* fix(proxy_server.py): get master key from environment, if not set in general settings or general settings not set at all
* test: mark flaky test
* test(test_proxy_server.py): mock prisma client
* ci: add new github workflow for testing just the mock tests
* fix: fix linting error
* ci(conftest.py): add conftest.py to isolate proxy tests
* build(pyproject.toml): add respx to dev dependencies
* build(pyproject.toml): add prisma to dev dependencies
* test: fix mock prompt management tests to use a mock anthropic key
* ci(test-litellm.yml): parallelize mock testing
make it run faster
* build(pyproject.toml): add hypercorn as dev dep
* build(pyproject.toml): separate proxy vs. core dev dependencies
make it easier for non-proxy contributors to run tests locally - e.g. no need to install hypercorn
* ci(test-litellm.yml): pin python version
* test(test_rerank.py): move test - cannot be mocked, requires aws credentials for e2e testing
* ci: add thank you message to ci
* test: add mock env var to test
* test: add autouse to tests
* test: test mock env vars for e2e tests
* build: new ui build
* build: new ui build
* fix(proxy_server.py): only show user models their key can access on `/models`
* fix(model_management_endpoints.py): ensure team admin can add models
* test: update unit testing to reflect changes
* fix(model_dashboard.tsx): fix sizing on models page
* build: fix ui
* feat(view_logs.tsx): show model id + api base in request logs
easier debugging
* fix(index.tsx): fix length of api base
easier viewing
* refactor(leftnav.tsx): show models tab to team admin
* feat(model_dashboard.tsx): add explainer for what the 'models' page is for team admin
helps them understand how they can use it
* feat(model_management_endpoints.py): restrict model add by team to just team admin
allow team admin to add models via non-team keys (e.g. ui token)
* test(test_add_update_models.py): update unit testing for new behaviour
* fix(model_dashboard.tsx): show user the models
* feat(proxy_server.py): add new query param 'user_models_only' to `/v2/model/info`
Allows user to retrieve just the models they've added
Used in UI to show internal users just the models they've added
* feat(model_dashboard.tsx): allow team admins to view their own models
* fix: allow ui user to fetch model cost map
* feat(add_model_tab.tsx): require team admins to specify team when onboarding models
* fix(_types.py): add `/v1/model/info` to info route
`/model/info` was already there
* fix(model_info_view.tsx): allow user to edit a model they created
* fix(model_management_endpoints.py): allow team admin to update team model
* feat(model_managament_endpoints.py): allow team admin to delete team models
* fix(model_management_endpoints.py): don't require team id to be set when adding a model
* fix(proxy_server.py): fix linting error
* fix: fix ui linting error
* fix(model_management_endpoints.py): ensure consistent auth checks on all model calls
* test: remove old test - function no longer exists in same form
* test: add updated mock testing
* feat: initial commit - enable dev to see translated request
* feat(utils.py): expose new endpoint - `/utils/transform_request` to see the raw request sent by litellm
* feat(transform_request.tsx): allow user to see their transformed request
* refactor(litellm_logging.py): return raw request in 3 parts - api_base, headers, request body
easier to render each individually on UI vs. extracting from combined string
* feat: transform_request.tsx
working e2e raw request viewing
* fix(litellm_logging.py): fix transform viewing for bedrock models
* fix(litellm_logging.py): don't return sensitive headers in raw request headers
prevent accidental leak
* feat(transform_request.tsx): style improvements
* feat(key_management_endpoints.py): adding support for rotating master key
* feat(key_management_endpoints.py): support decryption-re-encryption of models in db, when master key rotated
* fix(user_api_key_auth.py): raise valid token is None error earlier
enables easier debugging with api key hash in error message
* feat(key_management_endpoints.py): rotate any env vars
* fix(key_management_endpoints.py): uncomment check
* fix: fix linting error
* fix(core_helpers.py): handle litellm_metadata instead of 'metadata'
* feat(batches/): ensure batches logs are written to db
makes batches response dict compatible
* fix(cost_calculator.py): handle batch response being a dictionary
* fix(batches/main.py): modify retrieve endpoints to use @client decorator
enables logging to work on retrieve call
* fix(batches/main.py): fix retrieve batch response type to be 'dict' compatible
* fix(spend_tracking_utils.py): send unique uuid for retrieve batch call type
create batch and retrieve batch share the same id
* fix(spend_tracking_utils.py): prevent duplicate retrieve batch calls from being double counted
* refactor(batches/): refactor cost tracking for batches - do it on retrieve, and within the established litellm_logging pipeline
ensures cost is always logged to db
* fix: fix linting errors
* fix: fix linting error
* fix(common_utils.py): handle $id in response schema when calling vertex ai
Fixes issue where `$id` present in response_schema was not accepted by vertex ai
* test(test_vertex.py): add unit test to ensure $id stripped out of vertex schema