fix(ci): allow dependabot[bot] in Claude dependabot review workflow

The Claude Code Action rejects bot actors by default. Adding dependabot[bot] to allowed_bots so the automated dependency review can run on Dependabot PRs.
2026-02-10 06:45:28 -05:00 · 2026-02-08 17:01:28 -06:00
37 changed files with 636 additions and 1969 deletions
--- a/.github/workflows/classic-frontend-ci.yml
+++ b/.github/workflows/classic-frontend-ci.yml
@@ -49,7 +49,7 @@ jobs:
      - name: Create PR ${{ env.BUILD_BRANCH }} -> ${{ github.ref_name }}
        if: github.event_name == 'push'
-        uses: peter-evans/create-pull-request@v8
+        uses: peter-evans/create-pull-request@v7
        with:
          add-paths: classic/frontend/build/web
          base: ${{ github.ref_name }}
--- a/.github/workflows/claude-ci-failure-auto-fix.yml
+++ b/.github/workflows/claude-ci-failure-auto-fix.yml
@@ -42,7 +42,7 @@ jobs:
      - name: Get CI failure details
        id: failure_details
-        uses: actions/github-script@v8
+        uses: actions/github-script@v7
        with:
          script: |
            const run = await github.rest.actions.getWorkflowRun({
--- a/.github/workflows/claude-dependabot.yml
+++ b/.github/workflows/claude-dependabot.yml
@@ -41,7 +41,7 @@ jobs:
          python-version: "3.11"  # Use standard version matching CI
      - name: Set up Python dependency cache
-        uses: actions/cache@v5
+        uses: actions/cache@v4
        with:
          path: ~/.cache/pypoetry
          key: poetry-${{ runner.os }}-${{ hashFiles('autogpt_platform/backend/poetry.lock') }}
@@ -78,7 +78,7 @@ jobs:
      # Frontend Node.js/pnpm setup (mirrors platform-frontend-ci.yml)
      - name: Set up Node.js
-        uses: actions/setup-node@v6
+        uses: actions/setup-node@v4
        with:
          node-version: "22"
@@ -91,7 +91,7 @@ jobs:
          echo "PNPM_HOME=$HOME/.pnpm-store" >> $GITHUB_ENV
      - name: Cache frontend dependencies
-        uses: actions/cache@v5
+        uses: actions/cache@v4
        with:
          path: ~/.pnpm-store
          key: ${{ runner.os }}-pnpm-${{ hashFiles('autogpt_platform/frontend/pnpm-lock.yaml', 'autogpt_platform/frontend/package.json') }}
@@ -124,7 +124,7 @@ jobs:
      # Phase 1: Cache and load Docker images for faster setup
      - name: Set up Docker image cache
        id: docker-cache
-        uses: actions/cache@v5
+        uses: actions/cache@v4
        with:
          path: ~/docker-cache
          # Use a versioned key for cache invalidation when image list changes
--- a/.github/workflows/claude.yml
+++ b/.github/workflows/claude.yml
@@ -57,7 +57,7 @@ jobs:
          python-version: "3.11"  # Use standard version matching CI
      - name: Set up Python dependency cache
-        uses: actions/cache@v5
+        uses: actions/cache@v4
        with:
          path: ~/.cache/pypoetry
          key: poetry-${{ runner.os }}-${{ hashFiles('autogpt_platform/backend/poetry.lock') }}
@@ -94,7 +94,7 @@ jobs:
      # Frontend Node.js/pnpm setup (mirrors platform-frontend-ci.yml)
      - name: Set up Node.js
-        uses: actions/setup-node@v6
+        uses: actions/setup-node@v4
        with:
          node-version: "22"
@@ -107,7 +107,7 @@ jobs:
          echo "PNPM_HOME=$HOME/.pnpm-store" >> $GITHUB_ENV
      - name: Cache frontend dependencies
-        uses: actions/cache@v5
+        uses: actions/cache@v4
        with:
          path: ~/.pnpm-store
          key: ${{ runner.os }}-pnpm-${{ hashFiles('autogpt_platform/frontend/pnpm-lock.yaml', 'autogpt_platform/frontend/package.json') }}
@@ -140,7 +140,7 @@ jobs:
      # Phase 1: Cache and load Docker images for faster setup
      - name: Set up Docker image cache
        id: docker-cache
-        uses: actions/cache@v5
+        uses: actions/cache@v4
        with:
          path: ~/docker-cache
          # Use a versioned key for cache invalidation when image list changes
--- a/.github/workflows/copilot-setup-steps.yml
+++ b/.github/workflows/copilot-setup-steps.yml
@@ -39,7 +39,7 @@ jobs:
          python-version: "3.11"  # Use standard version matching CI
      - name: Set up Python dependency cache
-        uses: actions/cache@v5
+        uses: actions/cache@v4
        with:
          path: ~/.cache/pypoetry
          key: poetry-${{ runner.os }}-${{ hashFiles('autogpt_platform/backend/poetry.lock') }}
@@ -76,7 +76,7 @@ jobs:
      # Frontend Node.js/pnpm setup (mirrors platform-frontend-ci.yml)
      - name: Set up Node.js
-        uses: actions/setup-node@v6
+        uses: actions/setup-node@v4
        with:
          node-version: "22"
@@ -89,7 +89,7 @@ jobs:
          echo "PNPM_HOME=$HOME/.pnpm-store" >> $GITHUB_ENV
      - name: Cache frontend dependencies
-        uses: actions/cache@v5
+        uses: actions/cache@v4
        with:
          path: ~/.pnpm-store
          key: ${{ runner.os }}-pnpm-${{ hashFiles('autogpt_platform/frontend/pnpm-lock.yaml', 'autogpt_platform/frontend/package.json') }}
@@ -132,7 +132,7 @@ jobs:
      # Phase 1: Cache and load Docker images for faster setup
      - name: Set up Docker image cache
        id: docker-cache
-        uses: actions/cache@v5
+        uses: actions/cache@v4
        with:
          path: ~/docker-cache
          # Use a versioned key for cache invalidation when image list changes
--- a/.github/workflows/docs-block-sync.yml
+++ b/.github/workflows/docs-block-sync.yml
@@ -33,7 +33,7 @@ jobs:
          python-version: "3.11"
      - name: Set up Python dependency cache
-        uses: actions/cache@v5
+        uses: actions/cache@v4
        with:
          path: ~/.cache/pypoetry
          key: poetry-${{ runner.os }}-${{ hashFiles('autogpt_platform/backend/poetry.lock') }}
--- a/.github/workflows/docs-claude-review.yml
+++ b/.github/workflows/docs-claude-review.yml
@@ -33,7 +33,7 @@ jobs:
          python-version: "3.11"
      - name: Set up Python dependency cache
-        uses: actions/cache@v5
+        uses: actions/cache@v4
        with:
          path: ~/.cache/pypoetry
          key: poetry-${{ runner.os }}-${{ hashFiles('autogpt_platform/backend/poetry.lock') }}
--- a/.github/workflows/docs-enhance.yml
+++ b/.github/workflows/docs-enhance.yml
@@ -38,7 +38,7 @@ jobs:
          python-version: "3.11"
      - name: Set up Python dependency cache
-        uses: actions/cache@v5
+        uses: actions/cache@v4
        with:
          path: ~/.cache/pypoetry
          key: poetry-${{ runner.os }}-${{ hashFiles('autogpt_platform/backend/poetry.lock') }}
--- a/.github/workflows/platform-backend-ci.yml
+++ b/.github/workflows/platform-backend-ci.yml
@@ -88,7 +88,7 @@ jobs:
        run: echo "date=$(date +'%Y-%m-%d')" >> $GITHUB_OUTPUT
      - name: Set up Python dependency cache
-        uses: actions/cache@v5
+        uses: actions/cache@v4
        with:
          path: ~/.cache/pypoetry
          key: poetry-${{ runner.os }}-${{ hashFiles('autogpt_platform/backend/poetry.lock') }}
--- a/.github/workflows/platform-dev-deploy-event-dispatcher.yml
+++ b/.github/workflows/platform-dev-deploy-event-dispatcher.yml
@@ -17,7 +17,7 @@ jobs:
      - name: Check comment permissions and deployment status
        id: check_status
        if: github.event_name == 'issue_comment' && github.event.issue.pull_request
-        uses: actions/github-script@v8
+        uses: actions/github-script@v7
