fix: merge annotations from all streaming chunks in stream_chunk_builder#23663
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RheagalFire merged 11 commits intoBerriAI:litellm_oss_staging_03_14_2026from Mar 15, 2026
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) Fixes BerriAI#23502 The huggingface_embed.embedding() call was not receiving the headers parameter, causing extra_headers (e.g., X-HF-Bill-To) to be silently dropped. Other providers (openrouter, vercel_ai_gateway, bedrock) already pass headers correctly. This fix adds headers=headers to match the behavior of other providers. Co-authored-by: Jah-yee <sparklab@outlook.com>
…fix z-index issue (BerriAI#23516) The model dropdown menus in the Add Fallbacks modal were rendering behind the modal overlay because Ant Design portals Select dropdowns to document.body by default. By setting getPopupContainer to attach the dropdown to its parent element, the dropdown inherits the modal's stacking context and renders above the modal. Fixes BerriAI#17895
…nd Azur… (BerriAI#23183) * PR BerriAI#22867 added _remove_scope_from_cache_control for Bedrock and Azure AI but omitted Vertex AI. This applies the same pattern to VertexAIPartnerModelsAnthropicMessagesConfig." * PR BerriAI#22867 added _remove_scope_from_cache_control for Bedrock and Azure AI but omitted Vertex AI. This applies the same pattern to VertexAIPartnerModelsAnthropicMessagesConfig." * PR BerriAI#22867 added _remove_scope_from_cache_control to AzureAnthropicMessagesConfig but missed VertexAIPartnerModelsAnthropicMessagesConfi Rather than duplicating the method again, moved it up to the base AnthropicMessagesConfig so all providers inherit it, and removed the now-redundant copy from the Azure AI subclass. * PR BerriAI#22867 added _remove_scope_from_cache_control to AzureAnthropicMessagesConfig but missed VertexAIPartnerModelsAnthropicMessagesConfi Rather than duplicating the method again, moved it up to the base AnthropicMessagesConfig so all providers inherit it, and removed the now-redundant copy from the Azure AI subclass. --------- Co-authored-by: Krish Dholakia <krrishdholakia@gmail.com>
…n multi-turn tool calling (BerriAI#23580)
…erriAI#23492) * Handle response.failed, response.incomplete, and response.cancelled terminal events in background streaming Previously the background streaming task only handled response.completed and hardcoded the final status to "completed". This missed three other terminal event types from the OpenAI streaming spec, causing failed/incomplete/cancelled responses to be incorrectly marked as completed. Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com> Committed-By-Agent: claude * Remove unused terminal_response_data variable Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com> Committed-By-Agent: claude * Address code review: derive fallback status from event type, rewrite tests as integration tests 1. Replace hardcoded "completed" fallback in response_data.get("status") with _event_to_status lookup so that response.incomplete and response.cancelled events get the correct fallback if the response body ever omits the status field. 2. Replace duplicated-logic unit tests with integration tests that exercise background_streaming_task directly using mocked streaming responses and assert on the final update_state call arguments. Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com> Committed-By-Agent: claude * Remove dead mock_processor and unused mock_response parameter from test helper Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com> Committed-By-Agent: claude * Remove FastAPI and UserAPIKeyAuth imports from test file These types were only used as Mock(spec=...) arguments. Drop the spec constraints and remove the top-level imports to avoid pulling FastAPI into test files outside litellm/proxy/. Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com> Committed-By-Agent: claude * Log warning when streaming response has no body_iterator If base_process_llm_request returns a non-streaming response (no body_iterator), log a warning since this likely indicates a misconfiguration or provider error rather than a successful completion. Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com> Committed-By-Agent: claude --------- Co-authored-by: Claude Opus 4.6 <noreply@anthropic.com>
