* test: add 24hr Redis-backed VCR cache to additional test suites
Extracts the existing llm_translation VCR plumbing into a reusable helper
(tests/_vcr_conftest_common.py) and wires it into the conftest.py files
of the test directories listed in LIT-2787:
audio_tests, batches_tests, guardrails_tests, image_gen_tests,
litellm_utils_tests, local_testing, logging_callback_tests,
pass_through_unit_tests, router_unit_tests, unified_google_tests
The same helper is also adopted by the pre-existing llm_translation and
llm_responses_api_testing conftests to remove the copy-pasted VCR setup.
Each consuming conftest:
- registers the Redis persister via pytest_recording_configure
- auto-marks collected tests with pytest.mark.vcr (skipping respx-using
files where applicable, since respx and vcrpy both patch httpx)
- gates cassette writes on test success via _vcr_outcome_gate
The cache is opt-in via CASSETTE_REDIS_URL; when unset, VCR is disabled
and tests hit live providers as before. LITELLM_VCR_DISABLE=1 still
forces a bypass for ad-hoc local runs.
Test directories that run LiteLLM proxy in Docker (build_and_test,
proxy_logging_guardrails_model_info_tests, proxy_store_model_in_db_tests)
are intentionally not included: VCR.py patches the in-process httpx
transport and cannot intercept calls made from inside a Docker container.
The installing_litellm_on_python* jobs make no LLM calls and don't
benefit from caching.
https://linear.app/litellm-ai/issue/LIT-2787/add-24hr-caching-to-additional-test-suites
* test(vcr): add safe-body matcher to handle JSONL and binary request bodies
vcrpy's stock body matcher inspects Content-Type and unconditionally
runs json.loads on application/json bodies. JSON Lines payloads (used
by the Bedrock batch S3 PUT and other upload paths) crash that with
json.JSONDecodeError: Extra data, before the matcher can return
'not a match'.
This was the root cause of the batches_testing CI job failing on
test_async_create_file once VCR auto-marking was applied to the
batches_tests directory.
Add a conservative byte-equality body matcher and use it in place of
'body' in the shared match_on tuple. The matcher is strictly more
conservative than vcrpy's default — the only thing it gives up is
'different JSON key order is treated as the same body', which doesn't
apply to deterministic litellm-built request payloads. It can never
produce a false positive that the default would have rejected, so
there is no cross-contamination risk.
Co-authored-by: Mateo Wang <mateo-berri@users.noreply.github.com>
* test(vcr): exclude tests that VCR replay actively breaks
A few tests are incompatible with cassette replay and were failing on
the latest CI run after VCR auto-marking was extended to local_testing
and logging_callback_tests:
- test_amazing_s3_logs.py (logging_callback_tests): the test asserts on
a per-run response_id that should round-trip through a real S3
PUT/LIST. vcrpy's boto3 stub intercepts the PUT and the LIST replays
stale keys, so the freshly-generated id is never found.
- test_async_embedding_azure (logging_callback_tests) and
test_amazing_sync_embedding (local_testing): the failure branches
deliberately pass api_key='my-bad-key' to assert that the failure
callback fires. We scrub auth headers from cassettes (so the bad-key
request matches the prior good-key request), and vcrpy replays the
recorded 200 — the failure callback never fires.
- test_assistants.py (local_testing): the OpenAI Assistants polling
APIs mint fresh thread/run IDs every recording session and then poll
until status=='completed'. Replays of those polled GETs can never
match a freshly-generated run id, so every CI run effectively
re-records and the suite blows past the 15m no_output_timeout.
Skip these from VCR auto-marking so they continue to hit live providers
as they did before this change. The remaining tests in each directory
still get cached.
Co-authored-by: Mateo Wang <mateo-berri@users.noreply.github.com>
* test(vcr): expand skip lists for second batch of incompatible tests
Followup to the previous commit. After re-running CI on the rebuilt
branch, three more tests surfaced as VCR-replay-incompatible:
- litellm_utils_testing :: test_get_valid_models_from_dynamic_api_key
Calls GET /v1/models with api_key='123' to assert the result is empty.