        with:
          script: |
            const commentBody = context.payload.comment.body.trim();
@@ -55,7 +55,7 @@ jobs:
      - name: Post permission denied comment
        if: steps.check_status.outputs.permission_denied == 'true'
-        uses: actions/github-script@v8
+        uses: actions/github-script@v7
        with:
          script: |
            await github.rest.issues.createComment({
@@ -68,7 +68,7 @@ jobs:
      - name: Get PR details for deployment
        id: pr_details
        if: steps.check_status.outputs.should_deploy == 'true' || steps.check_status.outputs.should_undeploy == 'true'
-        uses: actions/github-script@v8
+        uses: actions/github-script@v7
        with:
          script: |
            const pr = await github.rest.pulls.get({
@@ -98,7 +98,7 @@ jobs:
      - name: Post deploy success comment
        if: steps.check_status.outputs.should_deploy == 'true'
-        uses: actions/github-script@v8
+        uses: actions/github-script@v7
        with:
          script: |
            await github.rest.issues.createComment({
@@ -126,7 +126,7 @@ jobs:
      - name: Post undeploy success comment
        if: steps.check_status.outputs.should_undeploy == 'true'
-        uses: actions/github-script@v8
+        uses: actions/github-script@v7
        with:
          script: |
            await github.rest.issues.createComment({
@@ -139,7 +139,7 @@ jobs:
      - name: Check deployment status on PR close
        id: check_pr_close
        if: github.event_name == 'pull_request' && github.event.action == 'closed'
-        uses: actions/github-script@v8
+        uses: actions/github-script@v7
        with:
          script: |
            const comments = await github.rest.issues.listComments({
@@ -187,7 +187,7 @@ jobs:
          github.event_name == 'pull_request' &&
          github.event.action == 'closed' &&
          steps.check_pr_close.outputs.should_undeploy == 'true'
-        uses: actions/github-script@v8
+        uses: actions/github-script@v7
        with:
          script: |
            await github.rest.issues.createComment({
--- a/.github/workflows/platform-frontend-ci.yml
+++ b/.github/workflows/platform-frontend-ci.yml
@@ -42,7 +42,7 @@ jobs:
              - 'autogpt_platform/frontend/src/components/**'
      - name: Set up Node.js
-        uses: actions/setup-node@v6
+        uses: actions/setup-node@v4
        with:
          node-version: "22.18.0"
@@ -54,7 +54,7 @@ jobs:
        run: echo "key=${{ runner.os }}-pnpm-${{ hashFiles('autogpt_platform/frontend/pnpm-lock.yaml', 'autogpt_platform/frontend/package.json') }}" >> $GITHUB_OUTPUT
      - name: Cache dependencies
-        uses: actions/cache@v5
+        uses: actions/cache@v4
        with:
          path: ~/.pnpm-store
          key: ${{ steps.cache-key.outputs.key }}
@@ -74,7 +74,7 @@ jobs:
        uses: actions/checkout@v4
      - name: Set up Node.js
-        uses: actions/setup-node@v6
+        uses: actions/setup-node@v4
        with:
          node-version: "22.18.0"
@@ -82,7 +82,7 @@ jobs:
        run: corepack enable
      - name: Restore dependencies cache
-        uses: actions/cache@v5
+        uses: actions/cache@v4
        with:
          path: ~/.pnpm-store
          key: ${{ needs.setup.outputs.cache-key }}
@@ -112,7 +112,7 @@ jobs:
          fetch-depth: 0
      - name: Set up Node.js
-        uses: actions/setup-node@v6
+        uses: actions/setup-node@v4
        with:
          node-version: "22.18.0"
@@ -120,7 +120,7 @@ jobs:
        run: corepack enable
      - name: Restore dependencies cache
-        uses: actions/cache@v5
+        uses: actions/cache@v4
        with:
          path: ~/.pnpm-store
          key: ${{ needs.setup.outputs.cache-key }}
@@ -153,7 +153,7 @@ jobs:
          submodules: recursive
      - name: Set up Node.js
-        uses: actions/setup-node@v6
+        uses: actions/setup-node@v4
        with:
          node-version: "22.18.0"
@@ -176,7 +176,7 @@ jobs:
        uses: docker/setup-buildx-action@v3
      - name: Cache Docker layers
-        uses: actions/cache@v5
+        uses: actions/cache@v4
        with:
          path: /tmp/.buildx-cache
          key: ${{ runner.os }}-buildx-frontend-test-${{ hashFiles('autogpt_platform/docker-compose.yml', 'autogpt_platform/backend/Dockerfile', 'autogpt_platform/backend/pyproject.toml', 'autogpt_platform/backend/poetry.lock') }}
@@ -231,7 +231,7 @@ jobs:
          fi
      - name: Restore dependencies cache
-        uses: actions/cache@v5
+        uses: actions/cache@v4
        with:
          path: ~/.pnpm-store
          key: ${{ needs.setup.outputs.cache-key }}
@@ -282,7 +282,7 @@ jobs:
          submodules: recursive
      - name: Set up Node.js
-        uses: actions/setup-node@v6
+        uses: actions/setup-node@v4
        with:
          node-version: "22.18.0"
@@ -290,7 +290,7 @@ jobs:
        run: corepack enable
      - name: Restore dependencies cache
-        uses: actions/cache@v5
+        uses: actions/cache@v4
        with:
          path: ~/.pnpm-store
          key: ${{ needs.setup.outputs.cache-key }}
--- a/.github/workflows/platform-fullstack-ci.yml
+++ b/.github/workflows/platform-fullstack-ci.yml
@@ -32,7 +32,7 @@ jobs:
        uses: actions/checkout@v4
      - name: Set up Node.js
-        uses: actions/setup-node@v6
+        uses: actions/setup-node@v4
        with:
          node-version: "22.18.0"
@@ -44,7 +44,7 @@ jobs:
        run: echo "key=${{ runner.os }}-pnpm-${{ hashFiles('autogpt_platform/frontend/pnpm-lock.yaml', 'autogpt_platform/frontend/package.json') }}" >> $GITHUB_OUTPUT
      - name: Cache dependencies
-        uses: actions/cache@v5
+        uses: actions/cache@v4
        with:
          path: ~/.pnpm-store
          key: ${{ steps.cache-key.outputs.key }}
@@ -68,7 +68,7 @@ jobs:
          submodules: recursive
      - name: Set up Node.js
-        uses: actions/setup-node@v6
+        uses: actions/setup-node@v4
        with:
          node-version: "22.18.0"
@@ -88,7 +88,7 @@ jobs:
          docker compose -f ../docker-compose.yml --profile local --profile deps_backend up -d
      - name: Restore dependencies cache
-        uses: actions/cache@v5
+        uses: actions/cache@v4
        with:
          path: ~/.pnpm-store
          key: ${{ needs.setup.outputs.cache-key }}
--- a/autogpt_platform/autogpt_libs/poetry.lock
+++ b/autogpt_platform/autogpt_libs/poetry.lock
@@ -1,4 +1,4 @@
-# This file is automatically @generated by Poetry 2.2.1 and should not be changed by hand.
+# This file is automatically @generated by Poetry 2.1.1 and should not be changed by hand.
 [[package]]
 name = "annotated-doc"
@@ -67,7 +67,7 @@ description = "Backport of asyncio.Runner, a context manager that controls event
 optional = false
 python-versions = "<3.11,>=3.8"
 groups = ["dev"]
-markers = "python_version == \"3.10\""
+markers = "python_version < \"3.11\""
 files = [
    {file = "backports_asyncio_runner-1.2.0-py3-none-any.whl", hash = "sha256:0da0a936a8aeb554eccb426dc55af3ba63bcdc69fa1a600b5bb305413a4477b5"},
    {file = "backports_asyncio_runner-1.2.0.tar.gz", hash = "sha256:a5aa7b2b7d8f8bfcaa2b57313f70792df84e32a2a746f585213373f900b42162"},
@@ -99,101 +99,84 @@ files = [
 [[package]]
 name = "cffi"
-version = "2.0.0"
+version = "1.17.1"
 description = "Foreign Function Interface for Python calling C code."
