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Commits
| Author | SHA1 | Message | Date | |
|---|---|---|---|---|
 Mateo WangandGitHub
|
2c733c00f5 |
chore(ci): modernize model references in tests and configs (#27856)
* test: modernize models used in CircleCI e2e test suites
Replaces obsolete models (gpt-4o, gpt-4o-mini, gpt-3.5-turbo,
claude-3-5-sonnet-20240620, claude-sonnet-4-20250514) with current
equivalents across the e2e_openai_endpoints and
proxy_e2e_anthropic_messages_tests CircleCI jobs.
- gpt-4o -> gpt-5.5 (responses API e2e tests)
- gpt-4o-mini -> gpt-5-mini (websocket responses, oai_misc_config)
- gpt-4o-mini-2024-07-18 -> gpt-4.1-mini-2025-04-14 (fine-tuning,
still actively fine-tunable)
- gpt-4 / gpt-3.5-turbo target_model_names example -> gpt-5.5 /
gpt-5-mini
- bedrock claude-3-5-sonnet-20240620 batch entry -> haiku-4-5-20251001
(also aligning oai_misc_config model_name with what
test_bedrock_batches_api.py actually requests)
- bedrock claude-sonnet-4-20250514 (deprecated, retires 2026-06-15)
-> claude-sonnet-4-5-20250929
* test: point bedrock-claude-sonnet-4 alias at Sonnet 4.6, not 4.5
Greptile/Cursor flagged that after the previous commit, the
bedrock-claude-sonnet-4 alias collided with bedrock-claude-sonnet-4.5
(both pointed to claude-sonnet-4-5-20250929). Rename to
bedrock-claude-sonnet-4.6 and point it at the Sonnet 4.6 Bedrock ID
(us.anthropic.claude-sonnet-4-6, already in the litellm model
registry) so the alias name matches the underlying model version.
* test: modernize models across remaining CI-mounted configs & tests
Expands the modernization sweep to all CircleCI-mounted proxy configs
and to test directories where the model literal is a fixture/route key
(not the test's subject).
Config changes:
- proxy_server_config.yaml: bump gpt-3.5-turbo / gpt-3.5-turbo-1106 /
gpt-4o / gemini-1.5-flash / dall-e-3 underlying models; rename
gpt-3.5-turbo-end-user-test alias to gpt-5-mini-end-user-test; bump
text-embedding-ada-002 underlying to text-embedding-3-small. User-
facing aliases (gpt-3.5-turbo, gpt-4, text-embedding-ada-002, etc.)
preserved for backward compatibility with tests.
- simple_config.yaml, otel_test_config.yaml, spend_tracking_config.yaml:
bump gpt-3.5-turbo underlying to gpt-5-mini.
- pass_through_config.yaml: claude-3-5-sonnet / claude-3-7-sonnet /
claude-3-haiku entries replaced with claude-sonnet-4-5 / claude-
haiku-4-5 / claude-opus-4-7.
- oai_misc_config.yaml: align alias name with the gpt-5-mini rename.
Test changes (proactive: claude-sonnet-4-20250514 / claude-opus-4-
20250514 retire 2026-06-15):
- tests/llm_translation/test_anthropic_completion.py: bump 3 references
+ paired Vertex AI ID to claude-sonnet-4-5.
- tests/llm_translation/test_optional_params.py: bump 2 references.
- tests/pass_through_unit_tests/test_anthropic_messages_passthrough.py
and test_bedrock_anthropic_messages_test.py: bump router fixtures
using the deprecated model IDs.
- tests/pass_through_unit_tests/base_anthropic_messages_tool_search_test.py:
modernize docstring examples.
- tests/test_end_users.py: update references to renamed alias.
* test: modernize placeholder model literals in router_unit_tests
Mass replace_all on fixture/placeholder model literals across the
router_unit_tests/ suite (model name is a routing key / label, not the
test subject). Sub-agent sweep so far — additional commits will follow
for logging_callback_tests/, enterprise/, top-level tests/test_*.py,
and other CI-mounted dirs.
