* test(e2e): add a HashiCorp Vault secret manager lane
key_management_system had no end-to-end coverage: the Rust crates and the
Python unit tests all run against mocked managers. This adds a secret_manager
suite that drives a proxy configured with hashicorp_vault against a real Vault.
The tests seed a fresh secret name per test with the runner's OPENAI_API_KEY and
register a deployment pointing at os.environ/<name>. The proxy's env never holds
that name, so get_secret's os.environ fallback cannot mask a broken manager, and
a bogus value in Vault must come back as the provider's 401. Virtual keys are
checked written to and removed from Vault under prefix_for_stored_virtual_keys.
The setting is global to the proxy, so the lane has its own config and the
secret_manager_vault opt-in marker, and stays out of the per-PR selector.
Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
* test(e2e): make the secret manager suite backend-agnostic
One marker and opt-in (secret_manager / E2E_SECRET_MANAGER=<system>) pick the
backend from secret_backends.BACKENDS. The tests reach the manager through a
SecretStore protocol, and each backend contributes a secret_store_<system>.py
module, a registry entry, and gateway/secret_manager_<system>_ci_config.yml.
requires_capability deselects tests a backend cannot support (CyberArk does
not delete), and test_secret_backends.py checks every lane config against its
backend without a live stack.
Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
* test(e2e): add a CyberArk Conjur secret manager lane
Adds cyberark as the second secret_manager backend: a Conjur store over its
REST API (policy-declared variables, raw-text values, policy-patch teardown),
its lane config, and a registry entry without deletes_stored_keys, since the
proxy's CyberArk delete answers not_supported and Conjur keeps the key.
secret_manager/backend.sh up|down <system> boots any backend in Docker and
writes proxy.env and tests.env, so every lane runs the same way; the registry
test checks the script boots exactly the registered backends. e2e_http gains
send_text_external for APIs that speak raw text rather than JSON.
Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
* fix(e2e): give the secret manager suite a client with .proxy and address review
The shared resources fixture reads client.proxy, so a bare ProxyClient errored every
live test at setup. backend.sh now writes its env under a per-user directory with
umask 077, the markerless unit tests are gone per tests/e2e/AGENTS.md, and routine
comments are trimmed.
Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
---------
Co-authored-by: Claude Opus 5 <noreply@anthropic.com>
Eight directories the misc shard named moved to tests/unit on 2026-09-20, and one
missing path makes pytest-xdist collect [0 items] for the whole shard, which the
exit-5 tolerance turned into a green required check running nothing. The shared
Run tests step now drops a path that does not exist with a :⚠️: and runs
pytest over the rest, keeping option tokens verbatim.
Co-authored-by: mateo-berri <277851410+mateo-berri@users.noreply.github.com>
* fix(otel): honor SSL_CERT_FILE and ssl_verify in OTLP HTTP exporters
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* test(otel): assert OTLP HTTP TLS behavior against a real TLS sink
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* test(otel): assert rejected exports by outcome, not by exception type
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* fix(otel): honor SSL_CERT_FILE and ssl_verify in the v2 OTLP HTTP exporters
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* refactor(otel): hoist otlp_tls imports and type the TLS sink fixture
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* test(e2e): gate the OTLP TLS export test behind an otel_tls opt-in
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* docs(e2e): drop CONTRIBUTING.md edit
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>
Co-authored-by: yucheng <yucheng@berri.ai>
* fix(langsmith): json.dumps with default=str so non-serializable metadata does not crash batch flush
Serialize the runs/batch payload with json.dumps(default=str, allow_nan=False) and send it as content= with an explicit Content-Type, so datetime, Decimal and similar metadata values no longer raise TypeError and drop the batch. Forward content= on the AsyncHTTPHandler retry path so a retried batch re-sends the identical body
Replaces #39133, which was cut from the retired staging branch and conflicts with main
Co-authored-by: Damien Smrt <dsmrt@users.noreply.github.com>
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* test(langsmith): drop test docstrings and replace monkeypatch with a client-injecting handler
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* test(langsmith): add live e2e for non-native metadata reaching LangSmith
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* test(langsmith): scope the e2e docstring to the values the test injects
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* test(http_handler): close injected retry clients
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* test(e2e): deselect the LangSmith live e2e on the stage-mirror stack
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
---------
Co-authored-by: yucheng <yucheng@berri.ai>
Co-authored-by: Damien Smrt <dsmrt@users.noreply.github.com>
Co-authored-by: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* fix(e2e-stack): print add-mask lines only under GitHub Actions
* refactor(e2e-stack): inline the add-mask lines into main
---------
Co-authored-by: mateo-berri <277851410+mateo-berri@users.noreply.github.com>
* fix(otel v2): map completions, images, speech, transcription and moderation output onto the generation output
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* fix(redaction): redact text completion choices in the standard logging payload
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* test(e2e): compare decoded generation output text and follow the live moderation verdict
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* test(otel v2): compare logged byte counts with the received media and move e2e schemas into models.py
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* ci(e2e): keep the otel_v2 Langfuse output e2e file out of the stage-mirror gate it cannot run in
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>
* 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>
The Buildkite ephemeral stack runs the gateway in another pod, so it cannot reach the pytest host's provider edge. The GitHub changed-e2e lane runs gateways on the runner and sets E2E_PROVIDER_EDGE_HOST_REACHABLE
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
The changed-test gate booted its stage-mirror stack without files_settings
or finetune_settings, so every raw upload with a custom_llm_provider hit a
500, and it exported the whole provider env into the gateways, so the
AWS_ROLE_NAME the assume-role test needs made the GovCloud deployment run
an AssumeRole with its static keys. The gate also deleted its pytest output,
so a red run left nothing to read. The mirror config now carries the
openai, azure, and vertex_ai file settings, gateways start without
AWS_ROLE_NAME, and the workflow uploads the pass logs and junit files with
every secret value, every field of a JSON-valued secret, and their
XML-escaped forms replaced before the raw files are removed.
