Documents (especially AI/LLM documentation) legitimately contain special token strings like <|endoftext|> as literal text. The tiktoken encoder raises a ValueError when encountering these during chunk size measurement in merge_docs_to_target_size(), preventing the entire file from being indexed. Pass disallowed_special=() to encoding.encode() to treat all text as normal content.
Audit of asyncio.sleep vs time.sleep and event-loop-blocking calls:
- utils/plugin.py: run pip `install_frontmatter_requirements`
(subprocess.check_call) via asyncio.to_thread in load_tool_module_by_id,
load_function_module_by_id, and install_tool_and_function_dependencies.
- retrieval/utils.py: move the synchronous SSRF-guarded requests probe and
loader.load() in get_content_from_url into a sync helper run via
asyncio.to_thread.
- routers/audio.py: write uploaded audio to disk off the event loop in
transcription().
- routers/pipelines.py: write uploaded pipeline file off the event loop in
upload_pipeline().
The existing time.sleep call sites are all in genuinely synchronous
functions (sync requests/DB drivers/daemon threads) with async
counterparts that already use asyncio.sleep, so no time.sleep -> asyncio.sleep
changes were needed.
Claude-Session: https://claude.ai/code/session_01LXR5bYfsfSS42RGHQZu2Ta
Co-authored-by: Claude <noreply@anthropic.com>
Adds a {{USER_AGENT}} custom-header placeholder that relays the inbound
client's User-Agent to upstream model backends, so providers see the real
client instead of Open WebUI's internal aiohttp UA. This makes upstream
usage/cost attribution and backend telemetry possible, and is opt-in
per-connection (no global flag): admins add {{USER_AGENT}} to a connection's
custom headers in Admin > Settings > Connections.
The placeholder is sourced from the live inbound request (with a metadata
fallback for detached RAG/tool calls), so it resolves on every prompt-sending
path, not just chat completions:
- OpenAI completions, Responses API, and proxy — all route through
get_headers_and_cookies, which now passes the request into get_custom_headers.
- Anthropic Messages API (/api/v1/messages) — already covered, it delegates
to the chat completion handler.
- Ollama (/api/chat, /v1/completions, /v1/chat/completions, /v1/messages,
/v1/responses) — previously had no custom-header support at all; send_request
now applies per-connection custom headers (with templating) for every
Ollama prompt endpoint.
Custom headers are applied after the built-in user-info headers so explicit
admin-configured headers take precedence. The other existing placeholders
({{CHAT_ID}}, {{USER_ID}}, ...) now also work on the newly covered paths.
Frontend: the connection editor's Headers field is now shown for Ollama
connections too (previously gated to non-Ollama), so the placeholder can be
configured there.
Ref: open-webui/open-webui#26159
get_protected_resource_metadata() only attempted RFC 9728 discovery when
the anonymous `initialize` probe returned 401 with a WWW-Authenticate
header. Some remote MCP servers — notably Google's Gmail/Drive/Calendar
MCPs (gmailmcp.googleapis.com, etc.) — answer 200 to an anonymous
initialize, so OAuth scope and authorization-server discovery silently
failed and connections to them could not be established.
Run the discovery regardless of the probe's HTTP status: prefer the
resource_metadata URL from WWW-Authenticate when present, and otherwise
fall back to the RFC 9728 §4.2 well-known URIs. The trade-off is a couple
of extra well-known GETs during MCP connection setup for servers that
expose no PRM document; behavior for 401-responding servers is unchanged.
routers/openai.py and routers/ollama.py decorated get_all_models with
`@cached(key=lambda _, user: ...)`. In aiocache 0.12, `key=` is a STATIC
cache key: get_cache_key returns `self.key` verbatim (the lambda object)
without calling it, so every caller collides to ONE shared entry within
the TTL. The intended per-user namespacing never happened — one user's
permission-filtered model list could be served to another user (or an
anonymous caller) during the cache window.
The per-call hook is `key_builder=` (called as key_builder(func, *args,
**kwargs)). Switch both sites to key_builder with a (func, request,
user=None) signature so the key is built per call. user=None mirrors
ollama's optional-user signature and stays correct whether user is passed
positionally, as a kwarg, or omitted.
Verified offline: old form returns the same key object for distinct users
(collision); new form yields distinct openai_all_models_<id> /
ollama_all_models_<id> keys, and the unauthenticated base key when no user.
These two were the only @cached(key=lambda ...) sites in the backend.
The Ollama model upload and download handlers perform three stages
of sync file I/O on multi-GB model files inside async handlers:
1. Persist upload — file.file.read() + write() in a loop
2. SHA-256 hash — calculate_sha256() reads the file sequentially
3. Read for blob push — open().read() loads entire model into memory
All three stages block the event loop for the duration of the I/O.
For a 4GB model, each stage freezes the event loop for 10+ seconds
while every other user's request stalls.
Wrap each blocking stage in asyncio.to_thread() in both handlers:
- upload_model(): persist upload, calculate_sha256, blob read
- download_file_stream(): calculate_sha256, blob read
Benchmark (full pipeline: write + SHA-256 + read back, 3 trials):
- 200MB: max jitter 145ms → 1ms (145x improvement)
- 500MB: max jitter 1,026ms → 1ms (1,026x improvement)
File I/O is pure I/O — no GIL contention. asyncio.to_thread()
completely eliminates event loop blocking.
GET /api/v1/channels/{id}/messages/{message_id}/thread authorized only the URL channel, but get_messages_by_parent_id() appended the thread parent (loaded by id) without checking it belonged to that channel, so a caller could read a message from a channel they cannot access by passing its id as the thread root. Require the parent to be in the requested channel before returning it, and reject a posted parent_id/reply_to_id that does not belong to the channel.
Co-authored-by: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
- Wrap get_content_from_url() in asyncio.to_thread() inside
get_sources_from_items() to prevent sync requests.get() from blocking
the event loop when users attach URL sources to chat messages.
The same function was already properly wrapped at retrieval.py:1839.
- Wrap hashlib.sha256(contents).hexdigest() in asyncio.to_thread()
inside upload_file_handler() to prevent CPU-bound hashing from
blocking the event loop during file uploads (44ms/100MB, scales
linearly with file size).
Web search results stored as a vector collection were silently dropped
before retrieval when BYPASS_RETRIEVAL_ACCESS_CONTROL is False (the
default). The server-generated web_search file item carries a
'collection_name' but its 'web_search' type is not matched by any
explicit dispatch branch in get_sources_from_items, so it fell through
to the untrusted client-supplied collection_name branch and was ignored.
Add an explicit branch for type == 'web_search' items so the collection
is queried again. Access control is preserved: the collection still
passes through filter_accessible_collections, which already allowlists
web-search-* and bypasses only for admins.
Regression introduced when the retrieval access-control hardening gated
the bare collection_name fallback behind BYPASS_RETRIEVAL_ACCESS_CONTROL.
get_embedding_function runs at import time (main.py), so the empty-engine
+ no-model guard added in 55ca719b raised ValueError during startup and
bricked the instance: a blank embedding model set via the UI made the app
unbootable, with no way back into settings to undo it. Move the check into
the returned coroutine so construction always succeeds and the error only
fires when something actually embeds, surfacing as a clear request error
instead of the old cryptic 'NoneType has no attribute encode'.
Fixes#25634Fixes#25165
Co-authored-by: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
