After a tool call, the model's thinking was streamed into the chat as if it were the main response, and only jumped into the collapsed Thoughts section once the turn finished. Every further tool call repeated it.
Each tool round appended an empty placeholder message item to the output and sent it to the browser, then dropped it again from the copy used to offset the next round's item indices. The browser therefore held one item more than the backend counted, so the first thinking chunk of the next round was written into that leftover message item and rendered as normal text until the finished output replaced it.
The placeholder is removed. It was never needed: a message item is already created when actual content arrives, and dropping it also stops an empty assistant message being sent back to the model on the follow-up request.
Co-authored-by: Claude <noreply@anthropic.com>
Any `<$...>` run in a chat message was treated as an inline skill mention and removed before the request reached the model, so text like `<$(=MonthStart($(vMaxMonthEndINC)))"}, [Registration day] >` silently vanished mid-message and the model only saw the part before it.
The mention regexes accepted any character except `|` and `>` as the skill id, so they matched far more than real mentions. Skill ids are already validated as `[a-z0-9_-]+` when a skill is created, so both regexes now require that charset. Ordinary text passes through untouched while `<$id>`, `<$id|Label>` and `</id|Label>` still resolve and strip as before.
Verified against the reported message (now preserved verbatim) and the three mention forms.
Co-authored-by: Claude <noreply@anthropic.com>
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New **pt-BR** translations for items introduced in the latest releases, plus a consistency/quality pass across existing strings (grammar, tone, capitalization, pluralization). Placeholders and hotkeys preserved. No logic changes.
Every chat request hands each builtin tool a fresh copy of its cached spec, because callers mutate what they get. That copy was a full deepcopy of a nested dict, repeated per tool per message.
The builder now caches the spec already serialized, so a request only parses it back. Parsing is what produces the independent tree callers mutate, and the cached value becomes an immutable string, so a request can no longer reach the cached object at all.
Measured on CPython 3.12 with a 1.1 KB spec and 20 builtin tools per request:
| | before | after |
|---|---|---|
| stdlib json, the default | 276.2 us | 66.4 us |
| orjson | 279.5 us | 37.5 us |
Builtin specs are plain JSON by construction: pydantic normalizes every default before it reaches the schema, so a tuple, set, enum or datetime cannot appear in one, and an unserializable default is dropped rather than embedded.
"RAG_METADATA_MAX_VALUE_CHARS" ships unset, and unset means no bound at all, so the limit only protects the deployments that already knew to configure it. A small Office document is a zip archive, and one crafted to expand enormously during extraction can turn a few hundred kilobytes into gigabytes of metadata held in memory; uploading it a handful of times is enough to exhaust a server and take Open WebUI down with it.
When no explicit limit is configured, the bound now follows "RAG_FILE_MAX_SIZE" instead of being absent, on the reasoning that a document cannot legitimately carry more metadata than the file itself is allowed to be. That keeps the number from being an arbitrary guess: it is whatever the administrator already decided an upload may weigh. Setting "RAG_METADATA_MAX_VALUE_CHARS" explicitly still wins, and a deployment that leaves both unset is unchanged, which is the same posture the upload limit itself takes.
"RAG_FILE_MAX_SIZE" is in MB and is treated as unset when it is zero, matching how the document loader already reads it.
Every streamed delta saves a snapshot of the in-progress response so a reconnecting client can resume it, and each save rebuilt the assistant text from scratch. On the Chat Completions path that re-joined every accumulated chunk, including on saves carrying no new text, so a long answer followed by a large tool call re-joined the whole answer once per argument chunk. The Responses API path never collects those chunks and reads the text back out of the output items instead, where the blank check copied it in full every time.
The joined string is now kept and reused until another chunk arrives, since content_parts is only ever appended to; the nonlocal declaration that suggested otherwise was already dead and is dropped, and inlining the single-use helper removes an unreachable branch with it. The blank check in get_output_text now tests the text rather than allocating a stripped copy of it, which is equivalent for all twelve of its callers. Text streaming on the Chat Completions path is unchanged, since a text delta always appends before it saves.
| stream | before | after |
| --- | --- | --- |
| 20k-char answer, 2000 tool-argument chunks | 21.4 ms | 0.06 ms |
| Responses API, 40k deltas, 200k chars | 80.7 ms | 50.5 ms |
Without Redis nothing extra is retained, since the snapshot store already held that string; with Redis one copy of the response text stays alive while the stream runs.
Tag detection for the code interpreter ran regardless of the tool-calling mode, so a model in Native (Agentic) Mode that emitted <code_interpreter> blocks in ordinary reply text had that code sent to the executor. Native mode never teaches the tag format and exposes execute_code as a builtin tool, so the parser had nothing legitimate to pick up there.
Gates detection on the legacy mode, matching the condition that already decides whether the tag prompt is injected at all. The five authorization checks are unchanged, and native mode keeps executing through the tool.
Deployments on native mode whose models emit the tags unprompted will now see them rendered as text.