We scrub auth headers, so the bad-key request matches the prior
good-key cassette and replays the recorded model list.
- litellm_utils_testing :: test_litellm_overhead.py
Measures litellm_overhead_time_ms as a percentage of total wall-clock
time. With cached responses the upstream 'network' time collapses to
microseconds, blowing past the 40%% threshold the test asserts on.
Skip the whole file (every parametrization is at risk).
- local_testing_part1 :: test_async_custom_handler_completion and
test_async_custom_handler_embedding
Same bad-key failure-callback pattern as the already-skipped
test_amazing_sync_embedding.
- litellm_router_testing :: test_router_caching.py
Asserts on litellm's own router-level response cache by comparing
response1.id to response2.id across repeat upstream calls (test
bypasses litellm cache via ttl=0 and expects upstream to return a
*new* id). With VCR replay both upstream calls return the same
cassette body, so the ids are identical. Skip the whole file.
- logging_callback_tests :: test_async_chat_azure (preemptive)
Same shape as already-skipped test_async_embedding_azure; was masked
by upstream OpenAI rate-limit failures on baseline.
Co-authored-by: Mateo Wang <mateo-berri@users.noreply.github.com>
* test(vcr): use item.path and tighten matcher docstring
- Replace pytest's deprecated item.fspath with item.path in
apply_vcr_auto_marker_to_items so we don't emit deprecation
warnings under pytest 8.
- Clarify _safe_body_matcher docstring to reflect actual behavior
(direct == first, then UTF-8 bytes comparison, no repr fallback).
Addresses Greptile review feedback on PR #27159.
* test(vcr): swallow all RedisError on cassette save/load
Cassette persistence is strictly best-effort: any Redis-side failure
(connection blip, timeout, OutOfMemoryError when the maxmemory cap is
hit, READONLY replicas, etc.) should degrade to 'test passed but
cassette not cached' rather than fail the test on teardown.
Previously the persister only caught ConnectionError and TimeoutError,
so OutOfMemoryError — which Redis Cloud raises when the cassette cache
hits its memory cap and there are no evictable keys — propagated out of
vcrpy's autouse fixture and ERRORed otherwise-passing tests on
teardown. This caused the litellm_utils_testing CircleCI job to fail on
the latest commit's run, even though the underlying test was a unit
test that used mock_response and produced no real upstream traffic
(the cassette was dirtied by a background langfuse callback). The
rerun only succeeded because Redis evictions happened to free enough
room before the SET — i.e. it was timing-dependent flakiness.
Catch redis.exceptions.RedisError (the common base of all server- and
client-side Redis exceptions) on both save and load, and parametrize
the regression tests across ConnectionError, TimeoutError, and
OutOfMemoryError to pin the new behavior.
* test(vcr): surface cassette-cache failures with warnings + session banner
When the persister silently swallows a Redis OOM (or any RedisError) on
save/load there is otherwise no visible signal that the cache is
degraded — tests pass, the cassette just isn't persisted, and the next
session still hits the same Redis at the same near-cap memory.
Add three layers of observability so that failure mode is loud:
1. Per-process health counters ("save_failures", "load_failures", and
the last error string for each), exposed via cassette_cache_health()
and reset via reset_cassette_cache_health(). The persister
increments these in addition to logging.
2. VCRCassetteCacheWarning (UserWarning subclass) emitted via
warnings.warn() inside the persister's except block. Pytest's
built-in warnings summary at session end automatically lists every
such warning, so the failure is visible in CI logs without any
conftest-level wiring.
3. Session-end banner via emit_cassette_cache_session_banner() and a
stderr-fallback atexit handler registered from
register_persister_if_enabled(). Two states:
- red "VCR CASSETTE CACHE DEGRADED" when save_failures or
load_failures > 0
- yellow "VCR CASSETTE CACHE NEAR CAPACITY" (no failures, but
used_memory >= 85% of maxmemory) so the next session knows
the Redis is approaching OOM before any SET actually fails
Capacity comes from a best-effort INFO memory probe
(cassette_cache_capacity_snapshot) that returns None on any failure or
when maxmemory is uncapped. The atexit handler skips xdist workers so
only the controller emits.
