/profile previously required auth and returned a raw JSON 401 for
guests. Now it renders a guest variant: edit guestUsername in
localStorage, clear it to re-prompt on next visit, or sign in to
claim a permanent username. Unifies the two username flows
(authed DB display_name vs guest localStorage) under one page.
chat_message (non-streaming) renders the sender header as the first
paragraph inside .message-content — '<p><strong>[name](link):</strong></p>'.
message_chunk uses a separate .message-header div, but the inline pattern
made the sender name sentence 0, so manual Play highlighted the model
name instead of the actual first sentence (and auto-play got every
highlight shifted by one because domIndexFor ratioed around it).
Detect the pattern (top-level <p> with one <strong> child, text ending
in ':') and exclude it from the sentence walk via a TreeWalker filter.
Also drops the diagnostic logging from cdf3c7c.
Temporary instrumentation to pinpoint why sentence highlighting fails on
manual Play. Logs whether audio/button are present, whether sentences is
the expected array, the post-wrap span count, and the wrap-flag state.
Will revert once root cause is found.
Guests had to retype their username on every page load. Now the entered
name is cached in localStorage and reused on subsequent visits. The
cache is invalidated by any login/logout transition:
- on a page load with a server-provided username (logged in), we clear
the cache, so a later logout starts fresh
- on a guest page load with no cache, we prompt and save what they type
wrapSentencesForGlow gated only on dataset.glowWrapped='1', but that flag
lives on the container element and survives innerHTML replacement. The
streaming chunk handler does targetMessageElement.innerHTML = sanitized
on every delta, and message_updated / edit-save both replace innerHTML
too. Spans got blown away while the flag persisted, so subsequent glow
attaches found the flag, skipped re-wrapping, and the highlight never
appeared.
Now also require an actual .tts-sentence span to exist before short-
circuiting. If the wrap was destroyed, re-wrap.
Two regressions surfaced after adding the Pause label in manual mode:
1. Clicking Pause restarted the cached blob from the beginning (looked
like the track played twice). speakText's onclick was still wired to
speakText itself, so each click created a fresh Audio and started
from 0. Manual play now uses the same takeOver pattern as the queued
path: while live audio owns playback, the click routes through
toggleAudioPlayback (which pauses any current audio and toggles this
one); when audio ends or errors, the original speakText handler is
restored so users can replay from cache.
2. Manual mode had no sentence highlights. The glow needs per-sentence
timing from the speech service, which only the SSE branch returns —
manual mode was using the older non-SSE streaming path. speakText now
branches on tts-1-f5 like speakTextQueued does, caches the sentences
array, and calls attachSentenceGlow. Pauses naturally pause the glow
(its tick loop checks audio.paused/ended).
Also routes the queued-audio onclick rebind through toggleAudioPlayback
for cross-message safety (was calling audio.play()/pause() directly,
which would let two queued audios play simultaneously if the user
clicked Play on a paused one while another was active).
The onplay handler set the button text to 'Pause' mid-playback but the
button's onclick was still wired to speakText. Clicking Pause re-ran
speakText, which created a fresh Audio from the cached blob — the queued
audio paused while a new one started from the beginning, sounding like a
double-play.
Rebind the click handler to direct audio.pause()/play() while the queued
audio owns playback, restore the original (cache-replay) handler on end
or error.
Auto-play TTS used to show zero feedback between message arrival and
audio start — users waited blind. Now the play button shows:
Queued + pulsing dot — message is waiting in line
Loading + spinner — actively fetching audio from speech service
Pause — audio is actually playing
Manual Play also uses the same spinner instead of the old 'Streaming...'
text-only state. Indicator clears on play, pause, end, error, and when
auto-play is toggled off.
Active Users counted all-time distinct UserSession usernames, not anyone
currently online. Active Rooms counted any room that ever received a
single message, with no decay. Both read as live metrics but aren't.
Keep Public Rooms and (when signed in) Private Rooms — those are real
counts users can verify by browsing.
Replace the non-streaming whole-clip timestamps fetch with an SSE consumer.
Each event carries one sentence's mp3 + exact start/end ms; audio feeds an
MSE SourceBuffer in sequence mode so playback starts after sentence 0, and
the sentences array grows live to drive the glow (tick reads its length each
frame). Falls back to a buffered single blob when the browser lacks mp3 MSE.
Removes fetchTTSWithTimestamps. Best of both: instant start and exact sync.
Restore the theme toggle into the chat utility belt (desktop + mobile),
placed directly above the Auto-Play TTS button. Re-wires updateThemeButtonText
to label both buttons (shows the mode a click switches to). toggleTheme()
already persisted to localStorage and swapped the highlight.js theme.