* fix(security): bump tar to 7.5.11 and tornado to 6.5.5 - tar >=7.5.11: fixes CVE-2026-31802 (HIGH) in node-pkg - tornado >=6.5.5: fixes CVE-2026-31958 (HIGH) and GHSA-78cv-mqj4-43f7 (MEDIUM) in python-pkg Addresses vulnerabilities found in ghcr.io/berriai/litellm:main-v1.82.0-stable Trivy scan. Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com> * fix: document tar override is enforced via Dockerfile, not npm * fix: revert invalid JSON comment in package.json tar override --------- Co-authored-by: Claude Sonnet 4.6 <noreply@anthropic.com>
* fix(bedrock): respect s3_region_name for batch file uploads (BerriAI#23569) * fix(bedrock): respect s3_region_name for batch file uploads (GovCloud fix) * fix: s3_region_name always wins over aws_region_name for S3 signing (Greptile feedback) * fix: _filter_headers_for_aws_signature - Bedrock KB (BerriAI#23571) * fix: _filter_headers_for_aws_signature * fix: filter None header values in all post-signing re-merge paths Addresses Greptile feedback: None-valued headers were being filtered during SigV4 signing but re-merged back into the final headers dict afterward, which would cause downstream HTTP client failures. Made-with: Cursor * feat(router): tag_regex routing — route by User-Agent regex without per-developer tag config (BerriAI#23594) * feat(router): add tag_regex support for header-based routing Adds a new `tag_regex` field to litellm_params that lets operators route requests based on regex patterns matched against request headers — primarily User-Agent — without requiring per-developer tag configuration. Use case: route all Claude Code traffic (User-Agent: claude-code/x.y.z) to a dedicated deployment by setting: tag_regex: - "^User-Agent: claude-code\\/" in the deployment's litellm_params. Works alongside existing `tags` routing; exact tag match takes precedence over regex match. Unmatched requests fall through to deployments tagged `default`. The matched deployment, pattern, and user_agent are recorded in `metadata["tag_routing"]` so they flow through to SpendLogs automatically. * fix(tag_regex): address backwards-compat, metadata overwrite, and warning noise Three issues from code review: 1. Backwards-compat: `has_tag_filter` was widened to activate on any non-empty User-Agent, which would raise ValueError for existing deployments using plain tags without a `default` fallback. Fix: only activate header-based regex filtering when at least one candidate deployment has `tag_regex` configured. 2. Metadata overwrite: `metadata["tag_routing"]` was overwritten for every matching deployment in the loop, leaving inaccurate provenance when multiple deployments match. Fix: write only for the first match. 3. Warning noise: an invalid regex pattern logged one warning per header string rather than once per pattern. Fix: compile first (catching re.error once), then iterate over header strings. Also adds two new tests covering these cases, and adds docs page for tag_regex routing with a Claude Code walk-through. * refactor(tag_regex): remove unnecessary _healthy_list copy * docs: merge tag_regex section into tag_routing.md, remove standalone page - Add ## Regex-based tag routing (tag_regex) section to existing tag_routing.md instead of a separate page - Remove tag_regex_routing.md standalone doc (odd UX to have a separate page for a sub-feature) - Remove proxy/tag_regex_routing from sidebars.js - Add match_any=False debug warning in tag_based_routing.py when regex routing fires under strict mode (regex always uses OR semantics) * fix(tag_regex): address greptile review - security docs, strict-mode enforcement, validation order - Strengthen security note in tag_routing.md: explicitly state User-Agent is client-supplied and can be set to any value; frame tag_regex as a traffic classification hint, not an access-control mechanism - Move tag_regex startup validation before _add_deployment() so an invalid pattern never leaves partial router state - Enforce match_any=False strict-tag policy: when a deployment has both tags and tag_regex and the strict tag check fails, skip the regex fallback rather than silently bypassing the operator's intent - Extract per-deployment match logic into _match_deployment() helper to keep get_deployments_for_tag() readable - Add two new tests: strict-mode