From 0f3c4ccfbba894c0a66d92ed44ca18f312bf75f0 Mon Sep 17 00:00:00 2001 From: jesus Date: Fri, 11 Sep 2026 00:00:17 +0000 Subject: [PATCH 01/83] fix(auth): inherit organization_alias from the org for JWT and team-linked keys Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> --- litellm/proxy/auth/user_api_key_auth.py | 42 ++++++- .../proxy/auth/test_user_api_key_auth.py | 104 +++++++++++++++++- 2 files changed, 143 insertions(+), 3 deletions(-) diff --git a/litellm/proxy/auth/user_api_key_auth.py b/litellm/proxy/auth/user_api_key_auth.py index 20ab9904f46..110c524ecdf 100644 --- a/litellm/proxy/auth/user_api_key_auth.py +++ b/litellm/proxy/auth/user_api_key_auth.py @@ -54,6 +54,7 @@ from litellm.proxy.auth.auth_checks import ( get_end_user_object, get_jwt_key_mapping_object, get_object_permission, + get_org_object, get_project_object, get_team_object, get_user_object, @@ -2398,6 +2399,37 @@ def _token_can_vouch_for_team(valid_token: UserAPIKeyAuth, lookup_error: BaseExc return PrismaDBExceptionHandler.should_allow_request_on_db_unavailable() +async def _inherit_org_identity( + user_api_key_auth_obj: UserAPIKeyAuth, + team_object: LiteLLM_TeamTableCachedObj | None, + prisma_client: PrismaClient | None, + user_api_key_cache: UserApiKeyCache, + parent_otel_span: Span | None, + proxy_logging_obj: ProxyLogging | None, +) -> None: + if user_api_key_auth_obj.org_id is None and team_object is not None and team_object.organization_id is not None: + user_api_key_auth_obj.org_id = team_object.organization_id + if ( + user_api_key_auth_obj.org_id is None + or user_api_key_auth_obj.organization_alias is not None + or prisma_client is None + ): + return + try: + org_object: Final = await get_org_object( + org_id=user_api_key_auth_obj.org_id, + prisma_client=prisma_client, + user_api_key_cache=user_api_key_cache, + parent_otel_span=parent_otel_span, + proxy_logging_obj=proxy_logging_obj, + ) + except Exception: + verbose_proxy_logger.debug("org alias lookup failed for org_id=%s", user_api_key_auth_obj.org_id, exc_info=True) + return + if org_object is not None: + user_api_key_auth_obj.organization_alias = org_object.organization_alias + + @tracer.wrap() async def _run_centralized_common_checks( user_api_key_auth_obj: UserAPIKeyAuth, @@ -2622,8 +2654,14 @@ async def _run_centralized_common_checks( ) global_proxy_spend: float | None = None if isinstance(global_spend_result, BaseException) else global_spend_result - if user_api_key_auth_obj.org_id is None and team_object is not None and team_object.organization_id is not None: - user_api_key_auth_obj.org_id = team_object.organization_id + await _inherit_org_identity( + user_api_key_auth_obj=user_api_key_auth_obj, + team_object=cast(LiteLLM_TeamTableCachedObj | None, team_object), + prisma_client=prisma_client, + user_api_key_cache=user_api_key_cache, + parent_otel_span=parent_otel_span, + proxy_logging_obj=proxy_logging_obj, + ) # common_checks identifies admin via user_object, not the token # (non_proxy_admin_allowed_routes_check). JWT admin shortcut and diff --git a/tests/test_litellm/proxy/auth/test_user_api_key_auth.py b/tests/test_litellm/proxy/auth/test_user_api_key_auth.py index 6cce6d0316b..03efbfa7185 100644 --- a/tests/test_litellm/proxy/auth/test_user_api_key_auth.py +++ b/tests/test_litellm/proxy/auth/test_user_api_key_auth.py @@ -23,6 +23,7 @@ from litellm.proxy._types import ( LiteLLM_JWTAuth, LiteLLM_BudgetTable, LiteLLM_EndUserTable, + LiteLLM_OrganizationTable, LiteLLM_UserTable, LitellmUserRoles, ProxyErrorTypes, @@ -31,7 +32,7 @@ from litellm.proxy._types import ( JWTRoutingOverride, ) from litellm.proxy.auth.handle_jwt import JWTHandler -from litellm.proxy.auth.auth_checks import get_key_object, _cache_key_object +from litellm.proxy.auth.auth_checks import OrganizationNotFoundError, get_key_object, _cache_key_object from litellm.proxy.auth.route_checks import RouteChecks from litellm.proxy.auth.user_api_key_auth import ( _check_key_model_budget_with_fallback, @@ -5293,6 +5294,107 @@ async def test_centralized_common_checks_backfills_org_id_from_team(key_org_id, setattr(_proxy_server_mod, k, v) +@pytest.mark.asyncio +@pytest.mark.parametrize( + "key_org_id,team_id,team_org_id,existing_alias,lookup_mode,expected_org_id,expected_alias", + [ + (None, "t1", "org-from-team", None, "success", "org-from-team", "acme-org"), + ("org-jwt", None, None, None, "success", "org-jwt", "acme-org"), + ("org-pinned", None, None, "preset", "success", "org-pinned", "preset"), + ("org-missing", None, None, None, "missing", "org-missing", None), + ], +) +async def test_centralized_common_checks_inherits_org_alias( + key_org_id, + team_id, + team_org_id, + existing_alias, + lookup_mode, + expected_org_id, + expected_alias, +): + import litellm.proxy.proxy_server as _proxy_server_mod + from fastapi import Request + from starlette.datastructures import URL + + from litellm.proxy._types import LiteLLM_TeamTableCachedObj + + token = UserAPIKeyAuth( + api_key="sk-test", + user_id="u", + team_id=team_id, + org_id=key_org_id, + organization_alias=existing_alias, + ) + request = Request(scope={"type": "http"}) + request._url = URL(url="/chat/completions") + + fetched_team = ( + LiteLLM_TeamTableCachedObj(team_id="t1", organization_id=team_org_id) if team_id is not None else None + ) + organization = LiteLLM_OrganizationTable( + organization_id=expected_org_id, + organization_alias="acme-org", + budget_id="budget-id", + models=[], + created_by="test", + updated_by="test", + ) + + attrs = _proxy_attrs_for_centralized_checks(user_custom_auth=None) + attrs["prisma_client"] = MagicMock() + originals = {a: getattr(_proxy_server_mod, a, None) for a in attrs} + try: + for k, v in attrs.items(): + setattr(_proxy_server_mod, k, v) + identity_seen_by_common_checks = [] + with ( + patch( + "litellm.proxy.auth.user_api_key_auth.get_team_object", + new_callable=AsyncMock, + return_value=fetched_team, + ) as mock_get_team_object, + patch( + "litellm.proxy.auth.user_api_key_auth.get_org_object", + new_callable=AsyncMock, + return_value=organization, + ) as mock_get_org_object, + patch( + "litellm.proxy.auth.user_api_key_auth.common_checks", + new_callable=AsyncMock, + side_effect=lambda **kw: identity_seen_by_common_checks.append( + (kw["valid_token"].org_id, kw["valid_token"].organization_alias) + ), + ) as mock_checks, + ): + if lookup_mode == "missing": + mock_get_org_object.side_effect = OrganizationNotFoundError("x") + + await _run_centralized_common_checks( + user_api_key_auth_obj=token, + request=request, + request_data={"model": "gpt-4o"}, + route="/chat/completions", + ) + + mock_checks.assert_awaited_once() + assert token.org_id == expected_org_id + assert token.organization_alias == expected_alias + assert identity_seen_by_common_checks == [(expected_org_id, expected_alias)] + if team_id is None: + mock_get_team_object.assert_not_awaited() + else: + mock_get_team_object.assert_awaited_once() + if existing_alias is not None: + mock_get_org_object.assert_not_awaited() + else: + mock_get_org_object.assert_awaited_once() + assert mock_get_org_object.await_args.kwargs["org_id"] == expected_org_id + finally: + for k, v in originals.items(): + setattr(_proxy_server_mod, k, v) + + @pytest.mark.asyncio async def test_cli_session_token_org_backfilled_from_team(monkeypatch): """LIT-4688 root cause: CLI session tokens (from /sso/cli/poll) are minted From e254377049ca6f7087693cff4b99b291c9ba6010 Mon Sep 17 00:00:00 2001 From: David Steele Date: Thu, 17 Sep 2026 07:07:57 +0100 Subject: [PATCH 02/83] fix(azure): drop tool_choice without tools DEVX-829 --- litellm/llms/azure/chat/gpt_transformation.py | 9 +- .../test_azure_chat_gpt_transformation.py | 123 ++++++++++++++++++ ...test_azure_chat_o_series_transformation.py | 3 +- 3 files changed, 133 insertions(+), 2 deletions(-) diff --git a/litellm/llms/azure/chat/gpt_transformation.py b/litellm/llms/azure/chat/gpt_transformation.py index 6d17a1359bc..0debbe4f74d 100644 --- a/litellm/llms/azure/chat/gpt_transformation.py +++ b/litellm/llms/azure/chat/gpt_transformation.py @@ -280,10 +280,17 @@ class AzureOpenAIConfig(BaseConfig): ordered_messages: Final = system_messages_first(messages) if litellm.openai_system_messages_first else messages stripped_messages: Final = drop_tool_reference_parts_from_tool_messages(ordered_messages) azure_messages: Final = convert_to_azure_openai_messages(hoist_images_from_tool_messages(stripped_messages)) + request_params: Final = { + key: value + for key, value in optional_params.items() + if key != "tool_choice" + or optional_params.get("tools") + or optional_params.get("functions") + } return { "model": model, "messages": azure_messages, - **optional_params, + **request_params, **sanitized_tools_update(optional_params), } diff --git a/tests/test_litellm/llms/azure/chat/test_azure_chat_gpt_transformation.py b/tests/test_litellm/llms/azure/chat/test_azure_chat_gpt_transformation.py index e8b98c696e1..92a8124d8a9 100644 --- a/tests/test_litellm/llms/azure/chat/test_azure_chat_gpt_transformation.py +++ b/tests/test_litellm/llms/azure/chat/test_azure_chat_gpt_transformation.py @@ -333,3 +333,126 @@ class TestAzureToolSchemaCombinatorFlattening: ) assert "tools" not in request assert request["temperature"] == 0.2 + + +@pytest.mark.parametrize("tool_choice", ["none", "auto"]) +def test_azure_drops_tool_choice_without_tools_or_functions(tool_choice: str) -> None: + optional_params = {"tool_choice": tool_choice, "temperature": 0.2} + request = AzureOpenAIConfig().transform_request( + model="gpt-4o", + messages=[{"role": "user", "content": "hi"}], + optional_params=optional_params, + litellm_params={"custom_llm_provider": "azure"}, + headers={}, + ) + + assert "tool_choice" not in request + assert request["temperature"] == 0.2 + assert optional_params["tool_choice"] == tool_choice + + +def test_azure_tools_empty_drops_tool_choice() -> None: + request = AzureOpenAIConfig().transform_request( + model="gpt-4o", + messages=[{"role": "user", "content": "hi"}], + optional_params={"tools": [], "tool_choice": "auto"}, + litellm_params={"custom_llm_provider": "azure"}, + headers={}, + ) + + assert request["tools"] == [] + assert "tool_choice" not in request + + +def test_azure_functions_empty_drops_tool_choice() -> None: + request = AzureOpenAIConfig().transform_request( + model="gpt-4o", + messages=[{"role": "user", "content": "hi"}], + optional_params={"functions": [], "tool_choice": "none"}, + litellm_params={"custom_llm_provider": "azure"}, + headers={}, + ) + + assert request["functions"] == [] + assert "tool_choice" not in request + + +def test_azure_preserves_tool_choice_with_tools() -> None: + tools = [{"type": "function", "function": {"name": "get_weather", "parameters": {}}}] + request = AzureOpenAIConfig().transform_request( + model="gpt-4o", + messages=[{"role": "user", "content": "hi"}], + optional_params={"tools": tools, "tool_choice": "auto"}, + litellm_params={"custom_llm_provider": "azure"}, + headers={}, + ) + + assert request["tools"] == tools + assert request["tool_choice"] == "auto" + + +def test_azure_preserves_tool_choice_with_legacy_functions() -> None: + functions = [{"name": "get_weather", "parameters": {}}] + request = AzureOpenAIConfig().transform_request( + model="gpt-4o", + messages=[{"role": "user", "content": "hi"}], + optional_params={"functions": functions, "tool_choice": "auto"}, + litellm_params={"custom_llm_provider": "azure"}, + headers={}, + ) + + assert request["functions"] == functions + assert request["tool_choice"] == "auto" + + +def test_azure_preserves_function_call_without_tools() -> None: + request = AzureOpenAIConfig().transform_request( + model="gpt-4o", + messages=[{"role": "user", "content": "hi"}], + optional_params={"function_call": "none", "tool_choice": "auto"}, + litellm_params={"custom_llm_provider": "azure"}, + headers={}, + ) + + assert request["function_call"] == "none" + assert "tool_choice" not in request + + +def test_azure_gpt5_drops_tool_choice_without_tools() -> None: + request = AzureOpenAIGPT5Config().transform_request( + model="gpt5_series/gpt-5.6-sol", + messages=[{"role": "user", "content": "hi"}], + optional_params={"tool_choice": "none"}, + litellm_params={"custom_llm_provider": "azure"}, + headers={}, + ) + + assert request["model"] == "gpt-5.6-sol" + assert "tool_choice" not in request + + +@pytest.mark.asyncio +async def test_azure_async_transform_drops_tool_choice_without_tools() -> None: + request = await AzureOpenAIConfig().async_transform_request( + model="gpt-4o", + messages=[{"role": "user", "content": "hi"}], + optional_params={"tool_choice": "none"}, + litellm_params={"custom_llm_provider": "azure"}, + headers={}, + ) + + assert "tool_choice" not in request + + +@pytest.mark.asyncio +async def test_azure_gpt5_async_transform_drops_tool_choice_without_tools() -> None: + request = await AzureOpenAIGPT5Config().async_transform_request( + model="gpt5_series/gpt-5.6-sol", + messages=[{"role": "user", "content": "hi"}], + optional_params={"tool_choice": "auto"}, + litellm_params={"custom_llm_provider": "azure"}, + headers={}, + ) + + assert request["model"] == "gpt-5.6-sol" + assert "tool_choice" not in request diff --git a/tests/test_litellm/llms/azure/chat/test_azure_chat_o_series_transformation.py b/tests/test_litellm/llms/azure/chat/test_azure_chat_o_series_transformation.py index 9db9ab971a0..57d60df3a11 100644 --- a/tests/test_litellm/llms/azure/chat/test_azure_chat_o_series_transformation.py +++ b/tests/test_litellm/llms/azure/chat/test_azure_chat_o_series_transformation.py @@ -14,7 +14,7 @@ async def test_azure_chat_o_series_transformation(): provider_config = AzureOpenAIO1Config() model = "o_series/web-interface-o1-mini" messages = [{"role": "user", "content": "Hello, how are you?"