feat(qwen): Alibaba Qwen built-in over Model Studio's OpenAI-compatible mode
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Adds the `qwen` built-in provider and the `qwen://` DSN scheme, keyed by
QWEN_API_KEY and defaulting to Model Studio's international host. Like kimi
(ADR-0026) it is `provider/openai` pointed elsewhere — no new client.

Model Studio serves the same models over two protocols, so the real decision
was which wire format to speak. ADR-0027 records why it is the OpenAI one:
down the anthropic client `ReasoningEffort` is ignored by design, structured
output rides the first-party `output_config.format` mechanism the shim does
not implement, and cached-token accounting reads Anthropic-only usage fields.
Each of those fails silently rather than loudly, which is what makes the
choice worth writing down. The shim stays reachable ad hoc via an
`anthropic://` DSN.

The kimi and qwen DSN factories were byte-identical, so they now share one
`openaiCompatScheme` helper: the "credential comes from the DSN token, and
the missing-key hint names LLM_<NAME>" rules hold by construction instead of
by copy.

Tests are hermetic and break-checked (all six fail on a deliberate mutation),
including the reverse credential leak — a visible QWEN_API_KEY must not
authenticate the openai built-in — and reasoning_effort asserted on the wire
body, which is the ADR's load-bearing claim.

Co-Authored-By: Claude Opus 5 (1M context) <[email protected]>
This commit is contained in:
2026-08-12 16:07:41 -04:00
co-authored by Claude Opus 5
parent 1bbbdaa1e5
commit 02cd561eaf
8 changed files with 461 additions and 20 deletions
+1
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@@ -7,6 +7,7 @@ OLLAMA_API_KEY=your-ollama-cloud-key-here
# Built-in provider keys (each optional; only needed for the providers you use).
#OPENAI_API_KEY=sk-...
#KIMI_API_KEY=sk-... # Moonshot AI (Kimi); provider name "kimi"
#QWEN_API_KEY=sk-... # Alibaba Model Studio (Qwen); provider name "qwen"
#ANTHROPIC_API_KEY=sk-ant-...
#GOOGLE_API_KEY=...
+23 -1
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@@ -122,6 +122,7 @@ Chains are health-tracked per target:
|----------|-----------|-------------|------------------|
| OpenAI (+compatible) | `openai` | `OPENAI_API_KEY` | https://api.openai.com/v1 |
| Kimi (Moonshot AI) | `kimi` | `KIMI_API_KEY` | https://api.moonshot.ai/v1 |
| Qwen (Alibaba) | `qwen` | `QWEN_API_KEY` | https://dashscope-intl.aliyuncs.com/compatible-mode/v1 |
| Anthropic (+compatible) | `anthropic` | `ANTHROPIC_API_KEY` | https://api.anthropic.com |
| Google (Gemini) | `google` | `GOOGLE_API_KEY` / `GEMINI_API_KEY` | Gemini API (official SDK) |
| Ollama Cloud | `ollama-cloud` | `OLLAMA_API_KEY` | https://ollama.com |
@@ -134,6 +135,19 @@ the openai client (like llama-swap). The `kimi` built-in defaults to the
international endpoint; reach the China endpoint (or any other host) with a
`kimi://` DSN, e.g. `LLM_KCN=kimi://[email protected]/v1`.
Qwen is the same shape: Alibaba Model Studio's OpenAI-compatible mode, reusing
the openai client. The `qwen` built-in defaults to the international
(Singapore) host; reach the China host or a workspace-scoped regional one with
a `qwen://` DSN, e.g.
`LLM_QCN=qwen://[email protected]/compatible-mode/v1`. Model Studio
also fronts the same models with an Anthropic-compatible `/v1/messages` shim —
majordomo does **not** use it, because on that surface `reasoning_effort` is
dropped, `Request.Schema` stops being enforced, and cached-token accounting
disappears; see [ADR-0027](docs/adr/0027-qwen-builtin.md). Two Alibaba-side
quirks are worth knowing: thinking is on by default for some models (e.g.