Mappings applied:
- gpt-3.5-turbo -> gpt-5-mini
- gpt-4 (bare) -> gpt-5.5
- gpt-4o (bare) -> gpt-5
- text-embedding-ada-002 -> text-embedding-3-small
- claude-3-sonnet-20240229 / claude-3-opus-20240229 /
claude-3-haiku-20240307 / claude-3-5-sonnet-20240620 ->
claude-sonnet-4-5-20250929 / claude-opus-4-7 /
claude-haiku-4-5-20251001 as appropriate
Explicitly preserved:
- gpt-4o-mini-* variants (transcribe, tts, etc.) where they're current
- gpt-4-turbo / gpt-4-vision-preview / gpt-4-0613 (subject literals)
- JSONL batch body literals
- Mock LLM response model fields (must match upstream)
- Fake/mock identifiers
* test: modernize placeholder model literals across remaining CI suites
Sub-agent sweep across logging_callback_tests/, guardrails_tests/,
enterprise/, pass_through_unit_tests/, otel_tests/,
llm_responses_api_testing/, batches_tests/, spend_tracking_tests/,
litellm_utils_tests/, unified_google_tests/, and a few top-level
tests/test_*.py files where the model literal is a fixture or
placeholder (router model_list, mock standard logging payload, mock
callback data) rather than the test's subject.
Mappings applied (see scope notes below):
- gpt-3.5-turbo -> gpt-5-mini
- gpt-4 (bare) -> gpt-5.5
- gpt-4o (bare) -> gpt-5.5 (corrected from initial gpt-5 — bare gpt-5
is not a valid OpenAI alias; only gpt-5.5 / gpt-5.4 / gpt-5.2-codex
/ gpt-5-mini exist)
- gpt-4o-mini (bare) -> gpt-5-mini
- text-embedding-ada-002 -> text-embedding-3-small
- claude-3-sonnet-20240229 -> claude-sonnet-4-5-20250929
- claude-3-opus-20240229 -> claude-opus-4-7
- claude-3-haiku-20240307 -> claude-haiku-4-5-20251001
- claude-3-5-sonnet-20240620/20241022 -> claude-sonnet-4-5-20250929
- claude-3-7-sonnet-20250219 -> claude-sonnet-4-6
- gemini-1.5-flash -> gemini-2.5-flash
- gemini-1.5-pro -> gemini-2.5-pro
Explicitly preserved (not modernized):
- llm_translation/ tests where model is the SUBJECT (provider-specific
translation/transformation logic). Only the deprecated 20250514
references were already bumped in a prior commit.
- Cost-calc / tokenizer subject tests in test_utils.py (skip-ranges
documented by the sub-agent).
- Bedrock model IDs in test_health_check.py path-stripping tests.
- JSONL batch request bodies and mock LLM response bodies (must match
upstream literal).
- Langfuse expected-request-body JSON fixtures (cost values are exact-
match-asserted; changing the model would shift response_cost).
- gpt-3.5-turbo-instruct (text-completion endpoint; no modern OpenAI
equivalent).
- Top-level tests calling the proxy through user-facing aliases
(gpt-3.5-turbo, gpt-4, text-embedding-ada-002, dall-e-3) — aliases
in proxy_server_config.yaml stay; only the underlying model was
bumped.
- tests/test_gpt5_azure_temperature_support.py (the test's whole point
is model-name handling).
- Fake / mock / openai/fake identifiers.
Notable side fixes:
- test_spend_accuracy_tests.py: UPSTREAM_MODEL now matches what
spend_tracking_config.yaml's proxy actually routes to (gpt-5-mini),
resolving a latent inconsistency.
- proxy_server_config.yaml: bare `gpt-5` alias renamed to `gpt-5.5`
(bare gpt-5 is not a valid OpenAI alias).
- test_batches_logging_unit_tests.py: explicit_models list entries
kept distinct (gpt-5-mini + gpt-5.5) after bulk rename.
* test: fix CI failures from model modernization sweep
CI surfaced 4 categories of regression from the bulk modernization:
1. Azure deployment names are customer-specific. Reverted:
- tests/litellm_utils_tests/test_health_check.py: azure/text-
embedding-3-small -> azure/text-embedding-ada-002 (the CI Azure
account does not have a text-embedding-3-small deployment).
