Claude hoists only the leading run of system messages, so a later one is now ordered where it sits when settling
ttls and trimming under drop_params. Before, a breakpoint ahead of a later system message's 1h mark went out as 5m
and Claude answered 400. A message-level breakpoint on a turn with no string content is no longer counted, since
Claude never receives it. The cache-control hook counts a prompt_cache_breakpoint on a tool call only for Claude
targets, so gpt-5.6 keeps the injection point it had before.
Unit tests for the block-level rename, the wire-order cap, the drop_params sources, prompt_cache_options rejection and the untouched native cache_control path on the Anthropic, Vertex AI, Bedrock invoke, Bedrock Converse and Azure AI transforms, plus a providers wire test that drives all five routes through a live proxy against scripted peers, including a proxy started with litellm_settings drop_params
A caller hitting /v1/messages with a cache_control mark and an OpenAI
gpt-5.6 or newer deployment behind it lost the mark when the request was
rebuilt as a Responses request, so OpenAI never cached at the boundary the
caller chose. The bridge now rewrites each marked system, user and
tool_result block to prompt_cache_breakpoint on the same block when the
deployment reads breakpoints, keeps the system prompt as a developer
message so its mark survives, and still strips the mark for deployments
that do not read it
The hook's gate becomes public so the bridge and the hook share one
answer for which deployments read breakpoints, and the one-block swap
lives next to the existing breakpoint helper in prompt_templates
* fix(responses): keep a flagged hosted deployment's prompt cache breakpoint on the chat bridge
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* fix(responses): read the serving provider's row for prompt cache breakpoints on the chat bridge and base_model
* fix(anthropic_cache_control_hook): rename the module-level provider resolver so the recursion check passes
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* test(ui): follow the credential dialog's new name field and auth method id in the federation e2e spec
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
---------
Co-authored-by: mateo <mateo@berri.ai>
Co-authored-by: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
Co-authored-by: mateo-berri <277851410+mateo-berri@users.noreply.github.com>
* fix(cache_control): let a hosted deployment opt into the OpenAI cache dialect
_targets_openai_prompt_cache_breakpoint gated on custom_llm_provider == "openai"
unconditionally, so an OpenAI-shaped model served by another provider could never
qualify, even with supports_prompt_cache_breakpoint set explicitly on its own
cost-map entry. bedrock_mantle honours prompt_cache_breakpoint end to end, and
had no way to say so.
model_cost is keyed per exact deployment string, so a flag on the deployment's own
entry states the dialect more precisely than a provider name can. Consult it
before the provider check, and require the entry's litellm_provider to match the
serving provider so an openai entry cannot license another provider. Entries for
the openai provider keep their api_base check, so an OpenAI-compatible third-party
host is still not assumed to speak the dialect.
Fixes#38666
* test: drop a laziness assertion the existing suite already makes
test_provider_lookup_skipped_for_models_below_gpt_5_6 already pins that
_resolve_provider is not called for an unflagged model, and it covers the new
flag lookup unchanged. The duplicate patched a litellm internal for no added
coverage, which the test-quality gate counts against TQ008.
* fix(bedrock_mantle): flag GPT-5.6 and newer rows for OpenAI explicit prompt cache breakpoints
* fix(responses): predict the chat-completions bridge with the model name the dispatch resolves
* fix(cache_control): read a region-prefixed Mantle GPT deployment through its region-free price-map row
* fix(cache_control): let a bare hosted deployment name read its own provider's price-map row
* fix(responses): hand the hook the provider the router resolved for a Foundry GPT deployment
* fix(cache_control): read the deployment breakpoint flag strictly and default a null prompt_cache_options
A cost-map or deployment `supports_prompt_cache_breakpoint` that is not the boolean `true` (the string "true",
the integer 1, "false", 0, a long string) no longer opts a deployment into the OpenAI prompt cache dialect; only
`true` does, the same reading Bedrock Converse applies to its own flag.
A client that sends `"prompt_cache_options": null` on `/v1/chat/completions` or `/v1/messages` now gets the
implicit default the hook already applied on `/v1/responses` when it placed a breakpoint; before, the null
suppressed the default and the request left with a breakpoint and no options.
* test(integration): audit cells for the Mantle GPT prompt cache breakpoint dialect
Deterministic cells for the configured-breakpoint path on Bedrock Mantle GPT and Azure AI Foundry GPT-6
deployments: every endpoint, streaming and not, sync and async SDKs and raw httpx, the hostile option shapes,
flag precedence, the response cache twin, a two-worker burst, a worker kill and a graceful restart.
* fix(cache_control): ignore a malformed cache_control_injection_points value instead of failing the request
A deployment or client `cache_control_injection_points` that is not a list of points (a string, an
integer, a bare point dict, a list of strings) raised inside the prompt hook (`'str' object has no
attribute 'get'`, `'int' object is not iterable`) and turned every request to that deployment into a
500 on `/v1/chat/completions`, `/v1/messages` and `/v1/responses`. Every entry point now reads such a
value as no configured points, the way a `null` already read, and the request leaves without a
breakpoint; entries of a list that are not points are dropped and the point entries kept.
