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https://github.com/anomalyco/opencode.git
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Compare commits
4
Commits
| Author | SHA1 | Date | |
|---|---|---|---|
 Kit Langtonand𝓛𝓲𝓽𝓽𝓵𝓮 𝓕𝓻𝓪𝓷𝓴
|
13ef9924fa | ||
|
Kit Langtonand𝓛𝓲𝓽𝓽𝓵𝓮 𝓕𝓻𝓪𝓷𝓴
|
746f941b40 | ||
|
Kit Langtonand𝓛𝓲𝓽𝓽𝓵𝓮 𝓕𝓻𝓪𝓷𝓴
|
4df54601df | ||
|
Kit Langtonand𝓛𝓲𝓽𝓽𝓵𝓮 𝓕𝓻𝓪𝓷𝓴
|
e2614f2be4 |
@@ -1,7 +1,5 @@
|
||||
---
|
||||
"@opencode-ai/client": patch
|
||||
"@opencode-ai/protocol": patch
|
||||
"@opencode-ai/cli": patch
|
||||
---
|
||||
|
||||
Expose background-service lifecycle status, preserve one process-held owner through startup and failure, reconnect TUIs without activating replacement, and stop exact service instances gracefully.
|
||||
Reuse a same-version background service when a repeated health probe succeeds instead of replacing an endpoint another client may already be using.
|
||||
|
||||
@@ -1,5 +0,0 @@
|
||||
---
|
||||
"@opencode-ai/cli": patch
|
||||
---
|
||||
|
||||
Expose a TUI plugin slot at the top of the session view.
|
||||
@@ -1,7 +0,0 @@
|
||||
---
|
||||
"@opencode-ai/client": patch
|
||||
"@opencode-ai/plugin": patch
|
||||
"@opencode-ai/protocol": patch
|
||||
---
|
||||
|
||||
Expose transient, read-only session generation through the HTTP API, generated clients, and V2 plugin session context.
|
||||
@@ -1,5 +0,0 @@
|
||||
---
|
||||
"@opencode-ai/cli": patch
|
||||
---
|
||||
|
||||
Expose a TUI plugin slot above the session composer.
|
||||
@@ -1,3 +1,2 @@
|
||||
packages/core/migration/**/snapshot.json linguist-generated
|
||||
packages/core/src/database/migration.gen.ts linguist-generated
|
||||
packages/core/src/**/*.txt text eol=lf
|
||||
|
||||
@@ -18,4 +18,4 @@ simonklee
|
||||
Slickstef11
|
||||
usrnk1
|
||||
vimtor
|
||||
StarpTech
|
||||
starptech
|
||||
|
||||
@@ -90,18 +90,11 @@ jobs:
|
||||
opencode-app-id: ${{ vars.OPENCODE_APP_ID }}
|
||||
opencode-app-secret: ${{ secrets.OPENCODE_APP_SECRET }}
|
||||
|
||||
- name: Build legacy CLI
|
||||
if: github.ref_name != 'v2'
|
||||
run: ./packages/opencode/script/build.ts ${{ (github.ref_name == 'beta' && '--sourcemaps') || '' }}
|
||||
env:
|
||||
OPENCODE_VERSION: ${{ needs.version.outputs.version }}
|
||||
OPENCODE_RELEASE: ${{ needs.version.outputs.release }}
|
||||
GH_REPO: ${{ needs.version.outputs.repo }}
|
||||
GH_TOKEN: ${{ steps.committer.outputs.token }}
|
||||
|
||||
- name: Build preview CLI
|
||||
- name: Build
|
||||
id: build
|
||||
run: ./packages/cli/script/build.ts ${{ (github.ref_name == 'beta' && '--sourcemaps') || '' }}
|
||||
run: |
|
||||
./packages/opencode/script/build.ts ${{ (github.ref_name == 'beta' && '--sourcemaps') || '' }}
|
||||
./packages/cli/script/build.ts ${{ (github.ref_name == 'beta' && '--sourcemaps') || '' }}
|
||||
env:
|
||||
OPENCODE_VERSION: ${{ needs.version.outputs.version }}
|
||||
OPENCODE_RELEASE: ${{ needs.version.outputs.release }}
|
||||
@@ -109,7 +102,6 @@ jobs:
|
||||
GH_TOKEN: ${{ steps.committer.outputs.token }}
|
||||
|
||||
- uses: actions/upload-artifact@ea165f8d65b6e75b540449e92b4886f43607fa02 # v4.6.2
|
||||
if: github.ref_name != 'v2'
|
||||
with:
|
||||
name: opencode-cli
|
||||
path: |
|
||||
@@ -117,7 +109,6 @@ jobs:
|
||||
packages/opencode/dist/opencode-linux*
|
||||
|
||||
- uses: actions/upload-artifact@ea165f8d65b6e75b540449e92b4886f43607fa02 # v4.6.2
|
||||
if: github.ref_name != 'v2'
|
||||
with:
|
||||
name: opencode-cli-windows
|
||||
path: packages/opencode/dist/opencode-windows*
|
||||
@@ -130,55 +121,6 @@ jobs:
|
||||
outputs:
|
||||
version: ${{ needs.version.outputs.version }}
|
||||
|
||||
build-node-cli:
|
||||
needs: version
|
||||
if: github.repository == 'anomalyco/opencode'
|
||||
strategy:
|
||||
fail-fast: false
|
||||
matrix:
|
||||
settings:
|
||||
- target: linux-arm64
|
||||
host: blacksmith-4vcpu-ubuntu-2404-arm
|
||||
- target: linux-x64
|
||||
host: blacksmith-4vcpu-ubuntu-2404
|
||||
- target: darwin-arm64
|
||||
host: macos-26
|
||||
- target: windows-arm64
|
||||
host: blacksmith-4vcpu-windows-2025
|
||||
- target: windows-x64
|
||||
host: blacksmith-4vcpu-windows-2025
|
||||
runs-on: ${{ matrix.settings.host }}
|
||||
defaults:
|
||||
run:
|
||||
shell: bash
|
||||
steps:
|
||||
- uses: actions/checkout@f43a0e5ff2bd294095638e18286ca9a3d1956744 # v3.6.0
|
||||
|
||||
- uses: ./.github/actions/setup-bun
|
||||
with:
|
||||
install-flags: --os=* --cpu=*
|
||||
|
||||
- uses: actions/setup-node@49933ea5288caeca8642d1e84afbd3f7d6820020 # v4.4.0
|
||||
with:
|
||||
node-version: "26.4.0"
|
||||
|
||||
- name: Build
|
||||
run: bun packages/cli/script/build-node.ts --target=${{ matrix.settings.target }} --skip-install --outdir=dist/node
|
||||
env:
|
||||
OPENCODE_VERSION: ${{ needs.version.outputs.version }}
|
||||
OPENCODE_RELEASE: ${{ needs.version.outputs.release }}
|
||||
|
||||
- name: Verify service lifecycle
|
||||
if: matrix.settings.target != 'windows-arm64'
|
||||
working-directory: packages/cli
|
||||
run: bun run script/service-smoke.ts --node
|
||||
|
||||
- uses: actions/upload-artifact@ea165f8d65b6e75b540449e92b4886f43607fa02 # v4.6.2
|
||||
with:
|
||||
name: opencode-node-cli-${{ matrix.settings.target }}
|
||||
path: packages/cli/dist/node/cli-node-*
|
||||
if-no-files-found: error
|
||||
|
||||
sign-cli-windows:
|
||||
needs:
|
||||
- build-cli
|
||||
@@ -471,7 +413,6 @@ jobs:
|
||||
needs:
|
||||
- version
|
||||
- build-cli
|
||||
- build-node-cli
|
||||
- sign-cli-windows
|
||||
- build-electron
|
||||
if: always() && !failure() && !cancelled()
|
||||
@@ -500,13 +441,11 @@ jobs:
|
||||
registry-url: "https://registry.npmjs.org"
|
||||
|
||||
- uses: actions/download-artifact@d3f86a106a0bac45b974a628896c90dbdf5c8093 # v4.3.0
|
||||
if: github.ref_name != 'v2'
|
||||
with:
|
||||
name: opencode-cli
|
||||
path: packages/opencode/dist
|
||||
|
||||
- uses: actions/download-artifact@d3f86a106a0bac45b974a628896c90dbdf5c8093 # v4.3.0
|
||||
if: github.ref_name != 'v2'
|
||||
with:
|
||||
name: opencode-cli-windows
|
||||
path: packages/opencode/dist
|
||||
@@ -522,12 +461,6 @@ jobs:
|
||||
name: opencode-preview-cli
|
||||
path: packages/cli/dist
|
||||
|
||||
- uses: actions/download-artifact@d3f86a106a0bac45b974a628896c90dbdf5c8093 # v4.3.0
|
||||
with:
|
||||
pattern: opencode-node-cli-*
|
||||
path: packages/cli/dist/node
|
||||
merge-multiple: true
|
||||
|
||||
- uses: actions/download-artifact@d3f86a106a0bac45b974a628896c90dbdf5c8093 # v4.3.0
|
||||
if: needs.version.outputs.release
|
||||
with:
|
||||
|
||||
@@ -70,38 +70,11 @@ jobs:
|
||||
env:
|
||||
OPENCODE_EXPERIMENTAL_DISABLE_FILEWATCHER: ${{ runner.os == 'Windows' && 'true' || 'false' }}
|
||||
|
||||
- name: Verify compiled service lifecycle
|
||||
if: always()
|
||||
timeout-minutes: 10
|
||||
working-directory: packages/cli
|
||||
run: |
|
||||
bun run script/build.ts --single --skip-install
|
||||
bun run script/service-smoke.ts
|
||||
|
||||
- name: Setup Node build runtime
|
||||
if: always()
|
||||
uses: actions/setup-node@49933ea5288caeca8642d1e84afbd3f7d6820020 # v4.4.0
|
||||
with:
|
||||
node-version: "26.4.0"
|
||||
|
||||
- name: Verify Node build
|
||||
if: always()
|
||||
timeout-minutes: 15
|
||||
working-directory: packages/cli
|
||||
run: |
|
||||
bun run script/build-node.ts --single --skip-install --outdir=dist/node
|
||||
bun run script/service-smoke.ts --node
|
||||
|
||||
- name: Check generated client
|
||||
if: runner.os == 'Linux'
|
||||
working-directory: packages/client
|
||||
run: bun run check:generated
|
||||
|
||||
- name: Check generated documentation
|
||||
if: runner.os == 'Linux'
|
||||
working-directory: packages/docs
|
||||
run: bun run check:generated
|
||||
|
||||
e2e:
|
||||
name: e2e (${{ matrix.settings.name }})
|
||||
if: github.ref_name != 'v2' && github.head_ref != 'v2'
|
||||
|
||||
@@ -11,7 +11,6 @@ node_modules
|
||||
playground
|
||||
tmp
|
||||
dist
|
||||
dist-node
|
||||
ts-dist
|
||||
.turbo
|
||||
.typecheck-profiles
|
||||
@@ -26,7 +25,6 @@ Session.vim
|
||||
a.out
|
||||
target
|
||||
.scripts
|
||||
.cache
|
||||
.direnv/
|
||||
|
||||
# Local dev files
|
||||
|
||||
@@ -1,6 +1,6 @@
|
||||
---
|
||||
description: translate English to other languages
|
||||
model: opencode/gpt-5.6-sol
|
||||
model: opencode/claude-opus-4-8
|
||||
---
|
||||
|
||||
run git diff and translate changed english doc and UI copy files to other international languages. Translate all languages in parallel to save time.
|
||||
|
||||
@@ -19,6 +19,8 @@ Valid types are `feat`, `fix`, `docs`, `chore`, `refactor`, and `test`. Scopes a
|
||||
|
||||
Examples: `fix(tui): simplify thinking toggle styling`, `docs: update contributing guide`, `chore(sdk): regenerate types`.
|
||||
|
||||
Never bypass Git hooks. Do not use `--no-verify` or otherwise disable, skip, or circumvent commit or push hooks. If a hook fails, fix the failure or stop and report it to the user.
|
||||
|
||||
## Style Guide
|
||||
|
||||
### General Principles
|
||||
|
||||
@@ -1,685 +0,0 @@
|
||||
# Service Lifecycle: Election, Restart, and Reconnect
|
||||
|
||||
Status: in progress
|
||||
|
||||
Incident: [#36688](https://github.com/anomalyco/opencode/issues/36688)
|
||||
|
||||
## Summary
|
||||
|
||||
The managed V2 service keeps its current update policy: the background updater
|
||||
may install a new package, but only a freshly launched TUI activates that update
|
||||
after finding an older running service. Existing TUIs never replace a service;
|
||||
they only reconnect.
|
||||
|
||||
The restart path changes in three places:
|
||||
|
||||
1. A process-held OS lock, not the HTTP port or registration file, elects
|
||||
exactly one server owner for its lifetime.
|
||||
2. The elected process binds and registers a minimal lifecycle surface before
|
||||
it initializes the application, so clients can distinguish a slow winner
|
||||
from an absent server.
|
||||
3. TUIs rediscover and reconnect indefinitely. Transport loss is never a
|
||||
terminal error by itself.
|
||||
|
||||
Several clients may spawn small contenders during a restart. This is safe and
|
||||
intentional: one contender acquires the lock and initializes, while every loser
|
||||
exits before expensive server boot. The design does not require clients to
|
||||
agree on a single initiator.
|
||||
|
||||
This proposal does not introduce a supervisor process, warm candidate server,
|
||||
protocol negotiation, idle background restart, or general execution-recovery
|
||||
framework.
|
||||
|
||||
## Architecture at a Glance
|
||||
|
||||
```text
|
||||
╭───────────────────╮
|
||||
│ CLI ServiceConfig │
|
||||
╰─────────┬─────────╯
|
||||
│
|
||||
▼
|
||||
╭──────────────────────╮
|
||||
│ CLI ServerConnection │
|
||||
╰───────────┬──────────╯
|
||||
╭──────────────────╰───────────────────╮
|
||||
▼ ▼
|
||||
╭──────────────────────────╮ ╭─────────────────────────╮
|
||||
│ Client Service lifecycle │ │ CLI runPromiseWith seam │
|
||||
╰─────────────┬────────────╯ ╰─────────────┬───────────╯
|
||||
╰─────╮ │
|
||||
▼ ▼
|
||||
╭────────────────────────────╮ ╭─────────────╮
|
||||
│ Background service process │ │ TUI / Solid │
|
||||
╰──────────────┬─────────────╯ ╰──────┬──────╯
|
||||
│ │
|
||||
╰────────────◀────────────────────╯
|
||||
╭───────────────────────╮
|
||||
│ Server HTTP transport │
|
||||
╰───────────┬───────────╯
|
||||
│
|
||||
▼
|
||||
╭──────────────────╮
|
||||
│ Core application │
|
||||
╰──────────────────╯
|
||||
```
|
||||
|
||||
| Owner | Responsibility |
|
||||
| ------------------------------------------------ | --------------------------------------------------------------------------------------------------- |
|
||||
| `packages/client/src/effect/service.ts` | Effect-native discovery, start, and stop lifecycle operations |
|
||||
| `packages/cli/src/services/service-config.ts` | CLI registration path, installed version, and daemon command |
|
||||
| `packages/cli/src/services/server-connection.ts` | Resolve an endpoint and, only for the shared service, grouped reconnect and restart Effects |
|
||||
| `packages/cli/src/server-process.ts` | Daemon election, registration, and server process boot |
|
||||
| `packages/server/src/process.ts` | HTTP lifecycle shell and application transport |
|
||||
| `packages/core` | Application behavior behind the transport |
|
||||
| CLI default handler | Convert lifecycle Effects with the outer `FileSystem` context and pass grouped Promise capabilities |
|
||||
| `packages/tui` Solid client context | Own event-stream reconnect, endpoint replacement, status, and user-triggered restart UI |
|
||||
|
||||
## Implementation Status
|
||||
|
||||
| Area | State |
|
||||
| ------------------------- | --------------------------------------------------------------------- |
|
||||
| Lifetime ownership | Implemented on this branch with a scoped OS lock |
|
||||
| Contender behavior | Implemented; losers exit before the server module is imported |
|
||||
| Registration repair | Implemented; the owner reasserts deleted or corrupt discovery |
|
||||
| Channel isolation | Implemented with no-clobber migration for legacy preview discovery |
|
||||
| Client startup waiting | Implemented; slow winners are not killed and waiting is indefinite |
|
||||
| Lifecycle shell | Implemented; the owner binds and registers before application boot |
|
||||
| Failed-state latching | Implemented; deterministic boot failure stays bound and actionable |
|
||||
| Recovery diagnostics | Implemented; the TUI shows status instead of transport internals |
|
||||
| Cross-platform validation | macOS runtime verified; Linux and Windows run in the unit-test matrix |
|
||||
|
||||
## Context
|
||||
|
||||
The V2 CLI runs a shared managed service that owns Sessions, location graphs,
|
||||
plugins, permissions, and tool execution. The service updater can replace the
|
||||
installed package while the current process continues running the old image.
|
||||
A later TUI launch then detects the version mismatch and replaces the service.
|
||||
|
||||
Incident #36688 showed four failures in that replacement path:
|
||||
|
||||
- Multiple TUIs spawned heavyweight server contenders.
|
||||
- A winner remained unobservable while it cold-booted, so another wave treated
|
||||
it as absent and displaced it.
|
||||
- A fresh TUI exhausted its reconnect budget and crashed with an unhandled
|
||||
transport defect.
|
||||
- A losing contender remained alive and consumed about 1 GB of RSS.
|
||||
|
||||
The `origin/v2` baseline serializes service startup with `EffectFlock`. A
|
||||
contender acquires a three-second heartbeat lease, checks whether another
|
||||
service became discoverable, and only the winner crosses the application-boot
|
||||
boundary. This already prevents simultaneous heavy boots and makes startup
|
||||
losers exit.
|
||||
|
||||
The lease is released immediately after registration, however, so it is not
|
||||
lifetime ownership. Registration then reverts to last-writer-wins authority: a
|
||||
deleted or corrupt registration can admit a second boot, a displaced server
|
||||
terminates itself through its 10-second registration self-check, and a stalled
|
||||
lease holder can be displaced after the three-second service staleness timeout.
|
||||
|
||||
`Flock` and `EffectFlock` live in `packages/core/src/util` and are also used for
|
||||
config writes, MCP auth, npm installs, and repository caching. Despite the
|
||||
name, the primitive is an atomic-mkdir lease with heartbeat and staleness
|
||||
takeover, not an OS-held lock. It remains appropriate for bounded critical
|
||||
sections, including today's startup fence, but is not lifetime service
|
||||
ownership.
|
||||
|
||||
The current implementation also mixes three different concepts:
|
||||
|
||||
- **Ownership:** which process is allowed to be the managed server.
|
||||
- **Discovery:** where clients can reach that process.
|
||||
- **Lifecycle:** whether that process is starting, ready, stopping, or failed.
|
||||
|
||||
This design gives each concept one authority.
|
||||
|
||||
```definitions
|
||||
[
|
||||
{
|
||||
"term": "Owner",
|
||||
"definition": "The one process holding the process-held OS service lock."
|
||||
},
|
||||
{
|
||||
"term": "Contender",
|
||||
"definition": "A small serve process attempting to acquire the service lock. It must not initialize the application before winning."
|
||||
},
|
||||
{
|
||||
"term": "Registration",
|
||||
"definition": "An atomic discovery record containing the elected owner's identity and endpoint. Registration never grants ownership."
|
||||
},
|
||||
{
|
||||
"term": "Lifecycle shell",
|
||||
"definition": "The minimal HTTP surface bound by the elected process before application initialization. It serves health and retryable startup responses."
|
||||
},
|
||||
{
|
||||
"term": "Application",
|
||||
"definition": "The full server routes and global or location-scoped modules used for normal OpenCode work."
|
||||
}
|
||||
]
|
||||
```
|
||||
|
||||
## Goals
|
||||
|
||||
- At most one process initializes and serves the managed application.
|
||||
- Losing contenders exit before database, route, plugin, MCP, or location boot.
|
||||
- A slow winner becomes observable before expensive initialization.
|
||||
- Existing and freshly launched TUIs survive retryable service unavailability.
|
||||
- Reconnect follows service state instead of displaying retry counts or raw
|
||||
transport failures.
|
||||
- Version-mismatch replacement remains triggered by a fresh TUI launch.
|
||||
- A stale or malformed registration cannot create a second owner.
|
||||
- An unresponsive owner is never killed automatically by an arbitrary TUI.
|
||||
- Every spawned contender has a bounded path to ownership or exit.
|
||||
|
||||
## Non-goals
|
||||
|
||||
- Restarting automatically when a background update finds an idle window.
|
||||
- Running old and candidate application servers concurrently.
|
||||
- Adding a permanent steward, proxy, or supervisor process.
|
||||
- Zero-downtime worker handoff or automatic rollback.
|
||||
- Application protocol negotiation or automatic TUI self-restart.
|
||||
- General hard-crash recovery for active Sessions.
|
||||
- Defining recovery semantics for provider attempts, tools, shells, sub-agents,
|
||||
permissions, questions, or background jobs.
|
||||
- Automatically killing a frozen owner.
|
||||
- Bounding concurrent location cold boots after clients reconnect.
|
||||
- Multi-machine or clustered service placement.
|
||||
|
||||
## Invariants
|
||||
|
||||
1. **The service lock is ownership.** Exactly one process may hold the OS lock
|
||||
for one installation channel and service profile.
|
||||
2. **Ownership precedes boot.** A contender performs no expensive application
|
||||
initialization before it acquires the lock.
|
||||
3. **Ownership lasts for the process lifetime.** The owner holds an open lock
|
||||
handle until the managed server exits. The OS releases it on process death
|
||||
without a cleanup callback.
|
||||
4. **The port is transport, not election.** The owner may select a dynamic port
|
||||
after acquiring the lock.
|
||||
5. **Registration is discovery, not election.** Deleting, corrupting, or
|
||||
replacing registration does not invalidate a live owner's lock.
|
||||
6. **Only a fresh launch enforces package version.** Existing TUIs reconnect to
|
||||
the current owner without initiating version replacement.
|
||||
7. **Transport loss is retryable.** It never terminates a TUI without a separate
|
||||
diagnosed, non-retryable cause.
|
||||
8. **Clients do not kill an unresponsive owner automatically.** Destructive
|
||||
recovery requires the explicit `service restart` command.
|
||||
9. **Lifecycle does not promise execution semantics.** Graceful replacement
|
||||
invokes Session suspension and resumption hooks, but tool-level continuity
|
||||
belongs to a separate design.
|
||||
|
||||
## System Model
|
||||
|
||||
```text
|
||||
╭───────────────────────╮ ╭──────────────────────────────╮
|
||||
│ Fresh or existing TUI │ │ Process-held OS service lock │
|
||||
╰───────────┬───────────╯ ╰───────────────┬──────────────╯
|
||||
╰─────┬ normal requests observe ───────────────────────╮ │
|
||||
│ discover │ ├──╯ authorizes one owner
|
||||
▼ │ ▼
|
||||
╭───────────────────╮ │ ╭─────────────────╮
|
||||
│ Registration file │ │ │ Lifecycle shell │
|
||||
╰───────────────────╯ │ ╰────────┬────────╯
|
||||
│ │
|
||||
├────────────────────────╯
|
||||
▼
|
||||
╭──────────────────────╮
|
||||
│ OpenCode application │
|
||||
╰──────────────────────╯
|
||||
```
|
||||
|
||||
The lifecycle shell and application run in the same process. The distinction is
|
||||
initialization order and responsibility, not process topology.
|
||||
|
||||
## Service Status
|
||||
|
||||
The server reports one small status value:
|
||||
|
||||
```typescript
|
||||
type ServiceStatus =
|
||||
| {
|
||||
type: "starting"
|
||||
}
|
||||
| {
|
||||
type: "ready"
|
||||
}
|
||||
| {
|
||||
type: "stopping"
|
||||
targetVersion?: string
|
||||
}
|
||||
| {
|
||||
type: "failed"
|
||||
message: string
|
||||
action: string
|
||||
}
|
||||
```
|
||||
|
||||
The client adds only the discovery states needed by callers:
|
||||
|
||||
```typescript
|
||||
type Status = { type: "missing" } | { type: "unreachable" } | { type: "unresponsive" } | ServiceStatus
|
||||
```
|
||||
|
||||
The health response retains the existing fields for old clients and adds the
|
||||
status discriminant:
|
||||
|
||||
```typescript
|
||||
type ServiceHealth = {
|
||||
healthy: true
|
||||
version: string
|
||||
pid: number
|
||||
instanceID: string
|
||||
status: ServiceStatus
|
||||
}
|
||||
```
|
||||
|
||||
`healthy: true` means the registered lifecycle shell is responding and its
|
||||
identity matches registration. New clients use `status.type === "ready"` as
|
||||
the application-readiness signal.
|
||||
|
||||
During `starting` or `stopping`, application requests are not held in memory.
|
||||
They receive an immediate retryable response:
|
||||
|
||||
```http
|
||||
HTTP/1.1 503 Service Unavailable
|
||||
Retry-After: 1
|
||||
Content-Type: application/json
|
||||
|
||||
{"code":"service_starting"}
|
||||
```
|
||||
|
||||
`stopping` uses `service_stopping`. A failed application boot uses
|
||||
`service_failed` and includes a safe diagnostic message.
|
||||
|
||||
A failed owner remains bound and keeps holding the service lock. Exiting on
|
||||
failure would let every waiting client's `ensureRunning` loop elect a new
|
||||
contender that repeats the same heavy failing boot, so staying bound turns a
|
||||
deterministic boot failure into one observable `failed` state instead of a
|
||||
client-driven respawn loop. Recovery still works: a fresh launch observes the
|
||||
failed instance through the stop path, and explicit `service restart` replaces
|
||||
it.
|
||||
|
||||
## Registration Contract
|
||||
|
||||
Registration contains only discovery identity:
|
||||
|
||||
```typescript
|
||||
type ServiceRegistration = {
|
||||
schema: 1
|
||||
instanceID: string
|
||||
version: string
|
||||
url: string
|
||||
pid: number
|
||||
}
|
||||
```
|
||||
|
||||
Authentication continues to use the existing private service credential
|
||||
storage. The registration schema does not change that policy.
|
||||
|
||||
The owner writes registration only after the lifecycle shell has bound:
|
||||
|
||||
1. Bind the lifecycle shell.
|
||||
2. Write a temporary registration file with mode `0600`.
|
||||
3. Atomically rename it over the old registration.
|
||||
4. Serve lifecycle health as `starting`.
|
||||
|
||||
On shutdown, the owner removes registration only if the current file still has
|
||||
its `instanceID`. An old finalizer can never remove a successor's registration.
|
||||
|
||||
While running, the owner periodically asserts its registration. Because the
|
||||
lock guarantees exactly one live owner, any registration that does not name the
|
||||
owner is stale or corrupt, and the owner rewrites it. A deleted or clobbered
|
||||
registration therefore heals within one assertion interval instead of leaving
|
||||
clients waiting on absent discovery. This inverts today's self-check loop,
|
||||
which terminates the displaced process instead of repairing discovery.
|
||||
|
||||
Legacy registration shapes are decoded by a compatibility adapter. The new
|
||||
domain type does not make fields optional to represent old formats.
|
||||
|
||||
## Election
|
||||
|
||||
This design promotes today's startup fence into lifetime ownership.
|
||||
Last-writer-wins registration is replaced by a process-held OS lock that is
|
||||
acquired before any expensive boot work and held for the entire service
|
||||
lifetime.
|
||||
|
||||
A heartbeat-and-staleness lease, including the existing `Flock` utility, is not
|
||||
sufficient for service ownership: the service configures a three-second stale
|
||||
timeout, after which its lock can be broken and recreated. An event-loop stall,
|
||||
a suspended machine, or a debugger pause can therefore make a live owner appear
|
||||
stale and allow a contender to displace it. Service ownership requires a
|
||||
process-held OS lock: `flock` on Unix and an exclusively bound named pipe on
|
||||
Windows. It cannot be broken because a heartbeat exceeded a timeout. Process
|
||||
death releases the lock through the OS.
|
||||
|
||||
Neither Bun nor Node exposes `flock` directly, the existing `Flock` utility is
|
||||
an mkdir-plus-heartbeat lease rather than an OS-held lock, and the common
|
||||
lockfile packages are staleness-based leases as well. The platform layer uses
|
||||
`bun:ffi` to call `flock` on POSIX and Node's named-pipe server support on
|
||||
Windows, where Bun FFI is not available on every shipped architecture. It lives
|
||||
alongside the existing utility in `packages/core/src/util`. This primitive is
|
||||
the foundation of the design, so the delivery sequence spikes it first.
|
||||
|
||||
```text
|
||||
Contender Lock Lifecycle Application
|
||||
│ │ │ │
|
||||
├─ try acquire ───▶ │ │
|
||||
│ │ │ │
|
||||
╭─ alt: lock held ────────────────────────────────────────────────╮
|
||||
│ │ │ │ │ │
|
||||
│ ◀─ busy ──────────┤ │ │ │
|
||||
│ │ │ │ │ │
|
||||
│ ├─────────╮ │ │ │ │
|
||||
│ │ exit │ │ │ │ │
|
||||
│ ◀─────────╯ │ │ │ │
|
||||
│ │ │ │ │ │
|
||||
├─ else: lock acquired ───────────────────────────────────────────┤
|
||||
│ │ │ │ │ │
|
||||
│ ◀─ owner ─────────┤ │ │ │
|
||||
│ │ │ │ │ │
|
||||
│ ├─ bind, register, starting ────────▶ │ │
|
||||
│ │ │ │ │ │
|
||||
│ ├─ initialize ──────────────────────────────────────────────▶ │
|
||||
│ │ │ │ │ │
|
||||
│╭─ alt: boot succeeds ──────────────────────────────────────────╮│
|
||||
││ │ │ │ │ ││
|
||||
││ │ │ ◀─ ready ───────────────┤ ││
|
||||
││ │ │ │ │ ││
|
||||
│├─ else: boot fails ────────────────────────────────────────────┤│
|
||||
││ │ │ │ │ ││
|
||||
││ │ │ ◀─ failed, stay bound ──┤ ││
|
||||
││ │ │ │ │ ││
|
||||
│╰───────────────────────────────────────────────────────────────╯│
|
||||
│ │ │ │ │ │
|
||||
╰─────────────────────────────────────────────────────────────────╯
|
||||
│ │ │ │
|
||||
```
|
||||
|
||||
Lock acquisition by a contender is nonblocking or tightly bounded. A loser
|
||||
must exit before constructing application routes or importing startup-heavy
|
||||
modules.
