chore: merge v2 into service channel config
This commit is contained in:
commit
e76b29c0b4
1174 changed files with 21121 additions and 336917 deletions
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@ -1,6 +1,6 @@
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---
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||||
description: translate English to other languages
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||||
model: opencode/claude-opus-4-8
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||||
model: opencode/gpt-5.6-sol
|
||||
---
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||||
|
||||
run git diff and translate changed english doc and UI copy files to other international languages. Translate all languages in parallel to save time.
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||||
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@ -8,6 +8,25 @@ export const zoneID = "430ba34c138cfb5360826c4909f99be8"
|
|||
export const awsStage = $app.stage === "production" ? "production" : "dev"
|
||||
export const deployAws = $app.stage === awsStage
|
||||
|
||||
if ($app.stage === "production") {
|
||||
new cloudflare.DnsRecord("TrustCenter", {
|
||||
zoneId: zoneID,
|
||||
name: "trust.opencode.ai",
|
||||
type: "CNAME",
|
||||
content: "3a69a5bb27875189.vercel-dns-016.com",
|
||||
proxied: false,
|
||||
ttl: 60,
|
||||
})
|
||||
|
||||
new cloudflare.DnsRecord("TrustCenterVerification", {
|
||||
zoneId: zoneID,
|
||||
name: "opencode.ai",
|
||||
type: "TXT",
|
||||
content: "compai-domain-verification=org_6993a99c6200a2d642bb115d",
|
||||
ttl: 60,
|
||||
})
|
||||
}
|
||||
|
||||
new cloudflare.RegionalHostname("RegionalHostname", {
|
||||
hostname: domain,
|
||||
regionKey: "us",
|
||||
|
|
|
|||
|
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@ -8,6 +8,8 @@
|
|||
makeWrapper,
|
||||
writableTmpDirAsHomeHook,
|
||||
autoPatchelfHook,
|
||||
copyDesktopItems,
|
||||
makeDesktopItem,
|
||||
opencode,
|
||||
}:
|
||||
let
|
||||
|
|
@ -27,9 +29,12 @@ stdenv.mkDerivation (finalAttrs: {
|
|||
nodejs
|
||||
makeWrapper
|
||||
writableTmpDirAsHomeHook
|
||||
] ++ lib.optionals stdenv.hostPlatform.isLinux [
|
||||
]
|
||||
++ lib.optionals stdenv.hostPlatform.isLinux [
|
||||
autoPatchelfHook
|
||||
] ++ lib.optionals stdenv.hostPlatform.isDarwin [
|
||||
copyDesktopItems
|
||||
]
|
||||
++ lib.optionals stdenv.hostPlatform.isDarwin [
|
||||
# Ad-hoc sign the .app: --config.mac.identity=null below skips signing.
|
||||
darwin.autoSignDarwinBinariesHook
|
||||
];
|
||||
|
|
@ -38,20 +43,37 @@ stdenv.mkDerivation (finalAttrs: {
|
|||
(lib.getLib stdenv.cc.cc)
|
||||
];
|
||||
|
||||
desktopItems = lib.optional stdenv.hostPlatform.isLinux (makeDesktopItem {
|
||||
name = "ai.opencode.desktop";
|
||||
desktopName = "OpenCode";
|
||||
exec = "opencode-desktop %U";
|
||||
icon = "ai.opencode.desktop";
|
||||
# Electron 41 derives X11 WM_CLASS from app.name.
|
||||
startupWMClass = "OpenCode";
|
||||
categories = [ "Development" ];
|
||||
});
|
||||
|
||||
env = opencode.env // {
|
||||
ELECTRON_SKIP_BINARY_DOWNLOAD = "1";
|
||||
};
|
||||
|
||||
# https://github.com/electron/electron/issues/31121
|
||||
# mac builds use a .app bundle which doesnt have this issue
|
||||
postPatch = lib.optionalString stdenv.isLinux ''
|
||||
BASE_PATH=packages/desktop
|
||||
FILES=(src/main/windows.ts)
|
||||
for file in "''${FILES[@]}"; do
|
||||
substituteInPlace $BASE_PATH/$file \
|
||||
--replace-fail "process.resourcesPath" "'$out/opt/opencode-desktop/resources'"
|
||||
done
|
||||
'';
|
||||
postPatch =
|
||||
# NOTE: Relax Bun version check to be a warning instead of an error
|
||||
''
|
||||
substituteInPlace packages/script/src/index.ts \
|
||||
--replace-fail 'throw new Error(`This script requires bun@''${expectedBunVersionRange}' \
|
||||
'console.warn(`Warning: This script requires bun@''${expectedBunVersionRange}'
|
||||
''
|
||||
# https://github.com/electron/electron/issues/31121
|
||||
# mac builds use a .app bundle which doesnt have this issue
|
||||
+ lib.optionalString stdenv.isLinux ''
|
||||
BASE_PATH=packages/desktop
|
||||
FILES=(src/main/windows.ts)
|
||||
for file in "''${FILES[@]}"; do
|
||||
substituteInPlace $BASE_PATH/$file \
|
||||
--replace-fail "process.resourcesPath" "'$out/opt/opencode-desktop/resources'"
|
||||
done
|
||||
'';
|
||||
|
||||
preBuild = ''
|
||||
cp -r "${electron.dist}" $HOME/.electron-dist
|
||||
|
|
@ -76,27 +98,38 @@ stdenv.mkDerivation (finalAttrs: {
|
|||
runHook postBuild
|
||||
'';
|
||||
|
||||
installPhase =
|
||||
''
|
||||
runHook preInstall
|
||||
''
|
||||
+ lib.optionalString stdenv.hostPlatform.isDarwin ''
|
||||
mkdir -p $out/Applications
|
||||
mv dist/mac*/*.app $out/Applications
|
||||
makeWrapper "$out/Applications/OpenCode.app/Contents/MacOS/OpenCode" $out/bin/opencode-desktop
|
||||
''
|
||||
+ lib.optionalString stdenv.hostPlatform.isLinux ''
|
||||
mkdir -p $out/opt/opencode-desktop
|
||||
cp -r dist/linux*-unpacked/{resources,LICENSE*} $out/opt/opencode-desktop
|
||||
makeWrapper ${lib.getExe electron} $out/bin/opencode-desktop \
|
||||
--inherit-argv0 \
|
||||
--set ELECTRON_FORCE_IS_PACKAGED 1 \
|
||||
--add-flags $out/opt/opencode-desktop/resources/app.asar \
|
||||
--add-flags "\''${NIXOS_OZONE_WL:+\''${WAYLAND_DISPLAY:+--ozone-platform-hint=auto --enable-features=WaylandWindowDecorations --enable-wayland-ime=true}}"
|
||||
''
|
||||
+ ''
|
||||
runHook postInstall
|
||||
'';
|
||||
installPhase = ''
|
||||
runHook preInstall
|
||||
''
|
||||
+ lib.optionalString stdenv.hostPlatform.isDarwin ''
|
||||
mkdir -p $out/Applications
|
||||
mv dist/mac*/*.app $out/Applications
|
||||
makeWrapper "$out/Applications/OpenCode.app/Contents/MacOS/OpenCode" $out/bin/opencode-desktop
|
||||
''
|
||||
+ lib.optionalString stdenv.hostPlatform.isLinux ''
|
||||
mkdir -p $out/opt/opencode-desktop
|
||||
cp -r dist/linux*-unpacked/{resources,LICENSE*} $out/opt/opencode-desktop
|
||||
install -Dm644 resources/icons/32x32.png \
|
||||
"$out/share/icons/hicolor/32x32/apps/ai.opencode.desktop.png"
|
||||
install -Dm644 resources/icons/64x64.png \
|
||||
"$out/share/icons/hicolor/64x64/apps/ai.opencode.desktop.png"
|
||||
install -Dm644 resources/icons/128x128.png \
|
||||
"$out/share/icons/hicolor/128x128/apps/ai.opencode.desktop.png"
|
||||
install -Dm644 resources/icons/128x128@2x.png \
|
||||
"$out/share/icons/hicolor/256x256/apps/ai.opencode.desktop.png"
|
||||
install -Dm644 resources/icons/icon.png \
|
||||
"$out/share/icons/hicolor/512x512/apps/ai.opencode.desktop.png"
|
||||
install -Dm644 resources/ai.opencode.desktop.metainfo.xml \
|
||||
"$out/share/metainfo/ai.opencode.desktop.metainfo.xml"
|
||||
makeWrapper ${lib.getExe electron} $out/bin/opencode-desktop \
|
||||
--inherit-argv0 \
|
||||
--set ELECTRON_FORCE_IS_PACKAGED 1 \
|
||||
--add-flags $out/opt/opencode-desktop/resources/app.asar \
|
||||
--add-flags "\''${NIXOS_OZONE_WL:+\''${WAYLAND_DISPLAY:+--ozone-platform-hint=auto --enable-features=WaylandWindowDecorations --enable-wayland-ime=true}}"
|
||||
''
|
||||
+ ''
|
||||
runHook postInstall
|
||||
'';
|
||||
|
||||
autoPatchelfIgnoreMissingDeps = [
|
||||
"libc.musl-x86_64.so.1"
|
||||
|
|
|
|||
|
|
@ -1,8 +1,8 @@
|
|||
{
|
||||
"nodeModules": {
|
||||
"x86_64-linux": "sha256-F1luclnqCPQk9yxfmeSYGaM/nScf28yBu9K3Fv+Xd24=",
|
||||
"aarch64-linux": "sha256-XW0XZnsCRkU3MFJH9TjMRYZHffzVy3cQyiNCkec2gl4=",
|
||||
"aarch64-darwin": "sha256-bf8kvORs3Fs2UYLp3PekF+AJR7NKOcHb+fIQA79RtMk=",
|
||||
"x86_64-darwin": "sha256-sBdQPkzd7JXNW6Lbi9JHiAsfHwdLwTKWY+uPeXAv2Nw="
|
||||
"x86_64-linux": "sha256-qt11SKmOjq0KU542QFbs+u7YyJicn4drCcwCdg325yk=",
|
||||
"aarch64-linux": "sha256-z68doReXTrWS7HeiAjc0btIjAsvzeZZ7hXAlHr0c77Q=",
|
||||
"aarch64-darwin": "sha256-PILYH1Pi8XBvSkuZ+1sNnUTao5kba+m5Z8iJKx6YXPo=",
|
||||
"x86_64-darwin": "sha256-KpcJzP4m0SUavu/WaSffgzOxrHq8ljdy0GOzs9p16lo="
|
||||
}
|
||||
}
|
||||
|
|
|
|||
|
|
@ -29,22 +29,149 @@ Run `LLMClient.stream(request)` instead of `generate` when you want incremental
|
|||
Use `Image.generate` with an image model for direct asset generation:
|
||||
|
||||
```ts
|
||||
import { Image } from "@opencode-ai/ai"
|
||||
import { Image, ImageInput } from "@opencode-ai/ai"
|
||||
import { OpenAI } from "@opencode-ai/ai/providers"
|
||||
|
||||
const program = Effect.gen(function* () {
|
||||
const response = yield* Image.generate({
|
||||
model: OpenAI.configure({ apiKey: process.env.OPENAI_API_KEY }).image("gpt-image-2"),
|
||||
prompt: "A robot tending a rooftop garden",
|
||||
count: 2,
|
||||
size: { width: 1024, height: 1024 },
|
||||
providerOptions: { openai: { quality: "high", outputFormat: "webp" } },
|
||||
options: {
|
||||
n: 2,
|
||||
size: "1024x1024",
|
||||
quality: "high", // inferred from the OpenAI image model
|
||||
outputFormat: "webp",
|
||||
future_option: true, // unknown native options pass through unchanged
|
||||
},
|
||||
})
|
||||
|
||||
return response.images // GeneratedImage[] with owned bytes or a provider URL
|
||||
})
|
||||
```
|
||||
|
||||
Pass ordered image inputs to the same method for editing, composition, or image-conditioned generation:
|
||||
|
||||
```ts
|
||||
const response =
|
||||
yield *
|
||||
Image.generate({
|
||||
model,
|
||||
prompt: "Combine these product photos into one studio scene",
|
||||
images: [
|
||||
ImageInput.bytes(firstBytes, "image/png"),
|
||||
ImageInput.url("https://example.com/second.webp"),
|
||||
ImageInput.file("file_123"),
|
||||
],
|
||||
options,
|
||||
http,
|
||||
})
|
||||
```
|
||||
|
||||
`ImageInput.fileUri(uri, mediaType)` represents provider file URIs such as Gemini Files. Raw strings are not
|
||||
accepted as image inputs, avoiding ambiguity between base64, URLs, and provider IDs. Empty or omitted `images`
|
||||
uses text-to-image generation; a non-empty array selects the provider's edit behavior without enforcing provider
|
||||
image-count limits locally. `images` is the only common image-editing field. OpenAI uses multipart for byte/data-URL
|
||||
edits and its JSON reference body for URL or file-ID edits. Its provider-specific `options.mask` accepts an
|
||||
`ImageInput` for inpainting:
|
||||
|
||||
```ts
|
||||
yield *
|
||||
Image.generate({
|
||||
model: OpenAI.configure({ apiKey }).image("gpt-image-2"),
|
||||
prompt,
|
||||
images: [ImageInput.bytes(sourceBytes, "image/png")],
|
||||
options: { mask: ImageInput.bytes(maskBytes, "image/png") },
|
||||
})
|
||||
```
|
||||
|
||||
The OpenAI adapter extracts this helper value into the edit request's native `mask` field rather than passing the
|
||||
tagged `ImageInput` object through as an ordinary option. On multipart requests, `http.body` can override option
|
||||
fields but not structural `model`, `prompt`, `image[]`, or `mask` fields, and the transport owns the multipart
|
||||
`Content-Type` boundary. For JSON requests, `http.body` remains the final raw-native overlay. Gemini does not fetch
|
||||
public HTTP URLs, and hosted Z.ai image generation does not accept image inputs. These cases fail with
|
||||
`InvalidRequest` before network I/O.
|
||||
|
||||
Provider-native image options belong to each request. Raw `http.body` fields have final precedence over them:
|
||||
|
||||
```ts
|
||||
const model = OpenAI.configure({ apiKey }).image("gpt-image-2")
|
||||
|
||||
yield *
|
||||
Image.generate({
|
||||
model,
|
||||
prompt,
|
||||
options: { quality: "medium" },
|
||||
http,
|
||||
})
|
||||
```
|
||||
|
||||
xAI image models use the same request API with xAI-native controls:
|
||||
|
||||
```ts
|
||||
yield *
|
||||
Image.generate({
|
||||
model: XAI.configure({ apiKey }).image("any-model-id"),
|
||||
prompt,
|
||||
options: {
|
||||
n: 2,
|
||||
aspectRatio: "16:9",
|
||||
resolution: "1k",
|
||||
responseFormat: "b64_json",
|
||||
future_option: true,
|
||||
},
|
||||
http,
|
||||
})
|
||||
```
|
||||
|
||||
Google's current Gemini image models use the same direct API:
|
||||
|
||||
```ts
|
||||
import { Google } from "@opencode-ai/ai/providers"
|
||||
|
||||
const googleProgram = Effect.gen(function* () {
|
||||
const response = yield* Image.generate({
|
||||
model: Google.configure({ apiKey }).image("any-model-id"),
|
||||
prompt: "A robot tending a rooftop garden",
|
||||
options: {
|
||||
aspectRatio: "16:9",
|
||||
imageSize: "2K",
|
||||
seed: 42,
|
||||
thinkingLevel: "HIGH",
|
||||
includeThoughts: true,
|
||||
futureOption: true,
|
||||
},
|
||||
http,
|
||||
})
|
||||
|
||||
return response.images
|
||||
})
|
||||
```
|
||||
|
||||
Google image options are request-scoped and inferred from the selected model. Known fields autocomplete while
|
||||
future string values and arbitrary native Gemini `generationConfig` fields remain available. Native fields override
|
||||
their mapped aliases, and `http.body` is the final deep overlay. The selected model ID is sent to Gemini
|
||||
`generateContent` without a local allowlist.
|
||||
|
||||
Z.ai image models infer open Z.ai-native options from the selected model:
|
||||
|
||||
```ts
|
||||
yield *
|
||||
Image.generate({
|
||||
model: ZAI.configure({ apiKey }).image("any-model-id"),
|
||||
prompt,
|
||||
options: {
|
||||
quality: "hd",
|
||||
userID: "user-123",
|
||||
future_option: true,
|
||||
},
|
||||
http,
|
||||
})
|
||||
```
|
||||
|
||||
Z.ai does not include trustworthy MIME metadata for output URLs, so generated images use
|
||||
`application/octet-stream`. Output URLs expire after 30 days; download and persist them promptly if they must
|
||||
remain available.
|
||||
|
||||
Conversational image generation remains part of the LLM interaction. OpenAI Responses exposes it through its hosted image tool:
|
||||
|
||||
```ts
|
||||
|
|
@ -145,7 +272,7 @@ const gateway = CloudflareAIGateway.configure({
|
|||
}).model("workers-ai/@cf/meta/llama-3.1-8b-instruct")
|
||||
```
|
||||
|
||||
Included providers: OpenAI, Anthropic, Google (Gemini), Google Vertex Gemini and Anthropic, Amazon Bedrock, Azure OpenAI, Cloudflare AI Gateway, Cloudflare Workers AI, GitHub Copilot, OpenRouter, xAI, plus generic OpenAI-compatible Chat and Responses entrypoints and an Anthropic Messages-compatible entrypoint.
|
||||
Included providers: OpenAI, Anthropic, Google (Gemini), Google Vertex Gemini and Anthropic, Amazon Bedrock, Azure OpenAI, Cloudflare AI Gateway, Cloudflare Workers AI, GitHub Copilot, OpenRouter, xAI, Z.ai, plus generic OpenAI-compatible Chat and Responses entrypoints and an Anthropic Messages-compatible entrypoint.
|
||||
|
||||
### Package-like entrypoints
|
||||
|
||||
|
|
|
|||
|
|
@ -7,7 +7,7 @@
|
|||
"scripts": {
|
||||
"setup:recording-env": "bun run script/setup-recording-env.ts",
|
||||
"test": "bun test --timeout 30000 --only-failures",
|
||||
"typecheck": "tsgo --noEmit",
|
||||
"typecheck": "tsgo --noEmit && tsgo --noEmit -p tsconfig.types.json",
|
||||
"build": "tsc -p tsconfig.build.json"
|
||||
},
|
||||
"files": [
|
||||
|
|
|
|||
|
|
@ -1,17 +1,21 @@
|
|||
import { Context, Effect, Layer } from "effect"
|
||||
import { RequestExecutor } from "./route/executor"
|
||||
import type { ImageRequest, ImageResponse } from "./image"
|
||||
import type { ImageOptions, ImageRequest, ImageRequestFor, ImageResponse } from "./image"
|
||||
import type { LLMError } from "./schema"
|
||||
|
||||
export type Execute = RequestExecutor.Interface["execute"]
|
||||
|
||||
export interface Interface {
|
||||
readonly generate: (request: ImageRequest) => Effect.Effect<ImageResponse, LLMError>
|
||||
readonly generate: <Options extends ImageOptions>(
|
||||
request: ImageRequestFor<Options>,
|
||||
) => Effect.Effect<ImageResponse, LLMError>
|
||||
}
|
||||
|
||||
export class Service extends Context.Service<Service, Interface>()("@opencode/ImageClient") {}
|
||||
|
||||
export const generate = (request: ImageRequest): Effect.Effect<ImageResponse, LLMError> =>
|
||||
export const generate = <Options extends ImageOptions>(
|
||||
request: ImageRequestFor<Options>,
|
||||
): Effect.Effect<ImageResponse, LLMError> =>
|
||||
Effect.gen(function* () {
|
||||
const client = yield* Service
|
||||
return yield* client.generate(request)
|
||||
|
|
|
|||
|
|
@ -1,80 +1,120 @@
|
|||
import { Effect, Schema } from "effect"
|
||||
import { HttpOptions, InvalidRequestReason, LLMError, ModelID, ProviderID, ProviderMetadata, Usage } from "./schema"
|
||||
import { ImageClient, type Execute as ImageExecute } from "./image-client"
|
||||
import { ImageClient, Service, type Execute as ImageExecute } from "./image-client"
|
||||
|
||||
export interface ImageRoute {
|
||||
export interface ImageRoute<Options extends ImageOptions = ImageOptions> {
|
||||
readonly id: string
|
||||
readonly generate: (request: ImageRequest, execute: ImageExecute) => Effect.Effect<ImageResponse, LLMError>
|
||||
readonly generate: (
|
||||
request: ImageRequestFor<Options>,
|
||||
execute: ImageExecute,
|
||||
) => Effect.Effect<ImageResponse, LLMError>
|
||||
}
|
||||
|
||||
export class ImageModel {
|
||||
export type ImageOptions = Record<string, unknown>
|
||||
|
||||
export class ImageModel<Options extends ImageOptions = ImageOptions> {
|
||||
declare protected readonly _Options: (options: Options) => Options
|
||||
readonly id: ModelID
|
||||
readonly provider: ProviderID
|
||||
readonly route: ImageRoute
|
||||
readonly defaults?: ImageModelDefaults
|
||||
readonly route: ImageRoute<Options>
|
||||
readonly http?: HttpOptions
|
||||
|
||||
constructor(input: ImageModel.Input) {
|
||||
constructor(input: ImageModel.Input<Options>) {
|
||||
this.id = input.id
|
||||
this.provider = input.provider
|
||||
this.route = input.route
|
||||
this.defaults = input.defaults
|
||||
this.http = input.http
|
||||
}
|
||||
|
||||
static make(input: ImageModel.MakeInput) {
|
||||
return new ImageModel({
|
||||
static make<Options extends ImageOptions = ImageOptions>(input: ImageModel.MakeInput<Options>) {
|
||||
return new ImageModel<Options>({
|
||||
id: ModelID.make(input.id),
|
||||
provider: ProviderID.make(input.provider),
|
||||
route: input.route,
|
||||
defaults: input.defaults,
|
||||
http: input.http,
|
||||
})
|
||||
}
|
||||
}
|
||||
|
||||
export namespace ImageModel {
|
||||
export interface Input {
|
||||
export interface Input<Options extends ImageOptions = ImageOptions> {
|
||||
readonly id: ModelID
|
||||
readonly provider: ProviderID
|
||||
readonly route: ImageRoute
|
||||
readonly defaults?: ImageModelDefaults
|
||||
readonly route: ImageRoute<Options>
|
||||
readonly http?: HttpOptions
|
||||
}
|
||||
|
||||
export interface MakeInput extends Omit<Input, "id" | "provider"> {
|
||||
export interface MakeInput<Options extends ImageOptions = ImageOptions>
|
||||
extends Omit<Input<Options>, "id" | "provider"> {
|
||||
readonly id: string | ModelID
|
||||
readonly provider: string | ProviderID
|
||||
}
|
||||
}
|
||||
|
||||
export interface ImageModelDefaults {
|
||||
readonly providerOptions?: Record<string, Record<string, unknown>>
|
||||
readonly http?: HttpOptions
|
||||
}
|
||||
|
||||
export const ImageModelSchema = Schema.declare((value): value is ImageModel => value instanceof ImageModel, {
|
||||
expected: "Image.Model",
|
||||
})
|
||||
|
||||
export const ImageSize = Schema.Struct({
|
||||
width: Schema.Int.check(Schema.isGreaterThanOrEqualTo(1)),
|
||||
height: Schema.Int.check(Schema.isGreaterThanOrEqualTo(1)),
|
||||
}).annotate({ identifier: "Image.Size" })
|
||||
export type ImageSize = Schema.Schema.Type<typeof ImageSize>
|
||||
const ImageBytesInput = Schema.Struct({
|
||||
type: Schema.Literal("bytes"),
|
||||
data: Schema.Uint8Array,
|
||||
mediaType: Schema.String,
|
||||
})
|
||||
const ImageUrlInput = Schema.Struct({
|
||||
type: Schema.Literal("url"),
|
||||
url: Schema.String,
|
||||
})
|
||||
const ImageFileIDInput = Schema.Struct({
|
||||
type: Schema.Literal("file-id"),
|
||||
id: Schema.String,
|
||||
})
|
||||
const ImageFileURIInput = Schema.Struct({
|
||||
type: Schema.Literal("file-uri"),
|
||||
uri: Schema.String,
|
||||
mediaType: Schema.String,
|
||||
})
|
||||
|
||||
export const ImageInputSchema = Schema.Union([
|
||||
ImageBytesInput,
|
||||
ImageUrlInput,
|
||||
ImageFileIDInput,
|
||||
ImageFileURIInput,
|
||||
]).pipe(Schema.toTaggedUnion("type"))
|
||||
export type ImageInput = Schema.Schema.Type<typeof ImageInputSchema>
|
||||
|
||||
export const ImageInput = {
|
||||
bytes: (data: Uint8Array, mediaType: string): ImageInput => ({ type: "bytes", data, mediaType }),
|
||||
url: (url: string): ImageInput => ({ type: "url", url }),
|
||||
file: (id: string): ImageInput => ({ type: "file-id", id }),
|
||||
fileUri: (uri: string, mediaType: string): ImageInput => ({ type: "file-uri", uri, mediaType }),
|
||||
} as const
|
||||
|
||||
export class ImageRequest extends Schema.Class<ImageRequest>("Image.Request")({
|
||||
model: ImageModelSchema,
|
||||
prompt: Schema.String,
|
||||
count: Schema.optional(Schema.Int.check(Schema.isGreaterThanOrEqualTo(1))),
|
||||
size: Schema.optional(ImageSize),
|
||||
aspectRatio: Schema.optional(Schema.String),
|
||||
seed: Schema.optional(Schema.Number),
|
||||
providerOptions: Schema.optional(Schema.Record(Schema.String, Schema.Record(Schema.String, Schema.Unknown))),
|
||||
images: Schema.optional(Schema.Array(ImageInputSchema)),
|
||||
options: Schema.optional(Schema.Record(Schema.String, Schema.Unknown)),
|
||||
http: Schema.optional(HttpOptions),
|
||||
metadata: Schema.optional(Schema.Record(Schema.String, Schema.Unknown)),
|
||||
}) {}
|
||||
|
||||
export type ImageRequestInput = Omit<ConstructorParameters<typeof ImageRequest>[0], "http"> & {
|
||||
readonly http?: HttpOptions.Input
|
||||
}) {
|
||||
declare protected readonly _ImageRequest: void
|
||||
}
|
||||
|
||||
export type ImageRequestFor<Options extends ImageOptions = ImageOptions> = Omit<ImageRequest, "model" | "options"> & {
|
||||
readonly model: ImageModel<Options>
|
||||
readonly options?: Options
|
||||
}
|
||||
|
||||
export type ImageModelOptions<Model> = Model extends ImageModel<infer Options> ? Options : never
|
||||
|
||||
export type ImageRequestInput<Model extends object = ImageModel> = Omit<
|
||||
ConstructorParameters<typeof ImageRequest>[0],
|
||||
"model" | "options" | "http"
|
||||
> & {
|
||||
readonly model: Model
|
||||
readonly options?: NoInfer<ImageModelOptions<Model>>
|
||||
readonly http?: HttpOptions.Input
|
||||
} & (Model extends ImageModel<ImageModelOptions<Model>> ? unknown : never)
|
||||
|
||||
export class GeneratedImage extends Schema.Class<GeneratedImage>("Image.Generated")({
|
||||
mediaType: Schema.String,
|
||||
data: Schema.Union([Schema.String, Schema.Uint8Array]),
|
||||
|
|
@ -91,24 +131,34 @@ export class ImageResponse extends Schema.Class<ImageResponse>("Image.Response")
|
|||
}
|
||||
}
|
||||
|
||||
export const request = (input: ImageRequest | ImageRequestInput) => {
|
||||
export function request<const Model extends object>(
|
||||
input: ImageRequestInput<Model>,
|
||||
): ImageRequestFor<ImageModelOptions<Model>>
|
||||
export function request(input: ImageRequest): ImageRequest
|
||||
export function request(input: ImageRequest | ImageRequestInput) {
|
||||
if (input instanceof ImageRequest) return input
|
||||
return new ImageRequest({
|
||||
...input,
|
||||
model: input.model as unknown as ImageModel,
|
||||
http: input.http === undefined ? undefined : HttpOptions.make(input.http),
|
||||
})
|
||||
}
|
||||
|
||||
export const generate = (input: ImageRequest | ImageRequestInput) =>
|
||||
Effect.try({
|
||||
try: () => request(input),
|
||||
export function generate<const Model extends object>(
|
||||
input: ImageRequestInput<Model>,
|
||||
): Effect.Effect<ImageResponse, LLMError, Service>
|
||||
export function generate(input: ImageRequest): Effect.Effect<ImageResponse, LLMError, Service>
|
||||
export function generate(input: ImageRequest | ImageRequestInput) {
|
||||
return Effect.try({
|
||||
try: () => (input instanceof ImageRequest ? input : request(input)),
|
||||
catch: (error) =>
|
||||
new LLMError({
|
||||
module: "Image",
|
||||
method: "generate",
|
||||
reason: new InvalidRequestReason({ message: error instanceof Error ? error.message : String(error) }),
|
||||
}),
|
||||
}).pipe(Effect.flatMap(ImageClient.generate))
|
||||
}).pipe(Effect.flatMap((request) => ImageClient.generate(request as unknown as ImageRequestFor<ImageOptions>)))
|
||||
}
|
||||
|
||||
export const Image = {
|
||||
request,
|
||||
|
|
|
|||
|
|
@ -11,8 +11,8 @@ export type {
|
|||
Service as LLMClientService,
|
||||
} from "./route/client"
|
||||
export * from "./schema"
|
||||
export { GeneratedImage, ImageModel, ImageRequest, ImageResponse, ImageSize } from "./image"
|
||||
export type { ImageModelDefaults, ImageRequestInput, ImageRoute } from "./image"
|
||||
export { GeneratedImage, ImageInput, ImageInputSchema, ImageModel, ImageRequest, ImageResponse } from "./image"
|
||||
export type { ImageModelOptions, ImageOptions, ImageRequestFor, ImageRequestInput, ImageRoute } from "./image"
|
||||
export { Image } from "./image"
|
||||
export { Tool, ToolFailure, toDefinitions } from "./tool"
|
||||
export { ToolRuntime } from "./tool-runtime"
|
||||
|
|
|
|||
314
packages/ai/src/protocols/google-images.ts
Normal file
314
packages/ai/src/protocols/google-images.ts
Normal file
|
|
@ -0,0 +1,314 @@
|
|||
import { Effect, Encoding, Schema } from "effect"
|
||||
import { Headers, HttpClientRequest } from "effect/unstable/http"
|
||||
import {
|
||||
GeneratedImage,
|
||||
ImageModel,
|
||||
ImageResponse,
|
||||
type ImageInput,
|
||||
type ImageRequestFor,
|
||||
type ImageRoute,
|
||||
} from "../image"
|
||||
import { Auth, type Definition as AuthDefinition } from "../route/auth"
|
||||
import {
|
||||
InvalidProviderOutputReason,
|
||||
LLMError,
|
||||
Usage,
|
||||
mergeHttpOptions,
|
||||
mergeJsonRecords,
|
||||
type HttpOptions,
|
||||
type ProviderMetadata,
|
||||
} from "../schema"
|
||||
import { ProviderShared } from "./shared"
|
||||
import { ImageInputs } from "./utils/image-input"
|
||||
|
||||
const ADAPTER = "google-images"
|
||||
export const DEFAULT_BASE_URL = "https://generativelanguage.googleapis.com/v1beta"
|
||||
|
||||
export type GoogleImageString<Known extends string> = Known | (string & {})
|
||||
|
||||
export type GoogleImageOptions = {
|
||||
readonly aspectRatio?: GoogleImageString<
|
||||
"1:1" | "2:3" | "3:2" | "3:4" | "4:3" | "4:5" | "5:4" | "9:16" | "16:9" | "21:9"
|
||||
>
|
||||
readonly imageSize?: GoogleImageString<"1K" | "2K" | "4K">
|
||||
readonly seed?: number
|
||||
readonly thinkingLevel?: GoogleImageString<"MINIMAL" | "LOW" | "MEDIUM" | "HIGH">
|
||||
readonly includeThoughts?: boolean
|
||||
} & Record<string, unknown>
|
||||
|
||||
export type GoogleImageBody = Record<string, unknown> & {
|
||||
readonly contents: ReadonlyArray<{
|
||||
readonly role: "user"
|
||||
readonly parts: ReadonlyArray<Record<string, unknown>>
|
||||
}>
|
||||
readonly generationConfig: Record<string, unknown>
|
||||
}
|
||||
|
||||
const GoogleUsage = Schema.StructWithRest(
|
||||
Schema.Struct({
|
||||
cachedContentTokenCount: Schema.optional(Schema.Number),
|
||||
thoughtsTokenCount: Schema.optional(Schema.Number),
|
||||
promptTokenCount: Schema.optional(Schema.Number),
|
||||
candidatesTokenCount: Schema.optional(Schema.Number),
|
||||
totalTokenCount: Schema.optional(Schema.Number),
|
||||
promptTokensDetails: Schema.optional(Schema.Unknown),
|
||||
candidatesTokensDetails: Schema.optional(Schema.Unknown),
|
||||
}),
|
||||
[Schema.Record(Schema.String, Schema.Unknown)],
|
||||
)
|
||||
|
||||
const GoogleImageResponse = Schema.Struct({
|
||||
candidates: Schema.optional(
|
||||
Schema.Array(
|
||||
Schema.Struct({
|
||||
index: Schema.optional(Schema.Number),
|
||||
content: Schema.optional(
|
||||
Schema.Struct({
|
||||
parts: Schema.Array(
|
||||
Schema.Struct({
|
||||
text: Schema.optional(Schema.String),
|
||||
thought: Schema.optional(Schema.Boolean),
|
||||
thoughtSignature: Schema.optional(Schema.String),
|
||||
inlineData: Schema.optional(
|
||||
Schema.Struct({
|
||||
mimeType: Schema.String,
|
||||
data: Schema.String,
|
||||
}),
|
||||
),
|
||||
}),
|
||||
),
|
||||
}),
|
||||
),
|
||||
finishReason: Schema.optional(Schema.String),
|
||||
finishMessage: Schema.optional(Schema.String),
|
||||
safetyRatings: Schema.optional(Schema.Unknown),
|
||||
citationMetadata: Schema.optional(Schema.Unknown),
|
||||
groundingMetadata: Schema.optional(Schema.Unknown),
|
||||
}),
|
||||
),
|
||||
),
|
||||
usageMetadata: Schema.optional(GoogleUsage),
|
||||
modelVersion: Schema.optional(Schema.String),
|
||||
responseId: Schema.optional(Schema.String),
|
||||
promptFeedback: Schema.optional(Schema.Unknown),
|
||||
})
|
||||
|
||||
export interface ModelInput {
|
||||
readonly id: string
|
||||
readonly auth: AuthDefinition
|
||||
readonly baseURL?: string
|
||||
readonly headers?: Record<string, string>
|
||||
readonly http?: HttpOptions
|
||||
}
|
||||
|
||||
const nativeOptions = (options: GoogleImageOptions | undefined) => {
|
||||
const { aspectRatio, imageSize, seed, thinkingLevel, includeThoughts, ...native } = options ?? {}
|
||||
const image = {
|
||||
aspectRatio,
|
||||
imageSize,
|
||||
}
|
||||
const thinkingConfig = {
|
||||
thinkingLevel,
|
||||
includeThoughts,
|
||||
}
|
||||
return (
|
||||
mergeJsonRecords(
|
||||
{
|
||||
responseModalities: ["IMAGE"],
|
||||
imageConfig: Object.values(image).some((value) => value !== undefined) ? image : undefined,
|
||||
seed,
|
||||
thinkingConfig: Object.values(thinkingConfig).some((value) => value !== undefined) ? thinkingConfig : undefined,
|
||||
},
|
||||
native,
|
||||
) ?? { responseModalities: ["IMAGE"] }
|
||||
)
|
||||
}
|
||||
|
||||
const invalidOutput = (message: string, providerMetadata?: ProviderMetadata) =>
|
||||
new LLMError({
|
||||
module: ADAPTER,
|
||||
method: "generate",
|
||||
reason: new InvalidProviderOutputReason({ message, route: ADAPTER, providerMetadata }),
|
||||
})
|
||||
|
||||
const applyQuery = (url: string, query: Record<string, string> | undefined) => {
|
||||
if (!query) return url
|
||||
const next = new URL(url)
|
||||
Object.entries(query).forEach(([key, value]) => next.searchParams.set(key, value))
|
||||
return next.toString()
|
||||
}
|
||||
|
||||
export const model = (input: ModelInput) => {
|
||||
const route: ImageRoute<GoogleImageOptions> = {
|
||||
id: ADAPTER,
|
||||
generate: Effect.fn("GoogleImages.generate")(function* (request: ImageRequestFor<GoogleImageOptions>, execute) {
|
||||
const imageParts = yield* Effect.forEach(request.images ?? [], googleImagePart)
|
||||
const http = mergeHttpOptions(request.model.http, request.http)
|
||||
const requestBody = mergeJsonRecords(
|
||||
{
|
||||
contents: [{ role: "user", parts: [{ text: request.prompt }, ...imageParts] }],
|
||||
generationConfig: nativeOptions(request.options),
|
||||
},
|
||||
http?.body,
|
||||
) as GoogleImageBody
|
||||
const text = ProviderShared.encodeJson(requestBody)
|
||||
const url = applyQuery(
|
||||
`${(input.baseURL ?? DEFAULT_BASE_URL).replace(/\/$/, "")}/models/${request.model.id}:generateContent`,
|
||||
http?.query,
|
||||
)
|
||||
const headers = yield* Auth.toEffect(input.auth)({
|
||||
request,
|
||||
method: "POST",
|
||||
url,
|
||||
body: text,
|
||||
headers: Headers.fromInput({ ...input.headers, ...http?.headers }),
|
||||
})
|
||||
const response = yield* execute(
|
||||
HttpClientRequest.post(url).pipe(
|
||||
HttpClientRequest.setHeaders(headers),
|
||||
HttpClientRequest.bodyText(text, "application/json"),
|
||||
),
|
||||
)
|
||||
const payload = yield* response.json.pipe(
|
||||
Effect.mapError(() => invalidOutput("Failed to read the Google Images response")),
|
||||
)
|
||||
const decoded = yield* Schema.decodeUnknownEffect(GoogleImageResponse)(payload).pipe(
|
||||
Effect.mapError(() => invalidOutput("Google Images returned an invalid response")),
|
||||
)
|
||||
const candidates = decoded.candidates ?? []
|
||||
const candidateMetadata = candidates.map((candidate, candidateIndex) => ({
|
||||
index: candidate.index ?? candidateIndex,
|
||||
finishReason: candidate.finishReason,
|
||||
finishMessage: candidate.finishMessage,
|
||||
safetyRatings: candidate.safetyRatings,
|
||||
citationMetadata: candidate.citationMetadata,
|
||||
groundingMetadata: candidate.groundingMetadata,
|
||||
parts: (candidate.content?.parts ?? []).map((part) =>
|
||||
part.inlineData === undefined
|
||||
? {
|
||||
type: "text",
|
||||
text: part.text,
|
||||
thought: part.thought,
|
||||
thoughtSignature: part.thoughtSignature,
|
||||
}
|
||||
: {
|
||||
type: "inlineData",
|
||||
mediaType: part.inlineData.mimeType,
|
||||
thought: part.thought,
|
||||
thoughtSignature: part.thoughtSignature,
|
||||
},
|
||||
),
|
||||
}))
|
||||
const encoded = candidates.flatMap((candidate, candidateIndex) =>
|
||||
(candidate.content?.parts ?? []).flatMap((part, partIndex) =>
|
||||
part.inlineData === undefined || part.thought === true
|
||||
? []
|
||||
: [{ candidate, candidateIndex, partIndex, inlineData: part.inlineData }],
|
||||
),
|
||||
)
|
||||
const images = yield* Effect.forEach(encoded, (item) =>
|
||||
Effect.fromResult(Encoding.decodeBase64(item.inlineData.data)).pipe(
|
||||
Effect.mapError(() =>
|
||||
invalidOutput(
|
||||
`Google Images candidate ${item.candidateIndex} part ${item.partIndex} contains invalid base64 data`,
|
||||
),
|
||||
),
|
||||
Effect.map(
|
||||
(data) =>
|
||||
new GeneratedImage({
|
||||
mediaType: item.inlineData.mimeType,
|
||||
data,
|
||||
providerMetadata: {
|
||||
google: {
|
||||
candidateIndex: item.candidate.index ?? item.candidateIndex,
|
||||
partIndex: item.partIndex,
|
||||
finishReason: item.candidate.finishReason,
|
||||
safetyRatings: item.candidate.safetyRatings,
|
||||
citationMetadata: item.candidate.citationMetadata,
|
||||
groundingMetadata: item.candidate.groundingMetadata,
|
||||
thoughtSignature: item.candidate.content?.parts[item.partIndex]?.thoughtSignature,
|
||||
},
|
||||
},
|
||||
}),
|
||||
),
|
||||
),
|
||||
)
|
||||
if (images.length === 0) {
|
||||
const finishReasons = candidates.flatMap((candidate) =>
|
||||
candidate.finishReason === undefined ? [] : [candidate.finishReason],
|
||||
)
|
||||
return yield* invalidOutput(
|
||||
`Google Images returned no final images${
|
||||
finishReasons.length === 0 ? "" : ` (finish reasons: ${finishReasons.join(", ")})`
|
||||
}; inspect reason.providerMetadata.google for prompt feedback and candidate details`,
|
||||
{
|
||||
google: {
|
||||
promptFeedback: decoded.promptFeedback,
|
||||
candidates: candidateMetadata,
|
||||