 optional = false
-python-versions = ">=3.9"
+python-versions = ">=3.8"
 groups = ["main"]
 markers = "platform_python_implementation != \"PyPy\""
 files = [
-    {file = "cffi-2.0.0-cp310-cp310-macosx_10_13_x86_64.whl", hash = "sha256:0cf2d91ecc3fcc0625c2c530fe004f82c110405f101548512cce44322fa8ac44"},
+    {file = "cffi-1.17.1-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:df8b1c11f177bc2313ec4b2d46baec87a5f3e71fc8b45dab2ee7cae86d9aba14"},
-    {file = "cffi-2.0.0-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:f73b96c41e3b2adedc34a7356e64c8eb96e03a3782b535e043a986276ce12a49"},
+    {file = "cffi-1.17.1-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:8f2cdc858323644ab277e9bb925ad72ae0e67f69e804f4898c070998d50b1a67"},
-    {file = "cffi-2.0.0-cp310-cp310-manylinux1_i686.manylinux2014_i686.manylinux_2_17_i686.manylinux_2_5_i686.whl", hash = "sha256:53f77cbe57044e88bbd5ed26ac1d0514d2acf0591dd6bb02a3ae37f76811b80c"},
+    {file = "cffi-1.17.1-cp310-cp310-manylinux_2_12_i686.manylinux2010_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:edae79245293e15384b51f88b00613ba9f7198016a5948b5dddf4917d4d26382"},
-    {file = "cffi-2.0.0-cp310-cp310-manylinux2014_aarch64.manylinux_2_17_aarch64.whl", hash = "sha256:3e837e369566884707ddaf85fc1744b47575005c0a229de3327f8f9a20f4efeb"},
+    {file = "cffi-1.17.1-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:45398b671ac6d70e67da8e4224a065cec6a93541bb7aebe1b198a61b58c7b702"},
-    {file = "cffi-2.0.0-cp310-cp310-manylinux2014_ppc64le.manylinux_2_17_ppc64le.whl", hash = "sha256:5eda85d6d1879e692d546a078b44251cdd08dd1cfb98dfb77b670c97cee49ea0"},
+    {file = "cffi-1.17.1-cp310-cp310-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:ad9413ccdeda48c5afdae7e4fa2192157e991ff761e7ab8fdd8926f40b160cc3"},
-    {file = "cffi-2.0.0-cp310-cp310-manylinux2014_s390x.manylinux_2_17_s390x.whl", hash = "sha256:9332088d75dc3241c702d852d4671613136d90fa6881da7d770a483fd05248b4"},
+    {file = "cffi-1.17.1-cp310-cp310-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:5da5719280082ac6bd9aa7becb3938dc9f9cbd57fac7d2871717b1feb0902ab6"},
-    {file = "cffi-2.0.0-cp310-cp310-manylinux2014_x86_64.manylinux_2_17_x86_64.whl", hash = "sha256:fc7de24befaeae77ba923797c7c87834c73648a05a4bde34b3b7e5588973a453"},
+    {file = "cffi-1.17.1-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:2bb1a08b8008b281856e5971307cc386a8e9c5b625ac297e853d36da6efe9c17"},
-    {file = "cffi-2.0.0-cp310-cp310-musllinux_1_2_aarch64.whl", hash = "sha256:cf364028c016c03078a23b503f02058f1814320a56ad535686f90565636a9495"},
+    {file = "cffi-1.17.1-cp310-cp310-musllinux_1_1_aarch64.whl", hash = "sha256:045d61c734659cc045141be4bae381a41d89b741f795af1dd018bfb532fd0df8"},
-    {file = "cffi-2.0.0-cp310-cp310-musllinux_1_2_i686.whl", hash = "sha256:e11e82b744887154b182fd3e7e8512418446501191994dbf9c9fc1f32cc8efd5"},
+    {file = "cffi-1.17.1-cp310-cp310-musllinux_1_1_i686.whl", hash = "sha256:6883e737d7d9e4899a8a695e00ec36bd4e5e4f18fabe0aca0efe0a4b44cdb13e"},
-    {file = "cffi-2.0.0-cp310-cp310-musllinux_1_2_x86_64.whl", hash = "sha256:8ea985900c5c95ce9db1745f7933eeef5d314f0565b27625d9a10ec9881e1bfb"},
+    {file = "cffi-1.17.1-cp310-cp310-musllinux_1_1_x86_64.whl", hash = "sha256:6b8b4a92e1c65048ff98cfe1f735ef8f1ceb72e3d5f0c25fdb12087a23da22be"},
-    {file = "cffi-2.0.0-cp310-cp310-win32.whl", hash = "sha256:1f72fb8906754ac8a2cc3f9f5aaa298070652a0ffae577e0ea9bd480dc3c931a"},
+    {file = "cffi-1.17.1-cp310-cp310-win32.whl", hash = "sha256:c9c3d058ebabb74db66e431095118094d06abf53284d9c81f27300d0e0d8bc7c"},
-    {file = "cffi-2.0.0-cp310-cp310-win_amd64.whl", hash = "sha256:b18a3ed7d5b3bd8d9ef7a8cb226502c6bf8308df1525e1cc676c3680e7176739"},
+    {file = "cffi-1.17.1-cp310-cp310-win_amd64.whl", hash = "sha256:0f048dcf80db46f0098ccac01132761580d28e28bc0f78ae0d58048063317e15"},
-    {file = "cffi-2.0.0-cp311-cp311-macosx_10_13_x86_64.whl", hash = "sha256:b4c854ef3adc177950a8dfc81a86f5115d2abd545751a304c5bcf2c2c7283cfe"},
+    {file = "cffi-1.17.1-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:a45e3c6913c5b87b3ff120dcdc03f6131fa0065027d0ed7ee6190736a74cd401"},
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+    {file = "cffi-1.17.1-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:30c5e0cb5ae493c04c8b42916e52ca38079f1b235c2f8ae5f4527b963c401caf"},
-    {file = "cffi-2.0.0-cp311-cp311-manylinux1_i686.manylinux2014_i686.manylinux_2_17_i686.manylinux_2_5_i686.whl", hash = "sha256:baf5215e0ab74c16e2dd324e8ec067ef59e41125d3eade2b863d294fd5035c92"},
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 [[package]]
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 python-versions = ">=3.8"
 groups = ["dev"]
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 files = [
    {file = "tomli-2.2.1-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:678e4fa69e4575eb77d103de3df8a895e1591b48e740211bd1067378c69e8249"},
    {file = "tomli-2.2.1-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:023aa114dd824ade0100497eb2318602af309e5a55595f76b626d6d9f3b7b0a6"},
@@ -2893,4 +2863,4 @@ type = ["pytest-mypy"]
 [metadata]
 lock-version = "2.1"
 python-versions = ">=3.10,<4.0"
-content-hash = "b7ac335a86aa44c3d7d2802298818b389a6f1286e3e9b7b0edb2ff06377cecaf"
+content-hash = "5f15a9c9381c9a374f3d18e087c23b1f1ba8cce192d6f67463a3e3a7a18fee44"
--- a/autogpt_platform/autogpt_libs/pyproject.toml
+++ b/autogpt_platform/autogpt_libs/pyproject.toml
@@ -9,7 +9,7 @@ packages = [{ include = "autogpt_libs" }]
 [tool.poetry.dependencies]
 python = ">=3.10,<4.0"
 colorama = "^0.4.6"
-cryptography = "^46.0"
+cryptography = "^45.0"
 expiringdict = "^1.2.2"
 fastapi = "^0.128.0"
 google-cloud-logging = "^3.13.0"
@@ -22,12 +22,12 @@ supabase = "^2.27.2"
 uvicorn = "^0.40.0"
 [tool.poetry.group.dev.dependencies]
-pyright = "^1.1.408"
+pyright = "^1.1.404"
 pytest = "^8.4.1"
-pytest-asyncio = "^1.3.0"
+pytest-asyncio = "^1.1.0"
-pytest-mock = "^3.15.1"
+pytest-mock = "^3.14.1"
 pytest-cov = "^6.2.1"
-ruff = "^0.15.0"
+ruff = "^0.12.11"
 [build-system]
 requires = ["poetry-core"]
--- a/autogpt_platform/backend/backend/api/features/chat/db.py
+++ b/autogpt_platform/backend/backend/api/features/chat/db.py
@@ -45,7 +45,10 @@ async def create_chat_session(
        successfulAgentRuns=SafeJson({}),
        successfulAgentSchedules=SafeJson({}),
    )
-    return await PrismaChatSession.prisma().create(data=data)
+    return await PrismaChatSession.prisma().create(
        data=data,
        include={"Messages": True},
    )
 async def update_chat_session(
--- a/autogpt_platform/backend/backend/api/features/chat/routes.py
+++ b/autogpt_platform/backend/backend/api/features/chat/routes.py
@@ -266,38 +266,12 @@ async def stream_chat_post(
    """
    import asyncio
    import time
    stream_start_time = time.perf_counter()
    # Base log metadata (task_id added after creation)
    log_meta = {"component": "ChatStream", "session_id": session_id}
    if user_id:
        log_meta["user_id"] = user_id
    logger.info(
        f"[TIMING] stream_chat_post STARTED, session={session_id}, "
        f"user={user_id}, message_len={len(request.message)}",
        extra={"json_fields": log_meta},
    )
    session = await _validate_and_get_session(session_id, user_id)
    logger.info(
        f"[TIMING] session validated in {(time.perf_counter() - stream_start_time)*1000:.1f}ms",
        extra={
            "json_fields": {
                **log_meta,
                "duration_ms": (time.perf_counter() - stream_start_time) * 1000,
            }
        },
    )
    # Create a task in the stream registry for reconnection support
    task_id = str(uuid_module.uuid4())
    operation_id = str(uuid_module.uuid4())
    log_meta["task_id"] = task_id
    task_create_start = time.perf_counter()
    await stream_registry.create_task(
        task_id=task_id,
        session_id=session_id,
@@ -306,46 +280,14 @@ async def stream_chat_post(
        tool_name="chat",
        operation_id=operation_id,
    )
    logger.info(
        f"[TIMING] create_task completed in {(time.perf_counter() - task_create_start)*1000:.1f}ms",
        extra={
            "json_fields": {
                **log_meta,
                "duration_ms": (time.perf_counter() - task_create_start) * 1000,
            }
        },
    )
    # Background task that runs the AI generation independently of SSE connection
    async def run_ai_generation():
        import time as time_module
        gen_start_time = time_module.perf_counter()
        logger.info(
            f"[TIMING] run_ai_generation STARTED, task={task_id}, session={session_id}, user={user_id}",
            extra={"json_fields": log_meta},
        )
        first_chunk_time, ttfc = None, None
        chunk_count = 0
        try:
            # Emit a start event with task_id for reconnection