When a message is deleted, drop its cached TTS audio (keys `${messageId}-${voice}`),
remove any pending entries from the playback queue, and if it is the message
currently playing, stop it and advance the queue. Track currentQueuedMessageId
so the active item can be identified. Keeps auto-play sequencing correct and
prevents a deleted message's stale audio from replaying.
Replace the fragile client-side RMS / Web Audio pause detection (which
stalled on sentence 0 whenever the audio context was suspended or the
MSE duration was unknown) with exact per-sentence timing from the speech
service. For tts-1-f5, fetch via the new timestamps mode and light each
sentence by comparing audio.currentTime to the returned start/end ms;
falls back to proportional mapping if the rendered and spoken sentence
counts differ. Cache now stores sentences for correct replay glow.
Non-F5 models keep streaming playback with no glow.
Flip the Thinking toggle to default ON: localStorage init now reads
!== 'false' (matching the standard default-on idiom), and both desktop
and mobile buttons render green "Thinking: ON" by default. Users opt out
to save tokens; the OFF path still drives server-side enable_thinking=false.
When Auto-Play TTS reads a message, wrap its sentences in spans and advance a
glow highlight on detected inter-sentence silences (RMS dips), with a
char-proportional fallback. Comma/clause pauses are detected too, reserved for
a future word-level highlight. Tunable via window.GLOW.
Add a Thinking on/off button next to Auto-Play TTS. When OFF (default),
the client sends enable_thinking=false with each chat_message and the
server passes chat_template_kwargs.enable_thinking=false to self-hosted
OpenAI-compatible endpoints (Qwen3-style), suppressing chain-of-thought
to save tokens rather than merely hiding it. Skips the param for
api.openai.com (which would 400) and o1/o3 (always think); templates that
ignore the kwarg simply drop it. Client-side reasoning suppression remains
as a fallback. State persists to localStorage across desktop and mobile.
Qwen3.x / Deepseek-R1 / o1 stream model thinking via
delta.reasoning_content during SSE; the final answer arrives later via
delta.content. Both server streaming paths (OpenAI client + llama-cpp
Python lib) now extract reasoning_content per chunk and emit it via the
same socketio "message_chunk" event with a `reasoning_content` field
(distinct from `content`). Reasoning is forwarded but NOT accumulated
into the buffer that persists to the DB — it's transient model-private
state, not part of the saved message.
Frontend (templates/chat.html): the message_chunk handler dispatches
on payload shape. On `reasoning_content`: lazy-create a
<details class="message-thinking"> block at the top of the message
wrapper, append text, return early (no buffer/markdown render). On
`content`: if a thinking block exists and is still open, auto-collapse
it to "thinking (click to expand)" before standard content rendering.
If a response never thinks, no thinking DOM element is created — no
visual artefact at all. Compatible with all existing message_chunk
listeners; reasoning_content is purely additive.
Belt-and-suspenders: inline onkeydown on textarea ensures Enter
works regardless of JS event listener registration order, plus
a visible Send button as clickable fallback.
- Audio starts playing as soon as ~1KB arrives instead of waiting for full download
- Browser-aware format detection (webm+opus for Firefox, mp3 for Chrome)
- Falls back to buffered download if MediaSource not supported
- Updated speakText() and speakTextQueued() to use streaming
- Cache blobs instead of Audio objects for cleaner replay
Correct the artifact implementation to match Unsandbox API:
- Request parameter: return_artifact (boolean, singular)
- Response field: artifacts (array, plural)
- Data field: content_base64 (not data/content)
Changes:
- Backend: Changed artifacts to return_artifact in request body
- Frontend: Use return_artifact in execute request
- Frontend: Look for artifacts array in response (not artifact singleton)
- Frontend: Decode content_base64 field (not data/content)
- Frontend: Use filename field (primary) over name
- Remove debug console.log statements
- Update CLAUDE.md with correct API contract
The API parameter is singular but response is plural - this is intentional
design by Unsandbox API. Request enables artifact collection, response
returns array of generated artifacts.
Add console.log statements to see actual artifact object structure:
- Log artifacts array when received
- Log each artifact object and its keys
- Log download attempt with artifact keys and data presence
This will help diagnose why artifacts show metadata but fail on download/view.
Artifacts are returned as base64-encoded data directly in the job response
payload, not as URLs. Previous implementation incorrectly tried to fetch
artifacts from URLs via a proxy endpoint.
Changes:
- Remove /api/code/artifacts proxy endpoint (not needed)
- Update downloadArtifact() to decode base64 and trigger download
- Update viewArtifact() to decode base64 and display inline:
* Images: rendered as data URLs (data:image/png;base64,...)
