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agent-framework/python/packages/orchestrations/tests/test_sequential.py
T
Eduard van Valkenburg 1e350ea22f Python: [BREAKING] PR2 — Wire context provider pipeline, remove old types, update all consumers (#3850)
* PR2: Wire context provider pipeline and update all internal consumers

- Replace AgentThread with AgentSession across all packages
- Replace ContextProvider with BaseContextProvider across all packages
- Replace context_provider param with context_providers (Sequence)
- Replace thread= with session= in run() signatures
- Replace get_new_thread() with create_session()
- Add get_session(service_session_id) to agent interface
- DurableAgentThread -> DurableAgentSession
- Remove _notify_thread_of_new_messages from WorkflowAgent
- Wire before_run/after_run context provider pipeline in RawAgent
- Auto-inject InMemoryHistoryProvider when no providers configured

* fix: update all tests for context provider pipeline, fix lazy-loaders, remove old test files

* refactor: update all sample files for context provider pipeline (AgentThread→AgentSession, ContextProvider→BaseContextProvider)

* fix: update remaining ag-ui references (client docstring, getting_started sample)

* fix: make get_session service_session_id keyword-only to avoid confusion with session_id

* refactor: rename _RunContext.thread_messages to session_messages

* refactor: remove _threads.py, _memory.py, and old provider files; migrate devui to use plain message lists

* rename: remove _new_ prefix from test files

* refactor: rewrite SlidingWindowChatMessageStore as SlidingWindowHistoryProvider(InMemoryHistoryProvider)

* fix: read full history from session state directly instead of reaching into provider internals

* fix: update stale .pyi stubs, sample imports, and README references for new provider types

* fix: remove stale message_store, _notify_thread_of_new_messages, and session_id.key references in samples

* refactor: merge context_providers and sessions sample folders into sessions, remove aggregate_context_provider

* refactor: UserInfoMemory stores state in session.state instead of instance attributes

* feat: add Pydantic BaseModel support to session state serialization

Pydantic models stored in session.state are now automatically serialized
via model_dump() and restored via model_validate() during to_dict()/from_dict()
round-trips. Models are auto-registered on first serialization; use
register_state_type() for cold-start deserialization.

Also export register_state_type as a public API.

* fix mem0

* Update sample README links and descriptions for session terminology

- Replace 'thread' with 'session' in sample descriptions across all READMEs
- Update file links for renamed samples (mem0_sessions, redis_sessions, etc.)
- Fix Threads section → Sessions section in main samples/README.md
- Update tools, middleware, workflows, durabletask, azure_functions READMEs
- Update architecture diagrams in concepts/tools/README.md
- Update migration guides (autogen, semantic-kernel)

* Fix broken Redis README link to renamed sample

* Fix Mem0 OSS client search: pass scoping params as direct kwargs

AsyncMemory (OSS) expects user_id/agent_id/run_id as direct kwargs,
while AsyncMemoryClient (Platform) expects them in a filters dict.
Adds tests for both client types.

Port of fix from #3844 to new Mem0ContextProvider.

* Fix rebase issues: restore missing _conversation_state.py and checkpoint decode logic

- Add back _conversation_state.py (encode/decode_chat_messages) lost in rebase
- Fix on_checkpoint_restore to decode cache/conversation with decode_chat_messages
- Fix on_checkpoint_restore to use decode_checkpoint_value for pending requests
- Add tests/workflow/__init__.py for relative import support
- Fix test_agent_executor checkpoint selection (checkpoints[1] not superstep)

* Add STORES_BY_DEFAULT ClassVar to skip redundant InMemoryHistoryProvider injection

Chat clients that store history server-side by default (OpenAI Responses API,
Azure AI Agent) now declare STORES_BY_DEFAULT = True. The agent checks this
during auto-injection and skips InMemoryHistoryProvider unless the user
explicitly sets store=False.

* Fix broken markdown links in azure_ai and redis READMEs

* Fix getting-started samples to use session API instead of removed thread/ContextProvider API

* updates to workflow as agent

* fix group chat import

* Rename Thread→Session throughout, fix service_session_id propagation, remove stale AGUIThread

- Fix: Propagate conversation_id from ChatResponse back to session.service_session_id
  in both streaming and non-streaming paths in _agents.py
- Rename AgentThreadException → AgentSessionException
- Remove stale AGUIThread from ag_ui lazy-loader
- Rename use_service_thread → use_service_session in ag-ui package
- Rename test functions from *_thread_* to *_session_*
- Rename sample files from *_thread* to *_session*
- Update docstrings and comments: thread → session
- Update _mcp.py kwargs filter: add 'session' alongside 'thread'
- Fix ContinuationToken docstring example: thread=thread → session=session
- Fix _clients.py docstring: 'Agent threads' → 'Agent sessions'

