mirror of
https://github.com/BerriAI/litellm.git
synced 2026-10-11 03:38:38 +00:00
9 commits
| Author | SHA1 | Message | Date | |
|---|---|---|---|---|
yuneng-jiang
|
a11a93f44a
|
test: move tests/test_litellm core utils, routing, responses, caching and rust_bridge into tests/unit (#43199)
* 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 Delete eight tests the audit found superseded by stronger ones kept in this move.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: move tests/test_litellm core utils, routing, responses, caching and rust_bridge into tests/unit Rename-only. Mirrors the old paths, including fixtures, the stubtest config and the native-route wheel script. Two files that collide with existing unit files are merged in a follow-up commit. * test: merge, prune and repoint the moved core, routing, responses, caching and rust_bridge tests Merges the two files that collided with existing unit files, folding the legacy extra case into test_is_chat_completion_cached_dict, and deletes the 9 audited tests a stronger test in the same file already covers. Keeps what needs the network in tests/test_litellm: test_tokenizers pulls a tokenizer from the Hugging Face hub, and the gpt2 and r50k_base tokenizer cases download their BPE files. The unit core_utils conftest points TIKTOKEN_CACHE_DIR at litellm's bundled encodings so the rest never depend on import order to stay offline, and FakeSecretVault moves to a shared module so both trees can build it. * ci: run the moved core, routing, responses, caching and rust_bridge tests under their flags core_utils gets a core-utils flag and CircleCI job, and its GHA shard keeps the legacy path for the retained network tests. router_utils and router_strategy join enterprise-routing, responses joins responses-caching-types (minus responses/mcp, which mcp-integration owns), caching joins caching-local and rust_bridge joins misc. The redis-compat, test-rust, stubtest and merge-smoke paths follow the move. * docs: point the Rust crate references at tests/unit * test: make the moved core, routing and rust_bridge directories packages * test: keep the no-loop DualCache batch_get_cache regression test It runs the sync path outside any event loop, which the inside-loop test cannot, so a change that picks the Redis client by loop state would only show up there. * test: keep the job's UNIT_FLAG out of the shard-script tests * fix(url_utils): block 192.0.0.0/24 on every Python patch release * test: move the new budget limiter tests into tests/unit/router_strategy * test: move the new sentry scrubbing tests into tests/unit/litellm_core_utils * test: move the new zerobus tests into tests/unit/integrations * test: make tests/unit/integrations/zerobus a package * test: load litellm's own tiktoken cache setup once instead of resetting it per test --------- Co-authored-by: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> |
||
|
devin-ai-integration[bot]
|
a173657dfb
|
fix(caching): keep embedding cache hits aligned with request inputs (#42571)
* fix(caching): keep embedding cache hits aligned with request inputs Partial hits now send only the uncached inputs to the provider and merge fresh vectors back into their original positions. Responses whose item count differs from the input count (one input scoring many documents) are no longer written to the per-input cache, since a later hit would return a single item. Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * fix(caching): drop mutable collection builds flagged by the type discipline gate Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * fix(caching): bypass embedding cache entries written before the per input cardinality check Embedding cache entries now carry format_version and readers treat entries without it as misses, so entries that only hold the first row of a multi row response are refetched instead of served until their TTL expires. The provider call also receives a copy of the request kwargs with the uncached inputs rather than mutating the caller's mapping Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * test(caching): assert a partial embedding cache hit becomes a full hit on repeat Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * test(caching): await pending embedding cache writes before asserting on cache hits Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * fix(caching): validate cached embeddings without mutating responses or request kwargs Validate cache rows through a frozen pydantic model so import does not depend on TypeAdapter support for ReadOnly TypedDicts, accept string embeddings, build the merged partial hit response instead of mutating the cached one, and hand the provider request mapping to post call hooks Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * fix(caching): keep cache_hit and response_ms on merged partial embedding hits Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> --------- Co-authored-by: yassin <yassin@berri.ai> Co-authored-by: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> |
||
|
yassin
|
bea22df6c2 |
fix(caching): keep generic add_cache failures at ERROR unless the backend is Redis
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> |
||
|
devin-ai-integration[bot]
|
16db51e2cf
|
feat(caching): add semantic_cache_scope to isolate semantic cache hits per end user (#39590)