},
|
||||
},
|
||||
)
|
||||
}
|
||||
const usage = decoded.usageMetadata
|
||||
const outputTokens =
|
||||
usage?.candidatesTokenCount === undefined
|
||||
? undefined
|
||||
: usage.candidatesTokenCount + (usage.thoughtsTokenCount ?? 0)
|
||||
return new ImageResponse({
|
||||
images,
|
||||
usage:
|
||||
usage === undefined
|
||||
? undefined
|
||||
: new Usage({
|
||||
inputTokens: usage.promptTokenCount,
|
||||
outputTokens,
|
||||
nonCachedInputTokens: ProviderShared.subtractTokens(
|
||||
usage.promptTokenCount,
|
||||
usage.cachedContentTokenCount,
|
||||
),
|
||||
cacheReadInputTokens: usage.cachedContentTokenCount,
|
||||
reasoningTokens: usage.thoughtsTokenCount,
|
||||
totalTokens: ProviderShared.totalTokens(usage.promptTokenCount, outputTokens, usage.totalTokenCount),
|
||||
providerMetadata: { google: usage },
|
||||
}),
|
||||
providerMetadata: {
|
||||
google: {
|
||||
modelVersion: decoded.modelVersion,
|
||||
responseId: decoded.responseId,
|
||||
promptFeedback: decoded.promptFeedback,
|
||||
candidates: candidateMetadata,
|
||||
},
|
||||
},
|
||||
})
|
||||
}),
|
||||
}
|
||||
return ImageModel.make<GoogleImageOptions>({ id: input.id, provider: "google", route, http: input.http })
|
||||
}
|
||||
|
||||
const googleImagePart = (image: ImageInput): Effect.Effect<Record<string, unknown>, LLMError> => {
|
||||
if (image.type === "bytes")
|
||||
return Effect.succeed({ inlineData: { mimeType: image.mediaType, data: Encoding.encodeBase64(image.data) } })
|
||||
if (image.type === "file-uri") return Effect.succeed({ fileData: { mimeType: image.mediaType, fileUri: image.uri } })
|
||||
if (image.type === "url")
|
||||
return ImageInputs.decodeDataUrl(image.url, ADAPTER).pipe(
|
||||
Effect.flatMap((decoded) => {
|
||||
if (decoded === undefined)
|
||||
return Effect.fail(
|
||||
ImageInputs.invalid(
|
||||
ADAPTER,
|
||||
"Google generateContent does not fetch public image URLs; use bytes, a data URL, or a Gemini file URI",
|
||||
),
|
||||
)
|
||||
return Effect.succeed({
|
||||
inlineData: { mimeType: decoded.mediaType, data: Encoding.encodeBase64(decoded.data) },
|
||||
})
|
||||
}),
|
||||
)
|
||||
return Effect.fail(
|
||||
ImageInputs.invalid(ADAPTER, "Google generateContent requires Gemini file URIs rather than provider file IDs"),
|
||||
)
|
||||
}
|
||||
|
||||
export const GoogleImages = {
|
||||
model,
|
||||
} as const
|
||||
|
|
@ -77,6 +77,7 @@ const OpenAIChatMessage = Schema.Union([
|
|||
reasoning_content: Schema.optional(Schema.String),
|
||||
reasoning: Schema.optional(Schema.String),
|
||||
reasoning_text: Schema.optional(Schema.String),
|
||||
reasoning_details: optionalArray(Schema.Unknown),
|
||||
}),
|
||||
Schema.Struct({ role: Schema.Literal("tool"), tool_call_id: Schema.String, content: Schema.String }),
|
||||
]).pipe(Schema.toTaggedUnion("role"))
|
||||
|
|
@ -149,6 +150,7 @@ const OpenAIChatDelta = Schema.Struct({
|
|||
reasoning_content: optionalNull(Schema.String),
|
||||
reasoning: optionalNull(Schema.String),
|
||||
reasoning_text: optionalNull(Schema.String),
|
||||
reasoning_details: optionalNull(Schema.Array(Schema.Unknown)),
|
||||
tool_calls: optionalNull(Schema.Array(OpenAIChatToolCallDelta)),
|
||||
})
|
||||
|
||||
|
|
@ -164,13 +166,23 @@ export const OpenAIChatEvent = Schema.Struct({
|
|||
export type OpenAIChatEvent = Schema.Schema.Type<typeof OpenAIChatEvent>
|
||||
type OpenAIChatRequestMessage = LLMRequest["messages"][number]
|
||||
|
||||
interface PendingToolDelta {
|
||||
readonly id?: string
|
||||
readonly name?: string
|
||||
readonly input: string
|
||||
}
|
||||
|
||||
export interface ParserState {
|
||||
readonly tools: ToolStream.State<number>
|
||||
readonly pendingTools: Partial<Record<number, PendingToolDelta>>
|
||||
readonly toolCallEvents: ReadonlyArray<LLMEvent>
|
||||
readonly usage?: Usage
|
||||
readonly finishReason?: FinishReason
|
||||
readonly lifecycle: Lifecycle.State
|
||||
readonly reasoningField?: "reasoning" | "reasoning_content" | "reasoning_text"
|
||||
readonly reasoningDetails: Array<unknown>
|
||||
readonly reasoningDetailsObserved: boolean
|
||||
readonly reasoningEmitted: boolean
|
||||
}
|
||||
|
||||
// =============================================================================
|
||||
|
|
@ -216,7 +228,15 @@ const openAICompatibleReasoningContent = (native: unknown) =>
|
|||
const reasoningField = (part: ReasoningPart) => {
|
||||
const field = part.providerMetadata?.openai?.reasoningField
|
||||
if (field === "reasoning" || field === "reasoning_content" || field === "reasoning_text") return field
|
||||
return "reasoning_content"
|
||||
}
|
||||
|
||||
const reasoningDetails = (parts: ReadonlyArray<ReasoningPart>, native: unknown) => {
|
||||
const observed = parts.flatMap((part) => {
|
||||
const details = part.providerMetadata?.openai?.reasoningDetails
|
||||
return Array.isArray(details) ? details : []
|
||||
})
|
||||
if (parts.some((part) => Array.isArray(part.providerMetadata?.openai?.reasoningDetails))) return observed
|
||||
if (isRecord(native) && Array.isArray(native.reasoning_details)) return native.reasoning_details
|
||||
}
|
||||
|
||||
const lowerUserMessage = Effect.fn("OpenAIChat.lowerUserMessage")(function* (message: OpenAIChatRequestMessage) {
|
||||
|
|
@ -260,19 +280,28 @@ const lowerAssistantMessage = Effect.fn("OpenAIChat.lowerAssistantMessage")(func
|
|||
}
|
||||
}
|
||||
const text = reasoning.map((part) => part.text).join("")
|
||||
const field = reasoning[0] ? reasoningField(reasoning[0]) : "reasoning_content"
|
||||
const details = reasoningDetails(reasoning, message.native?.openaiCompatible)
|
||||
const observedField = reasoning.map(reasoningField).find((value) => value !== undefined)
|
||||
const nativeReasoning = openAICompatibleReasoningContent(message.native?.openaiCompatible)
|
||||
const fullyStructured = reasoning.every((part) => Array.isArray(part.providerMetadata?.openai?.reasoningDetails))
|
||||
const field = (() => {
|
||||
if (reasoning.length === 0) return
|
||||
if (observedField !== undefined) return observedField
|
||||
if (nativeReasoning !== undefined) return "reasoning_content"
|
||||
if (!fullyStructured) return "reasoning_content"
|
||||
})()
|
||||
const reasoningContent = (() => {
|
||||
if (reasoning.length === 0) return nativeReasoning
|
||||
if (field === "reasoning_content") return text
|
||||
})()
|
||||
return {
|
||||
role: "assistant" as const,
|
||||
content: content.length === 0 ? null : ProviderShared.joinText(content),
|
||||
tool_calls: toolCalls.length === 0 ? undefined : toolCalls,
|
||||
reasoning_content:
|
||||
reasoning.length === 0
|
||||
? openAICompatibleReasoningContent(message.native?.openaiCompatible)
|
||||
: field === "reasoning_content"
|
||||
? text
|
||||
: undefined,
|
||||
reasoning_content: reasoningContent,
|
||||
reasoning: reasoning.length > 0 && field === "reasoning" ? text : undefined,
|
||||
reasoning_text: reasoning.length > 0 && field === "reasoning_text" ? text : undefined,
|
||||
reasoning_details: details,
|
||||
}
|
||||
})
|
||||
|
||||
|
|
@ -423,6 +452,59 @@ const reasoningDelta = (delta: Schema.Schema.Type<typeof OpenAIChatDelta> | null
|
|||
if (delta?.reasoning_text) return { field: "reasoning_text", text: delta.reasoning_text } as const
|
||||
}
|
||||
|
||||
const detailText = (details: ReadonlyArray<unknown>) => {
|
||||
const text = details.flatMap((detail) => {
|
||||
if (!isRecord(detail)) return []
|
||||
if (detail.type === "reasoning.text" && typeof detail.text === "string" && detail.text) return [detail.text]
|
||||
if (detail.type === "reasoning.summary" && typeof detail.summary === "string" && detail.summary)
|
||||
return [detail.summary]
|
||||
return []
|
||||
})
|
||||
if (text.length > 0) return text.join("")
|
||||
}
|
||||
|
||||
const appendReasoningDetails = (result: Array<unknown>, details: ReadonlyArray<unknown>) => {
|
||||
for (const detail of details) {
|
||||
const previous = result.at(-1)
|
||||
if (
|
||||
!isRecord(previous) ||
|
||||
previous.type !== "reasoning.text" ||
|
||||
!isRecord(detail) ||
|
||||
detail.type !== "reasoning.text" ||
|
||||
conflictingReasoningTextDetails(previous, detail)
|
||||
) {
|
||||
result.push(detail)
|
||||
continue
|
||||
}
|
||||
result[result.length - 1] = {
|
||||
...previous,
|
||||
...Object.fromEntries(Object.entries(detail).filter((entry) => entry[1] !== undefined)),
|
||||
text: `${typeof previous.text === "string" ? previous.text : ""}${typeof detail.text === "string" ? detail.text : ""}`,
|
||||
signature: mergeDetailValue(previous.signature, detail.signature),
|
||||
format: mergeDetailValue(previous.format, detail.format),
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
const mergeDetailValue = (previous: unknown, current: unknown) =>
|
||||
previous || current || (previous !== undefined ? previous : current)
|
||||
|
||||
const conflictingReasoningTextDetails = (previous: Record<string, unknown>, current: Record<string, unknown>) =>
|
||||
conflictingDetailValue(previous.id, current.id) ||
|
||||
conflictingDetailValue(previous.index, current.index) ||
|
||||
conflictingDetailValue(previous.format, current.format) ||
|
||||
(Boolean(previous.signature) && Boolean(current.signature) && previous.signature !== current.signature)
|
||||
|
||||
const conflictingDetailValue = (previous: unknown, current: unknown) =>
|
||||
previous !== undefined && previous !== null && current !== undefined && current !== null && previous !== current
|
||||
|
||||
const reasoningMetadata = (field: ParserState["reasoningField"], details?: ReadonlyArray<unknown>) => ({
|
||||
openai: {
|
||||
...(field ? { reasoningField: field } : {}),
|
||||
...(details ? { reasoningDetails: details } : {}),
|
||||
},
|
||||
})
|
||||
|
||||
const step = (state: ParserState, event: OpenAIChatEvent) =>
|
||||
Effect.gen(function* () {
|
||||
const events: LLMEvent[] = []
|
||||
|
|
@ -432,29 +514,56 @@ const step = (state: ParserState, event: OpenAIChatEvent) =>
|
|||
const delta = choice?.delta
|
||||
const toolDeltas = delta?.tool_calls ?? []
|
||||
let tools = state.tools
|
||||
let pendingTools = state.pendingTools
|
||||
|
||||
let lifecycle = state.lifecycle
|
||||
|
||||
const reasoning = reasoningDelta(delta)
|
||||
const reasoningField = state.reasoningField ?? reasoning?.field
|
||||
if (reasoning)
|
||||
lifecycle = Lifecycle.reasoningDelta(lifecycle, events, "reasoning-0", reasoning.text, {
|
||||
openai: { reasoningField: reasoningField ?? reasoning.field },
|
||||
})
|
||||
const reasoningField = state.reasoningField ?? (!state.lifecycle.text.has("text-0") ? reasoning?.field : undefined)
|
||||
const detailDelta = Array.isArray(delta?.reasoning_details) ? delta.reasoning_details : undefined
|
||||
if (detailDelta !== undefined) appendReasoningDetails(state.reasoningDetails, detailDelta)
|
||||
const reasoningDetailsObserved = state.reasoningDetailsObserved || detailDelta !== undefined
|
||||
const deltaMetadata = reasoningMetadata(reasoningField)
|
||||
const text = detailDelta?.length ? (detailText(detailDelta) ?? reasoning?.text) : reasoning?.text
|
||||
if (!state.lifecycle.text.has("text-0") && text !== undefined)
|
||||
lifecycle = Lifecycle.reasoningDelta(lifecycle, events, "reasoning-0", text, deltaMetadata)
|
||||
else if (
|
||||
reasoningDetailsObserved &&
|
||||
!lifecycle.reasoning.has("reasoning-0") &&
|
||||
(Boolean(delta?.content) || toolDeltas.length > 0)
|
||||
)
|
||||
lifecycle = Lifecycle.reasoningStart(lifecycle, events, "reasoning-0", deltaMetadata)
|
||||
const reasoningEmitted = state.reasoningEmitted || lifecycle.reasoning.has("reasoning-0")
|
||||
|
||||
if (delta?.content) {
|
||||
lifecycle = Lifecycle.reasoningEnd(lifecycle, events, "reasoning-0")
|
||||
lifecycle = Lifecycle.reasoningEnd(
|
||||
lifecycle,
|
||||
events,
|
||||
"reasoning-0",
|
||||
reasoningMetadata(reasoningField, reasoningDetailsObserved ? state.reasoningDetails : undefined),
|
||||
)
|
||||
lifecycle = Lifecycle.textDelta(lifecycle, events, "text-0", delta.content)
|
||||
}
|
||||
|
||||
if (toolDeltas.length) lifecycle = Lifecycle.reasoningEnd(lifecycle, events, "reasoning-0")
|
||||
|
||||
for (const tool of toolDeltas) {
|
||||
const current = tools[tool.index]
|
||||
const pending = pendingTools[tool.index]
|
||||
const id = current?.id ?? pending?.id ?? (tool.id || undefined)
|
||||
const name = current?.name ?? pending?.name ?? (tool.function?.name || undefined)
|
||||
const text = `${pending?.input ?? ""}${tool.function?.arguments ?? ""}`
|
||||
if (!current && (!id || !name)) {
|
||||
pendingTools = { ...pendingTools, [tool.index]: { id: id || undefined, name: name || undefined, input: text } }
|
||||
continue
|
||||
}
|
||||
if (pending) {
|
||||
pendingTools = { ...pendingTools }
|
||||
delete pendingTools[tool.index]
|
||||
}
|
||||
const result = ToolStream.appendOrStart(
|
||||
ADAPTER,
|
||||
tools,
|
||||
tool.index,
|
||||
{ id: tool.id ?? undefined, name: tool.function?.name ?? undefined, text: tool.function?.arguments ?? "" },
|
||||
{ id: id || undefined, name: name || undefined, text },
|
||||
"OpenAI Chat tool call delta is missing id or name",
|
||||
)
|
||||
if (ToolStream.isError(result)) return yield* result
|
||||
|
|
@ -463,6 +572,9 @@ const step = (state: ParserState, event: OpenAIChatEvent) =>
|
|||
events.push(...result.events)
|
||||
}
|
||||
|
||||
if (finishReason !== undefined && state.finishReason === undefined && Object.keys(pendingTools).length > 0)
|
||||
return yield* ProviderShared.eventError(ADAPTER, "OpenAI Chat tool call delta is missing id or name")
|
||||
|
||||
// Finalize accumulated tool inputs eagerly when finish_reason arrives so
|
||||
// valid calls and malformed local calls settle independently.
|
||||
const finished =
|
||||
|
|
@ -473,11 +585,15 @@ const step = (state: ParserState, event: OpenAIChatEvent) =>
|
|||
return [
|
||||
{
|
||||
tools: finished?.tools ?? tools,
|
||||
pendingTools,
|
||||
toolCallEvents: finished?.events ?? state.toolCallEvents,
|
||||
usage,
|
||||
finishReason,
|
||||
lifecycle,
|
||||
reasoningField,
|
||||
reasoningDetails: state.reasoningDetails,
|
||||
reasoningDetailsObserved,
|
||||
reasoningEmitted,
|
||||
},
|
||||
events,
|
||||
] as const
|
||||
|
|
@ -487,7 +603,16 @@ const finishEvents = (state: ParserState): ReadonlyArray<LLMEvent> => {
|
|||
const events: LLMEvent[] = []
|
||||
const hasToolCalls = state.toolCallEvents.length > 0
|
||||
const reason = state.finishReason === "stop" && hasToolCalls ? "tool-calls" : state.finishReason
|
||||
const lifecycle = state.toolCallEvents.length ? Lifecycle.stepStart(state.lifecycle, events) : state.lifecycle
|
||||
const metadata = reasoningMetadata(
|
||||
state.reasoningField,
|
||||
state.reasoningDetailsObserved ? state.reasoningDetails : undefined,
|
||||
)
|
||||
const started =
|
||||
state.reasoningDetailsObserved && !state.reasoningEmitted
|
||||
? Lifecycle.reasoningStart(state.lifecycle, events, "reasoning-0", reasoningMetadata(state.reasoningField))
|
||||
: state.lifecycle
|
||||
const ended = Lifecycle.reasoningEnd(started, events, "reasoning-0", metadata)
|
||||
const lifecycle = state.toolCallEvents.length ? Lifecycle.stepStart(ended, events) : ended
|
||||
events.push(...state.toolCallEvents)
|
||||
if (reason) Lifecycle.finish(lifecycle, events, { reason, usage: state.usage })
|
||||
return events
|
||||
|
|
@ -512,9 +637,13 @@ export const protocol = Protocol.make({
|
|||
event: Protocol.jsonEvent(OpenAIChatEvent),
|
||||
initial: () => ({
|
||||
tools: ToolStream.empty<number>(),
|
||||
pendingTools: {},
|
||||
toolCallEvents: [],
|
||||
lifecycle: Lifecycle.initial(),
|
||||
reasoningField: undefined,
|
||||
reasoningDetails: [],
|
||||
reasoningDetailsObserved: false,
|
||||
reasoningEmitted: false,
|
||||
}),
|
||||
step,
|
||||
onHalt: finishEvents,
|
||||
|
|
|
|||
|
|
@ -1,42 +1,50 @@
|
|||
import { Effect, Encoding, Schema } from "effect"
|
||||
import { Headers, HttpClientRequest } from "effect/unstable/http"
|
||||
import { Headers, HttpClientRequest, HttpClientResponse } from "effect/unstable/http"
|
||||
import {
|
||||
ImageModel,
|
||||
GeneratedImage,
|
||||
ImageResponse,
|
||||
type ImageRequest,
|
||||
type ImageModelDefaults,
|
||||
type ImageInput,
|
||||
type ImageRequestFor,
|
||||
type ImageRoute,
|
||||
} from "../image"
|
||||
import { Auth, type Definition as AuthDefinition } from "../route/auth"
|
||||
import { InvalidProviderOutputReason, LLMError, Usage, mergeHttpOptions, mergeJsonRecords } from "../schema"
|
||||
import {
|
||||
InvalidProviderOutputReason,
|
||||
LLMError,
|
||||
Usage,
|
||||
mergeHttpOptions,
|
||||
mergeJsonRecords,
|
||||
type HttpOptions,
|
||||
} from "../schema"
|
||||
import { ProviderShared } from "./shared"
|
||||
import { ImageInputs } from "./utils/image-input"
|
||||
import { OpenAIImage } from "./utils/openai-image"
|
||||
|
||||
const ADAPTER = "openai-images"
|
||||
export const DEFAULT_BASE_URL = "https://api.openai.com/v1"
|
||||
export const PATH = "/images/generations"
|
||||
export const EDIT_PATH = "/images/edits"
|
||||
|
||||
export interface OpenAIImageOptions {
|
||||
readonly quality?: "auto" | "low" | "medium" | "high"
|
||||
readonly background?: "auto" | "opaque" | "transparent"
|
||||
readonly moderation?: "auto" | "low"
|
||||
readonly outputFormat?: "png" | "jpeg" | "webp"
|
||||
export type OpenAIImageString<Known extends string> = Known | (string & {})
|
||||
|
||||
export type OpenAIImageOptions = {
|
||||
readonly mask?: ImageInput
|
||||
readonly n?: number
|
||||
readonly size?: OpenAIImageString<
|
||||
"auto" | "256x256" | "512x512" | "1024x1024" | "1536x1024" | "1024x1536" | "1792x1024" | "1024x1792"
|
||||
>
|
||||
readonly quality?: OpenAIImageString<"auto" | "low" | "medium" | "high" | "standard" | "hd">
|
||||
readonly background?: OpenAIImageString<"auto" | "opaque" | "transparent">
|
||||
readonly moderation?: OpenAIImageString<"auto" | "low">
|
||||
readonly outputFormat?: OpenAIImageString<"png" | "jpeg" | "webp">
|
||||
readonly outputCompression?: number
|
||||
}
|
||||
} & Record<string, unknown>
|
||||
|
||||
const OpenAIImageBody = Schema.Struct({
|
||||
model: Schema.String,
|
||||
prompt: Schema.String,
|
||||
n: Schema.optional(Schema.Int.check(Schema.isGreaterThanOrEqualTo(1))),
|
||||
size: Schema.optional(Schema.String),
|
||||
quality: Schema.optional(Schema.Literals(["auto", "low", "medium", "high"])),
|
||||
background: Schema.optional(Schema.Literals(["auto", "opaque", "transparent"])),
|
||||
moderation: Schema.optional(Schema.Literals(["auto", "low"])),
|
||||
output_format: Schema.optional(Schema.Literals(["png", "jpeg", "webp"])),
|
||||
output_compression: Schema.optional(Schema.Int.check(Schema.isBetween({ minimum: 0, maximum: 100 }))),
|
||||
})
|
||||
export type OpenAIImageBody = Schema.Schema.Type<typeof OpenAIImageBody>
|
||||
export type OpenAIImageBody = Record<string, unknown> & {
|
||||
readonly model: string
|
||||
readonly prompt: string
|
||||
}
|
||||
|
||||
const OpenAIImageResponse = Schema.Struct({
|
||||
data: Schema.Array(
|
||||
|
|
@ -63,26 +71,16 @@ export interface ModelInput {
|
|||
readonly auth: AuthDefinition
|
||||
readonly baseURL?: string
|
||||
readonly headers?: Record<string, string>
|
||||
readonly defaults?: ImageModelDefaults
|
||||
readonly http?: HttpOptions
|
||||
}
|
||||
|
||||
const providerOptions = (request: ImageRequest): OpenAIImageOptions => ({
|
||||
...request.model.defaults?.providerOptions?.openai,
|
||||
...request.providerOptions?.openai,
|
||||
})
|
||||
|
||||
const body = (request: ImageRequest): OpenAIImageBody => {
|
||||
const options = providerOptions(request)
|
||||
const nativeOptions = (options: OpenAIImageOptions | undefined) => {
|
||||
if (!options) return undefined
|
||||
const { mask: _, outputFormat, outputCompression, ...native } = options
|
||||
return {
|
||||
model: request.model.id,
|
||||
prompt: request.prompt,
|
||||
n: request.count,
|
||||
size: request.size === undefined ? undefined : `${request.size.width}x${request.size.height}`,
|
||||
quality: options.quality,
|
||||
background: options.background,
|
||||
moderation: options.moderation,
|
||||
output_format: options.outputFormat,
|
||||
output_compression: options.outputCompression,
|
||||
output_format: outputFormat,
|
||||
output_compression: outputCompression,
|
||||
...native,
|
||||
}
|
||||
}
|
||||
|
||||
|
|
@ -100,45 +98,93 @@ const applyQuery = (url: string, query: Record<string, string> | undefined) => {
|
|||
return next.toString()
|
||||
}
|
||||
|
||||
const PROTOCOL_BODY_FIELDS = new Set([
|
||||
"model",
|
||||
"prompt",
|
||||
"n",
|
||||
"size",
|
||||
"quality",
|
||||
"background",
|
||||
"moderation",
|
||||
"output_format",
|
||||
"output_compression",
|
||||
])
|
||||
|
||||
const bodyWithOverlay = Effect.fn("OpenAIImages.bodyWithOverlay")(function* (
|
||||
imageBody: OpenAIImageBody,
|
||||
overlay: Record<string, unknown> | undefined,
|
||||
) {
|
||||
if (!overlay) return imageBody
|
||||
const reserved = Object.keys(overlay).filter((key) => PROTOCOL_BODY_FIELDS.has(key))
|
||||
if (reserved.length > 0)
|
||||
return yield* ProviderShared.invalidRequest(
|
||||
`http.body cannot overlay protocol-owned field(s): ${reserved.join(", ")}`,
|
||||
)
|
||||
return mergeJsonRecords(imageBody, overlay) ?? imageBody
|
||||
})
|
||||
|
||||
export const model = (input: ModelInput) => {
|
||||
const route: ImageRoute = {
|
||||
const route: ImageRoute<OpenAIImageOptions> = {
|
||||
id: ADAPTER,
|
||||
generate: Effect.fn("OpenAIImages.generate")(function* (request: ImageRequest, execute) {
|
||||
if (request.aspectRatio !== undefined)
|
||||
return yield* ProviderShared.invalidRequest("OpenAI Images does not support the common aspectRatio option")
|
||||
if (request.seed !== undefined)
|
||||
return yield* ProviderShared.invalidRequest("OpenAI Images does not support the common seed option")
|
||||
generate: Effect.fn("OpenAIImages.generate")(function* (request: ImageRequestFor<OpenAIImageOptions>, execute) {
|
||||
const mask = request.options?.mask
|
||||
if (mask !== undefined && (request.images?.length ?? 0) === 0)
|
||||
return yield* ImageInputs.invalid(ADAPTER, "An OpenAI image mask requires at least one input image")
|
||||
const http = mergeHttpOptions(request.model.http, request.http)
|
||||
const sourceImages = request.images ?? []
|
||||
const multipartImages = yield* Effect.forEach(sourceImages, (image) => {
|
||||
if (image.type === "bytes") return Effect.succeed({ data: image.data, mediaType: image.mediaType })
|
||||
if (image.type === "url") return ImageInputs.decodeDataUrl(image.url, ADAPTER)
|
||||
return Effect.succeed(undefined)
|
||||
})
|
||||
const multipartMask =
|
||||
mask === undefined
|
||||
? undefined
|
||||
: mask.type === "bytes"
|
||||
? { data: mask.data, mediaType: mask.mediaType }
|
||||
: mask.type === "url"
|
||||
? yield* ImageInputs.decodeDataUrl(mask.url, ADAPTER)
|
||||
: undefined
|
||||
const useMultipart =
|
||||
sourceImages.length > 0 &&
|
||||
multipartImages.every((image) => image !== undefined) &&
|
||||
(mask === undefined || multipartMask !== undefined)
|
||||
const path = sourceImages.length === 0 ? PATH : EDIT_PATH
|
||||
const url = applyQuery(`${(input.baseURL ?? DEFAULT_BASE_URL).replace(/\/$/, "")}${path}`, http?.query)
|
||||
|
||||
const requestBody = yield* ProviderShared.validateWith(Schema.decodeUnknownEffect(OpenAIImageBody))(body(request))
|
||||
const http = mergeHttpOptions(request.model.defaults?.http, request.http)
|
||||
const overlaidBody = yield* bodyWithOverlay(requestBody, http?.body)
|
||||
const text = ProviderShared.encodeJson(overlaidBody)
|
||||
const url = applyQuery(`${(input.baseURL ?? DEFAULT_BASE_URL).replace(/\/$/, "")}${PATH}`, http?.query)
|
||||
if (useMultipart) {
|
||||
const form = new FormData()
|
||||
form.append("model", request.model.id)
|
||||
form.append("prompt", request.prompt)
|
||||
Object.entries(mergeJsonRecords(nativeOptions(request.options), http?.body) ?? {}).forEach(([key, value]) => {
|
||||
if (["model", "prompt", "image", "image[]", "images", "mask"].includes(key)) return
|
||||
form.append(key, typeof value === "string" ? value : ProviderShared.encodeJson(value))
|
||||
})
|
||||
multipartImages.forEach((image, index) => {
|
||||
if (image === undefined) return
|
||||
form.append("image[]", imageBlob(image.data, image.mediaType), `image-${index}`)
|
||||
})
|
||||
if (multipartMask !== undefined)
|
||||
form.append("mask", imageBlob(multipartMask.data, multipartMask.mediaType), "mask")
|
||||
const headers = yield* Auth.toEffect(input.auth)({
|
||||
request,
|
||||
method: "POST",
|
||||
url,
|
||||
body: "[multipart/form-data]",
|
||||
headers: Headers.remove(Headers.fromInput({ ...input.headers, ...http?.headers }), "content-type"),
|
||||
})
|
||||
const response = yield* execute(
|
||||
HttpClientRequest.post(url).pipe(HttpClientRequest.setHeaders(headers), HttpClientRequest.bodyFormData(form)),
|
||||
)
|
||||
return yield* parseResponse(response, request.options, http?.body)
|
||||
}
|
||||
|
||||
const references = sourceImages.map((image) => {
|
||||
if (image.type === "bytes") return { image_url: ImageInputs.dataUrl(image) }
|
||||
if (image.type === "url") return { image_url: image.url }
|
||||
if (image.type === "file-id") return { file_id: image.id }
|
||||
return undefined
|
||||
})
|
||||
if (references.some((image) => image === undefined))
|
||||
return yield* ImageInputs.invalid(ADAPTER, "OpenAI Images accepts image URLs, data URLs, bytes, and file IDs")
|
||||
const maskReference =
|
||||
mask === undefined
|
||||
? undefined
|
||||
: mask.type === "bytes"
|
||||
? { image_url: ImageInputs.dataUrl(mask) }
|
||||
: mask.type === "url"
|
||||
? { image_url: mask.url }
|
||||
: mask.type === "file-id"
|
||||
? { file_id: mask.id }
|
||||
: undefined
|
||||
if (mask !== undefined && maskReference === undefined)
|
||||
return yield* ImageInputs.invalid(ADAPTER, "OpenAI Images accepts masks as URLs, data URLs, bytes, or file IDs")
|
||||
const requestBody = mergeJsonRecords(
|
||||
{
|
||||
model: request.model.id,
|
||||
prompt: request.prompt,
|
||||
images: references.length === 0 ? undefined : references,
|
||||
mask: maskReference,
|
||||
},
|
||||
nativeOptions(request.options),
|
||||
http?.body,
|
||||
) as OpenAIImageBody
|
||||
const text = ProviderShared.encodeJson(requestBody)
|
||||
const headers = yield* Auth.toEffect(input.auth)({
|
||||
request,
|
||||
method: "POST",
|
||||
|
|
@ -152,55 +198,71 @@ export const model = (input: ModelInput) => {
|
|||
HttpClientRequest.bodyText(text, "application/json"),
|
||||
),
|
||||
)
|
||||
const payload = yield* response.json.pipe(
|
||||
Effect.mapError(() => invalidOutput("Failed to read the OpenAI Images response")),
|
||||
)
|
||||
const decoded = yield* Schema.decodeUnknownEffect(OpenAIImageResponse)(payload).pipe(
|
||||
Effect.mapError(() => invalidOutput("OpenAI Images returned an invalid response")),
|
||||
)
|
||||
const format = decoded.output_format ?? providerOptions(request).outputFormat ?? "png"
|
||||
const images = yield* Effect.forEach(decoded.data, (item, index) => {
|
||||
if (item.b64_json)
|
||||
return Effect.fromResult(Encoding.decodeBase64(item.b64_json)).pipe(
|
||||
Effect.mapError(() => invalidOutput(`OpenAI Images result ${index} contains invalid base64 data`)),
|
||||
Effect.map(
|
||||
(data) =>
|
||||
new GeneratedImage({
|
||||
mediaType: `image/${format}`,
|
||||
data,
|
||||
providerMetadata:
|
||||
item.revised_prompt === undefined ? undefined : { openai: { revisedPrompt: item.revised_prompt } },
|
||||
}),
|
||||
),
|
||||
)
|
||||
if (item.url)
|
||||
return Effect.succeed(
|
||||
return yield* parseResponse(response, request.options, http?.body)
|
||||
}),
|
||||
}
|
||||
return ImageModel.make<OpenAIImageOptions>({ id: input.id, provider: "openai", route, http: input.http })
|
||||
}
|
||||
|
||||
const parseResponse = Effect.fn("OpenAIImages.parseResponse")(function* (
|
||||
response: HttpClientResponse.HttpClientResponse,
|
||||
options: OpenAIImageOptions | undefined,
|
||||
overlay: Record<string, unknown> | undefined,
|
||||
) {
|
||||
const payload = yield* response.json.pipe(
|
||||
Effect.mapError(() => invalidOutput("Failed to read the OpenAI Images response")),
|
||||
)
|
||||
const decoded = yield* Schema.decodeUnknownEffect(OpenAIImageResponse)(payload).pipe(
|
||||
Effect.mapError(() => invalidOutput("OpenAI Images returned an invalid response")),
|
||||
)
|
||||
const requestBody = mergeJsonRecords(nativeOptions(options), overlay)
|
||||
const format =
|
||||
decoded.output_format ?? (typeof requestBody?.output_format === "string" ? requestBody.output_format : "png")
|
||||
const images = yield* Effect.forEach(decoded.data, (item, index) => {
|
||||
if (item.b64_json)
|
||||
return Effect.fromResult(Encoding.decodeBase64(item.b64_json)).pipe(
|
||||
Effect.mapError(() => invalidOutput(`OpenAI Images result ${index} contains invalid base64 data`)),
|
||||
Effect.map(
|
||||
(data) =>
|
||||
new GeneratedImage({
|
||||
mediaType: `image/${format}`,
|
||||
data: item.url,
|
||||
data,
|
||||
providerMetadata:
|
||||
item.revised_prompt === undefined ? undefined : { openai: { revisedPrompt: item.revised_prompt } },
|
||||
}),
|
||||
)
|
||||
return Effect.fail(invalidOutput(`OpenAI Images result ${index} has neither image data nor a URL`))
|
||||
})
|
||||
if (images.length === 0) return yield* invalidOutput("OpenAI Images returned no images")
|
||||
return new ImageResponse({
|
||||
images,
|
||||
usage:
|
||||
decoded.usage === undefined
|
||||
? undefined
|
||||
: new Usage({
|
||||
inputTokens: decoded.usage.input_tokens,
|
||||
outputTokens: decoded.usage.output_tokens,
|
||||
totalTokens: decoded.usage.total_tokens,
|
||||
providerMetadata: { openai: decoded.usage },
|
||||
}),
|
||||
providerMetadata: { openai: { outputFormat: format } },
|
||||
})
|
||||
}),
|
||||
}
|
||||
return ImageModel.make({ id: input.id, provider: "openai", route, defaults: input.defaults })
|
||||
),
|
||||
)
|
||||
if (item.url)
|
||||
return Effect.succeed(
|
||||
new GeneratedImage({
|
||||
mediaType: `image/${format}`,
|
||||
data: item.url,
|
||||
providerMetadata:
|
||||
item.revised_prompt === undefined ? undefined : { openai: { revisedPrompt: item.revised_prompt } },
|
||||
}),
|
||||
)
|
||||
return Effect.fail(invalidOutput(`OpenAI Images result ${index} has neither image data nor a URL`))
|
||||
})
|
||||
if (images.length === 0) return yield* invalidOutput("OpenAI Images returned no images")
|
||||
return new ImageResponse({
|
||||
images,
|
||||
usage:
|
||||
decoded.usage === undefined
|
||||
? undefined
|
||||
: new Usage({
|
||||
inputTokens: decoded.usage.input_tokens,
|
||||
outputTokens: decoded.usage.output_tokens,
|
||||
totalTokens: decoded.usage.total_tokens,
|
||||
providerMetadata: { openai: decoded.usage },
|
||||
}),
|
||||
providerMetadata: { openai: { outputFormat: format } },
|
||||
})
|
||||
})
|
||||
|
||||
const imageBlob = (data: Uint8Array, mediaType: string) => {
|
||||
const buffer = new ArrayBuffer(data.byteLength)
|
||||
new Uint8Array(buffer).set(data)
|
||||
return new Blob([buffer], { type: mediaType })
|
||||
}
|
||||
|
||||
export const OpenAIImages = {
|
||||
|
|
|
|||
34
packages/ai/src/protocols/utils/image-input.ts
Normal file
34
packages/ai/src/protocols/utils/image-input.ts
Normal file
|
|
@ -0,0 +1,34 @@
|
|||
import { Effect, Encoding } from "effect"
|
||||
import type { ImageInput } from "../../image"
|
||||
import { InvalidRequestReason, LLMError } from "../../schema"
|
||||
|
||||
const invalid = (module: string, message: string) =>
|
||||
new LLMError({
|
||||
module,
|
||||
method: "generate",
|
||||
reason: new InvalidRequestReason({ message }),
|
||||
})
|
||||
|
||||
export const dataUrl = (input: Extract<ImageInput, { readonly type: "bytes" }>) =>
|
||||
`data:${input.mediaType};base64,${Encoding.encodeBase64(input.data)}`
|
||||
|
||||
export const decodeDataUrl = (
|
||||
url: string,
|
||||
module: string,
|
||||
): Effect.Effect<{ readonly mediaType: string; readonly data: Uint8Array } | undefined, LLMError> => {
|
||||
if (!url.startsWith("data:")) return Effect.succeed(undefined)
|
||||
const match = /^data:([^;,]+);base64,(.*)$/s.exec(url)
|
||||
if (!match) return Effect.fail(invalid(module, "Image data URLs must contain a MIME type and base64 data"))
|
||||
return Effect.fromResult(Encoding.decodeBase64(match[2])).pipe(
|
||||
Effect.mapError(() => invalid(module, "Image data URL contains invalid base64 data")),
|
||||
Effect.map((data) => ({ mediaType: match[1], data })),
|
||||
)
|
||||
}
|
||||
|
||||
export const invalidImageInput = invalid
|
||||
|
||||
export const ImageInputs = {
|
||||
dataUrl,
|
||||
decodeDataUrl,
|
||||
invalid: invalidImageInput,
|
||||
} as const
|
||||
|
|
@ -44,7 +44,7 @@ export const reasoningDelta = (
|
|||
providerMetadata?: ProviderMetadata,
|
||||
): State => {
|
||||
const started = reasoningStart(state, events, id, providerMetadata)
|
||||
events.push(LLMEvent.reasoningDelta({ id, text }))
|
||||
events.push(LLMEvent.reasoningDelta({ id, text, providerMetadata }))
|
||||
return started
|
||||
}
|
||||
|
||||
|
|
|
|||
|
|
@ -140,8 +140,8 @@ export const appendOrStart = <K extends StreamKey>(
|
|||
missingToolMessage: string,
|
||||
): AppendOutcome<K> | LLMError => {
|
||||
const current = tools[key]
|
||||
const id = delta.id ?? current?.id
|
||||
const name = delta.name ?? current?.name
|
||||
const id = current?.id ?? delta.id
|
||||
const name = current?.name ?? delta.name
|
||||
if (!id || !name) return eventError(route, missingToolMessage)
|
||||
|
||||
const tool = {
|
||||
|
|
|
|||
202
packages/ai/src/protocols/xai-images.ts
Normal file
202
packages/ai/src/protocols/xai-images.ts
Normal file
|
|
@ -0,0 +1,202 @@
|
|||
import { Effect, Encoding, Schema } from "effect"
|
||||
import { Headers, HttpClientRequest } from "effect/unstable/http"
|
||||
import { GeneratedImage, ImageModel, ImageResponse, type ImageRequestFor, type ImageRoute } from "../image"
|
||||
import { Auth, type Definition as AuthDefinition } from "../route/auth"
|
||||
import {
|
||||
InvalidProviderOutputReason,
|
||||
LLMError,
|
||||
Usage,
|
||||
mergeHttpOptions,
|
||||
mergeJsonRecords,
|
||||
type HttpOptions,
|
||||
} from "../schema"
|
||||
import { ProviderShared, optionalNull } from "./shared"
|
||||
import { ImageInputs } from "./utils/image-input"
|
||||
|
||||
const ADAPTER = "xai-images"
|
||||