|
||||
|
||||
Several clients may spawn contenders concurrently. The design guarantees one
|
||||
heavy winner, not one process spawn. If the winner crashes during startup, the
|
||||
OS releases the lock and a later client retry starts another election.
|
||||
|
||||
The lock is scoped by installation channel and service profile. Local, preview,
|
||||
and stable installations cannot displace one another.
|
||||
|
||||
## Update Activation
|
||||
|
||||
Background update behavior remains unchanged:
|
||||
|
||||
1. The running service checks for an update.
|
||||
2. The updater installs the package in the background.
|
||||
3. The running process continues using its existing process image.
|
||||
4. No idle check or automatic restart occurs.
|
||||
|
||||
A fresh TUI launch activates the installed update:
|
||||
|
||||
1. Read registration and authenticate the responding service.
|
||||
2. If its package version matches the fresh client, attach normally.
|
||||
3. If the version differs, request graceful stop of that exact registered
|
||||
instance using the existing authenticated stop path.
|
||||
4. Re-check instance identity before every signal or escalation in that path.
|
||||
5. Wait for the old process to exit and release the service lock.
|
||||
6. Call `ensureRunning` until a compatible service becomes ready.
|
||||
|
||||
Concurrent fresh launchers may all observe the same old instance. Stopping that
|
||||
exact instance must be idempotent. Once registration names a different instance,
|
||||
a stale launcher stops signaling and returns to discovery.
|
||||
|
||||
No durable restart-transition record is introduced. The initiating fresh TUI
|
||||
already knows the source and target versions and can display its update
|
||||
preflight. Existing TUIs may display `Updating...` if they observed `stopping`;
|
||||
otherwise `Waiting for background service...` is the honest fallback.
|
||||
|
||||
## Fresh Launch Versus Reconnect
|
||||
|
||||
Fresh launch and reconnect deliberately have different version policies:
|
||||
|
||||
```typescript
|
||||
type ManagedConnection =
|
||||
| {
|
||||
type: "launch"
|
||||
requiredVersion: string
|
||||
}
|
||||
| {
|
||||
type: "reconnect"
|
||||
}
|
||||
```
|
||||
|
||||
- `launch` requires the installed package version and may activate replacement.
|
||||
- `reconnect` accepts the current owner and never activates replacement.
|
||||
|
||||
This preserves today's permissive reconnect behavior. Explicit application
|
||||
protocol negotiation and automatic TUI re-exec remain follow-ups.
|
||||
|
||||
## Client Reconnect
|
||||
|
||||
Fresh and existing TUIs use the same status loop after startup:
|
||||
|
||||
1. Read registration on every attempt. Do not retry a stale URL indefinitely.
|
||||
2. If registration is absent, call `ensureRunning` and continue waiting.
|
||||
3. If registration is unreachable, call `ensureRunning`. A live owner prevents
|
||||
contenders from acquiring the lock; a dead owner does not.
|
||||
4. If status is `starting` or `stopping`, wait.
|
||||
5. If status is `failed`, show its actionable message.
|
||||
6. If status is `ready`, rebuild HTTP and event-stream clients for the new
|
||||
endpoint and perform authoritative state reconciliation.
|
||||
|
||||
Retry cadence is internal policy. Retry counts are telemetry, not user-facing
|
||||
state. The TUI waits until the service is ready or the user exits.
|
||||
|
||||
Transport failures are handled at the TUI run boundary. A raw client transport
|
||||
error or Effect defect must not escape to the terminal. Hard exit is reserved
|
||||
for diagnosed causes such as invalid local configuration, failed authentication,
|
||||
or a foreign process occupying an explicitly configured port.
|
||||
|
||||
The UI derives text from status:
|
||||
|
||||
| Status | User-facing state |
|
||||
| ------------------------ | ----------------------------------- |
|
||||
| No registration | `Starting background service...` |
|
||||
| Registration unreachable | `Waiting for background service...` |
|
||||
| `starting` | `Starting OpenCode vX...` |
|
||||
| `stopping` | `Updating to vX...` |
|
||||
| `failed` | Actionable failure message |
|
||||
| `ready` | Normal TUI |
|
||||
|
||||
## Graceful Session Continuity
|
||||
|
||||
Version-mismatch replacement uses the existing graceful Session suspension and
|
||||
resumption hooks:
|
||||
|
||||
1. The old server snapshots active Session IDs during graceful teardown.
|
||||
2. The successor schedules those Sessions for continuation.
|
||||
3. The runner reloads durable Session history before continuing.
|
||||
|
||||
This lifecycle design does not define what an interrupted physical provider
|
||||
attempt or tool invocation means. It does not promise that external side effects
|
||||
did not occur, replay the exact interrupted tool, preserve an in-memory form, or
|
||||
recover process-local background work.
|
||||
|
||||
Those concerns require a separate execution-continuity design covering tools,
|
||||
shells, sub-agents, permissions, questions, provider attempts, and hard-crash
|
||||
recovery.
|
||||
|
||||
## Unresponsive Owner
|
||||
|
||||
An unreachable registration does not prove that the owner is dead. A contender
|
||||
attempts the service lock:
|
||||
|
||||
- If the lock is free, the contender starts a replacement.
|
||||
- If the lock is held, the contender exits and the client keeps waiting.
|
||||
|
||||
After a bounded diagnostic threshold, the client may show:
|
||||
|
||||
```text
|
||||
The background service owns the service lock but is not responding.
|
||||
Run `opencode service restart` to recover it.
|
||||
```
|
||||
|
||||
Only explicit `service restart` may perform destructive recovery. It verifies
|
||||
the complete registration and process instance before signaling, waits for
|
||||
graceful exit, re-checks identity before escalation, and refuses to kill a
|
||||
process it cannot positively identify.
|
||||
|
||||
Automatic frozen-owner recovery is deferred.
|
||||
|
||||
## Failure Walkthroughs
|
||||
|
||||
### Update with open TUIs
|
||||
|
||||
1. The old service installs vNext but keeps running.
|
||||
2. A fresh vNext TUI finds the healthy vOld service and requests graceful stop.
|
||||
3. The old service reports `stopping`, suspends active Sessions, and exits.
|
||||
4. Open TUIs enter their indefinite status loops.
|
||||
5. One or more clients spawn contenders.
|
||||
6. One contender acquires the service lock. Losers exit before heavy boot.
|
||||
7. The winner binds and registers the lifecycle shell as `starting`.
|
||||
8. Clients stop spawning and wait on the observable winner.
|
||||
9. The winner initializes the application and reports `ready`.
|
||||
10. TUIs rebuild clients, reconcile state, and resume.
|
||||
|
||||
### Server crashes while ready
|
||||
|
||||
1. The endpoint becomes unreachable and registration may remain stale.
|
||||
2. Clients call `ensureRunning`.
|
||||
3. Process death has released the service lock.
|
||||
4. One contender wins, replaces registration, and starts normally.
|
||||
5. Detailed active-execution recovery is outside this design.
|
||||
|
||||
### Winner crashes during startup
|
||||
|
||||
1. Clients observed `starting` and remain alive.
|
||||
2. Process death releases the service lock.
|
||||
3. A later reconnect attempt starts another election.
|
||||
4. One new contender wins; all other contenders exit.
|
||||
|
||||
### Registration is deleted while the owner is healthy
|
||||
|
||||
1. Clients may call `ensureRunning` because discovery is absent.
|
||||
2. Every contender fails to acquire the owner's lock and exits.
|
||||
3. No second application initializes.
|
||||
4. The owner's next registration assertion republishes discovery.
|
||||
|
||||
### Owner is alive but unresponsive
|
||||
|
||||
1. Health fails, but the process still holds the service lock.
|
||||
2. Contenders fail lock acquisition and exit.
|
||||
3. Clients wait and eventually show explicit recovery guidance.
|
||||
4. No TUI kills the owner automatically.
|
||||
|
||||
## TDD Verification
|
||||
|
||||
Implementation should proceed test-first with real subprocesses and real locks.
|
||||
Mocks cannot establish process death, lock release, loser cleanup, or port
|
||||
behavior.
|
||||
|
||||
### Election tests
|
||||
|
||||
| Scenario | Required result |
|
||||
| ----------------------------------------------------- | ------------------------------------------------------- |
|
||||
| Ten contenders start simultaneously | Exactly one crosses the application-boot boundary |
|
||||
| Winner pauses after lock acquisition | No loser initializes or remains alive |
|
||||
| Winner event loop pauses beyond the old stale timeout | Ownership is not displaced |
|
||||
| Winner crashes before bind | Lock releases; a later attempt wins |
|
||||
| Winner crashes after bind but before registration | Lock releases; a later attempt replaces stale discovery |
|
||||
| Registration is deleted while owner runs | No second owner initializes |
|
||||
| Registration is malformed | Lock still prevents a second owner |
|
||||
| Registration names a dead PID | New contender can acquire the released lock |
|
||||
| Two installation channels start | Each elects an independent owner |
|
||||
| Explicit configured port is foreign-owned | Fail diagnostically; do not kill the foreign process |
|
||||
|
||||
The fixture records a marker immediately before application initialization. The
|
||||
tests assert that only one process writes that marker and that every loser exits
|
||||
within a bounded interval. The harness should also assert that a loser's peak
|
||||
RSS stays an order of magnitude below an application boot, since import weight
|
||||
was the observed incident cost.
|
||||
|
||||
### Lifecycle tests
|
||||
|
||||
| Scenario | Required result |
|
||||
| ----------------------------------------------- | ---------------------------------------------------------------- |
|
||||
| Winner owns lock but application boot is paused | Health reports `starting` |
|
||||
| Application request arrives during startup | Immediate retryable `503` |
|
||||
| Application becomes ready | Status changes once from `starting` to `ready` |
|
||||
| Graceful replacement begins | Status reports `stopping` before disconnect |
|
||||
| Application initialization fails | Actionable `failed` status; owner stays bound and holds the lock |
|
||||
| Registration is deleted while owner runs | Owner republishes it within one assertion interval |
|
||||
| Owner exits | Registration is removed only if it still names that owner |
|
||||
|
||||
### Update tests
|
||||
|
||||
| Scenario | Required result |
|
||||
| -------------------------------------- | -------------------------------------------------------- |
|
||||
| Background update installs vNext | Running vOld service does not restart |
|
||||
| Fresh vNext launch finds vOld | Exact old instance stops; vNext eventually becomes ready |
|
||||
| Two fresh vNext launches race | One heavy successor; both clients attach |
|
||||
| Existing vOld TUI reconnects to vNext | It never requests replacement |
|
||||
| Stale launcher observes a new instance | It does not signal the new instance |
|
||||
|
||||
### Reconnect tests
|
||||
|
||||
| Scenario | Required result |
|
||||
| --------------------------------------------------- | -------------------------------------------------- |
|
||||
| Endpoint disappears and changes port | TUI rediscovers and rebuilds clients |
|
||||
| Service remains unavailable beyond old retry budget | TUI remains alive |
|
||||
| Event stream reconnects | Client performs authoritative state reconciliation |
|
||||
| Transport returns an unexpected defect | TUI formats it; no raw stack escapes |
|
||||
| Owner remains unresponsive | TUI waits and shows explicit restart guidance |
|
||||
|
||||
## Delivery Sequence
|
||||
|
||||
1. **Spike the lock primitive.** Prove a nonblocking, process-held OS lock
|
||||
under Bun on macOS, Linux, and Windows (`bun:ffi` to `flock` on POSIX and a
|
||||
named pipe on Windows), including release on hard kill and behavior across
|
||||
containers and network filesystems used in CI.
|
||||
2. **Expand the subprocess test harness.** Begin from the baseline
|
||||
two-contender test and cover ten contenders, lock release on crash, a paused
|
||||
winner, deleted or corrupt registration, and bounded loser exit before
|
||||
changing ownership.
|
||||
3. **Contain client failure.** Make transport loss nonterminal, rediscover on
|
||||
every cycle, and format unexpected failures at the TUI boundary.
|
||||
4. **Promote the startup fence to process-held ownership.** Preserve the
|
||||
existing pre-boot acquisition seam, replace its lease with the OS lock, hold
|
||||
it until process exit, and invert the registration self-check from
|
||||
self-termination to reassertion.
|
||||
5. **Bind the lifecycle shell first.** Publish registration and `starting`,
|
||||
return retryable `503` for application requests, then initialize the app.
|
||||
The health contract change is public API: regenerate clients from
|
||||
`packages/client` with `bun run generate`.
|
||||
6. **Codify launch versus reconnect.** Fresh launch enforces installed version;
|
||||
reconnect never activates replacement.
|
||||
7. **Integrate graceful replacement.** Preserve current background-install and
|
||||
fresh-launch activation behavior while invoking Session continuity hooks.
|
||||
8. **Harden explicit recovery.** Verify exact process identity during explicit
|
||||
`service restart`; never automatically kill an unresponsive owner.
|
||||
9. **Run the full multi-process suite.** Include repeated restart cycles and
|
||||
assert that no contender or child process remains afterward.
|
||||
|
||||
## Acceptance Criteria
|
||||
|
||||
- Ten concurrent restart observers produce one application initialization.
|
||||
- No losing contender survives or builds a location graph.
|
||||
- A 30-second application boot remains continuously observable as `starting`.
|
||||
- A TUI remains alive through a service outage longer than the previous retry
|
||||
budget.
|
||||
- A service endpoint change does not require restarting an existing TUI.
|
||||
- Background installation alone does not restart the service.
|
||||
- A fresh mismatched TUI eventually attaches to the installed service version.
|
||||
- Existing reconnecting TUIs never replace the current owner.
|
||||
- Registration corruption cannot produce two owners.
|
||||
- A deleted registration heals without restarting the owner or any client.
|
||||
- An unresponsive owner is not killed without an explicit recovery command.
|
||||
- Raw transport defects never escape to the terminal.
|
||||
|
||||
## Follow-ups
|
||||
|
||||
- Idle background update activation with an admission fence.
|
||||
- Application protocol compatibility and automatic local TUI re-exec.
|
||||
- Durable execution recovery for provider attempts and tools.
|
||||
- Shell, sub-agent, permission, question, and background-job continuity.
|
||||
- Automatic recovery for a positively identified frozen owner.
|
||||
- Cold-boot concurrency limits and interaction-prioritized location loading.
|
||||
- A steward or socket-handoff architecture if zero-downtime replacement becomes
|
||||
a real requirement.
|
||||
@@ -8,25 +8,6 @@ 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",
|
||||
|
||||
+33
-66
@@ -8,8 +8,6 @@
|
||||
makeWrapper,
|
||||
writableTmpDirAsHomeHook,
|
||||
autoPatchelfHook,
|
||||
copyDesktopItems,
|
||||
makeDesktopItem,
|
||||
opencode,
|
||||
}:
|
||||
let
|
||||
@@ -29,12 +27,9 @@ stdenv.mkDerivation (finalAttrs: {
|
||||
nodejs
|
||||
makeWrapper
|
||||
writableTmpDirAsHomeHook
|
||||
]
|
||||
++ lib.optionals stdenv.hostPlatform.isLinux [
|
||||
] ++ lib.optionals stdenv.hostPlatform.isLinux [
|
||||
autoPatchelfHook
|
||||
copyDesktopItems
|
||||
]
|
||||
++ lib.optionals stdenv.hostPlatform.isDarwin [
|
||||
] ++ lib.optionals stdenv.hostPlatform.isDarwin [
|
||||
# Ad-hoc sign the .app: --config.mac.identity=null below skips signing.
|
||||
darwin.autoSignDarwinBinariesHook
|
||||
];
|
||||
@@ -43,37 +38,20 @@ 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";
|
||||
};
|
||||
|
||||
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" "'$out/opt/opencode-desktop/resources'"
|
||||
done
|
||||
'';
|
||||
# https://github.com/electron/electron/issues/31121
|
||||
# mac builds use a .app bundle which doesnt have this issue
|
||||
postPatch = lib.optionalString stdenv.isLinux ''
|
||||
BASE_PATH=packages/desktop
|
||||
FILES=(src/main/windows.ts)
|
||||
for file in "''${FILES[@]}"; do
|
||||
substituteInPlace $BASE_PATH/$file \
|
||||
--replace-fail "process.resourcesPath" "'$out/opt/opencode-desktop/resources'"
|
||||
done
|
||||
'';
|
||||
|
||||
preBuild = ''
|
||||
cp -r "${electron.dist}" $HOME/.electron-dist
|
||||
@@ -98,38 +76,27 @@ 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*} $out/opt/opencode-desktop
|
||||
install -Dm644 resources/icons/32x32.png \
|
||||
"$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
|
||||
'';
|
||||
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
|
||||
'';
|
||||
|
||||
autoPatchelfIgnoreMissingDeps = [
|
||||
"libc.musl-x86_64.so.1"
|
||||
|
||||
+4
-4
@@ -1,8 +1,8 @@
|
||||
{
|
||||
"nodeModules": {
|
||||
"x86_64-linux": "sha256-qt11SKmOjq0KU542QFbs+u7YyJicn4drCcwCdg325yk=",
|
||||
"aarch64-linux": "sha256-z68doReXTrWS7HeiAjc0btIjAsvzeZZ7hXAlHr0c77Q=",
|
||||
"aarch64-darwin": "sha256-PILYH1Pi8XBvSkuZ+1sNnUTao5kba+m5Z8iJKx6YXPo=",
|
||||
"x86_64-darwin": "sha256-KpcJzP4m0SUavu/WaSffgzOxrHq8ljdy0GOzs9p16lo="
|
||||
"x86_64-linux": "sha256-N4zM1zNufSg8DrDWOHWJYgVpn6vDghX/CJ0pym9ItxI=",
|
||||
"aarch64-linux": "sha256-Votrb6IbVt6OS5pcAlBd3L2btkZHa62Eu3mAFzKSlGM=",
|
||||
"aarch64-darwin": "sha256-Ofmy6plO4CFt/DoVdyt3Sr2rk6VJhas4zXq3DnvP/6A=",
|
||||
"x86_64-darwin": "sha256-LOeqfqlPbhp1c0Gq56fvKSzve7dvcCwlooTmDMFMznw="
|
||||
}
|
||||
}
|
||||
|
||||
+9
-12
@@ -15,7 +15,7 @@
|
||||
"dev:www": "bun run --cwd packages/www dev",
|
||||
"dev:storybook": "bun --cwd packages/storybook storybook",
|
||||
"lint": "oxlint",
|
||||
"lint:effect-patterns": "ast-grep scan -c script/ast-grep/sgconfig.yml packages/util/src packages/core/src packages/server/src packages/protocol/src packages/cli/src",
|
||||
"lint:effect-patterns": "ast-grep scan -c script/ast-grep/sgconfig.yml packages/core/src packages/server/src packages/protocol/src packages/cli/src",
|
||||
"test:lint-rules": "ast-grep test -c script/ast-grep/sgconfig.yml",
|
||||
"typecheck": "bun turbo typecheck --concurrency=3",
|
||||
"typecheck:profile": "bun script/profile-typecheck.ts",
|
||||
@@ -37,18 +37,18 @@
|
||||
"packages/slack"
|
||||
],
|
||||
"catalog": {
|
||||
"@effect/opentelemetry": "4.0.0-beta.98",
|
||||
"@effect/platform-node": "4.0.0-beta.98",
|
||||
"@effect/sql-sqlite-bun": "4.0.0-beta.98",
|
||||
"@effect/opentelemetry": "4.0.0-beta.83",
|
||||
"@effect/platform-node": "4.0.0-beta.83",
|
||||
"@effect/sql-sqlite-bun": "4.0.0-beta.83",
|
||||
"@npmcli/arborist": "9.4.0",
|
||||
"@types/bun": "1.3.13",
|
||||
"@types/cross-spawn": "6.0.6",
|
||||
"@octokit/rest": "22.0.0",
|
||||
"@hono/standard-validator": "0.2.0",
|
||||
"@hono/zod-validator": "0.4.2",
|
||||
"@opentui/core": "0.4.5",
|
||||
"@opentui/keymap": "0.4.5",
|
||||
"@opentui/solid": "0.4.5",
|
||||
"@opentui/core": "0.4.3",
|
||||
"@opentui/keymap": "0.4.3",
|
||||
"@opentui/solid": "0.4.3",
|
||||
"@tanstack/solid-virtual": "3.13.32",
|
||||
"@shikijs/stream": "4.2.0",
|
||||
"ulid": "3.0.1",
|
||||
@@ -69,13 +69,12 @@
|
||||
"dompurify": "3.3.1",
|
||||
"drizzle-kit": "1.0.0-rc.2",
|
||||
"drizzle-orm": "1.0.0-rc.2",
|
||||
"effect": "4.0.0-beta.98",
|
||||
"effect": "4.0.0-beta.83",
|
||||
"ai": "6.0.168",
|
||||
"cross-spawn": "7.0.6",
|
||||
"hono": "4.10.7",
|
||||
"hono-openapi": "1.1.2",
|
||||
"fuzzysort": "3.1.0",
|
||||
"get-east-asian-width": "1.6.0",
|
||||
"luxon": "3.6.1",
|
||||
"marked": "17.0.6",
|
||||
"marked-shiki": "1.2.1",
|
||||
@@ -86,11 +85,9 @@
|
||||
"@typescript/native-preview": "7.0.0-dev.20251207.1",
|
||||
"zod": "4.1.8",
|
||||
"remeda": "2.26.0",
|
||||
"resolve.exports": "2.0.3",
|
||||
"sst": "4.13.1",
|
||||
"shiki": "4.2.0",
|
||||
"solid-list": "0.3.0",
|
||||
"string-width": "7.2.0",
|
||||
"tailwindcss": "4.1.11",
|
||||
"vite": "7.1.4",
|
||||
"@solidjs/meta": "0.29.4",
|
||||
@@ -166,7 +163,7 @@
|
||||
"@ai-sdk/google@3.0.73": "patches/@ai-sdk%2Fgoogle@3.0.73.patch",
|
||||
"@pierre/trees@1.0.0-beta.4": "patches/@pierre%2Ftrees@1.0.0-beta.4.patch",
|
||||
"@modelcontextprotocol/sdk@1.29.0": "patches/@modelcontextprotocol%2Fsdk@1.29.0.patch",
|
||||
"effect@4.0.0-beta.98": "patches/effect@4.0.0-beta.98.patch",
|
||||
"effect@4.0.0-beta.83": "patches/effect@4.0.0-beta.83.patch",
|
||||
"@tanstack/virtual-core@3.17.3": "patches/@tanstack%2Fvirtual-core@3.17.3.patch"
|
||||
}
|
||||
}
|
||||
|
||||
@@ -1,360 +0,0 @@
|
||||
# @opencode-ai/ai
|
||||
|
||||
Schema-first AI primitives for opencode. Provider quirks live in adapters, not in calling code.
|
||||
|
||||
```ts
|
||||
import { Effect } from "effect"
|
||||
import { LLM, LLMClient } from "@opencode-ai/ai"
|
||||
import { OpenAI } from "@opencode-ai/ai/providers"
|
||||
|
||||
const model = OpenAI.configure({ apiKey: process.env.OPENAI_API_KEY }).responses("gpt-4o-mini")
|
||||
|
||||
const request = LLM.request({
|
||||
model,
|
||||
system: "You are concise.",
|
||||
prompt: "Say hello in one short sentence.",
|
||||
generation: { maxTokens: 40 },
|
||||
})
|
||||
|
||||
const program = Effect.gen(function* () {
|
||||
const response = yield* LLMClient.generate(request)
|
||||
console.log(response.text)
|
||||
})
|
||||
```
|
||||
|
||||
Run `LLMClient.stream(request)` instead of `generate` when you want incremental `LLMEvent`s. The event stream is provider-neutral — same shape across OpenAI Chat, OpenAI Responses, Anthropic Messages, Gemini, Bedrock Converse, and any OpenAI-compatible deployment.
|
||||
|
||||
## Image generation
|
||||
|
||||
Use `Image.generate` with an image model for direct asset generation:
|
||||
|
||||
```ts
|
||||
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",
|
||||
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
|
||||
const program = Effect.gen(function* () {
|
||||
const response = yield* LLM.generate(
|
||||
LLM.request({
|
||||
model: OpenAI.configure({ apiKey }).responses("gpt-5"),
|
||||
prompt: "Design a solarpunk rooftop garden, then show me.",
|
||||
tools: [OpenAI.imageGeneration({ quality: "high" })],
|
||||
}),
|
||||
)
|
||||
|
||||
return response.message
|
||||
})
|
||||
```
|
||||
|
||||
The hosted result is represented as a provider-executed tool call and tool result. Its image is a `file` content item with a data URI, so retaining `response.message` preserves the generated image for continuation.
|
||||
|
||||
## Public API
|
||||
|
||||
- **`LLM.request({...})`** — build a provider-neutral `LLMRequest`. Accepts ergonomic inputs (`system: string`, `prompt: string`) that normalize into the canonical Schema classes.
|
||||
- **`LLM.generate` / `LLM.stream`** — re-exported from `LLMClient` for one-import use.
|
||||
- **`Message.user(...)` / `Message.assistant(...)` / `Message.tool(...)`** — message constructors from the canonical schema model.
|
||||
- **`Model.make(...)` / `ToolCallPart.make(...)` / `ToolResultPart.make(...)` / `ToolDefinition.make(...)`** — model and tool-related constructors from the canonical schema model.
|
||||
- **`LLMClient.prepare(request)`** — compile a request through protocol body construction, validation, and HTTP preparation without sending. Useful for inspection and testing.
|
||||
- **`LLMEvent.is.*`** — typed guards (`is.textDelta`, `is.toolCall`, `is.finish`, …) for filtering streams.
|
||||
- **`Image.generate({...})`** — generate images through a provider-neutral image request and response model.
|
||||
- **`ImageClient`** — Effect service and layer for image execution, parallel to `LLMClient`.
|
||||
|
||||
## Caching
|
||||
|
||||
Prompt caching is **on by default**. Every `LLMRequest` resolves to `cache: "auto"` unless the caller opts out with `cache: "none"`. Each protocol translates `CacheHint`s to its wire format (`cache_control` on Anthropic, `cachePoint` on Bedrock; OpenAI and Gemini do implicit caching server-side and don't need inline markers — auto is a no-op there).
|
||||
|
||||
### Auto placement
|
||||
|
||||
`"auto"` places three breakpoints — last tool definition, last system part, latest user message. The last-user-message boundary is the load-bearing detail: in a tool-use loop, a single user turn expands into many assistant/tool round-trips, all sharing that prefix. Caching at that boundary lets every intra-turn API call hit.
|
||||
|
||||
The math justifies the default: Anthropic's 5-minute cache write is 1.25× base, read is 0.1×, so a single reuse within 5 minutes already wins. One-shot completions below the per-model minimum-cacheable-token threshold silently no-op on the wire, so the worst case is harmless.
|
||||
|
||||
### Opting out
|
||||
|
||||
```ts
|
||||
LLM.request({
|
||||
model,
|
||||
system,
|
||||
prompt: "one-off question",
|
||||
cache: "none",
|
||||
})
|
||||
```
|
||||
|
||||
### Granular policy
|
||||
|
||||
```ts
|
||||
cache: {
|
||||
tools?: boolean,
|
||||
system?: boolean,
|
||||
messages?: "latest-user-message" | "latest-assistant" | { tail: number },
|
||||
ttlSeconds?: number, // ≥ 3600 → 1h on Anthropic/Bedrock; else 5m
|
||||
}
|
||||
```
|
||||
|
||||
### Manual hints
|
||||
|
||||
Inline `CacheHint` on any text / system / tool / tool-result part overrides automatic placement. The auto policy preserves manual hints; it only fills gaps.
|
||||
|
||||
```ts
|
||||
LLM.request({
|
||||
model,
|
||||
system: [
|
||||
{ type: "text", text: "stable system prompt", cache: { type: "ephemeral" } },
|
||||
],
|
||||
...
|
||||
})
|
||||
```
|
||||
|
||||
### Provider behavior table
|
||||
|
||||
| Protocol | `cache: "auto"` |
|
||||
| ----------------------- | ------------------------------------------------------------------------- |
|
||||
| Anthropic Messages | emits up to 3 `cache_control` markers (4-breakpoint cap enforced) |
|
||||
| Bedrock Converse | emits up to 3 `cachePoint` blocks (4-breakpoint cap enforced) |
|
||||
| OpenAI Chat / Responses | no-op (implicit caching above 1024 tokens) |
|
||||
| Gemini | no-op (implicit caching on 2.5+; explicit `CachedContent` is out-of-band) |
|
||||
|
||||
Normalized cache usage is read back into `response.usage.cacheReadInputTokens` and `cacheWriteInputTokens` across every provider.
|
||||
|
||||
## Providers
|
||||
|
||||
Provider facades configure endpoint/auth/deployment details first, then expose model selectors that take only a model or deployment id. The selected model carries the executable route value used at runtime.
|
||||
|
||||
```ts
|
||||
import { OpenAI, CloudflareAIGateway } from "@opencode-ai/ai/providers"
|
||||
|
||||
const openai = OpenAI.configure({ apiKey: process.env.OPENAI_API_KEY }).responses("gpt-4o-mini")
|
||||
const gateway = CloudflareAIGateway.configure({
|
||||
accountId: process.env.CLOUDFLARE_ACCOUNT_ID,
|
||||
gatewayApiKey: process.env.CLOUDFLARE_API_TOKEN,
|
||||
}).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, Z.ai, plus generic OpenAI-compatible Chat and Responses entrypoints and an Anthropic Messages-compatible entrypoint.
