* fix(model_checks.py): update returning known model from wildcard to filter based on given model prefix
ensures wildcard route - `vertex_ai/gemini-*` just returns known vertex_ai/gemini- models
* test(test_proxy_utils.py): add unit testing for new 'get_known_models_from_wildcard' helper
* test(test_models.py): add e2e testing for `/model_group/info` endpoint
* feat(prometheus.py): support tracking total requests by user_email on prometheus
adds initial support for tracking total requests by user_email
* test(test_prometheus.py): add testing to ensure user email is always tracked
* test: update testing for new prometheus metric
* test(test_prometheus_unit_tests.py): add user email to total proxy metric
* test: update tests
* test: fix spend tests
* test: fix test
* fix(pagerduty.py): fix linting error
* 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 prometheus have well defined latency buckets
* use a well define latency bucket
* use types file for prometheus logging
* add test for LATENCY_BUCKETS
* track api key and team in prom latency metric
* add test for latency metric
* test prometheus success metrics for latency
* track team and key labels for deployment failures
* add test for litellm_deployment_failure_responses_total
* fix checks for premium user on prometheus
* log_success_fallback_event and log_failure_fallback_event
* log original_exception in log_success_fallback_event
* track key, team and exception status and class on fallback metrics
* use get_standard_logging_metadata
* fix import error
* track litellm_deployment_successful_fallbacks
* add test test_proxy_fallback_metrics
* add log log_success_fallback_event
* fix test prometheus
* prom - show status code and class type on prom
* log exception_class name on prometheus metrics
* prometheus track error code and status
* add bad model
* add prometheus failure metric test
* remove outdated file
* fix litellm_proxy_total_requests_metric
* add prometheus metrics testing
