From 6544bbe8230406cc7fa832b2b06137a51072228a Mon Sep 17 00:00:00 2001 From: Andrey Buzin Date: Mon, 2 Nov 2026 13:46:54 -0800 Subject: [PATCH 1/3] Bump openai to 3.42.0 3.42.0 adds `client.decisions` for `POST /v1/decisions`. The OpenAI decisions protocol will use it. Raise the dev dependency floor so the lock cannot fall back to an SDK without it. --- pyproject.toml | 2 +- uv.lock | 8 ++++---- 2 files changed, 5 insertions(+), 5 deletions(-) diff --git a/pyproject.toml b/pyproject.toml index d2f0e042..43c421ad 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -75,7 +75,7 @@ dev = [ "pytest-asyncio>=0.24", "rich>=14.2.0", "mypy~=2.1.0", - "openai>=2.14.0", + "openai>=3.42.0", "ruff~=0.8.0", "async-solipsism>=0.9", "ty~=0.0.37", diff --git a/uv.lock b/uv.lock index 6166b164..a6de3244 100644 --- a/uv.lock +++ b/uv.lock @@ -83,7 +83,7 @@ dev = [ { name = "async-solipsism", specifier = ">=0.9" }, { name = "mcp", specifier = ">=2.0.0,<3.0.0" }, { name = "mypy", specifier = "~=2.1.0" }, - { name = "openai", specifier = ">=2.14.0" }, + { name = "openai", specifier = ">=3.42.0" }, { name = "opentelemetry-exporter-otlp-proto-http", specifier = ">=1.43.0" }, { name = "opentelemetry-sdk", specifier = ">=1.43.0" }, { name = "pytest", specifier = ">=8.0" }, @@ -803,7 +803,7 @@ wheels = [ [[package]] name = "openai" -version = "3.6.0" +version = "3.42.0" source = { registry = "https://pypi.org/simple" } dependencies = [ { name = "anyio" }, @@ -813,9 +813,9 @@ dependencies = [ { name = "sniffio" }, { name = "typing-extensions" }, ] -sdist = { url = "https://files.pythonhosted.org/packages/ac/76/913b755a1a6b54e2d9140eb8d488aa0d47c7359b1d7eac5e864cb7913bbf/openai-3.6.0.tar.gz", hash = "sha256:18fe3f6e96390ef41ee27b152fc9effefca321c33673bd9b956a572493d3ab9b", size = 1455376, upload-time = "2026-08-28T22:29:18.268Z" } +sdist = { url = "https://files.pythonhosted.org/packages/f9/ef/c17c9ca921c1991b0a7185e8282da1996d09292b0caaf2e7cffd7e051eb6/openai-3.42.0.tar.gz", hash = "sha256:deffe27f9e20e4f1d9d471978d12f23aa119382494c0a9860795e66943d0fe42", size = 2353482, upload-time = "2026-10-31T00:27:26.502Z" } wheels = [ - { url = "https://files.pythonhosted.org/packages/a1/94/805b87ecc951c49ec8f247f5e8eb324ab064bd2ad73b6a0e704dd49aa073/openai-3.6.0-py3-none-any.whl", hash = "sha256:508e2158bf971687f953b62e44b02f207792c815aac306816386d7ba34d37f5f", size = 1699841, upload-time = "2026-08-28T22:29:16.436Z" }, + { url = "https://files.pythonhosted.org/packages/c5/79/904afac12186d9ab9e3f731eb798e36dc0f5b991a557c4304b0a43e393c1/openai-3.42.0-py3-none-any.whl", hash = "sha256:efb9d089ecf66c668289f647717389df98b40b954cd86d4fe54eddce39aabb3f", size = 2397860, upload-time = "2026-10-31T00:27:24.493Z" }, ] [[package]] From 7ef6e2c5582f4970dbda974af563378e18804391 Mon Sep 17 00:00:00 2001 From: Andrey Buzin Date: Mon, 2 Nov 2026 14:19:20 -0800 Subject: [PATCH 2/3] Implement OpenAI decisions protocol Add `OpenAIResponsesProtocol.decide`, which sends decisions to `POST /v1/decisions` through `client.decisions.create`. Text, images, and JSON go as content parts. Question IDs go as question names, and answers map back by name. Choice and score probability lists become maps keyed by choice value or level index, like the shared answer models. OpenAI can refuse a single question. Add `RefusalAnswer`. Dynamic mode returns it for any question. Typed mode accepts it only in fields annotated `XAnswer | RefusalAnswer`; a refusal in another field raises `ValueError`. Raise the `openai` extra floor to 3.42.0, the first SDK with `client.decisions`, and test that floor in CI. This makes the `httpx`/`httpx2` switch in the OpenAI tests dead, so import `httpx2` directly. --- .github/workflows/ci.yml | 4 +- examples/models/openai/decisions_images.py | 11 +- pyproject.toml | 2 +- src/ai/ops/experimental/__init__.py | 2 + src/ai/ops/experimental/decisions.py | 51 +- src/ai/providers/openai/_sdk.py | 17 + src/ai/providers/openai/protocol.py | 203 +++ tests/ops/experimental/test_decisions.py | 84 +- tests/providers/openai/test_adapter.py | 6 +- tests/providers/openai/test_probe.py | 7 +- tests/providers/openai/test_protocol.py | 414 ++++++ tests/providers/openai/test_provider.py | 5 +- uv.lock | 1460 ++++++++++---------- 