|
||||
|
||||
### Package-like entrypoints
|
||||
|
||||
Native catalog integrations load provider behavior through package-like entrypoints. These are export paths from the same `@opencode-ai/ai` npm package, not independently published packages. Each entrypoint exports the same `model(modelID, settings)` contract, and `settings` contains serializable provider configuration plus common `headers`, `body`, and `limits` overlays.
|
||||
|
||||
```ts
|
||||
import { model } from "@opencode-ai/ai/providers/openai/responses"
|
||||
|
||||
const selected = model("gpt-5", {
|
||||
apiKey: process.env.OPENAI_API_KEY,
|
||||
transport: "websocket",
|
||||
headers: { "x-application": "opencode" },
|
||||
limits: { context: 200_000, output: 64_000 },
|
||||
})
|
||||
```
|
||||
|
||||
OpenAI Chat and OpenAI Responses are separate semantic entrypoints:
|
||||
|
||||
- `@opencode-ai/ai/providers/openai/chat`
|
||||
- `@opencode-ai/ai/providers/openai/responses`
|
||||
- `@opencode-ai/ai/providers/openai-compatible/responses`
|
||||
- `@opencode-ai/ai/providers/anthropic-compatible`
|
||||
- `@opencode-ai/ai/providers/google-vertex/gemini`
|
||||
- `@opencode-ai/ai/providers/google-vertex/chat`
|
||||
- `@opencode-ai/ai/providers/google-vertex/responses`
|
||||
- `@opencode-ai/ai/providers/google-vertex/messages`
|
||||
|
||||
Responses HTTP versus WebSocket is a scoped `transport` setting on the OpenAI Responses entrypoint, not another entrypoint. Azure follows the same Chat/Responses split at `providers/azure/chat` and `providers/azure/responses`. Generic OpenAI-compatible Chat remains at `providers/openai-compatible`; compatible Responses is separate at `providers/openai-compatible/responses`. Generic Anthropic Messages-compatible providers use `providers/anthropic-compatible`, which the named Anthropic provider composes. Google Gemini and Amazon Bedrock expose their single native API through their existing provider paths.
|
||||
|
||||
Vertex Gemini, Vertex Chat, Vertex Responses, and Vertex Messages are separate API entrypoints. All accept `project`, `location`, and an optional `accessToken`; when no explicit token or auth override is supplied they lazily use Google Application Default Credentials. Vertex Gemini instead selects express mode when `apiKey` or `GOOGLE_VERTEX_API_KEY` is present. Vertex Chat targets MaaS models through the OpenAI-compatible Chat Completions endpoint, while Vertex Responses targets Grok models and defaults `store` to `false` as required by Vertex. `providers/google-vertex` remains the default alias for `providers/google-vertex/gemini`.
|
||||
|
||||
Tuned Vertex Gemini deployments use model ids shaped like `endpoints/1234567890` and require OAuth or ADC; Vertex express-mode API keys support publisher models only.
|
||||
|
||||
```ts
|
||||
import { model } from "@opencode-ai/ai/providers/google-vertex/gemini"
|
||||
|
||||
model("gemini-3.5-flash", { project: "my-project", location: "global" })
|
||||
```
|
||||
|
||||
```ts
|
||||
import { model } from "@opencode-ai/ai/providers/google-vertex/chat"
|
||||
|
||||
model("deepseek-ai/deepseek-v3.2-maas", { project: "my-project", location: "global" })
|
||||
```
|
||||
|
||||
```ts
|
||||
import { model } from "@opencode-ai/ai/providers/google-vertex/responses"
|
||||
|
||||
model("xai/grok-4.20-reasoning", { project: "my-project", location: "global" })
|
||||
```
|
||||
|
||||
```ts
|
||||
import { model } from "@opencode-ai/ai/providers/google-vertex/messages"
|
||||
|
||||
model("claude-sonnet-4-6", { project: "my-project", location: "global" })
|
||||
```
|
||||
|
||||
Provider facades such as `OpenAI.configure(...).responses(...)` remain the direct application API. Package-like entrypoints are the self-similar loading contract used when a catalog selects behavior by export path.
|
||||
|
||||
Other provider exports listed above remain direct facades until they explicitly implement the package-like contract. Exporting a provider facade does not implicitly make it a catalog-loadable provider package.
|
||||
|
||||
## Provider options & HTTP overlays
|
||||
|
||||
Three escape hatches in order of stability:
|
||||
|
||||
1. **`generation`** — portable knobs (`maxTokens`, `temperature`, `topP`, `topK`, penalties, seed, stop).
|
||||
2. **`providerOptions: { <provider>: {...} }`** — typed-at-the-facade provider-specific knobs (OpenAI `promptCacheKey`, Anthropic `thinking`, Gemini `thinkingConfig`, OpenRouter routing).
|
||||
3. **`http: { body, headers, query }`** — last-resort serializable overlays merged into the final HTTP request. Reach for this only when a stable typed path doesn't yet exist.
|
||||
|
||||
Route/provider defaults are overridden by request-level values for each axis.
|
||||
|
||||
## Routes
|
||||
|
||||
Adding a new model or deployment is usually 5-15 lines using `Route.make({ protocol, endpoint, auth, framing, ... })`. The route owns endpoint/auth/framing and the protocol owns body construction plus stream parsing. Transports are reusable IO templates that receive route endpoint/auth at compile time. Capability/catalog metadata lives outside this low-level package; unsupported request shapes fail during protocol lowering. See `AGENTS.md` for the architectural detail.
|
||||
|
||||
## Effect
|
||||
|
||||
This package is built on Effect. Public methods return `Effect` or `Stream`; provide `LLMClient.layer` for LLM dispatch and `ImageClient.layer` for image dispatch, then import the provider/protocol modules for the routes you use. The example at `example/tutorial.ts` is a runnable walkthrough.
|
||||
|
||||
## See also
|
||||
|
||||
- `AGENTS.md` — architecture, route construction, contributor guide
|
||||
- `STATUS.md` — native provider parity status and AI SDK migration gaps
|
||||
- `example/tutorial.ts` — runnable end-to-end walkthrough
|
||||
- `test/provider/*.test.ts` — fixture-first protocol tests; `*.recorded.test.ts` files cover live cassettes
|
||||
@@ -1,37 +0,0 @@
|
||||
{
|
||||
"$schema": "https://json.schemastore.org/package.json",
|
||||
"version": "1.17.20",
|
||||
"name": "@opencode-ai/ai",
|
||||
"type": "module",
|
||||
"license": "MIT",
|
||||
"scripts": {
|
||||
"setup:recording-env": "bun run script/setup-recording-env.ts",
|
||||
"test": "bun test --timeout 30000 --only-failures",
|
||||
"typecheck": "tsgo --noEmit && tsgo --noEmit -p tsconfig.types.json",
|
||||
"build": "tsc -p tsconfig.build.json"
|
||||
},
|
||||
"files": [
|
||||
"dist"
|
||||
],
|
||||
"exports": {
|
||||
".": "./src/index.ts",
|
||||
"./*": "./src/*.ts"
|
||||
},
|
||||
"devDependencies": {
|
||||
"@clack/prompts": "1.0.0-alpha.1",
|
||||
"@effect/platform-node": "catalog:",
|
||||
"@opencode-ai/http-recorder": "workspace:*",
|
||||
"@tsconfig/bun": "catalog:",
|
||||
"@types/bun": "catalog:",
|
||||
"@typescript/native-preview": "catalog:",
|
||||
"typescript": "catalog:"
|
||||
},
|
||||
"dependencies": {
|
||||
"@smithy/eventstream-codec": "4.2.14",
|
||||
"@smithy/util-utf8": "4.2.2",
|
||||
"@opencode-ai/schema": "workspace:*",
|
||||
"aws4fetch": "1.0.20",
|
||||
"effect": "catalog:",
|
||||
"google-auth-library": "10.5.0"
|
||||
}
|
||||
}
|
||||
@@ -1,38 +0,0 @@
|
||||
#!/usr/bin/env bun
|
||||
import { Script } from "@opencode-ai/script"
|
||||
import { $ } from "bun"
|
||||
import { fileURLToPath } from "url"
|
||||
|
||||
const dir = fileURLToPath(new URL("..", import.meta.url))
|
||||
process.chdir(dir)
|
||||
|
||||
async function published(name: string, version: string) {
|
||||
return (await $`npm view ${name}@${version} version`.nothrow()).exitCode === 0
|
||||
}
|
||||
|
||||
await $`bun run build`
|
||||
const originalText = await Bun.file("package.json").text()
|
||||
const pkg = JSON.parse(originalText) as {
|
||||
name: string
|
||||
version: string
|
||||
exports: Record<string, string>
|
||||
}
|
||||
if (await published(pkg.name, pkg.version)) {
|
||||
console.log(`already published ${pkg.name}@${pkg.version}`)
|
||||
} else {
|
||||
for (const [key, value] of Object.entries(pkg.exports)) {
|
||||
const file = value.replace("./src/", "./dist/").replace(".ts", "")
|
||||
// @ts-ignore
|
||||
pkg.exports[key] = {
|
||||
import: file + ".js",
|
||||
types: file + ".d.ts",
|
||||
}
|
||||
}
|
||||
await Bun.write("package.json", JSON.stringify(pkg, null, 2))
|
||||
try {
|
||||
await $`bun pm pack`
|
||||
await $`npm publish *.tgz --tag ${Script.channel} --access public`
|
||||
} finally {
|
||||
await Bun.write("package.json", originalText)
|
||||
}
|
||||
}
|
||||
@@ -1,38 +0,0 @@
|
||||
import { Context, Effect, Layer } from "effect"
|
||||
import { RequestExecutor } from "./route/executor"
|
||||
import type { ImageOptions, ImageRequest, ImageRequestFor, ImageResponse } from "./image"
|
||||
import type { LLMError } from "./schema"
|
||||
|
||||
export type Execute = RequestExecutor.Interface["execute"]
|
||||
|
||||
export interface Interface {
|
||||
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 = <Options extends ImageOptions>(
|
||||
request: ImageRequestFor<Options>,
|
||||
): Effect.Effect<ImageResponse, LLMError> =>
|
||||
Effect.gen(function* () {
|
||||
const client = yield* Service
|
||||
return yield* client.generate(request)
|
||||
}) as Effect.Effect<ImageResponse, LLMError>
|
||||
|
||||
export const layer: Layer.Layer<Service, never, RequestExecutor.Service> = Layer.effect(
|
||||
Service,
|
||||
Effect.gen(function* () {
|
||||
const executor = yield* RequestExecutor.Service
|
||||
return Service.of({
|
||||
generate: (request) => request.model.route.generate(request, executor.execute),
|
||||
})
|
||||
}),
|
||||
)
|
||||
|
||||
export const ImageClient = {
|
||||
Service,
|
||||
layer,
|
||||
generate,
|
||||
} as const
|
||||
@@ -1,166 +0,0 @@
|
||||
import { Effect, Schema } from "effect"
|
||||
import { HttpOptions, InvalidRequestReason, LLMError, ModelID, ProviderID, ProviderMetadata, Usage } from "./schema"
|
||||
import { ImageClient, Service, type Execute as ImageExecute } from "./image-client"
|
||||
|
||||
export interface ImageRoute<Options extends ImageOptions = ImageOptions> {
|
||||
readonly id: string
|
||||
readonly generate: (
|
||||
request: ImageRequestFor<Options>,
|
||||
execute: ImageExecute,
|
||||
) => Effect.Effect<ImageResponse, LLMError>
|
||||
}
|
||||
|
||||
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<Options>
|
||||
readonly http?: HttpOptions
|
||||
|
||||
constructor(input: ImageModel.Input<Options>) {
|
||||
this.id = input.id
|
||||
this.provider = input.provider
|
||||
this.route = input.route
|
||||
this.http = input.http
|
||||
}
|
||||
|
||||
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,
|
||||
http: input.http,
|
||||
})
|
||||
}
|
||||
}
|
||||
|
||||
export namespace ImageModel {
|
||||
export interface Input<Options extends ImageOptions = ImageOptions> {
|
||||
readonly id: ModelID
|
||||
readonly provider: ProviderID
|
||||
readonly route: ImageRoute<Options>
|
||||
readonly http?: HttpOptions
|
||||
}
|
||||
|
||||
export interface MakeInput<Options extends ImageOptions = ImageOptions>
|
||||
extends Omit<Input<Options>, "id" | "provider"> {
|
||||
readonly id: string | ModelID
|
||||
readonly provider: string | ProviderID
|
||||
}
|
||||
}
|
||||
|
||||
export const ImageModelSchema = Schema.declare((value): value is ImageModel => value instanceof ImageModel, {
|
||||
expected: "Image.Model",
|
||||
})
|
||||
|
||||
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,
|
||||
images: Schema.optional(Schema.Array(ImageInputSchema)),
|
||||
options: Schema.optional(Schema.Record(Schema.String, Schema.Unknown)),
|
||||
http: Schema.optional(HttpOptions),
|
||||
}) {
|
||||
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]),
|
||||
providerMetadata: Schema.optional(ProviderMetadata),
|
||||
}) {}
|
||||
|
||||
export class ImageResponse extends Schema.Class<ImageResponse>("Image.Response")({
|
||||
images: Schema.Array(GeneratedImage),
|
||||
usage: Schema.optional(Usage),
|
||||
providerMetadata: Schema.optional(ProviderMetadata),
|
||||
}) {
|
||||
get image() {
|
||||
return this.images[0]
|
||||
}
|
||||
}
|
||||
|
||||
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 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((request) => ImageClient.generate(request as unknown as ImageRequestFor<ImageOptions>)))
|
||||
}
|
||||
|
||||
export const Image = {
|
||||
request,
|
||||
generate,
|
||||
} as const
|
||||
@@ -1 +0,0 @@
|
||||
export * from "./protocols/index"
|
||||
@@ -1,314 +0,0 @@
|
||||
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
|
||||
@@ -1,270 +0,0 @@
|
||||
import { Effect, Encoding, Schema } from "effect"
|
||||
import { Headers, HttpClientRequest, HttpClientResponse } from "effect/unstable/http"
|
||||
import {
|
||||
ImageModel,
|
||||
GeneratedImage,
|
||||
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,
|
||||
} 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 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>
|
||||
|
||||
export type OpenAIImageBody = Record<string, unknown> & {
|
||||
readonly model: string
|
||||
readonly prompt: string
|
||||
}
|
||||
|
||||
const OpenAIImageResponse = Schema.Struct({
|
||||
data: Schema.Array(
|
||||
Schema.Struct({
|
||||
b64_json: Schema.optional(Schema.String),
|
||||
url: Schema.optional(Schema.String),
|
||||
revised_prompt: Schema.optional(Schema.String),
|
||||
}),
|
||||
),
|
||||
output_format: Schema.optional(Schema.String),
|
||||
usage: Schema.optional(
|
||||
Schema.Struct({
|
||||
input_tokens: Schema.optional(Schema.Number),
|
||||
output_tokens: Schema.optional(Schema.Number),
|
||||
total_tokens: Schema.optional(Schema.Number),
|
||||
input_tokens_details: Schema.optional(Schema.Record(Schema.String, Schema.Unknown)),
|
||||
output_tokens_details: Schema.optional(Schema.Record(Schema.String, 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: OpenAIImageOptions | undefined) => {
|
||||
if (!options) return undefined
|
||||
const { mask: _, outputFormat, outputCompression, ...native } = options
|
||||
return {
|
||||
output_format: outputFormat,
|
||||
output_compression: outputCompression,
|
||||
...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<OpenAIImageOptions> = {
|
||||
id: ADAPTER,
|
||||
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)
|
||||
|
||||
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",
|
||||
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"),
|
||||
),
|
||||
)
|
||||
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,
|
||||
providerMetadata:
|
||||
item.revised_prompt === undefined ? undefined : { openai: { revisedPrompt: item.revised_prompt } },
|
||||
}),
|
||||
),
|
||||
)
|
||||
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 ${index} has neither image data nor a URL`))
|
||||
})
|
||||
if (images.length === 0) return yield* invalidOutput("OpenAI Images returned no images")
|
||||
return new ImageResponse({
|
||||
images,
|
||||
usage:
|
||||
decoded.usage === undefined
|
||||
? undefined
|
||||
: new Usage({
|
||||
inputTokens: decoded.usage.input_tokens,
|
||||
outputTokens: decoded.usage.output_tokens,
|
||||
totalTokens: decoded.usage.total_tokens,
|
||||
providerMetadata: { openai: decoded.usage },
|
||||
}),
|
||||
providerMetadata: { openai: { outputFormat: format } },
|
||||
})
|
||||
})
|
||||
|
||||
const imageBlob = (data: Uint8Array, mediaType: string) => {
|
||||
const buffer = new ArrayBuffer(data.byteLength)
|
||||
new Uint8Array(buffer).set(data)
|
||||
return new Blob([buffer], { type: mediaType })
|
||||
}
|
||||
|
||||
export const OpenAIImages = {
|
||||
model,
|
||||
} as const
|
||||
@@ -1,34 +0,0 @@
|
||||
import { Effect, Encoding } from "effect"
|
||||
import type { ImageInput } from "../../image"
|
||||
import { InvalidRequestReason, LLMError } from "../../schema"
|
||||
|
||||
const invalid = (module: string, message: string) =>
|
||||
new LLMError({
|
||||
module,
|
||||
method: "generate",
|
||||
reason: new InvalidRequestReason({ message }),
|
||||
})
|
||||
|
||||
export const dataUrl = (input: Extract<ImageInput, { readonly type: "bytes" }>) =>
|
||||
`data:${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
|
||||
@@ -1,20 +0,0 @@
|
||||
import { Schema } from "effect"
|
||||
|
||||
const dimensions = (value: string) => {
|
||||
const match = /^(\d+)x(\d+)$/.exec(value)
|
||||
if (!match) return undefined
|
||||
return { width: Number(match[1]), height: Number(match[2]) }
|
||||
}
|
||||
|
||||
export const Size = Schema.String.check(
|
||||
Schema.makeFilter((value) => {
|
||||
if (value === "auto") return undefined
|
||||
const parsed = dimensions(value)
|
||||
if (!parsed) return "image size must be `auto` or `{width}x{height}`"
|
||||
return parsed.width > 0 && parsed.height > 0 ? undefined : "image dimensions must be positive integers"
|
||||
}),
|
||||
)
|
||||
|
||||
export const OpenAIImage = {
|
||||
Size,
|
||||
} as const
|
||||
@@ -1,202 +0,0 @@
|
||||
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
|
||||
@@ -1,132 +0,0 @@
|
||||
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
|
||||
@@ -1 +0,0 @@
|
||||
export * from "./providers/index"
|
||||
@@ -1,67 +0,0 @@
|
||||
import type { ProviderPackage } from "../provider-package"
|
||||
import { AnthropicMessages } from "../protocols/anthropic-messages"
|
||||
import { Auth } from "../route/auth"
|
||||
import type { ProviderAuthOption } from "../route/auth-options"
|
||||
import type { RouteDefaultsInput } from "../route/client"
|
||||
import { ProviderID, type ModelID } from "../schema"
|
||||
|
||||
export const id = ProviderID.make("anthropic-compatible")
|
||||
|
||||
export type Config = RouteDefaultsInput &
|
||||
ProviderAuthOption<"optional"> & {
|
||||
readonly provider?: string
|
||||
readonly baseURL: string
|
||||
}
|
||||
|
||||
export type Settings = ProviderPackage.Settings &
|
||||
(
|
||||
| { readonly apiKey?: string; readonly authToken?: never }
|
||||
| { readonly apiKey?: never; readonly authToken?: string }
|
||||
) & {
|
||||
readonly baseURL: string
|
||||
readonly provider?: string
|
||||
}
|
||||
|
||||
export const routes = [AnthropicMessages.route]
|
||||
|
||||
const auth = (input: ProviderAuthOption<"optional">) => {
|
||||
if ("auth" in input && input.auth) return input.auth
|
||||
return Auth.optional("apiKey" in input ? input.apiKey : undefined, "apiKey").pipe(Auth.header("x-api-key"))
|
||||
}
|
||||
|
||||
export const configure = (input: Config) => {
|
||||
if (!input.baseURL) throw new Error("Anthropic-compatible providers require a baseURL")
|
||||
const provider = input.provider ?? "anthropic-compatible"
|
||||
const { provider: _, baseURL, apiKey: _apiKey, auth: _auth, ...rest } = input
|
||||
const route = AnthropicMessages.route.with({
|
||||
...rest,
|
||||
provider,
|
||||
endpoint: { baseURL },
|
||||
auth: auth(input),
|
||||
})
|
||||
return {
|
||||
id: ProviderID.make(provider),
|
||||
model: (modelID: string | ModelID) => route.model({ id: modelID }),
|
||||
configure,
|
||||
}
|
||||
}
|
||||
|
||||
export const provider = {
|
||||
id,
|
||||
configure,
|
||||
}
|
||||
|
||||
export const model: ProviderPackage.Definition<Settings>["model"] = (modelID, settings) => {
|
||||
if (settings.apiKey !== undefined && settings.authToken !== undefined)
|
||||
throw new Error("Anthropic-compatible apiKey cannot be combined with authToken")
|
||||
return configure({
|
||||
...(settings.authToken === undefined ? { apiKey: settings.apiKey } : { auth: Auth.bearer(settings.authToken) }),
|
||||
baseURL: settings.baseURL,
|
||||
headers: settings.headers === undefined ? undefined : { ...settings.headers },
|
||||
http: settings.body === undefined ? undefined : { body: { ...settings.body } },
|
||||
limits: settings.limits,
|
||||
provider: settings.provider,
|
||||
}).model(modelID)
|
||||
}
|
||||
|
||||
export * as AnthropicCompatible from "./anthropic-compatible"
|
||||
@@ -1,81 +0,0 @@
|
||||
import type { ProviderPackage } from "../provider-package"
|
||||
import { OpenAICompatibleChat } from "../protocols/openai-compatible-chat"
|
||||
import type { RouteDefaultsInput } from "../route/client"
|
||||
import { ProviderID, type ModelID, type ProviderOptions } from "../schema"
|
||||
import { GoogleVertexShared } from "./google-vertex-shared"
|
||||
|
||||
export const id = ProviderID.make("google-vertex")
|
||||
|
||||
export type Config = RouteDefaultsInput &
|
||||
GoogleVertexShared.OAuthOptions & {
|
||||
readonly baseURL?: string
|
||||
readonly location?: string
|
||||
readonly project?: string
|
||||
}
|
||||
|
||||
export interface Settings extends ProviderPackage.Settings {
|
||||
readonly accessToken?: string
|
||||
readonly apiKey?: never
|
||||
readonly baseURL?: string
|
||||
readonly location?: string
|
||||
readonly project?: string
|
||||
readonly providerOptions?: ProviderOptions
|
||||
}
|
||||
|
||||
const route = OpenAICompatibleChat.route.with({
|
||||
id: "google-vertex-chat",
|
||||
provider: id,
|
||||
})
|
||||
|
||||
export const routes = [route]
|
||||
|
||||
const configuredRoute = (input: Config) => {
|
||||
if ("apiKey" in input && input.apiKey !== undefined) throw new Error("Google Vertex Chat does not support API keys")
|
||||
const {
|
||||
accessToken: _accessToken,
|
||||
auth: _auth,
|
||||
baseURL,
|
||||
location: inputLocation,
|
||||
project: inputProject,
|
||||
...rest
|
||||
} = input
|
||||
const location = GoogleVertexShared.location(inputLocation, "global")
|
||||
const project = GoogleVertexShared.project(inputProject)
|
||||
return route.with({
|
||||
...rest,
|
||||
endpoint: {
|
||||
baseURL:
|
||||
baseURL ??
|
||||
`https://aiplatform.googleapis.com/v1/projects/${GoogleVertexShared.requireProject(project)}/locations/${location}/endpoints/openapi`,
|
||||
},
|
||||
auth: GoogleVertexShared.oauth(input, project),
|
||||
})
|
||||
}
|
||||
|
||||
export const configure = (input: Config = {}) => {
|
||||
const route = configuredRoute(input)
|
||||
return {
|
||||
id,
|
||||
model: (modelID: string | ModelID) => route.model({ id: modelID }),
|
||||
configure,
|
||||
}
|
||||
}
|
||||
|
||||
export const provider = {
|
||||
id,
|
||||
configure,
|
||||
}
|
||||
|
||||
export const model: ProviderPackage.Definition<Settings>["model"] = (modelID, settings) => {
|
||||
if (settings.apiKey !== undefined) throw new Error("Google Vertex Chat does not support API keys")
|
||||
return configure({
|
||||
accessToken: settings.accessToken,
|
||||
baseURL: settings.baseURL,
|
||||
headers: settings.headers === undefined ? undefined : { ...settings.headers },
|
||||
http: settings.body === undefined ? undefined : { body: { ...settings.body } },
|
||||
limits: settings.limits,
|
||||
location: settings.location,
|
||||
project: settings.project,
|
||||
providerOptions: settings.providerOptions,
|
||||
}).model(modelID)
|
||||
}
|
||||
@@ -1,111 +0,0 @@
|
||||
import { Effect, Schema, Struct } from "effect"
|
||||
import type { ProviderPackage } from "../provider-package"
|
||||
import { AnthropicMessages } from "../protocols/anthropic-messages"
|
||||
import { Auth } from "../route/auth"
|
||||
import { Route, type RouteDefaultsInput } from "../route/client"
|
||||
import { Endpoint } from "../route/endpoint"
|
||||
import { Framing } from "../route/framing"
|
||||
import { Protocol } from "../route/protocol"
|
||||
import { ProviderID, type ModelID, type ProviderOptions } from "../schema"
|
||||
import { GoogleVertexShared } from "./google-vertex-shared"
|
||||
|
||||
const VERSION = "vertex-2023-10-16" as const
|
||||
|
||||
// models.dev uses this provider id even though the API contract is Anthropic Messages.
|
||||
export const id = ProviderID.make("google-vertex-anthropic")
|
||||
|
||||
export type Config = RouteDefaultsInput &
|
||||
GoogleVertexShared.OAuthOptions & {
|
||||
readonly baseURL?: string
|
||||
readonly location?: string
|
||||
readonly project?: string
|
||||
}
|
||||
|
||||
export interface Settings extends ProviderPackage.Settings {
|
||||
readonly accessToken?: string
|
||||
readonly apiKey?: never
|
||||
readonly baseURL?: string
|
||||
readonly location?: string
|
||||
readonly project?: string
|
||||
readonly providerOptions?: ProviderOptions
|
||||
}
|
||||
|
||||
const route = Route.make({
|
||||
id: "google-vertex-messages",
|
||||
provider: id,
|
||||
providerMetadataKey: "anthropic",
|
||||
protocol: Protocol.make({
|
||||
id: AnthropicMessages.protocol.id,
|
||||
body: {
|
||||
schema: Schema.Struct({
|
||||
...Struct.omit(AnthropicMessages.AnthropicMessagesBody.fields, ["model"]),
|
||||
anthropic_version: Schema.Literal(VERSION),
|
||||
}),
|
||||
from: (request) =>
|
||||
AnthropicMessages.protocol.body.from(request).pipe(
|
||||
Effect.map((body) => ({
|
||||
...Struct.omit(body, ["model"]),
|
||||
anthropic_version: VERSION,
|
||||
})),
|
||||
),
|
||||
},
|
||||
stream: AnthropicMessages.protocol.stream,
|
||||
}),
|
||||
endpoint: Endpoint.path(({ request }) => `/${request.model.id}:streamRawPredict`),
|
||||
auth: Auth.none,
|
||||
framing: Framing.sse,
|
||||
})
|
||||
|
||||
export const routes = [route]
|
||||
|
||||
const configuredRoute = (input: Config) => {
|
||||
if ("apiKey" in input && input.apiKey !== undefined)
|
||||
throw new Error("Google Vertex Messages does not support API keys")
|
||||
const {
|
||||
accessToken: _accessToken,
|
||||
auth: _auth,
|
||||
baseURL,
|
||||
location: inputLocation,
|
||||
project: inputProject,
|
||||
...rest
|
||||
} = input
|
||||
const location = GoogleVertexShared.location(inputLocation, "global")
|
||||
const project = GoogleVertexShared.project(inputProject)
|
||||
return route.with({
|
||||
...rest,
|
||||
endpoint: {
|
||||
baseURL:
|
||||
baseURL ??
