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fix(chatgpt): preserve requested service tier in Responses calls (#40108)
* fix(chatgpt): preserve requested service tier in Responses calls * fix(chatgpt): avoid extra mutable collections in tier filtering * test(chatgpt): refresh service-tier cases after main rebase Keep the tier-preservation regression on the current subscription model and match the moved unit-test suite's formatting. The adapter still forwards preferences without claiming backend priority entitlement. * refactor(chatgpt): map service tier through a lookup table after the allowlist filter --------- Co-authored-by: ryan-crabbe-berri <ryan@berri.ai>
This commit is contained in:
Steffan W
GitHub
parent
56bba4fbbe
commit
e5873adbc4
2 changed files with 57 additions and 29 deletions
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@ -35,6 +35,8 @@ from ..common_utils import (
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if TYPE_CHECKING:
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from litellm.litellm_core_utils.litellm_logging import Logging as LiteLLMLoggingObj
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_CHATGPT_SERVICE_TIERS: Final = {"default": "default", "priority": "priority", "fast": "priority"}
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class ChatGPTResponsesAPIConfig(OpenAIResponsesAPIConfig):
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def __init__(self) -> None:
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@ -108,7 +110,11 @@ class ChatGPTResponsesAPIConfig(OpenAIResponsesAPIConfig):
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"truncation",
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}
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return {k: v for k, v in request.items() if k in allowed_keys}
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filtered: Final = {k: v for k, v in request.items() if k in allowed_keys}
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service_tier: Final = _CHATGPT_SERVICE_TIERS.get(request.get("service_tier"))
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if service_tier is not None:
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filtered["service_tier"] = service_tier
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return filtered
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def transform_response_api_response(
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self,
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@ -6,6 +6,7 @@ Source: litellm/llms/chatgpt/responses/transformation.py
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import json
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from collections.abc import Generator
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from typing import Final
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from unittest.mock import MagicMock, patch
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import httpx
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@ -30,6 +31,46 @@ def local_model_cost_map(monkeypatch: pytest.MonkeyPatch) -> Generator[None, Non
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class TestChatGPTResponsesAPITransformation:
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@pytest.mark.parametrize(
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("requested_tier", "expected_tier"),
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[("default", "default"), ("priority", "priority"), ("fast", "priority")],
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)
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@pytest.mark.parametrize("effort", ["low", "high"])
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def test_chatgpt_preserves_service_tier(self, requested_tier: str, expected_tier: str, effort: str) -> None:
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config: Final = ChatGPTResponsesAPIConfig()
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request: Final = config.transform_responses_api_request(
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model="chatgpt/gpt-6.1-sol",
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input=[{"role": "user", "content": "Reply with OK"}],
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response_api_optional_request_params={
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"service_tier": requested_tier,
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"reasoning": {"effort": effort},
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"max_output_tokens": 16,
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"prompt_cache_options": {"ttl": "30m"},
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},
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litellm_params=GenericLiteLLMParams(),
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headers={},
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)
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assert request["service_tier"] == expected_tier
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assert request["reasoning"] == {"effort": effort}
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assert request["stream"] is True
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assert request["store"] is False
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assert "max_output_tokens" not in request
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assert "prompt_cache_options" not in request
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@pytest.mark.parametrize("requested_tier", [None, "auto", "flex", "unknown"])
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def test_chatgpt_does_not_introduce_unsupported_service_tier(self, requested_tier: str | None) -> None:
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config: Final = ChatGPTResponsesAPIConfig()
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request: Final = config.transform_responses_api_request(
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model="chatgpt/gpt-6.1-sol",
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input=[{"role": "user", "content": "Reply with OK"}],
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response_api_optional_request_params={} if requested_tier is None else {"service_tier": requested_tier},
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litellm_params=GenericLiteLLMParams(),
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headers={},
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)
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assert "service_tier" not in request
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@pytest.mark.parametrize(
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"model_name",
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[
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@ -55,7 +96,6 @@ class TestChatGPTResponsesAPITransformation:
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assert isinstance(config, ChatGPTResponsesAPIConfig)
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assert config.custom_llm_provider == LlmProviders.CHATGPT
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@pytest.mark.parametrize(
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"model_name",
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[
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@ -92,14 +132,10 @@ class TestChatGPTResponsesAPITransformation:
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url = config.get_complete_url(api_base=None, litellm_params={})
