fix: remove warnings, upgrade typing

docs/core/getting_started.md

@@ -117,14 +117,13 @@ Upon successful authentication, your project will contain a `.env` file with you
 Open `main.py` in your code editor. You can start with this example code:
 ```python
 from dataclasses import dataclass
-from typing import Optional
 
 
 @dataclass
 class EchoIn:
     message: str
-    repeat: Optional[int] = 1
-    prefix: Optional[str] = None
+    repeat: int | None = 1
+    prefix: str | None = None
 
 
 @dataclass

docs/eval/custom_evaluators.md

@@ -92,7 +92,6 @@ class MyEvaluatorConfig(BaseEvaluatorConfig[MyEvaluationCriteria]):
 Implement the core evaluation logic:
 
 ```python
-from typing import List
 from uipath.eval.evaluators import BaseEvaluator
 from uipath.eval.models import AgentExecution, NumericEvaluationResult
 import json
@@ -150,13 +149,13 @@ class MyCustomEvaluator(
             }),
         )
 
-    def _extract_values(self, agent_execution: AgentExecution) -> List[str]:
+    def _extract_values(self, agent_execution: AgentExecution) -> list[str]:
         """Extract values from agent execution (implement your logic)."""
         # Your custom extraction logic here
         return []
 
     def _compute_similarity(
-        self, actual: List[str], expected: List[str]
+        self, actual: list[str], expected: list[str]
     ) -> float:
         """Compute similarity score (implement your logic)."""
         # Your custom scoring logic here
@@ -248,7 +247,7 @@ Custom evaluators often need to extract information from tool calls in the agent
 ```python
 from uipath.eval._helpers.evaluators_helpers import extract_tool_calls
 
-def _process_tool_calls(self, agent_execution: AgentExecution) -> List[str]:
+def _process_tool_calls(self, agent_execution: AgentExecution) -> list[str]:
     """Extract and process tool calls from the execution trace."""
     tool_calls = extract_tool_calls(agent_execution.agent_trace)
 
@@ -286,7 +285,6 @@ Here's a complete example based on real-world usage that compares data patterns
 ```python
 """Custom evaluator for pattern comparison."""
 import json
-from typing import List
 
 from pydantic import Field
 from uipath.eval.evaluators import BaseEvaluator
@@ -299,7 +297,7 @@ from uipath.eval.models import AgentExecution
 from uipath.eval._helpers.evaluators_helpers import extract_tool_calls
 
 
-def _compute_jaccard_similarity(expected: List[str], actual: List[str]) -> float:
+def _compute_jaccard_similarity(expected: list[str], actual: list[str]) -> float:
     """Compute Jaccard similarity (intersection over union).
 
     Returns 1.0 when both expected and actual are empty (perfect match).
@@ -319,7 +317,7 @@ def _compute_jaccard_similarity(expected: List[str], actual: List[str]) -> float
 class PatternEvaluatorCriteria(BaseEvaluationCriteria):
     """Evaluation criteria for pattern evaluator."""
 
-    expected_output: List[str] = Field(default_factory=list)
+    expected_output: list[str] = Field(default_factory=list)
 
 
 class PatternEvaluatorConfig(BaseEvaluatorConfig[PatternEvaluatorCriteria]):
@@ -371,7 +369,7 @@ class PatternComparisonEvaluator(
             }),
         )
 
-    def _extract_patterns(self, agent_execution: AgentExecution) -> List[str]:
+    def _extract_patterns(self, agent_execution: AgentExecution) -> list[str]:
         """Extract patterns from tool calls.
 
         Args:
@@ -418,7 +416,7 @@ def _extract_data(
     self,
     agent_execution: AgentExecution,
     tool_name: str
-) -> List[str]:
+) -> list[str]:
     """Extract data from specific tool calls.
 
