amoghrajesh commented on code in PR #76752:
URL: https://github.com/apache/airflow/pull/76752#discussion_r4534095744
##########
providers/common/ai/src/airflow/providers/common/ai/tools/_from_toolset.py:
##########
@@ -88,12 +93,104 @@ def airflow_tools_from_toolset(toolset:
AbstractToolset[Any], *, deps: Any = Non
:param toolset: The pydantic-ai toolset to expose.
:param deps: Exposed to the toolset as ``ctx.deps``.
"""
- ctx: RunContext[Any] = RunContext(deps=deps, model=TestModel(),
usage=RunUsage(), max_retries=1)
+ ctx = _build_inert_context(deps)
toolset_tools = run_coroutine_sync(toolset.get_tools(ctx))
in_order = _InOrder()
return [_as_airflow_tool(toolset, name, tool, ctx, in_order) for name,
tool in toolset_tools.items()]
+def _build_inert_context(deps: Any = None) -> RunContext[Any]:
+ return RunContext(deps=deps, model=TestModel(), usage=RunUsage(),
max_retries=1)
+
+
+# The wrappers that only choose which tools the model is offered, and under
what name.
+_NAMING_WRAPPERS = (FilteredToolset, PrefixedToolset, RenamedToolset)
+
+
+def _is_naming_wrapper(
+ toolset: object,
+) -> TypeGuard[FilteredToolset[Any] | PrefixedToolset[Any] |
RenamedToolset[Any]]:
+ # Exact types: the tools reached around a wrapper skip its call_tool,
which a subclass may override.
+ return type(toolset) in _NAMING_WRAPPERS
+
+
+def resolve_airflow_tools(source: object) -> list[AirflowTool]:
+ """
+ Return the tools of a toolset a framework adapter was given.
+
+ A source with an ``airflow_tools()`` method is asked for them. A toolset
wrapped with
+ ``.filtered()``, ``.prefixed()`` or ``.renamed()``, nested in any order,
gives the innermost
+ toolset's own ``airflow_tools()``, so they behave as they do without the
wrappers. The
+ wrappers' own ``get_tools`` decides which of them the model is offered and
under what name,
+ given the same inert ``RunContext`` :func:`airflow_tools_from_toolset`
passes. A ``.filtered()``
+ function therefore runs once, when the adapter is built, rather than
before every model turn
+ as in a pydantic-ai run.
+
+ :raises TypeError: when ``source`` is any other wrapper, such as
``.approval_required()``,
+ or there is no ``airflow_tools()`` method under its wrappers.
+ :raises ValueError: when a ``.renamed()`` map sends an offered name to a
name the toolset does
+ not have, such as a map written backwards.
+ """
+ # Looked up, not checked against ToolProvider: since Python 3.12 a
Protocol check misses a
+ # method that a mock or proxy only provides through __getattr__.
+ own = getattr(source, "airflow_tools", None)
+ if callable(own):
+ return list(own())
+ if not _is_naming_wrapper(source):
+ raise TypeError(_describe_unsupported_toolset(source))
+ renames: list[PrefixedToolset[Any] | RenamedToolset[Any]] = []
+ inner: AbstractToolset[Any] = source
+ while _is_naming_wrapper(inner):
+ if not isinstance(inner, FilteredToolset):
+ renames.append(inner)
+ inner = inner.wrapped
+ provide = getattr(inner, "airflow_tools", None)
+ if not callable(provide):
+ raise TypeError(_describe_unsupported_toolset(inner))
+ by_name = {tool.name: tool for tool in provide()}
+ offered = run_coroutine_sync(source.get_tools(_build_inert_context()))
+ tools = []
+ for name in offered:
+ # Map the offered name back through each wrapper, as its ``call_tool``
does.
+ original = name
+ for wrapper in renames:
+ if isinstance(wrapper, PrefixedToolset):
+ original = original.removeprefix(f"{wrapper.prefix}_")
+ else:
+ original = wrapper.name_map.get(original, original)
+ if original not in by_name:
+ raise ValueError(
+ f"The tool offered as {name!r} maps back to {original!r},
which "
+ f"{type(inner).__name__} does not have. .renamed() maps each
new name to the "
+ "toolset's own name, as in .renamed({'run_sql': 'query'})."
+ )
+ tools.append(replace(by_name[original], name=name))
+ return tools
+
+
+def _describe_unsupported_toolset(toolset: object) -> str:
+ if isinstance(toolset, ApprovalRequiredToolset):
+ return (
+ "AirflowTools cannot carry ApprovalRequiredToolset
(.approval_required()) to another "
+ "framework's agent: only a Pydantic AI run pauses for the approval
it asks for. Pass the "
+ "toolset without it. To have a person approve tool calls, run the
agent with "
+ "AgentOperator; a framework's own tool approval, such as
needs_approval in the OpenAI "
+ "Agents SDK, stops the run and nothing in Airflow resumes it."
Review Comment:
The `.approval_required()` error says needs_approval "stops the run and
nothing in Airflow resumes it". But #76786 makes `run_durably` pause for
needs_approval on Airflow 3.4+, so after both merge, this message points users
the wrong way. Whichever PR lands second should update this string, its
exact-match test in test_tools.py, and the openai_agents.rst line.
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