- tests/logging_callback_tests/test_custom_callback_router.py:
same revert for two router fixtures driving aembedding.
2. gpt-5 family does not accept temperature != 1. Tests that pass a
custom temperature swapped from gpt-5-mini to gpt-4.1-mini (modern
non-reasoning OpenAI mini that still accepts temperature/logprobs):
- tests/logging_callback_tests/test_datadog.py
- tests/logging_callback_tests/test_langsmith_unit_test.py
- tests/logging_callback_tests/test_otel_logging.py
3. proxy_server_config.yaml's gpt-3.5-turbo-large alias was routing to
gpt-5.5 (a reasoning model that rejects logprobs). The proxy test
tests/test_openai_endpoints.py::test_chat_completion_streaming
exercises logprobs/top_logprobs through that alias. Bumped the
underlying model to gpt-4.1 (non-reasoning, still modern).
4. tests/logging_callback_tests/test_gcs_pub_sub.py asserts against a
pinned JSON fixture (gcs_pub_sub_body/spend_logs_payload.json) with
hardcoded model="gpt-4o" and a model-specific spend value. Reverted
the litellm.acompletion calls in the test to model="gpt-4o" so the
fixture's exact-match assertions still hold.
5. tests/pass_through_unit_tests/test_anthropic_messages_passthrough.py:
anthropic.messages.create routing to openai/gpt-5-mini returned an
empty content[0] with max_tokens=100 (reasoning-token consumption).
Swapped to openai/gpt-4.1-mini.
* test: fix Assistants API model + 2 cursor[bot] review nits
1. pass_through_unit_tests/test_custom_logger_passthrough.py: gpt-5.5
isn't accepted by the /v1/assistants endpoint
("unsupported_model"). Switch to gpt-4.1-mini (modern, Assistants-
API-supported, non-reasoning).
2. example_config_yaml/pass_through_config.yaml: the previous sweep
bumped the claude-3-7-sonnet alias to claude-opus-4-7, which is a
tier change (Sonnet -> Opus). Map to claude-sonnet-4-6 to keep the
Sonnet tier intact. (Cursor bugbot review.)
3. example_config_yaml/simple_config.yaml: model_name was left as
gpt-3.5-turbo while the underlying was bumped to gpt-5-mini, which
muddles the "simple" example. Make both sides gpt-5-mini so the
most basic example is a straight 1:1 mapping again. (Cursor bugbot
review.)
* fix: revert gpt-4/gpt-3.5-turbo alias underlying to non-reasoning models
tests/test_openai_endpoints.py::test_completion calls the proxy alias
"gpt-4" with temperature=0, and other tests call gpt-3.5-turbo with
custom temperature / logprobs / the legacy /v1/completions endpoint.
The earlier modernization mapped both aliases to gpt-5.5 / gpt-5-mini,
which are reasoning models that reject temperature != 1 and don't
expose /v1/completions. Map the aliases to gpt-4.1 / gpt-4.1-mini
(modern non-reasoning OpenAI models) instead — keeps user-facing
aliases preserved while picking a current underlying that still
supports the parameters/endpoints the tests exercise.
|
||
|
user
|
c8325ff007 | chore(proxy): guard sensitive public endpoints | ||
|
Yuneng Jiang
|
a292845dcf |
[Fix] Harden spend accuracy test against transient aiohttp connection errors
Two changes, both test-only: - Configure the aiohttp session with TCPConnector(force_close=True) and an explicit ClientTimeout(total=30, connect=10). Prevents reuse of idle TCP connections that the proxy/kernel may have closed during the long window between setup POSTs and the later poll loop, and surfaces a blocked proxy event loop quickly instead of hanging on aiohttp's 5-minute default. - In poll_key_spend_until, catch aiohttp.ClientError and asyncio.TimeoutError around the single /key/info call. A transient transport hiccup now logs and retries on the next tick instead of failing the entire polling loop. Addresses the ConnectionTimeoutError observed on the first /key/info call after the 20 chat completions. |
||
|
Yuneng Jiang
|
5445297da9 |
[Fix] Stabilize flaky spend accuracy tests with local ground truth
Replace the calibration step (one request + 10-minute poll) with an independent ground truth computed from response usage via litellm.cost_per_token. All N requests are made up front, so a single dropped Redis write no longer kills the test. Add /health/readiness checks at test start and on poll timeout so the failure message surfaces proxy state (db, cache) instead of "calibration timed out". Set PROXY_BATCH_WRITE_AT=2 in the spend tracking CI job to shorten the scheduler flush window. |
||
|
Ishaan Jaffer
|
e8461b5b97 | style: run black formatter on files from main merge | ||
|
|
8e61b32b8e |
[Staging] - Ishaan March 17th (#23903)
* feat(xai): add grok-4.20 beta 2 models with pricing (#23900)
Add three grok-4.20 beta 2 model variants from xAI:
- grok-4.20-multi-agent-beta-0309 (reasoning + multi-agent)
- grok-4.20-beta-0309-reasoning (reasoning)
- grok-4.20-beta-0309-non-reasoning
Pricing (from https://docs.x.ai/docs/models):
- Input: $2.00/1M tokens ($0.20/1M cached)
- Output: $6.00/1M tokens
- Context: 2M tokens
All variants support vision, function calling, tool choice, and web search.
Closes LIT-2171
* docs: add Quick Install section for litellm --setup wizard (#23905)
* docs: add Quick Install section for litellm --setup wizard
* docs: clarify setup wizard is for local/beginner use
* feat(setup): interactive setup wizard + install.sh (#23644)
* feat(setup): add interactive setup wizard + install.sh
Adds `litellm --setup` — a Claude Code-style TUI onboarding wizard that
guides users through provider selection, API key entry, and proxy config
generation, then optionally starts the proxy immediately.
- litellm/setup_wizard.py: wizard with ASCII art, numbered provider menu
(OpenAI, Anthropic, Azure, Gemini, Bedrock, Ollama), API key prompts,
port/master-key config, and litellm_config.yaml generation
- litellm/proxy/proxy_cli.py: adds --setup flag that invokes the wizard
- scripts/install.sh: curl-installable script (detect OS/Python, pip
install litellm[proxy], launch wizard)
Usage:
curl -fsSL https://raw.githubusercontent.com/BerriAI/litellm/main/scripts/install.sh | sh
litellm --setup
* fix(install.sh): remove orange color, add LITELLM_BRANCH env var for branch installs
* fix(install.sh): install from git branch so --setup is available for QA
* fix(install.sh): remove stale LITELLM_BRANCH reference that caused unbound variable error
* fix(install.sh): force-reinstall from git to bypass cached PyPI version
* fix(install.sh): show pip progress bar during install
* fix(install.sh): always launch wizard via $PYTHON_BIN -m litellm, not PATH binary
* fix(install.sh): use litellm.proxy.proxy_cli module (no __main__.py exists)
* fix(install.sh): suppress RuntimeWarning from module invocation
* fix(install.sh): use Python bin-dir litellm binary to avoid CWD sys.path shadowing
* fix(install.sh): use sysconfig.get_path('scripts') to find pip-installed litellm binary
* fix(install.sh): redirect stdin from /dev/tty on exec so wizard gets terminal, not exhausted pipe
* fix(install.sh): warn about git clone duration, drop --no-cache-dir so re-runs are faster
* feat(setup_wizard): arrow-key selector, updated model names
* fix(setup_wizard): use sysconfig binary to start proxy, not python -m litellm
* feat(setup_wizard): credential validation after key entry + clear next-steps after proxy start
* style(install.sh): show git clone warning in blue
* refactor(setup_wizard): class with static methods, use check_valid_key from litellm.utils
* address greptile review: fix yaml escaping, port validation, display name collisions, tests
- setup_wizard.py: add _yaml_escape() for safe YAML embedding of API keys
- setup_wizard.py: add _styled_input() with readline ANSI ignore markers
- setup_wizard.py: change DIVIDER to _divider() fn to avoid import-time color capture
- setup_wizard.py: validate port range 1-65535, initialize before loop
- setup_wizard.py: qualify azure display names (azure-gpt-4o) to avoid collision with openai
- setup_wizard.py: work on env_copy in _build_config to avoid mutating caller's dict
- setup_wizard.py: skip model_list entries for providers with no credentials
- setup_wizard.py: prompt for azure deployment name
- setup_wizard.py: wrap os.execlp in try/except with friendly fallback
- setup_wizard.py: wrap config write in try/except OSError
- setup_wizard.py: fix _validate_and_report to use two print lines (no \r overwrite)
- setup_wizard.py: add .gitignore tip next to key storage notice
- setup_wizard.py: fix run_setup_wizard() return type annotation to None
- scripts/install.sh: drop pipefail (not supported by dash on Ubuntu when invoked as sh)
- scripts/install.sh: use litellm[proxy] from PyPI (not hardcoded dev branch)
- scripts/install.sh: guard /dev/tty read with -r check for Docker/CI compat
- scripts/install.sh: remove --force-reinstall to avoid downgrading dependencies
- tests/test_litellm/test_setup_wizard.py: 13 unit tests for _build_config and _yaml_escape
* style: black format setup_wizard.py
* fix: address remaining greptile issues - Windows compat, YAML quoting, credential flow
- guard termios/tty imports with try/except ImportError for Windows compat
- quote master_key as YAML double-quoted scalar (same as env vars)
- remove unused port param from _build_config signature
- _validate_and_report now returns the final key so re-entered creds are stored
- add test for master_key YAML quoting
* fix: add --port to suggested command, guard /dev/tty exec in install.sh
* fix: quote api_base in YAML, skip azure if no deployment, only redraw on state change
* fix: address greptile review comments
- _yaml_escape: add control character escaping (\n, \r, \t)
- test: fix tautological assertion in test_build_config_azure_no_deployment_skipped
- test: add tests for control character escaping in _yaml_escape
* feat(ui): remove Chat UI page link and banner from sidebar and playground (#23908)
* feat(guardrails): MCPJWTSigner - built-in guardrail for zero trust MCP auth (#23897)
* Allow pre_mcp_call guardrail hooks to mutate outbound MCP headers
* Enhance MCPServerManager to support hook-modified arguments and extra headers. Update tests to validate argument mutation and header injection behavior, including warnings for OpenAPI-backed servers when headers are present.
* Refactor MCPServerManager to raise HTTPException for extra headers in OpenAPI-backed servers. Update tests to reflect this change, ensuring proper exception handling instead of logging warnings.
* Allow pre_mcp_call guardrail hooks to mutate outbound MCP headers
* Enhance MCPServerManager to support hook-modified arguments and extra headers. Update tests to validate argument mutation and header injection behavior, including warnings for OpenAPI-backed servers when headers are present.
* Refactor MCPServerManager to raise HTTPException for extra headers in OpenAPI-backed servers. Update tests to reflect this change, ensuring proper exception handling instead of logging warnings.
* feat(guardrails): add MCPJWTSigner built-in guardrail for zero trust MCP auth
Signs outbound MCP tool calls with a LiteLLM-issued RS256 JWT so MCP servers
can trust a single signing authority instead of every upstream IdP.
Enable in config.yaml:
guardrails:
- guardrail_name: mcp-jwt-signer
litellm_params:
guardrail: mcp_jwt_signer
mode: pre_mcp_call
default_on: true
JWT carries sub (user_id), act.sub (team_id, RFC 8693), tool-level scope, iss,
aud, iat/exp/nbf. RSA-2048 keypair auto-generated at startup unless
MCP_JWT_SIGNING_KEY env var is set.
Adds /.well-known/jwks.json endpoint and jwks_uri to /.well-known/openid-configuration
so MCP servers can verify LiteLLM-issued tokens via OIDC discovery.
* Update MCPServerManager to raise HTTPException with status code 400 for extra headers in OpenAPI-backed servers. Adjust tests to verify the correct status code and exception message.