Tests: parametrize the existing save/load swallow-error tests across
ConnectionError/TimeoutError/OutOfMemoryError, add direct tests for
the health counters and warning emission, and a new
test_vcr_conftest_common_banner.py covering banner output for every
state (silent/red/yellow/disabled/xdist-worker).
* test(vcr): bucket cassettes by API key fingerprint, drop bad-key skips
Tests that deliberately call an LLM API with a bad key (e.g. to assert
that the failure callback fires, or that check_valid_key returns False)
were being silently served the prior good-key cassette: we scrub the
real Authorization / x-api-key header from the cassette before storing
it, so a follow-up bad-key call is byte-identical to the good-key call
under the existing match_on tuple.
Add a 'key_fingerprint' custom matcher that distinguishes requests by
the SHA-256 of their API-key headers. The fingerprint is stamped into
a synthetic 'x-litellm-key-fp' header by a new before_record_request
hook, which then strips the real auth headers (we have to do the
scrubbing here instead of via vcrpy's filter_headers knob, because
filter_headers runs *first* and would erase the value we want to hash).
Bad-key requests now get a different cassette bucket than good-key
requests, so vcrpy will not replay a recorded 200 in place of the
expected 401. The fingerprint is a one-way hash of the secret, so
cassettes never contain the key.
This permanently removes the 'bad-key' category of skips:
- tests/local_testing: dropped ::test_amazing_sync_embedding,
::test_async_custom_handler_completion,
::test_async_custom_handler_embedding
- tests/logging_callback_tests: dropped ::test_async_chat_azure,
::test_async_embedding_azure
- tests/litellm_utils_tests: dropped
::test_get_valid_models_from_dynamic_api_key
Coverage: 7 new unit tests in tests/test_litellm/test_vcr_safe_body_matcher.py
covering header stripping, fingerprint determinism, no-auth bucketing,
good-vs-bad key discrimination, x-api-key (Anthropic/Azure) discrimination,
and idempotence under replay.
Co-authored-by: Mateo Wang <mateo-berri@users.noreply.github.com>
* test(vcr): drop redundant comments and docstrings
Trim narration of code that is already self-evident from function and
variable names. Keep the two genuinely non-obvious bits:
- ordering constraint between filter_headers and before_record_request,
which would invite a maintainer to re-introduce the bug if removed
- the per-directory _VCR_INCOMPATIBLE_FILES rationale, since 'why
exactly is this skipped' is not knowable from the test name alone
Also drop the 40-line commented-out drop-in conftest snippet at the
bottom of _vcr_conftest_common.py — the consuming conftests are the
canonical reference.
Co-authored-by: Mateo Wang <mateo-berri@users.noreply.github.com>
* test(vcr): make _before_record_request idempotent
vcrpy invokes before_record_request more than once per request:
can_play_response_for calls it, then __contains__ /
_responses (reached via play_response) call it again on the
result. The second invocation sees a request whose auth headers we
already stripped, so a naive recompute yields "no-key" and
overwrites the real fingerprint stored in the header.
This makes can_play_response_for and play_response disagree on
matchability — the former says "yes, we have a stored response for
this" (matching no-key to no-key) and the latter throws
UnhandledHTTPRequestError because it computes a fresh real
fingerprint that doesn't match the stored no-key.
In CI this manifested as ~30 failing tests across guardrails_testing,
audio_testing, batches_testing, image_gen_testing, llm_responses_api,
litellm_router_unit_testing, etc. Skip the recompute when the header
is already set, so re-applying the hook is a no-op.
Adds a regression test that fires the hook twice on the same dict and
asserts the fingerprint stays put.
Co-authored-by: Mateo Wang <mateo-berri@users.noreply.github.com>
* test(vcr): drop more redundant docstrings and headers
* test(vcr): enable 24hr cache for ocr_tests and search_tests
These two directories were the only non-dockerized test suites in the
build_and_test workflow that make live LLM/provider API calls but were
not VCR-enabled by this PR. Together they account for 96 tests:
- tests/ocr_tests/ (31): Mistral OCR, Azure AI OCR, Azure Document
Intelligence, Vertex AI OCR. Pure-unit tests inside the same files
(e.g. TestAzureDocumentIntelligencePagesParam) make no HTTP calls
and become benign VCR NOOPs.
