Every stream used to carry two chunks with an empty choices array: usage,
which the upstream emits BEFORE the stop reason, and a cortiq_cost_usd chunk
the gateway added itself. OpenAI ships the usage chunk only when the request
sets stream_options: {"include_usage": true}, and chat UIs do not set it -
which is why the same tool, in the same Open WebUI, sees neither chunk from
Groq and two from us.
Honour the flag. With no stream_options a stream is now exactly
role -> content... -> tool_calls -> finish_reason -> [DONE], with no
choice-less chunks at all. When usage is requested it ships once, after the
stop reason, with cortiq_cost_usd folded into the same chunk rather than
trailing behind it.
Token accounting, cost and the X-Cortiq-* headers are untouched: those numbers
were never read back off the wire.
Verified: the default stream matches the reference shape byte for byte, the
opt-in stream matches OpenAI's, the official OpenAI SDK reassembles the
streamed tool call, and the full Open WebUI 0.11.0 tool loop still runs the
tool and answers from its result.
Qwen-family templates write a function call into the generated text as
<tool_call>{...}</tool_call>. Runtimes disagree on what to do with it: some
parse it into structured tool_calls AND still stream the raw markup as
content - the client then gets the same call twice, once as prose it must not
show and once as the real thing - while others never parse it at all, so a
perfectly good call arrives as text no tool loop will run.
Settle it in the gateway. A streaming-aware filter strips the markup from
content (handling a marker split across SSE chunks, leaving ordinary text
containing "<" alone, and handing an unterminated block back as text), and
when nothing structured came with it the markup is promoted into a real
tool_calls entry with a generated call_... id. Markup that is not a JSON
object with a name is ignored so a stray marker cannot become a bogus call.
Streamed tool_calls are also brought to the OpenAI shape: index on every
entry, id and type exactly once per call so continuation deltas carrying only
an argument fragment stay legal, and function.arguments always a string. A
reply that carries tool calls now always ends with finish_reason "tool_calls",
whatever the upstream called it. The same cleanup runs on the non-streaming
path, so every protocol adapter benefits.
Verified end to end: Open WebUI 0.11.0 -> gateway -> managed CMF/Qwen with
native function calling. The model returns get_weather({"city":"Paris"}), Open
WebUI executes the tool, feeds the result back, and the assistant answers from
it - no markup in content, finish_reason tool_calls, stream closed with [DONE].
router.allaigate.com now resolves and serves a valid certificate, so the
hosted routing API no longer has to be reached by bare IP with certificate
verification switched off. Make https://router.allaigate.com the default
[router].url with verify_tls = true.
Existing configs still pointing at 138.226.222.209 (with or without a scheme
or a trailing slash) are moved to the hostname on load and have verification
restored, then saved: it is the same machine, and this is the difference
between a verified connection and a blind one. A self-hosted router URL is
left untouched.
README, docs/ROUTER.md (both languages), config/gateway.example.toml and
bench/accuracy.py follow.
Verified live: the migration rewrites a legacy config on startup, admin
health reports the hostname reachable over verified TLS (389 ms), and real
requests route through it - "math"/medium 0.416 and "translation"/low 0.268
with route_source=router.
Verified against a real Open WebUI container: it attaches its ~26 built-in
tools (knowledge bases, notes, calendar, ...) to every single message, and
resolve() treated that offer as a hard capability requirement. On a pool of
tools-less local models a plain "hello" therefore failed with "No healthy
model available that satisfies required capabilities", and a pinned local
model was reported as "not available - not in the pool (deleted?)".
In the OpenAI contract `tools` is an offer; only tool_choice: "required" (or
a named function) makes the call impossible without them. Keep preferring a
tool-capable model, but fall back to serving the request with the tools
stripped - together with tool_choice/parallel_tool_calls, which a provider
rejects on their own. A pin whose only shortcoming is tool support is now
honoured; an unknown pin and tool_choice: "required" still fail loudly.
The downgrade is never silent: X-Cortiq-Tools-Dropped: true, plus
cortiq.tools_dropped in the echo block.
/v1/chat/completions answered ordinary client payloads with a bare HTTP 422
(a plain-text body no OpenAI client can parse), so Open WebUI showed neither
an answer nor an error — it just hung. Parse the body leniently instead:
content as string/null/content-part array, tools: null, stream: null, a
string reasoning_effort, max_completion_tokens, messages[].name and
tool_call_id, and a missing Content-Type. Unreadable bodies now come back as
an OpenAI error envelope with 400.
