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234 commits
| Author | SHA1 | Message | Date | |
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Sameer Kankute
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3b40ac987f
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Litellm oss 090626 (#30021)
* fix(mcp): report scoped server name during initialize (#29865) * fix mcp scoped server name * Update litellm/proxy/_experimental/mcp_server/mcp_context.py Co-authored-by: greptile-apps[bot] <165735046+greptile-apps[bot]@users.noreply.github.com> * test(mcp): cover scoped server name in the SSE initialize handler --------- Co-authored-by: greptile-apps[bot] <165735046+greptile-apps[bot]@users.noreply.github.com> * fix(ui): show all session logs in the drawer, not just the first 50 (#29795) * fix(ui): show newest session logs first * test(ui): keep session log pagination coverage * fix(ui): show all session logs in the drawer, not just the first page The session detail drawer fetched session logs via sessionSpendLogsCall without page/page_size, so it only ever received the backend default of one page (50 rows). Sessions with more than 50 calls had the rest unreachable in the UI (#29153). sessionSpendLogsCall now takes page/page_size, and the drawer fetches the first page, reads total_pages, then fetches the remaining pages and accumulates them before the existing client-side sort. This keeps the single continuous list (and the selected-log lookup and keyboard navigation, which all assume the full session) correct. Fetching is bounded by a page cap, and the sidebar shows a "showing most recent N" note if a session exceeds it. The rows are lightweight metadata (the endpoint excludes messages/response), so the full set is small; request/response bodies are still loaded per log on demand. * fix(ui): default session drawer to most recent log, newest first Open a session with its most recent log selected, and order the sidebar newest-first to match the all-sessions logs overview. MCP calls stay grouped last. The latest log by time is computed explicitly, since the MCP grouping means it is not always the first row. * Apply fetching pages in batches suggestion from @greptile-apps[bot] Co-authored-by: greptile-apps[bot] <165735046+greptile-apps[bot]@users.noreply.github.com> * fix(ui): derive session total from accumulated rows when backend omits it Compute the session total after all pages are fetched, falling back to the accumulated row count rather than the first page's. Guards the truncation note against a backend response that omits total but spans multiple pages. --------- Co-authored-by: Yufeng He <40085740+he-yufeng@users.noreply.github.com> Co-authored-by: greptile-apps[bot] <165735046+greptile-apps[bot]@users.noreply.github.com> * fix(proxy): handle Mistral multipart passthrough (#29927) * fix(proxy): handle Mistral multipart passthrough * chore: satisfy passthrough ci formatting * test(proxy): cover Mistral passthrough in CI shard * fix(vertex_ai): use REP host for context caching on eu/us multi-region endpoints (#29573) Context caching built the cachedContents URL as https://{location}-aiplatform.googleapis.com, which is an invalid host for the eu/us multi-region endpoints and returns 404. The inference path already resolves these to the REP host (https://aiplatform.{geo}.rep.googleapis.com) via get_vertex_base_url(); reuse that helper in _get_token_and_url_context_caching so caching uses the same host as inference. Adds tests covering the eu/us multi-region cachedContents URLs (v1 and v1beta1). Fixes #29571 * Support per-model encrypted content affinity config (#29760) Co-authored-by: shin-berri <shin-laptop@berri.ai> Co-authored-by: yuneng-jiang <yuneng@berri.ai> * fix: propagate upstream status code in proxy API exception handler (#29402) * fix: propagate upstream status code in proxy API exception handler When Google GenAI / Vertex returns a 404 for deprecated or missing models via streamGenerateContent, the exception was falling through to a generic handler that defaulted to 500. Now provider exceptions carrying a valid HTTP status_code correctly propagate it through to the ProxyException. * fix: apply black formatting to common_request_processing.py * fix: tighten status code range to 400-599 and deduplicate ProxyException raise * fix(tests): use valid vertex_location in context caching tests Replace "test_location" (contains underscore) with "us-central1" so tests pass the regex validation added in get_vertex_base_url(). Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com> * feat(sdk): add xAI OAuth provider (#29866) * Add xAI OAuth provider * Update oauth.py Co-authored-by: greptile-apps[bot] <165735046+greptile-apps[bot]@users.noreply.github.com> * Fix xAI OAuth CI failures * Add xAI OAuth coverage tests * Move xAI OAuth coverage tests to core utils * Address xAI OAuth review comments * Prevent xAI OAuth api_base token exfiltration * Treat blank xAI OAuth api keys as absent * Wrap invalid xAI OAuth JSON responses * Use xAI OAuth behind explicit flag --------- Co-authored-by: greptile-apps[bot] <165735046+greptile-apps[bot]@users.noreply.github.com> * fix(proxy) #27734 allow clearing budget_duration and team_member fields by sending null on /key/update and /team/update (#27751) * fix(proxy): allow clearing budget_duration and team_member fields by sending null on /key/update and /team/update Fixes #27734 Sending null for budget_duration, team_member_budget, team_member_budget_duration, team_member_rpm_limit, or team_member_tpm_limit via /key/update or /team/update returned 200 OK but silently ignored the null value. The fields remained unchanged in the database. Root causes: - /key/update: prepare_key_update_data() popped budget_duration from the update dict but never re-added it (or budget_reset_at) when the value was None. - /team/update: _set_budget_reset_at() only acted when budget_duration was non-None, leaving a stale budget_reset_at in the DB. - /team/update: team_member_* null values bypassed the budget table update entirely because should_create_budget() requires at least one non-None field. * test(proxy): cover no-budget-row path in clear_team_member_budget_fields * fix(presidio): unmask PII tokens in Anthropic native SSE streaming bytes (#30028) * fix(presidio): unmask PII tokens in Anthropic native SSE streaming bytes When output_parse_pii=true on the Anthropic native path (anthropic/claude-*), response chunks arrive as raw bytes in SSE format. _stream_pii_unmasking was yielding those bytes unchanged, so <PERSON_1> tokens were never replaced with the original values before reaching the caller. Add _unmask_sse_bytes_chunk to parse each data: line, find content_block_delta / text_delta events, and apply _unmask_pii_text before re-encoding. Wire it into _stream_pii_unmasking so bytes chunks are unmasked when pii_tokens exist. * fix(presidio): handle CRLF line endings and non-ASCII PII in SSE unmask Strip trailing \r before the [DONE] guard so CRLF-terminated SSE chunks don't bypass it and silently swallow a JSONDecodeError. Add ensure_ascii=False to json.dumps so non-ASCII replacement values like accented names are preserved as UTF-8 on the wire rather than being \uXXXX-escaped. Add regression tests for both cases. * feat(bedrock_mantle): path-aware Responses routing (/v1/responses vs /openai/v1/responses) (#29925) * feat(bedrock_mantle): path-aware Responses routing (/v1/responses vs /openai/v1/responses) Bedrock Mantle serves the Responses API on two upstream paths: - gpt frontier models (gpt-5.5 / gpt-5.4) on /openai/v1/responses - every other Responses-capable model (e.g. gpt-oss) on the standard /v1/responses BedrockMantleResponsesAPIConfig gains a `use_openai_path` flag; the provider gate in utils.py picks the path per model: openai.gpt-* (non gpt-oss) -> /openai/v1/responses; any model declared mode=responses (price-map entry or user model_info) -> /v1/responses; everything else returns None and keeps the existing chat-completions emulation. Adds gpt-5.5 / gpt-5.4 price-map entries, registry wiring, and the routing-matrix tests. * feat(bedrock_mantle): data-driven frontier routing via use_openai_responses_path Addresses the Greptile review point that frontier detection should be a price-map field rather than a hardcoded name match. The gate now routes a model to /openai/v1/responses when its price-map entry declares use_openai_responses_path, so a frontier model whose name does not follow the openai.gpt- convention can be onboarded by JSON alone. The name-convention check is kept as a fallback that needs no price-map entry, which preserves zero-change routing for a future gpt-6 before its entry loads. gpt-5.5 / gpt-5.4 get the flag in both price maps. Adds tests for the data-driven flag path and for the flag presence on the gpt-5.x entries; both branches are mutation-tested. * test(model_prices): allow use_openai_responses_path in price-map schema The model_prices_and_context_window.json schema validator (test_aaamodel_prices_and_context_window_json_is_valid) enforces additionalProperties: false, so the new use_openai_responses_path flag on the gpt-5.5 / gpt-5.4 entries failed validation. Add it to the schema as a boolean, alongside the other supports_* / capability flags. * Add Tensormesh serverless models to the model cost map (#30037) * Add Tensormesh serverless models to the model cost map * Flag reasoning support on the Tensormesh models that expose thinking mode * fix(proxy): invalidate stale key spend counter after budget reset or manual spend update (#30001) * fix(proxy): reconcile stale key spend counter after budget reset * fix(proxy): invalidate stale key spend counter after budget reset or manual spend update * fix(proxy): remove read-time stale counter reconciliation to prevent budget bypass * revert: undo unrelated formatting changes in enterprise directory * test(proxy): add unit test for key spend update invalidating counter * test(proxy): fix mocked update_data and hash token expectations in unit test * fix(proxy): use Responses-API transformer in pass-through cost tracking (#29728) The `elif is_responses:` branch of `openai_passthrough_handler` was calling the chat-completions `transform_response` on a Responses API payload. The chat-completions transformer expects `choices: [...]` in the raw response; the Responses API uses `output: [...]` and `usage.input_tokens` / `usage.output_tokens` (not `prompt_tokens` / `completion_tokens`). The result was a KeyError 'choices' deep inside `convert_to_model_response_object`, swallowed by the surrounding `except Exception` in the handler, and the SpendLogs row was written by the fallback path with zeroed-out tokens, spend, and model. This bug silently undercounts cost for every successful pass-through call to either OpenAI's `/v1/responses` or Azure's `/openai/v1/responses` (deployments configured for the Responses API). Reproduced 2026-06-04 against a real Azure OpenAI Responses API deployment proxied through LiteLLM v1.88.0. Fix: use the dedicated `OpenAIResponsesAPIConfig.transform_response_api_response` for the Responses branch. This transformer already exists in LiteLLM (`litellm/llms/openai/responses/transformation.py`) and knows the Responses-API on-the-wire shape. `litellm.completion_cost` already handles `ResponsesAPIResponse` natively with `call_type="responses"`, so no downstream changes are needed. Tests: test_responses_api_uses_responses_transformer_not_chat_completions NEW. Real regression test — exercises the openai_passthrough_handler with a real-shaped Responses payload (no `choices`, has `output` and Responses-API `usage` keys) and NO mocked `get_provider_config`. Pre-fix: raises KeyError 'choices' inside the chat-completions transformer (the bug). Post-fix: returns a ResponsesAPIResponse, completion_cost is called with call_type="responses" and a ResponsesAPIResponse instance (asserted). Verified to fail on un-fixed handler + pass on fixed handler before commit. test_responses_api_cost_tracking UPDATED. Old test mocked `get_provider_config` (no longer called in the responses branch post-fix). Now mocks the Responses transformer directly (`OpenAIResponsesAPIConfig.transform_response_api_response`) to test the downstream cost-calc contract. Out of scope for this PR (separate followup): - Recognizing *.cognitiveservices.azure.com (the newer Azure OpenAI