Files
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

168 lines
5.7 KiB
Python

# Copyright (c) Microsoft. All rights reserved.
"""Agent definitions and AgentCard factories for the A2A server sample.
Provides factory functions to create Agent Framework agents and A2A
AgentCards for the invoice, policy, and logistics agent types.
"""
from __future__ import annotations
from a2a.types import AgentCapabilities, AgentCard, AgentInterface, AgentSkill
from agent_framework import Agent
from agent_framework.foundry import FoundryChatClient
from invoice_data import query_by_invoice_id, query_by_transaction_id, query_invoices # pyrefly: ignore[missing-import]
# ---------------------------------------------------------------------------
# Agent instructions
# ---------------------------------------------------------------------------
INVOICE_INSTRUCTIONS = "You specialize in handling queries related to invoices."
POLICY_INSTRUCTIONS = """\
You specialize in handling queries related to policies and customer communications.
Always reply with exactly this text:
Policy: Short Shipment Dispute Handling Policy V2.1
Summary: "For short shipments reported by customers, first verify internal shipment records
(SAP) and physical logistics scan data (BigQuery). If discrepancy is confirmed and logistics data
shows fewer items packed than invoiced, issue a credit for the missing items. Document the
resolution in SAP CRM and notify the customer via email within 2 business days, referencing the
original invoice and the credit memo number. Use the 'Formal Credit Notification' email
template."
"""
LOGISTICS_INSTRUCTIONS = """\
You specialize in handling queries related to logistics.
Always reply with exactly:
Shipment number: SHPMT-SAP-001
Item: TSHIRT-RED-L
Quantity: 900
"""
# ---------------------------------------------------------------------------
# Agent factories
# ---------------------------------------------------------------------------
def create_invoice_agent(client: FoundryChatClient) -> Agent:
"""Create an invoice agent backed by the given client with query tools."""
return Agent(
client=client,
name="InvoiceAgent",
instructions=INVOICE_INSTRUCTIONS,
tools=[query_invoices, query_by_transaction_id, query_by_invoice_id],
)
def create_policy_agent(client: FoundryChatClient) -> Agent:
"""Create a policy agent backed by the given client."""
return Agent(
client=client,
name="PolicyAgent",
instructions=POLICY_INSTRUCTIONS,
)
def create_logistics_agent(client: FoundryChatClient) -> Agent:
"""Create a logistics agent backed by the given client."""
return Agent(
client=client,
name="LogisticsAgent",
instructions=LOGISTICS_INSTRUCTIONS,
)
# ---------------------------------------------------------------------------
# AgentCard factories
# ---------------------------------------------------------------------------
_CAPABILITIES = AgentCapabilities(streaming=True, push_notifications=False)
def get_invoice_agent_card(url: str) -> AgentCard:
"""Return an A2A AgentCard for the invoice agent."""
return AgentCard(
name="InvoiceAgent",
description="Handles requests relating to invoices.",
version="1.0.0",
default_input_modes=["text"],
default_output_modes=["text"],
capabilities=_CAPABILITIES,
supported_interfaces=[AgentInterface(url=url, protocol_binding="JSONRPC")],
skills=[
AgentSkill(
id="id_invoice_agent",
name="InvoiceQuery",
description="Handles requests relating to invoices.",
tags=["invoice", "agent-framework"],
examples=["List the latest invoices for Contoso."],
),
],
)
def get_policy_agent_card(url: str) -> AgentCard:
"""Return an A2A AgentCard for the policy agent."""
return AgentCard(
name="PolicyAgent",
description="Handles requests relating to policies and customer communications.",
version="1.0.0",
default_input_modes=["text"],
default_output_modes=["text"],
capabilities=_CAPABILITIES,
supported_interfaces=[AgentInterface(url=url, protocol_binding="JSONRPC")],
skills=[
AgentSkill(
id="id_policy_agent",
name="PolicyAgent",
description="Handles requests relating to policies and customer communications.",
tags=["policy", "agent-framework"],
examples=["What is the policy for short shipments?"],
),
],
)
def get_logistics_agent_card(url: str) -> AgentCard:
"""Return an A2A AgentCard for the logistics agent."""
return AgentCard(
name="LogisticsAgent",
description="Handles requests relating to logistics.",
version="1.0.0",
default_input_modes=["text"],
default_output_modes=["text"],
capabilities=_CAPABILITIES,
supported_interfaces=[AgentInterface(url=url, protocol_binding="JSONRPC")],
skills=[
AgentSkill(
id="id_logistics_agent",
name="LogisticsQuery",
description="Handles requests relating to logistics.",
tags=["logistics", "agent-framework"],
examples=["What is the status for SHPMT-SAP-001"],
),
],
)
# ---------------------------------------------------------------------------
# Lookup helpers
# ---------------------------------------------------------------------------
AGENT_FACTORIES = {
"invoice": create_invoice_agent,
"policy": create_policy_agent,
"logistics": create_logistics_agent,
}
AGENT_CARD_FACTORIES = {
"invoice": get_invoice_agent_card,
"policy": get_policy_agent_card,
"logistics": get_logistics_agent_card,
}