* test(e2e): assert bare-key budget refusal is 429 and /key/info spend reaches the cap
* test(e2e): keep the bare-key budget assertion to the 429 refusal shape
* test(e2e): assert a team's max_budget blocks every key on the team
* test(e2e): focus the team budget case on the 429 blocking behavior
* test(e2e): harness fixes for long_context, complexity router, UI, and unit coverage
Point long_context_1m at 1M-capable models, harden complexity-smart-router
registration and spend-log assertions, fix key models dropdown selectors, and
add gateway/lifecycle/transport and claude_code unit tests
* test(e2e): harden remaining stage failures in harness
Register complexity-smart-router via create_model + callable probe, fix
create-key UI navigation race, retry management writes and budget ALB
502s, mark Vertex count_tokens N/A when unsupported, and tighten
tool_search model lists for Azure/Bedrock capability gaps
* test(e2e): drop claude_code and harness unit tests from this PR
Keep management, router, budget, and shared conftest harness fixes only
* test(e2e): restore E2E_RESULT pytest_runtest_makereport hook
Accidentally dropped in an earlier harness commit; Grafana status history
depends on these structured log lines
* test(e2e): drop management control-plane write retries
Transient 500 retries do not fix the underlying control plane failures
* test(e2e): skip stage-red claude_code cells; fix multi-window budget latency
Mark the twelve failing claude_code matrix cells skip until product/config
lands. Multi-window budget polls gpt-5.5 with max_tokens=1 instead of
Claude so the reset wait stays under ALB target idle timeout rather than
masking awselb 502s
* test(e2e): require exactly one LLM-tier spend row for complexity router
Keep alias membership for compose vs stage model names, but assert
len(served) == 1 so a leaked classifier sub-call cannot pass. Also pin
LIT-4521 skip and align LIT-4522/23/24 skip reasons
* test(e2e): harden router callable probe and multi-window budget exhaustion
_router_is_callable treated any non-success chat whose body lacked "Invalid
model name" as callable, so an unpropagated probe key (401), a generic 502, or
a connection reset let the session proceed and hit real "Invalid model name"
failures inside the tests. Require a Success outcome instead; the reload-race
400 and every infra/auth error now correctly read as not-callable.
The multi-window budget test capped the tight window at 3e-6, which gpt-5.5
exhausts on the first call but a cheaper CHEAP_OPENAI_MODEL might not within the
20-call loop, turning a reset test into a spurious "window never enforced"
failure. Drop the tight cap to 1e-9 so the first billed call exhausts it
regardless of model price; the roomy 1m window stays at 1.0 and never blocks.
* test(e2e): use a tradeoff-decision prompt for the complexity router classifier
"Is P equal to NP?" reads to the LLM classifier as a short yes/no question, so
gpt-5.5 classified it SIMPLE and the request routed to the openai backend, which
made the test fail even though the classifier was running. The tier definitions
key on what the request demands, not how hard the answer is, and a short direct
question maps to SIMPLE regardless of subject.
Swap in "Should I pay off my mortgage early or invest the extra money instead?".
It carries none of the heuristic scorer's reasoning/technical/code keywords and
stays short, so heuristic scoring still lands SIMPLE (openai), but the LLM reads
it as a decision that has to weigh tradeoffs and lands it above SIMPLE, which the
config routes to anthropic. Any non-SIMPLE tier serves anthropic, so the classifier
only has to avoid SIMPLE for the test to distinguish a real classifier run from the
heuristic fallback.
* fix(e2e): make the datadog read-back find what DataDog actually indexes
Live verification of the merged #33604 against real DataDog (us5) exposed
three read-back defects that the local-sink tests could never see; all
three fixes are verified against the real API:
- Marker search: DataDog consumes the shipped JSON message into the
event's attributes and leaves the indexed message EMPTY, so the
full-text '"marker"' query matched nothing and every test failed with
zero events. The query is now '*:*marker*', which scans all attributes
(the marker sits in messages.content); verified to return exactly the
event for the call.
- Rate limit: the Logs Search API budget is 2 requests per 10s org-wide
(x-ratelimit-name logs_public_search_api). Polling at POLL_INTERVAL=5s
sat exactly at the limit and the reader hard-failed on the first 429.
Searches now pace at DD_SEARCH_INTERVAL (10s default) and a 429 backs
off and retries up to 5 times; only non-429 failures stay hard fails.
- Envelope status: DataDog re-derives the indexed event status from the
parsed payload's status attribute ('success') and normalizes it to its
OK severity, so the assertion expects 'ok', not the shipped 'info'.
