diff --git a/python/.pre-commit-config.yaml b/python/.pre-commit-config.yaml index bbb2683c5c..adf7e6e5b3 100644 --- a/python/.pre-commit-config.yaml +++ b/python/.pre-commit-config.yaml @@ -1,7 +1,8 @@ fail_fast: true exclude: ^scripts/ repos: - - repo: builtin + - repo: https://github.com/pre-commit/pre-commit-hooks + rev: v6.0.0 hooks: - id: check-toml name: Check TOML files @@ -34,9 +35,6 @@ repos: - id: no-commit-to-branch name: Protect main branch args: [--branch, main] - - repo: https://github.com/pre-commit/pre-commit-hooks - rev: v6.0.0 - hooks: - id: check-ast name: Check Valid Python Samples types: ["python"] diff --git a/python/packages/core/agent_framework/_workflows/_checkpoint.py b/python/packages/core/agent_framework/_workflows/_checkpoint.py index b442f445f8..f9a940a7db 100644 --- a/python/packages/core/agent_framework/_workflows/_checkpoint.py +++ b/python/packages/core/agent_framework/_workflows/_checkpoint.py @@ -244,14 +244,39 @@ class FileCheckpointStorage: is serialized using pickle and embedded as base64-encoded strings within the JSON. This allows for human-readable checkpoint files while preserving the ability to store complex Python objects. - SECURITY WARNING: Checkpoints use pickle for data serialization. Only load checkpoints - from trusted sources. Loading a malicious checkpoint file can execute arbitrary code. + By default, checkpoint deserialization is restricted to a built-in set of safe + Python types (primitives, datetime, uuid, ...) and all ``agent_framework`` + internal types. To allow additional application-specific types, pass them via + the ``allowed_checkpoint_types`` parameter using ``"module:qualname"`` format. + + Example:: + + storage = FileCheckpointStorage( + "/tmp/checkpoints", + allowed_checkpoint_types=[ + "my_app.models:MyState", + ], + ) """ - def __init__(self, storage_path: str | Path): - """Initialize the file storage.""" + def __init__( + self, + storage_path: str | Path, + *, + allowed_checkpoint_types: list[str] | None = None, + ) -> None: + """Initialize the file storage. + + Args: + storage_path: Directory path where checkpoint files will be stored. + allowed_checkpoint_types: Additional types (beyond the built-in safe set + and framework types) that are permitted during checkpoint + deserialization. Each entry should be a ``"module:qualname"`` + string (e.g., ``"my_app.models:MyState"``). + """ self.storage_path = Path(storage_path) self.storage_path.mkdir(parents=True, exist_ok=True) + self._allowed_types: frozenset[str] = frozenset(allowed_checkpoint_types or []) logger.info(f"Initialized file checkpoint storage at {self.storage_path}") def _validate_file_path(self, checkpoint_id: CheckpointID) -> Path: @@ -327,7 +352,7 @@ def _read() -> dict[str, Any]: from ._checkpoint_encoding import decode_checkpoint_value try: - decoded_checkpoint_dict = decode_checkpoint_value(encoded_checkpoint) + decoded_checkpoint_dict = decode_checkpoint_value(encoded_checkpoint, allowed_types=self._allowed_types) except WorkflowCheckpointException: raise checkpoint = WorkflowCheckpoint.from_dict(decoded_checkpoint_dict) @@ -352,7 +377,9 @@ def _list_checkpoints() -> list[WorkflowCheckpoint]: encoded_checkpoint = json.load(f) from ._checkpoint_encoding import decode_checkpoint_value - decoded_checkpoint_dict = decode_checkpoint_value(encoded_checkpoint) + decoded_checkpoint_dict = decode_checkpoint_value( + encoded_checkpoint, allowed_types=self._allowed_types + ) checkpoint = WorkflowCheckpoint.from_dict(decoded_checkpoint_dict) if checkpoint.workflow_name == workflow_name: checkpoints.append(checkpoint) diff --git a/python/packages/core/agent_framework/_workflows/_checkpoint_encoding.py b/python/packages/core/agent_framework/_workflows/_checkpoint_encoding.py index 