Responses are strict OpenAI JSON: no "tool_calls": null, finish_reason mapped
to the spec's closed set (cortiq serve's max_tokens -> length), never an empty
id, and `model` echoes the id the client requested — the model that actually
answered stays in cortiq.selected_model and X-Cortiq-Selected-Model.
Streaming is re-normalised rather than forwarded verbatim: a leading role
delta, message-shaped chunks converted to delta, one terminal finish_reason,
always a trailing data: [DONE], and an SSE error event when the upstream dies
mid-flight. Adds X-Accel-Buffering: no so a fronting proxy cannot buffer the
stream into a hang.
GET /v1/models now lists managed [[cmf.servers]] models with their live
running/healthy state, so clients can pin a local .cmf directly.
Also strips client bookkeeping keys (chat_id, session_id, metadata, features,
...) from the upstream call and drops the leftover [to_wire] debug prints.
Fifteen changes aimed at the first day of real use:
- Import and media jobs persist to <data>/jobs-*.json and reload on start
(running ones settle as errors); the Register button no longer vanishes
because the gateway restarted.
- Docker ships the cortiq binary (built in the builder stage) — local .cmf
chat models and image/video generation now work in containers, where
auto-install never could (no cargo in the runtime image). libvulkan1 added
for optional GPU offload.
- Open admin console on 0.0.0.0 without a token now warns in the log and
shows a dismissible banner — the VPS footgun is at least labeled.
- "Restart gateway" button in Settings: stops managed model servers, spawns
a fresh copy (bind retried while the port frees), Docker relies on the
container restart policy instead.
- Dashboard "System" panel: CPU sparkline + load, RAM (with the gateway's
own RSS), free disk at the models dir — sampled by sysinfo every 2 s.
- Featured model cards warn "not enough disk" / "may not fit in RAM" before
the download, from the same live snapshot.
- Log viewer in the sidebar: a 500-line in-memory ring fed by a second
ANSI-free tracing layer; filter, level, pause, copy.
- Update check: crates.io polled twice a day, the console shows an
"update available" notice.
- Media generations queue up (with position shown) instead of being
rejected; progress gained an honest ETA from measured throughput.
- Generation gallery under the image/video tabs: lazy PPM thumbnails,
click to reopen with seed/steps, delete.
- Playground chat is a real dialogue now: history is resent, bubbles,
Clear, Cmd/Ctrl+Enter.
- "Connect your app" snippets (curl / Python / JS) on the keys page, with
the real key inlined right after creation.
- One-click benchmark on the Models page via `cortiq bench --json`.
- Config export now downloads the actual gateway.toml (comments intact);
import accepts TOML (validated, hot-reloaded) and the legacy JSON.
- Streaming token counts are exact when the model server provides usage
(cortiq-server patch, shipped separately); the gateway fallback now
counts content chunks (1/token on cortiq) instead of chars/4.
Wizard's Finish lands on the Playground. 37 new strings in all 7 languages.
Startup no longer needs arguments: the config is created on first launch, a busy
port is swapped for a free one, the console is open by default, and the browser
lands on a setup wizard that downloads a ready-made .cmf model and wires it into
routing (managed server + routing.default) when you press Finish.
Download progress was reported from curl's own meter, which prints a full
0→100% bar for the -L redirect hop before the transfer starts — so every job
showed 100% and then hung. Progress now comes from bytes on disk against the
size from the HuggingFace tree (or a HEAD request).
The UI and the gateway also disagreed about the output file name, so a finished
download never marked its card as downloaded; the gateway now returns the exact
stem and the UI sends it back verbatim for download, progress and delete.
Featured models are read live from the infosave HF account in both the wizard
and Import, and all 432 UI strings now exist in every one of the 7 languages.
- New Advanced controls on the import page: O(1) attention spec (off / all /
deep N / explicit layer list) plus the --o1-m / --o1-window / --o1-sink knobs
with validated defaults (32 / 128 / 4) and explanatory hints.
- Backend passes --o1* to the native `cortiq convert`; fails fast with clear
messages when combined with Python-only options, used on GGUF imports, or
when the installed cortiq predates 0.2.0 (the hint needs the new runtime).
- The hint is recorded in the .cmf header (weights byte-identical); the runtime
applies it at load. Verified end-to-end: converted a model with --o1 all and
the runtime logged "o1 nystrom attention: 2/2 layer(s)".
- Stats snapshot now computes the KPI totals AND the breakdown from the
in-window per-minute buckets (previously they used all-time accumulators, so
switching 1h/24h/7d changed only the chart, not the numbers). Buckets now
carry failovers + per-group breakdown; Prometheus keeps all-time counters.
- New DELETE /admin/api/stats clears all in-memory stats and truncates the
JSONL log; the dashboard gets a "Clear logs" button (with confirm).
