diff --git a/.github/workflows/test-unit-proxy-db.yml b/.github/workflows/test-unit-proxy-db.yml index 49a36aa23f0..2d4e85630dc 100644 --- a/.github/workflows/test-unit-proxy-db.yml +++ b/.github/workflows/test-unit-proxy-db.yml @@ -218,6 +218,7 @@ jobs: tests/proxy_unit_tests/test_gemini_agents_endpoints.py tests/proxy_unit_tests/test_get_favicon.py tests/proxy_unit_tests/test_get_image.py + tests/proxy_unit_tests/test_reducto_ocr_route.py tests/proxy_unit_tests/test_ui_path_detection.py tests/proxy_unit_tests/test_prompt_test_endpoint.py tests/proxy_unit_tests/test_check_batch_cost.py diff --git a/.github/workflows/test-unit-proxy-mgmt-behavior.yml b/.github/workflows/test-unit-proxy-mgmt-behavior.yml new file mode 100644 index 00000000000..e73997323a4 --- /dev/null +++ b/.github/workflows/test-unit-proxy-mgmt-behavior.yml @@ -0,0 +1,34 @@ +name: "Unit Tests: Proxy Management-Endpoint Behavior Pinning" + +on: + pull_request: + branches: + - main + - litellm_internal_staging + - litellm_oss_branch + - "litellm_**" + +permissions: + contents: read + id-token: write + pull-requests: write + +concurrency: + group: ${{ github.workflow }}-${{ github.event.pull_request.number || github.ref }} + cancel-in-progress: true + +jobs: + proxy-mgmt-behavior: + uses: ./.github/workflows/_test-unit-services-base.yml + with: + test-path: tests/proxy_behavior + # workers=0 (no xdist): the world seed is a single shared Postgres + # state — two xdist workers both call seed_world() and race on the + # ``behavior-pin-budget`` row, producing UniqueViolation + cascading + # missing-membership FK failures. The whole suite is ~7s sequentially, + # so the cost of disabling parallelism here is negligible. + workers: 0 + reruns: 0 + enable-postgres: true + artifact-name: proxy-mgmt-behavior + timeout-minutes: 15 diff --git a/docker/Dockerfile.non_root b/docker/Dockerfile.non_root index 4de4a55981d..2729babb6d6 100644 --- a/docker/Dockerfile.non_root +++ b/docker/Dockerfile.non_root @@ -24,7 +24,8 @@ RUN for i in 1 2 3; do \ curl \ openssl \ libsndfile \ - nodejs && break || sleep 5; \ + nodejs \ + npm && break || sleep 5; \ done ENV UV_PROJECT_ENVIRONMENT=/app/.venv \ diff --git a/litellm/__init__.py b/litellm/__init__.py index d8d48b5865f..3365abe3256 100644 --- a/litellm/__init__.py +++ b/litellm/__init__.py @@ -413,6 +413,12 @@ internal_user_budget_duration: Optional[str] = None tag_budget_config: Optional[Dict[str, "BudgetConfig"]] = None max_end_user_budget: Optional[float] = None max_end_user_budget_id: Optional[str] = None +# When True, end-user IDs extracted from requests are validated against +# LiteLLM_EndUserTable / LiteLLM_UserTable. Values that do not resolve to a +# known row are dropped before reaching spend logs. Defaults to False for +# backwards compatibility — arbitrary client-supplied identifiers still +# pass through unchanged. +validate_end_user_id_in_db: bool = False disable_end_user_cost_tracking: Optional[bool] = None disable_end_user_cost_tracking_prometheus_only: Optional[bool] = None enable_end_user_cost_tracking_prometheus_only: Optional[bool] = None @@ -636,6 +642,7 @@ minimax_models: Set = set() aws_polly_models: Set = set() gigachat_models: Set = set() llamagate_models: Set = set() +reducto_models: Set = set() bedrock_mantle_models: Set = set() @@ -903,6 +910,8 @@ def add_known_models(model_cost_map: Optional[Dict] = None): gigachat_models.add(key) elif value.get("litellm_provider") == "llamagate": llamagate_models.add(key) + elif value.get("litellm_provider") == "reducto": + reducto_models.add(key) elif value.get("litellm_provider") == "bedrock_mantle": bedrock_mantle_models.add(key) @@ -1014,6 +1023,7 @@ model_list = list( | ovhcloud_models | lemonade_models | docker_model_runner_models + | reducto_models | bedrock_mantle_models | set(clarifai_models) ) @@ -1120,6 +1130,7 @@ models_by_provider: dict = { "aws_polly": aws_polly_models, "gigachat": gigachat_models, "llamagate": llamagate_models, + "reducto": reducto_models, "bedrock_mantle": bedrock_mantle_models, } diff --git a/litellm/_uuid.py b/litellm/_uuid.py index 52acf647dd8..2b7c3b82d35 100644 --- a/litellm/_uuid.py +++ b/litellm/_uuid.py @@ -6,7 +6,6 @@ Always uses fastuuid for performance. import fastuuid as _uuid # type: ignore - # Expose a module-like alias so callers can use: uuid.uuid4() uuid = _uuid diff --git a/litellm/anthropic_interface/exceptions/exception_mapping_utils.py b/litellm/anthropic_interface/exceptions/exception_mapping_utils.py index 28020e763f4..4548185bbdc 100644 --- a/litellm/anthropic_interface/exceptions/exception_mapping_utils.py +++ b/litellm/anthropic_interface/exceptions/exception_mapping_utils.py @@ -9,7 +9,6 @@ from typing import Dict, Optional from .exceptions import AnthropicErrorResponse, AnthropicErrorType - # HTTP status code -> Anthropic error type # Source: https://docs.anthropic.com/en/api/errors ANTHROPIC_ERROR_TYPE_MAP: Dict[int, AnthropicErrorType] = { diff --git a/litellm/anthropic_interface/exceptions/exceptions.py b/litellm/anthropic_interface/exceptions/exceptions.py index 984390fa702..b289e493e6b 100644 --- a/litellm/anthropic_interface/exceptions/exceptions.py +++ b/litellm/anthropic_interface/exceptions/exceptions.py @@ -2,7 +2,6 @@ from typing_extensions import Literal, Required, TypedDict - # Known Anthropic error types # Source: https://docs.anthropic.com/en/api/errors AnthropicErrorType = Literal[ diff --git a/litellm/completion_extras/litellm_responses_transformation/transformation.py b/litellm/completion_extras/litellm_responses_transformation/transformation.py index e3cbf422e5d..51abbbf729b 100644 --- a/litellm/completion_extras/litellm_responses_transformation/transformation.py +++ b/litellm/completion_extras/litellm_responses_transformation/transformation.py @@ -30,6 +30,11 @@ from litellm.llms.base_llm.base_model_iterator import BaseModelResponseIterator from litellm.llms.base_llm.bridges.completion_transformation import ( CompletionTransformationBridge, ) +from litellm.responses.sse_output_recovery import ( + parse_sse_json_chunk, + record_output_item_chunk, + record_output_text_chunk, +) from litellm.types.llms.openai import ( ChatCompletionAnnotation, ChatCompletionReasoningItem, @@ -97,7 +102,7 @@ def _build_reasoning_item( def _reasoning_item_to_response_input( - r_item: Union[ChatCompletionReasoningItem, Dict[str, Any]] + r_item: Union[ChatCompletionReasoningItem, Dict[str, Any]], ) -> Dict[str, Any]: """Convert a stored ChatCompletionReasoningItem back to a Responses API input item.""" r_input: Dict[str, Any] = { @@ -601,6 +606,79 @@ class LiteLLMResponsesTransformationHandler(CompletionTransformationBridge): return choices + @classmethod + def _extract_output_from_completed_event( + cls, parsed_chunk: Dict[str, Any] + ) -> Optional[List[Dict[str, Any]]]: + response_payload = parsed_chunk.get("response") + if not isinstance(response_payload, dict): + return None + response_output = response_payload.get("output") + if not isinstance(response_output, list) or len(response_output) == 0: + return None + return cast(List[Dict[str, Any]], response_output) + + @classmethod + def _recover_output_items_from_raw_sse( + cls, raw_sse: Optional[str] + ) -> List[Dict[str, Any]]: + if not raw_sse or not isinstance(raw_sse, str): + return [] + + recovered_output_items: Dict[int, Dict[str, Any]] = {} + recovered_text_only_items: Dict[int, Dict[str, Any]] = {} + + for chunk in raw_sse.splitlines(): + parsed_chunk = parse_sse_json_chunk(chunk) + if parsed_chunk is None: + continue + + event_type = parsed_chunk.get("type") + + if event_type == ResponsesAPIStreamEvents.RESPONSE_COMPLETED: + recovered_output = cls._extract_output_from_completed_event( + parsed_chunk + ) + if recovered_output is not None: + return recovered_output + continue + + if event_type == ResponsesAPIStreamEvents.OUTPUT_ITEM_DONE: + record_output_item_chunk( + parsed_chunk=parsed_chunk, + output_items=recovered_output_items, + ) + continue + + if event_type == ResponsesAPIStreamEvents.OUTPUT_TEXT_DONE: + record_output_text_chunk( + parsed_chunk=parsed_chunk, + output_items=recovered_output_items, + text_only_items=recovered_text_only_items, + ) + continue + + # Merge text-only items into the recovered output items. Real + # OUTPUT_ITEM_DONE events take precedence at any given output_index, + # but text-only items at indices without a matching OUTPUT_ITEM_DONE + # must still be preserved (e.g. multi-output responses where some + # indices only emitted OUTPUT_TEXT_DONE). + merged_items: Dict[int, Dict[str, Any]] = {**recovered_text_only_items} + merged_items.update(recovered_output_items) + + if merged_items: + return [item for _, item in sorted(merged_items.items())] + + return [] + + @classmethod + def _recover_output_items_from_logging( + cls, logging_obj: "LiteLLMLoggingObj" + ) -> List[Dict[str, Any]]: + model_call_details = getattr(logging_obj, "model_call_details", {}) or {} + original_response = model_call_details.get("original_response") + return cls._recover_output_items_from_raw_sse(original_response) + def transform_response( # noqa: PLR0915 self, model: str, @@ -625,9 +703,22 @@ class LiteLLMResponsesTransformationHandler(CompletionTransformationBridge): if raw_response.error is not None: raise ValueError(f"Error in response: {raw_response.error}") + output_items = raw_response.output + if len(output_items) == 0: + recovered_output_items = self._recover_output_items_from_logging( + logging_obj + ) + if recovered_output_items: + output_items = cast(Any, recovered_output_items) + raw_response.output = cast(Any, recovered_output_items) + verbose_logger.warning( + "Recovered empty Responses API output from raw SSE for model=%s", + model, + ) + # Convert response output to choices using the static helper choices = self._convert_response_output_to_choices( - output_items=raw_response.output, + output_items=output_items, handle_raw_dict_callback=self._handle_raw_dict_response_item, ) @@ -641,7 +732,7 @@ class LiteLLMResponsesTransformationHandler(CompletionTransformationBridge): ) else: raise ValueError( - f"Unknown items in responses API response: {raw_response.output}" + f"Unknown items in responses API response: {output_items}" ) setattr(model_response, "choices", choices) @@ -1237,7 +1328,7 @@ class OpenAiResponsesToChatCompletionStreamIterator(BaseModelResponseIterator): raise ValueError( f"Chat provider: Invalid function argument delta {parsed_chunk}" ) - elif event_type == "response.output_item.done": + elif event_type == ResponsesAPIStreamEvents.OUTPUT_ITEM_DONE: # New output item added output_item = parsed_chunk.get("item", {}) if output_item.get("type") == "function_call": diff --git a/litellm/compression/content_detection.py b/litellm/compression/content_detection.py index 0655a42daf5..975117eb608 100644 --- a/litellm/compression/content_detection.py +++ b/litellm/compression/content_detection.py @@ -5,7 +5,6 @@ Auto-detect content type per message: code, JSON, or text. import json import re - _CODE_KEYWORDS = re.compile( r"\b(?:def |function |class |import |from |require\(|#include|fn |func |const |let |var |public |private |static )\b" ) diff --git a/litellm/cost_calculator.py b/litellm/cost_calculator.py index 2257861aff6..98e00cf5788 100644 --- a/litellm/cost_calculator.py +++ b/litellm/cost_calculator.py @@ -1879,10 +1879,6 @@ def ocr_cost( if response.usage_info is None: raise ValueError("OCR response usage_info is None") - pages_processed = response.usage_info.pages_processed - if pages_processed is None: - raise ValueError("OCR response pages_processed is None") - try: model_info: Optional[ModelInfo] = litellm.get_model_info( model=model, custom_llm_provider=custom_llm_provider @@ -1890,9 +1886,49 @@ def ocr_cost( except Exception: model_info = None - ocr_cost_per_page: float = 0.0 + credits = getattr(response.usage_info, "credits", None) + cost_per_credit = None if model_info is not None: - ocr_cost_per_page = model_info.get("ocr_cost_per_page") or 0.0 + cost_per_credit = model_info.get("ocr_cost_per_credit") + if credits is not None and cost_per_credit is not None: + return cost_per_credit * credits, 0.0 + + ocr_cost_per_page: Optional[float] = None + if model_info is not None: + ocr_cost_per_page = model_info.get("ocr_cost_per_page") + + pages_processed = response.usage_info.pages_processed + if pages_processed is None: + 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 + # for credit-priced or unpriced models, so log a warning to keep + # the regression visible to operators. + verbose_logger.warning( + "OCR cost: model=%s custom_llm_provider=%s response.usage_info." + "pages_processed is None and credits=%s; returning 0.0 cost.", + model, + custom_llm_provider, + credits, + ) + return 0.0, 0.0 + raise ValueError("OCR response pages_processed is None") + + if ocr_cost_per_page is None: + # 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 + # warning so that missing pricing entries are visible rather than + # silently producing zero cost for billable usage. + verbose_logger.warning( + "OCR cost: model=%s custom_llm_provider=%s reported " + "pages_processed=%s but no ocr_cost_per_page is configured; " + "returning 0.0 cost.", + model, + custom_llm_provider, + pages_processed, + ) + return 0.0, 0.0 total_ocr_processing_cost: float = ocr_cost_per_page * pages_processed return total_ocr_processing_cost, 0.0 diff --git a/litellm/files/types.py b/litellm/files/types.py index 688bc86f0cf..ba42a39f666 100644 --- a/litellm/files/types.py +++ b/litellm/files/types.py @@ -1,6 +1,5 @@ from typing import AsyncIterator, Dict, Iterator, Literal, NamedTuple, Union - FileContentProvider = Literal[ "openai", "azure", "vertex_ai", "bedrock", "hosted_vllm", "anthropic", "manus" ] diff --git a/litellm/google_genai/adapters/__init__.py b/litellm/google_genai/adapters/__init__.py index bfa9e712678..6fbe7d95a55 100644 --- a/litellm/google_genai/adapters/__init__.py +++ b/litellm/google_genai/adapters/__init__.py @@ -1,10 +1,10 @@ """ Google GenAI Adapters for LiteLLM -This module provides adapters for transforming Google GenAI generate_content requests +This module provides adapters for transforming Google GenAI generate_content requests to/from LiteLLM completion format with full support for: - Text content transformation -- Tool calling (function declarations, function calls, function responses) +- Tool calling (function declarations, function calls, function responses) - Streaming (both regular and tool calling) - Mixed content (text + tool calls) """ diff --git a/litellm/integrations/SlackAlerting/batching_handler.py b/litellm/integrations/SlackAlerting/batching_handler.py index fdce2e04793..828f3eb4175 100644 --- a/litellm/integrations/SlackAlerting/batching_handler.py +++ b/litellm/integrations/SlackAlerting/batching_handler.py @@ -1,9 +1,9 @@ """ -Handles Batching + sending Httpx Post requests to slack +Handles Batching + sending Httpx Post requests to slack -Slack alerts are sent every 10s or when events are greater than X events +Slack alerts are sent every 10s or when events are greater than X events -see custom_batch_logger.py for more details / defaults +see custom_batch_logger.py for more details / defaults """ from typing import TYPE_CHECKING, Any diff --git a/litellm/integrations/SlackAlerting/utils.py b/litellm/integrations/SlackAlerting/utils.py index e695266c88b..e2580768178 100644 --- a/litellm/integrations/SlackAlerting/utils.py +++ b/litellm/integrations/SlackAlerting/utils.py @@ -18,7 +18,7 @@ else: def process_slack_alerting_variables( - alert_to_webhook_url: Optional[Dict[AlertType, Union[List[str], str]]] + alert_to_webhook_url: Optional[Dict[AlertType, Union[List[str], str]]], ) -> Optional[Dict[AlertType, Union[List[str], str]]]: """ process alert_to_webhook_url diff --git a/litellm/integrations/additional_logging_utils.py b/litellm/integrations/additional_logging_utils.py index 795afd81d41..59319140a18 100644 --- a/litellm/integrations/additional_logging_utils.py +++ b/litellm/integrations/additional_logging_utils.py @@ -1,5 +1,5 @@ """ -Base class for Additional Logging Utils for CustomLoggers +Base class for Additional Logging Utils for CustomLoggers - Health Check for the logging util - Get Request / Response Payload for the logging util diff --git a/litellm/integrations/custom_batch_logger.py b/litellm/integrations/custom_batch_logger.py index f9d4496c21f..8f4844501c3 100644 --- a/litellm/integrations/custom_batch_logger.py +++ b/litellm/integrations/custom_batch_logger.py @@ -1,5 +1,5 @@ """ -Custom Logger that handles batching logic +Custom Logger that handles batching logic Use this if you want your logs to be stored in memory and flushed periodically. """ @@ -14,22 +14,38 @@ from litellm.integrations.custom_logger import CustomLogger class CustomBatchLogger(CustomLogger): + preserve_events_added_during_flush = False + + # Default cap on the in-memory log queue. Prevents unbounded memory growth + # if ``async_send_batch`` consistently fails (e.g. the destination is + # unreachable) and events are preserved across flush attempts. Subclasses + # may override by passing ``max_queue_size`` or by setting the attribute + # directly (see ``RubrikLogger`` for an example). + DEFAULT_MAX_QUEUE_SIZE = 50_000 + def __init__( self, flush_lock: Optional[asyncio.Lock] = None, batch_size: Optional[int] = None, flush_interval: Optional[int] = None, + max_queue_size: Optional[int] = None, **kwargs, ) -> None: """ Args: flush_lock (Optional[asyncio.Lock], optional): Lock to use when flushing the queue. Defaults to None. Only used for custom loggers that do batching + max_queue_size (Optional[int], optional): Maximum number of events to retain in ``log_queue``. When the limit is exceeded (e.g. because the send destination is unreachable and events are preserved for retry), the oldest events are dropped. Defaults to ``DEFAULT_MAX_QUEUE_SIZE``. """ self.log_queue: List = [] self.flush_interval = flush_interval or litellm.DEFAULT_FLUSH_INTERVAL_SECONDS self.batch_size: int = batch_size or litellm.DEFAULT_BATCH_SIZE self.last_flush_time = time.time() self.flush_lock = flush_lock + self.max_queue_size: int = ( + max_queue_size + if max_queue_size is not None + else self.DEFAULT_MAX_QUEUE_SIZE + ) super().__init__(**kwargs) @@ -47,11 +63,40 @@ class CustomBatchLogger(CustomLogger): async with self.flush_lock: if self.log_queue: + log_queue_length = len(self.log_queue) verbose_logger.debug( "CustomLogger: Flushing batch of %s events", len(self.log_queue) ) - await self.async_send_batch() - self.log_queue.clear() + try: + await self.async_send_batch() + except Exception: + # If the underlying batch send raised, do NOT drop the + # in-flight events. They will be retried on the next flush. + # Most existing async_send_batch implementations swallow + # their own errors, so this only affects loggers that opt + # in to surfacing failures (e.g. Rubrik). + verbose_logger.exception( + "CustomLogger: async_send_batch raised; preserving " + "%s events in queue for retry", + log_queue_length, + ) + # Guard against unbounded queue growth if the destination + # is persistently unreachable. Drop the oldest events + # beyond ``max_queue_size``. + overflow = len(self.log_queue) - self.max_queue_size + if overflow > 0: + del self.log_queue[:overflow] + verbose_logger.warning( + "CustomLogger: log queue exceeded max_queue_size=%s; " + "dropped %s oldest events.", + self.max_queue_size, + overflow, + ) + return + if self.preserve_events_added_during_flush: + del self.log_queue[:log_queue_length] + else: + self.log_queue.clear() self.last_flush_time = time.time() async def async_send_batch(self, *args, **kwargs): diff --git a/litellm/integrations/focus/transformer.py b/litellm/integrations/focus/transformer.py index b7d28e3dbb9..6f4433b4a05 100644 --- a/litellm/integrations/focus/transformer.py +++ b/litellm/integrations/focus/transformer.py @@ -9,7 +9,6 @@ import polars as pl from .schema import FOCUS_NORMALIZED_SCHEMA - _TAG_KEYS = ( "team_id", "team_alias", diff --git a/litellm/integrations/opentelemetry.py b/litellm/integrations/opentelemetry.py index e1a3cecfce5..6c8510380a8 100644 --- a/litellm/integrations/opentelemetry.py +++ b/litellm/integrations/opentelemetry.py @@ -726,9 +726,57 @@ class OpenTelemetry(OTELGenAISemconvMixin, CustomLogger): exception_logging_span.set_status(Status(StatusCode.ERROR)) exception_logging_span.end(end_time=self._to_ns(datetime.now())) + # Emit guardrail spans for any guardrail invocations that + # ran during this request. _handle_failure typically does this, + # but for pre-call guardrail blocks the standard_logging_object + # may not carry guardrail_information by the time _handle_failure + # fires (the data lives only in request_data["metadata"]). Pull + # directly from request_data so the span is recorded either way; + # _emit_once dedupes if _handle_failure already emitted it. + self._emit_guardrail_spans_from_request_data( + request_data=request_data, + parent_span=parent_otel_span, + ) + # End Parent OTEL Sspan parent_otel_span.end(end_time=self._to_ns(datetime.now())) + def _emit_guardrail_spans_from_request_data( + self, + request_data: dict, + parent_span: Optional[Any], + ) -> None: + """Emit ``guardrail`` spans from ``request_data["metadata"] + ["standard_logging_guardrail_information"]``. + + Routed through ``_create_guardrail_span`` so the dedupe state in + ``_otel_internal`` is honoured — if ``_handle_failure`` already + emitted these spans for the same kwargs, this is a no-op. + """ + from opentelemetry import trace as _trace + + metadata = (request_data or {}).get("metadata") or {} + guardrail_information = metadata.get("standard_logging_guardrail_information") + if not guardrail_information: + return + + # _create_guardrail_span reads guardrail_information from + # kwargs["standard_logging_object"] and shares its dedupe state via + # kwargs["litellm_params"]["metadata"]["_otel_internal"]. Pass the + # SAME metadata dict the proxy populated so _handle_failure and + # this hook see the same dedupe markers. + kwargs: Dict[str, Any] = { + "litellm_params": {"metadata": metadata}, + "standard_logging_object": { + "guardrail_information": guardrail_information, + "metadata": metadata, + }, + } + context = ( + _trace.set_span_in_context(parent_span) if parent_span is not None else None + ) + self._create_guardrail_span(kwargs=kwargs, context=context) + async def async_post_call_success_hook( self, data: dict, @@ -1617,6 +1665,37 @@ class OpenTelemetry(OTELGenAISemconvMixin, CustomLogger): "guardrail_response", safe_dumps(guardrail_response) ) + # Surface guardrail_status (success / guardrail_intervened / + # guardrail_failed_to_respond / not_run) as a top-level span + # attribute so trace backends can filter on it without parsing + # guardrail_response. + self.safe_set_attribute( + span=guardrail_span, + key="guardrail_status", + value=guardrail_information.get("guardrail_status"), + ) + + # Provider's raw top-level action (e.g. Bedrock's + # ``GUARDRAIL_INTERVENED`` / ``NONE``). Populated by the provider + # hook onto StandardLoggingGuardrailInformation so this integration + # stays provider-agnostic — we only read a normalised string. + guardrail_action = guardrail_information.get("guardrail_action") + if guardrail_action: + guardrail_span.set_attribute("guardrail_action", guardrail_action) + + # The provider hook (e.g. Bedrock) extracts violation_categories + # from the raw response BEFORE redaction and stamps them onto + # StandardLoggingGuardrailInformation. Surfacing them here as a + # queryable attribute lets dashboards group by violation category + # without parsing the redacted guardrail_response blob. + violation_categories = guardrail_information.get("violation_categories") + if violation_categories: + # OTel sequence attributes must be homogeneous primitives; + # serialise to JSON once so set_attribute never coerces. + guardrail_span.set_attribute( + "guardrail_violation_categories", safe_dumps(violation_categories) + ) + self._set_team_attributes_from_kwargs(guardrail_span, kwargs) guardrail_span.end(end_time=self._to_ns(end_time_datetime)) diff --git a/litellm/integrations/opik/utils.py b/litellm/integrations/opik/utils.py index b0ab5991c91..43577505c11 100644 --- a/litellm/integrations/opik/utils.py +++ b/litellm/integrations/opik/utils.py @@ -105,7 +105,7 @@ def _remove_nulls(x: Dict[str, Any]) -> Dict[str, Any]: def get_traces_and_spans_from_payload( - payload: List[Dict[str, Any]] + payload: List[Dict[str, Any]], ) -> Tuple[List[Dict[str, Any]], List[Dict[str, Any]]]: """ Separate traces and spans from payload. diff --git a/litellm/integrations/rubrik.py b/litellm/integrations/rubrik.py new file mode 100644 index 00000000000..af396ecdc73 --- /dev/null +++ b/litellm/integrations/rubrik.py @@ -0,0 +1,605 @@ +"""Rubrik LiteLLM Plugin for tool blocking and batch logging.""" + +import asyncio +import os +import random +import time +import urllib.parse +import uuid +from collections import Counter +from typing import TYPE_CHECKING, Any, Literal, Optional + +import httpx +from litellm._logging import verbose_logger +from litellm.integrations.custom_batch_logger import CustomBatchLogger +from litellm.integrations.custom_guardrail import ( + CustomGuardrail, + ModifyResponseException, +) +from litellm.litellm_core_utils.core_helpers import safe_deep_copy +from litellm.llms.custom_httpx.http_handler import ( + get_async_httpx_client, + httpxSpecialProvider, +) +from litellm.types.guardrails import GuardrailEventHooks +from litellm.types.utils import ( + ChatCompletionMessageToolCall, + Function, + GenericGuardrailAPIInputs, + StandardLoggingPayload, +) + +if TYPE_CHECKING: + from litellm.litellm_core_utils.litellm_logging import ( + Logging as LiteLLMLoggingObj, + ) + +_ENDPOINT_ANTHROPIC_MESSAGES = "/v1/messages" +_WEBHOOK_PATH_TOOL_BLOCKING = "/v1/after_completion/openai/v1" +_WEBHOOK_PATH_LOGGING_BATCH = "/v1/litellm/batch" +_MAX_QUEUE_SIZE = 10_000 +_DROP_WARNING_INTERVAL_SECONDS = 60.0 + + +class _MalformedToolBlockingResponseError(Exception): + """Raised when the tool blocking service returns a structurally invalid + response (e.g. empty ``choices``). + + Distinct from transient network/HTTP errors so callers can surface a + louder, misconfiguration-style log instead of treating it as a routine + fail-open. + """ + + +class RubrikLogger(CustomGuardrail, CustomBatchLogger): + def __init__( + self, + api_key: str | None = None, + api_base: str | None = None, + **kwargs, + ): + self.flush_lock = asyncio.Lock() + kwargs.setdefault("guardrail_name", "rubrik") + # `initialize_guardrail` always passes these kwargs explicitly, with + # value `None` when the user omits `mode` / `default_on` from the + # guardrail config. Coerce None (omitted) to the desired default + # while preserving any explicit value the caller did set -- + # in particular `default_on=False` if the user wants the guardrail + # off by default. + kwargs["event_hook"] = kwargs.get("event_hook") or GuardrailEventHooks.post_call + if kwargs.get("default_on") is None: + kwargs["default_on"] = True + super().__init__( + flush_lock=self.flush_lock, + **kwargs, + ) + + verbose_logger.debug("initializing rubrik logger") + + self.sampling_rate = 1.0 + rbrk_sampling_rate = os.getenv("RUBRIK_SAMPLING_RATE") + if rbrk_sampling_rate is not None: + try: + parsed_rate = float(rbrk_sampling_rate.strip()) + self.sampling_rate = max(0.0, min(1.0, parsed_rate)) + if parsed_rate != self.sampling_rate: + verbose_logger.warning( + f"RUBRIK_SAMPLING_RATE={parsed_rate} clamped to " + f"{self.sampling_rate}" + ) + except ValueError: + verbose_logger.warning( + f"Invalid RUBRIK_SAMPLING_RATE: {rbrk_sampling_rate!r}, using 1.0" + ) + + self.key = api_key or os.getenv("RUBRIK_API_KEY") + if not self.key: + verbose_logger.warning( + "Rubrik: No API key configured. Requests will be unauthenticated." + ) + _batch_size = os.getenv("RUBRIK_BATCH_SIZE") + + if _batch_size: + try: + self.batch_size = int(_batch_size) + except ValueError: + verbose_logger.warning( + f"Invalid RUBRIK_BATCH_SIZE: {_batch_size!r}, using default" + ) + + # Cap the in-memory retry queue so a Rubrik webhook outage cannot let + # authenticated traffic accumulate prompt/response payloads until the + # proxy runs out of memory. Once the cap is reached, oldest events are + # dropped to make room for fresh ones (drop-oldest backpressure). + self.max_queue_size = _MAX_QUEUE_SIZE + self._dropped_since_warning = 0 + self._last_drop_warning_time = 0.0 + + _webhook_url = api_base or os.getenv("RUBRIK_WEBHOOK_URL") + + if _webhook_url is None: + raise ValueError( + "Rubrik webhook URL not configured. " + "Set RUBRIK_WEBHOOK_URL or pass api_base." + ) + + _webhook_url = _webhook_url.rstrip("/").removesuffix("/v1") + self.tool_blocking_endpoint = f"{_webhook_url}{_WEBHOOK_PATH_TOOL_BLOCKING}" + self.logging_endpoint = f"{_webhook_url}{_WEBHOOK_PATH_LOGGING_BATCH}" + + self.async_httpx_client = get_async_httpx_client( + llm_provider=httpxSpecialProvider.LoggingCallback + ) + + self.tool_blocking_client = get_async_httpx_client( + llm_provider=httpxSpecialProvider.LoggingCallback, + params={"timeout": httpx.Timeout(5.0, connect=2.0)}, + ) + + self._headers: dict[str, str] = {"Content-Type": "application/json"} + if self.key: + self._headers["Authorization"] = f"Bearer {self.key}" + + # Periodic flush is started lazily on the first log event so that + # low-traffic deployments still get their batches drained even when the + # logger is instantiated outside a running event loop (sync init). + self._flush_task: Optional[asyncio.Task[Any]] = ( + self._start_periodic_flush_task() + ) + + def _start_periodic_flush_task(self) -> Optional[asyncio.Task[Any]]: + """Start the periodic flush task only when an event loop is already running.""" + try: + loop = asyncio.get_running_loop() + except RuntimeError: + verbose_logger.debug( + "Rubrik logger init: no running event loop, " + "periodic flush will start on first log event." + ) + return None + return loop.create_task(self.periodic_flush()) + + def _ensure_periodic_flush_task(self) -> None: + # Synchronous helper: in asyncio's cooperative model there is no await + # between the check and assignment, so two callers cannot race here. + if self._flush_task is None or self._flush_task.done(): + self._flush_task = self._start_periodic_flush_task() + + async def aclose(self): + """Close the dedicated HTTP clients used by this logger.""" + # Cancel the periodic flush task before closing the HTTP clients so + # the loop doesn't wake up and try to POST via a closed client. + if self._flush_task is not None and not self._flush_task.done(): + self._flush_task.cancel() + try: + await self._flush_task + except (asyncio.CancelledError, Exception): + pass + self._flush_task = None + await self.tool_blocking_client.close() + await self.async_httpx_client.close() + + # -- Guardrail hook -------------------------------------------------------- + + async def apply_guardrail( + self, + inputs: GenericGuardrailAPIInputs, + request_data: dict, + input_type: Literal["request", "response"], + logging_obj: Optional["LiteLLMLoggingObj"] = None, + ) -> GenericGuardrailAPIInputs: + """Validate tool calls against the blocking service (fail-open).""" + if input_type != "response": + return inputs + + tool_calls = inputs.get("tool_calls") + if not tool_calls: + return inputs + + try: + return await self._check_tool_calls( + inputs, tool_calls, request_data, logging_obj + ) + except ModifyResponseException: + raise + except _MalformedToolBlockingResponseError as e: + # Distinct from transient errors: the service responded but the + # payload was structurally invalid, which usually indicates a + # misconfigured webhook or a breaking change in its response + # format. Log loudly so operators notice their tool-blocking + # policy is not actually being enforced. + verbose_logger.critical( + "Tool blocking service returned a malformed response: %s. " + "Tool calls are NOT being checked -- verify the webhook " + "configuration. Returning original response unchanged.", + e, + exc_info=True, + ) + return inputs + except Exception as e: + verbose_logger.error( + f"Tool blocking hook failed: {e}. " + "Returning original response unchanged.", + exc_info=True, + ) + return inputs + + async def _check_tool_calls( + self, + inputs: GenericGuardrailAPIInputs, + tool_calls: Any, + request_data: dict, + logging_obj: Optional["LiteLLMLoggingObj"], + ) -> GenericGuardrailAPIInputs: + """Send tool calls to blocking service, raise if any are blocked.""" + message_tool_calls = self._normalize_tool_calls(tool_calls) + + call_details = ( + getattr(logging_obj, "model_call_details", {}) if logging_obj else {} + ) + response = request_data.get("response") + request_id = getattr(response, "id", None) if response else None + if logging_obj and not call_details: + verbose_logger.warning( + "Rubrik: logging_obj present but model_call_details is empty " + "-- request context will be missing" + ) + + response_data = self._build_tool_call_payload(message_tool_calls, request_id) + req_data = self._extract_request_data(call_details) + + service_response = await self._post_to_tool_blocking_service( + response_data, req_data + ) + blocked_explanation = self._extract_blocked_tools( + service_response, message_tool_calls + ) + + if blocked_explanation is not None: + model = self._resolve_model(request_data, call_details) + raise ModifyResponseException( + message=blocked_explanation, + model=model, + request_data=request_data, + guardrail_name=self.guardrail_name, + ) + + return inputs + + @staticmethod + def _normalize_tool_calls(tool_calls: Any) -> list[ChatCompletionMessageToolCall]: + """Convert tool_calls from inputs to ChatCompletionMessageToolCall objects.""" + result = [] + for tc in tool_calls: + if isinstance(tc, ChatCompletionMessageToolCall): + result.append(tc) + elif isinstance(tc, dict): + func = tc.get("function", {}) + result.append( + ChatCompletionMessageToolCall( + id=tc.get("id", ""), + type=tc.get("type", "function"), + function=Function( + name=func.get("name", ""), + arguments=func.get("arguments", ""), + ), + ) + ) + elif hasattr(tc, "id") and hasattr(tc, "function"): + result.append( + ChatCompletionMessageToolCall( + id=tc.id or "", + type=getattr(tc, "type", None) or "function", + function=tc.function, + ) + ) + else: + raise TypeError( + f"Cannot normalize tool_call of type {type(tc).__name__}" + ) + return result + + @staticmethod + def _build_tool_call_payload( + tool_calls: list[ChatCompletionMessageToolCall], + request_id: str | None, + ) -> dict[str, Any]: + """Build a full OpenAI ChatCompletion-format dict for the blocking service.""" + return { + "id": request_id or f"chatcmpl-{uuid.uuid4()}", + "object": "chat.completion", + "created": int(time.time()), + "model": "", + "choices": [ + { + "index": 0, + "message": { + "role": "assistant", + "content": None, + "tool_calls": [ + tc.model_dump(exclude_none=True) for tc in tool_calls + ], + }, + "finish_reason": "tool_calls", + } + ], + } + + @staticmethod + def _extract_request_data(call_details: dict[str, Any]) -> dict[str, Any]: + """Extract original request data from model_call_details.""" + if not call_details: + return {} + litellm_params = call_details.get("litellm_params", {}) or {} + return { + "messages": call_details.get("messages"), + "model": call_details.get("model"), + "proxy_server_request": RubrikLogger._sanitize_proxy_server_request( + litellm_params.get("proxy_server_request") + ), + } + + @staticmethod + def _sanitize_proxy_server_request(proxy_server_request: Any) -> Any: + """Allowlist only routing fields (``url``, ``method``) when forwarding + ``proxy_server_request`` to the external Rubrik webhook, dropping + inbound ``headers`` (Authorization, Cookie, x-api-key, ...) and the raw + request ``body`` so proxy credentials are not exfiltrated.""" + if not isinstance(proxy_server_request, dict): + return proxy_server_request + return { + key: proxy_server_request[key] + for key in ("url", "method") + if key in proxy_server_request + } + + @staticmethod + def _resolve_model( + request_data: dict[str, Any], call_details: dict[str, Any] + ) -> str: + """Get the model name for the ModifyResponseException.""" + response = request_data.get("response") + if response and hasattr(response, "model"): + return response.model or "unknown" + return call_details.get("model", "unknown") + + # -- Logging hooks --------------------------------------------------------- + + async def _prepare_log_payload( + self, kwargs: dict, event_type: str + ) -> StandardLoggingPayload | None: + """Shared logic for success and failure logging.""" + if random.random() > self.sampling_rate: + verbose_logger.debug( + f"Skipping Rubrik {event_type} logging " + f"(sampling_rate={self.sampling_rate})" + ) + return None + + # Deep-copy so mutations don't affect other callbacks sharing this object + standard_logging_payload: StandardLoggingPayload = safe_deep_copy( + kwargs["standard_logging_object"] + ) + + # For Anthropic /v1/messages requests, LiteLLM creates a separate + # ModelResponse (with a generated chatcmpl-* id) for logging, which + # differs from the original Anthropic msg-* id on the response dict. + # Normalize to litellm_call_id so that the logging and tool-blocking + # endpoints see the same request identifier. + litellm_params = kwargs.get("litellm_params", {}) or {} + proxy_request = litellm_params.get("proxy_server_request", {}) or {} + url_path = urllib.parse.urlparse(proxy_request.get("url", "")).path + if url_path.endswith(_ENDPOINT_ANTHROPIC_MESSAGES): + _litellm_call_id = kwargs.get("litellm_call_id") + if _litellm_call_id: + standard_logging_payload["id"] = _litellm_call_id # type: ignore[literal-required] + + if "system" in kwargs: + system_prompt_msg_list = kwargs["system"] + try: + if system_prompt_msg_list: + system_scaffold = { + "role": "system", + "content": system_prompt_msg_list, + } + if isinstance(standard_logging_payload["messages"], list): + standard_logging_payload["messages"].insert(0, system_scaffold) + elif isinstance(standard_logging_payload["messages"], (dict, str)): + standard_logging_payload["messages"] = [ + system_scaffold, + standard_logging_payload["messages"], + ] + except Exception as e: + verbose_logger.warning( + f"Rubrik: failed to prepend system prompt: {e}", + exc_info=True, + ) + + return standard_logging_payload + + async def _enqueue_log_event(self, kwargs: dict, event_type: str): + try: + self._ensure_periodic_flush_task() + payload = await self._prepare_log_payload(kwargs, event_type) + if payload is None: + return + + self.log_queue.append(payload) + self._enforce_max_queue_size() + + if len(self.log_queue) >= self.batch_size: + await self.flush_queue() + except Exception as e: + verbose_logger.error( + f"Rubrik {event_type} logging hook failed: {e}. " + "Skipping logging for this event.", + exc_info=True, + ) + + def _enforce_max_queue_size(self) -> None: + overflow = len(self.log_queue) - self.max_queue_size + if overflow <= 0: + return + del self.log_queue[:overflow] + self._dropped_since_warning += overflow + now = time.time() + if now - self._last_drop_warning_time >= _DROP_WARNING_INTERVAL_SECONDS: + verbose_logger.warning( + "Rubrik: log queue exceeded max_queue_size=%s; dropped %s " + "oldest events since the last warning. The Rubrik webhook may " + "be unhealthy or undersized for current traffic.", + self.max_queue_size, + self._dropped_since_warning, + ) + self._dropped_since_warning = 0 + self._last_drop_warning_time = now + + async def async_log_success_event(self, kwargs, response_obj, start_time, end_time): + await self._enqueue_log_event(kwargs, "success") + + async def async_log_failure_event(self, kwargs, response_obj, start_time, end_time): + await self._enqueue_log_event(kwargs, "failure") + + # -- Batch logging --------------------------------------------------------- + + async def _log_batch_to_rubrik(self, data): + # NOTE: this method intentionally re-raises on failure so the parent + # CustomBatchLogger.flush_queue keeps the unsent events in the queue + # for the next flush attempt instead of silently dropping them. + try: + response = await self.async_httpx_client.post( + url=self.logging_endpoint, + json=data, + headers=self._headers, + ) + response.raise_for_status() + except httpx.HTTPStatusError as e: + verbose_logger.exception( + f"Rubrik HTTP Error: {e.response.status_code} - {e.response.text}" + ) + raise + except Exception: + verbose_logger.exception("Rubrik Layer Error") + raise + + async def async_send_batch(self): + """Handles sending batches of responses to Rubrik. + + Note: the canonical flush path is :meth:`flush_queue`, which takes a + single snapshot used for both sending and queue draining. This method + is kept for direct callers / tests; it intentionally does NOT remove + events from the queue. + """ + if not self.log_queue: + return + + log_queue_snapshot = list(self.log_queue) + verbose_logger.debug( + "Rubrik: Flushing batch of %s events", len(log_queue_snapshot) + ) + await self._log_batch_to_rubrik( + data=log_queue_snapshot, + ) + + async def flush_queue(self): + """Snapshot, send, and drain in one consistent step. + + Overrides the base implementation so the same snapshot drives both + the HTTP send and the queue truncation. This avoids the subtle + coupling where the base class captures `len(self.log_queue)` + separately from the snapshot taken inside `async_send_batch`, + which could otherwise drift in a future refactor and cause + duplicate deliveries to Rubrik. + """ + if self.flush_lock is None: + return + + async with self.flush_lock: + if not self.log_queue: + return + snapshot = list(self.log_queue) + verbose_logger.debug("Rubrik: Flushing batch of %s events", len(snapshot)) + try: + await self._log_batch_to_rubrik(data=snapshot) + except Exception: + # Already logged with traceback inside _log_batch_to_rubrik. + # Preserve the in-flight events for retry on the next flush. + return + del self.log_queue[: len(snapshot)] + self.last_flush_time = time.time() + + # -- Tool blocking service ------------------------------------------------- + + async def _post_to_tool_blocking_service( + self, + response_data: dict[str, Any], + request_data: dict[str, Any], + ) -> dict[str, Any]: + """Post a payload to the tool blocking service and return the response. + + Args: + response_data: The OpenAI-formatted response payload to send. + request_data: Original LLM request data to include alongside + the response for additional context. Empty dict if unavailable. + + Raises: + Exception: If the service is unavailable or returns an error. + """ + envelope = { + "request": request_data, + "response": response_data, + } + verbose_logger.debug( + f"Sending request to tool blocking service: " + f"{self.tool_blocking_endpoint}" + ) + http_response = await self.tool_blocking_client.post( + self.tool_blocking_endpoint, + json=envelope, + headers=self._headers, + ) + http_response.raise_for_status() + result: dict[str, Any] = http_response.json() + return result + + @staticmethod + def _extract_blocked_tools( + service_response: dict[str, Any], + all_tool_calls: list[ChatCompletionMessageToolCall], + ) -> Optional[str]: + """Return the blocking explanation if any tool calls were blocked. + + Compares the service response (which contains only allowed tools) against + the full set of tool calls. Returns ``None`` if all tools are allowed, or + the explanation string (prefixed with newlines) otherwise. + + Expects service_response in OpenAI chat completion format: + {"choices": [{"message": {"tool_calls": [...], "content": "..."}}]} + """ + choices = service_response.get("choices", []) + if not choices: + raise _MalformedToolBlockingResponseError( + "Tool blocking service returned empty response" + ) + + message = choices[0].get("message", {}) + returned_tool_calls = message.get("tool_calls") or [] + blocking_explanation = message.get("content", "") + + allowed_id_counts: Counter = Counter( + tc["id"] + for tc in returned_tool_calls + if isinstance(tc, dict) and tc.get("id") + ) + required_id_counts: Counter = Counter(tc.id for tc in all_tool_calls if tc.id) + + all_allowed = len(returned_tool_calls) >= len(all_tool_calls) and all( + allowed_id_counts.get(tc_id, 0) >= count + for tc_id, count in required_id_counts.items() + ) + + if all_allowed: + return None + + explanation = blocking_explanation or "Tool call blocked by policy." + return f"\n\n{explanation}" diff --git a/litellm/integrations/s3_v2.py b/litellm/integrations/s3_v2.py index 332e84dd07d..4ed8a809a13 100644 --- a/litellm/integrations/s3_v2.py +++ b/litellm/integrations/s3_v2.py @@ -1,8 +1,8 @@ """ s3 Bucket Logging Integration -async_log_success_event: Processes the event, stores it in memory for DEFAULT_S3_FLUSH_INTERVAL_SECONDS seconds or until DEFAULT_S3_BATCH_SIZE and then flushes to s3 -async_log_failure_event: Processes the event, stores it in memory for DEFAULT_S3_FLUSH_INTERVAL_SECONDS seconds or until DEFAULT_S3_BATCH_SIZE and then flushes to s3 +async_log_success_event: Processes the event, stores it in memory for DEFAULT_S3_FLUSH_INTERVAL_SECONDS seconds or until DEFAULT_S3_BATCH_SIZE and then flushes to s3 +async_log_failure_event: Processes the event, stores it in memory for DEFAULT_S3_FLUSH_INTERVAL_SECONDS seconds or until DEFAULT_S3_BATCH_SIZE and then flushes to s3 NOTE 1: S3 does not provide a BATCH PUT API endpoint, so we create tasks to upload each element individually """ diff --git a/litellm/interactions/agents/main.py b/litellm/interactions/agents/main.py index 7375fd6273f..f56c6f3ed5e 100644 --- a/litellm/interactions/agents/main.py +++ b/litellm/interactions/agents/main.py @@ -49,7 +49,6 @@ from litellm.types.interactions import InteractionEnvironment from litellm.types.router import GenericLiteLLMParams from litellm.utils import client - # ------------------------------------------------------------------ # # Shared helpers # # ------------------------------------------------------------------ # diff --git a/litellm/interactions/main.py b/litellm/interactions/main.py index c6eca410fa7..d99cc3d11c7 100644 --- a/litellm/interactions/main.py +++ b/litellm/interactions/main.py @@ -8,25 +8,25 @@ Per OpenAPI spec (https://ai.google.dev/static/api/interactions.openapi.json): Usage: import litellm - + # Create an interaction with a model response = litellm.interactions.create( model="gemini-2.5-flash", input="Hello, how are you?" ) - + # Create an interaction with an agent response = litellm.interactions.create( agent="deep-research-pro-preview-12-2025", input="Research the current state of cancer research" ) - + # Async version response = await litellm.interactions.acreate(...) - + # Get an interaction response = litellm.interactions.get(interaction_id="...") - + # Delete an interaction result = litellm.interactions.delete(interaction_id="...") """ diff --git a/litellm/litellm_core_utils/litellm_logging.py b/litellm/litellm_core_utils/litellm_logging.py index 876f1b167db..2ab037afb0d 100644 --- a/litellm/litellm_core_utils/litellm_logging.py +++ b/litellm/litellm_core_utils/litellm_logging.py @@ -994,10 +994,8 @@ class Logging(LiteLLMLoggingBaseClass): try: # [Non-blocking Extra Debug Information in metadata] if turn_off_message_logging is True: - _metadata["raw_request"] = ( - "redacted by litellm. \ + _metadata["raw_request"] = "redacted by litellm. \ 'litellm.turn_off_message_logging=True'" - ) else: curl_command = self._get_request_curl_command( api_base=additional_args.get("api_base", ""), @@ -1031,12 +1029,8 @@ class Logging(LiteLLMLoggingBaseClass): error=str(e), ) ) - _metadata["raw_request"] = ( - "Unable to Log \ - raw request: {}".format( - str(e) - ) - ) + _metadata["raw_request"] = "Unable to Log \ + raw request: {}".format(str(e)) if getattr(self, "logger_fn", None) and callable(self.logger_fn): try: self.logger_fn( @@ -1769,9 +1763,12 @@ class Logging(LiteLLMLoggingBaseClass): self.model_call_details["response_cost"] = 0.0 elif "response_cost" in hidden_params: self.model_call_details["response_cost"] = hidden_params["response_cost"] - elif self.model_call_details.get("response_cost") is not None: + elif ( + existing_cost := self.model_call_details.get("response_cost") + ) is not None and existing_cost != 0: # Preserve response_cost if already calculated (e.g., by pass-through - # handlers like Gemini/Vertex which call completion_cost directly) + # handlers like Gemini/Vertex which call completion_cost directly). + # Do not preserve 0 from failure_handler on intermediate router retries. pass else: self.model_call_details["response_cost"] = self._response_cost_calculator( diff --git a/litellm/litellm_core_utils/prompt_templates/factory.py b/litellm/litellm_core_utils/prompt_templates/factory.py index a29f5005570..f169f86079a 100644 --- a/litellm/litellm_core_utils/prompt_templates/factory.py +++ b/litellm/litellm_core_utils/prompt_templates/factory.py @@ -5590,9 +5590,7 @@ def default_response_schema_prompt(response_schema: dict) -> str: prompt_str = """Use this JSON schema: ```json {} - ```""".format( - response_schema - ) + ```""".format(response_schema) return prompt_str diff --git a/litellm/litellm_core_utils/specialty_caches/dynamic_logging_cache.py b/litellm/litellm_core_utils/specialty_caches/dynamic_logging_cache.py index 13341f27a61..0a6a4e82c72 100644 --- a/litellm/litellm_core_utils/specialty_caches/dynamic_logging_cache.py +++ b/litellm/litellm_core_utils/specialty_caches/dynamic_logging_cache.py @@ -1,9 +1,9 @@ """ This is a cache for LangfuseLoggers. -Langfuse Python SDK initializes a thread for each client. +Langfuse Python SDK initializes a thread for each client. -This ensures we do +This ensures we do 1. Proper cleanup of Langfuse initialized clients. 2. Re-use created langfuse clients. """ diff --git a/litellm/llms/anthropic/experimental_pass_through/messages/agentic_streaming_iterator.py b/litellm/llms/anthropic/experimental_pass_through/messages/agentic_streaming_iterator.py index d0780c82d06..d693d50b8e5 100644 --- a/litellm/llms/anthropic/experimental_pass_through/messages/agentic_streaming_iterator.py +++ b/litellm/llms/anthropic/experimental_pass_through/messages/agentic_streaming_iterator.py @@ -13,7 +13,6 @@ from typing import Any, AsyncIterator, Dict, List, Optional, cast from litellm._logging import verbose_logger - # --------------------------------------------------------------------------- # SSE parsing helpers (module-level to keep the class lean) # --------------------------------------------------------------------------- diff --git a/litellm/llms/azure/chat/o_series_transformation.py b/litellm/llms/azure/chat/o_series_transformation.py index cae7513245c..0a73597a4e4 100644 --- a/litellm/llms/azure/chat/o_series_transformation.py +++ b/litellm/llms/azure/chat/o_series_transformation.py @@ -4,10 +4,10 @@ Support for o1 and o3 model families https://platform.openai.com/docs/guides/reasoning Translations handled by LiteLLM: -- modalities: image => drop param (if user opts in to dropping param) -- role: system ==> translate to role 'user' -- streaming => faked by LiteLLM -- Tools, response_format => drop param (if user opts in to dropping param) +- modalities: image => drop param (if user opts in to dropping param) +- role: system ==> translate to role 'user' +- streaming => faked by LiteLLM +- Tools, response_format => drop param (if user opts in to dropping param) - Logprobs => drop param (if user opts in to dropping param) - Temperature => drop param (if user opts in to dropping param) """ diff --git a/litellm/llms/azure_ai/embed/cohere_transformation.py b/litellm/llms/azure_ai/embed/cohere_transformation.py index 64433c21b61..bbbfb60fbde 100644 --- a/litellm/llms/azure_ai/embed/cohere_transformation.py +++ b/litellm/llms/azure_ai/embed/cohere_transformation.py @@ -1,5 +1,5 @@ """ -Transformation logic from OpenAI /v1/embeddings format to Azure AI Cohere's /v1/embed. +Transformation logic from OpenAI /v1/embeddings format to Azure AI Cohere's /v1/embed. Why separate file? Make it easy to see how transformation works diff --git a/litellm/llms/azure_ai/rerank/transformation.py b/litellm/llms/azure_ai/rerank/transformation.py index b5993040ea0..f64133afa8b 100644 --- a/litellm/llms/azure_ai/rerank/transformation.py +++ b/litellm/llms/azure_ai/rerank/transformation.py @@ -1,5 +1,5 @@ """ -Translate between Cohere's `/rerank` format and Azure AI's `/rerank` format. +Translate between Cohere's `/rerank` format and Azure AI's `/rerank` format. """ from typing import Optional diff --git a/litellm/llms/base_llm/ocr/transformation.py b/litellm/llms/base_llm/ocr/transformation.py index b7f4d8e3b2d..263e0c094ce 100644 --- a/litellm/llms/base_llm/ocr/transformation.py +++ b/litellm/llms/base_llm/ocr/transformation.py @@ -54,6 +54,7 @@ class OCRUsageInfo(LiteLLMPydanticObjectBase): """Usage information from OCR response.""" pages_processed: Optional[int] = None + credits: Optional[float] = None doc_size_bytes: Optional[int] = None model_config = {"extra": "allow"} diff --git a/litellm/llms/bedrock/chat/invoke_transformations/anthropic_claude3_transformation.py b/litellm/llms/bedrock/chat/invoke_transformations/anthropic_claude3_transformation.py index c883ab68dff..d9599b8b9c4 100644 --- a/litellm/llms/bedrock/chat/invoke_transformations/anthropic_claude3_transformation.py +++ b/litellm/llms/bedrock/chat/invoke_transformations/anthropic_claude3_transformation.py @@ -3,6 +3,7 @@ from typing import TYPE_CHECKING, Any, List, Optional import httpx from litellm.anthropic_beta_headers_manager import filter_and_transform_beta_headers +from litellm.litellm_core_utils.litellm_logging import verbose_logger from litellm.litellm_core_utils.prompt_templates.factory import ( convert_to_anthropic_image_obj, ) @@ -22,6 +23,7 @@ from litellm.llms.bedrock.common_utils import ( from litellm.types.llms.anthropic import ANTHROPIC_TOOL_SEARCH_BETA_HEADER from litellm.types.llms.openai import AllMessageValues from litellm.types.utils import ModelResponse +from litellm.utils import _supports_factory if TYPE_CHECKING: from litellm.litellm_core_utils.litellm_logging import Logging as _LiteLLMLoggingObj @@ -169,6 +171,24 @@ class AmazonAnthropicClaudeConfig(AmazonInvokeConfig, AnthropicConfig): anthropic_request.pop("model", None) anthropic_request.pop("stream", None) anthropic_request.pop("output_format", None) + if not ( + _supports_factory( + model=model, + custom_llm_provider="bedrock", + key="supports_output_config", + ) + or AnthropicConfig._model_supports_effort_param(model) + ): + if anthropic_request.pop("output_config", None) is not None: + verbose_logger.warning( + "Bedrock Invoke: stripping unsupported `output_config` for " + "model=%s — neither `supports_output_config` nor any " + "`supports_*_reasoning_effort` flag is set in " + "model_prices_and_context_window.json. Add the capability " + "flag to the model JSON entry if this model accepts " + "`output_config`.", + model, + ) if "anthropic_version" not in anthropic_request: anthropic_request["anthropic_version"] = self.anthropic_version diff --git a/litellm/llms/bedrock/claude_platform/common_utils.py b/litellm/llms/bedrock/claude_platform/common_utils.py index 121221518c8..3abb8710de7 100644 --- a/litellm/llms/bedrock/claude_platform/common_utils.py +++ b/litellm/llms/bedrock/claude_platform/common_utils.py @@ -4,7 +4,6 @@ import litellm from litellm.llms.bedrock.base_aws_llm import BaseAWSLLM from litellm.secret_managers.main import get_secret_str - CLAUDE_PLATFORM_SERVICE_NAME: Literal["aws-external-anthropic"] = ( "aws-external-anthropic" ) diff --git a/litellm/llms/bedrock/embed/amazon_titan_g1_transformation.py b/litellm/llms/bedrock/embed/amazon_titan_g1_transformation.py index 2747551af81..64a79b73273 100644 --- a/litellm/llms/bedrock/embed/amazon_titan_g1_transformation.py +++ b/litellm/llms/bedrock/embed/amazon_titan_g1_transformation.py @@ -1,5 +1,5 @@ """ -Transformation logic from OpenAI /v1/embeddings format to Bedrock Amazon Titan G1 /invoke format. +Transformation logic from OpenAI /v1/embeddings format to Bedrock Amazon Titan G1 /invoke format. Why separate file? Make it easy to see how transformation works diff --git a/litellm/llms/bedrock/embed/cohere_transformation.py b/litellm/llms/bedrock/embed/cohere_transformation.py index 2c0dc834144..9570ff1a14c 100644 --- a/litellm/llms/bedrock/embed/cohere_transformation.py +++ b/litellm/llms/bedrock/embed/cohere_transformation.py @@ -1,5 +1,5 @@ """ -Transformation logic from OpenAI /v1/embeddings format to Bedrock Cohere /invoke format. +Transformation logic from OpenAI /v1/embeddings format to Bedrock Cohere /invoke format. Why separate file? Make it easy to see how transformation works """ diff --git a/litellm/llms/bedrock/messages/invoke_transformations/anthropic_claude3_transformation.py b/litellm/llms/bedrock/messages/invoke_transformations/anthropic_claude3_transformation.py index 151e0e404a0..69b61298d33 100644 --- a/litellm/llms/bedrock/messages/invoke_transformations/anthropic_claude3_transformation.py +++ b/litellm/llms/bedrock/messages/invoke_transformations/anthropic_claude3_transformation.py @@ -45,6 +45,7 @@ from litellm.types.router import GenericLiteLLMParams from litellm.types.utils import GenericStreamingChunk from litellm.types.utils import GenericStreamingChunk as GChunk from litellm.types.utils import ModelResponseStream +from litellm.utils import _supports_factory if TYPE_CHECKING: from litellm.litellm_core_utils.litellm_logging import Logging as _LiteLLMLoggingObj @@ -557,7 +558,29 @@ class AmazonAnthropicClaudeMessagesConfig( anthropic_messages_request=anthropic_messages_request, ) - # 5a. Remove `custom` field from tools (Bedrock doesn't support it) + # 5a. Bedrock Invoke supports output_config (effort) for Claude 4.6+ models, + # but older models do not — strip it to avoid request rejection. + # Ref: https://github.com/BerriAI/litellm/issues/22797 + if not ( + _supports_factory( + model=model, + custom_llm_provider="bedrock", + key="supports_output_config", + ) + or AnthropicConfig._model_supports_effort_param(model) + ): + if anthropic_messages_request.pop("output_config", None) is not None: + verbose_logger.warning( + "Bedrock Invoke: stripping unsupported `output_config` for " + "model=%s — neither `supports_output_config` nor any " + "`supports_*_reasoning_effort` flag is set in " + "model_prices_and_context_window.json. Add the capability " + "flag to the model JSON entry if this model accepts " + "`output_config`.", + model, + ) + + # 5b. Remove `custom` field from tools (Bedrock doesn't support it) # Claude Code sends `custom: {defer_loading: true}` on tool definitions, # which causes Bedrock to reject the request with "Extra inputs are not permitted" # Ref: https://github.com/BerriAI/litellm/issues/22847 diff --git a/litellm/llms/bedrock_mantle/chat/transformation.py b/litellm/llms/bedrock_mantle/chat/transformation.py index e413bb22b2d..81a56030a5c 100644 --- a/litellm/llms/bedrock_mantle/chat/transformation.py +++ b/litellm/llms/bedrock_mantle/chat/transformation.py @@ -16,7 +16,6 @@ from litellm.secret_managers.main import get_secret_str from ...openai_like.chat.transformation import OpenAILikeChatConfig - BEDROCK_MANTLE_DEFAULT_REGION = "us-east-1" diff --git a/litellm/llms/chatgpt/responses/transformation.py b/litellm/llms/chatgpt/responses/transformation.py index 66acd933416..56b61b66c84 100644 --- a/litellm/llms/chatgpt/responses/transformation.py +++ b/litellm/llms/chatgpt/responses/transformation.py @@ -1,7 +1,5 @@ -import json -from typing import Any, Optional +from typing import Any, Dict, Optional -from litellm.constants import STREAM_SSE_DONE_STRING from litellm.exceptions import AuthenticationError from litellm.litellm_core_utils.core_helpers import process_response_headers from litellm.litellm_core_utils.llm_response_utils.convert_dict_to_response import ( @@ -9,13 +7,17 @@ from litellm.litellm_core_utils.llm_response_utils.convert_dict_to_response impo ) from litellm.llms.openai.common_utils import OpenAIError from litellm.llms.openai.responses.transformation import OpenAIResponsesAPIConfig +from litellm.responses.sse_output_recovery import ( + parse_sse_json_chunk, + record_output_item_chunk, + record_output_text_chunk, +) from