hostname) in the is_openai_*_route checks. Separate PR. Co-authored-by: shin-berri <shin-laptop@berri.ai> Co-authored-by: yuneng-jiang <yuneng@berri.ai> * fix(skills): execute DB skills by matching the litellm_skill_ tool name prefix (#30116) Skill IDs are generated as litellm_skill_<uuid> and the model-facing tool name is the sanitized skill ID, but the post-call execution gates in SkillsInjectionHook only ran tools whose name starts with "skill_", so DB skills were silently returned to the client as raw tool calls. Fixes #28122. Co-authored-by: Cursor <cursoragent@cursor.com> * fix(anthropic): synthesize content_block_start when Responses stream omits output_item.added (#30115) * fix(team): reserve team budget raises for proxy admins on /team/update (#30030) The caller's PERSONAL max_budget was the wrong yardstick for /team/update: a team's spend ceiling has nothing to do with the admin's own key budget. That comparison was an unintended side effect of reusing _check_user_team_limits() (which exists for the /team/new path) and broke the UI, which re-sends the unchanged budget on every save. New behavior on /team/update for standalone teams: - A team admin (already authorized via _verify_team_access) may freely KEEP or LOWER the team budget, and change models/tpm/rpm, without being gated by their personal limits. - GROWING a team's spend ceiling is a budget-authority action reserved for proxy admins -> 403 for team admins. "Growing" covers both raising max_budget above the team's current finite value and removing the cap entirely (max_budget=null, detected via model_fields_set so an explicit null is distinguished from an omitted field). For a team that currently has no cap, setting a finite value is a restriction and is allowed. - Org-scoped teams remain governed by _check_org_team_limits() (capped by the org budget). Also reverts the #29525 existing_team_max_budget workaround in _check_user_team_limits() back to the create-only form; /team/new still enforces the creator's personal caps. docs(access_control): resolve the contradiction in the team-admin section — team admins can keep/lower the budget and manage rate limits/models, but cannot raise the team budget (proxy-admin only). tests: unit + behavior coverage for raise-blocked, cap-removal-blocked (team admin), raise/removal allowed (proxy admin), uncapped-team restriction allowed, keep/lower/resend allowed, and unchanged create-path guards. Co-authored-by: Cursor <cursoragent@cursor.com> * test(ui): data-driven App Router migration E2E smoke (default + server-root-path) (#29974) * test(ui): add a data-driven App Router migration E2E smoke Add a growing Playwright smoke for migrated pages: for each segment it deep-links to the path route, asserts the URL and that the dashboard shell rendered, then clicks off to a legacy page and asserts navigation still works. Driven by e2e_tests/fixtures/migratedPages.ts, so adding a page is one line. Runs in two situations against the same proxy: the default mount (npm run e2e:migration) and a non-root SERVER_ROOT_PATH mount (npm run e2e:migration:root). globalSetup now logs in at `${SERVER_ROOT_PATH}/ui/login` so the admin storage state is valid under a prefix. Seeded with api-reference; append the rest as their migrations merge. * test(ui): support headed slow-motion + watch pauses in the migration smoke Honor SLOWMO in the server-root-path config (the default config already did), and add an env-gated E2E_WATCH_MS pause so a headed run lingers on each state. Both are no-ops by default, so CI behavior is unchanged. * test(ui): make the migration smoke a sidebar-click user journey Rework the smoke from deep-linking to a real navigation journey: start at the landing page, click the migrated page in the sidebar (expanding submenus for nested items), assert the path route rendered, reload it (the check a wrong server_root_path breaks), bounce to a legacy page and back, and — once two pages are migrated — navigate directly between two migrated pages. Verifies via URL + shell render, driven by the same fixture list. * test(ui): address review on the migration smoke Escape ROOT and segment before interpolating them into RegExp URL matchers so a future segment containing regex metacharacters can't silently widen the match. Make the server-root-path config fail fast when SERVER_ROOT_PATH is unset instead of silently re-running the default mount and passing without exercising the prefix. * test(ui): drop unused watch helper and fix stale smoke README * test(ui): run the migration smoke under a server root path in CI * test(ui): harden + instrument the server-root-path proxy reboot in CI * test(ui): run the server-root-path migration smoke as its own CI job Replace the in-place proxy reboot in e2e_ui_testing with a dedicated e2e_ui_testing_server_root_path job that boots the proxy once with SERVER_ROOT_PATH=/litellm, matching how every other proxy variant in the config gets its own job rather than killing and relaunching the live proxy. The reboot was failing deterministically: after pkill -9 and relaunch the prefixed proxy never came back up on :4000 (connection refused), so the smoke never ran. The readiness step that was supposed to surface the cause could never reach its boot-log tail because CircleCI runs steps under bash -eo pipefail and the preceding `curl -sv ... | tail` aborted the step with curl's exit 7. Booting the proxy as the job's own background step lets any boot crash land in that step's log instead of being swallowed. The default e2e_ui_testing job is unchanged aside from dropping the reboot, prefixed-readiness, and prefixed-smoke steps; the migration smoke still runs at the root mount there via the default Playwright config. * fix(proxy): extend response headers hook to streaming, TTS, image gen, and pass-through (#24232) * fix(proxy): extend response headers hook to streaming, TTS, image gen, and pass-through * test: mock post_call_response_headers_hook in audio speech route tests * chore(ui): remove dead App Router route stubs under (dashboard) (#30045) models-and-endpoints, organizations, and virtual-keys each had a page.tsx route under (dashboard)/ that is not in MIGRATED_PAGES, so the sidebar and deep links never resolve to it and the route is unreachable. Each was a thin wrapper that handed the shared view empty or no-op props (empty modelData with a no-op setModelData, hardcoded empty organizations, no-op setUserRole/setUserEmail), so reaching one would render a degraded page in any case. The real wrapper belongs in the PR that flips each page into MIGRATED_PAGES, written with eyes on it and a test This continues the dead-scaffolding cleanup from #28891. The shared components these wrappers rendered (ModelsAndEndpointsView, OrganizationFilters) stay, since the legacy ?page= switch in app/page.tsx and src/components still import them * fix(ui/mcp): reset OAuth state on create-server modal close so a prior server's token no longer leaks into the next add-server session (#30000) * fix(ui/mcp): reset OAuth hook state on modal close so a prior server's token no longer leaks into the next add-server session * fix(ui/mcp): clear in-flight OAuth guard on reset and reset form/tools on modal close so nothing leaks on a parent-driven dismiss * fix(mcp): allow team access-group grants in OAuth authorize/token access check (#30041) * fix(mcp): honor team access-group grants in OAuth authorize/token access check * test(mcp): mock build_effective_auth_contexts in non-admin authorize tests for isolation * docs(security): require a reproduction video for vulnerability reports (#30048) (#30063) With AI models capable of automated vulnerability discovery now publicly available, we expect a large increase in report volume, much of it unverified. Requiring a video of the exploit running against a live instance raises the bar for submissions and keeps triage focused on reproducible issues. Reports without a video will be closed and reopened if one is added later. Co-authored-by: stuxf <70670632+stuxf@users.noreply.github.com> * feat(ui): add admin flag to disable in-product UI nudges for everyone (#29796) * feat(ui): add admin flag to disable in-product UI nudges for everyone Admins can now suppress the survey and Claude Code feedback popups for all users via a single disable_ui_nudges UI setting, instead of relying on each user dismissing them individually. * fix(ui): suppress nudges while ui settings are loading Gate nudgesDisabled on the ui-settings loading state so an admin with disable_ui_nudges on doesn't see the survey prompt flash, and the getInProductNudgesCall fetch doesn't fire, on a cold page load before the flag resolves. Falls back to showing nudges if the fetch errors. * test(ui): wrap CreateKeyPage test in QueryClientProvider page.tsx now calls useUISettings (react-query), which needs a QueryClient that layout.tsx supplies in production but the test did not. Add the provider and mock getUiSettings so the query resolves. * chore(ui): remove dead dashboard files and unused dependencies (#30047) * chore(ui): remove dead dashboard files and unused dependencies knip flagged seven orphaned source/config files with no importers and five declared dependencies that nothing in the tree uses. Removing them shrinks the dashboard bundle's source surface and keeps the manifest honest; vite stays installed transitively via vitest, so test tooling is unaffected. * fix(ci): restore serverRootPath.config.ts referenced by SERVER_ROOT_PATH workflow The dead-code sweep removed e2e_tests/serverRootPath.config.ts, but its spec (tests/login/serverRootPathRedirect.spec.ts) and the test_server_root_path.yml workflow step still depend on it, so the redirect e2e job failed to load a config that no longer existed. * fix(proxy): authorize batch files using upload target_model_names (LIT-3593) (#30009) * fix(proxy): authorize batch files using upload target_model_names (LIT-3593) After replace_model_in_jsonl, body.model is a stripped provider id. Reverse-mapping it via resolve_model_name_from_model_id is first-match on model_list and caused false 403s when multiple deployments share the same stripped name. Use target_model_names from the unified file id instead. Co-authored-by: Cursor <cursoragent@cursor.com> * fix(proxy): restore resolve_model_name_from_model_id for JSONL fallback path (LIT-3593) Restores the reverse-lookup for the JSONL body.model fallback path so that legacy/pre-target_model_names managed files still map stripped provider IDs back to proxy aliases before auth. Also cleans up redundant `or None`. Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com> * Revert "fix(proxy): restore resolve_model_name_from_model_id for JSONL fallback path (LIT-3593)" This reverts commit |
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Mateo Wang
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e15b37a18e
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Add Claude Fable 5 across Anthropic, Bedrock, Vertex AI, and Azure AI (#30064)
* Add Claude Fable 5 across Anthropic, Bedrock, Vertex AI, and Azure AI
Adds cost map entries for claude-fable-5 ($10/$50 per MTok, 1M context,
128K output, adaptive thinking only) on the Anthropic API, Bedrock
converse (base, global, and us/eu geo inference profiles at the 10%
regional premium), Vertex AI, and Azure AI (Microsoft Foundry, which
serves Fable 5 with the full 1M context window unlike Opus 4.8).
Registers anthropic.claude-fable-5 in BEDROCK_CONVERSE_MODELS, lists the
model in the setup wizard, and extends the reasoning effort e2e grid.
The Bedrock, Vertex, and Azure grid cells carry fail_reason markers
until the CI accounts are provisioned: Bedrock needs the provider data
sharing opt-in Fable 5 requires, and the Foundry resource needs a
claude-fable-5 deployment.
The first-party entry carries provider_specific_entry {us: 1.1} for the
inference_geo premium and deliberately no fast multiplier since Fable 5
has no fast mode.
https://claude.ai/code/session_01MZarYYT3aS7DxaNjoax6Gm
* Drop removed sampling params for Claude 4.7+ when drop_params is set
Fable 5, Opus 4.7, and Opus 4.8 removed sampling params: the API rejects
top_p, top_k, and any temperature other than 1 with a 400. LiteLLM was
forwarding them even with drop_params enabled because the Anthropic and
Bedrock converse transformations passed temperature/top_p through
unconditionally.