* fix: address P1 issues in MCPJWTSigner
- OpenAPI servers: warn + skip header injection instead of 500
- JWKS Cache-Control: 5min for auto-generated keys, 1h for persistent
- sub claim: fallback to apikey:{token_hash} for anonymous callers
- ttl_seconds: validate > 0 at init time
* docs: add MCP zero trust auth guide with architecture diagram
* docs: add FastMCP JWT verification guide to zero trust doc
* fix: address remaining Greptile review issues (round 2)
- mcp_server_manager: warn when hook Authorization overwrites existing header
- __init__: remove _mcp_jwt_signer_instance from __all__ (private internal)
- discoverable_endpoints: copy dict instead of mutating in-place on OIDC augmentation
- test docstring: reflect warn-and-continue behavior for OpenAPI servers
- test: update scope assertions for least-privilege (no mcp:tools/list on tool-call JWTs)
* fix: address Greptile round 3 feedback
- initialize_guardrail: validate mode='pre_mcp_call' at init time — misconfigured
mode silently bypasses JWT injection, which is a zero-trust bypass
- _build_claims: remove duplicate inline 'import re' (module-level import already present)
- _types.py: add TODO comment explaining jwt_claims is forward-compat plumbing
for a follow-up PR that will forward upstream IdP claims into outbound MCP JWTs
* feat(mcp_jwt_signer): add verify+re-sign, claim ops, two-token model, configurable scopes
Addresses all missing pieces from the scoping doc review:
FR-5 (Verify + re-sign): MCPJWTSigner now accepts access_token_discovery_uri
and token_introspection_endpoint. When set, the incoming Bearer token is
extracted from raw_headers (threaded through pre_call_tool_check), verified
against the IdP's JWKS (JWT) or introspected (opaque), and only re-signed if
valid. Falls back to user_api_key_dict.jwt_claims for LiteLLM JWT-auth mode.
FR-12 (Configurable end-user identity mapping): end_user_claim_sources
ordered list drives sub resolution — sources: token:<claim>, litellm:user_id,
litellm:email, litellm:end_user_id, litellm:team_id.
FR-13 (Claim operations): add_claims (insert-if-absent), set_claims (always
override), remove_claims (delete) applied in that order.
FR-14 (Two-token model): channel_token_audience + channel_token_ttl issue a
second JWT injected as x-mcp-channel-token: Bearer <token>.
FR-15 (Incoming claim validation): required_claims raises HTTP 403 when any
listed claim is absent; optional_claims passes listed claims from verified
token into the outbound JWT.
FR-9 (Debug headers): debug_headers: true emits x-litellm-mcp-debug with kid,
sub, iss, exp, scope.
FR-10 (Configurable scopes): allowed_scopes replaces auto-generation. Also
fixed: tool-call JWTs no longer grant mcp:tools/list (overpermission).
P1 fixes:
- proxy/utils.py: _convert_mcp_hook_response_to_kwargs merges rather than
replaces extra_headers, preserving headers from prior guardrails.
- mcp_server_manager.py: warns when hook injects Authorization alongside a
server-configured authentication_token (previously silent).
- mcp_server_manager.py: pre_call_tool_check now accepts raw_headers and
extracts incoming_bearer_token so FR-5 verification has the raw token.
- proxy/utils.py: remove stray inline import inspect inside loop (pre-existing
lint error, now cleaned up).
Tests: 43 passing (28 new tests covering all FR flags + P1 fixes).
