Continuous 30s listing after first sight made the suite crawl: every
create_model slept through repeated GET /v1/models, and multi-worker misses
could reset the window. Keep the 40s first-listing budget; set
model_servable_db_sync_seconds to 0 so we return as soon as the model appears
A poll may start with remaining budget and still return after started+timeout
if the transport overruns its clamp. Recheck the first-listing deadline after
the response so a late listing does not open the continuous DB-sync phase
When less than one full poll interval remained in the first-listing budget,
the pre-sleep check returned NotServable without another /v1/models call.
Sleep only min(interval, time left) so a model that becomes listable in the
last seconds of the timeout still gets a clamped final poll
create_model returned after the first /v1/models hit that listed the model,
so chat could still land on a cold gateway worker (numWorkers>1 / peer pod)
and 400 Invalid model name. Require continuous listing for the product
default add_deployment interval (30s) after first sight so every worker has
synced from the DB; first listing still bounded at 40s
_await_model_servable used poll_timeout (120s), the spend/log read-back
budget. A stuck model reload therefore stalled every suite that creates a
deployment for two minutes before failing
Give create_model a fixed harness middle ground: model_servable_timeout=40s,
polled every 2s, with each /v1/models call capped at 5s and clamped to the
remaining deadline so one slow GET cannot overrun the wait. Happy path still
returns on the first listing. Not derived from proxy general_settings or env
Transport.get accepts an optional per-call timeout for that clamp. Unit tests
cover the deadline arithmetic and clamp without a live proxy
Add a live spend-tracking e2e that drives a streaming anthropic-format
/v1/messages request through litellm's anthropic-messages -> OpenAI Responses
adapter and asserts the consumed stream writes exactly one SpendLogs row with
nonzero cost and token counts, attributed to the calling key under
custom_llm_provider openai and the /v1/messages call_type.
The deployment is a Responses-only OpenAI model (gpt-5.3-codex), so a served,
costed row proves the Responses path was taken; the chat-completions bridge
would have failed at OpenAI on an endpoint the model does not expose. Adds a
streaming /v1/messages method to the shared Gateway and the suite client, the
model to the inline compose config and driver-model registration, a coverage
registry row (quota_management.spend_tracking.messages_bridge.logs_cost), and
the matching variant vocab entry. The _summarize spend-row detail also gains
call_type and custom_llm_provider so a failed assertion prints the fields it
asserts on.
Resolves LIT-4546
* refactor(e2e): fold claude_code HTTP probes onto shared Gateway methods
Migrate tests/e2e/claude_code/http_probe.py off its own httpx client onto the
shared transport, and promote count_tokens and native anthropic messages to
first-class Gateway methods (Gateway.count_tokens / Gateway.messages) with typed
request/response models in the shared models.py so other suites reuse them.
The probes now take an injected Gateway and issue their request through the
shared count_tokens/messages methods, reusing the split control/data-plane
routing, timeout, and typed Result handling the rest of tests/e2e uses. The wire
shape is preserved: the pydantic bodies serialize byte-for-byte to what the old
httpx probes sent, and the anthropic-version header is carried by a small
AnthropicHeaders model. httpx is gone from the module.
* test(e2e): drop unit-level probe harness test
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
---------
Co-authored-by: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
The shared proxy wrapper in tests/e2e/e2e_gateway.py was misnamed: Gateway is
not a gateway server, it is the client every suite uses to talk to the proxy
(keys, models, chat/embed/ocr, spend read-backs, poll helpers). Rename the
module to proxy_client.py and the class to ProxyClient, with build_gateway
becoming build_proxy_client and the GatewayProvider protocol becoming
ProxyClientProvider. The .gateway attribute suites held is now .proxy. Only
identifiers changed; prose and string literals that use the word gateway for the
proxy-server concept were left alone.
Each suite previously built its own instance through a per-suite build_client()
that called build_gateway() inside, duplicating the proxy wiring across suites.
There is now one session-scoped proxy fixture in tests/e2e/conftest.py; every
suite's client fixture depends on it and injects it, so the wiring lives in one
place. claude_code keeps building its own client directly since it has its own
harness and does not use the shared fixtures.
Behavior is unchanged: shared transport, data-plane/control-plane split routing,
poll budget, typed request/response models, and resource cleanup all go through
the same object.