85f9327663..a25a08c66a 100644 --- a/python/packages/core/agent_framework/_workflows/_checkpoint_encoding.py +++ b/python/packages/core/agent_framework/_workflows/_checkpoint_encoding.py @@ -1,14 +1,5 @@ # Copyright (c) Microsoft. All rights reserved. -from __future__ import annotations - -import base64 -import logging -import pickle # nosec # noqa: S403 -from typing import Any - -from ..exceptions import WorkflowCheckpointException - """Checkpoint encoding using JSON structure with pickle+base64 for arbitrary data. This hybrid approach provides: @@ -16,10 +7,23 @@ - Full Python object fidelity via pickle for data values (non-JSON-native types) - Base64 encoding to embed binary pickle data in JSON strings -SECURITY WARNING: Checkpoints use pickle for data serialization. Only load checkpoints -from trusted sources. Loading a malicious checkpoint file can execute arbitrary code. +When ``allowed_types`` is supplied to :func:`decode_checkpoint_value`, a +``RestrictedUnpickler`` is used that limits which classes may be instantiated +during deserialization. The default built-in safe set covers common Python +value types (primitives, datetime, uuid, ...) and all ``agent_framework`` +internal types. Callers can extend the set by passing additional +``"module:qualname"`` strings. """ +from __future__ import annotations + +import base64 +import io +import logging +import pickle # nosec # noqa: S403 +from typing import Any + +from ..exceptions import WorkflowCheckpointException logger = logging.getLogger("agent_framework") @@ -30,6 +34,82 @@ # Types that are natively JSON-serializable and don't need pickling _JSON_NATIVE_TYPES = (str, int, float, bool, type(None)) +# Module prefix for framework-internal types that are always allowed +_FRAMEWORK_MODULE_PREFIX = "agent_framework." + +# Built-in types considered safe for checkpoint deserialization. +# Each entry is a ``module:qualname`` string matching the format produced by +# :func:`_type_to_key`. These are the classes for which pickle's +# ``find_class`` will be called when unpickling common Python value types. +_BUILTIN_ALLOWED_TYPE_KEYS: frozenset[str] = frozenset({ + # builtins + "builtins:object", + "builtins:complex", + "builtins:range", + "builtins:slice", + "builtins:int", + "builtins:float", + "builtins:str", + "builtins:bytes", + "builtins:bytearray", + "builtins:bool", + "builtins:set", + "builtins:frozenset", + "builtins:list", + "builtins:dict", + "builtins:tuple", + "builtins:type", + # getattr is used by pickle to reconstruct enum members + "builtins:getattr", + # copyreg helpers used by pickle for object reconstruction + "copyreg:_reconstructor", + # datetime + "datetime:datetime", + "datetime:date", + "datetime:time", + "datetime:timedelta", + "datetime:timezone", + # uuid + "uuid:UUID", + # decimal + "decimal:Decimal", + # collections + "collections:OrderedDict", + "collections:defaultdict", + "collections:deque", +}) + + +class _RestrictedUnpickler(pickle.Unpickler): # noqa: S301 + """Unpickler that restricts which classes may be instantiated. + + Only classes whose ``module:qualname`` key appears in the combined allow + set (built-in safe types + framework types + caller-specified extras) are + permitted. All other classes raise :class:`pickle.UnpicklingError`. + """ + + def __init__(self, data: bytes, allowed_types: frozenset[str]) -> None: + super().