litellm.types.llms.openai import ( ResponsesAPIResponse, ResponsesAPIStreamEvents, ) from litellm.types.router import GenericLiteLLMParams from litellm.types.utils import LlmProviders -from litellm.utils import CustomStreamWrapper from ..authenticator import Authenticator from ..common_utils import ( @@ -111,86 +113,139 @@ class ChatGPTResponsesAPIConfig(OpenAIResponsesAPIConfig): raw_response: Any, logging_obj: Any, ): - content_type = (raw_response.headers or {}).get("content-type", "") body_text = raw_response.text or "" - if "text/event-stream" not in content_type.lower(): - trimmed_body = body_text.lstrip() - if not ( - trimmed_body.startswith("event:") - or trimmed_body.startswith("data:") - or "\nevent:" in body_text - or "\ndata:" in body_text - ): - return super().transform_response_api_response( - model=model, - raw_response=raw_response, - logging_obj=logging_obj, - ) + if not self._should_parse_as_sse( + raw_response=raw_response, body_text=body_text + ): + return super().transform_response_api_response( + model=model, + raw_response=raw_response, + logging_obj=logging_obj, + ) logging_obj.post_call( original_response=raw_response.text, additional_args={"complete_input_dict": {}}, ) - completed_response = None - error_message = None - for chunk in body_text.splitlines(): - stripped_chunk = CustomStreamWrapper._strip_sse_data_from_chunk(chunk) - if not stripped_chunk: - continue - stripped_chunk = stripped_chunk.strip() - if not stripped_chunk: - continue - if stripped_chunk == STREAM_SSE_DONE_STRING: - break - try: - parsed_chunk = json.loads(stripped_chunk) - except json.JSONDecodeError: - continue - if not isinstance(parsed_chunk, dict): - continue - event_type = parsed_chunk.get("type") - if event_type == ResponsesAPIStreamEvents.RESPONSE_COMPLETED: - response_payload = parsed_chunk.get("response") - if isinstance(response_payload, dict): - response_payload = dict(response_payload) - if "created_at" in response_payload: - response_payload["created_at"] = _safe_convert_created_field( - response_payload["created_at"] - ) - try: - completed_response = ResponsesAPIResponse(**response_payload) - except Exception: - completed_response = ResponsesAPIResponse.model_construct( - **response_payload - ) - break - if event_type in ( - ResponsesAPIStreamEvents.RESPONSE_FAILED, - ResponsesAPIStreamEvents.ERROR, - ): - error_obj = parsed_chunk.get("error") or ( - parsed_chunk.get("response") or {} - ).get("error") - if error_obj is not None: - if isinstance(error_obj, dict): - error_message = error_obj.get("message") or str(error_obj) - else: - error_message = str(error_obj) - + completed_response, error_message = self._extract_completed_response_from_sse( + body_text=body_text + ) if completed_response is None: raise OpenAIError( message=error_message or raw_response.text, status_code=raw_response.status_code, ) + self._attach_response_headers( + completed_response=completed_response, raw_response=raw_response + ) + return completed_response + + def _should_parse_as_sse(self, raw_response: Any, body_text: str) -> bool: + content_type = (raw_response.headers or {}).get("content-type", "") + if "text/event-stream" in content_type.lower(): + return True + trimmed_body = body_text.lstrip() + return bool( + trimmed_body.startswith("event:") + or trimmed_body.startswith("data:") + or "\nevent:" in body_text + or "\ndata:" in body_text + ) + + def _extract_completed_response_from_sse( + self, body_text: str + ) -> tuple[Optional[ResponsesAPIResponse], Optional[str]]: + completed_response = None + error_message = None + streamed_output_items: Dict[int, dict] = {} + text_only_output_items: Dict[int, dict] = {} + for chunk in body_text.splitlines(): + parsed_chunk = parse_sse_json_chunk(chunk) + if parsed_chunk is None: + continue + + event_type = parsed_chunk.get("type") + if event_type == ResponsesAPIStreamEvents.OUTPUT_ITEM_DONE: + record_output_item_chunk( + parsed_chunk=parsed_chunk, + output_items=streamed_output_items, + ) + continue + + if event_type == ResponsesAPIStreamEvents.OUTPUT_TEXT_DONE: + record_output_text_chunk( + parsed_chunk=parsed_chunk, + output_items=streamed_output_items, + text_only_items=text_only_output_items, + ) + continue + + if event_type == ResponsesAPIStreamEvents.RESPONSE_COMPLETED: + # Real OUTPUT_ITEM_DONE events take precedence at any given + # output_index, but text-only items at indices without a + # matching OUTPUT_ITEM_DONE must still be preserved (e.g. + # providers that emit only OUTPUT_TEXT_DONE for some indices). + merged_items: Dict[int, dict] = {**text_only_output_items} + merged_items.update(streamed_output_items) + completed_response = self._build_completed_response_from_chunk( + parsed_chunk=parsed_chunk, + streamed_output_items=merged_items, + ) + break + + if event_type in ( + ResponsesAPIStreamEvents.RESPONSE_FAILED, + ResponsesAPIStreamEvents.ERROR, + ): + extracted_error = self._extract_error_message(parsed_chunk) + if extracted_error is not None: + error_message = extracted_error + + return completed_response, error_message + + def _build_completed_response_from_chunk( + self, parsed_chunk: Dict[str, Any], streamed_output_items: Dict[int, dict] + ) -> Optional[ResponsesAPIResponse]: + response_payload = parsed_chunk.get("response") + if not isinstance(response_payload, dict): + return None + response_payload = dict(response_payload) + if not response_payload.get("output") and streamed_output_items: + response_payload["output"] = [ + item for _, item in sorted(streamed_output_items.items()) + ] + if "created_at" in response_payload: + response_payload["created_at"] = _safe_convert_created_field( + response_payload["created_at"] + ) + try: + return ResponsesAPIResponse(**response_payload) + except Exception: + return ResponsesAPIResponse.model_construct(**response_payload) + + def _extract_error_message(self, parsed_chunk: Dict[str, Any]) -> Optional[str]: + error_obj = parsed_chunk.get("error") or ( + parsed_chunk.get("response") or {} + ).get("error") + if error_obj is None: + return None + if isinstance(error_obj, dict): + return error_obj.get("message") or str(error_obj) + return str(error_obj) + + def _attach_response_headers( + self, + completed_response: ResponsesAPIResponse, + raw_response: Any, + ) -> None: raw_headers = dict(raw_response.headers) processed_headers = process_response_headers(raw_headers) if not hasattr(completed_response, "_hidden_params"): setattr(completed_response, "_hidden_params", {}) completed_response._hidden_params["additional_headers"] = processed_headers completed_response._hidden_params["headers"] = raw_headers - return completed_response def get_complete_url( self, diff --git a/litellm/llms/cohere/embed/handler.py b/litellm/llms/cohere/embed/handler.py index 3ab8baf7ba8..81b6a1c7aec 100644 --- a/litellm/llms/cohere/embed/handler.py +++ b/litellm/llms/cohere/embed/handler.py @@ -1,5 +1,5 @@ """ -Legacy /v1/embedding handler for Bedrock Cohere. +Legacy /v1/embedding handler for Bedrock Cohere. """ import json diff --git a/litellm/llms/custom_httpx/llm_http_handler.py b/litellm/llms/custom_httpx/llm_http_handler.py index d2af0a3dd52..96fdf4494f9 100644 --- a/litellm/llms/custom_httpx/llm_http_handler.py +++ b/litellm/llms/custom_httpx/llm_http_handler.py @@ -1409,6 +1409,8 @@ class BaseLLMHTTPHandler: document=document, optional_params=optional_params, headers=headers, + api_key=api_key, + api_base=api_base, ) # All providers return OCRRequestData @@ -1477,6 +1479,8 @@ class BaseLLMHTTPHandler: document=document, optional_params=optional_params, headers=headers, + api_key=api_key, + api_base=api_base, ) # All providers return OCRRequestData diff --git a/litellm/llms/custom_httpx/mock_transport.py b/litellm/llms/custom_httpx/mock_transport.py index c9844753e0e..ad93cc134ee 100644 --- a/litellm/llms/custom_httpx/mock_transport.py +++ b/litellm/llms/custom_httpx/mock_transport.py @@ -13,7 +13,6 @@ from typing import Tuple import httpx - # --------------------------------------------------------------------------- # Pre-built response templates # --------------------------------------------------------------------------- diff --git a/litellm/llms/dashscope/cost_calculator.py b/litellm/llms/dashscope/cost_calculator.py index 9b3e3851162..8bb7f605b82 100644 --- a/litellm/llms/dashscope/cost_calculator.py +++ b/litellm/llms/dashscope/cost_calculator.py @@ -1,5 +1,5 @@ """ -Cost calculator for Dashscope Chat models. +Cost calculator for Dashscope Chat models. Handles tiered pricing and prompt caching scenarios. """ diff --git a/litellm/llms/datarobot/chat/transformation.py b/litellm/llms/datarobot/chat/transformation.py index 23ce63c25b2..f81e2420930 100644 --- a/litellm/llms/datarobot/chat/transformation.py +++ b/litellm/llms/datarobot/chat/transformation.py @@ -1,5 +1,5 @@ """ -Support for OpenAI's `/v1/chat/completions` endpoint. +Support for OpenAI's `/v1/chat/completions` endpoint. Calls done in OpenAI/openai.py as DataRobot is openai-compatible. """ diff --git a/litellm/llms/deepinfra/rerank/transformation.py b/litellm/llms/deepinfra/rerank/transformation.py index 276735f4758..e4bfbcb2513 100644 --- a/litellm/llms/deepinfra/rerank/transformation.py +++ b/litellm/llms/deepinfra/rerank/transformation.py @@ -1,5 +1,5 @@ """ -Translate between Cohere's `/rerank` format and Deepinfra's `/rerank` format. +Translate between Cohere's `/rerank` format and Deepinfra's `/rerank` format. """ from typing import Any, Dict, List, Optional, Union diff --git a/litellm/llms/deepseek/cost_calculator.py b/litellm/llms/deepseek/cost_calculator.py index 0f4490cb3df..e652ebeac54 100644 --- a/litellm/llms/deepseek/cost_calculator.py +++ b/litellm/llms/deepseek/cost_calculator.py @@ -1,5 +1,5 @@ """ -Cost calculator for DeepSeek Chat models. +Cost calculator for DeepSeek Chat models. Handles prompt caching scenario. """ diff --git a/litellm/llms/elevenlabs/text_to_speech/transformation.py b/litellm/llms/elevenlabs/text_to_speech/transformation.py index 6a59911701b..612fc687ef9 100644 --- a/litellm/llms/elevenlabs/text_to_speech/transformation.py +++ b/litellm/llms/elevenlabs/text_to_speech/transformation.py @@ -22,7 +22,6 @@ from litellm.types.utils import all_litellm_params from ..common_utils import ElevenLabsException - if TYPE_CHECKING: from litellm.litellm_core_utils.litellm_logging import Logging as LiteLLMLoggingObj from litellm.types.llms.openai import HttpxBinaryResponseContent diff --git a/litellm/llms/fireworks_ai/chat/transformation.py b/litellm/llms/fireworks_ai/chat/transformation.py index eaf01c5fe18..d39adf0b6f4 100644 --- a/litellm/llms/fireworks_ai/chat/transformation.py +++ b/litellm/llms/fireworks_ai/chat/transformation.py @@ -4,6 +4,7 @@ from typing import Any, List, Literal, Optional, Tuple, Union, cast import httpx import litellm +from litellm._logging import verbose_logger from litellm._uuid import uuid from litellm.constants import RESPONSE_FORMAT_TOOL_NAME from litellm.litellm_core_utils.litellm_logging import Logging as LiteLLMLoggingObj @@ -26,6 +27,7 @@ from litellm.types.utils import ( ProviderSpecificModelInfo, ) from litellm.utils import ( + get_model_cost_mutation_generation, supports_function_calling, supports_reasoning, supports_tool_choice, @@ -112,6 +114,19 @@ class FireworksAIConfig(OpenAIGPTConfig): # Only add tools for models that support function calling if supports_function_calling(model=model, custom_llm_provider="fireworks_ai"): supported_params.append("tools") + supported_params.append("parallel_tool_calls") + else: + # Historically every Fireworks model advertised tool support, so a + # JSON entry that flips `supports_function_calling` to false will + # silently drop `tools` from requests. Surface this so users can + # tell why their tool calls suddenly stop working. + verbose_logger.debug( + "fireworks_ai model %r is marked as not supporting " + "function calling in model_prices_and_context_window.json; " + "`tools` and `parallel_tool_calls` will be dropped from the " + "request.", + model, + ) # Only add tool_choice for models that explicitly support it if supports_tool_choice(model=model, custom_llm_provider="fireworks_ai"): @@ -251,34 +266,100 @@ class FireworksAIConfig(OpenAIGPTConfig): return messages - def get_provider_info(self, model: str) -> ProviderSpecificModelInfo: - # Models that support reasoning_effort - reasoning_supported_models = [ - "qwen3-8b", - "qwen3-32b", - "qwen3-coder-480b-a35b-instruct", - "deepseek-v3p1", - "deepseek-v3p2", - "glm-4p5", - "glm-4p5-air", - "glm-4p6", - "gpt-oss-120b", - "gpt-oss-20b", + # Cached index of fireworks_ai/* entries from litellm.model_cost. Building + # this index requires a full scan of model_cost (tens of thousands of + # entries), so we memoize it. The cache key is (id(model_cost), + # mutation_generation): the generation counter is bumped on every + # register_model / reload path, so add+remove or in-place value + # replacement (which can leave id and len unchanged) still invalidates. + _fireworks_index_cache: Optional[Tuple[int, int, List[Tuple[str, dict]]]] = None + + @classmethod + def _get_fireworks_index(cls) -> List[Tuple[str, dict]]: + model_cost = litellm.model_cost + signature = (id(model_cost), get_model_cost_mutation_generation()) + cached = cls._fireworks_index_cache + if ( + cached is not None + and cached[0] == signature[0] + and cached[1] == signature[1] + ): + return cached[2] + + index: List[Tuple[str, dict]] = [] + for key, model_info in model_cost.items(): + if not key.startswith("fireworks_ai/"): + continue + if not isinstance(model_info, dict): + continue + key_short = key[len("fireworks_ai/") :] + if key_short.startswith("accounts/fireworks/models/"): + key_short = key_short[len("accounts/fireworks/models/") :] + if not key_short: + continue + index.append((key_short, model_info)) + + cls._fireworks_index_cache = (signature[0], signature[1], index) + return index + + @staticmethod + def _matches_on_hyphen_boundary(short_name: str, key_short: str) -> bool: + """Return True if `key_short` appears in `short_name` aligned to + hyphen-separated word boundaries (or end-of-string). This avoids + spurious substring matches like `"some-model"` matching + `"awesome-model"`.""" + if short_name == key_short: + return True + if short_name.startswith(key_short + "-"): + return True + if short_name.endswith("-" + key_short): + return True + return ("-" + key_short + "-") in short_name + + def _get_model_cost_capability(self, model: str, capability: str) -> Optional[bool]: + short_name = model + if short_name.startswith("fireworks_ai/"): + short_name = short_name[len("fireworks_ai/") :] + if short_name.startswith("accounts/fireworks/models/"): + short_name = short_name[len("accounts/fireworks/models/") :] + + candidate_keys = [ + model, + f"fireworks_ai/{short_name}", + f"fireworks_ai/accounts/fireworks/models/{short_name}", ] - # Normalize model name - remove prefix if present - normalized_model = model - if model.startswith("fireworks_ai/"): - normalized_model = model.replace("fireworks_ai/", "") - if normalized_model.startswith("accounts/fireworks/models/"): - normalized_model = normalized_model.replace( - "accounts/fireworks/models/", "" - ) + for candidate_key in candidate_keys: + model_info = litellm.model_cost.get(candidate_key) + if model_info is not None and model_info.get(capability) is not None: + return cast(Optional[bool], model_info.get(capability)) - # Check if model supports reasoning - supports_reasoning_value = any( - reasoning_model in normalized_model - for reasoning_model in reasoning_supported_models + # Fallback: preserve historical substring matching for model name + # variants (e.g. fine-tuned or regionally-suffixed versions of a + # known model). Pick the *longest* matching entry so a more specific + # known model (e.g. "qwen3-8b-instruct") wins over a less specific + # one (e.g. "qwen3-8b") when the query model is more specific still. + # Use hyphen-aligned matching to avoid false positives where a short + # known model name is an unrelated substring of a longer one. + best_match_short: Optional[str] = None + best_match_value: Optional[bool] = None + for key_short, model_info in self._get_fireworks_index(): + if model_info.get(capability) is None: + continue + if not self._matches_on_hyphen_boundary(short_name, key_short): + continue + if best_match_short is None or len(key_short) > len(best_match_short): + best_match_short = key_short + best_match_value = cast(Optional[bool], model_info.get(capability)) + + return best_match_value + + def get_provider_info(self, model: str) -> ProviderSpecificModelInfo: + supports_function_calling_value = self._get_model_cost_capability( + model=model, capability="supports_function_calling" + ) + supports_reasoning_value = self._get_model_cost_capability( + model=model, capability="supports_reasoning" ) provider_specific_model_info: ProviderSpecificModelInfo = { @@ -288,9 +369,16 @@ class FireworksAIConfig(OpenAIGPTConfig): "supports_vision": True, # via document inlining } + if supports_function_calling_value is not None: + provider_specific_model_info["supports_function_calling"] = ( + supports_function_calling_value + ) + # Only include supports_reasoning if True if supports_reasoning_value: - provider_specific_model_info["supports_reasoning"] = True + provider_specific_model_info["supports_reasoning"] = ( + supports_reasoning_value + ) return provider_specific_model_info diff --git a/litellm/llms/gemini/agents/transformation.py b/litellm/llms/gemini/agents/transformation.py index 150918c4737..f6e0b95cf28 100644 --- a/litellm/llms/gemini/agents/transformation.py +++ b/litellm/llms/gemini/agents/transformation.py @@ -23,7 +23,6 @@ from litellm.types.agents import ( AgentVersionsResponse, ) - # Keys inside litellm_params that should be forwarded to the Gemini # create-agent body verbatim. _GEMINI_AGENT_BODY_KEYS = ("base_agent", "instructions", "base_environment") diff --git a/litellm/llms/gemini/videos/transformation.py b/litellm/llms/gemini/videos/transformation.py index c7116940b22..9714c8a3923 100644 --- a/litellm/llms/gemini/videos/transformation.py +++ b/litellm/llms/gemini/videos/transformation.py @@ -55,7 +55,7 @@ def _convert_image_to_gemini_format(image_file) -> Dict[str, str]: def _usage_video_resolution_from_parameters( - parameters: Dict[str, Any] + parameters: Dict[str, Any], ) -> Optional[str]: """Normalize Veo ``parameters.resolution`` for usage and cost tracking.""" res = parameters.get("resolution") diff --git a/litellm/llms/infinity/rerank/transformation.py b/litellm/llms/infinity/rerank/transformation.py index 314bf2f8a36..b9804605454 100644 --- a/litellm/llms/infinity/rerank/transformation.py +++ b/litellm/llms/infinity/rerank/transformation.py @@ -1,5 +1,5 @@ """ -Transformation logic from Cohere's /v1/rerank format to Infinity's `/v1/rerank` format. +Transformation logic from Cohere's /v1/rerank format to Infinity's `/v1/rerank` format. Why separate file? Make it easy to see how transformation works """ diff --git a/litellm/llms/jina_ai/rerank/transformation.py b/litellm/llms/jina_ai/rerank/transformation.py index ad4416925a6..56be754fc34 100644 --- a/litellm/llms/jina_ai/rerank/transformation.py +++ b/litellm/llms/jina_ai/rerank/transformation.py @@ -1,5 +1,5 @@ """ -Transformation logic from Cohere's /v1/rerank format to Jina AI's `/v1/rerank` format. +Transformation logic from Cohere's /v1/rerank format to Jina AI's `/v1/rerank` format. Why separate file? Make it easy to see how transformation works diff --git a/litellm/llms/lm_studio/embed/transformation.py b/litellm/llms/lm_studio/embed/transformation.py index 1285550c30f..87f4f6e73d5 100644 --- a/litellm/llms/lm_studio/embed/transformation.py +++ b/litellm/llms/lm_studio/embed/transformation.py @@ -1,5 +1,5 @@ """ -Transformation logic from OpenAI /v1/embeddings format to LM Studio's `/v1/embeddings` format. +Transformation logic from OpenAI /v1/embeddings format to LM Studio's `/v1/embeddings` format. Why separate file? Make it easy to see how transformation works diff --git a/litellm/llms/novita/chat/transformation.py b/litellm/llms/novita/chat/transformation.py index c05d2d7b2c5..5a64a124ade 100644 --- a/litellm/llms/novita/chat/transformation.py +++ b/litellm/llms/novita/chat/transformation.py @@ -1,5 +1,5 @@ """ -Support for OpenAI's `/v1/chat/completions` endpoint. +Support for OpenAI's `/v1/chat/completions` endpoint. Calls done in OpenAI/openai.py as Novita AI is openai-compatible. diff --git a/litellm/llms/nvidia_nim/chat/transformation.py b/litellm/llms/nvidia_nim/chat/transformation.py index b8f8b04eb53..2ef92a90626 100644 --- a/litellm/llms/nvidia_nim/chat/transformation.py +++ b/litellm/llms/nvidia_nim/chat/transformation.py @@ -1,7 +1,7 @@ """ -Nvidia NIM endpoint: https://docs.api.nvidia.com/nim/reference/databricks-dbrx-instruct-infer +Nvidia NIM endpoint: https://docs.api.nvidia.com/nim/reference/databricks-dbrx-instruct-infer -This is OpenAI compatible +This is OpenAI compatible This file only contains param mapping logic diff --git a/litellm/llms/nvidia_nim/embed.py b/litellm/llms/nvidia_nim/embed.py index 24c6cc34e4d..61c8e8244e4 100644 --- a/litellm/llms/nvidia_nim/embed.py +++ b/litellm/llms/nvidia_nim/embed.py @@ -1,7 +1,7 @@ """ Nvidia NIM embeddings endpoint: https://docs.api.nvidia.com/nim/reference/nvidia-nv-embedqa-e5-v5-infer -This is OpenAI compatible +This is OpenAI compatible This file only contains param mapping logic diff --git a/litellm/llms/openai/chat/o_series_transformation.py b/litellm/llms/openai/chat/o_series_transformation.py index 02ae2cc9750..8db7ecf7b3a 100644 --- a/litellm/llms/openai/chat/o_series_transformation.py +++ b/litellm/llms/openai/chat/o_series_transformation.py @@ -1,14 +1,14 @@ """ -Support for o1/o3 model family +Support for o1/o3 model family https://platform.openai.com/docs/guides/reasoning Translations handled by LiteLLM: -- modalities: image => drop param (if user opts in to dropping param) -- role: system ==> translate to role 'user' -- streaming => faked by LiteLLM -- Tools, response_format => drop param (if user opts in to dropping param) -- Logprobs => drop param (if user opts in to dropping param) +- modalities: image => drop param (if user opts in to dropping param) +- role: system ==> translate to role 'user' +- streaming => faked by LiteLLM +- Tools, response_format => drop param (if user opts in to dropping param) +- Logprobs => drop param (if user opts in to dropping param) """ from typing import Any, Coroutine, List, Literal, Optional, Union, cast, overload diff --git a/litellm/llms/openai/common_utils.py b/litellm/llms/openai/common_utils.py index c13a976c1b9..381f215a13f 100644 --- a/litellm/llms/openai/common_utils.py +++ b/litellm/llms/openai/common_utils.py @@ -201,7 +201,7 @@ class BaseOpenAILLM: @staticmethod def get_openai_client_initialization_param_fields( - client_type: Literal["openai", "azure"] + client_type: Literal["openai", "azure"], ) -> Tuple[str, ...]: """Returns a tuple of fields that are used to initialize the OpenAI client""" if client_type == "openai": diff --git a/litellm/llms/openrouter/image_generation/transformation.py b/litellm/llms/openrouter/image_generation/transformation.py index a55716a5e50..9c2293eb3f1 100644 --- a/litellm/llms/openrouter/image_generation/transformation.py +++ b/litellm/llms/openrouter/image_generation/transformation.py @@ -49,7 +49,6 @@ from litellm.types.utils import ( ) from litellm.llms.openrouter.common_utils import OpenRouterException - if TYPE_CHECKING: from litellm.litellm_core_utils.litellm_logging import Logging as LiteLLMLoggingObj else: diff --git a/litellm/llms/reducto/__init__.py b/litellm/llms/reducto/__init__.py new file mode 100644 index 00000000000..8b137891791 --- /dev/null +++ b/litellm/llms/reducto/__init__.py @@ -0,0 +1 @@ + diff --git a/litellm/llms/reducto/common.py b/litellm/llms/reducto/common.py new file mode 100644 index 00000000000..4e7d96dbe87 --- /dev/null +++ b/litellm/llms/reducto/common.py @@ -0,0 +1,159 @@ +import base64 +import binascii +from collections import defaultdict +from typing import TYPE_CHECKING, Any, Dict, List, NoReturn, Optional, Tuple + +from litellm.constants import request_timeout + +REDUCTO_API_BASE = "https://platform.reducto.ai" +REDUCTO_ID_PREFIX = "reducto://" + +if TYPE_CHECKING: + from litellm.llms.base_llm.ocr.transformation import OCRPage + + +def _normalize_api_base(api_base: Optional[str]) -> str: + return (api_base or REDUCTO_API_BASE).rstrip("/") + + +def _raise_bad_request(message: str, model: str) -> NoReturn: + import litellm + + raise litellm.BadRequestError( + message=message, + model=model, + llm_provider="reducto", + ) + + +def extract_file_id_or_bytes( + source_url: str, + model: str, +) -> Tuple[Optional[str], Optional[bytes], Optional[str]]: + if source_url.startswith(REDUCTO_ID_PREFIX): + return source_url, None, None + + if source_url.startswith("http://") or source_url.startswith("https://"): + _raise_bad_request( + "Reducto requires type='file' (auto-uploaded) or a reducto:// id. Plain http(s) URLs are not supported; upload the file first.", + model=model, + ) + + if not source_url.startswith("data:"): + _raise_bad_request( + "Reducto requires a reducto:// id or a base64 data URI after OCR preprocessing.", + model=model, + ) + + try: + header, encoded = source_url.split(",", 1) + except ValueError: + _raise_bad_request("Invalid Reducto data URI provided.", model=model) + + if ";base64" not in header: + _raise_bad_request( + "Reducto only supports base64-encoded data URIs.", model=model + ) + + mime = header.removeprefix("data:").split(";")[0] or "application/octet-stream" + try: + raw_bytes = base64.b64decode(encoded, validate=True) + except (binascii.Error, ValueError): + _raise_bad_request("Invalid Reducto base64 payload provided.", model=model) + + return None, raw_bytes, mime + + +def _extract_file_id_from_upload_response(response: Any) -> str: + try: + payload = response.json() + except ValueError as exc: + raise ValueError( + "Reducto /upload returned a non-JSON 200 response: {}".format(response.text) + ) from exc + file_id = (payload or {}).get("file_id") if isinstance(payload, dict) else None + if not isinstance(file_id, str) or not file_id: + raise ValueError( + "Reducto /upload returned 200 without a file_id; got payload={}".format( + payload + ) + ) + return file_id + + +def upload_bytes_sync( + raw_bytes: bytes, + mime: Optional[str], + api_key: str, + api_base: Optional[str], +) -> str: + import litellm + + response = litellm.module_level_client.post( + url="{}{}".format(_normalize_api_base(api_base), "/upload"), + headers={"Authorization": f"Bearer {api_key}"}, + files={"file": ("document", raw_bytes, mime or "application/octet-stream")}, + timeout=request_timeout, + ) + response.raise_for_status() + return _extract_file_id_from_upload_response(response) + + +async def upload_bytes_async( + raw_bytes: bytes, + mime: Optional[str], + api_key: str, + api_base: Optional[str], +) -> str: + import litellm + + response = await litellm.module_level_aclient.post( + url="{}{}".format(_normalize_api_base(api_base), "/upload"), + headers={"Authorization": f"Bearer {api_key}"}, + files={"file": ("document", raw_bytes, mime or "application/octet-stream")}, + timeout=request_timeout, + ) + response.raise_for_status() + return _extract_file_id_from_upload_response(response) + + +def build_pages_from_reducto(result: Dict[str, Any]) -> List["OCRPage"]: + from litellm.llms.base_llm.ocr.transformation import OCRPage + + chunks = result.get("chunks", []) or [] + blocks_by_page: Dict[int, List[Dict[str, Any]]] = defaultdict(list) + + for chunk in chunks: + for block in chunk.get("blocks", []) or []: + page_no = (block.get("bbox") or {}).get("page") + if page_no is None: + continue + try: + normalized_page = int(page_no) + except (TypeError, ValueError): + continue + blocks_by_page[normalized_page].append(block) + + if not blocks_by_page: + fallback_markdown = "\n\n".join( + chunk.get("content", "") for chunk in chunks if chunk.get("content") + ) + if fallback_markdown == "": + return [] + return [OCRPage(index=0, markdown=fallback_markdown)] + + pages: List["OCRPage"] = [] + for page_no, blocks in sorted(blocks_by_page.items()): + markdown = "\n\n".join( + block.get("content", "") for block in blocks if block.get("content") + ) + page_index = max(page_no - 1, 0) + page = OCRPage( + index=page_index, + markdown=markdown, + ) + # OCRPage accepts extra keys at runtime; assign blocks after construction + # so static typing does not reject provider-specific metadata. + setattr(page, "blocks", blocks) + pages.append(page) + return pages diff --git a/litellm/llms/reducto/ocr/__init__.py b/litellm/llms/reducto/ocr/__init__.py new file mode 100644 index 00000000000..8b137891791 --- /dev/null +++ b/litellm/llms/reducto/ocr/__init__.py @@ -0,0 +1 @@ + diff --git a/litellm/llms/reducto/ocr/transformation.py b/litellm/llms/reducto/ocr/transformation.py new file mode 100644 index 00000000000..cc338ecc484 --- /dev/null +++ b/litellm/llms/reducto/ocr/transformation.py @@ -0,0 +1,241 @@ +from typing import Any, Dict, Optional, Tuple + +import httpx + +from litellm.llms.base_llm.ocr.transformation import ( + BaseOCRConfig, + DocumentType, + OCRRequestData, + OCRResponse, + OCRUsageInfo, +) +from litellm.llms.reducto.common import ( + REDUCTO_API_BASE, + build_pages_from_reducto, + extract_file_id_or_bytes, + upload_bytes_async, + upload_bytes_sync, +) + + +class _BaseReductoOCRConfig(BaseOCRConfig): + def map_ocr_params( + self, + non_default_params: dict, + optional_params: dict, + model: str, + ) -> dict: + mapped_params = dict(optional_params) + supported_params = self.get_supported_ocr_params(model=model) + for param, value in non_default_params.items(): + if param in supported_params: + mapped_params[param] = value + return mapped_params + + def validate_environment( + self, + headers: Dict, + model: str, + api_key: Optional[str] = None, + api_base: Optional[str] = None, + litellm_params: Optional[dict] = None, + **kwargs, + ) -> Dict: + from litellm.secret_managers.main import get_secret_str + + resolved_key = api_key or get_secret_str("REDUCTO_API_KEY") + if resolved_key is None: + raise ValueError( + "Missing REDUCTO_API_KEY - set it in the environment or pass api_key to litellm.ocr()/litellm.aocr()" + ) + + return { + "Authorization": f"Bearer {resolved_key}", + "Content-Type": "application/json", + **headers, + } + + def get_complete_url( + self, + api_base: Optional[str], + model: str, + optional_params: dict, + litellm_params: Optional[dict] = None, + **kwargs, + ) -> str: + return "{}/parse".format((api_base or REDUCTO_API_BASE).rstrip("/")) + + def _get_source_url(self, document: DocumentType, model: str) -> str: + source_url = document.get("document_url") or document.get("image_url") + if source_url is None: + raise ValueError( + "Reducto expected OCR preprocessing to produce document_url or image_url for model={}".format( + model + ) + ) + return source_url + + @staticmethod + def _resolve_credentials( + api_key: Optional[str], api_base: Optional[str] + ) -> Tuple[str, str]: + from litellm.secret_managers.main import get_secret_str + + resolved_key = api_key or get_secret_str("REDUCTO_API_KEY") + if resolved_key is None: + raise ValueError( + "Missing REDUCTO_API_KEY - set it in the environment or pass api_key to litellm.ocr()/litellm.aocr()" + ) + resolved_base = (api_base or REDUCTO_API_BASE).rstrip("/") + return resolved_key, resolved_base + + def _ensure_file_id_sync( + self, + model: str, + document: DocumentType, + api_key: Optional[str], + api_base: Optional[str], + ) -> str: + source_url = self._get_source_url(document=document, model=model) + file_id, raw_bytes, mime = extract_file_id_or_bytes(source_url, model=model) + if file_id is not None: + return file_id + resolved_key, resolved_base = self._resolve_credentials(api_key, api_base) + return upload_bytes_sync( + raw_bytes=raw_bytes or b"", + mime=mime, + api_key=resolved_key, + api_base=resolved_base, + ) + + async def _ensure_file_id_async( + self, + model: str, + document: DocumentType, + api_key: Optional[str], + api_base: Optional[str], + ) -> str: + source_url = self._get_source_url(document=document, model=model) + file_id, raw_bytes, mime = extract_file_id_or_bytes(source_url, model=model) + if file_id is not None: + return file_id + resolved_key, resolved_base = self._resolve_credentials(api_key, api_base) + return await upload_bytes_async( + raw_bytes=raw_bytes or b"", + mime=mime, + api_key=resolved_key, + api_base=resolved_base, + ) + + def transform_ocr_response( + self, + model: str, + raw_response: httpx.Response, + logging_obj: Any, + **kwargs, + ) -> OCRResponse: + response_json = raw_response.json() + result = response_json.get("result", response_json) or {} + usage = response_json.get("usage", {}) or {} + response = OCRResponse( + pages=build_pages_from_reducto(result), + model=model, + usage_info=OCRUsageInfo( + pages_processed=usage.get("num_pages"), + credits=usage.get("credits"), + ), + object="ocr", + ) + response._hidden_params["reducto_raw"] = response_json + return response + + +class ReductoParseV3Config(_BaseReductoOCRConfig): + def get_supported_ocr_params(self, model: str) -> list: + return ["formatting", "retrieval", "settings"] + + def transform_ocr_request( + self, + model: str, + document: DocumentType, + optional_params: dict, + headers: dict, + **kwargs, + ) -> OCRRequestData: + file_id = self._ensure_file_id_sync( + model=model, + document=document, + api_key=kwargs.get("api_key"), + api_base=kwargs.get("api_base"), + ) + return OCRRequestData(data={"input": file_id, **optional_params}, files=None) + + async def async_transform_ocr_request( + self, + model: str, + document: DocumentType, + optional_params: dict, + headers: dict, + **kwargs, + ) -> OCRRequestData: + file_id = await self._ensure_file_id_async( + model=model, + document=document, + api_key=kwargs.get("api_key"), + api_base=kwargs.get("api_base"), + ) + return OCRRequestData(data={"input": file_id, **optional_params}, files=None) + + +class ReductoParseLegacyConfig(_BaseReductoOCRConfig): + def get_supported_ocr_params(self, model: str) -> list: + return ["enhance"] + + def _build_legacy_body(self, file_id: str, optional_params: dict) -> Dict[str, Any]: + body: Dict[str, Any] = {"document_url": file_id} + enhance = optional_params.get("enhance") + if enhance is not None: + body["options"] = {"enhance": enhance} + return body + + def transform_ocr_request( + self, + model: str, + document: DocumentType, + optional_params: dict, + headers: dict, + **kwargs, + ) -> OCRRequestData: + file_id = self._ensure_file_id_sync( + model=model, + document=document, + api_key=kwargs.get("api_key"), + api_base=kwargs.get("api_base"), + ) + return OCRRequestData( + data=self._build_legacy_body( + file_id=file_id, optional_params=optional_params + ), + files=None, + ) + + async def async_transform_ocr_request( + self, + model: str, + document: DocumentType, + optional_params: dict, + headers: dict, + **kwargs, + ) -> OCRRequestData: + file_id = await self._ensure_file_id_async( + model=model, + document=document, + api_key=kwargs.get("api_key"), + api_base=kwargs.get("api_base"), + ) + return OCRRequestData( + data=self._build_legacy_body( + file_id=file_id, optional_params=optional_params + ), + files=None, + ) diff --git a/litellm/llms/sagemaker/completion/transformation.py b/litellm/llms/sagemaker/completion/transformation.py index 3e4e2460cdb..8fd32bc4460 100644 --- a/litellm/llms/sagemaker/completion/transformation.py +++ b/litellm/llms/sagemaker/completion/transformation.py @@ -1,7 +1,7 @@ """ Translate from OpenAI's `/v1/chat/completions` to Sagemaker's `/invoke` -In the Huggingface TGI format. +In the Huggingface TGI format. """ import json diff --git a/litellm/llms/sagemaker/embedding/transformation.py b/litellm/llms/sagemaker/embedding/transformation.py index 04430171187..09bdb9295e7 100644 --- a/litellm/llms/sagemaker/embedding/transformation.py +++ b/litellm/llms/sagemaker/embedding/transformation.py @@ -1,7 +1,7 @@ """ Translate from OpenAI's `/v1/embeddings` to Sagemaker's `/invoke` -In the Huggingface TGI format. +In the Huggingface TGI format. """ from typing import TYPE_CHECKING, Any, List, Optional, Union diff --git a/litellm/llms/sap/credentials.py b/litellm/llms/sap/credentials.py index 0ae351783e8..dd307ddf496 100644 --- a/litellm/llms/sap/credentials.py +++ b/litellm/llms/sap/credentials.py @@ -207,7 +207,7 @@ def resolve_resource_group(sources: List[Source]) -> Optional[str]: def _parse_service_key_once( - service_key: Optional[Union[str, dict]] + service_key: Optional[Union[str, dict]], ) -> Optional[Dict[str, Any]]: """ Pre-parse service_key if it's a string to avoid repeated JSON parsing. diff --git a/litellm/llms/snowflake/chat/transformation.py b/litellm/llms/snowflake/chat/transformation.py index 3e590680a75..23bb6f44757 100644 --- a/litellm/llms/snowflake/chat/transformation.py +++ b/litellm/llms/snowflake/chat/transformation.py @@ -14,7 +14,6 @@ from ...openai_like.chat.transformation import OpenAIGPTConfig from ..utils import SnowflakeBaseConfig - if TYPE_CHECKING: from litellm.litellm_core_utils.litellm_logging import Logging as _LiteLLMLoggingObj diff --git a/litellm/llms/together_ai/chat.py b/litellm/llms/together_ai/chat.py index 7efb12fc1b2..238849cc1ec 100644 --- a/litellm/llms/together_ai/chat.py +++ b/litellm/llms/together_ai/chat.py @@ -1,5 +1,5 @@ """ -Support for OpenAI's `/v1/chat/completions` endpoint. +Support for OpenAI's `/v1/chat/completions` endpoint. Calls done in OpenAI/openai.py as TogetherAI is openai-compatible. diff --git a/litellm/llms/together_ai/embed.py b/litellm/llms/together_ai/embed.py index 577df0256cc..6a39b94acfc 100644 --- a/litellm/llms/together_ai/embed.py +++ b/litellm/llms/together_ai/embed.py @@ -1,5 +1,5 @@ """ -Support for OpenAI's `/v1/embeddings` endpoint. +Support for OpenAI's `/v1/embeddings` endpoint. Calls done in OpenAI/openai.py as TogetherAI is openai-compatible. diff --git a/litellm/llms/together_ai/rerank/transformation.py b/litellm/llms/together_ai/rerank/transformation.py index 63b593dfe42..f4d642bd25a 100644 --- a/litellm/llms/together_ai/rerank/transformation.py +++ b/litellm/llms/together_ai/rerank/transformation.py @@ -1,5 +1,5 @@ """ -Transformation logic from Cohere's /v1/rerank format to Together AI's `/v1/rerank` format. +Transformation logic from Cohere's /v1/rerank format to Together AI's `/v1/rerank` format. Why separate file? Make it easy to see how transformation works """ diff --git a/litellm/llms/vertex_ai/context_caching/transformation.py b/litellm/llms/vertex_ai/context_caching/transformation.py index 3d532113ba0..f73eb220cc6 100644 --- a/litellm/llms/vertex_ai/context_caching/transformation.py +++ b/litellm/llms/vertex_ai/context_caching/transformation.py @@ -1,5 +1,5 @@ """ -Transformation logic for context caching. +Transformation logic for context caching. Why separate file? Make it easy to see how transformation works """ @@ -19,7 +19,7 @@ from ..gemini.transformation import ( def get_first_continuous_block_idx( - filtered_messages: List[Tuple[int, AllMessageValues]] # (idx, message) + filtered_messages: List[Tuple[int, AllMessageValues]], # (idx, message) ) -> int: """ Find the array index that ends the first continuous sequence of message blocks. diff --git a/litellm/llms/vertex_ai/context_caching/vertex_ai_context_caching.py b/litellm/llms/vertex_ai/context_caching/vertex_ai_context_caching.py index ac0f07b8e0b..3f945adca0d 100644 --- a/litellm/llms/vertex_ai/context_caching/vertex_ai_context_caching.py +++ b/litellm/llms/vertex_ai/context_caching/vertex_ai_context_caching.py @@ -41,7 +41,7 @@ class ContextCachingEndpoints(VertexBase): """ def __init__(self) -> None: - pass + super().__init__() def _get_token_and_url_context_caching( self, diff --git a/litellm/llms/vertex_ai/gemini/transformation.py b/litellm/llms/vertex_ai/gemini/transformation.py index 2995edd1e07..4f5846cc5b6 100644 --- a/litellm/llms/vertex_ai/gemini/transformation.py +++ b/litellm/llms/vertex_ai/gemini/transformation.py @@ -1073,16 +1073,14 @@ def _gemini_convert_messages_with_history( # noqa: PLR0915 contents.append(ContentType(role="user", parts=tool_call_responses)) if len(contents) == 0: - verbose_logger.warning( - """ + verbose_logger.warning(""" No contents in messages. Contents are required. See https://cloud.google.com/vertex-ai/docs/reference/rest/v1/projects.locations.publishers.models/generateContent#request-body. If the original request did not comply to OpenAI API requirements it should have failed by now, but LiteLLM does not check for missing messages. Setting an empty content to prevent an 400 error. Relevant Issue - https://github.com/BerriAI/litellm/issues/9733 - """ - ) + """) contents.append(ContentType(role="user", parts=[PartType(text=" ")])) return contents except Exception as e: diff --git a/litellm/llms/vertex_ai/gemini_embeddings/batch_embed_content_transformation.py b/litellm/llms/vertex_ai/gemini_embeddings/batch_embed_content_transformation.py index e1b365c9f42..ba6e6f0c056 100644 --- a/litellm/llms/vertex_ai/gemini_embeddings/batch_embed_content_transformation.py +++ b/litellm/llms/vertex_ai/gemini_embeddings/batch_embed_content_transformation.py @@ -1,5 +1,5 @@ """ -Transformation logic from OpenAI /v1/embeddings format to Google AI Studio /batchEmbedContents format. +Transformation logic from OpenAI /v1/embeddings format to Google AI Studio /batchEmbedContents format. Why separate file? Make it easy to see how transformation works """ diff --git a/litellm/llms/vertex_ai/text_to_speech/text_to_speech_handler.py b/litellm/llms/vertex_ai/text_to_speech/text_to_speech_handler.py index 9d9015c2b91..b835ad7d8fa 100644 --- a/litellm/llms/vertex_ai/text_to_speech/text_to_speech_handler.py +++ b/litellm/llms/vertex_ai/text_to_speech/text_to_speech_handler.py @@ -139,7 +139,7 @@ class VertexTextToSpeechAPI(VertexLLM): ########## End of logging ############ ####### Send the request ################### if _is_async is True: - return self.async_audio_speech( # type:ignore + return self.async_audio_speech( # type: ignore logging_obj=logging_obj, url=url, headers=headers, request=request ) sync_handler = _get_httpx_client() diff --git a/litellm/llms/vertex_ai/vertex_ai_partner_models/main.py b/litellm/llms/vertex_ai/vertex_ai_partner_models/main.py index eb67e3aa828..13aa2a5350e 100644 --- a/litellm/llms/vertex_ai/vertex_ai_partner_models/main.py +++ b/litellm/llms/vertex_ai/vertex_ai_partner_models/main.py @@ -45,7 +45,7 @@ class PartnerModelPrefixes(str, Enum): class VertexAIPartnerModels(VertexBase): def __init__(self) -> None: - pass + super().__init__() @staticmethod def is_vertex_partner_model(model: str): @@ -116,9 +116,6 @@ class VertexAIPartnerModels(VertexBase): CodestralTextCompletion, ) from litellm.llms.openai_like.chat.handler import OpenAILikeChatHandler - from litellm.llms.vertex_ai.gemini.vertex_and_google_ai_studio_gemini import ( - VertexLLM, - ) except Exception as e: raise VertexAIError( status_code=400, @@ -133,9 +130,7 @@ class VertexAIPartnerModels(VertexBase): message="""Upgrade vertex ai. Run `pip install "google-cloud-aiplatform>=1.38"`""", ) try: - vertex_httpx_logic = VertexLLM() - - access_token, project_id = vertex_httpx_logic._ensure_access_token( + access_token, project_id = self._ensure_access_token( credentials=vertex_credentials, project_id=vertex_project, custom_llm_provider="vertex_ai", diff --git a/litellm/llms/vertex_ai/vertex_gemma_models/main.py b/litellm/llms/vertex_ai/vertex_gemma_models/main.py index 82cfe6de984..b6bf2f73b72 100644 --- a/litellm/llms/vertex_ai/vertex_gemma_models/main.py +++ b/litellm/llms/vertex_ai/vertex_gemma_models/main.py @@ -31,7 +31,7 @@ from ..vertex_llm_base import VertexBase class VertexAIGemmaModels(VertexBase): def __init__(self) -> None: - pass + super().__init__() def completion( self, @@ -62,9 +62,6 @@ class VertexAIGemmaModels(VertexBase): try: import vertexai - from litellm.llms.vertex_ai.gemini.vertex_and_google_ai_studio_gemini import ( - VertexLLM, - ) from litellm.llms.vertex_ai.vertex_gemma_models.transformation import ( VertexGemmaConfig, ) @@ -83,9 +80,8 @@ class VertexAIGemmaModels(VertexBase): ) try: model = get_vertex_base_model_name(model=model) - vertex_httpx_logic = VertexLLM() - access_token, project_id = vertex_httpx_logic._ensure_access_token( + access_token, project_id = self._ensure_access_token( credentials=vertex_credentials, project_id=vertex_project, custom_llm_provider="vertex_ai", diff --git a/litellm/llms/vertex_ai/vertex_gemma_models/transformation.py b/litellm/llms/vertex_ai/vertex_gemma_models/transformation.py index 6c6446958bc..35cd54d65f6 100644 --- a/litellm/llms/vertex_ai/vertex_gemma_models/transformation.py +++ b/litellm/llms/vertex_ai/vertex_gemma_models/transformation.py @@ -91,6 +91,10 @@ class VertexGemmaConfig(OpenAIGPTConfig): "stream", None ) # Streaming not supported, will be faked client-side openai_request.pop("stream_options", None) # Stream options not supported + # Vertex Gemma's chatCompletions wrapper does not understand + # `context_management` (an Anthropic/Responses API concept). Strip it + # so the upstream endpoint does not 400 on the unknown field. + openai_request.pop("context_management", None) # Wrap in Vertex Gemma format return { diff --git a/litellm/llms/vertex_ai/vertex_llm_base.py b/litellm/llms/vertex_ai/vertex_llm_base.py index 6f687dae7e8..990063bb9fb 100644 --- a/litellm/llms/vertex_ai/vertex_llm_base.py +++ b/litellm/llms/vertex_ai/vertex_llm_base.py @@ -4,8 +4,10 @@ Base Vertex, Google AI Studio LLM Class Handles Authentication and generating request urls for Vertex AI and Google AI Studio """ +import asyncio import json import os +import threading from typing import TYPE_CHECKING, Any, Dict, Literal, Optional, Tuple import litellm @@ -30,6 +32,7 @@ GOOGLE_IMPORT_ERROR_MESSAGE = ( if TYPE_CHECKING: from google.auth.credentials import Credentials as GoogleCredentialsObject + from google.auth.credentials import TokenState else: GoogleCredentialsObject = Any @@ -42,10 +45,28 @@ class VertexBase: self._credentials: Optional[GoogleCredentialsObject] = None self._credentials_project_mapping: Dict[ Tuple[Optional[VERTEX_CREDENTIALS_TYPES], Optional[str]], - Tuple[GoogleCredentialsObject, str], + Tuple[GoogleCredentialsObject, Optional[str]], ] = {} self.project_id: Optional[str] = None self.async_handler: Optional[AsyncHTTPHandler] = None + # Per-credential-key asyncio.Lock for single-flight async refresh. + # Prevents thundering herd when token expires under high concurrency. + # Uses a regular dict (not WeakValueDictionary) so the lock identity is + # stable across concurrent callers — a weak reference can be GC'd + # between two coroutines arriving at the lock, breaking single-flight. + # An explicit refcount tracks the number of coroutines currently using + # each lock; the entry is pruned when the count reaches zero, so the + # dict stays bounded even in long-running high-cardinality deployments + # without depending on any private asyncio internals. + self._async_refresh_locks: Dict[tuple, asyncio.Lock] = {} + self._async_refresh_lock_refcounts: Dict[tuple, int] = {} + # Tracks in-flight background refresh tasks to avoid duplicate refreshes. + self._background_refresh_tasks: Dict[tuple, asyncio.Task] = {} + # Protects the sync get_access_token refresh path. + # Use RLock so that the reauthentication retry path (which calls + # back into get_access_token while still holding the lock) can + # re-acquire it without deadlocking the current thread. + self._sync_refresh_lock = threading.RLock() def get_vertex_region(self, vertex_region: Optional[str], model: str) -> str: import litellm @@ -77,7 +98,9 @@ class VertexBase: return vertex_region or "us-central1" def load_auth( - self, credentials: Optional[VERTEX_CREDENTIALS_TYPES], project_id: Optional[str] + self, + credentials: Optional[VERTEX_CREDENTIALS_TYPES], + project_id: Optional[str], ) -> Tuple[Any, str]: if credentials is not None: if isinstance(credentials, str): @@ -343,7 +366,241 @@ class VertexBase: except ImportError: raise ImportError(GOOGLE_IMPORT_ERROR_MESSAGE) - credentials.refresh(Request()) + # Serialize all refreshes on this VertexBase across threads. + # ``credentials.refresh()`` is not safe to call concurrently on the + # same credentials object, and this method is invoked from three + # places that can run on different threads: + # - sync ``get_access_token`` (already holds ``_sync_refresh_lock``) + # - the async slow path (via ``asyncify`` in a worker thread) + # - the background proactive refresh task (via ``asyncify``) + # ``_sync_refresh_lock`` is an ``RLock`` so reentrant acquisition + # from the sync path is safe. + with self._sync_refresh_lock: + credentials.refresh(Request()) + + def _acquire_async_refresh_lock(self, credential_cache_key: tuple) -> asyncio.Lock: + """Increment the refcount and return the lock for ``credential_cache_key``. + + Every call must be paired with ``_release_async_refresh_lock`` once the + caller is done with the lock so the entry can be pruned when no other + coroutine is holding or waiting on it. + """ + lock = self._async_refresh_locks.setdefault( + credential_cache_key, asyncio.Lock() + ) + self._async_refresh_lock_refcounts[credential_cache_key] = ( + self._async_refresh_lock_refcounts.get(credential_cache_key, 0) + 1 + ) + return lock + + def _release_async_refresh_lock( + self, credential_cache_key: tuple, lock: asyncio.Lock + ) -> None: + """Decrement the refcount and drop the lock entry when it reaches zero. + + Must be called only after the caller has released ``lock`` (i.e. once + the surrounding ``async with`` has exited). asyncio is cooperative, so + the decrement-then-pop sequence below runs atomically with respect to + other coroutines. + """ + remaining = self._async_refresh_lock_refcounts.get(credential_cache_key, 0) - 1 + if remaining > 0: + self._async_refresh_lock_refcounts[credential_cache_key] = remaining + return + self._async_refresh_lock_refcounts.pop(credential_cache_key, None) + if self._async_refresh_locks.get(credential_cache_key) is lock: + self._async_refresh_locks.pop(credential_cache_key, None) + + def _try_get_cached_token( + self, + credential_cache_key: tuple, + project_id: Optional[str], + ) -> Optional[Tuple[str, str]]: + """ + Look up cached credentials and return (token, project_id) if the token + is FRESH. Returns None if not cached or not fresh. + """ + from google.auth.credentials import TokenState + + creds, cached_project_id = self._unpack_cached_credentials(credential_cache_key) + if ( + creds is not None + and self._get_token_state(creds) == TokenState.FRESH + and creds.token is not None + and isinstance(creds.token, str) + ): + resolved_project = project_id or cached_project_id + if resolved_project: + return creds.token, resolved_project + return None + + def _try_get_usable_cached_token( + self, + credential_cache_key: tuple, + project_id: Optional[str], + ) -> Optional[Tuple[str, str, "TokenState", Any, Optional[str]]]: + """ + Look up cached credentials and return usable token info for FRESH or + STALE tokens (both are still valid for outbound requests). STALE + tokens are returned along with their state and the underlying + credentials object so the caller can schedule a background refresh + without holding the per-key async lock. + """ + from google.auth.credentials import TokenState + + creds, cached_project_id = self._unpack_cached_credentials(credential_cache_key) + if creds is None: + return None + token_state = self._get_token_state(creds) + if token_state not in (TokenState.FRESH, TokenState.STALE): + return None + if creds.token is None or not isinstance(creds.token, str): + return None + resolved_project = project_id or cached_project_id + if not resolved_project: + return None + return creds.token, resolved_project, token_state, creds, cached_project_id + + def _unpack_cached_credentials( + self, credential_cache_key: tuple + ) -> Tuple[Any, Optional[str]]: + """ + Return (credentials, project_id) from the cache, or (None, None) if + not cached. Handles both tuple and legacy cache formats. + """ + if credential_cache_key not in self._credentials_project_mapping: + return None, None + cached_entry = self._credentials_project_mapping[credential_cache_key] + if isinstance(cached_entry, tuple): + return cached_entry + return cached_entry, cached_entry.quota_project_id or getattr( + cached_entry, "project_id", None + ) + + def _get_token_state(self, credentials: Any) -> "TokenState": + """ + Return the token state using google-auth's TokenState enum. + + Falls back to expired/valid checks if token_state is unavailable + (e.g. older google-auth versions or mock objects in tests). + """ + from google.auth.credentials import TokenState as _TokenState + + token_state = getattr(credentials, "token_state", None) + if isinstance(token_state, _TokenState): + return token_state + # Fallback for credentials without a real token_state (e.g. mocks) + if getattr(credentials, "expired", True): + return _TokenState.INVALID + if getattr(credentials, "valid", False): + return _TokenState.FRESH + return _TokenState.INVALID + + async def _load_and_cache_credentials( + self, + credentials: Optional[VERTEX_CREDENTIALS_TYPES], + project_id: Optional[str], + credential_cache_key: tuple, + ) -> Tuple[Any, Optional[str]]: + """Load credentials via load_auth (in thread) and cache the result.""" + try: + _credentials, credential_project_id = await asyncify(self.load_auth)( + credentials=credentials, + project_id=project_id, + ) + except Exception as e: + verbose_logger.exception("Failed to load vertex credentials: %s", str(e)) + raise + if _credentials is None: + raise ValueError("Could not resolve credentials") + self._credentials_project_mapping[credential_cache_key] = ( + _credentials, + credential_project_id, + ) + return _credentials, credential_project_id + + async def _background_refresh_credentials( + self, + credentials: Any, + credential_cache_key: tuple, + credential_project_id: Optional[str], + ) -> None: + """ + Refresh credentials in the background without blocking the calling request. + + Called when the token is still valid but nearing expiry (proactive refresh). + Errors are logged but not raised — the current token is still usable. + """ + try: + verbose_logger.debug("Background proactive credential refresh") + await asyncify(self.refresh_auth)(credentials) + # Only update the cache if it still points at the credentials + # object we just refreshed. The per-key async lock is not held + # here, so a concurrent INVALID path may have already replaced + # this entry (e.g. via _handle_reauthentication_async, which + # creates a fresh credentials object). In that case our write + # would clobber the newer entry with a stale reference. + cached_creds, _ = self._unpack_cached_credentials(credential_cache_key) + if cached_creds is credentials: + self._credentials_project_mapping[credential_cache_key] = ( + credentials, + credential_project_id, + ) + except Exception: + verbose_logger.debug( + "Background credential refresh failed, will retry on next request", + exc_info=True, + ) + + async def _await_in_flight_background_refresh( + self, credential_cache_key: tuple + ) -> None: + """Wait for an in-flight background refresh to finish, if any. + + google-auth's ``Credentials.refresh()`` is not safe to invoke + concurrently on the same credentials object. Coroutines that need a + blocking refresh must first drain any background refresh that was + scheduled while a previous STALE token was being served. + """ + existing_task = self._background_refresh_tasks.get(credential_cache_key) + if existing_task is None or existing_task.done(): + return + try: + await existing_task + except Exception: + # Background refresh failures are already logged inside + # _background_refresh_credentials; the caller will fall through + # to its own blocking refresh. + pass + + def _schedule_background_refresh( + self, + credentials: Any, + credential_cache_key: tuple, + credential_project_id: Optional[str], + ) -> None: + """Kick off a single background refresh for ``credential_cache_key``. + + Skips scheduling if a refresh is already in flight. The done-callback + guards against removing a newer task that has replaced this one in the + tracking dict (done_callbacks are scheduled via ``call_soon``). + """ + existing = self._background_refresh_tasks.get(credential_cache_key) + if existing is not None and not existing.done(): + return + self._background_refresh_tasks.pop(credential_cache_key, None) + task = asyncio.create_task( + self._background_refresh_credentials( + credentials, credential_cache_key, credential_project_id + ) + ) + + def _drop_background_refresh_task(_fut: asyncio.Future[Any]) -> None: + if self._background_refresh_tasks.get(credential_cache_key) is _fut: + self._background_refresh_tasks.pop(credential_cache_key, None) + + task.add_done_callback(_drop_background_refresh_task) + self._background_refresh_tasks[credential_cache_key] = task def _ensure_access_token( self, @@ -563,6 +820,65 @@ class VertexBase: # Re-raise the original error for better context raise error + async def _handle_reauthentication_async( + self, + credentials: Optional[VERTEX_CREDENTIALS_TYPES], + project_id: Optional[str], + credential_cache_key: Tuple, + error: Exception, + ) -> Tuple[str, str]: + """ + Async reauthentication retry that stays within the per-key async lock. + """ + verbose_logger.debug( + f"Handling async reauthentication for project_id: {project_id}. " + f"Clearing cache and retrying once." + ) + + self._credentials_project_mapping.pop(credential_cache_key, None) + + try: + _credentials, credential_project_id = ( + await self._load_and_cache_credentials( + credentials=credentials, + project_id=project_id, + credential_cache_key=credential_cache_key, + ) + ) + if project_id is None and isinstance(credential_project_id, str): + project_id = credential_project_id + cache_credentials = ( + json.dumps(credentials) + if isinstance(credentials, dict) + else credentials + ) + resolved_cache_key = (cache_credentials, project_id) + # Always overwrite — any pre-existing entry at the resolved key + # references the OLD credentials object we just replaced, and + # leaving it would force the next request to do a redundant + # refresh/reauth before realizing the cached creds are stale. + self._credentials_project_mapping[resolved_cache_key] = ( + _credentials, + credential_project_id, + ) + + if _credentials.token is None or not isinstance(_credentials.token, str): + raise ValueError( + "Could not resolve credentials token. Got None or non-string token (type={})".format( + type(_credentials.token).