- The model id is now auto-filled from the model name as you type, and if left
blank it's derived on save (slug of the last path segment, e.g.
"qwen/qwen3.7-max" → "qwen3-7-max") — saving no longer errors on a blank id.
- probe/test auth failures (401 / "User not found" / "No auth") now append a
hint to check the API key (for OpenRouter: use an inference key, not a
provisioning/management key).
- ui.js: mount() now wraps non-node children in text nodes (like h()), so
mount(el, "") no longer throws in appendChild — this is what broke the
"Add model" form (applyDefaults cleared a status via mount(x,"")).
- probe_model: resolve managed local models too (they are synthesized into the
registry, not [[models]]) — probing them no longer returns "model not found".
- models.js: await reload() after delete so the row is removed immediately.
- Providers: add openrouter (https://openrouter.ai/api/v1) and lmstudio
(http://localhost:1234/v1), both OpenAI-compatible. Selecting a provider now
auto-fills its verified base URL, cost tier and default capabilities.
- API key is typed directly in the form and stored securely as a secret under the
provider's env name — no manual env var to manage.
- New POST /admin/api/provider/models validates the key and lists the provider's
models; a "Test & load models" button fills a searchable dropdown. The model
field now sits below the key (some providers list models from the key).
- Fuller capability set: tools, vision, audio, reasoning, json, caching.
- New GET /admin/api/cmf/files lists the .cmf files (and tensor-dir .cmf) under
models_dir, with sizes.
- Settings → Local models: the per-row model field is now a dropdown of those
files instead of a hand-typed path, and auto-fills the id from the filename.
- The gateway can now run several local .cmf models at once: a [[cmf.servers]]
list, one supervised `cortiq serve` per entry on its own port, each registered
in the pool and independently routable/pinnable. The single legacy
local_model/local_port still works (back-compat via effective_servers()).
- Settings → Local models is now a rows editor (id · path · port + check · threads
· GPU) with add/remove and per-server serving status.
- Deleting a managed model stops just its server and removes its file — unless
another model still points at the same file (shared-file guard).
- A pinned playground model that is unavailable now errors clearly instead of
silently answering from the managed local model (route_source no longer lies).
- The managed CMF model is surfaced in GET /admin/api/models (marked "managed",
shown read-only in the UI) so the real running model is visible and pinnable
without a hand-maintained [[models]] entry; a fresh install still lists nothing.
- Deleting a model now removes its local .cmf physically (file or tensor-dir);
deleting the managed model also stops the server and clears the [cmf] config.
Routing is stripped of the deleted id so the config still validates.
- Settings: "?" help tooltips on every option; router key auto-probes the
connection right after saving (no more hanging "unavailable")
- Local models card reworked into 3 clear steps (install cortiq → add model →
run locally); removed the hand-entered .cmf path / pool-id fields — models
are added via the Import tab and the managed server registers them
- Fresh install ships an EMPTY model pool; the local .cmf is auto-registered by
the managed CMF server, so it needs no static [[models]] entry
- New: port-availability check — GET /admin/api/cmf/port + "Check port" button
with next-free-port suggestion. bind()+connect() probe so Docker-proxied /
dual-stack ports (e.g. 8081) are correctly detected as occupied
- /admin/api/cmf now reports the serving model + port; card shows "▶ serving …"
- On-demand runtime install: POST /admin/api/cmf/install
The crates.io/release build shipped a STALE frontend (committed web/js was behind
the working tree), so the admin console hung on load. Commit the current working
web/js (app, api, dashboard, login, import view, i18n de/es/fr/tr/zh, css) and the
backend WIP (import.rs, admin/assets.rs) so the released console matches the dev
build. Verified: clean `cargo build --release`, empty-pool start, working
dashboard served.
- GET /v1/models: pool + virtual cortiq-auto
- POST /v1/completions (legacy): non-stream + streaming text_completion
- POST /route: native passthrough returning the routing decision
- all inbound protocol adapters now implemented; admin meta + README/CHANGELOG updated
- bump to 0.2.1
- release.yml: add x86_64-pc-windows-msvc target, OS-aware packaging (.exe + .zip)
- ci.yml: split into lint (fmt/clippy) + test matrix (ubuntu/windows/macos)
- use getrandom for the admin/key token CSPRNG (secure on Windows too)
- bump version to 0.1.0; add crates.io metadata (include list, homepage, rust-version)
- add .github/workflows/release.yml: on tag v* → publish to crates.io + GitHub Release with binaries
- README: absolute links/images and badges so it renders on crates.io; add install section
- CHANGELOG: 0.1.0
infosave2007