`qwen3.7-plus`), and the Qwen3 open-source models require streaming while
thinking, so buffered `Generate` calls want a Max/Plus model.
OpenAI-compatible / Anthropic-compatible endpoints: construct the provider
with a name and base URL and register it —
@@ -165,7 +179,7 @@ m, _ := reg.Parse("m5/qwen3:30b,m1/qwen3:30b,thinking")
```
DSN format: `scheme://[token@]host[/path]`, scheme ∈ `foreman`, `ollama`,
`ollama-cloud`, `openai`, `kimi`, `anthropic`, `google`/`gemini`, `llama-swap`,
`ollama-cloud`, `openai`, `kimi`, `qwen`, `anthropic`, `google`/`gemini`, `llama-swap`,
`llama-swaps`, or any scheme you add with `RegisterScheme`. The token is the
credential (bearer token / API key); the base URL is always `https://host[/path]`
— except `llama-swap`, which builds `http://host[:port]` since it's local-first
@@ -407,6 +421,7 @@ to build one.
|----------------------|:---:|:---:|:---:|:---:|:---:|:---:|:---:|
| OpenAI (+compatible) | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ |
| Kimi (Moonshot AI) | ✅ | ✅ | ✅ | ✅ | ✅ | ✅³ | ✅ |
| Qwen (Alibaba) | ✅ | ✅ | ✅ | ✅ | ✅⁴ | ✅⁴ | ✅ |
| Anthropic (+compat) | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ |
| Google (Gemini) | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ |
| Ollama Cloud | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ |
@@ -431,6 +446,13 @@ probe and management methods on `*llamaswap.Provider`.
level; whether a call succeeds depends on the Moonshot model — only the vision
variants (e.g. `moonshot-v1-8k-vision-preview`) accept images.
⁴ Qwen also reuses the openai client (ADR-0027), so both columns are present at
the client level and gated by the Model Studio model you name: `json_schema`
structured output is on the Max/Plus families, image inputs on the `qwen-vl-*`
/ `qwen3-vl-*` models. `reasoning_effort` rides through as a top-level field —
one reason the built-in speaks OpenAI-compat rather than Model Studio's
Anthropic-compat shim.
Notes: Ollama has no native tool_choice — `"none"` drops the tools;
`"required"`/named choices are best-effort ignored there. Ollama Cloud
ignores the `format` field (verified live), so the provider also states
+55 -13
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@@ -19,6 +19,15 @@ const (
// Chat Completions endpoint. Reuses the openai client (like llama-swap);
// keyed by KIMI_API_KEY, default base URL kimiBaseURL.
ProviderKimi = "kimi"
// ProviderQwen is Alibaba's Qwen models over Model Studio's
// OpenAI-compatible Chat Completions endpoint. Reuses the openai client
// (like kimi and llama-swap); keyed by QWEN_API_KEY, default base URL
// qwenBaseURL. Why OpenAI-compat and not the Anthropic-compat endpoint
// Model Studio also exposes: see ADR-0027 — the OpenAI surface is the
// first-class one there (reasoning_effort, json_schema structured output,
// cached_tokens accounting all ride it), while the Anthropic shim exists
// mainly to host Claude Code.
ProviderQwen = "qwen"
ProviderAnthropic = "anthropic"
ProviderGoogle = "google"
ProviderOllama = "ollama"
@@ -37,6 +46,32 @@ const (
// China endpoint (api.moonshot.cn/v1) is reachable via a kimi:// LLM_* DSN.
const kimiBaseURL = "https://api.moonshot.ai/v1"
// qwenBaseURL is Alibaba Model Studio's international (Singapore) endpoint in
// OpenAI-compatible mode. The China endpoint
// (dashscope.aliyuncs.com/compatible-mode/v1) and any regional host are
// reachable via a qwen:// LLM_* DSN.
const qwenBaseURL = "https://dashscope-intl.aliyuncs.com/compatible-mode/v1"
// openaiCompatScheme builds the DSN factory shared by every built-in that is
// "the openai client pointed somewhere else" (kimi, qwen, ...). The provider
// is named after the LLM_<NAME> var that defined it, takes its credential from
// the DSN token — not the built-in's own env var, which does nothing for a
// DSN-defined provider — and so names that same LLM_<NAME> var in the
// missing-key hint, matching the lazy-resolution key form in providerFor.