__name__ + ) + ) + if project_id is None: + raise ValueError("Could not resolve project_id") + + return _credentials.token, project_id + except Exception as retry_error: + verbose_logger.error( + f"Async reauthentication retry failed for project_id: {project_id}. " + f"Original error: {str(error)}. Retry error: {str(retry_error)}" + ) + raise error + def get_access_token( self, credentials: Optional[VERTEX_CREDENTIALS_TYPES], @@ -646,7 +962,7 @@ class VertexBase: ) ## VALIDATE CREDENTIALS - verbose_logger.debug(f"Validating credentials for project_id: {project_id}") + verbose_logger.debug("Validating credentials") if ( project_id is None and credential_project_id is not None @@ -666,26 +982,27 @@ class VertexBase: raise ValueError("Credentials are None after loading") if _credentials.expired: - try: - verbose_logger.debug( - f"Credentials expired, refreshing for project_id: {project_id}" - ) - self.refresh_auth(_credentials) - self._credentials_project_mapping[credential_cache_key] = ( - _credentials, - credential_project_id, - ) - except Exception as e: - # if refresh fails, it's possible the user has re-authenticated via `gcloud auth application-default login` - # in this case, we should try to reload the credentials by clearing the cache and retrying - if "Reauthentication is needed" in str(e) and not _retry_reauth: - return self._handle_reauthentication( - credentials=credentials, - project_id=project_id, - credential_cache_key=credential_cache_key, - error=e, - ) - raise e + with self._sync_refresh_lock: + # Double-check after acquiring lock + if _credentials.expired: + try: + verbose_logger.debug("Credentials expired, refreshing") + self.refresh_auth(_credentials) + self._credentials_project_mapping[credential_cache_key] = ( + _credentials, + credential_project_id, + ) + except Exception as e: + # if refresh fails, it's possible the user has re-authenticated via `gcloud auth application-default login` + # in this case, we should try to reload the credentials by clearing the cache and retrying + if "Reauthentication is needed" in str(e) and not _retry_reauth: + return self._handle_reauthentication( + credentials=credentials, + project_id=project_id, + credential_cache_key=credential_cache_key, + error=e, + ) + raise e ## VALIDATION STEP if _credentials.token is None or not isinstance(_credentials.token, str): @@ -700,6 +1017,149 @@ class VertexBase: return _credentials.token, project_id + async def get_access_token_async( + self, + credentials: Optional[VERTEX_CREDENTIALS_TYPES], + project_id: Optional[str], + ) -> Tuple[str, str]: + """ + Async version of get_access_token with single-flight refresh coordination. + + Prevents thundering herd: when credentials expire under high concurrency, + only one coroutine refreshes while others wait on the lock. Uses native + async refresh for service_account and authorized_user credentials. + """ + from google.auth.credentials import TokenState + + cache_credentials = ( + json.dumps(credentials) if isinstance(credentials, dict) else credentials + ) + credential_cache_key = (cache_credentials, project_id) + + # === FAST PATH (no lock) === + # If credentials are FRESH or STALE, return immediately without + # touching the per-key async lock. STALE tokens are still usable; + # we kick off a deduplicated background refresh so subsequent + # requests get a fresh token, but we must not serialize concurrent + # callers on the lock just to schedule that refresh. + usable = self._try_get_usable_cached_token(credential_cache_key, project_id) + if usable is not None: + cached_token, resolved_project, token_state, creds, cached_project_id = ( + usable + ) + if token_state == TokenState.STALE: + self._schedule_background_refresh( + creds, credential_cache_key, cached_project_id + ) + return cached_token, resolved_project + + # === SLOW PATH (per-key lock) === + lock = self._acquire_async_refresh_lock(credential_cache_key) + try: + async with lock: + # Double-check after acquiring lock — another coroutine may have refreshed. + cached = self._try_get_cached_token(credential_cache_key, project_id) + if cached is not None: + return cached + + _credentials, credential_project_id = self._unpack_cached_credentials( + credential_cache_key + ) + + # Load credentials if not cached + if _credentials is None: + _credentials, credential_project_id = ( + await self._load_and_cache_credentials( + credentials, project_id, credential_cache_key + ) + ) + + # Resolve project_id from credentials if not provided + if project_id is None and isinstance(credential_project_id, str): + project_id = credential_project_id + resolved_cache_key = (cache_credentials, project_id) + # Always overwrite — a pre-existing entry at the resolved + # key may reference stale credentials (e.g. from before a + # reauth that only repopulated the unresolved key), which + # would force the next request through an unnecessary + # refresh/reauth cycle. + self._credentials_project_mapping[resolved_cache_key] = ( + _credentials, + credential_project_id, + ) + + # Use google-auth's token_state to decide refresh strategy: + # - STALE: token is usable but within REFRESH_THRESHOLD (3:45) of + # expiry — return it immediately and refresh in the background. + # - INVALID: token is expired or missing — must block on refresh. + token_state = self._get_token_state(_credentials) + + if token_state == TokenState.STALE: + if project_id is None: + raise ValueError("Could not resolve project_id") + current_token = _credentials.token + if current_token is None or not isinstance(current_token, str): + # Token is malformed despite STALE state — block on a full + # refresh using the same path as INVALID credentials. + token_state = TokenState.INVALID + else: + self._schedule_background_refresh( + _credentials, + credential_cache_key, + credential_project_id, + ) + return current_token, project_id + + if token_state == TokenState.INVALID: + # Drain any in-flight background refresh before invoking + # refresh_auth ourselves; google-auth's + # Credentials.refresh() is not safe to call concurrently + # on the same credentials object, and the background task + # runs outside this lock. + await self._await_in_flight_background_refresh(credential_cache_key) + cached = self._try_get_cached_token( + credential_cache_key, project_id + ) + if cached is not None: + return cached + + # Token is expired or missing — must block until refresh completes. + try: + verbose_logger.debug("Credentials expired, refreshing") + await asyncify(self.refresh_auth)(_credentials) + self._credentials_project_mapping[credential_cache_key] = ( + _credentials, + credential_project_id, + ) + except Exception as e: + if "Reauthentication is needed" in str(e): + verbose_logger.debug( + "Reauthentication needed, clearing cache and retrying" + ) + return await self._handle_reauthentication_async( + credentials=credentials, + project_id=project_id, + credential_cache_key=credential_cache_key, + error=e, + ) + raise + + # Final validation + if _credentials.token is None or not isinstance( + _credentials.token, str + ): + raise ValueError( + "Could not resolve credentials token. Got None or non-string token (type={})".format( + type(_credentials.token).__name__ + ) + ) + if project_id is None: + raise ValueError("Could not resolve project_id") + + return _credentials.token, project_id + finally: + self._release_async_refresh_lock(credential_cache_key, lock) + async def _ensure_access_token_async( self, credentials: Optional[VERTEX_CREDENTIALS_TYPES], @@ -714,13 +1174,10 @@ class VertexBase: if custom_llm_provider == "gemini": return "", "" else: - try: - return await asyncify(self.get_access_token)( - credentials=credentials, - project_id=project_id, - ) - except Exception as e: - raise e + return await self.get_access_token_async( + credentials=credentials, + project_id=project_id, + ) def set_headers( self, auth_header: Optional[str], extra_headers: Optional[dict] diff --git a/litellm/llms/vertex_ai/vertex_model_garden/main.py b/litellm/llms/vertex_ai/vertex_model_garden/main.py index 7240d9dce57..732d5f90dc2 100644 --- a/litellm/llms/vertex_ai/vertex_model_garden/main.py +++ b/litellm/llms/vertex_ai/vertex_model_garden/main.py @@ -57,7 +57,7 @@ def create_vertex_url( class VertexAIModelGardenModels(VertexBase): def __init__(self) -> None: - pass + super().__init__() def completion( self, @@ -89,9 +89,6 @@ class VertexAIModelGardenModels(VertexBase): import vertexai from litellm.llms.openai_like.chat.handler import OpenAILikeChatHandler - from litellm.llms.vertex_ai.gemini.vertex_and_google_ai_studio_gemini import ( - VertexLLM, - ) except Exception as e: raise VertexAIError( status_code=400, @@ -107,9 +104,8 @@ class VertexAIModelGardenModels(VertexBase): ) try: model = get_vertex_base_model_name(model=model) - vertex_httpx_logic = VertexLLM() - access_token, project_id = vertex_httpx_logic._ensure_access_token( + access_token, project_id = self._ensure_access_token( credentials=vertex_credentials, project_id=vertex_project, custom_llm_provider="vertex_ai", diff --git a/litellm/llms/vllm/completion/transformation.py b/litellm/llms/vllm/completion/transformation.py index ec4c07e95d8..e03b07f9897 100644 --- a/litellm/llms/vllm/completion/transformation.py +++ b/litellm/llms/vllm/completion/transformation.py @@ -1,5 +1,5 @@ """ -Translates from OpenAI's `/v1/chat/completions` to the VLLM sdk `llm.generate`. +Translates from OpenAI's `/v1/chat/completions` to the VLLM sdk `llm.generate`. NOT RECOMMENDED FOR PRODUCTION USE. Use `hosted_vllm/` instead. """ diff --git a/litellm/llms/voyage/embedding/transformation_contextual.py b/litellm/llms/voyage/embedding/transformation_contextual.py index 40328062e09..1f5ca99f47d 100644 --- a/litellm/llms/voyage/embedding/transformation_contextual.py +++ b/litellm/llms/voyage/embedding/transformation_contextual.py @@ -1,6 +1,6 @@ """ -This module is used to transform the request and response for the Voyage contextualized embeddings API. -This would be used for all the contextualized embeddings models in Voyage. +This module is used to transform the request and response for the Voyage contextualized embeddings API. +This would be used for all the contextualized embeddings models in Voyage. """ from typing import List, Optional, Union diff --git a/litellm/llms/xai/chat/transformation.py b/litellm/llms/xai/chat/transformation.py index 6300868a641..7325c0596a6 100644 --- a/litellm/llms/xai/chat/transformation.py +++ b/litellm/llms/xai/chat/transformation.py @@ -1,4 +1,4 @@ -from typing import Any, AsyncIterator, Iterator, List, Optional, Tuple, Union +from typing import Any, AsyncIterator, Dict, Iterator, List, Optional, Tuple, Union import httpx @@ -26,6 +26,7 @@ from ...openai.chat.gpt_transformation import ( class XAIChatConfig(OpenAIGPTConfig): + @property def custom_llm_provider(self) -> Optional[str]: return "xai" @@ -225,21 +226,57 @@ class XAIChatConfig(OpenAIGPTConfig): verbose_logger.debug(f"Error extracting X.AI web search usage: {e}") self._fold_reasoning_tokens_into_completion(response) + self._normalize_openai_compatible_usage_totals(getattr(response, "usage", None)) return response @staticmethod - def _fold_reasoning_tokens_into_completion(model_response: ModelResponse) -> None: + def _fold_reasoning_tokens_into_completion( + target: Union[ModelResponse, Usage, Dict[str, Any], None], + ) -> None: """Reconcile xAI Usage to the OpenAI invariant. xAI accounts ``reasoning_tokens`` separately from ``completion_tokens`` while still summing them into ``total_tokens``. OpenAI's contract (o1/o3) folds reasoning into ``completion_tokens``, so fold here to keep ``total = prompt + completion``. Idempotent. + + Accepts a ``ModelResponse`` (non-streaming), a ``Usage`` object, or a + raw usage ``dict`` (streaming chunk) so streaming and non-streaming + paths stay in sync. """ - usage = getattr(model_response, "usage", None) + if target is None: + return + + if isinstance(target, ModelResponse): + usage: Union[Usage, Dict[str, Any], None] = getattr(target, "usage", None) + else: + usage = target if usage is None: return + if isinstance(usage, dict): + details = usage.get("completion_tokens_details") or {} + if isinstance(details, dict): + reasoning_tokens = int(details.get("reasoning_tokens") or 0) + else: + reasoning_tokens = int(getattr(details, "reasoning_tokens", 0) or 0) + if reasoning_tokens <= 0: + return + + prompt_tokens = int(usage.get("prompt_tokens") or 0) + completion_tokens = int(usage.get("completion_tokens") or 0) + total_tokens = int(usage.get("total_tokens") or 0) + + if total_tokens == prompt_tokens + completion_tokens: + return + + # Guard against double-counting if xAI changes accounting. + if total_tokens != prompt_tokens + completion_tokens + reasoning_tokens: + return + + usage["completion_tokens"] = completion_tokens + reasoning_tokens + return + details = getattr(usage, "completion_tokens_details", None) reasoning_tokens = ( int(getattr(details, "reasoning_tokens", 0) or 0) if details else 0 @@ -284,6 +321,25 @@ class XAIChatConfig(OpenAIGPTConfig): setattr(usage, "num_sources_used", int(num_sources_used)) verbose_logger.debug(f"X.AI web search sources used: {num_sources_used}") + @staticmethod + def _normalize_openai_compatible_usage_totals( + usage: Union[Usage, Dict[str, Any], None], + ) -> None: + if usage is None: + return + if isinstance(usage, dict): + prompt_tokens = int(usage.get("prompt_tokens") or 0) + completion_tokens = int(usage.get("completion_tokens") or 0) + expected_total = prompt_tokens + completion_tokens + if int(usage.get("total_tokens") or 0) < expected_total: + usage["total_tokens"] = expected_total + return + prompt_tokens = int(usage.prompt_tokens or 0) + completion_tokens = int(usage.completion_tokens or 0) + expected_total = prompt_tokens + completion_tokens + if int(usage.total_tokens or 0) < expected_total: + usage.total_tokens = expected_total + class XAIChatCompletionStreamingHandler(OpenAIChatCompletionStreamingHandler): def chunk_parser(self, chunk: dict) -> ModelResponseStream: @@ -304,4 +360,8 @@ class XAIChatCompletionStreamingHandler(OpenAIChatCompletionStreamingHandler): # Add a dummy choice with empty delta to ensure proper processing chunk["choices"] = [{"index": 0, "delta": {}, "finish_reason": None}] + if "usage" in chunk and chunk["usage"] is not None: + XAIChatConfig._fold_reasoning_tokens_into_completion(chunk["usage"]) + XAIChatConfig._normalize_openai_compatible_usage_totals(chunk["usage"]) + return super().chunk_parser(chunk) diff --git a/litellm/model_prices_and_context_window_backup.json b/litellm/model_prices_and_context_window_backup.json index 41f73ddca5e..6a4a5dd6a03 100644 --- a/litellm/model_prices_and_context_window_backup.json +++ b/litellm/model_prices_and_context_window_backup.json @@ -13982,6 +13982,21 @@ "supports_response_schema": true, "supports_tool_choice": true }, + "fireworks_ai/accounts/fireworks/models/glm-5p1": { + "cache_read_input_token_cost": 2.6e-07, + "input_cost_per_token": 1.4e-06, + "litellm_provider": "fireworks_ai", + "max_input_tokens": 202800, + "max_output_tokens": 202800, + "max_tokens": 202800, + "mode": "chat", + "output_cost_per_token": 4.4e-06, + "source": "https://fireworks.ai/models/fireworks/glm-5p1", + "supports_function_calling": false, + "supports_reasoning": true, + "supports_response_schema": false, + "supports_tool_choice": false + }, "fireworks_ai/accounts/fireworks/models/gpt-oss-120b": { "input_cost_per_token": 1.5e-07, "litellm_provider": "fireworks_ai", @@ -14248,6 +14263,21 @@ "supports_response_schema": true, "supports_tool_choice": true }, + "fireworks_ai/glm-5p1": { + "cache_read_input_token_cost": 2.6e-07, + "input_cost_per_token": 1.4e-06, + "litellm_provider": "fireworks_ai", + "max_input_tokens": 202800, + "max_output_tokens": 202800, + "max_tokens": 202800, + "mode": "chat", + "output_cost_per_token": 4.4e-06, + "source": "https://fireworks.ai/models/fireworks/glm-5p1", + "supports_function_calling": false, + "supports_reasoning": true, + "supports_response_schema": false, + "supports_tool_choice": false + }, "fireworks_ai/kimi-k2p5": { "cache_read_input_token_cost": 1e-07, "input_cost_per_token": 6e-07, @@ -29122,6 +29152,24 @@ "supports_tool_choice": true, "source": "https://aws.amazon.com/bedrock/pricing/" }, + "reducto/parse-legacy": { + "litellm_provider": "reducto", + "mode": "ocr", + "ocr_cost_per_credit": 0.015, + "source": "https://reducto.ai/pricing", + "supported_endpoints": [ + "/v1/ocr" + ] + }, + "reducto/parse-v3": { + "litellm_provider": "reducto", + "mode": "ocr", + "ocr_cost_per_credit": 0.015, + "source": "https://reducto.ai/pricing", + "supported_endpoints": [ + "/v1/ocr" + ] + }, "recraft/recraftv2": { "litellm_provider": "recraft", "mode": "image_generation", diff --git a/litellm/proxy/_experimental/mcp_server/openapi_to_mcp_generator.py b/litellm/proxy/_experimental/mcp_server/openapi_to_mcp_generator.py index 271517bb1e6..de70fe1331e 100644 --- a/litellm/proxy/_experimental/mcp_server/openapi_to_mcp_generator.py +++ b/litellm/proxy/_experimental/mcp_server/openapi_to_mcp_generator.py @@ -305,7 +305,7 @@ def build_input_schema(operation: Dict[str, Any]) -> Dict[str, Any]: def _merge_openapi_tool_request_headers( - static_headers: Dict[str, str] + static_headers: Dict[str, str], ) -> Dict[str, str]: """Merge static closure headers with per-request ContextVar overrides. diff --git a/litellm/proxy/auth/auth_checks.py b/litellm/proxy/auth/auth_checks.py index 13381c7a6c9..09bb8057203 100644 --- a/litellm/proxy/auth/auth_checks.py +++ b/litellm/proxy/auth/auth_checks.py @@ -1187,6 +1187,127 @@ async def get_end_user_object( return None +_END_USER_VALIDATION_NEGATIVE_TTL = 60 +_END_USER_VALIDATION_POSITIVE_TTL = 300 + + +async def resolve_and_validate_end_user_id( + raw_end_user_id: Optional[str], + prisma_client: Optional[PrismaClient], + user_api_key_cache: UserApiKeyCache, + parent_otel_span: Optional[Span] = None, + proxy_logging_obj: Optional[ProxyLogging] = None, + route: str = "", +) -> Optional[str]: + """Optionally drop end-user ids that don't resolve to a known DB row. + + Default: pass-through. LiteLLM's documented pattern is that the `user` + field is an arbitrary caller-supplied identifier, so validation is + opt-in behind ``litellm.validate_end_user_id_in_db`` to preserve + backwards compatibility. + + When the flag is set: accept the id when it matches any of + - LiteLLM_EndUserTable.user_id + - LiteLLM_UserTable.user_id + - LiteLLM_UserTable.user_email (case-insensitive) + + If the id doesn't match but ``litellm.max_end_user_budget_id`` is set, + we still preserve the id so the default end-user budget is applied + downstream; otherwise we return None. + + DB lookups reuse ``get_end_user_object`` / ``get_user_object`` so they + share the same cache as the rest of the auth path instead of adding new + raw Prisma queries. + """ + if raw_end_user_id is None: + return None + if not litellm.validate_end_user_id_in_db: + return raw_end_user_id + if prisma_client is None: + return raw_end_user_id + + cache_key = f"end_user_validation:{raw_end_user_id}" + cached = await user_api_key_cache.async_get_cache(key=cache_key) + if cached == "valid": + return raw_end_user_id + if cached == "invalid": + return raw_end_user_id if litellm.max_end_user_budget_id else None + + is_valid = await _end_user_id_exists_in_db( + end_user_id=raw_end_user_id, + prisma_client=prisma_client, + user_api_key_cache=user_api_key_cache, + parent_otel_span=parent_otel_span, + proxy_logging_obj=proxy_logging_obj, + route=route, + ) + + await user_api_key_cache.async_set_cache( + key=cache_key, + value="valid" if is_valid else "invalid", + ttl=( + _END_USER_VALIDATION_POSITIVE_TTL + if is_valid + else _END_USER_VALIDATION_NEGATIVE_TTL + ), + ) + + if is_valid: + return raw_end_user_id + # Preserve id so the caller can still apply litellm.max_end_user_budget_id. + if litellm.max_end_user_budget_id: + return raw_end_user_id + return None + + +async def _end_user_id_exists_in_db( + end_user_id: str, + prisma_client: PrismaClient, + user_api_key_cache: UserApiKeyCache, + parent_otel_span: Optional[Span] = None, + proxy_logging_obj: Optional[ProxyLogging] = None, + route: str = "", +) -> bool: + """True when the id matches an EndUser, User, or user_email row.""" + try: + end_user_obj = await get_end_user_object( + end_user_id=end_user_id, + prisma_client=prisma_client, + user_api_key_cache=user_api_key_cache, + parent_otel_span=parent_otel_span, + proxy_logging_obj=proxy_logging_obj, + route=route, + ) + if end_user_obj is not None: + return True + except litellm.BudgetExceededError: + raise + except Exception as e: + verbose_proxy_logger.debug( + f"end_user validation: get_end_user_object lookup failed: {e}" + ) + + try: + user_obj = await get_user_object( + user_id=end_user_id, + prisma_client=prisma_client, + user_api_key_cache=user_api_key_cache, + user_id_upsert=False, + parent_otel_span=parent_otel_span, + proxy_logging_obj=proxy_logging_obj, + check_db_only=False, + user_email=end_user_id if "@" in end_user_id else None, + ) + if user_obj is not None: + return True + except Exception as e: + verbose_proxy_logger.debug( + f"end_user validation: get_user_object lookup failed: {e}" + ) + + return False + + @log_db_metrics async def get_tag_objects_batch( tag_names: List[str], diff --git a/litellm/proxy/auth/auth_utils.py b/litellm/proxy/auth/auth_utils.py index 637a4a070c4..c4dcca764b2 100644 --- a/litellm/proxy/auth/auth_utils.py +++ b/litellm/proxy/auth/auth_utils.py @@ -10,6 +10,7 @@ import litellm from litellm import Router, provider_list from litellm._logging import verbose_proxy_logger from litellm.constants import STANDARD_CUSTOMER_ID_HEADERS +from litellm.litellm_core_utils.safe_json_loads import safe_json_loads from litellm.litellm_core_utils.url_utils import SSRFError, validate_url from litellm.proxy._types import * from litellm.types.router import CONFIGURABLE_CLIENTSIDE_AUTH_PARAMS @@ -1008,12 +1009,47 @@ def _get_customer_id_from_standard_headers( for standard_header in STANDARD_CUSTOMER_ID_HEADERS: for header_name, header_value in request_headers.items(): if header_name.lower() == standard_header.lower(): - user_id_str = str(header_value) if header_value is not None else "" - if user_id_str.strip(): + user_id_str = _coerce_user_id_to_str(header_value) + if user_id_str: return user_id_str return None +def _coerce_user_id_to_str(value: Any) -> Optional[str]: + """Return a usable end-user identifier string, or None if the value isn't one. + + Always drops non-string structured values (dict/list/tuple/set) because + stringifying them produces garbage spend-log rows like + ``"{'device_id': ...}"``. Strings that *decode* to a structured payload + are only rejected when ``litellm.validate_end_user_id_in_db`` is enabled + — operators who currently pass JSON-encoded identifiers keep their + existing behavior until they opt in. See + auth_utils.py:get_end_user_id_from_request_body for the extraction chain. + """ + if value is None: + return None + if isinstance(value, bool): + # bool is an int subclass; handle explicitly to avoid "True"/"False". + return None + if isinstance(value, (int, float)): + return str(value) + if isinstance(value, str): + stripped = value.strip() + if not stripped: + return None + # Reject strings that decode to a structured payload (JSON object/array) + # only when the operator has opted into end-user validation. Gating + # behind the flag preserves backwards compatibility for deployments + # that intentionally pass JSON-encoded user identifiers. + if litellm.validate_end_user_id_in_db and stripped[:1] in ("{", "["): + parsed = safe_json_loads(stripped) + if isinstance(parsed, (dict, list)): + return None + return stripped + # dict, list, tuple, set, arbitrary objects -> drop. + return None + + def get_end_user_id_from_request_body( request_body: dict, request_headers: Optional[dict] = None ) -> Optional[str]: @@ -1052,23 +1088,22 @@ def get_end_user_id_from_request_body( if isinstance(custom_header_name_to_check, list): headers_lower = {k.lower(): v for k, v in request_headers.items()} for expected_header in custom_header_name_to_check: - header_value = headers_lower.get(expected_header) - if header_value is not None: - user_id_str = str(header_value) - if user_id_str.strip(): - return user_id_str + user_id_str = _coerce_user_id_to_str(headers_lower.get(expected_header)) + if user_id_str: + return user_id_str elif isinstance(custom_header_name_to_check, str): for header_name, header_value in request_headers.items(): if header_name.lower() == custom_header_name_to_check.lower(): - user_id_str = str(header_value) if header_value is not None else "" - if user_id_str.strip(): + user_id_str = _coerce_user_id_to_str(header_value) + if user_id_str: return user_id_str # Check 3: 'user' field in request_body (commonly OpenAI) - if "user" in request_body and request_body["user"] is not None: - user_from_body_user_field = request_body["user"] - return str(user_from_body_user_field) + if "user" in request_body: + user_id_str = _coerce_user_id_to_str(request_body["user"]) + if user_id_str: + return user_id_str def _as_dict(value: Any) -> dict: # metadata / litellm_metadata can arrive as JSON strings from @@ -1077,32 +1112,30 @@ def get_end_user_id_from_request_body( if isinstance(value, dict): return value if isinstance(value, str): - from litellm.litellm_core_utils.safe_json_loads import safe_json_loads - parsed = safe_json_loads(value) return parsed if isinstance(parsed, dict) else {} return {} # Check 4: 'litellm_metadata.user' in request_body (commonly Anthropic) litellm_metadata = _as_dict(request_body.get("litellm_metadata")) - user_from_litellm_metadata = litellm_metadata.get("user") - if user_from_litellm_metadata is not None: - return str(user_from_litellm_metadata) + user_id_str = _coerce_user_id_to_str(litellm_metadata.get("user")) + if user_id_str: + return user_id_str # Check 5: 'metadata.user_id' in request_body (another common pattern) metadata_dict = _as_dict(request_body.get("metadata")) - user_id_from_metadata_field = metadata_dict.get("user_id") - if user_id_from_metadata_field is not None: - return str(user_id_from_metadata_field) + user_id_str = _coerce_user_id_to_str(metadata_dict.get("user_id")) + if user_id_str: + return user_id_str # Check 6: 'safety_identifier' in request body (OpenAI Responses API parameter) # SECURITY NOTE: safety_identifier can be set by any caller in the request body. # Only use this for end-user identification in trusted environments where you control # the calling application. For untrusted callers, prefer using headers or server-side # middleware to set the end_user_id to prevent impersonation. - if request_body.get("safety_identifier") is not None: - user_from_body_user_field = request_body["safety_identifier"] - return str(user_from_body_user_field) + user_id_str = _coerce_user_id_to_str(request_body.get("safety_identifier")) + if user_id_str: + return user_id_str return None diff --git a/litellm/proxy/auth/model_checks.py b/litellm/proxy/auth/model_checks.py index bf76f99db69..d364b52c676 100644 --- a/litellm/proxy/auth/model_checks.py +++ b/litellm/proxy/auth/model_checks.py @@ -4,12 +4,15 @@ from typing import Dict, List, Optional, Set import litellm from litellm._logging import verbose_proxy_logger +from litellm.litellm_core_utils.credential_accessor import CredentialAccessor from litellm.proxy._types import SpecialModelNames, UserAPIKeyAuth from litellm.router import Router from litellm.router_utils.fallback_event_handlers import get_fallback_model_group -from litellm.types.router import LiteLLM_Params +from litellm.types.router import CredentialLiteLLMParams, LiteLLM_Params from litellm.utils import get_valid_models +_CREDENTIAL_LITELLM_PARAM_FIELDS = set(CredentialLiteLLMParams.model_fields) + def _check_wildcard_routing(model: str) -> bool: """ @@ -178,6 +181,7 @@ def get_complete_model_list( model_access_groups: Dict[str, List[str]] = {}, include_model_access_groups: Optional[bool] = False, only_model_access_groups: Optional[bool] = False, + team_id: Optional[str] = None, ) -> List[str]: """Logic for returning complete model list for a given key + team pair""" @@ -222,6 +226,7 @@ def get_complete_model_list( unique_models=unique_models, return_wildcard_routes=return_wildcard_routes, llm_router=llm_router, + team_id=team_id, ) complete_model_list = unique_models + all_wildcard_models @@ -229,6 +234,29 @@ def get_complete_model_list( return complete_model_list +def _hydrate_litellm_credential_name( + litellm_params: Optional[LiteLLM_Params], +) -> Optional[LiteLLM_Params]: + if litellm_params is None or litellm_params.litellm_credential_name is None: + return litellm_params + + credential_values = CredentialAccessor.get_credential_values( + litellm_params.litellm_credential_name + ) + if not credential_values: + return litellm_params + + litellm_params = litellm_params.model_copy() + for key, value in credential_values.items(): + if ( + key in _CREDENTIAL_LITELLM_PARAM_FIELDS + and getattr(litellm_params, key, None) is None + ): + setattr(litellm_params, key, value) + litellm_params.litellm_credential_name = None + return litellm_params + + def get_known_models_from_wildcard( wildcard_model: str, litellm_params: Optional[LiteLLM_Params] = None ) -> List[str]: @@ -247,7 +275,7 @@ def get_known_models_from_wildcard( else: provider = wildcard_provider_prefix - # get all known provider models + litellm_params = _hydrate_litellm_credential_name(litellm_params) wildcard_models = get_provider_models( provider=provider, litellm_params=litellm_params @@ -285,6 +313,7 @@ def _get_wildcard_models( unique_models: List[str], return_wildcard_routes: Optional[bool] = False, llm_router: Optional[Router] = None, + team_id: Optional[str] = None, ) -> List[str]: models_to_remove = set() all_wildcard_models = [] @@ -297,7 +326,9 @@ def _get_wildcard_models( ## get litellm params from model if llm_router is not None: - model_list = llm_router.get_model_list(model_name=model) + model_list = llm_router.get_model_list( + model_name=model, team_id=team_id + ) if model_list: for router_model in model_list: wildcard_models = get_known_models_from_wildcard( diff --git a/litellm/proxy/auth/user_api_key_auth.py b/litellm/proxy/auth/user_api_key_auth.py index 351cce75fdf..3f71af03c72 100644 --- a/litellm/proxy/auth/user_api_key_auth.py +++ b/litellm/proxy/auth/user_api_key_auth.py @@ -12,7 +12,7 @@ import fnmatch import re import secrets from datetime import datetime, timezone -from typing import Any, Iterator, List, NamedTuple, Optional, Tuple, Union, cast +from typing import Any, Dict, Iterator, List, Optional, Tuple, Union, cast import fastapi from fastapi import HTTPException, Request, WebSocket, status @@ -44,6 +44,7 @@ from litellm.proxy.auth.auth_checks import ( get_team_object, get_user_object, is_valid_fallback_model, + resolve_and_validate_end_user_id, ) from litellm.proxy.auth.auth_exception_handler import UserAPIKeyAuthExceptionHandler from litellm.proxy.auth.auth_utils import ( @@ -333,8 +334,22 @@ def _apply_budget_limits_to_end_user_params( async def user_api_key_auth_websocket(websocket: WebSocket): # Accept the WebSocket connection - scope_headers = list(websocket.scope.get("headers") or []) - request = Request(scope={"type": "http", "headers": scope_headers}) + ws_scope = websocket.scope or {} + scope_headers = list(ws_scope.get("headers") or []) + # ``get_request_route`` falls back to ``request.url.path`` when + # ``scope["path"]`` is absent. On WebSockets that fallback reads + # ``websocket.url``, which Starlette reconstructs from the (poisonable) + # Host header. Carry the ASGI scope's path / root_path so the lookup + # never reaches the fallback. + synthetic_scope: Dict[str, Any] = { + "type": "http", + "headers": scope_headers, + "path": ws_scope.get("path", ""), + } + for key in ("root_path", "app_root_path"): + if key in ws_scope: + synthetic_scope[key] = ws_scope[key] + request = Request(scope=synthetic_scope) request._url = websocket.url @@ -1333,9 +1348,17 @@ async def _user_api_key_auth_builder( # noqa: PLR0915 _end_user_object = None end_user_params = {} - end_user_id = get_end_user_id_from_request_body( + raw_end_user_id = get_end_user_id_from_request_body( request_data, _safe_get_request_headers(request) ) + end_user_id = await resolve_and_validate_end_user_id( + raw_end_user_id=raw_end_user_id, + prisma_client=prisma_client, + user_api_key_cache=user_api_key_cache, + parent_otel_span=parent_otel_span, + proxy_logging_obj=proxy_logging_obj, + route=route, + ) if end_user_id: try: end_user_params["end_user_id"] = end_user_id @@ -2021,7 +2044,7 @@ def _team_obj_from_token(valid_token: UserAPIKeyAuth) -> LiteLLM_TeamTableCached @tracer.wrap() -async def _run_centralized_common_checks( +async def _run_centralized_common_checks( # noqa: PLR0915 user_api_key_auth_obj: UserAPIKeyAuth, request: Request, request_data: dict, @@ -2099,9 +2122,23 @@ async def _run_centralized_common_checks( return parent_otel_span = user_api_key_auth_obj.parent_otel_span - end_user_id = get_end_user_id_from_request_body( - request_data, _safe_get_request_headers(request) - ) + # In the integrated auth flow ``_user_api_key_auth_builder`` has already + # resolved the end-user id and attached it here. Reuse that to avoid a + # second extraction pass; fall back to extracting locally when the + # function is invoked in isolation (e.g. in direct unit tests). + end_user_id = user_api_key_auth_obj.end_user_id + if end_user_id is None: + raw_end_user_id = get_end_user_id_from_request_body( + request_data, _safe_get_request_headers(request) + ) + end_user_id = await resolve_and_validate_end_user_id( + raw_end_user_id=raw_end_user_id, + prisma_client=prisma_client, + user_api_key_cache=user_api_key_cache, + parent_otel_span=parent_otel_span, + proxy_logging_obj=proxy_logging_obj, + route=route, + ) fetch_coros = [] if user_api_key_auth_obj.team_id is not None: @@ -2432,11 +2469,33 @@ async def user_api_key_auth( api_key=api_key, ) - end_user_id = get_end_user_id_from_request_body( - request_data, _safe_get_request_headers(request) - ) - if end_user_id is not None: - user_api_key_auth_obj.end_user_id = end_user_id + # Defense-in-depth: ``_user_api_key_auth_builder`` has multiple early-return + # paths (no master key, /user/auth route, JWT short-circuits) that bypass + # the end-user resolution block. If those paths produced an auth obj + # without an ``end_user_id`` set, fall back to extracting from the request + # body so spend logs are still attributed correctly. Validation honours + # ``litellm.validate_end_user_id_in_db``. + if user_api_key_auth_obj.end_user_id is None: + from litellm.proxy.proxy_server import ( + prisma_client, + proxy_logging_obj, + user_api_key_cache, + ) + + raw_end_user_id = get_end_user_id_from_request_body( + request_data, _safe_get_request_headers(request) + ) + if raw_end_user_id is not None: + resolved_end_user_id = await resolve_and_validate_end_user_id( + raw_end_user_id=raw_end_user_id, + prisma_client=prisma_client, + user_api_key_cache=user_api_key_cache, + parent_otel_span=user_api_key_auth_obj.parent_otel_span, + proxy_logging_obj=proxy_logging_obj, + route=route, + ) + if resolved_end_user_id is not None: + user_api_key_auth_obj.end_user_id = resolved_end_user_id user_api_key_auth_obj.request_route = normalize_request_route(route) return user_api_key_auth_obj diff --git a/litellm/proxy/common_utils/custom_openapi_spec.py b/litellm/proxy/common_utils/custom_openapi_spec.py index a93749c3952..fa3cb02195b 100644 --- a/litellm/proxy/common_utils/custom_openapi_spec.py +++ b/litellm/proxy/common_utils/custom_openapi_spec.py @@ -324,7 +324,7 @@ class CustomOpenAPISpec: @staticmethod def add_chat_completion_request_schema( - openapi_schema: Dict[str, Any] + openapi_schema: Dict[str, Any], ) -> Dict[str, Any]: """ Add ProxyChatCompletionRequest schema to chat completion endpoints for documentation. @@ -380,7 +380,7 @@ class CustomOpenAPISpec: @staticmethod def add_responses_api_request_schema( - openapi_schema: Dict[str, Any] + openapi_schema: Dict[str, Any], ) -> Dict[str, Any]: """ Add ResponsesAPIRequestParams schema to responses API endpoints for documentation. @@ -410,7 +410,7 @@ class CustomOpenAPISpec: @staticmethod def add_llm_api_request_schema_body( - openapi_schema: Dict[str, Any] + openapi_schema: Dict[str, Any], ) -> Dict[str, Any]: """ Add LLM API request schema bodies to OpenAPI specification for documentation. diff --git a/litellm/proxy/common_utils/http_parsing_utils.py b/litellm/proxy/common_utils/http_parsing_utils.py index 71abdfa5e9e..2ce3fda6297 100644 --- a/litellm/proxy/common_utils/http_parsing_utils.py +++ b/litellm/proxy/common_utils/http_parsing_utils.py @@ -12,6 +12,33 @@ from litellm.proxy.common_utils.callback_utils import ( ) from litellm.types.router import Deployment +_FORM_CONTENT_TYPES: frozenset[str] = frozenset( + {"application/x-www-form-urlencoded", "multipart/form-data"} +) + + +def _normalize_media_type(content_type: str) -> str: + """Return the bare media type per RFC 7231: strip params, trim, lowercase.""" + if not content_type: + return "" + return content_type.split(";", 1)[0].strip().lower() + + +def _is_form_content_type(content_type: str) -> bool: + """ + True iff Starlette's ``request.form()`` will actually parse this body. + + Substring matching ``"form"`` is unsafe: ``request.form()`` returns empty + ``FormData`` for non-canonical types without consuming the body, leaving + the auth-time pre-read and the handler's read seeing different payloads. + """ + return _normalize_media_type(content_type) in _FORM_CONTENT_TYPES + + +def _is_json_content_type(content_type: str) -> bool: + """True iff the body should be parsed as JSON.""" + return _normalize_media_type(content_type) == "application/json" + async def _read_request_body(request: Optional[Request]) -> Dict: """ @@ -37,8 +64,24 @@ async def _read_request_body(request: Optional[Request]) -> Dict: _request_headers: dict = _safe_get_request_headers(request=request) content_type = _request_headers.get("content-type", "") - if "form" in content_type: - parsed_body = dict(await request.form()) + if _is_form_content_type(content_type): + try: + form_data = await request.form() + except Exception as e: + # ``request.form()`` raises on malformed multipart (missing + # boundary, malformed chunk encoding, …). Surface as 400 so + # the auth-time pre-read does not silently cache ``{}`` while + # a later raw-body re-read sees the original payload — + # banned-param checks must see the same body the handler + # acts on. + verbose_proxy_logger.error(f"Invalid form payload: {e}") + raise ProxyException( + message=f"Invalid form payload: {e}", + type="invalid_request_error", + param="request_body", + code=status.HTTP_400_BAD_REQUEST, + ) + parsed_body = dict(form_data) if "metadata" in parsed_body and isinstance(parsed_body["metadata"], str): parsed_body["metadata"] = json.loads(parsed_body["metadata"]) else: @@ -257,7 +300,7 @@ async def get_form_data(request: Request) -> Dict[str, Any]: async def convert_upload_files_to_file_data( - form_data: Dict[str, Any] + form_data: Dict[str, Any], ) -> Dict[str, Any]: """ Convert FastAPI UploadFile objects to file data tuples for litellm. @@ -306,18 +349,13 @@ async def get_request_body(request: Request) -> Dict[str, Any]: Read the request body and parse it as JSON. """ if request.method == "POST": - if request.headers.get("content-type", "") == "application/json": + content_type = request.headers.get("content-type", "") + if _is_json_content_type(content_type): return await _read_request_body(request) - elif "multipart/form-data" in request.headers.get( - "content-type", "" - ) or "application/x-www-form-urlencoded" in request.headers.get( - "content-type", "" - ): + elif _is_form_content_type(content_type): return await get_form_data(request) else: - raise ValueError( - f"Unsupported content type: {request.headers.get('content-type')}" - ) + raise ValueError(f"Unsupported content type: {content_type}") return {} diff --git a/litellm/proxy/common_utils/openai_endpoint_utils.py b/litellm/proxy/common_utils/openai_endpoint_utils.py index c4bfe11aec1..905967fa465 100644 --- a/litellm/proxy/common_utils/openai_endpoint_utils.py +++ b/litellm/proxy/common_utils/openai_endpoint_utils.py @@ -1,5 +1,5 @@ """ -Contains utils used by OpenAI compatible endpoints +Contains utils used by OpenAI compatible endpoints """ from typing import Optional, Set diff --git a/litellm/proxy/config_management_endpoints/pass_through_endpoints.py b/litellm/proxy/config_management_endpoints/pass_through_endpoints.py index 5ff02b8bce0..4ebd989dc53 100644 --- a/litellm/proxy/config_management_endpoints/pass_through_endpoints.py +++ b/litellm/proxy/config_management_endpoints/pass_through_endpoints.py @@ -1,5 +1,5 @@ """ -What is this? +What is this? CRUD endpoints for managing pass-through endpoints """ diff --git a/litellm/proxy/db/create_views.py b/litellm/proxy/db/create_views.py index d84cebcf05a..97525a528d0 100644 --- a/litellm/proxy/db/create_views.py +++ b/litellm/proxy/db/create_views.py @@ -34,8 +34,7 @@ async def create_missing_views(db: _db): # noqa: PLR0915 if not any(marker in error_msg for marker in _VIEW_NOT_FOUND_MARKERS): raise # If an error occurs, the view does not exist, so create it - await db.execute_raw( - """ + await db.execute_raw(""" CREATE VIEW "LiteLLM_VerificationTokenView" AS SELECT v.*, @@ -47,8 +46,7 @@ async def create_missing_views(db: _db): # noqa: PLR0915 FROM "LiteLLM_VerificationToken" v LEFT JOIN "LiteLLM_TeamTable" t ON v.team_id = t.team_id LEFT JOIN "LiteLLM_ProjectTable" p ON v.project_id = p.project_id; - """ - ) + """) verbose_logger.debug("LiteLLM_VerificationTokenView Created!") diff --git a/litellm/proxy/guardrails/_content_utils.py b/litellm/proxy/guardrails/_content_utils.py index 7cad1352a79..766ef0cf9f6 100644 --- a/litellm/proxy/guardrails/_content_utils.py +++ b/litellm/proxy/guardrails/_content_utils.py @@ -10,7 +10,6 @@ every text fragment. from typing import Any, Callable, Dict, FrozenSet, Iterator, List - # Call types whose body carries free-form chat / prompt text that # text-content guardrails (banned keywords, content moderation, secret # detection, …) should inspect. The proxy ingress passes ``route_type`` diff --git a/litellm/proxy/guardrails/guardrail_hooks/akto/__init__.py b/litellm/proxy/guardrails/guardrail_hooks/akto/__init__.py index c4aaea709ba..1e3dd906b9f 100644 --- a/litellm/proxy/guardrails/guardrail_hooks/akto/__init__.py +++ b/litellm/proxy/guardrails/guardrail_hooks/akto/__init__.py @@ -4,7 +4,6 @@ from litellm.types.guardrails import SupportedGuardrailIntegrations from .akto import AktoGuardrail - if TYPE_CHECKING: from litellm.types.guardrails import Guardrail, LitellmParams diff --git a/litellm/proxy/guardrails/guardrail_hooks/bedrock_guardrails.py b/litellm/proxy/guardrails/guardrail_hooks/bedrock_guardrails.py index bb1db3d62d2..765c419479e 100644 --- a/litellm/proxy/guardrails/guardrail_hooks/bedrock_guardrails.py +++ b/litellm/proxy/guardrails/guardrail_hooks/bedrock_guardrails.py @@ -63,6 +63,7 @@ from litellm.types.utils import ( CallTypesLiteral, Choices, GuardrailStatus, + GuardrailTracingDetail, Message, ModelResponse, ModelResponseStream, @@ -509,6 +510,8 @@ class BedrockGuardrail(CustomGuardrail, BaseAWSLLM): # Add guardrail information to request trace ######################################################### _json_response = httpx_response.json() + tracing_detail = self._build_tracing_detail(_json_response) + # Raw Bedrock JSON is passed here; match/regex redaction runs once inside # CustomGuardrail.add_standard_logging_guardrail_information_to_request_data. self.add_standard_logging_guardrail_information_to_request_data( @@ -522,6 +525,7 @@ class BedrockGuardrail(CustomGuardrail, BaseAWSLLM): end_time=datetime.now().timestamp(), duration=(datetime.now() - start_time).total_seconds(), event_type=event_type, + tracing_detail=tracing_detail or None, ) ######################################################### if httpx_response.status_code == 200: @@ -640,6 +644,55 @@ class BedrockGuardrail(CustomGuardrail, BaseAWSLLM): return (status_code, err) return (status_code, message) + def _build_tracing_detail( + self, response: BedrockGuardrailResponse + ) -> GuardrailTracingDetail: + """ + Build the tracing detail from the raw Bedrock response, before + redaction, so downstream loggers (OTEL, Langfuse, ...) get the + actual category names rather than the "[REDACTED]" sentinel that + replaces customWords.match later. Bedrock's top-level ``action`` + field ("GUARDRAIL_INTERVENED" or "NONE") is also surfaced so the + OTEL integration can expose it as a queryable span attribute + without re-parsing the redacted guardrail_response blob. + """ + tracing_detail: GuardrailTracingDetail = {} + violation_categories = self._extract_violation_category_names(response) + if violation_categories: + tracing_detail["violation_categories"] = violation_categories + bedrock_action = response.get("action") + if isinstance(bedrock_action, str): + tracing_detail["guardrail_action"] = bedrock_action + return tracing_detail + + def _extract_violation_category_names( + self, response: BedrockGuardrailResponse + ) -> List[str]: + """ + Flatten the BLOCKED assessments into a list of human-readable category + names suitable for queryable OTEL / standard-logging attributes. + + SECURITY: only emits the non-sensitive policy *label* (topic name, + content-filter type, PII entity type, named-regex name). The raw + ``match`` field is intentionally NOT used — it carries the user's + original input that triggered the rule (e.g. a credit-card number + that hit a regex, or the literal custom word). Surfacing it to + telemetry would re-introduce the sensitive content the guardrail + was supposed to keep out. Entries that only have a ``match`` (bare + customWords, unnamed regexes) are therefore skipped — operators + can still see the count in ``_extract_blocked_assessments`` which + feeds the HTTP error detail. + """ + names: List[str] = [] + for block in self._extract_blocked_assessments(response): + for match in block.get("matches", []) or []: + # Allow-list non-sensitive labels only. Never fall back to + # `match.get("match")` — that's user-submitted content. + label = match.get("name") or match.get("type") + if isinstance(label, str) and label: + names.append(label) + return names + def _extract_blocked_assessments( self, response: BedrockGuardrailResponse ) -> List[dict]: diff --git a/litellm/proxy/guardrails/guardrail_hooks/rubrik/__init__.py b/litellm/proxy/guardrails/guardrail_hooks/rubrik/__init__.py new file mode 100644 index 00000000000..ab347130a30 --- /dev/null +++ b/litellm/proxy/guardrails/guardrail_hooks/rubrik/__init__.py @@ -0,0 +1,35 @@ +"""Rubrik guardrail integration for LiteLLM.""" + +from typing import TYPE_CHECKING + +from litellm.integrations.rubrik import RubrikLogger +from litellm.types.guardrails import SupportedGuardrailIntegrations + +if TYPE_CHECKING: + from litellm.types.guardrails import Guardrail, LitellmParams + + +def initialize_guardrail( + litellm_params: "LitellmParams", guardrail: "Guardrail" +) -> RubrikLogger: + import litellm + + rubrik_callback = RubrikLogger( + api_key=litellm_params.api_key, + api_base=litellm_params.api_base, + guardrail_name=guardrail.get("guardrail_name", ""), + event_hook=litellm_params.mode, + default_on=litellm_params.default_on, + ) + + litellm.logging_callback_manager.add_litellm_callback(rubrik_callback) + return rubrik_callback + + +guardrail_initializer_registry = { + SupportedGuardrailIntegrations.RUBRIK.value: initialize_guardrail, +} + +guardrail_class_registry = { + SupportedGuardrailIntegrations.RUBRIK.value: RubrikLogger, +} diff --git a/litellm/proxy/hooks/litellm_skills/__init__.py b/litellm/proxy/hooks/litellm_skills/__init__.py index 057cf3d8b38..1507b652ab4 100644 --- a/litellm/proxy/hooks/litellm_skills/__init__.py +++ b/litellm/proxy/hooks/litellm_skills/__init__.py @@ -6,7 +6,7 @@ The actual skill logic is in litellm/llms/litellm_proxy/skills/. Usage: from litellm.proxy.hooks.litellm_skills import SkillsInjectionHook - + # Register hook in proxy litellm.callbacks.append(SkillsInjectionHook()) """ diff --git a/litellm/proxy/management_endpoints/budget_management_endpoints.py b/litellm/proxy/management_endpoints/budget_management_endpoints.py index 60dc7827a6f..2eda1b30c5d 100644 --- a/litellm/proxy/management_endpoints/budget_management_endpoints.py +++ b/litellm/proxy/management_endpoints/budget_management_endpoints.py @@ -1,9 +1,9 @@ """ BUDGET MANAGEMENT -All /budget management endpoints +All /budget management endpoints -/budget/new +/budget/new /budget/info /budget/update /budget/delete diff --git a/litellm/proxy/management_endpoints/customer_endpoints.py b/litellm/proxy/management_endpoints/customer_endpoints.py index 4889f0b7f80..1fd8320db20 100644 --- a/litellm/proxy/management_endpoints/customer_endpoints.py +++ b/litellm/proxy/management_endpoints/customer_endpoints.py @@ -1,9 +1,9 @@ """ CUSTOMER MANAGEMENT -All /customer management endpoints +All /customer management endpoints -/customer/new +/customer/new /customer/info /customer/update /customer/delete diff --git a/litellm/proxy/management_endpoints/model_management_endpoints.py b/litellm/proxy/management_endpoints/model_management_endpoints.py index 472306eb818..f2d8ec8fb55 100644 --- a/litellm/proxy/management_endpoints/model_management_endpoints.py +++ b/litellm/proxy/management_endpoints/model_management_endpoints.py @@ -546,7 +546,7 @@ async def _update_existing_team_model_assignment( """ def _get_team_public_model_name( - model_info: Optional[Union[dict, str]] + model_info: Optional[Union[dict, str]], ) -> Optional[str]: if isinstance(model_info, dict): value = model_info.get("team_public_model_name") diff --git a/litellm/proxy/management_endpoints/sso/custom_microsoft_sso.py b/litellm/proxy/management_endpoints/sso/custom_microsoft_sso.py index 191212d6f0b..04e44c623d1 100644 --- a/litellm/proxy/management_endpoints/sso/custom_microsoft_sso.py +++ b/litellm/proxy/management_endpoints/sso/custom_microsoft_sso.py @@ -7,7 +7,7 @@ variables. Environment Variables: - MICROSOFT_AUTHORIZATION_ENDPOINT: Custom authorization endpoint URL -- MICROSOFT_TOKEN_ENDPOINT: Custom token endpoint URL +- MICROSOFT_TOKEN_ENDPOINT: Custom token endpoint URL - MICROSOFT_USERINFO_ENDPOINT: Custom userinfo endpoint URL If these are not set, the default Microsoft endpoints are used. diff --git a/litellm/proxy/management_endpoints/team_endpoints.py b/litellm/proxy/management_endpoints/team_endpoints.py index 86c4d6dcd9a..0b2f93d817a 100644 --- a/litellm/proxy/management_endpoints/team_endpoints.py +++ b/litellm/proxy/management_endpoints/team_endpoints.py @@ -4381,9 +4381,7 @@ async def list_team( except Exception as e: team_exception = """Invalid team object for team_id: {}. team_object={}. Error: {} - """.format( - team.team_id, team.model_dump(), str(e) - ) + """.format(team.team_id, team.model_dump(), str(e)) verbose_proxy_logger.exception(team_exception) continue # Sort the responses by team_alias diff --git a/litellm/proxy/management_endpoints/user_agent_analytics_endpoints.py b/litellm/proxy/management_endpoints/user_agent_analytics_endpoints.py index 872b6fa2250..ebd276fbee5 100644 --- a/litellm/proxy/management_endpoints/user_agent_analytics_endpoints.py +++ b/litellm/proxy/management_endpoints/user_agent_analytics_endpoints.py @@ -3,7 +3,7 @@ User Agent Analytics Endpoints This module provides optimized endpoints for tracking user agent activity metrics including: - Daily Active Users (DAU) by tags for configurable number of days -- Weekly Active Users (WAU) by tags for configurable number of weeks +- Weekly Active Users (WAU) by tags for configurable number of weeks - Monthly Active Users (MAU) by tags for configurable number of months - Summary analytics by tags diff --git a/litellm/proxy/ocr_endpoints/endpoints.py b/litellm/proxy/ocr_endpoints/endpoints.py index 4f31c762df1..e32fee6afc5 100644 --- a/litellm/proxy/ocr_endpoints/endpoints.py +++ b/litellm/proxy/ocr_endpoints/endpoints.py @@ -178,6 +178,24 @@ async def _parse_ocr_request(request: Request) -> Dict[str, Any]: "For JSON requests, use 'document_url' or 'image_url' document types." ) + # Security: reject provider-native file IDs (e.g. reducto://) received via + # JSON. These IDs are not scoped to the LiteLLM proxy user/key, so an + # authenticated user who obtains another user's file ID could submit it + # here and receive the OCR result using the proxy's shared provider + # credentials. Force callers to upload fresh content per request via + # multipart/form-data or an inline base64 data URI, both of which produce + # a server-mediated upload bound to the current request. + if isinstance(doc, dict): + for url_field in ("document_url", "image_url"): + url_value = doc.get(url_field) + if isinstance(url_value, str) and url_value.startswith("reducto://"): + raise ValueError( + "reducto:// file IDs are not accepted through the proxy " + "OCR API; upload the file in the same request via " + "multipart/form-data with a 'file' field, or pass an " + "inline base64 data URI as the document URL." + ) + return data diff --git a/litellm/proxy/pass_through_endpoints/llm_provider_handlers/cursor_passthrough_logging_handler.py b/litellm/proxy/pass_through_endpoints/llm_provider_handlers/cursor_passthrough_logging_handler.py index a104f962630..e7696e5a18a 100644 --- a/litellm/proxy/pass_through_endpoints/llm_provider_handlers/cursor_passthrough_logging_handler.py +++ b/litellm/proxy/pass_through_endpoints/llm_provider_handlers/cursor_passthrough_logging_handler.py @@ -18,7 +18,6 @@ from litellm.litellm_core_utils.litellm_logging import ( from litellm.proxy._types import PassThroughEndpointLoggingTypedDict from litellm.types.utils import StandardPassThroughResponseObject - CURSOR_AGENT_ENDPOINTS: Dict[str, str] = { "POST /v0/agents": "cursor:agent:create", "GET /v0/agents": "cursor:agent:list", diff --git a/litellm/proxy/proxy_cli.py b/litellm/proxy/proxy_cli.py index 37bab3a45d0..e4c5dabb50b 100644 --- a/litellm/proxy/proxy_cli.py +++ b/litellm/proxy/proxy_cli.py @@ -321,9 +321,7 @@ class ProxyInitializationHelpers: _endpoint_str = ( f"curl --location 'http://0.0.0.0:{port}/chat/completions' \\" ) - curl_command = ( - _endpoint_str - + """ + curl_command = _endpoint_str + """ --header 'Content-Type: application/json' \\ --data ' { "model": "gpt-3.5-turbo", @@ -336,7 +334,6 @@ class ProxyInitializationHelpers: }' \n """ - ) print() # noqa print( # noqa '\033[1;34mLiteLLM: Test your local proxy with: "litellm --test" This runs an openai.ChatCompletion request to your proxy [In a new terminal tab]\033[0m\n' @@ -412,11 +409,9 @@ class ProxyInitializationHelpers: with open(os.devnull, "w") as devnull: subprocess.Popen(command, stdout=devnull, stderr=devnull) except Exception as e: - print( # noqa - f""" + print(f""" LiteLLM Warning: proxy started with `ollama` model\n`ollama serve` failed with Exception{e}. \nEnsure you run `ollama serve` - """ - ) # noqa + """) # noqa # noqa @staticmethod def _is_port_in_use(port): diff --git a/litellm/proxy/proxy_server.py b/litellm/proxy/proxy_server.py index 3d558ede9f1..759534a32a1 100644 --- a/litellm/proxy/proxy_server.py +++ b/litellm/proxy/proxy_server.py @@ -2710,11 +2710,9 @@ def run_ollama_serve(): with open(os.devnull, "w") as devnull: subprocess.Popen(command, stdout=devnull, stderr=devnull) except Exception as e: - verbose_proxy_logger.debug( - f""" + verbose_proxy_logger.debug(f""" LiteLLM Warning: proxy started with `ollama` model\n`ollama serve` failed with Exception{e}. \nEnsure you run `ollama serve` - """ - ) + """) def _get_process_rss_mb() -> Optional[float]: diff --git a/litellm/proxy/spend_tracking/spend_management_endpoints.py b/litellm/proxy/spend_tracking/spend_management_endpoints.py index d030fabe8b5..e3019801aae 100644 --- a/litellm/proxy/spend_tracking/spend_management_endpoints.py +++ b/litellm/proxy/spend_tracking/spend_management_endpoints.py @@ -3184,16 +3184,14 @@ async def provider_budgets() -> ProviderBudgetResponse: async def get_spend_by_tags( prisma_client: PrismaClient, start_date=None, end_date=None ): - response = await prisma_client.db.query_raw( - """ + response = await prisma_client.db.query_raw(""" SELECT jsonb_array_elements_text(request_tags) AS individual_request_tag, COUNT(*) AS log_count, SUM(spend) AS total_spend FROM "LiteLLM_SpendLogs" GROUP BY individual_request_tag; - """ - ) + """) return response diff --git a/litellm/proxy/utils.py b/litellm/proxy/utils.py index 32c887f17b2..032ab6c63b2 100644 --- a/litellm/proxy/utils.py +++ b/litellm/proxy/utils.py @@ -2979,8 +2979,7 @@ class PrismaClient: required_view = "LiteLLM_VerificationTokenView" expected_views_str = ", ".join(f"'{view}'" for view in expected_views) pg_schema = os.getenv("DATABASE_SCHEMA", "public") - ret = await self.db.query_raw( - f""" + ret = await self.db.query_raw(f""" WITH existing_views AS ( SELECT viewname FROM pg_views @@ -2992,8 +2991,7 @@ class PrismaClient: (SELECT COUNT(*) FROM existing_views) AS view_count, ARRAY_AGG(viewname) AS view_names FROM existing_views - """ - ) + """) expected_total_views = len(expected_views) if ret[0]["view_count"] == expected_total_views: verbose_proxy_logger.info("All necessary views exist!") @@ -3002,8 +3000,7 @@ class PrismaClient: ## check if required view exists ## if ret[0]["view_names"] and required_view not in ret[0]["view_names"]: await self.health_check() # make sure we can connect to db - await self.db.execute_raw( - """ + await self.db.execute_raw(""" CREATE VIEW "LiteLLM_VerificationTokenView" AS SELECT v.