            start_chunk = StreamStart(messageId=task_id, taskId=task_id)
            await stream_registry.publish_chunk(task_id, start_chunk)
            logger.info(
                f"[TIMING] StreamStart published at {(time_module.perf_counter() - gen_start_time)*1000:.1f}ms",
                extra={
                    "json_fields": {
                        **log_meta,
                        "elapsed_ms": (time_module.perf_counter() - gen_start_time)
                        * 1000,
                    }
                },
            )
            logger.info(
                "[TIMING] Calling stream_chat_completion",
                extra={"json_fields": log_meta},
            )
            async for chunk in chat_service.stream_chat_completion(
                session_id,
                request.message,
@@ -354,202 +296,54 @@ async def stream_chat_post(
                session=session,  # Pass pre-fetched session to avoid double-fetch
                context=request.context,
            ):
                chunk_count += 1
                if first_chunk_time is None:
                    first_chunk_time = time_module.perf_counter()
                    ttfc = first_chunk_time - gen_start_time
                    logger.info(
                        f"[TIMING] FIRST AI CHUNK at {ttfc:.2f}s, type={type(chunk).__name__}",
                        extra={
                            "json_fields": {
                                **log_meta,
                                "chunk_type": type(chunk).__name__,
                                "time_to_first_chunk_ms": ttfc * 1000,
                            }
                        },
                    )
                # Write to Redis (subscribers will receive via XREAD)
                await stream_registry.publish_chunk(task_id, chunk)
-            gen_end_time = time_module.perf_counter()
+            # Mark task as completed
            total_time = (gen_end_time - gen_start_time) * 1000
            logger.info(
                f"[TIMING] run_ai_generation FINISHED in {total_time/1000:.1f}s; "
                f"task={task_id}, session={session_id}, "
                f"ttfc={ttfc or -1:.2f}s, n_chunks={chunk_count}",
                extra={
                    "json_fields": {
                        **log_meta,
                        "total_time_ms": total_time,
                        "time_to_first_chunk_ms": (
                            ttfc * 1000 if ttfc is not None else None
                        ),
                        "n_chunks": chunk_count,
                    }
                },
            )
            await stream_registry.mark_task_completed(task_id, "completed")
        except Exception as e:
            elapsed = time_module.perf_counter() - gen_start_time
            logger.error(
-                f"[TIMING] run_ai_generation ERROR after {elapsed:.2f}s: {e}",
+                f"Error in background AI generation for session {session_id}: {e}"
                extra={
                    "json_fields": {
                        **log_meta,
                        "elapsed_ms": elapsed * 1000,
                        "error": str(e),
                    }
                },
            )
            await stream_registry.mark_task_completed(task_id, "failed")
    # Start the AI generation in a background task
    bg_task = asyncio.create_task(run_ai_generation())
    await stream_registry.set_task_asyncio_task(task_id, bg_task)
    setup_time = (time.perf_counter() - stream_start_time) * 1000
    logger.info(
        f"[TIMING] Background task started, setup={setup_time:.1f}ms",
        extra={"json_fields": {**log_meta, "setup_time_ms": setup_time}},
    )
    # SSE endpoint that subscribes to the task's stream
    async def event_generator() -> AsyncGenerator[str, None]:
        import time as time_module
        event_gen_start = time_module.perf_counter()
        logger.info(
            f"[TIMING] event_generator STARTED, task={task_id}, session={session_id}, "
            f"user={user_id}",
            extra={"json_fields": log_meta},
        )
        subscriber_queue = None
        first_chunk_yielded = False
        chunks_yielded = 0
        try:
            # Subscribe to the task stream (this replays existing messages + live updates)
            subscribe_start = time_module.perf_counter()
            logger.info(
                "[TIMING] Calling subscribe_to_task",
                extra={"json_fields": log_meta},
            )
            subscriber_queue = await stream_registry.subscribe_to_task(
                task_id=task_id,
                user_id=user_id,
                last_message_id="0-0",  # Get all messages from the beginning
            )
            subscribe_time = (time_module.perf_counter() - subscribe_start) * 1000
            logger.info(
                f"[TIMING] subscribe_to_task completed in {subscribe_time:.1f}ms, "
                f"queue_ok={subscriber_queue is not None}",
                extra={
                    "json_fields": {
                        **log_meta,
                        "duration_ms": subscribe_time,
                        "queue_obtained": subscriber_queue is not None,
                    }
                },
            )
            if subscriber_queue is None:
                logger.info(
                    "[TIMING] subscriber_queue is None, yielding finish",
                    extra={"json_fields": log_meta},
                )
                yield StreamFinish().to_sse()
                yield "data: [DONE]\n\n"
                return
            # Read from the subscriber queue and yield to SSE
            logger.info(
                "[TIMING] Starting to read from subscriber_queue",
                extra={"json_fields": log_meta},
            )
            while True:
                try:
                    queue_wait_start = time_module.perf_counter()
                    chunk = await asyncio.wait_for(subscriber_queue.get(), timeout=30.0)
                    queue_wait_time = (
                        time_module.perf_counter() - queue_wait_start
                    ) * 1000
                    chunks_yielded += 1
                    if not first_chunk_yielded:
                        first_chunk_yielded = True
                        elapsed = time_module.perf_counter() - event_gen_start
                        logger.info(
                            f"[TIMING] FIRST CHUNK from queue at {elapsed:.2f}s, "
                            f"type={type(chunk).__name__}, "
                            f"wait={queue_wait_time:.1f}ms",
                            extra={
                                "json_fields": {
                                    **log_meta,
                                    "chunk_type": type(chunk).__name__,
                                    "elapsed_ms": elapsed * 1000,
                                    "queue_wait_ms": queue_wait_time,
                                }
                            },
                        )
                    elif chunks_yielded % 50 == 0:
                        logger.info(
                            f"[TIMING] Chunk #{chunks_yielded}, "
                            f"type={type(chunk).__name__}",
                            extra={
                                "json_fields": {
                                    **log_meta,
                                    "chunk_number": chunks_yielded,
                                    "chunk_type": type(chunk).__name__,
                                }
                            },
                        )
                    yield chunk.to_sse()
                    # Check for finish signal
                    if isinstance(chunk, StreamFinish):
                        total_time = time_module.perf_counter() - event_gen_start
                        logger.info(
                            f"[TIMING] StreamFinish received in {total_time:.2f}s; "
                            f"n_chunks={chunks_yielded}",
                            extra={
                                "json_fields": {
                                    **log_meta,
                                    "chunks_yielded": chunks_yielded,
                                    "total_time_ms": total_time * 1000,
                                }
                            },
                        )
                        break
                except asyncio.TimeoutError:
                    # Send heartbeat to keep connection alive
                    logger.info(
                        f"[TIMING] Heartbeat timeout, chunks_so_far={chunks_yielded}",
                        extra={
                            "json_fields": {**log_meta, "chunks_so_far": chunks_yielded}
                        },
