OpenCode Free returns HTTP 400 for muse-spark-1.3-contributor-free when tool_choice is non-auto. Declare forceAutoToolChoiceModels quirk and normalize explicit tool_choice to auto.
Forward images inside tool_result to OpenAI and Kiro upstreams via following user messages, restore original client tool names on Kiro responses via _toolNameMap, and preserve thinking display settings across translations.
Route union-alpha to /zen/v1/messages with targetFormat claude, add anthropic-version header, and register model capabilities (vision, 262K context, 131K max output).
- Declare deepseek-v4.1-flash and deepseek-flash as vision-capable in MODEL_CAPABILITIES
- Share installed catalogSource across route chunks via globalThis.__9rCatalogSource
- Scope catalog modality keys by provider:model to prevent cross-gateway collisions
- Upgrade catalog format to v2 with automatic rebuild of older schemas
Command Code dropped vision and ignored client effort through the router:
image blocks became "[image omitted]", HTTP image URLs were never inlined,
and reasoning_effort landed on the envelope wrapper instead of params (so the
DeepSeek family mapping remapped low -> high). The catalog also treated
deepseek/deepseek-v4.1-flash as text-only, so the vision adapter stole those
requests to another provider.
- Map OpenAI image_url / Claude image blocks (base64 or data-URI) to the
native {type:"image", image:"data:...;base64,...", mimeType} generate block.
- Add FORMATS.COMMANDCODE to TARGETS_NEED_BASE64 so remote http(s) images are
inlined by the existing SSRF-safe fetcher before translation.
- Write reasoning_effort inside params for targetFormat commandcode and pass
low|medium|high|xhigh|max through unmapped; allow it in thinkingLevels.
- Provider-scoped capabilities for commandcode/cmc: vision except the CLI
text-only denylist, thinkingFormat commandcode, so family patterns
(deepseek-v4 -> thinkingFormat deepseek, vision false) no longer win.
- Quota Tracker: whoami + billing credits/subscriptions (credits vs plan cap,
5h and weekly windows), labels from AI_PROVIDERS[].name.
codebuddy-intl: deepseek-v4-flash replaced by deepseek-v4.1-flash (same
gateway catalog as CN) and a capability override so the model keeps the
openai-style reasoning_effort path instead of the vendor-native "deepseek"
thinking shape the gateway rejects. Thinking levels low/high/xhigh.
ollama: add deepseek-v4.1-flash:cloud (verified on ollama.com/api/tags) with
vision + 1M context caps.
Co-Authored-By: Claude Code <noreply@anthropic.com>
Adds the Desktop-exclusive Preview models and the Xiaomi account-session
route to the existing xiaomi-mimo provider instead of a separate
xiaomi-desktop provider, so the dashboard shows one MiMo entry rather than
three overlapping ones.
Dual auth, same pattern as kimi — API key (sk-) covers the cloud API,
Desktop/OAuth adds the account session used by the Preview models:
- registry: category oauth, authModes [oauth, apikey], oauth block, the two
mimo-x-*-preview models, and the invite signupUrl
- executor: routes Preview models to the account-service route with a Cookie
session, everything else keeps the sourceFormat-matched transport
- oauth: custom ECDH encrypted-callback flow (X25519 -> SHA256 -> AES-256-GCM)
with a loopback callback proxy, plus one-click import of the local Desktop
auth.json
- usage: weekly quota from the account session
Fixes found while merging:
- the OAuth browser flow was dead: poll-status cleared the session before the
client could POST /exchange, so every exchange returned 400
- a Claude-format client was sent to /v1/chat/completions instead of the
declared /anthropic/v1/messages transport, because buildUrl ignored
runtimeTransport
- stopXiaomiMimoProxy leaked every pending session (each holding an X25519
private key) for the process lifetime
- the OAuth exchange did not persist the Desktop passToken, so the Preview
models could never work after a browser sign-in
Removes dead code: the local engine token minting (mimoEngine, never called
on the request path), the model-catalog and usage routes, engineToken/
engineUrl plumbing, and an unread top-level usage block.