}] - optional_params = {} + optional_params = {"tool_choice": "none"} litellm_params = {} headers = {} @@ -23,6 +23,7 @@ async def test_azure_chat_o_series_transformation(): ) print(response) assert response["model"] == "web-interface-o1-mini" + assert "tool_choice" not in response def test_azure_o_series_transform_request_flattens_top_level_anyof(): From 48712f733a641f16b0b4fe60c221fd9f1c7076fa Mon Sep 17 00:00:00 2001 From: David Steele Date: Thu, 17 Sep 2026 07:30:06 +0100 Subject: [PATCH 03/83] style(azure): format request parameter filter DEVX-829 Co-Authored-By: Claude Code --- litellm/llms/azure/chat/gpt_transformation.py | 4 +--- 1 file changed, 1 insertion(+), 3 deletions(-) diff --git a/litellm/llms/azure/chat/gpt_transformation.py b/litellm/llms/azure/chat/gpt_transformation.py index 0debbe4f74d..7cb50ee5348 100644 --- a/litellm/llms/azure/chat/gpt_transformation.py +++ b/litellm/llms/azure/chat/gpt_transformation.py @@ -283,9 +283,7 @@ class AzureOpenAIConfig(BaseConfig): request_params: Final = { key: value for key, value in optional_params.items() - if key != "tool_choice" - or optional_params.get("tools") - or optional_params.get("functions") + if key != "tool_choice" or optional_params.get("tools") or optional_params.get("functions") } return { "model": model, From bd222bd8d9f6d083b8058c5fef3e998b4f92b3af Mon Sep 17 00:00:00 2001 From: David Steele Date: Thu, 17 Sep 2026 08:18:36 +0100 Subject: [PATCH 04/83] fix(azure): avoid mutable request mapping DEVX-829 Co-Authored-By: Claude Code --- litellm/llms/azure/chat/gpt_transformation.py | 12 +++++++----- 1 file changed, 7 insertions(+), 5 deletions(-) diff --git a/litellm/llms/azure/chat/gpt_transformation.py b/litellm/llms/azure/chat/gpt_transformation.py index 7cb50ee5348..424422612db 100644 --- a/litellm/llms/azure/chat/gpt_transformation.py +++ b/litellm/llms/azure/chat/gpt_transformation.py @@ -280,11 +280,13 @@ class AzureOpenAIConfig(BaseConfig): ordered_messages: Final = system_messages_first(messages) if litellm.openai_system_messages_first else messages stripped_messages: Final = drop_tool_reference_parts_from_tool_messages(ordered_messages) azure_messages: Final = convert_to_azure_openai_messages(hoist_images_from_tool_messages(stripped_messages)) - request_params: Final = { - key: value - for key, value in optional_params.items() - if key != "tool_choice" or optional_params.get("tools") or optional_params.get("functions") - } + request_params: Final = MappingProxyType( + { + key: value + for key, value in optional_params.items() + if key != "tool_choice" or optional_params.get("tools") or optional_params.get("functions") + } + ) return { "model": model, "messages": azure_messages, From 2fa115db2bac68ac90b0b900dc9eecb728c3bd4d Mon Sep 17 00:00:00 2001 From: Tin Chi Lo Date: Thu, 17 Sep 2026 12:53:15 -0400 Subject: [PATCH 05/83] feat(router): add maintained Fuse model and harness presets --- .../public_endpoints/public_endpoints.py | 9 + .../complexity_router/README.md | 45 +++++ .../complexity_router/fuse_presets.json | 100 +++++++++++ .../complexity_router/fuse_presets.py | 52 ++++++ .../complexity_router/llm_v2.py | 37 +++- pyproject.toml | 1 + .../public_endpoints/test_public_endpoints.py | 11 ++ .../router_strategy/test_fuse_presets.py | 43 +++++ .../router_strategy/test_llm_v2.py | 110 ++++++++++++ .../test_auto_router_model_naming.py | 49 ++++++ ...ecastClassifierConfig.integration.test.tsx | 163 +++++++++++++++++- .../add_model/ForecastClassifierConfig.tsx | 26 +-- .../add_model/FuseProfilePresets.tsx | 117 +++++++++++++ .../build_complexity_router_config.test.ts | 17 ++ .../forecast_classifier_config.test.ts | 65 ++++++- .../add_model/forecast_classifier_config.ts | 33 +++- ui/litellm-dashboard/src/lib/http/schema.d.ts | 82 ++++++++- 17 files changed, 917 insertions(+), 43 deletions(-) create mode 100644 litellm/router_strategy/complexity_router/fuse_presets.json create mode 100644 litellm/router_strategy/complexity_router/fuse_presets.py create mode 100644 tests/test_litellm/router_strategy/test_fuse_presets.py create mode 100644 ui/litellm-dashboard/src/components/add_model/FuseProfilePresets.tsx diff --git a/litellm/proxy/public_endpoints/public_endpoints.py b/litellm/proxy/public_endpoints/public_endpoints.py index 94a59828451..e395f56194f 100644 --- a/litellm/proxy/public_endpoints/public_endpoints.py +++ b/litellm/proxy/public_endpoints/public_endpoints.py @@ -23,6 +23,7 @@ from litellm.proxy._types import ( ) from litellm.proxy.utils import get_custom_url from litellm.repositories.table_repositories import ClaudeCodePluginRepository +from litellm.router_strategy.complexity_router.fuse_presets import FusePresetCatalog, get_fuse_presets from litellm.types.agents import AgentCard from litellm.types.mcp import MCPPublicServer from litellm.types.proxy.management_endpoints.model_management_endpoints import ( @@ -424,6 +425,14 @@ async def get_complexity_scorer_defaults() -> ComplexityScorerDefaults: ) +@router.get( + "/public/complexity_router/fuse_presets", + response_model=FusePresetCatalog, +) +async def get_public_fuse_presets() -> FusePresetCatalog: + return get_fuse_presets() + + @router.get( "/public/litellm_model_cost_map", tags=["public", "model management"], diff --git a/litellm/router_strategy/complexity_router/README.md b/litellm/router_strategy/complexity_router/README.md index 6505746bca1..d9159cea426 100644 --- a/litellm/router_strategy/complexity_router/README.md +++ b/litellm/router_strategy/complexity_router/README.md @@ -179,6 +179,51 @@ Configure capability forecasting through YAML or the model-management API. The dashboard preserves its classifier and calibration on an untouched save; it does not provide a capability-card editor +### Fuse v2 profile presets + +Fuse v2 accepts maintained model and runtime descriptions instead of requiring +custom prose for both solvers and the harness. Select profiles explicitly for +all deployments behind your configured model groups and their actual settings. +Group names do not select profiles automatically + +```yaml +complexity_router_config: + classifier_type: llm_v2 + classifier_llm_config: + model: your-judge-group + tiers: + SIMPLE: your-efficient-group + REASONING: your-capable-group + llm_v2_config: + efficient_profile_preset: claude-sonnet-5-v1 + capable_profile_preset: claude-fable-5-1-v1 + harness_preset: claude-code-v1 + max_quality_gap: 0.05 +``` + +`GET /public/complexity_router/fuse_presets` returns the catalog version, model +profiles, and runtime descriptions, including source URLs. The bundled catalog +is loaded once per process without network requests. Sources are citations only + +Each of `efficient_profile`, `capable_profile`, and `harness` requires either +nonblank custom text or its corresponding preset reference. Custom text wins +when both are supplied, but an unknown or wrong-kind preset is still rejected. +Explicit blank text is invalid even with a valid preset. Custom text remains +limited to 4000 characters + +Saved configurations retain preset references and explicit text separately. +Preset text is resolved when building the classifier prompt, not copied into +stored custom fields. Existing all-custom configurations keep the same prompt. +Versioned preset IDs identify immutable content: revised wording receives a new +ID, and older referenced entries must remain available + +The runtime presets do not imply a repository, runnable tests, network access, +additional tools, or a step, time, or spending budget. mini-SWE-agent describes +an agent interface, not a SWE-bench task. Model descriptions summarize provider +positioning without solve rates or guaranteed rankings. Wording is an evaluation +input, not a calibrated quality claim. Existing Fuse licensing, policy, +calibration, and prompt version are unchanged + ### Heuristic v2 Set `classifier_type: heuristic_v2` to classify with the bundled calibrated diff --git a/litellm/router_strategy/complexity_router/fuse_presets.json b/litellm/router_strategy/complexity_router/fuse_presets.json new file mode 100644 index 00000000000..4006366dc25 --- /dev/null +++ b/litellm/router_strategy/complexity_router/fuse_presets.json @@ -0,0 +1,100 @@ +{ + "version": "2026-09-17-v1", + "models": [ + { + "id": "gpt-6-astra-v1", + "label": "GPT-6 Astra", + "model": "gpt-6-astra", + "text": "OpenAI model for demanding end-to-end work, including reasoning, coding, research, and document tasks", + "sources": ["https://developers.openai.com/api/docs/models/gpt-6-astra"] + }, + { + "id": "gpt-5.6-sol-v1", + "label": "GPT-5.6 Sol", + "model": "gpt-5.6-sol", + "text": "OpenAI model for complex professional work, supporting reasoning and tool calling", + "sources": ["https://developers.openai.com/api/docs/models/gpt-5.6-sol"] + }, + { + "id": "gpt-5.6-luna-v1", + "label": "GPT-5.6 Luna", + "model": "gpt-5.6-luna", + "text": "OpenAI model for high-volume workloads, supporting reasoning and tool calling", + "sources": ["https://developers.openai.com/api/docs/models/gpt-5.6-luna"] + }, + { + "id": "gpt-5.6-terra-v1", + "label": "GPT-5.6 Terra", + "model": "gpt-5.6-terra", + "text": "OpenAI general-purpose model supporting reasoning, text and image input, and tool calling", + "sources": ["https://developers.openai.com/api/docs/models/gpt-5.6-terra"] + }, + { + "id": "claude-haiku-4-5-v1", + "label": "Claude Haiku 4.5", + "model": "claude-haiku-4-5", + "text": "Anthropic latency-focused model supporting text and image input, tool use, and extended thinking", + "sources": ["https://platform.claude.com/docs/en/models/haiku-4-5/overview"] + }, + { + "id": "claude-sonnet-5-v1", + "label": "Claude Sonnet 5", + "model": "claude-sonnet-5", + "text": "Anthropic model balancing speed and capability, with adaptive thinking and tool use", + "sources": ["https://platform.claude.com/docs/en/models/sonnet-5/overview"] + }, + { + "id": "claude-opus-5-v1", + "label": "Claude Opus 5", + "model": "claude-opus-5", + "text": "Anthropic model for complex agentic coding and enterprise work, with adaptive thinking", + "sources": ["https://platform.claude.com/docs/en/models/opus-5/overview"] + }, + { + "id": "claude-fable-5-v1", + "label": "Claude Fable 5", + "model": "claude-fable-5", + "text": "Anthropic model for demanding reasoning and long-running agent tasks, with always-on adaptive thinking", + "sources": ["https://platform.claude.com/docs/en/models/fable-5/introducing-claude-fable-5-and-claude-mythos-5"] + }, + { + "id": "claude-fable-5-1-v1", + "label": "Claude Fable 5.1", + "model": "claude-fable-5-1", + "text": "Anthropic model for demanding reasoning, long-running agentic coding, and multistep research, with always-on adaptive thinking", + "sources": ["https://platform.claude.com/docs/en/models/fable-5-1/overview"] + } + ], + "harnesses": [ + { + "id": "unspecified-v1", + "label": "Unspecified runtime", + "text": "Agent runtime is unspecified. Assess the task using the supplied context without assuming repository access, runnable tests, network access, additional tools, or a step, time, or spending budget", + "sources": ["https://code.claude.com/docs/en/how-claude-code-works", "https://mini-swe-agent.com/latest/faq/"] + }, + { + "id": "claude-code-v1", + "label": "Claude Code", + "text": "Claude Code supplies an agent loop with context management and configured tools. Available actions depend on the session's tools, permissions, and execution environment. The runtime name alone does not establish repository access, runnable tests, network access, additional tools, or a step, time, or spending budget", + "sources": ["https://code.claude.com/docs/en/how-claude-code-works"] + }, + { + "id": "codex-cli-v1", + "label": "Codex CLI", + "text": "Codex CLI supplies a terminal-based coding agent. File operations, command execution, and integrations depend on the session's tools, permissions, and sandbox. The runtime name alone does not establish repository access, runnable tests, network access, additional tools, or a step, time, or spending budget", + "sources": ["https://learn.chatgpt.com/docs/codex/cli", "https://learn.chatgpt.com/codex/permissions"] + }, + { + "id": "opencode-v1", + "label": "OpenCode", + "text": "OpenCode supplies a configurable agent runtime. Available actions depend on the selected agent, tools, permissions, and execution environment. The runtime name alone does not establish repository access, runnable tests, network access, additional tools, or a step, time, or spending budget", + "sources": ["https://opencode.ai/docs/agents/"] + }, + { + "id": "mini-swe-agent-v1", + "label": "mini-SWE-agent", + "text": "The standard mini-SWE-agent setup uses a bash-only action interface and separate command executions. Available commands and resources depend on its configured environment. The runtime name alone does not establish repository access, runnable tests, network access, additional tools, or a step, time, or spending budget", + "sources": ["https://mini-swe-agent.com/latest/faq/"] + } + ] +} diff --git a/litellm/router_strategy/complexity_router/fuse_presets.py