export const DEFAULT_BASE_URL = "https://api.x.ai/v1"
|
||||
export const PATH = "/images/generations"
|
||||
export const EDIT_PATH = "/images/edits"
|
||||
|
||||
export type XAIImageString<Known extends string> = Known | (string & {})
|
||||
|
||||
export type XAIImageOptions = {
|
||||
readonly n?: number
|
||||
readonly aspectRatio?: XAIImageString<
|
||||
| "1:1"
|
||||
| "3:4"
|
||||
| "4:3"
|
||||
| "9:16"
|
||||
| "16:9"
|
||||
| "2:3"
|
||||
| "3:2"
|
||||
| "9:19.5"
|
||||
| "19.5:9"
|
||||
| "9:20"
|
||||
| "20:9"
|
||||
| "1:2"
|
||||
| "2:1"
|
||||
| "auto"
|
||||
>
|
||||
readonly aspect_ratio?: XAIImageString<
|
||||
| "1:1"
|
||||
| "3:4"
|
||||
| "4:3"
|
||||
| "9:16"
|
||||
| "16:9"
|
||||
| "2:3"
|
||||
| "3:2"
|
||||
| "9:19.5"
|
||||
| "19.5:9"
|
||||
| "9:20"
|
||||
| "20:9"
|
||||
| "1:2"
|
||||
| "2:1"
|
||||
| "auto"
|
||||
>
|
||||
readonly resolution?: XAIImageString<"1k" | "2k">
|
||||
readonly responseFormat?: XAIImageString<"url" | "b64_json">
|
||||
readonly response_format?: XAIImageString<"url" | "b64_json">
|
||||
} & Record<string, unknown>
|
||||
|
||||
type XAIImageBody = Record<string, unknown> & {
|
||||
readonly model: string
|
||||
readonly prompt: string
|
||||
}
|
||||
|
||||
const XAIImageResponse = Schema.Struct({
|
||||
data: Schema.Array(
|
||||
Schema.Struct({
|
||||
b64_json: optionalNull(Schema.String),
|
||||
url: optionalNull(Schema.String),
|
||||
revised_prompt: optionalNull(Schema.String),
|
||||
mime_type: optionalNull(Schema.String),
|
||||
}),
|
||||
),
|
||||
usage: Schema.optional(Schema.Unknown),
|
||||
})
|
||||
|
||||
export interface ModelInput {
|
||||
readonly id: string
|
||||
readonly auth: AuthDefinition
|
||||
readonly baseURL?: string
|
||||
readonly headers?: Record<string, string>
|
||||
readonly http?: HttpOptions
|
||||
}
|
||||
|
||||
const nativeOptions = (options: XAIImageOptions | undefined) => {
|
||||
if (!options) return undefined
|
||||
const { aspectRatio, responseFormat, ...native } = options
|
||||
return {
|
||||
aspect_ratio: aspectRatio,
|
||||
response_format: responseFormat,
|
||||
...native,
|
||||
}
|
||||
}
|
||||
|
||||
const invalidOutput = (message: string) =>
|
||||
new LLMError({
|
||||
module: ADAPTER,
|
||||
method: "generate",
|
||||
reason: new InvalidProviderOutputReason({ message, route: ADAPTER }),
|
||||
})
|
||||
|
||||
const applyQuery = (url: string, query: Record<string, string> | undefined) => {
|
||||
if (!query) return url
|
||||
const next = new URL(url)
|
||||
Object.entries(query).forEach(([key, value]) => next.searchParams.set(key, value))
|
||||
return next.toString()
|
||||
}
|
||||
|
||||
export const model = (input: ModelInput) => {
|
||||
const route: ImageRoute<XAIImageOptions> = {
|
||||
id: ADAPTER,
|
||||
generate: Effect.fn("XAIImages.generate")(function* (request: ImageRequestFor<XAIImageOptions>, execute) {
|
||||
const http = mergeHttpOptions(request.model.http, request.http)
|
||||
const imageReferences = (request.images ?? []).map((image) => {
|
||||
if (image.type === "bytes") return { url: ImageInputs.dataUrl(image), type: "image_url" as const }
|
||||
if (image.type === "url") return { url: image.url, type: "image_url" as const }
|
||||
if (image.type === "file-id") return { file_id: image.id }
|
||||
return undefined
|
||||
})
|
||||
if (imageReferences.some((image) => image === undefined))
|
||||
return yield* ImageInputs.invalid(ADAPTER, "xAI Images accepts image URLs, data URLs, bytes, and file IDs")
|
||||
const requestBody = mergeJsonRecords(
|
||||
{
|
||||
model: request.model.id,
|
||||
prompt: request.prompt,
|
||||
image: imageReferences.length === 1 ? imageReferences[0] : undefined,
|
||||
images: imageReferences.length > 1 ? imageReferences : undefined,
|
||||
},
|
||||
nativeOptions(request.options),
|
||||
http?.body,
|
||||
) as XAIImageBody
|
||||
const text = ProviderShared.encodeJson(requestBody)
|
||||
const url = applyQuery(
|
||||
`${(input.baseURL ?? DEFAULT_BASE_URL).replace(/\/$/, "")}${imageReferences.length === 0 ? PATH : EDIT_PATH}`,
|
||||
http?.query,
|
||||
)
|
||||
const headers = yield* Auth.toEffect(input.auth)({
|
||||
request,
|
||||
method: "POST",
|
||||
url,
|
||||
body: text,
|
||||
headers: Headers.fromInput({ ...input.headers, ...http?.headers }),
|
||||
})
|
||||
const response = yield* execute(
|
||||
HttpClientRequest.post(url).pipe(
|
||||
HttpClientRequest.setHeaders(headers),
|
||||
HttpClientRequest.bodyText(text, "application/json"),
|
||||
),
|
||||
)
|
||||
const payload = yield* response.json.pipe(
|
||||
Effect.mapError(() => invalidOutput("Failed to read the xAI Images response")),
|
||||
)
|
||||
const decoded = yield* Schema.decodeUnknownEffect(XAIImageResponse)(payload).pipe(
|
||||
Effect.mapError(() => invalidOutput("xAI Images returned an invalid response")),
|
||||
)
|
||||
const images = yield* Effect.forEach(decoded.data, (item, index) => {
|
||||
const mediaType = item.mime_type ?? "application/octet-stream"
|
||||
if (item.b64_json)
|
||||
return Effect.fromResult(Encoding.decodeBase64(item.b64_json)).pipe(
|
||||
Effect.mapError(() => invalidOutput(`xAI Images result ${index} contains invalid base64 data`)),
|
||||
Effect.map(
|
||||
(data) =>
|
||||
new GeneratedImage({
|
||||
mediaType,
|
||||
data,
|
||||
providerMetadata:
|
||||
item.revised_prompt === undefined || item.revised_prompt === null
|
||||
? undefined
|
||||
: { xai: { revisedPrompt: item.revised_prompt } },
|
||||
}),
|
||||
),
|
||||
)
|
||||
if (item.url)
|
||||
return Effect.succeed(
|
||||
new GeneratedImage({
|
||||
mediaType,
|
||||
data: item.url,
|
||||
providerMetadata:
|
||||
item.revised_prompt === undefined || item.revised_prompt === null
|
||||
? undefined
|
||||
: { xai: { revisedPrompt: item.revised_prompt } },
|
||||
}),
|
||||
)
|
||||
return Effect.fail(invalidOutput(`xAI Images result ${index} has neither image data nor a URL`))
|
||||
})
|
||||
if (images.length === 0) return yield* invalidOutput("xAI Images returned no images")
|
||||
const usage = ProviderShared.isRecord(decoded.usage) ? decoded.usage : undefined
|
||||
return new ImageResponse({
|
||||
images,
|
||||
usage: usage === undefined ? undefined : new Usage({ providerMetadata: { xai: usage } }),
|
||||
providerMetadata: usage === undefined ? undefined : { xai: { usage } },
|
||||
})
|
||||
}),
|
||||
}
|
||||
return ImageModel.make<XAIImageOptions>({ id: input.id, provider: "xai", route, http: input.http })
|
||||
}
|
||||
|
||||
export const XAIImages = {
|
||||
model,
|
||||
} as const
|
||||
132
packages/ai/src/protocols/zai-images.ts
Normal file
132
packages/ai/src/protocols/zai-images.ts
Normal file
|
|
@ -0,0 +1,132 @@
|
|||
import { Effect, Schema } from "effect"
|
||||
import { Headers, HttpClientRequest } from "effect/unstable/http"
|
||||
import { GeneratedImage, ImageModel, ImageResponse, type ImageRequestFor, type ImageRoute } from "../image"
|
||||
import { Auth, type Definition as AuthDefinition } from "../route/auth"
|
||||
import { InvalidProviderOutputReason, LLMError, mergeHttpOptions, mergeJsonRecords, type HttpOptions } from "../schema"
|
||||
import { ProviderShared } from "./shared"
|
||||
import { ImageInputs } from "./utils/image-input"
|
||||
|
||||
const ADAPTER = "zai-images"
|
||||
export const DEFAULT_BASE_URL = "https://api.z.ai/api/paas/v4"
|
||||
export const PATH = "/images/generations"
|
||||
|
||||
export type ZAIImageString<Known extends string> = Known | (string & {})
|
||||
|
||||
export type ZAIImageOptions = {
|
||||
readonly size?: ZAIImageString<
|
||||
"1024x1024" | "768x1344" | "864x1152" | "1344x768" | "1152x864" | "1440x720" | "720x1440"
|
||||
>
|
||||
readonly quality?: ZAIImageString<"hd" | "standard">
|
||||
readonly userID?: string
|
||||
} & Record<string, unknown>
|
||||
|
||||
type ZAIImageBody = Record<string, unknown> & {
|
||||
readonly model: string
|
||||
readonly prompt: string
|
||||
}
|
||||
|
||||
const ZAIImageResponse = Schema.Struct({
|
||||
created: Schema.optional(Schema.Int),
|
||||
id: Schema.optional(Schema.String),
|
||||
request_id: Schema.optional(Schema.String),
|
||||
data: Schema.Array(Schema.Struct({ url: Schema.String })),
|
||||
content_filter: Schema.optional(
|
||||
Schema.Array(
|
||||
Schema.Struct({
|
||||
role: Schema.optional(Schema.String),
|
||||
level: Schema.optional(Schema.Number),
|
||||
}),
|
||||
),
|
||||
),
|
||||
})
|
||||
|
||||
export interface ModelInput {
|
||||
readonly id: string
|
||||
readonly auth: AuthDefinition
|
||||
readonly baseURL?: string
|
||||
readonly headers?: Record<string, string>
|
||||
readonly http?: HttpOptions
|
||||
}
|
||||
|
||||
const nativeOptions = (options: ZAIImageOptions | undefined) => {
|
||||
if (!options) return undefined
|
||||
const { userID, ...native } = options
|
||||
return {
|
||||
user_id: userID,
|
||||
...native,
|
||||
}
|
||||
}
|
||||
|
||||
const invalidOutput = (message: string) =>
|
||||
new LLMError({
|
||||
module: ADAPTER,
|
||||
method: "generate",
|
||||
reason: new InvalidProviderOutputReason({ message, route: ADAPTER }),
|
||||
})
|
||||
|
||||
const applyQuery = (url: string, query: Record<string, string> | undefined) => {
|
||||
if (!query) return url
|
||||
const next = new URL(url)
|
||||
Object.entries(query).forEach(([key, value]) => next.searchParams.set(key, value))
|
||||
return next.toString()
|
||||
}
|
||||
|
||||
export const model = (input: ModelInput) => {
|
||||
const route: ImageRoute<ZAIImageOptions> = {
|
||||
id: ADAPTER,
|
||||
generate: Effect.fn("ZAIImages.generate")(function* (request: ImageRequestFor<ZAIImageOptions>, execute) {
|
||||
if ((request.images?.length ?? 0) > 0)
|
||||
return yield* ImageInputs.invalid(ADAPTER, "Z.ai hosted image generation does not support image inputs")
|
||||
const http = mergeHttpOptions(request.model.http, request.http)
|
||||
const requestBody = mergeJsonRecords(
|
||||
{ model: request.model.id, prompt: request.prompt },
|
||||
nativeOptions(request.options),
|
||||
http?.body,
|
||||
) as ZAIImageBody
|
||||
const text = ProviderShared.encodeJson(requestBody)
|
||||
const url = applyQuery(`${(input.baseURL ?? DEFAULT_BASE_URL).replace(/\/$/, "")}${PATH}`, http?.query)
|
||||
const headers = yield* Auth.toEffect(input.auth)({
|
||||
request,
|
||||
method: "POST",
|
||||
url,
|
||||
body: text,
|
||||
headers: Headers.fromInput({ ...input.headers, ...http?.headers }),
|
||||
})
|
||||
const response = yield* execute(
|
||||
HttpClientRequest.post(url).pipe(
|
||||
HttpClientRequest.setHeaders(headers),
|
||||
HttpClientRequest.bodyText(text, "application/json"),
|
||||
),
|
||||
)
|
||||
const payload = yield* response.json.pipe(
|
||||
Effect.mapError(() => invalidOutput("Failed to read the Z.ai Images response")),
|
||||
)
|
||||
const decoded = yield* Schema.decodeUnknownEffect(ZAIImageResponse)(payload).pipe(
|
||||
Effect.mapError(() => invalidOutput("Z.ai Images returned an invalid response")),
|
||||
)
|
||||
if (decoded.data.length === 0) return yield* invalidOutput("Z.ai Images returned no images")
|
||||
return new ImageResponse({
|
||||
images: decoded.data.map(
|
||||
(item) =>
|
||||
new GeneratedImage({
|
||||
mediaType: "application/octet-stream",
|
||||
data: item.url,
|
||||
}),
|
||||
),
|
||||
providerMetadata: {
|
||||
zai: {
|
||||
created: decoded.created,
|
||||
id: decoded.id,
|
||||
requestID: decoded.request_id,
|
||||
contentFilter: decoded.content_filter,
|
||||
},
|
||||
},
|
||||
})
|
||||
}),
|
||||
}
|
||||
return ImageModel.make<ZAIImageOptions>({ id: input.id, provider: "zai", route, http: input.http })
|
||||
}
|
||||
|
||||
export const ZAIImages = {
|
||||
model,
|
||||
} as const
|
||||
|
|
@ -16,13 +16,17 @@ import {
|
|||
|
||||
const patterns = [
|
||||
/prompt is too long/i,
|
||||
/request_too_large/i,
|
||||
/input is too long for requested model/i,
|
||||
/exceeds the context window/i,
|
||||
/exceeds (?:the )?(?:model'?s )?maximum context length(?: of [\d,]+ tokens?|\s*\([\d,]+\))/i,
|
||||
/input token count.*exceeds the maximum/i,
|
||||
/tokens in request more than max tokens allowed/i,
|
||||
/maximum prompt length is \d+/i,
|
||||
/reduce the length of the messages/i,
|
||||
/maximum context length is \d+ tokens/i,
|
||||
/exceeds (?:the )?maximum allowed input length of [\d,]+ tokens?/i,
|
||||
/input \(\d+ tokens\) is longer than the model'?s context length \(\d+ tokens\)/i,
|
||||
/exceeds the limit of \d+/i,
|
||||
/exceeds the available context size/i,
|
||||
/greater than the context length/i,
|
||||
|
|
@ -34,11 +38,17 @@ const patterns = [
|
|||
/input length.*exceeds.*context length/i,
|
||||
/prompt too long; exceeded (?:max )?context length/i,
|
||||
/too large for model with \d+ maximum context length/i,
|
||||
/prompt has [\d,]+ tokens?, but the configured context size is [\d,]+ tokens?/i,
|
||||
/model_context_window_exceeded/i,
|
||||
/too many tokens/i,
|
||||
/token limit exceeded/i,
|
||||
]
|
||||
|
||||
const exclusions = [/^(throttling error|service unavailable):/i, /rate limit/i, /too many requests/i]
|
||||
|
||||
export const isContextOverflow = (message: string) =>
|
||||
patterns.some((pattern) => pattern.test(message)) || /^4(00|13)\s*(status code)?\s*\(no body\)/i.test(message)
|
||||
!exclusions.some((pattern) => pattern.test(message)) &&
|
||||
(patterns.some((pattern) => pattern.test(message)) || /^4(00|13)\s*(status code)?\s*\(no body\)/i.test(message))
|
||||
|
||||
export const isContextOverflowFailure = (failure: unknown) =>
|
||||
failure instanceof LLMError
|
||||
|
|
|
|||
|
|
@ -2,14 +2,20 @@ import type { RouteDefaultsInput } from "../route/client"
|
|||
import { Auth } from "../route/auth"
|
||||
import type { ProviderAuthOption } from "../route/auth-options"
|
||||
import type { ProviderPackage } from "../provider-package"
|
||||
import { ProviderID, type ModelID, type ProviderOptions } from "../schema"
|
||||
import * as Gemini from "../protocols/gemini"
|
||||
import { HttpOptions, ProviderID, mergeHttpOptions, type ModelID, type ProviderOptions } from "../schema"
|
||||
import { Gemini } from "../protocols/gemini"
|
||||
import { GoogleImages } from "../protocols/google-images"
|
||||
|
||||
export type { GoogleImageOptions } from "../protocols/google-images"
|
||||
|
||||
export const id = ProviderID.make("google")
|
||||
|
||||
export const routes = [Gemini.route]
|
||||
|
||||
export type Config = RouteDefaultsInput & ProviderAuthOption<"optional"> & { readonly baseURL?: string }
|
||||
export type Config = RouteDefaultsInput &
|
||||
ProviderAuthOption<"optional"> & {
|
||||
readonly baseURL?: string
|
||||
}
|
||||
|
||||
export interface Settings extends ProviderPackage.Settings {
|
||||
readonly apiKey?: string
|
||||
|
|
@ -31,9 +37,18 @@ const configuredRoute = (input: Config) => {
|
|||
|
||||
export const configure = (input: Config = {}) => {
|
||||
const route = configuredRoute(input)
|
||||
const image = (modelID: string | ModelID) =>
|
||||
GoogleImages.model({
|
||||
id: modelID,
|
||||
auth: auth(input),
|
||||
baseURL: input.baseURL,
|
||||
headers: input.headers,
|
||||
http: mergeHttpOptions(input.http === undefined ? undefined : HttpOptions.make(input.http)),
|
||||
})
|
||||
return {
|
||||
id,
|
||||
model: (modelID: string | ModelID) => route.model({ id: modelID }),
|
||||
image,
|
||||
configure,
|
||||
}
|
||||
}
|
||||
|
|
@ -48,3 +63,5 @@ export const model: ProviderPackage.Definition<Settings>["model"] = (modelID, se
|
|||
limits: settings.limits,
|
||||
providerOptions: settings.providerOptions,
|
||||
}).model(modelID)
|
||||
|
||||
export const image = provider.image
|
||||
|
|
|
|||
|
|
@ -15,3 +15,4 @@ export * as OpenAICompatible from "./openai-compatible"
|
|||
export * as OpenAICompatibleResponses from "./openai-compatible-responses"
|
||||
export * as OpenRouter from "./openrouter"
|
||||
export * as XAI from "./xai"
|
||||
export * as ZAI from "./zai"
|
||||
|
|
|
|||
|
|
@ -5,7 +5,7 @@ import { HttpOptions, ProviderID, ToolDefinition, mergeHttpOptions, type ModelID
|
|||
import * as OpenAIChat from "../protocols/openai-chat"
|
||||
import * as OpenAIResponses from "../protocols/openai-responses"
|
||||
import { withOpenAIOptions, type OpenAIProviderOptionsInput } from "./openai-options"
|
||||
import { OpenAIImages, type OpenAIImageOptions } from "../protocols/openai-images"
|
||||
import { OpenAIImages, type OpenAIImageString } from "../protocols/openai-images"
|
||||
|
||||
export type { OpenAIOptionsInput, OpenAIResponseIncludable } from "./openai-options"
|
||||
export type { OpenAIImageOptions } from "../protocols/openai-images"
|
||||
|
|
@ -22,22 +22,19 @@ export type Config = RouteDefaultsInput &
|
|||
readonly baseURL?: string
|
||||
readonly queryParams?: Record<string, string>
|
||||
readonly providerOptions?: OpenAIProviderOptionsInput
|
||||
readonly image?: ImageConfig
|
||||
}
|
||||
|
||||
export interface ImageConfig {
|
||||
readonly providerOptions?: OpenAIImageOptions
|
||||
}
|
||||
|
||||
export interface ImageGenerationOptions {
|
||||
readonly action?: "auto" | "generate" | "edit"
|
||||
readonly background?: "auto" | "opaque" | "transparent"
|
||||
readonly inputFidelity?: "low" | "high"
|
||||
readonly action?: OpenAIImageString<"auto" | "generate" | "edit">
|
||||
readonly background?: OpenAIImageString<"auto" | "opaque" | "transparent">
|
||||
readonly inputFidelity?: OpenAIImageString<"low" | "high">
|
||||
readonly outputCompression?: number
|
||||
readonly outputFormat?: "png" | "jpeg" | "webp"
|
||||
readonly outputFormat?: OpenAIImageString<"png" | "jpeg" | "webp">
|
||||
readonly partialImages?: number
|
||||
readonly quality?: "auto" | "low" | "medium" | "high"
|
||||
readonly size?: string
|
||||
readonly quality?: OpenAIImageString<"auto" | "low" | "medium" | "high" | "standard" | "hd">
|
||||
readonly size?: OpenAIImageString<
|
||||
"auto" | "256x256" | "512x512" | "1024x1024" | "1536x1024" | "1024x1536" | "1792x1024" | "1024x1792"
|
||||
>
|
||||
}
|
||||
|
||||
export const imageGeneration = (options: ImageGenerationOptions = {}) =>
|
||||
|
|
@ -73,7 +70,7 @@ export interface Settings extends ProviderPackage.Settings {
|
|||
const auth = (options: ProviderAuthOption<"optional">) => AuthOptions.bearer(options, "OPENAI_API_KEY")
|
||||
|
||||
const defaults = (input: Config) => {
|
||||
const { apiKey: _, auth: _auth, baseURL: _baseURL, queryParams: _queryParams, image: _image, ...rest } = input
|
||||
const { apiKey: _, auth: _auth, baseURL: _baseURL, queryParams: _queryParams, ...rest } = input
|
||||
return rest
|
||||
}
|
||||
|
||||
|
|
@ -99,14 +96,10 @@ export const configure = (input: Config = {}) => {
|
|||
auth: auth(input),
|
||||
baseURL: input.baseURL,
|
||||
headers: input.headers,
|
||||
defaults: {
|
||||
providerOptions:
|
||||
input.image?.providerOptions === undefined ? undefined : { openai: { ...input.image.providerOptions } },
|
||||
http: mergeHttpOptions(
|
||||
input.http === undefined ? undefined : HttpOptions.make(input.http),
|
||||
input.queryParams === undefined ? undefined : new HttpOptions({ query: input.queryParams }),
|
||||
),
|
||||
},
|
||||
http: mergeHttpOptions(
|
||||
input.http === undefined ? undefined : HttpOptions.make(input.http),
|
||||
input.queryParams === undefined ? undefined : new HttpOptions({ query: input.queryParams }),
|
||||
),
|
||||
})
|
||||
|
||||
return {
|
||||
|
|
|
|||
|
|
@ -41,13 +41,31 @@ export const protocol = Protocol.make({
|
|||
schema: OpenRouterBody,
|
||||
from: (request) =>
|
||||
OpenAIChat.protocol.body.from(request).pipe(
|
||||
Effect.map(
|
||||
(body) =>
|
||||
({
|
||||
...body,
|
||||
...bodyOptions(request.providerOptions?.openrouter),
|
||||
}) as OpenRouterBody,
|
||||
),
|
||||
Effect.map((body) => {
|
||||
const sourceAssistants = request.messages.filter((message) => message.role === "assistant")
|
||||
let assistantIndex = 0
|
||||
const messages = body.messages.map((message) => {
|
||||
if (message.role !== "assistant") return message
|
||||
const source = sourceAssistants[assistantIndex++]
|
||||
const reasoning = source?.content
|
||||
.filter((part) => part.type === "reasoning")
|
||||
.map((part) => part.text)
|
||||
.join("")
|
||||
const reasoningDetails = Array.isArray(message.reasoning_details) ? message.reasoning_details : undefined
|
||||
return {
|
||||
...message,
|
||||
reasoning_content: undefined,
|
||||
reasoning_text: undefined,
|
||||
reasoning: reasoning && reasoningDetails && reasoningDetails.length > 0 ? reasoning : undefined,
|
||||
reasoning_details: reasoningDetails,
|
||||
}
|
||||
})
|
||||
return {
|
||||
...body,
|
||||
messages,
|
||||
...bodyOptions(request.providerOptions?.openrouter),
|
||||
} as OpenRouterBody
|
||||
}),
|
||||
),
|
||||
},
|
||||
stream: OpenAIChat.protocol.stream,
|
||||
|
|
|
|||
|
|
@ -1,9 +1,10 @@
|
|||
import { AuthOptions, type ProviderAuthOption } from "../route/auth-options"
|
||||
import type { RouteDefaultsInput } from "../route/client"
|
||||
import { ProviderID, type ModelID } from "../schema"
|
||||
import { HttpOptions, ProviderID, type ModelID } from "../schema"
|
||||
import * as OpenAICompatibleProfiles from "./openai-compatible-profile"
|
||||
import * as OpenAICompatibleChat from "../protocols/openai-compatible-chat"
|
||||
import * as OpenAIResponses from "../protocols/openai-responses"
|
||||
import { XAIImages } from "../protocols/xai-images"
|
||||
|
||||
export const id = ProviderID.make("xai")
|
||||
|
||||
|
|
@ -12,6 +13,8 @@ export type ModelOptions = RouteDefaultsInput &
|
|||
readonly baseURL?: string
|
||||
}
|
||||
|
||||
export type { XAIImageOptions } from "../protocols/xai-images"
|
||||
|
||||
export const routes = [OpenAIResponses.route, OpenAICompatibleChat.route]
|
||||
|
||||
const auth = (options: ProviderAuthOption<"optional">) => AuthOptions.bearer(options, "XAI_API_KEY")
|
||||
|
|
@ -41,11 +44,20 @@ export const configure = (input: ModelOptions = {}) => {
|
|||
const chatRoute = configuredChatRoute(input)
|
||||
const responses = (modelID: string | ModelID) => responsesRoute.model({ id: modelID })
|
||||
const chat = (modelID: string | ModelID) => chatRoute.model({ id: modelID })
|
||||
const image = (modelID: string | ModelID) =>
|
||||
XAIImages.model({
|
||||
id: modelID,
|
||||
auth: auth(input),
|
||||
baseURL: input.baseURL ?? OpenAICompatibleProfiles.profiles.xai.baseURL,
|
||||
headers: input.headers,
|
||||
http: input.http === undefined ? undefined : HttpOptions.make(input.http),
|
||||
})
|
||||
return {
|
||||
id,
|
||||
model: responses,
|
||||
responses,
|
||||
chat,
|
||||
image,
|
||||
configure,
|
||||
}
|
||||
}
|
||||
|
|
@ -54,3 +66,4 @@ export const provider = configure()
|
|||
export const model = provider.model
|
||||
export const responses = provider.responses
|
||||
export const chat = provider.chat
|
||||
export const image = provider.image
|
||||
|
|
|
|||
35
packages/ai/src/providers/zai.ts
Normal file
35
packages/ai/src/providers/zai.ts
Normal file
|
|
@ -0,0 +1,35 @@
|
|||
import { ZAIImages } from "../protocols/zai-images"
|
||||
import { AuthOptions, type ProviderAuthOption } from "../route/auth-options"
|
||||
import { HttpOptions, ProviderID, type ModelID } from "../schema"
|
||||
|
||||
export const id = ProviderID.make("zai")
|
||||
|
||||
export type Config = ProviderAuthOption<"optional"> & {
|
||||
readonly baseURL?: string
|
||||
readonly headers?: Record<string, string>
|
||||
readonly http?: HttpOptions.Input
|
||||
}
|
||||
|
||||
export type { ZAIImageOptions } from "../protocols/zai-images"
|
||||
|
||||
const auth = (options: ProviderAuthOption<"optional">) => AuthOptions.bearer(options, "ZAI_API_KEY")
|
||||
|
||||
export const configure = (input: Config = {}) => {
|
||||
const image = (modelID: string | ModelID) =>
|
||||
ZAIImages.model({
|
||||
id: modelID,
|
||||
auth: auth(input),
|
||||
baseURL: input.baseURL,
|
||||
headers: input.headers,
|
||||
http: input.http === undefined ? undefined : HttpOptions.make(input.http),
|
||||
})
|
||||
|
||||
return {
|
||||
id,
|
||||
image,
|
||||
configure,
|
||||
}
|
||||
}
|
||||
|
||||
export const provider = configure()
|
||||
export const image = provider.image
|
||||
|
|
@ -1,7 +1,6 @@
|
|||
import { Config } from "effect"
|
||||
import type { Auth } from "../src/route/auth"
|
||||
import { Auth } from "../src/route"
|
||||
import type { ModelFactory } from "../src/route/auth-options"
|
||||
import { Auth as RuntimeAuth } from "../src/route/auth"
|
||||
import * as OpenAIChat from "../src/protocols/openai-chat"
|
||||
import * as AmazonBedrock from "../src/providers/amazon-bedrock"
|
||||
import * as Anthropic from "../src/providers/anthropic"
|
||||
|
|
@ -28,7 +27,7 @@ type Model = {
|
|||
readonly id: string
|
||||
}
|
||||
|
||||
declare const auth: Auth
|
||||
declare const auth: Auth.Definition
|
||||
declare const optionalAuthModel: ModelFactory<BaseOptions, "optional", Model>
|
||||
declare const requiredAuthModel: ModelFactory<BaseOptions, "required", Model>
|
||||
const configApiKey = Config.redacted("OPENAI_API_KEY")
|
||||
|
|
@ -76,9 +75,9 @@ OpenAI.responses("gpt-4.1-mini")
|
|||
OpenAI.configure({}).responses("gpt-4.1-mini")
|
||||
OpenAI.configure({ apiKey: "sk-test" }).responses("gpt-4.1-mini")
|
||||
OpenAI.configure({ apiKey: configApiKey }).responses("gpt-4.1-mini")
|
||||
OpenAI.configure({ auth: RuntimeAuth.bearer("oauth-token") }).responses("gpt-4.1-mini")
|
||||
OpenAI.configure({ auth: Auth.bearer("oauth-token") }).responses("gpt-4.1-mini")
|
||||
OpenAI.configure({
|
||||
auth: RuntimeAuth.headers({ authorization: "Bearer gateway" }),
|
||||
auth: Auth.headers({ authorization: "Bearer gateway" }),
|
||||
baseURL: "https://gateway.example.com/v1",
|
||||
}).responses("gpt-4.1-mini")
|
||||
OpenAI.configure({
|
||||
|
|
@ -102,40 +101,40 @@ OpenAI.configure({ generation: { maxTokens: "many" } })
|
|||
OpenAI.configure({ providerOptions: { openai: { store: "false" } } })
|
||||
|
||||
// @ts-expect-error auth is an override, so OpenAI rejects apiKey with auth.
|
||||
OpenAI.configure({ apiKey: "sk-test", auth: RuntimeAuth.bearer("oauth-token") })
|
||||
OpenAI.configure({ apiKey: "sk-test", auth: Auth.bearer("oauth-token") })
|
||||
|
||||
OpenAI.chat("gpt-4.1-mini")
|
||||
OpenAI.configure({ apiKey: "sk-test" }).chat("gpt-4.1-mini")
|
||||
OpenAI.configure({ apiKey: configApiKey }).chat("gpt-4.1-mini")
|
||||
OpenAI.configure({ auth: RuntimeAuth.bearer("oauth-token") }).chat("gpt-4.1-mini")
|
||||
OpenAI.configure({ auth: Auth.bearer("oauth-token") }).chat("gpt-4.1-mini")
|
||||
|
||||
// @ts-expect-error OpenAI chat selectors only accept model ids.
|
||||
OpenAI.configure({ apiKey: "sk-test" }).chat("gpt-4.1-mini", {})
|
||||
|
||||
// @ts-expect-error auth is an override, so OpenAI Chat rejects apiKey with auth.
|
||||
OpenAI.configure({ apiKey: "sk-test", auth: RuntimeAuth.bearer("oauth-token") })
|
||||
OpenAI.configure({ apiKey: "sk-test", auth: Auth.bearer("oauth-token") })
|
||||
|
||||
// @ts-expect-error Azure requires at least one of `resourceName` or `baseURL`.
|
||||
Azure.configure()
|
||||
Azure.configure({ apiKey: "azure-key", resourceName: "resource" }).responses("deployment")
|
||||
Azure.configure({ apiKey: configApiKey, resourceName: "resource" }).responses("deployment")
|
||||
Azure.configure({ auth: RuntimeAuth.header("api-key", "azure-key"), resourceName: "resource" }).responses("deployment")
|
||||
Azure.configure({ auth: Auth.header("api-key", "azure-key"), resourceName: "resource" }).responses("deployment")
|
||||
|
||||
// @ts-expect-error Azure model selectors only accept deployment ids.
|
||||
Azure.configure({ apiKey: "azure-key", resourceName: "resource" }).responses("deployment", {})
|
||||
|
||||
// @ts-expect-error auth is an override, so Azure rejects apiKey with auth.
|
||||
Azure.configure({ resourceName: "resource", apiKey: "azure-key", auth: RuntimeAuth.header("api-key", "override") })
|
||||
Azure.configure({ resourceName: "resource", apiKey: "azure-key", auth: Auth.header("api-key", "override") })
|
||||
|
||||
Azure.configure({ apiKey: "azure-key", resourceName: "resource" }).chat("deployment")
|
||||
Azure.configure({ apiKey: configApiKey, resourceName: "resource" }).chat("deployment")
|
||||
Azure.configure({ auth: RuntimeAuth.header("api-key", "azure-key"), resourceName: "resource" }).chat("deployment")
|
||||
Azure.configure({ auth: Auth.header("api-key", "azure-key"), resourceName: "resource" }).chat("deployment")
|
||||
|
||||
// @ts-expect-error Azure chat model selectors only accept deployment ids.
|
||||
Azure.configure({ apiKey: "azure-key", resourceName: "resource" }).chat("deployment", {})
|
||||
|
||||
// @ts-expect-error auth is an override, so Azure Chat rejects apiKey with auth.
|
||||
Azure.configure({ resourceName: "resource", apiKey: "azure-key", auth: RuntimeAuth.header("api-key", "override") })
|
||||
Azure.configure({ resourceName: "resource", apiKey: "azure-key", auth: Auth.header("api-key", "override") })
|
||||
|
||||
Anthropic.configure({ apiKey: "anthropic-key" }).model("claude-haiku")
|
||||
// @ts-expect-error Anthropic model selectors only accept model ids.
|
||||
|
|
@ -165,7 +164,7 @@ Google.configure({ apiKey: "google-key" }).model("gemini-2.5-flash", {})
|
|||
|
||||
GoogleVertex.configure({ apiKey: "vertex-key" }).model("gemini-3.5-flash")
|
||||
GoogleVertex.configure({ accessToken: "vertex-token", project: "project" }).model("gemini-3.5-flash")
|
||||
GoogleVertex.configure({ auth: RuntimeAuth.bearer("vertex-token"), project: "project" }).model("gemini-3.5-flash")
|
||||
GoogleVertex.configure({ auth: Auth.bearer("vertex-token"), project: "project" }).model("gemini-3.5-flash")
|
||||
// @ts-expect-error Vertex Gemini model selectors only accept model ids.
|
||||
GoogleVertex.configure({ apiKey: "vertex-key" }).model("gemini-3.5-flash", {})
|
||||
// @ts-expect-error Vertex Gemini config accepts only one auth source.
|
||||
|
|
@ -174,7 +173,7 @@ GoogleVertex.configure({ accessToken: "vertex-token", apiKey: "vertex-key", proj
|
|||
GoogleVertex.model("gemini-3.5-flash", { accessToken: "vertex-token", apiKey: "vertex-key", project: "project" })
|
||||
|
||||
GoogleVertexChat.configure({ accessToken: "vertex-token", project: "project" }).model("deepseek-ai/deepseek-v3.2-maas")
|
||||
GoogleVertexChat.configure({ auth: RuntimeAuth.bearer("vertex-token"), project: "project" }).model(
|
||||
GoogleVertexChat.configure({ auth: Auth.bearer("vertex-token"), project: "project" }).model(
|
||||
"deepseek-ai/deepseek-v3.2-maas",
|
||||
)
|
||||
// @ts-expect-error Vertex Chat package settings do not accept API keys.
|
||||
|
|
@ -187,12 +186,12 @@ GoogleVertexChat.configure({ accessToken: "vertex-token", project: "project" }).
|
|||
GoogleVertexChat.configure({
|
||||
accessToken: "vertex-token",
|
||||
// @ts-expect-error Vertex Chat config accepts only one auth source.
|
||||
auth: RuntimeAuth.bearer("vertex-token"),
|
||||
auth: Auth.bearer("vertex-token"),
|
||||
project: "project",
|
||||
})
|
||||
|
||||
GoogleVertexResponses.configure({ accessToken: "vertex-token", project: "project" }).model("xai/grok-4.20-reasoning")
|
||||
GoogleVertexResponses.configure({ auth: RuntimeAuth.bearer("vertex-token"), project: "project" }).model(
|
||||
GoogleVertexResponses.configure({ auth: Auth.bearer("vertex-token"), project: "project" }).model(
|
||||
"xai/grok-4.20-reasoning",
|
||||
)
|
||||
// @ts-expect-error Vertex Responses package settings do not accept API keys.
|
||||
|
|
@ -205,16 +204,14 @@ GoogleVertexResponses.configure({ accessToken: "vertex-token", project: "project
|
|||
GoogleVertexResponses.configure({
|
||||
accessToken: "vertex-token",
|
||||
// @ts-expect-error Vertex Responses config accepts only one auth source.
|
||||
auth: RuntimeAuth.bearer("vertex-token"),
|
||||
auth: Auth.bearer("vertex-token"),
|
||||
project: "project",
|
||||
})
|
||||
|
||||
GoogleVertexMessages.configure({ accessToken: "vertex-token", project: "project" }).model("claude-sonnet-4-6")
|
||||
// @ts-expect-error Vertex Messages package settings do not accept API keys.
|
||||
GoogleVertexMessages.model("claude-sonnet-4-6", { apiKey: "vertex-key", project: "project" })
|
||||
GoogleVertexMessages.configure({ auth: RuntimeAuth.bearer("vertex-token"), project: "project" }).model(
|
||||
"claude-sonnet-4-6",
|
||||
)
|
||||
GoogleVertexMessages.configure({ auth: Auth.bearer("vertex-token"), project: "project" }).model("claude-sonnet-4-6")
|
||||
GoogleVertexMessages.configure({ accessToken: "vertex-token", project: "project" }).model(
|
||||
"claude-sonnet-4-6",
|
||||
// @ts-expect-error Vertex Messages model selectors only accept model ids.
|
||||
|
|
@ -223,7 +220,7 @@ GoogleVertexMessages.configure({ accessToken: "vertex-token", project: "project"
|
|||
GoogleVertexMessages.configure({
|
||||
accessToken: "vertex-token",
|
||||
// @ts-expect-error Vertex Messages config accepts only one auth source.
|
||||
auth: RuntimeAuth.bearer("vertex-token"),
|
||||
auth: Auth.bearer("vertex-token"),
|
||||
project: "project",
|
||||
})
|
||||
|
||||
|
|
|
|||
|
|
@ -1,5 +1,5 @@
|
|||
import { describe, expect, test } from "bun:test"
|
||||
import { LLM, LLMClient, Provider } from "@opencode-ai/ai"
|
||||
import { ImageInput, LLM, LLMClient, Provider } from "@opencode-ai/ai"
|
||||
import { Route, Protocol } from "@opencode-ai/ai/route"
|
||||
import { Provider as ProviderSubpath } from "@opencode-ai/ai/provider"
|
||||
import {
|
||||
|
|
@ -11,12 +11,7 @@ import {
|
|||
XAI,
|
||||
} from "@opencode-ai/ai/providers"
|
||||
import * as GitHubCopilot from "@opencode-ai/ai/providers/github-copilot"
|
||||
import {
|
||||
OpenAIChat,
|
||||
OpenAICompatibleChat,
|
||||
OpenAICompatibleResponses,
|
||||
OpenAIResponses,
|
||||
} from "@opencode-ai/ai/protocols"
|
||||
import { OpenAIChat, OpenAICompatibleChat, OpenAICompatibleResponses, OpenAIResponses } from "@opencode-ai/ai/protocols"
|
||||
import * as AnthropicMessages from "@opencode-ai/ai/protocols/anthropic-messages"
|
||||
|
||||
describe("public exports", () => {
|
||||
|
|
@ -24,6 +19,7 @@ describe("public exports", () => {
|
|||
expect(LLM.request).toBeFunction()
|
||||
expect(LLMClient.Service).toBeFunction()
|
||||
expect(LLMClient.layer).toBeDefined()
|
||||
expect(ImageInput.bytes).toBeFunction()
|
||||
expect(Provider.make).toBeFunction()
|
||||
expect(ProviderSubpath.make).toBe(Provider.make)
|
||||
})
|
||||
|
|
|
|||
BIN
packages/ai/test/fixtures/images/edit-source.jpg
vendored
Normal file
BIN
packages/ai/test/fixtures/images/edit-source.jpg
vendored
Normal file
Binary file not shown.