//
// wrap is the caller's option-decorator (it injects the registry's HTTP
// client), so a DSN provider is built exactly like the eager built-ins.
func openaiCompatScheme(wrap func(...openai.Option) []openai.Option) SchemeFactory {
return func(name string, dsn DSN) (llm.Provider, error) {
return openai.New(wrap(
openai.WithName(name),
openai.WithBaseURL(dsn.BaseURL()),
openai.WithAPIKey(dsn.Token),
openai.WithAPIKeyName("LLM_"+strings.ToUpper(strings.ReplaceAll(name, "-", "_"))),
)...), nil
}
}
// registerBuiltins installs the built-in providers and env-DSN scheme
// factories into a fresh registry. httpClient, when non-nil, is used by
// every provider and factory the registry itself constructs.
@@ -96,19 +131,26 @@ func registerBuiltins(r *Registry, httpClient *http.Client) {
openai.WithAPIKeyName("KIMI_API_KEY"),
)...)
// kimi:// DSN scheme: an OpenAI-compatible target labeled kimi, base URL
// from the DSN host (e.g. kimi://[email protected]/v1 for China). Its
// credential is the DSN token, not KIMI_API_KEY, so the missing-key hint
// names the LLM_<NAME> env var that defines this provider (matching the
// lazy-resolution key form in providerFor) — the fix for a keyless target
// here is adding a token to that DSN.
r.schemes[ProviderKimi] = func(name string, dsn DSN) (llm.Provider, error) {
return openai.New(openaiOpts(
openai.WithName(name),
openai.WithBaseURL(dsn.BaseURL()),
openai.WithAPIKey(dsn.Token),
openai.WithAPIKeyName("LLM_"+strings.ToUpper(strings.ReplaceAll(name, "-", "_"))),
)...), nil
}
// from the DSN host (e.g. kimi://[email protected]/v1 for China).
r.schemes[ProviderKimi] = openaiCompatScheme(openaiOpts)
// Qwen (Alibaba Model Studio): same shape as kimi — an OpenAI-compatible
// Chat Completions endpoint, so it reuses the openai client rather than a
// new package. Model Studio also exposes an Anthropic-compatible endpoint;
// ADR-0027 records why the OpenAI one is the built-in. Same unconditional
// WithAPIKey + WithAPIKeyName discipline as kimi: an unset QWEN_API_KEY
// must never fall through to OPENAI_API_KEY, and the missing-key error
// must name the variable the operator actually has to set.
r.providers[ProviderQwen] = openai.New(openaiOpts(
openai.WithName(ProviderQwen),
openai.WithBaseURL(qwenBaseURL),
openai.WithAPIKey(r.envLookup("QWEN_API_KEY")),
openai.WithAPIKeyName("QWEN_API_KEY"),
)...)
// qwen:// DSN scheme: an OpenAI-compatible target labeled qwen on any
// Model Studio host (e.g. qwen://[email protected]/compatible-mode/v1
// for China, or a workspace-scoped regional host).
r.schemes[ProviderQwen] = openaiCompatScheme(openaiOpts)
// llama-swap: OpenAI-compatible chat + image generation + management
// endpoints over a model-swapping proxy. Chat reuses the openai client
+12 -3
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@@ -16,16 +16,25 @@ import (
const kimiResponse = `{"id":"c1","object":"chat.completion","choices":[` +
`{"index":0,"message":{"role":"assistant","content":"ok"},"finish_reason":"stop"}]}`
// captureRT records the last request and returns a canned response without
// touching the network, so these tests stay hermetic while still exercising
// the real openai client the kimi built-in reuses (base URL + auth header).