- tests/search_tests/ (65): Brave, DataForSEO, DuckDuckGo, Exa,
Firecrawl, Google PSE, Linkup, Parallel.ai, Perplexity, SearchAPI,
Searxng, Serper, Tavily.
Both directories use the canonical minimal conftest pattern from
tests/audio_tests/conftest.py with no skip lists. None of the test
files use respx, none assert on per-call upstream non-determinism
(no response1.id != response2.id, no overhead-as-fraction-of-total,
no live polling), so the default match_on tuple should cache cleanly.
If a flake surfaces during the first cassette-recording CI run, we
can add a targeted skip the same way we did for the other dirs.
Co-authored-by: Mateo Wang <mateo-berri@users.noreply.github.com>
---------
Co-authored-by: Claude <noreply@anthropic.com>
Co-authored-by: Cursor Agent <cursoragent@cursor.com>
Co-authored-by: Mateo Wang <mateo-berri@users.noreply.github.com>
* akto guardrails support in litellm
* docs(guardrails): add akto to supported values in types/guardrails.py
* frontend changes + fixes
* feat(akto): update Akto guardrail integration with new configuration options and modes
* docs(akto): enhance Akto documentation and configuration descriptions for clarity
* feat(tests): add proxy server request headers to sample request data
* refactor(akto): remove optional account and VXLAN IDs; update documentation and tests
* feat(akto): add event_type parameter for enhanced observability in guardrail logging
* refactor(akto): update environment variable references
* refactor the python codes
* refactor and fix linting
* refactor(akto): remove unused event hook and clean up imports
* refactor(akto): enhance AktoGuardrail with async support and improved logging
* fix: Register DynamoAI guardrail initializer and enum entry (#23752)
* fix: Register DynamoAI guardrail initializer and enum entry
Fix the "Unsupported guardrail: dynamoai" error by:
1. Adding DYNAMOAI to SupportedGuardrailIntegrations enum
2. Implementing initialize_guardrail() and registries in dynamoai/__init__.py
The DynamoAI guardrail was added in PR #15920 but never properly registered
in the initialization system. The __init__.py was missing the
guardrail_initializer_registry and guardrail_class_registry dictionaries
that the dynamic discovery mechanism looks for at module load time.
Fixes#22773
Co-Authored-By: Claude Haiku 4.5 <noreply@anthropic.com>
* Update litellm/proxy/guardrails/guardrail_hooks/dynamoai/__init__.py
Co-authored-by: greptile-apps[bot] <165735046+greptile-apps[bot]@users.noreply.github.com>
* Update litellm/proxy/guardrails/guardrail_hooks/dynamoai/__init__.py
Co-authored-by: greptile-apps[bot] <165735046+greptile-apps[bot]@users.noreply.github.com>
* test: Add tests for DynamoAI guardrail registration
Verifies enum entry, initializer registry, class registry,
instance creation, and global registry discovery.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
---------
Co-authored-by: Claude Haiku 4.5 <noreply@anthropic.com>
Co-authored-by: greptile-apps[bot] <165735046+greptile-apps[bot]@users.noreply.github.com>
* docs: add v1.82.3 release notes and update provider_endpoints_support.json (#23816)
* Revert "docs: add v1.82.3 release notes and update provider_endpoints_support…" (#23817)
This reverts commit 966124966f.
