The Gemini batch embedding transformation was spreading all
optional_params into the request body via **gemini_params. Params
like max_tokens (injected by add_provider_specific_params_to_optional_params)
would reach the Gemini API and cause a 400 BadRequestError.
Extract _filter_embed_params() that maps dimensions/task_type and
keeps only the fields Gemini embeddings actually accept
(outputDimensionality, taskType, title). Applied to both
transform_openai_input_gemini_content and
transform_openai_input_gemini_embed_content.
This also fixes drop_params: true not preventing the error, since
the param was re-injected after the drop_params check.
Fixes#24293
When the Responses API converts function_call and message output items
into chat completion messages, they can become two consecutive assistant
messages. The Bedrock Converse transformer merges these into one, but
the merge preserves input order — so if function_call came first, the
toolUse block ends up before the text block.
Claude models (Sonnet 4, Haiku 3.5+) reject this ordering with:
"tool_use ids were found without tool_result blocks immediately after"
Add _sort_bedrock_assistant_content_blocks() that reorders content
blocks within assistant messages: reasoningContent → text → toolUse.
Applied in both sync and async Bedrock Converse transformation paths.
Fixes#24361
When Gemini sends tool call arguments in the same streaming chunk as a
content block transition, the Anthropic adapter discarded the
processed_chunk containing the input_json_delta. This caused tool_use
blocks to arrive with empty input: {}.
Queue the processed_chunk alongside the block transition events when it
contains input_json_delta data. Applied to both sync and async paths.
Fixes#24134
When Azure sends stream_options.include_usage=True, it emits an initial
chunk with choices=[] (prompt_filter_results) before the first content
chunk. Previously, LiteLLM inflated this empty-choices chunk with a
default StreamingChoices, which consumed the sent_first_chunk flag and
caused strip_role_from_delta to strip role from the real first chunk.
Additionally, the first real chunk with role='assistant' and content=''
was discarded by is_chunk_non_empty as "empty".
This fix:
- Forwards chunks with choices=[] faithfully (no inflated default)
- Only marks sent_first_chunk for chunks with real choices
- Treats chunks with role in delta as non-empty
- Guards choices[0] access in __next__/__anext__ and stream_chunk_builder
Fixes#24221
- Use Select.Option with font-medium alias + Text secondary ID to match OrganizationDropdown
- Default page size to 20
- Add useInfiniteTeams mock to AddModelForm tests
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
- OldTeams: refresh table via fetchTeamsV2 after team create instead of appending
- TeamDropdown: rewrite with useInfiniteTeams for paginated fetch, scroll-to-load, and debounced search
- Update all TeamDropdown consumers to use the new self-fetching API
- Dashboard layout: switch from Sidebar2 to SidebarProvider (leftnav)
- Leftnav: add MIGRATED_PAGES routing for path-based navigation (api-reference)
- Navbar: remove chat button
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
Allows wrapping multiple inputs in a nested list to produce a single
combined embedding (text + image = 1 vector). Flat lists continue to
produce separate embeddings per input (OpenAI-compatible default).
Examples:
input=["text", "image"] → 2 separate embeddings
input=[["text", "image"]] → 1 combined embedding
input=[["text", "image"], "x"] → 2 embeddings (1 combined + 1 separate)
When multiple inputs were passed to the Gemini embedding endpoint and any
contained multimodal data (images, audio, etc.), LiteLLM incorrectly used
the `embedContent` endpoint which combines all inputs into a single
aggregated embedding. Now uses `batchEmbedContents` with each input as a
separate request, returning N embeddings for N inputs as expected.
Also fixes hardcoded index=0 in batch embedding responses.
New docs page covering the HA control plane architecture where each
worker instance has its own DB, Redis, and master key. Includes a
React component diagram, setup configs, SSO notes, and local testing
instructions.
Extract multiline `or` chain from LiteLLM_AuditLogs constructor to fix
pydantic mypy plugin field-type misattribution, and add explicit
Optional[bool] annotation to avoid variable name shadowing conflict.