* test(integration): cover int, dict and string-list injection point shapes in the Mantle audit cells
The D9 cell now also sends an integer, a bare point dict and a list of strings as the deployment's
`cache_control_injection_points`, which the merge base answered with a 500 on every request.
* fix(cache_control): stamp the OpenAI dialect for a bare deployment name served by a flagged provider
A deployment written as `model: openai.gpt-5.6-sol` with `custom_llm_provider: bedrock_mantle` has no cost-map row
of its own and no openai row of the same name, so the dialect stamp's cheap gate (`supports_openai_prompt_cache_breakpoint`)
returned early and the configured point was never stamped. On `/v1/responses` and on the chat seeding path the hook
sees no provider, so it fell back to the Anthropic `cache_control` marker, which Bedrock Mantle strips.
The gate now also passes a model whose serving provider is already known and whose provider-keyed row carries the
flag, which is the same row the dialect resolution reads and costs no provider lookup. A bare name without a provider
is still left alone, so models below GPT-5.6 keep their points untouched and resolve nothing.
* test(integration): cover a bare Mantle deployment name with its provider in the audit cells
A deployment configured as `model: openai.gpt-5.6-sol` plus `custom_llm_provider: bedrock_mantle` sends the
breakpoint and the implicit options on all three endpoints; the merge base leaves it on the Anthropic dialect.
* fix(cache_control): keep a configured point that sits beside junk entries on every chat seed path
`configured_injection_points` kept the point dicts of a mixed `cache_control_injection_points` list as a tuple,
but only read a `list` back. The chat seed and the `/v1/responses` dialect stamp write the normalized value back
onto the request, and on a deployment the OpenAI dialect does not stamp (an Anthropic model, Claude on Bedrock
Mantle) that value is the tuple itself, so the hook then read it as no configured points and the valid point was
silently dropped. The stamped OpenAI dialect and the `/v1/messages` path kept it only because they build a new list.
The normalizer now reads back the tuple it wrote, so the point reaches the wire on every path; an all-dict list
still passes through as the same object.
* test(integration): cover a configured point beside junk entries on a Claude Mantle deployment
A deployment configured with `cache_control_injection_points: ["system", {system point}, 3]` marks the system
block on the Anthropic dialect on all three endpoints; the merge base answers 500 on the junk entry.
---------
Co-authored-by: mateo-berri <277851410+mateo-berri@users.noreply.github.com>
* fix(caching): count tool_call cache_control marks in the injection census
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* fix(caching): remove cache census casts
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* fix(caching): only skip injection on message or content marks
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* fix(caching): skip injection on messages whose tool calls carry marks
Reverts 9f08d8aef8. A default 5m mark injected on assistant text lands
before the client's 1h tool_use mark, which Anthropic rejects with a 400
because a 1h breakpoint must not follow a 5m one. Keeping the full census
in the skip check leaves the client's tool_call breakpoint as the only
one on that message.
* fix(caching): count every client tool_call cache mark in the breakpoint census
The census gated tool_call marks on type function and dict shape, so a client mark on a call without a type or with a string cache_control slipped past the count and injection overflowed the 4 breakpoint cap. Count any non-None tool_call mark, keep the server tool exclusion, and add integration cells for the capped surfaces, the yaml stand-down, Bedrock and Gemini, and router affinity
* test(integration): hold the upstream so the worker kill lands mid-burst
* refactor(caching): reuse the transform's server tool lookup in the breakpoint census
The census now calls the same helper the Anthropic transform uses to decide
whether a marked tool call becomes a server tool block, so the two cannot
drift apart. The owned-proxy burst test waits up to 90 seconds for the burst
to reach the wire before it kills a worker
* refactor(anthropic): move the server tool rebuild check under llms/anthropic
* test(integration): audit the tool call mark census across chat, messages, responses, and chaos
Adds the /audit cells for the breakpoint census on assistant tool_calls marks: the
Responses stream bridge, the OpenAI and Anthropic SDK clients, in-process Pydantic
messages, response cache twins, request-level points, a provider 401 on a capped request,
malformed provider_specific_fields and tool_call ids, null or empty points, a points
update mid-burst, a proxy restart mid-burst, and a worker SIGKILL that picks the worker
holding the burst's upstream connections
* test(integration): close the SDK clients the cache census cells open
---------
Co-authored-by: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
Co-authored-by: mateo-berri <277851410+mateo-berri@users.noreply.github.com>
* fix(caching): stand default cache points down when extra_body hides a direct client mark
On native /v1/messages the extra_body envelope is dropped, so a client tool mark or root cache_control reaches Anthropic even when extra_body overrides it. The stand-down check only counted the envelope-merged view and injected two default marks on top of the client's.
* fix(caching): keep chat completions on the envelope-merged mark count for the default stand-down
Chat completions merge extra_body over the request, so a direct tool mark that extra_body replaces never reaches the provider there. Only /v1/messages, where the native transforms drop the envelope, needs to count marks on both sides.