                    )
                    yield StreamHeartbeat().to_sse()
        except GeneratorExit:
            logger.info(
                f"[TIMING] GeneratorExit (client disconnected), chunks={chunks_yielded}",
                extra={
                    "json_fields": {
                        **log_meta,
                        "chunks_yielded": chunks_yielded,
                        "reason": "client_disconnect",
                    }
                },
            )
            pass  # Client disconnected - background task continues
        except Exception as e:
-            elapsed = (time_module.perf_counter() - event_gen_start) * 1000
+            logger.error(f"Error in SSE stream for task {task_id}: {e}")
            logger.error(
                f"[TIMING] event_generator ERROR after {elapsed:.1f}ms: {e}",
                extra={
                    "json_fields": {**log_meta, "elapsed_ms": elapsed, "error": str(e)}
                },
            )
        finally:
            # Unsubscribe when client disconnects or stream ends to prevent resource leak
            if subscriber_queue is not None:
@@ -563,18 +357,6 @@ async def stream_chat_post(
                        exc_info=True,
                    )
            # AI SDK protocol termination - always yield even if unsubscribe fails
            total_time = time_module.perf_counter() - event_gen_start
            logger.info(
                f"[TIMING] event_generator FINISHED in {total_time:.2f}s; "
                f"task={task_id}, session={session_id}, n_chunks={chunks_yielded}",
                extra={
                    "json_fields": {
                        **log_meta,
                        "total_time_ms": total_time * 1000,
                        "chunks_yielded": chunks_yielded,
                    }
                },
            )
            yield "data: [DONE]\n\n"
    return StreamingResponse(
@@ -643,7 +425,7 @@ async def stream_chat_get(
            "Chat stream completed",
            extra={
                "session_id": session_id,
-                "n_chunks": chunk_count,
+                "chunk_count": chunk_count,
                "first_chunk_type": first_chunk_type,
            },
        )
--- a/autogpt_platform/backend/backend/api/features/chat/service.py
+++ b/autogpt_platform/backend/backend/api/features/chat/service.py
@@ -371,45 +371,21 @@ async def stream_chat_completion(
        ValueError: If max_context_messages is exceeded
    """
    completion_start = time.monotonic()
    # Build log metadata for structured logging
    log_meta = {"component": "ChatService", "session_id": session_id}
    if user_id:
        log_meta["user_id"] = user_id
    logger.info(
-        f"[TIMING] stream_chat_completion STARTED, session={session_id}, user={user_id}, "
+        f"Streaming chat completion for session {session_id} for message {message} and user id {user_id}. Message is user message: {is_user_message}"
        f"message_len={len(message) if message else 0}, is_user={is_user_message}",
        extra={
            "json_fields": {
                **log_meta,
                "message_len": len(message) if message else 0,
                "is_user_message": is_user_message,
            }
        },
    )
    # Only fetch from Redis if session not provided (initial call)
    if session is None:
        fetch_start = time.monotonic()
        session = await get_chat_session(session_id, user_id)
        fetch_time = (time.monotonic() - fetch_start) * 1000
        logger.info(
-            f"[TIMING] get_chat_session took {fetch_time:.1f}ms, "
+            f"Fetched session from Redis: {session.session_id if session else 'None'}, "
-            f"n_messages={len(session.messages) if session else 0}",
+            f"message_count={len(session.messages) if session else 0}"
            extra={
                "json_fields": {
                    **log_meta,
                    "duration_ms": fetch_time,
                    "n_messages": len(session.messages) if session else 0,
                }
            },
        )
    else:
        logger.info(
-            f"[TIMING] Using provided session, messages={len(session.messages)}",
+            f"Using provided session object: {session.session_id}, "
-            extra={"json_fields": {**log_meta, "n_messages": len(session.messages)}},
+            f"message_count={len(session.messages)}"
        )
    if not session:
@@ -430,25 +406,17 @@ async def stream_chat_completion(
        # Track user message in PostHog
        if is_user_message:
            posthog_start = time.monotonic()
            track_user_message(
                user_id=user_id,
                session_id=session_id,
                message_length=len(message),
            )
            posthog_time = (time.monotonic() - posthog_start) * 1000
            logger.info(
                f"[TIMING] track_user_message took {posthog_time:.1f}ms",
                extra={"json_fields": {**log_meta, "duration_ms": posthog_time}},
            )
    upsert_start = time.monotonic()
    session = await upsert_chat_session(session)
    upsert_time = (time.monotonic() - upsert_start) * 1000
    logger.info(
-        f"[TIMING] upsert_chat_session took {upsert_time:.1f}ms",
+        f"Upserting session: {session.session_id} with user id {session.user_id}, "
-        extra={"json_fields": {**log_meta, "duration_ms": upsert_time}},
+        f"message_count={len(session.messages)}"
    )
    session = await upsert_chat_session(session)
    assert session, "Session not found"
    # Generate title for new sessions on first user message (non-blocking)
@@ -486,13 +454,7 @@ async def stream_chat_completion(
            asyncio.create_task(_update_title())
    # Build system prompt with business understanding
    prompt_start = time.monotonic()
    system_prompt, understanding = await _build_system_prompt(user_id)
    prompt_time = (time.monotonic() - prompt_start) * 1000
    logger.info(
        f"[TIMING] _build_system_prompt took {prompt_time:.1f}ms",
        extra={"json_fields": {**log_meta, "duration_ms": prompt_time}},
    )
    # Initialize variables for streaming
    assistant_response = ChatMessage(
@@ -521,18 +483,9 @@ async def stream_chat_completion(
    text_block_id = str(uuid_module.uuid4())
    # Yield message start
    setup_time = (time.monotonic() - completion_start) * 1000
    logger.info(
        f"[TIMING] Setup complete, yielding StreamStart at {setup_time:.1f}ms",
        extra={"json_fields": {**log_meta, "setup_time_ms": setup_time}},
    )
    yield StreamStart(messageId=message_id)
    try:
        logger.info(
            "[TIMING] Calling _stream_chat_chunks",
            extra={"json_fields": log_meta},
        )
        async for chunk in _stream_chat_chunks(
            session=session,
            tools=tools,
@@ -940,21 +893,9 @@ async def _stream_chat_chunks(
        SSE formatted JSON response objects
    """
    import time as time_module
    stream_chunks_start = time_module.perf_counter()
    model = config.model
-    # Build log metadata for structured logging
+    logger.info("Starting pure chat stream")
    log_meta = {"component": "ChatService", "session_id": session.session_id}
    if session.user_id:
        log_meta["user_id"] = session.user_id
    logger.info(
        f"[TIMING] _stream_chat_chunks STARTED, session={session.session_id}, "
        f"user={session.user_id}, n_messages={len(session.messages)}",
        extra={"json_fields": {**log_meta, "n_messages": len(session.messages)}},
    )
    messages = session.to_openai_messages()
    if system_prompt:
@@ -965,18 +906,12 @@ async def _stream_chat_chunks(
        messages = [system_message] + messages
    # Apply context window management
    context_start = time_module.perf_counter()
    context_result = await _manage_context_window(
        messages=messages,
        model=model,
        api_key=config.api_key,
        base_url=config.base_url,
    )
    context_time = (time_module.perf_counter() - context_start) * 1000
    logger.info(
        f"[TIMING] _manage_context_window took {context_time:.1f}ms",
        extra={"json_fields": {**log_meta, "duration_ms": context_time}},
    )
    if context_result.error:
        if "System prompt dropped" in context_result.error:
@@ -1011,19 +946,9 @@ async def _stream_chat_chunks(
        while retry_count <= MAX_RETRIES:
            try:
                elapsed = (time_module.perf_counter() - stream_chunks_start) * 1000
                retry_info = (
                    f" (retry {retry_count}/{MAX_RETRIES})" if retry_count > 0 else ""
                )
                logger.info(
-                    f"[TIMING] Creating OpenAI stream at {elapsed:.1f}ms{retry_info}",
+                    f"Creating OpenAI chat completion stream..."
