litellm/tests/test_litellm/proxy/test_proxy_server.py
yuneng-jiang 6ff668c7aa
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[Infra] Promote internal staging to main (#27245)
* default requested_model to empty string on litellm-side rejects

* Update litellm/router.py

Co-authored-by: greptile-apps[bot] <165735046+greptile-apps[bot]@users.noreply.github.com>

* fix: scope key access_group_ids override by team's assigned groups

A team member could set any access_group_ids on their key (e.g. a group
assigned only to a different team) and override the team's model
restriction. Intersect the key's access_group_ids with team_object.access_group_ids
in _key_access_group_grants_model so foreign groups are dropped before
model expansion. Adds a regression test that asserts expansion is never
called for foreign groups.

* [Fix] Proxy: Skip Personal Budget Hook When Reservation Covers Counter

The reservation path (PR #26845) atomically pre-fills `spend:user:{user_id}`
and admits at the strict-`<` boundary. The legacy `_PROXY_MaxBudgetLimiter`
pre-call hook re-reads the same counter with `>=`, so a reservation that
fills the counter to exactly `max_budget` (e.g. a request without a
`max_tokens` cap that falls back to reserving the smallest remaining
headroom) is rejected by the hook even though the reservation already
admitted it.

Skip the hook when the request's active `budget_reservation` covers
`spend:user:{user_id}`. The reservation is the source of truth for that
counter cross-pod; the legacy `>=` path remains in place for requests
without a reservation (e.g. paths that bypass the reservation entirely).

Reproduces as `tests/otel_tests/test_prometheus.py::test_user_budget_metrics`
on a fresh user with `max_budget=10` calling `fake-openai-endpoint` without
`max_tokens`. Adds focused unit coverage in
`tests/test_litellm/proxy/hooks/test_max_budget_limiter.py`.

* harden bedrock file bucket validation

* Fix syntax errors from botched merge in router.py

* Fix Vertex batch output edge cases

* [Fix] RBAC: Drop management_routes Write Fallback for Admin Viewer

Greptile P1: the unsafe-method branch of `_check_proxy_admin_viewer_access`
ended with a blanket `if route in management_routes: return`. That set is a
mix of reads (info/list — handled via the safe-method GET branch above) and
writes. The fallback let Admin Viewer POST to write endpoints not enumerated
in `_ADMIN_VIEWER_BLOCKED_WRITE_ROUTES`, including:
  - /team/block, /team/unblock, /team/permissions_update
  - /jwt/key/mapping/{new,update,delete}
  - /key/bulk_update
  - /key/{key_id}/reset_spend

Remove the fallback. The two remaining allow sets (admin_viewer_routes and
global_spend_tracking_routes) are both read-only, so removal does not affect
the legitimate POST-as-read cases (e.g. /spend/calculate, which is in
spend_tracking_routes ⊂ admin_viewer_routes).

Tests:
  - 8 new parametrized cases pinning each previously-leaking management write
    endpoint to 403 on POST for PROXY_ADMIN_VIEW_ONLY.

* fix(tests): anchor VCR redis cassette key to repo root

`os.path.relpath` with no `start` arg uses the current working
directory, so running pytest from a subdirectory produced a
different Redis key than running from the repo root. CI-recorded
cassettes and locally-replayed runs would silently miss each
other's cache.

Anchor the path to the repo root (derived from `__file__`) so the
key is stable regardless of CWD.

https://claude.ai/code/session_018uCx7pcrkdUJZrCVMaTdPx

* fix: gate key access_group override on group's own assignment

Replaces the previous intersect-with-team.access_group_ids check, which
made the override unreachable in practice (the team-gate fallback already
covered every case the intersection allowed). The override now resolves
each of the key's access_group_ids via get_access_object and accepts the
group only if its assigned_team_ids includes the key's team_id, or its
assigned_key_ids includes the key's token. This fulfills the original ask
(a key can extend a team's allow-list via a group the admin granted to
that team or that specific key) while still rejecting foreign groups
referenced by team members of other teams.

* [Fix] Proxy/Key Management: Honor team_member_permissions /key/list In /key/list Endpoint

When a team grants /key/list via team_member_permissions, non-admin members
should see all keys for that team — same as a team admin. Previously the
classification in list_keys() only checked admin status, so permitted
members fell into the service-account-only path and could not see other
members' personal keys. Routes those members into the full-visibility set.

* Fix access-group bypass via litellm-model fallback path

When _get_all_deployments returns 0 candidates and the litellm-model
fallback branch (_get_deployment_by_litellm_model) finds deployments that
the access-group filter then empties, _access_group_filter_emptied_candidates
remained False (it was captured before that branch ran). The router would
then proceed to default fallbacks; the fallback model could have no
access_groups and short-circuit the filter, silently serving a caller
blocked by access-group restrictions.

Update the flag inside the litellm-model branch when filtering empties a
non-empty candidate set so the default-fallback guard still triggers.

* fix(proxy): redact MCP server URL and headers for non-admin viewers (VERIA-8)

Many MCP integrations (Zapier, etc.) embed an upstream API key
directly in the server URL, e.g.
``https://actions.zapier.com/mcp/<api-key>/sse``. The list and
single-server endpoints were returning the full URL to any
authenticated user — `_redact_mcp_credentials` only stripped the
explicit ``credentials`` field, and `_sanitize_mcp_server_for_virtual_key`
only ran for restricted virtual keys. Non-admin internal users could
read the dashboard, click the unmask toggle, and exfiltrate the raw
token.

Add `_sanitize_mcp_server_for_non_admin` that runs on top of the
existing credential redaction and clears the credential-bearing
fields:

- ``url`` (the primary leak vector)
- ``spec_path`` (OpenAPI spec URLs that may carry tokens)
- ``static_headers`` / ``extra_headers`` (Authorization)
- ``env`` (arbitrary secrets)
- ``authorization_url`` / ``token_url`` / ``registration_url``

Identity fields (``server_id``, ``alias``, ``mcp_info``, etc.) are
preserved so the UI can still list servers a non-admin's team has
access to.

Apply the new sanitizer in `fetch_all_mcp_servers` and the per-server
fetch path right after the existing virtual-key branch. Update the
existing `test_list_mcp_servers_non_admin_user_filtered` assertions
that previously checked URL visibility.

Frontend defense-in-depth: hide the URL unmask toggle on
`mcp_server_view.tsx` unless the viewer is a proxy admin.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>

* Fix runtime policy attachment initialization

Mark runtime-created policies and attachments initialized so global policy attachments created from the policy builder apply immediately without requiring a restart.

Co-authored-by: Cursor <cursoragent@cursor.com>

* test(router): cover _try_early_resolve_deployments_for_model_not_in_names

The router_code_coverage CI check requires every function in router.py to
be referenced by at least one test under tests/{local_testing,
router_unit_tests,test_litellm} in a file with "router" in its name.
The recently-extracted helper had no direct test, so the check failed
with "0.45% of functions in router.py are not tested".

Add a focused test that exercises the four return paths: model already
in self.model_names, no fallback applies, pattern-router match, and
default_deployment substitution (also asserting the stored default
isn't mutated).

https://claude.ai/code/session_019AVp1XL7RT9RxRe4qRLkay

* Fix policy registry teardown in tests

Reset the policy ID index during policy engine test cleanup so stale policy versions cannot leak between tests.

Co-authored-by: Cursor <cursoragent@cursor.com>

* fix(batches): count non-chat tokens, validate batch-file model access (VERIA-39) (#27015)

* fix(batches): count non-chat tokens and validate every model in batch file

Two security control bypasses on POST /v1/batches:

1. `_get_batch_job_input_file_usage` only summed tokens for
   `body.messages` (chat completions). Embedding (`input`) and text
   completion (`prompt`) batches reported zero, letting massive
   non-chat workloads slip past TPM rate limits. Extend the counter
   to handle string and list shapes for both fields.

2. The batch input file was forwarded to the upstream provider
   without inspecting the models named inside the JSONL — only the
   outer `model` query parameter was checked against the caller's
   allowlist. A caller restricted to gpt-3.5 could submit a batch
   targeting gpt-4o and the upstream would execute it under the
   proxy's shared API key.

Add `_get_models_from_batch_input_file_content` (returns the
distinct `body.model` values) and call it from
`_enforce_batch_file_model_access` in the pre-call hook, which runs
each model through `can_key_call_model` so the same allowlist
semantics (wildcards, access groups, all-proxy-models, team aliases)
the proxy enforces on `/chat/completions` apply here too. Any
unauthorized model raises a 403 before the file is forwarded.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>

* fix(batches): count pre-tokenized prompt/input shapes, classify 403 logs

Two follow-ups from the Greptile review on the batch validation PR:

1. P1 TPM bypass via integer token arrays. The OpenAI batch schema
   accepts ``prompt`` and ``input`` as ``list[int]`` (a single
   pre-tokenized prompt) or ``list[list[int]]`` (multiple) in addition
   to the string and ``list[str]`` shapes. Pre-fix only the string
   shapes were counted, so a caller could submit a batch with hundreds
   of millions of pre-tokenized tokens and the rate limiter would
   record zero. Extract the per-field logic into
   ``_count_prompt_or_input_tokens`` and count each int as one token.

2. P2 access-denial logs were indistinguishable from I/O failures.
   ``count_input_file_usage`` caught every exception under a generic
   "Error counting input file usage" message, so an intentional 403
   from ``_enforce_batch_file_model_access`` looked the same in the
   logs as a missing file or a Prisma timeout. Catch ``HTTPException``
   separately and log 403s at WARNING level with a security-relevant
   message before re-raising.

Tests cover the new shapes: single ``list[int]``, ``list[list[int]]``
(the worst-case bypass vector), and embeddings ``input`` with
pre-tokenized arrays.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>

---------

Co-authored-by: Claude Opus 4.7 (1M context) <noreply@anthropic.com>

* fix(proxy): re-validate user_id after /user/info re-parses query (#27009)

* fix(proxy): re-validate user_id ownership after /user/info re-parses query

The route-level access check in `RouteChecks.non_proxy_admin_allowed_routes_check`
reads `request.query_params.get("user_id")`, which decodes literal `+` to
spaces. The endpoint then re-parses the raw query string with `urllib.unquote`
in `get_user_id_from_request` to preserve `+` characters (so plus-addressed
emails work as user_ids). Those two paths produce different ids: a caller
who registered a user_id containing a literal space could pass the route
check and then read another user's row by sending the encoded `+` form.

Add `_enforce_user_info_access` and call it after `_normalize_user_info_user_id`
returns the final id. Proxy admin / view-only admin still bypass; everyone
else must match the resolved user_id (or have no user_id, which falls back
to the caller's own id later in the handler).

Tests cover the admin bypass, owner-match path, and the cross-user lookup
that this change blocks.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>

* fix(proxy): apply user_info ownership check to PROXY_ADMIN_VIEW_ONLY

`_enforce_user_info_access` was bypassing both PROXY_ADMIN and
PROXY_ADMIN_VIEW_ONLY, but the upstream route check in
`RouteChecks.non_proxy_admin_allowed_routes_check` only treats
PROXY_ADMIN as a true admin for the `/user/info` route — view-only
admins go through the `user_id == valid_token.user_id` enforcement
along with regular users. Mirroring that asymmetry left the same
encoded-`+` bypass open for view-only admins whose user_id contains a
literal space.

Drop the PROXY_ADMIN_VIEW_ONLY exemption so the post-decode re-check
matches the upstream rule. Update tests: a view-only admin must now
be blocked from cross-user lookups but still allowed to read their
own row.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>

---------

Co-authored-by: yuneng-jiang <yuneng@berri.ai>
Co-authored-by: Claude Opus 4.7 (1M context) <noreply@anthropic.com>

* feat(spend-logs): opt-in suppression of stack traces in spend-tracking error logs

Adds LITELLM_SUPPRESS_SPEND_LOG_TRACEBACKS env var. When set to true and the
proxy log level is INFO or above, spend-tracking error paths emit a single
ERROR line without the full traceback. Stack traces are preserved at DEBUG
and the Sentry / proxy_logging_obj.failure_handler path is unchanged.

The new spend_log_error helper is wired through the spend write hot path:
  - DBSpendUpdateWriter (update_database, _update_*_db, batch upsert,
    redis-commit fallbacks)
  - _ProxyDBLogger._PROXY_track_cost_callback
  - get_logging_payload exception path
  - update_spend / update_daily_tag_spend / spend logs queue monitor

Resolves LIT-2704.

Co-authored-by: Mateo Wang <mateo-berri@users.noreply.github.com>

* fix(spend-logs): preserve no-traceback behavior for update_daily_tag_spend

This call site previously logged a single-line error via verbose_proxy_logger.error()
with no traceback. Switching it to spend_log_error(..., exc=e) caused a full stack
trace to render by default (when LITELLM_SUPPRESS_SPEND_LOG_TRACEBACKS is unset),
which contradicts the PR goal of leaving default behavior unchanged. Revert this
specific site to the original error log call.

* fix(spend-logs): preserve no-traceback behavior for update_daily_tag_spend

Bugbot caught a regression: the previous error log here was a single-line
verbose_proxy_logger.error(...) with no traceback. spend_log_error attaches
the active exception's traceback by default (when the suppression env var
is unset), so swapping it in changed default behavior. Revert this one site
to its original .error() call to keep the PR strictly opt-in.

Co-authored-by: Mateo Wang <mateo-berri@users.noreply.github.com>

* feat(spend-logs): suppress traceback in SpendLogs error_information row

Extend LITELLM_SUPPRESS_SPEND_LOG_TRACEBACKS to the failure callback so the
per-row Metadata pane in the UI no longer shows the stack trace when the
opt-in env var is set, matching the existing console-side suppression.

https://claude.ai/code/session_014dztoRbRnRvq54HL9EyHx6

* [Fix] Proxy: Repair Merge Fallout In Router-Override Fallback Auth

Conflict resolution for #26968 dropped the `Iterator` typing import
(NameError at module load), left a dead `fallback_models = cast(...)`
block, and the new tests called `_enforce_key_and_fallback_model_access`
without the now-required `request` kwarg.

* isolate dual OTEL handlers

* harden cloud file compatibility path

* harden cloud file compatibility path

* [Fix] Proxy/Key Management: Align Key-Org Membership Checks On Generate And Regenerate

Mirrors the membership rule on /key/update so that /key/generate and
/key/{key}/regenerate apply the same `_validate_caller_can_assign_key_org`
gate when the caller specifies an `organization_id`. Proxy admins bypass.
The check no-ops when `organization_id` is not being set.

* thread trusted params through vertex file content

* trust only server legacy file flag

* chore(proxy): keep public AI hub unauthenticated

* fix(proxy): preserve low-detail readiness status

* [Test] Anthropic: Replace Legacy Claude-4-Sonnet Alias With Haiku 4.5

Three live-API tests pinned to claude-4-sonnet-20250514, which is a
non-canonical alias of claude-sonnet-4-20250514. Anthropic's main API
no longer resolves the legacy form under freshly issued keys, so the
tests fail with not_found_error. The token counter test pinned to
claude-sonnet-4-20250514 itself (deprecation_date 2026-05-14, two weeks
out) was on borrowed time too.

Bump all four to claude-haiku-4-5-20251001 — capability superset for what
these tests exercise (streaming, parallel tool calling, extended thinking,
token counting), no upcoming deprecation, cheaper per-token.

* chore(proxy): move URL-valued model/file_id guard from SDK to proxy

The previous per-provider guards in HuggingFace, Oobabooga, and Gemini
files lived in the SDK layer, breaking SDK callers who legitimately pass
URL-valued model identifiers. Move the check to the proxy boundary in
add_litellm_data_to_request so SDK users keep working while proxy users
default-deny URL-valued model and file_id, with admin opt-in via
litellm.provider_url_destination_allowed_hosts.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>

* [Chore] Proxy/UI: Drop stray _experimental/out/chat/index.html

This file is a regenerable UI build artifact that should not be tracked
in source. Removing so the merge into litellm_internal_staging stays clean.

* [Test] Anthropic Passthrough: Bump Streaming Cost-Injection Test To Haiku 4.5

test_anthropic_messages_streaming_cost_injection hits the proxy's
/v1/messages route, which routes via the anthropic/* wildcard to
api.anthropic.com. The 404 surfaced in the test was Anthropic's own
not_found_error propagated back through the proxy (visible from the
x-litellm-model-id hash on the response — the proxy did route).

Same root cause as the prior commit: the legacy claude-4-sonnet-20250514
alias is no longer recognized by Anthropic's main API under the new key.
Swap to claude-haiku-4-5-20251001 — same routing path, canonical model.

* fix(proxy): handle ownership-recording failures after upstream create

If record_container_owner raises after the upstream container is created,
the user previously got a 500 with no usable container — they were billed
for an unreachable resource. Move ownership recording into the create
path's exception handling and split the two failure modes:

- HTTPException from the recorder (auth conflicts) propagates verbatim
  so the client sees the real status code, not a generic LLM error.
- Unexpected exceptions are logged and swallowed; the response is
  returned to the caller so they aren't billed for a container they
  can't address. The DB row stays untracked until an operator reconciles.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>

* fix(guardrails): close post-call coverage gaps

* fix(types): add /team/permissions_bulk_update to management_routes

The blocklist check in _check_proxy_admin_viewer_access only fires for
routes that match LiteLLMRoutes.management_routes — the bulk-update
endpoint was missing from that list, so the test for view-only admins
on /team/permissions_bulk_update fell through to "allow."

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>

* [Test] Anthropic Passthrough: Bump Thinking Tests Off Legacy Sonnet 4 Alias

base_anthropic_messages_test.test_anthropic_messages_with_thinking and
test_anthropic_streaming_with_thinking still pinned to
claude-4-sonnet-20250514 — the same legacy alias Anthropic no longer
recognizes under freshly issued keys. The other four tests in this base
class already use claude-sonnet-4-5-20250929; these two were missed.

Bump to claude-haiku-4-5-20251001 (supports_reasoning=true, no upcoming
deprecation). Subclasses including TestAnthropicPassthroughBasic
inherit these methods.

* fix(guardrails): cover multi-choice output variants

* fix(proxy): preserve public ai hub ui setting

* fix(scim): cascade FK cleanup on user delete and surface block status in UI

SCIM DELETE /Users/{id} previously called litellm_usertable.delete without
clearing rows that FK back to the user, so Postgres rejected the delete with
LiteLLM_InvitationLink_user_id_fkey and the SCIM caller saw a 500. Add a
helper to drop invitation_link, organization_membership, and team_membership
rows before the user delete (mirrors /user/delete in internal_user_endpoints).

Also add a Status column to the Virtual Keys and Internal Users tables so
admins can see at a glance which keys are blocked and which users SCIM has
deactivated. SCIM-blocked keys carry a tooltip explaining the origin.

Pin the dashboard's Node version to 20 via .nvmrc to match CI.

* chore: update Next.js build artifacts (2026-05-02 03:21 UTC, node v20.20.2)

* perf(proxy): cache container/skill ownership reads on the hot path

Container ownership and skill rows are looked up on every retrieve /
delete / list / file-content / chat-completion-with-skill call. The new
stores wrapped raw Prisma queries with no cache, putting one DB
round-trip on each request. Add an in-process TTL'd cache mirroring the
_byok_cred_cache pattern in mcp_server/server.py: per-key (value,
monotonic_timestamp), 60s TTL, 10000-entry cap with full-clear on
overflow, invalidated by every write. Negative results (`None`) are
cached too so untracked-resource checks also skip the DB.

Tests cover: cache-after-first-hit, negative caching, write
invalidation, no-caching-on-DB-error, TTL expiry, capacity eviction.
56 tests pass.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>

* chore: update Next.js build artifacts (2026-05-02 03:39 UTC, node v20.20.2)

* fix: remove traceback key instead of it being ""

* fix: linting error

* fix(scim): preserve scim_active on PUT when client omits the field

A SCIM PUT may legally omit `active` (full-replace with the field
absent). Pydantic fills the SCIMUser.active default of True, so the PUT
handler was overwriting metadata.scim_active with True even when the
client never sent it — silently reactivating a previously SCIM-blocked
user and unblocking their keys.

Use model_fields_set to detect whether the client actually sent
`active`. If omitted, preserve the prior scim_active value and skip
the cascade to virtual keys.

Also drop comments added in this PR that just narrate what the code
does; keep only the docstrings and the SQL-NULL pitfall note that
explain non-obvious behaviour.

Co-authored-by: Mateo Wang <mateo-berri@users.noreply.github.com>

* fix(proxy): use set lookup for permitted agent filters

* fix(mcp): redact command fields for non-admin server views

* fix(proxy): forward decoded container ids after ownership checks

* fix(caching): handle stale isolated Redis semantic index

* fix(cloudflare): support response_text in streaming chunk parser

Newer Cloudflare Workers AI models (e.g. Nemotron) emit 'response_text'
instead of 'response' on streamed chunks. The non-streaming path was
already updated to fall back to 'response_text' (#26385), but the
streaming chunk parser still only read 'response', which caused
streaming requests against those models to silently produce empty
content.

Mirror the non-streaming fallback in CloudflareChatResponseIterator.chunk_parser
and add a streaming test for the response_text shape.

Co-authored-by: Mateo Wang <mateo-berri@users.noreply.github.com>

* Fix code qa

* Address bugbot: drop dead encode/decode helpers; preserve empty custom_id

- Remove unused _encode_gcp_label_value / _decode_gcp_label_value singular
  helpers; only the _chunks variants are actually called.
- Use 'is not None' check for custom_id so empty-string custom_ids are
  still labeled and round-trip through batch outputs.

Co-authored-by: Mateo Wang <mateo-berri@users.noreply.github.com>

* Forward Vertex file content logging context

* test vertex file content logging forwarding

Co-authored-by: Sameer Kankute <Sameerlite@users.noreply.github.com>

* Fix Vertex batch output logging mutation

* fix: don't mutate caller's logging_obj in _try_transform_vertex_batch_output_to_openai

The method was overwriting logging_obj.optional_params, logging_obj.model,
and logging_obj.start_time on the caller's Logging instance. When invoked
from llm_http_handler.py's generic framework path, the framework's own
logging_obj (which already went through pre_call) had its properties
clobbered, causing model and start_time to reflect the last batch line's
values rather than the original call context.

Fix: create a fresh local Logging instance for the per-line transformation
instead of mutating the incoming logging_obj. The caller's object is now
left entirely untouched regardless of whether a logging_obj was passed in
or not.

Regression tests added to verify model, start_time, and optional_params
are not mutated on the caller's logging_obj.

Co-authored-by: Sameer Kankute <Sameerlite@users.noreply.github.com>

* feat: add opt-out flag for Vertex batch output transformation

Adds litellm.disable_vertex_batch_output_transformation (default False).
When True, afile_content returns raw Vertex predictions.jsonl untouched
so users that parse candidates/modelVersion directly are not broken.

* fix(anthropic,bedrock): omit thinking/output_config when reasoning_effort="none"

Setting reasoning_effort="none" on Anthropic chat models (direct, Bedrock
Invoke, Bedrock Converse, Vertex AI Anthropic, Azure AI Anthropic) crashed
LiteLLM with:

  litellm.APIConnectionError: 'NoneType' object has no attribute 'get'

Both the Anthropic chat transformation and Bedrock Converse called
``AnthropicConfig._map_reasoning_effort`` and assigned the ``None`` it returns
for ``"none"`` directly to ``optional_params["thinking"]``. Downstream
``is_thinking_enabled`` then did ``optional_params["thinking"].get("type")``
and crashed.

Pop ``thinking`` (and on Claude 4.6/4.7, ``output_config``) instead of
assigning ``None``, restoring the documented contract that
``reasoning_effort="none"`` means "do not enable thinking". This also
prevents downstream Anthropic 400s ("thinking: Input should be an object",
"output_config.effort: Input should be ...") if the bug were ever masked.

Verified end-to-end against the live Anthropic API and Bedrock Converse
on claude-opus-4-{5,6,7} and claude-sonnet-4-6, plus Bedrock Invoke for
Claude 4.5/4.6. Vertex AI Anthropic and Azure AI Anthropic inherit the
fixed ``map_openai_params`` from ``AnthropicConfig`` and need no further
changes.

* fix(vertex-ai): set response=null on batch error entries per OpenAI spec

The Vertex batch output transformer was emitting both a populated 'response' and 'error' for failed batch entries. The OpenAI Batch output spec defines them as mutually exclusive: on error 'response' MUST be null. This broke any consumer using 'result["response"] is None' to detect failures.

* test(vertex-ai): cover transformation_error path emits response=null

* fix(security): sandbox jinja2 in gitlab/arize/bitbucket prompt managers

DotpromptManager was hardened to render through
ImmutableSandboxedEnvironment. The three sibling managers (gitlab,
arize, bitbucket) were missed and still instantiate plain
jinja2.Environment(), leaving the same attribute-traversal SSTI
primitive open: a template fetched from a GitLab/BitBucket repo or
Arize Phoenix workspace can reach __class__.__init__.__globals__ and
execute arbitrary Python on the proxy host.

Match the dotprompt pattern by switching all three to
ImmutableSandboxedEnvironment. The sandbox blocks the dunder-traversal
chain while leaving normal {{ var }} substitution intact, so the
template surface is unchanged for legitimate use.

Adds tests/test_litellm/integrations/test_prompt_manager_ssti.py
(18 cases) verifying each manager's jinja_env is a sandbox, that
classic SSTI payloads raise SecurityError, and that ordinary variable
rendering still works.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>

* chore(proxy): drop client-supplied pricing fields from request bodies

The proxy currently forwards request-body pricing parameters (the fields
on `CustomPricingLiteLLMParams`, plus `metadata.model_info`) into the
core call path. Those fields belong to deployment configuration, not to
per-request input — sending them from a client mutates the request's
recorded cost and, via `litellm.completion` → `register_model`, the
process-wide `litellm.model_cost` map for every later caller in the
worker. Strip them at the boundary.

The strip set is built from `CustomPricingLiteLLMParams.model_fields` so
pricing fields added later are covered automatically. Operators who do
want clients to supply per-request pricing can opt back in per key or
team via `metadata.allow_client_pricing_override = true`, mirroring the
existing `allow_client_mock_response` and
`allow_client_message_redaction_opt_out` flags.

Tests cover the strip set's coverage, root and metadata strips, the
opt-in skip on both key and team metadata, and a regression check that
the global `litellm.model_cost` map is unmutated after a stripped
request.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>

* chore(proxy): log stripped pricing fields at debug for operator visibility

Operators upgrading would otherwise see client-supplied pricing overrides
silently stop applying with no diagnostic. Emit a debug-level line listing
the dropped fields and pointing at the opt-in flag when any are stripped;
stay silent on the no-op path so the log isn't filled with noise.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>

* fix(proxy): move pricing strip below the litellm_metadata JSON-string parse

The strip ran before the proxy parses ``litellm_metadata`` from a JSON
string into a dict (a path used by multipart/form-data and ``extra_body``
callers), so ``isinstance(metadata, dict)`` was False and ``model_info``
survived the strip. Move the call to the same post-parse position the
``user_api_key_*`` strip already uses for the same reason. Adds a
regression test exercising the JSON-string ``litellm_metadata`` path.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>

* test(responses): replace legacy claude-4-sonnet alias in multiturn tool-call test

Anthropic's main API no longer resolves the non-canonical 'claude-4-sonnet-20250514'
alias for freshly issued keys, returning 404 not_found_error. PR #27031 already
swept three other live tests pinned to this alias to claude-haiku-4-5-20251001
but missed test_multiturn_tool_calls in the responses API suite, which is now
failing reliably on PR CI runs (e.g. PR #27074, job 1603363).

Bump the two model references in test_multiturn_tool_calls to the same
claude-haiku-4-5-20251001 snapshot used by PR #27031 -- it covers everything
this test exercises (tool calling, multi-turn) and isn't on a deprecation
schedule.

Co-authored-by: Mateo Wang <mateo-berri@users.noreply.github.com>

* chore(proxy): close callback-config and observability-credential side channels

Two related gaps in the proxy's request bouncer:

1. ``is_request_body_safe`` (auth_utils.py) walked the request-body root
   and the ``litellm_embedding_config`` nested dict, but not ``metadata``
   or ``litellm_metadata``. The same fields it bans at root — Langfuse /
   Langsmith / Arize / PostHog / Braintrust / Phoenix / W&B Weave / GCS /
   Humanloop / Lunary credentials and routing — were silently accepted
   when the caller put them inside metadata, retargeting observability
   callbacks to a caller-controlled host with caller-supplied creds.
   Walk both metadata containers (and parse the JSON-string form sent via
   multipart / ``extra_body``) through the same banned-params helper, so
   the existing ``allow_client_side_credentials`` opt-in covers both
   paths consistently.

2. The banned-params list was hand-maintained and lagged the canonical
   ``_supported_callback_params`` allow-list in
   ``initialize_dynamic_callback_params``. Derive the observability bans
   from that allow-list (minus a small ``_SAFE_CLIENT_CALLBACK_PARAMS``
   set for informational fields like ``langfuse_prompt_version`` and
   ``langsmith_sampling_rate``) so future integrations are covered
   automatically; ``_EXTRA_BANNED_OBSERVABILITY_PARAMS`` carries the
   handful of fields integrations read but the allow-list hasn't caught
   up to. A guard test fails CI if a new entry is added to
   ``_supported_callback_params`` without an explicit safe-list decision.

Separately in ``litellm_pre_call_utils.py``: add ``callbacks``,
``service_callback``, ``logger_fn``, and ``litellm_disabled_callbacks``
to ``_UNTRUSTED_ROOT_CONTROL_FIELDS``. The first three are appended to
worker-wide ``litellm.{input,success,failure,_async_*,service}_callback``
lists / ``litellm.user_logger_fn`` from inside ``function_setup`` — one
request poisons every subsequent caller in that worker. The last is the
inverse primitive: the legitimate path reads it from key/team metadata,
the request-body version silently disables admin-configured audit /
observability for the call.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>

* fix(auth): per-param allow must continue, not return early

A pre-existing logic bug in ``_check_banned_params``: when the
deployment-level ``configurable_clientside_auth_params`` permitted one
banned field, the loop ``return``-ed on the first match instead of
``continue``-ing, so any other banned param later in the same body or
metadata dict was never checked. This PR's metadata walk multiplies the
surface where that bypass matters — a body pairing an allowed
``api_base`` with an observability credential like ``langfuse_host``
would silently pass.

Proxy-wide ``allow_client_side_credentials`` keeps ``return`` (it's a
global opt-in for every banned param). The per-param branch becomes
``continue`` so only the one explicitly-permitted field is skipped.

Adds a regression test that exercises the api_base + langfuse_host pair.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>

* fix(vector_store): resolve embedding config at request time, never persist creds

The vector store create/update path previously called
``_resolve_embedding_config`` against the admin-configured router/DB
model and persisted the resolved ``litellm_embedding_config`` dict
(``api_key`` / ``api_base`` / ``api_version``) into the
``litellm_managedvectorstorestable.litellm_params`` column. Because the
resolver expanded ``os.environ/...`` references via ``get_secret``, the
DB row carried cleartext provider credentials, and the
``/vector_store/{new,info,update,list}`` responses returned them to any
authenticated caller who could supply a known admin model name.

Move the auto-resolve out of ``create_vector_store_in_db`` and out of
the update path. Persist only the user-supplied ``litellm_embedding_model``
reference. Resolve at request-handling time inside
``_update_request_data_with_litellm_managed_vector_store_registry`` so
the resolved config lives in the per-request ``data`` dict and is
garbage-collected after the response. Legacy rows that were created by
an earlier proxy version and already carry a resolved
``litellm_embedding_config`` skip the re-resolution and pass through
unchanged so embedding calls keep working.

The ``new_vector_store`` response now also runs the existing
``_redact_sensitive_litellm_params`` masker (already used by ``info``,
``update``, and ``list``), defending against caller-supplied cleartext
on the create path and against legacy rows whose persisted credentials
are still in the database.

Existing tests that asserted the old write-time-resolve behaviour are
updated to assert the new persistence shape (no embedding config
stored, just the model reference). Two new tests cover the use-time
path: one asserting fresh resolution happens when a row carries only
the model reference, the other asserting legacy rows with persisted
config skip re-resolution and continue to work.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>

* fix(vector_store): tighten registry-mutation comment and dedupe test helpers

* fix(vector_store): cache use-time embedding-config resolution

Hold the resolved config in a process-memory TTL cache so the
request-handling path doesn't run litellm_proxymodeltable.find_first
on every vector-store call.

* fix(anthropic,bedrock,vertex): forward output_config.effort + 400 on garbage reasoning_effort

Follow-up bugs surfaced by the QA sweep on PR #27039
(https://github.com/BerriAI/litellm/pull/27039#issuecomment-4363363610).

1. Stop stripping output_config.effort on Bedrock + Vertex adaptive routes.
   - Vertex AI Claude 4.6/4.7 accepts output_config.effort on rawPredict
     (verified end-to-end against us-east5 / global). The strip helper now
     no-ops for effort.
   - Bedrock Converse routes output_config into additionalModelRequestFields
     for anthropic base models so the requested adaptive tier (low/medium/
     high/xhigh/max) actually reaches the wire instead of all collapsing to
     identical thinking.
   - Bedrock Invoke chat transformation (AmazonAnthropicClaudeConfig) stops
     popping output_config from the post-AnthropicConfig request body.
   - Bedrock Invoke /v1/messages allowlist (BedrockInvokeAnthropicMessagesRequest)
     now lists output_config so the runtime allowlist filter forwards it.

2. Validate effort across Bedrock Converse so 'disabled' / 'invalid' / '' /
   unsupported tiers (xhigh/max on Sonnet 4.6 or budget-mode 4.5 models)
   surface as a clean 400 BadRequestError instead of 500.

3. ValueError -> BadRequestError throughout (AnthropicConfig.map_openai_params,
   _apply_output_config, AmazonConverseConfig._handle_reasoning_effort_parameter).
   Empty-string effort is now rejected (was silently passing the
   'if effort and ...' short-circuit).

4. Floor reasoning_effort='minimal' at the Anthropic provider minimum
   (1024 budget_tokens) via new ANTHROPIC_MIN_THINKING_BUDGET_TOKENS so it's
   a usable tier on direct Anthropic / Azure AI Anthropic / Vertex AI Anthropic /
   Bedrock Invoke (all of which 400 below 1024).

5. model_prices: dedupe duplicate supports_max_reasoning_effort key on
   claude-opus-4-7 / claude-opus-4-7-20260416.

Adds regression tests across all five affected paths; existing tests asserting
the silent-strip behavior were updated to reflect the new pass-through and
clean 400 surfaces.

Co-authored-by: Mateo Wang <mateo-berri@users.noreply.github.com>

* fix(constants): make ANTHROPIC_MIN_THINKING_BUDGET_TOKENS a plain constant

The documentation CI test (tests/documentation_tests/test_env_keys.py)
asserts every os.getenv() key in the source has a matching entry in the
litellm-docs config_settings.md table. ANTHROPIC_MIN_THINKING_BUDGET_TOKENS
tracks Anthropic's published wire-protocol minimum (1024) — it's not a
user-tunable, so making it env-overridable was wrong anyway. Drop the
os.getenv() wrapper; the value is now a plain literal.

Co-authored-by: Mateo Wang <mateo-berri@users.noreply.github.com>

* fix(anthropic,bedrock): correct effort error message and dedupe effort_map

- Remove 'none' from the Bedrock _validate_anthropic_adaptive_effort error
  message; it was listed as a valid value but rejected by the membership
  check, leaving users in a feedback loop if they tried 'none'.
- Hoist the duplicated reasoning_effort -> output_config.effort mapping
  out of AnthropicConfig.map_openai_params and
  AmazonConverseConfig._handle_reasoning_effort_parameter into a single
  AnthropicConfig.REASONING_EFFORT_TO_OUTPUT_CONFIG_EFFORT class constant
  so the two routes cannot drift.

* fix(anthropic): translate reasoning_effort on /v1/messages route

Closes the remaining QA-sweep gap on PR #27074: Bedrock Invoke
/v1/messages was silently ignoring ``reasoning_effort`` because the
shared param filter only kept native Anthropic keys, so every effort
tier collapsed to the same behavior on the wire (27/231 cells failing
across opus-4-5 / opus-4-6 / sonnet-4-6).

Map ``reasoning_effort`` to native Anthropic ``thinking`` /
``output_config.effort`` at the ``AnthropicMessagesConfig`` layer so
all four /v1/messages routes (direct Anthropic, Azure AI, Vertex AI,
Bedrock Invoke) inherit the same translation:

- Add ``reasoning_effort`` to ``AnthropicMessagesRequestOptionalParams``
  so the param filter in
  ``AnthropicMessagesRequestUtils.get_requested_anthropic_messages_optional_param``
  no longer drops it before the transformation runs.

- Add ``_translate_reasoning_effort_to_anthropic`` and call it from
  ``transform_anthropic_messages_request``. Mirrors
  ``AnthropicConfig.map_openai_params`` on the chat completion path
  (re-uses ``_map_reasoning_effort`` and
  ``REASONING_EFFORT_TO_OUTPUT_CONFIG_EFFORT``) so the two routes
  cannot drift. Pops ``reasoning_effort`` so it never reaches the wire.

- Caller-supplied native ``thinking`` / ``output_config.effort`` always
  win — same precedence as
  ``_translate_legacy_thinking_for_adaptive_model``.

- Garbage values (``""``, ``"disabled"``, ``"invalid"``) raise
  ``AnthropicError(status_code=400)`` instead of falling through and
  surfacing as 500s from the provider.

- ``"none"`` clears thinking + output_config so callers can opt out
  per request.

Also restores the non-adaptive-model test coverage on Bedrock Invoke
/v1/messages that the previous commit lost when
``test_bedrock_messages_strips_output_config`` was renamed to the
``forwards`` variant on Opus 4.7.

Adds a new test file
``test_reasoning_effort_translation.py`` covering the translation at
the shared config level (adaptive + non-adaptive models, none, garbage,
caller precedence) so all four /v1/messages routes are exercised by a
single suite.

Adds parametrized + behavioral tests on the Bedrock Invoke /v1/messages
suite covering: minimal/low/medium/high/xhigh/max mapping for adaptive
models, thinking-budget mapping for non-adaptive Opus 4.5, ``none``
clears both, garbage raises 400, explicit ``output_config`` wins.

Refs: https://github.com/BerriAI/litellm/pull/27074

* fix(anthropic,bedrock): reject unmapped reasoning_effort at mapping site

Both the chat completion path (AnthropicConfig.map_openai_params) and the
Bedrock Converse path (_handle_reasoning_effort_parameter) used
REASONING_EFFORT_TO_OUTPUT_CONFIG_EFFORT.get(value, value) which falls
back to the raw input on unmapped keys. Combined with _map_reasoning_effort
returning type='adaptive' for any string on Claude 4.6/4.7, garbage values
(e.g. 'disabled') could leak into optional_params['output_config']['effort']
unvalidated if map_openai_params ran without the downstream transform_request
or _validate_anthropic_adaptive_effort check.

Mirror the /v1/messages pattern: use .get(value) (no fallback) and raise
BadRequestError immediately when the value is unmapped, co-locating
validation with the mapping for defense in depth.

* style: black formatting

Co-authored-by: Mateo Wang <mateo-berri@users.noreply.github.com>

* fix(anthropic): stop class-attr leak; gate xhigh/max on every route

The reasoning-effort mapping dict was a public class attribute on
AnthropicConfig, so BaseConfig.get_config returned it as a request
parameter and every Anthropic-backed call (Anthropic / Azure / Vertex /
Bedrock Invoke) hit a 400 'REASONING_EFFORT_TO_OUTPUT_CONFIG_EFFORT:
Extra inputs are not permitted' from the provider. Move the mapping
to a module-level constant.

_supports_effort_level only looked the model up under
custom_llm_provider='anthropic', so bedrock-prefixed model ids
(e.g. bedrock/invoke/us.anthropic.claude-opus-4-7) returned False
for both 'max' and 'xhigh' even when the underlying model entry has
the flag set. Strip known provider prefixes and retry the lookup
against litellm.model_cost directly so per-model gating works on
every route.

Mirror the per-model xhigh/max gate from
AnthropicConfig._apply_output_config in
AnthropicMessagesConfig._translate_reasoning_effort_to_anthropic so
the /v1/messages route also raises a clean 400 instead of forwarding
the unsupported tier.

* feat(anthropic,bedrock): strip output_config under drop_params for non-effort models

When a proxy fronts Claude Code (which always sends `output_config.effort`)
at a pre-4.5 Anthropic model — haiku-3, sonnet-3.5, opus-3, sonnet-4 — the
forwarded knob causes a forced 400 the client can't fix. Gating a strip
behind the existing `drop_params` flag lets operators opt into silent
fixup once and stop worrying about per-model param hygiene.

Default (`drop_params=False`) still forwards and surfaces the provider's
error, preserving the strict, debuggable contract from #27074.

Per https://platform.claude.com/docs/en/build-with-claude/effort the
supporting set is Opus 4.5+, Sonnet 4.6+, and Mythos Preview; everything
else is dropped (with a verbose_logger warning so the strip is visible).
Recognition uses model-name patterns plus a fallback to any
`supports_*_reasoning_effort` flag in the model map for forward
compatibility with new entries.

https://claude.ai/code/session_01WjHq31rvXT6xYNdVmSJvRp

(cherry picked from commit 1233943e78)

* fix(base_llm): filter all _-prefixed class attrs from get_config

The drop_params strip work added `AnthropicConfig._EFFORT_SUPPORTING_MODEL_PATTERNS`
as a private class-level lookup tuple. `BaseConfig.get_config()` only
filtered the `__`-prefixed names plus `_abc` / `_is_base_class`, so
`_EFFORT_SUPPORTING_MODEL_PATTERNS` would have leaked into the request
body the same way `REASONING_EFFORT_TO_OUTPUT_CONFIG_EFFORT` did before
the previous commit.

Generalize the existing `_abc` / `_is_base_class` carve-outs to skip
every `_`-prefixed name. `AmazonConverseConfig.get_config()` overrides
the base method, so apply the same change there.

Also unblocks future internal helpers from accidentally serialising into
the wire body.

* fix(anthropic): drive output_config.effort support from model map flags

Replace hardcoded _EFFORT_SUPPORTING_MODEL_PATTERNS with a JSON-backed
check that uses supports_*_reasoning_effort flags from the model map.
Add supports_minimal_reasoning_effort: true to opus-4-5 and mythos-preview
entries (which previously only carried supports_reasoning) so the JSON
remains the single source of truth for effort capability.

* fix(anthropic,bedrock,databricks): four reasoning_effort follow-ups

- claude-sonnet-4-6 + reasoning_effort=max no longer 400s. Renamed
  _is_opus_4_6_model to _is_claude_4_6_model at three sites and added
  supports_max_reasoning_effort: true to 12 model entries in the JSON
  cost map (10 sonnet 4.6 ids + OpenRouter opus 4.6/4.7).
- _map_reasoning_effort now raises BadRequestError(400) directly with
  llm_provider, instead of letting Databricks (and similar callers)
  surface its raw ValueError as a 500.
- output_config.effort on Opus 4.5 over Bedrock no longer 400s for
  missing effort-2025-11-24 beta. Flipped JSON to "effort-2025-11-24"
  for bedrock + bedrock_converse and added an auto-attach branch in
  _process_tools_and_beta for non-adaptive Anthropic + output_config
  on Converse.
- reasoning_effort=xhigh / =max on legacy budget-mode models
  (Haiku 4.5, Sonnet 4.5, Opus 4.5) now map to thinking.budget_tokens
  8192 / 16384 instead of returning 400. Added two constants in
  litellm/constants.py.

Tests updated for all four flips. Validated end-to-end via 306-cell
live proxy matrix (6 model families x 3 routes x 17 effort cases),
all pass.

* fix(databricks): validate reasoning_effort and set output_config on adaptive Claude

The Databricks path called `AnthropicConfig._map_reasoning_effort` for
Claude models but never validated the effort string nor set
`output_config.effort` for adaptive models (Claude 4.6/4.7). Since
`_map_reasoning_effort` returns `type=adaptive` for ANY non-None /
non-"none" string on adaptive models (including "disabled",
"invalid", ""), Databricks silently accepted garbage and emitted a
request without an `output_config.effort`, collapsing every adaptive
tier to identical behavior.

Match the Anthropic native, Bedrock Converse, Bedrock Invoke, and
/v1/messages paths: when the resolved `thinking` is non-None on a
4.6/4.7 model, look up the value in
`REASONING_EFFORT_TO_OUTPUT_CONFIG_EFFORT` and either raise a clean
`BadRequestError` or set `optional_params["output_config"]`.

* fix(azure): omit model from image generation and image edit deployment requests

Azure OpenAI routes image gen/edit by deployment in the URL; sending the
deployment id in model breaks gpt-image-2 (invalid_value). Strip model from
JSON for deployments/.../images/generations and from multipart data for
.../images/edits. Non-deployment URLs (e.g. Azure AI FLUX) unchanged.

Fixes #26316.

Co-authored-by: Cursor <cursoragent@cursor.com>

* test(azure): exercise image gen JSON filter via HTTP client; dedupe image edit URL

- Image generation tests patch HTTPHandler.post / get_async_httpx_client so
  make_*_azure_httpx_request runs and wire json is asserted on call kwargs.
- Azure image edit: strip model in finalize_image_edit_multipart_data using the
  same URL string the handler passes to POST (no second get_complete_url in
  transform). BaseImageEditConfig default finalize is a no-op.

Co-authored-by: Cursor <cursoragent@cursor.com>

* fix(azure_ai/anthropic): promote output_config out of extra_body so validation runs

`azure_ai` is registered in `litellm.openai_compatible_providers`, so
`add_provider_specific_params_to_optional_params` (litellm/utils.py)
auto-stuffs any non-OpenAI kwarg (e.g. `output_config={"effort": "..."}`)
into `optional_params["extra_body"]`. `AzureAnthropicConfig.transform_request`
then strips `extra_body` entirely on the way out, silently dropping the
param — and `AnthropicConfig._apply_output_config` never sees it, so
`effort="invalid"` / `effort="xhigh"` on a non-supporting model
quietly reaches the model with default behavior instead of returning a
clean 400 (as the native `anthropic` provider does).

Promote the keys back to top-level `optional_params` (using `setdefault`
so explicit top-level values win) before delegating to the parent
`AnthropicConfig`. Apply in both `validate_environment` and
`transform_request` so flag detection (`is_mcp_server_used`, etc.) and
output-config validation both run.

Surfaced by the QA matrix expansion on PR #27074: 20 cells where Azure
returned 200 while `anthropic` returned 400 — all `output_config` mode
across haiku_4_5, sonnet_4_5, opus_4_5, sonnet_4_6, opus_4_6, opus_4_7
families with `effort` in {invalid, xhigh, max, low, medium, high}.

Tests:
* `test_output_config_promoted_from_extra_body`: valid effort reaches data
* `test_invalid_output_config_effort_raises_via_extra_body`: 400 on bad effort
* `test_unsupported_effort_xhigh_raises_via_extra_body`: 400 on xhigh-on-Sonnet-4.6
* `test_extra_body_promotion_does_not_clobber_top_level`: setdefault semantics

* test(image_gen): expect no model in Azure image edit multipart (#26316)

Align test_azure_image_edit_litellm_sdk with deployment-scoped Azure edits.

Co-authored-by: Cursor <cursoragent@cursor.com>

* refactor(anthropic): extract _validate_effort_for_model to prevent drift

The chat completion path (`_apply_output_config`) and the /v1/messages
pass-through (`AnthropicMessagesConfig._translate_reasoning_effort_to_anthropic`)
both gate `max` / `xhigh` per model. The two sites had diverged from
near-identical copies into separately maintained blocks, creating a real
drift risk when a new model tier (e.g. Claude 4.8) lands -- a contributor
could update one site and miss the other.

Centralise the gating in `AnthropicConfig._validate_effort_for_model`,
which returns an error message string or `None`. Each call site keeps
its own provider-appropriate exception type (`BadRequestError` for the
chat path, `AnthropicError` for the /v1/messages pass-through) but the
gating decision now comes from one place. Net -11 LOC.

Adds a parametrised unit test exercising the helper directly across
4.5 / 4.6 / 4.7 model families and `max` / `xhigh` / lower-effort
inputs. Existing tests at both call sites continue to pass unchanged.

Addresses Greptile finding on PR #27074.

* fix(databricks): narrow reasoning_effort_value to str for mypy

`non_default_params.get("reasoning_effort")` returns `Any | None`,
but `REASONING_EFFORT_TO_OUTPUT_CONFIG_EFFORT.get()` expects `str`.
Mypy flagged this on the strict pass. Narrow with `isinstance` before
the lookup; non-strings fall through to the existing `BadRequestError`
below with a clean validation message, so behavior is unchanged.

Fixes a regression introduced by 1a10746e95 in this PR.

* feat(proxy): add health_check_reasoning_effort for model health checks

Co-authored-by: Cursor <cursoragent@cursor.com>

* test(image_gen): align Azure image gen fixture with body omitting model

Expected JSON matches deployment-scoped Azure POST (#26316).

Co-authored-by: Cursor <cursoragent@cursor.com>

* test(anthropic/chat): force PR-local model_cost map via autouse fixture

CI runs without LITELLM_LOCAL_MODEL_COST_MAP=True, so litellm.model_cost
is loaded from main-branch JSON (default model_cost_map_url) instead of
the PR's checked-out model_prices_and_context_window.json. Tests that
assert per-model flags added in this PR (supports_max_reasoning_effort,
supports_xhigh_reasoning_effort) therefore pass locally but fail in CI
with 'AssertionError: assert False is True' on 5 cases:

  - test_anthropic_model_supports_effort_param_recognizes_supporting_models
    [anthropic.claude-mythos-preview, bedrock/.../mythos-preview,
     claude-opus-4-5-20251101]
  - test_supports_effort_level_handles_provider_prefixes
    [bedrock/invoke/us.anthropic.claude-sonnet-4-6-max-True,
     claude-sonnet-4-6-max-True]

Add an autouse fixture at tests/test_litellm/llms/anthropic/chat/conftest.py
that monkey-patches litellm.model_cost to the PR-local JSON for every test
in this directory. The parent conftest already snapshots+restores
litellm.model_cost per-function, so the mutation is contained.

This is a scoped workaround. The proper fix is to set the env var
globally in the test workflow once the ~10 inline self-set test files
are audited; tracking that as a follow-up issue.

* [Fix] Docker: Pin Wolfi And Uv To Multi-Arch Index Digests

The previous pins resolved to single-platform amd64 manifests, so buildx
pulled the same amd64 base for both linux/amd64 and linux/arm64 targets.
The published OCI index then advertised an arm64 entry whose layers are
byte-identical to amd64 -- arm64 users got an amd64 binary.

Switch all three Dockerfiles to the multi-arch image-index digests:
  - cgr.dev/chainguard/wolfi-base   (index has linux/amd64 + linux/arm64)
  - ghcr.io/astral-sh/uv:0.11.7     (index has linux/amd64 + linux/arm64)

Resolved with `docker buildx imagetools inspect <ref>` -- that returns
the index digest. `docker pull` + `docker inspect` returns the per-host
platform digest, which is what slipped in last time.

* [Fix] Docker: Pin Uv To Multi-Arch Index Digest In Remaining Dockerfiles

Apply the same fix to the three Dockerfiles not in the release pipeline
today (alpine, dev, health_check) so they stay correct if/when they're
built for arm64 in the future.

Wolfi pins are not present in these files; the python:3.11-alpine and
python:3.13-slim digests they already use are multi-arch indexes that
include arm64/v8, so only the uv pin needed swapping.

* fix(xai): fold reasoning_tokens into completion_tokens to satisfy OpenAI invariant

xAI's chat completions API accounts reasoning_tokens separately from
completion_tokens, but rolls them into total_tokens. This breaks the
OpenAI invariant total_tokens == prompt_tokens + completion_tokens
that downstream consumers (including litellm's own _usage_format_tests
in tests/llm_translation/base_llm_unit_tests.py:58) rely on.

Live capture (grok-3-mini-beta, 2026-05-04):
    prompt=14, completion=10, total=336, reasoning=312
    14 + 10 = 24, NOT 336.

OpenAI's o1/o3 reasoning models include reasoning_tokens in
completion_tokens, leaving the prompt+completion=total invariant
intact. xAI deviates. This patch aligns xAI to OpenAI semantics by
folding reasoning_tokens into completion_tokens after the parent
OpenAI parser runs.

The fold is idempotent and defensive:
- Only fires when total_tokens == prompt_tokens + completion_tokens
  + reasoning_tokens (the documented xAI shape). Refuses to fold if
  the gap doesn't match, guarding against silent corruption when xAI
  changes accounting.
- Skips if completion_tokens already covers the gap (already
  normalised — e.g. cost calc replays a previously-folded Usage).

xai.cost_calculator.cost_per_token already added reasoning_tokens to
the visible completion count for billing. Post-fold the Usage block
now satisfies that invariant directly, so the cost calc would
double-bill. Updated cost_per_token to detect the OpenAI-normalised
shape (total == prompt + completion) and skip the reasoning add-on
in that case, falling through to the legacy raw-shape behaviour for
callers that bypass the transformation (e.g. proxy log replay).

Tests:
- Adds TestXAIReasoningTokenFolding covering: gap-explained-fold,
  idempotent-no-double-fold, no-reasoning-skip, gap-mismatch-skip.
- Adds test_already_normalised_usage_does_not_double_count_reasoning
  to lock the cost-calc idempotency.
- Updates 7 pre-existing cost-calc tests whose total_tokens was
  internally inconsistent (used the OpenAI-normalised total but kept
  reasoning_tokens external) to use the documented xAI raw shape
  total = prompt + visible completion + reasoning. Pre-existing
  values masked the missing-fold by accident.

Verified end-to-end against the live xAI API:
    LITELLM_LOCAL_MODEL_COST_MAP=False (CI default) +
    XAI_API_KEY set +
    pytest tests/llm_translation/test_xai.py::TestXAIChat::test_prompt_caching
        -> PASSED in 18.81s (was: AssertionError on
        usage.total_tokens == usage.prompt_tokens + usage.completion_tokens)

20/20 tests in tests/test_litellm/llms/xai/test_xai_cost_calculator.py
and 8/8 in tests/test_litellm/llms/xai/test_xai_chat_transformation.py
pass.

* refactor(bedrock/converse): delegate effort gating to AnthropicConfig._validate_effort_for_model

Removes the duplicated max/xhigh gating logic in
_validate_anthropic_adaptive_effort and the now-unused
_supports_effort_level_on_bedrock helper. Per-model gating now flows
through the centralized AnthropicConfig._validate_effort_for_model
(whose _supports_effort_level already strips Bedrock prefixes), so the
chat completion, /v1/messages, and Bedrock Converse paths can't drift
when a new gated effort tier is added.

* Implement normalize_nonempty_secret_str function to trim whitespace from secrets and treat empty values as unset. Update proxy_server to use this function for Grafana credentials. Enhance tests to validate the new normalization behavior.

* Fix qdrant semantic cache miss metadata

* chore(deps): refresh dependency locks

* chore(deps): authorize pytest license

* fix: preserve tokenizer decode round trips

* refactor(anthropic): drive adaptive-thinking gate via supports_adaptive_thinking flag

Three of greptile's open comments on #27074 (P2 converse:512, P1
databricks:361, and the underlying capability-flag policy rule) flagged
the same pattern: _is_claude_4_6_model(...) or _is_claude_4_7_model(...)
used inline as a runtime 'is this an adaptive-thinking model?' check.
That requires a code release each time a new adaptive Claude lands.

Consolidate the inline gating to AnthropicModelInfo._is_adaptive_thinking_model,
and switch the helper itself to read a new supports_adaptive_thinking
flag from `model_prices_and_context_window.json` via `_supports_factory`,
falling back to the family pattern only when the model-map entry doesn't
carry the flag (preserves OpenRouter / Vercel / Bedrock-prefixed variants
that route through the same code path with non-canonical ids).

Adds `supports_adaptive_thinking: true` to the four 4.6/4.7 anthropic
entries (opus-4-6 + dated, opus-4-7 + dated, sonnet-4-6). Bedrock-prefixed
and Vertex-prefixed entries don't need the flag because both fall back
through the family pattern (the helper short-circuits early on True from
either path) and the bedrock/vertex Claude IDs all match the existing
opus-4-{6,7} / sonnet-4-{6,7} pattern.

Affected call sites:

- `bedrock/chat/converse_transformation.py:_handle_reasoning_effort_parameter`
- `anthropic/chat/transformation.py:_map_reasoning_effort`
- `anthropic/chat/transformation.py:map_openai_params` (output_config branch)
- `databricks/chat/transformation.py:map_openai_params` (output_config branch)

The remaining `_is_claude_4_6_model` / `_is_claude_4_7_model` references
in `AnthropicConfig._validate_effort_for_model` and
`AnthropicConfig.get_supported_openai_params` are intentionally retained:
they're per-model gating fallbacks for variants whose model-map entries
don't yet carry the `supports_max_reasoning_effort` /
`supports_reasoning` flag. Those are documented in-place.

Tests: 537 anthropic/bedrock/databricks/vertex/messages tests pass.

Co-authored-by: Mateo Wang <mateo-berri@users.noreply.github.com>

* chore(deps): address dependency review notes

* test(model_prices): add supports_adaptive_thinking to schema

`test_aaamodel_prices_and_context_window_json_is_valid` validates the
model-map JSON against an explicit schema with `additionalProperties`,
so the new `supports_adaptive_thinking` flag added in
98ced0ae43 needs a matching schema entry.

Co-authored-by: Mateo Wang <mateo-berri@users.noreply.github.com>

* refactor: remove unnecessary comments from #27074

Strip out the explanatory and historical comments that don't carry
business-logic justification. Comments that simply narrate what code
does — or that explain prior behavior, what was changed, or which PR
introduced a fix — are removed. Docstrings are reduced to a one-line
summary where the long form repeated information already evident from
the code or test data.

No code-behavior changes. All 643 affected unit tests still pass.

Co-authored-by: Mateo Wang <mateo-berri@users.noreply.github.com>

* test: keep decode token test local

* chore(deps): align dashboard node engine

* feat: selectively apply routing strategy according to model name

* style: make _model_supports_effort_param more concise

* refactor(anthropic,bedrock): hoist drop_params output_config warning to module constant

Three call sites (anthropic chat, bedrock converse, bedrock invoke messages)
emitted the same '...Effort is only supported on Opus 4.5+, Sonnet 4.6+, and
Mythos Preview' warning verbatim. Extract DROP_UNSUPPORTED_OUTPUT_CONFIG_WARNING
in litellm/llms/anthropic/chat/transformation.py and import it from the bedrock
sites so future copy edits live in one place.

Addresses Michael's review on PR #27074.

Co-authored-by: Mateo Wang <mateo-berri@users.noreply.github.com>

* refactor(anthropic,bedrock,databricks): factor BadRequestError for unknown reasoning_effort

Three call sites raised the same BadRequestError("Invalid reasoning_effort:
... Must be one of 'minimal', 'low', ...") block when REASONING_EFFORT_TO_OUTPUT_CONFIG_EFFORT
returned None: anthropic chat map_openai_params, bedrock converse
_handle_reasoning_effort_parameter, and databricks chat reasoning_effort path.

Extract AnthropicConfig._raise_invalid_reasoning_effort(model, value, llm_provider)
so future copy edits / valid-set changes happen in one place. Typed as NoReturn
so type-checkers correctly narrow control flow at call sites.

Addresses Michael's review on PR #27074.

Co-authored-by: Mateo Wang <mateo-berri@users.noreply.github.com>

* Clean up Redis semantic cache isolation fallback

* fix(guardrails): align banned_keywords + azure_content_safety call_type gates with runtime route_type

The hooks gated on ``call_type == "completion"`` but the proxy ingress
passes ``route_type`` straight through as ``call_type`` —
``"acompletion"`` for /v1/chat/completions and ``"aresponses"`` for
/v1/responses. Tests passed because they used the literal sync
``"completion"`` value, masking the gap.

Switch both hooks to ``is_text_content_call_type`` (matches the
canonical runtime values: completion / acompletion / aresponses) and
update existing tests to assert against runtime values, plus parametrize
a regression test that pins the gate.

* fix: remove unused import

* Add semantic cache legacy migration flag

* Treat 0 team_member_budget as no cap

* chore(caching): annotate qdrant quantization_params dict type

Mypy infers the dict's value type from the first branch
(Dict[str, bool]) which clashes with the scalar branch's mixed-type
inner dict. Explicit Dict[str, Any] annotation lifts the inference.

* chore(caching): remove allow_legacy_unscoped_cache_hits opt-in

The flag was an opt-in escape hatch for the cross-tenant leak the rest
of the patch closes — flipping it on (env var or constructor param)
re-enables exactly the VERIA-54 primitive on either backend. There is
no operational need that the secure path doesn't already meet:

- Qdrant: legacy points without ``litellm_cache_key`` payload are
  excluded by the must-clause filter and treated as misses; new sets
  populate the cache key, so cold-start lasts only as long as the
  natural cache rebuild.
- Redis: existing unscoped index can't carry the new schema; the init
  path falls back to ``{name}_isolated`` (and recreates it on stale
  schema), leaving the legacy index untouched.

Drop the constructor param, env-var fallback, ``_using_legacy_unscoped_index``
flag, the legacy-reuse branch in ``_init_semantic_cache``, and the
matching guards in set/get paths. Update tests to drop the legacy-mode
cases and assert the secure-only behaviour.

* fix(container): keep ownership-filter exceptions out of the LLM-error path

filter_container_list_response runs after the upstream call has
already succeeded; treating an ownership-lookup failure as an LLM-API
error fires post_call_failure_hook for a successful upstream call and
returns a misleading provider-shaped error to the client. Run the
filter outside the try/except so genuine LLM errors stay scoped to
the upstream call.

* chore(container,skills): LRU eviction for owner caches; widen file_purpose Literal

Two cleanups from the /simplify pass:

* ``_CONTAINER_OWNER_CACHE`` and ``_SKILL_CACHE`` now LRU-evict via
  ``OrderedDict.popitem(last=False)`` instead of full ``clear()`` at
  capacity. Full clears converted a steady-state cached workload into a
  periodic full-DB-load oscillation as the cache repopulated from zero
  and cleared again. Reads now ``move_to_end`` so the just-touched
  entry survives the next eviction. Mirrors the pre-existing LRU
  pattern in ``_remember_container_owner``.

* ``LiteLLM_ManagedObjectTable.file_purpose`` Literal now includes
  ``"container"`` so Pydantic validation accepts rows written by the
  ownership store.

* chore(container,skills): drop legacy-access opt-out env vars

LITELLM_ALLOW_UNTRACKED_CONTAINER_ACCESS and
LITELLM_ALLOW_UNOWNED_SKILL_ACCESS were operator-toggleable opt-outs
for the cross-tenant access primitive this PR closes — flipping either
on re-enabled exactly the VERIA-20 read path. Default-secure with no
escape hatch matches sibling fixes (vector-store cred isolation, semantic
cache key isolation, user_config strip): all rejected the
opt-out-of-security pattern.

Untracked containers and unowned skills (rows that pre-date this
enforcement) are admin-only. Non-admin owners need to either re-create
via the now-tracked flow or have an admin assign ``created_by`` on the
existing row. Update tests to assert the strict-only behaviour.

* fix(ownership): reject identity-less callers instead of sharing a sentinel scope

UNSCOPED_RESOURCE_OWNER_SCOPE collapsed every caller without an
identity field (no user_id / team_id / org_id / api_key / token) into
a single shared owner — a cross-tenant access primitive: any two such
callers could see and delete each other's containers and skills.

Drop the sentinel. ``get_primary_resource_owner_scope`` returns
``None`` and ``get_resource_owner_scopes`` returns ``[]`` for
identity-less callers. ``record_container_owner`` and
``LiteLLMSkillsHandler.create_skill`` now reject creates from
identity-less callers with a 403 instead of stamping the placeholder.
Read paths already deny ``owner is None`` correctly so legacy rows
(if any) are admin-only.

* fix(proxy): include request-blocked callback params in auth bans

* fix: keep skills handler FastAPI-free; fold gcs deny list into the body bouncer

Two cleanups:

* ``LiteLLMSkillsHandler.create_skill`` raised ``HTTPException`` for
  identity-less callers, importing FastAPI from a ``litellm/llms/``
  module — that violates the project rule that FastAPI lives only
  under ``proxy/``. Switch to ``ValueError`` (the same shape the rest
  of the handler uses for not-found/forbidden) and update the test.

* The proxy-auth body bouncer derived its observability ban list from
  ``_supported_callback_params`` only, missing
  ``_request_blocked_callback_params`` (where ``gcs_bucket_name`` and
  ``gcs_path_service_account`` live). Two recently-merged sibling PRs
  (#27019 added the deny list, #27081 added the test asserting these
  are rejected at the request body root) crossed without folding them
  together. Union the GCS deny list into the bouncer's derivation so
  the single source of truth covers both code paths.

* fix(proxy): normalize managed resource team owner field

* chore: simplify ownership tracking — drop thin stores, in-memory fallback, hand-rolled cache

Substantial reduction (~765 LOC) without changing the security
boundary:

* Drop ContainerOwnershipStore and LiteLLMSkillsStore — both were
  one-method-per-Prisma-call wrappers. Inline the calls instead,
  matching the established pattern in vector_store_endpoints,
  agent_endpoints, and mcp_server/db.py.

* Drop the prisma_client is None in-memory fallback. Production
  deploys always have Prisma; running ownership-critical paths on a
  process-local dict is a security footgun in the dev-mode case it
  was meant to support, and complicates every code path with a
  branch. Fail-secure: skip recording if Prisma is unavailable, and
  treat reads as "not found" (admin-only).

* Drop the hand-rolled module-level cache. Replace with the existing
  litellm.caching.in_memory_cache.InMemoryCache, which already has
  TTL + max-size + eviction tested in its own module. Sentinel string
  for negative caching since InMemoryCache can't disambiguate "miss"
  from "cached as None".

* Tests: drop coverage for removed code paths (in-memory fallback,
  hand-rolled cache internals). Keep tests for actual behavior (cache
  hit-rate, negative caching, owner check, list filtering,
  identity-less reject, admin bypass).

* fix(container): cache list-allow-set, track admin-created containers

Address Greptile P2 follow-ups from the prior round:

* Cache ``_get_allowed_container_ids`` (60s LRU/TTL keyed by sorted
  owner-scope tuple) so ``GET /v1/containers`` doesn't issue a fresh
  ``find_many`` against ``litellm_managedobjecttable`` on every list
  call. Invalidate the caller's own cache entry when they record a
  new owner so the just-created container shows up on their next list.

* Tighten the admin early-return in ``record_container_owner`` to skip
  ONLY when there's literally no container ID to stamp. An admin with
  identity (the master-key path populates ``user_id`` + ``api_key``)
  flows through the normal record path so admin-created containers are
  tracked like any other caller's. The truly-identity-less admin case
  still falls through to the 403 below — correct fail-secure default.

Skill-cache invalidation gap (also flagged by Greptile) is moot: there
is no skill update endpoint exposed; ownership-affecting mutations are
only delete (already invalidates) and create (new ID, no cache entry
to update).

* chore(container): use delete_cache, json-encode scope key, clean test

/simplify follow-ups:

* Replace the two-``pop`` reach into ``cache_dict``/``ttl_dict`` with
  the existing public ``InMemoryCache.delete_cache(key)`` — the same
  idiom used elsewhere in the proxy. Bonus: ``delete_cache`` calls
  ``_remove_key`` which also handles ``expiration_heap`` consistency
  the direct pops were silently leaking.

* JSON-encode the sorted scope list for the cache key instead of
  ``"|".join``. ``user_id`` / ``team_id`` / ``org_id`` / ``api_key``
  are free-form strings and could contain a literal ``|`` — JSON
  quoting escapes any in-string separator unambiguously.

* Extract ``_allowed_container_ids_cache_key()`` so the read and
  invalidation sites compute the key the same way.

* Fix a placeholder-then-overwrite test construction: the
  ``__module__.split(".")[0] and "proxy_admin"`` line evaluated to a
  literal string that was immediately overwritten with the real enum
  value. Hoist the import and construct directly.

* [Fix] Tests: Replace deprecated openrouter/claude-3.7-sonnet with claude-sonnet-4.5

OpenRouter has dropped active endpoints for anthropic/claude-3.7-sonnet,
causing test_reasoning_content_completion to fail with a 404 "No endpoints
found" error. Switch to anthropic/claude-sonnet-4.5, which is current and
supports reasoning streaming.

* feat: routing groups ui

* fix(security): prevent secret_fields from leaking into spend logs

secret_fields (containing raw HTTP headers including Authorization
Bearer tokens) was being included in proxy_server_request['body']
because the body snapshot was a copy.copy(data) of the full request
dict. This body gets serialized and persisted in the LiteLLM_SpendLogs
table, exposing user credentials in the database.

Root cause: data['secret_fields'] was set before the body snapshot at
data['proxy_server_request']['body'] = copy.copy(data), so the full
raw headers (including auth tokens) ended up in the snapshot.

Fix (defense in depth):
1. Exclude 'secret_fields' when creating the body snapshot in
   litellm_pre_call_utils.py (primary fix)
2. Strip 'secret_fields' in _sanitize_request_body_for_spend_logs_payload
   as a secondary safeguard

secret_fields remains available on the live data dict for legitimate
downstream consumers (MCP, Responses API).

Co-authored-by: Krrish Dholakia <krrish-berri-2@users.noreply.github.com>

* chore: update Next.js build artifacts (2026-05-05 02:13 UTC, node v20.20.2)

* [Fix] Proxy: Break managed-resources import cycle on Python 3.13

The Python 3.13 CCI smoke matrix surfaces a partially-initialized-module
ImportError when loading the managed files hook chain:

  litellm.proxy.hooks/__init__ (mid-import)
    -> enterprise.enterprise_hooks
    -> litellm_enterprise.proxy.hooks.managed_files
    -> litellm.llms.base_llm.managed_resources.isolation
    -> litellm.proxy.management_endpoints.common_utils
    -> litellm.proxy.utils  (re-enters litellm.proxy.hooks)

The except ImportError block in hooks/__init__.py silently swallowed the
failure, leaving managed_files unregistered and POST /files returning
500 "Managed files hook not found".

Two-layer fix:
- Inline the 3-line _user_has_admin_view check in isolation.py instead
  of importing it from litellm.proxy.management_endpoints.common_utils.
  litellm.llms.* should not depend on litellm.proxy.* — removing this
  layering violation breaks the cycle at its root.
- Define PROXY_HOOKS and get_proxy_hook before the conditional
  enterprise import in litellm/proxy/hooks/__init__.py, so any future
  re-entry resolves the public names instead of hitting an
  ImportError on a partially-initialized module.

Also fold in two unrelated CCI repairs surfaced in the same staging run:
- tests/otel_tests/test_key_logging_callbacks.py: per-key
  gcs_bucket_name / gcs_path_service_account are now stripped by
  initialize_dynamic_callback_params, so the GCS client falls through
  to the env-only branch. Update the assertion to match the new
  "GCS_BUCKET_NAME is not set" message.
- .circleci/config.yml: tests/pass_through_tests now resolves
  google-auth-library@10.x via the @google-cloud/vertexai 1.12.0 bump,
  which uses dynamic ESM imports Jest 29 cannot load without
  --experimental-vm-modules. Pass that flag in the Vertex JS test step.

Adds tests/test_litellm/proxy/hooks/test_proxy_hooks_init.py as a
regression guard: managed_files / managed_vector_stores must register,
and isolation.py must not transitively import litellm.proxy.utils.

* [Fix] Proxy: Address Greptile feedback on hook-cycle PR

- Move _user_has_admin_view to litellm.proxy._types as
  user_api_key_has_admin_view (single source of truth). common_utils.py
  and isolation.py both import from there now, removing the duplicated
  role-check that could silently diverge if new admin roles are added.
- Add pytest.importorskip("litellm_enterprise") to the two regression
  tests that assert managed_files / managed_vector_stores are registered;
  those keys come from ENTERPRISE_PROXY_HOOKS so the tests would fail
  unconditionally in a checkout without the enterprise extra installed.

* [Fix] Lint: Mark _user_has_admin_view re-export in common_utils

Ruff F401 flagged the aliased import as unused within common_utils.py
because the name is consumed only by external modules (~15 callers
across guardrails, spend tracking, MCP, agents, management endpoints).
Add `# noqa: F401  re-exported` so the alias survives lint while
keeping a single source of truth in litellm.proxy._types.

* refactor(azure): move image gen JSON helper; rename image edit finalize hook

- Add image_generation/http_utils.azure_deployment_image_generation_json_body; call
  from azure.py (keeps AzureChatCompletion focused on chat).
- Rename finalize_image_edit_multipart_data to finalize_image_edit_request_data with
  docstring covering multipart and JSON POST payloads (review feedback).

Co-authored-by: Cursor <cursoragent@cursor.com>

* test(proxy): cover health_check_reasoning_effort for completion mode

Co-authored-by: Cursor <cursoragent@cursor.com>

* [Fix] Tests: Use master key for /otel-spans in test_chat_completion_check_otel_spans

/otel-spans now requires proxy admin (returns 401 'Only proxy admin
can be used to generate, delete, update info for new keys/users/teams.
Route=/otel-spans' for non-admin callers). Switch the GET call to use
the master key sk-1234 while keeping the generated key for the
chat-completion request that produces the spans.

* [Fix] Tests: Pick chat-completion OTEL trace by content, not recency

The /otel-spans endpoint returns process-wide spans and tags
most_recent_parent by max start_time. After tightening that route to
proxy_admin (sk-1234), the GET /otel-spans request itself emits auth
spans that beat the chat-completion spans on start_time, so
most_recent_parent now points at the request's own auth trace
(['postgres', 'postgres']) and the >=5-span assertion fails.

Pick the chat-completion trace by content: it is the only trace whose
span list is a superset of {postgres, redis, raw_gen_ai_request,
batch_write_to_db}. Verified locally end-to-end against
otel_test_config.yaml + OTEL_EXPORTER=in_memory: 3/3 runs green.

* [Fix] CI: Enable VCR replay for test_azure_o_series

The Azure o-series tests were excluded from the conftest's VCR auto-marker
because of a respx/vcrpy transport-patching conflict, but the only respx
reference in the file was an unused `MockRouter` import. Drop the dead
import and remove the file from the conflict set so cassettes record on
first run and replay thereafter, eliminating the 60-95s live Azure latency
that was crashing xdist workers under --timeout=120 thread-mode timeouts.

* [Fix] Tests: Restore /metrics access for prometheus test suite

/metrics now requires auth by default; tests/otel_tests/test_prometheus.py
makes 4+ unauthenticated GETs against http://0.0.0.0:4000/metrics, so
every prometheus test in CI now fails the metric assertion.

Set require_auth_for_metrics_endpoint: false in otel_test_config.yaml
to opt out for this test job, which scrapes /metrics directly. Verified
locally: 8/8 prometheus tests green (one flaky retry on
test_proxy_success_metrics that pre-dates this PR).

Also drop the -x stop-on-first-failure flag from the otel test command
so all failures in the job surface in a single CI run rather than
hiding behind whichever one trips first.

* [Perf] CI: Skip Redundant Playwright Apt Install in E2E UI Job

The cimg/python:3.12-browsers base image already ships every Chromium
system dependency Playwright needs (libnss3, libatk-bridge2.0-0,
libcups2, etc. — the install log shows them all as "already the newest
version"). Passing --with-deps to `npx playwright install` therefore
runs an apt-get update + install for nothing, but pays the full cost of
hitting Ubuntu mirrors. On a recent run those mirrors stalled hard:
apt-get update alone took 6m53s at 81.5 kB/s with several archives
returning connection refused.

Drop --with-deps and persist ~/.cache/ms-playwright alongside
node_modules so the Chromium binary is also reused across runs. Bump
the cache key to v2 so the existing v1 entry (which only contained
node_modules) is not loaded and skipped over the new browser path.

* [Fix] Docker: Remove Hardcoded Prisma Binary Target For Multi-Arch Builds

PRISMA_CLI_BINARY_TARGETS="debian-openssl-3.0.x" was hardcoded in
docker/Dockerfile.non_root by #17695. On a buildx linux/arm64 leg this
forces prisma to download the amd64 schema-engine into an arm64 image,
so 'prisma migrate deploy' fails at startup with 'Could not find
schema-engine binary'.