* Fix broken markdown links after thread→session file renames

* fix azure ai test
2026-02-12 21:00:32 +00:00

254 lines
9.8 KiB
Python

# Copyright (c) Microsoft. All rights reserved.
from collections.abc import AsyncIterable, Awaitable
from typing import Any
import pytest
from agent_framework import (
AgentExecutorResponse,
AgentResponse,
AgentResponseUpdate,
AgentSession,
BaseAgent,
Content,
Executor,
Message,
TypeCompatibilityError,
WorkflowContext,
WorkflowRunState,
handler,
)
from agent_framework._workflows._checkpoint import InMemoryCheckpointStorage
from agent_framework.orchestrations import SequentialBuilder
class _EchoAgent(BaseAgent):
"""Simple agent that appends a single assistant message with its name."""
def run( # type: ignore[override]
self,
messages: str | Message | list[str] | list[Message] | None = None,
*,
stream: bool = False,
session: AgentSession | None = None,
**kwargs: Any,
) -> Awaitable[AgentResponse] | AsyncIterable[AgentResponseUpdate]:
if stream:
return self._run_stream()
async def _run() -> AgentResponse:
return AgentResponse(messages=[Message("assistant", [f"{self.name} reply"])])
return _run()
async def _run_stream(self) -> AsyncIterable[AgentResponseUpdate]:
# Minimal async generator with one assistant update
yield AgentResponseUpdate(contents=[Content.from_text(text=f"{self.name} reply")])
class _SummarizerExec(Executor):
"""Custom executor that summarizes by appending a short assistant message."""
@handler
async def summarize(self, agent_response: AgentExecutorResponse, ctx: WorkflowContext[list[Message]]) -> None:
conversation = agent_response.full_conversation or []
user_texts = [m.text for m in conversation if m.role == "user"]
agents = [m.author_name or m.role for m in conversation if m.role == "assistant"]
summary = Message("assistant", [f"Summary of users:{len(user_texts)} agents:{len(agents)}"])
await ctx.send_message(list(conversation) + [summary])
class _InvalidExecutor(Executor):
"""Invalid executor that does not have a handler that accepts a list of chat messages"""
@handler
async def summarize(self, conversation: list[str], ctx: WorkflowContext[list[Message]]) -> None:
pass
def test_sequential_builder_rejects_empty_participants() -> None:
with pytest.raises(ValueError):
SequentialBuilder(participants=[])
def test_sequential_builder_validation_rejects_invalid_executor() -> None:
"""Test that adding an invalid executor to the builder raises an error."""
with pytest.raises(TypeCompatibilityError):
SequentialBuilder(participants=[_EchoAgent(id="agent1", name="A1"), _InvalidExecutor(id="invalid")]).build()
async def test_sequential_agents_append_to_context() -> None:
a1 = _EchoAgent(id="agent1", name="A1")
a2 = _EchoAgent(id="agent2", name="A2")
wf = SequentialBuilder(participants=[a1, a2]).build()
completed = False
output: list[Message] | None = None
async for ev in wf.run("hello sequential", stream=True):
if ev.type == "status" and ev.state == WorkflowRunState.IDLE:
completed = True
elif ev.type == "output":
output = ev.data # type: ignore[assignment]
if completed and output is not None:
break
assert completed
assert output is not None
assert isinstance(output, list)
msgs: list[Message] = output
assert len(msgs) == 3
assert msgs[0].role == "user" and "hello sequential" in msgs[0].text
assert msgs[1].role == "assistant" and (msgs[1].author_name == "A1" or True)
assert msgs[2].role == "assistant" and (msgs[2].author_name == "A2" or True)
assert "A1 reply" in msgs[1].text
assert "A2 reply" in msgs[2].text
async def test_sequential_with_custom_executor_summary() -> None:
a1 = _EchoAgent(id="agent1", name="A1")
summarizer = _SummarizerExec(id="summarizer")
wf = SequentialBuilder(participants=[a1, summarizer]).build()
completed = False
output: list[Message] | None = None
async for ev in wf.run("topic X", stream=True):
if ev.type == "status" and ev.state == WorkflowRunState.IDLE:
completed = True
elif ev.type == "output":
output = ev.data
if completed and output is not None:
break
assert completed
assert output is not None
msgs: list[Message] = output
# Expect: [user, A1 reply, summary]
assert len(msgs) == 3
assert msgs[0].role == "user"
assert msgs[1].role == "assistant" and "A1 reply" in msgs[1].text
assert msgs[2].role == "assistant" and msgs[2].text.startswith("Summary of users:")
async def test_sequential_checkpoint_resume_round_trip() -> None:
storage = InMemoryCheckpointStorage()
initial_agents = (_EchoAgent(id="agent1", name="A1"), _EchoAgent(id="agent2", name="A2"))