|
After Width: | Height: | Size: 896 B |
28
packages/ai/test/fixtures/recordings/google-images/edits-an-image.json
vendored
Normal file
28
packages/ai/test/fixtures/recordings/google-images/edits-an-image.json
vendored
Normal file
File diff suppressed because one or more lines are too long
32
packages/ai/test/fixtures/recordings/google-images/generates-an-image.json
vendored
Normal file
32
packages/ai/test/fixtures/recordings/google-images/generates-an-image.json
vendored
Normal file
File diff suppressed because one or more lines are too long
28
packages/ai/test/fixtures/recordings/openai-images/edits-an-image.json
vendored
Normal file
28
packages/ai/test/fixtures/recordings/openai-images/edits-an-image.json
vendored
Normal file
File diff suppressed because one or more lines are too long
55
packages/ai/test/fixtures/recordings/openrouter-reasoning-tool-loop.json
vendored
Normal file
55
packages/ai/test/fixtures/recordings/openrouter-reasoning-tool-loop.json
vendored
Normal file
File diff suppressed because one or more lines are too long
55
packages/ai/test/fixtures/recordings/vercel-ai-gateway-reasoning-tool-loop.json
vendored
Normal file
55
packages/ai/test/fixtures/recordings/vercel-ai-gateway-reasoning-tool-loop.json
vendored
Normal file
File diff suppressed because one or more lines are too long
28
packages/ai/test/fixtures/recordings/xai-images/edits-an-image.json
vendored
Normal file
28
packages/ai/test/fixtures/recordings/xai-images/edits-an-image.json
vendored
Normal file
File diff suppressed because one or more lines are too long
32
packages/ai/test/fixtures/recordings/xai-images/generates-an-image.json
vendored
Normal file
32
packages/ai/test/fixtures/recordings/xai-images/generates-an-image.json
vendored
Normal file
File diff suppressed because one or more lines are too long
28
packages/ai/test/fixtures/recordings/zai-images/generates-an-image.json
vendored
Normal file
28
packages/ai/test/fixtures/recordings/zai-images/generates-an-image.json
vendored
Normal file
|
|
@ -0,0 +1,28 @@
|
|||
{
|
||||
"version": 1,
|
||||
"metadata": {
|
||||
"tags": ["prefix:zai-images", "provider:zai", "protocol:zai-images"],
|
||||
"name": "zai-images/generates-an-image",
|
||||
"recordedAt": "2026-07-19T16:03:55.761Z"
|
||||
},
|
||||
"interactions": [
|
||||
{
|
||||
"transport": "http",
|
||||
"request": {
|
||||
"method": "POST",
|
||||
"url": "https://api.z.ai/api/paas/v4/images/generations",
|
||||
"headers": {
|
||||
"content-type": "application/json"
|
||||
},
|
||||
"body": "{\"model\":\"cogview-4-250304\",\"prompt\":\"A simple flat red circle centered on a plain white background.\",\"size\":\"1024x1024\",\"quality\":\"standard\",\"user_id\":\"opencode-image-test\"}"
|
||||
},
|
||||
"response": {
|
||||
"status": 200,
|
||||
"headers": {
|
||||
"content-type": "application/json; charset=UTF-8"
|
||||
},
|
||||
"body": "{\"created\":1784477028,\"data\":[{\"url\":\"https://mfile.z.ai/1784477035500-43574eab2b6e402da9063d6ac22dfefb.png?ufileattname=202607200003482062c3bba9b04f7d_watermark.png\"}],\"id\":\"202607200003482062c3bba9b04f7d\",\"request_id\":\"202607200003482062c3bba9b04f7d\"}"
|
||||
}
|
||||
}
|
||||
]
|
||||
}
|
||||
|
|
@ -1,8 +1,8 @@
|
|||
import { describe, expect } from "bun:test"
|
||||
import { Effect, Layer } from "effect"
|
||||
import { HttpClientRequest } from "effect/unstable/http"
|
||||
import { Image, ImageClient } from "../src"
|
||||
import { OpenAI } from "../src/providers"
|
||||
import { Image, ImageClient, ImageInput } from "../src"
|
||||
import { Google, OpenAI, XAI, ZAI } from "../src/providers"
|
||||
import { it } from "./lib/effect"
|
||||
import { dynamicResponse } from "./lib/http"
|
||||
|
||||
|
|
@ -17,13 +17,20 @@ describe("Image", () => {
|
|||
http: { body: { deployment: "test" }, headers: { "x-default": "yes" } },
|
||||
}).image("gpt-image-2"),
|
||||
prompt: "A robot tending a rooftop garden",
|
||||
count: 2,
|
||||
size: { width: 1024, height: 1024 },
|
||||
providerOptions: {
|
||||
openai: { quality: "high", outputFormat: "webp" },
|
||||
options: {
|
||||
n: 2,
|
||||
size: "2048x2048",
|
||||
quality: "future-quality",
|
||||
outputFormat: "jpeg",
|
||||
output_format: "avif",
|
||||
outputCompression: 30,
|
||||
output_compression: 40,
|
||||
background: "opaque",
|
||||
native_default: true,
|
||||
future_option: true,
|
||||
},
|
||||
http: {
|
||||
body: { request_metadata: "value" },
|
||||
body: { output_format: "webp", output_compression: 50, future_option: "http", request_metadata: "value" },
|
||||
headers: { "x-request": "yes" },
|
||||
query: { trace: "1" },
|
||||
},
|
||||
|
|
@ -49,9 +56,13 @@ describe("Image", () => {
|
|||
model: "gpt-image-2",
|
||||
prompt: "A robot tending a rooftop garden",
|
||||
n: 2,
|
||||
size: "1024x1024",
|
||||
quality: "high",
|
||||
size: "2048x2048",
|
||||
quality: "future-quality",
|
||||
background: "opaque",
|
||||
output_format: "webp",
|
||||
output_compression: 50,
|
||||
native_default: true,
|
||||
future_option: "http",
|
||||
deployment: "test",
|
||||
request_metadata: "value",
|
||||
})
|
||||
|
|
@ -71,23 +82,495 @@ describe("Image", () => {
|
|||
),
|
||||
)
|
||||
|
||||
it.effect("rejects invalid common and OpenAI image options locally", () =>
|
||||
it.effect("preserves native snake_case and unknown request options", () =>
|
||||
Image.generate({
|
||||
model: OpenAI.configure({ apiKey: "test", baseURL: "https://api.openai.test/v1" }).image("gpt-image-2"),
|
||||
prompt: "A robot tending a rooftop garden",
|
||||
count: -1,
|
||||
size: { width: -1, height: 0.5 },
|
||||
providerOptions: { openai: { outputCompression: 101 } },
|
||||
model: OpenAI.configure({
|
||||
apiKey: "test",
|
||||
baseURL: "https://api.openai.test/v1",
|
||||
}).image("future-image-model"),
|
||||
prompt: "A lighthouse in fog",
|
||||
options: {
|
||||
outputFormat: "jpeg",
|
||||
output_format: "avif",
|
||||
outputCompression: 30,
|
||||
output_compression: 40,
|
||||
provider_future_option: { enabled: true },
|
||||
},
|
||||
}).pipe(
|
||||
Effect.flip,
|
||||
Effect.tap((error) =>
|
||||
Effect.tap((response) =>
|
||||
Effect.sync(() => {
|
||||
expect(error.reason._tag).toBe("InvalidRequest")
|
||||
expect(response.image?.mediaType).toBe("image/avif")
|
||||
}),
|
||||
),
|
||||
Effect.provide(
|
||||
ImageClient.layer.pipe(
|
||||
Layer.provide(dynamicResponse(() => Effect.die("invalid request should not reach the provider"))),
|
||||
Layer.provide(
|
||||
dynamicResponse((input) => {
|
||||
expect(JSON.parse(input.text)).toEqual({
|
||||
model: "future-image-model",
|
||||
prompt: "A lighthouse in fog",
|
||||
output_format: "avif",
|
||||
output_compression: 40,
|
||||
provider_future_option: { enabled: true },
|
||||
})
|
||||
return Effect.succeed(
|
||||
input.respond(JSON.stringify({ data: [{ b64_json: "AQID" }] }), {
|
||||
headers: { "content-type": "application/json" },
|
||||
}),
|
||||
)
|
||||
}),
|
||||
),
|
||||
),
|
||||
),
|
||||
),
|
||||
)
|
||||
|
||||
it.effect("routes OpenAI byte inputs and masks through multipart edits", () =>
|
||||
Image.generate({
|
||||
model: OpenAI.configure({ apiKey: "test", baseURL: "https://api.openai.test/v1" }).image("future-model"),
|
||||
prompt: "Combine these images",
|
||||
images: [
|
||||
ImageInput.bytes(Uint8Array.from([1, 2, 3]), "image/png"),
|
||||
ImageInput.url("data:image/jpeg;base64,BAUG"),
|
||||
],
|
||||
options: {
|
||||
mask: ImageInput.bytes(Uint8Array.from([7, 8, 9]), "image/png"),
|
||||
quality: "high",
|
||||
future_option: true,
|
||||
},
|
||||
http: {
|
||||
body: { quality: "low", model: "corrupt", prompt: "corrupt", image: "corrupt", "image[]": "corrupt" },
|
||||
headers: { "content-type": "application/json" },
|
||||
},
|
||||
}).pipe(
|
||||
Effect.provide(
|
||||
ImageClient.layer.pipe(
|
||||
Layer.provide(
|
||||
dynamicResponse((input) =>
|
||||
Effect.gen(function* () {
|
||||
const request = yield* HttpClientRequest.toWeb(input.request).pipe(Effect.orDie)
|
||||
expect(request.url).toBe("https://api.openai.test/v1/images/edits")
|
||||
expect(request.headers.get("content-type")).toStartWith("multipart/form-data; boundary=")
|
||||
expect(input.text).toContain('name="model"\r\n\r\nfuture-model')
|
||||
expect(input.text).toContain('name="prompt"\r\n\r\nCombine these images')
|
||||
expect(input.text.match(/name="image\[\]"/g)).toHaveLength(2)
|
||||
expect(input.text).toContain('name="mask"')
|
||||
expect(input.text).toContain('name="quality"\r\n\r\nlow')
|
||||
expect(input.text).not.toContain("corrupt")
|
||||
return input.respond(JSON.stringify({ data: [{ b64_json: "AQID" }] }), {
|
||||
headers: { "content-type": "application/json" },
|
||||
})
|
||||
}),
|
||||
),
|
||||
),
|
||||
),
|
||||
),
|
||||
),
|
||||
)
|
||||
|
||||
it.effect("routes OpenAI URL and file inputs through JSON edits", () =>
|
||||
Image.generate({
|
||||
model: OpenAI.configure({ apiKey: "test", baseURL: "https://api.openai.test/v1" }).image("future-model"),
|
||||
prompt: "Combine these images",
|
||||
images: [ImageInput.url("https://example.test/source.png"), ImageInput.file("file_123")],
|
||||
options: { mask: ImageInput.file("file_mask") },
|
||||
http: { body: { future_option: true } },
|
||||
}).pipe(
|
||||
Effect.provide(
|
||||
ImageClient.layer.pipe(
|
||||
Layer.provide(
|
||||
dynamicResponse((input) => {
|
||||
expect(JSON.parse(input.text)).toEqual({
|
||||
model: "future-model",
|
||||
prompt: "Combine these images",
|
||||
images: [{ image_url: "https://example.test/source.png" }, { file_id: "file_123" }],
|
||||
mask: { file_id: "file_mask" },
|
||||
future_option: true,
|
||||
})
|
||||
return Effect.succeed(
|
||||
input.respond(JSON.stringify({ data: [{ b64_json: "AQID" }] }), {
|
||||
headers: { "content-type": "application/json" },
|
||||
}),
|
||||
)
|
||||
}),
|
||||
),
|
||||
),
|
||||
),
|
||||
),
|
||||
)
|
||||
|
||||
it.effect("routes ordered xAI image inputs through JSON edits", () =>
|
||||
Image.generate({
|
||||
model: XAI.configure({ apiKey: "test", baseURL: "https://api.xai.test/v1" }).image("future-model"),
|
||||
prompt: "Combine these images",
|
||||
images: [
|
||||
ImageInput.bytes(Uint8Array.from([1, 2, 3]), "image/png"),
|
||||
ImageInput.url("https://example.test/source.jpg"),
|
||||
ImageInput.file("file_123"),
|
||||
],
|
||||
}).pipe(
|
||||
Effect.provide(
|
||||
ImageClient.layer.pipe(
|
||||
Layer.provide(
|
||||
dynamicResponse((input) => {
|
||||
expect(JSON.parse(input.text)).toEqual({
|
||||
model: "future-model",
|
||||
prompt: "Combine these images",
|
||||
images: [
|
||||
{ url: "data:image/png;base64,AQID", type: "image_url" },
|
||||
{ url: "https://example.test/source.jpg", type: "image_url" },
|
||||
{ file_id: "file_123" },
|
||||
],
|
||||
})
|
||||
return Effect.succeed(
|
||||
input.respond(JSON.stringify({ data: [{ b64_json: "AQID", mime_type: "image/png" }] }), {
|
||||
headers: { "content-type": "application/json" },
|
||||
}),
|
||||
)
|
||||
}),
|
||||
),
|
||||
),
|
||||
),
|
||||
),
|
||||
)
|
||||
|
||||
it.effect("uses xAI's singular image field for one input", () =>
|
||||
Image.generate({
|
||||
model: XAI.configure({ apiKey: "test", baseURL: "https://api.xai.test/v1" }).image("future-model"),
|
||||
prompt: "Edit this image",
|
||||
images: [ImageInput.file("file_123")],
|
||||
}).pipe(
|
||||
Effect.provide(
|
||||
ImageClient.layer.pipe(
|
||||
Layer.provide(
|
||||
dynamicResponse((input) => {
|
||||
expect(JSON.parse(input.text)).toEqual({
|
||||
model: "future-model",
|
||||
prompt: "Edit this image",
|
||||
image: { file_id: "file_123" },
|
||||
})
|
||||
return Effect.succeed(
|
||||
input.respond(JSON.stringify({ data: [{ b64_json: "AQID", mime_type: "image/png" }] }), {
|
||||
headers: { "content-type": "application/json" },
|
||||
}),
|
||||
)
|
||||
}),
|
||||
),
|
||||
),
|
||||
),
|
||||
),
|
||||
)
|
||||
|
||||
it.effect("lowers ordered Google image inputs into generateContent parts", () =>
|
||||
Image.generate({
|
||||
model: Google.configure({ apiKey: "test", baseURL: "https://google.test/v1beta" }).image("future-model"),
|
||||
prompt: "Combine these images",
|
||||
images: [
|
||||
ImageInput.bytes(Uint8Array.from([1, 2, 3]), "image/png"),
|
||||
ImageInput.url("data:image/jpeg;base64,BAUG"),
|
||||
ImageInput.fileUri("https://generativelanguage.googleapis.com/v1beta/files/123", "image/webp"),
|
||||
],
|
||||
}).pipe(
|
||||
Effect.provide(
|
||||
ImageClient.layer.pipe(
|
||||
Layer.provide(
|
||||
dynamicResponse((input) => {
|
||||
expect(JSON.parse(input.text).contents[0].parts).toEqual([
|
||||
{ text: "Combine these images" },
|
||||
{ inlineData: { mimeType: "image/png", data: "AQID" } },
|
||||
{ inlineData: { mimeType: "image/jpeg", data: "BAUG" } },
|
||||
{
|
||||
fileData: {
|
||||
mimeType: "image/webp",
|
||||
fileUri: "https://generativelanguage.googleapis.com/v1beta/files/123",
|
||||
},
|
||||
},
|
||||
])
|
||||
return Effect.succeed(
|
||||
input.respond(
|
||||
JSON.stringify({
|
||||
candidates: [{ content: { parts: [{ inlineData: { mimeType: "image/png", data: "AQID" } }] } }],
|
||||
}),
|
||||
{ headers: { "content-type": "application/json" } },
|
||||
),
|
||||
)
|
||||
}),
|
||||
),
|
||||
),
|
||||
),
|
||||
),
|
||||
)
|
||||
|
||||
it.effect("rejects unsupported provider inputs before sending", () =>
|
||||
Effect.gen(function* () {
|
||||
const cases = [
|
||||
Image.generate({
|
||||
model: Google.configure({ apiKey: "test" }).image("model"),
|
||||
prompt: "edit",
|
||||
images: [ImageInput.url("https://example.test/image.png")],
|
||||
}),
|
||||
Image.generate({
|
||||
model: ZAI.configure({ apiKey: "test" }).image("model"),
|
||||
prompt: "edit",
|
||||
images: [ImageInput.bytes(Uint8Array.from([1]), "image/png")],
|
||||
}),
|
||||
]
|
||||
yield* Effect.forEach(cases, (program) =>
|
||||
program.pipe(
|
||||
Effect.flip,
|
||||
Effect.tap((error) => Effect.sync(() => expect(error.reason._tag).toBe("InvalidRequest"))),
|
||||
),
|
||||
)
|
||||
}).pipe(
|
||||
Effect.provide(
|
||||
ImageClient.layer.pipe(
|
||||
Layer.provide(dynamicResponse(() => Effect.die("unsupported input reached the network"))),
|
||||
),
|
||||
),
|
||||
),
|
||||
)
|
||||
|
||||
it.effect("generates images through the Google generateContent API", () =>
|
||||
Effect.gen(function* () {
|
||||
const response = yield* Image.generate({
|
||||
model: Google.configure({
|
||||
apiKey: "test",
|
||||
baseURL: "https://generativelanguage.test/v1beta/",
|
||||
headers: { "x-default": "yes" },
|
||||
http: { body: { labels: { deployment: "test" } }, query: { api: "v1" } },
|
||||
}).image("any-model-id"),
|
||||
prompt: "A robot tending a rooftop garden",
|
||||
options: {
|
||||
aspectRatio: "16:9",
|
||||
imageSize: "2K",
|
||||
seed: 42,
|
||||
thinkingLevel: "HIGH",
|
||||
includeThoughts: true,
|
||||
futureOption: true,
|
||||
imageConfig: { aspectRatio: "4:3", nativeImageOption: true },
|
||||
thinkingConfig: { thinkingLevel: "LOW", nativeThinkingOption: true },
|
||||
},
|
||||
http: {
|
||||
body: {
|
||||
safetySettings: [],
|
||||
generationConfig: {
|
||||
imageConfig: { aspectRatio: "3:2", httpImageOption: true },
|
||||
thinkingConfig: { includeThoughts: false, httpThinkingOption: true },
|
||||
futureOption: "http",
|
||||
httpOption: true,
|
||||
},
|
||||
},
|
||||
headers: { "x-request": "yes" },
|
||||
query: { trace: "1" },
|
||||
},
|
||||
})
|
||||
|
||||
expect(response.images).toHaveLength(3)
|
||||
expect(response.images.map((image) => image.data)).toEqual([
|
||||
Uint8Array.from([1, 2, 3]),
|
||||
Uint8Array.from([4, 5, 6]),
|
||||
Uint8Array.from([7, 8, 9]),
|
||||
])
|
||||
expect(response.images.map((image) => image.mediaType)).toEqual(["image/png", "image/jpeg", "image/webp"])
|
||||
expect(response.images[0].providerMetadata).toMatchObject({ google: { thoughtSignature: "signature-1" } })
|
||||
expect(response.images[1].providerMetadata).toMatchObject({
|
||||
google: { candidateIndex: 0, partIndex: 3, finishReason: "STOP" },
|
||||
})
|
||||
expect(response.images[2].providerMetadata).toMatchObject({ google: { candidateIndex: 7, partIndex: 0 } })
|
||||
expect(response.usage?.inputTokens).toBe(5)
|
||||
expect(response.usage?.outputTokens).toBe(10)
|
||||
expect(response.usage?.reasoningTokens).toBe(3)
|
||||
expect(response.usage?.providerMetadata).toMatchObject({ google: { serviceTier: "STANDARD" } })
|
||||
expect(response.providerMetadata).toEqual({
|
||||
google: {
|
||||
modelVersion: "gemini-3.1-flash-image",
|
||||
responseId: "response-1",
|
||||
promptFeedback: undefined,
|
||||
candidates: [
|
||||
{
|
||||
index: 0,
|
||||
finishReason: "STOP",
|
||||
finishMessage: undefined,
|
||||
safetyRatings: [{ category: "safe" }],
|
||||
citationMetadata: undefined,
|
||||
groundingMetadata: undefined,
|
||||
parts: [
|
||||
{
|
||||
type: "inlineData",
|
||||
mediaType: "image/png",
|
||||
thought: undefined,
|
||||
thoughtSignature: "signature-1",
|
||||
},
|
||||
{ type: "text", text: "planning", thought: true, thoughtSignature: "text-signature" },
|
||||
{
|
||||
type: "inlineData",
|
||||
mediaType: "image/png",
|
||||
thought: true,
|
||||
thoughtSignature: "draft-signature",
|
||||
},
|
||||
{
|
||||
type: "inlineData",
|
||||
mediaType: "image/jpeg",
|
||||
thought: undefined,
|
||||
thoughtSignature: undefined,
|
||||
},
|
||||
],
|
||||
},
|
||||
{
|
||||
index: 7,
|
||||
finishReason: undefined,
|
||||
finishMessage: undefined,
|
||||
safetyRatings: undefined,
|
||||
citationMetadata: undefined,
|
||||
groundingMetadata: undefined,
|
||||
parts: [
|
||||
{
|
||||
type: "inlineData",
|
||||
mediaType: "image/webp",
|
||||
thought: undefined,
|
||||
thoughtSignature: undefined,
|
||||
},
|
||||
],
|
||||
},
|
||||
],
|
||||
},
|
||||
})
|
||||
}).pipe(
|
||||
Effect.provide(
|
||||
ImageClient.layer.pipe(
|
||||
Layer.provide(
|
||||
dynamicResponse((input) =>
|
||||
Effect.gen(function* () {
|
||||
const request = yield* HttpClientRequest.toWeb(input.request).pipe(Effect.orDie)
|
||||
expect(request.url).toBe(
|
||||
"https://generativelanguage.test/v1beta/models/any-model-id:generateContent?api=v1&trace=1",
|
||||
)
|
||||
expect(request.headers.get("x-goog-api-key")).toBe("test")
|
||||
expect(request.headers.get("x-default")).toBe("yes")
|
||||
expect(request.headers.get("x-request")).toBe("yes")
|
||||
expect(JSON.parse(input.text)).toEqual({
|
||||
contents: [{ role: "user", parts: [{ text: "A robot tending a rooftop garden" }] }],
|
||||
generationConfig: {
|
||||
responseModalities: ["IMAGE"],
|
||||
imageConfig: {
|
||||
aspectRatio: "3:2",
|
||||
imageSize: "2K",
|
||||
nativeImageOption: true,
|
||||
httpImageOption: true,
|
||||
},
|
||||
seed: 42,
|
||||
thinkingConfig: {
|
||||
thinkingLevel: "LOW",
|
||||
includeThoughts: false,
|
||||
nativeThinkingOption: true,
|
||||
httpThinkingOption: true,
|
||||
},
|
||||
futureOption: "http",
|
||||
httpOption: true,
|
||||
},
|
||||
labels: { deployment: "test" },
|
||||
safetySettings: [],
|
||||
})
|
||||
return input.respond(
|
||||
JSON.stringify({
|
||||
candidates: [
|
||||
{
|
||||
content: {
|
||||
parts: [
|
||||
{
|
||||
inlineData: { mimeType: "image/png", data: "AQID" },
|
||||
thoughtSignature: "signature-1",
|
||||
},
|
||||
{ text: "planning", thought: true, thoughtSignature: "text-signature" },
|
||||
{
|
||||
inlineData: { mimeType: "image/png", data: "CgsM" },
|
||||
thought: true,
|
||||
thoughtSignature: "draft-signature",
|
||||
},
|
||||
{ inlineData: { mimeType: "image/jpeg", data: "BAUG" } },
|
||||
],
|
||||
},
|
||||
finishReason: "STOP",
|
||||
safetyRatings: [{ category: "safe" }],
|
||||
},
|
||||
{
|
||||
index: 7,
|
||||
content: { parts: [{ inlineData: { mimeType: "image/webp", data: "BwgJ" } }] },
|
||||
},
|
||||
],
|
||||
usageMetadata: {
|
||||
promptTokenCount: 5,
|
||||
candidatesTokenCount: 7,
|
||||
thoughtsTokenCount: 3,
|
||||
totalTokenCount: 15,
|
||||
serviceTier: "STANDARD",
|
||||
},
|
||||
modelVersion: "gemini-3.1-flash-image",
|
||||
responseId: "response-1",
|
||||
}),
|
||||
{ headers: { "content-type": "application/json" } },
|
||||
)
|
||||
}),
|
||||
),
|
||||
),
|
||||
),
|
||||
),
|
||||
),
|
||||
)
|
||||
|
||||
it.effect("includes Google diagnostics when no final image is returned", () =>
|
||||
Image.generate({
|
||||
model: Google.configure({ apiKey: "test", baseURL: "https://generativelanguage.test/v1beta" }).image(
|
||||
"gemini-3.1-flash-image",
|
||||
),
|
||||
prompt: "A robot tending a rooftop garden",
|
||||
}).pipe(
|
||||
Effect.flip,
|
||||
Effect.tap((error) =>
|
||||
Effect.sync(() => {
|
||||
expect(error.reason._tag).toBe("InvalidProviderOutput")
|
||||
if (error.reason._tag !== "InvalidProviderOutput") return
|
||||
expect(error.reason.message).toContain("finish reasons: IMAGE_SAFETY")
|
||||
expect(error.reason.providerMetadata).toEqual({
|
||||
google: {
|
||||
promptFeedback: { blockReason: "SAFETY" },
|
||||
candidates: [
|
||||
{
|
||||
index: 0,
|
||||
finishReason: "IMAGE_SAFETY",
|
||||
finishMessage: "The generated image was blocked by safety filters.",
|
||||
safetyRatings: [{ category: "HARM_CATEGORY_DANGEROUS_CONTENT", blocked: true }],
|
||||
citationMetadata: undefined,
|
||||
groundingMetadata: undefined,
|
||||
parts: [{ type: "text", text: "blocked", thought: false, thoughtSignature: undefined }],
|
||||
},
|
||||
],
|
||||
},
|
||||
})
|
||||
}),
|
||||
),
|
||||
Effect.provide(
|
||||
ImageClient.layer.pipe(
|
||||
Layer.provide(
|
||||
dynamicResponse((input) =>
|
||||
Effect.succeed(
|
||||
input.respond(
|
||||
JSON.stringify({
|
||||
candidates: [
|
||||
{
|
||||
content: { parts: [{ text: "blocked", thought: false }] },
|
||||
finishReason: "IMAGE_SAFETY",
|
||||
finishMessage: "The generated image was blocked by safety filters.",
|
||||
safetyRatings: [{ category: "HARM_CATEGORY_DANGEROUS_CONTENT", blocked: true }],
|
||||
},
|
||||
],
|
||||
promptFeedback: { blockReason: "SAFETY" },
|
||||
}),
|
||||
{ headers: { "content-type": "application/json" } },
|
||||
),
|
||||
),
|
||||
),
|
||||
),
|
||||
),
|
||||
),
|
||||
),
|
||||
|
|
|
|||
161
packages/ai/test/image.types.ts
Normal file
161
packages/ai/test/image.types.ts
Normal file
|
|
@ -0,0 +1,161 @@
|
|||
import {
|
||||
Image,
|
||||
ImageInput,
|
||||
ImageModel,
|
||||
type ImageModelOptions,
|
||||
type ImageOptions,
|
||||
type ImageRequestFor,
|
||||
type ImageRoute,
|
||||
} from "../src"
|
||||
import { Google, OpenAI, XAI, ZAI } from "../src/providers"
|
||||
|
||||
type GoogleLikeOptions = {
|
||||
readonly aspectRatio?: "1:1" | "16:9"
|
||||
readonly imageSize?: "1K" | "2K"
|
||||
} & Record<string, unknown>
|
||||
|
||||
declare const route: ImageRoute<GoogleLikeOptions>
|
||||
const google = ImageModel.make<GoogleLikeOptions>({ id: "gemini-image", provider: "google", route })
|
||||
// @ts-expect-error Extracted model options retain known provider fields.
|
||||
const invalidGoogleOptions: ImageModelOptions<typeof google> = { aspectRatio: "wide" }
|
||||
void invalidGoogleOptions
|
||||
|
||||
Image.generate({
|
||||
model: google,
|
||||
prompt: "A lighthouse",
|
||||
images: [
|
||||
ImageInput.bytes(Uint8Array.from([1, 2, 3]), "image/png"),
|
||||
ImageInput.url("data:image/jpeg;base64,AQID"),
|
||||
ImageInput.fileUri("https://generativelanguage.googleapis.com/v1beta/files/example", "image/webp"),
|
||||
],
|
||||
options: { aspectRatio: "16:9", imageSize: "2K", futureOption: true },
|
||||
})
|
||||
|
||||
const googleProvider = Google.configure({ apiKey: "test" }).image("any-model-id")
|
||||
Image.generate({
|
||||
model: googleProvider,
|
||||
prompt: "A lighthouse",
|
||||
options: {
|
||||
aspectRatio: "16:9",
|
||||
imageSize: "2K",
|
||||
seed: 42,
|
||||
thinkingLevel: "HIGH",
|
||||
includeThoughts: true,
|
||||
futureOption: true,
|
||||
},
|
||||
})
|
||||
Image.generate({
|
||||
model: googleProvider,
|
||||
prompt: "A lighthouse",
|
||||
options: { aspectRatio: "future-ratio", imageSize: "8K", thinkingLevel: "FUTURE" },
|
||||
})
|
||||
// @ts-expect-error Image generation options are request-scoped, not provider configuration.
|
||||
Google.configure({ image: { providerOptions: { imageSize: "2K" } } })
|
||||
// @ts-expect-error Known Google string options retain their value kind.
|
||||
Image.generate({ model: googleProvider, prompt: "A lighthouse", options: { imageSize: 2 } })
|
||||
// @ts-expect-error Known Google numeric options retain their value kind.
|
||||
Image.generate({ model: googleProvider, prompt: "A lighthouse", options: { seed: "42" } })
|
||||
// @ts-expect-error Known Google boolean options retain their value kind.
|
||||
Image.generate({ model: googleProvider, prompt: "A lighthouse", options: { includeThoughts: "yes" } })
|
||||
|
||||
const openai = OpenAI.image("gpt-image-2")
|
||||
// @ts-expect-error Image generation options are request-scoped, not provider configuration.
|
||||
OpenAI.configure({ image: { options: { quality: "medium" } } })
|
||||
const futureOpenAIOptions: ImageModelOptions<typeof openai> = { quality: "future-quality" }
|
||||
void futureOpenAIOptions
|
||||
Image.generate({
|
||||
model: openai,
|
||||
prompt: "A lighthouse",
|
||||
images: [ImageInput.url("https://example.com/source.png"), ImageInput.file("file_123")],
|
||||
options: {
|
||||
mask: ImageInput.bytes(Uint8Array.from([1]), "image/png"),
|
||||
quality: "hd",
|
||||
outputFormat: "webp",
|
||||
size: "2048x2048",
|
||||
future_option: true,
|
||||
},
|
||||
})
|
||||
Image.generate({ model: openai, prompt: "A lighthouse", options: { quality: "future-quality", size: "256x256" } })
|
||||
Image.generate({ model: openai, prompt: "A lighthouse", options: { size: "1792x1024" } })
|
||||
Image.generate({ model: openai, prompt: "A lighthouse", options: { native_future_option: true } })
|
||||
// @ts-expect-error Known OpenAI string options retain their value kind.
|
||||
Image.generate({ model: openai, prompt: "A lighthouse", options: { quality: 1 } })
|
||||
// @ts-expect-error Known OpenAI numeric options retain their value kind.
|
||||
Image.generate({ model: openai, prompt: "A lighthouse", options: { outputCompression: "80" } })
|
||||
OpenAI.imageGeneration({ action: "future-action", quality: "future-quality", size: "2048x2048" })
|
||||
// @ts-expect-error Hosted image generation numeric options retain their value kind.
|
||||
OpenAI.imageGeneration({ partialImages: "2" })
|
||||
// @ts-expect-error Known Google-like options are inferred from the selected model.
|
||||
Image.generate({ model: google, prompt: "A lighthouse", options: { aspectRatio: "wide" } })
|
||||
|
||||
const xai = XAI.configure({ apiKey: "test" }).image("any-model-id")
|
||||
// @ts-expect-error Image generation options are request-scoped, not provider configuration.
|
||||
XAI.configure({ image: { options: { resolution: "1k" } } })
|
||||
Image.generate({
|
||||
model: xai,
|
||||
prompt: "A lighthouse",
|
||||
images: [ImageInput.url("data:image/png;base64,AQID"), ImageInput.file("file_123")],
|
||||
options: {
|
||||
n: 2,
|
||||
aspectRatio: "future-ratio",
|
||||
resolution: "future-resolution",
|
||||
responseFormat: "future-format",
|
||||
future_option: true,
|
||||
},
|
||||
})
|
||||
Image.generate({
|
||||
model: xai,
|
||||
prompt: "A lighthouse",
|
||||
options: { aspect_ratio: "16:9", response_format: "b64_json", native_future_option: true },
|
||||
})
|
||||
// @ts-expect-error Known xAI numeric options retain their value kind.
|
||||
Image.generate({ model: xai, prompt: "A lighthouse", options: { n: "2" } })
|
||||
// @ts-expect-error Known xAI string options retain their value kind.
|
||||
Image.generate({ model: xai, prompt: "A lighthouse", options: { resolution: 2 } })
|
||||
|
||||
const zai = ZAI.configure({ apiKey: "test" }).image("any-model-id")
|
||||
// @ts-expect-error Image generation options are request-scoped, not provider configuration.
|
||||
ZAI.configure({ image: { options: { quality: "hd" } } })
|
||||
Image.generate({
|
||||
model: zai,
|
||||
prompt: "A lighthouse",
|
||||
options: { quality: "future-quality", userID: "user-123", future_option: true },
|
||||
})
|
||||
Image.generate({ model: zai, prompt: "A lighthouse", options: { user_id: "raw-user" } })
|
||||
// @ts-expect-error Known Z.ai string options retain their value kind.
|
||||
Image.generate({ model: zai, prompt: "A lighthouse", options: { quality: 1 } })
|
||||
// @ts-expect-error Known Z.ai user IDs retain their value kind.
|
||||
Image.generate({ model: zai, prompt: "A lighthouse", options: { userID: 1 } })
|
||||
|
||||
declare const generic: ImageModel<ImageOptions>
|
||||
Image.generate({ model: generic, prompt: "A lighthouse", options: { arbitrary: true } })
|
||||
const explicitImageInput: ImageInput = ImageInput.url("https://example.com/image.png")
|
||||
void explicitImageInput
|
||||
|
||||
// @ts-expect-error Raw strings are ambiguous and are not image inputs.
|
||||
Image.generate({ model: openai, prompt: "A lighthouse", images: ["AQID"] })
|
||||
// @ts-expect-error Byte image inputs require an explicit MIME type.
|
||||
Image.generate({ model: openai, prompt: "A lighthouse", images: [{ type: "bytes", data: new Uint8Array() }] })
|
||||
// @ts-expect-error File URIs require an explicit MIME type for Gemini fileData.
|
||||
Image.generate({ model: google, prompt: "A lighthouse", images: [{ type: "file-uri", uri: "files/123" }] })
|
||||
|
||||
const request = Image.request({
|
||||
model: google,
|
||||
prompt: "A lighthouse",
|
||||
options: { aspectRatio: "1:1", futureOption: true },
|
||||
})
|
||||
const typedRequest: ImageRequestFor<GoogleLikeOptions> = request
|
||||
void typedRequest
|
||||
|
||||
// @ts-expect-error Image requests no longer expose a common count option.
|
||||
Image.generate({ model: openai, prompt: "A lighthouse", count: 2 })
|
||||
// @ts-expect-error Image requests no longer expose a common size option.
|
||||
Image.generate({ model: openai, prompt: "A lighthouse", size: { width: 1024, height: 1024 } })
|
||||
// @ts-expect-error Image requests no longer expose a common aspectRatio option.
|
||||
Image.generate({ model: openai, prompt: "A lighthouse", aspectRatio: "16:9" })
|
||||
// @ts-expect-error Image requests no longer expose a common seed option.
|
||||
Image.generate({ model: openai, prompt: "A lighthouse", seed: 1 })
|
||||
// @ts-expect-error Image requests do not expose metadata.
|
||||
Image.generate({ model: openai, prompt: "A lighthouse", metadata: { trace: true } })
|
||||
// @ts-expect-error Masks are provider options, not a common image request field.
|
||||
Image.generate({ model: openai, prompt: "A lighthouse", mask: ImageInput.url("https://example.com/mask.png") })
|
||||
29
packages/ai/test/lib/image.ts
Normal file
29
packages/ai/test/lib/image.ts
Normal file
|
|
@ -0,0 +1,29 @@
|
|||
export const dimensions = (data: Uint8Array) => {
|
||||
if (data[0] === 0x89 && data[1] === 0x50 && data[2] === 0x4e && data[3] === 0x47)
|
||||
return {
|
||||
width: readUint32(data, 16),
|
||||
height: readUint32(data, 20),
|
||||
}
|
||||
if (data[0] === 0xff && data[1] === 0xd8) {
|
||||
for (let offset = 2; offset + 8 < data.length; ) {
|
||||
if (data[offset] !== 0xff) {
|
||||
offset++
|
||||
continue
|
||||
}
|
||||
const marker = data[offset + 1]
|
||||
if (
|
||||
marker !== undefined &&
|
||||
[0xc0, 0xc1, 0xc2, 0xc3, 0xc5, 0xc6, 0xc7, 0xc9, 0xca, 0xcb, 0xcd, 0xce, 0xcf].includes(marker)
|
||||
)
|
||||
return {
|
||||
width: (data[offset + 7] << 8) | data[offset + 8],
|
||||
height: (data[offset + 5] << 8) | data[offset + 6],
|
||||
}
|
||||
offset += 2 + ((data[offset + 2] << 8) | data[offset + 3])
|
||||
}
|
||||
}
|
||||
throw new Error("Unsupported image fixture format")
|
||||
}
|
||||
|
||||
const readUint32 = (data: Uint8Array, offset: number) =>
|
||||
((data[offset] << 24) | (data[offset + 1] << 16) | (data[offset + 2] << 8) | data[offset + 3]) >>> 0
|
||||
|
|
@ -3,8 +3,30 @@ import { isContextOverflow } from "../src"
|
|||
import { classifyProviderFailure } from "../src/provider-error"
|
||||
|
||||
describe("provider error classification", () => {
|
||||
test("classifies Z.AI GLM token limit messages as context overflow", () => {
|
||||
expect(isContextOverflow("tokens in request more than max tokens allowed")).toBe(true)
|
||||
test("classifies provider token limit messages as context overflow", () => {
|
||||
const messages = [
|
||||
"tokens in request more than max tokens allowed",
|
||||
'{"error":{"type":"request_too_large","message":"Request exceeds the maximum size"}}',
|
||||
"Requested token count exceeds the model's maximum context length of 131072 tokens.",
|
||||
"Input length (265330) exceeds model's maximum context length (262144).",
|
||||
"Input length 131393 exceeds the maximum allowed input length of 131040 tokens.",
|
||||
"The input (516368 tokens) is longer than the model's context length (262144 tokens).",
|
||||
"Prompt has 5,958,968 tokens, but the configured context size is 256,000 tokens",
|
||||
"Too many tokens",
|
||||
"Token limit exceeded",
|
||||
]
|
||||
|
||||
expect(messages.every(isContextOverflow)).toBe(true)
|
||||
})
|
||||
|
||||
test("does not classify rate limits as context overflow", () => {
|
||||
const messages = [
|
||||
"Throttling error: Too many tokens, please wait before trying again.",
|
||||
"Rate limit exceeded, please retry after 30 seconds.",
|
||||
"Too many requests. Please slow down.",
|
||||
]
|
||||
|
||||
expect(messages.some(isContextOverflow)).toBe(false)
|
||||
})
|
||||
|
||||
test("classifies V1 plain-text rate limit fallbacks", () => {
|
||||
|
|
|
|||
|
|
@ -1,7 +1,7 @@
|
|||
import { describe, expect } from "bun:test"
|
||||
import { ConfigProvider, Effect, Schema } from "effect"
|
||||
import { HttpClientRequest } from "effect/unstable/http"
|
||||
import { LLM } from "../../src"
|
||||
import { LLM, LLMEvent } from "../../src"
|
||||
import { CloudflareAIGateway, CloudflareWorkersAI } from "../../src/providers/cloudflare"
|
||||
import { LLMClient } from "../../src/route"
|
||||
import { it } from "../lib/effect"
|
||||
|
|
@ -83,6 +83,59 @@ describe("Cloudflare", () => {
|
|||
}),
|
||||
)
|
||||
|
||||
it.effect("preserves reasoning details for AI Gateway continuation", () =>
|
||||
Effect.gen(function* () {
|
||||
const model = CloudflareAIGateway.configure({
|
||||
accountId: "test-account",
|
||||
gatewayId: "test-gateway",
|
||||
apiKey: "test-token",
|
||||
}).model("anthropic/claude-sonnet-4.6")
|
||||
const details = [
|
||||
{ type: "reasoning.text", text: "Think", format: "anthropic-claude-v1", index: 0 },
|
||||
{ type: "reasoning.text", text: "ing", format: "anthropic-claude-v1", index: 0 },
|
||||
{ type: "reasoning.text", signature: "signed", format: "anthropic-claude-v1", index: 0 },
|
||||
]
|
||||
const merged = [
|
||||
{
|
||||
type: "reasoning.text",
|
||||
text: "Thinking",
|
||||
signature: "signed",
|
||||
format: "anthropic-claude-v1",
|
||||
index: 0,
|
||||
},
|
||||
]
|
||||
const response = yield* LLM.generate(LLM.request({ model, prompt: "Say hello." })).pipe(
|
||||
Effect.provide(
|
||||
dynamicResponse((input) =>
|
||||
Effect.succeed(
|
||||
input.respond(
|
||||
sseEvents(
|
||||
deltaChunk({ reasoning: "Think", reasoning_details: [details[0]] }),
|
||||
deltaChunk({ reasoning: "ing", reasoning_details: [details[1]] }),
|
||||
deltaChunk({ reasoning_details: [details[2]] }),
|
||||
deltaChunk({ content: "Hello" }),
|
||||
deltaChunk({}, "stop"),
|
||||
),
|
||||
{ headers: { "content-type": "text/event-stream" } },
|
||||
),
|
||||
),
|
||||
),
|
||||
),
|
||||
)
|
||||
|
||||
expect(response.reasoning).toBe("Thinking")
|
||||
expect(response.events.filter(LLMEvent.is.reasoningDelta)).toHaveLength(2)
|
||||
expect(response.message.content.find((part) => part.type === "reasoning")?.providerMetadata).toEqual({
|
||||
openai: { reasoningField: "reasoning", reasoningDetails: merged },
|
||||
})
|
||||
|
||||
const replay = yield* LLMClient.prepare(LLM.request({ model, messages: [response.message] }))
|
||||
expect(replay.body.messages).toEqual([
|
||||
{ role: "assistant", content: "Hello", reasoning: "Thinking", reasoning_details: merged },
|
||||
])
|
||||
}),
|
||||
)
|
||||
|
||||
it.effect("defaults AI Gateway id to default when omitted or blank", () =>
|
||||
Effect.gen(function* () {
|
||||
expect(
|
||||
|
|
|
|||
56
packages/ai/test/provider/google-images.recorded.test.ts
Normal file
56
packages/ai/test/provider/google-images.recorded.test.ts
Normal file
|
|
@ -0,0 +1,56 @@
|
|||
import { describe, expect } from "bun:test"
|
||||
import { Effect } from "effect"
|
||||
import { Image, ImageInput } from "../../src"
|
||||
import { Google } from "../../src/providers"
|
||||
import { dimensions } from "../lib/image"
|
||||
import { recordedTests } from "../recorded-test"
|
||||
|
||||
const model = Google.configure({
|
||||
apiKey: process.env.GOOGLE_GENERATIVE_AI_API_KEY ?? "fixture",
|
||||
}).image("gemini-3.1-flash-image")
|
||||
|
||||
const recorded = recordedTests({
|
||||
prefix: "google-images",
|
||||
provider: "google",
|
||||
protocol: "google-images",
|
||||
requires: ["GOOGLE_GENERATIVE_AI_API_KEY"],
|
||||
})
|
||||
|
||||
describe("Google Images recorded", () => {
|
||||
recorded.effect("generates an image", () =>
|
||||
Effect.gen(function* () {
|
||||
const response = yield* Image.generate({
|
||||
model,
|
||||
prompt: "A simple flat blue circle centered on a plain white background.",
|
||||
options: { aspectRatio: "1:1" },
|
||||
})
|
||||
|
||||
expect(response.images).toHaveLength(1)
|
||||
expect(response.image?.mediaType).toMatch(/^image\//)
|
||||
expect(response.image?.data).toBeInstanceOf(Uint8Array)
|
||||
expect(response.image?.data.length).toBeGreaterThan(0)
|
||||
}),
|
||||
)
|
||||
|
||||
recorded.effect("edits an image", () =>
|
||||
Effect.gen(function* () {
|
||||
const response = yield* Image.generate({
|
||||
model,
|
||||
prompt:
|
||||
"Transform this minimal source into a bright orange sun icon with eight rounded rays on a pale blue background.",
|
||||
images: [
|
||||
ImageInput.bytes(
|
||||
yield* Effect.promise(() => Bun.file("test/fixtures/images/edit-source.jpg").bytes()),
|
||||
"image/jpeg",
|
||||
),
|
||||
],
|
||||
options: { aspectRatio: "1:1" },
|
||||
})
|
||||
|
||||
expect(response.image?.mediaType).toBe("image/jpeg")
|
||||
expect(response.image?.data).toBeInstanceOf(Uint8Array)
|
||||
if (!(response.image?.data instanceof Uint8Array)) throw new Error("Expected owned Google image bytes")
|
||||
expect(dimensions(response.image.data)).toEqual({ width: 1024, height: 1024 })
|
||||
}),
|
||||
)
|
||||
})
|
||||
|
|
@ -1,10 +1,12 @@
|
|||
import { describe, expect } from "bun:test"
|
||||
import { Effect } from "effect"
|
||||
import { LLM, LLMEvent } from "../../src"
|
||||
import { LLM, LLMEvent, LLMResponse } from "../../src"
|
||||
import { OpenAIChat } from "../../src/protocols/openai-chat"
|
||||
import * as OpenAICompatible from "../../src/providers/openai-compatible"
|
||||
import * as OpenRouter from "../../src/providers/openrouter"
|
||||
import { LLMClient } from "../../src/route"
|
||||
import { recordedTests } from "../recorded-test"
|
||||
import { expectWeatherToolLoop, goldenWeatherToolLoopRequest, runWeatherToolLoop } from "../recorded-scenarios"
|
||||
|
||||
const cases = [
|
||||
{
|
||||
|
|
@ -15,6 +17,7 @@ const cases = [
|
|||
}).model("anthropic/claude-sonnet-4.6"),
|
||||
requires: ["OPENROUTER_API_KEY"],
|
||||
cassette: "openrouter-reasoning",
|
||||
structured: true,
|
||||
},
|
||||
{
|
||||
name: "Vercel AI Gateway",
|
||||
|
|
@ -26,6 +29,7 @@ const cases = [
|
|||
}).model("anthropic/claude-sonnet-4.6"),
|
||||
requires: ["AI_GATEWAY_API_KEY"],
|
||||
cassette: "vercel-ai-gateway-reasoning",
|
||||
structured: true,
|
||||
},
|
||||
] as const
|
||||
|
||||
|
|
@ -57,11 +61,82 @@ for (const item of cases) {
|
|||
expect(response.text.replaceAll(",", "").trim()).toBe("37887")
|
||||
expect(response.reasoning.length).toBeGreaterThan(0)
|
||||
expect(response.events.some(LLMEvent.is.reasoningDelta)).toBe(true)
|
||||
expect(response.message.content.find((part) => part.type === "reasoning")?.providerMetadata).toEqual({
|
||||
openai: { reasoningField: "reasoning" },
|
||||
const metadata = response.message.content.find((part) => part.type === "reasoning")?.providerMetadata
|
||||
expect(metadata?.openai?.reasoningField).toBe(item.structured ? "reasoning" : "reasoning_content")
|
||||
expect(Array.isArray(metadata?.openai?.reasoningDetails)).toBe(item.structured)
|
||||
if (!item.structured) return
|
||||
const details = metadata?.openai?.reasoningDetails
|
||||
if (!Array.isArray(details)) return
|
||||
expect(
|
||||
details.some(
|
||||
(detail) =>
|
||||
typeof detail === "object" &&
|
||||
detail !== null &&
|
||||
"signature" in detail &&
|
||||