Removing the env lets prisma auto-detect per build platform: amd64
builds still resolve to debian-openssl-3.0.x (Wolfi falls back to
debian, same binary as before), and arm64 builds now correctly fetch
linux-arm64-openssl-3.0.x. The offline-cache pre-warm goal of #17695 is
preserved — only which binaries fill the cache changes.

Fixes #19458

* [Fix] UI: Clear Admin Session Cookies Before Establishing Invited User's Session (#27227)

The invite-signup form was writing the new user's token via raw
`document.cookie` at `path=/`, while the rest of the auth surface uses
`storeLoginToken` (which writes at `path=/ui` and mirrors to
sessionStorage). After signup the inviter's `path=/ui` cookie kept
winning path-specificity matching, and sessionStorage still held the
inviter's token, so the dashboard rendered as the inviter rather than
the newly created user.

Treat invite signup as a principal-change boundary — clear prior
session cookies first, then store the new token via the canonical
helper.

* test: add 24hr Redis-backed VCR cache to additional test suites (#27159)

* test: add 24hr Redis-backed VCR cache to additional test suites

Extracts the existing llm_translation VCR plumbing into a reusable helper
(tests/_vcr_conftest_common.py) and wires it into the conftest.py files
of the test directories listed in LIT-2787:

  audio_tests, batches_tests, guardrails_tests, image_gen_tests,
  litellm_utils_tests, local_testing, logging_callback_tests,
  pass_through_unit_tests, router_unit_tests, unified_google_tests

The same helper is also adopted by the pre-existing llm_translation and
llm_responses_api_testing conftests to remove the copy-pasted VCR setup.

Each consuming conftest:
- registers the Redis persister via pytest_recording_configure
- auto-marks collected tests with pytest.mark.vcr (skipping respx-using
  files where applicable, since respx and vcrpy both patch httpx)
- gates cassette writes on test success via _vcr_outcome_gate

The cache is opt-in via CASSETTE_REDIS_URL; when unset, VCR is disabled
and tests hit live providers as before. LITELLM_VCR_DISABLE=1 still
forces a bypass for ad-hoc local runs.

Test directories that run LiteLLM proxy in Docker (build_and_test,
proxy_logging_guardrails_model_info_tests, proxy_store_model_in_db_tests)
are intentionally not included: VCR.py patches the in-process httpx
transport and cannot intercept calls made from inside a Docker container.
The installing_litellm_on_python* jobs make no LLM calls and don't
benefit from caching.

https://linear.app/litellm-ai/issue/LIT-2787/add-24hr-caching-to-additional-test-suites

* test(vcr): add safe-body matcher to handle JSONL and binary request bodies

vcrpy's stock body matcher inspects Content-Type and unconditionally
runs json.loads on application/json bodies. JSON Lines payloads (used
by the Bedrock batch S3 PUT and other upload paths) crash that with
json.JSONDecodeError: Extra data, before the matcher can return
'not a match'.

This was the root cause of the batches_testing CI job failing on
test_async_create_file once VCR auto-marking was applied to the
batches_tests directory.

Add a conservative byte-equality body matcher and use it in place of
'body' in the shared match_on tuple. The matcher is strictly more
conservative than vcrpy's default — the only thing it gives up is
'different JSON key order is treated as the same body', which doesn't
apply to deterministic litellm-built request payloads. It can never
produce a false positive that the default would have rejected, so
there is no cross-contamination risk.

Co-authored-by: Mateo Wang <mateo-berri@users.noreply.github.com>

* test(vcr): exclude tests that VCR replay actively breaks

A few tests are incompatible with cassette replay and were failing on
the latest CI run after VCR auto-marking was extended to local_testing
and logging_callback_tests:

- test_amazing_s3_logs.py (logging_callback_tests): the test asserts on
  a per-run response_id that should round-trip through a real S3
  PUT/LIST. vcrpy's boto3 stub intercepts the PUT and the LIST replays
  stale keys, so the freshly-generated id is never found.
- test_async_embedding_azure (logging_callback_tests) and
  test_amazing_sync_embedding (local_testing): the failure branches
  deliberately pass api_key='my-bad-key' to assert that the failure
  callback fires. We scrub auth headers from cassettes (so the bad-key
  request matches the prior good-key request), and vcrpy replays the
  recorded 200 — the failure callback never fires.
- test_assistants.py (local_testing): the OpenAI Assistants polling
  APIs mint fresh thread/run IDs every recording session and then poll
  until status=='completed'. Replays of those polled GETs can never
  match a freshly-generated run id, so every CI run effectively
  re-records and the suite blows past the 15m no_output_timeout.

Skip these from VCR auto-marking so they continue to hit live providers
as they did before this change. The remaining tests in each directory
still get cached.

Co-authored-by: Mateo Wang <mateo-berri@users.noreply.github.com>

* test(vcr): expand skip lists for second batch of incompatible tests

Followup to the previous commit. After re-running CI on the rebuilt
branch, three more tests surfaced as VCR-replay-incompatible:

- litellm_utils_testing :: test_get_valid_models_from_dynamic_api_key
  Calls GET /v1/models with api_key='123' to assert the result is empty.
  We scrub auth headers, so the bad-key request matches the prior
  good-key cassette and replays the recorded model list.
- litellm_utils_testing :: test_litellm_overhead.py
  Measures litellm_overhead_time_ms as a percentage of total wall-clock
  time. With cached responses the upstream 'network' time collapses to
  microseconds, blowing past the 40%% threshold the test asserts on.
  Skip the whole file (every parametrization is at risk).
- local_testing_part1 :: test_async_custom_handler_completion and
  test_async_custom_handler_embedding
  Same bad-key failure-callback pattern as the already-skipped
  test_amazing_sync_embedding.
- litellm_router_testing :: test_router_caching.py
  Asserts on litellm's own router-level response cache by comparing
  response1.id to response2.id across repeat upstream calls (test
  bypasses litellm cache via ttl=0 and expects upstream to return a
  *new* id). With VCR replay both upstream calls return the same
  cassette body, so the ids are identical. Skip the whole file.
- logging_callback_tests :: test_async_chat_azure (preemptive)
  Same shape as already-skipped test_async_embedding_azure; was masked
  by upstream OpenAI rate-limit failures on baseline.

Co-authored-by: Mateo Wang <mateo-berri@users.noreply.github.com>

* test(vcr): use item.path and tighten matcher docstring

- Replace pytest's deprecated item.fspath with item.path in
  apply_vcr_auto_marker_to_items so we don't emit deprecation
  warnings under pytest 8.
- Clarify _safe_body_matcher docstring to reflect actual behavior
  (direct == first, then UTF-8 bytes comparison, no repr fallback).

Addresses Greptile review feedback on PR #27159.

* test(vcr): swallow all RedisError on cassette save/load

Cassette persistence is strictly best-effort: any Redis-side failure
(connection blip, timeout, OutOfMemoryError when the maxmemory cap is
hit, READONLY replicas, etc.) should degrade to 'test passed but
cassette not cached' rather than fail the test on teardown.

Previously the persister only caught ConnectionError and TimeoutError,
so OutOfMemoryError — which Redis Cloud raises when the cassette cache
hits its memory cap and there are no evictable keys — propagated out of
vcrpy's autouse fixture and ERRORed otherwise-passing tests on
teardown. This caused the litellm_utils_testing CircleCI job to fail on
the latest commit's run, even though the underlying test was a unit
test that used mock_response and produced no real upstream traffic
(the cassette was dirtied by a background langfuse callback). The
rerun only succeeded because Redis evictions happened to free enough
room before the SET — i.e. it was timing-dependent flakiness.

Catch redis.exceptions.RedisError (the common base of all server- and
client-side Redis exceptions) on both save and load, and parametrize
the regression tests across ConnectionError, TimeoutError, and
OutOfMemoryError to pin the new behavior.

* test(vcr): surface cassette-cache failures with warnings + session banner

When the persister silently swallows a Redis OOM (or any RedisError) on
save/load there is otherwise no visible signal that the cache is
degraded — tests pass, the cassette just isn't persisted, and the next
session still hits the same Redis at the same near-cap memory.

Add three layers of observability so that failure mode is loud:

1. Per-process health counters ("save_failures", "load_failures", and
   the last error string for each), exposed via cassette_cache_health()
   and reset via reset_cassette_cache_health(). The persister
   increments these in addition to logging.

2. VCRCassetteCacheWarning (UserWarning subclass) emitted via
   warnings.warn() inside the persister's except block. Pytest's
   built-in warnings summary at session end automatically lists every
   such warning, so the failure is visible in CI logs without any
   conftest-level wiring.

3. Session-end banner via emit_cassette_cache_session_banner() and a
   stderr-fallback atexit handler registered from
   register_persister_if_enabled(). Two states:
     - red "VCR CASSETTE CACHE DEGRADED" when save_failures or
       load_failures > 0
     - yellow "VCR CASSETTE CACHE NEAR CAPACITY" (no failures, but
       used_memory >= 85% of maxmemory) so the next session knows
       the Redis is approaching OOM before any SET actually fails

Capacity comes from a best-effort INFO memory probe
(cassette_cache_capacity_snapshot) that returns None on any failure or
when maxmemory is uncapped. The atexit handler skips xdist workers so
only the controller emits.

Tests: parametrize the existing save/load swallow-error tests across
ConnectionError/TimeoutError/OutOfMemoryError, add direct tests for
the health counters and warning emission, and a new
test_vcr_conftest_common_banner.py covering banner output for every
state (silent/red/yellow/disabled/xdist-worker).

* test(vcr): bucket cassettes by API key fingerprint, drop bad-key skips

Tests that deliberately call an LLM API with a bad key (e.g. to assert
that the failure callback fires, or that check_valid_key returns False)
were being silently served the prior good-key cassette: we scrub the
real Authorization / x-api-key header from the cassette before storing
it, so a follow-up bad-key call is byte-identical to the good-key call
under the existing match_on tuple.

Add a 'key_fingerprint' custom matcher that distinguishes requests by
the SHA-256 of their API-key headers. The fingerprint is stamped into
a synthetic 'x-litellm-key-fp' header by a new before_record_request
hook, which then strips the real auth headers (we have to do the
scrubbing here instead of via vcrpy's filter_headers knob, because
filter_headers runs *first* and would erase the value we want to hash).

Bad-key requests now get a different cassette bucket than good-key
requests, so vcrpy will not replay a recorded 200 in place of the
expected 401. The fingerprint is a one-way hash of the secret, so
cassettes never contain the key.

This permanently removes the 'bad-key' category of skips:

- tests/local_testing: dropped ::test_amazing_sync_embedding,
  ::test_async_custom_handler_completion,
  ::test_async_custom_handler_embedding
- tests/logging_callback_tests: dropped ::test_async_chat_azure,
  ::test_async_embedding_azure
- tests/litellm_utils_tests: dropped
  ::test_get_valid_models_from_dynamic_api_key

Coverage: 7 new unit tests in tests/test_litellm/test_vcr_safe_body_matcher.py
covering header stripping, fingerprint determinism, no-auth bucketing,
good-vs-bad key discrimination, x-api-key (Anthropic/Azure) discrimination,
and idempotence under replay.

Co-authored-by: Mateo Wang <mateo-berri@users.noreply.github.com>

* test(vcr): drop redundant comments and docstrings

Trim narration of code that is already self-evident from function and
variable names. Keep the two genuinely non-obvious bits:

- ordering constraint between filter_headers and before_record_request,
  which would invite a maintainer to re-introduce the bug if removed
- the per-directory _VCR_INCOMPATIBLE_FILES rationale, since 'why
  exactly is this skipped' is not knowable from the test name alone

Also drop the 40-line commented-out drop-in conftest snippet at the
bottom of _vcr_conftest_common.py — the consuming conftests are the
canonical reference.

Co-authored-by: Mateo Wang <mateo-berri@users.noreply.github.com>

* test(vcr): make _before_record_request idempotent

vcrpy invokes before_record_request more than once per request:
can_play_response_for calls it, then __contains__ /
_responses (reached via play_response) call it again on the
result. The second invocation sees a request whose auth headers we
already stripped, so a naive recompute yields "no-key" and
overwrites the real fingerprint stored in the header.

This makes can_play_response_for and play_response disagree on
matchability — the former says "yes, we have a stored response for
this" (matching no-key to no-key) and the latter throws
UnhandledHTTPRequestError because it computes a fresh real
fingerprint that doesn't match the stored no-key.

In CI this manifested as ~30 failing tests across guardrails_testing,
audio_testing, batches_testing, image_gen_testing, llm_responses_api,
litellm_router_unit_testing, etc. Skip the recompute when the header
is already set, so re-applying the hook is a no-op.

Adds a regression test that fires the hook twice on the same dict and
asserts the fingerprint stays put.

Co-authored-by: Mateo Wang <mateo-berri@users.noreply.github.com>

* test(vcr): drop more redundant docstrings and headers

* test(vcr): enable 24hr cache for ocr_tests and search_tests

These two directories were the only non-dockerized test suites in the
build_and_test workflow that make live LLM/provider API calls but were
not VCR-enabled by this PR. Together they account for 96 tests:

- tests/ocr_tests/ (31): Mistral OCR, Azure AI OCR, Azure Document
  Intelligence, Vertex AI OCR. Pure-unit tests inside the same files
  (e.g. TestAzureDocumentIntelligencePagesParam) make no HTTP calls
  and become benign VCR NOOPs.
- tests/search_tests/ (65): Brave, DataForSEO, DuckDuckGo, Exa,
  Firecrawl, Google PSE, Linkup, Parallel.ai, Perplexity, SearchAPI,
  Searxng, Serper, Tavily.

Both directories use the canonical minimal conftest pattern from
tests/audio_tests/conftest.py with no skip lists. None of the test
files use respx, none assert on per-call upstream non-determinism
(no response1.id != response2.id, no overhead-as-fraction-of-total,
no live polling), so the default match_on tuple should cache cleanly.
If a flake surfaces during the first cassette-recording CI run, we
can add a targeted skip the same way we did for the other dirs.

Co-authored-by: Mateo Wang <mateo-berri@users.noreply.github.com>

---------

Co-authored-by: Claude <noreply@anthropic.com>
Co-authored-by: Cursor Agent <cursoragent@cursor.com>
Co-authored-by: Mateo Wang <mateo-berri@users.noreply.github.com>

* [Fix] Team UI: handle legacy dict shape for metadata.guardrails (#27224)

* [Fix] Team UI: handle legacy dict shape for metadata.guardrails

A team can have metadata.guardrails stored as {"modify_guardrails": bool}
(the permission-flag shape introduced in PR #4810) rather than the
expected string[]. The opt-out logic added in PR #25575 calls .filter()
on this field, which throws TypeError on a dict and crashes the team
detail page.

Add a safeGuardrailsList helper that returns [] when the field is not
an array, and route the three read sites through it.

* [Fix] Team UI: inline Array.isArray guards for guardrails metadata

Replace the safeGuardrailsList helper with inline Array.isArray checks
at each call site, and apply the same guard to opted_out_global_guardrails
for consistency. No known legacy dict rows for opted_out_global_guardrails,
but the unguarded `|| []` pattern is the same shape risk.

Six call sites now defended directly: three for metadata.guardrails
and three for metadata.opted_out_global_guardrails.

* chore: update Next.js build artifacts (2026-05-05 22:45 UTC, node v20.20.2) (#27240)

* [Infra] Bump deps (#27157)

* bump: version 0.4.70 → 0.4.71

* bump: version 0.1.39 → 0.1.40

* uv lock

---------

Co-authored-by: Michael Riad Zaky <michaelr@Mac.localdomain>
Co-authored-by: Mateo Wang <277851410+mateo-berri@users.noreply.github.com>
Co-authored-by: greptile-apps[bot] <165735046+greptile-apps[bot]@users.noreply.github.com>
Co-authored-by: ryan-crabbe-berri <ryan@berri.ai>
Co-authored-by: user <70670632+stuxf@users.noreply.github.com>
Co-authored-by: Cursor Agent <cursoragent@cursor.com>
Co-authored-by: Claude <noreply@anthropic.com>
Co-authored-by: shivam <shivam@berri.ai>
Co-authored-by: Mateo Wang <mateo-berri@users.noreply.github.com>
Co-authored-by: Yassin Kortam <yassin@berri.ai>
Co-authored-by: Krrish Dholakia <krrish+github@berri.ai>
Co-authored-by: shin-berri <shin-laptop@berri.ai>
Co-authored-by: Sameer Kankute <sameer@berri.ai>
Co-authored-by: Sameer Kankute <Sameerlite@users.noreply.github.com>
Co-authored-by: Michael-RZ-Berri <michael@berri.ai>
Co-authored-by: harish-berri <harish@berri.ai>
Co-authored-by: Yassin Kortam <yassinkortam@g.ucla.edu>
Co-authored-by: Michael Riad Zaky <michaelr@Michaels-MacBook-Air.local>
Co-authored-by: Krrish Dholakia <krrish-berri-2@users.noreply.github.com>
2026-05-05 16:15:03 -07:00

