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5 commits
| Author | SHA1 | Message | Date | |
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yuneng-jiang
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6ca90b927c
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test(ci): repair stale tests and flaky CI infrastructure (#43983)
* test(ci): add used_client_oauth_token to the GCS pub/sub spend-log golden #43063 stamps used_client_oauth_token into spend-log metadata, so test_async_gcs_pub_sub_v1 failed on main with an extra metadata key * test(ui): give the auto-router threshold save wait room for the availability debounce #42625 keeps Save disabled while a 300ms-debounced availability check runs. This test waits for Save right after the change, so the whole debounce lands inside waitFor's 1s default and it times out under CI load. It is the recurring UI Unit Tests failure on main since #42625 landed * test(e2e): expect no pricing tier on bills for streamed calls OpenAI served at default #42870 added both the rule that a served default or standard tier bills at base pricing and records no service_tier, and streamed tests expecting the row to record 'default'. They have failed on every scheduled litellm-e2e run since. The tests now map the served tier to the pricing basis the bill must record and check input is billed at that basis's rate; the messages case registers custom rates so the rate check has something to compare against * test(e2e-ui): wait for the call-id search before hovering the logs row The row the spec hovers is already on the unfiltered first page, so it was found before the search request returned. The search response then re-rendered the table under the mouse, and the Base UI tooltip never opened. Reproduced with Playwright against a local proxy: hovering right after the fill never shows the tooltip, hovering after the search response shows the call id every time * test(e2e): run the Together structured-output case on the hybrid Qwen with reasoning off The case picked the cheapest Together row flagged supports_response_schema. DeepSeek-V4-Flash-0731 hit its cost-map deprecation date on 2026-09-29, so the pick moved to GLM-5.3-Flash, a reasoning-only model that spends the 1024-token budget thinking and returns content=None. Qwen3.5-9B is the pinned hybrid model the reasoning_effort=none case already exercises, and Together lists it with structured output support * test(integration): read the agent 365 guardrail status by its own name in spend logs The MCP shard runs under xdist against one database, and a sibling file creates a default_on pre_mcp_call content filter there. The owned proxy reloads DB guardrails, so that filter's 'success' entry could land first in guardrail_information and the test read it instead of the agent 365 verdict * test(unit): ignore asyncio's leaked-task records in the budget limiter push-failure log check gc.collect() inside the caplog window can collect a pending task an earlier test left on a closed loop, and asyncio logs 'Task was destroyed but it is pending' into this test's records. The check still counts every LiteLLM logger, and unretrieved task exceptions on this loop still go through the asserted exception handler * test(e2e-ui): fill the create-tag fields inside the dialog #42949 added 'Filter by tag name' and 'Filter by description' inputs to the Tag Management page, so page-wide getByLabel('Tag Name') and getByLabel('Description') match two elements and Playwright's strict mode fails the create step * test(integration): run integration proxies with the CI license Multi-worker proxies start each uvicorn worker in a fresh process, so every worker reads the license from its environment. Forward LITELLM_LICENSE into the proxy and test runner environments * ci: save GitHub Actions caches only from main and bump codecov-action to 5.5.5 Every pull request saved its own uv, maturin, Rust and Prisma caches, about 4.5 GB per PR, so the repository's 10 GB cache budget evicted main's entries within minutes. Pull request jobs then missed every cache, downloaded all dependencies from PyPI and hit the install step timeouts. Pull requests now restore only, and main keeps the caches warm for them. test-linting and check-ui-api-types run only on pull requests and keep saving codecov-action 5.5.4 imports its signing key from the deleted codecovsecurity keybase account, so every upload failed signature verification. 5.5.5 reads it from codecovsecops; the key ID matches the one signing the current CLI * test(unit): join the session-minting thread before collecting the handler asyncio.to_thread resumes the test as soon as the worker sets its result, while the pool thread can still hold the work item and through it the handler. gc.collect() then cannot finalize the handler and the session stays open. A pool that shuts down before the test continues drops that reference * test(integration): relaunch owned proxies that lose their port, expire idle gateway connections early owned_proxy_process released its reserved port and the proxy bound it only after full startup, so another xdist worker or an outgoing connection could take it first and the proxy exited with 'address already in use'. The launch now retries on a fresh port when that happens and stops every failed attempt. uvicorn closes idle keep-alive connections after 5 seconds