b/litellm/router_strategy/complexity_router/fuse_presets.py new file mode 100644 index 00000000000..66a96ec5ad5 --- /dev/null +++ b/litellm/router_strategy/complexity_router/fuse_presets.py @@ -0,0 +1,52 @@ +from functools import lru_cache +from importlib.resources import files +from typing import Annotated, Final, Literal, TypeAlias + +from pydantic import BaseModel, ConfigDict, Field, StringConstraints + +ProfileText: TypeAlias = Annotated[str, StringConstraints(strip_whitespace=True, min_length=1, max_length=4000)] + + +class FuseModelPreset(BaseModel): + model_config = ConfigDict(extra="forbid", frozen=True) + + id: str + label: str + text: ProfileText + sources: tuple[str, ...] = Field(min_length=1) + model: str + + +class FuseHarnessPreset(BaseModel): + model_config = ConfigDict(extra="forbid", frozen=True) + + id: str + label: str + text: ProfileText + sources: tuple[str, ...] = Field(min_length=1) + + +class FusePresetCatalog(BaseModel): + model_config = ConfigDict(extra="forbid", frozen=True) + + version: str + models: tuple[FuseModelPreset, ...] + harnesses: tuple[FuseHarnessPreset, ...] + + +@lru_cache(maxsize=1) +def get_fuse_presets() -> FusePresetCatalog: + return FusePresetCatalog.model_validate_json( + files(__package__).joinpath("fuse_presets.json").read_text(encoding="utf-8") + ) + + +def resolve_fuse_profile(text: str | None, preset_id: str | None, kind: Literal["model", "harness"]) -> str | None: + if preset_id is None: + return text + catalog: Final = get_fuse_presets() + presets: Final = catalog.models if kind == "model" else catalog.harnesses + preset: Final = next((entry for entry in presets if entry.id == preset_id), None) + if preset is None: + return None + return text if text is not None else preset.text diff --git a/litellm/router_strategy/complexity_router/llm_v2.py b/litellm/router_strategy/complexity_router/llm_v2.py index 2f545a65aaa..18351237e65 100644 --- a/litellm/router_strategy/complexity_router/llm_v2.py +++ b/litellm/router_strategy/complexity_router/llm_v2.py @@ -7,15 +7,15 @@ from dataclasses import dataclass from sys import float_info from typing import Annotated, Final, Literal, TypeAlias -from pydantic import BaseModel, ConfigDict, Field, StrictFloat, StringConstraints, TypeAdapter +from pydantic import BaseModel, ConfigDict, Field, StrictFloat, StringConstraints, TypeAdapter, model_validator from typing_extensions import ReadOnly, TypedDict from litellm.llms.base_llm.base_utils import ( type_to_response_format_param, # pyright: ignore[reportUnknownVariableType] # legacy output validated below ) +from litellm.router_strategy.complexity_router.fuse_presets import ProfileText, resolve_fuse_profile ShortText: TypeAlias = Annotated[str, StringConstraints(strip_whitespace=True, min_length=1, max_length=512)] -ProfileText: TypeAlias = Annotated[str, StringConstraints(strip_whitespace=True, min_length=1, max_length=4000)] class _SolverProfile(TypedDict): @@ -139,20 +139,41 @@ class LLMV2Config(BaseModel): efficient_tier: str = "SIMPLE" capable_tier: str = "REASONING" - efficient_profile: ProfileText - capable_profile: ProfileText - harness: ProfileText + efficient_profile: ProfileText | None = None + capable_profile: ProfileText | None = None + harness: ProfileText | None = None + efficient_profile_preset: str | None = None + capable_profile_preset: str | None = None + harness_preset: str | None = None max_quality_gap: float = Field(ge=0.0, le=1.0, description="Maximum estimated success loss allowed for efficient.") max_output_tokens: int = Field(default=1024, ge=1) response_format: Literal["json_schema", "json_object"] = "json_schema" calibration: LLMV2Calibration | None = None + @model_validator(mode="after") + def validate_profiles(self) -> LLMV2Config: + self._profile_texts() + return self + + def _profile_texts(self) -> tuple[str, str, str]: + efficient: Final = resolve_fuse_profile(self.efficient_profile, self.efficient_profile_preset, "model") + capable: Final = resolve_fuse_profile(self.capable_profile, self.capable_profile_preset, "model") + harness: Final = resolve_fuse_profile(self.harness, self.harness_preset, "harness") + if efficient is None: + raise ValueError("efficient_profile requires text or a known efficient_profile_preset") + if capable is None: + raise ValueError("capable_profile requires text or a known capable_profile_preset") + if harness is None: + raise ValueError("harness requires text or a known harness_preset") + return efficient, capable, harness + def system_prompt(self, efficient_model: str, capable_model: str) -> str: + efficient, capable, harness = self._profile_texts() profiles: Final[_SolverProfiles] = { "prompt_version": LLM_V2_PROMPT_VERSION, - "harness": self.harness, - "efficient": {"model": efficient_model, "profile": self.efficient_profile}, - "capable": {"model": capable_model, "profile": self.capable_profile}, + "harness": harness, + "efficient": {"model": efficient_model, "profile": efficient}, + "capable": {"model": capable_model, "profile": capable}, } schema: Final = ( "\n\nResponse JSON schema:\n" + json.dumps(LLMV2Verdict.model_json_schema()) diff --git a/pyproject.toml b/pyproject.toml index 93ff55c4069..2d6d133cd0e 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -290,6 +290,7 @@ editable-profile = "dev" include = [ "litellm/proxy/_experimental/out/**", "litellm/router_strategy/complexity_router/artifacts/*.json", + "litellm/router_strategy/complexity_router/fuse_presets.json", "litellm/proxy/client/cli/commands/codex_base_instructions.md", ] exclude = [ diff --git a/tests/test_litellm/proxy/public_endpoints/test_public_endpoints.py b/tests/test_litellm/proxy/public_endpoints/test_public_endpoints.py index 0d82ed778f5..b830eb588a5 100644 --- a/tests/test_litellm/proxy/public_endpoints/test_public_endpoints.py +++ b/tests/test_litellm/proxy/public_endpoints/test_public_endpoints.py @@ -11,12 +11,23 @@ from fastapi.testclient import TestClient from litellm.proxy.auth.user_api_key_auth import user_api_key_auth from litellm.proxy.public_endpoints import router +from litellm.router_strategy.complexity_router.fuse_presets import get_fuse_presets from litellm.types.proxy.management_endpoints.model_management_endpoints import ( ModelGroupInfoProxy, ) from litellm.types.utils import LlmProviders +def test_fuse_presets_route_serves_the_shared_catalog_without_authentication() -> None: + app: Final = FastAPI() + app.include_router(router) + client: Final = TestClient(app) + response: Final = client.get("/public/complexity_router/fuse_presets") + assert response.status_code == 200 + assert response.json() == get_fuse_presets().model_dump(mode="json") + assert client.get("/public/complexity_router/fuse_presets").json() == response.json() + + def