diff --git a/basedpyright-code-budget.json b/basedpyright-code-budget.json index 551423c7707..a07b9352659 100644 --- a/basedpyright-code-budget.json +++ b/basedpyright-code-budget.json @@ -1,9 +1,9 @@ { "reportAny": { - "limit": 16171 + "limit": 14765 }, "reportArgumentType": { - "limit": 2224 + "limit": 2216 }, "reportAssignmentType": { "limit": 319 @@ -24,7 +24,7 @@ "limit": 19 }, "reportExplicitAny": { - "limit": 5199 + "limit": 4493 }, "reportFunctionMemberAccess": { "limit": 7 @@ -42,7 +42,7 @@ "limit": 12 }, "reportIndexIssue": { - "limit": 35 + "limit": 25 }, "reportInvalidTypeForm": { "limit": 34 @@ -54,10 +54,10 @@ "limit": 0 }, "reportMissingParameterType": { - "limit": 5611 + "limit": 5607 }, "reportMissingTypeArgument": { - "limit": 15348 + "limit": 15310 }, "reportMissingTypeStubs": { "limit": 40 @@ -105,13 +105,13 @@ "limit": 109 }, "reportUnknownMemberType": { - "limit": 38465 + "limit": 38368 }, "reportUnknownParameterType": { - "limit": 19663 + "limit": 19633 }, "reportUnknownVariableType": { - "limit": 30064 + "limit": 29908 }, "reportUnnecessaryCast": { "limit": 111 @@ -141,6 +141,6 @@ "limit": 543 }, "reportUnusedVariable": { - "limit": 139 + "limit": 137 } } diff --git a/enterprise/litellm_enterprise/proxy/common_utils/check_batch_cost.py b/enterprise/litellm_enterprise/proxy/common_utils/check_batch_cost.py index 3b09dc9272e..354a6ed2fd0 100644 --- a/enterprise/litellm_enterprise/proxy/common_utils/check_batch_cost.py +++ b/enterprise/litellm_enterprise/proxy/common_utils/check_batch_cost.py @@ -5,7 +5,7 @@ Polls LiteLLM_ManagedObjectTable to check if the batch job is complete, and if t from dataclasses import replace as dataclasses_replace from datetime import datetime, timedelta, timezone from types import MappingProxyType -from typing import TYPE_CHECKING, Any, Dict, Final, List, Literal, Optional, Tuple, cast +from typing import TYPE_CHECKING, Final, List, Literal, Optional, Tuple, cast from litellm._logging import verbose_proxy_logger from litellm._uuid import uuid @@ -87,7 +87,7 @@ class CheckBatchCost: return self.batch_processed_support_confirmed = True - async def _get_user_info(self, batch_id: str, user_id: Optional[str]) -> Dict[str, Any]: + async def _get_user_info(self, batch_id: str, user_id: Optional[str]) -> dict[str, str | None]: """ Look up user email and key alias by user_id for enriching the S3 callback metadata. Returns a dict with user_api_key_user_email and user_api_key_alias (both may be None). @@ -97,8 +97,10 @@ class CheckBatchCost: if not user_id: return {} try: - user_row = await self.prisma_client.db.litellm_usertable.find_unique( - where={"user_id": user_id} + user_row: prisma_models.LiteLLM_UserTable | None = ( + await self.prisma_client.db.litellm_usertable.find_unique( + where={"user_id": user_id} + ) ) if user_row is None: return {} @@ -115,8 +117,10 @@ class CheckBatchCost: if not api_key: return None try: - key_row = await self.prisma_client.db.litellm_verificationtoken.find_unique( - where={"token": api_key} + key_row: prisma_models.LiteLLM_VerificationToken | None = ( + await self.prisma_client.db.litellm_verificationtoken.find_unique( + where={"token": api_key} + ) ) return getattr(key_row, "key_alias", None) if key_row is not None else None except Exception as e: @@ -128,8 +132,10 @@ class CheckBatchCost: if not team_id: return None try: - team_row = await self.prisma_client.db.litellm_teamtable.find_unique( - where={"team_id": team_id} + team_row: prisma_models.LiteLLM_TeamTable | None = ( + await self.prisma_client.db.litellm_teamtable.find_unique( + where={"team_id": team_id} + ) ) return getattr(team_row, "team_alias", None) if team_row is not None else None except Exception as e: @@ -138,7 +144,7 @@ class CheckBatchCost: async def _build_creator_attribution_metadata( self, job: "LiteLLM_ManagedObjectTable", batch_id: str - ) -> Dict[str, Any]: + ) -> dict[str, object]: """ Rebuild the spend-tracking metadata for the key, team, and tags that created the batch so the batch-cost spend log is attributed the same way a non-batch request @@ -152,7 +158,7 @@ class CheckBatchCost: team_id = getattr(job, "team_id", None) request_tags = getattr(job, "request_tags", None) - metadata: Dict[str, Any] = { + metadata: dict[str, object] = { "user_api_key_user_id": job.created_by, "user_api_key": api_key, "user_api_key_team_id": team_id, diff --git a/enterprise/litellm_enterprise/proxy/hooks/managed_files.py b/enterprise/litellm_enterprise/proxy/hooks/managed_files.py index 570b306d6df..5cfcf6129f0 100644 --- a/enterprise/litellm_enterprise/proxy/hooks/managed_files.py +++ b/enterprise/litellm_enterprise/proxy/hooks/managed_files.py @@ -182,6 +182,10 @@ class _ManagedObjectTableActions(Protocol): async def update_many(self, where: Mapping[str, object], data: Mapping[str, object]) -> int: ... +class _SchedulerWithJobLookup(Protocol): + def get_job(self, job_id: str) -> object: ... + + class _CursorPageArgs(TypedDict, total=False): cursor: Mapping[str, str] skip: int @@ -853,7 +857,7 @@ class _PROXY_LiteLLMManagedFiles(CustomLogger, BaseFileEndpoints): file_ids.append(file_id) return file_ids - def get_file_ids_from_responses_input(self, input: Union[str, List[Dict[str, Any]]]) -> List[str]: + def get_file_ids_from_responses_input(self, input: Union[str, List[Dict[str, object]]]) -> List[str]: """ Gets file ids from responses API input. @@ -878,7 +882,7 @@ class _PROXY_LiteLLMManagedFiles(CustomLogger, BaseFileEndpoints): # Check for direct input_file type if item.get("type") == "input_file": file_id = item.get("file_id") - if file_id: + if isinstance(file_id, str) and file_id: file_ids.append(file_id) # Check for input_file in content array @@ -887,7 +891,7 @@ class _PROXY_LiteLLMManagedFiles(CustomLogger, BaseFileEndpoints): for content_item in content: if isinstance(content_item, dict) and content_item.get("type") == "input_file": file_id = content_item.get("file_id") - if file_id: + if isinstance(file_id, str) and file_id: file_ids.append(file_id) return file_ids @@ -1227,7 +1231,7 @@ class _PROXY_LiteLLMManagedFiles(CustomLogger, BaseFileEndpoints): # Handle both output_file_id and error_file_id for file_attr in ["output_file_id", "error_file_id"]: - file_id_value = getattr(response, file_attr, None) + file_id_value: str | None = getattr(response, file_attr, None) if file_id_value and model_id: decoded_output_file_id = _is_base64_encoded_unified_file_id(file_id_value) if decoded_output_file_id and "llm_output_file_id," in decoded_output_file_id: @@ -1496,7 +1500,7 @@ class _PROXY_LiteLLMManagedFiles(CustomLogger, BaseFileEndpoints): import litellm.proxy.proxy_server as proxy_server_module # Check if the scheduler has the batch cost checking job registered - scheduler = getattr(proxy_server_module, "scheduler", None) + scheduler: Final[_SchedulerWithJobLookup | None] = getattr(proxy_server_module, "scheduler", None) if scheduler is None: return False @@ -1542,7 +1546,7 @@ class _PROXY_LiteLLMManagedFiles(CustomLogger, BaseFileEndpoints): ) MAX_MATCHES_TO_RETURN = 10 - batches = await self.prisma_client.db.litellm_managedobjecttable.find_many( + batches = await _managed_object_table(self.prisma_client).find_many( where={ "file_purpose": "batch", "batch_processed": False, @@ -1552,11 +1556,14 @@ class _PROXY_LiteLLMManagedFiles(CustomLogger, BaseFileEndpoints): order={"created_at": "desc"}, ) - referencing_batches = [] + referencing_batches: Final[list[dict[str, object]]] = [] for batch in batches: try: # Parse the batch file_object to check for file references - batch_data = json.loads(batch.file_object) if isinstance(batch.file_object, str) else batch.file_object + decoded_file_object = _decode_json_blob(batch.file_object) + batch_data: Mapping[str, object] = ( + decoded_file_object if isinstance(decoded_file_object, Mapping) else {} + ) # Extract file IDs from batch # Batches typically reference the unified file ID in input_file_id diff --git a/enterprise/pyproject.toml b/enterprise/pyproject.toml index cac98b69793..8360c0a077d 100644 --- a/enterprise/pyproject.toml +++ b/enterprise/pyproject.toml @@ -1,6 +1,6 @@ [project] name = "litellm-enterprise" -version = "0.1.62" +version = "0.1.63" description = "Package for LiteLLM Enterprise features" readme = "README.md" requires-python = ">=3.9" @@ -26,7 +26,7 @@ required-version = ">=0.10.9" module-root = "" [tool.commitizen] -version = "0.1.62" +version = "0.1.63" version_files = [ "pyproject.toml:^version", "../pyproject.toml:litellm-enterprise==", diff --git a/helm/litellm/templates/backend/deployment.yaml b/helm/litellm/templates/backend/deployment.yaml index 5c0431fc0bd..0db2f0b3d43 100644 --- a/helm/litellm/templates/backend/deployment.yaml +++ b/helm/litellm/templates/backend/deployment.yaml @@ -7,6 +7,10 @@ metadata: {{- include "litellm.commonLabels" . | nindent 4 }} app.kubernetes.io/component: backend spec: + {{- with .Values.backend.strategy }} + strategy: + {{- toYaml . | nindent 4 }} + {{- end }} selector: matchLabels: {{- include "litellm.backend.selectorLabels" . | nindent 6 }} diff --git a/helm/litellm/templates/gateway/deployment.yaml b/helm/litellm/templates/gateway/deployment.yaml index d5363d0096e..5030ba2c9dc 100644 --- a/helm/litellm/templates/gateway/deployment.yaml +++ b/helm/litellm/templates/gateway/deployment.yaml @@ -7,6 +7,10 @@ metadata: {{- include "litellm.commonLabels" . | nindent 4 }} app.kubernetes.io/component: gateway spec: + {{- with .Values.gateway.strategy }} + strategy: + {{- toYaml . | nindent 4 }} + {{- end }} selector: matchLabels: {{- include "litellm.gateway.selectorLabels" . | nindent 6 }} diff --git a/helm/litellm/templates/migrations-job.yaml b/helm/litellm/templates/migrations-job.yaml index 9cd8397f794..8d33081e72f 100644 --- a/helm/litellm/templates/migrations-job.yaml +++ b/helm/litellm/templates/migrations-job.yaml @@ -7,6 +7,8 @@ # # Running this pre-upgrade closes the window where new application pods would # otherwise serve traffic against the previous release's unmigrated schema. +# Argo CD users can swap the Helm hook for a PreSync hook through +# `migrationJob.hooks`, which re-runs the Job on every sync. apiVersion: batch/v1 kind: Job metadata: @@ -14,10 +16,18 @@ metadata: labels: {{- include "litellm.commonLabels" . | nindent 4 }} app.kubernetes.io/component: migrations + {{- if or .Values.migrationJob.hooks.helm.enabled .Values.migrationJob.hooks.argocd.enabled }} annotations: + {{- if .Values.migrationJob.hooks.helm.enabled }} helm.sh/hook: pre-install,pre-upgrade helm.sh/hook-delete-policy: before-hook-creation - helm.sh/hook-weight: "0" + helm.sh/hook-weight: {{ .Values.migrationJob.hooks.helm.weight | default "0" | quote }} + {{- end }} + {{- if .Values.migrationJob.hooks.argocd.enabled }} + argocd.argoproj.io/hook: PreSync + argocd.argoproj.io/hook-delete-policy: BeforeHookCreation + {{- end }} + {{- end }} spec: backoffLimit: {{ .Values.migrationJob.backoffLimit }} ttlSecondsAfterFinished: {{ .Values.migrationJob.ttlSecondsAfterFinished }} diff --git a/helm/litellm/templates/ui/deployment.yaml b/helm/litellm/templates/ui/deployment.yaml index 91d6de39ea6..b992b347bad 100644 --- a/helm/litellm/templates/ui/deployment.yaml +++ b/helm/litellm/templates/ui/deployment.yaml @@ -7,6 +7,10 @@ metadata: {{- include "litellm.commonLabels" . | nindent 4 }} app.kubernetes.io/component: ui spec: + {{- with .Values.ui.strategy }} + strategy: + {{- toYaml . | nindent 4 }} + {{- end }} selector: matchLabels: {{- include "litellm.ui.selectorLabels" . | nindent 6 }} diff --git a/helm/litellm/tests/migration_job_hooks_tests.yaml b/helm/litellm/tests/migration_job_hooks_tests.yaml new file mode 100644 index 00000000000..650d2700429 --- /dev/null +++ b/helm/litellm/tests/migration_job_hooks_tests.yaml @@ -0,0 +1,63 @@ +suite: test migrations Job hook annotations +templates: + - migrations-job.yaml +values: + - ./values/required.yaml +tests: + - it: runs as a Helm pre-install / pre-upgrade hook by default + asserts: + - equal: + path: metadata.annotations["helm.sh/hook"] + value: pre-install,pre-upgrade + - equal: + path: metadata.annotations["helm.sh/hook-delete-policy"] + value: before-hook-creation + - equal: + path: metadata.annotations["helm.sh/hook-weight"] + value: "0" + - notExists: + path: metadata.annotations["argocd.argoproj.io/hook"] + + - it: adds the Argo CD PreSync hook when asked + set: + migrationJob.hooks.argocd.enabled: true + asserts: + - equal: + path: metadata.annotations["argocd.argoproj.io/hook"] + value: PreSync + - equal: + path: metadata.annotations["argocd.argoproj.io/hook-delete-policy"] + value: BeforeHookCreation + + - it: drops the Helm hook so Argo CD owns the Job + set: + migrationJob.hooks.argocd.enabled: true + migrationJob.hooks.helm.enabled: false + asserts: + - equal: + path: metadata.annotations["argocd.argoproj.io/hook"] + value: PreSync + - notExists: + path: metadata.annotations["helm.sh/hook"] + - notExists: + path: metadata.annotations["helm.sh/hook-delete-policy"] + - notExists: + path: metadata.annotations["helm.sh/hook-weight"] + + - it: renders an ordinary Job when both hooks are disabled + set: + migrationJob.hooks.helm.enabled: false + asserts: + - notExists: + path: metadata.annotations + - equal: + path: kind + value: Job + + - it: honours a custom Helm hook weight + set: + migrationJob.hooks.helm.weight: "-5" + asserts: + - equal: + path: metadata.annotations["helm.sh/hook-weight"] + value: "-5" diff --git a/helm/litellm/tests/rollout_strategy_tests.yaml b/helm/litellm/tests/rollout_strategy_tests.yaml new file mode 100644 index 00000000000..b12e2073c7c --- /dev/null +++ b/helm/litellm/tests/rollout_strategy_tests.yaml @@ -0,0 +1,66 @@ +suite: test rolling update strategy on the component deployments +templates: + - gateway/deployment.yaml + - gateway/configmap.yaml + - backend/deployment.yaml + - ui/deployment.yaml +values: + - ./values/required.yaml +tests: + - it: leaves the strategy to Kubernetes defaults when unset + asserts: + - notExists: + path: spec.strategy + + - it: renders the configured strategy on each deployment + set: + gateway.strategy: + type: RollingUpdate + rollingUpdate: + maxUnavailable: 0 + maxSurge: 1 + backend.strategy: + type: RollingUpdate + rollingUpdate: + maxUnavailable: "25%" + maxSurge: 2 + ui.strategy: + type: Recreate + asserts: + - equal: + path: spec.strategy + value: + type: RollingUpdate + rollingUpdate: + maxUnavailable: 0 + maxSurge: 1 + template: gateway/deployment.yaml + - equal: + path: spec.strategy + value: + type: RollingUpdate + rollingUpdate: + maxUnavailable: 25% + maxSurge: 2 + template: backend/deployment.yaml + - equal: + path: spec.strategy + value: + type: Recreate + template: ui/deployment.yaml + + - it: keeps a component on the cluster default when only another one sets a strategy + set: + gateway.strategy: + type: Recreate + asserts: + - equal: + path: spec.strategy.type + value: Recreate + template: gateway/deployment.yaml + - notExists: + path: spec.strategy + template: backend/deployment.yaml + - notExists: + path: spec.strategy + template: ui/deployment.yaml diff --git a/helm/litellm/values.yaml b/helm/litellm/values.yaml index d0c80fd6f6f..378c3b7a618 100644 --- a/helm/litellm/values.yaml +++ b/helm/litellm/values.yaml @@ -75,6 +75,22 @@ serviceAccounts: # generate` — the migration engine doesn't need the generated client. migrationJob: enabled: true + # Which controller is responsible for running the Job. + # + # `helm.enabled` renders the Helm pre-install / pre-upgrade hook, so the Job + # runs whenever `helm upgrade` sees a change to apply. `argocd.enabled` + # renders an Argo CD PreSync hook instead, which runs the Job on every sync + # even when the rendered manifests are unchanged: the way to re-run + # migrations on demand from a GitOps pipeline. Turning the Helm hook off + # while the Argo CD hook is on leaves the Job out of Helm's own upgrade + # path, which is what Argo CD users want since Argo, not Helm, applies the + # manifests. + hooks: + helm: + enabled: true + weight: "0" + argocd: + enabled: false backoffLimit: 4 ttlSecondsAfterFinished: 120 # Wall-clock budget for the whole Job, shared across every `backoffLimit` @@ -257,6 +273,15 @@ gateway: initialDelaySeconds: 5 periodSeconds: 10 timeoutSeconds: 10 + # Rolling update tuning for the gateway Deployment. Empty by default, so + # Kubernetes applies its own RollingUpdate defaults (25% maxSurge / + # 25% maxUnavailable). Example, for a surge-only rollout behind a load + # balancer that must never lose capacity: + # type: RollingUpdate + # rollingUpdate: + # maxUnavailable: 0 + # maxSurge: 1 + strategy: {} # Optional startupProbe. Empty by default, so existing installs are unchanged # and liveness/readiness apply from container start. Set it to gate # liveness/readiness until a slow cold start finishes — a high failureThreshold @@ -369,6 +394,8 @@ backend: initialDelaySeconds: 5 periodSeconds: 10 timeoutSeconds: 10 + # Same shape as gateway.strategy. + strategy: {} # Optional startupProbe; same shape as gateway.startupProbe. Empty by default. startupProbe: {} hpa: @@ -433,6 +460,8 @@ ui: httpGet: { path: /, port: http } initialDelaySeconds: 2 periodSeconds: 10 + # Same shape as gateway.strategy. + strategy: {} # Optional startupProbe; same shape as gateway.startupProbe. Empty by default. startupProbe: {} hpa: diff --git a/litellm-proxy-extras/pyproject.toml b/litellm-proxy-extras/pyproject.toml index d5741d479bf..0944f99ad54 100644 --- a/litellm-proxy-extras/pyproject.toml +++ b/litellm-proxy-extras/pyproject.toml @@ -1,6 +1,6 @@ [project] name = "litellm-proxy-extras" -version = "0.4.91" +version = "0.4.92" description = "Additional files for the LiteLLM Proxy. Reduces the size of the main litellm package." readme = "README.md" requires-python = ">=3.9" @@ -26,7 +26,7 @@ required-version = ">=0.10.9" module-root = "" [tool.commitizen] -version = "0.4.91" +version = "0.4.92" version_files = [ "pyproject.toml:^version", "../pyproject.toml:litellm-proxy-extras==", diff --git a/litellm/caching/redis_cache.py b/litellm/caching/redis_cache.py index f1c80eaacbe..2b04a075114 100644 --- a/litellm/caching/redis_cache.py +++ b/litellm/caching/redis_cache.py @@ -18,7 +18,7 @@ import time from collections.abc import Awaitable, Callable, Sequence from contextvars import ContextVar from datetime import timedelta -from typing import TYPE_CHECKING, Any, Final, TypeVar, cast +from typing import TYPE_CHECKING, Any, Final, Protocol, TypeVar, cast import litellm from litellm._logging import print_verbose, verbose_logger @@ -58,6 +58,26 @@ else: Span = Any +class _AsyncRedisCommands(Protocol): + """Async redis commands this cache issues. + + redis-py's type stubs omit these methods on RedisCluster, so the union returned by + init_async_client() is untyped at every call site without this protocol. + """ + + def ping(self) -> Awaitable[bool]: ... + + def delete(self, *names: str) -> Awaitable[int]: ... + + def ttl(self, name: str) -> Awaitable[int]: ... + + def rpush(self, name: str, *values: str | bytes | float) -> Awaitable[int]: ... + + def lpop(self, name: str, count: int | None = None) -> Awaitable[object]: ... + + def pipeline(self, transaction: bool = True) -> "Pipeline[bytes]": ... + + def _get_call_stack_info(num_frames: int = 2) -> str: """ Get the function names from the previous 1-2 functions in the call stack. @@ -429,6 +449,9 @@ class RedisCache(BaseCache): self.redis_async_client = redis_async_client return redis_async_client + def _async_commands(self) -> _AsyncRedisCommands: + return self.init_async_client() + def check_and_fix_namespace(self, key: str) -> str: """ Make sure each key starts with the given namespace @@ -1055,19 +1078,17 @@ class RedisCache(BaseCache): await self.async_set_cache_pipeline(self.redis_batch_writing_buffer) self.redis_batch_writing_buffer = [] - def _get_cache_logic(self, cached_response: Any): + def _get_cache_logic(self, cached_response: bytes | str | None): """ Common 'get_cache_logic' across sync + async redis client implementations """ if cached_response is None: - return cached_response - # cached_response is in `b{} convert it to ModelResponse - cached_response = cached_response.decode("utf-8") # Convert bytes to string + return None + decoded: Final = cached_response.decode("utf-8") if isinstance(cached_response, bytes) else cached_response try: - cached_response = json.loads(cached_response) # Convert string to dictionary + return json.loads(decoded) except Exception: - cached_response = ast.literal_eval(cached_response) - return cached_response + return ast.literal_eval(decoded) def get_cache(self, key, parent_otel_span: Span | None = None, **kwargs): try: @@ -1314,8 +1335,7 @@ class RedisCache(BaseCache): raise e async def ping(self) -> bool: - # typed as Any, redis python lib has incomplete type stubs for RedisCluster and does not include `ping` - _redis_client: Final[Any] = self.init_async_client() + _redis_client: Final = self._async_commands() start_time: Final = time.time() print_verbose("Pinging Async Redis Cache") try: @@ -1349,8 +1369,7 @@ class RedisCache(BaseCache): @_redis_circuit_breaker_guard async def delete_cache_keys(self, keys): - # typed as Any, redis python lib has incomplete type stubs for RedisCluster and does not include `delete` - _redis_client: Final[Any] = self.init_async_client() + _redis_client: Final = self._async_commands() keys = [self.check_and_fix_namespace(key=key) for key in keys] # keys is a list, unpack it so it gets passed as individual elements to delete await _redis_client.delete(*keys) @@ -1415,8 +1434,7 @@ class RedisCache(BaseCache): @_redis_circuit_breaker_guard async def async_delete_cache(self, key: str): - # typed as Any, redis python lib has incomplete type stubs for RedisCluster and does not include `delete` - _redis_client: Final[Any] = self.init_async_client() + _redis_client: Final = self._async_commands() key = self.check_and_fix_namespace(key=key) # keys is str return await _redis_client.delete(key) @@ -1523,8 +1541,7 @@ class RedisCache(BaseCache): Redis ref: https://redis.io/docs/latest/commands/ttl/ """ try: - # typed as Any, redis python lib has incomplete type stubs for RedisCluster and does not include `ttl` - _redis_client: Final[Any] = self.init_async_client() + _redis_client: Final = self._async_commands() key = self.check_and_fix_namespace(key=key) ttl: Final = await _redis_client.ttl(key) if ttl <= -1: # -1 means the key does not exist, -2 key does not exist @@ -1554,7 +1571,7 @@ class RedisCache(BaseCache): Returns: int: The length of the list after the push operation """ - _redis_client: Final[Any] = self.init_async_client() + _redis_client: Final = self._async_commands() key = self.check_and_fix_namespace(key=key) start_time: Final = time.time() try: @@ -1621,7 +1638,7 @@ class RedisCache(BaseCache): if len(rpush_list) == 0: return [] - _redis_client: Final[Any] = self.init_async_client() + _redis_client: Final = self._async_commands() start_time: Final = time.time() try: @@ -1678,7 +1695,7 @@ class RedisCache(BaseCache): parent_otel_span: Span | None = None, **kwargs, ) -> Any | list[Any]: - _redis_client: Final[Any] = self.init_async_client() + _redis_client: Final = self._async_commands() key = self.check_and_fix_namespace(key=key) start_time: Final = time.time() print_verbose(f"LPOP from Redis list: key: {key}, count: {count}") @@ -1810,7 +1827,7 @@ class RedisCache(BaseCache): if len(lpop_list) == 0: return [] - _redis_client: Final[Any] = self.init_async_client() + _redis_client: Final = self._async_commands() start_time: Final = time.time() try: diff --git a/litellm/completion_extras/litellm_responses_transformation/transformation.py b/litellm/completion_extras/litellm_responses_transformation/transformation.py index 85fb0bc8dc6..7368de1e968 100644 --- a/litellm/completion_extras/litellm_responses_transformation/transformation.py +++ b/litellm/completion_extras/litellm_responses_transformation/transformation.py @@ -212,7 +212,8 @@ def _tool_call_dict_from_output_item(item: Mapping[str, Any], index: int) -> _Ch LiteLLMCompletionResponsesConfig, ) - is_custom: Final = item.get("type") == "custom_tool_call" + item_type: Final[object] = item.get("type") + is_custom: Final = item_type == "custom_tool_call" arguments: Final = (item.get("input") if is_custom else item.get("arguments")) or "" name: Final = item.get("name") or ("custom_tool" if is_custom else "") function_chunk: Final = ChatCompletionToolCallFunctionChunk(name=name, arguments=arguments) @@ -222,7 +223,7 @@ def _tool_call_dict_from_output_item(item: Mapping[str, Any], index: int) -> _Ch function=function_chunk, index=index, ) - raw_provider_fields: Final = item.get("provider_specific_fields") + raw_provider_fields: Final[object] = item.get("provider_specific_fields") if isinstance(raw_provider_fields, dict): provider_specific_fields = raw_provider_fields elif raw_provider_fields and hasattr(raw_provider_fields, "__dict__"): @@ -507,7 +508,7 @@ class LiteLLMResponsesTransformationHandler(CompletionTransformationBridge): def _merge_responses_api_request_into_request_data( self, - request_data: dict[str, Any], + request_data: dict[str, object], responses_api_request: "ResponsesAPIOptionalRequestParams", instructions: str | None, ) -> None: diff --git a/litellm/cost_calculator.py b/litellm/cost_calculator.py index 3adc1c25dfd..13005d7975e 100644 --- a/litellm/cost_calculator.py +++ b/litellm/cost_calculator.py @@ -1910,12 +1910,15 @@ def ocr_cost( if credits is not None and cost_per_credit is not None: return cost_per_credit * credits, 0.0 - ocr_cost_per_page: float | None = None - if model_info is not None: - ocr_cost_per_page = model_info.get("ocr_cost_per_page") + ocr_cost_per_page: Final = model_info.get("ocr_cost_per_page") if model_info is not None else None + annotation_cost_per_page: Final = model_info.get("annotation_cost_per_page") if model_info is not None else None + annotation_rate: Final = annotation_cost_per_page if annotation_cost_per_page is not None else ocr_cost_per_page pages_processed: Final = response.usage_info.pages_processed - if pages_processed is None: + annotation_pages: Final = response.usage_info.pages_processed_annotation or 0 + has_billable_annotation_pages: Final = annotation_rate is not None and annotation_pages > 0 + + if pages_processed is None and not has_billable_annotation_pages: if cost_per_credit is not None or ocr_cost_per_page is None: # Surface missing usage data instead of silently under-reporting # cost. The previous behavior raised ValueError; we now return 0.0 @@ -1931,7 +1934,7 @@ def ocr_cost( return 0.0, 0.0 raise ValueError("OCR response pages_processed is None") - if ocr_cost_per_page is None: + if ocr_cost_per_page is None and not has_billable_annotation_pages: # No per-page pricing configured. Either the model is on credit-based # pricing (and credits weren't returned, so the credit branch above did # not match) or the model has no OCR pricing entry at all. Surface a @@ -1947,8 +1950,9 @@ def ocr_cost( ) return 0.0, 0.0 - total_ocr_processing_cost: Final[float] = ocr_cost_per_page * pages_processed - return total_ocr_processing_cost, 0.0 + ocr_pages_cost: Final = (ocr_cost_per_page or 0.0) * (pages_processed or 0) + annotation_pages_cost: Final = (annotation_rate or 0.0) * annotation_pages + return ocr_pages_cost + annotation_pages_cost, 0.0 def vector_store_search_cost( @@ -2268,6 +2272,10 @@ def batch_cost_calculator( return total_prompt_cost, total_completion_cost +def _attribute_value(obj: object, name: str) -> object: + return getattr(obj, name) + + def _summable_prompt_token_fields(prompt_tokens_details: BaseModel) -> list[str]: field_names: Final = list(type(prompt_tokens_details).model_fields) if getattr(prompt_tokens_details, "cache_write_tokens", None) is None: @@ -2293,7 +2301,7 @@ class BaseTokenUsageProcessor: for usage in usage_objects: # Handle direct attributes by checking what exists in the model for attr in dir(usage): - if not attr.startswith("_") and not callable(getattr(usage, attr)): + if not attr.startswith("_") and not callable(_attribute_value(usage, attr)): current_val = getattr(combined, attr, 0) new_val = getattr(usage, attr, 0) if ( @@ -2313,7 +2321,7 @@ class BaseTokenUsageProcessor: if ( hasattr(usage.prompt_tokens_details, attr) and not attr.startswith("_") - and not callable(getattr(usage.prompt_tokens_details, attr)) + and not callable(_attribute_value(usage.prompt_tokens_details, attr)) ): current_val = getattr(combined.prompt_tokens_details, attr, 0) or 0 new_val = getattr(usage.prompt_tokens_details, attr, 0) or 0 @@ -2332,7 +2340,9 @@ class BaseTokenUsageProcessor: # Check what keys exist in the model's completion_tokens_details # Access model_fields on the class, not the instance, to avoid Pydantic 2.11+ deprecation warnings for attr in type(usage.completion_tokens_details).model_fields: - if not attr.startswith("_") and not callable(getattr(usage.completion_tokens_details, attr)): + if not attr.startswith("_") and not callable( + _attribute_value(usage.completion_tokens_details, attr) + ): current_val = getattr(combined.completion_tokens_details, attr, 0) or 0 new_val = getattr(usage.completion_tokens_details, attr, 0) or 0 if isinstance(new_val, (int, float)): diff --git a/litellm/google_genai/adapters/transformation.py b/litellm/google_genai/adapters/transformation.py index 8ea19deef4c..6a698bb6018 100644 --- a/litellm/google_genai/adapters/transformation.py +++ b/litellm/google_genai/adapters/transformation.py @@ -722,7 +722,7 @@ class GoogleGenAIAdapter: ) for tool_call in tool_calls: - if not hasattr(tool_call, "function"): + if not hasattr(tool_call, "function") or isinstance(tool_call, ChatCompletionDeltaCustomToolCall): continue # 3. Use `index` as the primary key for accumulation diff --git a/litellm/integrations/arize/arize_phoenix_prompt_manager.py b/litellm/integrations/arize/arize_phoenix_prompt_manager.py index 71f4902bbe5..0c9e868c146 100644 --- a/litellm/integrations/arize/arize_phoenix_prompt_manager.py +++ b/litellm/integrations/arize/arize_phoenix_prompt_manager.py @@ -3,10 +3,12 @@ Arize Phoenix prompt manager that integrates with LiteLLM's prompt management sy Fetches prompt versions from Arize Phoenix and provides workspace-based access control. """ -from typing import Any, Final +from collections.abc import Mapping, Sequence +from typing import Any, Final, cast from jinja2 import DictLoader, select_autoescape from jinja2.sandbox import ImmutableSandboxedEnvironment +from typing_extensions import ReadOnly, TypedDict from litellm.integrations.custom_prompt_management import CustomPromptManagement from litellm.integrations.prompt_management_base import ( @@ -20,6 +22,31 @@ from litellm.types.utils import StandardCallbackDynamicParams from .arize_phoenix_client import ArizePhoenixClient +class ArizePhoenixContentPart(TypedDict, total=False): + type: ReadOnly[str] + text: ReadOnly[str] + + +class ArizePhoenixTemplateMessage(TypedDict, total=False): + role: ReadOnly[str] + content: ReadOnly[Sequence[ArizePhoenixContentPart]] + + +class ArizePhoenixTemplateBody(TypedDict, total=False): + messages: ReadOnly[Sequence[ArizePhoenixTemplateMessage]] + + +class ArizePhoenixPromptMetadata(TypedDict): + model_name: ReadOnly[str | None] + model_provider: ReadOnly[str | None] + description: ReadOnly[str] + template_type: ReadOnly[str | None] + template_format: ReadOnly[str] + invocation_parameters: ReadOnly[Mapping[str, Mapping[str, object]]] + temperature: ReadOnly[float | None] + max_tokens: ReadOnly[int | None] + + class ArizePhoenixPromptTemplate: """ Represents a prompt template loaded from Arize Phoenix. @@ -28,10 +55,10 @@ class ArizePhoenixPromptTemplate: def __init__( self, template_id: str, - messages: list[dict[str, Any]], - metadata: dict[str, Any], + messages: Sequence[ArizePhoenixTemplateMessage], + metadata: ArizePhoenixPromptMetadata, model: str | None = None, - ): + ) -> None: self.template_id = template_id self.messages = messages self.metadata = metadata @@ -43,7 +70,7 @@ class ArizePhoenixPromptTemplate: self.description = metadata.get("description", "") self.template_format = metadata.get("template_format", "MUSTACHE") - def __repr__(self): + def __repr__(self) -> str: return f"ArizePhoenixPromptTemplate(id='{self.template_id}', model='{self.model}')" @@ -109,7 +136,7 @@ class ArizePhoenixTemplateManager: def _parse_prompt_data(self, data: dict[str, Any], prompt_version_id: str) -> ArizePhoenixPromptTemplate: """Parse Arize Phoenix prompt data and extract messages and metadata.""" - template_data: Final = data.get("template", {}) + template_data: Final[ArizePhoenixTemplateBody] = data.get("template", {}) messages: Final = template_data.get("messages", []) # Extract invocation parameters @@ -129,7 +156,7 @@ class ArizePhoenixTemplateManager: break # Build metadata dictionary - metadata: Final = { + metadata: Final[ArizePhoenixPromptMetadata] = { "model_name": data.get("model_name"), "model_provider": data.get("model_provider"), "description": data.get("description", ""), @@ -146,7 +173,9 @@ class ArizePhoenixTemplateManager: metadata=metadata, ) - def render_template(self, template_id: str, variables: dict[str, Any] | None = None) -> list[AllMessageValues]: + def render_template( + self, template_id: str, variables: Mapping[str, object] | None = None + ) -> list[AllMessageValues]: """Render a template with the given variables and return formatted messages.""" if template_id not in self.prompts: raise ValueError(f"Template '{template_id}' not found") @@ -174,7 +203,9 @@ class ArizePhoenixTemplateManager: # Combine rendered content final_content = " ".join(rendered_content_parts) - rendered_messages.append({"role": role, "content": final_content}) + rendered_messages.append( + cast("AllMessageValues", {"role": role, "content": final_content}) # cast-ok: Phoenix roles are OpenAI + ) return rendered_messages @@ -243,8 +274,8 @@ class ArizePhoenixPromptManager(CustomPromptManagement): def get_prompt_template( self, prompt_id: str, - prompt_variables: dict[str, Any] | None = None, - ) -> tuple[list[AllMessageValues], dict[str, Any]]: + prompt_variables: Mapping[str, object] | None = None, + ) -> tuple[list[AllMessageValues], dict[str, object]]: """ Get a prompt template and render it with variables. @@ -263,7 +294,7 @@ class ArizePhoenixPromptManager(CustomPromptManagement): rendered_messages: Final = self.prompt_manager.render_template(prompt_id, prompt_variables or {}) # Extract metadata - metadata: Final = { + metadata: Final[dict[str, object]] = { "model": template.model, "temperature": template.temperature, "max_tokens": template.max_tokens, @@ -271,7 +302,7 @@ class ArizePhoenixPromptManager(CustomPromptManagement): # Add additional invocation parameters invocation_params: Final = template.invocation_parameters - provider_params = {} + provider_params: Mapping[str, object] = {} if "openai" in invocation_params: provider_params = invocation_params["openai"] @@ -289,12 +320,12 @@ class ArizePhoenixPromptManager(CustomPromptManagement): self, user_id: str | None, messages: list[AllMessageValues], - function_call: dict[str, Any] | str | None = None, - litellm_params: dict[str, Any] | None = None, + function_call: dict[str, object] | str | None = None, + litellm_params: dict[str, object] | None = None, prompt_id: str | None = None, - prompt_variables: dict[str, Any] | None = None, + prompt_variables: dict[str, object] | None = None, **kwargs, - ) -> tuple[list[AllMessageValues], dict[str, Any] | None]: + ) -> tuple[list[AllMessageValues], dict[str, object] | None]: """ Pre-call hook that processes the prompt template before making the LLM call. """ @@ -335,9 +366,9 @@ class ArizePhoenixPromptManager(CustomPromptManagement): except Exception as e: # Log error but don't fail the call - import litellm + from litellm._logging import verbose_proxy_logger - litellm._logging.verbose_proxy_logger.error("Error in Arize Phoenix prompt pre_call_hook: %s", e) + verbose_proxy_logger.error("Error in Arize Phoenix prompt pre_call_hook: %s", e) return messages, litellm_params def get_available_prompts(self) -> list[str]: @@ -393,7 +424,8 @@ class ArizePhoenixPromptManager(CustomPromptManagement): rendered_messages, prompt_metadata = self.get_prompt_template(prompt_id, prompt_variables) # Extract model from metadata (if specified) - template_model: Final = prompt_metadata.get("model") + raw_template_model: Final = prompt_metadata.get("model") + template_model: Final = raw_template_model if isinstance(raw_template_model, str) else None # Extract optional parameters from metadata optional_params: Final = {} diff --git a/litellm/integrations/custom_logger.py b/litellm/integrations/custom_logger.py index f177076d8fe..8f03e08f02d 100644 --- a/litellm/integrations/custom_logger.py +++ b/litellm/integrations/custom_logger.py @@ -31,6 +31,9 @@ if TYPE_CHECKING: from litellm.caching.caching import DualCache from litellm.litellm_core_utils.litellm_logging import Logging as LiteLLMLoggingObj + from litellm.llms.base_llm.anthropic_messages.transformation import ( + BaseAnthropicMessagesConfig, + ) from litellm.proxy._types import UserAPIKeyAuth from litellm.types.mcp import ( MCPPostCallResponseObject, @@ -39,7 +42,7 @@ if TYPE_CHECKING: ) from litellm.types.router import PreRoutingHookResponse - Span = _Span | Any + Span = _Span else: Span = Any LiteLLMLoggingObj = Any @@ -268,7 +271,9 @@ class CustomLogger: # https://docs.litellm.ai/docs/observability/custom_callbac ) -> list[dict]: return healthy_deployments - async def async_pre_call_deployment_hook(self, kwargs: dict[str, Any], call_type: CallTypes | None) -> dict | None: + async def async_pre_call_deployment_hook( + self, kwargs: dict[str, object], call_type: CallTypes | None + ) -> dict | None: """ Allow modifying the request just before it's sent to the deployment. @@ -344,9 +349,9 @@ class CustomLogger: # https://docs.litellm.ai/docs/observability/custom_callbac async def async_post_call_streaming_deployment_hook( self, request_data: dict, - response_chunk: Any, + response_chunk: object, call_type: CallTypes | None, - ) -> Any | None: + ) -> object | None: """ Allow modifying streaming chunks just before they're returned to the user. @@ -378,7 +383,7 @@ class CustomLogger: # https://docs.litellm.ai/docs/observability/custom_callbac """ def translate_completion_output_params_streaming( - self, completion_stream: Any + self, completion_stream: object ) -> AdapterCompletionStreamWrapper | None: """ Translates the streaming chunk, from the OpenAI format to the custom format. @@ -418,9 +423,9 @@ class CustomLogger: # https://docs.litellm.ai/docs/observability/custom_callbac self, data: dict, user_api_key_dict: UserAPIKeyAuth, - response: Any, + response: object, request_headers: dict[str, str] | None = None, - litellm_call_info: dict[str, Any] | None = None, + litellm_call_info: dict[str, object] | None = None, ) -> dict[str, str] | None: """ Called after an LLM API call (success or failure) to allow injecting custom HTTP response headers. @@ -471,11 +476,11 @@ class CustomLogger: # https://docs.litellm.ai/docs/observability/custom_callbac ) -> Any: pass - async def async_logging_hook(self, kwargs: dict, result: Any, call_type: str) -> tuple[dict, Any]: + async def async_logging_hook(self, kwargs: dict, result: object, call_type: str) -> tuple[dict, object]: """For masking logged request/response. Return a modified version of the request/result.""" return kwargs, result - def logging_hook(self, kwargs: dict, result: Any, call_type: str) -> tuple[dict, Any]: + def logging_hook(self, kwargs: dict, result: object, call_type: str) -> tuple[dict, object]: """For masking logged request/response. Return a modified version of the request/result.""" return kwargs, result @@ -581,7 +586,7 @@ class CustomLogger: # https://docs.litellm.ai/docs/observability/custom_callbac async def async_should_run_agentic_loop( self, - response: Any, + response: object, model: str, messages: list[dict], tools: list[dict] | None, @@ -642,8 +647,8 @@ class CustomLogger: # https://docs.litellm.ai/docs/observability/custom_callbac tools: dict, model: str, messages: list[dict], - response: Any, - anthropic_messages_provider_config: Any, + response: object, + anthropic_messages_provider_config: "BaseAnthropicMessagesConfig | None", anthropic_messages_optional_request_params: dict, logging_obj: "LiteLLMLoggingObj", stream: bool, @@ -711,8 +716,8 @@ class CustomLogger: # https://docs.litellm.ai/docs/observability/custom_callbac tools: dict, model: str, messages: list[dict], - response: Any, - anthropic_messages_provider_config: Any, + response: object, + anthropic_messages_provider_config: "BaseAnthropicMessagesConfig | None", anthropic_messages_optional_request_params: dict, logging_obj: "LiteLLMLoggingObj", stream: bool, @@ -728,7 +733,7 @@ class CustomLogger: # https://docs.litellm.ai/docs/observability/custom_callbac async def async_post_agentic_loop_response_hook( self, - response: Any, + response: object, plan: AgenticLoopPlan, kwargs: dict, ) -> Any: @@ -767,7 +772,7 @@ class CustomLogger: # https://docs.litellm.ai/docs/observability/custom_callbac async def async_should_run_chat_completion_agentic_loop( self, - response: Any, + response: object, model: str, messages: list[dict], tools: list[dict] | None, @@ -785,12 +790,12 @@ class CustomLogger: # https://docs.litellm.ai/docs/observability/custom_callbac tools: dict, model: str, messages: list[dict], - response: Any, + response: object, optional_params: dict, logging_obj: "LiteLLMLoggingObj", stream: bool, kwargs: dict, - ) -> Any: + ) -> object: """ Hook to execute chat completion agentic loop based on context from should_run hook. """ @@ -800,7 +805,7 @@ class CustomLogger: # https://docs.litellm.ai/docs/observability/custom_callbac tools: dict, model: str, messages: list[dict], - response: Any, + response: object, optional_params: dict, logging_obj: "LiteLLMLoggingObj", stream: bool, @@ -1056,7 +1061,7 @@ class CustomLogger: # https://docs.litellm.ai/docs/observability/custom_callbac def _redact_base64( self, - value: Any, + value: object, depth: int = 0, max_depth: int = DEFAULT_MAX_RECURSE_DEPTH_SENSITIVE_DATA_MASKER, ) -> object: @@ -1079,7 +1084,7 @@ class CustomLogger: # https://docs.litellm.ai/docs/observability/custom_callbac return value - def _should_keep_content(self, content: Any) -> bool: + def _should_keep_content(self, content: object) -> bool: """Return True if this content item should be retained.""" if not isinstance(content, dict): return True diff --git a/litellm/integrations/gitlab/gitlab_prompt_manager.py b/litellm/integrations/gitlab/gitlab_prompt_manager.py index c41d9dd240f..d4602176650 100644 --- a/litellm/integrations/gitlab/gitlab_prompt_manager.py +++ b/litellm/integrations/gitlab/gitlab_prompt_manager.py @@ -2,10 +2,12 @@ GitLab prompt manager with configurable prompts folder. """ -from typing import TYPE_CHECKING, Any, Final +from collections.abc import Mapping +from typing import TYPE_CHECKING, Any, Final, TypeVar from jinja2 import DictLoader, select_autoescape from jinja2.sandbox import ImmutableSandboxedEnvironment +from typing_extensions import ReadOnly, TypedDict from litellm.integrations.custom_prompt_management import CustomPromptManagement @@ -24,6 +26,19 @@ from litellm.types.utils import StandardCallbackDynamicParams GITLAB_PREFIX: Final = "gitlab::" +_ResponseT = TypeVar("_ResponseT") + + +class GitLabCachedPrompt(TypedDict): + id: ReadOnly[str] + path: ReadOnly[str] + content: ReadOnly[str] + metadata: ReadOnly[Mapping[str, object]] + model: ReadOnly[str | None] + temperature: ReadOnly[float | None] + max_tokens: ReadOnly[int | None] + optional_params: ReadOnly[Mapping[str, object]] + def encode_prompt_id(raw_id: str) -> str: """Convert GitLab path IDs like 'invoice/extract' → 'gitlab::invoice::extract'""" @@ -206,7 +221,7 @@ class GitLabTemplateManager: result[key] = value.strip("\"'") return result - def render_template(self, template_id: str, variables: dict[str, Any] | None = None) -> str: + def render_template(self, template_id: str, variables: Mapping[str, object] | None = None) -> str: if template_id not in self.prompts: raise ValueError(f"Template '{template_id}' not found") template: Final = self.prompts[template_id] @@ -313,7 +328,7 @@ class GitLabPromptManager(CustomPromptManagement): def get_prompt_template( self, prompt_id: str, - prompt_variables: dict[str, Any] | None = None, + prompt_variables: Mapping[str, object] | None = None, *, ref: str | None = None, ) -> tuple[str, dict[str, Any]]: @@ -338,13 +353,13 @@ class GitLabPromptManager(CustomPromptManagement): self, user_id: str | None, messages: list[AllMessageValues], - function_call: dict[str, Any] | str | None = None, - litellm_params: dict[str, Any] | None = None, + function_call: Mapping[str, object] | str | None = None, + litellm_params: dict[str, object] | None = None, prompt_id: str | None = None, - prompt_variables: dict[str, Any] | None = None, + prompt_variables: Mapping[str, object] | None = None, prompt_version: str | None = None, **kwargs, - ) -> tuple[list[AllMessageValues], dict[str, Any] | None]: + ) -> tuple[list[AllMessageValues], dict[str, object] | None]: if not prompt_id: return messages, litellm_params try: @@ -377,9 +392,9 @@ class GitLabPromptManager(CustomPromptManagement): return final_messages, litellm_params except Exception as e: - import litellm + from litellm._logging import verbose_proxy_logger - litellm._logging.verbose_proxy_logger.error("Error in GitLab prompt pre_call_hook: %s", e) + verbose_proxy_logger.error("Error in GitLab prompt pre_call_hook: %s", e) return messages, litellm_params def _parse_prompt_to_messages(self, prompt_content: str) -> list[AllMessageValues]: @@ -435,14 +450,14 @@ class GitLabPromptManager(CustomPromptManagement): def post_call_hook( self, user_id: str | None, - response: Any, + response: _ResponseT, input_messages: list[AllMessageValues], - function_call: dict[str, Any] | str | None = None, - litellm_params: dict[str, Any] | None = None, + function_call: Mapping[str, object] | str | None = None, + litellm_params: Mapping[str, object] | None = None, prompt_id: str | None = None, - prompt_variables: dict[str, Any] | None = None, + prompt_variables: Mapping[str, object] | None = None, **kwargs, - ) -> Any: + ) -> _ResponseT: return response def get_available_prompts(self) -> list[str]: @@ -498,7 +513,7 @@ class GitLabPromptManager(CustomPromptManagement): messages: Final = self._parse_prompt_to_messages(rendered_prompt) template_model: Final = prompt_metadata.get("model") - optional_params: Final[dict[str, Any]] = {} + optional_params: Final[dict[str, object]] = {} for param in [ "temperature", "max_tokens", @@ -658,14 +673,14 @@ class GitLabPromptCache: self.template_manager: GitLabTemplateManager = self.prompt_manager.prompt_manager # In-memory stores - self._by_file: dict[str, dict[str, Any]] = {} - self._by_id: dict[str, dict[str, Any]] = {} + self._by_file: dict[str, GitLabCachedPrompt] = {} + self._by_id: dict[str, GitLabCachedPrompt] = {} # ------------------------- # Public API # ------------------------- - def load_all(self, *, recursive: bool = True) -> dict[str, dict[str, Any]]: + def load_all(self, *, recursive: bool = True) -> dict[str, GitLabCachedPrompt]: """ Scan GitLab for all .prompt files under prompts_path, load and parse each, and return the mapping of repo file path -> JSON-like dict. @@ -695,7 +710,7 @@ class GitLabPromptCache: return self._by_id - def reload(self, *, recursive: bool = True) -> dict[str, dict[str, Any]]: + def reload(self, *, recursive: bool = True) -> dict[str, GitLabCachedPrompt]: """Clear the cache and re-load from GitLab.""" self._by_file.clear() self._by_id.clear() @@ -709,11 +724,11 @@ class GitLabPromptCache: """Return the template IDs (relative to prompts_path, without extension) currently cached.""" return list(self._by_id.keys()) - def get_by_file(self, file_path: str) -> dict[str, Any] | None: + def get_by_file(self, file_path: str) -> GitLabCachedPrompt | None: """Get a cached prompt JSON by repo file path.""" return self._by_file.get(file_path) - def get_by_id(self, prompt_id: str) -> dict[str, Any] | None: + def get_by_id(self, prompt_id: str) -> GitLabCachedPrompt | None: """Get a cached prompt JSON by prompt ID (relative to prompts_path).""" if prompt_id in self._by_id: return self._by_id[prompt_id] @@ -728,7 +743,7 @@ class GitLabPromptCache: # Internals # ------------------------- - def _template_to_json(self, prompt_id: str, tmpl: GitLabPromptTemplate) -> dict[str, Any]: + def _template_to_json(self, prompt_id: str, tmpl: GitLabPromptTemplate) -> GitLabCachedPrompt: """ Normalize a GitLabPromptTemplate into a JSON-like dict that is easy to serialize. """ diff --git a/litellm/integrations/posthog.py b/litellm/integrations/posthog.py index db9610a5a3c..4f7dff952e6 100644 --- a/litellm/integrations/posthog.py +++ b/litellm/integrations/posthog.py @@ -12,7 +12,10 @@ For batching specific details see CustomBatchLogger class import asyncio import atexit import os -from typing import Any, Final +from collections.abc import Mapping, Sequence +from typing import Final + +from typing_extensions import ReadOnly, TypedDict from litellm._logging import verbose_logger from litellm._uuid import uuid @@ -34,6 +37,21 @@ from litellm.types.integrations.posthog import ( from litellm.types.utils import StandardCallbackDynamicParams, StandardLoggingPayload +class PostHogBatchPayload(TypedDict): + api_key: ReadOnly[str] + batch: ReadOnly[Sequence[PostHogEventPayload]] + + +class PostHogLiteLLMParams(TypedDict, total=False): + metadata: ReadOnly[Mapping[str, object]] + + +class PostHogLogKwargs(TypedDict, total=False): + standard_logging_object: ReadOnly[StandardLoggingPayload] + standard_callback_dynamic_params: ReadOnly[StandardCallbackDynamicParams] + litellm_params: ReadOnly[PostHogLiteLLMParams] + + class PostHogLogger(CustomBatchLogger): def __init__(self, **kwargs): """ @@ -137,7 +155,7 @@ class PostHogLogger(CustomBatchLogger): if len(self.log_queue) >= self.batch_size: await self.flush_queue() - def create_posthog_event_payload(self, kwargs: dict[str, Any]) -> PostHogEventPayload: + def create_posthog_event_payload(self, kwargs: PostHogLogKwargs) -> PostHogEventPayload: """ Helper function to create a PostHog event payload for logging @@ -171,11 +189,11 @@ class PostHogLogger(CustomBatchLogger): def _create_posthog_properties( self, standard_logging_object: StandardLoggingPayload, - kwargs: dict[str, Any], + kwargs: PostHogLogKwargs, event_name: str, - ) -> dict[str, Any]: + ) -> dict[str, object]: """Create PostHog properties following LLM Analytics spec""" - properties: Final = {} + properties: Final[dict[str, object]] = {} # Core model information properties["$ai_model"] = self._safe_get(standard_logging_object, "model", "") @@ -211,16 +229,19 @@ class PostHogLogger(CustomBatchLogger): properties["$ai_error"] = error_str # Add trace properties - self._add_trace_properties(properties, kwargs) + self._add_trace_properties(properties, standard_logging_object, kwargs) # Add custom metadata fields self._add_custom_metadata_properties(properties, kwargs) return properties - def _add_trace_properties(self, properties: dict[str, Any], kwargs: dict[str, Any]): - standard_logging_object: Final = self._safe_get(kwargs, "standard_logging_object", {}) - + def _add_trace_properties( + self, + properties: dict[str, object], + standard_logging_object: StandardLoggingPayload, + kwargs: PostHogLogKwargs, + ) -> None: trace_id: Final = self._safe_get(standard_logging_object, "trace_id", self._safe_uuid()) properties["$ai_trace_id"] = trace_id @@ -232,7 +253,7 @@ class PostHogLogger(CustomBatchLogger): if parent_id: properties["$ai_parent_id"] = parent_id - def _add_custom_metadata_properties(self, properties: dict[str, Any], kwargs: dict[str, Any]): + def _add_custom_metadata_properties(self, properties: dict[str, object], kwargs: PostHogLogKwargs) -> None: """Add custom metadata fields to PostHog properties""" metadata: Final = self._extract_metadata(kwargs) if not isinstance(metadata, dict): @@ -277,7 +298,7 @@ class PostHogLogger(CustomBatchLogger): if key not in litellm_internal_fields: properties[key] = value - def _get_distinct_id(self, standard_logging_object: StandardLoggingPayload, kwargs: dict[str, Any]) -> str: + def _get_distinct_id(self, standard_logging_object: StandardLoggingPayload, kwargs: PostHogLogKwargs) -> str: metadata: Final = self._extract_metadata(kwargs) user_id: Final = self._safe_get(metadata, "user_id") if user_id: @@ -291,7 +312,7 @@ class PostHogLogger(CustomBatchLogger): return self._safe_uuid() - def _get_credentials_for_request(self, kwargs: dict[str, Any]) -> tuple[str | None, str | None]: + def _get_credentials_for_request(self, kwargs: PostHogLogKwargs) -> tuple[str | None, str | None]: """ Get PostHog credentials for this request. @@ -334,7 +355,7 @@ class PostHogLogger(CustomBatchLogger): verbose_logger.debug("[POSTHOG MOCK] Mock mode enabled - API calls will be intercepted") # Group events by credentials for batch sending - batches_by_credentials: Final[dict[tuple[str, str], list]] = {} + batches_by_credentials: Final[dict[tuple[str, str], list[PostHogEventPayload]]] = {} for item in self.log_queue: key = (item["api_key"], item["api_url"]) if key not in batches_by_credentials: @@ -380,18 +401,19 @@ class PostHogLogger(CustomBatchLogger): verbose_logger.error("PostHog: Failed to initialize async components: %s", e) raise - def _extract_metadata(self, kwargs: dict[str, Any]) -> dict[str, Any]: - litellm_params: Final = kwargs.get("litellm_params", {}) or {} - return litellm_params.get("metadata", {}) or {} + def _extract_metadata(self, kwargs: PostHogLogKwargs) -> Mapping[str, object]: + litellm_params: Final[PostHogLiteLLMParams] = kwargs.get("litellm_params", {}) or {} + metadata: Final[Mapping[str, object]] = litellm_params.get("metadata", {}) or {} + return metadata def _safe_uuid(self) -> str: return str(uuid.uuid4()) - def _create_posthog_payload(self, events: list, api_key: str) -> dict[str, Any]: + def _create_posthog_payload(self, events: Sequence[PostHogEventPayload], api_key: str) -> PostHogBatchPayload: return {"api_key": api_key, "batch": events} - def _safe_get(self, obj: Any, key: str, default: Any = None) -> Any: - if obj is None or not hasattr(obj, "get"): + def _safe_get(self, obj: Mapping[str, object] | None, key: str, default: object = None) -> object: + if not isinstance(obj, Mapping): return default return obj.get(key, default) @@ -412,7 +434,7 @@ class PostHogLogger(CustomBatchLogger): try: # Group events by credentials (same logic as async_send_batch) - batches_by_credentials: Final[dict[tuple[str, str], list]] = {} + batches_by_credentials: Final[dict[tuple[str, str], list[PostHogEventPayload]]] = {} for item in self.log_queue: key = (item["api_key"], item["api_url"]) if key not in batches_by_credentials: diff --git a/litellm/litellm_core_utils/llm_cost_calc/tool_call_cost_tracking.py b/litellm/litellm_core_utils/llm_cost_calc/tool_call_cost_tracking.py index 9250b92e268..5504756ceb8 100644 --- a/litellm/litellm_core_utils/llm_cost_calc/tool_call_cost_tracking.py +++ b/litellm/litellm_core_utils/llm_cost_calc/tool_call_cost_tracking.py @@ -3,7 +3,7 @@ Helper utilities for tracking the cost of built-in tools. """ from collections.abc import Mapping -from typing import Any, Final, Literal +from typing import Final, Literal import litellm from litellm.constants import OPENAI_FILE_SEARCH_COST_PER_1K_CALLS @@ -16,6 +16,7 @@ from litellm.types.llms.openai import ( WebSearchOptions, ) from litellm.types.utils import ( + ChatCompletionAnnotation, Message, ModelInfo, ModelResponse, @@ -49,7 +50,7 @@ class StandardBuiltInToolCostTracking: @staticmethod def get_cost_for_built_in_tools( model: str, - response_object: Any, + response_object: object, usage: Usage | None = None, custom_llm_provider: str | None = None, standard_built_in_tools_params: StandardBuiltInToolsParams | None = None, @@ -201,8 +202,7 @@ class StandardBuiltInToolCostTracking: model_info: Final = StandardBuiltInToolCostTracking._safe_get_model_info( model=model, custom_llm_provider=custom_llm_provider ) - file_search_raw: Final[Any] = standard_built_in_tools_params.get("file_search", {}) - file_search_usage: Final[FileSearchTool | None] = FileSearchTool(**file_search_raw) if file_search_raw else None + file_search_usage: Final[FileSearchTool | None] = standard_built_in_tools_params.get("file_search") or None # Convert model_info to dict and extract usage parameters model_info_dict: Final = dict(model_info) if model_info is not None else None @@ -245,7 +245,7 @@ class StandardBuiltInToolCostTracking: @staticmethod def _extract_file_search_params( - file_search_usage: Any, + file_search_usage: object, ) -> tuple[float | None, float | None]: """Extract and convert file search parameters safely.""" storage_gb = None @@ -335,7 +335,7 @@ class StandardBuiltInToolCostTracking: @staticmethod def _extract_token_counts( - computer_use_usage: Any, + computer_use_usage: object, ) -> tuple[int | None, int | None]: """Extract and convert token counts safely.""" input_tokens = None @@ -351,9 +351,9 @@ class StandardBuiltInToolCostTracking: return input_tokens, output_tokens @staticmethod - def _safe_convert_to_int(value: Any) -> int | None: + def _safe_convert_to_int(value: object) -> int | None: """Safely convert a value to int.""" - if value is not None: + if isinstance(value, (int, float, str)): try: return int(value) except (TypeError, ValueError): @@ -381,7 +381,7 @@ class StandardBuiltInToolCostTracking: return usage.model_copy(update={"server_tool_use": server_tool_use}) @staticmethod - def response_object_includes_web_search_call(response_object: Any, usage: Usage | None = None) -> bool: + def response_object_includes_web_search_call(response_object: object, usage: Usage | None = None) -> bool: """ Check if the response object includes a web search call. @@ -446,7 +446,7 @@ class StandardBuiltInToolCostTracking: @staticmethod def response_object_includes_file_search_call( - response_object: Any, + response_object: object, ) -> bool: """ Check if the response object includes a file search call. @@ -477,11 +477,11 @@ class StandardBuiltInToolCostTracking: message: Message | None = getattr(choice, "message", None) if message is None: continue - if annotations := getattr(message, "annotations", None): - if len(annotations) > 0: - for annotation in annotations: - if annotation.get("type", None) == annotation_type: - return True + annotations: list[ChatCompletionAnnotation] | None = getattr(message, "annotations", None) + if annotations: + for annotation in annotations: + if annotation.get("type", None) == annotation_type: + return True return False @staticmethod @@ -522,10 +522,8 @@ class StandardBuiltInToolCostTracking: if model_info is None: return 0.0 - search_context_raw: Final[Any] = model_info.get("search_context_cost_per_query", {}) - search_context_pricing: Final[SearchContextCostPerQuery] = ( - SearchContextCostPerQuery(**search_context_raw) if search_context_raw else SearchContextCostPerQuery() - ) + search_context_raw: Final = model_info.get("search_context_cost_per_query") + search_context_pricing: Final[SearchContextCostPerQuery] = search_context_raw or SearchContextCostPerQuery() if web_search_options.get("search_context_size", None) == "low": return search_context_pricing.get("search_context_size_low", 0.0) elif web_search_options.get("search_context_size", None) == "medium": @@ -545,10 +543,8 @@ class StandardBuiltInToolCostTracking: """ if model_info is None: return 0.0 - search_context_raw: Final[Any] = model_info.get("search_context_cost_per_query", {}) or {} - search_context_pricing: Final[SearchContextCostPerQuery] = ( - SearchContextCostPerQuery(**search_context_raw) if search_context_raw else SearchContextCostPerQuery() - ) + search_context_raw: Final = model_info.get("search_context_cost_per_query") + search_context_pricing: Final[SearchContextCostPerQuery] = search_context_raw or SearchContextCostPerQuery() return search_context_pricing.get("search_context_size_medium", 0.0) @staticmethod @@ -714,7 +710,7 @@ class StandardBuiltInToolCostTracking: response_object: ModelResponse, ) -> bool: for _choice in response_object.choices: - message = getattr(_choice, "message", None) + message: Message | None = getattr(_choice, "message", None) if ( message is not None and hasattr(message, "annotations") diff --git a/litellm/litellm_core_utils/prompt_templates/common_utils.py b/litellm/litellm_core_utils/prompt_templates/common_utils.py index bda365102af..2fca19dc8d1 100644 --- a/litellm/litellm_core_utils/prompt_templates/common_utils.py +++ b/litellm/litellm_core_utils/prompt_templates/common_utils.py @@ -555,10 +555,10 @@ def update_messages_with_model_file_ids( def update_responses_input_with_model_file_ids( - input: Any, + input: object, model_id: str | None = None, model_file_id_mapping: dict[str, dict[str, str]] | None = None, -) -> str | list[dict[str, Any]]: +) -> object: """ Updates responses API input with provider-specific file IDs. File IDs are always inside the content array, not as direct input_file items. @@ -639,8 +639,8 @@ def update_responses_input_with_model_file_ids( def _decode_vector_store_ids_in_tools( - tools: list[dict[str, Any]] | None, -) -> list[dict[str, Any]] | None: + tools: list[dict[str, object]] | None, +) -> list[dict[str, object]] | None: """ Decodes unified (LiteLLM-managed) vector_store_ids in file_search tools to provider-native IDs. Non-unified IDs are passed through unchanged. @@ -692,10 +692,10 @@ def _decode_vector_store_ids_in_tools( def update_responses_tools_with_model_file_ids( - tools: list[dict[str, Any]] | None, + tools: list[dict[str, object]] | None, model_id: str | None = None, model_file_id_mapping: dict[str, dict[str, str]] | None = None, -) -> list[dict[str, Any]] | None: +) -> list[dict[str, object]] | None: """ Updates responses API tools with provider-specific file IDs. @@ -888,7 +888,7 @@ def extract_file_data(file_data: FileTypes) -> ExtractedFileData: # --------------------------------------------------------------------------- -def _estimate_json_bytes(obj: Any) -> int: +def _estimate_json_bytes(obj: object) -> int: """Estimate the JSON-serialised byte size of ``obj`` without materialising JSON. Walks iteratively (no recursion stack risk). @@ -1979,7 +1979,7 @@ def drop_tool_reference_parts_from_tool_messages( return [_drop_tool_reference_parts(message) for message in messages] # mutable-ok: pipelines mutate message lists -def _attempt_json_repair(s: str) -> Any | None: +def _attempt_json_repair(s: str) -> object | None: """ Attempt to repair truncated JSON produced by LLM tool calls. @@ -2095,7 +2095,7 @@ def parse_tool_call_arguments( raise ValueError(error_message) from original_error -def split_concatenated_json_objects(raw: str) -> list[dict[str, Any]]: +def split_concatenated_json_objects(raw: str) -> list[dict[str, object]]: """ Split a string that contains one or more concatenated JSON objects into a list of parsed dicts. @@ -2131,7 +2131,7 @@ def split_concatenated_json_objects(raw: str) -> list[dict[str, Any]]: return [] decoder: Final = json.JSONDecoder() - results: Final[list[dict[str, Any]]] = [] + results: Final[list[dict[str, object]]] = [] idx = 0 length: Final = len(raw) diff --git a/litellm/litellm_core_utils/token_counter.py b/litellm/litellm_core_utils/token_counter.py index c350bc5569e..3732ffd734c 100644 --- a/litellm/litellm_core_utils/token_counter.py +++ b/litellm/litellm_core_utils/token_counter.py @@ -4,8 +4,9 @@ import base64 import io import struct from collections.abc import Callable, Iterable, Mapping, Sequence -from typing import Any, Final, Literal, cast +from typing import Final, Literal, cast +import httpx import tiktoken import litellm @@ -171,6 +172,10 @@ def calculate_tiles_needed( return total_tiles +def _unpack_ints(fmt: str, buffer: bytes) -> tuple[int, ...]: + return struct.unpack(fmt, buffer) + + def get_image_type(image_data: bytes) -> str | None: """take an image (really only the first ~100 bytes max are needed) and return 'png' 'gif' 'jpeg' 'webp' 'heic' or None. method added to @@ -210,9 +215,9 @@ def get_image_dimensions( if data.startswith(("http://", "https://")): try: client: Final = _get_httpx_client() - response: Final = safe_get(client, data) + response: Final[httpx.Response] = safe_get(client, data) max_bytes: Final = int(MAX_IMAGE_URL_DOWNLOAD_SIZE_MB * 1024 * 1024) - content_length: Final = response.headers.get("Content-Length") + content_length: Final[str | None] = response.headers.get("Content-Length") if content_length is not None and int(content_length) > max_bytes: pass # skip download; img_data stays None else: @@ -229,10 +234,10 @@ def get_image_dimensions( img_type: Final = get_image_type(img_data) if img_type == "png": - w, h = struct.unpack(">LL", img_data[16:24]) + w, h = _unpack_ints(">LL", img_data[16:24]) return w, h elif img_type == "gif": - w, h = struct.unpack("H", fhandle.read(2))[0] - 2 + size = _unpack_ints(">H", fhandle.read(2))[0] - 2 fhandle.seek(1, 1) - h, w = struct.unpack(">HH", fhandle.read(4)) + h, w = _unpack_ints(">HH", fhandle.read(4)) return w, h elif img_type == "webp": # For WebP, the dimensions are stored at different offsets depending on the format # Check for VP8X (extended format) if img_data[12:16] == b"VP8X": - w = struct.unpack("> 14) & 0x3FFF) + 1 return w, h @@ -420,8 +425,8 @@ def token_counter( def _count_function_call_tokens( key: str, - value: Any, - message: Mapping[str, Any], + value: object, + message: Mapping[str, object], count_function: TokenCounterFunction, ) -> int: """ @@ -587,7 +592,7 @@ def _fix_model_name(model: str) -> str: def _count_image_tokens( - image_url: Any, + image_url: object, use_default_image_token_count: bool, ) -> int: """ @@ -627,7 +632,7 @@ def _count_image_tokens( raise ValueError(f"Invalid image_url type: {type(image_url).__name__}. Expected str or dict with 'url' field.") -def _validate_anthropic_content(content: Mapping[str, Any]) -> type: +def _validate_anthropic_content(content: Mapping[str, object]) -> type: """ Validate and determine which Anthropic TypedDict applies. @@ -642,7 +647,7 @@ def _validate_anthropic_content(content: Mapping[str, Any]) -> type: "tool_result": AnthropicMessagesToolResultParam, } - expected_cls: Final = mapping.get(content_type) + expected_cls: Final = mapping.get(content_type) if isinstance(content_type, str) else None if expected_cls is None: raise ValueError(f"Unknown Anthropic content type: '{content_type}'") @@ -714,7 +719,7 @@ def _count_file_tokens( def _count_anthropic_content( - content: Mapping[str, Any], + content: Mapping[str, object], count_function: TokenCounterFunction, use_default_image_token_count: bool, default_token_count: int | None, @@ -729,7 +734,7 @@ def _count_anthropic_content( avoiding hardcoded field names. """ typeddict_cls: Final = _validate_anthropic_content(content) - type_hints: Final = getattr(typeddict_cls, "__annotations__", {}) + type_hints: Final[Mapping[str, object]] = getattr(typeddict_cls, "__annotations__", {}) tokens = 0 # Fields to skip (metadata/identifiers that don't contribute to prompt tokens) diff --git a/litellm/llms/anthropic/chat/guardrail_translation/handler.py b/litellm/llms/anthropic/chat/guardrail_translation/handler.py index 9395cc3d33e..c7d12e5cf3a 100644 --- a/litellm/llms/anthropic/chat/guardrail_translation/handler.py +++ b/litellm/llms/anthropic/chat/guardrail_translation/handler.py @@ -100,16 +100,6 @@ InputWriteBackTarget = ( ) -class _SSEDelta(TypedDict, total=False): - type: ReadOnly[str] - text: ReadOnly[str] - stop_reason: ReadOnly[str | None] - - -class _SSEEventData(TypedDict, total=False): - delta: ReadOnly[_SSEDelta] - - def _as_str_mapping(value: Mapping[str, object]) -> Mapping[str, object]: return value @@ -157,6 +147,16 @@ class ExtractedInput: EMPTY_EXTRACTED_INPUT: Final = ExtractedInput(scanned=(), images=()) +class _AnthropicSSEDelta(TypedDict, total=False): + type: ReadOnly[str] + text: ReadOnly[str] + stop_reason: ReadOnly[str | None] + + +class _AnthropicSSEEvent(TypedDict, total=False): + delta: ReadOnly[_AnthropicSSEDelta] + + class AnthropicMessagesHandler(BaseTranslation): """Process Anthropic messages with guardrails. @@ -1247,8 +1247,8 @@ class AnthropicMessagesHandler(BaseTranslation): # Only process content_block_delta events if event_type == "content_block_delta" and data_line: try: - data: _SSEEventData = json.loads(data_line) - delta = data.get("delta", {}) + data: _AnthropicSSEEvent = json.loads(data_line) + delta: _AnthropicSSEDelta = data.get("delta", {}) if delta.get("type") == "text_delta": text += delta.get("text", "") except json.JSONDecodeError: @@ -1310,9 +1310,9 @@ class AnthropicMessagesHandler(BaseTranslation): # Check for message_delta event with stop_reason if event_type == "message_delta" and data_line: try: - data: _SSEEventData = json.loads(data_line) - delta = data.get("delta", {}) - stop_reason = delta.get("stop_reason") + data: _AnthropicSSEEvent = json.loads(data_line) + delta: _AnthropicSSEDelta = data.get("delta", {}) + stop_reason: str | None = delta.get("stop_reason") if stop_reason is not None: return True except json.JSONDecodeError: diff --git a/litellm/llms/anthropic/chat/handler.py b/litellm/llms/anthropic/chat/handler.py index cd47cdd57d6..c82be07a5c5 100644 --- a/litellm/llms/anthropic/chat/handler.py +++ b/litellm/llms/anthropic/chat/handler.py @@ -66,6 +66,10 @@ if TYPE_CHECKING: from litellm.llms.base_llm.chat.transformation import BaseConfig +def _loads_stream_chunk(payload: str) -> dict[str, object]: + return json.loads(payload) + + async def make_call( client: AsyncHTTPHandler | None, api_base: str, @@ -78,7 +82,7 @@ async def make_call( json_mode: bool, speed: str | None = None, tool_name_reverse_map: dict[str, str] | None = None, -) -> tuple[Any, httpx.Headers]: +) -> tuple["ModelResponseIterator", httpx.Headers]: if client is None: client = litellm.module_level_aclient @@ -93,7 +97,7 @@ async def make_call( ) except httpx.HTTPStatusError as e: error_headers = getattr(e, "headers", None) - error_response: Final = getattr(e, "response", None) + error_response: Final[object] = getattr(e, "response", None) if error_headers is None and error_response: error_headers = getattr(error_response, "headers", None) raise AnthropicError( @@ -138,7 +142,7 @@ def make_sync_call( json_mode: bool, speed: str | None = None, tool_name_reverse_map: dict[str, str] | None = None, -) -> tuple[Any, httpx.Headers]: +) -> tuple["ModelResponseIterator", httpx.Headers]: if client is None: client = litellm.module_level_client # re-use a module level client @@ -153,7 +157,7 @@ def make_sync_call( ) except httpx.HTTPStatusError as e: error_headers = getattr(e, "headers", None) - error_response: Final = getattr(e, "response", None) + error_response: Final[object] = getattr(e, "response", None) if error_headers is None and error_response: error_headers = getattr(error_response, "headers", None) raise AnthropicError( @@ -292,7 +296,7 @@ class AnthropicChatCompletion(BaseLLM): status_code: Final = getattr(e, "status_code", 500) error_headers = getattr(e, "headers", None) error_text = getattr(e, "text", str(e)) - error_response: Final = getattr(e, "response", None) + error_response: Final[object] = getattr(e, "response", None) if error_headers is None and error_response: error_headers = getattr(error_response, "headers", None) if error_response and hasattr(error_response, "text"): @@ -593,7 +597,7 @@ class AnthropicChatCompletion(BaseLLM): status_code: Final = getattr(e, "status_code", 500) error_headers = getattr(e, "headers", None) error_text = getattr(e, "text", str(e)) - error_response: Final = getattr(e, "response", None) + error_response: Final[object] = getattr(e, "response", None) if error_headers is None and error_response: error_headers = getattr(error_response, "headers", None) if error_response and hasattr(error_response, "text"): @@ -664,10 +668,10 @@ class ModelResponseIterator: # Accumulate web_search_tool_result blocks for multi-turn reconstruction # See: https://github.com/BerriAI/litellm/issues/17737 - self.web_search_results: list[dict[str, Any]] = [] + self.web_search_results: list[dict[str, object]] = [] # Accumulate compaction blocks for multi-turn reconstruction - self.compaction_blocks: list[dict[str, Any]] = [] + self.compaction_blocks: list[dict[str, object]] = [] # Accumulate streamed thinking text so final usage can split reasoning # tokens from regular output tokens. @@ -727,7 +731,7 @@ class ModelResponseIterator: str, ChatCompletionToolCallChunk | None, list[ChatCompletionThinkingBlock | ChatCompletionRedactedThinkingBlock], - dict[str, Any], + dict[str, object], str | None, ]: """ @@ -735,7 +739,7 @@ class ModelResponseIterator: """ text = "" tool_use: ChatCompletionToolCallChunk | None = None - provider_specific_fields: Final = {} + provider_specific_fields: Final[dict[str, object]] = {} reasoning_content: str | None = None content_block: Final = ContentBlockDelta(**chunk) thinking_blocks: list[ChatCompletionThinkingBlock | ChatCompletionRedactedThinkingBlock] = [] @@ -809,8 +813,8 @@ class ModelResponseIterator: def _handle_redacted_thinking_content( self, content_block_start: ContentBlockStart, - provider_specific_fields: dict[str, Any], - ) -> tuple[list[ChatCompletionRedactedThinkingBlock], dict[str, Any]]: + provider_specific_fields: dict[str, object], + ) -> tuple[list[ChatCompletionRedactedThinkingBlock], dict[str, object]]: """ Handle the redacted thinking content """ @@ -878,7 +882,7 @@ class ModelResponseIterator: tool_use: ChatCompletionToolCallChunk | None = None finish_reason = "" usage: Usage | None = None - provider_specific_fields: dict[str, Any] = {} + provider_specific_fields: dict[str, object] = {} reasoning_content: str | None = None thinking_blocks: list[ChatCompletionThinkingBlock | ChatCompletionRedactedThinkingBlock] | None = None @@ -1212,7 +1216,7 @@ class ModelResponseIterator: # Try to parse as valid JSON first try: - data_json: Final = json.loads(data_str) + data_json: Final = _loads_stream_chunk(data_str) return self.chunk_parser(chunk=data_json) except json.JSONDecodeError: # Switch to accumulation mode and start accumulating @@ -1330,7 +1334,7 @@ class ModelResponseIterator: str_line = str_line[index:] if str_line.startswith("data:"): - data_json: Final = json.loads(str_line[5:]) + data_json: Final = _loads_stream_chunk(str_line[5:]) return self.chunk_parser(chunk=data_json) else: return ModelResponseStream(id=self.response_id) diff --git a/litellm/llms/anthropic/common_utils.py b/litellm/llms/anthropic/common_utils.py index d8d6a7fc9f8..9871001bf66 100644 --- a/litellm/llms/anthropic/common_utils.py +++ b/litellm/llms/anthropic/common_utils.py @@ -865,13 +865,9 @@ class AnthropicModelInfo(BaseLLMModelInfo): f"Failed to fetch models from Anthropic. Status code: {response.status_code}, Response: {response.text}" ) - models: Final = response.json()["data"] + models: Final[Sequence[Mapping[str, str]]] = response.json()["data"] - litellm_model_names: Final = [] - for model in models: - stripped_model_name = model["id"] - litellm_model_name = "anthropic/" + stripped_model_name - litellm_model_names.append(litellm_model_name) + litellm_model_names: Final = ["anthropic/" + model["id"] for model in models] return litellm_model_names def get_token_counter(self) -> BaseTokenCounter | None: @@ -1077,7 +1073,7 @@ def strip_empty_content_blocks_from_anthropic_messages( return out -def _is_empty_text_block(block: Any) -> bool: +def _is_empty_text_block(block: object) -> bool: if not isinstance(block, dict) or block.get("type") != "text": return False text: Final = block.get("text") @@ -1131,7 +1127,7 @@ def normalize_anthropic_tool_use_id(raw_id: str) -> str: return sanitized or "tool_use_id" -def _sanitize_tool_use_id_content_block(block: Any) -> Any: +def _sanitize_tool_use_id_content_block(block: object) -> object: if not isinstance(block, dict): return block block_type: Final = block.get("type") diff --git a/litellm/llms/anthropic/experimental_pass_through/adapters/transformation.py b/litellm/llms/anthropic/experimental_pass_through/adapters/transformation.py index 411df267442..199a8ab77e7 100644 --- a/litellm/llms/anthropic/experimental_pass_through/adapters/transformation.py +++ b/litellm/llms/anthropic/experimental_pass_through/adapters/transformation.py @@ -18,6 +18,24 @@ TOOL_NAME_PREFIX_LENGTH: Final = OPENAI_MAX_TOOL_NAME_LENGTH - TOOL_NAME_HASH_LE PROVIDERS_PROXYING_AN_UNKNOWN_BACKEND: Final = frozenset({"litellm_proxy"}) +def _optional_attr(source: object, name: str) -> object: + return getattr(source, name, None) + + +def _as_string_mapping(value: object) -> Mapping[str, object] | None: + if isinstance(value, Mapping): + return value + return None + + +def _thought_signature(provider_specific_fields: object) -> str | None: + fields: Final = _as_string_mapping(provider_specific_fields) + if fields is None: + return None + signature: Final = fields.get("thought_signature") + return signature if isinstance(signature, str) else None + + _ANTHROPIC_TOOL_SCHEMA_KEYS: Final = frozenset( {"name", "type", "input_schema", "description", "cache_control", "strict"} ) @@ -56,7 +74,7 @@ def truncate_tool_name(name: str) -> str: def create_tool_name_mapping( - tools: list[dict[str, Any]], + tools: Sequence[Mapping[str, object]], ) -> dict[str, str]: """ Create a mapping of truncated tool names to original names. @@ -70,6 +88,8 @@ def create_tool_name_mapping( mapping: Final[dict[str, str]] = {} for tool in tools: original_name = tool.get("name", "") + if not isinstance(original_name, str): + continue truncated_name = truncate_tool_name(original_name) if truncated_name != original_name: mapping[truncated_name] = original_name @@ -286,44 +306,44 @@ class LiteLLMAnthropicMessagesAdapter: ### FOR [BETA] `/v1/messages` endpoint support - def _extract_signature_from_tool_call(self, tool_call: Any) -> str | None: + def _extract_signature_from_tool_call(self, tool_call: object) -> str | None: """ Extract signature from a tool call's provider_specific_fields. Only checks provider_specific_fields, not thinking blocks. """ - signature = None + fields: Final = _optional_attr(tool_call, "provider_specific_fields") + if fields: + return _thought_signature(fields) - if hasattr(tool_call, "provider_specific_fields") and tool_call.provider_specific_fields: - if "thought_signature" in tool_call.provider_specific_fields: - signature = tool_call.provider_specific_fields["thought_signature"] - elif hasattr(tool_call.function, "provider_specific_fields") and tool_call.function.provider_specific_fields: - if "thought_signature" in tool_call.function.provider_specific_fields: - signature = tool_call.function.provider_specific_fields["thought_signature"] + function_fields: Final = _optional_attr(_optional_attr(tool_call, "function"), "provider_specific_fields") + if function_fields: + return _thought_signature(function_fields) - return signature + return None - def _extract_signature_from_tool_use_content(self, content: dict[str, Any]) -> str | None: + def _extract_signature_from_tool_use_content(self, content: Mapping[str, object]) -> str | None: """ Extract signature from a tool_use content block's provider_specific_fields. """ - provider_specific_fields: Final = content.get("provider_specific_fields", {}) + provider_specific_fields: Final = _as_string_mapping(content.get("provider_specific_fields", {})) if provider_specific_fields: - return provider_specific_fields.get("signature") + signature: Final = provider_specific_fields.get("signature") + return signature if isinstance(signature, str) else None return None def _add_cache_control_if_applicable( self, - source: Any, - target: Any, + source: object, + target: object, model: str | None, ) -> None: """ Extract cache_control from source and add to target if it should be preserved. - This method accepts Any type to support both regular dicts and TypedDict objects. - TypedDict objects (like ChatCompletionTextObject, ChatCompletionImageObject, etc.) - are dicts at runtime but have specific types at type-check time. Using Any allows - this method to work with both while maintaining runtime correctness. + This method accepts an unconstrained type to support both regular dicts and + TypedDict objects. TypedDict objects (like ChatCompletionTextObject, + ChatCompletionImageObject, etc.) are dicts at runtime but have specific types at + type-check time, so the widest parameter type works with both. Args: source: Dict or TypedDict containing potential cache_control field @@ -751,7 +771,7 @@ class LiteLLMAnthropicMessagesAdapter: return new_tools, tool_name_mapping - def translate_anthropic_output_format_to_openai(self, output_format: Any) -> dict[str, object] | None: + def translate_anthropic_output_format_to_openai(self, output_format: object) -> dict[str, object] | None: """ Translate Anthropic's output_format to OpenAI's response_format. @@ -1366,7 +1386,7 @@ class LiteLLMAnthropicMessagesAdapter: @classmethod def _first_positive_prompt_tokens_detail_value(cls, usage: Usage, field_names: tuple[str, ...]) -> int: - prompt_tokens_details: Final = getattr(usage, "prompt_tokens_details", None) + prompt_tokens_details: Final = _optional_attr(usage, "prompt_tokens_details") if prompt_tokens_details is None: return 0 @@ -1374,7 +1394,7 @@ class LiteLLMAnthropicMessagesAdapter: if isinstance(prompt_tokens_details, dict): value = cls._positive_int(prompt_tokens_details.get(field_name)) else: - value = cls._positive_int(getattr(prompt_tokens_details, field_name, None)) + value = cls._positive_int(_optional_attr(prompt_tokens_details, field_name)) if value > 0: return value return 0 diff --git a/litellm/llms/anthropic/experimental_pass_through/context_management/editors/compact.py b/litellm/llms/anthropic/experimental_pass_through/context_management/editors/compact.py index 1cf52045a48..050ab67c86c 100644 --- a/litellm/llms/anthropic/experimental_pass_through/context_management/editors/compact.py +++ b/litellm/llms/anthropic/experimental_pass_through/context_management/editors/compact.py @@ -14,7 +14,7 @@ Mirrors Anthropic's native ``compact_20260112`` for non-Anthropic providers: import re from collections.abc import Awaitable, Mapping, Sequence -from typing import TYPE_CHECKING, Any, Final, Literal, Optional, Protocol, TypeVar, Union, cast +from typing import TYPE_CHECKING, Final, Literal, Optional, Protocol, TypeVar, Union, cast from typing_extensions import NotRequired, ReadOnly, TypedDict, Unpack @@ -232,7 +232,7 @@ async def _check_summary_model_access( key_models: Final = list(getattr(user_api_key_auth, "models", None) or []) team_id: Final[str | None] = getattr(user_api_key_auth, "team_id", None) - team_model_aliases: Final = getattr(user_api_key_auth, "team_model_aliases", None) + team_model_aliases: Final[dict[str, str] | None] = getattr(user_api_key_auth, "team_model_aliases", None) team_models: Final = list(getattr(user_api_key_auth, "team_models", None) or []) user_id: Final[str | None] = getattr(user_api_key_auth, "user_id", None) project_id: Final[str | None] = getattr(user_api_key_auth, "project_id", None) @@ -443,7 +443,9 @@ async def _check_summary_model_budget( ) return False - end_user_model_max_budget: Final = getattr(user_api_key_auth, "end_user_model_max_budget", None) + end_user_model_max_budget: Final[dict[str, object] | None] = getattr( + user_api_key_auth, "end_user_model_max_budget", None + ) end_user_id: Final[str | None] = getattr(user_api_key_auth, "end_user_id", None) if isinstance(end_user_model_max_budget, dict) and end_user_model_max_budget and end_user_id is not None: try: @@ -854,8 +856,8 @@ def _extract_summary_text(raw: str | None) -> str | None: def _system_to_openai_message( - system: str | list[dict[str, Any]] | None, -) -> Mapping[str, object] | None: + system: str | list[dict[str, object]] | None, +) -> dict[str, object] | None: """Translate Anthropic-shaped ``system`` to an OpenAI system message. Accepts a bare string or a list of Anthropic content blocks; returns @@ -866,10 +868,10 @@ def _system_to_openai_message( if isinstance(system, str): return {"role": "system", "content": system} if system else None if isinstance(system, list): - parts: Final[tuple[str, ...]] = tuple( + parts: Final[list[object]] = [ block.get("text", "") for block in system if isinstance(block, dict) and block.get("type") == "text" - ) - joined: Final = "\n\n".join(part for part in parts if part) + ] + joined: Final = "\n\n".join(part for part in parts if isinstance(part, str) and part) return {"role": "system", "content": joined} if joined else None return None @@ -951,7 +953,7 @@ async def _call_summary_model( summary_model: str, summary_messages: Sequence[Mapping[str, object]], metadata: Mapping[str, object], - llm_router: object, + llm_router: Optional["Router"], allowed_model_region: str | None = None, max_tokens: int = COMPACT_SUMMARY_MAX_TOKENS, ) -> Union["ModelResponse", "CustomStreamWrapper"]: @@ -1036,10 +1038,9 @@ def _extract_usage(response: object) -> tuple[int, int]: usage: Final[object] = getattr(response, "usage", None) if usage is None: return 0, 0 - return ( - int(getattr(usage, "prompt_tokens", 0) or 0), - int(getattr(usage, "completion_tokens", 0) or 0), - ) + prompt_tokens: Final[int | None] = getattr(usage, "prompt_tokens", 0) + completion_tokens: Final[int | None] = getattr(usage, "completion_tokens", 0) + return int(prompt_tokens or 0), int(completion_tokens or 0) def apply_client_compaction_block_history( diff --git a/litellm/llms/anthropic/experimental_pass_through/responses_adapters/transformation.py b/litellm/llms/anthropic/experimental_pass_through/responses_adapters/transformation.py index ace7fc25dc9..0eb0e38a46e 100644 --- a/litellm/llms/anthropic/experimental_pass_through/responses_adapters/transformation.py +++ b/litellm/llms/anthropic/experimental_pass_through/responses_adapters/transformation.py @@ -179,14 +179,14 @@ class LiteLLMAnthropicToResponsesAPIAdapter: ) @staticmethod - def _assistant_block_group_key(indexed_block: tuple[int, Mapping[str, Any]]) -> str: + def _assistant_block_group_key(indexed_block: tuple[int, Mapping[str, object]]) -> str: """Group a run of consecutive thinking blocks together; keep every other block alone.""" index, block = indexed_block return "thinking" if block.get("type") == "thinking" else f"block:{index}" @classmethod def _assistant_group_to_input_item( - cls, group: tuple[Mapping[str, Any], ...] + cls, group: tuple[Mapping[str, object], ...] ) -> dict[str, Any] | None: # mutable-ok: API message payload first: Final = group[0] btype: Final = first.get("type") @@ -206,7 +206,7 @@ class LiteLLMAnthropicToResponsesAPIAdapter: def translate_messages_to_responses_input( self, messages: list[AllAnthropicPassThroughMessageValues], - ) -> list[dict[str, Any]]: + ) -> list[dict[str, object]]: """ Convert Anthropic messages list to Responses API `input` items. @@ -220,7 +220,7 @@ class LiteLLMAnthropicToResponsesAPIAdapter: assistant thinking -> reasoning assistant tool_use -> function_call """ - input_items: Final[list[dict[str, Any]]] = [] + input_items: Final[list[dict[str, object]]] = [] for m in messages: if m["role"] == "system": @@ -248,7 +248,7 @@ class LiteLLMAnthropicToResponsesAPIAdapter: } ) elif isinstance(content, list): - user_parts: list[dict[str, Any]] = [] + user_parts: list[Mapping[str, object]] = [] tool_image_parts: list[dict[str, Any]] = [] # mutable-ok: json content parts for block in content: if not isinstance(block, dict): @@ -379,9 +379,9 @@ class LiteLLMAnthropicToResponsesAPIAdapter: def translate_tools_to_responses_api( self, tools: list[AllAnthropicToolsValues], - ) -> list[dict[str, Any]]: + ) -> list[dict[str, object]]: """Convert Anthropic tool definitions to Responses API function tools.""" - result: Final[list[dict[str, Any]]] = [] + result: Final[list[dict[str, object]]] = [] for tool in tools: tool_dict = cast(dict[str, Any], tool) tool_type = tool_dict.get("type", "") @@ -392,7 +392,7 @@ class LiteLLMAnthropicToResponsesAPIAdapter: continue # Responses turns strict mode on when `strict` is omitted, silently rewriting # `required` to every property. Anthropic tools are non-strict unless asked. - func_tool: dict[str, Any] = { + func_tool: dict[str, object] = { "type": "function", "name": tool_name, "strict": bool(tool_dict.get("strict")), @@ -407,7 +407,7 @@ class LiteLLMAnthropicToResponsesAPIAdapter: @staticmethod def translate_tool_choice_to_responses_api( tool_choice: AnthropicMessagesToolChoice, - ) -> str | dict[str, Any]: + ) -> str | dict[str, object]: """Convert Anthropic tool_choice to Responses API tool_choice.""" tc_type: Final = tool_choice.get("type") if tc_type == "any": @@ -420,8 +420,8 @@ class LiteLLMAnthropicToResponsesAPIAdapter: @staticmethod def translate_context_management_to_responses_api( - context_management: dict[str, Any], - ) -> list[dict[str, Any]] | None: + context_management: dict[str, object], + ) -> list[dict[str, object]] | None: """ Convert Anthropic context_management dict to OpenAI Responses API array format. @@ -435,13 +435,13 @@ class LiteLLMAnthropicToResponsesAPIAdapter: if not isinstance(edits, list): return None - result: Final[list[dict[str, Any]]] = [] + result: Final[list[dict[str, object]]] = [] for edit in edits: if not isinstance(edit, dict): continue edit_type = edit.get("type", "") if edit_type == "compact_20260112": - entry: dict[str, Any] = {"type": "compaction"} + entry: dict[str, object] = {"type": "compaction"} trigger = edit.get("trigger") if isinstance(trigger, dict) and trigger.get("value") is not None: entry["compact_threshold"] = int(trigger["value"]) @@ -451,9 +451,9 @@ class LiteLLMAnthropicToResponsesAPIAdapter: @staticmethod def translate_thinking_to_reasoning( - thinking: dict[str, Any], - output_config: dict[str, Any] | None = None, - ) -> dict[str, Any] | None: + thinking: dict[str, object], + output_config: dict[str, object] | None = None, + ) -> dict[str, object] | None: """ Convert Anthropic thinking param to Responses API reasoning param. @@ -473,12 +473,14 @@ class LiteLLMAnthropicToResponsesAPIAdapter: if isinstance(output_config, dict) and output_config.get("effort"): effort = output_config["effort"] elif thinking_type == "enabled": - effort = reasoning_effort_from_thinking_budget(thinking.get("budget_tokens", 0)) + raw_budget: Final = thinking.get("budget_tokens", 0) + budget_tokens: Final = int(raw_budget) if isinstance(raw_budget, (int, float)) else 0 + effort = reasoning_effort_from_thinking_budget(budget_tokens) else: return None auto_summary: Final = is_reasoning_auto_summary_enabled() - result: Final[dict[str, Any]] = {"effort": effort} + result: Final[dict[str, object]] = {"effort": effort} summary: Final = thinking.get("summary") if summary: result["summary"] = summary @@ -570,7 +572,7 @@ class LiteLLMAnthropicToResponsesAPIAdapter: # output_format / output_config.format -> text format # output_format: {"type": "json_schema", "schema": {...}} # output_config: {"format": {"type": "json_schema", "schema": {...}}} - output_format: Any = anthropic_request.get("output_format") + output_format: object = anthropic_request.get("output_format") output_config = anthropic_request.get("output_config") if not isinstance(output_format, dict) and isinstance(output_config, dict): output_format = output_config.get("format") @@ -620,7 +622,7 @@ class LiteLLMAnthropicToResponsesAPIAdapter: ResponseReasoningItem, ) - content: Final[list[dict[str, Any]]] = [] + content: Final[list[dict[str, object]]] = [] stop_reason: AnthropicFinishReason = "end_turn" for item in response.output: diff --git a/litellm/llms/base_llm/managed_resources/base_managed_resource.py b/litellm/llms/base_llm/managed_resources/base_managed_resource.py index cced330d873..4fbc0ce51b0 100644 --- a/litellm/llms/base_llm/managed_resources/base_managed_resource.py +++ b/litellm/llms/base_llm/managed_resources/base_managed_resource.py @@ -5,7 +5,8 @@ import base64 import json from abc import ABC, abstractmethod -from typing import TYPE_CHECKING, Any, Final, Generic, TypeVar, cast +from collections.abc import Mapping +from typing import TYPE_CHECKING, Any, Final, Generic, Protocol, TypeVar, cast, runtime_checkable from litellm import verbose_logger from litellm.llms.base_llm.managed_resources.isolation import ( @@ -38,6 +39,30 @@ else: ResourceObjectType = TypeVar("ResourceObjectType") +@runtime_checkable +class _HasIdentifier(Protocol): + id: str + + +class _ManagedResourceRecord(Protocol[ResourceObjectType]): + unified_resource_id: str + resource_object: ResourceObjectType + + def model_dump(self) -> dict[str, object]: ... + + +class _ManagedResourceTable(Protocol[ResourceObjectType]): + async def create(self, *, data: Mapping[str, object]) -> object: ... + + async def find_first(self, *, where: Mapping[str, object]) -> _ManagedResourceRecord[ResourceObjectType] | None: ... + + async def find_many( + self, *, where: Mapping[str, object], take: int, order: Mapping[str, str] + ) -> list[_ManagedResourceRecord[ResourceObjectType]]: ... + + async def delete(self, *, where: Mapping[str, object]) -> object: ... + + class BaseManagedResource(ABC, Generic[ResourceObjectType]): """ Base class for managing resources with target_model_names support. @@ -64,6 +89,9 @@ class BaseManagedResource(ABC, Generic[ResourceObjectType]): self.internal_usage_cache = internal_usage_cache self.prisma_client = prisma_client + def _resource_table(self) -> _ManagedResourceTable[ResourceObjectType]: + return getattr(self.prisma_client.db, self.table_name) + # ============================================================================ # ABSTRACT METHODS # ============================================================================ @@ -137,7 +165,7 @@ class BaseManagedResource(ABC, Generic[ResourceObjectType]): litellm_parent_otel_span: Span | None, model_mappings: dict[str, str], user_api_key_dict: UserAPIKeyAuth, - additional_db_fields: dict[str, Any] | None = None, + additional_db_fields: Mapping[str, object] | None = None, ) -> None: """ Store unified resource ID with model mappings in cache and database. @@ -153,7 +181,7 @@ class BaseManagedResource(ABC, Generic[ResourceObjectType]): verbose_logger.info("Storing LiteLLM Managed %s with id=%s in cache", self.resource_type, unified_resource_id) # Prepare cache data - cache_data: Final = { + cache_data: Final[dict[str, object]] = { "unified_resource_id": unified_resource_id, "resource_object": resource_object, "model_mappings": model_mappings, @@ -176,7 +204,7 @@ class BaseManagedResource(ABC, Generic[ResourceObjectType]): ) # Prepare database data - db_data: Final = { + db_data: Final[dict[str, object]] = { "unified_resource_id": unified_resource_id, "model_mappings": json.dumps(model_mappings), "flat_model_resource_ids": list(model_mappings.values()), @@ -205,7 +233,7 @@ class BaseManagedResource(ABC, Generic[ResourceObjectType]): db_data.update(additional_db_fields) # Store in database - table: Final = getattr(self.prisma_client.db, self.table_name) + table: Final = self._resource_table() result: Final = await table.create(data=db_data) verbose_logger.debug( @@ -240,7 +268,7 @@ class BaseManagedResource(ABC, Generic[ResourceObjectType]): return result # Check database - table: Final = getattr(self.prisma_client.db, self.table_name) + table: Final = self._resource_table() db_object: Final = await table.find_first(where={"unified_resource_id": unified_resource_id}) if db_object: @@ -264,7 +292,7 @@ class BaseManagedResource(ABC, Generic[ResourceObjectType]): The deleted resource object or None if not found """ # Get old value from database - table: Final = getattr(self.prisma_client.db, self.table_name) + table: Final = self._resource_table() initial_value: Final = await table.find_first(where={"unified_resource_id": unified_resource_id}) if initial_value is None: @@ -515,7 +543,7 @@ class BaseManagedResource(ABC, Generic[ResourceObjectType]): user_api_key_dict: UserAPIKeyAuth, limit: int | None = None, after: str | None = None, - additional_filters: dict[str, Any] | None = None, + additional_filters: Mapping[str, object] | None = None, ) -> dict[str, Any]: """ List resources created by a user. @@ -533,7 +561,7 @@ class BaseManagedResource(ABC, Generic[ResourceObjectType]): if owner_filter is None: return build_list_page([]) - where_clause: Final[dict[str, Any]] = {**owner_filter} + where_clause: Final[dict[str, object]] = {**owner_filter} if after: where_clause["id"] = {"gt": after} @@ -544,14 +572,14 @@ class BaseManagedResource(ABC, Generic[ResourceObjectType]): # Fetch resources fetch_limit: Final = limit or 20 - table: Final = getattr(self.prisma_client.db, self.table_name) + table: Final = self._resource_table() resources: Final = await table.find_many( where=where_clause, take=fetch_limit, order={"created_at": "desc"}, ) - resource_objects: Final[list[Any]] = [] + resource_objects: Final[list[object]] = [] for resource in resources: try: # Stop once we have enough @@ -559,12 +587,13 @@ class BaseManagedResource(ABC, Generic[ResourceObjectType]): break # Parse resource object - resource_data = resource.resource_object - if isinstance(resource_data, str): - resource_data = json.loads(resource_data) + stored_resource = resource.resource_object + resource_data: object = ( + json.loads(stored_resource) if isinstance(stored_resource, str) else stored_resource + ) # Set unified ID - if hasattr(resource_data, "id"): + if isinstance(resource_data, _HasIdentifier): resource_data.id = resource.unified_resource_id elif isinstance(resource_data, dict): resource_data["id"] = resource.unified_resource_id diff --git a/litellm/llms/base_llm/ocr/transformation.py b/litellm/llms/base_llm/ocr/transformation.py index d1c77186ea8..3b302837032 100644 --- a/litellm/llms/base_llm/ocr/transformation.py +++ b/litellm/llms/base_llm/ocr/transformation.py @@ -75,6 +75,7 @@ class OCRUsageInfo(LiteLLMPydanticObjectBase): """Usage information from OCR response.""" pages_processed: int | None = None + pages_processed_annotation: int | None = None credits: float | None = None doc_size_bytes: int | None = None diff --git a/litellm/llms/bedrock/common_utils.py b/litellm/llms/bedrock/common_utils.py index df65df642a2..30a77d57f24 100644 --- a/litellm/llms/bedrock/common_utils.py +++ b/litellm/llms/bedrock/common_utils.py @@ -1576,6 +1576,7 @@ class CommonBatchFilesUtils: aws_role_name=optional_params.get("aws_role_name"), aws_web_identity_token=optional_params.get("aws_web_identity_token"), aws_sts_endpoint=optional_params.get("aws_sts_endpoint"), + aws_external_id=optional_params.get("aws_external_id"), ) # Prepare the request data diff --git a/litellm/llms/bedrock/files/handler.py b/litellm/llms/bedrock/files/handler.py index 13718d41cc1..e74c3802d20 100644 --- a/litellm/llms/bedrock/files/handler.py +++ b/litellm/llms/bedrock/files/handler.py @@ -113,6 +113,7 @@ class BedrockFilesHandler(BaseAWSLLM): aws_role_name=optional_params.get("aws_role_name"), aws_web_identity_token=optional_params.get("aws_web_identity_token"), aws_sts_endpoint=optional_params.get("aws_sts_endpoint"), + aws_external_id=optional_params.get("aws_external_id"), ) # Create S3 client diff --git a/litellm/llms/bedrock/files/transformation.py b/litellm/llms/bedrock/files/transformation.py index f442608a288..33b27943ad8 100644 --- a/litellm/llms/bedrock/files/transformation.py +++ b/litellm/llms/bedrock/files/transformation.py @@ -146,6 +146,7 @@ class _BedrockS3RequestParams(BaseModel): aws_role_name: str | None = None aws_web_identity_token: str | None = None aws_sts_endpoint: str | None = None + aws_external_id: str | None = None s3_region_name: str | None = None s3_endpoint_url: str | None = None @@ -1029,6 +1030,7 @@ class BedrockFilesConfig(BaseAWSLLM, BaseFilesConfig): aws_role_name=optional_params.get("aws_role_name"), aws_web_identity_token=optional_params.get("aws_web_identity_token"), aws_sts_endpoint=optional_params.get("aws_sts_endpoint"), + aws_external_id=optional_params.get("aws_external_id"), ) # Calculate SHA256 hash of the content (REQUIRED for S3) @@ -1290,6 +1292,7 @@ class BedrockFilesConfig(BaseAWSLLM, BaseFilesConfig): aws_role_name=request_params.aws_role_name, aws_web_identity_token=request_params.aws_web_identity_token, aws_sts_endpoint=request_params.aws_sts_endpoint, + aws_external_id=request_params.aws_external_id, ) empty_body_hash: Final = hashlib.sha256(b"").hexdigest() diff --git a/litellm/llms/gemini/common_utils.py b/litellm/llms/gemini/common_utils.py index bd2b124605c..78e6e6aaf82 100644 --- a/litellm/llms/gemini/common_utils.py +++ b/litellm/llms/gemini/common_utils.py @@ -2,7 +2,7 @@ import base64 import datetime import json import math -from collections.abc import Sequence +from collections.abc import Mapping, Sequence from typing import Any, Final import httpx @@ -128,24 +128,35 @@ def is_gemini_image_model(model: str) -> bool: return "gemini" in base_model +def _parse_image_config_string(raw_image_config: str, model: str) -> object: + try: + return json.loads(raw_image_config) + except json.JSONDecodeError as exc: + raise litellm.UnsupportedParamsError( + model=model, + message="`imageConfig` must be valid JSON when provided as a string.", + ) from exc + + def map_openai_image_params_to_gemini( - params: dict[str, Any], + params: Mapping[str, object], model: str, supported_params: Sequence[str], - optional_params: dict[str, Any] | None = None, + optional_params: Mapping[str, object] | None = None, parse_image_config_string: bool = False, -) -> dict[str, Any]: - optional_params = optional_params or {} +) -> dict[str, object]: + already_mapped: Final[Mapping[str, object]] = optional_params or {} filtered_params: Final = {key: value for key, value in params.items() if key in supported_params} - mapped_params: Final[dict[str, Any]] = {} + mapped_params: Final[dict[str, object]] = {} - if "n" in filtered_params and "n" not in optional_params: + if "n" in filtered_params and "n" not in already_mapped: mapped_params["sampleCount"] = filtered_params["n"] - if "size" in filtered_params and "size" not in optional_params: + size_param: Final = filtered_params.get("size") + if isinstance(size_param, str) and "size" not in already_mapped: image_config: Final = map_openai_size_to_gemini_image_config( - filtered_params["size"], + size_param, model, ) if image_config is not None: @@ -156,33 +167,30 @@ def map_openai_image_params_to_gemini( if "imageSize" in image_config: mapped_params["imageSize"] = image_config["imageSize"] - image_config_param = filtered_params.get("imageConfig") - if isinstance(image_config_param, str) and parse_image_config_string: - try: - image_config_param = json.loads(image_config_param) - except json.JSONDecodeError as exc: - raise litellm.UnsupportedParamsError( - model=model, - message="`imageConfig` must be valid JSON when provided as a string.", - ) from exc + raw_image_config: Final = filtered_params.get("imageConfig") + image_config_param: Final[object] = ( + _parse_image_config_string(raw_image_config, model) + if isinstance(raw_image_config, str) and parse_image_config_string + else raw_image_config + ) if isinstance(image_config_param, dict): mapped_params["imageConfig"] = image_config_param for key, value in filtered_params.items(): - if key not in ("n", "size", "imageConfig", "tools", "web_search_options") and key not in optional_params: + if key not in ("n", "size", "imageConfig", "tools", "web_search_options") and key not in already_mapped: mapped_params[key] = value return mapped_params -def _dedupe_gemini_search_tools(tools: list[dict[str, Any]]) -> list[dict[str, Any]]: +def _dedupe_gemini_search_tools(tools: list[dict[str, object]]) -> list[dict[str, object]]: from litellm.llms.vertex_ai.gemini.vertex_and_google_ai_studio_gemini import ( VertexGeminiConfig, ) search_tool_keys: Final = VertexGeminiConfig._search_tool_keys() seen_search_keys: Final[set[str]] = set() - deduped_tools: Final[list[dict[str, Any]]] = [] + deduped_tools: Final[list[dict[str, object]]] = [] for tool in tools: if not isinstance(tool, dict): @@ -203,7 +211,7 @@ def _dedupe_gemini_search_tools(tools: list[dict[str, Any]]) -> list[dict[str, A return deduped_tools -def _has_gemini_search_tool(tools: list[Any]) -> bool: +def _has_gemini_search_tool(tools: list[object]) -> bool: from litellm.llms.vertex_ai.gemini.vertex_and_google_ai_studio_gemini import ( VertexGeminiConfig, ) @@ -213,9 +221,9 @@ def _has_gemini_search_tool(tools: list[Any]) -> bool: def map_gemini_image_tools_params( - non_default_params: dict[str, Any], - mapped_params: dict[str, Any], -) -> dict[str, Any]: + non_default_params: Mapping[str, object], + mapped_params: Mapping[str, object], +) -> dict[str, object]: from litellm.llms.vertex_ai.gemini.vertex_and_google_ai_studio_gemini import ( VertexGeminiConfig, ) @@ -239,21 +247,24 @@ def map_gemini_image_tools_params( gemini_config._drop_search_tools_mixed_with_functions(result) - if isinstance(result.get("tools"), list): - result["tools"] = _dedupe_gemini_search_tools(result["tools"]) + resolved_tools: Final = result.get("tools") + if isinstance(resolved_tools, list): + result["tools"] = _dedupe_gemini_search_tools(resolved_tools) return result def get_gemini_image_web_search_requests( - response_data: dict[str, Any], + response_data: Mapping[str, object], ) -> int | None: from litellm.llms.vertex_ai.gemini.vertex_and_google_ai_studio_gemini import ( VertexGeminiConfig, ) - grounding_metadata: Final[list[dict[str, Any]]] = [] - for candidate in response_data.get("candidates", []): + raw_candidates: Final = response_data.get("candidates") + candidates: Final[list[object]] = raw_candidates if isinstance(raw_candidates, list) else [] + grounding_metadata: Final[list[dict[str, object]]] = [] + for candidate in candidates: if not isinstance(candidate, dict): continue candidate_grounding = candidate.get("groundingMetadata") @@ -267,13 +278,14 @@ def get_gemini_image_web_search_requests( def get_gemini_image_generation_config( model: str, - optional_params: dict[str, Any], -) -> dict[str, Any]: - generation_config: Final[dict[str, Any]] = {"response_modalities": ["IMAGE", "TEXT"]} + optional_params: Mapping[str, object], +) -> dict[str, object]: + generation_config: Final[dict[str, object]] = {"response_modalities": ["IMAGE", "TEXT"]} - image_config: Final[dict[str, Any]] = {} - if isinstance(optional_params.get("imageConfig"), dict): - image_config.update(optional_params["imageConfig"]) + raw_image_config: Final = optional_params.get("imageConfig") + image_config: Final[dict[str, object]] = {} + if isinstance(raw_image_config, dict): + image_config.update(raw_image_config) if not supports_gemini_image_size(model): image_config.pop("imageSize", None) @@ -398,7 +410,7 @@ class GeminiModelInfo(BaseLLMModelInfo): f"Failed to fetch models from Gemini. Status code: {response.status_code}, Response: {response.json()}" ) - models: Final = response.json()["models"] + models: Final[list[dict[str, str]]] = response.json()["models"] litellm_model_names: Final = self.process_model_name(models) return litellm_model_names @@ -473,12 +485,12 @@ class GoogleAIStudioTokenCounter(BaseTokenCounter): async def count_tokens( self, model_to_use: str, - messages: list[dict[str, Any]] | None, - contents: list[dict[str, Any]] | None, + messages: list[dict[str, object]] | None, + contents: list[dict[str, object]] | None, deployment: dict[str, Any] | None = None, request_model: str = "", - tools: list[dict[str, Any]] | None = None, - system: Any | None = None, + tools: list[dict[str, object]] | None = None, + system: object | None = None, ) -> TokenCountResponse | None: import copy diff --git a/litellm/llms/gemini/files/transformation.py b/litellm/llms/gemini/files/transformation.py index dee83407cb5..2c62e04c5a3 100644 --- a/litellm/llms/gemini/files/transformation.py +++ b/litellm/llms/gemini/files/transformation.py @@ -5,11 +5,13 @@ For vertex ai, check out the vertex_ai/files/handler.py file. """ import time -from typing import Any, Final, Literal +from collections.abc import Mapping +from typing import Final, Literal, TypedDict from urllib.parse import urlparse import httpx from openai.types.file_deleted import FileDeleted +from typing_extensions import ReadOnly, Required from litellm._logging import verbose_logger from litellm.litellm_core_utils.prompt_templates.common_utils import extract_file_data @@ -18,7 +20,6 @@ from litellm.llms.base_llm.files.transformation import ( BaseFilesConfig, LiteLLMLoggingObj, ) -from litellm.types.llms.gemini import GeminiCreateFilesResponseObject from litellm.types.llms.openai import ( AllMessageValues, CreateFileRequest, @@ -31,6 +32,25 @@ from litellm.types.utils import LlmProviders from ..common_utils import GeminiModelInfo +class _GeminiFileMetadata(TypedDict, total=False): + name: ReadOnly[str] + uri: ReadOnly[Required[str]] + displayName: ReadOnly[Required[str]] + mimeType: ReadOnly[str] + sizeBytes: ReadOnly[Required[str]] + createTime: ReadOnly[Required[str]] + updateTime: ReadOnly[str] + expirationTime: ReadOnly[str] + sha256Hash: ReadOnly[str] + state: ReadOnly[str] + source: ReadOnly[str] + error: ReadOnly[Mapping[str, object]] + + +class _GeminiCreateFileResponse(TypedDict): + file: ReadOnly[_GeminiFileMetadata] + + class GoogleAIStudioFilesHandler(GeminiModelInfo, BaseFilesConfig): def __init__(self): pass @@ -41,14 +61,14 @@ class GoogleAIStudioFilesHandler(GeminiModelInfo, BaseFilesConfig): def validate_environment( self, - headers: dict[Any, Any], + headers: dict[str, str], model: str, messages: list[AllMessageValues], - optional_params: dict[Any, Any], - litellm_params: dict[Any, Any], + optional_params: dict[str, object], + litellm_params: dict[str, object], api_key: str | None = None, api_base: str | None = None, - ) -> dict[Any, Any]: + ) -> dict[str, str]: """ Validate environment and add Gemini API key to headers. Google AI Studio uses x-goog-api-key header for authentication. @@ -164,9 +184,9 @@ class GoogleAIStudioFilesHandler(GeminiModelInfo, BaseFilesConfig): Transform Gemini's file upload response into OpenAI-style FileObject """ try: - response_json: Final = raw_response.json() + response_json: Final[_GeminiCreateFileResponse] = raw_response.json() - response_object: Final = GeminiCreateFilesResponseObject(**response_json.get("file", {})) + response_object: Final = response_json["file"] # Extract file information from Gemini response @@ -262,7 +282,7 @@ class GoogleAIStudioFilesHandler(GeminiModelInfo, BaseFilesConfig): """ try: verbose_logger.debug("Retrieve file response: %s", raw_response.text) - response_json: Final = raw_response.json() + response_json: Final[_GeminiFileMetadata] = raw_response.json() verbose_logger.debug("Response JSON: %s", response_json) # Map Gemini state to OpenAI status gemini_state: Final = response_json.get("state", "STATE_UNSPECIFIED") diff --git a/litellm/llms/gemini/realtime/transformation.py b/litellm/llms/gemini/realtime/transformation.py index 367619db37d..c92af7de145 100644 --- a/litellm/llms/gemini/realtime/transformation.py +++ b/litellm/llms/gemini/realtime/transformation.py @@ -7,6 +7,8 @@ from collections import OrderedDict from collections.abc import Mapping, Sequence from typing import Any, Final, cast +from typing_extensions import ReadOnly, Required, TypedDict + import litellm from litellm import verbose_logger from litellm._uuid import uuid @@ -96,6 +98,23 @@ def _gemini_live_speech_config(voice: object) -> Mapping[str, object] | None: return VertexGeminiConfig()._map_audio_params({"voice": voice}) +class _GeminiLiveSetupEnvelope(TypedDict, total=False): + setup: ReadOnly[BidiGenerateContentSetup] + + +class _OpenAIRealtimeClientEvent(TypedDict, total=False): + type: ReadOnly[str] + audio: ReadOnly[Required[str]] + session: ReadOnly[dict[str, object]] + item: ReadOnly[dict[str, object]] + + +def _parse_setup(session_configuration_request: str) -> BidiGenerateContentSetup: + envelope: Final[_GeminiLiveSetupEnvelope] = json.loads(session_configuration_request) + empty_setup: Final[BidiGenerateContentSetup] = {} + return envelope.get("setup", empty_setup) + + # Google bills Live transcription at an estimated 25 audio tokens/sec of input and # 175 text tokens/min of output (ai.google.dev/gemini-api/docs/pricing). GEMINI_LIVE_TRANSCRIBE_AUDIO_TOKENS_PER_SECOND: Final = 25 @@ -130,7 +149,7 @@ class GeminiRealtimeConfig(BaseRealtimeConfig): return True @staticmethod - def _usage_detail_alias(details: Any, defaults: dict[str, int]) -> dict[str, Any]: + def _usage_detail_alias(details: Mapping[str, int | None] | None, defaults: dict[str, int]) -> dict[str, int]: if not isinstance(details, dict): return dict(defaults) return { @@ -139,7 +158,7 @@ class GeminiRealtimeConfig(BaseRealtimeConfig): } @staticmethod - def _add_pipecat_usage_detail_aliases(usage_dict: dict[str, Any]) -> dict[str, Any]: + def _add_pipecat_usage_detail_aliases(usage_dict: dict[str, Any]) -> dict[str, object]: usage_dict.setdefault( "input_token_details", GeminiRealtimeConfig._usage_detail_alias( @@ -222,8 +241,10 @@ class GeminiRealtimeConfig(BaseRealtimeConfig): if not session_configuration_request: return False try: - setup: Final = json.loads(session_configuration_request).get("setup", {}) - automatic_detection: Final = setup.get("realtimeInputConfig", {}).get("automaticActivityDetection", {}) + setup: Final = _parse_setup(session_configuration_request) + automatic_detection: Final[object] = setup.get("realtimeInputConfig", {}).get( + "automaticActivityDetection", {} + ) return isinstance(automatic_detection, dict) and automatic_detection.get("disabled") is True except (json.JSONDecodeError, TypeError, AttributeError): return False @@ -406,7 +427,7 @@ class GeminiRealtimeConfig(BaseRealtimeConfig): return "TEXT" if GeminiRealtimeConfig._is_text_only_live_model(model) else "AUDIO" @staticmethod - def _coerce_response_modalities(model: str, modalities: Sequence[Any]) -> tuple[str, ...]: + def _coerce_response_modalities(model: str, modalities: Sequence[object]) -> tuple[str, ...]: """Swap responseModalities a Live model cannot produce: TEXT to AUDIO for audio-only models, AUDIO to TEXT for text-only ones (e.g. transcribe-live).""" normalized: Final = tuple( @@ -431,7 +452,7 @@ class GeminiRealtimeConfig(BaseRealtimeConfig): def _handle_session_update( self, - json_message: dict, + json_message: _OpenAIRealtimeClientEvent, model: str, session_configuration_request: str | None, ) -> list[str]: @@ -445,7 +466,8 @@ class GeminiRealtimeConfig(BaseRealtimeConfig): with a 1007, tearing the session down). To carry tools/instructions, send them on the first session.update before any conversation content. """ - session_payload = json_message.get("session") or {} + empty_session: Final[dict[str, object]] = {} + session_payload = json_message.get("session") or empty_session # Normalize GA-remapped fields (``output_modalities``, # nested ``audio.input.transcription``, # ``audio.input.turn_detection``) back to their flat beta keys so @@ -486,14 +508,15 @@ class GeminiRealtimeConfig(BaseRealtimeConfig): verbose_logger.debug("Gemini Realtime: Ignoring session.update (setup already sent)") return [] - def _handle_conversation_item(self, json_message: dict) -> list[str]: + def _handle_conversation_item(self, json_message: _OpenAIRealtimeClientEvent) -> list[str]: """ Handle conversation.item.create for user text or function call output. Converts OpenAI format to Gemini's clientContent (for user text) or toolResponse (for function outputs). """ - item: Final = json_message.get("item", {}) + empty_item: Final[dict[str, object]] = {} + item: Final = json_message.get("item", empty_item) item_type: Final = item.get("type") if item_type == "function_call_output": @@ -524,7 +547,7 @@ class GeminiRealtimeConfig(BaseRealtimeConfig): call_id, ) - function_response: Final[dict[str, Any]] = {"response": output_dict} + function_response: Final[dict[str, object]] = {"response": output_dict} if self._include_function_response_id() and call_id: function_response["id"] = call_id if function_name: @@ -559,7 +582,7 @@ class GeminiRealtimeConfig(BaseRealtimeConfig): ) -> list[str]: realtime_input_dict: BidiGenerateContentRealtimeInput = {} try: - json_message: Final = json.loads(message) + json_message: Final[_OpenAIRealtimeClientEvent] = json.loads(message) except json.JSONDecodeError: if isinstance(message, bytes): message_str = message.decode("utf-8", errors="replace") @@ -610,9 +633,7 @@ class GeminiRealtimeConfig(BaseRealtimeConfig): session_configuration_request: str | None = None, ) -> OpenAIRealtimeStreamSessionEvents: if session_configuration_request: - session_configuration_request_dict: BidiGenerateContentSetup = json.loads( - session_configuration_request - ).get("setup", {}) + session_configuration_request_dict: BidiGenerateContentSetup = _parse_setup(session_configuration_request) else: session_configuration_request_dict = {} @@ -663,7 +684,7 @@ class GeminiRealtimeConfig(BaseRealtimeConfig): session_configuration_request_dict: BidiGenerateContentSetup = {} if session_configuration_request is not None: try: - session_configuration_request_dict = json.loads(session_configuration_request).get("setup", {}) + session_configuration_request_dict = _parse_setup(session_configuration_request) except json.JSONDecodeError: session_configuration_request_dict = {} generation_config: Final = session_configuration_request_dict.get("generationConfig", {}) @@ -931,9 +952,9 @@ class GeminiRealtimeConfig(BaseRealtimeConfig): return events @staticmethod - def get_nested_value(obj: dict, path: str) -> Any: + def get_nested_value(obj: dict, path: str) -> object | None: keys: Final = path.split(".") - current = obj + current: object = obj for key in keys: if isinstance(current, dict) and key in current: current = current[key] @@ -1011,9 +1032,7 @@ class GeminiRealtimeConfig(BaseRealtimeConfig): current_response_id = f"resp_{uuid.uuid4()}" if session_configuration_request: - session_configuration_request_dict: BidiGenerateContentSetup = json.loads( - session_configuration_request - ).get("setup", {}) + session_configuration_request_dict: BidiGenerateContentSetup = _parse_setup(session_configuration_request) else: session_configuration_request_dict = {} @@ -1337,7 +1356,7 @@ class GeminiRealtimeConfig(BaseRealtimeConfig): session_setup: BidiGenerateContentSetup = {} if session_configuration_request is not None: try: - session_setup = json.loads(session_configuration_request).get("setup", {}) + session_setup = _parse_setup(session_configuration_request) except (json.JSONDecodeError, TypeError): session_setup = {} tool_call_generation_config = session_setup.get("generationConfig", {}) or {} diff --git a/litellm/llms/hosted_vllm/embedding/README.md b/litellm/llms/hosted_vllm/embedding/README.md index 2c58e16fc23..50474aabdeb 100644 --- a/litellm/llms/hosted_vllm/embedding/README.md +++ b/litellm/llms/hosted_vllm/embedding/README.md @@ -4,13 +4,12 @@ VLLM is a superset of OpenAI's `embedding` endpoint. ## `encoding_format` -For OpenAI-compatible embedding calls (including `openai/...` with a custom `api_base` pointing at vLLM), LiteLLM resolves `encoding_format` when it is not set on the request: +For OpenAI-compatible embedding calls (including `openai/...` with a custom `api_base` pointing at vLLM), LiteLLM resolves `encoding_format` when it is not set on the request. `hosted_vllm/...` models use a separate handler that never adds the field on its own, so this resolution applies to the `openai/...`-style routes only: 1. Explicit value on the embedding call (`encoding_format=...`). 2. Model config (`litellm_params.encoding_format` on the proxy `model_list` entry). 3. Environment variable `LITELLM_DEFAULT_EMBEDDING_ENCODING_FORMAT` (e.g. in `.env` or container env). -4. Default **`float`**. -That avoids forwarding `encoding_format=None` to the provider/SDK where some servers behave poorly. +If none of those is set, or the winning value is the literal string `none`, the field is omitted from the upstream request entirely (LiteLLM also bypasses the OpenAI SDK's own base64 default), so OpenAI-compatible servers that reject `encoding_format` keep working. -To pass provider-specific parameters, see [provider-specific params](https://docs.litellm.ai/docs/completion/provider_specific_params). \ No newline at end of file +To pass provider-specific parameters, see [provider-specific params](https://docs.litellm.ai/docs/completion/provider_specific_params). diff --git a/litellm/llms/litellm_proxy/skills/code_execution.py b/litellm/llms/litellm_proxy/skills/code_execution.py index f51213ca1c3..fbc287589b3 100644 --- a/litellm/llms/litellm_proxy/skills/code_execution.py +++ b/litellm/llms/litellm_proxy/skills/code_execution.py @@ -13,55 +13,109 @@ Generated files are returned directly in the response - no separate storage need import base64 import json -from collections.abc import Sequence +from collections.abc import Mapping, Sequence from enum import Enum -from typing import Any, Final, Protocol +from typing import Any, Final, Protocol, TypedDict -from typing_extensions import NotRequired, ReadOnly, TypedDict +from typing_extensions import ReadOnly from litellm._logging import verbose_logger -class _ToolCallFunction(Protocol): - """Function payload of an assistant tool call.""" - - name: str | None - arguments: str +class _ToolParameterSchema(TypedDict, total=False): + type: ReadOnly[str] + description: ReadOnly[str] -class _ToolCall(Protocol): - """Tool call requested by the assistant on a chat completion choice.""" - - id: str - function: _ToolCallFunction +class _ToolArgumentSchema(TypedDict, total=False): + type: ReadOnly[str] + properties: ReadOnly[Mapping[str, _ToolParameterSchema]] + required: ReadOnly[Sequence[str]] -class _AssistantMessage(Protocol): - """Assistant message carried by a chat completion choice.""" - - content: str | None - tool_calls: Sequence[_ToolCall] | None +class _OpenAIToolFunction(TypedDict, total=False): + name: ReadOnly[str] + description: ReadOnly[str] + parameters: ReadOnly[_ToolArgumentSchema] -class _CompletionChoice(Protocol): - """Single choice of a chat completion response.""" - - finish_reason: str - message: _AssistantMessage +class _OpenAIToolSpec(TypedDict, total=False): + type: ReadOnly[str] + function: ReadOnly[_OpenAIToolFunction] -class _SandboxFile(TypedDict): - """File generated inside the sandbox during a code execution run.""" +class _AnthropicToolSpec(TypedDict, total=False): + name: ReadOnly[str] + description: ReadOnly[str] + input_schema: ReadOnly[_ToolArgumentSchema] + +class _CodeExecutionArguments(TypedDict, total=False): + code: ReadOnly[str] + + +class _GeneratedFile(TypedDict, total=False): + name: ReadOnly[str] + mime_type: ReadOnly[str] + content_base64: ReadOnly[str] + size: ReadOnly[int] + + +class _SandboxGeneratedFile(TypedDict): name: ReadOnly[str] mime_type: ReadOnly[str] content_base64: ReadOnly[str] -class _CodeExecutionArguments(TypedDict): - """Arguments the model passes to the `litellm_code_execution` tool.""" +class _SandboxExecutionResult(TypedDict): + success: ReadOnly[bool] + output: ReadOnly[str] + error: ReadOnly[str] + files: ReadOnly[Sequence[_SandboxGeneratedFile]] - code: NotRequired[ReadOnly[str]] + +class _ExecutionResult(TypedDict, total=False): + iteration: ReadOnly[int] + success: ReadOnly[bool] + output: ReadOnly[str] + error: ReadOnly[str] + files: ReadOnly[Sequence[str]] + + +class _ToolCallFunction(Protocol): + name: str + arguments: str + + +class _ToolCall(Protocol): + id: str + function: _ToolCallFunction + + +class _AssistantMessage(Protocol): + content: str | None + tool_calls: Sequence[_ToolCall] | None + + +class _ResponseChoice(Protocol): + message: _AssistantMessage + finish_reason: str | None + + +class _CompletionResponse(Protocol): + choices: Sequence[_ResponseChoice] + + +class _CodeExecutionOutcome(TypedDict, total=False): + response: ReadOnly[_CompletionResponse | None] + files: ReadOnly[Sequence[_GeneratedFile]] + execution_results: ReadOnly[Sequence[_ExecutionResult]] + messages: ReadOnly[Sequence[dict[str, object]]] + max_iterations_reached: ReadOnly[bool] + + +def _parse_code_execution_arguments(serialized_arguments: str) -> _CodeExecutionArguments: + return json.loads(serialized_arguments) class LiteLLMInternalTools(str, Enum): @@ -75,7 +129,7 @@ class LiteLLMInternalTools(str, Enum): CODE_EXECUTION = "litellm_code_execution" -def get_litellm_code_execution_tool() -> dict[str, object]: +def get_litellm_code_execution_tool() -> _OpenAIToolSpec: """ Returns the litellm_code_execution tool definition in OpenAI format. @@ -96,7 +150,7 @@ def get_litellm_code_execution_tool() -> dict[str, object]: } -def get_litellm_code_execution_tool_anthropic() -> dict[str, object]: +def get_litellm_code_execution_tool_anthropic() -> _AnthropicToolSpec: """ Returns the litellm_code_execution tool definition in Anthropic/messages API format. @@ -143,12 +197,12 @@ class CodeExecutionHandler: async def execute_with_code_execution( self, model: str, - messages: list[dict], - tools: list[dict], + messages: list[dict[str, object]], + tools: list[_OpenAIToolSpec], skill_files: dict[str, bytes], skill_id: str | None = None, **kwargs, - ) -> dict[str, object]: + ) -> _CodeExecutionOutcome: """ Execute an LLM call with automatic code execution handling. @@ -179,8 +233,8 @@ class CodeExecutionHandler: ) current_messages: Final = list(messages) - generated_files: Final[list[dict[str, object]]] = [] # Files returned directly - execution_results: Final[list[dict[str, object]]] = [] + generated_files: Final[list[_GeneratedFile]] = [] # Files returned directly + execution_results: Final[list[_ExecutionResult]] = [] executor: Final = SkillsSandboxExecutor(timeout=self.sandbox_timeout) response: Any = None # Initialize to avoid possibly unbound error @@ -196,9 +250,9 @@ class CodeExecutionHandler: **kwargs, ) - choice: _CompletionChoice = response.choices[0] + choice: _ResponseChoice = response.choices[0] assistant_message = choice.message - stop_reason: str = choice.finish_reason + stop_reason = choice.finish_reason # Build assistant message for conversation history assistant_msg_dict: dict[str, object] = { @@ -236,19 +290,19 @@ class CodeExecutionHandler: if tool_name == LiteLLMInternalTools.CODE_EXECUTION.value: # Execute code in sandbox try: - args: _CodeExecutionArguments = json.loads(tool_call.function.arguments) - code: str = args.get("code", "") + args = _parse_code_execution_arguments(tool_call.function.arguments) + code = args.get("code", "") verbose_logger.debug("CodeExecutionHandler: Executing code (%s chars)", len(code)) - exec_result = executor.execute( + exec_result: _SandboxExecutionResult = executor.execute( code=code, skill_files=skill_files, ) verbose_logger.debug("CodeExecutionHandler: Execution result: %s", exec_result) - sandbox_files: Sequence[_SandboxFile] = exec_result["files"] + sandbox_files: Sequence[_SandboxGeneratedFile] = exec_result["files"] execution_results.append( { @@ -326,7 +380,7 @@ class CodeExecutionHandler: } -def has_code_execution_tool(tools: list[dict] | None) -> bool: +def has_code_execution_tool(tools: list[_OpenAIToolSpec] | None) -> bool: """Check if litellm_code_execution tool is in the tools list.""" if not tools: return False @@ -337,7 +391,7 @@ def has_code_execution_tool(tools: list[dict] | None) -> bool: return False -def add_code_execution_tool(tools: list[dict] | None) -> list[dict]: +def add_code_execution_tool(tools: list[_OpenAIToolSpec] | None) -> list[_OpenAIToolSpec]: """Add litellm_code_execution tool if not already present.""" tools = tools or [] if not has_code_execution_tool(tools): diff --git a/litellm/llms/nvidia_riva/audio_transcription/audio_utils.py b/litellm/llms/nvidia_riva/audio_transcription/audio_utils.py index 008a5a5780f..046b4e29a0a 100644 --- a/litellm/llms/nvidia_riva/audio_transcription/audio_utils.py +++ b/litellm/llms/nvidia_riva/audio_transcription/audio_utils.py @@ -16,7 +16,7 @@ import io import os import tempfile from dataclasses import dataclass -from typing import Any, Final, cast +from typing import Final, Protocol, cast from litellm.llms.nvidia_riva.audio_transcription.transformation import ( RIVA_TARGET_NUM_CHANNELS, @@ -24,10 +24,30 @@ from litellm.llms.nvidia_riva.audio_transcription.transformation import ( ) from litellm.llms.nvidia_riva.common_utils import NvidiaRivaException -# Keep this as Any: the module intentionally avoids importing numpy at module -# import time (optional dependency), and project-wide mypy config evaluates this -# file in contexts where conditional type aliases can degrade to "FloatArray?". -FloatArray = Any + +class FloatArray(Protocol): + """Structural view of the ``numpy.ndarray`` surface this module relies on.""" + + @property + def ndim(self) -> int: ... + + @property + def shape(self) -> tuple[int, ...]: ... + + @property + def size(self) -> int: ... + + def mean(self, axis: int) -> "FloatArray": ... + + def ravel(self) -> "FloatArray": ... + + def astype(self, dtype: object) -> "FloatArray": ... + + def tobytes(self) -> bytes: ... + + def __getitem__(self, key: object) -> "FloatArray": ... + + def __mul__(self, other: float) -> "FloatArray": ... _INSTALL_HINT = "Install Riva STT extras to enable automatic audio resampling: `pip install 'litellm[stt-nvidia-riva]'`" diff --git a/litellm/llms/oci/common_utils.py b/litellm/llms/oci/common_utils.py index 5c3962bc05d..3f703564b5a 100644 --- a/litellm/llms/oci/common_utils.py +++ b/litellm/llms/oci/common_utils.py @@ -5,10 +5,11 @@ import os import re from dataclasses import dataclass from email.utils import formatdate -from typing import Any, Final, Protocol +from typing import Final, Protocol from urllib.parse import urlparse import httpx +from pydantic import JsonValue from litellm.llms.base_llm.chat.transformation import BaseLLMException @@ -64,7 +65,7 @@ class OCISignerProtocol(Protocol): See: https://docs.oracle.com/en-us/iaas/tools/python/latest/api/signing.html """ - def do_request_sign(self, request: Any, *, enforce_content_headers: bool = False) -> None: + def do_request_sign(self, request: "OCIRequestWrapper", *, enforce_content_headers: bool = False) -> None: pass @@ -113,7 +114,7 @@ def build_signature_string(method: str, path: str, headers: dict, signed_headers return "\n".join(lines) -def load_private_key_from_str(key_str: str) -> Any: +def load_private_key_from_str(key_str: str) -> "rsa.RSAPrivateKey": _require_cryptography() key: Final = serialization.load_pem_private_key( key_str.encode("utf-8"), @@ -124,7 +125,7 @@ def load_private_key_from_str(key_str: str) -> Any: return key -def load_private_key_from_file(file_path: str) -> Any: +def load_private_key_from_file(file_path: str) -> "rsa.RSAPrivateKey": """Loads a private key from a file path.""" try: with open(file_path, "r", encoding="utf-8") as f: @@ -421,16 +422,17 @@ OCI_JSON_TO_PYTHON_TYPES: Final[dict[str, str]] = { } -def resolve_oci_schema_refs(schema: dict[str, Any]) -> dict[str, Any]: +def resolve_oci_schema_refs(schema: JsonValue) -> JsonValue: """Inline all ``$ref``/``$defs`` references — OCI does not support JSON Schema ``$ref``.""" - defs: Final = schema.get("$defs", {}) - resolving_stack: Final[set] = set() + raw_defs: Final = schema.get("$defs") if isinstance(schema, dict) else None + defs: Final[dict[str, JsonValue]] = raw_defs if isinstance(raw_defs, dict) else {} + resolving_stack: Final[set[str]] = set() - def _resolve(obj: Any) -> Any: + def _resolve(obj: JsonValue) -> JsonValue: if isinstance(obj, dict): - if "$ref" in obj: - ref: Final = obj["$ref"] - if ref.startswith("#/$defs/"): + ref: Final = obj.get("$ref") + if ref is not None: + if isinstance(ref, str) and ref.startswith("#/$defs/"): key: Final = ref.split("/")[-1] if key in resolving_stack: return {"type": "object"} # break cycles @@ -451,7 +453,7 @@ def resolve_oci_schema_refs(schema: dict[str, Any]) -> dict[str, Any]: return resolved -def resolve_oci_schema_anyof(obj: Any) -> Any: +def resolve_oci_schema_anyof(obj: JsonValue) -> JsonValue: """Resolve Pydantic v2 ``Optional[T]`` → ``anyOf`` patterns. Pydantic v2 emits ``{"anyOf": [{"type": "T"}, {"type": "null"}]}`` for @@ -459,10 +461,13 @@ def resolve_oci_schema_anyof(obj: Any) -> Any: first non-null branch and merge top-level metadata into it. """ if isinstance(obj, dict): - if "anyOf" in obj and "type" not in obj: - non_null: Final = [t for t in obj["anyOf"] if not (isinstance(t, dict) and t.get("type") == "null")] + raw_any_of: Final = obj.get("anyOf") + if raw_any_of is not None and "type" not in obj: + branches: Final = raw_any_of if isinstance(raw_any_of, list) else [] + non_null: Final = [t for t in branches if not (isinstance(t, dict) and t.get("type") == "null")] if non_null: - resolved: Final = {**obj, **non_null[0]} + first: Final = non_null[0] + resolved: Final[dict[str, JsonValue]] = {**obj, **first} if isinstance(first, dict) else {**obj} resolved.pop("anyOf", None) return resolve_oci_schema_anyof(resolved) return {k: resolve_oci_schema_anyof(v) for k, v in obj.items()} @@ -471,7 +476,7 @@ def resolve_oci_schema_anyof(obj: Any) -> Any: return obj -def sanitize_oci_schema(schema: Any) -> Any: +def sanitize_oci_schema(schema: JsonValue) -> JsonValue: """Recursively remove OCI-incompatible fields from a JSON schema. Strips ``title`` keys, removes ``None``-valued ``default`` entries, @@ -483,7 +488,7 @@ def sanitize_oci_schema(schema: Any) -> Any: if not isinstance(schema, dict): return schema - sanitized: Final[dict[str, Any]] = {} + sanitized: Final[dict[str, JsonValue]] = {} for key, value in schema.items(): if key == "title": continue @@ -513,7 +518,7 @@ def sanitize_oci_schema(schema: Any) -> Any: return sanitized -def enrich_cohere_param_description(description: str, param_schema: dict[str, Any]) -> str: +def enrich_cohere_param_description(description: str, param_schema: dict[str, JsonValue]) -> str: """Embed schema constraints into a Cohere parameter description. ``CohereParameterDefinition`` only has ``type``, ``description``, and diff --git a/litellm/llms/openai/chat/gpt_transformation.py b/litellm/llms/openai/chat/gpt_transformation.py index 5894658e5d2..d4747b2fb06 100644 --- a/litellm/llms/openai/chat/gpt_transformation.py +++ b/litellm/llms/openai/chat/gpt_transformation.py @@ -170,16 +170,20 @@ class OpenAIGPTConfig(BaseLLMModelInfo, BaseConfig): if model != "gpt-3.5-turbo-16k" and model != "gpt-4": # gpt-4 does not support 'response_format' model_specific_params.append("response_format") - # Normalize model name for responses API (e.g., "responses/gpt-4.1" -> "gpt-4.1") - model_for_check: Final = model.split("responses/", 1)[1] if "responses/" in model else model - if ( - model_for_check in litellm.open_ai_chat_completion_models - ) or model_for_check in litellm.open_ai_text_completion_models: + if OpenAIGPTConfig.is_openai_catalog_model(model): model_specific_params.append( "user" ) # user is not a param supported by all openai-compatible endpoints - e.g. azure ai return base_params + model_specific_params + @staticmethod + def is_openai_catalog_model(model: str) -> bool: + model_for_check: Final = model.split("responses/", 1)[1] if "responses/" in model else model + return ( + model_for_check in litellm.open_ai_chat_completion_models + or model_for_check in litellm.open_ai_text_completion_models + ) + def _map_openai_params( self, non_default_params: dict, @@ -755,6 +759,14 @@ class OpenAIGPTConfig(BaseLLMModelInfo, BaseConfig): ) +class OpenAIUnknownModelConfig(OpenAIGPTConfig): + """A model the openai provider does not recognize is typically a LiteLLM proxy alias, so + forward reasoning_effort and let the server decide whether it is supported.""" + + def get_supported_openai_params(self, model: str) -> list: # mutable-ok: inherited contract + return super().get_supported_openai_params(model) + ["reasoning_effort"] # mutable-ok: inherited contract + + class OpenAIChatCompletionStreamingHandler(BaseModelResponseIterator): def _map_reasoning_to_reasoning_content(self, choices: list) -> list: """ diff --git a/litellm/llms/openai/containers/transformation.py b/litellm/llms/openai/containers/transformation.py index 44bd401c115..1a5211d5ff5 100644 --- a/litellm/llms/openai/containers/transformation.py +++ b/litellm/llms/openai/containers/transformation.py @@ -155,10 +155,7 @@ class OpenAIContainerConfig(BaseContainerConfig): logging_obj: LiteLLMLoggingObj, ) -> ContainerObject: """Transform the OpenAI container creation response.""" - response_data: Final[OpenAIContainerPayload] = raw_response.json() - - # Transform the response data - container_obj: Final = ContainerObject(**response_data) + container_obj: Final = ContainerObject.model_validate(raw_response.json()) # Add cost for container creation (OpenAI containers are code interpreter sessions) # https://platform.openai.com/docs/pricing @@ -215,10 +212,7 @@ class OpenAIContainerConfig(BaseContainerConfig): logging_obj: LiteLLMLoggingObj, ) -> ContainerListResponse: """Transform the OpenAI container list response.""" - response_data: Final[OpenAIContainerListPayload] = raw_response.json() - - # Transform the response data - container_list: Final = ContainerListResponse(**response_data) + container_list: Final = ContainerListResponse.model_validate(raw_response.json()) return container_list @@ -235,7 +229,7 @@ class OpenAIContainerConfig(BaseContainerConfig): url: Final = join_container_api_base_path(api_base, f"/{encoded_container_id}") # No additional data needed for GET request - data: Final[dict[str, object]] = {} + data: Final[dict[str, str]] = {} return url, data @@ -245,9 +239,7 @@ class OpenAIContainerConfig(BaseContainerConfig): logging_obj: LiteLLMLoggingObj, ) -> ContainerObject: """Transform the OpenAI container retrieve response.""" - response_data: Final[OpenAIContainerPayload] = raw_response.json() - # Transform the response data - container_obj: Final = ContainerObject(**response_data) + container_obj: Final = ContainerObject.model_validate(raw_response.json()) return container_obj @@ -268,7 +260,7 @@ class OpenAIContainerConfig(BaseContainerConfig): url: Final = join_container_api_base_path(api_base, f"/{encoded_container_id}") # No data needed for DELETE request - data: Final[dict[str, object]] = {} + data: Final[dict[str, str]] = {} return url, data @@ -278,10 +270,7 @@ class OpenAIContainerConfig(BaseContainerConfig): logging_obj: LiteLLMLoggingObj, ) -> DeleteContainerResult: """Transform the OpenAI container delete response.""" - response_data: Final[OpenAIContainerDeletedPayload] = raw_response.json() - - # Transform the response data - delete_result: Final = DeleteContainerResult(**response_data) + delete_result: Final = DeleteContainerResult.model_validate(raw_response.json()) return delete_result @@ -326,10 +315,7 @@ class OpenAIContainerConfig(BaseContainerConfig): logging_obj: LiteLLMLoggingObj, ) -> ContainerFileListResponse: """Transform the OpenAI container file list response.""" - response_data: Final[OpenAIContainerFileListPayload] = raw_response.json() - - # Transform the response data - file_list: Final = ContainerFileListResponse(**response_data) + file_list: Final = ContainerFileListResponse.model_validate(raw_response.json()) return file_list @@ -352,7 +338,7 @@ class OpenAIContainerConfig(BaseContainerConfig): url: Final = join_container_api_base_path(api_base, f"/{encoded_container_id}/files/{encoded_file_id}/content") # No query parameters needed - params: Final[dict[str, object]] = {} + params: Final[dict[str, str]] = {} return url, params diff --git a/litellm/llms/openai/openai.py b/litellm/llms/openai/openai.py index 16fa0017b23..1cfc6e06ee9 100644 --- a/litellm/llms/openai/openai.py +++ b/litellm/llms/openai/openai.py @@ -12,9 +12,14 @@ if TYPE_CHECKING: import openai from openai import AsyncOpenAI, OpenAI +from openai._base_client import make_request_options +from openai._constants import RAW_RESPONSE_HEADER +from openai._legacy_response import LegacyAPIResponse +from openai._types import RequestOptions +from openai.types import CreateEmbeddingResponse from openai.types.beta.assistant_deleted import AssistantDeleted from openai.types.file_deleted import FileDeleted -from pydantic import BaseModel +from pydantic import BaseModel, TypeAdapter from typing_extensions import overload import litellm @@ -43,6 +48,7 @@ from litellm.utils import ( from ...types.llms.openai import * from ..base import BaseLLM from .chat.gpt_5_transformation import OpenAIGPT5Config +from .chat.gpt_transformation import OpenAIGPTConfig, OpenAIUnknownModelConfig from .chat.o_series_transformation import OpenAIOSeriesConfig from .common_utils import ( BaseOpenAILLM, @@ -189,7 +195,12 @@ class OpenAIConfig(BaseConfig): elif litellm.openAIGPTAudioConfig.is_model_gpt_audio_model(model=model): return litellm.openAIGPTAudioConfig.get_supported_openai_params(model=model) else: - return litellm.openAIGPTConfig.get_supported_openai_params(model=model) + return self._gpt_config_for_model(model).get_supported_openai_params(model=model) + + def _gpt_config_for_model(self, model: str) -> OpenAIGPTConfig: + if type(self) is OpenAIConfig and not OpenAIGPTConfig.is_openai_catalog_model(model): + return OpenAIUnknownModelConfig() + return litellm.openAIGPTConfig def _map_openai_params(self, non_default_params: dict, optional_params: dict, model: str) -> dict: supported_openai_params: Final = self.get_supported_openai_params(model) @@ -231,7 +242,7 @@ class OpenAIConfig(BaseConfig): drop_params=drop_params, ) - return litellm.openAIGPTConfig.map_openai_params( + return self._gpt_config_for_model(model).map_openai_params( non_default_params=non_default_params, optional_params=optional_params, model=model, @@ -323,6 +334,28 @@ class OpenAIChatCompletionResponseIterator(BaseModelResponseIterator): raise e +_EXTRA_HEADERS_ADAPTER: Final = TypeAdapter(dict[str, str] | None) +_EXTRA_QUERY_ADAPTER: Final = TypeAdapter(dict[str, object] | None) +_NO_EXTRA_HEADERS: Final[Mapping[str, str]] = types.MappingProxyType({}) +_SDK_OPTION_KEYS: Final = frozenset(("extra_headers", "extra_query", "extra_body")) + + +def _embedding_request_without_sdk_defaults( + data: Mapping[str, object], timeout: float | httpx.Timeout +) -> tuple[Mapping[str, object], RequestOptions]: + body: Final = { # mutable-ok: the SDK json-encodes the body and needs a plain dict + k: v for k, v in data.items() if k not in _SDK_OPTION_KEYS + } + extra_headers: Final = _EXTRA_HEADERS_ADAPTER.validate_python(data.get("extra_headers")) or _NO_EXTRA_HEADERS + options: Final = make_request_options( + extra_headers=types.MappingProxyType({**extra_headers, RAW_RESPONSE_HEADER: "true"}), + extra_query=_EXTRA_QUERY_ADAPTER.validate_python(data.get("extra_query")), + extra_body=data.get("extra_body"), + timeout=timeout, + ) + return body, options + + class OpenAIChatCompletion(BaseLLM, BaseOpenAILLM): def __init__(self) -> None: super().__init__() @@ -1171,19 +1204,15 @@ class OpenAIChatCompletion(BaseLLM, BaseOpenAILLM): data: dict, timeout: float | httpx.Timeout, logging_obj: LiteLLMLoggingObj, - ): - """ - Helper to: - - call embeddings.create.with_raw_response when litellm.return_response_headers is True - - call embeddings.create by default - """ - try: - raw_response = await openai_aclient.embeddings.with_raw_response.create(**data, timeout=timeout) - headers: Final = dict(raw_response.headers) - response: Final = raw_response.parse() - return headers, response - except Exception as e: - raise e + ) -> LegacyAPIResponse[CreateEmbeddingResponse]: + if "encoding_format" not in data: + body, options = _embedding_request_without_sdk_defaults(data, timeout) + bypass_response: Final = await openai_aclient.post( + "/embeddings", body=body, options=options, cast_to=CreateEmbeddingResponse + ) + assert isinstance(bypass_response, LegacyAPIResponse) + return bypass_response + return await openai_aclient.embeddings.with_raw_response.create(**data, timeout=timeout) @track_llm_api_timing() def make_sync_openai_embedding_request( @@ -1192,20 +1221,15 @@ class OpenAIChatCompletion(BaseLLM, BaseOpenAILLM): data: dict, timeout: float | httpx.Timeout, logging_obj: LiteLLMLoggingObj, - ): - """ - Helper to: - - call embeddings.create.with_raw_response when litellm.return_response_headers is True - - call embeddings.create by default - """ - try: - raw_response = openai_client.embeddings.with_raw_response.create(**data, timeout=timeout) - - headers: Final = dict(raw_response.headers) - response: Final = raw_response.parse() - return headers, response - except Exception as e: - raise e + ) -> LegacyAPIResponse[CreateEmbeddingResponse]: + if "encoding_format" not in data: + body, options = _embedding_request_without_sdk_defaults(data, timeout) + bypass_response: Final = openai_client.post( + "/embeddings", body=body, options=options, cast_to=CreateEmbeddingResponse + ) + assert isinstance(bypass_response, LegacyAPIResponse) + return bypass_response + return openai_client.embeddings.with_raw_response.create(**data, timeout=timeout) async def aembedding( self, @@ -1230,14 +1254,15 @@ class OpenAIChatCompletion(BaseLLM, BaseOpenAILLM): client=client, shared_session=shared_session, ) - headers, response = await self.make_openai_embedding_request( + raw_response: Final = await self.make_openai_embedding_request( openai_aclient=openai_aclient, data=data, timeout=timeout, logging_obj=logging_obj, ) + headers: Final = dict(raw_response.headers) logging_obj.model_call_details["response_headers"] = headers - stringified_response: Final = response.model_dump() + stringified_response: Final = raw_response.parse().model_dump() ## LOGGING logging_obj.post_call( input=input, @@ -1329,13 +1354,14 @@ class OpenAIChatCompletion(BaseLLM, BaseOpenAILLM): ) ## embedding CALL - headers: dict | None = None - headers, sync_embedding_response = self.make_sync_openai_embedding_request( + raw_response: Final = self.make_sync_openai_embedding_request( openai_client=openai_client, data=data, timeout=timeout, logging_obj=logging_obj, ) + headers: Final = dict(raw_response.headers) + sync_embedding_response: Final = raw_response.parse() ## LOGGING logging_obj.model_call_details["response_headers"] = headers diff --git a/litellm/llms/runwayml/text_to_speech/transformation.py b/litellm/llms/runwayml/text_to_speech/transformation.py index 1da8f0c66f0..19e6d8ff494 100644 --- a/litellm/llms/runwayml/text_to_speech/transformation.py +++ b/litellm/llms/runwayml/text_to_speech/transformation.py @@ -6,10 +6,11 @@ Maps OpenAI TTS spec to RunwayML Text-to-Speech API import asyncio import time -from collections.abc import Coroutine -from typing import TYPE_CHECKING, Any, Final, Union +from collections.abc import Coroutine, Sequence +from typing import TYPE_CHECKING, Any, Final, TypedDict, Union import httpx +from typing_extensions import ReadOnly import litellm from litellm._logging import verbose_logger @@ -31,6 +32,14 @@ else: HttpxBinaryResponseContent = Any +class _RunwayTtsTaskResponse(TypedDict, total=False): + id: ReadOnly[str] + status: ReadOnly[str] + output: ReadOnly[Sequence[object]] + failure: ReadOnly[str] + failureCode: ReadOnly[str] + + class RunwayMLTextToSpeechConfig(BaseTextToSpeechConfig): """ Configuration for RunwayML Text-to-Speech @@ -64,7 +73,7 @@ class RunwayMLTextToSpeechConfig(BaseTextToSpeechConfig): litellm_params_dict: dict, logging_obj: "LiteLLMLoggingObj", timeout: float | httpx.Timeout, - extra_headers: dict[str, Any] | None, + extra_headers: dict[str, object] | None, base_llm_http_handler: Any, aspeech: bool, api_base: str | None, @@ -72,7 +81,7 @@ class RunwayMLTextToSpeechConfig(BaseTextToSpeechConfig): **kwargs: Any, ) -> Union[ "HttpxBinaryResponseContent", - Coroutine[Any, Any, "HttpxBinaryResponseContent"], + Coroutine[object, object, "HttpxBinaryResponseContent"], ]: """ Dispatch method to handle RunwayML TTS requests @@ -242,7 +251,7 @@ class RunwayMLTextToSpeechConfig(BaseTextToSpeechConfig): raise TimeoutError(f"RunwayML TTS task polling timed out after {timeout_secs} seconds") @staticmethod - def _check_task_status(response_data: dict[str, Any]) -> str: + def _check_task_status(response_data: _RunwayTtsTaskResponse) -> str: """ Check RunwayML task status from response. @@ -314,7 +323,7 @@ class RunwayMLTextToSpeechConfig(BaseTextToSpeechConfig): response = client.get(url=task_url, headers=headers) response.raise_for_status() - response_data = response.json() + response_data: _RunwayTtsTaskResponse = response.json() # Check task status status = self._check_task_status(response_data=response_data) @@ -362,7 +371,7 @@ class RunwayMLTextToSpeechConfig(BaseTextToSpeechConfig): response = await client.get(url=task_url, headers=headers) response.raise_for_status() - response_data = response.json() + response_data: _RunwayTtsTaskResponse = response.json() # Check task status status = self._check_task_status(response_data=response_data) @@ -453,7 +462,7 @@ class RunwayMLTextToSpeechConfig(BaseTextToSpeechConfig): from litellm.types.llms.openai import HttpxBinaryResponseContent try: - response_data: Final = raw_response.json() + response_data: Final[_RunwayTtsTaskResponse] = raw_response.json() except Exception as e: raise self.get_error_class( error_message=f"Error parsing RunwayML TTS response: {e}", @@ -483,7 +492,7 @@ class RunwayMLTextToSpeechConfig(BaseTextToSpeechConfig): ) # Get the completed task data - task_data: Final = polled_response.json() + task_data: Final[_RunwayTtsTaskResponse] = polled_response.json() verbose_logger.debug("RunwayML TTS polling complete, downloading audio") @@ -522,7 +531,7 @@ class RunwayMLTextToSpeechConfig(BaseTextToSpeechConfig): from litellm.types.llms.openai import HttpxBinaryResponseContent try: - response_data: Final = raw_response.json() + response_data: Final[_RunwayTtsTaskResponse] = raw_response.json() except Exception as e: raise self.get_error_class( error_message=f"Error parsing RunwayML TTS response: {e}", @@ -552,7 +561,7 @@ class RunwayMLTextToSpeechConfig(BaseTextToSpeechConfig): ) # Get the completed task data - task_data: Final = polled_response.json() + task_data: Final[_RunwayTtsTaskResponse] = polled_response.json() verbose_logger.debug("RunwayML TTS polling complete (async), downloading audio") diff --git a/litellm/llms/vertex_ai/common_utils.py b/litellm/llms/vertex_ai/common_utils.py index 1de2337d8eb..a36c920dda0 100644 --- a/litellm/llms/vertex_ai/common_utils.py +++ b/litellm/llms/vertex_ai/common_utils.py @@ -1,7 +1,7 @@ import re from copy import deepcopy from enum import Enum -from typing import Any, Final, Literal, get_type_hints +from typing import Any, Final, Literal, cast, get_type_hints import httpx @@ -31,7 +31,7 @@ class VertexAIError(BaseLLMException): super().__init__(message=message, status_code=status_code, headers=headers) -def redact_vertex_ai_metadata_from_logged_object(obj: Any) -> None: +def redact_vertex_ai_metadata_from_logged_object(obj: object) -> None: if isinstance(obj, dict): for field in VERTEX_AI_PROVIDER_METADATA_FIELDS: if field in obj: @@ -651,7 +651,7 @@ def _build_json_schema(parameters: dict) -> dict: return parameters -def _filter_anyof_fields(schema_dict: dict[str, Any]) -> dict[str, Any]: +def _filter_anyof_fields(schema_dict: dict[str, object]) -> dict[str, object]: """ When anyof is present, only keep the anyof field and its contents - otherwise VertexAI will throw an error - https://github.com/BerriAI/litellm/issues/11164 Filter out other fields in the same dict. @@ -704,7 +704,7 @@ def process_items(schema, depth=0): process_items(item, depth + 1) -def set_schema_property_ordering(schema: dict[str, Any], depth: int = 0) -> dict[str, Any]: +def set_schema_property_ordering(schema: dict[str, object], depth: int = 0) -> dict[str, object]: """ vertex ai and generativeai apis order output of fields alphabetically, unless you specify the order. python dicts retain order, so we just use that. Note that this field only applies to structured outputs, and not tools. @@ -724,14 +724,16 @@ def set_schema_property_ordering(schema: dict[str, Any], depth: int = 0) -> dict # retain propertyOrdering as an escape hatch if user already specifies it if "propertyOrdering" not in schema: schema["propertyOrdering"] = [k for k, v in schema["properties"].items()] - for k, v in schema["properties"].items(): - set_schema_property_ordering(v, depth + 1) - if "items" in schema: - set_schema_property_ordering(schema["items"], depth + 1) + for v in schema["properties"].values(): + if isinstance(v, dict): + set_schema_property_ordering(cast("dict[str, object]", v), depth + 1) # cast-ok: JSON Schema child + items: Final = schema.get("items") + if isinstance(items, dict): + set_schema_property_ordering(cast("dict[str, object]", items), depth + 1) # cast-ok: JSON Schema child return schema -def filter_schema_fields(schema_dict: dict[str, Any], valid_fields: set[str], processed=None) -> dict[str, Any]: +def filter_schema_fields(schema_dict: dict[str, object], valid_fields: set[str], processed=None) -> dict[str, object]: """ Recursively filter a schema dictionary to keep only valid fields. """ @@ -905,7 +907,7 @@ def _convert_schema_types(schema, depth=0): "maxProperties", } - any_of: Final[list[dict[str, Any]]] = [] + any_of: Final[list[dict[str, object]]] = [] for t in type_val: if not isinstance(t, str): continue @@ -916,7 +918,7 @@ def _convert_schema_types(schema, depth=0): # For object/array types, include type-specific fields if t in ("object", "array"): - item_schema = {"type": t} + item_schema: dict[str, object] = {"type": t} # Move type-specific fields into this anyOf item for field in type_specific_fields: if field in schema: @@ -1110,11 +1112,11 @@ class VertexAITokenCounter(BaseTokenCounter): self, model_to_use: str, messages: list[dict[str, Any]] | None, - contents: list[dict[str, Any]] | None, + contents: list[dict[str, object]] | None, deployment: dict[str, Any] | None = None, request_model: str = "", - tools: list[dict[str, Any]] | None = None, - system: Any | None = None, + tools: list[dict[str, object]] | None = None, + system: object | None = None, ) -> TokenCountResponse | None: import copy @@ -1131,25 +1133,26 @@ class VertexAITokenCounter(BaseTokenCounter): partner_models_handler: Final = VertexAIPartnerModels() # Extract vertex-specific params from litellm_params - vertex_project = count_tokens_params_request.get("vertex_project") or count_tokens_params_request.get( + partner_litellm_params: Final[dict[str, object]] = count_tokens_params_request + vertex_project = partner_litellm_params.get("vertex_project") or partner_litellm_params.get( "vertex_ai_project" ) - vertex_location = count_tokens_params_request.get("vertex_location") or count_tokens_params_request.get( + vertex_location = partner_litellm_params.get("vertex_location") or partner_litellm_params.get( "vertex_ai_location" ) # Count tokens not available on global location: https://docs.cloud.google.com/vertex-ai/generative-ai/docs/partner-models/claude/count-tokens - vertex_location = count_tokens_params_request.get("vertex_count_tokens_location") or vertex_location + vertex_location = partner_litellm_params.get("vertex_count_tokens_location") or vertex_location - vertex_credentials: Final = count_tokens_params_request.get( - "vertex_credentials" - ) or count_tokens_params_request.get("vertex_ai_credentials") + vertex_credentials: Final = partner_litellm_params.get("vertex_credentials") or partner_litellm_params.get( + "vertex_ai_credentials" + ) result = await partner_models_handler.count_tokens( model=model_to_use, messages=messages or [], - litellm_params=count_tokens_params_request, + litellm_params=partner_litellm_params, vertex_project=vertex_project, vertex_location=vertex_location, vertex_credentials=vertex_credentials, diff --git a/litellm/main.py b/litellm/main.py index 0c8bff16f81..c7d44e32719 100644 --- a/litellm/main.py +++ b/litellm/main.py @@ -6292,18 +6292,15 @@ def embedding( if headers is not None and headers != {}: optional_params["extra_headers"] = headers - if encoding_format is not None: - optional_params["encoding_format"] = encoding_format + requested_encoding_format: Final = ( + encoding_format + or optional_params.get("encoding_format") + or get_secret_str("LITELLM_DEFAULT_EMBEDDING_ENCODING_FORMAT") + ) + if requested_encoding_format is None or requested_encoding_format.strip().lower() == "none": + optional_params.pop("encoding_format", None) else: - env_fmt: Final = get_secret_str("LITELLM_DEFAULT_EMBEDDING_ENCODING_FORMAT") - if env_fmt is not None and env_fmt.strip().lower() == "none": - optional_params.pop("encoding_format", None) - else: - _default_fmt: Final = optional_params.get("encoding_format") or env_fmt or "float" - if _default_fmt.strip().lower() == "none": - optional_params.pop("encoding_format", None) - else: - optional_params["encoding_format"] = _default_fmt + optional_params["encoding_format"] = requested_encoding_format api_version = None diff --git a/litellm/model_prices_and_context_window_backup.json b/litellm/model_prices_and_context_window_backup.json index 80dc49a770b..e001c6b0f9d 100644 --- a/litellm/model_prices_and_context_window_backup.json +++ b/litellm/model_prices_and_context_window_backup.json @@ -554,6 +554,7 @@ "supports_vision": true }, "amazon.nova-sonic-v1:0": { + "deprecation_date": "2026-09-14", "input_cost_per_audio_token": 3.4e-06, "input_cost_per_token": 6e-08, "litellm_provider": "bedrock", @@ -3045,6 +3046,7 @@ "prompt_cache_min_tokens": 2048 }, "azure_ai/claude-fable-5": { + "deprecation_date": "2027-12-05", "supports_mid_conversation_system": true, "input_cost_per_token": 1e-05, "output_cost_per_token": 5e-05, @@ -3078,6 +3080,7 @@ "prompt_cache_min_tokens": 512 }, "azure_ai/claude-opus-5": { + "deprecation_date": "2027-07-08", "supports_mid_conversation_system": true, "supports_adaptive_thinking": true, "input_cost_per_token": 5e-06, @@ -3110,6 +3113,7 @@ "prompt_cache_min_tokens": 512 }, "azure_ai/claude-opus-4-8": { + "deprecation_date": "2027-09-01", "supports_mid_conversation_system": true, "supports_adaptive_thinking": true, "input_cost_per_token": 5e-06, @@ -3188,6 +3192,7 @@ "prompt_cache_min_tokens": 1024 }, "azure_ai/claude-sonnet-5": { + "deprecation_date": "2027-06-30", "supports_mid_conversation_system": true, "cache_creation_input_token_cost": 2.5e-06, "cache_creation_input_token_cost_above_1hr": 4e-06, @@ -12287,6 +12292,7 @@ "supports_tool_choice": true }, "cerebras/zai-glm-4.7": { + "deprecation_date": "2026-08-17", "input_cost_per_token": 2.25e-06, "litellm_provider": "cerebras", "max_input_tokens": 128000, @@ -15101,6 +15107,62 @@ "supports_tool_choice": true, "supports_vision": true }, + "databricks/databricks-deepseek-v4-flash-0731": { + "cache_creation_input_token_cost": 1.4e-07, + "cache_read_input_token_cost": 2.8e-08, + "input_cost_per_token": 1.4e-07, + "input_dbu_cost_per_token": 2e-06, + "litellm_provider": "databricks", + "max_input_tokens": 1000000, + "max_output_tokens": 393216, + "max_tokens": 393216, + "metadata": { + "notes": "Input/output cost per token is dbu cost * $0.070. Billing reads the per-token dollar fields; the '*_dbu_cost_per_token' fields are the published Databricks rates, kept for reference. Context/max output are the DeepSeek-published model limits (1M context, 384K max output)." + }, + "mode": "chat", + "output_cost_per_token": 2.8e-07, + "output_dbu_cost_per_token": 4e-06, + "source": "https://www.databricks.com/product/pricing/foundation-model-serving", + "supported_modalities": [ + "text" + ], + "supported_output_modalities": [ + "text" + ], + "supports_function_calling": true, + "supports_prompt_caching": true, + "supports_reasoning": true, + "supports_tool_choice": true, + "supports_vision": false + }, + "databricks/databricks-deepseek-v4-pro-0813": { + "cache_creation_input_token_cost": 1.31999e-06, + "cache_read_input_token_cost": 1.3202e-07, + "input_cost_per_token": 1.31999e-06, + "input_dbu_cost_per_token": 1.8857e-05, + "litellm_provider": "databricks", + "max_input_tokens": 1000000, + "max_output_tokens": 393216, + "max_tokens": 393216, + "metadata": { + "notes": "Input/output cost per token is dbu cost * $0.070. Billing reads the per-token dollar fields; the '*_dbu_cost_per_token' fields are the published Databricks rates, kept for reference. Context/max output are the DeepSeek-published model limits (1M context, 384K max output)." + }, + "mode": "chat", + "output_cost_per_token": 3.95997e-06, + "output_dbu_cost_per_token": 5.6571e-05, + "source": "https://www.databricks.com/product/pricing/foundation-model-serving", + "supported_modalities": [ + "text" + ], + "supported_output_modalities": [ + "text" + ], + "supports_function_calling": true, + "supports_prompt_caching": true, + "supports_reasoning": true, + "supports_tool_choice": true, + "supports_vision": false + }, "databricks/databricks-gemini-2-5-flash": { "cache_creation_input_token_cost": 3.0002e-07, "cache_read_input_token_cost": 3.0002e-08, @@ -20631,6 +20693,7 @@ "supports_image_size": false }, "gemini-live-2.5-flash-native-audio": { + "deprecation_date": "2026-12-13", "input_cost_per_audio_token": 3e-06, "input_cost_per_token": 5e-07, "litellm_provider": "vertex_ai-language-models", @@ -23852,8 +23915,10 @@ "max_input_tokens": 1024, "max_tokens": 1024, "mode": "video_generation", - "output_cost_per_second": 0.15, - "source": "https://ai.google.dev/gemini-api/docs/video", + "output_cost_per_second": 0.1, + "output_cost_per_second_1080p": 0.12, + "output_cost_per_second_4k": 0.3, + "source": "https://ai.google.dev/gemini-api/docs/pricing", "supported_modalities": [ "text" ], @@ -23867,7 +23932,8 @@ "max_tokens": 1024, "mode": "video_generation", "output_cost_per_second": 0.4, - "source": "https://ai.google.dev/gemini-api/docs/video", + "output_cost_per_second_4k": 0.6, + "source": "https://ai.google.dev/gemini-api/docs/pricing", "supported_modalities": [ "text" ], @@ -23895,8 +23961,10 @@ "max_input_tokens": 1024, "max_tokens": 1024, "mode": "video_generation", - "output_cost_per_second": 0.15, - "source": "https://ai.google.dev/gemini-api/docs/video", + "output_cost_per_second": 0.1, + "output_cost_per_second_1080p": 0.12, + "output_cost_per_second_4k": 0.3, + "source": "https://ai.google.dev/gemini-api/docs/pricing", "supported_modalities": [ "text" ], @@ -23910,7 +23978,8 @@ "max_tokens": 1024, "mode": "video_generation", "output_cost_per_second": 0.4, - "source": "https://ai.google.dev/gemini-api/docs/video", + "output_cost_per_second_4k": 0.6, + "source": "https://ai.google.dev/gemini-api/docs/pricing", "supported_modalities": [ "text" ], @@ -43440,7 +43509,8 @@ "max_tokens": 1024, "mode": "video_generation", "output_cost_per_second": 0.4, - "source": "https://docs.cloud.google.com/gemini-enterprise-agent-platform/models/veo/3-1-generate", + "output_cost_per_second_4k": 0.6, + "source": "https://cloud.google.com/vertex-ai/generative-ai/pricing", "supported_modalities": [ "text" ], @@ -43453,8 +43523,10 @@ "max_input_tokens": 1024, "max_tokens": 1024, "mode": "video_generation", - "output_cost_per_second": 0.15, - "source": "https://docs.cloud.google.com/gemini-enterprise-agent-platform/models/veo/3-1-generate", + "output_cost_per_second": 0.1, + "output_cost_per_second_1080p": 0.12, + "output_cost_per_second_4k": 0.3, + "source": "https://cloud.google.com/vertex-ai/generative-ai/pricing", "supported_modalities": [ "text" ], @@ -43469,7 +43541,8 @@ "max_tokens": 1024, "mode": "video_generation", "output_cost_per_second": 0.4, - "source": "https://docs.cloud.google.com/gemini-enterprise-agent-platform/models/veo/3-1-generate", + "output_cost_per_second_4k": 0.6, + "source": "https://cloud.google.com/vertex-ai/generative-ai/pricing", "supported_modalities": [ "text" ], @@ -43483,8 +43556,10 @@ "max_input_tokens": 1024, "max_tokens": 1024, "mode": "video_generation", - "output_cost_per_second": 0.15, - "source": "https://docs.cloud.google.com/gemini-enterprise-agent-platform/models/veo/3-1-generate", + "output_cost_per_second": 0.1, + "output_cost_per_second_1080p": 0.12, + "output_cost_per_second_4k": 0.3, + "source": "https://cloud.google.com/vertex-ai/generative-ai/pricing", "supported_modalities": [ "text" ], @@ -52231,14 +52306,14 @@ "supports_vision": true }, "fireworks_ai/deepseek-v4-flash-0731": { - "cache_read_input_token_cost": 2.8e-08, - "input_cost_per_token": 1.4e-07, + "cache_read_input_token_cost": 7e-09, + "input_cost_per_token": 2.2e-07, "litellm_provider": "fireworks_ai", "max_input_tokens": 1048576, "max_output_tokens": 131072, "max_tokens": 131072, "mode": "chat", - "output_cost_per_token": 2.8e-07, + "output_cost_per_token": 6.6e-07, "source": "https://docs.fireworks.ai/serverless/pricing", "supports_function_calling": true, "supports_reasoning": true, @@ -55124,5 +55199,55 @@ "max_tokens": 40960, "mode": "embedding", "source": "https://docs.fireworks.ai/serverless/pricing" + }, + "zai/glm-5.2": { + "cache_creation_input_token_cost": 0, + "cache_read_input_token_cost": 2.6e-07, + "input_cost_per_token": 1.4e-06, + "litellm_provider": "zai", + "max_input_tokens": 1000000, + "max_output_tokens": 128000, + "mode": "chat", + "output_cost_per_token": 4.4e-06, + "source": "https://docs.z.ai/guides/overview/pricing", + "supports_function_calling": true, + "supports_prompt_caching": true, + "supports_reasoning": true, + "supports_tool_choice": true + }, + "together_ai/Qwen/Qwen3.8-Flash": { + "input_cost_per_token": 1.5e-07, + "litellm_provider": "together_ai", + "max_input_tokens": 1000000, + "max_tokens": 1000000, + "mode": "chat", + "output_cost_per_token": 4.7e-07, + "source": "https://docs.together.ai/docs/serverless-models" + }, + "cerebras/gemma-4-31b": { + "input_cost_per_token": 9.9e-07, + "litellm_provider": "cerebras", + "max_input_tokens": 131072, + "max_output_tokens": 40960, + "max_tokens": 40960, + "mode": "chat", + "output_cost_per_token": 1.49e-06, + "source": "https://api.cerebras.ai/public/v1/models/gemma-4-31b", + "supports_function_calling": true, + "supports_parallel_function_calling": true, + "supports_reasoning": true, + "supports_response_schema": true, + "supports_tool_choice": true, + "supports_vision": true + }, + "elevenlabs/scribe_v2": { + "input_cost_per_second": 6.11e-05, + "litellm_provider": "elevenlabs", + "mode": "audio_transcription", + "output_cost_per_second": 0.0, + "source": "https://elevenlabs.io/pricing/api", + "supported_endpoints": [ + "/v1/audio/transcriptions" + ] } } diff --git a/litellm/proxy/_experimental/mcp_server/mcp_server_manager.py b/litellm/proxy/_experimental/mcp_server/mcp_server_manager.py index 2330120adad..1f552ff3e13 100644 --- a/litellm/proxy/_experimental/mcp_server/mcp_server_manager.py +++ b/litellm/proxy/_experimental/mcp_server/mcp_server_manager.py @@ -13,7 +13,7 @@ import json import os import re import time -from collections.abc import AsyncIterator, Callable, Mapping, Sequence +from collections.abc import AsyncIterator, Awaitable, Callable, Mapping, Sequence from contextlib import asynccontextmanager from dataclasses import dataclass, replace from typing import TYPE_CHECKING, Any, Final, Literal, TypeAlias, TypedDict, cast @@ -1206,7 +1206,7 @@ def _deserialize_json_dict(data: str | _StringMap | None) -> dict[str, str] | No return data -def _deserialize_json_list(data: Any) -> list[dict[str, Any]] | None: +def _deserialize_json_list(data: object) -> list[dict[str, Any]] | None: """Deserialize a JSON array stored in the DB (``env_vars`` and friends). Returns ``None`` for empty / null / unparseable input. Accepts strings @@ -1219,7 +1219,7 @@ def _deserialize_json_list(data: Any) -> list[dict[str, Any]] | None: return None if isinstance(data, str): try: - parsed: Final = json.loads(data) + parsed: Final[object] = json.loads(data) except (json.JSONDecodeError, TypeError): return None data = parsed @@ -1914,7 +1914,7 @@ class MCPServerManager: async def load_servers_from_config( self, - mcp_servers_config: dict[str, Any], + mcp_servers_config: dict[str, MCPServerConfig], mcp_aliases: dict[str, str] | None = None, ): """ @@ -3068,7 +3068,7 @@ class MCPServerManager: return {} cache_key: Final = "toolset_perms:" + ",".join(sorted(toolset_ids)) - cached: Final = await user_api_key_cache.async_get_cache(key=cache_key) + cached: Final[dict[str, list[str]] | None] = await user_api_key_cache.async_get_cache(key=cache_key) if cached is not None: return cached @@ -5154,7 +5154,7 @@ class MCPServerManager: # Wrapped so the bridge runs inside the task: the caller only holds the task and # gathers it later, so there is no other point that still sees a block here. - async def _run_during_call_hook() -> Mapping[str, Any] | None: + async def _run_during_call_hook() -> Mapping[str, object] | None: try: return await proxy_logging_obj.during_call_hook( user_api_key_dict=user_api_key_auth, @@ -5656,7 +5656,7 @@ class MCPServerManager: async def _gather_openapi_tool_tasks( self, - tasks: list[Any], + tasks: Sequence[Awaitable[object]], proxy_logging_obj: ProxyLogging | None, ) -> CallToolResult: """Await OpenAPI tool tasks and return the tool call result.""" diff --git a/litellm/proxy/auth/auth_utils.py b/litellm/proxy/auth/auth_utils.py index 83ee10b8108..89b2c92cdfd 100644 --- a/litellm/proxy/auth/auth_utils.py +++ b/litellm/proxy/auth/auth_utils.py @@ -994,7 +994,7 @@ def get_key_model_rpm_limit( # 2. Check model_max_budget if user_api_key_dict.model_max_budget: - model_rpm_limit: Final[dict[str, Any]] = {} + model_rpm_limit: Final[dict[str, int]] = {} for model, budget in user_api_key_dict.model_max_budget.items(): if isinstance(budget, dict) and budget.get("rpm_limit") is not None: model_rpm_limit[model] = budget["rpm_limit"] @@ -1037,7 +1037,7 @@ def get_key_model_tpm_limit( # 2. Check model_max_budget (iterate per-model like RPM does) if user_api_key_dict.model_max_budget: - model_tpm_limit: Final[dict[str, Any]] = {} + model_tpm_limit: Final[dict[str, int]] = {} for model, budget in user_api_key_dict.model_max_budget.items(): if isinstance(budget, dict) and budget.get("tpm_limit") is not None: model_tpm_limit[model] = budget["tpm_limit"] @@ -1100,7 +1100,7 @@ def _validated_output_token_estimates_per_model(raw: object) -> Mapping[str, int def _estimated_output_tokens_from_metadata( - metadata: Mapping[str, Any] | None, + metadata: Mapping[str, object] | None, model_name: str | None, ) -> int | None: """Resolve the per-model, then global, estimate out of one metadata blob. @@ -1666,7 +1666,7 @@ def _dedupe_model_candidates(candidates: list[str]) -> list[str]: return deduped -def _get_case_insensitive_mapping_value(mapping: Mapping[str, Any] | None, key: str) -> Any: +def _get_case_insensitive_mapping_value(mapping: Mapping[str, object] | None, key: str) -> object: if not mapping: return None if key in mapping: @@ -1770,8 +1770,8 @@ def _resolve_model_id_with_router(model_id: str | None, llm_router: Router | Non def _extract_model_candidates_from_request( request_data: dict, route: str, - request_headers: Mapping[str, Any] | None = None, - request_query_params: Mapping[str, Any] | None = None, + request_headers: Mapping[str, object] | None = None, + request_query_params: Mapping[str, object] | None = None, llm_router: Router | None = None, ) -> list[str]: candidates: Final[list[str]] = [] @@ -1863,8 +1863,8 @@ def request_dispatched_to_pass_through_endpoint(request: Request | None) -> bool def get_model_from_request( request_data: dict, route: str, - request_headers: Mapping[str, Any] | None = None, - request_query_params: Mapping[str, Any] | None = None, + request_headers: Mapping[str, object] | None = None, + request_query_params: Mapping[str, object] | None = None, llm_router: Router | None = None, request: Request | None = None, ) -> str | list[str] | None: diff --git a/litellm/proxy/common_utils/callback_utils.py b/litellm/proxy/common_utils/callback_utils.py index a28d03eebf0..39e74d2c8bd 100644 --- a/litellm/proxy/common_utils/callback_utils.py +++ b/litellm/proxy/common_utils/callback_utils.py @@ -533,8 +533,8 @@ def sanitize_openai_provider_metadata( Strips LiteLLM proxy-internal tracking fields that must not be forwarded to OpenAI batch/file APIs. """ - if not metadata: - return metadata + if metadata is None: + return None sanitized: Final[dict[str, str]] = {} for key, value in metadata.items(): if key in LITELLM_PROXY_INTERNAL_METADATA_KEYS: @@ -547,7 +547,7 @@ def sanitize_openai_provider_metadata( key, type(value).__name__, ) - return sanitized or None + return None if metadata and not sanitized else sanitized def add_guardrail_to_applied_guardrails_header(request_data: dict, guardrail_name: str | None): @@ -650,7 +650,7 @@ def normalize_callback_names(callbacks: Iterable[object] | None) -> list[object] return [c.lower() if isinstance(c, str) else c for c in callbacks] -def strip_callback_config(metadata: dict[str, Any] | None) -> dict[str, Any] | None: +def strip_callback_config(metadata: dict[str, object] | None) -> dict[str, object] | None: """Return key/team metadata without the slots that carry callback credentials.""" if not isinstance(metadata, dict): return metadata diff --git a/litellm/proxy/common_utils/custom_openapi_spec.py b/litellm/proxy/common_utils/custom_openapi_spec.py index bc7b80801fe..2a20e7b07ce 100644 --- a/litellm/proxy/common_utils/custom_openapi_spec.py +++ b/litellm/proxy/common_utils/custom_openapi_spec.py @@ -1,8 +1,12 @@ from collections.abc import Mapping, Sequence -from typing import Any, Final +from typing import Final, TypeAlias, Union from litellm._logging import verbose_proxy_logger +JsonValue: TypeAlias = Union["JsonObject", "JsonArray", str, int, float, bool, None] +JsonObject: TypeAlias = dict[str, JsonValue] +JsonArray: TypeAlias = list[JsonValue] + class CustomOpenAPISpec: """ @@ -27,7 +31,20 @@ class CustomOpenAPISpec: RESPONSES_API_PATHS = ["/v1/responses", "/responses"] @staticmethod - def get_pydantic_schema(model_class) -> Mapping[str, object] | None: + def _as_object(node: JsonValue) -> JsonObject: + return node if isinstance(node, dict) else {} + + @staticmethod + def _as_array(node: JsonValue) -> JsonArray: + return node if isinstance(node, list) else [] + + @staticmethod + def _components_schemas(openapi_schema: JsonObject) -> JsonObject: + components: Final = CustomOpenAPISpec._as_object(openapi_schema.setdefault("components", {})) + return CustomOpenAPISpec._as_object(components.setdefault("schemas", {})) + + @staticmethod + def get_pydantic_schema(model_class) -> JsonObject | None: """ Get JSON schema from a Pydantic model, handling both v1 and v2 APIs. @@ -54,9 +71,7 @@ class CustomOpenAPISpec: return None @staticmethod - def add_schema_to_components( - openapi_schema: dict[str, Any], schema_name: str, schema_def: Mapping[str, object] - ) -> None: + def add_schema_to_components(openapi_schema: JsonObject, schema_name: str, schema_def: JsonObject) -> None: """ Add a schema definition to the OpenAPI components/schemas section. @@ -66,16 +81,25 @@ class CustomOpenAPISpec: schema_def: The schema definition """ # Ensure components/schemas structure exists - if "components" not in openapi_schema: - openapi_schema["components"] = {} - if "schemas" not in openapi_schema["components"]: - openapi_schema["components"]["schemas"] = {} + _ = CustomOpenAPISpec._components_schemas(openapi_schema) # Add the schema CustomOpenAPISpec._move_defs_to_components(openapi_schema, {schema_name: schema_def}) @staticmethod - def add_request_body_to_paths(openapi_schema: dict[str, Any], paths: Sequence[str], schema_ref: str) -> None: + def _expanded_request_field(field_name: str, field_def: JsonValue) -> JsonValue: + expanded: Final = CustomOpenAPISpec._rewrite_defs_refs( + CustomOpenAPISpec._expand_field_definition(CustomOpenAPISpec._as_object(field_def)) + ) + if field_name != "messages": + return expanded + return { + **CustomOpenAPISpec._as_object(expanded), + "example": [{"role": "user", "content": "Hello, how are you?"}], + } + + @staticmethod + def add_request_body_to_paths(openapi_schema: JsonObject, paths: Sequence[str], schema_ref: str) -> None: """ Add request body with expanded form fields for better Swagger UI display. This keeps the request body but expands it to show individual fields in the UI. @@ -86,54 +110,58 @@ class CustomOpenAPISpec: schema_ref: Reference to the schema component (e.g., "#/components/schemas/ModelName") """ for path in paths: - if path in openapi_schema.get("paths", {}) and "post" in openapi_schema["paths"][path]: - # Get the actual schema to extract ALL field definitions - schema_name = schema_ref.split("/")[-1] # Extract "ProxyChatCompletionRequest" from the ref - actual_schema = openapi_schema.get("components", {}).get("schemas", {}).get(schema_name, {}) - schema_properties = actual_schema.get("properties", {}) - required_fields = actual_schema.get("required", []) + path_item = CustomOpenAPISpec._as_object( + CustomOpenAPISpec._as_object(openapi_schema.get("paths")).get(path) + ) + if "post" not in path_item: + continue - # Extract $defs and add them to components/schemas - # This fixes Pydantic v2 $defs not being resolvable in Swagger/OpenAPI - if "$defs" in actual_schema: - CustomOpenAPISpec._move_defs_to_components(openapi_schema, actual_schema["$defs"]) + post_operation = CustomOpenAPISpec._as_object(path_item["post"]) - # Create an expanded inline schema instead of just a $ref - # This makes Swagger UI show all individual fields in the request body editor - expanded_schema = { - "type": "object", - "required": required_fields, - "properties": {}, - } + # Get the actual schema to extract ALL field definitions + schema_name = schema_ref.split("/")[-1] # Extract "ProxyChatCompletionRequest" from the ref + components = CustomOpenAPISpec._as_object(openapi_schema.get("components")) + actual_schema = CustomOpenAPISpec._as_object( + CustomOpenAPISpec._as_object(components.get("schemas")).get(schema_name) + ) + schema_properties = CustomOpenAPISpec._as_object(actual_schema.get("properties")) + required_fields = actual_schema.get("required", []) - # Add all properties with their full definitions - for field_name, field_def in schema_properties.items(): - expanded_field = CustomOpenAPISpec._expand_field_definition(field_def) + # Extract $defs and add them to components/schemas + # This fixes Pydantic v2 $defs not being resolvable in Swagger/OpenAPI + if "$defs" in actual_schema: + CustomOpenAPISpec._move_defs_to_components( + openapi_schema, CustomOpenAPISpec._as_object(actual_schema["$defs"]) + ) - # Rewrite $defs references to use components/schemas instead - expanded_field = CustomOpenAPISpec._rewrite_defs_refs(expanded_field) + # Create an expanded inline schema instead of just a $ref + # This makes Swagger UI show all individual fields in the request body editor + expanded_schema: JsonObject = { + "type": "object", + "required": required_fields, + "properties": { + field_name: CustomOpenAPISpec._expanded_request_field(field_name, field_def) + for field_name, field_def in schema_properties.items() + }, + } - # Add a simple example for the messages field - if field_name == "messages": - expanded_field["example"] = [{"role": "user", "content": "Hello, how are you?"}] + # Set the request body with the expanded schema + post_operation["requestBody"] = { + "required": True, + "content": {"application/json": {"schema": expanded_schema}}, + } - expanded_schema["properties"][field_name] = expanded_field - - # Set the request body with the expanded schema - openapi_schema["paths"][path]["post"]["requestBody"] = { - "required": True, - "content": {"application/json": {"schema": expanded_schema}}, - } - - # Keep any existing parameters (like path parameters) but remove conflicting query params - if "parameters" in openapi_schema["paths"][path]["post"]: - existing_params = openapi_schema["paths"][path]["post"]["parameters"] - # Only keep path parameters, remove query params that conflict with request body - filtered_params = [param for param in existing_params if param.get("in") == "path"] - openapi_schema["paths"][path]["post"]["parameters"] = filtered_params + # Keep any existing parameters (like path parameters) but remove conflicting query params + if "parameters" in post_operation: + # Only keep path parameters, remove query params that conflict with request body + post_operation["parameters"] = [ + param + for param in CustomOpenAPISpec._as_array(post_operation["parameters"]) + if CustomOpenAPISpec._as_object(param).get("in") == "path" + ] @staticmethod - def _move_defs_to_components(openapi_schema: dict[str, Any], defs: Mapping[str, Mapping[str, Any]]) -> None: + def _move_defs_to_components(openapi_schema: JsonObject, defs: Mapping[str, JsonValue]) -> None: """ Move $defs from Pydantic v2 schema to OpenAPI components/schemas. This makes the definitions resolvable in Swagger/OpenAPI viewers. @@ -146,23 +174,31 @@ class CustomOpenAPISpec: return # Ensure components/schemas exists - if "components" not in openapi_schema: - openapi_schema["components"] = {} - if "schemas" not in openapi_schema["components"]: - openapi_schema["components"]["schemas"] = {} + schemas: Final = CustomOpenAPISpec._components_schemas(openapi_schema) # Add each definition to components/schemas for def_name, def_schema in defs.items(): # Recursively rewrite any nested $defs references within this definition - rewritten_def = CustomOpenAPISpec._rewrite_defs_refs(def_schema) - openapi_schema["components"]["schemas"][def_name] = rewritten_def + schemas[def_name] = CustomOpenAPISpec._rewrite_defs_refs(def_schema) # If this definition also has $defs, process them recursively - if "$defs" in def_schema: - CustomOpenAPISpec._move_defs_to_components(openapi_schema, def_schema["$defs"]) + def_object = CustomOpenAPISpec._as_object(def_schema) + if "$defs" in def_object: + CustomOpenAPISpec._move_defs_to_components( + openapi_schema, CustomOpenAPISpec._as_object(def_object["$defs"]) + ) @staticmethod - def _rewrite_defs_refs(schema: Any) -> Any: + def _rewritten_defs_entry(key: str, value: JsonValue) -> JsonValue: + if key == "$ref" and isinstance(value, str) and value.startswith("#/$defs/"): + # Rewrite the reference to use components/schemas + def_name: Final = value.replace("#/$defs/", "") + return f"#/components/schemas/{def_name}" + # Recursively process nested structures + return CustomOpenAPISpec._rewrite_defs_refs(value) + + @staticmethod + def _rewrite_defs_refs(schema: JsonValue) -> JsonValue: """ Recursively rewrite $ref values from #/$defs/... to #/components/schemas/... This converts Pydantic v2 references to OpenAPI-compatible references. @@ -174,26 +210,17 @@ class CustomOpenAPISpec: Schema with rewritten references """ if isinstance(schema, dict): - result: Final = {} - for key, value in schema.items(): - if key == "$ref" and isinstance(value, str) and value.startswith("#/$defs/"): - # Rewrite the reference to use components/schemas - def_name = value.replace("#/$defs/", "") - result[key] = f"#/components/schemas/{def_name}" - elif key == "$defs": - # Remove $defs from the schema since they're moved to components - continue - else: - # Recursively process nested structures - result[key] = CustomOpenAPISpec._rewrite_defs_refs(value) - return result - elif isinstance(schema, list): + return { + key: CustomOpenAPISpec._rewritten_defs_entry(key, value) + for key, value in schema.items() + if key != "$defs" + } + if isinstance(schema, list): return [CustomOpenAPISpec._rewrite_defs_refs(item) for item in schema] - else: - return schema + return schema @staticmethod - def _extract_field_schema(field_def: dict[str, Any]) -> dict[str, Any]: + def _extract_field_schema(field_def: JsonObject) -> JsonValue: """ Extract a simple schema from a Pydantic field definition for parameter display. @@ -209,10 +236,10 @@ class CustomOpenAPISpec: # Handle anyOf (Optional fields in Pydantic v2) if "anyOf" in field_def: - any_of: Final = field_def["anyOf"] + any_of: Final = CustomOpenAPISpec._as_array(field_def["anyOf"]) # Find the non-null type for option in any_of: - if option.get("type") != "null": + if CustomOpenAPISpec._as_object(option).get("type") != "null": return option # Fallback to string if all else fails return {"type": "string"} @@ -221,7 +248,7 @@ class CustomOpenAPISpec: return {"type": "string"} @staticmethod - def _expand_field_definition(field_def: dict[str, object]) -> dict[str, object]: + def _expand_field_definition(field_def: JsonObject) -> JsonObject: """ Expand a Pydantic field definition for inline use in OpenAPI schema. This creates a full field definition that Swagger UI can render as individual form fields. @@ -237,12 +264,12 @@ class CustomOpenAPISpec: @staticmethod def add_request_schema( - openapi_schema: dict[str, object], + openapi_schema: JsonObject, model_class: type, schema_name: str, paths: Sequence[str], operation_name: str, - ) -> dict[str, object]: + ) -> JsonObject: """ Generic method to add a request schema to OpenAPI specification. @@ -282,8 +309,8 @@ class CustomOpenAPISpec: @staticmethod def add_chat_completion_request_schema( - openapi_schema: dict[str, object], - ) -> dict[str, object]: + openapi_schema: JsonObject, + ) -> JsonObject: """ Add ProxyChatCompletionRequest schema to chat completion endpoints for documentation. This shows the request body in Swagger without runtime validation. @@ -309,7 +336,7 @@ class CustomOpenAPISpec: return openapi_schema @staticmethod - def add_embedding_request_schema(openapi_schema: dict[str, object]) -> dict[str, object]: + def add_embedding_request_schema(openapi_schema: JsonObject) -> JsonObject: """ Add EmbeddingRequest schema to embedding endpoints for documentation. This shows the request body in Swagger without runtime validation. @@ -336,8 +363,8 @@ class CustomOpenAPISpec: @staticmethod def add_responses_api_request_schema( - openapi_schema: dict[str, object], - ) -> dict[str, object]: + openapi_schema: JsonObject, + ) -> JsonObject: """ Add ResponsesAPIRequestParams schema to responses API endpoints for documentation. This shows the request body in Swagger without runtime validation. @@ -364,8 +391,8 @@ class CustomOpenAPISpec: @staticmethod def add_llm_api_request_schema_body( - openapi_schema: dict[str, object], - ) -> dict[str, object]: + openapi_schema: JsonObject, + ) -> JsonObject: """ Add LLM API request schema bodies to OpenAPI specification for documentation. @@ -376,12 +403,10 @@ class CustomOpenAPISpec: OpenAPI schema with added request body schemas """ # Add chat completion request schema - openapi_schema = CustomOpenAPISpec.add_chat_completion_request_schema(openapi_schema) + with_chat_completions: Final = CustomOpenAPISpec.add_chat_completion_request_schema(openapi_schema) # Add embedding request schema - openapi_schema = CustomOpenAPISpec.add_embedding_request_schema(openapi_schema) + with_embeddings: Final = CustomOpenAPISpec.add_embedding_request_schema(with_chat_completions) # Add responses API request schema - openapi_schema = CustomOpenAPISpec.add_responses_api_request_schema(openapi_schema) - - return openapi_schema + return CustomOpenAPISpec.add_responses_api_request_schema(with_embeddings) diff --git a/litellm/proxy/common_utils/user_api_key_cache.py b/litellm/proxy/common_utils/user_api_key_cache.py index 44b88aec47b..76982d30306 100644 --- a/litellm/proxy/common_utils/user_api_key_cache.py +++ b/litellm/proxy/common_utils/user_api_key_cache.py @@ -1,6 +1,6 @@ from __future__ import annotations -from typing import Any, Final, TypeVar, cast, overload +from typing import TYPE_CHECKING, Any, Final, TypeVar, cast, overload from pydantic import BaseModel @@ -9,6 +9,9 @@ from litellm.caching.dual_cache import DualCache from litellm.constants import DEFAULT_MANAGEMENT_OBJECT_IN_MEMORY_CACHE_TTL from litellm.proxy.common_utils.cache_pydantic_utils import CacheCodec +if TYPE_CHECKING: + from opentelemetry.trace import Span + T = TypeVar("T", bound=BaseModel) @@ -40,8 +43,8 @@ class UserApiKeyCache(DualCache): @overload def get_cache( self, - key: object, - parent_otel_span: object = None, + key: str, + parent_otel_span: Span | None = None, local_only: bool = False, *, model_type: type[T], @@ -51,8 +54,8 @@ class UserApiKeyCache(DualCache): @overload def get_cache( self, - key: object, - parent_otel_span: object = None, + key: str, + parent_otel_span: Span | None = None, local_only: bool = False, model_type: None = None, **kwargs: object, @@ -60,12 +63,12 @@ class UserApiKeyCache(DualCache): def get_cache( self, - key: object, - parent_otel_span: object = None, + key: str, + parent_otel_span: Span | None = None, local_only: bool = False, model_type: type[BaseModel] | None = None, **kwargs: object, - ) -> Any | BaseModel | None: + ) -> object: if model_type is None and "model_type" in kwargs: model_type = cast(type[BaseModel] | None, kwargs.pop("model_type", None)) cached: Final = super().get_cache(key=key, parent_otel_span=parent_otel_span, local_only=local_only, **kwargs) @@ -86,8 +89,8 @@ class UserApiKeyCache(DualCache): @overload async def async_get_cache( self, - key: object, - parent_otel_span: object = None, + key: str, + parent_otel_span: Span | None = None, local_only: bool = False, *, model_type: type[T], @@ -97,8 +100,8 @@ class UserApiKeyCache(DualCache): @overload async def async_get_cache( self, - key: object, - parent_otel_span: object = None, + key: str, + parent_otel_span: Span | None = None, local_only: bool = False, model_type: None = None, **kwargs: object, @@ -106,12 +109,12 @@ class UserApiKeyCache(DualCache): async def async_get_cache( self, - key: object, - parent_otel_span: object = None, + key: str, + parent_otel_span: Span | None = None, local_only: bool = False, model_type: type[BaseModel] | None = None, **kwargs: object, - ) -> Any | BaseModel | None: + ) -> object: if model_type is None and "model_type" in kwargs: model_type = cast(type[BaseModel] | None, kwargs.pop("model_type", None)) cached: Final = await super().async_get_cache( @@ -131,12 +134,12 @@ class UserApiKeyCache(DualCache): return None return decoded - def set_cache(self, key: object, value: object, local_only: bool = False, **kwargs: object): + def set_cache(self, key: str | None, value: object, local_only: bool = False, **kwargs: object): model_type: Final = cast(type[BaseModel] | None, kwargs.pop("model_type", None)) payload: Final[object] = CacheCodec.serialize(value, model_type=model_type) return super().set_cache(key=key, value=payload, local_only=local_only, **kwargs) - async def async_set_cache(self, key: object, value: object, local_only: bool = False, **kwargs: object): + async def async_set_cache(self, key: str | None, value: object, local_only: bool = False, **kwargs: object): model_type: Final = cast(type[BaseModel] | None, kwargs.pop("model_type", None)) payload: Final[object] = CacheCodec.serialize(value, model_type=model_type) return await super().async_set_cache(key=key, value=payload, local_only=local_only, **kwargs) diff --git a/litellm/proxy/guardrails/guardrail_hooks/bedrock_guardrails.py b/litellm/proxy/guardrails/guardrail_hooks/bedrock_guardrails.py index a6635ea0776..0237d82a0d9 100644 --- a/litellm/proxy/guardrails/guardrail_hooks/bedrock_guardrails.py +++ b/litellm/proxy/guardrails/guardrail_hooks/bedrock_guardrails.py @@ -32,6 +32,9 @@ from litellm.constants import BEDROCK_APPLY_GUARDRAIL_CHUNK_BUDGET_CHARS from litellm.exceptions import ModifyResponseException from litellm.integrations.custom_guardrail import CustomGuardrail from litellm.litellm_core_utils.core_helpers import redact_nested_match_and_regex_keys +from litellm.litellm_core_utils.litellm_logging import ( + _get_masked_values, # pyright: ignore[reportPrivateUsage] # the shared header-masking helper has no public name +) from litellm.litellm_core_utils.llm_cost_calc.guardrail_cost import bedrock_guardrail_cost from litellm.llms.anthropic.chat.guardrail_translation.handler import AnthropicMessagesHandler from litellm.llms.base_llm.guardrail_translation.utils import ( @@ -252,7 +255,7 @@ class BedrockGuardrail(CustomGuardrail, BaseAWSLLM): # Resource-less, detect-only InvokeGuardrailChecks mode. Present `checks` # routes the guardrail to InvokeGuardrailChecks; absent => ApplyGuardrail. - self.checks: dict[str, Any] | None = self._normalize_checks(checks) + self.checks: dict[str, object] | None = self._normalize_checks(checks) # Per-check block thresholds; a score >= threshold blocks. None => the # check is detect-only (logged, never blocks). self.content_filter_threshold = content_filter_threshold @@ -321,7 +324,7 @@ class BedrockGuardrail(CustomGuardrail, BaseAWSLLM): ] @staticmethod - def _normalize_checks(checks: BedrockChecksConfigModel | Mapping[str, object] | None) -> dict[str, Any] | None: + def _normalize_checks(checks: BedrockChecksConfigModel | Mapping[str, object] | None) -> dict[str, object] | None: """Normalize the configured `checks` into a plain dict for the API body. Accepts a pydantic ``BedrockChecksConfigModel`` or a raw dict; drops None / @@ -372,7 +375,7 @@ class BedrockGuardrail(CustomGuardrail, BaseAWSLLM): def _create_bedrock_output_content_request( self, - response: Any | ModelResponse, + response: object, messages: list[AllMessageValues] | None = None, ) -> BedrockRequest: """ @@ -396,9 +399,7 @@ class BedrockGuardrail(CustomGuardrail, BaseAWSLLM): bedrock_request["content"] = bedrock_request_content return bedrock_request - def _build_response_content_items( - self, response: Any | ModelResponse, has_grounding: bool - ) -> list[BedrockContentItem]: + def _build_response_content_items(self, response: object, has_grounding: bool) -> list[BedrockContentItem]: """Build content item(s) from the model response. When the request supplied grounding, the response is qualified ``guard_content`` so Bedrock can score it. """ @@ -422,7 +423,7 @@ class BedrockGuardrail(CustomGuardrail, BaseAWSLLM): self, source: Literal["INPUT", "OUTPUT"], messages: list[AllMessageValues] | None = None, - response: Any | ModelResponse | None = None, + response: object | None = None, ) -> BedrockRequest: """ Convert the litellm messages/response to the bedrock request format. @@ -945,7 +946,7 @@ class BedrockGuardrail(CustomGuardrail, BaseAWSLLM): async def _apply_guardrail_content_with_chunking( self, content: Sequence[BedrockContentItem], - base_request_data: Mapping[str, Any], + base_request_data: Mapping[str, object], credentials: "Credentials", aws_region_name: str, api_key: str | None, @@ -1083,7 +1084,7 @@ class BedrockGuardrail(CustomGuardrail, BaseAWSLLM): async def _post_apply_guardrail_content_with_retry( self, content: Sequence[BedrockContentItem], - base_request_data: Mapping[str, Any], + base_request_data: Mapping[str, object], credentials: "Credentials", aws_region_name: str, api_key: str | None, @@ -1133,7 +1134,7 @@ class BedrockGuardrail(CustomGuardrail, BaseAWSLLM): async def _post_apply_guardrail_content( self, content: Sequence[BedrockContentItem], - base_request_data: Mapping[str, Any], + base_request_data: Mapping[str, object], credentials: "Credentials", aws_region_name: str, api_key: str | None, @@ -1172,11 +1173,12 @@ class BedrockGuardrail(CustomGuardrail, BaseAWSLLM): aws_region_name=aws_region_name, api_key=api_key, ) + headers_dict: Final = dict(prepared_request.headers) # mutable-ok: the masking helper requires a dict verbose_proxy_logger.debug( "Bedrock AI request body: %s, url %s, headers: %s", bedrock_request_data, prepared_request.url, - prepared_request.headers, + _get_masked_values(headers_dict), ) httpx_response: Final = await self._sign_and_post( @@ -1861,7 +1863,7 @@ class BedrockGuardrail(CustomGuardrail, BaseAWSLLM): return BedrockGuardrailResponse() credentials, aws_region_name = self._load_credentials() - body: Final[dict[str, Any]] = {"messages": checks_messages, "checks": self.checks} + body: Final[dict[str, object]] = {"messages": checks_messages, "checks": self.checks} api_key: Final[str | None] = request_data.get("api_key") if request_data else None prepared_request: Final = self._prepare_request( @@ -2343,7 +2345,7 @@ class BedrockGuardrail(CustomGuardrail, BaseAWSLLM): guardrail_name=self.guardrail_name, ) - detail: Final[dict[str, Any]] = { + detail: Final[dict[str, object]] = { "error": "Violated guardrail policy", "bedrock_guardrail_response": bedrock_guardrail_output_text, } @@ -2902,7 +2904,7 @@ class BedrockGuardrail(CustomGuardrail, BaseAWSLLM): return updated_messages def _mask_content_list( - self, content_list: list[Any], masked_texts: list[str], masking_index: int + self, content_list: Sequence[object], masked_texts: list[str], masking_index: int ) -> tuple[list[Any], int]: """ Apply masking to a list of content items. @@ -2915,7 +2917,7 @@ class BedrockGuardrail(CustomGuardrail, BaseAWSLLM): Returns: Updated content list with masked items """ - new_content: Final[list[dict | str]] = [] + new_content: Final[list[dict[str, object] | str]] = [] for item in content_list: if isinstance(item, dict) and "text" in item: new_item = item.copy() @@ -2934,7 +2936,7 @@ class BedrockGuardrail(CustomGuardrail, BaseAWSLLM): def _apply_masking_to_response( self, - response: ModelResponse | Any, + response: object, bedrock_guardrail_response: BedrockGuardrailResponse, ) -> None: """ diff --git a/litellm/proxy/guardrails/guardrail_hooks/cisco_ai_defense/cisco_ai_defense_mcp.py b/litellm/proxy/guardrails/guardrail_hooks/cisco_ai_defense/cisco_ai_defense_mcp.py index 8398ec9f141..5a6be1089b6 100644 --- a/litellm/proxy/guardrails/guardrail_hooks/cisco_ai_defense/cisco_ai_defense_mcp.py +++ b/litellm/proxy/guardrails/guardrail_hooks/cisco_ai_defense/cisco_ai_defense_mcp.py @@ -5,8 +5,9 @@ The public guardrail class imports this private mixin from while preserving the existing public import path. """ +from collections.abc import Sequence from datetime import datetime -from typing import TYPE_CHECKING, Any, Final, Optional +from typing import TYPE_CHECKING, Final, Optional from fastapi import HTTPException @@ -23,7 +24,7 @@ if TYPE_CHECKING: from .cisco_ai_defense import _ScanContext -def _serialize_mcp_content_item(item: object) -> dict[str, Any]: +def _serialize_mcp_content_item(item: object) -> dict[str, object]: """Serialize an MCP content item to a JSON-friendly dict. Handles raw dicts, MCP SDK Pydantic models, and simple ``.text`` objects. @@ -57,7 +58,7 @@ class _CiscoAIDefenseMcpMixin: def should_run_guardrail(self, data: dict, event_type: GuardrailEventHooks) -> bool: ... - async def _post_inspection(self, url: str, payload: dict[str, Any], surface: str) -> dict[str, Any]: ... + async def _post_inspection(self, url: str, payload: dict[str, object], surface: str) -> dict[str, object]: ... def _handle_api_error( self, @@ -67,16 +68,16 @@ class _CiscoAIDefenseMcpMixin: start_time: datetime | None = ..., surface: str = ..., direction: str = ..., - ) -> dict[str, Any]: ... + ) -> dict[str, object]: ... def _finalize_inspection( self, - inspect_response: dict[str, Any], + inspect_response: dict[str, object], request_data: dict, context: "_ScanContext", start_time: datetime, response_obj: object = ..., - ) -> dict[str, Any]: ... + ) -> dict[str, object]: ... # ------------------------------------------------------------------ # MCP post-tool hook (dispatcher contract) @@ -95,7 +96,7 @@ class _CiscoAIDefenseMcpMixin: if self.inspection_type != "mcp": return None - request_data: Final[dict[str, Any]] = {} + request_data: Final[dict[str, object]] = {} for key in ( "name", "litellm_call_id", @@ -188,9 +189,9 @@ class _CiscoAIDefenseMcpMixin: original_hidden: Final = getattr(original_response_obj, "hidden_params", None) if isinstance(original_hidden, HiddenParams): - hidden_params: Any = original_hidden + hidden_params: HiddenParams = original_hidden else: - response_cost: Final = getattr(original_hidden, "response_cost", None) + response_cost: Final[float | None] = getattr(original_hidden, "response_cost", None) hidden_params = HiddenParams(response_cost=response_cost) if response_cost is not None else HiddenParams() return MCPPostCallResponseObject( @@ -200,11 +201,11 @@ class _CiscoAIDefenseMcpMixin: @staticmethod def _replace_mcp_tool_response(response_obj: object, replacement_obj: object) -> bool: - replacement: Final = getattr(replacement_obj, "mcp_tool_call_response", None) + replacement: Final[list[object] | None] = getattr(replacement_obj, "mcp_tool_call_response", None) if replacement is None: return False - inner: Final = getattr(response_obj, "mcp_tool_call_response", None) + inner: Final[object | None] = getattr(response_obj, "mcp_tool_call_response", None) if inner is not None: if _CiscoAIDefenseMcpMixin._replace_mcp_tool_response(inner, replacement_obj): return True @@ -276,7 +277,7 @@ class _CiscoAIDefenseMcpMixin: self, data: dict, user_api_key_dict: UserAPIKeyAuth, - ) -> dict[str, Any]: + ) -> dict[str, object]: del user_api_key_dict # carried via logging metadata, not the wire payload url: Final = f"{self.api_base}{self.inspect_path}" payload: Final = self._build_mcp_request_payload(data=data) @@ -312,7 +313,7 @@ class _CiscoAIDefenseMcpMixin: response: object, user_api_key_dict: UserAPIKeyAuth | None = None, redact_response_obj: object = None, - ) -> dict[str, Any]: + ) -> dict[str, object]: del user_api_key_dict # carried via logging metadata, not the wire payload url: Final = f"{self.api_base}{self.inspect_path}" payload: Final = self._build_mcp_response_payload( @@ -349,7 +350,7 @@ class _CiscoAIDefenseMcpMixin: def _build_mcp_request_payload( self, data: dict, - ) -> dict[str, Any] | None: + ) -> dict[str, object] | None: """Build the JSON-RPC ``tools/call`` envelope sent to ``/inspect/mcp``. The Cisco AI Defense MCP inspect endpoint expects the JSON-RPC @@ -390,7 +391,7 @@ class _CiscoAIDefenseMcpMixin: self, request_data: dict, response: object, - ) -> dict[str, Any] | None: + ) -> dict[str, object] | None: """Build the MCP response-inspection body sent to ``/inspect/mcp``.""" request_payload: Final = self._build_mcp_request_payload(data=request_data) if request_payload is None: @@ -415,7 +416,7 @@ class _CiscoAIDefenseMcpMixin: return payload @staticmethod - def _hydrate_mcp_tool_context(request_data: dict[str, Any]) -> None: + def _hydrate_mcp_tool_context(request_data: dict[str, object]) -> None: metadata = request_data.get("mcp_tool_call_metadata") if metadata is None: nested: Final = request_data.get("metadata") or request_data.get("litellm_metadata") @@ -440,7 +441,7 @@ class _CiscoAIDefenseMcpMixin: request_data.setdefault("server_name", server_name) @staticmethod - def _normalize_mcp_response(response: object) -> dict[str, Any] | None: + def _normalize_mcp_response(response: object) -> dict[str, object] | None: """Normalize an MCP tool response into a JSON-RPC envelope. Handles JSON-RPC dicts, raw content lists, MCP SDK models, and @@ -502,10 +503,10 @@ class _CiscoAIDefenseMcpMixin: @staticmethod def _build_mcp_result( - content: list[Any], + content: Sequence[object], source: object = None, - ) -> dict[str, Any]: - result: Final[dict[str, Any]] = {"content": [_serialize_mcp_content_item(item) for item in content]} + ) -> dict[str, object]: + result: Final[dict[str, object]] = {"content": [_serialize_mcp_content_item(item) for item in content]} for key in ("structuredContent", "isError"): value = source.get(key) if isinstance(source, dict) else getattr(source, key, None) if value is not None and (key != "isError" or isinstance(value, bool)): @@ -522,7 +523,7 @@ class _CiscoAIDefenseMcpMixin: if response_obj is None: return False - inner: Final = getattr(response_obj, "mcp_tool_call_response", None) + inner: Final[object | None] = getattr(response_obj, "mcp_tool_call_response", None) if inner is not None: return _CiscoAIDefenseMcpMixin._set_mcp_tool_response_text(inner, text) @@ -559,7 +560,7 @@ class _CiscoAIDefenseMcpMixin: pass elif isinstance(response_obj, dict): result: Final = response_obj.get("result") - target: Final[dict[Any, Any]] = result if isinstance(result, dict) else response_obj + target: Final[dict[object, object]] = result if isinstance(result, dict) else response_obj if "structuredContent" in target: target["structuredContent"] = replacement replaced = True @@ -567,11 +568,11 @@ class _CiscoAIDefenseMcpMixin: return replaced @staticmethod - def _coerce_to_content_list(response_obj: object) -> list[Any] | None: + def _coerce_to_content_list(response_obj: object) -> list[object] | None: """Find the MCP content list inside supported response shapes.""" if response_obj is None: return None - inner: Final = getattr(response_obj, "mcp_tool_call_response", None) + inner: Final[object | None] = getattr(response_obj, "mcp_tool_call_response", None) if inner is not None: return _CiscoAIDefenseMcpMixin._coerce_to_content_list(inner) content: Final = getattr(response_obj, "content", None) @@ -594,8 +595,8 @@ class _CiscoAIDefenseMcpMixin: @staticmethod def _extract_sanitized_mcp_arguments( - inspect_response: dict[str, Any], - ) -> dict[str, Any] | None: + inspect_response: dict[str, object], + ) -> dict[str, object] | None: """Pull sanitized MCP tool-call arguments off the verdict. Cisco can return them at the top level (``params.arguments``) or diff --git a/litellm/proxy/guardrails/guardrail_hooks/mcp_jwt_signer/mcp_jwt_signer.py b/litellm/proxy/guardrails/guardrail_hooks/mcp_jwt_signer/mcp_jwt_signer.py index e2d7c06f7c5..a269ad31a6b 100644 --- a/litellm/proxy/guardrails/guardrail_hooks/mcp_jwt_signer/mcp_jwt_signer.py +++ b/litellm/proxy/guardrails/guardrail_hooks/mcp_jwt_signer/mcp_jwt_signer.py @@ -80,7 +80,7 @@ import jwt from cryptography.hazmat.primitives import serialization from cryptography.hazmat.primitives.asymmetric import rsa from cryptography.hazmat.primitives.asymmetric.rsa import RSAPrivateKey, RSAPublicKey -from typing_extensions import NotRequired, TypedDict +from typing_extensions import NotRequired, ReadOnly, TypedDict from litellm._logging import verbose_proxy_logger from litellm.caching import DualCache @@ -89,6 +89,7 @@ from litellm.integrations.custom_guardrail import ( log_guardrail_information, ) from litellm.proxy._types import UserAPIKeyAuth +from litellm.types.guardrail_base_init import GuardrailBaseInitKwargs from litellm.types.guardrails import GuardrailEventHooks from litellm.types.utils import CallTypesLiteral @@ -107,6 +108,19 @@ class _JWTDecodeKwargs(TypedDict): issuer: NotRequired[str] +class _DebugHeaderClaims(TypedDict, total=False): + sub: ReadOnly[object] + iss: ReadOnly[object] + exp: ReadOnly[object] + scope: ReadOnly[str] + + +class _SignedClaimSummary(TypedDict): + sub: ReadOnly[object] + act: ReadOnly[Mapping[str, object]] + exp: ReadOnly[object] + + # Module-level singleton for the JWKS discovery endpoint to access. _mcp_jwt_signer_instance: Optional["MCPJWTSigner"] = None @@ -265,7 +279,8 @@ class MCPJWTSigner(CustomGuardrail): **kwargs: Any, ) -> None: kwargs.setdefault("supported_event_hooks", list(self.get_supported_event_hooks())) - super().__init__(**kwargs) + base_kwargs: Final[GuardrailBaseInitKwargs] = kwargs + super().__init__(**base_kwargs) # --- Signing key setup --- key_material: Final = os.environ.get(self.SIGNING_KEY_ENV) @@ -677,7 +692,7 @@ class MCPJWTSigner(CustomGuardrail): data: dict, jwt_claims: Mapping[str, object] | None = None, call_type: CallTypesLiteral | None = None, - ) -> dict[str, Any]: + ) -> dict[str, object]: """ Build JWT claims for the outbound MCP access token. @@ -752,7 +767,7 @@ class MCPJWTSigner(CustomGuardrail): # ------------------------------------------------------------------ @staticmethod - def _build_debug_header(claims: dict[str, Any], kid: str) -> str: + def _build_debug_header(claims: _DebugHeaderClaims, kid: str) -> str: """ Build the x-litellm-mcp-debug header value. @@ -873,16 +888,18 @@ class MCPJWTSigner(CustomGuardrail): # FR-9: Debug header # ------------------------------------------------------------------ if self.debug_headers: - new_headers["x-litellm-mcp-debug"] = self._build_debug_header(claims, self._kid) + debug_claims: Final[_DebugHeaderClaims] = claims + new_headers["x-litellm-mcp-debug"] = self._build_debug_header(debug_claims, self._kid) hook_data["extra_headers"] = new_headers + logged_claims: Final[_SignedClaimSummary] = claims verbose_proxy_logger.debug( "MCPJWTSigner: signed JWT sub=%s act=%s tool=%s exp=%d verified=%s channel=%s call_type=%s", - claims.get("sub"), - claims.get("act", {}).get("sub"), + logged_claims.get("sub"), + logged_claims.get("act", {}).get("sub"), hook_data.get("mcp_tool_name"), - claims["exp"], + logged_claims["exp"], jwt_claims is not None, bool(self.channel_token_audience), call_type, diff --git a/litellm/proxy/guardrails/guardrail_hooks/noma/noma_v2.py b/litellm/proxy/guardrails/guardrail_hooks/noma/noma_v2.py index 704e2564ef5..292f395053b 100644 --- a/litellm/proxy/guardrails/guardrail_hooks/noma/noma_v2.py +++ b/litellm/proxy/guardrails/guardrail_hooks/noma/noma_v2.py @@ -24,6 +24,7 @@ from litellm.llms.custom_httpx.http_handler import ( httpxSpecialProvider, ) from litellm.proxy.guardrails.guardrail_hooks.noma.noma import NomaBlockedMessage +from litellm.types.guardrail_base_init import GuardrailBaseInitKwargs from litellm.types.guardrails import GuardrailEventHooks from litellm.types.utils import GenericGuardrailAPIInputs, GuardrailStatus @@ -83,7 +84,8 @@ class NomaV2Guardrail(CustomGuardrail): kwargs.setdefault("supported_event_hooks", list(self.get_supported_event_hooks())) - super().__init__(**kwargs) + base_kwargs: Final[GuardrailBaseInitKwargs] = kwargs + super().