// captureRT records the last request (and the bytes of its body) and returns a
// canned response without touching the network, so these tests stay hermetic
// while still exercising the real openai client the kimi and qwen built-ins
// reuse: base URL, auth header, and the JSON actually put on the wire.
type captureRT struct {
req *http.Request
reqBody []byte
body string
}
func (c *captureRT) RoundTrip(r *http.Request) (*http.Response, error) {
c.req = r
// Drain and close the request body: a RoundTripper owns it, and those
// bytes are what wire-shape assertions read.
c.reqBody = nil
if r.Body != nil {
c.reqBody, _ = io.ReadAll(r.Body)
_ = r.Body.Close()
}
return &http.Response{
StatusCode: http.StatusOK,
Body: io.NopCloser(strings.NewReader(c.body)),
+235
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@@ -0,0 +1,235 @@
package majordomo
import (
"context"
"encoding/json"
"errors"
"net/http"
"strings"
"testing"
"gitea.stevedudenhoeffer.com/steve/majordomo/llm"
)
// qwenResponse is a minimal valid Chat Completions body so Generate returns a
// non-empty response (an empty one would trigger failover, not a clean pass).
const qwenResponse = `{"id":"c1","object":"chat.completion","choices":[` +
`{"index":0,"message":{"role":"assistant","content":"ok"},"finish_reason":"stop"}]}`
// TestQwenBuiltin: the built-in "qwen" provider resolves in Parse, targets
// Model Studio's international OpenAI-compatible endpoint, and authenticates
// with QWEN_API_KEY.
func TestQwenBuiltin(t *testing.T) {
rt := &captureRT{body: qwenResponse}
r := newTestRegistry(t,
WithEnvLookup(func(k string) string {
if k == "QWEN_API_KEY" {
return "qwen-secret"
}
return ""
}),
WithHTTPClient(&http.Client{Transport: rt}),
)
if p, ok := r.Provider(ProviderQwen); !ok {
t.Fatal("built-in qwen provider not registered")
} else if p.Name() != ProviderQwen {
t.Errorf("name = %q, want %q", p.Name(), ProviderQwen)
}
m, err := r.Parse("qwen/qwen3-max")
if err != nil {
t.Fatalf("Parse: %v", err)
}
if got := targetsOf(t, m); len(got) != 1 || got[0] != "qwen/qwen3-max" {
t.Fatalf("targets = %v", got)
}
if _, err := m.Generate(context.Background(), llm.Request{Messages: []llm.Message{llm.UserText("hi")}}); err != nil {
t.Fatalf("Generate: %v", err)
}
if rt.req == nil {
t.Fatal("no request captured")
}
if want := "https://dashscope-intl.aliyuncs.com/compatible-mode/v1/chat/completions"; rt.req.URL.String() != want {
t.Errorf("URL = %q, want %q", rt.req.URL.String(), want)
}
if want := "Bearer qwen-secret"; rt.req.Header.Get("Authorization") != want {
t.Errorf("Authorization = %q, want %q", rt.req.Header.Get("Authorization"), want)
}
}
// TestQwenBuiltinMissingKey: with no QWEN_API_KEY the built-in fails fast with
// a synthetic 401 whose hint names QWEN_API_KEY — never OPENAI_API_KEY (proving
// the credential does not fall through to the openai client's default), and
// without hitting the network.
