* test: point router/completion/triton tests at the local fake OpenAI endpoint
The shared Railway-hosted mock (exampleopenaiendpoint-production.up.railway.app)
takes down unrelated CI jobs whenever it is unreachable. #30695 moved the mounted
proxy configs onto a job-local fake server but left these in-Python api_base
literals pointing at the dead host, so litellm_router_testing, local_testing_part1,
local_testing_part2 and llm_translation_testing still fail with a 404
"Application not found" when Railway is down
Resolve the api_base from FAKE_OPENAI_API_BASE (default http://127.0.0.1:8190)
through a shared helper, auto-start the canned server from the local_testing and
llm_translation conftests when nothing is already serving, and extend the server
with a Triton embeddings route and a slow-endpoint delay so the triton and
latency-timeout tests run fully offline. The deliberately broken fallback URL is
left as-is so fallback handling still has a failing upstream
* fix: ignore non-loopback FAKE_OPENAI_API_BASE so the local mock is used in CI
* fix: drop 0.0.0.0 from loopback hosts, an unreliable client connect target
* fix(tests): keep fake OpenAI mock alive across xdist workers
ensure_fake_openai_endpoint registered atexit on the worker that spawned
the subprocess, so under -n 4 the first worker to drain its queue would
terminate the shared mock while siblings were still hitting it. Detach
the child via start_new_session and drop the per-worker teardown; reuse
on /health handles re-runs and CI containers clean up themselves
* feat(triton): add embedding usage estimation for self-hosted responses
Populate Triton embedding usage from request input using token counting with a safe fallback so cost/observability flows work even when provider usage is missing.
Made-with: Cursor
* fix(triton): sum per-input embedding token counts for batches
Joining batch strings with newlines before token_counter added spurious
tokens. Count each input separately and sum, matching OpenAI-style usage.
Made-with: Cursor
* fix(triton/completion/transformation.py): remove bad_words / stop words from triton call
parameter 'bad_words' has invalid type. It should be either 'int', 'bool', or 'string'.
* fix(proxy_track_cost_callback.py): add debug logging for track cost callback error
