- Move setModels() and setToolServers() out of the loaded gate in
+layout.svelte so the page renders immediately instead of blocking
behind slow/unreachable connection timeouts
- Track failed Ollama backend URLs from /api/tags and skip them in the
subsequent /api/ps fan-out, eliminating a redundant second timeout
- Silence the autocomplete toast that fires during the transient empty
model state
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
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).
validate_url() calls socket.getaddrinfo() for SSRF protection, which
blocks the event loop for 100-700ms per DNS lookup. This affects:
- Image generation (get_image_data) — every external image URL
- Image editing (load_url_image) — every external image URL
- OAuth profile pictures (_process_picture_url) — every login
- Webhook delivery (post_webhook) — every notification
- Image base64 conversion (get_image_base64_from_url) — chat images
Wrap all 5 async call sites in asyncio.to_thread() so DNS resolution
runs in the thread pool. The event loop remains free to serve other
requests during the lookup.
Benchmark (3 domains, 3 trials averaged):
- BEFORE: max jitter 479ms, 1 blocked ping per trial
- AFTER: max jitter 1ms, 0 blocked pings (324x improvement)
Co-authored-by: Tim Baek <tim@openwebui.com>
The Azure TTS handler (_tts_azure) interpolated the user-supplied voice,
and the locale derived from it, into the SSML xml:lang and <voice name>
attributes without XML-escaping, while the text body was already escaped
(2e75c6dbd). Escape both attributes too, so every user-derived value in
the SSML document is consistently encoded.
Co-authored-by: alanturing881 <alanturing881@users.noreply.github.com>
Co-authored-by: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
Replace per-message database queries with batch IN-clause queries in
channel message handlers. This eliminates the N+1 query pattern that
caused ~102 queries per channel page load (50 messages × 2 queries each).
Changes:
- Add get_reactions_by_message_ids() to MessageTable: single query
fetches all reactions for multiple messages using IN clause with
User JOIN, returns dict[message_id, list[Reactions]]
- Add get_thread_reply_counts_by_message_ids() to MessageTable: single
GROUP BY aggregate query returns (count, max_created_at) per parent,
replacing full object loads just to call len()
- Refactor get_channel_messages(): 102 → 4 queries per page
- Refactor get_pinned_channel_messages(): 22 → 3 queries per page
- Refactor get_channel_thread_messages(): 53 → 4 queries per page
- Refactor send_notification(): N+1 membership check → batch set lookup
pydub imports the stdlib `audioop`, removed in Python 3.13, so audio
preprocessing would break there. requires-python is already capped at
< 3.13; this one-line pointer flags what to handle (audioop-lts, or drop
pydub) before raising that cap.
Timothy Jaeryang Baek