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6 commits
| Author | SHA1 | Message | Date | |
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yuneng-jiang
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6a0d03914c
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test: drop the cwd-relative sys.path.insert calls from the test suite (#37802)
* test: drop the cwd-relative sys.path.insert calls from the test suite
TQ003 stands at 1,077 across 1,058 files, and 1,015 of them are the same shape:
sys.path.insert(0, os.path.abspath("../..")) and its deeper siblings. The
argument resolves against the working directory rather than the file, so from
the repo root, where every job runs pytest, it inserts the directory two levels
above the checkout. It has never pointed at litellm. The package is installed
into the environment anyway, which is what actually makes the import work, and
what the rule's message has said all along.
Removing them leaves 1,634 imports of sys and os with no remaining reference,
and those go too, except where another test module imports the name back out of
the file. The rest of TQ003 is 62 call sites that resolve against __file__ or a
variable, which are a different question and are left alone.
Collection is identical either way: 45,871 tests and the same 51 pre-existing
collection errors before and after, and ruff reports no new undefined name.
* test: drop the duplicate imports the sys.path sweep exposed to F811
* test(pre-call-utils): restore the os import the new bedrock tests need
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Mateo Wang
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2c733c00f5
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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.
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Ishaan Jaffer
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e8461b5b97
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style: run black formatter on files from main merge | ||
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Vedant Madane
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11a622aa5a | Fix extract_cacheable_prefix to handle string content with message-level cache_control (fixes #19228) | ||
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Alexsander Hamir
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6e70c279f8
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[Fix] - Router's Cache: Fix routing for requests with same cacheable prefix but different user messages (#16951)
* fix(router): use cacheable prefix for prompt caching cache keys Fix issue where requests with same cacheable prefix but different user messages were routing to different deployments, preventing cached token reuse. The cache key now correctly includes only the cacheable prefix (up to and including the last cache_control block) instead of the entire messages array. ## New Functions ### extract_cacheable_prefix() Static method that extracts the cacheable prefix from messages for prompt caching. The cacheable prefix is defined as everything UP TO AND INCLUDING the LAST content block (across all messages) that has cache_control with type "ephemeral". This includes ALL blocks before the last cacheable block (even if they don't have cache_control themselves). - Finds the last content block with cache_control across all messages - Returns all messages and content blocks up to and including that last cacheable block - Excludes everything after the last cacheable block (including user messages that come after) - Returns empty list if no cacheable blocks are found ## Changed Functions ### get_prompt_caching_cache_key() Modified to use the cacheable prefix instead of the full messages array when generating cache keys. This ensures that requests with the same cacheable prefix but different user messages generate the same cache key, enabling proper routing to the same deployment. - Now calls extract_cacheable_prefix() to get only cacheable content - Returns None if no cacheable prefix is found (can't generate key) - Cache key is now based on cacheable prefix only, not full messages ### async_get_model_id() Completely refactored to use the cacheable prefix directly instead of the previous workaround that checked progressively shorter message slices. The previous implementation was inefficient and unreliable. - Removed progressive message slicing logic (messages[:-1], messages[:-2], etc.) - Now uses single direct cache lookup with cacheable prefix-based key - More efficient (1 lookup instead of up to 4) - More reliable (uses correct cache key based on cacheable prefix) - Returns None if no cacheable prefix found ### add_model_id() Added None check for cache_key to prevent caching when no cacheable