Python: refresh dev dependencies and validate runtime bounds (#6238)

Updates third-party dev dependencies across the Python workspace and
validates that all runtime dependency bounds still hold at both ends.

Dev dependency bumps (root, lab, declarative, durabletask):
- uv 0.11.6 -> 0.11.17, ruff 0.15.8 -> 0.15.15,
  pytest-asyncio 1.3.0 -> 1.4.0, mcp 1.27.0 -> 1.27.2,
  azure-monitor-opentelemetry 1.8.7 -> 1.8.8,
  poethepoet 0.42.1 -> 0.46.0, prek 0.3.9 -> 0.4.3,
  types-python-dateutil and types-PyYaml stub bumps.
- Transitive Dependabot items swept via lock: idna 3.11 -> 3.17,
  pip 26.0.1 -> 26.1.2.

Deliberately excluded:
- opentelemetry-sdk stays 1.40.0: azure-monitor-opentelemetry (incl.
  1.8.8) hard-pins opentelemetry-sdk==1.40.
- mypy stays 1.20.0 and pyright stays 1.1.408: the 2.1.0 / 1.1.409
  bumps introduce new diagnostics that fail type checking and need
  dedicated PRs.
- rich kept as a range: agentlightning (lab[lightning]) forces
  rich==13.9.4.

Code/formatting changes driven by the ruff upgrade:
- devui lifespan now uses try/finally so shutdown cleanup always runs
  (ruff RUF075).
- Removed unused TYPE_CHECKING imports in core and foundry flagged by
  ruff 0.15.15.
- Reapplied ruff 0.15.15 formatting to the files it changed.

Validation: validate-dependency-bounds-test "*" passes (31/31 lower +
31/31 upper); typing 62/62; lint 31/31; devui tests pass.

Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>

python/samples/02-agents/harness/harness_research.py

@@ -109,7 +109,10 @@ async def main() -> None:
                         print(f"\n  [calling tool: {content.name}]", flush=True)
                         print("  ", end="", flush=True)
                     # Show web search activity when the result arrives with action details.
-                    elif content.type in ("search_tool_call", "search_tool_result") and getattr(content, "tool_name", None) == "web_search":
+                    elif (
+                        content.type in ("search_tool_call", "search_tool_result")
+                        and getattr(content, "tool_name", None) == "web_search"
+                    ):
                         action = None
                         if content.type == "search_tool_result" and isinstance(content.result, dict):
                             action = content.result.get("action", {})

python/samples/autogen-migration/orchestrations/02_selector_group_chat.py

@@ -74,19 +74,22 @@ async def run_agent_framework() -> None:
     client = OpenAIChatClient(model="gpt-4.1-mini")
 
     # Create specialized agents
-    python_expert = Agent(client=client,
+    python_expert = Agent(
+        client=client,
         name="python_expert",
         instructions="You are a Python programming expert. Answer Python-related questions.",
         description="Expert in Python programming",
     )
 
-    javascript_expert = Agent(client=client,
+    javascript_expert = Agent(
+        client=client,
         name="javascript_expert",
         instructions="You are a JavaScript programming expert. Answer JavaScript-related questions.",
         description="Expert in JavaScript programming",
     )
 
-    database_expert = Agent(client=client,
+    database_expert = Agent(
+        client=client,
         name="database_expert",
         instructions="You are a database expert. Answer SQL and database-related questions.",
         description="Expert in databases and SQL",
@@ -95,7 +98,8 @@ async def run_agent_framework() -> None:
     workflow = GroupChatBuilder(
         participants=[python_expert, javascript_expert, database_expert],
         max_rounds=1,
-        orchestrator_agent=Agent(client=client,
+        orchestrator_agent=Agent(
+            client=client,
             name="selector_manager",
             instructions="Based on the conversation, select the most appropriate expert to respond next.",
         ),

python/samples/autogen-migration/orchestrations/03_swarm.py

@@ -113,7 +113,8 @@ async def run_agent_framework() -> None:
     client = OpenAIChatClient(model="gpt-4.1-mini")
 
     # Create triage agent
-    triage_agent = Agent(client=client,
+    triage_agent = Agent(
+        client=client,
         name="triage",
         instructions=(
             "You are a triage agent. Analyze the user's request and route to the appropriate specialist:\n"
@@ -125,7 +126,8 @@ async def run_agent_framework() -> None:
     )
 
     # Create billing specialist
-    billing_agent = Agent(client=client,
+    billing_agent = Agent(
+        client=client,
         name="billing_agent",
         instructions="You are a billing specialist. Help with payment and billing questions. Provide clear assistance.",
         description="Handles billing and payment questions",
@@ -133,7 +135,8 @@ async def run_agent_framework() -> None:
     )
 
     # Create technical support specialist
-    tech_support = Agent(client=client,
+    tech_support = Agent(
+        client=client,
         name="technical_support",
         instructions="You are technical support. Help with technical issues. Provide clear assistance.",
         description="Handles technical support questions",

python/samples/autogen-migration/single_agent/02_agent_with_tool.py

@@ -73,7 +73,8 @@ async def run_agent_framework() -> None:
 
     # Create agent with tool
     client = OpenAIChatClient(model="gpt-4.1-mini")
-    agent = Agent(client=client,
+    agent = Agent(
+        client=client,
         name="assistant",
         instructions="You are a helpful assistant. Use available tools to answer questions.",
         tools=[get_weather],

python/samples/autogen-migration/single_agent/04_agent_as_tool.py

@@ -61,7 +61,8 @@ async def run_agent_framework() -> None:
     client = OpenAIChatClient(model="gpt-4.1-mini")
 
     # Create specialized writer agent
-    writer = Agent(client=client,
+    writer = Agent(
+        client=client,
         name="writer",
         instructions="You are a creative writer. Write short, engaging content.",
     )
@@ -75,7 +76,8 @@ async def run_agent_framework() -> None:
     )
 
     # Create coordinator agent with writer tool
-    coordinator = Agent(client=client,
+    coordinator = Agent(
+        client=client,
         name="coordinator",
         instructions="You coordinate with specialized agents. Delegate writing tasks to the writer agent.",
         tools=[writer_tool],

python/samples/semantic-kernel-migration/orchestrations/sequential.py

@@ -78,12 +78,14 @@ async def sk_agent_response_callback(
 async def run_agent_framework_example(prompt: str) -> list[Message]:
     client = OpenAIChatCompletionClient(credential=AzureCliCredential())
 
-    writer = Agent(client=client,
+    writer = Agent(
+        client=client,
         instructions=("You are a concise copywriter. Provide a single, punchy marketing sentence based on the prompt."),
         name="writer",
     )
 
-    reviewer = Agent(client=client,
+    reviewer = Agent(
+        client=client,
         instructions=("You are a thoughtful reviewer. Give brief feedback on the previous assistant message."),
         name="reviewer",
     )