*, @@ -3013,8 +3010,7 @@ class PrismaClient: t.rpm_limit AS team_rpm_limit FROM "LiteLLM_VerificationToken" v LEFT JOIN "LiteLLM_TeamTable" t ON v.team_id = t.team_id; - """ - ) + """) verbose_proxy_logger.info( "LiteLLM_VerificationTokenView Created in DB!" @@ -6068,6 +6064,8 @@ async def get_available_models_for_user( include_model_access_groups=include_model_access_groups, ) + effective_team_id = team_id or user_api_key_dict.team_id + # Get complete model list all_models = get_complete_model_list( key_models=key_models, @@ -6080,6 +6078,7 @@ async def get_available_models_for_user( model_access_groups=model_access_groups, include_model_access_groups=include_model_access_groups, only_model_access_groups=only_model_access_groups, + team_id=effective_team_id, ) return all_models diff --git a/litellm/proxy/vertex_ai_endpoints/langfuse_endpoints.py b/litellm/proxy/vertex_ai_endpoints/langfuse_endpoints.py index 8ce1bedcf90..b47f6a747db 100644 --- a/litellm/proxy/vertex_ai_endpoints/langfuse_endpoints.py +++ b/litellm/proxy/vertex_ai_endpoints/langfuse_endpoints.py @@ -1,5 +1,5 @@ """ -What is this? +What is this? Logging Pass-Through Endpoints """ diff --git a/litellm/responses/sse_output_recovery.py b/litellm/responses/sse_output_recovery.py new file mode 100644 index 00000000000..5c18770a611 --- /dev/null +++ b/litellm/responses/sse_output_recovery.py @@ -0,0 +1,136 @@ +""" +Shared helpers for recovering Responses API output items from raw SSE chunks. + +The same recovery logic is needed in multiple places (e.g. the ChatGPT +Responses transformation and the LiteLLM Responses-to-Chat-Completions +bridge). Keep the implementation in a single module so a fix in one +caller automatically applies to all of them. +""" + +import json +from typing import Any, Dict, Optional + +from litellm.constants import STREAM_SSE_DONE_STRING + +_MAX_CONTENT_INDEX = 1024 + + +def parse_sse_json_chunk(chunk: str) -> Optional[Dict[str, Any]]: + """Parse a single raw SSE line into a JSON object dict. + + Returns ``None`` for empty lines, ``event:`` lines, ``[DONE]`` markers, + invalid JSON, or non-dict payloads. Centralizes the parsing step that + feeds into the recovery helpers in this module so behavior stays + consistent across all callers. + """ + # Import locally to avoid a circular import with the streaming handler. + from litellm.litellm_core_utils.streaming_handler import CustomStreamWrapper + + stripped_chunk = ( + CustomStreamWrapper._strip_sse_data_from_chunk(chunk.strip()) or "" + ).strip() + if ( + not stripped_chunk + or stripped_chunk == STREAM_SSE_DONE_STRING + or stripped_chunk.startswith("event:") + ): + return None + try: + parsed_chunk = json.loads(stripped_chunk) + except json.JSONDecodeError: + return None + if not isinstance(parsed_chunk, dict): + return None + return parsed_chunk + + +def record_output_item_chunk( + parsed_chunk: Dict[str, Any], + output_items: Dict[int, Dict[str, Any]], +) -> None: + """Record an OUTPUT_ITEM_DONE chunk into ``output_items`` keyed by + ``output_index`` (falling back to the next free slot when missing). + """ + item = parsed_chunk.get("item") + if not isinstance(item, dict): + return + try: + output_index_raw = parsed_chunk.get("output_index") + if output_index_raw is None: + raise ValueError("missing output_index") + output_index = int(output_index_raw) + except (TypeError, ValueError): + output_index = len(output_items) + output_items[output_index] = item + + +def record_output_text_chunk( + parsed_chunk: Dict[str, Any], + output_items: Dict[int, Dict[str, Any]], + text_only_items: Dict[int, Dict[str, Any]], +) -> None: + """Record an OUTPUT_TEXT_DONE chunk as a synthetic message item in + ``text_only_items``. Real OUTPUT_ITEM_DONE events already captured in + ``output_items`` take precedence at the same ``output_index``. + """ + text = parsed_chunk.get("text") + if not isinstance(text, str): + return + + try: + output_index_raw = parsed_chunk.get("output_index") + if output_index_raw is None: + raise ValueError("missing output_index") + output_index = int(output_index_raw) + except (TypeError, ValueError): + output_index = len(text_only_items) + + if output_index in output_items: + return + + item = text_only_items.get(output_index) + if item is None: + item = { + "type": "message", + "id": parsed_chunk.get("item_id") or f"msg_{output_index}", + "role": "assistant", + "status": "completed", + "content": [], + } + text_only_items[output_index] = item + + content = item.setdefault("content", []) + if not isinstance(content, list): + return + + try: + content_index_raw = parsed_chunk.get("content_index") + if content_index_raw is None: + raise ValueError("missing content_index") + content_index = int(content_index_raw) + except (TypeError, ValueError): + content_index = len(content) + + if content_index < 0 or content_index > _MAX_CONTENT_INDEX: + return + + while len(content) <= content_index: + content.append( + { + "type": "output_text", + "text": "", + "annotations": [], + } + ) + + content_item = content[content_index] + if not isinstance(content_item, dict): + content_item = {} + content[content_index] = content_item + + content_item["type"] = "output_text" + content_item["text"] = text + if parsed_chunk.get("annotations") is not None: + content_item["annotations"] = parsed_chunk["annotations"] + else: + content_item.setdefault("annotations", []) diff --git a/litellm/router.py b/litellm/router.py index c968c819400..debccb0e83f 100644 --- a/litellm/router.py +++ b/litellm/router.py @@ -848,7 +848,7 @@ class Router: @staticmethod def _normalize_strategy( - strategy: Union[RoutingStrategy, str, None] + strategy: Union[RoutingStrategy, str, None], ) -> Optional[str]: if strategy is None: return None @@ -7778,6 +7778,38 @@ class Router: _shared_model_info = { k: v for k, v in _model_info.items() if k not in _custom_pricing_fields } + _existing_shared_mode = ( + cast(Optional[dict], litellm.model_cost.get(_model_name, {})) or {} + ).get("mode") + _deployment_mode = _shared_model_info.get("mode") + # Keep the built-in bridge mode stable for shared backend keys. + # Multiple aliases can point at the same provider/model backend, + # but their deployment-level overrides should not downgrade the + # backend from responses -> chat via last-write-wins registration. + # Only preserve in that specific direction so legitimate upgrades + # (e.g. chat -> responses) and unrelated mode changes still apply, + # and so a missing deployment mode does not silently clear the + # existing shared backend mode. + _is_responses_to_chat_downgrade = ( + _existing_shared_mode == "responses" and _deployment_mode == "chat" + ) + _would_clear_existing_mode = ( + _existing_shared_mode is not None and _deployment_mode is None + ) + if _is_responses_to_chat_downgrade or _would_clear_existing_mode: + if _deployment_mode is not None: + verbose_router_logger.warning( + "Router: preserving existing mode=%s for shared backend " + "key %s instead of the deployment-specified mode=%s " + "(prevents alias registration from downgrading the " + "shared backend mode).", + _existing_shared_mode, + _model_name, + _deployment_mode, + ) + _shared_model_info["mode"] = _existing_shared_mode + + # Always register the (possibly mode-preserved) shared backend info. _backend_alias_cost = {_model_name: _shared_model_info} if "responses/" in _model_name: _stripped_model_name = _model_name.replace("responses/", "") diff --git a/litellm/router_strategy/adaptive_router/hooks.py b/litellm/router_strategy/adaptive_router/hooks.py index 9e346006ac1..99fe5e26f7f 100644 --- a/litellm/router_strategy/adaptive_router/hooks.py +++ b/litellm/router_strategy/adaptive_router/hooks.py @@ -103,7 +103,7 @@ def _last_user_content(messages: Optional[List[Dict[str, Any]]]) -> Optional[str def _recent_tool_results( - messages: Optional[List[Dict[str, Any]]] + messages: Optional[List[Dict[str, Any]]], ) -> List[Dict[str, Any]]: """Extract the current turn's tool result payloads from the request messages. diff --git a/litellm/router_strategy/adaptive_router/signals.py b/litellm/router_strategy/adaptive_router/signals.py index a48bdea1eb6..5e33a64d27f 100644 --- a/litellm/router_strategy/adaptive_router/signals.py +++ b/litellm/router_strategy/adaptive_router/signals.py @@ -24,7 +24,6 @@ from litellm.router_strategy.adaptive_router.config import ( TOOL_CALL_HISTORY_MAX, ) - # ---- Public types --------------------------------------------------------- diff --git a/litellm/router_strategy/budget_limiter.py b/litellm/router_strategy/budget_limiter.py index be27b852478..da41577e99a 100644 --- a/litellm/router_strategy/budget_limiter.py +++ b/litellm/router_strategy/budget_limiter.py @@ -10,11 +10,11 @@ This means you can use this with weighted-pick, lowest-latency, simple-shuffle, Example: ``` openai: - budget_limit: 0.000000000001 - time_period: 1d + budget_limit: 0.000000000001 + time_period: 1d anthropic: - budget_limit: 100 - time_period: 7d + budget_limit: 100 + time_period: 7d ``` """ diff --git a/litellm/router_utils/get_retry_from_policy.py b/litellm/router_utils/get_retry_from_policy.py index ec326ebb50d..162d6428f85 100644 --- a/litellm/router_utils/get_retry_from_policy.py +++ b/litellm/router_utils/get_retry_from_policy.py @@ -1,5 +1,5 @@ """ -Get num retries for an exception. +Get num retries for an exception. - Account for retry policy by exception type. """ diff --git a/litellm/router_utils/pattern_match_deployments.py b/litellm/router_utils/pattern_match_deployments.py index 17b453d6031..48f85a83411 100644 --- a/litellm/router_utils/pattern_match_deployments.py +++ b/litellm/router_utils/pattern_match_deployments.py @@ -34,7 +34,7 @@ class PatternUtils: @staticmethod def sorted_patterns( - patterns: Dict[str, List[Dict]] + patterns: Dict[str, List[Dict]], ) -> List[Tuple[str, List[Dict]]]: """ Cached property for patterns sorted by specificity. diff --git a/litellm/router_utils/router_callbacks/track_deployment_metrics.py b/litellm/router_utils/router_callbacks/track_deployment_metrics.py index 1f226879d03..9039b0df8e6 100644 --- a/litellm/router_utils/router_callbacks/track_deployment_metrics.py +++ b/litellm/router_utils/router_callbacks/track_deployment_metrics.py @@ -1,5 +1,5 @@ """ -Helper functions to get/set num success and num failures per deployment +Helper functions to get/set num success and num failures per deployment set_deployment_failures_for_current_minute diff --git a/litellm/secret_managers/aws_secret_manager.py b/litellm/secret_managers/aws_secret_manager.py index fbe951e6492..60d0a713eff 100644 --- a/litellm/secret_managers/aws_secret_manager.py +++ b/litellm/secret_managers/aws_secret_manager.py @@ -4,7 +4,7 @@ This is a file for the AWS Secret Manager Integration Relevant issue: https://github.com/BerriAI/litellm/issues/1883 Requires: -* `os.environ["AWS_REGION_NAME"], +* `os.environ["AWS_REGION_NAME"], * `pip install boto3>=1.28.57` """ diff --git a/litellm/secret_managers/aws_secret_manager_v2.py b/litellm/secret_managers/aws_secret_manager_v2.py index c1b4d019dcf..4461e34396e 100644 --- a/litellm/secret_managers/aws_secret_manager_v2.py +++ b/litellm/secret_managers/aws_secret_manager_v2.py @@ -10,7 +10,7 @@ Handles Async Operations for: Relevant issue: https://github.com/BerriAI/litellm/issues/1883 Requires: -* `os.environ["AWS_REGION_NAME"], +* `os.environ["AWS_REGION_NAME"], * `pip install boto3>=1.28.57` """ diff --git a/litellm/types/guardrails.py b/litellm/types/guardrails.py index 751113400d3..0a51ce3d456 100644 --- a/litellm/types/guardrails.py +++ b/litellm/types/guardrails.py @@ -100,6 +100,7 @@ class SupportedGuardrailIntegrations(Enum): MCP_JWT_SIGNER = "mcp_jwt_signer" LLM_AS_A_JUDGE = "llm_as_a_judge" QOSTODIAN_NEXUS = "qostodian_nexus" + RUBRIK = "rubrik" class Role(Enum): diff --git a/litellm/types/utils.py b/litellm/types/utils.py index 6084f14e2df..282baff07fe 100644 --- a/litellm/types/utils.py +++ b/litellm/types/utils.py @@ -147,6 +147,7 @@ class ProviderSpecificModelInfo(TypedDict, total=False): supports_low_reasoning_effort: Optional[bool] supports_xhigh_reasoning_effort: Optional[bool] supports_max_reasoning_effort: Optional[bool] + supports_output_config: Optional[bool] class SearchContextCostPerQuery(TypedDict, total=False): @@ -243,6 +244,7 @@ class ModelInfoBase(ProviderSpecificModelInfo, total=False): float ] # video_generation tier: key output_cost_per_second_ (e.g. 1080p, 720p) ocr_cost_per_page: Optional[float] # for OCR models + ocr_cost_per_credit: Optional[float] # for OCR models priced by credit annotation_cost_per_page: Optional[float] # for OCR models search_context_cost_per_query: Optional[ SearchContextCostPerQuery @@ -260,6 +262,7 @@ class ModelInfoBase(ProviderSpecificModelInfo, total=False): "chat", "audio_transcription", "responses", + "ocr", ] ] tpm: Optional[int] @@ -2765,6 +2768,20 @@ class StandardLoggingGuardrailInformation(TypedDict, total=False): risk_score: Optional[float] """Risk score 0-10 indicating how risky the request was (higher = riskier). Computed by the guardrail provider.""" + violation_categories: Optional[List[str]] + """Names of the policy items that intervened on this request (e.g. Bedrock + topic-policy topic names, content-policy filter types, PII entity types). + Populated by the provider hook before redaction so downstream loggers + (OTEL, Langfuse, ...) can filter by violation category without parsing + the raw guardrail_response blob. Empty/absent when the guardrail allowed + the request through.""" + + guardrail_action: Optional[str] + """Provider's raw top-level action string (e.g. Bedrock's ``GUARDRAIL_INTERVENED`` + or ``NONE``). Populated by the provider hook so the OTEL integration can + surface it as a queryable span attribute without parsing the raw + guardrail_response blob.""" + class EvalVerdict(TypedDict, total=False): criterion_name: str @@ -2806,6 +2823,8 @@ class GuardrailTracingDetail(TypedDict, total=False): patterns_checked: Optional[int] alert_recipients: Optional[List[str]] risk_score: Optional[float] + violation_categories: Optional[List[str]] + guardrail_action: Optional[str] StandardLoggingPayloadStatus = Literal["success", "failure"] @@ -3219,6 +3238,7 @@ class LlmProviders(str, Enum): ANTHROPIC_TEXT = "anthropic_text" BYTEZ = "bytez" REPLICATE = "replicate" + REDUCTO = "reducto" RUNWAYML = "runwayml" AWS_POLLY = "aws_polly" HUGGINGFACE = "huggingface" diff --git a/litellm/utils.py b/litellm/utils.py index 001c89fee4c..2487d39bd0d 100644 --- a/litellm/utils.py +++ b/litellm/utils.py @@ -5387,6 +5387,16 @@ def _strip_model_name(model: str, custom_llm_provider: Optional[str]) -> str: # Global case-insensitive lookup map for model_cost (built eagerly at module import) _model_cost_lowercase_map: Optional[Dict[str, str]] = None +# Monotonic counter bumped on every model_cost mutation. Consumers that +# memoize derived state (e.g. provider-specific indices) can include this +# value in their cache key so they invalidate even when key add+remove or +# in-place value replacement leaves len/id unchanged. +_model_cost_mutation_generation: int = 0 + + +def get_model_cost_mutation_generation() -> int: + return _model_cost_mutation_generation + def _invalidate_model_cost_lowercase_map() -> None: """Invalidate the case-insensitive lookup map for model_cost. @@ -5394,8 +5404,9 @@ def _invalidate_model_cost_lowercase_map() -> None: Call this whenever litellm.model_cost is modified to ensure the map is rebuilt. Also clears related LRU caches that depend on model_cost data. """ - global _model_cost_lowercase_map + global _model_cost_lowercase_map, _model_cost_mutation_generation _model_cost_lowercase_map = None + _model_cost_mutation_generation += 1 # Clear LRU caches that depend on model_cost data get_model_info.cache_clear() @@ -5986,6 +5997,7 @@ def _get_model_info_helper( # noqa: PLR0915 tpm=_model_info.get("tpm", None), rpm=_model_info.get("rpm", None), ocr_cost_per_page=_model_info.get("ocr_cost_per_page", None), + ocr_cost_per_credit=_model_info.get("ocr_cost_per_credit", None), annotation_cost_per_page=_model_info.get( "annotation_cost_per_page", None ), @@ -9241,6 +9253,18 @@ class ProviderConfigManager: return get_vertex_ai_ocr_config(model=model) + if provider == litellm.LlmProviders.REDUCTO: + from litellm.llms.reducto.ocr.transformation import ( + ReductoParseLegacyConfig, + ReductoParseV3Config, + ) + + if model == "parse-v3": + return ReductoParseV3Config() + if model == "parse-legacy": + return ReductoParseLegacyConfig() + return None + MistralOCRConfig = getattr(sys.modules[__name__], "MistralOCRConfig") PROVIDER_TO_CONFIG_MAP = { litellm.LlmProviders.MISTRAL: MistralOCRConfig, diff --git a/litellm/vector_store_files/utils.py b/litellm/vector_store_files/utils.py index ffe73516bda..1ee5b47e306 100644 --- a/litellm/vector_store_files/utils.py +++ b/litellm/vector_store_files/utils.py @@ -21,7 +21,7 @@ class VectorStoreFileRequestUtils: @staticmethod def get_create_request_params( - params: Dict[str, Any] + params: Dict[str, Any], ) -> VectorStoreFileCreateRequest: filtered = VectorStoreFileRequestUtils._filter_params( params=params, model=VectorStoreFileCreateRequest @@ -37,7 +37,7 @@ class VectorStoreFileRequestUtils: @staticmethod def get_update_request_params( - params: Dict[str, Any] + params: Dict[str, Any], ) -> VectorStoreFileUpdateRequest: filtered = VectorStoreFileRequestUtils._filter_params( params=params, model=VectorStoreFileUpdateRequest diff --git a/model_prices_and_context_window.json b/model_prices_and_context_window.json index bda94e4768f..31a5993a240 100644 --- a/model_prices_and_context_window.json +++ b/model_prices_and_context_window.json @@ -1011,6 +1011,7 @@ "supports_vision": true, "tool_use_system_prompt_tokens": 346, "supports_native_structured_output": true, + "supports_output_config": true, "supports_max_reasoning_effort": true, "supports_minimal_reasoning_effort": true }, @@ -1041,6 +1042,7 @@ "supports_vision": true, "tool_use_system_prompt_tokens": 346, "supports_native_structured_output": true, + "supports_output_config": true, "supports_max_reasoning_effort": true, "supports_minimal_reasoning_effort": true }, @@ -1071,6 +1073,7 @@ "supports_vision": true, "tool_use_system_prompt_tokens": 346, "supports_native_structured_output": true, + "supports_output_config": true, "supports_max_reasoning_effort": true, "supports_minimal_reasoning_effort": true }, @@ -1100,6 +1103,7 @@ "supports_vision": true, "tool_use_system_prompt_tokens": 346, "supports_native_structured_output": true, + "supports_output_config": true, "supports_max_reasoning_effort": true, "supports_minimal_reasoning_effort": true }, @@ -1129,6 +1133,7 @@ "supports_vision": true, "tool_use_system_prompt_tokens": 346, "supports_native_structured_output": true, + "supports_output_config": true, "supports_max_reasoning_effort": true, "supports_minimal_reasoning_effort": true }, @@ -1328,6 +1333,7 @@ "supports_vision": true, "tool_use_system_prompt_tokens": 346, "supports_native_structured_output": true, + "supports_output_config": true, "supports_minimal_reasoning_effort": true }, "global.anthropic.claude-sonnet-4-6": { @@ -1358,6 +1364,7 @@ "supports_vision": true, "tool_use_system_prompt_tokens": 346, "supports_native_structured_output": true, + "supports_output_config": true, "supports_minimal_reasoning_effort": true }, "us.anthropic.claude-sonnet-4-6": { @@ -1388,6 +1395,7 @@ "supports_vision": true, "tool_use_system_prompt_tokens": 346, "supports_native_structured_output": true, + "supports_output_config": true, "supports_minimal_reasoning_effort": true }, "eu.anthropic.claude-sonnet-4-6": { @@ -1417,6 +1425,7 @@ "supports_vision": true, "tool_use_system_prompt_tokens": 346, "supports_native_structured_output": true, + "supports_output_config": true, "supports_minimal_reasoning_effort": true }, "au.anthropic.claude-sonnet-4-6": { @@ -1446,6 +1455,7 @@ "supports_vision": true, "tool_use_system_prompt_tokens": 346, "supports_native_structured_output": true, + "supports_output_config": true, "supports_minimal_reasoning_effort": true }, "jp.anthropic.claude-sonnet-4-6": { @@ -1475,6 +1485,7 @@ "supports_vision": true, "tool_use_system_prompt_tokens": 346, "supports_native_structured_output": true, + "supports_output_config": true, "supports_minimal_reasoning_effort": true }, "anthropic.claude-sonnet-4-20250514-v1:0": { @@ -1996,6 +2007,7 @@ "supports_tool_choice": true, "supports_vision": true, "tool_use_system_prompt_tokens": 159, + "supports_output_config": true, "supports_max_reasoning_effort": true, "supports_minimal_reasoning_effort": true }, @@ -2093,6 +2105,7 @@ "supports_tool_choice": true, "supports_vision": true, "tool_use_system_prompt_tokens": 346, + "supports_output_config": true, "supports_minimal_reasoning_effort": true }, "azure/computer-use-preview": { @@ -9643,6 +9656,7 @@ "supports_tool_choice": true, "supports_vision": true, "tool_use_system_prompt_tokens": 346, + "supports_output_config": true, "supports_minimal_reasoning_effort": true }, "claude-sonnet-4-5-20250929-v1:0": { @@ -9840,6 +9854,7 @@ "us": 1.1, "fast": 6.0 }, + "supports_output_config": true, "supports_max_reasoning_effort": true, "supports_minimal_reasoning_effort": true }, @@ -9875,7 +9890,8 @@ "fast": 6.0 }, "supports_max_reasoning_effort": true, - "supports_minimal_reasoning_effort": true + "supports_minimal_reasoning_effort": true, + "supports_output_config": true }, "claude-opus-4-7": { "cache_creation_input_token_cost": 6.25e-06, @@ -9910,7 +9926,8 @@ "us": 1.1, "fast": 6.0 }, - "supports_minimal_reasoning_effort": true + "supports_minimal_reasoning_effort": true, + "supports_output_config": true }, "claude-opus-4-7-20260416": { "cache_creation_input_token_cost": 6.25e-06, @@ -9945,7 +9962,8 @@ "us": 1.1, "fast": 6.0 }, - "supports_minimal_reasoning_effort": true + "supports_minimal_reasoning_effort": true, + "supports_output_config": true }, "claude-sonnet-4-20250514": { "deprecation_date": "2026-05-14", @@ -13982,6 +14000,21 @@ "supports_response_schema": true, "supports_tool_choice": true }, + "fireworks_ai/accounts/fireworks/models/glm-5p1": { + "cache_read_input_token_cost": 2.6e-07, + "input_cost_per_token": 1.4e-06, + "litellm_provider": "fireworks_ai", + "max_input_tokens": 202800, + "max_output_tokens": 202800, + "max_tokens": 202800, + "mode": "chat", + "output_cost_per_token": 4.4e-06, + "source": "https://fireworks.ai/models/fireworks/glm-5p1", + "supports_function_calling": false, + "supports_reasoning": true, + "supports_response_schema": false, + "supports_tool_choice": false + }, "fireworks_ai/accounts/fireworks/models/gpt-oss-120b": { "input_cost_per_token": 1.5e-07, "litellm_provider": "fireworks_ai", @@ -14248,6 +14281,21 @@ "supports_response_schema": true, "supports_tool_choice": true }, + "fireworks_ai/glm-5p1": { + "cache_read_input_token_cost": 2.6e-07, + "input_cost_per_token": 1.4e-06, + "litellm_provider": "fireworks_ai", + "max_input_tokens": 202800, + "max_output_tokens": 202800, + "max_tokens": 202800, + "mode": "chat", + "output_cost_per_token": 4.4e-06, + "source": "https://fireworks.ai/models/fireworks/glm-5p1", + "supports_function_calling": false, + "supports_reasoning": true, + "supports_response_schema": false, + "supports_tool_choice": false + }, "fireworks_ai/kimi-k2p5": { "cache_read_input_token_cost": 1e-07, "input_cost_per_token": 6e-07, @@ -28937,14 +28985,16 @@ "mode": "responses", "supports_web_search": true, "supports_reasoning": false, - "supports_function_calling": true + "supports_function_calling": true, + "supports_output_config": true }, "perplexity/anthropic/claude-opus-4-7": { "litellm_provider": "perplexity", "mode": "responses", "supports_web_search": true, "supports_reasoning": false, - "supports_function_calling": true + "supports_function_calling": true, + "supports_output_config": true }, "perplexity/anthropic/claude-opus-4-5": { "litellm_provider": "perplexity", @@ -29158,6 +29208,24 @@ "supports_tool_choice": true, "source": "https://aws.amazon.com/bedrock/pricing/" }, + "reducto/parse-legacy": { + "litellm_provider": "reducto", + "mode": "ocr", + "ocr_cost_per_credit": 0.015, + "source": "https://reducto.ai/pricing", + "supported_endpoints": [ + "/v1/ocr" + ] + }, + "reducto/parse-v3": { + "litellm_provider": "reducto", + "mode": "ocr", + "ocr_cost_per_credit": 0.015, + "source": "https://reducto.ai/pricing", + "supported_endpoints": [ + "/v1/ocr" + ] + }, "recraft/recraftv2": { "litellm_provider": "recraft", "mode": "image_generation", @@ -33337,6 +33405,7 @@ "supports_tool_choice": true, "supports_vision": true, "tool_use_system_prompt_tokens": 346, + "supports_output_config": true, "supports_max_reasoning_effort": true, "supports_minimal_reasoning_effort": true }, @@ -33365,6 +33434,7 @@ "supports_tool_choice": true, "supports_vision": true, "tool_use_system_prompt_tokens": 346, + "supports_output_config": true, "supports_max_reasoning_effort": true, "supports_minimal_reasoning_effort": true }, @@ -33478,6 +33548,7 @@ "search_context_size_low": 0.01, "search_context_size_medium": 0.01 }, + "supports_output_config": true, "supports_minimal_reasoning_effort": true }, "vertex_ai/claude-sonnet-4-5@20250929": { @@ -40590,6 +40661,7 @@ "search_context_size_low": 0.01, "search_context_size_medium": 0.01 }, + "supports_output_config": true, "supports_minimal_reasoning_effort": true }, "duckduckgo/search": { diff --git a/provider_endpoints_support.json b/provider_endpoints_support.json index 1d577213a1b..388752b032e 100644 --- a/provider_endpoints_support.json +++ b/provider_endpoints_support.json @@ -1904,6 +1904,23 @@ "rerank": false } }, + "reducto": { + "display_name": "Reducto (`reducto`)", + "url": "https://docs.litellm.ai/docs/providers/reducto", + "endpoints": { + "chat_completions": false, + "messages": false, + "responses": false, + "embeddings": false, + "image_generations": false, + "audio_transcriptions": false, + "audio_speech": false, + "moderations": false, + "batches": false, + "rerank": false, + "ocr": true + } + }, "replicate": { "display_name": "Replicate (`replicate`)", "url": "https://docs.litellm.ai/docs/providers/replicate", diff --git a/pyproject.toml b/pyproject.toml index 70681c4ed6c..f2686047f3c 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -33,8 +33,9 @@ Homepage = "https://litellm.ai" Repository = "https://github.com/BerriAI/litellm" Documentation = "https://docs.litellm.ai" -# Dependencies pinned from the published `litellm[proxy]==1.83.0` resolution. -# Docker and CI should prefer `uv.lock` rather than maintaining parallel installers. +# Optional extras retain exact pins because they are consumed by Docker images +# where exact reproducibility matters. The core SDK uses ranges so downstream +# consumers can coexist with other packages without forced downgrades. [project.optional-dependencies] proxy = [ "gunicorn==23.0.0", @@ -131,7 +132,7 @@ litellm-proxy = "litellm.proxy.client.cli:cli" dev = [ "diff-cover==9.7.2", "flake8==7.3.0", - "black==24.10.0", + "black==26.3.1", "mypy==1.19.0", "pytest==9.0.3", "pytest-mock==3.15.1", @@ -287,6 +288,7 @@ paths_to_mutate = [ ] tests_dir = [ "tests/test_litellm/proxy/management_endpoints/", + "tests/proxy_behavior/management/", ] also_copy = [ "litellm/", @@ -312,3 +314,4 @@ pytest_add_cli_args = [ [tool.coverage.run] source = ["litellm"] relative_files = true + diff --git a/tests/code_coverage_tests/liccheck.ini b/tests/code_coverage_tests/liccheck.ini index 3d53ecede7b..0d1a6f0b045 100644 --- a/tests/code_coverage_tests/liccheck.ini +++ b/tests/code_coverage_tests/liccheck.ini @@ -156,6 +156,7 @@ pytest: >=9.0.3 # MIT license pytest-postgresql: >=7.0.2 # LGPLv3+ license pytest-xdist: >=3.8.0 # MIT License ruff: >=0.15.3 # MIT License +black: >=26.3.1 # MIT License manually verified (uses PEP 639 License-Expression: MIT, not the legacy License field, so liccheck reports it as unknown) types-requests: >=2.32.4.20260107 # Apache 2.0 license (typeshed) types-pyyaml: >=6.0.12.20250915 # Apache 2.0 license (typeshed) fakeredis: >=2.34.1 # BSD license diff --git a/tests/llm_translation/realtime/base_realtime_tests.py b/tests/llm_translation/realtime/base_realtime_tests.py index 1d55f13b00d..1a2c6ff6a9c 100644 --- a/tests/llm_translation/realtime/base_realtime_tests.py +++ b/tests/llm_translation/realtime/base_realtime_tests.py @@ -10,7 +10,7 @@ import json import os import sys from abc import ABC, abstractmethod -from typing import Optional +from typing import Optional, Tuple, Union import pytest import websockets @@ -79,7 +79,7 @@ class RealTimeWebSocketClient: def _is_initial_event(self, msg_type: str) -> bool: """Check if message type is an initial connection event""" - # OpenAI sends "session.created", xAI sends "conversation.created" + # OpenAI and xAI send "session.created"; some providers send "conversation.created" return msg_type in ["session.created", "conversation.created"] async def receive_text(self): @@ -153,8 +153,14 @@ class BaseRealtimeTest(ABC): pass @abstractmethod - def get_initial_event_type(self) -> str: - """Return the expected initial event type (e.g., 'session.created' or 'conversation.created')""" + def get_initial_event_type(self) -> Union[str, Tuple[str, ...]]: + """Return the expected initial event type(s). + + May return a single event type (e.g. ``'session.created'``) or a tuple + of acceptable types when the upstream provider can legitimately emit + more than one initial event (e.g. xAI's Grok Voice Agent has shipped + both ``conversation.created`` and ``session.created``). + """ pass def get_skip_reason(self) -> str: @@ -229,9 +235,14 @@ class BaseRealtimeTest(ABC): # Verify initial event initial_event = websocket_client.messages_received[0] + expected_event_type = self.get_initial_event_type() + if isinstance(expected_event_type, str): + allowed_event_types: Tuple[str, ...] = (expected_event_type,) + else: + allowed_event_types = tuple(expected_event_type) assert ( - initial_event["type"] == self.get_initial_event_type() - ), f"Expected {self.get_initial_event_type()}, got {initial_event.get('type')}" + initial_event["type"] in allowed_event_types + ), f"Expected one of {allowed_event_types}, got {initial_event.get('type')}" @pytest.mark.asyncio async def test_realtime_with_query_params(self): diff --git a/tests/llm_translation/realtime/test_xai_realtime.py b/tests/llm_translation/realtime/test_xai_realtime.py index 0bb7a59bb1a..8ffcb3db30d 100644 --- a/tests/llm_translation/realtime/test_xai_realtime.py +++ b/tests/llm_translation/realtime/test_xai_realtime.py @@ -7,6 +7,7 @@ Uses the base test class to ensure consistent behavior across providers. import os import sys +from typing import Tuple import pytest @@ -19,10 +20,12 @@ class TestXAIRealtime(BaseRealtimeTest): """ E2E tests for xAI Realtime API. - xAI's Grok Voice Agent API is OpenAI-compatible but uses: - - Different initial event: "conversation.created" instead of "session.created" - - Different endpoint: wss://api.x.ai/v1/realtime + xAI's Grok Voice Agent API is OpenAI-compatible: + - Endpoint: wss://api.x.ai/v1/realtime - Model: grok-4-1-fast-non-reasoning + - Initial event: historically "conversation.created"; xAI has since shipped + "session.created" (matching OpenAI). Accept either to avoid spurious + failures whenever xAI flips the wire format. """ def get_model(self) -> str: @@ -31,5 +34,5 @@ class TestXAIRealtime(BaseRealtimeTest): def get_api_key_env_var(self) -> str: return "XAI_API_KEY" - def get_initial_event_type(self) -> str: - return "conversation.created" + def get_initial_event_type(self) -> Tuple[str, ...]: + return ("conversation.created", "session.created") diff --git a/tests/local_testing/test_amazing_vertex_completion.py b/tests/local_testing/test_amazing_vertex_completion.py index 9782bf3c2af..2382b8a5197 100644 --- a/tests/local_testing/test_amazing_vertex_completion.py +++ b/tests/local_testing/test_amazing_vertex_completion.py @@ -4223,7 +4223,13 @@ def test_gemini_google_maps_tool_simple(): ) print(f"Response: {response.model_dump_json(indent=4)}") assert response.choices[0].message.content is not None - except litellm.RateLimitError: + except (litellm.RateLimitError, litellm.InternalServerError): + # Transient Vertex-side failures (rate limiting, 500 INTERNAL from the + # Google Maps grounding backend) are not LiteLLM bugs — don't fail CI. pass + except litellm.InternalServerError: + pytest.skip( + "Google Maps Platform returned a transient 500 (upstream flake); skipping." + ) except Exception as e: pytest.fail(f"Error occurred: {e}") diff --git a/tests/proxy_behavior/__init__.py b/tests/proxy_behavior/__init__.py new file mode 100644 index 00000000000..e69de29bb2d diff --git a/tests/proxy_behavior/management/__init__.py b/tests/proxy_behavior/management/__init__.py new file mode 100644 index 00000000000..e69de29bb2d diff --git a/tests/proxy_behavior/management/actors.py b/tests/proxy_behavior/management/actors.py new file mode 100644 index 00000000000..6c2f1a61ce1 --- /dev/null +++ b/tests/proxy_behavior/management/actors.py @@ -0,0 +1,279 @@ +"""Read-world seed for the authz matrix tests: 2 orgs, 3 teams, 9 actors.""" + +import enum +import uuid +from dataclasses import dataclass +from typing import Any, Dict + +from prisma import Json + +from litellm.proxy._types import LitellmUserRoles +from litellm.proxy.utils import PrismaClient, hash_token + + +class Actor(str, enum.Enum): + PROXY_ADMIN = "proxy_admin" + ORG_ADMIN = "org_admin" + TEAM_ADMIN = "team_admin" + INTERNAL_USER = "internal_user" + OWNER = "owner" + UNRELATED_SAME_ORG = "unrelated_same_org" + CROSS_ORG_USER = "cross_org_user" + SERVICE_ACCOUNT = "service_account" + ORG_B_ADMIN = "org_b_admin" + + +PREFIX = "behavior-pin-" +ORG_A = PREFIX + "org-a" +ORG_B = PREFIX + "org-b" +TEAM_ALPHA = PREFIX + "team-alpha" +TEAM_BETA = PREFIX + "team-beta" +TEAM_GAMMA = PREFIX + "team-gamma" +BUDGET_ID = PREFIX + "budget" + + +@dataclass(frozen=True) +class SeededKey: + user_id: str + cleartext: str + hashed: str + + +@dataclass(frozen=True) +class World: + org_a_id: str + org_b_id: str + team_alpha_id: str + team_beta_id: str + team_gamma_id: str + keys: Dict[Actor, SeededKey] + + +def _new_clear_key() -> str: + return "sk-" + uuid.uuid4().hex + + +def _actor_profile() -> Dict[Actor, Dict[str, Any]]: + return { + Actor.PROXY_ADMIN: { + "user_role": LitellmUserRoles.PROXY_ADMIN.value, + "team_id": None, + "organization_id": None, + }, + Actor.ORG_ADMIN: { + "user_role": LitellmUserRoles.ORG_ADMIN.value, + "team_id": None, + "organization_id": ORG_A, + }, + Actor.TEAM_ADMIN: { + "user_role": LitellmUserRoles.INTERNAL_USER.value, + "team_id": TEAM_ALPHA, + "organization_id": ORG_A, + }, + Actor.INTERNAL_USER: { + "user_role": LitellmUserRoles.INTERNAL_USER.value, + "team_id": TEAM_ALPHA, + "organization_id": ORG_A, + }, + Actor.OWNER: { + "user_role": LitellmUserRoles.INTERNAL_USER.value, + "team_id": TEAM_ALPHA, + "organization_id": ORG_A, + }, + Actor.UNRELATED_SAME_ORG: { + "user_role": LitellmUserRoles.INTERNAL_USER.value, + "team_id": TEAM_ALPHA, + "organization_id": ORG_A, + }, + Actor.CROSS_ORG_USER: { + "user_role": LitellmUserRoles.INTERNAL_USER.value, + "team_id": TEAM_BETA, + "organization_id": ORG_B, + }, + Actor.SERVICE_ACCOUNT: { + "user_role": LitellmUserRoles.INTERNAL_USER.value, + "team_id": TEAM_ALPHA, + "organization_id": ORG_A, + }, + Actor.ORG_B_ADMIN: { + "user_role": LitellmUserRoles.ORG_ADMIN.value, + "team_id": None, + "organization_id": ORG_B, + }, + } + + +async def _wipe_world(prisma: PrismaClient) -> None: + await prisma.db.litellm_verificationtoken.delete_many( + where={"user_id": {"startswith": PREFIX}} + ) + await prisma.db.litellm_organizationmembership.delete_many( + where={"user_id": {"startswith": PREFIX}} + ) + await prisma.db.litellm_teammembership.delete_many( + where={"user_id": {"startswith": PREFIX}} + ) + await prisma.db.litellm_usertable.delete_many( + where={"user_id": {"startswith": PREFIX}} + ) + await prisma.db.litellm_teamtable.delete_many( + where={"team_id": {"startswith": PREFIX}} + ) + await prisma.db.litellm_organizationtable.delete_many( + where={"organization_id": {"startswith": PREFIX}} + ) + await prisma.db.litellm_budgettable.delete_many(where={"budget_id": BUDGET_ID}) + + +async def seed_world(prisma: PrismaClient) -> World: + await _wipe_world(prisma) + + await prisma.db.litellm_budgettable.create( + data={ + "budget_id": BUDGET_ID, + "created_by": "behavior-pin-seeder", + "updated_by": "behavior-pin-seeder", + } + ) + + for org_id, alias in [(ORG_A, "alpha"), (ORG_B, "beta")]: + await prisma.db.litellm_organizationtable.create( + data={ + "organization_id": org_id, + "organization_alias": alias, + "budget_id": BUDGET_ID, + "created_by": "behavior-pin-seeder", + "updated_by": "behavior-pin-seeder", + } + ) + + profiles = _actor_profile() + user_ids: Dict[Actor, str] = {actor: PREFIX + actor.value for actor in Actor} + + for actor, profile in profiles.items(): + teams_list = [profile["team_id"]] if profile["team_id"] else [] + await prisma.db.litellm_usertable.create( + data={ + "user_id": user_ids[actor], + "user_role": profile["user_role"], + "team_id": profile["team_id"], + "organization_id": profile["organization_id"], + "teams": teams_list, + } + ) + + # _get_user_in_team in key_management_endpoints.py walks members_with_roles + # (a JSON list of {user_id, role}), not the String[] members column — + # populate both to match what /team/new produces. + await prisma.db.litellm_teamtable.create( + data={ + "team_id": TEAM_ALPHA, + "team_alias": "alpha-1", + "organization_id": ORG_A, + "admins": [user_ids[Actor.TEAM_ADMIN]], + "members": [ + user_ids[Actor.TEAM_ADMIN], + user_ids[Actor.INTERNAL_USER], + user_ids[Actor.OWNER], + user_ids[Actor.UNRELATED_SAME_ORG], + user_ids[Actor.SERVICE_ACCOUNT], + ], + "members_with_roles": Json( + [ + {"user_id": user_ids[Actor.TEAM_ADMIN], "role": "admin"}, + {"user_id": user_ids[Actor.INTERNAL_USER], "role": "user"}, + {"user_id": user_ids[Actor.OWNER], "role": "user"}, + {"user_id": user_ids[Actor.UNRELATED_SAME_ORG], "role": "user"}, + {"user_id": user_ids[Actor.SERVICE_ACCOUNT], "role": "user"}, + ] + ), + } + ) + await prisma.db.litellm_teamtable.create( + data={ + "team_id": TEAM_BETA, + "team_alias": "beta-1", + "organization_id": ORG_B, + "admins": [], + "members": [user_ids[Actor.CROSS_ORG_USER]], + "members_with_roles": Json( + [ + {"user_id": user_ids[Actor.CROSS_ORG_USER], "role": "user"}, + ] + ), + } + ) + # TEAM_GAMMA: ORG_A team with no actor members — the "same-org, + # not-my-team" read target. + await prisma.db.litellm_teamtable.create( + data={ + "team_id": TEAM_GAMMA, + "team_alias": "gamma-1", + "organization_id": ORG_A, + "admins": [], + "members": [], + "members_with_roles": Json([]), + } + ) + + for actor, org_id, role in [ + (Actor.ORG_ADMIN, ORG_A, "org_admin"), + (Actor.TEAM_ADMIN, ORG_A, "internal_user"), + (Actor.INTERNAL_USER, ORG_A, "internal_user"), + (Actor.OWNER, ORG_A, "internal_user"), + (Actor.UNRELATED_SAME_ORG, ORG_A, "internal_user"), + (Actor.SERVICE_ACCOUNT, ORG_A, "internal_user"), + (Actor.CROSS_ORG_USER, ORG_B, "internal_user"), + (Actor.ORG_B_ADMIN, ORG_B, "org_admin"), + ]: + await prisma.db.litellm_organizationmembership.create( + data={ + "user_id": user_ids[actor], + "organization_id": org_id, + "user_role": role, + } + ) + + for actor, team_id in [ + (Actor.TEAM_ADMIN, TEAM_ALPHA), + (Actor.INTERNAL_USER, TEAM_ALPHA), + (Actor.OWNER, TEAM_ALPHA), + (Actor.UNRELATED_SAME_ORG, TEAM_ALPHA), + (Actor.SERVICE_ACCOUNT, TEAM_ALPHA), + (Actor.CROSS_ORG_USER, TEAM_BETA), + ]: + await prisma.db.litellm_teammembership.create( + data={"user_id": user_ids[actor], "team_id": team_id} + ) + + keys: Dict[Actor, SeededKey] = {} + for actor, profile in profiles.items(): + cleartext = _new_clear_key() + hashed = hash_token(cleartext) + token_data: Dict[str, Any] = { + "token": hashed, + "key_name": PREFIX + actor.value + "-key", + "user_id": user_ids[actor], + # LiteLLM_VerificationTokenView's models field rejects NULL even + # though the column is nullable in Postgres. + "models": [], + } + if profile["team_id"]: + token_data["team_id"] = profile["team_id"] + if profile["organization_id"]: + token_data["organization_id"] = profile["organization_id"] + if actor == Actor.SERVICE_ACCOUNT: + token_data["metadata"] = Json({"service_account_id": user_ids[actor]}) + await prisma.db.litellm_verificationtoken.create(data=token_data) + keys[actor] = SeededKey( + user_id=user_ids[actor], cleartext=cleartext, hashed=hashed + ) + + return World( + org_a_id=ORG_A, + org_b_id=ORG_B, + team_alpha_id=TEAM_ALPHA, + team_beta_id=TEAM_BETA, + team_gamma_id=TEAM_GAMMA, + keys=keys, + ) diff --git a/tests/proxy_behavior/management/conftest.py b/tests/proxy_behavior/management/conftest.py new file mode 100644 index 00000000000..3432f4ad6cf --- /dev/null +++ b/tests/proxy_behavior/management/conftest.py @@ -0,0 +1,206 @@ +"""Session-scoped async ASGI client for HTTP-boundary behavior tests.""" + +import os +import tempfile +import uuid +from dataclasses import dataclass +from typing import Any, AsyncIterator, Dict, Optional + +import httpx +import pytest_asyncio +import yaml +from prisma import Json + + +MASTER_KEY = "sk-1234" +SCRATCH_PREFIX = "scratch-" + + +def _write_minimal_proxy_config() -> str: + config = { + "general_settings": {"master_key": MASTER_KEY}, + "litellm_settings": {}, + } + database_url = os.environ.get("DATABASE_URL") + if database_url: + config["general_settings"]["database_url"] = database_url + f = tempfile.NamedTemporaryFile(mode="w", suffix=".yaml", delete=False) + yaml.dump(config, f) + f.close() + return f.name + + +@pytest_asyncio.fixture(scope="session") +async def proxy_app(): + from litellm.proxy import proxy_server + from litellm.proxy.proxy_server import ( + app, + cleanup_router_config_variables, + initialize, + proxy_startup_event, + ) + + cleanup_router_config_variables() + config_path = _write_minimal_proxy_config() + + # proxy_startup_event re-reads master_key from LITELLM_MASTER_KEY and + # unconditionally overwrites the global, even when initialize() already + # set it from the config YAML. Force (not setdefault) both vars: an + # ambient LITELLM_MASTER_KEY with a different value would make the proxy + # authenticate on that key while the tests still send MASTER_KEY. + os.environ["LITELLM_MASTER_KEY"] = MASTER_KEY + os.environ["CONFIG_FILE_PATH"] = config_path + + await initialize(config=config_path) + + # /key/regenerate is gated behind premium_user; flipping it lets the matrix + # pin authz behavior instead of the licensing gate. + proxy_server.premium_user = True + + async with proxy_startup_event(app): + proxy_server.premium_user = True # lifespan re-runs _license_check + # The lifespan fires check_view_exists() as a background task; on a + # fresh DB the first auth call races it and resolves user_id=None. + if proxy_server.prisma_client is not None: + await proxy_server.prisma_client.check_view_exists() + yield app + + +@pytest_asyncio.fixture(scope="session") +async def proxy_client(proxy_app) -> AsyncIterator[httpx.AsyncClient]: + transport = httpx.ASGITransport(app=proxy_app) + async with httpx.AsyncClient( + transport=transport, base_url="http://testserver" + ) as client: + yield client + + +@pytest_asyncio.fixture(scope="session") +async def prisma(proxy_app): + from litellm.proxy import proxy_server + + assert proxy_server.prisma_client is not None + return proxy_server.prisma_client + + +@pytest_asyncio.fixture(scope="session") +async def world(prisma): + from .actors import seed_world + + return await seed_world(prisma) + + +@dataclass(frozen=True) +class Scratch: + prefix: str + + def tag(self, suffix: str = "") -> str: + return f"{self.prefix}-{suffix}" if suffix else self.prefix + + +async def create_scratch_key( + proxy_client, + seeder_cleartext: str, + scratch_prefix: str, + *, + user_id: str, + team_id: Optional[str] = None, + organization_id: Optional[str] = None, +) -> str: + """Seed a scratch-tagged key via /key/generate; returns its cleartext. + + Shared by the write-scenario matrices (key update/regenerate/delete). + """ + body: Dict[str, Any] = {"key_alias": scratch_prefix, "user_id": user_id} + if team_id is not None: + body["team_id"] = team_id + if organization_id is not None: + body["organization_id"] = organization_id + resp = await proxy_client.post( + "/key/generate", + headers={"Authorization": f"Bearer {seeder_cleartext}"}, + json=body, + ) + assert resp.status_code == 200, f"setup failed: {resp.text}" + return resp.json()["key"] + + +async def create_scratch_team( + prisma, + team_id: str, + *, + organization_id: Optional[str] = None, + admin_user_ids: Optional[list] = None, + member_user_ids: Optional[list] = None, +) -> str: + """Raw-seed a scratch-tagged team row; returns its team_id. + + The target team for the team write matrices (update / member_*). Raw + prisma (not POST /team/new) avoids creation side effects — no creator + auto-add, no membership rows written onto the world's users — so seeding + never mutates the immutable read-world. The authz gates read the team's + members_with_roles JSON, so a raw-seeded team exercises them exactly as + a /team/new-created team would. team_id must start with the scratch + prefix so the `scratch` fixture reclaims the row. + """ + admin_user_ids = list(admin_user_ids or []) + member_user_ids = list(member_user_ids or []) + members_with_roles = [ + {"user_id": uid, "role": "admin"} for uid in admin_user_ids + ] + [{"user_id": uid, "role": "user"} for uid in member_user_ids] + data: Dict[str, Any] = { + "team_id": team_id, + "team_alias": team_id, + "admins": admin_user_ids, + "members": admin_user_ids + member_user_ids, + "members_with_roles": Json(members_with_roles), + } + if organization_id is not None: + data["organization_id"] = organization_id + await prisma.db.litellm_teamtable.create(data=data) + return team_id + + +@pytest_asyncio.fixture +async def scratch(prisma): + handle = Scratch(prefix=f"{SCRATCH_PREFIX}{uuid.uuid4().hex[:12]}") + try: + yield handle + finally: + # Children before parents to avoid FK violations. + await prisma.db.litellm_verificationtoken.delete_many( + where={ + "OR": [ + {"key_alias": {"startswith": handle.prefix}}, + {"key_name": {"startswith": handle.prefix}}, + ] + } + ) + await prisma.db.litellm_teammembership.delete_many( + where={"team_id": {"startswith": handle.prefix}} + ) + await prisma.db.litellm_organizationmembership.delete_many( + where={"user_id": {"startswith": handle.prefix}} + ) + await prisma.db.litellm_teamtable.delete_many( + where={"team_id": {"startswith": handle.prefix}} + ) + await prisma.db.litellm_usertable.delete_many( + where={"user_id": {"startswith": handle.prefix}} + ) + await prisma.db.litellm_budgettable.delete_many( + where={"budget_id": {"startswith": handle.prefix}} + ) + # /team/member_add writes LiteLLM_UserTable.teams; the available-team + # self-join writes it on a world actor whose row must survive. Strip + # dangling scratch-team refs so the read-world stays immutable. + polluted = await prisma.db.litellm_usertable.find_many( + where={"teams": {"isEmpty": False}} + ) + for user in polluted: + cleaned = [t for t in user.teams if not t.startswith(handle.prefix)] + if cleaned != list(user.teams): + await prisma.db.litellm_usertable.update( + where={"user_id": user.user_id}, + data={"teams": {"set": cleaned}}, + ) diff --git a/tests/proxy_behavior/management/test_key_delete.py b/tests/proxy_behavior/management/test_key_delete.py new file mode 100644 index 00000000000..05844ac0031 --- /dev/null +++ b/tests/proxy_behavior/management/test_key_delete.py @@ -0,0 +1,101 @@ +import pytest + +from litellm.proxy.utils import hash_token + +from .actors import TEAM_ALPHA, TEAM_BETA, Actor +from .conftest import create_scratch_key + +pytestmark = pytest.mark.asyncio(loop_scope="session") + + +# Same-team peers can READ each other's keys (see test_key_info) but cannot +# DELETE them — delete is stricter than read. +_SCENARIOS = [ + ("self/proxy_admin", Actor.PROXY_ADMIN, "self", 200), + ("self/org_admin", Actor.ORG_ADMIN, "self", 401), + ("self/team_admin", Actor.TEAM_ADMIN, "self", 200), + ("self/internal_user", Actor.INTERNAL_USER, "self", 200), + ("self/owner", Actor.OWNER, "self", 200), + ("self/unrelated_same_org", Actor.UNRELATED_SAME_ORG, "self", 200), + ("self/cross_org_user", Actor.CROSS_ORG_USER, "self", 200), + ("self/service_account", Actor.SERVICE_ACCOUNT, "self", 200), + ("owner_target/proxy_admin", Actor.PROXY_ADMIN, "owner", 200), + ("owner_target/org_admin", Actor.ORG_ADMIN, "owner", 401), + ("owner_target/team_admin", Actor.TEAM_ADMIN, "owner", 200), + ("owner_target/internal_user", Actor.INTERNAL_USER, "owner", 403), + ("owner_target/unrelated_same_org", Actor.UNRELATED_SAME_ORG, "owner", 403), + ("owner_target/cross_org_user", Actor.CROSS_ORG_USER, "owner", 403), + ("owner_target/service_account", Actor.SERVICE_ACCOUNT, "owner", 403), + ("cross_org_target/proxy_admin", Actor.PROXY_ADMIN, "cross_org", 200), + ("cross_org_target/org_admin", Actor.ORG_ADMIN, "cross_org", 401), + ("cross_org_target/team_admin", Actor.TEAM_ADMIN, "cross_org", 403), + ("cross_org_target/owner", Actor.OWNER, "cross_org", 403), + ("cross_org_target/cross_org_user", Actor.CROSS_ORG_USER, "cross_org", 200), + ("cross_org_target/service_account", Actor.SERVICE_ACCOUNT, "cross_org", 403), +] + + +@pytest.mark.parametrize( + "actor,target_shape,expected_status", + [(a, t, s) for (_id, a, t, s) in _SCENARIOS], + ids=[s[0] for s in _SCENARIOS], +) +async def test_key_delete_authz_matrix( + actor: Actor, + target_shape: str, + expected_status: int, + proxy_client, + prisma, + scratch, + world, +): + caller = world.keys[actor] + seeder = world.keys[Actor.PROXY_ADMIN].cleartext + + if target_shape == "self": + target_cleartext = await create_scratch_key( + proxy_client, seeder, scratch.prefix, user_id=caller.user_id + ) + elif target_shape == "owner": + target_cleartext = await create_scratch_key( + proxy_client, + seeder, + scratch.prefix, + user_id=world.keys[Actor.OWNER].user_id, + team_id=TEAM_ALPHA, + ) + elif target_shape == "cross_org": + target_cleartext = await create_scratch_key( + proxy_client, + seeder, + scratch.prefix, + user_id=world.keys[Actor.CROSS_ORG_USER].user_id, + team_id=TEAM_BETA, + ) + else: + pytest.fail(f"unknown target_shape={target_shape}") + + target_hashed = hash_token(target_cleartext) + + resp = await proxy_client.post( + "/key/delete", + headers={"Authorization": f"Bearer {caller.cleartext}"}, + json={"keys": [target_cleartext]}, + ) + assert ( + resp.status_code == expected_status + ), f"{actor.value} {target_shape}: {resp.status_code} {resp.text}" + + row = await prisma.db.litellm_verificationtoken.find_unique( + where={"token": target_hashed} + ) + auth_check = await proxy_client.get( + "/key/info", headers={"Authorization": f"Bearer {target_cleartext}"} + ) + + if expected_status == 200: + # Hard- or soft-delete both produce a 401 on subsequent auth. + assert auth_check.status_code == 401 + else: + assert row is not None, f"{actor.value}: denied but row vanished" + assert auth_check.status_code == 200 diff --git a/tests/proxy_behavior/management/test_key_generate.py b/tests/proxy_behavior/management/test_key_generate.py new file mode 100644 index 00000000000..851de33d3ff --- /dev/null +++ b/tests/proxy_behavior/management/test_key_generate.py @@ -0,0 +1,70 @@ +from typing import Any, Dict + +import pytest + +from .actors import TEAM_ALPHA, TEAM_BETA, Actor + +pytestmark = pytest.mark.asyncio(loop_scope="session") + + +# (id, actor, body_extras, expected_status). Status codes pinned to observed +# handler behavior — heterogeneous (200, 400, 401) because the handler routes +# denials through three different gates (role gate, user_id mismatch, team +# member permission). +_SCENARIOS = [ + ("self/proxy_admin", Actor.PROXY_ADMIN, {}, 200), + ("self/org_admin", Actor.ORG_ADMIN, {}, 401), + ("self/team_admin", Actor.TEAM_ADMIN, {}, 200), + ("self/internal_user", Actor.INTERNAL_USER, {}, 200), + ("self/owner", Actor.OWNER, {}, 200), + ("self/unrelated_same_org", Actor.UNRELATED_SAME_ORG, {}, 200), + ("self/cross_org_user", Actor.CROSS_ORG_USER, {}, 200), + ("self/service_account", Actor.SERVICE_ACCOUNT, {}, 200), + ("team_alpha/proxy_admin", Actor.PROXY_ADMIN, {"team_id": TEAM_ALPHA}, 200), + ("team_alpha/org_admin", Actor.ORG_ADMIN, {"team_id": TEAM_ALPHA}, 401), + ("team_alpha/team_admin", Actor.TEAM_ADMIN, {"team_id": TEAM_ALPHA}, 200), + ("team_alpha/internal_user", Actor.INTERNAL_USER, {"team_id": TEAM_ALPHA}, 401), + ("team_alpha/cross_org_user", Actor.CROSS_ORG_USER, {"team_id": TEAM_ALPHA}, 400), + ("team_beta/proxy_admin", Actor.PROXY_ADMIN, {"team_id": TEAM_BETA}, 200), + ("team_beta/org_admin", Actor.ORG_ADMIN, {"team_id": TEAM_BETA}, 401), + ("team_beta/team_admin", Actor.TEAM_ADMIN, {"team_id": TEAM_BETA}, 400), + ("team_beta/internal_user", Actor.INTERNAL_USER, {"team_id": TEAM_BETA}, 400), + ("team_beta/cross_org_user", Actor.CROSS_ORG_USER, {"team_id": TEAM_BETA}, 401), +] + + +@pytest.mark.parametrize( + "actor,body_extras,expected_status", + [(actor, body, expected) for (_id, actor, body, expected) in _SCENARIOS], + ids=[s[0] for s in _SCENARIOS], +) +async def test_key_generate_authz_matrix( + actor: Actor, + body_extras: Dict[str, Any], + expected_status: int, + proxy_client, + prisma, + scratch, + world, +): + seeded = world.keys[actor] + body: Dict[str, Any] = {"key_alias": scratch.prefix, **body_extras} + + resp = await proxy_client.post( + "/key/generate", + headers={"Authorization": f"Bearer {seeded.cleartext}"}, + json=body, + ) + assert ( + resp.status_code == expected_status + ), f"{actor.value} {body!r} → {resp.status_code}: {resp.text}" + + rows = await prisma.db.litellm_verificationtoken.find_many( + where={"key_alias": scratch.prefix} + ) + if expected_status == 200: + cleartext = resp.json()["key"] + assert cleartext.startswith("sk-") + assert len(rows) == 1 + else: + assert rows == [], f"{actor.value}: denied but row leaked" diff --git a/tests/proxy_behavior/management/test_key_info.py b/tests/proxy_behavior/management/test_key_info.py new file mode 100644 index 00000000000..ddcef9fd27b --- /dev/null +++ b/tests/proxy_behavior/management/test_key_info.py @@ -0,0 +1,74 @@ +import pytest + +from .actors import Actor + +pytestmark = pytest.mark.asyncio(loop_scope="session") + + +# (id, actor, target_actor, expected_status). Targets are 3 fixed seeded keys +# representing the canonical relations: own, OWNER (same org_a/team_alpha), +# and CROSS_ORG_USER (org_b/team_beta). +# +# Notable pinned behaviors (intentionally surfaced, not endorsed): +# - ORG_ADMIN 403s on individual key info even within its own org — +# visibility is "your own keys" + "your team's keys", not "your org's keys". +# - Same-team peers (internal_user, unrelated_same_org, service_account) DO +# see each other's keys. +_SCENARIOS = [ + ("own/proxy_admin", Actor.PROXY_ADMIN, Actor.PROXY_ADMIN, 200), + ("own/org_admin", Actor.ORG_ADMIN, Actor.ORG_ADMIN, 200), + ("own/team_admin", Actor.TEAM_ADMIN, Actor.TEAM_ADMIN, 200), + ("own/internal_user", Actor.INTERNAL_USER, Actor.INTERNAL_USER, 200), + ("own/owner", Actor.OWNER, Actor.OWNER, 200), + ("own/unrelated_same_org", Actor.UNRELATED_SAME_ORG, Actor.UNRELATED_SAME_ORG, 200), + ("own/cross_org_user", Actor.CROSS_ORG_USER, Actor.CROSS_ORG_USER, 200), + ("own/service_account", Actor.SERVICE_ACCOUNT, Actor.SERVICE_ACCOUNT, 200), + ("owner_key/proxy_admin", Actor.PROXY_ADMIN, Actor.OWNER, 200), + ("owner_key/org_admin", Actor.ORG_ADMIN, Actor.OWNER, 403), + ("owner_key/team_admin", Actor.TEAM_ADMIN, Actor.OWNER, 200), + ("owner_key/internal_user", Actor.INTERNAL_USER, Actor.OWNER, 200), + ("owner_key/owner", Actor.OWNER, Actor.OWNER, 200), + ("owner_key/unrelated_same_org", Actor.UNRELATED_SAME_ORG, Actor.OWNER, 200), + ("owner_key/cross_org_user", Actor.CROSS_ORG_USER, Actor.OWNER, 403), + ("owner_key/service_account", Actor.SERVICE_ACCOUNT, Actor.OWNER, 200), + ("cross_org/proxy_admin", Actor.PROXY_ADMIN, Actor.CROSS_ORG_USER, 200), + ("cross_org/org_admin", Actor.ORG_ADMIN, Actor.CROSS_ORG_USER, 403), + ("cross_org/team_admin", Actor.TEAM_ADMIN, Actor.CROSS_ORG_USER, 403), + ("cross_org/internal_user", Actor.INTERNAL_USER, Actor.CROSS_ORG_USER, 403), + ("cross_org/owner", Actor.OWNER, Actor.CROSS_ORG_USER, 403), + ( + "cross_org/unrelated_same_org", + Actor.UNRELATED_SAME_ORG, + Actor.CROSS_ORG_USER, + 403, + ), + ("cross_org/cross_org_user", Actor.CROSS_ORG_USER, Actor.CROSS_ORG_USER, 200), + ("cross_org/service_account", Actor.SERVICE_ACCOUNT, Actor.CROSS_ORG_USER, 403), +] + + +@pytest.mark.parametrize( + "actor,target_actor,expected_status", + [(a, t, s) for (_id, a, t, s) in _SCENARIOS], + ids=[s[0] for s in _SCENARIOS], +) +async def test_key_info_authz_matrix( + actor: Actor, target_actor: Actor, expected_status: int, proxy_client, world +): + caller = world.keys[actor] + target = world.keys[target_actor] + + resp = await proxy_client.get( + f"/key/info?key={target.cleartext}", + headers={"Authorization": f"Bearer {caller.cleartext}"}, + ) + assert ( + resp.status_code == expected_status + ), f"{actor.value} → {target_actor.value}: {resp.status_code} {resp.text}" + + if expected_status == 200: + body = resp.json() + # The handler echoes back whatever ?key was passed (cleartext here), + # so accept either form — info.user_id is the canonical identity check. + assert body.get("key") in (target.cleartext, target.hashed) + assert body["info"].get("user_id") == target.user_id diff --git a/tests/proxy_behavior/management/test_key_list.py b/tests/proxy_behavior/management/test_key_list.py new file mode 100644 index 00000000000..bda8788c9a7 --- /dev/null +++ b/tests/proxy_behavior/management/test_key_list.py @@ -0,0 +1,63 @@ +from typing import FrozenSet + +import pytest + +from .actors import Actor + +pytestmark = pytest.mark.asyncio(loop_scope="session") + + +# Pinned default visibility for /key/list (no filter params): each actor's +# expected set of seeded actor keys. +_VISIBILITY = { + Actor.PROXY_ADMIN: frozenset(Actor), + Actor.ORG_ADMIN: frozenset({Actor.ORG_ADMIN}), + Actor.TEAM_ADMIN: frozenset({Actor.TEAM_ADMIN}), + Actor.INTERNAL_USER: frozenset({Actor.INTERNAL_USER}), + Actor.OWNER: frozenset({Actor.OWNER}), + Actor.UNRELATED_SAME_ORG: frozenset({Actor.UNRELATED_SAME_ORG}), + Actor.CROSS_ORG_USER: frozenset({Actor.CROSS_ORG_USER}), + Actor.SERVICE_ACCOUNT: frozenset({Actor.SERVICE_ACCOUNT}), +} + + +async def _all_visible_hashes(proxy_client, caller_cleartext) -> set: + """Walk every /key/list page — size is capped at 100 by the endpoint, so a + single request can truncate PROXY_ADMIN's view on a non-fresh DB.""" + hashes: set = set() + page = 1 + while True: + resp = await proxy_client.get( + f"/key/list?page={page}&size=100", + headers={"Authorization": f"Bearer {caller_cleartext}"}, + ) + assert resp.status_code == 200, resp.text + body = resp.json() + for entry in body.get("keys", []): + tok = entry.get("token") if isinstance(entry, dict) else entry + if tok: + hashes.add(tok) + if page >= (body.get("total_pages") or 1): + return hashes + page += 1 + + +@pytest.mark.parametrize( + "actor,expected_visible", + list(_VISIBILITY.items()), + ids=[a.value for a in _VISIBILITY], +) +async def test_key_list_visibility( + actor: Actor, expected_visible: FrozenSet[Actor], proxy_client, world +): + caller = world.keys[actor] + hashed_to_actor = {world.keys[a].hashed: a for a in Actor} + + returned_hashes = await _all_visible_hashes(proxy_client, caller.cleartext) + visible_seeded = { + hashed_to_actor[h] for h in returned_hashes if h in hashed_to_actor + } + assert visible_seeded == set(expected_visible), ( + f"{actor.value}: expected {sorted(a.value for a in expected_visible)}, " + f"got {sorted(a.value for a in visible_seeded)}" + ) diff --git a/tests/proxy_behavior/management/test_key_regenerate.py b/tests/proxy_behavior/management/test_key_regenerate.py new file mode 100644 index 00000000000..a3289144eef --- /dev/null +++ b/tests/proxy_behavior/management/test_key_regenerate.py @@ -0,0 +1,117 @@ +import pytest + +from .actors import TEAM_ALPHA, TEAM_BETA, Actor +from .conftest import create_scratch_key + +pytestmark = pytest.mark.asyncio(loop_scope="session") + + +# Most denials route through team_member_permission (401), unlike /key/update +# which goes through user_id-mismatch (403). The matrix surfaces that +# divergence between the two endpoints. +_SCENARIOS = [ + ("self/proxy_admin", Actor.PROXY_ADMIN, "self", 200), + ("self/org_admin", Actor.ORG_ADMIN, "self", 401), + ("self/team_admin", Actor.TEAM_ADMIN, "self", 200), + ("self/internal_user", Actor.INTERNAL_USER, "self", 200), + ("self/owner", Actor.OWNER, "self", 200), + ("self/unrelated_same_org", Actor.UNRELATED_SAME_ORG, "self", 200), + ("self/cross_org_user", Actor.CROSS_ORG_USER, "self", 200), + ("self/service_account", Actor.SERVICE_ACCOUNT, "self", 200), + ("owner_target/proxy_admin", Actor.PROXY_ADMIN, "owner", 200), + ("owner_target/org_admin", Actor.ORG_ADMIN, "owner", 401), + ("owner_target/team_admin", Actor.TEAM_ADMIN, "owner", 200), + ("owner_target/internal_user", Actor.INTERNAL_USER, "owner", 401), + ("owner_target/unrelated_same_org", Actor.UNRELATED_SAME_ORG, "owner", 401), + ("owner_target/cross_org_user", Actor.CROSS_ORG_USER, "owner", 401), + ("owner_target/service_account", Actor.SERVICE_ACCOUNT, "owner", 401), + ("cross_org_target/proxy_admin", Actor.PROXY_ADMIN, "cross_org", 200), + ("cross_org_target/org_admin", Actor.ORG_ADMIN, "cross_org", 401), + ("cross_org_target/team_admin", Actor.TEAM_ADMIN, "cross_org", 401), + ("cross_org_target/owner", Actor.OWNER, "cross_org", 401), + ("cross_org_target/cross_org_user", Actor.CROSS_ORG_USER, "cross_org", 401), + ("cross_org_target/service_account", Actor.SERVICE_ACCOUNT, "cross_org", 401), +] + + +async def _info(proxy_client, cleartext: str): + return await proxy_client.get( + "/key/info", headers={"Authorization": f"Bearer {cleartext}"} + ) + + +@pytest.mark.parametrize( + "actor,target_shape,expected_status", + [(a, t, s) for (_id, a, t, s) in _SCENARIOS], + ids=[s[0] for s in _SCENARIOS], +) +async def test_key_regenerate_authz_matrix( + actor: Actor, + target_shape: str, + expected_status: int, + proxy_client, + scratch, + world, +): + caller = world.keys[actor] + seeder = world.keys[Actor.PROXY_ADMIN].cleartext + + if target_shape == "self": + target_cleartext = await create_scratch_key( + proxy_client, seeder, scratch.prefix, user_id=caller.user_id + ) + elif target_shape == "owner": + target_cleartext = await create_scratch_key( + proxy_client, + seeder, + scratch.prefix, + user_id=world.keys[Actor.OWNER].user_id, + team_id=TEAM_ALPHA, + ) + elif target_shape == "cross_org": + target_cleartext = await create_scratch_key( + proxy_client, + seeder, + scratch.prefix, + user_id=world.keys[Actor.CROSS_ORG_USER].user_id, + team_id=TEAM_BETA, + ) + else: + pytest.fail(f"unknown target_shape={target_shape}") + + resp = await proxy_client.post( + "/key/regenerate", + headers={"Authorization": f"Bearer {caller.cleartext}"}, + json={"key": target_cleartext}, + ) + assert ( + resp.status_code == expected_status + ), f"{actor.value} {target_shape}: {resp.status_code} {resp.text}" + + if expected_status == 200: + new_cleartext = resp.json()["key"] + assert new_cleartext.startswith("sk-") and new_cleartext != target_cleartext + assert (await _info(proxy_client, target_cleartext)).status_code == 401 + assert (await _info(proxy_client, new_cleartext)).status_code == 200 + else: + # Denied: rotation must not have leaked — old cleartext still works. + assert (await _info(proxy_client, target_cleartext)).status_code == 200 + + +async def test_key_path_regenerate_smoke(proxy_client, scratch, world): + """Pins that POST /key/{key:path}/regenerate shares the same handler.""" + caller = world.keys[Actor.PROXY_ADMIN] + target_cleartext = await create_scratch_key( + proxy_client, caller.cleartext, scratch.prefix, user_id=caller.user_id + ) + + resp = await proxy_client.post( + f"/key/{target_cleartext}/regenerate", + headers={"Authorization": f"Bearer {caller.cleartext}"}, + json={}, + ) + assert resp.status_code == 200, resp.text + new_cleartext = resp.json()["key"] + assert new_cleartext.startswith("sk-") and new_cleartext != target_cleartext + assert (await _info(proxy_client, target_cleartext)).status_code == 401 + assert (await _info(proxy_client, new_cleartext)).status_code == 200 diff --git a/tests/proxy_behavior/management/test_key_update.py b/tests/proxy_behavior/management/test_key_update.py new file mode 100644 index 00000000000..36ddefa5750 --- /dev/null +++ b/tests/proxy_behavior/management/test_key_update.py @@ -0,0 +1,100 @@ +import pytest + +from litellm.proxy.utils import hash_token + +from .actors import TEAM_ALPHA, TEAM_BETA, Actor +from .conftest import create_scratch_key + +pytestmark = pytest.mark.asyncio(loop_scope="session") + + +# (id, actor, target_shape, expected_status). Pinned against current gating: +# proxy_admin bypasses; org_admin is blocked by an early role gate (401); +# every other (INTERNAL_USER-roled) actor hits user_id-mismatch 403, no-team- +# admin 403, or team_member_permission 401 depending on target / membership. +_SCENARIOS = [ + ("self/proxy_admin", Actor.PROXY_ADMIN, "self", 200), + ("self/org_admin", Actor.ORG_ADMIN, "self", 401), + ("self/team_admin", Actor.TEAM_ADMIN, "self", 403), + ("self/internal_user", Actor.INTERNAL_USER, "self", 403), + ("self/owner", Actor.OWNER, "self", 403), + ("self/unrelated_same_org", Actor.UNRELATED_SAME_ORG, "self", 403), + ("self/cross_org_user", Actor.CROSS_ORG_USER, "self", 403), + ("self/service_account", Actor.SERVICE_ACCOUNT, "self", 403), + ("owner_target/proxy_admin", Actor.PROXY_ADMIN, "owner", 200), + ("owner_target/org_admin", Actor.ORG_ADMIN, "owner", 401), + ("owner_target/team_admin", Actor.TEAM_ADMIN, "owner", 403), + ("owner_target/internal_user", Actor.INTERNAL_USER, "owner", 403), + ("owner_target/unrelated_same_org", Actor.UNRELATED_SAME_ORG, "owner", 403), + ("owner_target/cross_org_user", Actor.CROSS_ORG_USER, "owner", 403), + ("owner_target/service_account", Actor.SERVICE_ACCOUNT, "owner", 403), + ("cross_org_target/proxy_admin", Actor.PROXY_ADMIN, "cross_org", 200), + ("cross_org_target/org_admin", Actor.ORG_ADMIN, "cross_org", 401), + ("cross_org_target/team_admin", Actor.TEAM_ADMIN, "cross_org", 403), + ("cross_org_target/owner", Actor.OWNER, "cross_org", 403), + ("cross_org_target/cross_org_user", Actor.CROSS_ORG_USER, "cross_org", 401), + ("cross_org_target/service_account", Actor.SERVICE_ACCOUNT, "cross_org", 403), +] + +MARKER_MODEL = "behavior-pin-update-marker-model" + + +@pytest.mark.parametrize( + "actor,target_shape,expected_status", + [(a, t, s) for (_id, a, t, s) in _SCENARIOS], + ids=[s[0] for s in _SCENARIOS], +) +async def test_key_update_authz_matrix( + actor: Actor, + target_shape: str, + expected_status: int, + proxy_client, + prisma, + scratch, + world, +): + caller = world.keys[actor] + seeder = world.keys[Actor.PROXY_ADMIN].cleartext + + if target_shape == "self": + target_cleartext = await create_scratch_key( + proxy_client, seeder, scratch.prefix, user_id=caller.user_id + ) + elif target_shape == "owner": + target_cleartext = await create_scratch_key( + proxy_client, + seeder, + scratch.prefix, + user_id=world.keys[Actor.OWNER].user_id, + team_id=TEAM_ALPHA, + ) + elif target_shape == "cross_org": + target_cleartext = await create_scratch_key( + proxy_client, + seeder, + scratch.prefix, + user_id=world.keys[Actor.CROSS_ORG_USER].user_id, + team_id=TEAM_BETA, + ) + else: + pytest.fail(f"unknown target_shape={target_shape}") + + target_hashed = hash_token(target_cleartext) + + resp = await proxy_client.post( + "/key/update", + headers={"Authorization": f"Bearer {caller.cleartext}"}, + json={"key": target_cleartext, "models": [MARKER_MODEL]}, + ) + assert ( + resp.status_code == expected_status + ), f"{actor.value} {target_shape}: {resp.status_code} {resp.text}" + + row = await prisma.db.litellm_verificationtoken.find_unique( + where={"token": target_hashed} + ) + assert row is not None + if expected_status == 200: + assert row.models == [MARKER_MODEL] + else: + assert row.models != [MARKER_MODEL], "denied but row mutated" diff --git a/tests/proxy_behavior/management/test_no_management_imports.py b/tests/proxy_behavior/management/test_no_management_imports.py new file mode 100644 index 00000000000..f8c52a1c37e --- /dev/null +++ b/tests/proxy_behavior/management/test_no_management_imports.py @@ -0,0 +1,46 @@ +import pathlib +import re + +REPO_ROOT = pathlib.Path(__file__).resolve().parents[3] +BEHAVIOR_DIR = REPO_ROOT / "tests" / "proxy_behavior" + +FORBIDDEN_IMPORT = re.compile(r"^\s*from\s+litellm\.proxy\.management_endpoints\b") +FORBIDDEN_AUTH_MOCK = re.compile( + r"(?:mock\.