Live run: chat_completions and responses pass every assertion including
the exact response-cost cross-check; messages red-pins the LIT-4447
duplicate for real (one call -> two sync-sweep copies + one async batch
copy, same request id, confirmed in proxy debug logs). The duplicate is
race-dependent, so the pin flickers until #33589 lands.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
* test(e2e): datadog log delivery for streamed chat, messages, and responses
Rewritten from the dd-sink version (original #33566) to judge delivery on
what real DataDog ingested, matching the merged #33604 conversion: the
dd_logs reader searches events back through the Logs Search API and the
assertions validate the indexed envelope (source:litellm tag, ok status)
and the StandardLoggingPayload fields under the event's attributes.
Each streamed test drives one STREAMED call per route, asserts the stream
actually streamed (event-stream content type, >0 chunks, no upstream error
event), then pins exactly one DataDog event whose payload records
stream=true, the aggregated token count, and a response_cost equal to the
/spend/logs row for the call - a stream's headers ship before its cost
exists, so the spend row is the cross-check anchor, and the spend row and
DataDog event must also agree on total_tokens.
Coverage registry: adds logging.datadog.stream.exports_metric exercised on
chat_completions, messages, and responses.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
* Update test_datadog_log_e2e.py
---------
Co-authored-by: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
* feat(e2e): emit structured E2E_RESULT lines for package status history
Pytest progress logs only expose file basenames and collapse multi-test files
into one status-history row. Emit one logfmt E2E_RESULT per finished node with
package, file, outcome, duration_ms, node_id, and covers so Grafana can roll up
by package (stable cardinality) and drill down by node_id in Explore
* test(e2e): drop unit tests from the live e2e tree
tests/e2e is for live proxy suites only. Remove harness, coverage-registry,
and claude_code unit trees so the e2e run does not collect them
* fix(e2e): type E2E_RESULT hook for basedpyright zero-error gate
Protocol-typed covers extraction and pluggy Result typing on the
makereport hook so tests/e2e stays under the e2e basedpyright ceiling
* fix(e2e): drop unused xfailed/xpassed from E2E_RESULT Outcome
We never emit those states; xfail collapses to skipped/passed via pytest
report flags. Keep the literal honest so the dashboard only sees real outcomes
* fix(e2e): strip tests/e2e prefix when deriving E2E_RESULT package
Repo-root pytest nodeids are tests/e2e/<suite>/...; without stripping,
every line would package=tests and status history would be useless
* fix(e2e): use pytest wrapper=True instead of deprecated hookwrapper
pytest 8.1+ deprecates hookwrapper; yield returns the TestReport directly
so we return it for the outer chain and drop pluggy.Result
* fix(e2e): import e2e_result_reporter at module load
Surface a missing module as a collection-time ImportError instead of a
per-test hook failure mid-run
* test(e2e): restore coverage_registry/test_collector.py
Needed to validate registry coverage math and the checked-in cell
denominator; not a live proxy suite
* chore(e2e): establish litellm_e2e_staging integration line
Long-lived berri branch for e2e suite recovery work (LIT-4479 through LIT-4486) before merge to litellm_internal_staging
* test(e2e): remove langfuse_otel logging e2e suite (#33558)
* test(e2e): remove langfuse_otel logging e2e suite
Removes the LIT-4483 dynamic per-team/key/org langfuse_otel logging e2e tests (tests/e2e/logging/test_langfuse_e2e.py, added in #32857). The shared logging_client harness and the langfuse coverage-registry cells are left in place; only the test module is removed. The otel and prometheus logging e2e suites are unaffected.
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* test(e2e): drop orphaned langfuse coverage-registry cells
The three logging.langfuse.*.logs_spend P0 cells were only exercised by the deleted langfuse_otel e2e suite. Remove them so the coverage registry has no orphaned rows.
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
---------
Co-authored-by: yucheng <yucheng@berri.ai>
Co-authored-by: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* fix(e2e): log into the react admin ui in the management browser fixture (#33562)
The management ui_page fixture drove the old server-rendered login form: it clicked input[type="submit"] and treated wait_for_url("**/ui/**") as the done signal. /ui/ now serves the react (antd) dashboard whose submit is a <button type="submit">, so the click waited out the full 30s timeout and errored every browser test in the suite. wait_for_url also matched instantly because the login page already lives at /ui/, so on the fast path the fixture navigated before the auth cookie landed and got bounced back to login.
Click the antd submit button and wait for the token cookie loginCall sets on document.cookie, the real post-login signal.