Mirror the GPT-5/o-series handling: temperature=1 still passes through,
other values and any top_p are dropped when drop_params is set, and
without drop_params a clean client-side UnsupportedParamsError tells the
caller how to opt in, instead of surfacing the raw provider error.
https://claude.ai/code/session_01MZarYYT3aS7DxaNjoax6Gm
* Drive sampling param gating from the cost map and cover top_k
Greptile review follow-ups on the sampling param fix: the restriction for
Fable 5 / Opus 4.7 / 4.8 is now declared as supports_sampling_params: false
on every affected cost map entry (perplexity excluded; that route is
OpenAI-compatible and maps sampling params upstream) and read back through
a tri-state map lookup, keeping the name check only as a fallback for
provider-routed ids whose hosted map entries predate the flag, the same
layering supports_adaptive_thinking uses. top_k bypasses map_openai_params
as a provider-specific kwarg, so it is gated at the shared
AnthropicConfig.transform_request boundary (direct, Bedrock invoke, Vertex,
Azure) and in the Bedrock converse _handle_top_k_value path, with
drop_params threaded through the converse transform helpers.
Also updates the reasoning effort grid cell count assertion for the four
Fable 5 rows added on this branch (29 x 11 cells).
https://claude.ai/code/session_01MZarYYT3aS7DxaNjoax6Gm
* Declare supports_sampling_params in the cost map schema
The model map validation schema uses additionalProperties: false, so the
new flag must be declared for the 28 entries that carry it; this was the
one failing job (misc / Run tests) on the previous commit.
https://claude.ai/code/session_01MZarYYT3aS7DxaNjoax6Gm
* fix(bedrock): gate top_k=0 on converse to match Anthropic boundary
Truthiness check let top_k=0 silently disappear on models that removed
sampling params, while AnthropicConfig.transform_request treats 0 as
present and raises UnsupportedParamsError (or drops when drop_params is
set). Switch to 'is not None' so converse, direct Anthropic, invoke,
Vertex, and Azure all behave the same for top_k=0.
---------
Co-authored-by: Cursor Agent <cursoragent@cursor.com>
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Sameer Kankute
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32c88ca74f
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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 |
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Sameer Kankute
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5fd27141cf
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Litellm OSS Staging 010626 (#29422) | ||
|
Mateo Wang
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f11c12d157
|
Revert "chore(tests): migrate Bedrock CI to AWS account 941277531214 (#28728)" (#29326)
This reverts the Bedrock CI account migration (#28728). The original account (888602223428) was put under an AWS security restriction after a leaked key and has since been reactivated, while the replacement account (941277531214) lacks access to several models the suites exercise (legacy Bedrock Claude 3 models, Cohere, Nova Canvas image gen, Bedrock batch inference, and flagship Opus). Pointing CI back at the reactivated account restores that coverage. This is the exact inverse of #28728: all hardcoded 941277531214 references go back to 888602223428 (provisioned/imported-model ARNs, AgentCore runtime ARNs and their suffixes, batch execution role ARN, and the example proxy config), the S3 buckets revert to litellm-proxy and load-testing-oct, the guardrail IDs revert to wf0hkdb5x07f and ff6ujrregl1q, the SageMaker endpoint and Knowledge Base revert to their original ids, and the live-call tests go back to the legacy model strings. The grid_spec fail_reason workaround for the unentitled Opus cells is dropped while keeping the unrelated bedrock_effort_ceiling field added after the migration. The CircleCI AWS_ACCESS_KEY_ID / AWS_SECRET_ACCESS_KEY env vars still point at 941277531214 and must be set to the reactivated account's fresh credentials separately via the CircleCI API; AWS_REGION_NAME stays us-west-2. |
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Sameer Kankute
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4cc3dd7aad
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feat(context_management): compact_20260112 polyfill for non-Anthropic providers (#28868)
* feat(anthropic/messages): in-gateway context_management polyfill for non-Anthropic providers
- Add `context_management/` module with `clear_tool_uses_20250919` editor
dispatched before chat-completions translation on `/v1/messages`
- Hard-protect most-recently completed tool_result from being cleared
- Attach `context_management.applied_edits` to both non-streaming and
streaming (final `message_delta`) responses
- Bedrock Converse: forward `context_management`; filter to
`compact_20260112`-only edits with `compact-2026-01-12` beta header
- token_counter: guard Anthropic-format tools (no `function` key) to
prevent AttributeError during polyfill token counting
- Streaming: handle empty-choices usage-only trailing chunks
- Skip polyfill when `litellm.drop_params = True`
Co-authored-by: Cursor <cursoragent@cursor.com>
* fix(bedrock): pop None context_management before sending to Bedrock Converse
If context_management is forwarded as None (e.g. when mapping returns
None for an invalid format), _filter_context_management_for_bedrock_converse
previously returned early without removing the key, leaving
"context_management": null in the request and causing a validation
error. Pop the key when the value is not a dict.
Co-authored-by: Yassin Kortam <yassin@berri.ai>
* fix(bedrock/converse): pop None context_management; extract helpers to fix PLR0915
Co-authored-by: Cursor <cursoragent@cursor.com>
* fix(anthropic/messages): check per-request drop_params alongside global
Co-authored-by: Cursor <cursoragent@cursor.com>
* fix(anthropic/messages): preserve drop_params for downstream and respect explicit False
Co-authored-by: Yassin Kortam <yassin@berri.ai>
* fix: lazy debug logging in clear_tool_uses; remove unused context_management constants
Co-authored-by: Yassin Kortam <yassin@berri.ai>
* fix(anthropic/messages): guard context_management polyfill with try/except
Wrap apply_context_management() in a try/except so any failure (e.g.
litellm.token_counter raising on an unknown tokenizer or unexpected
message format) is logged but does not crash the underlying LLM
request. The polyfill is a best-effort additive feature; on failure we
forward the original messages without applied edits.
Co-authored-by: Yassin Kortam <yassin@berri.ai>
* fix(token_counter): guard None input_schema in Anthropic tool fallback
Use `or {}` instead of `.get(..., {})` so explicit null parameters do not
raise AttributeError when formatting function definitions for token counting.
Co-authored-by: Cursor <cursoragent@cursor.com>
* fix: minimize context_management polyfill threading
- Use None (not empty list) for polyfill_applied_edits when context
management isn't requested, so semantics of 'feature not requested'
vs 'feature requested but no edits applied' are distinct.
- In the streaming iterator, only pass applied_edits to the per-chunk
translator on the final (finish_reason) chunk; intermediate chunks
ignore it anyway, and this makes intent explicit on both sync and
async paths.
Co-authored-by: Yassin Kortam <yassin@berri.ai>
* fix(context_management): align tool_use counts and normalize list spec
- _count_tool_uses now requires a string id, matching _collect_tool_use_ids_in_order so the tool_uses trigger can't fire on blocks that aren't clearable.
- apply_context_management dispatcher now accepts the OpenAI list form and normalizes it via AnthropicConfig.map_openai_context_management_to_anthropic, so the polyfill path no longer silently no-ops on list input.
Co-authored-by: Yassin Kortam <yassin@berri.ai>
* feat(context_management): add compact_20260112 polyfill for non-Anthropic providers
Implements an in-gateway compaction polyfill that summarizes long conversations
using a configurable model when `compact_20260112` is requested for non-Anthropic
targets (e.g. OpenAI, Gemini), matching Anthropic's context management beta
behaviour for those providers.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
* fix(compact): skip tool_result-only user turns; bedrock: elif for context_management
- compact_20260112 Phase D: when keeping the last user turn after a full
summary, skip role=user turns whose content is exclusively tool_result
blocks. Such turns translate to OpenAI tool-role messages with no
preceding assistant tool_calls (those got summarized away), which
non-Anthropic providers reject. Fall back to a synthetic continuation
prompt if no eligible user question exists, so the downstream call
always has a non-empty user message.
- bedrock converse: chain the context_management param as elif so it
follows the same if/elif pattern as the surrounding thinking/
reasoning_effort checks.
Co-authored-by: Yassin Kortam <yassin@berri.ai>
* fix(anthropic): post-compaction question selection, system type, sync stream merge
- compact.py: select last user question from effective_messages (post-compaction slice) instead of raw messages, so prior summarized turns aren't reintroduced
- handler.py: widen _prepare_completion_kwargs system parameter type to Union[str, List[Dict]] matching PolyfillResult.system
- streaming_iterator.py: mirror async hold-and-merge logic in sync __next__ so context_management is attached to the final merged message_delta when stop_reason and usage arrive in separate chunks
Co-authored-by: Yassin Kortam <yassin@berri.ai>
* fix(anthropic/messages): apply context_management on sync path; clear held stop_reason chunk in async iterator
- Sync `anthropic_messages_handler` was silently dropping the
`context_management` kwarg via `ANTHROPIC_ONLY_REQUEST_KEYS` after the
polyfill was moved into the async handler. Bridge to the async
dispatcher with `run_async_function` so `litellm.messages.create()`
callers keep working (regressed e.g. `clear_tool_uses_20250919`).
- In the streaming iterator's `__anext__` `StopIteration` handler, clear
`self.holding_stop_reason_chunk` after capturing it (matches `__next__`)
so a subsequent call doesn't re-emit the same chunk.
Co-authored-by: Yassin Kortam <yassin@berri.ai>
* fix(bugfixes): bedrock None context_mgmt; stream per-instance queue; sync polyfill; trailing-chunk passthrough
Co-authored-by: Yassin Kortam <yassin@berri.ai>
* fix(anthropic): silently drop trailing chunks after usage; remove dead _polyfill_result key
- streaming_iterator: in sync __next__, after the usage chunk has been
merged and emitted, silently consume any trailing provider events
via 'continue' instead of forwarding them through the queue. Trailing
chunks would translate to content_block_delta or message_delta and
violate Anthropic SSE ordering after the final message_delta. The
async __anext__ already drops these via 'if not self.queued_usage_chunk:'
gating, so this aligns sync and async behavior.
- handler: drop unused '_polyfill_result' from ANTHROPIC_ONLY_REQUEST_KEYS.
PolyfillResult is passed as an explicit arg to the adapter methods, never
through extra_kwargs, so the entry was dead code.
Co-authored-by: Yassin Kortam <yassin@berri.ai>
* refactor(anthropic): extract usage-merge helper; guard empty slice-only compaction result
- Extract the duplicated hold-and-merge usage logic from the sync __next__ and
async __anext__ paths into a shared _merge_usage_into_held_stop_reason_chunk
helper so the subtle cache-token / context_management attachment lives in
exactly one place.
- In the compact_20260112 slice-only path, fall back to _select_last_user_question
when _strip_compaction_blocks produces an empty list (e.g. messages ending on
an assistant turn whose only content was the compaction block) so the
downstream API never receives an empty messages array.