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assert url == "https://chatgpt.example.com/responses"
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custom_url = config.get_complete_url(
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api_base="https://custom.chatgpt.com", litellm_params={}
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)
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custom_url = config.get_complete_url(api_base="https://custom.chatgpt.com", litellm_params={})
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assert custom_url == "https://custom.chatgpt.com/responses"
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url_with_slash = config.get_complete_url(
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api_base="https://chatgpt.example.com/", litellm_params={}
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)
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url_with_slash = config.get_complete_url(api_base="https://chatgpt.example.com/", litellm_params={})
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assert url_with_slash == "https://chatgpt.example.com/responses"
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@patch("litellm.llms.chatgpt.responses.transformation.Authenticator")
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@ -162,9 +198,7 @@ class TestChatGPTResponsesAPITransformation:
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"user": "user_123",
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"temperature": 0.2,
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"top_p": 0.9,
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"context_management": [
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{"type": "compaction", "compact_threshold": 200000}
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],
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"context_management": [{"type": "compaction", "compact_threshold": 200000}],
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"metadata": {"foo": "bar"},
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"max_output_tokens": 123,
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"stream_options": {"include_usage": True},
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@ -203,9 +237,7 @@ class TestChatGPTResponsesAPITransformation:
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("chatgpt/gpt-5.3-codex", "gpt-5.3-codex"),
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],
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)
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def test_chatgpt_non_stream_sse_response_parsing(
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self, model_name: str, response_model: str
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):
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def test_chatgpt_non_stream_sse_response_parsing(self, model_name: str, response_model: str):
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config = ChatGPTResponsesAPIConfig()
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response_payload = {
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"id": "resp_test",
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@ -228,9 +260,7 @@ class TestChatGPTResponsesAPITransformation:
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"",
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]
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)
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raw_response = httpx.Response(
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200, headers={"content-type": "text/event-stream"}, text=sse_body
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)
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raw_response = httpx.Response(200, headers={"content-type": "text/event-stream"}, text=sse_body)
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logging_obj = MagicMock()
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parsed = config.transform_response_api_response(
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@ -248,9 +278,7 @@ class TestChatGPTResponsesAPITransformation:
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("chatgpt/gpt-5.3-codex", "gpt-5.3-codex"),
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],
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)
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def test_chatgpt_non_stream_sse_response_recovers_output_items(
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self, model_name: str, response_model: str
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):
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def test_chatgpt_non_stream_sse_response_recovers_output_items(self, model_name: str, response_model: str):
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config = ChatGPTResponsesAPIConfig()
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response_payload = {
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"id": "resp_test",
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@ -273,9 +301,7 @@ class TestChatGPTResponsesAPITransformation:
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"",
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]
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)
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raw_response = httpx.Response(
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200, headers={"content-type": "text/event-stream"}, text=sse_body
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)
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raw_response = httpx.Response(200, headers={"content-type": "text/event-stream"}, text=sse_body)
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logging_obj = MagicMock()
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parsed = config.transform_response_api_response(
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@ -315,9 +341,7 @@ class TestChatGPTResponsesAPITransformation:
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"",
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]
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)
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raw_response = httpx.Response(
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200, headers={"content-type": "text/event-stream"}, text=sse_body
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)
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raw_response = httpx.Response(200, headers={"content-type": "text/event-stream"}, text=sse_body)
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logging_obj = MagicMock()
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parsed = config.transform_response_api_response(
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@ -350,9 +374,7 @@ class TestChatGPTResponsesAPITransformation:
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"",
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]
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)
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raw_response = httpx.Response(
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502, headers={"content-type": "text/event-stream"}, text=sse_body
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)
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raw_response = httpx.Response(502, headers={"content-type": "text/event-stream"}, text=sse_body)
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logging_obj = MagicMock()
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with pytest.raises(OpenAIError) as exc_info:
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