diff --git a/litellm/model_prices_and_context_window_backup.json b/litellm/model_prices_and_context_window_backup.json index c565b6ecc4b..ed852bc490c 100644 --- a/litellm/model_prices_and_context_window_backup.json +++ b/litellm/model_prices_and_context_window_backup.json @@ -69158,5 +69158,26 @@ "supports_prompt_caching": true, "supports_reasoning": true, "supports_vision": true + }, + "typesafe/jev-1.13.0": { + "input_cost_per_token": 4.2e-08, + "litellm_provider": "typesafe", + "mode": "evaluation", + "output_cost_per_token": 0.0, + "source": "https://docs.typesafe.ai/models" + }, + "typesafe/jev-latest": { + "input_cost_per_token": 4.2e-08, + "litellm_provider": "typesafe", + "mode": "evaluation", + "output_cost_per_token": 0.0, + "source": "https://docs.typesafe.ai/models" + }, + "typesafe/jev-preview": { + "input_cost_per_token": 4.2e-08, + "litellm_provider": "typesafe", + "mode": "evaluation", + "output_cost_per_token": 0.0, + "source": "https://docs.typesafe.ai/models" } } diff --git a/litellm/proxy/_lazy_features.py b/litellm/proxy/_lazy_features.py index faf95397fa5..2a28ea3763f 100644 --- a/litellm/proxy/_lazy_features.py +++ b/litellm/proxy/_lazy_features.py @@ -208,6 +208,7 @@ LAZY_FEATURES: Final[tuple[LazyFeature, ...]] = ( "/nvidia_nim/", "/openai/", "/openai_passthrough/", + "/typesafe/", "/vertex-ai/", "/vertex_ai/", "/vllm/", diff --git a/litellm/proxy/_lazy_openapi_snapshot.json b/litellm/proxy/_lazy_openapi_snapshot.json index 74f38b3ca6d..5e1b7c85760 100644 --- a/litellm/proxy/_lazy_openapi_snapshot.json +++ b/litellm/proxy/_lazy_openapi_snapshot.json @@ -20373,6 +20373,96 @@ ] } }, + "/typesafe/{endpoint}": { + "get": { + "description": "[Docs](https://docs.litellm.ai/docs/pass_through/typesafe)", + "operationId": "typesafe_proxy_route_typesafe__endpoint__get", + "parameters": [ + { + "in": "path", + "name": "endpoint", + "required": true, + "schema": { + "title": "Endpoint", + "type": "string" + } + } + ], + "responses": { + "200": { + "content": { + "application/json": { + "schema": {} + } + }, + "description": "Successful Response" + }, + "422": { + "content": { + "application/json": { + "schema": { + "$ref": "#/components/schemas/HTTPValidationError" + } + } + }, + "description": "Validation Error" + } + }, + "security": [ + { + "APIKeyHeader": [] + } + ], + "summary": "Typesafe Proxy Route", + "tags": [ + "llm_passthrough" + ] + }, + "post": { + "description": "[Docs](https://docs.litellm.ai/docs/pass_through/typesafe)", + "operationId": "typesafe_proxy_route_typesafe__endpoint__post", + "parameters": [ + { + "in": "path", + "name": "endpoint", + "required": true, + "schema": { + "title": "Endpoint", + "type": "string" + } + } + ], + "responses": { + "200": { + "content": { + "application/json": { + "schema": {} + } + }, + "description": "Successful Response" + }, + "422": { + "content": { + "application/json": { + "schema": { + "$ref": "#/components/schemas/HTTPValidationError" + } + } + }, + "description": "Validation Error" + } + }, + "security": [ + { + "APIKeyHeader": [] + } + ], + "summary": "Typesafe Proxy Route", + "tags": [ + "llm_passthrough" + ] + } + }, "/vertex_ai/discovery/{endpoint}": { "delete": { "description": "Call any vertex discovery endpoint using the proxy.