and httpx expired them at the same 5 seconds, so a request sent right at that mark could reuse a socket the server was closing and get 'Connection reset by peer'. Gateway clients now drop idle connections after 2 seconds * ci(circleci): give the base SDK wheel build the same 30 minute no-output window as the Windows build The release profile builds with fat LTO and one codegen unit, so the final link of litellm-cache-s3 runs silently for minutes. Successful builds take 711 to 749 seconds, right at the default 10 minute no-output limit, and about 30% of recent runs were killed there * test(integration): model the budget-reset database outage as 10 seconds instead of 5 refused connections The proxy retries the database about every 30 seconds and each retry opens roughly one connection, so a 5-connection outage took 3 to 4 retries to clear and recovery landed between 60 and 90 seconds, straddling the test's 80 second reset window. A fixed 10 second outage still refuses the immediate reconnect and recovers on the next retry * ci: move the unit-test uv cache split into a composite action check_workflow_startup_safety sums every setup step's timeout, so the save and restore variants each counted 5 minutes although only one runs. One composite step keeps the setup ceiling at 35 minutes * test(unit): point tiktoken at the bundled cache for every unit test The rust_bridge tokenizer tests loaded o200k_base before any test in their xdist worker had imported default_encoding, so tiktoken fell back to the temp cache and tried to download under pytest-socket. Move the session fixture from litellm_core_utils/conftest.py to the root unit conftest. * test(integration): answer model discovery probes in the hosted_vllm wire tests The router's periodic upstream model info refresh sends GET /v1/models to hosted_vllm deployments, so a wire server that is live during a refresh sees an extra request. Answer the probe with an empty model list and leave it out of the provider-call assertions, matching the responses bridge tests. |
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devin-ai-integration[bot]
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0abd9267c1
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feat(tokenizer): preserve Python defaults with opt-in Rust dispatch (#42174)
* ci: benchmark and gate an installed release wheel Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * ci: simplify installed-wheel benchmark check Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * feat(rust): add native tokenizer codec Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * refactor(tokenizer): route Python tokenization through the Rust extension Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * style(lint): format tokenizer call Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * fix(packaging): restore runtime dependencies and native images Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * fix(tokenizer): preserve Python SDK behavior with Rust tokenizers * fix(tokenizer): restore compatibility paths Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * refactor(tokenizer): count custom tokenizers directly Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * fix(tokenizer): preserve caller-supplied Python tokenizer counts * fix(tokenizer): reuse packaged vocabularies in the native wheel * refactor(rust_bridge): route token counting through the catalog as RUST_OPT_IN Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * fix(spend_tracking): compare tokenizer groups by value Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * chore(deps): re-resolve filelock under the <4.0 pin Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * fix(llms): align transformation override signatures with base configs Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * build(rust): use fat LTO to keep the native wheel under the 35 MB limit Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * feat(tokenizer): preserve Python defaults with opt-in Rust dispatch * test(proxy): tolerate missing litellm.utils.Tokenizer when patching it Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * test(proxy): patch the tokenizer dispatch function instead of the removed alias Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * feat(tokenizer): give the Rust wrappers the tiktoken and tokenizers surface Callers of litellm.encoding and litellm.create_tokenizer must see the same read-only API whichever backend the catalog selects. - OpenAIEncoding mirrors tiktoken.Encoding: n_vocab, max_token_value, token_byte_values, encode_single_token, encode_with_unstable, encode_to_numpy, decode_with_offsets, is_special_token, repr; the Rust tiktoken crate keeps a Vocabulary beside each CoreBPE and reports the requested encoding name (gpt2 stays gpt2). - HuggingFaceTokenizer mirrors the read-only tokenizers.Tokenizer surface (token_to_id, id_to_token, get_vocab, get_vocab_size, get_added_tokens_decoder, num_special_tokens_to_add, padding, truncation, encode_special_tokens, from_buffer); HuggingFaceEncoding gains the char/word/token lookups, pad, truncate, set_sequence_id and merge. Mutators stay on the Python tokenizer. - from_json/from_pretrained claim the fork gate only when the huggingface feature is compiled in; the surrogate fallback matches on the Codec. - Tokenizer caching is keyed on the same catalog Context the