func TestQwenBuiltinMissingKey(t *testing.T) {
rt := &captureRT{body: qwenResponse}
r := newTestRegistry(t, WithHTTPClient(&http.Client{Transport: rt}))
m, err := r.Parse("qwen/qwen3-max")
if err != nil {
t.Fatalf("Parse: %v", err)
}
_, err = m.Generate(context.Background(), llm.Request{Messages: []llm.Message{llm.UserText("hi")}})
apiErr, ok := errors.AsType[*llm.APIError](err)
if !ok {
t.Fatalf("err = %v (%T), want *llm.APIError", err, err)
}
if apiErr.Status != http.StatusUnauthorized || apiErr.Code != "missing_api_key" {
t.Errorf("Status/Code = %d/%q, want 401/missing_api_key", apiErr.Status, apiErr.Code)
}
if !strings.Contains(apiErr.Message, "QWEN_API_KEY") {
t.Errorf("message = %q, want it to name QWEN_API_KEY", apiErr.Message)
}
if strings.Contains(apiErr.Message, "OPENAI_API_KEY") {
t.Errorf("message = %q, must not name OPENAI_API_KEY", apiErr.Message)
}
if rt.req != nil {
t.Error("network was hit despite missing key")
}
}
// TestQwenBuiltinKeyDoesNotLeakToOpenAI: QWEN_API_KEY is the qwen built-in's
// credential and nothing else's. Why this direction too: the fallthrough guard
// only proves qwen never borrows OPENAI_API_KEY; this proves the reverse — a
// registry that can see QWEN_API_KEY must not hand it to the openai built-in,
// which would send an Alibaba key to api.openai.com.
func TestQwenBuiltinKeyDoesNotLeakToOpenAI(t *testing.T) {
// Set before newTestRegistry: the openai built-in reads OPENAI_API_KEY at
// construction. Giving it a real key is what keeps this test honest — a
// keyless openai target would 401 before any request, and the assertion
// below would pass without a single byte reaching the wire.
t.Setenv("OPENAI_API_KEY", "openai-secret")
rt := &captureRT{body: qwenResponse}
r := newTestRegistry(t,
WithEnvLookup(func(k string) string {
if k == "QWEN_API_KEY" {
return "qwen-secret"
}
return ""
}),
WithHTTPClient(&http.Client{Transport: rt}),
)
m, err := r.Parse("openai/gpt-4o-mini")
if err != nil {
t.Fatalf("Parse: %v", err)
}
if _, err := m.Generate(context.Background(), llm.Request{Messages: []llm.Message{llm.UserText("hi")}}); err != nil {
t.Fatalf("Generate: %v", err)
}
if rt.req == nil {
t.Fatal("no request captured")
}
if want := "Bearer openai-secret"; rt.req.Header.Get("Authorization") != want {
t.Errorf("Authorization = %q, want %q — the qwen credential must not reach the openai built-in",
rt.req.Header.Get("Authorization"), want)
}
}
// TestQwenScheme: a qwen:// LLM_* DSN defines a named provider on any Model
// Studio host (here the China endpoint) that is first-class in Parse and
// carries the DSN token as its bearer credential.
func TestQwenScheme(t *testing.T) {
rt := &captureRT{body: qwenResponse}
r := newTestRegistry(t, WithHTTPClient(&http.Client{Transport: rt}))
if err := r.LoadEnv(map[string]string{
"LLM_QCN": "qwen://[email protected]/compatible-mode/v1",
}); err != nil {
t.Fatalf("LoadEnv: %v", err)
}
m, err := r.Parse("qcn/qwen-plus")
if err != nil {
t.Fatalf("Parse: %v", err)
}
if _, err := m.Generate(context.Background(), llm.Request{Messages: []llm.Message{llm.UserText("hi")}}); err != nil {
t.Fatalf("Generate: %v", err)
}
if rt.req == nil {
t.Fatal("no request captured")
}
if want := "https://dashscope.aliyuncs.com/compatible-mode/v1/chat/completions"; rt.req.URL.String() != want {
t.Errorf("URL = %q, want %q", rt.req.URL.String(), want)
}
if want := "Bearer tok"; rt.req.Header.Get("Authorization") != want {
t.Errorf("Authorization = %q, want %q", rt.req.Header.Get("Authorization"), want)
}
}
// TestQwenSchemeMissingToken: a qwen:// DSN with no token is fixed by adding
// one to the DSN, not by setting QWEN_API_KEY — so the missing-key hint names
// the defining LLM_<NAME> env var, never QWEN_API_KEY (which does nothing for a
// DSN-defined provider).