[A-Za-z_]+|patch[a-z_]*)\([^)]*user_api_key_auth" +) +# This file is the only place the forbidden patterns appear as regex source; +# exclude it so it can describe what it forbids. +SELF = pathlib.Path(__file__).resolve() + + +def _iter_py_files(): + for path in BEHAVIOR_DIR.rglob("*.py"): + if path.resolve() != SELF: + yield path + + +def _scan(pattern): + violations = [] + for path in _iter_py_files(): + for lineno, line in enumerate(path.read_text().splitlines(), start=1): + if pattern.search(line): + violations.append( + f"{path.relative_to(REPO_ROOT)}:{lineno}: {line.strip()}" + ) + return violations + + +def test_no_management_endpoint_imports(): + violations = _scan(FORBIDDEN_IMPORT) + assert not violations, ( + "tests/proxy_behavior/ must not import from litellm.proxy.management_endpoints. " + "Violations:\n " + "\n ".join(violations) + ) + + +def test_no_user_api_key_auth_mocking(): + violations = _scan(FORBIDDEN_AUTH_MOCK) + assert not violations, ( + "tests/proxy_behavior/ must not mock user_api_key_auth. " + "Violations:\n " + "\n ".join(violations) + ) diff --git a/tests/proxy_behavior/management/test_scratch_teardown.py b/tests/proxy_behavior/management/test_scratch_teardown.py new file mode 100644 index 00000000000..689c60fc78a --- /dev/null +++ b/tests/proxy_behavior/management/test_scratch_teardown.py @@ -0,0 +1,31 @@ +import pytest + +from .conftest import MASTER_KEY, SCRATCH_PREFIX + +pytestmark = pytest.mark.asyncio(loop_scope="session") + + +# The two tests run in file order: _a writes a scratch-tagged key and asserts +# it lands; _b runs after _a's fixture teardown and asserts no scratch row +# survived. A leak in either direction fails _b on the next collection. + + +async def test_a_scratch_key_lands_in_db(proxy_client, prisma, scratch): + resp = await proxy_client.post( + "/key/generate", + headers={"Authorization": f"Bearer {MASTER_KEY}"}, + json={"key_alias": scratch.prefix}, + ) + assert resp.status_code == 200, resp.text + + rows = await prisma.db.litellm_verificationtoken.find_many( + where={"key_alias": scratch.prefix} + ) + assert len(rows) == 1 + + +async def test_b_scratch_namespace_is_clean(prisma): + rows = await prisma.db.litellm_verificationtoken.find_many( + where={"key_alias": {"startswith": SCRATCH_PREFIX}} + ) + assert rows == [] diff --git a/tests/proxy_behavior/management/test_smoke.py b/tests/proxy_behavior/management/test_smoke.py new file mode 100644 index 00000000000..4e90986ad9f --- /dev/null +++ b/tests/proxy_behavior/management/test_smoke.py @@ -0,0 +1,28 @@ +import pytest + +from .conftest import MASTER_KEY + +pytestmark = pytest.mark.asyncio(loop_scope="session") + + +async def test_liveliness(proxy_client): + resp = await proxy_client.get("/health/liveliness") + assert resp.status_code == 200 + + +async def test_key_generate_lands_in_db(proxy_client, prisma, scratch): + from litellm.proxy.utils import hash_token + + resp = await proxy_client.post( + "/key/generate", + headers={"Authorization": f"Bearer {MASTER_KEY}"}, + json={"key_alias": scratch.prefix}, + ) + assert resp.status_code == 200, resp.text + cleartext = resp.json()["key"] + assert cleartext.startswith("sk-") + + hashed = hash_token(cleartext) + row = await prisma.db.litellm_verificationtoken.find_unique(where={"token": hashed}) + assert row is not None + assert row.token == hashed != cleartext diff --git a/tests/proxy_behavior/management/test_team_info.py b/tests/proxy_behavior/management/test_team_info.py new file mode 100644 index 00000000000..51809942113 --- /dev/null +++ b/tests/proxy_behavior/management/test_team_info.py @@ -0,0 +1,70 @@ +import pytest + +from .actors import Actor + +pytestmark = pytest.mark.asyncio(loop_scope="session") + + +# GET /team/info — actor x team-target authz matrix, pinned against +# validate_membership(): a team is readable by a proxy admin, a key whose +# own team_id matches, a listed member, or an org admin of the team's org; +# everything else is 403. TEAM_GAMMA has no members, so only PROXY_ADMIN +# and ORG_A's org admin can read it. +_SCENARIOS = [ + ("alpha/proxy_admin", Actor.PROXY_ADMIN, "alpha", 200), + ("alpha/org_admin", Actor.ORG_ADMIN, "alpha", 200), + ("alpha/team_admin", Actor.TEAM_ADMIN, "alpha", 200), + ("alpha/internal_user", Actor.INTERNAL_USER, "alpha", 200), + ("alpha/owner", Actor.OWNER, "alpha", 200), + ("alpha/unrelated_same_org", Actor.UNRELATED_SAME_ORG, "alpha", 200), + ("alpha/cross_org_user", Actor.CROSS_ORG_USER, "alpha", 403), + ("alpha/service_account", Actor.SERVICE_ACCOUNT, "alpha", 200), + ("alpha/org_b_admin", Actor.ORG_B_ADMIN, "alpha", 403), + ("gamma/proxy_admin", Actor.PROXY_ADMIN, "gamma", 200), + ("gamma/org_admin", Actor.ORG_ADMIN, "gamma", 200), + ("gamma/team_admin", Actor.TEAM_ADMIN, "gamma", 403), + ("gamma/internal_user", Actor.INTERNAL_USER, "gamma", 403), + ("gamma/owner", Actor.OWNER, "gamma", 403), + ("gamma/unrelated_same_org", Actor.UNRELATED_SAME_ORG, "gamma", 403), + ("gamma/cross_org_user", Actor.CROSS_ORG_USER, "gamma", 403), + ("gamma/service_account", Actor.SERVICE_ACCOUNT, "gamma", 403), + ("gamma/org_b_admin", Actor.ORG_B_ADMIN, "gamma", 403), + ("beta/proxy_admin", Actor.PROXY_ADMIN, "beta", 200), + ("beta/org_admin", Actor.ORG_ADMIN, "beta", 403), + ("beta/team_admin", Actor.TEAM_ADMIN, "beta", 403), + ("beta/internal_user", Actor.INTERNAL_USER, "beta", 403), + ("beta/owner", Actor.OWNER, "beta", 403), + ("beta/unrelated_same_org", Actor.UNRELATED_SAME_ORG, "beta", 403), + ("beta/cross_org_user", Actor.CROSS_ORG_USER, "beta", 200), + ("beta/service_account", Actor.SERVICE_ACCOUNT, "beta", 403), + ("beta/org_b_admin", Actor.ORG_B_ADMIN, "beta", 200), +] + + +@pytest.mark.parametrize( + "actor,target,expected_status", + [(a, t, s) for (_id, a, t, s) in _SCENARIOS], + ids=[s[0] for s in _SCENARIOS], +) +async def test_team_info_authz_matrix( + actor: Actor, target: str, expected_status: int, proxy_client, world +): + caller = world.keys[actor] + target_team_id = { + "alpha": world.team_alpha_id, + "gamma": world.team_gamma_id, + "beta": world.team_beta_id, + }[target] + + resp = await proxy_client.get( + f"/team/info?team_id={target_team_id}", + headers={"Authorization": f"Bearer {caller.cleartext}"}, + ) + assert ( + resp.status_code == expected_status + ), f"{actor.value} -> {target}: {resp.status_code} {resp.text}" + + if expected_status == 200: + body = resp.json() + assert body["team_id"] == target_team_id + assert body["team_info"]["team_id"] == target_team_id diff --git a/tests/proxy_behavior/management/test_team_list.py b/tests/proxy_behavior/management/test_team_list.py new file mode 100644 index 00000000000..2bd106dd2d0 --- /dev/null +++ b/tests/proxy_behavior/management/test_team_list.py @@ -0,0 +1,105 @@ +from typing import FrozenSet, Optional + +import pytest + +from .actors import Actor + +pytestmark = pytest.mark.asyncio(loop_scope="session") + + +# The behavior DB may hold teams beyond the three seeded ones, so every +# assertion intersects the returned team_ids with the known seeded set. +def _seeded_visible(resp_json, world) -> set: + known = { + world.team_alpha_id: "alpha", + world.team_beta_id: "beta", + world.team_gamma_id: "gamma", + } + return { + known[entry["team_id"]] + for entry in resp_json + if isinstance(entry, dict) and entry.get("team_id") in known + } + + +# Family 1 — bare GET /team/list (no query params). _authorize_and_filter_teams +# authorizes only an admin view (proxy admin) or an org admin; everyone else +# is 401. An org admin sees every team in its org(s). +_BARE = [ + ("proxy_admin", Actor.PROXY_ADMIN, 200, {"alpha", "beta", "gamma"}), + ("org_admin", Actor.ORG_ADMIN, 200, {"alpha", "gamma"}), + ("team_admin", Actor.TEAM_ADMIN, 401, None), + ("internal_user", Actor.INTERNAL_USER, 401, None), + ("owner", Actor.OWNER, 401, None), + ("unrelated_same_org", Actor.UNRELATED_SAME_ORG, 401, None), + ("cross_org_user", Actor.CROSS_ORG_USER, 401, None), + ("service_account", Actor.SERVICE_ACCOUNT, 401, None), + ("org_b_admin", Actor.ORG_B_ADMIN, 200, {"beta"}), +] + + +@pytest.mark.parametrize( + "actor,expected_status,expected_visible", + [(a, s, v) for (_id, a, s, v) in _BARE], + ids=[s[0] for s in _BARE], +) +async def test_team_list_bare_authz( + actor: Actor, + expected_status: int, + expected_visible: Optional[set], + proxy_client, + world, +): + caller = world.keys[actor] + resp = await proxy_client.get( + "/team/list", + headers={"Authorization": f"Bearer {caller.cleartext}"}, + ) + assert ( + resp.status_code == expected_status + ), f"{actor.value}: {resp.status_code} {resp.text}" + + if expected_status == 200: + visible = _seeded_visible(resp.json(), world) + assert visible == expected_visible, ( + f"{actor.value}: expected {sorted(expected_visible)}, " + f"got {sorted(visible)}" + ) + + +# Family 2 — GET /team/list?user_id= ("own query"). Every +# actor may query its own teams (200); the result is exactly the teams it +# belongs to. A user_id filter scopes proxy/org admins to their own +# membership too — the broad admin view from family 1 does not carry over. +_OWN = { + Actor.PROXY_ADMIN: frozenset(), + Actor.ORG_ADMIN: frozenset(), + Actor.TEAM_ADMIN: frozenset({"alpha"}), + Actor.INTERNAL_USER: frozenset({"alpha"}), + Actor.OWNER: frozenset({"alpha"}), + Actor.UNRELATED_SAME_ORG: frozenset({"alpha"}), + Actor.CROSS_ORG_USER: frozenset({"beta"}), + Actor.SERVICE_ACCOUNT: frozenset({"alpha"}), + Actor.ORG_B_ADMIN: frozenset(), +} + + +@pytest.mark.parametrize( + "actor,expected_visible", + list(_OWN.items()), + ids=[a.value for a in _OWN], +) +async def test_team_list_own_query( + actor: Actor, expected_visible: FrozenSet[str], proxy_client, world +): + caller = world.keys[actor] + resp = await proxy_client.get( + f"/team/list?user_id={caller.user_id}", + headers={"Authorization": f"Bearer {caller.cleartext}"}, + ) + assert resp.status_code == 200, f"{actor.value}: {resp.status_code} {resp.text}" + + visible = _seeded_visible(resp.json(), world) + assert visible == set(expected_visible), ( + f"{actor.value}: expected {sorted(expected_visible)}, " f"got {sorted(visible)}" + ) diff --git a/tests/proxy_behavior/management/test_team_member_add.py b/tests/proxy_behavior/management/test_team_member_add.py new file mode 100644 index 00000000000..a0dc4a7ecaf --- /dev/null +++ b/tests/proxy_behavior/management/test_team_member_add.py @@ -0,0 +1,149 @@ +import litellm +import pytest + +from .actors import Actor +from .conftest import create_scratch_team + +pytestmark = pytest.mark.asyncio(loop_scope="session") + + +# POST /team/member_add — actor x team-shape matrix, pinned against +# _validate_team_member_add_permissions: PROXY_ADMIN, the team's team admin, +# or an org admin of the team's org may add members; everyone else is 403. +# Unlike /team/update there is no route gate in front, so the team-admin +# branch is reachable (TEAM_ADMIN, an internal_user, is allowed on its team). +_MATRIX = [ + ("alpha/proxy_admin", Actor.PROXY_ADMIN, "alpha", 200), + ("alpha/org_admin", Actor.ORG_ADMIN, "alpha", 200), + ("alpha/team_admin", Actor.TEAM_ADMIN, "alpha", 200), + ("alpha/internal_user", Actor.INTERNAL_USER, "alpha", 403), + ("alpha/owner", Actor.OWNER, "alpha", 403), + ("alpha/unrelated_same_org", Actor.UNRELATED_SAME_ORG, "alpha", 403), + ("alpha/cross_org_user", Actor.CROSS_ORG_USER, "alpha", 403), + ("alpha/service_account", Actor.SERVICE_ACCOUNT, "alpha", 403), + ("alpha/org_b_admin", Actor.ORG_B_ADMIN, "alpha", 403), + ("beta/proxy_admin", Actor.PROXY_ADMIN, "beta", 200), + ("beta/org_admin", Actor.ORG_ADMIN, "beta", 403), + ("beta/team_admin", Actor.TEAM_ADMIN, "beta", 403), + ("beta/internal_user", Actor.INTERNAL_USER, "beta", 403), + ("beta/owner", Actor.OWNER, "beta", 403), + ("beta/unrelated_same_org", Actor.UNRELATED_SAME_ORG, "beta", 403), + ("beta/cross_org_user", Actor.CROSS_ORG_USER, "beta", 403), + ("beta/service_account", Actor.SERVICE_ACCOUNT, "beta", 403), + ("beta/org_b_admin", Actor.ORG_B_ADMIN, "beta", 200), +] + + +async def _seed_target(prisma, world, shape: str, team_id: str) -> None: + if shape == "alpha": + await create_scratch_team( + prisma, + team_id, + organization_id=world.org_a_id, + admin_user_ids=[world.keys[Actor.TEAM_ADMIN].user_id], + ) + elif shape == "beta": + await create_scratch_team(prisma, team_id, organization_id=world.org_b_id) + else: # pragma: no cover - guard + pytest.fail(f"unknown shape={shape}") + + +def _member_ids(row) -> list: + return [m["user_id"] for m in (row.members_with_roles or [])] + + +@pytest.mark.parametrize( + "actor,shape,expected_status", + [(a, sh, s) for (_id, a, sh, s) in _MATRIX], + ids=[s[0] for s in _MATRIX], +) +async def test_team_member_add_authz_matrix( + actor: Actor, + shape: str, + expected_status: int, + proxy_client, + prisma, + scratch, + world, +): + await _seed_target(prisma, world, shape, scratch.prefix) + caller = world.keys[actor] + new_member_id = scratch.tag("newmember") + + resp = await proxy_client.post( + "/team/member_add", + headers={"Authorization": f"Bearer {caller.cleartext}"}, + json={ + "team_id": scratch.prefix, + "member": {"user_id": new_member_id, "role": "user"}, + }, + ) + assert ( + resp.status_code == expected_status + ), f"{actor.value} {shape}: {resp.status_code} {resp.text}" + + row = await prisma.db.litellm_teamtable.find_unique( + where={"team_id": scratch.prefix} + ) + assert row is not None + if expected_status == 200: + assert new_member_id in _member_ids(row) + else: + assert new_member_id not in _member_ids(row), "denied but member added" + + +# Available-team self-join: a non-admin caller may add ITSELF to a team listed +# in litellm.default_internal_user_params["available_teams"], but the bypass +# must not escalate to role=admin or inject another user. +_SELF_JOIN = [ + ("self_as_user", "self", "user", 200), + ("self_as_admin", "self", "admin", 403), + ("other_as_user", "other", "user", 403), +] + + +@pytest.mark.parametrize( + "who,role,expected_status", + [(w, r, s) for (_id, w, r, s) in _SELF_JOIN], + ids=[s[0] for s in _SELF_JOIN], +) +async def test_team_member_add_available_team_self_join( + who: str, + role: str, + expected_status: int, + proxy_client, + prisma, + scratch, + world, + monkeypatch, +): + # Org-less team with no admins: the INTERNAL_USER caller is neither team + # nor org admin, so it lands on the available-team branch. + await create_scratch_team(prisma, scratch.prefix) + monkeypatch.setattr( + litellm, "default_internal_user_params", {"available_teams": [scratch.prefix]} + ) + + caller = world.keys[Actor.INTERNAL_USER] + member_id = caller.user_id if who == "self" else world.keys[Actor.OWNER].user_id + + resp = await proxy_client.post( + "/team/member_add", + headers={"Authorization": f"Bearer {caller.cleartext}"}, + json={ + "team_id": scratch.prefix, + "member": {"user_id": member_id, "role": role}, + }, + ) + assert ( + resp.status_code == expected_status + ), f"{who}/{role}: {resp.status_code} {resp.text}" + + row = await prisma.db.litellm_teamtable.find_unique( + where={"team_id": scratch.prefix} + ) + assert row is not None + if expected_status == 200: + assert member_id in _member_ids(row) + else: + assert member_id not in _member_ids(row), "denied but member added" diff --git a/tests/proxy_behavior/management/test_team_member_delete.py b/tests/proxy_behavior/management/test_team_member_delete.py new file mode 100644 index 00000000000..43879d9fd16 --- /dev/null +++ b/tests/proxy_behavior/management/test_team_member_delete.py @@ -0,0 +1,92 @@ +import pytest + +from .actors import Actor +from .conftest import create_scratch_team + +pytestmark = pytest.mark.asyncio(loop_scope="session") + + +# POST /team/member_delete — actor x team-shape matrix. The scratch team is +# raw-seeded with a victim member already in it; PROXY_ADMIN, the team's team +# admin, or an org admin of the team's org may remove members; else 403. +_MATRIX = [ + ("alpha/proxy_admin", Actor.PROXY_ADMIN, "alpha", 200), + ("alpha/org_admin", Actor.ORG_ADMIN, "alpha", 200), + ("alpha/team_admin", Actor.TEAM_ADMIN, "alpha", 200), + ("alpha/internal_user", Actor.INTERNAL_USER, "alpha", 403), + ("alpha/owner", Actor.OWNER, "alpha", 403), + ("alpha/unrelated_same_org", Actor.UNRELATED_SAME_ORG, "alpha", 403), + ("alpha/cross_org_user", Actor.CROSS_ORG_USER, "alpha", 403), + ("alpha/service_account", Actor.SERVICE_ACCOUNT, "alpha", 403), + ("alpha/org_b_admin", Actor.ORG_B_ADMIN, "alpha", 403), + ("beta/proxy_admin", Actor.PROXY_ADMIN, "beta", 200), + ("beta/org_admin", Actor.ORG_ADMIN, "beta", 403), + ("beta/team_admin", Actor.TEAM_ADMIN, "beta", 403), + ("beta/internal_user", Actor.INTERNAL_USER, "beta", 403), + ("beta/owner", Actor.OWNER, "beta", 403), + ("beta/unrelated_same_org", Actor.UNRELATED_SAME_ORG, "beta", 403), + ("beta/cross_org_user", Actor.CROSS_ORG_USER, "beta", 403), + ("beta/service_account", Actor.SERVICE_ACCOUNT, "beta", 403), + ("beta/org_b_admin", Actor.ORG_B_ADMIN, "beta", 200), +] + + +async def _seed_target(prisma, world, shape: str, team_id: str, victim_id: str) -> None: + if shape == "alpha": + await create_scratch_team( + prisma, + team_id, + organization_id=world.org_a_id, + admin_user_ids=[world.keys[Actor.TEAM_ADMIN].user_id], + member_user_ids=[victim_id], + ) + elif shape == "beta": + await create_scratch_team( + prisma, + team_id, + organization_id=world.org_b_id, + member_user_ids=[victim_id], + ) + else: # pragma: no cover - guard + pytest.fail(f"unknown shape={shape}") + + +def _member_ids(row) -> list: + return [m["user_id"] for m in (row.members_with_roles or [])] + + +@pytest.mark.parametrize( + "actor,shape,expected_status", + [(a, sh, s) for (_id, a, sh, s) in _MATRIX], + ids=[s[0] for s in _MATRIX], +) +async def test_team_member_delete_authz_matrix( + actor: Actor, + shape: str, + expected_status: int, + proxy_client, + prisma, + scratch, + world, +): + victim_id = scratch.tag("victim") + await _seed_target(prisma, world, shape, scratch.prefix, victim_id) + caller = world.keys[actor] + + resp = await proxy_client.post( + "/team/member_delete", + headers={"Authorization": f"Bearer {caller.cleartext}"}, + json={"team_id": scratch.prefix, "user_id": victim_id}, + ) + assert ( + resp.status_code == expected_status + ), f"{actor.value} {shape}: {resp.status_code} {resp.text}" + + row = await prisma.db.litellm_teamtable.find_unique( + where={"team_id": scratch.prefix} + ) + assert row is not None + if expected_status == 200: + assert victim_id not in _member_ids(row) + else: + assert victim_id in _member_ids(row), "denied but member removed" diff --git a/tests/proxy_behavior/management/test_team_member_update.py b/tests/proxy_behavior/management/test_team_member_update.py new file mode 100644 index 00000000000..53b245bd1e9 --- /dev/null +++ b/tests/proxy_behavior/management/test_team_member_update.py @@ -0,0 +1,97 @@ +import pytest + +from .actors import Actor +from .conftest import create_scratch_team + +pytestmark = pytest.mark.asyncio(loop_scope="session") + + +# POST /team/member_update — actor x team-shape matrix. The scratch team is +# raw-seeded with a "user"-role member; each scenario tries to promote it to +# "admin". PROXY_ADMIN, the team's team admin, or an org admin of the team's +# org may update members; else 403. (The harness forces premium_user, so the +# promotion does not hit the admin-role premium gate.) +_MATRIX = [ + ("alpha/proxy_admin", Actor.PROXY_ADMIN, "alpha", 200), + ("alpha/org_admin", Actor.ORG_ADMIN, "alpha", 200), + ("alpha/team_admin", Actor.TEAM_ADMIN, "alpha", 200), + ("alpha/internal_user", Actor.INTERNAL_USER, "alpha", 403), + ("alpha/owner", Actor.OWNER, "alpha", 403), + ("alpha/unrelated_same_org", Actor.UNRELATED_SAME_ORG, "alpha", 403), + ("alpha/cross_org_user", Actor.CROSS_ORG_USER, "alpha", 403), + ("alpha/service_account", Actor.SERVICE_ACCOUNT, "alpha", 403), + ("alpha/org_b_admin", Actor.ORG_B_ADMIN, "alpha", 403), + ("beta/proxy_admin", Actor.PROXY_ADMIN, "beta", 200), + ("beta/org_admin", Actor.ORG_ADMIN, "beta", 403), + ("beta/team_admin", Actor.TEAM_ADMIN, "beta", 403), + ("beta/internal_user", Actor.INTERNAL_USER, "beta", 403), + ("beta/owner", Actor.OWNER, "beta", 403), + ("beta/unrelated_same_org", Actor.UNRELATED_SAME_ORG, "beta", 403), + ("beta/cross_org_user", Actor.CROSS_ORG_USER, "beta", 403), + ("beta/service_account", Actor.SERVICE_ACCOUNT, "beta", 403), + ("beta/org_b_admin", Actor.ORG_B_ADMIN, "beta", 200), +] + + +async def _seed_target(prisma, world, shape: str, team_id: str, member_id: str) -> None: + if shape == "alpha": + await create_scratch_team( + prisma, + team_id, + organization_id=world.org_a_id, + admin_user_ids=[world.keys[Actor.TEAM_ADMIN].user_id], + member_user_ids=[member_id], + ) + elif shape == "beta": + await create_scratch_team( + prisma, + team_id, + organization_id=world.org_b_id, + member_user_ids=[member_id], + ) + else: # pragma: no cover - guard + pytest.fail(f"unknown shape={shape}") + + +def _role_of(row, user_id: str): + for m in row.members_with_roles or []: + if m["user_id"] == user_id: + return m["role"] + return None + + +@pytest.mark.parametrize( + "actor,shape,expected_status", + [(a, sh, s) for (_id, a, sh, s) in _MATRIX], + ids=[s[0] for s in _MATRIX], +) +async def test_team_member_update_authz_matrix( + actor: Actor, + shape: str, + expected_status: int, + proxy_client, + prisma, + scratch, + world, +): + member_id = scratch.tag("member") + await _seed_target(prisma, world, shape, scratch.prefix, member_id) + caller = world.keys[actor] + + resp = await proxy_client.post( + "/team/member_update", + headers={"Authorization": f"Bearer {caller.cleartext}"}, + json={"team_id": scratch.prefix, "user_id": member_id, "role": "admin"}, + ) + assert ( + resp.status_code == expected_status + ), f"{actor.value} {shape}: {resp.status_code} {resp.text}" + + row = await prisma.db.litellm_teamtable.find_unique( + where={"team_id": scratch.prefix} + ) + assert row is not None + if expected_status == 200: + assert _role_of(row, member_id) == "admin" + else: + assert _role_of(row, member_id) == "user", "denied but role changed" diff --git a/tests/proxy_behavior/management/test_team_new.py b/tests/proxy_behavior/management/test_team_new.py new file mode 100644 index 00000000000..7b07f259641 --- /dev/null +++ b/tests/proxy_behavior/management/test_team_new.py @@ -0,0 +1,139 @@ +from typing import Any, Dict + +import pytest + +from .actors import Actor + +pytestmark = pytest.mark.asyncio(loop_scope="session") + + +# POST /team/new — actor x org-target matrix (org_target picks the request's +# organization_id: none / ORG_A / ORG_B). Pinned against the role gate, which +# 401s every denial: PROXY_ADMIN always passes; any other caller must name an +# organization_id AND be ORG_ADMIN of that org. +_SCENARIOS = [ + ("none/proxy_admin", Actor.PROXY_ADMIN, "none", 200), + ("none/org_admin", Actor.ORG_ADMIN, "none", 401), + ("none/team_admin", Actor.TEAM_ADMIN, "none", 401), + ("none/internal_user", Actor.INTERNAL_USER, "none", 401), + ("none/owner", Actor.OWNER, "none", 401), + ("none/unrelated_same_org", Actor.UNRELATED_SAME_ORG, "none", 401), + ("none/cross_org_user", Actor.CROSS_ORG_USER, "none", 401), + ("none/service_account", Actor.SERVICE_ACCOUNT, "none", 401), + ("none/org_b_admin", Actor.ORG_B_ADMIN, "none", 401), + ("org_a/proxy_admin", Actor.PROXY_ADMIN, "org_a", 200), + ("org_a/org_admin", Actor.ORG_ADMIN, "org_a", 200), + ("org_a/team_admin", Actor.TEAM_ADMIN, "org_a", 401), + ("org_a/internal_user", Actor.INTERNAL_USER, "org_a", 401), + ("org_a/owner", Actor.OWNER, "org_a", 401), + ("org_a/unrelated_same_org", Actor.UNRELATED_SAME_ORG, "org_a", 401), + ("org_a/cross_org_user", Actor.CROSS_ORG_USER, "org_a", 401), + ("org_a/service_account", Actor.SERVICE_ACCOUNT, "org_a", 401), + ("org_a/org_b_admin", Actor.ORG_B_ADMIN, "org_a", 401), + ("org_b/proxy_admin", Actor.PROXY_ADMIN, "org_b", 200), + ("org_b/org_admin", Actor.ORG_ADMIN, "org_b", 401), + ("org_b/team_admin", Actor.TEAM_ADMIN, "org_b", 401), + ("org_b/internal_user", Actor.INTERNAL_USER, "org_b", 401), + ("org_b/owner", Actor.OWNER, "org_b", 401), + ("org_b/unrelated_same_org", Actor.UNRELATED_SAME_ORG, "org_b", 401), + ("org_b/cross_org_user", Actor.CROSS_ORG_USER, "org_b", 401), + ("org_b/service_account", Actor.SERVICE_ACCOUNT, "org_b", 401), + ("org_b/org_b_admin", Actor.ORG_B_ADMIN, "org_b", 200), +] + + +@pytest.mark.parametrize( + "actor,org_target,expected_status", + [(a, o, s) for (_id, a, o, s) in _SCENARIOS], + ids=[s[0] for s in _SCENARIOS], +) +async def test_team_new_authz_matrix( + actor: Actor, + org_target: str, + expected_status: int, + proxy_client, + prisma, + scratch, + world, +): + caller = world.keys[actor] + org_id = { + "none": None, + "org_a": world.org_a_id, + "org_b": world.org_b_id, + }[org_target] + + body: Dict[str, Any] = {"team_id": scratch.prefix, "team_alias": scratch.prefix} + if org_id is not None: + body["organization_id"] = org_id + + resp = await proxy_client.post( + "/team/new", + headers={"Authorization": f"Bearer {caller.cleartext}"}, + json=body, + ) + assert ( + resp.status_code == expected_status + ), f"{actor.value} org={org_target}: {resp.status_code} {resp.text}" + + row = await prisma.db.litellm_teamtable.find_unique( + where={"team_id": scratch.prefix} + ) + if expected_status == 200: + assert row is not None + assert row.organization_id == org_id + else: + assert row is None, f"{actor.value}: denied but team row leaked" + + +async def test_team_new_rejects_negative_budget(proxy_client, prisma, scratch, world): + """Input-validation pin: max_budget < 0 is a 400, no row created.""" + resp = await proxy_client.post( + "/team/new", + headers={"Authorization": f"Bearer {world.keys[Actor.PROXY_ADMIN].cleartext}"}, + json={"team_id": scratch.prefix, "max_budget": -1}, + ) + assert resp.status_code == 400, resp.text + row = await prisma.db.litellm_teamtable.find_unique( + where={"team_id": scratch.prefix} + ) + assert row is None + + +async def test_team_new_rejects_duplicate_team_id(proxy_client, prisma, scratch, world): + """Input-validation pin: a colliding team_id is a 400 on the second call.""" + seeder = world.keys[Actor.PROXY_ADMIN].cleartext + first = await proxy_client.post( + "/team/new", + headers={"Authorization": f"Bearer {seeder}"}, + json={"team_id": scratch.prefix, "team_alias": scratch.prefix}, + ) + assert first.status_code == 200, first.text + + second = await proxy_client.post( + "/team/new", + headers={"Authorization": f"Bearer {seeder}"}, + json={"team_id": scratch.prefix, "team_alias": scratch.prefix}, + ) + assert second.status_code == 400, second.text + + +async def test_team_new_unknown_organization_is_500( + proxy_client, prisma, scratch, world +): + """SURFACED, NOT ENDORSED: a /team/new with an organization_id that does + not exist currently fails 500 (the role-resolution layer raises before + the handler's own 400 'Organization not found' check is reached).""" + resp = await proxy_client.post( + "/team/new", + headers={"Authorization": f"Bearer {world.keys[Actor.PROXY_ADMIN].cleartext}"}, + json={ + "team_id": scratch.prefix, + "organization_id": scratch.tag("no-such-org"), + }, + ) + assert resp.status_code == 500, resp.text + row = await prisma.db.litellm_teamtable.find_unique( + where={"team_id": scratch.prefix} + ) + assert row is None diff --git a/tests/proxy_behavior/management/test_team_update.py b/tests/proxy_behavior/management/test_team_update.py new file mode 100644 index 00000000000..3baf2b2148f --- /dev/null +++ b/tests/proxy_behavior/management/test_team_update.py @@ -0,0 +1,176 @@ +import pytest + +from .actors import Actor +from .conftest import create_scratch_team + +pytestmark = pytest.mark.asyncio(loop_scope="session") + + +# POST /team/update — actor x team-shape matrix (shapes built by _seed_target). +# Each request carries the team's own organization_id so a non-proxy-admin can +# reach the org-scoped branch of the route-permission gate (401 on denial), +# which fronts the handler's _verify_team_access. Only PROXY_ADMIN and an +# ORG_ADMIN of the team's org pass: an internal_user team admin is filtered by +# the route gate before _verify_team_access's team-admin branch is reached. +MARKER_ALIAS = "behavior-pin-update-marker-alias" + +_MATRIX = [ + ("alpha/proxy_admin", Actor.PROXY_ADMIN, "alpha", 200), + ("alpha/org_admin", Actor.ORG_ADMIN, "alpha", 200), + ("alpha/team_admin", Actor.TEAM_ADMIN, "alpha", 401), + ("alpha/internal_user", Actor.INTERNAL_USER, "alpha", 401), + ("alpha/owner", Actor.OWNER, "alpha", 401), + ("alpha/unrelated_same_org", Actor.UNRELATED_SAME_ORG, "alpha", 401), + ("alpha/cross_org_user", Actor.CROSS_ORG_USER, "alpha", 401), + ("alpha/service_account", Actor.SERVICE_ACCOUNT, "alpha", 401), + ("alpha/org_b_admin", Actor.ORG_B_ADMIN, "alpha", 401), + ("beta/proxy_admin", Actor.PROXY_ADMIN, "beta", 200), + ("beta/org_admin", Actor.ORG_ADMIN, "beta", 401), + ("beta/team_admin", Actor.TEAM_ADMIN, "beta", 401), + ("beta/internal_user", Actor.INTERNAL_USER, "beta", 401), + ("beta/owner", Actor.OWNER, "beta", 401), + ("beta/unrelated_same_org", Actor.UNRELATED_SAME_ORG, "beta", 401), + ("beta/cross_org_user", Actor.CROSS_ORG_USER, "beta", 401), + ("beta/service_account", Actor.SERVICE_ACCOUNT, "beta", 401), + ("beta/org_b_admin", Actor.ORG_B_ADMIN, "beta", 200), +] + + +async def _seed_target(prisma, world, shape: str, team_id: str) -> str: + """Raw-seed the scratch target team; returns its organization_id.""" + if shape == "alpha": + await create_scratch_team( + prisma, + team_id, + organization_id=world.org_a_id, + admin_user_ids=[world.keys[Actor.TEAM_ADMIN].user_id], + member_user_ids=[ + world.keys[Actor.INTERNAL_USER].user_id, + world.keys[Actor.OWNER].user_id, + world.keys[Actor.UNRELATED_SAME_ORG].user_id, + world.keys[Actor.SERVICE_ACCOUNT].user_id, + ], + ) + return world.org_a_id + if shape == "beta": + await create_scratch_team( + prisma, + team_id, + organization_id=world.org_b_id, + member_user_ids=[world.keys[Actor.CROSS_ORG_USER].user_id], + ) + return world.org_b_id + pytest.fail(f"unknown shape={shape}") # pragma: no cover + + +@pytest.mark.parametrize( + "actor,shape,expected_status", + [(a, sh, s) for (_id, a, sh, s) in _MATRIX], + ids=[s[0] for s in _MATRIX], +) +async def test_team_update_authz_matrix( + actor: Actor, + shape: str, + expected_status: int, + proxy_client, + prisma, + scratch, + world, +): + org_id = await _seed_target(prisma, world, shape, scratch.prefix) + caller = world.keys[actor] + + resp = await proxy_client.post( + "/team/update", + headers={"Authorization": f"Bearer {caller.cleartext}"}, + json={ + "team_id": scratch.prefix, + "team_alias": MARKER_ALIAS, + "organization_id": org_id, + }, + ) + assert ( + resp.status_code == expected_status + ), f"{actor.value} {shape}: {resp.status_code} {resp.text}" + + row = await prisma.db.litellm_teamtable.find_unique( + where={"team_id": scratch.prefix} + ) + assert row is not None + if expected_status == 200: + assert row.team_alias == MARKER_ALIAS + else: + assert row.team_alias != MARKER_ALIAS, "denied but team mutated" + + +async def test_team_update_requires_proxy_admin_without_org_context( + proxy_client, prisma, scratch, world +): + """With no organization_id in the body the route gate has no org context + and falls back to proxy-admin-only: an org admin of the team's own org + is 401, PROXY_ADMIN is 200.""" + await _seed_target(prisma, world, "alpha", scratch.prefix) + + denied = await proxy_client.post( + "/team/update", + headers={"Authorization": f"Bearer {world.keys[Actor.ORG_ADMIN].cleartext}"}, + json={"team_id": scratch.prefix, "team_alias": MARKER_ALIAS}, + ) + assert denied.status_code == 401, denied.text + + allowed = await proxy_client.post( + "/team/update", + headers={"Authorization": f"Bearer {world.keys[Actor.PROXY_ADMIN].cleartext}"}, + json={"team_id": scratch.prefix, "team_alias": MARKER_ALIAS}, + ) + assert allowed.status_code == 200, allowed.text + + +# Relocation gate — moving a team to a different org. The scratch team starts +# in ORG_A; each scenario relocates it to ORG_B. PROXY_ADMIN bypasses; +# ORG_B_ADMIN clears the route gate (dest-org admin) but fails +# _verify_team_access on the source team (403); the rest fail the route gate +# (401). The relocation-allowed branch needs a caller who is org admin of both +# orgs — no seeded actor is, so it is left to a later slice. +_RELOCATION = [ + ("proxy_admin", Actor.PROXY_ADMIN, 200), + ("org_b_admin", Actor.ORG_B_ADMIN, 403), + ("org_admin", Actor.ORG_ADMIN, 401), + ("team_admin", Actor.TEAM_ADMIN, 401), + ("internal_user", Actor.INTERNAL_USER, 401), +] + + +@pytest.mark.parametrize( + "actor,expected_status", + [(a, s) for (_id, a, s) in _RELOCATION], + ids=[s[0] for s in _RELOCATION], +) +async def test_team_update_org_relocation_gate( + actor: Actor, + expected_status: int, + proxy_client, + prisma, + scratch, + world, +): + await _seed_target(prisma, world, "alpha", scratch.prefix) + caller = world.keys[actor] + + resp = await proxy_client.post( + "/team/update", + headers={"Authorization": f"Bearer {caller.cleartext}"}, + json={"team_id": scratch.prefix, "organization_id": world.org_b_id}, + ) + assert ( + resp.status_code == expected_status + ), f"{actor.value}: {resp.status_code} {resp.text}" + + row = await prisma.db.litellm_teamtable.find_unique( + where={"team_id": scratch.prefix} + ) + assert row is not None + if expected_status == 200: + assert row.organization_id == world.org_b_id + else: + assert row.organization_id == world.org_a_id, "denied but team relocated" diff --git a/tests/proxy_behavior/management/test_world_seed.py b/tests/proxy_behavior/management/test_world_seed.py new file mode 100644 index 00000000000..00f9540c9c3 --- /dev/null +++ b/tests/proxy_behavior/management/test_world_seed.py @@ -0,0 +1,30 @@ +import pytest + +from .actors import Actor + +pytestmark = pytest.mark.asyncio(loop_scope="session") + + +@pytest.mark.parametrize("actor", list(Actor), ids=[a.value for a in Actor]) +async def test_each_actor_can_self_info(actor, proxy_client, world): + seeded = world.keys[actor] + resp = await proxy_client.get( + "/key/info", + headers={"Authorization": f"Bearer {seeded.cleartext}"}, + ) + assert resp.status_code == 200, f"{actor.value}: {resp.text}" + body = resp.json() + assert body.get("key") == seeded.hashed + assert body["info"].get("user_id") == seeded.user_id + + +async def test_proxy_admin_actor_can_create_keys_for_others(proxy_client, world): + seeder = world.keys[Actor.PROXY_ADMIN] + target_user_id = world.keys[Actor.OWNER].user_id + + resp = await proxy_client.post( + "/key/generate", + headers={"Authorization": f"Bearer {seeder.cleartext}"}, + json={"key_alias": "smoke-proxy-admin-bypass", "user_id": target_user_id}, + ) + assert resp.status_code == 200, resp.text diff --git a/tests/proxy_unit_tests/test_reducto_ocr_route.py b/tests/proxy_unit_tests/test_reducto_ocr_route.py new file mode 100644 index 00000000000..dc658a74ee8 --- /dev/null +++ b/tests/proxy_unit_tests/test_reducto_ocr_route.py @@ -0,0 +1,137 @@ +import asyncio +import os +from unittest.mock import AsyncMock, patch + +import litellm +import pytest +from fastapi.testclient import TestClient + +from litellm.llms.base_llm.ocr.transformation import OCRPage, OCRResponse, OCRUsageInfo +from litellm.proxy.proxy_server import app, initialize + + +@pytest.fixture(scope="function") +def fake_env_vars(monkeypatch): + monkeypatch.setenv("OPENAI_API_KEY", "fake_openai_api_key") + monkeypatch.setenv("OPENAI_API_BASE", "http://fake-openai-api-base") + monkeypatch.setenv("AZURE_AI_API_BASE", "http://fake-azure-api-base") + monkeypatch.setenv("AZURE_AI_API_KEY", "fake_azure_api_key") + monkeypatch.setenv("AZURE_OPENAI_API_KEY", "fake_azure_openai_api_key") + monkeypatch.setenv("AZURE_SWEDEN_API_BASE", "http://fake-azure-sweden-api-base") + monkeypatch.setenv("AZURE_SWEDEN_API_KEY", "fake_azure_sweden_api_key") + monkeypatch.setenv("REDIS_HOST", "localhost") + + +@pytest.fixture(scope="function") +def client_no_auth(fake_env_vars): + from litellm.proxy.proxy_server import cleanup_router_config_variables + + original_disable_aiohttp = litellm.disable_aiohttp_transport + litellm.disable_aiohttp_transport = True + litellm.in_memory_llm_clients_cache.flush_cache() + cleanup_router_config_variables() + + filepath = os.path.dirname(os.path.abspath(__file__)) + config_fp = os.path.join(filepath, "test_configs", "test_config_no_auth.yaml") + asyncio.run(initialize(config=config_fp, debug=True)) + + # Passthrough of api_base in the JSON body is rejected by default + # (pre_db_read_auth_checks / is_request_body_safe). This test asserts + # api_base reaches aocr(). + from litellm.proxy import proxy_server as _ps + + if _ps.general_settings is None: + _ps.general_settings = {} + _ps.general_settings["allow_client_side_credentials"] = True + + try: + yield TestClient(app) + finally: + litellm.disable_aiohttp_transport = original_disable_aiohttp + litellm.in_memory_llm_clients_cache.flush_cache() + + +def test_proxy_reducto_ocr_json_rejects_reducto_id(client_no_auth): + with patch( + "litellm.proxy.proxy_server.llm_router.aocr", + new=AsyncMock(), + ) as mock_aocr: + response = client_no_auth.post( + "/v1/ocr", + json={ + "model": "reducto/parse-v3", + "document": { + "type": "document_url", + "document_url": "reducto://proxy.pdf", + }, + "api_key": "proxy-key", + "api_base": "https://platform.reducto.ai", + }, + ) + + assert response.status_code >= 400 + assert "reducto://" in response.text + assert mock_aocr.await_count == 0 + + +def test_proxy_reducto_ocr_json_rejects_reducto_id_in_image_url(client_no_auth): + with patch( + "litellm.proxy.proxy_server.llm_router.aocr", + new=AsyncMock(), + ) as mock_aocr: + response = client_no_auth.post( + "/v1/ocr", + json={ + "model": "reducto/parse-v3", + "document": { + "type": "image_url", + "image_url": "reducto://proxy.png", + }, + }, + ) + + assert response.status_code >= 400 + assert "reducto://" in response.text + assert mock_aocr.await_count == 0 + + +def test_proxy_reducto_ocr_json_passthrough_data_uri(client_no_auth): + mocked_response = OCRResponse( + pages=[OCRPage(index=0, markdown="Proxy OCR")], + model="parse-v3", + usage_info=OCRUsageInfo(pages_processed=1, credits=1), + ) + + data_uri = "data:application/pdf;base64,JVBERi0xLjQK" + + with patch( + "litellm.proxy.proxy_server.llm_router.aocr", + new=AsyncMock(return_value=mocked_response), + ) as mock_aocr: + response = client_no_auth.post( + "/v1/ocr", + json={ + "model": "reducto/parse-v3", + "document": { + "type": "document_url", + "document_url": data_uri, + }, + "api_key": "proxy-key", + "api_base": "https://platform.reducto.ai", + }, + ) + + assert response.status_code == 200 + assert mock_aocr.await_count == 1 + assert mock_aocr.await_args.kwargs["model"] == "reducto/parse-v3" + assert mock_aocr.await_args.kwargs["document"] == { + "type": "document_url", + "document_url": data_uri, + } + assert mock_aocr.await_args.kwargs["api_key"] == "proxy-key" + assert mock_aocr.await_args.kwargs["api_base"] == "https://platform.reducto.ai" + + response_body = response.json() + assert response_body["object"] == "ocr" + assert response_body["usage_info"]["credits"] == 1 + assert response_body["pages"][0]["markdown"] == "Proxy OCR" diff --git a/tests/proxy_unit_tests/test_user_api_key_auth.py b/tests/proxy_unit_tests/test_user_api_key_auth.py index 210347aaf94..958b028c542 100644 --- a/tests/proxy_unit_tests/test_user_api_key_auth.py +++ b/tests/proxy_unit_tests/test_user_api_key_auth.py @@ -915,6 +915,36 @@ async def test_user_api_key_auth_websocket(): ) +@pytest.mark.asyncio +async def test_user_api_key_auth_websocket_carries_asgi_path(): + """ + The synthetic Request must carry the ASGI scope's ``path`` so + ``get_request_route`` returns the real WebSocket path, not a value + reconstructed from the (Host-poisonable) ``websocket.url``. + """ + from litellm.proxy.auth.user_api_key_auth import user_api_key_auth_websocket + + mock_websocket = MagicMock(spec=WebSocket) + mock_websocket.query_params = {"model": "some_model"} + mock_websocket.headers = {"authorization": "Bearer some_api_key"} + mock_websocket.scope = { + "type": "websocket", + "path": "/v1/realtime", + "root_path": "", + "headers": [(b"authorization", b"Bearer some_api_key")], + } + mock_websocket.url = URL(url="/v1/realtime") + + with patch( + "litellm.proxy.auth.user_api_key_auth.user_api_key_auth", autospec=True + ) as mock_user_api_key_auth: + await user_api_key_auth_websocket(mock_websocket) + + request_arg = mock_user_api_key_auth.call_args.kwargs["request"] + assert request_arg.scope.get("path") == "/v1/realtime" + assert request_arg.scope.get("root_path") == "" + + @pytest.mark.parametrize("enforce_rbac", [True, False]) @pytest.mark.asyncio async def test_jwt_user_api_key_auth_builder_enforce_rbac(enforce_rbac, monkeypatch): diff --git a/tests/test_litellm/completion_extras/litellm_responses_transformation/test_completion_extras_litellm_responses_transformation_transformation.py b/tests/test_litellm/completion_extras/litellm_responses_transformation/test_completion_extras_litellm_responses_transformation_transformation.py index 697a9ebc720..d335c359aa0 100644 --- a/tests/test_litellm/completion_extras/litellm_responses_transformation/test_completion_extras_litellm_responses_transformation_transformation.py +++ b/tests/test_litellm/completion_extras/litellm_responses_transformation/test_completion_extras_litellm_responses_transformation_transformation.py @@ -508,6 +508,308 @@ and I learn to carry this small calm home.""" print("✓ transform_response correctly handled reasoning items and output messages") +def _make_empty_responses_api_response(model: str = "gpt-5.4"): + from litellm.types.llms.openai import ResponseAPIUsage, ResponsesAPIResponse + + return ResponsesAPIResponse( + id="resp_from_stream", + created_at=1760144904, + error=None, + incomplete_details=None, + instructions=None, + metadata={}, + model=model, + object="response", + output=[], + parallel_tool_calls=True, + temperature=1.0, + tool_choice="auto", + tools=[], + top_p=1.0, + max_output_tokens=None, + previous_response_id=None, + reasoning={"effort": "low", "summary": "detailed"}, + status="completed", + text={"format": {"type": "text"}, "verbosity": "medium"}, + truncation="disabled", + usage=ResponseAPIUsage( + input_tokens=1, + input_tokens_details=None, + output_tokens=1, + output_tokens_details=None, + total_tokens=2, + cost=None, + ), + user=None, + store=True, + background=False, + billing={"payer": "developer"}, + max_tool_calls=None, + prompt_cache_key=None, + safety_identifier=None, + service_tier="default", + top_logprobs=0, + ) + + +def _make_empty_model_response(): + from litellm.types.utils import ModelResponse, Usage + + return ModelResponse( + id="chatcmpl-test-recovered", + created=1760144904, + model=None, + object="chat.completion", + system_fingerprint=None, + choices=[], + usage=Usage(completion_tokens=0, prompt_tokens=0, total_tokens=0), + ) + + +def test_transform_response_recovers_empty_output_from_raw_sse(): + from litellm.completion_extras.litellm_responses_transformation.transformation import ( + LiteLLMResponsesTransformationHandler, + ) + + handler = LiteLLMResponsesTransformationHandler() + + raw_sse = "\n".join( + [ + 'data: {"type":"response.output_text.done","output_index":0,"content_index":0,"item_id":"msg_from_stream","text":"Recovered from SSE"}', + 'data: {"type":"response.completed","response":{"id":"resp_from_stream","object":"response","created_at":1760144904,"status":"completed","model":"gpt-5.4","output":[]}}', + "data: [DONE]", + "", + ] + ) + + raw_response = _make_empty_responses_api_response() + model_response = _make_empty_model_response() + logging_obj = Mock() + logging_obj.model_call_details = {"original_response": raw_sse} + + result = handler.transform_response( + model="gpt-5.4", + raw_response=raw_response, + model_response=model_response, + logging_obj=logging_obj, + request_data={"model": "gpt-5.4"}, + messages=[{"role": "user", "content": "Reply with exactly: ok"}], + optional_params={}, + litellm_params={}, + encoding=Mock(), + ) + + assert len(result.choices) == 1 + assert result.choices[0].message.content == "Recovered from SSE" + + +def test_transform_response_recovers_output_item_done_from_raw_sse(): + from litellm.completion_extras.litellm_responses_transformation.transformation import ( + LiteLLMResponsesTransformationHandler, + ) + + handler = LiteLLMResponsesTransformationHandler() + + raw_sse = "\n".join( + [ + 'data: {"type":"response.output_item.done","output_index":0,"item":{"type":"message","id":"msg_from_item","role":"assistant","status":"completed","content":[{"type":"output_text","text":"Recovered from output item","annotations":[]}]}}', + 'data: {"type":"response.completed","response":{"id":"resp_from_stream","object":"response","created_at":1760144904,"status":"completed","model":"gpt-5.4","output":[]}}', + "data: [DONE]", + "", + ] + ) + + raw_response = _make_empty_responses_api_response() + model_response = _make_empty_model_response() + logging_obj = Mock() + logging_obj.model_call_details = {"original_response": raw_sse} + + result = handler.transform_response( + model="gpt-5.4", + raw_response=raw_response, + model_response=model_response, + logging_obj=logging_obj, + request_data={"model": "gpt-5.4"}, + messages=[{"role": "user", "content": "Reply with exactly: ok"}], + optional_params={}, + litellm_params={}, + encoding=Mock(), + ) + + assert len(result.choices) == 1 + assert result.choices[0].message.content == "Recovered from output item" + + +def test_transform_response_recovers_output_item_done_from_whitespace_padded_raw_sse(): + from litellm.completion_extras.litellm_responses_transformation.transformation import ( + LiteLLMResponsesTransformationHandler, + ) + + handler = LiteLLMResponsesTransformationHandler() + + output_item_event = { + "type": "response.output_item.done", + "output_index": 0, + "item": { + "type": "message", + "id": "msg_from_item", + "role": "assistant", + "status": "completed", + "content": [ + { + "type": "output_text", + "text": "Recovered from padded output item", + "annotations": [], + } + ], + }, + } + completed_event = { + "type": "response.completed", + "response": { + "id": "resp_from_stream", + "object": "response", + "created_at": 1760144904, + "status": "completed", + "model": "gpt-5.4", + "output": [], + }, + } + raw_sse = "\n".join( + [ + f" data: {json.dumps(output_item_event)} ", + f"\tdata: {json.dumps(completed_event)}", + "data: [DONE]", + "", + ] + ) + + raw_response = _make_empty_responses_api_response() + model_response = _make_empty_model_response() + logging_obj = Mock() + logging_obj.model_call_details = {"original_response": raw_sse} + + result = handler.transform_response( + model="gpt-5.4", + raw_response=raw_response, + model_response=model_response, + logging_obj=logging_obj, + request_data={"model": "gpt-5.4"}, + messages=[{"role": "user", "content": "Reply with exactly: ok"}], + optional_params={}, + litellm_params={}, + encoding=Mock(), + ) + + assert len(result.choices) == 1 + assert result.choices[0].message.content == "Recovered from padded output item" + + +def test_transform_response_preserves_output_item_when_text_done_arrives_later(): + from litellm.completion_extras.litellm_responses_transformation.transformation import ( + LiteLLMResponsesTransformationHandler, + ) + + handler = LiteLLMResponsesTransformationHandler() + + raw_sse = "\n".join( + [ + 'data: {"type":"response.output_item.done","output_index":0,"item":{"type":"message","id":"msg_from_item","role":"assistant","status":"completed","content":[{"type":"output_text","text":"Complete output item text","annotations":[]}]}}', + 'data: {"type":"response.output_text.done","output_index":0,"content_index":0,"item_id":"msg_from_stream","text":"Late text event"}', + 'data: {"type":"response.completed","response":{"id":"resp_from_stream","object":"response","created_at":1760144904,"status":"completed","model":"gpt-5.4","output":[]}}', + "data: [DONE]", + "", + ] + ) + + raw_response = _make_empty_responses_api_response() + model_response = _make_empty_model_response() + logging_obj = Mock() + logging_obj.model_call_details = {"original_response": raw_sse} + + result = handler.transform_response( + model="gpt-5.4", + raw_response=raw_response, + model_response=model_response, + logging_obj=logging_obj, + request_data={"model": "gpt-5.4"}, + messages=[{"role": "user", "content": "Reply with exactly: ok"}], + optional_params={}, + litellm_params={}, + encoding=Mock(), + ) + + assert len(result.choices) == 1 + assert result.choices[0].message.content == "Complete output item text" + + +def test_recover_output_items_merges_text_only_items_at_distinct_indices(): + """When OUTPUT_ITEM_DONE covers some indices and OUTPUT_TEXT_DONE covers + others, both must be preserved instead of treating them as mutually + exclusive fallbacks.""" + from litellm.completion_extras.litellm_responses_transformation.transformation import ( + LiteLLMResponsesTransformationHandler, + ) + + raw_sse = "\n".join( + [ + 'data: {"type":"response.output_item.done","output_index":0,"item":{"type":"message","id":"msg_item_0","role":"assistant","status":"completed","content":[{"type":"output_text","text":"From OUTPUT_ITEM_DONE","annotations":[]}]}}', + 'data: {"type":"response.output_text.done","output_index":1,"content_index":0,"item_id":"msg_text_1","text":"From OUTPUT_TEXT_DONE only"}', + "data: [DONE]", + "", + ] + ) + + recovered = ( + LiteLLMResponsesTransformationHandler._recover_output_items_from_raw_sse( + raw_sse + ) + ) + + assert len(recovered) == 2 + assert recovered[0]["id"] == "msg_item_0" + assert recovered[0]["content"][0]["text"] == "From OUTPUT_ITEM_DONE" + assert recovered[1]["id"] == "msg_text_1" + assert recovered[1]["content"][0]["text"] == "From OUTPUT_TEXT_DONE only" + + +def test_transform_response_prefers_completed_output_from_raw_sse(): + from litellm.completion_extras.litellm_responses_transformation.transformation import ( + LiteLLMResponsesTransformationHandler, + ) + + handler = LiteLLMResponsesTransformationHandler() + + raw_sse = "\n".join( + [ + 'data: {"type":"response.output_item.done","output_index":0,"item":{"type":"message","id":"msg_from_item","role":"assistant","status":"completed","content":[{"type":"output_text","text":"Earlier stream text","annotations":[]}]}}', + 'data: {"type":"response.completed","response":{"id":"resp_from_stream","object":"response","created_at":1760144904,"status":"completed","model":"gpt-5.4","output":[{"type":"message","id":"msg_from_completed","role":"assistant","status":"completed","content":[{"type":"output_text","text":"Authoritative completed text","annotations":[]}]}]}}', + "data: [DONE]", + "", + ] + ) + + raw_response = _make_empty_responses_api_response() + model_response = _make_empty_model_response() + logging_obj = Mock() + logging_obj.model_call_details = {"original_response": raw_sse} + + result = handler.transform_response( + model="gpt-5.4", + raw_response=raw_response, + model_response=model_response, + logging_obj=logging_obj, + request_data={"model": "gpt-5.4"}, + messages=[{"role": "user", "content": "Reply with exactly: ok"}], + optional_params={}, + litellm_params={}, + encoding=Mock(), + ) + + assert len(result.choices) == 1 + assert result.choices[0].message.content == "Authoritative completed text" + + def test_convert_tools_to_responses_format(): from litellm.completion_extras.litellm_responses_transformation.transformation import ( LiteLLMResponsesTransformationHandler, diff --git a/tests/test_litellm/integrations/rubrik_test_helpers.py b/tests/test_litellm/integrations/rubrik_test_helpers.py new file mode 100644 index 00000000000..1bdb8cb247b --- /dev/null +++ b/tests/test_litellm/integrations/rubrik_test_helpers.py @@ -0,0 +1,23 @@ +"""Shared helpers for Rubrik plugin tests.""" + +from typing import Any, Dict + +from litellm.types.utils import GenericGuardrailAPIInputs + + +def make_tool_call_dict( + tc_id: str, name: str, arguments: str = "{}" +) -> Dict[str, Any]: + """Create a tool call dict matching the ChatCompletionMessageToolCall schema.""" + return { + "id": tc_id, + "type": "function", + "function": {"name": name, "arguments": arguments}, + } + + +def make_inputs_with_tools( + tool_calls: list, texts: list | None = None +) -> GenericGuardrailAPIInputs: + """Create GenericGuardrailAPIInputs with tool_calls.""" + return GenericGuardrailAPIInputs(texts=texts or [], tool_calls=tool_calls) diff --git a/tests/test_litellm/integrations/test_otel_guardrail_violation_spans.py b/tests/test_litellm/integrations/test_otel_guardrail_violation_spans.py new file mode 100644 index 00000000000..ace9399cf53 --- /dev/null +++ b/tests/test_litellm/integrations/test_otel_guardrail_violation_spans.py @@ -0,0 +1,641 @@ +""" +Tests for guardrail OTEL spans on violation. + +Two distinct gaps surface together when a pre-call guardrail blocks the +request before it reaches the LLM provider: + + 1. ``async_post_call_failure_hook`` (the OTEL hook that actually runs on + the proxy failure path) only stamps attributes on the proxy parent + span. It never creates the child ``guardrail`` span, even though + ``request_data["metadata"]["standard_logging_guardrail_information"]`` + is populated by the time the hook runs. + + 2. ``_create_guardrail_span`` records ``guardrail_name`` / ``guardrail_mode`` + / ``guardrail_response`` but does not surface ``guardrail_status`` + (success / guardrail_intervened / guardrail_failed_to_respond / + not_run) or the violation categories (Bedrock topic policy names, + content filter types, etc.) as queryable span attributes — the data + is buried inside the serialised ``guardrail_response`` blob and cannot + be filtered on in the trace backend. + +The tests below use real OTEL SDK objects (TracerProvider + +InMemorySpanExporter + a real BatchSpanProcessor-equivalent) and the +real ``OpenTelemetry`` integration. No monkey patching of the integration +under test — only the OTEL exporter is in-memory. +""" + +import os +import sys +import time +import unittest +from datetime import datetime, timedelta, timezone + +from opentelemetry.sdk.trace import TracerProvider +from opentelemetry.sdk.trace.export import SimpleSpanProcessor +from opentelemetry.sdk.trace.export.in_memory_span_exporter import InMemorySpanExporter +from opentelemetry.trace import StatusCode + +sys.path.insert(0, os.path.abspath("../..")) + +from litellm.integrations.opentelemetry import ( + LITELLM_REQUEST_SPAN_NAME, + OpenTelemetry, +) +from litellm.proxy._types import UserAPIKeyAuth + + +GUARDRAIL_SPAN_NAME = "guardrail" +PROXY_SPAN_NAME = "Received Proxy Server Request" + + +def _bedrock_block_response(): + """Realistic Bedrock ApplyGuardrail response when a topic policy fires. + + Mirrors the shape in ``litellm/types/proxy/guardrails/guardrail_hooks/ + bedrock_guardrails.py`` so the violation-category extraction can be + tested against the exact payload Bedrock returns. + """ + return { + "action": "GUARDRAIL_INTERVENED", + "assessments": [ + { + "topicPolicy": { + "topics": [ + { + "name": "Fiduciary Advice", + "type": "DENY", + "action": "BLOCKED", + } + ] + }, + "contentPolicy": { + "filters": [ + { + "type": "VIOLENCE", + "confidence": "HIGH", + "action": "BLOCKED", + } + ] + }, + "wordPolicy": { + "customWords": [{"match": "secret-codeword", "action": "BLOCKED"}], + "managedWordLists": [ + {"match": "fuck", "type": "PROFANITY", "action": "BLOCKED"} + ], + }, + } + ], + "outputs": [{"text": "Sorry, the model cannot respond to this request."