Co-authored-by: Yassin Kortam <yassin@berri.ai>
* refactor(anthropic/context_management): streaming iterator compaction fixes and compact polyfill improvements
- Extract usage-merge helper; guard empty slice-only compaction result
- Silently drop trailing chunks after usage; remove dead _polyfill_result key
- Fix bedrock None context_mgmt; stream per-instance queue; sync polyfill; trailing-chunk passthrough
- Apply context_management on sync path; clear held stop_reason chunk in async iterator
- Fix post-compaction question selection, system type, sync stream merge
- Skip tool_result-only user turns; bedrock: elif for context_management
- Add streaming iterator compaction test suite
Co-authored-by: Cursor <cursoragent@cursor.com>
* revert(html): restore flat *.html naming in _experimental/out
Reverses the accidental rename from *.html → */index.html introduced in
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||
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Sameer Kankute
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1d9095f914
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fix(bedrock): support tool search results + chat annotations (#29120)
* Fix overiding of fastapi_response headers * fix(bedrock): support tool search results and surface citations as annotations Add an optional tool-message search_results path that maps directly to Bedrock toolResult.searchResult blocks, and convert Converse citationsContent into chat completion annotations for user-facing citation metadata. Co-authored-by: Cursor <cursoragent@cursor.com> * fix(format): align bedrock prompt factory with black Reformat the updated bedrock prompt template conversion file so CI black --check passes. Co-authored-by: Cursor <cursoragent@cursor.com> * fix(bedrock): harden citations, search_results mapping, and token counting Resolve mypy issues in citation parsing, only attach url_citation annotations when citation text is stitched into content, fall back to tool content when search_results is empty, and count search_results text in token/TPM preflight paths. Co-authored-by: Cursor <cursoragent@cursor.com> * fix(bedrock): extract tool result helpers to satisfy PLR0915 Refactor _convert_to_bedrock_tool_call_result into smaller helpers so lint passes without changing Bedrock tool result behavior. Co-authored-by: Cursor <cursoragent@cursor.com> * fix(bedrock): count all forwarded search_results fields in token estimates Include source, title, content text, and citations when estimating tokens so large metadata cannot bypass TPM preflight checks. Reformat factory.py with black. Co-authored-by: Cursor <cursoragent@cursor.com> * fix(managed-files): skip content blocks without a type key in get_file_ids_from_messages * fix(bedrock): stitch citations for any punctuation-only text block * fix(bedrock): map null citation source/title to empty annotation strings * fix(bedrock): advance citation offset for text-only citationsContent blocks * fix(bedrock): complete citation TypedDicts for grounding annotations --------- Co-authored-by: Cursor <cursoragent@cursor.com> Co-authored-by: mateo-berri <277851410+mateo-berri@users.noreply.github.com> |
||
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Mateo Wang
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95015de733
|
feat: add support for claude code goal mode for bedrock opus output config (#28898)
* feat: support goal mode for claude on bedrock
* fix failing lint test
* addressing greptile comments
* fixing failed test
* address greptile: copy output_config and warn on dropped converse format
* fix(bedrock): skip redundant output_config normalization on Converse reasoning_effort path
When reasoning_effort is mapped via _handle_reasoning_effort_parameter, the
resulting output_config is already normalized via
normalize_bedrock_opus_output_config_effort. Mark it as normalized so
_prepare_request_params can skip the redundant call (and the associated
get_model_info lookup) on every request.
Co-authored-by: Yassin Kortam <yassin@berri.ai>
* test(reasoning-effort-grid): reflect Bedrock opus-4-6 xhigh→max clamping
* fix(bedrock): stop leaking output_config marker and message-content mutation
* fix(bedrock): guard effort key access in normalize_bedrock_opus_output_config_effort
Defensively check that 'effort' is a valid key in _BEDROCK_OUTPUT_CONFIG_EFFORT_ORDER
before indexing, to prevent a KeyError if the hardcoded guard tuple ever drifts from
the order dict's keys.
Co-authored-by: Yassin Kortam <yassin@berri.ai>
* fix(bedrock): drop dead second clause in effort normalization guard
The 'effort not in _BEDROCK_OUTPUT_CONFIG_EFFORT_ORDER' check is
unreachable once 'effort not in ("xhigh", "max")' has been ruled out,
since both literals are present in the order dict. Keep the literal
membership check and let the dict lookups below speak for themselves.
* fix(bedrock): clamp output_config.effort against ceiling for any known value
The early return when effort was not 'xhigh'/'max' meant a ceiling of
'low' or 'medium' would silently forward an out-of-range value. Gate on
the known effort ordering instead so the ceiling comparison runs for
every recognized effort.
* test(grid_spec): use _CAPS_OPUS_4_7 for non-Bedrock opus-4-6 entries
claude-opus-4-6 now declares supports_xhigh_reasoning_effort in the model
map, so production accepts xhigh on Azure AI and Vertex AI routes. Update
those grid_spec entries to match production capabilities so expected()
predicts 200 for xhigh instead of 400.
Co-authored-by: Yassin Kortam <yassin@berri.ai>
* test(grid_spec): revert xhigh caps for non-Bedrock opus-4-6
azure_ai/claude-opus-4-6 and vertex_ai/claude-opus-4-6 do not declare
supports_xhigh_reasoning_effort in model_prices_and_context_window.json.
Azure AI upstream rejects xhigh with HTTP 400 ("Supported levels: high,
low, max, medium"). Restore _CAPS_4_6 so the grid predicts 400 for
xhigh, matching production capabilities.
* fix: stop advertising xhigh effort on Opus 4.5/4.6
Only Opus 4.7 supports the xhigh reasoning effort level. Remove the
supports_xhigh_reasoning_effort flag from every Opus 4.5 and Opus 4.6
entry (direct Anthropic, Bedrock, and regional variants) in both model
catalog files.
On the direct Anthropic path there is no effort clamp, so flagging 4.5/4.6
as xhigh-capable caused litellm to forward xhigh to a model that rejects it
(and made get_model_info misreport the capability). xhigh now correctly
degrades to high / raises on those models.
Bedrock graceful degradation for Claude Code goal mode is unaffected: it
relies solely on the bedrock_output_config_effort_ceiling clamp (4.5->high,
4.6->max, 4.7->xhigh), which runs before validation, so xhigh requests to
older Bedrock Opus models are still silently lowered rather than rejected.
Update effort-gating tests to reflect that 4.5/4.6 no longer accept xhigh.
* fix: clamp xhigh effort on Bedrock Invoke /v1/messages instead of rejecting
Claude Code "goal mode" sends output_config.effort=xhigh over the Anthropic
/v1/messages API, which routes Bedrock models through
AmazonAnthropicClaudeMessagesConfig. That path validated effort against the
model's native capability and raised 400 for xhigh on Opus 4.6, while the
chat-completions paths (Converse + Invoke) already clamp xhigh to the model's
bedrock_output_config_effort_ceiling. That asymmetry broke goal mode on the
exact API surface Claude Code uses.
Apply the same ceiling clamp on the messages path before the shared effort
gate runs, so xhigh degrades to max on Opus 4.6 (and stays xhigh on 4.7).
Scoped to adaptive-thinking models and to models that declare a ceiling, so
Sonnet 4.6 (no ceiling) and Opus 4.5 (budget mode) are unaffected and still
reject xhigh.
* fix(bedrock): preserve user output_config when applying reasoning_effort
- Converse path: merge mapped effort into existing output_config via
setdefault instead of overwriting it, matching the Anthropic Messages
path. Prevents user-supplied output_config.format from being silently
dropped when reasoning_effort is also provided.
- tests: clear _get_local_model_cost_map lru_cache in the autouse
fixture alongside get_bedrock_response_stream_shape to avoid stale
cache leakage between tests.
Co-authored-by: Yassin Kortam <yassin@berri.ai>
* fix(bedrock): pre-clamp reasoning_effort for chat invoke; correct test caps
- Add _clamp_adaptive_reasoning_effort_for_bedrock to AmazonAnthropicClaudeConfig
so raw reasoning_effort=xhigh degrades to the model's bedrock effort ceiling
before AnthropicConfig.map_openai_params converts it to output_config.
Mirrors converse path (_handle_reasoning_effort_parameter) and messages path
(_clamp_adaptive_reasoning_effort_for_bedrock) so the three Bedrock paths
are consistent.
- grid_spec: restore caps=_CAPS_4_6 for Bedrock converse/invoke Opus 4.6 entries
so the test reflects the model's actual JSON capabilities. Teach expected()
to bypass the xhigh/max cap check when bedrock_effort_ceiling will clamp
the wire effort, so the test still passes for Bedrock's graceful degradation
contract without lying about native model caps.
Co-authored-by: Yassin Kortam <yassin@berri.ai>
---------
Co-authored-by: Dennis Henry <dennis.henry@okta.com>
Co-authored-by: Cursor Agent <cursoragent@cursor.com>
Co-authored-by: Yassin Kortam <yassin@berri.ai>
|
||
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Mateo Wang
|
f9407bc036
|
chore(tests): migrate Bedrock CI to AWS account 941277531214 (#28728)
* chore(tests): migrate Bedrock CI from AWS account 888602223428 to 941277531214
The original account (888602223428) was put under a security restriction by
AWS after a root access key leaked in a PR comment. While that account works
its way through the AWS Support unlock process, Bedrock-touching CI tests have
been migrated to a fresh account (941277531214).
Changes:
- Replace 26 hardcoded references to 888602223428 with 941277531214 across
8 files (provisioned-model ARNs, imported-model ARNs, AgentCore runtime
ARNs, batch execution role ARN, and example proxy config).
- The provisioned-model and imported-model ARNs are referenced only from
mocked unit tests — no AWS resources to recreate.
- The batch execution IAM role has been recreated in the new account with
the same name and equivalent permissions.
- The two AgentCore runtimes (hosted_agent_r9jvp-3ySZuRHjLC,
hosted_agent_13sf6-cALnp38iZD) are being recreated in the new account
under the same names — see tools/agentcore-deploy/ in a follow-up.
CircleCI env vars AWS_ACCESS_KEY_ID / AWS_SECRET_ACCESS_KEY / AWS_REGION_NAME
were updated separately via the CircleCI API to point at the new account.
Smoke-tested locally against the new account:
aws bedrock-runtime converse --region us-west-2 \
--model-id us.anthropic.claude-sonnet-4-5-20250929-v1:0 \
--messages '[{"role":"user","content":[{"text":"ping"}]}]'
→ 200, model returned 'pong'
Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
* chore(tests): refresh AgentCore ARN suffixes to match newly-deployed runtimes
The first migration commit replaced just the account ID, but AgentCore
auto-assigns a random 10-char suffix to every runtime on creation — we
can't reuse the original suffixes (`3ySZuRHjLC`, `cALnp38iZD`) in the
new account. Updated the AgentCore-runtime ARNs in the three files that
reference real runtime IDs (not the mock-based unit-test ARNs).
Deployed runtimes:
arn:aws:bedrock-agentcore:us-west-2:941277531214:runtime/hosted_agent_r9jvp-Rq79QFC2fp
arn:aws:bedrock-agentcore:us-west-2:941277531214:runtime/hosted_agent_13sf6-4046UzHSwy
Both runtimes are status=READY and pass a smoke invoke:
$ aws bedrock-agentcore invoke-agent-runtime --agent-runtime-arn ... --payload '{"prompt":"ping"}'
→ 200, {"result": "echo: ping"}
The agent is a minimal echo (see /tmp/agentcore_deploy/agent.py for the
deploy artifacts). Tests that only verify the SDK wiring will pass; if any
test asserts on agent output content, swap the echo for the real agent.
Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
* chore(tests): point Bedrock batch tests at new-account S3 bucket
The account migration (888602223428 -> 941277531214) was a flat
account-ID swap, which only rewrites ARNs that embed the account
number. S3 bucket names carry no account ID, so the live Bedrock
batch tests still uploaded to `litellm-proxy` — a bucket that lives
in the old account. S3 names are globally unique, and the old account
still holds that name, so it can't be recreated in the new account.
Rename to `litellm-proxy-941277531214` (account-ID suffix guarantees
global uniqueness). The bucket must be created in 941277531214 and the
batch execution role granted s3:GetObject/PutObject/ListBucket on it
before this job is run in CI.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
* chore(tests): point live S3 logging test at new-account bucket
Same account-ID-free blind spot as the batch bucket: `load-testing-oct`
lives in the old account and its name can't be reused globally. The
`logging_testing` CI job is wired into the workflow and runs
test_basic_s3_logging, which uploads to this bucket with the CI env
creds, then lists and deletes objects — a live dependency.