test_get_supported_providers_returns_enum_values(): app_instance = FastAPI() app_instance.include_router(router) diff --git a/tests/test_litellm/router_strategy/test_fuse_presets.py b/tests/test_litellm/router_strategy/test_fuse_presets.py new file mode 100644 index 00000000000..0b8d936383b --- /dev/null +++ b/tests/test_litellm/router_strategy/test_fuse_presets.py @@ -0,0 +1,43 @@ +import json +from importlib.resources import files +from typing import Final + +import pytest +from pydantic import ValidationError + +from litellm.router_strategy.complexity_router.fuse_presets import get_fuse_presets, resolve_fuse_profile + + +def test_catalog_is_loaded_once_and_preserves_bundled_content() -> None: + get_fuse_presets.cache_clear() + first: Final = get_fuse_presets() + second: Final = get_fuse_presets() + assert first is second + bundled: Final = json.loads( + files("litellm.router_strategy.complexity_router").joinpath("fuse_presets.json").read_text(encoding="utf-8") + ) + assert first.model_dump(mode="json") == bundled + entries: Final = (*first.models, *first.harnesses) + assert len({entry.id for entry in entries}) == len(entries) + assert len(first.models) == 9 + assert len(first.harnesses) == 5 + assert all(entry.sources and all(source.startswith("https://") for source in entry.sources) for entry in entries) + + +def test_every_catalog_entry_resolves_without_changing_custom_ownership() -> None: + catalog: Final = get_fuse_presets() + for entry in catalog.models: + assert resolve_fuse_profile(None, entry.id, "model") == entry.text + assert resolve_fuse_profile("Custom text", entry.id, "model") == "Custom text" + for entry in catalog.harnesses: + assert resolve_fuse_profile(None, entry.id, "harness") == entry.text + assert resolve_fuse_profile("Custom text", entry.id, "harness") == "Custom text" + assert resolve_fuse_profile("Custom text", None, "model") == "Custom text" + assert resolve_fuse_profile("Custom text", None, "harness") == "Custom text" + + +def test_cached_catalog_and_records_cannot_be_modified() -> None: + catalog: Final = get_fuse_presets() + for record, field in ((catalog, "version"), (catalog.models[0], "text"), (catalog.harnesses[0], "text")): + with pytest.raises(ValidationError, match="frozen"): + setattr(record, field, "Changed") diff --git a/tests/test_litellm/router_strategy/test_llm_v2.py b/tests/test_litellm/router_strategy/test_llm_v2.py index 5447c8b43ce..27d31cbe640 100644 --- a/tests/test_litellm/router_strategy/test_llm_v2.py +++ b/tests/test_litellm/router_strategy/test_llm_v2.py @@ -11,8 +11,10 @@ from litellm import ModelResponse, Router from litellm.caching.dual_cache import DualCache from litellm.router_strategy.complexity_router.complexity_router import ComplexityRouter from litellm.router_strategy.complexity_router.config import ComplexityRouterConfig, ComplexityTier +from litellm.router_strategy.complexity_router.fuse_presets import get_fuse_presets from litellm.router_strategy.complexity_router.llm_v2 import ( LLM_V2_PROMPT_VERSION, + LLM_V2_SYSTEM_PROMPT, LLMV2Calibration, LLMV2Config, LLMV2ProbabilityCalibration, @@ -174,6 +176,114 @@ def test_invalid_forecast_settings_are_rejected(overrides: dict[str, object]) -> LLMV2Config.model_validate({**base.model_dump(), **overrides}) +def _preset_config(**overrides: object) -> LLMV2Config: + catalog: Final = get_fuse_presets() + return LLMV2Config.model_validate( + { + "efficient_profile_preset": catalog.models[0].id, + "capable_profile_preset": catalog.models[-1].id, + "harness_preset": catalog.harnesses[-1].id, + "max_quality_gap": 0.05, + **overrides, + } + ) + + +def test_preset_roundtrip_keeps_references_without_materializing_text() -> None: + config: Final = _preset_config() + serialized: Final = config.model_dump(exclude_none=True) + assert serialized["efficient_profile_preset"] == config.efficient_profile_preset + assert serialized["capable_profile_preset"] == config.capable_profile_preset + assert serialized["harness_preset"] == config.harness_preset + assert not {"efficient_profile", "capable_profile", "harness"}.intersection(serialized) + assert LLMV2Config.model_validate(config.model_dump()) == config + assert LLMV2Config.model_validate_json(config.model_dump_json()) == config + + +@pytest.mark.parametrize("field", ("efficient_profile", "capable_profile", "harness")) +def test_preset_explicit_override_wins_and_survives_roundtrip(field: str) -> None: + config: Final = _preset_config(**{field: " Operator description "}) + roundtrip: Final = LLMV2Config.model_validate_json(config.model_dump_json()) + assert roundtrip.model_dump()[field] == "Operator description" + assert roundtrip.efficient_profile_preset == config.efficient_profile_preset + assert roundtrip.capable_profile_preset == config.capable_profile_preset + assert roundtrip.harness_preset == config.harness_preset + payload: Final = json.loads( + roundtrip.system_prompt("opaque-efficient", "opaque-capable").split("Configured solver profiles:\n")[1] + ) + if field == "harness": + assert payload["harness"] == "Operator description" + else: + assert payload[field.removesuffix("_profile")]["profile"] == "Operator description" + + +@pytest.mark.parametrize("field", ("efficient_profile", "capable_profile", "harness")) +@pytest.mark.parametrize("invalid", ("", " \n\t", "x" * 4001)) +def test_preset_does_not_bypass_supplied_text_bounds(field: str, invalid: str) -> None: + with pytest.raises(ValidationError, match=field): + _preset_config(**{field: invalid}) + + +@pytest.mark.parametrize("field", ("efficient_profile", "capable_profile", "harness")) +@pytest.mark.parametrize("override", (None, "Custom override")) +@pytest.mark.parametrize("invalid_id", ("missing-v1", "")) +def test_preset_unknown_reference_rejects_even_when_overridden( + field: str, override: str | None, invalid_id: str +) -> None: + with pytest.raises(ValidationError, match=f"{field}.