__init__(io.BytesIO(data)) + self._allowed_types = allowed_types + + def find_class(self, module: str, name: str) -> type: + type_key = f"{module}:{name}" + + if ( + type_key in _BUILTIN_ALLOWED_TYPE_KEYS + or type_key in self._allowed_types + or module.startswith(_FRAMEWORK_MODULE_PREFIX) + ): + return super().find_class(module, name) # type: ignore[no-any-return] # nosec + + raise pickle.UnpicklingError( + f"Checkpoint deserialization blocked for type '{type_key}'. " + f"To allow this type, either include its 'module:qualname' key in the " + f"'allowed_types' set passed to 'decode_checkpoint_value', or add it to " + f"'allowed_checkpoint_types' on your checkpoint storage " + f"(for example, 'FileCheckpointStorage.allowed_checkpoint_types')." + ) + def encode_checkpoint_value(value: Any) -> Any: """Encode a Python value for checkpoint storage. @@ -48,29 +128,51 @@ def encode_checkpoint_value(value: Any) -> Any: return _encode(value) -def decode_checkpoint_value(value: Any) -> Any: +def decode_checkpoint_value(value: Any, *, allowed_types: frozenset[str] | None = None) -> Any: """Decode a value from checkpoint storage. Reverses the encoding performed by encode_checkpoint_value. Pickled values (identified by _PICKLE_MARKER) are decoded and unpickled. - WARNING: Only call this with trusted data. Pickle can execute - arbitrary code during deserialization. The post-unpickle type verification - detects accidental corruption or type mismatches, but cannot prevent - arbitrary code execution from malicious pickle payloads. - Args: value: A JSON-deserialized value from checkpoint storage. + allowed_types: If not ``None``, restrict pickle deserialization to the + built-in safe set, framework types, and the types listed here. + Each entry should use ``"module:qualname"`` format — that is, the + dotted module path followed by a colon and the class + ``__qualname__``. For example, given a user-defined class:: + + # my_app/models.py + class MyState: ... + + the corresponding entry would be ``"my_app.models:MyState"``:: + + decode_checkpoint_value( + data, + allowed_types=frozenset({"my_app.models:MyState"}), + ) + + When using :class:`FileCheckpointStorage`, pass the same strings + via ``allowed_checkpoint_types``:: + + storage = FileCheckpointStorage( + "/tmp/checkpoints", + allowed_checkpoint_types=["my_app.models:MyState"], + ) + + If ``None``, no restriction is applied (backward-compatible + behavior). Returns: The original Python value. Raises: WorkflowCheckpointException: If the unpickled object's type doesn't match - the recorded type, indicating corruption, or if the base64/pickle - data is malformed. + the recorded type, indicating corruption, if the base64/pickle + data is malformed, or if a disallowed type is encountered during + restricted deserialization. """ - return _decode(value) + return _decode(value, allowed_types=allowed_types) def _encode(value: Any) -> Any: @@ -94,7 +196,7 @@ def _encode(value: Any) -> Any: } -def _decode(value: Any) -> Any: +def _decode(value: Any, *, allowed_types: frozenset[str] | None = None) -> Any: """Recursively decode a value from JSON storage.""" # JSON-native types pass through if isinstance(value, _JSON_NATIVE_TYPES): @@ -104,16 +206,16 @@ def _decode(value: Any) -> Any: if isinstance(value, dict): # Pickled value: decode, unpickle, and verify type if _PICKLE_MARKER in value and _TYPE_MARKER in value: - obj = _base64_to_unpickle(value[_PICKLE_MARKER]) # type: ignore + obj = _base64_to_unpickle(value[_PICKLE_MARKER], allowed_types=allowed_types) # type: ignore _verify_type(obj, value.get(_TYPE_MARKER)) # type: ignore return obj # Regular dict: decode values recursively - return {k: _decode(v) for k, v in value.items()} # type: ignore + return {k: _decode(v, allowed_types=allowed_types) for k, v in value.items()} # type: ignore # Handle encoded lists if isinstance(value, list): - return [_decode(item) for item in value] # type: ignore + return [_decode(item, allowed_types=allowed_types) for item in value] # type: ignore return value @@ -148,15 +250,23 @@ def _pickle_to_base64(value: Any) -> str: return base64.b64encode(pickled).decode("ascii") -def _base64_to_unpickle(encoded: str) -> Any: +def _base64_to_unpickle(encoded: str, *, allowed_types: frozenset[str] | None = None) -> Any: """Decode base64 string and unpickle. + Args: + encoded: Base64-encoded pickle data. + allowed_types: If not ``None``, use restricted unpickling that only + permits built-in safe types, framework types, and the specified + extra types. + Raises: - WorkflowCheckpointException: If the base64 data is corrupted or the pickle - format is incompatible. + WorkflowCheckpointException: If the base64 data is corrupted, the pickle + format is incompatible, or a disallowed type is encountered. """ try: pickled = base64.b64decode(encoded.encode("ascii")) + if allowed_types is not None: + return _RestrictedUnpickler(pickled, allowed_types).load() return pickle.loads(pickled) # nosec # noqa: S301 except Exception as exc: raise WorkflowCheckpointException(f"Failed to decode pickled checkpoint data: {exc}") from exc diff --git a/python/packages/core/tests/workflow/test_checkpoint.py b/python/packages/core/tests/workflow/test_checkpoint.py index a32489acc0..e395655afa 100644 --- a/python/packages/core/tests/workflow/test_checkpoint.py +++ b/python/packages/core/tests/workflow/test_checkpoint.py @@ -1048,7 +1048,10 @@ async def test_file_checkpoint_storage_roundtrip_datetime(): async def test_file_checkpoint_storage_roundtrip_dataclass(): """Test that dataclass objects roundtrip correctly via pickle encoding.""" with tempfile.TemporaryDirectory() as temp_dir: - storage = FileCheckpointStorage(temp_dir) + storage = FileCheckpointStorage( + temp_dir, + allowed_checkpoint_types=["tests.workflow.test_checkpoint:_TestCustomData"], + ) custom_obj = _TestCustomData(name="test", value=42, tags=["a", "b", "c"]) @@ -1238,7 +1241,10 @@ async def test_file_checkpoint_storage_roundtrip_messages_with_complex_data(): async def test_file_checkpoint_storage_roundtrip_pending_request_info_events(): """Test that pending_request_info_events with WorkflowEvent objects roundtrip correctly.""" with tempfile.TemporaryDirectory() as temp_dir: - storage = FileCheckpointStorage(temp_dir) + storage = FileCheckpointStorage( + temp_dir, + allowed_checkpoint_types=["tests.workflow.test_checkpoint:_TestToolApprovalRequest"], + ) # Create request_info events using the proper WorkflowEvent factory event1 = WorkflowEvent.request_info( @@ -1300,7 +1306,13 @@ async def test_file_checkpoint_storage_roundtrip_pending_request_info_events(): async def test_file_checkpoint_storage_roundtrip_full_checkpoint(): """Test complete WorkflowCheckpoint roundtrip with all fields populated using proper types.""" with tempfile.TemporaryDirectory() as temp_dir: - storage = FileCheckpointStorage(temp_dir) + storage = FileCheckpointStorage( + temp_dir, + allowed_checkpoint_types=[ + "tests.workflow.test_checkpoint:_TestApprovalRequest", + "tests.workflow.test_checkpoint:_TestExecutorState", + ], + ) # Create proper WorkflowMessage objects msg1 = WorkflowMessage(data="msg1", source_id="s", target_id="t") diff --git a/python/packages/core/tests/workflow/test_checkpoint_unrestricted_pickle.py b/python/packages/core/tests/workflow/test_checkpoint_unrestricted_pickle.py new file mode 100644 index 0000000000..c70d8c85c3 --- /dev/null +++ b/python/packages/core/tests/workflow/test_checkpoint_unrestricted_pickle.py @@ -0,0 +1,218 @@ +# Copyright (c) Microsoft. All rights reserved. + +"""Tests for restricted checkpoint deserialization. + +These tests verify that persisted checkpoint loading uses a restricted +unpickler by default: +- Arbitrary callables are blocked during deserialization +- __reduce__ payloads cannot execute code during deserialization +- FileCheckpointStorage accepts allowed_checkpoint_types for extension +- User-defined types are blocked unless explicitly allowed +- Built-in safe