6515 lines
235 KiB
Python

import asyncio
import importlib
import json
import os
import socket
import subprocess
import sys
from datetime import datetime, timedelta, timezone
from pathlib import Path
from unittest import mock
from unittest.mock import AsyncMock, MagicMock, mock_open, patch
import click
import httpx
import pytest
import yaml
from fastapi import FastAPI
from fastapi.staticfiles import StaticFiles
from fastapi.testclient import TestClient
sys.path.insert(
0, os.path.abspath("../../..")
) # Adds the parent directory to the system-path
import litellm
from litellm.proxy.auth.user_api_key_auth import user_api_key_auth
from litellm.proxy.proxy_server import app, initialize
from litellm.utils import _invalidate_model_cost_lowercase_map
example_embedding_result = {
"object": "list",
"data": [
{
"object": "embedding",
"index": 0,
"embedding": [
-0.006929283495992422,
-0.005336422007530928,
-4.547132266452536e-05,
-0.024047505110502243,
-0.006929283495992422,
-0.005336422007530928,
-4.547132266452536e-05,
-0.024047505110502243,
-0.006929283495992422,
-0.005336422007530928,
-4.547132266452536e-05,
-0.024047505110502243,
],
}
],
"model": "text-embedding-3-small",
"usage": {"prompt_tokens": 5, "total_tokens": 5},
}
def mock_patch_aembedding():
return mock.patch(
"litellm.proxy.proxy_server.llm_router.aembedding",
return_value=example_embedding_result,
)
@pytest.fixture(scope="function")
def client_no_auth():
# Assuming litellm.proxy.proxy_server is an object
from litellm.proxy.proxy_server import cleanup_router_config_variables
cleanup_router_config_variables()
filepath = os.path.dirname(os.path.abspath(__file__))
config_fp = f"{filepath}/test_configs/test_config_no_auth.yaml"
# initialize can get run in parallel, it sets specific variables for the fast api app, sinc eit gets run in parallel different tests use the wrong variables
asyncio.run(initialize(config=config_fp, debug=True))
return TestClient(app)
def test_login_v2_returns_redirect_url_and_sets_cookie(monkeypatch):
mock_login_result = {"user_id": "test-user"}
mock_prisma_client = MagicMock()
mock_authenticate_user = AsyncMock(return_value=mock_login_result)
mock_create_ui_token_object = MagicMock(return_value={"user_id": "test-user"})
mock_jwt_encode = MagicMock(return_value="signed-token")
monkeypatch.setattr(
"litellm.proxy.auth.login_utils.authenticate_user",
mock_authenticate_user,
)
monkeypatch.setattr(
"litellm.proxy.auth.login_utils.create_ui_token_object",
mock_create_ui_token_object,
)
monkeypatch.setattr("jwt.encode", mock_jwt_encode)
monkeypatch.setattr("litellm.proxy.proxy_server.master_key", "test-master-key")
monkeypatch.setattr("litellm.proxy.proxy_server.general_settings", {})
monkeypatch.setattr("litellm.proxy.proxy_server.premium_user", False)
monkeypatch.setattr("litellm.proxy.proxy_server.prisma_client", mock_prisma_client)
monkeypatch.setattr("litellm.proxy.utils.get_server_root_path", lambda: "")
monkeypatch.setattr("litellm.proxy.utils.get_proxy_base_url", lambda: None)
client = TestClient(app)
response = client.post(
"/v2/login",
json={"username": "alice", "password": "secret"},
)
assert response.status_code == 200
assert response.json() == {
"redirect_url": "http://testserver/ui/?login=success",
"token": "signed-token",
}
assert response.cookies.get("token") == "signed-token"
mock_authenticate_user.assert_awaited_once_with(
username="alice",
password="secret",
master_key="test-master-key",
prisma_client=mock_prisma_client,
)
mock_create_ui_token_object.assert_called_once_with(
login_result=mock_login_result,
general_settings={},
premium_user=False,
)
mock_jwt_encode.assert_called_once_with(
{"user_id": "test-user"},
"test-master-key",
algorithm="HS256",
)
def test_login_v2_returns_json_on_proxy_exception(monkeypatch):
"""Test that /v2/login returns JSON error when ProxyException is raised"""
from litellm.proxy._types import ProxyErrorTypes, ProxyException
mock_prisma_client = MagicMock()
mock_authenticate_user = AsyncMock(
side_effect=ProxyException(
message="Invalid credentials",
type=ProxyErrorTypes.auth_error,
param="password",
code=401,
)
)
monkeypatch.setattr(
"litellm.proxy.auth.login_utils.authenticate_user",
mock_authenticate_user,
)
monkeypatch.setattr("litellm.proxy.proxy_server.master_key", "test-master-key")
monkeypatch.setattr("litellm.proxy.proxy_server.prisma_client", mock_prisma_client)
client = TestClient(app)
response = client.post(
"/v2/login",
json={"username": "alice", "password": "wrong"},
)
assert response.status_code == 401
assert response.headers["content-type"] == "application/json"
data = response.json()
assert "error" in data
assert data["error"]["message"] == "Invalid credentials"
assert data["error"]["type"] == "auth_error"
def test_login_v2_returns_json_on_http_exception(monkeypatch):
"""Test that /v2/login converts HTTPException to JSON error response"""
from fastapi import HTTPException
mock_prisma_client = MagicMock()
mock_authenticate_user = AsyncMock(
side_effect=HTTPException(status_code=401, detail="Unauthorized")
)
monkeypatch.setattr(
"litellm.proxy.auth.login_utils.authenticate_user",
mock_authenticate_user,
)
monkeypatch.setattr("litellm.proxy.proxy_server.master_key", "test-master-key")
monkeypatch.setattr("litellm.proxy.proxy_server.prisma_client", mock_prisma_client)
client = TestClient(app)
response = client.post(
"/v2/login",
json={"username": "alice", "password": "secret"},
)
assert response.status_code == 401
assert response.headers["content-type"] == "application/json"
data = response.json()
assert "error" in data
assert isinstance(data["error"], dict)
def test_login_v2_returns_json_on_unexpected_exception(monkeypatch):
"""Test that /v2/login returns JSON error when unexpected exception occurs"""
mock_prisma_client = MagicMock()
mock_authenticate_user = AsyncMock(side_effect=ValueError("Unexpected error"))
monkeypatch.setattr(
"litellm.proxy.auth.login_utils.authenticate_user",
mock_authenticate_user,
)
monkeypatch.setattr("litellm.proxy.proxy_server.master_key", "test-master-key")
monkeypatch.setattr("litellm.proxy.proxy_server.prisma_client", mock_prisma_client)
client = TestClient(app)
response = client.post(
"/v2/login",
json={"username": "alice", "password": "secret"},
)
assert response.status_code == 500
assert response.headers["content-type"] == "application/json"
data = response.json()
assert "error" in data
assert isinstance(data["error"], dict)
assert "Unexpected error" in data["error"]["message"]
def test_login_v2_returns_json_on_invalid_json_body(monkeypatch):
"""Test that /v2/login returns JSON error when request body is invalid JSON"""
monkeypatch.setattr("litellm.proxy.proxy_server.master_key", "test-master-key")
client = TestClient(app)
response = client.post(
"/v2/login",
content="invalid json",
headers={"Content-Type": "application/json"},
)
assert response.status_code == 500
assert response.headers["content-type"] == "application/json"
data = response.json()
assert "error" in data
assert isinstance(data["error"], dict)
def test_login_v3_rejected_without_control_plane_url(monkeypatch):
"""v3/login returns 404 when control_plane_url is not configured."""
mock_prisma_client = MagicMock()
monkeypatch.setattr("litellm.proxy.proxy_server.master_key", "test-master-key")
monkeypatch.setattr("litellm.proxy.proxy_server.general_settings", {})
monkeypatch.setattr("litellm.proxy.proxy_server.prisma_client", mock_prisma_client)
client = TestClient(app)
response = client.post(
"/v3/login",
json={"username": "alice", "password": "secret"},
)
assert response.status_code == 404
assert "control_plane_url" in response.json()["error"]["message"]
def test_login_v3_returns_code(monkeypatch):
"""v3/login returns an opaque code, not the JWT directly."""
mock_prisma_client = MagicMock()
monkeypatch.setattr(
"litellm.proxy.auth.login_utils.authenticate_user",
AsyncMock(return_value={"user_id": "test-user"}),
)
monkeypatch.setattr(
"litellm.proxy.auth.login_utils.create_ui_token_object",
MagicMock(return_value={"user_id": "test-user"}),
)
monkeypatch.setattr("jwt.encode", MagicMock(return_value="signed-token"))
monkeypatch.setattr("litellm.proxy.proxy_server.master_key", "test-master-key")
monkeypatch.setattr(
"litellm.proxy.proxy_server.general_settings",
{"control_plane_url": "https://cp.example.com"},
)
monkeypatch.setattr("litellm.proxy.proxy_server.premium_user", False)
monkeypatch.setattr("litellm.proxy.proxy_server.prisma_client", mock_prisma_client)
mock_config = MagicMock()
mock_config.worker_registry = []
monkeypatch.setattr("litellm.proxy.proxy_server.proxy_config", mock_config)
monkeypatch.setattr("litellm.proxy.utils.get_server_root_path", lambda: "")
monkeypatch.setattr("litellm.proxy.utils.get_proxy_base_url", lambda: None)
client = TestClient(app)
response = client.post(
"/v3/login",
json={"username": "alice", "password": "secret"},
)
assert response.status_code == 200
data = response.json()
assert "code" in data
assert data["expires_in"] == 60
assert "token" not in data
def test_login_v3_exchange_happy_path(monkeypatch):
"""Full flow: v3/login returns code, v3/login/exchange redeems it for JWT."""
mock_prisma_client = MagicMock()
monkeypatch.setattr(
"litellm.proxy.auth.login_utils.authenticate_user",
AsyncMock(return_value={"user_id": "test-user"}),
)
monkeypatch.setattr(
"litellm.proxy.auth.login_utils.create_ui_token_object",
MagicMock(return_value={"user_id": "test-user"}),
)
monkeypatch.setattr("jwt.encode", MagicMock(return_value="signed-token"))
monkeypatch.setattr("litellm.proxy.proxy_server.master_key", "test-master-key")
monkeypatch.setattr(
"litellm.proxy.proxy_server.general_settings",
{"control_plane_url": "https://cp.example.com"},
)
monkeypatch.setattr("litellm.proxy.proxy_server.premium_user", False)
monkeypatch.setattr("litellm.proxy.proxy_server.prisma_client", mock_prisma_client)
mock_config = MagicMock()
mock_config.worker_registry = []
monkeypatch.setattr("litellm.proxy.proxy_server.proxy_config", mock_config)
monkeypatch.setattr("litellm.proxy.utils.get_server_root_path", lambda: "")
monkeypatch.setattr("litellm.proxy.utils.get_proxy_base_url", lambda: None)
client = TestClient(app)
# Step 1: login — get code
login_response = client.post(
"/v3/login",
json={"username": "alice", "password": "secret"},
)
assert login_response.status_code == 200
code = login_response.json()["code"]
# Step 2: exchange — get JWT
exchange_response = client.post(
"/v3/login/exchange",
json={"code": code},
)
assert exchange_response.status_code == 200
exchange_data = exchange_response.json()
assert exchange_data["token"] == "signed-token"
assert "redirect_url" in exchange_data
assert exchange_response.cookies.get("token") == "signed-token"
def test_login_v3_exchange_single_use(monkeypatch):
"""Code can only be redeemed once."""
mock_prisma_client = MagicMock()
monkeypatch.setattr(
"litellm.proxy.auth.login_utils.authenticate_user",
AsyncMock(return_value={"user_id": "test-user"}),
)
monkeypatch.setattr(
"litellm.proxy.auth.login_utils.create_ui_token_object",
MagicMock(return_value={"user_id": "test-user"}),
)
monkeypatch.setattr("jwt.encode", MagicMock(return_value="signed-token"))
monkeypatch.setattr("litellm.proxy.proxy_server.master_key", "test-master-key")
monkeypatch.setattr(
"litellm.proxy.proxy_server.general_settings",
{"control_plane_url": "https://cp.example.com"},
)
monkeypatch.setattr("litellm.proxy.proxy_server.premium_user", False)
monkeypatch.setattr("litellm.proxy.proxy_server.prisma_client", mock_prisma_client)
mock_config = MagicMock()
mock_config.worker_registry = []
monkeypatch.setattr("litellm.proxy.proxy_server.proxy_config", mock_config)
monkeypatch.setattr("litellm.proxy.utils.get_server_root_path", lambda: "")
monkeypatch.setattr("litellm.proxy.utils.get_proxy_base_url", lambda: None)
client = TestClient(app)
login_response = client.post(
"/v3/login",
json={"username": "alice", "password": "secret"},
)
code = login_response.json()["code"]
# First exchange succeeds
first = client.post("/v3/login/exchange", json={"code": code})
assert first.status_code == 200
# Second exchange fails
second = client.post("/v3/login/exchange", json={"code": code})
assert second.status_code == 401
def test_login_v3_exchange_invalid_code(monkeypatch):
"""Random code returns 401."""
monkeypatch.setattr(
"litellm.proxy.proxy_server.general_settings",
{"control_plane_url": "https://cp.example.com"},
)
client = TestClient(app)
response = client.post(
"/v3/login/exchange",
json={"code": "nonexistent-code"},
)
assert response.status_code == 401
def test_login_v3_exchange_rejected_without_control_plane_url(monkeypatch):
"""v3/login/exchange returns 404 when control_plane_url is not configured."""
monkeypatch.setattr("litellm.proxy.proxy_server.general_settings", {})
client = TestClient(app)
response = client.post(
"/v3/login/exchange",
json={"code": "some-code"},
)
assert response.status_code == 404
assert "control_plane_url" in response.json()["error"]["message"]
def test_login_v3_returns_json_on_proxy_exception(monkeypatch):
"""Test that /v3/login returns JSON error when ProxyException is raised"""
from litellm.proxy._types import ProxyErrorTypes, ProxyException
mock_prisma_client = MagicMock()
mock_authenticate_user = AsyncMock(
side_effect=ProxyException(
message="Invalid credentials",
type=ProxyErrorTypes.auth_error,
param="password",
code=401,
)
)
monkeypatch.setattr(
"litellm.proxy.auth.login_utils.authenticate_user",
mock_authenticate_user,
)
monkeypatch.setattr("litellm.proxy.proxy_server.master_key", "test-master-key")
monkeypatch.setattr(
"litellm.proxy.proxy_server.general_settings",
{"control_plane_url": "https://cp.example.com"},
)
monkeypatch.setattr("litellm.proxy.proxy_server.prisma_client", mock_prisma_client)
client = TestClient(app)
response = client.post(
"/v3/login",
json={"username": "alice", "password": "wrong"},
)
assert response.status_code == 401
assert response.headers["content-type"] == "application/json"
data = response.json()
assert "error" in data
assert data["error"]["message"] == "Invalid credentials"
assert data["error"]["type"] == "auth_error"
def test_fallback_login_has_no_deprecation_banner(client_no_auth):
response = client_no_auth.get("/fallback/login")
assert response.status_code == 200
html = response.text
assert '<div class="deprecation-banner">' not in html
assert "Deprecated:" not in html
assert "<form" in html
@pytest.mark.parametrize(
"ui_logo_path",
[
"/etc/litellm/secret-config.json",
"/var/secrets/admin.key",
"/proc/self/environ",
"relative/path/logo.png",
],
)
def test_get_logo_url_does_not_disclose_local_paths(
client_no_auth, monkeypatch, ui_logo_path
):
# ``/get_logo_url`` is unauthenticated. Returning a local filesystem
# path verbatim discloses admin-only config to any caller. Only
# browser-loadable HTTP(S) URLs should be returned; for local paths
# the dashboard falls back to ``/get_image``.
monkeypatch.setenv("UI_LOGO_PATH", ui_logo_path)
response = client_no_auth.get("/get_logo_url")
assert response.status_code == 200
assert response.json() == {"logo_url": ""}
def test_get_logo_url_returns_https_url(client_no_auth, monkeypatch):
monkeypatch.setenv("UI_LOGO_PATH", "https://cdn.public.example/logo.png")
response = client_no_auth.get("/get_logo_url")
assert response.status_code == 200
assert response.json() == {"logo_url": "https://cdn.public.example/logo.png"}
def test_get_logo_url_returns_http_url(client_no_auth, monkeypatch):
# HTTP URLs (typically internal CDN) are still returned — those are
# intended to be loaded directly by the browser.
monkeypatch.setenv("UI_LOGO_PATH", "http://internal-cdn.corp:8080/logo.png")
response = client_no_auth.get("/get_logo_url")
assert response.status_code == 200
assert response.json() == {"logo_url": "http://internal-cdn.corp:8080/logo.png"}
def test_get_logo_url_returns_empty_when_unset(client_no_auth, monkeypatch):
monkeypatch.delenv("UI_LOGO_PATH", raising=False)
response = client_no_auth.get("/get_logo_url")
assert response.status_code == 200
assert response.json() == {"logo_url": ""}
def test_sso_key_generate_shows_deprecation_banner(client_no_auth, monkeypatch):
# Ensure the route returns the HTML form instead of redirecting
monkeypatch.setattr(
"litellm.proxy.management_endpoints.ui_sso.show_missing_vars_in_env",
lambda: None,
)
monkeypatch.setattr(
"litellm.proxy.management_endpoints.ui_sso.SSOAuthenticationHandler.get_redirect_url_for_sso",
lambda *args, **kwargs: "http://test/redirect",
)
monkeypatch.setattr(
"litellm.proxy.management_endpoints.ui_sso.SSOAuthenticationHandler._get_cli_state",
lambda *args, **kwargs: None,
)
monkeypatch.setattr(
"litellm.proxy.management_endpoints.ui_sso.SSOAuthenticationHandler.should_use_sso_handler",
lambda *args, **kwargs: False,
)
# Mock premium_user to bypass enterprise check (prevents 403 Forbidden)
monkeypatch.setattr(
"litellm.proxy.proxy_server.premium_user",
True,
)
monkeypatch.setenv("UI_USERNAME", "admin")
response = client_no_auth.get("/sso/key/generate")
assert response.status_code == 200
html = response.text
assert '<div class="deprecation-banner">' in html
assert "Deprecated:" in html
def test_restructure_ui_html_files_handles_nested_routes(tmp_path):
"""
Test that _restructure_ui_html_files correctly restructures HTML files.
Note: This function is always called now, both in development and non-root Docker environments.
"""
from litellm.proxy import proxy_server
ui_root = tmp_path / "ui"
ui_root.mkdir()
def write_file(path: Path, content: str) -> None:
path.parent.mkdir(parents=True, exist_ok=True)
path.write_text(content)
write_file(ui_root / "home.html", "home")
write_file(ui_root / "mcp" / "oauth" / "callback.html", "callback")
write_file(ui_root / "existing" / "index.html", "keep")
write_file(ui_root / "_next" / "ignore.html", "asset")
write_file(ui_root / "litellm-asset-prefix" / "ignore.html", "asset")
proxy_server._restructure_ui_html_files(str(ui_root))
assert not (ui_root / "home.html").exists()
assert (ui_root / "home" / "index.html").read_text() == "home"
assert not (ui_root / "mcp" / "oauth" / "callback.html").exists()
assert (
ui_root / "mcp" / "oauth" / "callback" / "index.html"
).read_text() == "callback"
assert (ui_root / "existing" / "index.html").read_text() == "keep"
assert (ui_root / "_next" / "ignore.html").read_text() == "asset"
assert (ui_root / "litellm-asset-prefix" / "ignore.html").read_text() == "asset"
def test_ui_extensionless_route_requires_restructure(tmp_path):
"""
Regression for non-root fallback: /ui/login expects login/index.html.
Note: Restructuring always happens now, both in development and non-root Docker environments.
"""
from litellm.proxy import proxy_server
ui_root = tmp_path / "ui"
ui_root.mkdir()
(ui_root / "index.html").write_text("index")
(ui_root / "login.html").write_text("login")
fastapi_app = FastAPI()
fastapi_app.mount("/ui", StaticFiles(directory=str(ui_root), html=True), name="ui")
client = TestClient(fastapi_app)
assert client.get("/ui/login.html").status_code == 200
assert client.get("/ui/login").status_code == 404
proxy_server._restructure_ui_html_files(str(ui_root))
response = client.get("/ui/login")
assert response.status_code == 200
assert "login" in response.text
def test_restructure_always_happens(monkeypatch):
"""
Test that restructuring logic always executes regardless of LITELLM_NON_ROOT setting.
In development (is_non_root=False), restructuring happens directly in _experimental/out.
In non-root Docker (is_non_root=True), restructuring happens in /var/lib/litellm/ui.
"""
# Test Case 1: is_non_root is True - restructuring happens in /var/lib/litellm/ui
monkeypatch.setenv("LITELLM_NON_ROOT", "true")
runtime_ui_path = "/var/lib/litellm/ui"
packaged_ui_path = "/some/packaged/ui/path"
# Simulate the logic from proxy_server.py
is_non_root = os.getenv("LITELLM_NON_ROOT", "").lower() == "true"
if is_non_root:
ui_path = runtime_ui_path
else:
ui_path = packaged_ui_path
# Restructuring always happens now, regardless of ui_path vs packaged_ui_path
should_restructure = True
assert is_non_root is True
assert should_restructure is True
assert ui_path == runtime_ui_path
# Test Case 2: is_non_root is False - restructuring happens directly in packaged_ui_path
monkeypatch.delenv("LITELLM_NON_ROOT", raising=False)
# Simulate the logic from proxy_server.py
is_non_root = os.getenv("LITELLM_NON_ROOT", "").lower() == "true"
if is_non_root:
ui_path = runtime_ui_path
else:
ui_path = packaged_ui_path
# Restructuring always happens now, even when ui_path == packaged_ui_path
should_restructure = True
assert is_non_root is False
assert should_restructure is True
assert ui_path == packaged_ui_path
@pytest.mark.asyncio
async def test_initialize_scheduled_jobs_credentials(monkeypatch):
"""
Test that get_credentials is only called when store_model_in_db is True
"""
monkeypatch.delenv("DISABLE_PRISMA_SCHEMA_UPDATE", raising=False)
monkeypatch.delenv("STORE_MODEL_IN_DB", raising=False)
from litellm.proxy.proxy_server import ProxyStartupEvent
from litellm.proxy.utils import ProxyLogging
# Mock dependencies
mock_prisma_client = MagicMock()
mock_proxy_logging = MagicMock(spec=ProxyLogging)
mock_proxy_logging.slack_alerting_instance = MagicMock()
mock_proxy_config = AsyncMock()
with (
patch("litellm.proxy.proxy_server.proxy_config", mock_proxy_config),
patch("litellm.proxy.proxy_server.store_model_in_db", False),
): # set store_model_in_db to False
# Test when store_model_in_db is False
await ProxyStartupEvent.initialize_scheduled_background_jobs(
general_settings={},
prisma_client=mock_prisma_client,
proxy_budget_rescheduler_min_time=1,
proxy_budget_rescheduler_max_time=2,
proxy_batch_write_at=5,
proxy_logging_obj=mock_proxy_logging,
)
# Verify get_credentials was not called
mock_proxy_config.get_credentials.assert_not_called()
# Now test with store_model_in_db = True
with (
patch("litellm.proxy.proxy_server.proxy_config", mock_proxy_config),
patch("litellm.proxy.proxy_server.store_model_in_db", True),
patch("litellm.proxy.proxy_server.get_secret_bool", return_value=True),
):
await ProxyStartupEvent.initialize_scheduled_background_jobs(
general_settings={},
prisma_client=mock_prisma_client,
proxy_budget_rescheduler_min_time=1,
proxy_budget_rescheduler_max_time=2,
proxy_batch_write_at=5,
proxy_logging_obj=mock_proxy_logging,
)
# Verify get_credentials was called both directly and scheduled
assert mock_proxy_config.get_credentials.call_count == 1 # Direct call
# Verify a scheduled job was added for get_credentials
mock_scheduler_calls = [
call[0] for call in mock_proxy_config.get_credentials.mock_calls
]
assert len(mock_scheduler_calls) > 0
def test_update_config_fields_deep_merge_db_wins():
from litellm.proxy.proxy_server import ProxyConfig
proxy_config = ProxyConfig()
current_config = {
"router_settings": {
"routing_mode": "cost_optimized",
"model_group_alias": {
# Existing alias with older model + different hidden flag
"claude-sonnet-4": {
"model": "claude-sonnet-4-20240219",
"hidden": True,
},
# An extra alias that should remain untouched unless DB overrides it
"legacy-sonnet": {
"model": "claude-2.1",
"hidden": True,
},
},
}
}
db_param_value = {
"model_group_alias": {
# Conflict: DB should win (both 'model' and 'hidden')
"claude-sonnet-4": {
"model": "claude-sonnet-4-20250514",
"hidden": False,
},
# New alias to be added by the merge
"claude-sonnet-latest": {
"model": "claude-sonnet-4-20250514",
"hidden": True,
},
# Demonstrate that None values from DB are skipped (preserve existing)
"legacy-sonnet": {"hidden": None}, # should not clobber current True
}
}
updated = proxy_config._update_config_fields(
current_config=current_config,
param_name="router_settings",
db_param_value=db_param_value,
)
rs = updated["router_settings"]
aliases = rs["model_group_alias"]
# DB wins on conflicts (deep) for existing alias
assert aliases["claude-sonnet-4"]["model"] == "claude-sonnet-4-20250514"
assert aliases["claude-sonnet-4"]["hidden"] is False
# New alias introduced by DB is present with its values
assert "claude-sonnet-latest" in aliases
assert aliases["claude-sonnet-latest"]["model"] == "claude-sonnet-4-20250514"
assert aliases["claude-sonnet-latest"]["hidden"] is True
# None in DB does not overwrite existing values
assert aliases["legacy-sonnet"]["model"] == "claude-2.1"
assert aliases["legacy-sonnet"]["hidden"] is True
# Unrelated router_settings keys are preserved
assert rs["routing_mode"] == "cost_optimized"
def test_get_config_custom_callback_api_env_vars(monkeypatch):
"""
Ensure /get/config/callbacks returns custom callback env vars when both custom values are provided.
"""
from litellm.proxy.proxy_server import app, proxy_config, user_api_key_auth
# Mock config with custom_callback_api enabled and generic logger env vars present
config_data = {
"litellm_settings": {"success_callback": ["custom_callback_api"]},
"general_settings": {},
"environment_variables": {
"GENERIC_LOGGER_ENDPOINT": "https://callback.example.com",
"GENERIC_LOGGER_HEADERS": "Auth: token",
},
}
# Mock proxy_config.get_config and router settings
mock_router = MagicMock()
mock_router.get_settings.return_value = {}
monkeypatch.setattr("litellm.proxy.proxy_server.llm_router", mock_router)
monkeypatch.setattr(proxy_config, "get_config", AsyncMock(return_value=config_data))
# Bypass auth dependency
original_overrides = app.dependency_overrides.copy()
app.dependency_overrides[user_api_key_auth] = lambda: MagicMock()
client = TestClient(app)
try:
response = client.get("/get/config/callbacks")
finally:
app.dependency_overrides = original_overrides
assert response.status_code == 200
callbacks = response.json()["callbacks"]
custom_cb = next(
(cb for cb in callbacks if cb["name"] == "custom_callback_api"), None
)
assert custom_cb is not None
assert custom_cb["variables"] == {
"GENERIC_LOGGER_ENDPOINT": "https://callback.example.com",
"GENERIC_LOGGER_HEADERS": "Auth: token",
}
# Mock Prisma
class MockPrisma:
def __init__(self, database_url=None, proxy_logging_obj=None, http_client=None):
self.database_url = database_url
self.proxy_logging_obj = proxy_logging_obj
self.http_client = http_client
async def connect(self):
pass
async def disconnect(self):
pass
mock_prisma = MockPrisma()
@patch(
"litellm.proxy.proxy_server.ProxyStartupEvent._setup_prisma_client",
return_value=mock_prisma,
)
@pytest.mark.asyncio
async def test_aaaproxy_startup_master_key(mock_prisma, monkeypatch, tmp_path):
"""
Test that master_key is correctly loaded from either config.yaml or environment variables
"""
import yaml
from fastapi import FastAPI
# Import happens here - this is when the module probably reads the config path
from litellm.proxy.proxy_server import proxy_startup_event
# Mock the Prisma import
monkeypatch.setattr("litellm.proxy.proxy_server.PrismaClient", MockPrisma)
# Create test app
app = FastAPI()
# Test Case 1: Master key from config.yaml
test_master_key = "sk-12345"
test_config = {"general_settings": {"master_key": test_master_key}}
# Create a temporary config file
config_path = tmp_path / "config.yaml"
with open(config_path, "w") as f:
yaml.dump(test_config, f)
print(f"SET ENV VARIABLE - CONFIG_FILE_PATH, str(config_path): {str(config_path)}")
# Second setting of CONFIG_FILE_PATH to a different value
monkeypatch.setenv("CONFIG_FILE_PATH", str(config_path))
print(f"config_path: {config_path}")
print(f"os.getenv('CONFIG_FILE_PATH'): {os.getenv('CONFIG_FILE_PATH')}")
async with proxy_startup_event(app):
from litellm.proxy.proxy_server import master_key
assert master_key == test_master_key
# Test Case 2: Master key from environment variable
test_env_master_key = "sk-test-67890"
# Create empty config
empty_config = {"general_settings": {}}
with open(config_path, "w") as f:
yaml.dump(empty_config, f)
monkeypatch.setenv("LITELLM_MASTER_KEY", test_env_master_key)
print("test_env_master_key: {}".format(test_env_master_key))
async with proxy_startup_event(app):
from litellm.proxy.proxy_server import master_key
assert master_key == test_env_master_key
# Test Case 3: Master key with os.environ prefix
test_resolved_key = "sk-resolved-key"
test_config_with_prefix = {
"general_settings": {"master_key": "os.environ/CUSTOM_MASTER_KEY"}
}
# Create config with os.environ prefix
with open(config_path, "w") as f:
yaml.dump(test_config_with_prefix, f)
monkeypatch.setenv("CUSTOM_MASTER_KEY", test_resolved_key)
async with proxy_startup_event(app):
from litellm.proxy.proxy_server import master_key
assert master_key == test_resolved_key
def test_team_info_masking():
"""
Test that sensitive team information is properly masked
Ref: https://huntr.com/bounties/661b388a-44d8-4ad5-862b-4dc5b80be30a
"""
from litellm.proxy.proxy_server import ProxyConfig
proxy_config = ProxyConfig()
# Test team object with sensitive data
team1_info = {
"success_callback": "['langfuse', 's3']",
"langfuse_secret": "secret-test-key",
"langfuse_public_key": "public-test-key",
}
with pytest.raises(Exception) as exc_info:
proxy_config._get_team_config(
team_id="test_dev",
all_teams_config=[team1_info],
)
print("Got exception: {}".format(exc_info.value))
assert "secret-test-key" not in str(exc_info.value)
assert "public-test-key" not in str(exc_info.value)
def test_embedding_input_array_of_tokens(client_no_auth):
"""
Test to bypass decoding input as array of tokens for selected providers
Ref: https://github.com/BerriAI/litellm/issues/10113
"""
from litellm.proxy import proxy_server
# The client_no_auth fixture should initialize the router
# Assert this to catch any router initialization regressions
assert proxy_server.llm_router is not None, (
"llm_router is None after client_no_auth fixture initialized. "
"This indicates a router initialization issue that should be investigated."
)
try:
with mock.patch.object(
proxy_server.llm_router,
"aembedding",
return_value=example_embedding_result,
) as mock_aembedding:
test_data = {
"model": "vllm_embed_model",
"input": [[2046, 13269, 158208]],
}
response = client_no_auth.post("/v1/embeddings", json=test_data)
# Assert that aembedding was called, and that input was not modified
mock_aembedding.assert_called_once()
call_args, call_kwargs = mock_aembedding.call_args
assert call_kwargs["model"] == "vllm_embed_model"
assert call_kwargs["input"] == [[2046, 13269, 158208]]
assert response.status_code == 200
result = response.json()
print(len(result["data"][0]["embedding"]))
assert (
len(result["data"][0]["embedding"]) > 10
) # this usually has len==1536 so
except Exception as e:
pytest.fail(f"LiteLLM Proxy test failed. Exception - {str(e)}")
@pytest.mark.asyncio
async def test_get_all_team_models():
"""
Test get_all_team_models function with both "*" and specific team IDs
"""
from unittest.mock import AsyncMock, MagicMock
from litellm.proxy._types import LiteLLM_TeamTable
from litellm.proxy.proxy_server import get_all_team_models
# Mock team data
mock_team1 = MagicMock()
mock_team1.model_dump.return_value = {
"team_id": "team1",
"models": ["gpt-4", "gpt-3.5-turbo"],
"team_alias": "Team 1",
}
mock_team2 = MagicMock()
mock_team2.model_dump.return_value = {
"team_id": "team2",
"models": ["claude-3", "gpt-4"],
"team_alias": "Team 2",
}
# Mock model data returned by router
mock_models_gpt4 = [
{"model_info": {"id": "gpt-4-model-1"}},
{"model_info": {"id": "gpt-4-model-2"}},
]
mock_models_gpt35 = [
{"model_info": {"id": "gpt-3.5-turbo-model-1"}},
]
mock_models_claude = [
{"model_info": {"id": "claude-3-model-1"}},
]
# Mock prisma client
mock_prisma_client = MagicMock()
mock_db = MagicMock()
mock_litellm_teamtable = MagicMock()
mock_prisma_client.db = mock_db
mock_db.litellm_teamtable = mock_litellm_teamtable
# Make find_many async
mock_litellm_teamtable.find_many = AsyncMock()
# Mock router
mock_router = MagicMock()
def mock_get_model_list(model_name, team_id=None):
if model_name == "gpt-4":
return mock_models_gpt4
elif model_name == "gpt-3.5-turbo":
return mock_models_gpt35
elif model_name == "claude-3":
return mock_models_claude
return None
mock_router.get_model_list.side_effect = mock_get_model_list
# Test Case 1: user_teams = "*" (all teams)
mock_litellm_teamtable.find_many.return_value = [mock_team1, mock_team2]
with patch("litellm.proxy.proxy_server.LiteLLM_TeamTable") as mock_team_table_class:
# Configure the mock class to return proper instances
def mock_team_table_constructor(**kwargs):
mock_instance = MagicMock()
mock_instance.team_id = kwargs["team_id"]
mock_instance.models = kwargs["models"]
mock_instance.access_group_ids = kwargs.get("access_group_ids")
return mock_instance
mock_team_table_class.side_effect = mock_team_table_constructor
result = await get_all_team_models(
user_teams="*",
prisma_client=mock_prisma_client,
llm_router=mock_router,
)
# Verify find_many was called without where clause for "*"
mock_litellm_teamtable.find_many.assert_called_with()
# Verify router.get_model_list was called for each model
expected_calls = [
mock.call(model_name="gpt-4", team_id="team1"),
mock.call(model_name="gpt-3.5-turbo", team_id="team1"),
mock.call(model_name="claude-3", team_id="team2"),
mock.call(model_name="gpt-4", team_id="team2"),
]
mock_router.get_model_list.assert_has_calls(expected_calls, any_order=True)
# Test Case 2: user_teams = specific list
mock_litellm_teamtable.reset_mock()
mock_router.reset_mock()
mock_router.get_model_list.side_effect = mock_get_model_list
# Only return team1 for specific team query
mock_litellm_teamtable.find_many.return_value = [mock_team1]
with patch("litellm.proxy.proxy_server.LiteLLM_TeamTable") as mock_team_table_class:
mock_team_table_class.side_effect = mock_team_table_constructor
result = await get_all_team_models(
user_teams=["team1"],
prisma_client=mock_prisma_client,
llm_router=mock_router,
)
# Verify find_many was called with where clause for specific teams
mock_litellm_teamtable.find_many.assert_called_with(
where={"team_id": {"in": ["team1"]}}
)
# Verify router.get_model_list was called only for team1 models
expected_calls = [
mock.call(model_name="gpt-4", team_id="team1"),
mock.call(model_name="gpt-3.5-turbo", team_id="team1"),
]
mock_router.get_model_list.assert_has_calls(expected_calls, any_order=True)
# Test Case 3: Empty teams list
mock_litellm_teamtable.reset_mock()
mock_router.reset_mock()
mock_litellm_teamtable.find_many.return_value = []
result = await get_all_team_models(
user_teams=[],
prisma_client=mock_prisma_client,
llm_router=mock_router,
)
# Verify find_many was called with empty list
mock_litellm_teamtable.find_many.assert_called_with(where={"team_id": {"in": []}})
# Should return empty list when no teams
assert result == {}
# Test Case 4: Router returns None for some models
mock_litellm_teamtable.reset_mock()
mock_router.reset_mock()
mock_litellm_teamtable.find_many.return_value = [mock_team1]
def mock_get_model_list_with_none(model_name, team_id=None):
if model_name == "gpt-4":
return mock_models_gpt4
# Return None for gpt-3.5-turbo to test None handling
return None
mock_router.get_model_list.side_effect = mock_get_model_list_with_none
with patch("litellm.proxy.proxy_server.LiteLLM_TeamTable") as mock_team_table_class:
mock_team_table_class.side_effect = mock_team_table_constructor
result = await get_all_team_models(
user_teams=["team1"],
prisma_client=mock_prisma_client,
llm_router=mock_router,
)
# Should handle None return gracefully
assert isinstance(result, dict)
print("result: ", result)
assert result == {"gpt-4-model-1": ["team1"], "gpt-4-model-2": ["team1"]}
def test_add_team_models_to_all_models():
"""
Test add_team_models_to_all_models function
"""
from litellm.proxy._types import LiteLLM_TeamTable
from litellm.proxy.proxy_server import _add_team_models_to_all_models
team_db_objects_typed = MagicMock(spec=LiteLLM_TeamTable)
team_db_objects_typed.team_id = "team1"
team_db_objects_typed.models = ["all-proxy-models"]
llm_router = MagicMock()
llm_router.get_model_list.return_value = [
{"model_info": {"id": "gpt-4-model-1", "team_id": "team2"}},
{"model_info": {"id": "gpt-4-model-2"}},
]
result = _add_team_models_to_all_models(
team_db_objects_typed=[team_db_objects_typed],
llm_router=llm_router,
)
assert result == {"gpt-4-model-2": {"team1"}}
@pytest.mark.asyncio
async def test_add_access_group_models_to_team_models():
"""
Test that models reachable via team access groups are included in team_models.
Scenario: A team has models=["gpt-4"] and access_group_ids=["premium"].
The "premium" access group contains ["claude-3", "gemini"].
After resolution, the team should see gpt-4 (direct) + claude-3/gemini (via access group).
"""
from litellm.proxy._types import LiteLLM_TeamTable
from litellm.proxy.proxy_server import _add_access_group_models_to_team_models
# Team with specific models AND access groups
team_with_access_groups = MagicMock(spec=LiteLLM_TeamTable)
team_with_access_groups.team_id = "team1"
team_with_access_groups.models = ["gpt-4"] # non-empty = specific models
team_with_access_groups.access_group_ids = ["premium"]
# Team with no access groups — should be skipped
team_without_access_groups = MagicMock(spec=LiteLLM_TeamTable)
team_without_access_groups.team_id = "team2"
team_without_access_groups.models = ["gpt-4"]
team_without_access_groups.access_group_ids = None
# Team with empty access_group_ids list — should be skipped
team_empty_access_groups = MagicMock(spec=LiteLLM_TeamTable)
team_empty_access_groups.team_id = "team2b"
team_empty_access_groups.models = ["gpt-4"]
team_empty_access_groups.access_group_ids = []
# Team with empty models (all access) — should be skipped
team_all_access = MagicMock(spec=LiteLLM_TeamTable)
team_all_access.team_id = "team3"
team_all_access.models = []
team_all_access.access_group_ids = ["premium"]
# Team with all-proxy-models sentinel (all access) — should be skipped
team_all_proxy = MagicMock(spec=LiteLLM_TeamTable)
team_all_proxy.team_id = "team4"
team_all_proxy.models = ["all-proxy-models"]
team_all_proxy.access_group_ids = ["premium"]
# Mock router
mock_router = MagicMock()
def mock_get_model_list(model_name, team_id=None):
if model_name == "claude-3":
return [{"model_info": {"id": "claude-3-id"}}]
elif model_name == "gemini":
return [{"model_info": {"id": "gemini-id"}}]
return None
mock_router.get_model_list.side_effect = mock_get_model_list
# Pre-existing team_models (e.g., from _add_team_models_to_all_models)
existing_team_models = {
"gpt-4-id": {"team1"},
}
# Mock prisma client with batch find_many returning access group rows
mock_ag_row = MagicMock()
mock_ag_row.access_group_id = "premium"
mock_ag_row.access_model_names = ["claude-3", "gemini"]
mock_prisma_client = MagicMock()
mock_prisma_client.db.litellm_accessgrouptable.find_many = AsyncMock(
return_value=[mock_ag_row]
)
result = await _add_access_group_models_to_team_models(
team_db_objects_typed=[
team_with_access_groups,
team_without_access_groups,
team_empty_access_groups,
team_all_access,
team_all_proxy,
],
llm_router=mock_router,
prisma_client=mock_prisma_client,
team_models=existing_team_models,
)
# Single batch query with only the eligible team's access group IDs
mock_prisma_client.db.litellm_accessgrouptable.find_many.assert_called_once()
call_args = mock_prisma_client.db.litellm_accessgrouptable.find_many.call_args
queried_ids = call_args[1]["where"]["access_group_id"]["in"]
assert set(queried_ids) == {"premium"}
# Original model still present
assert "gpt-4-id" in result
assert "team1" in result["gpt-4-id"]
# Access group models added for team1
assert "claude-3-id" in result
assert "team1" in result["claude-3-id"]
assert "gemini-id" in result
assert "team1" in result["gemini-id"]
# Skipped teams should NOT have added these models
for skipped_team in ["team2", "team2b", "team3", "team4"]:
assert skipped_team not in result.get("claude-3-id", set())
assert skipped_team not in result.get("gemini-id", set())
@pytest.mark.asyncio
async def test_add_access_group_models_multiple_teams_shared_group():
"""
Test that multiple teams sharing the same access group each get the models,
and only one batch DB query is made.
"""
from litellm.proxy._types import LiteLLM_TeamTable
from litellm.proxy.proxy_server import _add_access_group_models_to_team_models
team_a = MagicMock(spec=LiteLLM_TeamTable)
team_a.team_id = "team-a"
team_a.models = ["gpt-4"]
team_a.access_group_ids = ["shared-group"]
team_b = MagicMock(spec=LiteLLM_TeamTable)
team_b.team_id = "team-b"
team_b.models = ["gpt-3.5"]
team_b.access_group_ids = ["shared-group", "extra-group"]
mock_router = MagicMock()
def mock_get_model_list(model_name, team_id=None):
if model_name == "claude-3":
return [{"model_info": {"id": "claude-3-id"}}]
elif model_name == "gemini":