* Videos: decoded to blob URLs with controls
* Text: decoded and displayed in <pre> blocks
- Update CLAUDE.md with correct artifact format and implementation details
- Add artifact response format example showing base64 data structure
Artifact format in response:
{
"artifacts": [{
"name": "output.png",
"type": "image/png",
"data": "base64string...",
"size": 12345
}]
}
- Add helper functions to extract first image and generate description from chat messages
- Update base.html and index.html with og:image, og:description, twitter:card meta tags
- Chat rooms now use first image from messages for unfurling instead of site logo
- Description shows first 500 chars of room content for link previews
- Add default OG image (black with OC) as fallback when no image found
Remove race condition where syncDropdownsAndQueryString() was called before
dropdowns were populated, causing empty values to overwrite localStorage.
Model and voice restoration now happens only in populateModelDropdown() and
populateVoiceDropdown() after async fetch completes.
- Fetch external images through proxy.unturf.com (respects robots.txt)
- Convert fetched images to base64 for vision API
- Cache both fetched images and descriptions
- Shows "Fetching image..." for external URLs, "Generating description..." for base64
- Handles 403 responses when blocked by robots.txt
Backend:
- Track VISION_MODELS list at startup from available endpoints
- Add is_vision_model() to detect vision-capable models (*-vl*, *vision*, gpt-4o)
- Add extract_base64_from_img_tag() and build_message_content() helpers
- Modify chat_gpt() to include base64 images for vision models
- Add GET /vision endpoint for vision availability status
- Add POST /vision/describe endpoint for image alt-text generation
Frontend:
- Check vision availability on page load via /vision
- Add hover event delegation on chat images
- On hover: call vision model, cache result, set img.title and img.alt
- Shows cursor:wait while loading description
Update code execution error detection to use stderr exclusively
instead of checking both stdout and stderr. This aligns with the
Unsandbox API's proper stream separation where:
- stdout is for program output
- stderr is for errors/warnings
Changes:
- Remove stdout from error detection logic
- Only trigger auto-fix when exit_code != 0 AND stderr is non-empty
- Send only stderr to /api/fix-code endpoint
This prevents false positives where stdout contains normal output
that was previously being treated as error content.
- Use codeBlock.dataset.autoExecAttempt to pass attempt number
- executeCodeBlock transfers attempt to results container
- No longer pre-creates empty results container
- Clean up data attribute after use
- Add null check for classList before calling contains()
- Handles case where nextSibling might be a text node
- Prevents 'classList is undefined' error
- Correctly insert results container after button container
- Use buttonContainer.parentNode.insertBefore() instead of preElement
- Add proper styling when creating results container
- Fixes 'Child to insert before is not a child of this node' error
- Post fixed code to chat so user can see what was changed
- Store fix data in window.pendingAutoExec for message handler
- Auto-trigger execution on newly posted code block
- Preserve attempt counter across fix iterations
- User now sees: original error → fixed code posted → auto-execution → results
- Remove chat message posting that prevented automatic re-execution
- Fixed code now executes directly using same blockElement
- Simplify re-execution flow with direct recursive call
- Results display in same execution results container
Implements an AI-powered auto-fix system that automatically attempts to
repair code execution errors up to 3 times.
Backend changes (app.py):
- Add /api/fix-code endpoint that uses MODEL_1 (Hermes) to analyze
stderr output and generate corrected code
- System prompt instructs AI to output only raw fixed code without
explanations or markdown formatting
- Accepts code, language, stderr, exit_code, and attempt number
Frontend changes (templates/chat.html):
- Modify executeCodeBlock() to detect failed executions (exit_code !== 0)
- Track fix attempts per code block (max 3) using dataset attributes
- Call /api/fix-code when errors are detected
- Display fixed code as new chat message with markdown formatting
- Automatically re-execute the corrected code recursively
- Show progress messages during auto-fix attempts
- Display warning when max attempts (3) are exhausted
Features:
- Fixes common issues: missing imports, syntax errors, type errors
- Posts fixed code to chat for transparency
- Prevents infinite loops with 3-attempt limit
- Graceful error handling with user-friendly status messages
Add inline script at top of base.html <head> to set theme immediately
before any rendering occurs. Prevents white flash when loading chat
and other pages that extend base.html in dark mode.
- Chat messages: logged-in user's name links to /profile
- User lists (sidebar): logged-in user's name is clickable link
- Previous messages: same profile link logic applied
- Other users still link to /profile/username (future feature)
Anywhere the logged-in user's name appears, it now links to their
profile settings page for quick access to logout and username change.
- Add inline script to set theme before page render (browse, profile)
- Prevents white flash when loading pages in dark mode
- Add logout button with confirmation to profile page
- Username already clickable in browse page header (links to profile)
- Update CODE_EXEC_URL from code.ai.unturf.com to api.unsandbox.com
- Fix response field handling for Unsandbox API format (flat structure)
- Add exit code display with color coding (green=0, red=error)
- Update displayExecutionResults to handle stdout/stderr/exit_code at top level
- Simplify error handling for timeout/cancelled jobs
- Add comprehensive Unsandbox API documentation to CLAUDE.md