|
||||
`https://${GoogleVertexShared.host(location)}/v1/projects/${GoogleVertexShared.requireProject(project)}/locations/${location}/publishers/anthropic/models`,
|
||||
},
|
||||
auth: GoogleVertexShared.oauth(input, project),
|
||||
})
|
||||
}
|
||||
|
||||
export const configure = (input: Config = {}) => {
|
||||
const route = configuredRoute(input)
|
||||
return {
|
||||
id,
|
||||
model: (modelID: string | ModelID) => route.model({ id: modelID }),
|
||||
configure,
|
||||
}
|
||||
}
|
||||
|
||||
export const provider = {
|
||||
id,
|
||||
configure,
|
||||
}
|
||||
|
||||
export const model: ProviderPackage.Definition<Settings>["model"] = (modelID, settings) => {
|
||||
if (settings.apiKey !== undefined) throw new Error("Google Vertex Messages does not support API keys")
|
||||
return configure({
|
||||
accessToken: settings.accessToken,
|
||||
baseURL: settings.baseURL,
|
||||
headers: settings.headers === undefined ? undefined : { ...settings.headers },
|
||||
http: settings.body === undefined ? undefined : { body: { ...settings.body } },
|
||||
limits: settings.limits,
|
||||
location: settings.location,
|
||||
project: settings.project,
|
||||
providerOptions: settings.providerOptions,
|
||||
}).model(modelID)
|
||||
}
|
||||
@@ -1,82 +0,0 @@
|
||||
import type { ProviderPackage } from "../provider-package"
|
||||
import { OpenAICompatibleResponses } from "../protocols/openai-compatible-responses"
|
||||
import type { RouteDefaultsInput } from "../route/client"
|
||||
import { ProviderID, type ModelID, type ProviderOptions } from "../schema"
|
||||
import { GoogleVertexShared } from "./google-vertex-shared"
|
||||
|
||||
export const id = ProviderID.make("google-vertex")
|
||||
|
||||
export type Config = RouteDefaultsInput &
|
||||
GoogleVertexShared.OAuthOptions & {
|
||||
readonly baseURL?: string
|
||||
readonly location?: string
|
||||
readonly project?: string
|
||||
}
|
||||
|
||||
export interface Settings extends ProviderPackage.Settings {
|
||||
readonly accessToken?: string
|
||||
readonly apiKey?: never
|
||||
readonly baseURL?: string
|
||||
readonly location?: string
|
||||
readonly project?: string
|
||||
readonly providerOptions?: ProviderOptions
|
||||
}
|
||||
|
||||
const route = OpenAICompatibleResponses.route.with({
|
||||
id: "google-vertex-responses",
|
||||
provider: id,
|
||||
})
|
||||
|
||||
export const routes = [route]
|
||||
|
||||
const configuredRoute = (input: Config) => {
|
||||
if ("apiKey" in input && input.apiKey !== undefined)
|
||||
throw new Error("Google Vertex Responses does not support API keys")
|
||||
const {
|
||||
accessToken: _accessToken,
|
||||
auth: _auth,
|
||||
baseURL,
|
||||
location: inputLocation,
|
||||
project: inputProject,
|
||||
...rest
|
||||
} = input
|
||||
const location = GoogleVertexShared.location(inputLocation, "global")
|
||||
const project = GoogleVertexShared.project(inputProject)
|
||||
return route.with({
|
||||
...rest,
|
||||
endpoint: {
|
||||
baseURL:
|
||||
baseURL ??
|
||||
`https://aiplatform.googleapis.com/v1/projects/${GoogleVertexShared.requireProject(project)}/locations/${location}/endpoints/openapi`,
|
||||
},
|
||||
auth: GoogleVertexShared.oauth(input, project),
|
||||
})
|
||||
}
|
||||
|
||||
export const configure = (input: Config = {}) => {
|
||||
const route = configuredRoute(input)
|
||||
return {
|
||||
id,
|
||||
model: (modelID: string | ModelID) => route.model({ id: modelID }),
|
||||
configure,
|
||||
}
|
||||
}
|
||||
|
||||
export const provider = {
|
||||
id,
|
||||
configure,
|
||||
}
|
||||
|
||||
export const model: ProviderPackage.Definition<Settings>["model"] = (modelID, settings) => {
|
||||
if (settings.apiKey !== undefined) throw new Error("Google Vertex Responses does not support API keys")
|
||||
return configure({
|
||||
accessToken: settings.accessToken,
|
||||
baseURL: settings.baseURL,
|
||||
headers: settings.headers === undefined ? undefined : { ...settings.headers },
|
||||
http: settings.body === undefined ? undefined : { body: { ...settings.body } },
|
||||
limits: settings.limits,
|
||||
location: settings.location,
|
||||
project: settings.project,
|
||||
providerOptions: settings.providerOptions,
|
||||
}).model(modelID)
|
||||
}
|
||||
@@ -1,77 +0,0 @@
|
||||
import type { AnyAuthClient } from "google-auth-library"
|
||||
import { Effect, Redacted } from "effect"
|
||||
import { Auth, MissingCredentialError } from "../route/auth"
|
||||
|
||||
const SCOPE = "https://www.googleapis.com/auth/cloud-platform"
|
||||
|
||||
export type OAuthOptions =
|
||||
| { readonly accessToken?: string; readonly auth?: never }
|
||||
| { readonly accessToken?: never; readonly auth?: Auth.Definition }
|
||||
|
||||
export type ApiKeyOptions =
|
||||
| (OAuthOptions & { readonly apiKey?: never })
|
||||
| { readonly accessToken?: never; readonly apiKey?: string; readonly auth?: never }
|
||||
|
||||
export const project = (value?: string) =>
|
||||
value ??
|
||||
process.env.GOOGLE_VERTEX_PROJECT ??
|
||||
process.env.GOOGLE_CLOUD_PROJECT ??
|
||||
process.env.GCP_PROJECT ??
|
||||
process.env.GCLOUD_PROJECT
|
||||
|
||||
export const location = (value: string | undefined, fallback: string) =>
|
||||
value ??
|
||||
process.env.GOOGLE_VERTEX_LOCATION ??
|
||||
process.env.GOOGLE_CLOUD_LOCATION ??
|
||||
process.env.VERTEX_LOCATION ??
|
||||
fallback
|
||||
|
||||
export const host = (location: string) => {
|
||||
if (location === "global") return "aiplatform.googleapis.com"
|
||||
// Jurisdictional multi-regions use Regional Endpoint Platform domains.
|
||||
if (location === "eu" || location === "us") return `aiplatform.${location}.rep.googleapis.com`
|
||||
return `${location}-aiplatform.googleapis.com`
|
||||
}
|
||||
|
||||
export const requireProject = (value: string | undefined) => {
|
||||
if (value) return value
|
||||
throw new Error("Google Vertex requires a project when baseURL is not configured")
|
||||
}
|
||||
|
||||
export const apiKey = (input: ApiKeyOptions) => {
|
||||
if (input.apiKey !== undefined && (input.accessToken !== undefined || input.auth !== undefined))
|
||||
throw new Error("Google Vertex apiKey cannot be combined with accessToken or auth")
|
||||
if (input.accessToken !== undefined || input.auth !== undefined) return undefined
|
||||
return input.apiKey ?? process.env.GOOGLE_VERTEX_API_KEY
|
||||
}
|
||||
|
||||
const adc = (project?: string) => {
|
||||
let client: Promise<AnyAuthClient> | undefined
|
||||
const loadClient = () => {
|
||||
if (client) return client
|
||||
client = import("google-auth-library").then(({ GoogleAuth }) =>
|
||||
new GoogleAuth({ projectId: project, scopes: [SCOPE] }).getClient(),
|
||||
)
|
||||
return client
|
||||
}
|
||||
return Auth.effect(
|
||||
Effect.tryPromise({
|
||||
try: async () => {
|
||||
const token = await (await loadClient()).getAccessToken()
|
||||
if (!token.token) throw new Error("Google ADC returned an empty access token")
|
||||
return Redacted.make(token.token)
|
||||
},
|
||||
catch: () => new MissingCredentialError("Google Application Default Credentials"),
|
||||
}),
|
||||
).bearer()
|
||||
}
|
||||
|
||||
export const oauth = (input: OAuthOptions, project?: string) => {
|
||||
if (input.accessToken !== undefined && input.auth !== undefined)
|
||||
throw new Error("Google Vertex accessToken cannot be combined with auth")
|
||||
if (input.auth) return input.auth
|
||||
if (input.accessToken !== undefined) return Auth.bearer(input.accessToken)
|
||||
return adc(project)
|
||||
}
|
||||
|
||||
export * as GoogleVertexShared from "./google-vertex-shared"
|
||||
@@ -1,98 +0,0 @@
|
||||
import type { ProviderPackage } from "../provider-package"
|
||||
import { Gemini } from "../protocols/gemini"
|
||||
import { Auth } from "../route/auth"
|
||||
import { Route, type RouteDefaultsInput } from "../route/client"
|
||||
import { Endpoint } from "../route/endpoint"
|
||||
import { Framing } from "../route/framing"
|
||||
import { ProviderID, type ModelID, type ProviderOptions } from "../schema"
|
||||
import { GoogleVertexShared } from "./google-vertex-shared"
|
||||
|
||||
export const id = ProviderID.make("google-vertex")
|
||||
|
||||
export type Config = RouteDefaultsInput &
|
||||
GoogleVertexShared.ApiKeyOptions & {
|
||||
readonly baseURL?: string
|
||||
readonly location?: string
|
||||
readonly project?: string
|
||||
}
|
||||
|
||||
export type Settings = ProviderPackage.Settings &
|
||||
(
|
||||
| { readonly accessToken?: string; readonly apiKey?: never }
|
||||
| { readonly accessToken?: never; readonly apiKey?: string }
|
||||
) & {
|
||||
readonly baseURL?: string
|
||||
readonly location?: string
|
||||
readonly project?: string
|
||||
readonly providerOptions?: ProviderOptions
|
||||
}
|
||||
|
||||
const route = Route.make({
|
||||
id: "google-vertex-gemini",
|
||||
provider: id,
|
||||
providerMetadataKey: "google",
|
||||
protocol: Gemini.protocol,
|
||||
endpoint: Endpoint.path(({ request }) => {
|
||||
const model = String(request.model.id)
|
||||
return `/${model.startsWith("endpoints/") ? model : `models/${model}`}:streamGenerateContent?alt=sse`
|
||||
}),
|
||||
auth: Auth.none,
|
||||
framing: Framing.sse,
|
||||
})
|
||||
|
||||
export const routes = [route]
|
||||
|
||||
const configuredRoute = (input: Config, modelID: string | ModelID) => {
|
||||
const {
|
||||
accessToken: _accessToken,
|
||||
apiKey: _apiKey,
|
||||
auth: _auth,
|
||||
baseURL,
|
||||
location: inputLocation,
|
||||
project: inputProject,
|
||||
...rest
|
||||
} = input
|
||||
const apiKey = GoogleVertexShared.apiKey(input)
|
||||
const endpointModel = String(modelID).startsWith("endpoints/")
|
||||
if (apiKey !== undefined && endpointModel)
|
||||
throw new Error("Google Vertex tuned models do not support Express Mode API keys")
|
||||
const location = GoogleVertexShared.location(inputLocation, "us-central1")
|
||||
const project = GoogleVertexShared.project(inputProject)
|
||||
const endpoint =
|
||||
baseURL ??
|
||||
(apiKey
|
||||
? "https://aiplatform.googleapis.com/v1/publishers/google"
|
||||
: `https://${GoogleVertexShared.host(location)}/v1beta1/projects/${GoogleVertexShared.requireProject(project)}/locations/${location}${endpointModel ? "" : "/publishers/google"}`)
|
||||
return route.with({
|
||||
...rest,
|
||||
endpoint: { baseURL: endpoint },
|
||||
auth: apiKey === undefined ? GoogleVertexShared.oauth(input, project) : Auth.header("x-goog-api-key", apiKey),
|
||||
})
|
||||
}
|
||||
|
||||
export const configure = (input: Config = {}) => {
|
||||
return {
|
||||
id,
|
||||
model: (modelID: string | ModelID) => configuredRoute(input, modelID).model({ id: modelID }),
|
||||
configure,
|
||||
}
|
||||
}
|
||||
|
||||
export const provider = {
|
||||
id,
|
||||
configure,
|
||||
}
|
||||
export const model: ProviderPackage.Definition<Settings>["model"] = (modelID, settings) => {
|
||||
if (settings.apiKey !== undefined && settings.accessToken !== undefined)
|
||||
throw new Error("Google Vertex apiKey cannot be combined with accessToken or auth")
|
||||
return configure({
|
||||
...(settings.apiKey === undefined ? { accessToken: settings.accessToken } : { apiKey: settings.apiKey }),
|
||||
baseURL: settings.baseURL,
|
||||
headers: settings.headers === undefined ? undefined : { ...settings.headers },
|
||||
http: settings.body === undefined ? undefined : { body: { ...settings.body } },
|
||||
limits: settings.limits,
|
||||
location: settings.location,
|
||||
project: settings.project,
|
||||
providerOptions: settings.providerOptions,
|
||||
}).model(modelID)
|
||||
}
|
||||
@@ -1,2 +0,0 @@
|
||||
export { model } from "../google-vertex-chat"
|
||||
export type { Settings } from "../google-vertex-chat"
|
||||
@@ -1,2 +0,0 @@
|
||||
export { model } from "../google-vertex"
|
||||
export type { Settings } from "../google-vertex"
|
||||
@@ -1,2 +0,0 @@
|
||||
export { model } from "../google-vertex-messages"
|
||||
export type { Settings } from "../google-vertex-messages"
|
||||
@@ -1,2 +0,0 @@
|
||||
export { model } from "../google-vertex-responses"
|
||||
export type { Settings } from "../google-vertex-responses"
|
||||
@@ -1 +0,0 @@
|
||||
export * from "../openai-compatible-responses"
|
||||
@@ -1,35 +0,0 @@
|
||||
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 +0,0 @@
|
||||
export * from "./route/index"
|
||||
Binary file not shown.
|
Before Width: | Height: | Size: 896 B |
-40
@@ -1,40 +0,0 @@
|
||||
{
|
||||
"version": 1,
|
||||
"metadata": {
|
||||
"provider": "minimax",
|
||||
"protocol": "anthropic-messages",
|
||||
"route": "anthropic-messages",
|
||||
"transport": "http",
|
||||
"model": "MiniMax-M3",
|
||||
"tags": [
|
||||
"prefix:anthropic-compatible-messages",
|
||||
"provider:minimax",
|
||||
"protocol:anthropic-messages",
|
||||
"text",
|
||||
"golden"
|
||||
],
|
||||
"name": "anthropic-compatible-messages/minimax-m3-anthropic-compatible-text",
|
||||
"recordedAt": "2026-07-18T03:42:22.893Z"
|
||||
},
|
||||
"interactions": [
|
||||
{
|
||||
"transport": "http",
|
||||
"request": {
|
||||
"method": "POST",
|
||||
"url": "https://api.minimax.io/anthropic/v1/messages",
|
||||
"headers": {
|
||||
"anthropic-version": "2023-06-01",
|
||||
"content-type": "application/json"
|
||||
},
|
||||
"body": "{\"model\":\"MiniMax-M3\",\"system\":[{\"type\":\"text\",\"text\":\"You are concise.\"}],\"messages\":[{\"role\":\"user\",\"content\":[{\"type\":\"text\",\"text\":\"Reply exactly with: Hello!\"}]}],\"stream\":true,\"max_tokens\":40,\"temperature\":0}"
|
||||
},
|
||||
"response": {
|
||||
"status": 200,
|
||||
"headers": {
|
||||
"content-type": "text/event-stream; charset=utf-8"
|
||||
},
|
||||
"body": "event: message_start\ndata: {\"type\":\"message_start\",\"message\":{\"id\":\"1a0b363d0882af316faebcec4d4855a8\",\"type\":\"message\",\"role\":\"assistant\",\"content\":[],\"model\":\"MiniMax-M3\",\"stop_reason\":null,\"stop_sequence\":null,\"usage\":{\"input_tokens\":53,\"output_tokens\":0,\"cache_creation_input_tokens\":0,\"cache_read_input_tokens\":114,\"service_tier\":\"standard\"},\"service_tier\":\"standard\"}}\n\nevent: ping\ndata: {\"type\":\"ping\"}\n\nevent: content_block_start\ndata: {\"type\":\"content_block_start\",\"index\":0,\"content_block\":{\"type\":\"text\",\"text\":\"\"}}\n\nevent: content_block_delta\ndata: {\"type\":\"content_block_delta\",\"index\":0,\"delta\":{\"type\":\"text_delta\",\"text\":\"Hello\"}}\n\nevent: content_block_delta\ndata: {\"type\":\"content_block_delta\",\"index\":0,\"delta\":{\"type\":\"text_delta\",\"text\":\"!\"}}\n\nevent: content_block_stop\ndata: {\"type\":\"content_block_stop\",\"index\":0}\n\nevent: message_delta\ndata: {\"type\":\"message_delta\",\"delta\":{\"stop_reason\":\"end_turn\"},\"usage\":{\"input_tokens\":53,\"output_tokens\":2,\"cache_read_input_tokens\":114,\"service_tier\":\"standard\"}}\n\nevent: message_stop\ndata: {\"type\":\"message_stop\"}\n\n"
|
||||
}
|
||||
}
|
||||
]
|
||||
}
|
||||
-41
@@ -1,41 +0,0 @@
|
||||
{
|
||||
"version": 1,
|
||||
"metadata": {
|
||||
"provider": "minimax",
|
||||
"protocol": "anthropic-messages",
|
||||
"route": "anthropic-messages",
|
||||
"transport": "http",
|
||||
"model": "MiniMax-M3",
|
||||
"tags": [
|
||||
"prefix:anthropic-compatible-messages",
|
||||
"provider:minimax",
|
||||
"protocol:anthropic-messages",
|
||||
"tool",
|
||||
"tool-call",
|
||||
"golden"
|
||||
],
|
||||
"name": "anthropic-compatible-messages/minimax-m3-anthropic-compatible-tool-call",
|
||||
"recordedAt": "2026-07-18T03:42:23.876Z"
|
||||
},
|
||||
"interactions": [
|
||||
{
|
||||
"transport": "http",
|
||||
"request": {
|
||||
"method": "POST",
|
||||
"url": "https://api.minimax.io/anthropic/v1/messages",
|
||||
"headers": {
|
||||
"anthropic-version": "2023-06-01",
|
||||
"content-type": "application/json"
|
||||
},
|
||||
"body": "{\"model\":\"MiniMax-M3\",\"system\":[{\"type\":\"text\",\"text\":\"Call tools exactly as requested.\"}],\"messages\":[{\"role\":\"user\",\"content\":[{\"type\":\"text\",\"text\":\"Call get_weather with city exactly Paris.\"}]}],\"tools\":[{\"name\":\"get_weather\",\"description\":\"Get current weather for a city.\",\"input_schema\":{\"type\":\"object\",\"properties\":{\"city\":{\"type\":\"string\"}},\"required\":[\"city\"],\"additionalProperties\":false}}],\"tool_choice\":{\"type\":\"tool\",\"name\":\"get_weather\"},\"stream\":true,\"max_tokens\":80,\"temperature\":0}"
|
||||
},
|
||||
"response": {
|
||||
"status": 200,
|
||||
"headers": {
|
||||
"content-type": "text/event-stream; charset=utf-8"
|
||||
},
|
||||
"body": "event: message_start\ndata: {\"type\":\"message_start\",\"message\":{\"id\":\"6731ecc323233459d1792df9a733dd98\",\"type\":\"message\",\"role\":\"assistant\",\"content\":[],\"model\":\"MiniMax-M3\",\"stop_reason\":null,\"stop_sequence\":null,\"usage\":{\"input_tokens\":0,\"output_tokens\":0,\"cache_creation_input_tokens\":0,\"cache_read_input_tokens\":404,\"service_tier\":\"standard\"},\"service_tier\":\"standard\"}}\n\nevent: ping\ndata: {\"type\":\"ping\"}\n\nevent: content_block_start\ndata: {\"type\":\"content_block_start\",\"index\":0,\"content_block\":{\"type\":\"tool_use\",\"id\":\"call_function_vkxtif4epmvm_1\",\"name\":\"get_weather\",\"input\":{}}}\n\nevent: content_block_delta\ndata: {\"type\":\"content_block_delta\",\"index\":0,\"delta\":{\"type\":\"input_json_delta\",\"partial_json\":\"{\\\"city\\\": \\\"Paris\"}}\n\nevent: content_block_delta\ndata: {\"type\":\"content_block_delta\",\"index\":0,\"delta\":{\"type\":\"input_json_delta\",\"partial_json\":\"\\\"}\"}}\n\nevent: content_block_stop\ndata: {\"type\":\"content_block_stop\",\"index\":0}\n\nevent: message_delta\ndata: {\"type\":\"message_delta\",\"delta\":{\"stop_reason\":\"tool_use\"},\"usage\":{\"input_tokens\":290,\"output_tokens\":27,\"cache_read_input_tokens\":114,\"service_tier\":\"standard\"}}\n\nevent: message_stop\ndata: {\"type\":\"message_stop\"}\n\n"
|
||||
}
|
||||
}
|
||||
]
|
||||
}
|
||||
-60
@@ -1,60 +0,0 @@
|
||||
{
|
||||
"version": 1,
|
||||
"metadata": {
|
||||
"provider": "minimax",
|
||||
"protocol": "anthropic-messages",
|
||||
"route": "anthropic-messages",
|
||||
"transport": "http",
|
||||
"model": "MiniMax-M3",
|
||||
"tags": [
|
||||
"prefix:anthropic-compatible-messages",
|
||||
"provider:minimax",
|
||||
"protocol:anthropic-messages",
|
||||
"tool",
|
||||
"tool-loop",
|
||||
"golden"
|
||||
],
|
||||
"name": "anthropic-compatible-messages/minimax-m3-anthropic-compatible-tool-loop",
|
||||
"recordedAt": "2026-07-18T03:42:25.248Z"
|
||||
},
|
||||
"interactions": [
|
||||
{
|
||||
"transport": "http",
|
||||
"request": {
|
||||
"method": "POST",
|
||||
"url": "https://api.minimax.io/anthropic/v1/messages",
|
||||
"headers": {
|
||||
"anthropic-version": "2023-06-01",
|
||||
"content-type": "application/json"
|
||||
},
|
||||
"body": "{\"model\":\"MiniMax-M3\",\"system\":[{\"type\":\"text\",\"text\":\"Use the get_weather tool exactly once. After the tool result, reply exactly: Paris is sunny.\"}],\"messages\":[{\"role\":\"user\",\"content\":[{\"type\":\"text\",\"text\":\"What is the weather in Paris?\"}]}],\"tools\":[{\"name\":\"get_weather\",\"description\":\"Get current weather for a city.\",\"input_schema\":{\"type\":\"object\",\"properties\":{\"city\":{\"type\":\"string\"}},\"required\":[\"city\"],\"additionalProperties\":false}}],\"stream\":true,\"max_tokens\":80,\"temperature\":0}"
|
||||
},
|
||||
"response": {
|
||||
"status": 200,
|
||||
"headers": {
|
||||
"content-type": "text/event-stream; charset=utf-8"
|
||||
},
|
||||
"body": "event: message_start\ndata: {\"type\":\"message_start\",\"message\":{\"id\":\"3807fa12f9ecb9357df511e099da6da0\",\"type\":\"message\",\"role\":\"assistant\",\"content\":[],\"model\":\"MiniMax-M3\",\"stop_reason\":null,\"stop_sequence\":null,\"usage\":{\"input_tokens\":0,\"output_tokens\":0,\"cache_creation_input_tokens\":0,\"cache_read_input_tokens\":417,\"service_tier\":\"standard\"},\"service_tier\":\"standard\"}}\n\nevent: ping\ndata: {\"type\":\"ping\"}\n\nevent: content_block_start\ndata: {\"type\":\"content_block_start\",\"index\":0,\"content_block\":{\"type\":\"tool_use\",\"id\":\"call_function_yr64rwmre4gr_1\",\"name\":\"get_weather\",\"input\":{}}}\n\nevent: content_block_delta\ndata: {\"type\":\"content_block_delta\",\"index\":0,\"delta\":{\"type\":\"input_json_delta\",\"partial_json\":\"{\\\"city\\\": \\\"Paris\"}}\n\nevent: content_block_delta\ndata: {\"type\":\"content_block_delta\",\"index\":0,\"delta\":{\"type\":\"input_json_delta\",\"partial_json\":\"\\\"}\"}}\n\nevent: content_block_stop\ndata: {\"type\":\"content_block_stop\",\"index\":0}\n\nevent: message_delta\ndata: {\"type\":\"message_delta\",\"delta\":{\"stop_reason\":\"tool_use\"},\"usage\":{\"input_tokens\":303,\"output_tokens\":27,\"cache_read_input_tokens\":114,\"service_tier\":\"standard\"}}\n\nevent: message_stop\ndata: {\"type\":\"message_stop\"}\n\n"
|
||||
}
|
||||
},
|
||||
{
|
||||
"transport": "http",
|
||||
"request": {
|
||||
"method": "POST",
|
||||
"url": "https://api.minimax.io/anthropic/v1/messages",
|
||||
"headers": {
|
||||
"anthropic-version": "2023-06-01",
|
||||
"content-type": "application/json"
|
||||
},
|
||||
"body": "{\"model\":\"MiniMax-M3\",\"system\":[{\"type\":\"text\",\"text\":\"Use the get_weather tool exactly once. After the tool result, reply exactly: Paris is sunny.\"}],\"messages\":[{\"role\":\"user\",\"content\":[{\"type\":\"text\",\"text\":\"What is the weather in Paris?\"}]},{\"role\":\"assistant\",\"content\":[{\"type\":\"tool_use\",\"id\":\"call_function_yr64rwmre4gr_1\",\"name\":\"get_weather\",\"input\":{\"city\":\"Paris\"}}]},{\"role\":\"user\",\"content\":[{\"type\":\"tool_result\",\"tool_use_id\":\"call_function_yr64rwmre4gr_1\",\"content\":\"{\\\"temperature\\\":22,\\\"condition\\\":\\\"sunny\\\"}\"}]}],\"tools\":[{\"name\":\"get_weather\",\"description\":\"Get current weather for a city.\",\"input_schema\":{\"type\":\"object\",\"properties\":{\"city\":{\"type\":\"string\"}},\"required\":[\"city\"],\"additionalProperties\":false}}],\"stream\":true,\"max_tokens\":80,\"temperature\":0}"
|
||||
},
|
||||
"response": {
|
||||
"status": 200,
|
||||
"headers": {
|
||||
"content-type": "text/event-stream; charset=utf-8"
|
||||
},
|
||||
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-50
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"body": "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",
|
||||
"bodyEncoding": "base64"
|
||||
}
|
||||
}
|
||||
]
|
||||
}
|
||||
@@ -1,35 +0,0 @@
|
||||
{
|
||||
"version": 1,
|
||||
"metadata": {
|
||||
"tags": [
|
||||
"prefix:pdf",
|
||||
"pdf",
|
||||
"provider:amazon-bedrock",
|
||||
"protocol:bedrock-converse",
|
||||
"user-input"
|
||||
],
|
||||
"name": "pdf/bedrock-user-input",
|
||||
"recordedAt": "2026-07-22T18:15:48.408Z"
|
||||
},
|
||||
"interactions": [
|
||||
{
|
||||
"transport": "http",
|
||||
"request": {
|
||||
"method": "POST",
|
||||
"url": "https://bedrock-runtime.us-east-1.amazonaws.com/model/us.anthropic.claude-haiku-4-5-20251001-v1%3A0/converse-stream",
|
||||
"headers": {
|
||||
"content-type": "application/json"
|
||||
},
|
||||
"body": "{\"modelId\":\"us.anthropic.claude-haiku-4-5-20251001-v1:0\",\"messages\":[{\"role\":\"user\",\"content\":[{\"document\":{\"format\":\"pdf\",\"name\":\"verification\",\"source\":{\"bytes\":\"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\"}}},{\"text\":\"Return only the verification code from the PDF.\"}]}],\"inferenceConfig\":{\"maxTokens\":40,\"temperature\":0}}"
|
||||
},
|
||||
"response": {
|
||||
"status": 200,
|
||||
"headers": {
|
||||
"content-type": "application/vnd.amazon.eventstream"
|
||||
},
|
||||
"body": "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",
|
||||
"bodyEncoding": "base64"
|
||||
}
|
||||
}
|
||||
]
|
||||
}
|
||||
@@ -1,53 +0,0 @@
|
||||
{
|
||||
"version": 1,
|
||||
"metadata": {
|
||||
"tags": [
|
||||
"prefix:pdf",
|
||||
"pdf",
|
||||
"provider:google",
|
||||
"protocol:gemini",
|
||||
"tool",
|
||||
"tool-result"
|
||||
],
|
||||
"name": "pdf/gemini-tool-result",
|
||||
"recordedAt": "2026-07-22T18:21:59.606Z"
|
||||
},
|
||||
"interactions": [
|
||||
{
|
||||
"transport": "http",
|
||||
"request": {
|
||||
"method": "POST",
|
||||
"url": "https://generativelanguage.googleapis.com/v1beta/models/gemini-3.5-flash:streamGenerateContent?alt=sse",
|
||||
"headers": {
|
||||
"content-type": "application/json"
|
||||
},
|
||||
"body": "{\"contents\":[{\"role\":\"user\",\"parts\":[{\"text\":\"Use read_pdf with path verification.pdf and return the verification code.\"}]}],\"systemInstruction\":{\"parts\":[{\"text\":\"Call read_pdf exactly once with path verification.pdf, then reply only with the verification code from its PDF.\"}]},\"tools\":[{\"functionDeclarations\":[{\"name\":\"read_pdf\",\"description\":\"Read the attached PDF.\",\"parameters\":{\"required\":[\"path\"],\"type\":\"object\",\"properties\":{\"path\":{\"type\":\"string\"}}}}]}],\"generationConfig\":{\"maxOutputTokens\":256,\"temperature\":0}}"
|
||||
},
|
||||
"response": {
|
||||
"status": 200,
|
||||
"headers": {
|
||||
"content-type": "text/event-stream"
|
||||
},
|
||||
"body": "data: {\"candidates\": [{\"content\": {\"parts\": [{\"functionCall\": {\"name\": \"read_pdf\",\"args\": {\"path\": \"verification.pdf\"},\"id\": \"58shgmez\"},\"thoughtSignature\": \"EqkCCqYCARFNMg/JrCTv5i3zYENFBVpZNFL3pbzJmi5Eu387ncF703xFMB4pwyaP7a1gi49EqBhCI2hWOpesU5nZQOLAhGgExKGa2GM+HzpEB5g62r0NFblm/BGkVZaImTuHR7bytfRC5jHQlHKo4OS27OLUVjvkMkBIYsvjhDErY7niERbXJVpyxTVqUf1GgZMSu8kC9/5WDlMs9xVKNT/6KMW4PhhSR9nXg4KZUa+bC03/ydhsWWgBa5aLCgvTq7WPj217xIsmUkSiRedIffPsUSNjYdMHUvWi8bOlvM1veEEP6GIfv5h9gXXzjnHbEHfQxV8PZuBAyY7iM6nqyfkJNdkZ1HdB7DXMBsMsRN6SgrIrFoXX2WaGrkoEI5tdZx1t/gdwF1jEVT6k\"}],\"role\": \"model\"},\"index\": 0}],\"usageMetadata\": {\"promptTokenCount\": 81,\"candidatesTokenCount\": 18,\"totalTokenCount\": 151,\"promptTokensDetails\": [{\"modality\": \"TEXT\",\"tokenCount\": 81}],\"thoughtsTokenCount\": 52,\"serviceTier\": \"standard\"},\"modelVersion\": \"gemini-3.5-flash\",\"responseId\": \"RAphaui3OaSHz7IPy8Kb4Ak\"}\r\n\r\ndata: {\"candidates\": [{\"content\": {\"parts\": [{\"text\": \"\"}],\"role\": \"model\"},\"finishReason\": \"STOP\",\"index\": 0}],\"usageMetadata\": {\"promptTokenCount\": 81,\"candidatesTokenCount\": 18,\"totalTokenCount\": 151,\"promptTokensDetails\": [{\"modality\": \"TEXT\",\"tokenCount\": 81}],\"thoughtsTokenCount\": 52,\"serviceTier\": \"standard\"},\"modelVersion\": \"gemini-3.5-flash\",\"responseId\": \"RAphaui3OaSHz7IPy8Kb4Ak\"}\r\n\r\n"
|
||||
}
|
||||
},