dispatch runs on; rust_tokenizer reads the encoding name without loading an encoding; LITELLM_RUST parsing is cached. - Drop the unused tiktoken_encoding_for_model export and Error::Download. Co-Authored-By: Claude Fable 5.1 <noreply@anthropic.com> * fix(tokenizer): close the exhaustive matches with assert_never CodeQL reads a `match` over a Literal with no default arm as an implicit `None` return. `assert_never` makes the exhaustiveness explicit for both the HuggingFace tokenizer loader and the Rust token-counter factory. Co-Authored-By: Claude Fable 5.1 <noreply@anthropic.com> * feat(tokenizer): derive the fast counter from the shared tokenizer The count-only counter (`fast` feature) and the codec each parsed the same artifact: TokenCounter took the Anthropic JSON and the tiktoken rank files from Python while Tokenizer loaded them again. One parse now serves both. - FastTokenizer builds from a model another loader holds: `from_shared` takes the Arc<tokenizers::Tokenizer> the HF codec keeps, and `from_*_pairs` take the ranks the tiktoken vocabulary already parsed. - `FastCounter::fast_counter` in the core crate derives it from either codec; encodings the fast scanner does not reproduce are refused. - Native `Tokenizer.count(text, fast=False)` opts into that counter, built once per tokenizer on first use; `TokenCounter.from_tokenizer(tokenizer, fast=False)` replaces the JSON and rank-file constructors. - The Python route counts over the native tokenizers the codec path shares (`native_encoding`, `native_anthropic`) and no longer reads rank files; the packaged Anthropic tokenizer has one loader, `tokenizer_dispatch.anthropic`. - Public wrappers gain `count(text, fast=False)`. Co-Authored-By: Claude Fable 5.1 <noreply@anthropic.com> --------- Co-authored-by: Yujong Lee <yujong@berri.ai> Co-authored-by: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> Co-authored-by: Claude Fable 5.1 <noreply@anthropic.com> |
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Yujong Lee
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9b774d3dcf
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fix(ci): isolate editable Cargo cache namespace | ||
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Yujong Lee
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849269d52d
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build(rust): configure native extension profiles | ||
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yuneng-jiang
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afec9b8ab9
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perf(ci): cache the Rust build the unit shards compile from scratch (#37795)
* perf(ci): cache the Rust build the unit shards compile from scratch Every unit shard installs the workspace, and the root package builds through maturin, so each of the eleven jobs compiles litellm-rust/crates/python-bridge in release mode before a single test runs. That step measured 2m40s a shard on 2026-08-21, which is more wall clock than the entire unit tier spends running tests, and none of it was cached: the uv cache covers wheels it downloads, not wheels it builds, and a path dependency whose source moves every commit can never hit that cache anyway. A composite action now exports CARGO_TARGET_DIR to a fixed workspace path and caches it alongside the Cargo registry, keyed on Cargo.lock. Cargo rebuilds only what changed, so a warm job pays for the bridge crate rather than its whole dependency graph. Measured locally, that is 34s cold against 8s warm, including after a Python-only or Rust-only edit. The absolute path matters: uv builds the wheel from its own working directory, so a relative target directory lands the artifacts where nothing can find them again. * perf(ci): cache the Rust build in the other four workflows that sync the workspace code-quality, mcp, documentation and the schema.d.ts check each install the workspace and so each compile the bridge from scratch, measured at 138s, 177s, 163s and 154s on 2026-08-21. The lint job pays the same and is left to #37783, which already owns that file's setup section. * perf(ci): cache the Rust build in the lint job too * fix(ci): cache cargo's own target directory instead of redirecting it uv builds the wheel in place, so cargo already writes to litellm-rust/target, which test-rust.yml has cached all along. Redirecting CARGO_TARGET_DIR bought nothing and cost a GITHUB_ENV write that zizmor rejects as a code-execution path. * chore(ci): raise the job backstop for the added setup step The cargo cache is a fifth bounded setup step, so the base's setup ceiling goes 30m to 35m and every job budget follows: 55 to 60, and proxy-server's 95 to 100. check_workflow_startup_safety enforces exactly this sum, and failed on the first push without it. * perf(ci): cache the Rust build in the four remaining workflows that sync Six workflows were wired; ten install the workspace. The four left out still compile the pyo3 bridge from scratch. test-terraform-provider.yml is the one that matters per PR: its endpoint-drift job triggers on any change under litellm/proxy/**. The other three are a scheduled load check, a manual mutation run, and the staging-push counts publisher, whose gate syncs the project inside scripts/type_check_gate.py rather than in a workflow step, so nothing in the file names the build it pays for. |