*preset"): + _preset_config(**{field: override, f"{field}_preset": invalid_id}) + + +@pytest.mark.parametrize("field", ("efficient_profile", "capable_profile", "harness")) +def test_preset_missing_text_and_reference_rejects(field: str) -> None: + with pytest.raises(ValidationError, match=field): + _preset_config(**{f"{field}_preset": None}) + + +@pytest.mark.parametrize("field", ("efficient_profile", "capable_profile", "harness")) +def test_preset_reference_rejects_the_wrong_catalog_kind(field: str) -> None: + catalog: Final = get_fuse_presets() + wrong_id: Final = catalog.models[0].id if field == "harness" else catalog.harnesses[0].id + with pytest.raises(ValidationError, match=field): + _preset_config(**{f"{field}_preset": wrong_id}) + + +@pytest.mark.parametrize("mode", ("json_schema", "json_object")) +def test_custom_profile_prompt_bytes_are_unchanged(mode: str) -> None: + base: Final = _config().llm_v2_config + assert base is not None + config: Final = LLMV2Config.model_validate({**base.model_dump(), "response_format": mode}) + old_payload: Final = { + "prompt_version": LLM_V2_PROMPT_VERSION, + "harness": config.harness, + "efficient": {"model": "opaque-efficient", "profile": config.efficient_profile}, + "capable": {"model": "opaque-capable", "profile": config.capable_profile}, + } + schema: Final = ( + "\n\nResponse JSON schema:\n" + json.dumps(LLMV2Verdict.model_json_schema()) if mode == "json_object" else "" + ) + assert config.system_prompt("opaque-efficient", "opaque-capable") == ( + LLM_V2_SYSTEM_PROMPT + "\n\nConfigured solver profiles:\n" + json.dumps(old_payload) + schema + ) + + +@pytest.mark.asyncio +async def test_preset_router_passes_catalog_text_and_opaque_group_names_to_judge() -> None: + catalog: Final = get_fuse_presets() + config: Final = _config(llm_v2_config=_preset_config().model_dump()) + router, client = _router(_verdict().model_dump_json(), config) + outcome: Final = await router.aclassify("Complete the supplied task") + assert outcome.tier == ComplexityTier.SIMPLE + prompt: Final = client.acompletion.call_args.kwargs["messages"][0]["content"] + payload: Final = json.loads(prompt.split("Configured solver profiles:\n")[1]) + assert payload == { + "prompt_version": LLM_V2_PROMPT_VERSION, + "harness": catalog.harnesses[-1].text, + "efficient": {"model": "efficient", "profile": catalog.models[0].text}, + "capable": {"model": "capable", "profile": catalog.models[-1].text}, + } + + @pytest.mark.asyncio async def test_one_judge_fuses_whole_task_and_keeps_caller_text_out_of_system_prompt() -> None: router, client = _router(_verdict().model_dump_json()) diff --git a/tests/test_litellm/router_utils/test_auto_router_model_naming.py b/tests/test_litellm/router_utils/test_auto_router_model_naming.py index 3dcb8d5af94..7d59a0590f2 100644 --- a/tests/test_litellm/router_utils/test_auto_router_model_naming.py +++ b/tests/test_litellm/router_utils/test_auto_router_model_naming.py @@ -1,7 +1,10 @@ from collections.abc import Mapping +from typing import Final import pytest +from litellm.router_strategy.complexity_router.fuse_presets import get_fuse_presets + from litellm.router_utils.auto_router_model_naming import ( carries_complexity_router_settings, classify_strategy_router_model, @@ -171,6 +174,52 @@ def test_validate_accepts_loadable_complexity_config(complexity_router_config): assert validate_complexity_router_config_write(complexity_router_config=complexity_router_config) is None +def _fuse_write_config(profiles: Mapping[str, object]) -> Mapping[str, object]: + return { + "classifier_type": "llm_v2", + "classifier_llm_config": {"model": "judge"}, + "tiers": {"SIMPLE": ["opaque-efficient"], "REASONING": ["opaque-capable"]}, + "llm_v2_config": {"max_quality_gap": 0.05, **profiles}, + } + + +def test_fuse_write_accepts_presets_and_custom_text_with_the_same_entitlement() -> None: + catalog: Final = get_fuse_presets() + presets: Final = _fuse_write_config( + { + "efficient_profile_preset": catalog.models[0].id, + "capable_profile_preset": catalog.models[-1].id, + "harness_preset": catalog.harnesses[0].id, + } + ) + custom: Final = _fuse_write_config( + { + "efficient_profile": catalog.models[0].text, + "capable_profile": catalog.models[-1].text, + "harness": catalog.harnesses[0].text, + } + ) + assert validate_complexity_router_config_write(presets) is None + assert validate_complexity_router_config_write(custom) is None + assert claimed_capability(presets) is claimed_capability(custom) + assert claimed_capability(presets) is not None + + +@pytest.mark.parametrize("field", ("efficient_profile", "capable_profile", "harness")) +def test_fuse_write_rejects_unknown_preset_even_with_custom_text(field: str) -> None: + config: Final = _fuse_write_config( + { + "efficient_profile": "Custom efficient solver", + "capable_profile": "Custom capable solver", + "harness": "Custom runtime", + f"{field}_preset": "unknown-v1", + } + ) + violation: Final = validate_complexity_router_config_write(config) + assert violation is not None + assert f"{field}_preset" in violation + + def test_naming_check_ignores_the_config_entirely(): """The naming contract and the config's contents are separate questions with separate owners; a write may carry a config without naming a model, so neither can stand in for the other.""" diff --git a/ui/litellm-dashboard/src/components/add_model/ForecastClassifierConfig.integration.test.tsx b/ui/litellm-dashboard/src/components/add_model/ForecastClassifierConfig.integration.test.tsx index 4a574ac736d..f9b0edf9508 100644 --- a/ui/litellm-dashboard/src/components/add_model/ForecastClassifierConfig.integration.test.tsx +++ b/ui/litellm-dashboard/src/components/add_model/ForecastClassifierConfig.integration.test.tsx @@ -1,7 +1,7 @@ import React, { useState } from "react"; -import { describe, expect, it, vi } from "vitest"; +import { afterEach, beforeEach, describe, expect, it, vi } from "vitest"; import userEvent from "@testing-library/user-event"; -import { fireEvent, renderWithProviders, screen } from "../../../tests/test-utils"; +import { act, fireEvent, renderWithProviders, screen, testQueryClient, waitFor } from "../../../tests/test-utils"; import ClassificationMethodConfig from "./ClassificationMethodConfig"; import AutoRouterClassifierTabs from "./AutoRouterClassifierTabs"; import ForecastClassifierConfig from "./ForecastClassifierConfig"; @@ -37,6 +37,53 @@ const fuseInitial: ComplexityRouterConfigValue = { }, }; const options = ["judge", "efficient", "capable"].map((model) => ({ value: model, label: model })); +const catalog = { + version: "catalog-v1", + models: [ + { + id: "efficient-v1", + label: "Efficient preset", + text: "Maintained efficient profile", + sources: ["https://example.com/efficient"], + model: "efficient-model", + }, + { + id: "capable-v1", + label: "Capable preset", + text: "Maintained capable profile", + sources: ["https://example.com/capable"], + model: "capable-model", + }, + ], + harnesses: [ + { + id: "runtime-v1", + label: "Runtime preset", + text: "Maintained runtime profile", + sources: ["https://example.com/runtime"], + }, + ], +}; +const presetConfig = { + efficient_profile_preset: catalog.models[0].id, + capable_profile_preset: catalog.models[1].id, + harness_preset: catalog.harnesses[0].id, + max_quality_gap: 0.05, +}; +const presetInitial = { ...fuseInitial, llm_v2_config: presetConfig }; + +beforeEach(() => { + testQueryClient.clear(); + vi.stubGlobal( + "fetch", + vi.fn().mockImplementation(async () => Response.json(catalog)), + ); +}); + +afterEach(() => { + testQueryClient.clear(); + vi.unstubAllGlobals(); +}); function Form({ initialValue = initial }: { initialValue?: ComplexityRouterConfigValue }) { const [value, setValue] = useState(initialValue); @@ -72,6 +119,118 @@ function Form({ initialValue = initial }: { initialValue?: ComplexityRouterConfi } describe("forecast classifier form", () => { + it("selects all three maintained presets, previews provenance, and saves only references", async () => { + const user = userEvent.setup(); + renderWithProviders(
