chore: upgrade Effect to 4.0 stable

Co-authored-by: rekram1-node <rekram1-node@users.noreply.github.com>

.github/actions/setup-bun/action.yml

@@ -45,14 +45,16 @@ runs:
     - name: Get cache directory
       id: cache
       shell: bash
-      run: echo "dir=$(bun pm cache)" >> "$GITHUB_OUTPUT"
+      run: |
+        echo "dir=$(bun pm cache)" >> "$GITHUB_OUTPUT"
+        echo "version=$(bun --version)" >> "$GITHUB_OUTPUT"
 
     - name: Restore Bun dependencies
       id: bun-cache
       uses: actions/cache/restore@0057852bfaa89a56745cba8c7296529d2fc39830 # v4.3.0
       with:
         path: ${{ steps.cache.outputs.dir }}
-        key: ${{ runner.os }}-bun-${{ hashFiles('**/bun.lock') }}
+        key: ${{ runner.os }}-${{ runner.arch }}-bun-${{ steps.cache.outputs.version }}-${{ hashFiles('bun.lock', 'patches/**') }}
 
     - name: Install setuptools for distutils compatibility
       run: python3 -m pip install setuptools || pip install setuptools || true
@@ -75,4 +77,4 @@ runs:
       uses: actions/cache/save@0057852bfaa89a56745cba8c7296529d2fc39830 # v4.3.0
       with:
         path: ${{ steps.cache.outputs.dir }}
-        key: ${{ runner.os }}-bun-${{ hashFiles('**/bun.lock') }}
+        key: ${{ steps.bun-cache.outputs.cache-primary-key }}

.github/workflows/check.yml

@@ -7,6 +7,10 @@ on:
     branches: [dev, v2]
   workflow_dispatch:
 
+concurrency:
+  group: ${{ case(github.ref == 'refs/heads/dev', format('{0}-{1}', github.workflow, github.run_id), format('{0}-{1}', github.workflow, github.event.pull_request.number || github.ref)) }}
+  cancel-in-progress: true
+
 jobs:
   check:
     name: typecheck

.github/workflows/test.yml

@@ -94,12 +94,6 @@ jobs:
           git config --global user.email "bot@opencode.ai"
           git config --global user.name "opencode"
 
-      - name: Install ffmpeg
-        if: runner.os == 'Linux'
-        run: |
-          sudo apt-get update
-          sudo apt-get install --yes ffmpeg
-
       - name: Cache Turbo
         uses: actions/cache@0057852bfaa89a56745cba8c7296529d2fc39830 # v4.3.0
         with:

bun.lock

@@ -118,7 +118,7 @@
         "opencode2": "./bin/opencode2.cjs",
       },
       "dependencies": {
-        "@agentclientprotocol/sdk": "1.2.1",
+        "@agentclientprotocol/sdk": "1.6.0",
         "@clack/core": "1.0.0-alpha.1",
         "@clack/prompts": "1.0.0-alpha.1",
         "@effect/platform-node": "catalog:",
@@ -194,7 +194,7 @@
         "zod": "catalog:",
       },
       "peerDependencies": {
-        "effect": "4.0.0-rc.112",
+        "effect": "4.0.0",
         "solid-js": ">=1.9.0",
       },
       "optionalPeers": [
@@ -406,6 +406,7 @@
         "@types/node": "catalog:",
         "@types/which": "3.0.4",
         "drizzle-kit": "catalog:",
+        "fast-check": "4.9.0",
       },
     },
     "packages/desktop": {
@@ -441,7 +442,7 @@
         "electron-builder": "26.15.7",
         "electron-vite": "6.0.0-beta.1",
         "solid-js": "catalog:",
-        "typescript": "~5.6.2",
+        "typescript": "catalog:",
         "vite": "8.2.2",
       },
       "optionalDependencies": {
@@ -555,7 +556,7 @@
       "name": "@opencode/http-recorder",
       "version": "2.0.21",
       "dependencies": {
-        "@effect/platform-node-shared": "4.0.0-rc.112",
+        "@effect/platform-node-shared": "4.0.0",
       },
       "devDependencies": {
         "@effect/platform-node": "catalog:",
@@ -1147,10 +1148,10 @@
   "catalog": {
     "@cloudflare/workers-types": "4.20251008.0",
     "@corvu/drawer": "0.2.4",
-    "@effect/opentelemetry": "4.0.0-rc.112",
-    "@effect/platform-node": "4.0.0-rc.112",
-    "@effect/platform-node-shared": "4.0.0-rc.112",
-    "@effect/sql-sqlite-bun": "4.0.0-rc.112",
+    "@effect/opentelemetry": "4.0.0",
+    "@effect/platform-node": "4.0.0",
+    "@effect/platform-node-shared": "4.0.0",
+    "@effect/sql-sqlite-bun": "4.0.0",
     "@hono/standard-validator": "0.2.0",
     "@hono/zod-validator": "0.4.2",
     "@kobalte/core": "0.13.13",
@@ -1190,7 +1191,7 @@
     "dompurify": "3.4.14",
     "drizzle-kit": "1.0.0-rc.5-ab785fc",
     "drizzle-orm": "1.0.0-rc.5-169397b",
-    "effect": "4.0.0-rc.112",
+    "effect": "4.0.0",
     "fuzzysort": "3.1.0",
     "get-east-asian-width": "1.6.0",
     "hono": "4.10.7",
@@ -1209,7 +1210,7 @@
     "sst": "4.13.1",
     "string-width": "7.2.0",
     "tailwindcss": "4.1.11",
-    "typescript": "5.8.2",
+    "typescript": "5.9.3",
     "ulid": "3.0.1",
     "vite": "7.3.6",
     "vite-plugin-solid": "2.11.10",
@@ -1230,7 +1231,7 @@
 
     "@adobe/css-tools": ["@adobe/css-tools@4.5.0", "", {}, "sha512-6OzddxPio9UiWTCemp4N8cYLV2ZN1ncRnV1cVGtve7dhPOtRkleRyx32GQCYSwDYgaHU3USMm84tNsvKzRCa1Q=="],
 
-    "@agentclientprotocol/sdk": ["@agentclientprotocol/sdk@1.2.1", "", { "peerDependencies": { "zod": "^3.25.0 || ^4.0.0" } }, "sha512-jwYUdOQR7tc+Zfch53VL4JJyUNK/46q03uUTYb+PjECsmnNl94XFXOfYLJ8RBpMNidXd1rpOAVgb0vqD98xImA=="],
+    "@agentclientprotocol/sdk": ["@agentclientprotocol/sdk@1.6.0", "", { "peerDependencies": { "zod": "^3.25.0 || ^4.0.0" } }, "sha512-XxXrmX7aZkDgOB0Rg9cu+ZFyiUUc5lF2n9seO3Gc4OR+MTdfZOwIqF6m3LvsmmM8K3qgPmXkDH8/IFM2u9vdcQ=="],
 
     "@ai-sdk/cohere": ["@ai-sdk/cohere@3.0.27", "", { "dependencies": { "@ai-sdk/provider": "3.0.8", "@ai-sdk/provider-utils": "4.0.21" }, "peerDependencies": { "zod": "^3.25.76 || ^4.1.8" } }, "sha512-OqcCq2PiFY1dbK/0Ck45KuvE8jfdxRuuAE9Y5w46dAk6U+9vPOeg1CDcmR+ncqmrYrhRl3nmyDttyDahyjCzAw=="],
 
@@ -1722,13 +1723,13 @@
 
     "@drizzle-team/brocli": ["@drizzle-team/brocli@0.12.0", "", {}, "sha512-mlUE+rZ8CatQekLhnaiN91Iemdd+e2gFKooGlnRB3oPTL3VghLfX24dx7HrzMNeC1JrIB/0kpsfyty3f5HNfxQ=="],
 
-    "@effect/opentelemetry": ["@effect/opentelemetry@4.0.0-rc.112", "", { "peerDependencies": { "@opentelemetry/api": ">=1.9.0 <2.0.0", "@opentelemetry/api-logs": ">=0.203.0 <0.300.0", "@opentelemetry/resources": ">=2.0.0 <3.0.0", "@opentelemetry/sdk-logs": ">=0.203.0 <0.300.0", "@opentelemetry/sdk-metrics": ">=2.0.0 <3.0.0", "@opentelemetry/sdk-trace-base": ">=2.0.0 <3.0.0", "@opentelemetry/sdk-trace-node": ">=2.0.0 <3.0.0", "@opentelemetry/sdk-trace-web": ">=2.0.0 <3.0.0", "@opentelemetry/semantic-conventions": ">=1.33.0 <2.0.0", "effect": "^4.0.0-rc.112" }, "optionalPeers": ["@opentelemetry/api", "@opentelemetry/api-logs", "@opentelemetry/resources", "@opentelemetry/sdk-logs", "@opentelemetry/sdk-metrics", "@opentelemetry/sdk-trace-base", "@opentelemetry/sdk-trace-node", "@opentelemetry/sdk-trace-web"] }, "sha512-OTRv1DxTHUmnakgJ6XVM8wVgF1KgZH4UXnOemwSLUwUjXO+RCikzF8oR/rlVmOGq81KtQzj1URM4M4nchlQOuQ=="],
+    "@effect/opentelemetry": ["@effect/opentelemetry@4.0.0", "", { "peerDependencies": { "@opentelemetry/api": ">=1.9.0 <2.0.0", "@opentelemetry/api-logs": ">=0.203.0 <0.300.0", "@opentelemetry/resources": ">=2.0.0 <3.0.0", "@opentelemetry/sdk-logs": ">=0.203.0 <0.300.0", "@opentelemetry/sdk-metrics": ">=2.0.0 <3.0.0", "@opentelemetry/sdk-trace-base": ">=2.0.0 <3.0.0", "@opentelemetry/sdk-trace-node": ">=2.0.0 <3.0.0", "@opentelemetry/sdk-trace-web": ">=2.0.0 <3.0.0", "@opentelemetry/semantic-conventions": ">=1.33.0 <2.0.0", "effect": "^4.0.0" }, "optionalPeers": ["@opentelemetry/api", "@opentelemetry/api-logs", "@opentelemetry/resources", "@opentelemetry/sdk-logs", "@opentelemetry/sdk-metrics", "@opentelemetry/sdk-trace-base", "@opentelemetry/sdk-trace-node", "@opentelemetry/sdk-trace-web"] }, "sha512-vXVhqlcADHtmKlw2gIqRRlXFve4ms4JJ5ykAqzNe37QQ/5N5A5gJ9VOXkMBORHZC5O4gdHZwxhAzGZb0zvFf/Q=="],
 
-    "@effect/platform-node": ["@effect/platform-node@4.0.0-rc.112", "", { "dependencies": { "@effect/platform-node-shared": "^4.0.0-rc.112", "mime": "^4.1.0", "undici": "^8.10.0" }, "peerDependencies": { "effect": "^4.0.0-rc.112", "redis": ">=5.0.0 <7.0.0" } }, "sha512-/BMAcdNGQQskLmI0Zoa95KfTZkr9HV9N4NSxaSrusG6GeW6Ulp9KvZ+Rlaiw8lnOt43CXjFLdfll5/k5rxL4hQ=="],
+    "@effect/platform-node": ["@effect/platform-node@4.0.0", "", { "dependencies": { "@effect/platform-node-shared": "^4.0.0", "undici": "^8.11.2" }, "peerDependencies": { "effect": "^4.0.0", "redis": ">=5.0.0 <7.0.0" } }, "sha512-/L+4MUbl8FejPKLHLROYSOebvHnfixkP8KiblSD/DE5uH5xENZBHaux4nH6XMnRP+lr8ajpEJFS8sUrmmxFJeQ=="],
 
-    "@effect/platform-node-shared": ["@effect/platform-node-shared@4.0.0-rc.112", "", { "dependencies": { "@types/ws": "^8.18.1", "ws": "^8.21.3" }, "peerDependencies": { "effect": "^4.0.0-rc.112" } }, "sha512-ttjz0xKamFN7vL8pNDYVwddJLjZvqKePc05djlz2VcdaKbLsnYbtMnL1rbOfHgEnIUSHGh7FkjaN4DM1Ov81sQ=="],
+    "@effect/platform-node-shared": ["@effect/platform-node-shared@4.0.0", "", { "dependencies": { "@types/ws": "^8.18.1", "ws": "^8.22.0" }, "peerDependencies": { "effect": "^4.0.0" } }, "sha512-VBXHJU9UXVZPdQGGDRjGXpo+TpOzRwZuMrdKAtIxi1qwcRftmacZ1zTgIrzBa0Z2RA2KVkoOecQUsTlt/nJZhw=="],
 
-    "@effect/sql-sqlite-bun": ["@effect/sql-sqlite-bun@4.0.0-rc.112", "", { "peerDependencies": { "effect": "^4.0.0-rc.112" } }, "sha512-EqR8pWZo3VzedRvP6qo5HcfqNmFvSa+sQLWQl3oBMx2KY1FCc8NYjep79wYjNkW0qABnffrPUXCMTOncd1A+5g=="],
+    "@effect/sql-sqlite-bun": ["@effect/sql-sqlite-bun@4.0.0", "", { "peerDependencies": { "effect": "^4.0.0" } }, "sha512-tUDqqNq4lZMLQkp8YDQej2uuy8BBjmqfMXcJU/KOmrK/WWbzudC8oabZ1TEs1lLSuKzhBEPhnE0cRtAOYe05ew=="],
 
     "@electron-internal/extract-zip": ["@electron-internal/extract-zip@1.0.5", "", {}, "sha512-+bqFCP98pLI0Tt0XQo1TmlXtwjWchISndDOxCkEcIuUgXWpBnLyRI+2DU+mesvnMMX6L1XDqYNA0lXNDHd/yiA=="],
 
@@ -2062,18 +2063,6 @@
 
     "@motionone/utils": ["@motionone/utils@10.18.0", "", { "dependencies": { "@motionone/types": "^10.17.1", "hey-listen": "^1.0.8", "tslib": "^2.3.1" } }, "sha512-3XVF7sgyTSI2KWvTf6uLlBJ5iAgRgmvp3bpuOiQJvInd4nZ19ET8lX5unn30SlmRH7hXbBbH+Gxd0m0klJ3Xtw=="],
 
-    "@msgpackr-extract/msgpackr-extract-darwin-arm64": ["@msgpackr-extract/msgpackr-extract-darwin-arm64@3.0.4", "", { "os": "darwin", "cpu": "arm64" }, "sha512-LCkGo6JDfaBhgST7UpPWgNgLINpcpabaHfyz5OBx75nUYxBsaEPxjnyNjWpeb/xBup/682QnBfRBy2/LvPutZQ=="],
-
-    "@msgpackr-extract/msgpackr-extract-darwin-x64": ["@msgpackr-extract/msgpackr-extract-darwin-x64@3.0.4", "", { "os": "darwin", "cpu": "x64" }, "sha512-zExlW9zUJKZH/tOtVMttwjKa4Xm/3KcNjnE3dPN92uCktwavMxpgCA3MoJK/DOnTWsQgo224OaST27/mPNAf+w=="],
-
-    "@msgpackr-extract/msgpackr-extract-linux-arm": ["@msgpackr-extract/msgpackr-extract-linux-arm@3.0.4", "", { "os": "linux", "cpu": "arm" }, "sha512-Tg3yX65f5GbtXLkrYEHE5oibZG9epyYWas7FogTTEJeDEF9JlXJzKgXaNhT3UXlTOeA+AfZpYZYZ0uPj7Cfquw=="],
-
-    "@msgpackr-extract/msgpackr-extract-linux-arm64": ["@msgpackr-extract/msgpackr-extract-linux-arm64@3.0.4", "", { "os": "linux", "cpu": "arm64" }, "sha512-dgX0P/9wGPJeHFBG+ZmhgE6bmtMt7NP5CRBGyyktpopdk/mW4POnrpQsSLtKI1dwpc+pPLuXHDh6vvskyQE/sw=="],
-
-    "@msgpackr-extract/msgpackr-extract-linux-x64": ["@msgpackr-extract/msgpackr-extract-linux-x64@3.0.4", "", { "os": "linux", "cpu": "x64" }, "sha512-8TNXMEjJc3QEy7R/x1INhgiU+XakDAFUzBhaz7+Rbrs8NH5UQeHQxxmzsSBJGyV6I1jW79undiQm8tOI+D+8FQ=="],
-
-    "@msgpackr-extract/msgpackr-extract-win32-x64": ["@msgpackr-extract/msgpackr-extract-win32-x64@3.0.4", "", { "os": "win32", "cpu": "x64" }, "sha512-CmCXPQrkbwExx3j946/PtHWHbYJiCRBRDl4BlkRQcJB/YOwQxJRTpoo7aTsortjgoJ1x7opzTSxn7C+ASSLVjQ=="],
-
     "@napi-rs/lzma-linux-x64-gnu": ["@napi-rs/lzma-linux-x64-gnu@1.5.1", "", { "os": "linux", "cpu": "x64" }, "sha512-oTXEIha4SsuXdTA4Iyskj0kpdx2yVXdhd75c2v3xGrHFfVMsbhTPZU/nMPL4sWKo4pBHm3aucLaqGlF696dTyQ=="],
 
     "@napi-rs/wasm-runtime": ["@napi-rs/wasm-runtime@1.2.3", "", { "dependencies": { "@tybys/wasm-util": "^0.10.3" }, "peerDependencies": { "@emnapi/core": "^1.7.1 || ^2.0.0-alpha.4", "@emnapi/runtime": "^1.7.1 || ^2.0.0-alpha.4" } }, "sha512-UMduMbqO5s5zF2NkNacMT/yK5Y5QiKvWr2+50bzIIxFDwVJ2h49b+oyjaCGPhJxd2/gC2x39EHv/gHVuu36x2Q=="],
@@ -3912,7 +3901,7 @@
 
     "editorconfig": ["editorconfig@1.0.7", "", { "dependencies": { "@one-ini/wasm": "0.1.1", "commander": "^10.0.0", "minimatch": "^9.0.1", "semver": "^7.5.3" }, "bin": { "editorconfig": "bin/editorconfig" } }, "sha512-e0GOtq/aTQhVdNyDU9e02+wz9oDDM+SIOQxWME2QRjzRX5yyLAuHDE+0aE8vHb9XRC8XD37eO2u57+F09JqFhw=="],
 
-    "effect": ["effect@4.0.0-rc.112", "", { "dependencies": { "fast-check": "^4.9.0", "msgpackr": "^2.0.5" } }, "sha512-wXxwuh1Ywnv4cPRM3Wfa0vDwuOHnZ1TsTgHJkG9XgzND6inhBH9n1vBxhg3iIXOia/OrpmvVmd3lrD4vq6bF3A=="],
+    "effect": ["effect@4.0.0", "", {}, "sha512-ooc1TG5t+FfzgYnFz2ff6BBKyZ7EwBRVXC7c4RhQUAD6/TZ2gTXXMeb4WX7a19ozQo4J73/QW+S00YAIresoMQ=="],
 
     "ejs": ["ejs@3.1.10", "", { "dependencies": { "jake": "^10.8.5" }, "bin": { "ejs": "bin/cli.js" } }, "sha512-UeJmFfOrAQS8OJWPZ4qtgHyWExa088/MtK5UEyoJGFH67cDEXkZSviOiKRCZ4Xij0zxI3JECgYs3oKx+AizQBA=="],
 
@@ -4750,7 +4739,7 @@
 
     "micromatch": ["micromatch@4.0.8", "", { "dependencies": { "braces": "^3.0.3", "picomatch": "^2.3.1" } }, "sha512-PXwfBhYu0hBCPw8Dn0E+WDYb7af3dSLVWKi3HGv84IdF4TyFoC0ysxFd0Goxw7nSv4T/PzEJQxsYsEiFCKo2BA=="],
 
-    "mime": ["mime@4.1.0", "", { "bin": { "mime": "bin/cli.js" } }, "sha512-X5ju04+cAzsojXKes0B/S4tcYtFAJ6tTMuSPBEn9CPGlrWr8Fiw7qYeLT0XyH80HSoAoqWCaz+MWKh22P7G1cw=="],
+    "mime": ["mime@3.0.0", "", { "bin": { "mime": "cli.js" } }, "sha512-jSCU7/VB1loIWBZe14aEYHU/+1UMEHoaO7qxCOVJOw9GgH72VAWppxNcjU+x9a2k3GSIBXNKxXQFqRvvZ7vr3A=="],
 
     "mime-db": ["mime-db@1.54.0", "", {}, "sha512-aU5EJuIN2WDemCcAp2vFBfp/m4EAhWJnUNSSw0ixs7/kXbd6Pg64EmwJkNdFhB8aWt1sH2CTXrLxo/iAGV3oPQ=="],
 
@@ -4798,10 +4787,6 @@
 
     "ms": ["ms@2.1.3", "", {}, "sha512-6FlzubTLZG3J2a/NVCAleEhjzq5oxgHyaCU9yYXvcLsvoVaHJq/s5xXI6/XXP6tz7R9xAOtHnSO/tXtF3WRTlA=="],
 
-    "msgpackr": ["msgpackr@2.0.5", "", { "optionalDependencies": { "msgpackr-extract": "^3.0.4" } }, "sha512-cef05H/dSYpLpqp3sj/qyZh5vhUYCalnaLO7j1yOmpsR0y/XwLVtK7r5gn+U/F7CTEfMowcGhlUQJDLcLf7jcA=="],
-
-    "msgpackr-extract": ["msgpackr-extract@3.0.4", "", { "dependencies": { "node-gyp-build-optional-packages": "5.2.2" }, "optionalDependencies": { "@msgpackr-extract/msgpackr-extract-darwin-arm64": "3.0.4", "@msgpackr-extract/msgpackr-extract-darwin-x64": "3.0.4", "@msgpackr-extract/msgpackr-extract-linux-arm": "3.0.4", "@msgpackr-extract/msgpackr-extract-linux-arm64": "3.0.4", "@msgpackr-extract/msgpackr-extract-linux-x64": "3.0.4", "@msgpackr-extract/msgpackr-extract-win32-x64": "3.0.4" }, "bin": { "download-msgpackr-prebuilds": "bin/download-prebuilds.js" } }, "sha512-4kmO/MdyUIkLIvTPr8VHLil4AtoKIoniWPIEk5+CDy0xnWC84azhSFmuJ7PxZdsYtiP5kEeQsORAVIeMgxT+Hw=="],
-
     "muggle-string": ["muggle-string@0.4.1", "", {}, "sha512-VNTrAak/KhO2i8dqqnqnAHOa3cYBwXEZe9h+D5h/1ZqFSTEFHdM65lR7RoIqq3tBBYavsOXV84NoHXZ0AkPyqQ=="],
 
     "mustache": ["mustache@4.2.0", "", { "bin": { "mustache": "bin/mustache" } }, "sha512-71ippSywq5Yb7/tVYyGbkBggbU8H3u5Rz56fH60jGFgr8uHwxs+aSKeqmluIVzM0m0kB7xQjKS6qPfd0b2ZoqQ=="],
@@ -4844,8 +4829,6 @@
 
     "node-gyp-build": ["node-gyp-build@4.8.4", "", { "bin": { "node-gyp-build": "bin.js", "node-gyp-build-optional": "optional.js", "node-gyp-build-test": "build-test.js" } }, "sha512-LA4ZjwlnUblHVgq0oBF3Jl/6h/Nvs5fzBLwdEF4nuxnFdsfajde4WfxtJr3CaiH+F6ewcIB/q4jQ4UzPyid+CQ=="],
 
-    "node-gyp-build-optional-packages": ["node-gyp-build-optional-packages@5.2.2", "", { "dependencies": { "detect-libc": "^2.0.1" }, "bin": { "node-gyp-build-optional-packages": "bin.js", "node-gyp-build-optional-packages-optional": "optional.js", "node-gyp-build-optional-packages-test": "build-test.js" } }, "sha512-s+w+rBWnpTMwSFbaE0UXsRlg7hU4FjekKU4eyAih5T8nJuNZT1nNsskXpxmeqSK9UzkBl6UgRlnKc8hz8IEqOw=="],
-
     "node-html-parser": ["node-html-parser@7.1.0", "", { "dependencies": { "css-select": "^5.1.0", "he": "1.2.0" } }, "sha512-iJo8b2uYGT40Y8BTyy5ufL6IVbN8rbm/1QK2xffXU/1a/v3AAa0d1YAoqBNYqaS4R/HajkWIpIfdE6KcyFh1AQ=="],
 
     "node-int64": ["node-int64@0.4.0", "", {}, "sha512-O5lz91xSOeoXP6DulyHfllpq+Eg00MWitZIbtPfoSEvqIHdl5gfcY6hYzDWnj0qD5tz52PI08u9qUvSVeUBeHw=="],
@@ -5628,7 +5611,7 @@
 
     "typesafe-path": ["typesafe-path@0.2.2", "", {}, "sha512-OJabfkAg1WLZSqJAJ0Z6Sdt3utnbzr/jh+NAHoyWHJe8CMSy79Gm085094M9nvTPy22KzTVn5Zq5mbapCI/hPA=="],
 
-    "typescript": ["typescript@5.8.2", "", { "bin": { "tsc": "bin/tsc", "tsserver": "bin/tsserver" } }, "sha512-aJn6wq13/afZp/jT9QZmwEjDqqvSGp1VT5GVg+f/t6/oVyrgXM6BY1h9BRh/O5p3PlUPAe+WuiEZOmb/49RqoQ=="],
+    "typescript": ["typescript@5.9.3", "", { "bin": { "tsc": "bin/tsc", "tsserver": "bin/tsserver" } }, "sha512-jl1vZzPDinLr9eUt3J/t7V6FgNEw9QjvBPdysz9KfQDD41fQrC2Y4vKQdiaUpFT4bXlb1RHhLpp8wtm6M5TgSw=="],
 
     "typescript-auto-import-cache": ["typescript-auto-import-cache@0.3.6", "", { "dependencies": { "semver": "^7.3.8" } }, "sha512-RpuHXrknHdVdK7wv/8ug3Fr0WNsNi5l5aB8MYYuXhq2UH5lnEB1htJ1smhtD5VeCsGr2p8mUDtd83LCQDFVgjQ=="],
 
@@ -5642,7 +5625,7 @@
 
     "uncrypto": ["uncrypto@0.1.3", "", {}, "sha512-Ql87qFHB3s/De2ClA9e0gsnS6zXG27SkTiSJwjCc9MebbfapQfuPzumMIUMi38ezPZVNFcHI9sUIepeQfw8J8Q=="],
 
-    "undici": ["undici@8.10.0", "", {}, "sha512-HvltHd7avK13QIw/oLe4qoOLyoVSoafqJ2jYOrtMRBkbYT31eiBQ8O0ehRKZiEZCMEyLFQNIADpgCWC5fALvYQ=="],
+    "undici": ["undici@8.11.2", "", {}, "sha512-u4UB2/IrKdU6lFxumHmmo1a3fCQO5tzQllRorfoRS63txhrB7xTpSn1PftwC4qEHkOaqP95fCWW4lJzwErwzhQ=="],
 
     "undici-types": ["undici-types@7.16.0", "", {}, "sha512-Zz+aZWSj8LE6zoxD+xrjh4VfkIG8Ya6LvYkZqtUQGJPZjYl53ypCaUwWqo7eI0x66KBGeRo+mlBEkMSeSZ38Nw=="],
 
@@ -6094,15 +6077,13 @@
 
     "@bufbuild/protoplugin/typescript": ["typescript@5.4.5", "", { "bin": { "tsc": "bin/tsc", "tsserver": "bin/tsserver" } }, "sha512-vcI4UpRgg81oIRUFwR0WSIHKt11nJ7SAVlYNIu+QpqeyXP+gpQJy/Z4+F0aGxSE4MqwjyXvW/TzgkLAx2AGHwQ=="],
 
-    "@cloudflare/kv-asset-handler/mime": ["mime@3.0.0", "", { "bin": { "mime": "cli.js" } }, "sha512-jSCU7/VB1loIWBZe14aEYHU/+1UMEHoaO7qxCOVJOw9GgH72VAWppxNcjU+x9a2k3GSIBXNKxXQFqRvvZ7vr3A=="],
-
     "@cloudflare/vite-plugin/vite": ["vite@7.3.6", "", { "dependencies": { "esbuild": "^0.27.0 || ^0.28.0", "fdir": "^6.5.0", "picomatch": "^4.0.3", "postcss": "^8.5.6", "rollup": "^4.43.0", "tinyglobby": "^0.2.15" }, "optionalDependencies": { "fsevents": "~2.3.3" }, "peerDependencies": { "@types/node": "^20.19.0 || >=22.12.0", "jiti": ">=1.21.0", "less": "^4.0.0", "lightningcss": "^1.21.0", "sass": "^1.70.0", "sass-embedded": "^1.70.0", "stylus": ">=0.54.8", "sugarss": "^5.0.0", "terser": "^5.16.0", "tsx": "^4.8.1", "yaml": "^2.4.2" }, "optionalPeers": ["@types/node", "jiti", "less", "lightningcss", "sass", "sass-embedded", "stylus", "sugarss", "terser", "tsx", "yaml"], "bin": { "vite": "bin/vite.js" } }, "sha512-4XP60spRGjSZFf1qYH+dJIkK2znL3zQfl9KkOV9MkkRR/3Dls0dxaBsQPTloEc5BLXWPL9vsOxopxyKoMmDueg=="],
 
     "@cloudflare/vite-plugin/ws": ["ws@8.18.0", "", { "peerDependencies": { "bufferutil": "^4.0.1", "utf-8-validate": ">=5.0.2" }, "optionalPeers": ["bufferutil", "utf-8-validate"] }, "sha512-8VbfWfHLbbwu3+N6OKsOMpBdT4kXPDDB9cJk2bJ6mh9ucxdlnNvH1e+roYkKmN9Nxw2yjz7VzeO9oOz2zJ04Pw=="],
 
     "@cspotcode/source-map-support/@jridgewell/trace-mapping": ["@jridgewell/trace-mapping@0.3.9", "", { "dependencies": { "@jridgewell/resolve-uri": "^3.0.3", "@jridgewell/sourcemap-codec": "^1.4.10" } }, "sha512-3Belt6tdc8bPgAtbcmdtNJlirVoTmEb5e2gC94PnkwEW9jI6CAHUeoG85tjWP5WquqfavoMtMwiG4P926ZKKuQ=="],
 
-    "@effect/platform-node-shared/ws": ["ws@8.21.3", "", { "peerDependencies": { "bufferutil": "^4.0.1", "utf-8-validate": ">=5.0.2" }, "optionalPeers": ["bufferutil", "utf-8-validate"] }, "sha512-201TZ/kPWxoPr/OKWjquZR1SWKXcvxdH+e1xrx89b3YbmzLMFCLfnaG1HFIgWzJOEWZ7MvpK++odZufgYR50Rw=="],
+    "@effect/platform-node-shared/ws": ["ws@8.22.0", "", { "peerDependencies": { "bufferutil": "^4.0.1", "utf-8-validate": ">=5.0.2" }, "optionalPeers": ["bufferutil", "utf-8-validate"] }, "sha512-Ydggc987+RO0AnWtZ/7Wq9FtNvcrL1b/RO0ud9mWjUPgDrsAAwQSF51sm2hm1XofbU/4jkpGEsLFsZZxU+1DOg=="],
 
     "@electron/asar/commander": ["commander@5.1.0", "", {}, "sha512-P0CysNDQ7rtVw4QIQtm+MRxV66vKFSvlsQvGYXZWR3qFU0jlMKHZZZgw8e+8DSah4UDKMqnknRDQz+xuQXQ/Zg=="],
 
@@ -6234,8 +6215,6 @@
 
     "@opencode/console-support/vite": ["vite@7.3.6", "", { "dependencies": { "esbuild": "^0.27.0 || ^0.28.0", "fdir": "^6.5.0", "picomatch": "^4.0.3", "postcss": "^8.5.6", "rollup": "^4.43.0", "tinyglobby": "^0.2.15" }, "optionalDependencies": { "fsevents": "~2.3.3" }, "peerDependencies": { "@types/node": "^20.19.0 || >=22.12.0", "jiti": ">=1.21.0", "less": "^4.0.0", "lightningcss": "^1.21.0", "sass": "^1.70.0", "sass-embedded": "^1.70.0", "stylus": ">=0.54.8", "sugarss": "^5.0.0", "terser": "^5.16.0", "tsx": "^4.8.1", "yaml": "^2.4.2" }, "optionalPeers": ["@types/node", "jiti", "less", "lightningcss", "sass", "sass-embedded", "stylus", "sugarss", "terser", "tsx", "yaml"], "bin": { "vite": "bin/vite.js" } }, "sha512-4XP60spRGjSZFf1qYH+dJIkK2znL3zQfl9KkOV9MkkRR/3Dls0dxaBsQPTloEc5BLXWPL9vsOxopxyKoMmDueg=="],
 
-    "@opencode/desktop/typescript": ["typescript@5.6.3", "", { "bin": { "tsc": "bin/tsc", "tsserver": "bin/tsserver" } }, "sha512-hjcS1mhfuyi4WW8IWtjP7brDrG2cuDZukyrYrSauoXGNgx0S7zceP07adYkJycEr56BOUTNPzbInooiN3fn1qw=="],
-
     "@opencode/enterprise/@tailwindcss/vite": ["@tailwindcss/vite@4.1.11", "", { "dependencies": { "@tailwindcss/node": "4.1.11", "@tailwindcss/oxide": "4.1.11", "tailwindcss": "4.1.11" }, "peerDependencies": { "vite": "^5.2.0 || ^6 || ^7" } }, "sha512-RHYhrR3hku0MJFRV+fN2gNbDNEh3dwKvY8XJvTxCSXeMOsCRSr+uKvDWQcbizrHgjML6ZmTE5OwMrl5wKcujCw=="],
 
     "@opencode/enterprise/tailwindcss": ["tailwindcss@4.1.11", "", {}, "sha512-2E9TBm6MDD/xKYe+dvJZAmg3yxIEDNRc0jwlNyDg/4Fil2QcSLjFKGVff0lAf1jjeaArlG/M75Ey/EYr/OJtBA=="],
@@ -6694,6 +6673,8 @@
 
     "tw-to-css/tailwindcss": ["tailwindcss@3.3.2", "", { "dependencies": { "@alloc/quick-lru": "^5.2.0", "arg": "^5.0.2", "chokidar": "^3.5.3", "didyoumean": "^1.2.2", "dlv": "^1.1.3", "fast-glob": "^3.2.12", "glob-parent": "^6.0.2", "is-glob": "^4.0.3", "jiti": "^1.18.2", "lilconfig": "^2.1.0", "micromatch": "^4.0.5", "normalize-path": "^3.0.0", "object-hash": "^3.0.0", "picocolors": "^1.0.0", "postcss": "^8.4.23", "postcss-import": "^15.1.0", "postcss-js": "^4.0.1", "postcss-load-config": "^4.0.1", "postcss-nested": "^6.0.1", "postcss-selector-parser": "^6.0.11", "postcss-value-parser": "^4.2.0", "resolve": "^1.22.2", "sucrase": "^3.32.0" }, "bin": { "tailwind": "lib/cli.js", "tailwindcss": "lib/cli.js" } }, "sha512-9jPkMiIBXvPc2KywkraqsUfbfj+dHDb+JPWtSJa9MLFdrPyazI7q6WX2sUrm7R9eVR7qqv3Pas7EvQFzxKnI6w=="],
 
+    "unifont/undici": ["undici@8.10.0", "", {}, "sha512-HvltHd7avK13QIw/oLe4qoOLyoVSoafqJ2jYOrtMRBkbYT31eiBQ8O0ehRKZiEZCMEyLFQNIADpgCWC5fALvYQ=="],
+
     "unplugin/acorn": ["acorn@8.18.0", "", { "bin": { "acorn": "bin/acorn" } }, "sha512-lGq+9yr1/GuAWaVYIHRjvvySG5/4VfKIvC8EWxStPdcDh/Ka7FG3twP6v4d5BkravUilhIAsG4Qj83t02LWUPQ=="],
 
     "unused-filename/escape-string-regexp": ["escape-string-regexp@5.0.0", "", {}, "sha512-/veY75JbMK4j1yjvuUxuVsiS/hr/4iHs9FTT6cgTexxdE0Ly/glccBAkloH/DofkjRbZU3bnoj38mOmhkZ0lHw=="],

nix/hashes.json

@@ -1,7 +1,7 @@
 {
   "nodeModules": {
-    "x86_64-linux": "sha256-yCdtDQsXERjfL9bJg7YXNloMBOPwFkPMFVNAzXlarBM=",
-    "aarch64-linux": "sha256-iQ1bLIszETcFoD4CENpoaDZJZF/KBKZFeTp9r7ogJ9Y=",
-    "aarch64-darwin": "sha256-G7oIrTXEFQ5iEF8KSpA4xJPw9xwqRDpbIR472iIoqC4="
+    "x86_64-linux": "sha256-g3k0cAFGqzmRYlcIkg1NDvlx1WxHYhnYPL0/a8E+qTg=",
+    "aarch64-linux": "sha256-a+3ymqdxOONGe2Tpq4GUccl1b+Dwzxlb9LFXgE1gZ+0=",
+    "aarch64-darwin": "sha256-h8xIzuMmaWfJqjHCO74xUDCWNKQLFrIGoKYZ+2TauYc="
   }
 }

package.json

@@ -42,10 +42,10 @@
       "packages/stats/*"
     ],
     "catalog": {
-      "@effect/opentelemetry": "4.0.0-rc.112",
-      "@effect/platform-node": "4.0.0-rc.112",
-      "@effect/platform-node-shared": "4.0.0-rc.112",
-      "@effect/sql-sqlite-bun": "4.0.0-rc.112",
+      "@effect/opentelemetry": "4.0.0",
+      "@effect/platform-node": "4.0.0",
+      "@effect/platform-node-shared": "4.0.0",
+      "@effect/sql-sqlite-bun": "4.0.0",
       "@npmcli/arborist": "9.4.0",
       "@types/bun": "1.4.0",
       "@types/cross-spawn": "6.0.6",
@@ -79,7 +79,7 @@
       "dompurify": "3.4.14",
       "drizzle-kit": "1.0.0-rc.5-ab785fc",
       "drizzle-orm": "1.0.0-rc.5-169397b",
-      "effect": "4.0.0-rc.112",
+      "effect": "4.0.0",
       "ai": "6.0.168",
       "cross-spawn": "7.0.6",
       "hono": "4.10.7",
@@ -92,7 +92,7 @@
       "remend": "1.3.1",
       "@playwright/test": "1.59.1",
       "semver": "7.7.4",
-      "typescript": "5.8.2",
+      "typescript": "5.9.3",
       "@typescript/native-preview": "7.0.0-dev.20251207.1",
       "zod": "4.1.8",
       "remeda": "2.26.0",

packages/ai/example/tutorial.ts

@@ -15,7 +15,7 @@ import { OpenAI } from "@opencode/ai/providers"
  * hover imports and local values to see how the public API is typed.
  */
 
-const apiKey = Config.redacted("OPENAI_API_KEY")
+const apiKey = Config.Redacted("OPENAI_API_KEY")
 
 // 1. Configure a provider. The configured facade records provider identity,
 // deployment options, authentication, and defaults. Per-modality selectors pick

packages/ai/script/setup-recording-env.ts

@@ -5,7 +5,7 @@ import * as path from "node:path"
 import * as prompts from "@clack/prompts"
 import { AwsV4Signer } from "aws4fetch"
 import { Config, ConfigProvider, Effect, FileSystem, PlatformError, Redacted } from "effect"
-import { FetchHttpClient, HttpClient, HttpClientRequest, type HttpClientResponse } from "effect/unstable/http"
+import { FetchHttpClient, HttpClient, HttpClientRequest, type HttpClientResponse } from "effect/http"
 import * as ProviderShared from "../src/protocols/shared"
 import { CloudflareAIGateway } from "../src/providers/cloudflare-ai-gateway.js"
 import { CloudflareWorkersAI } from "../src/providers/cloudflare-workers-ai.js"
@@ -383,7 +383,7 @@ const readEnvFile = Effect.fn("RecordingEnv.readFile")(function* () {
 })
 
 const readConfigString = (provider: ConfigProvider.ConfigProvider, name: string) =>
-  Config.string(name)
+  Config.String(name)
     .parse(provider)
     .pipe(
       Effect.match({

packages/ai/src/cache-policy.ts

@@ -49,6 +49,7 @@ const RESPECTS_INLINE_HINTS = new Set([
   "zai-coding-messages",
   "bedrock-converse",
   "openrouter",
+  "digitalocean",
 ])
 
 // OpenRouter upstreams other than Anthropic and Alibaba Qwen cache without breakpoints. Gemini uses only the last

packages/ai/src/experimental/system-one.ts

@@ -1,5 +1,5 @@
 import { Effect, Schema } from "effect"
-import { Headers, HttpClientRequest } from "effect/unstable/http"
+import { Headers, HttpClientRequest } from "effect/http"
 import {
   ChoiceQuestion,
   EvaluationInput,

packages/ai/src/image.ts

@@ -1,4 +1,5 @@
 import { Effect, Schema, Stream } from "effect"
+import { extendSchema } from "@opencode/schema/schema"
 import { Generation, ProgressEvent, QueuedEvent, type AwaitOptions } from "./generation.js"
 import { Media } from "./media.js"
 import { MediaModel, composeRoute, tryRequest } from "./media-model.js"
@@ -142,7 +143,7 @@ const imageEventTagged = Schema.Union([
   ImageOutputEvent,
   ImageFinishEvent,
 ]).pipe(Schema.toTaggedUnion("type"))
-export const ImageEvent = Object.assign(imageEventTagged, {
+export const ImageEvent = extendSchema(imageEventTagged, {
   is: {
     generationQueued: imageEventTagged.guards["generation-queued"],
     generationProgress: imageEventTagged.guards["generation-progress"],

packages/ai/src/media.ts

@@ -1,7 +1,8 @@
 export * as Media from "./media.js"
 
-import { Effect, Encoding, FileSystem, Schema, SchemaGetter } from "effect"
-import { HttpClientRequest } from "effect/unstable/http"
+import { Effect, FileSystem, Schema, SchemaGetter } from "effect"
+import { Base64 } from "effect/encoding"
+import { HttpClientRequest } from "effect/http"
 import { ProviderID } from "./schema/ids.js"
 import { AIError, HttpContext, InvalidProviderOutputError, InvalidRequestError } from "./schema/errors.js"
 import { ProviderMetadata } from "./schema/options.js"
@@ -140,7 +141,7 @@ export class Asset {
   inline(): Inline | undefined {
     const source = this.source
     if (source.type !== "bytes" && source.type !== "base64") return undefined
-    const base64 = source.type === "base64" ? source.data : (this.#base64 ??= Encoding.encodeBase64(source.data))
+    const base64 = source.type === "base64" ? source.data : (this.#base64 ??= Base64.encode(source.data))
     const mime = this.mediaType.toLowerCase()
     return { mime, base64, dataUrl: `data:${mime};base64,${base64}` }
   }
@@ -155,7 +156,7 @@ export class Asset {
         return Effect.fail(invalid(`Cannot materialize provider ref ${source.provider}:${source.id}`))
       const decoded =
         source.type === "base64"
-          ? Effect.fromResult(Encoding.decodeBase64(source.data)).pipe(
+          ? Effect.fromResult(Base64.decode(source.data)).pipe(
               Effect.mapError((cause) => invalid(`Media asset contains invalid base64 data`, cause)),
             )
           : download(source, this.headers)
@@ -168,7 +169,7 @@ export class Asset {
       const source = this.source
       if (source.type === "base64") return Effect.succeed(source.data)
       if (this.#base64 !== undefined) return Effect.succeed(this.#base64)
-      return this.bytes().pipe(Effect.map((data) => (this.#base64 = Encoding.encodeBase64(data))))
+      return this.bytes().pipe(Effect.map((data) => (this.#base64 = Base64.encode(data))))
     })
   }
 
@@ -183,7 +184,7 @@ export class Asset {
   toJSON() {
     const source = this.source
     return {
-      source: source.type === "bytes" ? { ...source, data: Encoding.encodeBase64(source.data) } : source,
+      source: source.type === "bytes" ? { ...source, data: Base64.encode(source.data) } : source,
       info: this.info,
       providerMetadata: this.providerMetadata,
     }

packages/ai/src/protocols/anthropic-messages.ts

@@ -6,7 +6,7 @@ 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 { Headers } from "effect/unstable/http"
+import { Headers } from "effect/http"
 import { HttpTransport } from "../route/transport/index.js"
 import {
   AIError,
@@ -451,6 +451,9 @@ const AnthropicStreamDelta = Schema.Struct({
   signature: Schema.optional(Schema.String),
   stop_reason: optionalNull(Schema.String),
   stop_sequence: optionalNull(Schema.String),
+  stop_details: optionalNull(
+    Schema.Struct({ category: optionalNull(Schema.String), explanation: optionalNull(Schema.String) }),
+  ),
 })
 type AnthropicStreamDelta = Schema.Schema.Type<typeof AnthropicStreamDelta>
 const decodeAnthropicStreamDelta = Schema.decodeUnknownOption(AnthropicStreamDelta)
@@ -804,15 +807,12 @@ const requireThinkingSignature = (request: LLMRequest) => {
 // Mid-conversation system messages became available with Opus 4.8 and version
 // 5 of the other supported Claude families. Treat later family versions as
 // compatible without assuming that every Anthropic Messages model is Claude.
+// Opus 4.8 and every Claude 5 model accept mid-conversation system messages; later versions inherit support.
 const supportsNativeSystemUpdates = (request: LLMRequest) => {
-  const match = /(?:^|[./])claude-(fable|haiku|mythos|opus|sonnet)-(\d+)(?:[.-](\d+))?/.exec(
-    String(request.model.id).toLowerCase(),
-  )
-  if (!match) return false
-  const major = Number(match[2])
-  if (match[1] !== "opus") return major >= 5
-  if (major !== 4) return major >= 5
-  return match[3] !== undefined && match[3].length <= 2 && Number(match[3]) >= 8
+  const version = claudeVersion(String(request.model.id))
+  if (version === undefined) return false
+  if (version.family === "opus" && version.major === 4) return version.minor >= 8
+  return version.major >= 5
 }
 
 const endsInServerToolUse = (message: LLMRequest["messages"][number]) => {
@@ -989,13 +989,13 @@ const lowerMessages = Effect.fn("AnthropicMessages.lowerMessages")(function* (
   return messages
 })
 
+// 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
   if (override !== undefined) return override
   const version = claudeVersion(model.id)
   if (version === undefined) return false
-  if (version.family === "opus") return version.major >= 5
-  if (version.family !== "fable" && version.family !== "mythos") return false
+  if (version.family === "opus" && version.major >= 5) return true
   return version.major > 5 || (version.major === 5 && version.minor >= 1)
 }
 
@@ -1417,10 +1417,14 @@ const onMessageDelta = (
       stopSequence === null || stopSequence === undefined
         ? state.pendingFinish?.providerMetadata
         : providerMetadata(state.providerMetadataKey, { stopSequence })
+    const category = event.delta?.stop_details?.category
+    const explanation = event.delta?.stop_details?.explanation
     return {
       reason: {
         normalized: mapFinishReason(stopReason),
         raw: stopReason,
+        ...(category ? { category } : {}),
+        ...(explanation ? { explanation } : {}),
       },
       providerMetadata: finishMetadata,
     }

packages/ai/src/protocols/assemblyai-transcription.ts

@@ -1,5 +1,5 @@
 import { Effect, Schema } from "effect"
-import type { HttpClientResponse } from "effect/unstable/http"
+import type { HttpClientResponse } from "effect/http"
 import type { Status } from "../generation.js"
 import { Media } from "../media.js"
 import { MediaProtocol } from "../route/media-protocol.js"

packages/ai/src/protocols/bedrock-converse.ts

@@ -1,4 +1,5 @@
-import { Effect, Encoding, Schema } from "effect"
+import { Effect, Schema } from "effect"
+import { Base64 } from "effect/encoding"
 import { Route } from "../route/client.js"
 import { Endpoint } from "../route/endpoint.js"
 import { Protocol } from "../route/protocol.js"
@@ -319,6 +320,9 @@ const lowerToolResult = Effect.fn("BedrockConverse.lowerToolResult")(function* (
   } satisfies BedrockToolResultBlock
 })
 
+// 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* (
   request: LLMRequest,
   breakpoints: BedrockCache.Breakpoints,
@@ -328,8 +332,19 @@ const lowerMessages = Effect.fn("BedrockConverse.lowerMessages")(function* (
   // Mistral can reject replay IDs even when they satisfy Converse's broader ID syntax.
   const normalizeID = request.model.id.includes("mistral.") ? MistralToolID.normalizer(request) : (id: string) => id
   const providerMetadataKey = request.model.route.providerMetadataKey ?? String(request.model.provider)
+  const hoistImages = !keepToolImagesInline(request.model.id)
+  // Bedrock expects parallel tool results before any images hoisted beside them.
+  const pendingImages: BedrockMedia.ImageBlock[] = []
+  const flushImages = () => {
+    if (pendingImages.length === 0) return
+    const previous = messages.at(-1)
+    if (previous?.role === "user")
+      messages[messages.length - 1] = { role: "user", content: [...previous.content, ...pendingImages] }
+    pendingImages.length = 0
+  }
 
   for (const message of request.messages) {
+    if (message.role !== "tool") flushImages()
     if (message.role === "system") {
       const part = yield* ProviderShared.wrappedSystemUpdate("Bedrock Converse", message)
       const content = textWithCache(breakpoints, part.text, part.cache)
@@ -403,7 +418,22 @@ const lowerMessages = Effect.fn("BedrockConverse.lowerMessages")(function* (
     for (const part of message.content) {
       if (!ProviderShared.supportsContent(part, ["tool-result"]))
         return yield* ProviderShared.unsupportedContent("Bedrock Converse", "tool", ["tool-result"])
-      content.push(yield* lowerToolResult(part, documentNames, normalizeID))
+      const result = yield* lowerToolResult(part, documentNames, normalizeID)
+      const images: BedrockMedia.ImageBlock[] = hoistImages
+        ? result.toolResult.content.filter((item) => "image" in item)
+        : []
+      const nonImageContent = result.toolResult.content.filter((item) => !("image" in item))
+      content.push(
+        images.length === 0
+          ? result
+          : {
+              toolResult: {
+                ...result.toolResult,
+                content: nonImageContent.length > 0 ? nonImageContent : [{ text: "See attached image." }],
+              },
+            },
+      )
+      pendingImages.push(...images)
       const cachePoint = BedrockCache.block(breakpoints, part.cache)
       if (cachePoint) content.push(cachePoint)
     }
@@ -413,6 +443,7 @@ const lowerMessages = Effect.fn("BedrockConverse.lowerMessages")(function* (
     else messages.push({ role: "user", content })
   }
 
+  flushImages()
   return messages
 })
 
@@ -580,7 +611,7 @@ interface ParserState {
   readonly reasoningRedactedContent: Readonly<Record<number, Uint8Array[]>>
 }
 
-const encodeRedactedContent = (chunks: ReadonlyArray<Uint8Array>) => Encoding.encodeBase64(concatBytes(chunks))
+const encodeRedactedContent = (chunks: ReadonlyArray<Uint8Array>) => Base64.encode(concatBytes(chunks))
 
 const step = (state: ParserState, event: BedrockEvent) =>
   Effect.gen(function* () {
@@ -629,7 +660,7 @@ const step = (state: ParserState, event: BedrockEvent) =>
       const events: LLMEvent[] = []
       const redactedChunk = yield* (() => {
         if (reasoning.redactedContent === undefined) return Effect.succeed(undefined)
-        return Effect.fromResult(Encoding.decodeBase64(reasoning.redactedContent)).pipe(
+        return Effect.fromResult(Base64.decode(reasoning.redactedContent)).pipe(
           Effect.mapError((cause) =>
             ProviderShared.eventError(
               ADAPTER,

packages/ai/src/protocols/bedrock-event-stream.ts

@@ -1,6 +1,7 @@
 import { EventStreamCodec } from "@smithy/eventstream-codec"
 import { fromUtf8, toUtf8 } from "@smithy/util-utf8"
-import { Effect, Encoding, Stream } from "effect"
+import { Effect, Stream } from "effect"
+import { Base64 } from "effect/encoding"
 import { AIError, AIErrorReason, InvalidProviderOutputError } from "../schema/index.js"
 import { Framing } from "../route/framing.js"
 import { ProviderShared } from "./shared.js"
@@ -47,7 +48,7 @@ const consumeFrames = (route: string) => (state: FrameBufferState, input: FrameI
             route,
             classification: "incomplete-stream",
             message: `Incomplete Bedrock Converse event-stream frame: ${remaining.length} buffered bytes remain at end of stream`,
-            body: Encoding.encodeBase64(remaining),
+            body: Base64.encode(remaining),
           }),
         })
       return [state, []] as const
@@ -68,7 +69,7 @@ const consumeFrames = (route: string) => (state: FrameBufferState, input: FrameI
             `Failed to decode Bedrock Converse event-stream frame: ${
               error instanceof Error ? error.message : String(error)
             }`,
-            Encoding.encodeBase64(view.subarray(0, totalLength)),
+            Base64.encode(view.subarray(0, totalLength)),
             error,
           ),
       })

packages/ai/src/protocols/bfl-images.ts

@@ -1,5 +1,5 @@
 import { Effect, Schema } from "effect"
-import type { HttpClientResponse } from "effect/unstable/http"
+import type { HttpClientResponse } from "effect/http"
 import type { Status } from "../generation.js"
 import { ImageModel, ImageResponse, type ImageRequestFor } from "../image.js"
 import { Media } from "../media.js"

packages/ai/src/protocols/deepgram-transcription.ts

@@ -1,5 +1,5 @@
 import { Effect, Schema } from "effect"
-import type { HttpClientResponse } from "effect/unstable/http"
+import type { HttpClientResponse } from "effect/http"
 import { MediaProtocol } from "../route/media-protocol.js"
 import { MediaRoute } from "../route/media.js"
 import { mergeJsonRecords, type OpenString } from "../schema/index.js"

packages/ai/src/protocols/elevenlabs-transcription.ts

@@ -1,5 +1,5 @@
 import { Effect, Schema } from "effect"
-import type { HttpClientResponse } from "effect/unstable/http"
+import type { HttpClientResponse } from "effect/http"
 import { MediaProtocol } from "../route/media-protocol.js"
 import { MediaRoute } from "../route/media.js"
 import { mergeJsonRecords, type OpenString } from "../schema/index.js"

packages/ai/src/protocols/fal-images.ts

@@ -1,5 +1,5 @@
 import { Effect, Schema } from "effect"
-import type { HttpClientResponse } from "effect/unstable/http"
+import type { HttpClientResponse } from "effect/http"
 import { ImageModel, ImageResponse, type ImageRequestFor } from "../image.js"
 import { Media } from "../media.js"
 import { MediaProtocol } from "../route/media-protocol.js"

packages/ai/src/protocols/fal-video.ts

@@ -1,5 +1,5 @@
 import { Effect, Schema } from "effect"
-import type { HttpClientResponse } from "effect/unstable/http"
+import type { HttpClientResponse } from "effect/http"
 import { Media } from "../media.js"
 import { MediaProtocol } from "../route/media-protocol.js"
 import { MediaRoute } from "../route/media.js"

packages/ai/src/protocols/google-images.ts

@@ -1,5 +1,5 @@
 import { Effect, Schema } from "effect"
-import type { HttpClientResponse } from "effect/unstable/http"
+import type { HttpClientResponse } from "effect/http"
 import { ImageModel, ImageResponse, type ImageRequestFor } from "../image.js"
 import { MediaProtocol } from "../route/media-protocol.js"
 import { MediaRoute } from "../route/media.js"

packages/ai/src/protocols/google-video.ts

@@ -1,5 +1,5 @@
 import { Duration, Effect, Schema } from "effect"
-import type { HttpClientResponse } from "effect/unstable/http"
+import type { HttpClientResponse } from "effect/http"
 import type { Status } from "../generation.js"
 import { Media } from "../media.js"
 import { MediaProtocol } from "../route/media-protocol.js"

packages/ai/src/protocols/meta-images.ts

@@ -1,5 +1,5 @@
 import { Effect, Schema } from "effect"
-import type { HttpClientResponse } from "effect/unstable/http"
+import type { HttpClientResponse } from "effect/http"
 import { ImageModel, ImageResponse, type ImageRequestFor } from "../image.js"
 import { Media } from "../media.js"
 import { MediaProtocol } from "../route/media-protocol.js"

packages/ai/src/protocols/meta-responses.ts

@@ -1,4 +1,5 @@
-import { Effect, Encoding, Schema } from "effect"
+import { Effect, Schema } from "effect"
+import { Base64 } from "effect/encoding"
 import { Protocol } from "../route/protocol.js"
 import { HttpTransport } from "../route/transport/index.js"
 import { LLMEvent, LLMRequest, Message, ToolResultPart } from "../schema/index.js"
@@ -135,7 +136,7 @@ const HOSTED_TOOLS = {
           "Meta returned an image without data",
           ProviderShared.encodeJson(raw),
         )
-      const data = yield* Effect.fromResult(Encoding.decodeBase64(item.result)).pipe(
+      const data = yield* Effect.fromResult(Base64.decode(item.result)).pipe(
         Effect.mapError((cause) =>
           ProviderShared.eventError(
             ADAPTER,

packages/ai/src/protocols/open-responses-channel.ts

@@ -1,5 +1,5 @@
 import { Effect, Schema, Stream } from "effect"
-import { Headers } from "effect/unstable/http"
+import { Headers } from "effect/http"
 import { Framing } from "../route/framing.js"
 import type { HttpContext } from "../schema/index.js"
 import {

packages/ai/src/protocols/openai-chat.ts

@@ -212,9 +212,11 @@ const OpenAIChatUsage = Schema.StructWithRest(
     prompt_tokens: optionalNull(Schema.Number),
     completion_tokens: optionalNull(Schema.Number),
     total_tokens: optionalNull(Schema.Number),
-    // Zai reports cache hits as top-level `cached_tokens`; DeepSeek uses `prompt_cache_hit_tokens`.
+    // Provider-specific cache accounting fields.
     cached_tokens: optionalNull(Schema.Number),
     prompt_cache_hit_tokens: optionalNull(Schema.Number),
+    cache_read_input_tokens: optionalNull(Schema.Number),
+    cache_created_input_tokens: optionalNull(Schema.Number),
     prompt_tokens_details: optionalNull(
       Schema.StructWithRest(
         Schema.Struct({
@@ -903,16 +905,19 @@ const mapFinishReason = Effect.fn("OpenAIChat.mapFinishReason")(function* (event
 // satisfied on both sides.
 // Providers differ on cache-hit location: OpenAI uses
 // `prompt_tokens_details.cached_tokens`, DeepSeek uses
-// `prompt_cache_hit_tokens`, and Zai uses top-level `cached_tokens`.
+// `prompt_cache_hit_tokens`, Zai uses top-level `cached_tokens`, and
+// DigitalOcean uses top-level `cache_read_input_tokens` / `cache_created_input_tokens`.
 const mapUsage = (usage: OpenAIChatEvent["usage"], providerMetadataKey: string): Usage | undefined => {
   if (!usage) return undefined
   const input = usage.prompt_tokens ?? undefined
   const output = usage.completion_tokens ?? undefined
-  const cached = (usage.prompt_tokens_details?.cached_tokens ??
-    (usage as { prompt_cache_hit_tokens?: number | null }).prompt_cache_hit_tokens ??
-    (usage as { cached_tokens?: number | null }).cached_tokens ??
-    undefined) as number | undefined
-  const cacheWrite = usage.prompt_tokens_details?.cache_write_tokens ?? undefined
+  const cached =
+    usage.prompt_tokens_details?.cached_tokens ??
+    usage.prompt_cache_hit_tokens ??
+    usage.cached_tokens ??
+    usage.cache_read_input_tokens ??
+    undefined
+  const cacheWrite = usage.prompt_tokens_details?.cache_write_tokens ?? usage.cache_created_input_tokens ?? undefined
   const reasoning = usage.completion_tokens_details?.reasoning_tokens ?? undefined
   const nonCached = ProviderShared.subtractTokens(input, ProviderShared.sumTokens(cached, cacheWrite))
   return new Usage({

packages/ai/src/protocols/openai-responses.ts

@@ -1,5 +1,6 @@
-import { Effect, Encoding, Schema } from "effect"
-import { Headers } from "effect/unstable/http"
+import { Effect, Schema } from "effect"
+import { Base64 } from "effect/encoding"
+import { Headers } from "effect/http"
 import { Route } from "../route/client.js"
 import { Auth } from "../route/auth.js"
 import { Endpoint } from "../route/endpoint.js"
@@ -249,7 +250,7 @@ const checkpointBody = {
 const hostedToolResult = Effect.fn("OpenAIResponses.hostedToolResult")(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(
+    yield* Effect.fromResult(Base64.decode(item.result)).pipe(
       Effect.mapError((cause) =>
         ProviderShared.eventError(ADAPTER, "OpenAI Responses returned invalid image base64", undefined, cause),
       ),

packages/ai/src/protocols/replicate-images.ts

@@ -1,5 +1,5 @@
 import { Duration, Effect, Schema } from "effect"
-import type { HttpClientResponse } from "effect/unstable/http"
+import type { HttpClientResponse } from "effect/http"
 import type { Status } from "../generation.js"
 import { ImageModel, ImageResponse, type ImageRequestFor } from "../image.js"
 import { Media } from "../media.js"

packages/ai/src/protocols/runway-video.ts

@@ -1,5 +1,5 @@
 import { Duration, Effect, Schema } from "effect"
-import type { HttpClientResponse } from "effect/unstable/http"
+import type { HttpClientResponse } from "effect/http"
 import type { Status } from "../generation.js"
 import { Media } from "../media.js"
 import { MediaProtocol } from "../route/media-protocol.js"

packages/ai/src/protocols/shared.ts

@@ -1,6 +1,6 @@
 import { Tool } from "@opencode/schema/tool"
 import { Effect, Option, Schema } from "effect"
-import { Headers, HttpClientRequest } from "effect/unstable/http"
+import { Headers, HttpClientRequest } from "effect/http"
 import { Media } from "../media.js"
 import {
   InvalidProviderOutputError,

packages/ai/src/protocols/stability-images.ts

@@ -1,5 +1,5 @@
 import { Effect, Schema } from "effect"
-import type { HttpClientResponse } from "effect/unstable/http"
+import type { HttpClientResponse } from "effect/http"
 import { ImageModel, ImageResponse, type ImageRequestFor } from "../image.js"
 import { MediaProtocol } from "../route/media-protocol.js"
 import { MediaRoute } from "../route/media.js"

packages/ai/src/protocols/utils/bedrock-auth.ts

@@ -1,6 +1,6 @@
 import { AwsV4Signer } from "aws4fetch"
 import { Effect } from "effect"
-import { Headers } from "effect/unstable/http"
+import { Headers } from "effect/http"
 import { Auth, type AuthInput } from "../../route/auth.js"
 import { AIError, AuthenticationError } from "../../schema/index.js"
 import { ProviderShared } from "../shared.js"

packages/ai/src/protocols/utils/bedrock-media.ts

@@ -1,4 +1,5 @@
-import { Effect, Encoding, Schema } from "effect"
+import { Effect, Schema } from "effect"
+import { Base64 } from "effect/encoding"
 import type { MediaPart } from "../../schema/index.js"
 import { ProviderShared } from "../shared.js"
 