\n\nJust use `{PROXY_BASE_URL}/vertex_ai/discovery/{endpoint:path}`\n\nTarget url: `https://discoveryengine.googleapis.com`", diff --git a/litellm/proxy/_types.py b/litellm/proxy/_types.py index 680c63393e8..008cc8354b4 100644 --- a/litellm/proxy/_types.py +++ b/litellm/proxy/_types.py @@ -483,6 +483,7 @@ class LiteLLMRoutes(enum.Enum): "/eu.assemblyai", "/vllm", "/mistral", + "/typesafe", "/milvus", "/gigachat", "/watsonx", diff --git a/litellm/proxy/pass_through_endpoints/llm_passthrough_endpoints.py b/litellm/proxy/pass_through_endpoints/llm_passthrough_endpoints.py index b9b8cb3a22b..c75a3227366 100644 --- a/litellm/proxy/pass_through_endpoints/llm_passthrough_endpoints.py +++ b/litellm/proxy/pass_through_endpoints/llm_passthrough_endpoints.py @@ -525,6 +525,53 @@ async def mistral_proxy_route( return received_value +@router.api_route( + "/typesafe/{endpoint:path}", + methods=["GET", "POST"], + tags=["TypeSafe AI Pass-through", "pass-through"], +) +async def typesafe_proxy_route( + endpoint: str, + request: Request, + fastapi_response: Response, + user_api_key_dict: UserAPIKeyAuth = Depends(user_api_key_auth), +): + """[Docs](https://docs.litellm.ai/docs/pass_through/typesafe)""" + if request.method == "POST": + try: + request_body: Final = await _json_request_body(request) + except Exception as e: + raise HTTPException(status_code=400, detail=str(e)) + if not isinstance(request_body, dict): + raise HTTPException(status_code=400, detail="Request body must be a JSON object") + if "stream" in request_body: + raise HTTPException(status_code=400, detail="'stream' is not a TypeSafe request member") + + base_target_url: Final = get_secret_str("TYPESAFE_API_BASE") or "https://api.typesafe.ai" + encoded_endpoint: Final = httpx.URL(endpoint).path + normalized_endpoint: Final = encoded_endpoint if encoded_endpoint.startswith("/") else f"/{encoded_endpoint}" + base_url: Final = httpx.URL(base_target_url) + updated_url: Final = base_url.copy_with( + path=HttpPassThroughEndpointHelpers.join_base_and_endpoint_path(base_url, normalized_endpoint), + params=request.query_params, + ) + typesafe_api_key: Final = passthrough_endpoint_router.get_credentials( + custom_llm_provider="typesafe", + region_name=None, + ) + endpoint_func: Final = create_pass_through_route( + endpoint=endpoint, + target=str(updated_url), + custom_headers={ + "Authorization": f"Bearer {typesafe_api_key}", + "Content-Type": "application/json", + }, + custom_llm_provider="typesafe", + is_streaming_request=False, + ) + return await endpoint_func(request, fastapi_response, user_api_key_dict) + + @router.api_route( "/milvus/{endpoint:path}", methods=["GET", "POST", "PUT", "DELETE", "PATCH"], diff --git a/litellm/proxy/pass_through_endpoints/llm_provider_handlers/typesafe_passthrough_logging_handler.py b/litellm/proxy/pass_through_endpoints/llm_provider_handlers/typesafe_passthrough_logging_handler.py new file mode 100644 index 00000000000..b9ba265044d --- /dev/null +++ b/litellm/proxy/pass_through_endpoints/llm_provider_handlers/typesafe_passthrough_logging_handler.py @@ -0,0 +1,116 @@ +from collections.abc import Mapping +from datetime import datetime +from typing import Final, cast + +import httpx +from pydantic import BaseModel, TypeAdapter, ValidationError + +import litellm +from litellm.litellm_core_utils.litellm_logging import Logging as LiteLLMLoggingObj +from litellm.litellm_core_utils.litellm_logging import ( + get_standard_logging_object_payload, # pyright: ignore[reportUnknownVariableType] # legacy helper has an untyped signature +) +from litellm.proxy._types import PassThroughEndpointLoggingTypedDict +from litellm.types.utils import ModelResponse, StandardPassThroughResponseObject, Usage + + +class _TypeSafeUsage(BaseModel): + input_tokens: int = 0 + output_tokens: int = 0 + + +class _TypeSafeResponse(BaseModel): + model: str | None = None + usage: _TypeSafeUsage | None = None + + +_TYPESAFE_RESPONSE_ADAPTER: Final = TypeAdapter(_TypeSafeResponse) +_MODEL_COST_ENTRY_ADAPTER: Final = TypeAdapter(dict[str, object]) + + +def _parse_typesafe_response(response_body: Mapping[str, object]) -> _TypeSafeResponse: + try: + return _TYPESAFE_RESPONSE_ADAPTER.validate_python(response_body) + except ValidationError: + return _TypeSafeResponse() + + +def _get_model_cost_entry(model_key: str) -> Mapping[str, object] | None: + model_cost: Final[Mapping[str, object]] = cast(Mapping[str, object], litellm.model_cost) + entry: Final[object] = model_cost.get(model_key) + try: + return _MODEL_COST_ENTRY_ADAPTER.validate_python(entry) + except ValidationError: + return None + + +class TypeSafePassthroughLoggingHandler: + @staticmethod + def typesafe_passthrough_handler( + httpx_response: httpx.Response, + response_body: Mapping[str, object], + logging_obj: LiteLLMLoggingObj, + url_route: str, + result: str, + start_time: datetime, + end_time: datetime, + cache_hit: bool, + request_body: Mapping[str, object], + **kwargs: object, + ) -> PassThroughEndpointLoggingTypedDict: + response: Final = _parse_typesafe_response(response_body) + response_model: Final = response.model + request_model_value: Final = request_body.get("model") + request_model: Final = request_model_value if isinstance(request_model_value, str) else None + logged_model: Final = response_model or request_model or "jev-latest" + model_name: Final = f"typesafe/{logged_model}" + usage: Final = response.usage or _TypeSafeUsage() + input_tokens: Final = usage.input_tokens + output_tokens: Final = usage.output_tokens + candidate_model_keys: Final = tuple( + f"typesafe/{model}" for model in (response_model, request_model) if model is not None + ) + cost_entry: Final = next( + (entry for model_key in candidate_model_keys if (entry := _get_model_cost_entry(model_key)) is not None), + None, + ) + input_cost_per_token: Final = ( + cost_entry.get("input_cost_per_token", 0.0) if isinstance(cost_entry, Mapping) else 0.0 + ) + output_cost_per_token: Final = ( + cost_entry.get("output_cost_per_token", 0.0) if isinstance(cost_entry, Mapping) else 0.0 + ) + response_cost: Final = ( + input_tokens * float(input_cost_per_token) + output_tokens * float(output_cost_per_token) + if isinstance(input_cost_per_token, (int, float)) and isinstance(output_cost_per_token, (int, float)) + else 0.0 + ) + usage_object: Final = Usage( + prompt_tokens=input_tokens, + completion_tokens=output_tokens, + total_tokens=input_tokens + output_tokens, + ) + updated_kwargs: Final = { + **kwargs, + "model": model_name, + "custom_llm_provider": "typesafe", + "response_cost": response_cost, + "combined_usage_object": usage_object, + } + logging_obj.model_call_details.update( + model=model_name, + custom_llm_provider="typesafe", + response_cost=response_cost, + ) + standard_logging_object: Final = get_standard_logging_object_payload( + kwargs=updated_kwargs, + init_response_obj=ModelResponse(model=model_name, usage=usage_object), + start_time=start_time, + end_time=end_time, + logging_obj=logging_obj, + status="success", + ) + return { + "result": StandardPassThroughResponseObject(response=result), + "kwargs": {**updated_kwargs, "standard_logging_object": standard_logging_object}, + } diff --git a/litellm/proxy/pass_through_endpoints/success_handler.py b/litellm/proxy/pass_through_endpoints/success_handler.py index 76a471302f4..b4bfaf6ec9e 100644 --- a/litellm/proxy/pass_through_endpoints/success_handler.py +++ b/litellm/proxy/pass_through_endpoints/success_handler.py @@ -256,6 +256,25 @@ class PassThroughEndpointLogging: ) standard_logging_response_object = comprehend_medical_handler_result["result"] # rebind-ok: elif-chain kwargs = comprehend_medical_handler_result["kwargs"] # rebind-ok: elif-chain contract + elif self.is_typesafe_route(custom_llm_provider): + from .llm_provider_handlers.typesafe_passthrough_logging_handler import ( + TypeSafePassthroughLoggingHandler, + ) + + typesafe_handler_result: Final = TypeSafePassthroughLoggingHandler.typesafe_passthrough_handler( + httpx_response=httpx_response, + response_body=response_body if isinstance(response_body, dict) else {}, + logging_obj=logging_obj, + url_route=url_route, + result=result, + start_time=start_time, + end_time=end_time, + cache_hit=cache_hit, + request_body=request_body, + **kwargs, + ) + standard_logging_response_object = typesafe_handler_result["result"] + kwargs = typesafe_handler_result["kwargs"] elif self.is_vertex_ai_live_route(url_route): from .llm_provider_handlers.vertex_ai_live_passthrough_logging_handler import ( VertexAILivePassthroughLoggingHandler, @@ -389,6 +408,9 @@ class PassThroughEndpointLogging: def is_comprehend_medical_route(self, custom_llm_provider: str | None) -> bool: return custom_llm_provider == "comprehendmedical" + def is_typesafe_route(self, custom_llm_provider: str | None) -> bool: + return custom_llm_provider == "typesafe" + def is_langfuse_route(self, url_route: str): parsed_url: Final = urlparse(url_route) for route in self.TRACKED_LANGFUSE_ROUTES: diff --git a/litellm/types/utils.py b/litellm/types/utils.py index aaa16fd2d44..c732a617c77 100644 --- a/litellm/types/utils.py +++ b/litellm/types/utils.py @@ -348,6 +348,7 @@ class ModelInfoBase(ProviderSpecificModelInfo, total=False): "audio_transcription", "audio_speech", "responses", + "evaluation", "ocr", "realtime", ] diff --git a/model_prices_and_context_window.json b/model_prices_and_context_window.json index c565b6ecc4b..ed852bc490c 100644 --- a/model_prices_and_context_window.json +++ b/model_prices_and_context_window.json @@ -69158,5 +69158,26 @@ "supports_prompt_caching": true, "supports_reasoning": true, "supports_vision": true + }, + "typesafe/jev-1.13.0": { + "input_cost_per_token": 4.2e-08, + "litellm_provider": "typesafe", + "mode": "evaluation", + "output_cost_per_token": 0.0, + "source": "https://docs.typesafe.ai/models" + }, + "typesafe/jev-latest": { + "input_cost_per_token": 4.2e-08, + "litellm_provider": "typesafe", + "mode": "evaluation", + "output_cost_per_token": 0.0, + "source": "https://docs.typesafe.ai/models" + }, + "typesafe/jev-preview": { + "input_cost_per_token": 4.2e-08, + "litellm_provider": "typesafe", + "mode": "evaluation", + "output_cost_per_token": 0.0, + "source": "https://docs.typesafe.ai/models" } } diff --git a/tests/test_litellm/proxy/pass_through_endpoints/llm_provider_handlers/test_typesafe_passthrough_logging_handler.py b/tests/test_litellm/proxy/pass_through_endpoints/llm_provider_handlers/test_typesafe_passthrough_logging_handler.py new file mode 100644 index 00000000000..326b86654fe --- /dev/null +++ b/tests/test_litellm/proxy/pass_through_endpoints/llm_provider_handlers/test_typesafe_passthrough_logging_handler.py @@ -0,0 +1,127 @@ +from datetime import datetime +from unittest.mock import MagicMock + +import httpx +import pytest + +import litellm +from litellm.proxy.pass_through_endpoints.llm_provider_handlers.typesafe_passthrough_logging_handler import ( + TypeSafePassthroughLoggingHandler, +) +from litellm.proxy.pass_through_endpoints.success_handler import PassThroughEndpointLogging + + +@pytest.fixture(autouse=True) +def local_model_cost_map(monkeypatch: pytest.MonkeyPatch): + monkeypatch.setenv("LITELLM_LOCAL_MODEL_COST_MAP", "True") + monkeypatch.setattr(litellm, "model_cost", litellm.get_model_cost_map(url="")) + + +def _response() -> httpx.Response: + return httpx.Response( + 200, + request=httpx.Request("POST", "https://api.typesafe.ai/v1/systemone"), + json={"model": "jev-1.13.0"}, + ) + + +def _logging_obj() -> MagicMock: + logging_obj = MagicMock() + logging_obj.model_call_details = {} + return