13 files changed, 1509 insertions(+), 757 deletions(-) create mode 100644 tests/providers/openai/test_protocol.py diff --git a/.github/workflows/ci.yml b/.github/workflows/ci.yml index 1808541c..625c6a41 100644 --- a/.github/workflows/ci.yml +++ b/.github/workflows/ci.yml @@ -42,10 +42,10 @@ jobs: matrix: include: - sdk-versions: minimum - openai: openai==2.34.0 + openai: openai==3.42.0 anthropic: anthropic==0.83.0 - sdk-versions: latest - openai: openai>=2.34.0,<4.0.0 + openai: openai>=3.42.0,<4.0.0 anthropic: anthropic>=0.83.0,<2.0.0 name: Provider SDKs (${{ matrix.sdk-versions }}) steps: diff --git a/examples/models/openai/decisions_images.py b/examples/models/openai/decisions_images.py index 62a3f94f..fbf61520 100644 --- a/examples/models/openai/decisions_images.py +++ b/examples/models/openai/decisions_images.py @@ -27,7 +27,11 @@ class DeliveryQuestions(pydantic.BaseModel): class DeliveryAnswers(pydantic.BaseModel): - damaged: ai.ops.experimental.PredicateAnswer + # OpenAI can refuse a question. This field accepts a refusal; a refusal + # for the other fields raises ValueError. + damaged: ( + ai.ops.experimental.PredicateAnswer | ai.ops.experimental.RefusalAnswer + ) condition: ai.ops.experimental.ScoreAnswer matches_reference: ai.ops.experimental.PredicateAnswer @@ -77,7 +81,10 @@ async def main() -> None: ) answers = result.value - print("damaged:", f"{answers.damaged.probability:.0%}") + if isinstance(answers.damaged, ai.ops.experimental.RefusalAnswer): + print("damaged: refused") + else: + print("damaged:", f"{answers.damaged.probability:.0%}") print("condition:", answers.condition.score) print("matches reference:", f"{answers.matches_reference.probability:.0%}") print("usage:", result.usage) diff --git a/pyproject.toml b/pyproject.toml index 43c421ad..99d9ad1c 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -36,7 +36,7 @@ dependencies = [ [project.optional-dependencies] anthropic = ["anthropic>=0.83.0,<2.0.0"] mcp = ["mcp>=2.0.0,<3.0.0"] -openai = ["openai>=2.34.0,<4.0.0"] +openai = ["openai>=3.42.0,<4.0.0"] otel = [ "opentelemetry-exporter-otlp-proto-http>=1.30", "opentelemetry-sdk>=1.30", diff --git a/src/ai/ops/experimental/__init__.py b/src/ai/ops/experimental/__init__.py index 36a66697..32ebb340 100644 --- a/src/ai/ops/experimental/__init__.py +++ b/src/ai/ops/experimental/__init__.py @@ -11,6 +11,7 @@ PredicateAnswer, PredicateCriteria, PredicateQuestion, + RefusalAnswer, ScoreAnswer, ScoreQuestion, decide, @@ -56,6 +57,7 @@ def __getattr__(name: str) -> Any: "PredicateAnswer", "PredicateCriteria", "PredicateQuestion", + "RefusalAnswer", "ScoreAnswer", "ScoreQuestion", "decide", diff --git a/src/ai/ops/experimental/decisions.py b/src/ai/ops/experimental/decisions.py index eee8e94d..cacb073c 100644 --- a/src/ai/ops/experimental/decisions.py +++ b/src/ai/ops/experimental/decisions.py @@ -268,6 +268,18 @@ def noul(self) -> float: return self.probability +class RefusalAnswer(pydantic.BaseModel): + """The model declined to answer this question. + + Annotate an output field as ``XAnswer | RefusalAnswer`` to accept a + refusal for that question. + """ + + type: Literal["refusal"] = "refusal" + + model_config = pydantic.ConfigDict(frozen=True) + + @dataclasses.dataclass(frozen=True, kw_only=True) class DecideParams: """Parameters for decisions.""" @@ -279,7 +291,7 @@ class DecideParams: type _Question = ChoiceQuestion | ScoreQuestion | PredicateQuestion -type _Answer = ChoiceAnswer | ScoreAnswer | PredicateAnswer +type _Answer = ChoiceAnswer | ScoreAnswer | PredicateAnswer | RefusalAnswer _QUESTION_TYPES = (ChoiceQuestion, ScoreQuestion, PredicateQuestion) _ANSWER_TYPES: dict[type[_Question], type[pydantic.BaseModel]] = { @@ -334,6 +346,11 @@ async def decide( ``{"photo": ai.file_part(data), "note": "..."