* Refactor Akto guardrail configuration and tests; update UI description and tags
* add account and vxlan ID parameters to Akto guardrail initialization; update Akto logo format
* enhance Akto guardrail documentation and improve error handling for non-JSON responses
* address greptile issues
* fix: update payload handling to use 'data' instead of 'json' in AktoGuardrail and adjust tests accordingly
---------
Co-authored-by: Harshit Jain <48647625+Harshit28j@users.noreply.github.com>
Co-authored-by: Claude Haiku 4.5 <noreply@anthropic.com>
Co-authored-by: greptile-apps[bot] <165735046+greptile-apps[bot]@users.noreply.github.com>
Co-authored-by: Joe Reyna <joseph.reyna@gmail.com>
Co-authored-by: Krish Dholakia <krrishdholakia@gmail.com>
- Router testing: add CircleCI parallelism=4 with timing-based test splitting
- Guardrails testing: add pytest-xdist -n 4, suppress DEBUG logs with LITELLM_LOG=WARNING
- Rewrite conftest.py in both test dirs for xdist compatibility (save/restore pattern)
- Fix module-level Router instances in test_router_fallback_handlers, test_router_custom_routing, test_acooldowns_router
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
* fix(ci): handle inline table in pyproject.toml for litellm-proxy-extras version check
* fix: bump litellm-proxy-extras to 0.4.50 in pyproject.toml, requirements.txt, and poetry.lock
* fix(tests): set status_code=200 on JWT mocks and pass pii_tokens through data in presidio test
* Add post-call hook for Lakera guardrail and mask PII in responses
* Add post-call hook for Lakera and mask PII in responses
* Fix post-call hook: pass event_type to call_v2_guard
* Address Greptile review: return ModelResponse, fix mutation, add header, test location, mask order
- PII masking path: return ModelResponse instead of dict so deployment hook accepts it
- Avoid mutating request data: deep copy original_messages and messages in _mask_pii_in_messages
- Add guardrail header in PII-only return path
- Add test in tests/test_litellm/ (test_lakera_ai_v2.py) per PR checklist
- Sort PII payload spans by (start,end) descending so multiple spans in one message mask correctly
Co-authored-by: Cursor <cursoragent@cursor.com>
* Updated ponteital for index mismatch when choices have null content and inconsistent on_flagged access pattern
* Update litellm/proxy/guardrails/guardrail_hooks/lakera_ai_v2.py
Co-authored-by: greptile-apps[bot] <165735046+greptile-apps[bot]@users.noreply.github.com>
* Update to explicitly state supported endpoints - chat completions
* Fix minor lint error on masked_entity_count
---------
Co-authored-by: Steve <steve.giguere@lakera.ai>
Co-authored-by: Cursor <cursoragent@cursor.com>
Co-authored-by: greptile-apps[bot] <165735046+greptile-apps[bot]@users.noreply.github.com>
* Add French language support for EU AI Act Article 5 template
- Create eu_ai_act_article5_fr.yaml with comprehensive French keywords
- Includes identifier words: concevoir, créer, développer, noter, classer, etc.
- Includes block words: crédit social, comportement social, émotion des employés, etc.
- Includes always-block keywords for explicit prohibited practices
- Includes exceptions for research, compliance, and legitimate use cases
- Catches circumvention attempts with phrase variations
* Add comprehensive tests for French EU AI Act guardrail
- Test 3 critical scenarios: blocked query, circumvention attempt, safe query
- Test edge cases: case-insensitive, mixed language, research exceptions
- All 7 tests passing
- Validates both blocking and allowing behavior
* Fix content filter to support conditional matching without inherit_from
- Enable conditional matching when identifier_words + additional_block_words are present
- Previously required inherit_from, but EU AI Act templates are self-contained
- Fixes Greptile feedback: conditional matching now works as documented
* Add pure conditional matching test for French guardrail
- Test identifier + block word combinations not in always_block_keywords
- Verifies conditional matching works independently
- Addresses Greptile feedback about test coverage gap
* Fix exception word bypass risk in French template
- Replace short words (film, jeu, juste) with context-specific phrases
- Prevents substring matching bypasses (e.g., enjeu matching jeu)
- Add tests for bypass prevention and legitimate game context
- Addresses Greptile security feedback