Semantic cache keys omit the prompt, so every end user behind one virtual key shares a bucket and can be served another user's semantically similar response. Add an opt-in cache_params.semantic_cache_scope (key | end_user) that appends the authenticated end-user id to the tenant scope, read from metadata and litellm_metadata so /v1/chat/completions, /v1/responses and /v1/messages are all covered, falling back to the key scope when no end-user id is present. Expose the setting in the cache settings API and the Admin UI cache settings form Co-authored-by: yassin <yassin@berri.ai> Co-authored-by: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> |
||
|
mateo-berri
|
ef2c30227a | fix(caching): truncate semantic cache embedding input, send extra_body top-level | ||
|
shivam
|
ab997e04eb |
fix(caching): cache anthropic /v1/messages responses, including streaming
anthropic_messages was missing from the cache's supported call types, so every /v1/messages request went to the provider. Adding it alone is not enough: the cache key is built from the OpenAI-ish param set, which has no system, top_k or stop_sequences, so two requests differing only by system prompt shared an entry and the second got the first one's answer. The Anthropic Messages request shape now feeds the key set as well. Streaming responses return to the caller before async_set_cache runs, so they are teed on the way out and the SSE events are stored verbatim once the stream reaches message_stop without a provider error. A hit replays those bytes and logs the request as a cache hit with zero cost. Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> |
||
|
Yassin Kortam
|
9c3ad1b094
|
feat(caching): add valkey-semantic cache backend and fix semantic cache scope keys (#30675)
Adds a "valkey-semantic" cache type so semantic prompt caching can run against Valkey clusters (for example AWS ElastiCache for Valkey) using the valkey-search module. The existing "redis-semantic" backend cannot drive valkey-search. RedisVL gates the connection on a RediSearch module version that valkey-search does not report, and its SemanticCache index declares the prompt as a TEXT field, which valkey-search does not implement. ValkeySemanticCache therefore talks to valkey-search directly over redis-py: it builds a vector index from the field types valkey-search supports (TAG for caller scope, VECTOR for the prompt embedding) and runs KNN queries for retrieval. Prompt extraction, embedding generation, and cached-response parsing are reused from RedisSemanticCache since those are backend agnostic. The redis dependency is imported lazily in the cache dispatch so importing litellm without redis installed still works. It also fixes semantic-cache scope keys so similarity matching works across reworded prompts. get_cache_key() hashed messages / prompt / input into the litellm_cache_key that every semantic backend filters its KNN search on, so a paraphrase landed in a different bucket and never matched, even far above the similarity threshold. For semantic cache types the prompt-bearing params are now excluded from the scope key and the server-set tenant identity (user_api_key, team, org) is appended instead, restoring embedding matching within a tenant while keeping cache entries scoped to the authenticated key / team / org. The three semantic backends share this key, so the same change fixes redis-semantic and qdrant-semantic. Connections resolve from VALKEY_HOST / VALKEY_PORT / VALKEY_PASSWORD, falling back to REDIS_* for drop-in compatibility, and passwordless clusters (IAM or no-auth) are supported. Resolves #29121 Fixes #29086 |
||
|
michelligabriele
|
2fe9feda71
|
fix(caching): restore stored prompt_tokens on embedding cache hits instead of recomputing (#30046) | ||
|
Sameer Kankute
|
32c88ca74f
|
Litellm oss staging 080626 (#29932)
* feat(bedrock_mantle): add SigV4/IAM auth to Responses API route (fixes #29665) (#29788) * feat(responses): add default no-op sign_request to BaseResponsesAPIConfig * feat(responses): call sign_request after body is final, send signed bytes when signed * feat(bedrock_mantle): add SigV4 sign_request via composed BaseAWSLLM (bearer path) * test(bedrock_mantle): cover SigV4 access-key, AssumeRole, body bytes, region/auth consistency * feat(bedrock_mantle): defer auth to sign_request; validate_environment no longer requires bearer * docs(bedrock_mantle): document SigV4 + Bearer auth on Responses route * test(responses): cover fake-stream signing order and mantle bearer arg/env precedence * fix(bedrock_mantle): wrap all botocore credential errors with both-paths guidance * fix(bedrock_mantle): catch specific credential errors, not all BotoCoreError, so STS transport failures are not masked * fix(bedrock_mantle): sign the compact Responses route too, not just create * fix(github-copilot): route per-model on /v1/responses based on model info (#29747) * feat(focus): add GCS destination for FOCUS export (#29751) * test: add failing tests for FocusGCSDestination * feat: add FocusGCSDestination reusing GCSBucketBase auth * feat: register FocusGCSDestination in factory; export from __init__ * fix(focus): preserve GCS_PATH_SERVICE_ACCOUNT when service_account_json not in config * style: apply Black formatting to gcs_destination and tests * style: apply Black formatting to factory.py * fix(bedrock): omit empty additionalModelRequestFields and system from Converse API payload (#29565) Amazon Nova Pro (and other strict Bedrock models) return 400 Malformed input request when additionalModelRequestFields: {} or system: [] are present in the payload. Both fields are optional in CommonRequestObject (total=False) and must be omitted rather than sent as empty structures. Co-authored-by: shin-berri <shin-laptop@berri.ai> Co-authored-by: yuneng-jiang <yuneng@berri.ai> Co-authored-by: Claude Sonnet 4.6 <noreply@anthropic.com> * fix(proxy): recognize *.cognitiveservices.azure.com as OpenAI-compatible in pass-through cost tracking (#29730) * fix(proxy): recognize *.cognitiveservices.azure.com as OpenAI-compatible Azure OpenAI resources created via the newer "Azure AI Foundry" / Cognitive Services pathway live on `*.cognitiveservices.azure.com` subdomains, not the older `openai.azure.com`. Both are valid Azure OpenAI surfaces in production today. The OpenAI pass-through cost-tracking handler hard-codes only the older hostname in five places (four `is_openai_*_route` methods on OpenAIPassthroughLoggingHandler, plus is_openai_route on PassThroughEndpointLogging). As a result, calls from newer Azure deployments are silently classified as "not an OpenAI route", the dispatch into the cost-tracking handler is skipped, and tokens/cost never get extracted into LiteLLM_SpendLogs — the row gets written with prompt_tokens=0, completion_tokens=0, spend=0, model='unknown'. Reproduced 2026-06-04 against a real Azure OpenAI deployment on `*.cognitiveservices.azure.com` proxied through LiteLLM v1.88.0. Fix: factor the hostname check into a single helper `_is_openai_compatible_host` listing all three recognized surfaces (api.openai.com, openai.azure.com, cognitiveservices.azure.com), and have all five call sites delegate to it. Purely additive — never weakens recognition for the originally-supported hostnames. Adds a test `test_is_openai_route_recognizes_cognitiveservices_azure_com` that exercises all four `is_openai_*_route` static methods against `*.cognitiveservices.azure.com` URLs (positive cases per route + a small cross-route negative to confirm route-specific path matching still works on the new hostname). Out of scope for this PR (separate followup): - `openai_passthrough_handler` calls chat/completions `transform_response` on Responses API payloads (`output:` not `choices:`), which throws inside the dispatch and drops the SpendLogs row entirely. Recognized + tracked separately. * ci: trigger fresh run Empty commit to re-run checks. The previous auth-and-jwt failure was a transient HuggingFace Hub 429 rate-limit hitting tokenizer downloads in tests/proxy_unit_tests/test_custom_tokenizer_bug.py — unrelated to this PR's scope (hostname recognition in pass-through cost tracking). No code change. --------- Co-authored-by: shin-berri <shin-laptop@berri.ai> Co-authored-by: yuneng-jiang <yuneng@berri.ai> * fix(responses): preserve forced-function tool_choice name in Responses to Chat transform (#29812) The Responses API forces a specific function with a top-level name ({"type": "function", "name": "X"}), but _transform_tool_choice only handled the nested Chat Completions shape and fell through to returning "required" for the flat form, silently dropping the function name and degrading a forced function call to force-any-tool. Map the flat Responses shape to the nested Chat shape, keeping the "required" fallback when no name is present. * Preserve x-anthropic-billing-header system blocks for first-party Anthropic (#29584) * Preserve x-anthropic-billing-header system blocks for first-party Anthropic PR #20951 strips system blocks beginning with "x-anthropic-billing-header:" for every Anthropic target. That block is how the first-party Anthropic API recognizes Claude Code subscription (OAuth) traffic, so dropping it makes requests that carry only that block, such as the auto-mode tool-safety classifier, fail with a misleading 429 rate_limit_error; normal turns still work because they also carry the "You are Claude Code" identity block. Gate the strip behind should_strip_billing_metadata(), defaulting to False on the first-party AnthropicConfig and AnthropicMessagesConfig so the block is kept, and overridden to True on the providers that reach these transforms and reject the block (Bedrock platform, Vertex, Azure for the chat path; Minimax, Azure, DeepSeek for the messages path). Behavior for those providers is unchanged. * Strip billing header on Bedrock invoke and Vertex messages pass-through Two more subclasses reach the gated strip but inherited keep-by-default. AmazonAnthropicClaudeConfig (Bedrock invoke) calls AnthropicConfig.transform_request, which calls translate_system_message, and VertexAIPartnerModelsAnthropicMessagesConfig (Vertex messages pass-through) calls super().transform_anthropic_messages_request. Override should_strip_billing_metadata() to True on both. Add a parametrized test asserting the flag for every first-party base (False) and provider subclass (True), covering all overrides, plus a translate_system_message regression test for the Bedrock invoke path. * fix(cache): log hashed cache keys (#29890) * fix(ui): save routing groups as list (#29889) * Revert "fix(ui): save routing groups as list (#29889)" (#29928) This reverts commit |