prefix is found. This ensures we don't attempt to cache when there's no meaningful cache key to use. - Added guard: returns early if cache_key is None - Prevents attempting to cache when no cacheable prefix exists ### async_add_model_id() Added None check for cache_key to prevent caching when no cacheable prefix is found. Matches the behavior of add_model_id() for consistency. - Added guard: returns early if cache_key is None - Prevents attempting to cache when no cacheable prefix exists ### get_model_id() Added None check for cache_key to handle cases where no cacheable prefix is found. Ensures consistent behavior across all cache methods. - Added guard: returns None if cache_key is None - Prevents calling get_cache() with None key ## Test ### test_router_prompt_caching_same_cacheable_prefix_routes_to_same_deployment() New end-to-end test that validates the fix. Tests that requests with the same cacheable prefix (system blocks with cache_control) but different user messages: 1. Generate the same cache key 2. Successfully perform cache lookup 3. Route to the same deployment This test reproduces the exact scenario from the user's bug report where three requests with different user messages should route to the same deployment but were previously routing to different ones. Fixes issue where cached tokens couldn't be reused because requests were routed to different providers due to different cache keys. * fix(router): use cast() for proper type handling in extract_cacheable_prefix Replace type annotation with type: ignore comment with proper cast() from typing module, matching the pattern used throughout the codebase for creating modified AllMessageValues dictionaries. |
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Krish Dholakia
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0c0498dd60
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Litellm dev 12 07 2024 (#7086)
* fix(main.py): support passing max retries to azure/openai embedding integrations Fixes https://github.com/BerriAI/litellm/issues/7003 * feat(team_endpoints.py): allow updating team model aliases Closes https://github.com/BerriAI/litellm/issues/6956 * feat(router.py): allow specifying model id as fallback - skips any cooldown check Allows a default model to be checked if all models in cooldown s/o @micahjsmith * docs(reliability.md): add fallback to specific model to docs * fix(utils.py): new 'is_prompt_caching_valid_prompt' helper util Allows user to identify if messages/tools have prompt caching Related issue: https://github.com/BerriAI/litellm/issues/6784 * feat(router.py): store model id for prompt caching valid prompt Allows routing to that model id on subsequent requests * fix(router.py): only cache if prompt is valid prompt caching prompt prevents storing unnecessary items in cache * feat(router.py): support routing prompt caching enabled models to previous deployments Closes https://github.com/BerriAI/litellm/issues/6784 * test: fix linting errors * feat(databricks/): convert basemodel to dict and exclude none values allow passing pydantic message to databricks * fix(utils.py): ensure all chat completion messages are dict * (feat) Track `custom_llm_provider` in LiteLLMSpendLogs (#7081) * add custom_llm_provider to SpendLogsPayload * add custom_llm_provider to SpendLogs * add custom llm provider to SpendLogs payload * test_spend_logs_payload * Add MLflow to the side bar (#7031) Signed-off-by: B-Step62 <yuki.watanabe@databricks.com> * (bug fix) SpendLogs update DB catch all possible DB errors for retrying (#7082) * catch DB_CONNECTION_ERROR_TYPES * fix DB retry mechanism for SpendLog updates * use DB_CONNECTION_ERROR_TYPES in auth checks * fix exp back off for writing SpendLogs * use _raise_failed_update_spend_exception to ensure errors print as NON blocking * test_update_spend_logs_multiple_batches_with_failure * (Feat) Add StructuredOutputs support for Fireworks.AI (#7085) * fix model cost map fireworks ai "supports_response_schema": true, * fix supports_response_schema * fix map openai params fireworks ai * test_map_response_format * test_map_response_format * added deepinfra/Meta-Llama-3.1-405B-Instruct (#7084) * bump: version 1.53.9 → 1.54.0 * fix deepinfra * litellm db fixes LiteLLM_UserTable (#7089) * ci/cd queue new release * fix llama-3.3-70b-versatile * refactor - use consistent file naming convention `AI21/` -> `ai21` (#7090) * fix refactor - use consistent file naming convention * ci/cd run again * fix naming structure * fix use consistent naming (#7092) --------- Signed-off-by: B-Step62 <yuki.watanabe@databricks.com> Co-authored-by: Ishaan Jaff <ishaanjaffer0324@gmail.com> Co-authored-by: Yuki Watanabe <31463517+B-Step62@users.noreply.github.com> Co-authored-by: ali sayyah <ali.sayyah2@gmail.com> |