-                    extra={
+                    f"{f' (retry {retry_count}/{MAX_RETRIES})' if retry_count > 0 else ''}"
                        "json_fields": {
                            **log_meta,
                            "elapsed_ms": elapsed,
                            "retry_count": retry_count,
                        }
                    },
                )
                # Build extra_body for OpenRouter tracing and PostHog analytics
@@ -1040,7 +965,6 @@ async def _stream_chat_chunks(
                        :128
                    ]  # OpenRouter limit
                api_call_start = time_module.perf_counter()
                stream = await client.chat.completions.create(
                    model=model,
                    messages=cast(list[ChatCompletionMessageParam], messages),
@@ -1050,11 +974,6 @@ async def _stream_chat_chunks(
                    stream_options=ChatCompletionStreamOptionsParam(include_usage=True),
                    extra_body=extra_body,
                )
                api_init_time = (time_module.perf_counter() - api_call_start) * 1000
                logger.info(
                    f"[TIMING] OpenAI stream object returned in {api_init_time:.1f}ms",
                    extra={"json_fields": {**log_meta, "duration_ms": api_init_time}},
                )
                # Variables to accumulate tool calls
                tool_calls: list[dict[str, Any]] = []
@@ -1065,13 +984,10 @@ async def _stream_chat_chunks(
                # Track if we've started the text block
                text_started = False
                first_content_chunk = True
                chunk_count = 0
                # Process the stream
                chunk: ChatCompletionChunk
                async for chunk in stream:
                    chunk_count += 1
                    if chunk.usage:
                        yield StreamUsage(
                            promptTokens=chunk.usage.prompt_tokens,
@@ -1094,23 +1010,6 @@ async def _stream_chat_chunks(
                            if not text_started and text_block_id:
                                yield StreamTextStart(id=text_block_id)
                                text_started = True
                            # Log timing for first content chunk
                            if first_content_chunk:
                                first_content_chunk = False
                                ttfc = (
                                    time_module.perf_counter() - api_call_start
                                ) * 1000
                                logger.info(
                                    f"[TIMING] FIRST CONTENT CHUNK at {ttfc:.1f}ms "
                                    f"(since API call), n_chunks={chunk_count}",
                                    extra={
                                        "json_fields": {
                                            **log_meta,
                                            "time_to_first_chunk_ms": ttfc,
                                            "n_chunks": chunk_count,
                                        }
                                    },
                                )
                            # Stream the text delta
                            text_response = StreamTextDelta(
                                id=text_block_id or "",
@@ -1167,21 +1066,7 @@ async def _stream_chat_chunks(
                                        toolName=tool_calls[idx]["function"]["name"],
                                    )
                                    emitted_start_for_idx.add(idx)
-                stream_duration = time_module.perf_counter() - api_call_start
+                logger.info(f"Stream complete. Finish reason: {finish_reason}")
                logger.info(
                    f"[TIMING] OpenAI stream COMPLETE, finish_reason={finish_reason}, "
                    f"duration={stream_duration:.2f}s, "
                    f"n_chunks={chunk_count}, n_tool_calls={len(tool_calls)}",
                    extra={
                        "json_fields": {
                            **log_meta,
                            "stream_duration_ms": stream_duration * 1000,
                            "finish_reason": finish_reason,
                            "n_chunks": chunk_count,
                            "n_tool_calls": len(tool_calls),
                        }
                    },
                )
                # Yield all accumulated tool calls after the stream is complete
                # This ensures all tool call arguments have been fully received
@@ -1201,12 +1086,6 @@ async def _stream_chat_chunks(
                        # Re-raise to trigger retry logic in the parent function
                        raise
                total_time = (time_module.perf_counter() - stream_chunks_start) * 1000
                logger.info(
                    f"[TIMING] _stream_chat_chunks COMPLETED in {total_time/1000:.1f}s; "
                    f"session={session.session_id}, user={session.user_id}",
                    extra={"json_fields": {**log_meta, "total_time_ms": total_time}},
                )
                yield StreamFinish()
                return
            except Exception as e:
--- a/autogpt_platform/backend/backend/api/features/chat/stream_registry.py
+++ b/autogpt_platform/backend/backend/api/features/chat/stream_registry.py
@@ -104,24 +104,6 @@ async def create_task(
    Returns:
        The created ActiveTask instance (metadata only)
    """
    import time
    start_time = time.perf_counter()
    # Build log metadata for structured logging
    log_meta = {
        "component": "StreamRegistry",
        "task_id": task_id,
        "session_id": session_id,
    }
    if user_id:
        log_meta["user_id"] = user_id
    logger.info(
        f"[TIMING] create_task STARTED, task={task_id}, session={session_id}, user={user_id}",
        extra={"json_fields": log_meta},
    )
    task = ActiveTask(
        task_id=task_id,
        session_id=session_id,
@@ -132,18 +114,10 @@ async def create_task(
    )
    # Store metadata in Redis
    redis_start = time.perf_counter()
    redis = await get_redis_async()
    redis_time = (time.perf_counter() - redis_start) * 1000
    logger.info(
        f"[TIMING] get_redis_async took {redis_time:.1f}ms",
        extra={"json_fields": {**log_meta, "duration_ms": redis_time}},
    )
    meta_key = _get_task_meta_key(task_id)
    op_key = _get_operation_mapping_key(operation_id)
    hset_start = time.perf_counter()
    await redis.hset(  # type: ignore[misc]
        meta_key,
        mapping={
@@ -157,22 +131,12 @@ async def create_task(
            "created_at": task.created_at.isoformat(),
        },
    )
    hset_time = (time.perf_counter() - hset_start) * 1000
    logger.info(
        f"[TIMING] redis.hset took {hset_time:.1f}ms",
        extra={"json_fields": {**log_meta, "duration_ms": hset_time}},
    )
    await redis.expire(meta_key, config.stream_ttl)
    # Create operation_id -> task_id mapping for webhook lookups
    await redis.set(op_key, task_id, ex=config.stream_ttl)
-    total_time = (time.perf_counter() - start_time) * 1000
+    logger.debug(f"Created task {task_id} for session {session_id}")
    logger.info(
        f"[TIMING] create_task COMPLETED in {total_time:.1f}ms; task={task_id}, session={session_id}",
        extra={"json_fields": {**log_meta, "total_time_ms": total_time}},
    )
    return task
@@ -192,60 +156,26 @@ async def publish_chunk(
    Returns:
        The Redis Stream message ID
    """
    import time
    start_time = time.perf_counter()
    chunk_type = type(chunk).__name__
    chunk_json = chunk.model_dump_json()
    message_id = "0-0"
    # Build log metadata
    log_meta = {
        "component": "StreamRegistry",
        "task_id": task_id,
        "chunk_type": chunk_type,
    }
    try:
        redis = await get_redis_async()
        stream_key = _get_task_stream_key(task_id)
        # Write to Redis Stream for persistence and real-time delivery
        xadd_start = time.perf_counter()
        raw_id = await redis.xadd(
            stream_key,
            {"data": chunk_json},
            maxlen=config.stream_max_length,
        )
        xadd_time = (time.perf_counter() - xadd_start) * 1000
        message_id = raw_id if isinstance(raw_id, str) else raw_id.decode()
        # Set TTL on stream to match task metadata TTL
        await redis.expire(stream_key, config.stream_ttl)
        total_time = (time.perf_counter() - start_time) * 1000
        # Only log timing for significant chunks or slow operations
        if (
            chunk_type
            in ("StreamStart", "StreamFinish", "StreamTextStart", "StreamTextEnd")
            or total_time > 50
        ):
            logger.info(
                f"[TIMING] publish_chunk {chunk_type} in {total_time:.1f}ms (xadd={xadd_time:.1f}ms)",
                extra={
                    "json_fields": {
                        **log_meta,
                        "total_time_ms": total_time,
                        "xadd_time_ms": xadd_time,
                        "message_id": message_id,
                    }
                },
            )
    except Exception as e:
        elapsed = (time.perf_counter() - start_time) * 1000
        logger.error(
-            f"[TIMING] Failed to publish chunk {chunk_type} after {elapsed:.1f}ms: {e}",
+            f"Failed to publish chunk for task {task_id}: {e}",
            extra={"json_fields": {**log_meta, "elapsed_ms": elapsed, "error": str(e)}},
            exc_info=True,
        )
@@ -270,61 +200,24 @@ async def subscribe_to_task(
        An asyncio Queue that will receive stream chunks, or None if task not found
        or user doesn't have access
    """
    import time
    start_time = time.perf_counter()
    # Build log metadata
    log_meta = {"component": "StreamRegistry", "task_id": task_id}
    if user_id:
        log_meta["user_id"] = user_id
    logger.info(
        f"[TIMING] subscribe_to_task STARTED, task={task_id}, user={user_id}, last_msg={last_message_id}",
        extra={"json_fields": {**log_meta, "last_message_id": last_message_id}},
    )
    redis_start = time.perf_counter()
    redis = await get_redis_async()
    meta_key = _get_task_meta_key(task_id)
    meta: dict[Any, Any] = await redis.hgetall(meta_key)  # type: ignore[misc]
    hgetall_time = (time.perf_counter() - redis_start) * 1000
    logger.info(
        f"[TIMING] Redis hgetall took {hgetall_time:.1f}ms",
        extra={"json_fields": {**log_meta, "duration_ms": hgetall_time}},
    )
    if not meta:
-        elapsed = (time.perf_counter() - start_time) * 1000
+        logger.debug(f"Task {task_id} not found in Redis")
        logger.info(
            f"[TIMING] Task not found in Redis after {elapsed:.1f}ms",
            extra={
                "json_fields": {
                    **log_meta,
                    "elapsed_ms": elapsed,
                    "reason": "task_not_found",
                }
            },
        )
        return None
    # Note: Redis client uses decode_responses=True, so keys are strings
    task_status = meta.get("status", "")
    task_user_id = meta.get("user_id", "") or None
    log_meta["session_id"] = meta.get("session_id", "")
    # Validate ownership - if task has an owner, requester must match
    if task_user_id:
        if user_id != task_user_id:
            logger.warning(
-                f"[TIMING] Access denied: user {user_id} tried to access task owned by {task_user_id}",
+                f"User {user_id} denied access to task {task_id} "
-                extra={
+                f"owned by {task_user_id}"
                    "json_fields": {
                        **log_meta,
                        "task_owner": task_user_id,
                        "reason": "access_denied",
                    }
                },
            )
            return None
@@ -332,19 +225,7 @@ async def subscribe_to_task(
    stream_key = _get_task_stream_key(task_id)
    # Step 1: Replay messages from Redis Stream
    xread_start = time.perf_counter()
    messages = await redis.xread({stream_key: last_message_id}, block=0, count=1000)
    xread_time = (time.perf_counter() - xread_start) * 1000
    logger.info(
        f"[TIMING] Redis xread (replay) took {xread_time:.1f}ms, status={task_status}",
        extra={
            "json_fields": {
                **log_meta,
                "duration_ms": xread_time,
                "task_status": task_status,
            }
        },
    )
    replayed_count = 0
    replay_last_id = last_message_id
@@ -363,48 +244,19 @@ async def subscribe_to_task(
                    except Exception as e:
                        logger.warning(f"Failed to replay message: {e}")
-    logger.info(
+    logger.debug(f"Task {task_id}: replayed {replayed_count} messages")
        f"[TIMING] Replayed {replayed_count} messages, last_id={replay_last_id}",
        extra={
            "json_fields": {
                **log_meta,
                "n_messages_replayed": replayed_count,
                "replay_last_id": replay_last_id,
            }
        },
    )
    # Step 2: If task is still running, start stream listener for live updates
    if task_status == "running":
        logger.info(
            "[TIMING] Task still running, starting _stream_listener",
            extra={"json_fields": {**log_meta, "task_status": task_status}},
        )
        listener_task = asyncio.create_task(
-            _stream_listener(task_id, subscriber_queue, replay_last_id, log_meta)
+            _stream_listener(task_id, subscriber_queue, replay_last_id)
        )
        # Track listener task for cleanup on unsubscribe
        _listener_tasks[id(subscriber_queue)] = (task_id, listener_task)
    else:
        # Task is completed/failed - add finish marker
        logger.info(
            f"[TIMING] Task already {task_status}, adding StreamFinish",
            extra={"json_fields": {**log_meta, "task_status": task_status}},
        )
        await subscriber_queue.put(StreamFinish())
    total_time = (time.perf_counter() - start_time) * 1000
    logger.info(
        f"[TIMING] subscribe_to_task COMPLETED in {total_time:.1f}ms; task={task_id}, "
        f"n_messages_replayed={replayed_count}",
        extra={
            "json_fields": {
                **log_meta,
                "total_time_ms": total_time,
                "n_messages_replayed": replayed_count,
            }
        },
    )
    return subscriber_queue
@@ -412,7 +264,6 @@ async def _stream_listener(
    task_id: str,
    subscriber_queue: asyncio.Queue[StreamBaseResponse],
    last_replayed_id: str,
    log_meta: dict | None = None,
 ) -> None:
    """Listen to Redis Stream for new messages using blocking XREAD.
@@ -423,27 +274,10 @@ async def _stream_listener(
        task_id: Task ID to listen for
        subscriber_queue: Queue to deliver messages to
        last_replayed_id: Last message ID from replay (continue from here)
        log_meta: Structured logging metadata
    """
    import time
    start_time = time.perf_counter()
    # Use provided log_meta or build minimal one
    if log_meta is None:
        log_meta = {"component": "StreamRegistry", "task_id": task_id}
    logger.info(
        f"[TIMING] _stream_listener STARTED, task={task_id}, last_id={last_replayed_id}",
        extra={"json_fields": {**log_meta, "last_replayed_id": last_replayed_id}},
    )
    queue_id = id(subscriber_queue)
    # Track the last successfully delivered message ID for recovery hints
    last_delivered_id = last_replayed_id
    messages_delivered = 0
    first_message_time = None
    xread_count = 0
    try:
        redis = await get_redis_async()
@@ -453,39 +287,9 @@ async def _stream_listener(
        while True:
            # Block for up to 30 seconds waiting for new messages
            # This allows periodic checking if task is still running
            xread_start = time.perf_counter()
            xread_count += 1
            messages = await redis.xread(
                {stream_key: current_id}, block=30000, count=100
            )
            xread_time = (time.perf_counter() - xread_start) * 1000
            if messages:
                msg_count = sum(len(msgs) for _, msgs in messages)
                logger.info(
                    f"[TIMING] xread #{xread_count} returned {msg_count} messages in {xread_time:.1f}ms",
                    extra={
                        "json_fields": {
                            **log_meta,
                            "xread_count": xread_count,
                            "n_messages": msg_count,
                            "duration_ms": xread_time,
                        }
                    },
                )
            elif xread_time > 1000:
                # Only log timeouts (30s blocking)
                logger.info(
                    f"[TIMING] xread #{xread_count} timeout after {xread_time:.1f}ms",
                    extra={
                        "json_fields": {
                            **log_meta,
                            "xread_count": xread_count,
                            "duration_ms": xread_time,
                            "reason": "timeout",
                        }
                    },
                )
            if not messages:
                # Timeout - check if task is still running
@@ -522,30 +326,10 @@ async def _stream_listener(
                                )
                                # Update last delivered ID on successful delivery
                                last_delivered_id = current_id
                                messages_delivered += 1
                                if first_message_time is None:
                                    first_message_time = time.perf_counter()
                                    elapsed = (first_message_time - start_time) * 1000
                                    logger.info(
                                        f"[TIMING] FIRST live message at {elapsed:.1f}ms, type={type(chunk).__name__}",
                                        extra={
                                            "json_fields": {
                                                **log_meta,
                                                "elapsed_ms": elapsed,
                                                "chunk_type": type(chunk).__name__,
                                            }
                                        },
                                    )
                            except asyncio.TimeoutError:
                                logger.warning(
-                                    f"[TIMING] Subscriber queue full, delivery timed out after {QUEUE_PUT_TIMEOUT}s",
+                                    f"Subscriber queue full for task {task_id}, "
-                                    extra={
+                                    f"message delivery timed out after {QUEUE_PUT_TIMEOUT}s"
                                        "json_fields": {
                                            **log_meta,
                                            "timeout_s": QUEUE_PUT_TIMEOUT,
                                            "reason": "queue_full",
                                        }
                                    },
                                )
                                # Send overflow error with recovery info
                                try:
@@ -567,44 +351,15 @@ async def _stream_listener(
                            # Stop listening on finish
                            if isinstance(chunk, StreamFinish):
                                total_time = (time.perf_counter() - start_time) * 1000
                                logger.info(
                                    f"[TIMING] StreamFinish received in {total_time/1000:.1f}s; delivered={messages_delivered}",
                                    extra={
                                        "json_fields": {
                                            **log_meta,
                                            "total_time_ms": total_time,
                                            "messages_delivered": messages_delivered,
                                        }
                                    },
                                )
                                return
                    except Exception as e:
-                        logger.warning(
+                        logger.warning(f"Error processing stream message: {e}")
                            f"Error processing stream message: {e}",
                            extra={"json_fields": {**log_meta, "error": str(e)}},
                        )
    except asyncio.CancelledError:
-        elapsed = (time.perf_counter() - start_time) * 1000
+        logger.debug(f"Stream listener cancelled for task {task_id}")
        logger.info(
            f"[TIMING] _stream_listener CANCELLED after {elapsed:.1f}ms, delivered={messages_delivered}",
            extra={
                "json_fields": {
                    **log_meta,
                    "elapsed_ms": elapsed,
                    "messages_delivered": messages_delivered,
                    "reason": "cancelled",
                }
            },
        )
        raise  # Re-raise to propagate cancellation
    except Exception as e:
-        elapsed = (time.perf_counter() - start_time) * 1000
+        logger.error(f"Stream listener error for task {task_id}: {e}")
        logger.error(
            f"[TIMING] _stream_listener ERROR after {elapsed:.1f}ms: {e}",
            extra={"json_fields": {**log_meta, "elapsed_ms": elapsed, "error": str(e)}},
        )
        # On error, send finish to unblock subscriber
        try:
            await asyncio.wait_for(
@@ -613,24 +368,10 @@ async def _stream_listener(
            )
        except (asyncio.TimeoutError, asyncio.QueueFull):
            logger.warning(
-                "Could not deliver finish event after error",
+                f"Could not deliver finish event for task {task_id} after error"
                extra={"json_fields": log_meta},
            )
    finally:
        # Clean up listener task mapping on exit
        total_time = (time.perf_counter() - start_time) * 1000
        logger.info(
            f"[TIMING] _stream_listener FINISHED in {total_time/1000:.1f}s; task={task_id}, "
            f"delivered={messages_delivered}, xread_count={xread_count}",
            extra={
                "json_fields": {
                    **log_meta,
                    "total_time_ms": total_time,
                    "messages_delivered": messages_delivered,
                    "xread_count": xread_count,
                }
            },
        )
        _listener_tasks.pop(queue_id, None)
--- a/autogpt_platform/backend/backend/api/features/chat/tools/find_block.py
+++ b/autogpt_platform/backend/backend/api/features/chat/tools/find_block.py
@@ -13,32 +13,10 @@ from backend.api.features.chat.tools.models import (
    NoResultsResponse,
 )
 from backend.api.features.store.hybrid_search import unified_hybrid_search
-from backend.data.block import BlockType, get_block
+from backend.data.block import get_block
 logger = logging.getLogger(__name__)