wf = SequentialBuilder(participants=list(initial_agents), checkpoint_storage=storage).build()
baseline_output: list[Message] | None = None
async for ev in wf.run("checkpoint sequential", stream=True):
if ev.type == "output":
baseline_output = ev.data # type: ignore[assignment]
if ev.type == "status" and ev.state == WorkflowRunState.IDLE:
break
assert baseline_output is not None
checkpoints = await storage.list_checkpoints(workflow_name=wf.name)
assert checkpoints
checkpoints.sort(key=lambda cp: cp.timestamp)
resume_checkpoint = checkpoints[0]
resumed_agents = (_EchoAgent(id="agent1", name="A1"), _EchoAgent(id="agent2", name="A2"))
wf_resume = SequentialBuilder(participants=list(resumed_agents), checkpoint_storage=storage).build()
resumed_output: list[Message] | None = None
async for ev in wf_resume.run(checkpoint_id=resume_checkpoint.checkpoint_id, stream=True):
if ev.type == "output":
resumed_output = ev.data # type: ignore[assignment]
if ev.type == "status" and ev.state in (
WorkflowRunState.IDLE,
WorkflowRunState.IDLE_WITH_PENDING_REQUESTS,
):
break
assert resumed_output is not None
assert [m.role for m in resumed_output] == [m.role for m in baseline_output]
assert [m.text for m in resumed_output] == [m.text for m in baseline_output]
async def test_sequential_checkpoint_runtime_only() -> None:
"""Test checkpointing configured ONLY at runtime, not at build time."""
storage = InMemoryCheckpointStorage()
agents = (_EchoAgent(id="agent1", name="A1"), _EchoAgent(id="agent2", name="A2"))
wf = SequentialBuilder(participants=list(agents)).build()
baseline_output: list[Message] | None = None
async for ev in wf.run("runtime checkpoint test", checkpoint_storage=storage, stream=True):
if ev.type == "output":
baseline_output = ev.data # type: ignore[assignment]
if ev.type == "status" and ev.state == WorkflowRunState.IDLE:
break
assert baseline_output is not None
checkpoints = await storage.list_checkpoints(workflow_name=wf.name)
assert checkpoints
checkpoints.sort(key=lambda cp: cp.timestamp)
resume_checkpoint = checkpoints[0]
resumed_agents = (_EchoAgent(id="agent1", name="A1"), _EchoAgent(id="agent2", name="A2"))
wf_resume = SequentialBuilder(participants=list(resumed_agents)).build()
resumed_output: list[Message] | None = None
async for ev in wf_resume.run(
checkpoint_id=resume_checkpoint.checkpoint_id, checkpoint_storage=storage, stream=True
):
if ev.type == "output":
resumed_output = ev.data # type: ignore[assignment]
if ev.type == "status" and ev.state in (
WorkflowRunState.IDLE,
WorkflowRunState.IDLE_WITH_PENDING_REQUESTS,
):
break
assert resumed_output is not None
assert [m.role for m in resumed_output] == [m.role for m in baseline_output]
assert [m.text for m in resumed_output] == [m.text for m in baseline_output]
async def test_sequential_checkpoint_runtime_overrides_buildtime() -> None:
"""Test that runtime checkpoint storage overrides build-time configuration."""
import tempfile
with tempfile.TemporaryDirectory() as temp_dir1, tempfile.TemporaryDirectory() as temp_dir2:
from agent_framework._workflows._checkpoint import FileCheckpointStorage
buildtime_storage = FileCheckpointStorage(temp_dir1)
runtime_storage = FileCheckpointStorage(temp_dir2)
agents = (_EchoAgent(id="agent1", name="A1"), _EchoAgent(id="agent2", name="A2"))
wf = SequentialBuilder(participants=list(agents), checkpoint_storage=buildtime_storage).build()
baseline_output: list[Message] | None = None
async for ev in wf.run("override test", checkpoint_storage=runtime_storage, stream=True):
if ev.type == "output":
baseline_output = ev.data # type: ignore[assignment]
if ev.type == "status" and ev.state == WorkflowRunState.IDLE:
break
assert baseline_output is not None
buildtime_checkpoints = await buildtime_storage.list_checkpoints(workflow_name=wf.name)
runtime_checkpoints = await runtime_storage.list_checkpoints(workflow_name=wf.name)
assert len(runtime_checkpoints) > 0, "Runtime storage should have checkpoints"
assert len(buildtime_checkpoints) == 0, "Build-time storage should have no checkpoints when overridden"
async def test_sequential_builder_reusable_after_build_with_participants() -> None:
"""Test that the builder can be reused to build multiple identical workflows with participants()."""
a1 = _EchoAgent(id="agent1", name="A1")
a2 = _EchoAgent(id="agent2", name="A2")
builder = SequentialBuilder(participants=[a1, a2])
# Build first workflow
builder.build()
assert builder._participants[0] is a1 # type: ignore
assert builder._participants[1] is a2 # type: ignore