* feat(key_management_endpoints.py): Support new 'key_type' field
allow user to specify if key should be 'management' or 'llm api' key
Security fix
* test(test_route_checks.py): add unit tests
* fix(create_key_button.tsx): add ui component to select key type
allows specifying if key can call llm api vs. management routes
* feat(create_key_button.tsx): add specifying key type to ui
* fix(route_checks.py): add sensitive data masker for user id on not allowed error message
prevent leaking sensitive information
* fix(prometheus.py): sanitize tag-based labels to handle colons (:) and spaces ( )
* fix(prometheus.py): working tag based metrics
* fix(prometheus.py): emit request tags on post call success hook
* fix(prometheus.py): add user agent tags on request failure
* fix(prometheus.py): add request tags to deployment failure metric
s
* fix(proxy_server.py): update swagger-ui-bundle.js + bring back swagger in airgapped environments
* fix(proxy_server.py): support local swagger on custom root path
enables on prem usage of litellm
* feat: Add Pillar Security guardrail integration
Implements comprehensive LLM security guardrails using Pillar Security API with support for prompt injection detection, PII/secret detection, content moderation, and multi-mode execution (pre_call, during_call, post_call). Includes complete documentation, testing, and configurable actions on flagged content.
* fix: Resolve MyPy type error in Pillar guardrail config
Restructure PillarGuardrailConfigModel to properly inherit from GuardrailConfigModel[T]
and resolve return type compatibility issue in get_config_model method.
* fix: Resolve MyPy type error in Pillar guardrail config
Restructure PillarGuardrailConfigModel to properly inherit from GuardrailConfigModel[T]
and resolve return type compatibility issue in get_config_model method.
* fix docs
* fix docs
* improved docs
* fix examples, READY
* feat(litellm_pre_call_utils.py): add num_retries to litellm data for backend call
allow user to pass in num retries via request headers
* test(test_litellm_pre_call_utils.py): add unit test
* docs(request_headers.md): document new request header
* fix(common_daily_activity.py): show spend breakdown by model group
Partial fix for https://github.com/BerriAI/litellm/issues/12887
* feat(new_usage.tsx): new tab switcher for viewing usage by model group vs. received model
Closes https://github.com/BerriAI/litellm/issues/12887
* fix(main.py): fix async retryer
Fixes https://github.com/BerriAI/litellm/issues/12830
* fix(forward_clientside_headers_by_model_group.py): filter out 'content-type' from forwardable headers
clientside content-type != proxy content type, can cause requests to hang
* add gemini 2.0 live to model context and priceS
* added files to dump
* Update litellm/model_prices_and_context_window_backup.json
Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com>
* Update model_prices_and_context_window.json
Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com>
* added vertex ai live preview
* added vertex ai change
* add input video and image cosT
* add input video and image cosT
---------
Co-authored-by: Ishaan Jaff <ishaanjaffer0324@gmail.com>
Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com>