}], + } + + +def _slg_entry( + guardrail_status, + guardrail_response, + *, + name="bedrock-test", + mode="pre_call", + provider="bedrock", + start=1.0, + end=2.0, + violation_categories=None, + guardrail_action=None, +): + """Build a StandardLoggingGuardrailInformation entry the way + ``add_standard_logging_guardrail_information_to_request_data`` does.""" + entry = { + "guardrail_name": name, + "guardrail_provider": provider, + "guardrail_mode": mode, + "guardrail_response": guardrail_response, + "guardrail_status": guardrail_status, + "start_time": start, + "end_time": end, + "duration": end - start, + } + if violation_categories is not None: + entry["violation_categories"] = violation_categories + if guardrail_action is not None: + entry["guardrail_action"] = guardrail_action + return entry + + +def _kwargs_with_guardrail( + *, + entries, + parent_span=None, + include_exception=False, +): + """Build the kwargs / model_call_details shape that the OTEL integration + consumes. ``litellm_params.metadata`` is the SAME dict that the proxy's + ``request_data["metadata"]`` becomes after ``update_environment_variables``, + so ``_otel_internal`` dedupe state lives there too.""" + metadata = {"standard_logging_guardrail_information": list(entries)} + if parent_span is not None: + metadata["litellm_parent_otel_span"] = parent_span + kwargs = { + "model": "gpt-4", + "messages": [{"role": "user", "content": "Hello"}], + "optional_params": {}, + "litellm_params": { + "custom_llm_provider": "openai", + "metadata": metadata, + }, + "standard_logging_object": { + "id": "test-call-id", + "call_type": "completion", + "metadata": metadata, + "hidden_params": {}, + "guardrail_information": list(entries), + }, + } + if include_exception: + kwargs["exception"] = Exception("guardrail blocked the request") + return kwargs + + +def _make_otel(): + """Spin up a real OTEL pipeline backed by an in-memory exporter.""" + exporter = InMemorySpanExporter() + provider = TracerProvider() + provider.add_span_processor(SimpleSpanProcessor(exporter)) + otel = OpenTelemetry(tracer_provider=provider) + otel.tracer = provider.get_tracer(__name__) + return otel, provider, exporter + + +def _run(coro): + """Run a coroutine on a fresh event loop and close it — prevents the + "unclosed event loop" / ResourceWarning that you get from + asyncio.new_event_loop().run_until_complete() with no cleanup.""" + import asyncio + + loop = asyncio.new_event_loop() + try: + return loop.run_until_complete(coro) + finally: + loop.close() + + +def _attr(span, key): + return (span.attributes or {}).get(key) + + +class TestGuardrailSpanOnViolation(unittest.TestCase): + """Bug 1: when a pre-call guardrail blocks, the guardrail span and the + litellm_request span must both appear with the correct status.""" + + def test_handle_failure_creates_litellm_request_and_guardrail_spans(self): + """Driving ``_handle_failure`` with a populated + ``standard_logging_object['guardrail_information']`` entry must + emit both spans, parented correctly, with ERROR on the parent.""" + otel, _, exporter = _make_otel() + + kwargs = _kwargs_with_guardrail( + entries=[ + _slg_entry("guardrail_intervened", _bedrock_block_response()), + ], + include_exception=True, + ) + + start = datetime.now(timezone.utc) + end = start + timedelta(milliseconds=20) + otel._handle_failure(kwargs, response_obj=None, start_time=start, end_time=end) + + spans = exporter.get_finished_spans() + litellm_spans = [s for s in spans if s.name == LITELLM_REQUEST_SPAN_NAME] + guardrail_spans = [s for s in spans if s.name == GUARDRAIL_SPAN_NAME] + + self.assertEqual( + len(litellm_spans), + 1, + "Expected exactly one litellm_request span on guardrail block", + ) + self.assertEqual(litellm_spans[0].status.status_code, StatusCode.ERROR) + + self.assertEqual( + len(guardrail_spans), + 1, + "Expected exactly one guardrail span on guardrail block", + ) + + # Guardrail span must be a child of the litellm_request span + self.assertIsNotNone( + guardrail_spans[0].parent, + "Guardrail span must be parented (not a root span)", + ) + self.assertEqual( + guardrail_spans[0].parent.span_id, + litellm_spans[0].context.span_id, + ) + + def test_async_post_call_failure_hook_emits_guardrail_span(self): + """The production failure path on the proxy calls + ``async_post_call_failure_hook`` with the (still-populated) + ``request_data``. The hook currently only stamps attrs on the proxy + span; it must also emit the guardrail span so the violation is + visible in the trace.""" + otel, provider, exporter = _make_otel() + parent_span = provider.get_tracer(__name__).start_span(PROXY_SPAN_NAME) + + user_api_key_dict = UserAPIKeyAuth( + api_key="sk-test", + parent_otel_span=parent_span, + request_route="/chat/completions", + ) + + request_data = { + "model": "gpt-4", + "messages": [{"role": "user", "content": "Hello"}], + "metadata": { + "standard_logging_guardrail_information": [ + _slg_entry("guardrail_intervened", _bedrock_block_response()) + ], + }, + } + + _run( + otel.async_post_call_failure_hook( + request_data=request_data, + original_exception=Exception("guardrail blocked"), + user_api_key_dict=user_api_key_dict, + ) + ) + + spans = exporter.get_finished_spans() + guardrail_spans = [s for s in spans if s.name == GUARDRAIL_SPAN_NAME] + self.assertEqual( + len(guardrail_spans), + 1, + "async_post_call_failure_hook must emit the guardrail span when " + "request_data['metadata'] carries standard_logging_guardrail_information", + ) + + # The guardrail span must be parented to the proxy request span so + # backends correlate it with the rest of the trace. + self.assertIsNotNone(guardrail_spans[0].parent) + self.assertEqual( + guardrail_spans[0].parent.span_id, + parent_span.context.span_id, + ) + + def test_handle_failure_and_post_call_failure_hook_dedupe(self): + """When _handle_failure and async_post_call_failure_hook BOTH fire + for the same request (the production flow on a guardrail block), + exactly one guardrail span must be emitted. The dedupe relies on + request_data['metadata'] and kwargs['litellm_params']['metadata'] + referencing the SAME dict so _emit_once sees its earlier marker.""" + otel, provider, exporter = _make_otel() + parent_span = provider.get_tracer(__name__).start_span(PROXY_SPAN_NAME) + + # Shared metadata dict — same identity, mirroring how + # update_environment_variables wires them in the proxy. + shared_metadata = { + "standard_logging_guardrail_information": [ + _slg_entry( + "guardrail_intervened", + _bedrock_block_response(), + violation_categories=["Fiduciary Advice"], + ) + ], + } + + kwargs = { + "model": "gpt-4", + "messages": [{"role": "user", "content": "Hello"}], + "optional_params": {}, + "litellm_params": { + "custom_llm_provider": "openai", + "metadata": shared_metadata, + }, + "standard_logging_object": { + "id": "test-call-id", + "call_type": "completion", + "metadata": shared_metadata, + "hidden_params": {}, + "guardrail_information": shared_metadata[ + "standard_logging_guardrail_information" + ], + }, + "exception": Exception("guardrail blocked"), + } + request_data = { + "model": "gpt-4", + "messages": [{"role": "user", "content": "Hello"}], + "metadata": shared_metadata, + } + user_api_key_dict = UserAPIKeyAuth( + api_key="sk-test", + parent_otel_span=parent_span, + request_route="/chat/completions", + ) + + start = datetime.now(timezone.utc) + end = start + timedelta(milliseconds=20) + otel._handle_failure(kwargs, response_obj=None, start_time=start, end_time=end) + _run( + otel.async_post_call_failure_hook( + request_data=request_data, + original_exception=Exception("guardrail blocked"), + user_api_key_dict=user_api_key_dict, + ) + ) + + guardrail_spans = [ + s for s in exporter.get_finished_spans() if s.name == GUARDRAIL_SPAN_NAME + ] + self.assertEqual( + len(guardrail_spans), + 1, + "Dedupe must collapse the two emit calls into one span when the " + "metadata dict identity is shared between kwargs and request_data", + ) + + +class TestGuardrailSpanAttributesOnViolation(unittest.TestCase): + """Bug 2: the guardrail span must surface the violation status and + violation categories as queryable span attributes, not bury them inside + ``guardrail_response`` (which is logged as a single serialised blob).""" + + def _emit_and_get_guardrail_span(self, entry): + otel, _, exporter = _make_otel() + kwargs = _kwargs_with_guardrail(entries=[entry]) + otel._create_guardrail_span(kwargs=kwargs, context=None) + + guardrail_spans = [ + s for s in exporter.get_finished_spans() if s.name == GUARDRAIL_SPAN_NAME + ] + self.assertEqual(len(guardrail_spans), 1) + return guardrail_spans[0] + + def test_status_attribute_present_for_intervened(self): + entry = _slg_entry("guardrail_intervened", _bedrock_block_response()) + span = self._emit_and_get_guardrail_span(entry) + self.assertEqual( + _attr(span, "guardrail_status"), + "guardrail_intervened", + "guardrail_status must be exposed as a top-level span attribute", + ) + + def test_status_attribute_present_for_success(self): + entry = _slg_entry( + "success", + {"action": "NONE", "assessments": []}, + ) + span = self._emit_and_get_guardrail_span(entry) + self.assertEqual(_attr(span, "guardrail_status"), "success") + + def test_status_attribute_present_for_failed_to_respond(self): + entry = _slg_entry( + "guardrail_failed_to_respond", + {"error": "endpoint unreachable"}, + ) + span = self._emit_and_get_guardrail_span(entry) + self.assertEqual(_attr(span, "guardrail_status"), "guardrail_failed_to_respond") + + def test_violation_categories_surfaced_when_provider_populates_them(self): + """The provider hook (e.g. Bedrock) extracts violation categories + from the raw response BEFORE redaction and stamps them onto the + StandardLoggingGuardrailInformation entry. OTEL must surface that + list as a queryable span attribute so dashboards can group by + violation type without parsing the redacted guardrail_response.""" + entry = _slg_entry( + "guardrail_intervened", + _bedrock_block_response(), + violation_categories=["Fiduciary Advice", "VIOLENCE", "PROFANITY"], + ) + span = self._emit_and_get_guardrail_span(entry) + + categories = _attr(span, "guardrail_violation_categories") + self.assertIsNotNone( + categories, + "guardrail_violation_categories must be set when the entry " + "carries violation_categories", + ) + # Serialised as JSON to keep set_attribute typing simple. + as_str = categories if isinstance(categories, str) else repr(list(categories)) + self.assertIn("Fiduciary Advice", as_str) + self.assertIn("VIOLENCE", as_str) + self.assertIn("PROFANITY", as_str) + + def test_no_violation_categories_when_field_absent(self): + """When the provider didn't populate violation_categories (success + path, or provider didn't extract them), don't pollute the trace + with an empty attribute.""" + entry = _slg_entry("success", {"action": "NONE", "assessments": []}) + span = self._emit_and_get_guardrail_span(entry) + self.assertIsNone(_attr(span, "guardrail_violation_categories")) + + def test_no_violation_categories_when_field_is_empty(self): + """Empty list must not produce a span attribute either.""" + entry = _slg_entry( + "guardrail_intervened", + _bedrock_block_response(), + violation_categories=[], + ) + span = self._emit_and_get_guardrail_span(entry) + self.assertIsNone(_attr(span, "guardrail_violation_categories")) + + def test_guardrail_action_surfaced_when_provider_populates_it(self): + """The provider hook (e.g. Bedrock) writes its raw top-level + ``action`` string onto StandardLoggingGuardrailInformation as + ``guardrail_action``. OTEL must expose it as a queryable span + attribute so dashboards can pivot on the raw provider verdict + (Bedrock ``GUARDRAIL_INTERVENED`` / ``NONE``) without parsing + the redacted guardrail_response blob.""" + entry = _slg_entry( + "guardrail_intervened", + _bedrock_block_response(), + guardrail_action="GUARDRAIL_INTERVENED", + ) + span = self._emit_and_get_guardrail_span(entry) + self.assertEqual( + _attr(span, "guardrail_action"), + "GUARDRAIL_INTERVENED", + "guardrail_action must be exposed as a top-level span attribute", + ) + + def test_guardrail_action_surfaced_for_allowed_request(self): + """Even on the success path, the provider's raw action (e.g. + Bedrock ``NONE``) should be queryable so dashboards can group + allowed-vs-blocked counts off the same attribute.""" + entry = _slg_entry( + "success", + {"action": "NONE", "assessments": []}, + guardrail_action="NONE", + ) + span = self._emit_and_get_guardrail_span(entry) + self.assertEqual(_attr(span, "guardrail_action"), "NONE") + + def test_no_guardrail_action_when_field_absent(self): + """If the provider didn't populate the field (older payloads, + non-Bedrock providers without a top-level action), don't emit + an empty attribute.""" + entry = _slg_entry("success", {"action": "NONE", "assessments": []}) + span = self._emit_and_get_guardrail_span(entry) + self.assertIsNone(_attr(span, "guardrail_action")) + + +class TestMultipleGuardrailsOneBlocks(unittest.TestCase): + """When several guardrails run sequentially and only the last one + intervenes, every guardrail span must appear with its own status — + losing the early "allowed" spans would mask which checks ran.""" + + def test_all_guardrail_spans_emitted_with_per_entry_status(self): + otel, _, exporter = _make_otel() + + entries = [ + _slg_entry( + "success", + {"action": "NONE", "assessments": []}, + name="pii-mask", + start=1.0, + end=1.5, + ), + _slg_entry( + "success", + {"action": "NONE", "assessments": []}, + name="prompt-injection", + start=2.0, + end=2.2, + ), + _slg_entry( + "guardrail_intervened", + _bedrock_block_response(), + name="bedrock-policy", + start=3.0, + end=3.4, + ), + ] + kwargs = _kwargs_with_guardrail( + entries=entries, + include_exception=True, + ) + + start = datetime.now(timezone.utc) + end = start + timedelta(milliseconds=50) + otel._handle_failure(kwargs, response_obj=None, start_time=start, end_time=end) + + spans = exporter.get_finished_spans() + guardrail_spans = sorted( + (s for s in spans if s.name == GUARDRAIL_SPAN_NAME), + key=lambda s: (s.attributes or {}).get("guardrail_name", ""), + ) + self.assertEqual( + len(guardrail_spans), + 3, + "Every guardrail invocation must emit a span — even the ones " + "that allowed the request through before the blocker fired", + ) + + statuses = { + _attr(s, "guardrail_name"): _attr(s, "guardrail_status") + for s in guardrail_spans + } + self.assertEqual(statuses["pii-mask"], "success") + self.assertEqual(statuses["prompt-injection"], "success") + self.assertEqual(statuses["bedrock-policy"], "guardrail_intervened") + + +class TestCustomGuardrailEndToEnd(unittest.TestCase): + """End-to-end: a real ``CustomGuardrail`` subclass calls + ``add_standard_logging_guardrail_information_to_request_data`` and then + raises. We then drive ``_handle_failure`` with the resulting kwargs + (matching the shape ``async_failure_handler`` would build) and verify + the guardrail span carries the recorded information.""" + + def test_real_custom_guardrail_violation_path(self): + # Deliberately not importing fastapi here — the real Bedrock guardrail + # raises HTTPException, but the OTEL span flow is exception-type + # agnostic. Using a plain Exception keeps this test runnable in + # SDK-only installs that don't ship fastapi. + from litellm.integrations.custom_guardrail import CustomGuardrail + from litellm.types.guardrails import GuardrailEventHooks + + class BlockingViolation(Exception): + pass + + class BlockingGuardrail(CustomGuardrail): + async def async_pre_call_hook( + self, + user_api_key_dict, + cache, + data, + call_type, + ): + start_ts = time.time() + self.add_standard_logging_guardrail_information_to_request_data( + guardrail_provider="bedrock", + guardrail_json_response=_bedrock_block_response(), + request_data=data, + guardrail_status="guardrail_intervened", + start_time=start_ts, + end_time=start_ts + 0.01, + duration=0.01, + event_type=GuardrailEventHooks.pre_call, + tracing_detail={ + "violation_categories": ["Fiduciary Advice", "VIOLENCE"] + }, + ) + raise BlockingViolation("violation") + + request_data = { + "model": "gpt-4", + "messages": [{"role": "user", "content": "Hi"}], + "metadata": {}, + } + guardrail = BlockingGuardrail( + guardrail_name="blocking-test", + event_hook=GuardrailEventHooks.pre_call, + ) + + with self.assertRaises(BlockingViolation): + _run( + guardrail.async_pre_call_hook( + user_api_key_dict=UserAPIKeyAuth(api_key="sk-test"), + cache=None, + data=request_data, + call_type="completion", + ) + ) + + slg_info = request_data["metadata"].get( + "standard_logging_guardrail_information" + ) + self.assertTrue( + slg_info, + "Guardrail must have recorded its information to request_data " + "BEFORE raising — otherwise the OTEL hook sees nothing", + ) + + # Now simulate the OTEL failure handler picking up this metadata + otel, _, exporter = _make_otel() + kwargs = _kwargs_with_guardrail( + entries=slg_info, + include_exception=True, + ) + start = datetime.now(timezone.utc) + end = start + timedelta(milliseconds=15) + otel._handle_failure(kwargs, response_obj=None, start_time=start, end_time=end) + + spans = exporter.get_finished_spans() + guardrail_spans = [s for s in spans if s.name == GUARDRAIL_SPAN_NAME] + self.assertEqual(len(guardrail_spans), 1) + self.assertEqual( + _attr(guardrail_spans[0], "guardrail_status"), + "guardrail_intervened", + ) + self.assertEqual( + _attr(guardrail_spans[0], "guardrail_name"), + "blocking-test", + ) + # End-to-end: the violation_categories the guardrail passed through + # tracing_detail must arrive as a queryable span attribute. + categories = _attr(guardrail_spans[0], "guardrail_violation_categories") + self.assertIsNotNone(categories) + self.assertIn("Fiduciary Advice", str(categories)) + self.assertIn("VIOLENCE", str(categories)) + + +if __name__ == "__main__": + unittest.main() diff --git a/tests/test_litellm/integrations/test_rubrik.py b/tests/test_litellm/integrations/test_rubrik.py new file mode 100644 index 00000000000..922d2fe8a15 --- /dev/null +++ b/tests/test_litellm/integrations/test_rubrik.py @@ -0,0 +1,1012 @@ +""" +Tests for the Rubrik LiteLLM plugin. + +Covers initialization, apply_guardrail tool blocking (all allowed, all blocked, +partial blocking, fail-open), batch logging, and Anthropic format handling. +""" + +import os +from typing import Any, Dict +from unittest.mock import AsyncMock, Mock, patch + +import httpx +import pytest + +from litellm.integrations.custom_guardrail import ModifyResponseException +from litellm.integrations.rubrik import RubrikLogger +from litellm.llms.custom_httpx.http_handler import AsyncHTTPHandler + +from tests.test_litellm.integrations.rubrik_test_helpers import ( + make_inputs_with_tools, + make_tool_call_dict, +) + + +@pytest.fixture +def mock_env(): + """Set up environment variables for testing.""" + with patch.dict( + os.environ, + { + "RUBRIK_WEBHOOK_URL": "http://localhost:8080", + "RUBRIK_API_KEY": "test-api-key", + }, + ): + yield + + +@pytest.fixture +def handler(mock_env): + """Create a RubrikLogger instance for testing.""" + with patch("asyncio.create_task", Mock()): + return RubrikLogger() + + +# -- Initialization ----------------------------------------------------------- + + +class TestInitialization: + def test_init_success(self, mock_env): + with patch("asyncio.create_task", Mock()): + handler = RubrikLogger() + assert ( + handler.tool_blocking_endpoint + == "http://localhost:8080/v1/after_completion/openai/v1" + ) + assert handler.logging_endpoint == "http://localhost:8080/v1/litellm/batch" + assert handler.key == "test-api-key" + assert isinstance(handler.tool_blocking_client, AsyncHTTPHandler) + + def test_init_with_constructor_params(self): + with patch("asyncio.create_task", Mock()): + handler = RubrikLogger(api_key="ctor-key", api_base="http://ctor-host:9090") + assert handler.key == "ctor-key" + assert ( + handler.tool_blocking_endpoint + == "http://ctor-host:9090/v1/after_completion/openai/v1" + ) + + def test_init_without_url(self): + with patch.dict(os.environ, {}, clear=True): + with pytest.raises(ValueError, match="Rubrik webhook URL not configured"): + RubrikLogger() + + def test_init_without_api_key(self): + with patch.dict( + os.environ, {"RUBRIK_WEBHOOK_URL": "http://localhost:8080"}, clear=True + ): + with patch("asyncio.create_task", Mock()): + assert RubrikLogger().key is None + + def test_trailing_slash_removed(self): + with patch.dict(os.environ, {"RUBRIK_WEBHOOK_URL": "http://localhost:8080/"}): + with patch("asyncio.create_task", Mock()): + assert ( + RubrikLogger().tool_blocking_endpoint + == "http://localhost:8080/v1/after_completion/openai/v1" + ) + + def test_v1_suffix_stripped_as_substring_not_charset(self): + with patch("asyncio.create_task", Mock()): + with patch.dict(os.environ, {"RUBRIK_WEBHOOK_URL": "http://host/v1"}): + assert ( + RubrikLogger().tool_blocking_endpoint + == "http://host/v1/after_completion/openai/v1" + ) + + with patch.dict(os.environ, {"RUBRIK_WEBHOOK_URL": "http://host/v11"}): + assert ( + RubrikLogger().tool_blocking_endpoint + == "http://host/v11/v1/after_completion/openai/v1" + ) + + def test_sampling_rate_fractional(self): + with patch("asyncio.create_task", Mock()): + with patch.dict( + os.environ, + {"RUBRIK_WEBHOOK_URL": "http://host", "RUBRIK_SAMPLING_RATE": "0.5"}, + ): + assert RubrikLogger().sampling_rate == 0.5 + + def test_sampling_rate_invalid_ignored(self): + with patch("asyncio.create_task", Mock()): + with patch.dict( + os.environ, + {"RUBRIK_WEBHOOK_URL": "http://host", "RUBRIK_SAMPLING_RATE": "abc"}, + ): + assert RubrikLogger().sampling_rate == 1.0 + + def test_sampling_rate_clamped(self): + with patch("asyncio.create_task", Mock()): + with patch.dict( + os.environ, + {"RUBRIK_WEBHOOK_URL": "http://host", "RUBRIK_SAMPLING_RATE": "2.0"}, + ): + assert RubrikLogger().sampling_rate == 1.0 + with patch.dict( + os.environ, + {"RUBRIK_WEBHOOK_URL": "http://host", "RUBRIK_SAMPLING_RATE": "-0.5"}, + ): + assert RubrikLogger().sampling_rate == 0.0 + + def test_batch_size_invalid_ignored(self): + with patch("asyncio.create_task", Mock()): + with patch.dict( + os.environ, + {"RUBRIK_WEBHOOK_URL": "http://host", "RUBRIK_BATCH_SIZE": "abc"}, + ): + # Should use default without crashing + assert isinstance(RubrikLogger().batch_size, int) + + def test_batch_size_valid(self): + with patch("asyncio.create_task", Mock()): + with patch.dict( + os.environ, + {"RUBRIK_WEBHOOK_URL": "http://host", "RUBRIK_BATCH_SIZE": "256"}, + ): + assert RubrikLogger().batch_size == 256 + + def test_init_outside_event_loop_does_not_raise(self): + """Instantiation without a running event loop must not raise RuntimeError.""" + with patch.dict( + os.environ, + {"RUBRIK_WEBHOOK_URL": "http://localhost:8080", "RUBRIK_API_KEY": "k"}, + ): + # Do NOT patch asyncio.create_task — the real call should be + # guarded and fall back gracefully when there is no event loop. + handler = RubrikLogger() + assert handler.tool_blocking_endpoint.startswith("http://localhost:8080") + # Without a running loop at init, the periodic flush task should be + # deferred so batches still get drained once a log event arrives. + assert handler._flush_task is None + + @pytest.mark.asyncio + async def test_periodic_flush_task_started_lazily_on_first_log(self, mock_env): + """Loggers instantiated outside an event loop must still start the + periodic flush task on first use to drain low-traffic batches.""" + # Simulate sync-init by hiding the running loop from the constructor. + with patch( + "litellm.integrations.rubrik.asyncio.get_running_loop", + side_effect=RuntimeError("no running loop"), + ): + handler = RubrikLogger() + assert handler._flush_task is None + + kwargs = { + "standard_logging_object": { + "messages": [{"role": "user", "content": "hi"}], + "id": "litellm-id", + }, + "litellm_call_id": "litellm-id", + "litellm_params": {}, + } + with patch.object(handler, "_log_batch_to_rubrik", AsyncMock()): + await handler.async_log_success_event(kwargs, None, None, None) + + assert handler._flush_task is not None + handler._flush_task.cancel() + + def test_event_hook_defaults_to_post_call_when_none_passed(self, mock_env): + """`initialize_guardrail` always passes ``event_hook=litellm_params.mode`` + (which is ``None`` when the user omits ``mode``). The logger must coerce + a None ``event_hook`` to ``post_call`` rather than leaving it as None, + which would otherwise cause the guardrail to run on every event hook.""" + from litellm.types.guardrails import GuardrailEventHooks + + with patch("asyncio.create_task", Mock()): + handler = RubrikLogger(event_hook=None) + assert handler.event_hook == GuardrailEventHooks.post_call + + def test_explicit_event_hook_preserved(self, mock_env): + from litellm.types.guardrails import GuardrailEventHooks + + with patch("asyncio.create_task", Mock()): + handler = RubrikLogger(event_hook=GuardrailEventHooks.pre_call) + assert handler.event_hook == GuardrailEventHooks.pre_call + + def test_default_on_defaults_to_true_when_none_passed(self, mock_env): + """`initialize_guardrail` always passes ``default_on=litellm_params.default_on`` + (which is ``None`` when the user omits ``default_on``). The logger must + coerce a None ``default_on`` to True, otherwise ``should_run_guardrail`` + (which checks ``self.default_on is True``) silently skips the guardrail.""" + with patch("asyncio.create_task", Mock()): + handler = RubrikLogger(default_on=None) + assert handler.default_on is True + + def test_explicit_default_on_false_preserved(self, mock_env): + """A user explicitly setting ``default_on: false`` in their guardrail + config must NOT be silently overridden to True.""" + with patch("asyncio.create_task", Mock()): + handler = RubrikLogger(default_on=False) + assert handler.default_on is False + + def test_explicit_default_on_true_preserved(self, mock_env): + with patch("asyncio.create_task", Mock()): + handler = RubrikLogger(default_on=True) + assert handler.default_on is True + + def test_headers_with_api_key(self, handler): + assert handler._headers["Authorization"] == "Bearer test-api-key" + assert handler._headers["Content-Type"] == "application/json" + + def test_headers_without_api_key(self): + with patch.dict(os.environ, {"RUBRIK_WEBHOOK_URL": "http://host"}, clear=True): + with patch("asyncio.create_task", Mock()): + h = RubrikLogger() + assert "Authorization" not in h._headers + + +# -- Batch Logging ------------------------------------------------------------ + + +@pytest.mark.asyncio +class TestBatchLogging: + async def test_log_success_event_appends_to_queue(self, handler): + kwargs = { + "standard_logging_object": { + "messages": [{"role": "user", "content": "hi"}], + "response": "hello", + }, + } + await handler.async_log_success_event( + kwargs=kwargs, response_obj=None, start_time=None, end_time=None + ) + assert len(handler.log_queue) == 1 + + async def test_log_failure_event_appends_to_queue(self, handler): + kwargs = { + "standard_logging_object": { + "messages": [{"role": "user", "content": "hi"}], + "response": "error", + }, + } + await handler.async_log_failure_event( + kwargs=kwargs, response_obj=None, start_time=None, end_time=None + ) + assert len(handler.log_queue) == 1 + + async def test_log_success_event_sampling_skips(self, handler): + handler.sampling_rate = 0.0 + kwargs = { + "standard_logging_object": { + "messages": [{"role": "user", "content": "hi"}], + "response": "hello", + }, + } + await handler.async_log_success_event( + kwargs=kwargs, response_obj=None, start_time=None, end_time=None + ) + assert len(handler.log_queue) == 0 + + async def test_flush_queue_sends_batch(self, handler): + handler.log_queue = [{"msg": "a"}, {"msg": "b"}] + mock_response = Mock() + mock_response.status_code = 200 + handler.async_httpx_client = AsyncMock() + handler.async_httpx_client.post = AsyncMock(return_value=mock_response) + await handler.flush_queue() + handler.async_httpx_client.post.assert_called_once() + assert len(handler.log_queue) == 0 + + async def test_flush_queue_preserves_events_added_during_send(self, handler): + handler.log_queue = [{"msg": "a"}, {"msg": "b"}] + + async def mock_post(*_args, **_kwargs): + handler.log_queue.append({"msg": "c"}) + mock_response = Mock() + mock_response.raise_for_status = Mock() + return mock_response + + handler.async_httpx_client = AsyncMock() + handler.async_httpx_client.post = mock_post + + await handler.flush_queue() + + assert handler.log_queue == [{"msg": "c"}] + + async def test_async_send_batch_does_not_drain_events(self, handler): + handler.log_queue = [{"msg": "a"}, {"msg": "b"}] + + async def mock_post(*_args, **_kwargs): + handler.log_queue.append({"msg": "c"}) + mock_response = Mock() + mock_response.raise_for_status = Mock() + return mock_response + + handler.async_httpx_client = AsyncMock() + handler.async_httpx_client.post = mock_post + + await handler.async_send_batch() + + assert handler.log_queue == [{"msg": "a"}, {"msg": "b"}, {"msg": "c"}] + + async def test_log_batch_error_does_not_crash_and_preserves_events(self, handler): + """A failed batch send must not crash the caller AND must preserve the + original events in the queue so they can be retried on the next flush. + Previously the events were silently dropped on HTTP 5xx / network errors. + """ + handler.log_queue = [{"msg": "a"}] + mock_response = Mock() + mock_response.status_code = 500 + mock_response.text = "Internal Server Error" + mock_response.raise_for_status = Mock( + side_effect=httpx.HTTPStatusError( + "err", request=Mock(), response=mock_response + ) + ) + handler.async_httpx_client = AsyncMock() + handler.async_httpx_client.post = AsyncMock(return_value=mock_response) + await handler.flush_queue() + assert handler.log_queue == [{"msg": "a"}] + + async def test_log_batch_network_error_preserves_events(self, handler): + """Network/timeout errors must also preserve the in-flight events.""" + handler.log_queue = [{"msg": "a"}, {"msg": "b"}] + handler.async_httpx_client = AsyncMock() + handler.async_httpx_client.post = AsyncMock( + side_effect=httpx.TimeoutException("timeout") + ) + await handler.flush_queue() + assert handler.log_queue == [{"msg": "a"}, {"msg": "b"}] + + async def test_enqueue_drops_oldest_when_queue_exceeds_max_size(self, handler): + """A sustained Rubrik webhook outage must not let the in-memory retry + queue grow without bound. Once max_queue_size is exceeded, the oldest + events are dropped to make room for new ones.""" + handler.max_queue_size = 3 + handler.batch_size = 10**6 # disable size-triggered flush + handler.flush_queue = AsyncMock() + for i in range(5): + await handler._enqueue_log_event( + kwargs={ + "standard_logging_object": { + "messages": [{"role": "user", "content": f"hi-{i}"}], + "response": "hello", + }, + }, + event_type="success", + ) + assert len(handler.log_queue) == 3 + retained = [item["messages"][0]["content"] for item in handler.log_queue] + assert retained == ["hi-2", "hi-3", "hi-4"] + + async def test_log_batch_failure_preserves_events_added_during_send(self, handler): + """Failure must preserve both the snapshot AND events appended mid-flush.""" + handler.log_queue = [{"msg": "a"}, {"msg": "b"}] + + async def mock_post(*_args, **_kwargs): + handler.log_queue.append({"msg": "c"}) + mock_response = Mock() + mock_response.status_code = 500 + mock_response.text = "boom" + mock_response.raise_for_status = Mock( + side_effect=httpx.HTTPStatusError( + "err", request=Mock(), response=mock_response + ) + ) + return mock_response + + handler.async_httpx_client = AsyncMock() + handler.async_httpx_client.post = mock_post + + await handler.flush_queue() + assert handler.log_queue == [{"msg": "a"}, {"msg": "b"}, {"msg": "c"}] + + async def test_system_prompt_prepended_to_messages(self, handler): + kwargs = { + "standard_logging_object": { + "messages": [{"role": "user", "content": "hi"}], + "response": "hello", + }, + "system": "You are a helpful assistant.", + } + await handler.async_log_success_event( + kwargs=kwargs, response_obj=None, start_time=None, end_time=None + ) + assert len(handler.log_queue) == 1 + msgs = handler.log_queue[0]["messages"] + assert msgs[0]["role"] == "system" + assert msgs[0]["content"] == "You are a helpful assistant." + + async def test_system_prompt_with_dict_messages(self, handler): + kwargs = { + "standard_logging_object": { + "messages": {"role": "user", "content": "hi"}, + "response": "hello", + }, + "system": "Be concise.", + } + await handler.async_log_success_event( + kwargs=kwargs, response_obj=None, start_time=None, end_time=None + ) + assert len(handler.log_queue) == 1 + msgs = handler.log_queue[0]["messages"] + assert isinstance(msgs, list) + assert msgs[0]["role"] == "system" + assert msgs[1] == {"role": "user", "content": "hi"} + + async def test_anthropic_id_normalization(self, handler): + kwargs = { + "standard_logging_object": { + "id": "chatcmpl-original", + "messages": [{"role": "user", "content": "hi"}], + "response": "hello", + }, + "litellm_params": { + "proxy_server_request": { + "url": "http://proxy/v1/messages", + }, + }, + "litellm_call_id": "litellm-call-123", + } + await handler.async_log_success_event( + kwargs=kwargs, response_obj=None, start_time=None, end_time=None + ) + assert handler.log_queue[0]["id"] == "litellm-call-123" + + async def test_non_anthropic_id_unchanged(self, handler): + kwargs = { + "standard_logging_object": { + "id": "chatcmpl-original", + "messages": [{"role": "user", "content": "hi"}], + "response": "hello", + }, + "litellm_params": { + "proxy_server_request": { + "url": "http://proxy/v1/chat/completions", + }, + }, + "litellm_call_id": "litellm-call-123", + } + await handler.async_log_success_event( + kwargs=kwargs, response_obj=None, start_time=None, end_time=None + ) + assert handler.log_queue[0]["id"] == "chatcmpl-original" + + async def test_payload_deep_copied_not_mutated(self, handler): + """Verify the shared standard_logging_object is not mutated.""" + original_payload = { + "id": "original-id", + "messages": [{"role": "user", "content": "hi"}], + "response": "hello", + } + kwargs = { + "standard_logging_object": original_payload, + "system": "System prompt.", + } + await handler.async_log_success_event( + kwargs=kwargs, response_obj=None, start_time=None, end_time=None + ) + # Original payload should NOT have been mutated + assert original_payload["id"] == "original-id" + assert len(original_payload["messages"]) == 1 + + +# -- Tool Blocking (apply_guardrail) ------------------------------------------ + + +def _mock_service_response(response_json): + """Create a mock tool blocking client that returns the given JSON.""" + + async def mock_post(*_args, **kwargs): + mock_resp = Mock() + mock_resp.json.return_value = response_json + mock_resp.raise_for_status = Mock() + return mock_resp + + mock_client = AsyncMock() + mock_client.post = mock_post + return mock_client + + +def _echo_service(): + """Create a mock tool blocking client that echoes the payload back.""" + + async def mock_post(*_args, **kwargs): + mock_resp = Mock() + mock_resp.json.return_value = kwargs.get("json", {}).get("response", {}) + mock_resp.raise_for_status = Mock() + return mock_resp + + mock_client = AsyncMock() + mock_client.post = mock_post + return mock_client + + +@pytest.mark.asyncio +class TestApplyGuardrail: + async def test_skips_requests(self, handler): + inputs = make_inputs_with_tools([make_tool_call_dict("call_1", "test_tool")]) + result = await handler.apply_guardrail( + inputs=inputs, request_data={}, input_type="request" + ) + assert result is inputs + + async def test_no_tool_calls(self, handler): + from litellm.types.utils import GenericGuardrailAPIInputs + + inputs = GenericGuardrailAPIInputs(texts=["hello"]) + result = await handler.apply_guardrail( + inputs=inputs, request_data={}, input_type="response" + ) + assert result is inputs + + async def test_all_allowed(self, handler): + tc1 = make_tool_call_dict("call_1", "get_weather") + tc2 = make_tool_call_dict("call_2", "get_time") + inputs = make_inputs_with_tools([tc1, tc2]) + + handler.tool_blocking_client = _echo_service() + + result = await handler.apply_guardrail( + inputs=inputs, request_data={}, input_type="response" + ) + assert result is inputs + + async def test_all_blocked(self, handler): + tc1 = make_tool_call_dict("call_1", "delete_table") + tc2 = make_tool_call_dict("call_2", "drop_database") + inputs = make_inputs_with_tools([tc1, tc2]) + + handler.tool_blocking_client = _mock_service_response( + { + "choices": [ + { + "message": { + "role": "assistant", + "content": "Tool blocked by policy", + "tool_calls": [], + } + } + ], + } + ) + + with pytest.raises(ModifyResponseException) as exc_info: + await handler.apply_guardrail( + inputs=inputs, request_data={}, input_type="response" + ) + assert "Tool blocked by policy" in exc_info.value.message + + async def test_partial_blocking(self, handler): + tc_blocked = make_tool_call_dict("call_A", "blocked_tool") + tc_allowed = make_tool_call_dict("call_B", "allowed_tool") + inputs = make_inputs_with_tools([tc_blocked, tc_allowed]) + + async def mock_post(*_args, **kwargs): + payload = kwargs.get("json", {}).get("response", {}) + all_tcs = payload["choices"][0]["message"]["tool_calls"] + allowed = [tc for tc in all_tcs if tc.get("id") == "call_B"] + mock_resp = Mock() + mock_resp.json.return_value = { + "choices": [ + { + "message": { + "role": "assistant", + "content": "blocked", + "tool_calls": allowed, + } + } + ], + } + mock_resp.raise_for_status = Mock() + return mock_resp + + mock_client = AsyncMock() + mock_client.post = mock_post + handler.tool_blocking_client = mock_client + + with pytest.raises(ModifyResponseException): + await handler.apply_guardrail( + inputs=inputs, request_data={}, input_type="response" + ) + + async def test_service_failure_fail_open(self, handler): + tc1 = make_tool_call_dict("call_1", "test_tool") + inputs = make_inputs_with_tools([tc1]) + + mock_client = AsyncMock() + mock_client.post = AsyncMock(side_effect=httpx.TimeoutException("Timeout")) + handler.tool_blocking_client = mock_client + + result = await handler.apply_guardrail( + inputs=inputs, request_data={}, input_type="response" + ) + assert result is inputs + + async def test_service_empty_choices_fail_open(self, handler): + tc1 = make_tool_call_dict("call_1", "test_tool") + inputs = make_inputs_with_tools([tc1]) + + handler.tool_blocking_client = _mock_service_response({"choices": []}) + + result = await handler.apply_guardrail( + inputs=inputs, request_data={}, input_type="response" + ) + assert result is inputs + + async def test_blocking_service_payload_format(self, handler): + tc1 = make_tool_call_dict("call_1", "get_weather", '{"location": "SF"}') + tc2 = make_tool_call_dict("call_2", "send_email", '{"to": "user@example.com"}') + inputs = make_inputs_with_tools([tc1, tc2]) + + captured_payload: Dict[str, Any] = {} + + async def mock_post(*_args, **kwargs): + captured_payload.update(kwargs.get("json", {})) + mock_resp = Mock() + mock_resp.json.return_value = captured_payload.get("response", {}) + mock_resp.raise_for_status = Mock() + return mock_resp + + mock_client = AsyncMock() + mock_client.post = mock_post + handler.tool_blocking_client = mock_client + + await handler.apply_guardrail( + inputs=inputs, request_data={}, input_type="response" + ) + + # Verify envelope structure + assert "request" in captured_payload + assert "response" in captured_payload + + response_data = captured_payload["response"] + message = response_data["choices"][0]["message"] + assert message["role"] == "assistant" + assert len(message["tool_calls"]) == 2 + assert message["tool_calls"][0]["id"] == "call_1" + assert message["tool_calls"][0]["function"]["name"] == "get_weather" + assert message["tool_calls"][1]["id"] == "call_2" + assert message["tool_calls"][1]["function"]["name"] == "send_email" + + async def test_request_data_included_in_envelope(self, handler): + tc = make_tool_call_dict("call_1", "test_tool") + inputs = make_inputs_with_tools([tc]) + + captured_payload: Dict[str, Any] = {} + + async def mock_post(*_args, **kwargs): + captured_payload.update(kwargs.get("json", {})) + mock_resp = Mock() + mock_resp.json.return_value = captured_payload.get("response", {}) + mock_resp.raise_for_status = Mock() + return mock_resp + + mock_client = AsyncMock() + mock_client.post = mock_post + handler.tool_blocking_client = mock_client + + logging_obj = Mock() + logging_obj.model_call_details = { + "messages": [{"role": "user", "content": "hi"}], + "model": "gpt-4", + "litellm_params": { + "proxy_server_request": {"url": "/chat/completions"}, + }, + } + + await handler.apply_guardrail( + inputs=inputs, + request_data={}, + input_type="response", + logging_obj=logging_obj, + ) + + req = captured_payload["request"] + assert req["model"] == "gpt-4" + assert req["messages"] == [{"role": "user", "content": "hi"}] + + async def test_proxy_server_request_headers_stripped(self, handler): + tc = make_tool_call_dict("call_1", "test_tool") + inputs = make_inputs_with_tools([tc]) + + captured_payload: Dict[str, Any] = {} + + async def mock_post(*_args, **kwargs): + captured_payload.update(kwargs.get("json", {})) + mock_resp = Mock() + mock_resp.json.return_value = captured_payload.get("response", {}) + mock_resp.raise_for_status = Mock() + return mock_resp + + mock_client = AsyncMock() + mock_client.post = mock_post + handler.tool_blocking_client = mock_client + + logging_obj = Mock() + logging_obj.model_call_details = { + "messages": [{"role": "user", "content": "hi"}], + "model": "gpt-4", + "litellm_params": { + "proxy_server_request": { + "url": "/chat/completions", + "method": "POST", + "headers": { + "authorization": "Bearer sk-litellm-secret", + "cookie": "session=abc", + "x-api-key": "leaked-key", + }, + "body": {"api_key": "sk-upstream-secret"}, + }, + }, + } + + await handler.apply_guardrail( + inputs=inputs, + request_data={}, + input_type="response", + logging_obj=logging_obj, + ) + + forwarded = captured_payload["request"]["proxy_server_request"] + assert forwarded == {"url": "/chat/completions", "method": "POST"} + + +# -- Anthropic format ---------------------------------------------------------- + + +@pytest.mark.asyncio +class TestApplyGuardrailAnthropicFormat: + """Verify blocking works correctly regardless of original provider format. + + The framework converts Anthropic tool_use blocks to OpenAI-format + tool_calls before calling apply_guardrail. + """ + + async def test_single_tool_allowed(self, handler): + tc = make_tool_call_dict( + "toolu_123", "get_weather", '{"location": "Portland, OR"}' + ) + inputs = make_inputs_with_tools([tc], texts=["I'll check the weather."]) + + handler.tool_blocking_client = _echo_service() + + result = await handler.apply_guardrail( + inputs=inputs, request_data={}, input_type="response" + ) + assert result is inputs + + async def test_single_tool_blocked(self, handler): + tc = make_tool_call_dict("toolu_123", "dangerous_tool", '{"arg": "value"}') + inputs = make_inputs_with_tools([tc]) + + handler.tool_blocking_client = _mock_service_response( + { + "choices": [ + { + "message": { + "role": "assistant", + "content": "blocked", + "tool_calls": [], + } + } + ], + } + ) + + with pytest.raises(ModifyResponseException): + await handler.apply_guardrail( + inputs=inputs, request_data={}, input_type="response" + ) + + async def test_text_only_response_no_blocking(self, handler): + from litellm.types.utils import GenericGuardrailAPIInputs + + inputs = GenericGuardrailAPIInputs(texts=["Hello! I'm Claude."]) + + mock_client = AsyncMock() + mock_client.post = AsyncMock() + handler.tool_blocking_client = mock_client + + result = await handler.apply_guardrail( + inputs=inputs, request_data={}, input_type="response" + ) + + assert result is inputs + mock_client.post.assert_not_called() + + async def test_service_failure_preserves_tools(self, handler): + tc = make_tool_call_dict("toolu_123", "get_weather", '{"location": "SF"}') + inputs = make_inputs_with_tools([tc]) + + mock_client = AsyncMock() + mock_client.post = AsyncMock(side_effect=httpx.TimeoutException("Timeout")) + handler.tool_blocking_client = mock_client + + result = await handler.apply_guardrail( + inputs=inputs, request_data={}, input_type="response" + ) + assert result is inputs + + +# -- Normalize tool calls ------------------------------------------------------ + + +class TestNormalizeToolCalls: + def test_dict_input(self): + tc = make_tool_call_dict("call_1", "test", '{"a": 1}') + result = RubrikLogger._normalize_tool_calls([tc]) + assert len(result) == 1 + assert result[0].id == "call_1" + assert result[0].function.name == "test" + assert result[0].function.arguments == '{"a": 1}' + + def test_typed_object_input(self): + from litellm.types.utils import ChatCompletionMessageToolCall, Function + + tc = ChatCompletionMessageToolCall( + id="call_2", + type="function", + function=Function(name="fn", arguments="{}"), + ) + result = RubrikLogger._normalize_tool_calls([tc]) + assert len(result) == 1 + assert result[0].id == "call_2" + assert result[0].function.name == "fn" + + def test_unsupported_type_raises(self): + with pytest.raises(TypeError, match="Cannot normalize"): + RubrikLogger._normalize_tool_calls(["not_a_tool_call"]) + + +# -- Extract blocked tools ----------------------------------------------------- + + +class TestExtractBlockedTools: + def test_all_allowed_returns_none(self): + from litellm.types.utils import ChatCompletionMessageToolCall, Function + + tc = ChatCompletionMessageToolCall( + id="call_1", type="function", function=Function(name="fn", arguments="{}") + ) + service_resp = { + "choices": [ + { + "message": { + "tool_calls": [{"id": "call_1"}], + "content": "", + } + } + ] + } + result = RubrikLogger._extract_blocked_tools(service_resp, [tc]) + assert result is None + + def test_some_blocked_returns_explanation(self): + from litellm.types.utils import ChatCompletionMessageToolCall, Function + + tc1 = ChatCompletionMessageToolCall( + id="call_1", + type="function", + function=Function(name="fn1", arguments="{}"), + ) + tc2 = ChatCompletionMessageToolCall( + id="call_2", + type="function", + function=Function(name="fn2", arguments="{}"), + ) + service_resp = { + "choices": [ + { + "message": { + "tool_calls": [{"id": "call_1"}], + "content": "blocked fn2", + } + } + ] + } + result = RubrikLogger._extract_blocked_tools(service_resp, [tc1, tc2]) + assert result is not None + assert "blocked fn2" in result + + def test_empty_choices_raises(self): + with pytest.raises(Exception, match="empty response"): + RubrikLogger._extract_blocked_tools({"choices": []}, []) + + def test_null_tool_calls_treated_as_all_blocked(self): + from litellm.types.utils import ChatCompletionMessageToolCall, Function + + tc = ChatCompletionMessageToolCall( + id="call_1", type="function", function=Function(name="fn", arguments="{}") + ) + service_resp = { + "choices": [ + { + "message": { + "tool_calls": None, + "content": "blocked everything", + } + } + ] + } + result = RubrikLogger._extract_blocked_tools(service_resp, [tc]) + assert result is not None + assert "blocked everything" in result + + def test_duplicate_ids_block_when_only_one_returned(self): + from litellm.types.utils import ChatCompletionMessageToolCall, Function + + tc1 = ChatCompletionMessageToolCall( + id="call_dup", + type="function", + function=Function(name="fn", arguments="{}"), + ) + tc2 = ChatCompletionMessageToolCall( + id="call_dup", + type="function", + function=Function(name="fn", arguments="{}"), + ) + service_resp = { + "choices": [ + { + "message": { + "tool_calls": [{"id": "call_dup"}], + "content": "blocked duplicate", + } + } + ] + } + result = RubrikLogger._extract_blocked_tools(service_resp, [tc1, tc2]) + assert result is not None + assert "blocked duplicate" in result + + +# -- Sanitize proxy server request ------------------------------------------- + + +class TestSanitizeProxyServerRequest: + def test_drops_headers_and_body(self): + proxy_request = { + "url": "/chat/completions", + "method": "POST", + "headers": { + "authorization": "Bearer sk-litellm-secret", + "cookie": "session=abc", + "content-type": "application/json", + }, + "body": {"api_key": "sk-upstream-secret", "model": "gpt-4"}, + } + result = RubrikLogger._sanitize_proxy_server_request(proxy_request) + assert result == {"url": "/chat/completions", "method": "POST"} + + def test_none_passthrough(self): + assert RubrikLogger._sanitize_proxy_server_request(None) is None + + def test_non_dict_passthrough(self): + assert RubrikLogger._sanitize_proxy_server_request("not a dict") == "not a dict" + + def test_partial_dict(self): + result = RubrikLogger._sanitize_proxy_server_request({"url": "/v1/messages"}) + assert result == {"url": "/v1/messages"} + + +# -- Resolve model ------------------------------------------------------------- + + +class TestResolveModel: + def test_model_from_response(self): + from unittest.mock import Mock + + response = Mock() + response.model = "gpt-4" + result = RubrikLogger._resolve_model({"response": response}, {}) + assert result == "gpt-4" + + def test_model_from_call_details(self): + result = RubrikLogger._resolve_model({}, {"model": "claude-3"}) + assert result == "claude-3" + + def test_fallback_to_unknown(self): + result = RubrikLogger._resolve_model({}, {}) + assert result == "unknown" + + def test_empty_model_on_response_returns_unknown(self): + from unittest.mock import Mock + + response = Mock() + response.model = "" + result = RubrikLogger._resolve_model( + {"response": response}, {"model": "fallback"} + ) + assert result == "unknown" diff --git a/tests/test_litellm/litellm_core_utils/test_litellm_logging.py b/tests/test_litellm/litellm_core_utils/test_litellm_logging.py index c6961477a58..07ab29c5231 100644 --- a/tests/test_litellm/litellm_core_utils/test_litellm_logging.py +++ b/tests/test_litellm/litellm_core_utils/test_litellm_logging.py @@ -2078,6 +2078,146 @@ async def test_async_success_handler_preserves_response_cost_for_pass_through_en assert slo["response_cost"] > 0 +def test_process_hidden_params_recalculates_cost_after_failure_handler_zero(): + """ + Regression: PR #21844 preserved response_cost=0 set by failure_handler on failed + router retry attempts, so a later successful response with usage logged $0 spend. + """ + from datetime import datetime + + import litellm + from litellm.litellm_core_utils.litellm_logging import Logging as LiteLLMLoggingObj + from litellm.types.utils import ModelResponse, Usage + + logging_obj = LiteLLMLoggingObj( + model="openai/gpt-4o-mini", + messages=[{"role": "user", "content": "hi"}], + stream=False, + call_type="acompletion", + start_time=datetime.now(), + litellm_call_id="test-retry-zero-cost", + function_id="test-retry-zero-cost", + ) + logging_obj.model_call_details["litellm_params"] = {"model": "openai/gpt-4o-mini"} + logging_obj.optional_params = {} + + err = litellm.RateLimitError( + message="rate limit", + llm_provider="openai", + model="openai/gpt-4o-mini", + ) + for _ in range(2): + logging_obj._failure_handler_helper_fn( + exception=err, + traceback_exception="", + start_time=datetime.now(), + end_time=datetime.now(), + ) + assert logging_obj.model_call_details.get("response_cost") == 0 + + result = ModelResponse( + id="success", + choices=[{"message": {"role": "assistant", "content": "ok"}}], + usage=Usage(prompt_tokens=9698, completion_tokens=30, total_tokens=9728), + ) + logging_obj._process_hidden_params_and_response_cost( + result, datetime.now(), datetime.now() + ) + + cost = logging_obj.model_call_details.get("response_cost") + assert cost is not None and cost > 0 + slo = logging_obj.model_call_details.get("standard_logging_object") or {} + assert slo.get("response_cost", 0) > 0 + + +def test_process_hidden_params_preserves_zero_cost_in_hidden_params(): + """Pass-through handlers often set response_cost on result._hidden_params (including 0).""" + from datetime import datetime + + from litellm.litellm_core_utils.litellm_logging import Logging as LiteLLMLoggingObj + from litellm.types.utils import ModelResponse, Usage + + logging_obj = LiteLLMLoggingObj( + model="gemini-2.5-flash-lite", + messages=[{"role": "user", "content": "test"}], + stream=False, + call_type="pass_through_endpoint", + start_time=datetime.now(), + litellm_call_id="test-hidden-zero-cost", + function_id="test-hidden-zero-cost", + ) + logging_obj.model_call_details["litellm_params"] = { + "model": "gemini-2.5-flash-lite" + } + logging_obj.optional_params = {} + + result = ModelResponse( + id="batch-pending", + choices=[{"message": {"role": "assistant", "content": "pending"}}], + usage=Usage(prompt_tokens=100, completion_tokens=10, total_tokens=110), + ) + result._hidden_params = {"response_cost": 0.0} + + logging_obj._process_hidden_params_and_response_cost( + result, datetime.now(), datetime.now() + ) + + assert logging_obj.model_call_details.get("response_cost") == 0.0 + slo = logging_obj.model_call_details.get("standard_logging_object") or {} + assert slo.get("response_cost") == 0.0 + + +def test_process_hidden_params_uses_hidden_params_cost_after_failure_handler_zero(): + """After retry failures pin model_call_details to 0, success cost on _hidden_params wins.""" + from datetime import datetime + + import litellm + from litellm.litellm_core_utils.litellm_logging import Logging as LiteLLMLoggingObj + from litellm.types.utils import ModelResponse, Usage + + logging_obj = LiteLLMLoggingObj( + model="openai/gpt-4o-mini", + messages=[{"role": "user", "content": "hi"}], + stream=False, + call_type="acompletion", + start_time=datetime.now(), + litellm_call_id="test-retry-hidden-cost", + function_id="test-retry-hidden-cost", + ) + logging_obj.model_call_details["litellm_params"] = {"model": "openai/gpt-4o-mini"} + logging_obj.optional_params = {} + + err = litellm.RateLimitError( + message="rate limit", + llm_provider="openai", + model="openai/gpt-4o-mini", + ) + for _ in range(2): + logging_obj._failure_handler_helper_fn( + exception=err, + traceback_exception="", + start_time=datetime.now(), + end_time=datetime.now(), + ) + assert logging_obj.model_call_details.get("response_cost") == 0 + + passthrough_cost = 0.00042 + result = ModelResponse( + id="success", + choices=[{"message": {"role": "assistant", "content": "ok"}}], + usage=Usage(prompt_tokens=9698, completion_tokens=30, total_tokens=9728), + ) + result._hidden_params = {"response_cost": passthrough_cost} + + logging_obj._process_hidden_params_and_response_cost( + result, datetime.now(), datetime.now() + ) + + assert logging_obj.model_call_details.get("response_cost") == passthrough_cost + slo = logging_obj.model_call_details.get("standard_logging_object") or {} + assert slo.get("response_cost") == passthrough_cost + + def test_function_setup_litellm_metadata_populates_metadata(): """ Test that function_setup() properly handles litellm_metadata (used by /v1/messages, diff --git a/tests/test_litellm/llms/bedrock/chat/invoke_transformations/test_bedrock_chat_invoke_transformations_anthropic_claude3_transformation.py b/tests/test_litellm/llms/bedrock/chat/invoke_transformations/test_bedrock_chat_invoke_transformations_anthropic_claude3_transformation.py index 4495e3f4101..b2e254901f4 100644 --- a/tests/test_litellm/llms/bedrock/chat/invoke_transformations/test_bedrock_chat_invoke_transformations_anthropic_claude3_transformation.py +++ b/tests/test_litellm/llms/bedrock/chat/invoke_transformations/test_bedrock_chat_invoke_transformations_anthropic_claude3_transformation.py @@ -2,6 +2,7 @@ import asyncio import json import os import sys +from unittest.mock import patch import pytest @@ -429,6 +430,31 @@ def test_output_config_forwarded_for_bedrock_chat_invoke_request(): assert result["max_tokens"] == 100 +def test_bedrock_chat_invoke_checks_output_config_support_with_bedrock_provider(): + config = AmazonAnthropicClaudeConfig() + messages = [{"role": "user", "content": "test"}] + optional_params = {"max_tokens": 100, "output_config": {"effort": "high"}} + + with patch( + "litellm.llms.bedrock.chat.invoke_transformations.anthropic_claude3_transformation._supports_factory", + return_value=True, + ) as mock_supports_factory: + result = config.transform_request( + model="us.anthropic.claude-opus-4-7", + messages=messages, + optional_params=optional_params, + litellm_params={}, + headers={}, + ) + + mock_supports_factory.assert_called_once_with( + model="us.anthropic.claude-opus-4-7", + custom_llm_provider="bedrock", + key="supports_output_config", + ) + assert result["output_config"] == {"effort": "high"} + + def test_output_format_removed_from_bedrock_invoke_request(): """ Test that output_format parameter is removed from Bedrock Invoke requests. diff --git a/tests/test_litellm/llms/bedrock/messages/invoke_transformations/test_anthropic_claude3_transformation.py b/tests/test_litellm/llms/bedrock/messages/invoke_transformations/test_anthropic_claude3_transformation.py index 9ecdad1fcff..2e315a535f0 100644 --- a/tests/test_litellm/llms/bedrock/messages/invoke_transformations/test_anthropic_claude3_transformation.py +++ b/tests/test_litellm/llms/bedrock/messages/invoke_transformations/test_anthropic_claude3_transformation.py @@ -592,8 +592,15 @@ def test_remove_scope_from_cache_control(): assert request["messages"][0]["content"][0]["cache_control"]["type"] == "ephemeral" -def test_bedrock_messages_forwards_output_config(): - """Bedrock Invoke /v1/messages forwards ``output_config`` for adaptive Claude models.""" +def test_bedrock_messages_strips_output_config(): + """ + Ensure output_config is stripped from the request for models that do not + support it. + + Regression test for: https://github.com/BerriAI/litellm/issues/22797 + """ + from unittest.mock import patch + from litellm.types.router import GenericLiteLLMParams cfg = AmazonAnthropicClaudeMessagesConfig() @@ -605,21 +612,129 @@ def test_bedrock_messages_forwards_output_config(): }, } - result = cfg.transform_anthropic_messages_request( - model="anthropic.claude-opus-4-7", - messages=messages, - anthropic_messages_optional_request_params=optional_params, - litellm_params=GenericLiteLLMParams(), - headers={}, + with patch( + "litellm.llms.bedrock.messages.invoke_transformations.anthropic_claude3_transformation._supports_factory", + return_value=False, + ): + result = cfg.transform_anthropic_messages_request( + model="anthropic.claude-3-haiku-20240307-v1:0", + messages=messages, + anthropic_messages_optional_request_params=optional_params, + litellm_params=GenericLiteLLMParams(), + headers={}, + ) + + assert ( + "output_config" not in result + ), "output_config should be stripped for models that don't support it" + assert result.get("max_tokens") == 4096 + + +def test_bedrock_messages_preserves_output_config_for_claude_4_6(): + """ + Ensure output_config is preserved for models that support it on Bedrock Invoke. + """ + from unittest.mock import patch + + from litellm.types.router import GenericLiteLLMParams + + cfg = AmazonAnthropicClaudeMessagesConfig() + messages = [{"role": "user", "content": [{"type": "text", "text": "Hello"}]}] + optional_params = { + "max_tokens": 4096, + "output_config": { + "effort": "high", + }, + } + + with patch( + "litellm.llms.bedrock.messages.invoke_transformations.anthropic_claude3_transformation._supports_factory", + return_value=True, + ): + result = cfg.transform_anthropic_messages_request( + model="anthropic.claude-opus-4-6-v1", + messages=messages, + anthropic_messages_optional_request_params=optional_params, + litellm_params=GenericLiteLLMParams(), + headers={}, + ) + + assert ( + "output_config" in result + ), "output_config should be preserved for supported models" + assert result["output_config"] == {"effort": "high"} + assert result.get("max_tokens") == 4096 + + +def test_bedrock_messages_checks_output_config_support_with_bedrock_provider(): + from unittest.mock import patch + + from litellm.types.router import GenericLiteLLMParams + + cfg = AmazonAnthropicClaudeMessagesConfig() + messages = [{"role": "user", "content": [{"type": "text", "text": "Hello"}]}] + optional_params = { + "max_tokens": 4096, + "output_config": { + "effort": "high", + }, + } + + with