}``. Providers reject files they cannot send. + Some providers can refuse a question. A refusal is a + :class:`RefusalAnswer`. In typed mode, annotate the output field as + ``XAnswer | RefusalAnswer`` to accept it; otherwise a refusal raises + ``ValueError``. + Experimental: not part of the stable API, may change or be removed. """ # Validate the shared state before dispatching it to a provider. @@ -372,21 +389,29 @@ async def decide( # Normalize either public input form to the mapping expected by providers. normalized: dict[str, _Question] = {} + # Questions that accept a refusal. In dynamic mode, all of them do. + refusable: set[str] = set() for name, question in values: if not isinstance(name, str): raise TypeError("question IDs must be strings") if not isinstance(question, _QUESTION_TYPES): raise TypeError(f"question field {name!r} must contain a question") - # In typed mode, verify each question has its corresponding answer type. + # In typed mode, verify each question has its corresponding answer + # type, optionally in a union with RefusalAnswer. if answer_fields is not None: expected = _ANSWER_TYPES[type(question)] actual = answer_fields[name].annotation - if actual is not expected: + if actual == expected | RefusalAnswer: + refusable.add(name) + elif actual is not expected: raise TypeError( f"output field {name!r} must be annotated as " - f"{expected.__name__}" + f"{expected.__name__} or " + f"{expected.__name__} | RefusalAnswer" ) + else: + refusable.add(name) normalized[name] = question # Start telemetry after local validation, immediately around provider work. @@ -410,6 +435,20 @@ async def decide( if raw_item.value.keys() != normalized.keys(): raise ValueError("answer fields must match question fields") + # A refusal needs an output field that accepts it. + refused = { + name + for name, raw_answer in raw_item.value.items() + if isinstance(raw_answer, Mapping) + and raw_answer.get("type") == "refusal" + } + unaccepted = sorted(refused - refusable) + if unaccepted: + raise ValueError( + f"the model refused question {unaccepted[0]!r}; annotate its " + "output field with '| RefusalAnswer' to accept refusals" + ) + if output_type is not None: # Typed mode validates the complete response into the user's model. value: pydantic.BaseModel | dict[str, _Answer] = ( @@ -421,7 +460,9 @@ async def decide( answers: dict[str, _Answer] = {} for name, question in normalized.items(): raw_answer = raw_item.value[name] - if isinstance(question, ChoiceQuestion): + if name in refused: + answers[name] = RefusalAnswer.model_validate(raw_answer) + elif isinstance(question, ChoiceQuestion): answers[name] = ChoiceAnswer.model_validate(raw_answer) elif isinstance(question, ScoreQuestion): answers[name] = ScoreAnswer.model_validate(raw_answer) diff --git a/src/ai/providers/openai/_sdk.py b/src/ai/providers/openai/_sdk.py index 92c2ac23..ab95328e 100644 --- a/src/ai/providers/openai/_sdk.py +++ b/src/ai/providers/openai/_sdk.py @@ -10,6 +10,7 @@ from collections.abc import Callable import openai + from openai.types import decision class OpenAISDK(Protocol): @@ -26,6 +27,11 @@ class OpenAIPydantic(Protocol): to_strict_json_schema: Callable[[Any], dict[str, Any]] +class OpenAIDecisionTypes(Protocol): + AnswerAnswerResourceChoice: type[decision.AnswerAnswerResourceChoice] + AnswerAnswerResourceScore: type[decision.AnswerAnswerResourceScore] + + def import_sdk(*, provider: str = "openai") -> OpenAISDK: return cast( "OpenAISDK", @@ -44,3 +50,14 @@ def import_pydantic(*, provider: str = "openai") -> OpenAIPydantic: extra="openai", ), ) + + +def import_decision_types(*, provider: str = "openai") -> OpenAIDecisionTypes: + return cast( + "OpenAIDecisionTypes", + _optional.import_optional_sdk( + "openai.types.decision", + provider=provider, + extra="openai", + ), + ) diff --git a/src/ai/providers/openai/protocol.py b/src/ai/providers/openai/protocol.py index 147d2d14..54fbf1f4 100644 --- a/src/ai/providers/openai/protocol.py +++ b/src/ai/providers/openai/protocol.py @@ -15,6 +15,8 @@ from ... import types from ...models import core from ...models.core import params as params_ +from ...ops import items +from ...ops.experimental import decisions from .. import base, history_utils from . import _sdk, errors from . import params as openai_params @@ -1898,6 +1900,182 @@ async def _stream_responses( ) from exc +# --------------------------------------------------------------------------- +# Decisions — ``/v1/decisions`` +# --------------------------------------------------------------------------- + + +_DECISIONS_PROTECTED_PARAMS = frozenset({"model", "input", "questions"}) + + +async def _decide( + sdk_client: openai.AsyncOpenAI, + model: core.model.Model, + state: decisions.DecisionInput, + questions: Mapping[ + str, + decisions.ChoiceQuestion + | decisions.ScoreQuestion + | decisions.PredicateQuestion, + ], + *, + params: decisions.DecideParams, + provider: str, +) -> items.Item[dict[str, Any]]: + openai_sdk = _sdk.import_sdk(provider=provider) + + # Provider options are extra top-level request body fields, e.g. + # prompt_cache_key or safety_identifier. + options = params.provider_options.get(provider) + if options is not None and not isinstance(options, Mapping): + raise TypeError(f"provider_options[{provider!r}] must be a mapping") + protected = sorted(_DECISIONS_PROTECTED_PARAMS & (options or {}).keys()) + if protected: + raise ValueError( + "openai decisions provider options cannot override " + "protocol-owned fields: " + ", ".join(protected) + ) + + def has_file(value: Any) -> bool: + if isinstance(value, types.messages.FilePart): + return True + if isinstance(value, dict): + return any(has_file(item) for item in value.values()) + if isinstance(value, list): + return any(has_file(item) for item in value) + return False + + # OpenAI takes content parts: text, images, and JSON objects. A list is + # an ordered list of parts; any other value is one part. Images use the + # Responses API image part. OpenAI does not take files inside JSON. + async def to_parts(value: Any) -> list[dict[str, Any]]: + parts: list[dict[str, Any]] = [] + for item in value if isinstance(value, list) else [value]: + match item: + case str(): + parts.append({"type": "input_text", "text": item}) + case types.messages.FilePart(media_type=media_type): + if not media_type.startswith("image/"): + raise ValueError( + "Unsupported media type for OpenAI decisions: " + f"{media_type}" + ) + parts.append(await _file_part_to_responses(item)) + case dict() if has_file(item): + raise ValueError( + "OpenAI decisions do not support files inside JSON" + ) + case dict(): + parts.append({"type": "input_json", "data": item}) + case _: + raise ValueError( + "OpenAI decisions accept only text, files, and JSON " + f"objects in a list, got {type(item).__name__}" + ) + return parts + + # OpenAI choice and level descriptions are text only. + def description(name: str, criterion: Any) -> dict[str, str]: + if criterion is None: + return {} + if not isinstance(criterion, str): + raise ValueError( + "OpenAI decisions accept only text criteria, " + f"see question {name!r}" + ) + return {"description": criterion} + + # Questions go as a list; the question ID is the name. OpenAI answers + # by name, so each answer goes back to its question. + wire_questions: list[dict[str, Any]] = [] + for name, question in questions.items(): + wire_question: dict[str, Any] = { + "type": question.type, + "name": name, + "instructions": question.instructions + if isinstance(question.instructions, str) + else await to_parts(question.instructions), + } + if isinstance(question, decisions.ChoiceQuestion): + wire_question["choices"] = [ + {"value": value, **description(name, criterion)} + for value, criterion in question.criteria.items() + ] + elif isinstance(question, decisions.ScoreQuestion): + # OpenAI levels need a label. The label is the level index, + # which is also the key of the answer's probabilities. + wire_question["levels"] = [ + {"label": str(index), **description(name, criterion)} + for index, criterion in enumerate(question.criteria) + ] + elif question.criteria and any( + criterion is not None for criterion in question.criteria.values() + ): + raise ValueError( + "OpenAI decisions do not support predicate criteria, " + f"see question {name!r}" + ) + wire_questions.append(wire_question) + + # Shared state is a text string or one user message. + api_kwargs: dict[str, Any] = { + "model": model.id, + "input": state + if isinstance(state, str) + else [{"role": "user", "content": await to_parts(state)}], + "questions": wire_questions, + } + # The SDK takes only known fields as arguments, so provider options go + # in the body. + if options: + api_kwargs["extra_body"] = dict(options) + + try: + response = await sdk_client.decisions.create(**api_kwargs) + except openai_sdk.OpenAIError as exc: + raise errors.map_error( + exc, provider=provider, model_id=model.id + ) from exc + + # Answers come as a list with names. Probability lists become maps + # keyed by choice value or level index, like the shared answer models. + decision_types = _sdk.import_decision_types(provider=provider) + answers: dict[str, Any] = {} + for answer in response.answers: + if ( + answer.name is None + or answer.name not in questions + or answer.name in answers + ): + raise ValueError( + "decision response has an unexpected answer name: " + f"{answer.name!r}" + ) + data = answer.model_dump(mode="json", exclude={"name"}) + if isinstance( + answer, decision_types.AnswerAnswerResourceChoice + ) or isinstance(answer, decision_types.AnswerAnswerResourceScore): + data["probabilities"] = { + str(item.value): item.probability + for item in answer.probabilities + } + answers[answer.name] = data + + usage = response.usage + return items.Item( + value=answers, + usage=types.usage.Usage( + input_tokens=usage.input_tokens, + output_tokens=usage.output_tokens, + reasoning_tokens=usage.output_tokens_details.reasoning_tokens, + cache_read_tokens=usage.input_tokens_details.cached_tokens, + cache_write_tokens=usage.input_tokens_details.cache_write_tokens, + raw=usage.model_dump(mode="json"), + ), + provider_metadata={provider: {"model": response.model}}, + ) + + class OpenAIResponsesProtocol(base.ProviderProtocol[Any]): """OpenAI Responses API protocol.""" @@ -1924,6 +2102,31 @@ def stream( provider=provider, ) + async def decide( + self, + client: openai.AsyncOpenAI, + model: core.model.Model, + state: decisions.DecisionInput, + questions: Mapping[ + str, + decisions.ChoiceQuestion + | decisions.ScoreQuestion + | decisions.PredicateQuestion, + ], + *, + params: decisions.DecideParams, + provider: str, + ) -> items.Item[dict[str, Any]]: + """Hit ``/v1/decisions`` and return raw decision answers.""" + return await _decide( + client, + model, + state, + questions, + params=params, + provider=provider, + ) + def default_protocol(provider: str) -> base.ProviderProtocol[Any]: """Return the best default OpenAI-compatible protocol for *provider*.""" diff --git a/tests/ops/experimental/test_decisions.py b/tests/ops/experimental/test_decisions.py index 480ed82d..b56ad2b8 100644 --- a/tests/ops/experimental/test_decisions.py +++ b/tests/ops/experimental/test_decisions.py @@ -200,7 +200,8 @@ async def test_decide_dynamic_questions() -> None: str, ops.experimental.ChoiceAnswer | ops.experimental.ScoreAnswer - | ops.experimental.PredicateAnswer, + | ops.experimental.PredicateAnswer + | ops.experimental.RefusalAnswer, ] ], ) @@ -215,7 +216,11 @@ async def test_decide_dynamic_questions() -> None: async def test_decide_raises_not_implemented() -> None: provider = ai.get_provider("openai", api_key="[redacted]") - model = ai.Model(id="decision-test", provider=provider) + model = ai.Model( + id="decision-test", + provider=provider, + protocol=ai.providers.openai.OpenAIChatCompletionsProtocol(), + ) class PredicateQuestions(pydantic.BaseModel): answer: ops.experimental.PredicateQuestion @@ -458,6 +463,81 @@ async def test_decide_requires_matching_answer_fields() -> None: ) +def refusal_model() -> models.Model: + return models.Model( + id="mock-decision-model", + provider=StaticDecisionProvider( + answers={ + "department": {"type": "refusal"}, + "severity": {"type": "score", "score": 1.5}, + "refund": {"type": "predicate", "probability": 0.98}, + } + ), + ) + + +async def test_decide_accepts_refusals_in_opted_in_fields() -> None: + class RefusableAnswers(pydantic.BaseModel): + department: ( + ops.experimental.ChoiceAnswer | ops.experimental.RefusalAnswer + ) + severity: ops.experimental.ScoreAnswer + refund: ops.experimental.PredicateAnswer + + result = await ops.experimental.decide( + refusal_model(), + "state", + questions(), + output_type=RefusableAnswers, + ) + + assert result.value.department == ops.experimental.RefusalAnswer() + assert result.value.severity.score == 1.5 + assert result.value.refund.probability == 0.98 + + +async def test_decide_rejects_refusals_in_other_fields() -> None: + with pytest.raises(ValueError, match="refused question 'department'"): + await ops.experimental.decide( + refusal_model(), + "state", + questions(), + output_type=Answers, + ) + + +async