typeof detail.signature === "string" &&
|
||||
detail.signature.length > 0,
|
||||
),
|
||||
).toBe(true)
|
||||
|
||||
const replay = yield* LLMClient.prepare<OpenAIChat.OpenAIChatBody>(
|
||||
LLM.request({ model: item.model, messages: [response.message] }),
|
||||
)
|
||||
expect(replay.body.messages).toMatchObject([
|
||||
{ role: "assistant", content: response.text, reasoning: response.reasoning },
|
||||
])
|
||||
const replayDetails =
|
||||
replay.body.messages[0]?.role === "assistant" ? replay.body.messages[0].reasoning_details : undefined
|
||||
expect(Array.isArray(replayDetails)).toBe(true)
|
||||
if (!Array.isArray(replayDetails)) return
|
||||
expect(replayDetails).toEqual(details)
|
||||
expect(replayDetails).toHaveLength(1)
|
||||
expect(replayDetails[0]).toMatchObject({
|
||||
type: "reasoning.text",
|
||||
text: response.reasoning,
|
||||
signature: expect.any(String),
|
||||
})
|
||||
}),
|
||||
30_000,
|
||||
)
|
||||
|
||||
recorded.effect.with(
|
||||
"continues signed reasoning through a tool loop",
|
||||
{ cassette: `${item.cassette}-tool-loop`, tags: ["continuation", "tool", "tool-loop"] },
|
||||
() =>
|
||||
Effect.gen(function* () {
|
||||
const events = yield* runWeatherToolLoop(
|
||||
goldenWeatherToolLoopRequest({
|
||||
id: `${item.cassette}-tool-loop`,
|
||||
model: item.model,
|
||||
maxTokens: 1536,
|
||||
temperature: false,
|
||||
}),
|
||||
)
|
||||
|
||||
expectWeatherToolLoop(events)
|
||||
expect(
|
||||
LLMResponse.text({
|
||||
events: events.slice(events.findIndex(LLMEvent.is.stepFinish) + 1),
|
||||
}).trim(),
|
||||
).toMatch(/^Paris is sunny\.?$/)
|
||||
const details = events
|
||||
.filter(LLMEvent.is.reasoningEnd)
|
||||
.map((event) => event.providerMetadata?.openai?.reasoningDetails)
|
||||
.find(Array.isArray)
|
||||
expect(Array.isArray(details)).toBe(item.structured)
|
||||
if (!item.structured || !Array.isArray(details)) return
|
||||
expect(
|
||||
details.some(
|
||||
(detail) =>
|
||||
typeof detail === "object" &&
|
||||
detail !== null &&
|
||||
"signature" in detail &&
|
||||
typeof detail.signature === "string" &&
|
||||
detail.signature.length > 0,
|
||||
),
|
||||
).toBe(true)
|
||||
}),
|
||||
60_000,
|
||||
)
|
||||
})
|
||||
}
|
||||
|
|
|
|||
|
|
@ -570,6 +570,375 @@ describe("OpenAI Chat route", () => {
|
|||
}),
|
||||
)
|
||||
|
||||
it.effect("preserves and replays reasoning details alongside scalar reasoning", () =>
|
||||
Effect.gen(function* () {
|
||||
const details = [
|
||||
{ type: "reasoning.text", text: "thinking", format: "anthropic-claude-v1", index: 0 },
|
||||
{ type: "reasoning.encrypted", data: "opaque", format: "anthropic-claude-v1", index: 1 },
|
||||
]
|
||||
const response = yield* LLMClient.generate(
|
||||
LLM.updateRequest(request, {
|
||||
tools: [{ name: "lookup", description: "Lookup data", inputSchema: { type: "object" } }],
|
||||
}),
|
||||
).pipe(
|
||||
Effect.provide(
|
||||
fixedResponse(
|
||||
sseEvents(
|
||||
{ choices: [{ delta: { reasoning: "thinking", reasoning_details: [details[0]] } }] },
|
||||
{ choices: [{ delta: { reasoning_details: [details[1]] } }] },
|
||||
{
|
||||
choices: [
|
||||
{
|
||||
delta: {
|
||||
tool_calls: [
|
||||
{ index: 0, id: "call_1", function: { name: "lookup", arguments: '{"query":"weather"}' } },
|
||||
],
|
||||
},
|
||||
finish_reason: "tool_calls",
|
||||
},
|
||||
],
|
||||
},
|
||||
),
|
||||
),
|
||||
),
|
||||
)
|
||||
|
||||
expect(response.reasoning).toBe("thinking")
|
||||
expect(response.message.content.find((part) => part.type === "reasoning")?.providerMetadata).toEqual({
|
||||
openai: { reasoningField: "reasoning", reasoningDetails: details },
|
||||
})
|
||||
|
||||
const replay = yield* LLMClient.prepare<OpenAIChat.OpenAIChatBody>(
|
||||
LLM.request({ model, messages: [response.message] }),
|
||||
)
|
||||
expect(replay.body.messages).toEqual([
|
||||
{
|
||||
role: "assistant",
|
||||
content: null,
|
||||
reasoning: "thinking",
|
||||
reasoning_details: details,
|
||||
tool_calls: [
|
||||
{
|
||||
id: "call_1",
|
||||
type: "function",
|
||||
function: { name: "lookup", arguments: '{"query":"weather"}' },
|
||||
},
|
||||
],
|
||||
},
|
||||
])
|
||||
}),
|
||||
)
|
||||
|
||||
it.effect("uses reasoning details as display fallback without inventing a scalar replay field", () =>
|
||||
Effect.gen(function* () {
|
||||
const details = [
|
||||
{ type: "reasoning.summary", summary: "thinking", format: "openai-responses-v1", index: 0 },
|
||||
{ type: "reasoning.encrypted", data: "opaque", format: "openai-responses-v1", index: 1 },
|
||||
]
|
||||
const response = yield* LLMClient.generate(request).pipe(
|
||||
Effect.provide(
|
||||
fixedResponse(
|
||||
sseEvents(
|
||||
{ choices: [{ delta: { reasoning_details: [details[0]] } }] },
|
||||
{ choices: [{ delta: { reasoning_details: [details[1]] } }] },
|
||||
{ choices: [{ delta: { content: "Hello" } }] },
|
||||
{ choices: [{ delta: {}, finish_reason: "stop" }] },
|
||||
),
|
||||
),
|
||||
),
|
||||
)
|
||||
|
||||
expect(response.reasoning).toBe("thinking")
|
||||
expect(response.message.content.find((part) => part.type === "reasoning")?.providerMetadata).toEqual({
|
||||
openai: { reasoningDetails: details },
|
||||
})
|
||||
|
||||
const replay = yield* LLMClient.prepare<OpenAIChat.OpenAIChatBody>(
|
||||
LLM.request({ model, messages: [response.message] }),
|
||||
)
|
||||
expect(replay.body.messages).toEqual([{ role: "assistant", content: "Hello", reasoning_details: details }])
|
||||
}),
|
||||
)
|
||||
|
||||
it.effect("preserves unknown reasoning details while using scalar display text", () =>
|
||||
Effect.gen(function* () {
|
||||
const details = [{ type: "reasoning.future", format: "provider-v2", state: { opaque: true } }]
|
||||
const response = yield* LLMClient.generate(request).pipe(
|
||||
Effect.provide(
|
||||
fixedResponse(
|
||||
sseEvents(
|
||||
{ choices: [{ delta: { reasoning: "thinking", reasoning_details: details } }] },
|
||||
{ choices: [{ delta: { content: "Hello" } }] },
|
||||
{ choices: [{ delta: {}, finish_reason: "stop" }] },
|
||||
),
|
||||
),
|
||||
),
|
||||
)
|
||||
|
||||
expect(response.reasoning).toBe("thinking")
|
||||
expect(response.message.content.find((part) => part.type === "reasoning")?.providerMetadata).toEqual({
|
||||
openai: { reasoningField: "reasoning", reasoningDetails: details },
|
||||
})
|
||||
|
||||
const replay = yield* LLMClient.prepare<OpenAIChat.OpenAIChatBody>(
|
||||
LLM.request({ model, messages: [response.message] }),
|
||||
)
|
||||
expect(replay.body.messages).toEqual([
|
||||
{ role: "assistant", content: "Hello", reasoning: "thinking", reasoning_details: details },
|
||||
])
|
||||
}),
|
||||
)
|
||||
|
||||
it.effect("uses scalar display text for signature-only reasoning details", () =>
|
||||
Effect.gen(function* () {
|
||||
const details = [{ type: "reasoning.text", signature: "signed", format: "provider-v2", index: 0 }]
|
||||
const response = yield* LLMClient.generate(request).pipe(
|
||||
Effect.provide(
|
||||
fixedResponse(
|
||||
sseEvents(
|
||||
{ choices: [{ delta: { reasoning: "thinking", reasoning_details: details } }] },
|
||||
{ choices: [{ delta: { content: "Hello" } }] },
|
||||
{ choices: [{ delta: {}, finish_reason: "stop" }] },
|
||||
),
|
||||
),
|
||||
),
|
||||
)
|
||||
|
||||
expect(response.reasoning).toBe("thinking")
|
||||
expect(response.message.content.find((part) => part.type === "reasoning")?.providerMetadata).toEqual({
|
||||
openai: { reasoningField: "reasoning", reasoningDetails: details },
|
||||
})
|
||||
}),
|
||||
)
|
||||
|
||||
it.effect("ignores scalar reasoning after content starts", () =>
|
||||
Effect.gen(function* () {
|
||||
const details = [{ type: "reasoning.text", text: "detail", format: "unknown", index: 0 }]
|
||||
const response = yield* LLMClient.generate(request).pipe(
|
||||
Effect.provide(
|
||||
fixedResponse(
|
||||
sseEvents(
|
||||
{ choices: [{ delta: { reasoning_details: details } }] },
|
||||
{ choices: [{ delta: { content: "Hello" } }] },
|
||||
{ choices: [{ delta: { reasoning: "scalar" } }] },
|
||||
{ choices: [{ delta: {}, finish_reason: "stop" }] },
|
||||
),
|
||||
),
|
||||
),
|
||||
)
|
||||
|
||||
expect(response.reasoning).toBe("detail")
|
||||
expect(response.events.filter(LLMEvent.is.reasoningStart)).toHaveLength(1)
|
||||
expect(response.events.filter(LLMEvent.is.reasoningEnd)).toHaveLength(1)
|
||||
expect(response.message.content.find((part) => part.type === "reasoning")?.providerMetadata).toEqual({
|
||||
openai: { reasoningDetails: details },
|
||||
})
|
||||
}),
|
||||
)
|
||||
|
||||
it.effect("preserves an explicitly empty reasoning details array", () =>
|
||||
Effect.gen(function* () {
|
||||
const response = yield* LLMClient.generate(request).pipe(
|
||||
Effect.provide(
|
||||
fixedResponse(
|
||||
sseEvents(
|
||||
{ choices: [{ delta: { reasoning_details: [] } }] },
|
||||
{ choices: [{ delta: { content: "Hello" } }] },
|
||||
{ choices: [{ delta: {}, finish_reason: "stop" }] },
|
||||
),
|
||||
),
|
||||
),
|
||||
)
|
||||
|
||||
expect(response.reasoning).toBe("")
|
||||
expect(response.message.content.find((part) => part.type === "reasoning")?.providerMetadata).toEqual({
|
||||
openai: { reasoningDetails: [] },
|
||||
})
|
||||
|
||||
const replay = yield* LLMClient.prepare<OpenAIChat.OpenAIChatBody>(
|
||||
LLM.request({ model, messages: [response.message] }),
|
||||
)
|
||||
expect(replay.body.messages).toEqual([{ role: "assistant", content: "Hello", reasoning_details: [] }])
|
||||
}),
|
||||
)
|
||||
|
||||
it.effect("attaches signature-only details that arrive after content", () =>
|
||||
Effect.gen(function* () {
|
||||
const details = [
|
||||
{ type: "reasoning.text", text: "thinking", format: "anthropic-claude-v1", index: 0 },
|
||||
{ type: "reasoning.text", signature: "signed", format: "anthropic-claude-v1", index: 0 },
|
||||
]
|
||||
const merged = [
|
||||
{
|
||||
type: "reasoning.text",
|
||||
text: "thinking",
|
||||
signature: "signed",
|
||||
format: "anthropic-claude-v1",
|
||||
index: 0,
|
||||
},
|
||||
]
|
||||
const response = yield* LLMClient.generate(request).pipe(
|
||||
Effect.provide(
|
||||
fixedResponse(
|
||||
sseEvents(
|
||||
{ choices: [{ delta: { reasoning: "thinking", reasoning_details: [details[0]] } }] },
|
||||
{ choices: [{ delta: { content: "Hello" } }] },
|
||||
{ choices: [{ delta: { reasoning_details: [details[1]] } }] },
|
||||
{ choices: [{ delta: {}, finish_reason: "stop" }] },
|
||||
),
|
||||
),
|
||||
),
|
||||
)
|
||||
|
||||
expect(response.reasoning).toBe("thinking")
|
||||
expect(response.message.content.filter((part) => part.type === "reasoning")).toHaveLength(1)
|
||||
expect(response.message.content.find((part) => part.type === "reasoning")?.providerMetadata).toEqual({
|
||||
openai: { reasoningField: "reasoning", reasoningDetails: merged },
|
||||
})
|
||||
expect(response.events.filter(LLMEvent.is.reasoningStart)).toHaveLength(1)
|
||||
expect(response.events.filter(LLMEvent.is.reasoningDelta)).toHaveLength(1)
|
||||
expect(response.events.filter(LLMEvent.is.reasoningEnd)).toHaveLength(1)
|
||||
expect(response.events.filter(LLMEvent.is.reasoningEnd).at(-1)?.providerMetadata).toEqual({
|
||||
openai: { reasoningField: "reasoning", reasoningDetails: merged },
|
||||
})
|
||||
expect(response.events.findIndex(LLMEvent.is.reasoningEnd)).toBeLessThan(
|
||||
response.events.findIndex(LLMEvent.is.textStart),
|
||||
)
|
||||
|
||||
const replay = yield* LLMClient.prepare<OpenAIChat.OpenAIChatBody>(
|
||||
LLM.request({ model, messages: [response.message] }),
|
||||
)
|
||||
expect(replay.body.messages).toEqual([
|
||||
{ role: "assistant", content: "Hello", reasoning: "thinking", reasoning_details: merged },
|
||||
])
|
||||
}),
|
||||
)
|
||||
|
||||
it.effect("preserves metadata-only reasoning when the stream ends", () =>
|
||||
Effect.gen(function* () {
|
||||
const details = [{ type: "reasoning.encrypted", data: "opaque", format: "openai-responses-v1", index: 0 }]
|
||||
const response = yield* LLMClient.generate(request).pipe(
|
||||
Effect.provide(
|
||||
fixedResponse(
|
||||
sseEvents(
|
||||
{ choices: [{ delta: { reasoning_details: details } }] },
|
||||
{ choices: [{ delta: {}, finish_reason: "stop" }] },
|
||||
),
|
||||
),
|
||||
),
|
||||
)
|
||||
|
||||
expect(response.message.content).toEqual([
|
||||
{ type: "reasoning", text: "", providerMetadata: { openai: { reasoningDetails: details } } },
|
||||
])
|
||||
expect(response.events.filter(LLMEvent.is.reasoningStart)).toHaveLength(1)
|
||||
expect(response.events.filter(LLMEvent.is.reasoningEnd)).toHaveLength(1)
|
||||
|
||||
const replay = yield* LLMClient.prepare<OpenAIChat.OpenAIChatBody>(
|
||||
LLM.request({ model, messages: [response.message] }),
|
||||
)
|
||||
expect(replay.body.messages).toEqual([{ role: "assistant", content: null, reasoning_details: details }])
|
||||
}),
|
||||
)
|
||||
|
||||
it.effect("flushes details-only display reasoning when the stream ends", () =>
|
||||
Effect.gen(function* () {
|
||||
const details = [{ type: "reasoning.summary", summary: "summary", format: "openai-responses-v1", index: 0 }]
|
||||
const response = yield* LLMClient.generate(request).pipe(
|
||||
Effect.provide(
|
||||
fixedResponse(
|
||||
sseEvents(
|
||||
{ choices: [{ delta: { reasoning_details: details } }] },
|
||||
{ choices: [{ delta: {}, finish_reason: "stop" }] },
|
||||
),
|
||||
),
|
||||
),
|
||||
)
|
||||
|
||||
expect(response.reasoning).toBe("summary")
|
||||
expect(response.message.content).toEqual([
|
||||
{ type: "reasoning", text: "summary", providerMetadata: { openai: { reasoningDetails: details } } },
|
||||
])
|
||||
}),
|
||||
)
|
||||
|
||||
it.effect("replays details from multiple reasoning parts in order", () =>
|
||||
Effect.gen(function* () {
|
||||
const first = { type: "reasoning.text", text: "first", signature: "signed-0", index: 0 }
|
||||
const second = { type: "reasoning.text", text: "second", signature: "signed-1", index: 1 }
|
||||
const replay = yield* LLMClient.prepare<OpenAIChat.OpenAIChatBody>(
|
||||
LLM.request({
|
||||
model,
|
||||
messages: [
|
||||
Message.assistant([
|
||||
{
|
||||
type: "reasoning",
|
||||
text: "first",
|
||||
providerMetadata: { openai: { reasoningDetails: [first] } },
|
||||
},
|
||||
{
|
||||
type: "reasoning",
|
||||
text: "second",
|
||||
providerMetadata: { openai: { reasoningField: "reasoning", reasoningDetails: [second] } },
|
||||
},
|
||||
]),
|
||||
],
|
||||
}),
|
||||
)
|
||||
|
||||
expect(replay.body.messages).toEqual([
|
||||
{ role: "assistant", content: null, reasoning: "firstsecond", reasoning_details: [first, second] },
|
||||
])
|
||||
}),
|
||||
)
|
||||
|
||||
it.effect("retains scalar replay for mixed structured reasoning parts", () =>
|
||||
Effect.gen(function* () {
|
||||
const detail = { type: "reasoning.encrypted", data: "opaque", index: 0 }
|
||||
const replay = yield* LLMClient.prepare<OpenAIChat.OpenAIChatBody>(
|
||||
LLM.request({
|
||||
model,
|
||||
messages: [
|
||||
Message.assistant([
|
||||
{
|
||||
type: "reasoning",
|
||||
text: "A",
|
||||
providerMetadata: { openai: { reasoningDetails: [detail] } },
|
||||
},
|
||||
{ type: "reasoning", text: "B" },
|
||||
]),
|
||||
],
|
||||
}),
|
||||
)
|
||||
|
||||
expect(replay.body.messages).toEqual([
|
||||
{ role: "assistant", content: null, reasoning_content: "AB", reasoning_details: [detail] },
|
||||
])
|
||||
}),
|
||||
)
|
||||
|
||||
it.effect("replays native scalar reasoning alongside native details", () =>
|
||||
Effect.gen(function* () {
|
||||
const details = [{ type: "reasoning.encrypted", data: "opaque", index: 0 }]
|
||||
const replay = yield* LLMClient.prepare<OpenAIChat.OpenAIChatBody>(
|
||||
LLM.request({
|
||||
model,
|
||||
messages: [
|
||||
Message.make({
|
||||
role: "assistant",
|
||||
content: [{ type: "reasoning", text: "thinking" }],
|
||||
native: { openaiCompatible: { reasoning_content: "thinking", reasoning_details: details } },
|
||||
}),
|
||||
],
|
||||
}),
|
||||
)
|
||||
|
||||
expect(replay.body.messages).toEqual([
|
||||
{ role: "assistant", content: null, reasoning_content: "thinking", reasoning_details: details },
|
||||
])
|
||||
}),
|
||||
)
|
||||
|
||||
it.effect("assembles streamed tool call input", () =>
|
||||
Effect.gen(function* () {
|
||||
const body = sseEvents(
|
||||
|
|
@ -606,6 +975,67 @@ describe("OpenAI Chat route", () => {
|
|||
}),
|
||||
)
|
||||
|
||||
it.effect("ignores empty identity fields on later tool call deltas", () =>
|
||||
Effect.gen(function* () {
|
||||
const body = sseEvents(
|
||||
deltaChunk({
|
||||
tool_calls: [{ index: 0, id: "call_1", function: { name: "lookup", arguments: "{" } }],
|
||||
}),
|
||||
deltaChunk({
|
||||
tool_calls: [{ index: 0, id: "", function: { name: "", arguments: '\"query\":\"weather\"}' } }],
|
||||
}),
|
||||
deltaChunk({}, "tool_calls"),
|
||||
)
|
||||
const response = yield* LLMClient.generate(
|
||||
LLM.updateRequest(request, {
|
||||
tools: [{ name: "lookup", description: "Lookup data", inputSchema: { type: "object" } }],
|
||||
}),
|
||||
).pipe(Effect.provide(fixedResponse(body)))
|
||||
|
||||
expect(response.toolCalls).toMatchObject([{ id: "call_1", name: "lookup", input: { query: "weather" } }])
|
||||
}),
|
||||
)
|
||||
|
||||
it.effect("buffers tool call deltas until the function name arrives", () =>
|
||||
Effect.gen(function* () {
|
||||
const body = sseEvents(
|
||||
deltaChunk({
|
||||
tool_calls: [{ index: 0, id: "call_1", function: { arguments: "{" } }],
|
||||
}),
|
||||
deltaChunk({
|
||||
tool_calls: [{ index: 0, function: { name: "lookup", arguments: '\"query\":' } }],
|
||||
}),
|
||||
deltaChunk({ tool_calls: [{ index: 0, function: { arguments: '\"weather\"}' } }] }),
|
||||
deltaChunk({}, "tool_calls"),
|
||||
)
|
||||
const response = yield* LLMClient.generate(
|
||||
LLM.updateRequest(request, {
|
||||
tools: [{ name: "lookup", description: "Lookup data", inputSchema: { type: "object" } }],
|
||||
}),
|
||||
).pipe(Effect.provide(fixedResponse(body)))
|
||||
|
||||
expect(response.toolCalls).toMatchObject([{ id: "call_1", name: "lookup", input: { query: "weather" } }])
|
||||
}),
|
||||
)
|
||||
|
||||
it.effect("fails when a buffered tool call never receives a function name", () =>
|
||||
Effect.gen(function* () {
|
||||
const body = sseEvents(
|
||||
deltaChunk({
|
||||
tool_calls: [{ index: 0, id: "call_1", function: { arguments: "{}" } }],
|
||||
}),
|
||||
deltaChunk({}, "tool_calls"),
|
||||
)
|
||||
const error = yield* LLMClient.generate(
|
||||
LLM.updateRequest(request, {
|
||||
tools: [{ name: "lookup", description: "Lookup data", inputSchema: { type: "object" } }],
|
||||
}),
|
||||
).pipe(Effect.provide(fixedResponse(body)), Effect.flip)
|
||||
|
||||
expect(error.message).toContain("OpenAI Chat tool call delta is missing id or name")
|
||||
}),
|
||||
)
|
||||
|
||||
it.effect("fails a streamed tool call when the provider ends without a finish reason", () =>
|
||||
Effect.gen(function* () {
|
||||
const body = sseEvents(
|
||||
|
|
|
|||
|
|
@ -1,18 +1,12 @@
|
|||
import { describe, expect } from "bun:test"
|
||||
import { Effect } from "effect"
|
||||
import { Image } from "../../src"
|
||||
import { Image, ImageInput } from "../../src"
|
||||
import { OpenAI } from "../../src/providers"
|
||||
import { dimensions } from "../lib/image"
|
||||
import { recordedTests } from "../recorded-test"
|
||||
|
||||
const model = OpenAI.configure({
|
||||
apiKey: process.env.OPENAI_API_KEY ?? "fixture",
|
||||
image: {
|
||||
providerOptions: {
|
||||
quality: "low",
|
||||
outputFormat: "jpeg",
|
||||
outputCompression: 10,
|
||||
},
|
||||
},
|
||||
}).image("gpt-image-1-mini")
|
||||
|
||||
const recorded = recordedTests({
|
||||
|
|
@ -28,7 +22,7 @@ describe("OpenAI Images recorded", () => {
|
|||
const response = yield* Image.generate({
|
||||
model,
|
||||
prompt: "A simple flat black circle centered on a plain white background.",
|
||||
size: { width: 1024, height: 1024 },
|
||||
options: { quality: "low", outputFormat: "jpeg", outputCompression: 10, size: "1024x1024" },
|
||||
})
|
||||
|
||||
expect(response.images).toHaveLength(1)
|
||||
|
|
@ -37,4 +31,32 @@ describe("OpenAI Images recorded", () => {
|
|||
expect(response.image?.data.length).toBeGreaterThan(0)
|
||||
}),
|
||||
)
|
||||
|
||||
recorded.effect.with(
|
||||
"edits an image",
|
||||
{
|
||||
options: {
|
||||
match: (incoming, recorded) => incoming.method === recorded.method && incoming.url === recorded.url,
|
||||
},
|
||||
},
|
||||
() =>
|
||||
Effect.gen(function* () {
|
||||
const response = yield* Image.generate({
|
||||
model,
|
||||
prompt: "Keep the simple shape and change it from black to bright green.",
|
||||
images: [
|
||||
ImageInput.bytes(
|
||||
yield* Effect.promise(() => Bun.file("test/fixtures/images/edit-source.jpg").bytes()),
|
||||
"image/jpeg",
|
||||
),
|
||||
],
|
||||
options: { quality: "low", outputFormat: "jpeg", outputCompression: 10, size: "1024x1024" },
|
||||
})
|
||||
|
||||
expect(response.image?.mediaType).toBe("image/jpeg")
|
||||
expect(response.image?.data).toBeInstanceOf(Uint8Array)
|
||||
if (!(response.image?.data instanceof Uint8Array)) throw new Error("Expected owned OpenAI image bytes")
|
||||
expect(dimensions(response.image.data)).toEqual({ width: 1024, height: 1024 })
|
||||
}),
|
||||
)
|
||||
})
|
||||
|
|
|
|||
|
|
@ -1,6 +1,6 @@
|
|||
import { describe, expect } from "bun:test"
|
||||
import { Effect } from "effect"
|
||||
import { LLM } from "../../src"
|
||||
import { LLM, Message } from "../../src"
|
||||
import { LLMClient } from "../../src/route"
|
||||
import * as OpenRouter from "../../src/providers/openrouter"
|
||||
import { it } from "../lib/effect"
|
||||
|
|
@ -53,4 +53,102 @@ describe("OpenRouter", () => {
|
|||
})
|
||||
}),
|
||||
)
|
||||
|
||||
it.effect("preserves manually supplied reasoning details", () =>
|
||||
Effect.gen(function* () {
|
||||
const details = [
|
||||
{ type: "reasoning.text", text: "Think", format: "anthropic-claude-v1", index: 0 },
|
||||
{ type: "reasoning.text", text: "ing", format: "anthropic-claude-v1", index: 0 },
|
||||
{ type: "reasoning.text", signature: "signed", format: "anthropic-claude-v1", index: 0 },
|
||||
{ type: "reasoning.encrypted", data: "opaque", format: "openai-responses-v1", index: 1 },
|
||||
]
|
||||
const prepared = yield* LLMClient.prepare<OpenRouter.OpenRouterBody>(
|
||||
LLM.request({
|
||||
model: OpenRouter.configure({ apiKey: "test-key" }).model("anthropic/claude-sonnet-4.6"),
|
||||
messages: [
|
||||
Message.assistant([
|
||||
{
|
||||
type: "reasoning",
|
||||
text: "Thinking",
|
||||
providerMetadata: { openai: { reasoningField: "reasoning", reasoningDetails: details } },
|
||||
},
|
||||
]),
|
||||
],
|
||||
}),
|
||||
)
|
||||
|
||||
expect(prepared.body.messages).toEqual([
|
||||
{
|
||||
role: "assistant",
|
||||
content: null,
|
||||
reasoning: "Thinking",
|
||||
reasoning_details: details,
|
||||
},
|
||||
])
|
||||
}),
|
||||
)
|
||||
|
||||
it.effect("preserves opaque and duplicate continuation details", () =>
|
||||
Effect.gen(function* () {
|
||||
const details = [
|
||||
{ type: "reasoning.future", format: "provider-v2", state: { opaque: true } },
|
||||
{ type: "reasoning.encrypted", id: "state", data: "opaque" },
|
||||
{ type: "reasoning.encrypted", id: "state", data: "opaque" },
|
||||
]
|
||||
const prepared = yield* LLMClient.prepare<OpenRouter.OpenRouterBody>(
|
||||
LLM.request({
|
||||
model: OpenRouter.configure({ apiKey: "test-key" }).model("anthropic/claude-sonnet-4.6"),
|
||||
messages: [
|
||||
Message.assistant({
|
||||
type: "reasoning",
|
||||
text: "Thinking",
|
||||
providerMetadata: { openai: { reasoningField: "reasoning", reasoningDetails: details } },
|
||||
}),
|
||||
],
|
||||
}),
|
||||
)
|
||||
|
||||
expect(prepared.body.messages).toEqual([
|
||||
{ role: "assistant", content: null, reasoning: "Thinking", reasoning_details: details },
|
||||
])
|
||||
}),
|
||||
)
|
||||
|
||||
it.effect("does not merge distinct adjacent reasoning text blocks", () =>
|
||||
Effect.gen(function* () {
|
||||
const details = [
|
||||
{ type: "reasoning.text", id: "first", index: 0, text: "A", opaque: "first" },
|
||||
{ type: "reasoning.text", id: "second", index: 1, text: "B", opaque: "second" },
|
||||
]
|
||||
const prepared = yield* LLMClient.prepare<OpenRouter.OpenRouterBody>(
|
||||
LLM.request({
|
||||
model: OpenRouter.configure({ apiKey: "test-key" }).model("anthropic/claude-sonnet-4.6"),
|
||||
messages: [
|
||||
Message.assistant({
|
||||
type: "reasoning",
|
||||
text: "AB",
|
||||
providerMetadata: { openai: { reasoningField: "reasoning", reasoningDetails: details } },
|
||||
}),
|
||||
],
|
||||
}),
|
||||
)
|
||||
|
||||
expect(prepared.body.messages).toEqual([
|
||||
{ role: "assistant", content: null, reasoning: "AB", reasoning_details: details },
|
||||
])
|
||||
}),
|
||||
)
|
||||
|
||||
it.effect("omits scalar reasoning without continuation details", () =>
|
||||
Effect.gen(function* () {
|
||||
const prepared = yield* LLMClient.prepare<OpenRouter.OpenRouterBody>(
|
||||
LLM.request({
|
||||
model: OpenRouter.configure({ apiKey: "test-key" }).model("anthropic/claude-sonnet-4.6"),
|
||||
messages: [Message.assistant({ type: "reasoning", text: "Thinking" })],
|
||||
}),
|
||||
)
|
||||
|
||||
expect(prepared.body.messages).toEqual([{ role: "assistant", content: null }])
|
||||
}),
|
||||
)
|
||||
})
|
||||
|
|
|
|||
55
packages/ai/test/provider/xai-images.recorded.test.ts
Normal file
55
packages/ai/test/provider/xai-images.recorded.test.ts
Normal file
|
|
@ -0,0 +1,55 @@
|
|||
import { describe, expect } from "bun:test"
|
||||
import { Effect } from "effect"
|
||||
import { Image, ImageInput } from "../../src"
|
||||
import { XAI } from "../../src/providers"
|
||||
import { dimensions } from "../lib/image"
|
||||
import { recordedTests } from "../recorded-test"
|
||||
|
||||
const model = XAI.configure({
|
||||
apiKey: process.env.XAI_API_KEY ?? "fixture",
|
||||
}).image("grok-imagine-image")
|
||||
|
||||
const recorded = recordedTests({
|
||||
prefix: "xai-images",
|
||||
provider: "xai",
|
||||
protocol: "xai-images",
|
||||
requires: ["XAI_API_KEY"],
|
||||
})
|
||||
|
||||
describe("xAI Images recorded", () => {
|
||||
recorded.effect("generates an image", () =>
|
||||
Effect.gen(function* () {
|
||||
const response = yield* Image.generate({
|
||||
model,
|
||||
prompt: "A simple flat black diamond centered on a plain white background.",
|
||||
options: { aspectRatio: "1:1", resolution: "1k", responseFormat: "b64_json" },
|
||||
})
|
||||
|
||||
expect(response.images).toHaveLength(1)
|
||||
expect(response.image?.mediaType.startsWith("image/")).toBe(true)
|
||||
expect(response.image?.data).toBeInstanceOf(Uint8Array)
|
||||
expect(response.image?.data.length).toBeGreaterThan(0)
|
||||
}),
|
||||
)
|
||||
|
||||
recorded.effect("edits an image", () =>
|
||||
Effect.gen(function* () {
|
||||
const response = yield* Image.generate({
|
||||
model,
|
||||
prompt: "Keep the simple shape and change it from black to bright purple.",
|
||||
images: [
|
||||
ImageInput.bytes(
|
||||
yield* Effect.promise(() => Bun.file("test/fixtures/images/edit-source.jpg").bytes()),
|
||||
"image/jpeg",
|
||||
),
|
||||
],
|
||||
options: { aspectRatio: "1:1", resolution: "1k", responseFormat: "b64_json" },
|
||||
})
|
||||
|
||||
expect(response.image?.mediaType).toMatch(/^image\/(jpeg|png)$/)
|
||||
expect(response.image?.data).toBeInstanceOf(Uint8Array)
|
||||
if (!(response.image?.data instanceof Uint8Array)) throw new Error("Expected owned xAI image bytes")
|
||||
expect(dimensions(response.image.data)).toEqual({ width: 1024, height: 1024 })
|
||||
}),
|
||||
)
|
||||
})
|
||||
109
packages/ai/test/provider/xai-images.test.ts
Normal file
109
packages/ai/test/provider/xai-images.test.ts
Normal file
|
|
@ -0,0 +1,109 @@
|
|||
import { describe, expect } from "bun:test"
|
||||
import { Effect, Layer } from "effect"
|
||||
import { Headers, HttpClientRequest } from "effect/unstable/http"
|
||||
import { Image, ImageClient } from "../../src"
|
||||
import { XAI } from "../../src/providers"
|
||||
import { Auth } from "../../src/route"
|
||||
import { it } from "../lib/effect"
|
||||
import { dynamicResponse } from "../lib/http"
|
||||
|
||||
describe("xAI Images", () => {
|
||||
it.effect("generates through the OpenAI-compatible Images API", () =>
|
||||
Effect.gen(function* () {
|
||||
const response = yield* Image.generate({
|
||||
model: XAI.configure({
|
||||
apiKey: "test",
|
||||
baseURL: "https://api.xai.test/v1",
|
||||
http: { body: { configured: true }, headers: { "x-default": "yes" } },
|
||||
}).image("grok-imagine-image"),
|
||||
prompt: "A robot tending a rooftop garden",
|
||||
options: {
|
||||
n: 2,
|
||||
aspectRatio: "16:9",
|
||||
aspect_ratio: "4:3",
|
||||
resolution: "1k",
|
||||
responseFormat: "url",
|
||||
response_format: "b64_json",
|
||||
future_option: true,
|
||||
},
|
||||
http: {
|
||||
body: { resolution: "2k", future_option: "http" },
|
||||
headers: { "x-request": "yes" },
|
||||
query: { trace: "1" },
|
||||
},
|
||||
})
|
||||
|
||||
expect(response.images).toHaveLength(2)
|
||||
expect(response.image?.mediaType).toBe("image/jpeg")
|
||||
expect(response.image?.data).toEqual(Uint8Array.from([1, 2, 3]))
|
||||
expect(response.images[1]?.mediaType).toBe("application/octet-stream")
|
||||
expect(response.images[1]?.data).toBe("https://api.xai.test/image.jpg")
|
||||
expect(response.usage?.providerMetadata).toEqual({ xai: { num_images: 2 } })
|
||||
expect(response.providerMetadata).toEqual({ xai: { usage: { num_images: 2 } } })
|
||||
}).pipe(
|
||||
Effect.provide(
|
||||
ImageClient.layer.pipe(
|
||||
Layer.provide(
|
||||
dynamicResponse((input) =>
|
||||
Effect.gen(function* () {
|
||||
const request = yield* HttpClientRequest.toWeb(input.request).pipe(Effect.orDie)
|
||||
expect(request.url).toBe("https://api.xai.test/v1/images/generations?trace=1")
|
||||
expect(request.headers.get("authorization")).toBe("Bearer test")
|
||||
expect(request.headers.get("x-default")).toBe("yes")
|
||||
expect(request.headers.get("x-request")).toBe("yes")
|
||||
expect(JSON.parse(input.text)).toEqual({
|
||||
model: "grok-imagine-image",
|
||||
prompt: "A robot tending a rooftop garden",
|
||||
n: 2,
|
||||
aspect_ratio: "4:3",
|
||||
resolution: "2k",
|
||||
response_format: "b64_json",
|
||||
future_option: "http",
|
||||
configured: true,
|
||||
})
|
||||
return input.respond(
|
||||
JSON.stringify({
|
||||
data: [
|
||||
{ b64_json: "AQID", url: null, mime_type: "image/jpeg" },
|
||||
{ b64_json: null, url: "https://api.xai.test/image.jpg", mime_type: null },
|
||||
],
|
||||
usage: { num_images: 2 },
|
||||
}),
|
||||
{ headers: { "content-type": "application/json" } },
|
||||
)
|
||||
}),
|
||||
),
|
||||
),
|
||||
),
|
||||
),
|
||||
),
|
||||
)
|
||||
|
||||
it.effect("supports request-level custom auth", () =>
|
||||
Image.generate({
|
||||
model: XAI.configure({
|
||||
baseURL: "https://api.xai.test/v1",
|
||||
auth: Auth.custom((input) =>
|
||||
Effect.succeed(Headers.set(input.headers, "x-custom-auth", new URL(input.url).hostname)),
|
||||
),
|
||||
}).image("grok-imagine-image"),
|
||||
prompt: "A robot tending a rooftop garden",
|
||||
}).pipe(
|
||||
Effect.provide(
|
||||
ImageClient.layer.pipe(
|
||||
Layer.provide(
|
||||
dynamicResponse((input) =>
|
||||
Effect.gen(function* () {
|
||||
const request = yield* HttpClientRequest.toWeb(input.request).pipe(Effect.orDie)
|
||||
expect(request.headers.get("x-custom-auth")).toBe("api.xai.test")
|
||||
return input.respond(JSON.stringify({ data: [{ b64_json: "AQID", mime_type: "image/png" }] }), {
|
||||
headers: { "content-type": "application/json" },
|
||||
})
|
||||
}),
|
||||
),
|
||||
),
|
||||
),
|
||||
),
|
||||
),
|
||||
)
|
||||
})
|
||||
32
packages/ai/test/provider/zai-images.recorded.test.ts
Normal file
32
packages/ai/test/provider/zai-images.recorded.test.ts
Normal file
|
|
@ -0,0 +1,32 @@
|
|||
import { describe, expect } from "bun:test"
|
||||
import { Effect } from "effect"
|
||||
import { Image } from "../../src"
|
||||
import { ZAI } from "../../src/providers"
|
||||
import { recordedTests } from "../recorded-test"
|
||||
|
||||
const model = ZAI.configure({ apiKey: process.env.ZAI_API_KEY ?? "fixture" }).image("cogview-4-250304")
|
||||
|
||||
const recorded = recordedTests({
|
||||
prefix: "zai-images",
|
||||
provider: "zai",
|
||||
protocol: "zai-images",
|
||||
requires: ["ZAI_API_KEY"],
|
||||
})
|
||||
|
||||
describe("Z.ai Images recorded", () => {
|
||||
recorded.effect("generates an image", () =>
|
||||
Effect.gen(function* () {
|
||||
const response = yield* Image.generate({
|
||||
model,
|
||||
prompt: "A simple flat red circle centered on a plain white background.",
|
||||
options: { size: "1024x1024", quality: "standard", userID: "opencode-image-test" },
|
||||
})
|
||||
|
||||
expect(response.images).toHaveLength(1)
|
||||
expect(response.image?.mediaType).toBe("application/octet-stream")
|
||||
expect(response.image?.data).toBeString()
|
||||
expect(response.image?.data).toStartWith("https://")
|
||||
expect(response.providerMetadata?.zai).toBeDefined()
|
||||
}),
|
||||
)
|
||||
})
|
||||
130
packages/ai/test/provider/zai-images.test.ts
Normal file
130
packages/ai/test/provider/zai-images.test.ts
Normal file
|
|
@ -0,0 +1,130 @@
|
|||
import { describe, expect } from "bun:test"
|
||||
import { Effect, Layer } from "effect"
|
||||
import { HttpClientRequest } from "effect/unstable/http"
|
||||
import { Image, ImageClient } from "../../src"
|
||||
import { ZAI } from "../../src/providers"
|
||||
import { it } from "../lib/effect"
|
||||
import { dynamicResponse, fixedResponse } from "../lib/http"
|
||||
|
||||
describe("Z.ai Images", () => {
|
||||
it.effect("generates through the Z.ai Images API", () =>
|
||||
Effect.gen(function* () {
|
||||
const response = yield* Image.generate({
|
||||
model: ZAI.configure({
|
||||
apiKey: "test",
|
||||
baseURL: "https://api.z.ai.test/api/paas/v4",
|
||||
headers: { "x-default": "yes" },
|
||||
http: { body: { configured: true, quality: "configured" }, query: { trace: "default" } },
|
||||
}).image("glm-image"),
|
||||
prompt: "A red circle on a white background",
|
||||
options: {
|
||||
quality: "hd",
|
||||
userID: "alias-user",
|
||||
user_id: "raw-user",
|
||||
future_option: true,
|
||||
},
|
||||
http: {
|
||||
headers: { "x-request": "yes" },
|
||||
query: { trace: "request" },
|
||||
body: { quality: "final", user_id: "final-user" },
|
||||
},
|
||||
})
|
||||
|
||||
expect(response.images).toHaveLength(1)
|
||||
expect(response.image?.mediaType).toBe("application/octet-stream")
|
||||
expect(response.image?.data).toBe("https://cdn.z.ai/generated.png")
|
||||
expect(response.providerMetadata).toEqual({
|
||||
zai: {
|
||||
created: 1_760_335_349,
|
||||
id: "generation-1",
|
||||
requestID: "request-1",
|
||||
contentFilter: [{ role: "future-role", level: 4.5 }],
|
||||
},
|
||||
})
|
||||
}).pipe(
|
||||
Effect.provide(
|
||||
ImageClient.layer.pipe(
|
||||
Layer.provide(
|
||||
dynamicResponse((input) =>
|
||||
Effect.gen(function* () {
|
||||
const request = yield* HttpClientRequest.toWeb(input.request).pipe(Effect.orDie)
|
||||
expect(request.url).toBe("https://api.z.ai.test/api/paas/v4/images/generations?trace=request")
|
||||
expect(request.headers.get("authorization")).toBe("Bearer test")
|
||||
expect(request.headers.get("x-default")).toBe("yes")
|
||||
expect(request.headers.get("x-request")).toBe("yes")
|
||||
expect(JSON.parse(input.text)).toEqual({
|
||||
model: "glm-image",
|
||||
prompt: "A red circle on a white background",
|
||||
quality: "final",
|
||||
user_id: "final-user",
|
||||
future_option: true,
|
||||
configured: true,
|
||||
})
|
||||
return input.respond(
|
||||
JSON.stringify({
|
||||
created: 1_760_335_349,
|
||||
id: "generation-1",
|
||||
request_id: "request-1",
|
||||
data: [{ url: "https://cdn.z.ai/generated.png" }],
|
||||
content_filter: [{ role: "future-role", level: 4.5 }],
|
||||
}),
|
||||
{ headers: { "content-type": "application/json" } },
|
||||
)
|
||||
}),
|
||||
),
|
||||
),
|
||||
),
|
||||
),
|
||||
),
|
||||
)
|
||||
|
||||
it.effect("lets raw native options override aliases", () =>
|
||||
Image.generate({
|
||||
model: ZAI.configure({ apiKey: "test" }).image("model"),
|
||||
prompt: "test",
|
||||
options: { quality: "future-quality", userID: "x", user_id: "raw-user" },
|
||||
}).pipe(
|
||||
Effect.provide(
|
||||
ImageClient.layer.pipe(
|
||||
Layer.provide(
|
||||
dynamicResponse((input) => {
|
||||
expect(JSON.parse(input.text)).toMatchObject({ quality: "future-quality", user_id: "raw-user" })
|
||||
return Effect.succeed(
|
||||
input.respond(JSON.stringify({ data: [{ url: "https://example.test/image.jpg" }] }), {
|
||||
headers: { "content-type": "application/json" },
|
||||
}),
|
||||
)
|
||||
}),
|
||||
),
|
||||
),
|
||||
),
|
||||
),
|
||||
)
|
||||
|
||||
it.effect("rejects invalid response structures", () =>
|
||||
Effect.gen(function* () {
|
||||
const model = ZAI.configure({ apiKey: "test" }).image("model")
|
||||
const payloads = [
|
||||
{},
|
||||
{ data: [] },
|
||||
{ data: [{ b64_json: "image" }] },
|
||||
{ data: [{ url: 1 }] },
|
||||
{ data: [{ url: "https://example.test/image.jpg" }], content_filter: [{ role: 1, level: "high" }] },
|
||||
]
|
||||
|
||||
yield* Effect.forEach(payloads, (payload) =>
|
||||
Image.generate({ model, prompt: "test" }).pipe(
|
||||
Effect.provide(
|
||||
ImageClient.layer.pipe(
|
||||
Layer.provide(
|
||||
fixedResponse(JSON.stringify(payload), { headers: { "content-type": "application/json" } }),
|
||||
),
|
||||
),
|
||||
),
|
||||
Effect.flip,
|
||||
Effect.tap((error) => Effect.sync(() => expect(error.reason._tag).toBe("InvalidProviderOutput"))),
|
||||
),
|
||||
)
|
||||
}),
|
||||
)
|
||||
})
|
||||
|
|
@ -120,29 +120,8 @@ export const runWeatherToolLoop = (request: LLMRequest) =>
|
|||
throw new Error("Weather tool loop exceeded 10 steps")
|
||||
})
|
||||
|
||||
const assistantContent = (events: ReadonlyArray<LLMEvent>) => {
|
||||
const content: ContentPart[] = []
|
||||
for (const event of events) {
|
||||
if (event.type === "text-delta" || event.type === "reasoning-delta") {
|
||||
const type = event.type === "text-delta" ? "text" : "reasoning"
|
||||
const last = content.at(-1)
|
||||
if (last?.type === type) {
|
||||
content[content.length - 1] = { ...last, text: `${last.text}${event.text}` }
|
||||
} else {
|
||||
content.push({ type, text: event.text })
|
||||
}
|
||||
continue
|
||||
}
|
||||
if (event.type === "text-end" || event.type === "reasoning-end") {
|
||||
const type = event.type === "text-end" ? "text" : "reasoning"
|
||||
const last = content.at(-1)
|
||||
if (last?.type === type) content[content.length - 1] = { ...last, providerMetadata: event.providerMetadata }
|
||||
continue
|
||||
}
|
||||
if (event.type === "tool-call") content.push(event)
|
||||
}
|
||||
return content
|
||||
}
|
||||
const assistantContent = (events: ReadonlyArray<LLMEvent>) =>
|
||||
events.reduce(LLMResponse.reduce, LLMResponse.empty()).message.content
|
||||
|
||||
export const expectFinish = (
|
||||
events: ReadonlyArray<LLMEvent>,
|
||||
|
|
|
|||
|
|
@ -36,6 +36,33 @@ describe("ToolStream", () => {
|
|||
}),
|
||||
)
|
||||
|
||||
it.effect("keeps accumulated identity when later deltas contain empty strings", () =>
|
||||
Effect.gen(function* () {
|
||||
const first = ToolStream.appendOrStart(
|
||||
ADAPTER,
|
||||
ToolStream.empty<number>(),
|
||||
0,
|
||||
{ id: "call_1", name: "lookup", text: '{"query"' },
|
||||
"missing tool",
|
||||
)
|
||||
if (ToolStream.isError(first)) return yield* first
|
||||
const second = ToolStream.appendOrStart(
|
||||
ADAPTER,
|
||||
first.tools,
|
||||
0,
|
||||
{ id: "", name: "", text: ':"weather"}' },
|
||||
"missing tool",
|
||||
)
|
||||
if (ToolStream.isError(second)) return yield* second
|
||||
const finished = yield* ToolStream.finish(ADAPTER, second.tools, 0)
|
||||
|
||||
expect(finished.events).toEqual([
|
||||
{ type: "tool-input-end", id: "call_1", name: "lookup" },
|
||||
{ type: "tool-call", id: "call_1", name: "lookup", input: { query: "weather" } },
|
||||
])
|
||||
}),
|
||||
)
|
||||
|
||||
it.effect("fails appendExisting when the provider skipped the tool start", () =>
|
||||
Effect.gen(function* () {
|
||||
const error = ToolStream.appendExisting(ADAPTER, ToolStream.empty<number>(), 0, "{}", "missing tool")
|
||||
|
|
|
|||
9
packages/ai/tsconfig.types.json
Normal file
9
packages/ai/tsconfig.types.json
Normal file
|
|
@ -0,0 +1,9 @@
|
|||
{
|
||||
"$schema": "https://json.schemastore.org/tsconfig",
|
||||
"extends": "./tsconfig.json",
|
||||
"compilerOptions": {
|
||||
"noEmit": true,
|
||||
"rootDir": "."