     Args:
@@ -484,8 +482,8 @@ Make your scoring logic explicit and well-documented, using config values approp
 ```python
 def _compute_score(
     self,
-    actual: List[str],
-    expected: List[str]
+    actual: list[str],
+    expected: list[str]
 ) -> float:
     """Compute evaluation score.
 
@@ -618,7 +616,7 @@ def _extract_from_specific_tool(
 
 ```python
 def _compute_set_similarity(
-    self, actual: List[str], expected: List[str]
+    self, actual: list[str], expected: list[str]
 ) -> float:
     """Compute similarity using set operations."""
     actual_set = set(actual)

pyproject.toml

@@ -1,12 +1,12 @@
 [project]
 name = "uipath"
-version = "2.2.7"
+version = "2.2.8"
 description = "Python SDK and CLI for UiPath Platform, enabling programmatic interaction with automation services, process management, and deployment tools."
 readme = { file = "README.md", content-type = "text/markdown" }
 requires-python = ">=3.11"
 dependencies = [
   "uipath-core>=0.0.5, <0.1.0",
-  "uipath-runtime>=0.1.0, <0.2.0",
+  "uipath-runtime>=0.1.1, <0.2.0",
   "click>=8.3.1",
   "httpx>=0.28.1",
   "pyjwt>=2.10.1",
@@ -17,7 +17,7 @@ dependencies = [
   "truststore>=0.10.1",
   "mockito>=1.5.4",
   "hydra-core>=1.3.2",
-  "pydantic-function-models>=0.1.10",
+  "pydantic-function-models>=0.1.11",
   "pysignalr==1.3.0",
   "coverage>=7.8.2",
   "mermaid-builder==0.0.3",

samples/asset-modifier-agent/main.py

@@ -2,8 +2,7 @@
 import dotenv
 import logging
 import os
-
-from typing import Optional
+from typing import Any
 from uipath.platform import UiPath
 from uipath.tracing import traced
 
@@ -38,15 +37,15 @@ class AgentInput:
     asset_name: str
     folder_path: str
 
-def get_asset(client: UiPath, name: str, folder_path: str) -> Optional[object]:
+def get_asset(client: UiPath, name: str, folder_path: str) -> Any:
     """Retrieve an asset from UiPath.
 
     Args:
         name (str): The asset name.
         folder_path (str): The UiPath folder path.
 
     Returns:
-        Optional[object]: The asset object if found, else None.
+        Any: The asset object if found, else None.
     """
     return client.assets.retrieve(name=name, folder_path=folder_path)
 

samples/google-ADK-agent/multi_tool_agent/agent.py

@@ -1,6 +1,5 @@
 import dataclasses
 import datetime
-from typing import Dict
 from zoneinfo import ZoneInfo
 
 from google.adk.agents import Agent
@@ -9,7 +8,7 @@
 from google.genai.types import Content, Part
 
 
-def get_weather(city: str) -> Dict[str, str]:
+def get_weather(city: str) -> dict[str, str]:
     """Retrieves the current weather report for a specified city.
 
     Args:
@@ -33,7 +32,7 @@ def get_weather(city: str) -> Dict[str, str]:
         }
 
 
-def get_current_time(city: str) -> Dict[str, str]:
+def get_current_time(city: str) -> dict[str, str]:
     """Returns the current time in a specified city.
 
     Args:

samples/llm_chat_agent/agent.py

@@ -15,7 +15,7 @@
 import asyncio
 import json
 import os
-from typing import Any, Dict, List
+from typing import Any
 
 import httpx
 from dotenv import load_dotenv
@@ -54,14 +54,14 @@ class AgentOutput(BaseModel):
     """Output model for the agent."""
 
     response: str = Field(description="Agent's response to the user")
-    tool_calls_made: List[str] = Field(
+    tool_calls_made: list[str] = Field(
         default_factory=list, description="Names of tools that were called"
     )
 
 
 # Tool implementations
 @traced()
-async def get_current_weather(city: str) -> Dict[str, Any]:
+async def get_current_weather(city: str) -> dict[str, Any]:
     """
     Get the current weather for a city using Open-Meteo API.
 
@@ -174,7 +174,7 @@ def get_weather_description(code: int) -> str:
 
 
 @traced()
-async def calculate(expression: str) -> Dict[str, Any]:
+async def calculate(expression: str) -> dict[str, Any]:
     """
     Perform a mathematical calculation using Newton API.
 
@@ -274,7 +274,7 @@ async def calculate(expression: str) -> Dict[str, Any]:
 
 
 @traced()
-async def execute_tool_call(tool_name: str, tool_arguments: Dict[str, Any]) -> Dict[str, Any]:
+async def execute_tool_call(tool_name: str, tool_arguments: dict[str, Any]) -> dict[str, Any]:
     """
     Execute a tool based on its name and arguments.