* feat(mcp_jwt_signer): add verify+re-sign, claim ops, two-token model, configurable scopes (core)
Remaining files from the FR implementation:
mcp_jwt_signer.py — full rewrite with all new params:
FR-5: access_token_discovery_uri, token_introspection_endpoint,
verify_issuer, verify_audience + _verify_incoming_jwt(),
_introspect_opaque_token()
FR-12: end_user_claim_sources ordered resolution chain
FR-13: add_claims, set_claims, remove_claims
FR-14: channel_token_audience, channel_token_ttl → x-mcp-channel-token
FR-15: required_claims (raises 403), optional_claims (passthrough)
FR-9: debug_headers → x-litellm-mcp-debug
FR-10: allowed_scopes; tool-call JWTs no longer over-grant tools/list
mcp_server_manager.py:
- pre_call_tool_check gains raw_headers param to extract incoming_bearer_token
- Silent Authorization override warning fixed: now fires when server has
authentication_token AND hook injects Authorization
tests/test_mcp_jwt_signer.py:
28 new tests covering all FR flags + P1 fixes (43 total, all passing)
* fix(mcp_jwt_signer): address pre-landing review issues
- Remove stale TODO comment on UserAPIKeyAuth.jwt_claims — the field is
already populated and consumed by MCPJWTSigner in the same PR
- Fix _get_oidc_discovery to only cache the OIDC discovery doc when
jwks_uri is present; a malformed/empty doc now retries on the next
request instead of being permanently cached until proxy restart
- Add FR-5 test coverage for _fetch_jwks (cache hit/miss),
_get_oidc_discovery (cache/no-cache on bad doc), _verify_incoming_jwt
(valid token, expired token), _introspect_opaque_token (active,
inactive, no endpoint), and the end-to-end 401 hook path — 53 tests
total, all passing
* docs(mcp_zero_trust): rewrite as use-case guide covering all new JWT signer features
Add scenario-driven sections for each new config area:
- Verify+re-sign with Okta/Azure AD (access_token_discovery_uri,
end_user_claim_sources, token_introspection_endpoint)
- Enforcing caller attributes with required_claims / optional_claims
- Adding metadata via add_claims / set_claims / remove_claims
- Two-token model for AWS Bedrock AgentCore Gateway
(channel_token_audience / channel_token_ttl)
- Controlling scopes with allowed_scopes
- Debugging JWT rejections with debug_headers
Update JWT claims table to reflect configurable sub (end_user_claim_sources)
* fix(mcp_jwt_signer): wire all config.yaml params through initialize_guardrail
The factory was only passing issuer/audience/ttl_seconds to MCPJWTSigner.
All FR-5/9/10/12/13/14/15 params (access_token_discovery_uri,
end_user_claim_sources, add/set/remove_claims, channel_token_audience,
required/optional_claims, debug_headers, allowed_scopes, etc.) were
silently dropped, making every advertised advanced feature non-functional
when loaded from config.yaml.
Add regression test that asserts every param is wired through correctly.
* docs(mcp_zero_trust): add hero image
* docs(mcp_zero_trust): apply Linear-style edits
- Lead with the problem (unsigned direct calls bypass access controls)
- Shorter statement section headers instead of question-form headers
- Move diagram/OIDC discovery block after the reader is bought in
- Add 'read further only if you need to' callout after basic setup
- Two-token section now opens from the user problem not product jargon
- Add concrete 403 error response example in required_claims section
- Debug section opens from the symptom (MCP server returning 401)
- Lowercase claims reference header for consistency
* fix(mcp_jwt_signer): fix algorithm confusion attack + add OIDC discovery 24h TTL
- Remove alg from unverified JWT header; use signing_jwk.algorithm_name from JWKS key instead.
Reading alg from attacker-controlled headers enables alg:none / HS256 confusion attacks.
- Add _oidc_discovery_fetched_at timestamp and _OIDC_DISCOVERY_TTL = 86400 (24h).
Without a TTL the cached discovery doc never refreshes, so IdP key rotation is invisible.
---------
Co-authored-by: Noah Nistler <60981020+noahnistler@users.noreply.github.com>
* fix(ci): stabilize CI - formatting, type errors, test polling, security CVEs, router bug, batch resolution
Fix 1: Run Black formatter on 35 files
Fix 2: Fix MyPy type errors:
- setup_wizard.py: add type annotation for 'selected' set variable
- user_api_key_auth.py: remove redundant type annotation on jwt_claims reassignment
Fix 3: Fix spend accuracy test burst 2 polling to wait for expected total
spend instead of just 'any increase' from burst 2
Fix 4: Bump Next.js 16.1.6 -> 16.1.7 to fix CVE-2026-27978, CVE-2026-27979,
CVE-2026-27980, CVE-2026-29057
Fix 5: Fix router _pre_call_checks model variable being overwritten inside
loop, causing wrong model lookups on subsequent deployments. Use local
_deployment_model variable instead.
