* fix(rebuild-usage-object---ensure-cache_tokens-is-set): Ensures cache tokens is correctly set
Fixes https://github.com/BerriAI/litellm/issues/12149
* test(test_stream_chunk_builder_utils.py): add unit test to ensure cached tokens is part of stream chunk builder
Ensures standardized values are used
* fix(proxy_server.py): handle empty config yaml
Fixes https://github.com/BerriAI/litellm/issues/12163
* fix(gemini/common_utils.py): replace models/ as expected, instead of using 'strip'
Fixes https://github.com/BerriAI/litellm/issues/12160
* fix(anthropic/experimental_pass_through/messages/transformation.py): check for env var when selecting api key
* docs(config_settings.md): add api key to docs
* fix: support Cursor IDE tool_choice format {"type": "auto"}
- Update validate_chat_completion_tool_choice to normalize {"type": "auto"} to "auto"
- Handles Cursor IDE sending non-standard tool_choice format
- Add comprehensive tests for tool choice validation
Fixes#12098
* fix: return full tool_choice object for Cursor IDE format
Based on PR feedback, updated validate_chat_completion_tool_choice to return
the full tool_choice dictionary instead of just extracting the type string.
This maintains consistency with downstream code that expects the full object
structure.
- Changed behavior: {"type": "auto"} now returns {"type": "auto"} instead of "auto"
- Updated tests to reflect the new expected behavior
- Ensures compatibility with code that passes tool_choice to optional_params
Addresses feedback from PR #12168
* fix(team_endpoints.py): prevent overwriting current list of team models on new model add
* fix(networking.tsx): fix default proxy base url
* fix(proxy_server.py): include team only models when retrieving all deployments on `/v2/model/info` helper util
ensures team only models are shown to user
* fix(router.py): check model name by team public model name when team id given
Fixes issue where team member could not see team only models when clicking into that team on `Models + Endpoints`
* fix(team_member_view.tsx): fix rendering team member budget, when budget is set
* test: update tests
* test: update unit test
* fix(anthropic/experimental_pass_through): use given model name when returning streaming chunks
don't harcode model name on streaming
confusing for user
* fix(anthropic/streaming_iterator.py): remove scope of import
* feat(litellm_logging.py): allow admin to specify additional headers for using as spend tags
Closes https://github.com/BerriAI/litellm/issues/12129
* test(test_litellm_logging.py): add unit tests
* feat(openweb_ui.md): add custom tag tutorial to docs
* docs(cost_tracking.md): add tag based usage UI screenshot
* test: update test
* fix: fix import
* use common helper create_invitation_for_user
* use common util in proxy
* fix create_invitation_for_user
* refactor base email
* test_get_invitation_link_creates_new_when_none_exist
* fix code QA checks
* feat(check_batch_cost.py): emit spend log on successful request
ensures cost tracked for batch requests
* feat(proxy_server.py): add background job to poll completed batch jobs
used for calculating cost for batch jobs
* fix(proxy_server.py): run batch cost tracking job every hour
batch jobs take time to complete, no need to run every few seconds
* feat(proxy_server.py): run batch cost tracking job every hour
Jugal Bhatt