chore: update poetry ci version

Author: shan

.github/workflows/ci.yml

@@ -17,7 +17,7 @@ concurrency:
   cancel-in-progress: true
 
 env:
-  POETRY_VERSION: "1.8.5"
+  POETRY_VERSION: "2.2.1"
 
 jobs:
   quality:

.github/workflows/release.yml

@@ -14,7 +14,7 @@ concurrency:
   cancel-in-progress: false
 
 env:
-  POETRY_VERSION: "1.8.5"
+  POETRY_VERSION: "2.2.1"
 
 jobs:
   build:

.github/workflows/testpypi.yml

@@ -14,7 +14,7 @@ concurrency:
   cancel-in-progress: false
 
 env:
-  POETRY_VERSION: "1.8.5"
+  POETRY_VERSION: "2.2.1"
 
 jobs:
   build:

examples/17_runtime_kernel_platform.py

@@ -160,7 +160,9 @@ def extract_memory(
         return []
     start = lowered.index(marker) + len(marker)
     content = user_content[start:].strip()
-    return [MemoryRecord(content=content, metadata={"kind": "explicit_preference"})] if content else []
+    return (
+        [MemoryRecord(content=content, metadata={"kind": "explicit_preference"})] if content else []
+    )
 
 
 def build_knowledge_source() -> KnowledgeSource:
@@ -356,7 +358,9 @@ async def main() -> None:
     print(f"Run state:          {result.state.value}")
     print(f"Output:             {result.output}")
 
-    recall = agent.config.memory.sources[0].prefetch("checkout deploy approval", session_id=session.id)
+    recall = agent.config.memory.sources[0].prefetch(
+        "checkout deploy approval", session_id=session.id
+    )
     print("\n=== Recalled Memory ===")
     print(recall or "(empty)")
 

loom/_agent/core.py

@@ -891,9 +891,7 @@ def _normalize_schedule_jobs(jobs: list[ScheduledJob]) -> list[ScheduledJob]:
     normalized: list[ScheduledJob] = []
     for index, job in enumerate(jobs):
         if not isinstance(job, ScheduledJob):
-            raise TypeError(
-                f"schedule entries must be ScheduledJob, got {type(job).__name__}"
-            )
+            raise TypeError(f"schedule entries must be ScheduledJob, got {type(job).__name__}")
         if not isinstance(job.schedule, ScheduleConfig):
             raise TypeError(
                 f"schedule[{index}].schedule must be ScheduleConfig, "

loom/_config/runtime.py

@@ -47,7 +47,9 @@ class RuntimeConfig:
     delegation: Any | None = None
     governance: Any | None = None
     feedback: Any | None = None
-    skill_injection: Any | None = None  # Deprecated: prefer ContextPolicy.manager(skill_injection=...)
+    skill_injection: Any | None = (
+        None  # Deprecated: prefer ContextPolicy.manager(skill_injection=...)
+    )
     session_restore: Any | None = None
     extensions: dict[str, Any] = field(default_factory=dict)
 

loom/_config/schedule.py

@@ -39,7 +39,9 @@ def cron(cls, expr: str) -> ScheduleConfig:
         try:
             import_module("croniter")
         except ImportError as exc:  # pragma: no cover - depends on optional package
-            raise ImportError("ScheduleConfig.cron() requires optional dependency 'croniter'") from exc
+            raise ImportError(
+                "ScheduleConfig.cron() requires optional dependency 'croniter'"
+            ) from exc
         if not expr.strip():
             raise ValueError("cron expression must not be empty")
         return cls(kind="cron", cron_expr=expr)
@@ -64,12 +66,8 @@ def compute_next_run(self, last_run_at: datetime | None = None) -> datetime | No
             try:
                 croniter_fn = import_module("croniter").croniter
             except ImportError as exc:  # pragma: no cover - depends on optional package
-                raise ImportError(
-                    "cron schedules require optional dependency 'croniter'"
-                ) from exc
-            next_run = croniter_fn(self.cron_expr, last_run_at or datetime.now()).get_next(
-                datetime
-            )
+                raise ImportError("cron schedules require optional dependency 'croniter'") from exc
+            next_run = croniter_fn(self.cron_expr, last_run_at or datetime.now()).get_next(datetime)
             if not isinstance(next_run, datetime):
                 raise TypeError("croniter returned a non-datetime next run")
             return next_run

loom/runtime/engine.py

@@ -412,7 +412,9 @@ async def _run_with_harness(
         )
         run = getattr(harness, "run", None)
         if not callable(run):
-            raise TypeError(f"runtime harness must provide async run(request), got {type(harness).__name__}")
+            raise TypeError(
+                f"runtime harness must provide async run(request), got {type(harness).__name__}"
+            )
 
         outcome = await run(request)
         if isinstance(outcome, str):

loom/runtime/harness.py

@@ -238,7 +238,9 @@ def _coerce_request(
         if context is None:
             raise TypeError("HarnessContext is required when running a harness with RuntimeTask")
         return HarnessRequest(task=request, context=context)
-    raise TypeError(f"harness request must be HarnessRequest or RuntimeTask, got {type(request).__name__}")
+    raise TypeError(
+        f"harness request must be HarnessRequest or RuntimeTask, got {type(request).__name__}"
+    )
 
 
 def _result_field(result: Any, key: str, default: Any) -> Any:

tests/core/test_081_subsystems.py

@@ -131,7 +131,9 @@ def test_inject_knowledge_writes_to_surface_not_memory() -> None:
 
     surface = engine.context_manager.dashboard.dashboard.knowledge_surface
     assert surface.evidence_packs[0]["content"] == "Loom has dashboard knowledge."
-    assert not any("Knowledge:" in message.content for message in engine.context_manager.partitions.memory)
+    assert not any(
+        "Knowledge:" in message.content for message in engine.context_manager.partitions.memory
+    )
 
 
 def test_dashboard_renders_evidence_content() -> None:
@@ -239,9 +241,7 @@ def upsert(self, record: MemoryRecord, query: MemoryQuery | None = None) -> None
 
 
 def test_memory_resolver_callable_validates_records() -> None:
-    resolver = MemoryResolver.callable(
-        lambda query: [MemoryRecord(content=query.text, key="k")]
-    )
+    resolver = MemoryResolver.callable(lambda query: [MemoryRecord(content=query.text, key="k")])
 
     result = resolver.retrieve(MemoryQuery(text="needle", top_k=1))
 
@@ -287,9 +287,7 @@ async def _complete_request(self, request: CompletionRequest) -> CompletionRespo
     result = await agent.session(SessionConfig(id="memory-source")).run("remember this")
 
     assert result.output == "stored answer"
-    assert store.records == [
-        MemoryRecord(content="extracted remember this -> stored answer")
-    ]
+    assert store.records == [MemoryRecord(content="extracted remember this -> stored answer")]
 
 
 def test_knowledge_resolver_factories(tmp_path) -> None: