Compare commits

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Author SHA1 Message Date
Kit Langton 9f06708d0e fix(plugin): load Effect from the host for plugins 2026-10-04 23:14:49 -07:00
usrnk1andLuke Parker e86ec98711 feat(desktop): move review controls into their panels (#51312)
Co-authored-by: Luke Parker <10430890+Hona@users.noreply.github.com>
2026-10-05 03:18:48 +00:00
Luke Parker c542a43503 fix(cli): indent every row of the pairing QR code on Windows (#53265) 2026-10-05 03:02:36 +00:00
Luke Parker 2db9c2e1b3 fix(app): match TUI inbox, steer, queue, and revert behavior (#53076) 2026-10-05 12:54:06 +10:00
Luke Parker 3a861ff8b0 feat(app): show running subagents and shells in the session header (#53247) 2026-10-05 12:30:44 +10:00
Aiden Cline 22803892bc feat(ai): support Anthropic Messages on Bedrock Mantle (#53073) 2026-10-04 20:51:33 -05:00
Aiden Cline 69ba898a7b perf(ai): lazily parse partial JSON on tool-input-delta (#53255) 2026-10-04 20:41:46 -05:00
opencode-agent[bot]andrekram1-node 375ff827aa feat(tui): show read ranges after file paths (#53250)
Co-authored-by: rekram1-node <rekram1-node@users.noreply.github.com>
2026-10-04 20:14:48 -05:00
Luke Parker ed747091e9 fix(gui-extensions): hold agent previews for sessions that are not on screen (#53249) 2026-10-05 00:56:05 +00:00
Aiden Cline 44193bd71f refactor(ai): untrace stream event handlers and inner protocol helpers (#53232) 2026-10-04 19:43:29 -05:00
Aiden Cline 238d4cf5ca refactor(ai): simplify sseFraming and untrace inner request-lowering helpers (#53072) 2026-10-04 16:27:06 -05:00
Kit Langton 3e77d5c170 fix(client): preserve service on protocol-only reconnect mismatch (#50825) 2026-10-04 13:30:43 -07:00
Kit Langton eaf80d99e5 chore(app): clear lint warnings in GUI files touched by the Effect upgrade (#53098) 2026-10-04 12:04:16 -07:00
opencode-agent[bot] 0a46301e36 chore(core): refresh bundled models.dev snapshot 2026-10-04 13:59:27 +00:00
Shoubhit Dash c789aa16d1 refactor(ai): remove unused test code (#53126) 2026-10-04 17:07:07 +05:30
Shoubhit Dash a515e3bf4b refactor(ai): delete unregistered recording cassettes (#53127) 2026-10-04 17:06:42 +05:30
Shoubhit Dash 8380c864bf feat(plugin): add select dialog search and actions (#53009) 2026-10-04 16:10:27 +05:30
Shoubhit Dash 247eb5cc9a fix(tui): allow plugin keymaps during setup (#53010) 2026-10-04 15:46:34 +05:30
Luke Parker ecfa884ff8 feat(session-ui): show model variant in message meta (#53112) 2026-10-04 08:21:24 +00:00
Luke Parker 0d536d2d7d fix(gui-extensions): avoid startup round trip and keep renamed enable state (#53077) 2026-10-04 17:40:36 +10:00
Luke Parker 715de7af15 fix(gui-extensions): fix stale details, browser cleanup, update checks and panel state (#53075) 2026-10-04 17:21:04 +10:00
Luke Parker 077444b94b fix(app): keep side panel tabs when a session moves (#53081) 2026-10-04 16:59:52 +10:00
Luke Parker 5589ca43f1 refactor(gui-extensions): tighten the SDK surface (#53078) 2026-10-04 16:59:43 +10:00
Luke Parker 453dd2ad01 fix(app): load Windows-path markdown images (#53100) 2026-10-04 06:49:36 +00:00
Luke Parker 44579a5d98 test(app): mock session wait and parse e2e mock payloads (#53095) 2026-10-04 16:32:34 +10:00
Luke Parker f8cafd8362 fix(app): stop the browser address bar looking bold when selected (#53087) 2026-10-04 16:23:08 +10:00
Kit Langton 9155b7b791 fix(app): load component-test modules at the URLs Vite imports them by (#53091) 2026-10-04 16:06:48 +10:00
Kit Langton 9c66a0acb0 refactor(tui): remove unused plugin theme registration (#52992) 2026-10-03 21:50:55 -07:00
Kit Langton ee730bdd91 refactor(tui): remove unused V1 syntax theme generation (#52987) 2026-10-03 21:43:07 -07:00
Kit Langton cfbdefa041 refactor(tui): trim unused package exports (#52988) 2026-10-03 21:43:03 -07:00
Kit Langton 2884b49f8f refactor(tui): remove permanently disabled unshare command (#53003) 2026-10-03 21:34:00 -07:00
Kit Langton b79da2697a refactor(tui): drop unused ComposerTab.onClose and composer re-export (#53002) 2026-10-03 21:33:55 -07:00
Kit Langton 552d2b9c8a refactor(tui): drop never-passed component props (#53001) 2026-10-03 21:33:51 -07:00
Kit Langton 0d98734fb2 refactor(tui): share mini requestOptions helper (#53000) 2026-10-03 21:33:47 -07:00
Kit Langton 5ac5027cce refactor(tui): remove unused mini thinking override (#52999) 2026-10-03 21:33:42 -07:00
Kit Langton 4cb7ac9dab refactor(tui): drop constant mini frontend exit code (#52998) 2026-10-03 21:33:37 -07:00
Kit Langton bc499e4562 refactor(tui): remove unused monoTruncateMiddle (#52997) 2026-10-03 21:33:33 -07:00
Kit Langton fa373ddb51 refactor(tui): share clamp between tab pulse and fade-in text (#52996) 2026-10-03 21:33:28 -07:00
Kit Langton 2a02be02a7 refactor(tui): remove unused TabPulse outerFlashTail prop (#52995) 2026-10-03 21:33:23 -07:00
Kit Langton fc224dc8f0 refactor(tui): remove unused DialogSelect details and category view options (#52994) 2026-10-03 21:33:18 -07:00
Kit Langton eec8cf912e refactor(tui): remove unused Prompt hint, right, and showPlaceholder props (#52993) 2026-10-03 21:33:13 -07:00
Kit Langton 86f9edc107 refactor(tui): remove unread terminal environment fields (#52991) 2026-10-03 21:33:08 -07:00
Kit Langton 5d6804eaac refactor(tui): remove unused v1 config aliases and keybind values (#52990) 2026-10-03 21:33:03 -07:00
Kit Langton 697ca1c9d3 refactor(tui): drop unused theme re-exports (#52986) 2026-10-03 21:32:58 -07:00
Kit Langton 1287996a91 refactor(tui): drop stale terminal-win32 export (#52985) 2026-10-03 21:32:54 -07:00
Kit Langton a30f24355e refactor(tui): share file change status label (#53004) 2026-10-03 23:50:25 -04:00
Jérôme Benoit 96ecd60bdb fix(nix): provide desktop signing tools on darwin (#53007) 2026-10-03 22:33:12 -05:00
Aiden Cline 15c4e5d537 feat(ai): add Google Interactions protocol (#52981) 2026-10-03 22:22:58 -05:00
Aiden Cline 5617044dc9 refactor(ai): avoid redundant request body validation (#52909) 2026-10-03 22:22:15 -05:00
Luke Parker 0048c97c27 feat(gui-extensions): add typed composition and lifetime primitives (#52868) 2026-10-04 13:16:37 +10:00
opencode-agent[bot]andHona f72a103a4b fix(windows): hide background subprocess windows (#52871)
Co-authored-by: Hona <10430890+Hona@users.noreply.github.com>
2026-10-04 11:20:47 +10:00
opencode-agent[bot] f74512bfe0 chore: update nix node_modules hashes 2026-10-03 23:05:19 +00:00
opencode-agent[bot]andneriousy 63b7de9434 fix(cli): restore Linux x64 musl PTY lock entry (#53035)
Co-authored-by: neriousy <34747899+neriousy@users.noreply.github.com>
2026-10-04 00:55:38 +02:00
Filip e8c75c2de0 fix(cli): run the curl installer with Git Bash on Windows (#53029) 2026-10-04 00:29:09 +02:00
opencode-agent[bot] d1f8f5b35e chore: update nix node_modules hashes 2026-10-03 18:57:44 +00:00
Kit Langton 334f7a3510 fix(core): keep the first PTY output after spawn (#52960) 2026-10-03 11:51:01 -07:00
opencode-agent[bot] f02e184ba4 chore: update nix node_modules hashes 2026-10-03 14:32:42 +00:00
James Long 5ad0786536 fix(core): never let persistent PTY handoff break a server restart (#52573) 2026-10-03 10:23:31 -04:00
opencode-agent[bot] d8a3962923 chore(core): refresh bundled models.dev snapshot 2026-10-03 13:46:03 +00:00
Simon Klee 40679546d4 fix(tui): keep transcript rows stable when history is prepended (#52824)
Session rows have no id, so reconcile matched them by position. Each page of older history shifted every row into a different store object and remounted the visible transcript. Newly mounted markdown is blank until highlighting finishes, so the transcript blinked once per page. This was most visible with Low verbosity, where opening a session loads several pages to complete the oldest group.
2026-10-03 06:09:37 +00:00
Daniel Chen 12810e84d3 docs(www): add Fledge Alpha Free to Console models (#52896) 2026-10-02 21:59:24 -07:00
Aiden Cline 3e1aa1e58c fix(server): return 404 when a location folder is missing (#52668) 2026-10-02 23:43:56 -05:00
Aiden Cline 7ced9326e6 fix(ai): preserve Mistral and Cohere system parts (#52890) 2026-10-02 23:36:36 -05:00
Aiden Cline d1ff6f90cf fix(ai): preserve Gemini system text parts (#52888) 2026-10-02 23:04:49 -05:00
James Long d9d094a543 fix(tui): keep question form highlights on the raised surface (#52872) 2026-10-02 20:34:12 -04:00
Kit Langton d113a40f55 fix(core): rename legacy provider in top-level model (#51901) 2026-10-02 16:02:13 -07:00
Kit Langton 54956aac22 chore: enable noUnusedLocals in ai and core (#52858) 2026-10-02 22:45:27 +00:00
Kit Langton c1536734ce chore(cli): enable noUnusedLocals (#52857) 2026-10-02 22:45:05 +00:00
Kit Langton cf7fcfad0a chore(app): enable noUnusedLocals (#52856) 2026-10-02 22:44:02 +00:00
Kit Langton 17955a1100 refactor(core): remove duplicate v1 config migration (#51889) 2026-10-02 15:40:41 -07:00
Kit Langton c0c9c69a27 chore(tui): enable noUnusedLocals (#52851) 2026-10-02 22:36:03 +00:00
Kit Langton eb1a9ea4d9 chore: enable noUnusedLocals in schema, server, sdk and smaller packages (#52850) 2026-10-02 15:23:59 -07:00
Kit Langton 680bca3183 chore: enable noUnusedLocals in already-clean packages (#52849) 2026-10-02 15:23:50 -07:00
Kit Langton 22f81eed0b test(tui): drop title shimmer animation timing tests (#52848) 2026-10-02 15:23:31 -07:00
Aiden Cline 421a04f5fd fix(core): retry transient MCP connect failures (#52614) 2026-10-02 17:22:25 -05:00
Jérôme BenoitandTest User ec541abbcd chore(nix): run the nix eval workflow on v2 (#52143)
Co-authored-by: Test User <test@test.com>
2026-10-02 16:52:46 -05:00
Kit Langton 4c63a35dbe refactor(schema): drop unused FileAttachment re-export from SessionEvent (#52842) 2026-10-02 21:35:12 +00:00
Kit Langton 0e4dd7bfe9 refactor(ai): remove unused declarations in OpenAI chat protocol (#52840) 2026-10-02 21:33:58 +00:00
Kit Langton e28a624b8b refactor(core): remove unused git strategy in worktree layer (#52841) 2026-10-02 21:28:27 +00:00
Kit Langton 9277761af6 refactor(schema): remove unused QuestionV1 contract (#52838) 2026-10-02 21:28:13 +00:00
Kit Langton 0bef0eab67 refactor(core): remove legacy id prefix table (#52810) 2026-10-02 18:40:26 +00:00
Shoubhit Dash 66d15a7352 refactor(acp): split module seams and drop dead code (#52803) 2026-10-03 00:04:06 +05:30
Kit Langton 9f8551ab6b refactor(core): require job ids from their subject (#52806) 2026-10-02 18:27:13 +00:00
Kit Langton 8bcda4c718 refactor(core): name tool output files in ToolOutput (#52808) 2026-10-02 18:24:57 +00:00
Kit Langton ccd2aca07a test(core): match Code Mode description after allSettled change (#52812) 2026-10-02 18:14:27 +00:00
1391c0d52c docs(core): recommend settled results for independent calls (#52798)
Co-authored-by: rekram1-node <rekram1-node@users.noreply.github.com>
Co-authored-by: Aiden Cline <63023139+rekram1-node@users.noreply.github.com>
2026-10-02 12:26:05 -05:00
Shoubhit Dash ec90ad50d3 fix(acp): settle permissions replied elsewhere and type request failures (#52774) 2026-10-02 22:43:32 +05:30
Shoubhit Dash 2a01ed60b1 perf(core): keep unchanged messages in request shaping (#52784) 2026-10-02 22:12:21 +05:30
Shoubhit Dash 80caae8ad1 test(acp): keep only spec and essential tests (#52775) 2026-10-02 22:01:49 +05:30
Jack 35a41b5d53 docs(www): add Ling 3.1 Flash Free to Console models (#52780) 2026-10-03 00:08:55 +08:00
Aiden Cline d49ec44298 feat(ai): add native Cohere chat provider (#52633) 2026-10-02 11:07:02 -05:00
Shoubhit Dash 7440ff7844 chore(acp): trim comments (#52770) 2026-10-02 20:50:09 +05:30
Shoubhit Dash f902a0fae7 fix(cli): support Homebrew Core upgrades (#52753) 2026-10-02 20:27:14 +05:30
Filip 661853903b fix(tui): gate terminals on server persistent PTY support (#52760) 2026-10-02 16:49:15 +02:00
Shoubhit Dash 06b6c916a5 refactor(acp): drop the promise client (#52751) 2026-10-02 19:52:02 +05:30
Shoubhit Dash bf25bd2ec7 docs(acp): document opencode protocol extensions (#52745) 2026-10-02 19:50:17 +05:30
Filip 3ddb0cb1d3 docs: remove skill slash frontmatter from v2 docs (#52752) 2026-10-02 15:09:38 +02:00
Filip f3a23e52b3 feat(core): support disable-model-invocation in skill frontmatter (#52747) 2026-10-02 15:07:30 +02:00
opencode-agent[bot] dbe08d2ac3 chore(core): refresh bundled models.dev snapshot 2026-10-02 12:22:07 +00:00
Shoubhit Dash 77eceb8c85 fix(core): merge formatter config across files (#52739) 2026-10-02 17:49:12 +05:30
Shoubhit Dash e2a700dc90 fix(acp): let the model continue when a question can't be shown (#52740) 2026-10-02 17:39:54 +05:30
Shoubhit Dash ebad4bc84c feat(acp): report compaction with standard session updates (#52737) 2026-10-02 17:39:24 +05:30
opencode-agent[bot] d82b75f090 chore: update nix node_modules hashes 2026-10-02 11:32:57 +00:00
Shoubhit Dash 134d0ede4d fix(acp): align permission requests with the tool call spec (#52565) 2026-10-02 16:51:36 +05:30
Shoubhit Dash 4a2c024ea7 fix(acp): detach new and resumed sessions when setup fails (#52558) 2026-10-02 16:07:33 +05:30
Shoubhit Dash 4cb56a829e fix(acp): send remote image links as references (#52557) 2026-10-02 16:06:58 +05:30
opencode-agent[bot]andBrendonovich 41516c78c8 fix(app): restore Git initialization for non-Git projects (#51455)
Co-authored-by: Brendonovich <14191578+Brendonovich@users.noreply.github.com>
2026-10-02 06:13:19 +00:00
1055 changed files with 39053 additions and 17145 deletions

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+11
View File
@@ -18,9 +18,20 @@ jobs:
steps:
- name: Checkout repository
uses: actions/checkout@34e114876b0b11c390a56381ad16ebd13914f8d5 # v4.3.1
with:
# A pull request checks out its merge into the current base; the first parent is that base.
fetch-depth: 2
- name: Setup Bun
uses: ./.github/actions/setup-bun
- name: Run checks
run: bun run check
# Every GUI package file (app, desktop, gui-extensions, ui, session-ui) a pull request adds or edits must be free of
# oxlint problems, warn-level rules (anti-slop) included. Other packages are not affected.
- name: Lint changed files
if: github.event_name == 'pull_request'
# Against the merge's first parent, so base-branch commits the pull request has not merged are not counted as its
# changes (the event's base SHA can predate them).
run: bun run lint:changed HEAD^1
+2 -2
View File
@@ -2,9 +2,9 @@ name: nix-eval
on:
push:
branches: [dev]
branches: [dev, v2]
pull_request:
branches: [dev]
branches: [dev, v2]
workflow_dispatch:
concurrency:
+9
View File
@@ -252,6 +252,13 @@ jobs:
CI: true
timeout-minutes: 15
- name: Run app component tests
if: ${{ !cancelled() && env.E2E_ENABLED == 'true' }}
run: bun --cwd packages/app test:components
env:
CI: true
timeout-minutes: 15
- name: Upload Playwright artifacts
if: always() && env.E2E_ENABLED == 'true'
uses: actions/upload-artifact@ea165f8d65b6e75b540449e92b4886f43607fa02 # v4.6.2
@@ -264,3 +271,5 @@ jobs:
packages/app/e2e/playwright-report
packages/session-ui/component-tests/test-results
packages/session-ui/component-tests/playwright-report
packages/app/component-tests/test-results
packages/app/component-tests/playwright-report
+52
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@@ -63,8 +63,60 @@
"anti-slop-effect/prefer-effect-match": "warn"
}
},
{
"files": ["packages/gui-extensions/src/*.ts", "packages/gui-extensions/src/*.tsx"],
"rules": {
"no-restricted-imports": [
"error",
{
"paths": [
{
"name": "solid-js",
"importNames": ["createEffect", "createRenderEffect", "createComputed"],
"message": "Extension code runs side effects through the SDK: createKeyed(source, fn, { otherwise }) per provider generation or value, createMemo or a plain function for derived values, createLatest for async data, createVisitState for per-visit state, and the handler for logic a user action causes. An escape hatch needs an oxlint-disable comment with a reason."
}
]
}
]
}
},
{
"files": ["packages/gui-extensions/src/*/**"],
"rules": {
"no-restricted-imports": [
"error",
{
"paths": [
{
"name": "solid-js",
"importNames": ["createEffect", "createRenderEffect", "createComputed"],
"message": "Extension code runs side effects through the SDK: createKeyed(source, fn, { otherwise }) per provider generation or value, createMemo or a plain function for derived values, createLatest for async data, createVisitState for per-visit state, and the handler for logic a user action causes. An escape hatch needs an oxlint-disable comment with a reason."
}
],
"patterns": [
{
"regex": "^@opencode/(app|desktop)(/|$)",
"message": "GUI extensions never import the app or desktop packages. Use the SDK."
},
{
"regex": "^@/",
"message": "GUI extensions never import app internals. Use the SDK."
},
{
"group": ["../*/*", "!../*/contract", "!../sdk/*"],
"message": "Import another extension only through its contract.ts."
},
{
"regex": "\\.css$",
"message": "Import CSS with ?inline and contribute it with ctx.add(Style, css)."
}
]
}
]
}
},
{
"files": ["packages/gui-extensions/src/sdk/**"],
"rules": {
"no-restricted-imports": [
"error",
+12 -11
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@@ -122,7 +122,7 @@
"@clack/core": "1.0.0-alpha.1",
"@clack/prompts": "1.0.0-alpha.1",
"@effect/platform-node": "catalog:",
"@opencode-ai/pty": "0.1.13",
"@opencode-ai/pty": "0.2.0",
"@opencode/client": "workspace:*",
"@opencode/plugin": "workspace:*",
"@opencode/schema": "workspace:*",
@@ -133,6 +133,7 @@
"@opentui/solid": "catalog:",
"@parcel/watcher": "2.5.1",
"@silvia-odwyer/photon-node": "0.3.4",
"diff": "catalog:",
"effect": "catalog:",
"immer": "11.1.4",
"jsonc-parser": "3.3.1",
@@ -354,7 +355,7 @@
"@lydell/node-pty": "catalog:",
"@modelcontextprotocol/client": "2.0.0",
"@modelcontextprotocol/core": "2.0.0",
"@opencode-ai/pty": "0.1.13",
"@opencode-ai/pty": "0.2.0",
"@opencode/ai": "workspace:*",
"@opencode/codemode": "workspace:*",
"@opencode/plugin": "workspace:*",
@@ -364,7 +365,7 @@
"@parcel/watcher": "2.5.1",
"@silvia-odwyer/photon-node": "0.3.4",
"@standard-schema/spec": "catalog:",
"bun-pty": "0.4.8",
"bun-pty": "0.4.9",
"diff": "catalog:",
"drizzle-orm": "catalog:",
"effect": "catalog:",
@@ -2166,19 +2167,19 @@
"@opencode-ai/protocol": ["@opencode-ai/protocol@0.0.0-beta-18050", "", { "dependencies": { "@opencode-ai/schema": "0.0.0-beta-18050", "effect": "4.0.0-rc.111" } }, "sha512-HDQMnvGp8IU0MdBRbEuydX1WQm09BZ4HJm9iSMQwzweJuQ2HNscgzHJPIH6P02BsbbtfJ8J7sZGPItrz1tWSgw=="],
"@opencode-ai/pty": ["@opencode-ai/pty@0.1.13", "", { "optionalDependencies": { "@opencode-ai/pty-darwin-arm64": "0.1.13", "@opencode-ai/pty-darwin-x64": "0.1.13", "@opencode-ai/pty-linux-arm64-gnu": "0.1.13", "@opencode-ai/pty-linux-arm64-musl": "0.1.13", "@opencode-ai/pty-linux-x64-gnu": "0.1.13", "@opencode-ai/pty-linux-x64-musl": "0.1.13" }, "bin": { "opencode-pty": "bin/opencode-pty.js" } }, "sha512-WPCN8h8HaZhhUcrMG0zu+4D9vco0EZiEg/gCF1K3JPRN6UsHMiXq1HVIy5IlyfcoyjfViRmQmXYE4AuU3laBjA=="],
"@opencode-ai/pty": ["@opencode-ai/pty@0.2.0", "", { "optionalDependencies": { "@opencode-ai/pty-darwin-arm64": "0.2.0", "@opencode-ai/pty-darwin-x64": "0.2.0", "@opencode-ai/pty-linux-arm64-gnu": "0.2.0", "@opencode-ai/pty-linux-arm64-musl": "0.2.0", "@opencode-ai/pty-linux-x64-gnu": "0.2.0", "@opencode-ai/pty-linux-x64-musl": "0.2.0" }, "bin": { "opencode-pty": "bin/opencode-pty.js" } }, "sha512-pV86urAwinpwFXX8AJlOf8S9CVJhGsV+11I/J6TcxMW0c7u6LgeODzdj/BVBC6jUhsG2aKDxg8rACMcDCy3HiA=="],
"@opencode-ai/pty-darwin-arm64": ["@opencode-ai/pty-darwin-arm64@0.1.13", "", { "os": "darwin", "cpu": "arm64" }, "sha512-fVtQZqVLBuJx/aB+5ojfmQifS1KMc9gxlxpFQ6bxEFU8tn8xHQTiFPaNroZgOtaw7I4ceGyx/eXieK1wp68yAA=="],
"@opencode-ai/pty-darwin-arm64": ["@opencode-ai/pty-darwin-arm64@0.2.0", "", { "os": "darwin", "cpu": "arm64" }, "sha512-2y6xrktb2J7rRk+mzAJHA8cCbWhC4Lo2zJ66t9ad59qFhL5nzAPfpEOwnyvvFqhxebHNvL08Mp64M9IHnM0aiA=="],
"@opencode-ai/pty-darwin-x64": ["@opencode-ai/pty-darwin-x64@0.1.13", "", { "os": "darwin", "cpu": "x64" }, "sha512-b/tAEm0hCMXraPM9cxR8Rg7X1UBZInRTaxWAS4Ht9eH1nWj1rANOLvHWiWX/vVh5TB0Ubg8bWPu4B0nZkEHROQ=="],
"@opencode-ai/pty-darwin-x64": ["@opencode-ai/pty-darwin-x64@0.2.0", "", { "os": "darwin", "cpu": "x64" }, "sha512-XVQwK9+KgVGYunCYPCCBf1Or0z6zSkzjgfdJd7dEe/LOFg5vmMkOfSB9dCXnoRCWGviWYk7xd07iFIFOgyj5Ig=="],
"@opencode-ai/pty-linux-arm64-gnu": ["@opencode-ai/pty-linux-arm64-gnu@0.1.13", "", { "os": "linux", "cpu": "arm64" }, "sha512-I124aSYBBjpGZnYExHfIajkvVK1FiK+//OJBGdqqFp5pas2Oruq4O8tv+pMoxomZIYh2ce/QhOOYLHRwXsthTg=="],
"@opencode-ai/pty-linux-arm64-gnu": ["@opencode-ai/pty-linux-arm64-gnu@0.2.0", "", { "os": "linux", "cpu": "arm64" }, "sha512-TPVGCQk5E65IY3ipcpd17rwKehdvXcXEYRhhGzok/6Dske69ei2S+ERz7NXZ8cKFAvbiiT771HHM+XyVYAl+7A=="],
"@opencode-ai/pty-linux-arm64-musl": ["@opencode-ai/pty-linux-arm64-musl@0.1.13", "", { "os": "linux", "cpu": "arm64" }, "sha512-feWsfKpaDytGJzutoK43GqQwVghG2vHZt6BE/ydPZNuqIrySQ/6JfliUAMwn5BWs/Ky7ouSwKHCyAVeukusSvg=="],
"@opencode-ai/pty-linux-arm64-musl": ["@opencode-ai/pty-linux-arm64-musl@0.2.0", "", { "os": "linux", "cpu": "arm64" }, "sha512-iH6/liY7xN1OXVD9eGzdH11BVGvnpPsH5Z1Unz0Pn9EzkPFf28oDNKNyeXV0xIAP53oiYp8gpRq2PADNwbVsTg=="],
"@opencode-ai/pty-linux-x64-gnu": ["@opencode-ai/pty-linux-x64-gnu@0.1.13", "", { "os": "linux", "cpu": "x64" }, "sha512-jliNgsevGuxfIeX7eyzjHhrJkF8uEUPnDLbF2v16uv69FhEHrraf7jyWkxazMP6rNvn2CGtwMMc4BXPS5pzjhg=="],
"@opencode-ai/pty-linux-x64-gnu": ["@opencode-ai/pty-linux-x64-gnu@0.2.0", "", { "os": "linux", "cpu": "x64" }, "sha512-GhdrmbUzxGHRfWvt1qutgVD4HLb7aSBsgWGjFsc6k8HjO5ZbdaC3ScRyd512YAAG5KAROLKZ6+0SEBsm5xFYlA=="],
"@opencode-ai/pty-linux-x64-musl": ["@opencode-ai/pty-linux-x64-musl@0.1.13", "", { "os": "linux", "cpu": "x64" }, "sha512-rXDpidW66gz2b2M/NbUN8ZKmAxaJcASnuHATeXevlrFdiPUv8uJwvkRd6Pla1fp01Q65MkBmgRa7Q9c+H1PlzA=="],
"@opencode-ai/pty-linux-x64-musl": ["@opencode-ai/pty-linux-x64-musl@0.2.0", "", { "os": "linux", "cpu": "x64" }, "sha512-EbHchDsMmL5aOReIoo8NvQkKnyhyKmoL2RleF2JYF76va3FKuksmwsOBgQJh54i+QA4Fd0+9x54Q+2fJOzPiRQ=="],
"@opencode-ai/schema": ["@opencode-ai/schema@0.0.0-beta-18050", "", { "dependencies": { "@standard-schema/spec": "1.1.0", "effect": "4.0.0-rc.111" } }, "sha512-/D6VXaWlytTXR3IOiMLIKuPcfp7FQNUzRPm9z3K7UBFd1Bw4q/WZksaf5RVcBGz+0YRxYMc1V4D7MFlceSgtyg=="],
@@ -3548,7 +3549,7 @@
"bun-ffi-structs": ["bun-ffi-structs@0.3.1", "", { "peerDependencies": { "typescript": "^5" } }, "sha512-3gM7PpVWLyrwxWjcilSiGuhWanhZivvo6l0u573NziPH6f/gwk6McbaYgn7oJWov6pKGRTDbrg94W5DcJsKTtQ=="],
"bun-pty": ["bun-pty@0.4.8", "", {}, "sha512-rO70Mrbr13+jxHHHu2YBkk2pNqrJE5cJn29WE++PUr+GFA0hq/VgtQPZANJ8dJo6d7XImvBk37Innt8GM7O28w=="],
"bun-pty": ["bun-pty@0.4.9", "", {}, "sha512-IUF/B3FANo8vIQ775Zt7Er7lphMpYMhLkes45am2WE8FaVI7KRYtj1rQwliZ18b6GpNzBNWcl7sz9QT5wDFBeQ=="],
"bun-types": ["bun-types@1.4.2", "", { "dependencies": { "@types/node": "*" } }, "sha512-bxV1FgK7yBIzjRe5zBozIM4Bem11ZJcCXSrjWRG3YWLt8yFDePu4cLjpebO8OvPeIE9trbyPF4fuj3Cia4Fj3w=="],
+2
View File
@@ -40,6 +40,8 @@ stdenv.mkDerivation (finalAttrs: {
copyDesktopItems
]
++ lib.optionals stdenv.hostPlatform.isDarwin [
darwin.cctools
darwin.sigtool
# Ad-hoc sign the .app: --config.mac.identity=null below skips signing.
darwin.autoSignDarwinBinariesHook
];
+3 -3
View File
@@ -1,7 +1,7 @@
{
"nodeModules": {
"x86_64-linux": "sha256-g3k0cAFGqzmRYlcIkg1NDvlx1WxHYhnYPL0/a8E+qTg=",
"aarch64-linux": "sha256-a+3ymqdxOONGe2Tpq4GUccl1b+Dwzxlb9LFXgE1gZ+0=",
"aarch64-darwin": "sha256-h8xIzuMmaWfJqjHCO74xUDCWNKQLFrIGoKYZ+2TauYc="
"x86_64-linux": "sha256-2RlbJRTEKSliuUbAE2lAktX63JFR/RKAuLkcCou8wb4=",
"aarch64-linux": "sha256-P7DAE018lTJNGmttg87U9oaTAuw/wHlnMStdnXYKCr0=",
"aarch64-darwin": "sha256-N+NfV1ObOTnW+ez7As+CS+6ci/iRGCQ6cslvyQFCp6E="
}
}
+2 -1
View File
@@ -18,7 +18,8 @@
"dev:www": "bun run --cwd services/www dev",
"dev:storybook": "bun --cwd packages/storybook storybook",
"bench:devex": "bun run --cwd packages/app test:bench:devex",
"lint": "oxlint && ast-grep scan -c script/ast-grep/gui-extensions/sgconfig.yml",
"lint": "oxlint && ast-grep scan -c script/ast-grep/gui-extensions/sgconfig.yml && bun script/sdk-docs.ts",
"lint:changed": "bun script/lint-changed.ts",
"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-simplifications": "ast-grep scan -c script/ast-grep/effect-simplifications/sgconfig.yml --off=unused-suppression packages",
"test:lint-rules": "ast-grep test -c script/ast-grep/sgconfig.yml",
+26 -1
View File
@@ -27,6 +27,31 @@ Run `LLM.stream(...)` instead of `generate` when you want incremental `LLMEvent`
`LLM.request(...)`. The event stream is provider-neutral — same shape across OpenAI Chat, OpenAI Responses,
Anthropic Messages, Gemini, Bedrock Converse, and any OpenAI-compatible deployment.
### Google Interactions
`Google.configure({ apiKey }).interactions(modelID)` selects the Interactions API; `.model(modelID)` still selects
GenerateContent. The package entrypoint is `@opencode/ai/providers/google/interactions`.
```ts
const model = Google.configure({ apiKey }).interactions("gemini-3.8-flash")
const response = yield* LLM.generate({
model,
prompt: "Say hello.",
providerOptions: { thinkingLevel: "low", thinkingSummaries: "auto", store: true },
})
```
Interactions supports text output, streamed function calls, native tool results, thought signatures, and multimodal
input. Full-history replay is the default (`store: false`); implicit caching works without retained interactions.
For server-side continuation, set `store: true` on the predecessor, read `interactionId` from the final event's
`providerMetadata.google`, and pass `previousInteractionId` on the next request with **only new messages**. Repeat
the system instructions and tool declarations on each request. Set `store: true` on each response you intend to
continue from. The package does not automatically select or persist continuation IDs.
Raw usage is preserved in `usage.providerMetadata.google`. `inputTokens` follows Google's top-level accounting;
`contextTokens` uses its full `raw_prompt_token` count when supplied. These can differ substantially with server-side
continuation. Explicit caches, hosted tools, and generated media are not supported by this initial protocol.
The same configured facade names image, video, speech, and transcription models. `Image.generate` resolves the
provider's image route from the model and returns `Media.Asset`s with lazily decoded bytes:
@@ -1223,7 +1248,7 @@ const gateway = CloudflareAIGateway.configure({
}).model("workers-ai/@cf/meta/llama-3.1-8b-instruct")
```
Included LLM providers: OpenAI, Anthropic, Google (Gemini), Google Vertex, Amazon Bedrock, Azure OpenAI, Baseten, Cerebras, Cloudflare AI Gateway, Cloudflare Workers AI, DeepInfra, DeepSeek, Fireworks, Groq, Mistral, OpenRouter, TogetherAI, and xAI. Z.ai currently exposes image generation. Generic Chat Completions, Responses, and Anthropic Messages-compatible entrypoints support custom endpoints.
Included LLM providers: OpenAI, Anthropic, Google (Gemini), Google Vertex, Amazon Bedrock, Azure OpenAI, Baseten, Cerebras, Cohere, Cloudflare AI Gateway, Cloudflare Workers AI, DeepInfra, DeepSeek, Fireworks, Groq, Mistral, OpenRouter, TogetherAI, and xAI. Z.ai currently exposes image generation. Generic Chat Completions, Responses, and Anthropic Messages-compatible entrypoints support custom endpoints.
Each named provider owns its module, endpoint, authentication, and route setup. Providers with the same wire format compose the shared protocol directly:
+1
View File
@@ -42,6 +42,7 @@ const RESPECTS_INLINE_HINTS = new Set([
"alibaba-messages",
"anthropic-messages",
"anthropic-compatible-messages",
"bedrock-mantle-messages",
"cloudflare-ai-gateway-messages",
"google-vertex-messages",
"meta-messages",
@@ -1,7 +1,7 @@
import { Effect, Schema } from "effect"
import { Protocol } from "../route/protocol.js"
import { OpenResponses } from "./open-responses.js"
import { JsonObject, optionalArray, ProviderShared } from "./shared.js"
import { JsonObject, ProviderShared } from "./shared.js"
import { OpenResponsesOptions } from "./utils/open-responses-options.js"
import { ResponsesHostedTools } from "./utils/responses-hosted-tools.js"
@@ -25,8 +25,6 @@ const WebExtractorItem = Schema.StructWithRest(
)
const Body = Schema.Struct({
...OpenResponses.coreFields,
input: Schema.Array(Schema.Union([OpenResponses.InputItem, WebExtractorItem])),
tools: optionalArray(Schema.Union([OpenResponses.Tool, NativeTool])),
enable_thinking: Options.fields.enableThinking,
previous_response_id: Options.fields.previousResponseId,
conversation: Options.fields.conversation,
@@ -52,7 +50,7 @@ export const protocol = Protocol.make({
const opts = yield* ProviderShared.validateWith(Schema.decodeUnknownEffect(Options))(req.providerOptions ?? {})
const body = yield* OpenResponses.fromRequestWithAdapter(req, adapter)
const choice = body.tool_choice
return yield* ProviderShared.validateWith(Schema.decodeUnknownEffect(Body))({
return {
...body,
enable_thinking: opts.enableThinking,
previous_response_id: opts.previousResponseId,
@@ -62,7 +60,7 @@ export const protocol = Protocol.make({
typeof choice === "object" && choice.type === "function"
? { type: "allowed_tools" as const, mode: "required" as const, tools: [choice] }
: choice,
})
}
}),
},
stream: {
@@ -584,7 +584,7 @@ const serverToolResultType = (name: string): AnthropicServerToolResultType | und
return undefined
}
const lowerServerToolResult = Effect.fn("AnthropicMessages.lowerServerToolResult")(function* (
const lowerServerToolResult = Effect.fnUntraced(function* (
part: ToolResultPart,
providerMetadataKey: string,
) {
@@ -657,7 +657,7 @@ const citationsFromMetadata = (metadata: MediaPart["metadata"]): AnthropicDocume
const isHttpUrl = (value: string) => /^https?:\/\//i.test(value.trim())
const lowerMedia = Effect.fn("AnthropicMessages.lowerMedia")(function* (
const lowerMedia = Effect.fnUntraced(function* (
part: MediaPart,
breakpoints?: Cache.Breakpoints,
) {
@@ -847,7 +847,7 @@ const splitsLocalToolResults = (messages: LLMRequest["messages"], index: number)
return pending.size > 0
}
const lowerNativeSystemUpdate = Effect.fn("AnthropicMessages.lowerNativeSystemUpdate")(function* (
const lowerNativeSystemUpdate = Effect.fnUntraced(function* (
message: LLMRequest["messages"][number],
breakpoints: Cache.Breakpoints,
) {
@@ -862,7 +862,7 @@ const lowerNativeSystemUpdate = Effect.fn("AnthropicMessages.lowerNativeSystemUp
}
})
const lowerMessages = Effect.fn("AnthropicMessages.lowerMessages")(function* (
const lowerMessages = Effect.fnUntraced(function* (
request: LLMRequest,
breakpoints: Cache.Breakpoints,
) {
@@ -989,6 +989,9 @@ const lowerMessages = Effect.fn("AnthropicMessages.lowerMessages")(function* (
return messages
})
// TODO: Move per-model capability heuristics (`supportsEffortUpdates`, `supportsNativeSystemUpdates`,
// `supportsThinkingBlockBinding`) into explicit model/provider `compatibility` metadata so the protocol
// only reads `request.model.compatibility`.
// Per-turn effort started with Claude Opus 5 and every Claude 5.1 model; later versions of any family inherit it.
const supportsEffortUpdates = (model: LLMRequest["model"]) => {
const override = model.compatibility?.supportsEffortUpdates
@@ -1300,7 +1303,7 @@ const onContentBlockStart = (
return [{ ...state, lifecycle: Lifecycle.stepStart(state.lifecycle, events) }, [...events, result]]
}
const onContentBlockDelta = Effect.fn("AnthropicMessages.onContentBlockDelta")(function* (
const onContentBlockDelta = Effect.fnUntraced(function* (
state: ParserState,
event: AnthropicEvent & { readonly delta: AnthropicStreamDelta },
) {
@@ -1368,7 +1371,7 @@ const onContentBlockDelta = Effect.fn("AnthropicMessages.onContentBlockDelta")(f
return [state, NO_EVENTS] satisfies StepResult
})
const onContentBlockStop = Effect.fn("AnthropicMessages.onContentBlockStop")(function* (
const onContentBlockStop = Effect.fnUntraced(function* (
state: ParserState,
event: AnthropicEvent,
) {
@@ -1439,7 +1442,7 @@ const onMessageDelta = (
]
}
const onMessageStop = Effect.fn("AnthropicMessages.onMessageStop")(function* (state: ParserState) {
const onMessageStop = Effect.fnUntraced(function* (state: ParserState) {
if (Object.keys(state.compactions).length)
return yield* ProviderShared.eventError(ADAPTER, "Response ended with an incomplete compaction block")
const result = yield* ToolStream.finishAll(ADAPTER, state.tools)
@@ -285,7 +285,7 @@ const lowerToolCall = (part: ToolCallPart, normalizeID: (id: string) => string):
},
})
const lowerToolResultContent = Effect.fn("BedrockConverse.lowerToolResultContent")(function* (
const lowerToolResultContent = Effect.fnUntraced(function* (
part: ToolResultPart,
documentNames: Set<string>,
) {
@@ -305,7 +305,7 @@ const lowerToolResultContent = Effect.fn("BedrockConverse.lowerToolResultContent
return content
})
const lowerToolResult = Effect.fn("BedrockConverse.lowerToolResult")(function* (
const lowerToolResult = Effect.fnUntraced(function* (
part: ToolResultPart,
documentNames: Set<string>,
normalizeID: (id: string) => string,
@@ -322,7 +322,7 @@ const lowerToolResult = Effect.fn("BedrockConverse.lowerToolResult")(function* (
// Keep Claude and Nova tool-result images inline; put other models' images beside the result.
const keepToolImagesInline = (id: string) => id.includes("anthropic.claude-") || id.includes("amazon.nova-")
const lowerMessages = Effect.fn("BedrockConverse.lowerMessages")(function* (
const lowerMessages = Effect.fnUntraced(function* (
request: LLMRequest,
breakpoints: BedrockCache.Breakpoints,
) {
+3 -3
View File
@@ -75,7 +75,7 @@ const usesSse = (request: MediaProtocol.Addressed<Request>) => request.mode ===
const CONTAINERS: Readonly<Record<string, "raw" | "wav" | "mp3">> = { pcm: "raw", wav: "wav", mp3: "mp3" }
const outputFormat = Effect.fn("CartesiaSpeech.outputFormat")(function* (request: MediaProtocol.Addressed<Request>) {
const outputFormat = Effect.fnUntraced(function* (request: MediaProtocol.Addressed<Request>) {
const sse = usesSse(request)
const format = request.format ?? (sse ? "pcm" : "mp3")
const container = CONTAINERS[format]
@@ -121,7 +121,7 @@ const fromRequest = Effect.fn("CartesiaSpeech.fromRequest")(function* (request:
// 6. Stream parsing
// ---------------------------------------------------------------------------
const onEvent = Effect.fn("CartesiaSpeech.onEvent")(function* (state: State, frame: string) {
const onEvent = Effect.fnUntraced(function* (state: State, frame: string) {
const event = yield* decodeEvent(frame)
if (event.type === "chunk" && event.data !== undefined) return SpeechStream.delta(state, event.data)
if (event.type === "timestamps" && event.word_timestamps !== undefined) {
@@ -140,7 +140,7 @@ const onEvent = Effect.fn("CartesiaSpeech.onEvent")(function* (state: State, fra
return [state, []] as const
})
const finish = Effect.fn("CartesiaSpeech.finish")(function* (
const finish = Effect.fnUntraced(function* (
state: State,
context: MediaProtocol.ResponseContext<Request>,
) {
+334
View File
@@ -0,0 +1,334 @@
import { Effect, Schema } from "effect"
import { Route } from "../route/client.js"
import { Endpoint } from "../route/endpoint.js"
import { Framing } from "../route/framing.js"
import { Protocol } from "../route/protocol.js"
import { LLMEvent, Usage, type FinishReasonDetails, type LLMRequest } from "../schema/index.js"
import { ProviderShared } from "./shared.js"
import { Lifecycle } from "./utils/lifecycle.js"
import { ToolStream } from "./utils/tool-stream.js"
const ADAPTER = "cohere-chat"
export const DEFAULT_BASE_URL = "https://api.cohere.com/v2"
const Options = Schema.Struct({
thinking: Schema.optional(
Schema.Struct({
type: Schema.optional(Schema.Literals(["enabled", "disabled"])),
tokenBudget: Schema.optional(Schema.Int.check(Schema.isGreaterThan(0))),
}),
),
})
export type ProviderOptionsInput = Schema.Schema.Type<typeof Options>
const Content = Schema.Union([
Schema.Struct({ type: Schema.Literal("text"), text: Schema.String }),
Schema.Struct({ type: Schema.Literal("thinking"), thinking: Schema.String }),
Schema.Struct({ type: Schema.Literal("image_url"), image_url: Schema.Struct({ url: Schema.String }) }),
])
const ToolCall = Schema.Struct({
id: Schema.String,
type: Schema.Literal("function"),
function: Schema.Struct({ name: Schema.String, arguments: Schema.String }),
})
const Message = Schema.Struct({
role: Schema.Literals(["system", "user", "assistant", "tool"]),
content: Schema.optional(Schema.Union([Schema.String, Schema.Array(Content)])),
tool_calls: Schema.optional(Schema.Array(ToolCall)),
tool_call_id: Schema.optional(Schema.String),
tool_plan: Schema.optional(Schema.String),
})
const Body = Schema.Struct({
model: Schema.String,
messages: Schema.Array(Message),
stream: Schema.Literal(true),
tools: Schema.optional(
Schema.Array(
Schema.Struct({
type: Schema.Literal("function"),
function: Schema.Struct({
name: Schema.String,
description: Schema.optional(Schema.String),
parameters: Schema.Unknown,
}),
}),
),
),
tool_choice: Schema.optional(Schema.Literals(["NONE", "REQUIRED"])),
thinking: Schema.optional(Schema.Struct({ type: Schema.String, token_budget: Schema.optional(Schema.Number) })),
max_tokens: Schema.optional(Schema.Number),
temperature: Schema.optional(Schema.Number),
p: Schema.optional(Schema.Number),
k: Schema.optional(Schema.Number),
seed: Schema.optional(Schema.Number),
stop_sequences: Schema.optional(Schema.Array(Schema.String)),
frequency_penalty: Schema.optional(Schema.Number),
presence_penalty: Schema.optional(Schema.Number),
})
const TokenCounts = Schema.Struct({
input_tokens: Schema.optional(Schema.Number),
output_tokens: Schema.optional(Schema.Number),
reasoning_tokens: Schema.optional(Schema.Number),
})
const NativeUsage = Schema.Struct({
tokens: Schema.optional(TokenCounts),
billed_units: Schema.optional(TokenCounts),
cached_tokens: Schema.optional(Schema.Number),
})
const Event = Schema.Union([
Schema.Struct({ type: Schema.Literal("message-start") }),
Schema.Struct({
type: Schema.Literals(["content-start", "content-delta"]),
index: Schema.Number,
delta: Schema.Struct({
message: Schema.Struct({
content: Schema.Struct({ text: Schema.optional(Schema.String), thinking: Schema.optional(Schema.String) }),
}),
}),
}),
Schema.Struct({ type: Schema.Literal("content-end"), index: Schema.Number }),
Schema.Struct({
type: Schema.Literal("tool-plan-delta"),
delta: Schema.Struct({ message: Schema.Struct({ tool_plan: Schema.String }) }),
}),
Schema.Struct({
type: Schema.Literals(["tool-call-start", "tool-call-delta"]),
index: Schema.Number,
delta: Schema.Struct({
message: Schema.Struct({
tool_calls: Schema.Struct({
id: Schema.optional(Schema.String),
function: Schema.Struct({ name: Schema.optional(Schema.String), arguments: Schema.optional(Schema.String) }),
}),
}),
}),
}),
Schema.Struct({ type: Schema.Literal("tool-call-end"), index: Schema.Number }),
Schema.Struct({
type: Schema.Literal("message-end"),
delta: Schema.Struct({ finish_reason: Schema.String, usage: Schema.optional(NativeUsage) }),
}),
// Citation output is outside this basic chat surface.
Schema.Struct({ type: Schema.Literals(["citation-start", "citation-end"]) }),
])
type Event = typeof Event.Type
type State = {
readonly lifecycle: Lifecycle.State
readonly tools: ToolStream.State<number>
readonly finished: boolean
}
const TOOL_CHOICE = { auto: undefined, none: "NONE", required: "REQUIRED", tool: "REQUIRED" } as const
const fromRequest = Effect.fn("CohereChat.fromRequest")(function* (request: LLMRequest) {
const options = yield* ProviderShared.validateWith(Schema.decodeUnknownEffect(Options))(request.providerOptions ?? {})
const flattened = ProviderShared.flattenToolRequest(request)
const messages: (typeof Message.Type)[] = request.system.length
? [
{
role: "system",
content:
request.system.length === 1
? request.system[0].text
: request.system.map((part) => ({ type: "text", text: part.text })),
},
]
: []
for (const message of flattened.request.messages) {
if (message.role === "system") {
messages.push({ role: "user", content: (yield* ProviderShared.wrappedSystemUpdate("Cohere Chat", message)).text })
continue
}
if (message.role === "tool") {
for (const part of message.content) {
if (part.type !== "tool-result")
return yield* ProviderShared.unsupportedContent("Cohere Chat", "tool", ["tool-result"])
if (part.result.type === "content" && part.result.value.some((item) => item.type === "file"))
return yield* ProviderShared.invalidRequest("Cohere Chat does not support file content in tool results")
messages.push({ role: "tool", tool_call_id: part.id, content: ProviderShared.toolResultText(part) })
}
continue
}
const content: (typeof Content.Type)[] = []
const calls: (typeof ToolCall.Type)[] = []
const plans: string[] = []
for (const part of message.content) {
if (part.type === "text") {
content.push({ type: "text", text: part.text })
continue
}
if (message.role === "assistant" && part.type === "reasoning") {
if (part.providerMetadata?.cohere?.toolPlan === true) plans.push(part.text)
else content.push({ type: "thinking", thinking: part.text })
continue
}
if (message.role === "assistant" && part.type === "tool-call") {
const args = ProviderShared.encodeJson(part.input)
calls.push({ id: part.id, type: "function", function: { name: part.name, arguments: args } })
continue
}
if (message.role === "user" && part.type === "media" && part.media.mediaType.startsWith("image/")) {
const url =
ProviderShared.mediaUrl(part.media) ??
(yield* ProviderShared.requireInlineMedia("Cohere Chat", part.media)).dataUrl
content.push({ type: "image_url", image_url: { url } })
continue
}
return yield* ProviderShared.unsupportedContent(
"Cohere Chat",
message.role,
message.role === "user" ? ["text", "media"] : ["text", "reasoning", "tool-call"],
)
}
messages.push({
role: message.role,
content: content.length ? content : undefined,
tool_calls: calls.length ? calls : undefined,
tool_plan: plans.length ? plans.join("") : undefined,
})
}
const selected = request.toolChoice?.type === "tool" ? request.toolChoice.name : undefined
const tools = selected === undefined ? flattened.tools : flattened.tools.filter((tool) => tool.name === selected)
if (selected !== undefined && tools.length === 0)
return yield* ProviderShared.invalidRequest("Cohere Chat tool choice must name an available tool")
if (tools.some((tool) => tool.native !== undefined))
return yield* ProviderShared.invalidRequest("Cohere Chat does not support provider-defined tools")
return {
model: request.model.id,
messages,
stream: true as const,
tools: tools.length
? tools.map((tool) => ({
type: "function" as const,
function: { name: tool.name, description: tool.description, parameters: tool.inputSchema },
}))
: undefined,
tool_choice: TOOL_CHOICE[request.toolChoice?.type ?? "auto"],
thinking: options.thinking && {
type: options.thinking.type ?? "enabled",
// Cohere rejects budgets above max_tokens; fitting also leaves room for the answer.
token_budget:
options.thinking.tokenBudget === undefined
? undefined
: ProviderShared.fitThinkingBudget(options.thinking.tokenBudget, request.generation?.maxTokens),
},
max_tokens: request.generation?.maxTokens,
temperature: request.generation?.temperature,
p: request.generation?.topP,
k: request.generation?.topK,
seed: request.generation?.seed,
stop_sequences: request.generation?.stop,
frequency_penalty: request.generation?.frequencyPenalty,
presence_penalty: request.generation?.presencePenalty,
}
})
const finishReason = (raw: string): FinishReasonDetails => {
switch (raw) {
case "COMPLETE":
case "STOP_SEQUENCE":
return { normalized: "stop", raw }
case "MAX_TOKENS":
return { normalized: "length", raw }
case "TOOL_CALL":
return { normalized: "tool-calls", raw }
case "ERROR":
case "TIMEOUT":
return { normalized: "error", raw }
default:
return { normalized: "unknown", raw }
}
}
const mapUsage = (usage: typeof NativeUsage.Type) =>
new Usage({
inputTokens: usage.tokens?.input_tokens,
outputTokens: usage.tokens?.output_tokens,
nonCachedInputTokens: ProviderShared.subtractTokens(usage.tokens?.input_tokens, usage.cached_tokens),
cacheReadInputTokens: usage.cached_tokens,
reasoningTokens: usage.tokens?.reasoning_tokens,
totalTokens: ProviderShared.totalTokens(usage.tokens?.input_tokens, usage.tokens?.output_tokens, undefined),
providerMetadata: { cohere: usage },
})
// Lifecycle deltas open blocks on demand and ends are no-ops for closed blocks, so content-start needs no handling.
const step = Effect.fnUntraced(function* (state: State, event: Event) {
const events: LLMEvent[] = []
switch (event.type) {
case "message-start":
return [{ ...state, lifecycle: Lifecycle.stepStart(state.lifecycle, events) }, events] as const
case "content-delta": {
const id = String(event.index)
const content = event.delta.message.content
const lifecycle =
content.thinking !== undefined
? Lifecycle.reasoningDelta(state.lifecycle, events, id, content.thinking)
: Lifecycle.textDelta(state.lifecycle, events, id, content.text ?? "")
return [{ ...state, lifecycle }, events] as const
}
case "content-end": {
const id = String(event.index)
const lifecycle = Lifecycle.textEnd(Lifecycle.reasoningEnd(state.lifecycle, events, id), events, id)
return [{ ...state, lifecycle }, events] as const
}
case "tool-plan-delta": {
const plan = event.delta.message.tool_plan
const lifecycle = Lifecycle.reasoningDelta(state.lifecycle, events, "tool-plan", plan, {
cohere: { toolPlan: true },
})
return [{ ...state, lifecycle }, events] as const
}
case "tool-call-start":
case "tool-call-delta": {
const call = event.delta.message.tool_calls
const result = ToolStream.appendOrStart(
ADAPTER,
state.tools,
event.index,
{ id: call.id, name: call.function.name, text: call.function.arguments ?? "" },
"Cohere tool call is missing id or name",
)
if (ToolStream.isError(result)) return yield* result
return [{ ...state, tools: result.tools }, result.events] as const
}
case "tool-call-end": {
const result = yield* ToolStream.finish(ADAPTER, state.tools, event.index)
return [{ ...state, tools: result.tools }, result.events ?? []] as const
}
case "message-end": {
const pending = yield* ToolStream.finishAll(ADAPTER, state.tools)
events.push(...pending.events)
const lifecycle = Lifecycle.finish(state.lifecycle, events, {
reason: finishReason(event.delta.finish_reason),
usage: event.delta.usage && mapUsage(event.delta.usage),
})
return [{ tools: pending.tools, lifecycle, finished: true }, events] as const
}
default:
return [state, events] as const
}
})
export const protocol = Protocol.make({
id: ADAPTER,
body: { schema: Body, from: fromRequest },
stream: {
event: Protocol.jsonEvent(Event),
initial: (): State => ({ lifecycle: Lifecycle.initial(), tools: ToolStream.empty(), finished: false }),
step,
terminal: (event) => event.type === "message-end",
onHalt: (state) =>
state.finished
? Effect.succeed([])
: Effect.fail(ProviderShared.eventError(ADAPTER, "Cohere stream ended without message-end")),
},
})
export const route = Route.make({
id: ADAPTER,
provider: "cohere",
providerMetadataKey: "cohere",
protocol,
endpoint: Endpoint.path("/chat", { baseURL: DEFAULT_BASE_URL }),
framing: Framing.sse,
})
export * as CohereChat from "./cohere-chat.js"
@@ -95,7 +95,7 @@ const OUTPUT_FORMATS: Readonly<Record<string, string>> = {
}
/** WAV is served only by the non-streaming endpoints. */
const outputFormat = Effect.fn("ElevenLabsSpeech.outputFormat")(function* (request: MediaProtocol.Addressed<Request>) {
const outputFormat = Effect.fnUntraced(function* (request: MediaProtocol.Addressed<Request>) {
const format = request.providerOptions?.outputFormat ?? OUTPUT_FORMATS[request.format ?? "mp3"]
if (format === undefined)
return yield* route.unsupported(
@@ -138,7 +138,7 @@ const path = (request: MediaProtocol.Addressed<Request>) =>
// 6. Stream parsing
// ---------------------------------------------------------------------------
const onRecord = Effect.fn("ElevenLabsSpeech.onRecord")(function* (state: State, frame: string) {
const onRecord = Effect.fnUntraced(function* (state: State, frame: string) {
const record = yield* decodeRecord(frame)
const [next, events] = SpeechStream.delta(state, record.audio_base64)
const alignment = record.alignment
@@ -169,7 +169,7 @@ const describeOutput = (format: string) => {
return encoding === undefined ? SpeechStream.container(codec, sampleRate) : SpeechStream.pcm(encoding, sampleRate)
}
const finish = Effect.fn("ElevenLabsSpeech.finish")(function* (
const finish = Effect.fnUntraced(function* (
state: State,
context: MediaProtocol.ResponseContext<Request>,
) {
+3 -3
View File
@@ -283,7 +283,7 @@ const lowerToolConfig = (toolChoice: NonNullable<LLMRequest["toolChoice"]>) =>
tool: (name) => ({ functionCallingConfig: { mode: "ANY" as const, allowedFunctionNames: [name] } }),
})
const lowerContentPart = Effect.fn("Gemini.lowerContentPart")(function* (part: TextPart | MediaPart) {
const lowerContentPart = Effect.fnUntraced(function* (part: TextPart | MediaPart) {
if (part.type === "text") return { text: part.text }
return yield* GeminiGenerateContent.mediaPart("Gemini", part.media)
})
@@ -302,7 +302,7 @@ const lowerToolCall = (part: ToolCallPart, omitIds: boolean, metadataKey: string
thoughtSignature: thoughtSignature(part.providerMetadata, metadataKey),
})
const lowerMessages = Effect.fn("Gemini.lowerMessages")(function* (request: LLMRequest) {
const lowerMessages = Effect.fnUntraced(function* (request: LLMRequest) {
const contents: GeminiContent[] = []
const metadataKey = request.model.route.providerMetadataKey ?? String(request.model.provider)
const omitCallIds = omitsFunctionCallIds(request.model.id)
@@ -475,7 +475,7 @@ const fromRequest = Effect.fn("Gemini.fromRequest")(function* (request: LLMReque
safetySettings: options.safetySettings,
serviceTier: options.serviceTier,
systemInstruction:
request.system.length === 0 ? undefined : { parts: [{ text: ProviderShared.joinText(request.system) }] },
request.system.length === 0 ? undefined : { parts: request.system.map((part) => ({ text: part.text })) },
tools: hasTools
? [
{
@@ -0,0 +1,561 @@
import { Effect, Schema } from "effect"
import { Route } from "../route/client.js"
import { Auth } from "../route/auth.js"
import { Endpoint } from "../route/endpoint.js"
import { Framing } from "../route/framing.js"
import { Protocol } from "../route/protocol.js"
import {
AIError,
LLMEvent,
ProviderID,
Usage,
type LLMRequest,
type ProviderMetadata,
type ToolResultPart,
} from "../schema/index.js"
import { Media } from "../media.js"
import { classifyProviderFailure, providerErrorMessage } from "../provider-error.js"
import { encodeJson } from "../utils/json.js"
import { JsonObject, knownString, lenient, optionalNull, ProviderShared } from "./shared.js"
import { Lifecycle } from "./utils/lifecycle.js"
import { MediaInput } from "./utils/media-input.js"
import { ToolStream } from "./utils/tool-stream.js"
const ADAPTER = "google-interactions"
export const DEFAULT_BASE_URL = "https://generativelanguage.googleapis.com/v1beta"
// =============================================================================
// Public Model Input
// =============================================================================
const ThinkingLevel = knownString<"minimal" | "low" | "medium" | "high">()
const Options = Schema.Struct({
previousInteractionId: lenient(Schema.String),
store: lenient(Schema.Boolean),
thinkingLevel: lenient(ThinkingLevel),
thinkingSummaries: lenient(knownString<"auto" | "none">()),
serviceTier: lenient(knownString<"standard" | "flex" | "priority">()),
})
export type OptionsInput = typeof Options.Encoded
export type ProviderOptionsInput = OptionsInput
const decodeOptions = ProviderShared.validateWith(Schema.decodeUnknownEffect(Options))
// =============================================================================
// Request Body Schema
// =============================================================================
const Text = Schema.Struct({ type: Schema.Literal("text"), text: Schema.String })
const MediaContent = Schema.Struct({
type: Schema.Literals(["image", "audio", "video", "document"]),
data: Schema.optional(Schema.String),
uri: Schema.optional(Schema.String),
mime_type: Schema.String,
})
const Content = Schema.Union([Text, MediaContent])
const InputStep = Schema.Union([
Schema.Struct({ type: Schema.Literals(["user_input", "model_output"]), content: Schema.Array(Content) }),
Schema.Struct({
type: Schema.Literal("thought"),
signature: Schema.optional(Schema.String),
summary: Schema.optional(Schema.Array(Text)),
}),
Schema.Struct({
type: Schema.Literal("function_call"),
id: Schema.String,
name: Schema.String,
arguments: Schema.Unknown,
signature: Schema.optional(Schema.String),
}),
Schema.Struct({
type: Schema.Literal("function_result"),
call_id: Schema.String,
name: Schema.String,
result: Schema.Unknown,
is_error: Schema.optional(Schema.Boolean),
}),
])
type InputStep = typeof InputStep.Type
const ToolChoice = Schema.Union([
Schema.Literals(["auto", "any", "none"]),
Schema.Struct({ allowed_tools: Schema.Struct({ mode: Schema.Literal("any"), tools: Schema.Array(Schema.String) }) }),
])
const Body = Schema.Struct({
model: Schema.String,
input: Schema.Array(InputStep),
stream: Schema.Literal(true),
store: Schema.Boolean,
previous_interaction_id: Schema.optional(Schema.String),
system_instruction: Schema.optional(Schema.String),
service_tier: Schema.optional(Schema.String),
tools: Schema.optional(
Schema.Array(
Schema.Struct({
type: Schema.Literal("function"),
name: Schema.String,
description: Schema.String,
parameters: JsonObject,
}),
),
),
generation_config: Schema.Struct({
max_output_tokens: Schema.optional(Schema.Number),
temperature: Schema.optional(Schema.Number),
top_p: Schema.optional(Schema.Number),
seed: Schema.optional(Schema.Number),
stop_sequences: Schema.optional(Schema.Array(Schema.String)),
thinking_level: Schema.optional(ThinkingLevel),
thinking_summaries: Schema.optional(Schema.String),
tool_choice: Schema.optional(ToolChoice),
}),
})
// =============================================================================
// Streaming Event Schema
// =============================================================================
const RawUsage = Schema.StructWithRest(
Schema.Struct({
total_input_tokens: optionalNull(Schema.Number),
total_cached_tokens: optionalNull(Schema.Number),
total_output_tokens: optionalNull(Schema.Number),
total_thought_tokens: optionalNull(Schema.Number),
total_tokens: optionalNull(Schema.Number),
raw_prompt_token: optionalNull(Schema.Number),
}),
[Schema.Record(Schema.String, Schema.Unknown)],
)
type RawUsage = typeof RawUsage.Type
const OutputStep = Schema.Struct({
type: Schema.String,
id: Schema.optional(Schema.String),
name: Schema.optional(Schema.String),
arguments: Schema.optional(JsonObject),
signature: Schema.optional(Schema.String),
summary: Schema.optional(Schema.Array(Text)),
content: Schema.optional(Schema.Array(Schema.Struct({ type: Schema.String, text: Schema.optional(Schema.String) }))),
})
type OutputStep = typeof OutputStep.Type
const Delta = Schema.Union([
Schema.Struct({ type: Schema.Literal("text"), text: Schema.String }),
Schema.Struct({ type: Schema.Literal("arguments_delta"), arguments: Schema.String }),
Schema.Struct({ type: Schema.Literal("thought_signature"), signature: Schema.String }),
Schema.Struct({ type: Schema.Literal("thought_summary"), content: Text }),
// Unknown output modalities must fail explicitly rather than disappearing from a successful response.
Schema.Struct({ type: Schema.String }),
])
const Interaction = Schema.StructWithRest(
Schema.Struct({
id: Schema.optional(Schema.String),
status: Schema.String,
usage: Schema.optional(RawUsage),
}),
[Schema.Record(Schema.String, Schema.Unknown)],
)
const Event = Schema.Union([
Schema.Struct({ event_type: Schema.Literal("step.start"), index: Schema.Number, step: OutputStep }),
Schema.Struct({ event_type: Schema.Literal("step.delta"), index: Schema.Number, delta: Delta }),
Schema.Struct({ event_type: Schema.Literal("step.stop"), index: Schema.Number }),
Schema.Struct({
event_type: Schema.Literal("interaction.created"),
interaction: Schema.Struct({ id: Schema.optional(Schema.String) }),
}),
Schema.Struct({
event_type: Schema.Literal("interaction.status_update"),
interaction_id: Schema.optional(Schema.String),
status: Schema.String,
}),
Schema.Struct({ event_type: Schema.Literal("interaction.completed"), interaction: Interaction }),
Schema.Struct({ event_type: Schema.Literal("error"), error: Schema.Unknown }),
])
type Event = typeof Event.Type
// =============================================================================
// Parser State
// =============================================================================
interface ParserState {
readonly route: string
readonly metadataKey: string
readonly lifecycle: Lifecycle.State
readonly steps: Partial<Record<number, OutputStep>>
readonly tools: ToolStream.State<number>
readonly completed: boolean
}
type StepResult = readonly [ParserState, ReadonlyArray<LLMEvent>]
// =============================================================================
// Request Body Construction
// =============================================================================
const mediaContent = Effect.fnUntraced(function* (asset: Media.Asset) {
if (
asset.kind !== "image" &&
asset.kind !== "audio" &&
asset.kind !== "video" &&
asset.mediaType !== "application/pdf" &&
asset.mediaType !== "text/csv"
)
return yield* ProviderShared.invalidRequest(
`Google Interactions does not support ${asset.mediaType} document input`,
)
const type: (typeof MediaContent.Type)["type"] =
asset.kind === "image" || asset.kind === "audio" || asset.kind === "video" ? asset.kind : "document"
const uri = MediaInput.refID(asset, ProviderID.make("google"))
if (uri !== undefined) return { type, uri, mime_type: asset.mediaType }
const inline = yield* ProviderShared.requireInlineMedia("Google Interactions", asset)
return { type, data: inline.base64, mime_type: inline.mime }
})
const signature = (metadata: ProviderMetadata | undefined, key: string) => {
const value = metadata?.[key]
return ProviderShared.isRecord(value) && typeof value.interactionSignature === "string"
? value.interactionSignature
: undefined
}
const lowerMessages = Effect.fnUntraced(function* (request: LLMRequest) {
const steps: InputStep[] = []
const key = request.model.route.providerMetadataKey ?? String(request.model.provider)
for (const message of request.messages) {
if (message.role === "system") {
const part = yield* ProviderShared.wrappedSystemUpdate("Google Interactions", message)
steps.push({ type: "user_input", content: [{ type: "text", text: part.text }] })
continue
}
const start = steps.length
// Consecutive ordinary content remains one native message; tools and thoughts retain their chronology.
const append = (content: typeof Content.Type) => {
const type = message.role === "assistant" ? "model_output" : "user_input"
const last = steps.at(-1)
if (steps.length > start && last?.type === type)
steps[steps.length - 1] = { type, content: [...last.content, content] }
else steps.push({ type, content: [content] })
}
for (const part of message.content) {
if (message.role === "tool") {
if (part.type !== "tool-result")
return yield* ProviderShared.unsupportedContent(ADAPTER, "tool", ["tool-result"])
steps.push({
type: "function_result",
call_id: part.id,
name: part.name,
result: yield* lowerToolResult(part),
is_error: part.result.type === "error" || undefined,
})
continue
}
if (part.type === "text") {
append({ type: "text", text: part.text })
continue
}
if (part.type === "media") {
append(yield* mediaContent(part.media))
continue
}
if (message.role === "assistant" && part.type === "reasoning") {
steps.push({
type: "thought",
signature: signature(part.providerMetadata, key),
summary: part.text ? [{ type: "text", text: part.text }] : undefined,
})
continue
}
if (message.role === "assistant" && part.type === "tool-call") {
steps.push({
type: "function_call",
id: part.id,
name: part.name,
arguments: part.input,
signature: signature(part.providerMetadata, key),
})
continue
}
return yield* ProviderShared.unsupportedContent(
ADAPTER,
message.role,
message.role === "user" ? ["text", "media"] : ["text", "media", "reasoning", "tool-call"],
)
}
}
return steps
})
const lowerToolResult = Effect.fnUntraced(function* (part: ToolResultPart) {
if (part.result.type === "json" && ProviderShared.isRecord(part.result.value)) return part.result.value
if (part.result.type !== "content") return ProviderShared.toolResultText(part)
return yield* Effect.forEach(part.result.value, (item): Effect.Effect<typeof Content.Type, AIError> => {
if (item.type === "text") return Effect.succeed({ type: "text", text: item.text })
return mediaContent(ProviderShared.toolFileMedia(item).media)
})
})
const fromRequest = Effect.fn("GoogleInteractions.fromRequest")(function* (request: LLMRequest) {
const options = yield* decodeOptions(request.providerOptions ?? {})
const flattened = ProviderShared.flattenToolRequest(request)
if (flattened.tools.some((tool) => tool.native !== undefined))
return yield* ProviderShared.invalidRequest("Google Interactions hosted tools are not supported")
if (
request.generation?.topK !== undefined ||
request.generation?.frequencyPenalty !== undefined ||
request.generation?.presencePenalty !== undefined
)
return yield* ProviderShared.invalidRequest(
"Google Interactions does not support topK, frequencyPenalty, or presencePenalty",
)
const choice =
request.toolChoice === undefined
? undefined
: yield* ProviderShared.matchToolChoice(ADAPTER, request.toolChoice, {
auto: () => "auto" as const,
none: () => "none" as const,
required: () => "any" as const,
tool: (name) => ({ allowed_tools: { mode: "any" as const, tools: [name] } }),
})
return {
model: request.model.id,
input: yield* lowerMessages(flattened.request),
stream: true as const,
// Full-history replay need not create retained provider resources. Continuation callers opt in to storage.
store: options.store ?? false,
previous_interaction_id: options.previousInteractionId,
system_instruction: request.system.length ? ProviderShared.joinText(request.system) : undefined,
service_tier: options.serviceTier,
tools: flattened.tools.length
? flattened.tools.map((tool) => ({
type: "function" as const,
name: tool.name,
description: tool.description,
parameters: tool.inputSchema,
}))
: undefined,
generation_config: {
max_output_tokens: request.generation?.maxTokens,
temperature: request.generation?.temperature,
top_p: request.generation?.topP,
seed: request.generation?.seed,
stop_sequences: request.generation?.stop,
thinking_level: options.thinkingLevel,
thinking_summaries: options.thinkingSummaries,
tool_choice: choice,
},
}
})
// =============================================================================
// Stream Parsing
// =============================================================================
const metadata = (state: ParserState, step: OutputStep): ProviderMetadata => ({
[state.metadataKey]: { interactionSignature: step.signature },
})
const mapUsage = (usage: RawUsage | undefined, key: string) => {
if (!usage) return undefined
const input = usage.total_input_tokens ?? undefined
const cached = usage.total_cached_tokens ?? undefined
const reasoning = usage.total_thought_tokens ?? undefined
const output =
usage.total_output_tokens === undefined || usage.total_output_tokens === null
? undefined
: usage.total_output_tokens + (reasoning ?? 0)
return new Usage({
contextTokens: usage.raw_prompt_token ?? input,
inputTokens: input,
outputTokens: output,
nonCachedInputTokens: ProviderShared.subtractTokens(input, cached),
cacheReadInputTokens: cached,
reasoningTokens: reasoning,
totalTokens: usage.total_tokens ?? undefined,
providerMetadata: { [key]: usage },
})
}
const onStart = Effect.fnUntraced(function* (
state: ParserState,
index: number,
step: OutputStep,
) {
const events: LLMEvent[] = []
let lifecycle = Lifecycle.stepStart(state.lifecycle, events)
let tools = state.tools
const id = String(index)
if (step.type === "thought") {
lifecycle = Lifecycle.reasoningStart(lifecycle, events, id, metadata(state, step))
for (const part of step.summary ?? []) lifecycle = Lifecycle.reasoningDelta(lifecycle, events, id, part.text)
} else if (step.type === "model_output") {
lifecycle = Lifecycle.textStart(lifecycle, events, id)
for (const part of step.content ?? []) {
if (part.type !== "text")
return yield* ProviderShared.eventError(
ADAPTER,
`Unsupported Interactions output: ${part.type}`,
encodeJson(step),
)
if (part.text) lifecycle = Lifecycle.textDelta(lifecycle, events, id, part.text)
}
} else if (step.type === "function_call") {
if (!step.id || !step.name)
return yield* ProviderShared.eventError(ADAPTER, "Interactions function call lacks id or name", encodeJson(step))
tools = ToolStream.start(tools, index, {
id: step.id,
name: step.name,
providerMetadata: metadata(state, step),
input: step.arguments && Object.keys(step.arguments).length ? encodeJson(step.arguments) : "",
})
events.push(LLMEvent.toolInputStart({ id: step.id, name: step.name, providerMetadata: metadata(state, step) }))
} else
return yield* ProviderShared.eventError(ADAPTER, `Unsupported Interactions step: ${step.type}`, encodeJson(step))
return [{ ...state, lifecycle, tools, steps: { ...state.steps, [index]: step } }, events] satisfies StepResult
})
const onDelta = Effect.fnUntraced(function* (
state: ParserState,
index: number,
delta: typeof Delta.Type,
) {
const step = state.steps[index]
if (!step)
return yield* ProviderShared.eventError(ADAPTER, "Interactions delta without step.start", encodeJson(delta))
const events: LLMEvent[] = []
if (delta.type === "text" && "text" in delta && step.type === "model_output")
return [
{ ...state, lifecycle: Lifecycle.textDelta(state.lifecycle, events, String(index), delta.text) },
events,
] satisfies StepResult
if (delta.type === "thought_summary" && "content" in delta && step.type === "thought")
return [
{ ...state, lifecycle: Lifecycle.reasoningDelta(state.lifecycle, events, String(index), delta.content.text) },
events,
] satisfies StepResult
if (delta.type === "thought_signature" && "signature" in delta) {
const next = { ...step, signature: delta.signature }
const tool = state.tools[index]
return [
{
...state,
steps: { ...state.steps, [index]: next },
tools: tool ? { ...state.tools, [index]: { ...tool, providerMetadata: metadata(state, next) } } : state.tools,
},
events,
] satisfies StepResult
}
if (delta.type === "arguments_delta" && "arguments" in delta && step.type === "function_call") {
const result = ToolStream.appendExisting(
ADAPTER,
state.tools,
index,
delta.arguments,
"Interactions arguments without function call",
)
if (ToolStream.isError(result)) return yield* result
return [{ ...state, tools: result.tools }, result.events] satisfies StepResult
}
return yield* ProviderShared.eventError(ADAPTER, `Unsupported Interactions delta: ${delta.type}`, encodeJson(delta))
})
const onStop = Effect.fnUntraced(function* (state: ParserState, index: number) {
const step = state.steps[index]
if (!step) return yield* ProviderShared.eventError(ADAPTER, "Interactions step.stop without step.start")
const events: LLMEvent[] = []
if (step.type === "thought")
return [
{ ...state, lifecycle: Lifecycle.reasoningEnd(state.lifecycle, events, String(index), metadata(state, step)) },
events,
] satisfies StepResult
if (step.type === "model_output")
return [
{ ...state, lifecycle: Lifecycle.textEnd(state.lifecycle, events, String(index)) },
events,
] satisfies StepResult
const result = yield* ToolStream.finish(ADAPTER, state.tools, index)
return [{ ...state, tools: result.tools }, result.events ?? []] satisfies StepResult
})
const step = Effect.fnUntraced(function* (state: ParserState, event: Event) {
switch (event.event_type) {
case "step.start":
return yield* onStart(state, event.index, event.step)
case "step.delta":
return yield* onDelta(state, event.index, event.delta)
case "step.stop":
return yield* onStop(state, event.index)
case "interaction.created":
case "interaction.status_update":
return [state, []] satisfies StepResult
case "error":
return yield* new AIError({
reason: classifyProviderFailure({
message: providerErrorMessage(encodeJson(event)) ?? "Google Interactions stream error",
data: event.error,
rawBody: encodeJson(event),
}),
})
case "interaction.completed": {
const interaction = event.interaction
if (interaction.status === "failed" || interaction.status === "cancelled")
return yield* new AIError({
reason: classifyProviderFailure({
message: `Google Interactions ${interaction.status}`,
data: interaction,
rawBody: encodeJson(event),
}),
})
if (!["completed", "requires_action", "incomplete"].includes(interaction.status))
return yield* ProviderShared.eventError(
ADAPTER,
`Unexpected terminal Interactions status: ${interaction.status}`,
encodeJson(event),
)
const pending = yield* ToolStream.finishAll(ADAPTER, state.tools)
const events = [...pending.events]
const lifecycle = Lifecycle.finish(state.lifecycle, events, {
reason: {
normalized:
interaction.status === "requires_action"
? "tool-calls"
: interaction.status === "incomplete"
? "length"
: "stop",
raw: interaction.status,
},
usage: mapUsage(interaction.usage, state.metadataKey),
providerMetadata: { [state.metadataKey]: { interactionId: interaction.id } },
})
return [{ ...state, lifecycle, tools: pending.tools, completed: true }, events] satisfies StepResult
}
}
})
// =============================================================================
// Protocol And Route
// =============================================================================
export const protocol = Protocol.make({
id: ADAPTER,
sanitizer: "gemini",
body: { schema: Body, from: fromRequest },
stream: {
event: Protocol.jsonEvent(Event),
initial: (request): ParserState => ({
route: `${request.model.provider}/${ADAPTER}`,
metadataKey: request.model.route.providerMetadataKey ?? String(request.model.provider),
lifecycle: Lifecycle.initial(),
steps: {},
tools: ToolStream.empty<number>(),
completed: false,
}),
step,
terminal: (event) => event.event_type === "interaction.completed",
onHalt: (state) =>
state.completed
? Effect.succeed([])
: Effect.fail(
ProviderShared.eventError(ADAPTER, "Google Interactions stream ended before interaction.completed"),
),
},
})
export const route = Route.make({
id: ADAPTER,
provider: "google",
providerMetadataKey: "google",
protocol,
endpoint: Endpoint.path("/interactions", { baseURL: DEFAULT_BASE_URL }),
auth: Auth.none,
framing: Framing.sse,
})
export * as GoogleInteractions from "./google-interactions.js"
+1 -1
View File
@@ -94,7 +94,7 @@ const fromRequest = Effect.fn("GoogleSpeech.fromRequest")(function* (request: Me
// 6. Stream parsing
// ---------------------------------------------------------------------------
const step = Effect.fn("GoogleSpeech.step")(function* (state: State, frame: string) {
const step = Effect.fnUntraced(function* (state: State, frame: string) {
const chunk = yield* decodeChunk(frame)
const blocked = GeminiGenerateContent.blocked(route.name, chunk, frame)
if (blocked !== undefined) return yield* blocked
@@ -138,7 +138,7 @@ const turn = (part: Schema.Schema.Type<typeof AudioTranscription>) => {
}
}
const step = Effect.fn("GoogleTranscription.step")(function* (state: State, frame: string) {
const step = Effect.fnUntraced(function* (state: State, frame: string) {
const chunk = yield* decodeChunk(frame)
const blocked = GeminiGenerateContent.blocked(route.name, chunk, frame)
if (blocked !== undefined) return yield* blocked
+2
View File
@@ -1,6 +1,8 @@
export * as AnthropicMessages from "./anthropic-messages.js"
export * as BedrockConverse from "./bedrock-converse.js"
export * as CohereChat from "./cohere-chat.js"
export * as Gemini from "./gemini.js"
export * as GoogleInteractions from "./google-interactions.js"
export * as MistralChat from "./mistral-chat.js"
export * as OpenAIChat from "./openai-chat.js"
export * as OpenAIImages from "./openai-images.js"
+8 -30
View File
@@ -1,6 +1,5 @@
import { Effect, Encoding, Schema } from "effect"
import { Protocol } from "../route/protocol.js"
import { HttpTransport } from "../route/transport/index.js"
import { LLMEvent, LLMRequest, Message, ToolResultPart } from "../schema/index.js"
import { OpenResponses } from "./open-responses.js"
import { JsonObject, optionalArray, optionalNull, ProviderShared } from "./shared.js"
@@ -44,13 +43,6 @@ const ImageItem = Schema.Struct({
error: Schema.optional(Schema.Unknown),
})
const Body = Schema.Struct({
...OpenResponses.coreFields,
input: Schema.Array(Schema.Union([OpenResponses.InputItem, ImageItem])),
tools: optionalArray(Schema.Union([OpenResponses.Tool, NativeTool])),
stream: Schema.Literal(true),
})
const MessageAnnotations = Schema.Struct({
content: Schema.Array(Schema.Struct({ annotations: optionalArray(JsonObject) })),
})
@@ -62,12 +54,13 @@ interface ParserState extends OpenResponses.ParserState {
const adapter = {
id: ADAPTER,
name: NAME,
nativeTool: (native) => ProviderShared.validateWith(Schema.decodeUnknownEffect(NativeTool))(native.meta),
restoreHostedToolItem: (item: unknown) => (Schema.is(ImageItem)(item) ? item : undefined),
} satisfies OpenResponses.ProviderAdapter
const fromRequest = Effect.fn("MetaResponses.fromRequest")(function* (request: LLMRequest) {
const key = request.model.route.providerMetadataKey ?? String(request.model.provider)
const projected = ProviderShared.flattenToolRequest(
return yield* OpenResponses.fromRequestWithAdapter(
LLMRequest.update(request, {
messages: request.messages.map((message) =>
Message.make({
@@ -93,23 +86,8 @@ const fromRequest = Effect.fn("MetaResponses.fromRequest")(function* (request: L
}),
),
}),
adapter,
)
return yield* ProviderShared.validateWith(Schema.decodeUnknownEffect(Body))({
...(yield* OpenResponses.lowerConversation(projected.request, adapter)),
...OpenResponses.lowerGeneration(request),
tools:
projected.tools.length === 0
? undefined
: yield* Effect.forEach(projected.tools, (tool) =>
Effect.gen(function* () {
if (tool.native === undefined) return yield* OpenResponses.lowerTool(NAME, tool)
return yield* ProviderShared.validateWith(Schema.decodeUnknownEffect(NativeTool))(tool.native.meta)
}),
),
tool_choice:
OpenResponses.allowedToolChoice(request) ??
(request.toolChoice ? yield* OpenResponses.lowerToolChoice(NAME, request.toolChoice) : undefined),
})
})
const HOSTED_TOOLS = {
@@ -117,7 +95,7 @@ const HOSTED_TOOLS = {
image_generation_call: {
name: "image_generation",
input: () => ({}),
result: Effect.fn("MetaResponses.imageResult")(function* (raw: ResponsesHostedTools.Item) {
result: Effect.fnUntraced(function* (raw: ResponsesHostedTools.Item) {
const item = yield* Schema.decodeUnknownEffect(ImageItem)(raw).pipe(
Effect.mapError((cause) =>
ProviderShared.eventError(
@@ -158,7 +136,7 @@ const HOSTED_TOOLS = {
},
} satisfies ResponsesHostedTools.Definitions
const onEvent = Effect.fn("MetaResponses.onEvent")(function* (
const onEvent = Effect.fnUntraced(function* (
state: OpenResponses.ParserState,
input: OpenResponses.Event,
) {
@@ -195,7 +173,7 @@ const onEvent = Effect.fn("MetaResponses.onEvent")(function* (
] satisfies OpenResponses.StepResult
})
const step = Effect.fn("MetaResponses.step")(function* (state: ParserState, input: OpenResponses.Event) {
const step = Effect.fnUntraced(function* (state: ParserState, input: OpenResponses.Event) {
const completedItems = new Set(state.completedItems)
const event = OpenResponses.normalize(state, input)
if (event.type === "response.output_item.done" && event.item && completedItems.has(event.item.id))
@@ -222,7 +200,7 @@ const step = Effect.fn("MetaResponses.step")(function* (state: ParserState, inpu
export const protocol = Protocol.make({
id: ADAPTER,
body: { schema: Body, from: fromRequest },
body: { schema: OpenResponses.OpenResponsesBody, from: fromRequest },
stream: {
event: OpenResponses.protocol.stream.event,
initial: (request): ParserState => ({ ...OpenResponses.initial(request, adapter), completedItems: new Set() }),
@@ -231,6 +209,6 @@ export const protocol = Protocol.make({
},
})
export const httpTransport = HttpTransport.sseJson.with<Schema.Schema.Type<typeof Body>>()
export const httpTransport = OpenResponses.httpTransport
export * as MetaResponses from "./meta-responses.js"
+23 -10
View File
@@ -68,7 +68,10 @@ const MistralAssistantToolCall = Schema.Struct({
type MistralAssistantToolCall = Schema.Schema.Type<typeof MistralAssistantToolCall>
const MistralMessage = Schema.Union([
Schema.Struct({ role: Schema.Literal("system"), content: Schema.String }),
Schema.Struct({
role: Schema.Literal("system"),
content: Schema.Union([Schema.String, Schema.Array(MistralTextContent)]),
}),
Schema.Struct({
role: Schema.Literal("user"),
content: Schema.Union([Schema.String, Schema.Array(MistralUserContent)]),
@@ -223,7 +226,7 @@ const MistralEvent = Schema.StructWithRest(
type MistralEvent = Schema.Schema.Type<typeof MistralEvent>
const MistralStreamEvent = Schema.Union([Schema.Literal(DONE), Protocol.jsonEvent(MistralEvent)])
const lowerMedia = Effect.fn("MistralChat.lowerMedia")(function* (part: MediaPart) {
const lowerMedia = Effect.fnUntraced(function* (part: MediaPart) {
const mime = part.media.mediaType.toLowerCase()
const url =
ProviderShared.mediaUrl(part.media) ??
@@ -233,7 +236,7 @@ const lowerMedia = Effect.fn("MistralChat.lowerMedia")(function* (part: MediaPar
return yield* ProviderShared.invalidRequest(`Mistral Chat does not support media type ${part.media.mediaType}`)
})
const lowerUser = Effect.fn("MistralChat.lowerUser")(function* (message: LLMRequest["messages"][number]) {
const lowerUser = Effect.fnUntraced(function* (message: LLMRequest["messages"][number]) {
const content: MistralUserContent[] = []
for (const part of message.content) {
if (part.type === "text") {
@@ -257,7 +260,7 @@ const lowerToolCall = (part: ToolCallPart, normalizeID: (id: string) => string):
function: { name: part.name, arguments: ProviderShared.encodeJson(part.input) },
})
const lowerAssistant = Effect.fn("MistralChat.lowerAssistant")(function* (
const lowerAssistant = Effect.fnUntraced(function* (
message: LLMRequest["messages"][number],
normalizeID: (id: string) => string,
prefix: boolean,
@@ -295,7 +298,7 @@ const lowerAssistant = Effect.fn("MistralChat.lowerAssistant")(function* (
}
})
const lowerToolResults = Effect.fn("MistralChat.lowerToolResults")(function* (
const lowerToolResults = Effect.fnUntraced(function* (
message: LLMRequest["messages"][number],
normalizeID: (id: string) => string,
) {
@@ -332,10 +335,20 @@ const lowerToolResults = Effect.fn("MistralChat.lowerToolResults")(function* (
return output
})
const lowerMessages = Effect.fn("MistralChat.lowerMessages")(function* (request: LLMRequest) {
const lowerMessages = Effect.fnUntraced(function* (request: LLMRequest) {
const normalizeID = MistralToolID.normalizer(request)
const messages: MistralMessage[] =
request.system.length === 0 ? [] : [{ role: "system", content: ProviderShared.joinText(request.system) }]
request.system.length === 0
? []
: [
{
role: "system",
content:
request.system.length === 1
? request.system[0].text
: request.system.map((part) => ({ type: "text", text: part.text })),
},
]
for (const message of request.messages) {
if (message.role === "system") {
const update = yield* ProviderShared.wrappedSystemUpdate("Mistral Chat", message)
@@ -583,7 +596,7 @@ const toolText = (tool: MistralToolDelta) => {
return value === null || value === undefined ? "" : ProviderShared.encodeJson(value)
}
const appendTools = Effect.fn("MistralChat.appendTools")(function* (
const appendTools = Effect.fnUntraced(function* (
initial: ParserState,
events: LLMEvent[],
deltas: ReadonlyArray<MistralToolDelta>,
@@ -649,7 +662,7 @@ const hasLateContent = (event: MistralEvent) => {
)
}
const step = Effect.fn("MistralChat.step")(function* (state: ParserState, event: MistralEvent) {
const step = Effect.fnUntraced(function* (state: ParserState, event: MistralEvent) {
if (event.error) {
const body = ProviderShared.encodeJson(event)
return yield* new AIError({
@@ -713,7 +726,7 @@ const step = Effect.fn("MistralChat.step")(function* (state: ParserState, event:
] as const
})
const finishEvents = Effect.fn("MistralChat.finishEvents")(function* (state: ParserState) {
const finishEvents = Effect.fnUntraced(function* (state: ParserState) {
if (!state.finishReason)
return yield* new AIError({
reason: new InvalidProviderOutputError({
+43 -43
View File
@@ -168,10 +168,20 @@ export const ConfigurationUpdate = Schema.Struct({
type: Schema.Literal("configuration_update"),
reasoning: Schema.Struct({ effort: OpenResponsesOptions.ReasoningEffort }),
})
type ConfigurationUpdate = Schema.Schema.Type<typeof ConfigurationUpdate>
export type ConfigurationUpdate = Schema.Schema.Type<typeof ConfigurationUpdate>
export const HostedToolReplay = Schema.StructWithRest(
Schema.Struct({
type: Schema.String,
id: Schema.String,
}),
[JsonObject],
)
export type HostedToolReplayItem = Schema.Schema.Type<typeof HostedToolReplay>
export const InputItem = Schema.Union([
CompactionItem,
ConfigurationUpdate,
Schema.Struct({ type: Schema.tag("message"), role: Schema.tag("system"), content: Schema.String }),
Schema.Struct({ type: Schema.tag("message"), role: Schema.tag("developer"), content: Schema.String }),
Schema.Struct({
@@ -204,24 +214,9 @@ export const InputItem = Schema.Union([
output: OpenResponsesFunctionCallOutput,
}),
HostedToolItem,
HostedToolReplay,
])
type OpenResponsesInputItem = Schema.Schema.Type<typeof InputItem>
export type HostedToolReplayItem = {
readonly type: string
readonly id: string
readonly [key: string]: unknown
}
type LoweredInputItem =
| OpenResponsesInputItem
| HostedToolReplayItem
| ConfigurationUpdate
| {
readonly type: "message"
readonly id?: string
readonly role: "assistant"
readonly content: ReadonlyArray<{ readonly type: "output_text"; readonly text: string }>
readonly phase?: MessagePhase | null
}
// Mutable counterpart of the schema reasoning item so `lowerMessages` can fold
// multiple streamed summary parts into the same item before flushing.
@@ -239,6 +234,14 @@ export const Tool = Schema.Struct({
strict: Schema.optional(Schema.Boolean),
})
export const HostedTool = Schema.StructWithRest(
Schema.Struct({
type: Schema.String,
}),
[JsonObject],
)
export type HostedTool = Schema.Schema.Type<typeof HostedTool>
export const ToolChoice = Schema.Union([
Schema.Literals(["auto", "none", "required"]),
Schema.Struct({ type: Schema.tag("function"), name: Schema.String }),
@@ -257,7 +260,7 @@ export const coreFields = {
model: Schema.String,
input: Schema.Array(InputItem),
instructions: Schema.optional(Schema.String),
tools: optionalArray(Tool),
tools: optionalArray(Schema.Union([Tool, HostedTool])),
tool_choice: Schema.optional(ToolChoice),
store: Schema.optional(Schema.Boolean),
metadata: Schema.optional(Schema.Record(Schema.String, Schema.String)),
@@ -292,7 +295,7 @@ export const coreFields = {
frequency_penalty: Schema.optional(Schema.Number),
}
const OpenResponsesBody = Schema.Struct({
export const OpenResponsesBody = Schema.Struct({
...coreFields,
stream: Schema.Literal(true),
})
@@ -397,9 +400,7 @@ export const decodeChannelEvent = (frame: string) =>
export interface ProviderAdapter {
readonly id: string
readonly name: string
readonly nativeTool?: (
native: NonNullable<ToolDefinition["native"]>,
) => Effect.Effect<{ readonly type: string }, AIError>
readonly nativeTool?: (native: NonNullable<ToolDefinition["native"]>) => Effect.Effect<HostedTool, AIError>
readonly lowerMedia?: (input: {
readonly part: MediaPart
readonly media: Media.Inline | undefined
@@ -441,7 +442,7 @@ interface ReasoningStreamItem {
// =============================================================================
// Request Lowering
// =============================================================================
export const lowerTool = Effect.fn("OpenResponses.lowerTool")(function* (protocolName: string, tool: ToolDefinition) {
export const lowerTool = Effect.fnUntraced(function* (protocolName: string, tool: ToolDefinition) {
if (tool.native !== undefined)
return yield* ProviderShared.invalidRequest(`${protocolName} does not support provider-native tool ${tool.name}`)
return {
@@ -455,8 +456,10 @@ export const lowerTool = Effect.fn("OpenResponses.lowerTool")(function* (protoco
})
export const lowerTools = (tools: ReadonlyArray<ToolDefinition>, adapter: ProviderAdapter) =>
Effect.forEach(tools, (tool) =>
tool.native !== undefined && adapter.nativeTool ? adapter.nativeTool(tool.native) : lowerTool(adapter.name, tool),
Effect.forEach(
tools,
(tool): Effect.Effect<Schema.Schema.Type<typeof Tool> | HostedTool, AIError> =>
tool.native !== undefined && adapter.nativeTool ? adapter.nativeTool(tool.native) : lowerTool(adapter.name, tool),
)
export const lowerToolChoice = (protocolName: string, toolChoice: NonNullable<LLMRequest["toolChoice"]>) =>
@@ -504,7 +507,10 @@ const lowerReasoning = (part: ReasoningPart, providerMetadataKey: string): OpenR
}
}
const lowerMedia = Effect.fn("OpenResponses.lowerMedia")(function* (
const decodeImageDetail = ProviderShared.validateWith(Schema.decodeUnknownEffect(OpenResponsesInputImage.fields.detail))
const decodeMessageMetadata = ProviderShared.validateWith(Schema.decodeUnknownEffect(MessageMetadata))
const lowerMedia = Effect.fnUntraced(function* (
part: MediaPart,
request: LLMRequest,
adapter: ProviderAdapter,
@@ -513,9 +519,8 @@ const lowerMedia = Effect.fn("OpenResponses.lowerMedia")(function* (
const media = part.media.inline()
const providerMedia = adapter.lowerMedia?.({ part, media, request })
if (providerMedia) return providerMedia
const detail = yield* ProviderShared.validateWith(Schema.decodeUnknownEffect(OpenResponsesInputImage.fields.detail))(
part.providerMetadata?.[metadataKey(request.model)]?.detail,
)
const rawDetail = part.providerMetadata?.[metadataKey(request.model)]?.detail
const detail = rawDetail === undefined ? undefined : yield* decodeImageDetail(rawDetail)
const mime = part.media.mediaType.toLowerCase()
const url = ProviderShared.mediaUrl(part.media)
const location = url ?? (yield* ProviderShared.requireInlineMedia(adapter.name, part.media)).dataUrl
@@ -588,17 +593,16 @@ const lowerToolResultOutput = Effect.fnUntraced(function* (
const DEFAULT_EFFORT = "medium"
const lowerMessages = Effect.fn("OpenResponses.lowerMessages")(function* (
const lowerMessages = Effect.fnUntraced(function* (
request: LLMRequest,
adapter: ProviderAdapter,
) {
const input: LoweredInputItem[] = []
const input: OpenResponsesInputItem[] = []
const providerMetadataKey = metadataKey(request.model)
for (const message of request.messages) {
const metadata = yield* ProviderShared.validateWith(
Schema.decodeUnknownEffect(Schema.UndefinedOr(MessageMetadata)),
)(message.providerMetadata?.[providerMetadataKey])
const rawMetadata = message.providerMetadata?.[providerMetadataKey]
const metadata = rawMetadata === undefined ? undefined : yield* decodeMessageMetadata(rawMetadata)
if (message.role === "system") {
const update = effortUpdate(message)
if (update) {
@@ -752,7 +756,7 @@ const lowerMessages = Effect.fn("OpenResponses.lowerMessages")(function* (
return input
})
export const lowerConversation = Effect.fn("OpenResponses.lowerConversation")(function* (
export const lowerConversation = Effect.fnUntraced(function* (
request: LLMRequest,
adapter: ProviderAdapter,
) {
@@ -827,11 +831,7 @@ export const fromRequestWithAdapter = Effect.fn("OpenResponses.fromRequestWithAd
}
})
const decodeBody = ProviderShared.validateWith(Schema.decodeUnknownEffect(OpenResponsesBody))
export const fromRequest = Effect.fn("OpenResponses.fromRequest")(function* (request: LLMRequest) {
return yield* decodeBody(yield* fromRequestWithAdapter(request, BASE_ADAPTER))
})
export const fromRequest = (request: LLMRequest) => fromRequestWithAdapter(request, BASE_ADAPTER)
// =============================================================================
// Stream Parsing
@@ -1143,7 +1143,7 @@ const onReasoningSummaryPartDone = (state: ParserState, event: Event): StepResul
]
}
const onFunctionCallArgumentsDelta = Effect.fn("OpenResponses.onFunctionCallArgumentsDelta")(function* (
const onFunctionCallArgumentsDelta = Effect.fnUntraced(function* (
state: ParserState,
event: Event,
) {
@@ -1174,7 +1174,7 @@ const onFunctionCallArgumentsDelta = Effect.fn("OpenResponses.onFunctionCallArgu
return [{ ...state, lifecycle, tools: result.tools }, events] satisfies StepResult
})
const onOutputItemDone = Effect.fn("OpenResponses.onOutputItemDone")(function* (
const onOutputItemDone = Effect.fnUntraced(function* (
state: ParserState,
item: NormalizedEvent["item"],
) {
@@ -1310,7 +1310,7 @@ const onOutputItemDone = Effect.fn("OpenResponses.onOutputItemDone")(function* (
return [state, NO_EVENTS] satisfies StepResult
})
const onResponseFinish = Effect.fn("OpenResponses.onResponseFinish")(function* (state: ParserState, event: Event) {
const onResponseFinish = Effect.fnUntraced(function* (state: ParserState, event: Event) {
let current = state
const events: LLMEvent[] = []
if (event.type === "response.completed") {
+8 -15
View File
@@ -14,7 +14,6 @@ import {
ProviderInternalError,
UnknownProviderError,
Usage,
type FinishReason,
type FinishReasonDetails,
type CacheHint,
type LLMRequest,
@@ -46,12 +45,6 @@ const OpenAIChatCacheControl = Schema.Struct({
})
type OpenAIChatCacheControl = Schema.Schema.Type<typeof OpenAIChatCacheControl>
const OpenAIChatFunction = Schema.Struct({
name: Schema.String,
description: Schema.String,
parameters: JsonObject,
})
const OpenAIChatTool = Schema.Struct({
type: Schema.tag("function"),
function: Schema.Struct({
@@ -367,7 +360,7 @@ const lowerToolCall = (
extra_content: decodeExtraContent(part.providerMetadata?.[options.providerMetadataKey]?.extraContent),
})
const lowerMedia = Effect.fn("OpenAIChat.lowerMedia")(function* (part: MediaPart) {
const lowerMedia = Effect.fnUntraced(function* (part: MediaPart) {
// Chat Completions accepts PDFs, and no other documents, as inline `file` parts; file URLs are not supported.
if (part.media.mediaType.toLowerCase() === "application/pdf")
return {
@@ -413,7 +406,7 @@ const lowerReasoningDetail = (detail: ReasoningDetail) => {
const isKimiDetail = (detail: { readonly type: string }) => detail.type === "summary" || detail.type === "encrypted"
const lowerUserMessage = Effect.fn("OpenAIChat.lowerUserMessage")(function* (
const lowerUserMessage = Effect.fnUntraced(function* (
message: OpenAIChatRequestMessage,
options: LoweringOptions,
) {
@@ -437,7 +430,7 @@ const lowerUserMessage = Effect.fn("OpenAIChat.lowerUserMessage")(function* (
return { role: "user" as const, content }
})
const lowerAssistantMessage = Effect.fn("OpenAIChat.lowerAssistantMessage")(function* (
const lowerAssistantMessage = Effect.fnUntraced(function* (
message: OpenAIChatRequestMessage,
configuredField: string | undefined,
requireReasoning: boolean,
@@ -502,7 +495,7 @@ const lowerAssistantMessage = Effect.fn("OpenAIChat.lowerAssistantMessage")(func
return { ...result, [field]: reasoningText }
})
const lowerToolMessages = Effect.fn("OpenAIChat.lowerToolMessages")(function* (
const lowerToolMessages = Effect.fnUntraced(function* (
message: OpenAIChatRequestMessage,
options: LoweringOptions,
) {
@@ -539,7 +532,7 @@ const toolMessage = (toolCallID: string, text: string, cacheControl: OpenAIChatC
content: cacheControl === undefined ? text : [{ type: "text" as const, text, cache_control: cacheControl }],
})
const lowerMessage = Effect.fn("OpenAIChat.lowerMessage")(function* (
const lowerMessage = Effect.fnUntraced(function* (
message: OpenAIChatRequestMessage,
reasoningField: string | undefined,
requireReasoning: boolean,
@@ -551,7 +544,7 @@ const lowerMessage = Effect.fn("OpenAIChat.lowerMessage")(function* (
return (yield* lowerToolMessages(message, options)).messages
})
const lowerMessages = Effect.fn("OpenAIChat.lowerMessages")(function* (request: LLMRequest, options: LoweringOptions) {
const lowerMessages = Effect.fnUntraced(function* (request: LLMRequest, options: LoweringOptions) {
const system: OpenAIChatMessage[] =
request.system.length === 0
? []
@@ -862,7 +855,7 @@ export const fromRequest = Effect.fn("OpenAIChat.fromRequest")(function* (
// Streaming parsers are small state machines: every event returns a new state
// plus the common `LLMEvent`s produced by that event. Tool calls are accumulated
// because OpenAI streams JSON arguments across multiple deltas.
const mapFinishReason = Effect.fn("OpenAIChat.mapFinishReason")(function* (event: OpenAIChatEvent, reason: string) {
const mapFinishReason = Effect.fnUntraced(function* (event: OpenAIChatEvent, reason: string) {
switch (reason) {
case "error":
return yield* new AIError({
@@ -1221,7 +1214,7 @@ const step = (state: ParserState, event: OpenAIChatEvent) =>
] as const
})
const finishEvents = Effect.fn("OpenAIChat.finishEvents")(function* (state: ParserState) {
const finishEvents = Effect.fnUntraced(function* (state: ParserState) {
if (state.finishReason === undefined && state.requireFinishReason)
return yield* new AIError({
reason: new InvalidProviderOutputError({
+2 -2
View File
@@ -208,7 +208,7 @@ const eventImage = (frame: string, label: string, data: string, format: string,
info: info(format, size),
})
const onEvent = Effect.fn("OpenAIImages.onEvent")(function* (state: State, frame: string) {
const onEvent = Effect.fnUntraced(function* (state: State, frame: string) {
const event = yield* decodeEvent(frame)
const format = event.output_format
if ("partial_image_index" in event) {
@@ -229,7 +229,7 @@ const onEvent = Effect.fn("OpenAIImages.onEvent")(function* (state: State, frame
] as const
})
const onDocument = Effect.fn("OpenAIImages.onDocument")(function* (frame: Exclude<Frame, string>) {
const onDocument = Effect.fnUntraced(function* (frame: Exclude<Frame, string>) {
const invalid = (message: string, cause?: unknown) => route.frameError(message, frame.document, cause)
const decoded = yield* decodeDocument(frame.document).pipe(
Effect.mapError((cause) => invalid(`${route.name} returned an invalid response`, cause)),
+6 -15
View File
@@ -103,15 +103,8 @@ const OpenAIResponsesToolChoice = Schema.Union([
Schema.Struct({ type: Schema.tag("image_generation") }),
])
const OpenAIResponsesInputItem = Schema.Union([
OpenResponses.InputItem,
OpenAIResponsesHostedToolItem,
OpenResponses.ConfigurationUpdate,
])
const OpenAIResponsesCoreFields = {
...OpenResponses.coreFields,
input: Schema.Array(OpenAIResponsesInputItem),
tools: optionalArray(OpenAIResponsesTools),
tool_choice: Schema.optional(OpenAIResponsesToolChoice),
context_management: Schema.optional(
@@ -134,7 +127,7 @@ export type OpenAIResponsesBody = Schema.Schema.Type<typeof OpenAIResponsesBody>
export const CompactionTrigger = Schema.Struct({ type: Schema.Literal("compaction_trigger") })
const CheckpointBody = Schema.Struct({
...OpenAIResponsesBody.fields,
input: Schema.Array(Schema.Union([OpenAIResponsesInputItem, CompactionTrigger])),
input: Schema.Array(Schema.Union([OpenResponses.InputItem, CompactionTrigger])),
})
const adapter = {
@@ -164,7 +157,7 @@ const nativeImageTool = (tool: ToolDefinition) => {
return Schema.is(OpenAIResponsesImageGenerationTool)(native) ? native : undefined
}
const lowerTool = Effect.fn("OpenAIResponses.lowerTool")(function* (tool: ToolDefinition) {
const lowerTool = Effect.fnUntraced(function* (tool: ToolDefinition) {
const native = nativeImageToolInput(tool)
if (native !== undefined) {
if (Schema.is(OpenAIResponsesImageGenerationTool)(native)) return native
@@ -175,7 +168,7 @@ const lowerTool = Effect.fn("OpenAIResponses.lowerTool")(function* (tool: ToolDe
// Native namespaces hold only function tools, so deeper levels flatten into
// the leaf names the same way non-native protocols flatten the whole tree.
const lowerToolEntry = Effect.fn("OpenAIResponses.lowerToolEntry")(function* (tool: ToolEntry) {
const lowerToolEntry = Effect.fnUntraced(function* (tool: ToolEntry) {
if (tool.type === "tool") return yield* lowerTool(tool)
// OpenAI requires a namespace description; fall back to a generic one so a
// missing description never blocks the request.
@@ -202,15 +195,13 @@ const lowerToolChoice = (toolChoice: NonNullable<LLMRequest["toolChoice"]>, tool
: { type: "function" as const, name },
})
const decodeBody = ProviderShared.validateWith(Schema.decodeUnknownEffect(OpenAIResponsesBody))
const fromRequest = Effect.fn("OpenAIResponses.fromRequest")(function* (request: LLMRequest) {
const management = yield* ProviderShared.validateWith(
Schema.decodeUnknownEffect(Schema.UndefinedOr(ContextManagement)),
)(request.providerOptions?.contextManagement)
const options = OpenResponsesOptions.resolve(request)
const updates = resolveEffortUpdates(request, options.reasoningEffort)
return yield* decodeBody({
return {
...(yield* OpenResponses.lowerConversation(updates.request, adapter)),
...OpenResponses.lowerGeneration(request, { ...options, reasoningEffort: updates.effort }),
context_management: management?.map((edit) => ({ type: edit.type, compact_threshold: edit.compactThreshold })),
@@ -220,7 +211,7 @@ const fromRequest = Effect.fn("OpenAIResponses.fromRequest")(function* (request:
? undefined
: (OpenResponses.allowedToolChoice(request) ??
(request.toolChoice ? yield* lowerToolChoice(request.toolChoice, request.tools) : undefined)),
})
}
})
const checkpointBody = {
@@ -246,7 +237,7 @@ const checkpointBody = {
}),
}
const hostedToolResult = Effect.fn("OpenAIResponses.hostedToolResult")(function* (item: ResponsesHostedTools.Item) {
const hostedToolResult = Effect.fnUntraced(function* (item: ResponsesHostedTools.Item) {
const isError = item.error !== undefined && item.error !== null
if (item.type === "image_generation_call" && item.result) {
yield* Effect.fromResult(Encoding.decodeBase64(item.result)).pipe(
+1 -1
View File
@@ -94,7 +94,7 @@ const fromRequest = Effect.fn("OpenAISpeech.fromRequest")(function* (request: Me
const isSse = (body: MediaProtocol.Body) => body.type === "json" && body.value.stream_format === "sse"
const onEvent = Effect.fn("OpenAISpeech.onEvent")(function* (state: State, frame: string) {
const onEvent = Effect.fnUntraced(function* (state: State, frame: string) {
const event = yield* decodeEvent(frame)
if (event.type === "speech.audio.delta") return SpeechStream.delta(state, event.audio)
const usage = event.usage
@@ -210,7 +210,7 @@ const segment = (value: Schema.Schema.Type<typeof Segment>): TranscriptionSegmen
speaker: value.speaker,
})
const onEvent = Effect.fn("OpenAITranscription.onEvent")(function* (state: State, frame: string) {
const onEvent = Effect.fnUntraced(function* (state: State, frame: string) {
if (!EVENT_TYPES.has((yield* decodeEventType(frame)).type)) return [state, []] as const
const event = yield* decodeEvent(frame)
if (event.type === "error")
+2 -2
View File
@@ -154,7 +154,7 @@ export const wrapSystemUpdate = (parts: ReadonlyArray<{ readonly text: string }>
* raw retrieved, tool, or web content into privileged updates: keep untrusted
* data in ordinary user/tool messages instead.
*/
export const systemUpdateText = Effect.fn("ProviderShared.systemUpdateText")(function* (
export const systemUpdateText = Effect.fnUntraced(function* (
route: string,
message: LLMRequest["messages"][number],
) {
@@ -167,7 +167,7 @@ export const systemUpdateText = Effect.fn("ProviderShared.systemUpdateText")(fun
})
/** Lower an unsupported privileged update into visible, in-order user text. */
export const wrappedSystemUpdate = Effect.fn("ProviderShared.wrappedSystemUpdate")(function* (
export const wrappedSystemUpdate = Effect.fnUntraced(function* (
route: string,
message: LLMRequest["messages"][number],
) {
@@ -82,7 +82,7 @@ const endpoint = (model: string) => (model.startsWith("sd3") ? "sd3" : model)
const RESERVED_FORM_FIELDS = new Set(["image", "prompt", "mode", "model"])
const form = Effect.fn("StabilityImages.form")(function* (
const form = Effect.fnUntraced(function* (
identity: MediaProtocol.Identity,
fields: Record<string, unknown>,
native: Record<string, unknown> | undefined,
@@ -76,7 +76,7 @@ function documentName(filename: string | undefined, names: Set<string>) {
return name
}
const mediaBase64 = Effect.fn("BedrockMedia.mediaBase64")(function* (part: MediaPart) {
const mediaBase64 = Effect.fnUntraced(function* (part: MediaPart) {
const media = yield* ProviderShared.requireInlineMedia("Bedrock Converse", part.media)
const bytes = yield* Effect.fromResult(Encoding.decodeBase64(media.base64)).pipe(
Effect.mapError((cause) =>
@@ -91,7 +91,7 @@ const mediaBase64 = Effect.fn("BedrockMedia.mediaBase64")(function* (part: Media
// document block. Image MIME types not in `IMAGE_FORMATS` (e.g. `image/svg+xml`)
// get an image-specific error so the caller knows it's a format-support issue,
// not a kind-detection issue.
export const lower = Effect.fn("BedrockMedia.lower")(function* (part: MediaPart, documentNames: Set<string>) {
export const lower = Effect.fnUntraced(function* (part: MediaPart, documentNames: Set<string>) {
const mime = part.media.mediaType.toLowerCase()
const imageFormat = IMAGE_FORMATS[mime as keyof typeof IMAGE_FORMATS]
if (imageFormat) {
@@ -11,7 +11,7 @@ interface State {
readonly responseID?: string
}
const onOutputItem = Effect.fn("ResponsesCheckpoint.onOutputItem")(function* (
const onOutputItem = Effect.fnUntraced(function* (
state: State,
input: OpenResponses.Event,
) {
@@ -63,7 +63,7 @@ export const make = <Body>(body: RouteBody<Body>): TriggerCompactOperation =>
checkpoints: {},
}),
terminal: OpenResponses.terminal,
step: Effect.fn("ResponsesCheckpoint.step")(function* (state: State, event: OpenResponses.Event) {
step: Effect.fnUntraced(function* (state: State, event: OpenResponses.Event) {
if (event.response?.id && state.responseID && event.response.id !== state.responseID)
return yield* ProviderShared.eventError(source.id, "Compaction response ID changed during execution")
if (event.type === "response.created") return [{ ...state, responseID: event.response?.id }, []] as const
@@ -33,7 +33,7 @@ export const onDone: (
state: OpenResponses.ParserState,
item: Item,
tools: Definitions,
) => Effect.Effect<OpenResponses.StepResult, AIError> = Effect.fn("ResponsesHostedTools.onDone")(
) => Effect.Effect<OpenResponses.StepResult, AIError> = Effect.fnUntraced(
function* (state, item, tools) {
const tool = tools[item.type]
if (!tool) return [state, []] satisfies OpenResponses.StepResult
+15 -8
View File
@@ -60,14 +60,21 @@ const inputStart = (tool: PendingTool) =>
providerMetadata: tool.providerMetadata,
})
const inputDelta = (tool: PendingTool, text: string) =>
LLMEvent.toolInputDelta({
id: tool.id,
name: tool.name,
namespace: tool.namespace,
text,
input: Option.getOrElse(parsePartialInput(tool.input), () => ({})),
})
const inputDelta = (tool: PendingTool, text: string): LLMEvent => {
const raw = tool.input
let parsed: unknown
return {
...LLMEvent.toolInputDelta({
id: tool.id,
name: tool.name,
namespace: tool.namespace,
text,
}),
get input() {
return (parsed ??= Option.getOrElse(parsePartialInput(raw), () => ({})))
},
}
}
const toolCall = (route: string, tool: PendingTool, inputOverride?: string) => {
const raw = inputOverride ?? tool.input
+2 -9
View File
@@ -31,19 +31,12 @@ const XAIResponsesHostedToolItem = Schema.Union([
),
])
const XAIResponsesBody = Schema.Struct({
...OpenResponses.coreFields,
input: Schema.Array(Schema.Union([OpenResponses.InputItem, XAIResponsesHostedToolItem])),
stream: Schema.Literal(true),
})
const adapter = {
id: ADAPTER,
name: NAME,
restoreHostedToolItem: (item: unknown) => (Schema.is(XAIResponsesHostedToolItem)(item) ? item : undefined),
} satisfies OpenResponses.ProviderAdapter
const decodeBody = ProviderShared.validateWith(Schema.decodeUnknownEffect(XAIResponsesBody))
const fromRequest = Effect.fn("XAIResponses.fromRequest")(function* (request: LLMRequest) {
if (request.providerOptions?.contextManagement !== undefined)
return yield* ProviderShared.unsupportedOperation({
@@ -53,7 +46,7 @@ const fromRequest = Effect.fn("XAIResponses.fromRequest")(function* (request: LL
message:
"xAI requires explicit compaction through LLMClient.compact; automatic context management is not supported",
})
return yield* decodeBody(yield* OpenResponses.fromRequestWithAdapter(request, adapter))
return yield* OpenResponses.fromRequestWithAdapter(request, adapter)
})
const HOSTED_TOOLS = {
@@ -83,7 +76,7 @@ const step = (state: OpenResponses.ParserState, input: OpenResponses.Event) => {
export const protocol = Protocol.make({
id: ADAPTER,
body: {
schema: XAIResponsesBody,
schema: OpenResponses.OpenResponsesBody,
from: fromRequest,
},
stream: {
+7 -1
View File
@@ -55,7 +55,13 @@ const patterns = [
const payloadPatterns = [/request entity too large/i, /payload too large/i, /request too large/i]
const exclusions = [/^(throttling error|service unavailable):/i, /rate limit/i, /too many requests/i]
const exclusions = [
/^(throttling error|service unavailable):/i,
/rate limit/i,
/too many requests/i,
// Cohere reports an output limit above the model maximum as "too many tokens"; compaction cannot fix it.
/max[_ ]tokens must be less than/i,
]
export const isContextOverflow = (message: string) =>
!exclusions.some((pattern) => pattern.test(message)) &&
@@ -1,15 +1,20 @@
import { Route, type RouteDefaultsInput } from "../route/client.js"
import { Endpoint } from "../route/endpoint.js"
import type { ProviderPackage } from "../provider-package.js"
import { AnthropicMessages } from "../protocols/anthropic-messages.js"
import { OpenAIChat } from "../protocols/openai-chat.js"
import { OpenResponses } from "../protocols/open-responses.js"
import { BedrockAuth, type Credentials } from "../protocols/utils/bedrock-auth.js"
import { claudeVersion } from "../protocols/utils/claude-model.js"
import { ProviderConfigurationError, ProviderID, type ModelID } from "../schema/index.js"
import { withOpenAIOptions, type OpenAIProviderOptionsInput } from "./openai-options.js"
export const id = ProviderID.make("amazon-bedrock")
export type Config = RouteDefaultsInput & {
export type OpenAIOptionsInput = OpenAIProviderOptionsInput
export type MessagesOptionsInput = AnthropicMessages.ProviderOptionsInput
export type Config = Omit<RouteDefaultsInput, "providerOptions"> & {
/** Bedrock API key. Falls back to `AWS_BEARER_TOKEN_BEDROCK`; bearer auth takes precedence over SigV4. */
readonly apiKey?: string
/** `sigv4` ignores `apiKey` fallbacks from the environment; `bearer` requires a token. */
@@ -20,11 +25,11 @@ export type Config = RouteDefaultsInput & {
/** Shared config profile for the default credential chain. */
readonly profile?: string
readonly region?: string
readonly providerOptions?: OpenAIProviderOptionsInput
readonly providerOptions?: OpenAIProviderOptionsInput | AnthropicMessages.ProviderOptionsInput
}
export type Settings = ProviderPackage.Settings &
OpenAIProviderOptionsInput & {
export type Settings<Options = OpenAIProviderOptionsInput> = ProviderPackage.Settings &
Options & {
readonly apiKey?: string
readonly auth?: "bearer" | "sigv4"
readonly baseURL?: string
@@ -34,6 +39,8 @@ export type Settings = ProviderPackage.Settings &
readonly topP?: number
}
export type MessagesSettings = Settings<AnthropicMessages.ProviderOptionsInput>
const responsesRoute = Route.make({
id: "bedrock-mantle-responses",
provider: id,
@@ -50,12 +57,35 @@ const chatRoute = OpenAIChat.route.with({
providerMetadataKey: "mantle",
})
export const routes = [responsesRoute, chatRoute]
const messagesRoute = Route.make({
id: "bedrock-mantle-messages",
provider: id,
providerMetadataKey: "mantle",
protocol: {
...AnthropicMessages.protocol,
// Mantle rejects mid-conversation `output_config` on Opus 5.0; support starts at 5.1+.
supportsEffortUpdates: (request) => {
const override = request.model.compatibility?.supportsEffortUpdates
if (override !== undefined) return override
const version = claudeVersion(request.model.id)
return version !== undefined && (version.major > 5 || (version.major === 5 && version.minor >= 1))
},
},
endpoint: Endpoint.path(AnthropicMessages.PATH),
transport: AnthropicMessages.transport<AnthropicMessages.AnthropicMessagesBody>(),
headers: () => ({ "anthropic-version": "2023-06-01" }),
})
const configuredRoute = <Body, Prepared>(route: Route<Body, Prepared>, input: Config) => {
export const routes = [responsesRoute, chatRoute, messagesRoute]
const configuredRoute = <Body, Prepared>(
route: Route<Body, Prepared>,
input: Config,
defaultBaseURL = (region: string) => `https://bedrock-mantle.${region}.api.aws/v1`,
) => {
const region = BedrockAuth.resolveRegion(input)
return route.with({
endpoint: { baseURL: input.baseURL ?? `https://bedrock-mantle.${region}.api.aws/v1` },
endpoint: { baseURL: input.baseURL ?? defaultBaseURL(region) },
auth: BedrockAuth.resolveAuth(input, region, {
service: "bedrock-mantle",
name: "Bedrock Mantle",
@@ -87,6 +117,11 @@ export const configure = (input: Config = {}) => {
})
const configuredResponsesRoute = configuredRoute(responsesRoute, input)
const configuredChatRoute = configuredRoute(chatRoute, input)
const configuredMessagesRoute = configuredRoute(
messagesRoute,
input,
(region) => `https://bedrock-mantle.${region}.api.aws/anthropic/v1`,
)
const modelDefaults = defaults(input)
const responses = (modelID: string | ModelID) =>
configuredResponsesRoute
@@ -96,11 +131,14 @@ export const configure = (input: Config = {}) => {
configuredChatRoute
.with(withOpenAIOptions(modelID, modelDefaults))
.model<OpenAIProviderOptionsInput>({ id: modelID })
const messages = (modelID: string | ModelID) =>
configuredMessagesRoute.with(modelDefaults).model<AnthropicMessages.ProviderOptionsInput>({ id: modelID })
return {
id,
model: responses,
chat,
messages,
responses,
configure,
}
@@ -119,7 +157,7 @@ const fromSettings = ({
region,
topP,
...providerOptions
}: Settings) =>
}: Settings<Config["providerOptions"]>) =>
configure({
apiKey,
auth,
@@ -137,6 +175,10 @@ export const chatModel: ProviderPackage.Definition<Settings, OpenAIProviderOptio
modelID,
settings,
) => fromSettings(settings).chat(modelID)
export const messagesModel: ProviderPackage.Definition<
MessagesSettings,
AnthropicMessages.ProviderOptionsInput
>["model"] = (modelID, settings) => fromSettings(settings).messages(modelID)
export const responsesModel: ProviderPackage.Definition<Settings, OpenAIProviderOptionsInput>["model"] = (
modelID,
settings,
@@ -0,0 +1,2 @@
export { messagesModel as model } from "../../amazon-bedrock-mantle.js"
export type { MessagesSettings as Settings } from "../../amazon-bedrock-mantle.js"
+66
View File
@@ -0,0 +1,66 @@
import { CohereChat } from "../protocols/cohere-chat.js"
import { OpenAIChat } from "../protocols/openai-chat.js"
import { Route, type RouteDefaultsInput } from "../route/client.js"
import { Endpoint } from "../route/endpoint.js"
import { AuthOptions, type ProviderAuthOption } from "../route/auth-options.js"
import { ProviderID, type ModelID, type OpenString } from "../schema/index.js"
import type { ProviderPackage } from "../provider-package.js"
export const id = ProviderID.make("cohere")
const COMPATIBILITY_BASE_URL = "https://api.cohere.ai/compatibility/v1"
export type ChatOptionsInput = { readonly reasoningEffort?: OpenString<"none" | "high"> }
export type ProviderOptions = CohereChat.ProviderOptionsInput & ChatOptionsInput
export type LanguageModelOptions = Omit<RouteDefaultsInput, "providerOptions"> &
ProviderAuthOption<"optional"> & {
readonly baseURL?: string
readonly providerOptions?: ProviderOptions
}
export type Settings<Options = CohereChat.ProviderOptionsInput> = ProviderPackage.Settings &
Options & { readonly apiKey?: string; readonly baseURL?: string }
export const route = CohereChat.route
export const chatRoute = Route.make({
id: "cohere-chat-completions",
provider: id,
providerMetadataKey: "cohere",
protocol: OpenAIChat.protocol,
endpoint: Endpoint.path("/chat/completions", { baseURL: COMPATIBILITY_BASE_URL }),
framing: OpenAIChat.framing,
})
export const routes = [route, chatRoute]
export const configure = (input: LanguageModelOptions = {}) => {
const { apiKey: _apiKey, auth: _auth, baseURL, ...defaults } = input
const auth = AuthOptions.bearer(input, "COHERE_API_KEY")
const native = route.with({ ...defaults, auth, endpoint: { baseURL: baseURL ?? CohereChat.DEFAULT_BASE_URL } })
const chat = chatRoute.with({ ...defaults, auth, endpoint: { baseURL: baseURL ?? COMPATIBILITY_BASE_URL } })
return {
id,
model: (modelID: string | ModelID) => native.model<CohereChat.ProviderOptionsInput>({ id: modelID }),
chat: (modelID: string | ModelID) =>
chat.model<ChatOptionsInput>({
id: modelID,
compatibility: {
maxTokensField: "max_tokens",
supportsStore: false,
supportsUsageInStreaming: true,
reasoningField: "reasoning_content",
supportsStrictMode: false,
},
}),
configure,
}
}
export const provider = configure()
export const model: ProviderPackage.Definition<Settings, CohereChat.ProviderOptionsInput>["model"] = (
modelID,
{ apiKey, baseURL, body, headers, ...providerOptions },
) =>
configure({
apiKey,
baseURL,
headers,
http: body === undefined ? undefined : { body: { ...body } },
providerOptions,
}).model(modelID)
export * as Cohere from "./cohere.js"
+16
View File
@@ -0,0 +1,16 @@
import type { ProviderPackage } from "../../provider-package.js"
import { Cohere } from "../cohere.js"
export type Settings = Cohere.Settings<Cohere.ChatOptionsInput>
export const model: ProviderPackage.Definition<Settings, Cohere.ChatOptionsInput>["model"] = (
modelID,
{ apiKey, baseURL, body, headers, ...providerOptions },
) =>
Cohere.configure({
apiKey,
baseURL,
headers,
http: body === undefined ? undefined : { body: { ...body } },
providerOptions,
}).chat(modelID)
+12 -2
View File
@@ -5,6 +5,7 @@ import { MediaRoute } from "../route/media.js"
import type { ProviderPackage } from "../provider-package.js"
import { ProviderID, type ModelID } from "../schema/index.js"
import { Gemini } from "../protocols/gemini.js"
import { GoogleInteractions } from "../protocols/google-interactions.js"
import { GoogleImages } from "../protocols/google-images.js"
import { GoogleSpeech } from "../protocols/google-speech.js"
import { GoogleTranscription } from "../protocols/google-transcription.js"
@@ -16,15 +17,16 @@ export type { GoogleTranscriptionOptions } from "../protocols/google-transcripti
export type { GoogleVideoOptions } from "../protocols/google-video.js"
export type GeminiOptionsInput = Gemini.OptionsInput
export type GeminiProviderOptionsInput = Gemini.ProviderOptionsInput
export type GoogleInteractionsOptionsInput = GoogleInteractions.OptionsInput
export const id = ProviderID.make("google")
export const routes = [Gemini.route]
export const routes = [Gemini.route, GoogleInteractions.route]
export type Config = RouteDefaultsInput &
ProviderAuthOption<"optional"> & {
readonly baseURL?: string
readonly providerOptions?: Gemini.ProviderOptionsInput
readonly providerOptions?: Gemini.ProviderOptionsInput & GoogleInteractions.ProviderOptionsInput
}
export type Settings = ProviderPackage.Settings &
@@ -45,12 +47,19 @@ const configuredRoute = (input: Config) => {
return Gemini.route.with({ ...rest, endpoint: { baseURL }, auth: auth(input) })
}
const interactionsRoute = (input: Config) => {
const { apiKey: _, auth: _auth, baseURL, ...rest } = input
return GoogleInteractions.route.with({ ...rest, endpoint: { baseURL }, auth: auth(input) })
}
export const configure = (input: Config = {}) => {
const route = configuredRoute(input)
const media = MediaRoute.deployment(input, auth(input))
return {
id,
model: (modelID: string | ModelID) => route.model<Gemini.ProviderOptionsInput>({ id: modelID }),
interactions: (modelID: string | ModelID) =>
interactionsRoute(input).model<GoogleInteractions.ProviderOptionsInput>({ id: modelID }),
image: (modelID: string | ModelID) => GoogleImages.model({ ...media, id: modelID }),
video: (modelID: string | ModelID) => GoogleVideo.model({ ...media, id: modelID }),
speech: (modelID: string | ModelID) => GoogleSpeech.model({ ...media, id: modelID }),
@@ -73,6 +82,7 @@ export const model: ProviderPackage.Definition<Settings, Gemini.ProviderOptionsI
}).model(modelID)
export const image = provider.image
export const interactions = provider.interactions
export const video = provider.video
export const speech = provider.speech
export const transcription = provider.transcription
@@ -0,0 +1,21 @@
import { configure } from "../google.js"
import type { ProviderPackage } from "../../provider-package.js"
import type { GoogleInteractions } from "../../protocols/google-interactions.js"
export type Settings = ProviderPackage.Settings &
GoogleInteractions.ProviderOptionsInput & {
readonly apiKey?: string
readonly baseURL?: string
}
export const model: ProviderPackage.Definition<Settings, GoogleInteractions.ProviderOptionsInput>["model"] = (
modelID,
{ apiKey, baseURL, body, headers, ...providerOptions },
) =>
configure({
apiKey,
baseURL,
headers: headers === undefined ? undefined : { ...headers },
http: body === undefined ? undefined : { body: { ...body } },
providerOptions,
}).interactions(modelID)
+1
View File
@@ -9,6 +9,7 @@ export * as Baseten from "./baseten.js"
export * as BlackForestLabs from "./black-forest-labs.js"
export * as Cartesia from "./cartesia.js"
export * as Cerebras from "./cerebras.js"
export * as Cohere from "./cohere.js"
export * as CloudflareAIGateway from "./cloudflare-ai-gateway.js"
export * as CloudflareWorkersAI from "./cloudflare-workers-ai.js"
export * as DeepInfra from "./deepinfra.js"
+1 -1
View File
@@ -50,7 +50,7 @@ export const gpt5DefaultOptions = (modelID: string): ProviderOptions | undefined
export const openAIDefaultOptions = (modelID: string): ProviderOptions | undefined =>
mergeProviderOptions(openAIProviderOptions({ store: false }), gpt5DefaultOptions(modelID))
export const withOpenAIOptions = <Options extends { readonly providerOptions?: OpenAIProviderOptionsInput }>(
export const withOpenAIOptions = <Options extends { readonly providerOptions?: ProviderOptions }>(
modelID: string,
options: Options,
): Omit<Options, "providerOptions"> & { readonly providerOptions?: ProviderOptions } => {
+2 -5
View File
@@ -358,7 +358,6 @@ function makeFromTransport<Body, Prepared, Frame, Event, State>(
input: MakeTransportInput<Body, Prepared, Frame, Event, State>,
): Route<Body, Prepared> {
const protocol = input.protocol
const encodeBody = Schema.encodeSync(Schema.fromJsonString(protocol.body.schema))
const decodeEventEffect = Schema.decodeUnknownEffect(protocol.stream.event)
const decodeEvent = (route: string) => (frame: Frame) =>
decodeEventEffect(frame).pipe(
@@ -417,7 +416,7 @@ function makeFromTransport<Body, Prepared, Frame, Event, State>(
request,
endpoint: routeInput.endpoint,
auth: routeInput.auth ?? Auth.none,
encodeBody,
encodeBody: ProviderShared.encodeJson,
middleware: options?.http,
webSocket: options?.webSocket,
}),
@@ -576,9 +575,7 @@ const compile = Effect.fn("LLM.compile")(function* (request: LLMRequest, options
const resolved = prepareRequest(request)
const route = resolved.model.route
const body = yield* route.body
.from(resolved)
.pipe(Effect.flatMap(ProviderShared.validateWith(Schema.decodeUnknownEffect(route.body.schema))))
const body = yield* route.body.from(resolved)
const prepared = yield* route.prepareTransport(body, resolved, options)
return {
+27 -31
View File
@@ -1,5 +1,5 @@
import { Effect, Stream } from "effect"
import { makeParser, type Event } from "effect/unstable/encoding/Sse"
import { makeParser } from "effect/unstable/encoding/Sse"
import { AIError, InvalidProviderOutputError } from "../schema/index.js"
/**
@@ -42,43 +42,39 @@ export const sseFraming = (
Stream.decodeText(),
Stream.mapAccumEffect(
() => {
const output: Event[] = []
const output: string[] = []
return {
output,
parser: makeParser((event) => {
if (event._tag === "Event") output.push(event)
if (
event._tag === "Event" &&
(events === undefined || events.has(event.event)) &&
event.data.length > 0 &&
// Some OpenAI-compatible proxies serialize an empty flush as a bare
// `data: null`, between events or after `[DONE]`. No protocol has a
// null event, so it carries nothing and must not abort the stream.
event.data !== "null" &&
// Vertex AI partner models (e.g. `xai/grok-4.6`) send their SSE
// keepalive comment as `data: : keepalive` while reasoning.
event.data !== ": keepalive" &&
(event.data !== "[DONE]" || includeDone || (events !== undefined && event.event !== "message"))
)
output.push(event.data)
}),
}
},
(state, chunk) =>
Effect.gen(function* () {
const error = state.parser.feed(chunk)
if (error)
return yield* new AIError({
reason: new InvalidProviderOutputError({
route: "sse",
message: error.message,
body: chunk,
cause: error,
}),
})
return [state, state.output.splice(0)] as const
}),
(state, chunk) => {
const error = state.parser.feed(chunk)
if (!error) return Effect.succeed([state, state.output.splice(0)] as const)
const reason = new InvalidProviderOutputError({
route: "sse",
message: error.message,
body: chunk,
cause: error,
})
return Effect.fail(new AIError({ reason }))
},
),
Stream.filter(
(event) =>
(events === undefined || events.has(event.event)) &&
event.data.length > 0 &&
// Some OpenAI-compatible proxies serialize an empty flush as a bare
// `data: null`, between events or after `[DONE]`. No protocol has a
// null event, so it carries nothing and must not abort the stream.
event.data !== "null" &&
// Vertex AI partner models (e.g. `xai/grok-4.6`) send their SSE
// keepalive comment as `data: : keepalive` while reasoning.
event.data !== ": keepalive" &&
(event.data !== "[DONE]" || includeDone || (events !== undefined && event.event !== "message")),
),
Stream.map((event) => event.data),
)
/** Server-Sent Events framing. Used by every JSON-streaming HTTP provider. */
-1
View File
@@ -14,7 +14,6 @@ import * as GoogleVertexChat from "../src/providers/google-vertex-chat.js"
import * as GoogleVertexMessages from "../src/providers/google-vertex-messages.js"
import * as GoogleVertexResponses from "../src/providers/google-vertex-responses.js"
import * as OpenAI from "../src/providers/openai.js"
import * as OpenAICompatible from "../src/providers/openai-compatible.js"
import * as OpenRouter from "../src/providers/openrouter.js"
import * as XAI from "../src/providers/xai.js"
+27 -3
View File
@@ -1,13 +1,12 @@
import { describe, expect, test } from "bun:test"
import { Effect } from "effect"
import { LLM, LLMRequest, Message, ToolCallPart } from "../src/index.js"
import { LLM, Message, ToolCallPart } from "../src/index.js"
import { Auth, LLMClient } from "../src/route.js"
import { compileRequest } from "../src/route/client.js"
import { AnthropicMessages } from "../src/protocols/anthropic-messages.js"
import { OpenAIResponses } from "../src/protocols/openai-responses.js"
import { Gemini } from "../src/protocols/gemini.js"
import { GoogleVertexMessages, OpenAI } from "../src/providers.js"
import { applyCachePolicy } from "../src/cache-policy.js"
import { AmazonBedrockMantle, GoogleVertexMessages, OpenAI } from "../src/providers.js"
import { applyEffortUpdates } from "../src/effort-updates.js"
import { it, testEffect } from "./lib/effect.js"
import { dynamicResponse } from "./lib/http.js"
@@ -242,6 +241,31 @@ describe("Anthropic Messages effort updates", () => {
}),
)
it.effect("strips markers for Opus 5.0 on Bedrock Mantle Messages while lowering Opus 5.5", () =>
Effect.gen(function* () {
const mantle = AmazonBedrockMantle.configure({ apiKey: "test", region: "us-east-1" })
const opus50 = yield* compileRequest(
LLM.request({
model: mantle.messages("anthropic.claude-opus-5"),
messages: conversation,
providerOptions: { effort: "low" },
}),
)
const opus55 = yield* compileRequest(
LLM.request({
model: mantle.messages("anthropic.claude-opus-5-5"),
messages: conversation,
providerOptions: { effort: "low" },
}),
)
expect(systemMessages(opus50.body)).toHaveLength(0)
expect(opus50.body.output_config).toEqual({ effort: "low" })
expect(systemMessages(opus55.body)).toEqual([{ role: "system", content: [], output_config: { effort: "low" } }])
expect(opus55.body.output_config).toEqual({ effort: "high" })
}),
)
it.effect("strips markers on the Vertex Anthropic route, whose protocol wrapper does not forward support", () =>
Effect.gen(function* () {
const prepared = yield* compileRequest(
@@ -1,29 +0,0 @@
{
"version": 1,
"metadata": {
"name": "anthropic-messages/accepts-malformed-assistant-tool-order-with-default-patch",
"recordedAt": "2026-05-05T20:09:16.245Z",
"tags": ["prefix:anthropic-messages", "provider:anthropic", "protocol:anthropic-messages", "tool"]
},
"interactions": [
{
"transport": "http",
"request": {
"method": "POST",
"url": "https://api.anthropic.com/v1/messages",
"headers": {
"anthropic-version": "2023-06-01",
"content-type": "application/json"
},
"body": "{\"model\":\"claude-haiku-4-5-20251001\",\"messages\":[{\"role\":\"assistant\",\"content\":[{\"type\":\"text\",\"text\":\"I will check the weather.\"}]},{\"role\":\"assistant\",\"content\":[{\"type\":\"tool_use\",\"id\":\"call_1\",\"name\":\"get_weather\",\"input\":{\"city\":\"Paris\"}}]},{\"role\":\"user\",\"content\":[{\"type\":\"tool_result\",\"tool_use_id\":\"call_1\",\"content\":\"{\\\"temperature\\\":\\\"72F\\\"}\"}]},{\"role\":\"user\",\"content\":[{\"type\":\"text\",\"text\":\"Use that result to answer briefly.\",\"cache_control\":{\"type\":\"ephemeral\"}}]}],\"tools\":[{\"name\":\"get_weather\",\"description\":\"Get weather\",\"input_schema\":{\"type\":\"object\",\"properties\":{}}}],\"stream\":true,\"max_tokens\":4096}"
},
"response": {
"status": 200,
"headers": {
"content-type": "text/event-stream; charset=utf-8"
},
"body": "event: message_start\ndata: {\"type\":\"message_start\",\"message\":{\"model\":\"claude-haiku-4-5-20251001\",\"id\":\"msg_01SikJVFaMR1XLMtavUhvuog\",\"type\":\"message\",\"role\":\"assistant\",\"content\":[],\"stop_reason\":null,\"stop_sequence\":null,\"stop_details\":null,\"usage\":{\"input_tokens\":638,\"cache_creation_input_tokens\":0,\"cache_read_input_tokens\":0,\"cache_creation\":{\"ephemeral_5m_input_tokens\":0,\"ephemeral_1h_input_tokens\":0},\"output_tokens\":1,\"service_tier\":\"standard\",\"inference_geo\":\"not_available\"}} }\n\nevent: content_block_start\ndata: {\"type\":\"content_block_start\",\"index\":0,\"content_block\":{\"type\":\"text\",\"text\":\"\"} }\n\nevent: ping\ndata: {\"type\": \"ping\"}\n\nevent: content_block_delta\ndata: {\"type\":\"content_block_delta\",\"index\":0,\"delta\":{\"type\":\"text_delta\",\"text\":\"The\"} }\n\nevent: content_block_delta\ndata: {\"type\":\"content_block_delta\",\"index\":0,\"delta\":{\"type\":\"text_delta\",\"text\":\" weather in Paris is currently 72°F.\"} }\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\",\"stop_sequence\":null,\"stop_details\":null},\"usage\":{\"input_tokens\":638,\"cache_creation_input_tokens\":0,\"cache_read_input_tokens\":0,\"output_tokens\":14} }\n\nevent: message_stop\ndata: {\"type\":\"message_stop\" }\n\n"
}
}
]
}
@@ -1,56 +0,0 @@
{
"version": 1,
"metadata": {
"name": "anthropic-messages/claude-opus-4-7-drives-a-tool-loop",
"recordedAt": "2026-05-03T19:59:44.186Z",
"tags": [
"prefix:anthropic-messages",
"provider:anthropic",
"protocol:anthropic-messages",
"tool",
"tool-loop",
"golden",
"flagship"
]
},
"interactions": [
{
"transport": "http",
"request": {
"method": "POST",
"url": "https://api.anthropic.com/v1/messages",
"headers": {
"anthropic-version": "2023-06-01",
"content-type": "application/json"
},
"body": "{\"model\":\"claude-opus-4-7\",\"system\":[{\"type\":\"text\",\"text\":\"Use the get_weather tool, then answer in one short sentence.\"}],\"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}"
},
"response": {
"status": 200,
"headers": {
"content-type": "text/event-stream; charset=utf-8"
},
"body": "event: message_start\ndata: {\"type\":\"message_start\",\"message\":{\"model\":\"claude-opus-4-7\",\"id\":\"msg_01DgAEgLgB1ZhavZon4qGE1t\",\"type\":\"message\",\"role\":\"assistant\",\"content\":[],\"stop_reason\":null,\"stop_sequence\":null,\"stop_details\":null,\"usage\":{\"input_tokens\":798,\"cache_creation_input_tokens\":0,\"cache_read_input_tokens\":0,\"cache_creation\":{\"ephemeral_5m_input_tokens\":0,\"ephemeral_1h_input_tokens\":0},\"output_tokens\":0,\"service_tier\":\"standard\",\"inference_geo\":\"global\"}} }\n\nevent: content_block_start\ndata: {\"type\":\"content_block_start\",\"index\":0,\"content_block\":{\"type\":\"tool_use\",\"id\":\"toolu_01M8nJQQMxqpv1VaPYuJKT4j\",\"name\":\"get_weather\",\"input\":{},\"caller\":{\"type\":\"direct\"}} }\n\nevent: ping\ndata: {\"type\": \"ping\"}\n\nevent: content_block_delta\ndata: {\"type\":\"content_block_delta\",\"index\":0,\"delta\":{\"type\":\"input_json_delta\",\"partial_json\":\"\"} }\n\nevent: content_block_delta\ndata: {\"type\":\"content_block_delta\",\"index\":0,\"delta\":{\"type\":\"input_json_delta\",\"partial_json\":\"{\\\"city\\\": \"} }\n\nevent: content_block_delta\ndata: {\"type\":\"content_block_delta\",\"index\":0,\"delta\":{\"type\":\"input_json_delta\",\"partial_json\":\"\\\"Pa\"} }\n\nevent: content_block_delta\ndata: {\"type\":\"content_block_delta\",\"index\":0,\"delta\":{\"type\":\"input_json_delta\",\"partial_json\":\"ris\\\"}\"} }\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\",\"stop_sequence\":null,\"stop_details\":null},\"usage\":{\"input_tokens\":798,\"cache_creation_input_tokens\":0,\"cache_read_input_tokens\":0,\"output_tokens\":66} }\n\nevent: message_stop\ndata: {\"type\":\"message_stop\" }\n\n"
}
},
{
"transport": "http",
"request": {
"method": "POST",
"url": "https://api.anthropic.com/v1/messages",
"headers": {
"anthropic-version": "2023-06-01",
"content-type": "application/json"
},
"body": "{\"model\":\"claude-opus-4-7\",\"system\":[{\"type\":\"text\",\"text\":\"Use the get_weather tool, then answer in one short sentence.\"}],\"messages\":[{\"role\":\"user\",\"content\":[{\"type\":\"text\",\"text\":\"What is the weather in Paris?\"}]},{\"role\":\"assistant\",\"content\":[{\"type\":\"tool_use\",\"id\":\"toolu_01M8nJQQMxqpv1VaPYuJKT4j\",\"name\":\"get_weather\",\"input\":{\"city\":\"Paris\"}}]},{\"role\":\"user\",\"content\":[{\"type\":\"tool_result\",\"tool_use_id\":\"toolu_01M8nJQQMxqpv1VaPYuJKT4j\",\"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}"
},
"response": {
"status": 200,
"headers": {
"content-type": "text/event-stream; charset=utf-8"
},
"body": "event: message_start\ndata: {\"type\":\"message_start\",\"message\":{\"model\":\"claude-opus-4-7\",\"id\":\"msg_011KJqj32QjkrUAiBFxhmEoG\",\"type\":\"message\",\"role\":\"assistant\",\"content\":[],\"stop_reason\":null,\"stop_sequence\":null,\"stop_details\":null,\"usage\":{\"input_tokens\":895,\"cache_creation_input_tokens\":0,\"cache_read_input_tokens\":0,\"cache_creation\":{\"ephemeral_5m_input_tokens\":0,\"ephemeral_1h_input_tokens\":0},\"output_tokens\":5,\"service_tier\":\"standard\",\"inference_geo\":\"global\"}} }\n\nevent: content_block_start\ndata: {\"type\":\"content_block_start\",\"index\":0,\"content_block\":{\"type\":\"text\",\"text\":\"\"} }\n\nevent: ping\ndata: {\"type\": \"ping\"}\n\nevent: content_block_delta\ndata: {\"type\":\"content_block_delta\",\"index\":0,\"delta\":{\"type\":\"text_delta\",\"text\":\"Paris is curr\"} }\n\nevent: content_block_delta\ndata: {\"type\":\"content_block_delta\",\"index\":0,\"delta\":{\"type\":\"text_delta\",\"text\":\"ently sunny at 22°C.\"} }\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\",\"stop_sequence\":null,\"stop_details\":null},\"usage\":{\"input_tokens\":895,\"cache_creation_input_tokens\":0,\"cache_read_input_tokens\":0,\"output_tokens\":19}}\n\nevent: message_stop\ndata: {\"type\":\"message_stop\"}\n\n"
}
}
]
}
@@ -1,29 +0,0 @@
{
"version": 1,
"metadata": {
"name": "anthropic-messages/rejects-malformed-assistant-tool-order-without-patch",
"recordedAt": "2026-05-05T20:08:42.597Z",
"tags": ["prefix:anthropic-messages", "provider:anthropic", "protocol:anthropic-messages", "tool", "sad-path"]
},
"interactions": [
{
"transport": "http",
"request": {
"method": "POST",
"url": "https://api.anthropic.com/v1/messages",
"headers": {
"anthropic-version": "2023-06-01",
"content-type": "application/json"
},
"body": "{\"model\":\"claude-haiku-4-5-20251001\",\"messages\":[{\"role\":\"assistant\",\"content\":[{\"type\":\"tool_use\",\"id\":\"call_1\",\"name\":\"get_weather\",\"input\":{\"city\":\"Paris\"}},{\"type\":\"text\",\"text\":\"I will check the weather.\"}]},{\"role\":\"user\",\"content\":[{\"type\":\"tool_result\",\"tool_use_id\":\"call_1\",\"content\":\"{\\\"temperature\\\":\\\"72F\\\"}\"}]},{\"role\":\"user\",\"content\":[{\"type\":\"text\",\"text\":\"Use that result to answer briefly.\"}]}],\"tools\":[{\"name\":\"get_weather\",\"description\":\"Get weather\",\"input_schema\":{\"type\":\"object\",\"properties\":{}}}],\"stream\":true,\"max_tokens\":4096}"
},
"response": {
"status": 400,
"headers": {
"content-type": "application/json"
},
"body": "{\"type\":\"error\",\"error\":{\"type\":\"invalid_request_error\",\"message\":\"messages.1: `tool_use` ids were found without `tool_result` blocks immediately after: call_1. Each `tool_use` block must have a corresponding `tool_result` block in the next message.\"},\"request_id\":\"req_011Cak2XdJgnzxKCY2BC2Beh\"}"
}
}
]
}
@@ -1,29 +0,0 @@
{
"version": 1,
"metadata": {
"name": "anthropic-messages/streams-text",
"recordedAt": "2026-04-28T21:18:45.535Z",
"tags": ["prefix:anthropic-messages", "provider:anthropic", "protocol:anthropic-messages"]
},
"interactions": [
{
"transport": "http",
"request": {
"method": "POST",
"url": "https://api.anthropic.com/v1/messages",
"headers": {
"anthropic-version": "2023-06-01",
"content-type": "application/json"
},
"body": "{\"model\":\"claude-haiku-4-5-20251001\",\"system\":[{\"type\":\"text\",\"text\":\"You are concise.\"}],\"messages\":[{\"role\":\"user\",\"content\":[{\"type\":\"text\",\"text\":\"Reply with exactly: Hello!\"}]}],\"stream\":true,\"max_tokens\":20,\"temperature\":0}"
},
"response": {
"status": 200,
"headers": {
"content-type": "text/event-stream; charset=utf-8"
},
"body": "event: message_start\ndata: {\"type\":\"message_start\",\"message\":{\"model\":\"claude-haiku-4-5-20251001\",\"id\":\"msg_01UodR8c3ezAK8rAfi8HAs8g\",\"type\":\"message\",\"role\":\"assistant\",\"content\":[],\"stop_reason\":null,\"stop_sequence\":null,\"stop_details\":null,\"usage\":{\"input_tokens\":18,\"cache_creation_input_tokens\":0,\"cache_read_input_tokens\":0,\"cache_creation\":{\"ephemeral_5m_input_tokens\":0,\"ephemeral_1h_input_tokens\":0},\"output_tokens\":2,\"service_tier\":\"standard\",\"inference_geo\":\"not_available\"}} }\n\nevent: content_block_start\ndata: {\"type\":\"content_block_start\",\"index\":0,\"content_block\":{\"type\":\"text\",\"text\":\"\"} }\n\nevent: ping\ndata: {\"type\": \"ping\"}\n\nevent: content_block_delta\ndata: {\"type\":\"content_block_delta\",\"index\":0,\"delta\":{\"type\":\"text_delta\",\"text\":\"Hello!\"} }\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\",\"stop_sequence\":null,\"stop_details\":null},\"usage\":{\"input_tokens\":18,\"cache_creation_input_tokens\":0,\"cache_read_input_tokens\":0,\"output_tokens\":5} }\n\nevent: message_stop\ndata: {\"type\":\"message_stop\" }\n\n"
}
}
]
}
@@ -1,29 +0,0 @@
{
"version": 1,
"metadata": {
"name": "anthropic-messages/streams-tool-call",
"recordedAt": "2026-04-28T21:18:46.878Z",
"tags": ["prefix:anthropic-messages", "provider:anthropic", "protocol:anthropic-messages", "tool"]
},
"interactions": [
{
"transport": "http",
"request": {
"method": "POST",
"url": "https://api.anthropic.com/v1/messages",
"headers": {
"anthropic-version": "2023-06-01",
"content-type": "application/json"
},
"body": "{\"model\":\"claude-haiku-4-5-20251001\",\"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\":{\"model\":\"claude-haiku-4-5-20251001\",\"id\":\"msg_01RYgU7NUPMK4B9v8S7gVpCS\",\"type\":\"message\",\"role\":\"assistant\",\"content\":[],\"stop_reason\":null,\"stop_sequence\":null,\"stop_details\":null,\"usage\":{\"input_tokens\":677,\"cache_creation_input_tokens\":0,\"cache_read_input_tokens\":0,\"cache_creation\":{\"ephemeral_5m_input_tokens\":0,\"ephemeral_1h_input_tokens\":0},\"output_tokens\":16,\"service_tier\":\"standard\",\"inference_geo\":\"not_available\"}} }\n\nevent: content_block_start\ndata: {\"type\":\"content_block_start\",\"index\":0,\"content_block\":{\"type\":\"tool_use\",\"id\":\"toolu_012rmAruviySvUXSjgCPWVRu\",\"name\":\"get_weather\",\"input\":{},\"caller\":{\"type\":\"direct\"}} }\n\nevent: ping\ndata: {\"type\": \"ping\"}\n\nevent: content_block_delta\ndata: {\"type\":\"content_block_delta\",\"index\":0,\"delta\":{\"type\":\"input_json_delta\",\"partial_json\":\"\"} }\n\nevent: content_block_delta\ndata: {\"type\":\"content_block_delta\",\"index\":0,\"delta\":{\"type\":\"input_json_delta\",\"partial_json\":\"{\\\"city\\\":\"} }\n\nevent: content_block_delta\ndata: {\"type\":\"content_block_delta\",\"index\":0,\"delta\":{\"type\":\"input_json_delta\",\"partial_json\":\" \\\"Paris\\\"}\"} }\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\",\"stop_sequence\":null,\"stop_details\":null},\"usage\":{\"input_tokens\":677,\"cache_creation_input_tokens\":0,\"cache_read_input_tokens\":0,\"output_tokens\":33} }\n\nevent: message_stop\ndata: {\"type\":\"message_stop\" }\n\n"
}
}
]
}
@@ -0,0 +1,57 @@
{
"version": 1,
"metadata": {
"model": "anthropic.claude-opus-5-5",
"tags": [
"prefix:bedrock-mantle-messages",
"provider:amazon-bedrock",
"protocol:anthropic-messages",
"reasoning",
"effort-update"
],
"name": "bedrock-mantle-messages/applies-mid-conversation-effort-updates-and-thinking-block-binding-on-opus-5-5",
"recordedAt": "2026-10-04T03:56:23.139Z"
},
"interactions": [
{
"transport": "http",
"request": {
"method": "POST",
"url": "https://bedrock-mantle.us-east-1.api.aws/anthropic/v1/messages",
"headers": {
"anthropic-beta": "interleaved-thinking-2025-05-14,thinking-binding-controls-2026-08-01",
"anthropic-version": "2023-06-01",
"content-type": "application/json"
},
"body": "{\"model\":\"anthropic.claude-opus-5-5\",\"messages\":[{\"role\":\"user\",\"content\":[{\"type\":\"text\",\"text\":\"Compute 37 * 43 step by step, then reply with only the integer.\",\"cache_control\":{\"type\":\"ephemeral\"}}]}],\"stream\":true,\"max_tokens\":2048,\"thinking\":{\"type\":\"adaptive\",\"display\":\"summarized\",\"block_binding\":{\"prefix_mismatch_behavior\":\"drop_block\"}},\"output_config\":{\"effort\":\"high\"}}"
},
"response": {
"status": 200,
"headers": {
"content-type": "text/event-stream; charset=utf-8"
},
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"content-type": "text/event-stream"
},
"body": ": OPENROUTER PROCESSING\n\ndata: {\"id\":\"gen-1778031306-HYzOq04JIk1hZQ4iaNjD\",\"object\":\"chat.completion.chunk\",\"created\":1778031306,\"model\":\"openai/gpt-4o-mini\",\"provider\":\"OpenAI\",\"system_fingerprint\":\"fp_b6580bbee1\",\"choices\":[{\"index\":0,\"delta\":{\"content\":null,\"role\":\"assistant\",\"tool_calls\":[{\"index\":0,\"id\":\"call_L7mHMq49ZSUTBHjLJfBIP2eT\",\"type\":\"function\",\"function\":{\"name\":\"get_weather\",\"arguments\":\"\"}}]},\"finish_reason\":null,\"native_finish_reason\":null}]}\n\ndata: {\"id\":\"gen-1778031306-HYzOq04JIk1hZQ4iaNjD\",\"object\":\"chat.completion.chunk\",\"created\":1778031306,\"model\":\"openai/gpt-4o-mini\",\"provider\":\"OpenAI\",\"system_fingerprint\":\"fp_b6580bbee1\",\"choices\":[{\"index\":0,\"delta\":{\"content\":null,\"role\":\"assistant\",\"tool_calls\":[{\"index\":0,\"function\":{\"arguments\":\"\"}}]},\"finish_reason\":null,\"native_finish_reason\":null}]}\n\ndata: {\"id\":\"gen-1778031306-HYzOq04JIk1hZQ4iaNjD\",\"object\":\"chat.completion.chunk\",\"created\":1778031306,\"model\":\"openai/gpt-4o-mini\",\"provider\":\"OpenAI\",\"system_fingerprint\":\"fp_b6580bbee1\",\"choices\":[{\"index\":0,\"delta\":{\"content\":null,\"role\":\"assistant\",\"tool_calls\":[{\"index\":0,\"function\":{\"arguments\":\"{\\\"\"}}]},\"finish_reason\":null,\"native_finish_reason\":null}]}\n\ndata: {\"id\":\"gen-1778031306-HYzOq04JIk1hZQ4iaNjD\",\"object\":\"chat.completion.chunk\",\"created\":1778031306,\"model\":\"openai/gpt-4o-mini\",\"provider\":\"OpenAI\",\"system_fingerprint\":\"fp_b6580bbee1\",\"choices\":[{\"index\":0,\"delta\":{\"content\":null,\"role\":\"assistant\",\"tool_calls\":[{\"index\":0,\"function\":{\"arguments\":\"city\"}}]},\"finish_reason\":null,\"native_finish_reason\":null}]}\n\ndata: {\"id\":\"gen-1778031306-HYzOq04JIk1hZQ4iaNjD\",\"object\":\"chat.completion.chunk\",\"created\":1778031306,\"model\":\"openai/gpt-4o-mini\",\"provider\":\"OpenAI\",\"system_fingerprint\":\"fp_b6580bbee1\",\"choices\":[{\"index\":0,\"delta\":{\"content\":null,\"role\":\"assistant\",\"tool_calls\":[{\"index\":0,\"function\":{\"arguments\":\"\\\":\\\"\"}}]},\"finish_reason\":null,\"native_finish_reason\":null}]}\n\ndata: {\"id\":\"gen-1778031306-HYzOq04JIk1hZQ4iaNjD\",\"object\":\"chat.completion.chunk\",\"created\":1778031306,\"model\":\"openai/gpt-4o-mini\",\"provider\":\"OpenAI\",\"system_fingerprint\":\"fp_b6580bbee1\",\"choices\":[{\"index\":0,\"delta\":{\"content\":null,\"role\":\"assistant\",\"tool_calls\":[{\"index\":0,\"function\":{\"arguments\":\"Paris\"}}]},\"finish_reason\":null,\"native_finish_reason\":null}]}\n\ndata: {\"id\":\"gen-1778031306-HYzOq04JIk1hZQ4iaNjD\",\"object\":\"chat.completion.chunk\",\"created\":1778031306,\"model\":\"openai/gpt-4o-mini\",\"provider\":\"OpenAI\",\"system_fingerprint\":\"fp_b6580bbee1\",\"choices\":[{\"index\":0,\"delta\":{\"content\":null,\"role\":\"assistant\",\"tool_calls\":[{\"index\":0,\"function\":{\"arguments\":\"\\\"}\"}}]},\"finish_reason\":null,\"native_finish_reason\":null}]}\n\ndata: {\"id\":\"gen-1778031306-HYzOq04JIk1hZQ4iaNjD\",\"object\":\"chat.completion.chunk\",\"created\":1778031306,\"model\":\"openai/gpt-4o-mini\",\"provider\":\"OpenAI\",\"system_fingerprint\":\"fp_b6580bbee1\",\"choices\":[{\"index\":0,\"delta\":{\"content\":\"\",\"role\":\"assistant\"},\"finish_reason\":\"tool_calls\",\"native_finish_reason\":\"stop\"}]}\n\ndata: {\"id\":\"gen-1778031306-HYzOq04JIk1hZQ4iaNjD\",\"object\":\"chat.completion.chunk\",\"created\":1778031306,\"model\":\"openai/gpt-4o-mini\",\"provider\":\"OpenAI\",\"system_fingerprint\":\"fp_b6580bbee1\",\"choices\":[{\"index\":0,\"delta\":{\"content\":\"\",\"role\":\"assistant\"},\"finish_reason\":\"tool_calls\",\"native_finish_reason\":\"stop\"}],\"usage\":{\"prompt_tokens\":67,\"completion_tokens\":5,\"total_tokens\":72,\"cost\":0.00001305,\"is_byok\":false,\"prompt_tokens_details\":{\"cached_tokens\":0,\"cache_write_tokens\":0,\"audio_tokens\":0,\"video_tokens\":0},\"cost_details\":{\"upstream_inference_cost\":0.00001305,\"upstream_inference_prompt_cost\":0.00001005,\"upstream_inference_completions_cost\":0.000003},\"completion_tokens_details\":{\"reasoning_tokens\":0,\"image_tokens\":0,\"audio_tokens\":0}}}\n\ndata: [DONE]\n\n"
}
}
]
}
-1
View File
@@ -8,7 +8,6 @@ import {
type ProviderMetadata,
type ToolCallPart,
ToolResultPart,
type ToolResultValue,
type Usage,
} from "../../src/schema/index.js"
import { type Tools, toDefinitions } from "../../src/tool.js"
+22 -3
View File
@@ -39,9 +39,7 @@ describe("provider error classification", () => {
]
expect(failures).toEqual(
failures.map((failure) =>
expect.objectContaining({ _tag: "InvalidRequest", classification: "payload-too-large" }),
),
failures.map(() => expect.objectContaining({ _tag: "InvalidRequest", classification: "payload-too-large" })),
)
})
@@ -462,6 +460,27 @@ describe("provider error rawBody classification", () => {
expect(reason._tag === "InvalidRequest" ? reason.classification : reason._tag).toBe("context-overflow")
})
test("separates Cohere prompt overflow from output limit rejections", () => {
const classify = (message: string) => {
const reason = classifyProviderFailure({
message,
status: 400,
rawBody: JSON.stringify({ error_type: "TOO_MANY_TOKENS", message }),
})
return reason._tag === "InvalidRequest" ? reason.classification : reason._tag
}
expect(
classify(
"too many tokens: size limit exceeded by 168512 tokens. Try using shorter or fewer inputs. The limit for this model is 132000 tokens.",
),
).toBe("context-overflow")
expect(
classify(
"too many tokens: max tokens must be less than or equal to 4096, the maximum output length for this model - received 1000000.",
),
).toBeUndefined()
})
test("classifies invalid API keys reported as HTTP 400 as authentication failures", () => {
const rawBody = JSON.stringify({
error: {
+30 -68
View File
@@ -7,67 +7,6 @@ const configuration = (provider: string, message: string) =>
expect.objectContaining({ _tag: "ProviderConfiguration", provider, message })
describe("provider package entrypoints", () => {
test("semantic API aliases expose the same contract", async () => {
const modules = await Promise.all([
import("@opencode/ai/providers/openai"),
import("@opencode/ai/providers/openai/responses"),
import("@opencode/ai/providers/openai/chat"),
import("@opencode/ai/providers/anthropic"),
import("@opencode/ai/providers/anthropic-compatible"),
import("@opencode/ai/providers/openai-compatible"),
import("@opencode/ai/providers/openai-compatible/responses"),
import("@opencode/ai/providers/amazon-bedrock"),
import("@opencode/ai/providers/azure"),
import("@opencode/ai/providers/azure/responses"),
import("@opencode/ai/providers/azure/chat"),
import("@opencode/ai/providers/google"),
import("@opencode/ai/providers/google-vertex"),
import("@opencode/ai/providers/google-vertex/gemini"),
import("@opencode/ai/providers/google-vertex/chat"),
import("@opencode/ai/providers/google-vertex/responses"),
import("@opencode/ai/providers/google-vertex/messages"),
import("@opencode/ai/providers/openrouter"),
import("@opencode/ai/providers/xai"),
import("@opencode/ai/providers/amazon-bedrock/mantle"),
import("@opencode/ai/providers/amazon-bedrock/mantle/chat"),
import("@opencode/ai/providers/amazon-bedrock/mantle/responses"),
import("@opencode/ai/providers/togetherai"),
import("@opencode/ai/providers/cerebras"),
import("@opencode/ai/providers/deepinfra"),
import("@opencode/ai/providers/groq"),
import("@opencode/ai/providers/baseten"),
import("@opencode/ai/providers/deepseek"),
import("@opencode/ai/providers/fireworks"),
import("@opencode/ai/providers/cloudflare-ai-gateway"),
import("@opencode/ai/providers/cloudflare-workers-ai"),
import("@opencode/ai/providers/minimax"),
import("@opencode/ai/providers/minimax/messages"),
import("@opencode/ai/providers/minimax/chat"),
import("@opencode/ai/providers/minimax/responses"),
import("@opencode/ai/providers/moonshot"),
import("@opencode/ai/providers/moonshot/chat"),
import("@opencode/ai/providers/moonshot/messages"),
import("@opencode/ai/providers/moonshot/responses"),
import("@opencode/ai/providers/zai"),
import("@opencode/ai/providers/zai/chat"),
import("@opencode/ai/providers/zai-coding-plan"),
import("@opencode/ai/providers/zai-coding-plan/chat"),
import("@opencode/ai/providers/zai-coding-plan/messages"),
import("@opencode/ai/providers/zai-coding-plan/responses"),
import("@opencode/ai/providers/alibaba"),
import("@opencode/ai/providers/alibaba/chat"),
import("@opencode/ai/providers/alibaba/messages"),
import("@opencode/ai/providers/alibaba/responses"),
])
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)
expect(modules[19].model).toBe(modules[21].model)
expect(modules[19].model).not.toBe(modules[20].model)
})
test("maps Alibaba API entrypoints onto explicit regional routes", async () => {
const modules = await Promise.all([
import("@opencode/ai/providers/alibaba"),
@@ -75,7 +14,6 @@ describe("provider package entrypoints", () => {
import("@opencode/ai/providers/alibaba/messages"),
import("@opencode/ai/providers/alibaba/responses"),
])
expect(modules[0].model).toBe(modules[1].model)
const settings = {
region: "eu-central-1",
workspaceID: "llm-fixture",
@@ -103,7 +41,6 @@ describe("provider package entrypoints", () => {
import("@opencode/ai/providers/moonshot/messages"),
import("@opencode/ai/providers/moonshot/responses"),
])
expect(modules[0].model).toBe(modules[1].model)
const settings = {
apiKey: "fixture",
baseURL: "https://gateway.example/v1",
@@ -121,6 +58,25 @@ describe("provider package entrypoints", () => {
})
})
test("maps Cohere entrypoints onto native and compatibility routes", async () => {
const modules = await Promise.all([
import("@opencode/ai/providers/cohere"),
import("@opencode/ai/providers/cohere/chat"),
])
const settings = { apiKey: "fixture", headers: { "x-test": "fixture" }, body: { future_option: true } }
const routes = [
["cohere-chat", "https://api.cohere.com/v2"],
["cohere-chat-completions", "https://api.cohere.ai/compatibility/v1"],
]
modules.forEach((module, index) => {
const selected = module.model("command-a-03-2025", settings)
expect(selected.provider).toBe("cohere")
expect([selected.route.id, selected.route.endpoint.baseURL]).toEqual(routes[index])
expect(selected.route.defaults.headers).toEqual(settings.headers)
expect(selected.route.defaults.http?.body).toEqual(settings.body)
})
})
test("maps MiniMax API entrypoints onto provider-owned routes", async () => {
const modules = await Promise.all([
import("@opencode/ai/providers/minimax"),
@@ -128,7 +84,6 @@ describe("provider package entrypoints", () => {
import("@opencode/ai/providers/minimax/chat"),
import("@opencode/ai/providers/minimax/responses"),
])
expect(modules[0].model).toBe(modules[1].model)
const settings = {
apiKey: "fixture",
baseURL: "https://gateway.example/v1",
@@ -155,8 +110,6 @@ describe("provider package entrypoints", () => {
import("@opencode/ai/providers/zai-coding-plan/messages"),
import("@opencode/ai/providers/zai-coding-plan/responses"),
])
expect(modules[0].model).toBe(modules[1].model)
expect(modules[2].model).toBe(modules[3].model)
const routes = [
"zai-chat",
"zai-chat",
@@ -411,6 +364,7 @@ describe("provider package entrypoints", () => {
test("maps Google package settings onto the Gemini model", async () => {
const Google = await import("@opencode/ai/providers/google")
const GoogleInteractions = await import("@opencode/ai/providers/google/interactions")
const selected = Google.model("gemini-2.5-flash", {
apiKey: "fixture",
baseURL: "https://generativelanguage.test/v1beta",
@@ -424,11 +378,20 @@ describe("provider package entrypoints", () => {
expect(selected.route.defaults.headers).toEqual({ "x-application": "opencode" })
expect(selected.route.defaults.http?.body).toEqual({ safetySettings: [] })
expect(selected.route.defaults.providerOptions).toEqual({ thinkingConfig: { thinkingBudget: 1_024 } })
const interactions = GoogleInteractions.model("gemini-3.8-flash", {
apiKey: "fixture",
baseURL: "https://generativelanguage.test/v1beta",
thinkingLevel: "low",
store: true,
})
expect(interactions.route.id).toBe("google-interactions")
expect(interactions.route.endpoint.baseURL).toBe("https://generativelanguage.test/v1beta")
expect(interactions.route.defaults.providerOptions).toEqual({ thinkingLevel: "low", store: true })
expect(Google.configure().interactions("gemini-3.8-flash").route.protocol).toBe("google-interactions")
})
test("selects Vertex entrypoints with the same model contract", async () => {
const GoogleVertex = await import("@opencode/ai/providers/google-vertex")
const GoogleVertexGemini = await import("@opencode/ai/providers/google-vertex/gemini")
const GoogleVertexChat = await import("@opencode/ai/providers/google-vertex/chat")
const GoogleVertexResponses = await import("@opencode/ai/providers/google-vertex/responses")
const GoogleVertexMessages = await import("@opencode/ai/providers/google-vertex/messages")
@@ -453,7 +416,6 @@ describe("provider package entrypoints", () => {
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")
@@ -21,7 +21,6 @@ import {
import { LLMClient } from "../../src/route.js"
import { compileRequest } from "../../src/route/client.js"
import { AmazonBedrock } from "../../src/providers.js"
import * as BedrockConverse from "../../src/protocols/bedrock-converse.js"
import { it } from "../lib/effect.js"
import { withProcessEnv } from "../lib/env.js"
import { dynamicResponse, fixedResponse } from "../lib/http.js"
+254 -21
View File
@@ -1,9 +1,8 @@
import { describe, expect } from "bun:test"
import { Effect } from "effect"
import { HttpClientRequest } from "effect/unstable/http"
import { LLM, Message } from "../../src/index.js"
import { LLM, LLMEvent, LLMRequest, Message, ToolDefinition } from "../../src/index.js"
import { AmazonBedrockMantle } from "../../src/providers.js"
import { model } from "../../src/providers/amazon-bedrock/mantle.js"
import { OpenResponses } from "../../src/protocols/open-responses.js"
import { compileRequest, LLMClient } from "../../src/route/client.js"
import { it } from "../lib/effect.js"
@@ -19,14 +18,14 @@ const credentials = {
}
describe("Amazon Bedrock Mantle provider", () => {
it.effect("uses Responses by default and exposes Chat explicitly", () =>
it.effect("uses Responses by default and exposes Chat and Messages explicitly", () =>
Effect.gen(function* () {
const provider = AmazonBedrockMantle.configure({ credentials })
expect(provider.model).toBe(provider.responses)
expect(AmazonBedrockMantle.model).toBe(AmazonBedrockMantle.responsesModel)
expect(model).toBe(AmazonBedrockMantle.responsesModel)
expect(provider.model("openai.gpt-oss-120b").route.transport).toBe(OpenResponses.httpTransport)
const chat = yield* compileRequest(LLM.request({ model: provider.chat("openai.gpt-oss-120b"), prompt: "Hi" }))
const messages = yield* compileRequest(
LLM.request({ model: provider.messages("anthropic.claude-opus-4-8"), prompt: "Hi", cache: "none" }),
)
const responses = yield* compileRequest(
LLM.request({ model: provider.model("openai.gpt-oss-120b"), prompt: "Hi" }),
)
@@ -36,6 +35,11 @@ describe("Amazon Bedrock Mantle provider", () => {
protocol: "openai-chat",
body: { model: "openai.gpt-oss-120b" },
})
expect(messages).toMatchObject({
route: "bedrock-mantle-messages",
protocol: "anthropic-messages",
body: { model: "anthropic.claude-opus-4-8", stream: true },
})
expect(responses).toMatchObject({
route: "bedrock-mantle-responses",
protocol: "open-responses",
@@ -43,43 +47,77 @@ describe("Amazon Bedrock Mantle provider", () => {
})
expect(provider.model("openai.gpt-oss-120b").route.providerMetadataKey).toBe("mantle")
expect(provider.chat("openai.gpt-oss-120b").route.providerMetadataKey).toBe("mantle")
expect(provider.messages("anthropic.claude-opus-4-8").route.providerMetadataKey).toBe("mantle")
}),
)
it.effect("preserves configured top-p generation defaults for Chat and Responses", () =>
it.effect("preserves configured top-p generation defaults for Chat, Messages, and Responses", () =>
Effect.gen(function* () {
const settings = { apiKey: "test-key", topP: 0.8 }
const chat = yield* compileRequest(
LLM.request({ model: AmazonBedrockMantle.chatModel("openai.gpt-oss-safeguard-20b", settings), prompt: "Hi" }),
)
const messages = yield* compileRequest(
LLM.request({ model: AmazonBedrockMantle.messagesModel("anthropic.claude-opus-4-8", settings), prompt: "Hi" }),
)
const responses = yield* compileRequest(
LLM.request({ model: AmazonBedrockMantle.responsesModel("openai.gpt-oss-120b", settings), prompt: "Hi" }),
)
expect(chat.body.top_p).toBe(0.8)
expect(messages.body.top_p).toBe(0.8)
expect(responses.body.top_p).toBe(0.8)
}),
)
it.effect("uses the Mantle endpoint and signing service", () =>
it.effect("uses the Mantle endpoint and signing service across Responses and Messages", () =>
Effect.gen(function* () {
const seen: Array<{ readonly url: string; readonly authorization: string | undefined }> = []
const model = AmazonBedrockMantle.configure({ credentials, region: "us-west-1" }).responses("openai.gpt-oss-120b")
yield* LLMClient.generate(LLM.request({ model, prompt: "Hi" })).pipe(
Effect.provide(
dynamicResponse((input) =>
Effect.gen(function* () {
const request = yield* HttpClientRequest.toWeb(input.request)
seen.push({ url: request.url, authorization: request.headers.get("authorization") ?? undefined })
return input.respond("", { headers: { "content-type": "text/event-stream" } })
}),
const configured = AmazonBedrockMantle.configure({ credentials, region: "us-west-1" })
for (const selected of [
configured.responses("openai.gpt-oss-120b"),
configured.messages("anthropic.claude-opus-4-8"),
]) {
yield* LLMClient.generate(LLM.request({ model: selected, prompt: "Hi" })).pipe(
Effect.provide(
dynamicResponse((input) =>
Effect.gen(function* () {
const request = yield* HttpClientRequest.toWeb(input.request)
seen.push({ url: request.url, authorization: request.headers.get("authorization") ?? undefined })
return input.respond("", { headers: { "content-type": "text/event-stream" } })
}),
),
),
),
Effect.flip,
Effect.flip,
)
}
expect(seen.map((item) => item.url)).toEqual([
"https://bedrock-mantle.us-west-1.api.aws/v1/responses",
"https://bedrock-mantle.us-west-1.api.aws/anthropic/v1/messages",
])
expect(seen.every((item) => item.authorization?.includes("/us-west-1/bedrock-mantle/aws4_request"))).toBe(true)
}).pipe(withProcessEnv({ AWS_BEARER_TOKEN_BEDROCK: undefined })),
)
it.effect("applies inline cache breakpoints on Mantle Messages", () =>
Effect.gen(function* () {
const model = AmazonBedrockMantle.configure({ apiKey: "test-key" }).messages("anthropic.claude-opus-4-8")
const prepared = yield* compileRequest(
LLM.request({
model,
system: "You are concise.",
messages: [Message.user("Hello")],
cache: "auto",
}),
)
expect(seen[0]?.url).toBe("https://bedrock-mantle.us-west-1.api.aws/v1/responses")
expect(seen[0]?.authorization).toContain("/us-west-1/bedrock-mantle/aws4_request")
expect(prepared.body.system).toEqual([
{ type: "text", text: "You are concise.", cache_control: { type: "ephemeral" } },
])
expect(prepared.body.messages).toEqual([
{ role: "user", content: [{ type: "text", text: "Hello", cache_control: { type: "ephemeral" } }] },
])
}),
)
@@ -201,3 +239,198 @@ describe("Amazon Bedrock Mantle recorded", () => {
}),
)
})
const recordedMessages = recordedTests({
prefix: "bedrock-mantle-messages",
provider: "amazon-bedrock",
protocol: "anthropic-messages",
requires: ["AWS_BEARER_TOKEN_BEDROCK"],
options: { redact: { allowRequestHeaders: ["anthropic-version", "anthropic-beta"] } },
})
const mantleMessages = (modelID: string) =>
AmazonBedrockMantle.configure({
apiKey: process.env.AWS_BEARER_TOKEN_BEDROCK ?? "fixture",
region: "us-east-1",
}).messages(modelID)
const weatherTool = ToolDefinition.make({
name: "get_weather",
description: "Get the current weather in a city",
inputSchema: {
type: "object",
properties: { city: { type: "string", enum: ["Paris"] } },
required: ["city"],
additionalProperties: false,
},
})
describe("Amazon Bedrock Mantle Messages recorded", () => {
recordedMessages.effect.with(
"replays signed thinking through a tool loop and native system update",
{ tags: ["tool", "tool-loop", "reasoning", "system-update"], metadata: { model: "anthropic.claude-opus-4-8" } },
() =>
Effect.gen(function* () {
const model = mantleMessages("anthropic.claude-opus-4-8")
const initial = LLM.request({
model,
system: "You are a concise assistant.",
prompt:
"First calculate 37 * 43. Then call get_weather for Paris. After receiving the tool result, state both the product and the weather.",
tools: [weatherTool],
providerOptions: {
thinking: { type: "adaptive", display: "summarized" },
effort: "medium",
},
generation: { maxTokens: 2048 },
})
const first = yield* LLMClient.generate(initial)
expect(first.finishReason.normalized).toBe("tool-calls")
expect(first.toolCalls).toMatchObject([{ name: "get_weather", input: { city: "Paris" } }])
expect(first.reasoning.length).toBeGreaterThan(0)
expect(first.events.some(LLMEvent.is.toolInputDelta)).toBe(true)
const reasoningPart = first.message.content.find((part) => part.type === "reasoning")
const signature = (reasoningPart?.providerMetadata?.mantle as { readonly signature?: unknown } | undefined)
?.signature
expect(typeof signature).toBe("string")
const followUp = LLMRequest.update(initial, {
messages: [
...initial.messages,
first.message,
...first.toolCalls.map((call) =>
Message.tool({ id: call.id, name: call.name, result: { condition: "sunny", temperatureC: 18 } }),
),
Message.system("Reply in French in one short sentence."),
],
})
const compiled = yield* compileRequest(followUp)
expect(compiled.body.messages[1]?.content[0]).toEqual({
type: "thinking",
thinking: first.reasoning,
signature: signature as string,
})
expect(compiled.body.messages.at(-1)).toEqual({
role: "system",
content: [
{ type: "text", text: "Reply in French in one short sentence.", cache_control: { type: "ephemeral" } },
],
})
const second = yield* LLMClient.generate(followUp)
expect(second.finishReason.normalized).toBe("stop")
expect(second.text).toContain("1591")
expect(second.text).toContain("18")
}),
120_000,
)
recordedMessages.effect.with(
"lowers system updates to wrapped user text on Haiku 4.5 with budget thinking",
{ tags: ["reasoning", "system-update"], metadata: { model: "anthropic.claude-haiku-4-5" } },
() =>
Effect.gen(function* () {
const request = LLM.request({
model: mantleMessages("anthropic.claude-haiku-4-5"),
messages: [Message.user("What is 19 multiplied by 23?"), Message.system("Reply with only the integer.")],
providerOptions: {
thinking: { type: "enabled", budgetTokens: 1024 },
},
generation: { maxTokens: 2048 },
})
const compiled = yield* compileRequest(request)
expect(compiled.body.thinking).toEqual({ type: "enabled", budget_tokens: 1024 })
expect(compiled.body.messages.some((message) => message.role === "system")).toBe(false)
const response = yield* LLMClient.generate(request)
expect(response.finishReason.normalized).toBe("stop")
expect(response.reasoning.length).toBeGreaterThan(0)
expect(response.text.trim()).toContain("437")
}),
120_000,
)
recordedMessages.effect.with(
"applies mid-conversation effort updates and thinking block binding on Opus 5.5",
{ tags: ["reasoning", "effort-update"], metadata: { model: "anthropic.claude-opus-5-5" } },
() =>
Effect.gen(function* () {
const model = mantleMessages("anthropic.claude-opus-5-5")
const firstRequest = LLM.request({
model,
prompt: "Compute 37 * 43 step by step, then reply with only the integer.",
providerOptions: {
thinking: { type: "adaptive", display: "summarized" },
effort: "high",
},
generation: { maxTokens: 2048 },
})
const firstCompiled = yield* compileRequest(firstRequest)
expect(firstCompiled.body.thinking).toEqual({
type: "adaptive",
display: "summarized",
block_binding: { prefix_mismatch_behavior: "drop_block" },
})
const first = yield* LLMClient.generate(firstRequest)
expect(first.finishReason.normalized).toBe("stop")
expect(first.reasoning.length).toBeGreaterThan(0)
expect(first.text.replaceAll(",", "")).toContain("1591")
const secondRequest = LLM.request({
model,
messages: [
...firstRequest.messages,
first.message,
Message.effort({ effort: "low", previous: "high" }),
Message.user("Add 9 to that result. Reply with only the integer."),
],
providerOptions: {
thinking: { type: "adaptive", display: "summarized" },
effort: "low",
},
generation: { maxTokens: 2048 },
})
const secondCompiled = yield* compileRequest(secondRequest)
expect(secondCompiled.body.output_config).toEqual({ effort: "high" })
expect(secondCompiled.body.messages.filter((message) => message.role === "system")).toEqual([
{ role: "system", content: [], output_config: { effort: "low" } },
])
const second = yield* LLMClient.generate(secondRequest)
expect(second.finishReason.normalized).toBe("stop")
expect(second.text.replaceAll(",", "")).toContain("1600")
}),
120_000,
)
recordedMessages.effect.with(
"strips unsupported mid-conversation effort updates on Opus 5.0",
{ tags: ["reasoning", "effort-update"], metadata: { model: "anthropic.claude-opus-5" } },
() =>
Effect.gen(function* () {
const request = LLM.request({
model: mantleMessages("anthropic.claude-opus-5"),
messages: [
Message.user("What is 12 + 30?"),
Message.assistant("42"),
Message.effort({ effort: "low", previous: "high" }),
Message.user("Add 8 to that result. Reply with only the integer."),
],
providerOptions: {
thinking: { type: "adaptive", display: "summarized" },
effort: "low",
},
generation: { maxTokens: 1024 },
})
const compiled = yield* compileRequest(request)
expect(compiled.body.output_config).toEqual({ effort: "low" })
expect(compiled.body.messages.some((message) => message.role === "system")).toBe(false)
const response = yield* LLMClient.generate(request)
expect(response.finishReason.normalized).toBe("stop")
expect(response.text.trim()).toContain("50")
}),
120_000,
)
})
+1 -1
View File
@@ -1,4 +1,4 @@
import { describe, expect, test } from "bun:test"
import { describe, expect } from "bun:test"
import { ConfigProvider, Effect, Schema } from "effect"
import { HttpClientRequest } from "effect/unstable/http"
import { LLM, LLMEvent } from "../../src/index.js"
@@ -0,0 +1,98 @@
import { expect } from "bun:test"
import { Effect } from "effect"
import { LLM, LLMEvent, LLMRequest, SystemPart } from "../../src/index.js"
import { Cohere } from "../../src/providers/cohere.js"
import { LLMClient } from "../../src/route.js"
import { expectWeatherToolLoop, goldenWeatherToolLoopRequest, runWeatherToolLoop } from "../recorded-scenarios.js"
import { recordedTests } from "../recorded-test.js"
const recorded = recordedTests({ prefix: "cohere", provider: "cohere", requires: ["COHERE_API_KEY"] })
const cohere = Cohere.configure({ apiKey: process.env.COHERE_API_KEY ?? "fixture" })
recorded.effect(
"streams native text and usage",
() =>
Effect.gen(function* () {
const response = yield* LLMClient.generate(
LLM.request({
model: cohere.model("command-a-03-2025"),
prompt: "Reply exactly: OK",
generation: { maxTokens: 64 },
}),
)
expect(response.text.trim()).toMatch(/^OK\.?$/)
expect(response.usage.inputTokens).toBeGreaterThan(0)
expect(response.usage.outputTokens).toBeGreaterThan(0)
expect(response.events.find(LLMEvent.is.finish)?.reason).toEqual({ normalized: "stop", raw: "COMPLETE" })
expect(response.usage.providerMetadata?.cohere?.billed_units).toBeDefined()
}),
60_000,
)
recorded.effect(
"streams native thinking with a budget",
() =>
Effect.gen(function* () {
const response = yield* LLMClient.generate(
LLM.request({
model: cohere.model("command-a-reasoning-08-2025"),
prompt: "What is 17 times 23? Answer briefly.",
providerOptions: { thinking: { type: "enabled", tokenBudget: 128 } },
generation: { maxTokens: 2048 },
}),
)
expect(response.reasoning.length).toBeGreaterThan(0)
expect(response.text).toContain("391")
expect(response.usage.reasoningTokens).toBeGreaterThan(0)
expect(response.usage.reasoningTokens).toBeLessThanOrEqual(128)
expect(response.events.filter(LLMEvent.is.finish)).toHaveLength(1)
}),
60_000,
)
recorded.effect(
"continues a native tool call",
() =>
Effect.gen(function* () {
const events = yield* runWeatherToolLoop(
LLMRequest.update(
goldenWeatherToolLoopRequest({
id: "cohere-tool-loop",
model: cohere.model("command-a-plus-05-2026"),
maxTokens: 2048,
temperature: false,
}),
{
system: [
SystemPart.make("Use the get_weather tool exactly once."),
SystemPart.make("After the tool result, reply exactly: Paris is sunny."),
],
},
),
)
expectWeatherToolLoop(events)
expect(events.some(LLMEvent.is.toolInputDelta)).toBe(true)
}),
60_000,
)
recorded.effect(
"streams compatible chat reasoning",
() =>
Effect.gen(function* () {
const response = yield* LLMClient.generate(
LLM.request({
model: cohere.chat("command-a-reasoning-08-2025"),
prompt: "What is 17 times 23? Answer briefly.",
providerOptions: { reasoningEffort: "high" },
generation: { maxTokens: 2048 },
}),
)
expect(response.reasoning.length).toBeGreaterThan(0)
expect(response.text).toContain("391")
expect(response.events.find(LLMEvent.is.finish)?.reason.normalized).toBe("stop")
expect(response.usage.inputTokens).toBeGreaterThan(0)
expect(response.usage.reasoningTokens).toBeGreaterThan(0)
}),
60_000,
)
+272
View File
@@ -0,0 +1,272 @@
import { expect, test } from "bun:test"
import { Effect } from "effect"
import { LLM, LLMClient, LLMEvent, Media, Message, SystemPart, isRetryable } from "../../src/index.js"
import { Cohere } from "../../src/providers/cohere.js"
import { compileRequest } from "../../src/route/client.js"
import { it } from "../lib/effect.js"
import { fixedResponse } from "../lib/http.js"
import { sseEvents } from "../lib/sse.js"
const cohere = Cohere.configure({ apiKey: "fixture" })
test("Cohere exposes native and compatible endpoints without Core remapping", () => {
expect(cohere.model("command-a-03-2025").route.endpoint.baseURL).toBe("https://api.cohere.com/v2")
expect(cohere.chat("command-a-03-2025").route.endpoint.baseURL).toBe("https://api.cohere.ai/compatibility/v1")
expect(
Cohere.model("command-a-03-2025", { apiKey: "fixture", headers: { "X-Test": "yes" }, body: { temperature: 0 } })
.route.defaults?.http,
).toMatchObject({ body: { temperature: 0 } })
})
it.effect("Cohere lowers native history, thinking, tools, and sampling", () =>
Effect.gen(function* () {
const prepared = yield* compileRequest(
LLM.request({
model: cohere.model("command-a-reasoning-08-2025"),
system: [SystemPart.make("Be concise.\nKeep this newline."), SystemPart.make("Second instructions.")],
messages: [
Message.user("Lookup Paris"),
Message.assistant([{ type: "tool-call", id: "lookup-1", name: "lookup", input: { city: "Paris" } }]),
Message.tool({ id: "lookup-1", name: "lookup", result: { sunny: true } }),
],
tools: [{ name: "lookup", description: "Look up a city", inputSchema: { type: "object", properties: {} } }],
toolChoice: "required",
providerOptions: { thinking: { tokenBudget: 128 } },
generation: { maxTokens: 2048, topP: 0.9, topK: 10 },
}),
)
expect(prepared.body).toMatchObject({
model: "command-a-reasoning-08-2025",
stream: true,
p: 0.9,
k: 10,
max_tokens: 2048,
thinking: { type: "enabled", token_budget: 128 },
tool_choice: "REQUIRED",
messages: [
{
role: "system",
content: [
{ type: "text", text: "Be concise.\nKeep this newline." },
{ type: "text", text: "Second instructions." },
],
},
{ role: "user", content: [{ type: "text", text: "Lookup Paris" }] },
{
role: "assistant",
tool_calls: [{ id: "lookup-1", function: { name: "lookup", arguments: '{"city":"Paris"}' } }],
},
{ role: "tool", tool_call_id: "lookup-1", content: '{"sunny":true}' },
],
})
}),
)
it.effect("Cohere compatibility omits unsupported OpenAI fields", () =>
Effect.gen(function* () {
const prepared = yield* compileRequest(
LLM.request({
model: cohere.chat("command-a-reasoning-08-2025"),
prompt: "Hello",
providerOptions: { reasoningEffort: "high" },
generation: { maxTokens: 64 },
}),
)
expect(prepared.body).toMatchObject({ reasoning_effort: "high", max_tokens: 64, stream: true })
expect(prepared.body.stream_options).toEqual({ include_usage: true })
for (const key of ["store", "max_completion_tokens", "parallel_tool_calls", "prompt_cache_key"])
expect(prepared.body[key]).toBeUndefined()
}),
)
it.effect("Cohere maps inclusive usage while retaining distinct billed units", () =>
Effect.gen(function* () {
const response = yield* LLMClient.generate(
LLM.request({ model: cohere.model("command-a-03-2025"), prompt: "Hi" }),
).pipe(
Effect.provide(
fixedResponse(
sseEvents(
{ type: "message-start" },
{ type: "content-start", index: 0, delta: { message: { content: { type: "thinking", thinking: "" } } } },
{ type: "content-delta", index: 0, delta: { message: { content: { thinking: "Think" } } } },
{ type: "content-end", index: 0 },
{ type: "content-start", index: 1, delta: { message: { content: { type: "text", text: "" } } } },
{ type: "content-delta", index: 1, delta: { message: { content: { text: "OK" } } } },
{ type: "content-end", index: 1 },
{
type: "message-end",
delta: {
finish_reason: "COMPLETE",
usage: {
tokens: { input_tokens: 100, output_tokens: 20, reasoning_tokens: 10 },
billed_units: { input_tokens: 30, output_tokens: 15 },
cached_tokens: 60,
},
},
},
),
),
),
)
expect(response.text).toBe("OK")
expect(response.reasoning).toBe("Think")
expect(response.usage).toMatchObject({
inputTokens: 100,
nonCachedInputTokens: 40,
cacheReadInputTokens: 60,
outputTokens: 20,
reasoningTokens: 10,
totalTokens: 120,
providerMetadata: { cohere: { billed_units: { input_tokens: 30, output_tokens: 15 } } },
})
expect(response.events.filter(LLMEvent.is.finish)).toHaveLength(1)
}),
)
it.effect("Cohere rejects incomplete streams", () =>
Effect.gen(function* () {
const error = yield* LLMClient.generate(
LLM.request({ model: cohere.model("command-a-03-2025"), prompt: "Hi" }),
).pipe(Effect.provide(fixedResponse(sseEvents({ type: "message-start" }))), Effect.flip)
expect(error.message).toContain("without message-end")
}),
)
it.effect("Cohere preserves native tool plans in continued history", () =>
Effect.gen(function* () {
const response = yield* LLMClient.generate(
LLM.request({ model: cohere.model("command-a-03-2025"), prompt: "Hi" }),
).pipe(
Effect.provide(
fixedResponse(
sseEvents(
{ type: "message-start" },
{ type: "tool-plan-delta", delta: { message: { tool_plan: "Look up the weather." } } },
{
type: "tool-call-start",
index: 0,
delta: { message: { tool_calls: { id: "lookup-1", function: { name: "lookup", arguments: "" } } } },
},
{
type: "tool-call-delta",
index: 0,
delta: { message: { tool_calls: { function: { arguments: '{"city":"Paris"}' } } } },
},
{ type: "tool-call-end", index: 0 },
{ type: "message-end", delta: { finish_reason: "TOOL_CALL" } },
),
),
),
)
expect(response.toolCalls[0]?.input).toEqual({ city: "Paris" })
const prepared = yield* compileRequest(
LLM.request({
model: cohere.model("command-a-03-2025"),
messages: [response.message, Message.tool({ id: "lookup-1", name: "lookup", result: { sunny: true } })],
}),
)
expect(prepared.body.messages).toMatchObject([
{ role: "assistant", tool_plan: "Look up the weather.", tool_calls: [{ id: "lookup-1" }] },
{ role: "tool", tool_call_id: "lookup-1" },
])
}),
)
it.effect("Cohere rejects unsupported media instead of silently dropping it", () =>
Effect.gen(function* () {
const error = yield* compileRequest(
LLM.request({
model: cohere.model("command-a-03-2025"),
messages: [Message.user([{ type: "media", media: Media.base64("Zm9v", "audio/wav") }])],
}),
).pipe(Effect.flip)
expect(error.reason._tag).toBe("InvalidRequest")
}),
)
it.effect("Cohere thinking budgets must be positive integers", () =>
Effect.gen(function* () {
const error = yield* compileRequest(
LLM.request({
model: cohere.model("command-a-reasoning-08-2025"),
providerOptions: { thinking: { tokenBudget: 0 } },
}),
).pipe(Effect.flip)
expect(error.reason._tag).toBe("InvalidRequest")
}),
)
it.effect("Cohere fits thinking budgets under the output limit", () =>
Effect.gen(function* () {
const prepared = yield* compileRequest(
LLM.request({
model: cohere.model("command-a-reasoning-08-2025"),
prompt: "Hi",
providerOptions: { thinking: { tokenBudget: 31_999 } },
generation: { maxTokens: 4096 },
}),
)
expect(prepared.body.thinking).toEqual({ type: "enabled", token_budget: 2048 })
}),
)
// Bodies captured live on 2026-10-02, except 402 and 429, which are Cohere's documented messages.
const errors = [
{ status: 401, message: "Incorrect API key provided: ***-123.", tag: "Authentication", retry: false },
{ status: 404, message: "model 'no-such-model-xyz' not found", tag: "InvalidRequest", retry: false },
{
status: 400,
message: "invalid request: temperature must be between 0 and 2.0 inclusive.",
tag: "InvalidRequest",
retry: false,
},
{
status: 400,
error_type: "TOO_MANY_TOKENS",
message: "too many tokens: size limit exceeded by 168512 tokens. The limit for this model is 132000 tokens.",
tag: "InvalidRequest",
classification: "context-overflow",
retry: false,
},
{
status: 400,
error_type: "TOO_MANY_TOKENS",
message:
"too many tokens: max tokens must be less than or equal to 4096, the maximum output length for this model - received 1000000.",
tag: "InvalidRequest",
retry: false,
},
{ status: 402, message: "Please add or update your payment method to continue", tag: "QuotaExceeded", retry: false },
{
status: 429,
message: "You are using a Trial key, which is limited to 40 API calls / minute.",
tag: "RateLimit",
retry: true,
},
{ status: 500, message: "internal server error", tag: "ProviderInternal", retry: true },
]
it.effect("Cohere HTTP errors map to AI error reasons", () =>
Effect.forEach(errors, (item) =>
Effect.gen(function* () {
const error = yield* LLMClient.generate(
LLM.request({ model: cohere.model("command-a-03-2025"), prompt: "Hi" }),
).pipe(
Effect.provide(
fixedResponse(JSON.stringify({ id: "fixture", error_type: item.error_type, message: item.message }), {
status: item.status,
headers: { "content-type": "application/json" },
}),
),
Effect.flip,
)
expect({
message: error.message,
tag: error.reason._tag,
classification: error.reason._tag === "InvalidRequest" ? error.reason.classification : undefined,
retry: isRetryable(error),
}).toEqual({ message: item.message, tag: item.tag, classification: item.classification, retry: item.retry })
}),
),
)
@@ -52,7 +52,6 @@ describe("experimental Evaluation recorded", () => {
typesafe.effect("evaluates choice score and boolean questions", () =>
assertEvaluation(
TypeSafeAI.configure({ apiKey: process.env.TYPESAFE_API_KEY ?? "fixture" }).experimental.evaluation("jev-latest"),
"typesafe",
),
)
@@ -61,7 +60,6 @@ describe("experimental Evaluation recorded", () => {
OpenCodeZen.configure({ apiKey: process.env.OPENCODE_API_KEY ?? "fixture" }).experimental.evaluation(
"jev-1.13-free",
),
"opencode",
),
)
@@ -70,15 +68,11 @@ describe("experimental Evaluation recorded", () => {
OpenRouter.configure({ apiKey: process.env.OPENROUTER_API_KEY ?? "fixture" }).experimental.evaluation(
"typesafe/jev-1.13",
),
"openrouter",
),
)
})
const assertEvaluation = <Options extends EvaluationOptions>(
model: EvaluationModel<Options>,
metadataKey: "typesafe" | "opencode" | "openrouter",
) =>
const assertEvaluation = <Options extends EvaluationOptions>(model: EvaluationModel<Options>) =>
Effect.gen(function* () {
const response = yield* Evaluation.run({ model, state, questions })
expect(response.model).toContain("jev-")
@@ -0,0 +1,169 @@
import { describe, expect } from "bun:test"
import { Effect, Schema } from "effect"
import { HttpClientRequest } from "effect/unstable/http"
import { LLM, LLMEvent, Message } from "../../src/index.js"
import { Google } from "../../src/providers.js"
import { LLMClient, RequestExecutor } from "../../src/route.js"
import { recordedTests } from "../recorded-test.js"
import { weatherTool } from "../recorded-scenarios.js"
const model = Google.configure({ apiKey: process.env.GEMINI_API_KEY ?? "fixture" }).interactions("gemini-3.8-flash")
const recorded = recordedTests({
prefix: "google-interactions",
provider: "google",
protocol: "google-interactions",
requires: ["GEMINI_API_KEY"],
})
const InteractionMetadata = Schema.Struct({ interactionId: Schema.String })
describe("Google Interactions recorded", () => {
recorded.effect("streams text and reports usage", () =>
Effect.gen(function* () {
const response = yield* LLMClient.generate(
LLM.request({
model,
prompt: "Reply with exactly one word: hello",
generation: { maxTokens: 2048 },
providerOptions: { thinkingLevel: "low" },
}),
)
expect(response.text.trim().toLowerCase()).toBe("hello")
expect(response.events.some(LLMEvent.is.textDelta)).toBe(true)
expect(response.finishReason.normalized).toBe("stop")
expect(response.events.filter(LLMEvent.is.finish)).toHaveLength(1)
expect(response.usage?.inputTokens).toBeGreaterThan(0)
expect(response.usage?.contextTokens).toBeGreaterThan(0)
expect(response.usage?.providerMetadata?.google).toMatchObject({ total_input_tokens: expect.any(Number) })
}),
)
recorded.effect(
"streams reasoning and retains thought signatures",
() =>
Effect.gen(function* () {
const response = yield* LLMClient.generate(
LLM.request({
model,
prompt:
"Find the smallest positive integer that leaves remainder 1 modulo 7, 2 modulo 9, and 3 modulo 11. Explain briefly.",
generation: { maxTokens: 4096 },
providerOptions: { thinkingLevel: "high", thinkingSummaries: "auto" },
}),
)
expect(response.reasoning.length).toBeGreaterThan(0)
expect(response.events.some(LLMEvent.is.reasoningDelta)).toBe(true)
expect(response.events.filter(LLMEvent.is.reasoningEnd)).toEqual(
expect.arrayContaining([
expect.objectContaining({
providerMetadata: { google: { interactionSignature: expect.any(String) } },
}),
]),
)
expect(response.text.length).toBeGreaterThan(0)
expect(response.finishReason.normalized).toBe("stop")
}),
120_000,
)
recorded.effect(
"replays native tool results and signatures statelessly",
() =>
Effect.gen(function* () {
const request = LLM.request({
model,
system: "Use get_weather for weather questions. Answer concisely after receiving the result.",
prompt: "What is the weather in Paris?",
tools: [weatherTool],
toolChoice: { type: "tool", name: weatherTool.name },
generation: { maxTokens: 2048 },
providerOptions: { thinkingLevel: "low", thinkingSummaries: "auto" },
})
const first = yield* LLMClient.generate(request)
expect(first.toolCalls).toHaveLength(1)
expect(first.events.some(LLMEvent.is.toolInputDelta)).toBe(true)
expect(first.finishReason.normalized).toBe("tool-calls")
const call = first.toolCalls[0]
if (!call) throw new Error("Missing recorded weather tool call")
expect(call.name).toBe(weatherTool.name)
expect(call.input).toEqual({ city: "Paris" })
expect(call.providerMetadata?.google).toHaveProperty("interactionSignature")
const second = yield* LLMClient.generate(
LLM.request({
model,
system: request.system,
tools: [weatherTool],
toolChoice: "none",
generation: { maxTokens: 2048 },
providerOptions: { thinkingLevel: "low", thinkingSummaries: "auto" },
messages: [
...request.messages,
first.message,
Message.tool({ id: call.id, name: call.name, result: { temperature: 22, condition: "sunny" } }),
],
}),
)
expect(second.text.toLowerCase()).toContain("sunny")
expect(second.text).toContain("22")
expect(second.toolCalls).toHaveLength(0)
expect(second.finishReason.normalized).toBe("stop")
}),
120_000,
)
recorded.effect(
"continues tool results with previous interaction id",
() =>
Effect.gen(function* () {
const request = LLM.request({
model,
system: "Use get_weather for weather questions. Answer concisely after receiving the result.",
prompt: "What is the weather in Paris?",
tools: [weatherTool],
toolChoice: "required",
generation: { maxTokens: 2048 },
providerOptions: { thinkingLevel: "low", store: true },
})
const first = yield* LLMClient.generate(request)
const metadata = yield* Schema.decodeUnknownEffect(InteractionMetadata)(
first.events.find(LLMEvent.is.finish)?.providerMetadata?.google,
)
const executor = yield* RequestExecutor.Service
const cleanup = executor
.execute(
HttpClientRequest.delete(
`https://generativelanguage.googleapis.com/v1beta/interactions/${metadata.interactionId}`,
).pipe(HttpClientRequest.setHeader("x-goog-api-key", process.env.GEMINI_API_KEY ?? "fixture")),
)
.pipe(Effect.orDie)
yield* Effect.gen(function* () {
expect(first.toolCalls).toHaveLength(1)
const call = first.toolCalls[0]
if (!call) throw new Error("Missing recorded weather tool call")
const second = yield* LLMClient.generate(
LLM.request({
model,
system: request.system,
tools: [weatherTool],
toolChoice: "none",
generation: { maxTokens: 2048 },
providerOptions: { thinkingLevel: "low", previousInteractionId: metadata.interactionId, store: false },
messages: [
Message.tool({ id: call.id, name: call.name, result: { temperature: 22, condition: "sunny" } }),
],
}),
)
expect(second.text.toLowerCase()).toContain("sunny")
expect(second.text).toContain("22")
expect(second.toolCalls).toHaveLength(0)
expect(second.finishReason.normalized).toBe("stop")
}).pipe(Effect.ensuring(cleanup))
}),
120_000,
)
})
@@ -1,7 +1,7 @@
import { describe, expect, test } from "bun:test"
import { ConfigProvider, Effect } from "effect"
import { HttpClientRequest } from "effect/unstable/http"
import { LLM, LLMEvent, Message, ToolDefinition, Media } from "../../src/index.js"
import { LLM, LLMEvent, Message, SystemPart, ToolDefinition, Media } from "../../src/index.js"
import { Mistral } from "../../src/providers/index.js"
import { MistralChat } from "../../src/protocols/index.js"
import { LLMClient } from "../../src/route.js"
@@ -41,7 +41,7 @@ describe("Mistral Chat", () => {
const prepared = yield* compileRequest(
LLM.request({
model,
system: "Initial",
system: [SystemPart.make("Initial\nKeep this newline."), SystemPart.make("Second instructions.")],
messages: [
Message.system("Updated"),
Message.user([
@@ -105,7 +105,13 @@ describe("Mistral Chat", () => {
reasoning_effort: "high",
})
expect(prepared.body.messages.slice(0, 4)).toMatchObject([
{ role: "system", content: "Initial" },
{
role: "system",
content: [
{ type: "text", text: "Initial\nKeep this newline." },
{ type: "text", text: "Second instructions." },
],
},
{ role: "user", content: "<system-update>\nUpdated\n</system-update>" },
{
role: "user",
@@ -1,7 +1,7 @@
import { configure } from "@opencode/ai/providers/mistral"
import { describe, expect } from "bun:test"
import { Effect } from "effect"
import { LLM, LLMEvent, LLMRequest, Message, ToolChoice, ToolDefinition } from "../../src/index.js"
import { LLM, LLMEvent, LLMRequest, Message, SystemPart, ToolChoice, ToolDefinition } from "../../src/index.js"
import { LLMClient } from "../../src/route.js"
import { compileRequest } from "../../src/route/client.js"
import { recordedTests } from "../recorded-test.js"
@@ -97,7 +97,10 @@ describe("Mistral recorded", () => {
const model = configure({ apiKey, providerOptions: { reasoningEffort: "none" } }).model("mistral-small-latest")
const firstRequest = LLM.request({
model,
system: "Call lookup_weather exactly once with Paris.",
system: [
SystemPart.make("Call lookup_weather exactly once with Paris."),
SystemPart.make("After the tool result, describe the weather briefly."),
],
prompt: "What is the weather?",
tools: [weather],
toolChoice: weather,
@@ -43,6 +43,7 @@ describe("native OpenAI-compatible providers", () => {
[Azure.configure({ resourceName: "resource", apiKey: "test" }).responses("model"), "azure"],
[AmazonBedrock.configure({ apiKey: "test" }).model("model"), "bedrock"],
[AmazonBedrockMantle.configure({ apiKey: "test" }).chat("model"), "mantle"],
[AmazonBedrockMantle.configure({ apiKey: "test" }).messages("model"), "mantle"],
[AmazonBedrockMantle.configure({ apiKey: "test" }).responses("model"), "mantle"],
[Google.configure({ apiKey: "test" }).model("model"), "google"],
[GoogleVertex.configure(vertex).model("model"), "vertex"],
@@ -1,7 +1,6 @@
import { describe, expect } from "bun:test"
import { Effect } from "effect"
import { LLM, LLMEvent, LLMResponse, LanguageModel } from "../../src/index.js"
import { OpenAIChat } from "../../src/protocols/openai-chat.js"
import * as OpenAICompatible from "../../src/providers/openai-compatible.js"
import * as OpenRouter from "../../src/providers/openrouter.js"
import { LLMClient } from "../../src/route.js"
@@ -1,4 +1,4 @@
import { describe, expect, test } from "bun:test"
import { describe, expect } from "bun:test"
import { Effect, Schema } from "effect"
import { HttpClientRequest } from "effect/unstable/http"
import { LLM, LLMRequest, Message, ToolCallPart, ToolChoice, ToolDefinition } from "../../src/index.js"
@@ -3895,7 +3895,6 @@ describe("OpenAI Responses route", () => {
it.effect("preserves foreign hosted images as portable image content when storage is enabled", () =>
Effect.gen(function* () {
const item = { type: "image_generation_call", id: "ig_1", status: "completed", result: "AQID" }
const prepared = yield* compileRequest(
LLM.request({
model: xaiModel,
-5
View File
@@ -127,11 +127,6 @@ const assistantContent = (events: ReadonlyArray<LLMEvent>) =>
export const expectFinish = (events: ReadonlyArray<LLMEvent>, reason: FinishReason) =>
expect(events.at(-1)).toMatchObject({ type: "finish", reason: { normalized: reason } })
export const expectWeatherToolCall = (response: LLMResponse) =>
expect(response.toolCalls).toMatchObject([
{ type: "tool-call", id: expect.any(String), name: weatherToolName, input: { city: "Paris" } },
])
export const expectWeatherToolLoop = (events: ReadonlyArray<LLMEvent>) => {
const finishes = events.filter(LLMEvent.is.finish)
expect(finishes).toHaveLength(1)
+1
View File
@@ -2,6 +2,7 @@
"$schema": "https://json.schemastore.org/tsconfig.json",
"extends": "@tsconfig/bun/tsconfig.json",
"compilerOptions": {
"noUnusedLocals": true,
"module": "NodeNext",
"moduleResolution": "NodeNext",
"allowImportingTsExtensions": false,
@@ -1,7 +1,7 @@
import { fileURLToPath } from "node:url"
import { expect, story } from "../../storybook/playwright/story"
import { expect, sourceURL, story } from "../../storybook/playwright/story"
const source = (path: string) => sourceURL(new URL(path, import.meta.url))
const source = (path: string) => `/@fs/${fileURLToPath(new URL(path, import.meta.url)).replaceAll("\\", "/")}`
const modules = {
fixture: source("../../gui-extensions/src/browser/panel.fixture.tsx"),
host: source("../src/runtime/extension/host.tsx"),
@@ -13,49 +13,74 @@ const modules = {
fileRenderer: source("../../gui-extensions/src/file/renderer.tsx"),
}
story.beforeEach(async ({ mount, page }) => {
// Any story loads the app styles; the fixture mounts the real side region and extensions beside it.
await mount("ui-line-comment--editor")
await page.evaluate(async (modules) => {
const [{ mountBrowserRegion }, host, panels, language, browser, file] = await Promise.all([
import(modules.fixture),
import(modules.host),
import(modules.panels),
import(modules.language),
import(modules.browser),
import(modules.file),
])
mountBrowserRegion({
LanguageProvider: language.LanguageProvider,
ExtensionHostProvider: host.ExtensionHostProvider,
useExtensionHost: host.useExtensionHost,
createRegion: panels.createRegion,
definitions: [
{ ...browser.default, renderer: () => import(modules.browserRenderer) },
{ ...file.default, renderer: () => import(modules.fileRenderer) },
],
})
}, modules)
})
story("keeps a restored browser tab selected and undrawn until the desktop's first inventory", async ({ page }) => {
const root = page.getByTestId("browser-region-fixture")
const tabs = root.getByRole("tab")
const tree = root.getByTestId("tree")
await expect(root.getByText("Registrations: 1", { exact: true })).toBeVisible()
await expect(tabs).toHaveText(["alpha.ts"])
await expect(tree).toHaveText('{"tab":"changes"}')
// Beta was left on its browser tab, which the desktop has not reported yet.
await root.getByRole("button", { name: "Beta", exact: true }).click()
await expect(root.getByText("Registrations: 2", { exact: true })).toBeVisible()
await expect(root.getByTestId("selected")).toHaveText(/^browser:tab_/)
await expect(tabs).toHaveText(["beta.ts"])
// No fallback tab was selected, so the file tab's selection never switched the tree to All files.
await expect(tree).toHaveText('{"tab":"changes"}')
await root.getByRole("button", { name: "First inventory", exact: true }).click()
await expect(tabs).toHaveText(["beta.ts", "Preview"])
await expect(root.getByRole("tab", { name: "Preview", exact: true })).toHaveAttribute("aria-selected", "true")
await expect(tree).toHaveText('{"tab":"changes"}')
})
story(
"keeps a restored browser tab selected and undrawn until the desktop's first inventory",
async ({ mount, page }) => {
// Any story loads the app styles; the fixture mounts the real side region and extensions beside it.
await mount("ui-line-comment--editor")
await page.evaluate(async (modules) => {
const [{ mountBrowserRegion }, host, panels, language, browser, file] = await Promise.all([
import(modules.fixture),
import(modules.host),
import(modules.panels),
import(modules.language),
import(modules.browser),
import(modules.file),
])
mountBrowserRegion({
LanguageProvider: language.LanguageProvider,
ExtensionHostProvider: host.ExtensionHostProvider,
useExtensionHost: host.useExtensionHost,
createRegion: panels.createRegion,
definitions: [
{ ...browser.default, renderer: () => import(modules.browserRenderer) },
{ ...file.default, renderer: () => import(modules.fileRenderer) },
],
})
}, modules)
"keeps the browser tabs while the pane's Ipc is away and registers them again when it returns",
async ({ page }) => {
const root = page.getByTestId("browser-region-fixture")
const tabs = root.getByRole("tab")
const tree = root.getByTestId("tree")
await expect(root.getByText("Registrations: 1", { exact: true })).toBeVisible()
await expect(tabs).toHaveText(["alpha.ts"])
await expect(tree).toHaveText('{"tab":"changes"}')
// Beta was left on its browser tab, which the desktop has not reported yet.
await root.getByRole("button", { name: "Beta", exact: true }).click()
await expect(root.getByText("Registrations: 2", { exact: true })).toBeVisible()
await expect(root.getByTestId("selected")).toHaveText(/^browser:tab_/)
await expect(tabs).toHaveText(["beta.ts"])
// No fallback tab was selected, so the file tab's selection never switched the tree to All files.
await expect(tree).toHaveText('{"tab":"changes"}')
await root.getByRole("button", { name: "First inventory", exact: true }).click()
await expect(tabs).toHaveText(["beta.ts", "Preview"])
// The pane's main extension reloads: every binding goes with it, and the strip keeps the tab it will restore.
await root.getByRole("button", { name: "Pane away", exact: true }).click()
await expect(tabs).toHaveText(["beta.ts", "Preview"])
await expect(root.getByRole("tab", { name: "Preview", exact: true })).toHaveAttribute("aria-selected", "true")
await expect(tree).toHaveText('{"tab":"changes"}')
// Both attachments register again at once, without a retry timer; Beta hands main the tab to restore.
await root.getByRole("button", { name: "Pane back", exact: true }).click()
await expect(root.getByText("Registrations: 4", { exact: true })).toBeVisible()
await expect(root.getByText("Beta restores: 1", { exact: true })).toBeVisible()
await expect(tabs).toHaveText(["beta.ts", "Preview"])
},
)
@@ -1,24 +1,25 @@
import { fileURLToPath } from "node:url"
import { expect, story } from "../../storybook/playwright/story"
import { expect, sourceURL, story } from "../../storybook/playwright/story"
const source = (path: string) => sourceURL(new URL(path, import.meta.url))
const source = (path: string) => `/@fs/${fileURLToPath(new URL(path, import.meta.url)).replaceAll("\\", "/")}`
const modules = {
fixture: source("../../gui-extensions/src/browser/panel.fixture.tsx"),
surface: source("../src/runtime/extension/surface.tsx"),
embeds: source("../src/runtime/extension/embeds.tsx"),
language: source("../src/runtime/i18n/language.tsx"),
}
story.beforeEach(async ({ mount, page }) => {
// Any story loads the app styles; the fixture mounts the pane beside it on the real host surface.
// Any story loads the app styles; the fixture mounts the pane beside it on the real host embeds.
await mount("ui-line-comment--editor")
await page.evaluate(async (modules) => {
const [{ mountBrowserPane }, { createSurfaces }, language] = await Promise.all([
const [{ mountBrowserPane }, { createEmbeds }, language] = await Promise.all([
import(modules.fixture),
import(modules.surface),
import(modules.embeds),
import(modules.language),
])
mountBrowserPane({
createSurfaces,
createEmbeds,
LanguageProvider: language.LanguageProvider,
UiI18nBridge: language.UiI18nBridge,
useLanguage: language.useLanguage,
@@ -26,6 +27,7 @@ story.beforeEach(async ({ mount, page }) => {
}, modules)
await expect(page.getByTestId("native-Alpha")).toHaveAttribute("data-visible", "true")
})
story("hides a native page when another takes the pane, the pane hides, or it unmounts", async ({ page }) => {
const root = page.getByTestId("browser-pane-fixture")
const alpha = root.getByTestId("native-Alpha")
@@ -50,11 +52,14 @@ story("hides the native view immediately while the pane stays mounted", async ({
const root = page.getByTestId("browser-pane-fixture")
const toggle = root.getByRole("button", { name: "Toggle Review tab", exact: true })
await expect(toggle).toBeEnabled()
// Read in the same task as the click so a deferred animation-frame hide cannot pass.
const visible = await toggle.evaluate((element) => {
element.dispatchEvent(new MouseEvent("click", { bubbles: true }))
return document.querySelector('[data-testid="native-Alpha"]')?.getAttribute("data-visible")
})
expect(visible).toBe("false")
await expect(root.locator("#browser-panel")).toHaveCount(1)
await toggle.click()
@@ -87,6 +92,7 @@ story("comments on a picked element over a still of the page", async ({ page })
await picker.click()
await expect(picker).toHaveAttribute("aria-pressed", "true")
await expect(root.getByText("Picker: on", { exact: true })).toBeVisible()
await expect(root.getByText("Session getter reads: 0", { exact: true })).toBeVisible()
await expect(root.getByRole("status")).toHaveText(
"Click an element in the page to comment on it. Press Escape to cancel.",
)
@@ -95,6 +101,7 @@ story("comments on a picked element over a still of the page", async ({ page })
await expect(picker).toHaveAttribute("aria-pressed", "false")
const editor = root.locator('[data-slot="browser-comment-editor"] textarea')
await expect(editor).toBeFocused()
await expect(root.getByText("Session getter reads: 0", { exact: true })).toBeVisible()
await expect(root.locator('[data-slot="browser-comment-editor"]')).toContainText("button.primary")
// The spotlight frames the picked element in surface pixels.
await expect(root.locator('[data-slot="browser-comment-spotlight"]')).toHaveCSS("left", "48px")
@@ -108,6 +115,19 @@ story("comments on a picked element over a still of the page", async ({ page })
await expect(root.locator('[data-component="browser-comment"]')).toHaveCount(0)
await expect(root.getByText("Highlights: clear", { exact: true })).toBeVisible()
await expect(root.getByTestId("native-Alpha")).toHaveAttribute("data-visible", "true")
// The pane stays mounted when Beta is routed, and its picker then listens to Beta's page.
await root.getByRole("button", { name: "Beta", exact: true }).click()
await expect(root.getByTestId("native-Beta")).toHaveAttribute("data-visible", "true")
await picker.click()
await root.getByRole("button", { name: "Pick element", exact: true }).click()
await expect(editor).toBeFocused()
await editor.fill("Beta's button too")
await editor.press("Enter")
await expect(root.getByTestId("fixture-comments").getByRole("listitem")).toHaveText([
"button.primary @e7: Make this the primary colour",
"button.primary @e7: Beta's button too",
])
})
story("cancels the picker and a comment with Escape", async ({ page }) => {
@@ -129,6 +149,44 @@ story("cancels the picker and a comment with Escape", async ({ page }) => {
await expect(root.getByTestId("native-Alpha")).toHaveAttribute("data-visible", "true")
})
story("cleans up the originating session's picker and comment after a session switch", async ({ page }) => {
const root = page.getByTestId("browser-pane-fixture")
const picker = root.getByRole("button", { name: "Select an element to comment on", exact: true })
await picker.click()
await expect(root.getByText("Picker Alpha: on", { exact: true })).toBeVisible()
await root.getByRole("button", { name: "Beta", exact: true }).click()
await expect(root.getByTestId("native-Beta")).toHaveAttribute("data-visible", "true")
await expect(root.getByText("Picker Alpha: off", { exact: true })).toBeVisible()
await expect(picker).toHaveAttribute("aria-pressed", "false")
await root.getByRole("button", { name: "Alpha", exact: true }).click()
await picker.click()
await root.getByRole("button", { name: "Pick element", exact: true }).click()
await expect(root.locator('[data-slot="browser-comment-editor"] textarea')).toBeFocused()
await root.getByRole("button", { name: "Beta", exact: true }).click()
await expect(root.locator('[data-component="browser-comment"]')).toHaveCount(0)
await expect(root.getByText("Highlights: clear", { exact: true })).toBeVisible()
await expect(root.getByText("Highlight owners: Alpha", { exact: true })).toBeVisible()
})
story("ends the native picker and highlight when the pane unmounts", async ({ page }) => {
const root = page.getByTestId("browser-pane-fixture")
const picker = root.getByRole("button", { name: "Select an element to comment on", exact: true })
await picker.click()
await expect(root.getByText("Picker: on", { exact: true })).toBeVisible()
await root.getByRole("button", { name: "Unmount pane", exact: true }).click()
await expect(root.locator("#browser-panel")).toHaveCount(0)
await expect(root.getByText("Picker: off", { exact: true })).toBeVisible()
await root.getByRole("button", { name: "Alpha", exact: true }).click()
await picker.click()
await root.getByRole("button", { name: "Pick element", exact: true }).click()
await expect(root.locator('[data-slot="browser-comment-editor"] textarea')).toBeFocused()
await root.getByRole("button", { name: "Unmount pane", exact: true }).click()
await expect(root.locator("#browser-panel")).toHaveCount(0)
await expect(root.getByText("Highlights: clear", { exact: true })).toBeVisible()
})
story("keeps a comment draft but drops its ref when the page navigates", async ({ page }) => {
const root = page.getByTestId("browser-pane-fixture")
await root.getByRole("button", { name: "Select an element to comment on", exact: true }).click()
@@ -157,6 +215,7 @@ story("keeps the comment editor and its actions inside the page", async ({ page
.poll(async () => {
const surface = await root.locator('[data-component="browser-comment"]').boundingBox()
const box = await editor.boundingBox()
return !!surface && !!box && box.y + box.height <= surface.y + surface.height
})
.toBe(true)
@@ -212,17 +271,22 @@ story("keeps the submitted URL visible until the browser reports navigation", as
await expect(address).toHaveValue("https://example.com/")
})
story("restores the current URL when a submitted navigation is blocked", async ({ page }) => {
story("restores the current URL each time the same submitted navigation is blocked", async ({ page }) => {
const root = page.getByTestId("browser-pane-fixture")
await root.getByRole("button", { name: "Delay navigation", exact: true }).click()
const address = root.getByRole("textbox", { name: "Browser address", exact: true })
await address.fill("https://blocked.example/")
await address.press("Enter")
await expect(address).toHaveValue("https://blocked.example/")
await root.getByRole("button", { name: "Block navigation", exact: true }).click()
await expect(root.getByText("ERR_BLOCKED_BY_CLIENT", { exact: true })).toBeVisible()
await expect(address).toHaveValue("https://alpha.example/")
await expect(root.getByTestId("native-Alpha")).toHaveAttribute("data-visible", "true")
for (const submission of [1, 2]) {
await story.step(`blocked submission ${submission}`, async () => {
await address.fill("https://blocked.example/")
await address.press("Enter")
await expect(address).toHaveValue("https://blocked.example/")
await root.getByRole("button", { name: "Block navigation", exact: true }).click()
await expect(root.getByRole("alert")).toHaveText("Request failed")
await expect(address).toHaveValue("https://alpha.example/")
await expect(root.getByTestId("native-Alpha")).toHaveAttribute("data-visible", "true")
})
}
})
story("shows a themed failure state for only the failed tab and allows retry", async ({ page }) => {
@@ -280,10 +344,12 @@ story("selects the full URL when the address field gains focus", async ({ page }
await address.focus()
await expect(address).toHaveJSProperty("selectionStart", 0)
await expect(address).toHaveJSProperty("selectionEnd", "https://example.com/".length)
// A click on the focused field places the caret instead of selecting the URL again.
await address.press("ArrowRight")
await address.click()
await expect(address).toHaveJSProperty("selectionStart", 0)
await expect(address).toHaveJSProperty("selectionEnd", "https://example.com/".length)
await expect
.poll(() => address.evaluate((input: HTMLInputElement) => input.selectionStart === input.selectionEnd))
.toBe(true)
})
story("keeps the current page visible while a submitted URL loads", async ({ page }) => {
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