Rename to `load-testing-oct-941277531214`. The bucket must exist in the
new account with the CI IAM principal granted
s3:PutObject/GetObject/ListBucket/DeleteObject before this job runs.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
* chore(tests): repoint Bedrock guardrail IDs to new-account guardrails
The migration left guardrail IDs untouched (no account ID in them), so
all live guardrail tests failed with "guardrail identifier or version
does not exist" against 941277531214. Recreated both guardrails in the
new account and updated the hardcoded IDs:
- wf0hkdb5x07f -> zgkmukebruil (PII mask: PHONE + CREDIT_DEBIT_CARD,
with explicit inputAction=ANONYMIZE so masking applies to INPUT,
which is the source litellm's moderation hook sends)
- ff6ujrregl1q -> 4w3d1di3snt5 (blocks "coffee"; blocked message set
to the exact string the tests assert on)
Updated test_bedrock_guardrails.py, otel_test_config.yaml, and the
guardrailConfig in test_bedrock_completion.py. Verified locally: the 5
previously-failing guardrail tests now pass.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
* test(bedrock): migrate legacy models to current inference profiles
The new CI account (941277531214) cannot invoke legacy Bedrock models
(AWS gates them: "marked by provider as Legacy... not actively using in
the last 30 days"). Migrated the live-call tests:
- anthropic.claude-3-sonnet-20240229 -> us.anthropic.claude-sonnet-4-5-20250929-v1:0
- anthropic.claude-3-haiku-20240307 -> us.anthropic.claude-haiku-4-5-20251001-v1:0
Current Claude models on Bedrock require the us. inference-profile prefix
(bare on-demand ids are rejected).
cohere.command-r-plus has no working replacement (all Cohere is legacy-
gated in the new account): swapped to claude-haiku-4-5 in provider-
agnostic param lists. amazon.titan-image-generator skipped (no working
replacement). Mocked/transformation/cost tests that reference the legacy
strings are intentionally left unchanged. Verified live against the new
account.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
* test(bedrock): repoint SageMaker + Knowledge Base to new-account resources
These referenced account-scoped resources by hardcoded id that only
existed in the old account, so the migration's account-ID swap missed
them. Recreated in 941277531214 and repointed:
- SageMaker endpoint jumpstart-dft-hf-textgeneration1-mp-20240815-185614
-> litellm-ci-textgen (gpt2 on a TGI container, ml.g5.xlarge)
- Bedrock Knowledge Base T37J8R4WTM -> LCYXFBR2TU (OpenSearch Serverless
vector store + titan-embed-text-v2, seeded with a LiteLLM doc)
Verified live: test_sagemaker.py (12 passed) and
test_bedrock_knowledgebase_hook.py (12 passed).
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
* test(reasoning_effort_grid): skip bedrock claude-opus-4-7 cells (not entitled on 941277531214)
claude-opus-4-7 is listed in the new Bedrock CI account's foundation
models but invoke is denied (AccessDeniedException: "not available for
this account"). Bedrock access to the flagship Opus requires an AWS
Sales request, not the self-serve model-access toggle, so it can't be
enabled inline with the rest of the account migration.
Add an optional `skip_reason` to ModelEntry and set it on the
bedrock-claude-opus-4-7 entry; the grid test honors it via pytest.skip.
Cell count (231) and route coverage are unchanged, so the structural
asserts still pass. Restore coverage by deleting the one skip_reason
line once access is granted.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
* test(bedrock): swap/skip legacy-gated models unavailable on new CI account
The migrated AWS account (941277531214) cannot access several models that
the old account could, so the remaining red CI jobs were hitting real
Bedrock "Access denied / Legacy" and "account not authorized" errors:
- image_gen: skip both Nova Canvas test classes (amazon.nova-canvas-v1:0 is
legacy-gated), matching the existing titan skip.
- batches: skip test_async_file_and_batch (Bedrock batch inference is not
authorized on the new account; requires an AWS support case).
- litellm_overhead: swap legacy claude-3-5-haiku for the active
us.anthropic.claude-haiku-4-5 inference profile.
- test_completion_claude_3_function_call: swap legacy claude-3-sonnet for the
active us.anthropic.claude-sonnet-4-5 inference profile.
https://claude.ai/code/session_01Y7zgHYu9GX29YRwV4yiWAa
* test(bedrock): fix remaining e2e legacy-model + batch failures on new CI account
- e2e_openai_endpoints: skip test_bedrock_batches_api (Bedrock batch inference
is not authorized on account 941277531214) and migrate the missed
s3_bucket_name in oai_misc_config.yaml to litellm-proxy-941277531214.
- build_and_test: swap legacy bedrock claude-3-sonnet for the active
us.anthropic.claude-sonnet-4-5 inference profile in the proxy structured
output e2e test.
https://claude.ai/code/session_01Y7zgHYu9GX29YRwV4yiWAa
* test(bedrock): make opus-4-7 + batch cells fail loudly and mock image-gen (#28791)
Replace the silent skips added for the new CI account with noisier behavior:
- reasoning-effort grid: opus-4-7 cells now fail (when AWS creds are present)
instead of skipping, so the missing entitlement stays visible in CI; they
still skip when AWS creds are absent (local dev)
- Bedrock batch inference tests: drop the skip so they run and fail until
batch access is granted
- Titan + Nova Canvas image-gen tests: mock the Bedrock HTTP call so the
transform + cost-tracking path stays under test without live model access
https://claude.ai/code/session_01MT7SWDnXUjv6e6EPG7BDjT
Co-authored-by: Claude <noreply@anthropic.com>
* test(bedrock): use pytest.xfail for known-failing opus-4-7 cells
Replace pytest.fail with pytest.xfail when a model has a fail_reason,
so known-broken cells stay visible as XFAIL without keeping CI red.
Co-authored-by: Yassin Kortam <yassin@berri.ai>
---------
Co-authored-by: Mateo <mateo@Mateos-MacBook-Pro.local>
Co-authored-by: Claude Opus 4.7 <noreply@anthropic.com>
Co-authored-by: Cursor Agent <cursoragent@cursor.com>
Co-authored-by: Yassin Kortam <yassin@berri.ai>
|
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milan-berri
|
1b141bc588
|
fix(bedrock): decouple STS region from Bedrock aws_region_name (#28245)
* fix(bedrock): decouple STS region from Bedrock aws_region_name STS AssumeRole now resolves signing region from aws_sts_endpoint (parsed host) or AWS_REGION/AWS_DEFAULT_REGION instead of aws_region_name, fixing air-gapped cross-region Bedrock setups and endpoint/signature mismatches. Co-authored-by: Cursor <cursoragent@cursor.com> * test(bedrock): add regression coverage for _build_sts_client_kwargs Parametrize _resolve_sts_region and _build_sts_client_kwargs matrix cases, and assert IRSA/web-identity paths use aligned STS endpoint and region_name. Co-authored-by: Cursor <cursoragent@cursor.com> * refactor(bedrock): tighten STS region helpers and drop redundant web-identity endpoint synthesis Co-authored-by: Cursor <cursoragent@cursor.com> * test(bedrock): cover FIPS, GovCloud, and China STS endpoints Addresses greptile P2: regex sts(?:-fips)? supported sts-fips hosts but was not exercised by the parametrized parse test. Co-authored-by: Cursor <cursoragent@cursor.com> --------- Co-authored-by: Cursor <cursoragent@cursor.com> |
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Krrish Dholakia
|
a3c953ed4e
|
style: apply black formatting to fix lint CI (LIT-3274) (#28639) (#28641)
* fix(bedrock): strip bedrock/ prefix and URL-encode ARNs in get_bedrock_model_id for invoke path
The invoke path (used by /v1/messages → Anthropic SDK / Claude Code) called
get_bedrock_model_id() which, when falling back to the raw model string, did
not strip the 'bedrock/' routing prefix and did not URL-encode ARNs.
For a model like:
bedrock/arn:aws:bedrock:us-east-1:<ACCOUNT>:inference-profile/global.anthropic...
the URL built was:
/model/bedrock/arn:aws:bedrock:…/invoke-with-response-stream ❌
Bedrock returned a JSON error body. LiteLLM's AWSEventStreamDecoder passed
those bytes into botocore's EventStreamBuffer which expects binary event-stream
framing. Checksum validation failed on the JSON prelude (0x223a7b22 == ':{"')
producing a misleading botocore.eventstream.ChecksumMismatch instead of the
actual Bedrock error.
Fix: strip 'bedrock/' (and 'invoke/') routing prefix from model string, then
URL-encode if the result is an ARN — matching what the converse path already
does in converse_handler.py.
Fixes: LIT-3274
* fix(bedrock): use strip_bedrock_routing_prefix to handle compound prefixes
Address greptile review: the original fix used a loop with break, so
bedrock/invoke/arn:... only stripped bedrock/ leaving invoke/arn:...
which is not an ARN → fell through to .replace('invoke/','',1) →
bare unencoded ARN → same malformed-URL bug.
strip_bedrock_routing_prefix() iterates without break, correctly
stripping bedrock/ then invoke/ in sequence. Also adds test case
for the compound-prefix scenario.