__init__(**base_kwargs) @staticmethod def get_config_model() -> type["GuardrailConfigModel"] | None: @@ -114,7 +116,7 @@ class NomaV2Guardrail(CustomGuardrail): return parsed.hostname == _DEFAULT_API_BASE_HOSTNAME @staticmethod - def _get_non_empty_str(value: Any) -> str | None: + def _get_non_empty_str(value: object) -> str | None: if not isinstance(value, str): return None stripped: Final = value.strip() @@ -156,7 +158,7 @@ class NomaV2Guardrail(CustomGuardrail): else model_call_details ) - payload: Final[dict[str, Any]] = { + payload: Final[dict[str, object]] = { "inputs": inputs, "request_data": payload_request_data, "input_type": input_type, @@ -324,8 +326,9 @@ class NomaV2Guardrail(CustomGuardrail): except NomaBlockedMessage as e: guardrail_status = "guardrail_intervened" + blocked_detail: Final[dict[str, object]] = {"error": "blocked"} guardrail_json_response = ( - response_json if isinstance(response_json, dict) else getattr(e, "detail", {"error": "blocked"}) + response_json if isinstance(response_json, dict) else getattr(e, "detail", blocked_detail) ) raise except Exception as e: diff --git a/litellm/proxy/guardrails/guardrail_hooks/presidio.py b/litellm/proxy/guardrails/guardrail_hooks/presidio.py index 8d78393d687..da51a905ae3 100644 --- a/litellm/proxy/guardrails/guardrail_hooks/presidio.py +++ b/litellm/proxy/guardrails/guardrail_hooks/presidio.py @@ -11,10 +11,10 @@ import asyncio import json import threading -from collections.abc import AsyncGenerator, Sequence +from collections.abc import AsyncGenerator, AsyncIterable, Awaitable, Sequence from contextlib import asynccontextmanager from datetime import datetime -from typing import TYPE_CHECKING, Any, Final, Literal, Optional, TypedDict, cast +from typing import TYPE_CHECKING, Any, Final, Literal, Optional, Protocol, TypedDict, cast import aiohttp from typing_extensions import NotRequired, ReadOnly @@ -68,6 +68,14 @@ class _PresidioAnonymizeResponse(TypedDict): items: ReadOnly[NotRequired[list[_PresidioAnonymizeItem]]] +class _JsonResponse(Protocol): + def json(self) -> Awaitable[object]: ... + + +async def _json_body(response: _JsonResponse) -> object: + return await response.json() + + _LoopSemaphores = dict[asyncio.AbstractEventLoop, asyncio.Semaphore] @@ -389,7 +397,7 @@ class _OPTIONAL_PresidioPIIMasking(CustomGuardrail): f"expected application/json Content-Type but received '{content_type}'; body: '{error_body[:200]}'" ) - analyze_results: Final = await response.json() + analyze_results: Final = await _json_body(response) verbose_proxy_logger.debug("analyze_results: %s", analyze_results) # Handle error responses from Presidio (e.g., {'error': 'No text provided'}) @@ -997,7 +1005,7 @@ class _OPTIONAL_PresidioPIIMasking(CustomGuardrail): except Exception as e: raise e - def logging_hook(self, kwargs: dict, result: Any, call_type: str) -> tuple[dict, Any]: + def logging_hook(self, kwargs: dict, result: object, call_type: str) -> tuple[dict, object]: from concurrent.futures import ThreadPoolExecutor def run_in_new_loop(): @@ -1025,7 +1033,7 @@ class _OPTIONAL_PresidioPIIMasking(CustomGuardrail): # No running event loop, we can safely run in this thread return run_in_new_loop() - async def async_logging_hook(self, kwargs: dict, result: Any, call_type: str) -> tuple[dict, Any]: + async def async_logging_hook(self, kwargs: dict, result: object, call_type: str) -> tuple[dict, object]: """ Masks the input and output before logging to langfuse, datadog, etc. """ @@ -1092,9 +1100,9 @@ class _OPTIONAL_PresidioPIIMasking(CustomGuardrail): and not isinstance(result.choices[0], StreamingChoices) ): await self._process_response_for_pii(response=result, request_data=kwargs, mode="mask") - elif self._is_anthropic_message_response(result): + elif isinstance(result, dict) and self._is_anthropic_message_response(result): await self._process_anthropic_response_for_pii( - response=cast(dict, result), # cast-ok: _is_anthropic_message_response narrows via isinstance + response=result, request_data=kwargs, mode="mask", ) @@ -1321,7 +1329,7 @@ class _OPTIONAL_PresidioPIIMasking(CustomGuardrail): async def _stream_apply_output_masking( self, - response: Any, + response: AsyncIterable[object], request_data: dict, ) -> AsyncGenerator[ModelResponseStream | bytes, None]: """Apply Presidio masking to streaming output (apply_to_output=True path).""" @@ -1425,7 +1433,7 @@ class _OPTIONAL_PresidioPIIMasking(CustomGuardrail): return "\n".join(result_lines).encode("utf-8") - def _unmask_responses_api_completed_chunk(self, chunk: Any, pii_tokens: dict[str, str]) -> None: + def _unmask_responses_api_completed_chunk(self, chunk: object, pii_tokens: dict[str, str]) -> None: """ Unmask PII tokens in-place for a ``response.completed`` Responses API event. @@ -1434,7 +1442,7 @@ class _OPTIONAL_PresidioPIIMasking(CustomGuardrail): blocks; text blocks expose a ``.text`` string attribute. We walk the tree and replace every PII token with its original value. """ - response_obj: Final = getattr(chunk, "response", None) + response_obj: Final[object] = getattr(chunk, "response", None) if response_obj is None: return @@ -1450,7 +1458,7 @@ class _OPTIONAL_PresidioPIIMasking(CustomGuardrail): async def _stream_pii_unmasking( self, - response: Any, + response: AsyncIterable[object], request_data: dict, ) -> AsyncGenerator[ModelResponseStream | bytes, None]: """Apply PII unmasking to streaming output (output_parse_pii=True path).""" @@ -1526,7 +1534,7 @@ class _OPTIONAL_PresidioPIIMasking(CustomGuardrail): async def async_post_call_streaming_iterator_hook( self, user_api_key_dict: UserAPIKeyAuth, - response: Any, + response: AsyncIterable[object], request_data: dict, ) -> AsyncGenerator[ModelResponseStream | bytes, None]: """ diff --git a/litellm/proxy/guardrails/guardrail_hooks/xecguard/xecguard.py b/litellm/proxy/guardrails/guardrail_hooks/xecguard/xecguard.py index ddb40dc3ca0..831df43692b 100644 --- a/litellm/proxy/guardrails/guardrail_hooks/xecguard/xecguard.py +++ b/litellm/proxy/guardrails/guardrail_hooks/xecguard/xecguard.py @@ -310,7 +310,7 @@ class XecGuardGuardrail(CustomGuardrail): scan_type: str, suppress_errors: bool = False, ) -> dict | None: - payload: Final[dict[str, Any]] = { + payload: Final[dict[str, object]] = { "model": self.xecguard_model, "scan_type": scan_type, "messages": messages, @@ -385,7 +385,7 @@ class XecGuardGuardrail(CustomGuardrail): def _build_full_history( self, request_data: dict, - inputs: Any, + inputs: GenericGuardrailAPIInputs, input_type: str, ) -> list[dict]: """Assemble the full message list that will be sent to XecGuard. diff --git a/litellm/proxy/hooks/mcp_semantic_filter/hook.py b/litellm/proxy/hooks/mcp_semantic_filter/hook.py index 3ce406eef73..8b82842353c 100644 --- a/litellm/proxy/hooks/mcp_semantic_filter/hook.py +++ b/litellm/proxy/hooks/mcp_semantic_filter/hook.py @@ -5,10 +5,11 @@ Pre-call hook that filters MCP tools semantically before LLM inference. Reduces context window size and improves tool selection accuracy. """ -from collections.abc import Mapping, Sequence -from typing import TYPE_CHECKING, Any, Final, Optional +from collections.abc import Iterable, Mapping, Sequence +from typing import TYPE_CHECKING, Final, Optional from fastapi import HTTPException +from typing_extensions import ReadOnly, TypedDict from litellm._logging import verbose_proxy_logger from litellm.constants import ( @@ -30,6 +31,13 @@ if TYPE_CHECKING: from litellm.router import Router +class SemanticToolFilterConfig(TypedDict, total=False): + enabled: ReadOnly[bool] + embedding_model: ReadOnly[str] + top_k: ReadOnly[int] + similarity_threshold: ReadOnly[float] + + def _truncate_csv_at_tool_name_boundary(tool_names_csv: str, max_length: int) -> str: """Cap a CSV of tool names to max_length, dropping any name that does not fit whole.""" if len(tool_names_csv) <= max_length: @@ -68,7 +76,7 @@ class SemanticToolFilterHook(CustomLogger): semantic_filter.top_k, ) - def _should_expand_mcp_tools(self, tools: list[Any]) -> bool: + def _should_expand_mcp_tools(self, tools: Iterable[Mapping[str, object]]) -> bool: """ Check if tools contain MCP references with server_url="litellm_proxy". @@ -82,9 +90,9 @@ class SemanticToolFilterHook(CustomLogger): async def _expand_mcp_tools( self, - tools: list[Any], + tools: Iterable[Mapping[str, object]], user_api_key_dict: "UserAPIKeyAuth", - ) -> list[dict[str, Any]]: + ) -> list[dict[str, object]]: """ Expand MCP references to actual tool definitions. @@ -111,7 +119,7 @@ class SemanticToolFilterHook(CustomLogger): ) # Convert Pydantic models to dicts for compatibility - openai_tools_as_dicts: Final = [] + openai_tools_as_dicts: Final[list[dict[str, object]]] = [] for tool in openai_tools: if hasattr(tool, "model_dump"): tool_dict = tool.model_dump(exclude_none=True) @@ -141,8 +149,8 @@ class SemanticToolFilterHook(CustomLogger): async def _filter_expanded_tools( self, data: dict, - expanded_tools: list[dict[str, Any]], - ) -> list[dict[str, Any]]: + expanded_tools: list[dict[str, object]], + ) -> list[dict[str, object]]: """ Apply the semantic filter to expanded MCP tool definitions. @@ -159,7 +167,7 @@ class SemanticToolFilterHook(CustomLogger): return await self.filter.filter_tools(query=user_query, available_tools=expanded_tools) - def _selected_tool_names(self, filtered_tools: list[dict[str, Any]]) -> list[str]: + def _selected_tool_names(self, filtered_tools: Sequence[object]) -> list[str]: """Names of the semantically selected tools, as produced by the MCP expansion.""" names: Final = (self.filter._extract_tool_info(tool)[0] for tool in filtered_tools) return [name for name in names if name] @@ -217,10 +225,10 @@ class SemanticToolFilterHook(CustomLogger): def _emit_filter_metadata( self, data: dict, - mcp_tools: list[object], - filtered_mcp_tools: list[object], - native_tools: list[object], - filtered_tools: list[object], + mcp_tools: Sequence[object], + filtered_mcp_tools: Sequence[object], + native_tools: Sequence[object], + filtered_tools: Sequence[object], ) -> None: """ Emit response-header metadata when MCP tools were filtered. @@ -252,10 +260,10 @@ class SemanticToolFilterHook(CustomLogger): def _emit_filter_metadata_safe( self, data: dict, - mcp_tools: list[object], - filtered_mcp_tools: list[object], - native_tools: list[object], - filtered_tools: list[object], + mcp_tools: Sequence[object], + filtered_mcp_tools: Sequence[object], + native_tools: Sequence[object], + filtered_tools: Sequence[object], ) -> None: """ Emit filter metadata without letting an emission failure abort the @@ -375,7 +383,7 @@ class SemanticToolFilterHook(CustomLogger): ) if mcp_tools: - filtered_mcp_tools = await self.filter.filter_tools( + filtered_mcp_tools: list[object] = await self.filter.filter_tools( query=user_query, available_tools=mcp_tools, ) @@ -419,9 +427,9 @@ class SemanticToolFilterHook(CustomLogger): self, data: dict, user_api_key_dict: "UserAPIKeyAuth", - response: Any, + response: object, request_headers: dict[str, str] | None = None, - litellm_call_info: dict[str, Any] | None = None, + litellm_call_info: dict[str, object] | None = None, ) -> dict[str, str] | None: """Add semantic filter stats and tool names to response headers.""" from litellm.constants import MAX_MCP_SEMANTIC_FILTER_TOOLS_HEADER_LENGTH @@ -446,7 +454,7 @@ class SemanticToolFilterHook(CustomLogger): return headers - def _get_tool_names_csv(self, tools: list[Any]) -> str: + def _get_tool_names_csv(self, tools: Sequence[object]) -> str: """Extract tool names and return as CSV string.""" if not tools: return "" @@ -461,7 +469,7 @@ class SemanticToolFilterHook(CustomLogger): @staticmethod async def initialize_from_config( - config: dict[str, Any] | None, + config: SemanticToolFilterConfig | None, llm_router: Optional["Router"], ) -> Optional["SemanticToolFilterHook"]: """ diff --git a/litellm/proxy/litellm_pre_call_utils.py b/litellm/proxy/litellm_pre_call_utils.py index ae55b7ab906..20f83085286 100644 --- a/litellm/proxy/litellm_pre_call_utils.py +++ b/litellm/proxy/litellm_pre_call_utils.py @@ -4,9 +4,10 @@ import json import re import time from collections import OrderedDict -from collections.abc import Mapping, MutableMapping +from collections.abc import Mapping, MutableMapping, Sequence +from datetime import datetime from types import MappingProxyType -from typing import TYPE_CHECKING, Any, Final +from typing import TYPE_CHECKING, Any, Final, cast from fastapi import HTTPException, Request from pydantic import ValidationError as PydanticValidationError @@ -55,7 +56,7 @@ from litellm.proxy.common_utils.http_parsing_utils import _safe_get_request_head from litellm.types.integrations.anthropic_cache_control_hook import GATEWAY_INJECTED_CACHE_METADATA_KEY # Cache special headers as a frozenset for O(1) lookup performance -_SPECIAL_HEADERS_CACHE: Final = frozenset(v.value.lower() for v in SpecialHeaders._member_map_.values()) +_SPECIAL_HEADERS_CACHE: Final = frozenset(str(v.value).lower() for v in SpecialHeaders) _REDACTED_HEADER_VALUE: Final = "***REDACTED***" _CREDENTIAL_HEADER_NAMES: Final = SpecialHeaders.litellm_credential_header_names() | frozenset( @@ -126,7 +127,7 @@ def _stampable_key_hash(user_api_key_dict: UserAPIKeyAuth) -> str | None: _ANTHROPIC_SESSION_ID_VALUE_RE: Final = re.compile(r"^[a-zA-Z0-9_\-]+$") -def _sanitize_for_log(value: Any) -> str: +def _sanitize_for_log(value: object) -> str: """ Basic log sanitization helper to reduce log-injection risk. @@ -164,7 +165,7 @@ _ENABLE_TEAM_STALE_ALIAS_BYPASS: bool | None = None if TYPE_CHECKING: from litellm.proxy.proxy_server import ProxyConfig as _ProxyConfig - from litellm.types.proxy.policy_engine import PolicyMatchContext + from litellm.types.proxy.policy_engine import Policy, PolicyMatchContext ProxyConfig = _ProxyConfig else: @@ -328,7 +329,7 @@ _ALLOW_CLIENT_PRICING_OVERRIDE_METADATA_KEY: Final = "allow_client_pricing_overr _URL_DESTINATION_REQUEST_FIELDS: Final = ("model", "file_id") -def _reject_url_valued_destinations(data: dict[str, Any]) -> None: +def _reject_url_valued_destinations(data: dict[str, object]) -> None: """Reject URL-valued ``model``/``file_id`` unless admin-allowlisted. Some providers (HuggingFace, Oobabooga, Gemini files) accept a URL in the @@ -387,7 +388,7 @@ def _invalid_metadata_type_error(field: str, value: object) -> ProxyException: ) -def _normalized_metadata_object(field: str, value: object) -> Mapping[str, Any]: +def _normalized_metadata_object(field: str, value: object) -> Mapping[str, object]: """Return ``value`` as a metadata object or raise a 400 like OpenAI does. A JSON string that parses to an object is accepted because multipart/form-data @@ -402,6 +403,23 @@ def _normalized_metadata_object(field: str, value: object) -> Mapping[str, Any]: raise _invalid_metadata_type_error(field=field, value=value) +def _normalized_metadata_slot( + request_data: MutableMapping[str, object], metadata_variable_name: str +) -> dict[str, object]: + """Return the request's metadata slot as a dict, normalising it in place first. + + Metadata can arrive as a JSON string (multipart/form-data, ``extra_body``). Parsing it here keeps + existing entries alive through a merge instead of silently overwriting them with an empty dict. + """ + raw: Final = request_data.get(metadata_variable_name) + if isinstance(raw, dict): + return raw + parsed: Final = safe_json_loads(raw) if isinstance(raw, str) else None + normalized: Final[dict[str, object]] = parsed if isinstance(parsed, dict) else {} + request_data[metadata_variable_name] = normalized + return normalized + + def _strip_untrusted_request_header_controls( headers: Any, *, @@ -417,7 +435,7 @@ def _strip_untrusted_request_header_controls( headers.pop(header_name, None) -def _is_false_like(value: Any) -> bool: +def _is_false_like(value: object) -> bool: if isinstance(value, bool): return value is False if isinstance(value, str): @@ -462,7 +480,7 @@ def _key_or_team_allows_client_pricing_override( ) -def _strip_client_message_redaction_opt_out(data: dict[str, Any]) -> None: +def _strip_client_message_redaction_opt_out(data: dict[str, object]) -> None: stripped: Final[list[str]] = [] if "turn_off_message_logging" in data and _is_false_like(data["turn_off_message_logging"]): stripped.append("turn_off_message_logging") @@ -513,7 +531,7 @@ def _strip_client_callback_credentials( ) -def _strip_client_pricing_overrides(data: dict[str, Any]) -> None: +def _strip_client_pricing_overrides(data: dict[str, object]) -> None: """Drop pricing overrides from the request body and any metadata variant. Skipped only when the calling key/team carries @@ -580,9 +598,9 @@ def _get_metadata_variable_name(request: Request) -> str: def _promoted_trace_control_fields( - requester_metadata: Mapping[str, Any], - litellm_metadata: Mapping[str, Any], -) -> tuple[tuple[str, Any], ...]: + requester_metadata: Mapping[str, object], + litellm_metadata: Mapping[str, object], +) -> tuple[tuple[str, object], ...]: """Return the caller's trace-control fields that ``litellm_metadata`` does not already set.""" return tuple( (key, value) @@ -1193,7 +1211,7 @@ class LiteLLMProxyRequestSetup: def add_litellm_data_for_backend_llm_call( *, headers: dict, - request_data: Mapping[str, Any], + request_data: Mapping[str, object], user_api_key_dict: UserAPIKeyAuth, general_settings: dict[str, Any] | None = None, ) -> LitellmDataForBackendLLMCall: @@ -1327,6 +1345,8 @@ class LiteLLMProxyRequestSetup: def get_sanitized_user_information_from_key( user_api_key_dict: UserAPIKeyAuth, ) -> StandardLoggingUserAPIKeyMetadata: + stripped_metadata: Final = strip_callback_config(user_api_key_dict.metadata) + auth_metadata: Final = cast("dict[str, str] | None", stripped_metadata) # cast-ok: metadata is free-form JSON user_api_key_logged_metadata: Final = StandardLoggingUserAPIKeyMetadata( user_api_key_hash=user_api_key_dict.api_key, # just the hashed token user_api_key_alias=user_api_key_dict.key_alias, @@ -1349,7 +1369,7 @@ class LiteLLMProxyRequestSetup: user_api_key_budget_reset_at=( user_api_key_dict.budget_reset_at.isoformat() if user_api_key_dict.budget_reset_at else None ), - user_api_key_auth_metadata=strip_callback_config(user_api_key_dict.metadata), + user_api_key_auth_metadata=auth_metadata, ) return user_api_key_logged_metadata @@ -1577,14 +1597,7 @@ class LiteLLMProxyRequestSetup: return _metadata_variable_name: Final = get_metadata_variable_name_from_kwargs(request_data) - metadata = request_data.get(_metadata_variable_name) - if isinstance(metadata, str): - parsed: Final = safe_json_loads(metadata) - metadata = parsed if isinstance(parsed, dict) else {} - request_data[_metadata_variable_name] = metadata - elif not isinstance(metadata, dict): - metadata = {} - request_data[_metadata_variable_name] = metadata + metadata: Final = _normalized_metadata_slot(request_data, _metadata_variable_name) existing_tags: Final = metadata.get("tags") metadata["tags"] = LiteLLMProxyRequestSetup._merge_tags( @@ -1636,18 +1649,7 @@ class LiteLLMProxyRequestSetup: # from (litellm_metadata vs metadata) so the merged tags are visible # to _tag_max_budget_check. _metadata_variable_name: Final = get_metadata_variable_name_from_kwargs(request_data) - metadata = request_data.get(_metadata_variable_name) - # metadata can arrive as a JSON string (multipart/form-data, extra_body). - # Parse it so existing tags survive the merge — overwriting the string - # with {} would let a caller bypass _tag_max_budget_check on an - # over-budget body tag by also sending a within-budget header tag. - if isinstance(metadata, str): - parsed: Final = safe_json_loads(metadata) - metadata = parsed if isinstance(parsed, dict) else {} - request_data[_metadata_variable_name] = metadata - elif not isinstance(metadata, dict): - metadata = {} - request_data[_metadata_variable_name] = metadata + metadata: Final = _normalized_metadata_slot(request_data, _metadata_variable_name) existing_tags: Final = metadata.get("tags") metadata["tags"] = LiteLLMProxyRequestSetup._merge_tags( @@ -1787,7 +1789,7 @@ async def add_litellm_data_to_request( # admin-injection strip below so the audit / spend-tracking consumers of # proxy_server_request["body"] see the cleaned metadata rather than # attacker-forged user_api_key_* fields. - _litellm_received_at: Final = getattr(request.state, "litellm_received_at", None) + _litellm_received_at: Final[datetime | None] = getattr(request.state, "litellm_received_at", None) arrival_time: Final = _litellm_received_at.timestamp() if _litellm_received_at is not None else time.time() data["proxy_server_request"] = { "url": str(request.url), @@ -2472,16 +2474,16 @@ def _resolve_provider_from_deployment( if deployment is None: continue - litellm_params = getattr(deployment, "litellm_params", None) + litellm_params: object = getattr(deployment, "litellm_params", None) if litellm_params is None: continue custom_provider = getattr(litellm_params, "custom_llm_provider", None) - if custom_provider: + if isinstance(custom_provider, str) and custom_provider: return custom_provider - deployment_model = getattr(litellm_params, "model", "") or "" - if "/" in deployment_model: + deployment_model = getattr(litellm_params, "model", "") + if isinstance(deployment_model, str) and "/" in deployment_model: return deployment_model.split("/", 1)[0] return None @@ -2904,8 +2906,8 @@ def _extract_policy_id(s: str) -> str | None: def _match_and_track_policies( data: dict, context: "PolicyMatchContext", - request_body_policies: Any, - policies_override: dict[str, Any] | None = None, + request_body_policies: Sequence[str], + policies_override: dict[str, "Policy"] | None = None, ) -> tuple[list[str], dict[str, str]]: """ Match policies via attachments and request body, track them in metadata. @@ -2963,7 +2965,7 @@ def _apply_resolved_guardrails_to_metadata( metadata_variable_name: str, context: "PolicyMatchContext", policy_names: list[str] | None = None, - policies: dict[str, Any] | None = None, + policies: dict[str, "Policy"] | None = None, ) -> None: """Apply resolved guardrails and pipelines to request metadata.""" from litellm._logging import verbose_proxy_logger @@ -3093,7 +3095,7 @@ async def add_guardrails_from_policy_engine( request_body_names.append(item) # Resolve policy versions by ID from in-memory cache (populated by sync job; no DB in hot path) - merged_policies: Final[dict[str, Any]] = dict(registry.get_all_policies()) + merged_policies: Final[dict[str, Policy]] = dict(registry.get_all_policies()) fetched_policy_names: Final[list[str]] = [] for policy_id in request_body_version_ids: result = registry.get_policy_by_id_for_request(policy_id=policy_id) diff --git a/litellm/proxy/management_endpoints/key_management_endpoints.py b/litellm/proxy/management_endpoints/key_management_endpoints.py index 99e201930c1..c3403cf477c 100644 --- a/litellm/proxy/management_endpoints/key_management_endpoints.py +++ b/litellm/proxy/management_endpoints/key_management_endpoints.py @@ -738,6 +738,45 @@ def _check_allowed_routes_caller_permission( ) +_READ_ONLY_ALLOWED_ROUTES_PRESET: Final = frozenset(("info_routes",)) + + +def _is_safe_preset_route_transition( + incoming_allowed_routes: Sequence[str] | None, + existing_allowed_routes: Sequence[str] | None, +) -> bool: + """ + True when every route on BOTH sides is a safe `key_type` preset bucket + (empty = full access, which non-admins already get from a default + `/key/generate`), with one carve-out: a read-only (`info_routes`) key + stays read-only, so widening it needs an admin. Requiring the existing + side to be a safe preset keeps an owner from clearing an admin-set + custom route restriction (LIT-4139). + """ + incoming: Final = frozenset(incoming_allowed_routes or ()) + existing: Final = frozenset(existing_allowed_routes or ()) + if not (incoming | existing) <= _NON_ADMIN_SAFE_ALLOWED_ROUTES_PRESETS: + return False + return existing != _READ_ONLY_ALLOWED_ROUTES_PRESET or incoming == existing + + +def _enforce_allowed_routes_update_permission( + data: UpdateKeyRequest, + existing_key_row: LiteLLM_VerificationToken, + user_api_key_dict: UserAPIKeyAuth, +) -> None: + if _is_safe_preset_route_transition( + incoming_allowed_routes=data.allowed_routes, + existing_allowed_routes=existing_key_row.allowed_routes, + ): + return + _check_allowed_routes_caller_permission( + allowed_routes=data.allowed_routes, + user_api_key_dict=user_api_key_dict, + allowed_routes_was_provided="allowed_routes" in data.model_fields_set, + ) + + def _check_permissions_caller_permission( data: GenerateRequestBase, user_api_key_dict: UserAPIKeyAuth, @@ -2522,26 +2561,34 @@ async def _validate_mcp_servers_for_key_update( return normalized_object_permission +def _require_prisma_client(prisma_client: PrismaClient | None) -> PrismaClient: + if prisma_client is None: + raise HTTPException(status_code=500, detail={"error": "Database not connected"}) + return prisma_client + + async def _validate_update_key_data( data: UpdateKeyRequest, existing_key_row: LiteLLM_VerificationToken, user_api_key_dict: UserAPIKeyAuth, llm_router: Router | None, premium_user: bool, - prisma_client: Any, + prisma_client: PrismaClient | None, user_api_key_cache: UserApiKeyCache, ) -> None: """Validate permissions and constraints for key update.""" + checked_prisma_client: Final = _require_prisma_client(prisma_client) + # Reject NaN/±inf spend before it can reach the DB / spend counter. validate_finite_spend(data.spend) validate_budget_duration(data.budget_duration) _is_proxy_admin: Final = user_api_key_dict.user_role == LitellmUserRoles.PROXY_ADMIN.value - _check_allowed_routes_caller_permission( - allowed_routes=data.allowed_routes, + _enforce_allowed_routes_update_permission( + data=data, + existing_key_row=existing_key_row, user_api_key_dict=user_api_key_dict, - allowed_routes_was_provided="allowed_routes" in data.model_fields_set, ) _check_passthrough_routes_caller_permission( data=data, @@ -2569,7 +2616,7 @@ async def _validate_update_key_data( await TeamMemberPermissionChecks.can_team_member_execute_key_management_endpoint( user_api_key_dict=user_api_key_dict, route=KeyManagementRoutes.KEY_UPDATE, - prisma_client=prisma_client, + prisma_client=checked_prisma_client, existing_key_row=existing_key_row, user_api_key_cache=user_api_key_cache, ) @@ -2650,12 +2697,12 @@ async def _validate_update_key_data( # _check_key_admin_access that would otherwise require team/org admin status. _key_is_team_key: Final = getattr(existing_key_row, "team_id", None) is not None can_skip_admin_check: Final = (caller_is_creator or _key_is_team_key) and not _is_budget_change - if (not _is_proxy_admin) and prisma_client is not None and not can_skip_admin_check: + if (not _is_proxy_admin) and not can_skip_admin_check: hashed_key: Final = existing_key_row.token await _check_key_admin_access( user_api_key_dict=user_api_key_dict, hashed_token=hashed_key, - prisma_client=prisma_client, + prisma_client=checked_prisma_client, user_api_key_cache=user_api_key_cache, route=("/key/update (max_budget/spend)" if _is_budget_change else "/key/update"), ) @@ -2666,7 +2713,7 @@ async def _validate_update_key_data( if _team_id_to_check is not None: team_obj = await get_team_object( team_id=_team_id_to_check, - prisma_client=prisma_client, + prisma_client=checked_prisma_client, user_api_key_cache=user_api_key_cache, check_db_only=True, ) @@ -2682,7 +2729,7 @@ async def _validate_update_key_data( await _check_team_key_limits( team_table=team_obj, data=data, - prisma_client=prisma_client, + prisma_client=checked_prisma_client, ) TeamMemberPermissionChecks.enforce_member_can_assign_access_groups( @@ -2697,7 +2744,7 @@ async def _validate_update_key_data( await _check_project_key_limits( project_id=_project_id_to_check, data=data, - prisma_client=prisma_client, + prisma_client=checked_prisma_client, user_api_key_cache=user_api_key_cache, ) @@ -2712,7 +2759,7 @@ async def _validate_update_key_data( await _validate_caller_can_assign_key_org( user_api_key_dict=user_api_key_dict, organization_id=data.organization_id, - prisma_client=prisma_client, + prisma_client=checked_prisma_client, ) # Check org key limits only when throughput-related fields or organization_id change @@ -2728,7 +2775,7 @@ async def _validate_update_key_data( org_table: Final = await get_org_object( org_id=_org_id_to_check, user_api_key_cache=user_api_key_cache, - prisma_client=prisma_client, + prisma_client=checked_prisma_client, ) if org_table is None: raise HTTPException( @@ -2738,7 +2785,7 @@ async def _validate_update_key_data( await _check_org_key_limits( org_table=org_table, data=data, - prisma_client=prisma_client, + prisma_client=checked_prisma_client, ) # if team change - check if this is possible @@ -2768,7 +2815,7 @@ async def _validate_update_key_data( data=data, team_obj=team_obj, existing_key_row=existing_key_row, - prisma_client=prisma_client, + prisma_client=checked_prisma_client, user_api_key_cache=user_api_key_cache, is_proxy_admin=_is_proxy_admin, ) @@ -3834,7 +3881,7 @@ async def info_key_fn( except Exception: # if using pydantic v1 key_info = key_info.dict() # pyright: ignore[reportDeprecated] # deliberate pydantic v1 fallback - key_token_hash: Final = key_info.pop("token") + key_token_hash: Final[str | None] = key_info.pop("token") model_max_budget = key_info.get("model_max_budget") or {} budget_table: Final = key_info.get("litellm_budget_table") or {} @@ -5296,7 +5343,7 @@ def _validate_reset_spend_value(reset_to: object, key_in_db: LiteLLM_Verificatio max_budget = key_in_db.max_budget if key_in_db.litellm_budget_table is not None: - budget_max_budget: Final = getattr(key_in_db.litellm_budget_table, "max_budget", None) + budget_max_budget: Final[float | None] = getattr(key_in_db.litellm_budget_table, "max_budget", None) if budget_max_budget is not None: if max_budget is None or budget_max_budget < max_budget: max_budget = budget_max_budget diff --git a/litellm/proxy/management_endpoints/policy_endpoints/endpoints.py b/litellm/proxy/management_endpoints/policy_endpoints/endpoints.py index 108e6a7b47d..f58f3722741 100644 --- a/litellm/proxy/management_endpoints/policy_endpoints/endpoints.py +++ b/litellm/proxy/management_endpoints/policy_endpoints/endpoints.py @@ -13,7 +13,7 @@ import copy import json import os from collections.abc import AsyncIterator -from typing import TYPE_CHECKING, Any, Final, Literal, cast +from typing import TYPE_CHECKING, Final, Literal, cast from fastapi import APIRouter, Depends, HTTPException, Request from fastapi.responses import Response, StreamingResponse @@ -90,7 +90,7 @@ class _ApplyPoliciesResultBase(TypedDict): class ApplyPoliciesResult(_ApplyPoliciesResultBase, total=False): """Result of apply_policies. agent_response set when agent_id provided.""" - agent_response: Any + agent_response: object class _ApplyPoliciesPerItemResultBase(TypedDict): @@ -103,7 +103,7 @@ class _ApplyPoliciesPerItemResultBase(TypedDict): class ApplyPoliciesPerItemResult(_ApplyPoliciesPerItemResultBase, total=False): """Result for one input when using inputs_list. agent_response set when agent_id provided.""" - agent_response: Any + agent_response: object class ApplyPoliciesListResult(TypedDict): @@ -295,8 +295,8 @@ async def test_policies_and_guardrails( from litellm.proxy.proxy_server import chat_completion, proxy_logging_obj from litellm.proxy.utils import handle_exception_on_proxy - def _serialize_chat_response(response: Any) -> Any: - if hasattr(response, "model_dump"): + def _serialize_chat_response(response: object) -> object: + if isinstance(response, BaseModel): return response.model_dump(exclude_unset=True) if isinstance(response, dict): return response @@ -306,7 +306,7 @@ async def test_policies_and_guardrails( inputs: GenericGuardrailAPIInputs, agent_id: str, user_api_key_dict: UserAPIKeyAuth, - ) -> Any: + ) -> object: body: Final = _chat_body_from_inputs(inputs, agent_id, data.request_data) req: Final = _request_with_json_body(body) resp: Final = Response() diff --git a/litellm/proxy/management_endpoints/team_endpoints.py b/litellm/proxy/management_endpoints/team_endpoints.py index c6d7975b75e..714cf252e69 100644 --- a/litellm/proxy/management_endpoints/team_endpoints.py +++ b/litellm/proxy/management_endpoints/team_endpoints.py @@ -5148,6 +5148,7 @@ async def list_team_v2( # Get teams with pagination if use_deleted_table: + # LiteLLM_DeletedTeamTable has no litellm_model_table relation, unlike below teams = await _deleted_team_db(prisma_client).find_many( where=where_conditions, skip=skip, @@ -5162,6 +5163,7 @@ async def list_team_v2( skip=skip, take=page_size, order=order_by if order_by else {"created_at": "desc"}, # Default sort + include=_INCLUDE_MODEL_TABLE, ) # Get total count for pagination total_count = await _team_db(prisma_client).count(where=where_conditions) diff --git a/litellm/proxy/management_helpers/object_permission_utils.py b/litellm/proxy/management_helpers/object_permission_utils.py index 13080a6cf83..a2fbf80422c 100644 --- a/litellm/proxy/management_helpers/object_permission_utils.py +++ b/litellm/proxy/management_helpers/object_permission_utils.py @@ -286,7 +286,7 @@ async def _resolve_mcp_server_identifiers_to_ids( return resolved -def _rewrite_object_permission_mcp_servers( +def _drop_stale_object_permission_mcp_servers( object_permission: ObjectPermissionDict, identifier_to_server_ids: dict[str, set[str]], ) -> None: @@ -294,16 +294,18 @@ def _rewrite_object_permission_mcp_servers( if not isinstance(mcp_servers, list): return - normalized_servers: Final[list[str]] = [] - for identifier in mcp_servers: - if identifier == SpecialMCPServerNames.no_mcp_servers.value: - normalized_servers.append(SpecialMCPServerNames.no_mcp_servers.value) - continue - normalized_servers.extend(sorted(identifier_to_server_ids.get(identifier, []))) - object_permission["mcp_servers"] = _dedupe_preserving_order(normalized_servers) + # Persist original identifiers, never resolved ids: shared-DB multi-region + # instances each expand a name/alias to their own local server id at read + # time. Only entries resolving to nothing (deleted servers, typos) drop. + kept_servers: Final = [ + identifier + for identifier in mcp_servers + if identifier == SpecialMCPServerNames.no_mcp_servers.value or identifier_to_server_ids.get(identifier) + ] + object_permission["mcp_servers"] = _dedupe_preserving_order(kept_servers) -def _rewrite_object_permission_mcp_tool_permissions( +def _drop_stale_object_permission_mcp_tool_permissions( object_permission: ObjectPermissionDict, identifier_to_server_ids: dict[str, set[str]], ) -> None: @@ -311,31 +313,25 @@ def _rewrite_object_permission_mcp_tool_permissions( if not isinstance(mcp_tool_permissions, dict): return - normalized_tool_permissions: Final[dict[str, list[str]]] = {} - for identifier, tools in mcp_tool_permissions.items(): - if not isinstance(tools, list): - tools = [] - for server_id in sorted(identifier_to_server_ids.get(identifier, [])): - normalized_tool_permissions.setdefault(server_id, []) - normalized_tool_permissions[server_id].extend(tools) - object_permission["mcp_tool_permissions"] = { - server_id: _dedupe_preserving_order(tools) for server_id, tools in normalized_tool_permissions.items() + identifier: _dedupe_preserving_order(tools if isinstance(tools, list) else []) + for identifier, tools in mcp_tool_permissions.items() + if identifier_to_server_ids.get(identifier) } -def _rewrite_object_permission_mcp_identifiers( +def _drop_stale_object_permission_mcp_identifiers( object_permission: ObjectPermissionDict | None, identifier_to_server_ids: dict[str, set[str]], ) -> None: if not object_permission or not isinstance(object_permission, dict): return - _rewrite_object_permission_mcp_servers( + _drop_stale_object_permission_mcp_servers( object_permission=object_permission, identifier_to_server_ids=identifier_to_server_ids, ) - _rewrite_object_permission_mcp_tool_permissions( + _drop_stale_object_permission_mcp_tool_permissions( object_permission=object_permission, identifier_to_server_ids=identifier_to_server_ids, ) @@ -615,7 +611,7 @@ async def validate_key_mcp_servers_against_team( "validate_key_mcp_servers_against_team: ignoring stale MCP server identifiers (no longer in registry or DB): %s", sorted(stale_identifiers), ) - _rewrite_object_permission_mcp_identifiers( + _drop_stale_object_permission_mcp_identifiers( object_permission=object_permission, identifier_to_server_ids=identifier_to_server_ids, ) diff --git a/litellm/proxy/pass_through_endpoints/llm_passthrough_endpoints.py b/litellm/proxy/pass_through_endpoints/llm_passthrough_endpoints.py index 1d28ad1914f..78d8ce296b8 100644 --- a/litellm/proxy/pass_through_endpoints/llm_passthrough_endpoints.py +++ b/litellm/proxy/pass_through_endpoints/llm_passthrough_endpoints.py @@ -14,7 +14,7 @@ import os import re from collections.abc import Callable, Mapping from types import MappingProxyType -from typing import TYPE_CHECKING, Annotated, Any, Final, cast +from typing import TYPE_CHECKING, Annotated, Final, cast import httpx from fastapi import APIRouter, Depends, HTTPException, Request, Response, WebSocket @@ -69,6 +69,7 @@ from litellm.types.passthrough_endpoints.pass_through_endpoints import ( ) from litellm.types.passthrough_endpoints.vertex_ai import VertexPassThroughCredentials from litellm.types.utils import LlmProviders +from litellm.types.vector_stores import LiteLLM_ManagedVectorStore from litellm.utils import ProviderConfigManager from .passthrough_endpoint_router import PassthroughEndpointRouter @@ -121,7 +122,21 @@ def is_passthrough_request_streaming(request_body: object) -> bool: return bool(request_body.get("stream", False)) -def get_passthrough_router_request_metadata(user_api_key_dict: UserAPIKeyAuth) -> Mapping[str, Any]: +def _optional_str(value: object) -> str | None: + return value if isinstance(value, str) else None + + +def _string_keyed_mapping(value: object) -> Mapping[str, object] | None: + if isinstance(value, Mapping): + return value + return None + + +async def _json_request_body(request: Request) -> Mapping[str, object]: + return await request.json() + + +def get_passthrough_router_request_metadata(user_api_key_dict: UserAPIKeyAuth) -> Mapping[str, object]: """ Build the request metadata carrying key-level spend attribution and the pre-call budget reservation for a router-model passthrough request. @@ -210,7 +225,7 @@ async def llm_passthrough_factory_proxy_route( # anthropic is streaming when 'stream' = True is in the body if request.method == "POST": if "multipart/form-data" not in request.headers.get("content-type", ""): - _request_body = await request.json() + _request_body = await _json_request_body(request) else: _request_body = await get_form_data(request) @@ -383,7 +398,7 @@ async def vllm_proxy_route( endpoint=endpoint, request_query_params=request.query_params, request_headers=_safe_get_request_headers(request), - stream=request_body.get("stream", False), + stream=is_streaming_request, content=None, data=None, files=None, @@ -817,7 +832,7 @@ async def handle_bedrock_passthrough_router_model( # Use the common processing path (same as non-router models) # This ensures all metadata, hooks, and logging are properly initialized - data: Final[dict[str, Any]] = {} + data: Final[dict[str, object]] = {} base_llm_response_processor: Final = ProxyBaseLLMRequestProcessing(data=data) data["model"] = model @@ -861,8 +876,8 @@ async def handle_bedrock_count_tokens( request: Request, fastapi_response: Response, user_api_key_dict: UserAPIKeyAuth, - request_body: dict[str, Any], -) -> dict[str, Any]: + request_body: dict[str, object], +) -> dict[str, object]: """ Handle AWS Bedrock CountTokens API requests. @@ -879,7 +894,7 @@ async def handle_bedrock_count_tokens( handler: Final = BedrockCountTokensHandler() # Extract model from request body - model: Final = request_body.get("model") + model: Final = _optional_str(request_body.get("model")) if not model: raise HTTPException(status_code=400, detail={"error": "Model is required in request body"}) @@ -1011,7 +1026,7 @@ async def bedrock_llm_proxy_route( "Bedrock passthrough: Using direct Bedrock model '%s' for endpoint '%s'", model, endpoint ) - data: Final[dict[str, Any]] = {} + data: Final[dict[str, object]] = {} base_llm_response_processor: Final = ProxyBaseLLMRequestProcessing(data=data) data["method"] = request.method @@ -1110,7 +1125,7 @@ async def bedrock_proxy_route( headers: Final = {"Content-Type": "application/json"} # Assuming the body contains JSON data, parse it try: - data: Final = await request.json() + data: Final = await _json_request_body(request) except Exception as e: raise HTTPException(status_code=400, detail={"error": e}) _request: Final = AWSRequest(method="POST", url=str(updated_url), data=json.dumps(data), headers=headers) @@ -1201,7 +1216,7 @@ async def comprehend_medical_proxy_route( ) try: - data: Final = await request.json() + data: Final = await _json_request_body(request) except Exception as e: raise HTTPException(status_code=400, detail=str(e)) @@ -1412,7 +1427,7 @@ async def assemblyai_proxy_route( is_streaming_request = False # assemblyai is streaming when 'stream' = True is in the body if request.method == "POST": - _request_body: Final = await request.json() + _request_body: Final = await _json_request_body(request) if _request_body.get("stream"): is_streaming_request = True @@ -1519,7 +1534,7 @@ async def azure_proxy_route( endpoint=endpoint, request_query_params=request.query_params, request_headers=_safe_get_request_headers(request), - stream=request_body.get("stream", False), + stream=is_streaming_request, content=None, data=None, files=None, @@ -1606,7 +1621,7 @@ async def azure_proxy_route( extra_headers = auth_credentials.get("headers") or {} - base_target_url = litellm_params.get("api_base") + base_target_url = _optional_str(litellm_params.get("api_base")) if base_target_url is None: raise Exception(f"API base not found for {part}") return await BaseOpenAIPassThroughHandler._base_openai_pass_through_handler( @@ -1727,7 +1742,7 @@ def get_vertex_pass_through_handler( def _override_vertex_params_from_router_credentials( - router_credentials: Any | None, + router_credentials: LiteLLM_ManagedVectorStore | None, vertex_project: str | None, vertex_location: str | None, ) -> tuple[str | None, str | None]: @@ -1747,14 +1762,14 @@ def _override_vertex_params_from_router_credentials( verbose_proxy_logger.debug("Using vector store credentials to override vertex project and location") - litellm_params: Final = router_credentials.get("litellm_params", {}) + litellm_params: Final = _string_keyed_mapping(router_credentials.get("litellm_params")) if not litellm_params: verbose_proxy_logger.warning("Vector store credentials found but litellm_params is empty") return vertex_project, vertex_location # Extract vertex_project and vertex_location from litellm_params - vector_store_project: Final = litellm_params.get("vertex_project") - vector_store_location: Final = litellm_params.get("vertex_location") + vector_store_project: Final = _optional_str(litellm_params.get("vertex_project")) + vector_store_location: Final = _optional_str(litellm_params.get("vertex_location")) if vector_store_project: verbose_proxy_logger.debug( @@ -1762,7 +1777,6 @@ def _override_vertex_params_from_router_credentials( vertex_project, vector_store_project, ) - vertex_project = vector_store_project else: verbose_proxy_logger.warning("Vector store credentials found but missing vertex_project in litellm_params") @@ -1772,11 +1786,10 @@ def _override_vertex_params_from_router_credentials( vertex_location, vector_store_location, ) - vertex_location = vector_store_location else: verbose_proxy_logger.warning("Vector store credentials found but missing vertex_location in litellm_params") - return vertex_project, vertex_location + return vector_store_project or vertex_project, vector_store_location or vertex_location _CREDENTIALLESS_VERTEX_MISSING_CREDENTIAL_DETAIL: Final = ( @@ -1884,8 +1897,8 @@ def _forwarded_headers_for_credentialless_vertex_passthrough( async def _prepare_vertex_auth_headers( request: Request, - vertex_credentials: Any | None, - router_credentials: Any | None, + vertex_credentials: VertexPassThroughCredentials | None, + router_credentials: LiteLLM_ManagedVectorStore | None, vertex_project: str | None, vertex_location: str | None, base_target_url: str | None, @@ -1982,7 +1995,7 @@ async def _base_vertex_proxy_route( fastapi_response: Response, get_vertex_pass_through_handler: BaseVertexAIPassThroughHandler, user_api_key_dict: UserAPIKeyAuth | None = None, - router_credentials: Any | None = None, + router_credentials: LiteLLM_ManagedVectorStore | None = None, ): """ Base function for Vertex AI passthrough routes. @@ -2152,8 +2165,6 @@ async def vertex_discovery_proxy_route( """ import re - from litellm.types.vector_stores import LiteLLM_ManagedVectorStore - # Extract vector store ID from endpoint if present (e.g., dataStores/test-litellm-app_1761094730750) vector_store_credentials: LiteLLM_ManagedVectorStore | None = None vector_store_id_match: Final = re.search(r"dataStores/([^/]+)", endpoint) @@ -3098,7 +3109,7 @@ async def watsonx_proxy_route( is_streaming_request = False if request.method == "POST": if "multipart/form-data" not in request.headers.get("content-type", ""): - _request_body = await request.json() + _request_body = await _json_request_body(request) else: _request_body = await get_form_data(request) diff --git a/litellm/proxy/pass_through_endpoints/pass_through_endpoints.py b/litellm/proxy/pass_through_endpoints/pass_through_endpoints.py index ddd27f0fc2a..ff306eb65f1 100644 --- a/litellm/proxy/pass_through_endpoints/pass_through_endpoints.py +++ b/litellm/proxy/pass_through_endpoints/pass_through_endpoints.py @@ -3233,6 +3233,14 @@ def _get_pass_through_endpoints_from_config() -> list[PassThroughGenericEndpoint return returned_endpoints +def _config_field_endpoints(response: ConfigFieldInfo) -> list[object] | None: + return response.field_value + + +def _request_app(request: Request) -> FastAPI: + return request.app + + async def _get_pass_through_endpoints_from_db( endpoint_id: str | None = None, user_api_key_dict: UserAPIKeyAuth | None = None, @@ -3249,7 +3257,7 @@ async def _get_pass_through_endpoints_from_db( except Exception: return [] - pass_through_endpoint_data: Final[list | None] = response.field_value + pass_through_endpoint_data: Final = _config_field_endpoints(response) if pass_through_endpoint_data is None: return [] @@ -3412,7 +3420,7 @@ async def update_pass_through_endpoints( detail={"error": "No pass-through endpoints found"}, ) - pass_through_endpoint_data: Final[list | None] = response.field_value + pass_through_endpoint_data: Final[list | None] = _config_field_endpoints(response) if pass_through_endpoint_data is None: raise HTTPException( status_code=404, @@ -3483,7 +3491,7 @@ async def update_pass_through_endpoints( _custom_headers: dict | None = updated_endpoint.headers or {} _custom_headers = await set_env_variables_in_header(custom_headers=_custom_headers) - route_app: Final[FastAPI] = request.app + route_app: Final = _request_app(request) if updated_endpoint.include_subpath: InitPassThroughEndpointHelpers.add_subpath_route( app=route_app, @@ -3575,7 +3583,7 @@ async def create_pass_through_endpoints( _custom_headers: dict | None = created_endpoint.headers or {} _custom_headers = await set_env_variables_in_header(custom_headers=_custom_headers) - route_app: Final[FastAPI] = request.app + route_app: Final = _request_app(request) if created_endpoint.include_subpath: InitPassThroughEndpointHelpers.add_subpath_route( app=route_app, @@ -3643,7 +3651,7 @@ async def delete_pass_through_endpoints( response = ConfigFieldInfo(field_name="pass_through_endpoints", field_value=None) ## Update field by removing endpoint - pass_through_endpoint_data: Final[list | None] = response.field_value + pass_through_endpoint_data: Final[list | None] = _config_field_endpoints(response) if response.field_value is None or pass_through_endpoint_data is None: raise HTTPException( status_code=400, diff --git a/litellm/proxy/policy_engine/pipeline_executor.py b/litellm/proxy/policy_engine/pipeline_executor.py index 50cb813c6fa..4be0f556ed7 100644 --- a/litellm/proxy/policy_engine/pipeline_executor.py +++ b/litellm/proxy/policy_engine/pipeline_executor.py @@ -6,6 +6,7 @@ pass/fail actions (allow, block, next, modify_response) and data forwarding. """ import time +from collections.abc import Sequence from typing import Any, Final, Literal import litellm @@ -114,11 +115,7 @@ class PipelineExecutor: # Handle terminal actions if action == "allow": - return PipelineExecutionResult( - terminal_action="allow", - step_results=step_results, - modified_data=working_data if working_data != data else None, - ) + return _allow_result(step_results=step_results, working_data=working_data, request_data=data) if action == "block": return PipelineExecutionResult( @@ -138,11 +135,7 @@ class PipelineExecutor: # action == "next" → continue to next step # Ran out of steps without a terminal action → default allow - return PipelineExecutionResult( - terminal_action="allow", - step_results=step_results, - modified_data=working_data if working_data != data else None, - ) + return _allow_result(step_results=step_results, working_data=working_data, request_data=data) @staticmethod async def _run_step( @@ -251,6 +244,45 @@ class PipelineExecutor: return None +def _allow_result( + step_results: Sequence[PipelineStepResult], + working_data: dict, # mutable-ok: same request-payload shape as execute_steps' data + request_data: dict, # mutable-ok: same request-payload shape as execute_steps' data +) -> PipelineExecutionResult: + """Build the terminal-allow result, propagating pipeline modifications without the per-step guardrail override.""" + restored: Final = _restore_request_guardrails(working_data, request_data) + return PipelineExecutionResult( + terminal_action="allow", + step_results=list(step_results), # mutable-ok: PipelineExecutionResult field is a list + modified_data=restored if restored != request_data else None, + ) + + +def _restore_request_guardrails( + working_data: dict, # mutable-ok: same request-payload shape as execute_steps' data + request_data: dict, # mutable-ok: same request-payload shape as execute_steps' data +) -> dict: # mutable-ok: merged back into the request dict, which downstream code mutates + """ + Restore the request's own metadata["guardrails"] activation list. + + _run_step overrides it to [step.guardrail] so should_run_guardrail() allows each + step; letting that override escape via modified_data permanently drops every + independently activated guardrail from later lifecycle stages (post_call, etc.). + """ + working_metadata: Final = working_data.get("metadata") + if not isinstance(working_metadata, dict): + return working_data + request_metadata: Final = request_data.get("metadata") + original_guardrails: Final = request_metadata.get("guardrails") if isinstance(request_metadata, dict) else None + stripped: Final = {k: v for k, v in working_metadata.items() if k != "guardrails"} # mutable-ok: request dict + if original_guardrails is not None: + restored: Final = {**stripped, "guardrails": original_guardrails} # mutable-ok: request dict + return {**working_data, "metadata": restored} # mutable-ok: request dict + if not stripped and not isinstance(request_metadata, dict): + return {k: v for k, v in working_data.items() if k != "metadata"} # mutable-ok: request dict + return {**working_data, "metadata": stripped} # mutable-ok: request dict + + def _pipeline_action_for_outcome(step: PipelineStep, outcome: str) -> str: """ Map pipeline step outcome to the configured action. diff --git a/litellm/proxy/rag_endpoints/endpoints.py b/litellm/proxy/rag_endpoints/endpoints.py index 4d62f1d6d71..db574f859b3 100644 --- a/litellm/proxy/rag_endpoints/endpoints.py +++ b/litellm/proxy/rag_endpoints/endpoints.py @@ -7,12 +7,14 @@ Provides: """ import base64 +import json from collections.abc import Mapping from typing import TYPE_CHECKING, Any, Final import orjson from fastapi import APIRouter, Depends, HTTPException, Request, Response, status from fastapi.responses import ORJSONResponse, StreamingResponse +from starlette.datastructures import UploadFile import litellm from litellm._logging import verbose_proxy_logger @@ -45,6 +47,16 @@ if TYPE_CHECKING: router: Final = APIRouter() +def _as_string_keyed_mapping(value: object) -> Mapping[str, object] | None: + if isinstance(value, Mapping): + return value + return None + + +def _response_attr(source: object, name: str) -> object: + return getattr(source, name, None) + + def _raise_vector_store_scan_depth_exceeded() -> None: raise HTTPException( status_code=400, @@ -53,8 +65,8 @@ def _raise_vector_store_scan_depth_exceeded() -> None: def _append_payload_to_scan_stack( - payload_stack: list[tuple[Any, int]], - value: Any, + payload_stack: list[tuple[object, int]], + value: object, next_depth: int, ) -> None: if isinstance(value, dict): @@ -117,7 +129,7 @@ async def _authorize_nested_vector_store_ids( def _build_file_metadata_entry( - response: Any, + response: object, file_data: tuple[str, bytes, str] | None = None, file_url: str | None = None, ) -> Mapping[str, str | int | None]: @@ -135,11 +147,11 @@ def _build_file_metadata_entry( from datetime import datetime, timezone # Extract file_id from response - file_id = None - if hasattr(response, "get"): - file_id = response.get("file_id") - elif hasattr(response, "file_id"): - file_id = response.file_id + mapping_response: Final = _as_string_keyed_mapping(response) + raw_file_id: Final = ( + mapping_response.get("file_id") if mapping_response is not None else _response_attr(response, "file_id") + ) + file_id: Final = raw_file_id if isinstance(raw_file_id, str) else None # Extract file information from file_data tuple filename = None @@ -152,7 +164,7 @@ def _build_file_metadata_entry( content_type = file_data[2] if len(file_data) > 2 else None # Build file metadata entry - file_entry: Final = { + file_entry: Final[dict[str, str | int | None]] = { "file_id": file_id, "filename": filename, "file_url": file_url, @@ -169,7 +181,7 @@ def _build_file_metadata_entry( async def _save_vector_store_to_db_from_rag_ingest( - response: Any, + response: object, ingest_options: Mapping[str, dict[str, str | None]], prisma_client: "PrismaClient", user_api_key_dict: UserAPIKeyAuth, @@ -197,10 +209,11 @@ async def _save_vector_store_to_db_from_rag_ingest( ) # Handle both dict and object responses - if hasattr(response, "get"): - vector_store_id = response.get("vector_store_id") + mapping_response: Final = _as_string_keyed_mapping(response) + if mapping_response is not None: + vector_store_id = mapping_response.get("vector_store_id") elif hasattr(response, "vector_store_id"): - vector_store_id = response.vector_store_id + vector_store_id = _response_attr(response, "vector_store_id") else: verbose_proxy_logger.warning("Unable to extract vector_store_id from response type: %s", type(response)) return @@ -266,14 +279,13 @@ async def _save_vector_store_to_db_from_rag_ingest( verbose_proxy_logger.info("Vector store %s already exists, appending file to metadata", vector_store_id) # Update existing vector store with new file - existing_metadata = existing_vector_store.vector_store_metadata or {} - if isinstance(existing_metadata, str): - import json + stored_metadata: Final = existing_vector_store.vector_store_metadata or {} + existing_metadata: dict[str, object] = ( + json.loads(stored_metadata) if isinstance(stored_metadata, str) else stored_metadata + ) - existing_metadata = json.loads(existing_metadata) - - ingested_files: Final = existing_metadata.get("ingested_files", []) - ingested_files.append(file_entry) + previous_files: Final = existing_metadata.get("ingested_files", []) + ingested_files: Final = [*previous_files, file_entry] if isinstance(previous_files, list) else [file_entry] existing_metadata["ingested_files"] = ingested_files # Update the vector store @@ -340,9 +352,9 @@ async def parse_rag_ingest_request( # Get file file_obj = form_data.get("file") - if file_obj is not None and hasattr(file_obj, "read"): + if isinstance(file_obj, UploadFile): file_content = await file_obj.read(MAX_UPLOAD_SIZE_BYTES + 1) - file_data = (file_obj.filename, file_content, file_obj.content_type) + file_data = (file_obj.filename or "", file_content, file_obj.content_type or "") # Parse JSON from 'request' form field (contains full request body as JSON) request_json_str: Final[str | bytes | None] = form_data.get("request") diff --git a/litellm/proxy/response_polling/background_streaming.py b/litellm/proxy/response_polling/background_streaming.py index b03122966c0..0fd242f2bc1 100644 --- a/litellm/proxy/response_polling/background_streaming.py +++ b/litellm/proxy/response_polling/background_streaming.py @@ -76,17 +76,17 @@ class _StreamEventParser: async def background_streaming_task( polling_id: str, - data: dict, + data: dict[str, object], polling_handler: ResponsePollingHandler, request: Request, fastapi_response: Response, user_api_key_dict: UserAPIKeyAuth, - general_settings: dict, + general_settings: dict[str, object], llm_router: "Router | None", proxy_config: "ProxyConfig", proxy_logging_obj: "ProxyLogging", - select_data_generator, - user_model, + select_data_generator: Callable[..., object] | None, + user_model: str | None, user_temperature: float | None, user_request_timeout: float | None, user_max_tokens: int | None, diff --git a/litellm/proxy/spend_tracking/budget_reservation.py b/litellm/proxy/spend_tracking/budget_reservation.py index 2d113cfe355..f4d8fd7d906 100644 --- a/litellm/proxy/spend_tracking/budget_reservation.py +++ b/litellm/proxy/spend_tracking/budget_reservation.py @@ -6,7 +6,7 @@ from collections.abc import Mapping, Sequence from dataclasses import dataclass from datetime import datetime, timedelta, timezone from types import MappingProxyType -from typing import Any, Final, NoReturn, cast +from typing import Final, NoReturn, SupportsFloat, SupportsIndex, SupportsInt, cast from fastapi import HTTPException, status @@ -35,6 +35,7 @@ from litellm.proxy.common_utils.user_api_key_cache import ( from litellm.proxy.utils import PrismaClient, ProxyLogging from litellm.router import Router from litellm.types.proxy.model_access_group_budget import ModelAccessGroupBudget +from litellm.types.router import DeploymentTypedDict @dataclass @@ -697,7 +698,7 @@ def _get_budget_limit_counters( for window in budget_limits: window_dict = _coerce_window(window) budget_duration = window_dict.get("budget_duration") - max_budget = window_dict.get("max_budget") + max_budget = _to_float(window_dict.get("max_budget")) if not budget_duration or max_budget is None or max_budget <= 0: continue window_start = get_budget_window_start(window_dict) @@ -724,18 +725,20 @@ def _get_budget_limit_counters( return counters -def _coerce_window(window: Any) -> dict: - if isinstance(window, dict): +def _coerce_window(window: object) -> Mapping[str, object]: + if isinstance(window, Mapping): return window if isinstance(window, str): try: - parsed: Final = json.loads(window) - return parsed if isinstance(parsed, dict) else {} + parsed: Final[object] = json.loads(window) except Exception: return {} - if hasattr(window, "model_dump"): - return window.model_dump() - return {} + return parsed if isinstance(parsed, Mapping) else {} + model_dump: Final = getattr(window, "model_dump", None) + if not callable(model_dump): + return {} + dumped: Final[object] = model_dump() + return dumped if isinstance(dumped, Mapping) else {} async def _reserve_counter( @@ -953,7 +956,7 @@ def _get_entry_reserved_cost(entry: dict, default_reserved_cost: float) -> float return default_reserved_cost -def get_budget_window_start(window: Any) -> datetime | None: +def get_budget_window_start(window: object) -> datetime | None: window_dict: Final = _coerce_window(window) budget_duration: Final = window_dict.get("budget_duration") if budget_duration is None: @@ -971,7 +974,7 @@ def get_budget_window_start(window: Any) -> datetime | None: return reset_at - timedelta(seconds=duration_seconds) -def _coerce_datetime(value: Any) -> datetime | None: +def _coerce_datetime(value: object) -> datetime | None: if value is None: return None if isinstance(value, datetime): @@ -1245,11 +1248,11 @@ def _get_model_cost_infos( def _deployment_tiered_pricing_table( - deployment: dict[str, Any], + deployment: DeploymentTypedDict, llm_router: Router, -) -> list[dict] | None: - model_id: Final = deployment.get("model_info", {}).get("id") - backend_model: Final = deployment.get("litellm_params", {}).get("model") +) -> Sequence[Mapping[str, object]] | None: + model_id: Final = _get_value(_get_value(deployment, "model_info"), "id") + backend_model: Final = _get_value(_get_value(deployment, "litellm_params"), "model") if not isinstance(model_id, str) or not isinstance(backend_model, str): return None deployment_model_info: Final = llm_router.get_deployment_model_info(model_id=model_id, model_name=backend_model) @@ -1414,7 +1417,7 @@ def _estimate_output_tokens( return min(requested, model_ceiling) -def _count_text_tokens(model: str, text: Any) -> int: +def _count_text_tokens(model: str, text: object) -> int: if text is None: return 0 @@ -1454,8 +1457,8 @@ def _is_input_only_route(route: str) -> bool: ) -def _to_float(value: Any) -> float | None: - if value is None: +def _to_float(value: object) -> float | None: + if not isinstance(value, (SupportsFloat, SupportsIndex, str, bytes, bytearray)): return None try: return float(value) @@ -1463,8 +1466,8 @@ def _to_float(value: Any) -> float | None: return None -def _to_int(value: Any) -> int | None: - if value is None: +def _to_int(value: object) -> int | None: + if not isinstance(value, (SupportsInt, SupportsIndex, str, bytes, bytearray)): return None try: return int(value) @@ -1472,7 +1475,7 @@ def _to_int(value: Any) -> int | None: return None -def _get_value(obj: Any, key: str) -> Any: - if isinstance(obj, dict): +def _get_value(obj: object, key: str) -> object: + if isinstance(obj, Mapping): return obj.get(key) return getattr(obj, key, None) diff --git a/litellm/proxy/spend_tracking/spend_tracking_utils.py b/litellm/proxy/spend_tracking/spend_tracking_utils.py index 9f718b7d20d..7442d71bd96 100644 --- a/litellm/proxy/spend_tracking/spend_tracking_utils.py +++ b/litellm/proxy/spend_tracking/spend_tracking_utils.py @@ -1,10 +1,10 @@ import os import re import secrets -from collections.abc import Mapping +from collections.abc import Mapping, Sequence from datetime import datetime, timezone from datetime import datetime as dt -from typing import Any, Final, Literal, cast +from typing import Final, Literal, Protocol, cast, runtime_checkable from pydantic import BaseModel @@ -222,7 +222,28 @@ def get_spend_logs_id(call_type: str, response_obj: dict, kwargs: dict) -> str | return resolved_id -def _extract_usage_for_ocr_call(response_obj: Any, response_obj_dict: dict) -> dict: +_MISSING_ATTRIBUTE: Final = object() + + +def _attribute_or_missing(source: object, name: str) -> object: + return getattr(source, name, _MISSING_ATTRIBUTE) + + +@runtime_checkable +class _ModelDumpable(Protocol): + def model_dump(self) -> object: ... + + +def _dumped_usage_info(usage_info: object) -> object: + if isinstance(usage_info, _ModelDumpable): + return usage_info.model_dump() + instance_dict: Final = _attribute_or_missing(usage_info, "__dict__") + if instance_dict is not _MISSING_ATTRIBUTE: + return instance_dict + return usage_info + + +def _extract_usage_for_ocr_call(response_obj: object, response_obj_dict: dict) -> dict: """ Extract usage information for OCR/AOCR calls. @@ -243,12 +264,10 @@ def _extract_usage_for_ocr_call(response_obj: Any, response_obj_dict: dict) -> d usage_info = response_obj_dict.get("usage_info") # Try to extract usage_info from object attributes if not found in dict - if not usage_info and hasattr(response_obj, "usage_info"): - usage_info = response_obj.usage_info - if hasattr(usage_info, "model_dump"): - usage_info = usage_info.model_dump() - elif hasattr(usage_info, "__dict__"): - usage_info = vars(usage_info) + if not usage_info: + attribute_usage_info: Final = _attribute_or_missing(response_obj, "usage_info") + if attribute_usage_info is not _MISSING_ATTRIBUTE: + usage_info = _dumped_usage_info(attribute_usage_info) # For OCR, we track pages instead of tokens if usage_info is not None: @@ -620,6 +639,14 @@ def _ensure_datetime_utc(timestamp: datetime) -> datetime: return timestamp +async def _query_raw_rows( + prisma_client: PrismaClient, + sql_query: str, + *args: object, +) -> Sequence[Mapping[str, object]] | None: + return await prisma_client.db.query_raw(sql_query, *args) + + async def get_spend_by_team( start_date: dt, end_date: dt, @@ -681,7 +708,7 @@ async def get_spend_by_team( group_by_day; """ - db_response: Final = await prisma_client.db.query_raw(sql_query, start_date, end_date, team_id) + db_response: Final = await _query_raw_rows(prisma_client, sql_query, start_date, end_date, team_id) if db_response is None: return [] @@ -756,7 +783,7 @@ async def get_spend_by_team_and_customer( group_by_day; """ - db_response: Final = await prisma_client.db.query_raw(sql_query, start_date, end_date, team_id, customer_id) + db_response: Final = await _query_raw_rows(prisma_client, sql_query, start_date, end_date, team_id, customer_id) if db_response is None: return [] @@ -811,7 +838,7 @@ def _sanitize_request_body_for_spend_logs_payload( return {} visited.add(obj_id) - def _sanitize_value(value: Any) -> Any: + def _sanitize_value(value: object) -> object: if isinstance(value, dict): return _sanitize_request_body_for_spend_logs_payload(value, visited, max_string_length_prompt_in_db) elif isinstance(value, list): @@ -1106,7 +1133,7 @@ def _sanitize_error_information_for_spend_logs( return cast(StandardLoggingPayloadErrorInformation, sanitized) -def _convert_to_json_serializable_dict(obj: Any, visited: set | None = None, max_depth: int = 20) -> Any: +def _convert_to_json_serializable_dict(obj: object, visited: set[int] | None = None, max_depth: int = 20) -> object: """ Convert object to JSON-serializable dict, handling Pydantic models safely. @@ -1160,6 +1187,13 @@ def _convert_to_json_serializable_dict(obj: Any, visited: set | None = None, max visited.remove(obj_id) +def _convert_mapping_to_json_serializable(obj: Mapping[str, object]) -> dict[str, object]: + converted: Final = _convert_to_json_serializable_dict(obj) + if isinstance(converted, dict): + return converted + return dict(obj) + + def _get_proxy_server_request_for_spend_logs_payload( metadata: dict, litellm_params: dict, @@ -1196,7 +1230,7 @@ def _get_proxy_server_request_for_spend_logs_payload( # If redaction is enabled, convert to serializable dict before redacting if should_redact_message_logging(model_call_details=model_call_details): - _request_body = _convert_to_json_serializable_dict(_request_body) + _request_body = _convert_mapping_to_json_serializable(_request_body) perform_redaction(model_call_details=_request_body, result=None) _request_body = _sanitize_request_body_for_spend_logs_payload(_request_body) @@ -1241,7 +1275,7 @@ def _get_response_for_spend_logs_payload( if payload is None: return "{}" if _should_store_prompts_and_responses_in_spend_logs(): - response_obj: Any = payload.get("response") + response_obj: object = payload.get("response") if response_obj is None: return "{}" diff --git a/litellm/proxy/ui_crud_endpoints/proxy_setting_endpoints.py b/litellm/proxy/ui_crud_endpoints/proxy_setting_endpoints.py index a1eb7ed06eb..52258602581 100644 --- a/litellm/proxy/ui_crud_endpoints/proxy_setting_endpoints.py +++ b/litellm/proxy/ui_crud_endpoints/proxy_setting_endpoints.py @@ -3,10 +3,11 @@ import asyncio import json import os from collections import Counter -from collections.abc import Mapping +from collections.abc import Mapping, Sequence +from types import MappingProxyType from typing import ( - Any, Final, + NamedTuple, Protocol, cast, # noqa: TID251 # prisma types Json columns as fields.Json but de-serializes them to plain python on read ) @@ -15,6 +16,7 @@ from urllib.parse import urlparse from fastapi import APIRouter, Body, Depends, File, HTTPException, UploadFile from pydantic import ConfigDict, JsonValue, ValidationError, create_model from pydantic.fields import FieldInfo +from typing_extensions import NotRequired, ReadOnly, TypedDict import litellm from litellm._logging import verbose_proxy_logger @@ -44,6 +46,31 @@ from litellm.types.proxy.management_endpoints.ui_sso import ( router: Final = APIRouter() +JsonSchemaItems: Final = TypedDict( + "JsonSchemaItems", + {"$ref": ReadOnly[str], "enum": ReadOnly[Sequence[JsonValue]]}, + total=False, +) + + +class JsonSchemaNode(TypedDict, total=False): + type: ReadOnly[str] + description: ReadOnly[str] + enum: ReadOnly[Sequence[JsonValue]] + anyOf: ReadOnly[Sequence["JsonSchemaNode"]] + items: ReadOnly["JsonSchemaItems"] + properties: ReadOnly[Mapping[str, "JsonSchemaNode"]] + + +_EMPTY_SCHEMA_DEFS: Final[Mapping[str, "JsonSchemaNode"]] = MappingProxyType({}) + + +class JsonSchemaPropertyEntry(TypedDict): + description: ReadOnly[str] + type: ReadOnly[str] + items: NotRequired[ReadOnly["JsonSchemaItems"]] + + class _SsoSettingsMappingRow(Protocol): @property def sso_settings(self) -> Mapping[str, object] | None: ... @@ -157,10 +184,10 @@ class UIThemeConfig(BaseModel): class SettingsResponse(BaseModel): """Base response model for settings with values and schema information""" - values: dict[str, Any] + values: dict[str, object] """The current configuration values""" - field_schema: dict[str, Any] + field_schema: dict[str, object] """Schema information including descriptions and property types for UI display""" @@ -548,6 +575,62 @@ async def delete_allowed_ip( return {"message": f"IP {ip_address.ip} deleted successfully", "status": "success"} +def _resolve_non_null_variant(field_info: JsonSchemaNode) -> JsonSchemaNode: + """Pydantic v2 renders Optional fields as ``anyOf: [actual_type, null]``.""" + if "anyOf" not in field_info: + return field_info + return next((variant for variant in field_info["anyOf"] if variant.get("type") != "null"), field_info) + + +def _schema_items_entry(resolved: JsonSchemaNode, defs: Mapping[str, JsonSchemaNode]) -> "JsonSchemaItems | None": + """Items info (including enum values) for array fields, so the UI can render a multi-select dropdown.""" + if "items" not in resolved: + return None + items: Final = resolved["items"] + if "$ref" not in items: + return items + ref_def: Final = defs.get(items["$ref"].split("/")[-1]) + if ref_def is None or "enum" not in ref_def: + return None + enum_items: Final[JsonSchemaItems] = {"enum": ref_def["enum"]} + return enum_items + + +def _schema_property_entry(field_info: JsonSchemaNode, defs: Mapping[str, JsonSchemaNode]) -> JsonSchemaPropertyEntry: + resolved: Final = _resolve_non_null_variant(field_info) + items_entry: Final = _schema_items_entry(resolved, defs) + description: Final = field_info.get("description", "") + type_name: Final = resolved.get("type", "string") + if items_entry is None: + entry: Final[JsonSchemaPropertyEntry] = {"description": description, "type": type_name} + return entry + entry_with_items: Final[JsonSchemaPropertyEntry] = { + "description": description, + "type": type_name, + "items": items_entry, + } + return entry_with_items + + +class _RootSchema(NamedTuple): + description: str + properties: Mapping[str, JsonSchemaNode] + nested_defs: Mapping[str, JsonSchemaNode] + defs: Mapping[str, JsonSchemaNode] + + +def _root_schema(settings_class: type[BaseModel]) -> _RootSchema: + from pydantic import TypeAdapter + + raw_schema: Final = TypeAdapter(settings_class).json_schema(by_alias=True) + return _RootSchema( + description=raw_schema.get("description", ""), + properties=raw_schema["properties"], + nested_defs=raw_schema.get("definitions", _EMPTY_SCHEMA_DEFS), + defs=raw_schema["$defs"] if "$defs" in raw_schema else raw_schema.get("definitions", _EMPTY_SCHEMA_DEFS), + ) + + async def _get_settings_with_schema( settings_key: str, settings_class: type[BaseModel], @@ -561,69 +644,43 @@ async def _get_settings_with_schema( settings_class: The Pydantic class to use for schema config: The config dictionary """ - from pydantic import TypeAdapter - litellm_settings: Final = config.get("litellm_settings", {}) or {} settings_data: Final = litellm_settings.get(settings_key, {}) or {} # Create the settings object settings: Final = settings_class(**(settings_data)) # Get the schema - schema: Final = TypeAdapter(settings_class).json_schema(by_alias=True) + root_schema: Final = _root_schema(settings_class) # Convert to dict for response settings_dict: Final = settings.model_dump() # Add descriptions to the response - result: Final = { - "values": settings_dict, - "field_schema": { - "description": schema.get("description", ""), - "properties": {}, - }, + schema_properties_out: Final[Mapping[str, JsonSchemaPropertyEntry]] = { + field_name: _schema_property_entry(field_info, root_schema.defs) + for field_name, field_info in root_schema.properties.items() } - # Add property descriptions - defs: Final = schema.get("$defs", schema.get("definitions", {})) - for field_name, field_info in schema["properties"].items(): - # For Optional fields, Pydantic v2 uses anyOf with [actual_type, null]. - # Resolve the non-null variant to get the real type and items. - resolved = field_info - if "anyOf" in field_info: - for variant in field_info["anyOf"]: - if variant.get("type") != "null": - resolved = variant - break - - prop_entry: dict = { - "description": field_info.get("description", ""), - "type": resolved.get("type", "string"), - } - # Pass through items info (including enum values) for array fields - # so the UI can render a multi-select dropdown - if "items" in resolved: - items = resolved["items"] - # Resolve $ref to enum definitions if needed - if "$ref" in items: - ref_name = items["$ref"].split("/")[-1] - ref_def = defs.get(ref_name, {}) - if "enum" in ref_def: - prop_entry["items"] = {"enum": ref_def["enum"]} - else: - prop_entry["items"] = items - result["field_schema"]["properties"][field_name] = prop_entry - # Add nested object descriptions - for def_name, def_schema in schema.get("definitions", {}).items(): - result["field_schema"][def_name] = { + nested_defs_out: Final[Mapping[str, Mapping[str, object]]] = { + def_name: { "description": def_schema.get("description", ""), "properties": { prop_name: {"description": prop_info.get("description", "")} for prop_name, prop_info in def_schema.get("properties", {}).items() }, } + for def_name, def_schema in root_schema.nested_defs.items() + } - return result + return { + "values": settings_dict, + "field_schema": { + "description": root_schema.description, + "properties": schema_properties_out, + **nested_defs_out, + }, + } @router.get( @@ -930,32 +987,29 @@ async def get_sso_settings(): resolved: Final = resolve_sso_config(sso_db_settings, os.environ) # Get the schema for UI display - from pydantic import TypeAdapter - - schema: Final = TypeAdapter(SSOConfig).json_schema(by_alias=True) + root_schema: Final = _root_schema(SSOConfig) # Convert to dict for response, masking OAuth client secrets so plaintext # is never sent to the UI. sso_dict: Final = mask_sensitive_keys(resolved.config.model_dump(), set(SSO_SECRET_FIELDS)) # Add descriptions to the response - result: Final = { - "values": sso_dict, - "provenance": resolved.provenance, - "field_schema": { - "description": schema.get("description", ""), - "properties": {}, - }, - } - - # Add property descriptions - for field_name, field_info in schema["properties"].items(): - result["field_schema"]["properties"][field_name] = { + schema_properties_out: Final[Mapping[str, Mapping[str, str]]] = { + field_name: { "description": field_info.get("description", ""), "type": field_info.get("type", "string"), } + for field_name, field_info in root_schema.properties.items() + } - return result + return { + "values": sso_dict, + "provenance": resolved.provenance, + "field_schema": { + "description": root_schema.description, + "properties": schema_properties_out, + }, + } @router.patch( @@ -1309,7 +1363,7 @@ UI_SETTINGS_CACHE_KEY: Final = "ui_settings:settings_dict" UI_SETTINGS_CACHE_TTL: Final = 600 # 10 minutes -async def get_ui_settings_cached() -> dict[str, Any]: +async def get_ui_settings_cached() -> dict[str, JsonValue]: """ Return the persisted UI settings dict, using DualCache for reads. diff --git a/litellm/responses/litellm_completion_transformation/custom_tools.py b/litellm/responses/litellm_completion_transformation/custom_tools.py index cccae06c74b..90491739bb0 100644 --- a/litellm/responses/litellm_completion_transformation/custom_tools.py +++ b/litellm/responses/litellm_completion_transformation/custom_tools.py @@ -45,6 +45,21 @@ def is_custom_tool_call(tool_name: str, custom_tool_names: set[str]) -> bool: return tool_name in custom_tool_names +def serialize_tool_call_arguments(raw_arguments: object, default: str = "") -> str: + """Render tool call arguments as the JSON string tool-call schemas require. + + Arguments normally arrive already JSON-encoded, but clients and providers + also send the decoded object. ``str()`` on a dict yields a Python repr with + single quotes, which every downstream JSON parser rejects with errors like + "Expecting ',' delimiter". + """ + if isinstance(raw_arguments, str): + return raw_arguments or default + if raw_arguments is None: + return default + return json.dumps(raw_arguments, default=str) + + def unwrap_custom_tool_arguments(arguments: str) -> str: """Extract the raw content string from JSON-wrapped arguments. diff --git a/litellm/responses/litellm_completion_transformation/streaming_iterator.py b/litellm/responses/litellm_completion_transformation/streaming_iterator.py index 8b1eeb30306..b2edf2bf9ed 100644 --- a/litellm/responses/litellm_completion_transformation/streaming_iterator.py +++ b/litellm/responses/litellm_completion_transformation/streaming_iterator.py @@ -8,6 +8,7 @@ from litellm.main import stream_chunk_builder from litellm.responses.litellm_completion_transformation.custom_tools import ( build_tool_call_item_kwargs, extract_custom_tool_names, + serialize_tool_call_arguments, ) from litellm.responses.litellm_completion_transformation.transformation import ( LiteLLMCompletionResponsesConfig, @@ -213,10 +214,10 @@ class LiteLLMCompletionStreamingIterator(ResponsesAPIStreamingIterator): fn_args_delta = "" if isinstance(fn, dict): fn_name = str(fn.get("name") or "") - fn_args_delta = str(fn.get("arguments") or "") + fn_args_delta = serialize_tool_call_arguments(fn.get("arguments")) else: fn_name = str(getattr(fn, "name", "") or "") - fn_args_delta = str(getattr(fn, "arguments", "") or "") + fn_args_delta = serialize_tool_call_arguments(getattr(fn, "arguments", "")) tool_name, tool_namespace = self._responses_namespace_tool_call_fields(fn_name) output_index = self._get_or_assign_tool_output_index(call_id) @@ -284,10 +285,10 @@ class LiteLLMCompletionStreamingIterator(ResponsesAPIStreamingIterator): fn_args = "" if isinstance(fn, dict): fn_name = str(fn.get("name") or "") - fn_args = str(fn.get("arguments") or "") + fn_args = serialize_tool_call_arguments(fn.get("arguments")) else: fn_name = str(getattr(fn, "name", "") or "") - fn_args = str(getattr(fn, "arguments", "") or "") + fn_args = serialize_tool_call_arguments(getattr(fn, "arguments", "")) tool_name, tool_namespace = self._responses_namespace_tool_call_fields(fn_name) # Track if this is a new tool call that wasn't streamed diff --git a/litellm/responses/litellm_completion_transformation/transformation.py b/litellm/responses/litellm_completion_transformation/transformation.py index 4a416f61e1b..3b7810e97e5 100644 --- a/litellm/responses/litellm_completion_transformation/transformation.py +++ b/litellm/responses/litellm_completion_transformation/transformation.py @@ -93,6 +93,7 @@ from .custom_tools import ( convert_custom_tool_to_function_tool, extract_custom_tool_names, is_custom_tool_call, + serialize_tool_call_arguments, unwrap_custom_tool_arguments, validated_allowed_callers, ) @@ -1010,7 +1011,7 @@ class LiteLLMCompletionResponsesConfig: type=cast(Literal["function"], tool_use_type), function=ChatCompletionToolCallFunctionChunk( name=str(function.get("name", "")), - arguments=str(function.get("arguments", "{}")), + arguments=serialize_tool_call_arguments(function.get("arguments"), "{}"), ), index=index, ) @@ -1539,7 +1540,7 @@ class LiteLLMCompletionResponsesConfig: type=cast(Literal["function"], _tool_use_definition.get("type") or "function"), function=ChatCompletionToolCallFunctionChunk( name=function.get("name") or "", - arguments=str(function.get("arguments") or ""), + arguments=serialize_tool_call_arguments(function.get("arguments")), ), index=0, ) @@ -1589,7 +1590,7 @@ class LiteLLMCompletionResponsesConfig: type="function", function=ChatCompletionToolCallFunctionChunk( name=f"{namespace}__{raw_name}" if qualify else raw_name, - arguments=str(raw_arguments or ""), + arguments=serialize_tool_call_arguments(raw_arguments), ), index=0, ) @@ -2024,7 +2025,7 @@ class LiteLLMCompletionResponsesConfig: function_definition = tool.function tool_name = function_definition.name or "" tool_id = tool.id or "" - tool_arguments = function_definition.get("arguments") or "" + tool_arguments = serialize_tool_call_arguments(function_definition.get("arguments")) # Check if this is a custom tool if is_custom_tool_call(tool_name, custom_tool_names): @@ -2559,7 +2560,7 @@ class LiteLLMCompletionResponsesConfig: type="function", function=Function( name=tool_call.get("name") or "", - arguments=tool_call.get("arguments") or "", + arguments=serialize_tool_call_arguments(tool_call.get("arguments")), ), ) diff --git a/litellm/responses/streaming_iterator.py b/litellm/responses/streaming_iterator.py index d070f7758fd..de802b95086 100644 --- a/litellm/responses/streaming_iterator.py +++ b/litellm/responses/streaming_iterator.py @@ -77,6 +77,16 @@ def _is_json_array(value: object) -> TypeIs[list[object]]: # guard-ok: trivial return isinstance(value, list) +def _optional_str(value: object) -> str | None: + """Keep a JSON payload entry only when it is a string, since the wire format is caller-controlled.""" + return value if isinstance(value, str) else None + + +def _json_array_or_empty(value: object) -> Sequence[object]: + """Narrow a JSON payload entry that the caller iterates, tolerating a missing or malformed value.""" + return value if _is_json_array(value) else () + + def _is_str_mapping(value: object) -> TypeIs[dict[str, str]]: # guard-ok: verifies every value is str return _is_json_object(value) and all(isinstance(item, str) for item in value.values()) @@ -96,10 +106,6 @@ class _GetsLitellmParams(Protocol): def __call__(self, key: str, default: Mapping[str, object], /) -> LiteLLM_Params: ... -class _PopsOptionalStr(Protocol): - def __call__(self, key: str, default: None, /) -> str | None: ... - - class _UnmasksPiiText(Protocol): def __call__(self, text: str, pii_tokens: Mapping[str, str]) -> str: ... @@ -127,10 +133,6 @@ def _typed_gets_litellm_params(fn: _GetsLitellmParams) -> _GetsLitellmParams: return fn -def _typed_pops_optional_str(fn: _PopsOptionalStr) -> _PopsOptionalStr: - return fn - - _SHOULD_STORE_RESULT_IN_CACHE_ATTR: Final = "_should_store_result_in_cache" _UNMASK_PII_TEXT_ATTR: Final = "_unmask_pii_text" @@ -342,7 +344,7 @@ class BaseResponsesAPIStreamingIterator: ResponsesAPIStreamEvents.OUTPUT_ITEM_ADDED, ResponsesAPIStreamEvents.OUTPUT_ITEM_DONE, ): - _item: Final = getattr(openai_responses_api_chunk, "item", None) + _item: Final[object] = getattr(openai_responses_api_chunk, "item", None) if _item is not None: ResponsesAPIRequestUtils._encode_container_id_on_output_item( item=_item, @@ -350,7 +352,7 @@ class BaseResponsesAPIStreamingIterator: model_id=_stream_model_id, ) elif _event_type == ResponsesAPIStreamEvents.OUTPUT_TEXT_ANNOTATION_ADDED: - _annotation: Final = getattr(openai_responses_api_chunk, "annotation", None) + _annotation: Final[object] = getattr(openai_responses_api_chunk, "annotation", None) if _annotation is not None: ResponsesAPIRequestUtils._encode_container_id_on_output_item( item=_annotation, @@ -1310,8 +1312,7 @@ def _build_synthetic_response_events( ) if item_type == "message": - raw_content_parts = output_item_payload.get("content") - content_parts: Sequence[object] = raw_content_parts if _is_json_array(raw_content_parts) else [] + content_parts: Sequence[object] = _json_array_or_empty(output_item_payload.get("content")) for content_index, part in enumerate(content_parts): part_payload = _dump_response_object(part) events.append( @@ -1359,9 +1360,8 @@ def _build_synthetic_response_events( ) ) elif item_type == "reasoning": - raw_summary_items = output_item_payload.get("summary") - summary_items: Sequence[object] = raw_summary_items if _is_json_array(raw_summary_items) else [] - for summary_index, summary in enumerate(summary_items): + summaries: Sequence[object] = _json_array_or_empty(output_item_payload.get("summary")) + for summary_index, summary in enumerate(summaries): summary_payload = _dump_response_object(summary) summary_text = str(summary_payload.get("text") or "") for i in range(0, len(summary_text), chunk_size): @@ -2518,14 +2518,12 @@ class ManagedResponsesWebSocketHandler: # reuse the router-resolved self.model; passing the alias raw to # litellm.aresponses fails in get_llm_provider. A genuinely different # provider-prefixed per-frame model is still honored. - requested_model: Final[str | None] = _typed_pops_optional_str(call_kwargs.pop)("model", None) + requested_model: Final[str | None] = _optional_str(call_kwargs.pop("model", None)) model: Final[str] = ( self.model if requested_model is None or requested_model == self.model_group else requested_model ) - previous_response_id: Final[str | None] = _typed_pops_optional_str(call_kwargs.pop)( - "previous_response_id", None - ) + previous_response_id: Final[str | None] = _optional_str(call_kwargs.pop("previous_response_id", None)) current_messages: Final = self._input_to_messages(call_kwargs.get("input")) # Fetch history once; reused in both _apply_history and _save_turn_history diff --git a/litellm/types/guardrail_base_init.py b/litellm/types/guardrail_base_init.py new file mode 100644 index 00000000000..9174e8d840f --- /dev/null +++ b/litellm/types/guardrail_base_init.py @@ -0,0 +1,24 @@ +"""Typed view of the scalar keyword payload guardrails forward to ``CustomGuardrail.__init__``. + +Guardrail subclasses collect their base-class options in ``**kwargs`` and splat them into +``super().__init__``. Declaring the payload's shape here lets the checker resolve each +forwarded argument to its real parameter type instead of ``Any``. +""" + +from typing_extensions import ReadOnly, TypedDict + + +class GuardrailBaseInitKwargs(TypedDict, total=False): + guardrail_name: ReadOnly[str | None] + default_on: ReadOnly[bool] + mask_request_content: ReadOnly[bool] + mask_response_content: ReadOnly[bool] + violation_message_template: ReadOnly[str | None] + end_session_after_n_fails: ReadOnly[int | None] + on_violation: ReadOnly[str | None] + realtime_violation_message: ReadOnly[str | None] + on_sensitive_data: ReadOnly[str | None] + sensitive_data_route_to_model: ReadOnly[str | None] + sticky_session_routing: ReadOnly[bool] + run_in_parallel: ReadOnly[bool] + only_scan_new_messages: ReadOnly[bool] diff --git a/litellm/utils.py b/litellm/utils.py index b6e8e378e81..b130dd45e89 100644 --- a/litellm/utils.py +++ b/litellm/utils.py @@ -3561,10 +3561,10 @@ def get_optional_params_embeddings( non_default_params=non_default_params, optional_params={}, kwargs=kwargs ) elif custom_llm_provider == "vertex_ai" or custom_llm_provider == "gemini": - # OpenAI SDKs (and litellm's own client) send encoding_format="float" - # by default; float lists are exactly what the vertex API returns, so - # the param is a no-op — don't reject the provider default. Other - # values (e.g. "base64") stay on the unsupported-param path below. + # OpenAI SDKs send encoding_format="float" by default; float lists are + # exactly what the vertex API returns, so the param is a no-op and the + # provider default is not rejected. Other values (e.g. "base64") stay + # on the unsupported-param path below. if non_default_params.get("encoding_format") == "float": non_default_params.pop("encoding_format") supported_params = get_supported_openai_params( @@ -8278,10 +8278,17 @@ class ProviderConfigManager: """ # Handle OpenAI special cases (O-series and GPT-5 models) if provider == LlmProviders.OPENAI: + from litellm.llms.openai.chat.gpt_transformation import ( + OpenAIGPTConfig, + OpenAIUnknownModelConfig, + ) + if litellm.openaiOSeriesConfig.is_model_o_series_model(model=model): return litellm.openaiOSeriesConfig if litellm.OpenAIGPT5Config.is_model_gpt_5_model(model=model): return litellm.OpenAIGPT5Config() + if not OpenAIGPTConfig.is_openai_catalog_model(model): + return OpenAIUnknownModelConfig() # Handle Azure before the generic map so base_model can be threaded through if provider == LlmProviders.AZURE: diff --git a/model_prices_and_context_window.json b/model_prices_and_context_window.json index 80dc49a770b..e001c6b0f9d 100644 --- a/model_prices_and_context_window.json +++ b/model_prices_and_context_window.json @@ -554,6 +554,7 @@ "supports_vision": true }, "amazon.nova-sonic-v1:0": { + "deprecation_date": "2026-09-14", "input_cost_per_audio_token": 3.4e-06, "input_cost_per_token": 6e-08, "litellm_provider": "bedrock", @@ -3045,6 +3046,7 @@ "prompt_cache_min_tokens": 2048 }, "azure_ai/claude-fable-5": { + "deprecation_date": "2027-12-05", "supports_mid_conversation_system": true, "input_cost_per_token": 1e-05, "output_cost_per_token": 5e-05, @@ -3078,6 +3080,7 @@ "prompt_cache_min_tokens": 512 }, "azure_ai/claude-opus-5": { + "deprecation_date": "2027-07-08", "supports_mid_conversation_system": true, "supports_adaptive_thinking": true, "input_cost_per_token": 5e-06, @@ -3110,6 +3113,7 @@ "prompt_cache_min_tokens": 512 }, "azure_ai/claude-opus-4-8": { + "deprecation_date": "2027-09-01", "supports_mid_conversation_system": true, "supports_adaptive_thinking": true, "input_cost_per_token": 5e-06, @@ -3188,6 +3192,7 @@ "prompt_cache_min_tokens": 1024 }, "azure_ai/claude-sonnet-5": { + "deprecation_date": "2027-06-30", "supports_mid_conversation_system": true, "cache_creation_input_token_cost": 2.5e-06, "cache_creation_input_token_cost_above_1hr": 4e-06, @@ -12287,6 +12292,7 @@ "supports_tool_choice": true }, "cerebras/zai-glm-4.7": { + "deprecation_date": "2026-08-17", "input_cost_per_token": 2.25e-06, "litellm_provider": "cerebras", "max_input_tokens": 128000, @@ -15101,6 +15107,62 @@ "supports_tool_choice": true, "supports_vision": true }, + "databricks/databricks-deepseek-v4-flash-0731": { + "cache_creation_input_token_cost": 1.4e-07, + "cache_read_input_token_cost": 2.8e-08, + "input_cost_per_token": 1.4e-07, + "input_dbu_cost_per_token": 2e-06, + "litellm_provider": "databricks", + "max_input_tokens": 1000000, + "max_output_tokens": 393216, + "max_tokens": 393216, + "metadata": { + "notes": "Input/output cost per token is dbu cost * $0.070. Billing reads the per-token dollar fields; the '*_dbu_cost_per_token' fields are the published Databricks rates, kept for reference. Context/max output are the DeepSeek-published model limits (1M context, 384K max output)." + }, + "mode": "chat", + "output_cost_per_token": 2.8e-07, + "output_dbu_cost_per_token": 4e-06, + "source": "https://www.databricks.com/product/pricing/foundation-model-serving", + "supported_modalities": [ + "text" + ], + "supported_output_modalities": [ + "text" + ], + "supports_function_calling": true, + "supports_prompt_caching": true, + "supports_reasoning": true, + "supports_tool_choice": true, + "supports_vision": false + }, + "databricks/databricks-deepseek-v4-pro-0813": { + "cache_creation_input_token_cost": 1.31999e-06, + "cache_read_input_token_cost": 1.3202e-07, + "input_cost_per_token": 1.31999e-06, + "input_dbu_cost_per_token": 1.8857e-05, + "litellm_provider": "databricks", + "max_input_tokens": 1000000, + "max_output_tokens": 393216, + "max_tokens": 393216, + "metadata": { + "notes": "Input/output cost per token is dbu cost * $0.070. Billing reads the per-token dollar fields; the '*_dbu_cost_per_token' fields are the published Databricks rates, kept for reference. Context/max output are the DeepSeek-published model limits (1M context, 384K max output)." + }, + "mode": "chat", + "output_cost_per_token": 3.95997e-06, + "output_dbu_cost_per_token": 5.6571e-05, + "source": "https://www.databricks.com/product/pricing/foundation-model-serving", + "supported_modalities": [ + "text" + ], + "supported_output_modalities": [ + "text" + ], + "supports_function_calling": true, + "supports_prompt_caching": true, + "supports_reasoning": true, + "supports_tool_choice": true, + "supports_vision": false + }, "databricks/databricks-gemini-2-5-flash": { "cache_creation_input_token_cost": 3.0002e-07, "cache_read_input_token_cost": 3.0002e-08, @@ -20631,6 +20693,7 @@ "supports_image_size": false }, "gemini-live-2.5-flash-native-audio": { + "deprecation_date": "2026-12-13", "input_cost_per_audio_token": 3e-06, "input_cost_per_token": 5e-07, "litellm_provider": "vertex_ai-language-models", @@ -23852,8 +23915,10 @@ "max_input_tokens": 1024, "max_tokens": 1024, "mode": "video_generation", - "output_cost_per_second": 0.15, - "source": "https://ai.google.dev/gemini-api/docs/video", + "output_cost_per_second": 0.1, + "output_cost_per_second_1080p": 0.12, + "output_cost_per_second_4k": 0.3, + "source": "https://ai.google.dev/gemini-api/docs/pricing", "supported_modalities": [ "text" ], @@ -23867,7 +23932,8 @@ "max_tokens": 1024, "mode": "video_generation", "output_cost_per_second": 0.4, - "source": "https://ai.google.dev/gemini-api/docs/video", + "output_cost_per_second_4k": 0.6, + "source": "https://ai.google.dev/gemini-api/docs/pricing", "supported_modalities": [ "text" ], @@ -23895,8 +23961,10 @@ "max_input_tokens": 1024, "max_tokens": 1024, "mode": "video_generation", - "output_cost_per_second": 0.15, - "source": "https://ai.google.dev/gemini-api/docs/video", + "output_cost_per_second": 0.1, + "output_cost_per_second_1080p": 0.12, + "output_cost_per_second_4k": 0.3, + "source": "https://ai.google.dev/gemini-api/docs/pricing", "supported_modalities": [ "text" ], @@ -23910,7 +23978,8 @@ "max_tokens": 1024, "mode": "video_generation", "output_cost_per_second": 0.4, - "source": "https://ai.google.dev/gemini-api/docs/video", + "output_cost_per_second_4k": 0.6, + "source": "https://ai.google.dev/gemini-api/docs/pricing", "supported_modalities": [ "text" ], @@ -43440,7 +43509,8 @@ "max_tokens": 1024, "mode": "video_generation", "output_cost_per_second": 0.4, - "source": "https://docs.cloud.google.com/gemini-enterprise-agent-platform/models/veo/3-1-generate", + "output_cost_per_second_4k": 0.6, + "source": "https://cloud.google.com/vertex-ai/generative-ai/pricing", "supported_modalities": [ "text" ], @@ -43453,8 +43523,10 @@ "max_input_tokens": 1024, "max_tokens": 1024, "mode": "video_generation", - "output_cost_per_second": 0.15, - "source": "https://docs.cloud.google.com/gemini-enterprise-agent-platform/models/veo/3-1-generate", + "output_cost_per_second": 0.1, + "output_cost_per_second_1080p": 0.12, + "output_cost_per_second_4k": 0.3, + "source": "https://cloud.google.com/vertex-ai/generative-ai/pricing", "supported_modalities": [ "text" ], @@ -43469,7 +43541,8 @@ "max_tokens": 1024, "mode": "video_generation", "output_cost_per_second": 0.4, - "source": "https://docs.cloud.google.com/gemini-enterprise-agent-platform/models/veo/3-1-generate", + "output_cost_per_second_4k": 0.6, + "source": "https://cloud.google.com/vertex-ai/generative-ai/pricing", "supported_modalities": [ "text" ], @@ -43483,8 +43556,10 @@ "max_input_tokens": 1024, "max_tokens": 1024, "mode": "video_generation", - "output_cost_per_second": 0.15, - "source": "https://docs.cloud.google.com/gemini-enterprise-agent-platform/models/veo/3-1-generate", + "output_cost_per_second": 0.1, + "output_cost_per_second_1080p": 0.12, + "output_cost_per_second_4k": 0.3, + "source": "https://cloud.google.com/vertex-ai/generative-ai/pricing", "supported_modalities": [ "text" ], @@ -52231,14 +52306,14 @@ "supports_vision": true }, "fireworks_ai/deepseek-v4-flash-0731": { - "cache_read_input_token_cost": 2.8e-08, - "input_cost_per_token": 1.4e-07, + "cache_read_input_token_cost": 7e-09, + "input_cost_per_token": 2.2e-07, "litellm_provider": "fireworks_ai", "max_input_tokens": 1048576, "max_output_tokens": 131072, "max_tokens": 131072, "mode": "chat", - "output_cost_per_token": 2.8e-07, + "output_cost_per_token": 6.6e-07, "source": "https://docs.fireworks.ai/serverless/pricing", "supports_function_calling": true, "supports_reasoning": true, @@ -55124,5 +55199,55 @@ "max_tokens": 40960, "mode": "embedding", "source": "https://docs.fireworks.ai/serverless/pricing" + }, + "zai/glm-5.2": { + "cache_creation_input_token_cost": 0, + "cache_read_input_token_cost": 2.6e-07, + "input_cost_per_token": 1.4e-06, + "litellm_provider": "zai", + "max_input_tokens": 1000000, + "max_output_tokens": 128000, + "mode": "chat", + "output_cost_per_token": 4.4e-06, + "source": "https://docs.z.ai/guides/overview/pricing", + "supports_function_calling": true, + "supports_prompt_caching": true, + "supports_reasoning": true, + "supports_tool_choice": true + }, + "together_ai/Qwen/Qwen3.8-Flash": { + "input_cost_per_token": 1.5e-07, + "litellm_provider": "together_ai", + "max_input_tokens": 1000000, + "max_tokens": 1000000, + "mode": "chat", + "output_cost_per_token": 4.7e-07, + "source": "https://docs.together.ai/docs/serverless-models" + }, + "cerebras/gemma-4-31b": { + "input_cost_per_token": 9.9e-07, + "litellm_provider": "cerebras", + "max_input_tokens": 131072, + "max_output_tokens": 40960, + "max_tokens": 40960, + "mode": "chat", + "output_cost_per_token": 1.49e-06, + "source": "https://api.cerebras.ai/public/v1/models/gemma-4-31b", + "supports_function_calling": true, + "supports_parallel_function_calling": true, + "supports_reasoning": true, + "supports_response_schema": true, + "supports_tool_choice": true, + "supports_vision": true + }, + "elevenlabs/scribe_v2": { + "input_cost_per_second": 6.11e-05, + "litellm_provider": "elevenlabs", + "mode": "audio_transcription", + "output_cost_per_second": 0.0, + "source": "https://elevenlabs.io/pricing/api", + "supported_endpoints": [ + "/v1/audio/transcriptions" + ] } } diff --git a/pyproject.toml b/pyproject.toml index f33bf68822a..2866e27e84c 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -1,6 +1,6 @@ [project] name = "litellm" -version = "1.100.0" +version = "1.101.0" description = "Library to easily interface with LLM API providers" readme = "README.md" requires-python = ">=3.10, <3.15" @@ -67,8 +67,8 @@ proxy = [ "azure-identity>=1.25.2,<2.0", "azure-storage-blob>=12.28.0,<13.0", "mcp>=1.28.1,<2.0", - "litellm-proxy-extras==0.4.91", - "litellm-enterprise==0.1.62", + "litellm-proxy-extras==0.4.92", + "litellm-enterprise==0.1.63", "RestrictedPython>=8.5,<9.0", "rich>=13.9.4,<14.0", "InquirerPy>=0.3.4,<1.0", @@ -319,7 +319,7 @@ members = ["enterprise", "litellm-proxy-extras"] profile = "black" [tool.commitizen] -version = "1.100.0" +version = "1.101.0" version_files = [ "pyproject.toml:^version", ] diff --git a/ruff-strict-budget.json b/ruff-strict-budget.json index 1e855ea1b71..0b64051f9d2 100644 --- a/ruff-strict-budget.json +++ b/ruff-strict-budget.json @@ -1,6 +1,6 @@ { "ANN001": { - "limit": 2995 + "limit": 2991 }, "ANN002": { "limit": 71 @@ -9,13 +9,13 @@ "limit": 809 }, "ANN201": { - "limit": 2002 + "limit": 2001 }, "ANN202": { - "limit": 845 + "limit": 841 }, "ANN204": { - "limit": 698 + "limit": 694 }, "ANN205": { "limit": 112 @@ -24,7 +24,7 @@ "limit": 133 }, "ANN401": { - "limit": 587 + "limit": 387 }, "ASYNC230": { "limit": 11 @@ -117,7 +117,7 @@ "limit": 1 }, "PERF102": { - "limit": 23 + "limit": 21 }, "PERF401": { "limit": 12 @@ -168,7 +168,7 @@ "limit": 3 }, "RET504": { - "limit": 175 + "limit": 173 }, "RUF012": { "limit": 239 @@ -198,7 +198,7 @@ "limit": 56 }, "SIM102": { - "limit": 314 + "limit": 310 }, "SIM103": { "limit": 119 @@ -231,7 +231,7 @@ "limit": 5 }, "TID251": { - "limit": 1108 + "limit": 1084 }, "TRY002": { "limit": 524 @@ -240,10 +240,10 @@ "limit": 96 }, "TRY201": { - "limit": 405 + "limit": 403 }, "TRY203": { - "limit": 113 + "limit": 111 }, "TRY300": { "limit": 855 diff --git a/test-quality-budget.json b/test-quality-budget.json index ee33eb581d6..d834c581609 100644 --- a/test-quality-budget.json +++ b/test-quality-budget.json @@ -3,7 +3,7 @@ "limit": 733 }, "TQ002": { - "limit": 742 + "limit": 741 }, "TQ003": { "limit": 62 @@ -21,6 +21,6 @@ "limit": 117 }, "TQ008": { - "limit": 11139 + "limit": 11135 } } diff --git a/tests/e2e/mcp/test_mcp_key_access_e2e.py b/tests/e2e/mcp/test_mcp_key_access_e2e.py index 88ab5666084..68005ae3f6a 100644 --- a/tests/e2e/mcp/test_mcp_key_access_e2e.py +++ b/tests/e2e/mcp/test_mcp_key_access_e2e.py @@ -30,6 +30,34 @@ def _key(client: McpClient, resources: ResourceManager, *, mcp_servers: list[str return key +class TestMcpKeyGrantByAlias: + def test_alias_grant_persists_verbatim_and_lists_tools( + self, + client: McpClient, + resources: ResourceManager, + ) -> None: + """A key granted an MCP server by its alias must store the alias, not the + resolved server_id: in a shared-DB multi-region deployment each instance + derives a different id for the same config server, so only the alias + grants access on every region. The same key must still see the server's + tools, proving the alias grant is honored at request time.""" + server_id = register_datadog_mcp(client, resources) + client.await_registered(server_id) + alias = next(row.alias for row in client.registered_servers() if row.server_id == server_id) + assert alias, f"registered server {server_id} has no alias to grant by" + + key = _key(client, resources, mcp_servers=[alias]) + + stored = client.proxy.key_info(key).object_permission + assert stored is not None and stored.mcp_servers == [alias], ( + f"alias grant was rewritten before persisting (expected [{alias!r}]): " + f"{stored.mcp_servers if stored else None}. A stored server_id is region-local " + f"and breaks the grant on every other instance sharing this database" + ) + + _ = client.await_tool(key, server_id, SEARCH_LOGS_TOOL) + + class TestMcpKeyWithoutAccessIsDenied: @pytest.mark.covers("mcp.list_tools.api_key.denied_without_permission") def test_list_tools_denied_without_permission( diff --git a/tests/e2e/models.py b/tests/e2e/models.py index 6d9ccad9a24..967144dfb16 100644 --- a/tests/e2e/models.py +++ b/tests/e2e/models.py @@ -114,6 +114,7 @@ class KeyInfo(BaseModel): budget_id: str | None = None litellm_budget_table: LiteLLMBudgetTable | None = None budget_limits: list[BudgetWindowState] | None = None + object_permission: ObjectPermission | None = None class KeyInfoResponse(BaseModel): diff --git a/tests/e2e/ui/constants.ts b/tests/e2e/ui/constants.ts index 9d918736262..bb33c90ddf3 100644 --- a/tests/e2e/ui/constants.ts +++ b/tests/e2e/ui/constants.ts @@ -29,6 +29,7 @@ export const E2E_PROXY_ADMIN_USER_ID = "e2e-proxy-admin"; export const E2E_PROXY_ADMIN_EMAIL = "admin@test.local"; export const E2E_INTERNAL_USER_ID = "e2e-internal-user"; export const E2E_INTERNAL_USER_EMAIL = "internal@test.local"; +export const E2E_TEAM_ADMIN_USER_ID = "e2e-team-admin"; // Key aliases for seeded test keys (match seed.sql) export const E2E_UPDATE_LIMITS_KEY_ALIAS = "e2eUpdateLimitsKey"; @@ -46,3 +47,5 @@ export const E2E_TEAM_ORG_ID = "e2e-team-org"; export const E2E_TEAM_ORG_ALIAS = "E2E Team In Org"; export const E2E_TEAM_NO_ADMIN_ID = "e2e-team-no-admin"; export const E2E_TEAM_NO_ADMIN_ALIAS = "E2E Team No Admin"; +export const E2E_TEAM_KEYGEN_ID = "e2e-team-keygen"; +export const E2E_TEAM_KEYGEN_ALIAS = "E2E Team Keygen"; diff --git a/tests/e2e/ui/fixtures/seed.sql b/tests/e2e/ui/fixtures/seed.sql index a1218633cdb..e77b4a16b3d 100644 --- a/tests/e2e/ui/fixtures/seed.sql +++ b/tests/e2e/ui/fixtures/seed.sql @@ -29,7 +29,7 @@ INSERT INTO "LiteLLM_UserTable" ("user_id", "user_email", "user_role", "teams", VALUES ('e2e-proxy-admin', 'admin@test.local', 'proxy_admin', '{"e2e-team-crud"}', 'scrypt:MU5CcTAi6rVK1HfY1rVPEWq6r4sxg837eq9dG4n5Q6BhDJ44442+seC6LAhLEAYr'), ('e2e-admin-viewer', 'adminviewer@test.local', 'proxy_admin_viewer', '{}', 'scrypt:MU5CcTAi6rVK1HfY1rVPEWq6r4sxg837eq9dG4n5Q6BhDJ44442+seC6LAhLEAYr'), - ('e2e-internal-user', 'internal@test.local', 'internal_user', '{"e2e-team-crud","e2e-team-org"}', 'scrypt:MU5CcTAi6rVK1HfY1rVPEWq6r4sxg837eq9dG4n5Q6BhDJ44442+seC6LAhLEAYr'), + ('e2e-internal-user', 'internal@test.local', 'internal_user', '{"e2e-team-crud","e2e-team-org","e2e-team-keygen"}', 'scrypt:MU5CcTAi6rVK1HfY1rVPEWq6r4sxg837eq9dG4n5Q6BhDJ44442+seC6LAhLEAYr'), ('e2e-internal-viewer', 'viewer@test.local', 'internal_user_viewer', '{"e2e-team-crud"}', 'scrypt:MU5CcTAi6rVK1HfY1rVPEWq6r4sxg837eq9dG4n5Q6BhDJ44442+seC6LAhLEAYr'), ('e2e-team-admin', 'teamadmin@test.local', 'internal_user', '{"e2e-team-crud","e2e-team-delete"}', 'scrypt:MU5CcTAi6rVK1HfY1rVPEWq6r4sxg837eq9dG4n5Q6BhDJ44442+seC6LAhLEAYr'), ('e2e-invitable-user', 'invitable@test.local', 'internal_user', '{}', 'scrypt:MU5CcTAi6rVK1HfY1rVPEWq6r4sxg837eq9dG4n5Q6BhDJ44442+seC6LAhLEAYr'), @@ -63,6 +63,17 @@ INSERT INTO "LiteLLM_TeamTable" ( '[{"role":"user","user_id":"e2e-invitable-user"}]'::jsonb, '{}'::jsonb, '{"fake-openai-gpt-4"}', 0.0, '{}'::jsonb, '{}'::jsonb, false); +INSERT INTO "LiteLLM_TeamTable" ( + "team_id", "team_alias", "organization_id", "admins", "members", + "members_with_roles", "metadata", "models", "spend", "model_spend", "model_max_budget", "blocked", + "team_member_permissions" +) VALUES + ('e2e-team-keygen', 'E2E Team Keygen', NULL, + '{}', '{"e2e-internal-user"}', + '[{"role":"user","user_id":"e2e-internal-user"}]'::jsonb, + '{}'::jsonb, '{"fake-openai-gpt-4"}', 0.0, '{}'::jsonb, '{}'::jsonb, false, + '{"/key/generate"}'); + -- 6. Team Memberships (only user_id, team_id, spend — no created_at/updated_at) INSERT INTO "LiteLLM_TeamMembership" ("user_id", "team_id", "spend") VALUES @@ -72,6 +83,7 @@ VALUES ('e2e-removable-member', 'e2e-team-crud', 0.0), ('e2e-team-admin', 'e2e-team-delete', 0.0), ('e2e-internal-user', 'e2e-team-org', 0.0), + ('e2e-internal-user', 'e2e-team-keygen', 0.0), ('e2e-invitable-user', 'e2e-team-no-admin', 0.0); -- 7. Verification Tokens (API Keys) diff --git a/tests/e2e/ui/helpers/traffic.ts b/tests/e2e/ui/helpers/traffic.ts index a2fc9463c94..ebd3c9a417f 100644 --- a/tests/e2e/ui/helpers/traffic.ts +++ b/tests/e2e/ui/helpers/traffic.ts @@ -84,6 +84,34 @@ export async function waitForSpendLog( throw new Error(`spend log for request ${requestId} never appeared (last /spend/logs status ${lastStatus})`); } +export async function waitForSpendLogByPrompt( + request: APIRequestContext, + prompt: string, + timeoutMs = 60_000, +): Promise { + const deadline = Date.now() + timeoutMs; + let lastStatus = 0; + while (Date.now() < deadline) { + const res = await request.get(`${rootPath()}/spend/logs`, { + headers: { Authorization: `Bearer ${masterKey()}` }, + }); + lastStatus = res.status(); + if (res.ok()) { + const rows: { request_id?: string; messages?: unknown; proxy_server_request?: unknown }[] = await res.json(); + const row = (Array.isArray(rows) ? rows : []).find( + (candidate) => + JSON.stringify(candidate.messages ?? "").includes(prompt) || + JSON.stringify(candidate.proxy_server_request ?? "").includes(prompt), + ); + if (row?.request_id) { + return row.request_id; + } + } + await new Promise((r) => setTimeout(r, 2_000)); + } + throw new Error(`no spend log row carrying prompt ${prompt} appeared (last /spend/logs status ${lastStatus})`); +} + const isoDay = (d: Date): string => d.toISOString().slice(0, 10); /** diff --git a/tests/e2e/ui/tests/guardrails/guardrails.spec.ts b/tests/e2e/ui/tests/guardrails/guardrails.spec.ts new file mode 100644 index 00000000000..77ff020510b --- /dev/null +++ b/tests/e2e/ui/tests/guardrails/guardrails.spec.ts @@ -0,0 +1,81 @@ +import { test, expect } from "@playwright/test"; +import { ADMIN_STORAGE_PATH, E2E_TEAM_NO_ADMIN_ID } from "../../constants"; +import { Page } from "../../fixtures/pages"; +import { navigateToPage, dismissFeedbackPopup, clickTeamId } from "../../helpers/navigation"; + +test.describe("Guardrails", () => { + test.use({ storageState: ADMIN_STORAGE_PATH }); + + test("Create a Presidio guardrail, see it in team settings, and delete it", async ({ page }) => { + const guardrailName = `e2e-presidio-${Date.now()}`; + + await navigateToPage(page, Page.Guardrails); + await dismissFeedbackPopup(page); + + await page.getByRole("button", { name: /Add New Guardrail/i }).click(); + await page.getByRole("menuitem", { name: "Add Provider Guardrail" }).click(); + + const dialog = page.getByRole("dialog", { name: "Create guardrail" }); + await expect(dialog).toBeVisible({ timeout: 10_000 }); + + await dialog.getByLabel("Guardrail Name").fill(guardrailName); + + const providerSelect = dialog.getByRole("combobox", { name: "Guardrail Provider" }); + await providerSelect.click(); + await providerSelect.fill("Presidio"); + await page.getByRole("option", { name: "Presidio PII" }).click(); + + await dialog.getByLabel("Mode", { exact: true }).click(); + await page.keyboard.type("pre_call"); + await expect(page.getByRole("option", { name: "pre_call" })).toBeAttached({ timeout: 5_000 }); + await page.keyboard.press("Enter"); + await expect(dialog.getByText("pre_call", { exact: true })).toBeVisible({ timeout: 5_000 }); + await dialog.getByText("Create guardrail", { exact: true }).click(); + + await dialog.getByLabel("presidio_analyzer_api_base").fill("http://127.0.0.1:9999"); + await expect(dialog.getByLabel("presidio_analyzer_api_base")).toHaveValue("http://127.0.0.1:9999"); + await dialog.getByLabel("presidio_anonymizer_api_base").fill("http://127.0.0.1:9999"); + await expect(dialog.getByLabel("presidio_anonymizer_api_base")).toHaveValue("http://127.0.0.1:9999"); + + await dialog.getByRole("button", { name: "Next" }).click(); + await expect(dialog.getByText("Configure PII Protection")).toBeVisible({ timeout: 10_000 }); + await dialog.getByRole("button", { name: "Select All & Mask" }).click(); + + await dialog.getByRole("button", { name: "Create Guardrail" }).click(); + await expect(page.getByText("Guardrail created successfully").first()).toBeVisible({ timeout: 15_000 }); + + const row = page.getByRole("row").filter({ hasText: guardrailName }); + await expect(row).toHaveCount(1, { timeout: 15_000 }); + + await navigateToPage(page, Page.Teams); + await dismissFeedbackPopup(page); + await clickTeamId(page, E2E_TEAM_NO_ADMIN_ID); + await page.getByRole("tab", { name: "Settings" }).click(); + await page.getByRole("button", { name: "Edit Settings" }).click(); + + const guardrailsSelect = page.getByRole("combobox", { name: "Select guardrails" }); + await expect(guardrailsSelect).toBeVisible({ timeout: 10_000 }); + await guardrailsSelect.click(); + await guardrailsSelect.fill(guardrailName); + await expect(page.getByRole("option", { name: guardrailName })).toBeVisible({ timeout: 10_000 }); + await page.keyboard.press("Escape"); + + await navigateToPage(page, Page.Guardrails); + await expect(row).toHaveCount(1, { timeout: 15_000 }); + await row.getByRole("button", { name: "Open guardrail actions" }).click(); + await page.getByRole("menuitem", { name: "Delete" }).click(); + + const deleteModal = page.getByRole("dialog", { name: "Delete Guardrail" }); + await expect(deleteModal).toBeVisible({ timeout: 5_000 }); + await deleteModal.getByRole("button", { name: "Delete", exact: true }).click(); + + await expect(page.getByText(`Guardrail "${guardrailName}" deleted successfully`)).toBeVisible({ + timeout: 10_000, + }); + await expect(row).toHaveCount(0, { timeout: 15_000 }); + + await page.reload(); + await expect(page.getByRole("button", { name: /Add New Guardrail/i })).toBeVisible({ timeout: 20_000 }); + await expect(page.getByRole("row").filter({ hasText: guardrailName })).toHaveCount(0); + }); +}); diff --git a/tests/e2e/ui/tests/internal-user/internalUser.spec.ts b/tests/e2e/ui/tests/internal-user/internalUser.spec.ts index 26e34dd2fe5..f392c5104da 100644 --- a/tests/e2e/ui/tests/internal-user/internalUser.spec.ts +++ b/tests/e2e/ui/tests/internal-user/internalUser.spec.ts @@ -3,10 +3,13 @@ import { E2E_INTERNAL_USER_KEY_ALIAS, E2E_TEAM_CRUD_ALIAS, E2E_TEAM_CRUD_ID, + E2E_TEAM_KEYGEN_ALIAS, INTERNAL_USER_STORAGE_PATH, } from "../../constants"; import { Page } from "../../fixtures/pages"; import { navigateToPage, clickTeamId } from "../../helpers/navigation"; +import { CHAT_MODEL_A, MOCK_RESPONSE_TEXT, masterKey } from "../../helpers/traffic"; +import { keySourceSelect, onlyVisible, openPlayground, selectModel, sendMessage } from "../../helpers/playground"; test.describe("Internal User", () => { test.use({ storageState: INTERNAL_USER_STORAGE_PATH }); @@ -37,6 +40,55 @@ test.describe("Internal User", () => { await expect(page.getByRole("tab", { name: "Members" })).not.toBeVisible(); }); + test("Internal user creates a team key and uses it in the Playground", async ({ page, request }) => { + const suffix = Date.now(); + const auth = { Authorization: `Bearer ${masterKey()}` }; + + await navigateToPage(page, Page.ApiKeys); + + await page.getByRole("button", { name: /Create New Key/i }).click(); + await expect(page.getByText("Key Ownership")).toBeVisible({ timeout: 10_000 }); + + await expect(page.getByRole("radio", { name: "You", exact: true })).toBeVisible({ timeout: 10_000 }); + await expect(page.getByRole("radio", { name: "Another User" })).toHaveCount(0); + + const keyName = `e2e-internal-team-key-${suffix}`; + await page.getByLabel(/Key Name/).fill(keyName); + + const teamSelect = page.getByTestId("team-dropdown").getByRole("combobox"); + await teamSelect.click(); + await page.keyboard.type(E2E_TEAM_KEYGEN_ALIAS); + await page.getByRole("option", { name: E2E_TEAM_KEYGEN_ALIAS }).first().click(); + + await page.getByRole("combobox", { name: "Select models" }).click(); + await page.getByRole("option", { name: "All Team Models", exact: true }).click(); + await page.keyboard.press("Escape"); + + await page.getByRole("button", { name: "Create Key", exact: true }).click(); + + await expect(page.getByText("Save your Key")).toBeVisible({ timeout: 10_000 }); + const apiKey = (await page.getByRole("dialog", { name: "Save your Key" }).locator("pre").innerText()).trim(); + expect(apiKey).toMatch(/^sk-/); + await page.keyboard.press("Escape"); + + try { + await openPlayground(page); + await keySourceSelect(page).click(); + await onlyVisible(page.getByRole("option", { name: "Virtual Key" })).click({ timeout: 15_000 }); + + const keyInput = onlyVisible(page.getByPlaceholder("Enter custom Virtual Key")); + await expect(keyInput).toBeVisible({ timeout: 10_000 }); + await keyInput.fill(apiKey); + + await selectModel(page, CHAT_MODEL_A); + await sendMessage(page, `internal user team key ping ${keyName}`); + + await expect(page.getByText(MOCK_RESPONSE_TEXT, { exact: false }).first()).toBeVisible({ timeout: 60_000 }); + } finally { + await request.post("/key/delete", { headers: auth, data: { keys: [apiKey] } }); + } + }); + test("Virtual Keys page does not surface litellm-dashboard team keys", async ({ page }) => { await navigateToPage(page, Page.ApiKeys); diff --git a/tests/e2e/ui/tests/internal-user/internalUserWithTeams.spec.ts b/tests/e2e/ui/tests/internal-user/internalUserWithTeams.spec.ts index 49e27a36673..62681e9ceb5 100644 --- a/tests/e2e/ui/tests/internal-user/internalUserWithTeams.spec.ts +++ b/tests/e2e/ui/tests/internal-user/internalUserWithTeams.spec.ts @@ -1,14 +1,13 @@ import { test, expect } from "@playwright/test"; -import { INTERNAL_USER_STORAGE_PATH, E2E_TEAM_CRUD_ALIAS, E2E_TEAM_ORG_ALIAS } from "../../constants"; +import { + INTERNAL_USER_STORAGE_PATH, + E2E_TEAM_CRUD_ALIAS, + E2E_TEAM_KEYGEN_ALIAS, + E2E_TEAM_ORG_ALIAS, +} from "../../constants"; import { Page } from "../../fixtures/pages"; import { navigateToPage } from "../../helpers/navigation"; -/** - * Differential partner to internalUserNoTeam.spec.ts: the seeded - * e2e-internal-user belongs to exactly two teams, so the Create Key dropdown - * must list both. Without this, the no-team spec's "zero options" assertion - * would still pass against a bug that empties the dropdown for everyone. - */ test.describe("Internal User with team memberships", () => { test.use({ storageState: INTERNAL_USER_STORAGE_PATH }); @@ -21,10 +20,9 @@ test.describe("Internal User with team memberships", () => { const teamSelect = page.getByTestId("team-dropdown").getByRole("combobox"); await teamSelect.click(); - // Both seeded memberships render, and nothing else does — proving the - // dropdown is scoped to the user's teams rather than empty or unfiltered. await expect(page.getByRole("option", { name: E2E_TEAM_CRUD_ALIAS })).toBeVisible({ timeout: 10_000 }); await expect(page.getByRole("option", { name: E2E_TEAM_ORG_ALIAS })).toBeVisible(); - await expect(page.getByRole("option")).toHaveCount(2); + await expect(page.getByRole("option", { name: E2E_TEAM_KEYGEN_ALIAS })).toBeVisible(); + await expect(page.getByRole("option")).toHaveCount(3); }); }); diff --git a/tests/e2e/ui/tests/logs/logs.spec.ts b/tests/e2e/ui/tests/logs/logs.spec.ts index 610a88c6cd0..2748c91395f 100644 --- a/tests/e2e/ui/tests/logs/logs.spec.ts +++ b/tests/e2e/ui/tests/logs/logs.spec.ts @@ -2,7 +2,14 @@ import { test, expect, type Locator, type Page as PlaywrightPage } from "@playwr import { ADMIN_STORAGE_PATH } from "../../constants"; import { navigateToPage, dismissFeedbackPopup } from "../../helpers/navigation"; import { Page } from "../../fixtures/pages"; -import { CHAT_MODEL_A, MOCK_RESPONSE_TEXT, sendChatCompletion, waitForSpendLog } from "../../helpers/traffic"; +import { + CHAT_MODEL_A, + MOCK_RESPONSE_TEXT, + sendChatCompletion, + waitForSpendLog, + waitForSpendLogByPrompt, +} from "../../helpers/traffic"; +import { openPlayground, selectModel, sendMessage } from "../../helpers/playground"; /** * Anchored to traffic this spec generates itself, with a unique prompt and end user per run, so it @@ -46,6 +53,23 @@ test.describe("Logs page", () => { permissions: ["clipboard-read", "clipboard-write"], }); + test("a chat sent from the Playground lands in Logs with its content", async ({ page, request }) => { + const prompt = `logs-playground-prompt-${uniqueSuffix()}`; + await openPlayground(page); + await selectModel(page, CHAT_MODEL_A); + await sendMessage(page, prompt); + await expect(page.getByText(MOCK_RESPONSE_TEXT, { exact: false }).first()).toBeVisible({ timeout: 60_000 }); + + const requestId = await waitForSpendLogByPrompt(request, prompt); + + const row = await openLogsForRequest(page, requestId); + await row.click(); + const drawer = page.getByRole("dialog").first(); + await expect(drawer.getByText("Request & Response")).toBeVisible({ timeout: 20_000 }); + await expect(drawer.getByText(prompt, { exact: false }).first()).toBeVisible({ timeout: 20_000 }); + await expect(drawer.getByText(MOCK_RESPONSE_TEXT, { exact: false }).first()).toBeVisible({ timeout: 20_000 }); + }); + test("a served request expands to its request and response", async ({ page, request }) => { const prompt = `logs-detail-prompt-${uniqueSuffix()}`; const requestId = await sendChatCompletion(request, { diff --git a/tests/e2e/ui/tests/modelHub/modelHub.spec.ts b/tests/e2e/ui/tests/modelHub/modelHub.spec.ts index 16ec94c1dc8..6877fc9c48d 100644 --- a/tests/e2e/ui/tests/modelHub/modelHub.spec.ts +++ b/tests/e2e/ui/tests/modelHub/modelHub.spec.ts @@ -1,7 +1,8 @@ -import { test, expect } from "@playwright/test"; +import { test, expect, type APIRequestContext } from "@playwright/test"; import { ADMIN_STORAGE_PATH } from "../../constants"; import { navigateToPage, dismissFeedbackPopup } from "../../helpers/navigation"; import { Page } from "../../fixtures/pages"; +import { masterKey } from "../../helpers/traffic"; test.describe("AI Hub (internal admin view)", () => { test.use({ storageState: ADMIN_STORAGE_PATH }); @@ -77,4 +78,89 @@ test.describe("Public model hub (/ui/model_hub_table)", () => { // agents/MCP servers exist, so we don't assert on them in a fresh CI run. await expect(page.getByRole("tab", { name: "Model Hub" })).toBeVisible({ timeout: 10_000 }); }); + + test("Agent Hub and MCP Hub tabs render their public entries", async ({ page, request }) => { + const suffix = `${Date.now()}`; + const agentName = `e2e-public-agent-${suffix}`; + const mcpServerName = `e2e_public_mcp_${suffix}`; + const auth = { Authorization: `Bearer ${masterKey()}` }; + + const publicMcpServerIds = async (api: APIRequestContext): Promise => { + const res = await api.get("/public/mcp_hub"); + expect(res.ok(), `public mcp_hub read failed (${res.status()}): ${await res.text()}`).toBe(true); + const servers: { server_id: string }[] = await res.json(); + return servers.map((server) => server.server_id); + }; + + const seedPublicEntries = async ( + api: APIRequestContext, + priorMcpIds: string[], + ): Promise<{ agentId: string; serverId: string }> => { + const agentRes = await api.post("/v1/agents", { + headers: auth, + data: { + agent_name: agentName, + agent_card_params: { + name: agentName, + description: "E2E public agent", + version: "1.0.0", + url: "http://127.0.0.1:9999/", + capabilities: {}, + skills: [], + defaultInputModes: ["text"], + defaultOutputModes: ["text"], + }, + }, + }); + expect(agentRes.ok(), `agent create failed (${agentRes.status()}): ${await agentRes.text()}`).toBe(true); + const agentId = (await agentRes.json()).agent_id as string; + + const serverRes = await api.post("/v1/mcp/server", { + headers: auth, + data: { + server_name: mcpServerName, + url: "http://127.0.0.1:9999/mcp", + transport: "http", + description: "E2E public MCP server", + }, + }); + expect(serverRes.ok(), `mcp server create failed (${serverRes.status()}): ${await serverRes.text()}`).toBe(true); + const serverId = (await serverRes.json()).server_id as string; + + const agentPublicRes = await api.post(`/v1/agents/${agentId}/make_public`, { headers: auth }); + expect(agentPublicRes.ok(), `agent make_public failed: ${await agentPublicRes.text()}`).toBe(true); + const mcpPublicRes = await api.post("/v1/mcp/make_public", { + headers: auth, + data: { mcp_server_ids: [...priorMcpIds, serverId] }, + }); + expect(mcpPublicRes.ok(), `mcp make_public failed: ${await mcpPublicRes.text()}`).toBe(true); + + return { agentId, serverId }; + }; + + const priorMcpIds = await publicMcpServerIds(request); + const { agentId, serverId } = await seedPublicEntries(request, priorMcpIds); + try { + await page.goto(`/ui/model_hub_table?key=${masterKey()}`); + await dismissFeedbackPopup(page); + + const agentHubTab = page.getByRole("tab", { name: "Agent Hub" }); + await expect(agentHubTab).toBeVisible({ timeout: 15_000 }); + await agentHubTab.click(); + await expect(page.getByText("Available Agents")).toBeVisible({ timeout: 10_000 }); + await expect(page.getByRole("row").filter({ hasText: agentName })).toHaveCount(1, { timeout: 10_000 }); + await expect(page.getByText("E2E public agent").first()).toBeVisible(); + + const mcpHubTab = page.getByRole("tab", { name: "MCP Hub" }); + await expect(mcpHubTab).toBeVisible(); + await mcpHubTab.click(); + await expect(page.getByText("Available MCP Servers")).toBeVisible({ timeout: 10_000 }); + await expect(page.getByRole("row").filter({ hasText: mcpServerName })).toHaveCount(1, { timeout: 10_000 }); + await expect(page.getByText("E2E public MCP server").first()).toBeVisible(); + } finally { + await request.post("/v1/mcp/make_public", { headers: auth, data: { mcp_server_ids: priorMcpIds } }); + await request.delete(`/v1/agents/${agentId}`, { headers: auth }); + await request.delete(`/v1/mcp/server/${serverId}`, { headers: auth }); + } + }); }); diff --git a/tests/e2e/ui/tests/modelsPage/addModel.spec.ts b/tests/e2e/ui/tests/modelsPage/addModel.spec.ts index 84d1c01b452..073d3c0b79c 100644 --- a/tests/e2e/ui/tests/modelsPage/addModel.spec.ts +++ b/tests/e2e/ui/tests/modelsPage/addModel.spec.ts @@ -212,6 +212,116 @@ test.describe("Add Model", () => { .toBe(true); }); + test("Add a model with a stored credential, pass Test Connect, and serve traffic", async ({ page, request }) => { + const masterKey = users[Role.ProxyAdmin].password; + const auth = { Authorization: `Bearer ${masterKey}` }; + const credentialName = `e2e-cred-reuse-${Date.now()}`; + const createCred = await page.request.post("/credentials", { + headers: auth, + data: { + credential_name: credentialName, + credential_values: { api_key: "fake-key", api_base: MOCK_LLM_BASE }, + credential_info: { custom_llm_provider: "openai" }, + }, + }); + expect(createCred.ok(), `POST /credentials failed (${createCred.status()}): ${await createCred.text()}`).toBe(true); + + // Multi-instance stacks propagate a new credential to the probe-serving instances on a periodic + // sync; consecutive successes guard against a load balancer alternating synced and stale replicas + let consecutiveProbeSuccesses = 0; + await expect + .poll( + async () => { + const probe = await page.request.post("/health/test_connection", { + headers: auth, + data: { + litellm_params: { + model: "openai/fake-gpt-4", + custom_llm_provider: "openai", + litellm_credential_name: credentialName, + }, + model_info: {}, + mode: "chat", + }, + }); + const healthy = probe.ok() && (await probe.json()).status === "success"; + consecutiveProbeSuccesses = healthy ? consecutiveProbeSuccesses + 1 : 0; + return consecutiveProbeSuccesses; + }, + { + message: `stored credential ${credentialName} never became usable for a connection test`, + timeout: 60_000, + }, + ) + .toBeGreaterThanOrEqual(3); + + try { + await navigateToPage(page, Page.Models); + await page.getByRole("tab", { name: "Add Model" }).click(); + + await selectProvider(page, "OpenAI-Compatible Endpoints (Together AI, etc.)"); + + const publicName = `e2e-cred-model-${Date.now()}`; + uiAddedModelName = publicName; + + await page.getByRole("combobox", { name: "Select models" }).click(); + await page.getByRole("option", { name: "Custom Model Name (Enter below)" }).click(); + await page.keyboard.press("Escape"); + await page.getByPlaceholder("Enter custom model name").fill(publicName); + + const credentialSelect = page.getByRole("combobox", { name: "Existing Credentials" }); + await credentialSelect.click(); + await credentialSelect.fill(credentialName); + await page.getByRole("option", { name: credentialName, exact: true }).click(); + + await expect(page.locator("#api_key")).toHaveCount(0); + await expect(page.locator("#api_base")).toHaveCount(0); + + await page.getByRole("button", { name: "Test Connect" }).click(); + await expect(page.getByText("Connection Test Results")).toBeVisible({ timeout: 10_000 }); + await expect(page.getByTestId("connection-success-msg")).toBeVisible({ timeout: 30_000 }); + + const resultsModal = page.getByRole("dialog", { name: "Connection Test Results" }); + await resultsModal.locator('[data-slot="dialog-footer"]').getByRole("button", { name: "Close" }).click(); + await expect(resultsModal).toBeHidden({ timeout: 5_000 }); + + const created = await captureRequestBody(page, { method: "POST", urlIncludes: "/model/new" }, async () => { + await page.getByRole("button", { name: "Add Model" }).last().click(); + }); + expect(created.litellm_params?.litellm_credential_name, "the picked credential goes on the wire").toBe( + credentialName, + ); + expect(created.litellm_params?.api_key, "no raw api key goes on the wire").toBeUndefined(); + + await expect(page.getByText("created successfully")).toBeVisible({ timeout: 15_000 }); + + await expect + .poll( + async () => { + try { + await sendChatCompletion(request, { model: publicName, prompt: `hello via ${credentialName}` }); + return true; + } catch { + return false; + } + }, + { + message: `model ${publicName} added with a stored credential never served a request`, + timeout: 30_000, + }, + ) + .toBe(true); + } finally { + const stored = uiAddedModelName ? await findDeploymentByName(page, uiAddedModelName) : undefined; + const id = stored?.model_info?.id; + if (id) { + await page.request.post("/model/delete", { headers: auth, data: { id } }); + uiAddedModelName = ""; + } + await page.request.delete(`/credentials/${credentialName}`, { headers: auth }); + } + }); + test("Test connection with bad credentials shows failure", async ({ page }) => { await navigateToPage(page, Page.Models); await page.getByRole("tab", { name: "Add Model" }).click(); diff --git a/tests/e2e/ui/tests/modelsPage/deleteTeamModel.spec.ts b/tests/e2e/ui/tests/modelsPage/deleteTeamModel.spec.ts new file mode 100644 index 00000000000..96abd9833c0 --- /dev/null +++ b/tests/e2e/ui/tests/modelsPage/deleteTeamModel.spec.ts @@ -0,0 +1,72 @@ +import { test, expect, type Page as PlaywrightPage } from "@playwright/test"; +import { ADMIN_STORAGE_PATH, E2E_TEAM_CRUD_ID } from "../../constants"; +import { Page } from "../../fixtures/pages"; +import { navigateToPage } from "../../helpers/navigation"; +import { readBack } from "../../helpers/roundTrip"; +import { masterKey } from "../../helpers/traffic"; + +type DeploymentRow = { model_name?: string }; + +async function findDeploymentByName(page: PlaywrightPage, modelName: string): Promise { + const body = await readBack<{ data: DeploymentRow[] }>(page, "/v2/model/info"); + return body.data.find((row) => row.model_name === modelName); +} + +test.describe("Delete team model", () => { + test.use({ storageState: ADMIN_STORAGE_PATH }); + + test("Delete a team-scoped model and verify it leaves the team's model list", async ({ page }) => { + const modelName = `e2e-team-model-delete-${Date.now()}`; + const createResponse = await page.request.post("/model/new", { + headers: { Authorization: `Bearer ${masterKey()}` }, + data: { + model_name: modelName, + litellm_params: { + model: "openai/fake-gpt-4", + api_base: `http://127.0.0.1:${process.env.MOCK_LLM_PORT ?? "8090"}/v1`, + api_key: "fake-key", + }, + model_info: { team_id: E2E_TEAM_CRUD_ID }, + }, + }); + expect(createResponse.ok(), `/model/new failed: ${createResponse.status()} ${await createResponse.text()}`).toBe( + true, + ); + + await expect + .poll(async () => (await findDeploymentByName(page, modelName)) !== undefined, { + message: `deployment ${modelName} never appeared in /v2/model/info after create`, + timeout: 30_000, + }) + .toBe(true); + + await navigateToPage(page, Page.Models); + await page.getByPlaceholder("Search model names").fill(modelName); + + const row = page.getByRole("row").filter({ hasText: modelName }); + await expect(row).toHaveCount(1, { timeout: 15_000 }); + await expect(row.getByText(E2E_TEAM_CRUD_ID)).toBeVisible({ timeout: 10_000 }); + + await row.getByRole("button", { name: "Delete model" }).click(); + + const modal = page.getByRole("dialog", { name: "Delete Model" }); + await expect(modal).toBeVisible({ timeout: 5_000 }); + await expect(modal.getByText(modelName).first()).toBeVisible(); + await modal.getByRole("button", { name: "Delete", exact: true }).click(); + + await expect(page.getByText("Model deleted successfully").first()).toBeVisible({ timeout: 10_000 }); + await expect(row).toHaveCount(0, { timeout: 15_000 }); + + await expect + .poll(async () => await findDeploymentByName(page, modelName), { + message: `deployment ${modelName} still readable from /v2/model/info after delete`, + timeout: 15_000, + }) + .toBeUndefined(); + + await page.reload(); + await page.getByPlaceholder("Search model names").fill(modelName); + await expect(page.getByText("No models found").first()).toBeVisible({ timeout: 15_000 }); + await expect(page.getByRole("row").filter({ hasText: modelName })).toHaveCount(0); + }); +}); diff --git a/tests/e2e/ui/tests/proxy-admin/secondAdmin.spec.ts b/tests/e2e/ui/tests/proxy-admin/secondAdmin.spec.ts new file mode 100644 index 00000000000..5a8bc84cc13 --- /dev/null +++ b/tests/e2e/ui/tests/proxy-admin/secondAdmin.spec.ts @@ -0,0 +1,97 @@ +import { test, expect } from "@playwright/test"; +import { ADMIN_STORAGE_PATH } from "../../constants"; +import { Page } from "../../fixtures/pages"; +import { navigateToPage, dismissFeedbackPopup } from "../../helpers/navigation"; +import { CHAT_MODEL_A, MOCK_RESPONSE_TEXT, masterKey } from "../../helpers/traffic"; + +test.describe("Second proxy admin", () => { + test.use({ storageState: { cookies: [], origins: [] } }); + + test("an invited admin can log in, mint a key, and call a model with it", async ({ page, browser, request }) => { + const suffix = Date.now(); + const email = `second-admin-${suffix}@test.local`; + const password = "e2e-second-admin-password"; + const auth = { Authorization: `Bearer ${masterKey()}` }; + + const inviteAdminUser = async (): Promise => { + const adminContext = await browser.newContext({ storageState: ADMIN_STORAGE_PATH }); + try { + const adminPage = await adminContext.newPage(); + await navigateToPage(adminPage, Page.Users); + await dismissFeedbackPopup(adminPage); + + await adminPage.getByRole("button", { name: "+ Invite User", exact: true }).click(); + const dialog = adminPage.getByRole("dialog", { name: "Invite User" }); + await expect(dialog).toBeVisible({ timeout: 5_000 }); + + await dialog.getByLabel("User Email").fill(email); + + await dialog.getByLabel(/Global Proxy Role/).click(); + await adminPage.getByRole("option", { name: /Admin \(All Permissions\)/ }).click(); + + const createdResponse = adminPage.waitForResponse( + (res) => res.url().includes("/user/new") && res.request().method() === "POST", + ); + await dialog.getByRole("button", { name: "Invite User" }).click(); + const createdBody = await (await createdResponse).json(); + const createdUserId = (createdBody.data?.user_id ?? createdBody.user_id) as string; + expect(createdUserId, "created user id from /user/new").toBeTruthy(); + + await expect(adminPage.getByText("API user Created").first()).toBeVisible({ timeout: 10_000 }); + return createdUserId; + } finally { + await adminContext.close(); + } + }; + + const userId = await inviteAdminUser(); + try { + const passwordRes = await request.post("/user/update", { + headers: auth, + data: { user_email: email, password }, + }); + expect(passwordRes.ok(), `setting password failed (${passwordRes.status()}): ${await passwordRes.text()}`).toBe( + true, + ); + + await page.goto("/ui/login"); + await page.getByPlaceholder("Enter your username").fill(email); + await page.getByPlaceholder("Enter your password").fill(password); + await page.getByRole("button", { name: "Login", exact: true }).click(); + await expect(page.locator("a", { hasText: "Virtual Keys" })).toBeVisible({ timeout: 30_000 }); + await dismissFeedbackPopup(page); + + await navigateToPage(page, Page.ApiKeys); + await page.getByRole("button", { name: /Create New Key/i }).click(); + await expect(page.getByText("Key Ownership")).toBeVisible({ timeout: 10_000 }); + + await page.getByLabel(/Key Name/).fill(`e2e-second-admin-key-${suffix}`); + + await page.getByRole("combobox", { name: "Select models" }).click(); + await page.getByRole("option", { name: "All Proxy Models", exact: true }).click(); + await page.keyboard.press("Escape"); + + await page.getByRole("button", { name: "Create Key", exact: true }).click(); + + await expect(page.getByText("Save your Key")).toBeVisible({ timeout: 10_000 }); + const apiKey = (await page.getByRole("dialog", { name: "Save your Key" }).locator("pre").innerText()).trim(); + expect(apiKey).toMatch(/^sk-/); + await page.keyboard.press("Escape"); + + const response = await page.request.post("/chat/completions", { + headers: { Authorization: `Bearer ${apiKey}` }, + data: { + model: CHAT_MODEL_A, + messages: [{ role: "user", content: `second admin ping ${suffix}` }], + }, + }); + expect(response.status()).toBe(200); + const body = await response.json(); + expect(body.choices?.[0]?.message?.content).toBe(MOCK_RESPONSE_TEXT); + } finally { + if (userId) { + await request.post("/user/delete", { headers: auth, data: { user_ids: [userId] } }); + } + } + }); +}); diff --git a/tests/e2e/ui/tests/team-admin/teamAdmin.spec.ts b/tests/e2e/ui/tests/team-admin/teamAdmin.spec.ts index 5116cb5df19..26a6fa50b4b 100644 --- a/tests/e2e/ui/tests/team-admin/teamAdmin.spec.ts +++ b/tests/e2e/ui/tests/team-admin/teamAdmin.spec.ts @@ -1,6 +1,7 @@ import { test, expect, type Page as PlaywrightPage } from "@playwright/test"; import { E2E_INTERNAL_USER_KEY_ALIAS, + E2E_TEAM_ADMIN_USER_ID, E2E_TEAM_CRUD_ALIAS, E2E_TEAM_CRUD_ID, TEAM_ADMIN_STORAGE_PATH, @@ -8,6 +9,8 @@ import { import { Page } from "../../fixtures/pages"; import { navigateToPage, dismissFeedbackPopup, clickTeamId } from "../../helpers/navigation"; import { captureRequestBody, readBack } from "../../helpers/roundTrip"; +import { CHAT_MODEL_A, masterKey } from "../../helpers/traffic"; +import { keySourceSelect, modelSelect, onlyVisible, openPlayground } from "../../helpers/playground"; /** * Every identifier a roster is addressable by. Which of user_id / user_email is populated depends on @@ -128,6 +131,91 @@ test.describe("Team Admin", () => { .not.toContain("e2e-removable-member"); }); + test("Team admin sees all team models in the Playground model dropdown", async ({ page, request }) => { + const suffix = Date.now(); + const teamModelName = `e2e-team-dropdown-model-${suffix}`; + const auth = { Authorization: `Bearer ${masterKey()}` }; + + const teamRes = await request.post("/team/new", { + headers: auth, + data: { + team_alias: `e2e-playground-team-${suffix}`, + models: [CHAT_MODEL_A], + members_with_roles: [{ role: "admin", user_id: E2E_TEAM_ADMIN_USER_ID }], + }, + }); + expect(teamRes.ok(), `team create failed (${teamRes.status()}): ${await teamRes.text()}`).toBe(true); + const teamId = (await teamRes.json()).team_id as string; + + try { + const modelRes = await request.post("/model/new", { + headers: auth, + data: { + model_name: teamModelName, + litellm_params: { + model: "openai/fake-gpt-4", + api_base: `http://127.0.0.1:${process.env.MOCK_LLM_PORT ?? "8090"}/v1`, + api_key: "fake-key", + }, + model_info: { team_id: teamId }, + }, + }); + expect(modelRes.ok(), `model create failed (${modelRes.status()}): ${await modelRes.text()}`).toBe(true); + const modelId = (await modelRes.json()).model_info?.id as string; + + try { + const keyRes = await request.post("/key/generate", { headers: auth, data: { team_id: teamId } }); + expect(keyRes.ok(), `key generate failed (${keyRes.status()}): ${await keyRes.text()}`).toBe(true); + const teamKey = (await keyRes.json()).key as string; + + try { + await expect + .poll( + async () => { + const res = await request.get("/model_group/info", { + headers: { Authorization: `Bearer ${teamKey}` }, + }); + if (!res.ok()) return false; + const body: { data?: { model_group?: string }[] } = await res.json(); + return (body.data ?? []).some((group) => group.model_group === teamModelName); + }, + { + message: `model group ${teamModelName} never became visible to the team key`, + timeout: 30_000, + }, + ) + .toBe(true); + + await openPlayground(page); + await keySourceSelect(page).click(); + await onlyVisible(page.getByRole("option", { name: "Virtual Key" })).click({ timeout: 15_000 }); + + const keyInput = onlyVisible(page.getByPlaceholder("Enter custom Virtual Key")); + await expect(keyInput).toBeVisible({ timeout: 10_000 }); + await keyInput.fill(teamKey); + + const select = modelSelect(page); + await select.click(); + await select.fill(teamModelName); + await expect(onlyVisible(page.getByRole("option", { name: teamModelName }))).toBeVisible({ + timeout: 15_000, + }); + + await select.fill(CHAT_MODEL_A); + await expect(onlyVisible(page.getByRole("option", { name: CHAT_MODEL_A }))).toBeVisible({ + timeout: 15_000, + }); + } finally { + await request.post("/key/delete", { headers: auth, data: { keys: [teamKey] } }); + } + } finally { + await request.post("/model/delete", { headers: auth, data: { id: modelId } }); + } + } finally { + await request.post("/team/delete", { headers: auth, data: { team_ids: [teamId] } }); + } + }); + test("Team admin can create a team key with All Team Models", async ({ page }) => { await navigateToPage(page, Page.ApiKeys); await dismissFeedbackPopup(page); diff --git a/tests/llm_translation/test_litellm_proxy_provider.py b/tests/llm_translation/test_litellm_proxy_provider.py index 1cb805bf9ba..8630259877d 100644 --- a/tests/llm_translation/test_litellm_proxy_provider.py +++ b/tests/llm_translation/test_litellm_proxy_provider.py @@ -5,6 +5,7 @@ from io import BytesIO from unittest.mock import AsyncMock +import httpx import litellm from litellm import completion, embedding import pytest @@ -92,44 +93,54 @@ async def test_litellm_gateway_from_sdk_embedding(is_async): litellm.set_verbose = True litellm._turn_on_debug() + captured_bodies = [] + + def handler(request: httpx.Request) -> httpx.Response: + captured_bodies.append(json.loads(request.content)) + return httpx.Response( + 200, + json={ + "object": "list", + "data": [{"object": "embedding", "index": 0, "embedding": [0.1, 0.2, 0.3]}], + "model": "my-vllm-model", + "usage": {"prompt_tokens": 2, "total_tokens": 2}, + }, + ) + if is_async: from openai import AsyncOpenAI - openai_client = AsyncOpenAI(api_key="fake-key") - mock_method = AsyncMock() - patch_target = openai_client.embeddings.create + openai_client = AsyncOpenAI( + api_key="fake-key", + http_client=httpx.AsyncClient(transport=httpx.MockTransport(handler)), + ) + response = await litellm.aembedding( + model="litellm_proxy/my-vllm-model", + input="Hello world", + client=openai_client, + api_base="my-custom-api-base", + ) else: from openai import OpenAI - openai_client = OpenAI(api_key="fake-key") - mock_method = MagicMock() - patch_target = openai_client.embeddings.create + openai_client = OpenAI( + api_key="fake-key", + http_client=httpx.Client(transport=httpx.MockTransport(handler)), + ) + response = litellm.embedding( + model="litellm_proxy/my-vllm-model", + input="Hello world", + client=openai_client, + api_base="my-custom-api-base", + ) - with patch.object(patch_target.__self__, patch_target.