return [{"model_info": {"id": "gemini-id"}}]
return None
mock_router.get_model_list.side_effect = mock_get_model_list
mock_shared_row = MagicMock()
mock_shared_row.access_group_id = "shared-group"
mock_shared_row.access_model_names = ["claude-3"]
mock_extra_row = MagicMock()
mock_extra_row.access_group_id = "extra-group"
mock_extra_row.access_model_names = ["gemini"]
mock_prisma_client = MagicMock()
mock_prisma_client.db.litellm_accessgrouptable.find_many = AsyncMock(
return_value=[mock_shared_row, mock_extra_row]
)
result = await _add_access_group_models_to_team_models(
team_db_objects_typed=[team_a, team_b],
llm_router=mock_router,
prisma_client=mock_prisma_client,
team_models={},
)
# Single batch query for both groups
mock_prisma_client.db.litellm_accessgrouptable.find_many.assert_called_once()
call_args = mock_prisma_client.db.litellm_accessgrouptable.find_many.call_args
queried_ids = set(call_args[1]["where"]["access_group_id"]["in"])
assert queried_ids == {"shared-group", "extra-group"}
# Both teams get claude-3 from the shared group
assert "claude-3-id" in result
assert "team-a" in result["claude-3-id"]
assert "team-b" in result["claude-3-id"]
# Only team-b gets gemini (from extra-group)
assert "gemini-id" in result
assert "team-b" in result["gemini-id"]
assert "team-a" not in result["gemini-id"]
@pytest.mark.asyncio
async def test_add_access_group_models_no_eligible_teams():
"""
When no teams have access groups, find_many should not be called at all.
"""
from litellm.proxy._types import LiteLLM_TeamTable
from litellm.proxy.proxy_server import _add_access_group_models_to_team_models
team = MagicMock(spec=LiteLLM_TeamTable)
team.team_id = "team1"
team.models = ["gpt-4"]
team.access_group_ids = None
mock_prisma_client = MagicMock()
mock_prisma_client.db.litellm_accessgrouptable.find_many = AsyncMock()
result = await _add_access_group_models_to_team_models(
team_db_objects_typed=[team],
llm_router=MagicMock(),
prisma_client=mock_prisma_client,
team_models={"existing-id": {"team1"}},
)
# No DB call made
mock_prisma_client.db.litellm_accessgrouptable.find_many.assert_not_called()
# Original data unchanged
assert result == {"existing-id": {"team1"}}
@pytest.mark.asyncio
async def test_get_all_team_models_with_access_groups():
"""
End-to-end test: get_all_team_models includes models from access groups.
Scenario: User is on team1 which has models=["gpt-4"] and
access_group_ids=["premium"]. The "premium" group has ["claude-3"].
The result should include both gpt-4 and claude-3 deployments for team1.
"""
from litellm.proxy.proxy_server import get_all_team_models
mock_team1 = MagicMock()
mock_team1.model_dump.return_value = {
"team_id": "team1",
"models": ["gpt-4"],
"team_alias": "Team 1",
"access_group_ids": ["premium"],
}
# Mock access group row returned by batch find_many
mock_ag_row = MagicMock()
mock_ag_row.access_group_id = "premium"
mock_ag_row.access_model_names = ["claude-3"]
mock_prisma_client = MagicMock()
mock_db = MagicMock()
mock_litellm_teamtable = MagicMock()
mock_prisma_client.db = mock_db
mock_db.litellm_teamtable = mock_litellm_teamtable
mock_litellm_teamtable.find_many = AsyncMock(return_value=[mock_team1])
mock_db.litellm_accessgrouptable = MagicMock()
mock_db.litellm_accessgrouptable.find_many = AsyncMock(return_value=[mock_ag_row])
mock_router = MagicMock()
def mock_get_model_list(model_name, team_id=None):
if model_name == "gpt-4":
return [{"model_info": {"id": "gpt-4-deploy-1"}}]
elif model_name == "claude-3":
return [{"model_info": {"id": "claude-3-deploy-1"}}]
return None
mock_router.get_model_list.side_effect = mock_get_model_list
with patch("litellm.proxy.proxy_server.LiteLLM_TeamTable") as mock_tt_class:
def mock_team_table_constructor(**kwargs):
mock_instance = MagicMock()
mock_instance.team_id = kwargs["team_id"]
mock_instance.models = kwargs["models"]
mock_instance.access_group_ids = kwargs.get("access_group_ids")
return mock_instance
mock_tt_class.side_effect = mock_team_table_constructor
result = await get_all_team_models(
user_teams=["team1"],
prisma_client=mock_prisma_client,
llm_router=mock_router,
)
# gpt-4 from direct team.models
assert "gpt-4-deploy-1" in result
assert "team1" in result["gpt-4-deploy-1"]
# claude-3 from access group
assert "claude-3-deploy-1" in result
assert "team1" in result["claude-3-deploy-1"]
# Return type is Dict[str, List[str]]
assert isinstance(result["gpt-4-deploy-1"], list)
assert isinstance(result["claude-3-deploy-1"], list)
@pytest.mark.asyncio
async def test_delete_deployment_type_mismatch():
"""
Test that the _delete_deployment function handles type mismatches correctly.
Specifically test that models 12345678 and 12345679 are NOT deleted when
they exist in both combined_id_list (as integers) and router_model_ids (as strings).
This test reproduces the bug where type mismatch causes valid models to be deleted.
"""
from unittest.mock import MagicMock, patch
from litellm.proxy.proxy_server import ProxyConfig
# Create mock ProxyConfig instance
pc = ProxyConfig()
pc.get_config = MagicMock(
return_value={
"model_list": [
{
"model_name": "openai-gpt-4o",
"litellm_params": {"model": "gpt-4o"},
"model_info": {"id": 12345678},
},
{
"model_name": "openai-gpt-4o",
"litellm_params": {"model": "gpt-4o"},
"model_info": {"id": 12345679},
},
]
}
)
# Mock llm_router with string IDs (this is the source of the type mismatch)
mock_llm_router = MagicMock()
mock_llm_router.get_model_ids.return_value = [
"a96e12e76b36a57cfae57a41288eb41567629cac89b4828c6f7074afc3534695",
"a40186dd0fdb9b7282380277d7f57044d29de95bfbfcd7f4322b3493702d5cd3",
"12345678", # String ID
"12345679", # String ID
]
# Track which deployments were deleted
deleted_ids = []
def mock_delete_deployment(id):
deleted_ids.append(id)
return True # Simulate successful deletion
mock_llm_router.delete_deployment = MagicMock(side_effect=mock_delete_deployment)
# Mock get_config to return empty config (no config models)
async def mock_get_config(config_file_path):
return {}
pc.get_config = MagicMock(side_effect=mock_get_config)
# Patch the global llm_router
with (
patch("litellm.proxy.proxy_server.llm_router", mock_llm_router),
patch("litellm.proxy.proxy_server.user_config_file_path", "test_config.yaml"),
):
# Call the function under test
deleted_count = await pc._delete_deployment(db_models=[])
# Assertions: Models 12345678 and 12345679 should NOT be deleted
# because they exist in combined_id_list (as integers) even though
# router has them as strings
# The function should delete the other 2 models that are not in combined_id_list
assert deleted_count == 0, f"Expected 0 deletions, got {deleted_count}"
# Verify that 12345678 and 12345679 were NOT deleted
assert (
"12345678" not in deleted_ids
), f"Model 12345678 should NOT be deleted. Deleted IDs: {deleted_ids}"
assert (
"12345679" not in deleted_ids
), f"Model 12345679 should NOT be deleted. Deleted IDs: {deleted_ids}"
@pytest.mark.asyncio
async def test_get_config_from_file(tmp_path, monkeypatch):
"""
Test the _get_config_from_file method of ProxyConfig class.
Tests various scenarios: valid file, non-existent file, no file path, None config.
"""
import yaml
from litellm.proxy.proxy_server import ProxyConfig
# Create a ProxyConfig instance
proxy_config = ProxyConfig()
# Test Case 1: Valid YAML config file exists
test_config = {
"model_list": [{"model_name": "gpt-4", "litellm_params": {"model": "gpt-4"}}],
"general_settings": {"master_key": "sk-test"},
"router_settings": {"enable_pre_call_checks": True},
"litellm_settings": {"drop_params": True},
}
config_file = tmp_path / "test_config.yaml"
with open(config_file, "w") as f:
yaml.dump(test_config, f)
# Clear global user_config_file_path for this test
monkeypatch.setattr("litellm.proxy.proxy_server.user_config_file_path", None)
result = await proxy_config._get_config_from_file(str(config_file))
assert result == test_config
# Verify that user_config_file_path was set
from litellm.proxy.proxy_server import user_config_file_path
assert user_config_file_path == str(config_file)
# Test Case 2: File path provided but file doesn't exist
non_existent_file = tmp_path / "non_existent.yaml"
with pytest.raises(Exception, match=f"Config file not found: {non_existent_file}"):
await proxy_config._get_config_from_file(str(non_existent_file))
# Test Case 3: No file path provided (should return default config)
monkeypatch.setattr("litellm.proxy.proxy_server.user_config_file_path", None)
expected_default = {
"model_list": [],
"general_settings": {},
"router_settings": {},
"litellm_settings": {},
}
result = await proxy_config._get_config_from_file(None)
assert result == expected_default
# Test Case 4: Empty YAML file (should raise exception for None config)
empty_file = tmp_path / "empty_config.yaml"
with open(empty_file, "w") as f:
f.write("") # Write empty content which will result in None when loaded
with pytest.raises(Exception, match="Config cannot be None or Empty."):
await proxy_config._get_config_from_file(str(empty_file))
# Test Case 5: Using global user_config_file_path when no config_file_path provided
monkeypatch.setattr(
"litellm.proxy.proxy_server.user_config_file_path", str(config_file)
)
result = await proxy_config._get_config_from_file(None)
assert result == test_config
def test_normalize_datetime_for_sorting():
"""
Test the _normalize_datetime_for_sorting function.
Tests various scenarios: None values, ISO format strings, datetime objects (naive and aware).
"""
from litellm.proxy.proxy_server import _normalize_datetime_for_sorting
# Test Case 1: None value
assert _normalize_datetime_for_sorting(None) is None
# Test Case 2: ISO format string with 'Z' suffix
dt_str_z = "2024-01-15T10:30:00Z"
result = _normalize_datetime_for_sorting(dt_str_z)
assert result is not None
assert isinstance(result, datetime)
assert result.tzinfo == timezone.utc
assert result.year == 2024
assert result.month == 1
assert result.day == 15
assert result.hour == 10
assert result.minute == 30
# Test Case 3: ISO format string without 'Z' suffix (naive)
dt_str_naive = "2024-01-15T10:30:00"
result = _normalize_datetime_for_sorting(dt_str_naive)
assert result is not None
assert isinstance(result, datetime)
assert result.tzinfo == timezone.utc
# Test Case 4: ISO format string with timezone offset
dt_str_tz = "2024-01-15T10:30:00+05:00"
result = _normalize_datetime_for_sorting(dt_str_tz)
assert result is not None
assert isinstance(result, datetime)
assert result.tzinfo == timezone.utc
# Should convert from +05:00 to UTC (subtract 5 hours)
assert result.hour == 5 # 10:30 - 5 hours = 5:30 UTC
# Test Case 5: Naive datetime object
naive_dt = datetime(2024, 1, 15, 10, 30, 0)
result = _normalize_datetime_for_sorting(naive_dt)
assert result is not None
assert isinstance(result, datetime)
assert result.tzinfo == timezone.utc
assert result.year == 2024
assert result.month == 1
assert result.day == 15
# Test Case 6: Timezone-aware datetime object (non-UTC)
from datetime import timedelta
aware_dt = datetime(2024, 1, 15, 10, 30, 0, tzinfo=timezone(timedelta(hours=5)))
result = _normalize_datetime_for_sorting(aware_dt)
assert result is not None
assert isinstance(result, datetime)
assert result.tzinfo == timezone.utc
# Should convert from +05:00 to UTC
assert result.hour == 5
# Test Case 7: UTC-aware datetime object
utc_dt = datetime(2024, 1, 15, 10, 30, 0, tzinfo=timezone.utc)
result = _normalize_datetime_for_sorting(utc_dt)
assert result is not None
assert isinstance(result, datetime)
assert result.tzinfo == timezone.utc
assert result == utc_dt
# Test Case 8: Invalid string format
invalid_str = "not-a-date"
result = _normalize_datetime_for_sorting(invalid_str)
assert result is None
# Test Case 9: Invalid type (should return None)
result = _normalize_datetime_for_sorting(12345)
assert result is None
@pytest.mark.asyncio
async def test_add_proxy_budget_to_db_only_creates_user_no_keys():
"""
Test that _add_proxy_budget_to_db only creates a user and no keys are added.
This validates that generate_key_helper_fn is called with table_name="user"
which should prevent key creation in LiteLLM_VerificationToken table.
"""
from unittest.mock import AsyncMock, patch
import litellm
from litellm.proxy.proxy_server import ProxyStartupEvent
# Set up required litellm settings
litellm.budget_duration = "30d"
litellm.max_budget = 100.0
litellm_proxy_budget_name = "litellm-proxy-budget"
# Mock generate_key_helper_fn to capture its call arguments
mock_generate_key_helper = AsyncMock(
return_value={
"user_id": litellm_proxy_budget_name,
"max_budget": 100.0,
"budget_duration": "30d",
"spend": 0,
"models": [],
}
)
# Patch generate_key_helper_fn in proxy_server where it's being called from
with patch(
"litellm.proxy.proxy_server.generate_key_helper_fn", mock_generate_key_helper
):
# Call the function under test
ProxyStartupEvent._add_proxy_budget_to_db(litellm_proxy_budget_name)
# Allow async task to complete
import asyncio
await asyncio.sleep(0.1)
# Verify that generate_key_helper_fn was called
mock_generate_key_helper.assert_called_once()
call_args = mock_generate_key_helper.call_args
# Verify critical parameters that prevent key creation
assert call_args.kwargs["request_type"] == "user"
assert call_args.kwargs["table_name"] == "user"
assert call_args.kwargs["user_id"] == litellm_proxy_budget_name
assert call_args.kwargs["max_budget"] == 100.0
assert call_args.kwargs["budget_duration"] == "30d"
assert call_args.kwargs["query_type"] == "update_data"
@pytest.mark.asyncio
async def test_custom_ui_sso_sign_in_handler_config_loading():
"""
Test that custom_ui_sso_sign_in_handler from config gets properly loaded into the global variable
"""
import tempfile
from unittest.mock import MagicMock, patch
import yaml
from litellm.proxy.proxy_server import ProxyConfig
# Create a test config with custom_ui_sso_sign_in_handler
test_config = {
"general_settings": {
"custom_ui_sso_sign_in_handler": "custom_hooks.custom_ui_sso_hook.custom_ui_sso_sign_in_handler"
},
"model_list": [],
"router_settings": {},
"litellm_settings": {},
}
# Create temporary config file
with tempfile.NamedTemporaryFile(mode="w", suffix=".yaml", delete=False) as f:
yaml.dump(test_config, f)
config_file_path = f.name
# Mock the get_instance_fn to return a mock handler
mock_custom_handler = MagicMock()
try:
with patch(
"litellm.proxy.proxy_server.get_instance_fn",
return_value=mock_custom_handler,
) as mock_get_instance:
# Create ProxyConfig instance and load config
proxy_config = ProxyConfig()
# Create a mock router since load_config requires it
mock_router = MagicMock()
await proxy_config.load_config(
router=mock_router, config_file_path=config_file_path
)
# Verify get_instance_fn was called with correct parameters
mock_get_instance.assert_called_with(
value="custom_hooks.custom_ui_sso_hook.custom_ui_sso_sign_in_handler",
config_file_path=config_file_path,
)
# Verify the global variable was set
from litellm.proxy.proxy_server import user_custom_ui_sso_sign_in_handler
assert user_custom_ui_sso_sign_in_handler == mock_custom_handler
finally:
# Clean up temporary file
import os
os.unlink(config_file_path)
@pytest.mark.asyncio
async def test_load_environment_variables_direct_and_os_environ():
"""
Test _load_environment_variables method with direct values and os.environ/ prefixed values
"""
from unittest.mock import patch
from litellm.proxy.proxy_server import ProxyConfig
proxy_config = ProxyConfig()
# Test config with both direct values and os.environ/ prefixed values
test_config = {
"environment_variables": {
"DIRECT_VAR": "direct_value",
"NUMERIC_VAR": 12345,
"BOOL_VAR": True,
"SECRET_VAR": "os.environ/ACTUAL_SECRET_VAR",
}
}
# Mock get_secret_str to return a resolved value
mock_secret_value = "resolved_secret_value"
with patch(
"litellm.proxy.proxy_server.get_secret_str", return_value=mock_secret_value
) as mock_get_secret:
with patch.dict(
os.environ, {}, clear=False
): # Don't clear existing env vars, just track changes
# Call the method under test
proxy_config._load_environment_variables(test_config)
# Verify direct environment variables were set correctly
assert os.environ["DIRECT_VAR"] == "direct_value"
assert os.environ["NUMERIC_VAR"] == "12345" # Should be converted to string
assert os.environ["BOOL_VAR"] == "True" # Should be converted to string
# Verify os.environ/ prefixed variable was resolved and set
assert os.environ["SECRET_VAR"] == mock_secret_value
# Verify get_secret_str was called with the correct value
mock_get_secret.assert_called_once_with(
secret_name="os.environ/ACTUAL_SECRET_VAR"
)
@pytest.mark.asyncio
async def test_load_environment_variables_litellm_license_and_edge_cases():
"""
Test _load_environment_variables method with LITELLM_LICENSE special handling and edge cases
"""
from unittest.mock import MagicMock, patch
from litellm.proxy.proxy_server import ProxyConfig
proxy_config = ProxyConfig()
# Test Case 1: LITELLM_LICENSE in environment_variables
test_config_with_license = {
"environment_variables": {
"LITELLM_LICENSE": "test_license_key",
"OTHER_VAR": "other_value",
}
}
# Mock _license_check
mock_license_check = MagicMock()
mock_license_check.is_premium.return_value = True
with patch("litellm.proxy.proxy_server._license_check", mock_license_check):
with patch.dict(os.environ, {}, clear=False):
# Call the method under test
proxy_config._load_environment_variables(test_config_with_license)
# Verify LITELLM_LICENSE was set in environment
assert os.environ["LITELLM_LICENSE"] == "test_license_key"
# Verify license check was updated
assert mock_license_check.license_str == "test_license_key"
mock_license_check.is_premium.assert_called_once()
# Test Case 2: No environment_variables in config
test_config_no_env_vars = {}
# This should not raise any errors and should return without doing anything
result = proxy_config._load_environment_variables(test_config_no_env_vars)
assert result is None # Method returns None
# Test Case 3: environment_variables is None
test_config_none_env_vars = {"environment_variables": None}
# This should not raise any errors and should return without doing anything
result = proxy_config._load_environment_variables(test_config_none_env_vars)
assert result is None # Method returns None
# Test Case 4: os.environ/ prefix but get_secret_str returns None
test_config_secret_none = {
"environment_variables": {"FAILED_SECRET": "os.environ/NONEXISTENT_SECRET"}
}
with patch("litellm.proxy.proxy_server.get_secret_str", return_value=None):
with patch.dict(os.environ, {}, clear=False):
# Call the method under test
proxy_config._load_environment_variables(test_config_secret_none)
# Verify that the environment variable was not set when secret resolution fails
assert "FAILED_SECRET" not in os.environ
@pytest.mark.asyncio
async def test_load_environment_variables_blocks_dangerous_keys():
"""
Test that _load_environment_variables rejects dangerous env var keys
like PATH, LD_PRELOAD, PYTHONPATH, etc.
"""
import logging
from litellm.proxy.proxy_server import ProxyConfig
proxy_config = ProxyConfig()
original_path = os.environ.get("PATH", "")
test_config = {
"environment_variables": {
"PATH": "/tmp/evil",
"LD_PRELOAD": "/tmp/evil.so",
"PYTHONPATH": "/tmp/evil",
"SAFE_CUSTOM_VAR": "safe_value",
}
}
with patch.dict(os.environ, {}, clear=False):
proxy_config._load_environment_variables(test_config)
# Blocked keys should not be set to the attacker value
assert os.environ.get("PATH") != "/tmp/evil"
assert (
"LD_PRELOAD" not in os.environ or os.environ["LD_PRELOAD"] != "/tmp/evil.so"
)
assert os.environ.get("PYTHONPATH") != "/tmp/evil"
# Safe keys should still be set
assert os.environ["SAFE_CUSTOM_VAR"] == "safe_value"
@pytest.mark.asyncio
async def test_load_environment_variables_allows_proxy_keys():
"""
Test that HTTP_PROXY/HTTPS_PROXY are allowed since they are commonly used
in corporate environments to route outbound API calls.
"""
from litellm.proxy.proxy_server import ProxyConfig
proxy_config = ProxyConfig()
test_config = {
"environment_variables": {
"HTTP_PROXY": "http://corp-proxy:8080",
"HTTPS_PROXY": "http://corp-proxy:8080",
}
}
with patch.dict(os.environ, {}, clear=False):
proxy_config._load_environment_variables(test_config)
assert os.environ["HTTP_PROXY"] == "http://corp-proxy:8080"
assert os.environ["HTTPS_PROXY"] == "http://corp-proxy:8080"
@pytest.mark.asyncio
async def test_load_environment_variables_blocks_no_proxy():
"""
Test that NO_PROXY/no_proxy are blocked to prevent bypassing proxy-based
network monitoring.
"""
from litellm.proxy.proxy_server import ProxyConfig
proxy_config = ProxyConfig()
test_config = {
"environment_variables": {
"NO_PROXY": "internal-service",
"no_proxy": "internal-service",
}
}
with patch.dict(os.environ, {}, clear=False):
proxy_config._load_environment_variables(test_config)
assert os.environ.get("NO_PROXY") != "internal-service"
assert os.environ.get("no_proxy") != "internal-service"
@pytest.mark.asyncio
async def test_write_config_to_file(monkeypatch):
"""
Do not write config to file if store_model_in_db is True
"""
from unittest.mock import AsyncMock, MagicMock, mock_open, patch
from litellm.proxy.proxy_server import ProxyConfig
# Set store_model_in_db to True
monkeypatch.setattr("litellm.proxy.proxy_server.store_model_in_db", True)
# Mock prisma_client to not be None (so DB path is taken)
mock_prisma_client = AsyncMock()
mock_prisma_client.insert_data = AsyncMock()
monkeypatch.setattr("litellm.proxy.proxy_server.prisma_client", mock_prisma_client)
# Mock general_settings
mock_general_settings = {"store_model_in_db": True}
monkeypatch.setattr(
"litellm.proxy.proxy_server.general_settings", mock_general_settings
)
# Mock user_config_file_path
test_config_path = "/tmp/test_config.yaml"
monkeypatch.setattr(
"litellm.proxy.proxy_server.user_config_file_path", test_config_path
)
proxy_config = ProxyConfig()
# Mock the open function to track if file writing is attempted
mock_file_open = mock_open()
with patch("builtins.open", mock_file_open), patch("yaml.dump") as mock_yaml_dump:
# Call save_config with test data
test_config = {"key": "value", "model_list": ["model1", "model2"]}
await proxy_config.save_config(new_config=test_config)
# Verify that file was NOT opened for writing (since store_model_in_db=True)
mock_file_open.assert_not_called()
mock_yaml_dump.assert_not_called()
# Verify that database insert was called instead
mock_prisma_client.insert_data.assert_called_once()
# Verify the config passed to DB has model_list removed
call_args = mock_prisma_client.insert_data.call_args
assert call_args.kwargs["data"] == {
"key": "value"
} # model_list should be popped
assert call_args.kwargs["table_name"] == "config"
@pytest.mark.asyncio
async def test_write_config_to_file_when_store_model_in_db_false(monkeypatch):
"""
Test that config IS written to file when store_model_in_db is False
"""
from unittest.mock import AsyncMock, MagicMock, mock_open, patch
from litellm.proxy.proxy_server import ProxyConfig
# Set store_model_in_db to False
monkeypatch.setattr("litellm.proxy.proxy_server.store_model_in_db", False)
# Mock prisma_client to be None (so file path is taken)
monkeypatch.setattr("litellm.proxy.proxy_server.prisma_client", None)
# Mock general_settings
mock_general_settings = {"store_model_in_db": False}
monkeypatch.setattr(
"litellm.proxy.proxy_server.general_settings", mock_general_settings
)
# Mock user_config_file_path
test_config_path = "/tmp/test_config.yaml"
monkeypatch.setattr(
"litellm.proxy.proxy_server.user_config_file_path", test_config_path
)
proxy_config = ProxyConfig()
# Mock the open function and yaml.dump
mock_file_open = mock_open()
with patch("builtins.open", mock_file_open), patch("yaml.dump") as mock_yaml_dump:
# Call save_config with test data
test_config = {"key": "value", "other_key": "other_value"}
await proxy_config.save_config(new_config=test_config)
# Verify that file WAS opened for writing (since store_model_in_db=False)
mock_file_open.assert_called_once_with(f"{test_config_path}", "w")
# Verify yaml.dump was called with the config
mock_yaml_dump.assert_called_once_with(
test_config,
mock_file_open.return_value.__enter__.return_value,
default_flow_style=False,
)
@pytest.mark.asyncio
async def test_async_data_generator_midstream_error():
"""
Test async_data_generator handles midstream error from async_post_call_streaming_hook
Specifically testing the case where Azure Content Safety Guardrail returns an error
"""
from litellm.proxy._types import UserAPIKeyAuth
from litellm.proxy.proxy_server import async_data_generator
from litellm.proxy.utils import ProxyLogging
# Create mock objects
mock_user_api_key_dict = MagicMock(spec=UserAPIKeyAuth)
mock_request_data = {
"model": "gpt-3.5-turbo",
"messages": [{"role": "user", "content": "test"}],
}
# Mock response chunks - simulating normal streaming that gets interrupted
mock_chunks = [
{"choices": [{"delta": {"content": "Hello"}}]},
{"choices": [{"delta": {"content": " world"}}]},
{"choices": [{"delta": {"content": " this"}}]},
]
# Mock the proxy_logging_obj
mock_proxy_logging_obj = MagicMock(spec=ProxyLogging)
# Mock async_post_call_streaming_iterator_hook to yield chunks
async def mock_streaming_iterator(*args, **kwargs):
for chunk in mock_chunks:
yield chunk
mock_proxy_logging_obj.async_post_call_streaming_iterator_hook = (
mock_streaming_iterator
)
# Mock async_post_call_streaming_hook to return error on third chunk
def mock_streaming_hook(*args, **kwargs):
chunk = kwargs.get("response")
# Return error message for the third chunk (simulating guardrail trigger)
if chunk == mock_chunks[2]:
return 'data: {"error": {"error": "Azure Content Safety Guardrail: Hate crossed severity 2, Got severity: 2"}}'
# Return normal chunks for first two
return chunk
mock_proxy_logging_obj.async_post_call_streaming_hook = AsyncMock(
side_effect=mock_streaming_hook
)
mock_proxy_logging_obj.post_call_failure_hook = AsyncMock()
# Mock the global proxy_logging_obj
with patch("litellm.proxy.proxy_server.proxy_logging_obj", mock_proxy_logging_obj):
# Create a mock response object
mock_response = MagicMock()
# Collect all yielded data from the generator
yielded_data = []
try:
async for data in async_data_generator(
mock_response, mock_user_api_key_dict, mock_request_data
):
yielded_data.append(data)
except Exception as e:
# If there's an exception, that's also part of what we want to test
pass
# Verify the results
assert (
len(yielded_data) >= 3
), f"Expected at least 3 chunks, got {len(yielded_data)}: {yielded_data}"
# First two chunks should be normal data
assert yielded_data[0].startswith(
"data: "
), f"First chunk should start with 'data: ', got: {yielded_data[0]}"
assert yielded_data[1].startswith(
"data: "
), f"Second chunk should start with 'data: ', got: {yielded_data[1]}"
# The error message should be yielded
error_found = False
done_found = False
for data in yielded_data:
if "Azure Content Safety Guardrail: Hate crossed severity 2" in data:
error_found = True
if "data: [DONE]" in data:
done_found = True
assert (
error_found
), f"Error message should be found in yielded data. Got: {yielded_data}"
assert done_found, f"[DONE] message should be found at the end. Got: {yielded_data}"
# Verify that the streaming hook was called for each chunk
assert mock_proxy_logging_obj.async_post_call_streaming_hook.call_count == len(
mock_chunks
)
# Verify that post_call_failure_hook was NOT called (since this is not an exception case)
mock_proxy_logging_obj.post_call_failure_hook.assert_not_called()
def _has_nested_none_values(obj, path="root"):
"""
Recursively check if an object contains nested None values.
Args:
obj: The object to check
path: Current path in the object tree (for debugging)
Returns:
List of paths where None values were found
"""
none_paths = []
if obj is None:
none_paths.append(path)
elif isinstance(obj, dict):
for key, value in obj.items():
none_paths.extend(_has_nested_none_values(value, f"{path}.{key}"))
elif isinstance(obj, (list, tuple)):
for i, item in enumerate(obj):
none_paths.extend(_has_nested_none_values(item, f"{path}[{i}]"))
elif hasattr(obj, "__dict__"):
# Handle object attributes
for key, value in obj.__dict__.items():
if not key.startswith("_"): # Skip private attributes
none_paths.extend(_has_nested_none_values(value, f"{path}.{key}"))
return none_paths
@pytest.mark.asyncio
async def test_chat_completion_result_no_nested_none_values():
"""
Test that chat_completion result doesn't have nested None values when using exclude_none=True
"""
from unittest.mock import AsyncMock, MagicMock, patch
from fastapi import Request, Response
from pydantic import BaseModel
import litellm
from litellm.proxy._types import UserAPIKeyAuth
from litellm.proxy.proxy_server import chat_completion
# Create a mock ModelResponse with nested None values
mock_model_response = litellm.ModelResponse()
mock_model_response.id = "test-id"
mock_model_response.model = "gpt-3.5-turbo"
mock_model_response.object = "chat.completion"
mock_model_response.created = 1234567890
# Create message with None values that should be excluded
mock_message = litellm.Message(
content="Hello, world!",
role="assistant",
function_call=None, # This should be excluded
tool_calls=None, # This should be excluded
audio=None, # This should be excluded
reasoning_content=None, # This should be excluded
thinking_blocks=None, # This should be excluded
annotations=None, # This should be excluded
)
# Create choice with potential None values
mock_choice = litellm.Choices(
finish_reason="stop",
index=0,
message=mock_message,
logprobs=None, # This should be excluded when exclude_none=True
)
mock_model_response.choices = [mock_choice]
setattr(
mock_model_response,
"usage",
litellm.Usage(prompt_tokens=10, completion_tokens=5, total_tokens=15),
)
# Verify the mock has None values before serialization
raw_dict = mock_model_response.model_dump()
none_paths_before = _has_nested_none_values(raw_dict)
assert (
len(none_paths_before) > 0
), "Mock should have None values before exclude_none=True"
# Mock the request processing to return our mock response
mock_base_processor = MagicMock()
mock_base_processor.base_process_llm_request = AsyncMock(
return_value=mock_model_response
)
# Mock other dependencies
mock_request = MagicMock(spec=Request)
mock_response = MagicMock(spec=Response)
mock_user_api_key_dict = MagicMock(spec=UserAPIKeyAuth)
with (
patch(
"litellm.proxy.proxy_server._read_request_body",
return_value={"model": "gpt-3.5-turbo", "messages": []},
),
patch(
"litellm.proxy.proxy_server.ProxyBaseLLMRequestProcessing",
return_value=mock_base_processor,
),
):
# Call the chat_completion function
result = await chat_completion(
request=mock_request,
fastapi_response=mock_response,
user_api_key_dict=mock_user_api_key_dict,
)
# Verify the result is a dict (since isinstance(result, BaseModel) was True)
assert isinstance(result, dict), f"Expected dict result, got {type(result)}"
# Check that there are no nested None values in the result
none_paths_after = _has_nested_none_values(result)
assert (
len(none_paths_after) == 0
), f"Result should not contain nested None values. Found None at: {none_paths_after}"
# Verify essential fields are present
assert "id" in result
assert "model" in result
assert "object" in result
assert "created" in result
assert "choices" in result
assert "usage" in result
# Verify that the choices contain the expected message content
assert len(result["choices"]) == 1
assert result["choices"][0]["message"]["content"] == "Hello, world!"
assert result["choices"][0]["message"]["role"] == "assistant"
# Verify that None fields were excluded (should not be present in the dict)
message = result["choices"][0]["message"]
excluded_fields = [
"function_call",
"tool_calls",
"audio",
"reasoning_content",
"thinking_blocks",
"annotations",
]
for field in excluded_fields:
assert (
field not in message
), f"Field '{field}' should be excluded when it's None"
# ============================================================================
# Price Data Reload Tests
# ============================================================================
class TestPriceDataReloadAPI:
"""Test cases for price data reload API endpoints"""
@pytest.fixture
def client_with_auth(self):
"""Create a test client with authentication"""
from litellm.proxy._types import LitellmUserRoles
from litellm.proxy.proxy_server import cleanup_router_config_variables
cleanup_router_config_variables()
filepath = os.path.dirname(os.path.abspath(__file__))
config_fp = f"{filepath}/test_configs/test_config_no_auth.yaml"
asyncio.run(initialize(config=config_fp, debug=True))
# Mock admin user authentication
mock_auth = MagicMock()
mock_auth.user_role = LitellmUserRoles.PROXY_ADMIN
app.dependency_overrides[user_api_key_auth] = lambda: mock_auth
return TestClient(app)
def test_reload_model_cost_map_admin_access(self, client_with_auth):
"""Test that admin users can access the reload endpoint"""
# Save the original model_cost so the endpoint's direct assignment
# (litellm.model_cost = new_model_cost_map) does not contaminate
# subsequent tests running in the same worker process.
original_model_cost = litellm.model_cost.copy()
try:
with patch(
"litellm.litellm_core_utils.get_model_cost_map.get_model_cost_map"
) as mock_get_map:
mock_get_map.return_value = {
"gpt-3.5-turbo": {"input_cost_per_token": 0.001}
}
# Mock the database connection
with patch("litellm.proxy.proxy_server.prisma_client") as mock_prisma:
mock_prisma.db.litellm_config.find_unique = AsyncMock(
return_value=None
)
mock_prisma.db.litellm_config.upsert = AsyncMock(return_value=None)
response = client_with_auth.post("/reload/model_cost_map")
assert response.status_code == 200
data = response.json()
assert data["status"] == "success"
assert "message" in data
assert "timestamp" in data
assert "models_count" in data
# The new implementation immediately reloads and returns the count
assert (
"Price data reloaded successfully! 1 models updated."
in data["message"]
)
assert data["models_count"] == 1
finally:
# Restore the full model cost map so subsequent tests are not affected
litellm.model_cost = original_model_cost
_invalidate_model_cost_lowercase_map()
def test_reload_model_cost_map_non_admin_access(self, client_with_auth):
"""Test that non-admin users cannot access the reload endpoint"""
# Mock non-admin user
mock_auth = MagicMock()
mock_auth.user_role = "user" # Non-admin role
app.dependency_overrides[user_api_key_auth] = lambda: mock_auth
response = client_with_auth.post("/reload/model_cost_map")
assert response.status_code == 403
data = response.json()
assert "Access denied" in data["detail"]
assert "Admin role required" in data["detail"]
def test_get_model_cost_map_public_access(self, client_no_auth):
"""Test that the model cost map endpoint is publicly accessible"""
with patch(
"litellm.model_cost", {"gpt-3.5-turbo": {"input_cost_per_token": 0.001}}
):
response = client_no_auth.get("/public/litellm_model_cost_map")
assert response.status_code == 200
data = response.json()
assert "gpt-3.5-turbo" in data
def test_reload_model_cost_map_error_handling(self, client_with_auth):
"""Test error handling in the reload endpoint"""
with patch(
"litellm.litellm_core_utils.get_model_cost_map.get_model_cost_map"
) as mock_get_map:
mock_get_map.side_effect = Exception("Network error")
# Mock the database connection
with patch("litellm.proxy.proxy_server.prisma_client") as mock_prisma:
mock_prisma.db.litellm_config.find_unique = AsyncMock(return_value=None)
mock_prisma.db.litellm_config.upsert = AsyncMock(return_value=None)
response = client_with_auth.post("/reload/model_cost_map")
assert (
response.status_code == 500
) # The new implementation immediately reloads and fails on error
data = response.json()
assert "Failed to reload model cost map" in data["detail"]
def test_schedule_model_cost_map_reload_admin_access(self, client_with_auth):
"""Test that admin users can schedule periodic reload"""
with patch("litellm.proxy.proxy_server.prisma_client") as mock_prisma:
# Mock database upsert
mock_prisma.db.litellm_config.upsert = AsyncMock(return_value=None)
response = client_with_auth.post("/schedule/model_cost_map_reload?hours=6")
assert response.status_code == 200
data = response.json()
assert data["status"] == "success"
assert data["interval_hours"] == 6
assert "message" in data
assert "timestamp" in data
def test_schedule_model_cost_map_reload_non_admin_access(self, client_with_auth):
"""Test that non-admin users cannot schedule periodic reload"""
# Mock non-admin user
mock_auth = MagicMock()
mock_auth.user_role = "user" # Non-admin role
app.dependency_overrides[user_api_key_auth] = lambda: mock_auth
response = client_with_auth.post("/schedule/model_cost_map_reload?hours=6")
assert response.status_code == 403
data = response.json()
assert "Access denied" in data["detail"]
assert "Admin role required" in data["detail"]
def test_schedule_model_cost_map_reload_invalid_hours(self, client_with_auth):
"""Test that invalid hours parameter is rejected"""
response = client_with_auth.post("/schedule/model_cost_map_reload?hours=0")
assert response.status_code == 400
data = response.json()
assert "Hours must be greater than 0" in data["detail"]
def test_cancel_model_cost_map_reload_admin_access(self, client_with_auth):
"""Test that admin users can cancel periodic reload"""
with patch("litellm.proxy.proxy_server.prisma_client") as mock_prisma:
# Mock database delete
mock_prisma.db.litellm_config.delete = AsyncMock(return_value=None)
response = client_with_auth.delete("/schedule/model_cost_map_reload")
assert response.status_code == 200
data = response.json()
assert data["status"] == "success"
assert "message" in data
assert "timestamp" in data
def test_cancel_model_cost_map_reload_non_admin_access(self, client_with_auth):
"""Test that non-admin users cannot cancel periodic reload"""
# Mock non-admin user
mock_auth = MagicMock()
mock_auth.user_role = "user" # Non-admin role
app.dependency_overrides[user_api_key_auth] = lambda: mock_auth
response = client_with_auth.delete("/schedule/model_cost_map_reload")
assert response.status_code == 403
data = response.json()
assert "Access denied" in data["detail"]
assert "Admin role required" in data["detail"]
def test_get_model_cost_map_reload_status_admin_access(self, client_with_auth):
"""Test that admin users can get reload status"""
with patch("litellm.proxy.proxy_server.prisma_client") as mock_prisma:
# Mock database config record
mock_config = MagicMock()
mock_config.param_value = {"interval_hours": 6, "force_reload": False}
mock_prisma.db.litellm_config.find_unique = AsyncMock(
return_value=mock_config
)
# Mock the last reload time and current time
with patch(
"litellm.proxy.proxy_server.last_model_cost_map_reload",
"2024-01-01T06:00:00",
):
with patch("litellm.proxy.proxy_server.datetime") as mock_datetime:
# Mock current time to be 1 hour after last reload
mock_datetime.utcnow.return_value = datetime(2024, 1, 1, 7, 0, 0)
mock_datetime.fromisoformat = datetime.fromisoformat
response = client_with_auth.get(
"/schedule/model_cost_map_reload/status"
)
assert response.status_code == 200
data = response.json()
assert data["scheduled"] == True
assert data["interval_hours"] == 6
assert data["last_run"] == "2024-01-01T06:00:00"
assert data["next_run"] == "2024-01-01T12:00:00"
def test_get_model_cost_map_reload_status_non_admin_access(self, client_with_auth):
"""Test that non-admin users cannot get reload status"""
# Mock non-admin user
mock_auth = MagicMock()
mock_auth.user_role = "user" # Non-admin role
app.dependency_overrides[user_api_key_auth] = lambda: mock_auth
response = client_with_auth.get("/schedule/model_cost_map_reload/status")
assert response.status_code == 403
data = response.json()
assert "Access denied" in data["detail"]
assert "Admin role required" in data["detail"]
def test_get_model_cost_map_reload_status_no_config(self, client_with_auth):
"""Test that status returns not scheduled when no config exists"""
with patch("litellm.proxy.proxy_server.prisma_client") as mock_prisma:
mock_prisma.db.litellm_config.find_unique = AsyncMock(return_value=None)
response = client_with_auth.get("/schedule/model_cost_map_reload/status")
assert response.status_code == 200
data = response.json()
assert data["scheduled"] == False
assert data["interval_hours"] == None
assert data["last_run"] == None
assert data["next_run"] == None
def test_get_model_cost_map_reload_status_no_interval(self, client_with_auth):
"""Test that status returns not scheduled when no interval is configured"""
with patch("litellm.proxy.proxy_server.prisma_client") as mock_prisma:
# Mock config with no interval
mock_config = MagicMock()
mock_config.param_value = {"interval_hours": None, "force_reload": False}
mock_prisma.db.litellm_config.find_unique = AsyncMock(
return_value=mock_config
)
response = client_with_auth.get("/schedule/model_cost_map_reload/status")
assert response.status_code == 200
data = response.json()
assert data["scheduled"] == False
assert data["interval_hours"] == None
assert data["last_run"] == None
assert data["next_run"] == None
class TestPriceDataReloadIntegration:
"""Integration tests for the complete price data reload feature"""
@pytest.fixture(autouse=True)
def _flush_litellm_config_cache(self):
from litellm.proxy.utils import litellm_config_cache
litellm_config_cache.flush_cache()
yield
litellm_config_cache.flush_cache()
@pytest.fixture
def client_with_auth(self):
"""Create a test client with authentication"""
from litellm.proxy._types import LitellmUserRoles
from litellm.proxy.proxy_server import cleanup_router_config_variables
cleanup_router_config_variables()
filepath = os.path.dirname(os.path.abspath(__file__))
config_fp = f"{filepath}/test_configs/test_config_no_auth.yaml"
asyncio.run(initialize(config=config_fp, debug=True))
# Mock admin user authentication
mock_auth = MagicMock()
mock_auth.user_role = LitellmUserRoles.PROXY_ADMIN
app.dependency_overrides[user_api_key_auth] = lambda: mock_auth
return TestClient(app)
def test_complete_reload_flow(self, client_with_auth):
"""Test the complete reload flow from API to model cost update"""
# Mock the model cost map
mock_cost_map = {
"gpt-3.5-turbo": {
"input_cost_per_token": 0.001,
"output_cost_per_token": 0.002,
},
"gpt-4": {"input_cost_per_token": 0.03, "output_cost_per_token": 0.06},
}
original_model_cost = litellm.model_cost.copy()
try:
with patch(
"litellm.litellm_core_utils.get_model_cost_map.get_model_cost_map"
) as mock_get_map:
mock_get_map.return_value = mock_cost_map
# Mock the database connection
with patch("litellm.proxy.proxy_server.prisma_client") as mock_prisma:
mock_prisma.db.litellm_config.find_unique = AsyncMock(
return_value=None
)
mock_prisma.db.litellm_config.upsert = AsyncMock(return_value=None)
# Test reload endpoint
response = client_with_auth.post("/reload/model_cost_map")
assert response.status_code == 200
# Test get endpoint
response = client_with_auth.get("/public/litellm_model_cost_map")
assert response.status_code == 200
finally:
litellm.model_cost = original_model_cost
_invalidate_model_cost_lowercase_map()
def test_distributed_reload_check_function(self):
"""Test the _check_and_reload_model_cost_map function"""
from litellm.proxy.proxy_server import ProxyConfig
from litellm.proxy.utils import litellm_config_cache
proxy_config = ProxyConfig()
# Mock prisma client
mock_prisma = MagicMock()
# Test case 1: No config in database
mock_prisma.db.litellm_config.find_unique = AsyncMock(return_value=None)
# _check_and_reload_model_cost_map routes through get_config_param,
# which calls prisma.get_generic_data on a cache miss.
mock_prisma.get_generic_data = AsyncMock(return_value=None)
# Should return early without reloading
asyncio.run(proxy_config._check_and_reload_model_cost_map(mock_prisma))
# Test case 2: Config with interval but not time to reload
litellm_config_cache.flush_cache()
mock_config = MagicMock()
mock_config.param_value = {"interval_hours": 6, "force_reload": False}
mock_prisma.db.litellm_config.find_unique = AsyncMock(return_value=mock_config)
mock_prisma.get_generic_data = AsyncMock(return_value=mock_config)
# Mock current time and last reload time
with patch(
"litellm.proxy.proxy_server.last_model_cost_map_reload",
"2024-01-01T06:00:00",
):
with patch("litellm.proxy.proxy_server.datetime") as mock_datetime:
mock_datetime.utcnow.return_value = datetime(
2024, 1, 1, 7, 0, 0
) # 1 hour later
# Should not reload (only 1 hour passed, need 6)
asyncio.run(proxy_config._check_and_reload_model_cost_map(mock_prisma))
# Test case 3: Config with force reload
litellm_config_cache.flush_cache()
mock_config.param_value = {"interval_hours": 6, "force_reload": True}
mock_prisma.db.litellm_config.find_unique = AsyncMock(return_value=mock_config)
mock_prisma.get_generic_data = AsyncMock(return_value=mock_config)
mock_prisma.db.litellm_config.upsert = AsyncMock(return_value=None)
original_model_cost = litellm.model_cost.copy()
try:
with patch(
"litellm.litellm_core_utils.get_model_cost_map.get_model_cost_map"
) as mock_get_map:
mock_get_map.return_value = {
"gpt-3.5-turbo": {"input_cost_per_token": 0.001}
}
# Should reload due to force flag
asyncio.run(proxy_config._check_and_reload_model_cost_map(mock_prisma))
# Verify force_reload was reset to False
mock_prisma.db.litellm_config.upsert.assert_called()
call_args = mock_prisma.db.litellm_config.upsert.call_args
# The param_value is now a JSON string, so we need to parse it
param_value_json = call_args[1]["data"]["update"]["param_value"]
param_value_dict = json.loads(param_value_json)
assert param_value_dict["force_reload"] == False
assert param_value_dict.get("interval_hours") == 6
finally:
litellm.model_cost = original_model_cost
_invalidate_model_cost_lowercase_map()
def test_distributed_reload_preserves_interval_hours(self):
"""Test that _check_and_reload_model_cost_map preserves interval_hours after reload.
Regression test: the update branch of the upsert was previously dropping
interval_hours, causing scheduled reloads to self-destruct after first execution.
"""
from litellm.proxy.proxy_server import ProxyConfig
proxy_config = ProxyConfig()
mock_prisma = MagicMock()
# Set up config with interval_hours=24 and force_reload=True to trigger reload
mock_config = MagicMock()
mock_config.param_value = {"interval_hours": 24, "force_reload": True}
mock_prisma.db.litellm_config.find_unique = AsyncMock(return_value=mock_config)
# _check_and_reload_model_cost_map now reads through get_generic_data.
mock_prisma.get_generic_data = AsyncMock(return_value=mock_config)
mock_prisma.db.litellm_config.upsert = AsyncMock(return_value=None)
original_model_cost = litellm.model_cost.copy()
try:
with patch(
"litellm.litellm_core_utils.get_model_cost_map.get_model_cost_map"
) as mock_get_map:
mock_get_map.return_value = {"gpt-4": {"input_cost_per_token": 0.001}}
asyncio.run(proxy_config._check_and_reload_model_cost_map(mock_prisma))
# Verify the upsert update branch preserves interval_hours
mock_prisma.db.litellm_config.upsert.assert_called()
call_args = mock_prisma.db.litellm_config.upsert.call_args
param_value_json = call_args[1]["data"]["update"]["param_value"]
param_value_dict = json.loads(param_value_json)
assert param_value_dict["force_reload"] == False
assert param_value_dict["interval_hours"] == 24, (
"interval_hours must be preserved in the update branch; "
"dropping it causes the schedule to self-destruct"
)
finally:
litellm.model_cost = original_model_cost
_invalidate_model_cost_lowercase_map()
def test_manual_reload_preserves_interval_hours(self):
"""Test that manual reload via /reload/model_cost_map preserves existing interval_hours.
Regression test: the manual reload endpoint was overwriting param_value with
only force_reload=True, dropping any existing interval_hours schedule.
"""
from litellm.proxy._types import LitellmUserRoles
from litellm.proxy.proxy_server import cleanup_router_config_variables
cleanup_router_config_variables()
filepath = os.path.dirname(os.path.abspath(__file__))
config_fp = f"{filepath}/test_configs/test_config_no_auth.yaml"
asyncio.run(initialize(config=config_fp, debug=True))
mock_auth = MagicMock()
mock_auth.user_role = LitellmUserRoles.PROXY_ADMIN
app.dependency_overrides[user_api_key_auth] = lambda: mock_auth
client = TestClient(app)
original_model_cost = litellm.model_cost.copy()
try:
with patch(
"litellm.litellm_core_utils.get_model_cost_map.get_model_cost_map"
) as mock_get_map:
mock_get_map.return_value = {"gpt-4": {"input_cost_per_token": 0.001}}
with patch("litellm.proxy.proxy_server.prisma_client") as mock_prisma:
# Simulate existing config with a schedule
mock_existing = MagicMock()
mock_existing.param_value = {
"interval_hours": 12,
"force_reload": False,
}
mock_prisma.db.litellm_config.find_unique = AsyncMock(
return_value=mock_existing
)
mock_prisma.db.litellm_config.upsert = AsyncMock(return_value=None)
response = client.post("/reload/model_cost_map")
assert response.status_code == 200
# Verify interval_hours was preserved in the upsert
mock_prisma.db.litellm_config.upsert.assert_called()
call_args = mock_prisma.db.litellm_config.upsert.call_args
param_value_json = call_args[1]["data"]["update"]["param_value"]
param_value_dict = json.loads(param_value_json)
assert param_value_dict["force_reload"] == True
assert param_value_dict["interval_hours"] == 12, (
"interval_hours must be preserved when manual reload sets force_reload; "
"dropping it destroys any existing schedule"
)
finally:
litellm.model_cost = original_model_cost
_invalidate_model_cost_lowercase_map()
def test_anthropic_beta_headers_reload_preserves_interval_hours(self):
"""Test that _check_and_reload_anthropic_beta_headers preserves interval_hours after reload.
Regression test: the update branch of the upsert was dropping interval_hours,
identical to the model cost map bug.
"""
from litellm.proxy.proxy_server import ProxyConfig
proxy_config = ProxyConfig()
mock_prisma = MagicMock()
# Set up config with interval_hours=12 and force_reload=True to trigger reload
mock_config = MagicMock()
mock_config.param_value = {"interval_hours": 12, "force_reload": True}
mock_prisma.db.litellm_config.find_unique = AsyncMock(return_value=mock_config)
# _check_and_reload_anthropic_beta_headers now reads through get_generic_data.
mock_prisma.get_generic_data = AsyncMock(return_value=mock_config)
mock_prisma.db.litellm_config.upsert = AsyncMock(return_value=None)
with patch(
"litellm.anthropic_beta_headers_manager.reload_beta_headers_config"
) as mock_reload:
mock_reload.return_value = {"anthropic": {"beta_header": "test-value"}}
asyncio.run(
proxy_config._check_and_reload_anthropic_beta_headers(mock_prisma)
)
# Verify the upsert update branch preserves interval_hours
mock_prisma.db.litellm_config.upsert.assert_called()
call_args = mock_prisma.db.litellm_config.upsert.call_args
param_value_json = call_args[1]["data"]["update"]["param_value"]
param_value_dict = json.loads(param_value_json)
assert param_value_dict["force_reload"] == False
assert param_value_dict["interval_hours"] == 12, (
"interval_hours must be preserved in the update branch; "
"dropping it causes the schedule to self-destruct"
)
def test_anthropic_beta_headers_manual_reload_preserves_interval_hours(self):
"""Test that manual reload via /reload/anthropic_beta_headers preserves existing interval_hours.
Regression test: the manual reload endpoint was overwriting param_value with
only force_reload=True, dropping any existing interval_hours schedule.
"""
from litellm.proxy._types import LitellmUserRoles
from litellm.proxy.proxy_server import cleanup_router_config_variables
cleanup_router_config_variables()
filepath = os.path.dirname(os.path.abspath(__file__))
config_fp = f"{filepath}/test_configs/test_config_no_auth.yaml"
asyncio.run(initialize(config=config_fp, debug=True))
mock_auth = MagicMock()
mock_auth.user_role = LitellmUserRoles.PROXY_ADMIN
app.dependency_overrides[user_api_key_auth] = lambda: mock_auth
client = TestClient(app)
with patch(
"litellm.anthropic_beta_headers_manager.reload_beta_headers_config"
) as mock_reload:
mock_reload.return_value = {"anthropic": {"beta_header": "test-value"}}
with patch("litellm.proxy.proxy_server.prisma_client") as mock_prisma:
# Simulate existing config with a schedule
mock_existing = MagicMock()
mock_existing.param_value = {"interval_hours": 8, "force_reload": False}
mock_prisma.db.litellm_config.find_unique = AsyncMock(
return_value=mock_existing
)
mock_prisma.db.litellm_config.upsert = AsyncMock(return_value=None)
response = client.post("/reload/anthropic_beta_headers")
assert response.status_code == 200
# Verify interval_hours was preserved in the upsert
mock_prisma.db.litellm_config.upsert.assert_called()
call_args = mock_prisma.db.litellm_config.upsert.call_args
param_value_json = call_args[1]["data"]["update"]["param_value"]
param_value_dict = json.loads(param_value_json)
assert param_value_dict["force_reload"] == True
assert param_value_dict["interval_hours"] == 8, (
"interval_hours must be preserved when manual reload sets force_reload; "
"dropping it destroys any existing schedule"
)
def test_config_file_parsing(self):
"""Test parsing of config file with reload settings"""
config_content = """
general_settings:
master_key: sk-1234
model_cost_map_reload_interval: 21600
model_list:
- model_name: gpt-3.5-turbo
litellm_params:
model: gpt-3.5-turbo
- model_name: gpt-4
litellm_params:
model: gpt-4
"""
# Parse the config
config = yaml.safe_load(config_content)
# Verify the reload setting is present
assert "general_settings" in config
assert "model_cost_map_reload_interval" in config["general_settings"]
assert config["general_settings"]["model_cost_map_reload_interval"] == 21600
# Verify models are present
assert "model_list" in config
assert len(config["model_list"]) == 2
def test_database_config_storage(self):
"""Test that configuration is properly stored in database"""
# Mock prisma client
mock_prisma = MagicMock()
# Test the database upsert call that would be made by the schedule endpoint
mock_prisma.db.litellm_config.upsert = AsyncMock(return_value=None)
# Simulate the database call that the schedule endpoint would make
asyncio.run(
mock_prisma.db.litellm_config.upsert(
where={"param_name": "model_cost_map_reload_config"},
data={
"create": {
"param_name": "model_cost_map_reload_config",
"param_value": {"interval_hours": 6, "force_reload": False},
},
"update": {
"param_value": {"interval_hours": 6, "force_reload": False}
},
},
)
)
# Verify database upsert was called with correct data
mock_prisma.db.litellm_config.upsert.assert_called_once()
call_args = mock_prisma.db.litellm_config.upsert.call_args
assert call_args[1]["where"]["param_name"] == "model_cost_map_reload_config"
assert call_args[1]["data"]["create"]["param_value"]["interval_hours"] == 6
assert call_args[1]["data"]["create"]["param_value"]["force_reload"] == False
def test_manual_reload_force_flag(self):
"""Test that manual reload sets force flag correctly"""
# Mock prisma client
mock_prisma = MagicMock()
# Test the database upsert call that would be made by the manual reload endpoint
mock_prisma.db.litellm_config.upsert = AsyncMock(return_value=None)
# Simulate the database call that the manual reload endpoint would make
asyncio.run(
mock_prisma.db.litellm_config.upsert(
where={"param_name": "model_cost_map_reload_config"},
data={
"create": {
"param_name": "model_cost_map_reload_config",
"param_value": {"interval_hours": None, "force_reload": True},
},
"update": {"param_value": {"force_reload": True}},
},
)
)
# Verify force_reload flag was set
mock_prisma.db.litellm_config.upsert.assert_called_once()
call_args = mock_prisma.db.litellm_config.upsert.call_args
assert call_args[1]["data"]["update"]["param_value"]["force_reload"] == True
@pytest.mark.asyncio
async def test_add_router_settings_from_db_config_merge_logic():
"""
Test the _add_router_settings_from_db_config method's merge logic.
This tests how router settings from config file and database are combined,
including scenarios where nested dictionaries should be properly merged.
"""
from unittest.mock import AsyncMock, MagicMock, patch
from litellm.proxy.proxy_server import ProxyConfig
# Create ProxyConfig instance
proxy_config = ProxyConfig()
# Mock router
mock_router = MagicMock()
mock_router.update_settings = MagicMock()
# Test Case 1: Both config and DB settings exist - should merge them
config_data = {
"router_settings": {
"routing_strategy": "usage-based-routing",
"model_group_alias": {"gpt-4": "openai-gpt-4"},
"enable_pre_call_checks": True,
"timeout": 30,
"nested_config": {"setting1": "config_value1", "setting2": "config_value2"},
}
}
# Mock database config record
mock_db_config = MagicMock()
mock_db_config.param_value = {
"routing_strategy": "least-busy", # This should override config value
"retry_delay": 2, # This is new, should be added
"nested_config": {
"setting2": "db_value2", # This should override config value
"setting3": "db_value3", # This is new, should be added
},
}
# Mock prisma client
mock_prisma_client = MagicMock()
mock_prisma_client.db.litellm_config.find_first = AsyncMock(
return_value=mock_db_config
)
# Call the method under test
await proxy_config._add_router_settings_from_db_config(
config_data=config_data,
llm_router=mock_router,
prisma_client=mock_prisma_client,
)
# Verify find_first was called with correct parameters
mock_prisma_client.db.litellm_config.find_first.assert_called_once_with(
where={"param_name": "router_settings"}
)
# Verify update_settings was called
mock_router.update_settings.assert_called_once()
# Get the actual settings passed to update_settings
call_args = mock_router.update_settings.call_args
combined_settings = call_args[1] # kwargs
# Verify the merge results
# DB values should override config values
assert combined_settings["routing_strategy"] == "least-busy"
# Config-only values should be preserved
assert combined_settings["model_group_alias"] == {"gpt-4": "openai-gpt-4"}
assert combined_settings["enable_pre_call_checks"] == True
assert combined_settings["timeout"] == 30
# DB-only values should be added
assert combined_settings["retry_delay"] == 2
# Nested dictionaries should be merged (but this is shallow merge)
expected_nested = {
"setting1": "config_value1",
"setting2": "db_value2",
"setting3": "db_value3",
}
assert combined_settings["nested_config"] == expected_nested
@pytest.mark.asyncio
async def test_add_router_settings_from_db_config_edge_cases():
"""
Test edge cases for _add_router_settings_from_db_config method.
"""
from unittest.mock import AsyncMock, MagicMock
from litellm.proxy.proxy_server import ProxyConfig
proxy_config = ProxyConfig()
mock_router = MagicMock()
mock_router.update_settings = MagicMock()
# Test Case 1: No router provided
await proxy_config._add_router_settings_from_db_config(
config_data={"router_settings": {"test": "value"}},
llm_router=None,
prisma_client=MagicMock(),
)
# Should not call anything when router is None
mock_router.update_settings.assert_not_called()
# Test Case 2: No prisma client provided
await proxy_config._add_router_settings_from_db_config(
config_data={"router_settings": {"test": "value"}},
llm_router=mock_router,
prisma_client=None,
)
# Should not call anything when prisma_client is None
mock_router.update_settings.assert_not_called()
# Test Case 3: DB returns None (no router_settings in DB)
mock_prisma_client = MagicMock()
mock_prisma_client.db.litellm_config.find_first = AsyncMock(return_value=None)
config_data = {"router_settings": {"routing_strategy": "usage-based"}}
await proxy_config._add_router_settings_from_db_config(
config_data=config_data,
llm_router=mock_router,
prisma_client=mock_prisma_client,
)
# Should use only config settings
mock_router.update_settings.assert_called_once_with(routing_strategy="usage-based")
mock_router.reset_mock()
# Test Case 4: Config has no router_settings
mock_db_config = MagicMock()
mock_db_config.param_value = {"db_setting": "db_value"}
mock_prisma_client.db.litellm_config.find_first = AsyncMock(
return_value=mock_db_config
)
await proxy_config._add_router_settings_from_db_config(
config_data={}, # No router_settings in config
llm_router=mock_router,
prisma_client=mock_prisma_client,
)
# Should use only DB settings
mock_router.update_settings.assert_called_once_with(db_setting="db_value")
mock_router.reset_mock()
# Test Case 5: Both config and DB router_settings are None/empty
mock_prisma_client.db.litellm_config.find_first = AsyncMock(return_value=None)
await proxy_config._add_router_settings_from_db_config(
config_data={}, llm_router=mock_router, prisma_client=mock_prisma_client
)
# Should not call update_settings when no settings exist
mock_router.update_settings.assert_not_called()
# Test Case 6: DB config exists but param_value is not a dict
mock_db_config_invalid = MagicMock()
mock_db_config_invalid.param_value = "not_a_dict"
mock_prisma_client.db.litellm_config.find_first = AsyncMock(
return_value=mock_db_config_invalid
)
config_data = {"router_settings": {"config_setting": "config_value"}}
await proxy_config._add_router_settings_from_db_config(
config_data=config_data,
llm_router=mock_router,
prisma_client=mock_prisma_client,
)
# Should use only config settings when DB param_value is invalid
mock_router.update_settings.assert_called_once_with(config_setting="config_value")
@pytest.mark.asyncio
async def test_add_router_settings_shallow_merge_behavior():
"""
Test that the merge behavior is shallow (nested dicts get replaced, not merged).
This documents the current behavior using _update_dictionary.
"""
from unittest.mock import AsyncMock, MagicMock
from litellm.proxy.proxy_server import ProxyConfig
proxy_config = ProxyConfig()
mock_router = MagicMock()
mock_router.update_settings = MagicMock()
# Config with nested dictionary
config_data = {
"router_settings": {
"nested_setting": {
"key1": "config_value1",
"key2": "config_value2",
"key3": "config_value3",
},
"top_level": "config_top",
}
}
# DB config that partially overlaps the nested dictionary
mock_db_config = MagicMock()
mock_db_config.param_value = {
"nested_setting": {
"key2": "db_value2", # Override existing key
"key4": "db_value4", # Add new key
# Note: key1 and key3 from config will be lost due to shallow merge
},
"top_level": "db_top", # Override top level
}
mock_prisma_client = MagicMock()
mock_prisma_client.db.litellm_config.find_first = AsyncMock(
return_value=mock_db_config
)
await proxy_config._add_router_settings_from_db_config(
config_data=config_data,
llm_router=mock_router,
prisma_client=mock_prisma_client,
)
# Get the merged settings
call_args = mock_router.update_settings.call_args
merged_settings = call_args[1]
# Verify shallow merge behavior:
# The entire nested_setting dict from config is replaced by the DB version
expected_nested = {
"key1": "config_value1",
"key3": "config_value3",
"key2": "db_value2",
"key4": "db_value4",
}
assert merged_settings["nested_setting"] == expected_nested
assert merged_settings["top_level"] == "db_top"
@pytest.mark.asyncio
async def test_model_info_v1_oci_secrets_not_leaked():
"""
Test that model_info_v1 endpoint properly masks OCI sensitive parameters and does not leak secrets.
"""
from unittest.mock import MagicMock, patch
from litellm.proxy._types import UserAPIKeyAuth
from litellm.proxy.proxy_server import model_info_v1
# Mock user authentication
mock_user_api_key_dict = MagicMock(spec=UserAPIKeyAuth)
mock_user_api_key_dict.user_id = "test-user"
mock_user_api_key_dict.api_key = "test-key"
mock_user_api_key_dict.team_models = []
mock_user_api_key_dict.models = ["oci-grok-test"]
# Mock model data with OCI sensitive information
mock_model_data = {
"model_name": "oci-grok-test",
"litellm_params": {
"model": "oci/xai.grok-4",
"oci_key": "ocid1.api_key.oc1..aaaaaaaa7kbkbkbkbkbkbkbkbkbkbkbkbkbkbkbkbkbkbkbkbkbkbkbkbkbk",
"oci_region": "us-phoenix-1",
"oci_user": "ocid1.user.oc1..aaaaaaaa7kbkbkbkbkbkbkbkbkbkbkbkbkbkbkbkbkbkbkbkbkbkbkbkbkbk",
"oci_fingerprint": "aa:bb:cc:dd:ee:ff:11:22:33:44:55:66:77:88:99:00",
"oci_tenancy": "ocid1.tenancy.oc1..aaaaaaaa7kbkbkbkbkbkbkbkbkbkbkbkbkbkbkbkbkbkbkbkbkbkbkbkbkbk",
"oci_key_file": "/path/to/oci_api_key.pem",
"oci_compartment_id": "ocid1.compartment.oc1..aaaaaaaa7kbkbkbkbkbkbkbkbkbkbkbkbkbkbkbkbkbkbkbkbkbkbkbkbkbk",
"drop_params": True,
},
"model_info": {"mode": "completion", "id": "test-model-id"},
}
# Mock the llm_router to return our test data
mock_router = MagicMock()
mock_router.get_model_names.return_value = ["oci-grok-test"]
mock_router.get_model_access_groups.return_value = {}
mock_router.get_model_list.return_value = [mock_model_data]
# Mock global variables
with (
patch("litellm.proxy.proxy_server.llm_router", mock_router),
patch("litellm.proxy.proxy_server.llm_model_list", [mock_model_data]),
patch(
"litellm.proxy.proxy_server.general_settings",
{"infer_model_from_keys": False},
),
patch("litellm.proxy.proxy_server.user_model", None),
):
# Call the model_info_v1 endpoint
result = await model_info_v1(
user_api_key_dict=mock_user_api_key_dict, litellm_model_id=None
)
# Verify the result structure
assert "data" in result
assert len(result["data"]) == 1
model_info = result["data"][0]
litellm_params = model_info["litellm_params"]
# Verify that sensitive OCI fields are masked
assert "****" in litellm_params["oci_key"], "oci_key should be masked"
assert (
"****" in litellm_params["oci_fingerprint"]
), "oci_fingerprint should be masked"
assert "****" in litellm_params["oci_tenancy"], "oci_tenancy should be masked"
assert "****" in litellm_params["oci_key_file"], "oci_key_file should be masked"
# Verify that non-sensitive fields are NOT masked
assert (
litellm_params["model"] == "oci/xai.grok-4"
), "model field should not be masked"
assert (
litellm_params["oci_region"] == "us-phoenix-1"
), "oci_region should not be masked"
assert litellm_params["drop_params"] is True, "drop_params should not be masked"
# Verify the model field specifically is not masked (this was the original issue)
assert (
"****" not in litellm_params["model"]
), "model field should never be masked"
assert litellm_params["model"].startswith(
"oci/"
), "model should retain its full value"
# Verify that actual secret values are not present in the response
result_str = str(result)
assert (
"ocid1.api_key.oc1..aaaaaaaa7kbkbkbkbkbkbkbkbkbkbkbkbkbkbkbkbkbkbkbkbkbkbkbkbkbk"
not in result_str
)
assert "aa:bb:cc:dd:ee:ff:11:22:33:44:55:66:77:88:99:00" not in result_str
assert (
"ocid1.tenancy.oc1..aaaaaaaa7kbkbkbkbkbkbkbkbkbkbkbkbkbkbkbkbkbkbkbkbkbkbkbkbkbk"
not in result_str
)
assert "/path/to/oci_api_key.pem" not in result_str
def test_add_callback_from_db_to_in_memory_litellm_callbacks():
"""
Test that _add_callback_from_db_to_in_memory_litellm_callbacks correctly adds callbacks
for success, failure, and combined event types.
"""
from unittest.mock import MagicMock, patch
from litellm.proxy.proxy_server import ProxyConfig
proxy_config = ProxyConfig()
# Mock the callback manager
mock_callback_manager = MagicMock()
with patch("litellm.proxy.proxy_server.litellm") as mock_litellm:
# Set up mock litellm attributes
mock_litellm._known_custom_logger_compatible_callbacks = []
mock_litellm.logging_callback_manager = mock_callback_manager
# Test Case 1: Add success callback
mock_success_callbacks = []
proxy_config._add_callback_from_db_to_in_memory_litellm_callbacks(
callback="prometheus",
event_types=["success"],
existing_callbacks=mock_success_callbacks,
)
mock_callback_manager.add_litellm_success_callback.assert_called_once_with(
"prometheus"
)
mock_callback_manager.reset_mock()
# Test Case 2: Add failure callback
mock_failure_callbacks = []
proxy_config._add_callback_from_db_to_in_memory_litellm_callbacks(
callback="langfuse",
event_types=["failure"],
existing_callbacks=mock_failure_callbacks,
)
mock_callback_manager.add_litellm_failure_callback.assert_called_once_with(
"langfuse"
)
mock_callback_manager.reset_mock()
# Test Case 3: Add callback for both success and failure
mock_callbacks = []
proxy_config._add_callback_from_db_to_in_memory_litellm_callbacks(
callback="s3",
event_types=["success", "failure"],
existing_callbacks=mock_callbacks,
)
mock_callback_manager.add_litellm_callback.assert_called_once_with("s3")
mock_callback_manager.reset_mock()
# Test Case 4: Don't add callback if it already exists
existing_callbacks_with_item = ["prometheus"]
proxy_config._add_callback_from_db_to_in_memory_litellm_callbacks(
callback="prometheus",
event_types=["success"],
existing_callbacks=existing_callbacks_with_item,
)
mock_callback_manager.add_litellm_success_callback.assert_not_called()
def test_should_load_db_object_with_supported_db_objects():
"""
Test _should_load_db_object method with supported_db_objects configuration.
Verifies that when supported_db_objects is set, only specified object types
are loaded from the database.
"""
from unittest.mock import patch
from litellm.proxy.proxy_server import ProxyConfig
proxy_config = ProxyConfig()
# Test Case 1: supported_db_objects not set - all objects should be loaded
with patch("litellm.proxy.proxy_server.general_settings", {}):
assert proxy_config._should_load_db_object(object_type="models") is True
assert proxy_config._should_load_db_object(object_type="mcp") is True
assert proxy_config._should_load_db_object(object_type="guardrails") is True
assert proxy_config._should_load_db_object(object_type="vector_stores") is True
# Test Case 2: supported_db_objects set to only load MCP
with patch(
"litellm.proxy.proxy_server.general_settings",
{"supported_db_objects": ["mcp"]},
):
assert proxy_config._should_load_db_object(object_type="models") is False
assert proxy_config._should_load_db_object(object_type="mcp") is True
assert proxy_config._should_load_db_object(object_type="guardrails") is False
assert proxy_config._should_load_db_object(object_type="vector_stores") is False
assert proxy_config._should_load_db_object(object_type="prompts") is False
# Test Case 3: supported_db_objects set to load multiple types
with patch(
"litellm.proxy.proxy_server.general_settings",
{"supported_db_objects": ["mcp", "guardrails", "vector_stores"]},
):
assert proxy_config._should_load_db_object(object_type="models") is False
assert proxy_config._should_load_db_object(object_type="mcp") is True
assert proxy_config._should_load_db_object(object_type="guardrails") is True
assert proxy_config._should_load_db_object(object_type="vector_stores") is True
assert proxy_config._should_load_db_object(object_type="prompts") is False
# Test Case 4: supported_db_objects is not a list (should default to loading all)
with patch(
"litellm.proxy.proxy_server.general_settings",
{"supported_db_objects": "invalid_type"},
):
assert proxy_config._should_load_db_object(object_type="models") is True
assert proxy_config._should_load_db_object(object_type="mcp") is True
# Test Case 5: supported_db_objects is an empty list (nothing should be loaded)
with patch(
"litellm.proxy.proxy_server.general_settings",
{"supported_db_objects": []},
):
assert proxy_config._should_load_db_object(object_type="models") is False
assert proxy_config._should_load_db_object(object_type="mcp") is False
assert proxy_config._should_load_db_object(object_type="guardrails") is False
# Test Case 6: Test all available object types
with patch(
"litellm.proxy.proxy_server.general_settings",
{
"supported_db_objects": [
"models",
"mcp",
"guardrails",
"vector_stores",
"pass_through_endpoints",
"prompts",
"model_cost_map",
]
},
):
assert proxy_config._should_load_db_object(object_type="models") is True
assert proxy_config._should_load_db_object(object_type="mcp") is True
assert proxy_config._should_load_db_object(object_type="guardrails") is True
assert proxy_config._should_load_db_object(object_type="vector_stores") is True
assert (
proxy_config._should_load_db_object(object_type="pass_through_endpoints")
is True
)
assert proxy_config._should_load_db_object(object_type="prompts") is True
assert proxy_config._should_load_db_object(object_type="model_cost_map") is True
@pytest.mark.asyncio
async def test_tag_cache_update_called():
"""
Test that update_cache updates tag cache when tags are provided.
"""
from litellm.caching.caching import DualCache
from litellm.proxy.proxy_server import user_api_key_cache
cache = DualCache()
setattr(
litellm.proxy.proxy_server,
"user_api_key_cache",
cache,
)
mock_tag_obj = {
"tag_name": "test-tag",
"spend": 10.0,
}
with patch.object(
cache, "async_get_cache", new=AsyncMock(return_value=mock_tag_obj)
) as mock_get_cache:
with patch.object(
cache, "async_set_cache_pipeline", new=AsyncMock()
) as mock_set_cache:
await litellm.proxy.proxy_server.update_cache(
token=None,
user_id=None,
end_user_id=None,
team_id=None,
response_cost=5.0,
parent_otel_span=None,
tags=["test-tag"],
)
await asyncio.sleep(0.1)
mock_get_cache.assert_awaited_once_with(key="tag:test-tag")
mock_set_cache.assert_awaited_once()
call_args = mock_set_cache.call_args
cache_list = call_args.kwargs["cache_list"]
assert len(cache_list) == 1
cache_key, cache_value = cache_list[0]
assert cache_key == "tag:test-tag"
assert cache_value["spend"] == 15.0
@pytest.mark.asyncio
async def test_tag_cache_update_multiple_tags():
"""
Test that multiple tags are updated in cache.
"""
from litellm.caching.caching import DualCache
from litellm.proxy.proxy_server import user_api_key_cache
cache = DualCache()
setattr(
litellm.proxy.proxy_server,
"user_api_key_cache",
cache,
)
mock_tag1_obj = {"tag_name": "tag1", "spend": 10.0}
mock_tag2_obj = {"tag_name": "tag2", "spend": 20.0}
async def mock_get_cache_side_effect(key):
if key == "tag:tag1":
return mock_tag1_obj
elif key == "tag:tag2":
return mock_tag2_obj
return None
with patch.object(
cache, "async_get_cache", new=AsyncMock(side_effect=mock_get_cache_side_effect)
) as mock_get_cache:
with patch.object(
cache, "async_set_cache_pipeline", new=AsyncMock()
) as mock_set_cache:
await litellm.proxy.proxy_server.update_cache(
token=None,
user_id=None,
end_user_id=None,
team_id=None,
response_cost=5.0,
parent_otel_span=None,
tags=["tag1", "tag2"],
)
await asyncio.sleep(0.1)
assert mock_get_cache.call_count == 2
mock_set_cache.assert_awaited_once()
call_args = mock_set_cache.call_args
cache_list = call_args.kwargs["cache_list"]
assert len(cache_list) == 2
tag_updates = {
cache_key: cache_value for cache_key, cache_value in cache_list
}
assert "tag:tag1" in tag_updates
assert "tag:tag2" in tag_updates
assert tag_updates["tag:tag1"]["spend"] == 15.0
assert tag_updates["tag:tag2"]["spend"] == 25.0
@pytest.mark.asyncio
async def test_init_sso_settings_in_db():
"""
Test that _init_sso_settings_in_db properly loads SSO settings from database,
uppercases keys, and calls _decrypt_and_set_db_env_variables.
"""
from unittest.mock import AsyncMock, MagicMock, patch
from litellm.proxy.proxy_server import ProxyConfig
proxy_config = ProxyConfig()
# Test Case 1: SSO settings exist in database
mock_sso_config = MagicMock()
mock_sso_config.sso_settings = {
"google_client_id": "test-client-id",
"google_client_secret": "test-client-secret",
"microsoft_client_id": "ms-client-id",
"microsoft_client_secret": "ms-client-secret",
}
mock_prisma_client = MagicMock()
mock_prisma_client.db.litellm_ssoconfig.find_unique = AsyncMock(
return_value=mock_sso_config
)
# Mock _decrypt_and_set_db_env_variables
with patch.object(
proxy_config, "_decrypt_and_set_db_env_variables"
) as mock_decrypt_and_set:
await proxy_config._init_sso_settings_in_db(prisma_client=mock_prisma_client)
# Verify find_unique was called with correct parameters
mock_prisma_client.db.litellm_ssoconfig.find_unique.assert_awaited_once_with(
where={"id": "sso_config"}
)
# Verify _decrypt_and_set_db_env_variables was called with uppercased keys
mock_decrypt_and_set.assert_called_once()
call_args = mock_decrypt_and_set.call_args
uppercased_settings = call_args.kwargs["environment_variables"]
# Verify all keys are uppercased
assert "GOOGLE_CLIENT_ID" in uppercased_settings
assert "GOOGLE_CLIENT_SECRET" in uppercased_settings
assert "MICROSOFT_CLIENT_ID" in uppercased_settings
assert "MICROSOFT_CLIENT_SECRET" in uppercased_settings
# Verify values are preserved
assert uppercased_settings["GOOGLE_CLIENT_ID"] == "test-client-id"
assert uppercased_settings["GOOGLE_CLIENT_SECRET"] == "test-client-secret"
assert uppercased_settings["MICROSOFT_CLIENT_ID"] == "ms-client-id"
assert uppercased_settings["MICROSOFT_CLIENT_SECRET"] == "ms-client-secret"
# Verify original lowercase keys are not present
assert "google_client_id" not in uppercased_settings
assert "microsoft_client_id" not in uppercased_settings
@pytest.mark.asyncio
async def test_init_sso_settings_in_db_no_settings():
"""
Test that _init_sso_settings_in_db handles the case when no SSO settings exist in database.
"""
from unittest.mock import AsyncMock, MagicMock, patch
from litellm.proxy.proxy_server import ProxyConfig
proxy_config = ProxyConfig()
# Mock prisma client to return None (no SSO settings)
mock_prisma_client = MagicMock()
mock_prisma_client.db.litellm_ssoconfig.find_unique = AsyncMock(return_value=None)
# Mock _decrypt_and_set_db_env_variables
with patch.object(
proxy_config, "_decrypt_and_set_db_env_variables"
) as mock_decrypt_and_set:
await proxy_config._init_sso_settings_in_db(prisma_client=mock_prisma_client)
# Verify find_unique was called
mock_prisma_client.db.litellm_ssoconfig.find_unique.assert_awaited_once_with(
where={"id": "sso_config"}
)
# Verify _decrypt_and_set_db_env_variables was NOT called when no settings exist
mock_decrypt_and_set.assert_not_called()
@pytest.mark.asyncio
async def test_init_sso_settings_in_db_error_handling():
"""
Test that _init_sso_settings_in_db handles database errors gracefully.
"""
from unittest.mock import AsyncMock, MagicMock, patch
from litellm.proxy.proxy_server import ProxyConfig
proxy_config = ProxyConfig()
# Mock prisma client to raise an exception
mock_prisma_client = MagicMock()
mock_prisma_client.db.litellm_ssoconfig.find_unique = AsyncMock(
side_effect=Exception("Database connection error")
)
# The method should not raise an exception, it should log it instead
try:
await proxy_config._init_sso_settings_in_db(prisma_client=mock_prisma_client)
# If we get here, the exception was handled properly
assert True
except Exception as e:
# The exception should be caught and logged, not propagated
pytest.fail(
f"Exception should have been caught and logged, but was raised: {e}"
)
@pytest.mark.asyncio
async def test_init_sso_settings_in_db_empty_settings():
"""
Test that _init_sso_settings_in_db handles empty SSO settings dictionary.
"""
from unittest.mock import AsyncMock, MagicMock, patch
from litellm.proxy.proxy_server import ProxyConfig
proxy_config = ProxyConfig()
# Mock SSO config with empty settings dictionary
mock_sso_config = MagicMock()
mock_sso_config.sso_settings = {}
mock_prisma_client = MagicMock()
mock_prisma_client.db.litellm_ssoconfig.find_unique = AsyncMock(
return_value=mock_sso_config
)
# Mock _decrypt_and_set_db_env_variables
with patch.object(
proxy_config, "_decrypt_and_set_db_env_variables"
) as mock_decrypt_and_set:
await proxy_config._init_sso_settings_in_db(prisma_client=mock_prisma_client)
# Verify find_unique was called
mock_prisma_client.db.litellm_ssoconfig.find_unique.assert_awaited_once_with(
where={"id": "sso_config"}
)
# Verify _decrypt_and_set_db_env_variables was called with empty dict
mock_decrypt_and_set.assert_called_once()
call_args = mock_decrypt_and_set.call_args
uppercased_settings = call_args.kwargs["environment_variables"]
# Verify empty dictionary
assert uppercased_settings == {}
def test_update_config_fields_uppercases_env_vars(monkeypatch):
"""
Ensure environment variables pulled from DB are uppercased when applied so
integrations like Datadog that expect uppercase env keys can read them.
"""
from litellm.proxy.proxy_server import ProxyConfig
for key in ["DD_API_KEY", "DD_SITE", "dd_api_key", "dd_site"]:
monkeypatch.delenv(key, raising=False)
proxy_config = ProxyConfig()
updated_config = proxy_config._update_config_fields(
current_config={},
param_name="environment_variables",
db_param_value={"dd_api_key": "test-api-key", "dd_site": "us5.datadoghq.com"},
)
env_vars = updated_config.get("environment_variables", {})
assert env_vars["DD_API_KEY"] == "test-api-key"
assert env_vars["DD_SITE"] == "us5.datadoghq.com"
assert os.environ.get("DD_API_KEY") == "test-api-key"
assert os.environ.get("DD_SITE") == "us5.datadoghq.com"
def test_get_prompt_spec_for_db_prompt_with_versions():
"""
Test that _get_prompt_spec_for_db_prompt correctly converts database prompts
to PromptSpec with versioned naming convention.
"""
from unittest.mock import MagicMock
from litellm.proxy.proxy_server import ProxyConfig
proxy_config = ProxyConfig()
# Mock database prompt version 1
mock_prompt_v1 = MagicMock()
mock_prompt_v1.model_dump.return_value = {
"id": "uuid-1",
"prompt_id": "chat_prompt",
"version": 1,
"litellm_params": '{"prompt_id": "chat_prompt", "prompt_integration": "dotprompt", "model": "gpt-3.5-turbo", "messages": [{"role": "user", "content": "v1 content"}]}',
"prompt_info": '{"prompt_type": "db"}',
"created_at": "2024-01-01T00:00:00",