func TestQwenSchemeMissingToken(t *testing.T) {
rt := &captureRT{body: qwenResponse}
r := newTestRegistry(t, WithHTTPClient(&http.Client{Transport: rt}))
if err := r.LoadEnv(map[string]string{
"LLM_QCN": "qwen://dashscope.aliyuncs.com/compatible-mode/v1", // no token
}); err != nil {
t.Fatalf("LoadEnv: %v", err)
}
m, err := r.Parse("qcn/qwen-plus")
if err != nil {
t.Fatalf("Parse: %v", err)
}
_, err = m.Generate(context.Background(), llm.Request{Messages: []llm.Message{llm.UserText("hi")}})
apiErr, ok := errors.AsType[*llm.APIError](err)
if !ok {
t.Fatalf("err = %v (%T), want *llm.APIError", err, err)
}
if !strings.Contains(apiErr.Message, "LLM_QCN") {
t.Errorf("message = %q, want it to name LLM_QCN", apiErr.Message)
}
if strings.Contains(apiErr.Message, "QWEN_API_KEY") {
t.Errorf("message = %q, must not name QWEN_API_KEY for a DSN provider", apiErr.Message)
}
if rt.req != nil {
t.Error("network was hit despite missing token")
}
}
// TestQwenReasoningEffortReachesWire is the load-bearing test for ADR-0027's
// central claim: Model Studio's OpenAI-compatible surface takes reasoning as a
// top-level "reasoning_effort" body field, which the openai client already
// sends — so llm.WithReasoningEffort survives the trip on qwen with no
// qwen-specific code. Routing qwen through the anthropic client instead would
// drop it silently (provider/anthropic ignores ReasoningEffort by design), and
// that difference would be invisible without asserting on the wire body.
func TestQwenReasoningEffortReachesWire(t *testing.T) {
rt := &captureRT{body: qwenResponse}
r := newTestRegistry(t,
WithEnvLookup(func(k string) string {
if k == "QWEN_API_KEY" {
return "qwen-secret"
}
return ""
}),
WithHTTPClient(&http.Client{Transport: rt}),
)
m, err := r.Parse("qwen/qwen3-max")
if err != nil {
t.Fatalf("Parse: %v", err)
}
_, err = m.Generate(context.Background(), llm.Request{
Messages: []llm.Message{llm.UserText("hi")},
ReasoningEffort: "high",
})
if err != nil {
t.Fatalf("Generate: %v", err)
}
if rt.reqBody == nil {
t.Fatal("no request body captured")
}
var sent map[string]any
if err := json.Unmarshal(rt.reqBody, &sent); err != nil {
t.Fatalf("decode request body: %v", err)
}
if got := sent["reasoning_effort"]; got != "high" {
t.Errorf("reasoning_effort = %v, want %q (body: %s)", got, "high", rt.reqBody)
}
}
+102
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@@ -0,0 +1,102 @@
# ADR-0027: Qwen (Alibaba) built-in provider — OpenAI-compat, not Anthropic-compat
**Status:** Accepted — 2026-08-12
## Context
Alibaba's Qwen models (`qwen3.8-max`, `qwen3.7-plus`, the `qwen3-vl-*` vision
variants, …) are served from Model Studio / DashScope, and mort wants them as a
first-class failover tier with a dedicated `QWEN_API_KEY` — the same ergonomics
ADR-0026 gave Kimi.