* style: apply black formatting to fix lint CI (LIT-3274)
---------
Co-authored-by: oss-agent-shin <ext-agent-shin@berri.ai>
Co-authored-by: LiteLLM Bot <bot@berri.ai>
|
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Sameer Kankute
|
b7e978a5c3
|
Litellm oss staging 04 21 2026 2 (#26569)
* fix(bedrock): use model info lookup for output_config support instead of hardcoded check Replace hardcoded _is_claude_4_6_model() string matching with supports_output_config flag in model_prices_and_context_window.json, accessed via _supports_factory(). This follows the project's established pattern for model capability checks (per AGENTS.md rule #8). Bedrock Invoke now conditionally preserves output_config for models that declare supports_output_config=true (currently Claude 4.6 models), while stripping it for older models to avoid request rejection. Ref: https://github.com/BerriAI/litellm/issues/22797 * fix(vertex_ai): single-flight credential refresh to prevent thundering herd (#26024) * fix(vertex_ai): single-flight credential refresh to prevent thundering herd When GCP credentials expire under high concurrency, all requests simultaneously call credentials.refresh() via asyncify, saturating the 40-thread anyio pool and blocking the proxy for 20+ seconds. This adds: - Per-credential asyncio.Lock in get_access_token_async for single-flight refresh (1 coroutine refreshes, others wait on the lock) - Background refresh when token_state is STALE (usable but near expiry), returning the current token immediately with zero added latency - threading.Lock on the sync get_access_token path - Uses google-auth's TokenState enum (FRESH/STALE/INVALID) instead of reimplementing expiry logic Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * fix: address PR review comments - Use asyncio.create_task() instead of deprecated get_event_loop().create_task() - Track in-flight background refresh tasks to prevent duplicate refreshes when multiple STALE-path callers pass through the lock before the first background task completes - Add token validation in the STALE branch (consistent with FRESH/INVALID) Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * fix: lazy-import TokenState to avoid breaking when google-auth is not installed Also extract helper methods to bring get_access_token_async under the PLR0915 statement limit (50). Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * chore: apply Black formatting to test file and update uv.lock Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * fix: remove user-provided project_id from log messages (CodeQL log injection) Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * fix: avoid leaking token value in error message, log type instead Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * chore: restore uv.lock to match litellm_oss_branch Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * fix: remove project_id from remaining log message (CodeQL log injection) Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * fix: remove remaining project_id from log and error messages Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> --------- Co-authored-by: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * fix: reuse cached credentials in VertexAIPartnerModels (#26065) * fix: reuse cached credentials in VertexAIPartnerModels instead of creating new VertexLLM per request VertexAIPartnerModels.completion() was creating a throwaway VertexLLM() instance on every call to get an access token, bypassing the credential cache inherited from VertexBase. This caused a fresh token fetch for every single request, adding significant latency overhead. Fix: call super().__init__() to initialize VertexBase's credential cache, and use self._ensure_access_token() instead of a new VertexLLM instance. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * fix: apply same credential caching fix to VertexAIGemmaModels and VertexAIModelGardenModels Same bug as VertexAIPartnerModels: both classes had `pass` in __init__ instead of `super().__init__()`, and created throwaway VertexLLM() instances per request instead of using self._ensure_access_token(). Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> --------- Co-authored-by: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * fix(fireworks): add glm-5p1 metadata and parallel_tool_calls (#26069) * fix(chatgpt): preserve responses routing and recover empty output (#25403) (#26219) - preserve existing shared backend `mode` when router deployment registration reuses a provider/model key already in `litellm.model_cost` (prevents alias with `mode: chat` from downgrading shared `chatgpt/gpt-5.4` from `responses` to `chat` and triggering 403s on /v1/chat/completions) - teach the ChatGPT Responses parser to recover `response.output_item.done` entries when `response.completed.output` is empty - add defensive /responses -> /chat/completions bridge fallback that reconstructs output items from raw SSE when `raw_response.output` is empty - regression coverage for shared alias routing, empty completed.output parsing, and SSE bridge recovery Closes #25403 Co-authored-by: afoninsky <andrey.afoninsky@gmail.com> Co-authored-by: Claude Opus 4.7 (1M context) <noreply@anthropic.com> * fix(deps): relax core runtime dependency pins from exact == to ranges When litellm migrated from Poetry to uv (PR #24905, v1.83.1), the core dependency specifications in pyproject.toml changed from Poetry bare-version strings (e.g. openai = "2.30.0") to PEP 621 exact pins (openai==2.24.0). Poetry bare-version strings are actually caret ranges (^X.Y.Z == >=X.Y.Z,<X+1), but PEP 621 == is exact. This means every downstream package that installs litellm as a library dependency is now forced to downgrade aiohttp, pydantic, openai, click, and 8 other common packages to exact old versions. Fix: restore range specifiers for the 12 core runtime dependencies. The optional extras (proxy, proxy-runtime, etc.) are consumed primarily by Docker images where exact pins are appropriate and are left unchanged. The uv.lock file continues to provide exact reproducibility for Docker builds and CI. Fixes: #26154 * Add Rubrik as officially-supported guardrail plugin (#25305) * Add Rubrik as officially-supported guardrail plugin Adds tool blocking and batch logging integration with an external Rubrik webhook service. The plugin validates LLM tool calls against a policy service (fail-open on errors) and batch-logs all requests/responses. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * Update Rubrik docs: config.yaml as primary, env vars as fallback Restructures the Quick Start to present config.yaml as the recommended approach with tabbed UI, and environment variables as an alternative fallback. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * Add Rubrik env vars to config_settings reference Fixes documentation validation by adding RUBRIK_API_KEY, RUBRIK_BATCH_SIZE, RUBRIK_SAMPLING_RATE, and RUBRIK_WEBHOOK_URL to the environment settings reference table. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * Add fallback message when blocking service returns empty explanation Prevents whitespace-only violation message when the tool blocking service blocks tools but returns an empty content field. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> --------- Co-authored-by: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * feat(ocr): add Reducto parse OCR support (#26068) * feat(ocr): add Reducto parse OCR support * fix(reducto): address OCR review feedback * chore: refresh uv lockfile * Revert "chore: refresh uv lockfile" This reverts commit |
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harish-berri
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cff3e0b75e
|
refactor(bedrock/sagemaker): switch to lazy loading for response stre… (#28189)
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* refactor(bedrock/sagemaker): switch to lazy loading for response stream shapes
- Replace eager loading of BEDROCK_RESPONSE_STREAM_SHAPE and SAGEMAKER_RESPONSE_STREAM_SHAPE with lazy loading via get_bedrock_response_stream_shape() and get_sagemaker_response_stream_shape() respectively.
- This change optimizes performance by avoiding unnecessary imports and logging warnings unless the response stream shapes are actually needed.
- Update relevant classes and tests to utilize the new lazy loading functions, ensuring consistent behavior across the codebase.
* test(bedrock/sagemaker): add fixtures to clear response stream shape cache
- Introduced `_reset_bedrock_response_stream_shape_cache` and `_reset_sagemaker_response_stream_shape_cache` fixtures to prevent lru_cache leakage between tests in their respective modules.
- Updated tests to utilize these fixtures, ensuring that the response stream shape cache is cleared before and after each test run.
- Added `pytest.importorskip("botocore")` to ensure that tests are skipped if the botocore library is not available.
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Mateo Wang
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761ab19209
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fix(bedrock): sanitize batch metadata to prevent Pydantic ValidationError (#28202)
* fix(bedrock): sanitize batch metadata to prevent Pydantic ValidationError Proxy guardrail hooks (Model Armor, OpenAI Moderations) and internal processing inject non-string values (dicts, floats) into the request metadata. When the Bedrock batch handler passes this metadata directly to LiteLLMBatch (which inherits OpenAI's Batch Pydantic model with metadata: Dict[str, str]), Pydantic raises a ValidationError. This causes the router retry loop to re-submit the same Bedrock job multiple times before ultimately failing. Add _get_openai_compatible_batch_metadata() that serializes non-string values to JSON strings via safe_dumps, skips None values and internal logging keys, ensuring the response object always validates. * test(bedrock): add tests for batch metadata sanitization Covers _get_openai_compatible_batch_metadata: string passthrough, dict/float serialization, None/internal key exclusion, and LiteLLMBatch compatibility. --------- Co-authored-by: Noah Nistler <60981020+noahnistler@users.noreply.github.com> |
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ishaan-berri
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8c6625216b
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fix(bedrock/cohere): send embedding_types as JSON array, not string (#28172)
* fix(bedrock/cohere): wrap embedding_types as list in map_openai_params Bedrock Cohere expects embedding_types as a JSON array but encoding_format was passed through as a raw string, causing: Malformed input request: #/embedding_types: expected type: JSONArray, found: String * test(bedrock/cohere): assert embedding_types is sent as JSON array --------- Co-authored-by: Ishaan Jaffer <ishaanjaffer0324@gmail.com> |
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ishaan-berri
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f9ba70d357
|
fix(bedrock-mantle): use /anthropic/v1/messages path for Mantle endpo… (#27976)
* fix(bedrock-mantle): use /anthropic/v1/messages path for Mantle endpoint (#27943) * docs: add one-line docstring to _disable_debugging (#27894) Squash-merged by litellm-agent from oss-agent-shin's PR. * Add jp. Bedrock cross-region inference profile for claude-sonnet-4-6 (#27831) Squash-merged by litellm-agent from Cyberfilo's PR. * Sanitize empty text content blocks on /v1/messages (#27832) Squash-merged by litellm-agent from Cyberfilo's PR. * fix(bedrock-mantle): use /anthropic/v1/messages path for Mantle endpoint The bedrock-mantle gateway (Claude Mythos Preview) serves the Anthropic Messages API at /anthropic/v1/messages; /v1/messages returns 404 Not Found. Both AmazonMantleConfig (chat/completions caller route) and AmazonMantleMessagesConfig (anthropic-messages caller route) hardcoded the wrong path, so every Mantle request 404'd before reaching the model. Per the Anthropic docs: "[Claude in Amazon Bedrock] uses the Messages API at /anthropic/v1/messages with SSE streaming." https://platform.claude.com/docs/en/api/claude-on-amazon-bedrock Confirmed independently against the live endpoint: /v1/chat/completions -> 200 OK /v1/messages -> 404 Not Found (what litellm used) /anthropic/v1/messages -> 200 OK (Claude only) Adds a regression test asserting both Mantle configs build the /anthropic/v1/messages path, and updates the existing assertions that encoded the wrong path. --------- Co-authored-by: oss-agent-shin <ext-agent-shin@berri.ai> Co-authored-by: Filippo Menghi <113345637+Cyberfilo@users.noreply.github.com> * fix: sanitize empty text blocks in sync anthropic_messages_handler path Co-authored-by: Yassin Kortam <yassin@berri.ai> --------- Co-authored-by: João Costa <13508071+jpv-costa@users.noreply.github.com> Co-authored-by: oss-agent-shin <ext-agent-shin@berri.ai> Co-authored-by: Filippo Menghi <113345637+Cyberfilo@users.noreply.github.com> Co-authored-by: Cursor Agent <cursoragent@cursor.com> Co-authored-by: Yassin Kortam <yassin@berri.ai> |
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oss-agent-shin
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473cfca969
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Add Bedrock Claude Platform route (#27678)
* Add Claude Platform AWS Bedrock route Co-authored-by: ishaan-berri <ishaan-berri@users.noreply.github.com> * Use Bedrock Claude Platform route Co-authored-by: ishaan-berri <ishaan-berri@users.noreply.github.com> * Move Claude Platform route under Bedrock Co-authored-by: ishaan-berri <ishaan-berri@users.noreply.github.com> * Split Claude Platform messages config Co-authored-by: ishaan-berri <ishaan-berri@users.noreply.github.com> * Centralize Claude Platform Bedrock route Co-authored-by: ishaan-berri <ishaan-berri@users.noreply.github.com> * Address Claude Platform review feedback Co-authored-by: ishaan-berri <ishaan-berri@users.noreply.github.com> --------- Co-authored-by: oss-agent-shin <279349115+oss-agent-shin@users.noreply.github.com> Co-authored-by: ishaan-berri <ishaan-berri@users.noreply.github.com> |
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Dawei Gu
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0751886680
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feat(batch-job): bedrock batch model invocation job retrieval (#26834)
* feat(bedrock): support retrieve for model-invocation-job batch ARNs `bedrock.retrieve_batch` previously only handled `:async-invoke/` ARNs (Twelve Labs Marengo embeddings). The `:model-invocation-job/` ARNs returned by `CreateModelInvocationJob` (the bulk batch inference API behind `bedrock.create_batch`) fell through and returned a misleading data-plane error, leaving created jobs unretrievable through the LiteLLM batches API. The two ARN families live on different AWS service endpoints (`bedrock-runtime` data plane vs `bedrock` control plane), so they need distinct handlers. This adds: * `BedrockBatchesHandler._handle_model_invocation_job_status` — calls the control plane via boto3 (`bedrock:GetModelInvocationJob`), reusing `BaseAWSLLM.get_credentials` for credential resolution so model_list / env / role-assumption configs continue to apply. The response is reshaped into a `LiteLLMBatch` with the same status mapping `transform_create_batch_response` already uses. * Output-file-URI prediction. Bedrock surfaces the user-supplied `s3OutputDataConfig.s3Uri` *prefix* in `GetModelInvocationJob`, but results actually land at `<prefix>/<job-id>/<basename(input)>.out`. We compute that single-file URI client-side and surface it as `output_file_id`, so OpenAI-style `client.files.content(...)` works without an extra `ListObjectsV2` round-trip. The bare prefix stays in metadata for callers that want the manifest. * Dispatch in `litellm/batches/main.py` for the new ARN family, alongside the existing async-invoke branch. * Unit tests covering ARN parsing, output-URI prediction (incl. edge cases), the full status mapping, region resolution precedence, and failure-message propagation. Note: `request_counts` is intentionally `(0, 0, 0)` — `GetModelInvocationJob` does not report per-record counts; getting accurate numbers requires parsing `manifest.json.out` from the output S3 prefix, which is left to callers. Made-with: Cursor * fix(bedrock): address PR feedback on model-invocation-job retrieve Addresses Greptile P2 findings on #26834: 1. Use the bare job id (not the full ARN) when constructing the `api_base` URL for `pre_call` logging. Passing the full ARN double- counts the `model-invocation-job/` segment and embeds colons in the path, producing misleading log lines. 2. Drop the `or output_prefix` fallback when `_predict_output_file_uri` returns None. A bare prefix is not a downloadable object and surfacing it as `output_file_id` re-creates the very NoSuchKey bug this handler exists to fix. The bare prefix is still preserved in `metadata["output_s3_uri"]` for callers that want to do their own S3 listing or read `manifest.json.out`. `metadata["output_file_uri"]` uses "" rather than None to satisfy the OpenAI Batch metadata schema (`dict[str, str]`); callers should branch on the typed `output_file_id` field instead. Also expands test coverage on the new code path: - new "stay None" regression test for the prediction-fail case - pre_call/post_call logging hook assertions (incl. the bare-id URL) - explicit cancelled_at / expired_at coverage - _to_epoch type-handling matrix and the boto3 ImportError branch - defensive _extract_region_from_bedrock_arn exception path - empty-basename case for _predict_output_file_uri Patch coverage on the changed lines is now 100% (the only remaining uncovered lines in the file belong to the pre-existing `_handle_async_invoke_status` method, which this PR does not touch). Made-with: Cursor * test(bedrock): cover retrieve_batch dispatch for both ARN families Codecov flagged 8 uncovered lines on `litellm/batches/main.py` after this PR refactored the Bedrock dispatch into a single guard with two sub-branches (`async-invoke` + `model-invocation-job`). Existing tests exercised the handlers directly but not the dispatch in `main.py`. Adds `tests/test_litellm/batches/test_retrieve_batch_bedrock_dispatch.py` with 6 mocked tests that exercise `litellm.retrieve_batch` end-to-end for the dispatch logic: - async-invoke ARN routes to `_handle_async_invoke_status` - async-invoke ARN with no region falls back to "us-east-1" (preserves prior behavior on this branch) - model-invocation-job ARN routes to the new `_handle_model_invocation_job_status` handler - model-invocation-job ARN with no region forwards None (so the new handler can sniff region from the ARN itself, rather than getting silently routed to us-east-1) - unrelated bedrock ARN family falls through to the generic provider-config retrieve path (neither special handler invoked) - non-bedrock batch ids skip the bedrock dispatch entirely Both handlers are mocked at the import site so the tests don't hit AWS — the focus here is purely the new dispatch logic in main.py. Co-authored-by: Cursor <cursoragent@cursor.com> * test(bedrock): move retrieve_batch dispatch test to tests/test_litellm/ The dispatch test landed under `tests/test_litellm/batches/`, a new directory that no upstream `test-unit-*.yml` workflow's `test-path` allow-list includes. As a result, the test was never executed in CI and codecov reported `litellm/batches/main.py` patch coverage at 11.11% (8 lines uncovered) — the lines belonging to this PR's dispatch refactor itself. Move the file up one level so it matches the `tests/test_litellm/test_*.py` glob that `test-unit-misc.yml` already runs, and adjust `sys.path.insert` for the new depth. The companion handler tests under `tests/test_litellm/llms/bedrock/batches/test_handler.py` are unaffected — they're picked up by the `llms` directory in `test-unit-llm-providers.yml`. Made-with: Cursor --------- Co-authored-by: Cursor <cursoragent@cursor.com> |
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Tai An
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f8b078b749
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fix(bedrock/messages): preserve compact_20260112 context_management on /v1/messages (#27534)
Squash-merged by litellm-agent from Anai-Guo's PR. |
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harish-berri
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a67b7a7e87
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Refactor Bedrock response stream shape handling (#27257)
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* Refactor Bedrock response stream shape handling - Introduced a module-level constant `BEDROCK_RESPONSE_STREAM_SHAPE` to cache the response stream shape, eliminating the need for per-instance caching in `BedrockEventStreamDecoderBase`. - Updated relevant methods to utilize the new constant, improving performance by avoiding redundant loading of the shape. - Added tests to ensure the shape is loaded correctly at import time and is consistent across different modules. - Added a new mock server script for testing Bedrock pass-through functionality. * Refactor response parsing for Bedrock and SageMaker - Improved code readability by formatting the parsing method calls in `AWSEventStreamDecoder` for both Bedrock and SageMaker response stream shapes. - Added blank lines for better separation of code blocks in `invoke_handler.py` and `common_utils.py` to enhance maintainability. * Enhance error handling for Bedrock and SageMaker response stream shape loading - Wrapped the loading logic in `_load_bedrock_response_stream_shape` and `_load_sagemaker_response_stream_shape` with try-except blocks to gracefully handle exceptions. - Added logging to warn when the response stream shape cannot be pre-loaded, ensuring the module imports cleanly. - Updated tests to verify that loading failures return `None` instead of propagating exceptions. * Implement error handling for missing response stream shapes in Bedrock and SageMaker - Added checks in `_parse_message_from_event` methods to raise appropriate errors when `BEDROCK_RESPONSE_STREAM_SHAPE` or `SAGEMAKER_RESPONSE_STREAM_SHAPE` is None, ensuring clearer error reporting. - Updated logging messages to reflect the unavailability of event-stream decoding for both Bedrock and SageMaker. - Enhanced unit tests to verify that the correct exceptions are raised when the response stream shapes are not loaded. |
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harish-berri
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4fec69dd1e
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refactor(BaseAWSLLM): implement shared IAM cache and static credentia… (#27125)
* refactor(BaseAWSLLM): implement shared IAM cache and static credential caching - Introduced a process-wide shared IAM cache to optimize credential management across instances. - Added a method to handle caching of static credentials, ensuring only long-lived credentials are cached. - Updated the get_credentials method to utilize the new caching mechanism for static credential flows. - Enhanced unit tests to verify the correct behavior of the shared cache and static credential usage. * refactor(BaseAWSLLM): enhance IAM credential caching and update related tests - Improved the process-wide IAM credential caching mechanism to better handle static and AssumeRole credentials. - Renamed the caching method for clarity and updated comments to reflect the new caching behavior. - Added a fixture to ensure the IAM cache is flushed between tests to prevent leakage of cached entries. - Updated unit tests to verify the correct behavior of the shared IAM cache, particularly for static credentials and role assumptions. * refactor(BaseAWSLLM): clarify IAM credential caching behavior and enhance tests - Updated documentation to specify that only static and ambient environment credentials are cached, excluding AssumeRole and other credential types. - Modified the caching logic to ensure that AssumeRole credentials are not stored in the IAM cache, requiring STS calls for each request. - Enhanced unit tests to verify that AssumeRole credentials are not cached and to ensure proper behavior of the IAM cache across different scenarios. * Code Readability improvement for aws auth path * refactor(BaseAWSLLM): enhance IAM credential caching documentation and add tests - Updated comments to clarify the behavior of the in-process IAM credential cache, specifying the TTL for static and ambient credentials. - Added new unit tests to verify the caching behavior for ambient environment credentials across instances and ensure that static access key sessions are constructed only once when cached. - Ensured that temporary session tokens and AWS profiles are not cached, validating the expected behavior through additional tests. * refactor(BaseAWSLLM): improve IAM credential handling and add tests for role assumption - Updated comments to clarify the behavior of IAM credential caching, particularly regarding the handling of ambient credentials and role assumptions. - Enhanced unit tests to verify that the caching mechanism correctly distinguishes between already running roles and new role assumptions, ensuring that cached environment credentials are not reused incorrectly. - Added a new test case to validate the behavior when switching roles, confirming that the system correctly uses AssumeRole when the role changes. |
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yuneng-jiang
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07807f760f
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Merge pull request #27019 from stuxf/codex/cloud-storage-file-guard
fix(files): constrain cloud storage file paths (VERIA-45, VERIA-59) |
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Cursor Agent
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2cb3f0f027
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refactor: remove unnecessary comments from #27074
Strip out the explanatory and historical comments that don't carry business-logic justification. Comments that simply narrate what code does — or that explain prior behavior, what was changed, or which PR introduced a fix — are removed. Docstrings are reduced to a one-line summary where the long form repeated information already evident from the code or test data. No code-behavior changes. All 643 affected unit tests still pass. Co-authored-by: Mateo Wang <mateo-berri@users.noreply.github.com> |
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user
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7c94149aeb |
Merge remote-tracking branch 'origin/litellm_internal_staging' into codex/cloud-storage-file-guard
# Conflicts: # litellm/llms/vertex_ai/files/handler.py # litellm/llms/vertex_ai/files/transformation.py |
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mateo-berri
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108b87fb24 |
fix(anthropic,bedrock,databricks): four reasoning_effort follow-ups
- claude-sonnet-4-6 + reasoning_effort=max no longer 400s. Renamed _is_opus_4_6_model to _is_claude_4_6_model at three sites and added supports_max_reasoning_effort: true to 12 model entries in the JSON cost map (10 sonnet 4.6 ids + OpenRouter opus 4.6/4.7). - _map_reasoning_effort now raises BadRequestError(400) directly with llm_provider, instead of letting Databricks (and similar callers) surface its raw ValueError as a 500. - output_config.effort on Opus 4.5 over Bedrock no longer 400s for missing effort-2025-11-24 beta. Flipped JSON to "effort-2025-11-24" for bedrock + bedrock_converse and added an auto-attach branch in _process_tools_and_beta for non-adaptive Anthropic + output_config on Converse. - reasoning_effort=xhigh / =max on legacy budget-mode models (Haiku 4.5, Sonnet 4.5, Opus 4.5) now map to thinking.budget_tokens 8192 / 16384 instead of returning 400. Added two constants in litellm/constants.py. Tests updated for all four flips. Validated end-to-end via 306-cell live proxy matrix (6 model families x 3 routes x 17 effort cases), all pass. |
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Claude
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09d37db8d9 |
feat(anthropic,bedrock): strip output_config under drop_params for non-effort models
When a proxy fronts Claude Code (which always sends `output_config.effort`)
at a pre-4.5 Anthropic model — haiku-3, sonnet-3.5, opus-3, sonnet-4 — the
forwarded knob causes a forced 400 the client can't fix. Gating a strip
behind the existing `drop_params` flag lets operators opt into silent
fixup once and stop worrying about per-model param hygiene.
Default (`drop_params=False`) still forwards and surfaces the provider's
error, preserving the strict, debuggable contract from #27074.
Per https://platform.claude.com/docs/en/build-with-claude/effort the
supporting set is Opus 4.5+, Sonnet 4.6+, and Mythos Preview; everything
else is dropped (with a verbose_logger warning so the strip is visible).