Fix 6: Add missing resolve_output_file_ids_to_unified call in batch retrieve
non-terminal-to-terminal path (matching the terminal path behavior)
Co-authored-by: Ishaan Jaff <ishaan-jaff@users.noreply.github.com>
* chore: regenerate poetry.lock to sync with pyproject.toml
Co-authored-by: Ishaan Jaff <ishaan-jaff@users.noreply.github.com>
* fix: format merged files from main and regenerate poetry.lock
Co-authored-by: Ishaan Jaff <ishaan-jaff@users.noreply.github.com>
* fix(mypy): annotate jwt_claims as Optional[dict] to fix type incompatibility
Co-authored-by: Ishaan Jaff <ishaan-jaff@users.noreply.github.com>
* fix(ci): update router region test to use gpt-4.1-mini (fix flaky model lookup)
Replace deprecated gpt-3.5-turbo-1106 with gpt-4.1-mini + mock_response in
test_router_region_pre_call_check, following the same pattern used in commit
|
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yuneng-jiangandClaude Opus 4.6
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f351bbdb36 |
[Fix] Derive SPEND_PER_REQUEST dynamically in spend accuracy tests
Instead of hardcoding SPEND_PER_REQUEST (which broke when the model changed from gpt-3.5-turbo-0301 to gpt-3.5-turbo), make a single calibration request first, poll for its spend, and use that as the per-request cost. Fails fast with pytest.fail() after 5 retries if calibration cannot determine the cost. Also fixes a bug in test_basic_spend_accuracy where the user spend assertion error message referenced user_info['info'] instead of user_info['user_info']. Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com> |
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yuneng-jiangandClaude Opus 4.6
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3012c6d070 |
fix(tests): replace fixed sleeps with polling in spend accuracy tests
The spend accuracy tests were flaky because they used fixed sleeps (45s/30s) to wait for the batch writer to flush. Under CI load, the batch writer scheduler can be delayed beyond these windows, causing all spend values to remain 0.0 and the test to fail. Replace fixed sleeps with a polling loop that checks key spend every 10s for up to 120s, only proceeding once spend becomes non-zero. Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com> |
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Cursor Agentandyuneng-jiang
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cc3f9cd65b |
fix(ci): stabilize CI tests - conditional import, mock fixes, timing adjustments
Fix 1.1: Make ResponseApplyPatchToolCall import conditional with try/except for compatibility with openai==1.100.1 (CI environment) Fix 1.2: Move Router creation inside mock context in vector store tests so mocks are applied before Router captures function references Fix 1.3: Update test_model_group_info_e2e to check for 'anthropic/*' wildcard group instead of specific model names not in proxy config Fix 2.1: Increase redis cache test sleep from 1s to 5s Fix 2.2: Increase spend accuracy test sleep from 25s to 45s Fix 2.3: Add 0.5s sleep between budget test calls Fix 2.4: Increase vertex AI spend test sleep from 20s to 40s Co-authored-by: yuneng-jiang <yuneng-jiang@users.noreply.github.com> |
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yuneng-jiang
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65829411e0 | increasing time for spend tracking | ||
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Ishaan Jaffer
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014362cace | fix ocr test | ||
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OrionCodeDevandGitHub
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5f52533294 |
Fix spend tracking for OCR/aOCR requests (log pages_processed + recognize OCRResponse) (#16070)
* fix-ocr-cost * fix1 |
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Alexsander HamirandGitHub
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eaa04cd8ce |
fix: use fastuuid helper (#14903)
* fix: use fastuuid helper across the codebase First batch of changes, simple drop in replacement. * second batch of changes * fixed: script mistake on helper file |
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Ishaan Jaff
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9951b356da | test_long_term_spend_accuracy_with_bursts | ||
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Ishaan Jaff
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271b8b95bc | test spend accuracy |