__name__, new=mock_method): - try: - if is_async: - await litellm.aembedding( - model="litellm_proxy/my-vllm-model", - input="Hello world", - client=openai_client, - api_base="my-custom-api-base", - ) - else: - litellm.embedding( - model="litellm_proxy/my-vllm-model", - input="Hello world", - client=openai_client, - api_base="my-custom-api-base", - ) - except Exception as e: - print(e) + request_body = captured_bodies[0] + print("Request body - {}".format(request_body)) - mock_method.assert_called_once() - - print("Call KWARGS - {}".format(mock_method.call_args.kwargs)) - - assert "Hello world" == mock_method.call_args.kwargs["input"] - assert "my-vllm-model" == mock_method.call_args.kwargs["model"] + assert "Hello world" == request_body["input"] + assert "my-vllm-model" == request_body["model"] + assert "encoding_format" not in request_body + assert response.data[0]["embedding"] == [0.1, 0.2, 0.3] @pytest.mark.parametrize("is_async", [False, True]) diff --git a/tests/llm_translation/test_nvidia_nim.py b/tests/llm_translation/test_nvidia_nim.py index 7ee4f347f72..d5942e674d0 100644 --- a/tests/llm_translation/test_nvidia_nim.py +++ b/tests/llm_translation/test_nvidia_nim.py @@ -63,27 +63,39 @@ def test_embedding_nvidia_nim(): litellm.set_verbose = True from openai import OpenAI + captured_bodies = [] + + def handler(request: httpx.Request) -> httpx.Response: + captured_bodies.append(json.loads(request.content)) + return httpx.Response( + 200, + json={ + "object": "list", + "data": [{"object": "embedding", "index": 0, "embedding": [0.1, 0.2, 0.3]}], + "model": "nvidia/nv-embedqa-e5-v5", + "usage": {"prompt_tokens": 6, "total_tokens": 6}, + }, + ) + client = OpenAI( api_key="fake-api-key", + http_client=httpx.Client(transport=httpx.MockTransport(handler)), ) - with patch.object(client.embeddings.with_raw_response, "create") as mock_client: - try: - litellm.embedding( - model="nvidia_nim/nvidia/nv-embedqa-e5-v5", - input="What is the meaning of life?", - input_type="passage", - dimensions=1024, - client=client, - ) - except Exception as e: - print(e) - mock_client.assert_called_once() - request_body = mock_client.call_args.kwargs - print("request_body: ", request_body) - assert request_body["input"] == "What is the meaning of life?" - assert request_body["model"] == "nvidia/nv-embedqa-e5-v5" - assert request_body["extra_body"]["input_type"] == "passage" - assert request_body["dimensions"] == 1024 + response = litellm.embedding( + model="nvidia_nim/nvidia/nv-embedqa-e5-v5", + input="What is the meaning of life?", + input_type="passage", + dimensions=1024, + client=client, + ) + request_body = captured_bodies[0] + print("request_body: ", request_body) + assert request_body["input"] == "What is the meaning of life?" + assert request_body["model"] == "nvidia/nv-embedqa-e5-v5" + assert request_body["input_type"] == "passage" + assert request_body["dimensions"] == 1024 + assert "encoding_format" not in request_body + assert response.data[0]["embedding"] == [0.1, 0.2, 0.3] def test_chat_completion_nvidia_nim_with_tools(): diff --git a/tests/local_testing/test_embedding.py b/tests/local_testing/test_embedding.py index aed2849f056..ee2ac14f498 100644 --- a/tests/local_testing/test_embedding.py +++ b/tests/local_testing/test_embedding.py @@ -3,6 +3,8 @@ import os import re import traceback +import httpx + import openai import pytest from dotenv import load_dotenv @@ -1255,56 +1257,42 @@ def test_jina_ai_img_embeddings(input_data, expected_payload_input): assert sent_data["input"] == expected_payload_input -def test_encoding_format_defaults_to_float_for_openai_sdk(monkeypatch): +def test_encoding_format_omitted_by_default_for_openai_sdk(monkeypatch): """ - When encoding_format is not provided, LiteLLM sends `float` for OpenAI-path embeddings. + When encoding_format is not provided, LiteLLM leaves it out of the upstream request. Optional global override: `LITELLM_DEFAULT_EMBEDDING_ENCODING_FORMAT`. """ monkeypatch.delenv("LITELLM_DEFAULT_EMBEDDING_ENCODING_FORMAT", raising=False) - with patch( - "litellm.llms.openai.openai.OpenAIChatCompletion._get_openai_client" - ) as mock_get_client: - # Create a mock client instance - mock_client_instance = MagicMock() - mock_get_client.return_value = mock_client_instance + captured_bodies = [] - # Mock the embeddings.with_raw_response.create method - mock_response = MagicMock() - mock_response.parse.return_value = MagicMock( - model_dump=lambda: { - "data": [{"embedding": [0.1, 0.2, 0.3], "index": 0}], - "model": "text-embedding-ada-002", + def handler(request: httpx.Request) -> httpx.Response: + captured_bodies.append(json.loads(request.content)) + return httpx.Response( + 200, + json={ "object": "list", + "data": [{"object": "embedding", "index": 0, "embedding": [0.1, 0.2, 0.3]}], + "model": "text-embedding-ada-002", "usage": {"prompt_tokens": 1, "total_tokens": 1}, - } - ) - mock_response.headers = {} - - mock_client_instance.embeddings.with_raw_response.create.return_value = ( - mock_response + }, ) - # Call the embedding function without encoding_format - response = embedding( - model="text-embedding-ada-002", - input="Hello world", - ) + client = openai.OpenAI( + api_key="sk-test", http_client=httpx.Client(transport=httpx.MockTransport(handler)) + ) - # Get the call arguments to verify what was sent to OpenAI SDK - call_args = mock_client_instance.embeddings.with_raw_response.create.call_args - assert ( - call_args is not None - ), "OpenAI SDK embeddings.create should have been called" + response = embedding( + model="text-embedding-ada-002", + input="Hello world", + api_key="sk-test", + client=client, + ) - call_kwargs = call_args[1] # Get kwargs - - assert "encoding_format" in call_kwargs - assert ( - call_kwargs["encoding_format"] == "float" - ), "encoding_format should default to float when not provided by user" - - print("✅ PASS: encoding_format='float' is correctly passed to OpenAI SDK") + assert response.data[0]["embedding"] == [0.1, 0.2, 0.3] + assert "encoding_format" not in captured_bodies[0], ( + "encoding_format should be omitted from the upstream request when not provided by user" + ) def test_encoding_format_explicit_value_preserved(): diff --git a/tests/local_testing/test_exceptions.py b/tests/local_testing/test_exceptions.py index 8370046446d..e6392cda406 100644 --- a/tests/local_testing/test_exceptions.py +++ b/tests/local_testing/test_exceptions.py @@ -5,7 +5,7 @@ import traceback from typing import Any import httpx -from openai import AsyncOpenAI, AuthenticationError, BadRequestError, OpenAIError, RateLimitError +from openai import AsyncAzureOpenAI, AsyncOpenAI, AuthenticationError, AzureOpenAI, BadRequestError, OpenAIError, RateLimitError from litellm.llms.custom_httpx.http_handler import AsyncHTTPHandler, HTTPHandler @@ -895,7 +895,12 @@ def _pre_call_utils( ): if call_type == "embedding": data["input"] = "Hello world!" - mapped_target: Any = client.embeddings.with_raw_response + if isinstance(client, (AzureOpenAI, AsyncAzureOpenAI)): + mapped_target: Any = client.embeddings.with_raw_response + patched_attr = "create" + else: + mapped_target = client + patched_attr = "post" if sync_mode: original_function = litellm.embedding else: @@ -905,6 +910,7 @@ def _pre_call_utils( if streaming is True: data["stream"] = True mapped_target = client.chat.completions.with_raw_response # type: ignore + patched_attr = "create" if sync_mode: original_function = litellm.completion else: @@ -914,12 +920,13 @@ def _pre_call_utils( if streaming is True: data["stream"] = True mapped_target = client.completions.with_raw_response # type: ignore + patched_attr = "create" if sync_mode: original_function = litellm.text_completion else: original_function = litellm.atext_completion - return data, original_function, mapped_target + return data, original_function, mapped_target, patched_attr def _pre_call_utils_httpx( @@ -1003,7 +1010,7 @@ async def test_exception_with_headers(sync_mode, provider, model, call_type, str ) data = {"model": model} - data, original_function, mapped_target = _pre_call_utils( + data, original_function, mapped_target, patched_attr = _pre_call_utils( call_type=call_type, data=data, client=openai_client, @@ -1049,7 +1056,7 @@ async def test_exception_with_headers(sync_mode, provider, model, call_type, str with patch.object( mapped_target, - "create", + patched_attr, side_effect=_return_exception, ): new_retry_after_mock_client = MagicMock(return_value=-1) diff --git a/tests/local_testing/test_router.py b/tests/local_testing/test_router.py index 370c43f8f44..c714bb4f9a7 100644 --- a/tests/local_testing/test_router.py +++ b/tests/local_testing/test_router.py @@ -2032,8 +2032,8 @@ def test_router_dynamic_cooldown_correct_retry_after_time(): raise exception with patch.object( - openai_client.embeddings.with_raw_response, - "create", + openai_client, + "post", side_effect=_return_exception, ): new_retry_after_mock_client = MagicMock(return_value=-1) diff --git a/tests/test_litellm/llms/bedrock/files/test_bedrock_files_handler.py b/tests/test_litellm/llms/bedrock/files/test_bedrock_files_handler.py index 7f91b49a6f5..639be272351 100644 --- a/tests/test_litellm/llms/bedrock/files/test_bedrock_files_handler.py +++ b/tests/test_litellm/llms/bedrock/files/test_bedrock_files_handler.py @@ -204,3 +204,69 @@ def test_should_forward_trusted_model_credentials_to_retrieve_provider_config(): assert response is mock_response litellm_params = mock_retrieve_file.call_args.kwargs["litellm_params"] assert litellm_params["_litellm_internal_model_credentials"] is trusted_credentials + + +@pytest.mark.asyncio +async def test_afile_content_assumes_role_with_external_id(monkeypatch): + """A trust policy requiring sts:ExternalId must be satisfied by the deployment's aws_external_id.""" + import datetime + + import boto3 + from botocore.exceptions import ClientError + + monkeypatch.delenv("AWS_EXTERNAL_ID", raising=False) + + class FakeSTSClient: + def get_caller_identity(self): + return {"Arn": "arn:aws:iam::111111111111:user/litellm-proxy-pod"} + + def assume_role(self, **params): + if params.get("ExternalId") != "external-id-files-download": + raise ClientError( + {"Error": {"Code": "AccessDenied", "Message": "is not authorized to perform: sts:AssumeRole"}}, + "AssumeRole", + ) + return { + "Credentials": { + "AccessKeyId": "ASIAFILESDOWNLOADROLE", + "SecretAccessKey": "assumed-secret", + "SessionToken": "assumed-session-token", + "Expiration": datetime.datetime.now(datetime.timezone.utc) + datetime.timedelta(minutes=30), + } + } + + class FakeS3Body: + def read(self): + return b'{"custom_id": "req-1"}' + + class FakeS3Client: + def get_object(self, Bucket, Key): + return {"Body": FakeS3Body()} + + def fake_boto3_client(service_name, **kwargs): + if service_name == "sts": + return FakeSTSClient() + return FakeS3Client() + + optional_params = { + "_litellm_internal_model_credentials": MappingProxyType({"s3_bucket_name": "safe-bucket"}), + "aws_region_name": "us-east-1", + "aws_access_key_id": "AKIAFILESDOWNLOADCALLER", + "aws_secret_access_key": "pod-caller-secret", + "aws_role_name": "arn:aws:iam::999999999999:role/litellm-files-download-role", + "aws_session_name": "litellm-files-download-session", + "aws_external_id": "external-id-files-download", + } + + with patch.object(boto3, "client", side_effect=fake_boto3_client) as mock_boto3_client: + response = await BedrockFilesHandler().afile_content( + file_content_request={"file_id": "s3://safe-bucket/litellm-bedrock-files-model-id-abc.jsonl"}, + optional_params=optional_params, + timeout=10.0, + max_retries=None, + ) + + s3_client_kwargs = next(call.kwargs for call in mock_boto3_client.call_args_list if call.args[0] == "s3") + assert s3_client_kwargs["aws_access_key_id"] == "ASIAFILESDOWNLOADROLE" + assert s3_client_kwargs["aws_session_token"] == "assumed-session-token" + assert response.content == b'{"custom_id": "req-1"}' diff --git a/tests/test_litellm/llms/bedrock/files/test_bedrock_files_transformation.py b/tests/test_litellm/llms/bedrock/files/test_bedrock_files_transformation.py index da13f265ee4..541c0db15d8 100644 --- a/tests/test_litellm/llms/bedrock/files/test_bedrock_files_transformation.py +++ b/tests/test_litellm/llms/bedrock/files/test_bedrock_files_transformation.py @@ -2404,3 +2404,111 @@ class TestBedrockFilesS3SignatureEncoding: body=None, headers=litellm_params[S3_SIGNED_GET_HEADERS_PARAM], ) + + +def test_sign_s3_request_assumes_role_with_external_id(monkeypatch): + """A trust policy requiring sts:ExternalId must be satisfied when signing the S3 upload request.""" + import datetime + from unittest.mock import patch + + import boto3 + from botocore.exceptions import ClientError + + from litellm.llms.bedrock.files.transformation import BedrockFilesConfig + + monkeypatch.delenv("AWS_EXTERNAL_ID", raising=False) + + class FakeSTSClient: + def get_caller_identity(self): + return {"Arn": "arn:aws:iam::111111111111:user/litellm-proxy-pod"} + + def assume_role(self, **params): + if params.get("ExternalId") != "external-id-files-put": + raise ClientError( + {"Error": {"Code": "AccessDenied", "Message": "is not authorized to perform: sts:AssumeRole"}}, + "AssumeRole", + ) + return { + "Credentials": { + "AccessKeyId": "ASIAFILESPUTROLE", + "SecretAccessKey": "assumed-secret", + "SessionToken": "assumed-session-token", + "Expiration": datetime.datetime.now(datetime.timezone.utc) + datetime.timedelta(minutes=30), + } + } + + optional_params = { + "aws_region_name": "us-east-1", + "aws_access_key_id": "AKIAFILESPUTCALLER", + "aws_secret_access_key": "pod-caller-secret", + "aws_role_name": "arn:aws:iam::999999999999:role/litellm-files-put-role", + "aws_session_name": "litellm-files-put-session", + "aws_external_id": "external-id-files-put", + } + + with patch.object(boto3, "client", return_value=FakeSTSClient()): + signed_headers, _signed_body = BedrockFilesConfig()._sign_s3_request( + content='{"custom_id": "req-1"}', + api_base="https://s3.us-east-1.amazonaws.com/safe-bucket/litellm-bedrock-files-model-id-abc.jsonl", + optional_params=optional_params, + ) + + authorization = {key.lower(): value for key, value in signed_headers.items()}["authorization"] + assert "ASIAFILESPUTROLE" in authorization + + +def test_sign_s3_get_request_assumes_role_with_external_id(monkeypatch): + """A trust policy requiring sts:ExternalId must be satisfied when signing the S3 download request.""" + import datetime + from unittest.mock import patch + + import boto3 + from botocore.exceptions import ClientError + + from litellm.llms.bedrock.files.transformation import ( + BedrockFilesConfig, + _BedrockS3RequestParams, + ) + + monkeypatch.delenv("AWS_EXTERNAL_ID", raising=False) + + class FakeSTSClient: + def get_caller_identity(self): + return {"Arn": "arn:aws:iam::111111111111:user/litellm-proxy-pod"} + + def assume_role(self, **params): + if params.get("ExternalId") != "external-id-files-get": + raise ClientError( + {"Error": {"Code": "AccessDenied", "Message": "is not authorized to perform: sts:AssumeRole"}}, + "AssumeRole", + ) + return { + "Credentials": { + "AccessKeyId": "ASIAFILESGETROLE", + "SecretAccessKey": "assumed-secret", + "SessionToken": "assumed-session-token", + "Expiration": datetime.datetime.now(datetime.timezone.utc) + datetime.timedelta(minutes=30), + } + } + + request_params = _BedrockS3RequestParams.model_validate( + { + "aws_region_name": "us-east-1", + "aws_access_key_id": "AKIAFILESGETCALLER", + "aws_secret_access_key": "pod-caller-secret", + "aws_role_name": "arn:aws:iam::999999999999:role/litellm-files-get-role", + "aws_session_name": "litellm-files-get-session", + "aws_external_id": "external-id-files-get", + } + ) + assert request_params.aws_external_id == "external-id-files-get" + + with patch.object(boto3, "client", return_value=FakeSTSClient()): + signed_headers = BedrockFilesConfig()._sign_s3_get_request( + api_base="https://s3.us-east-1.amazonaws.com/safe-bucket/litellm-bedrock-files-model-id-abc.jsonl", + aws_region_name="us-east-1", + request_params=request_params, + ) + + authorization = {key.lower(): value for key, value in signed_headers.items()}["authorization"] + assert "ASIAFILESGETROLE" in authorization diff --git a/tests/test_litellm/llms/bedrock/test_bedrock_common_utils.py b/tests/test_litellm/llms/bedrock/test_bedrock_common_utils.py index 609b5c75801..9302dc01abe 100644 --- a/tests/test_litellm/llms/bedrock/test_bedrock_common_utils.py +++ b/tests/test_litellm/llms/bedrock/test_bedrock_common_utils.py @@ -561,3 +561,56 @@ def test_apply_structured_output_prefers_legacy_output_format(local_model_cost_m assert body["output_config"] == {"format": legacy} assert "output_format" not in body + + +def test_sign_aws_request_assumes_role_with_external_id(monkeypatch): + """A trust policy requiring sts:ExternalId must be satisfied when signing batch API requests.""" + import datetime + from unittest.mock import patch + + import boto3 + from botocore.exceptions import ClientError + + from litellm.llms.bedrock.common_utils import CommonBatchFilesUtils + + monkeypatch.delenv("AWS_EXTERNAL_ID", raising=False) + + class FakeSTSClient: + def get_caller_identity(self): + return {"Arn": "arn:aws:iam::111111111111:user/litellm-proxy-pod"} + + def assume_role(self, **params): + if params.get("ExternalId") != "external-id-batch-sign": + raise ClientError( + {"Error": {"Code": "AccessDenied", "Message": "is not authorized to perform: sts:AssumeRole"}}, + "AssumeRole", + ) + return { + "Credentials": { + "AccessKeyId": "ASIABATCHSIGNROLE", + "SecretAccessKey": "assumed-secret", + "SessionToken": "assumed-session-token", + "Expiration": datetime.datetime.now(datetime.timezone.utc) + datetime.timedelta(minutes=30), + } + } + + optional_params = { + "aws_region_name": "us-east-1", + "aws_access_key_id": "AKIABATCHSIGNCALLER", + "aws_secret_access_key": "pod-caller-secret", + "aws_role_name": "arn:aws:iam::999999999999:role/litellm-batch-sign-role", + "aws_session_name": "litellm-batch-sign-session", + "aws_external_id": "external-id-batch-sign", + } + + with patch.object(boto3, "client", return_value=FakeSTSClient()): + signed_headers, signed_data = CommonBatchFilesUtils().sign_aws_request( + service_name="bedrock", + data={"jobName": "litellm-batch-job"}, + endpoint_url="https://bedrock.us-east-1.amazonaws.com/model-invocation-job", + optional_params=optional_params, + ) + + authorization = {key.lower(): value for key, value in signed_headers.items()}["authorization"] + assert "ASIABATCHSIGNROLE" in authorization + assert signed_data == b'{"jobName": "litellm-batch-job"}' diff --git a/tests/test_litellm/llms/databricks/test_databricks_cost_calculator.py b/tests/test_litellm/llms/databricks/test_databricks_cost_calculator.py index 29ad8ee4b6e..e72642f7a04 100644 --- a/tests/test_litellm/llms/databricks/test_databricks_cost_calculator.py +++ b/tests/test_litellm/llms/databricks/test_databricks_cost_calculator.py @@ -62,6 +62,8 @@ PUBLISHED_DBU_PER_MILLION: Final = { "databricks/databricks-gemini-2-5-pro": ("22.321", "178.571", "22.321", "2.232"), "databricks/databricks-gemini-2-5-flash": ("5.357", "44.643", "5.357", "0.536"), "databricks/databricks-kimi-k3": ("42.857", "214.286", "42.857", "4.286"), + "databricks/databricks-deepseek-v4-flash-0731": ("2.000", "4.000", "2.000", "0.400"), + "databricks/databricks-deepseek-v4-pro-0813": ("18.857", "56.571", "18.857", "1.886"), "databricks/databricks-glm-5-2": ("20.000", "62.857", "20.000", "3.714"), } PROMOTIONAL_DISCOUNT: Final = 0.80 diff --git a/tests/test_litellm/llms/mistral/ocr/test_mistral_ocr_cost.py b/tests/test_litellm/llms/mistral/ocr/test_mistral_ocr_cost.py index 890df597933..a0e1616d4b2 100644 --- a/tests/test_litellm/llms/mistral/ocr/test_mistral_ocr_cost.py +++ b/tests/test_litellm/llms/mistral/ocr/test_mistral_ocr_cost.py @@ -24,6 +24,9 @@ OCR3_MODEL = "mistral/mistral-ocr-2512" OCR3_COST_PER_PAGE = 0.002 OCR3_ANNOTATION_COST_PER_PAGE = 0.003 +AZURE_DOC_AI_MODEL = "azure_ai/mistral-document-ai-2512" +AZURE_DOC_AI_COST_PER_PAGE = 0.003 + def _ocr_response(model: str, pages_processed: int) -> OCRResponse: return OCRResponse( @@ -33,6 +36,14 @@ def _ocr_response(model: str, pages_processed: int) -> OCRResponse: ) +def _annotated_ocr_response(model: str, pages_processed: int | None, annotation_pages: int) -> OCRResponse: + return OCRResponse( + pages=[], + model=model, + usage_info=OCRUsageInfo(pages_processed=pages_processed, pages_processed_annotation=annotation_pages), + ) + + @pytest.mark.parametrize("model", ["mistral-ocr-4-0", "mistral-ocr-latest"]) def test_model_info_ocr4_price(model: str) -> None: info = litellm.get_model_info(model=f"mistral/{model}", custom_llm_provider="mistral") @@ -79,3 +90,46 @@ def test_ocr3_cost_scales_with_pages(local_model_cost_map, pages_processed: int) call_type="ocr", ) assert cost == pytest.approx(OCR3_COST_PER_PAGE * pages_processed) + + +def test_ocr3_bills_ocr_and_annotation_pages_at_their_own_rates(local_model_cost_map) -> None: + cost = completion_cost( + completion_response=_annotated_ocr_response("mistral-ocr-2512", 2, 3), + model=OCR3_MODEL, + custom_llm_provider="mistral", + call_type="ocr", + ) + assert cost == pytest.approx(2 * OCR3_COST_PER_PAGE + 3 * OCR3_ANNOTATION_COST_PER_PAGE) + + +def test_ocr3_bills_annotation_only_response(local_model_cost_map) -> None: + cost = completion_cost( + completion_response=_annotated_ocr_response("mistral-ocr-2512", 0, 3), + model=OCR3_MODEL, + custom_llm_provider="mistral", + call_type="ocr", + ) + assert cost == pytest.approx(3 * OCR3_ANNOTATION_COST_PER_PAGE) + + +def test_ocr3_bills_annotation_pages_when_pages_processed_missing(local_model_cost_map) -> None: + cost = completion_cost( + completion_response=_annotated_ocr_response("mistral-ocr-2512", None, 4), + model=OCR3_MODEL, + custom_llm_provider="mistral", + call_type="ocr", + ) + assert cost == pytest.approx(4 * OCR3_ANNOTATION_COST_PER_PAGE) + + +def test_azure_doc_ai_annotation_pages_fall_back_to_ocr_rate(local_model_cost_map) -> None: + info = litellm.get_model_info(model=AZURE_DOC_AI_MODEL, custom_llm_provider="azure_ai") + assert info.get("annotation_cost_per_page") is None + assert info["ocr_cost_per_page"] == AZURE_DOC_AI_COST_PER_PAGE + cost = completion_cost( + completion_response=_annotated_ocr_response("mistral-document-ai-2512", 0, 1), + model=AZURE_DOC_AI_MODEL, + custom_llm_provider="azure_ai", + call_type="ocr", + ) + assert cost == pytest.approx(AZURE_DOC_AI_COST_PER_PAGE) diff --git a/tests/test_litellm/llms/openai/chat/test_openai_gpt_transformation.py b/tests/test_litellm/llms/openai/chat/test_openai_gpt_transformation.py index 3f346b5e8e7..3ef5e39fc5f 100644 --- a/tests/test_litellm/llms/openai/chat/test_openai_gpt_transformation.py +++ b/tests/test_litellm/llms/openai/chat/test_openai_gpt_transformation.py @@ -145,6 +145,69 @@ class TestGetOptionalParamsIntegration: assert regular_params.get("user") == "my-end-user" assert responses_params.get("user") == "my-end-user" + def test_reasoning_effort_supported_for_unknown_model_alias(self): + """An openai/-routed model litellm doesn't recognize is likely a proxy alias: + reasoning_effort must be forwarded so the server decides support.""" + from litellm.llms.openai.openai import OpenAIConfig + + supported_params = OpenAIConfig().get_supported_openai_params( + "my-claude-alias" + ) + assert "reasoning_effort" in supported_params + + def test_reasoning_effort_not_supported_for_known_non_reasoning_models(self): + """Known OpenAI models keep failing closed client-side.""" + from litellm.llms.openai.openai import OpenAIConfig + + config = OpenAIConfig() + assert "reasoning_effort" not in config.get_supported_openai_params("gpt-4o") + assert "reasoning_effort" not in config.get_supported_openai_params( + "responses/gpt-4.1-mini" + ) + + def test_reasoning_effort_not_inherited_by_openai_compatible_subclasses(self): + """Providers subclassing either openai config keep their own reasoning_effort gating + for their models, which are all unknown to the openai catalog.""" + from litellm.llms.openai.openai import OpenAIConfig + + class InheritingDispatcherConfig(OpenAIConfig): + pass + + class InheritingGPTConfig(OpenAIGPTConfig): + pass + + assert "reasoning_effort" not in InheritingDispatcherConfig().get_supported_openai_params( + "some-unknown-model" + ) + assert "reasoning_effort" not in InheritingGPTConfig().get_supported_openai_params( + "some-unknown-model" + ) + + def test_reasoning_effort_forwarded_in_optional_params_for_unknown_model_alias( + self, + ): + """Regression test for reasoning_effort raising UnsupportedParamsError + client-side for openai/-prefixed proxy aliases before any HTTP request.""" + from litellm.utils import get_optional_params + + optional_params = get_optional_params( + model="my-claude-alias", + custom_llm_provider="openai", + reasoning_effort="low", + ) + assert optional_params.get("reasoning_effort") == "low" + + def test_reasoning_effort_still_rejected_for_known_non_reasoning_model(self): + """A real OpenAI model that doesn't reason still rejects the param client-side.""" + from litellm.utils import get_optional_params + + with pytest.raises(litellm.utils.UnsupportedParamsError): + get_optional_params( + model="gpt-4o", + custom_llm_provider="openai", + reasoning_effort="low", + ) + class TestOpenAIChatCompletionStreamingHandler: """Tests for OpenAIChatCompletionStreamingHandler.chunk_parser()""" diff --git a/tests/test_litellm/llms/vertex_ai/test_vertex_ai_common_utils.py b/tests/test_litellm/llms/vertex_ai/test_vertex_ai_common_utils.py index cc923f05831..d1d751989ea 100644 --- a/tests/test_litellm/llms/vertex_ai/test_vertex_ai_common_utils.py +++ b/tests/test_litellm/llms/vertex_ai/test_vertex_ai_common_utils.py @@ -195,6 +195,22 @@ def test_set_schema_property_ordering_with_excessive_nesting(): set_schema_property_ordering(schema) +def test_set_schema_property_ordering_skips_non_dict_property_values(): + """Non-dict property values must be skipped, not recursed into (they used to raise).""" + schema = { + "properties": { + "a": "hello", + "b": {"type": "string"}, + "c": ["x"], + "d": "a string mentioning items", + } + } + + result = set_schema_property_ordering(schema) + + assert result["propertyOrdering"] == ["a", "b", "c", "d"] + + def test_build_vertex_schema(): """Test build_vertex_schema with a sample schema""" from litellm.llms.vertex_ai.common_utils import _build_vertex_schema diff --git a/tests/test_litellm/proxy/_experimental/mcp_server/conftest.py b/tests/test_litellm/proxy/_experimental/mcp_server/conftest.py index b477bf3f406..2ccba2b2055 100644 --- a/tests/test_litellm/proxy/_experimental/mcp_server/conftest.py +++ b/tests/test_litellm/proxy/_experimental/mcp_server/conftest.py @@ -2,6 +2,30 @@ import os import pytest +from litellm.proxy._experimental.mcp_server.mcp_server_manager import ( + global_mcp_server_manager, +) + + +@pytest.fixture(autouse=True) +def _hermetic_mcp_server_registry(): + """Restore the singleton ``global_mcp_server_manager``'s registry state around every + test, so entries seeded by one test never leak into another on a shared shard.""" + saved_registry = dict(global_mcp_server_manager.registry) + saved_config_servers = dict(global_mcp_server_manager.config_mcp_servers) + saved_tool_mapping = dict(global_mcp_server_manager.tool_name_to_mcp_server_name_mapping) + saved_oauth_slots = global_mcp_server_manager._oauth_discovery_slots + try: + yield + finally: + global_mcp_server_manager.registry.clear() + global_mcp_server_manager.registry.update(saved_registry) + global_mcp_server_manager.config_mcp_servers.clear() + global_mcp_server_manager.config_mcp_servers.update(saved_config_servers) + global_mcp_server_manager.tool_name_to_mcp_server_name_mapping.clear() + global_mcp_server_manager.tool_name_to_mcp_server_name_mapping.update(saved_tool_mapping) + global_mcp_server_manager._oauth_discovery_slots = saved_oauth_slots + @pytest.fixture(autouse=True) def _hermetic_server_root_path(): diff --git a/tests/test_litellm/proxy/_experimental/mcp_server/test_mcp_server_identity_env.py b/tests/test_litellm/proxy/_experimental/mcp_server/test_mcp_server_identity_env.py index ac7082c2668..1c65adac4c6 100644 --- a/tests/test_litellm/proxy/_experimental/mcp_server/test_mcp_server_identity_env.py +++ b/tests/test_litellm/proxy/_experimental/mcp_server/test_mcp_server_identity_env.py @@ -23,6 +23,12 @@ MGMT_MODULE = "litellm.proxy.management_endpoints.mcp_management_endpoints" @contextlib.contextmanager def _env_and_reload(**env): saved = {key: os.environ.get(key) for key in env} + utils_module = importlib.import_module(UTILS_MODULE) + mgmt_module = importlib.import_module(MGMT_MODULE) + # Restore pre-reload module attributes afterwards instead of reloading again: + # a reload re-creates the module's classes, breaking exception identity for + # modules that imported them earlier + snapshots = {module: dict(vars(module)) for module in (utils_module, mgmt_module)} def _apply_env(values): for key, value in values.items(): @@ -32,8 +38,8 @@ def _env_and_reload(**env): os.environ[key] = value def _reload(): - utils = importlib.reload(importlib.import_module(UTILS_MODULE)) - mgmt = importlib.reload(importlib.import_module(MGMT_MODULE)) + utils = importlib.reload(utils_module) + mgmt = importlib.reload(mgmt_module) return utils, mgmt try: @@ -41,7 +47,10 @@ def _env_and_reload(**env): yield _reload() finally: _apply_env(saved) - _reload() + for module, snapshot in snapshots.items(): + for key in [key for key in vars(module) if key not in snapshot]: + delattr(module, key) + vars(module).update(snapshot) def test_defaults_used_when_env_unset(): diff --git a/tests/test_litellm/proxy/guardrails/guardrail_hooks/test_bedrock_guardrails.py b/tests/test_litellm/proxy/guardrails/guardrail_hooks/test_bedrock_guardrails.py index 235a5c0c09b..bcda1b8b61d 100644 --- a/tests/test_litellm/proxy/guardrails/guardrail_hooks/test_bedrock_guardrails.py +++ b/tests/test_litellm/proxy/guardrails/guardrail_hooks/test_bedrock_guardrails.py @@ -5590,3 +5590,52 @@ async def test_streaming_end_of_stream_block_emits_error_frame_instead_of_trunca assert payload["error"]["message"] == "Violated guardrail policy" assert payload["error"]["code"] == "400" assert payload["error"]["provider_specific_fields"]["guardrailIdentifier"] == "test-guardrail" + + +@pytest.mark.asyncio +async def test_apply_guardrail_debug_log_masks_signed_request_headers(): + import logging + + from litellm._logging import verbose_proxy_logger + + session_token = "FakeSessionTokenValueThatMustNeverAppearInLogs1234567890" + guardrail = BedrockGuardrail( + guardrailIdentifier="test-guardrail", + guardrailVersion="DRAFT", + aws_access_key_id="ASIAFAKEACCESSKEYID1", + aws_secret_access_key="fakeSecretAccessKeyForSigning", + aws_session_token=session_token, + aws_region_name="us-east-1", + ) + + mock_response = MagicMock() + mock_response.status_code = 200 + mock_response.json.return_value = {"action": "NONE", "outputs": []} + + captured_records: list[logging.LogRecord] = [] + + class _RecordingHandler(logging.Handler): + def emit(self, record: logging.LogRecord) -> None: + captured_records.append(record) + + handler = _RecordingHandler(level=logging.DEBUG) + previous_level = verbose_proxy_logger.level + verbose_proxy_logger.addHandler(handler) + verbose_proxy_logger.setLevel(logging.DEBUG) + try: + with patch.object(guardrail.async_handler, "post", new_callable=AsyncMock) as mock_post: + mock_post.return_value = mock_response + await guardrail.make_bedrock_api_request( + source="INPUT", + messages=[{"role": "user", "content": "hello"}], + request_data={}, + ) + finally: + verbose_proxy_logger.removeHandler(handler) + verbose_proxy_logger.setLevel(previous_level) + + rendered_messages = [record.getMessage() for record in captured_records] + header_lines = [message for message in rendered_messages if "headers:" in message] + assert header_lines, "expected the signed-request debug line to be logged" + assert any("X-Amz-Security-Token" in message for message in header_lines) + assert all(session_token not in message for message in rendered_messages) diff --git a/tests/test_litellm/proxy/guardrails/test_guardrail_endpoints.py b/tests/test_litellm/proxy/guardrails/test_guardrail_endpoints.py index 9b2117b7647..9511732fd50 100644 --- a/tests/test_litellm/proxy/guardrails/test_guardrail_endpoints.py +++ b/tests/test_litellm/proxy/guardrails/test_guardrail_endpoints.py @@ -917,7 +917,9 @@ async def test_bedrock_guardrail_make_api_request_passes_api_key(): "Content-Type": "application/json", "Authorization": "Bearer test-api-key-789", } - mock_request_instance.prepare.return_value = Mock() + mock_request_instance.prepare.return_value = Mock( + headers=mock_request_instance.headers + ) mock_aws_request.return_value = mock_request_instance await guardrail_hook.make_bedrock_api_request( diff --git a/tests/test_litellm/proxy/management_endpoints/test_key_management_endpoints.py b/tests/test_litellm/proxy/management_endpoints/test_key_management_endpoints.py index b5a4204f0af..a81c6b4c656 100644 --- a/tests/test_litellm/proxy/management_endpoints/test_key_management_endpoints.py +++ b/tests/test_litellm/proxy/management_endpoints/test_key_management_endpoints.py @@ -11033,6 +11033,123 @@ class TestLIT1884KeyUpdateValidation: ) +class TestLIT4891SafePresetKeyTypeTransition: + def _make_existing_key(self, allowed_routes): + row = MagicMock() + row.user_id = "internal-user-123" + row.created_by = "internal-user-123" + row.token = "hashed_token" + row.team_id = None + row.max_budget = None + row.spend = 0.0 + row.organization_id = None + row.project_id = None + row.allowed_routes = allowed_routes + return row + + def _make_auth(self): + return UserAPIKeyAuth( + user_id="internal-user-123", + user_role=LitellmUserRoles.INTERNAL_USER, + ) + + async def _run_update(self, data, existing_key_row): + try: + await _validate_update_key_data( + data=data, + existing_key_row=existing_key_row, + user_api_key_dict=self._make_auth(), + llm_router=None, + premium_user=False, + prisma_client=AsyncMock(), + user_api_key_cache=MagicMock(), + ) + except HTTPException as exc: + return exc + return None + + def _assert_routes_403(self, exc): + assert exc is not None + assert exc.status_code == 403 + assert "Only proxy admins can set" in str(exc.detail) + + @pytest.mark.asyncio + async def test_non_admin_owner_can_clear_safe_preset_to_full_access(self): + assert ( + await self._run_update( + data=UpdateKeyRequest(key="sk-test", allowed_routes=[]), + existing_key_row=self._make_existing_key(allowed_routes=["llm_api_routes"]), + ) + is None + ) + + @pytest.mark.asyncio + async def test_non_admin_owner_can_switch_full_access_to_safe_preset(self): + assert ( + await self._run_update( + data=UpdateKeyRequest(key="sk-test", allowed_routes=["llm_api_routes"]), + existing_key_row=self._make_existing_key(allowed_routes=[]), + ) + is None + ) + + @pytest.mark.asyncio + async def test_non_admin_owner_can_narrow_to_read_only_preset(self): + assert ( + await self._run_update( + data=UpdateKeyRequest(key="sk-test", allowed_routes=["info_routes"]), + existing_key_row=self._make_existing_key(allowed_routes=["llm_api_routes"]), + ) + is None + ) + + @pytest.mark.asyncio + async def test_non_admin_can_resend_read_only_preset_unchanged(self): + assert ( + await self._run_update( + data=UpdateKeyRequest(key="sk-test", allowed_routes=["info_routes"]), + existing_key_row=self._make_existing_key(allowed_routes=["info_routes"]), + ) + is None + ) + + @pytest.mark.asyncio + async def test_non_admin_cannot_widen_read_only_key_to_full_access(self): + self._assert_routes_403( + await self._run_update( + data=UpdateKeyRequest(key="sk-test", allowed_routes=[]), + existing_key_row=self._make_existing_key(allowed_routes=["info_routes"]), + ) + ) + + @pytest.mark.asyncio + async def test_non_admin_cannot_widen_read_only_key_to_llm_api(self): + self._assert_routes_403( + await self._run_update( + data=UpdateKeyRequest(key="sk-test", allowed_routes=["llm_api_routes"]), + existing_key_row=self._make_existing_key(allowed_routes=["info_routes"]), + ) + ) + + @pytest.mark.asyncio + async def test_non_admin_cannot_clear_custom_route_restriction(self): + self._assert_routes_403( + await self._run_update( + data=UpdateKeyRequest(key="sk-test", allowed_routes=[]), + existing_key_row=self._make_existing_key(allowed_routes=["/chat/completions"]), + ) + ) + + @pytest.mark.asyncio + async def test_non_admin_cannot_set_non_preset_routes(self): + self._assert_routes_403( + await self._run_update( + data=UpdateKeyRequest(key="sk-test", allowed_routes=["management_routes"]), + existing_key_row=self._make_existing_key(allowed_routes=["llm_api_routes"]), + ) + ) + + class TestKeyOwnerPrivilegeEscalation: """ Policy: @@ -12007,9 +12124,10 @@ class TestAllowedRoutesCallerPermission: @pytest.mark.asyncio async def test_non_admin_update_key_explicit_empty_allowed_routes_rejected(self): - """`update_key_fn` rejects a non-admin when `allowed_routes` is - present as `[]` in the request body. The value matches the model - default but `model_fields_set` distinguishes the two.""" + """`update_key_fn` rejects a non-admin clearing a custom (non-preset) + route restriction with an explicit `[]` in the request body. The value + matches the model default but `model_fields_set` distinguishes the + two. Clearing from a safe preset is allowed (LIT-4891).""" from litellm.proxy.management_endpoints.key_management_endpoints import ( update_key_fn, ) @@ -12032,7 +12150,7 @@ class TestAllowedRoutesCallerPermission: patch( "litellm.proxy.management_endpoints.key_management_endpoints._get_and_validate_existing_key", new_callable=AsyncMock, - return_value=MagicMock(), + return_value=MagicMock(allowed_routes=["/chat/completions"]), ), ): with pytest.raises(ProxyException) as exc_info: @@ -12047,8 +12165,8 @@ class TestAllowedRoutesCallerPermission: @pytest.mark.asyncio async def test_non_admin_update_key_explicit_null_allowed_routes_rejected(self): - """`update_key_fn` rejects a non-admin when `allowed_routes` is - present as `null` in the request body.""" + """`update_key_fn` rejects a non-admin clearing a custom (non-preset) + route restriction with an explicit `null` in the request body.""" from litellm.proxy.management_endpoints.key_management_endpoints import ( update_key_fn, ) @@ -12071,7 +12189,7 @@ class TestAllowedRoutesCallerPermission: patch( "litellm.proxy.management_endpoints.key_management_endpoints._get_and_validate_existing_key", new_callable=AsyncMock, - return_value=MagicMock(), + return_value=MagicMock(allowed_routes=["/chat/completions"]), ), ): with pytest.raises(ProxyException) as exc_info: diff --git a/tests/test_litellm/proxy/management_endpoints/test_team_endpoints.py b/tests/test_litellm/proxy/management_endpoints/test_team_endpoints.py index ffa6bc601e9..30b2ab86b9a 100644 --- a/tests/test_litellm/proxy/management_endpoints/test_team_endpoints.py +++ b/tests/test_litellm/proxy/management_endpoints/test_team_endpoints.py @@ -3741,6 +3741,93 @@ async def test_list_team_v2_with_status_deleted(): assert len(result["teams"]) == 2 +@pytest.mark.asyncio +async def test_list_team_v2_includes_litellm_model_table(): + """ + Regression test for GH #26312: GET /v2/team/list must eagerly load the + litellm_model_table relation for active teams, same as /team/info and + /team/list, or a team's model_aliases always read back as null from this + endpoint. Deleted teams are excluded: LiteLLM_DeletedTeamTable has no such + relation in the Prisma schema, so requesting it there raises + UnknownRelationalFieldError against a real database. + + The fake find_many below only attaches litellm_model_table when its own + `include` kwarg actually asks for the relation, so the assertions below + are on what the caller gets back, not on how find_many was called. + """ + from unittest.mock import AsyncMock, Mock, patch + + from fastapi import Request + + from litellm.proxy._types import LitellmUserRoles, UserAPIKeyAuth + from litellm.proxy.management_endpoints.team_endpoints import list_team_v2 + + mock_request = Mock(spec=Request) + mock_user_api_key_dict_admin = UserAPIKeyAuth( + user_role=LitellmUserRoles.PROXY_ADMIN, + user_id="admin_user_123", + ) + + def _team_row(team_id: str, include) -> Mock: + model_table = ( + { + "id": 1, + "model_aliases": {"my-fast-model": "fake-model"}, + "created_by": "u", + "updated_by": "u", + "team": None, + } + if (include or {}).get("litellm_model_table") + else None + ) + return Mock( + team_id=team_id, + model_dump=lambda: { + "team_id": team_id, + "team_alias": "t", + "litellm_model_table": model_table, + }, + ) + + with patch("litellm.proxy.proxy_server.prisma_client") as mock_prisma_client: # test-quality-ok: this file's DB-mock convention + mock_db = Mock() + mock_prisma_client.db = mock_db + + mock_db.litellm_teamtable.find_many = AsyncMock( + side_effect=lambda **kw: [_team_row("team_1", kw.get("include"))] + ) + mock_db.litellm_teamtable.count = AsyncMock(return_value=1) + mock_db.litellm_verificationtoken.group_by = AsyncMock(return_value=[]) + + result = await list_team_v2( + http_request=mock_request, + user_id=None, + user_api_key_dict=mock_user_api_key_dict_admin, + page=1, + page_size=10, + status=None, + ) + + assert result["teams"][0].litellm_model_table is not None + assert result["teams"][0].litellm_model_table.model_aliases == {"my-fast-model": "fake-model"} + + mock_db.litellm_deletedteamtable.find_many = AsyncMock( + side_effect=lambda **kw: [_team_row("team_2", kw.get("include"))] + ) + mock_db.litellm_deletedteamtable.count = AsyncMock(return_value=1) + + await list_team_v2( + http_request=mock_request, + user_id=None, + user_api_key_dict=mock_user_api_key_dict_admin, + page=1, + page_size=10, + status="deleted", + ) + + assert "include" not in mock_db.litellm_deletedteamtable.find_many.call_args.kwargs + + @pytest.mark.asyncio async def test_list_team_v2_org_admin_sees_org_teams(): """ diff --git a/tests/test_litellm/proxy/management_helpers/test_object_permission_utils.py b/tests/test_litellm/proxy/management_helpers/test_object_permission_utils.py index 5ef83344c1a..f2b6b799271 100644 --- a/tests/test_litellm/proxy/management_helpers/test_object_permission_utils.py +++ b/tests/test_litellm/proxy/management_helpers/test_object_permission_utils.py @@ -1,11 +1,9 @@ import json +from unittest.mock import AsyncMock, MagicMock, patch import pytest from fastapi import HTTPException - -from unittest.mock import AsyncMock, MagicMock, patch - from litellm.proxy._types import ( LiteLLM_ObjectPermissionBase, LiteLLM_ObjectPermissionTable, @@ -13,10 +11,10 @@ from litellm.proxy._types import ( SpecialMCPServerName, ) from litellm.proxy.management_helpers.object_permission_utils import ( + _drop_stale_object_permission_mcp_servers, _extract_requested_mcp_access_groups, _extract_requested_mcp_server_ids, _resolve_team_allowed_mcp_servers, - _rewrite_object_permission_mcp_servers, _set_object_permission, enforce_all_proxy_mcp_servers_grant_is_admin_only, validate_key_mcp_servers_against_team, @@ -153,10 +151,10 @@ def test_extract_requested_mcp_server_ids_excludes_no_mcp_servers_sentinel(): assert _extract_requested_mcp_server_ids(obj_perm) == {"server-1"} -def test_rewrite_object_permission_mcp_servers_preserves_sentinel(): - obj_perm = {"mcp_servers": ["no-mcp-servers", "alias-1"]} - _rewrite_object_permission_mcp_servers(obj_perm, {"alias-1": {"server-1"}}) - assert obj_perm["mcp_servers"] == ["no-mcp-servers", "server-1"] +def test_drop_stale_object_permission_mcp_servers_preserves_sentinel_and_alias(): + obj_perm = {"mcp_servers": ["no-mcp-servers", "alias-1", "gone-id"]} + _drop_stale_object_permission_mcp_servers(obj_perm, {"alias-1": {"server-1"}, "gone-id": set()}) + assert obj_perm["mcp_servers"] == ["no-mcp-servers", "alias-1"] @pytest.mark.asyncio @@ -692,9 +690,10 @@ async def test_validate_mcp_server_alias_outside_team_scope_raises( new_callable=AsyncMock, return_value=[], ) -async def test_validate_mcp_server_alias_is_normalized_before_save( - mock_access_groups, mock_allow_all -): +async def test_validate_mcp_server_alias_persists_verbatim(mock_access_groups, mock_allow_all): + """Regression for the multi-region shared-DB setup: an alias grant must be + stored as the alias, so every instance can expand it to its own local id. + Rewriting to this instance's server_id breaks access on the other region.""" team_obj = _make_team_obj(mcp_servers=["allowed-server-id"]) object_permission = { "mcp_servers": ["allowed-alias"], @@ -706,8 +705,27 @@ async def test_validate_mcp_server_alias_is_normalized_before_save( team_obj=team_obj, ) - assert object_permission["mcp_servers"] == ["allowed-server-id"] - assert object_permission["mcp_tool_permissions"] == {"allowed-server-id": ["tool1"]} + assert object_permission["mcp_servers"] == ["allowed-alias"] + assert object_permission["mcp_tool_permissions"] == {"Allowed Server": ["tool1"]} + + +def test_alias_grant_expands_on_other_region_after_save(): + """Cross-region flow: the west instance saves an alias grant (its resolver maps + the alias to west's hash-derived id), then the central instance, whose registry + maps the same alias to a different id, expands the persisted grant. Rewriting + to west's id at save time is exactly the regression this guards against.""" + west_mgr = _make_mock_mcp_manager(servers=[_make_mock_mcp_server("west-id", alias="github-mcp")]) + central_mgr = _make_mock_mcp_manager(servers=[_make_mock_mcp_server("central-id", alias="github-mcp")]) + + object_permission = {"mcp_servers": ["github-mcp"]} + _drop_stale_object_permission_mcp_servers(object_permission, {"github-mcp": {"west-id"}}) + assert object_permission["mcp_servers"] == ["github-mcp"] + + from litellm.proxy._experimental.mcp_server.mcp_server_manager import MCPServerManager + + expand = MCPServerManager.expand_permission_list + assert expand(west_mgr, object_permission["mcp_servers"]) == ["west-id"] + assert expand(central_mgr, object_permission["mcp_servers"]) == ["central-id"] @pytest.mark.asyncio diff --git a/tests/test_litellm/proxy/policy_engine/test_pipeline_executor.py b/tests/test_litellm/proxy/policy_engine/test_pipeline_executor.py index 054a5af4148..4fcb7d22588 100644 --- a/tests/test_litellm/proxy/policy_engine/test_pipeline_executor.py +++ b/tests/test_litellm/proxy/policy_engine/test_pipeline_executor.py @@ -749,6 +749,106 @@ async def test_single_step_pipeline_allow(monkeypatch): assert guard.calls == 1 +@pytest.mark.asyncio +async def test_allow_restores_independent_guardrails_list(monkeypatch): + """ + Request activates an independent guardrail; an unrelated pipeline runs and allows. + Expected: no modified_data escapes, so the request's guardrails list survives + and the independent guardrail still runs at later lifecycle stages (post_call). + Regression: LIT-6587 (pipeline clobbered the list with its last step's guardrail). + """ + pipeline_guard = AlwaysPassGuardrail(guardrail_name="input-scan") + + pipeline = GuardrailPipeline( + mode="pre_call", + steps=[PipelineStep(guardrail="input-scan", on_fail="block", on_pass="allow")], + ) + + monkeypatch.setattr(litellm, "callbacks", [pipeline_guard]) + + data = { + "messages": [{"role": "user", "content": "clean content"}], + "metadata": {"guardrails": ["independent-output-guard"]}, + } + result = await PipelineExecutor.execute_steps( + steps=pipeline.steps, + mode=pipeline.mode, + data=data, + user_api_key_dict=MagicMock(), + call_type="completion", + policy_name="input-pipeline-policy", + ) + + assert pipeline_guard.calls == 1 + assert result.terminal_action == "allow" + propagated = result.modified_data or data + assert propagated["metadata"]["guardrails"] == ["independent-output-guard"] + assert data["metadata"]["guardrails"] == ["independent-output-guard"] + + +@pytest.mark.asyncio +async def test_allow_does_not_leak_guardrails_into_bare_request(monkeypatch): + """A request without metadata must not gain a metadata.guardrails list from the pipeline.""" + pipeline_guard = AlwaysPassGuardrail(guardrail_name="input-scan") + + pipeline = GuardrailPipeline( + mode="pre_call", + steps=[PipelineStep(guardrail="input-scan", on_fail="block", on_pass="allow")], + ) + + monkeypatch.setattr(litellm, "callbacks", [pipeline_guard]) + + data = {"messages": [{"role": "user", "content": "clean content"}]} + result = await PipelineExecutor.execute_steps( + steps=pipeline.steps, + mode=pipeline.mode, + data=data, + user_api_key_dict=MagicMock(), + call_type="completion", + policy_name="input-pipeline-policy", + ) + + assert result.terminal_action == "allow" + propagated = result.modified_data or data + assert "guardrails" not in propagated.get("metadata", {}) + assert "metadata" not in data + + +@pytest.mark.asyncio +async def test_data_forwarding_keeps_changes_and_restores_guardrails_list(monkeypatch): + """A pass_data pipeline's modifications propagate while the request's guardrails list is restored.""" + pii_guard = PiiMaskingGuardrail(guardrail_name="pii-masker") + content_guard = ContentCheckGuardrail(guardrail_name="content-check") + + pipeline = GuardrailPipeline( + mode="pre_call", + steps=[ + PipelineStep(guardrail="pii-masker", on_fail="block", on_pass="next", pass_data=True), + PipelineStep(guardrail="content-check", on_fail="block", on_pass="allow"), + ], + ) + + monkeypatch.setattr(litellm, "callbacks", [pii_guard, content_guard]) + + data = { + "messages": [{"role": "user", "content": "Hello John Smith"}], + "metadata": {"guardrails": ["independent-output-guard"]}, + } + result = await PipelineExecutor.execute_steps( + steps=pipeline.steps, + mode=pipeline.mode, + data=data, + user_api_key_dict=MagicMock(), + call_type="completion", + policy_name="pii-then-safety", + ) + + assert result.terminal_action == "allow" + assert result.modified_data is not None + assert result.modified_data["messages"][0]["content"] == "Hello [REDACTED]" + assert result.modified_data["metadata"]["guardrails"] == ["independent-output-guard"] + + @pytest.mark.asyncio async def test_step_results_include_duration(monkeypatch): """Step results should include timing information.""" diff --git a/tests/test_litellm/proxy/spend_tracking/test_savings.py b/tests/test_litellm/proxy/spend_tracking/test_savings.py index c3297ee6ae9..7dd18587df3 100644 --- a/tests/test_litellm/proxy/spend_tracking/test_savings.py +++ b/tests/test_litellm/proxy/spend_tracking/test_savings.py @@ -14,6 +14,8 @@ from litellm.proxy.spend_tracking.savings import ( from litellm.router import Router from litellm.types.utils import Usage +pytestmark = pytest.mark.usefixtures("local_model_cost_map") + def _anthropic_costs(model: str) -> tuple[float, float]: info = litellm.get_model_info(model=model, custom_llm_provider="anthropic") diff --git a/tests/test_litellm/responses/litellm_completion_transformation/test_litellm_completion_responses.py b/tests/test_litellm/responses/litellm_completion_transformation/test_litellm_completion_responses.py index bb59e576568..aba79fe11bf 100644 --- a/tests/test_litellm/responses/litellm_completion_transformation/test_litellm_completion_responses.py +++ b/tests/test_litellm/responses/litellm_completion_transformation/test_litellm_completion_responses.py @@ -985,6 +985,55 @@ class TestFunctionCallTransformation: assert result[0]["tool_calls"][0]["function"]["arguments"] == "{}" + def test_function_call_transformation_json_encodes_object_arguments(self): + """A decoded arguments object must be JSON-encoded, not str()'d. + + Clients and providers sometimes send `arguments` as an object rather + than a JSON string; `str()` on a dict produces a Python repr with + single quotes, which downstream JSON parsers reject with errors like + "Expecting ',' delimiter". + """ + function_call_item = { + "type": "function_call", + "name": "shell", + "arguments": {"command": "ls", "timeout": 30, "flags": ["-l", "-a"]}, + "call_id": "call_123", + "id": "call_123", + "status": "completed", + } + + result = LiteLLMCompletionResponsesConfig._transform_responses_api_function_call_to_chat_completion_message( + function_call=function_call_item + ) + + arguments = result[0].get("tool_calls", [])[0].get("function", {}).get("arguments") + assert json.loads(arguments) == {"command": "ls", "timeout": 30, "flags": ["-l", "-a"]} + assert "'" not in arguments + + def test_create_tool_call_chunk_json_encodes_object_arguments(self): + """Cached tool_call definitions with object arguments stay valid JSON.""" + chunk = LiteLLMCompletionResponsesConfig._create_tool_call_chunk( + tool_use_definition={ + "id": "call_456", + "type": "function", + "function": {"name": "shell", "arguments": {"command": "ls"}}, + }, + tool_call_id="call_456", + index=0, + ) + + assert json.loads(chunk["function"]["arguments"]) == {"command": "ls"} + + def test_create_tool_call_chunk_keeps_empty_arguments_default(self): + """Missing arguments still fall back to an empty JSON object.""" + chunk = LiteLLMCompletionResponsesConfig._create_tool_call_chunk( + tool_use_definition={"id": "call_789", "type": "function", "function": {"name": "shell"}}, + tool_call_id="call_789", + index=0, + ) + + assert chunk["function"]["arguments"] == "{}" + def test_complete_input_transformation_with_function_calls(self): """Test the complete transformation with the exact input from the issue""" test_input = [ diff --git a/tests/test_litellm/responses/litellm_completion_transformation/test_streaming_iterator_transformation.py b/tests/test_litellm/responses/litellm_completion_transformation/test_streaming_iterator_transformation.py index 823f656ddc5..01148f627f1 100644 --- a/tests/test_litellm/responses/litellm_completion_transformation/test_streaming_iterator_transformation.py +++ b/tests/test_litellm/responses/litellm_completion_transformation/test_streaming_iterator_transformation.py @@ -10,6 +10,7 @@ before response.completed, and that every event of a bridged stream carries the spend tracking stores, so a follow-up previous_response_id still finds the conversation. """ +import json from unittest.mock import AsyncMock, MagicMock import pytest @@ -523,3 +524,36 @@ async def test_streaming_response_id_falls_back_when_upstream_yields_nothing(): assert response_ids assert len(set(response_ids)) == 1 assert response_ids[0].startswith("resp_") + + +def test_object_tool_call_arguments_stream_as_valid_json(): + """A provider that sends decoded object arguments must still stream valid JSON. + + `str()` on a dict yields a Python repr with single quotes, which clients + parsing function_call_arguments reject with errors like + "Expecting ',' delimiter". + """ + iterator = LiteLLMCompletionStreamingIterator( + model="test-model", + litellm_custom_stream_wrapper=AsyncMock(), + request_input="Test input", + responses_api_request={}, + ) + iterator._queue_tool_call_delta_events( + [ + { + "index": 0, + "id": "call_obj", + "type": "function", + "function": {"name": "shell", "arguments": {"command": "ls", "flags": ["-l"]}}, + } + ] + ) + + streamed_arguments = "".join( + evt.delta + for evt in iterator._pending_tool_events + if evt.type == ResponsesAPIStreamEvents.FUNCTION_CALL_ARGUMENTS_DELTA + ) + + assert json.loads(streamed_arguments) == {"command": "ls", "flags": ["-l"]} diff --git a/tests/test_litellm/test_fireworks_serverless_model_costs.py b/tests/test_litellm/test_fireworks_serverless_model_costs.py index 0458af0da0e..a7a9e0fc37d 100644 --- a/tests/test_litellm/test_fireworks_serverless_model_costs.py +++ b/tests/test_litellm/test_fireworks_serverless_model_costs.py @@ -84,3 +84,41 @@ def test_bare_fireworks_ids_resolve_through_prefixed_entries(): assert info["output_cost_per_token"] == pytest.approx(expected["output_cost_per_token"]) assert info["max_input_tokens"] == expected["max_input_tokens"] assert info["max_output_tokens"] == expected["max_output_tokens"] + + +TWIN_PINNED_PRICES = { + "deepseek-v4-flash-0731": { + "input_cost_per_token": 2.2e-07, + "cache_read_input_token_cost": 7e-09, + "output_cost_per_token": 6.6e-07, + }, +} + + +def test_deepseek_v4_flash_0731_twins_pin_published_pricing(model_data): + """Both 0731 entries carry the price published at docs.fireworks.ai/serverless/pricing.""" + for bare_suffix, expected in TWIN_PINNED_PRICES.items(): + for key in ( + f"fireworks_ai/{bare_suffix}", + f"fireworks_ai/accounts/fireworks/models/{bare_suffix}", + ): + entry = model_data[key] + for field, value in expected.items(): + assert entry[field] == pytest.approx(value), f"{key}.{field}" + + +def test_fireworks_account_prefixed_twins_agree_on_price(model_data): + """Every accounts/fireworks/models/X entry prices identically to its bare fireworks_ai/X twin.""" + prefix = "fireworks_ai/accounts/fireworks/models/" + pairs_checked = 0 + for key, entry in model_data.items(): + if not key.startswith(prefix): + continue + bare_key = f"fireworks_ai/{key[len(prefix):]}" + bare_entry = model_data.get(bare_key) + if bare_entry is None: + continue + pairs_checked += 1 + for field in sorted({f for f in (*entry, *bare_entry) if "cost" in f}): + assert entry.get(field) == bare_entry.get(field), f"{key} vs {bare_key}: {field}" + assert pairs_checked >= 20 diff --git a/tests/test_litellm/test_openai_embedding_encoding_format_default.py b/tests/test_litellm/test_openai_embedding_encoding_format_default.py index 94e4e3c81e5..7a42eaf0f0a 100644 --- a/tests/test_litellm/test_openai_embedding_encoding_format_default.py +++ b/tests/test_litellm/test_openai_embedding_encoding_format_default.py @@ -1,124 +1,121 @@ -from unittest.mock import MagicMock, patch +import json +from typing import Final +import httpx import pytest +import respx -from litellm import embedding +import litellm -@pytest.mark.parametrize( - "set_env, env_value, expected", - [ - (False, None, "float"), - (True, "base64", "base64"), - ], -) -def test_openai_embedding_encoding_format_default( - monkeypatch, set_env, env_value, expected -): - monkeypatch.delenv("LITELLM_DEFAULT_EMBEDDING_ENCODING_FORMAT", raising=False) - if set_env: - monkeypatch.setenv("LITELLM_DEFAULT_EMBEDDING_ENCODING_FORMAT", env_value) - - mock_response = MagicMock() - mock_response.parse.return_value = MagicMock( - model_dump=lambda: { - "data": [{"embedding": [0.1, 0.2, 0.3], "index": 0}], - "model": "text-embedding-ada-002", - "object": "list", - "usage": {"prompt_tokens": 1, "total_tokens": 1}, - } +def _mock_openai_embedding_route(respx_mock: respx.MockRouter) -> respx.Route: + return respx_mock.post("https://api.openai.com/v1/embeddings").mock( + return_value=httpx.Response( + 200, + json={ + "object": "list", + "data": [{"object": "embedding", "index": 0, "embedding": [0.1, 0.2, 0.3]}], + "model": "text-embedding-3-small", + "usage": {"prompt_tokens": 2, "total_tokens": 2}, + }, + ) ) - mock_response.headers = {} - with patch( - "litellm.llms.openai.openai.OpenAIChatCompletion._get_openai_client" - ) as mock_get_client: - mock_client_instance = MagicMock() - mock_get_client.return_value = mock_client_instance - mock_client_instance.embeddings.with_raw_response.create.return_value = ( - mock_response - ) - embedding( - model="text-embedding-ada-002", - input="Hello world", - ) +@pytest.fixture(autouse=True) +def clear_default_encoding_format_env(monkeypatch: pytest.MonkeyPatch): + monkeypatch.delenv("LITELLM_DEFAULT_EMBEDDING_ENCODING_FORMAT", raising=False) - call_kwargs = ( - mock_client_instance.embeddings.with_raw_response.create.call_args[1] - ) - assert call_kwargs["encoding_format"] == expected + +def test_embedding_openai_omits_encoding_format_when_client_omits_it(respx_mock: respx.MockRouter) -> None: + mock_route: Final = _mock_openai_embedding_route(respx_mock) + + response: Final = litellm.embedding(model="openai/text-embedding-3-small", input=["hello"], api_key="sk-test") + + request_body: Final = json.loads(mock_route.calls.last.request.read()) + assert "encoding_format" not in request_body + assert response.data[0]["embedding"] == [0.1, 0.2, 0.3] + + +def test_embedding_openai_forwards_explicit_encoding_format(respx_mock: respx.MockRouter) -> None: + mock_route: Final = _mock_openai_embedding_route(respx_mock) + + litellm.embedding( + model="openai/text-embedding-3-small", input=["hello"], api_key="sk-test", encoding_format="base64" + ) + + request_body: Final = json.loads(mock_route.calls.last.request.read()) + assert request_body["encoding_format"] == "base64" + + +def test_embedding_openai_explicit_encoding_format_wins_over_env_var( + respx_mock: respx.MockRouter, monkeypatch: pytest.MonkeyPatch +) -> None: + monkeypatch.setenv("LITELLM_DEFAULT_EMBEDDING_ENCODING_FORMAT", "float") + mock_route: Final = _mock_openai_embedding_route(respx_mock) + + litellm.embedding( + model="openai/text-embedding-3-small", input=["hello"], api_key="sk-test", encoding_format="base64" + ) + + request_body: Final = json.loads(mock_route.calls.last.request.read()) + assert request_body["encoding_format"] == "base64" + + +@pytest.mark.parametrize("env_value", ["float", "base64"]) +def test_embedding_openai_env_var_sets_default_encoding_format( + respx_mock: respx.MockRouter, monkeypatch: pytest.MonkeyPatch, env_value: str +) -> None: + monkeypatch.setenv("LITELLM_DEFAULT_EMBEDDING_ENCODING_FORMAT", env_value) + mock_route: Final = _mock_openai_embedding_route(respx_mock) + + litellm.embedding(model="openai/text-embedding-3-small", input=["hello"], api_key="sk-test") + + request_body: Final = json.loads(mock_route.calls.last.request.read()) + assert request_body["encoding_format"] == env_value @pytest.mark.parametrize("env_none", ["none", "NONE", " none "]) -def test_openai_embedding_encoding_format_env_none_omits_param( - monkeypatch, env_none -): - """LITELLM_DEFAULT_EMBEDDING_ENCODING_FORMAT=none omits encoding_format (provider default).""" +def test_embedding_openai_env_none_omits_encoding_format( + respx_mock: respx.MockRouter, monkeypatch: pytest.MonkeyPatch, env_none: str +) -> None: monkeypatch.setenv("LITELLM_DEFAULT_EMBEDDING_ENCODING_FORMAT", env_none) + mock_route: Final = _mock_openai_embedding_route(respx_mock) - mock_response = MagicMock() - mock_response.parse.return_value = MagicMock( - model_dump=lambda: { - "data": [{"embedding": [0.1, 0.2, 0.3], "index": 0}], - "model": "text-embedding-ada-002", - "object": "list", - "usage": {"prompt_tokens": 1, "total_tokens": 1}, - } + litellm.embedding(model="openai/text-embedding-3-small", input=["hello"], api_key="sk-test") + + request_body: Final = json.loads(mock_route.calls.last.request.read()) + assert "encoding_format" not in request_body + + +@pytest.mark.asyncio +async def test_aembedding_openai_omits_encoding_format_when_client_omits_it( + respx_mock: respx.MockRouter, monkeypatch: pytest.MonkeyPatch +) -> None: + monkeypatch.setattr(litellm, "disable_aiohttp_transport", True) + mock_route: Final = _mock_openai_embedding_route(respx_mock) + + response: Final = await litellm.aembedding(model="openai/text-embedding-3-small", input=["hello"], api_key="sk-test") + + request_body: Final = json.loads(mock_route.calls.last.request.read()) + assert "encoding_format" not in request_body + assert response.data[0]["embedding"] == [0.1, 0.2, 0.3] + + +def test_embedding_openai_omitted_encoding_format_maps_provider_errors( + respx_mock: respx.MockRouter, monkeypatch: pytest.MonkeyPatch +) -> None: + respx_mock.post("https://api.openai.com/v1/embeddings").mock( + return_value=httpx.Response( + 429, + headers={"retry-after": "42", "x-should-retry": "false"}, + json={"error": {"message": "rate limited", "type": "rate_limit_error"}}, + ) ) - mock_response.headers = {} - with patch( - "litellm.llms.openai.openai.OpenAIChatCompletion._get_openai_client" - ) as mock_get_client: - mock_client_instance = MagicMock() - mock_get_client.return_value = mock_client_instance - mock_client_instance.embeddings.with_raw_response.create.return_value = ( - mock_response + with pytest.raises(litellm.RateLimitError) as exc_info: + litellm.embedding( + model="openai/text-embedding-3-small", input=["hello"], api_key="sk-test", max_retries=0 ) - embedding( - model="text-embedding-ada-002", - input="Hello world", - ) - - call_kwargs = ( - mock_client_instance.embeddings.with_raw_response.create.call_args[1] - ) - assert "encoding_format" not in call_kwargs - - -def test_openai_embedding_encoding_format_explicit_overrides_env(monkeypatch): - """Request `encoding_format` wins over LITELLM_DEFAULT_EMBEDDING_ENCODING_FORMAT.""" - monkeypatch.setenv("LITELLM_DEFAULT_EMBEDDING_ENCODING_FORMAT", "float") - - mock_response = MagicMock() - mock_response.parse.return_value = MagicMock( - model_dump=lambda: { - "data": [{"embedding": [0.1, 0.2, 0.3], "index": 0}], - "model": "text-embedding-ada-002", - "object": "list", - "usage": {"prompt_tokens": 1, "total_tokens": 1}, - } - ) - mock_response.headers = {} - - with patch( - "litellm.llms.openai.openai.OpenAIChatCompletion._get_openai_client" - ) as mock_get_client: - mock_client_instance = MagicMock() - mock_get_client.return_value = mock_client_instance - mock_client_instance.embeddings.with_raw_response.create.return_value = ( - mock_response - ) - - embedding( - model="text-embedding-ada-002", - input="Hello world", - encoding_format="base64", - ) - - call_kwargs = ( - mock_client_instance.embeddings.with_raw_response.create.call_args[1] - ) - assert call_kwargs["encoding_format"] == "base64" + assert int(exc_info.value.litellm_response_headers["retry-after"]) == 42 diff --git a/tests/test_litellm/test_video_generation.py b/tests/test_litellm/test_video_generation.py index b166e902d6e..2a60ff9c4b5 100644 --- a/tests/test_litellm/test_video_generation.py +++ b/tests/test_litellm/test_video_generation.py @@ -532,6 +532,41 @@ class TestVideoGeneration: assert abs(cost_for("runwayml/seedance2_5", "480p", 8.0) - 1.6) < 0.001 assert abs(cost_for("runwayml/gen4.5", None, 8.0) - 0.96) < 0.001 + def test_completion_cost_veo_31_tiers_pin_published_rates(self, monkeypatch): + """The gemini and vertex_ai veo 3.1 entries bill Google's published per-second tier rates.""" + from litellm.cost_calculator import completion_cost + + local_map_path = os.path.join( + os.path.dirname(__file__), "..", "..", "model_prices_and_context_window.json" + ) + with open(local_map_path, "r") as f: + monkeypatch.setattr(litellm, "model_cost", json.load(f)) + + def cost_for(model: str, provider: str, resolution: str | None, duration: float) -> float: + mock_response = MagicMock() + mock_response.usage = { + "duration_seconds": duration, + **({"video_resolution": resolution} if resolution else {}), + } + type(mock_response)._hidden_params = {} + return completion_cost( + completion_response=mock_response, + model=model, + call_type="create_video", + custom_llm_provider=provider, + ) + + for provider in ("gemini", "vertex_ai"): + for suffix in ("generate-preview", "generate-001"): + standard = f"{provider}/veo-3.1-{suffix}" + fast = f"{provider}/veo-3.1-fast-{suffix}" + assert abs(cost_for(standard, provider, None, 8.0) - 3.2) < 1e-6 + assert abs(cost_for(standard, provider, "1080p", 8.0) - 3.2) < 1e-6 + assert abs(cost_for(standard, provider, "4k", 8.0) - 4.8) < 1e-6 + assert abs(cost_for(fast, provider, "720p", 8.0) - 0.8) < 1e-6 + assert abs(cost_for(fast, provider, "1080p", 8.0) - 0.96) < 1e-6 + assert abs(cost_for(fast, provider, "4k", 8.0) - 2.4) < 1e-6 + def test_video_generation_with_files(self): """Test video generation with file uploads.""" config = OpenAIVideoConfig() diff --git a/type-discipline-budget.json b/type-discipline-budget.json index 6eb7e115586..83c49afb538 100644 --- a/type-discipline-budget.json +++ b/type-discipline-budget.json @@ -1,9 +1,9 @@ { "LIT001": { - "limit": 22519 + "limit": 22403 }, "LIT002": { - "limit": 26818 + "limit": 26780 }, "LIT003": { "limit": 269 @@ -27,10 +27,10 @@ "limit": 0 }, "LIT010": { - "limit": 16544 + "limit": 16512 }, "LIT011": { - "limit": 5575 + "limit": 5537 }, "LIT012": { "limit": 4495 diff --git a/ui/litellm-dashboard/eslint-budgets.json b/ui/litellm-dashboard/eslint-budgets.json index bbf69c4a77a..e8207d179bd 100644 --- a/ui/litellm-dashboard/eslint-budgets.json +++ b/ui/litellm-dashboard/eslint-budgets.json @@ -4,5 +4,8 @@ "complexity": { "max": 140, "target": 80 }, "max-depth": { "max": 70, "target": 30 }, "local/no-large-inline-object-arg": { "max": 559, "target": 300 }, - "local/no-long-condition-chain": { "max": 265, "target": 120 } + "local/no-long-condition-chain": { "max": 265, "target": 120 }, + "testing-library/no-container": { "max": 133, "target": 50 }, + "testing-library/no-node-access": { "max": 716, "target": 500 }, + "testing-library/prefer-screen-queries": { "max": 18, "target": 18 } } diff --git a/ui/litellm-dashboard/eslint.config.mjs b/ui/litellm-dashboard/eslint.config.mjs index 23cc5096bb1..f5e3b23b3ec 100644 --- a/ui/litellm-dashboard/eslint.config.mjs +++ b/ui/litellm-dashboard/eslint.config.mjs @@ -104,10 +104,13 @@ const eslintConfig = [ plugins: { "testing-library": testingLibrary, "jest-dom": jestDom }, rules: { "testing-library/await-async-queries": "error", + "testing-library/no-container": "warn", + "testing-library/no-node-access": "warn", "testing-library/no-wait-for-multiple-assertions": "error", "testing-library/no-wait-for-side-effects": "error", "testing-library/prefer-find-by": "error", "testing-library/prefer-presence-queries": "error", + "testing-library/prefer-screen-queries": "warn", "jest-dom/prefer-checked": "error", "jest-dom/prefer-empty": "error", "jest-dom/prefer-enabled-disabled": "error", diff --git a/ui/litellm-dashboard/src/app/(dashboard)/api-reference/_components/APIReferenceView.test.tsx b/ui/litellm-dashboard/src/app/(dashboard)/api-reference/_components/APIReferenceView.test.tsx index b2e0a42eecb..dae19032e20 100644 --- a/ui/litellm-dashboard/src/app/(dashboard)/api-reference/_components/APIReferenceView.test.tsx +++ b/ui/litellm-dashboard/src/app/(dashboard)/api-reference/_components/APIReferenceView.test.tsx @@ -13,17 +13,17 @@ describe("APIReferenceView", () => { it("uses the API doc base url when provided", () => { const apiDocUrl = "https://docs.litellm.test"; - const { getAllByTestId } = render(); + render(); - const codeBlocks = getAllByTestId(codeBlockTestId); + const codeBlocks = screen.getAllByTestId(codeBlockTestId); expect(codeBlocks[0]).toHaveTextContent(new RegExp(apiDocUrl)); }); it("falls back to the proxy base url when the docs url is missing", () => { const proxyUrl = "https://proxy.litellm.test"; - const { getAllByTestId } = render(); + render(); - const codeBlocks = getAllByTestId(codeBlockTestId); + const codeBlocks = screen.getAllByTestId(codeBlockTestId); expect(codeBlocks[0]).toHaveTextContent(new RegExp(proxyUrl)); }); @@ -31,7 +31,7 @@ describe("APIReferenceView", () => { const apiDocUrl = "https://docs-preferred.litellm.test"; const proxyUrl = "https://proxy-backup.litellm.test"; - const { getAllByTestId } = render( + render( { />, ); - const codeBlocks = getAllByTestId(codeBlockTestId); + const codeBlocks = screen.getAllByTestId(codeBlockTestId); const renderedCode = codeBlocks[0].textContent ?? ""; expect(renderedCode).toContain(apiDocUrl); expect(renderedCode).not.toContain(proxyUrl); diff --git a/ui/litellm-dashboard/src/app/(dashboard)/caching/_components/cache_settings/RedisTypeSelector.test.tsx b/ui/litellm-dashboard/src/app/(dashboard)/caching/_components/cache_settings/RedisTypeSelector.test.tsx index 9d4d5a6d425..372f27e2be1 100644 --- a/ui/litellm-dashboard/src/app/(dashboard)/caching/_components/cache_settings/RedisTypeSelector.test.tsx +++ b/ui/litellm-dashboard/src/app/(dashboard)/caching/_components/cache_settings/RedisTypeSelector.test.tsx @@ -1,12 +1,10 @@ import { describe, expect, it } from "vitest"; import RedisTypeSelector from "./RedisTypeSelector"; -import { render } from "@testing-library/react"; +import { render, screen } from "@testing-library/react"; describe("RedisTypeSelector", () => { it("should render the component", () => { - const { getAllByText } = render( - {}} />, - ); - expect(getAllByText(/Redis/i).length).toBeGreaterThan(0); + render( {}} />); + expect(screen.getAllByText(/Redis/i).length).toBeGreaterThan(0); }); }); diff --git a/ui/litellm-dashboard/src/app/(dashboard)/cost-optimization/_components/CacheLeakageCard.test.tsx b/ui/litellm-dashboard/src/app/(dashboard)/cost-optimization/_components/CacheLeakageCard.test.tsx index 8c36b934789..f320d8e0f97 100644 --- a/ui/litellm-dashboard/src/app/(dashboard)/cost-optimization/_components/CacheLeakageCard.test.tsx +++ b/ui/litellm-dashboard/src/app/(dashboard)/cost-optimization/_components/CacheLeakageCard.test.tsx @@ -1,4 +1,4 @@ -import { fireEvent, render } from "@testing-library/react"; +import { fireEvent, render, screen } from "@testing-library/react"; import { describe, expect, it, vi } from "vitest"; import type { DailyData, KeyMetricWithMetadata, SpendMetrics } from "@/components/UsagePage/types"; @@ -79,25 +79,25 @@ const renderWith = (results: DailyData[], overrides: Partial describe("CacheLeakageCard", () => { it("ranks leaking keys by uncached prompt tokens and shows cache hit ratio", () => { - const { getByText, getByLabelText } = renderWith([ + renderWith([ dayWithKeys("2026-07-12", { "hash-caching": key("caching-key", { prompt_tokens: 1000, cache_read_input_tokens: 900 }), "hash-leaky": key("leaky-key", { prompt_tokens: 10000, cache_read_input_tokens: 0 }), }), ]); - expect(getByText("leaky-key")).toBeInTheDocument(); - expect(getByText("0.0%")).toBeInTheDocument(); - expect(getByText("90.0%")).toBeInTheDocument(); + expect(screen.getByText("leaky-key")).toBeInTheDocument(); + expect(screen.getByText("0.0%")).toBeInTheDocument(); + expect(screen.getByText("90.0%")).toBeInTheDocument(); [ "Input tokens you sent in this range that weren't served from or written to the cache", "Share of your input tokens that were served from the cache", "About how much you'd save if this uncached input used prompt caching. Estimated as uncached input tokens times what your cached traffic already nets per cached token (realized cache savings, after write premiums, ÷ cache read and write tokens). Blank when caching is not currently saving anything overall.", - ].forEach((info) => expect(getByLabelText(info)).toBeInTheDocument()); + ].forEach((info) => expect(screen.getByLabelText(info)).toBeInTheDocument()); }); it("sorts by the clicked column, worst cache hit rate first", () => { - const { getAllByRole, getByText } = renderWith([ + renderWith([ dayWithKeys("2026-07-12", { "hash-a": key("alpha", { prompt_tokens: 10000, @@ -111,48 +111,48 @@ describe("CacheLeakageCard", () => { }), }), ]); - const firstDataRow = () => getAllByRole("row")[1]; + const firstDataRow = () => screen.getAllByRole("row")[1]; expect(firstDataRow()).toHaveTextContent("alpha"); - fireEvent.click(getByText("Cache hit rate")); + fireEvent.click(screen.getByText("Cache hit rate")); expect(firstDataRow()).toHaveTextContent("bravo"); - fireEvent.click(getByText("Cache hit rate")); + fireEvent.click(screen.getByText("Cache hit rate")); expect(firstDataRow()).toHaveTextContent("alpha"); }); it("switches to the model view and lists only Anthropic models", () => { - const { getByText, queryByText } = renderWith([ + renderWith([ dayWithModels("2026-07-12", { "claude-sonnet-5": { prompt_tokens: 5000, cache_read_input_tokens: 0 }, "gpt-4o": { prompt_tokens: 8000, cache_read_input_tokens: 0 }, }), ]); - fireEvent.click(getByText("By model")); + fireEvent.click(screen.getByText("By model")); - expect(getByText("Cache leakage by model")).toBeInTheDocument(); - expect(getByText("claude-sonnet-5")).toBeInTheDocument(); - expect(queryByText("gpt-4o")).not.toBeInTheDocument(); + expect(screen.getByText("Cache leakage by model")).toBeInTheDocument(); + expect(screen.getByText("claude-sonnet-5")).toBeInTheDocument(); + expect(screen.queryByText("gpt-4o")).not.toBeInTheDocument(); }); it("shows an empty state when no key used tokens in the range", () => { - const { getByText, queryByRole } = renderWith([dayWithKeys("2026-07-12", {})]); + renderWith([dayWithKeys("2026-07-12", {})]); - expect(getByText("No key usage in this range.")).toBeInTheDocument(); - expect(queryByRole("table")).not.toBeInTheDocument(); + expect(screen.getByText("No key usage in this range.")).toBeInTheDocument(); + expect(screen.queryByRole("table")).not.toBeInTheDocument(); }); it("tells the user the table is still filling in while fallback pages stream", () => { const day = dayWithKeys("2026-07-12", { "hash-leaky": key("leaky-key", { prompt_tokens: 10000, cache_read_input_tokens: 0 }), }); - const { getByText, getByRole } = renderWith([day], { isFetchingMore: true }); + renderWith([day], { isFetchingMore: true }); - expect(getByRole("table")).toBeInTheDocument(); + expect(screen.getByRole("table")).toBeInTheDocument(); expect( - getByText("Data is still loading; rows and totals will update as the rest of the range arrives."), + screen.getByText("Data is still loading; rows and totals will update as the rest of the range arrives."), ).toBeInTheDocument(); }); @@ -160,10 +160,10 @@ describe("CacheLeakageCard", () => { const day = dayWithKeys("2026-07-12", { "hash-leaky": key("leaky-key", { prompt_tokens: 10000, cache_read_input_tokens: 0 }), }); - const { queryByText } = renderWith([day], { loading: true }); + renderWith([day], { loading: true }); expect( - queryByText("Data is still loading; rows and totals will update as the rest of the range arrives."), + screen.queryByText("Data is still loading; rows and totals will update as the rest of the range arrives."), ).not.toBeInTheDocument(); }); @@ -171,10 +171,10 @@ describe("CacheLeakageCard", () => { const day = dayWithKeys("2026-07-12", { "hash-leaky": key("leaky-key", { prompt_tokens: 10000, cache_read_input_tokens: 0 }), }); - const { queryByText } = renderWith([day]); + renderWith([day]); expect( - queryByText("Data is still loading; rows and totals will update as the rest of the range arrives."), + screen.queryByText("Data is still loading; rows and totals will update as the rest of the range arrives."), ).not.toBeInTheDocument(); }); }); diff --git a/ui/litellm-dashboard/src/app/(dashboard)/cost-optimization/_components/CostOptimizationView.activity.test.tsx b/ui/litellm-dashboard/src/app/(dashboard)/cost-optimization/_components/CostOptimizationView.activity.test.tsx index 1cc7bec13d1..03250e3e53b 100644 --- a/ui/litellm-dashboard/src/app/(dashboard)/cost-optimization/_components/CostOptimizationView.activity.test.tsx +++ b/ui/litellm-dashboard/src/app/(dashboard)/cost-optimization/_components/CostOptimizationView.activity.test.tsx @@ -1,5 +1,5 @@ import React from "react"; -import { fireEvent, render, waitFor } from "@testing-library/react"; +import { fireEvent, render, waitFor, screen } from "@testing-library/react"; import { describe, expect, it, vi } from "vitest"; import { QueryClient, QueryClientProvider } from "@tanstack/react-query"; @@ -56,7 +56,7 @@ describe("CostOptimizationView daily activity", () => { useAuthorizedMock.mockReturnValue({ accessToken: "test-token", userId: "u1", userRole: "proxy_admin" }); const queryClient = new QueryClient({ defaultOptions: { queries: { retry: false } } }); - const { getByRole, getByTestId, findByTestId, queryByText } = render( + render( , @@ -64,12 +64,12 @@ describe("CostOptimizationView daily activity", () => { await waitFor(() => expect(mockUserDailyActivityAggregatedCall).toHaveBeenCalledTimes(1)); - fireEvent.click(getByRole("tab", { name: "Prompt Caching" })); - await findByTestId("caching-settings"); + fireEvent.click(screen.getByRole("tab", { name: "Prompt Caching" })); + await screen.findByTestId("caching-settings"); expect(mockUserDailyActivityAggregatedCall).toHaveBeenCalledTimes(1); expect(mockUserDailyActivityCall).not.toHaveBeenCalled(); - expect(queryByText(/Currently fetching spend data/)).not.toBeInTheDocument(); + expect(screen.queryByText(/Currently fetching spend data/)).not.toBeInTheDocument(); }); it("shows the fetch-progress banner while the paginated fallback streams pages in", async () => { @@ -84,13 +84,13 @@ describe("CostOptimizationView daily activity", () => { useAuthorizedMock.mockReturnValue({ accessToken: "test-token", userId: "u1", userRole: "proxy_admin" }); const queryClient = new QueryClient({ defaultOptions: { queries: { retry: false } } }); - const { findByText, getByRole } = render( + render( , ); - expect(await findByText(/Currently fetching spend data: fetched 1 \/ 3 pages/)).toBeInTheDocument(); - expect(getByRole("button", { name: "Stop" })).toBeInTheDocument(); + expect(await screen.findByText(/Currently fetching spend data: fetched 1 \/ 3 pages/)).toBeInTheDocument(); + expect(screen.getByRole("button", { name: "Stop" })).toBeInTheDocument(); }); }); diff --git a/ui/litellm-dashboard/src/app/(dashboard)/cost-optimization/_components/CostOptimizationView.test.tsx b/ui/litellm-dashboard/src/app/(dashboard)/cost-optimization/_components/CostOptimizationView.test.tsx index d5df5aa75da..028367555a1 100644 --- a/ui/litellm-dashboard/src/app/(dashboard)/cost-optimization/_components/CostOptimizationView.test.tsx +++ b/ui/litellm-dashboard/src/app/(dashboard)/cost-optimization/_components/CostOptimizationView.test.tsx @@ -1,5 +1,5 @@ import React from "react"; -import { fireEvent, render } from "@testing-library/react"; +import { fireEvent, render, screen } from "@testing-library/react"; import { beforeEach, describe, expect, it, vi } from "vitest"; import { QueryClient, QueryClientProvider } from "@tanstack/react-query"; @@ -45,32 +45,32 @@ describe("CostOptimizationView", () => { }); it("renders the standard page header with the sidebar's Cost Optimization icon", () => { - const { container, getByRole, getByText } = renderView(); + const { container } = renderView(); - expect(getByRole("heading", { level: 1, name: "Cost Optimization" })).toBeInTheDocument(); - expect(getByText(/Track and configure the mechanisms that save you money/)).toBeInTheDocument(); + expect(screen.getByRole("heading", { level: 1, name: "Cost Optimization" })).toBeInTheDocument(); + expect(screen.getByText(/Track and configure the mechanisms that save you money/)).toBeInTheDocument(); expect(container.querySelector(".lucide-piggy-bank")).not.toBeNull(); }); it("renders the four cost-optimization tabs", () => { - const { getByText } = renderView(); + renderView(); - expect(getByText("Overall")).toBeInTheDocument(); - expect(getByText("Prompt Compression")).toBeInTheDocument(); - expect(getByText("Prompt Caching")).toBeInTheDocument(); - expect(getByText("Auto-Router")).toBeInTheDocument(); + expect(screen.getByText("Overall")).toBeInTheDocument(); + expect(screen.getByText("Prompt Compression")).toBeInTheDocument(); + expect(screen.getByText("Prompt Caching")).toBeInTheDocument(); + expect(screen.getByText("Auto-Router")).toBeInTheDocument(); }); it("defaults to the Overall tab and switches the active tab on click", () => { - const { getByRole } = renderView(); + renderView(); - expect(getByRole("tab", { name: "Overall" })).toHaveAttribute("aria-selected", "true"); - expect(getByRole("tab", { name: "Prompt Compression" })).toHaveAttribute("aria-selected", "false"); + expect(screen.getByRole("tab", { name: "Overall" })).toHaveAttribute("aria-selected", "true"); + expect(screen.getByRole("tab", { name: "Prompt Compression" })).toHaveAttribute("aria-selected", "false"); - fireEvent.click(getByRole("tab", { name: "Prompt Compression" })); + fireEvent.click(screen.getByRole("tab", { name: "Prompt Compression" })); - expect(getByRole("tab", { name: "Overall" })).toHaveAttribute("aria-selected", "false"); - expect(getByRole("tab", { name: "Prompt Compression" })).toHaveAttribute("aria-selected", "true"); + expect(screen.getByRole("tab", { name: "Overall" })).toHaveAttribute("aria-selected", "false"); + expect(screen.getByRole("tab", { name: "Prompt Compression" })).toHaveAttribute("aria-selected", "true"); }); // Unlike the other three pages in this cleanup, Cost Optimization keeps its @@ -80,21 +80,21 @@ describe("CostOptimizationView", () => { // are proxy-admin-only, so those are what disappear. describe("proxy-admin-only tabs", () => { it.each(["Internal User", "Internal Viewer", "Org Admin"])("shows %s the Overall tab only", (userRole) => { - const { getByRole, queryByRole } = renderView(userRole); + renderView(userRole); - expect(getByRole("tab", { name: "Overall" })).toBeInTheDocument(); - expect(queryByRole("tab", { name: "Prompt Compression" })).not.toBeInTheDocument(); - expect(queryByRole("tab", { name: "Prompt Caching" })).not.toBeInTheDocument(); - expect(queryByRole("tab", { name: "Auto-Router" })).not.toBeInTheDocument(); + expect(screen.getByRole("tab", { name: "Overall" })).toBeInTheDocument(); + expect(screen.queryByRole("tab", { name: "Prompt Compression" })).not.toBeInTheDocument(); + expect(screen.queryByRole("tab", { name: "Prompt Caching" })).not.toBeInTheDocument(); + expect(screen.queryByRole("tab", { name: "Auto-Router" })).not.toBeInTheDocument(); }); it("never mounts the panels behind the admin-only endpoints for an internal user", () => { - const { getByTestId, queryByTestId } = renderView("Internal User"); + renderView("Internal User"); - expect(getByTestId("usage-tab")).toBeInTheDocument(); - expect(queryByTestId("compression-tab")).not.toBeInTheDocument(); - expect(queryByTestId("caching-tab")).not.toBeInTheDocument(); - expect(queryByTestId("autorouter-benchmarks-tab")).not.toBeInTheDocument(); + expect(screen.getByTestId("usage-tab")).toBeInTheDocument(); + expect(screen.queryByTestId("compression-tab")).not.toBeInTheDocument(); + expect(screen.queryByTestId("caching-tab")).not.toBeInTheDocument(); + expect(screen.queryByTestId("autorouter-benchmarks-tab")).not.toBeInTheDocument(); }); }); }); diff --git a/ui/litellm-dashboard/src/app/(dashboard)/cost-optimization/_components/PromptCachingTab.test.tsx b/ui/litellm-dashboard/src/app/(dashboard)/cost-optimization/_components/PromptCachingTab.test.tsx index 38517dab0ab..2c602033171 100644 --- a/ui/litellm-dashboard/src/app/(dashboard)/cost-optimization/_components/PromptCachingTab.test.tsx +++ b/ui/litellm-dashboard/src/app/(dashboard)/cost-optimization/_components/PromptCachingTab.test.tsx @@ -1,4 +1,4 @@ -import { render, waitFor } from "@testing-library/react"; +import { render, waitFor, screen } from "@testing-library/react"; import { describe, expect, it, vi } from "vitest"; const mockGetGeneralSettingsCall = vi.fn(); @@ -37,10 +37,10 @@ describe("PromptCachingTab", () => { cancelled: false, cancel: vi.fn(), }; - const { getByTestId } = render(); + render(); - expect(getByTestId("caching-settings")).toBeInTheDocument(); - expect(getByTestId("cache-leakage-card")).toBeInTheDocument(); + expect(screen.getByTestId("caching-settings")).toBeInTheDocument(); + expect(screen.getByTestId("cache-leakage-card")).toBeInTheDocument(); await waitFor(() => expect(mockCacheLeakageCard).toHaveBeenCalledWith(expect.objectContaining({ activity }))); }); }); diff --git a/ui/litellm-dashboard/src/app/(dashboard)/cost-optimization/_components/UsageTab.test.tsx b/ui/litellm-dashboard/src/app/(dashboard)/cost-optimization/_components/UsageTab.test.tsx index df23e5509bf..f85a667a074 100644 --- a/ui/litellm-dashboard/src/app/(dashboard)/cost-optimization/_components/UsageTab.test.tsx +++ b/ui/litellm-dashboard/src/app/(dashboard)/cost-optimization/_components/UsageTab.test.tsx @@ -1,4 +1,4 @@ -import { render } from "@testing-library/react"; +import { render, screen } from "@testing-library/react"; import userEvent from "@testing-library/user-event"; import { beforeEach, describe, expect, it, vi } from "vitest"; import type { ToolSpendResponse } from "@/components/networking"; @@ -152,13 +152,13 @@ describe("UsageTab", () => { gateway_injected_caching_savings_spend: 0.006, compression_saved_tokens: 100000, }; - const { getByText } = renderWith([day("2026-07-12", firstDay), day("2026-07-13", secondDay)]); + renderWith([day("2026-07-12", firstDay), day("2026-07-13", secondDay)]); - expect(getByText("$0.1500")).toBeInTheDocument(); - expect(getByText("$0.1400")).toBeInTheDocument(); - expect(getByText("$0.0100")).toBeInTheDocument(); - expect(getByText("$0.0160")).toBeInTheDocument(); - expect(getByText("140,000 tokens compressed")).toBeInTheDocument(); + expect(screen.getByText("$0.1500")).toBeInTheDocument(); + expect(screen.getByText("$0.1400")).toBeInTheDocument(); + expect(screen.getByText("$0.0100")).toBeInTheDocument(); + expect(screen.getByText("$0.0160")).toBeInTheDocument(); + expect(screen.getByText("140,000 tokens compressed")).toBeInTheDocument(); }); const twoDays = () => [ @@ -167,11 +167,11 @@ describe("UsageTab", () => { ]; it("opens on a running total anchored at $0 at the start of the range", () => { - const { getByTestId } = renderWith(twoDays()); + renderWith(twoDays()); // Cumulative prepends a synthetic $0 point at the range start (Jul 1) so the // line rises from zero rather than floating; the daily running totals follow. - const series = readSeries(getByTestId("area-chart")); + const series = readSeries(screen.getByTestId("area-chart")); expect(series).toHaveLength(3); expect(series[0]).toMatchObject({ date: "Jul 1", Compression: 0, "Prompt caching": 0 }); expect(series[1]).toMatchObject({ Compression: 0.04, "Prompt caching": 0.006 }); @@ -183,12 +183,12 @@ describe("UsageTab", () => { // The original complaint: a one-day range plotted a single floating dot. The // synthetic start anchor gives the line a zero origin to climb from. const oneDay = new Date(2026, 6, 24); - const { getByTestId } = renderWith( - [day("2026-07-24", { compression_savings_spend: 0.2, gateway_injected_caching_savings_spend: 0.05 })], - { from: oneDay, to: oneDay }, - ); + renderWith([day("2026-07-24", { compression_savings_spend: 0.2, gateway_injected_caching_savings_spend: 0.05 })], { + from: oneDay, + to: oneDay, + }); - const series = readSeries(getByTestId("area-chart")); + const series = readSeries(screen.getByTestId("area-chart")); expect(series).toHaveLength(2); expect(series[0]).toMatchObject({ date: "Jul 24", Compression: 0, "Prompt caching": 0 }); expect(series[1]).toMatchObject({ date: "Jul 24", Compression: 0.2, "Prompt caching": 0.05 }); @@ -202,49 +202,49 @@ describe("UsageTab", () => { day("2026-07-13", { gateway_injected_caching_savings_spend: 0.1 }), day("2026-07-12", { gateway_injected_caching_savings_spend: 0.04 }), ]; - const { getByTestId, getByRole } = renderWith(newestFirst); + renderWith(newestFirst); // The $0 anchor leads, then the days climb oldest to newest. - const cumulative = readSeries(getByTestId("area-chart")); + const cumulative = readSeries(screen.getByTestId("area-chart")); expect(cumulative.map((p: { date: string }) => p.date)).toEqual(["Jul 1", "Jul 12", "Jul 13"]); expect(cumulative[1]["Prompt caching"]).toBeCloseTo(0.04, 5); expect(cumulative[2]["Prompt caching"]).toBeCloseTo(0.14, 5); expect(cumulative[2]["Prompt caching"]).toBeGreaterThan(cumulative[1]["Prompt caching"]); - await userEvent.click(getByRole("tab", { name: "Per day" })); - const perDay = readSeries(getByTestId("bar-chart")); + await userEvent.click(screen.getByRole("tab", { name: "Per day" })); + const perDay = readSeries(screen.getByTestId("bar-chart")); expect(perDay.map((p: { date: string }) => p.date)).toEqual(["Jul 12", "Jul 13"]); }); it("draws bars of the raw per-interval readings on the other tab", async () => { - const { getByRole, getByTestId, queryByTestId } = renderWith(twoDays()); + renderWith(twoDays()); // Cumulative opens on the area line. - expect(getByTestId("area-chart")).toBeInTheDocument(); + expect(screen.getByTestId("area-chart")).toBeInTheDocument(); - await userEvent.click(getByRole("tab", { name: "Per day" })); + await userEvent.click(screen.getByRole("tab", { name: "Per day" })); // Per day switches to a bar chart of the unaccumulated daily savings, with no // synthetic anchor prepended. - expect(queryByTestId("area-chart")).not.toBeInTheDocument(); - const series = readSeries(getByTestId("bar-chart")); + expect(screen.queryByTestId("area-chart")).not.toBeInTheDocument(); + const series = readSeries(screen.getByTestId("bar-chart")); expect(series).toHaveLength(2); expect(series[0]).toMatchObject({ Compression: 0.04, "Prompt caching": 0.006 }); expect(series[1]).toMatchObject({ Compression: 0.1, "Prompt caching": 0.01 }); }); it("says what the line means and over what range", async () => { - const { getByText, getByRole } = renderWith(twoDays()); + renderWith(twoDays()); - expect(getByText("Running total saved · Jul 1 – Jul 14 (UTC)")).toBeInTheDocument(); - await userEvent.click(getByRole("tab", { name: "Per day" })); - expect(getByText("Saved per day · Jul 1 – Jul 14 (UTC)")).toBeInTheDocument(); + expect(screen.getByText("Running total saved · Jul 1 – Jul 14 (UTC)")).toBeInTheDocument(); + await userEvent.click(screen.getByRole("tab", { name: "Per day" })); + expect(screen.getByText("Saved per day · Jul 1 – Jul 14 (UTC)")).toBeInTheDocument(); }); it("builds the per-driver donut from the range totals, not the running total", () => { - const { getByTestId } = renderWith(twoDays()); + renderWith(twoDays()); - const slices = JSON.parse(getByTestId("donut-chart").getAttribute("data-slices") ?? "[]"); + const slices = JSON.parse(screen.getByTestId("donut-chart").getAttribute("data-slices") ?? "[]"); expect(slices).toEqual([ { driver: "Compression", color: "emerald", usd: expect.closeTo(0.14, 5) }, { driver: "Prompt caching", color: "blue", usd: expect.closeTo(0.016, 5) }, @@ -252,9 +252,9 @@ describe("UsageTab", () => { }); it("omits a driver slice when that driver has no savings", () => { - const { getByTestId } = renderWith([day("2026-07-12", { compression_savings_spend: 0.04 })]); + renderWith([day("2026-07-12", { compression_savings_spend: 0.04 })]); - const slices = JSON.parse(getByTestId("donut-chart").getAttribute("data-slices") ?? "[]"); + const slices = JSON.parse(screen.getByTestId("donut-chart").getAttribute("data-slices") ?? "[]"); expect(slices).toEqual([{ driver: "Compression", color: "emerald", usd: expect.closeTo(0.04, 5) }]); }); @@ -262,7 +262,7 @@ describe("UsageTab", () => { // Stacking sums the series into one bar. Auto-router savings go negative when a // model switch pays for a cold cache, and that segment would be drawn below the // axis while the rest of the bar still read as the day's total. - const { getByRole, getByTestId } = renderWith([ + renderWith([ day("2026-07-12", { compression_savings_spend: 0.1, gateway_injected_caching_savings_spend: 0.02, @@ -270,8 +270,8 @@ describe("UsageTab", () => { }), ]); - await userEvent.click(getByRole("tab", { name: "Per day" })); - const bars = getByTestId("bar-chart"); + await userEvent.click(screen.getByRole("tab", { name: "Per day" })); + const bars = screen.getByTestId("bar-chart"); expect(bars).toHaveAttribute("data-stack", "false"); expect(readSeries(bars)[0]).toMatchObject({ "Auto-router": -0.05 }); }); @@ -281,10 +281,10 @@ describe("UsageTab", () => { // per day"). Hand-rolled rows made it compete with the legend and the toggle for // width, so the header grew a line on one tab and the chart moved with it. CardHeader // sizes the action column to its content and gives the rest to the title column. - const { getByRole, getByTestId, container } = renderWith(twoDays()); + const { container } = renderWith(twoDays()); const header = () => { - const legend = getByTestId("chart-legend"); + const legend = screen.getByTestId("chart-legend"); const action = legend.closest('[data-slot="card-action"]') as HTMLElement; const cardHeader = action.parentElement as HTMLElement; const description = cardHeader.querySelector('[data-slot="card-description"]') as HTMLElement; @@ -295,12 +295,12 @@ describe("UsageTab", () => { expect(before.action).toBeTruthy(); expect(before.description).toBeTruthy(); // the toggle rides in the same action slot as the legend, so neither moves alone - expect(before.action.contains(getByRole("tablist"))).toBe(true); + expect(before.action.contains(screen.getByRole("tablist"))).toBe(true); // the subtitle lives outside that slot, so its length cannot reposition the controls expect(before.action.contains(before.description)).toBe(false); expect(before.description).toHaveTextContent(/Running total saved/); - await userEvent.click(getByRole("tab", { name: "Per day" })); + await userEvent.click(screen.getByRole("tab", { name: "Per day" })); const after = header(); expect(after.action).toBe(before.action); @@ -314,7 +314,7 @@ describe("UsageTab", () => { // Switching models leaves the new one with a cold cache, so a route can cost more // than the baseline would have. A negative slice is meaningless in a donut, but the // total has to keep the loss or the page can only ever report good news. - const { getByText, getByTestId } = renderWith([ + renderWith([ day("2026-07-12", { compression_savings_spend: 0.1, gateway_injected_caching_savings_spend: 0.02, @@ -322,16 +322,16 @@ describe("UsageTab", () => { }), ]); - expect(getByText("$0.0700")).toBeInTheDocument(); - expect(getByText("-$0.0500")).toBeInTheDocument(); + expect(screen.getByText("$0.0700")).toBeInTheDocument(); + expect(screen.getByText("-$0.0500")).toBeInTheDocument(); - const slices = JSON.parse(getByTestId("donut-chart").getAttribute("data-slices") ?? "[]"); + const slices = JSON.parse(screen.getByTestId("donut-chart").getAttribute("data-slices") ?? "[]"); expect(slices.map((d: { driver: string }) => d.driver)).toEqual(["Compression", "Prompt caching"]); - expect(getByTestId("donut-chart")).toHaveAttribute("data-label", "$0.1200"); + expect(screen.getByTestId("donut-chart")).toHaveAttribute("data-label", "$0.1200"); }); it("carries auto-router savings into the summary card, donut slice, and cumulative series", () => { - const { getByText, getByTestId } = renderWith([ + renderWith([ day("2026-07-12", { compression_savings_spend: 0.04, gateway_injected_caching_savings_spend: 0.006, @@ -345,11 +345,11 @@ describe("UsageTab", () => { ]); // Total saved now sums three drivers, and the auto-router card carries its own total. - expect(getByText("$0.2260")).toBeInTheDocument(); - expect(getByText("$0.0700")).toBeInTheDocument(); + expect(screen.getByText("$0.2260")).toBeInTheDocument(); + expect(screen.getByText("$0.0700")).toBeInTheDocument(); // The driver donut gains a third slice priced from the range totals. - const slices = JSON.parse(getByTestId("donut-chart").getAttribute("data-slices") ?? "[]"); + const slices = JSON.parse(screen.getByTestId("donut-chart").getAttribute("data-slices") ?? "[]"); expect(slices).toEqual([ { driver: "Compression", color: "emerald", usd: expect.closeTo(0.14, 5) }, { driver: "Prompt caching", color: "blue", usd: expect.closeTo(0.016, 5) }, @@ -357,7 +357,7 @@ describe("UsageTab", () => { ]); // And the cumulative line accumulates the auto-router series alongside the others. - const series = readSeries(getByTestId("area-chart")); + const series = readSeries(screen.getByTestId("area-chart")); expect(series[2]["Auto-router"]).toBeCloseTo(0.07, 5); }); @@ -371,9 +371,9 @@ describe("UsageTab", () => { start_date: "2026-07-12", end_date: "2026-07-12", }; - const { findAllByTestId } = renderWith([day("2026-07-12", {})], { toolSpend }); + renderWith([day("2026-07-12", {})], { toolSpend }); - const bars = await findAllByTestId("bar-chart"); + const bars = await screen.findAllByTestId("bar-chart"); const series = JSON.parse(bars[0].getAttribute("data-series") ?? "[]"); expect(series[0]).toMatchObject({ tool_name: "search", spend: 4.0 }); // The 64px bar cap is this card's opt-in; the shared BarChart must not cap @@ -391,14 +391,16 @@ describe("UsageTab", () => { start_date: "2026-07-12", end_date: "2026-07-12", }; - const { findAllByTestId, getAllByTestId } = renderWith([day("2026-07-12", {})], { toolSpend }); + renderWith([day("2026-07-12", {})], { toolSpend }); - const bars = await findAllByTestId("bar-chart"); + const bars = await screen.findAllByTestId("bar-chart"); const [totalByTool, dailyByTool] = bars.slice(-2); expect(dailyByTool).toHaveAttribute("data-show-legend", "false"); expect(totalByTool).toHaveAttribute("data-colors", dailyByTool.getAttribute("data-colors")); - const toolLegends = getAllByTestId("chart-legend").filter((legend) => legend.textContent === "search,read_file"); + const toolLegends = screen + .getAllByTestId("chart-legend") + .filter((legend) => legend.textContent === "search,read_file"); expect(toolLegends).toHaveLength(1); }); @@ -415,23 +417,23 @@ describe("UsageTab", () => { it.each(["Internal User", "Internal Viewer", "Org Admin"])( "hides the card and never calls the endpoint for %s", async (userRole) => { - const { queryByText, getByTestId } = renderWith([day("2026-07-12", { compression_savings_spend: 0.04 })], { + renderWith([day("2026-07-12", { compression_savings_spend: 0.04 })], { toolSpend, userRole, }); // Liveness gate: the daily-activity charts still render for this role, // so the absence below is the gate, not an empty tab. - expect(getByTestId("donut-chart")).toBeInTheDocument(); - expect(queryByText("Spend by tool")).not.toBeInTheDocument(); + expect(screen.getByTestId("donut-chart")).toBeInTheDocument(); + expect(screen.queryByText("Spend by tool")).not.toBeInTheDocument(); await vi.waitFor(() => expect(mockGetToolSpend).not.toHaveBeenCalled()); }, ); it("keeps the card and the endpoint call for an admin", async () => { - const { findByText } = renderWith([day("2026-07-12", { compression_savings_spend: 0.04 })], { toolSpend }); + renderWith([day("2026-07-12", { compression_savings_spend: 0.04 })], { toolSpend }); - expect(await findByText("Spend by tool")).toBeInTheDocument(); + expect(await screen.findByText("Spend by tool")).toBeInTheDocument(); expect(mockGetToolSpend).toHaveBeenCalled(); }); }); diff --git a/ui/litellm-dashboard/src/app/(dashboard)/guardrails/_components/guardrail_info.test.tsx b/ui/litellm-dashboard/src/app/(dashboard)/guardrails/_components/guardrail_info.test.tsx index 2b90a1d8cbc..fcffc2122e7 100644 --- a/ui/litellm-dashboard/src/app/(dashboard)/guardrails/_components/guardrail_info.test.tsx +++ b/ui/litellm-dashboard/src/app/(dashboard)/guardrails/_components/guardrail_info.test.tsx @@ -1,5 +1,5 @@ import * as networking from "@/components/networking"; -import { fireEvent, render, waitFor, within } from "@testing-library/react"; +import { fireEvent, render, waitFor, within, screen } from "@testing-library/react"; import userEvent from "@testing-library/user-event"; import { afterEach, describe, expect, it, vi } from "vitest"; import GuardrailInfoView from "./guardrail_info"; @@ -65,21 +65,19 @@ describe("Guardrail Info", () => { vi.mocked(networking.getGuardrailProviderSpecificParams).mockResolvedValue({}); - const { getAllByText, getByText } = render( - {}} accessToken="123" isAdmin={true} />, - ); + render( {}} accessToken="123" isAdmin={true} />); // Wait for the loading to complete and data to be rendered await waitFor(() => { // The guardrail name appears in multiple places (title and settings tab) - const elements = getAllByText("Test Guardrail"); + const elements = screen.getAllByText("Test Guardrail"); expect(elements.length).toBeGreaterThan(0); }); // Verify other key elements are present - expect(getByText("Back to Guardrails")).toBeInTheDocument(); - expect(getByText("Overview")).toBeInTheDocument(); - expect(getByText("Settings")).toBeInTheDocument(); + expect(screen.getByText("Back to Guardrails")).toBeInTheDocument(); + expect(screen.getByText("Overview")).toBeInTheDocument(); + expect(screen.getByText("Settings")).toBeInTheDocument(); }); it("should render a tag-based mode object rather than crashing the detail view", async () => { @@ -105,11 +103,9 @@ describe("Guardrail Info", () => { vi.mocked(networking.getGuardrailProviderSpecificParams).mockResolvedValue({}); - const { findAllByText } = render( - {}} accessToken="123" isAdmin={true} />, - ); + render( {}} accessToken="123" isAdmin={true} />); - expect(await findAllByText("pre_call, post_call (tag-based)")).not.toHaveLength(0); + expect(await screen.findAllByText("pre_call, post_call (tag-based)")).not.toHaveLength(0); }); it("should render the provider logo from the bundled guardrail logo map", async () => { @@ -135,11 +131,9 @@ describe("Guardrail Info", () => { vi.mocked(networking.getGuardrailProviderSpecificParams).mockResolvedValue({}); - const { findByAltText } = render( - {}} accessToken="123" isAdmin={true} />, - ); + render( {}} accessToken="123" isAdmin={true} />); - const logo = await findByAltText("Presidio PII logo"); + const logo = await screen.findByAltText("Presidio PII logo"); expect(logo).toHaveAttribute("src", expect.stringContaining("microsoft_azure.svg")); }); @@ -167,25 +161,27 @@ describe("Guardrail Info", () => { vi.mocked(networking.getGuardrailProviderSpecificParams).mockResolvedValue({}); - const { getByText, findByText, container } = render( + const { container } = render( {}} accessToken="123" isAdmin={true} />, ); await waitFor(() => { - expect(getByText("Settings")).toBeInTheDocument(); + expect(screen.getByText("Settings")).toBeInTheDocument(); }); // Click the Settings tab - fireEvent.click(getByText("Settings")); + fireEvent.click(screen.getByText("Settings")); // Wait for the Settings panel to render await waitFor(() => { - expect(getByText("Guardrail Settings")).toBeInTheDocument(); + expect(screen.getByText("Guardrail Settings")).toBeInTheDocument(); }); await userEvent.hover(within(container).getByRole("img", { name: "Config guardrail details" })); - expect(await findByText("Guardrail is defined in the config file and cannot be edited.")).toBeInTheDocument(); + expect( + await screen.findByText("Guardrail is defined in the config file and cannot be edited."), + ).toBeInTheDocument(); }); it("should render the guardrail info", async () => { @@ -216,12 +212,10 @@ describe("Guardrail Info", () => { vi.mocked(networking.getGuardrailProviderSpecificParams).mockResolvedValue({}); - const { getByText } = render( - {}} accessToken="123" isAdmin={true} />, - ); + render( {}} accessToken="123" isAdmin={true} />); await waitFor(() => { - expect(getByText("PII Entity Configuration")).toBeInTheDocument(); + expect(screen.getByText("PII Entity Configuration")).toBeInTheDocument(); }); }); it("should handle content filter updates correctly", async () => { @@ -251,30 +245,28 @@ describe("Guardrail Info", () => { vi.mocked(networking.getGuardrailProviderSpecificParams).mockResolvedValue({}); vi.mocked(networking.updateGuardrailCall).mockResolvedValue({ status: "success" }); - const { getByText, getByLabelText } = render( - {}} accessToken="123" isAdmin={true} />, - ); + render( {}} accessToken="123" isAdmin={true} />); await waitFor(() => { - expect(getByText("Settings")).toBeInTheDocument(); + expect(screen.getByText("Settings")).toBeInTheDocument(); }); // Go to Settings tab - fireEvent.click(getByText("Settings")); + fireEvent.click(screen.getByText("Settings")); await waitFor(() => { - expect(getByText("Guardrail Settings")).toBeInTheDocument(); + expect(screen.getByText("Guardrail Settings")).toBeInTheDocument(); }); // Enter Edit Mode - fireEvent.click(getByText("Edit Settings")); + fireEvent.click(screen.getByText("Edit Settings")); // Modify Guardrail Name to force an update - const nameInput = getByLabelText("Guardrail Name"); + const nameInput = screen.getByLabelText("Guardrail Name"); fireEvent.change(nameInput, { target: { value: "Updated Name" } }); // Save with only name change - const saveButton = getByText("Save Changes"); + const saveButton = screen.getByText("Save Changes"); fireEvent.click(saveButton); await waitFor(() => { @@ -300,16 +292,16 @@ describe("Guardrail Info", () => { // Enter Edit Mode again to make changes await waitFor(() => { - expect(getByText("Edit Settings")).toBeInTheDocument(); + expect(screen.getByText("Edit Settings")).toBeInTheDocument(); }); - fireEvent.click(getByText("Edit Settings")); + fireEvent.click(screen.getByText("Edit Settings")); // Now modify the values using the mock button - const simulateChangeButton = getByText("Simulate Change"); + const simulateChangeButton = screen.getByText("Simulate Change"); fireEvent.click(simulateChangeButton); // Save again - fireEvent.click(getByText("Save Changes")); + fireEvent.click(screen.getByText("Save Changes")); await waitFor(() => { expect(networking.updateGuardrailCall).toHaveBeenCalled(); @@ -339,12 +331,10 @@ describe("Guardrail Info", () => { }); vi.mocked(networking.getGuardrailProviderSpecificParams).mockResolvedValue({}); - const { findByRole, getByRole, getByText } = render( - {}} accessToken="123" isAdmin={true} />, - ); + render( {}} accessToken="123" isAdmin={true} />); - expect(await findByRole("tab", { name: "Overview" })).toHaveAttribute("aria-selected", "true"); - expect(getByRole("tab", { name: "Settings" })).toHaveAttribute("aria-selected", "false"); - expect(getByText("Guardrail Settings")).toBeInTheDocument(); + expect(await screen.findByRole("tab", { name: "Overview" })).toHaveAttribute("aria-selected", "true"); + expect(screen.getByRole("tab", { name: "Settings" })).toHaveAttribute("aria-selected", "false"); + expect(screen.getByText("Guardrail Settings")).toBeInTheDocument(); }); }); diff --git a/ui/litellm-dashboard/src/app/(dashboard)/guardrails/_components/pii_components.test.tsx b/ui/litellm-dashboard/src/app/(dashboard)/guardrails/_components/pii_components.test.tsx index 2f839487111..30ff2cf7c5f 100644 --- a/ui/litellm-dashboard/src/app/(dashboard)/guardrails/_components/pii_components.test.tsx +++ b/ui/litellm-dashboard/src/app/(dashboard)/guardrails/_components/pii_components.test.tsx @@ -1,4 +1,4 @@ -import { render } from "@testing-library/react"; +import { render, screen } from "@testing-library/react"; import { describe, it, expect } from "vitest"; import { CategoryFilter, QuickActions, PiiEntityList } from "./pii_components"; import type { PiiEntityCategory } from "@/components/guardrails/types"; @@ -6,25 +6,21 @@ import type { PiiEntityCategory } from "@/components/guardrails/types"; describe("CategoryFilter", () => { it("should render", () => { const emptyCategories: PiiEntityCategory[] = []; - const { getByText } = render( - {}} />, - ); - expect(getByText("Filter by category")).toBeInTheDocument(); + render( {}} />); + expect(screen.getByText("Filter by category")).toBeInTheDocument(); }); }); describe("QuickActions", () => { it("should render", () => { - const { getByText } = render( - {}} onUnselectAll={() => {}} hasSelectedEntities={false} />, - ); - expect(getByText("Quick Actions")).toBeInTheDocument(); + render( {}} onUnselectAll={() => {}} hasSelectedEntities={false} />); + expect(screen.getByText("Quick Actions")).toBeInTheDocument(); }); }); describe("PiiEntityList", () => { it("should render", () => { - const { getByText } = render( + render( { entityToCategoryMap={new Map()} />, ); - expect(getByText("No PII types match your filter criteria")).toBeInTheDocument(); + expect(screen.getByText("No PII types match your filter criteria")).toBeInTheDocument(); }); }); diff --git a/ui/litellm-dashboard/src/app/(dashboard)/guardrails/_components/pii_configuration.test.tsx b/ui/litellm-dashboard/src/app/(dashboard)/guardrails/_components/pii_configuration.test.tsx index 00c568ef35b..4f822578fe8 100644 --- a/ui/litellm-dashboard/src/app/(dashboard)/guardrails/_components/pii_configuration.test.tsx +++ b/ui/litellm-dashboard/src/app/(dashboard)/guardrails/_components/pii_configuration.test.tsx @@ -1,10 +1,10 @@ -import { render } from "@testing-library/react"; +import { render, screen } from "@testing-library/react"; import { describe, it, expect } from "vitest"; import PiiConfiguration from "./pii_configuration"; describe("PiiConfiguration", () => { it("should render", () => { - const { getByText } = render( + render( { entityCategories={[]} />, ); - expect(getByText("Configure PII Protection")).toBeInTheDocument(); + expect(screen.getByText("Configure PII Protection")).toBeInTheDocument(); }); }); diff --git a/ui/litellm-dashboard/src/app/(dashboard)/mcp-servers/_components/mcp_servers.test.tsx b/ui/litellm-dashboard/src/app/(dashboard)/mcp-servers/_components/mcp_servers.test.tsx index 8dca87e24ef..8abb8855e3d 100644 --- a/ui/litellm-dashboard/src/app/(dashboard)/mcp-servers/_components/mcp_servers.test.tsx +++ b/ui/litellm-dashboard/src/app/(dashboard)/mcp-servers/_components/mcp_servers.test.tsx @@ -45,7 +45,7 @@ describe("MCPServers", () => { vi.mocked(networking.fetchMCPServers).mockResolvedValue([]); const queryClient = createQueryClient(); - const { getByText } = render( + render( , @@ -53,11 +53,11 @@ describe("MCPServers", () => { // Wait for the component to load and check if title renders await waitFor(() => { - expect(getByText("MCP Servers")).toBeInTheDocument(); + expect(screen.getByText("MCP Servers")).toBeInTheDocument(); }); // Verify the title is rendered - expect(getByText("MCP Servers")).toBeInTheDocument(); + expect(screen.getByText("MCP Servers")).toBeInTheDocument(); }); it("should render mocked MCP servers data in the table", async () => { @@ -96,7 +96,7 @@ describe("MCPServers", () => { vi.mocked(networking.fetchMCPServers).mockResolvedValue(mockServers); const queryClient = createQueryClient(); - const { getByText, getAllByText } = render( + render( , @@ -104,19 +104,19 @@ describe("MCPServers", () => { // Wait for the component to load await waitFor(() => { - expect(getByText("MCP Servers")).toBeInTheDocument(); + expect(screen.getByText("MCP Servers")).toBeInTheDocument(); }); // Wait for the mocked data to render in the table await waitFor(() => { - expect(getByText("Test Server 1")).toBeInTheDocument(); + expect(screen.getByText("Test Server 1")).toBeInTheDocument(); }); // Verify the mocked server data is rendered in the table - expect(getByText("Test Server 1")).toBeInTheDocument(); - expect(getByText("Test Server 2")).toBeInTheDocument(); - expect(getAllByText("test-server-1").length).toBeGreaterThan(0); - expect(getAllByText("test-server-2").length).toBeGreaterThan(0); + expect(screen.getByText("Test Server 1")).toBeInTheDocument(); + expect(screen.getByText("Test Server 2")).toBeInTheDocument(); + expect(screen.getAllByText("test-server-1").length).toBeGreaterThan(0); + expect(screen.getAllByText("test-server-2").length).toBeGreaterThan(0); // Verify the API was called // Note: useMCPServers uses useAuthorized() internally, which returns "123" from global mock @@ -168,7 +168,7 @@ describe("MCPServers", () => { vi.mocked(networking.fetchMCPServerHealth).mockResolvedValue(mockHealthStatuses); const queryClient = createQueryClient(); - const { getByText } = render( + render( , @@ -176,7 +176,7 @@ describe("MCPServers", () => { // Wait for the component to load await waitFor(() => { - expect(getByText("MCP Servers")).toBeInTheDocument(); + expect(screen.getByText("MCP Servers")).toBeInTheDocument(); }); // Verify the health check API was called (without a server ID filter — the hook always @@ -211,7 +211,7 @@ describe("MCPServers", () => { ); const queryClient = createQueryClient(); - const { getByText } = render( + render( , @@ -219,7 +219,7 @@ describe("MCPServers", () => { // Wait for the component to load await waitFor(() => { - expect(getByText("MCP Servers")).toBeInTheDocument(); + expect(screen.getByText("MCP Servers")).toBeInTheDocument(); }); // Verify that health check was initiated diff --git a/ui/litellm-dashboard/src/app/(dashboard)/models-and-endpoints/components/PriceDataManagementTab.test.tsx b/ui/litellm-dashboard/src/app/(dashboard)/models-and-endpoints/components/PriceDataManagementTab.test.tsx index 8b34d61ebad..7cd418bc176 100644 --- a/ui/litellm-dashboard/src/app/(dashboard)/models-and-endpoints/components/PriceDataManagementTab.test.tsx +++ b/ui/litellm-dashboard/src/app/(dashboard)/models-and-endpoints/components/PriceDataManagementTab.test.tsx @@ -1,5 +1,5 @@ /* @vitest-environment jsdom */ -import { render } from "@testing-library/react"; +import { render, screen } from "@testing-library/react"; import { describe, expect, it, vi } from "vitest"; import PriceDataManagementTab from "./PriceDataManagementTab"; @@ -11,7 +11,7 @@ vi.mock("@/app/(dashboard)/hooks/models/useModelCostMap", () => ({ describe("PriceDataManagementTab", () => { it("renders its content standalone, without a tab-panel ancestor", () => { - const { getByText } = render(); - expect(getByText("Price Data Management")).toBeInTheDocument(); + render(); + expect(screen.getByText("Price Data Management")).toBeInTheDocument(); }); }); diff --git a/ui/litellm-dashboard/src/app/(dashboard)/models-and-endpoints/page.test.tsx b/ui/litellm-dashboard/src/app/(dashboard)/models-and-endpoints/page.test.tsx index 521f89a39f2..a504d75bb63 100644 --- a/ui/litellm-dashboard/src/app/(dashboard)/models-and-endpoints/page.test.tsx +++ b/ui/litellm-dashboard/src/app/(dashboard)/models-and-endpoints/page.test.tsx @@ -1,6 +1,6 @@ /* @vitest-environment jsdom */ import { QueryClient, QueryClientProvider } from "@tanstack/react-query"; -import { render } from "@testing-library/react"; +import { render, screen } from "@testing-library/react"; import userEvent from "@testing-library/user-event"; import { beforeEach, describe, expect, it, vi } from "vitest"; import ModelsAndEndpointsPage from "./page"; @@ -64,48 +64,48 @@ describe("ModelsAndEndpointsPage", () => { }); it("renders the admin tab bar and the All Models panel by default", () => { - const { getByRole, getByTestId } = renderPage(); - expect(getByRole("tab", { name: "All Models" })).toBeInTheDocument(); - expect(getByRole("tab", { name: "LLM Credentials" })).toBeInTheDocument(); - expect(getByRole("tab", { name: "Health Status" })).toBeInTheDocument(); - expect(getByTestId("panel-all-models")).toBeInTheDocument(); + renderPage(); + expect(screen.getByRole("tab", { name: "All Models" })).toBeInTheDocument(); + expect(screen.getByRole("tab", { name: "LLM Credentials" })).toBeInTheDocument(); + expect(screen.getByRole("tab", { name: "Health Status" })).toBeInTheDocument(); + expect(screen.getByTestId("panel-all-models")).toBeInTheDocument(); }); it("switches tabs in-memory, mounting only the active panel", async () => { const user = userEvent.setup(); - const { getByRole, getByTestId, queryByTestId } = renderPage(); - await user.click(getByRole("tab", { name: "Health Status" })); - expect(getByTestId("panel-health")).toBeInTheDocument(); - expect(queryByTestId("panel-all-models")).not.toBeInTheDocument(); + renderPage(); + await user.click(screen.getByRole("tab", { name: "Health Status" })); + expect(screen.getByTestId("panel-health")).toBeInTheDocument(); + expect(screen.queryByTestId("panel-all-models")).not.toBeInTheDocument(); }); it("renders the model detail overlay from the ?model drill-in and hides the tabs", () => { detailState.modelId = "abc-123"; - const { getByTestId, queryByRole } = renderPage(); - expect(getByTestId("model-info")).toHaveTextContent("model:abc-123"); - expect(queryByRole("tab", { name: "All Models" })).not.toBeInTheDocument(); + renderPage(); + expect(screen.getByTestId("model-info")).toHaveTextContent("model:abc-123"); + expect(screen.queryByRole("tab", { name: "All Models" })).not.toBeInTheDocument(); }); it("renders the team detail overlay from the ?team drill-in", () => { detailState.teamId = "team-9"; - const { getByTestId } = renderPage(); - expect(getByTestId("team-info")).toHaveTextContent("team:team-9"); + renderPage(); + expect(screen.getByTestId("team-info")).toHaveTextContent("team:team-9"); }); it("hides admin-only tabs for a non-admin user", () => { mockUseAuthorized.mockReturnValue(NON_ADMIN); - const { queryByRole } = renderPage(); - expect(queryByRole("tab", { name: "LLM Credentials" })).not.toBeInTheDocument(); - expect(queryByRole("tab", { name: "Health Status" })).not.toBeInTheDocument(); + renderPage(); + expect(screen.queryByRole("tab", { name: "LLM Credentials" })).not.toBeInTheDocument(); + expect(screen.queryByRole("tab", { name: "Health Status" })).not.toBeInTheDocument(); }); // Auto-routers are excluded from the All Models table, so this tab is their home: the only // place in the product to list, create, edit or delete one. describe("Auto-Routers tab", () => { it("sits third, after All Models and Add Model", () => { - const { getAllByRole } = renderPage(); + renderPage(); - const tabs = getAllByRole("tab").map((tab) => tab.textContent); + const tabs = screen.getAllByRole("tab").map((tab) => tab.textContent); expect(tabs[0]).toContain("All Models"); expect(tabs[1]).toBe("Add Model"); expect(tabs[2]).toContain("Auto-Routers"); @@ -115,17 +115,17 @@ describe("ModelsAndEndpointsPage", () => { it("renders its panel when selected", async () => { const user = userEvent.setup(); - const { getByRole, getByTestId } = renderPage(); + renderPage(); - await user.click(getByRole("tab", { name: /Auto-Routers/ })); - expect(getByTestId("panel-auto-routers")).toBeInTheDocument(); + await user.click(screen.getByRole("tab", { name: /Auto-Routers/ })); + expect(screen.getByTestId("panel-auto-routers")).toBeInTheDocument(); }); it("is hidden from non-admins, who cannot write models", () => { mockUseAuthorized.mockReturnValue(NON_ADMIN); - const { queryByRole } = renderPage(); + renderPage(); - expect(queryByRole("tab", { name: /Auto-Routers/ })).not.toBeInTheDocument(); + expect(screen.queryByRole("tab", { name: /Auto-Routers/ })).not.toBeInTheDocument(); }); }); }); diff --git a/ui/litellm-dashboard/src/app/(dashboard)/playground/components/chat_ui/ChatMessageBubble.test.tsx b/ui/litellm-dashboard/src/app/(dashboard)/playground/components/chat_ui/ChatMessageBubble.test.tsx index a83c11d1444..ed02e7e16cc 100644 --- a/ui/litellm-dashboard/src/app/(dashboard)/playground/components/chat_ui/ChatMessageBubble.test.tsx +++ b/ui/litellm-dashboard/src/app/(dashboard)/playground/components/chat_ui/ChatMessageBubble.test.tsx @@ -93,13 +93,13 @@ describe("ChatMessageBubble", () => { ])("should paint the $role surface from theme tokens, not fixed colours", ({ role, bubble, avatar }) => { render(); - const header = screen.getByText(role).closest("div") as HTMLElement; - const surface = header.parentElement as HTMLElement; + const surface = screen.getByTestId("message-surface"); + const avatarEl = screen.getByTestId("message-avatar"); expect(surface).toHaveClass(...bubble); expect(surface).not.toHaveAttribute("style"); - expect(header.firstElementChild).toHaveClass(avatar); - expect(header.firstElementChild).not.toHaveAttribute("style"); + expect(avatarEl).toHaveClass(avatar); + expect(avatarEl).not.toHaveAttribute("style"); }); it("should show model badge for assistant messages when model is provided", () => { diff --git a/ui/litellm-dashboard/src/app/(dashboard)/playground/components/chat_ui/ChatMessageBubble.tsx b/ui/litellm-dashboard/src/app/(dashboard)/playground/components/chat_ui/ChatMessageBubble.tsx index 8c54d9e89fa..bd6a4bc49a4 100644 --- a/ui/litellm-dashboard/src/app/(dashboard)/playground/components/chat_ui/ChatMessageBubble.tsx +++ b/ui/litellm-dashboard/src/app/(dashboard)/playground/components/chat_ui/ChatMessageBubble.tsx @@ -46,6 +46,7 @@ function ChatMessageBubble({ return (
{ describe("CompareUI", () => { it("should render", () => { - const { getByTestId } = render(); - expect(getByTestId("comparison-panel-1")).toBeInTheDocument(); - expect(getByTestId("comparison-panel-2")).toBeInTheDocument(); - expect(getByTestId("message-input")).toBeInTheDocument(); + render(); + expect(screen.getByTestId("comparison-panel-1")).toBeInTheDocument(); + expect(screen.getByTestId("comparison-panel-2")).toBeInTheDocument(); + expect(screen.getByTestId("message-input")).toBeInTheDocument(); }); it("adds a comparison when Add Comparison button is clicked", async () => { const user = userEvent.setup(); - const { container, getByTestId } = render( - , - ); + const { container } = render(); // Verify initial state: 2 comparison panels - expect(getByTestId("comparison-panel-1")).toBeInTheDocument(); - expect(getByTestId("comparison-panel-2")).toBeInTheDocument(); + expect(screen.getByTestId("comparison-panel-1")).toBeInTheDocument(); + expect(screen.getByTestId("comparison-panel-2")).toBeInTheDocument(); let comparisonPanels = container.querySelectorAll('[data-testid^="comparison-panel-"]'); expect(comparisonPanels).toHaveLength(2); @@ -117,15 +115,13 @@ describe("CompareUI", () => { }); // Verify the original 2 panels are still there - expect(getByTestId("comparison-panel-1")).toBeInTheDocument(); - expect(getByTestId("comparison-panel-2")).toBeInTheDocument(); + expect(screen.getByTestId("comparison-panel-1")).toBeInTheDocument(); + expect(screen.getByTestId("comparison-panel-2")).toBeInTheDocument(); }); it("should handle image upload and send message with attachment", async () => { const user = userEvent.setup(); - const { getByTestId, queryByTestId } = render( - , - ); + render(); const file = new File(["test content"], "test-image.png", { type: "image/png" }); @@ -138,13 +134,13 @@ describe("CompareUI", () => { } await waitFor(() => { - expect(getByTestId("has-attachment")).toBeInTheDocument(); + expect(screen.getByTestId("has-attachment")).toBeInTheDocument(); }); - const textarea = getByTestId("message-textarea"); + const textarea = screen.getByTestId("message-textarea"); fireEvent.change(textarea, { target: { value: "Describe this image" } }); - const sendButton = getByTestId("send-button"); + const sendButton = screen.getByTestId("send-button"); expect(sendButton).toBeEnabled(); await user.click(sendButton); diff --git a/ui/litellm-dashboard/src/app/(dashboard)/playground/components/compareUI/components/MessageDisplay.test.tsx b/ui/litellm-dashboard/src/app/(dashboard)/playground/components/compareUI/components/MessageDisplay.test.tsx index 72a1d41f9fe..69b50d4088f 100644 --- a/ui/litellm-dashboard/src/app/(dashboard)/playground/components/compareUI/components/MessageDisplay.test.tsx +++ b/ui/litellm-dashboard/src/app/(dashboard)/playground/components/compareUI/components/MessageDisplay.test.tsx @@ -1,4 +1,4 @@ -import { render } from "@testing-library/react"; +import { render, screen } from "@testing-library/react"; import { describe, expect, it, vi } from "vitest"; import type { MessageType } from "@/components/chat_ui/types"; import { MessageDisplay } from "./MessageDisplay"; @@ -39,9 +39,9 @@ describe("MessageDisplay", () => { model: "gpt-4", }, ]; - const { getByText } = render(); - expect(getByText("Hello")).toBeInTheDocument(); - expect(getByText("Hi there!")).toBeInTheDocument(); + render(); + expect(screen.getByText("Hello")).toBeInTheDocument(); + expect(screen.getByText("Hi there!")).toBeInTheDocument(); }); it("displays user and assistant messages with proper grouping and shows loading state", () => { @@ -64,13 +64,13 @@ describe("MessageDisplay", () => { }, }, ]; - const { getByText, getByTestId } = render(); - expect(getByText("You")).toBeInTheDocument(); - expect(getByText("What is 2+2?")).toBeInTheDocument(); - expect(getByText("gpt-4")).toBeInTheDocument(); - expect(getByText("calculator")).toBeInTheDocument(); - expect(getByText("2+2 equals 4")).toBeInTheDocument(); - expect(getByTestId("response-metrics")).toBeInTheDocument(); + render(); + expect(screen.getByText("You")).toBeInTheDocument(); + expect(screen.getByText("What is 2+2?")).toBeInTheDocument(); + expect(screen.getByText("gpt-4")).toBeInTheDocument(); + expect(screen.getByText("calculator")).toBeInTheDocument(); + expect(screen.getByText("2+2 equals 4")).toBeInTheDocument(); + expect(screen.getByTestId("response-metrics")).toBeInTheDocument(); }); it("should display image attachment in user message", () => { @@ -86,10 +86,10 @@ describe("MessageDisplay", () => { model: "gpt-4", }, ]; - const { getByTestId, getByText } = render(); - expect(getByText("What is in this image? [Image attached]")).toBeInTheDocument(); - expect(getByTestId("chat-image-renderer")).toBeInTheDocument(); - const image = getByTestId("chat-image-renderer").querySelector("img"); + render(); + expect(screen.getByText("What is in this image? [Image attached]")).toBeInTheDocument(); + expect(screen.getByTestId("chat-image-renderer")).toBeInTheDocument(); + const image = screen.getByTestId("chat-image-renderer").querySelector("img"); expect(image).toHaveAttribute("src", "blob:test-image-url"); }); }); diff --git a/ui/litellm-dashboard/src/autorouter_presets.json b/ui/litellm-dashboard/src/autorouter_presets.json index 4cbb548a855..b977bd484ac 100644 --- a/ui/litellm-dashboard/src/autorouter_presets.json +++ b/ui/litellm-dashboard/src/autorouter_presets.json @@ -14,7 +14,9 @@ }, "classifier_type": "heuristic", "escalation_keywords": ["LITELLM ESCALATE"], + "classification_mode": "every_request", "session_affinity": false, + "modality_routing": false, "deployment_affinity": true } }, @@ -30,7 +32,9 @@ }, "classifier_type": "heuristic", "escalation_keywords": ["LITELLM ESCALATE"], + "classification_mode": "every_request", "session_affinity": false, + "modality_routing": false, "deployment_affinity": true } }, @@ -56,7 +60,9 @@ }, "classifier_context_window_size": 0, "escalation_keywords": ["LITELLM ESCALATE"], + "classification_mode": "every_request", "session_affinity": false, + "modality_routing": false, "deployment_affinity": true } }, @@ -72,7 +78,9 @@ }, "classifier_type": "heuristic", "escalation_keywords": ["LITELLM ESCALATE"], + "classification_mode": "every_request", "session_affinity": false, + "modality_routing": false, "deployment_affinity": true } } diff --git a/ui/litellm-dashboard/src/components/CreateUserButton.test.tsx b/ui/litellm-dashboard/src/components/CreateUserButton.test.tsx index 3777c46973f..68bfd94bd63 100644 --- a/ui/litellm-dashboard/src/components/CreateUserButton.test.tsx +++ b/ui/litellm-dashboard/src/components/CreateUserButton.test.tsx @@ -5,6 +5,7 @@ import { describe, it, expect, vi, beforeEach } from "vitest"; import { CreateUserButton } from "./CreateUserButton"; import * as networking from "./networking"; import { toast } from "@/lib/toast"; +import { expectControlBesideLabel } from "../../tests/fieldOrientation"; vi.mock("./networking", () => ({ userCreateCall: vi.fn(), @@ -294,6 +295,20 @@ describe("CreateUserButton", () => { }); }); + it("lays the send invitation email checkbox out beside its label", async () => { + const user = userEvent.setup({ pointerEventsCheck: PointerEventsCheckLevel.Never }); + renderWithProviders(); + + await waitFor(() => { + expect(screen.getByRole("button", { name: /\+ invite user/i })).toBeInTheDocument(); + }); + await user.click(screen.getByRole("button", { name: /\+ invite user/i })); + + const dialog = screen.getByRole("dialog", { name: /invite user/i }); + + expectControlBesideLabel(within(dialog).getByRole("checkbox")); + }); + describe("organizations", () => { it("should send organizations list in POST body when organizations are selected", async () => { const { useOrganizations } = await import("@/app/(dashboard)/hooks/organizations/useOrganizations"); diff --git a/ui/litellm-dashboard/src/components/CreateUserButton.tsx b/ui/litellm-dashboard/src/components/CreateUserButton.tsx index e052a9e0818..0f7c356b8cc 100644 --- a/ui/litellm-dashboard/src/components/CreateUserButton.tsx +++ b/ui/litellm-dashboard/src/components/CreateUserButton.tsx @@ -270,7 +270,7 @@ export const CreateUserButton: React.FC = ({ ); const sendInviteEmailField = ( - + {({ id, value, onChange, onBlur }) => ( )} diff --git a/ui/litellm-dashboard/src/components/EntityUsageExport/EntityUsageExportModal.test.tsx b/ui/litellm-dashboard/src/components/EntityUsageExport/EntityUsageExportModal.test.tsx index 8edf2174eee..cb04323e4c9 100644 --- a/ui/litellm-dashboard/src/components/EntityUsageExport/EntityUsageExportModal.test.tsx +++ b/ui/litellm-dashboard/src/components/EntityUsageExport/EntityUsageExportModal.test.tsx @@ -10,6 +10,7 @@ */ import { describe, it, expect, vi, beforeEach } from "vitest"; +import { screen } from "@testing-library/react"; import { renderWithProviders } from "../../../tests/test-utils"; import userEvent from "@testing-library/user-event"; import EntityUsageExportModal from "./EntityUsageExportModal"; @@ -73,13 +74,13 @@ describe("EntityUsageExportModal", () => { const user = userEvent.setup(); const { handleExportCSV } = await import("./utils"); - const { getByRole } = renderWithProviders(); + renderWithProviders(); // Default primary action reflects CSV export - expect(getByRole("button", { name: /Export CSV/i })).toBeInTheDocument(); + expect(screen.getByRole("button", { name: /Export CSV/i })).toBeInTheDocument(); // Click export - await user.click(getByRole("button", { name: /Export CSV/i })); + await user.click(screen.getByRole("button", { name: /Export CSV/i })); // Verifies export function was invoked with correct parameters expect(handleExportCSV).toHaveBeenCalledWith(baseProps.spendData, "daily", "Tag", "tag", {}); @@ -97,14 +98,14 @@ describe("EntityUsageExportModal", () => { const user = userEvent.setup(); const { handleExportCSV } = await import("./utils"); - const { getByText, getByRole } = renderWithProviders(); + renderWithProviders(); // Choose the alternate export type - click the label to trigger radio - const dailyModelLabel = getByText(/Day-by-day by tag and model/i); + const dailyModelLabel = screen.getByText(/Day-by-day by tag and model/i); await user.click(dailyModelLabel); // Export with default CSV format - const exportBtn = getByRole("button", { name: /Export CSV/i }); + const exportBtn = screen.getByRole("button", { name: /Export CSV/i }); await user.click(exportBtn); // Ensure the selected scope flowed through diff --git a/ui/litellm-dashboard/src/components/Settings/AdminSettings/SSOSettings/Modals/BaseSSOSettingsForm.test.tsx b/ui/litellm-dashboard/src/components/Settings/AdminSettings/SSOSettings/Modals/BaseSSOSettingsForm.test.tsx index 54566e1d75a..eddc5716305 100644 --- a/ui/litellm-dashboard/src/components/Settings/AdminSettings/SSOSettings/Modals/BaseSSOSettingsForm.test.tsx +++ b/ui/litellm-dashboard/src/components/Settings/AdminSettings/SSOSettings/Modals/BaseSSOSettingsForm.test.tsx @@ -9,6 +9,7 @@ import BaseSSOSettingsForm, { submitMountedSSOValues, useSSOSettingsForm, } from "./BaseSSOSettingsForm"; +import { expectControlBesideLabel } from "../../../../../../tests/fieldOrientation"; const user = () => userEvent.setup({ pointerEventsCheck: 0 }); @@ -233,6 +234,38 @@ describe("BaseSSOSettingsForm", () => { expect(screen.queryByText("Use Team Mappings")).not.toBeInTheDocument(); }); + + it("lays a provider checkbox field out beside its label", async () => { + const TestWrapper = () => { + const form = useSSOSettingsForm("sso-settings"); + + return ; + }; + + renderWithProviders(); + + await openProviderDropdown(); + await user().click(await screen.findByText(/saml sso/i)); + + expectControlBesideLabel( + await screen.findByRole("checkbox", { name: "Allow IdP-initiated (unsolicited) responses" }), + ); + }); + + it.each(["Use Role Mappings", "Use Team Mappings"])("lays the %s toggle out beside its label", async (label) => { + const TestWrapper = () => { + const form = useSSOSettingsForm("sso-settings"); + + return ; + }; + + renderWithProviders(); + + await openProviderDropdown(); + await user().click(await screen.findByText(/okta/i)); + + expectControlBesideLabel(await screen.findByRole("checkbox", { name: label })); + }); }); describe("renderProviderFields", () => { diff --git a/ui/litellm-dashboard/src/components/Settings/AdminSettings/SSOSettings/Modals/BaseSSOSettingsForm.tsx b/ui/litellm-dashboard/src/components/Settings/AdminSettings/SSOSettings/Modals/BaseSSOSettingsForm.tsx index 5216da382d0..cb97304f77a 100644 --- a/ui/litellm-dashboard/src/components/Settings/AdminSettings/SSOSettings/Modals/BaseSSOSettingsForm.tsx +++ b/ui/litellm-dashboard/src/components/Settings/AdminSettings/SSOSettings/Modals/BaseSSOSettingsForm.tsx @@ -303,7 +303,7 @@ const SSOProviderField = ({ field }: { field: SSOProviderConfig["fields"][number if (field.type === "checkbox") { return ( - + {({ value, onChange, onBlur, id, ...rest }) => ( (); return ( - + {({ value, onChange, onBlur, id, ...rest }) => ( void; +}> = ({ value, onChange }) => ( + <> +
+ onChange({ ...value, deployment_affinity: deploymentAffinity })} + aria-label="Pin a session to one deployment per model group" + /> + Pin a session to one deployment per model group +
+ + Keeps a session on the same deployment within a group, so provider prompt caches stay warm. Turn off to + load-balance every turn. + + +); diff --git a/ui/litellm-dashboard/src/components/add_model/ClassificationMethodConfig.tsx b/ui/litellm-dashboard/src/components/add_model/ClassificationMethodConfig.tsx index 84f61c95eca..96c93306611 100644 --- a/ui/litellm-dashboard/src/components/add_model/ClassificationMethodConfig.tsx +++ b/ui/litellm-dashboard/src/components/add_model/ClassificationMethodConfig.tsx @@ -15,9 +15,12 @@ import { RestrictedSection, restrictedBy } from "./TierRestrictions"; import HeuristicScoringConfig from "./HeuristicScoringConfig"; import { useComplexityScorerDefaults } from "@/app/(dashboard)/hooks/autoRouter/useComplexityScorerDefaults"; import { + ClassificationFrequency, ClassifierFallback, ClassifierType, ComplexityRouterConfigValue, + classificationFrequency, + withClassificationFrequency, DEFAULT_CLASSIFIER_CONTEXT_BUDGET_CHARS, MIN_QUOTED_CONTEXT_TURN_CHARS, DEFAULT_CLASSIFIER_CONTEXT_WINDOW_SIZE, @@ -211,6 +214,7 @@ const ClassificationMethodConfig: React.FC = ({ const [draft, setDraft] = React.useState<{ id: string; raw: string } | null>(null); const hasDefaultModel = Boolean(defaultModel); const classifierType = effectiveClassifierType(value); + const sessionFrequencyRestriction = restrictedBy(value, "sessionAffinity"); const classifierModelMissing = showValidationErrors && usesLlmClassifier(classifierType) && !value.classifier_llm_config?.model; const usesCustomPrompt = Boolean(value.classifier_llm_config?.system_prompt?.trim()); @@ -305,6 +309,10 @@ const ClassificationMethodConfig: React.FC = ({ onChange({ ...value, classifier_fallback: fallback }); }; + const handleClassificationFrequencyChange = (frequency: ClassificationFrequency) => { + onChange(withClassificationFrequency(value, frequency)); + }; + const handleClassifierContextWindowSizeChange = (windowSize: number) => { onChange({ ...value, @@ -367,6 +375,49 @@ const ClassificationMethodConfig: React.FC = ({
)} +
+ How often to classify + + handleClassificationFrequencyChange(frequency as ClassificationFrequency) + } + > +
+ + + +
+ +

+ Holding the tier keeps an agent on one model for a whole tool loop and cuts scoring cost. A turn the router + cannot match to a held decision, such as one with no session id or an expired one, is scored again +

+
+ {usesLlmClassifier(classifierType) && (
diff --git a/ui/litellm-dashboard/src/components/add_model/ComplexityRouterConfig.test.tsx b/ui/litellm-dashboard/src/components/add_model/ComplexityRouterConfig.test.tsx index 218c99e32c5..751f8870561 100644 --- a/ui/litellm-dashboard/src/components/add_model/ComplexityRouterConfig.test.tsx +++ b/ui/litellm-dashboard/src/components/add_model/ComplexityRouterConfig.test.tsx @@ -598,6 +598,82 @@ describe("ComplexityRouterConfig classifier fallback", () => { }); }); +describe("ComplexityRouterConfig classification frequency", () => { + const llmValue: ComplexityRouterConfigValue = { + ...defaultValue, + classifier_type: "llm", + classifier_llm_config: { model: "gpt-3.5-turbo", timeout_ms: 3000 }, + }; + + it("defaults to every request, matching both backend field defaults", () => { + renderWithProviders(); + fireEvent.click(screen.getByText("Advanced: Classification Method")); + expect(screen.getByRole("radio", { name: /Every request/ })).toBeChecked(); + expect(screen.getByRole("radio", { name: /Every new user message/ })).not.toBeChecked(); + expect(screen.getByRole("radio", { name: /Once per session/ })).not.toBeChecked(); + }); + + it("writes both wire fields when the frequency moves to every new user message", () => { + const onChange = vi.fn(); + renderWithProviders(); + fireEvent.click(screen.getByText("Advanced: Classification Method")); + fireEvent.click(screen.getByRole("radio", { name: /Every new user message/ })); + expect(onChange).toHaveBeenCalledWith({ + ...llmValue, + classification_mode: "user_turn", + session_affinity: false, + }); + }); + + it("writes session affinity, not a classification mode, when the frequency moves to once per session", () => { + const onChange = vi.fn(); + renderWithProviders(); + fireEvent.click(screen.getByText("Advanced: Classification Method")); + fireEvent.click(screen.getByRole("radio", { name: /Once per session/ })); + expect(onChange).toHaveBeenCalledWith({ + ...llmValue, + classification_mode: "every_request", + session_affinity: true, + }); + }); + + it("shows a hand-authored config that sets both fields as once per session, matching the backend", () => { + renderWithProviders( + , + ); + fireEvent.click(screen.getByText("Advanced: Classification Method")); + expect(screen.getByRole("radio", { name: /Once per session/ })).toBeChecked(); + expect(screen.getByRole("radio", { name: /Every new user message/ })).not.toBeChecked(); + }); + + it("records a switch back to every request", () => { + const onChange = vi.fn(); + renderWithProviders( + , + ); + fireEvent.click(screen.getByText("Advanced: Classification Method")); + expect(screen.getByRole("radio", { name: /Every new user message/ })).toBeChecked(); + fireEvent.click(screen.getByRole("radio", { name: /Every request/ })); + expect(onChange).toHaveBeenCalledWith(expect.objectContaining({ classification_mode: "every_request" })); + }); + + it("offers the frequency on a heuristic router, where holding the tier still pins the model", () => { + // The backend pin is gated on the two fields alone, so a heuristic router that switches models + // mid tool loop is fixed by this control too. + renderWithProviders(); + fireEvent.click(screen.getByText("Advanced: Classification Method")); + expect(screen.getByRole("radio", { name: /Every new user message/ })).toBeInTheDocument(); + }); +}); + describe("ComplexityRouterConfig classifier rubric", () => { const llmValue: ComplexityRouterConfigValue = { ...defaultValue, @@ -760,13 +836,34 @@ describe("ComplexityRouterConfig tier labels", () => { }); }); +describe("ComplexityRouterConfig modality panel", () => { + it("defaults the image-routing switch off and writes modality_routing through onChange", () => { + const onChange = vi.fn(); + renderWithProviders(); + fireEvent.click(screen.getByText("Advanced: Modality Routing")); + + const toggle = screen.getByRole("switch", { name: "Route image requests to vision-capable models" }); + expect(toggle).not.toBeChecked(); + fireEvent.click(toggle); + + expect(onChange).toHaveBeenCalledWith({ ...defaultValue, modality_routing: true }); + }); + + it("renders a stored modality_routing=true as on", () => { + renderWithProviders(); + fireEvent.click(screen.getByText("Advanced: Modality Routing")); + + expect(screen.getByRole("switch", { name: "Route image requests to vision-capable models" })).toBeChecked(); + }); +}); + describe("ComplexityRouterConfig affinity panel", () => { - it("holds both affinity switches with their backend defaults", () => { + it("holds the deployment switch at its backend default, session pinning having moved to the frequency choice", () => { renderWithProviders(); fireEvent.click(screen.getByText("Advanced: Affinity")); expect(screen.getByRole("switch", { name: "Pin a session to one deployment per model group" })).toBeChecked(); - expect(screen.getByRole("switch", { name: "Pin a session to its first model" })).not.toBeChecked(); + expect(screen.queryByRole("switch", { name: "Pin a session to its first model" })).not.toBeInTheDocument(); }); it("writes deployment_affinity through onChange without touching other keys", () => { @@ -1291,10 +1388,18 @@ describe("ComplexityRouterConfig tier editing", () => { expect(screen.getByLabelText("Fallback tier")).toBeInTheDocument(); }); - it("disables session pinning and says why, rather than letting a stripped value look saved", () => { - renderWithProviders(); - fireEvent.click(screen.getByText("Advanced: Affinity")); - expect(screen.getByLabelText("Pin a session to its first model")).toHaveAttribute("data-disabled"); + it("disables the once-per-session frequency and says why, rather than letting a stripped value look saved", () => { + renderWithProviders( + , + ); + fireEvent.click(screen.getByText("Advanced: Classification Method")); + const sessionOption = screen.getByRole("radio", { name: /Once per session/ }); + expect(sessionOption).toHaveAttribute("aria-disabled", "true"); + expect(sessionOption).not.toBeChecked(); expect( screen.getByText("Session pinning escalates along the built-in tier ladder", { exact: false }), ).toBeInTheDocument(); diff --git a/ui/litellm-dashboard/src/components/add_model/ComplexityRouterConfig.tsx b/ui/litellm-dashboard/src/components/add_model/ComplexityRouterConfig.tsx index 111a7c9f10a..6062705aa82 100644 --- a/ui/litellm-dashboard/src/components/add_model/ComplexityRouterConfig.tsx +++ b/ui/litellm-dashboard/src/components/add_model/ComplexityRouterConfig.tsx @@ -4,6 +4,9 @@ import { SearchSelect } from "@/components/shared/SearchSelect"; import { Select, SelectContent, SelectItem, SelectTrigger, SelectValue } from "@/components/ui/select"; import { ChevronRight, Info, Plus, Trash2, X } from "lucide-react"; import { Switch } from "@/components/ui/switch"; + +import { AffinityControls } from "./AffinityControls"; +import { ModalityRoutingControls } from "./ModalityRoutingControls"; import { Card, CardContent } from "@/components/ui/card"; import { Collapsible, CollapsibleContent, CollapsibleTrigger } from "@/components/ui/collapsible"; import { InputGroup, InputGroupAddon, InputGroupButton, InputGroupInput } from "@/components/ui/input-group"; @@ -56,6 +59,16 @@ export const MIN_QUOTED_CONTEXT_TURN_CHARS = 120; export const DEFAULT_SESSION_AFFINITY = false; export const DEFAULT_DEPLOYMENT_AFFINITY = true; +export type ClassificationMode = "every_request" | "user_turn"; + +export const DEFAULT_CLASSIFICATION_MODE: ClassificationMode = "every_request"; + +/** + * One operator-facing choice over the two wire fields that share the router's tier-pin machinery: + * session affinity pins every turn, user_turn pins every turn except a new human ask. + */ +export type ClassificationFrequency = ClassificationMode | "session"; + export type ComplexityTiers = { SIMPLE: string[]; MEDIUM: string[]; @@ -384,7 +397,9 @@ export interface ComplexityRouterConfigValue { classification_prompt?: string; /** Highest tier the scorer may decide alone under heuristic_first. Required by that type, rejected by the others. */ heuristic_first_max_tier?: string; + classification_mode?: ClassificationMode; session_affinity?: boolean; + modality_routing?: boolean; deployment_affinity?: boolean; /** Plan-mode floor as a tier ROW ID, unset meaning off. The wire carries the row's name. */ plan_mode_min_tier?: string; @@ -420,6 +435,21 @@ export interface ComplexityRouterConfigValue { tier_model_params?: TierModelParamsByTier; } +/** Session affinity wins where a hand-authored config sets both, matching the backend's own `or`. */ +export const classificationFrequency = (value: ComplexityRouterConfigValue): ClassificationFrequency => { + if (!value.custom_tier_set && (value.session_affinity ?? DEFAULT_SESSION_AFFINITY)) return "session"; + return value.classification_mode === "user_turn" ? "user_turn" : "every_request"; +}; + +export const withClassificationFrequency = ( + value: ComplexityRouterConfigValue, + frequency: ClassificationFrequency, +): ComplexityRouterConfigValue => ({ + ...value, + classification_mode: frequency === "user_turn" ? "user_turn" : "every_request", + session_affinity: frequency === "session", +}); + interface ComplexityRouterConfigProps { modelInfo: ModelGroup[]; value: ComplexityRouterConfigValue; @@ -485,39 +515,6 @@ export const DEFAULT_HEURISTIC_FIRST_MAX_TIER = "SIMPLE"; */ export const HEURISTIC_FIRST_MAX_TIER_KEYS = TIER_KEYS.slice(0, -1); -const AffinityControls: React.FC<{ - value: ComplexityRouterConfigValue; - onChange: (value: ComplexityRouterConfigValue) => void; -}> = ({ value, onChange }) => ( - <> -