* Make conditional match assertion more robust
- Use getattr to safely access exception detail field
- Check if detail is dict before calling .get()
- Addresses Greptile feedback about brittle string assertion
* Add 6 new EU PII patterns for GDPR compliance
- fr_nir: French Social Security Number (NIR/INSEE) with validation
- eu_iban_enhanced: Enhanced IBAN detection with specific format
- fr_phone: French phone numbers (+33, 0033, 0 formats)
- eu_vat: EU VAT identification numbers (all 27 member states)
- eu_passport_generic: Generic EU passport format
- fr_postal_code: French postal codes with contextual keywords
* Add GDPR Art. 32 EU PII Protection policy template
- Comprehensive GDPR Article 32 compliance policy
- 4 guardrail groups: National IDs, Financial, Contact Info, Business IDs
- Masks French NIR/INSEE, EU IBANs, French phones, EU VAT numbers
- Includes EU passport numbers and email addresses
- Medium complexity template with indigo icon
* Add comprehensive tests for EU PII patterns
- Test French NIR validation (sex digit, month range)
- Test enhanced IBAN detection (French, German)
- Test French phone number formats
- Test EU VAT numbers
- Test generic EU passport format
- Test French postal code pattern
* Add EU pattern loading and category validation tests
- Verify all 6 EU PII patterns are loaded correctly
- Verify patterns are categorized as 'EU PII Patterns'
- Ensure pattern loading consistency
* Add end-to-end tests for GDPR policy template
- 4 tests for PII that should be masked (NIR, IBAN, phone, VAT)
- 4 tests for text that should pass through (invalid patterns, no PII)
- 1 bonus test for multiple PII types in same message
- All tests verify correct masking behavior
* Add region field to policy templates
- Added region field to all 6 templates (EU, AU, Global)
- Updated both main and backup JSON files
- Enables region-based filtering in UI
* Add region filter to policy templates UI
- Added Radio.Group filter for regions (All, AU, EU, Global)
- Efficient filtering with useMemo hooks
- Clean button-based UI matching existing design
- Defaults missing regions to Global
* feat: add EU AI Act Article 5 policy template
Add policy template for detecting EU AI Act Article 5 prohibited practices using conditional keyword matching.
Coverage:
- Article 5.1.c: Social scoring systems
- Article 5.1.f: Emotion recognition in workplace/education
- Article 5.1.h: Biometric categorization of protected characteristics
- Article 5.1.a: Harmful manipulation techniques
- Article 5.1.b: Vulnerability exploitation
Implementation:
- Uses proven conditional matching pattern (identifier + block words)
- 10 always-block keywords for explicit violations
- 8 exceptions for research/compliance/entertainment
- Zero cost (<5ms), no external APIs, 100% private
* feat: add EU AI Act guardrail config example
Example configuration showing how to enable EU AI Act Article 5 guardrail.
* test: add 40 test cases for EU AI Act Article 5
Comprehensive test coverage:
- 10 always-block keywords (explicit violations)
- 15 conditional matches (identifier + block word)
- 8 exceptions (research, compliance, entertainment)
- 7 no-match cases (legitimate uses)
Tests validate correct blocking/allowing behavior for Article 5 prohibited practices.
* Fix: support standalone conditional matching without inherit_from
- Updated loading logic to activate conditional matching when either:
1. identifier_words + inherit_from (existing pattern)
2. identifier_words + additional_block_words (new standalone pattern)
- Modified _load_conditional_category to handle standalone templates
- EU AI Act template now works properly without inherit_from
- All 45 tests passing
Fixes Greptile feedback: conditional matching now activates for templates
that define additional_block_words without requiring inherit_from
* fix: address Greptile code review feedback (2/5 score)
- patterns.json: add keyword_pattern to eu_vat and eu_passport_generic
- patterns.json: fix fr_phone pattern with leading word boundary
- patterns.json: fix eu_iban_enhanced regex efficiency
- policy_templates.json: remove country-specific passport patterns from GDPR template
- policy_templates_backup.json: sync with main templates file
- test_gdpr_policy_e2e.py: update test setup and fix VAT test text
All tests now pass. Keyword guards prevent false positives.
