- Fix case-insensitive tool name matching in _tool_name_matches() so that
OpenAPI operationIds (camelCase) match lowercase registered tool names
when filtering by allowed_tools
- Fix get_base_url() to resolve relative server URLs (e.g. /api/v3) by
deriving full base URL from spec_path when OpenAPI spec has relative URLs
- Add tests for case-insensitive matching and filter_tools_by_allowed_tools
Made-with: Cursor
`all_models = user_api_key_dict.models` was creating an alias, so
`_get_models_from_access_groups` (which uses `.pop()`/`.extend()`) would
mutate the cached object in-place. Now both `.models` and `.team_models`
assignments create copies via `list()`.
Added test to verify the input is not mutated.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Adds dedup to get_key_models and get_team_models to prevent duplicate
entries when access group member models overlap with proxy_model_list.
Removes dead assignment of all_models in get_team_models.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
When a team has "all-proxy-models", the model list expansion now includes
model access group names so they appear in the UI key creation form.
Also fixes get_key_models not forwarding include_model_access_groups to
_get_models_from_access_groups, and removes unused _unfurl_all_proxy_models.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
The SageMaker embedding handler was not using _load_credentials(),
which meant aws_role_name and aws_session_name parameters were
ignored. This prevented cross-account role assumption for embeddings
while it worked for completions.
Changes:
- Replace direct boto3 client creation with _load_credentials() call
- Create boto3.Session with assumed credentials
- Add comprehensive unit tests for role assumption
This aligns the embedding handler behavior with the completion handler,
which already supports role assumption via the BaseAWSLLM.get_credentials()
method.
Fixes cross-account SageMaker embedding access where users need to
assume a role in another account to invoke endpoints.
Any param in DEFAULT_CHAT_COMPLETION_PARAM_VALUES that arrives via
completion(**kwargs) is now automatically forwarded to
get_optional_params(), even if it's not a named parameter of
completion().
Previously, get_non_default_completion_params() excluded params in
OPENAI_CHAT_COMPLETION_PARAMS (assuming they'd be forwarded via the
named-param path), while optional_param_args only contained explicitly
named params. Params like 'store' that were in the known-params list
but not named params fell through both paths and were silently dropped.
The fix adds a 7-line loop after building optional_param_args that
forwards any kwargs present in DEFAULT_CHAT_COMPLETION_PARAM_VALUES.
This means new OpenAI params only need to be added to the constants
dict — no boilerplate changes to 3+ function signatures required.
Fixes#23087
Co-authored-by: Cursor Agent <cursoragent@cursor.com>
* feat(charity_engine): add Charity Engine provider
Charity Engine is a crowdsourced distributed computing platform that
donates processing power to charitable causes. Its inference API
provides OpenAI-compatible chat, completions, and embeddings endpoints.
* test(charity_engine): add provider config and resolution tests
Verify JSONProviderRegistry config, provider list membership,
model routing for charity_engine/<model>, and Router compatibility.
* feat(charity_engine): add Charity Engine to LlmProviders enum
Enables provider_list membership and LlmProviders.CHARITY_ENGINE
resolution required by the provider and test suite.
* fix(charity_engine): remove api_base_env to fix non-deterministic test
The CHARITY_ENGINE_API_BASE env var could override the base_url in CI,
causing test_charity_engine_provider_resolution to fail intermittently.
* fix(charity_engine): remove trailing slash from base_url
Claude's API returns assistant messages with empty text blocks
({"type": "text", "text": ""}) alongside tool_use blocks during
multi-turn tool-use conversations. These blocks are rejected when
sent back to the API with "text content blocks must be non-empty".
Sanitization already exists for other code paths (/v1/chat/completions
for both Anthropic and Bedrock), but NOT for the /v1/messages native
path. This adds the same treatment by stripping empty text blocks
from messages in async_anthropic_messages_handler before they are
forwarded to the provider.
Fixes#22930
_get_openai_compatible_provider_info already returns an api_base
ending in /v1, but get_models prepended another /v1, producing
.../inference/v1/v1/accounts/... which 404s.