|
||||
},
|
||||
"include": ["test/**/*.types.ts"]
|
||||
}
|
||||
|
|
@ -0,0 +1,50 @@
|
|||
import { expect, test } from "@playwright/test"
|
||||
import { base64Encode } from "@opencode-ai/core/util/encode"
|
||||
import { mockOpenCodeServer } from "../utils/mock-server"
|
||||
import { expectAppVisible } from "../utils/waits"
|
||||
|
||||
const directory = "C:/OpenCode/PromptInputV2Editing"
|
||||
const projectID = "proj_prompt_input_v2_editing"
|
||||
const sessionID = "ses_prompt_input_v2_editing"
|
||||
|
||||
test("preserves the draft when a populated command menu triggers a built-in", async ({ page }) => {
|
||||
await mockOpenCodeServer(page, {
|
||||
directory,
|
||||
project: {
|
||||
id: projectID,
|
||||
worktree: directory,
|
||||
vcs: "git",
|
||||
name: "prompt-input-v2-editing",
|
||||
time: { created: 1700000000000, updated: 1700000000000 },
|
||||
sandboxes: [],
|
||||
},
|
||||
provider: { all: [], connected: [], default: {} },
|
||||
sessions: [
|
||||
{
|
||||
id: sessionID,
|
||||
slug: "prompt-input-v2-editing",
|
||||
projectID,
|
||||
directory,
|
||||
title: "Prompt input V2 editing",
|
||||
version: "dev",
|
||||
time: { created: 1700000000000, updated: 1700000000000 },
|
||||
},
|
||||
],
|
||||
pageMessages: () => ({ items: [] }),
|
||||
})
|
||||
await page.addInitScript(() => {
|
||||
localStorage.setItem("settings.v3", JSON.stringify({ general: { newLayoutDesigns: true } }))
|
||||
})
|
||||
|
||||
await page.goto(`/${base64Encode(directory)}/session/${sessionID}`)
|
||||
const composer = page.locator('[data-component="prompt-input-v2"]')
|
||||
const input = composer.locator('[data-component="prompt-input"]')
|
||||
await expectAppVisible(composer)
|
||||
|
||||
await input.fill("keep me")
|
||||
await composer.getByRole("button", { name: "Add images and files" }).click()
|
||||
await page.getByRole("menuitem", { name: "Commands" }).click()
|
||||
await page.locator('[data-suggestion-id="model.choose"]').click()
|
||||
|
||||
await expect(input).toHaveText("keep me")
|
||||
})
|
||||
|
|
@ -54,18 +54,15 @@ test("shows the V2 thinking level control while relevant", async ({ page }) => {
|
|||
})
|
||||
|
||||
await page.goto(`/${base64Encode(directory)}/session/${sessionID}`)
|
||||
const composer = page.locator('[data-component="session-composer"]')
|
||||
const composer = page.locator('[data-component="prompt-input-v2"]')
|
||||
const input = composer.locator('[data-component="prompt-input"]')
|
||||
const control = composer.locator('[data-component="prompt-variant-control"]')
|
||||
const control = composer.getByRole("button", { name: "Choose model variant" })
|
||||
await expectAppVisible(composer)
|
||||
|
||||
await idleComposer(page)
|
||||
await expect(control).toBeHidden()
|
||||
|
||||
await composer.hover()
|
||||
await expect(control).toBeVisible()
|
||||
|
||||
await control.locator('[data-action="prompt-model-variant"]').click()
|
||||
await control.click()
|
||||
const high = page.getByRole("menuitemradio", { name: "high" })
|
||||
await expect(high).toBeVisible()
|
||||
await page.mouse.move(0, 0)
|
||||
|
|
|
|||
|
|
@ -736,5 +736,5 @@ async function switchTitlebarSession(page: Page, sessionID: string, title: strin
|
|||
}
|
||||
|
||||
async function expectSessionReady(page: Page) {
|
||||
await expectAppVisible(page.getByRole("textbox", { name: /Ask anything/i }))
|
||||
await expectAppVisible(page.getByRole("textbox", { name: "Prompt" }))
|
||||
}
|
||||
|
|
|
|||
|
|
@ -1,6 +1,6 @@
|
|||
{
|
||||
"name": "@opencode-ai/app",
|
||||
"version": "1.18.3",
|
||||
"version": "1.18.4",
|
||||
"description": "",
|
||||
"type": "module",
|
||||
"exports": {
|
||||
|
|
@ -81,7 +81,7 @@
|
|||
"diff": "catalog:",
|
||||
"effect": "catalog:",
|
||||
"fuzzysort": "catalog:",
|
||||
"ghostty-web": "github:anomalyco/ghostty-web#513463a6f1190253057e8a3f0dac8f6ee8393553",
|
||||
"ghostty-web": "github:anomalyco/ghostty-web#83c0a07b8628b748aed073b232cb4b52a6ca11c1",
|
||||
"luxon": "catalog:",
|
||||
"marked": "catalog:",
|
||||
"marked-shiki": "catalog:",
|
||||
|
|
|
|||
|
|
@ -37,6 +37,14 @@ function writeAndWait(term: Terminal, data: string): Promise<void> {
|
|||
}
|
||||
|
||||
describe("SerializeAddon", () => {
|
||||
test("preserves color scheme reporting mode", async () => {
|
||||
const { term, addon } = createTerminal()
|
||||
await writeAndWait(term, "\x1b[?2031h")
|
||||
|
||||
expect(addon.serialize().startsWith("\x1b[?2031h")).toBe(true)
|
||||
expect(addon.serialize({ excludeModes: true }).startsWith("\x1b[?2031h")).toBe(false)
|
||||
})
|
||||
|
||||
describe("ANSI color preservation", () => {
|
||||
test("should preserve text attributes (bold, italic, underline)", async () => {
|
||||
const { term, addon } = createTerminal()
|
||||
|
|
|
|||
|
|
@ -89,6 +89,13 @@ const getTerminalBuffers = (value: ITerminalCore): TerminalBuffers | undefined =
|
|||
return { active, normal, alternate }
|
||||
}
|
||||
|
||||
const getTerminalMode = (value: ITerminalCore, mode: number) => {
|
||||
if (!isRecord(value)) return false
|
||||
const terminal = value.wasmTerm
|
||||
if (!isRecord(terminal) || typeof terminal.getMode !== "function") return false
|
||||
return terminal.getMode(mode) === true
|
||||
}
|
||||
|
||||
// ============================================================================
|
||||
// Types
|
||||
// ============================================================================
|
||||
|
|
@ -544,7 +551,8 @@ export class SerializeAddon implements ITerminalAddon {
|
|||
return ""
|
||||
}
|
||||
|
||||
let content = options?.range
|
||||
let content = !options?.excludeModes && getTerminalMode(this._terminal, 2031) ? "\u001b[?2031h" : ""
|
||||
content += options?.range
|
||||
? this._serializeBufferByRange(normalBuffer, options.range, true)
|
||||
: this._serializeBufferByScrollback(normalBuffer, options?.scrollback)
|
||||
|
||||
|
|
|
|||
|
|
@ -9,7 +9,16 @@ import { Font } from "@opencode-ai/ui/font"
|
|||
import { Splash } from "@opencode-ai/ui/logo"
|
||||
import { ThemeProvider } from "@opencode-ai/ui/theme/context"
|
||||
import { MetaProvider } from "@solidjs/meta"
|
||||
import { type BaseRouterProps, Navigate, Route, Router, useNavigate, useParams, useSearchParams } from "@solidjs/router"
|
||||
import {
|
||||
type BaseRouterProps,
|
||||
Navigate,
|
||||
Route,
|
||||
Router,
|
||||
useLocation,
|
||||
useNavigate,
|
||||
useParams,
|
||||
useSearchParams,
|
||||
} from "@solidjs/router"
|
||||
import { QueryClient, QueryClientProvider } from "@tanstack/solid-query"
|
||||
import { Effect } from "effect"
|
||||
import { base64Encode } from "@opencode-ai/core/util/encode"
|
||||
|
|
@ -29,6 +38,7 @@ import {
|
|||
Show,
|
||||
} from "solid-js"
|
||||
import { Dynamic } from "solid-js/web"
|
||||
import { makeEventListener } from "@solid-primitives/event-listener"
|
||||
import { CommandProvider, useCommand, type CommandOption } from "@/context/command"
|
||||
import { CommentsProvider } from "@/context/comments"
|
||||
import { FileProvider } from "@/context/file"
|
||||
|
|
|
|||
|
|
@ -5,6 +5,7 @@ import { makeEventListener } from "@solid-primitives/event-listener"
|
|||
import { Tooltip } from "@opencode-ai/ui/tooltip"
|
||||
import { TooltipV2 } from "@opencode-ai/ui/v2/tooltip-v2"
|
||||
import { useLanguage } from "@/context/language"
|
||||
import { usePlatform } from "@/context/platform"
|
||||
|
||||
type Mem = Performance & {
|
||||
memory?: {
|
||||
|
|
@ -107,8 +108,45 @@ function Cell(props: {
|
|||
)
|
||||
}
|
||||
|
||||
function FocusCell(props: { active: boolean; inline?: boolean; onClick: () => void }) {
|
||||
const content = () => (
|
||||
<button
|
||||
type="button"
|
||||
aria-label="Force focus styles on all interactive elements"
|
||||
aria-pressed={props.active}
|
||||
classList={{
|
||||
"flex min-w-0 items-center font-mono uppercase hover:bg-surface-raised-base focus-visible:outline focus-visible:outline-2 focus-visible:outline-offset-[-2px] focus-visible:outline-border-focus": true,
|
||||
"min-h-[20px] w-fit flex-row justify-start gap-1.5 rounded px-1.5 py-0.5 text-left": !!props.inline,
|
||||
"min-h-[42px] w-full flex-col justify-center rounded-[8px] px-0.5 py-1 text-center": !props.inline,
|
||||
"bg-surface-raised-base text-text-strong": props.active,
|
||||
}}
|
||||
onClick={props.onClick}
|
||||
>
|
||||
<span class="text-[10px] leading-none font-black tracking-[0.04em] opacity-70">FOCUS</span>
|
||||
<span classList={{ "leading-none font-bold": true, "text-[11px]": !!props.inline, "text-[13px]": !props.inline }}>
|
||||
{props.active ? "ON" : "OFF"}
|
||||
</span>
|
||||
</button>
|
||||
)
|
||||
|
||||
if (props.inline) {
|
||||
return (
|
||||
<TooltipV2 value="Force focus styles on all interactive elements" placement="top">
|
||||
{content()}
|
||||
</TooltipV2>
|
||||
)
|
||||
}
|
||||
|
||||
return (
|
||||
<Tooltip value="Force focus styles on all interactive elements" placement="top">
|
||||
{content()}
|
||||
</Tooltip>
|
||||
)
|
||||
}
|
||||
|
||||
export function DebugBar(props: { inline?: boolean } = {}) {
|
||||
const language = useLanguage()
|
||||
const platform = usePlatform()
|
||||
const location = useLocation()
|
||||
const routing = useIsRouting()
|
||||
const [state, setState] = createStore({
|
||||
|
|
@ -116,6 +154,7 @@ export function DebugBar(props: { inline?: boolean } = {}) {
|
|||
delay: undefined as number | undefined,
|
||||
fps: undefined as number | undefined,
|
||||
gap: undefined as number | undefined,
|
||||
focus: false,
|
||||
heap: {
|
||||
limit: undefined as number | undefined,
|
||||
used: undefined as number | undefined,
|
||||
|
|
@ -142,6 +181,16 @@ export function DebugBar(props: { inline?: boolean } = {}) {
|
|||
}
|
||||
const longv = () => (state.long.count === undefined ? na() : `${time(state.long.block) ?? na()}/${state.long.count}`)
|
||||
const navv = () => (state.nav.pending ? "..." : (time(state.nav.dur) ?? na()))
|
||||
const toggleFocus = async () => {
|
||||
if (!platform.setForceFocus) return
|
||||
const enabled = !state.focus
|
||||
await platform.setForceFocus(enabled)
|
||||
setState("focus", enabled)
|
||||
}
|
||||
|
||||
onCleanup(() => {
|
||||
if (state.focus) void platform.setForceFocus?.(false).catch(() => undefined)
|
||||
})
|
||||
|
||||
let prev = ""
|
||||
let start = 0
|
||||
|
|
@ -490,8 +539,11 @@ export function DebugBar(props: { inline?: boolean } = {}) {
|
|||
bad={bad(heap(), 0.8)}
|
||||
dim={state.heap.used === undefined}
|
||||
inline={props.inline}
|
||||
wide
|
||||
wide={!platform.setForceFocus}
|
||||
/>
|
||||
{platform.setForceFocus && (
|
||||
<FocusCell active={state.focus} inline={props.inline} onClick={() => void toggleFocus()} />
|
||||
)}
|
||||
</div>
|
||||
</aside>
|
||||
)
|
||||
|
|
|
|||
|
|
@ -0,0 +1,73 @@
|
|||
// @ts-nocheck
|
||||
import { Button } from "@opencode-ai/ui/button"
|
||||
import { useDialog } from "@opencode-ai/ui/context/dialog"
|
||||
import { QueryClient, QueryClientProvider } from "@tanstack/solid-query"
|
||||
import { mockProviderAuth } from "@/context/server-sync"
|
||||
import { onCleanup, onMount } from "solid-js"
|
||||
import { DialogConnectProvider, useProviderConnectController } from "./dialog-connect-provider"
|
||||
|
||||
function ConnectProviderDialogStory() {
|
||||
const dialog = useDialog()
|
||||
const open = () => dialog.show(() => <DialogConnectProvider />)
|
||||
|
||||
onMount(open)
|
||||
|
||||
return (
|
||||
<Button variant="secondary" onClick={open}>
|
||||
Open connect provider dialog
|
||||
</Button>
|
||||
)
|
||||
}
|
||||
|
||||
function ProviderConnectionDialogStory(props) {
|
||||
onCleanup(mockProviderAuth(props.provider, props.methods))
|
||||
const dialog = useDialog()
|
||||
const controller = useProviderConnectController()
|
||||
controller.select(props.provider)
|
||||
const open = () => dialog.show(() => <DialogConnectProvider controller={controller} />)
|
||||
|
||||
onMount(open)
|
||||
|
||||
return (
|
||||
<Button variant="secondary" onClick={open}>
|
||||
Open {props.provider} connection dialog
|
||||
</Button>
|
||||
)
|
||||
}
|
||||
|
||||
function renderConnection(provider, methods) {
|
||||
return () => (
|
||||
<QueryClientProvider client={new QueryClient()}>
|
||||
<ProviderConnectionDialogStory provider={provider} methods={methods} />
|
||||
</QueryClientProvider>
|
||||
)
|
||||
}
|
||||
|
||||
export default {
|
||||
title: "App/Dialogs/Connect Provider",
|
||||
id: "app-dialog-connect-provider",
|
||||
}
|
||||
|
||||
export const V2 = {
|
||||
render: () => (
|
||||
<QueryClientProvider client={new QueryClient()}>
|
||||
<ConnectProviderDialogStory />
|
||||
</QueryClientProvider>
|
||||
),
|
||||
}
|
||||
|
||||
export const ApiKey = {
|
||||
render: renderConnection("openrouter", [{ type: "api", label: "API key" }]),
|
||||
}
|
||||
|
||||
export const OpenCodeZen = {
|
||||
render: renderConnection("opencode", [{ type: "api", label: "API key" }]),
|
||||
}
|
||||
|
||||
export const LoginMethods = {
|
||||
render: renderConnection("openai", [
|
||||
{ type: "oauth", label: "ChatGPT Pro/Plus (browser)" },
|
||||
{ type: "oauth", label: "ChatGPT Pro/Plus (headless)" },
|
||||
{ type: "api", label: "API key" },
|
||||
]),
|
||||
}
|
||||
|
|
@ -9,6 +9,9 @@ import { ProviderIcon } from "@opencode-ai/ui/provider-icon"
|
|||
import { Spinner } from "@opencode-ai/ui/spinner"
|
||||
import { Tag } from "@opencode-ai/ui/tag"
|
||||
import { TextField } from "@opencode-ai/ui/text-field"
|
||||
import { ButtonV2 } from "@opencode-ai/ui/v2/button-v2"
|
||||
import { DialogBody, DialogHeader, DialogTitle, DialogV2 } from "@opencode-ai/ui/v2/dialog-v2"
|
||||
import { TextInputV2 } from "@opencode-ai/ui/v2/text-input-v2"
|
||||
import { showToast } from "@/utils/toast"
|
||||
import {
|
||||
type Accessor,
|
||||
|
|
@ -16,6 +19,8 @@ import {
|
|||
createEffect,
|
||||
createMemo,
|
||||
createResource,
|
||||
createUniqueId,
|
||||
For,
|
||||
Match,
|
||||
onCleanup,
|
||||
onMount,
|
||||
|
|
@ -27,6 +32,7 @@ import { Link } from "@/components/link"
|
|||
import { useServerSDK } from "@/context/server-sdk"
|
||||
import { useServerSync } from "@/context/server-sync"
|
||||
import { useLanguage } from "@/context/language"
|
||||
import { useSettings } from "@/context/settings"
|
||||
import { popularProviders, useProviders } from "@/hooks/use-providers"
|
||||
import { CustomProviderForm } from "./dialog-custom-provider"
|
||||
|
||||
|
|
@ -50,32 +56,22 @@ export const DialogConnectProvider: Component<{
|
|||
const fallback = useProviderConnectController()
|
||||
const controller = props.controller ?? fallback
|
||||
const language = useLanguage()
|
||||
const settings = useSettings()
|
||||
const newLayout = settings.general.newLayoutDesigns
|
||||
const reset = controller.back
|
||||
const back = { current: reset }
|
||||
let focusHost: HTMLDivElement | undefined
|
||||
const holdFocus = () => focusHost?.focus({ preventScroll: true })
|
||||
const select = (provider?: string) => {
|
||||
back.current = reset
|
||||
controller.select(provider)
|
||||
}
|
||||
|
||||
return (
|
||||
<Dialog
|
||||
class="h-full"
|
||||
transition
|
||||
title={
|
||||
<Show when={controller.selected()} fallback={language.t("command.provider.connect")}>
|
||||
<IconButton
|
||||
tabIndex={-1}
|
||||
icon="arrow-left"
|
||||
variant="ghost"
|
||||
onClick={() => back.current()}
|
||||
aria-label={language.t("common.goBack")}
|
||||
/>
|
||||
</Show>
|
||||
}
|
||||
>
|
||||
function Content() {
|
||||
return (
|
||||
<Switch>
|
||||
<Match when={controller.selected() === CUSTOM_ID}>
|
||||
<CustomProviderForm />
|
||||
<CustomProviderForm autofocus={!newLayout()} />
|
||||
</Match>
|
||||
<Match when={controller.selected() && controller.selected() !== CUSTOM_ID ? controller.selected() : undefined}>
|
||||
{(provider) => (
|
||||
|
|
@ -88,14 +84,76 @@ export const DialogConnectProvider: Component<{
|
|||
)}
|
||||
</Match>
|
||||
<Match when={true}>
|
||||
<ProviderPicker directory={props.directory} onSelect={select} />
|
||||
<ProviderPicker
|
||||
directory={props.directory}
|
||||
onSelect={select}
|
||||
onPrepare={newLayout() ? holdFocus : undefined}
|
||||
/>
|
||||
</Match>
|
||||
</Switch>
|
||||
</Dialog>
|
||||
)
|
||||
}
|
||||
|
||||
return (
|
||||
<Show
|
||||
when={newLayout()}
|
||||
fallback={
|
||||
<Dialog
|
||||
class="h-full"
|
||||
transition
|
||||
title={
|
||||
<Show when={controller.selected()} fallback={language.t("command.provider.connect")}>
|
||||
<IconButton
|
||||
tabIndex={-1}
|
||||
icon="arrow-left"
|
||||
variant="ghost"
|
||||
onClick={() => back.current()}
|
||||
aria-label={language.t("common.goBack")}
|
||||
/>
|
||||
</Show>
|
||||
}
|
||||
>
|
||||
<Content />
|
||||
</Dialog>
|
||||
}
|
||||
>
|
||||
<DialogV2
|
||||
containerClass="!h-[min(calc(100vh_-_16px),512px)] !w-[min(calc(100vw_-_16px),640px)]"
|
||||
class="[font-family:var(--v2-font-family-sans)] [&_[data-slot=dialog-header]]:!px-5 [&_[data-slot=dialog-header-title]]:!text-[15px] [&_[data-slot=dialog-header-title]]:!tracking-[-0.13px]"
|
||||
>
|
||||
<DialogHeader closeLabel={language.t("common.close")}>
|
||||
<Show
|
||||
when={controller.selected()}
|
||||
fallback={<DialogTitle>{language.t("command.provider.connect")}</DialogTitle>}
|
||||
>
|
||||
<button
|
||||
type="button"
|
||||
class="flex size-5 items-center justify-center rounded-sm text-v2-icon-icon-muted hover:bg-v2-overlay-simple-overlay-hover focus-visible:bg-v2-overlay-simple-overlay-hover focus-visible:outline-none"
|
||||
onClick={() => back.current()}
|
||||
aria-label={language.t("common.goBack")}
|
||||
>
|
||||
<Icon name="arrow-left" size="small" />
|
||||
</button>
|
||||
</Show>
|
||||
</DialogHeader>
|
||||
<DialogBody class="min-h-0 flex-1 overflow-hidden px-2 pb-2">
|
||||
<div ref={focusHost} tabIndex={-1} class="flex min-h-0 flex-1 flex-col outline-none">
|
||||
<Content />
|
||||
</div>
|
||||
</DialogBody>
|
||||
</DialogV2>
|
||||
</Show>
|
||||
)
|
||||
}
|
||||
|
||||
function ProviderPicker(props: { directory?: Accessor<string | undefined>; onSelect: (provider: string) => void }) {
|
||||
function ProviderPicker(props: {
|
||||
directory?: Accessor<string | undefined>
|
||||
onSelect: (provider: string) => void
|
||||
onPrepare?: () => void
|
||||
}) {
|
||||
const settings = useSettings()
|
||||
if (settings.general.newLayoutDesigns())
|
||||
return <ProviderPickerV2 directory={props.directory} onSelect={props.onSelect} onPrepare={props.onPrepare} />
|
||||
const providers = useProviders(props.directory)
|
||||
const language = useLanguage()
|
||||
const popularGroup = () => language.t("dialog.provider.group.popular")
|
||||
|
|
@ -163,6 +221,171 @@ function ProviderPicker(props: { directory?: Accessor<string | undefined>; onSel
|
|||
)
|
||||
}
|
||||
|
||||
function ProviderPickerV2(props: {
|
||||
directory?: Accessor<string | undefined>
|
||||
onSelect: (provider: string) => void
|
||||
onPrepare?: () => void
|
||||
}) {
|
||||
const providers = useProviders(props.directory)
|
||||
const language = useLanguage()
|
||||
const serverSync = useServerSync()
|
||||
const serverSDK = useServerSDK()
|
||||
const [store, setStore] = createStore({
|
||||
filter: "",
|
||||
active: undefined as string | undefined,
|
||||
connecting: undefined as string | undefined,
|
||||
})
|
||||
const featured = ["opencode", "opencode-go", "anthropic", "openai", "google", "openrouter", "vercel"]
|
||||
const custom = () => ({ id: CUSTOM_ID, name: language.t("dialog.provider.custom.label") })
|
||||
const all = createMemo(() => {
|
||||
language.locale()
|
||||
const query = store.filter.trim().toLowerCase()
|
||||
const values = [custom(), ...providers.all().values()]
|
||||
if (!query) return values
|
||||
return values.filter((provider) => `${provider.id} ${provider.name}`.toLowerCase().includes(query))
|
||||
})
|
||||
const popular = createMemo(() =>
|
||||
all()
|
||||
.filter((provider) => featured.includes(provider.id))
|
||||
.sort((a, b) => featured.indexOf(a.id) - featured.indexOf(b.id)),
|
||||
)
|
||||
const other = createMemo(() =>
|
||||
all()
|
||||
.filter((provider) => !featured.includes(provider.id))
|
||||
.sort((a, b) => {
|
||||
if (a.id === CUSTOM_ID) return -1
|
||||
if (b.id === CUSTOM_ID) return 1
|
||||
return a.name.localeCompare(b.name)
|
||||
}),
|
||||
)
|
||||
const rows = createMemo(() => [...popular(), ...other()])
|
||||
let picker: HTMLDivElement | undefined
|
||||
let search: HTMLInputElement | undefined
|
||||
|
||||
onMount(() => search?.focus({ preventScroll: true }))
|
||||
|
||||
const connect = (provider: string) => {
|
||||
props.onPrepare?.()
|
||||
if (provider === CUSTOM_ID || serverSync().data.provider_auth[provider]) {
|
||||
props.onSelect(provider)
|
||||
return
|
||||
}
|
||||
if (store.connecting) return
|
||||
setStore("connecting", provider)
|
||||
void serverSDK()
|
||||
.client.provider.auth()
|
||||
.then((response) => {
|
||||
serverSync().set("provider_auth", response.data ?? {})
|
||||
props.onSelect(provider)
|
||||
})
|
||||
.catch(() => props.onSelect(provider))
|
||||
}
|
||||
|
||||
const move = (event: KeyboardEvent, direction: number) => {
|
||||
const items = rows()
|
||||
if (items.length === 0) return
|
||||
const index = items.findIndex((provider) => provider.id === store.active)
|
||||
const next = index < 0 ? (direction > 0 ? 0 : items.length - 1) : (index + direction + items.length) % items.length
|
||||
setStore("active", items[next].id)
|
||||
picker
|
||||
?.querySelector<HTMLElement>(`[data-provider-id="${CSS.escape(items[next].id)}"]`)
|
||||
?.focus({ preventScroll: true })
|
||||
event.preventDefault()
|
||||
}
|
||||
|
||||
const handleKeyDown = (event: KeyboardEvent) => {
|
||||
if (event.key === "ArrowDown") return move(event, 1)
|
||||
if (event.key === "ArrowUp") return move(event, -1)
|
||||
if (event.key !== "Enter" || !store.active) return
|
||||
connect(store.active)
|
||||
event.preventDefault()
|
||||
}
|
||||
|
||||
return (
|
||||
<div ref={picker} class="flex min-h-0 flex-1 flex-col gap-4" onKeyDown={handleKeyDown}>
|
||||
<div class="shrink-0 px-1 pt-px">
|
||||
<TextInputV2
|
||||
ref={search}
|
||||
type="search"
|
||||
class="!w-full [font-family:var(--v2-font-family-sans)]"
|
||||
leadingIcon={<Icon name="magnifying-glass" size="small" />}
|
||||
placeholder={language.t("dialog.provider.search.placeholder")}
|
||||
value={store.filter}
|
||||
onInput={(event) => {
|
||||
setStore({ filter: event.currentTarget.value, active: undefined })
|
||||
}}
|
||||
/>
|
||||
</div>
|
||||
<div class="relative min-h-0 flex-1">
|
||||
<div class="flex size-full min-h-0 flex-col gap-4 overflow-y-auto pb-8 [scrollbar-width:none] [&::-webkit-scrollbar]:hidden">
|
||||
<For
|
||||
each={[
|
||||
{ title: language.t("dialog.provider.group.popular"), items: popular },
|
||||
{ title: language.t("dialog.provider.group.other"), items: other },
|
||||
]}
|
||||
>
|
||||
{(group) => (
|
||||
<Show when={group.items().length > 0}>
|
||||
<section class="flex flex-col">
|
||||
<div class="px-3 pb-2 text-[13px] font-[440] leading-none tracking-[-0.04px] text-v2-text-text-muted">
|
||||
{group.title}
|
||||
</div>
|
||||
<For each={group.items()}>
|
||||
{(provider) => (
|
||||
<button
|
||||
type="button"
|
||||
data-provider-id={provider.id}
|
||||
class="flex min-h-9 w-full items-center gap-2 rounded-md px-3 py-2.5 text-left text-[13px] leading-none tracking-[-0.04px] hover:bg-v2-overlay-simple-overlay-hover focus:bg-v2-overlay-simple-overlay-hover focus:outline-none"
|
||||
classList={{ "bg-v2-overlay-simple-overlay-hover": store.active === provider.id }}
|
||||
onMouseEnter={() => setStore("active", provider.id)}
|
||||
disabled={store.connecting !== undefined}
|
||||
aria-busy={store.connecting === provider.id}
|
||||
onClick={() => connect(provider.id)}
|
||||
>
|
||||
<ProviderIcon id={provider.id} class="size-4 shrink-0 text-v2-icon-icon-base" />
|
||||
<span class="min-w-0 truncate font-[530] text-v2-text-text-base">{provider.name}</span>
|
||||
<Show when={provider.id === "opencode" || provider.id === "opencode-go"}>
|
||||
<span class="min-w-0 truncate font-[440] text-v2-text-text-muted">
|
||||
{language.t(
|
||||
provider.id === "opencode"
|
||||
? "dialog.provider.opencode.tagline"
|
||||
: "dialog.provider.opencodeGo.tagline",
|
||||
)}
|
||||
</span>
|
||||
<span class="flex h-4 shrink-0 items-center rounded-xs border-[0.5px] border-v2-border-border-base bg-v2-background-bg-layer-03 px-1 text-[11px] font-[530] leading-none tracking-[0.05px] text-v2-text-text-muted">
|
||||
{language.t("dialog.provider.tag.recommended")}
|
||||
</span>
|
||||
</Show>
|
||||
<Show when={provider.id === CUSTOM_ID}>
|
||||
<span class="flex h-4 shrink-0 items-center rounded-xs border-[0.5px] border-v2-border-border-base bg-v2-background-bg-layer-03 px-1 text-[11px] font-[530] leading-none tracking-[0.05px] text-v2-text-text-muted">
|
||||
{language.t("settings.providers.tag.custom")}
|
||||
</span>
|
||||
</Show>
|
||||
<Show when={store.connecting === provider.id}>
|
||||
<Spinner class="ml-auto size-4 shrink-0 text-v2-icon-icon-muted" />
|
||||
</Show>
|
||||
</button>
|
||||
)}
|
||||
</For>
|
||||
</section>
|
||||
</Show>
|
||||
)}
|
||||
</For>
|
||||
<Show when={rows().length === 0}>
|
||||
<div class="flex h-24 items-center justify-center text-[13px] font-[440] text-v2-text-text-muted">
|
||||
{language.t("dialog.provider.empty")}
|
||||
</div>
|
||||
</Show>
|
||||
</div>
|
||||
<div
|
||||
class="pointer-events-none absolute inset-x-0 bottom-0 h-10"
|
||||
style={{ background: "linear-gradient(to bottom, transparent, var(--v2-background-bg-layer-01))" }}
|
||||
/>
|
||||
</div>
|
||||
</div>
|
||||
)
|
||||
}
|
||||
|
||||
function ProviderConnection(props: {
|
||||
provider: string
|
||||
directory?: Accessor<string | undefined>
|
||||
|
|
@ -173,6 +396,8 @@ function ProviderConnection(props: {
|
|||
const serverSync = useServerSync()
|
||||
const serverSDK = useServerSDK()
|
||||
const language = useLanguage()
|
||||
const settings = useSettings()
|
||||
const newLayout = settings.general.newLayoutDesigns
|
||||
const providers = useProviders(props.directory)
|
||||
|
||||
const alive = { value: true }
|
||||
|
|
@ -207,11 +432,19 @@ function ProviderConnection(props: {
|
|||
)
|
||||
const loading = createMemo(() => auth.loading && !serverSync().data.provider_auth[props.provider])
|
||||
const methods = createMemo(() => auth.latest ?? serverSync().data.provider_auth[props.provider] ?? fallback())
|
||||
const cachedMethods = serverSync().data.provider_auth[props.provider]
|
||||
const directMethod =
|
||||
cachedMethods?.length === 1 && cachedMethods[0].type === "api" && !cachedMethods[0].prompts?.length ? 0 : undefined
|
||||
const [store, setStore] = createStore({
|
||||
methodIndex: undefined as undefined | number,
|
||||
methodIndex: directMethod as undefined | number,
|
||||
authorization: undefined as undefined | ProviderAuthAuthorization,
|
||||
promptInputs: undefined as undefined | Record<string, string>,
|
||||
state: "pending" as undefined | "pending" | "complete" | "error" | "prompt",
|
||||
state: (directMethod === undefined ? "pending" : undefined) as
|
||||
| undefined
|
||||
| "pending"
|
||||
| "complete"
|
||||
| "error"
|
||||
| "prompt",
|
||||
error: undefined as string | undefined,
|
||||
})
|
||||
|
||||
|
|
@ -279,6 +512,16 @@ function ProviderConnection(props: {
|
|||
return value.label ?? ""
|
||||
}
|
||||
|
||||
const methodDetails = (value?: { type?: string; label?: string }) => {
|
||||
const label = methodLabel(value)
|
||||
const suffix = value?.label?.match(/\s+\((browser|headless)\)$/i)
|
||||
const hint = suffix?.[1]
|
||||
return {
|
||||
label: suffix ? label.slice(0, -suffix[0].length) : label,
|
||||
hint: hint ? hint[0].toUpperCase() + hint.slice(1) : value?.type === "api" ? "Browser" : undefined,
|
||||
}
|
||||
}
|
||||
|
||||
function formatError(value: unknown, fallback: string): string {
|
||||
if (value && typeof value === "object" && "data" in value) {
|
||||
const data = (value as { data?: { message?: unknown } }).data
|
||||
|
|
@ -519,6 +762,37 @@ function ProviderConnection(props: {
|
|||
props.setBack(goBack)
|
||||
|
||||
function MethodSelection() {
|
||||
if (newLayout())
|
||||
return (
|
||||
<div class="flex flex-col gap-2">
|
||||
<div class="px-3 text-[13px] font-[440] leading-5 tracking-[-0.04px] text-v2-text-text-muted">
|
||||
{language.t("provider.connect.selectMethod", { provider: provider().name })}
|
||||
</div>
|
||||
<div class="flex flex-col">
|
||||
<For each={methods()}>
|
||||
{(item, index) => {
|
||||
const details = () => methodDetails(item)
|
||||
return (
|
||||
<button
|
||||
type="button"
|
||||
class="group flex h-9 w-full items-center gap-2 rounded-md px-3 text-left text-[13px] leading-5 tracking-[-0.04px] hover:bg-v2-overlay-simple-overlay-hover focus-visible:bg-v2-overlay-simple-overlay-hover focus-visible:outline-none"
|
||||
onClick={() => void selectMethod(index())}
|
||||
>
|
||||
<span class="flex h-2 w-4 shrink-0 items-center justify-center rounded-[1px] bg-v2-background-bg-base shadow-[var(--v2-elevation-button-neutral)]">
|
||||
<span class="hidden h-0.5 w-2.5 bg-v2-icon-icon-base group-hover:block group-focus-visible:block" />
|
||||
</span>
|
||||
<span class="font-[530] text-v2-text-text-base">{details().label}</span>
|
||||
<Show when={details().hint}>
|
||||
{(hint) => <span class="font-[440] text-v2-text-text-muted">{hint()}</span>}
|
||||
</Show>
|
||||
</button>
|
||||
)
|
||||
}}
|
||||
</For>
|
||||
</div>
|
||||
</div>
|
||||
)
|
||||
|
||||
return (
|
||||
<>
|
||||
<div class="text-14-regular text-text-base">
|
||||
|
|
@ -552,11 +826,18 @@ function ProviderConnection(props: {
|
|||
}
|
||||
|
||||
function ApiAuthView() {
|
||||
let apiKey: HTMLInputElement | undefined
|
||||
const errorID = createUniqueId()
|
||||
const [formStore, setFormStore] = createStore({
|
||||
value: "",
|
||||
error: undefined as string | undefined,
|
||||
})
|
||||
|
||||
onMount(() => {
|
||||
if (!newLayout()) return
|
||||
apiKey?.focus({ preventScroll: true })
|
||||
})
|
||||
|
||||
async function handleSubmit(e: SubmitEvent) {
|
||||
e.preventDefault()
|
||||
|
||||
|
|
@ -581,6 +862,58 @@ function ProviderConnection(props: {
|
|||
await complete()
|
||||
}
|
||||
|
||||
if (newLayout())
|
||||
return (
|
||||
<div class="flex flex-col gap-5 px-3 text-[13px] font-[440] leading-5 tracking-[-0.04px] text-v2-text-text-muted">
|
||||
<Show
|
||||
when={provider().id === "opencode"}
|
||||
fallback={language.t("provider.connect.apiKey.description", { provider: provider().name })}
|
||||
>
|
||||
<div class="flex flex-col gap-5">
|
||||
<div>{language.t("provider.connect.opencodeZen.line1")}</div>
|
||||
<div>{language.t("provider.connect.opencodeZen.line2")}</div>
|
||||
<div>
|
||||
{language.t("provider.connect.opencodeZen.visit.prefix")}
|
||||
<Link
|
||||
href="https://opencode.ai/zen"
|
||||
class="text-v2-text-text-base focus-visible:rounded-xs focus-visible:outline-2 focus-visible:outline-v2-border-border-focus"
|
||||
>
|
||||
{language.t("provider.connect.opencodeZen.visit.link")}
|
||||
</Link>
|
||||
{language.t("provider.connect.opencodeZen.visit.suffix")}
|
||||
</div>
|
||||
</div>
|
||||
</Show>
|
||||
<form onSubmit={handleSubmit} class="flex flex-col items-start gap-5 self-stretch">
|
||||
<label class="flex w-full flex-col gap-1 font-[530] leading-4 text-v2-text-text-base">
|
||||
{language.t("provider.connect.apiKey.label", { provider: provider().name })}
|
||||
<TextInputV2
|
||||
ref={apiKey}
|
||||
class="!w-full"
|
||||
name="apiKey"
|
||||
placeholder={language.t("provider.connect.apiKey.placeholder")}
|
||||
value={formStore.value}
|
||||
invalid={formStore.error !== undefined}
|
||||
aria-describedby={formStore.error ? errorID : undefined}
|
||||
autocomplete="off"
|
||||
spellcheck={false}
|
||||
onInput={(event) => setFormStore("value", event.currentTarget.value)}
|
||||
/>
|
||||
</label>
|
||||
<Show when={formStore.error}>
|
||||
{(error) => (
|
||||
<div id={errorID} role="alert" class="-mt-4 text-xs text-v2-state-fg-danger">
|
||||
{error()}
|
||||
</div>
|
||||
)}
|
||||
</Show>
|
||||
<ButtonV2 type="submit" variant="contrast">
|
||||