|
||||
{
|
||||
"transport": "http",
|
||||
"request": {
|
||||
"method": "POST",
|
||||
"url": "https://generativelanguage.googleapis.com/v1beta/models/gemini-3.5-flash:streamGenerateContent?alt=sse",
|
||||
"headers": {
|
||||
"content-type": "application/json"
|
||||
},
|
||||
"body": "{\"contents\":[{\"role\":\"user\",\"parts\":[{\"text\":\"Use read_pdf with path verification.pdf and return the verification code.\"}]},{\"role\":\"model\",\"parts\":[{\"functionCall\":{\"id\":\"58shgmez\",\"name\":\"read_pdf\",\"args\":{\"path\":\"verification.pdf\"}},\"thoughtSignature\":\"EqkCCqYCARFNMg/JrCTv5i3zYENFBVpZNFL3pbzJmi5Eu387ncF703xFMB4pwyaP7a1gi49EqBhCI2hWOpesU5nZQOLAhGgExKGa2GM+HzpEB5g62r0NFblm/BGkVZaImTuHR7bytfRC5jHQlHKo4OS27OLUVjvkMkBIYsvjhDErY7niERbXJVpyxTVqUf1GgZMSu8kC9/5WDlMs9xVKNT/6KMW4PhhSR9nXg4KZUa+bC03/ydhsWWgBa5aLCgvTq7WPj217xIsmUkSiRedIffPsUSNjYdMHUvWi8bOlvM1veEEP6GIfv5h9gXXzjnHbEHfQxV8PZuBAyY7iM6nqyfkJNdkZ1HdB7DXMBsMsRN6SgrIrFoXX2WaGrkoEI5tdZx1t/gdwF1jEVT6k\"}]},{\"role\":\"user\",\"parts\":[{\"functionResponse\":{\"id\":\"58shgmez\",\"name\":\"read_pdf\",\"response\":{\"name\":\"read_pdf\",\"content\":\"PDF read successfully\"},\"parts\":[{\"inlineData\":{\"mimeType\":\"application/pdf\",\"data\":\"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\"}}]}}]}],\"systemInstruction\":{\"parts\":[{\"text\":\"Call read_pdf exactly once with path verification.pdf, then reply only with the verification code from its PDF.\"}]},\"tools\":[{\"functionDeclarations\":[{\"name\":\"read_pdf\",\"description\":\"Read the attached PDF.\",\"parameters\":{\"required\":[\"path\"],\"type\":\"object\",\"properties\":{\"path\":{\"type\":\"string\"}}}}]}],\"generationConfig\":{\"maxOutputTokens\":256,\"temperature\":0}}"
|
||||
},
|
||||
"response": {
|
||||
"status": 200,
|
||||
"headers": {
|
||||
"content-type": "text/event-stream"
|
||||
},
|
||||
"body": "data: {\"candidates\": [{\"content\": {\"parts\": [{\"text\": \"ORCHID-7391\"}],\"role\": \"model\"},\"index\": 0}],\"usageMetadata\": {\"promptTokenCount\": 123,\"candidatesTokenCount\": 8,\"totalTokenCount\": 184,\"promptTokensDetails\": [{\"modality\": \"TEXT\",\"tokenCount\": 123}],\"thoughtsTokenCount\": 53,\"serviceTier\": \"standard\"},\"modelVersion\": \"gemini-3.5-flash\",\"responseId\": \"RgphaoL6CMjQz7IPjOnEmQI\"}\r\n\r\ndata: {\"candidates\": [{\"content\": {\"parts\": [{\"text\": \"\",\"thoughtSignature\": \"EqECCp4CARFNMg9obBl8O6iU9lawUIWiE+1vztZm9NtaT9FuyJz343hd9ruz+xPco4Q1DY1GF81ZiSI2ElBkt8Wfwsqtix9LNGSMvbZhhk/ZnB54t05M/Dft1kujcMvEdZUWUI/jWaJ349tO1bKVH9MacG5+gl0n4y8DwyQZSV3xIcet547drSkcA/TM03RB+yj1/dcLHsvUjmv9EnO897vZgO2Dk4tbZ2NyCtOeQ3JKVhUTLg2pjkGk+POCNiOdESWiUzxdQKw9LiV6nnzi071tXNiMeVimq6d7xAzRVNapI2uXynvn9Uk3eyn85purOFa8cKriK9oD6vcyGMqgd9+gu2m3to0IHqd7o+2YSr1m5qV1xT1R2/WRQEtb1b1AuOAU6w==\"}],\"role\": \"model\"},\"finishReason\": \"STOP\",\"index\": 0}],\"usageMetadata\": {\"promptTokenCount\": 1277,\"candidatesTokenCount\": 8,\"totalTokenCount\": 1338,\"promptTokensDetails\": [{\"modality\": \"IMAGE\",\"tokenCount\": 1102},{\"modality\": \"TEXT\",\"tokenCount\": 175}],\"thoughtsTokenCount\": 53,\"serviceTier\": \"standard\"},\"modelVersion\": \"gemini-3.5-flash\",\"responseId\": \"RgphaoL6CMjQz7IPjOnEmQI\"}\r\n\r\n"
|
||||
}
|
||||
}
|
||||
]
|
||||
}
|
||||
@@ -1,34 +0,0 @@
|
||||
{
|
||||
"version": 1,
|
||||
"metadata": {
|
||||
"tags": [
|
||||
"prefix:pdf",
|
||||
"pdf",
|
||||
"provider:google",
|
||||
"protocol:gemini",
|
||||
"user-input"
|
||||
],
|
||||
"name": "pdf/gemini-user-input",
|
||||
"recordedAt": "2026-07-22T18:20:55.140Z"
|
||||
},
|
||||
"interactions": [
|
||||
{
|
||||
"transport": "http",
|
||||
"request": {
|
||||
"method": "POST",
|
||||
"url": "https://generativelanguage.googleapis.com/v1beta/models/gemini-3.5-flash:streamGenerateContent?alt=sse",
|
||||
"headers": {
|
||||
"content-type": "application/json"
|
||||
},
|
||||
"body": "{\"contents\":[{\"role\":\"user\",\"parts\":[{\"inlineData\":{\"mimeType\":\"application/pdf\",\"data\":\"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\"}},{\"text\":\"Return only the verification code from the PDF.\"}]}],\"generationConfig\":{\"maxOutputTokens\":256,\"temperature\":0}}"
|
||||
},
|
||||
"response": {
|
||||
"status": 200,
|
||||
"headers": {
|
||||
"content-type": "text/event-stream"
|
||||
},
|
||||
"body": "data: {\"candidates\": [{\"content\": {\"parts\": [{\"text\": \"ORCH\"}],\"role\": \"model\"},\"index\": 0}],\"usageMetadata\": {\"promptTokenCount\": 10,\"candidatesTokenCount\": 2,\"totalTokenCount\": 127,\"promptTokensDetails\": [{\"modality\": \"TEXT\",\"tokenCount\": 10}],\"thoughtsTokenCount\": 115,\"serviceTier\": \"standard\"},\"modelVersion\": \"gemini-3.5-flash\",\"responseId\": \"BQpharW2KaPgz7IP6uSLiAw\"}\r\n\r\ndata: {\"candidates\": [{\"content\": {\"parts\": [{\"text\": \"ID-7391\"}],\"role\": \"model\"},\"index\": 0}],\"usageMetadata\": {\"promptTokenCount\": 10,\"candidatesTokenCount\": 8,\"totalTokenCount\": 133,\"promptTokensDetails\": [{\"modality\": \"TEXT\",\"tokenCount\": 10}],\"thoughtsTokenCount\": 115,\"serviceTier\": \"standard\"},\"modelVersion\": \"gemini-3.5-flash\",\"responseId\": \"BQpharW2KaPgz7IP6uSLiAw\"}\r\n\r\ndata: {\"candidates\": [{\"content\": {\"parts\": [{\"text\": \"\",\"thoughtSignature\": \"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\"}],\"role\": \"model\"},\"finishReason\": \"STOP\",\"index\": 0}],\"usageMetadata\": {\"promptTokenCount\": 530,\"candidatesTokenCount\": 8,\"totalTokenCount\": 653,\"promptTokensDetails\": [{\"modality\": \"IMAGE\",\"tokenCount\": 520},{\"modality\": \"TEXT\",\"tokenCount\": 10}],\"thoughtsTokenCount\": 115,\"serviceTier\": \"standard\"},\"modelVersion\": \"gemini-3.5-flash\",\"responseId\": \"BQpharW2KaPgz7IP6uSLiAw\"}\r\n\r\n"
|
||||
}
|
||||
}
|
||||
]
|
||||
}
|
||||
File diff suppressed because one or more lines are too long
File diff suppressed because one or more lines are too long
File diff suppressed because one or more lines are too long
File diff suppressed because one or more lines are too long
-55
File diff suppressed because one or more lines are too long
File diff suppressed because one or more lines are too long
File diff suppressed because one or more lines are too long
File diff suppressed because one or more lines are too long
@@ -1,28 +0,0 @@
|
||||
{
|
||||
"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\"}"
|
||||
}
|
||||
}
|
||||
]
|
||||
}
|
||||
@@ -1,578 +0,0 @@
|
||||
import { describe, expect } from "bun:test"
|
||||
import { Effect, Layer } from "effect"
|
||||
import { HttpClientRequest } from "effect/unstable/http"
|
||||
import { Image, ImageClient, ImageInput } from "../src"
|
||||
import { Google, OpenAI, XAI, ZAI } from "../src/providers"
|
||||
import { it } from "./lib/effect"
|
||||
import { dynamicResponse } from "./lib/http"
|
||||
|
||||
describe("Image", () => {
|
||||
it.effect("generates images through the OpenAI Images API", () =>
|
||||
Effect.gen(function* () {
|
||||
const response = yield* Image.generate({
|
||||
model: OpenAI.configure({
|
||||
apiKey: "test",
|
||||
baseURL: "https://api.openai.test/v1",
|
||||
queryParams: { "api-version": "v1" },
|
||||
http: { body: { deployment: "test" }, headers: { "x-default": "yes" } },
|
||||
}).image("gpt-image-2"),
|
||||
prompt: "A robot tending a rooftop garden",
|
||||
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: { output_format: "webp", output_compression: 50, future_option: "http", request_metadata: "value" },
|
||||
headers: { "x-request": "yes" },
|
||||
query: { trace: "1" },
|
||||
},
|
||||
})
|
||||
|
||||
expect(response.images).toHaveLength(2)
|
||||
expect(response.image?.mediaType).toBe("image/webp")
|
||||
expect(response.image?.data).toEqual(Uint8Array.from([1, 2, 3]))
|
||||
expect(response.image?.providerMetadata).toEqual({ openai: { revisedPrompt: "A precise robot" } })
|
||||
expect(response.usage?.totalTokens).toBe(12)
|
||||
}).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/generations?api-version=v1&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: "gpt-image-2",
|
||||
prompt: "A robot tending a rooftop garden",
|
||||
n: 2,
|
||||
size: "2048x2048",
|
||||
quality: "future-quality",
|
||||
background: "opaque",
|
||||
output_format: "webp",
|
||||
output_compression: 50,
|
||||
native_default: true,
|
||||
future_option: "http",
|
||||
deployment: "test",
|
||||
request_metadata: "value",
|
||||
})
|
||||
return input.respond(
|
||||
JSON.stringify({
|
||||
data: [{ b64_json: "AQID", revised_prompt: "A precise robot" }, { b64_json: "BAUG" }],
|
||||
output_format: "webp",
|
||||
usage: { input_tokens: 4, output_tokens: 8, total_tokens: 12 },
|
||||
}),
|
||||
{ headers: { "content-type": "application/json" } },
|
||||
)
|
||||
}),
|
||||
),
|
||||
),
|
||||
),
|
||||
),
|
||||
),
|
||||
)
|
||||
|
||||
it.effect("preserves native snake_case and unknown request options", () =>
|
||||
Image.generate({
|
||||
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.tap((response) =>
|
||||
Effect.sync(() => {
|
||||
expect(response.image?.mediaType).toBe("image/avif")
|
||||
}),
|
||||
),
|
||||
Effect.provide(
|
||||
ImageClient.layer.pipe(
|
||||
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" } },
|
||||
),
|
||||
),
|
||||
),
|
||||
),
|
||||
),
|
||||
),
|
||||
),
|
||||
)
|
||||
})
|
||||
@@ -1,161 +0,0 @@
|
||||
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") })
|
||||
@@ -1,29 +0,0 @@
|
||||
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
|
||||
@@ -1,296 +0,0 @@
|
||||
import { describe, expect, test } from "bun:test"
|
||||
import { model } from "@opencode-ai/ai/providers/openai"
|
||||
|
||||
describe("provider package entrypoints", () => {
|
||||
test("semantic API aliases expose the same contract", async () => {
|
||||
const modules = await Promise.all([
|
||||
import("@opencode-ai/ai/providers/openai"),
|
||||
import("@opencode-ai/ai/providers/openai/responses"),
|
||||
import("@opencode-ai/ai/providers/openai/chat"),
|
||||
import("@opencode-ai/ai/providers/anthropic"),
|
||||
import("@opencode-ai/ai/providers/anthropic-compatible"),
|
||||
import("@opencode-ai/ai/providers/openai-compatible"),
|
||||
import("@opencode-ai/ai/providers/openai-compatible/responses"),
|
||||
import("@opencode-ai/ai/providers/amazon-bedrock"),
|
||||
import("@opencode-ai/ai/providers/azure"),
|
||||
import("@opencode-ai/ai/providers/azure/responses"),
|
||||
import("@opencode-ai/ai/providers/azure/chat"),
|
||||
import("@opencode-ai/ai/providers/google"),
|
||||
import("@opencode-ai/ai/providers/google-vertex"),
|
||||
import("@opencode-ai/ai/providers/google-vertex/gemini"),
|
||||
import("@opencode-ai/ai/providers/google-vertex/chat"),
|
||||
import("@opencode-ai/ai/providers/google-vertex/responses"),
|
||||
import("@opencode-ai/ai/providers/google-vertex/messages"),
|
||||
])
|
||||
|
||||
for (const module of modules) expect(module.model).toBeFunction()
|
||||
expect(modules[0].model).toBe(modules[1].model)
|
||||
expect(modules[8].model).toBe(modules[9].model)
|
||||
expect(modules[12].model).toBe(modules[13].model)
|
||||
})
|
||||
|
||||
test("maps package settings onto the executable model", () => {
|
||||
const selected = model("gpt-5", {
|
||||
apiKey: "fixture",
|
||||
baseURL: "https://api.openai.test/v1",
|
||||
headers: { "x-application": "opencode" },
|
||||
body: { service_tier: "priority" },
|
||||
limits: { context: 200_000, output: 64_000 },
|
||||
unrelatedInheritedSetting: true,
|
||||
})
|
||||
|
||||
expect(selected.route.id).toBe("openai-responses")
|
||||
expect(selected.route.defaults.headers).toEqual({ "x-application": "opencode" })
|
||||
expect(selected.route.defaults.http?.body).toEqual({ service_tier: "priority" })
|
||||
expect(selected.route.defaults.limits).toEqual({ context: 200_000, output: 64_000 })
|
||||
})
|
||||
|
||||
test("selects transport without changing the semantic API", () => {
|
||||
expect(model("gpt-5", { apiKey: "fixture" }).route.id).toBe("openai-responses")
|
||||
expect(model("gpt-5", { apiKey: "fixture", transport: "websocket" }).route.id).toBe("openai-responses-websocket")
|
||||
})
|
||||
|
||||
test("maps OpenAI-compatible Responses settings onto the executable model", async () => {
|
||||
const OpenAICompatibleResponses = await import("@opencode-ai/ai/providers/openai-compatible/responses")
|
||||
const selected = OpenAICompatibleResponses.model("custom-model", {
|
||||
apiKey: "fixture",
|
||||
baseURL: "https://responses.example.test/v1",
|
||||
provider: "example",
|
||||
headers: { "x-application": "opencode" },
|
||||
body: { service_tier: "priority" },
|
||||
limits: { context: 200_000, output: 64_000 },
|
||||
providerOptions: { openai: { reasoningEffort: "low", store: true } },
|
||||
})
|
||||
|
||||
expect(String(selected.provider)).toBe("example")
|
||||
expect(selected.route.id).toBe("openai-compatible-responses")
|
||||
expect(selected.route.endpoint).toMatchObject({
|
||||
baseURL: "https://responses.example.test/v1",
|
||||
path: "/responses",
|
||||
})
|
||||
expect(selected.route.defaults.headers).toEqual({ "x-application": "opencode" })
|
||||
expect(selected.route.defaults.http?.body).toEqual({ service_tier: "priority" })
|
||||
expect(selected.route.defaults.limits).toEqual({ context: 200_000, output: 64_000 })
|
||||
expect(selected.route.defaults.providerOptions).toEqual({
|
||||
openai: { reasoningEffort: "low", store: true },
|
||||
})
|
||||
})
|
||||
|
||||
test("maps Anthropic-compatible settings onto the executable model", async () => {
|
||||
const AnthropicCompatible = await import("@opencode-ai/ai/providers/anthropic-compatible")
|
||||
const selected = AnthropicCompatible.model("compatible-model", {
|
||||
apiKey: "fixture",
|
||||
baseURL: "https://messages.example.test/v1",
|
||||
provider: "example",
|
||||
headers: { "x-application": "opencode" },
|
||||
body: { metadata: { user_id: "user_1" } },
|
||||
limits: { context: 200_000, output: 64_000 },
|
||||
})
|
||||
|
||||
expect(String(selected.provider)).toBe("example")
|
||||
expect(selected.route.id).toBe("anthropic-messages")
|
||||
expect(selected.route.endpoint).toMatchObject({
|
||||
baseURL: "https://messages.example.test/v1",
|
||||
path: "/messages",
|
||||
})
|
||||
expect(selected.route.defaults.headers).toEqual({ "x-application": "opencode" })
|
||||
expect(selected.route.defaults.http?.body).toEqual({ metadata: { user_id: "user_1" } })
|
||||
expect(selected.route.defaults.limits).toEqual({ context: 200_000, output: 64_000 })
|
||||
})
|
||||
|
||||
test("requires an Anthropic-compatible base URL at runtime", async () => {
|
||||
const AnthropicCompatible = await import("@opencode-ai/ai/providers/anthropic-compatible")
|
||||
expect(() =>
|
||||
Reflect.apply(AnthropicCompatible.model, undefined, ["compatible-model", { apiKey: "fixture" }]),
|
||||
).toThrow("Anthropic-compatible providers require a baseURL")
|
||||
})
|
||||
|
||||
test("rejects conflicting Anthropic-compatible auth settings at runtime", async () => {
|
||||
const Anthropic = await import("@opencode-ai/ai/providers/anthropic")
|
||||
const AnthropicCompatible = await import("@opencode-ai/ai/providers/anthropic-compatible")
|
||||
expect(() =>
|
||||
Reflect.apply(AnthropicCompatible.model, undefined, [
|
||||
"compatible-model",
|
||||
{
|
||||
apiKey: "fixture",
|
||||
authToken: "token",
|
||||
baseURL: "https://messages.example.test/v1",
|
||||
},
|
||||
]),
|
||||
).toThrow("Anthropic-compatible apiKey cannot be combined with authToken")
|
||||
expect(() =>
|
||||
Reflect.apply(Anthropic.model, undefined, ["claude-sonnet-4-6", { apiKey: "fixture", authToken: "token" }]),
|
||||
).toThrow("Anthropic apiKey cannot be combined with authToken")
|
||||
})
|
||||
|
||||
test("maps legacy OpenAI organization and project settings to headers", () => {
|
||||
const selected = model("gpt-5", {
|
||||
apiKey: "fixture",
|
||||
organization: "org_123",
|
||||
project: "proj_123",
|
||||
})
|
||||
|
||||
expect(selected.route.defaults.headers).toMatchObject({
|
||||
"OpenAI-Organization": "org_123",
|
||||
"OpenAI-Project": "proj_123",
|
||||
})
|
||||
})
|
||||
|
||||
test("selects Azure API entrypoints with the same model contract", async () => {
|
||||
const Azure = await import("@opencode-ai/ai/providers/azure")
|
||||
const AzureChat = await import("@opencode-ai/ai/providers/azure/chat")
|
||||
const AzureResponses = await import("@opencode-ai/ai/providers/azure/responses")
|
||||
const settings = {
|
||||
apiKey: "fixture",
|
||||
resourceName: "opencode-test",
|
||||
headers: { "x-application": "opencode" },
|
||||
body: { service_tier: "priority" },
|
||||
limits: { context: 200_000, output: 64_000 },
|
||||
}
|
||||
|
||||
const responses = AzureResponses.model("deployment", settings)
|
||||
const chat = AzureChat.model("deployment", settings)
|
||||
|
||||
expect(Azure.model("deployment", settings).route.id).toBe("azure-openai-responses")
|
||||
expect(responses.route.id).toBe("azure-openai-responses")
|
||||
expect(responses.route.endpoint.baseURL).toBe("https://opencode-test.openai.azure.com/openai/v1")
|
||||
expect(responses.route.defaults.headers).toEqual({ "x-application": "opencode" })
|
||||
expect(responses.route.defaults.http?.body).toEqual({ service_tier: "priority" })
|
||||
expect(responses.route.defaults.limits).toEqual({ context: 200_000, output: 64_000 })
|
||||
expect(chat.route.id).toBe("azure-openai-chat")
|
||||
})
|
||||
|
||||
test("maps Google package settings onto the Gemini model", async () => {
|
||||
const Google = await import("@opencode-ai/ai/providers/google")
|
||||
const selected = Google.model("gemini-2.5-flash", {
|
||||
apiKey: "fixture",
|
||||
baseURL: "https://generativelanguage.test/v1beta",
|
||||
headers: { "x-application": "opencode" },
|
||||
body: { safetySettings: [] },
|
||||
limits: { context: 1_000_000, output: 65_536 },
|
||||
providerOptions: { gemini: { thinkingConfig: { thinkingBudget: 1_024 } } },
|
||||
})
|
||||
|
||||
expect(selected.route.id).toBe("gemini")
|
||||
expect(selected.route.endpoint.baseURL).toBe("https://generativelanguage.test/v1beta")
|
||||
expect(selected.route.defaults.headers).toEqual({ "x-application": "opencode" })
|
||||
expect(selected.route.defaults.http?.body).toEqual({ safetySettings: [] })
|
||||
expect(selected.route.defaults.limits).toEqual({ context: 1_000_000, output: 65_536 })
|
||||
expect(selected.route.defaults.providerOptions).toEqual({
|
||||
gemini: { thinkingConfig: { thinkingBudget: 1_024 } },
|
||||
})
|
||||
})
|
||||
|
||||
test("selects Vertex entrypoints with the same model contract", async () => {
|
||||
const GoogleVertex = await import("@opencode-ai/ai/providers/google-vertex")
|
||||
const GoogleVertexGemini = await import("@opencode-ai/ai/providers/google-vertex/gemini")
|
||||
const GoogleVertexChat = await import("@opencode-ai/ai/providers/google-vertex/chat")
|
||||
const GoogleVertexResponses = await import("@opencode-ai/ai/providers/google-vertex/responses")
|
||||
const GoogleVertexMessages = await import("@opencode-ai/ai/providers/google-vertex/messages")
|
||||
const gemini = GoogleVertex.model("gemini-3.5-flash", {
|
||||
apiKey: "fixture",
|
||||
headers: { "x-application": "opencode" },
|
||||
body: { safetySettings: [] },
|
||||
limits: { context: 1_000_000, output: 65_536 },
|
||||
})
|
||||
const messages = GoogleVertexMessages.model("claude-sonnet-4-6", {
|
||||
accessToken: "fixture",
|
||||
location: "global",
|
||||
project: "vertex-project",
|
||||
})
|
||||
const chat = GoogleVertexChat.model("deepseek-ai/deepseek-v3.2-maas", {
|
||||
accessToken: "fixture",
|
||||
location: "global",
|
||||
project: "vertex-project",
|
||||
})
|
||||
const responses = GoogleVertexResponses.model("xai/grok-4.20-reasoning", {
|
||||
accessToken: "fixture",
|
||||
location: "global",
|
||||
project: "vertex-project",
|
||||
})
|
||||
|
||||
expect(GoogleVertexGemini.model).toBe(GoogleVertex.model)
|
||||
expect(gemini.route.id).toBe("google-vertex-gemini")
|
||||
expect(gemini.route.protocol).toBe("gemini")
|
||||
expect(gemini.route.endpoint.baseURL).toBe("https://aiplatform.googleapis.com/v1/publishers/google")
|
||||
expect(gemini.route.defaults.headers).toEqual({ "x-application": "opencode" })
|
||||
expect(gemini.route.defaults.http?.body).toEqual({ safetySettings: [] })
|
||||
expect(gemini.route.defaults.limits).toEqual({ context: 1_000_000, output: 65_536 })
|
||||
expect(
|
||||
GoogleVertex.model("gemini-3.5-flash", {
|
||||
accessToken: "fixture",
|
||||
location: "eu",
|
||||
project: "vertex-project",
|
||||
}).route.endpoint.baseURL,
|
||||
).toBe("https://aiplatform.eu.rep.googleapis.com/v1beta1/projects/vertex-project/locations/eu/publishers/google")
|
||||
expect(messages.route.id).toBe("google-vertex-messages")
|
||||
expect(messages.route.protocol).toBe("anthropic-messages")
|
||||
expect(messages.route.endpoint.baseURL).toBe(
|
||||
"https://aiplatform.googleapis.com/v1/projects/vertex-project/locations/global/publishers/anthropic/models",
|
||||
)
|
||||
expect(chat.route.id).toBe("google-vertex-chat")
|
||||
expect(chat.route.protocol).toBe("openai-chat")
|
||||
expect(chat.route.endpoint).toMatchObject({
|
||||
baseURL: "https://aiplatform.googleapis.com/v1/projects/vertex-project/locations/global/endpoints/openapi",
|
||||
path: "/chat/completions",
|
||||
})
|
||||
expect(responses.route.id).toBe("google-vertex-responses")
|
||||
expect(responses.route.protocol).toBe("openai-responses")
|
||||
expect(responses.route.endpoint).toMatchObject({
|
||||
baseURL: "https://aiplatform.googleapis.com/v1/projects/vertex-project/locations/global/endpoints/openapi",
|
||||
path: "/responses",
|
||||
})
|
||||
expect(responses.route.defaults.providerOptions).toEqual({ openai: { store: false } })
|
||||
})
|
||||
|
||||
test("rejects conflicting Vertex auth settings at runtime", async () => {
|
||||
const GoogleVertex = await import("@opencode-ai/ai/providers/google-vertex")
|
||||
const GoogleVertexChat = await import("@opencode-ai/ai/providers/google-vertex/chat")
|
||||
const GoogleVertexMessages = await import("@opencode-ai/ai/providers/google-vertex/messages")
|
||||
const GoogleVertexResponses = await import("@opencode-ai/ai/providers/google-vertex/responses")
|
||||
const Providers = await import("@opencode-ai/ai/providers")
|
||||
expect(() =>
|
||||
Reflect.apply(GoogleVertex.model, undefined, [
|
||||
"gemini-3.5-flash",
|
||||
{ accessToken: "token", apiKey: "fixture", project: "vertex-project" },
|
||||
]),
|
||||
).toThrow("Google Vertex apiKey cannot be combined with accessToken or auth")
|
||||
const configured = Reflect.apply(GoogleVertex.configure, undefined, [
|
||||
{ accessToken: "token", auth: {}, project: "vertex-project" },
|
||||
])
|
||||
expect(() => configured.model("gemini-3.5-flash")).toThrow("Google Vertex accessToken cannot be combined with auth")
|
||||
expect(() =>
|
||||
Reflect.apply(GoogleVertexMessages.model, undefined, [
|
||||
"claude-sonnet-4-6",
|
||||
{ apiKey: "fixture", project: "vertex-project" },
|
||||
]),
|
||||
).toThrow("Google Vertex Messages does not support API keys")
|
||||
expect(() =>
|
||||
Reflect.apply(Providers.GoogleVertexMessages.configure, undefined, [
|
||||
{ apiKey: "fixture", project: "vertex-project" },
|
||||
]),
|
||||
).toThrow("Google Vertex Messages does not support API keys")
|
||||
expect(() =>
|
||||
Reflect.apply(GoogleVertexChat.model, undefined, [
|
||||
"deepseek-ai/deepseek-v3.2-maas",
|
||||
{ apiKey: "fixture", project: "vertex-project" },
|
||||
]),
|
||||
).toThrow("Google Vertex Chat does not support API keys")
|
||||
expect(() =>
|
||||
Reflect.apply(Providers.GoogleVertexChat.configure, undefined, [
|
||||
{ apiKey: "fixture", project: "vertex-project" },
|
||||
]),
|
||||
).toThrow("Google Vertex Chat does not support API keys")
|
||||
expect(() =>
|
||||
Reflect.apply(GoogleVertexResponses.model, undefined, [
|
||||
"xai/grok-4.20-reasoning",
|
||||
{ apiKey: "fixture", project: "vertex-project" },
|
||||
]),
|
||||
).toThrow("Google Vertex Responses does not support API keys")
|
||||
expect(() =>
|
||||
Reflect.apply(Providers.GoogleVertexResponses.configure, undefined, [
|
||||
{ apiKey: "fixture", project: "vertex-project" },
|
||||
]),
|
||||
).toThrow("Google Vertex Responses does not support API keys")
|
||||
})
|
||||
})
|
||||
@@ -1,56 +0,0 @@
|
||||
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 })
|
||||
}),
|
||||
)
|
||||
})
|
||||
@@ -1,246 +0,0 @@
|
||||
import { describe, expect } from "bun:test"
|
||||
import { Effect } from "effect"
|
||||
import { HttpClientRequest } from "effect/unstable/http"
|
||||
import { LLM } from "../../src"
|
||||
import { GoogleVertex, GoogleVertexChat, GoogleVertexMessages, GoogleVertexResponses } from "../../src/providers"
|
||||
import { LLMClient } from "../../src/route"
|
||||
import { it } from "../lib/effect"
|
||||
import { dynamicResponse } from "../lib/http"
|
||||
import { deltaChunk, finishChunk } from "../lib/openai-chunks"
|
||||
import { sseEvents } from "../lib/sse"
|
||||
|
||||
describe("Google Vertex providers", () => {
|
||||
it.effect("sends Gemini requests to the global Vertex endpoint", () =>
|
||||
Effect.gen(function* () {
|
||||
const response = yield* LLMClient.generate(
|
||||
LLM.request({
|
||||
model: GoogleVertex.configure({
|
||||
accessToken: "vertex-token",
|
||||
location: "global",
|
||||
project: "vertex-project",
|
||||
}).model("gemini-3.5-flash"),
|
||||
prompt: "Say hello.",
|
||||
}),
|
||||
).pipe(
|
||||
Effect.provide(
|
||||
dynamicResponse((input) =>
|
||||
Effect.gen(function* () {
|
||||
const request = yield* HttpClientRequest.toWeb(input.request).pipe(Effect.orDie)
|
||||
expect(request.url).toBe(
|
||||
"https://aiplatform.googleapis.com/v1beta1/projects/vertex-project/locations/global/publishers/google/models/gemini-3.5-flash:streamGenerateContent?alt=sse",
|
||||
)
|
||||
expect(request.headers.get("authorization")).toBe("Bearer vertex-token")
|
||||
expect(yield* Effect.promise(() => request.json())).toMatchObject({
|
||||
contents: [{ role: "user", parts: [{ text: "Say hello." }] }],
|
||||
})
|
||||
return input.respond(
|
||||
sseEvents({
|
||||
candidates: [
|
||||
{
|
||||
content: { role: "model", parts: [{ text: "Hello." }] },
|
||||
finishReason: "STOP",
|
||||
},
|
||||
],
|
||||
}),
|
||||
{ headers: { "content-type": "text/event-stream" } },
|
||||
)
|
||||
}),
|
||||
),
|
||||
),
|
||||
)
|
||||
|
||||
expect(response.text).toBe("Hello.")