Strip the trailing /v1 from api_base before re-adding it so that
both the default and any user-supplied base work correctly.
Add parametrized tests covering the default URL, trailing-slash,
custom base with /v1, and custom base without /v1.
Fixes#23106
The bug occurred when user data inadvertently contained reserved Python
keywords like 'self', 'params', or '__class__' as keys. When such a dict
was unpacked via **kwargs to LiteLLM_Params() or GenericLiteLLMParams(),
Python raised TypeError because 'self' was passed both implicitly and
as a keyword argument.
The fix:
- Add a Pydantic model_validator(mode='before') to GenericLiteLLMParams
that filters out reserved keys ('self', 'params', '__class__') before
validation
- Move the max_retries str-to-int conversion into the same validator
- Remove the custom __init__ methods from both GenericLiteLLMParams and
LiteLLM_Params, since the validator now handles the preprocessing
- Clean up unused VERTEX_CREDENTIALS_TYPES import
This fix applies to all classes that inherit from GenericLiteLLMParams,
including LiteLLM_Params and updateLiteLLMParams.
Added comprehensive tests in tests/test_litellm/test_litellm_params_reserved_keys.py
Co-authored-by: Cursor Agent <cursoragent@cursor.com>
Add input_fidelity parameter ("high"/"low") to the image edit pipeline,
allowing users to control how much effort the model exerts to match
input image style and features. Fixes#22813.
The tag daily activity endpoint used compute_tag_metadata_totals which
deduplicates by request_id, but LiteLLM_DailyTagSpend stores aggregated
daily records where request_id is either NULL or stale. This caused all
metadata totals (total_spend, total_requests, etc.) to be 0 in the UI
cost panel. Now uses the same standard totals as every other entity type.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
The test was flaky under pytest-xdist parallel execution because it used
async acompletion (which runs completion() in a thread pool via
run_in_executor) and relied on shared global state (known_tokenizer_config,
iam_token_cache, module_level_client) that could be modified by other tests
running in parallel. Failures were silently swallowed by a broad try/except,
causing mock_post.call_count to remain 0.
Fix:
- Convert from async acompletion to sync completion, matching every other
test in the file. The test's intent is verifying prompt transformation,
not async behavior.
- Use monkeypatch.setitem for known_tokenizer_config to ensure proper
teardown isolation.
- Remove unnecessary mock layers (async template fetchers, iam_token_cache
pre-population, mock completion response) that were only needed for the
async code path.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
The gemini-3.1-flash-image-preview model introduced a new pricing field
that was missing from the test's validation schema and cost_fields list.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
* fix(agentcore): handle JSON responses from agents using sync return
BedrockAgentCoreApp agents that use synchronous `return` (instead of
async `yield`) respond with Content-Type: application/json instead of
text/event-stream. The streaming parser only handles SSE format, silently
discarding the JSON body and returning empty content to the client.
This adds Content-Type detection in both sync and async streaming
wrappers — when application/json is received, the response is parsed
and converted to a single-chunk stream. Also extends _parse_json_response
with a fallback chain supporting multiple agent response schemas (standard
AgentCore, Strands framework, plain string, raw JSON fallback).
* fix(agentcore): add dict-type guard to _parse_json_response
Prevent AttributeError when json.loads() returns a non-dict
(e.g. JSON array or primitive) by adding an isinstance check
at the top of _parse_json_response. Non-dict values fall back
to raw JSON string content.
* fix(agentcore): handle malformed JSON and split streaming chunks
- Wrap json.loads() in try/except in both sync and async streaming
wrappers so malformed JSON bodies raise a structured BedrockError
instead of a raw JSONDecodeError
- Split the JSON-fallback streaming path into two chunks (content
chunk with finish_reason=None, then stop sentinel with empty delta)
to match the SSE path convention
* fix(agentcore): catch IO errors in streaming JSON path + async error test
- Broaden except clause to catch both json.JSONDecodeError and IO-level
exceptions (httpx.ReadError, etc.) from response.read()/aread(), so
all failures surface as structured BedrockError
- Add async malformed-JSON test to mirror the sync test coverage
Audit logs (CRUD events on keys, teams, users, models) were only stored in
the Prisma DB. This adds a pluggable callback system so audit logs can be
forwarded to external services like S3 for ingestion into security monitoring
tools.