@@ -78,12 +79,12 @@ function documentName(filename: string | undefined, names: Set<string>) {
 
 const mediaBase64 = Effect.fn("BedrockMedia.mediaBase64")(function* (part: MediaPart) {
   const media = yield* ProviderShared.requireInlineMedia("Bedrock Converse", part.media)
-  const bytes = yield* Effect.fromResult(Encoding.decodeBase64(media.base64)).pipe(
+  const bytes = yield* Effect.fromResult(Base64.decode(media.base64)).pipe(
     Effect.mapError((cause) =>
       ProviderShared.invalidRequest("Bedrock Converse media data must be valid base64", cause),
     ),
   )
-  return Encoding.encodeBase64(bytes)
+  return Base64.encode(bytes)
 })
 
 // Route by MIME. Known image/document formats lower into a typed block; anything

packages/ai/src/protocols/utils/cache.ts

@@ -1,4 +1,5 @@
 // Shared counter and TTL mapping for provider cache-marker lowering.
+import type { CacheHint } from "../../schema/index.js"
 
 export interface Breakpoints {
   remaining: number
@@ -11,3 +12,12 @@ export const newBreakpoints = (cap: number): Breakpoints => ({ remaining: cap, d
 // requests omit the wire TTL and use the provider default.
 export const ttlBucket = (ttlSeconds: number | undefined): "1h" | undefined =>
   ttlSeconds !== undefined && ttlSeconds >= 3600 ? "1h" : undefined
+
+export const cacheControl = () => {
+  const breakpoints = newBreakpoints(4)
+  return (cache: CacheHint | undefined) => {
+    if (cache === undefined || breakpoints.remaining === 0) return undefined
+    breakpoints.remaining -= 1
+    return { type: "ephemeral" as const, ttl: ttlBucket(cache.ttlSeconds) }
+  }
+}

packages/ai/src/protocols/utils/fal-queue.ts

@@ -1,5 +1,5 @@
 import { Effect, Schema } from "effect"
-import type { HttpClientResponse } from "effect/unstable/http"
+import type { HttpClientResponse } from "effect/http"
 import type { Status } from "../../generation.js"
 import type { Media } from "../../media.js"
 import { MediaProtocol } from "../../route/media-protocol.js"

packages/ai/src/protocols/utils/media-input.ts

@@ -1,4 +1,5 @@
-import { Effect, Encoding } from "effect"
+import { Effect } from "effect"
+import { Base64 } from "effect/encoding"
 import { Media } from "../../media.js"
 import type { MediaProtocol } from "../../route/media-protocol.js"
 import { mergeJsonRecords, type AIError, type ProviderID } from "../../schema/index.js"
@@ -10,7 +11,7 @@ export const inlineBytes = (route: string, asset: Media.Asset): Effect.Effect<Ui
   if (asset.source.type === "bytes") return Effect.succeed(asset.source.data)
   const inline = asset.inline()
   if (!inline) return Effect.fail(ProviderShared.inlineRequired(route, asset))
-  return Effect.fromResult(Encoding.decodeBase64(inline.base64)).pipe(
+  return Effect.fromResult(Base64.decode(inline.base64)).pipe(
     Effect.mapError((cause) => ProviderShared.invalidRequest(`${route} media contains invalid base64 data`, cause)),
   )
 }
@@ -52,7 +53,7 @@ export const decodedAsset = (
   mediaType: string | undefined,
   options?: Media.AssetOptions,
 ) =>
-  Effect.fromResult(Encoding.decodeBase64(data)).pipe(
+  Effect.fromResult(Base64.decode(data)).pipe(
     Effect.mapError((cause) => invalid(`${label} contains invalid base64 data`, cause)),
     Effect.map((bytes) => Media.bytes(bytes, mediaType, options)),
   )

packages/ai/src/protocols/utils/tool-schema.ts

@@ -63,6 +63,9 @@ const objectRoot = (schema: JsonSchema): JsonSchema => {
     schema.anyOf.some((branch) => isRecord(branch) && branch.type === "object" && Object.keys(branch).length === 1)
   )
     return { type: "object", ...Object.fromEntries(Object.entries(schema).filter(([key]) => key !== "anyOf")) }
+  // Effect 4 represents an empty Struct as `not: { type: "null" }`; an object root already excludes null.
+  if (isRecord(schema.not) && schema.not.type === "null" && Object.keys(schema.not).length === 1)
+    return { type: "object", ...Object.fromEntries(Object.entries(schema).filter(([key]) => key !== "not")) }
   return { type: "object", ...schema }
 }
 

packages/ai/src/protocols/xai-images.ts

@@ -1,5 +1,5 @@
 import { Effect, Schema } from "effect"
-import type { HttpClientResponse } from "effect/unstable/http"
+import type { HttpClientResponse } from "effect/http"
 import { ImageModel, ImageResponse, type ImageRequestFor } from "../image.js"
 import { Media } from "../media.js"
 import { MediaProtocol } from "../route/media-protocol.js"

packages/ai/src/protocols/xai-video.ts

@@ -1,5 +1,5 @@
 import { Effect, Schema } from "effect"
-import type { HttpClientResponse } from "effect/unstable/http"
+import type { HttpClientResponse } from "effect/http"
 import type { Status } from "../generation.js"
 import { Media } from "../media.js"
 import { MediaProtocol } from "../route/media-protocol.js"

packages/ai/src/protocols/zai-images.ts

@@ -1,5 +1,5 @@
 import { Duration, Effect, Schema } from "effect"
-import type { HttpClientResponse } from "effect/unstable/http"
+import type { HttpClientResponse } from "effect/http"
 import { ImageModel, ImageResponse, type ImageRequestFor } from "../image.js"
 import { MediaProtocol } from "../route/media-protocol.js"
 import { MediaRoute } from "../route/media.js"

packages/ai/src/provider-error.ts

@@ -35,6 +35,8 @@ const patterns = [
   /exceeds the limit of \d+/i,
   /exceeds the available context size/i,
   /greater than the context length/i,
+  // Hugging Face Text Generation Inference, e.g. Together
+  /`inputs` tokens \+ `max_new_tokens` must be <= \d+/i,
   /context window exceeds limit/i,
   /exceeded model token limit/i,
   /context[_ ]length[_ ]exceeded/i,

packages/ai/src/providers/digitalocean.ts

@@ -0,0 +1,76 @@
+import type { ProviderPackage } from "../provider-package.js"
+import { OpenAIChat } from "../protocols/openai-chat.js"
+import { cacheControl } from "../protocols/utils/cache.js"
+import { AuthOptions, type ProviderAuthOption } from "../route/auth-options.js"
+import { Route, type RouteDefaultsInput } from "../route/client.js"
+import { Endpoint } from "../route/endpoint.js"
+import { Protocol } from "../route/protocol.js"
+import { ProviderID, type ModelID } from "../schema/index.js"
+import type { OpenAIProviderOptionsInput } from "./openai-options.js"
+
+export const id = ProviderID.make("digitalocean")
+const baseURL = "https://inference.do-ai.run/v1"
+
+export type LanguageModelOptions = Omit<RouteDefaultsInput, "providerOptions"> &
+  ProviderAuthOption<"optional"> & {
+    readonly baseURL?: string
+    readonly providerOptions?: OpenAIProviderOptionsInput
+  }
+
+export type Settings = ProviderPackage.Settings & OpenAIProviderOptionsInput & { readonly apiKey?: string }
+
+export const protocol = Protocol.make({
+  id: "digitalocean-chat",
+  body: {
+    schema: OpenAIChat.protocol.body.schema,
+    from: (request) => OpenAIChat.fromRequest(request, { cacheControl: cacheControl() }),
+  },
+  stream: OpenAIChat.protocol.stream,
+})
+
+export const route = Route.make({
+  id: "digitalocean",
+  provider: id,
+  providerMetadataKey: "digitalocean",
+  protocol,
+  endpoint: Endpoint.path("/chat/completions", { baseURL }),
+  framing: OpenAIChat.framing,
+})
+
+export const routes = [route]
+
+export const configure = (input: LanguageModelOptions = {}) => {
+  const { apiKey: _apiKey, auth: _auth, baseURL: endpoint, ...defaults } = input
+  const configured = route.with({
+    ...defaults,
+    endpoint: { baseURL: endpoint ?? baseURL },
+    auth: AuthOptions.bearer(input, ["DIGITALOCEAN_ACCESS_TOKEN", "DIGITALOCEAN_API_KEY", "DO_INFERENCE_API_KEY"]),
+  })
+  return {
+    id,
+    model: (modelID: string | ModelID) =>
+      configured.model<OpenAIProviderOptionsInput>({
+        id: modelID,
+        compatibility: {
+          supportsPromptCacheKey: true,
+        },
+      }),
+    configure,
+  }
+}
+
+export const provider = configure()
+
+export const model: ProviderPackage.Definition<Settings, OpenAIProviderOptionsInput>["model"] = (
+  modelID,
+  { apiKey, baseURL, body, headers, ...providerOptions },
+) =>
+  configure({
+    apiKey,
+    baseURL,
+    headers,
+    http: { body },
+    providerOptions,
+  }).model(modelID)
+
+export * as DigitalOcean from "./digitalocean.js"

packages/ai/src/providers/google-vertex-messages.ts

@@ -37,7 +37,7 @@ export type Settings = ProviderPackage.Settings &
 const route = Route.make({
   id: "google-vertex-messages",
   provider: id,
-  providerMetadataKey: "anthropic",
+  providerMetadataKey: "vertex",
   protocol: Protocol.make({
     id: AnthropicMessages.protocol.id,
     body: {

packages/ai/src/providers/groq.ts

@@ -71,7 +71,7 @@ export const protocol = Protocol.make({
 export const route = Route.make({
   id: "groq-chat",
   provider: id,
-  providerMetadataKey: "openai",
+  providerMetadataKey: "groq",
   protocol,
   endpoint: Endpoint.path("/chat/completions", { baseURL }),
   framing: OpenAIChat.framing,

packages/ai/src/providers/index.ts

@@ -14,6 +14,7 @@ export * as CloudflareWorkersAI from "./cloudflare-workers-ai.js"
 export * as DeepInfra from "./deepinfra.js"
 export * as Deepgram from "./deepgram.js"
 export * as DeepSeek from "./deepseek.js"
+export * as DigitalOcean from "./digitalocean.js"
 export * as ElevenLabs from "./elevenlabs.js"
 export * as Fal from "./fal.js"
 export * as Fireworks from "./fireworks.js"

packages/ai/src/providers/openrouter.ts

@@ -3,11 +3,11 @@ import { Route, type RouteDefaultsInput } from "../route/client.js"
 import { Endpoint } from "../route/endpoint.js"
 import { Protocol } from "../route/protocol.js"
 import { AuthOptions, type ProviderAuthOption } from "../route/auth-options.js"
-import { HttpOptions, ProviderID, type CacheHint, type ModelID, type OpenString } from "../schema/index.js"
+import { HttpOptions, ProviderID, type ModelID, type OpenString } from "../schema/index.js"
 import type { ProviderPackage } from "../provider-package.js"
 import { SystemOne } from "../experimental/system-one.js"
 import { OpenAIChat } from "../protocols/openai-chat.js"
-import { newBreakpoints, ttlBucket } from "../protocols/utils/cache.js"
+import { cacheControl } from "../protocols/utils/cache.js"
 import { isRecord, ProviderShared } from "../protocols/shared.js"
 
 export const id = ProviderID.make("openrouter")
@@ -131,18 +131,6 @@ export const protocol = Protocol.make({
   stream: OpenAIChat.protocol.stream,
 })
 
-const cacheControl = () => {
-  const breakpoints = newBreakpoints(4)
-  return (cache: CacheHint | undefined) => {
-    if (cache === undefined || breakpoints.remaining === 0) return undefined
-    breakpoints.remaining -= 1
-    return {
-      type: "ephemeral" as const,
-      ...(ttlBucket(cache.ttlSeconds) === "1h" ? { ttl: "1h" } : {}),
-    }
-  }
-}
-
 // OpenRouter forwards `reasoning.max_tokens` as the upstream thinking budget. Upstreams such as Anthropic and Alibaba
 // reject one that is not below the output limit; 1,024 is Anthropic's minimum budget.
 const fitReasoning = (reasoning: Record<string, unknown>, maxTokens: number | undefined) =>

packages/ai/src/providers/vercel-ai-gateway.ts

@@ -1,5 +1,5 @@
 import { Effect, Schema } from "effect"
-import { Headers, HttpClientRequest } from "effect/unstable/http"
+import { Headers, HttpClientRequest } from "effect/http"
 import {
   EvaluationAnswer,
   EvaluationInput,

packages/ai/src/route/auth.ts

@@ -1,5 +1,5 @@
 import { Config, Effect, Option, Redacted } from "effect"
-import { Headers } from "effect/unstable/http"
+import { Headers } from "effect/http"
 import { AuthenticationError, AIError, type HttpOptions } from "../schema/index.js"
 
 export class MissingCredentialError extends Error {
@@ -95,7 +95,7 @@ export const optional = (secret: Secret | undefined, source = "optional value")
 export const config = (name: string) =>
   credential(
     Effect.gen(function* () {
-      const secret = yield* Config.option(Config.redacted(name))
+      const secret = yield* Config.option(Config.Redacted(name))
       if (Option.isSome(secret) && Redacted.value(secret.value) !== "") return secret.value
       return yield* Effect.fail(new MissingCredentialError(name, `${name} is not set`))
     }),

packages/ai/src/route/executor-service.ts

@@ -1,5 +1,5 @@
 import { Context, type Effect } from "effect"
-import type { HttpClientRequest, HttpClientResponse } from "effect/unstable/http"
+import type { HttpClientRequest, HttpClientResponse } from "effect/http"
 import type { AIError } from "../schema/errors.js"
 
 // The service tag lives in its own leaf module so `Media.Asset` (imported by the schema layer) can require the

packages/ai/src/route/executor.ts

@@ -6,7 +6,7 @@ import {
   HttpClientError,
   HttpClientRequest,
   HttpClientResponse,
-} from "effect/unstable/http"
+} from "effect/http"
 import { HttpContext, HttpRateLimitDetails, AIError, TransportError } from "../schema/index.js"
 import { classifyProviderFailure, providerErrorMessage } from "../provider-error.js"
 import { Service, type HttpMiddleware, type Interface } from "./executor-service.js"

packages/ai/src/route/framing.ts

@@ -1,5 +1,5 @@
 import { Effect, Stream } from "effect"
-import { makeParser, type Event } from "effect/unstable/encoding/Sse"
+import { makeParser, type Event } from "effect/encoding/Sse"
 import { AIError, InvalidProviderOutputError } from "../schema/index.js"
 
 /**

packages/ai/src/route/media-protocol.ts

@@ -1,5 +1,5 @@
 import { Clock, Duration, Effect, Schema, type Stream } from "effect"
-import { HttpClientResponse } from "effect/unstable/http"
+import { HttpClientResponse } from "effect/http"
 import type { Snapshot, Status } from "../generation.js"
 import { Media } from "../media.js"
 import type { AuthInput } from "./auth.js"

packages/ai/src/route/media.ts

@@ -1,5 +1,5 @@
 import { Duration, Effect, Schedule, Schema, Stream } from "effect"
-import { Headers, HttpClientRequest, type HttpClientResponse } from "effect/unstable/http"
+import { Headers, HttpClientRequest, type HttpClientResponse } from "effect/http"
 import { Auth, type AuthInput } from "./auth.js"
 import { Endpoint } from "./endpoint.js"
 import { RequestExecutorService, type Interface } from "./executor-service.js"

packages/ai/src/route/transport/http.ts

@@ -1,5 +1,5 @@
 import { Effect } from "effect"
-import { Headers, HttpClientRequest } from "effect/unstable/http"
+import { Headers, HttpClientRequest } from "effect/http"
 import { Auth } from "../auth.js"
 import { render as renderEndpoint } from "../endpoint.js"
 import { Framing } from "../framing.js"

packages/ai/src/route/transport/websocket-channel.ts

@@ -1,5 +1,5 @@
 import type { Effect, Scope, Stream } from "effect"
-import type { Headers } from "effect/unstable/http"
+import type { Headers } from "effect/http"
 import type { AIError, HttpContext } from "../../schema/index.js"
 
 export interface WebSocketChannelExecutor {

packages/ai/src/route/transport/websocket.ts

@@ -1,6 +1,6 @@
 import { Cause, Effect, Queue, Stream } from "effect"
-import { Headers } from "effect/unstable/http"
-import { Socket } from "effect/unstable/socket"
+import { Headers } from "effect/http"
+import { Socket } from "effect/socket"
 import {
   AIError,
   AIErrorReason,

packages/ai/src/schema/events.ts

@@ -1,4 +1,5 @@
 import { Schema } from "effect"
+import { extendSchema } from "@opencode/schema/schema"
 import { LLM } from "@opencode/schema/llm"
 import { ContentBlockID, ToolCallID } from "./ids.js"
 import {
@@ -264,6 +265,10 @@ export type ToolError = Schema.Schema.Type<typeof ToolError>
 export const FinishReasonDetails = Schema.Struct({
   normalized: FinishReason,
   raw: Schema.optional(Schema.String),
+  /** The provider's policy area for a content-filter finish, such as `cyber`. */
+  category: Schema.optional(Schema.String),
+  /** The provider's human-readable reason for a content-filter finish. */
+  explanation: Schema.optional(Schema.String),
 }).annotate({ identifier: "LLM.FinishReasonDetails" })
 export type FinishReasonDetails = Schema.Schema.Type<typeof FinishReasonDetails>
 
@@ -335,7 +340,7 @@ const toolCallID = (value: ToolCallID | string) => ToolCallID.make(value)
  * Lets consumers write `events.filter(LLMEvent.is.toolCall)` instead of
  * `events.filter(LLMEvent.guards["tool-call"])`.
  */
-export const LLMEvent = Object.assign(llmEventTagged, {
+export const LLMEvent = extendSchema(llmEventTagged, {
   compaction: CompactionPart.make,
   stepStart: StepStart.make,
   textStart: (input: WithID<TextStart, ContentBlockID>) => TextStart.make({ ...input, id: contentBlockID(input.id) }),

packages/ai/src/schema/messages.ts

@@ -1,4 +1,5 @@
 import { Schema } from "effect"
+import { extendSchema } from "@opencode/schema/schema"
 import { Tool } from "@opencode/schema/tool"
 import {
   CacheHint,
@@ -28,7 +29,7 @@ export type SystemPart = Schema.Schema.Type<typeof systemPartSchema>
 
 const makeSystemPart = (text: string): SystemPart => ({ type: "text", text })
 
-export const SystemPart = Object.assign(systemPartSchema, {
+export const SystemPart = extendSchema(systemPartSchema, {
   make: makeSystemPart,
   content: (input?: string | SystemPart | ReadonlyArray<SystemPart>) => {
     if (input === undefined) return []
@@ -76,7 +77,7 @@ const toolResultValueSchema = Schema.Union([
 export type ToolResultValue = Schema.Schema.Type<typeof toolResultValueSchema>
 const isToolResultValue = Schema.is(toolResultValueSchema)
 
-export const ToolResultValue = Object.assign(toolResultValueSchema, {
+export const ToolResultValue = extendSchema(toolResultValueSchema, {
   is: isToolResultValue,
   make: (value: unknown, type: ToolResultValue["type"] = "json"): ToolResultValue => {
     if (isToolResultValue(value)) return value
@@ -90,7 +91,7 @@ export interface ToolOutput {
   readonly content: ReadonlyArray<Tool.Content>
 }
 
-export const ToolOutput = Object.assign(
+export const ToolOutput = extendSchema(
   Schema.Struct({
     structured: Schema.Unknown,
     content: Schema.Array(Tool.Content),
@@ -127,7 +128,7 @@ const toolResultText = (value: unknown) => {
   }
 }
 
-export const ToolCallPart = Object.assign(
+export const ToolCallPart = extendSchema(
   Schema.Struct({
     type: Schema.Literal("tool-call"),
     id: Schema.String,
@@ -145,7 +146,7 @@ export const ToolCallPart = Object.assign(
 )
 export type ToolCallPart = Schema.Schema.Type<typeof ToolCallPart>
 
-export const ToolResultPart = Object.assign(
+export const ToolResultPart = extendSchema(
   Schema.Struct({
     type: Schema.Literal("tool-result"),
     id: Schema.String,
@@ -209,7 +210,7 @@ const compactionPartSchema = Schema.Struct({
   )
   .annotate({ identifier: "LLM.Content.Compaction" })
 export type CompactionPart = typeof compactionPartSchema.Type
-export const CompactionPart = Object.assign(compactionPartSchema, {
+export const CompactionPart = extendSchema(compactionPartSchema, {
   make: (input: Omit<CompactionPart, "type" | "encrypted" | "text"> & CompactionContent): CompactionPart =>
     Schema.decodeUnknownSync(compactionPartSchema)({ type: "compaction", ...input }),
 })
@@ -326,7 +327,7 @@ export type ToolNamespaceEntryInput = ToolNamespaceInput & { readonly type: "nam
 
 export const ToolNamespace: Schema.Codec<ToolNamespace> & {
   readonly make: (input: ToolNamespace | ToolNamespaceInput) => ToolNamespace
-} = Object.assign(
+} = extendSchema(
   Schema.Struct({
     type: Schema.Literal("namespace"),
     name: Schema.String,
@@ -346,7 +347,7 @@ export type ToolEntry = ToolDefinition | ToolNamespace
 export type ToolEntryInput = ToolDefinition.Input | ToolNamespaceEntryInput
 export const ToolEntry: Schema.Codec<ToolEntry> & {
   readonly make: (input: ToolEntryInput) => ToolEntry
-} = Object.assign(
+} = extendSchema(
   Schema.Union([ToolDefinition, ToolNamespace]).pipe(
     Schema.toTaggedUnion("type"),
     Schema.annotate({ identifier: "LLM.ToolEntry" }),

packages/ai/src/speech.ts

@@ -1,4 +1,5 @@
 import { Effect, Schema, Stream } from "effect"
+import { extendSchema } from "@opencode/schema/schema"
 import { ProgressEvent, QueuedEvent } from "./generation.js"
 import { Media } from "./media.js"
 import { MediaModel, composeRoute, tryRequest } from "./media-model.js"
@@ -141,7 +142,7 @@ const speechEventTagged = Schema.Union([
   SpeechTimestampsEvent,
   SpeechFinishEvent,
 ]).pipe(Schema.toTaggedUnion("type"))
-export const SpeechEvent = Object.assign(speechEventTagged, {
+export const SpeechEvent = extendSchema(speechEventTagged, {
   is: {
     generationQueued: speechEventTagged.guards["generation-queued"],
     generationProgress: speechEventTagged.guards["generation-progress"],

packages/ai/src/tool.ts

@@ -231,7 +231,8 @@ export const toDefinitions = (tools: Tools): ReadonlyArray<ToolDefinitionClass>
   )
 
 const toJsonSchema = (schema: Schema.Top): JsonSchema.JsonSchema => {
-  const document = Schema.toJsonSchemaDocument(schema)
+  // Keep provider-facing tool schemas closed; Effect 4's default now emits additionalProperties: true.
+  const document = Schema.toJsonSchemaDocument(schema, { onExcessProperty: "error" })
   if (Object.keys(document.definitions).length === 0) return document.schema
   return { ...document.schema, $defs: document.definitions }
 }

packages/ai/src/transcription.ts

@@ -1,4 +1,5 @@
 import { Effect, Schema, Stream } from "effect"
+import { extendSchema } from "@opencode/schema/schema"
 import { Generation, ProgressEvent, QueuedEvent, type AwaitOptions } from "./generation.js"
 import { Media } from "./media.js"
 import { MediaModel, composeRoute, tryRequest } from "./media-model.js"
@@ -159,7 +160,7 @@ const transcriptionEventTagged = Schema.Union([
   TranscriptionSegmentEvent,
   TranscriptionFinishEvent,
 ]).pipe(Schema.toTaggedUnion("type"))
-export const TranscriptionEvent = Object.assign(transcriptionEventTagged, {
+export const TranscriptionEvent = extendSchema(transcriptionEventTagged, {
   is: {
     generationQueued: transcriptionEventTagged.guards["generation-queued"],
     generationProgress: transcriptionEventTagged.guards["generation-progress"],

packages/ai/src/video.ts

@@ -1,4 +1,5 @@
 import { Effect, Schema, Stream } from "effect"
+import { extendSchema } from "@opencode/schema/schema"
 import { Generation, ProgressEvent, QueuedEvent, type AwaitOptions } from "./generation.js"
 import { Media } from "./media.js"
 import { MediaModel, composeRoute, tryRequest } from "./media-model.js"
@@ -136,7 +137,7 @@ export const VideoFinishEvent = Schema.Struct({
 const videoEventTagged = Schema.Union([QueuedEvent, ProgressEvent, VideoOutputEvent, VideoFinishEvent]).pipe(
   Schema.toTaggedUnion("type"),
 )
-export const VideoEvent = Object.assign(videoEventTagged, {
+export const VideoEvent = extendSchema(videoEventTagged, {
   is: {
     generationQueued: videoEventTagged.guards["generation-queued"],
     generationProgress: videoEventTagged.guards["generation-progress"],

packages/ai/test/auth-options.types.ts

@@ -30,7 +30,7 @@ type LanguageModel = {
 declare const auth: Auth.Definition
 declare const optionalAuthModel: LanguageModelFactory<BaseOptions, "optional", LanguageModel>
 declare const requiredAuthModel: LanguageModelFactory<BaseOptions, "required", LanguageModel>
-const configApiKey = Config.redacted("OPENAI_API_KEY")
+const configApiKey = Config.Redacted("OPENAI_API_KEY")
 
 OpenAIChat.route.model({ id: "gpt-4.1-mini" })
 

packages/ai/test/auth.test.ts

@@ -1,6 +1,6 @@
 import { describe, expect } from "bun:test"
 import { ConfigProvider, Effect } from "effect"
-import { Headers } from "effect/unstable/http"
+import { Headers } from "effect/http"
 import { LLM } from "../src/index.js"
 import { Auth } from "../src/route/auth.js"
 import * as OpenAIChat from "../src/protocols/openai-chat.js"

packages/ai/test/cache-policy.test.ts

@@ -8,6 +8,7 @@ import {
   AmazonBedrock,
   AnthropicCompatible,
   CloudflareAIGateway,
+  DigitalOcean,
   GoogleVertexMessages,
   Meta,
   MiniMax,
@@ -117,6 +118,33 @@ describe("applyCachePolicy", () => {
     }),
   )
 
+  it.effect("'auto' emits cache_control markers on DigitalOcean", () =>
+    Effect.gen(function* () {
+      const prepared = yield* compileRequest(
+        LLM.request({
+          model: DigitalOcean.configure({ apiKey: "test" }).model("anthropic-claude-fable-5.1"),
+          system: "You are concise.",
+          tools: [{ name: "lookup", description: "Look up a value", inputSchema: { type: "object", properties: {} } }],
+          prompt: "hi",
+        }),
+      )
+
+      expect(prepared.body).toMatchObject({
+        tools: [{ type: "function", function: { name: "lookup" }, cache_control: { type: "ephemeral" } }],
+        messages: [
+          {
+            role: "system",
+            content: [{ text: "You are concise.", cache_control: { type: "ephemeral" } }],
+          },
+          {
+            role: "user",
+            content: [{ text: "hi", cache_control: { type: "ephemeral" } }],
+          },
+        ],
+      })
+    }),
+  )
+
   it.effect("'auto' emits Anthropic cache markers on Anthropic-compatible routes", () =>
     Effect.gen(function* () {
       const prepared = yield* compileRequest(

packages/ai/test/compaction-http.test.ts

@@ -1,6 +1,6 @@
 import { expect } from "bun:test"
 import { Effect } from "effect"
-import { FetchHttpClient } from "effect/unstable/http"
+import { FetchHttpClient } from "effect/http"
 import { LLM, LLMRequest, Message } from "../src/index.js"
 import { LLMClient } from "../src/route/client.js"
 import { OpenAI } from "../src/providers.js"

packages/ai/test/compile.test.ts

@@ -1,6 +1,6 @@
 import { describe, expect, test } from "bun:test"
 import { Effect, Ref, Schema } from "effect"
-import { HttpClientRequest, HttpClientResponse } from "effect/unstable/http"
+import { HttpClientRequest, HttpClientResponse } from "effect/http"
 import {
   LLM,
   LLMRequest,

packages/ai/test/effort-updates.test.ts

@@ -197,9 +197,15 @@ describe("Anthropic Messages effort updates", () => {
     ["anthropic/claude-opus-5", true],
     ["claude-fable-5-1", true],
     ["claude-mythos-5-1", true],
+    ["claude-opus-5-5", true],
+    ["claude-sonnet-5-5", true],
+    ["anthropic/claude-sonnet-5-5", true],
+    ["claude-sonnet-6", true],
+    ["claude-haiku-6", true],
     ["claude-fable-5", false],
     ["claude-opus-4-8", false],
     ["claude-sonnet-5", false],
+    ["claude-sonnet-5-20260801", false],
     ["kimi-k2.5", false],
   ] as const) {
     it.effect(`${supported ? "lowers" : "strips"} markers for ${id}`, () =>

packages/ai/test/evaluation.test.ts

@@ -1,6 +1,6 @@
 import { describe, expect } from "bun:test"
 import { Effect, Layer } from "effect"
-import { HttpClientRequest } from "effect/unstable/http"
+import { HttpClientRequest } from "effect/http"
 import { Evaluation, EvaluationClient } from "../src/experimental.js"
 import { OpenCodeZen, OpenRouter, TypeSafeAI, VercelAIGateway } from "../src/providers.js"
 import { it } from "./lib/effect.js"

packages/ai/test/executor.test.ts

@@ -1,6 +1,6 @@
 import { describe, expect } from "bun:test"
 import { Deferred, Effect, Fiber, Layer, Ref, Stream } from "effect"
-import { Headers, HttpClientError, HttpClientRequest } from "effect/unstable/http"
+import { Headers, HttpClientError, HttpClientRequest } from "effect/http"
 import { LLM, AIError, HttpContext, InvalidProviderOutputError, TransportError } from "../src/index.js"
 import { LLMClient, RequestExecutor, WebSocketTransport, type WebSocketChannelExecutor } from "../src/route.js"
 import { route } from "../src/protocols/openai-chat.js"

packages/ai/test/fixtures/recordings/digitalocean-chat/gpt-nano-continues-a-tool-call-with-cache-markers.json

@@ -0,0 +1,54 @@
+{
+  "version": 1,
+  "metadata": {
+    "model": "openai-gpt-5-nano",
+    "tags": [
+      "prefix:digitalocean-chat",
+      "provider:digitalocean",
+      "protocol:digitalocean-chat",
+      "cache",
+      "tool",
+      "tool-loop"
+    ],
+    "name": "digitalocean-chat/gpt-nano-continues-a-tool-call-with-cache-markers",
+    "recordedAt": "2026-10-01T07:36:41.717Z"
+  },
+  "interactions": [
+    {
+      "transport": "http",
+      "request": {
+        "method": "POST",
+        "url": "https://inference.do-ai.run/v1/chat/completions",
+        "headers": {
+          "content-type": "application/json"
+        },
+        "body": "{\"model\":\"openai-gpt-5-nano\",\"messages\":[{\"role\":\"system\",\"content\":[{\"type\":\"text\",\"text\":\"Use the get_weather tool exactly once. After the tool result, reply exactly: Paris is sunny.\",\"cache_control\":{\"type\":\"ephemeral\"}}]},{\"role\":\"user\",\"content\":[{\"type\":\"text\",\"text\":\"What is the weather in Paris?\",\"cache_control\":{\"type\":\"ephemeral\"}}]}],\"tools\":[{\"type\":\"function\",\"function\":{\"name\":\"get_weather\",\"description\":\"Get current weather for a city.\",\"parameters\":{\"type\":\"object\",\"properties\":{\"city\":{\"type\":\"string\"}},\"required\":[\"city\"],\"additionalProperties\":false},\"strict\":false},\"cache_control\":{\"type\":\"ephemeral\"}}],\"stream\":true,\"stream_options\":{\"include_usage\":true},\"store\":false,\"reasoning_effort\":\"minimal\",\"max_completion_tokens\":1024}"
+      },
+      "response": {
+        "status": 200,
+        "headers": {
+          "content-type": "text/event-stream"
+        },
+        "body": "data: {\"choices\":[{\"delta\":{\"content\":\"\",\"role\":\"assistant\"},\"finish_reason\":null,\"index\":0,\"logprobs\":null}],\"created\":1790840200,\"id\":\"chatcmpl-EU5dIREwFebLDdrnmX7ftaDIK4qrZ\",\"model\":\"openai-gpt-5-nano\",\"object\":\"chat.completion.chunk\"}\n\ndata: {\"choices\":[{\"delta\":{\"tool_calls\":[{\"function\":{\"arguments\":\"\",\"name\":\"get_weather\"},\"id\":\"call_zPwN7xhG4uXQINkufgtjVJ7L\",\"index\":0,\"type\":\"function\"}]},\"finish_reason\":null,\"index\":0,\"logprobs\":null}],\"created\":1790840200,\"id\":\"chatcmpl-EU5dIREwFebLDdrnmX7ftaDIK4qrZ\",\"model\":\"openai-gpt-5-nano\",\"object\":\"chat.completion.chunk\"}\n\ndata: {\"choices\":[{\"delta\":{\"tool_calls\":[{\"function\":{\"arguments\":\"{\\\"\"},\"index\":0,\"type\":\"function\"}]},\"finish_reason\":null,\"index\":0,\"logprobs\":null}],\"created\":1790840200,\"id\":\"chatcmpl-EU5dIREwFebLDdrnmX7ftaDIK4qrZ\",\"model\":\"openai-gpt-5-nano\",\"object\":\"chat.completion.chunk\"}\n\ndata: {\"choices\":[{\"delta\":{\"tool_calls\":[{\"function\":{\"arguments\":\"city\"},\"index\":0,\"type\":\"function\"}]},\"finish_reason\":null,\"index\":0,\"logprobs\":null}],\"created\":1790840200,\"id\":\"chatcmpl-EU5dIREwFebLDdrnmX7ftaDIK4qrZ\",\"model\":\"openai-gpt-5-nano\",\"object\":\"chat.completion.chunk\"}\n\ndata: {\"choices\":[{\"delta\":{\"tool_calls\":[{\"function\":{\"arguments\":\"\\\":\\\"\"},\"index\":0,\"type\":\"function\"}]},\"finish_reason\":null,\"index\":0,\"logprobs\":null}],\"created\":1790840200,\"id\":\"chatcmpl-EU5dIREwFebLDdrnmX7ftaDIK4qrZ\",\"model\":\"openai-gpt-5-nano\",\"object\":\"chat.completion.chunk\"}\n\ndata: {\"choices\":[{\"delta\":{\"tool_calls\":[{\"function\":{\"arguments\":\"Paris\"},\"index\":0,\"type\":\"function\"}]},\"finish_reason\":null,\"index\":0,\"logprobs\":null}],\"created\":1790840200,\"id\":\"chatcmpl-EU5dIREwFebLDdrnmX7ftaDIK4qrZ\",\"model\":\"openai-gpt-5-nano\",\"object\":\"chat.completion.chunk\"}\n\ndata: {\"choices\":[{\"delta\":{\"tool_calls\":[{\"function\":{\"arguments\":\"\\\"}\"},\"index\":0,\"type\":\"function\"}]},\"finish_reason\":null,\"index\":0,\"logprobs\":null}],\"created\":1790840200,\"id\":\"chatcmpl-EU5dIREwFebLDdrnmX7ftaDIK4qrZ\",\"model\":\"openai-gpt-5-nano\",\"object\":\"chat.completion.chunk\"}\n\ndata: {\"choices\":[{\"delta\":{},\"finish_reason\":\"tool_calls\",\"index\":0,\"logprobs\":null}],\"created\":1790840200,\"id\":\"chatcmpl-EU5dIREwFebLDdrnmX7ftaDIK4qrZ\",\"model\":\"openai-gpt-5-nano\",\"object\":\"chat.completion.chunk\"}\n\ndata: {\"choices\":[],\"created\":1790840200,\"id\":\"chatcmpl-EU5dIREwFebLDdrnmX7ftaDIK4qrZ\",\"model\":\"openai-gpt-5-nano\",\"object\":\"chat.completion.chunk\",\"usage\":{\"cache_created_input_tokens\":0,\"cache_creation\":{\"ephemeral_1h_input_tokens\":0,\"ephemeral_5m_input_tokens\":0},\"cache_read_input_tokens\":0,\"completion_tokens\":23,\"completion_tokens_details\":{\"reasoning_tokens\":0},\"prompt_tokens\":155,\"prompt_tokens_details\":{\"cached_tokens\":0},\"speed\":null,\"total_tokens\":178}}\n\ndata: [DONE]\n\n"
+      }
+    },
+    {
+      "transport": "http",
+      "request": {
+        "method": "POST",
+        "url": "https://inference.do-ai.run/v1/chat/completions",
+        "headers": {
+          "content-type": "application/json"
+        },
+        "body": "{\"model\":\"openai-gpt-5-nano\",\"messages\":[{\"role\":\"system\",\"content\":[{\"type\":\"text\",\"text\":\"Use the get_weather tool exactly once. After the tool result, reply exactly: Paris is sunny.\",\"cache_control\":{\"type\":\"ephemeral\"}}]},{\"role\":\"user\",\"content\":\"What is the weather in Paris?\"},{\"role\":\"assistant\",\"content\":null,\"tool_calls\":[{\"id\":\"call_zPwN7xhG4uXQINkufgtjVJ7L\",\"type\":\"function\",\"function\":{\"name\":\"get_weather\",\"arguments\":\"{\\\"city\\\":\\\"Paris\\\"}\"}}]},{\"role\":\"tool\",\"tool_call_id\":\"call_zPwN7xhG4uXQINkufgtjVJ7L\",\"content\":[{\"type\":\"text\",\"text\":\"{\\\"temperature\\\":22,\\\"condition\\\":\\\"sunny\\\"}\",\"cache_control\":{\"type\":\"ephemeral\"}}]}],\"tools\":[{\"type\":\"function\",\"function\":{\"name\":\"get_weather\",\"description\":\"Get current weather for a city.\",\"parameters\":{\"type\":\"object\",\"properties\":{\"city\":{\"type\":\"string\"}},\"required\":[\"city\"],\"additionalProperties\":false},\"strict\":false},\"cache_control\":{\"type\":\"ephemeral\"}}],\"stream\":true,\"stream_options\":{\"include_usage\":true},\"store\":false,\"reasoning_effort\":\"minimal\",\"max_completion_tokens\":1024}"
+      },
+      "response": {
+        "status": 200,
+        "headers": {
+          "content-type": "text/event-stream"
+        },
+        "body": "data: {\"choices\":[{\"delta\":{\"content\":\"\",\"role\":\"assistant\"},\"finish_reason\":null,\"index\":0,\"logprobs\":null}],\"created\":1790840201,\"id\":\"chatcmpl-EU5dJprTkE7OHEKnmvot7rR0LSo5L\",\"model\":\"openai-gpt-5-nano\",\"object\":\"chat.completion.chunk\"}\n\ndata: {\"choices\":[{\"delta\":{\"content\":\"Paris\"},\"finish_reason\":null,\"index\":0,\"logprobs\":null}],\"created\":1790840201,\"id\":\"chatcmpl-EU5dJprTkE7OHEKnmvot7rR0LSo5L\",\"model\":\"openai-gpt-5-nano\",\"object\":\"chat.completion.chunk\"}\n\ndata: {\"choices\":[{\"delta\":{\"content\":\" is\"},\"finish_reason\":null,\"index\":0,\"logprobs\":null}],\"created\":1790840201,\"id\":\"chatcmpl-EU5dJprTkE7OHEKnmvot7rR0LSo5L\",\"model\":\"openai-gpt-5-nano\",\"object\":\"chat.completion.chunk\"}\n\ndata: {\"choices\":[{\"delta\":{\"content\":\" sunny\"},\"finish_reason\":null,\"index\":0,\"logprobs\":null}],\"created\":1790840201,\"id\":\"chatcmpl-EU5dJprTkE7OHEKnmvot7rR0LSo5L\",\"model\":\"openai-gpt-5-nano\",\"object\":\"chat.completion.chunk\"}\n\ndata: {\"choices\":[{\"delta\":{\"content\":\".\"},\"finish_reason\":null,\"index\":0,\"logprobs\":null}],\"created\":1790840201,\"id\":\"chatcmpl-EU5dJprTkE7OHEKnmvot7rR0LSo5L\",\"model\":\"openai-gpt-5-nano\",\"object\":\"chat.completion.chunk\"}\n\ndata: {\"choices\":[{\"delta\":{},\"finish_reason\":\"stop\",\"index\":0,\"logprobs\":null}],\"created\":1790840201,\"id\":\"chatcmpl-EU5dJprTkE7OHEKnmvot7rR0LSo5L\",\"model\":\"openai-gpt-5-nano\",\"object\":\"chat.completion.chunk\"}\n\ndata: {\"choices\":[],\"created\":1790840201,\"id\":\"chatcmpl-EU5dJprTkE7OHEKnmvot7rR0LSo5L\",\"model\":\"openai-gpt-5-nano\",\"object\":\"chat.completion.chunk\",\"usage\":{\"cache_created_input_tokens\":0,\"cache_creation\":{\"ephemeral_1h_input_tokens\":0,\"ephemeral_5m_input_tokens\":0},\"cache_read_input_tokens\":0,\"completion_tokens\":13,\"completion_tokens_details\":{\"reasoning_tokens\":0},\"prompt_tokens\":193,\"prompt_tokens_details\":{\"cached_tokens\":0},\"speed\":null,\"total_tokens\":206}}\n\ndata: [DONE]\n\n"
+      }
+    }
+  ]
+}

packages/ai/test/fixtures/recordings/digitalocean-chat/gpt-nano-reuses-a-cached-prompt.json

@@ -0,0 +1,53 @@
+{
+  "version": 1,
+  "metadata": {
+    "model": "openai-gpt-5-nano",
+    "tags": [
+      "prefix:digitalocean-chat",
+      "provider:digitalocean",
+      "protocol:digitalocean-chat",
+      "cache",
+      "usage"
+    ],
+    "name": "digitalocean-chat/gpt-nano-reuses-a-cached-prompt",
+    "recordedAt": "2026-10-01T07:36:40.074Z"
+  },
+  "interactions": [
+    {
+      "transport": "http",
+      "request": {
+        "method": "POST",
+        "url": "https://inference.do-ai.run/v1/chat/completions",
+        "headers": {
+          "content-type": "application/json"
+        },
+        "body": "{\"model\":\"openai-gpt-5-nano\",\"messages\":[{\"role\":\"system\",\"content\":[{\"type\":\"text\",\"text\":\"You are a concise, factual assistant. Answer precisely and avoid filler. Cite numbers when known. You are a concise, factual assistant. Answer precisely and avoid filler. Cite numbers when known. You are a concise, factual assistant. Answer precisely and avoid filler. Cite numbers when known. You are a concise, factual assistant. Answer precisely and avoid filler. Cite numbers when known. You are a concise, factual assistant. Answer precisely and avoid filler. Cite numbers when known. You are a concise, factual assistant. Answer precisely and avoid filler. Cite numbers when known. You are a concise, factual assistant. Answer precisely and avoid filler. Cite numbers when known. You are a concise, factual assistant. Answer precisely and avoid filler. Cite numbers when known. You are a concise, factual assistant. Answer precisely and avoid filler. 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Cite numbers when known. You are a concise, factual assistant. Answer precisely and avoid filler. Cite numbers when known. You are a concise, factual assistant. Answer precisely and avoid filler. Cite numbers when known. You are a concise, factual assistant. Answer precisely and avoid filler. Cite numbers when known. You are a concise, factual assistant. Answer precisely and avoid filler. Cite numbers when known. You are a concise, factual assistant. Answer precisely and avoid filler. Cite numbers when known. You are a concise, factual assistant. Answer precisely and avoid filler. Cite numbers when known. You are a concise, factual assistant. Answer precisely and avoid filler. Cite numbers when known. You are a concise, factual assistant. Answer precisely and avoid filler. Cite numbers when known. You are a concise, factual assistant. Answer precisely and avoid filler. Cite numbers when known. You are a concise, factual assistant. Answer precisely and avoid filler. Cite numbers when known. You are a concise, factual assistant. Answer precisely and avoid filler. Cite numbers when known. You are a concise, factual assistant. Answer precisely and avoid filler. Cite numbers when known. You are a concise, factual assistant. Answer precisely and avoid filler. Cite numbers when known. You are a concise, factual assistant. Answer precisely and avoid filler. Cite numbers when known. You are a concise, factual assistant. Answer precisely and avoid filler. Cite numbers when known. You are a concise, factual assistant. Answer precisely and avoid filler. Cite numbers when known. You are a concise, factual assistant. Answer precisely and avoid filler. Cite numbers when known. You are a concise, factual assistant. Answer precisely and avoid filler. Cite numbers when known. You are a concise, factual assistant. Answer precisely and avoid filler. Cite numbers when known. You are a concise, factual assistant. Answer precisely and avoid filler. Cite numbers when known. You are a concise, factual assistant. Answer precisely and avoid fillLine truncated
+      },
+      "response": {
+        "status": 200,
+        "headers": {
+          "content-type": "text/event-stream"
+        },
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+      }
+    },
+    {
+      "transport": "http",
+      "request": {
+        "method": "POST",
+        "url": "https://inference.do-ai.run/v1/chat/completions",
+        "headers": {
+          "content-type": "application/json"
+        },
+        "body": "{\"model\":\"openai-gpt-5-nano\",\"messages\":[{\"role\":\"system\",\"content\":[{\"type\":\"text\",\"text\":\"You are a concise, factual assistant. Answer precisely and avoid filler. Cite numbers when known. You are a concise, factual assistant. Answer precisely and avoid filler. Cite numbers when known. You are a concise, factual assistant. Answer precisely and avoid filler. Cite numbers when known. You are a concise, factual assistant. Answer precisely and avoid filler. Cite numbers when known. You are a concise, factual assistant. Answer precisely and avoid filler. Cite numbers when known. You are a concise, factual assistant. Answer precisely and avoid filler. Cite numbers when known. You are a concise, factual assistant. Answer precisely and avoid filler. Cite numbers when known. You are a concise, factual assistant. Answer precisely and avoid filler. Cite numbers when known. You are a concise, factual assistant. Answer precisely and avoid filler. 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Cite numbers when known. You are a concise, factual assistant. Answer precisely and avoid filler. Cite numbers when known. You are a concise, factual assistant. Answer precisely and avoid filler. Cite numbers when known. You are a concise, factual assistant. Answer precisely and avoid filler. Cite numbers when known. You are a concise, factual assistant. Answer precisely and avoid filler. Cite numbers when known. You are a concise, factual assistant. Answer precisely and avoid filler. Cite numbers when known. You are a concise, factual assistant. Answer precisely and avoid filler. Cite numbers when known. You are a concise, factual assistant. Answer precisely and avoid filler. Cite numbers when known. You are a concise, factual assistant. Answer precisely and avoid filler. Cite numbers when known. You are a concise, factual assistant. Answer precisely and avoid filler. Cite numbers when known. You are a concise, factual assistant. Answer precisely and avoid filler. Cite numbers when known. You are a concise, factual assistant. Answer precisely and avoid filler. Cite numbers when known. You are a concise, factual assistant. Answer precisely and avoid filler. Cite numbers when known. You are a concise, factual assistant. Answer precisely and avoid filler. Cite numbers when known. You are a concise, factual assistant. Answer precisely and avoid filler. Cite numbers when known. You are a concise, factual assistant. Answer precisely and avoid filler. Cite numbers when known. You are a concise, factual assistant. Answer precisely and avoid filler. Cite numbers when known. You are a concise, factual assistant. Answer precisely and avoid filler. Cite numbers when known. You are a concise, factual assistant. Answer precisely and avoid filler. Cite numbers when known. You are a concise, factual assistant. Answer precisely and avoid filler. Cite numbers when known. You are a concise, factual assistant. Answer precisely and avoid filler. Cite numbers when known. You are a concise, factual assistant. Answer precisely and avoid filler. Cite numbers when known. You are a concise, factual assistant. Answer precisely and avoid filler. Cite numbers when known. You are a concise, factual assistant. Answer precisely and avoid filler. Cite numbers when known. You are a concise, factual assistant. Answer precisely and avoid filler. Cite numbers when known. You are a concise, factual assistant. Answer precisely and avoid filler. Cite numbers when known. You are a concise, factual assistant. Answer precisely and avoid filler. Cite numbers when known. You are a concise, factual assistant. Answer precisely and avoid filler. Cite numbers when known. You are a concise, factual assistant. Answer precisely and avoid filler. Cite numbers when known. You are a concise, factual assistant. Answer precisely and avoid filler. Cite numbers when known. You are a concise, factual assistant. Answer precisely and avoid filler. Cite numbers when known. You are a concise, factual assistant. Answer precisely and avoid fillLine truncated
+      },
+      "response": {
+        "status": 200,
+        "headers": {
+          "content-type": "text/event-stream"
+        },
+        "body": "data: {\"choices\":[{\"delta\":{\"content\":\"\",\"role\":\"assistant\"},\"finish_reason\":null,\"index\":0,\"logprobs\":null}],\"created\":1790840200,\"id\":\"chatcmpl-EU5dHYe8HWjEAEIIvsJ6Hk0EUxL9r\",\"model\":\"openai-gpt-5-nano\",\"object\":\"chat.completion.chunk\"}\n\ndata: {\"choices\":[{\"delta\":{\"content\":\"OK\"},\"finish_reason\":null,\"index\":0,\"logprobs\":null}],\"created\":1790840200,\"id\":\"chatcmpl-EU5dHYe8HWjEAEIIvsJ6Hk0EUxL9r\",\"model\":\"openai-gpt-5-nano\",\"object\":\"chat.completion.chunk\"}\n\ndata: {\"choices\":[{\"delta\":{},\"finish_reason\":\"stop\",\"index\":0,\"logprobs\":null}],\"created\":1790840200,\"id\":\"chatcmpl-EU5dHYe8HWjEAEIIvsJ6Hk0EUxL9r\",\"model\":\"openai-gpt-5-nano\",\"object\":\"chat.completion.chunk\"}\n\ndata: {\"choices\":[],\"created\":1790840200,\"id\":\"chatcmpl-EU5dHYe8HWjEAEIIvsJ6Hk0EUxL9r\",\"model\":\"openai-gpt-5-nano\",\"object\":\"chat.completion.chunk\",\"usage\":{\"cache_created_input_tokens\":0,\"cache_creation\":{\"ephemeral_1h_input_tokens\":0,\"ephemeral_5m_input_tokens\":0},\"cache_read_input_tokens\":4608,\"completion_tokens\":10,\"completion_tokens_details\":{\"reasoning_tokens\":0},\"prompt_tokens\":4765,\"prompt_tokens_details\":{\"cached_tokens\":4608},\"speed\":null,\"total_tokens\":4775}}\n\ndata: [DONE]\n\n"
+      }
+    }
+  ]
+}

packages/ai/test/fixtures/recordings/digitalocean-chat/haiku-continues-a-tool-call-with-cache-markers.json

@@ -0,0 +1,54 @@
+{
+  "version": 1,
+  "metadata": {
+    "model": "anthropic-claude-haiku-4.5",
+    "tags": [
+      "prefix:digitalocean-chat",
+      "provider:digitalocean",
+      "protocol:digitalocean-chat",
+      "cache",
+      "tool",
+      "tool-loop"
+    ],
+    "name": "digitalocean-chat/haiku-continues-a-tool-call-with-cache-markers",
+    "recordedAt": "2026-10-01T07:36:38.471Z"
+  },
+  "interactions": [
+    {
+      "transport": "http",
+      "request": {
+        "method": "POST",
+        "url": "https://inference.do-ai.run/v1/chat/completions",
+        "headers": {
+          "content-type": "application/json"
+        },
+        "body": "{\"model\":\"anthropic-claude-haiku-4.5\",\"messages\":[{\"role\":\"system\",\"content\":[{\"type\":\"text\",\"text\":\"Use the get_weather tool exactly once. After the tool result, reply exactly: Paris is sunny.\",\"cache_control\":{\"type\":\"ephemeral\"}}]},{\"role\":\"user\",\"content\":[{\"type\":\"text\",\"text\":\"What is the weather in Paris?\",\"cache_control\":{\"type\":\"ephemeral\"}}]}],\"tools\":[{\"type\":\"function\",\"function\":{\"name\":\"get_weather\",\"description\":\"Get current weather for a city.\",\"parameters\":{\"type\":\"object\",\"properties\":{\"city\":{\"type\":\"string\"}},\"required\":[\"city\"],\"additionalProperties\":false},\"strict\":false},\"cache_control\":{\"type\":\"ephemeral\"}}],\"stream\":true,\"stream_options\":{\"include_usage\":true},\"store\":false,\"max_completion_tokens\":128}"
+      },
+      "response": {
+        "status": 200,
+        "headers": {
+          "content-type": "text/event-stream"
+        },
+        "body": "data: {\"choices\":[{\"delta\":{\"content\":\"\",\"role\":\"assistant\"},\"finish_reason\":null,\"index\":0,\"logprobs\":null}],\"created\":1790840197,\"id\":\"chatcmpl-ccddd771-e8a6-4b59-b819-614f79ac4624\",\"model\":\"anthropic-claude-haiku-4.5\",\"object\":\"chat.completion.chunk\"}\n\ndata: {\"choices\":[{\"delta\":{\"tool_calls\":[{\"function\":{\"arguments\":\"\",\"name\":\"get_weather\"},\"id\":\"toolu_014LEa2F66CGw2SoLmWBeH5C\",\"index\":0,\"type\":\"function\"}]},\"finish_reason\":null,\"index\":0,\"logprobs\":null}],\"created\":1790840197,\"id\":\"chatcmpl-ccddd771-e8a6-4b59-b819-614f79ac4624\",\"model\":\"anthropic-claude-haiku-4.5\",\"object\":\"chat.completion.chunk\"}\n\ndata: {\"choices\":[{\"delta\":{\"tool_calls\":[{\"function\":{\"arguments\":\"\"},\"index\":0,\"type\":\"function\"}]},\"finish_reason\":null,\"index\":0,\"logprobs\":null}],\"created\":1790840197,\"id\":\"chatcmpl-ccddd771-e8a6-4b59-b819-614f79ac4624\",\"model\":\"anthropic-claude-haiku-4.5\",\"object\":\"chat.completion.chunk\"}\n\ndata: {\"choices\":[{\"delta\":{\"tool_calls\":[{\"function\":{\"arguments\":\"{\\\"city\\\"\"},\"index\":0,\"type\":\"function\"}]},\"finish_reason\":null,\"index\":0,\"logprobs\":null}],\"created\":1790840197,\"id\":\"chatcmpl-ccddd771-e8a6-4b59-b819-614f79ac4624\",\"model\":\"anthropic-claude-haiku-4.5\",\"object\":\"chat.completion.chunk\"}\n\ndata: {\"choices\":[{\"delta\":{\"tool_calls\":[{\"function\":{\"arguments\":\": \\\"Pari\"},\"index\":0,\"type\":\"function\"}]},\"finish_reason\":null,\"index\":0,\"logprobs\":null}],\"created\":1790840197,\"id\":\"chatcmpl-ccddd771-e8a6-4b59-b819-614f79ac4624\",\"model\":\"anthropic-claude-haiku-4.5\",\"object\":\"chat.completion.chunk\"}\n\ndata: {\"choices\":[{\"delta\":{\"tool_calls\":[{\"function\":{\"arguments\":\"s\\\"}\"},\"index\":0,\"type\":\"function\"}]},\"finish_reason\":null,\"index\":0,\"logprobs\":null}],\"created\":1790840197,\"id\":\"chatcmpl-ccddd771-e8a6-4b59-b819-614f79ac4624\",\"model\":\"anthropic-claude-haiku-4.5\",\"object\":\"chat.completion.chunk\"}\n\ndata: {\"choices\":[{\"delta\":{},\"finish_reason\":\"tool_calls\",\"index\":0,\"logprobs\":null}],\"created\":1790840197,\"id\":\"chatcmpl-ccddd771-e8a6-4b59-b819-614f79ac4624\",\"model\":\"anthropic-claude-haiku-4.5\",\"object\":\"chat.completion.chunk\"}\n\ndata: {\"choices\":[],\"created\":1790840197,\"id\":\"chatcmpl-ccddd771-e8a6-4b59-b819-614f79ac4624\",\"model\":\"anthropic-claude-haiku-4.5\",\"object\":\"chat.completion.chunk\",\"usage\":{\"cache_created_input_tokens\":0,\"cache_creation\":{\"ephemeral_1h_input_tokens\":0,\"ephemeral_5m_input_tokens\":0},\"cache_read_input_tokens\":0,\"completion_tokens\":54,\"completion_tokens_details\":{\"reasoning_tokens\":0},\"prompt_tokens\":593,\"prompt_tokens_details\":{\"cached_tokens\":0},\"speed\":null,\"total_tokens\":647}}\n\ndata: [DONE]\n\n"
+      }
+    },
+    {
+      "transport": "http",
+      "request": {
+        "method": "POST",
+        "url": "https://inference.do-ai.run/v1/chat/completions",
+        "headers": {
+          "content-type": "application/json"
+        },
+        "body": "{\"model\":\"anthropic-claude-haiku-4.5\",\"messages\":[{\"role\":\"system\",\"content\":[{\"type\":\"text\",\"text\":\"Use the get_weather tool exactly once. After the tool result, reply exactly: Paris is sunny.\",\"cache_control\":{\"type\":\"ephemeral\"}}]},{\"role\":\"user\",\"content\":\"What is the weather in Paris?\"},{\"role\":\"assistant\",\"content\":null,\"tool_calls\":[{\"id\":\"toolu_014LEa2F66CGw2SoLmWBeH5C\",\"type\":\"function\",\"function\":{\"name\":\"get_weather\",\"arguments\":\"{\\\"city\\\":\\\"Paris\\\"}\"}}]},{\"role\":\"tool\",\"tool_call_id\":\"toolu_014LEa2F66CGw2SoLmWBeH5C\",\"content\":[{\"type\":\"text\",\"text\":\"{\\\"temperature\\\":22,\\\"condition\\\":\\\"sunny\\\"}\",\"cache_control\":{\"type\":\"ephemeral\"}}]}],\"tools\":[{\"type\":\"function\",\"function\":{\"name\":\"get_weather\",\"description\":\"Get current weather for a city.\",\"parameters\":{\"type\":\"object\",\"properties\":{\"city\":{\"type\":\"string\"}},\"required\":[\"city\"],\"additionalProperties\":false},\"strict\":false},\"cache_control\":{\"type\":\"ephemeral\"}}],\"stream\":true,\"stream_options\":{\"include_usage\":true},\"store\":false,\"max_completion_tokens\":128}"
+      },
+      "response": {
+        "status": 200,
+        "headers": {
+          "content-type": "text/event-stream"
+        },
+        "body": "data: {\"choices\":[{\"delta\":{\"content\":\"Paris\",\"role\":\"assistant\"},\"finish_reason\":null,\"index\":0,\"logprobs\":null}],\"created\":1790840198,\"id\":\"chatcmpl-3914ee28-f256-4a49-994f-49365922a7a6\",\"model\":\"anthropic-claude-haiku-4.5\",\"object\":\"chat.completion.chunk\"}\n\ndata: {\"choices\":[{\"delta\":{\"content\":\" is sunny.\"},\"finish_reason\":null,\"index\":0,\"logprobs\":null}],\"created\":1790840198,\"id\":\"chatcmpl-3914ee28-f256-4a49-994f-49365922a7a6\",\"model\":\"anthropic-claude-haiku-4.5\",\"object\":\"chat.completion.chunk\"}\n\ndata: {\"choices\":[{\"delta\":{},\"finish_reason\":\"stop\",\"index\":0,\"logprobs\":null}],\"created\":1790840198,\"id\":\"chatcmpl-3914ee28-f256-4a49-994f-49365922a7a6\",\"model\":\"anthropic-claude-haiku-4.5\",\"object\":\"chat.completion.chunk\"}\n\ndata: {\"choices\":[],\"created\":1790840198,\"id\":\"chatcmpl-3914ee28-f256-4a49-994f-49365922a7a6\",\"model\":\"anthropic-claude-haiku-4.5\",\"object\":\"chat.completion.chunk\",\"usage\":{\"cache_created_input_tokens\":0,\"cache_creation\":{\"ephemeral_1h_input_tokens\":0,\"ephemeral_5m_input_tokens\":0},\"cache_read_input_tokens\":0,\"completion_tokens\":7,\"completion_tokens_details\":{\"reasoning_tokens\":0},\"prompt_tokens\":668,\"prompt_tokens_details\":{\"cached_tokens\":0},\"speed\":null,\"total_tokens\":675}}\n\ndata: [DONE]\n\n"
+      }
+    }
+  ]
+}

packages/ai/test/fixtures/recordings/digitalocean-chat/haiku-reuses-a-cached-prompt.json

@@ -0,0 +1,53 @@
+{
+  "version": 1,
+  "metadata": {
+    "model": "anthropic-claude-haiku-4.5",
+    "tags": [
+      "prefix:digitalocean-chat",
+      "provider:digitalocean",
+      "protocol:digitalocean-chat",
+      "cache",
+      "usage"
+    ],
+    "name": "digitalocean-chat/haiku-reuses-a-cached-prompt",
+    "recordedAt": "2026-10-01T07:36:36.689Z"
+  },
+  "interactions": [
+    {
+      "transport": "http",
+      "request": {
+        "method": "POST",
+        "url": "https://inference.do-ai.run/v1/chat/completions",
+        "headers": {
+          "content-type": "application/json"
+        },
+        "body": "{\"model\":\"anthropic-claude-haiku-4.5\",\"messages\":[{\"role\":\"system\",\"content\":[{\"type\":\"text\",\"text\":\"You are a concise, factual assistant. Answer precisely and avoid filler. Cite numbers when known. You are a concise, factual assistant. Answer precisely and avoid filler. Cite numbers when known. You are a concise, factual assistant. Answer precisely and avoid filler. Cite numbers when known. You are a concise, factual assistant. Answer precisely and avoid filler. Cite numbers when known. You are a concise, factual assistant. Answer precisely and avoid filler. Cite numbers when known. You are a concise, factual assistant. Answer precisely and avoid filler. Cite numbers when known. You are a concise, factual assistant. Answer precisely and avoid filler. Cite numbers when known. You are a concise, factual assistant. Answer precisely and avoid filler. Cite numbers when known. You are a concise, factual assistant. Answer precisely and avoid filler. Cite numbers when known. You are a concise, factual assistant. Answer precisely and avoid filler. Cite numbers when known. You are a concise, factual assistant. Answer precisely and avoid filler. Cite numbers when known. You are a concise, factual assistant. Answer precisely and avoid filler. Cite numbers when known. You are a concise, factual assistant. Answer precisely and avoid filler. Cite numbers when known. You are a concise, factual assistant. Answer precisely and avoid filler. Cite numbers when known. You are a concise, factual assistant. Answer precisely and avoid filler. Cite numbers when known. You are a concise, factual assistant. Answer precisely and avoid filler. Cite numbers when known. You are a concise, factual assistant. Answer precisely and avoid filler. Cite numbers when known. You are a concise, factual assistant. Answer precisely and avoid filler. Cite numbers when known. You are a concise, factual assistant. Answer precisely and avoid filler. Cite numbers when known. You are a concise, factual assistant. Answer precisely and avoid filler. Cite numbers when known. You are a concise, factual assistant. Answer precisely and avoid filler. Cite numbers when known. You are a concise, factual assistant. Answer precisely and avoid filler. Cite numbers when known. You are a concise, factual assistant. Answer precisely and avoid filler. Cite numbers when known. You are a concise, factual assistant. Answer precisely and avoid filler. Cite numbers when known. You are a concise, factual assistant. Answer precisely and avoid filler. Cite numbers when known. You are a concise, factual assistant. Answer precisely and avoid filler. Cite numbers when known. You are a concise, factual assistant. Answer precisely and avoid filler. Cite numbers when known. You are a concise, factual assistant. Answer precisely and avoid filler. Cite numbers when known. You are a concise, factual assistant. Answer precisely and avoid filler. Cite numbers when known. You are a concise, factual assistant. Answer precisely and avoid filler. Cite numbers when known. You are a concise, factual assistant. Answer precisely and avoid filler. Cite numbers when known. You are a concise, factual assistant. Answer precisely and avoid filler. Cite numbers when known. You are a concise, factual assistant. Answer precisely and avoid filler. Cite numbers when known. You are a concise, factual assistant. Answer precisely and avoid filler. Cite numbers when known. You are a concise, factual assistant. Answer precisely and avoid filler. Cite numbers when known. You are a concise, factual assistant. Answer precisely and avoid filler. Cite numbers when known. You are a concise, factual assistant. Answer precisely and avoid filler. Cite numbers when known. You are a concise, factual assistant. Answer precisely and avoid filler. Cite numbers when known. You are a concise, factual assistant. Answer precisely and avoid filler. Cite numbers when known. You are a concise, factual assistant. Answer precisely and avoid filler. Cite numbers when known. You are a concise, factual assistant. Answer precisely and avoid filler. Cite numbers when known. You are a concise, factual assistant. Answer precisely and avoid filler. Cite numbers when known. You are a concise, factual assistant. Answer precisely and avoid filler. Cite numbers when known. You are a concise, factual assistant. Answer precisely and avoid filler. Cite numbers when known. You are a concise, factual assistant. Answer precisely and avoid filler. Cite numbers when known. You are a concise, factual assistant. Answer precisely and avoid filler. Cite numbers when known. You are a concise, factual assistant. Answer precisely and avoid filler. Cite numbers when known. You are a concise, factual assistant. Answer precisely and avoid filler. Cite numbers when known. You are a concise, factual assistant. Answer precisely and avoid filler. Cite numbers when known. You are a concise, factual assistant. Answer precisely and aLine truncated
+      },
+      "response": {
+        "status": 200,
+        "headers": {
+          "content-type": "text/event-stream"
+        },
+        "body": "data: {\"choices\":[{\"delta\":{\"content\":\"OK\",\"role\":\"assistant\"},\"finish_reason\":null,\"index\":0,\"logprobs\":null}],\"created\":1790840195,\"id\":\"chatcmpl-94f208e5-82fa-4ec6-b014-1b4ea9fbb98c\",\"model\":\"anthropic-claude-haiku-4.5\",\"object\":\"chat.completion.chunk\"}\n\ndata: {\"choices\":[{\"delta\":{},\"finish_reason\":\"stop\",\"index\":0,\"logprobs\":null}],\"created\":1790840195,\"id\":\"chatcmpl-94f208e5-82fa-4ec6-b014-1b4ea9fbb98c\",\"model\":\"anthropic-claude-haiku-4.5\",\"object\":\"chat.completion.chunk\"}\n\ndata: {\"choices\":[],\"created\":1790840195,\"id\":\"chatcmpl-94f208e5-82fa-4ec6-b014-1b4ea9fbb98c\",\"model\":\"anthropic-claude-haiku-4.5\",\"object\":\"chat.completion.chunk\",\"usage\":{\"cache_created_input_tokens\":5759,\"cache_creation\":{\"ephemeral_1h_input_tokens\":0,\"ephemeral_5m_input_tokens\":5759},\"cache_read_input_tokens\":0,\"completion_tokens\":4,\"completion_tokens_details\":{\"reasoning_tokens\":0},\"prompt_tokens\":5762,\"prompt_tokens_details\":{\"cached_tokens\":0},\"speed\":null,\"total_tokens\":5766}}\n\ndata: [DONE]\n\n"
+      }
+    },
+    {
+      "transport": "http",
+      "request": {
+        "method": "POST",
+        "url": "https://inference.do-ai.run/v1/chat/completions",
+        "headers": {
+          "content-type": "application/json"
+        },
+        "body": "{\"model\":\"anthropic-claude-haiku-4.5\",\"messages\":[{\"role\":\"system\",\"content\":[{\"type\":\"text\",\"text\":\"You are a concise, factual assistant. Answer precisely and avoid filler. Cite numbers when known. You are a concise, factual assistant. Answer precisely and avoid filler. Cite numbers when known. You are a concise, factual assistant. Answer precisely and avoid filler. Cite numbers when known. You are a concise, factual assistant. Answer precisely and avoid filler. Cite numbers when known. You are a concise, factual assistant. Answer precisely and avoid filler. Cite numbers when known. You are a concise, factual assistant. Answer precisely and avoid filler. Cite numbers when known. You are a concise, factual assistant. Answer precisely and avoid filler. Cite numbers when known. You are a concise, factual assistant. Answer precisely and avoid filler. Cite numbers when known. You are a concise, factual assistant. Answer precisely and avoid filler. Cite numbers when known. You are a concise, factual assistant. Answer precisely and avoid filler. Cite numbers when known. You are a concise, factual assistant. Answer precisely and avoid filler. Cite numbers when known. You are a concise, factual assistant. Answer precisely and avoid filler. Cite numbers when known. You are a concise, factual assistant. Answer precisely and avoid filler. Cite numbers when known. You are a concise, factual assistant. Answer precisely and avoid filler. Cite numbers when known. You are a concise, factual assistant. Answer precisely and avoid filler. Cite numbers when known. You are a concise, factual assistant. Answer precisely and avoid filler. Cite numbers when known. You are a concise, factual assistant. Answer precisely and avoid filler. Cite numbers when known. You are a concise, factual assistant. Answer precisely and avoid filler. Cite numbers when known. You are a concise, factual assistant. Answer precisely and avoid filler. Cite numbers when known. You are a concise, factual assistant. Answer precisely and avoid filler. Cite numbers when known. You are a concise, factual assistant. Answer precisely and avoid filler. Cite numbers when known. You are a concise, factual assistant. Answer precisely and avoid filler. Cite numbers when known. You are a concise, factual assistant. Answer precisely and avoid filler. Cite numbers when known. You are a concise, factual assistant. Answer precisely and avoid filler. Cite numbers when known. You are a concise, factual assistant. Answer precisely and avoid filler. Cite numbers when known. You are a concise, factual assistant. Answer precisely and avoid filler. Cite numbers when known. You are a concise, factual assistant. Answer precisely and avoid filler. Cite numbers when known. You are a concise, factual assistant. Answer precisely and avoid filler. Cite numbers when known. You are a concise, factual assistant. Answer precisely and avoid filler. Cite numbers when known. You are a concise, factual assistant. Answer precisely and avoid filler. Cite numbers when known. You are a concise, factual assistant. Answer precisely and avoid filler. Cite numbers when known. You are a concise, factual assistant. Answer precisely and avoid filler. Cite numbers when known. You are a concise, factual assistant. Answer precisely and avoid filler. Cite numbers when known. You are a concise, factual assistant. Answer precisely and avoid filler. Cite numbers when known. You are a concise, factual assistant. Answer precisely and avoid filler. Cite numbers when known. You are a concise, factual assistant. Answer precisely and avoid filler. Cite numbers when known. You are a concise, factual assistant. Answer precisely and avoid filler. Cite numbers when known. You are a concise, factual assistant. Answer precisely and avoid filler. Cite numbers when known. You are a concise, factual assistant. Answer precisely and avoid filler. Cite numbers when known. You are a concise, factual assistant. Answer precisely and avoid filler. Cite numbers when known. You are a concise, factual assistant. Answer precisely and avoid filler. Cite numbers when known. You are a concise, factual assistant. Answer precisely and avoid filler. Cite numbers when known. You are a concise, factual assistant. Answer precisely and avoid filler. Cite numbers when known. You are a concise, factual assistant. Answer precisely and avoid filler. Cite numbers when known. You are a concise, factual assistant. Answer precisely and avoid filler. Cite numbers when known. You are a concise, factual assistant. Answer precisely and avoid filler. Cite numbers when known. You are a concise, factual assistant. Answer precisely and avoid filler. Cite numbers when known. You are a concise, factual assistant. Answer precisely and avoid filler. Cite numbers when known. You are a concise, factual assistant. Answer precisely and avoid filler. Cite numbers when known. You are a concise, factual assistant. Answer precisely and aLine truncated
+      },
+      "response": {
+        "status": 200,
+        "headers": {
+          "content-type": "text/event-stream"
+        },
+        "body": "data: {\"choices\":[{\"delta\":{\"content\":\"OK\",\"role\":\"assistant\"},\"finish_reason\":null,\"index\":0,\"logprobs\":null}],\"created\":1790840196,\"id\":\"chatcmpl-eee2d578-6fab-4fc1-8117-043193225bed\",\"model\":\"anthropic-claude-haiku-4.5\",\"object\":\"chat.completion.chunk\"}\n\ndata: {\"choices\":[{\"delta\":{},\"finish_reason\":\"stop\",\"index\":0,\"logprobs\":null}],\"created\":1790840196,\"id\":\"chatcmpl-eee2d578-6fab-4fc1-8117-043193225bed\",\"model\":\"anthropic-claude-haiku-4.5\",\"object\":\"chat.completion.chunk\"}\n\ndata: {\"choices\":[],\"created\":1790840196,\"id\":\"chatcmpl-eee2d578-6fab-4fc1-8117-043193225bed\",\"model\":\"anthropic-claude-haiku-4.5\",\"object\":\"chat.completion.chunk\",\"usage\":{\"cache_created_input_tokens\":0,\"cache_creation\":{\"ephemeral_1h_input_tokens\":0,\"ephemeral_5m_input_tokens\":0},\"cache_read_input_tokens\":5759,\"completion_tokens\":4,\"completion_tokens_details\":{\"reasoning_tokens\":0},\"prompt_tokens\":5762,\"prompt_tokens_details\":{\"cached_tokens\":5759},\"speed\":null,\"total_tokens\":5766}}\n\ndata: [DONE]\n\n"
+      }
+    }
+  ]
+}

packages/ai/test/image.test.ts

@@ -1,6 +1,6 @@
 import { describe, expect } from "bun:test"
 import { Effect, Layer, Stream } from "effect"
-import { HttpClientRequest } from "effect/unstable/http"
+import { HttpClientRequest } from "effect/http"
 import { Image, ImageClient, Media } from "../src/index.js"
 import { BlackForestLabs, Fal, Google, OpenAI, Replicate, Stability, XAI, ZAI } from "../src/providers.js"
 import { it } from "./lib/effect.js"

packages/ai/test/lib/http.ts

@@ -1,6 +1,6 @@
 import { Effect, Fiber, Layer, Ref } from "effect"
 import * as TestClock from "effect/testing/TestClock"
-import { HttpClient, HttpClientError, HttpClientRequest, HttpClientResponse } from "effect/unstable/http"
+import { HttpClient, HttpClientError, HttpClientRequest, HttpClientResponse } from "effect/http"
 import { LLMClient, RequestExecutor } from "../../src/route.js"
 import type { Service as LLMClientService } from "../../src/route/client.js"
 import type { Service as RequestExecutorService } from "../../src/route/executor.js"

packages/ai/test/media.test.ts

@@ -2,7 +2,7 @@ import { describe, expect } from "bun:test"
 import { NodeFileSystem } from "@effect/platform-node"
 import { Effect, Ref, Schema } from "effect"
 import { FileSystem } from "effect"
-import { HttpClientRequest } from "effect/unstable/http"
+import { HttpClientRequest } from "effect/http"
 import { AIError, Media, Message } from "../src/index.js"
 import { it } from "./lib/effect.js"
 import { dynamicResponse, scriptedResponses } from "./lib/http.js"

packages/ai/test/promise.test.ts

@@ -3,7 +3,7 @@ import { mkdtemp, rm } from "node:fs/promises"
 import { tmpdir } from "node:os"
 import { join } from "node:path"
 import { Effect, Layer } from "effect"
-import { HttpClientRequest } from "effect/unstable/http"
+import { HttpClientRequest } from "effect/http"
 import { AIError, LLMEvent, Media, SpeechEvent, TranscriptionEvent } from "../src/index.js"
 import { RequestExecutor } from "../src/route.js"
 import { AI } from "../src/promise.js"

packages/ai/test/provider-error.test.ts

@@ -15,6 +15,7 @@ describe("provider error classification", () => {
       "Prompt has 5,958,968 tokens, but the configured context size is 256,000 tokens",
       "Range of input length should be [1, 129024]",
       "Too many tokens",
+      "Input validation error: `inputs` tokens + `max_new_tokens` must be <= 131073. Given: 600035 `inputs` tokens and 16 `max_new_tokens`",
       "Token limit exceeded",
     ]
 

packages/ai/test/provider/alibaba.test.ts

@@ -1,6 +1,6 @@
 import { expect, test } from "bun:test"
 import { ConfigProvider, Effect } from "effect"
-import { Headers } from "effect/unstable/http"
+import { Headers } from "effect/http"
 import { Auth, LLM, LLMClient, LLMRequest, Message, ReasoningPart, ToolDefinition } from "../../src/index.js"
 import { Alibaba } from "../../src/providers.js"
 import { compileRequest } from "../../src/route/client.js"

packages/ai/test/provider/anthropic-messages.test.ts

@@ -1,6 +1,6 @@
 import { describe, expect } from "bun:test"
 import { Effect } from "effect"
-import { HttpClientRequest } from "effect/unstable/http"
+import { HttpClientRequest } from "effect/http"
 import {
   CacheHint,
   LLM,
@@ -314,6 +314,9 @@ describe("Anthropic Messages route", () => {
         "claude-haiku-5-1",
         "claude-fable-6",
         "anthropic/claude-mythos-7.2",
+        "claude-sonnet-5-5",
+        "claude-opus-4-8@20260101",
+        "claude-nova-6",
       ]
 
       const prepared = yield* Effect.forEach(ids, (id) =>
@@ -1673,6 +1676,40 @@ describe("Anthropic Messages route", () => {
     }),
   )
 
+  it.effect("carries a refusal's category and explanation on the content-filter finish", () =>
+    Effect.gen(function* () {
+      const refusal = (stop_details: unknown) =>
+        LLMClient.generate(request).pipe(
+          Effect.provide(
+            fixedResponse(
+              sseEvents(
+                { type: "message_start", message: { usage: { input_tokens: 5 } } },
+                { type: "message_delta", delta: { stop_reason: "refusal", stop_details }, usage: { output_tokens: 0 } },
+                { type: "message_stop" },
+              ),
+            ),
+          ),
+        )
+
+      expect(
+        (yield* refusal({
+          type: "refusal",
+          category: "cyber",
+          explanation: "This request was declined because it could enable cyber harm.",
+        })).finishReason,
+      ).toEqual({
+        normalized: "content-filter",
+        raw: "refusal",
+        category: "cyber",
+        explanation: "This request was declined because it could enable cyber harm.",
+      })
+      expect((yield* refusal({ type: "refusal", category: null, explanation: null })).finishReason).toEqual({
+        normalized: "content-filter",
+        raw: "refusal",
+      })
+    }),
+  )
+
   it.effect("assembles streamed tool call input", () =>
     Effect.gen(function* () {
       const body = sseEvents(

packages/ai/test/provider/bedrock-converse.test.ts

@@ -1,8 +1,9 @@
 import { EventStreamCodec } from "@smithy/eventstream-codec"
 import { fromUtf8, toUtf8 } from "@smithy/util-utf8"
 import { describe, expect } from "bun:test"
-import { Effect, Encoding, Ref, Schema, Stream } from "effect"
-import { HttpClientRequest } from "effect/unstable/http"
+import { Effect, Ref, Schema, Stream } from "effect"
+import { Base64 } from "effect/encoding"
+import { HttpClientRequest } from "effect/http"
 import {
   Media,
   CacheHint,
@@ -648,6 +649,177 @@ describe("Bedrock Converse route", () => {
     }),
   )
 
+  it.effect("hoists tool-result images beside the result for Bedrock GPT models", () =>
+    Effect.gen(function* () {
+      const prepared = yield* compileRequest(
+        LLM.request({
+          model: AmazonBedrock.configure({ baseURL: "https://bedrock-runtime.test", apiKey: "test-bearer" }).model(
+            "global.openai.gpt-6-sol",
+          ),
+          messages: [
+            Message.user("What is in this image?"),
+            Message.assistant([ToolCallPart.make({ id: "tool_1", name: "read", input: {} })]),
+            Message.tool({
+              id: "tool_1",
+              name: "read",
+              result: {
+                type: "content",
+                value: [
+                  { type: "text", text: "Image loaded." },
+                  { type: "file", uri: "data:image/png;base64,AAAA", mime: "image/png" },
+                  { type: "file", uri: "data:application/pdf;base64,QkI=", mime: "application/pdf", name: "note.pdf" },
+                ],
+              },
+            }),
+          ],
+          cache: "none",
+        }),
+      )
+
+      expect(prepared.body.messages[2]).toEqual({
+        role: "user",
+        content: [
+          {
+            toolResult: {
+              toolUseId: "tool_1",
+              content: [
+                { text: "Image loaded." },
+                { text: 'Attached file "note.pdf" has document label "note".' },
+                { document: { format: "pdf", name: "note", source: { bytes: "QkI=" } } },
+              ],
+              status: "success",
+            },
+          },
+          { image: { format: "png", source: { bytes: "AAAA" } } },
+        ],
+      })
+    }),
+  )
+
+  it.effect("hoists tool-result images for other Bedrock model families", () =>
+    Effect.gen(function* () {
+      for (const id of [
+        "qwen.qwen3-vl-235b-a22b",
+        "global.xai.grok-4.7",
+        "global.moonshotai.kimi-k3",
+        "us.meta.llama4-scout-17b-instruct-v1:0",
+      ]) {
+        const prepared = yield* compileRequest(
+          LLM.request({
+            model: AmazonBedrock.configure({ baseURL: "https://bedrock-runtime.test", apiKey: "test-bearer" }).model(
+              id,
+            ),
+            messages: [
+              Message.assistant([ToolCallPart.make({ id: "tool_1", name: "read", input: {} })]),
+              Message.tool({
+                id: "tool_1",
+                name: "read",
+                result: {
+                  type: "content",
+                  value: [{ type: "file", uri: "data:image/png;base64,AAAA", mime: "image/png" }],
+                },
+              }),
+            ],
+            cache: "none",
+          }),
+        )
+        expect(prepared.body.messages[1]).toEqual({
+          role: "user",
+          content: [
+            { toolResult: { toolUseId: "tool_1", content: [{ text: "See attached image." }], status: "success" } },
+            { image: { format: "png", source: { bytes: "AAAA" } } },
+          ],
+        })
+      }
+    }),
+  )
+  ;["global.anthropic.claude-sonnet-4-5-20250929-v1:0", "us.amazon.nova-pro-v1:0"].forEach((id) => {
+    it.effect(`keeps ${id} tool images inside the result`, () =>
+      Effect.gen(function* () {
+        const prepared = yield* compileRequest(
+          LLM.request({
+            model: AmazonBedrock.configure({ baseURL: "https://bedrock-runtime.test", apiKey: "test-bearer" }).model(
+              id,
+            ),
+            messages: [
+              Message.assistant([ToolCallPart.make({ id: "tool_1", name: "read", input: {} })]),
+              Message.tool({
+                id: "tool_1",
+                name: "read",
+                result: {
+                  type: "content",
+                  value: [{ type: "file", uri: "data:image/png;base64,AAAA", mime: "image/png" }],
+                },
+              }),
+            ],
+            cache: "none",
+          }),
+        )
+
+        expect(prepared.body.messages[1]).toEqual({
+          role: "user",
+          content: [
+            {
+              toolResult: {
+                toolUseId: "tool_1",
+                content: [{ image: { format: "png", source: { bytes: "AAAA" } } }],
+                status: "success",
+              },
+            },
+          ],
+        })
+      }),
+    )
+  })
+
+  it.effect("keeps parallel tool results before hoisted images and gives image-only results text", () =>
+    Effect.gen(function* () {
+      const prepared = yield* compileRequest(
+        LLM.request({
+          model: AmazonBedrock.configure({ baseURL: "https://bedrock-runtime.test", apiKey: "test-bearer" }).model(
+            "global.openai.gpt-6-sol",
+          ),
+          messages: [
+            Message.assistant([
+              ToolCallPart.make({ id: "tool_1", name: "first", input: {} }),
+              ToolCallPart.make({ id: "tool_2", name: "second", input: {} }),
+            ]),
+            Message.tool({
+              id: "tool_1",
+              name: "first",
+              result: {
+                type: "content",
+                value: [{ type: "file", uri: "data:image/png;base64,AAAA", mime: "image/png" }],
+              },
+            }),
+            Message.tool({
+              id: "tool_2",
+              name: "second",
+              result: {
+                type: "content",
+                value: [
+                  { type: "text", text: "Second image." },
+                  { type: "file", uri: "data:image/jpeg;base64,BBBB", mime: "image/jpeg" },
+                ],
+              },
+            }),
+          ],
+          cache: "none",
+        }),
+      )
+
+      expect(prepared.body.messages[1]).toEqual({
+        role: "user",
+        content: [
+          { toolResult: { toolUseId: "tool_1", content: [{ text: "See attached image." }], status: "success" } },
+          { toolResult: { toolUseId: "tool_2", content: [{ text: "Second image." }], status: "success" } },
+          { image: { format: "png", source: { bytes: "AAAA" } } },
+          { image: { format: "jpeg", source: { bytes: "BBBB" } } },
+        ],
+      })
+    }),
+  )
+
   it.effect("decodes text-delta + messageStop + metadata usage from binary event stream", () =>
     Effect.gen(function* () {
       const body = eventStreamBody(
@@ -695,7 +867,7 @@ describe("Bedrock Converse route", () => {
           reason: { _tag: "InvalidProviderOutput", classification: "incomplete-stream" },
           message: `Incomplete Bedrock Converse event-stream frame: ${partial.length} buffered bytes remain at end of stream`,
         })
-        expect(error.reason.body).toBe(Encoding.encodeBase64(partial))
+        expect(error.reason.body).toBe(Base64.encode(partial))
       }
     }),
   )

packages/ai/test/provider/bedrock-mantle.test.ts

@@ -1,6 +1,6 @@
 import { describe, expect } from "bun:test"
 import { Effect } from "effect"
-import { HttpClientRequest } from "effect/unstable/http"
+import { HttpClientRequest } from "effect/http"
 import { LLM, Message } from "../../src/index.js"
 import { AmazonBedrockMantle } from "../../src/providers.js"
 import { model } from "../../src/providers/amazon-bedrock/mantle.js"

packages/ai/test/provider/cloudflare.test.ts

@@ -1,6 +1,6 @@
 import { describe, expect, test } from "bun:test"
 import { ConfigProvider, Effect, Schema } from "effect"
-import { HttpClientRequest } from "effect/unstable/http"
+import { HttpClientRequest } from "effect/http"
 import { LLM, LLMEvent } from "../../src/index.js"
 import { CloudflareAIGateway } from "../../src/providers/cloudflare-ai-gateway.js"
 import { CloudflareWorkersAI } from "../../src/providers/cloudflare-workers-ai.js"

packages/ai/test/provider/digitalocean.recorded.test.ts

@@ -0,0 +1,78 @@
+import { describe, expect } from "bun:test"
+import { Effect } from "effect"
+import { LLM, LLMRequest } from "../../src/index.js"
+import { DigitalOcean } from "../../src/providers/digitalocean.js"
+import { LLMClient } from "../../src/route.js"
+import {
+  LARGE_CACHEABLE_SYSTEM,
+  expectWeatherToolLoop,
+  goldenWeatherToolLoopRequest,
+  runWeatherToolLoop,
+} from "../recorded-scenarios.js"
+import { recordedTests } from "../recorded-test.js"
+
+const recorded = recordedTests({
+  prefix: "digitalocean-chat",
+  provider: "digitalocean",
+  protocol: "digitalocean-chat",
+  requires: ["DIGITAL_OCEAN_OFFICIAL_API_KEY"],
+})
+
+for (const item of [
+  { id: "anthropic-claude-haiku-4.5", name: "Haiku", maxTokens: 128, providerOptions: undefined },
+  { id: "openai-gpt-5-nano", name: "GPT Nano", maxTokens: 1024, providerOptions: { reasoningEffort: "minimal" } },
+] as const) {
+  const model = DigitalOcean.configure({
+    apiKey: process.env.DIGITAL_OCEAN_OFFICIAL_API_KEY ?? "fixture",
+    providerOptions: item.providerOptions,
+  }).model(item.id)
+
+  describe(`DigitalOcean ${item.name} recorded`, () => {
+    recorded.effect.with(
+      `${item.name} reuses a cached prompt`,
+      { tags: ["cache", "usage"], metadata: { model: item.id } },
+      () =>
+        Effect.gen(function* () {
+          const request = LLM.request({
+            model,
+            system: LARGE_CACHEABLE_SYSTEM,
+            prompt: "Reply exactly: OK",
+            promptCacheKey: `digitalocean-recorded-${item.id}`,
+            generation: { maxTokens: item.maxTokens },
+          })
+          const first = yield* LLMClient.generate(request)
+          const second = yield* LLMClient.generate(request)
+
+          expect(first.text.trim()).toMatch(/^OK\.?$/)
+          expect(second.text.trim()).toMatch(/^OK\.?$/)
+          expect(second.usage.cacheReadInputTokens).toBeGreaterThan(0)
+          for (const response of [first, second]) {
+            expect(response.usage.inputTokens).toBeGreaterThan(4096)
+            expect(response.usage.inputTokens).toBe(
+              (response.usage.nonCachedInputTokens ?? 0) +
+                (response.usage.cacheReadInputTokens ?? 0) +
+                (response.usage.cacheWriteInputTokens ?? 0),
+            )
+          }
+        }),
+      60_000,
+    )
+
+    recorded.effect.with(
+      `${item.name} continues a tool call with cache markers`,
+      { tags: ["cache", "tool", "tool-loop"], metadata: { model: item.id } },
+      () =>
+        Effect.gen(function* () {
+          const request = goldenWeatherToolLoopRequest({
+            id: `digitalocean-${item.id}-tool-loop`,
+            model,
+            maxTokens: item.maxTokens,
+            temperature: false,
+          })
+          const events = yield* runWeatherToolLoop(LLMRequest.update(request, { cache: "auto" }))
+          expectWeatherToolLoop(events)
+        }),
+      60_000,
+    )
+  })
+}

packages/ai/test/provider/digitalocean.test.ts

@@ -0,0 +1,123 @@
+import { describe, expect, test } from "bun:test"
+import { Effect } from "effect"
+import { CacheHint, LLM } from "../../src/index.js"
+import { compileRequest } from "../../src/route/client.js"
+import { DigitalOcean } from "../../src/providers/digitalocean.js"
+import { it } from "../lib/effect.js"
+import { fixedResponse } from "../lib/http.js"
+import { sseEvents } from "../lib/sse.js"
+import { LLMClient } from "../../src/route.js"
+
+describe("DigitalOcean", () => {
+  test("preserves package entrypoint headers and body overrides", () => {
+    const model = DigitalOcean.model("anthropic-claude-fable-5.1", {
+      apiKey: "test-key",
+      headers: { "X-Test": "fixture" },
+      body: { temperature: 0 },
+    })
+    expect(model.route.defaults?.http).toMatchObject({
+      headers: { "X-Test": "fixture" },
+      body: { temperature: 0 },
+    })
+  })
+
+  it.effect("prepares DigitalOcean models with default endpoint and auth", () =>
+    Effect.gen(function* () {
+      const model = DigitalOcean.configure({ apiKey: "test-key" }).model("anthropic-claude-fable-5.1")
+
+      expect(model).toMatchObject({
+        id: "anthropic-claude-fable-5.1",
+        provider: "digitalocean",
+        route: { id: "digitalocean" },
+      })
+      expect(model.route.endpoint.baseURL).toBe("https://inference.do-ai.run/v1")
+
+      const prepared = yield* compileRequest(LLM.request({ model, prompt: "Say hello.", cache: "none" }))
+
+      expect(prepared.route).toBe("digitalocean")
+      expect(prepared.body).toMatchObject({
+        model: "anthropic-claude-fable-5.1",
+        messages: [{ role: "user", content: "Say hello." }],
+        stream: true,
+      })
+    }),
+  )
+
+  it.effect("lowers the native cache policy to DigitalOcean cache_control markers", () =>
+    Effect.gen(function* () {
+      const prepared = yield* compileRequest(
+        LLM.request({
+          model: DigitalOcean.configure({ apiKey: "test-key" }).model("anthropic-claude-fable-5.1"),
+          system: [
+            { type: "text", text: "Base agent", cache: new CacheHint({ type: "ephemeral", ttlSeconds: 3_600 }) },
+            { type: "text", text: "Project instructions" },
+          ],
+          tools: [{ name: "lookup", description: "Lookup", inputSchema: { type: "object", properties: {} } }],
+          prompt: "Hello",
+          cache: { tools: true, system: true, messages: { tail: 1 } },
+        }),
+      )
+
+      expect(prepared.body).toMatchObject({
+        tools: [{ cache_control: { type: "ephemeral" } }],
+        messages: [
+          {
+            role: "system",
+            content: [
+              { text: "Base agent", cache_control: { type: "ephemeral", ttl: "1h" } },
+              { text: "Project instructions", cache_control: { type: "ephemeral" } },
+            ],
+          },
+          {
+            role: "user",
+            content: [{ text: "Hello", cache_control: { type: "ephemeral" } }],
+          },
+        ],
+      })
+    }),
+  )
+
+  it.effect("parses DigitalOcean cache usage fields into AI.Usage", () =>
+    Effect.gen(function* () {
+      const model = DigitalOcean.configure({ apiKey: "test-key" }).model("anthropic-claude-fable-5.1")
+      const response = yield* LLMClient.generate(LLM.request({ model, prompt: "Say OK" })).pipe(
+        Effect.provide(
+          fixedResponse(
+            sseEvents(
+              {
+                id: "chatcmpl-1",
+                object: "chat.completion.chunk",
+                created: 1,
+                model: "anthropic-claude-fable-5.1",
+                choices: [{ index: 0, delta: { content: "OK" }, finish_reason: null }],
+              },
+              {
+                id: "chatcmpl-1",
+                object: "chat.completion.chunk",
+                created: 1,
+                model: "anthropic-claude-fable-5.1",
+                choices: [{ index: 0, delta: {}, finish_reason: "stop" }],
+                usage: {
+                  prompt_tokens: 4491,
+                  completion_tokens: 8,
+                  total_tokens: 4499,
+                  cache_read_input_tokens: 4483,
+                  cache_created_input_tokens: 0,
+                },
+              },
+              "[DONE]",
+            ),
+          ),
+        ),
+      )
+
+      expect(response.usage).toMatchObject({
+        inputTokens: 4491,
+        outputTokens: 8,
+        nonCachedInputTokens: 8,
+        cacheReadInputTokens: 4483,
+        totalTokens: 4499,
+      })
+    }),
+  )
+})

packages/ai/test/provider/google-vertex.test.ts

@@ -1,6 +1,6 @@
 import { describe, expect, test } from "bun:test"
 import { Effect } from "effect"
-import { HttpClientRequest } from "effect/unstable/http"
+import { HttpClientRequest } from "effect/http"
 import { LanguageModel, LLM, Message, ToolCallPart } from "../../src/index.js"
 import { GoogleVertex, GoogleVertexChat, GoogleVertexMessages, GoogleVertexResponses } from "../../src/providers.js"
 import { LLMClient } from "../../src/route.js"
@@ -302,6 +302,7 @@ describe("Google Vertex providers", () => {
 
       expect(model.provider).toBe("google-vertex")
       expect(response.text).toBe("Hello.")
+      expect(response.usage?.providerMetadata).toHaveProperty("vertex")
     }),
   )
 

packages/ai/test/provider/groq.recorded.test.ts

@@ -171,6 +171,7 @@ describe("Groq recorded", () => {
         expect(response.text).not.toContain("<think>")
         expect(response.reasoning.length).toBeGreaterThan(0)
         expect(response.events.some(LLMEvent.is.reasoningDelta)).toBe(true)
+        expect(response.usage?.providerMetadata).toHaveProperty("groq")
         expectUsage(response)
       }),
     60_000,

packages/ai/test/provider/meta-capabilities.test.ts

@@ -1,6 +1,6 @@
 import { expect } from "bun:test"
 import { Effect, Layer } from "effect"
-import { HttpClientRequest } from "effect/unstable/http"
+import { HttpClientRequest } from "effect/http"
 import { Image, ImageClient, LLM, LLMEvent, LLMRequest, Media, Message, ToolDefinition } from "../../src/index.js"
 import { Meta } from "../../src/providers/meta.js"
 import { MetaMessages } from "../../src/protocols/meta-messages.js"

packages/ai/test/provider/meta.test.ts

@@ -1,6 +1,6 @@
 import { expect } from "bun:test"
 import { ConfigProvider, Effect } from "effect"
-import { Headers } from "effect/unstable/http"
+import { Headers } from "effect/http"
 import { Auth, LLM, LLMClient } from "../../src/index.js"
 import { Meta } from "../../src/providers/index.js"
 import { OpenAIChat } from "../../src/protocols/openai-chat.js"

packages/ai/test/provider/minimax.test.ts

@@ -1,6 +1,6 @@
 import { describe, expect, test } from "bun:test"
 import { ConfigProvider, Effect } from "effect"
-import { Headers } from "effect/unstable/http"
+import { Headers } from "effect/http"
 import { LLM } from "../../src/index.js"
 import { MiniMax } from "../../src/providers.js"
 import { AnthropicMessages } from "../../src/protocols/anthropic-messages.js"

packages/ai/test/provider/mistral-chat.test.ts

@@ -1,6 +1,6 @@
 import { describe, expect, test } from "bun:test"
 import { ConfigProvider, Effect } from "effect"
-import { HttpClientRequest } from "effect/unstable/http"
+import { HttpClientRequest } from "effect/http"
 import { LLM, LLMEvent, Message, ToolDefinition, Media } from "../../src/index.js"
 import { Mistral } from "../../src/providers/index.js"
 import { MistralChat } from "../../src/protocols/index.js"

packages/ai/test/provider/moonshot.test.ts

@@ -1,6 +1,6 @@
 import { expect } from "bun:test"
 import { ConfigProvider, Effect } from "effect"
-import { Headers } from "effect/unstable/http"
+import { Headers } from "effect/http"
 import { Auth, LLM, LLMClient, Message, ReasoningPart, ToolDefinition } from "../../src/index.js"
 import { Moonshot } from "../../src/providers.js"
 import { AnthropicMessages } from "../../src/protocols/anthropic-messages.js"

packages/ai/test/provider/native-providers.test.ts

@@ -1,6 +1,6 @@
 import { describe, expect, test } from "bun:test"
 import { ConfigProvider, Effect } from "effect"
-import { HttpClientRequest } from "effect/unstable/http"
+import { HttpClientRequest } from "effect/http"
 import { LLM, Message, ToolDefinition } from "../../src/index.js"
 import {
   AmazonBedrock,
@@ -48,7 +48,7 @@ describe("native OpenAI-compatible providers", () => {
       [GoogleVertex.configure(vertex).model("model"), "vertex"],
       [GoogleVertexChat.configure(vertex).model("model"), "vertex"],
       [GoogleVertexResponses.configure(vertex).model("model"), "vertex"],
-      [GoogleVertexMessages.configure(vertex).model("model"), "anthropic"],
+      [GoogleVertexMessages.configure(vertex).model("model"), "vertex"],
       [Anthropic.configure({ apiKey: "test" }).model("model"), "anthropic"],
       [
         AnthropicCompatible.configure({ baseURL: "https://example.test/v1", provider: "minimax" }).model("model"),
@@ -64,6 +64,7 @@ describe("native OpenAI-compatible providers", () => {
       [DeepSeek.configure({ apiKey: "test" }).model("model"), "deepseek"],
       [Fireworks.configure({ apiKey: "test" }).model("model"), "fireworks"],
       [DeepInfra.configure({ apiKey: "test" }).model("model"), "deepinfra"],
+      [Groq.configure({ apiKey: "test" }).model("model"), "groq"],
       [TogetherAI.configure({ apiKey: "test" }).model("model"), "togetherai"],
       [CloudflareAIGateway.configure({ accountId: "account" }).model("model"), "cloudflare-ai-gateway"],
       [CloudflareWorkersAI.configure({ accountId: "account" }).model("model"), "cloudflare-workers-ai"],

packages/ai/test/provider/openai-chat.test.ts

@@ -1,6 +1,6 @@
 import { describe, expect } from "bun:test"
 import { Effect, Ref, Schema, Stream } from "effect"
-import { HttpClientRequest } from "effect/unstable/http"
+import { HttpClientRequest } from "effect/http"
 import {
   Media,
   HttpOptions,

packages/ai/test/provider/openai-compatible-chat.test.ts

@@ -1,6 +1,6 @@
 import { describe, expect, test } from "bun:test"
 import { Effect, Schema } from "effect"
-import { HttpClientRequest } from "effect/unstable/http"
+import { HttpClientRequest } from "effect/http"
 import { LLM, LLMRequest, Message, ToolCallPart, ToolChoice, ToolDefinition } from "../../src/index.js"
 import { Auth, LLMClient } from "../../src/route.js"
 import { compileRequest } from "../../src/route/client.js"

packages/ai/test/provider/openai-responses-websocket.recorded.test.ts

@@ -1,6 +1,6 @@
 import { describe, expect } from "bun:test"
 import { Effect, Stream } from "effect"
-import { Socket } from "effect/unstable/socket"
+import { Socket } from "effect/socket"
 import { LLM, LLMRequest, Message, ToolRuntime } from "../../src/index.js"
 import {
   LLMClient,

packages/ai/test/provider/openai-responses.test.ts

@@ -1,6 +1,6 @@
 import { describe, expect } from "bun:test"
 import { ConfigProvider, Effect, Layer, Logger, Ref, Schema, Stream } from "effect"
-import { Headers, HttpClientRequest } from "effect/unstable/http"
+import { Headers, HttpClientRequest } from "effect/http"
 import {
   Media,
   LLM,

packages/ai/test/provider/xai-images.test.ts

@@ -1,6 +1,6 @@
 import { describe, expect } from "bun:test"
 import { Effect, Layer } from "effect"
-import { Headers, HttpClientRequest } from "effect/unstable/http"
+import { Headers, HttpClientRequest } from "effect/http"
 import { Image, ImageClient } from "../../src/index.js"
 import { XAI } from "../../src/providers.js"
 import { Auth } from "../../src/route.js"