logging_obj + + +def _handler_result(response_body: dict, request_body: dict) -> dict: + return TypeSafePassthroughLoggingHandler.typesafe_passthrough_handler( + httpx_response=_response(), + response_body=response_body, + logging_obj=_logging_obj(), + url_route="https://api.typesafe.ai/v1/systemone", + result='{"answers": {}}', + start_time=datetime.now(), + end_time=datetime.now(), + cache_hit=False, + request_body=request_body, + ) + + +def test_uses_registry_pricing_and_standard_usage(): + logging_obj = _logging_obj() + model_key = "typesafe/jev-1.13.0" + model_cost = litellm.model_cost[model_key] + response = TypeSafePassthroughLoggingHandler.typesafe_passthrough_handler( + httpx_response=_response(), + response_body={"model": "jev-1.13.0", "usage": {"input_tokens": 312, "output_tokens": 48}}, + logging_obj=logging_obj, + url_route="https://api.typesafe.ai/v1/systemone", + result='{"answers": {}}', + start_time=datetime.now(), + end_time=datetime.now(), + cache_hit=False, + request_body={"model": "jev-latest"}, + ) + + expected_cost = 312 * model_cost["input_cost_per_token"] + 48 * model_cost["output_cost_per_token"] + assert response["kwargs"]["response_cost"] == pytest.approx(expected_cost) + assert response["kwargs"]["combined_usage_object"].prompt_tokens == 312 + assert response["kwargs"]["combined_usage_object"].completion_tokens == 48 + assert response["kwargs"]["combined_usage_object"].total_tokens == 360 + + +def test_falls_back_to_request_model_when_response_model_is_missing(): + result = _handler_result( + {"usage": {"input_tokens": 10, "output_tokens": 2}}, + {"model": "jev-latest"}, + ) + + model_cost = litellm.model_cost["typesafe/jev-latest"] + expected_cost = 10 * model_cost["input_cost_per_token"] + 2 * model_cost["output_cost_per_token"] + assert result["kwargs"]["model"] == "typesafe/jev-latest" + assert result["kwargs"]["response_cost"] == pytest.approx(expected_cost) + + +def test_missing_usage_is_zero_cost(): + result = _handler_result({"model": "jev-1.13.0"}, {"model": "jev-latest"}) + + assert result["kwargs"]["response_cost"] == 0.0 + + +def test_records_model_provider_and_cost_on_logging_details(): + logging_obj = _logging_obj() + result = TypeSafePassthroughLoggingHandler.typesafe_passthrough_handler( + httpx_response=_response(), + response_body={"model": "jev-1.13.0", "usage": {"input_tokens": 1, "output_tokens": 0}}, + logging_obj=logging_obj, + url_route="https://api.typesafe.ai/v1/systemone", + result="{}", + start_time=datetime.now(), + end_time=datetime.now(), + cache_hit=False, + request_body={"model": "jev-latest"}, + ) + + assert result["kwargs"]["model"] == "typesafe/jev-1.13.0" + assert result["kwargs"]["custom_llm_provider"] == "typesafe" + assert result["kwargs"]["response_cost"] > 0 + assert logging_obj.model_call_details["model"] == "typesafe/jev-1.13.0" + assert logging_obj.model_call_details["custom_llm_provider"] == "typesafe" + assert logging_obj.model_call_details["response_cost"] == result["kwargs"]["response_cost"] + + +def test_success_handler_dispatches_to_typesafe_handler(): + logging_obj = _logging_obj() + normalized = PassThroughEndpointLogging().normalize_llm_passthrough_logging_payload( + httpx_response=_response(), + response_body={"model": "jev-1.13.0", "usage": {"input_tokens": 1, "output_tokens": 0}}, + request_body={"model": "jev-latest"}, + logging_obj=logging_obj, + url_route="https://api.typesafe.ai/v1/systemone", + result="{}", + start_time=datetime.now(), + end_time=datetime.now(), + cache_hit=False, + custom_llm_provider="typesafe", + ) + + assert normalized["kwargs"]["custom_llm_provider"] == "typesafe" + assert normalized["kwargs"]["model"] == "typesafe/jev-1.13.0" diff --git a/tests/test_litellm/proxy/pass_through_endpoints/test_llm_pass_through_endpoints.py b/tests/test_litellm/proxy/pass_through_endpoints/test_llm_pass_through_endpoints.py index 6e82c90514d..13f4aae96b3 100644 --- a/tests/test_litellm/proxy/pass_through_endpoints/test_llm_pass_through_endpoints.py +++ b/tests/test_litellm/proxy/pass_through_endpoints/test_llm_pass_through_endpoints.py @@ -43,6 +43,7 @@ from litellm.proxy.pass_through_endpoints.llm_passthrough_endpoints import ( mistral_proxy_route, relay_nvidia_nim_request, openai_proxy_route, + typesafe_proxy_route, vertex_discovery_proxy_route, vertex_proxy_route, vllm_proxy_route, @@ -6136,3 +6137,61 @@ class TestAzureRelayDeploymentSegment: ) assert [call["model"] for call in captured] == ["gpt", "gpt"] + + +class TestTypeSafePassthroughRoute: + @staticmethod + def _request(body: object, query_params: Mapping[str, str] | None = None) -> MagicMock: + request = MagicMock(spec=Request) + request.method = "POST" + request.query_params = query_params or {} + request.json = AsyncMock(return_value=body) + return request + + @pytest.mark.asyncio + async def test_forwards_target_auth_headers_provider_and_query(self, monkeypatch): + monkeypatch.setenv("TYPESAFE_API_KEY", "typesafe-test-key") + monkeypatch.setenv("TYPESAFE_API_BASE", "https://typesafe.example/base") + endpoint_func = AsyncMock(return_value={"ok": True}) + create_route = Mock(return_value=endpoint_func) + monkeypatch.setattr( + "litellm.proxy.pass_through_endpoints.llm_passthrough_endpoints.create_pass_through_route", + create_route, + ) + + request = self._request({"state": "x"}, {"trace": "yes"}) + result = await typesafe_proxy_route( + endpoint="v1/systemone", + request=request, + fastapi_response=MagicMock(spec=Response), + user_api_key_dict=UserAPIKeyAuth(api_key="virtual-key"), + ) + + assert result == {"ok": True} + endpoint_func.assert_awaited_once() + create_route.assert_called_once_with( + endpoint="v1/systemone", + target="https://typesafe.example/base/v1/systemone?trace=yes", + custom_headers={ + "Authorization": "Bearer typesafe-test-key", + "Content-Type": "application/json", + }, + custom_llm_provider="typesafe", + is_streaming_request=False, + ) + assert request.json.await_count == 1 + + @pytest.mark.asyncio + async def test_rejects_stream_body(self, monkeypatch): + monkeypatch.setenv("TYPESAFE_API_KEY", "typesafe-test-key") + request = self._request({"stream": True}) + + with pytest.raises(HTTPException) as exc_info: + await typesafe_proxy_route( + endpoint="v1/systemone", + request=request, + fastapi_response=MagicMock(spec=Response), + user_api_key_dict=UserAPIKeyAuth(api_key="virtual-key"), + ) + + assert exc_info.value.status_code == 400 diff --git a/tests/test_litellm/test_typesafe_model_metadata.py b/tests/test_litellm/test_typesafe_model_metadata.py new file mode 100644 index 00000000000..a27180afbe9 --- /dev/null +++ b/tests/test_litellm/test_typesafe_model_metadata.py @@ -0,0 +1,17 @@ +import pytest + +import litellm + + +@pytest.fixture(autouse=True) +def local_model_cost_map(monkeypatch: pytest.MonkeyPatch): + monkeypatch.setenv("LITELLM_LOCAL_MODEL_COST_MAP", "True") + monkeypatch.setattr(litellm, "model_cost", litellm.get_model_cost_map(url="")) + + +def test_typesafe_models_share_pricing_and_provider_metadata(): + entries = [litellm.model_cost[f"typesafe/{model}"] for model in ("jev-1.13.0", "jev-latest", "jev-preview")] + + assert {entry["input_cost_per_token"] for entry in entries} == {entries[0]["input_cost_per_token"]} + assert {entry["output_cost_per_token"] for entry in entries} == {entries[0]["output_cost_per_token"]} + assert {entry["litellm_provider"] for entry in entries} == {"typesafe"}