{language.t("common.continue")}
|
||||
</ButtonV2>
|
||||
</form>
|
||||
</div>
|
||||
)
|
||||
|
||||
return (
|
||||
<div class="flex flex-col gap-6">
|
||||
<Switch>
|
||||
|
|
@ -605,7 +938,8 @@ function ProviderConnection(props: {
|
|||
</Switch>
|
||||
<form onSubmit={handleSubmit} class="flex flex-col items-start gap-4">
|
||||
<TextField
|
||||
autofocus
|
||||
autofocus={!newLayout()}
|
||||
ref={apiKey}
|
||||
type="text"
|
||||
label={language.t("provider.connect.apiKey.label", { provider: provider().name })}
|
||||
placeholder={language.t("provider.connect.apiKey.placeholder")}
|
||||
|
|
@ -624,11 +958,18 @@ function ProviderConnection(props: {
|
|||
}
|
||||
|
||||
function OAuthCodeView() {
|
||||
let codeInput: HTMLInputElement | undefined
|
||||
const errorID = createUniqueId()
|
||||
const [formStore, setFormStore] = createStore({
|
||||
value: "",
|
||||
error: undefined as string | undefined,
|
||||
})
|
||||
|
||||
onMount(() => {
|
||||
if (!newLayout()) return
|
||||
codeInput?.focus({ preventScroll: true })
|
||||
})
|
||||
|
||||
async function handleSubmit(e: SubmitEvent) {
|
||||
e.preventDefault()
|
||||
|
||||
|
|
@ -657,6 +998,46 @@ function ProviderConnection(props: {
|
|||
setFormStore("error", formatError(result.error, language.t("provider.connect.oauth.code.invalid")))
|
||||
}
|
||||
|
||||
if (newLayout())
|
||||
return (
|
||||
<div class="flex flex-col gap-5 px-3 text-[13px] font-[440] leading-5 tracking-[-0.04px] text-v2-text-text-muted">
|
||||
<div>
|
||||
{language.t("provider.connect.oauth.code.visit.prefix")}
|
||||
<Link href={store.authorization!.url} class="text-v2-text-text-base">
|
||||
{language.t("provider.connect.oauth.code.visit.link")}
|
||||
</Link>
|
||||
{language.t("provider.connect.oauth.code.visit.suffix", { provider: provider().name })}
|
||||
</div>
|
||||
<form onSubmit={handleSubmit} class="flex flex-col items-start gap-5 self-stretch">
|
||||
<label class="flex w-full flex-col gap-1 font-[530] leading-4 text-v2-text-text-base">
|
||||
{language.t("provider.connect.oauth.code.label", { method: method()?.label ?? "" })}
|
||||
<TextInputV2
|
||||
ref={codeInput}
|
||||
class="!w-full"
|
||||
name="code"
|
||||
placeholder={language.t("provider.connect.oauth.code.placeholder")}
|
||||
value={formStore.value}
|
||||
invalid={formStore.error !== undefined}
|
||||
aria-describedby={formStore.error ? errorID : undefined}
|
||||
autocomplete="off"
|
||||
spellcheck={false}
|
||||
onInput={(event) => setFormStore("value", event.currentTarget.value)}
|
||||
/>
|
||||
</label>
|
||||
<Show when={formStore.error}>
|
||||
{(error) => (
|
||||
<div id={errorID} role="alert" class="-mt-4 text-xs text-v2-state-fg-danger">
|
||||
{error()}
|
||||
</div>
|
||||
)}
|
||||
</Show>
|
||||
<ButtonV2 type="submit" variant="contrast">
|
||||
{language.t("common.continue")}
|
||||
</ButtonV2>
|
||||
</form>
|
||||
</div>
|
||||
)
|
||||
|
||||
return (
|
||||
<div class="flex flex-col gap-6">
|
||||
<div class="text-14-regular text-text-base">
|
||||
|
|
@ -666,7 +1047,8 @@ function ProviderConnection(props: {
|
|||
</div>
|
||||
<form onSubmit={handleSubmit} class="flex flex-col items-start gap-4">
|
||||
<TextField
|
||||
autofocus
|
||||
autofocus={!newLayout()}
|
||||
ref={codeInput}
|
||||
type="text"
|
||||
label={language.t("provider.connect.oauth.code.label", { method: method()?.label ?? "" })}
|
||||
placeholder={language.t("provider.connect.oauth.code.placeholder")}
|
||||
|
|
@ -738,10 +1120,19 @@ function ProviderConnection(props: {
|
|||
}
|
||||
|
||||
return (
|
||||
<div class="flex flex-col gap-6 px-2.5 pb-3">
|
||||
<div class="px-2.5 flex gap-4 items-center">
|
||||
<ProviderIcon id={props.provider} class="size-5 shrink-0 icon-strong-base" />
|
||||
<div class="text-16-medium text-text-strong">
|
||||
<div class={newLayout() ? "flex min-h-0 flex-1 flex-col" : "flex flex-col gap-6 px-2.5 pb-3"}>
|
||||
<div class={newLayout() ? "flex h-10 shrink-0 items-start gap-2 px-3" : "flex items-center gap-4 px-2.5"}>
|
||||
<ProviderIcon
|
||||
id={props.provider}
|
||||
class={newLayout() ? "mt-0.5 size-4 shrink-0 text-v2-icon-icon-base" : "size-5 shrink-0 icon-strong-base"}
|
||||
/>
|
||||
<div
|
||||
class={
|
||||
newLayout()
|
||||
? "text-[15px] font-[530] leading-5 tracking-[-0.13px] text-v2-text-text-base"
|
||||
: "text-16-medium text-text-strong"
|
||||
}
|
||||
>
|
||||
<Switch>
|
||||
<Match when={props.provider === "anthropic" && method()?.label?.toLowerCase().includes("max")}>
|
||||
{language.t("provider.connect.title.anthropicProMax")}
|
||||
|
|
@ -750,8 +1141,12 @@ function ProviderConnection(props: {
|
|||
</Switch>
|
||||
</div>
|
||||
</div>
|
||||
<div class="px-2.5 pb-10 flex flex-col gap-6">
|
||||
<div onKeyDown={handleKey} tabIndex={0} autofocus={store.methodIndex === undefined ? true : undefined}>
|
||||
<div class={newLayout() ? "flex min-h-0 flex-1 flex-col" : "flex flex-col gap-6 px-2.5 pb-10"}>
|
||||
<div
|
||||
onKeyDown={handleKey}
|
||||
tabIndex={newLayout() ? undefined : 0}
|
||||
autofocus={!newLayout() && store.methodIndex === undefined ? true : undefined}
|
||||
>
|
||||
<Switch>
|
||||
<Match when={loading()}>
|
||||
<div class="text-14-regular text-text-base">
|
||||
|
|
|
|||
|
|
@ -40,7 +40,7 @@ export function DialogCustomProvider(props: Props) {
|
|||
)
|
||||
}
|
||||
|
||||
export function CustomProviderForm() {
|
||||
export function CustomProviderForm(props: { autofocus?: boolean } = {}) {
|
||||
const dialog = useDialog()
|
||||
const serverSync = useServerSync()
|
||||
const serverSDK = useServerSDK()
|
||||
|
|
@ -192,7 +192,7 @@ export function CustomProviderForm() {
|
|||
|
||||
<div class="flex flex-col gap-4">
|
||||
<TextField
|
||||
autofocus
|
||||
autofocus={props.autofocus ?? true}
|
||||
label={language.t("provider.custom.field.providerID.label")}
|
||||
placeholder={language.t("provider.custom.field.providerID.placeholder")}
|
||||
description={language.t("provider.custom.field.providerID.description")}
|
||||
|
|
|
|||
|
|
@ -0,0 +1,55 @@
|
|||
// @ts-nocheck
|
||||
import { Button } from "@opencode-ai/ui/button"
|
||||
import { useDialog } from "@opencode-ai/ui/context/dialog"
|
||||
import { createSignal, onMount } from "solid-js"
|
||||
import { DialogSelectModelUnpaidV2 } from "./dialog-select-model-unpaid-v2"
|
||||
|
||||
const names = [
|
||||
"MiMo V2.5 Free",
|
||||
"Nemotron 3 Ultra Free",
|
||||
"Deepseek V4 Flash Free",
|
||||
"North Mini Code Free",
|
||||
"Hy3 Free",
|
||||
"Big Pickle",
|
||||
]
|
||||
|
||||
function SelectModelWithoutProviders() {
|
||||
const dialog = useDialog()
|
||||
const models = names.map((name, index) => ({
|
||||
id: name.toLowerCase().replaceAll(" ", "-"),
|
||||
name,
|
||||
provider: { id: "opencode", name: "OpenCode" },
|
||||
cost: { input: 0, output: 0 },
|
||||
limit: { context: 128_000 },
|
||||
capabilities: {
|
||||
reasoning: index !== 5,
|
||||
input: { text: true, image: false, audio: false, video: false, pdf: false },
|
||||
},
|
||||
}))
|
||||
const [current, setCurrent] = createSignal(models[2])
|
||||
const model = {
|
||||
list: () => models,
|
||||
current,
|
||||
set(value) {
|
||||
setCurrent(models.find((item) => item.id === value?.modelID))
|
||||
},
|
||||
}
|
||||
const open = () => dialog.show(() => <DialogSelectModelUnpaidV2 model={model} />)
|
||||
|
||||
onMount(open)
|
||||
|
||||
return (
|
||||
<Button variant="secondary" onClick={open}>
|
||||
Open select model dialog
|
||||
</Button>
|
||||
)
|
||||
}
|
||||
|
||||
export default {
|
||||
title: "App/Dialogs/Select Model",
|
||||
id: "app-dialog-select-model",
|
||||
}
|
||||
|
||||
export const WithoutProviders = {
|
||||
render: () => <SelectModelWithoutProviders />,
|
||||
}
|
||||
|
|
@ -1,23 +1,26 @@
|
|||
import { DialogBody, DialogHeader, DialogTitle, DialogV2 } from "@opencode-ai/ui/v2/dialog-v2"
|
||||
import { Icon } from "@opencode-ai/ui/v2/icon"
|
||||
import { ProviderIcon } from "@opencode-ai/ui/provider-icon"
|
||||
import { ScrollView } from "@opencode-ai/ui/scroll-view"
|
||||
import { Tag } from "@opencode-ai/ui/v2/badge-v2"
|
||||
import { TooltipV2 } from "@opencode-ai/ui/v2/tooltip-v2"
|
||||
import { useDialog } from "@opencode-ai/ui/context/dialog"
|
||||
import { useTheme } from "@opencode-ai/ui/theme"
|
||||
import { createMemo, onCleanup, onMount, type Component, For, Show } from "solid-js"
|
||||
import { useLocal } from "@/context/local"
|
||||
import { popularProviders, useProviders } from "@/hooks/use-providers"
|
||||
import { useProviders } from "@/hooks/use-providers"
|
||||
import { decode64 } from "@/utils/base64"
|
||||
import { useLanguage } from "@/context/language"
|
||||
import { ModelTooltip } from "./model-tooltip"
|
||||
|
||||
type ModelState = ReturnType<typeof useLocal>["model"]
|
||||
const featuredProviders = ["opencode", "opencode-go", "openai", "anthropic", "google", "github-copilot"]
|
||||
const displayModelName = (name: string) => name.replace(/\s+(?:\(free\)|free)$/i, "")
|
||||
|
||||
export const DialogSelectModelUnpaidV2: Component<{ model?: ModelState }> = (props) => {
|
||||
const local = useLocal()
|
||||
const model = props.model ?? local.model
|
||||
const dialog = useDialog()
|
||||
const theme = useTheme()
|
||||
const directory = () => decode64(local.slug())
|
||||
const providers = useProviders(directory)
|
||||
const language = useLanguage()
|
||||
|
|
@ -28,6 +31,7 @@ export const DialogSelectModelUnpaidV2: Component<{ model?: ModelState }> = (pro
|
|||
})
|
||||
const isFree = (item: ReturnType<ModelState["list"]>[number]) =>
|
||||
item.provider.id === "opencode" && (!item.cost || item.cost.input === 0)
|
||||
const freeModels = createMemo(() => model.list().filter(isFree))
|
||||
|
||||
const openProviders = (provider?: string) => {
|
||||
void import("./dialog-connect-provider").then((x) => {
|
||||
|
|
@ -62,111 +66,109 @@ export const DialogSelectModelUnpaidV2: Component<{ model?: ModelState }> = (pro
|
|||
})
|
||||
|
||||
return (
|
||||
<DialogV2 containerClass="!h-[min(calc(100vh_-_16px),480px)] !w-[min(calc(100vw_-_16px),560px)]">
|
||||
<DialogV2
|
||||
fit
|
||||
containerClass="!h-auto max-h-[calc(100vh_-_16px)] !w-[min(calc(100vw_-_16px),640px)]"
|
||||
class="[font-family:var(--v2-font-family-sans)] [&_[data-slot=dialog-header]]:!px-5 [&_[data-slot=dialog-header-title]]:!text-[15px] [&_[data-slot=dialog-header-title]]:!tracking-[-0.13px]"
|
||||
>
|
||||
<DialogHeader closeLabel={language.t("common.close")}>
|
||||
<DialogTitle>{language.t("dialog.model.select.title")}</DialogTitle>
|
||||
</DialogHeader>
|
||||
<div class="h-px w-full shrink-0 bg-v2-border-border-muted" />
|
||||
<DialogBody class="min-h-0 flex-1 gap-0">
|
||||
<ScrollView class="min-h-0 flex-1 w-full">
|
||||
<div ref={listEl} class="flex min-h-full flex-col">
|
||||
<div class="flex h-fit w-full flex-col items-start gap-0.5 px-3.5 pb-3.5 pt-3">
|
||||
<div class="flex h-8 w-full flex-none select-none flex-row items-center gap-2 self-stretch px-2.5 pb-2 pt-1">
|
||||
<div class="flex h-5 flex-none flex-row items-center p-0 font-[440] text-[13px] leading-5 tracking-[-0.04px] text-v2-text-text-faint [font-family:Inter,var(--font-family-sans)] [font-variant-numeric:tabular-nums] [font-variation-settings:'slnt'_0]">
|
||||
{language.t("dialog.model.unpaid.freeModels.title")}
|
||||
</div>
|
||||
<DialogBody class="max-h-[calc(100vh_-_68px)] min-h-0 flex-none gap-0 overflow-y-auto px-2 pb-2">
|
||||
<div ref={listEl} class="flex min-h-0 flex-col">
|
||||
<div class="flex w-full flex-col items-start pb-3">
|
||||
<div class="flex h-8 w-full flex-none select-none flex-row items-center px-3 pb-2">
|
||||
<div class="flex h-5 items-center text-[13px] font-[440] leading-5 tracking-[-0.04px] text-v2-text-text-muted [font-family:var(--v2-font-family-sans)] [font-variant-numeric:tabular-nums] [font-variation-settings:'slnt'_0]">
|
||||
{language.t("dialog.model.unpaid.freeModels.title")}
|
||||
</div>
|
||||
<For each={model.list()}>
|
||||
{(item) => (
|
||||
<TooltipV2
|
||||
class="w-full"
|
||||
placement="right-start"
|
||||
gutter={6}
|
||||
openDelay={0}
|
||||
value={<ModelTooltip model={item} latest={item.latest} free={isFree(item)} v2 />}
|
||||
>
|
||||
<button
|
||||
type="button"
|
||||
class="flex w-full scroll-my-3.5 flex-row items-center gap-2 rounded-md px-2.5 py-2 text-left text-[13px] font-[530] leading-5 tracking-[-0.04px] text-v2-text-text-base [font-family:Inter,var(--font-family-sans)] [font-variation-settings:'slnt'_0] hover:bg-v2-overlay-simple-overlay-hover focus:bg-v2-overlay-simple-overlay-hover focus:outline-none"
|
||||
onClick={() => selectModel(item)}
|
||||
>
|
||||
<span class="min-w-0 truncate">{item.name}</span>
|
||||
<Show when={isFree(item)}>
|
||||
<Tag class="shrink-0">{language.t("model.tag.free")}</Tag>
|
||||
</Show>
|
||||
<Show when={item.latest}>
|
||||
<Tag class="shrink-0">{language.t("model.tag.latest")}</Tag>
|
||||
</Show>
|
||||
<Show when={currentKey() === modelKey(item)}>
|
||||
<Icon name="check" class="ml-auto size-4 shrink-0 text-v2-icon-icon-base" />
|
||||
</Show>
|
||||
</button>
|
||||
</TooltipV2>
|
||||
)}
|
||||
</For>
|
||||
</div>
|
||||
|
||||
<div class="flex w-full flex-col p-2.5 pt-0">
|
||||
<div class="flex h-fit w-full flex-none grow-0 flex-col items-start gap-0.5 self-stretch rounded-lg bg-v2-background-bg-layer-02 p-1 shadow-[var(--v2-elevation-switch-off)]">
|
||||
<div class="flex h-8 w-full flex-none select-none flex-row items-center gap-2 self-stretch px-2.5 py-1.5">
|
||||
<div class="flex h-5 flex-none flex-row items-center p-0 text-[13px] font-[440] leading-5 tracking-[-0.04px] text-v2-text-text-faint [font-family:Inter,var(--font-family-sans)] [font-variant-numeric:tabular-nums] [font-variation-settings:'slnt'_0]">
|
||||
{language.t("dialog.model.unpaid.addMore.title")}
|
||||
</div>
|
||||
</div>
|
||||
<div class="flex w-full flex-col">
|
||||
<For
|
||||
each={[...providers.popular()].sort((a, b) => {
|
||||
if (popularProviders.includes(a.id) && popularProviders.includes(b.id)) {
|
||||
return popularProviders.indexOf(a.id) - popularProviders.indexOf(b.id)
|
||||
}
|
||||
return a.name.localeCompare(b.name)
|
||||
})}
|
||||
>
|
||||
{(provider) => (
|
||||
<button
|
||||
type="button"
|
||||
class="flex w-full scroll-my-3.5 flex-row items-center gap-2 rounded-[6px] px-2.5 py-2 text-left text-[13px] font-[530] leading-5 tracking-[-0.04px] text-v2-text-text-base [font-family:Inter,var(--font-family-sans)] [font-variation-settings:'slnt'_0] hover:bg-v2-overlay-simple-overlay-hover focus:bg-v2-overlay-simple-overlay-hover focus:outline-none"
|
||||
onClick={() => openProviders(provider.id)}
|
||||
>
|
||||
<ProviderIcon id={provider.id} class="size-4 shrink-0 text-v2-icon-icon-muted" />
|
||||
<span class="min-w-0 truncate">{provider.name}</span>
|
||||
<Show when={provider.id === "opencode"}>
|
||||
<span class="min-w-0 truncate text-[13px] font-[440] leading-5 tracking-[-0.04px] text-v2-text-text-muted [font-family:Inter,var(--font-family-sans)] [font-variation-settings:'slnt'_0]">
|
||||
{language.t("dialog.provider.opencode.tagline")}
|
||||
</span>
|
||||
<Tag class="shrink-0">{language.t("dialog.provider.tag.recommended")}</Tag>
|
||||
</Show>
|
||||
<Show when={provider.id === "opencode-go"}>
|
||||
<span class="min-w-0 truncate text-[13px] font-[440] leading-5 tracking-[-0.04px] text-v2-text-text-muted [font-family:Inter,var(--font-family-sans)] [font-variation-settings:'slnt'_0]">
|
||||
{language.t("dialog.provider.opencodeGo.tagline")}
|
||||
</span>
|
||||
<Tag class="shrink-0">{language.t("dialog.provider.tag.recommended")}</Tag>
|
||||
</Show>
|
||||
<Show when={provider.id === "anthropic"}>
|
||||
<span class="min-w-0 truncate text-[13px] font-[440] leading-5 tracking-[-0.04px] text-v2-text-text-muted [font-family:Inter,var(--font-family-sans)] [font-variation-settings:'slnt'_0]">
|
||||
{language.t("dialog.provider.anthropic.note")}
|
||||
</span>
|
||||
</Show>
|
||||
</button>
|
||||
)}
|
||||
</For>
|
||||
<For each={freeModels()}>
|
||||
{(item) => (
|
||||
<TooltipV2
|
||||
class="w-full"
|
||||
placement="right-start"
|
||||
gutter={6}
|
||||
openDelay={0}
|
||||
contentStyle={{ "font-family": "var(--v2-font-family-sans)" }}
|
||||
value={
|
||||
<ModelTooltip
|
||||
model={{ ...item, name: displayModelName(item.name) }}
|
||||
latest={item.latest}
|
||||
free={isFree(item)}
|
||||
v2
|
||||
/>
|
||||
}
|
||||
>
|
||||
<button
|
||||
type="button"
|
||||
class="flex h-9 w-full scroll-my-3.5 flex-row items-center justify-start gap-2 rounded-[6px] px-2.5 py-2 text-left text-[13px] font-[530] leading-5 tracking-[-0.04px] text-v2-text-text-base [font-family:Inter,var(--font-family-sans)] [font-variation-settings:'slnt'_0] hover:bg-v2-overlay-simple-overlay-hover focus:bg-v2-overlay-simple-overlay-hover focus:outline-none"
|
||||
onClick={() => openProviders()}
|
||||
class="flex w-full scroll-my-3.5 flex-row items-center gap-1.5 rounded-md px-3 py-2 text-left text-[13px] font-[530] leading-5 tracking-[-0.04px] text-v2-text-text-base [font-family:var(--v2-font-family-sans)] [font-variation-settings:'slnt'_0] hover:bg-v2-overlay-simple-overlay-hover focus:bg-v2-overlay-simple-overlay-hover focus:outline-none"
|
||||
onClick={() => selectModel(item)}
|
||||
>
|
||||
<span class="flex size-4 shrink-0 items-center justify-center text-v2-icon-icon-muted">
|
||||
<Icon name="dot-grid" size="small" />
|
||||
</span>
|
||||
<span class="min-w-0 truncate text-left text-[13px] font-[530] leading-5 tracking-[-0.04px] text-v2-text-text-base [font-family:Inter,var(--font-family-sans)] [font-variation-settings:'slnt'_0]">
|
||||
{language.t("dialog.provider.viewAll")}
|
||||
</span>
|
||||
<span class="min-w-0 truncate">{displayModelName(item.name)}</span>
|
||||
<Tag class="shrink-0">{language.t("model.tag.free")}</Tag>
|
||||
<Show when={item.latest}>
|
||||
<Tag class="shrink-0">{language.t("model.tag.latest")}</Tag>
|
||||
</Show>
|
||||
<Show when={currentKey() === modelKey(item)}>
|
||||
<Icon name="check" class="ml-auto size-4 shrink-0 text-v2-icon-icon-base" />
|
||||
</Show>
|
||||
</button>
|
||||
</TooltipV2>
|
||||
)}
|
||||
</For>
|
||||
</div>
|
||||
|
||||
<div class="flex w-full flex-col">
|
||||
<div class="flex w-full flex-col items-start rounded-lg border-[0.5px] border-v2-border-border-muted bg-v2-background-bg-layer-02 p-2.5 pt-2">
|
||||
<div class="flex h-8 w-full select-none items-center px-0.5 pb-2">
|
||||
<div class="flex h-5 items-center text-[13px] font-[440] leading-5 tracking-[-0.04px] text-v2-text-text-muted [font-family:var(--v2-font-family-sans)] [font-variant-numeric:tabular-nums] [font-variation-settings:'slnt'_0]">
|
||||
{language.t("dialog.model.unpaid.addMore.title")}
|
||||
</div>
|
||||
</div>
|
||||
<div class="grid w-full grid-cols-1 gap-y-1.5 gap-x-2 sm:grid-cols-2">
|
||||
<For
|
||||
each={[...providers.popular()]
|
||||
.filter((provider) => featuredProviders.includes(provider.id))
|
||||
.sort((a, b) => featuredProviders.indexOf(a.id) - featuredProviders.indexOf(b.id))}
|
||||
>
|
||||
{(provider) => (
|
||||
<button
|
||||
type="button"
|
||||
class="flex min-h-11 w-full scroll-my-3.5 flex-row items-start gap-2 rounded-md bg-v2-background-bg-base px-3 py-2.5 text-left text-[13px] font-[530] leading-5 tracking-[-0.04px] text-v2-text-text-base [font-family:var(--v2-font-family-sans)] [font-variation-settings:'slnt'_0] hover:bg-v2-background-bg-layer-01 focus:bg-v2-background-bg-layer-01 focus:outline-none"
|
||||
classList={{
|
||||
"border-[0.5px] border-transparent shadow-[var(--v2-elevation-raised)]":
|
||||
theme.mode() !== "dark",
|
||||
"border-[0.5px] border-v2-border-border-strong": theme.mode() === "dark",
|
||||
}}
|
||||
onClick={() => openProviders(provider.id)}
|
||||
>
|
||||
<ProviderIcon id={provider.id} class="mt-0.5 size-4 shrink-0 text-v2-icon-icon-base" />
|
||||
<span class="flex min-w-0 flex-col">
|
||||
<span class="truncate">{provider.name}</span>
|
||||
<Show when={provider.id === "opencode" || provider.id === "opencode-go"}>
|
||||
<span class="truncate font-[440] text-v2-text-text-muted">
|
||||
{language.t(
|
||||
provider.id === "opencode"
|
||||
? "dialog.provider.opencode.tagline"
|
||||
: "dialog.provider.opencodeGo.tagline",
|
||||
)}
|
||||
</span>
|
||||
</Show>
|
||||
</span>
|
||||
</button>
|
||||
)}
|
||||
</For>
|
||||
<button
|
||||
type="button"
|
||||
class="col-span-full flex h-8 w-full scroll-my-3.5 items-center justify-start rounded-md px-3 text-left text-[13px] font-[440] leading-5 tracking-[-0.04px] text-v2-text-text-muted [font-family:var(--v2-font-family-sans)] [font-variation-settings:'slnt'_0] hover:bg-v2-overlay-simple-overlay-hover focus:bg-v2-overlay-simple-overlay-hover focus:outline-none"
|
||||
onClick={() => openProviders()}
|
||||
>
|
||||
{language.t("dialog.model.unpaid.viewMoreProviders")}
|
||||
</button>
|
||||
</div>
|
||||
</div>
|
||||
</div>
|
||||
</ScrollView>
|
||||
</div>
|
||||
</DialogBody>
|
||||
</DialogV2>
|
||||
)
|
||||
|
|
|
|||
|
|
@ -16,6 +16,7 @@ export function TabsInfoPopup() {
|
|||
const settings = useSettings()
|
||||
const platform = usePlatform()
|
||||
const [drawerOpen, setDrawerOpen] = createSignal(false)
|
||||
const windows = () => platform.platform === "desktop" && platform.os === "windows"
|
||||
|
||||
return (
|
||||
<Drawer open={drawerOpen()} onOpenChange={setDrawerOpen} side="right">
|
||||
|
|
@ -70,12 +71,40 @@ export function TabsInfoPopup() {
|
|||
</button>
|
||||
</div>
|
||||
</Show>
|
||||
<DrawerContent>
|
||||
<div class="flex h-[52px] w-full shrink-0 items-center gap-4 self-stretch border-b border-v2-border-border-muted p-4">
|
||||
<DrawerContent
|
||||
style={
|
||||
windows()
|
||||
? {
|
||||
inset: "0 0 0 auto",
|
||||
"max-height": "100vh",
|
||||
"max-width": "100vw",
|
||||
"border-radius": "0",
|
||||
}
|
||||
: undefined
|
||||
}
|
||||
>
|
||||
<Show when={windows()}>
|
||||
<DrawerClose
|
||||
as={IconButtonV2}
|
||||
type="button"
|
||||
size="small"
|
||||
variant="neutral"
|
||||
aria-label="Close"
|
||||
icon={<IconV2 name="xmark-small" />}
|
||||
class="absolute top-[10px] left-[-36px]"
|
||||
/>
|
||||
</Show>
|
||||
<div
|
||||
class="flex w-full shrink-0 items-center gap-4 self-stretch border-b border-v2-border-border-muted"
|
||||
classList={{
|
||||
"h-[40px] px-4": windows(),
|
||||
"h-[52px] p-4": !windows(),
|
||||
}}
|
||||
>
|
||||
<p class="min-h-0 min-w-0 flex-1 text-[13px] font-[530] leading-5 tracking-[-0.04px] tabular-nums text-v2-text-text-muted">
|
||||
July 14
|
||||
</p>
|
||||
<Show when={platform.platform !== "desktop" || platform.os !== "windows"}>
|
||||
<Show when={!windows()}>
|
||||
<DrawerClose
|
||||
as={IconButtonV2}
|
||||
type="button"
|
||||
|
|
|
|||
591
packages/app/src/components/prompt-input-v2.tsx
Normal file
591
packages/app/src/components/prompt-input-v2.tsx
Normal file
|
|
@ -0,0 +1,591 @@
|
|||
import { ImagePreview } from "@opencode-ai/ui/image-preview"
|
||||
import { useDialog } from "@opencode-ai/ui/context/dialog"
|
||||
import { ProviderIcon } from "@opencode-ai/ui/provider-icon"
|
||||
import { ButtonV2 } from "@opencode-ai/ui/v2/button-v2"
|
||||
import { Icon } from "@opencode-ai/ui/v2/icon"
|
||||
import { KeybindV2 } from "@opencode-ai/ui/v2/keybind-v2"
|
||||
import { TooltipV2 } from "@opencode-ai/ui/v2/tooltip-v2"
|
||||
import type { ReferenceInfo } from "@opencode-ai/sdk/v2/client"
|
||||
import { createEffect, createMemo, on, Show } from "solid-js"
|
||||
import { ModelSelectorPopoverV2 } from "@/components/dialog-select-model"
|
||||
import { DialogSelectModelUnpaidV2 } from "@/components/dialog-select-model-unpaid-v2"
|
||||
import type { PromptInputProps } from "@/components/prompt-input/contracts"
|
||||
import { normalizePromptHistoryEntry, promptLength, type PromptHistoryComment } from "@/components/prompt-input/history"
|
||||
import { createPersistedPromptInputHistory } from "@/components/prompt-input/history-store"
|
||||
import { promptDesignPlaceholder, promptPlaceholder } from "@/components/prompt-input/placeholder"
|
||||
import { createPromptSubmit } from "@/components/prompt-input/submit"
|
||||
import { selectionFromLines, type SelectedLineRange, useFile } from "@/context/file"
|
||||
import { useComments } from "@/context/comments"
|
||||
import { useCommand } from "@/context/command"
|
||||
import { useLanguage } from "@/context/language"
|
||||
import { useLayout } from "@/context/layout"
|
||||
import { usePermission } from "@/context/permission"
|
||||
import { type ImageAttachmentPart, usePrompt } from "@/context/prompt"
|
||||
import { usePlatform } from "@/context/platform"
|
||||
import { useSDK } from "@/context/sdk"
|
||||
import { useSync } from "@/context/sync"
|
||||
import { createSessionTabs } from "@/pages/session/helpers"
|
||||
import { showToast } from "@/utils/toast"
|
||||
import { PromptInputV2, type PromptInputV2Suggestion } from "@opencode-ai/session-ui/v2/prompt-input"
|
||||
import {
|
||||
createPromptInputV2Controller,
|
||||
createPromptInputV2State,
|
||||
type PromptInputV2Interaction,
|
||||
} from "@opencode-ai/session-ui/v2/prompt-input/interaction"
|
||||
|
||||
export type PromptInputV2ComposerProps = {
|
||||
class?: string
|
||||
controller: PromptInputV2ComposerController
|
||||
borderUnderlay?: boolean
|
||||
edit?: PromptInputProps["edit"]
|
||||
onEditLoaded?: PromptInputProps["onEditLoaded"]
|
||||
}
|
||||
|
||||
export type PromptInputV2ControllerProps = Omit<PromptInputProps, "class" | "edit" | "onEditLoaded" | "submission">
|
||||
export type PromptInputV2ComposerController = PromptInputV2Interaction & {
|
||||
readonly model: PromptInputProps["controls"]["model"]
|
||||
}
|
||||
|
||||
export function PromptInputV2Composer(props: PromptInputV2ComposerProps) {
|
||||
const dialog = useDialog()
|
||||
const command = useCommand()
|
||||
const language = useLanguage()
|
||||
|
||||
useCommands(props)
|
||||
useEditHandler(props)
|
||||
|
||||
return (
|
||||
<div class="flex flex-col gap-3">
|
||||
<PromptInputV2
|
||||
controller={props.controller}
|
||||
borderUnderlay={props.borderUnderlay}
|
||||
class={props.class}
|
||||
attachKeybind={command.keybindParts("file.attach")}
|
||||
attachShortcut={command.keybind("file.attach")}
|
||||
modelControl={
|
||||
<PromptInputV2ModelControl
|
||||
loading={props.controller.model.loading}
|
||||
paid={props.controller.model.paid}
|
||||
title={language.t("command.model.choose")}
|
||||
keybind={command.keybindParts("model.choose")}
|
||||
model={props.controller.model.selection}
|
||||
providerID={props.controller.model.selection.current()?.provider?.id}
|
||||
modelName={props.controller.model.selection.current()?.name ?? language.t("dialog.model.select.title")}
|
||||
onClose={props.controller.restoreFocus}
|
||||
onUnpaidClick={() =>
|
||||
dialog.show(() => <DialogSelectModelUnpaidV2 model={props.controller.model.selection} />)
|
||||
}
|
||||
/>
|
||||
}
|
||||
/>
|
||||
</div>
|
||||
)
|
||||
}
|
||||
|
||||
const useEditHandler = (props: PromptInputV2ComposerProps) => {
|
||||
const prompt = usePrompt()
|
||||
|
||||
createEffect(
|
||||
on(
|
||||
() => props.edit?.id,
|
||||
(id) => {
|
||||
const edit = props.edit
|
||||
if (!id || !edit) return
|
||||
prompt.context.items().forEach((item) => prompt.context.remove(item.key))
|
||||
edit.context.forEach((item) =>
|
||||
prompt.context.add({
|
||||
type: item.type,
|
||||
path: item.path,
|
||||
selection: item.selection,
|
||||
comment: item.comment,
|
||||
commentID: item.commentID,
|
||||
commentOrigin: item.commentOrigin,
|
||||
preview: item.preview,
|
||||
}),
|
||||
)
|
||||
props.controller.dispatch({ type: "mode.normal" })
|
||||
props.controller.resetHistory()
|
||||
prompt.set(edit.prompt, promptLength(edit.prompt))
|
||||
props.controller.restoreFocus()
|
||||
props.onEditLoaded?.()
|
||||
},
|
||||
{ defer: true },
|
||||
),
|
||||
)
|
||||
}
|
||||
|
||||
const useCommands = (props: PromptInputV2ComposerProps) => {
|
||||
const command = useCommand()
|
||||
const language = useLanguage()
|
||||
|
||||
command.register("prompt-input", () => [
|
||||
{
|
||||
id: "file.attach",
|
||||
title: language.t("prompt.action.attachFile"),
|
||||
category: language.t("command.category.file"),
|
||||
keybind: "mod+u",
|
||||
disabled: props.controller.state.mode !== "normal",
|
||||
onSelect: () => props.controller.attach(),
|
||||
},
|
||||
{
|
||||
id: "prompt.mode.shell",
|
||||
title: language.t("command.prompt.mode.shell"),
|
||||
category: language.t("command.category.session"),
|
||||
keybind: "mod+shift+x",
|
||||
disabled: props.controller.state.mode === "shell",
|
||||
onSelect: () => props.controller.dispatch({ type: "mode.shell" }),
|
||||
},
|
||||
{
|
||||
id: "prompt.mode.normal",
|
||||
title: language.t("command.prompt.mode.normal"),
|
||||
category: language.t("command.category.session"),
|
||||
keybind: "mod+shift+e",
|
||||
disabled: props.controller.state.mode === "normal",
|
||||
onSelect: () => props.controller.dispatch({ type: "mode.normal" }),
|
||||
},
|
||||
])
|
||||
}
|
||||
|
||||
export function usePromptInputV2Controller(props: PromptInputV2ControllerProps): PromptInputV2ComposerController {
|
||||
const sdk = useSDK()
|
||||
const sync = useSync()
|
||||
const files = useFile()
|
||||
const layout = useLayout()
|
||||
const comments = useComments()
|
||||
const dialog = useDialog()
|
||||
const command = useCommand()
|
||||
const permission = usePermission()
|
||||
const language = useLanguage()
|
||||
const platform = usePlatform()
|
||||
const prompt = props.state ?? usePrompt()
|
||||
let editor: HTMLDivElement | undefined
|
||||
|
||||
const interaction = createPromptInputV2State()
|
||||
const mode = () => interaction[0].mode
|
||||
const history = props.history ?? createPersistedPromptInputHistory()
|
||||
const tabs = () => props.controls.session.tabs
|
||||
const activeFileTab = createSessionTabs({
|
||||
tabs,
|
||||
pathFromTab: files.pathFromTab,
|
||||
normalizeTab: (tab) => (tab.startsWith("file://") ? files.tab(tab) : tab),
|
||||
}).activeFileTab
|
||||
const recent = createMemo(() => {
|
||||
const all = tabs().all()
|
||||
const active = activeFileTab()
|
||||
const order = active ? [active, ...all.filter((tab) => tab !== active)] : all
|
||||
return order.reduce<string[]>((result, tab) => {
|
||||
const path = files.pathFromTab(tab)
|
||||
if (!path || result.includes(path)) return result
|
||||
return [...result, path]
|
||||
}, [])
|
||||
})
|
||||
const info = createMemo(() => (props.controls.session.id ? sync().session.get(props.controls.session.id) : undefined))
|
||||
const working = createMemo(() => sync().data.session_working(props.controls.session.id ?? ""))
|
||||
const attachments = createMemo(() =>
|
||||
prompt.current().filter((part): part is ImageAttachmentPart => part.type === "image"),
|
||||
)
|
||||
const commentCount = createMemo(() => {
|
||||
if (mode() === "shell") return 0
|
||||
return prompt.context.items().filter((item) => !!item.comment?.trim()).length
|
||||
})
|
||||
const blank = createMemo(() => {
|
||||
const text = prompt
|
||||
.current()
|
||||
.map((part) => ("content" in part ? part.content : ""))
|
||||
.join("")
|
||||
return text.trim().length === 0 && attachments().length === 0 && commentCount() === 0
|
||||
})
|
||||
const stopping = createMemo(() => working() && blank())
|
||||
const placeholder = createMemo(() =>
|
||||
promptPlaceholder({
|
||||
mode: mode(),
|
||||
commentCount: commentCount(),
|
||||
example: mode() === "shell" ? "git status" : "",
|
||||
suggest: false,
|
||||
t: (key, params) => language.t(key as Parameters<typeof language.t>[0], params as never),
|
||||
}),
|
||||
)
|
||||
const designPlaceholder = () => promptDesignPlaceholder(mode(), placeholder())
|
||||
|
||||
const historyComments = () => {
|
||||
const byID = new Map(comments.all().map((item) => [`${item.file}\n${item.id}`, item] as const))
|
||||
return prompt.context.items().flatMap((item) => {
|
||||
const comment = item.comment?.trim()
|
||||
if (!comment) return []
|
||||
const selection = item.commentID ? byID.get(`${item.path}\n${item.commentID}`)?.selection : undefined
|
||||
const nextSelection =
|
||||
selection ??