Unlike Kimi, Model Studio exposes the same models over **two** protocols:
| | OpenAI-compatible | Anthropic-compatible |
|---|---|---|
| Base URL | `https://dashscope-intl.aliyuncs.com/compatible-mode/v1` | `https://dashscope-intl.aliyuncs.com/apps/anthropic` |
| Endpoints | full Chat Completions surface | `/v1/messages` only (no `/v1/models`) |
| Purpose | the documented developer API | a shim, documented around hosting Claude Code |
So the question this ADR answers is not "which client do we reuse" but
"which of Alibaba's two wire protocols does the built-in speak".
## Decision
**The `qwen` built-in and the `qwen://` DSN scheme speak OpenAI-compat**, over
`provider/openai` — no new package, mirroring ADR-0026 (kimi) and ADR-0015
(llama-swap chat). Default base URL is the international host; the China host
(`dashscope.aliyuncs.com/compatible-mode/v1`) and workspace-scoped regional
hosts are reachable with a `qwen://` DSN.
Credential handling is copied from kimi verbatim, because both of its rules
are load-bearing: `WithAPIKey` is passed unconditionally (even empty) so an
unset `QWEN_API_KEY` can never fall through to `openai.New`'s `OPENAI_API_KEY`
default, and `WithAPIKeyName("QWEN_API_KEY")` makes the synthetic-401 hint name
the variable the operator actually has to set.
The kimi and qwen DSN factories were identical, so they now share one
`openaiCompatScheme` helper — the next OpenAI-compat built-in gets the
credential and key-hint rules by construction rather than by copy.
### Why not the Anthropic-compatible endpoint
Every concrete difference favors OpenAI-compat *for this codebase*:
- **Reasoning survives the trip.** Model Studio takes `reasoning_effort` as a
top-level field on the OpenAI surface, which `provider/openai` already sends
`llm.WithReasoningEffort` works on qwen with zero qwen-specific code
(`TestQwenReasoningEffortReachesWire` asserts it on the wire). Down the
anthropic client it would be dropped in silence: `provider/anthropic`
deliberately ignores `Request.ReasoningEffort`, because first-party Claude
has no such knob.
- **Structured output would regress.** `provider/anthropic` implements
`Request.Schema` with the first-party GA `output_config.format` mechanism.
Alibaba's shim does not implement it; a compat endpoint that ignores an
unknown field returns unconstrained prose while still reporting success.
The OpenAI path sends `response_format: json_schema`, which Model Studio
supports natively on the Max/Plus families.
- **Cache accounting already lands.** Model Studio's implicit prefix cache
reports hits in `usage.prompt_tokens_details.cached_tokens`, which the openai
client already maps to `llm.Usage.CacheReadTokens`. The anthropic client
reads `cache_read_input_tokens`, a field the shim has no reason to emit.
- **Thinking content is discarded on the anthropic path anyway.**
`provider/anthropic` skips `thinking` blocks in both the buffered and
streaming decoders, so the shim's headline feature — first-class
`thinking: {type: "enabled", budget_tokens: N}` — buys majordomo nothing
today.
- **Smaller blast radius.** The anthropic client has no `WithAPIKeyName`
option, so a keyless qwen would tell the operator to set `ANTHROPIC_API_KEY`;
fixing that means changing the first-party Anthropic client to serve a
third-party shim.
- **It is the less-exercised surface.** The Anthropic endpoint is documented as
Messages-only, with a temperature range that differs from Anthropic's own
([0, 2) vs [0.0, 1.0]) — i.e. it is Qwen semantics wearing an Anthropic
envelope, not an Anthropic-equivalent target.
The one thing the Anthropic surface offers that OpenAI-compat does not is
explicit `cache_control` breakpoints reached through `Request.PromptCache`.
That is not a reason to route Qwen through it: Model Studio's implicit cache is
automatic and already metered, and if explicit breakpoints ever matter they
belong in `provider/openai` (Model Studio accepts `cache_control` on content
blocks there too), where every OpenAI-compat target would get them.
## Consequences
- `qwen/<model>` is first-class in Parse, chains, aliases, and health/failover
with no consumer wiring; model ids pass through verbatim (no catalog).