types and framework types are always allowed +""" + +import base64 +import os +import pickle +import tempfile +from dataclasses import dataclass +from datetime import datetime, timezone + +import pytest + +from agent_framework import WorkflowCheckpointException +from agent_framework._workflows._checkpoint import FileCheckpointStorage +from agent_framework._workflows._checkpoint_encoding import ( + _PICKLE_MARKER, + _TYPE_MARKER, + decode_checkpoint_value, + encode_checkpoint_value, +) + + +class MaliciousPayload: + """A class whose __reduce__ executes code during unpickling.""" + + def __reduce__(self): + return (os.getpid, ()) + + +def test_restricted_decode_blocks_arbitrary_callable(): + """Restricted decoding blocks arbitrary module-level callables.""" + pickled = pickle.dumps(os.getpid, protocol=pickle.HIGHEST_PROTOCOL) + encoded_b64 = base64.b64encode(pickled).decode("ascii") + + checkpoint_value = { + _PICKLE_MARKER: encoded_b64, + _TYPE_MARKER: "builtins:builtin_function_or_method", + } + + with pytest.raises(WorkflowCheckpointException, match="deserialization blocked"): + decode_checkpoint_value(checkpoint_value, allowed_types=frozenset()) + + +def test_restricted_decode_blocks_reduce_payload(): + """__reduce__-based payloads are blocked before code can execute.""" + payload = MaliciousPayload() + pickled = pickle.dumps(payload, protocol=pickle.HIGHEST_PROTOCOL) + encoded_b64 = base64.b64encode(pickled).decode("ascii") + + checkpoint_value = { + _PICKLE_MARKER: encoded_b64, + _TYPE_MARKER: f"{MaliciousPayload.__module__}:{MaliciousPayload.__qualname__}", + } + + with pytest.raises(WorkflowCheckpointException, match="deserialization blocked"): + decode_checkpoint_value(checkpoint_value, allowed_types=frozenset()) + + +def test_restricted_decode_prevents_code_execution(): + """Restricted deserialization prevents __reduce__ code from running.""" + with tempfile.TemporaryDirectory() as tmpdir: + marker_file = os.path.join(tmpdir, "checkpoint_test_marker") + + payload_bytes = pickle.dumps( + type( + "Exploit", + (), + { + "__reduce__": lambda self: ( + eval, + (f"open({marker_file!r}, 'w').write('pwned')",), + ) + }, + )(), + protocol=pickle.HIGHEST_PROTOCOL, + ) + encoded_b64 = base64.b64encode(payload_bytes).decode("ascii") + + checkpoint_value = { + _PICKLE_MARKER: encoded_b64, + _TYPE_MARKER: "builtins:int", + } + with pytest.raises(WorkflowCheckpointException, match="deserialization blocked"): + decode_checkpoint_value(checkpoint_value, allowed_types=frozenset()) + + assert not os.path.exists(marker_file), ( + "Restricted unpickler should have prevented code execution, but the marker file was created." + ) + + +def test_file_checkpoint_storage_accepts_allowed_types(): + """FileCheckpointStorage.__init__ accepts allowed_checkpoint_types.""" + with tempfile.TemporaryDirectory() as tmpdir: + storage = FileCheckpointStorage( + tmpdir, + allowed_checkpoint_types=["some.module:SomeType"], + ) + assert storage is not None + + +@dataclass +class _AllowedTestState: + """Test dataclass that will be explicitly allowed.""" + + name: str + value: int + + +def test_restricted_decode_blocks_unlisted_user_type(): + """User-defined types are blocked when not in allowed_checkpoint_types.""" + original = _AllowedTestState(name="test", value=42) + encoded = encode_checkpoint_value(original) + + with pytest.raises(WorkflowCheckpointException, match="deserialization blocked"): + decode_checkpoint_value(encoded, allowed_types=frozenset()) + + +def test_restricted_decode_allows_listed_user_type(): + """User-defined types are allowed when listed in allowed_types.""" + original = _AllowedTestState(name="test", value=42) + encoded = encode_checkpoint_value(original) + + type_key = f"{_AllowedTestState.__module__}:{_AllowedTestState.