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Eduard van Valkenburg 6e95517659 Python: Split type checkers by target (pyright source, 5 checkers on tests/samples) (#6443)
* Python: Split type checkers by target (pyright source, 5 checkers on tests/samples)

Rework the typing setup along the lines of the 'too many type checkers'
approach:

- Pyright (strict) is now the sole source-code type checker; mypy is
  removed from source and its [tool.mypy] block becomes a relaxed profile
  used only for tests/samples.
- Tests are checked by all five checkers (pyright relaxed, mypy, pyrefly,
  ty, zuban); samples by pyright, pyrefly, and ty. All run in a relaxed/
  basic profile so authors aren't forced into over-annotation.
- Add pyrightconfig.tests.json and bump sample pyright configs to basic.
- Unify test/sample typing onto the same parallel fan-out used by source
  pyright via run_command_items in task_runner.py.
- Make version-conditional imports symmetric: keep or drop the
  '# type: ignore' on both branches so results match across interpreter
  versions (local vs CI).
- Update SKILL.md, DEV_SETUP.md, and CODING_STANDARD.md for the five
  gating checkers and pyright on source+tests+samples.

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

* Python: Fix merge regressions from main (typing + runtime)

Merging main into the type-checker split branch surfaced regressions that
the new five-checker test suite and unit tests caught:

Runtime fixes:
- anthropic: restore the dropped `cache_read_input_token_count` mapping in
  _parse_usage_from_anthropic (lost during merge conflict resolution).
- gemini: _get_function_calling_mode test helper returned str(enum)
  ('FunctionCallingConfigMode.AUTO') instead of the enum value ('AUTO').
- openai: _response_id_from_token test helper was an infinite self-recursion;
  return token['response_id'].
- orchestrations: reset output_events per approval iteration so the terminal
  output assertion counts only the final run.
- core: drop a stale duplicate harness test whose message ('non-negative')
  contradicted the source ('positive').
- purview: import PolicyLocation/PolicyScope/ProtectionScopeActivities/
  ExecutionMode used by the processor tests.

Type-checker fixes (tests, relaxed profile):
- core: pyright/mypy/pyrefly/ty/zuban green-ups across the harness, MCP,
  observability and types tests.
- anthropic/openai: route provider-namespaced UsageDetails keys through a
  dict cast (extra_items TypedDict unsupported by mypy/ty).
- purview: typed model constructors and cache-mock casts.
- ag-ui: annotate WorkflowContext[Any, Any] so yield_output accepts test
  payloads, guard Optional forwarded_props, and ty-ignore intentional bad args.

Source pyright (sole source checker) flagged unnecessary ignores newly
introduced by merged code in core _tools.py and declarative _declarative_base.py.

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

* Python: Isolate per-package mypy cache in test-typing fan-out

The parallel test-typing fan-out runs many mypy processes concurrently,
all defaulting to a single shared ./.mypy_cache. Concurrent writes corrupt
the cache and mypy aborts with INTERNAL ERROR (intermittently, depending on
worker timing) -- which is why CI's Test Typing job failed on a shifting set
of packages while a single-package run was fine.

Give each mypy invocation an isolated cache dir keyed by its target paths so
incremental caching still works per package without races. Other checkers
(zuban/pyrefly/ty/pyright) maintain their own caches and are unaffected.

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

* Python: Make lab pyright-only on source (drop source mypy)

Lab was the last package still running mypy on its source code, requiring
mypy-only `# type: ignore` comments that pyright (the sole source checker
everywhere else) flags as unnecessary. Align lab with the rest of the
monorepo:

- Remove the lab source mypy poe tasks (mypy-gaia/lightning/tau2) and the
  now-dead strict [tool.mypy] config block.
- Drop the 'Run lab mypy' CI step; lab source is type-checked by pyright only.

Lab tests remain covered by the workspace test-typing fan-out (mypy, pyrefly,
ty, zuban, pyright over tests using the relaxed root config).

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

* Python: Fix test-typing regressions from latest main merge

A fresh merge from main brought in new test code never run under the
five-checker test-typing suite. Green up across the affected packages:

- core: narrow Optional span.attributes with 'and' guards in span filters
  and assert+cast the json.loads(...attributes[...]) reads (test_observability);
  match the existing as_agent ignore on the protocol-typed fixture (test_clients).
- openai: align new streaming tests with the established chat_options dict
  pattern (ChatOptions TypedDict isn't assignable to dict), route Optional
  .annotations[0] access through a small _first_annotation helper (mirrors the
  file's assert-not-None convention), and annotate a mapped ResponseStream.
- foundry_hosting: annotate error: dict[str, Any] = body.get(...) or {}
  (zuban needs the annotation).
- foundry: narrow ignores for the live AIProjectClient credential arg (pyrefly)
  and connections.get_default (zuban) SDK type gaps.

