refactor(types): update type hints to use built-in generic types

reme/core/op/mcp_tool.py

@@ -1,7 +1,5 @@
 """MCP (Model Context Protocol) tool integration for remote tool execution."""
 
-from typing import List
-
 from mcp.types import CallToolResult, TextContent
 
 from .base_tool import BaseTool
@@ -16,9 +14,9 @@ class MCPTool(BaseTool):
         self,
         mcp_server: str = "",
         tool_name: str = "",
-        parameter_required: List[str] | None = None,
-        parameter_optional: List[str] | None = None,
-        parameter_deleted: List[str] | None = None,
+        parameter_required: list[str] | None = None,
+        parameter_optional: list[str] | None = None,
+        parameter_deleted: list[str] | None = None,
         max_retries: int = 3,
         timeout: float | None = None,
         raise_exception: bool = False,
@@ -28,9 +26,9 @@ class MCPTool(BaseTool):
 
         self.mcp_server: str = mcp_server
         self.tool_name: str = tool_name
-        self.parameter_required: List[str] | None = parameter_required
-        self.parameter_optional: List[str] | None = parameter_optional
-        self.parameter_deleted: List[str] | None = parameter_deleted
+        self.parameter_required: list[str] | None = parameter_required
+        self.parameter_optional: list[str] | None = parameter_optional
+        self.parameter_deleted: list[str] | None = parameter_deleted
         self.timeout: float | None = timeout
 
         # Example MCP marketplace: https://bailian.console.aliyun.com/?tab=mcp#/mcp-market

reme/core/schema/tool_call.py

@@ -1,7 +1,7 @@
 """MCP Tool Schema definitions for recursive JSON Schema representation."""
 
 import json
-from typing import Any, Dict, List, Optional, Union
+from typing import Any, Union, Optional
 
 from mcp.types import Tool
 from pydantic import BaseModel, ConfigDict, Field, model_validator, field_validator
@@ -16,10 +16,10 @@ class ToolAttr(BaseModel):
 
     type: str = Field(default=str(JsonSchemaEnum.STRING), description="The data type of the attribute")
     description: Optional[str] = Field(default=None, description="Description of the attribute")
-    required: Optional[List[str]] = Field(default=None, description="Required property names for object types")
-    properties: Optional[Dict[str, "ToolAttr"]] = Field(default=None, description="Child properties for objects")
-    items: Optional[Union[Dict[str, Any], "ToolAttr"]] = Field(default=None, description="Schema for array items")
-    enum: Optional[List[str]] = Field(default=None, description="Allowed values for the attribute")
+    required: Optional[list[str]] = Field(default=None, description="Required property names for object types")
+    properties: Optional[dict[str, "ToolAttr"]] = Field(default=None, description="Child properties for objects")
+    items: Optional[Union[dict[str, Any], "ToolAttr"]] = Field(default=None, description="Schema for array items")
+    enum: Optional[list[str]] = Field(default=None, description="Allowed values for the attribute")
 
     @field_validator("type")
     @classmethod
@@ -129,9 +129,13 @@ class ToolCall(BaseModel):
 
         return data
 
-    def simple_input_dump(self) -> dict:
-        """Returns a standardized tool definition dictionary."""
-        return {
+    def simple_input_dump(self, as_dict: bool = True) -> dict | str:
+        """Returns a standardized tool definition dictionary or JSON string.
+        
+        Args:
+            as_dict: If True, returns dict; if False, returns JSON string.
+        """
+        result = {
             "type": self.type,
             self.type: {
                 "name": self.name,
@@ -139,10 +143,15 @@ class ToolCall(BaseModel):
                 "parameters": self.parameters.simple_input_dump(),
             },
         }
+        return result if as_dict else json.dumps(result)
 
-    def simple_output_dump(self) -> dict:
-        """Convert ToolCall to output format dictionary for API responses."""
-        return {
+    def simple_output_dump(self, as_dict: bool = True) -> dict | str:
+        """Convert ToolCall to output format dictionary or JSON string for API responses.
+        
+        Args:
+            as_dict: If True, returns dict; if False, returns JSON string.
+        """
+        result = {
             "index": self.index,
             "id": self.id,
             self.type: {
@@ -151,6 +160,7 @@ class ToolCall(BaseModel):
             },
             "type": self.type,
         }
+        return result if as_dict else json.dumps(result)
 
     @property
     def argument_dict(self) -> dict:

reme/core/schema/vector_node.py

@@ -1,6 +1,5 @@
 """Defines the data structure for individual vector embedding nodes within a retrieval system."""
 
-from typing import List, Dict
 from uuid import uuid4
 
 from pydantic import BaseModel, Field
@@ -11,5 +10,5 @@ class VectorNode(BaseModel):
 
     vector_id: str = Field(default_factory=lambda: uuid4().hex)
     content: str = Field(default="")
-    vector: List[float] | None = Field(default=None)
-    metadata: Dict[str, str | bool | int | float] = Field(default_factory=dict)
+    vector: list[float] | None = Field(default=None)
+    metadata: dict[str, str | bool | int | float] = Field(default_factory=dict)

reme/core/utils/http_client.py

@@ -2,7 +2,6 @@
 
 import json
 from collections.abc import AsyncIterator
-from typing import Optional
 
 import httpx
 from loguru import logger
@@ -45,7 +44,7 @@ class HttpClient:
         response.raise_for_status()
         return response.json()
 
-    async def execute_flow(self, flow_name: str, **kwargs) -> Optional[Response]:
+    async def execute_flow(self, flow_name: str, **kwargs) -> Response | None:
         """Execute a flow with automated retry logic."""
         endpoint = f"{self.base_url}/{flow_name}"