|
||||
}),
|
||||
)
|
||||
|
||||
it.effect("projects Anthropic Messages onto the Vertex raw-predict API", () =>
|
||||
Effect.gen(function* () {
|
||||
const response = yield* LLMClient.generate(
|
||||
LLM.request({
|
||||
model: GoogleVertexMessages.configure({
|
||||
accessToken: "vertex-token",
|
||||
location: "eu",
|
||||
project: "vertex-project",
|
||||
}).model("claude-sonnet-4-6"),
|
||||
prompt: "Say hello.",
|
||||
}),
|
||||
).pipe(
|
||||
Effect.provide(
|
||||
dynamicResponse((input) =>
|
||||
Effect.gen(function* () {
|
||||
const request = yield* HttpClientRequest.toWeb(input.request).pipe(Effect.orDie)
|
||||
expect(request.url).toBe(
|
||||
"https://aiplatform.eu.rep.googleapis.com/v1/projects/vertex-project/locations/eu/publishers/anthropic/models/claude-sonnet-4-6:streamRawPredict",
|
||||
)
|
||||
expect(request.headers.get("authorization")).toBe("Bearer vertex-token")
|
||||
expect(request.headers.get("anthropic-version")).toBeNull()
|
||||
const body = yield* Effect.promise(() => request.json())
|
||||
expect(body).toMatchObject({
|
||||
anthropic_version: "vertex-2023-10-16",
|
||||
messages: [{ role: "user", content: [{ type: "text", text: "Say hello." }] }],
|
||||
stream: true,
|
||||
})
|
||||
expect(body).not.toHaveProperty("model")
|
||||
return input.respond(
|
||||
sseEvents(
|
||||
{ type: "content_block_start", index: 0, content_block: { type: "text", text: "" } },
|
||||
{ type: "content_block_delta", index: 0, delta: { type: "text_delta", text: "Hello." } },
|
||||
{ type: "content_block_stop", index: 0 },
|
||||
{ type: "message_delta", delta: { stop_reason: "end_turn" }, usage: { output_tokens: 2 } },
|
||||
{ type: "message_stop" },
|
||||
),
|
||||
{ headers: { "content-type": "text/event-stream" } },
|
||||
)
|
||||
}),
|
||||
),
|
||||
),
|
||||
)
|
||||
|
||||
expect(response.text).toBe("Hello.")
|
||||
}),
|
||||
)
|
||||
|
||||
it.effect("sends MaaS requests through Vertex Chat Completions", () =>
|
||||
Effect.gen(function* () {
|
||||
const response = yield* LLMClient.generate(
|
||||
LLM.request({
|
||||
model: GoogleVertexChat.configure({
|
||||
accessToken: "vertex-token",
|
||||
location: "global",
|
||||
project: "vertex-project",
|
||||
}).model("deepseek-ai/deepseek-v3.2-maas"),
|
||||
prompt: "Say hello.",
|
||||
}),
|
||||
).pipe(
|
||||
Effect.provide(
|
||||
dynamicResponse((input) =>
|
||||
Effect.gen(function* () {
|
||||
const request = yield* HttpClientRequest.toWeb(input.request).pipe(Effect.orDie)
|
||||
expect(request.url).toBe(
|
||||
"https://aiplatform.googleapis.com/v1/projects/vertex-project/locations/global/endpoints/openapi/chat/completions",
|
||||
)
|
||||
expect(request.headers.get("authorization")).toBe("Bearer vertex-token")
|
||||
expect(yield* Effect.promise(() => request.json())).toMatchObject({
|
||||
model: "deepseek-ai/deepseek-v3.2-maas",
|
||||
messages: [{ role: "user", content: "Say hello." }],
|
||||
stream: true,
|
||||
stream_options: { include_usage: true },
|
||||
})
|
||||
return input.respond(sseEvents(deltaChunk({ content: "Hello." }), finishChunk("stop")), {
|
||||
headers: { "content-type": "text/event-stream" },
|
||||
})
|
||||
}),
|
||||
),
|
||||
),
|
||||
)
|
||||
|
||||
expect(response.text).toBe("Hello.")
|
||||
}),
|
||||
)
|
||||
|
||||
it.effect("sends Grok requests through Vertex Responses", () =>
|
||||
Effect.gen(function* () {
|
||||
const response = yield* LLMClient.generate(
|
||||
LLM.request({
|
||||
model: GoogleVertexResponses.configure({
|
||||
accessToken: "vertex-token",
|
||||
location: "global",
|
||||
project: "vertex-project",
|
||||
}).model("xai/grok-4.20-reasoning"),
|
||||
prompt: "Say hello.",
|
||||
}),
|
||||
).pipe(
|
||||
Effect.provide(
|
||||
dynamicResponse((input) =>
|
||||
Effect.gen(function* () {
|
||||
const request = yield* HttpClientRequest.toWeb(input.request).pipe(Effect.orDie)
|
||||
expect(request.url).toBe(
|
||||
"https://aiplatform.googleapis.com/v1/projects/vertex-project/locations/global/endpoints/openapi/responses",
|
||||
)
|
||||
expect(request.headers.get("authorization")).toBe("Bearer vertex-token")
|
||||
expect(yield* Effect.promise(() => request.json())).toMatchObject({
|
||||
model: "xai/grok-4.20-reasoning",
|
||||
input: [{ role: "user", content: [{ type: "input_text", text: "Say hello." }] }],
|
||||
store: false,
|
||||
stream: true,
|
||||
})
|
||||
return input.respond(
|
||||
sseEvents(
|
||||
{ type: "response.output_text.delta", item_id: "msg_1", delta: "Hello." },
|
||||
{ type: "response.completed", response: { id: "resp_1" } },
|
||||
),
|
||||
{ headers: { "content-type": "text/event-stream" } },
|
||||
)
|
||||
}),
|
||||
),
|
||||
),
|
||||
)
|
||||
|
||||
expect(response.text).toBe("Hello.")
|
||||
}),
|
||||
)
|
||||
|
||||
it.effect("protects the Vertex Messages API version from body overlays", () =>
|
||||
Effect.gen(function* () {
|
||||
const error = yield* LLMClient.prepare(
|
||||
LLM.request({
|
||||
model: GoogleVertexMessages.configure({
|
||||
accessToken: "vertex-token",
|
||||
http: { body: { anthropic_version: "wrong" } },
|
||||
project: "vertex-project",
|
||||
}).model("claude-sonnet-4-6"),
|
||||
prompt: "Say hello.",
|
||||
}),
|
||||
).pipe(Effect.flip)
|
||||
|
||||
expect(error.message).toContain("http.body cannot overlay protocol-owned field(s): anthropic_version")
|
||||
}),
|
||||
)
|
||||
|
||||
it.effect("routes tuned Gemini models through their deployed endpoint", () =>
|
||||
Effect.gen(function* () {
|
||||
const response = yield* LLMClient.generate(
|
||||
LLM.request({
|
||||
model: GoogleVertex.configure({
|
||||
accessToken: "vertex-token",
|
||||
location: "us-central1",
|
||||
project: "vertex-project",
|
||||
}).model("endpoints/1234567890"),
|
||||
prompt: "Say hello.",
|
||||
}),
|
||||
).pipe(
|
||||
Effect.provide(
|
||||
dynamicResponse((input) =>
|
||||
Effect.gen(function* () {
|
||||
const request = yield* HttpClientRequest.toWeb(input.request).pipe(Effect.orDie)
|
||||
expect(request.url).toBe(
|
||||
"https://us-central1-aiplatform.googleapis.com/v1beta1/projects/vertex-project/locations/us-central1/endpoints/1234567890:streamGenerateContent?alt=sse",
|
||||
)
|
||||
return input.respond(
|
||||
sseEvents({
|
||||
candidates: [
|
||||
{
|
||||
content: { role: "model", parts: [{ text: "Hello." }] },
|
||||
finishReason: "STOP",
|
||||
},
|
||||
],
|
||||
}),
|
||||
{ headers: { "content-type": "text/event-stream" } },
|
||||
)
|
||||
}),
|
||||
),
|
||||
),
|
||||
)
|
||||
|
||||
expect(response.text).toBe("Hello.")
|
||||
}),
|
||||
)
|
||||
|
||||
it.effect("rejects tuned Gemini models in express mode", () =>
|
||||
Effect.sync(() => {
|
||||
expect(() => GoogleVertex.configure({ apiKey: "fixture" }).model("endpoints/1234567890")).toThrow(
|
||||
"Google Vertex tuned models do not support Express Mode API keys",
|
||||
)
|
||||
}),
|
||||
)
|
||||
})
|
||||
@@ -1,148 +0,0 @@
|
||||
import { describe, expect } from "bun:test"
|
||||
import { Effect } from "effect"
|
||||
import { LLM, LLMEvent, LLMResponse, Model } 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 = [
|
||||
{
|
||||
name: "OpenRouter",
|
||||
model: Model.update(
|
||||
OpenRouter.configure({
|
||||
apiKey: process.env.OPENROUTER_API_KEY ?? "fixture",
|
||||
providerOptions: { openrouter: { reasoning: { max_tokens: 1024 } } },
|
||||
}).model("anthropic/claude-sonnet-4.6"),
|
||||
{ compatibility: { reasoningField: "reasoning" } },
|
||||
),
|
||||
requires: ["OPENROUTER_API_KEY"],
|
||||
cassette: "openrouter-reasoning",
|
||||
structured: true,
|
||||
},
|
||||
{
|
||||
name: "Vercel AI Gateway",
|
||||
model: Model.update(
|
||||
OpenAICompatible.configure({
|
||||
provider: "vercel-ai-gateway",
|
||||
baseURL: "https://ai-gateway.vercel.sh/v1",
|
||||
apiKey: process.env.AI_GATEWAY_API_KEY ?? "fixture",
|
||||
http: { body: { reasoning: { enabled: true, max_tokens: 1024 } } },
|
||||
}).model("anthropic/claude-sonnet-4.6"),
|
||||
{ compatibility: { reasoningField: "reasoning" } },
|
||||
),
|
||||
requires: ["AI_GATEWAY_API_KEY"],
|
||||
cassette: "vercel-ai-gateway-reasoning",
|
||||
structured: true,
|
||||
},
|
||||
] as const
|
||||
|
||||
for (const item of cases) {
|
||||
const recorded = recordedTests({
|
||||
prefix: "openai-compatible-chat",
|
||||
provider: item.model.provider,
|
||||
protocol: "openai-chat",
|
||||
requires: item.requires,
|
||||
tags: ["reasoning"],
|
||||
metadata: { model: item.model.id },
|
||||
})
|
||||
|
||||
describe(`${item.name} reasoning recorded`, () => {
|
||||
recorded.effect.with(
|
||||
"streams scalar reasoning",
|
||||
{ cassette: item.cassette },
|
||||
() =>
|
||||
Effect.gen(function* () {
|
||||
const response = yield* LLMClient.generate(
|
||||
LLM.request({
|
||||
model: item.model,
|
||||
system: "Think through the arithmetic, then reply with only the final integer.",
|
||||
prompt: "What is 173 multiplied by 219?",
|
||||
generation: { maxTokens: 1536, temperature: 0 },
|
||||
}),
|
||||
)
|
||||
|
||||
expect(response.text.replaceAll(",", "").trim()).toBe("37887")
|
||||
expect(response.reasoning.length).toBeGreaterThan(0)
|
||||
expect(response.events.some(LLMEvent.is.reasoningDelta)).toBe(true)
|
||||
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,
|
||||
)
|
||||
})
|
||||
}
|
||||
@@ -1,62 +0,0 @@
|
||||
import { describe, expect } from "bun:test"
|
||||
import { Effect } from "effect"
|
||||
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("gpt-image-1-mini")
|
||||
|
||||
const recorded = recordedTests({
|
||||
prefix: "openai-images",
|
||||
provider: "openai",
|
||||
protocol: "openai-images",
|
||||
requires: ["OPENAI_API_KEY"],
|
||||
})
|
||||
|
||||
describe("OpenAI Images recorded", () => {
|
||||
recorded.effect("generates an image", () =>
|
||||
Effect.gen(function* () {
|
||||
const response = yield* Image.generate({
|
||||
model,
|
||||
prompt: "A simple flat black circle centered on a plain white background.",
|
||||
options: { quality: "low", outputFormat: "jpeg", outputCompression: 10, size: "1024x1024" },
|
||||
})
|
||||
|
||||
expect(response.images).toHaveLength(1)
|
||||
expect(response.image?.mediaType).toBe("image/jpeg")
|
||||
expect(response.image?.data).toBeInstanceOf(Uint8Array)
|
||||
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 })
|
||||
}),
|
||||
)
|
||||
})
|
||||
@@ -1,66 +0,0 @@
|
||||
import { describe, expect } from "bun:test"
|
||||
import { Effect } from "effect"
|
||||
import { LLM, LLMEvent, Message } from "../../src"
|
||||
import { OpenAI } from "../../src/providers"
|
||||
import { recordedTests } from "../recorded-test"
|
||||
|
||||
const openai = OpenAI.configure({
|
||||
apiKey: process.env.OPENAI_API_KEY ?? "fixture",
|
||||
})
|
||||
|
||||
const recorded = recordedTests({
|
||||
prefix: "openai-responses-images",
|
||||
provider: "openai",
|
||||
protocol: "openai-responses",
|
||||
requires: ["OPENAI_API_KEY"],
|
||||
})
|
||||
|
||||
describe("OpenAI Responses image generation recorded", () => {
|
||||
recorded.effect("generates and edits an image with the hosted tool", () =>
|
||||
Effect.gen(function* () {
|
||||
const initial = Message.user("Generate a simple flat black triangle centered on a plain white background.")
|
||||
const tools = [
|
||||
OpenAI.imageGeneration({
|
||||
action: "auto",
|
||||
quality: "low",
|
||||
size: "1024x1024",
|
||||
outputFormat: "jpeg",
|
||||
outputCompression: 10,
|
||||
partialImages: 0,
|
||||
}),
|
||||
]
|
||||
const response = yield* LLM.generate(
|
||||
LLM.request({
|
||||
model: openai.responses("gpt-5-mini"),
|
||||
messages: [initial],
|
||||
tools,
|
||||
toolChoice: "image_generation",
|
||||
}),
|
||||
)
|
||||
|
||||
const result = response.events.find(LLMEvent.is.toolResult)
|
||||
expect(result).toBeDefined()
|
||||
expect(result?.providerExecuted).toBe(true)
|
||||
expect(result?.result.type).toBe("content")
|
||||
if (result?.result.type !== "content") return
|
||||
expect(result.result.value).toHaveLength(1)
|
||||
expect(result.result.value[0]?.type).toBe("file")
|
||||
if (result.result.value[0]?.type !== "file") return
|
||||
expect(result.result.value[0].mime).toBe("image/jpeg")
|
||||
expect(result.result.value[0].uri.startsWith("data:image/jpeg;base64,")).toBe(true)
|
||||
|
||||
const edited = yield* LLM.generate(
|
||||
LLM.request({
|
||||
model: openai.responses("gpt-5-mini"),
|
||||
messages: [initial, response.message, Message.user("Now make the triangle blue.")],
|
||||
tools,
|
||||
toolChoice: "image_generation",
|
||||
}),
|
||||
)
|
||||
const editedResult = edited.events.find(LLMEvent.is.toolResult)
|
||||
expect(editedResult?.result.type).toBe("content")
|
||||
if (editedResult?.result.type !== "content") return
|
||||
expect(editedResult.result.value[0]?.type).toBe("file")
|
||||
}),
|
||||
)
|
||||
})
|
||||
@@ -1,154 +0,0 @@
|
||||
import { describe, expect } from "bun:test"
|
||||
import { Effect } from "effect"
|
||||
import { LLM, Message } from "../../src"
|
||||
import { LLMClient } from "../../src/route"
|
||||
import * as OpenRouter from "../../src/providers/openrouter"
|
||||
import { it } from "../lib/effect"
|
||||
|
||||
describe("OpenRouter", () => {
|
||||
it.effect("prepares OpenRouter models through the OpenAI-compatible Chat route", () =>
|
||||
Effect.gen(function* () {
|
||||
const model = OpenRouter.configure({ apiKey: "test-key" }).model("openai/gpt-4o-mini")
|
||||
|
||||
expect(model).toMatchObject({
|
||||
id: "openai/gpt-4o-mini",
|
||||
provider: "openrouter",
|
||||
route: { id: "openrouter" },
|
||||
})
|
||||
expect(model.route.endpoint.baseURL).toBe("https://openrouter.ai/api/v1")
|
||||
|
||||
const prepared = yield* LLMClient.prepare(LLM.request({ model, prompt: "Say hello." }))
|
||||
|
||||
expect(prepared.route).toBe("openrouter")
|
||||
expect(prepared.body).toMatchObject({
|
||||
model: "openai/gpt-4o-mini",
|
||||
messages: [{ role: "user", content: "Say hello." }],
|
||||
stream: true,
|
||||
})
|
||||
}),
|
||||
)
|
||||
|
||||
it.effect("applies OpenRouter payload options from the model helper", () =>
|
||||
Effect.gen(function* () {
|
||||
const prepared = yield* LLMClient.prepare(
|
||||
LLM.request({
|
||||
model: OpenRouter.configure({
|
||||
apiKey: "test-key",
|
||||
providerOptions: {
|
||||
openrouter: {
|
||||
usage: true,
|
||||
reasoning: { effort: "high" },
|
||||
promptCacheKey: "session_123",
|
||||
},
|
||||
},
|
||||
}).model("anthropic/claude-3.7-sonnet:thinking"),
|
||||
prompt: "Think briefly.",
|
||||
}),
|
||||
)
|
||||
|
||||
expect(prepared.body).toMatchObject({
|
||||
usage: { include: true },
|
||||
reasoning: { effort: "high" },
|
||||
prompt_cache_key: "session_123",
|
||||
})
|
||||
}),
|
||||
)
|
||||
|
||||
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 }])
|
||||
}),
|
||||
)
|
||||
})
|
||||
@@ -1,207 +0,0 @@
|
||||
import { describe, expect } from "bun:test"
|
||||
import { Effect, Schema, Stream } from "effect"
|
||||
import { LLM, LLMResponse, Message, ToolDefinition, type Model } from "../../src"
|
||||
import { AmazonBedrock, Anthropic, Google, OpenAI, XAI } from "../../src/providers"
|
||||
import { LLMClient } from "../../src/route"
|
||||
import { Tool } from "../../src/tool"
|
||||
import { runTools } from "../lib/tool-runtime"
|
||||
import { recordedTests } from "../recorded-test"
|
||||
|
||||
const CODE = "ORCHID-7391"
|
||||
const PDF =
|
||||
"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"
|
||||
|
||||
const openai = OpenAI.configure({ apiKey: process.env.OPENAI_API_KEY ?? "fixture" })
|
||||
const anthropic = Anthropic.configure({ apiKey: process.env.ANTHROPIC_API_KEY ?? "fixture" })
|
||||
const google = Google.configure({ apiKey: process.env.GOOGLE_API_KEY ?? "fixture" })
|
||||
const xai = XAI.configure({ apiKey: process.env.XAI_API_KEY ?? "fixture" })
|
||||
const bedrock = AmazonBedrock.configure({
|
||||
apiKey: process.env.AWS_BEDROCK_API_KEY ?? "fixture",
|
||||
region: process.env.AWS_REGION ?? "us-east-1",
|
||||
})
|
||||
|
||||
const targets: ReadonlyArray<{
|
||||
readonly id: string
|
||||
readonly name: string
|
||||
readonly provider: string
|
||||
readonly protocol: string
|
||||
readonly requires: string
|
||||
readonly filename: string
|
||||
readonly maxTokens: number
|
||||
readonly model: Model
|
||||
}> = [
|
||||
{
|
||||
id: "openai",
|
||||
name: "OpenAI Responses gpt-4o-mini",
|
||||
provider: "openai",
|
||||
protocol: "openai-responses",
|
||||
requires: "OPENAI_API_KEY",
|
||||
filename: "verification.pdf",
|
||||
maxTokens: 40,
|
||||
model: openai.responses("gpt-4o-mini"),
|
||||
},
|
||||
{
|
||||
id: "anthropic",
|
||||
name: "Anthropic Haiku 4.5",
|
||||
provider: "anthropic",
|
||||
protocol: "anthropic-messages",
|
||||
requires: "ANTHROPIC_API_KEY",
|
||||
filename: "verification.pdf",
|
||||
maxTokens: 40,
|
||||
model: anthropic.model("claude-haiku-4-5-20251001"),
|
||||
},
|
||||
{
|
||||
id: "gemini",
|
||||
name: "Gemini 3.5 Flash",
|
||||
provider: "google",
|
||||
protocol: "gemini",
|
||||
requires: "GOOGLE_API_KEY",
|
||||
filename: "verification.pdf",
|
||||
maxTokens: 256,
|
||||
model: google.model("gemini-3.5-flash"),
|
||||
},
|
||||
{
|
||||
id: "xai",
|
||||
name: "xAI Grok 4.5",
|
||||
provider: "xai",
|
||||
protocol: "openai-responses",
|
||||
requires: "XAI_API_KEY",
|
||||
filename: "verification.pdf",
|
||||
maxTokens: 40,
|
||||
model: xai.responses("grok-4.5"),
|
||||
},
|
||||
{
|
||||
id: "bedrock",
|
||||
name: "Bedrock Claude Haiku 4.5",
|
||||
provider: "amazon-bedrock",
|
||||
protocol: "bedrock-converse",
|
||||
requires: "AWS_BEDROCK_API_KEY",
|
||||
filename: "verification",
|
||||
maxTokens: 40,
|
||||
model: bedrock.model("us.anthropic.claude-haiku-4-5-20251001-v1:0"),
|
||||
},
|
||||
]
|
||||
|
||||
const recorded = recordedTests({ prefix: "pdf", tags: ["pdf"] })
|
||||
const prompt = "Return only the verification code from the PDF."
|
||||
const readPdf = ToolDefinition.make({
|
||||
name: "read_pdf",
|
||||
description: "Read the attached PDF.",
|
||||
inputSchema: { type: "object", properties: {}, additionalProperties: false },
|
||||
})
|
||||
const readPdfRuntime = Tool.make({
|
||||
description: readPdf.description,
|
||||
parameters: Schema.Struct({ path: Schema.String }),
|
||||
success: Schema.String,
|
||||
execute: () => Effect.succeed("PDF read successfully"),
|
||||
toModelOutput: () => [
|
||||
{ type: "text", text: "PDF read successfully" },
|
||||
{
|
||||
type: "file",
|
||||
uri: `data:application/pdf;base64,${PDF}`,
|
||||
mime: "application/pdf",
|
||||
name: "verification.pdf",
|
||||
},
|
||||
],
|
||||
})
|
||||
|
||||
const expectCode = (response: LLMResponse) => {
|
||||
expect(response.finishReason).toBe("stop")
|
||||
expect(response.text.toUpperCase()).toContain(CODE)
|
||||
}
|
||||
|
||||
describe("PDF recorded", () => {
|
||||
for (const target of targets) {
|
||||
recorded.effect.with(
|
||||
`reads a user PDF with ${target.name}`,
|
||||
{
|
||||
id: `${target.id}-user-input`,
|
||||
provider: target.provider,
|
||||
protocol: target.protocol,
|
||||
requires: [target.requires],
|
||||
tags: ["user-input"],
|
||||
},
|
||||
Effect.gen(function* () {
|
||||
expectCode(
|
||||
yield* LLMClient.generate(
|
||||
LLM.request({
|
||||
id: `recorded_pdf_${target.id}_user_input`,
|
||||
model: target.model,
|
||||
cache: "none",
|
||||
generation: { maxTokens: target.maxTokens, temperature: 0 },
|
||||
messages: [
|
||||
Message.user([
|
||||
{ type: "media", mediaType: "application/pdf", data: PDF, filename: target.filename },
|
||||
{ type: "text", text: prompt },
|
||||
]),
|
||||
],
|
||||
}),
|
||||
),
|
||||
)
|
||||
}),
|
||||
)
|
||||
|
||||
recorded.effect.with(
|
||||
`reads a PDF tool result with ${target.name}`,
|
||||
{
|
||||
id: `${target.id}-tool-result`,
|
||||
provider: target.provider,
|
||||
protocol: target.protocol,
|
||||
requires: [target.requires],
|
||||
tags: ["tool", "tool-result"],
|
||||
},
|
||||
Effect.gen(function* () {
|
||||
if (target.id === "gemini") {
|
||||
const events = Array.from(
|
||||
yield* runTools({
|
||||
request: LLM.request({
|
||||
id: "recorded_pdf_gemini_tool_result",
|
||||
model: target.model,
|
||||
system:
|
||||
"Call read_pdf exactly once with path verification.pdf, then reply only with the verification code from its PDF.",
|
||||
prompt: "Use read_pdf with path verification.pdf and return the verification code.",
|
||||
cache: "none",
|
||||
generation: { maxTokens: target.maxTokens, temperature: 0 },
|
||||
}),
|
||||
tools: { read_pdf: readPdfRuntime },
|
||||
}).pipe(Stream.runCollect),
|
||||
)
|
||||
expect(events.at(-1)).toMatchObject({ type: "finish", reason: "stop" })
|
||||
expect(LLMResponse.text({ events }).toUpperCase()).toContain(CODE)
|
||||
return
|
||||
}
|
||||
|
||||
expectCode(
|
||||
yield* LLMClient.generate(
|
||||
LLM.request({
|
||||
id: `recorded_pdf_${target.id}_tool_result`,
|
||||
model: target.model,
|
||||
system: "Read the PDF returned by the tool and follow the user's response format exactly.",
|
||||
cache: "none",
|
||||
generation: { maxTokens: target.maxTokens, temperature: 0 },
|
||||
messages: [
|
||||
Message.user(prompt),
|
||||
Message.assistant([{ type: "tool-call", id: "call_pdf_1", name: readPdf.name, input: {} }]),
|
||||
Message.tool({
|
||||
id: "call_pdf_1",
|
||||
name: readPdf.name,
|
||||
resultType: "content",
|
||||
result: [
|
||||
{ type: "text", text: "PDF read successfully" },
|
||||
{
|
||||
type: "file",
|
||||
uri: `data:application/pdf;base64,${PDF}`,
|
||||
mime: "application/pdf",
|
||||
name: target.filename,
|
||||
},
|
||||
],
|
||||
}),
|
||||
],
|
||||
tools: [readPdf],
|
||||
}),
|
||||
),
|
||||
)
|
||||
}),
|
||||
)
|
||||
}
|
||||
})
|
||||
@@ -1,55 +0,0 @@
|
||||
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 })
|
||||
}),
|
||||
)
|
||||
})
|
||||
@@ -1,109 +0,0 @@
|
||||
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" },
|
||||
})
|
||||
}),
|
||||
),
|
||||
),
|
||||
),
|
||||
),
|
||||
),
|
||||
)
|
||||
})
|
||||
@@ -1,32 +0,0 @@
|
||||
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()
|
||||
}),
|
||||
)
|
||||
})
|
||||
@@ -1,130 +0,0 @@
|
||||
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"))),
|
||||
),
|
||||
)
|
||||
}),
|
||||
)
|
||||
})
|
||||
@@ -1,8 +0,0 @@
|
||||
{
|
||||
"$schema": "https://json.schemastore.org/tsconfig",
|
||||
"extends": "./tsconfig.json",
|
||||
"compilerOptions": {
|
||||
"allowImportingTsExtensions": false,
|
||||
"noEmit": false
|
||||
}
|
||||
}
|
||||
@@ -1,12 +0,0 @@
|
||||
{
|
||||
"$schema": "https://json.schemastore.org/tsconfig.json",
|
||||
"extends": "@tsconfig/bun/tsconfig.json",
|
||||
"compilerOptions": {
|
||||
"rootDir": "src",
|
||||
"outDir": "dist",
|
||||
"declaration": true,
|
||||
"lib": ["ESNext", "DOM", "DOM.Iterable"],
|
||||
"noUncheckedIndexedAccess": false
|
||||
},
|
||||
"include": ["src"]
|
||||
}
|
||||
@@ -1,9 +0,0 @@
|
||||
{
|
||||
"$schema": "https://json.schemastore.org/tsconfig",
|
||||
"extends": "./tsconfig.json",
|
||||
"compilerOptions": {
|
||||
"noEmit": true,
|
||||
"rootDir": "."