Recognition uses model-name patterns plus a fallback to any
`supports_*_reasoning_effort` flag in the model map for forward
compatibility with new entries.
https://claude.ai/code/session_01WjHq31rvXT6xYNdVmSJvRp
(cherry picked from commit
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Claude
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e400de4654 |
fix(anthropic): translate reasoning_effort on /v1/messages route
Closes the remaining QA-sweep gap on PR #27074: Bedrock Invoke /v1/messages was silently ignoring ``reasoning_effort`` because the shared param filter only kept native Anthropic keys, so every effort tier collapsed to the same behavior on the wire (27/231 cells failing across opus-4-5 / opus-4-6 / sonnet-4-6). Map ``reasoning_effort`` to native Anthropic ``thinking`` / ``output_config.effort`` at the ``AnthropicMessagesConfig`` layer so all four /v1/messages routes (direct Anthropic, Azure AI, Vertex AI, Bedrock Invoke) inherit the same translation: - Add ``reasoning_effort`` to ``AnthropicMessagesRequestOptionalParams`` so the param filter in ``AnthropicMessagesRequestUtils.get_requested_anthropic_messages_optional_param`` no longer drops it before the transformation runs. - Add ``_translate_reasoning_effort_to_anthropic`` and call it from ``transform_anthropic_messages_request``. Mirrors ``AnthropicConfig.map_openai_params`` on the chat completion path (re-uses ``_map_reasoning_effort`` and ``REASONING_EFFORT_TO_OUTPUT_CONFIG_EFFORT``) so the two routes cannot drift. Pops ``reasoning_effort`` so it never reaches the wire. - Caller-supplied native ``thinking`` / ``output_config.effort`` always win — same precedence as ``_translate_legacy_thinking_for_adaptive_model``. - Garbage values (``""``, ``"disabled"``, ``"invalid"``) raise ``AnthropicError(status_code=400)`` instead of falling through and surfacing as 500s from the provider. - ``"none"`` clears thinking + output_config so callers can opt out per request. Also restores the non-adaptive-model test coverage on Bedrock Invoke /v1/messages that the previous commit lost when ``test_bedrock_messages_strips_output_config`` was renamed to the ``forwards`` variant on Opus 4.7. Adds a new test file ``test_reasoning_effort_translation.py`` covering the translation at the shared config level (adaptive + non-adaptive models, none, garbage, caller precedence) so all four /v1/messages routes are exercised by a single suite. Adds parametrized + behavioral tests on the Bedrock Invoke /v1/messages suite covering: minimal/low/medium/high/xhigh/max mapping for adaptive models, thinking-budget mapping for non-adaptive Opus 4.5, ``none`` clears both, garbage raises 400, explicit ``output_config`` wins. Refs: https://github.com/BerriAI/litellm/pull/27074 |
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Cursor Agent
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a6c673e7b9 |
fix(anthropic,bedrock,vertex): forward output_config.effort + 400 on garbage reasoning_effort
Follow-up bugs surfaced by the QA sweep on PR #27039 (https://github.com/BerriAI/litellm/pull/27039#issuecomment-4363363610). 1. Stop stripping output_config.effort on Bedrock + Vertex adaptive routes. - Vertex AI Claude 4.6/4.7 accepts output_config.effort on rawPredict (verified end-to-end against us-east5 / global). The strip helper now no-ops for effort. - Bedrock Converse routes output_config into additionalModelRequestFields for anthropic base models so the requested adaptive tier (low/medium/ high/xhigh/max) actually reaches the wire instead of all collapsing to identical thinking. - Bedrock Invoke chat transformation (AmazonAnthropicClaudeConfig) stops popping output_config from the post-AnthropicConfig request body. - Bedrock Invoke /v1/messages allowlist (BedrockInvokeAnthropicMessagesRequest) now lists output_config so the runtime allowlist filter forwards it. 2. Validate effort across Bedrock Converse so 'disabled' / 'invalid' / '' / unsupported tiers (xhigh/max on Sonnet 4.6 or budget-mode 4.5 models) surface as a clean 400 BadRequestError instead of 500. 3. ValueError -> BadRequestError throughout (AnthropicConfig.map_openai_params, _apply_output_config, AmazonConverseConfig._handle_reasoning_effort_parameter). Empty-string effort is now rejected (was silently passing the 'if effort and ...' short-circuit). 4. Floor reasoning_effort='minimal' at the Anthropic provider minimum (1024 budget_tokens) via new ANTHROPIC_MIN_THINKING_BUDGET_TOKENS so it's a usable tier on direct Anthropic / Azure AI Anthropic / Vertex AI Anthropic / Bedrock Invoke (all of which 400 below 1024). 5. model_prices: dedupe duplicate supports_max_reasoning_effort key on claude-opus-4-7 / claude-opus-4-7-20260416. Adds regression tests across all five affected paths; existing tests asserting the silent-strip behavior were updated to reflect the new pass-through and clean 400 surfaces. Co-authored-by: Mateo Wang <mateo-berri@users.noreply.github.com> |
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mateo-berri
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7f3d7616b7
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Merge remote-tracking branch 'origin/litellm_internal_staging' into litellm_fix_reasoning_effort_none_anthropic
Co-authored-by: Mateo Wang <mateo-berri@users.noreply.github.com> |
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mateo-berri
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3835306c83 |
fix(anthropic,bedrock): omit thinking/output_config when reasoning_effort="none"
Setting reasoning_effort="none" on Anthropic chat models (direct, Bedrock
Invoke, Bedrock Converse, Vertex AI Anthropic, Azure AI Anthropic) crashed
LiteLLM with:
litellm.APIConnectionError: 'NoneType' object has no attribute 'get'
Both the Anthropic chat transformation and Bedrock Converse called
``AnthropicConfig._map_reasoning_effort`` and assigned the ``None`` it returns
for ``"none"`` directly to ``optional_params["thinking"]``. Downstream
``is_thinking_enabled`` then did ``optional_params["thinking"].get("type")``
and crashed.
Pop ``thinking`` (and on Claude 4.6/4.7, ``output_config``) instead of
assigning ``None``, restoring the documented contract that
``reasoning_effort="none"`` means "do not enable thinking". This also
prevents downstream Anthropic 400s ("thinking: Input should be an object",
"output_config.effort: Input should be ...") if the bug were ever masked.
Verified end-to-end against the live Anthropic API and Bedrock Converse
on claude-opus-4-{5,6,7} and claude-sonnet-4-6, plus Bedrock Invoke for
Claude 4.5/4.6. Vertex AI Anthropic and Azure AI Anthropic inherit the
fixed ``map_openai_params`` from ``AnthropicConfig`` and need no further
changes.
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user
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e7c23fc041 | harden cloud file compatibility path | ||
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user
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2776e0162c | harden cloud file compatibility path | ||
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user
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f53e8d6803 | harden bedrock file bucket validation | ||
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user
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ba1188117d | fix cloud storage file guards | ||
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yuneng-jiang
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3583ac1159
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Merge pull request #26860 from stuxf/fix/provider-path-traversal
chore(security): encode upstream URL path identifiers |
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Yassin Kortam
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d47948ab23 | fix: validate aws region name | ||
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user
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94c13fe399 | fix: cover provider path traversal variants | ||
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user
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d4dd865b1a | fix: encode upstream URL path identifiers | ||
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Cursor Agent
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1b6ab9facf
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Merge branch 'litellm_internal_staging' into litellm_oss_staging
Resolves merge conflict in tests/test_litellm/llms/bedrock/chat/test_converse_transformation.py by keeping both the new bedrock tool-result file/document tests and the transform_response body-leak regression test. Also addresses Greptile P2 comment: when BedrockImageProcessor returns a block with neither 'image' nor 'document' keys on the tool-result path (image_url and file content types), log a warning instead of silently dropping the block. Co-authored-by: Mateo Wang <mateo-berri@users.noreply.github.com> |
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Michael-RZ-Berri
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08d35f6b42
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Merge pull request #26662 from BerriAI/litellm_spendLogsErrorRedaction
[Fix] Redact spend logs error message |
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Sameer Kankute
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d8d1444da4
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Merge pull request #26710 from minznerjosh/fix/bedrock-anthropic-tool-result-pdf-content
fix(bedrock, anthropic): translate OpenAI file content on tool-result path |
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Sameer Kankute
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b516120036
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Merge pull request #26737 from BerriAI/litellm_internal_staging
merge internal staging |
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Sameer Kankute
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cf74f55b79
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Fix extra body error | ||
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Michael Riad Zaky
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b07e1c0341 |
drop response body from vertex/bedrock transformation errors
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Ryan Crabbe
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dc46467235
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fix(tests): replace deprecated Bedrock Claude 3.7 Sonnet model ID
AWS Bedrock has reached end-of-life for `claude-3-7-sonnet-20250219-v1:0`, returning 404s with "This model version has reached the end of its life." Update test references to `claude-sonnet-4-5-20250929-v1:0` (same capability surface: thinking, tools, prompt caching, PDF input, vision, computer use). The bedrock/invoke pass-through tests stay on Sonnet 3.5 since Sonnet 4.5 is converse-only on Bedrock. |
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Josh Minzner
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12e1d02d4e |
address Greptile review feedback on tool-result PDF fix
- Tighten _is_anthropic_document_data_uri to match the mimes Anthropic
actually accepts as base64 `document` source ({application/pdf,
text/plain}). The previous application/* + text/* prefix match would
route e.g. data:application/json URIs through the document path,
producing blocks the Anthropic API rejects. Unsupported mimes now
stay on the existing image code path (same failure mode as before the
fix — no regression, just stops introducing a new one).
- On the Bedrock tool-result `type: "file"` branch, accept either
file_data or file_id and raise BadRequestError on both-None, mirroring
the user-message _process_file_message pattern. Previously a file
block with only file_id was silently dropped.
- Consolidate the six new PDF tool-result tests under tests/test_litellm/
only (the PR template's required location and where the unit-test CI
workflow runs with coverage). The duplicate copies under
tests/llm_translation/ added drift risk with no additional coverage.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
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Josh Minzner
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5b5363cd54 |
test: mirror PDF tool-result tests under tests/test_litellm
Duplicate the three Bedrock and three Anthropic tool-result tests into tests/test_litellm/ so they're picked up by `make test-unit` (and its coverage report). The originals in tests/llm_translation/ stay — they run under integration and remain the canonical translation-suite regression cases. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com> |
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Sameer Kankute
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6b86e544e8
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Fix greptile reviews | ||
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Sameer Kankute
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cfe4bc678e
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feat(vector-stores): support provider-specific Bedrock retrieval config
Route vector store search `extra_body` into provider transformers and handle Bedrock `retrievalConfiguration` explicitly so only intended provider-specific fields are forwarded. Made-with: Cursor |
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shubham-arora-clear
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5ccb385a86
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fix(bedrock): preserve cache_control TTL on tools for Claude 4.5+ (#25855)
Bedrock enforces non-increasing TTL ordering across cache_control blocks (tools → system → messages). The tool cache_control TTL was being unconditionally dropped to the default 5m, while system blocks preserved the user-specified TTL for Claude 4.5+ models. This mismatch caused "a ttl='1h' block must not come after a ttl='5m' block" errors when users set ttl='1h' on both tools and system. Converse path: add_cache_point_tool_block() now accepts a model param and preserves TTL for Claude 4.5+, matching _get_cache_point_block(). Invoke path: _remove_ttl_from_cache_control() now also processes tools (was only processing system and messages). Co-authored-by: Claude Opus 4.6 (1M context) <noreply@anthropic.com> |