def test_decide_returns_refusals_in_dynamic_mode() -> None: + dynamic_questions: dict[str, DecisionQuestion] = { + "department": questions().department, + "severity": questions().severity, + "refund": questions().refund, + } + + result = await ops.experimental.decide( + refusal_model(), "state", dynamic_questions + ) + + assert result.value["department"] == ops.experimental.RefusalAnswer() + assert isinstance(result.value["severity"], ops.experimental.ScoreAnswer) + + +async def test_decide_requires_refusal_union_with_matching_answer() -> None: + class WrongAnswers(pydantic.BaseModel): + department: ( + ops.experimental.PredicateAnswer | ops.experimental.RefusalAnswer + ) + severity: ops.experimental.ScoreAnswer + refund: ops.experimental.PredicateAnswer + + with pytest.raises(TypeError, match=r"ChoiceAnswer \| RefusalAnswer"): + await ops.experimental.decide( + refusal_model(), + "state", + questions(), + output_type=WrongAnswers, + ) + + async def test_decide_accepts_files_in_state_and_questions() -> None: photo = ai.file_part(b"\x89PNG\r\n\x1a\n", media_type="image/png") reference = ai.file_part("https://example.com/reference.jpg") diff --git a/tests/providers/openai/test_adapter.py b/tests/providers/openai/test_adapter.py index f62b61d2..f8b7b76f 100644 --- a/tests/providers/openai/test_adapter.py +++ b/tests/providers/openai/test_adapter.py @@ -6,10 +6,10 @@ from __future__ import annotations -import importlib from types import SimpleNamespace from typing import Any, cast +import httpx2 as httpx import openai import pydantic import pytest @@ -20,10 +20,6 @@ from ai.providers.openai import tools as openai_tools from ai.types import events, messages, tools -httpx = importlib.import_module( - "httpx2" if int(openai.__version__.partition(".")[0]) >= 3 else "httpx" -) - class _Answer(pydantic.BaseModel): answer: str diff --git a/tests/providers/openai/test_probe.py b/tests/providers/openai/test_probe.py index ee2c66e5..e8064d08 100644 --- a/tests/providers/openai/test_probe.py +++ b/tests/providers/openai/test_probe.py @@ -1,18 +1,13 @@ from __future__ import annotations -import importlib import json from typing import Any -import openai +import httpx2 as httpx import pytest import ai -httpx = importlib.import_module( - "httpx2" if int(openai.__version__.partition(".")[0]) >= 3 else "httpx" -) - def _client_with_mock( status_code: int = 200, diff --git a/tests/providers/openai/test_protocol.py b/tests/providers/openai/test_protocol.py new file mode 100644 index 00000000..d9ecf03a --- /dev/null +++ b/tests/providers/openai/test_protocol.py @@ -0,0 +1,414 @@ +"""Tests for the OpenAI ``/v1/decisions`` protocol.""" + +from __future__ import annotations + +import base64 +import json +from typing import Any + +import httpx2 as httpx +import pydantic +import pytest + +import ai +from ai import ops + +_PNG = b"\x89PNG\r\n\x1a\n" + b"\x00" * 16 +_PNG_URL = "data:image/png;base64," + base64.b64encode(_PNG).decode() + + +def _model(handler: Any) -> ai.Model: + provider = ai.get_provider( + "openai", + base_url="https://openai.test/v1", + api_key="sk-test", + client=httpx.AsyncClient(transport=httpx.MockTransport(handler)), + ) + return ai.Model(id="gpt-6-luna", provider=provider) + + +def _response(answers: list[dict[str, Any]]) -> dict[str, Any]: + return { + "model": "gpt-6-luna", + "answers": answers, + "usage": { + "input_tokens": 42, + "input_tokens_details": { + "cached_tokens": 10, + "cache_write_tokens": 2, + }, + "output_tokens": 0, + "output_tokens_details": {"reasoning_tokens": 0}, + "total_tokens": 42, + }, + } + + +class Questions(pydantic.BaseModel): + department: ops.experimental.ChoiceQuestion + severity: ops.experimental.ScoreQuestion + refund: ops.experimental.PredicateQuestion + + +class Answers(pydantic.BaseModel): + department: ops.experimental.ChoiceAnswer + severity: ops.experimental.ScoreAnswer + refund: ops.experimental.PredicateAnswer + + +async def test_decide_sends_native_request_and_parses_answers() -> None: + requests: list[httpx.Request] = [] + + def handler(request: httpx.Request) -> httpx.Response: + requests.append(request) + return httpx.Response( + 200, + json=_response( + [ + { + "type": "choice", + "name": "department", + "choice": "billing", + "confidence": 0.8, + "probabilities": [ + {"value": "billing", "probability": 0.9}, + {"value": "support", "probability": 0.1}, + ], + }, + { + "type": "score", + "name": "severity", + "score": 1.1, + "confidence": 0.55, + "probabilities": [ + {"value": 0, "label": "0", "probability": 0.1}, + {"value": 1, "label": "1", "probability": 0.7}, + {"value": 2, "label": "2", "probability": 0.2}, + ], + }, + { + "type": "predicate", + "name": "refund", + "probability": 0.95, + }, + ] + ), + ) + + result = await ops.experimental.decide( + _model(handler), + "I was charged twice.", + Questions( + department=ops.experimental.ChoiceQuestion( + instructions="Which team should handle this?", + criteria={"billing": "Payments and refunds.", "support": None}, + ), + severity=ops.experimental.ScoreQuestion( + instructions="How severe is this?", + criteria=["Cosmetic", "Workaround", None], + ), + refund=ops.experimental.PredicateQuestion( + instructions="Does the customer want a refund?", + ), + ), + output_type=Answers, + ) + + assert len(requests) == 1 + assert str(requests[0].url) == "https://openai.test/v1/decisions" + assert json.loads(requests[0].content) == { + "model": "gpt-6-luna", + "input": "I was charged twice.", + "questions": [ + { + "type": "choice", + "name": "department", + "instructions": "Which team should handle this?", + "choices": [ + { + "value": "billing", + "description": "Payments and refunds.", + }, + {"value": "support"}, + ], + }, + { + "type": "score", + "name": "severity", + "instructions": "How severe is this?", + "levels": [ + {"label": "0", "description": "Cosmetic"}, + {"label": "1", "description": "Workaround"}, + {"label": "2"}, + ], + }, + { + "type": "predicate", + "name": "refund", + "instructions": "Does the customer want a refund?", + }, + ], + } + assert result.value == Answers( + department=ops.experimental.ChoiceAnswer( + choice="billing", + confidence=0.8, + probabilities={"billing": 0.9, "support": 0.1}, + ), + severity=ops.experimental.ScoreAnswer( + score=1.1, + confidence=0.55, + probabilities={"0": 0.1, "1": 0.7, "2": 0.2}, + ), + refund=ops.experimental.PredicateAnswer(probability=0.95), + ) + assert result.usage == ai.types.usage.Usage( + input_tokens=42, + output_tokens=0, + reasoning_tokens=0, + cache_read_tokens=10, + cache_write_tokens=2, + raw=_response([])["usage"], + ) + assert result.provider_metadata == {"openai": {"model": "gpt-6-luna"}} + + +async def test_decide_sends_files_and_json_as_parts() -> None: + requests: list[httpx.Request] = [] + + def handler(request: httpx.Request) -> httpx.Response: + requests.append(request) + return httpx.Response( + 200, + json=_response( + [{"type": "predicate", "name": "match", "probability": 0.99}] + ), + ) + + await ops.experimental.decide( + _model(handler), + [ + "This is photo A.", + ai.file_part(_PNG, media_type="image/png"), + {"order": {"charges": [49, 49]}}, + ], + { + "match": ops.experimental.PredicateQuestion( + instructions=[ + "Is photo B a copy of photo A?", + ai.file_part( + "https://example.com/b.jpg", media_type="image/jpeg" + ), + ], + ), + }, + ) + + body = json.loads(requests[0].content) + assert body["input"] == [ + { + "role": "user", + "content": [ + {"type": "input_text", "text": "This is photo A."}, + {"type": "input_image", "image_url": _PNG_URL}, + { + "type": "input_json", + "data": {"order": {"charges": [49, 49]}}, + }, + ], + } + ] + assert body["questions"][0]["instructions"] == [ + {"type": "input_text", "text": "Is photo B a copy of photo A?"}, + {"type": "input_image", "image_url": "https://example.com/b.jpg"}, + ] + + +@pytest.mark.parametrize( + ("state", "content"), + [ + ({"a": 1}, [{"type": "input_json", "data": {"a": 1}}]), + ( + ai.file_part(_PNG, media_type="image/png"), + [{"type": "input_image", "image_url": _PNG_URL}], + ), + ], +) +async def test_decide_sends_single_values_as_one_part( + state: Any, content: list[dict[str, Any]] +) -> None: + requests: list[httpx.Request] = [] + + def handler(request: httpx.Request) -> httpx.Response: + requests.append(request) + return httpx.Response( + 200, + json=_response( + [{"type": "predicate", "name": "ok", "probability": 0.5}] + ), + ) + + await ops.experimental.decide( + _model(handler), + state, + {"ok": ops.experimental.PredicateQuestion(instructions="OK?")