* ci: run the unit_selection.sh shard files on every event instead of only fork pull requests
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* ci: rename fork-flag to unit-flag now that it applies on every event
* test: move tests/test_litellm root and small trees into tests/unit
Pure renames, no content changes. Follow-up commits in this PR fix
references, merge the three files that already existed in tests/unit,
keep live-provider tests in tests/test_litellm and wire CI.
* test: carry tests/test_litellm conftest isolation into tests/unit
Callback lists, routing fallbacks, cached HTTP clients, logger state, AWS,
proxy-URL and keychain env, and session-end client cleanup now reset for
unit tests too. The environment isolation owns its MonkeyPatch so a test's
own monkeypatch is undone before the model-cost teardown runs.
* test: merge, split and prune the moved root and small-tree tests
Merge batches/test_batch_utils.py and the chat_completions and messages
dispatch tests into the files that already existed in tests/unit. Keep
the live Gemini interactions tests, the async image-fetch format test and
the OpenAI embedding scorer test in tests/test_litellm since they need
real network or keys. Put test_router.py under tests/unit/test_router so
the existing package no longer shadows it. Delete eight tests the audit
found superseded by stronger ones kept in this move.
* ci: run the moved root and small-tree tests under their legacy flags
Add the misc and responses-caching-types flags to unit_selection.sh and
CircleCI, extend enterprise-routing and mcp-integration, and point the
legacy GHA shards, Makefile, redis-compat workflow, merge smoke manifest
and change classifier at the new paths.
* test: make the new tests/unit directories packages
tests/unit/test_package_layout.py requires every directory to carry an
__init__.py, and without one the moved and retained
test_litellm_responses_bridge.py modules collide on import.
* test: scope the unit socket block to tests/unit in shared sessions
The GHA shards collect the legacy test-path and the unit selection in one
pytest session. The unit conftest's loopback-only block leaked into legacy
modules that reach the network at import. The legacy conftest now lifts the
restriction at collect and setup time, and the unit conftest re-applies it
when collecting its own modules.
* test: move tests/test_litellm/llms into tests/unit/llms
Rename-only. Moves the provider tests and the fine-tuning fixtures they
load, mirroring the old paths. Follow-up commits merge, split and wire them.
* test: merge, split and prune the moved llms tests
Merges the Databricks chat transformation tests into the existing unit
file, keeps the tests that need real keys or the network in
tests/test_litellm, deletes the audited tests a stronger unit test
already covers, and points imports at tests.unit.llms.
* ci: run the moved llms tests under their legacy flags
The Vertex AI and All Other Providers shards keep their legacy test-path
for the retained files and add the llm-vertex-ai and llm-other-providers
unit selections. CircleCI gets matching unit jobs.
* test: make the tests/unit/llms directories packages
Adds __init__.py to the moved dirs and drops the legacy ones whose
directories no longer hold tests.
* test: drop script runners and path hacks the llms split left dangling
The __main__ runners in the split openai_like files and the Databricks e2e
runner called tests that now live in the other half of the split or were
deleted. The retained legacy halves also no longer need sys.path edits.
* test: give the shard-script tests their own GITHUB_OUTPUT
They only passed where the runner set it. The CircleCI unit job's env
allowlist drops it, so the script's redirect failed there.
* test: point the router and module-deletion checks at tests/unit
router_code_coverage and code_qa_check_tests only searched tests/test_litellm,
so the moved router tests no longer counted. The two silent-experiment tests
the audit deleted were the only direct callers of those methods; they are
replaced with tests that assert the forwarded shadow request and the
recursion guard.
* test: move tests/test_litellm integrations and secret_managers into tests/unit
Rename-only. Mirrors the old paths, including the directory conftests
and the prompt and JSON fixtures. Follow-up commits prune and wire them.
* test: prune and repoint the moved integrations tests
Deletes the 7 audited tests a stronger test in the same tree already
covers, imports the TLS sink helpers from their new conftest path, and
restores os.environ after each integrations test. Some presets write
OTEL_EXPORTER_OTLP_HEADERS straight into os.environ, and without the
legacy tree's test ordering that header leaked into the AgentOps tests.
* ci: run the moved integrations tests under their legacy flag
The integrations GHA shard and a new CircleCI job run the integrations
unit selection. secret_managers joins the misc selection.
* docs: point integrations and secret_managers references at tests/unit
* test: make the moved integrations directories packages
* test: keep the Databricks manual e2e runner and fix the SageMaker Nova run path
The Databricks e2e file is a manual script whose main() calls the tests
that were pruned, so pruning them broke the documented run. It is back to
its main version. The SageMaker Nova docstring now points at the file's
real location in tests/local_testing.
* test: keep the job's UNIT_FLAG out of the shard-script tests
---------
Co-authored-by: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
2026-09-25 12:57:07 -07:00
Renamed from tests/test_litellm/integrations/test_anthropic_cache_control_hook.py (Browse further)
