* fix(ui_sso.py): use common `get_user_object` logic across jwt + ui sso auth
Allows finding users by their email, and attaching the sso user id to the user if found
* Improve Team Management flow on UI (#8204)
* build(teams.tsx): refactor teams page to make it easier to add members to a team
make a row in table clickable -> allows user to add users to team they intended
* build(teams.tsx): make it clear user should click on team id to view team details
simplifies team management by putting team details on separate page
* build(team_info.tsx): separately show user id and user email
make it easy for user to understand the information they're seeing
* build(team_info.tsx): add back in 'add member' button
* build(team_info.tsx): working team member update on team_info.tsx
* build(team_info.tsx): enable team member delete on ui
allow user to delete accidental adds
* build(internal_user_endpoints.py): expose new endpoint for ui to allow filtering on user table
allows proxy admin to quickly find user they're looking for
* feat(team_endpoints.py): expose new team filter endpoint for ui
allows proxy admin to easily find team they're looking for
* feat(user_search_modal.tsx): allow admin to filter on users when adding new user to teams
* test: mark flaky test
* test: mark flaky test
* fix(exception_mapping_utils.py): fix anthropic text route error
* fix(ui_sso.py): handle situation when user not in db
* feat(lowest_tpm_rpm_v2.py): fix redis cache check to use >= instead of >
makes it consistent
* test(test_custom_guardrails.py): add more unit testing on default on guardrails
ensure it runs if user sent guardrail list is empty
* docs(quick_start.md): clarify default on guardrails run even if user guardrails list contains other guardrails
* refactor(litellm_logging.py): refactor no-log to helper util
allows for more consistent behavior
* feat(litellm_logging.py): add event hook to verbose logs
* fix(litellm_logging.py): add unit testing to ensure `litellm.disable_no_log_param` is respected
* docs(logging.md): document how to disable 'no-log' param
* test: fix test to handle feb
* test: cleanup old bedrock model
* fix: fix router check
* fix(base_utils.py): supported nested json schema passed in for anthropic calls
* refactor(base_utils.py): refactor ref parsing to prevent infinite loop
* test(test_openai_endpoints.py): refactor anthropic test to use bedrock
* fix(langfuse_prompt_management.py): add unit test for sync langfuse calls
Resolves https://github.com/BerriAI/litellm/issues/7938#issuecomment-2613293757
* fix(http_handler.py): support passing ssl verify dynamically and using the correct httpx client based on passed ssl verify param
Fixes https://github.com/BerriAI/litellm/issues/6499
* feat(llm_http_handler.py): support passing `ssl_verify=False` dynamically in call args
Closes https://github.com/BerriAI/litellm/issues/6499
* fix(proxy/utils.py): prevent bad logs from breaking all cost tracking + reset list regardless of success/failure
prevents malformed logs from causing all spend tracking to break since they're constantly retried
* test(test_proxy_utils.py): add test to ensure bad log is dropped
* test(test_proxy_utils.py): ensure in-memory spend logs reset after bad log error
* test(test_user_api_key_auth.py): add unit test to ensure end user id as str works
* fix(auth_utils.py): ensure extracted end user id is always a str
prevents db cost tracking errors
* test(test_auth_utils.py): ensure get end user id from request body always returns a string
* test: update tests
* test: skip bedrock test- behaviour now supported
* test: fix testing
* refactor(spend_tracking_utils.py): reduce size of get_logging_payload
* test: fix test
* bump: version 1.59.4 → 1.59.5
* Revert "bump: version 1.59.4 → 1.59.5"
This reverts commit 1182b46b2ed814064f55f438c11b590cd7248596.