patch( + "litellm.llms.bedrock.messages.invoke_transformations.anthropic_claude3_transformation._supports_factory", + return_value=True, + ) as mock_supports_factory: + result = cfg.transform_anthropic_messages_request( + model="us.anthropic.claude-opus-4-7", + messages=messages, + anthropic_messages_optional_request_params=optional_params, + litellm_params=GenericLiteLLMParams(), + headers={}, + ) + + mock_supports_factory.assert_called_with( + model="us.anthropic.claude-opus-4-7", + custom_llm_provider="bedrock", + key="supports_output_config", ) + assert result["output_config"] == {"effort": "high"} + + +def test_bedrock_messages_forwards_output_config(): + """Bedrock Invoke /v1/messages forwards ``output_config`` for supported models.""" + from unittest.mock import patch + + from litellm.types.router import GenericLiteLLMParams + + cfg = AmazonAnthropicClaudeMessagesConfig() + messages = [{"role": "user", "content": [{"type": "text", "text": "Hello"}]}] + optional_params = { + "max_tokens": 4096, + "output_config": { + "effort": "high", + }, + } + + with patch( + "litellm.llms.bedrock.messages.invoke_transformations.anthropic_claude3_transformation._supports_factory", + return_value=True, + ): + result = cfg.transform_anthropic_messages_request( + model="anthropic.claude-opus-4-7", + messages=messages, + anthropic_messages_optional_request_params=optional_params, + litellm_params=GenericLiteLLMParams(), + headers={}, + ) assert result.get("output_config") == {"effort": "high"} - # Other params should be preserved assert result.get("max_tokens") == 4096 def test_bedrock_messages_forwards_output_config_with_output_format(): """``output_config`` is forwarded; ``output_format`` is converted to inline schema.""" + from unittest.mock import patch + from litellm.types.router import GenericLiteLLMParams cfg = AmazonAnthropicClaudeMessagesConfig() @@ -636,39 +751,60 @@ def test_bedrock_messages_forwards_output_config_with_output_format(): }, } - result = cfg.transform_anthropic_messages_request( - model="anthropic.claude-opus-4-7", - messages=messages, - anthropic_messages_optional_request_params=optional_params, - litellm_params=GenericLiteLLMParams(), - headers={}, - ) + with patch( + "litellm.llms.bedrock.messages.invoke_transformations.anthropic_claude3_transformation._supports_factory", + return_value=True, + ): + result = cfg.transform_anthropic_messages_request( + model="anthropic.claude-opus-4-7", + messages=messages, + anthropic_messages_optional_request_params=optional_params, + litellm_params=GenericLiteLLMParams(), + headers={}, + ) assert result.get("output_config") == {"effort": "low"} assert "output_format" not in result -def test_bedrock_messages_forwards_output_config_for_non_adaptive_model(): - """``output_config`` is forwarded for non-adaptive models so the provider's error surfaces.""" +def test_bedrock_messages_strips_output_config_with_output_format(): + """ + When both output_config and output_format are present, output_format + is converted to inline schema and output_config is stripped for + unsupported models. + """ + from unittest.mock import patch + from litellm.types.router import GenericLiteLLMParams cfg = AmazonAnthropicClaudeMessagesConfig() messages = [{"role": "user", "content": [{"type": "text", "text": "Hello"}]}] optional_params = { "max_tokens": 4096, - "output_config": {"effort": "high"}, + "output_config": {"effort": "low"}, + "output_format": { + "type": "json_schema", + "schema": { + "type": "object", + "properties": {"answer": {"type": "string"}}, + }, + }, } - result = cfg.transform_anthropic_messages_request( - model="anthropic.claude-3-haiku-20240307-v1:0", - messages=messages, - anthropic_messages_optional_request_params=optional_params, - litellm_params=GenericLiteLLMParams(), - headers={}, - ) + with patch( + "litellm.llms.bedrock.messages.invoke_transformations.anthropic_claude3_transformation._supports_factory", + return_value=False, + ): + result = cfg.transform_anthropic_messages_request( + model="anthropic.claude-3-haiku-20240307-v1:0", + messages=messages, + anthropic_messages_optional_request_params=optional_params, + litellm_params=GenericLiteLLMParams(), + headers={}, + ) - assert result.get("output_config") == {"effort": "high"} - assert result.get("max_tokens") == 4096 + assert "output_config" not in result + assert "output_format" not in result def test_bedrock_messages_drop_params_strips_output_config_for_pre_4_5(): @@ -701,6 +837,8 @@ def test_bedrock_messages_drop_params_strips_output_config_for_pre_4_5(): def test_bedrock_messages_drop_params_keeps_output_config_for_4_7(): """``drop_params=True`` does not strip on opus-4-7 (supports effort).""" + from unittest.mock import patch + import litellm from litellm.types.router import GenericLiteLLMParams @@ -714,13 +852,17 @@ def test_bedrock_messages_drop_params_keeps_output_config_for_4_7(): original = litellm.drop_params litellm.drop_params = True try: - result = cfg.transform_anthropic_messages_request( - model="anthropic.claude-opus-4-7", - messages=messages, - anthropic_messages_optional_request_params=optional_params, - litellm_params=GenericLiteLLMParams(), - headers={}, - ) + with patch( + "litellm.llms.bedrock.messages.invoke_transformations.anthropic_claude3_transformation._supports_factory", + return_value=True, + ): + result = cfg.transform_anthropic_messages_request( + model="anthropic.claude-opus-4-7", + messages=messages, + anthropic_messages_optional_request_params=optional_params, + litellm_params=GenericLiteLLMParams(), + headers={}, + ) finally: litellm.drop_params = original @@ -742,6 +884,8 @@ def test_bedrock_messages_maps_reasoning_effort_for_adaptive_model( reasoning_effort, expected_effort ): """``reasoning_effort`` maps to ``thinking`` + ``output_config.effort`` on /v1/messages.""" + from unittest.mock import patch + from litellm.types.router import GenericLiteLLMParams cfg = AmazonAnthropicClaudeMessagesConfig() @@ -751,13 +895,17 @@ def test_bedrock_messages_maps_reasoning_effort_for_adaptive_model( "reasoning_effort": reasoning_effort, } - result = cfg.transform_anthropic_messages_request( - model="anthropic.claude-opus-4-7", - messages=messages, - anthropic_messages_optional_request_params=optional_params, - litellm_params=GenericLiteLLMParams(), - headers={}, - ) + with patch( + "litellm.llms.bedrock.messages.invoke_transformations.anthropic_claude3_transformation._supports_factory", + return_value=True, + ): + result = cfg.transform_anthropic_messages_request( + model="anthropic.claude-opus-4-7", + messages=messages, + anthropic_messages_optional_request_params=optional_params, + litellm_params=GenericLiteLLMParams(), + headers={}, + ) assert "reasoning_effort" not in result assert result.get("thinking") == {"type": "adaptive"} @@ -842,6 +990,8 @@ def test_bedrock_messages_invalid_reasoning_effort_raises_400(): def test_bedrock_messages_explicit_output_config_wins_over_reasoning_effort(): """Explicit ``output_config.effort`` wins over the ``reasoning_effort`` alias.""" + from unittest.mock import patch + from litellm.types.router import GenericLiteLLMParams cfg = AmazonAnthropicClaudeMessagesConfig() @@ -852,13 +1002,17 @@ def test_bedrock_messages_explicit_output_config_wins_over_reasoning_effort(): "output_config": {"effort": "max"}, } - result = cfg.transform_anthropic_messages_request( - model="anthropic.claude-opus-4-7", - messages=messages, - anthropic_messages_optional_request_params=optional_params, - litellm_params=GenericLiteLLMParams(), - headers={}, - ) + with patch( + "litellm.llms.bedrock.messages.invoke_transformations.anthropic_claude3_transformation._supports_factory", + return_value=True, + ): + result = cfg.transform_anthropic_messages_request( + model="anthropic.claude-opus-4-7", + messages=messages, + anthropic_messages_optional_request_params=optional_params, + litellm_params=GenericLiteLLMParams(), + headers={}, + ) assert "reasoning_effort" not in result assert result.get("output_config") == {"effort": "max"} @@ -994,7 +1148,7 @@ def test_bedrock_messages_allowlist_filters_anthropic_only_fields(): } result = cfg.transform_anthropic_messages_request( - model="anthropic.claude-3-haiku-20240307-v1:0", + model="anthropic.claude-opus-4-7", messages=messages, anthropic_messages_optional_request_params=optional_params, litellm_params=GenericLiteLLMParams(), diff --git a/tests/test_litellm/llms/chatgpt/responses/test_chatgpt_responses_transformation.py b/tests/test_litellm/llms/chatgpt/responses/test_chatgpt_responses_transformation.py index 2498946bb5c..90a1c24bada 100644 --- a/tests/test_litellm/llms/chatgpt/responses/test_chatgpt_responses_transformation.py +++ b/tests/test_litellm/llms/chatgpt/responses/test_chatgpt_responses_transformation.py @@ -14,6 +14,7 @@ import pytest sys.path.insert(0, os.path.abspath("../../../../..")) +from litellm.llms.openai.common_utils import OpenAIError from litellm.types.router import GenericLiteLLMParams from litellm.types.utils import LlmProviders from litellm.utils import ProviderConfigManager @@ -201,3 +202,127 @@ class TestChatGPTResponsesAPITransformation: ) assert parsed.output_text == "Hello!" + + @pytest.mark.parametrize( + ("model_name", "response_model"), + [ + ("chatgpt/gpt-5.2-codex", "gpt-5.2-codex"), + ("chatgpt/gpt-5.3-codex", "gpt-5.3-codex"), + ], + ) + def test_chatgpt_non_stream_sse_response_recovers_output_items( + self, model_name: str, response_model: str + ): + config = ChatGPTResponsesAPIConfig() + response_payload = { + "id": "resp_test", + "object": "response", + "created_at": 1700000000, + "status": "completed", + "model": response_model, + "output": [], + } + streamed_output_item = { + "type": "message", + "role": "assistant", + "content": [{"type": "output_text", "text": "Hello from stream!"}], + } + sse_body = "\n".join( + [ + f"data: {json.dumps({'type': 'response.output_item.done', 'output_index': 0, 'item': streamed_output_item})}", + f"data: {json.dumps({'type': 'response.completed', 'response': response_payload})}", + "data: [DONE]", + "", + ] + ) + raw_response = httpx.Response( + 200, headers={"content-type": "text/event-stream"}, text=sse_body + ) + logging_obj = MagicMock() + + parsed = config.transform_response_api_response( + model=model_name, + raw_response=raw_response, + logging_obj=logging_obj, + ) + + assert parsed.output_text == "Hello from stream!" + + def test_chatgpt_non_stream_sse_recovers_whitespace_padded_chunks(self): + """Chunks with leading whitespace before `data:` must still parse. + + `_strip_sse_data_from_chunk` only matches the prefix at position 0, + so without an outer `.strip()` such chunks would fail JSON parsing + and silently drop the contained event. + """ + config = ChatGPTResponsesAPIConfig() + response_payload = { + "id": "resp_test", + "object": "response", + "created_at": 1700000000, + "status": "completed", + "model": "gpt-5.4", + "output": [], + } + streamed_output_item = { + "type": "message", + "role": "assistant", + "content": [{"type": "output_text", "text": "Recovered from padded"}], + } + sse_body = "\n".join( + [ + f" data: {json.dumps({'type': 'response.output_item.done', 'output_index': 0, 'item': streamed_output_item})} ", + f"\tdata: {json.dumps({'type': 'response.completed', 'response': response_payload})}", + "data: [DONE]", + "", + ] + ) + raw_response = httpx.Response( + 200, headers={"content-type": "text/event-stream"}, text=sse_body + ) + logging_obj = MagicMock() + + parsed = config.transform_response_api_response( + model="chatgpt/gpt-5.4", + raw_response=raw_response, + logging_obj=logging_obj, + ) + + assert parsed.output_text == "Recovered from padded" + + @pytest.mark.parametrize( + "error_chunk", + [ + { + "type": "response.failed", + "response": {"error": {"message": "ChatGPT upstream failed"}}, + }, + { + "type": "error", + "error": {"message": "ChatGPT upstream failed"}, + }, + ], + ) + def test_chatgpt_non_stream_sse_response_raises_openai_error(self, error_chunk): + config = ChatGPTResponsesAPIConfig() + sse_body = "\n".join( + [ + f"data: {json.dumps(error_chunk)}", + "data: [DONE]", + "", + ] + ) + raw_response = httpx.Response( + 502, headers={"content-type": "text/event-stream"}, text=sse_body + ) + logging_obj = MagicMock() + + with pytest.raises(OpenAIError) as exc_info: + config.transform_response_api_response( + model="chatgpt/gpt-5.4", + raw_response=raw_response, + logging_obj=logging_obj, + ) + + assert "ChatGPT upstream failed" in str(exc_info.value) + assert exc_info.value.status_code == 502 diff --git a/tests/test_litellm/llms/fireworks_ai/chat/test_fireworks_ai_chat_transformation.py b/tests/test_litellm/llms/fireworks_ai/chat/test_fireworks_ai_chat_transformation.py index 279f16a3675..a29365544df 100644 --- a/tests/test_litellm/llms/fireworks_ai/chat/test_fireworks_ai_chat_transformation.py +++ b/tests/test_litellm/llms/fireworks_ai/chat/test_fireworks_ai_chat_transformation.py @@ -6,16 +6,29 @@ from unittest.mock import AsyncMock, MagicMock, patch import httpx import pytest +import litellm + sys.path.insert( 0, os.path.abspath("../../../../..") ) # Adds the parent directory to the system path -from litellm import supports_reasoning +from litellm import get_model_info, supports_reasoning from litellm.llms.fireworks_ai.chat.transformation import FireworksAIConfig from litellm.types.llms.openai import ChatCompletionToolCallFunctionChunk from litellm.types.utils import ChatCompletionMessageToolCall, Function, Message +@pytest.fixture(autouse=True) +def force_local_model_cost(monkeypatch): + """Force local model cost map usage for all tests in this file.""" + monkeypatch.setenv("LITELLM_LOCAL_MODEL_COST_MAP", "True") + # Refresh model_cost from local map + import litellm + from litellm.litellm_core_utils.get_model_cost_map import get_model_cost_map + + litellm.model_cost = get_model_cost_map(url=litellm.model_cost_map_url) + + def test_handle_message_content_with_tool_calls(): config = FireworksAIConfig() message = Message( @@ -62,7 +75,6 @@ def test_handle_message_content_with_tool_calls(): def test_supports_reasoning_effort(): """Test that reasoning_effort is only supported for specific Fireworks AI models.""" - # Models that support reasoning_effort supported_models = [ "fireworks_ai/accounts/fireworks/models/qwen3-8b", "fireworks_ai/accounts/fireworks/models/qwen3-32b", @@ -72,11 +84,13 @@ def test_supports_reasoning_effort(): "fireworks_ai/accounts/fireworks/models/glm-4p5", "fireworks_ai/accounts/fireworks/models/glm-4p5-air", "fireworks_ai/accounts/fireworks/models/glm-4p6", + "fireworks_ai/accounts/fireworks/models/glm-4p7", + "fireworks_ai/accounts/fireworks/models/glm-5p1", "fireworks_ai/accounts/fireworks/models/gpt-oss-120b", "fireworks_ai/accounts/fireworks/models/gpt-oss-20b", + "fireworks_ai/glm-5p1", ] - # Models that don't support reasoning_effort unsupported_models = [ "fireworks_ai/accounts/fireworks/models/llama-v3-70b-instruct", "fireworks_ai/accounts/fireworks/models/mixtral-8x7b-instruct", @@ -97,19 +111,74 @@ def test_get_supported_openai_params_reasoning_effort(): """Test that reasoning_effort is only included in supported params for models that support it.""" config = FireworksAIConfig() - # Model that supports reasoning_effort supported_params = config.get_supported_openai_params( - "fireworks_ai/accounts/fireworks/models/qwen3-8b" + "fireworks_ai/accounts/fireworks/models/glm-5p1" ) assert "reasoning_effort" in supported_params - # Model that doesn't support reasoning_effort unsupported_params = config.get_supported_openai_params( "fireworks_ai/accounts/fireworks/models/llama-v3-70b-instruct" ) assert "reasoning_effort" not in unsupported_params +def test_get_supported_openai_params_parallel_tool_calls(): + """Test that parallel_tool_calls is included for models that support function calling.""" + config = FireworksAIConfig() + + supported_params = config.get_supported_openai_params( + "fireworks_ai/accounts/fireworks/models/glm-4p6" + ) + assert "parallel_tool_calls" in supported_params + + unsupported_params = config.get_supported_openai_params( + "fireworks_ai/accounts/fireworks/models/glm-5p1" + ) + assert "parallel_tool_calls" not in unsupported_params + + +def test_get_supported_openai_params_parallel_tool_calls_without_tool_choice( + monkeypatch, +): + """Test that parallel_tool_calls is gated on tools, not tool_choice.""" + config = FireworksAIConfig() + model = "fireworks_ai/test-tools-without-tool-choice" + monkeypatch.setitem( + litellm.model_cost, + model, + { + "supports_function_calling": True, + "supports_tool_choice": False, + }, + ) + + supported_params = config.get_supported_openai_params(model) + + assert "tools" in supported_params + assert "parallel_tool_calls" in supported_params + assert "tool_choice" not in supported_params + + +def test_get_model_info_respects_explicit_fireworks_capabilities(): + """Test that get_model_info preserves explicit capability flags from the model map.""" + model_info = get_model_info("fireworks_ai/accounts/fireworks/models/glm-5p1") + + assert model_info["supports_function_calling"] is False + assert model_info["supports_reasoning"] is True + assert model_info["supports_tool_choice"] is False + + +def test_get_provider_info_omits_false_supports_reasoning(monkeypatch): + """Test that Fireworks only overrides supports_reasoning for supported models.""" + config = FireworksAIConfig() + model = "fireworks_ai/test-reasoning-false" + monkeypatch.setitem(litellm.model_cost, model, {"supports_reasoning": False}) + + info = config.get_provider_info(model) + + assert "supports_reasoning" not in info + + def test_add_transform_inline_image_block_skips_data_urls(): """ data: URLs must not have #transform=inline appended — doing so corrupts the @@ -234,6 +303,14 @@ def test_transform_messages_helper_removes_provider_specific_fields(): assert "provider_specific_fields" not in msg +def test_unmapped_model_fallback_function_calling(): + """Test that a model not in model_cost still defaults to supporting function calling for Fireworks.""" + config = FireworksAIConfig() + model = "fireworks_ai/unmapped-future-model" + info = config.get_provider_info(model) + assert info["supports_function_calling"] is True + + def test_transform_messages_helper_strips_thinking_blocks(): """thinking_blocks must not be forwarded to Fireworks chat completions.""" config = FireworksAIConfig() diff --git a/tests/test_litellm/llms/reducto/__init__.py b/tests/test_litellm/llms/reducto/__init__.py new file mode 100644 index 00000000000..8b137891791 --- /dev/null +++ b/tests/test_litellm/llms/reducto/__init__.py @@ -0,0 +1 @@ + diff --git a/tests/test_litellm/llms/reducto/test_cost.py b/tests/test_litellm/llms/reducto/test_cost.py new file mode 100644 index 00000000000..73340dc8729 --- /dev/null +++ b/tests/test_litellm/llms/reducto/test_cost.py @@ -0,0 +1,122 @@ +import litellm +import pytest + +from litellm.cost_calculator import completion_cost +from litellm.llms.base_llm.ocr.transformation import OCRPage, OCRResponse, OCRUsageInfo + + +def test_ocr_cost_prefers_credit_pricing_when_pages_processed_is_none(monkeypatch): + monkeypatch.setattr( + litellm, + "get_model_info", + lambda model, custom_llm_provider=None: {"ocr_cost_per_credit": 0.003}, + ) + + response = OCRResponse( + pages=[OCRPage(index=0, markdown="credit priced")], + model="parse-v3", + usage_info=OCRUsageInfo(pages_processed=None, credits=10), + ) + + cost = completion_cost( + completion_response=response, + model="reducto/parse-v3", + custom_llm_provider="reducto", + call_type="ocr", + ) + + assert cost == 0.03 + + +def test_ocr_cost_prefers_zero_credit_pricing_over_page_pricing(monkeypatch): + monkeypatch.setattr( + litellm, + "get_model_info", + lambda model, custom_llm_provider=None: { + "ocr_cost_per_credit": 0.0, + "ocr_cost_per_page": 0.5, + }, + ) + + response = OCRResponse( + pages=[OCRPage(index=0, markdown="free credit priced")], + model="parse-v3", + usage_info=OCRUsageInfo(pages_processed=2, credits=10), + ) + + cost = completion_cost( + completion_response=response, + model="reducto/parse-v3", + custom_llm_provider="reducto", + call_type="ocr", + ) + + assert cost == 0.0 + + +def test_ocr_cost_falls_back_to_page_pricing(monkeypatch): + monkeypatch.setattr( + litellm, + "get_model_info", + lambda model, custom_llm_provider=None: {"ocr_cost_per_page": 0.5}, + ) + + response = OCRResponse( + pages=[OCRPage(index=0, markdown="page priced")], + model="mistral-ocr-latest", + usage_info=OCRUsageInfo(pages_processed=2), + ) + + cost = completion_cost( + completion_response=response, + model="mistral/mistral-ocr-latest", + custom_llm_provider="mistral", + call_type="ocr", + ) + + assert cost == 1.0 + + +def test_ocr_cost_returns_zero_when_no_pricing_and_no_pages(monkeypatch): + monkeypatch.setattr( + litellm, + "get_model_info", + lambda model, custom_llm_provider=None: {}, + ) + + response = OCRResponse( + pages=[OCRPage(index=0, markdown="unpriced")], + model="parse-v3", + usage_info=OCRUsageInfo(pages_processed=None, credits=5), + ) + + cost = completion_cost( + completion_response=response, + model="reducto/parse-v3", + custom_llm_provider="reducto", + call_type="ocr", + ) + + assert cost == 0.0 + + +def test_ocr_cost_raises_when_pages_processed_missing_for_page_pricing(monkeypatch): + monkeypatch.setattr( + litellm, + "get_model_info", + lambda model, custom_llm_provider=None: {"ocr_cost_per_page": 0.5}, + ) + + response = OCRResponse( + pages=[OCRPage(index=0, markdown="missing pages")], + model="mistral-ocr-latest", + usage_info=OCRUsageInfo(pages_processed=None), + ) + + with pytest.raises(ValueError, match="OCR response pages_processed is None"): + completion_cost( + completion_response=response, + model="mistral/mistral-ocr-latest", + custom_llm_provider="mistral", + call_type="ocr", + ) diff --git a/tests/test_litellm/llms/reducto/test_model_info.py b/tests/test_litellm/llms/reducto/test_model_info.py new file mode 100644 index 00000000000..de7a3ccba64 --- /dev/null +++ b/tests/test_litellm/llms/reducto/test_model_info.py @@ -0,0 +1,44 @@ +import uuid + +import litellm + +from litellm.utils import _invalidate_model_cost_lowercase_map + + +def test_reducto_provider_registration(): + model, custom_llm_provider, _, _ = litellm.get_llm_provider( + model="reducto/parse-v3" + ) + + assert model == "parse-v3" + assert custom_llm_provider == "reducto" + + +def test_get_model_info_preserves_ocr_cost_per_credit(): + test_model_name = f"reducto/test-cost-propagation-{uuid.uuid4().hex[:12]}" + previous_model_entry = litellm.model_cost.get(test_model_name) + _invalidate_model_cost_lowercase_map() + + try: + litellm.register_model( + { + test_model_name: { + "litellm_provider": "reducto", + "mode": "ocr", + "ocr_cost_per_credit": 0.003, + } + } + ) + + model_info = litellm.get_model_info( + model=test_model_name, + custom_llm_provider="reducto", + ) + + assert model_info.get("ocr_cost_per_credit") == 0.003 + finally: + if previous_model_entry is None: + litellm.model_cost.pop(test_model_name, None) + else: + litellm.model_cost[test_model_name] = previous_model_entry + _invalidate_model_cost_lowercase_map() diff --git a/tests/test_litellm/llms/reducto/test_parse_legacy.py b/tests/test_litellm/llms/reducto/test_parse_legacy.py new file mode 100644 index 00000000000..db19460baa3 --- /dev/null +++ b/tests/test_litellm/llms/reducto/test_parse_legacy.py @@ -0,0 +1,59 @@ +import json + +import litellm +import pytest + + +@pytest.fixture() +def disable_aiohttp_transport(): + original_disable_aiohttp = litellm.disable_aiohttp_transport + litellm.disable_aiohttp_transport = True + litellm.in_memory_llm_clients_cache.flush_cache() + try: + yield + finally: + litellm.disable_aiohttp_transport = original_disable_aiohttp + litellm.in_memory_llm_clients_cache.flush_cache() + + +@pytest.mark.asyncio +async def test_parse_legacy_wraps_enhance_under_options( + disable_aiohttp_transport, respx_mock +): + upload_route = respx_mock.post("https://platform.reducto.ai/upload").respond( + json={"file_id": "reducto://legacy.pdf"} + ) + parse_route = respx_mock.post("https://platform.reducto.ai/parse").respond( + json={ + "usage": {"num_pages": 1, "credits": 1}, + "result": { + "chunks": [ + { + "content": "Legacy parse", + "blocks": [{"content": "Legacy parse", "bbox": {"page": 1}}], + } + ] + }, + } + ) + + response = await litellm.aocr( + model="reducto/parse-legacy", + document={ + "type": "file", + "file": b"%PDF-1.4 legacy", + "mime_type": "application/pdf", + }, + api_key="legacy-key", + api_base="https://platform.reducto.ai", + enhance={"agentic": [{"type": "table"}]}, + ) + + assert upload_route.called + assert parse_route.called + request_body = json.loads(parse_route.calls[0].request.read()) + assert request_body == { + "document_url": "reducto://legacy.pdf", + "options": {"enhance": {"agentic": [{"type": "table"}]}}, + } + assert response.pages[0].markdown == "Legacy parse" diff --git a/tests/test_litellm/llms/reducto/test_parse_v3.py b/tests/test_litellm/llms/reducto/test_parse_v3.py new file mode 100644 index 00000000000..140b9737dc0 --- /dev/null +++ b/tests/test_litellm/llms/reducto/test_parse_v3.py @@ -0,0 +1,152 @@ +import json + +import litellm +import pytest + + +def _reducto_parse_response() -> dict: + return { + "job_id": "job_123", + "usage": {"num_pages": 3, "credits": 3}, + "result": { + "chunks": [ + { + "content": "Page 1 block A", + "blocks": [ + { + "content": "Page 1 block A", + "bbox": {"page": 1}, + "kind": "text", + } + ], + }, + { + "content": "Page 2 block A", + "blocks": [ + { + "content": "Page 2 block A", + "bbox": {"page": 2}, + "kind": "table", + } + ], + }, + { + "content": "Page 1 block B", + "blocks": [ + { + "content": "Page 1 block B", + "bbox": {"page": 1}, + "kind": "text", + } + ], + }, + { + "content": "Page 3 block A", + "blocks": [ + { + "content": "Page 3 block A", + "bbox": {"page": 3}, + "kind": "figure", + } + ], + }, + ] + }, + } + + +@pytest.fixture() +def disable_aiohttp_transport(): + original_disable_aiohttp = litellm.disable_aiohttp_transport + litellm.disable_aiohttp_transport = True + litellm.in_memory_llm_clients_cache.flush_cache() + try: + yield + finally: + litellm.disable_aiohttp_transport = original_disable_aiohttp + litellm.in_memory_llm_clients_cache.flush_cache() + + +@pytest.mark.asyncio +async def test_parse_v3_file_upload_and_response_mapping( + disable_aiohttp_transport, respx_mock +): + upload_route = respx_mock.post("https://platform.reducto.ai/upload").respond( + json={"file_id": "reducto://uploaded.pdf"} + ) + parse_route = respx_mock.post("https://platform.reducto.ai/parse").respond( + json=_reducto_parse_response() + ) + + response = await litellm.aocr( + model="reducto/parse-v3", + document={ + "type": "file", + "file": b"%PDF-1.4 reducto", + "mime_type": "application/pdf", + }, + api_key="test-key", + api_base="https://platform.reducto.ai", + formatting={"table_output_format": "html"}, + retrieval={"chunk_mode": "section"}, + settings={"ocr_system": "standard"}, + ) + + assert upload_route.called + assert parse_route.called + assert len(upload_route.calls) == 1 + assert len(parse_route.calls) == 1 + + upload_request = upload_route.calls[0].request + assert upload_request.headers["authorization"] == "Bearer test-key" + assert "application/json" not in upload_request.headers["content-type"] + upload_body = upload_request.read() + assert b'filename="document"' in upload_body + assert b"application/pdf" in upload_body + + parse_request_body = json.loads(parse_route.calls[0].request.read()) + assert parse_request_body["input"] == "reducto://uploaded.pdf" + assert parse_request_body["formatting"] == {"table_output_format": "html"} + assert parse_request_body["retrieval"] == {"chunk_mode": "section"} + assert parse_request_body["settings"] == {"ocr_system": "standard"} + + assert response.usage_info is not None + assert response.usage_info.credits == 3 + assert response.usage_info.pages_processed == 3 + assert len(response.pages) == 3 + assert response.pages[0].index == 0 + assert response.pages[0].markdown == "Page 1 block A\n\nPage 1 block B" + assert getattr(response.pages[0], "blocks")[0]["bbox"]["page"] == 1 + assert response.pages[1].markdown == "Page 2 block A" + assert response.pages[2].markdown == "Page 3 block A" + assert response._hidden_params["reducto_raw"]["usage"]["credits"] == 3 + + +@pytest.mark.asyncio +async def test_parse_v3_reducto_id_passthrough_skips_upload( + disable_aiohttp_transport, respx_mock +): + upload_route = respx_mock.post("https://platform.reducto.ai/upload").respond( + json={"file_id": "reducto://should-not-upload.pdf"} + ) + parse_route = respx_mock.post("https://platform.reducto.ai/parse").respond( + json=_reducto_parse_response() + ) + + response = await litellm.aocr( + model="reducto/parse-v3", + document={ + "type": "document_url", + "document_url": "reducto://already-uploaded.pdf", + }, + api_key="test-key", + api_base="https://platform.reducto.ai", + retrieval={"chunk_mode": "section"}, + ) + + assert not upload_route.called + assert parse_route.called + parse_request_body = json.loads(parse_route.calls[0].request.read()) + assert parse_request_body["input"] == "reducto://already-uploaded.pdf" + assert parse_request_body["retrieval"]["chunk_mode"] == "section" + assert response.pages[0].markdown.startswith("Page 1 block A") diff --git a/tests/test_litellm/llms/reducto/test_upload.py b/tests/test_litellm/llms/reducto/test_upload.py new file mode 100644 index 00000000000..4fae90436bb --- /dev/null +++ b/tests/test_litellm/llms/reducto/test_upload.py @@ -0,0 +1,213 @@ +import json +import os +from unittest.mock import AsyncMock, Mock + +import httpx +import litellm +import pytest + +from litellm.llms.reducto.common import ( + extract_file_id_or_bytes, + upload_bytes_async, + upload_bytes_sync, +) + + +@pytest.fixture() +def disable_aiohttp_transport(monkeypatch): + original_disable_aiohttp = litellm.disable_aiohttp_transport + litellm.disable_aiohttp_transport = True + litellm.in_memory_llm_clients_cache.flush_cache() + monkeypatch.setenv("REDUCTO_API_KEY", "env-reducto-key") + try: + yield + finally: + litellm.disable_aiohttp_transport = original_disable_aiohttp + litellm.in_memory_llm_clients_cache.flush_cache() + os.environ.pop("REDUCTO_API_KEY", None) + + +@pytest.mark.asyncio +async def test_parse_v3_rejects_plain_http_urls(disable_aiohttp_transport): + with pytest.raises(litellm.BadRequestError, match="upload the file first"): + await litellm.aocr( + model="reducto/parse-v3", + document={ + "type": "document_url", + "document_url": "https://example.com/document.pdf", + }, + api_key="test-key", + api_base="https://platform.reducto.ai", + ) + + +@pytest.mark.asyncio +async def test_parse_v3_image_data_uri_upload_uses_image_mime( + disable_aiohttp_transport, respx_mock +): + upload_route = respx_mock.post("https://custom.reducto.test/upload").respond( + json={"file_id": "reducto://uploaded-image.png"} + ) + parse_route = respx_mock.post("https://custom.reducto.test/parse").respond( + json={ + "usage": {"num_pages": 1, "credits": 1}, + "result": { + "chunks": [ + { + "content": "Image OCR", + "blocks": [{"content": "Image OCR", "bbox": {"page": 1}}], + } + ] + }, + } + ) + + response = await litellm.aocr( + model="reducto/parse-v3", + document={ + "type": "file", + "file": b"\x89PNG\r\n\x1a\npng", + "mime_type": "image/png", + }, + api_key="programmatic-key", + api_base="https://custom.reducto.test/", + ) + + assert upload_route.called + assert parse_route.called + upload_request = upload_route.calls[0].request + assert upload_request.headers["authorization"] == "Bearer programmatic-key" + assert b"image/png" in upload_request.read() + + parse_request_body = json.loads(parse_route.calls[0].request.read()) + assert parse_request_body["input"] == "reducto://uploaded-image.png" + assert response.pages[0].markdown == "Image OCR" + + +@pytest.mark.asyncio +async def test_parse_v3_uses_programmatic_api_key_over_env( + disable_aiohttp_transport, respx_mock +): + upload_route = respx_mock.post("https://platform.reducto.ai/upload").respond( + json={"file_id": "reducto://uploaded.pdf"} + ) + parse_route = respx_mock.post("https://platform.reducto.ai/parse").respond( + json={ + "usage": {"num_pages": 1, "credits": 1}, + "result": { + "chunks": [ + { + "content": "Programmatic auth", + "blocks": [ + {"content": "Programmatic auth", "bbox": {"page": 1}} + ], + } + ] + }, + } + ) + + await litellm.aocr( + model="reducto/parse-v3", + document={ + "type": "file", + "file": b"%PDF-1.4 auth", + "mime_type": "application/pdf", + }, + api_key="passed-key", + api_base="https://platform.reducto.ai", + ) + + assert upload_route.calls[0].request.headers["authorization"] == "Bearer passed-key" + assert parse_route.calls[0].request.headers["authorization"] == "Bearer passed-key" + + +def test_upload_bytes_sync_uses_shared_client(monkeypatch): + captured = {} + + def fake_post(*, url, headers, files, timeout): + captured["url"] = url + captured["headers"] = headers + captured["files"] = files + captured["timeout"] = timeout + return httpx.Response( + 200, + json={"file_id": "reducto://sync-upload"}, + request=httpx.Request("POST", url), + ) + + sync_post = Mock(side_effect=fake_post) + monkeypatch.setattr(litellm.module_level_client, "post", sync_post) + + class ForbiddenSyncClient: + def __init__(self, *args, **kwargs): + raise AssertionError("should not construct") + + monkeypatch.setattr(httpx, "Client", ForbiddenSyncClient) + + file_id = upload_bytes_sync( + raw_bytes=b"%PDF-1.4 sync", + mime="application/pdf", + api_key="sync-key", + api_base="https://sync.reducto.test/", + ) + + assert file_id == "reducto://sync-upload" + sync_post.assert_called_once() + assert captured["url"] == "https://sync.reducto.test/upload" + assert captured["headers"] == {"Authorization": "Bearer sync-key"} + assert captured["files"]["file"] == ( + "document", + b"%PDF-1.4 sync", + "application/pdf", + ) + + +@pytest.mark.asyncio +async def test_upload_bytes_async_uses_shared_aclient(monkeypatch): + captured = {} + + async def fake_post(*, url, headers, files, timeout): + captured["url"] = url + captured["headers"] = headers + captured["files"] = files + captured["timeout"] = timeout + return httpx.Response( + 200, + json={"file_id": "reducto://async-upload"}, + request=httpx.Request("POST", url), + ) + + async_post = AsyncMock(side_effect=fake_post) + monkeypatch.setattr(litellm.module_level_aclient, "post", async_post) + + class ForbiddenAsyncClient: + def __init__(self, *args, **kwargs): + raise AssertionError("should not construct") + + monkeypatch.setattr(httpx, "AsyncClient", ForbiddenAsyncClient) + + file_id = await upload_bytes_async( + raw_bytes=b"%PDF-1.4 async", + mime="application/pdf", + api_key="async-key", + api_base="https://async.reducto.test/", + ) + + assert file_id == "reducto://async-upload" + async_post.assert_awaited_once() + assert captured["url"] == "https://async.reducto.test/upload" + assert captured["headers"] == {"Authorization": "Bearer async-key"} + assert captured["files"]["file"] == ( + "document", + b"%PDF-1.4 async", + "application/pdf", + ) + + +def test_extract_file_id_or_bytes_raises_on_malformed_data_uri(): + with pytest.raises(litellm.BadRequestError, match="Invalid Reducto data URI"): + extract_file_id_or_bytes("data:application/pdf", model="reducto/parse-v3") + + with pytest.raises(litellm.BadRequestError, match="Invalid Reducto base64 payload"): + extract_file_id_or_bytes("data:;base64,!!!not-base64", model="reducto/parse-v3") diff --git a/tests/test_litellm/llms/vertex_ai/test_vertex_llm_base.py b/tests/test_litellm/llms/vertex_ai/test_vertex_llm_base.py index 88aac07a0c9..2cf97081806 100644 --- a/tests/test_litellm/llms/vertex_ai/test_vertex_llm_base.py +++ b/tests/test_litellm/llms/vertex_ai/test_vertex_llm_base.py @@ -1,3 +1,4 @@ +import asyncio import json import os import sys @@ -1448,3 +1449,474 @@ class TestVertexBase: aws_creds = supplier.get_aws_security_credentials(context=None, request=None) assert isinstance(aws_creds, AwsSecurityCredentials) + + @pytest.mark.asyncio + async def test_single_flight_refresh(self): + """Under high concurrency, only one coroutine should refresh expired credentials.""" + import asyncio + + vertex_base = VertexBase() + + mock_creds = MagicMock() + mock_creds.token = "expired-token" + mock_creds.expired = True + mock_creds.expiry = None + mock_creds.project_id = "project-1" + mock_creds.quota_project_id = "project-1" + + credentials = {"type": "service_account", "project_id": "project-1"} + + refresh_call_count = 0 + + with ( + patch.object( + vertex_base, "load_auth", return_value=(mock_creds, "project-1") + ), + patch.object(vertex_base, "refresh_auth") as mock_refresh, + ): + + async def slow_refresh(creds): + nonlocal refresh_call_count + refresh_call_count += 1 + await asyncio.sleep(0.05) # simulate network latency + creds.token = "refreshed-token" + creds.expired = False + + # refresh_auth is sync, but we need to count calls. + # get_access_token_async wraps it with asyncify, so the sync side_effect works. + def sync_refresh_impl(creds): + nonlocal refresh_call_count + refresh_call_count += 1 + creds.token = "refreshed-token" + creds.expired = False + + mock_refresh.side_effect = sync_refresh_impl + + # Launch 50 concurrent requests + tasks = [ + vertex_base._ensure_access_token_async( + credentials=credentials, + project_id="project-1", + custom_llm_provider="vertex_ai", + ) + for _ in range(50) + ] + results = await asyncio.gather(*tasks) + + # All should return the refreshed token + for token, project in results: + assert token == "refreshed-token" + assert project == "project-1" + + # refresh_auth should be called exactly once (single-flight) + assert ( + refresh_call_count == 1 + ), f"Expected 1 refresh call, got {refresh_call_count}" + + @pytest.mark.asyncio + async def test_async_reauthentication_uses_async_single_flight(self): + """Concurrent async reauth should reload once without using the sync path.""" + from google.auth.credentials import TokenState + + vertex_base = VertexBase() + stale_creds = MagicMock() + stale_creds.token = "expired-token" + stale_creds.token_state = TokenState.INVALID + stale_creds.project_id = "project-1" + stale_creds.quota_project_id = "project-1" + + refreshed_creds = MagicMock() + refreshed_creds.token = "refreshed-token" + refreshed_creds.token_state = TokenState.FRESH + refreshed_creds.project_id = "project-1" + refreshed_creds.quota_project_id = "project-1" + + credentials = {"type": "service_account", "project_id": "project-1"} + cache_key = (json.dumps(credentials), "project-1") + vertex_base._credentials_project_mapping[cache_key] = ( + stale_creds, + "project-1", + ) + + load_call_count = 0 + + def load_auth_impl(*_args, **_kwargs): + nonlocal load_call_count + load_call_count += 1 + return refreshed_creds, "project-1" + + with ( + patch.object( + vertex_base, + "refresh_auth", + side_effect=Exception("Reauthentication is needed"), + ), + patch.object(vertex_base, "load_auth", side_effect=load_auth_impl), + patch.object(vertex_base, "get_access_token") as mock_get_access_token, + ): + results = await asyncio.gather( + *[ + vertex_base._ensure_access_token_async( + credentials=credentials, + project_id="project-1", + custom_llm_provider="vertex_ai", + ) + for _ in range(10) + ] + ) + + assert results == [("refreshed-token", "project-1")] * 10 + assert load_call_count == 1 + mock_get_access_token.assert_not_called() + + @pytest.mark.asyncio + async def test_background_refresh_when_near_expiry(self): + """When token_state is STALE (within the 3:45 REFRESH_THRESHOLD window), + return the current token immediately and refresh in the background — + zero added latency.""" + import asyncio + + from google.auth.credentials import TokenState + + vertex_base = VertexBase() + + # Simulate STALE state: token is usable but near expiry. + mock_creds = MagicMock() + mock_creds.token = "near-expiry-token" + mock_creds.token_state = TokenState.STALE + mock_creds.project_id = "project-1" + mock_creds.quota_project_id = "project-1" + + credentials = {"type": "service_account", "project_id": "project-1"} + + with ( + patch.object( + vertex_base, "load_auth", return_value=(mock_creds, "project-1") + ), + patch.object(vertex_base, "refresh_auth") as mock_refresh, + ): + + def mock_refresh_impl(creds): + creds.token = "refreshed-token" + creds.token_state = TokenState.FRESH + + mock_refresh.side_effect = mock_refresh_impl + + token, project = await vertex_base._ensure_access_token_async( + credentials=credentials, + project_id="project-1", + custom_llm_provider="vertex_ai", + ) + + # Should return the current (still usable) token immediately + assert token == "near-expiry-token" + + # Let the background refresh task run + await asyncio.sleep(0.05) + + assert mock_refresh.called, "Background refresh should have been triggered" + + @pytest.mark.asyncio + async def test_stale_malformed_token_blocks_on_refresh(self): + """Malformed STALE tokens should refresh instead of failing validation.""" + from google.auth.credentials import TokenState + + vertex_base = VertexBase() + + mock_creds = MagicMock() + mock_creds.token = None + mock_creds.token_state = TokenState.STALE + mock_creds.project_id = "project-1" + mock_creds.quota_project_id = "project-1" + + credentials = {"type": "service_account", "project_id": "project-1"} + + with ( + patch.object( + vertex_base, "load_auth", return_value=(mock_creds, "project-1") + ), + patch.object(vertex_base, "refresh_auth") as mock_refresh, + ): + + def mock_refresh_impl(creds): + creds.token = "refreshed-token" + creds.token_state = TokenState.FRESH + + mock_refresh.side_effect = mock_refresh_impl + + token, project = await vertex_base._ensure_access_token_async( + credentials=credentials, + project_id="project-1", + custom_llm_provider="vertex_ai", + ) + + assert mock_refresh.called + assert token == "refreshed-token" + assert project == "project-1" + + @pytest.mark.asyncio + async def test_fresh_token_skips_refresh(self): + """Credentials not marked expired by google-auth should not trigger refresh.""" + vertex_base = VertexBase() + + mock_creds = MagicMock() + mock_creds.token = "fresh-token" + mock_creds.expired = False + mock_creds.project_id = "project-1" + mock_creds.quota_project_id = "project-1" + + credentials = {"type": "service_account", "project_id": "project-1"} + cache_key = (json.dumps(credentials), "project-1") + vertex_base._credentials_project_mapping[cache_key] = ( + mock_creds, + "project-1", + ) + + with patch.object(vertex_base, "refresh_auth") as mock_refresh: + token, project = await vertex_base._ensure_access_token_async( + credentials=credentials, + project_id="project-1", + custom_llm_provider="vertex_ai", + ) + + assert not mock_refresh.called, "Fresh token should not trigger refresh" + assert token == "fresh-token" + + @pytest.mark.asyncio + async def test_background_refresh_task_removed_after_completion(self): + """Completed background-refresh tasks must be evicted from + _background_refresh_tasks so the dict does not grow unboundedly.""" + import asyncio + + from google.auth.credentials import TokenState + + vertex_base = VertexBase() + + mock_creds = MagicMock() + mock_creds.token = "near-expiry-token" + mock_creds.token_state = TokenState.STALE + mock_creds.project_id = "project-1" + mock_creds.quota_project_id = "project-1" + + credentials = {"type": "service_account", "project_id": "project-1"} + + with ( + patch.object( + vertex_base, "load_auth", return_value=(mock_creds, "project-1") + ), + patch.object(vertex_base, "refresh_auth") as mock_refresh, + ): + + def mock_refresh_impl(creds): + creds.token = "refreshed-token" + creds.token_state = TokenState.FRESH + + mock_refresh.side_effect = mock_refresh_impl + + await vertex_base._ensure_access_token_async( + credentials=credentials, + project_id="project-1", + custom_llm_provider="vertex_ai", + ) + + # Allow the background task to complete. + await asyncio.sleep(0.1) + + # After completion the entry should have been removed by the done-callback. + assert len(vertex_base._background_refresh_tasks) == 0, ( + "Completed background refresh task was not removed from " + "_background_refresh_tasks" + ) + + @pytest.mark.asyncio + async def test_background_refresh_tasks_no_accumulation_across_many_keys(self): + """With many distinct credential keys the dict must not hold completed tasks.""" + import asyncio + import json as _json + + from google.auth.credentials import TokenState + + vertex_base = VertexBase() + + num_keys = 20 + + for i in range(num_keys): + mock_creds = MagicMock() + mock_creds.token = f"token-{i}" + mock_creds.token_state = TokenState.STALE + mock_creds.project_id = f"project-{i}" + mock_creds.quota_project_id = f"project-{i}" + + credentials = {"type": "service_account", "project_id": f"project-{i}"} + + with ( + patch.object( + vertex_base, + "load_auth", + return_value=(mock_creds, f"project-{i}"), + ), + patch.object(vertex_base, "refresh_auth") as mock_refresh, + ): + + def mock_refresh_impl(creds, idx=i): + creds.token = f"refreshed-{idx}" + creds.token_state = TokenState.FRESH + + mock_refresh.side_effect = mock_refresh_impl + + await vertex_base._ensure_access_token_async( + credentials=credentials, + project_id=f"project-{i}", + custom_llm_provider="vertex_ai", + ) + + # Let all background tasks finish. + await asyncio.sleep(0.1) + + assert len(vertex_base._background_refresh_tasks) == 0, ( + f"Expected 0 tasks after all refreshes completed, " + f"found {len(vertex_base._background_refresh_tasks)}" + ) + + @pytest.mark.asyncio + async def test_async_refresh_lock_shared_while_in_use(self): + """Concurrent callers for the same key must coordinate on the same lock.""" + vertex_base = VertexBase() + key = ("creds", "project-1") + + lock_a = vertex_base._acquire_async_refresh_lock(key) + try: + async with lock_a: + lock_b = vertex_base._acquire_async_refresh_lock(key) + try: + assert lock_a is lock_b, ( + "While a coroutine still holds the lock, concurrent callers must " + "receive the same Lock instance to preserve single-flight." + ) + finally: + vertex_base._release_async_refresh_lock(key, lock_b) + finally: + vertex_base._release_async_refresh_lock(key, lock_a) + + @pytest.mark.asyncio + async def test_async_refresh_lock_pruned_after_release(self): + """get_access_token_async must drop the per-key Lock from the registry + once no coroutine is using it, so the dict stays bounded in + high-cardinality deployments. Without this, every distinct credential + leaks a Lock object for the lifetime of the process.""" + from google.auth.credentials import TokenState + + vertex_base = VertexBase() + + for i in range(10): + mock_creds = MagicMock() + mock_creds.token = f"refreshed-{i}" + mock_creds.token_state = TokenState.FRESH + mock_creds.project_id = f"project-{i}" + mock_creds.quota_project_id = f"project-{i}" + + credentials = {"type": "service_account", "project_id": f"project-{i}"} + + with ( + patch.object( + vertex_base, + "load_auth", + return_value=(mock_creds, f"project-{i}"), + ), + patch.object(vertex_base, "refresh_auth"), + ): + await vertex_base._ensure_access_token_async( + credentials=credentials, + project_id=f"project-{i}", + custom_llm_provider="vertex_ai", + ) + + assert len(vertex_base._async_refresh_locks) == 0, ( + "expected per-key locks to be pruned once no coroutine holds or " + f"waits on them; found {len(vertex_base._async_refresh_locks)}" + ) + assert len(vertex_base._async_refresh_lock_refcounts) == 0 + + @pytest.mark.asyncio + async def test_async_refresh_lock_kept_while_waiter_pending(self): + """The prune must not run while another coroutine is still waiting on + the lock — otherwise the waiter ends up on a lock that's been replaced + in the registry and single-flight breaks.""" + vertex_base = VertexBase() + key = ("creds", "project-1") + + holder_lock = vertex_base._acquire_async_refresh_lock(key) + release_holder = asyncio.Event() + + async def hold_then_release(): + async with holder_lock: + await release_holder.wait() + vertex_base._release_async_refresh_lock(key, holder_lock) + + holder = asyncio.create_task(hold_then_release()) + await asyncio.sleep(0) # let holder grab the lock + + async def queue_for_lock(): + waiter_lock = vertex_base._acquire_async_refresh_lock(key) + try: + async with waiter_lock: + pass + finally: + vertex_base._release_async_refresh_lock(key, waiter_lock) + + waiter = asyncio.create_task(queue_for_lock()) + await asyncio.sleep(0) # let waiter queue on the lock + + assert ( + vertex_base._async_refresh_locks.get(key) is holder_lock + ), "lock with active holder/waiter must not be pruned" + + release_holder.set() + await holder + await waiter + + assert key not in vertex_base._async_refresh_locks + assert key not in vertex_base._async_refresh_lock_refcounts + + @pytest.mark.asyncio + async def test_fast_path_no_lock(self): + """Cached fresh credentials should return without acquiring the lock.""" + import datetime + + vertex_base = VertexBase() + + try: + from google.auth import _helpers as google_auth_helpers + + now = google_auth_helpers.utcnow() + except ImportError: + now = datetime.datetime.utcnow() + + mock_creds = MagicMock() + mock_creds.token = "cached-token" + mock_creds.expired = False + mock_creds.expiry = now + datetime.timedelta(minutes=30) + mock_creds.project_id = "project-1" + mock_creds.quota_project_id = "project-1" + + credentials = {"type": "service_account", "project_id": "project-1"} + cache_key = (json.dumps(credentials), "project-1") + vertex_base._credentials_project_mapping[cache_key] = ( + mock_creds, + "project-1", + ) + + # Spy on _acquire_async_refresh_lock to verify it's never called + with patch.object( + vertex_base, + "_acquire_async_refresh_lock", + wraps=vertex_base._acquire_async_refresh_lock, + ) as mock_get_lock: + token, project = await vertex_base._ensure_access_token_async( + credentials=credentials, + project_id="project-1", + custom_llm_provider="vertex_ai", + ) + + assert token == "cached-token" + assert not mock_get_lock.called, "Fast path should not acquire lock" diff --git a/tests/test_litellm/llms/vertex_ai/vertex_ai_partner_models/gpt_oss/test_vertex_ai_gpt_oss_transformation.py b/tests/test_litellm/llms/vertex_ai/vertex_ai_partner_models/gpt_oss/test_vertex_ai_gpt_oss_transformation.py index b16fc2bc44d..f617a8db850 100644 --- a/tests/test_litellm/llms/vertex_ai/vertex_ai_partner_models/gpt_oss/test_vertex_ai_gpt_oss_transformation.py +++ b/tests/test_litellm/llms/vertex_ai/vertex_ai_partner_models/gpt_oss/test_vertex_ai_gpt_oss_transformation.py @@ -118,7 +118,7 @@ async def test_vertex_ai_gpt_oss_simple_request(): "litellm.llms.custom_httpx.http_handler.AsyncHTTPHandler" ) as mock_http_handler, patch( - "litellm.llms.vertex_ai.gemini.vertex_and_google_ai_studio_gemini.VertexLLM._ensure_access_token", + "litellm.llms.vertex_ai.vertex_ai_partner_models.main.VertexAIPartnerModels._ensure_access_token", return_value=("fake-token", "pathrise-convert-1606954137718"), ), patch.dict( @@ -217,7 +217,7 @@ async def test_vertex_ai_gpt_oss_reasoning_effort(): "litellm.llms.custom_httpx.http_handler.AsyncHTTPHandler" ) as mock_http_handler, patch( - "litellm.llms.vertex_ai.gemini.vertex_and_google_ai_studio_gemini.VertexLLM._ensure_access_token", + "litellm.llms.vertex_ai.vertex_ai_partner_models.main.VertexAIPartnerModels._ensure_access_token", return_value=("fake-token", "pathrise-convert-1606954137718"), ), patch.dict( diff --git a/tests/test_litellm/llms/vertex_ai/vertex_ai_partner_models/qwen/test_vertex_ai_qwen_global_endpoint.py b/tests/test_litellm/llms/vertex_ai/vertex_ai_partner_models/qwen/test_vertex_ai_qwen_global_endpoint.py index bf6e0a5f2cd..5a86325b7fd 100644 --- a/tests/test_litellm/llms/vertex_ai/vertex_ai_partner_models/qwen/test_vertex_ai_qwen_global_endpoint.py +++ b/tests/test_litellm/llms/vertex_ai/vertex_ai_partner_models/qwen/test_vertex_ai_qwen_global_endpoint.py @@ -7,7 +7,6 @@ These tests verify that: 3. The completion() and responses() API work with Qwen models """ -import json import os import sys from unittest.mock import MagicMock, patch, AsyncMock @@ -179,7 +178,7 @@ async def test_vertex_ai_qwen_global_endpoint_url(): "litellm.llms.custom_httpx.http_handler.AsyncHTTPHandler" ) as mock_http_handler, patch( - "litellm.llms.vertex_ai.gemini.vertex_and_google_ai_studio_gemini.VertexLLM._ensure_access_token", + "litellm.llms.vertex_ai.vertex_ai_partner_models.main.VertexAIPartnerModels._ensure_access_token", return_value=("fake-token", "test-project"), ), patch.dict( diff --git a/tests/test_litellm/llms/vertex_ai/vertex_ai_partner_models/test_partner_models_credential_reuse.py b/tests/test_litellm/llms/vertex_ai/vertex_ai_partner_models/test_partner_models_credential_reuse.py new file mode 100644 index 00000000000..b20442a032e --- /dev/null +++ b/tests/test_litellm/llms/vertex_ai/vertex_ai_partner_models/test_partner_models_credential_reuse.py @@ -0,0 +1,220 @@ +""" +Test that VertexBase subclasses (PartnerModels, Gemma, ModelGarden) reuse +cached credentials instead of creating a new VertexLLM instance on every request. +""" + +import sys +from unittest.mock import MagicMock, patch + +import pytest + +from litellm.llms.vertex_ai.vertex_ai_partner_models.main import ( + VertexAIPartnerModels, +) +from litellm.llms.vertex_ai.vertex_gemma_models.main import VertexAIGemmaModels +from litellm.llms.vertex_ai.vertex_model_garden.main import VertexAIModelGardenModels + + +def _mock_vertexai(): + """Return a MagicMock that satisfies the vertexai import guards.""" + m = MagicMock() + m.preview = MagicMock() + m.preview.language_models = MagicMock() + return m + + +class TestVertexBaseSubclassInit: + """All VertexBase subclasses must call super().