__qualname__}" + decoded = decode_checkpoint_value(encoded, allowed_types=frozenset({type_key})) + + assert isinstance(decoded, _AllowedTestState) + assert decoded.name == "test" + assert decoded.value == 42 + + +def test_restricted_decode_allows_builtin_safe_types(): + """Built-in safe types (datetime, set, etc.) are always allowed.""" + test_values = [ + datetime(2025, 1, 1, tzinfo=timezone.utc), + {1, 2, 3}, + frozenset({4, 5, 6}), + (1, "two", 3.0), + complex(1, 2), + ] + for original in test_values: + encoded = encode_checkpoint_value(original) + decoded = decode_checkpoint_value(encoded, allowed_types=frozenset()) + assert decoded == original + + +def test_unrestricted_decode_allows_arbitrary_types(): + """Without allowed_types, decode_checkpoint_value remains unrestricted.""" + original = _AllowedTestState(name="test", value=42) + encoded = encode_checkpoint_value(original) + + decoded = decode_checkpoint_value(encoded) + + assert isinstance(decoded, _AllowedTestState) + assert decoded.name == "test" + + +async def test_file_storage_blocks_unlisted_user_type(): + """FileCheckpointStorage blocks user types not in allowed_checkpoint_types.""" + from agent_framework import WorkflowCheckpoint + + with tempfile.TemporaryDirectory() as tmpdir: + # Save with a storage that allows the type + type_key = f"{_AllowedTestState.__module__}:{_AllowedTestState.__qualname__}" + save_storage = FileCheckpointStorage(tmpdir, allowed_checkpoint_types=[type_key]) + + checkpoint = WorkflowCheckpoint( + workflow_name="test", + graph_signature_hash="hash", + state={"data": _AllowedTestState(name="test", value=1)}, + ) + await save_storage.save(checkpoint) + + # Load with a storage that does NOT allow the type + load_storage = FileCheckpointStorage(tmpdir) + with pytest.raises(WorkflowCheckpointException, match="deserialization blocked"): + await load_storage.load(checkpoint.checkpoint_id) + + +async def test_file_storage_allows_listed_user_type(): + """FileCheckpointStorage allows user types listed in allowed_checkpoint_types.""" + from agent_framework import WorkflowCheckpoint + + with tempfile.TemporaryDirectory() as tmpdir: + type_key = f"{_AllowedTestState.__module__}:{_AllowedTestState.__qualname__}" + storage = FileCheckpointStorage(tmpdir, allowed_checkpoint_types=[type_key]) + + checkpoint = WorkflowCheckpoint( + workflow_name="test", + graph_signature_hash="hash", + state={"data": _AllowedTestState(name="allowed", value=99)}, + ) + await storage.save(checkpoint) + loaded = await storage.load(checkpoint.checkpoint_id) + + assert isinstance(loaded.state["data"], _AllowedTestState) + assert loaded.state["data"].name == "allowed" + assert loaded.state["data"].value == 99 + + +def test_restricted_unpickler_raises_pickle_error(): + """_RestrictedUnpickler.find_class raises pickle.UnpicklingError, not a framework exception.""" + from agent_framework._workflows._checkpoint_encoding import _RestrictedUnpickler + + pickled = pickle.dumps(os.getpid, protocol=pickle.HIGHEST_PROTOCOL) + + unpickler = _RestrictedUnpickler(pickled, frozenset()) + with pytest.raises(pickle.UnpicklingError, match="deserialization blocked"): + unpickler.load() diff --git a/python/packages/core/tests/workflow/test_request_info_event_rehydrate.py b/python/packages/core/tests/workflow/test_request_info_event_rehydrate.py index 9400084692..d280a788cd 100644 --- a/python/packages/core/tests/workflow/test_request_info_event_rehydrate.py +++ b/python/packages/core/tests/workflow/test_request_info_event_rehydrate.py @@ -130,7 +130,17 @@ async def test_checkpoint_with_pending_request_info_events(): with tempfile.TemporaryDirectory() as temp_dir: # Use file-based storage to test full serialization - storage = FileCheckpointStorage(temp_dir) + storage = FileCheckpointStorage( + temp_dir, + allowed_checkpoint_types=[ + "tests.workflow.test_request_info_and_response:UserApprovalRequest", + "tests.workflow.test_request_info_and_response:CalculationRequest", + "tests.workflow.test_request_info_event_rehydrate:MockRequest", + "tests.workflow.test_request_info_event_rehydrate:SimpleApproval", + "tests.workflow.test_request_info_event_rehydrate:SlottedApproval", + "tests.workflow.test_request_info_event_rehydrate:TimedApproval", + ], + ) # Create workflow with checkpointing enabled executor = ApprovalRequiredExecutor(id="approval_executor") @@ -225,7 +235,17 @@ async def test_checkpoint_restore_with_responses_does_not_reemit_handled_request with tempfile.TemporaryDirectory() as temp_dir: # Use file-based storage to test full serialization - storage = FileCheckpointStorage(temp_dir) + storage = FileCheckpointStorage( + temp_dir, + allowed_checkpoint_types=[ + "tests.workflow.test_request_info_and_response:UserApprovalRequest", + "tests.workflow.test_request_info_and_response:CalculationRequest", + "tests.workflow.test_request_info_event_rehydrate:MockRequest", + "tests.workflow.test_request_info_event_rehydrate:SimpleApproval", + "tests.workflow.test_request_info_event_rehydrate:SlottedApproval", + "tests.workflow.test_request_info_event_rehydrate:TimedApproval", + ], + ) # Create workflow with checkpointing enabled executor = ApprovalRequiredExecutor(id="approval_executor") @@ -288,7 +308,17 @@ async def test_checkpoint_restore_with_partial_responses_reemits_unhandled_reque import tempfile with tempfile.TemporaryDirectory() as temp_dir: - storage = FileCheckpointStorage(temp_dir) + storage = FileCheckpointStorage( + temp_dir, + allowed_checkpoint_types=[ + "tests.workflow.test_request_info_and_response:UserApprovalRequest", + "tests.workflow.test_request_info_and_response:CalculationRequest", + "tests.workflow.test_request_info_event_rehydrate:MockRequest", + "tests.workflow.test_request_info_event_rehydrate:SimpleApproval", + "tests.workflow.test_request_info_event_rehydrate:SlottedApproval", + "tests.workflow.test_request_info_event_rehydrate:TimedApproval", + ], + ) # Create workflow with multiple requests executor = MultiRequestExecutor(id="multi_executor") diff --git a/python/pytest.xml b/python/pytest.xml new file mode 100644 index 0000000000..13d4791f5a --- /dev/null +++ b/python/pytest.xml @@ -0,0 +1 @@ +/repos/agent-framework/.worktrees/agent/fix-4894-1/python/packages/core/tests/core/test_observability.py:592: Skipping OTLP exporter tests - optional dependency not installed by default/repos/agent-framework/.worktrees/agent/fix-4894-1/python/packages/core/tests/core/test_observability.py:609: Skipping OTLP exporter tests - optional dependency not installed by 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default/repos/agent-framework/.worktrees/agent/fix-4894-1/python/packages/core/tests/core/test_observability.py:776: Skipping OTLP exporter tests - optional dependency not installed by default/repos/agent-framework/.worktrees/agent/fix-4894-1/python/packages/core/tests/core/test_observability.py:790: Skipping OTLP exporter tests - optional dependency not installed by default/repos/agent-framework/.worktrees/agent/fix-4894-1/python/packages/core/tests/core/test_observability.py:804: Skipping OTLP exporter tests - optional dependency not installed by default/repos/agent-framework/.worktrees/agent/fix-4894-1/python/packages/core/tests/core/test_observability.py:823: Skipping OTLP exporter tests - optional dependency not installed by default/repos/agent-framework/.worktrees/agent/fix-4894-1/python/packages/core/tests/core/test_observability.py:839: Skipping OTLP exporter tests - optional dependency not installed by 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