- onChange({ ...value, deployment_affinity: deploymentAffinity })} - aria-label="Pin a session to one deployment per model group" - /> - Pin a session to one deployment per model group -
- - Keeps a session on the same deployment within a group, so provider prompt caches stay warm. Turn off to - load-balance every turn. - -
- onChange({ ...value, session_affinity: sessionAffinity })} - aria-label="Pin a session to its first model" - /> - Pin a session to its first model -
- - {restrictedBy(value, "sessionAffinity")?.reason ?? - "Keeps a session on its first turn's model instead of re-classifying each turn. Also pins the deployment."} - - -); - const PlanModeOverrideControls: React.FC<{ value: ComplexityRouterConfigValue; onChange: (value: ComplexityRouterConfigValue) => void; @@ -828,6 +825,11 @@ const ComplexityRouterConfig: React.FC = ({ label: Advanced: Affinity, children: , }, + { + key: "modality", + label: Advanced: Modality Routing, + children: , + }, { key: "plan-mode", label: Advanced: Plan-Mode Override, diff --git a/ui/litellm-dashboard/src/components/add_model/ModalityRoutingControls.tsx b/ui/litellm-dashboard/src/components/add_model/ModalityRoutingControls.tsx new file mode 100644 index 00000000000..dd697b35239 --- /dev/null +++ b/ui/litellm-dashboard/src/components/add_model/ModalityRoutingControls.tsx @@ -0,0 +1,26 @@ +import React from "react"; + +import { Switch } from "@/components/ui/switch"; + +import type { ComplexityRouterConfigValue } from "./ComplexityRouterConfig"; + +export const ModalityRoutingControls: React.FC<{ + value: ComplexityRouterConfigValue; + onChange: (value: ComplexityRouterConfigValue) => void; +}> = ({ value, onChange }) => ( + <> +
+ onChange({ ...value, modality_routing: modalityRouting })} + aria-label="Route image requests to vision-capable models" + /> + Route image requests to vision-capable models +
+ + Replaces a routed model that cannot take image input with the nearest higher tier that can, then the default + model, instead of failing with a provider 400. Only models explicitly declared supports_vision false are replaced, + and a kept session pin still wins. + + +); diff --git a/ui/litellm-dashboard/src/components/add_model/add_auto_router_tab.test.tsx b/ui/litellm-dashboard/src/components/add_model/add_auto_router_tab.test.tsx index 71b454dbb06..d8a955b719c 100644 --- a/ui/litellm-dashboard/src/components/add_model/add_auto_router_tab.test.tsx +++ b/ui/litellm-dashboard/src/components/add_model/add_auto_router_tab.test.tsx @@ -362,8 +362,8 @@ describe("AddAutoRouterTab", () => { await user.type(screen.getByPlaceholderText(/smart_router/i), "affinity-router"); expandDetailedConfiguration(); - await user.click(screen.getByText("Advanced: Affinity")); - expect(await screen.findByRole("switch", { name: "Pin a session to its first model" })).not.toBeChecked(); + await user.click(screen.getByText("Advanced: Classification Method")); + expect(await screen.findByRole("radio", { name: /Once per session/ })).not.toBeChecked(); await user.click(screen.getByRole("button", { name: /add auto router/i })); @@ -468,8 +468,8 @@ describe("AddAutoRouterTab", () => { await user.type(screen.getByPlaceholderText(/smart_router/i), "affinity-router"); expandDetailedConfiguration(); - await user.click(screen.getByText("Advanced: Affinity")); - await user.click(await screen.findByRole("switch", { name: "Pin a session to its first model" })); + await user.click(screen.getByText("Advanced: Classification Method")); + await user.click(await screen.findByRole("radio", { name: /Once per session/ })); await user.click(screen.getByRole("button", { name: /add auto router/i })); @@ -479,6 +479,44 @@ describe("AddAutoRouterTab", () => { }); }); + it("carries every new user message through to the create payload", async () => { + const user = userEvent.setup(); + vi.mocked(getMissingTiersError).mockReturnValue(null); + + renderWithProviders(); + + await user.type(screen.getByPlaceholderText(/smart_router/i), "user-turn-router"); + expandDetailedConfiguration(); + await user.click(screen.getByText("Advanced: Classification Method")); + await user.click(await screen.findByRole("radio", { name: /Every new user message/ })); + + await user.click(screen.getByRole("button", { name: /add auto router/i })); + + await waitFor(() => expect(handleAddAutoRouterSubmit).toHaveBeenCalled()); + expect(vi.mocked(handleAddAutoRouterSubmit).mock.calls.at(-1)?.[0].complexity_router_config).toMatchObject({ + classification_mode: "user_turn", + }); + }); + + it("writes every_request into the create payload when the default frequency stays selected", async () => { + const user = userEvent.setup(); + vi.mocked(getMissingTiersError).mockReturnValue(null); + + renderWithProviders(); + + await user.type(screen.getByPlaceholderText(/smart_router/i), "default-timing-router"); + expandDetailedConfiguration(); + await user.click(screen.getByText("Advanced: Classification Method")); + expect(await screen.findByRole("radio", { name: /Every request/ })).toBeChecked(); + + await user.click(screen.getByRole("button", { name: /add auto router/i })); + + await waitFor(() => expect(handleAddAutoRouterSubmit).toHaveBeenCalled()); + expect( + vi.mocked(handleAddAutoRouterSubmit).mock.calls.at(-1)?.[0].complexity_router_config.classification_mode, + ).toBe("every_request"); + }); + it("defaults a new router to deployment affinity on, matching the backend field default", async () => { const user = userEvent.setup(); vi.mocked(getMissingTiersError).mockReturnValue(null); diff --git a/ui/litellm-dashboard/src/components/add_model/add_auto_router_tab.tsx b/ui/litellm-dashboard/src/components/add_model/add_auto_router_tab.tsx index ed584a4882b..318adcce369 100644 --- a/ui/litellm-dashboard/src/components/add_model/add_auto_router_tab.tsx +++ b/ui/litellm-dashboard/src/components/add_model/add_auto_router_tab.tsx @@ -342,6 +342,7 @@ const AddAutoRouterTab: React.FC = ({ planModeMinTier: complexityRouterConfig.plan_mode_min_tier, classificationPrompt: complexityRouterConfig.classification_prompt, heuristicFirstMaxTier: complexityRouterConfig.heuristic_first_max_tier, + classificationMode: complexityRouterConfig.classification_mode, tierLabels: complexityRouterConfig.tier_labels, classifierType: complexityRouterConfig.classifier_type, classifierLlmConfig: complexityRouterConfig.classifier_llm_config, @@ -350,6 +351,7 @@ const AddAutoRouterTab: React.FC = ({ classifierContextIncludeAssistantTurns: complexityRouterConfig.classifier_context_include_assistant_turns, classifierFallback: complexityRouterConfig.classifier_fallback, sessionAffinity: complexityRouterConfig.session_affinity ?? DEFAULT_SESSION_AFFINITY, + modalityRouting: complexityRouterConfig.modality_routing ?? false, deploymentAffinity: complexityRouterConfig.deployment_affinity ?? DEFAULT_DEPLOYMENT_AFFINITY, customTechnicalKeywords, keywordTierRules, diff --git a/ui/litellm-dashboard/src/components/add_model/advanced_settings.test.tsx b/ui/litellm-dashboard/src/components/add_model/advanced_settings.test.tsx index 01e00d903aa..ceb9d1ca713 100644 --- a/ui/litellm-dashboard/src/components/add_model/advanced_settings.test.tsx +++ b/ui/litellm-dashboard/src/components/add_model/advanced_settings.test.tsx @@ -1,4 +1,4 @@ -import { act, fireEvent, render, waitFor } from "@testing-library/react"; +import { act, fireEvent, render, waitFor, screen } from "@testing-library/react"; import { beforeEach, describe, expect, it, vi } from "vitest"; import { MountedFormHost } from "../../../tests/mounted-form-host"; import AdvancedSettings from "./advanced_settings"; @@ -35,51 +35,51 @@ describe("AdvancedSettings", () => { }); it("should render tags list", async () => { - const { getByText } = renderAdvancedSettings(); - fireEvent.click(getByText("Advanced Settings")); + renderAdvancedSettings(); + fireEvent.click(screen.getByText("Advanced Settings")); await waitFor(() => { - expect(getByText("Tags")).toBeInTheDocument(); + expect(screen.getByText("Tags")).toBeInTheDocument(); }); }); it("should render the litellm params", async () => { - const { getByText } = renderAdvancedSettings(); + renderAdvancedSettings(); act(() => { - fireEvent.click(getByText("Advanced Settings")); + fireEvent.click(screen.getByText("Advanced Settings")); }); await waitFor(() => { - expect(getByText("LiteLLM Params")).toBeInTheDocument(); + expect(screen.getByText("LiteLLM Params")).toBeInTheDocument(); }); }); it("hides every PTU field when PTU cost attribution is disabled", async () => { - const { getByText, queryByText } = renderAdvancedSettings(); + renderAdvancedSettings(); act(() => { - fireEvent.click(getByText("Advanced Settings")); + fireEvent.click(screen.getByText("Advanced Settings")); }); await waitFor(() => { - expect(getByText("Tags")).toBeInTheDocument(); + expect(screen.getByText("Tags")).toBeInTheDocument(); }); for (const label of PTU_LABELS) { - expect(queryByText(label)).not.toBeInTheDocument(); + expect(screen.queryByText(label)).not.toBeInTheDocument(); } - expect(queryByText("PTU Effective To (UTC)")).not.toBeInTheDocument(); + expect(screen.queryByText("PTU Effective To (UTC)")).not.toBeInTheDocument(); }); it("shows every PTU field when PTU cost attribution is enabled", async () => { mockUsePtuCostAttributionEnabled.mockReturnValue(true); - const { getByText } = renderAdvancedSettings(); + renderAdvancedSettings(); act(() => { - fireEvent.click(getByText("Advanced Settings")); + fireEvent.click(screen.getByText("Advanced Settings")); }); await waitFor(() => { - expect(getByText("PTU Count")).toBeInTheDocument(); + expect(screen.getByText("PTU Count")).toBeInTheDocument(); }); for (const label of PTU_LABELS) { - expect(getByText(label)).toBeInTheDocument(); + expect(screen.getByText(label)).toBeInTheDocument(); } - expect(getByText("PTU Effective To (UTC)")).toBeInTheDocument(); + expect(screen.getByText("PTU Effective To (UTC)")).toBeInTheDocument(); }); }); diff --git a/ui/litellm-dashboard/src/components/add_model/build_complexity_router_config.test.ts b/ui/litellm-dashboard/src/components/add_model/build_complexity_router_config.test.ts index feddaaa0eac..af87cc6c8fb 100644 --- a/ui/litellm-dashboard/src/components/add_model/build_complexity_router_config.test.ts +++ b/ui/litellm-dashboard/src/components/add_model/build_complexity_router_config.test.ts @@ -52,8 +52,10 @@ describe("buildComplexityRouterConfig", () => { const expected = { tiers, classifier_type: "heuristic", + classification_mode: "every_request", session_affinity: false, deployment_affinity: true, + modality_routing: false, escalation_keywords: ["LITELLM ESCALATE"], }; expect(config).toEqual(expected); @@ -247,6 +249,12 @@ describe("buildComplexityRouterConfig", () => { expect(config.return_raw_model_name).toBeUndefined(); }); + it("writes modality_routing explicitly both ways, so the stored config never relies on the backend default", () => { + expect(buildComplexityRouterConfig({ ...baseParams, modalityRouting: true }).modality_routing).toBe(true); + expect(buildComplexityRouterConfig(baseParams).modality_routing).toBe(false); + expect(buildComplexityRouterConfig({ ...baseParams, modalityRouting: false }).modality_routing).toBe(false); + }); + it("writes session_affinity=true so turning the toggle on overrides the backend's off-by-default", () => { const config = buildComplexityRouterConfig({ ...baseParams, sessionAffinity: true }); expect(config.session_affinity).toBe(true); @@ -790,6 +798,20 @@ describe("heuristic_first", () => { }); }); +describe("classification_mode", () => { + it("emits user_turn", () => { + const config = buildComplexityRouterConfig({ ...baseParams, classificationMode: "user_turn" }); + expect(config.classification_mode).toBe("user_turn"); + }); + + it("writes every_request explicitly, so a saved router never depends on the backend default", () => { + expect( + buildComplexityRouterConfig({ ...baseParams, classificationMode: "every_request" }).classification_mode, + ).toBe("every_request"); + expect(buildComplexityRouterConfig(baseParams).classification_mode).toBe("every_request"); + }); +}); + describe("buildComplexityRouterConfig with an edited tier set", () => { const customTierSet = { tiers: [ @@ -902,6 +924,10 @@ describe("buildComplexityRouterConfig with an edited tier set", () => { expect(payload.classifier_llm_config).toEqual({ model: "gpt-4o-mini", timeout_ms: 3000 }); }); + it("keeps classification_mode, which the backend accepts beside tier_definitions", () => { + expect(build({ classificationMode: "user_turn" }).classification_mode).toBe("user_turn"); + }); + it("carries the plan-mode floor as the row's name, not the row id the form holds", () => { expect(build({ planModeMinTier: "sec" }).plan_mode_min_tier).toBe("SECURITY_REVIEW"); }); diff --git a/ui/litellm-dashboard/src/components/add_model/build_complexity_router_config.ts b/ui/litellm-dashboard/src/components/add_model/build_complexity_router_config.ts index 9a14e956207..af34dc92c0f 100644 --- a/ui/litellm-dashboard/src/components/add_model/build_complexity_router_config.ts +++ b/ui/litellm-dashboard/src/components/add_model/build_complexity_router_config.ts @@ -19,10 +19,12 @@ import { import { AdaptiveEligible, AdaptiveRouterWeights, + ClassificationMode, ClassifierFallback, ClassifierLLMConfig, ClassifierType, ComplexityTierLabels, + DEFAULT_CLASSIFICATION_MODE, ComplexityRouterConfigValue, ComplexityTiers, DimensionWeights, @@ -105,7 +107,9 @@ export interface BuildComplexityRouterConfigParams { classifierFallback: ClassifierFallback | undefined; classificationPrompt: string | undefined; heuristicFirstMaxTier: string | undefined; + classificationMode: ClassificationMode | undefined; sessionAffinity: boolean; + modalityRouting?: boolean; deploymentAffinity: boolean; customTechnicalKeywords: string[]; keywordTierRules: KeywordTierRule[]; @@ -159,8 +163,10 @@ export interface ComplexityRouterConfigPayload { classifier_fallback?: ClassifierFallback; classification_prompt?: string; heuristic_first_max_tier?: string; + classification_mode: ClassificationMode; session_affinity: boolean; deployment_affinity: boolean; + modality_routing: boolean; custom_technical_keywords?: string[]; keyword_tier_rules?: { keywords: string[]; tier: KeywordTierRule["tier"] }[]; semantic_keyword_matching?: boolean; @@ -393,7 +399,9 @@ export const buildComplexityRouterConfig = ({ classifierFallback, classificationPrompt, heuristicFirstMaxTier, + classificationMode, sessionAffinity, + modalityRouting, deploymentAffinity, customTechnicalKeywords, keywordTierRules, @@ -452,8 +460,10 @@ export const buildComplexityRouterConfig = ({ ...(cleanedTierLabels && { tier_labels: cleanedTierLabels }), classifier_type: classifierType, ...classifierWireFields(effectiveType, classifierInputs), + classification_mode: classificationMode ?? DEFAULT_CLASSIFICATION_MODE, session_affinity: sessionAffinity, deployment_affinity: deploymentAffinity, + modality_routing: modalityRouting ?? false, ...(customTechnicalKeywords.length > 0 && { custom_technical_keywords: customTechnicalKeywords }), ...(cleanedKeywordTierRules.length > 0 && { keyword_tier_rules: cleanedKeywordTierRules }), escalation_keywords: cleanedEscalationKeywords, diff --git a/ui/litellm-dashboard/src/components/add_model/litellm_model_name.test.tsx b/ui/litellm-dashboard/src/components/add_model/litellm_model_name.test.tsx index 64074481603..d6476089cd7 100644 --- a/ui/litellm-dashboard/src/components/add_model/litellm_model_name.test.tsx +++ b/ui/litellm-dashboard/src/components/add_model/litellm_model_name.test.tsx @@ -1,4 +1,4 @@ -import { render } from "@testing-library/react"; +import { render, screen } from "@testing-library/react"; import { describe, expect, it } from "vitest"; import { getPlaceholder, Providers } from "../provider_info_helpers"; import { MountedFormHost } from "../../../tests/mounted-form-host"; @@ -6,7 +6,7 @@ import LiteLLMModelNameField from "./litellm_model_name"; describe("LitellmModelNameField", () => { it("should render", () => { - const { getByText } = render( + render( { /> , ); - expect(getByText("LiteLLM Model Name(s)")).toBeInTheDocument(); + expect(screen.getByText("LiteLLM Model Name(s)")).toBeInTheDocument(); }); it("should show Azure placeholder as 'my-deployment'", () => { - const { getByPlaceholderText, queryByPlaceholderText } = render( + render( , ); - expect(getByPlaceholderText("my-deployment")).toBeInTheDocument(); - expect(queryByPlaceholderText("gpt-3.5-turbo")).not.toBeInTheDocument(); + expect(screen.getByPlaceholderText("my-deployment")).toBeInTheDocument(); + expect(screen.queryByPlaceholderText("gpt-3.5-turbo")).not.toBeInTheDocument(); }); }); diff --git a/ui/litellm-dashboard/src/components/bulk_create_users_button.test.tsx b/ui/litellm-dashboard/src/components/bulk_create_users_button.test.tsx index 24685f9c129..e1faf8be1df 100644 --- a/ui/litellm-dashboard/src/components/bulk_create_users_button.test.tsx +++ b/ui/litellm-dashboard/src/components/bulk_create_users_button.test.tsx @@ -26,8 +26,8 @@ const openUploadStep = async () => { describe("BulkCreateUsersButton", () => { it("should render", () => { - const { getByText } = render(); - expect(getByText("+ Bulk Invite Users")).toBeInTheDocument(); + render(); + expect(screen.getByText("+ Bulk Invite Users")).toBeInTheDocument(); }); it("parses a CSV chosen through the file input", async () => { diff --git a/ui/litellm-dashboard/src/components/edit_auto_router/build_updated_complexity_router_config.test.ts b/ui/litellm-dashboard/src/components/edit_auto_router/build_updated_complexity_router_config.test.ts index d8c2987ead5..3e63cbd3b32 100644 --- a/ui/litellm-dashboard/src/components/edit_auto_router/build_updated_complexity_router_config.test.ts +++ b/ui/litellm-dashboard/src/components/edit_auto_router/build_updated_complexity_router_config.test.ts @@ -257,6 +257,33 @@ describe("buildUpdatedComplexityRouterConfig session affinity", () => { }); }); +describe("buildUpdatedComplexityRouterConfig classification mode", () => { + it("round-trips a stored user_turn through hydrate then save", () => { + const stored = { ...STORED, classification_mode: "user_turn" }; + const hydrated = hydrateComplexityRouterConfig(stored, undefined); + + expect(hydrated.classification_mode).toBe("user_turn"); + expect(buildUpdatedComplexityRouterConfig(stored, hydrated).classification_mode).toBe("user_turn"); + }); + + it("round-trips an explicitly stored every_request, so an untouched save leaves it as written", () => { + const stored = { ...STORED, classification_mode: "every_request" }; + const hydrated = hydrateComplexityRouterConfig(stored, undefined); + + expect(hydrated.classification_mode).toBe("every_request"); + expect(buildUpdatedComplexityRouterConfig(stored, hydrated).classification_mode).toBe("every_request"); + }); + + it("rewrites a stored user_turn to every_request once the operator picks the default back", () => { + const stored = { ...STORED, classification_mode: "user_turn" }; + const result = buildUpdatedComplexityRouterConfig(stored, { + ...FORM_VALUE, + classification_mode: "every_request", + }); + expect(result.classification_mode).toBe("every_request"); + }); +}); + describe("buildUpdatedComplexityRouterConfig deployment affinity", () => { it("writes deployment_affinity=false when the toggle is off", () => { const result = buildUpdatedComplexityRouterConfig(STORED, { ...FORM_VALUE, deployment_affinity: false }); @@ -476,6 +503,7 @@ describe("managed keys survive an untouched open-and-save", () => { classifier_context_budget_chars: 4000, classifier_context_include_assistant_turns: true, classifier_fallback: "default_model", + classification_mode: "user_turn", session_affinity: true, deployment_affinity: false, adaptive: true, diff --git a/ui/litellm-dashboard/src/components/edit_auto_router/edit_auto_router_modal.test.ts b/ui/litellm-dashboard/src/components/edit_auto_router/edit_auto_router_modal.test.ts index 027e01a9351..481ba2b6b00 100644 --- a/ui/litellm-dashboard/src/components/edit_auto_router/edit_auto_router_modal.test.ts +++ b/ui/litellm-dashboard/src/components/edit_auto_router/edit_auto_router_modal.test.ts @@ -1,4 +1,4 @@ -import { buildUpdatedComplexityRouterConfig } from "./edit_auto_router_modal"; +import { buildUpdatedComplexityRouterConfig, hydrateComplexityRouterConfig } from "./edit_auto_router_modal"; const storedConfigValue = { tiers: { @@ -47,8 +47,10 @@ const expectedClassifiedTierConfig = { semantic_keyword_matching: true, embedding_model: "voyage-4-large", match_threshold: 0.65, + classification_mode: "every_request", session_affinity: false, deployment_affinity: true, + modality_routing: false, adaptive: true, adaptive_weights: { quality: 0.4, cost: 0.6 }, adaptive_eligible: "classified_tier", @@ -68,8 +70,10 @@ const expectedAdaptiveDisabledConfig = { semantic_keyword_matching: true, embedding_model: "voyage-4-large", match_threshold: 0.65, + classification_mode: "every_request", session_affinity: false, deployment_affinity: true, + modality_routing: false, }; describe("buildUpdatedComplexityRouterConfig", () => { @@ -85,6 +89,26 @@ describe("buildUpdatedComplexityRouterConfig", () => { expect(updatedConfig).toEqual(expectedAdaptiveDisabledConfig); }); + it("hydrates a stored modality_routing into form state and defaults absent to off", () => { + expect(hydrateComplexityRouterConfig({ ...storedConfig, modality_routing: true }, null).modality_routing).toBe( + true, + ); + expect(hydrateComplexityRouterConfig(storedConfig, null).modality_routing).toBe(false); + }); + + it("round-trips modality_routing explicitly in both directions", () => { + const enabled = buildUpdatedComplexityRouterConfig(storedConfig, { + ...classifiedTierValue, + modality_routing: true, + }); + expect(enabled.modality_routing).toBe(true); + const disabled = buildUpdatedComplexityRouterConfig( + { ...storedConfig, modality_routing: true }, + { ...classifiedTierValue, modality_routing: false }, + ); + expect(disabled.modality_routing).toBe(false); + }); + it("includes return_raw_model_name only when enabled", () => { const updatedConfig = buildUpdatedComplexityRouterConfig(storedConfig, { ...classifiedTierValue, diff --git a/ui/litellm-dashboard/src/components/edit_auto_router/edit_auto_router_modal.test.tsx b/ui/litellm-dashboard/src/components/edit_auto_router/edit_auto_router_modal.test.tsx index a4921fcfcb5..96e8549eac8 100644 --- a/ui/litellm-dashboard/src/components/edit_auto_router/edit_auto_router_modal.test.tsx +++ b/ui/litellm-dashboard/src/components/edit_auto_router/edit_auto_router_modal.test.tsx @@ -364,7 +364,7 @@ describe("EditAutoRouterModal assistant turns", () => { }); }); -describe("EditAutoRouterModal session affinity", () => { +describe("EditAutoRouterModal classification frequency", () => { beforeEach(() => { modelPatchUpdateCall.mockClear(); }); @@ -381,15 +381,15 @@ describe("EditAutoRouterModal session affinity", () => { />, ); - // A stored config with no session_affinity key now runs with affinity OFF, because the backend - // field defaults to False. The toggle has to render what the router actually does, and an - // untouched save must not flip it. - it("shows a stored config with no session_affinity key as off", async () => { + // A stored config with neither key now runs with affinity OFF, because both backend fields + // default that way. The picker has to render what the router actually does, and an untouched + // save must not flip it. + it("shows a stored config with neither key as every request", async () => { const user = userEvent.setup(); renderWithStoredConfig(STORED_CONFIG); - await user.click(await screen.findByText("Advanced: Affinity")); - expect(await screen.findByRole("switch", { name: "Pin a session to its first model" })).not.toBeChecked(); + await user.click(await screen.findByText("Advanced: Classification Method")); + expect(await screen.findByRole("radio", { name: /Every request/ })).toBeChecked(); await user.click(screen.getByRole("button", { name: /save changes/i })); @@ -397,12 +397,12 @@ describe("EditAutoRouterModal session affinity", () => { expect(savedConfig().session_affinity).toBe(false); }); - it("shows a stored session_affinity=true as on and preserves it through an untouched save", async () => { + it("shows a stored session_affinity=true as once per session and preserves it through an untouched save", async () => { const user = userEvent.setup(); renderWithStoredConfig({ ...STORED_CONFIG, session_affinity: true }); - await user.click(await screen.findByText("Advanced: Affinity")); - expect(await screen.findByRole("switch", { name: "Pin a session to its first model" })).toBeChecked(); + await user.click(await screen.findByText("Advanced: Classification Method")); + expect(await screen.findByRole("radio", { name: /Once per session/ })).toBeChecked(); await user.click(screen.getByRole("button", { name: /save changes/i })); @@ -410,12 +410,12 @@ describe("EditAutoRouterModal session affinity", () => { expect(savedConfig().session_affinity).toBe(true); }); - it("persists turning session affinity on", async () => { + it("persists picking once per session", async () => { const user = userEvent.setup(); renderWithStoredConfig(STORED_CONFIG); - await user.click(await screen.findByText("Advanced: Affinity")); - await user.click(await screen.findByRole("switch", { name: "Pin a session to its first model" })); + await user.click(await screen.findByText("Advanced: Classification Method")); + await user.click(await screen.findByRole("radio", { name: /Once per session/ })); await user.click(screen.getByRole("button", { name: /save changes/i })); @@ -423,18 +423,71 @@ describe("EditAutoRouterModal session affinity", () => { expect(savedConfig().session_affinity).toBe(true); }); - it("persists turning session affinity back off", async () => { + it("persists picking every request back over a stored session pin", async () => { const user = userEvent.setup(); renderWithStoredConfig({ ...STORED_CONFIG, session_affinity: true }); - await user.click(await screen.findByText("Advanced: Affinity")); - await user.click(await screen.findByRole("switch", { name: "Pin a session to its first model" })); + await user.click(await screen.findByText("Advanced: Classification Method")); + await user.click(await screen.findByRole("radio", { name: /Every request/ })); await user.click(screen.getByRole("button", { name: /save changes/i })); await waitFor(() => expect(modelPatchUpdateCall).toHaveBeenCalled()); expect(savedConfig().session_affinity).toBe(false); }); + + it("clears a stored session pin when the operator moves to every new user message", async () => { + const user = userEvent.setup(); + renderWithStoredConfig({ ...STORED_CONFIG, session_affinity: true }); + + await user.click(await screen.findByText("Advanced: Classification Method")); + await user.click(await screen.findByRole("radio", { name: /Every new user message/ })); + + await user.click(screen.getByRole("button", { name: /save changes/i })); + + await waitFor(() => expect(modelPatchUpdateCall).toHaveBeenCalled()); + expect(savedConfig().session_affinity).toBe(false); + expect(savedConfig().classification_mode).toBe("user_turn"); + }); + + it("shows a stored user_turn as selected and preserves it through an untouched save", async () => { + const user = userEvent.setup(); + renderWithStoredConfig({ ...STORED_CONFIG, classification_mode: "user_turn" }); + + await user.click(await screen.findByText("Advanced: Classification Method")); + expect(await screen.findByRole("radio", { name: /Every new user message/ })).toBeChecked(); + + await user.click(screen.getByRole("button", { name: /save changes/i })); + + await waitFor(() => expect(modelPatchUpdateCall).toHaveBeenCalled()); + expect(savedConfig().classification_mode).toBe("user_turn"); + }); + + it("persists switching a stored config to every new user message", async () => { + const user = userEvent.setup(); + renderWithStoredConfig(STORED_CONFIG); + + await user.click(await screen.findByText("Advanced: Classification Method")); + await user.click(await screen.findByRole("radio", { name: /Every new user message/ })); + + await user.click(screen.getByRole("button", { name: /save changes/i })); + + await waitFor(() => expect(modelPatchUpdateCall).toHaveBeenCalled()); + expect(savedConfig().classification_mode).toBe("user_turn"); + }); + + it("rewrites the stored mode to every_request when the operator picks it back", async () => { + const user = userEvent.setup(); + renderWithStoredConfig({ ...STORED_CONFIG, classification_mode: "user_turn" }); + + await user.click(await screen.findByText("Advanced: Classification Method")); + await user.click(await screen.findByRole("radio", { name: /Every request/ })); + + await user.click(screen.getByRole("button", { name: /save changes/i })); + + await waitFor(() => expect(modelPatchUpdateCall).toHaveBeenCalled()); + expect(savedConfig().classification_mode).toBe("every_request"); + }); }); describe("EditAutoRouterModal deployment affinity", () => { diff --git a/ui/litellm-dashboard/src/components/edit_auto_router/edit_auto_router_modal.tsx b/ui/litellm-dashboard/src/components/edit_auto_router/edit_auto_router_modal.tsx index 4751c2e64b7..e18582f77a0 100644 --- a/ui/litellm-dashboard/src/components/edit_auto_router/edit_auto_router_modal.tsx +++ b/ui/litellm-dashboard/src/components/edit_auto_router/edit_auto_router_modal.tsx @@ -96,11 +96,13 @@ export interface StoredComplexityRouterConfig { classifier_context_budget_chars?: unknown; classifier_context_include_assistant_turns?: unknown; classifier_fallback?: unknown; + classification_mode?: unknown; tier_boundaries?: unknown; token_thresholds?: unknown; dimension_weights?: unknown; reasoning_override_min_score?: unknown; session_affinity?: unknown; + modality_routing?: unknown; deployment_affinity?: unknown; adaptive?: boolean; adaptive_weights?: AdaptiveRouterWeights; @@ -165,12 +167,17 @@ export const hydrateComplexityRouterConfig = ( typeof parsedConfig.heuristic_first_max_tier === "string" && parsedConfig.heuristic_first_max_tier.trim() !== "" ? parsedConfig.heuristic_first_max_tier : undefined, + classification_mode: + parsedConfig.classification_mode === "user_turn" || parsedConfig.classification_mode === "every_request" + ? parsedConfig.classification_mode + : undefined, tier_boundaries: hydrateTierBoundaries(parsedConfig.tier_boundaries), token_thresholds: hydrateTokenThresholds(parsedConfig.token_thresholds), dimension_weights: hydrateDimensionWeights(parsedConfig.dimension_weights), reasoning_override_min_score: hydrateReasoningOverrideMinScore(parsedConfig.reasoning_override_min_score), session_affinity: typeof parsedConfig.session_affinity === "boolean" ? parsedConfig.session_affinity : DEFAULT_SESSION_AFFINITY, + modality_routing: typeof parsedConfig.modality_routing === "boolean" ? parsedConfig.modality_routing : false, deployment_affinity: typeof parsedConfig.deployment_affinity === "boolean" ? parsedConfig.deployment_affinity @@ -207,7 +214,9 @@ export const MANAGED_COMPLEXITY_ROUTER_KEYS = new Set([ "classifier_fallback", "classification_prompt", "heuristic_first_max_tier", + "classification_mode", "session_affinity", + "modality_routing", "deployment_affinity", "adaptive", "adaptive_weights", @@ -294,6 +303,7 @@ export const buildUpdatedComplexityRouterConfig = ( planModeMinTier: value.plan_mode_min_tier, classificationPrompt: value.classification_prompt, heuristicFirstMaxTier: value.heuristic_first_max_tier, + classificationMode: value.classification_mode, tierLabels: value.tier_labels, classifierType: value.classifier_type, classifierLlmConfig: value.classifier_llm_config, @@ -302,6 +312,7 @@ export const buildUpdatedComplexityRouterConfig = ( classifierContextIncludeAssistantTurns: value.classifier_context_include_assistant_turns, classifierFallback: value.classifier_fallback, sessionAffinity: value.session_affinity ?? DEFAULT_SESSION_AFFINITY, + modalityRouting: value.modality_routing ?? false, deploymentAffinity: value.deployment_affinity ?? DEFAULT_DEPLOYMENT_AFFINITY, customTechnicalKeywords: customTechnicalKeywords ?? [], keywordTierRules: keywordMatching?.keywordTierRules ?? [], diff --git a/ui/litellm-dashboard/src/components/molecules/cost_optimization_feedback_banner.test.tsx b/ui/litellm-dashboard/src/components/molecules/cost_optimization_feedback_banner.test.tsx index bad92555bd5..3fc1d41dfdd 100644 --- a/ui/litellm-dashboard/src/components/molecules/cost_optimization_feedback_banner.test.tsx +++ b/ui/litellm-dashboard/src/components/molecules/cost_optimization_feedback_banner.test.tsx @@ -1,4 +1,4 @@ -import { fireEvent, render } from "@testing-library/react"; +import { fireEvent, render, screen } from "@testing-library/react"; import { beforeEach, describe, expect, it } from "vitest"; import CostOptimizationFeedbackBanner from "./cost_optimization_feedback_banner"; @@ -10,24 +10,24 @@ describe("CostOptimizationFeedbackBanner", () => { }); it("renders with a link to the feedback discussion", () => { - const { getByText } = render(); - const link = getByText("Share Feedback").closest("a"); + render(); + const link = screen.getByText("Share Feedback").closest("a"); expect(link).toHaveAttribute("href", "https://github.com/BerriAI/litellm/discussions/32172"); }); it("hides itself and persists the dismissal when the dismiss button is clicked", () => { - const { getByText, queryByText, getByLabelText } = render(); - expect(getByText("Help shape cost optimization")).toBeInTheDocument(); + render(); + expect(screen.getByText("Help shape cost optimization")).toBeInTheDocument(); - fireEvent.click(getByLabelText("Dismiss banner")); + fireEvent.click(screen.getByLabelText("Dismiss banner")); - expect(queryByText("Help shape cost optimization")).not.toBeInTheDocument(); + expect(screen.queryByText("Help shape cost optimization")).not.toBeInTheDocument(); expect(localStorage.getItem(STORAGE_KEY)).toBe("true"); }); it("stays dismissed on remount once persisted", () => { localStorage.setItem(STORAGE_KEY, "true"); - const { queryByText } = render(); - expect(queryByText("Help shape cost optimization")).not.toBeInTheDocument(); + render(); + expect(screen.queryByText("Help shape cost optimization")).not.toBeInTheDocument(); }); }); diff --git a/ui/litellm-dashboard/src/components/organization/organization_view.test.tsx b/ui/litellm-dashboard/src/components/organization/organization_view.test.tsx index b8d8e3ba9c8..700d19eb13c 100644 --- a/ui/litellm-dashboard/src/components/organization/organization_view.test.tsx +++ b/ui/litellm-dashboard/src/components/organization/organization_view.test.tsx @@ -108,7 +108,7 @@ beforeEach(() => { test("renders organization view after loading data", async () => { mockUseOrganization.mockReturnValue({ data: mockOrg, isLoading: false } as any); - const { findAllByText } = renderWithProviders( + renderWithProviders( {}} @@ -120,7 +120,7 @@ test("renders organization view after loading data", async () => { />, ); - const [orgName] = await findAllByText("Acme Corp"); + const [orgName] = await screen.findAllByText("Acme Corp"); expect(orgName).toBeInTheDocument(); }); diff --git a/ui/litellm-dashboard/src/components/settings.test.tsx b/ui/litellm-dashboard/src/components/settings.test.tsx index b97fef32402..762b23f413e 100644 --- a/ui/litellm-dashboard/src/components/settings.test.tsx +++ b/ui/litellm-dashboard/src/components/settings.test.tsx @@ -77,21 +77,21 @@ describe("Settings", () => { }); it("should render the logging callbacks tab when access token is provided", async () => { - const { getByText } = render(); + render(); await waitFor(() => { - expect(getByText("Active Logging Callbacks")).toBeInTheDocument(); + expect(screen.getByText("Active Logging Callbacks")).toBeInTheDocument(); }); }); it("should display additional settings tabs", async () => { - const { getByText } = render(); + render(); await waitFor(() => { - expect(getByText("CloudZero Cost Tracking")).toBeInTheDocument(); - expect(getByText("Alerting Types")).toBeInTheDocument(); - expect(getByText("Alerting Settings")).toBeInTheDocument(); - expect(getByText("Email Alerts")).toBeInTheDocument(); + expect(screen.getByText("CloudZero Cost Tracking")).toBeInTheDocument(); + expect(screen.getByText("Alerting Types")).toBeInTheDocument(); + expect(screen.getByText("Alerting Settings")).toBeInTheDocument(); + expect(screen.getByText("Email Alerts")).toBeInTheDocument(); }); }); @@ -279,13 +279,13 @@ describe("Settings", () => { }); it("should display CloudZero Cost Tracking tab", async () => { - const { getByText } = render(); + render(); await waitFor(() => { - expect(getByText("Active Logging Callbacks")).toBeInTheDocument(); + expect(screen.getByText("Active Logging Callbacks")).toBeInTheDocument(); }); - expect(getByText("CloudZero Cost Tracking")).toBeInTheDocument(); + expect(screen.getByText("CloudZero Cost Tracking")).toBeInTheDocument(); }); }); diff --git a/ui/litellm-dashboard/src/components/shared/DataTable/DataTable.test.tsx b/ui/litellm-dashboard/src/components/shared/DataTable/DataTable.test.tsx index 58a0cd94997..7ead9bb64d4 100644 --- a/ui/litellm-dashboard/src/components/shared/DataTable/DataTable.test.tsx +++ b/ui/litellm-dashboard/src/components/shared/DataTable/DataTable.test.tsx @@ -1,5 +1,5 @@ import type { ColumnDef, ExpandedState } from "@tanstack/react-table"; -import { render, screen, waitFor } from "@testing-library/react"; +import { render, screen, waitFor, within } from "@testing-library/react"; import userEvent from "@testing-library/user-event"; import { useState } from "react"; import { describe, expect, it, vi } from "vitest"; @@ -21,6 +21,12 @@ function person(id: string, name: string, flagged = false): Person { const names = (): (string | null)[] => screen.getAllByTestId("name-cell").map((el) => el.textContent); +const heightClassesOf = (el: HTMLElement | undefined): string[] => + (el?.className ?? "") + .split(/\s+/) + .filter((cls) => cls.startsWith("h-")) + .sort(); + const nameCellColumns: ColumnDef[] = [ { accessorKey: "name", @@ -229,12 +235,10 @@ describe("DataTable sorting", () => { describe("DataTable layout", () => { it("stretches the table to fill the container when resizing is on, so hidden columns leave no right-side gap", () => { - const { container } = render(); + render(); - const table = container.querySelector("table"); - expect(table).not.toBeNull(); // width pins the natural column total (horizontal scroll on overflow); minWidth:100% fills the gap on underflow. - expect(table?.style.minWidth).toBe("100%"); + expect(screen.getByRole("table")).toHaveStyle({ minWidth: "100%" }); }); }); @@ -354,17 +358,21 @@ describe("DataTable loading", () => { const { rerender } = render( , ); - const skeletonRow = screen.getAllByTestId("skeleton-row").at(0); - const loadedRowHeight = "h-8"; - expect(skeletonRow?.className).toContain(loadedRowHeight); + const skeletonHeight = heightClassesOf(screen.getAllByRole("row").at(-1)); rerender(); - expect(document.querySelector("[data-row-id]")?.className).toContain(loadedRowHeight); + const loadedHeight = heightClassesOf(screen.getByRole("row", { name: /Charlie/ })); + + expect(loadedHeight).not.toEqual([]); + expect(skeletonHeight).toEqual(loadedHeight); }); it("does not force the compact height on default-size skeleton rows", () => { - render(); - expect(screen.getAllByTestId("skeleton-row").at(0)?.className).not.toContain("h-8"); + const { rerender } = render(); + const skeletonHeight = heightClassesOf(screen.getAllByRole("row").at(-1)); + + rerender(); + expect(heightClassesOf(screen.getAllByRole("row").at(-1))).not.toEqual(skeletonHeight); }); it("varies skeleton shape and width per column instead of one fixed bar", () => { @@ -420,7 +428,7 @@ describe("DataTable loading", () => { describe("DataTable column visibility", () => { it("hides a column when toggled off in the view-options menu", async () => { const user = userEvent.setup(); - const { container } = render( + render( { />, ); - expect(container.querySelector('th[data-header-id="email"]')).not.toBeNull(); + expect(screen.getByRole("columnheader", { name: "Email" })).toBeInTheDocument(); await user.click(screen.getByTestId("view-options-trigger")); await user.click(await screen.findByTestId("view-option-email")); - await waitFor(() => expect(container.querySelector('th[data-header-id="email"]')).toBeNull()); + await waitFor(() => expect(screen.queryByRole("columnheader", { name: "Email" })).not.toBeInTheDocument()); await user.click(screen.getByTestId("view-option-email")); - await waitFor(() => expect(container.querySelector('th[data-header-id="email"]')).not.toBeNull()); + expect(await screen.findByRole("columnheader", { name: "Email" })).toBeInTheDocument(); }); it("omits columns that opt out of hiding from the menu", async () => { @@ -468,14 +476,10 @@ describe("DataTable column visibility", () => { describe("DataTable pinned columns", () => { it("applies sticky positioning to a pinned column only", () => { - const { container } = render(); + render(); - const pinnedHead = container.querySelector('th[data-header-id="name"]'); - const normalHead = container.querySelector('th[data-header-id="email"]'); - - expect(pinnedHead?.style.position).toBe("sticky"); - expect(pinnedHead?.style.left).toBe("0px"); - expect(normalHead?.style.position).toBe(""); + expect(screen.getByRole("columnheader", { name: "Name" })).toHaveStyle({ position: "sticky", left: "0px" }); + expect(screen.getByRole("columnheader", { name: "Email" })).not.toHaveStyle({ position: "sticky" }); }); }); @@ -570,7 +574,7 @@ describe("DataTable expansion", () => { describe("DataTable row styling and footer", () => { it("applies rowClassName to the matching row only", () => { const data = [person("a", "Alice", true), person("b", "Bob", false)]; - const { container } = render( + render( { />, ); - expect(container.querySelector('tr[data-row-id="a"]')?.className).toContain("flagged-row"); - expect(container.querySelector('tr[data-row-id="b"]')?.className).not.toContain("flagged-row"); + expect(screen.getByRole("row", { name: /Alice/ })).toHaveClass("flagged-row"); + expect(screen.getByRole("row", { name: /Bob/ })).not.toHaveClass("flagged-row"); }); it("renders the footer slot inside a tfoot element", () => { @@ -596,63 +600,57 @@ describe("DataTable row styling and footer", () => { />, ); - expect(screen.getByTestId("footer-row").closest("tfoot")).not.toBeNull(); + const rowGroups = screen.getAllByRole("rowgroup"); + expect(within(rowGroups.at(-1) as HTMLElement).getByText("Total: 3")).toBeInTheDocument(); }); }); describe("DataTable layout", () => { it("exposes resize handles with stable selectors only when resizing is enabled", () => { - const { container, rerender } = render( - , - ); - expect(container.querySelectorAll("[data-resizer][data-header-id]").length).toBe(2); + const { rerender } = render(); + expect(screen.getByTestId("column-resizer-name")).toBeInTheDocument(); + expect(screen.getByTestId("column-resizer-email")).toBeInTheDocument(); rerender(); - expect(container.querySelectorAll("[data-resizer]").length).toBe(0); + expect(screen.queryByTestId("column-resizer-name")).not.toBeInTheDocument(); }); it("makes the header sticky and constrains body height when maxBodyHeight is set", () => { - const { container } = render(); - expect(container.querySelector("thead")?.className).toContain("sticky"); - const scroller = container.querySelector('[data-slot="table-container"]')?.parentElement as HTMLElement; - expect(scroller).toHaveStyle({ maxHeight: "240px" }); + render(); + expect(screen.getByTestId("data-table-head")).toHaveClass("sticky"); + expect(screen.getByTestId("data-table-scroller")).toHaveStyle({ maxHeight: "240px" }); }); it("caps fillHeight at the parent's height instead of stretching to it, so a short table stays short", () => { - const { container } = render(); - const scroller = container.querySelector('[data-slot="table-container"]')?.parentElement as HTMLElement; - const frame = scroller.parentElement as HTMLElement; - const outer = frame.parentElement as HTMLElement; + render(); + const outer = screen.getByTestId("data-table-root"); + const frame = screen.getByTestId("data-table-frame"); + const scroller = screen.getByTestId("data-table-scroller"); // A ceiling, not a stretch: flex-1 here would hold the footer at the bottom on a two-row table. - expect(outer.className).toContain("max-h-full"); - expect(outer.className).not.toContain("flex-1"); - expect(frame.className).not.toContain("flex-1"); - expect(scroller.className).not.toContain("flex-1"); + expect(outer).toHaveClass("max-h-full", "flex-col"); + expect(outer).not.toHaveClass("flex-1"); + expect(frame).toHaveClass("flex-col"); + expect(frame).not.toHaveClass("flex-1"); + expect(scroller).not.toHaveClass("flex-1"); - expect(outer.className).toContain("flex-col"); - expect(frame.className).toContain("flex-col"); - expect(scroller.className).toContain("min-h-0"); - expect(scroller.className).toContain("overflow-auto"); + expect(scroller).toHaveClass("min-h-0", "overflow-auto"); expect(scroller).toHaveStyle({ maxHeight: "" }); // Without this the Table primitive's own overflow container captures the sticky header. - expect(scroller.className).toContain("[&_[data-slot=table-container]]:overflow-visible"); + expect(scroller).toHaveClass("[&_[data-slot=table-container]]:overflow-visible"); - const thead = container.querySelector("thead") as HTMLElement; - expect(thead.className).toContain("sticky"); // Rows pass under the header, so the semi-transparent row tint alone would let them show through. - expect(thead.className).toContain("bg-background"); + expect(screen.getByTestId("data-table-head")).toHaveClass("sticky", "bg-background"); }); it("leaves the default layout untouched when neither height mode is set", () => { - const { container } = render(); - const scroller = container.querySelector('[data-slot="table-container"]')?.parentElement as HTMLElement; + render(); + const scroller = screen.getByTestId("data-table-scroller"); - expect(scroller.className).toContain("overflow-x-auto"); - expect(scroller.className).not.toContain("min-h-0"); + expect(scroller).toHaveClass("overflow-x-auto"); + expect(scroller).not.toHaveClass("min-h-0"); expect(scroller).toHaveStyle({ maxHeight: "" }); - expect((scroller.parentElement as HTMLElement).className).not.toContain("flex-col"); - expect(container.querySelector("thead")?.className).not.toContain("sticky"); - expect(container.querySelector("thead")?.className).not.toContain("bg-background"); + expect(screen.getByTestId("data-table-frame")).not.toHaveClass("flex-col"); + expect(screen.getByTestId("data-table-head")).not.toHaveClass("sticky", "bg-background"); }); }); diff --git a/ui/litellm-dashboard/src/components/shared/DataTable/DataTable.tsx b/ui/litellm-dashboard/src/components/shared/DataTable/DataTable.tsx index e8357b37715..60267606951 100644 --- a/ui/litellm-dashboard/src/components/shared/DataTable/DataTable.tsx +++ b/ui/litellm-dashboard/src/components/shared/DataTable/DataTable.tsx @@ -195,8 +195,7 @@ function DataTableHeadCell({ header, size, stickyHeader, enableColumnResi )} {canResize && (
column.resetSize()} @@ -589,15 +588,19 @@ export function DataTable(props: DataTableProps -
+
+
{toolbar !== undefined &&
{toolbar(table)}
}
- + {table.getHeaderGroups().map((headerGroup) => ( {headerGroup.headers.map((header) => ( diff --git a/ui/litellm-dashboard/src/components/shared/PaginationStatusAlerts.test.tsx b/ui/litellm-dashboard/src/components/shared/PaginationStatusAlerts.test.tsx index 3698b68155e..5bd48b1aa4c 100644 --- a/ui/litellm-dashboard/src/components/shared/PaginationStatusAlerts.test.tsx +++ b/ui/litellm-dashboard/src/components/shared/PaginationStatusAlerts.test.tsx @@ -1,4 +1,4 @@ -import { fireEvent, render } from "@testing-library/react"; +import { fireEvent, render, screen } from "@testing-library/react"; import { describe, expect, it, vi } from "vitest"; import PaginationStatusAlerts from "./PaginationStatusAlerts"; @@ -6,7 +6,7 @@ import PaginationStatusAlerts from "./PaginationStatusAlerts"; describe("PaginationStatusAlerts", () => { it("shows page progress and wires the Stop button while fetching", () => { const cancel = vi.fn(); - const { getByRole, getByText } = render( + render( { />, ); - expect(getByText(/Currently fetching spend data: fetched 7 \/ 42 pages/)).toBeInTheDocument(); - fireEvent.click(getByRole("button", { name: "Stop" })); + expect(screen.getByText(/Currently fetching spend data: fetched 7 \/ 42 pages/)).toBeInTheDocument(); + fireEvent.click(screen.getByRole("button", { name: "Stop" })); expect(cancel).toHaveBeenCalledTimes(1); }); it("shows the partial-data notice after a cancel, frozen at the last fetched page", () => { - const { getByText } = render( + render( { />, ); - expect(getByText("Showing partial spend data (7/42 pages loaded)")).toBeInTheDocument(); + expect(screen.getByText("Showing partial spend data (7/42 pages loaded)")).toBeInTheDocument(); }); it("names the subject it is fetching", () => { - const { getByText } = render( + render( { />, ); - expect(getByText(/Currently fetching agent data: fetched 1 \/ 3 pages/)).toBeInTheDocument(); + expect(screen.getByText(/Currently fetching agent data: fetched 1 \/ 3 pages/)).toBeInTheDocument(); }); it("renders nothing when idle", () => { diff --git a/ui/litellm-dashboard/src/components/shared/charts/area_chart.test.tsx b/ui/litellm-dashboard/src/components/shared/charts/area_chart.test.tsx index 6e4ab14be33..c81ade526dd 100644 --- a/ui/litellm-dashboard/src/components/shared/charts/area_chart.test.tsx +++ b/ui/litellm-dashboard/src/components/shared/charts/area_chart.test.tsx @@ -1,4 +1,4 @@ -import { render } from "@testing-library/react"; +import { render, screen } from "@testing-library/react"; import React from "react"; import { describe, expect, it } from "vitest"; import { AreaChart } from "./area_chart"; @@ -21,9 +21,9 @@ describe("AreaChart", () => { }); it("renders the No data placeholder instead of a chart when data is empty", () => { - const { container, getByText } = render(); + const { container } = render(); - expect(getByText("No data")).toBeInTheDocument(); + expect(screen.getByText("No data")).toBeInTheDocument(); expect(container.querySelector('[data-slot="chart"]')).toBeNull(); }); diff --git a/ui/litellm-dashboard/src/components/shared/charts/bar_chart.test.tsx b/ui/litellm-dashboard/src/components/shared/charts/bar_chart.test.tsx index a322eeb3ad0..3cd7bd2fd08 100644 --- a/ui/litellm-dashboard/src/components/shared/charts/bar_chart.test.tsx +++ b/ui/litellm-dashboard/src/components/shared/charts/bar_chart.test.tsx @@ -21,9 +21,9 @@ describe("BarChart", () => { }); it("renders the No data placeholder instead of a chart when data is empty", () => { - const { container, getByText } = render(); + const { container } = render(); - expect(getByText("No data")).toBeInTheDocument(); + expect(screen.getByText("No data")).toBeInTheDocument(); expect(container.querySelector('[data-slot="chart"]')).toBeNull(); }); diff --git a/ui/litellm-dashboard/src/components/templates/KeyInfoView.handleKeyUpdate.test.tsx b/ui/litellm-dashboard/src/components/templates/KeyInfoView.handleKeyUpdate.test.tsx index 6592ff8c357..705679fe2e6 100644 --- a/ui/litellm-dashboard/src/components/templates/KeyInfoView.handleKeyUpdate.test.tsx +++ b/ui/litellm-dashboard/src/components/templates/KeyInfoView.handleKeyUpdate.test.tsx @@ -445,7 +445,7 @@ describe("KeyInfoView handleKeyUpdate budget_duration", () => { ); fireEvent.click(screen.getByText("Settings")); - expect(screen.getByText("Budget Reset").parentElement?.textContent).toContain("Every 30d"); + expect(screen.getByTestId("budget-reset-value")).toHaveTextContent("Every 30d"); fireEvent.click(screen.getByText("Edit Settings")); (globalThis as any).__TEST_FORM_VALUES = { @@ -456,7 +456,7 @@ describe("KeyInfoView handleKeyUpdate budget_duration", () => { fireEvent.click(screen.getByText("Mock Submit")); await waitFor(() => { - expect(screen.getByText("Budget Reset").parentElement?.textContent).toBe("Budget ResetNever"); + expect(screen.getByTestId("budget-reset-value")).toHaveTextContent("Never"); }); }); }); diff --git a/ui/litellm-dashboard/src/components/templates/key_edit_view.test.tsx b/ui/litellm-dashboard/src/components/templates/key_edit_view.test.tsx index bf8f43b8b5f..97b09e00808 100644 --- a/ui/litellm-dashboard/src/components/templates/key_edit_view.test.tsx +++ b/ui/litellm-dashboard/src/components/templates/key_edit_view.test.tsx @@ -1,7 +1,7 @@ import { fireEvent, screen, waitFor } from "@testing-library/react"; import userEvent from "@testing-library/user-event"; import { beforeEach, describe, expect, it, vi } from "vitest"; -import { renderWithProviders } from "../../../tests/test-utils"; +import { chooseSelectOption, renderWithProviders } from "../../../tests/test-utils"; import { KeyResponse } from "../key_team_helpers/key_list"; import { MODEL_MAX_BUDGET_PREMIUM_HINT } from "../key_team_helpers/ModelMaxBudgetEditor"; import { @@ -300,7 +300,7 @@ describe("KeyEditView", () => { }); it("should render", async () => { - const { getByText } = renderWithProviders( + renderWithProviders( {}} @@ -313,12 +313,12 @@ describe("KeyEditView", () => { ); await waitFor(() => { - expect(getByText("Save Changes")).toBeInTheDocument(); + expect(screen.getByText("Save Changes")).toBeInTheDocument(); }); }); it("should render tags", async () => { - const { getByText } = renderWithProviders( + renderWithProviders( {}} @@ -331,12 +331,12 @@ describe("KeyEditView", () => { ); await waitFor(() => { - expect(getByText("test-tag")).toBeInTheDocument(); + expect(screen.getByText("test-tag")).toBeInTheDocument(); }); }); it("should not render tags in metadata textarea", async () => { - const { getByLabelText } = renderWithProviders( + renderWithProviders( {}} @@ -348,7 +348,7 @@ describe("KeyEditView", () => { />, ); - const metadataTextarea = getByLabelText("Metadata") as HTMLTextAreaElement; + const metadataTextarea = screen.getByLabelText("Metadata") as HTMLTextAreaElement; await waitFor(() => { expect(metadataTextarea).toHaveValue("{}"); }); @@ -963,10 +963,7 @@ describe("KeyEditView", () => { />, ); - await userEvent.click(await screen.findByLabelText("Reset Budget")); - - const weeklyOption = await screen.findByText("weekly"); - await userEvent.click(weeklyOption); + await chooseSelectOption(userEvent, await screen.findByLabelText("Reset Budget"), "weekly"); const submitButton = screen.getByRole("button", { name: /save changes/i }); await userEvent.click(submitButton); @@ -1042,8 +1039,7 @@ describe("KeyEditView", () => { ); const resetBudget = await screen.findByLabelText("Reset Budget"); - await userEvent.click(resetBudget); - await userEvent.click(await screen.findByText("Never resets")); + await chooseSelectOption(userEvent, resetBudget, "Never resets"); await waitFor(() => { expect(resetBudget).toHaveTextContent("Never resets"); @@ -1074,8 +1070,7 @@ describe("KeyEditView", () => { />, ); - await userEvent.click(await screen.findByLabelText("Reset Budget")); - await userEvent.click(await screen.findByText("Never resets")); + await chooseSelectOption(userEvent, await screen.findByLabelText("Reset Budget"), "Never resets"); await userEvent.click(screen.getByRole("button", { name: /save changes/i })); @@ -1946,8 +1941,7 @@ describe("KeyEditView", () => { await userEvent.clear(duration); await userEvent.type(duration, "45d"); - await userEvent.click(screen.getByLabelText(/TPM Rate Limit Type/)); - await userEvent.click(await screen.findByTitle("Guaranteed throughput")); + await chooseSelectOption(userEvent, screen.getByLabelText(/TPM Rate Limit Type/), /^Guaranteed throughput/); await userEvent.click(screen.getByRole("button", { name: /save changes/i })); @@ -2103,8 +2097,7 @@ describe("KeyEditView", () => { renderForPayload(onSubmitMock); await screen.findByRole("button", { name: /save changes/i }); - await userEvent.click(screen.getByLabelText(/RPM Rate Limit Type/)); - await userEvent.click(await screen.findByTitle("Guaranteed throughput")); + await chooseSelectOption(userEvent, screen.getByLabelText(/RPM Rate Limit Type/), /^Guaranteed throughput/); await userEvent.click(screen.getByRole("button", { name: /save changes/i })); diff --git a/ui/litellm-dashboard/src/components/templates/key_info_view.budget_display.test.tsx b/ui/litellm-dashboard/src/components/templates/key_info_view.budget_display.test.tsx index f506c0e51d7..a02f80f7800 100644 --- a/ui/litellm-dashboard/src/components/templates/key_info_view.budget_display.test.tsx +++ b/ui/litellm-dashboard/src/components/templates/key_info_view.budget_display.test.tsx @@ -381,6 +381,6 @@ describe("KeyInfoView budget reset visibility", () => { await waitFor(() => { expect(screen.getByText("Budget Reset")).toBeInTheDocument(); }); - expect(screen.getByText("Budget Reset").parentElement).toHaveTextContent("Never"); + expect(screen.getByTestId("budget-reset-value")).toHaveTextContent("Never"); }); }); diff --git a/ui/litellm-dashboard/src/components/templates/key_info_view.tsx b/ui/litellm-dashboard/src/components/templates/key_info_view.tsx index 0be80c3e173..0dd0dd6d6af 100644 --- a/ui/litellm-dashboard/src/components/templates/key_info_view.tsx +++ b/ui/litellm-dashboard/src/components/templates/key_info_view.tsx @@ -895,7 +895,7 @@ export default function KeyInfoView({

Budget Reset

-

+

{currentKeyData.budget_reset_at ? `${currentKeyData.budget_duration ? `Every ${currentKeyData.budget_duration}, next ` : ""}${formatTimestamp(currentKeyData.budget_reset_at)}` : "Never"} diff --git a/ui/litellm-dashboard/src/components/ui/field.test.tsx b/ui/litellm-dashboard/src/components/ui/field.test.tsx index 4bb3d0ec665..5765a637526 100644 --- a/ui/litellm-dashboard/src/components/ui/field.test.tsx +++ b/ui/litellm-dashboard/src/components/ui/field.test.tsx @@ -14,6 +14,7 @@ import { FieldSet, FieldTitle, } from "./field"; +import { ROW_LAYOUT_CLASSES, STRETCH_CHILDREN_CLASS } from "../../../tests/fieldOrientation"; describe("FieldError", () => { it("renders nothing when there are no errors and no children", () => { @@ -85,6 +86,20 @@ describe("Field", () => { expect(screen.getByRole("group")).toHaveAttribute("data-orientation", "horizontal"); }); + + it("stretches every child when vertical, which is what inputs, selects and textareas want", () => { + render(); + + expect(screen.getByRole("group")).toHaveClass("flex-col", STRETCH_CHILDREN_CLASS); + }); + + it("lays children in a row at their own width when horizontal, so a checkbox stays square", () => { + render(); + const field = screen.getByRole("group"); + + expect(field).toHaveClass(...ROW_LAYOUT_CLASSES); + expect(field).not.toHaveClass(STRETCH_CHILDREN_CLASS); + }); }); describe("field primitives forward refs to their DOM node", () => { diff --git a/ui/litellm-dashboard/src/lib/autorouter_presets.test.ts b/ui/litellm-dashboard/src/lib/autorouter_presets.test.ts index f14d6279e32..2a8306473b8 100644 --- a/ui/litellm-dashboard/src/lib/autorouter_presets.test.ts +++ b/ui/litellm-dashboard/src/lib/autorouter_presets.test.ts @@ -129,6 +129,18 @@ describe("autorouter_presets", () => { } }); + it("carries a preset's modality_routing into the prefilled form state", () => { + const preset = getPresetByKey("anthropic_family")!; + const withFlag = { ...preset.complexity_router_config, modality_routing: true }; + const prefill = buildPresetPrefill(withFlag, groupsOnly(getRequiredModelsInPreset(preset))); + expect(prefill.complexityRouterConfig.modality_routing).toBe(true); + const withoutFlag = buildPresetPrefill( + preset.complexity_router_config, + groupsOnly(getRequiredModelsInPreset(preset)), + ); + expect(withoutFlag.complexityRouterConfig.modality_routing).toBe(false); + }); + it("prefills the anthropic preset's effort through to tier_model_params", () => { const preset = getPresetByKey("anthropic_family")!; const prefill = buildPresetPrefill(preset.complexity_router_config, groupsOnly(getRequiredModelsInPreset(preset))); @@ -230,6 +242,7 @@ describe("autorouter_presets", () => { const config = { tiers: { SIMPLE: [presetModel], MEDIUM: [], COMPLEX: [], REASONING: [] }, classifier_type: "heuristic" as const, + classification_mode: "every_request" as const, session_affinity: false, deployment_affinity: true, }; @@ -273,6 +286,7 @@ describe("autorouter_presets", () => { const config = { tiers: { SIMPLE: ["claude-opus-5"], MEDIUM: [], COMPLEX: [], REASONING: [] }, classifier_type: "heuristic" as const, + classification_mode: "every_request" as const, session_affinity: false, deployment_affinity: true, }; @@ -287,6 +301,7 @@ describe("autorouter_presets", () => { const config = { tiers: { SIMPLE: ["claude-opus-5"], MEDIUM: [], COMPLEX: [], REASONING: [] }, classifier_type: "heuristic" as const, + classification_mode: "every_request" as const, session_affinity: false, deployment_affinity: true, }; @@ -320,6 +335,7 @@ describe("autorouter_presets", () => { const simpleTierConfig = (presetModel: string) => ({ tiers: { SIMPLE: [presetModel], MEDIUM: [], COMPLEX: [], REASONING: [] }, classifier_type: "heuristic" as const, + classification_mode: "every_request" as const, session_affinity: false, deployment_affinity: true, }); @@ -563,6 +579,7 @@ describe("autorouter_presets", () => { const config = { tiers: { SIMPLE: ["gpt-5-nano"], MEDIUM: [], COMPLEX: [], REASONING: [] }, classifier_type: "heuristic" as const, + classification_mode: "every_request" as const, session_affinity: false, deployment_affinity: true, match_threshold: 0, @@ -578,6 +595,7 @@ describe("autorouter_presets", () => { { tiers: { SIMPLE: ["gpt-5-nano"], MEDIUM: [], COMPLEX: [], REASONING: [] }, classifier_type: "heuristic", + classification_mode: "every_request", session_affinity: false, deployment_affinity: true, enable_context_window_escalation: false, @@ -589,11 +607,29 @@ describe("autorouter_presets", () => { expect(prefill.complexityRouterConfig.context_window_escalation_buffer).toBe(0.9); }); + it("carries a preset's classification_mode and defaults it when the preset omits one", () => { + const tiers = { SIMPLE: ["gpt-5-nano"], MEDIUM: [], COMPLEX: [], REASONING: [] }; + const base = { + tiers, + classifier_type: "heuristic" as const, + classification_mode: "every_request" as const, + session_affinity: false, + deployment_affinity: true, + }; + const availability = groupsOnly(["gpt-5-nano"]); + expect( + buildPresetPrefill({ ...base, classification_mode: "user_turn" }, availability).complexityRouterConfig + .classification_mode, + ).toBe("user_turn"); + expect(buildPresetPrefill(base, availability).complexityRouterConfig.classification_mode).toBe("every_request"); + }); + it("falls back to the defaults when a preset omits match_threshold and escalation_keywords", () => { const prefill = buildPresetPrefill( { tiers: { SIMPLE: ["gpt-5-nano"], MEDIUM: [], COMPLEX: [], REASONING: [] }, classifier_type: "heuristic", + classification_mode: "every_request" as const, session_affinity: false, deployment_affinity: true, }, @@ -610,6 +646,7 @@ describe("autorouter_presets", () => { const base = { tiers: { SIMPLE: ["gpt-5-nano"], MEDIUM: [], COMPLEX: [], REASONING: [] }, classifier_type: "heuristic" as const, + classification_mode: "every_request" as const, session_affinity: false, deployment_affinity: true, }; @@ -625,6 +662,7 @@ describe("autorouter_presets", () => { const config = { tiers: { SIMPLE: ["claude-sonnet-4-5"], MEDIUM: [], COMPLEX: [], REASONING: [] }, classifier_type: "heuristic" as const, + classification_mode: "every_request" as const, session_affinity: false, deployment_affinity: true, }; @@ -639,6 +677,7 @@ describe("autorouter_presets", () => { REASONING: [{ model_name: "o3", litellm_params: { reasoning_effort: "high" } }], }, classifier_type: "heuristic" as const, + classification_mode: "every_request" as const, session_affinity: false, deployment_affinity: true, }; @@ -658,6 +697,7 @@ describe("autorouter_presets", () => { REASONING: [{ model_name: "claude-sonnet-4-5", litellm_params: { reasoning_effort: "high" } }], }, classifier_type: "heuristic" as const, + classification_mode: "every_request" as const, session_affinity: false, deployment_affinity: true, }; @@ -680,6 +720,9 @@ describe("autorouter_presets", () => { ], }, classifier_type: "heuristic" as const, + classification_mode: "every_request" as const, + session_affinity: false, + deployment_affinity: true, }; const prefill = buildPresetPrefill(config, groupsOnly(["claude-sonnet-4.5"])); // temperature survives from the spelling that would otherwise have been overwritten; @@ -693,6 +736,7 @@ describe("autorouter_presets", () => { const config = { tiers: { SIMPLE: ["gpt-5-nano"], MEDIUM: [], COMPLEX: [], REASONING: [] }, classifier_type: "heuristic" as const, + classification_mode: "every_request" as const, session_affinity: false, deployment_affinity: true, }; diff --git a/ui/litellm-dashboard/src/lib/autorouter_presets.ts b/ui/litellm-dashboard/src/lib/autorouter_presets.ts index f96dd5ddb4c..721bd6f2b2a 100644 --- a/ui/litellm-dashboard/src/lib/autorouter_presets.ts +++ b/ui/litellm-dashboard/src/lib/autorouter_presets.ts @@ -6,6 +6,7 @@ import { ComplexityRouterConfigValue, ClassifierType, ClassifierLLMConfig, + DEFAULT_CLASSIFICATION_MODE, DEFAULT_SESSION_AFFINITY, DEFAULT_DEPLOYMENT_AFFINITY, usesLlmClassifier, @@ -288,8 +289,10 @@ export const buildPresetPrefill = ( classifier_context_budget_chars: config.classifier_context_budget_chars, classifier_context_per_turn_chars: config.classifier_context_per_turn_chars, classifier_context_include_assistant_turns: config.classifier_context_include_assistant_turns, + classification_mode: config.classification_mode ?? DEFAULT_CLASSIFICATION_MODE, session_affinity: config.session_affinity ?? DEFAULT_SESSION_AFFINITY, deployment_affinity: config.deployment_affinity ?? DEFAULT_DEPLOYMENT_AFFINITY, + modality_routing: config.modality_routing ?? false, adaptive: config.adaptive, adaptive_weights: config.adaptive_weights, tier_distance_penalty: config.tier_distance_penalty, diff --git a/ui/litellm-dashboard/tests/fieldOrientation.ts b/ui/litellm-dashboard/tests/fieldOrientation.ts new file mode 100644 index 00000000000..49ba5056d66 --- /dev/null +++ b/ui/litellm-dashboard/tests/fieldOrientation.ts @@ -0,0 +1,18 @@ +import { expect } from "vitest"; + +export const ROW_LAYOUT_CLASSES = ["flex-row", "items-center"] as const; +export const STRETCH_CHILDREN_CLASS = "*:w-full"; + +/** + * Asserts a control sits beside its label at its own width instead of being stretched across the + * field. Reaches for the resolved classes because the defect is purely visual: nothing accessible + * distinguishes a square checkbox from a full-width bar. + */ +export const expectControlBesideLabel = (control: HTMLElement): void => { + const field = control.closest('[data-slot="field"]'); + if (field === null) throw new Error("control is not rendered inside a form field"); + + expect(field).toHaveAttribute("data-orientation", "horizontal"); + expect(field).toHaveClass(...ROW_LAYOUT_CLASSES); + expect(field).not.toHaveClass(STRETCH_CHILDREN_CLASS); +}; diff --git a/ui/litellm-dashboard/tests/test-utils.tsx b/ui/litellm-dashboard/tests/test-utils.tsx index 66966201a9c..162b8a3df7b 100644 --- a/ui/litellm-dashboard/tests/test-utils.tsx +++ b/ui/litellm-dashboard/tests/test-utils.tsx @@ -52,7 +52,7 @@ const pointerBlocked = (element: HTMLElement): boolean => { * the option text alone is a race that React 19's flush timing loses. */ export const chooseSelectOption = async ( - user: ReturnType, + user: Pick, "click">, trigger: HTMLElement, optionName: string | RegExp, ) => { diff --git a/uv.lock b/uv.lock index 7df1a35b28a..27be919eea1 100644 --- a/uv.lock +++ b/uv.lock @@ -10,7 +10,7 @@ resolution-markers = [ ] [options] -exclude-newer = "2026-08-26T18:33:25.773031Z" +exclude-newer = "2026-08-29T17:58:57.633306Z" exclude-newer-span = "P3D" [manifest] @@ -4266,7 +4266,7 @@ wheels = [ [[package]] name = "litellm" -version = "1.100.0" +version = "1.101.0" source = { editable = "." } dependencies = [ { name = "aiohttp" }, @@ -4669,12 +4669,12 @@ proxy-dev = [ [[package]] name = "litellm-enterprise" -version = "0.1.62" +version = "0.1.63" source = { editable = "enterprise" } [[package]] name = "litellm-proxy-extras" -version = "0.4.91" +version = "0.4.92" source = { editable = "litellm-proxy-extras" } [[package]]