"updated_at": "2024-01-01T00:00:00",
}
# Mock database prompt version 2
mock_prompt_v2 = MagicMock()
mock_prompt_v2.model_dump.return_value = {
"id": "uuid-2",
"prompt_id": "chat_prompt",
"version": 2,
"litellm_params": '{"prompt_id": "chat_prompt", "prompt_integration": "dotprompt", "model": "gpt-4", "messages": [{"role": "user", "content": "v2 content"}]}',
"prompt_info": '{"prompt_type": "db"}',
"created_at": "2024-01-02T00:00:00",
"updated_at": "2024-01-02T00:00:00",
}
# Test version 1
prompt_spec_v1 = proxy_config._get_prompt_spec_for_db_prompt(
db_prompt=mock_prompt_v1
)
assert prompt_spec_v1.prompt_id == "chat_prompt.v1"
# Test version 2
prompt_spec_v2 = proxy_config._get_prompt_spec_for_db_prompt(
db_prompt=mock_prompt_v2
)
assert prompt_spec_v2.prompt_id == "chat_prompt.v2"
def test_root_redirect_when_docs_url_not_root_and_redirect_url_set(monkeypatch):
from fastapi.responses import RedirectResponse
from litellm.proxy.proxy_server import cleanup_router_config_variables
from litellm.proxy.utils import _get_docs_url
cleanup_router_config_variables()
filepath = os.path.dirname(os.path.abspath(__file__))
config_fp = f"{filepath}/test_configs/test_config_no_auth.yaml"
# Ensure docs are mounted on a non-root path to trigger redirect logic
monkeypatch.setenv("DOCS_URL", "/docs")
test_redirect_url = "/ui"
monkeypatch.setenv("ROOT_REDIRECT_URL", test_redirect_url)
asyncio.run(initialize(config=config_fp, debug=True))
docs_url = _get_docs_url()
root_redirect_url = os.getenv("ROOT_REDIRECT_URL")
# Remove any existing "/" route that might interfere
routes_to_remove = []
for route in app.routes:
if hasattr(route, "path") and route.path == "/":
if hasattr(route, "methods") and "GET" in route.methods:
routes_to_remove.append(route)
elif not hasattr(route, "methods"): # Catch-all routes
routes_to_remove.append(route)
for route in routes_to_remove:
app.routes.remove(route)
# Add the redirect route if conditions are met (matching the actual implementation)
if docs_url != "/" and root_redirect_url:
@app.get("/", include_in_schema=False)
async def root_redirect():
return RedirectResponse(url=root_redirect_url)
client = TestClient(app)
response = client.get("/", follow_redirects=False)
assert response.status_code == 307
assert response.headers["location"] == test_redirect_url
@pytest.mark.asyncio
async def test_get_image_non_root_uses_var_lib_assets_dir(monkeypatch):
"""
Test that get_image uses /var/lib/litellm/assets when LITELLM_NON_ROOT is true.
"""
from unittest.mock import patch
from litellm.proxy.proxy_server import get_image
# Set LITELLM_NON_ROOT to true
monkeypatch.setenv("LITELLM_NON_ROOT", "true")
monkeypatch.delenv("UI_LOGO_PATH", raising=False)
# Mock os.path operations - exists=False for assets_dir so makedirs gets called
def exists_side_effect(path):
return False if path == "/var/lib/litellm/assets" else True
with (
patch("litellm.proxy.proxy_server.os.makedirs") as mock_makedirs,
patch(
"litellm.proxy.proxy_server.os.path.exists", side_effect=exists_side_effect
),
patch("litellm.proxy.proxy_server.os.access", return_value=True),
patch("litellm.proxy.proxy_server.os.getenv") as mock_getenv,
patch("litellm.proxy.proxy_server.FileResponse") as mock_file_response,
):
# Setup mock_getenv to return empty string for UI_LOGO_PATH
def getenv_side_effect(key, default=""):
if key == "UI_LOGO_PATH":
return ""
elif key == "LITELLM_NON_ROOT":
return "true"
return default
mock_getenv.side_effect = getenv_side_effect
# Call the function
await get_image()
# Verify makedirs was called with /var/lib/litellm/assets
mock_makedirs.assert_called_once_with("/var/lib/litellm/assets", exist_ok=True)
@pytest.mark.asyncio
async def test_get_image_non_root_fallback_to_default_logo(monkeypatch):
"""
Test that get_image falls back to default_site_logo when logo doesn't exist
in /var/lib/litellm/assets for non-root case.
"""
from unittest.mock import patch
from litellm.proxy.proxy_server import get_image
# Set LITELLM_NON_ROOT to true
monkeypatch.setenv("LITELLM_NON_ROOT", "true")
monkeypatch.delenv("UI_LOGO_PATH", raising=False)
# Track path.exists calls to verify it checks /var/lib/litellm/assets/logo.jpg
exists_calls = []
def exists_side_effect(path):
exists_calls.append(path)
# Return False for /var/lib/litellm/assets* so: makedirs is called, logo fallback
# triggers, and we don't return early with cached file
if "/var/lib/litellm/assets" in path:
return False
return True
# Mock os.path operations
with (
patch("litellm.proxy.proxy_server.os.makedirs") as mock_makedirs,
patch(
"litellm.proxy.proxy_server.os.path.exists", side_effect=exists_side_effect
),
patch("litellm.proxy.proxy_server.os.access", return_value=True),
patch("litellm.proxy.proxy_server.os.getenv") as mock_getenv,
patch("litellm.proxy.proxy_server.FileResponse") as mock_file_response,
):
# Setup mock_getenv
def getenv_side_effect(key, default=""):
if key == "UI_LOGO_PATH":
return ""
elif key == "LITELLM_NON_ROOT":
return "true"
return default
mock_getenv.side_effect = getenv_side_effect
# Call the function
await get_image()
# Verify makedirs was called with /var/lib/litellm/assets
mock_makedirs.assert_called_once_with("/var/lib/litellm/assets", exist_ok=True)
# Verify that exists was called to check /var/lib/litellm/assets/logo.jpg
assets_logo_path = "/var/lib/litellm/assets/logo.jpg"
assert any(
assets_logo_path in str(call) for call in exists_calls
), f"Should check if {assets_logo_path} exists"
# Verify FileResponse was called (with fallback logo)
assert mock_file_response.called, "FileResponse should be called"
@pytest.mark.asyncio
async def test_get_image_root_case_uses_current_dir(monkeypatch):
"""
Test that get_image uses current_dir when LITELLM_NON_ROOT is not true.
"""
from unittest.mock import patch
from litellm.proxy.proxy_server import get_image
# Don't set LITELLM_NON_ROOT (or set it to false)
monkeypatch.delenv("LITELLM_NON_ROOT", raising=False)
monkeypatch.delenv("UI_LOGO_PATH", raising=False)
# Mock os.path operations
with (
patch("litellm.proxy.proxy_server.os.makedirs") as mock_makedirs,
patch("litellm.proxy.proxy_server.os.path.exists", return_value=True),
patch("litellm.proxy.proxy_server.os.getenv") as mock_getenv,
patch("litellm.proxy.proxy_server.FileResponse") as mock_file_response,
):
# Setup mock_getenv
def getenv_side_effect(key, default=""):
if key == "UI_LOGO_PATH":
return ""
elif key == "LITELLM_NON_ROOT":
return "" # Not set or empty
return default
mock_getenv.side_effect = getenv_side_effect
# Call the function
await get_image()
# Verify makedirs was NOT called with /var/lib/litellm/assets (should not create it for root case)
var_lib_assets_calls = [
call
for call in mock_makedirs.call_args_list
if "/var/lib/litellm/assets" in str(call)
]
assert (
len(var_lib_assets_calls) == 0
), "Should not create /var/lib/litellm/assets for root case"
# Verify FileResponse was called
assert mock_file_response.called, "FileResponse should be called"
@pytest.mark.asyncio
async def test_get_image_custom_local_logo_bypasses_cache(monkeypatch, tmp_path):
"""
Test that when UI_LOGO_PATH is set to a local file, get_image serves it
directly and does not return a stale cached_logo.jpg.
Regression test: previously the cache check ran before reading UI_LOGO_PATH,
so a pre-existing cached_logo.jpg (e.g. from the base Docker image) would
always be returned, ignoring the user's custom logo.
"""
from litellm.proxy.proxy_server import get_image
custom_logo = tmp_path / "custom_logo.jpg"
custom_logo.write_bytes(b"\xff\xd8\xff custom logo")
monkeypatch.setenv("UI_LOGO_PATH", str(custom_logo))
monkeypatch.delenv("LITELLM_NON_ROOT", raising=False)
monkeypatch.delenv("LITELLM_ASSETS_PATH", raising=False)
calls_to_file_response = []
def fake_file_response(path, **kwargs):
calls_to_file_response.append(path)
return MagicMock()
with (
patch(
"litellm.proxy.proxy_server.FileResponse", side_effect=fake_file_response
),
):
await get_image()
assert (
len(calls_to_file_response) == 1
), "FileResponse should be called exactly once"
assert calls_to_file_response[0] == str(custom_logo.resolve()), (
f"Expected custom logo path, got {calls_to_file_response[0]}. "
"A stale cached_logo.jpg may have been returned instead."
)
@pytest.mark.asyncio
async def test_get_image_default_logo_ignores_stale_cache(monkeypatch, tmp_path):
"""
Test that when UI_LOGO_PATH is NOT set, stale pre-fix cached_logo.jpg
files are ignored and the default logo is served.
"""
from unittest.mock import patch
from litellm.proxy.proxy_server import get_image
cache_path = tmp_path / "cached_logo.jpg"
cache_path.write_bytes(b"\xff\xd8\xff cached logo")
monkeypatch.delenv("UI_LOGO_PATH", raising=False)
monkeypatch.delenv("LITELLM_NON_ROOT", raising=False)
monkeypatch.setenv("LITELLM_ASSETS_PATH", str(tmp_path))
calls_to_file_response = []
def fake_file_response(path, **kwargs):
calls_to_file_response.append(path)
return MagicMock()
with (
patch(
"litellm.proxy.proxy_server.FileResponse", side_effect=fake_file_response
),
):
await get_image()
assert (
len(calls_to_file_response) == 1
), "FileResponse should be called exactly once"
served_path = calls_to_file_response[0]
assert served_path != str(cache_path.resolve())
assert served_path.endswith("logo.jpg")
@pytest.mark.asyncio
async def test_get_image_custom_logo_missing_falls_through_to_default(
monkeypatch, tmp_path
):
"""
Test that when UI_LOGO_PATH points to a non-existent local file,
get_image falls through to the default logo instead of failing.
"""
from unittest.mock import patch
from litellm.proxy.proxy_server import get_image
custom_logo_path = tmp_path / "nonexistent_logo.jpg"
monkeypatch.setenv("UI_LOGO_PATH", str(custom_logo_path))
monkeypatch.delenv("LITELLM_NON_ROOT", raising=False)
monkeypatch.setenv("LITELLM_ASSETS_PATH", str(tmp_path))
calls_to_file_response = []
def fake_file_response(path, **kwargs):
calls_to_file_response.append(path)
return MagicMock()
with (
patch(
"litellm.proxy.proxy_server.FileResponse", side_effect=fake_file_response
),
):
await get_image()
assert (
len(calls_to_file_response) == 1
), "FileResponse should be called exactly once"
served_path = calls_to_file_response[0]
assert served_path != str(
custom_logo_path
), "Should not attempt to serve a non-existent custom logo"
assert served_path.endswith("logo.jpg")
@pytest.mark.asyncio
async def test_get_image_custom_logo_missing_no_cache_serves_default(
monkeypatch, tmp_path
):
"""
Test that when UI_LOGO_PATH points to a non-existent file AND there is no
cached_logo.jpg, get_image serves the default logo instead of the non-existent
custom path.
"""
from unittest.mock import patch
from litellm.proxy.proxy_server import get_image
custom_logo_path = tmp_path / "nonexistent_logo.jpg"
monkeypatch.setenv("UI_LOGO_PATH", str(custom_logo_path))
monkeypatch.delenv("LITELLM_NON_ROOT", raising=False)
monkeypatch.setenv("LITELLM_ASSETS_PATH", str(tmp_path))
calls_to_file_response = []
def fake_file_response(path, **kwargs):
calls_to_file_response.append(path)
return MagicMock()
with (
patch(
"litellm.proxy.proxy_server.FileResponse", side_effect=fake_file_response
),
):
await get_image()
assert (
len(calls_to_file_response) == 1
), "FileResponse should be called exactly once"
served_path = calls_to_file_response[0]
assert served_path != str(
custom_logo_path
), "Should not attempt to serve a non-existent custom logo"
assert served_path.endswith(
"logo.jpg"
), f"Expected fallback to default logo.jpg, got {served_path}"
def test_get_config_normalizes_string_callbacks(monkeypatch):
"""
Test that /get/config/callbacks normalizes string callbacks to lists.
"""
from litellm.proxy.proxy_server import app, proxy_config, user_api_key_auth
config_data = {
"litellm_settings": {
"success_callback": "langfuse",
"failure_callback": None,
"callbacks": ["prometheus", "datadog"],
},
"general_settings": {},
"environment_variables": {},
}
mock_router = MagicMock()
mock_router.get_settings.return_value = {}
monkeypatch.setattr("litellm.proxy.proxy_server.llm_router", mock_router)
monkeypatch.setattr(proxy_config, "get_config", AsyncMock(return_value=config_data))
original_overrides = app.dependency_overrides.copy()
app.dependency_overrides[user_api_key_auth] = lambda: MagicMock()
client = TestClient(app)
try:
response = client.get("/get/config/callbacks")
finally:
app.dependency_overrides = original_overrides
assert response.status_code == 200
callbacks = response.json()["callbacks"]
success_callbacks = [cb["name"] for cb in callbacks if cb.get("type") == "success"]
failure_callbacks = [cb["name"] for cb in callbacks if cb.get("type") == "failure"]
success_and_failure_callbacks = [
cb["name"] for cb in callbacks if cb.get("type") == "success_and_failure"
]
assert "langfuse" in success_callbacks
assert len(failure_callbacks) == 0
assert "prometheus" in success_and_failure_callbacks
assert "datadog" in success_and_failure_callbacks
def test_deep_merge_dicts_skips_none_and_empty_lists(monkeypatch):
"""
Test that _update_config_fields deep merge skips None values and empty lists.
"""
from litellm.proxy.proxy_server import ProxyConfig
proxy_config = ProxyConfig()
current_config = {
"general_settings": {
"max_parallel_requests": 10,
"allowed_models": ["gpt-3.5-turbo", "gpt-4"],
"nested": {
"key1": "value1",
"key2": "value2",
},
}
}
db_param_value = {
"max_parallel_requests": None,
"allowed_models": [],
"new_key": "new_value",
"nested": {
"key1": "updated_value1",
"key3": "value3",
},
}
result = proxy_config._update_config_fields(
current_config, "general_settings", db_param_value
)
assert result["general_settings"]["max_parallel_requests"] == 10
assert result["general_settings"]["allowed_models"] == ["gpt-3.5-turbo", "gpt-4"]
assert result["general_settings"]["new_key"] == "new_value"
assert result["general_settings"]["nested"]["key1"] == "updated_value1"
assert result["general_settings"]["nested"]["key2"] == "value2"
assert result["general_settings"]["nested"]["key3"] == "value3"
class TestInvitationEndpoints:
"""Tests for /invitation/new and /invitation/delete endpoints."""
@pytest.fixture
def client_with_auth(self):
"""Create a test client with admin authentication."""
from litellm.proxy._types import LitellmUserRoles
from litellm.proxy.proxy_server import cleanup_router_config_variables
cleanup_router_config_variables()
filepath = os.path.dirname(os.path.abspath(__file__))
config_fp = f"{filepath}/test_configs/test_config_no_auth.yaml"
asyncio.run(initialize(config=config_fp, debug=True))
mock_auth = MagicMock()
mock_auth.user_id = "admin-user-id"
mock_auth.user_role = LitellmUserRoles.PROXY_ADMIN
mock_auth.api_key = "sk-test"
app.dependency_overrides[user_api_key_auth] = lambda: mock_auth
return TestClient(app)
@pytest.mark.parametrize(
"endpoint,payload,mock_return",
[
(
"/invitation/new",
{"user_id": "target-user-123"},
{
"id": "inv-123",
"user_id": "target-user-123",
"is_accepted": False,
"accepted_at": None,
"expires_at": "2025-02-18T00:00:00",
"created_at": "2025-02-11T00:00:00",
"created_by": "admin-user-id",
"updated_at": "2025-02-11T00:00:00",
"updated_by": "admin-user-id",
},
),
(
"/invitation/delete",
{"invitation_id": "inv-456"},
{
"id": "inv-456",
"user_id": "target-user-123",
"is_accepted": False,
"accepted_at": None,
"expires_at": "2025-02-18T00:00:00",
"created_at": "2025-02-11T00:00:00",
"created_by": "admin-user-id",
"updated_at": "2025-02-11T00:00:00",
"updated_by": "admin-user-id",
},
),
],
)
def test_invitation_endpoints_proxy_admin_success(
self, client_with_auth, endpoint, payload, mock_return
):
"""Proxy admin can successfully create and delete invitations."""
with patch("litellm.proxy.proxy_server.prisma_client") as mock_prisma:
mock_prisma.db.litellm_invitationlink = MagicMock()
if endpoint == "/invitation/new":
mock_create = AsyncMock(return_value=mock_return)
with patch(
"litellm.proxy.management_helpers.user_invitation.create_invitation_for_user",
mock_create,
):
response = client_with_auth.post(endpoint, json=payload)
else:
mock_prisma.db.litellm_invitationlink.find_unique = AsyncMock(
return_value={**mock_return, "created_by": "admin-user-id"}
)
mock_prisma.db.litellm_invitationlink.delete = AsyncMock(
return_value=mock_return
)
response = client_with_auth.post(endpoint, json=payload)
assert response.status_code == 200
data = response.json()
assert data["id"] == mock_return["id"]
assert data["user_id"] == mock_return["user_id"]
@pytest.mark.parametrize(
"endpoint,payload",
[
("/invitation/new", {"user_id": "target-user-123"}),
("/invitation/delete", {"invitation_id": "inv-456"}),
],
)
def test_invitation_endpoints_non_admin_denied(
self, client_with_auth, endpoint, payload
):
"""Non-admin users cannot access invitation endpoints."""
from litellm.proxy._types import LitellmUserRoles
mock_auth = MagicMock()
mock_auth.user_id = "regular-user"
mock_auth.user_role = LitellmUserRoles.INTERNAL_USER
mock_auth.api_key = "sk-regular"
app.dependency_overrides[user_api_key_auth] = lambda: mock_auth
with patch("litellm.proxy.proxy_server.prisma_client") as mock_prisma:
mock_prisma.db.litellm_invitationlink = MagicMock()
# Avoid triggering async DB calls in _user_has_admin_privileges
with patch(
"litellm.proxy.proxy_server._user_has_admin_privileges",
new_callable=AsyncMock,
return_value=False,
):
response = client_with_auth.post(endpoint, json=payload)
assert response.status_code == 400
body = response.json()
# ProxyException handler returns {"error": {...}}, HTTPException returns {"detail": {...}}
error_content = body.get("error", body.get("detail", body))
assert "not allowed" in str(error_content).lower()
@pytest.mark.asyncio
async def test_async_data_generator_cleanup_on_early_exit():
"""
Test that async_data_generator calls response.aclose() in the finally block
when the generator is abandoned mid-stream (client disconnect).
"""
from litellm.proxy._types import UserAPIKeyAuth
from litellm.proxy.proxy_server import async_data_generator
from litellm.proxy.utils import ProxyLogging
mock_user_api_key_dict = MagicMock(spec=UserAPIKeyAuth)
mock_request_data = {
"model": "gpt-3.5-turbo",
"messages": [{"role": "user", "content": "test"}],
}
mock_chunks = [
{"choices": [{"delta": {"content": "Hello"}}]},
{"choices": [{"delta": {"content": " world"}}]},
{"choices": [{"delta": {"content": " more"}}]},
]
mock_proxy_logging_obj = MagicMock(spec=ProxyLogging)
async def mock_streaming_iterator(*args, **kwargs):
for chunk in mock_chunks:
yield chunk
mock_proxy_logging_obj.async_post_call_streaming_iterator_hook = (
mock_streaming_iterator
)
mock_proxy_logging_obj.async_post_call_streaming_hook = AsyncMock(
side_effect=lambda **kwargs: kwargs.get("response")
)
mock_proxy_logging_obj.post_call_failure_hook = AsyncMock()
# Create a mock response with aclose
mock_response = MagicMock()
mock_response.aclose = AsyncMock()
with patch("litellm.proxy.proxy_server.proxy_logging_obj", mock_proxy_logging_obj):
# Consume only the first chunk then abandon the generator (simulates client disconnect)
gen = async_data_generator(
mock_response, mock_user_api_key_dict, mock_request_data
)
first_chunk = await gen.__anext__()
assert first_chunk.startswith("data: ")
# Close the generator early (simulates what ASGI does on client disconnect)
await gen.aclose()
# Verify aclose was called on the response to release the HTTP connection
mock_response.aclose.assert_awaited_once()
@pytest.mark.asyncio
async def test_async_data_generator_cleanup_on_normal_completion():
"""
Test that async_data_generator calls response.aclose() even on normal completion.
"""
from litellm.proxy._types import UserAPIKeyAuth
from litellm.proxy.proxy_server import async_data_generator
from litellm.proxy.utils import ProxyLogging
mock_user_api_key_dict = MagicMock(spec=UserAPIKeyAuth)
mock_request_data = {
"model": "gpt-3.5-turbo",
"messages": [{"role": "user", "content": "test"}],
}
mock_chunks = [
{"choices": [{"delta": {"content": "Hello"}}]},
]
mock_proxy_logging_obj = MagicMock(spec=ProxyLogging)
async def mock_streaming_iterator(*args, **kwargs):
for chunk in mock_chunks:
yield chunk
mock_proxy_logging_obj.async_post_call_streaming_iterator_hook = (
mock_streaming_iterator
)
mock_proxy_logging_obj.async_post_call_streaming_hook = AsyncMock(
side_effect=lambda **kwargs: kwargs.get("response")
)
mock_proxy_logging_obj.post_call_failure_hook = AsyncMock()
mock_response = MagicMock()
mock_response.aclose = AsyncMock()
with patch("litellm.proxy.proxy_server.proxy_logging_obj", mock_proxy_logging_obj):
yielded_data = []
async for data in async_data_generator(
mock_response, mock_user_api_key_dict, mock_request_data
):
yielded_data.append(data)
# Should have completed normally with [DONE]
assert any("[DONE]" in d for d in yielded_data)
# aclose should still be called via finally block
mock_response.aclose.assert_awaited_once()
@pytest.mark.asyncio
async def test_async_data_generator_cleanup_on_midstream_error():
"""
Test that async_data_generator calls response.aclose() via finally block
even when an exception occurs mid-stream.
"""
from litellm.proxy._types import UserAPIKeyAuth
from litellm.proxy.proxy_server import async_data_generator
from litellm.proxy.utils import ProxyLogging
mock_user_api_key_dict = MagicMock(spec=UserAPIKeyAuth)
mock_request_data = {
"model": "gpt-3.5-turbo",
"messages": [{"role": "user", "content": "test"}],
}
mock_proxy_logging_obj = MagicMock(spec=ProxyLogging)
async def mock_streaming_iterator_with_error(*args, **kwargs):
yield {"choices": [{"delta": {"content": "Hello"}}]}
raise RuntimeError("upstream connection reset")
mock_proxy_logging_obj.async_post_call_streaming_iterator_hook = (
mock_streaming_iterator_with_error
)
mock_proxy_logging_obj.async_post_call_streaming_hook = AsyncMock(
side_effect=lambda **kwargs: kwargs.get("response")
)
mock_proxy_logging_obj.post_call_failure_hook = AsyncMock()
mock_response = MagicMock()
mock_response.aclose = AsyncMock()
with patch("litellm.proxy.proxy_server.proxy_logging_obj", mock_proxy_logging_obj):
yielded_data = []
async for data in async_data_generator(
mock_response, mock_user_api_key_dict, mock_request_data
):
yielded_data.append(data)
# Should have yielded data chunk and then an error chunk
assert len(yielded_data) >= 2
assert any("error" in d for d in yielded_data)
# aclose must still be called via finally block despite the error
mock_response.aclose.assert_awaited_once()
# ============================================================================
# store_model_in_db DB Config Override Tests
# ============================================================================
def test_store_model_in_db_in_config_general_settings():
"""
Verify store_model_in_db is a valid field in ConfigGeneralSettings
and validates correctly for True/False values.
"""
from litellm.proxy._types import ConfigGeneralSettings
assert "store_model_in_db" in ConfigGeneralSettings.model_fields
# Should validate with True
config = ConfigGeneralSettings(store_model_in_db=True)
assert config.store_model_in_db is True
# Should validate with False
config = ConfigGeneralSettings(store_model_in_db=False)
assert config.store_model_in_db is False
# Should validate with None (default)
config = ConfigGeneralSettings(store_model_in_db=None)
assert config.store_model_in_db is None
# Should validate with no value
config = ConfigGeneralSettings()
assert config.store_model_in_db is None
@pytest.mark.asyncio
async def test_update_general_settings_store_model_in_db_true():
"""
Verify _update_general_settings sets global store_model_in_db to True
when DB general_settings has store_model_in_db=True.
"""
from litellm.proxy.proxy_server import ProxyConfig
proxy_config = ProxyConfig()
with (
patch("litellm.proxy.proxy_server.store_model_in_db", False) as mock_store,
patch("litellm.proxy.proxy_server.general_settings", {}) as mock_gs,
):
await proxy_config._update_general_settings(
db_general_settings={"store_model_in_db": True}
)
import litellm.proxy.proxy_server as ps
assert ps.store_model_in_db is True
assert ps.general_settings["store_model_in_db"] is True
@pytest.mark.asyncio
async def test_update_general_settings_store_model_in_db_false():
"""
Verify _update_general_settings sets global store_model_in_db to False
when DB general_settings has store_model_in_db=False.
"""
from litellm.proxy.proxy_server import ProxyConfig
proxy_config = ProxyConfig()
with (
patch("litellm.proxy.proxy_server.store_model_in_db", True),
patch("litellm.proxy.proxy_server.general_settings", {}),
):
await proxy_config._update_general_settings(
db_general_settings={"store_model_in_db": False}
)
import litellm.proxy.proxy_server as ps
assert ps.store_model_in_db is False
assert ps.general_settings["store_model_in_db"] is False
@pytest.mark.asyncio
async def test_update_general_settings_store_model_in_db_string_normalization():
"""
Verify _update_general_settings normalizes string values for store_model_in_db.
"""
from litellm.proxy.proxy_server import ProxyConfig
proxy_config = ProxyConfig()
# Test "true" string
with (
patch("litellm.proxy.proxy_server.store_model_in_db", False),
patch("litellm.proxy.proxy_server.general_settings", {}),
):
await proxy_config._update_general_settings(
db_general_settings={"store_model_in_db": "true"}
)
import litellm.proxy.proxy_server as ps
assert ps.store_model_in_db is True
# Test "True" string
with (
patch("litellm.proxy.proxy_server.store_model_in_db", False),
patch("litellm.proxy.proxy_server.general_settings", {}),
):
await proxy_config._update_general_settings(
db_general_settings={"store_model_in_db": "True"}
)
import litellm.proxy.proxy_server as ps
assert ps.store_model_in_db is True
# Test "false" string
with (
patch("litellm.proxy.proxy_server.store_model_in_db", True),
patch("litellm.proxy.proxy_server.general_settings", {}),
):
await proxy_config._update_general_settings(
db_general_settings={"store_model_in_db": "false"}
)
import litellm.proxy.proxy_server as ps
assert ps.store_model_in_db is False
@pytest.mark.asyncio
async def test_update_general_settings_store_model_in_db_none_keeps_current():
"""
Verify _update_general_settings does not change store_model_in_db
when DB value is None.
"""
from litellm.proxy.proxy_server import ProxyConfig
proxy_config = ProxyConfig()
# When current is True and DB sends None, should stay True
with (
patch("litellm.proxy.proxy_server.store_model_in_db", True),
patch("litellm.proxy.proxy_server.general_settings", {}),
):
await proxy_config._update_general_settings(
db_general_settings={"store_model_in_db": None}
)
import litellm.proxy.proxy_server as ps
assert ps.store_model_in_db is True
# When current is False and DB sends None, should stay False
with (
patch("litellm.proxy.proxy_server.store_model_in_db", False),
patch("litellm.proxy.proxy_server.general_settings", {}),
):
await proxy_config._update_general_settings(
db_general_settings={"store_model_in_db": None}
)
import litellm.proxy.proxy_server as ps
assert ps.store_model_in_db is False
@pytest.mark.asyncio
async def test_store_model_in_db_db_override_when_config_false():
"""
Verify the early DB check in initialize_scheduled_background_jobs
overrides store_model_in_db=False when DB has True.
"""
from litellm.proxy.proxy_server import ProxyStartupEvent
from litellm.proxy.utils import ProxyLogging
mock_prisma_client = MagicMock()
# Mock DB returning store_model_in_db=True in general_settings
mock_db_record = MagicMock()
mock_db_record.param_value = {"store_model_in_db": True}
mock_prisma_client.db.litellm_config.find_first = AsyncMock(
return_value=mock_db_record
)
mock_proxy_logging = MagicMock(spec=ProxyLogging)
mock_proxy_logging.slack_alerting_instance = MagicMock()
mock_proxy_config = AsyncMock()
with (
patch("litellm.proxy.proxy_server.proxy_config", mock_proxy_config),
patch("litellm.proxy.proxy_server.store_model_in_db", False),
patch("litellm.proxy.proxy_server.get_secret_bool", return_value=False),
):
await ProxyStartupEvent.initialize_scheduled_background_jobs(
general_settings={},
prisma_client=mock_prisma_client,
proxy_budget_rescheduler_min_time=1,
proxy_budget_rescheduler_max_time=2,
proxy_batch_write_at=5,
proxy_logging_obj=mock_proxy_logging,
)
import litellm.proxy.proxy_server as ps
# store_model_in_db should now be True (overridden by DB)
assert ps.store_model_in_db is True
# add_deployment and get_credentials should have been called
# since store_model_in_db is now True
assert mock_proxy_config.add_deployment.call_count == 1
assert mock_proxy_config.get_credentials.call_count == 1
@pytest.mark.asyncio
async def test_store_model_in_db_db_check_skipped_when_already_true(monkeypatch):
"""
Verify the early DB check is skipped when store_model_in_db is already True.
The DB query for the early check should not be called.
"""
monkeypatch.delenv("STORE_MODEL_IN_DB", raising=False)
from litellm.proxy.proxy_server import ProxyStartupEvent
from litellm.proxy.utils import ProxyLogging
mock_prisma_client = MagicMock()
mock_prisma_client.db.litellm_config.find_first = AsyncMock(return_value=None)
mock_proxy_logging = MagicMock(spec=ProxyLogging)
mock_proxy_logging.slack_alerting_instance = MagicMock()
mock_proxy_config = AsyncMock()
with (
patch("litellm.proxy.proxy_server.proxy_config", mock_proxy_config),
patch("litellm.proxy.proxy_server.store_model_in_db", True),
patch("litellm.proxy.proxy_server.get_secret_bool", return_value=True),
):
await ProxyStartupEvent.initialize_scheduled_background_jobs(
general_settings={},
prisma_client=mock_prisma_client,
proxy_budget_rescheduler_min_time=1,
proxy_budget_rescheduler_max_time=2,
proxy_batch_write_at=5,
proxy_logging_obj=mock_proxy_logging,
)
# The early DB check uses find_first with param_name="general_settings".
# When store_model_in_db is already True, the early check should be skipped.
# However, add_deployment may also call find_first.
# We just verify that store_model_in_db stays True and jobs are scheduled.
import litellm.proxy.proxy_server as ps
assert ps.store_model_in_db is True
assert mock_proxy_config.add_deployment.call_count == 1
@pytest.mark.asyncio
async def test_store_model_in_db_db_failure_graceful(monkeypatch):
"""
Verify the early DB check handles DB failures gracefully
without crashing and keeps store_model_in_db as False.
"""
monkeypatch.delenv("STORE_MODEL_IN_DB", raising=False)
from litellm.proxy.proxy_server import ProxyStartupEvent
from litellm.proxy.utils import ProxyLogging
mock_prisma_client = MagicMock()
# Simulate DB failure
mock_prisma_client.db.litellm_config.find_first = AsyncMock(
side_effect=Exception("DB connection error")
)
mock_proxy_logging = MagicMock(spec=ProxyLogging)
mock_proxy_logging.slack_alerting_instance = MagicMock()
mock_proxy_config = AsyncMock()
with (
patch("litellm.proxy.proxy_server.proxy_config", mock_proxy_config),
patch("litellm.proxy.proxy_server.store_model_in_db", False),
patch("litellm.proxy.proxy_server.get_secret_bool", return_value=False),
):
# Should not raise an exception
await ProxyStartupEvent.initialize_scheduled_background_jobs(
general_settings={},
prisma_client=mock_prisma_client,
proxy_budget_rescheduler_min_time=1,
proxy_budget_rescheduler_max_time=2,
proxy_batch_write_at=5,
proxy_logging_obj=mock_proxy_logging,
)
import litellm.proxy.proxy_server as ps
# store_model_in_db should remain False
assert ps.store_model_in_db is False
# add_deployment should NOT have been called since store_model_in_db is False
mock_proxy_config.add_deployment.assert_not_called()
# =====================================================================
# Spend counter tests (v2 — Redis-backed spend counters)
# =====================================================================
@pytest.mark.asyncio
async def test_get_current_spend_reads_redis_first():
"""get_current_spend should prefer Redis over in-memory."""
from litellm.caching.dual_cache import DualCache
counter_cache = DualCache()
# In-memory has stale value
counter_cache.in_memory_cache.set_cache(key="spend:key:test", value=0.30)
# Mock Redis with cross-pod authoritative value
mock_redis = AsyncMock()
mock_redis.async_get_cache = AsyncMock(return_value=0.90)
counter_cache.redis_cache = mock_redis
import litellm.proxy.proxy_server as ps
original = ps.spend_counter_cache
ps.spend_counter_cache = counter_cache
try:
from litellm.proxy.proxy_server import get_current_spend
result = await get_current_spend(
counter_key="spend:key:test",
fallback_spend=0.0,
)
# Should return Redis value (0.90), not in-memory (0.30)
assert result == 0.90
mock_redis.async_get_cache.assert_called_once_with(key="spend:key:test")
finally:
ps.spend_counter_cache = original
@pytest.mark.asyncio
async def test_get_current_spend_fallback_to_in_memory():
"""When Redis is not configured, get_current_spend uses in-memory."""
from litellm.caching.dual_cache import DualCache
counter_cache = DualCache() # no redis_cache
counter_cache.in_memory_cache.set_cache(key="spend:key:test", value=0.50)
import litellm.proxy.proxy_server as ps
original = ps.spend_counter_cache
ps.spend_counter_cache = counter_cache
try:
from litellm.proxy.proxy_server import get_current_spend
result = await get_current_spend(
counter_key="spend:key:test",
fallback_spend=0.0,
)
assert result == 0.50
finally:
ps.spend_counter_cache = original
@pytest.mark.asyncio
async def test_increment_spend_counters_initializes_and_increments():
"""Counter should initialize from cached object spend, then increment.
Uses a pre-hashed token to match production: metadata["user_api_key"]
is always hashed by the auth flow before reaching the cost callback.
"""
from litellm.caching.dual_cache import DualCache
from litellm.proxy._types import LiteLLM_VerificationTokenView, hash_token
key_cache = DualCache()
counter_cache = DualCache()
# In production, the auth flow hashes the raw key before it reaches
# the cost callback. Simulate that by passing the hashed token.
hashed_token = hash_token("sk-test-token-for-counter")
# Simulate a cached key object with existing spend from DB
cached_key = LiteLLM_VerificationTokenView(
token=hashed_token,
spend=5.0,
max_budget=10.0,
)
key_cache.in_memory_cache.set_cache(key=hashed_token, value=cached_key)
import litellm.proxy.proxy_server as ps
original_key_cache = ps.user_api_key_cache
original_counter_cache = ps.spend_counter_cache
ps.user_api_key_cache = key_cache
ps.spend_counter_cache = counter_cache
try:
from litellm.proxy.proxy_server import increment_spend_counters
# Pass pre-hashed token (as the cost callback would in production)
await increment_spend_counters(
token=hashed_token,
team_id=None,
user_id=None,
response_cost=0.50,
)
# Counter should be: base(5.0) + increment(0.50) = 5.50
counter = counter_cache.in_memory_cache.get_cache(
key=f"spend:key:{hashed_token}"
)
assert counter == 5.50
# Second increment — counter already exists, just increment
await increment_spend_counters(
token=hashed_token,
team_id=None,
user_id=None,
response_cost=0.25,
)
counter = counter_cache.in_memory_cache.get_cache(
key=f"spend:key:{hashed_token}"
)
assert counter == 5.75
finally:
ps.user_api_key_cache = original_key_cache
ps.spend_counter_cache = original_counter_cache
@pytest.mark.asyncio
async def test_increment_spend_counters_team_and_member():
"""Counter should track team and team member spend separately."""
from litellm.caching.dual_cache import DualCache
from litellm.proxy._types import LiteLLM_TeamTable
key_cache = DualCache()
counter_cache = DualCache()
# Cached team object
team_obj = LiteLLM_TeamTable(team_id="team-1", spend=2.0)
key_cache.in_memory_cache.set_cache(key="team_id:team-1", value=team_obj)
# Cached team membership
key_cache.in_memory_cache.set_cache(
key="team_membership:user-1:team-1",
value={"user_id": "user-1", "team_id": "team-1", "spend": 1.0},
)
import litellm.proxy.proxy_server as ps
original_key_cache = ps.user_api_key_cache
original_counter_cache = ps.spend_counter_cache
ps.user_api_key_cache = key_cache
ps.spend_counter_cache = counter_cache
try:
from litellm.proxy.proxy_server import increment_spend_counters
await increment_spend_counters(
token=None,
team_id="team-1",
user_id="user-1",
response_cost=0.30,
)
team_counter = counter_cache.in_memory_cache.get_cache(key="spend:team:team-1")
assert team_counter == 2.30
member_counter = counter_cache.in_memory_cache.get_cache(
key="spend:team_member:user-1:team-1"
)
assert member_counter == 1.30
finally:
ps.user_api_key_cache = original_key_cache
ps.spend_counter_cache = original_counter_cache
@pytest.mark.asyncio
async def test_init_and_increment_spend_counter_reseeds_from_db_on_counter_miss():
"""When the Redis counter is missing, the reseed path reads the
authoritative spend from the DB (not a stale cache), so the next
increment continues from the correct base value."""
from litellm.caching.dual_cache import DualCache
counter_cache = DualCache()
recorded_increments: list = []
async def record_increment(key, value, ttl=None, **kwargs):
recorded_increments.append({"key": key, "value": value, "ttl": ttl})
return value
fake_redis = AsyncMock()
fake_redis.async_increment = AsyncMock(side_effect=record_increment)
fake_redis.async_get_cache = AsyncMock(return_value=None) # counter missing
counter_cache.redis_cache = fake_redis
# Prisma returns spend=42.0 (authoritative) while the stale cached
# value (would be read only if prisma is None) is 10.0. The counter
# must seed from 42, not 10.
db_row = MagicMock()
db_row.spend = 42.0
fake_prisma = MagicMock()
fake_prisma.db.litellm_teamtable.find_unique = AsyncMock(return_value=db_row)
stale_cache = DualCache()
stale_team = MagicMock()
stale_team.spend = 10.0
stale_cache.in_memory_cache.set_cache(key="team_id:team-9", value=stale_team)
import litellm.proxy.proxy_server as ps
from litellm.proxy.proxy_server import _init_and_increment_spend_counter
orig_user, orig_counter, orig_prisma = (
ps.user_api_key_cache,
ps.spend_counter_cache,
ps.prisma_client,
)
ps.user_api_key_cache = stale_cache
ps.spend_counter_cache = counter_cache
ps.prisma_client = fake_prisma
try:
await _init_and_increment_spend_counter(
counter_key="spend:team:team-9",
source_cache_key="team_id:team-9",
increment=1.5,
)
fake_prisma.db.litellm_teamtable.find_unique.assert_awaited_once_with(
where={"team_id": "team-9"}
)
# Two increments keyed on the counter: seed ($42) then request ($1.50).
writes = [(c["key"], c["value"]) for c in recorded_increments]
assert ("spend:team:team-9", 42.0) in writes
assert ("spend:team:team-9", 1.5) in writes
finally:
ps.user_api_key_cache = orig_user
ps.spend_counter_cache = orig_counter
ps.prisma_client = orig_prisma
@pytest.mark.asyncio
async def test_reseed_spend_from_db_user_and_org_prefixes():
"""User and org counters reseed from their own DB tables.
End-user and tag counters use the already fetched auth objects passed as
fallback_spend, so this reseed helper must not add extra per-request DB
reads for them.
"""
from litellm.proxy.db.spend_counter_reseed import SpendCounterReseed
user_row = MagicMock()
user_row.spend = 17.0
org_row = MagicMock()
org_row.spend = 305.0
fake_prisma = MagicMock()
fake_prisma.db.litellm_usertable.find_unique = AsyncMock(return_value=user_row)
fake_prisma.db.litellm_endusertable.find_unique = AsyncMock()
fake_prisma.db.litellm_tagtable.find_unique = AsyncMock()
fake_prisma.db.litellm_organizationtable.find_unique = AsyncMock(
return_value=org_row
)
assert await SpendCounterReseed.from_db(fake_prisma, "spend:user:alice") == 17.0
fake_prisma.db.litellm_usertable.find_unique.assert_awaited_once_with(
where={"user_id": "alice"}
)
assert (
await SpendCounterReseed.from_db(
fake_prisma,
"spend:end_user:customer-1",
)
is None
)
fake_prisma.db.litellm_endusertable.find_unique.assert_not_awaited()
assert await SpendCounterReseed.from_db(fake_prisma, "spend:tag:paid-tag") is None
fake_prisma.db.litellm_tagtable.find_unique.assert_not_awaited()
assert await SpendCounterReseed.from_db(fake_prisma, "spend:org:acme") == 305.0
fake_prisma.db.litellm_organizationtable.find_unique.assert_awaited_once_with(
where={"organization_id": "acme"}
)
@pytest.mark.asyncio
async def test_reseed_spend_from_db_skips_window_variant_keys():
"""Window counters (spend:*:window:{duration}) share prefixes with
primary counters but don't correspond to a DB row. The guard must
short-circuit without querying the DB."""
from litellm.proxy.db.spend_counter_reseed import SpendCounterReseed
fake_prisma = MagicMock()
fake_prisma.db.litellm_verificationtoken.find_unique = AsyncMock()
fake_prisma.db.litellm_teamtable.find_unique = AsyncMock()
assert (
await SpendCounterReseed.from_db(fake_prisma, "spend:key:sk-abc:window:1h")
