Polars write_csv already handles empty DataFrames correctly (outputs
header-only CSV), so the conditional branch was a no-op.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
- Add missing except HTTPException: raise in vantage_dry_run_export
(consistent with all other endpoints in the file)
- Fix is_vantage_setup_in_config() to detect both the string "vantage"
and VantageLogger instances in litellm.callbacks, preventing duplicate
logger registration on startup
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Add missing `except HTTPException: raise` guard so intentional 404
responses (e.g. when settings are not configured) are not caught by the
generic Exception handler and re-raised as 500 errors.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
- Revert FocusExportEngine.dry_run_export_usage_data to use original raw
column names (spend, total_tokens, team_id, model) preserving backward
compatibility for existing callers
- Vantage dry-run endpoint computes its own summary from FOCUS columns
independently, avoiding coupling to the engine method
- Set VantageExportRequest.limit default to 500 (was None) matching docstring
- Add empty-settings guard in /vantage/export returning 404 instead of
deferring ValueError to runtime
- Fix misleading docstring in _build_tags_expr about Rust-level execution
- Clarify Tags schema comment: parquet is self-describing so existing
exports are unaffected
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
- Mask integration_token in GET /vantage/settings response (renamed field to integration_token_masked)
- Reuse single httpx.AsyncClient across all batch uploads in deliver()
- Align FocusExportEngine.dry_run_export_usage_data to use post-transform FOCUS columns (BilledCost, SubAccountId, ResourceType) matching the Vantage dry-run endpoint
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
- Enforce 10K row limit in single-shot upload path (not just 2MB size)
- Fix KeyError crash in update_vantage_settings when no settings exist
- Remove unreachable status_code==400 dead code branch
- Make dry-run endpoint work without Vantage credentials by using
FOCUS database + transformer directly instead of VantageLogger
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Adds a pluggable Vantage destination to the existing FOCUS export pipeline,
enabling LiteLLM to export spend data in FOCUS format directly to Vantage's
cost-import API. Supports automatic hourly exports via scheduled background job,
with admin API endpoints for manual control and configuration. Includes CSV
serializer, batching for 10K row / 2MB API limits, and enriched Tags JSON with
team/user/key metadata for Vantage Token Allocation feature.
- Add CSV serializer (FocusCsvSerializer) for FOCUS data
- Add Vantage API destination with automatic batching
- Add VantageLogger that wraps FocusLogger with Vantage defaults
- Add proxy endpoints: /vantage/{init,settings,export,dry-run,delete}
- Register "vantage" callback in logger registry and literal type
- Wire up background job in proxy_server.py startup
- Populate Tags column with JSON metadata (team_id, user_id, user_email, etc.)
- Add 14 unit tests covering serializer, destination, and factory
All tests pass (23 focus tests total, no regressions).
Co-Authored-By: Claude Haiku 4.5 <noreply@anthropic.com>
When a fetch fails, the button now exits the loading state instead of
staying stuck on "Fetching" indefinitely.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Show a Fetch/Fetching button next to "Showing X of Y results" that acts as
both a manual refetch trigger and a loading indicator. The "Loading keys..."
message now only appears on initial load; subsequent refetches keep the table
visible with stale data (via React Query's keepPreviousData).
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
- 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>
- Fix perform_redaction to handle dict representation of ModelResponse (from model_dump())
- Preserve full choices structure when redacting, redact content/audio in place
- Add _redact_standard_logging_object helper for standard_logging_object field
- Update test_logging_redaction_e2e_test assertions to expect choices format
- Add charity_engine to provider_endpoints_support.json
Fixes: test_standard_logging_payload, test_standard_logging_payload_audio
Made-with: Cursor
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>
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