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

* updated pyright version

* pyright fix

* Python: Fix source typing for pyright 1.1.410

Pyright 1.1.410 tightened several checks. Apply the same source fixes as
upstream PR #6275:

- anthropic: import AsyncAnthropicBedrock from anthropic.lib.bedrock and
  AsyncAnthropicVertex from anthropic.lib.vertex (no longer re-exported from
  the anthropic top-level package -> reportPrivateImportUsage).
- core _types.py: cast the transform-hook result to UpdateT (reportAssignmentType).
- core _workflows/_events.py: annotate the @contextmanager helper as
  Generator[None] instead of Iterator[None] (reportDeprecated).
- redis: build the combined filter expression with an explicit loop instead of
  reduce(and_, ...), which pyright could no longer fully type (drops the now
  unused functools.reduce / operator.and_ imports).

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

* Python: Accept plain-text body in Azure Functions workflow/run endpoint

The workflow_orchestrator already accepts plain strings as well as JSON
objects via context.get_input(), but the start_workflow_orchestration HTTP
handler only accepted JSON and returned 400 for any non-JSON body. This made
the functions integration tests that POST text/plain to /api/workflow/run
(e.g. test_09_workflow_shared_state) fail consistently with 400 != 202.

Fall back to the raw request body (decoded as UTF-8) when the body is not
JSON, rejecting only a truly empty body. The JSON path is unchanged.

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

---------

Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
2026-06-18 15:06:20 +00:00

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# Copyright (c) Microsoft. All rights reserved.
import asyncio
from typing import cast
from agent_framework import Agent
from agent_framework.openai import OpenAIChatClient, OpenAIChatOptions, OpenAIContinuationToken
from dotenv import load_dotenv
# Load environment variables from .env file
load_dotenv()
"""Background Responses Sample.
This sample demonstrates long-running agent operations using the OpenAI
Responses API ``background`` option. Two patterns are shown:
1. **Non-streaming polling** start a background run, then poll with the
``continuation_token`` until the operation completes.
2. **Streaming with resumption** start a background streaming run, simulate
an interruption, and resume from the last ``continuation_token``.
Prerequisites:
- Set the ``OPENAI_API_KEY`` environment variable.
- A model that benefits from background execution (e.g. ``o3``).
"""
# 1. Create the agent with an OpenAI Responses client.
agent = Agent(
name="researcher",
instructions="You are a helpful research assistant. Be concise.",
client=OpenAIChatClient(model="o3"),
)
async def non_streaming_polling() -> None:
"""Demonstrate non-streaming background run with polling."""
print("=== Non-Streaming Polling ===\n")
session = agent.create_session()
# 2. Start a background run — returns immediately.
response = await agent.run(
messages="Briefly explain the theory of relativity in two sentences.",
session=session,
options=OpenAIChatOptions(background=True),
)
print(f"Initial status: continuation_token={'set' if response.continuation_token else 'None'}")
# 3. Poll until the operation completes.
poll_count = 0
while response.continuation_token is not None:
poll_count += 1
await asyncio.sleep(2)
response = await agent.run(
session=session,
options=OpenAIChatOptions(continuation_token=cast(OpenAIContinuationToken, response.continuation_token)),
)
print(f" Poll {poll_count}: continuation_token={'set' if response.continuation_token else 'None'}")
# 4. Done — print the final result.
print(f"\nResult ({poll_count} poll(s)):\n{response.text}\n")
async def streaming_with_resumption() -> None:
"""Demonstrate streaming background run with simulated interruption and resumption."""
print("=== Streaming with Resumption ===\n")
session = agent.create_session()
# 2. Start a streaming background run.
last_token = None
stream = agent.run(
messages="Briefly list three benefits of exercise.",
stream=True,
session=session,
options=OpenAIChatOptions(background=True),
)
# 3. Read some chunks, then simulate an interruption.
chunk_count = 0
print("First stream (before interruption):")
async for update in stream:
last_token = update.continuation_token
if update.text:
print(update.text, end="", flush=True)
chunk_count += 1
if chunk_count >= 3:
print("\n [simulated interruption]")
break
# 4. Resume from the last continuation token.
if last_token is not None:
print("Resumed stream:")
stream = agent.run(
stream=True,
session=session,
options=OpenAIChatOptions(continuation_token=cast(OpenAIContinuationToken, last_token)),
)
async for update in stream:
if update.text:
print(update.text, end="", flush=True)
print("\n")
async def main() -> None:
await non_streaming_polling()
await streaming_with_resumption()
if __name__ == "__main__":
asyncio.run(main())
"""
Sample output:
=== Non-Streaming Polling ===
Initial status: continuation_token=set
Poll 1: continuation_token=set
Poll 2: continuation_token=None
Result (2 poll(s)):
The theory of relativity, developed by Albert Einstein, consists of special
relativity (1905), which shows that the laws of physics are the same for all
non-accelerating observers and that the speed of light is constant, and general
relativity (1915), which describes gravity as the curvature of spacetime caused
by mass and energy.
=== Streaming with Resumption ===
First stream (before interruption):
Here are three
[simulated interruption]
Resumed stream:
key benefits of regular exercise:
1. **Improved cardiovascular health** ...
2. **Better mental health** ...
3. **Stronger muscles and bones** ...
"""