Co-authored-by: Mubashir Osmani <mubashir@berri.ai>
Co-authored-by: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* fix(e2e): make ui login readiness robust to httpOnly token cookies (#33564)
The login readiness check waited only on document.cookie including token=, which is empty when the token cookie is httpOnly. If the server ever sets it via a Set-Cookie header, the wait would spin to the 30s timeout and silently reproduce the original hang. Also accept the login form detaching (#username gone after the post-login redirect) so readiness holds regardless of how the cookie is delivered.
Co-authored-by: Mubashir Osmani <mubashir@berri.ai>
Co-authored-by: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
---------
Co-authored-by: devin-ai-integration[bot] <158243242+devin-ai-integration[bot]@users.noreply.github.com>
Co-authored-by: yucheng <yucheng@berri.ai>
Co-authored-by: Mubashir Osmani <mubashir@berri.ai>
* refactor(e2e/claude_code): align proxy env names with the rest of tests/e2e
Every claude_code compat cell used to read its own `LITELLM_PROXY_BASE_URL` and `LITELLM_PROXY_API_KEY` and duplicate the same 12-line "missing env, hard fail" block. The rest of `tests/e2e/` reads `LITELLM_PROXY_URL` and `LITELLM_MASTER_KEY` from `e2e_config.py`, so anyone standing up a live proxy for one suite had to export a second spelling for claude_code, and every cell repeated the same boilerplate.
Centralize the resolution in `claude_code/_env.py`. `resolve_proxy()` prefers the suite-wide `LITELLM_PROXY_URL` / `LITELLM_MASTER_KEY` names and falls back to the legacy pair so existing CI wiring on stage keeps working during the roll-out. `require_proxy(compat_result)` is the one-liner cells call to bind `(base_url, api_key)` or hard-fail with a message that names both spellings.
55 cell files, `_basic_messaging.py`, and the driver's own unit-test fixture now go through the helper. `run_compat.sh` accepts either spelling and normalizes to the primary names before invoking pytest. `cron_vm/run_daily.sh` exports the primary names when launching pytest.
`_pr_gate_unit_tests/test_env_resolution.py` pins the resolution rules so a future edit cannot silently reintroduce the drift: primary names win on tie, legacy names still resolve when primary is unset, mixed URL-primary key-legacy still resolves, empty-string exports are treated as unset, `require_proxy` names both spellings in its error message.
Net diff: 71 files, +370/-1240.
* fix(e2e): anchor claude_code Bash pin at parents[1] so container run collects
`test_bash_tool_restrictions.py` derived `REPO_ROOT = Path(__file__).resolve().parents[4]` and then joined `tests/e2e/claude_code/<feature>`. That works locally, but the stage container mounts tests/e2e/ at /app/e2e/, so parents[4] resolves to filesystem root and the `_bash_cells()` assertion looks for `/tests/e2e/claude_code/tool_use` — a path that doesn't exist. Collection interrupts before any test runs, so the entire e2e suite appears broken.
Fix: `CLAUDE_CODE_DIR = Path(__file__).resolve().parents[1]` resolves to the sibling `claude_code/` dir in either layout, and the `relative_to(REPO_ROOT)` calls become `relative_to(CLAUDE_CODE_DIR)` so test IDs and error messages read the same.
Adds `test_claude_code_dir_anchor_is_layout_independent` as a regression pin: it checks the anchor lands on a directory named `claude_code` that contains this test file, which would fail under the old parents[4] anchor when run from /app/e2e/.
* feat(e2e/claude_code): register compat deployments via /model/new from a session fixture
Every compat cell hardcodes a virtual model name like `claude-sonnet-4-6` or `claude-sonnet-4-6-bedrock-invoke` and hits the proxy expecting it to be routable. On stage those live in the deployed model_list; locally the `docker-config.yaml` under tests/e2e/ only declares one of them, so anything past haiku 400s with `Invalid model name`.
`claude_code/test_config.yaml` is the ground-truth compat matrix config the deployment already uses. `_compat_models.py` loads it, normalizes the yaml keys pydantic would silently drop (vertex_ai_* → vertex_*), and selects the subset whose provider credentials are present in the environment. An autouse session fixture in `conftest.py` POSTs each selected deployment to `/model/new`, blocks until it is servable on the data plane, and tears them all down on session exit. Skips silently when the proxy env is unset so pure-unit runs stay hermetic.