* Fix: address Greptile pattern feedback
- Fix fr_phone: use negative lookbehind (?<!\d) to prevent false matches in digit strings
- Add keyword_pattern to eu_passport_generic to reduce false positives
- Add keyword_pattern to eu_vat for contextual matching
All pattern tests passing
* Update litellm/proxy/guardrails/guardrail_hooks/litellm_content_filter/patterns.json
Co-authored-by: greptile-apps[bot] <165735046+greptile-apps[bot]@users.noreply.github.com>
---------
Co-authored-by: greptile-apps[bot] <165735046+greptile-apps[bot]@users.noreply.github.com>
* support policy mapping on team key level
* update document
* update document
* address comments
* update document
* add unit test for new feature
* add more test case
* Add monitor mode support to Lakera guardrail
- Add on_flagged parameter to LakeraV2GuardrailConfigModel (default: 'block')
- Support 'monitor' mode that logs violations without blocking requests
- Support 'block' mode (default) that raises HTTPException on violations
- Update async_pre_call_hook and async_moderation_hook to check on_flagged
- Update guardrail initializer to pass on_flagged from config
- Add documentation with monitor mode examples
This allows users to tune Lakera security policies by monitoring violations
without blocking legitimate requests, similar to Pillar's on_flagged_action.
* Add tests for Lakera guardrail monitor mode
- Test monitor mode allows flagged content through (pre_call hook)
- Test block mode raises HTTPException for violations (pre_call hook)
- Test monitor mode works with during_call (moderation_hook)
These tests verify the on_flagged parameter functionality for both
monitor and block modes across different guardrail hooks.
---------
Co-authored-by: Steve <steve.giguere@lakera.ai>
Fixed two issues:
1. Presidio guardrail test TypeError:
- Issue: test_presidio_apply_guardrail() was calling apply_guardrail() with
incorrect arguments (text=, language=) instead of the correct signature
(inputs=, request_data=, input_type=)
- Fix: Updated test to use correct method signature:
- Changed from: apply_guardrail(text=..., language=...)
- Changed to: apply_guardrail(inputs={'texts': [...]}, request_data={}, input_type='request')
- Also updated assertions to extract text from response['texts'][0]
2. License verification base64 decoding error:
- Issue: verify_license_without_api_request() was failing with
'Invalid base64-encoded string: number of data characters (185) cannot be
1 more than a multiple of 4' when license keys lacked proper base64 padding
- Root cause: Base64 strings must be a multiple of 4 characters. Some license
keys were missing padding characters (=) needed for proper decoding
- Fix: Added automatic padding before base64 decoding:
- Calculate padding needed: len(license_key) % 4
- Add '=' characters to make length a multiple of 4
- This makes license verification robust to keys with or without padding
Both fixes ensure the code handles edge cases properly and tests use correct APIs.
* fix(unified_guardrail.py): correctly map a v1/messages call to the anthropic unified guardrail
* fix: add more rigorous call type checks
* fix(anthropic_endpoints/endpoints.py): initialize logging object at the beginning of endpoint
ensures call id + trace id are emitted to guardrail api
* feat(anthropic/chat/guardrail_translation): support streaming guardrails
sample on every 5 chunks
* fix(openai/chat/guardrail_translation): support openai streaming guardrails
* fix: initial commit fixing output guardrails for responses api
* feat(openai/responses/guardrail_translation): handler.py - fix output checks on responses api
* fix(openai/responses/guardrail_translation/handler.py): ensure responses api guardrails work on streaming
* test: update tests
* test: update tests
* test: update tests
* fix(bedrock_guardrails.py): fix post call streaming iterator logic
* fix: fix return
* fix(bedrock_guardrails.py): fix
* 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
* feat: Add Pillar Security guardrail integration
Implements comprehensive LLM security guardrails using Pillar Security API with support for prompt injection detection, PII/secret detection, content moderation, and multi-mode execution (pre_call, during_call, post_call). Includes complete documentation, testing, and configurable actions on flagged content.
* fix: Resolve MyPy type error in Pillar guardrail config
Restructure PillarGuardrailConfigModel to properly inherit from GuardrailConfigModel[T]
and resolve return type compatibility issue in get_config_model method.
* fix: Resolve MyPy type error in Pillar guardrail config
Restructure PillarGuardrailConfigModel to properly inherit from GuardrailConfigModel[T]
and resolve return type compatibility issue in get_config_model method.
* fix docs
* fix docs
* improved docs
* fix examples, READY