Adds tests/unit/xiaomi-mimo-{executor,oauth-session,oauth-proxy}.test.js —
the provider previously had none.
qwen.js points at the same transport as alims-intl — identical baseUrl
(dashscope-intl compatible-mode), headers, and quirks — but carries only 8
Qwen models against alims-intl's broader catalog, so it adds nothing a user
could not already reach. Node count is back to 81.
The id was dropped on 2026-08-05 (dcdd4628b) when the Qwen OAuth flow died;
this removes the standalone API-key entry that shadowed it. The `qw` alias
returns to unassigned, its state before today.
Co-Authored-By: Claude Code <noreply@anthropic.com>
Registry order is the display order for the provider page, /v1/models, and the
CLI selector, so moving the entry to the head of `models` is the whole change.
deepseek-flash keeps its id and supportedFormats — only its position moves.
Co-Authored-By: Claude Code <noreply@anthropic.com>
defaultClaudeToolType() stamped tools[].type = "custom" onto every
Claude-format request carrying tools since e08ac6da. That satisfied
MiniMax (error 2013) but broke Anthropic-compatible endpoints that only
accept the legacy typeless tool shape. DeepSeek's endpoint
(api.deepseek.com/anthropic/v1/messages) whitelists its tool `type` enum
to the web_search_* variants and answers HTTP 400 "unknown variant
`custom`", so every Claude Code request routed to a DeepSeek connection
failed and surfaced as a persistent 503.
Run the defaulting only when the target provider declares the new
requireClaudeToolType quirk (MiniMax, MiniMax-CN). Add
shouldDefaultClaudeToolType(provider, finalFormat, tools, PROVIDERS) in
translator/concerns/toolCall.js so the gate is unit-testable, and cover
MiniMax keeping the explicit type, DeepSeek/Anthropic staying typeless,
non-Claude formats and tool-less requests never defaulting.
Effectively a no-op for MiniMax and a restore of the pre-e08ac6da
behaviour everywhere else. Another strict gateway now only needs the same
one-line quirk instead of a global behavioural change.
Cline (api.cline.bot) wraps non-stream chat completions in
{"success":true,"data":{...choices...}}, which both the dashboard model-test
ping and the proxy non-stream path read at top level, producing "Provider
returned no completion choices for this model" (#3644). Unwrap the envelope
before usage extraction and response translation; the error envelope
({"success":false,...}) never matches and passes through untouched.
Scoped through `transport.quirks.clineEnvelope` so only cline/clinepass opt
in — no other provider's response body is ever rewritten.
Also adds a live Cline catalog: `fetchClineRawModels()` is shared between
`resolveClineModels()` (full catalog, including free-tier ids such as
z-ai/glm-5.3-flash) and `resolveClinepassModels()` (cline-pass/* only), wired
into /v1/models, the per-provider models route, and the combo selector's
model picker with the static catalog kept as fallback.
Refreshes the dead api-airforce free models (anthropic/claude-3.7-sonnet,
moonshot/kimi-k2.6, google/gemini-2.5-flash) with the live gpt-oss-120b,
gpt-oss-20b and kimi-k2.7-code, plus passthroughModels, forceStream and a
suggested-models filter.
Cline/ClinePass requests failed with HTTP 401 ("Please make sure you are using
the latest version of Cline and re-authenticate your Cline account", #3230 /
#2333 / #3644). `getClineAccessToken()` unconditionally prefixed every token
with `workos:`, which is correct for Cline OAuth access tokens (WorkOS JWTs)
but wrong for ClinePass API keys — those are opaque strings (e.g. `clp_…`)
that the API accepts only verbatim, so the `workos:`-prefixed value was
rejected.
Only prefix tokens that look like a WorkOS JWT (`eyJ…`); API keys and other
opaque tokens pass through untouched, and an existing `workos:` prefix is
never doubled.
Also register `clinepass` in the token-refresh handlers. ClinePass shares
Cline's WorkOS auth endpoints, but without the entry expired ClinePass OAuth
tokens were never rotated, so every request kept 401ing. Finally, list
`apikey` first in the ClinePass `authModes` (ClinePass is meant to be used
with an API key from app.cline.bot/settings/api-keys), and add an "Import
from /models" button that pulls the live Cline catalog into custom models.
DeepSeek's Anthropic-compatible endpoint accepts only the built-in
web_search_20250305 / web_search_20260209 tools and rejects client-defined
`custom` tools (MCP / Read / Bash) with HTTP 400 "unknown variant `custom`".
The generic non-Claude filter in prepareClaudeRequest dropped the offending
tools but also dropped the web_search_* ones DeepSeek does accept.
- Add an opt-in per-provider transport quirk `claudeSupportedToolTypes`; when
declared it becomes a strict allow-list for Anthropic tool `type` values
- Stop stripping the `type` discriminator from surviving tools under that
quirk, since DeepSeek needs it to route built-ins
- Declare the quirk on the deepseek transport with the two web_search_* types
- Providers without the quirk keep the previous filter and normalisation
behaviour byte-for-byte; openai-format targets never reach this path
- Coalesce Qoder's empty finish-in-delta frame with the later choices:[] usage
frame so OpenAI and Claude clients receive prompt_tokens, completion_tokens
and cache-hit tokens (the dashboard already saw them)
- Upload inlined images through /api/v2/image/upload like qodercli, and stub
oversized non-image files instead of stuffing 30MB+ data URIs into
agent_chat_generation
- Emit response.completed -> response.usage for chat-native upstreams so
/v1/responses clients (Codex CLI, sub2api) no longer log 0/0/0
- Keep Claude message_delta.usage working when usage arrives without choices[0]
- Escalate to the smallest advertised Qoder context tier (200K/400K/1M) when
the estimated prompt no longer fits max_input_tokens
- Pass apiKey for PAT connections and list hidden enable:false catalog keys
from /v1/models
- Add gpt-image-1.5, gpt-image-2, gpt-image-2.5, gpt-image-2.5-flare and
gpt-image-2.5-sunburst as Codex image models with multi-image support
- Add gpt-image-2.5, gpt-image-2.5-flare and gpt-image-2.5-sunburst to the
OpenAI provider catalog
- Route tool-backed image models through the Codex responses model while
passing the selected model to the image_generation tool, pinning
tool_choice and deriving generate/edit from the presence of references
- Cover the Codex gpt-image-2.5 request shape with a unit test
Video generation was xAI-only. Adds an adapter layer under
open-sse/handlers/videoProviders/ so /v1/videos/* can target OpenRouter or
Google Cloud credentials. A provider with no adapter keeps the exact previous
behaviour (raw body to {baseUrl}/{action}, poll {baseUrl}/{id}, verbatim
passthrough), so the xAI path is unchanged.
- openrouter: async job shape identical to xAI; creation POSTs to the /videos
collection root (no /generations suffix) and the registry HTTP-Referer /
X-Title headers are applied. Bodies pass through verbatim.
- vertex: two-way translation, since Veo does not speak the OpenAI-ish videos
shape. create -> :predictLongRunning { instances[], parameters{} }, poll ->
:fetchPredictOperation (Veo has no REST GET poll). The operation resource
name is base64url-encoded into the job id so GET /v1/videos/{id} stays a
flat path. Access tokens are minted from Service Account JSON via the
existing refreshVertexToken; raw API keys are rejected up front. The
operation response maps back onto the { id, status, video, videos } shape
clients already poll.
- videoCore: the request plan is rebuilt per attempt, so the 401 -> refresh
once -> retry once path picks up the refreshed token. Adapter validation
errors return 400 before any upstream call, so a malformed request can never
create a billable job.
- videoGeneration: GET /v1/videos/{id} resolves the provider from the pinned
x-connection-id connection, then ?provider=, then falls back to the xAI
default.
- registry: openrouter and vertex gain videoConfig, the video serviceKind and
video-kind models (Veo 3.1 / 3 / 2, Sora 2 Pro, Seedance 2.0).
The server's product-config payload (which the IDE plugin fetches from
copilot.tencent.com) publishes deepseek-v4.1-flash and no longer lists
deepseek-v4-flash, so the old id is dropped — same pattern as the previous
catalog refreshes (#3648, #3802). The v4-flash endpoint still answers 200,
but the published list is the contract.
Per the server table, maxOutput rises 50000 -> 128000 while contextWindow
stays 1000000.
- registry/codebuddy-cn.js: models[] entry swapped to the new id
- capabilities.js: per-model entry swapped, maxOutput -> 128000
No changes needed in thinkingLevels.js (the deepseek-v4* pattern already
matches the new id and publishes low/high/xhigh, matching the server's
supportedEfforts or pricing.js (the deepseek-v* glob yields the same rates).
EOF
)
The image handler's `version` header was commented out, so Codex image
requests reached chatgpt.com without the Version identity the backend
expects. Restore it and route every Codex identity header through one
constant.
The CLI version now lives on registry codex.transport as `cliVersion`
(the same pattern gemini-cli uses) and is re-exported as CODEX_CLI_VERSION,
so the registry User-Agent, the image handler and the connection test can
no longer drift apart. Bumped 0.136.0 -> 0.154.0 (current stable).
Co-Authored-By: Claude Code <noreply@anthropic.com>
Add the models the provider docs now list but the registry lacked:
chat/completions glm-5.3, kimi-k3, deepseek-flash, longcat-2.0,
hy4-preview, hy3
+ /messages qwen3.8-max, qwen3.8-flash
responses only grok-4.6, gpt-5.6-luna
Endpoints follow the table at https://opencode.ai/docs/go/. chat-only
models stay on the sourceFormat-matched transport guard so a Claude
client is never routed to /messages for a model that lacks it.
Co-Authored-By: Claude Code <noreply@anthropic.com>
- Add muse-spark-1.2-contributor as responses-only model on OpenCode Go
- Normalize object tool schemas without properties in OpenCode Go executor
- Make fallback Responses call_ids unique across same-millisecond calls
- Make Responses output coercion fail-soft for circular and non-stringifiable values
- Add muse-spark-1.3-contributor as responses-only model on OpenCode Go with dedicated executor
- Key Responses→chat streaming tool calls by item_id to prevent parallel tool calls merging into index 0
- Standardize tool coercions and call_id clamping in Responses API translation
- Sync codebuddy-cn catalog and capabilities with copilot.tencent.com server payload
- Fix thinkingCanDisable semantics for glm-5.3 and deepseek-v4 models
- Add missing glm-5.2 thinking levels to thinkingLevels.js
- Add glm-5-turbo model to glm and glm-cn registries
- Registry/constants: drop qmodel_preview/gm51model, add lite,
qmodel_38max (Qwen3.8-Max), qfmodel (Qwen3.8-Flash), gmodel (GLM-5.3),
gfmodel (GLM-5.3-Flash)
- capabilities: add PROVIDER_CAPABILITIES['qoder'] so opaque internal
ids resolve to their real models' context windows and limits
- executor: preserve image blocks instead of flattening away, convert
Claude-style image blocks, and hash images into chat_record_id
- tests: cover image preservation, data-URI and Claude-block conversion
- build(docker): use CN mirrors for apk and npm
Route all Muse Spark models (not just 1.2) on OpenCode Free to
/zen/v1/responses via isMuseSparkModel(), fixing HTTP 500 on
muse-spark-1.3-contributor-free. Declare vision:true on Muse Spark
models so image input is no longer stripped; register 1.3 in the
registry and capabilities. Scoped to opencode only — other providers
keep Chat Completions routing.
- add claude-fable-5-1 to the Claude Code model catalog (1M context,
permanent adaptive thinking)
- centralize the spoofed Claude Code version and update both request
and billing identities to 2.1.257 (Fable 5.1 rejects < 2.1.251)
- send output_config.effort without the redundant thinking switch for
permanently adaptive models
- add regression coverage for capabilities, headers, billing identity
and adaptive-effort payload
# Conflicts:
# open-sse/providers/registry/claude.js
# open-sse/providers/shared.js
# open-sse/utils/claudeCloaking.js
# tests/__baseline__/providers-baseline.json
Anthropic gates newly released models (e.g. claude-fable-5-1) to Claude
Code >= 2.1.251; the spoofed 2.1.92 client got HTTP 400 on every request.
Bump User-Agent + billing-header version to 2.1.258 and refresh the
providers baseline snapshot.
Co-Authored-By: Claude Code <noreply@anthropic.com>
The separate zai-search entry showed "No connections" on the web search
page because credentials live on the `glm` connection, not on it. Every
other provider that does both chat and search (antigravity, kimi, xai,
gemini) declares webSearch on the provider itself, so do the same here.