`test_compat_models.py` pins the invariants that keep this safe. Every cell-referenced name must have a yaml entry (drift check catches a cell probing a name the fixture never registered); the yaml has no unused declarations; the fixture registers exactly 15 deployments (3 tiers × 5 provider surfaces); vertex_ai_* yaml keys populate the pydantic body's vertex_* fields (they got silently dropped historically); Azure needs both AZURE_FOUNDRY_* env vars; Bedrock lifts creds from the ambient AWS chain; Vertex needs both the yaml refs AND ambient GCP credentials.
* refactor(e2e/claude_code): inject env + runner instead of monkeypatching
`require_proxy` and `_basic_messaging.run_basic_messaging_cell` now take the env mapping (and the CLI runner) as constructor-style arguments with `os.environ` and `run_claude_models_parallel` as defaults. Tests exercise the branching by passing dicts and callables directly, so `monkeypatch.setenv` and `monkeypatch.setattr(_basic_messaging, "run_claude_models_parallel", ...)` are gone from every unit test in this refactor's blast radius.
`test_env_resolution.py` drops the `monkeypatch.setenv`/`delenv` fixtures and passes `env={...}` dicts to `require_proxy`. Added a new pinned check that a successful resolution leaves `compat_result` untouched, and split the "unset env" test into three explicit shapes (empty, primary-only, legacy-only) so a regression that swaps the precedence rule can no longer hide behind a single monkeypatched fixture.
`test_basic_messaging.py` (driver) replaces the `_install_fake_runner(monkeypatch, ...)` helper with `_make_fake_runner(...)` that returns a `(callable, captured_dict)` pair the test passes in via the helper's new `runner=` kwarg. Also drops the autouse `_proxy_env` fixture in favor of a module-level `_PROXY_ENV` dict each test wires through the helper's new `env=` kwarg. Added a regression pin that a missing-env call hard-fails without ever invoking the runner (so the guard order stays correct).
`test_run_daily_pytest_scrubs_env.py` updates its pin to assert the new suite-wide env spellings (`LITELLM_PROXY_URL` / `LITELLM_MASTER_KEY`) instead of the legacy `LITELLM_PROXY_BASE_URL` / `LITELLM_PROXY_API_KEY` that `run_daily.sh` used to export.
* handwrote rules
* test(e2e): datadog log delivery for successful chat, messages, and responses
Covers logging.datadog.success.exports_metric on all three routes: one
successful non-streaming call must reach the DataDog logs intake as exactly
one log event whose StandardLoggingPayload message carries the model group,
real token counts, and a response cost equal to the x-litellm-response-cost
header of the same response. Delivery is judged at the intake: the compose
stack gains a dd-sink service recording every batch the datadog callback
ships via the DD_BASE_URL testing override, and a typed reader replays it.
Writing these caught a live product bug: /v1/messages double-logs every
success (two byte-identical events per call), filed as LIT-4447; the messages
test tolerates byte-identical duplicates of the one event until it lands,
while a second differing event still fails
* test(e2e): address review findings on the datadog delivery suite
Consolidates the fresh-key first_ok helper into logging_client now that the
otel PR it mirrored has merged (both test files use the shared copy), moves
intake batch parsing into a helper so no path can leave the batch unbound,
and gives the sink's /health endpoint a truthful text/plain content type
* test(e2e): tolerate same-logical-event duplicates by call id, not byte identity
A clean LIT-4447 repro showed the duplicated payload is built twice and can
mint a fresh synthetic completion id per emission, arriving as two separate
intake POSTs with the same litellm_call_id and identical substantive fields.
Byte-identity was therefore a flaky criterion; duplicates now qualify only
when they share the call id, call type, model group, tokens, and cost, and a
second differing event still fails
* test(e2e): assert the scenario strictly; the messages test is the LIT-4447 regression pin
Per review direction the tests now assert exactly what the scenario promises:
exactly one DataDog log event per successful call, on every route. The
/v1/messages test therefore fails on current code against the known
double-log (LIT-4447) and is its regression pin; it goes green when the fix
lands. The duplicate-tolerance machinery is removed
* Simplify docstrings for DataDog log tests
Removed redundant phrasing about cost cross-checking in docstrings.
* Update test_datadog_log_e2e.py
* fix(complexity_router): return empty dict from _classifier_call_metadata when metadata is absent
The LLM classifier reads request_kwargs.get("litellm_metadata"), but the proxy stores request metadata under "metadata", so this returned None. _classifier_call_metadata then passed None straight through to the classifier acompletion call, which assumes a dict and blows up with 'NoneType' object has no attribute 'update'; the router swallowed it and silently fell back to heuristic scoring, so the configured LLM classifier never ran. Returning an empty dict keeps the classifier call well-formed.