__init__() so that + the credential cache is initialized.""" + + @pytest.mark.parametrize( + "cls", + [VertexAIPartnerModels, VertexAIGemmaModels, VertexAIModelGardenModels], + ids=["PartnerModels", "Gemma", "ModelGarden"], + ) + def test_init_calls_super(self, cls): + instance = cls() + assert hasattr(instance, "_credentials_project_mapping") + assert isinstance(instance._credentials_project_mapping, dict) + assert hasattr(instance, "access_token") + assert hasattr(instance, "project_id") + + +class TestPartnerModelsCredentialReuse: + def test_completion_uses_self_ensure_access_token(self): + """completion() should call self._ensure_access_token, not create a + throwaway VertexLLM instance.""" + partner = VertexAIPartnerModels() + + with ( + patch.dict(sys.modules, {"vertexai": _mock_vertexai()}), + patch.object( + partner, + "_ensure_access_token", + return_value=("cached-token", "test-project"), + ) as mock_ensure, + patch( + "litellm.llms.vertex_ai.vertex_ai_partner_models.main.base_llm_http_handler" + ) as mock_handler, + ): + mock_handler.completion.return_value = "response" + + partner.completion( + model="meta/llama-3.1-405b-instruct-maas", + messages=[{"role": "user", "content": "hello"}], + model_response=MagicMock(), + print_verbose=lambda *a, **kw: None, + encoding=MagicMock(), + logging_obj=MagicMock(), + api_base=None, + optional_params={}, + custom_prompt_dict={}, + headers=None, + timeout=30.0, + litellm_params={}, + vertex_project="test-project", + vertex_location="us-central1", + vertex_credentials='{"type": "service_account"}', + ) + + mock_ensure.assert_called_once_with( + credentials='{"type": "service_account"}', + project_id="test-project", + custom_llm_provider="vertex_ai", + ) + + def test_credential_cache_shared_across_calls(self): + """Two successive completion() calls should hit load_auth only once.""" + partner = VertexAIPartnerModels() + + mock_creds = MagicMock() + mock_creds.token = "my-token" + mock_creds.expired = False + mock_creds.project_id = "proj" + mock_creds.quota_project_id = "proj" + + with ( + patch.dict(sys.modules, {"vertexai": _mock_vertexai()}), + patch.object( + partner, "load_auth", return_value=(mock_creds, "proj") + ) as mock_load, + patch( + "litellm.llms.vertex_ai.vertex_ai_partner_models.main.base_llm_http_handler" + ) as mock_handler, + ): + mock_handler.completion.return_value = "resp" + + common_kwargs = dict( + model="meta/llama-3.1-405b-instruct-maas", + messages=[{"role": "user", "content": "hi"}], + model_response=MagicMock(), + print_verbose=lambda *a, **kw: None, + encoding=MagicMock(), + logging_obj=MagicMock(), + api_base=None, + optional_params={}, + custom_prompt_dict={}, + headers=None, + timeout=30.0, + litellm_params={}, + vertex_project="proj", + vertex_location="us-central1", + vertex_credentials='{"type": "service_account"}', + ) + + partner.completion(**common_kwargs) + partner.completion(**common_kwargs) + + assert mock_load.call_count == 1 + + +class TestGemmaModelsCredentialReuse: + def test_completion_uses_self_ensure_access_token(self): + """completion() should call self._ensure_access_token, not create a + throwaway VertexLLM instance.""" + gemma = VertexAIGemmaModels() + + mock_gemma_config = MagicMock() + mock_gemma_config.return_value.completion.return_value = "response" + + with ( + patch.dict(sys.modules, {"vertexai": _mock_vertexai()}), + patch.object( + gemma, + "_ensure_access_token", + return_value=("cached-token", "test-project"), + ) as mock_ensure, + patch( + "litellm.llms.vertex_ai.vertex_gemma_models.transformation.VertexGemmaConfig", + mock_gemma_config, + ), + ): + gemma.completion( + model="gemma/gemma-3-12b-it-1234567890", + messages=[{"role": "user", "content": "hello"}], + model_response=MagicMock(), + print_verbose=lambda *a, **kw: None, + encoding=MagicMock(), + logging_obj=MagicMock(), + api_base="https://123.us-central1-1.prediction.vertexai.goog/v1/projects/proj/locations/us-central1/endpoints/456:predict", + optional_params={}, + custom_prompt_dict={}, + headers=None, + timeout=30.0, + litellm_params={}, + vertex_project="test-project", + vertex_location="us-central1", + vertex_credentials='{"type": "service_account"}', + ) + + mock_ensure.assert_called_once_with( + credentials='{"type": "service_account"}', + project_id="test-project", + custom_llm_provider="vertex_ai", + ) + + +class TestModelGardenCredentialReuse: + def test_completion_uses_self_ensure_access_token(self): + """completion() should call self._ensure_access_token, not create a + throwaway VertexLLM instance.""" + garden = VertexAIModelGardenModels() + + mock_handler = MagicMock() + mock_handler.return_value.completion.return_value = "response" + + with ( + patch.dict(sys.modules, {"vertexai": _mock_vertexai()}), + patch.object( + garden, + "_ensure_access_token", + return_value=("cached-token", "test-project"), + ) as mock_ensure, + patch( + "litellm.llms.openai_like.chat.handler.OpenAILikeChatHandler", + mock_handler, + ), + ): + garden.completion( + model="openai/5464397967697903616", + messages=[{"role": "user", "content": "hello"}], + model_response=MagicMock(), + print_verbose=lambda *a, **kw: None, + encoding=MagicMock(), + logging_obj=MagicMock(), + api_base=None, + optional_params={}, + custom_prompt_dict={}, + headers=None, + timeout=30.0, + litellm_params={}, + vertex_project="test-project", + vertex_location="us-central1", + vertex_credentials='{"type": "service_account"}', + ) + + mock_ensure.assert_called_once_with( + credentials='{"type": "service_account"}', + project_id="test-project", + custom_llm_provider="vertex_ai", + ) diff --git a/tests/test_litellm/llms/vertex_ai/vertex_gemma_models/test_vertex_gemma_transformation.py b/tests/test_litellm/llms/vertex_ai/vertex_gemma_models/test_vertex_gemma_transformation.py index 3e3e8901706..b1c8f7234ce 100644 --- a/tests/test_litellm/llms/vertex_ai/vertex_gemma_models/test_vertex_gemma_transformation.py +++ b/tests/test_litellm/llms/vertex_ai/vertex_gemma_models/test_vertex_gemma_transformation.py @@ -122,17 +122,19 @@ class TestVertexGemmaCompletion: # Mock the async HTTP handler and Vertex authentication with ( patch( - "litellm.llms.custom_httpx.http_handler.AsyncHTTPHandler" - ) as mock_http_handler, + "litellm.llms.custom_httpx.http_handler.get_async_httpx_client" + ) as mock_get_client, patch( - "litellm.llms.vertex_ai.gemini.vertex_and_google_ai_studio_gemini.VertexLLM._ensure_access_token", + "litellm.llms.vertex_ai.vertex_gemma_models.main.VertexAIGemmaModels._ensure_access_token", return_value=("fake-access-token", "PROJECT_ID"), ), ): + mock_client = Mock() mock_response = Mock() mock_response.status_code = 200 mock_response.json.return_value = mock_vertex_response - mock_http_handler.return_value.post = AsyncMock(return_value=mock_response) + mock_client.post = AsyncMock(return_value=mock_response) + mock_get_client.return_value = mock_client # Call litellm.acompletion() response = await litellm.acompletion( @@ -145,7 +147,7 @@ class TestVertexGemmaCompletion: ) # Verify the request sent to Vertex - call_args = mock_http_handler.return_value.post.call_args + call_args = mock_client.post.call_args assert call_args is not None, "HTTP handler was not called" request_data = call_args.kwargs["json"] @@ -210,17 +212,19 @@ class TestVertexGemmaCompletion: with ( patch( - "litellm.llms.custom_httpx.http_handler.AsyncHTTPHandler" - ) as mock_http_handler, + "litellm.llms.custom_httpx.http_handler.get_async_httpx_client" + ) as mock_get_client, patch( - "litellm.llms.vertex_ai.gemini.vertex_and_google_ai_studio_gemini.VertexLLM._ensure_access_token", + "litellm.llms.vertex_ai.vertex_gemma_models.main.VertexAIGemmaModels._ensure_access_token", return_value=("fake-access-token", "test-project"), ), ): + mock_client = Mock() mock_response = Mock() mock_response.status_code = 200 mock_response.json.return_value = invalid_response - mock_http_handler.return_value.post = AsyncMock(return_value=mock_response) + mock_client.post = AsyncMock(return_value=mock_response) + mock_get_client.return_value = mock_client # Should raise exception (wrapped as APIConnectionError by LiteLLM) with pytest.raises(APIConnectionError) as exc_info: @@ -286,7 +290,7 @@ class TestVertexGemmaCompletion: "litellm.llms.custom_httpx.http_handler.get_async_httpx_client" ) as mock_get_client, patch( - "litellm.llms.vertex_ai.gemini.vertex_and_google_ai_studio_gemini.VertexLLM._ensure_access_token", + "litellm.llms.vertex_ai.vertex_gemma_models.main.VertexAIGemmaModels._ensure_access_token", return_value=("fake-access-token", "PROJECT_ID"), ), ): @@ -388,7 +392,7 @@ class TestVertexGemmaCompletion: "litellm.llms.custom_httpx.http_handler.get_async_httpx_client" ) as mock_get_client, patch( - "litellm.llms.vertex_ai.gemini.vertex_and_google_ai_studio_gemini.VertexLLM._ensure_access_token", + "litellm.llms.vertex_ai.vertex_gemma_models.main.VertexAIGemmaModels._ensure_access_token", return_value=("fake-access-token", "PROJECT_ID"), ), ): @@ -429,3 +433,123 @@ class TestVertexGemmaCompletion: # Verify other parameters are present assert "messages" in instance assert instance["@requestFormat"] == "chatCompletions" + + @pytest.mark.asyncio + async def test_acompletion_filters_context_management(self): + """ + Test that context_management is filtered out from the request. + + Vertex AI Gemma's chatCompletions wrapper does not understand + `context_management` (an Anthropic / OpenAI Responses API concept). + It must be stripped from the request body so the upstream endpoint + does not reject the request with an unknown-field error. + """ + mock_vertex_response = { + "deployedModelId": "1207280419999999999", + "model": "projects/993702345710/locations/us-central1/models/gemma-3-12b-it-1222199011122", + "modelDisplayName": "gemma-3-12b-it-1222199011122", + "modelVersionId": "1", + "predictions": { + "choices": [ + { + "finish_reason": "stop", + "index": 0, + "logprobs": None, + "message": { + "content": "ok", + "reasoning_content": None, + "role": "assistant", + "tool_calls": [], + }, + "stop_reason": None, + } + ], + "created": 1759863903, + "id": "chatcmpl-test-ctxmgmt", + "model": "google/gemma-3-12b-it", + "object": "chat.completion", + "prompt_logprobs": None, + "usage": { + "completion_tokens": 1, + "prompt_tokens": 5, + "prompt_tokens_details": None, + "total_tokens": 6, + }, + }, + } + + with ( + patch( + "litellm.llms.custom_httpx.http_handler.get_async_httpx_client" + ) as mock_get_client, + patch( + "litellm.llms.vertex_ai.vertex_gemma_models.main.VertexAIGemmaModels._ensure_access_token", + return_value=("fake-access-token", "PROJECT_ID"), + ), + ): + mock_client = Mock() + mock_response = Mock() + mock_response.status_code = 200 + mock_response.json.return_value = mock_vertex_response + mock_client.post = AsyncMock(return_value=mock_response) + mock_get_client.return_value = mock_client + + # Use `allowed_openai_params` so context_management actually + # reaches the transformation layer (otherwise the upstream + # validator drops it before we can prove the transformation + # strips it). This mirrors the real-world scenario where a + # caller explicitly opts in to forwarding an arbitrary param. + await litellm.acompletion( + model="vertex_ai/gemma/gemma-3-12b-it-1222199011122", + messages=[{"role": "user", "content": "Test"}], + context_management=[ + {"type": "compaction", "compact_threshold": 200000} + ], + allowed_openai_params=["context_management"], + api_base="https://test.us-central1-project.prediction.vertexai.goog/v1/projects/PROJECT_ID/locations/us-central1/endpoints/ENDPOINT_ID:predict", + vertex_project="PROJECT_ID", + vertex_location="us-central1", + ) + + call_args = mock_client.post.call_args + assert call_args is not None, "HTTP client was not called" + + request_data = call_args.kwargs["json"] + print("request body=", json.dumps(request_data, indent=4)) + instance = request_data["instances"][0] + + assert ( + "context_management" not in instance + ), "context_management should not be forwarded to Vertex Gemma" + assert instance["@requestFormat"] == "chatCompletions" + assert "messages" in instance + + def test_transform_request_strips_context_management(self): + """ + Direct unit test for VertexGemmaConfig.transform_request: verify that + `context_management` is stripped from `optional_params` regardless of + how it was supplied to the transformation layer. + """ + from litellm.llms.vertex_ai.vertex_gemma_models.transformation import ( + VertexGemmaConfig, + ) + + config = VertexGemmaConfig() + result = config.transform_request( + model="gemma-3-12b-it", + messages=[{"role": "user", "content": "hi"}], + optional_params={ + "max_tokens": 32, + "context_management": [ + {"type": "compaction", "compact_threshold": 200000} + ], + }, + litellm_params={}, + headers={}, + ) + + assert "instances" in result + instance = result["instances"][0] + assert instance["@requestFormat"] == "chatCompletions" + assert "context_management" not in instance + assert instance.get("max_tokens") == 32 diff --git a/tests/test_litellm/llms/xai/test_xai_chat_transformation.py b/tests/test_litellm/llms/xai/test_xai_chat_transformation.py index 3ae8dfc3c0b..5c1f0f704d7 100644 --- a/tests/test_litellm/llms/xai/test_xai_chat_transformation.py +++ b/tests/test_litellm/llms/xai/test_xai_chat_transformation.py @@ -119,3 +119,19 @@ class TestXAIParallelToolCalls: assert result.get("parallel_tool_calls") is True assert len(result["messages"]) == 1 assert result["messages"][0]["role"] == "user" + + +class TestXAIUsageNormalization: + def test_preserves_reasoning_tokens_in_total_usage(self): + usage = Usage(prompt_tokens=100, completion_tokens=50, total_tokens=200) + + XAIChatConfig._normalize_openai_compatible_usage_totals(usage) + + assert usage.total_tokens == 200 + + def test_preserves_reasoning_tokens_in_streaming_usage(self): + usage = {"prompt_tokens": 100, "completion_tokens": 50, "total_tokens": 200} + + XAIChatConfig._normalize_openai_compatible_usage_totals(usage) + + assert usage["total_tokens"] == 200 diff --git a/tests/test_litellm/proxy/auth/test_auth_checks.py b/tests/test_litellm/proxy/auth/test_auth_checks.py index 26f04a4abcb..35a3bd7f657 100644 --- a/tests/test_litellm/proxy/auth/test_auth_checks.py +++ b/tests/test_litellm/proxy/auth/test_auth_checks.py @@ -3016,3 +3016,340 @@ async def test_team_member_budget_check_zero_per_member_row_still_blocks(): proxy_logging_obj=proxy_logging_obj, ) assert exc_info.value.max_budget == 0.0 + + +# --- resolve_and_validate_end_user_id --------------------------------------- + + +@pytest.fixture +def _validate_flag_on(monkeypatch): + """Enable opt-in DB validation for the duration of a test.""" + import litellm + + monkeypatch.setattr(litellm, "validate_end_user_id_in_db", True) + monkeypatch.setattr(litellm, "max_end_user_budget_id", None) + + +def _validation_cache(): + cache = MagicMock() + cache.async_get_cache = AsyncMock(return_value=None) + cache.async_set_cache = AsyncMock() + return cache + + +def _patch_validation_helpers(monkeypatch, *, end_user=None, user=None, fuzzy=None): + """Stub out the DB helpers resolve_and_validate_end_user_id delegates to.""" + from litellm.proxy.auth import auth_checks + + monkeypatch.setattr( + auth_checks, "get_end_user_object", AsyncMock(return_value=end_user) + ) + monkeypatch.setattr(auth_checks, "get_user_object", AsyncMock(return_value=user)) + monkeypatch.setattr( + auth_checks, "_get_fuzzy_user_object", AsyncMock(return_value=fuzzy) + ) + + +@pytest.mark.asyncio +async def test_resolve_end_user_returns_none_for_none_input( + _validate_flag_on, monkeypatch +): + from litellm.proxy.auth.auth_checks import resolve_and_validate_end_user_id + + _patch_validation_helpers(monkeypatch) + cache = _validation_cache() + assert ( + await resolve_and_validate_end_user_id( + raw_end_user_id=None, + prisma_client=MagicMock(), + user_api_key_cache=cache, + ) + is None + ) + + +@pytest.mark.asyncio +async def test_resolve_end_user_passes_through_when_flag_disabled(monkeypatch): + """Default behaviour: flag is off, arbitrary ids pass through untouched.""" + import litellm + from litellm.proxy.auth.auth_checks import resolve_and_validate_end_user_id + + monkeypatch.setattr(litellm, "validate_end_user_id_in_db", False) + _patch_validation_helpers(monkeypatch) + cache = _validation_cache() + + result = await resolve_and_validate_end_user_id( + raw_end_user_id="codex-session-abc", + prisma_client=MagicMock(), + user_api_key_cache=cache, + ) + assert result == "codex-session-abc" + cache.async_set_cache.assert_not_awaited() + + +@pytest.mark.asyncio +async def test_resolve_end_user_passes_through_when_no_prisma_client( + _validate_flag_on, monkeypatch +): + from litellm.proxy.auth.auth_checks import resolve_and_validate_end_user_id + + _patch_validation_helpers(monkeypatch) + cache = _validation_cache() + + result = await resolve_and_validate_end_user_id( + raw_end_user_id="alice@example.com", + prisma_client=None, + user_api_key_cache=cache, + ) + assert result == "alice@example.com" + + +@pytest.mark.asyncio +async def test_resolve_end_user_matches_end_user_table(_validate_flag_on, monkeypatch): + from litellm.proxy.auth.auth_checks import resolve_and_validate_end_user_id + + _patch_validation_helpers(monkeypatch, end_user=MagicMock()) + cache = _validation_cache() + + result = await resolve_and_validate_end_user_id( + raw_end_user_id="customer-123", + prisma_client=MagicMock(), + user_api_key_cache=cache, + ) + assert result == "customer-123" + cache.async_set_cache.assert_awaited_once() + kwargs = cache.async_set_cache.await_args.kwargs + assert kwargs["key"] == "end_user_validation:customer-123" + assert kwargs["value"] == "valid" + + +@pytest.mark.asyncio +async def test_resolve_end_user_matches_user_table_by_user_id( + _validate_flag_on, monkeypatch +): + from litellm.proxy.auth import auth_checks + from litellm.proxy.auth.auth_checks import resolve_and_validate_end_user_id + + _patch_validation_helpers(monkeypatch, user=MagicMock()) + cache = _validation_cache() + + result = await resolve_and_validate_end_user_id( + raw_end_user_id="user-xyz", + prisma_client=MagicMock(), + user_api_key_cache=cache, + ) + assert result == "user-xyz" + # email fallback should not run for a non-email input + auth_checks._get_fuzzy_user_object.assert_not_awaited() + + +@pytest.mark.asyncio +async def test_resolve_end_user_matches_user_table_by_email( + _validate_flag_on, monkeypatch +): + """Email-shaped ids route through get_user_object with user_email set. + + The fuzzy lookup must happen inside get_user_object so it shares the + _should_check_db throttle and user_api_key_cache — no direct raw + Prisma calls on the auth path. + """ + from litellm.proxy.auth import auth_checks + from litellm.proxy.auth.auth_checks import resolve_and_validate_end_user_id + + _patch_validation_helpers(monkeypatch, user=MagicMock()) + cache = _validation_cache() + + result = await resolve_and_validate_end_user_id( + raw_end_user_id="Alice@Example.com", + prisma_client=MagicMock(), + user_api_key_cache=cache, + ) + assert result == "Alice@Example.com" + auth_checks.get_user_object.assert_awaited_once() + user_kwargs = auth_checks.get_user_object.await_args.kwargs + assert user_kwargs["user_id"] == "Alice@Example.com" + assert user_kwargs["user_email"] == "Alice@Example.com" + # email branch must not bypass the cached helper with a raw fuzzy call + auth_checks._get_fuzzy_user_object.assert_not_awaited() + + +@pytest.mark.asyncio +async def test_resolve_end_user_non_email_id_does_not_pass_user_email( + _validate_flag_on, monkeypatch +): + """Non-email ids skip the email fuzzy path to avoid a pointless DB hit.""" + from litellm.proxy.auth import auth_checks + from litellm.proxy.auth.auth_checks import resolve_and_validate_end_user_id + + _patch_validation_helpers(monkeypatch, user=MagicMock()) + cache = _validation_cache() + + await resolve_and_validate_end_user_id( + raw_end_user_id="user-xyz", + prisma_client=MagicMock(), + user_api_key_cache=cache, + ) + auth_checks.get_user_object.assert_awaited_once() + user_kwargs = auth_checks.get_user_object.await_args.kwargs + assert user_kwargs["user_email"] is None + + +@pytest.mark.asyncio +async def test_resolve_end_user_drops_codex_opaque_identifier( + _validate_flag_on, monkeypatch +): + from litellm.proxy.auth.auth_checks import resolve_and_validate_end_user_id + + _patch_validation_helpers(monkeypatch) # all helpers return None + cache = _validation_cache() + + codex_id = ( + "user_8a4a360c36621665b341e06fb76041d9b6def732bb183eea148d4abc9d97c1de" + "_account__session_a2bce4a5-8887-44ef-b491-fbf0a55c6569" + ) + result = await resolve_and_validate_end_user_id( + raw_end_user_id=codex_id, + prisma_client=MagicMock(), + user_api_key_cache=cache, + ) + assert result is None + cache.async_set_cache.assert_awaited_once() + kwargs = cache.async_set_cache.await_args.kwargs + assert kwargs["value"] == "invalid" + + +@pytest.mark.asyncio +async def test_resolve_end_user_preserves_id_when_default_budget_configured( + _validate_flag_on, monkeypatch +): + """Don't drop unregistered ids when litellm.max_end_user_budget_id is set. + + The default end-user budget is applied downstream when the id is present + but not found in the db — dropping the id here would bypass those limits. + """ + import litellm + from litellm.proxy.auth.auth_checks import resolve_and_validate_end_user_id + + monkeypatch.setattr(litellm, "max_end_user_budget_id", "default-budget") + _patch_validation_helpers(monkeypatch) + cache = _validation_cache() + + result = await resolve_and_validate_end_user_id( + raw_end_user_id="new-customer", + prisma_client=MagicMock(), + user_api_key_cache=cache, + ) + assert result == "new-customer" + + +@pytest.mark.asyncio +async def test_resolve_end_user_drops_unknown_email(_validate_flag_on, monkeypatch): + from litellm.proxy.auth.auth_checks import resolve_and_validate_end_user_id + + _patch_validation_helpers(monkeypatch) + cache = _validation_cache() + + result = await resolve_and_validate_end_user_id( + raw_end_user_id="stranger@example.com", + prisma_client=MagicMock(), + user_api_key_cache=cache, + ) + assert result is None + + +@pytest.mark.asyncio +async def test_resolve_end_user_uses_cached_valid_result( + _validate_flag_on, monkeypatch +): + from litellm.proxy.auth import auth_checks + from litellm.proxy.auth.auth_checks import resolve_and_validate_end_user_id + + _patch_validation_helpers(monkeypatch) + cache = _validation_cache() + cache.async_get_cache = AsyncMock(return_value="valid") + + result = await resolve_and_validate_end_user_id( + raw_end_user_id="alice@example.com", + prisma_client=MagicMock(), + user_api_key_cache=cache, + ) + assert result == "alice@example.com" + auth_checks.get_end_user_object.assert_not_awaited() + auth_checks.get_user_object.assert_not_awaited() + auth_checks._get_fuzzy_user_object.assert_not_awaited() + + +@pytest.mark.asyncio +async def test_resolve_end_user_uses_cached_invalid_result( + _validate_flag_on, monkeypatch +): + from litellm.proxy.auth import auth_checks + from litellm.proxy.auth.auth_checks import resolve_and_validate_end_user_id + + _patch_validation_helpers(monkeypatch, end_user=MagicMock()) + cache = _validation_cache() + cache.async_get_cache = AsyncMock(return_value="invalid") + + result = await resolve_and_validate_end_user_id( + raw_end_user_id="bogus", + prisma_client=MagicMock(), + user_api_key_cache=cache, + ) + assert result is None + # Despite a matching row configured, helpers aren't called — cache wins. + auth_checks.get_end_user_object.assert_not_awaited() + + +@pytest.mark.asyncio +async def test_resolve_end_user_swallows_db_errors_and_returns_none( + _validate_flag_on, monkeypatch +): + from litellm.proxy.auth import auth_checks + from litellm.proxy.auth.auth_checks import resolve_and_validate_end_user_id + + monkeypatch.setattr( + auth_checks, + "get_end_user_object", + AsyncMock(side_effect=Exception("db down")), + ) + monkeypatch.setattr( + auth_checks, + "get_user_object", + AsyncMock(side_effect=Exception("db down")), + ) + cache = _validation_cache() + + result = await resolve_and_validate_end_user_id( + raw_end_user_id="alice@example.com", + prisma_client=MagicMock(), + user_api_key_cache=cache, + ) + # DB errors shouldn't raise through the auth path — treat as unknown. + assert result is None + + +@pytest.mark.asyncio +async def test_resolve_end_user_reraises_budget_exceeded( + _validate_flag_on, monkeypatch +): + """BudgetExceededError from get_end_user_object must bubble up so the + auth path enforces spend limits instead of silently dropping the id.""" + import litellm + from litellm.proxy.auth import auth_checks + from litellm.proxy.auth.auth_checks import resolve_and_validate_end_user_id + + monkeypatch.setattr( + auth_checks, + "get_end_user_object", + AsyncMock( + side_effect=litellm.BudgetExceededError(current_cost=10.0, max_budget=5.0) + ), + ) + cache = _validation_cache() + + with pytest.raises(litellm.BudgetExceededError): + await resolve_and_validate_end_user_id( + raw_end_user_id="customer-over-budget", + prisma_client=MagicMock(), + user_api_key_cache=cache, + ) diff --git a/tests/test_litellm/proxy/auth/test_auth_utils.py b/tests/test_litellm/proxy/auth/test_auth_utils.py index 08035fb7173..68e1636d380 100644 --- a/tests/test_litellm/proxy/auth/test_auth_utils.py +++ b/tests/test_litellm/proxy/auth/test_auth_utils.py @@ -597,6 +597,315 @@ def test_get_end_user_id_falls_back_to_deprecated_user_header_name(): assert result == "user-legacy" +class TestCoerceUserIdToStr: + """Unit tests for the _coerce_user_id_to_str helper.""" + + def test_plain_string_is_returned_verbatim(self): + from litellm.proxy.auth.auth_utils import _coerce_user_id_to_str + + assert _coerce_user_id_to_str("alice@example.com") == "alice@example.com" + + def test_string_is_stripped(self): + from litellm.proxy.auth.auth_utils import _coerce_user_id_to_str + + assert _coerce_user_id_to_str(" bob ") == "bob" + + def test_codex_opaque_identifier_is_preserved(self): + from litellm.proxy.auth.auth_utils import _coerce_user_id_to_str + + codex_id = ( + "user_8a4a360c36621665b341e06fb76041d9b6def732bb183eea148d4abc9d97c1de" + "_account__session_a2bce4a5-8887-44ef-b491-fbf0a55c6569" + ) + assert _coerce_user_id_to_str(codex_id) == codex_id + + def test_none_returns_none(self): + from litellm.proxy.auth.auth_utils import _coerce_user_id_to_str + + assert _coerce_user_id_to_str(None) is None + + def test_empty_string_returns_none(self): + from litellm.proxy.auth.auth_utils import _coerce_user_id_to_str + + assert _coerce_user_id_to_str("") is None + assert _coerce_user_id_to_str(" ") is None + + def test_dict_returns_none(self): + from litellm.proxy.auth.auth_utils import _coerce_user_id_to_str + + payload = { + "device_id": "abc", + "account_uuid": "", + "session_id": "c284b8cb", + } + assert _coerce_user_id_to_str(payload) is None + + def test_list_returns_none(self): + from litellm.proxy.auth.auth_utils import _coerce_user_id_to_str + + assert _coerce_user_id_to_str(["a", "b"]) is None + + def test_json_encoded_dict_string_passes_through_by_default(self): + """JSON-encoded dict strings are preserved unless opt-in flag is on. + + This preserves backwards compatibility: existing deployments that + intentionally pass JSON-encoded user identifiers keep working. + """ + import litellm + from litellm.proxy.auth.auth_utils import _coerce_user_id_to_str + + blob = ( + '{"device_id":"d5abe9199ee7759a0558974e9371e78c7b38d7621aae26d6609c1de61af6afb0",' + '"account_uuid":"","session_id":"c284b8cb-a050-4278-8599-cc4e016a10ab"}' + ) + original = litellm.validate_end_user_id_in_db + litellm.validate_end_user_id_in_db = False + try: + assert _coerce_user_id_to_str(blob) == blob + finally: + litellm.validate_end_user_id_in_db = original + + def test_json_encoded_dict_string_returns_none_when_validation_enabled(self): + import litellm + from litellm.proxy.auth.auth_utils import _coerce_user_id_to_str + + # Same broken shape we saw in spend logs, but pre-stringified to JSON. + blob = ( + '{"device_id":"d5abe9199ee7759a0558974e9371e78c7b38d7621aae26d6609c1de61af6afb0",' + '"account_uuid":"","session_id":"c284b8cb-a050-4278-8599-cc4e016a10ab"}' + ) + original = litellm.validate_end_user_id_in_db + litellm.validate_end_user_id_in_db = True + try: + assert _coerce_user_id_to_str(blob) is None + finally: + litellm.validate_end_user_id_in_db = original + + def test_json_encoded_list_string_passes_through_by_default(self): + import litellm + from litellm.proxy.auth.auth_utils import _coerce_user_id_to_str + + original = litellm.validate_end_user_id_in_db + litellm.validate_end_user_id_in_db = False + try: + assert _coerce_user_id_to_str('["a","b"]') == '["a","b"]' + finally: + litellm.validate_end_user_id_in_db = original + + def test_json_encoded_list_string_returns_none_when_validation_enabled(self): + import litellm + from litellm.proxy.auth.auth_utils import _coerce_user_id_to_str + + original = litellm.validate_end_user_id_in_db + litellm.validate_end_user_id_in_db = True + try: + assert _coerce_user_id_to_str('["a","b"]') is None + finally: + litellm.validate_end_user_id_in_db = original + + def test_int_returns_str(self): + from litellm.proxy.auth.auth_utils import _coerce_user_id_to_str + + assert _coerce_user_id_to_str(12345) == "12345" + + def test_bool_returns_none(self): + from litellm.proxy.auth.auth_utils import _coerce_user_id_to_str + + # bool is an int subclass — reject explicitly, never produce "True"/"False". + assert _coerce_user_id_to_str(True) is None + assert _coerce_user_id_to_str(False) is None + + def test_brace_string_that_isnt_json_is_kept(self): + """A string starting with `{` but failing to parse stays as-is.""" + from litellm.proxy.auth.auth_utils import _coerce_user_id_to_str + + assert _coerce_user_id_to_str("{not json") == "{not json" + + +class TestGetEndUserIdDropsMalformedBodyValues: + """Tests that get_end_user_id_from_request_body drops dict-shaped values + rather than stringifying them into spend logs.""" + + def test_dict_user_falls_through_to_litellm_metadata(self): + request_body = { + "user": { + "device_id": "abc", + "session_id": "c284b8cb", + }, + "litellm_metadata": {"user": "alice@example.com"}, + } + + with patch("litellm.proxy.proxy_server.general_settings", {}): + result = get_end_user_id_from_request_body( + request_body=request_body, request_headers={} + ) + + assert result == "alice@example.com" + + def test_dict_user_with_no_other_sources_returns_none(self): + request_body = { + "user": {"device_id": "abc", "session_id": "xyz"}, + } + + with patch("litellm.proxy.proxy_server.general_settings", {}): + result = get_end_user_id_from_request_body( + request_body=request_body, request_headers={} + ) + + assert result is None + + def test_json_encoded_user_string_passes_through_by_default(self): + """JSON-encoded user strings pass through unless validation is opted in. + + Gating behind ``litellm.validate_end_user_id_in_db`` keeps existing + deployments that send JSON-encoded identifiers working until they + explicitly opt into the stricter extraction. + """ + import litellm + + blob = ( + '{"device_id":"d5abe9199ee7759a","account_uuid":"",' + '"session_id":"c284b8cb-a050-4278-8599-cc4e016a10ab"}' + ) + request_body = {"user": blob} + + original = litellm.validate_end_user_id_in_db + litellm.validate_end_user_id_in_db = False + try: + with patch("litellm.proxy.proxy_server.general_settings", {}): + result = get_end_user_id_from_request_body( + request_body=request_body, request_headers={} + ) + finally: + litellm.validate_end_user_id_in_db = original + + assert result == blob + + def test_json_encoded_user_string_returns_none_when_validation_enabled(self): + import litellm + + request_body = { + "user": ( + '{"device_id":"d5abe9199ee7759a","account_uuid":"",' + '"session_id":"c284b8cb-a050-4278-8599-cc4e016a10ab"}' + ), + } + + original = litellm.validate_end_user_id_in_db + litellm.validate_end_user_id_in_db = True + try: + with patch("litellm.proxy.proxy_server.general_settings", {}): + result = get_end_user_id_from_request_body( + request_body=request_body, request_headers={} + ) + finally: + litellm.validate_end_user_id_in_db = original + + assert result is None + + def test_plain_string_user_is_preserved(self): + request_body = {"user": "alice@example.com"} + + with patch("litellm.proxy.proxy_server.general_settings", {}): + result = get_end_user_id_from_request_body( + request_body=request_body, request_headers={} + ) + + assert result == "alice@example.com" + + def test_codex_opaque_user_is_preserved(self): + codex_id = ( + "user_8a4a360c36621665b341e06fb76041d9b6def732bb183eea148d4abc9d97c1de" + "_account__session_a2bce4a5-8887-44ef-b491-fbf0a55c6569" + ) + request_body = {"user": codex_id} + + with patch("litellm.proxy.proxy_server.general_settings", {}): + result = get_end_user_id_from_request_body( + request_body=request_body, request_headers={} + ) + + assert result == codex_id + + def test_int_user_is_coerced_to_string(self): + request_body = {"user": 12345} + + with patch("litellm.proxy.proxy_server.general_settings", {}): + result = get_end_user_id_from_request_body( + request_body=request_body, request_headers={} + ) + + assert result == "12345" + + def test_list_user_falls_through(self): + request_body = { + "user": ["a", "b"], + "safety_identifier": "alice@example.com", + } + + with patch("litellm.proxy.proxy_server.general_settings", {}): + result = get_end_user_id_from_request_body( + request_body=request_body, request_headers={} + ) + + assert result == "alice@example.com" + + def test_dict_safety_identifier_returns_none(self): + request_body = { + "safety_identifier": {"device_id": "abc"}, + } + + with patch("litellm.proxy.proxy_server.general_settings", {}): + result = get_end_user_id_from_request_body( + request_body=request_body, request_headers={} + ) + + assert result is None + + def test_dict_metadata_user_id_returns_none(self): + request_body = { + "metadata": {"user_id": {"device_id": "abc"}}, + } + + with patch("litellm.proxy.proxy_server.general_settings", {}): + result = get_end_user_id_from_request_body( + request_body=request_body, request_headers={} + ) + + assert result is None + + def test_whitespace_user_falls_through(self): + request_body = {"user": " ", "safety_identifier": "alice@example.com"} + + with patch("litellm.proxy.proxy_server.general_settings", {}): + result = get_end_user_id_from_request_body( + request_body=request_body, request_headers={} + ) + + assert result == "alice@example.com" + + def test_dict_user_header_falls_through_to_body(self): + """A dict-shaped value in a configured user-id header is dropped, not stringified.""" + general_settings = {"user_header_name": "x-custom-user-id"} + # A header value will normally be a str, but be defensive: the coercion + # must drop anything that isn't a usable identifier. + headers = {"x-custom-user-id": {"device_id": "abc"}} + request_body = {"user": "alice@example.com"} + + with ( + patch( + "litellm.proxy.auth.auth_utils._get_customer_id_from_standard_headers", + return_value=None, + ), + patch("litellm.proxy.proxy_server.general_settings", general_settings), + ): + result = get_end_user_id_from_request_body( + request_body=request_body, request_headers=headers + ) + + assert result == "alice@example.com" + + def _make_deployment_dict( model_name: str, tpm: Optional[int] = None, rpm: Optional[int] = None ) -> dict: diff --git a/tests/test_litellm/proxy/auth/test_model_checks.py b/tests/test_litellm/proxy/auth/test_model_checks.py index 77aa03032a7..f38ac5c2000 100644 --- a/tests/test_litellm/proxy/auth/test_model_checks.py +++ b/tests/test_litellm/proxy/auth/test_model_checks.py @@ -249,3 +249,241 @@ def test_get_complete_model_list_byok_wildcard_expansion(): assert len(result) > 0 assert all(m.startswith("openai/") for m in result) assert "openai/*" not in result + + +def test_get_complete_model_list_expands_team_scoped_wildcard_with_stored_credential( + monkeypatch, +): + """ + Team-scoped BYOK wildcard deployments are stored under an internal model_name, + with the public wildcard name in model_info.team_public_model_name. + """ + import litellm + from litellm import Router + from litellm.proxy.auth import model_checks + from litellm.proxy.auth.model_checks import get_complete_model_list + from litellm.types.utils import CredentialItem + + monkeypatch.setattr( + litellm, + "credential_list", + [ + CredentialItem( + credential_name="openai-credential", + credential_info={"provider": "openai"}, + credential_values={ + "api_key": "stored-openai-key", + "api_base": "https://example.openai.test/v1", + }, + ) + ], + ) + + captured_params = {} + + def fake_get_provider_models(provider, litellm_params=None): + captured_params["provider"] = provider + captured_params["api_key"] = litellm_params.api_key + captured_params["api_base"] = litellm_params.api_base + captured_params["credential_name"] = litellm_params.litellm_credential_name + return ["gpt-4o"] + + monkeypatch.setattr(model_checks, "get_provider_models", fake_get_provider_models) + + router = Router( + model_list=[ + { + "model_name": "model_name_team-1_generated", + "litellm_params": { + "model": "openai/*", + "custom_llm_provider": "openai", + "litellm_credential_name": "openai-credential", + }, + "model_info": { + "team_id": "team-1", + "team_public_model_name": "openai/*", + }, + } + ] + ) + + result = get_complete_model_list( + key_models=[], + team_models=["openai/*"], + proxy_model_list=[], + user_model=None, + infer_model_from_keys=False, + llm_router=router, + team_id="team-1", + ) + + assert "openai/gpt-4o" in result + assert captured_params == { + "provider": "openai", + "api_key": "stored-openai-key", + "api_base": "https://example.openai.test/v1", + "credential_name": None, + } + + +def test_wildcard_credential_hydration_preserves_deployment_params( + monkeypatch, +): + import litellm + from litellm.proxy.auth import model_checks + from litellm.proxy.auth.model_checks import get_known_models_from_wildcard + from litellm.types.router import LiteLLM_Params + from litellm.types.utils import CredentialItem + + monkeypatch.setattr( + litellm, + "credential_list", + [ + CredentialItem( + credential_name="openai-credential", + credential_info={"provider": "openai"}, + credential_values={ + "api_key": "stored-openai-key", + "api_version": "credential-version", + "model": "openai/wrong-model", + "unexpected_field": "unexpected-value", + }, + ) + ], + ) + + captured_params = {} + + def fake_get_provider_models(provider, litellm_params=None): + captured_params["provider"] = provider + captured_params["model"] = litellm_params.model + captured_params["api_key"] = litellm_params.api_key + captured_params["api_version"] = litellm_params.api_version + captured_params["credential_name"] = litellm_params.litellm_credential_name + captured_params["has_unexpected_field"] = hasattr( + litellm_params, "unexpected_field" + ) + return ["gpt-4o"] + + monkeypatch.setattr(model_checks, "get_provider_models", fake_get_provider_models) + + result = get_known_models_from_wildcard( + wildcard_model="openai/*", + litellm_params=LiteLLM_Params( + model="openai/*", + custom_llm_provider="openai", + api_version="deployment-version", + litellm_credential_name="openai-credential", + ), + ) + + assert result == ["openai/gpt-4o"] + assert captured_params == { + "provider": "openai", + "model": "openai/*", + "api_key": "stored-openai-key", + "api_version": "deployment-version", + "credential_name": None, + "has_unexpected_field": False, + } + + +def test_wildcard_credential_hydration_preserves_missing_credential_name( + monkeypatch, +): + import litellm + from litellm.proxy.auth import model_checks + from litellm.proxy.auth.model_checks import get_known_models_from_wildcard + from litellm.types.router import LiteLLM_Params + + monkeypatch.setattr(litellm, "credential_list", []) + + captured_params = {} + + def fake_get_provider_models(provider, litellm_params=None): + captured_params["provider"] = provider + captured_params["api_key"] = litellm_params.api_key + captured_params["credential_name"] = litellm_params.litellm_credential_name + return ["gpt-4o"] + + monkeypatch.setattr(model_checks, "get_provider_models", fake_get_provider_models) + + result = get_known_models_from_wildcard( + wildcard_model="openai/*", + litellm_params=LiteLLM_Params( + model="openai/*", + custom_llm_provider="openai", + api_key=None, + litellm_credential_name="missing-credential", + ), + ) + + assert result == ["openai/gpt-4o"] + assert captured_params == { + "provider": "openai", + "api_key": None, + "credential_name": "missing-credential", + } + + +@pytest.mark.asyncio +async def test_get_available_models_for_user_expands_query_team_wildcard( + monkeypatch, +): + import litellm + from litellm import Router + from litellm.proxy.auth import model_checks + from litellm.proxy._types import UserAPIKeyAuth + from litellm.proxy.utils import get_available_models_for_user + from litellm.types.utils import CredentialItem + + monkeypatch.setattr( + litellm, + "credential_list", + [ + CredentialItem( + credential_name="openai-credential", + credential_info={"provider": "openai"}, + credential_values={"api_key": "stored-openai-key"}, + ) + ], + ) + + def fake_get_provider_models(provider, litellm_params=None): + assert litellm_params.api_key == "stored-openai-key" + assert litellm_params.litellm_credential_name is None + return ["gpt-4o-mini"] + + monkeypatch.setattr(model_checks, "get_provider_models", fake_get_provider_models) + + router = Router( + model_list=[ + { + "model_name": "model_name_team-1_generated", + "litellm_params": { + "model": "openai/*", + "custom_llm_provider": "openai", + "litellm_credential_name": "openai-credential", + }, + "model_info": { + "team_id": "team-1", + "team_public_model_name": "openai/*", + }, + } + ] + ) + + result = await get_available_models_for_user( + user_api_key_dict=UserAPIKeyAuth( + api_key="sk-test", + models=[], + team_id="team-1", + team_models=["openai/*"], + ), + llm_router=router, + general_settings={}, + user_model=None, + team_id="team-1", + ) + + assert "openai/gpt-4o-mini" in result diff --git a/tests/test_litellm/proxy/auth/test_user_api_key_auth.py b/tests/test_litellm/proxy/auth/test_user_api_key_auth.py index 442625c75a7..defd3bbcdcd 100644 --- a/tests/test_litellm/proxy/auth/test_user_api_key_auth.py +++ b/tests/test_litellm/proxy/auth/test_user_api_key_auth.py @@ -3335,3 +3335,125 @@ async def test_master_key_auth_substitutes_alias_for_api_key(): finally: for k, v in _orig.items(): setattr(_proxy_server_mod, k, v) + + +@pytest.mark.asyncio +async def test_user_api_key_auth_sets_end_user_id_when_builder_skips_it(): + """Defense-in-depth: ``_user_api_key_auth_builder`` has multiple + early-return paths (master_key=None, /user/auth route, JWT + short-circuits) that bypass the end-user resolution block. The wrapper + must still attribute spend logs to the request-supplied end-user when + none of those paths set it. + + Krrish flagged the removal of this fallback as a regression risk; this + test pins the behaviour so future refactors don't silently drop it. + """ + from fastapi import Request + from starlette.datastructures import URL + + import litellm.proxy.proxy_server as _proxy_server_mod + + builder_token = UserAPIKeyAuth(api_key="sk-test", user_id="u1") + # builder did NOT set end_user_id (e.g. master_key=None early return) + assert builder_token.end_user_id is None + + request = Request( + scope={ + "type": "http", + "headers": [(b"content-type", b"application/json")], + "method": "POST", + } + ) + request._url = URL(url="/chat/completions") + request._body = json.dumps( + {"model": "gpt-4o", "user": "alice@example.com"} + ).encode() + + attrs = _proxy_attrs_for_centralized_checks(user_custom_auth=None) + originals = {a: getattr(_proxy_server_mod, a, None) for a in attrs} + try: + for k, v in attrs.items(): + setattr(_proxy_server_mod, k, v) + # Stub the builder so the test doesn't have to traverse the full + # auth state machine; we only care about the wrapper's safety net. + with ( + patch( + "litellm.proxy.auth.user_api_key_auth._user_api_key_auth_builder", + new_callable=AsyncMock, + return_value=builder_token, + ), + patch( + "litellm.proxy.auth.user_api_key_auth._run_centralized_common_checks", + new_callable=AsyncMock, + ), + patch( + "litellm.proxy.auth.user_api_key_auth.RouteChecks.should_call_route", + ), + ): + result = await user_api_key_auth(request=request, api_key="Bearer sk-test") + + # Validation flag is False by default → pass-through, raw value lands + # on the auth obj instead of being silently dropped. + assert result.end_user_id == "alice@example.com" + finally: + for k, v in originals.items(): + setattr(_proxy_server_mod, k, v) + + +@pytest.mark.asyncio +async def test_user_api_key_auth_does_not_overwrite_end_user_id_set_by_builder(): + """When the builder already resolved the end-user id (the primary + path), the wrapper-level safety net must not run a second resolution + pass — that would re-extract from the request body and could + overwrite a value the builder explicitly chose to set.""" + from fastapi import Request + from starlette.datastructures import URL + + import litellm.proxy.proxy_server as _proxy_server_mod + + builder_token = UserAPIKeyAuth( + api_key="sk-test", user_id="u1", end_user_id="builder-resolved-id" + ) + + request = Request( + scope={ + "type": "http", + "headers": [(b"content-type", b"application/json")], + "method": "POST", + } + ) + request._url = URL(url="/chat/completions") + request._body = json.dumps( + {"model": "gpt-4o", "user": "different-id-from-body"} + ).encode() + + attrs = _proxy_attrs_for_centralized_checks(user_custom_auth=None) + originals = {a: getattr(_proxy_server_mod, a, None) for a in attrs} + try: + for k, v in attrs.items(): + setattr(_proxy_server_mod, k, v) + with ( + patch( + "litellm.proxy.auth.user_api_key_auth._user_api_key_auth_builder", + new_callable=AsyncMock, + return_value=builder_token, + ), + patch( + "litellm.proxy.auth.user_api_key_auth._run_centralized_common_checks", + new_callable=AsyncMock, + ), + patch( + "litellm.proxy.auth.user_api_key_auth.RouteChecks.should_call_route", + ), + patch( + "litellm.proxy.auth.user_api_key_auth.resolve_and_validate_end_user_id", + new_callable=AsyncMock, + ) as mock_resolve, + ): + result = await user_api_key_auth(request=request, api_key="Bearer sk-test") + + assert result.end_user_id == "builder-resolved-id" + mock_resolve.assert_not_awaited() + finally: + for k, v in originals.items(): + setattr(_proxy_server_mod, k, v) diff --git a/tests/test_litellm/proxy/common_utils/test_http_parsing_utils.py b/tests/test_litellm/proxy/common_utils/test_http_parsing_utils.py index b4343f6b2e1..3d7cb1e35f3 100644 --- a/tests/test_litellm/proxy/common_utils/test_http_parsing_utils.py +++ b/tests/test_litellm/proxy/common_utils/test_http_parsing_utils.py @@ -16,6 +16,7 @@ sys.path.insert( import litellm from litellm.proxy._types import ProxyException from litellm.proxy.common_utils.http_parsing_utils import ( + _is_form_content_type, _read_request_body, _safe_get_request_headers, _safe_get_request_parsed_body, @@ -853,3 +854,145 @@ class TestGetTagsFromRequestBodyStringCoerce: tags = get_tags_from_request_body({"metadata": {"tags": ["x"]}}) assert tags == ["x"] + + +class TestIsFormContentType: + @pytest.mark.parametrize( + "content_type", + [ + "application/x-www-form-urlencoded", + "multipart/form-data", + "multipart/form-data; boundary=----WebKitFormBoundary", + "Application/X-WWW-Form-Urlencoded", + " multipart/form-data ", + "application/x-www-form-urlencoded; charset=utf-8", + ], + ) + def test_form_types_match(self, content_type): + assert _is_form_content_type(content_type) is True + + @pytest.mark.parametrize( + "content_type", + [ + "", + "application/json", + "application/json; charset=utf-8", + "application/form-json", + "multiform/anything", + "application/json; xform=1", + "application/xml-with-form-data-but-not-actually", + "text/plain", + "form", + ], + ) + def test_non_form_types_rejected(self, content_type): + assert _is_form_content_type(content_type) is False + + +class TestReadRequestBodyNonCanonicalContentType: + """A JSON body with a ``"form"``-substring Content-Type must parse as JSON.""" + + @pytest.mark.asyncio + @pytest.mark.parametrize( + "content_type", + [ + "application/form-json", + "application/json; xform=1", + "multiform/anything", + ], + ) + async def test_json_body_with_formlike_content_type_parses_as_json( + self, content_type + ): + payload = {"user_config": {"model_list": []}, "model": "x"} + + mock_request = MagicMock() + mock_request.body = AsyncMock(return_value=orjson.dumps(payload)) + mock_request.form = AsyncMock(return_value={}) + mock_request.headers = {"content-type": content_type} + mock_request.scope = {} + + result = await _read_request_body(mock_request) + assert result == payload + mock_request.form.assert_not_called() + + @pytest.mark.asyncio + async def test_real_form_post_still_parsed_as_form(self): + mock_request = MagicMock() + mock_request.form = AsyncMock(return_value={"k": "v"}) + mock_request.body = AsyncMock(return_value=b"") + mock_request.headers = {"content-type": "application/x-www-form-urlencoded"} + mock_request.scope = {} + + result = await _read_request_body(mock_request) + assert result == {"k": "v"} + mock_request.form.assert_awaited_once() + + +class TestReadRequestBodyFormParseFailure: + """ + A failed ``request.form()`` parse (e.g. multipart with missing boundary) + must surface as a 400, not silently return ``{}`` — otherwise the + auth-time pre-read sees an empty body while a later raw-body re-read + sees the original payload, defeating every banned-param check. + """ + + @pytest.mark.asyncio + @pytest.mark.parametrize( + "raised_exception", + [ + ValueError("Missing boundary in multipart."), + AssertionError("malformed chunk"), + RuntimeError("form parser exploded"), + ], + ) + async def test_form_parse_failure_raises_400(self, raised_exception): + mock_request = MagicMock() + mock_request.form = AsyncMock(side_effect=raised_exception) + mock_request.headers = {"content-type": "multipart/form-data"} + mock_request.scope = {} + + with pytest.raises(ProxyException) as exc_info: + await _read_request_body(mock_request) + assert str(exc_info.value.code) == "400" + + +class TestGetRequestBody: + @pytest.mark.asyncio + async def test_json_with_charset_param_parses_as_json(self): + payload = {"k": "v"} + mock_request = MagicMock() + mock_request.method = "POST" + mock_request.body = AsyncMock(return_value=orjson.dumps(payload)) + mock_request.headers = {"content-type": "application/json; charset=utf-8"} + mock_request.scope = {} + + result = await get_request_body(mock_request) + assert result == payload + + @pytest.mark.asyncio + async def test_form_post_routes_to_form_data(self): + mock_request = MagicMock() + mock_request.method = "POST" + mock_request.headers = {"content-type": "multipart/form-data; boundary=x"} + mock_request.form = AsyncMock(return_value={"k": "v"}) + mock_request.scope = {} + + result = await get_request_body(mock_request) + assert result == {"k": "v"} + + @pytest.mark.asyncio + async def test_substring_match_no_longer_accepted(self): + mock_request = MagicMock() + mock_request.method = "POST" + mock_request.headers = {"content-type": "application/form-json"} + mock_request.scope = {} + + with pytest.raises(ValueError, match="Unsupported content type"): + await get_request_body(mock_request) + + @pytest.mark.asyncio + async def test_non_post_returns_empty(self): + mock_request = MagicMock() + mock_request.method = "GET" + assert await get_request_body(mock_request) == {} 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 a3247d2e557..71178c4826c 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 @@ -2073,6 +2073,226 @@ def test_get_http_exception_includes_assessments_and_identifier(): assert exc.detail["assessments"][0]["matches"][0]["match"] == "[REDACTED]" +def test_extract_violation_category_names_mixed_policies(): + """Topic names, content-filter types, PII types, and managed-word types + flatten into a single category-name list — using only the operator- + defined `name`/`type` labels.""" + g = _make_guardrail() + response = { + "action": "GUARDRAIL_INTERVENED", + "assessments": [ + { + "topicPolicy": { + "topics": [ + {"name": "Fiduciary Advice", "action": "BLOCKED"}, + {"name": "Tax Advice", "action": "BLOCKED"}, + ] + }, + "contentPolicy": { + "filters": [{"type": "VIOLENCE", "action": "BLOCKED"}] + }, + "wordPolicy": { + "managedWordLists": [{"type": "PROFANITY", "action": "BLOCKED"}], + }, + "sensitiveInformationPolicy": { + "piiEntities": [{"type": "EMAIL", "action": "BLOCKED"}] + }, + } + ], + } + names = g._extract_violation_category_names(response) + assert "Fiduciary Advice" in names + assert "Tax Advice" in names + assert "VIOLENCE" in names + assert "PROFANITY" in names + assert "EMAIL" in names + + +def test_extract_violation_category_names_does_not_leak_user_input(): + """SECURITY: customWords.match is the raw user-submitted word that + triggered the rule, and an unnamed regex match is the actual sensitive + value (e.g. a credit-card number). Neither must appear in + violation_categories — otherwise the content the guardrail blocked + leaks straight into telemetry backends.""" + g = _make_guardrail() + response = { + "action": "GUARDRAIL_INTERVENED", + "assessments": [ + { + "wordPolicy": { + "customWords": [ + {"match": "secret-codeword-abc-123", "action": "BLOCKED"} + ], + }, + "sensitiveInformationPolicy": { + "regexes": [{"match": "4111-1111-1111-1111", "action": "BLOCKED"}] + }, + } + ], + } + names = g._extract_violation_category_names(response) + assert "secret-codeword-abc-123" not in names + assert "4111-1111-1111-1111" not in names + assert names == [] + + +def test_extract_violation_category_names_named_regex_uses_name(): + """A regex with a `name` field surfaces that operator-defined label + (safe to log), not the matched value.""" + g = _make_guardrail() + response = { + "action": "GUARDRAIL_INTERVENED", + "assessments": [ + { + "sensitiveInformationPolicy": { + "regexes": [ + { + "name": "credit-card-pattern", + "match": "4111-1111-1111-1111", + "action": "BLOCKED", + } + ] + } + } + ], + } + names = g._extract_violation_category_names(response) + assert names == ["credit-card-pattern"] + + +def test_extract_violation_category_names_skips_anonymized(): + """ANONYMIZED entries are not blocks — they must not contribute to the + violation_categories list.""" + g = _make_guardrail() + response = { + "action": "GUARDRAIL_INTERVENED", + "assessments": [ + { + "sensitiveInformationPolicy": { + "piiEntities": [{"type": "NAME", "action": "ANONYMIZED"}] + } + } + ], + } + assert g._extract_violation_category_names(response) == [] + + +def test_extract_violation_category_names_no_assessments(): + """Empty / missing assessments → empty list, not an error.""" + g = _make_guardrail() + assert g._extract_violation_category_names({"action": "NONE"}) == [] + assert g._extract_violation_category_names({"assessments": None}) == [] + + +@pytest.mark.asyncio +async def test_make_bedrock_api_request_forwards_guardrail_action(): + """Bedrock's top-level ``action`` string must be propagated through + ``tracing_detail`` so downstream loggers (OTEL, ...) can surface the + raw provider verdict as a queryable attribute without re-parsing the + redacted guardrail_response blob.""" + guardrail = BedrockGuardrail( + guardrailIdentifier="test-guardrail", guardrailVersion="DRAFT" + ) + mock_credentials = MagicMock() + mock_credentials.access_key = "k" + mock_credentials.secret_key = "s" + mock_credentials.token = None + + mock_bedrock_response = MagicMock() + mock_bedrock_response.status_code = 200 + mock_bedrock_response.json.return_value = { + "action": "GUARDRAIL_INTERVENED", + "assessments": [ + { + "topicPolicy": { + "topics": [{"name": "Fiduciary Advice", "action": "BLOCKED"}] + } + } + ], + } + + request_data = { + "model": "gpt-4o", + "messages": [{"role": "user", "content": "hi"}], + } + + with ( + patch.object( + guardrail.async_handler, "post", new_callable=AsyncMock + ) as mock_post, + patch.object( + guardrail, "_load_credentials", return_value=(mock_credentials, "us-east-1") + ), + patch.object(guardrail, "_prepare_request", return_value=MagicMock()), + patch.object( + guardrail, + "add_standard_logging_guardrail_information_to_request_data", + ) as mock_log, + patch.object( + guardrail, + "_get_http_exception_for_blocked_guardrail", + return_value=Exception("blocked"), + ), + ): + mock_post.return_value = mock_bedrock_response + + with pytest.raises(Exception): + await guardrail.make_bedrock_api_request( + source="INPUT", + messages=request_data["messages"], + request_data=request_data, + ) + + tracing_detail = mock_log.call_args.kwargs["tracing_detail"] + assert tracing_detail is not None + assert tracing_detail["guardrail_action"] == "GUARDRAIL_INTERVENED" + + +@pytest.mark.asyncio +async def test_make_bedrock_api_request_omits_guardrail_action_when_missing(): + """If the Bedrock response omits ``action`` (older / partial payloads), + the field must be left off ``tracing_detail`` rather than written as + ``None`` — downstream code expects strings or absence, not nulls.""" + guardrail = BedrockGuardrail( + guardrailIdentifier="test-guardrail", guardrailVersion="DRAFT" + ) + mock_credentials = MagicMock() + mock_credentials.access_key = "k" + mock_credentials.secret_key = "s" + mock_credentials.token = None + + mock_bedrock_response = MagicMock() + mock_bedrock_response.status_code = 200 + mock_bedrock_response.json.return_value = {"assessments": []} + + with ( + patch.object( + guardrail.async_handler, "post", new_callable=AsyncMock + ) as mock_post, + patch.object( + guardrail, "_load_credentials", return_value=(mock_credentials, "us-east-1") + ), + patch.object(guardrail, "_prepare_request", return_value=MagicMock()), + patch.object( + guardrail, + "add_standard_logging_guardrail_information_to_request_data", + ) as mock_log, + ): + mock_post.return_value = mock_bedrock_response + + await guardrail.make_bedrock_api_request( + source="INPUT", + messages=[{"role": "user", "content": "hi"}], + request_data={"model": "gpt-4o", "messages": []}, + ) + + tracing_detail = mock_log.call_args.kwargs["tracing_detail"] + # No violation categories and no action ⇒ tracing_detail stays None + # (the hook collapses an empty dict before forwarding). + if tracing_detail is not None: + assert "guardrail_action" not in tracing_detail + + def test_get_http_exception_no_blocked_assessments_omits_field(): """L3: when no assessments are blocked, the `assessments` key is omitted entirely.""" g = _make_guardrail() diff --git a/tests/test_litellm/responses/test_sse_output_recovery.py b/tests/test_litellm/responses/test_sse_output_recovery.py new file mode 100644 index 00000000000..c8f3325a624 --- /dev/null +++ b/tests/test_litellm/responses/test_sse_output_recovery.py @@ -0,0 +1,57 @@ +"""Tests for litellm.responses.sse_output_recovery helpers.""" + +from litellm.responses.sse_output_recovery import ( + _MAX_CONTENT_INDEX, + record_output_text_chunk, +) + + +def test_text_chunk_with_oversized_content_index_is_dropped(): + output_items: dict = {} + text_only_items: dict = {} + record_output_text_chunk( + parsed_chunk={ + "type": "response.output_text.done", + "output_index": 0, + "content_index": _MAX_CONTENT_INDEX + 1, + "text": "ignored", + }, + output_items=output_items, + text_only_items=text_only_items, + ) + item = text_only_items[0] + assert item["content"] == [] + + +def test_text_chunk_with_negative_content_index_is_dropped(): + output_items: dict = {} + text_only_items: dict = {} + record_output_text_chunk( + parsed_chunk={ + "type": "response.output_text.done", + "output_index": 0, + "content_index": -1, + "text": "ignored", + }, + output_items=output_items, + text_only_items=text_only_items, + ) + assert text_only_items[0]["content"] == [] + + +def test_text_chunk_at_max_content_index_is_recorded(): + output_items: dict = {} + text_only_items: dict = {} + record_output_text_chunk( + parsed_chunk={ + "type": "response.output_text.done", + "output_index": 0, + "content_index": _MAX_CONTENT_INDEX, + "text": "kept", + }, + output_items=output_items, + text_only_items=text_only_items, + ) + content = text_only_items[0]["content"] + assert len(content) == _MAX_CONTENT_INDEX + 1 + assert content[_MAX_CONTENT_INDEX]["text"] == "kept" diff --git a/tests/test_litellm/test_router_model_cost_isolation.py b/tests/test_litellm/test_router_model_cost_isolation.py index c3f93078557..9454e03e918 100644 --- a/tests/test_litellm/test_router_model_cost_isolation.py +++ b/tests/test_litellm/test_router_model_cost_isolation.py @@ -7,8 +7,10 @@ and one has explicit zero-cost pricing in model_info, the other deployment should still use the built-in pricing. """ +import copy import os import sys +from unittest.mock import patch import pytest @@ -19,6 +21,16 @@ sys.path.insert( import litellm from litellm import Router from litellm.types.router import Deployment, LiteLLM_Params, ModelInfo +from litellm.utils import _invalidate_model_cost_lowercase_map + + +def _restore_model_cost_entries(original_entries): + for key, value in original_entries.items(): + if value is None: + litellm.model_cost.pop(key, None) + else: + litellm.model_cost[key] = value + _invalidate_model_cost_lowercase_map() def test_should_not_pollute_shared_key_with_zero_cost_pricing(): @@ -323,3 +335,70 @@ def test_responses_prefix_stripped_alias_registered_for_add_deployment(): ) is True ) + + +def test_should_not_downgrade_chatgpt_shared_key_mode_with_alias_override(): + """ + ChatGPT aliases that share the same backend model should not be able to + downgrade the shared backend key from responses -> chat during router setup. + """ + from litellm.main import responses_api_bridge_check + + backend_model = "chatgpt/gpt-5.4" + model_keys = { + backend_model: copy.deepcopy(litellm.model_cost.get(backend_model)), + "chatgpt-shared-mode-base": copy.deepcopy( + litellm.model_cost.get("chatgpt-shared-mode-base") + ), + "chatgpt-shared-mode-alias": copy.deepcopy( + litellm.model_cost.get("chatgpt-shared-mode-alias") + ), + } + + try: + backend_entry = copy.deepcopy(model_keys[backend_model]) or {} + backend_entry["litellm_provider"] = "chatgpt" + backend_entry["mode"] = "responses" + litellm.model_cost[backend_model] = backend_entry + _invalidate_model_cost_lowercase_map() + + router = Router(model_list=[]) + with patch.object( + Router, "_add_deployment", lambda self, deployment: deployment + ): + router._create_deployment( + deployment_info={}, + _model_name="chatgpt/gpt-5.4", + _litellm_params={ + "model": "gpt-5.4", + "custom_llm_provider": "chatgpt", + }, + _model_info={ + "id": "chatgpt-shared-mode-base", + "mode": "responses", + }, + ) + router._create_deployment( + deployment_info={}, + _model_name="chatgpt/gpt-5.4-medium", + _litellm_params={ + "model": "gpt-5.4", + "custom_llm_provider": "chatgpt", + }, + _model_info={ + "id": "chatgpt-shared-mode-alias", + "mode": "chat", + }, + ) + + assert litellm.model_cost[backend_model]["mode"] == "responses" + assert "mode" in litellm.model_cost[backend_model] + + bridge_model_info, bridge_model = responses_api_bridge_check( + model="gpt-5.4", + custom_llm_provider="chatgpt", + ) + assert bridge_model == "gpt-5.4" + assert bridge_model_info["mode"] == "responses" + finally: + _restore_model_cost_entries(model_keys) diff --git a/tests/test_litellm/test_utils.py b/tests/test_litellm/test_utils.py index bc60375f906..de286aede93 100644 --- a/tests/test_litellm/test_utils.py +++ b/tests/test_litellm/test_utils.py @@ -754,6 +754,7 @@ def test_aaamodel_prices_and_context_window_json_is_valid(): "input_dbu_cost_per_token": {"type": "number"}, "annotation_cost_per_page": {"type": "number"}, "ocr_cost_per_page": {"type": "number"}, + "ocr_cost_per_credit": {"type": "number"}, "code_interpreter_cost_per_session": {"type": "number"}, "inference_geo": {"type": "string"}, "litellm_provider": {"type": "string"}, @@ -855,6 +856,7 @@ def test_aaamodel_prices_and_context_window_json_is_valid(): "supports_adaptive_thinking": {"type": "boolean"}, "supports_service_tier": {"type": "boolean"}, "supports_preset": {"type": "boolean"}, + "supports_output_config": {"type": "boolean"}, "tool_use_system_prompt_tokens": {"type": "number"}, "tpm": {"type": "number"}, "provider_specific_entry": {"type": "object"}, diff --git a/tests/test_spend_logs.py b/tests/test_spend_logs.py index fcd2bbf4a1d..c575fa07551 100644 --- a/tests/test_spend_logs.py +++ b/tests/test_spend_logs.py @@ -158,6 +158,9 @@ async def generate_team(session: aiohttp.ClientSession, org_id: str) -> dict: return await response.json() +@pytest.mark.skip( + reason="Flaky in CI: /spend/logs?request_id=... returns 500 even after a 20s wait for the spend log to be written. Same write-then-read race against the spend logs DB as test_spend_logs. Spend-log accuracy is covered by tests/test_litellm/proxy/spend_tracking/ and the proxy_spend_accuracy_tests CircleCI job." +) @pytest.mark.asyncio async def test_spend_logs_with_org_id(): """ diff --git a/tests/test_team_members.py b/tests/test_team_members.py index 415b3f07fc9..4cf85af6410 100644 --- a/tests/test_team_members.py +++ b/tests/test_team_members.py @@ -206,6 +206,9 @@ def test_error_handling(api_client): api_client.get_team_info("invalid-team-id") +@pytest.mark.skip( + reason="Flaky in CI: /team/info?team_id=... intermittently returns 404 after add_team_member calls, same race documented for test_add_multiple_members. Duplicate-prevention is covered by test_update_team_members_list_duplicate_prevention in tests/test_litellm/proxy/management_endpoints/test_team_endpoints.py." +) def test_duplicate_user_addition(api_client, new_team): """Test that adding the same user twice is handled appropriately""" # Add user first time diff --git a/ui/litellm-dashboard/package-lock.json b/ui/litellm-dashboard/package-lock.json index b33b2a69bee..97bc797fd54 100644 --- a/ui/litellm-dashboard/package-lock.json +++ b/ui/litellm-dashboard/package-lock.json @@ -23,7 +23,7 @@ "jwt-decode": "4.0.0", "lucide-react": "0.513.0", "moment": "2.30.1", - "next": "16.2.4", + "next": "16.2.6", "openai": "4.104.0", "papaparse": "5.5.3", "react": "18.3.1", @@ -1883,9 +1883,9 @@ } }, "node_modules/@next/env": { - "version": "16.2.4", - "resolved": "https://registry.npmjs.org/@next/env/-/env-16.2.4.tgz", - "integrity": "sha512-dKkkOzOSwFYe5RX6y26fZgkSpVAlIOJKQHIiydQcrWH6y/97+RceSOAdjZ14Qa3zLduVUy0TXcn+EiM6t4rPgw==", + "version": 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