blocks regex fallback, regex-only deployment still matches under match_any=False * fix(ci): apply Black formatting to 14 files and stabilize flaky caplog tests - Run Black formatter on 14 files that were failing the lint check - Replace caplog-based assertions in TestAliasConflicts with unittest.mock.patch on verbose_logger.warning for xdist compatibility - The caplog fixture can produce empty text in pytest-xdist workers in certain CI environments, causing flaky test failures Co-authored-by: Ishaan Jaff <ishaan-jaff@users.noreply.github.com> --------- Co-authored-by: Cursor Agent <cursoragent@cursor.com> Co-authored-by: Ishaan Jaff <ishaan-jaff@users.noreply.github.com>
* fix: restore offline tiktoken cache for non-root envs Made-with: Cursor * chore: mkdir for custom tiktoken cache dir Made-with: Cursor * test: patch tiktoken.get_encoding in custom-dir test to avoid network Made-with: Cursor * test: clear CUSTOM_TIKTOKEN_CACHE_DIR in helper for test isolation Made-with: Cursor * test: restore default_encoding module state after custom-dir test Made-with: Cursor
Map provider finish_reason "content_filtered" to the OpenAI-compatible "content_filter" and extend core_helpers tests to cover this case. Made-with: Cursor
Previously, stream_chunk_builder only took annotations from the first chunk that contained them, losing any annotations from later chunks. This is a problem because providers like Gemini/Vertex AI send grounding metadata (converted to annotations) in the final streaming chunk, while other providers may spread annotations across multiple chunks. Changes: - Collect and merge annotations from ALL annotation-bearing chunks instead of only using the first one
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Contributor
Greptile SummaryThis PR fixes a bug in Key changes:
Confidence Score: 5/5
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| Filename | Overview |
|---|---|
| litellm/main.py | Fixes stream_chunk_builder to merge annotations from all streaming chunks instead of only the first — minimal, targeted, and correct change. |
| tests/test_litellm/test_stream_chunk_builder_annotations.py | New test file with three pure unit tests (no network calls): multi-chunk merge, single-chunk regression, and no-annotation regression — all compliant with the mock-only rule for this directory. |
Flowchart
%%{init: {'theme': 'neutral'}}%%
flowchart TD
A[stream_chunk_builder called with chunks] --> B[Filter annotation_chunks\nchunks where delta.annotations is not None]
B --> C{len annotation_chunks > 0?}
C -- No --> D[Skip annotation assignment]
C -- Yes --> E["all_annotations = []"]
E --> F[For each ac in annotation_chunks]
F --> G["all_annotations.extend(\n ac[choices][0][delta][annotations]\n)"]
G --> F
F -- done --> H["response[choices][0][message][annotations]\n= all_annotations"]
H --> I[Continue with audio/image chunks...]
Last reviewed commit: e38bbec
RheagalFire
approved these changes
Mar 15, 2026
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BerriAI:litellm_oss_staging_03_14_2026
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Relevant issues
Fixes
stream_chunk_builderlosing annotations from all but the first annotation-bearing streaming chunk.Pre-Submission checklist
tests/test_litellm/directory, Adding at least 1 test is a hard requirementmake test-unitType
Bug Fix
Changes
Problem
In
litellm/main.py,stream_chunk_builder()collects all streaming chunks that contain annotations, but then only uses annotations from the first chunk:This means if annotations arrive across multiple streaming chunks (e.g. Gemini sends grounding metadata in the final chunk while other providers may include citations in intermediate chunks), all but the first set of annotations are silently lost.
Fix
Merge annotations from ALL annotation-bearing chunks by extending a list:
Tests added
tests/test_litellm/test_stream_chunk_builder_annotations.py:test_stream_chunk_builder_merges_annotations_from_multiple_chunks— verifies annotations from chunk 1 and chunk 3 are both present in the assembled responsetest_stream_chunk_builder_single_annotation_chunk_still_works— verifies existing single-chunk behavior (no regression)test_stream_chunk_builder_no_annotations— verifies no annotations attribute when none are present (no regression)