|
||||
},
|
||||
"include": ["test/**/*.types.ts"]
|
||||
}
|
||||
@@ -136,9 +136,6 @@ export async function setupTimeline(
|
||||
},
|
||||
}),
|
||||
)
|
||||
if (settings.newLayoutDesigns === false) {
|
||||
localStorage.setItem("app-version.v1", JSON.stringify({ version: "1.17.20" }))
|
||||
}
|
||||
}, input.settings ?? {})
|
||||
if (input.locale) {
|
||||
await page.addInitScript((locale) => {
|
||||
|
||||
@@ -24,7 +24,6 @@ test("redirects a draft to the legacy new-session route", async ({ page }) => {
|
||||
await page.addInitScript(
|
||||
({ directory, draftID, server }) => {
|
||||
localStorage.setItem("settings.v3", JSON.stringify({ general: { newLayoutDesigns: false } }))
|
||||
localStorage.setItem("app-version.v1", JSON.stringify({ version: "1.17.20" }))
|
||||
localStorage.setItem(
|
||||
"opencode.window.browser.dat:tabs",
|
||||
JSON.stringify([{ type: "draft", draftID, server, directory }]),
|
||||
|
||||
@@ -1,50 +0,0 @@
|
||||
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")
|
||||
})
|
||||
@@ -54,15 +54,18 @@ test("shows the V2 thinking level control while relevant", async ({ page }) => {
|
||||
})
|
||||
|
||||
await page.goto(`/${base64Encode(directory)}/session/${sessionID}`)
|
||||
const composer = page.locator('[data-component="prompt-input-v2"]')
|
||||
const composer = page.locator('[data-component="session-composer"]')
|
||||
const input = composer.locator('[data-component="prompt-input"]')
|
||||
const control = composer.getByRole("button", { name: "Choose model variant" })
|
||||
const control = composer.locator('[data-component="prompt-variant-control"]')
|
||||
await expectAppVisible(composer)
|
||||
|
||||
await idleComposer(page)
|
||||
await expect(control).toBeHidden()
|
||||
|
||||
await composer.hover()
|
||||
await expect(control).toBeVisible()
|
||||
|
||||
await control.click()
|
||||
await control.locator('[data-action="prompt-model-variant"]').click()
|
||||
const high = page.getByRole("menuitemradio", { name: "high" })
|
||||
await expect(high).toBeVisible()
|
||||
await page.mouse.move(0, 0)
|
||||
|
||||
@@ -1,270 +0,0 @@
|
||||
import { base64Encode } from "@opencode-ai/core/util/encode"
|
||||
import { expect, test, type Page, type Route } from "@playwright/test"
|
||||
import { installSseTransport } from "../utils/sse-transport"
|
||||
|
||||
const serverA = "http://127.0.0.1:4096"
|
||||
const serverB = "http://127.0.0.1:4097"
|
||||
const directoryA = "C:/server-a"
|
||||
const directoryB = "/home/server-b"
|
||||
const sessionA = session("ses_server_a", directoryA, "Server A session")
|
||||
const childSessionA = { ...session("ses_server_a_child", directoryA, "Server A child session"), parentID: sessionA.id }
|
||||
const sessionB = session("ses_server_b", directoryB, "Server B session")
|
||||
|
||||
test("session settings use the remote server context", async ({ page }) => {
|
||||
const permissionRequests: string[] = []
|
||||
await mockServers(page, permissionRequests)
|
||||
await configureServers(page)
|
||||
|
||||
await page.goto(`/server/${base64Encode(serverB)}/session/${sessionB.id}`)
|
||||
await expect(page.getByText(sessionB.title).first()).toBeVisible()
|
||||
await page.keyboard.press(process.platform === "darwin" ? "Meta+," : "Control+,")
|
||||
|
||||
const dialog = page.locator(".settings-v2-dialog")
|
||||
const autoAccept = dialog.locator('[data-action="settings-auto-accept-permissions"]')
|
||||
const input = autoAccept.getByRole("switch")
|
||||
await expect(autoAccept).toBeVisible()
|
||||
await expect(input).toBeEnabled()
|
||||
permissionRequests.length = 0
|
||||
await autoAccept.locator('[data-slot="switch-control"]').click()
|
||||
await expect(input).toBeChecked()
|
||||
await expect
|
||||
.poll(() =>
|
||||
permissionRequests.some((request) => {
|
||||
const url = new URL(request)
|
||||
return url.origin === serverB && url.searchParams.get("directory") === directoryB
|
||||
}),
|
||||
)
|
||||
.toBe(true)
|
||||
expect(permissionRequests.every((request) => new URL(request).origin === serverB)).toBe(true)
|
||||
|
||||
await dialog.getByRole("tab", { name: "Models" }).click()
|
||||
await expect(dialog.getByRole("switch", { name: "Server B Model" })).toBeEnabled()
|
||||
await expect(dialog.getByRole("switch", { name: "Server A Model" })).toHaveCount(0)
|
||||
})
|
||||
|
||||
test("auto-accept responds for an unfocused server session", async ({ page }) => {
|
||||
const permissionRequests: string[] = []
|
||||
const permissionResponses: PermissionResponse[] = []
|
||||
const transport = await installSseTransport<{ directory: string; payload: Record<string, unknown> }>(page, {
|
||||
server: serverA,
|
||||
retry: 20,
|
||||
})
|
||||
await mockServers(page, permissionRequests, permissionResponses)
|
||||
await configureServers(page, [
|
||||
{ type: "session", server: serverA, sessionId: sessionA.id },
|
||||
{ type: "session", server: serverB, sessionId: sessionB.id },
|
||||
])
|
||||
|
||||
const hrefB = `/server/${base64Encode(serverB)}/session/${sessionB.id}`
|
||||
await page.goto(`/server/${base64Encode(serverA)}/session/${sessionA.id}`)
|
||||
await expect(page.getByText(sessionA.title).first()).toBeVisible()
|
||||
await page.keyboard.press(process.platform === "darwin" ? "Meta+," : "Control+,")
|
||||
const autoAccept = page.locator(".settings-v2-dialog").locator('[data-action="settings-auto-accept-permissions"]')
|
||||
await autoAccept.locator('[data-slot="switch-control"]').click()
|
||||
await expect(autoAccept.getByRole("switch")).toBeChecked()
|
||||
await expect
|
||||
.poll(() =>
|
||||
permissionRequests.some((request) => {
|
||||
const url = new URL(request)
|
||||
return url.origin === serverA && url.searchParams.get("directory") === directoryA
|
||||
}),
|
||||
)
|
||||
.toBe(true)
|
||||
await page.keyboard.press("Escape")
|
||||
|
||||
await page.locator(`[data-titlebar-tab-slot]:has(a[href="${hrefB}"])`).click()
|
||||
await expect(page).toHaveURL(new RegExp(`${hrefB.replace(/[.*+?^${}()|[\]\\]/g, "\\$&")}$`))
|
||||
await expect(page.getByText(sessionB.title).first()).toBeVisible()
|
||||
await transport.waitForConnection()
|
||||
|
||||
await transport.send({
|
||||
directory: directoryA,
|
||||
payload: {
|
||||
id: "event-permission-background-a",
|
||||
type: "permission.asked",
|
||||
properties: {
|
||||
id: "permission-background-a",
|
||||
sessionID: sessionA.id,
|
||||
permission: "bash",
|
||||
patterns: ["git status"],
|
||||
metadata: {},
|
||||
always: [],
|
||||
},
|
||||
},
|
||||
})
|
||||
|
||||
await expect
|
||||
.poll(() => permissionResponses)
|
||||
.toEqual([
|
||||
{
|
||||
origin: serverA,
|
||||
directory: directoryA,
|
||||
sessionID: sessionA.id,
|
||||
permissionID: "permission-background-a",
|
||||
body: { response: "once" },
|
||||
},
|
||||
])
|
||||
|
||||
await transport.send({
|
||||
directory: directoryA,
|
||||
payload: {
|
||||
id: "event-permission-background-a-child",
|
||||
type: "permission.asked",
|
||||
properties: {
|
||||
id: "permission-background-a-child",
|
||||
sessionID: childSessionA.id,
|
||||
permission: "bash",
|
||||
patterns: ["git diff"],
|
||||
metadata: {},
|
||||
always: [],
|
||||
},
|
||||
},
|
||||
})
|
||||
|
||||
await expect
|
||||
.poll(() => permissionResponses)
|
||||
.toEqual([
|
||||
{
|
||||
origin: serverA,
|
||||
directory: directoryA,
|
||||
sessionID: sessionA.id,
|
||||
permissionID: "permission-background-a",
|
||||
body: { response: "once" },
|
||||
},
|
||||
{
|
||||
origin: serverA,
|
||||
directory: directoryA,
|
||||
sessionID: childSessionA.id,
|
||||
permissionID: "permission-background-a-child",
|
||||
body: { response: "once" },
|
||||
},
|
||||
])
|
||||
})
|
||||
|
||||
type PermissionResponse = {
|
||||
origin: string
|
||||
directory?: string
|
||||
sessionID: string
|
||||
permissionID: string
|
||||
body: unknown
|
||||
}
|
||||
|
||||
async function configureServers(page: Page, tabs: { type: "session"; server: string; sessionId: string }[] = []) {
|
||||
await page.addInitScript(
|
||||
({ serverB, tabs }) => {
|
||||
localStorage.setItem("settings.v3", JSON.stringify({ general: { newLayoutDesigns: true } }))
|
||||
localStorage.setItem("opencode.global.dat:server", JSON.stringify({ list: [serverB] }))
|
||||
localStorage.setItem("opencode.window.browser.dat:tabs", JSON.stringify(tabs))
|
||||
},
|
||||
{ serverB, tabs },
|
||||
)
|
||||
}
|
||||
|
||||
async function mockServers(page: Page, permissionRequests: string[], permissionResponses: PermissionResponse[] = []) {
|
||||
await page.route("**/*", async (route) => {
|
||||
const url = new URL(route.request().url())
|
||||
if (url.origin !== serverA && url.origin !== serverB) return route.fallback()
|
||||
const remote = url.origin === serverB
|
||||
const directory = remote ? directoryB : directoryA
|
||||
const sessions = remote ? [sessionB] : [sessionA, childSessionA]
|
||||
const requestDirectory = url.searchParams.get("directory")
|
||||
const response = url.pathname.match(/^\/session\/([^/]+)\/permissions\/([^/]+)$/)
|
||||
if (route.request().method() === "POST" && response) {
|
||||
permissionResponses.push({
|
||||
origin: url.origin,
|
||||
directory: requestDirectory ?? undefined,
|
||||
sessionID: response[1]!,
|
||||
permissionID: response[2]!,
|
||||
body: route.request().postDataJSON(),
|
||||
})
|
||||
return json(route, true)
|
||||
}
|
||||
if (requestDirectory && requestDirectory !== directory) return json(route, { name: "InvalidDirectory" }, 500)
|
||||
if (url.pathname === "/global/event" || url.pathname === "/event") return sse(route)
|
||||
if (url.pathname === "/global/health") return json(route, { healthy: true })
|
||||
if (url.pathname === "/session/status") return json(route, {})
|
||||
if (url.pathname === "/session") return json(route, sessions)
|
||||
const current = sessions.find((session) => url.pathname === `/session/${session.id}`)
|
||||
if (current) return json(route, current)
|
||||
if (/^\/session\/[^/]+$/.test(url.pathname)) return json(route, { name: "NotFoundError" }, 404)
|
||||
if (/^\/session\/[^/]+\/message$/.test(url.pathname)) return json(route, [])
|
||||
if (/^\/session\/[^/]+\/(children|todo|diff)$/.test(url.pathname)) return json(route, [])
|
||||
if (url.pathname === "/permission") {
|
||||
permissionRequests.push(url.toString())
|
||||
return json(route, [])
|
||||
}
|
||||
if (["/skill", "/command", "/lsp", "/formatter", "/question", "/vcs/diff", "/pty/shells"].includes(url.pathname))
|
||||
return json(route, [])
|
||||
if (["/global/config", "/config", "/provider/auth", "/mcp"].includes(url.pathname)) return json(route, {})
|
||||
if (url.pathname === "/provider") return json(route, provider(remote ? "server-b" : "server-a"))
|
||||
if (url.pathname === "/agent") return json(route, [{ name: "build", mode: "primary" }])
|
||||
if (url.pathname === "/project" || url.pathname === "/project/current") {
|
||||
const project = {
|
||||
id: remote ? sessionB.projectID : "project-server-a",
|
||||
worktree: directory,
|
||||
vcs: "git",
|
||||
time: { created: 1, updated: 1 },
|
||||
sandboxes: [],
|
||||
}
|
||||
return json(route, url.pathname === "/project" ? [project] : project)
|
||||
}
|
||||
if (url.pathname === "/path")
|
||||
return json(route, {
|
||||
state: directory,
|
||||
config: directory,
|
||||
worktree: directory,
|
||||
directory,
|
||||
home: directory,
|
||||
})
|
||||
if (url.pathname === "/vcs") return json(route, { branch: "main", default_branch: "main" })
|
||||
return json(route, {})
|
||||
})
|
||||
}
|
||||
|
||||
function session(id: string, directory: string, title: string) {
|
||||
return {
|
||||
id,
|
||||
slug: id,
|
||||
projectID: `project-${id}`,
|
||||
directory,
|
||||
title,
|
||||
version: "dev",
|
||||
time: { created: 1, updated: 1 },
|
||||
}
|
||||
}
|
||||
|
||||
function provider(id: string) {
|
||||
const name = id === "server-b" ? "Server B" : "Server A"
|
||||
return {
|
||||
all: [
|
||||
{
|
||||
id,
|
||||
name: `${name} Provider`,
|
||||
models: {
|
||||
[id]: {
|
||||
id,
|
||||
name: `${name} Model`,
|
||||
family: id,
|
||||
release_date: "2026-01-01",
|
||||
limit: { context: 200_000 },
|
||||
},
|
||||
},
|
||||
},
|
||||
],
|
||||
connected: [id],
|
||||
default: { providerID: id, modelID: id },
|
||||
}
|
||||
}
|
||||
|
||||
function json(route: Route, body: unknown, status = 200) {
|
||||
return route.fulfill({
|
||||
status,
|
||||
contentType: "application/json",
|
||||
headers: { "access-control-allow-origin": "*" },
|
||||
body: JSON.stringify(body),
|
||||
})
|
||||
}
|
||||
|
||||
function sse(route: Route) {
|
||||
return route.fulfill({ status: 200, contentType: "text/event-stream", body: ": ok\n\n" })
|
||||
}
|
||||
@@ -17,14 +17,12 @@ import { mockOpenCodeServer } from "../utils/mock-server"
|
||||
import { installSseTransport } from "../utils/sse-transport"
|
||||
import { expectSessionTitle } from "../utils/waits"
|
||||
|
||||
const initialPageSize = 20
|
||||
const historyPageSize = 200
|
||||
const assistants = Array.from({ length: initialPageSize + 1 }, (_, index) =>
|
||||
const assistants = Array.from({ length: 14 }, (_, index) =>
|
||||
assistantMessage([textPart(`prt_history_root_${index}`, `Assistant response ${index}`)], {
|
||||
id: `msg_${String(index + 1001).padStart(4, "0")}_history_root_assistant`,
|
||||
parentID: userID,
|
||||
created: 1700000001000 + index * 1_000,
|
||||
completed: index < initialPageSize,
|
||||
completed: index < 13,
|
||||
}),
|
||||
)
|
||||
const messages = [userMessage(), ...assistants]
|
||||
@@ -48,7 +46,7 @@ const scenarios = [
|
||||
test.use({ viewport: { width: 646, height: 1385 } })
|
||||
|
||||
for (const scenario of scenarios) {
|
||||
test(`keeps visible timeline content visible through ${scenario.name}`, async ({ page }) => {
|
||||
test(`keeps the latest user turn visible through ${scenario.name}`, async ({ page }) => {
|
||||
const requests: { before?: string; phase: "start" | "end" }[] = []
|
||||
const pages: { before?: string; limit: number }[] = []
|
||||
const roots: { sessionID: string; messageID: string }[] = []
|
||||
@@ -103,51 +101,36 @@ for (const scenario of scenarios) {
|
||||
}
|
||||
},
|
||||
})
|
||||
await page.addInitScript(() => {
|
||||
const visibleParts = () => {
|
||||
const virtual = document.querySelector<HTMLElement>("[data-timeline-virtual-content]")
|
||||
const viewport = virtual?.closest<HTMLElement>(".scroll-view__viewport")
|
||||
const view = viewport?.getBoundingClientRect()
|
||||
if (!viewport || !view) return []
|
||||
return [...viewport.querySelectorAll<HTMLElement>("[data-timeline-part-id]")]
|
||||
.filter((part) => {
|
||||
const rect = part.getBoundingClientRect()
|
||||
return rect.width > 0 && rect.height > 0 && rect.bottom > view.top && rect.top < view.bottom
|
||||
})
|
||||
.flatMap((part) => (part.dataset.timelinePartId ? [part.dataset.timelinePartId] : []))
|
||||
}
|
||||
const state = {
|
||||
armed: false,
|
||||
hidden: false,
|
||||
visibleParts: [] as string[],
|
||||
samples: 0,
|
||||
stop: false,
|
||||
arm() {
|
||||
state.visibleParts = visibleParts()
|
||||
state.armed = true
|
||||
},
|
||||
}
|
||||
;(window as Window & { __historyRootProbe?: typeof state }).__historyRootProbe = state
|
||||
const sample = () => {
|
||||
if (state.armed) {
|
||||
const virtual = document.querySelector<HTMLElement>("[data-timeline-virtual-content]")
|
||||
const viewport = virtual?.closest<HTMLElement>(".scroll-view__viewport")
|
||||
const view = viewport?.getBoundingClientRect()
|
||||
const visible = (partID: string) => {
|
||||
const part = viewport?.querySelector<HTMLElement>(`[data-timeline-part-id="${CSS.escape(partID)}"]`)
|
||||
const rect = part?.getBoundingClientRect()
|
||||
return (
|
||||
!!rect && !!view && rect.width > 0 && rect.height > 0 && rect.bottom > view.top && rect.top < view.bottom
|
||||
)
|
||||
await page.addInitScript(
|
||||
({ userPartID, lastPartID }) => {
|
||||
const state = { armed: false, hidden: false, samples: 0, stop: false }
|
||||
;(window as Window & { __historyRootProbe?: typeof state }).__historyRootProbe = state
|
||||
const sample = () => {
|
||||
if (state.armed) {
|
||||
const virtual = document.querySelector<HTMLElement>("[data-timeline-virtual-content]")
|
||||
const viewport = virtual?.closest<HTMLElement>(".scroll-view__viewport")
|
||||
const view = viewport?.getBoundingClientRect()
|
||||
const visible = (partID: string) => {
|
||||
const part = viewport?.querySelector<HTMLElement>(`[data-timeline-part-id="${partID}"]`)
|
||||
const rect = part?.getBoundingClientRect()
|
||||
return (
|
||||
!!rect &&
|
||||
!!view &&
|
||||
rect.width > 0 &&
|
||||
rect.height > 0 &&
|
||||
rect.bottom > view.top &&
|
||||
rect.top < view.bottom
|
||||
)
|
||||
}
|
||||
if (!virtual || !visible(userPartID) || !visible(lastPartID)) state.hidden = true
|
||||
state.samples++
|
||||
}
|
||||
if (!virtual || state.visibleParts.length === 0 || state.visibleParts.some((partID) => !visible(partID)))
|
||||
state.hidden = true
|
||||
state.samples++
|
||||
if (!state.stop) requestAnimationFrame(() => setTimeout(sample, 0))
|
||||
}
|
||||
if (!state.stop) requestAnimationFrame(() => setTimeout(sample, 0))
|
||||
}
|
||||
requestAnimationFrame(() => setTimeout(sample, 0))
|
||||
})
|
||||
requestAnimationFrame(() => setTimeout(sample, 0))
|
||||
},
|
||||
{ userPartID, lastPartID },
|
||||
)
|
||||
|
||||
await page.goto(`/${base64Encode(directory)}/session/${sessionID}`)
|
||||
await transport.waitForConnection()
|
||||
@@ -160,28 +143,23 @@ for (const scenario of scenarios) {
|
||||
"messages:start:latest",
|
||||
"messages:end:latest",
|
||||
`message:${userID}`,
|
||||
`messages:start:${messages.at(-initialPageSize)!.info.id}`,
|
||||
`messages:start:${messages.at(-2)!.info.id}`,
|
||||
])
|
||||
await expect(page.locator('[data-timeline-part-id^="prt_history_root_"]')).toHaveCount(initialPageSize)
|
||||
await page.evaluate(() => {
|
||||
;(
|
||||
window as Window & {
|
||||
__historyRootProbe?: { arm(): void }
|
||||
__historyRootProbe?: { armed: boolean }
|
||||
}
|
||||
).__historyRootProbe!.arm()
|
||||
).__historyRootProbe!.armed = true
|
||||
})
|
||||
await waitForProbeSamples(page, 0)
|
||||
expect(await visibleContentHidden(page)).toBe(false)
|
||||
expect(await historyRootHidden(page)).toBe(false)
|
||||
const beforeHistory = await probeSamples(page)
|
||||
history.resolve()
|
||||
await expect(page.locator('[data-timeline-part-id^="prt_history_root_"]')).toHaveCount(assistants.length)
|
||||
await expect.poll(() => requests.filter((request) => request.phase === "end").length).toBe(2)
|
||||
await expect(page.locator('[data-timeline-part-id^="prt_history_root_"]')).toHaveCount(14)
|
||||
await expect(page.getByRole("button", { name: "Stop" })).toBeVisible()
|
||||
await waitForProbeSamples(page, beforeHistory)
|
||||
expect(pages).toEqual([
|
||||
{ before: undefined, limit: initialPageSize },
|
||||
{ before: messages.at(-initialPageSize)!.info.id, limit: historyPageSize },
|
||||
])
|
||||
expect(pages[0]).toEqual({ before: undefined, limit: 2 })
|
||||
expect(roots).toEqual([{ sessionID, messageID: userID }])
|
||||
|
||||
const message = messageUpdated(scenario.info)
|
||||
@@ -235,7 +213,7 @@ async function waitForProbeSamples(page: Page, after: number) {
|
||||
)
|
||||
}
|
||||
|
||||
function visibleContentHidden(page: Page) {
|
||||
function historyRootHidden(page: Page) {
|
||||
return page.evaluate(
|
||||
() => (window as Window & { __historyRootProbe?: { hidden: boolean } }).__historyRootProbe!.hidden,
|
||||
)
|
||||
|
||||
@@ -32,23 +32,6 @@ for (const expanded of [false, true]) {
|
||||
})
|
||||
}
|
||||
|
||||
test("shows and expands a running shell command without shimmering it", async ({ page }) => {
|
||||
const id = "prt_shell_running_command"
|
||||
const command = "sleep 10 && echo done"
|
||||
await setupTimeline(page, {
|
||||
messages: [userMessage(), assistantMessage([shell(id, "running", "still running", command)], { completed: false })],
|
||||
settings: { shellToolPartsExpanded: false },
|
||||
})
|
||||
|
||||
const tool = page.locator(`[data-timeline-part-id="${id}"]`)
|
||||
await expect(tool.locator('[data-component="text-shimmer"]')).toHaveAttribute("data-active", "true")
|
||||
await expect(tool.locator('[data-component="shell-submessage"]')).toHaveText(command)
|
||||
await expect(tool.locator('[data-component="shell-submessage"] [data-component="text-shimmer"]')).toHaveCount(0)
|
||||
await tool.locator('[data-slot="collapsible-trigger"]').click()
|
||||
await expect(tool.locator('[data-slot="collapsible-trigger"]')).toHaveAttribute("aria-expanded", "true")
|
||||
await expect(tool.locator('[data-slot="bash-pre"]')).toContainText("still running")
|
||||
})
|
||||
|
||||
test("transitions thinking and hidden reasoning through busy to idle", async ({ page }) => {
|
||||
const reasoningID = "prt_reasoning_hidden"
|
||||
const assistant = assistantMessage([reasoningPart(reasoningID, "## Inspecting stability")], { completed: false })
|
||||
|
||||
@@ -1,5 +1,5 @@
|
||||
import { base64Encode } from "@opencode-ai/core/util/encode"
|
||||
import { expect, test, type Page } from "@playwright/test"
|
||||
import { expect, test } from "@playwright/test"
|
||||
import { mockOpenCodeServer } from "../utils/mock-server"
|
||||
import { expectSessionTitle } from "../utils/waits"
|
||||
|
||||
@@ -7,11 +7,10 @@ const directory = "C:/OpenCode/TerminalComposerFocus"
|
||||
const projectID = "proj_terminal_composer_focus"
|
||||
const sessionID = "ses_terminal_composer_focus"
|
||||
const ptyID = "pty_terminal_composer_focus"
|
||||
const newPtyID = "pty_terminal_composer_focus_new"
|
||||
|
||||
test.use({ viewport: { width: 1440, height: 900 } })
|
||||
|
||||
test.beforeEach(async ({ page }) => {
|
||||
test("routes typing to the composer unless the open terminal is focused", async ({ page }) => {
|
||||
await mockOpenCodeServer(page, {
|
||||
directory,
|
||||
project: {
|
||||
@@ -68,9 +67,7 @@ test.beforeEach(async ({ page }) => {
|
||||
await page.addInitScript(() => {
|
||||
localStorage.setItem("settings.v3", JSON.stringify({ general: { newLayoutDesigns: true } }))
|
||||
})
|
||||
})
|
||||
|
||||
test("routes typing to the composer unless the open terminal is focused", async ({ page }) => {
|
||||
await page.goto(`/${base64Encode(directory)}/session/${sessionID}`)
|
||||
await expectSessionTitle(page, "Terminal composer focus")
|
||||
|
||||
@@ -90,120 +87,3 @@ test("routes typing to the composer unless the open terminal is focused", async
|
||||
await expect(composer).toBeFocused()
|
||||
await expect(composer).toHaveText("a")
|
||||
})
|
||||
|
||||
test("keeps composer focus when a cached terminal finishes mounting", async ({ page }) => {
|
||||
const ghostty = Promise.withResolvers<void>()
|
||||
const release = Promise.withResolvers<void>()
|
||||
const created = { count: 0 }
|
||||
await page.route("**/pty", (route) => {
|
||||
created.count += 1
|
||||
return route.fulfill({
|
||||
status: 200,
|
||||
contentType: "application/json",
|
||||
body: JSON.stringify({ id: ptyID, title: "Terminal 1" }),
|
||||
})
|
||||
})
|
||||
await page.route(/ghostty-web/, async (route) => {
|
||||
ghostty.resolve()
|
||||
await release.promise
|
||||
await route.continue()
|
||||
})
|
||||
await seedCachedTerminal(page)
|
||||
|
||||
await page.goto(`/${base64Encode(directory)}/session/${sessionID}`, { waitUntil: "commit" })
|
||||
await expectSessionTitle(page, "Terminal composer focus")
|
||||
|
||||
const composer = page.locator('[data-component="prompt-input"]')
|
||||
const terminal = page.locator('[data-component="terminal"]')
|
||||
await expect(terminal).toBeVisible()
|
||||
expect(created.count).toBe(0)
|
||||
await ghostty.promise
|
||||
await composer.click()
|
||||
await expect(composer).toBeFocused()
|
||||
|
||||
release.resolve()
|
||||
await expect(terminal.locator("textarea")).toHaveCount(1)
|
||||
await page.waitForTimeout(300)
|
||||
await expect(composer).toBeFocused()
|
||||
})
|
||||
|
||||
test("keeps newer composer focus while an explicit terminal open finishes", async ({ page }) => {
|
||||
const ghostty = Promise.withResolvers<void>()
|
||||
const release = Promise.withResolvers<void>()
|
||||
await page.route(/ghostty-web/, async (route) => {
|
||||
ghostty.resolve()
|
||||
await release.promise
|
||||
await route.continue()
|
||||
})
|
||||
|
||||
await page.goto(`/${base64Encode(directory)}/session/${sessionID}`)
|
||||
await expectSessionTitle(page, "Terminal composer focus")
|
||||
|
||||
const composer = page.locator('[data-component="prompt-input"]')
|
||||
const terminal = page.locator('[data-component="terminal"]')
|
||||
await page.keyboard.press("Control+Backquote")
|
||||
await expect(terminal).toBeVisible()
|
||||
await ghostty.promise
|
||||
await composer.click()
|
||||
await expect(composer).toBeFocused()
|
||||
|
||||
release.resolve()
|
||||
await expect(terminal.locator("textarea")).toHaveCount(1)
|
||||
await page.waitForTimeout(50)
|
||||
await expect(composer).toBeFocused()
|
||||
})
|
||||
|
||||
test("focuses a terminal created from the new-terminal button", async ({ page }) => {
|
||||
const created = { count: 0 }
|
||||
await page.route("**/pty", (route) => {
|
||||
created.count += 1
|
||||
const next = created.count === 1 ? { id: ptyID, title: "Terminal 1" } : { id: newPtyID, title: "Terminal 2" }
|
||||
return route.fulfill({
|
||||
status: 200,
|
||||
contentType: "application/json",
|
||||
body: JSON.stringify(next),
|
||||
})
|
||||
})
|
||||
await page.route(`**/pty/${newPtyID}`, (route) =>
|
||||
route.fulfill({ status: 200, contentType: "application/json", body: "{}" }),
|
||||
)
|
||||
await page.route(`**/pty/${newPtyID}/connect-token*`, (route) =>
|
||||
route.fulfill({
|
||||
status: 200,
|
||||
contentType: "application/json",
|
||||
headers: { "access-control-allow-origin": "*" },
|
||||
body: JSON.stringify({ ticket: "e2e-ticket" }),
|
||||
}),
|
||||
)
|
||||
await page.routeWebSocket(new RegExp(`/pty/${newPtyID}/connect`), () => undefined)
|
||||
|
||||
await page.goto(`/${base64Encode(directory)}/session/${sessionID}`)
|
||||
await expectSessionTitle(page, "Terminal composer focus")
|
||||
|
||||
const composer = page.locator('[data-component="prompt-input"]')
|
||||
const terminal = page.locator('[data-component="terminal"]')
|
||||
await page.keyboard.press("Control+Backquote")
|
||||
await expect(terminal.locator("textarea")).toHaveCount(1)
|
||||
await composer.click()
|
||||
await expect(composer).toBeFocused()
|
||||
|
||||
await page.getByRole("button", { name: "New terminal" }).click()
|
||||
await expect(page.getByRole("tab", { name: "Terminal 2" })).toHaveAttribute("aria-selected", "true")
|
||||
await expect.poll(() => terminal.evaluate((element) => element.contains(document.activeElement))).toBe(true)
|
||||
})
|
||||
|
||||
function seedCachedTerminal(page: Page) {
|
||||
return page.addInitScript(
|
||||
({ terminalKey, ptyID }) => {
|
||||
localStorage.setItem("opencode.global.dat:layout", JSON.stringify({ terminal: { height: 320, opened: true } }))
|
||||
localStorage.setItem(
|
||||
terminalKey,
|
||||
JSON.stringify({
|
||||
active: ptyID,
|
||||
all: [{ id: ptyID, title: "Terminal 1", titleNumber: 1 }],
|
||||
}),
|
||||
)
|
||||
},
|
||||
{ terminalKey: `${base64Encode(directory)}/terminal.v1`, ptyID },
|
||||
)
|
||||
}
|
||||
|
||||
@@ -1,34 +0,0 @@
|
||||
<!doctype html>
|
||||
<html lang="en">
|
||||
<head>
|
||||
<meta charset="UTF-8" />
|
||||
<meta name="viewport" content="width=device-width, initial-scale=1.0" />
|
||||
<title>Timeline Suspense Reproduction</title>
|
||||
<style>
|
||||
* {
|
||||
box-sizing: border-box;
|
||||
}
|
||||
|
||||
html,
|
||||
body,
|
||||
#root {
|
||||
margin: 0;
|
||||
min-height: 100%;
|
||||
}
|
||||
|
||||
body {
|
||||
background: #171717;
|
||||
color: #f5f5f5;
|
||||
font-family: ui-monospace, SFMono-Regular, Consolas, monospace;
|
||||
}
|
||||
|
||||
#root {
|
||||
padding: 24px;
|
||||
}
|
||||
</style>
|
||||
</head>
|
||||
<body>
|
||||
<main id="root"></main>
|
||||
<script type="module" src="/main.tsx"></script>
|
||||
</body>
|
||||
</html>
|
||||
@@ -1,315 +0,0 @@
|
||||
import { createResource, createSignal, For, onMount, Suspense } from "solid-js"
|
||||
import { render } from "solid-js/web"
|
||||
import { createVirtualizer, observeElementOffset, observeElementRect } from "@tanstack/solid-virtual"
|
||||
import { observeElementOffsetReconnectAware } from "../../../src/pages/session/timeline/observe-element-offset"
|
||||
|
||||
const rowCount = 2_000
|
||||
const rowHeight = 40
|
||||
const parameters = new URLSearchParams(location.search)
|
||||
const resourceMode = parameters.get("resource") === "guard" ? "guard" : "baseline"
|
||||
const reconnectMode = parameters.get("reconnect") === "candidate" ? "candidate" : "baseline"
|
||||
|
||||
type MutationEvent = {
|
||||
kind: "removed" | "added"
|
||||
callbackTime: number
|
||||
callbackFrame: number
|
||||
routeConnectedInCallback: boolean
|
||||
nativeOffsetInCallback: number
|
||||
}
|
||||
|
||||
type Snapshot = {
|
||||
mode: {
|
||||
resource: "baseline" | "guard"
|
||||
reconnect: "baseline" | "candidate"
|
||||
}
|
||||
operation: {
|
||||
sequence: number
|
||||
phase: string
|
||||
time: number
|
||||
frame: number
|
||||
}
|
||||
resourceState: string
|
||||
routeConnected: boolean
|
||||
viewportConnected: boolean
|
||||
viewportOwnedByRoute: boolean
|
||||
sameRoute: boolean
|
||||
sameViewport: boolean
|
||||
sameSurface: boolean
|
||||
sameMountedRows: boolean
|
||||
nativeOffset: number
|
||||
coreOffset: number
|
||||
rangeStart: number
|
||||
rangeEnd: number
|
||||
indexes: number[]
|
||||
domIndexes: number[]
|
||||
logicalSurfaceHeight: number
|
||||
renderedSurfaceHeight: number
|
||||
viewportClientHeight: number
|
||||
viewportScrollHeight: number
|
||||
visibleRows: number
|
||||
minimumRowTop: number
|
||||
domScrollEvents: number
|
||||
lastScrollTrusted: boolean
|
||||
coreOffsetCallbackCalls: number
|
||||
offsetCallbackSources: "observer"[]
|
||||
rectObserverCallbacks: number
|
||||
ignoredDetachedZeroRects: number
|
||||
syntheticScrollDispatches: number
|
||||
mutationEvents: MutationEvent[]
|
||||
}
|
||||
|
||||
declare global {
|
||||
interface Window {
|
||||
timelineSuspense: {
|
||||
prepare: () => Promise<Snapshot>
|
||||
trigger: () => void
|
||||
resolve: () => void
|
||||
frames: (count?: number) => Promise<void>
|
||||
snapshot: () => Snapshot
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
function App() {
|
||||
const [refresh, setRefresh] = createSignal(false)
|
||||
let resolveResource: (() => void) | undefined
|
||||
const [resource] = createResource(
|
||||
refresh,
|
||||
(version) =>
|
||||
new Promise<string>((resolve) => {
|
||||
resolveResource = () => resolve(`settled-${version}`)
|
||||
}),
|
||||
{ initialValue: "settled" },
|
||||
)
|
||||
|
||||
function Route() {
|
||||
let route: HTMLElement | undefined
|
||||
let viewport: HTMLDivElement | undefined
|
||||
let surface: HTMLDivElement | undefined
|
||||
let initialRoute: HTMLElement | undefined
|
||||
let initialViewport: HTMLDivElement | undefined
|
||||
let initialSurface: HTMLDivElement | undefined
|
||||
let initialRows: HTMLElement[] = []
|
||||
let phase = "mounting"
|
||||
let browserFrame = 0
|
||||
let snapshotSequence = 0
|
||||
let domScrollEvents = 0
|
||||
let lastScrollTrusted = false
|
||||
let coreOffsetCallbackCalls = 0
|
||||
let rectObserverCallbacks = 0
|
||||
let ignoredDetachedZeroRects = 0
|
||||
const offsetCallbackSources: "observer"[] = []
|
||||
const mutationEvents: MutationEvent[] = []
|
||||
const virtualizer = createVirtualizer<HTMLDivElement, HTMLDivElement>({
|
||||
count: rowCount,
|
||||
getScrollElement: () => viewport ?? null,
|
||||
estimateSize: () => rowHeight,
|
||||
initialRect: { width: 900, height: 600 },
|
||||
overscan: 2,
|
||||
observeElementRect: (instance, callback) =>
|
||||
observeElementRect(instance, (rect) => {
|
||||
rectObserverCallbacks++
|
||||
// A fixed 600px viewport has no usable geometry while detached. Keep the last connected rect.