* fix(utils.py): fix spend logs retry logic
* fix(spend_tracking_utils.py): fix get tags
* fix(spend_tracking_utils.py): fix end user id spend tracking on pass-through endpoints
* fix(utils.py): move adding custom logger callback to success event into separate function + don't add success callback to failure event
if user is explicitly choosing 'success' callback, don't log failure as well
* test(test_utils.py): add unit test to ensure custom logger callback only adds callback to specific event
* fix(utils.py): remove string from list of callbacks once corresponding callback class is added
prevents floating values - simplifies testing
* fix(utils.py): fix linting error
* test: cleanup args before test
* test: fix test
* test: update test
* test: fix test
* fix(vertex_ai/gemini/transformation.py): handle 'http://' in gemini process url
* refactor(router.py): refactor '_prompt_management_factory' to use logging obj get_chat_completion logic
deduplicates code
* fix(litellm_logging.py): update 'get_chat_completion_prompt' to update logging object messages
* docs(prompt_management.md): update prompt management to be in beta
given feedback - this still needs to be revised (e.g. passing in user message, not ignoring)
* refactor(prompt_management_base.py): introduce base class for prompt management
allows consistent behaviour across prompt management integrations
* feat(prompt_management_base.py): support adding client message to template message + refactor langfuse prompt management to use prompt management base
* fix(litellm_logging.py): log prompt id + prompt variables to langfuse if set
allows tracking what prompt was used for what purpose
* feat(litellm_logging.py): log prompt management metadata in standard logging payload + use in langfuse
allows logging prompt id / prompt variables to langfuse
* test: fix test
* fix(router.py): cleanup unused imports
* fix: fix linting error
* fix: fix trace param typing
* fix: fix linting errors
* fix: fix code qa check
* fix(redact_messages.py): fix redact messages for non-model response input to be dictionary
fixes issue with otel logging when message redaction is enabled
* fix(proxy_server.py): fix langfuse key leak in exception string
* test: fix test
* test: fix test
* test: fix tests
* refactor(prometheus.py): refactor to remove `_tag` metrics and incorporate in regular metrics
* fix(prometheus.py): handle label values not set in enum values
* feat(prometheus.py): working e2e custom metadata labels
* docs(prometheus.md): update docs to clarify how custom metrics would work
* test(test_prometheus_unit_tests.py): fix test
* test: add unit testing
* fix(prometheus.py): refactor litellm_input_tokens_metric to use label factory
makes adding new metrics easier
* feat(prometheus.py): add 'request_model' to 'litellm_input_tokens_metric'
* refactor(prometheus.py): refactor 'litellm_output_tokens_metric' to use label factory
makes adding new metrics easier
* feat(prometheus.py): emit requested model in 'litellm_output_tokens_metric'
* feat(prometheus.py): support tracking success events with custom metrics
* refactor(prometheus.py): refactor '_set_latency_metrics' to just use the initially created enum values dictionary
reduces scope for missing values
* feat(prometheus.py): refactor all tags to support custom metadata tags
enables metadata tags to be used across for e2e tracking
* fix(prometheus.py): fix requested model on success event enum_values
* test: fix test
* test: fix test
* test: handle filenotfound error
* docs(prometheus.md): add new values to prometheus
* docs(prometheus.md): document adding custom metrics on prometheus
* bump: version 1.56.5 → 1.56.6
* build(model_prices_and_context_window.json): update groq models to specify 'supports_vision' parameter
Closes https://github.com/BerriAI/litellm/issues/7433
* docs(groq.md): add groq vision example to docs
Closes https://github.com/BerriAI/litellm/issues/7433
* fix(prometheus.py): refactor self.litellm_proxy_failed_requests_metric to use label factory
* feat(prometheus.py): new 'litellm_proxy_failed_requests_by_tag_metric'
allows tracking failed requests by tag on proxy
* fix(prometheus.py): fix exception logging
* feat(prometheus.py): add new 'litellm_request_total_latency_by_tag_metric'
enables tracking latency by use-case
* feat(prometheus.py): add new llm api latency by tag metric
* feat(prometheus.py): new litellm_deployment_latency_per_output_token_by_tag metric
allows tracking deployment latency by tag
* fix(prometheus.py): refactor 'litellm_requests_metric' to use enum values + label factory
* feat(prometheus.py): new litellm_proxy_total_requests_by_tag metric
allows tracking total requests by tag
* feat(prometheus.py): new metric litellm_deployment_successful_fallbacks_by_tag
allows tracking deployment fallbacks by tag
* fix(prometheus.py): new 'litellm_deployment_failed_fallbacks_by_tag' metric
allows tracking failed fallbacks on deployment by custom tag
* test: fix test
* test: rename test to run earlier
* test: skip flaky test
* refactor(prometheus.py): refactor to use a factory method for setting label values
allows for enforcing end user id disabling on prometheus e2e
* fix: fix linting error
* fix(prometheus.py): ensure label factory drops end-user value if disabled by user
* fix(prometheus.py): specify service_type in end user tracking get
* test: fix test
* test: add unit test for prometheus factory
* test: improve test (cover flag not set scenario)
* test(test_prometheus.py): e2e test covering if 'end_user_id' shows up in testing if disabled
scrapes the `/metrics` endpoint and scans text to check if id appears in emitted metrics
* fix(prometheus.py): stringify status code before logging it
* fix(prometheus.py): support streaming end user litellm_proxy_total_requests_metric tracking
* fix(prometheus.py): add 'requested_model' and 'end_user_id' to 'litellm_request_total_latency_metric_bucket'
enables latency tracking by end user + requested model
* fix(prometheus.py): add end user, user and requested model metrics to 'litellm_llm_api_latency_metric'
* test: update prometheus unit tests
* test(test_prometheus.py): update tests
* test(test_prometheus.py): fix test
* test: reorder test
* fix(proxy_track_cost_callback.py): log to db if only end user param given
* fix: allows for jwt-auth based end user id spend tracking to work
* fix(utils.py): fix 'get_end_user_id_for_cost_tracking' to use 'user_api_key_end_user_id'
more stable - works with jwt-auth based end user tracking as well
* test(test_jwt.py): add e2e unit test to confirm end user cost tracking works for spend logs
* test: update test to use end_user api key hash param
* fix(langfuse.py): support end user cost tracking via jwt auth + langfuse
logs end user to langfuse if decoded from jwt token
* fix: fix linting errors
* test: fix test
* test: fix test
* fix: fix end user id extraction
* fix: run test earlier
Krish Dholakia