New config key `audit_log_callbacks` under `litellm_settings` reuses the
existing callback infrastructure. Any CustomLogger subclass can opt in by
overriding `async_log_audit_log_event()`. S3Logger (s3_v2) is implemented
as the first handler, storing audit logs under `audit_logs/{date}/` prefix.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
* feat(proxy): add Prisma DB pool and engine health metrics to Prometheus
Add a PrismaMetricsCollector that periodically queries pg_stat_activity
and the Prisma engine process to expose connection pool and engine health
as Prometheus gauges/counters. Auto-enabled when prometheus_system is in
service_callback.
New metrics:
- litellm_db_pool_active_connections (Gauge)
- litellm_db_pool_idle_connections (Gauge)
- litellm_db_pool_total_connections (Gauge)
- litellm_db_pool_waiting_connections (Gauge)
- litellm_db_engine_up (Gauge)
- litellm_db_engine_restarts_total (Counter)
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
* fix: address Greptile review feedback
- Only increment engine_restarts counter on heavy reconnects (engine
actually dead), not lightweight network-blip reconnects
- Fix potential KeyError in _get_or_create_gauge/counter fallback path
when REGISTRY._names_to_collectors is absent
- Rename litellm_db_pool_waiting_connections to
litellm_db_pool_lock_waiting_connections to clarify it measures lock
contention, not pool slot queuing
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
* fix: warn when prometheus_system enabled but watchdog disabled
Log a warning when users have prometheus_system in service_callback
but PRISMA_HEALTH_WATCHDOG_ENABLED=false, since DB pool and engine
metrics won't be collected in that configuration.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
* ci: retrigger CI checks
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
* refactor: use labeled gauge for DB pool connection metrics
Replace 3 separate pool gauges (active, idle, total) with a single
`litellm_db_pool_connections` gauge using a `state` label. This is more
Prometheus-idiomatic and exposes all pg_stat_activity states (active,
idle, idle in transaction, etc.) without ambiguity about what "total"
includes.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
* fix: address Greptile review — stale labels and fallback re-registration
- Zero out known pg_stat_activity states that are absent from the current
query result, preventing stale gauge values from persisting.
- Simplify _get_or_create_gauge/counter by removing the fallback loop
that could re-register an already-registered metric (ValueError).
- Add test for stale label clearing across collection cycles.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
* fix: include "unknown" in _PG_STATES for stale label clearing
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
* fix: collect immediately on start and consolidate into single query
- Move sleep to end of loop so metrics appear on /metrics immediately
after startup instead of after a 30s delay.
- Combine pool state and lock waiting queries into a single SQL query
using conditional aggregation, halving per-cycle DB overhead.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
* fix: prevent tight spin loop on collection error
Move asyncio.sleep outside the try/except so it always executes even
when _collect_engine_health() or _collect_pool_metrics() raises.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
* fix: add multiprocess_mode to _get_or_create_gauge initialization
- Include `multiprocess_mode` parameter to properly support multiprocessing in Gauge creation.
- Ensure consistent behavior for labeled and unlabeled Gauges.
* fix: handle invalid env var and document watchdog prerequisite
- Add try/except ValueError for PRISMA_METRICS_COLLECTION_INTERVAL_SECONDS
to prevent proxy startup crash on non-numeric values (e.g. "30s")
- Document that DB metrics require both prometheus_system callback and
PRISMA_HEALTH_WATCHDOG_ENABLED=true
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
* fix: use defensive null coalescing for query_raw row values
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
* test: add invalid env var fallback test and fix mock signature
- Add test for non-numeric PRISMA_METRICS_COLLECTION_INTERVAL_SECONDS
- Add **kwargs to mock _patched_get_or_create_gauge for forward compat
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
---------
Co-authored-by: Claude Opus 4.6 <noreply@anthropic.com>