- glm gains serviceKinds ["llm", "webSearch"] and the MCP searchConfig
- the request builder / normalizer move from "zai-search" to "glm"
- drop the zai-search registry entry and its svg logo, which also
removes the only need for svg logo support in getProviderIconSrc
ollama-search keeps its own entry and credentialFallback: its search
endpoint is unrelated to the ollama chat transport.
Register two web search providers that reuse an existing chat provider's
API key instead of requiring their own connection:
- ollama-search (POST ollama.com/api/web_search) reuses the `ollama` key
- zai-search (POST api.z.ai MCP web_search_prime) reuses the `glm` key
A new `credentialFallback` registry field drives this: when a search
provider has no connection of its own, the search handler falls back to
the linked chat provider's credentials.
Also teach getProviderIconSrc to serve .svg logos for providers that
ship vector art.
Z.ai / GLM-5.2+ require a top-level reasoning_effort (low/high/max)
alongside thinking:{type:"enabled"} to control reasoning depth; the zai
branch previously only set thinking and dropped reasoning_effort, so every
GLM-5.x request ran at the model default (max). Gate the field behind
GLM-5.2+ (thinkingEffortSupported in capabilities.js) since older GLM
(4.x, 5.0, 5.1, 5-turbo, 5v-turbo) do not read it, and map client levels
to the exact low/high/max values z.ai accepts.
extractThinking now checks reasoning_effort/reasoning.effort before the
thinking object so a client-supplied effort is not overwritten by
thinking:{type:"enabled"} mapping to mode:auto.
Fixes#2721
muse-spark-1.2-contributor-free returned HTTP 500 on /zen/v1/chat/completions.
The model is only served by /zen/v1/responses, so route it there via a per-model
targetFormat and normalize the Chat fields the Responses API rejects
(max_tokens -> max_output_tokens, reasoning_effort -> reasoning{effort,summary}),
clamping max/ultra down to the highest effort the model accepts (xhigh).
Routing stays per-model: the other free models (big-pickle, hy3-free, mimo,
nemotron, laguna) are not served by /responses and keep /chat/completions.
Route POST /v1/search with provider "antigravity" through Google Search
grounding on v1internal:generateContent, using the existing Antigravity
OAuth account pool. Grounding chunks become citations with the grounded
sentence as snippet and its surrounding answer text as content.
Upstream repeats a source across chunks, so citations are keyed by URL
and their snippets merged. A missing projectId is reported up front —
upstream answers a fabricated or absent project with a misleading
"no valid license" 403.
Based on the approach in #3437 by @Nautilaceae.
Capability tables are hand-maintained, so a model gains vision or a wider
context only when someone notices and edits the file. This adds a daily
sync that fills the gap for models already in the registry.
How it decides:
- Modalities (vision/pdf/audio/video) belong to the MODEL — every gateway
serving glm-5.3-flash serves the same weights — so they are keyed by
model id and shared. A majority of sources must declare one, which keeps
out lone mis-declarations: minimax-m2.5 (1 of 45), glm-4.7 (1 of 44) and
gpt-oss-120b (2 of 76) are text-only despite a reseller claiming vision.
- Context/output limits belong to the GATEWAY — each truncates differently
(glm-5 ships as 202752/16384 on one host and 204800/131072 on another) —
so they are keyed by provider + model and only the matching provider's
own numbers are trusted.
Both layers are strictly additive and sit BELOW the hand-written tables,
which short-circuit first. A capability already true stays true.
Mechanics: worker thread (the 4MB parse would block the loop ~20ms),
ETag so an unchanged catalog costs one empty request, 60s startup delay,
30min backoff on failure, MODEL_CATALOG_SYNC=off to disable. Only the
~57KB delta is kept; lookups cost ~0.1us via an mtime-guarded cache.
capabilities.js is bundled into the browser through useModelCaps, so it
cannot import node:fs — the server injects the reader via
setCatalogSource() from instrumentation.
visionPatterns.js is the last resort: a model nobody has catalogued yet
still accepts images when its id says so (qwen3-vl-plus, glm-4.6v, llava),
with image-generation and embedding ids excluded.
Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
Vendors shipped four multimodal models the registry did not carry:
- glm-5.3-flash — z.ai's first natively multimodal GLM-5, 1M context,
image + video + pdf input (glm, glm-cn, opencode-go)
- deepseek-v4-flash-vision-exp — image input at V4-Flash text parity,
1M context / 384k output (deepseek, opencode-go)
- grok-4.6, grok-4.5 — 500k context; 4.6 has no text output limit (xai)
Capabilities needed hand entries because the existing globs mis-matched:
*glm-5* and *deepseek-v4* carry no vision, and *grok-4* would have capped
grok-4.6 at 256k instead of 500k. The grok-4.6 pattern sits above the
generic *grok-4* so it wins the first-match lookup.
Also corrects glm-4.6v / glm-4.5v, which were missing video input and
declared no maxOutput, and backfills glm-4.6v on glm-cn — zhipuai serves
it and the sibling provider already listed it.
tests/unit/opencode-go-models.test.js pins the opencode-go model list, so
its expected array moves with the registry.
Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
Xquik needs a GET request with x-api-key auth and a tweets envelope
normalizer, neither of which the generic search fallback provides. Adds a
dedicated request builder and normalizer, cursor pagination passthrough,
result-based credit usage reporting, and a validateUrl probe so key
validation hits the no-charge credits endpoint.
opencode-go hard-coded targetFormat: claude per model, so every client
format was force-routed to /messages (Codex/OpenAI clients paid a lossy
Responses->OpenAI->Claude double translation). Declare the existing
upstream multi-endpoint transports [openai, claude, openai-responses]
and guard per model via registry supportedFormats: kimi/glm/mimo only
support /chat/completions, minimax/qwen add /messages, deepseek adds
/responses. Undeclared models keep the upstream default.
Drop the bespoke OpenCodeGoExecutor (its shared _lastModel cache could
cross auth headers between concurrent requests); DefaultExecutor already
consumes runtimeTransport and injects reasoning content.
Fourth Alibaba key type — Coding Plan (alicode/alicode-intl) and Model Studio
(alims-intl) both reject Token Plan keys. Registry entry only; PROVIDER_MODELS
builds from providers/registry so no executor or translator work is needed.
Singapore-only (eu-central-1 answers IllegalEndpoint) and OpenAI-compatible
transport only (the Anthropic surface is not authorized for this plan).
Closes#2754Closes#2806
Add gemini-3.7-flash and its tiered high/medium/low variants to the
Antigravity and Gemini registries, with matching capabilities, pricing
and Antigravity quota tracking.
extractModel now recognises gemini-3.7-flash-tiered alongside 3.6 and
derives the version from the request, so thinkingLevel still maps to the
right tiered alias.
Closes#3286Closes#3281
Registry entry plus one config-driven FORMAT_HANDLERS handler. The model id
travels in an HTTP `model` header rather than the JSON body, and the voice is
a reference_id (preset or cloned voice model).
Closes#2411
Zhipu released GLM-5.3 on both api.z.ai and open.bigmodel.cn coding
endpoints. Verified live against both, returning model:"glm-5.3" with
native reasoning_content.
No other changes needed: the '*glm-5*' family pattern in capabilities.js
and 'glm-5*' in pricing.js already cover it.
Kimchi's transport is OpenAI-compatible (Authorization: Bearer) but the
registry declared it OAuth-only, so the dashboard, /api/providers, and
the connection test all rejected API keys. Enable dual auth
(authModes: ["oauth", "apikey"]) and add a kimchi case to
testApiKeyConnection so the Test Connection button works for both modes.
Regenerate the golden snapshot with the Kimchi entries (+ other
previously-missing providers).
KunN-21
Manan Santoki
Hermes Agent
izzzzzi
KhuatHieu
decoluaandClaude Code
叶炜朋
galiehneh
Nick Nyanjui
kimono381
LLL
Hai Trinh
coozgan
zmf
617929zcxc
Christian Gennari
Sina Sadeghi
JOJO
An Nguyen
hangyu
Sami Basra
anojndr
LucasOl1337
openhands
qingyong
kriptoburak
KiMelody
Nguyen Thanh Dat
Azriel Akbar Ferry Ardiansyah Kusumawardhana
Fadjrir Herlambang