}, + ) + + assert json.loads(requests[0].content)["input"] == [ + {"role": "user", "content": content} + ] + + +async def test_decide_returns_refusals() -> None: + def handler(request: httpx.Request) -> httpx.Response: + return httpx.Response( + 200, + json=_response( + [ + {"type": "refusal", "name": "unsafe"}, + {"type": "predicate", "name": "safe", "probability": 0.1}, + ] + ), + ) + + result = await ops.experimental.decide( + _model(handler), + "state", + { + "unsafe": ops.experimental.PredicateQuestion(instructions="A?"), + "safe": ops.experimental.PredicateQuestion(instructions="B?"), + }, + ) + + assert result.value == { + "unsafe": ops.experimental.RefusalAnswer(), + "safe": ops.experimental.PredicateAnswer(probability=0.1), + } + + +async def test_decide_sends_provider_options() -> None: + requests: list[httpx.Request] = [] + + def handler(request: httpx.Request) -> httpx.Response: + requests.append(request) + return httpx.Response( + 200, + json=_response( + [{"type": "predicate", "name": "ok", "probability": 0.5}] + ), + ) + + await ops.experimental.decide( + _model(handler), + "state", + {"ok": ops.experimental.PredicateQuestion(instructions="OK?")}, + params=ops.experimental.DecideParams( + provider_options={ + "openai": {"prompt_cache_key": "tickets"}, + "gateway": {"ignored": True}, + } + ), + ) + + body = json.loads(requests[0].content) + assert body["prompt_cache_key"] == "tickets" + assert "ignored" not in body + + +@pytest.mark.parametrize( + ("state", "question", "match"), + [ + ( + "state", + ops.experimental.PredicateQuestion( + instructions="OK?", criteria={"true": "Yes."} + ), + "predicate criteria", + ), + ( + "state", + ops.experimental.ChoiceQuestion( + instructions="Which?", criteria={"a": {"rule": 1}, "b": None} + ), + "text criteria", + ), + ( + ai.file_part(b"%PDF-1.4", media_type="application/pdf"), + ops.experimental.PredicateQuestion(instructions="OK?"), + "application/pdf", + ), + ( + {"photo": ai.file_part(_PNG, media_type="image/png")}, + ops.experimental.PredicateQuestion(instructions="OK?"), + "files inside JSON", + ), + ( + ["text", 1], + ops.experimental.PredicateQuestion(instructions="OK?"), + "got int", + ), + ], +) +async def test_decide_rejects_unsupported_input( + state: Any, question: Any, match: str +) -> None: + def handler(request: httpx.Request) -> httpx.Response: + raise AssertionError("request must not be sent") + + with pytest.raises(ValueError, match=match): + await ops.experimental.decide(_model(handler), state, {"ok": question}) + + +@pytest.mark.parametrize( + ("options", "error", "match"), + [ + ("bad", TypeError, "must be a mapping"), + ({"model": "other"}, ValueError, "protocol-owned fields: model"), + ], +) +async def test_decide_rejects_invalid_provider_options( + options: Any, error: type[Exception], match: str +) -> None: + def handler(request: httpx.Request) -> httpx.Response: + raise AssertionError("request must not be sent") + + with pytest.raises(error, match=match): + await ops.experimental.decide( + _model(handler), + "state", + {"ok": ops.experimental.PredicateQuestion(instructions="OK?")}, + params=ops.experimental.DecideParams( + provider_options={"openai": options} + ), + ) + + +async def test_decide_maps_status_errors() -> None: + def handler(request: httpx.Request) -> httpx.Response: + return httpx.Response( + 429, json={"error": {"message": "slow down", "type": "rate"}} + ) + + with pytest.raises(ai.errors.ProviderRateLimitError): + await ops.experimental.decide( + _model(handler), + "state", + {"ok": ops.experimental.PredicateQuestion(instructions="OK?")}, + ) + + +async def test_decide_rejects_unexpected_answer_names() -> None: + def handler(request: httpx.Request) -> httpx.Response: + return httpx.Response( + 200, + json=_response( + [{"type": "predicate", "name": "other", "probability": 0.5}] + ), + ) + + with pytest.raises(ValueError, match="unexpected answer name: 'other'"): + await ops.experimental.decide( + _model(handler), + "state", + {"ok": ops.experimental.PredicateQuestion(instructions="OK?")}, + 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