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* tests: add e2e tests for spend, budgets and llms * style: make chained comparison of status_code clearer Co-authored-by: greptile-apps[bot] <165735046+greptile-apps[bot]@users.noreply.github.com> * remove e2e_tests folder * test: add spend tracking tests * fix: p0 issues, added types and shared functions for each test suite * style: carry clearer status_code comparison into renamed e2e dir * refactor: migrate to gateway client * fix: add new tests, split gateway * test(e2e): add live batches suite across providers and routing scenarios * test(batches): cover real cost tracking on completed batch retrieve * test(e2e): assert managed vs raw file and batch id shapes per routing scenario * test(e2e): assert full response shape of each batches and files endpoint * test(e2e): only accept transitional statuses for a freshly created batch * test(prompt-factory): make test_convert_url deterministic with a data URL picsum.photos is down (HTTP 522), so test_convert_url failed on every run. Swap the live external image for an inline data: URL and assert the round-trip through convert_url_to_base64 genuinely. A data URL is already inline base64 image data, so convert_url_to_base64 now short-circuits it instead of attempting an impossible HTTP fetch; add a regression for that branch in the mapped image_handling test * fix: pass through async image data urls * fix(image-handling): short-circuit data URLs in async path too Bugbot flagged that convert_url_to_base64 returns data: base64 URLs unchanged but async_convert_url_to_base64 still tried to fetch them, so async OCR flows (Bedrock, Azure) would reject inline images the sync path accepts. Add the same guard to the async function and a regression test that asserts the async path returns the data URL without touching the HTTP client * Fix: openai batches lifecycle * Fix: add e2e azure openai tests * Fix e2e for vertex ai * Add all models for testing * test(managed-files): assert idempotent upsert in store_unified_file_id store_unified_file_id switched from create to upsert to avoid UniqueViolationError when re-storing the same unified_file_id (e.g. batch output files stored before metadata is available). Update the unit test to assert the upsert call and its create payload instead of the removed create call. * test(batches): reconcile vertex_ai native batch-id comment with fallback guard * fix(test-config): keep rust-ocr models in model_list by moving files_settings after it * fix(test-config): move batch models after OCR block to keep merge with internal_staging clean * fix(batches): use '24hrs' completion window and allow managed-files listing with provider filter Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com> * style: ruff format transformation.py and endpoints.py Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com> * fix(e2e/batches): set Azure raw_model to gpt-4.1-mini-batch to match deployed model Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com> * fix(vertex-ai/batches): correct completion_window to 24h per Literal type definition * test(vertex-ai/batches): align completion_window assertion to 24h * fix: update managed file metadata on upsert --------- Co-authored-by: mubashir1osmani <mubashir.osmani777@gmail.com> 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: Cursor Agent <cursoragent@cursor.com> Co-authored-by: Claude Sonnet 4.6 <noreply@anthropic.com> |
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| .. | ||
| batches | ||
| budgets | ||
| gateway | ||
| llm_translation | ||
| realtime | ||
| spend_tracking | ||
| CLAUDE.md | ||
| conftest.py | ||
| CONTRIBUTING.md | ||
| e2e_config.py | ||
| e2e_gateway.py | ||
| e2e_http.py | ||
| lifecycle.py | ||
| models.py | ||
| pytest.ini | ||
| test_lifecycle.py | ||
| transport.py | ||