|
||||
if (!instance.scrollElement?.isConnected && rect.height === 0) {
|
||||
ignoredDetachedZeroRects++
|
||||
return
|
||||
}
|
||||
callback(rect)
|
||||
}),
|
||||
observeElementOffset: (instance, callback) => {
|
||||
const deliver = (offset: number, isScrolling: boolean) => {
|
||||
coreOffsetCallbackCalls++
|
||||
offsetCallbackSources.push("observer")
|
||||
callback(offset, isScrolling)
|
||||
}
|
||||
if (reconnectMode === "candidate") return observeElementOffsetReconnectAware(instance, deliver)
|
||||
return observeElementOffset(instance, deliver)
|
||||
},
|
||||
})
|
||||
|
||||
const frames = async (count = 2) => {
|
||||
for (let index = 0; index < count; index++) {
|
||||
await new Promise<void>((resolve) => requestAnimationFrame(() => resolve()))
|
||||
}
|
||||
}
|
||||
const mountedRows = () => [...(surface?.querySelectorAll<HTMLElement>("[data-row-index]") ?? [])]
|
||||
const snapshot = (): Snapshot => {
|
||||
const rows = mountedRows()
|
||||
const view = viewport?.getBoundingClientRect()
|
||||
const visibleRows =
|
||||
viewport?.isConnected && view
|
||||
? rows.filter((row) => {
|
||||
const rect = row.getBoundingClientRect()
|
||||
return rect.bottom > view.top && rect.top < view.bottom
|
||||
}).length
|
||||
: 0
|
||||
return {
|
||||
mode: { resource: resourceMode, reconnect: reconnectMode },
|
||||
operation: {
|
||||
sequence: ++snapshotSequence,
|
||||
phase,
|
||||
time: performance.now(),
|
||||
frame: browserFrame,
|
||||
},
|
||||
resourceState: resource.state,
|
||||
routeConnected: route?.isConnected ?? false,
|
||||
viewportConnected: viewport?.isConnected ?? false,
|
||||
viewportOwnedByRoute: !!route && !!viewport && route.contains(viewport),
|
||||
sameRoute: route === initialRoute,
|
||||
sameViewport: viewport === initialViewport,
|
||||
sameSurface: surface === initialSurface,
|
||||
sameMountedRows:
|
||||
initialRows.length > 0 &&
|
||||
initialRows.length === rows.length &&
|
||||
initialRows.every((row, index) => row === rows[index]),
|
||||
nativeOffset: viewport?.scrollTop ?? -1,
|
||||
coreOffset: virtualizer.scrollOffset ?? -1,
|
||||
rangeStart: virtualizer.range?.startIndex ?? -1,
|
||||
rangeEnd: virtualizer.range?.endIndex ?? -1,
|
||||
indexes: virtualizer.getVirtualItems().map((item) => item.index),
|
||||
domIndexes: rows.map((row) => Number(row.dataset.rowIndex)),
|
||||
logicalSurfaceHeight: Number.parseFloat(surface?.style.height ?? "-1"),
|
||||
renderedSurfaceHeight: surface?.getBoundingClientRect().height ?? -1,
|
||||
viewportClientHeight: viewport?.clientHeight ?? -1,
|
||||
viewportScrollHeight: viewport?.scrollHeight ?? -1,
|
||||
visibleRows,
|
||||
minimumRowTop:
|
||||
rows.length && view ? Math.min(...rows.map((row) => row.getBoundingClientRect().top - view.top)) : -1,
|
||||
domScrollEvents,
|
||||
lastScrollTrusted,
|
||||
coreOffsetCallbackCalls,
|
||||
offsetCallbackSources: [...offsetCallbackSources],
|
||||
rectObserverCallbacks,
|
||||
ignoredDetachedZeroRects,
|
||||
syntheticScrollDispatches: 0,
|
||||
mutationEvents: mutationEvents.map((event) => ({ ...event })),
|
||||
}
|
||||
}
|
||||
|
||||
onMount(() => {
|
||||
if (!route || !viewport || !surface) throw new Error("Timeline fixture did not mount")
|
||||
const routeRoot = route.parentElement
|
||||
if (!routeRoot) throw new Error("Timeline route root did not mount")
|
||||
initialRoute = route
|
||||
initialViewport = viewport
|
||||
initialSurface = surface
|
||||
viewport.addEventListener("scroll", (event) => {
|
||||
domScrollEvents++
|
||||
lastScrollTrusted = event.isTrusted
|
||||
})
|
||||
const countFrames = () => {
|
||||
browserFrame++
|
||||
requestAnimationFrame(countFrames)
|
||||
}
|
||||
requestAnimationFrame(countFrames)
|
||||
new MutationObserver((records) => {
|
||||
const callbackTime = performance.now()
|
||||
records.forEach((record) => {
|
||||
;([...(record.removedNodes ?? [])] as Node[]).forEach((node) => {
|
||||
if (node !== route) return
|
||||
phase = "detached"
|
||||
mutationEvents.push({
|
||||
kind: "removed",
|
||||
callbackTime,
|
||||
callbackFrame: browserFrame,
|
||||
routeConnectedInCallback: route.isConnected,
|
||||
nativeOffsetInCallback: viewport.scrollTop,
|
||||
})
|
||||
})
|
||||
;([...(record.addedNodes ?? [])] as Node[]).forEach((node) => {
|
||||
if (node !== route) return
|
||||
phase = "reinserted"
|
||||
mutationEvents.push({
|
||||
kind: "added",
|
||||
callbackTime,
|
||||
callbackFrame: browserFrame,
|
||||
routeConnectedInCallback: route.isConnected,
|
||||
nativeOffsetInCallback: viewport.scrollTop,
|
||||
})
|
||||
})
|
||||
})
|
||||
}).observe(routeRoot, { childList: true })
|
||||
window.timelineSuspense = {
|
||||
prepare: async () => {
|
||||
phase = "preparing"
|
||||
await frames(2)
|
||||
viewport.scrollTop = viewport.scrollHeight
|
||||
await frames(3)
|
||||
await new Promise((resolve) => setTimeout(resolve, 200))
|
||||
await frames(2)
|
||||
initialRows = mountedRows()
|
||||
phase = "prepared"
|
||||
return snapshot()
|
||||
},
|
||||
trigger: () => {
|
||||
phase = "triggering"
|
||||
setRefresh(true)
|
||||
},
|
||||
resolve: () => {
|
||||
if (!resolveResource) throw new Error("Resource is not pending")
|
||||
phase = "resolving"
|
||||
resolveResource()
|
||||
},
|
||||
frames,
|
||||
snapshot,
|
||||
}
|
||||
})
|
||||
|
||||
return (
|
||||
<section ref={route} data-route style={{ width: "900px", margin: "0 auto" }}>
|
||||
<span aria-hidden="true" style={{ display: "none" }}>
|
||||
{resourceMode === "guard" && resource.state === "refreshing" ? resource.latest : resource()}
|
||||
</span>
|
||||
<div
|
||||
ref={viewport}
|
||||
data-viewport
|
||||
style={{
|
||||
height: "600px",
|
||||
overflow: "auto",
|
||||
"overflow-anchor": "none",
|
||||
position: "relative",
|
||||
background: "#202020",
|
||||
outline: "1px solid #3f3f46",
|
||||
}}
|
||||
>
|
||||
<div
|
||||
ref={surface}
|
||||
data-surface
|
||||
style={{ height: `${virtualizer.getTotalSize()}px`, position: "relative", "overflow-anchor": "none" }}
|
||||
>
|
||||
<For each={virtualizer.getVirtualItems()}>
|
||||
{(item) => (
|
||||
<div
|
||||
data-row-index={item.index}
|
||||
style={{
|
||||
position: "absolute",
|
||||
top: "0",
|
||||
left: "0",
|
||||
width: "100%",
|
||||
height: `${item.size}px`,
|
||||
transform: `translateY(${item.start}px)`,
|
||||
padding: "10px 14px",
|
||||
border: "0 solid #333",
|
||||
"border-bottom-width": "1px",
|
||||
}}
|
||||
>
|
||||
logical row {item.index}
|
||||
</div>
|
||||
)}
|
||||
</For>
|
||||
</div>
|
||||
</div>
|
||||
</section>
|
||||
)
|
||||
}
|
||||
|
||||
return (
|
||||
<main>
|
||||
<Suspense>
|
||||
<Route />
|
||||
</Suspense>
|
||||
</main>
|
||||
)
|
||||
}
|
||||
|
||||
render(() => <App />, document.getElementById("root")!)
|
||||
@@ -1,34 +0,0 @@
|
||||
import { defineConfig, devices } from "@playwright/test"
|
||||
|
||||
const port = Number(process.env.PLAYWRIGHT_TIMELINE_SUSPENSE_PORT ?? 4317)
|
||||
|
||||
export default defineConfig({
|
||||
testDir: ".",
|
||||
testMatch: "timeline-suspense.repro.ts",
|
||||
outputDir: "../../test-results/timeline-suspense",
|
||||
fullyParallel: false,
|
||||
workers: 1,
|
||||
retries: 0,
|
||||
reporter: "line",
|
||||
timeout: 30_000,
|
||||
expect: {
|
||||
timeout: 10_000,
|
||||
},
|
||||
webServer: {
|
||||
command: `bunx vite --config vite.config.ts --host 127.0.0.1 --port ${port} --strictPort`,
|
||||
cwd: import.meta.dirname,
|
||||
url: `http://127.0.0.1:${port}`,
|
||||
reuseExistingServer: false,
|
||||
},
|
||||
use: {
|
||||
baseURL: `http://127.0.0.1:${port}`,
|
||||
trace: "retain-on-failure",
|
||||
screenshot: "only-on-failure",
|
||||
},
|
||||
projects: [
|
||||
{
|
||||
name: "chromium",
|
||||
use: { ...devices["Desktop Chrome"] },
|
||||
},
|
||||
],
|
||||
})
|
||||
@@ -1,179 +0,0 @@
|
||||
import { expect, test, type Page } from "@playwright/test"
|
||||
|
||||
test.beforeEach(async ({ page }) => {
|
||||
page.on("pageerror", (error) => console.error(error))
|
||||
await page.goto("/")
|
||||
await expect.poll(() => page.evaluate(() => !!window.timelineSuspense)).toBe(true)
|
||||
})
|
||||
|
||||
test("desired: preserves visible timeline continuity across descendant resource suspension", async ({ page }) => {
|
||||
await page.goto("/?reconnect=candidate")
|
||||
await expect.poll(() => page.evaluate(() => window.timelineSuspense.snapshot().mode.reconnect)).toBe("candidate")
|
||||
const before = await prepare(page)
|
||||
await triggerBaselineSuspension(page)
|
||||
const pending = await page.evaluate(() => window.timelineSuspense.snapshot())
|
||||
expect(pending.nativeOffset).toBe(0)
|
||||
expect(pending.coreOffset).toBe(before.coreOffset)
|
||||
expect(pending.indexes).toEqual(before.indexes)
|
||||
expect(pending.sameRoute).toBe(true)
|
||||
expect(pending.sameViewport).toBe(true)
|
||||
expect(pending.sameSurface).toBe(true)
|
||||
expect(pending.sameMountedRows).toBe(true)
|
||||
|
||||
await resolveSuspension(page)
|
||||
await expect.poll(() => page.evaluate(() => window.timelineSuspense.snapshot().coreOffset)).toBe(0)
|
||||
await page.waitForTimeout(250)
|
||||
await page.evaluate(() => window.timelineSuspense.frames(2))
|
||||
const after = await page.evaluate(() => window.timelineSuspense.snapshot())
|
||||
expect(after.sameRoute).toBe(true)
|
||||
expect(after.sameViewport).toBe(true)
|
||||
expect(after.sameSurface).toBe(true)
|
||||
expect(after.nativeOffset).toBe(0)
|
||||
expect(after.coreOffset).toBe(0)
|
||||
expect(after.rangeStart).toBeLessThan(10)
|
||||
expect(after.visibleRows, diagnostic({ before, pending, after })).toBeGreaterThan(0)
|
||||
expect(after.domScrollEvents).toBe(before.domScrollEvents)
|
||||
expect(after.coreOffsetCallbackCalls).toBe(before.coreOffsetCallbackCalls + 1)
|
||||
expect(after.offsetCallbackSources.at(-1)).toBe("observer")
|
||||
expect(after.syntheticScrollDispatches).toBe(0)
|
||||
})
|
||||
|
||||
test("forensic: proves detached same-node viewport leaves TanStack's bottom range blank until a real scroll", async ({
|
||||
page,
|
||||
}) => {
|
||||
const before = await prepare(page)
|
||||
const beforeRows = before.domIndexes
|
||||
expect(before.mode).toEqual({ resource: "baseline", reconnect: "baseline" })
|
||||
expect(before.logicalSurfaceHeight).toBe(80_000)
|
||||
expect(before.renderedSurfaceHeight).toBe(80_000)
|
||||
expect(before.viewportClientHeight).toBe(600)
|
||||
expect(before.viewportScrollHeight).toBe(80_000)
|
||||
expect(before.rangeStart).toBeGreaterThan(1_900)
|
||||
expect(before.nativeOffset).toBe(before.coreOffset)
|
||||
expect(before.visibleRows).toBeGreaterThan(0)
|
||||
|
||||
await triggerBaselineSuspension(page)
|
||||
const pending = await page.evaluate(() => window.timelineSuspense.snapshot())
|
||||
expect(pending.resourceState).toBe("refreshing")
|
||||
expect(pending.routeConnected).toBe(false)
|
||||
expect(pending.viewportConnected).toBe(false)
|
||||
expect(pending.viewportOwnedByRoute).toBe(true)
|
||||
expect(pending.nativeOffset).toBe(0)
|
||||
expect(pending.coreOffset).toBe(before.coreOffset)
|
||||
expect(pending.rangeStart).toBe(before.rangeStart)
|
||||
expect(pending.rangeEnd).toBe(before.rangeEnd)
|
||||
expect(pending.indexes).toEqual(before.indexes)
|
||||
expect(pending.domIndexes).toEqual(beforeRows)
|
||||
expect(pending.sameMountedRows).toBe(true)
|
||||
expect(pending.domScrollEvents).toBe(before.domScrollEvents)
|
||||
expect(pending.coreOffsetCallbackCalls).toBe(before.coreOffsetCallbackCalls)
|
||||
expect(pending.ignoredDetachedZeroRects).toBeGreaterThan(before.ignoredDetachedZeroRects)
|
||||
expect(pending.mutationEvents).toHaveLength(1)
|
||||
expect(pending.mutationEvents[0]).toMatchObject({
|
||||
kind: "removed",
|
||||
routeConnectedInCallback: false,
|
||||
nativeOffsetInCallback: 0,
|
||||
})
|
||||
expect(pending.mutationEvents[0]!.callbackTime).toBeLessThanOrEqual(pending.operation.time)
|
||||
expect(pending.mutationEvents[0]!.callbackFrame).toBeLessThanOrEqual(pending.operation.frame)
|
||||
|
||||
const after = await resolveSuspension(page)
|
||||
expect(after.resourceState).toBe("ready")
|
||||
expect(after.routeConnected).toBe(true)
|
||||
expect(after.viewportConnected).toBe(true)
|
||||
expect(after.viewportOwnedByRoute).toBe(true)
|
||||
expect(after.sameRoute).toBe(true)
|
||||
expect(after.sameViewport).toBe(true)
|
||||
expect(after.sameSurface).toBe(true)
|
||||
expect(after.sameMountedRows).toBe(true)
|
||||
expect(after.nativeOffset).toBe(0)
|
||||
expect(after.coreOffset).toBe(before.coreOffset)
|
||||
expect(after.rangeStart).toBe(before.rangeStart)
|
||||
expect(after.rangeEnd).toBe(before.rangeEnd)
|
||||
expect(after.indexes).toEqual(before.indexes)
|
||||
expect(after.domIndexes).toEqual(beforeRows)
|
||||
expect(after.domScrollEvents).toBe(before.domScrollEvents)
|
||||
expect(after.coreOffsetCallbackCalls).toBe(before.coreOffsetCallbackCalls)
|
||||
expect(after.mutationEvents).toHaveLength(2)
|
||||
expect(after.mutationEvents[1]).toMatchObject({
|
||||
kind: "added",
|
||||
routeConnectedInCallback: true,
|
||||
nativeOffsetInCallback: 0,
|
||||
})
|
||||
expect(after.mutationEvents[1]!.callbackTime).toBeLessThanOrEqual(after.operation.time)
|
||||
expect(after.mutationEvents[1]!.callbackFrame).toBeLessThanOrEqual(after.operation.frame)
|
||||
expect(after.visibleRows).toBe(0)
|
||||
expect(after.minimumRowTop).toBeGreaterThan(50_000)
|
||||
expect(after.syntheticScrollDispatches).toBe(0)
|
||||
|
||||
await page.locator("[data-viewport]").hover()
|
||||
await page.mouse.wheel(0, 80)
|
||||
await expect
|
||||
.poll(() =>
|
||||
page.evaluate(() => {
|
||||
const value = window.timelineSuspense.snapshot()
|
||||
return value.nativeOffset > 0 && value.coreOffset === value.nativeOffset
|
||||
}),
|
||||
)
|
||||
.toBe(true)
|
||||
await page.evaluate(() => window.timelineSuspense.frames(2))
|
||||
const recovered = await page.evaluate(() => window.timelineSuspense.snapshot())
|
||||
expect(recovered.domScrollEvents).toBeGreaterThan(after.domScrollEvents)
|
||||
expect(recovered.coreOffsetCallbackCalls).toBeGreaterThan(after.coreOffsetCallbackCalls)
|
||||
expect(recovered.offsetCallbackSources.at(-1)).toBe("observer")
|
||||
expect(recovered.lastScrollTrusted).toBe(true)
|
||||
expect(recovered.rangeStart).toBeLessThan(10)
|
||||
expect(recovered.visibleRows).toBeGreaterThan(0)
|
||||
})
|
||||
|
||||
test("matrix: fixture-only settled-resource guard keeps the route connected", async ({ page }) => {
|
||||
await page.goto("/?resource=guard")
|
||||
await expect.poll(() => page.evaluate(() => window.timelineSuspense.snapshot().mode.resource)).toBe("guard")
|
||||
const before = await prepare(page)
|
||||
|
||||
await page.evaluate(() => window.timelineSuspense.trigger())
|
||||
await expect.poll(() => page.evaluate(() => window.timelineSuspense.snapshot().resourceState)).toBe("refreshing")
|
||||
await page.evaluate(() => window.timelineSuspense.frames(3))
|
||||
const pending = await page.evaluate(() => window.timelineSuspense.snapshot())
|
||||
expect(pending.routeConnected).toBe(true)
|
||||
expect(pending.mutationEvents).toEqual([])
|
||||
expect(pending.nativeOffset).toBe(before.nativeOffset)
|
||||
expect(pending.coreOffset).toBe(before.coreOffset)
|
||||
expect(pending.visibleRows).toBeGreaterThan(0)
|
||||
|
||||
const after = await resolveSuspension(page)
|
||||
expect(after.routeConnected).toBe(true)
|
||||
expect(after.nativeOffset).toBe(before.nativeOffset)
|
||||
expect(after.coreOffset).toBe(before.coreOffset)
|
||||
expect(after.visibleRows).toBeGreaterThan(0)
|
||||
})
|
||||
|
||||
async function prepare(page: Page) {
|
||||
const before = await page.evaluate(() => window.timelineSuspense.prepare())
|
||||
expect(before.routeConnected).toBe(true)
|
||||
expect(before.viewportConnected).toBe(true)
|
||||
expect(before.viewportOwnedByRoute).toBe(true)
|
||||
expect(before.sameMountedRows).toBe(true)
|
||||
expect(before.rangeStart).toBeGreaterThan(1_900)
|
||||
expect(before.nativeOffset).toBe(before.coreOffset)
|
||||
return before
|
||||
}
|
||||
|
||||
async function triggerBaselineSuspension(page: Page) {
|
||||
await page.evaluate(() => window.timelineSuspense.trigger())
|
||||
await expect.poll(() => page.evaluate(() => window.timelineSuspense.snapshot().resourceState)).toBe("refreshing")
|
||||
await expect.poll(() => page.evaluate(() => window.timelineSuspense.snapshot().routeConnected)).toBe(false)
|
||||
await page.evaluate(() => window.timelineSuspense.frames(3))
|
||||
}
|
||||
|
||||
async function resolveSuspension(page: Page) {
|
||||
await page.evaluate(() => window.timelineSuspense.resolve())
|
||||
await expect.poll(() => page.evaluate(() => window.timelineSuspense.snapshot().resourceState)).toBe("ready")
|
||||
await expect.poll(() => page.evaluate(() => window.timelineSuspense.snapshot().routeConnected)).toBe(true)
|
||||
await page.evaluate(() => window.timelineSuspense.frames(3))
|
||||
return page.evaluate(() => window.timelineSuspense.snapshot())
|
||||
}
|
||||
|
||||
function diagnostic(value: unknown) {
|
||||
return JSON.stringify(value, null, 2)
|
||||
}
|
||||
Some files were not shown because too many files have changed in this diff Show More
Reference in New Issue
Block a user