin in {dict}:
return "object"
if origin is not None and str(origin) == "typing.Literal":
return "select"
return "string"