|
||||
(item.selection
|
||||
? ({ start: item.selection.startLine, end: item.selection.endLine } satisfies SelectedLineRange)
|
||||
: undefined)
|
||||
if (!nextSelection) return []
|
||||
return [
|
||||
{
|
||||
id: item.commentID ?? item.key,
|
||||
path: item.path,
|
||||
selection: { ...nextSelection },
|
||||
comment,
|
||||
time: item.commentID ? (byID.get(`${item.path}\n${item.commentID}`)?.time ?? Date.now()) : Date.now(),
|
||||
origin: item.commentOrigin,
|
||||
preview: item.preview,
|
||||
} satisfies PromptHistoryComment,
|
||||
]
|
||||
})
|
||||
}
|
||||
const restoreHistoryComments = (items: PromptHistoryComment[]) => {
|
||||
comments.replace(
|
||||
items.map((item) => ({
|
||||
id: item.id,
|
||||
file: item.path,
|
||||
selection: { ...item.selection },
|
||||
comment: item.comment,
|
||||
time: item.time,
|
||||
})),
|
||||
)
|
||||
prompt.context.replaceComments(
|
||||
items.map((item) => ({
|
||||
type: "file",
|
||||
path: item.path,
|
||||
selection: selectionFromLines(item.selection),
|
||||
comment: item.comment,
|
||||
commentID: item.id,
|
||||
commentOrigin: item.origin,
|
||||
preview: item.preview,
|
||||
})),
|
||||
)
|
||||
}
|
||||
|
||||
const accepting = createMemo(() => {
|
||||
const id = props.controls.session.id
|
||||
if (!id) return permission.isAutoAcceptingDirectory(sdk().directory)
|
||||
return permission.isAutoAccepting(id, sdk().directory)
|
||||
})
|
||||
const submission = createPromptSubmit({
|
||||
prompt,
|
||||
info,
|
||||
imageAttachments: attachments,
|
||||
commentCount,
|
||||
autoAccept: accepting,
|
||||
mode,
|
||||
working,
|
||||
editor: () => editor,
|
||||
queueScroll: () => requestAnimationFrame(() => editor?.scrollIntoView({ block: "nearest" })),
|
||||
promptLength,
|
||||
addToHistory: (value, mode) => controller.addHistory(value, mode),
|
||||
resetHistoryNavigation: () => controller.resetHistory(),
|
||||
setMode: (next) => controller.dispatch({ type: next === "shell" ? "mode.shell" : "mode.normal" }),
|
||||
setPopover: (popover) => {
|
||||
if (!popover) controller.dispatch({ type: "popover.close" })
|
||||
},
|
||||
newSessionWorktree: () => props.newSessionWorktree,
|
||||
onNewSessionWorktreeReset: props.onNewSessionWorktreeReset,
|
||||
shouldQueue: props.shouldQueue,
|
||||
onQueue: props.onQueue,
|
||||
onAbort: props.onAbort,
|
||||
onSubmit: props.onSubmit,
|
||||
model: props.controls.model.selection,
|
||||
})
|
||||
|
||||
const referenceDescription = (reference: ReferenceInfo) =>
|
||||
reference.source.type === "git" ? reference.source.repository : reference.source.path
|
||||
const references = createMemo(() =>
|
||||
sync()
|
||||
.data.reference.filter((reference) => !reference.hidden)
|
||||
.map((reference) => ({
|
||||
id: `reference:${reference.name}`,
|
||||
kind: "reference" as const,
|
||||
label: `@${reference.name}`,
|
||||
path: reference.path,
|
||||
description: reference.description ?? referenceDescription(reference),
|
||||
mention: {
|
||||
type: "file" as const,
|
||||
path: reference.path,
|
||||
content: `@${reference.name}`,
|
||||
start: 0,
|
||||
end: 0,
|
||||
mime: "application/x-directory",
|
||||
filename: reference.name,
|
||||
},
|
||||
})),
|
||||
)
|
||||
const resources = createMemo(() =>
|
||||
Object.values(sync().data.mcp_resource).map((resource) => ({
|
||||
id: `resource:${resource.client}:${resource.uri}`,
|
||||
kind: "resource" as const,
|
||||
label: `@${resource.name}`,
|
||||
path: resource.uri,
|
||||
description: resource.description,
|
||||
mention: {
|
||||
type: "file" as const,
|
||||
path: resource.uri,
|
||||
content: `@${resource.name}`,
|
||||
start: 0,
|
||||
end: 0,
|
||||
mime: resource.mimeType ?? "text/plain",
|
||||
filename: resource.name,
|
||||
url: resource.uri,
|
||||
source: {
|
||||
type: "resource" as const,
|
||||
text: { value: `@${resource.name}`, start: 0, end: resource.name.length + 1 },
|
||||
clientName: resource.client,
|
||||
uri: resource.uri,
|
||||
},
|
||||
},
|
||||
resource,
|
||||
})),
|
||||
)
|
||||
const context = createMemo<PromptInputV2Suggestion[]>(() => [
|
||||
...references(),
|
||||
...props.controls.agents.available
|
||||
.filter((agent) => !agent.hidden && agent.mode !== "primary")
|
||||
.map((agent) => ({
|
||||
id: `agent:${agent.name}`,
|
||||
kind: "agent" as const,
|
||||
label: `@${agent.name}`,
|
||||
mention: { type: "agent" as const, name: agent.name, content: `@${agent.name}`, start: 0, end: 0 },
|
||||
})),
|
||||
...resources(),
|
||||
...recent().map((path) => ({
|
||||
id: `file:${path}`,
|
||||
kind: "file" as const,
|
||||
label: path,
|
||||
path,
|
||||
recent: true,
|
||||
mention: { type: "file" as const, path, content: `@${path}`, start: 0, end: 0 },
|
||||
})),
|
||||
])
|
||||
const slashCommands = createMemo(() => [
|
||||
...sync().data.command.map((item) => ({
|
||||
id: `custom.${item.name}`,
|
||||
trigger: item.name,
|
||||
title: item.name,
|
||||
description: item.description,
|
||||
type: "custom" as const,
|
||||
})),
|
||||
...command.options
|
||||
.filter((item) => !item.disabled && !item.id.startsWith("suggested.") && item.slash)
|
||||
.map((item) => ({
|
||||
id: item.id,
|
||||
trigger: item.slash!,
|
||||
title: item.title,
|
||||
description: item.description,
|
||||
type: "builtin" as const,
|
||||
})),
|
||||
])
|
||||
const commands = createMemo<PromptInputV2Suggestion[]>(() =>
|
||||
slashCommands().map((item) => ({
|
||||
id: item.id,
|
||||
kind: "command",
|
||||
label: `/${item.trigger}`,
|
||||
trigger: item.trigger,
|
||||
title: item.title,
|
||||
description: item.description,
|
||||
keybind: command.keybindParts(item.id),
|
||||
})),
|
||||
)
|
||||
const variants = createMemo(() => ["default", ...props.controls.model.selection.variant.list()])
|
||||
const controller = createPromptInputV2Controller({
|
||||
store: () => prompt.capture().store,
|
||||
state: interaction,
|
||||
identity: () => prompt.capture(),
|
||||
history: {
|
||||
entries: (mode) =>
|
||||
history.entries(mode).map((value) => {
|
||||
const entry = normalizePromptHistoryEntry(value)
|
||||
return { prompt: entry.prompt, metadata: entry.comments }
|
||||
}),
|
||||
add: (value, mode) => history.add(value, mode, mode === "shell" ? [] : historyComments()),
|
||||
capture: historyComments,
|
||||
restore: (metadata) => restoreHistoryComments(metadata as PromptHistoryComment[]),
|
||||
},
|
||||
commands,
|
||||
context,
|
||||
searchContextFiles: async (query) =>
|
||||
(await files.searchFilesAndDirectories(query)).map((path) => ({
|
||||
id: `file:${path}`,
|
||||
kind: "file",
|
||||
label: path,
|
||||
path,
|
||||
mention: { type: "file", path, content: `@${path}`, start: 0, end: 0 },
|
||||
})),
|
||||
onContextRemove(item) {
|
||||
if (item?.commentID) comments.remove(item.path, item.commentID)
|
||||
},
|
||||
openAttachment: (attachment) =>
|
||||
dialog.show(() => <ImagePreview src={attachment.dataUrl} alt={attachment.filename} />),
|
||||
openContext(key) {
|
||||
const item = controller.contextItem(key)
|
||||
if (item) openComment(item, props, sync, layout, files, comments)
|
||||
},
|
||||
onEditor(element) {
|
||||
editor = element as HTMLDivElement
|
||||
props.ref?.(editor)
|
||||
},
|
||||
onSuggestionSelect(item) {
|
||||
if (item.kind !== "command") return
|
||||
const selected = slashCommands().find((entry) => entry.id === item.id)
|
||||
if (!selected || selected.type === "custom") return
|
||||
return () => command.trigger(selected.id, "slash")
|
||||
},
|
||||
attachments: {
|
||||
picker: platform.openAttachmentPickerDialog,
|
||||
directory: () => sdk().directory,
|
||||
isDialogActive: () => !!dialog.active,
|
||||
warn: () =>
|
||||
showToast({
|
||||
title: language.t("prompt.toast.pasteUnsupported.title"),
|
||||
description: language.t("prompt.toast.pasteUnsupported.description"),
|
||||
}),
|
||||
onError: (error) =>
|
||||
showToast({
|
||||
variant: "error",
|
||||
title: language.t("common.requestFailed"),
|
||||
description: error instanceof Error ? error.message : String(error),
|
||||
}),
|
||||
readClipboardImage: platform.readClipboardImage,
|
||||
getPathForFile: platform.getPathForFile,
|
||||
},
|
||||
view: {
|
||||
placeholder: designPlaceholder,
|
||||
agent:
|
||||
props.controls.agents.visible && props.controls.agents.options.length > 0
|
||||
? {
|
||||
options: () => props.controls.agents.options.map((name) => ({ id: name, label: name })),
|
||||
current: () => props.controls.agents.current,
|
||||
onSelect: props.controls.agents.select,
|
||||
keybind: () => command.keybindParts("agent.cycle"),
|
||||
}
|
||||
: undefined,
|
||||
variant: {
|
||||
options: () => variants().map((value) => ({ id: value, label: value })),
|
||||
current: () => props.controls.model.selection.variant.current() ?? "default",
|
||||
onSelect: (value) => props.controls.model.selection.variant.set(value === "default" ? undefined : value),
|
||||
keybind: () => command.keybindParts("model.variant.cycle"),
|
||||
},
|
||||
submit: {
|
||||
stopping,
|
||||
working,
|
||||
onSubmit: () => void submission.handleSubmit(new Event("submit")),
|
||||
onStop: () => void submission.abort(),
|
||||
},
|
||||
},
|
||||
})
|
||||
Object.defineProperty(controller, "model", { get: () => props.controls.model })
|
||||
return controller as PromptInputV2ComposerController
|
||||
}
|
||||
|
||||
function PromptInputV2ModelControl(props: {
|
||||
loading: boolean
|
||||
paid: boolean
|
||||
title: string
|
||||
keybind: string[]
|
||||
model: PromptInputV2ComposerController["model"]["selection"]
|
||||
providerID?: string
|
||||
modelName: string
|
||||
onClose: () => void
|
||||
onUnpaidClick: () => void
|
||||
}) {
|
||||
const shouldAnimate = createMemo<boolean>((previous) => previous ?? props.loading)
|
||||
const content = () => (
|
||||
<>
|
||||
<Show when={props.providerID}>
|
||||
{(providerID) => (
|
||||
<ProviderIcon
|
||||
id={providerID()}
|
||||
class="size-4 shrink-0 opacity-40 group-hover:opacity-100 transition-opacity duration-150"
|
||||
style={{ "will-change": "opacity", transform: "translateZ(0)" }}
|
||||
/>
|
||||
)}
|
||||
</Show>
|
||||
<span class="truncate leading-4">{props.modelName}</span>
|
||||
<span class="-ml-0.5 -mr-1 flex shrink-0">
|
||||
<Icon name="chevron-down" />
|
||||
</span>
|
||||
</>
|
||||
)
|
||||
return (
|
||||
<Show when={!props.loading}>
|
||||
<TooltipV2
|
||||
placement="top"
|
||||
gutter={4}
|
||||
value={
|
||||
<>
|
||||
{props.title}
|
||||
<KeybindV2 keys={props.keybind} variant="neutral" />
|
||||
</>
|
||||
}
|
||||
>
|
||||
<Show
|
||||
when={props.paid}
|
||||
fallback={
|
||||
<ButtonV2
|
||||
data-action="prompt-model"
|
||||
variant="ghost-muted"
|
||||
size="normal"
|
||||
class="min-w-0 max-w-[220px] justify-start ![font-weight:440] group"
|
||||
classList={{ "animate-in fade-in": shouldAnimate() }}
|
||||
style={{ height: "28px" }}
|
||||
onClick={props.onUnpaidClick}
|
||||
>
|
||||
{content()}
|
||||
</ButtonV2>
|
||||
}
|
||||
>
|
||||
<ModelSelectorPopoverV2
|
||||
model={props.model}
|
||||
triggerAs={ButtonV2}
|
||||
triggerProps={{
|
||||
variant: "ghost-muted",
|
||||
size: "normal",
|
||||
style: { height: "28px" },
|
||||
class: "min-w-0 max-w-[220px] justify-start ![font-weight:440] group",
|
||||
classList: { "animate-in fade-in": shouldAnimate() },
|
||||
"data-action": "prompt-model",
|
||||
}}
|
||||
onClose={props.onClose}
|
||||
>
|
||||
{content()}
|
||||
</ModelSelectorPopoverV2>
|
||||
</Show>
|
||||
</TooltipV2>
|
||||
</Show>
|
||||
)
|
||||
}
|
||||
|
||||
function openComment(
|
||||
item: { path: string; commentID?: string; commentOrigin?: "review" | "file" },
|
||||
props: PromptInputV2ControllerProps,
|
||||
sync: ReturnType<typeof useSync>,
|
||||
layout: ReturnType<typeof useLayout>,
|
||||
files: ReturnType<typeof useFile>,
|
||||
comments: ReturnType<typeof useComments>,
|
||||
) {
|
||||
if (!item.commentID) return
|
||||
const focus = { file: item.path, id: item.commentID }
|
||||
comments.setActive(focus)
|
||||
const queueFocus = (attempts = 6) => {
|
||||
requestAnimationFrame(() => {
|
||||
comments.setFocus({ ...focus })
|
||||
if (attempts <= 0) return
|
||||
requestAnimationFrame(() => {
|
||||
const current = comments.focus()
|
||||
if (current?.file === focus.file && current.id === focus.id) queueFocus(attempts - 1)
|
||||
})
|
||||
})
|
||||
}
|
||||
const diffs = props.controls.session.id ? sync().data.session_diff[props.controls.session.id] : undefined
|
||||
const review =
|
||||
item.commentOrigin === "review" || (item.commentOrigin !== "file" && diffs?.some((diff) => diff.file === item.path))
|
||||
if (!props.controls.session.reviewPanel.opened()) props.controls.session.reviewPanel.open()
|
||||
if (review) {
|
||||
layout.fileTree.setTab("changes")
|
||||
props.controls.session.tabs.setActive("review")
|
||||
queueFocus()
|
||||
return
|
||||
}
|
||||
layout.fileTree.setTab("all")
|
||||
const tab = files.tab(item.path)
|
||||
void props.controls.session.tabs.open(tab)
|
||||
props.controls.session.tabs.setActive(tab)
|
||||
void Promise.resolve(files.load(item.path)).finally(() => queueFocus())
|
||||
}
|
||||
File diff suppressed because it is too large
Load diff
|
|
@ -38,7 +38,7 @@ type PromptAttachmentsCoreInput = {
|
|||
getPathForFile?: (file: File) => string
|
||||
}
|
||||
|
||||
type PromptAttachmentsInput = {
|
||||
export type PromptAttachmentsInput = {
|
||||
prompt: ReturnType<typeof usePrompt>
|
||||
editor: () => HTMLDivElement | undefined
|
||||
isDialogActive: () => boolean
|
||||
|
|
|
|||
|
|
@ -89,13 +89,15 @@ const toOptimisticPart = (part: PromptRequestPart, sessionID: string, messageID:
|
|||
}
|
||||
|
||||
export function buildRequestParts(input: BuildRequestPartsInput) {
|
||||
const requestParts: PromptRequestPart[] = [
|
||||
{
|
||||
id: Identifier.ascending("part"),
|
||||
type: "text",
|
||||
text: input.text,
|
||||
},
|
||||
]
|
||||
const requestParts: PromptRequestPart[] = input.text.trim()
|
||||
? [
|
||||
{
|
||||
id: Identifier.ascending("part"),
|
||||
type: "text",
|
||||
text: input.text,
|
||||
},
|
||||
]
|
||||
: []
|
||||
|
||||
const files = input.prompt.filter(isFileAttachment).map((attachment) => {
|
||||
const path = absolute(input.sessionDirectory, attachment.path)
|
||||
|
|
|
|||
57
packages/app/src/components/prompt-input/contracts.ts
Normal file
57
packages/app/src/components/prompt-input/contracts.ts
Normal file
|
|
@ -0,0 +1,57 @@
|
|||
import type { useLocal } from "@/context/local"
|
||||
import type { Prompt, usePrompt } from "@/context/prompt"
|
||||
import type { PromptInputHistory } from "./history-store"
|
||||
import type { FollowupDraft } from "./submit"
|
||||
|
||||
export type PromptInputState = ReturnType<typeof usePrompt>
|
||||
|
||||
export type PromptInputSubmission = {
|
||||
abort: () => Promise<void> | void
|
||||
handleSubmit: (event: Event) => Promise<void> | void
|
||||
}
|
||||
|
||||
export type PromptInputControls = {
|
||||
agents: {
|
||||
available: { name: string; hidden?: boolean; mode: string }[]
|
||||
options: string[]
|
||||
current: string
|
||||
loading: boolean
|
||||
visible: boolean
|
||||
select: (name: string | undefined) => void
|
||||
}
|
||||
model: {
|
||||
selection: ReturnType<typeof useLocal>["model"]
|
||||
paid: boolean
|
||||
loading: boolean
|
||||
}
|
||||
session: {
|
||||
id?: string
|
||||
tabs: {
|
||||
active: () => string | undefined
|
||||
all: () => string[]
|
||||
open: (tab: string) => void | Promise<void>
|
||||
setActive: (tab: string) => void
|
||||
}
|
||||
reviewPanel: {
|
||||
opened: () => boolean
|
||||
open: () => void
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
export interface PromptInputProps {
|
||||
class?: string
|
||||
state?: PromptInputState
|
||||
history?: PromptInputHistory
|
||||
submission?: PromptInputSubmission
|
||||
controls: PromptInputControls
|
||||
ref?: (el: HTMLDivElement) => void
|
||||
newSessionWorktree?: string
|
||||
onNewSessionWorktreeReset?: () => void
|
||||
edit?: { id: string; prompt: Prompt; context: FollowupDraft["context"] }
|
||||
onEditLoaded?: () => void
|
||||
shouldQueue?: () => boolean
|
||||
onQueue?: (draft: FollowupDraft) => void
|
||||
onAbort?: () => void
|
||||
onSubmit?: () => void
|
||||
}
|
||||
47
packages/app/src/components/prompt-input/history-store.ts
Normal file
47
packages/app/src/components/prompt-input/history-store.ts
Normal file
|
|
@ -0,0 +1,47 @@
|
|||
import { createStore, type SetStoreFunction, type Store } from "solid-js/store"
|
||||
import type { Prompt } from "@/context/prompt"
|
||||
import { Persist, persisted } from "@/utils/persist"
|
||||
import { prependHistoryEntry, type PromptHistoryComment, type PromptHistoryStoredEntry } from "./history"
|
||||
|
||||
export type PromptInputHistory = {
|
||||
entries: (mode: "normal" | "shell") => PromptHistoryStoredEntry[]
|
||||
add: (prompt: Prompt, mode: "normal" | "shell", comments: PromptHistoryComment[]) => void
|
||||
}
|
||||
|
||||
type PromptHistoryState = { entries: PromptHistoryStoredEntry[] }
|
||||
|
||||
function createPromptInputHistoryStore(
|
||||
normal: Store<PromptHistoryState>,
|
||||
setNormal: SetStoreFunction<PromptHistoryState>,
|
||||
shell: Store<PromptHistoryState>,
|
||||
setShell: SetStoreFunction<PromptHistoryState>,
|
||||
): PromptInputHistory {
|
||||
return {
|
||||
entries: (mode) => (mode === "shell" ? shell.entries : normal.entries),
|
||||
add(prompt, mode, comments) {
|
||||
const current = mode === "shell" ? shell : normal
|
||||
const setCurrent = mode === "shell" ? setShell : setNormal
|
||||
const next = prependHistoryEntry(current.entries, prompt, comments)
|
||||
if (next === current.entries) return
|
||||
setCurrent("entries", next)
|
||||
},
|
||||
}
|
||||
}
|
||||
|
||||
export function createPromptInputHistory(): PromptInputHistory {
|
||||
const [normal, setNormal] = createStore<PromptHistoryState>({ entries: [] })
|
||||
const [shell, setShell] = createStore<PromptHistoryState>({ entries: [] })
|
||||
return createPromptInputHistoryStore(normal, setNormal, shell, setShell)
|
||||
}
|
||||
|
||||
export function createPersistedPromptInputHistory() {
|
||||
const [normal, setNormal] = persisted(
|
||||
Persist.global("prompt-history", ["prompt-history.v1"]),
|
||||
createStore<PromptHistoryState>({ entries: [] }),
|
||||
)
|
||||
const [shell, setShell] = persisted(
|
||||
Persist.global("prompt-history-shell", ["prompt-history-shell.v1"]),
|
||||
createStore<PromptHistoryState>({ entries: [] }),
|
||||
)
|
||||
return createPromptInputHistoryStore(normal, setNormal, shell, setShell)
|
||||
}
|
||||
|
|
@ -13,3 +13,8 @@ export function promptPlaceholder(input: PromptPlaceholderInput) {
|
|||
if (!input.suggest) return input.t("prompt.placeholder.simple")
|
||||
return input.t("prompt.placeholder.normal", { example: input.example })
|
||||
}
|
||||
|
||||
export function promptDesignPlaceholder(mode: PromptPlaceholderInput["mode"], placeholder: string) {
|
||||
if (mode === "shell") return placeholder
|
||||
return "Ask anything, / for commands, @ for context..."
|
||||
}
|
||||
|
|
|
|||
|
|
@ -1,5 +1,6 @@
|
|||
import { beforeAll, beforeEach, describe, expect, mock, test } from "bun:test"
|
||||
import type { Prompt } from "@/context/prompt"
|
||||
import { createStore } from "solid-js/store"
|
||||
import type { Prompt, PromptStore } from "@/context/prompt"
|
||||
import type { ModelSelection } from "@/context/local"
|
||||
|
||||
let createPromptSubmit: typeof import("./submit").createPromptSubmit
|
||||
|
|
@ -31,7 +32,13 @@ let permissionServer = "server-a"
|
|||
let createSessionGate: Promise<void> | undefined
|
||||
|
||||
const promptValue: Prompt = [{ type: "text", content: "ls", start: 0, end: 2 }]
|
||||
const [promptStore, setPromptStore] = createStore<PromptStore>({
|
||||
prompt: promptValue,
|
||||
cursor: 0,
|
||||
context: { items: [] },
|
||||
})
|
||||
const prompt = {
|
||||
store: [() => promptStore, setPromptStore] as [() => PromptStore, typeof setPromptStore],
|
||||
ready: Object.assign(() => true, { promise: Promise.resolve(true) }),
|
||||
current: () => promptValue,
|
||||
cursor: () => 0,
|
||||
|
|
|
|||
|
|
@ -12,7 +12,6 @@ export type PromptInputTransientState = {
|
|||
draggingType: "image" | "@mention" | null
|
||||
mode: "normal" | "shell"
|
||||
applyingHistory: boolean
|
||||
variantOpen: boolean
|
||||
}
|
||||
|
||||
function resetPromptInputTransientState(setStore: SetStoreFunction<PromptInputTransientState>) {
|
||||
|
|
@ -25,7 +24,6 @@ function resetPromptInputTransientState(setStore: SetStoreFunction<PromptInputTr
|
|||
draggingType: null,
|
||||
mode: "normal",
|
||||
applyingHistory: false,
|
||||
variantOpen: false,
|
||||
})
|
||||
}
|
||||
|
||||
|
|
@ -40,7 +38,6 @@ export function createPromptInputTransientState(identity: Accessor<unknown>, pla
|
|||
draggingType: null,
|
||||
mode: "normal",
|
||||
applyingHistory: false,
|
||||
variantOpen: false,
|
||||
})
|
||||
|
||||
createComputed(on(identity, () => resetPromptInputTransientState(setStore), { defer: true }))
|
||||
|
|
|
|||
|
|
@ -55,7 +55,7 @@ export function createPromptProjectController(input: {
|
|||
const [store, setStore] = createStore({ open: false, search: "", active: "" })
|
||||
let searchRef: HTMLInputElement | undefined
|
||||
|
||||
const selected = () => {
|
||||
const current = () => {
|
||||
const key = pathKey(input.controls().directory)
|
||||
return input
|
||||
.controls()
|
||||
|
|
@ -65,6 +65,7 @@ export function createPromptProjectController(input: {
|
|||
(pathKey(project.worktree) === key || project.sandboxes?.some((sandbox) => pathKey(sandbox) === key)),
|
||||
)
|
||||
}
|
||||
const selected = () => current() ?? input.controls().available[0]
|
||||
const projects = () => {
|
||||
const search = store.search.trim().toLowerCase()
|
||||
if (!search) return input.controls().available
|
||||
|
|
@ -100,8 +101,8 @@ export function createPromptProjectController(input: {
|
|||
}
|
||||
const select = (project: PromptProject) => {
|
||||
if (
|
||||
pathKey(project.worktree) !== pathKey(selected()?.worktree ?? "") ||
|
||||
project.server?.key !== selected()?.server?.key
|
||||
pathKey(project.worktree) !== pathKey(current()?.worktree ?? "") ||
|
||||
project.server?.key !== current()?.server?.key
|
||||
) {
|
||||
input.controls().select(project.worktree, project.server?.key)
|
||||
}
|
||||
|
|
@ -124,6 +125,7 @@ export function createPromptProjectController(input: {
|
|||
|
||||
return {
|
||||
selected,
|
||||
empty: () => input.controls().available.length === 0,
|
||||
projects,
|
||||
servers,
|
||||
projectKey,
|
||||
|
|
|
|||
|
|
@ -93,24 +93,36 @@ export function PromptWorkspaceSelector(props: {
|
|||
</MenuV2.Content>
|
||||
</MenuV2.Portal>
|
||||
</MenuV2>
|
||||
<Show when={props.branch}>
|
||||
{(branch) => (
|
||||
<>
|
||||
<span class="hidden select-none opacity-50 sm:inline mx-1">/</span>
|
||||
<TooltipV2
|
||||
placement="top"
|
||||
value={branch()}
|
||||
class="min-w-0 max-w-[220px]"
|
||||
contentClass="max-w-[calc(100vw-32px)] break-all"
|
||||
>
|
||||
<div class="flex h-7 min-w-0 max-w-[220px] items-center gap-1.5 px-2 text-[13px] font-[440] leading-5 tracking-[-0.04px]">
|
||||
<Icon name="branch" size="small" class="shrink-0 text-v2-icon-icon-muted" />
|
||||
<span class="min-w-0 truncate">{branch()}</span>
|
||||
</div>
|
||||
</TooltipV2>
|
||||
</>
|
||||
)}
|
||||
</Show>
|
||||
<PromptGitStatus branch={props.branch} />
|
||||
</>
|
||||
)
|
||||
}
|
||||
|
||||
export function PromptGitStatus(props: { branch?: string; noGit?: boolean }) {
|
||||
const language = useLanguage()
|
||||
const label = () => {
|
||||
if (props.noGit) return language.t("session.new.git.none")
|
||||
return props.branch
|
||||
}
|
||||
|
||||
return (
|
||||
<Show when={label()}>
|
||||
{(value) => (
|
||||
<>
|
||||
<span class="hidden select-none opacity-50 sm:inline mx-1">/</span>
|
||||
<TooltipV2
|
||||
placement="top"
|
||||
value={value()}
|
||||
class="min-w-0 max-w-[220px]"
|
||||
contentClass="max-w-[calc(100vw-32px)] break-all"
|
||||
>
|
||||
<div class="flex h-7 min-w-0 max-w-[220px] items-center gap-1.5 px-2 text-[13px] font-[440] leading-5 tracking-[-0.04px]">
|
||||
<Icon name="branch" size="small" class="shrink-0 text-v2-icon-icon-muted" />
|
||||
<span class="min-w-0 truncate">{value()}</span>
|
||||
</div>
|
||||
</TooltipV2>
|
||||
</>
|
||||
)}
|
||||
</Show>
|
||||
)
|
||||
}
|
||||
|
|
|
|||
|
|
@ -2,7 +2,8 @@ import { createMemo, Show } from "solid-js"
|
|||
import type { JSX } from "solid-js"
|
||||
import { useSortable } from "@dnd-kit/solid/sortable"
|
||||
import { IconButton } from "@opencode-ai/ui/icon-button"
|
||||
import { TooltipKeybind } from "@opencode-ai/ui/tooltip"
|
||||
import { KeybindV2 } from "@opencode-ai/ui/v2/keybind-v2"
|
||||
import { TooltipV2 } from "@opencode-ai/ui/v2/tooltip-v2"
|
||||
import { Tabs } from "@opencode-ai/ui/tabs"
|
||||
import { useFile } from "@/context/file"
|
||||
import { useLanguage } from "@/context/language"
|
||||
|
|
@ -19,6 +20,7 @@ export function SortableTabV2(props: {
|
|||
const file = useFile()
|
||||
const language = useLanguage()
|
||||
const command = useCommand()
|
||||
const closeTabKeybind = createMemo(() => command.keybindParts("tab.close"))
|
||||
const sortable = useSortable({
|
||||
get id() {
|
||||
return props.tab
|
||||
|
|
@ -39,9 +41,15 @@ export function SortableTabV2(props: {
|
|||
<Tabs.Trigger
|
||||
value={props.tab}
|
||||
closeButton={
|
||||
<TooltipKeybind
|
||||
title={language.t("common.closeTab")}
|
||||
keybind={command.keybind("tab.close")}
|
||||
<TooltipV2
|
||||
value={
|
||||
<>
|
||||
{language.t("common.closeTab")}
|
||||
<Show when={closeTabKeybind().length > 0}>
|
||||
<KeybindV2 keys={closeTabKeybind()} variant="neutral" />
|
||||
</Show>
|
||||
</>
|
||||
}
|
||||
placement="bottom"
|
||||
gutter={10}
|
||||
>
|
||||
|
|
@ -52,7 +60,7 @@ export function SortableTabV2(props: {
|
|||
onClick={() => props.onTabClose(props.tab)}
|
||||
aria-label={language.t("common.closeTab")}
|
||||
/>
|
||||
</TooltipKeybind>
|
||||
</TooltipV2>
|
||||
}
|
||||
hideCloseButton
|
||||
onMiddleClick={() => props.onTabClose(props.tab)}
|
||||
|
|
|
|||
|
|
@ -133,9 +133,10 @@
|
|||
}
|
||||
|
||||
[data-slot="settings-v2-row-description"] {
|
||||
margin-block: -3.5px;
|
||||
font-size: 13px;
|
||||
font-weight: 440;
|
||||
line-height: 1;
|
||||
line-height: 20px;
|
||||
color: var(--v2-text-text-muted);
|
||||
}
|
||||
|
||||
|
|
@ -270,10 +271,10 @@
|
|||
}
|
||||
|
||||
.settings-v2-provider-description {
|
||||
margin: 0;
|
||||
margin-block: -3.5px;
|
||||
font-size: 13px;
|
||||
font-weight: 440;
|
||||
line-height: 1;
|
||||
line-height: 20px;
|
||||
color: var(--v2-text-text-muted);
|
||||
}
|
||||
|
||||
|
|
|
|||
|
|
@ -292,7 +292,12 @@ export const Terminal = (props: TerminalProps) => {
|
|||
|
||||
const scheduleSize = (cols: number, rows: number) => {
|
||||
if (disposed) return
|
||||
if (lastSize?.cols === cols && lastSize?.rows === rows) return
|
||||
if (lastSize?.cols === cols && lastSize?.rows === rows) {
|
||||
pendingSize = undefined
|
||||
if (sizeTimer !== undefined) clearTimeout(sizeTimer)
|
||||
sizeTimer = undefined
|
||||
return
|
||||
}
|
||||
|
||||
pendingSize = { cols, rows }
|
||||
|
||||
|
|
@ -317,8 +322,10 @@ export const Terminal = (props: TerminalProps) => {
|
|||
|
||||
createEffect(() => {
|
||||
const colors = terminalColors()
|
||||
const mode = theme.mode() === "dark" ? "dark" : "light"
|
||||
if (!term) return
|
||||
setOptionIfSupported(term, "theme", colors)
|
||||
setOptionIfSupported(term, "colorScheme", mode)
|
||||
})
|
||||
|
||||
createEffect(() => {
|
||||
|
|
@ -396,6 +403,7 @@ export const Terminal = (props: TerminalProps) => {
|
|||
}
|
||||
_ghostty = g
|
||||
term = t
|
||||
setOptionIfSupported(t, "colorScheme", theme.mode() === "dark" ? "dark" : "light")
|
||||
output = terminalWriter((data, done) =>
|
||||
t.write(data, () => {
|
||||
done?.()
|
||||
|
|
@ -595,6 +603,7 @@ export const Terminal = (props: TerminalProps) => {
|
|||
tries = 0
|
||||
local.onConnect?.()
|
||||
scheduleSize(t.cols, t.rows)
|
||||
if (t.getMode(2031)) t.write("\x1b[?996n")
|
||||
}
|
||||
|
||||
const handleMessage = (event: MessageEvent) => {
|
||||
|
|
|
|||
|
|
@ -67,7 +67,7 @@ export function useTitlebarRightMount() {
|
|||
return mount
|
||||
}
|
||||
|
||||
export function Titlebar(props: { update?: TitlebarUpdate }) {
|
||||
export function Titlebar(props: { update?: TitlebarUpdate; debugTools?: { visible: boolean; toggle: () => void } }) {
|
||||
const layout = useLayout()
|
||||
const platform = usePlatform()
|
||||
const command = useCommand()
|
||||
|
|
@ -462,7 +462,7 @@ export function Titlebar(props: { update?: TitlebarUpdate }) {
|
|||
"md:pl-4": !mac(),
|
||||
}}
|
||||
>
|
||||
<ChannelIndicator />
|
||||
<ChannelIndicator debugTools={props.debugTools} />
|
||||
<Show when={windows() || linux()}>
|
||||
<WindowsAppMenu command={command} platform={platform} variant="v2" />
|
||||
</Show>
|
||||
|
|
@ -660,9 +660,9 @@ export function Titlebar(props: { update?: TitlebarUpdate }) {
|
|||
</div>
|
||||
</Show>
|
||||
<div id="opencode-titlebar-left" class="flex items-center gap-3 min-w-0 px-2" />
|
||||
<ChannelIndicator />
|
||||
</div>
|
||||
</div>
|
||||
<ChannelIndicator debugTools={props.debugTools} />
|
||||
</div>
|
||||
</div>
|
||||
|
||||
|
|
@ -747,12 +747,27 @@ function TitlebarUpdateIconButton(props: { state: TitlebarUpdatePillState }) {
|
|||
)
|
||||
}
|
||||
|
||||
function ChannelIndicator() {
|
||||
function ChannelIndicator(props: { debugTools?: { visible: boolean; toggle: () => void } }) {
|
||||
const channel = import.meta.env.VITE_OPENCODE_CHANNEL
|
||||
if (channel === "dev" && props.debugTools) {
|
||||
return (
|
||||
<button
|
||||
type="button"
|
||||
class="bg-icon-interactive-base text-[#FFF] font-medium px-2 rounded-sm uppercase font-mono cursor-pointer"
|
||||
onClick={props.debugTools.toggle}
|
||||
aria-label="Toggle debug tools"
|
||||
aria-pressed={props.debugTools.visible}
|
||||
>
|
||||
DEV
|
||||
</button>
|
||||
)
|
||||
}
|
||||
|
||||
return (
|
||||
<>
|
||||
{["beta", "dev"].includes(import.meta.env.VITE_OPENCODE_CHANNEL) && (
|
||||
{["beta", "dev"].includes(channel) && (
|
||||
<div class="bg-icon-interactive-base text-[#FFF] font-medium px-2 rounded-sm uppercase font-mono">
|
||||
{import.meta.env.VITE_OPENCODE_CHANNEL.toUpperCase()}
|
||||
{channel.toUpperCase()}
|
||||
</div>
|
||||
)}
|
||||
</>
|
||||
|
|
|
|||
|
|
@ -176,7 +176,14 @@ export const { use: useNotification, provider: NotificationProvider } = createSi
|
|||
|
||||
onCleanup(() => states.forEach((value) => value.dispose()))
|
||||
|
||||
const selected = () => ensure(activeServer())
|
||||
const selected = () => {
|
||||
const list = global.servers.list()
|
||||
const key = activeServer()
|
||||
if (list.some((conn) => ServerConnection.key(conn) === key)) return ensure(key)
|
||||
const conn = list.find((conn) => ServerConnection.key(conn) === server.key) ?? list[0]
|
||||
if (!conn) throw new Error("Notification server not found")
|
||||
return ensure(ServerConnection.key(conn))
|
||||
}
|
||||
|
||||
return {
|
||||
ready: () => selected().ready(),
|
||||
|
|
|
|||
|
|
@ -115,6 +115,9 @@ type PlatformBase = {
|
|||
/** Export collected diagnostic logs (desktop only) */
|
||||
exportDebugLogs?(): Promise<string>
|
||||
|
||||
/** Force focus styles on interactive elements through desktop devtools (desktop only) */
|
||||
setForceFocus?(enabled: boolean): Promise<void>
|
||||
|
||||
/** Record a fatal renderer error in platform logs (desktop only) */
|
||||
recordFatalRendererError?(error: FatalRendererErrorLog): Promise<void>
|
||||
}
|
||||
|
|
|
|||
|
|
@ -64,7 +64,7 @@ export type PromptScope = { draftID: string } | { dir: string; id?: string }
|
|||
|
||||
export const DEFAULT_PROMPT: Prompt = [{ type: "text", content: "", start: 0, end: 0 }]
|
||||
|
||||
type PromptStore = {
|
||||
export type PromptStore = {
|
||||
prompt: Prompt
|
||||
cursor?: number
|
||||
model?: PromptModel
|
||||
|
|
@ -189,6 +189,7 @@ function promptStore(initial?: InitialPrompt): PromptStore {
|
|||
function createPromptStateValue(store: PromptStore, setStore: SetStoreFunction<PromptStore>) {
|
||||
const actions = createPromptActions(setStore)
|
||||
const value = {
|
||||
store: [() => store, setStore] as [Accessor<PromptStore>, SetStoreFunction<PromptStore>],
|
||||
current: () => store.prompt,
|
||||
cursor: createMemo(() => store.cursor),
|
||||
dirty: () => !isPromptEqual(store.prompt, DEFAULT_PROMPT),
|
||||
|
|
|
|||
|
|
@ -1,7 +1,7 @@
|
|||
import { base64Encode } from "@opencode-ai/core/util/encode"
|
||||
import { createSimpleContext } from "@opencode-ai/ui/context"
|
||||
import { useParams, useSearchParams } from "@solidjs/router"
|
||||
import { createMemo, createRoot, getOwner, onCleanup } from "solid-js"
|
||||
import { createMemo, createResource, createRoot, getOwner, onCleanup } from "solid-js"
|
||||
import { requireServerKey } from "@/utils/session-route"
|
||||
import { ServerConnection } from "./server"
|
||||
import { useServerSDK } from "./server-sdk"
|
||||
|
|
@ -36,6 +36,7 @@ export type {
|
|||
ImageAttachmentPart,
|
||||
Prompt,
|
||||
PromptModel,
|
||||
PromptStore,
|
||||
PromptScope,
|
||||
PromptSession,
|
||||
TextPart,
|
||||
|
|
@ -132,18 +133,29 @@ export const { use: usePrompt, provider: PromptProvider } = createSimpleContext(
|
|||
const pick = (scope?: PromptScope) => (scope ? load(scope) : session())
|
||||
const ready = createPromptReady(session)
|
||||
|
||||
const withSuspense = <T,>(cb: () => T): (() => T) =>
|
||||
createResource(
|
||||
async () => {
|
||||
const value = cb()
|
||||
await session().ready.promise
|
||||
return value
|
||||
},
|
||||
cb,
|
||||
{ initialValue: cb() },
|
||||
)[0]
|
||||
|
||||
return {
|
||||
ready,
|
||||
capture: (scope?: PromptScope) => pick(scope).capture(),
|
||||
current: () => session().current(),
|
||||
cursor: () => session().cursor(),
|
||||
dirty: () => session().dirty(),
|
||||
current: withSuspense(() => session().current()),
|
||||
cursor: withSuspense(() => session().cursor()),
|
||||
dirty: withSuspense(() => session().dirty()),
|
||||
model: {
|
||||
current: () => session().model.current(),
|
||||
current: withSuspense(() => session().model.current()),
|
||||
set: (model: PromptModel | undefined) => session().model.set(model),
|
||||
},
|
||||
context: {
|
||||
items: () => session().context.items(),
|
||||
items: withSuspense(() => session().context.items()),
|
||||
add: (item: ContextItem) => session().context.add(item),
|
||||
remove: (key: string) => session().context.remove(key),
|
||||
removeComment: (path: string, commentID: string) => session().context.removeComment(path, commentID),
|
||||
|
|
|
|||
|
|
@ -199,6 +199,49 @@ describe("server session", () => {
|
|||
expect(store.history.more("child")).toBe(true)
|
||||
})
|
||||
|
||||
test("keeps assistant history when its deleted parent cannot be backfilled", async () => {
|
||||
const missing = Promise.withResolvers<SingleMessageResponse>()
|
||||
const assistant = assistantMessage("message-2", "message-missing")
|
||||
const client = rootMessageClient([response([{ info: assistant, parts: [] }], "older")], [missing.promise])
|
||||
const store = createServerSession(client)
|
||||
const loading = store.sync("child")
|
||||
await client.rootRequested(1)
|
||||
|
||||
missing.reject(new Error("Message not found: message-missing", { cause: { status: 404 } }))
|
||||
await loading
|
||||
|
||||
expect(client.rootRequests).toEqual([{ sessionID: "child", messageID: "message-missing" }])
|
||||
expect(store.data.message.child).toEqual([assistant])
|
||||
expect(store.history.more("child")).toBe(true)
|
||||
})
|
||||
|
||||
test("drops a cached parent when a forced refresh confirms it was deleted", async () => {
|
||||
const missing = Promise.withResolvers<SingleMessageResponse>()
|
||||
const parent = userMessage("message-1")
|
||||
const part = textPart(parent.id)
|
||||
const assistant = assistantMessage("message-2", parent.id)
|
||||
const client = rootMessageClient(
|
||||
[
|
||||
response([
|
||||
{ info: parent, parts: [part] },
|
||||
{ info: assistant, parts: [] },
|
||||
]),
|
||||
response([{ info: assistant, parts: [] }], "older"),
|
||||
],
|
||||
[missing.promise],
|
||||
)
|
||||
const store = createServerSession(client)
|
||||
await store.sync("child")
|
||||
const loading = store.sync("child", { force: true })
|
||||
await client.rootRequested(1)
|
||||
|
||||
missing.reject(new Error(`Message not found: ${parent.id}`, { cause: { status: 404 } }))
|
||||
await loading
|
||||
|
||||
expect(store.data.message.child).toEqual([assistant])
|
||||
expect(store.data.part[parent.id]).toBeUndefined()
|
||||
})
|
||||
|
||||
test("does not let an optimistic user suppress initial root backfill", async () => {
|
||||
const user = userMessage("message-1")
|
||||
const part = textPart(user.id)
|
||||
|
|
|
|||
|
|
@ -109,6 +109,7 @@ function reconcileFetched<T extends { id: string }>(
|
|||
options: {
|
||||
touched?: ReadonlySet<string>
|
||||
retained?: ReadonlySet<string>
|
||||
removed?: ReadonlySet<string>
|
||||
preserveUnfetched?: boolean | ((item: T) => boolean)
|
||||
} = {},
|
||||
) {
|
||||
|
|
@ -131,6 +132,7 @@ function reconcileFetched<T extends { id: string }>(
|
|||
if (item) result.set(id, item)
|
||||
if (!item) result.delete(id)
|
||||
}
|
||||
for (const id of options.removed ?? emptyIDs) result.delete(id)
|
||||
return [...result.values()].sort((a, b) => cmp(a.id, b.id))
|
||||
}
|
||||
|
||||
|
|
@ -570,6 +572,7 @@ export function createServerSession(client: OpencodeClient, options?: { retry?:
|
|||
const messages = reconcileFetched(merged.session, data.message[sessionID] ?? [], {
|
||||
touched: touchedMessages,
|
||||
retained: load?.retainedMessages,
|
||||
removed: load?.removedMessages,
|
||||
preserveUnfetched,
|
||||
})
|
||||
batch(() => {
|
||||
|
|
@ -638,7 +641,15 @@ export function createServerSession(client: OpencodeClient, options?: { retry?:
|
|||
if (generations.get(sessionID) !== active) break
|
||||
const parent = await fetchMessage(sessionID, parentID, () =>
|
||||
resetMessageLoad(sessionID, load, messageLoadBaseline(load, parentID)),
|
||||
)
|
||||
).catch((error) => {
|
||||
const cause = error instanceof Error && typeof error.cause === "object" ? error.cause : undefined
|
||||
if (cause && "status" in cause && cause.status === 404) {
|
||||
load.removedMessages.add(parentID)
|
||||
return
|
||||
}
|
||||
throw error
|
||||
})
|
||||
if (!parent) continue
|
||||
if (parent.message.role !== "user") throw new Error(`Assistant parent is not a user message: ${parentID}`)
|
||||
parents.push(parent)
|
||||
}
|
||||
|
|
|
|||
|
|
@ -610,6 +610,7 @@ export const dict = {
|
|||
"session.new.workspace.triggerLocal": "محلي",
|
||||
"session.new.workspace.local": "المستودع المحلي",
|
||||
"session.new.workspace.existing": "مساحة عمل…",
|
||||
"session.new.git.none": "لا يوجد Git",
|
||||
"session.new.lastModified": "آخر تعديل",
|
||||
"session.header.search.placeholder": "بحث {{project}}",
|
||||
"session.header.searchFiles": "بحث عن الملفات",
|
||||
|
|
|
|||
|
|
@ -616,6 +616,7 @@ export const dict = {
|
|||
"session.new.workspace.triggerLocal": "Local",
|
||||
"session.new.workspace.local": "Repositório local",
|
||||
"session.new.workspace.existing": "Espaço de trabalho…",
|
||||
"session.new.git.none": "Sem Git",
|
||||
"session.new.lastModified": "Última modificação",
|
||||
"session.header.search.placeholder": "Buscar {{project}}",
|
||||
"session.header.searchFiles": "Buscar arquivos",
|
||||
|
|
|
|||
|
|
@ -672,6 +672,7 @@ export const dict = {
|
|||
"session.new.workspace.triggerLocal": "Lokalno",
|
||||
"session.new.workspace.local": "Lokalni repozitorij",
|
||||
"session.new.workspace.existing": "Radni prostor…",
|
||||
"session.new.git.none": "Nema Gita",
|
||||
"session.new.lastModified": "Posljednja izmjena",
|
||||
|
||||
"session.header.search.placeholder": "Pretraži {{project}}",
|
||||
|
|
|
|||
|
|
@ -667,6 +667,7 @@ export const dict = {
|
|||
"session.new.workspace.triggerLocal": "Lokal",
|
||||
"session.new.workspace.local": "Lokalt repository",
|
||||
"session.new.workspace.existing": "Arbejdsområde…",
|
||||
"session.new.git.none": "Ingen Git",
|
||||
"session.new.lastModified": "Sidst ændret",
|
||||
|
||||
"session.header.search.placeholder": "Søg {{project}}",
|
||||
|
|
|
|||
|
|
@ -625,6 +625,7 @@ export const dict = {
|
|||
"session.new.workspace.triggerLocal": "Lokal",
|
||||
"session.new.workspace.local": "Lokales Repository",
|
||||
"session.new.workspace.existing": "Arbeitsbereich…",
|
||||
"session.new.git.none": "Kein Git",
|
||||
"session.new.lastModified": "Zuletzt geändert",
|
||||
"session.header.search.placeholder": "{{project}} durchsuchen",
|
||||
"session.header.searchFiles": "Dateien suchen",
|
||||
|
|
|
|||
|
|
@ -102,6 +102,7 @@ export const dict = {
|
|||
"dialog.provider.empty": "No providers found",
|
||||
"dialog.provider.group.popular": "Popular",
|
||||
"dialog.provider.group.other": "Other",
|
||||
"dialog.provider.custom.label": "Custom OpenAI-compatible provider",
|
||||
"dialog.provider.tag.recommended": "Recommended",
|
||||
"dialog.provider.opencode.note": "Curated models including Claude, GPT, Gemini and more",
|
||||
"dialog.provider.opencode.tagline": "Reliable optimized models",
|
||||
|
|
@ -122,6 +123,7 @@ export const dict = {
|
|||
|
||||
"dialog.model.unpaid.freeModels.title": "Free models provided by OpenCode",
|
||||
"dialog.model.unpaid.addMore.title": "Add more models from popular providers",
|
||||
"dialog.model.unpaid.viewMoreProviders": "See 70+ more providers",
|
||||
|
||||
"dialog.provider.viewAll": "Show more providers",
|
||||
|
||||
|
|
@ -694,6 +696,7 @@ export const dict = {
|
|||
"session.new.workspace.triggerLocal": "Local",
|
||||
"session.new.workspace.local": "Local repository",
|
||||
"session.new.workspace.existing": "Workspace…",
|
||||
"session.new.git.none": "No Git",
|
||||
"session.new.lastModified": "Last modified",
|
||||
|
||||
"session.header.search.placeholder": "Search {{project}}",
|
||||
|
|
|
|||
|
|
@ -673,6 +673,7 @@ export const dict = {
|
|||
"session.new.workspace.triggerLocal": "Local",
|
||||
"session.new.workspace.local": "Repositorio local",
|
||||
"session.new.workspace.existing": "Espacio de trabajo…",
|
||||
"session.new.git.none": "Sin Git",
|
||||
"session.new.lastModified": "Última modificación",
|
||||
|
||||
"session.header.search.placeholder": "Buscar {{project}}",
|
||||
|
|
|
|||
|
|
@ -621,6 +621,7 @@ export const dict = {
|
|||
"session.new.workspace.triggerLocal": "Local",
|
||||
"session.new.workspace.local": "Dépôt local",
|
||||
"session.new.workspace.existing": "Espace de travail…",
|
||||
"session.new.git.none": "Pas de Git",
|
||||
"session.new.lastModified": "Dernière modification",
|
||||
"session.header.search.placeholder": "Rechercher {{project}}",
|
||||
"session.header.searchFiles": "Rechercher des fichiers",
|
||||
|
|
|
|||
|
|
@ -612,6 +612,7 @@ export const dict = {
|
|||
"session.new.workspace.triggerLocal": "ローカル",
|
||||
"session.new.workspace.local": "ローカルリポジトリ",
|
||||
"session.new.workspace.existing": "ワークスペース…",
|
||||
"session.new.git.none": "Git なし",
|
||||
"session.new.lastModified": "最終更新",
|
||||
"session.header.search.placeholder": "{{project}}を検索",
|
||||
"session.header.searchFiles": "ファイルを検索",
|
||||
|
|
|
|||
|
|
@ -970,6 +970,7 @@ export const dict = {
|
|||
"session.new.workspace.triggerLocal": "로컬",
|
||||
"session.new.workspace.local": "로컬 저장소",
|
||||
"session.new.workspace.existing": "작업 공간…",
|
||||
"session.new.git.none": "Git 없음",
|
||||
|
||||
"sidebar.empty.title": "열린 프로젝트 없음",
|
||||
"sidebar.empty.description": "프로젝트를 열어 시작하세요",
|
||||
|
|
|
|||
|
|
@ -1064,6 +1064,7 @@ export const dict = {
|
|||
"session.new.workspace.triggerLocal": "Lokalt",
|
||||
"session.new.workspace.local": "Lokalt depot",
|
||||
"session.new.workspace.existing": "Arbeidsområde…",
|
||||
"session.new.git.none": "Ingen Git",
|
||||
|
||||
"sidebar.empty.title": "Ingen åpne prosjekter",
|
||||
"sidebar.empty.description": "Åpne et prosjekt for å komme i gang",
|
||||
|
|
|
|||
|
|
@ -616,6 +616,7 @@ export const dict = {
|
|||
"session.new.workspace.triggerLocal": "Lokalnie",
|
||||
"session.new.workspace.local": "Lokalne repozytorium",
|
||||
"session.new.workspace.existing": "Przestrzeń robocza…",
|
||||
"session.new.git.none": "Brak Git",
|
||||
"session.new.lastModified": "Ostatnio zmodyfikowano",
|
||||
"session.header.search.placeholder": "Szukaj {{project}}",
|
||||
"session.header.searchFiles": "Szukaj plików",
|
||||
|
|
|
|||
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Add a link
Reference in a new issue