); + await user.click(screen.getByRole("combobox", { name: "Efficient solver profile preset" })); + await user.click(await screen.findByRole("option", { name: /^Efficient preset/ })); + await user.click(screen.getByRole("combobox", { name: "Capable solver profile preset" })); + await user.click(screen.getByRole("option", { name: /^Capable preset/ })); + await user.click(screen.getByRole("combobox", { name: "Harness and budget preset" })); + await user.click(screen.getByRole("option", { name: /^Runtime preset/ })); + expect(screen.getByLabelText("Efficient solver profile")).toHaveValue(catalog.models[0].text); + expect(screen.getByLabelText("Efficient solver profile")).toHaveAttribute("readonly"); + expect(screen.getByLabelText("Capable solver profile")).toHaveValue(catalog.models[1].text); + expect(screen.getByLabelText("Harness and budget")).toHaveValue(catalog.harnesses[0].text); + expect(screen.getAllByText(`Catalog version: ${catalog.version}`)).toHaveLength(3); + expect(screen.getByText(`Model: ${catalog.models[0].model}`)).toBeInTheDocument(); + expect(screen.getAllByRole("link", { name: "Source 1" }).map((link) => link.getAttribute("href"))).toEqual([ + catalog.models[0].sources[0], + catalog.models[1].sources[0], + catalog.harnesses[0].sources[0], + ]); + fireEvent.click(screen.getByRole("button", { name: "Save configuration" })); + expect(JSON.parse(screen.getByRole("status", { name: "Saved configuration" }).textContent!).llm_v2_config).toEqual( + presetConfig, + ); + expect(fetch).toHaveBeenCalledTimes(1); + expect(fetch).toHaveBeenCalledWith( + expect.objectContaining({ url: expect.stringMatching(/\/public\/complexity_router\/fuse_presets$/) }), + ); + }); + + it.each([undefined, null, "Explicit override"])( + "copies effective text to Custom and clears only that reference, override=%s", + async (override) => { + const user = userEvent.setup(); + renderWithProviders( + , + ); + const effectiveText = override ?? catalog.models[0].text; + await waitFor(() => expect(screen.getByLabelText("Efficient solver profile")).toHaveValue(effectiveText)); + await user.click(screen.getByRole("combobox", { name: "Efficient solver profile preset" })); + await user.click(screen.getByRole("option", { name: "Custom", exact: true })); + expect(screen.getByLabelText("Efficient solver profile")).not.toHaveAttribute("readonly"); + expect(screen.getByLabelText("Efficient solver profile")).toHaveValue(effectiveText); + fireEvent.change(screen.getByLabelText("Efficient solver profile"), { target: { value: "Custom budget" } }); + fireEvent.click(screen.getByRole("button", { name: "Save configuration" })); + const { efficient_profile_preset: _preset, ...rest } = presetConfig; + expect( + JSON.parse(screen.getByRole("status", { name: "Saved configuration" }).textContent!).llm_v2_config, + ).toEqual({ + ...rest, + efficient_profile: "Custom budget", + }); + }, + ); + + it.each([ + { ...fuseInitial.llm_v2_config!, efficient_profile: catalog.models[0].text }, + { + ...presetConfig, + efficient_profile: "Explicit override", + capable_profile: "Capable override", + harness: "Harness override", + }, + ])("keeps existing custom ownership and references on an unchanged save: %j", async (settings) => { + renderWithProviders(); + await waitFor(() => expect(screen.queryByText(/Loading profile presets/)).not.toBeInTheDocument()); + expect(screen.getByRole("combobox", { name: "Efficient solver profile preset" })).toHaveValue("Custom"); + expect(screen.getByLabelText("Efficient solver profile")).toHaveValue(settings.efficient_profile); + fireEvent.click(screen.getByRole("button", { name: "Save configuration" })); + expect(JSON.parse(screen.getByRole("status", { name: "Saved configuration" }).textContent!).llm_v2_config).toEqual( + settings, + ); + }); + + it.each([true, false])( + "keeps edits and stored IDs while the pending catalog settles, success=%s", + async (success) => { + let resolveCatalog: (response: Response) => void = () => {}; + vi.mocked(fetch).mockReturnValue( + new Promise((resolve) => { + resolveCatalog = resolve; + }), + ); + const settings = { ...presetConfig, efficient_profile: "Original override" }; + renderWithProviders(); + expect(screen.getByText(/Loading profile presets/)).toBeInTheDocument(); + fireEvent.change(screen.getByLabelText("Efficient solver profile"), { target: { value: "Typed while loading" } }); + await act(async () => + resolveCatalog(success ? Response.json(catalog) : Response.json({ error: "unavailable" }, { status: 503 })), + ); + if (success) await screen.findAllByText(`Catalog version: ${catalog.version}`); + else expect(await screen.findByText(/Profile presets could not be loaded/)).toBeInTheDocument(); + expect(screen.getByLabelText("Efficient solver profile")).toHaveValue("Typed while loading"); + fireEvent.click(screen.getByRole("button", { name: "Save configuration" })); + expect( + JSON.parse(screen.getByRole("status", { name: "Saved configuration" }).textContent!).llm_v2_config, + ).toEqual({ ...settings, efficient_profile: "Typed while loading" }); + }, + ); + + it("keeps unknown saved IDs visible with unavailable previews rather than replacing them", async () => { + const settings = { ...presetConfig, efficient_profile_preset: "unavailable-v8" }; + renderWithProviders(); + await screen.findAllByText(`Catalog version: ${catalog.version}`); + expect(screen.getByRole("combobox", { name: "Efficient solver profile preset" })).toHaveValue("unavailable-v8"); + expect(screen.getByText("Preset preview unavailable. The saved reference is preserved")).toBeInTheDocument(); + fireEvent.click(screen.getByRole("button", { name: "Save configuration" })); + expect(JSON.parse(screen.getByRole("status", { name: "Saved configuration" }).textContent!).llm_v2_config).toEqual( + settings, + ); + }); + it("switches a populated standard router to Capability without saving hidden pools or their overrides", () => { renderWithProviders( ) : ( <> - {(["efficient_profile", "capable_profile", "harness"] as const).map((field) => { - const label = { - efficient_profile: "Efficient solver profile", - capable_profile: "Capable solver profile", - harness: "Harness and budget", - }[field]; - return ( -
- -