is None
)
assert (
await SpendCounterReseed.from_db(fake_prisma, "spend:team:team-1:window:1d")
is None
)
fake_prisma.db.litellm_verificationtoken.find_unique.assert_not_awaited()
fake_prisma.db.litellm_teamtable.find_unique.assert_not_awaited()
@pytest.mark.asyncio
async def test_window_spend_counter_reseeds_from_spend_logs_on_counter_miss():
from litellm.caching.dual_cache import DualCache
from litellm.proxy.proxy_server import _init_and_increment_window_spend_counter
counter_cache = DualCache()
window_start = datetime.now(timezone.utc) - timedelta(hours=1)
fake_prisma = MagicMock()
fake_prisma.db.litellm_spendlogs.group_by = AsyncMock(
return_value=[{"api_key": "key-window", "_sum": {"spend": 2.25}}]
)
import litellm.proxy.proxy_server as ps
orig_counter, orig_prisma = ps.spend_counter_cache, ps.prisma_client
ps.spend_counter_cache = counter_cache
ps.prisma_client = fake_prisma
try:
await _init_and_increment_window_spend_counter(
counter_key="spend:key:key-window:window:1h",
entity_type="Key",
entity_id="key-window",
window_start=window_start,
increment=0.5,
)
fake_prisma.db.litellm_spendlogs.group_by.assert_awaited_once_with(
by=["api_key"],
where={"api_key": "key-window", "startTime": {"gte": window_start}},
sum={"spend": True},
)
assert counter_cache.in_memory_cache.get_cache(
key="spend:key:key-window:window:1h"
) == pytest.approx(2.75)
finally:
ps.spend_counter_cache = orig_counter
ps.prisma_client = orig_prisma
@pytest.mark.asyncio
async def test_init_spend_counter_redis_clean_miss_skips_stale_in_memory():
from litellm.caching.dual_cache import DualCache
from litellm.proxy.proxy_server import _init_and_increment_spend_counter
counter_cache = DualCache()
counter_key = "spend:team:team-stale-local"
counter_cache.in_memory_cache.set_cache(key=counter_key, value=10.0)
redis_store: dict = {}
async def redis_increment(key, value, **_):
redis_store[key] = (redis_store.get(key) or 0.0) + value
return redis_store[key]
fake_redis = AsyncMock()
fake_redis.async_get_cache = AsyncMock(return_value=None)
fake_redis.async_increment = AsyncMock(side_effect=redis_increment)
counter_cache.redis_cache = fake_redis
db_row = MagicMock()
db_row.spend = 42.0
fake_prisma = MagicMock()
fake_prisma.db.litellm_teamtable.find_unique = AsyncMock(return_value=db_row)
import litellm.proxy.proxy_server as ps
orig_counter, orig_prisma, orig_user = (
ps.spend_counter_cache,
ps.prisma_client,
ps.user_api_key_cache,
)
ps.spend_counter_cache = counter_cache
ps.prisma_client = fake_prisma
ps.user_api_key_cache = DualCache()
try:
await _init_and_increment_spend_counter(
counter_key=counter_key,
source_cache_key="team_id:team-stale-local",
increment=1.5,
)
fake_prisma.db.litellm_teamtable.find_unique.assert_awaited_once_with(
where={"team_id": "team-stale-local"}
)
assert redis_store[counter_key] == pytest.approx(43.5)
assert counter_cache.in_memory_cache.get_cache(
key=counter_key
) == pytest.approx(43.5)
finally:
ps.spend_counter_cache = orig_counter
ps.prisma_client = orig_prisma
ps.user_api_key_cache = orig_user
@pytest.mark.asyncio
async def test_window_spend_counter_redis_clean_miss_skips_stale_in_memory():
from litellm.caching.dual_cache import DualCache
from litellm.proxy.proxy_server import _init_and_increment_window_spend_counter
counter_cache = DualCache()
counter_key = "spend:key:key-window-stale-local:window:1h"
counter_cache.in_memory_cache.set_cache(key=counter_key, value=100.0)
window_start = datetime.now(timezone.utc) - timedelta(hours=1)
redis_store: dict = {}
async def redis_increment(key, value, **_):
redis_store[key] = (redis_store.get(key) or 0.0) + value
return redis_store[key]
async def redis_set_cache(key, value, **_):
if key in redis_store:
return False
redis_store[key] = value
return True
fake_redis = AsyncMock()
fake_redis.async_get_cache = AsyncMock(return_value=None)
fake_redis.async_set_cache = AsyncMock(side_effect=redis_set_cache)
fake_redis.async_increment = AsyncMock(side_effect=redis_increment)
counter_cache.redis_cache = fake_redis
fake_prisma = MagicMock()
fake_prisma.db.litellm_spendlogs.group_by = AsyncMock(
return_value=[{"api_key": "key-window-stale-local", "_sum": {"spend": 2.25}}]
)
import litellm.proxy.proxy_server as ps
orig_counter, orig_prisma = ps.spend_counter_cache, ps.prisma_client
ps.spend_counter_cache = counter_cache
ps.prisma_client = fake_prisma
try:
await _init_and_increment_window_spend_counter(
counter_key=counter_key,
entity_type="Key",
entity_id="key-window-stale-local",
window_start=window_start,
increment=0.5,
)
fake_prisma.db.litellm_spendlogs.group_by.assert_awaited_once_with(
by=["api_key"],
where={
"api_key": "key-window-stale-local",
"startTime": {"gte": window_start},
},
sum={"spend": True},
)
assert redis_store[counter_key] == pytest.approx(2.75)
assert counter_cache.in_memory_cache.get_cache(
key=counter_key
) == pytest.approx(2.75)
finally:
ps.spend_counter_cache = orig_counter
ps.prisma_client = orig_prisma
@pytest.mark.asyncio
async def test_window_spend_counter_redis_concurrent_seed_does_not_double_seed():
from litellm.caching.dual_cache import DualCache
from litellm.proxy.proxy_server import _init_and_increment_window_spend_counter
counter_cache = DualCache()
counter_key = "spend:key:key-window-concurrent-seed:window:1h"
window_start = datetime.now(timezone.utc) - timedelta(hours=1)
redis_store = {counter_key: 2.75}
redis_reads = 0
async def redis_get_cache(key):
nonlocal redis_reads
redis_reads += 1
if redis_reads <= 2:
return None
return redis_store.get(key)
async def redis_increment(key, value, **_):
redis_store[key] = (redis_store.get(key) or 0.0) + value
return redis_store[key]
fake_redis = AsyncMock()
fake_redis.async_get_cache = AsyncMock(side_effect=redis_get_cache)
fake_redis.async_set_cache = AsyncMock(return_value=False)
fake_redis.async_increment = AsyncMock(side_effect=redis_increment)
counter_cache.redis_cache = fake_redis
fake_prisma = MagicMock()
fake_prisma.db.litellm_spendlogs.group_by = AsyncMock(
return_value=[
{"api_key": "key-window-concurrent-seed", "_sum": {"spend": 2.25}}
]
)
import litellm.proxy.proxy_server as ps
orig_counter, orig_prisma = ps.spend_counter_cache, ps.prisma_client
ps.spend_counter_cache = counter_cache
ps.prisma_client = fake_prisma
try:
await _init_and_increment_window_spend_counter(
counter_key=counter_key,
entity_type="Key",
entity_id="key-window-concurrent-seed",
window_start=window_start,
increment=0.5,
)
fake_redis.async_set_cache.assert_awaited_once_with(
key=counter_key,
value=2.25,
nx=True,
)
assert redis_store[counter_key] == pytest.approx(3.25)
assert counter_cache.in_memory_cache.get_cache(
key=counter_key
) == pytest.approx(3.25)
finally:
ps.spend_counter_cache = orig_counter
ps.prisma_client = orig_prisma
@pytest.mark.asyncio
async def test_window_spend_counter_skips_invalid_window_start():
from litellm.caching.dual_cache import DualCache
from litellm.proxy.proxy_server import _init_and_increment_window_spend_counter
counter_cache = DualCache()
import litellm.proxy.proxy_server as ps
orig_counter = ps.spend_counter_cache
ps.spend_counter_cache = counter_cache
try:
await _init_and_increment_window_spend_counter(
counter_key="spend:key:key-invalid-window:window:not-a-duration",
entity_type="Key",
entity_id="key-invalid-window",
window_start=None,
increment=0.5,
)
assert (
counter_cache.in_memory_cache.get_cache(
key="spend:key:key-invalid-window:window:not-a-duration"
)
is None
)
finally:
ps.spend_counter_cache = orig_counter
@pytest.mark.asyncio
async def test_window_spend_counter_does_not_seed_zero_when_db_unavailable():
from litellm.caching.dual_cache import DualCache
from litellm.proxy.proxy_server import _ensure_window_spend_counter_initialized
counter_cache = DualCache()
counter_key = "spend:key:key-window-db-unavailable:window:1h"
import litellm.proxy.proxy_server as ps
orig_counter, orig_prisma = ps.spend_counter_cache, ps.prisma_client
ps.spend_counter_cache = counter_cache
ps.prisma_client = None
try:
initialized = await _ensure_window_spend_counter_initialized(
counter_key=counter_key,
entity_type="Key",
entity_id="key-window-db-unavailable",
window_start=datetime.now(timezone.utc) - timedelta(hours=1),
)
assert initialized is False
assert counter_cache.in_memory_cache.get_cache(key=counter_key) is None
finally:
ps.spend_counter_cache = orig_counter
ps.prisma_client = orig_prisma
@pytest.mark.asyncio
async def test_increment_spend_counters_finalizes_after_unreserved_increments():
from litellm.caching.dual_cache import DualCache
from litellm.proxy.proxy_server import increment_spend_counters
counter_cache = DualCache()
counter_cache.in_memory_cache.set_cache(
key="spend:key:key-finalize-after-increments",
value=0.5,
)
budget_reservation = {
"reserved_cost": 0.5,
"entries": [
{
"counter_key": "spend:key:key-finalize-after-increments",
"entity_type": "Key",
"entity_id": "key-finalize-after-increments",
"reserved_cost": 0.5,
"applied_adjustment": 0.0,
}
],
"finalized": False,
}
incremented_counters = []
async def assert_reservation_not_finalized_yet(**kwargs):
assert budget_reservation["finalized"] is False
incremented_counters.append(kwargs["counter_key"])
import litellm.proxy.proxy_server as ps
orig_counter, orig_user = ps.spend_counter_cache, ps.user_api_key_cache
ps.spend_counter_cache = counter_cache
ps.user_api_key_cache = DualCache()
try:
with patch(
"litellm.proxy.proxy_server._init_and_increment_spend_counter",
new=AsyncMock(side_effect=assert_reservation_not_finalized_yet),
):
await increment_spend_counters(
token="key-finalize-after-increments",
team_id="team-finalize-after-increments",
user_id=None,
response_cost=0.25,
budget_reservation=budget_reservation,
)
assert incremented_counters == ["spend:team:team-finalize-after-increments"]
assert budget_reservation["finalized"] is True
assert counter_cache.in_memory_cache.get_cache(
key="spend:key:key-finalize-after-increments"
) == pytest.approx(0.25)
finally:
ps.spend_counter_cache = orig_counter
ps.user_api_key_cache = orig_user
@pytest.mark.asyncio
async def test_increment_spend_counters_finalizes_none_cost_reservation():
from litellm.caching.dual_cache import DualCache
from litellm.proxy.proxy_server import increment_spend_counters
counter_cache = DualCache()
counter_cache.in_memory_cache.set_cache(
key="spend:key:key-finalize-none-cost",
value=0.5,
)
budget_reservation = {
"reserved_cost": 0.5,
"entries": [
{
"counter_key": "spend:key:key-finalize-none-cost",
"entity_type": "Key",
"entity_id": "key-finalize-none-cost",
"reserved_cost": 0.5,
"applied_adjustment": 0.0,
}
],
"finalized": False,
}
import litellm.proxy.proxy_server as ps
orig_counter = ps.spend_counter_cache
ps.spend_counter_cache = counter_cache
try:
await increment_spend_counters(
token="key-finalize-none-cost",
team_id=None,
user_id=None,
response_cost=None,
budget_reservation=budget_reservation,
)
assert budget_reservation["finalized"] is True
assert counter_cache.in_memory_cache.get_cache(
key="spend:key:key-finalize-none-cost"
) == pytest.approx(0.0)
finally:
ps.spend_counter_cache = orig_counter
@pytest.mark.asyncio
async def test_increment_spend_counters_invalidates_bad_reserved_counter_without_failing():
from litellm.caching.dual_cache import DualCache
from litellm.proxy.proxy_server import increment_spend_counters
counter_cache = DualCache()
budget_reservation = {
"reserved_cost": 0.5,
"entries": [
{
"counter_key": "spend:key:key-bad-reserved-counter",
"entity_type": "Key",
"entity_id": "key-bad-reserved-counter",
"reserved_cost": 0.5,
"applied_adjustment": 0.0,
}
],
"finalized": False,
}
import litellm.proxy.proxy_server as ps
orig_counter = ps.spend_counter_cache
ps.spend_counter_cache = counter_cache
try:
with patch(
"litellm.proxy.proxy_server.verbose_proxy_logger.warning"
) as mock_warning:
await increment_spend_counters(
token="key-bad-reserved-counter",
team_id=None,
user_id=None,
response_cost=0.25,
budget_reservation=budget_reservation,
)
mock_warning.assert_called_once()
assert budget_reservation["finalized"] is True
assert (
counter_cache.in_memory_cache.get_cache(
key="spend:key:key-bad-reserved-counter"
)
is None
)
finally:
ps.spend_counter_cache = orig_counter
@pytest.mark.asyncio
async def test_increment_spend_counter_invalidates_stale_cache_on_redis_failure():
from litellm.caching.dual_cache import DualCache
from litellm.proxy.proxy_server import _increment_spend_counter_cache
counter_cache = DualCache()
counter_cache.in_memory_cache.set_cache(key="spend:team:redis-fail", value=4.0)
fake_redis = AsyncMock()
fake_redis.async_increment = AsyncMock(side_effect=RuntimeError("redis down"))
fake_redis.async_delete_cache = AsyncMock()
counter_cache.redis_cache = fake_redis
import litellm.proxy.proxy_server as ps
orig_counter = ps.spend_counter_cache
ps.spend_counter_cache = counter_cache
try:
with pytest.raises(RuntimeError):
await _increment_spend_counter_cache(
counter_key="spend:team:redis-fail",
increment=0.5,
)
assert (
counter_cache.in_memory_cache.get_cache(key="spend:team:redis-fail") is None
)
fake_redis.async_delete_cache.assert_awaited_once_with(
key="spend:team:redis-fail"
)
finally:
ps.spend_counter_cache = orig_counter
@pytest.mark.asyncio
async def test_get_current_spend_reseeds_from_db_when_counter_missing():
"""
When both the Redis and in-memory counters are missing, the enforcement
read path must reseed from the authoritative DB, not fall back to the
caller-supplied stale value. Otherwise, every Redis TTL expiry lets a
request through against a stale in-process `team_membership.spend`.
"""
from litellm.caching.dual_cache import DualCache
from litellm.proxy.proxy_server import get_current_spend
counter_cache = DualCache()
recorded_warms: list = []
async def record_increment(key, value, ttl=None, **kwargs):
recorded_warms.append({"key": key, "value": value})
return value
fake_redis = AsyncMock()
fake_redis.async_increment = AsyncMock(side_effect=record_increment)
fake_redis.async_get_cache = AsyncMock(return_value=None)
counter_cache.redis_cache = fake_redis
# DB has authoritative spend=362.0; caller hands us stale fallback=30.0
# (the in-process team_membership.spend that hasn't caught up to DB).
db_row = MagicMock()
db_row.spend = 362.0
fake_prisma = MagicMock()
fake_prisma.db.litellm_teammembership.find_unique = AsyncMock(return_value=db_row)
import litellm.proxy.proxy_server as ps
orig_counter, orig_prisma = ps.spend_counter_cache, ps.prisma_client
ps.spend_counter_cache = counter_cache
ps.prisma_client = fake_prisma
try:
spend = await get_current_spend(
counter_key="spend:team_member:user-1:team-1",
fallback_spend=30.0,
)
assert spend == 362.0, (
f"expected DB reseed to return 362.0, got {spend} "
f"(fallback would have returned 30.0 and caused bypass)"
)
# Counter warmed so subsequent reads are fast
assert ("spend:team_member:user-1:team-1", 362.0) in [
(w["key"], w["value"]) for w in recorded_warms
]
assert counter_cache.in_memory_cache.get_cache(
key="spend:team_member:user-1:team-1"
) == pytest.approx(362.0)
finally:
ps.spend_counter_cache = orig_counter
ps.prisma_client = orig_prisma
@pytest.mark.asyncio
async def test_get_current_spend_uses_fallback_when_db_unavailable():
"""
If prisma is unavailable and both counters are missing, the read path
must degrade to the caller-supplied fallback rather than raising.
"""
from litellm.caching.dual_cache import DualCache
from litellm.proxy.proxy_server import get_current_spend
counter_cache = DualCache()
fake_redis = AsyncMock()
fake_redis.async_get_cache = AsyncMock(return_value=None)
counter_cache.redis_cache = fake_redis
import litellm.proxy.proxy_server as ps
orig_counter, orig_prisma = ps.spend_counter_cache, ps.prisma_client
ps.spend_counter_cache = counter_cache
ps.prisma_client = None # simulate prisma unavailable
try:
spend = await get_current_spend(
counter_key="spend:team_member:user-1:team-1",
fallback_spend=15.5,
)
assert spend == 15.5
finally:
ps.spend_counter_cache = orig_counter
ps.prisma_client = orig_prisma
@pytest.mark.asyncio
async def test_get_current_spend_coalesces_concurrent_reseeds():
"""
When several concurrent calls hit a cold counter on the same pod,
only one DB query should fire. The rest should wait for the lock,
re-check the warmed counter, and return without hitting the DB.
"""
import asyncio as _asyncio
from litellm.caching.dual_cache import DualCache
from litellm.proxy.proxy_server import get_current_spend
counter_cache = DualCache()
counter_key = "spend:team_member:user-1:team-coalesce"
# Track DB query calls and inject a small delay so the concurrent
# callers actually overlap in the lock-acquire window.
db_call_count = 0
async def slow_find_unique(**kwargs):
nonlocal db_call_count
db_call_count += 1
await _asyncio.sleep(0.05)
row = MagicMock()
row.spend = 100.0
return row
fake_redis = AsyncMock()
redis_store: dict = {}
async def redis_get(key, **_):
return redis_store.get(key)
async def redis_increment(key, value, **_):
redis_store[key] = (redis_store.get(key) or 0.0) + value
return redis_store[key]
fake_redis.async_get_cache = AsyncMock(side_effect=redis_get)
fake_redis.async_increment = AsyncMock(side_effect=redis_increment)
counter_cache.redis_cache = fake_redis
fake_prisma = MagicMock()
fake_prisma.db.litellm_teammembership.find_unique = AsyncMock(
side_effect=slow_find_unique
)
import litellm.proxy.proxy_server as ps
orig_counter, orig_prisma = ps.spend_counter_cache, ps.prisma_client
ps.spend_counter_cache = counter_cache
ps.prisma_client = fake_prisma
try:
results = await _asyncio.gather(
*[
get_current_spend(counter_key=counter_key, fallback_spend=0.0)
for _ in range(5)
]
)
assert results == [100.0] * 5, f"all callers should see DB value, got {results}"
assert (
db_call_count == 1
), f"expected exactly 1 DB query for 5 concurrent reseeds, got {db_call_count}"
finally:
ps.spend_counter_cache = orig_counter
ps.prisma_client = orig_prisma
@pytest.mark.asyncio
async def test_get_current_spend_uses_db_zero_over_stale_fallback():
"""
When DB returns spend=0 (e.g. just after a budget period reset), the
authoritative DB value must win over a stale non-zero fallback. The
fallback in production is the in-process team_membership.spend, which
can still hold the pre-reset value across pods.
"""
from litellm.caching.dual_cache import DualCache
from litellm.proxy.proxy_server import get_current_spend
counter_cache = DualCache()
fake_redis = AsyncMock()
fake_redis.async_get_cache = AsyncMock(return_value=None)
counter_cache.redis_cache = fake_redis
db_row = MagicMock()
db_row.spend = 0.0
fake_prisma = MagicMock()
fake_prisma.db.litellm_teammembership.find_unique = AsyncMock(return_value=db_row)
import litellm.proxy.proxy_server as ps
orig_counter, orig_prisma = ps.spend_counter_cache, ps.prisma_client
ps.spend_counter_cache = counter_cache
ps.prisma_client = fake_prisma
try:
spend = await get_current_spend(
counter_key="spend:team_member:user-1:team-after-reset",
fallback_spend=42.0,
)
assert (
spend == 0.0
), f"DB authoritative 0 must override stale fallback 42, got {spend}"
finally:
ps.spend_counter_cache = orig_counter
ps.prisma_client = orig_prisma
@pytest.mark.asyncio
async def test_concurrent_read_and_write_paths_share_one_db_query():
"""
The read path (`get_current_spend`) and the write path
(`_init_and_increment_spend_counter`) both reseed cold counters from
the DB. They must share the per-counter lock so a concurrent pre-call
enforcement read and post-call increment for the same counter collapse
to one DB query, not two.
"""
import asyncio as _asyncio
from litellm.caching.dual_cache import DualCache
from litellm.proxy.proxy_server import (
_init_and_increment_spend_counter,
get_current_spend,
)
counter_cache = DualCache()
counter_key = "spend:team_member:user-1:team-cross-path"
db_call_count = 0
async def slow_find_unique(**kwargs):
nonlocal db_call_count
db_call_count += 1
await _asyncio.sleep(0.05)
row = MagicMock()
row.spend = 50.0
return row
redis_store: dict = {}
async def redis_get(key, **_):
return redis_store.get(key)
async def redis_increment(key, value, **_):
redis_store[key] = (redis_store.get(key) or 0.0) + value
return redis_store[key]
fake_redis = AsyncMock()
fake_redis.async_get_cache = AsyncMock(side_effect=redis_get)
fake_redis.async_increment = AsyncMock(side_effect=redis_increment)
counter_cache.redis_cache = fake_redis
fake_prisma = MagicMock()
fake_prisma.db.litellm_teammembership.find_unique = AsyncMock(
side_effect=slow_find_unique
)
import litellm.proxy.proxy_server as ps
orig_counter, orig_prisma, orig_user = (
ps.spend_counter_cache,
ps.prisma_client,
ps.user_api_key_cache,
)
ps.spend_counter_cache = counter_cache
ps.prisma_client = fake_prisma
ps.user_api_key_cache = DualCache()
try:
results = await _asyncio.gather(
get_current_spend(counter_key=counter_key, fallback_spend=0.0),
_init_and_increment_spend_counter(
counter_key=counter_key,
source_cache_key="ignored",
increment=1.5,
),
get_current_spend(counter_key=counter_key, fallback_spend=0.0),
)
assert (
db_call_count == 1
), f"expected 1 DB query for concurrent read+write+read, got {db_call_count}"
# Read-path callers see the warmed counter; the write path's
# increment may or may not have landed by then, so accept either
# the seeded value or seeded+increment.
assert results[0] in (50.0, 51.5), f"got {results[0]}"
assert results[2] in (50.0, 51.5), f"got {results[2]}"
finally:
ps.spend_counter_cache = orig_counter
ps.prisma_client = orig_prisma
ps.user_api_key_cache = orig_user
@pytest.mark.asyncio
async def test_reseed_locks_dict_is_bounded():
"""
`SpendCounterReseed._locks` is an LRU bounded at
`SPEND_COUNTER_RESEED_LOCKS_MAX_SIZE` to prevent unbounded growth in
long-lived deployments with high counter-key churn. Inserting more
than the cap evicts the oldest entries.
"""
import litellm.constants as constants
from litellm.proxy.db.spend_counter_reseed import SpendCounterReseed
orig_locks = SpendCounterReseed._locks.copy()
SpendCounterReseed._locks.clear()
orig_max = constants.SPEND_COUNTER_RESEED_LOCKS_MAX_SIZE
constants.SPEND_COUNTER_RESEED_LOCKS_MAX_SIZE = 5
# The class reads the constant via module-level import, so patch the
# module-level name on the spend_counter_reseed module too.
import litellm.proxy.db.spend_counter_reseed as scr
orig_module_max = scr.SPEND_COUNTER_RESEED_LOCKS_MAX_SIZE
scr.SPEND_COUNTER_RESEED_LOCKS_MAX_SIZE = 5
try:
for i in range(7):
await SpendCounterReseed._get_lock(f"spend:key:test-key-{i}")
assert (
len(SpendCounterReseed._locks) == 5
), f"got {len(SpendCounterReseed._locks)}"
# Oldest two evicted
assert "spend:key:test-key-0" not in SpendCounterReseed._locks
assert "spend:key:test-key-1" not in SpendCounterReseed._locks
# Most recent retained
assert "spend:key:test-key-6" in SpendCounterReseed._locks
finally:
constants.SPEND_COUNTER_RESEED_LOCKS_MAX_SIZE = orig_max
scr.SPEND_COUNTER_RESEED_LOCKS_MAX_SIZE = orig_module_max
SpendCounterReseed._locks.clear()
SpendCounterReseed._locks.update(orig_locks)
@pytest.mark.asyncio
async def test_reseed_warms_cache_even_on_zero_db_spend():
"""
When DB returns 0.0 (fresh entity / just after reset), the cache must
still be warmed so subsequent reads hit the cache instead of issuing
another DB query. Skipping the warm causes O(requests) DB load on
zero-spend entities.
"""
from litellm.caching.dual_cache import DualCache
from litellm.proxy.proxy_server import get_current_spend
counter_cache = DualCache()
counter_key = "spend:team_member:user-1:team-zero-warm"
redis_store: dict = {}
async def redis_get(key, **_):
return redis_store.get(key)
async def redis_increment(key, value, **_):
redis_store[key] = (redis_store.get(key) or 0.0) + value
return redis_store[key]
fake_redis = AsyncMock()
fake_redis.async_get_cache = AsyncMock(side_effect=redis_get)
fake_redis.async_increment = AsyncMock(side_effect=redis_increment)
counter_cache.redis_cache = fake_redis
db_call_count = 0
async def find_unique(**kwargs):
nonlocal db_call_count
db_call_count += 1
row = MagicMock()
row.spend = 0.0
return row
fake_prisma = MagicMock()
fake_prisma.db.litellm_teammembership.find_unique = AsyncMock(
side_effect=find_unique
)
import litellm.proxy.proxy_server as ps
orig_counter, orig_prisma = ps.spend_counter_cache, ps.prisma_client
ps.spend_counter_cache = counter_cache
ps.prisma_client = fake_prisma
try:
# First call: cold cache, hits DB, returns 0.
spend1 = await get_current_spend(counter_key=counter_key, fallback_spend=0.0)
# Second call: cache should be warmed at 0, no second DB query.
spend2 = await get_current_spend(counter_key=counter_key, fallback_spend=0.0)
assert spend1 == 0.0 and spend2 == 0.0
assert (
db_call_count == 1
), f"second read should hit warmed cache, got {db_call_count} DB queries"
assert redis_store.get(counter_key) == 0.0, "cache must be warmed at 0"
finally:
ps.spend_counter_cache = orig_counter
ps.prisma_client = orig_prisma
# -----------------------------------------------------------------------------
# /config/update — critical paths only.
#
# These exercise the four behaviors that broke or changed in the rewrite of
# update_config (litellm/proxy/proxy_server.py): targeted per-section writes,
# the removal of the store_model_in_db gate, env var encryption, and the
# success_callback / litellm_settings merge semantics. All other branches
# (auth, missing-DB, slack auto-enable, router_settings merge) are covered
# implicitly or by upstream tests.
# -----------------------------------------------------------------------------
class _FakeRow:
def __init__(self, param_name, param_value):
self.param_name = param_name
self.param_value = param_value
class _FakeLitellmConfig:
def __init__(self, initial_rows=None):
self.rows = dict(initial_rows or {})
self.upsert_calls: list = []
self.find_first = AsyncMock(side_effect=self._find_first)
self.upsert = AsyncMock(side_effect=self._upsert)
async def _find_first(self, where=None):
if where and "param_name" in where:
name = where["param_name"]
if name in self.rows:
return _FakeRow(name, self.rows[name])
return None
async def _upsert(self, where=None, data=None):
name = where["param_name"]
raw = data["update"]["param_value"]
value = json.loads(raw) if isinstance(raw, str) else raw
self.rows[name] = value
self.upsert_calls.append((name, value))
class _FakePrismaClient:
def __init__(self, initial_rows=None):
self.db = mock.MagicMock()
self.db.litellm_config = _FakeLitellmConfig(initial_rows=initial_rows)
self.jsonify_object = lambda obj: obj
@pytest.fixture
def _update_config_setup(monkeypatch):
"""Install fakes for the /config/update endpoint and return (client, prisma)."""
from litellm.proxy._types import LitellmUserRoles, UserAPIKeyAuth
from litellm.proxy.auth.user_api_key_auth import user_api_key_auth as auth_dep
def _install(initial_rows=None, store_model_in_db=True):
prisma = _FakePrismaClient(initial_rows=initial_rows)
monkeypatch.setattr("litellm.proxy.proxy_server.prisma_client", prisma)
monkeypatch.setattr(
"litellm.proxy.proxy_server.store_model_in_db", store_model_in_db
)
monkeypatch.setattr(
"litellm.proxy.proxy_server.encrypt_value_helper",
lambda value, **_: f"enc:{value}",
)
monkeypatch.setattr(
"litellm.proxy.proxy_server.invalidate_config_param",
AsyncMock(return_value=None),
)
from litellm.proxy.proxy_server import proxy_config as real_proxy_config
monkeypatch.setattr(
real_proxy_config, "add_deployment", AsyncMock(return_value=None)
)
original_overrides = app.dependency_overrides.copy()
app.dependency_overrides[auth_dep] = lambda: UserAPIKeyAuth(
user_id="test_admin",
user_role=LitellmUserRoles.PROXY_ADMIN,
api_key="sk-1234",
)
client = TestClient(app)
def _restore():
app.dependency_overrides = original_overrides
return client, prisma, _restore
return _install
def test_update_config_writes_only_sent_section(_update_config_setup):
"""A request that only touches general_settings must not write any other
section row, and must leave previously-written rows byte-identical."""
client, prisma, restore = _update_config_setup(
initial_rows={
"litellm_settings": {"drop_params": True},
"environment_variables": {"FOO": "enc:bar"},
}
)
try:
resp = client.post(
"/config/update",
json={"general_settings": {"store_prompts_in_spend_logs": True}},
)
assert resp.status_code == 200
written = {name for name, _ in prisma.db.litellm_config.upsert_calls}
assert written == {"general_settings"}
assert prisma.db.litellm_config.rows["litellm_settings"] == {
"drop_params": True
}
assert prisma.db.litellm_config.rows["environment_variables"] == {
"FOO": "enc:bar"
}
finally:
restore()
def test_update_config_can_flip_store_model_in_db_when_currently_false(
_update_config_setup,
):
"""The endpoint used to refuse all writes when store_model_in_db was
False, blocking the very request that would flip it to True."""
client, prisma, restore = _update_config_setup(store_model_in_db=False)
try:
resp = client.post(
"/config/update", json={"general_settings": {"store_model_in_db": True}}
)
assert resp.status_code == 200
assert (
prisma.db.litellm_config.rows["general_settings"]["store_model_in_db"]
is True
)
finally:
restore()
def test_update_config_environment_variables_encrypted_before_write(
_update_config_setup,
):
"""env var values must be encrypted before they hit the DB row."""
client, prisma, restore = _update_config_setup()
try:
resp = client.post(
"/config/update",
json={"environment_variables": {"OPENAI_API_KEY": "sk-secret"}},
)
assert resp.status_code == 200
stored = prisma.db.litellm_config.rows["environment_variables"]
assert stored == {"OPENAI_API_KEY": "enc:sk-secret"}
finally:
restore()
def test_update_config_litellm_settings_request_wins_for_non_callback_keys(
_update_config_setup,
):
"""Sending {"drop_params": False} when the row holds drop_params: True
must persist False (request wins). Untouched keys preserved."""
client, prisma, restore = _update_config_setup(
initial_rows={
"litellm_settings": {"drop_params": True, "set_verbose": True},
}
)
try:
resp = client.post(
"/config/update", json={"litellm_settings": {"drop_params": False}}
)
assert resp.status_code == 200
stored = prisma.db.litellm_config.rows["litellm_settings"]
assert stored["drop_params"] is False
assert stored["set_verbose"] is True
finally:
restore()
def test_update_config_success_callback_normalizes_existing_mixed_case(
_update_config_setup,
):
"""Existing mixed-case callback names (written elsewhere) must be
normalized to lowercase before union, otherwise the union dedup misses
against the lowercase incoming entry and delete_callback (lowercase
lookup) cannot find the original."""
client, prisma, restore = _update_config_setup(
initial_rows={"litellm_settings": {"success_callback": ["Langfuse", "SQS"]}}
)
try:
resp = client.post(
"/config/update",
json={"litellm_settings": {"success_callback": ["langfuse"]}},
)
assert resp.status_code == 200
stored = prisma.db.litellm_config.rows["litellm_settings"]["success_callback"]
assert set(stored) == {"langfuse", "sqs"}
finally:
restore()
# ---------------------------------------------------------------------------
# Lazy feature loading (LazyFeatureMiddleware) — verifies that optional
# routers are NOT imported at module load and ARE imported on first request
# to a matching path prefix. The same module isn't re-imported on subsequent
# requests.
# ---------------------------------------------------------------------------
class TestLazyFeatureRegistry:
"""Sanity checks on the registry shape — guards against accidental edits."""
def test_registry_entries_have_required_fields(self):
from litellm.proxy._lazy_features import LAZY_FEATURES, LazyFeature
assert len(LAZY_FEATURES) > 0
for feat in LAZY_FEATURES:
assert isinstance(feat, LazyFeature)
assert feat.name
assert feat.module_path
assert feat.path_prefixes
assert all(p.startswith("/") for p in feat.path_prefixes)
assert callable(feat.register_fn)
def test_registry_names_unique(self):
from litellm.proxy._lazy_features import LAZY_FEATURES
names = [f.name for f in LAZY_FEATURES]
assert len(names) == len(set(names)), "duplicate feature names"
class TestLazyFeaturesNotImportedAtStartup:
"""
The whole point of the refactor: gated feature modules must NOT be
present in `sys.modules` immediately after `proxy_server` imports.
"""
def test_heavy_modules_absent_at_startup(self):
# Static scan of proxy_server.py source — catches any top-level
# `from <lazy_module> import` that would defeat lazy loading.
# Importing proxy_server in a subprocess and diffing sys.modules
# would also work, but takes 60-120 s and flakes on slow CI runners.
import re
from pathlib import Path
from litellm.proxy._lazy_features import LAZY_FEATURES
proxy_server_src = (
Path(__file__).resolve().parents[3] / "litellm/proxy/proxy_server.py"
).read_text()
leaks = []
for feat in LAZY_FEATURES:
# Anchor at column 0 — indented imports inside function bodies
# are fine (deferred until the function runs).
pattern = (
rf"^(from\s+{re.escape(feat.module_path)}\s+import|"
rf"import\s+{re.escape(feat.module_path)})"
)
if re.search(pattern, proxy_server_src, re.MULTILINE):
leaks.append(feat.module_path)
assert not leaks, (
"proxy_server.py top-level imports a lazy feature module — these "
f"should be loaded via LazyFeatureMiddleware: {leaks}"
)
class TestLazyFeatureMiddleware:
"""Behavior of the middleware itself, exercised in isolation."""
@pytest.mark.asyncio
async def test_first_request_triggers_load_subsequent_does_not(self):
from fastapi import FastAPI
from litellm.proxy._lazy_features import (
LazyFeature,
LazyFeatureMiddleware,
)
loads = []
def fake_register(app, module):
loads.append(getattr(module, "__name__", "?"))
feat = LazyFeature(
name="dummy",
module_path="json", # any always-importable stdlib module
path_prefixes=("/dummy",),
register_fn=fake_register,
)
# Build a minimal ASGI receiver to satisfy the middleware contract
async def downstream(scope, receive, send):
# echo back; no-op handler
await send({"type": "http.response.start", "status": 200, "headers": []})
await send({"type": "http.response.body", "body": b""})
target_app = FastAPI()
mw = LazyFeatureMiddleware(downstream, fastapi_app=target_app, features=(feat,))
async def receive():
return {"type": "http.request", "body": b"", "more_body": False}
sent: list = []
async def send(message):
sent.append(message)
# First request matching the prefix triggers register
await mw(
{"type": "http", "path": "/dummy/x", "method": "GET", "headers": []},
receive,
send,
)
assert loads == ["json"]
# Second matching request must NOT re-register
sent.clear()
await mw(
{"type": "http", "path": "/dummy/y", "method": "GET", "headers": []},
receive,
send,
)
assert loads == ["json"], "register_fn called twice for the same feature"
# Non-matching path must not trigger anything
await mw(
{"type": "http", "path": "/unrelated", "method": "GET", "headers": []},
receive,
send,
)
assert loads == ["json"]
@pytest.mark.asyncio
async def test_concurrent_first_requests_only_register_once(self):
"""
Two requests to the same prefix arriving in parallel must result in
exactly one `register_fn` invocation — the lock prevents the import +
register from racing with itself.
"""
from fastapi import FastAPI
from litellm.proxy._lazy_features import (
LazyFeature,
LazyFeatureMiddleware,
)
loads = []
def slow_register(app, module):
loads.append(getattr(module, "__name__", "?"))
feat = LazyFeature(
name="dummy_concurrent",
module_path="json",
path_prefixes=("/dummy_c",),
register_fn=slow_register,
)
async def downstream(scope, receive, send):
await send({"type": "http.response.start", "status": 200, "headers": []})
await send({"type": "http.response.body", "body": b""})
target_app = FastAPI()
mw = LazyFeatureMiddleware(downstream, fastapi_app=target_app, features=(feat,))
async def receive():
return {"type": "http.request", "body": b"", "more_body": False}
sent: list = []
async def send(message):
sent.append(message)
async def hit():
await mw(
{
"type": "http",
"path": "/dummy_c/x",
"method": "GET",
"headers": [],
},
receive,
send,
)
await asyncio.gather(hit(), hit(), hit(), hit(), hit())
assert loads == [
"json"
], f"expected one registration despite concurrent first hits, got {loads}"
@pytest.mark.asyncio
async def test_failing_import_does_not_loop(self):
"""
If a feature's module can't be imported, the middleware should mark it
loaded anyway so subsequent requests don't repeatedly retry the failing
import (which would amplify the cost on every request).
"""
from fastapi import FastAPI
from litellm.proxy._lazy_features import (
LazyFeature,
LazyFeatureMiddleware,
)
attempts = []
def fail_register(app, module):
attempts.append("called")
raise RuntimeError("boom")
feat = LazyFeature(
name="failing",
module_path="json",
path_prefixes=("/fail",),
register_fn=fail_register,
)
async def downstream(scope, receive, send):
await send({"type": "http.response.start", "status": 200, "headers": []})
await send({"type": "http.response.body", "body": b""})
target_app = FastAPI()
mw = LazyFeatureMiddleware(downstream, fastapi_app=target_app, features=(feat,))
async def receive():
return {"type": "http.request", "body": b"", "more_body": False}
sent: list = []
async def send(message):
sent.append(message)
for _ in range(3):
await mw(
{"type": "http", "path": "/fail/x", "method": "GET", "headers": []},
receive,
send,
)
assert attempts == [
"called"
], f"failing register_fn should be invoked once, not on every request; got {attempts}"
@pytest.mark.asyncio
async def test_get_current_spend_redis_clean_miss_skips_stale_in_memory():
"""When Redis is reachable and cleanly returns None (TTL expired,
counter genuinely absent), the read must reseed from DB - NOT fall
through to per-pod in-memory which only contains this pod's writes.
Pre-fix in multi-pod deployments, in-memory contained a stale local
subset (e.g. $30) while DB had the true cross-pod total ($500). The
fall-through returned $30, enforcement passed, bypass.
"""
from litellm.caching.dual_cache import DualCache
from litellm.proxy.proxy_server import get_current_spend
counter_cache = DualCache()
counter_key = "spend:team_member:user-1:team-1"
# Per-pod stale in-memory: only this pod's writes, not cross-pod truth.
counter_cache.in_memory_cache.set_cache(key=counter_key, value=30.0)
# Redis cleanly returns None (key expired or never written on this pod).
fake_redis = AsyncMock()
fake_redis.async_get_cache = AsyncMock(return_value=None)
fake_redis.async_increment = AsyncMock(return_value=500.0)
counter_cache.redis_cache = fake_redis
# DB has the authoritative cross-pod spend.
db_row = MagicMock()
db_row.spend = 500.0
fake_prisma = MagicMock()
fake_prisma.db.litellm_teammembership.find_unique = AsyncMock(return_value=db_row)
import litellm.proxy.proxy_server as ps
orig_counter, orig_prisma = ps.spend_counter_cache, ps.prisma_client
ps.spend_counter_cache = counter_cache
ps.prisma_client = fake_prisma
try:
spend = await get_current_spend(counter_key=counter_key, fallback_spend=0.0)
assert spend == 500.0, (
f"expected DB-authoritative 500.0 on clean Redis miss, got {spend} "
f"(stale per-pod in-memory $30 would have caused multi-pod bypass)"
)
finally:
ps.spend_counter_cache = orig_counter
ps.prisma_client = orig_prisma
@pytest.mark.asyncio
async def test_get_current_spend_redis_error_falls_back_to_in_memory():
"""When Redis raises, the read should still degrade to in-memory rather
than going straight to DB - in-memory is at least same-pod-fresh and
cheaper than a DB query during a Redis outage."""
from litellm.caching.dual_cache import DualCache
from litellm.proxy.proxy_server import get_current_spend
counter_cache = DualCache()
counter_key = "spend:team_member:user-1:team-1"
counter_cache.in_memory_cache.set_cache(key=counter_key, value=42.0)
fake_redis = AsyncMock()
fake_redis.async_get_cache = AsyncMock(side_effect=ConnectionError("redis down"))
counter_cache.redis_cache = fake_redis
fake_prisma = MagicMock()
fake_prisma.db.litellm_teammembership.find_unique = AsyncMock(
return_value=MagicMock(spend=999.0)
)
import litellm.proxy.proxy_server as ps
orig_counter, orig_prisma = ps.spend_counter_cache, ps.prisma_client
ps.spend_counter_cache = counter_cache
ps.prisma_client = fake_prisma
try:
spend = await get_current_spend(counter_key=counter_key, fallback_spend=0.0)
assert spend == 42.0, (
f"expected in-memory fallback 42.0 on Redis error, got {spend} "
f"(should not have hit DB when Redis errored)"
)
# DB query should NOT have fired - in-memory short-circuits.
fake_prisma.db.litellm_teammembership.find_unique.assert_not_awaited()
finally:
ps.spend_counter_cache = orig_counter
ps.prisma_client = orig_prisma