"""Tests for LLM model recommendation helpers.""" from __future__ import annotations import litellm import pytest from agents.extensions.models.litellm_model import LitellmModel from agents.model_settings import ModelSettings from agents.models import _openai_shared from agents.models.openai_chatcompletions import OpenAIChatCompletionsModel from agents.models.openai_responses import OpenAIResponsesModel from strix.config.models import ( RECOMMENDED_MODEL_NAMES, StrixProvider, _NonStreamingModel, _TurnGuardModel, configure_sdk_model_defaults, is_recommended_or_frontier_model, request_timeout_extra_args, routes_through_litellm, supports_strict_tool_schemas, uses_chat_completions_tool_schema, ) from strix.config.settings import Settings @pytest.mark.parametrize("model_name", RECOMMENDED_MODEL_NAMES) def test_recommended_models_are_accepted(model_name: str) -> None: assert is_recommended_or_frontier_model(model_name) def test_request_timeout_extra_args_positive() -> None: assert request_timeout_extra_args(300) == {"timeout": 300} assert request_timeout_extra_args(10) == {"timeout": 10} def test_request_timeout_extra_args_survives_model_settings_json_dump() -> None: """The Chat Completions and LiteLLM paths pydantic-serialize ModelSettings for their tracing span; a non-JSON-serializable timeout fails every turn there.""" settings = ModelSettings(extra_args=request_timeout_extra_args(300)) assert settings.to_json_dict()["extra_args"] == {"timeout": 300} @pytest.mark.parametrize("value", [None, 0, -1]) def test_request_timeout_extra_args_disabled(value: float | None) -> None: assert request_timeout_extra_args(value) is None def test_recommended_models_are_matched_case_insensitively() -> None: assert is_recommended_or_frontier_model("Vertex_AI/Gemini-3-Pro-Preview") @pytest.mark.parametrize( "model_name", [ "gpt-5.5", "chatgpt/gpt-5.4", "litellm/openai/gpt-5.4-pro", "azure_ai/gpt-5.5-pro", "bedrock_mantle/openai.gpt-5.5", "anthropic/claude-opus-5", "anthropic/claude-opus-4-8", "anthropic.claude-opus-4-8", "anthropic/claude-opus-4-7", "anthropic/claude-fable-5", "anthropic/claude-sonnet-5", "vertex_ai/claude-sonnet-5@default", "vertex_ai/claude-sonnet-4-6@default", "any-llm/anthropic/claude-sonnet-4-6", "vertex_ai/gemini-3.1-pro-preview", "openrouter/google/gemini-3.1-pro-preview", "deepseek/deepseek-v4-pro", "deepseek/deepseek-r1-0528", "deepseek/deepseek-reasoner", "dashscope/qwen3-max-2026-01-23", "qwen3.7-max", "dashscope/qwen3.8-max", "moonshot/kimi-k2.6", "kimi-k2.7-code", "moonshot/kimi-k3", "anthropic/claude-fable-5-1", "vertex_ai/claude-fable-5-1@default", "gemini/gemini-3.7-flash", "glm-5.3", "zai/glm-5.3-flash", "openrouter/z-ai/glm-5.3", "novita/zai-org/glm-5.2", "openai/glm-5.3", "openai/zai-org/glm-5.3", "hosted_vllm/glm-5.3", "openai/claude-opus-4-8", "openai/deepseek-v4-pro", "custom-ollama/gpt-5-mini-local", "custom-provider/claude-opus-4-local", "custom-provider/glm-5.3-local", ], ) def test_frontier_model_families_are_accepted(model_name: str) -> None: assert is_recommended_or_frontier_model(model_name) @pytest.mark.parametrize( "model_name", [ "", "openai/gpt-4.1", "anthropic/claude-3-5-sonnet-latest", "ollama/llama3.1", "deepseek/deepseek-chat", "xai/grok-4.5", "openrouter/x-ai/grok-4", "mistral/mistral-medium-3-5", "mistral/magistral-medium-latest", "zai/glm-4.7", "openai/glm-4.7", "openrouter/z-ai/glm-5", ], ) def test_non_frontier_models_are_rejected(model_name: str) -> None: assert not is_recommended_or_frontier_model(model_name) @pytest.mark.parametrize( "model_name", [ "anthropic/claude-sonnet-4-6", "bedrock/anthropic.claude-opus-4-8-v1:0", "vertex_ai/claude-sonnet-5", "Sonnet-5", ], ) def test_claude_routes_reject_strict_tool_schemas(model_name: str) -> None: assert not supports_strict_tool_schemas(model_name) @pytest.mark.parametrize( "model_name", ["openai/gpt-5.4", "gpt-5.4", "gemini/gemini-3.1-pro-preview", "deepseek/deepseek-v4"], ) def test_other_routes_keep_strict_tool_schemas(model_name: str) -> None: assert supports_strict_tool_schemas(model_name) @pytest.mark.parametrize( ("model_name", "litellm"), [ ("claude-sonnet-4-5", False), ("openai/claude-sonnet-4-5", False), ("any-llm/anthropic/claude-sonnet-4-5", False), ("anthropic/claude-sonnet-4-5", True), ("litellm/anthropic/claude-sonnet-4-5", True), ("bedrock/anthropic.claude-sonnet-4-5-20250929-v1:0", True), ("ollama/llama3", True), ], ) def test_routes_through_litellm_matches_the_provider( monkeypatch: pytest.MonkeyPatch, model_name: str, litellm: bool ) -> None: """The helper must agree with what StrixProvider actually builds. Callers use it to decide whether a LiteLLM-only request field is safe to attach; on the SDK's own clients such a field raises TypeError mid-turn, so drift here breaks every request on that route. """ monkeypatch.setenv("OPENAI_API_KEY", "test-key") assert routes_through_litellm(model_name) is litellm try: model = StrixProvider().get_model(model_name) except ImportError: # any-llm's client is an optional dependency; reaching it at all already # proves the route is not LiteLLM's. assert not litellm return while isinstance(model, _NonStreamingModel | _TurnGuardModel): model = model._inner assert isinstance(model, LitellmModel) is litellm def test_api_type_override_settings(monkeypatch: pytest.MonkeyPatch) -> None: monkeypatch.setenv("STRIX_LLM", "gpt-4") monkeypatch.setenv("STRIX_API_TYPE", "chat_completions") assert uses_chat_completions_tool_schema("gpt-4", Settings()) is True monkeypatch.setenv("STRIX_LLM", "openai/gpt-4") monkeypatch.setenv("STRIX_API_TYPE", "responses") assert uses_chat_completions_tool_schema("openai/gpt-4", Settings()) is False monkeypatch.setenv("STRIX_LLM", "anthropic/claude-sonnet-4-5") assert uses_chat_completions_tool_schema("anthropic/claude-sonnet-4-5", Settings()) is True @pytest.mark.parametrize( ("api_type", "expected"), [ (None, OpenAIChatCompletionsModel), ("chat_completions", OpenAIChatCompletionsModel), ("responses", OpenAIResponsesModel), ], ) def test_api_type_overrides_the_api_base_route( monkeypatch: pytest.MonkeyPatch, api_type: str | None, expected: type ) -> None: """``LLM_API_BASE`` defaults to chat completions. ``STRIX_API_TYPE`` must win.""" monkeypatch.setattr(_openai_shared, "_use_responses_by_default", True) monkeypatch.setattr(_openai_shared, "_default_openai_client", None) monkeypatch.setattr(_openai_shared, "_default_openai_key", None) monkeypatch.setattr(litellm, "api_key", None) monkeypatch.setattr(litellm, "api_base", None) monkeypatch.setenv("OPENAI_API_KEY", "test-key") monkeypatch.setenv("OPENAI_BASE_URL", "") monkeypatch.setenv("STRIX_LLM", "gpt-5") monkeypatch.setenv("LLM_API_KEY", "test-key") monkeypatch.setenv("LLM_API_BASE", "https://gateway.example/v1") monkeypatch.delenv("STRIX_API_TYPE", raising=False) if api_type is not None: monkeypatch.setenv("STRIX_API_TYPE", api_type) configure_sdk_model_defaults(Settings()) model = StrixProvider().get_model("gpt-5") while isinstance(model, _NonStreamingModel | _TurnGuardModel): model = model._inner assert isinstance(model, expected)