- Chat, streaming, tools, structured output, reasoning effort, and cached-token
accounting all ride the openai client and inherit its fixes.
- Image *inputs* work at the client level, but only the `qwen-vl-*` /
`qwen3-vl-*` models accept them (matrix footnote ³, shared with kimi).
- Two model-side quirks are Alibaba's, not majordomo's, and are left to the
caller rather than papered over: thinking is **on by default** on some models
(e.g. `qwen3.7-plus`), and Qwen3 *open-source* models require streaming when
thinking is enabled — a buffered `Generate` against one of those needs a
model that supports non-streaming thinking (the Max/Plus families do).
- If a future consumer genuinely needs the Anthropic surface, it is reachable
today without library changes:
`LLM_QWEN_ANTHROPIC=anthropic://[email protected]/apps/anthropic`
— with the reasoning/structured-output caveats above.
- Second third-party built-in after kimi. The ADR-0026 bar still holds: a named
consumer needs it in-config. `RegisterProvider`/`LLM_*` remain the path for
everything else.
+1
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@@ -30,3 +30,4 @@ One decision per file, append-only; supersede rather than rewrite.
| [0024](0024-audio-wave3-surfaces.md) | Wave-3 audio surfaces (stems, SFX, speech enhance, voice clone, translate) | Accepted |
| [0025](0025-videogen-wave3-surfaces.md) | Wave-3 video surfaces (lipsync, video matte, video upscale, chain jobs) | Accepted |
| [0026](0026-kimi-builtin.md) | Kimi (Moonshot AI) built-in provider — reuse openai client, KIMI_API_KEY | Accepted |
| [0027](0027-qwen-builtin.md) | Qwen (Alibaba) built-in provider — OpenAI-compat, not Model Studio's Anthropic-compat endpoint | Accepted |
+29
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@@ -285,3 +285,32 @@ tests flush out.
(footnote ³), `.env.example`, ADR-0026 (+ index; also backfilled the missing
0024/0025 index rows).
- Consumer: mort names Kimi as a failover tier.
## 2026-08-12 — Qwen (Alibaba) built-in provider (ADR-0027)
- New built-in `qwen` provider + `qwen://` DSN scheme over Alibaba Model
Studio's OpenAI-compatible mode, reusing `provider/openai` (no new client,
mirrors kimi/llama-swap). Default base URL
`https://dashscope-intl.aliyuncs.com/compatible-mode/v1`; China/regional
hosts via `LLM_QCN=qwen://[email protected]/compatible-mode/v1`.
- Credential is `QWEN_API_KEY` (via the registry's injected envLookup).
`WithAPIKey` passed unconditionally so an unset key cannot fall through to
`OPENAI_API_KEY`; `WithAPIKeyName` names `QWEN_API_KEY` in the 401 hint.
- **Chose OpenAI-compat over Model Studio's Anthropic-compatible
`/apps/anthropic` shim** (ADR-0027): on the anthropic client
`ReasoningEffort` is ignored by design, `Request.Schema` rides
`output_config.format` (which the shim does not implement), and cached-token
accounting reads Anthropic-only usage fields. The shim is still reachable
ad hoc via an `anthropic://` DSN.
- kimi and qwen DSN factories were byte-identical, so they now share one
`openaiCompatScheme` helper — the credential + key-hint rules come by
construction, not by copy.
- Hermetic tests: built-in base URL + bearer, missing key names QWEN_API_KEY
with no OPENAI fallthrough and no network hit, the reverse leak (a visible
QWEN_API_KEY must not authenticate the openai built-in), `qwen://` round-trip
against the China host, its keyless hint naming LLM_QCN, and
`reasoning_effort` asserted on the wire body (the ADR's load-bearing claim).
captureRT now records the request body; all six break-checked.
- Docs in sync: README built-in table + Qwen paragraph + DSN scheme list +
support matrix (footnote ⁴), `.env.example`, ADR-0027 (+ index).
- Consumer: mort wants Qwen as a failover tier.