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* test(e2e): cover complexity-router LLM classifier routes over the proxy
Add a live e2e regression for the complexity auto-router: a lexically simple but hard prompt ("Is P equal to NP?") is routed by the LLM classifier to the higher-tier anthropic backend, read back from the spend log's model. Before the metadata fix the classifier silently crashed and the router fell back to heuristic SIMPLE scoring on the openai backend, so this test fails pre-fix and passes post-fix.
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
---------
Co-authored-by: Krrish Dholakia <krrishdholakia@berri.ai>
Co-authored-by: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* test(e2e): OTEL trace completeness on /v1/messages
Extends the LIT-3787 trace-completeness suite to the Anthropic-native route:
one successful non-streaming /v1/messages call must land at the destination as
ONE connected trace (root SERVER span + auth/db/cost children + gen-AI CLIENT
span, no dangling parents). Adds the raw /v1/messages sender to the logging
suite client.
* test(e2e): reuse the shared AnthropicMessagesBody per review
Drops the duplicate /v1/messages request model in favor of the one models.py
already provides (budget_client uses the same one), passes max_tokens at the
call site to match the sibling chat test, notes in the docstring why the
gen-AI span is named chat on this surface, and adopts the hardened read-back
signature
* test(e2e): author the messages trace test docstring
* test(e2e): declare the messages surface on the covers marker
* test(e2e): otel trace completeness on /v1/responses (#33134)
* test(e2e): OTEL trace completeness on /v1/responses
Extends the LIT-3787 trace-completeness suite to the OpenAI Responses API
route: one successful non-streaming /v1/responses call must land at the
destination as ONE connected trace. Adds the raw /v1/responses sender, a
CHEAP_OPENAI_MODEL config constant, and registers responses in the otel
registry cell's exercised_on.
* test(e2e): author the responses trace test docstring
* test(e2e): declare the responses and chat surfaces on the covers markers
* fix(ui): scope key models dropdown options to the key's team
A teamless key no longer offers the all-team-models option in the create and
edit forms; the backend expands that sentinel to the full proxy model list when
no team is attached, which is rarely what the user intended. A team key no
longer surfaces the all-proxy-models sentinel that leaks in verbatim when the
team's own model list carries it; the dropdown keeps All Team Models plus the
team's individual models.
Adds browser coverage to the management e2e suite: playwright (an optional
dependency behind importorskip) drives the proxy-served dashboard at /ui,
asserts the dropdown options a real user sees for teamless and team keys on
both create and edit, and walks the create modal end to end, reading the
persisted key back through /key/info.
* fix(ui): offer all-proxy-models on teamless keys in the models dropdown
A teamless key has no team allowlist to inherit, so the dropdown now offers All
Proxy Models in place of All Team Models on both the create and edit forms, with
the same exclusive-selection handling. Component and browser e2e tests updated to
pin the swapped option pair; the teamless create case now also walks the modal end
to end and reads the persisted key back through /key/info.
* test(ui): update no-team key creation spec to pick All Proxy Models
The create modal no longer offers All Team Models without a team; the teamless
path now offers All Proxy Models, which is what this spec exercises
* fix(ui): gate All Team Models on the team object being loaded
When a key has a team_id but the teams prop does not yet include the matching team, availableModels stays empty and the models dropdown rendered All Team Models on its own with nothing to compare against. Gate the option on the team object being present so it only appears once team models are known, and add a regression test for the loading state
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* fix(ui): filter all-proxy-models from teamless model fetch in key edit form
The teamless fetch path stored modelAvailableCall results without excludeProxyWideSentinel, so an all-proxy-models entry in the response rendered a second option colliding with the hardcoded All Proxy Models sentinel. Apply the same filter used on the team path and add a regression test asserting the sentinel option is not duplicated
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
---------
Co-authored-by: Mubashir Osmani <mubashir@berri.ai>
Co-authored-by: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
Introduce the e2e coverage denominator: 282 behavior cells across the six
tracking modules (LLMs, MCPs, Management/UI, Reliability & Performance,
Logging & Guardrails, Other), one validated YAML row each, plus a collector
that diffs the registry against @pytest.mark.covers markers and reports
coverage per module.
The registry rows validate against a pydantic discriminated union so a row
cannot carry a field from another module. The collector is static: a
collect-only pass reads the markers, so it runs no test and needs no live
proxy. Register the covers marker suite-wide so that pass works under
--strict-markers.
This is a draft for review. Tiers are proposed rather than signed off, and a
few cells still need a support check or a prune.