 _TARGET_RESULTS = 10
 # Over-fetch to compensate for post-hoc filtering of graph-only blocks.
 # 40 is 2x current removed; speed of query 10 vs 40 is minimial
 _OVERFETCH_PAGE_SIZE = 40
 # Block types that only work within graphs and cannot run standalone in CoPilot.
 COPILOT_EXCLUDED_BLOCK_TYPES = {
    BlockType.INPUT,  # Graph interface definition - data enters via chat, not graph inputs
    BlockType.OUTPUT,  # Graph interface definition - data exits via chat, not graph outputs
    BlockType.WEBHOOK,  # Wait for external events - would hang forever in CoPilot
    BlockType.WEBHOOK_MANUAL,  # Same as WEBHOOK
    BlockType.NOTE,  # Visual annotation only - no runtime behavior
    BlockType.HUMAN_IN_THE_LOOP,  # Pauses for human approval - CoPilot IS human-in-the-loop
    BlockType.AGENT,  # AgentExecutorBlock requires execution_context - use run_agent tool
 }
 # Specific block IDs excluded from CoPilot (STANDARD type but still require graph context)
 COPILOT_EXCLUDED_BLOCK_IDS = {
    # SmartDecisionMakerBlock - dynamically discovers downstream blocks via graph topology
    "3b191d9f-356f-482d-8238-ba04b6d18381",
 }
 class FindBlockTool(BaseTool):
    """Tool for searching available blocks."""
@@ -110,7 +88,7 @@ class FindBlockTool(BaseTool):
                query=query,
                content_types=[ContentType.BLOCK],
                page=1,
-                page_size=_OVERFETCH_PAGE_SIZE,
+                page_size=10,
            )
            if not results:
@@ -130,90 +108,60 @@ class FindBlockTool(BaseTool):
                block = get_block(block_id)
                # Skip disabled blocks
-                if not block or block.disabled:
+                if block and not block.disabled:
-                    continue
+                    # Get input/output schemas
                    input_schema = {}
                    output_schema = {}
                    try:
                        input_schema = block.input_schema.jsonschema()
                    except Exception:
                        pass
                    try:
                        output_schema = block.output_schema.jsonschema()
                    except Exception:
                        pass
-                # Skip blocks excluded from CoPilot (graph-only blocks)
+                    # Get categories from block instance
-                if (
+                    categories = []
-                    block.block_type in COPILOT_EXCLUDED_BLOCK_TYPES
+                    if hasattr(block, "categories") and block.categories:
-                    or block.id in COPILOT_EXCLUDED_BLOCK_IDS
+                        categories = [cat.value for cat in block.categories]
                ):
                    continue
-                # Get input/output schemas
+                    # Extract required inputs for easier use
-                input_schema = {}
+                    required_inputs: list[BlockInputFieldInfo] = []
-                output_schema = {}
+                    if input_schema:
-                try:
+                        properties = input_schema.get("properties", {})
-                    input_schema = block.input_schema.jsonschema()
+                        required_fields = set(input_schema.get("required", []))
-                except Exception as e:
+                        # Get credential field names to exclude from required inputs
-                    logger.debug(
+                        credentials_fields = set(
-                        "Failed to generate input schema for block %s: %s",
+                            block.input_schema.get_credentials_fields().keys()
                        block_id,
                        e,
                    )
                try:
                    output_schema = block.output_schema.jsonschema()
                except Exception as e:
                    logger.debug(
                        "Failed to generate output schema for block %s: %s",
                        block_id,
                        e,
                    )
                # Get categories from block instance
                categories = []
                if hasattr(block, "categories") and block.categories:
                    categories = [cat.value for cat in block.categories]
                # Extract required inputs for easier use
                required_inputs: list[BlockInputFieldInfo] = []
                if input_schema:
                    properties = input_schema.get("properties", {})
                    required_fields = set(input_schema.get("required", []))
                    # Get credential field names to exclude from required inputs
                    credentials_fields = set(
                        block.input_schema.get_credentials_fields().keys()
                    )
                    for field_name, field_schema in properties.items():
                        # Skip credential fields - they're handled separately
                        if field_name in credentials_fields:
                            continue
                        required_inputs.append(
                            BlockInputFieldInfo(
                                name=field_name,
                                type=field_schema.get("type", "string"),
                                description=field_schema.get("description", ""),
                                required=field_name in required_fields,
                                default=field_schema.get("default"),
                            )
                        )
-                blocks.append(
+                        for field_name, field_schema in properties.items():
-                    BlockInfoSummary(
+                            # Skip credential fields - they're handled separately
-                        id=block_id,
+                            if field_name in credentials_fields:
-                        name=block.name,
+                                continue
-                        description=block.description or "",
+
-                        categories=categories,
+                            required_inputs.append(
-                        input_schema=input_schema,
+                                BlockInputFieldInfo(
-                        output_schema=output_schema,
+                                    name=field_name,
-                        required_inputs=required_inputs,
+                                    type=field_schema.get("type", "string"),
                                    description=field_schema.get("description", ""),
                                    required=field_name in required_fields,
                                    default=field_schema.get("default"),
                                )
                            )
                    blocks.append(
                        BlockInfoSummary(
                            id=block_id,
                            name=block.name,
                            description=block.description or "",
                            categories=categories,
                            input_schema=input_schema,
                            output_schema=output_schema,
                            required_inputs=required_inputs,
                        )
                    )
                )
                if len(blocks) >= _TARGET_RESULTS:
                    break
            if blocks and len(blocks) < _TARGET_RESULTS:
                logger.debug(
                    "find_block returned %d/%d results for query '%s' "
                    "(filtered %d excluded/disabled blocks)",
                    len(blocks),
                    _TARGET_RESULTS,
                    query,
                    len(results) - len(blocks),
                )
            if not blocks:
                return NoResultsResponse(
--- a/autogpt_platform/backend/backend/api/features/chat/tools/find_block_test.py
+++ b/autogpt_platform/backend/backend/api/features/chat/tools/find_block_test.py
@@ -1,139 +0,0 @@
 """Tests for block filtering in FindBlockTool."""
 from unittest.mock import AsyncMock, MagicMock, patch
 import pytest
 from backend.api.features.chat.tools.find_block import (
    COPILOT_EXCLUDED_BLOCK_IDS,
    COPILOT_EXCLUDED_BLOCK_TYPES,
    FindBlockTool,
 )
 from backend.api.features.chat.tools.models import BlockListResponse
 from backend.data.block import BlockType
 from ._test_data import make_session
 _TEST_USER_ID = "test-user-find-block"
 def make_mock_block(
    block_id: str, name: str, block_type: BlockType, disabled: bool = False
 ):
    """Create a mock block for testing."""
    mock = MagicMock()
    mock.id = block_id
    mock.name = name
    mock.description = f"{name} description"
    mock.block_type = block_type
    mock.disabled = disabled
    mock.input_schema = MagicMock()
    mock.input_schema.jsonschema.return_value = {"properties": {}, "required": []}
    mock.input_schema.get_credentials_fields.return_value = {}
    mock.output_schema = MagicMock()
    mock.output_schema.jsonschema.return_value = {}
    mock.categories = []
    return mock
 class TestFindBlockFiltering:
    """Tests for block filtering in FindBlockTool."""
    def test_excluded_block_types_contains_expected_types(self):
        """Verify COPILOT_EXCLUDED_BLOCK_TYPES contains all graph-only types."""
        assert BlockType.INPUT in COPILOT_EXCLUDED_BLOCK_TYPES
        assert BlockType.OUTPUT in COPILOT_EXCLUDED_BLOCK_TYPES
        assert BlockType.WEBHOOK in COPILOT_EXCLUDED_BLOCK_TYPES
        assert BlockType.WEBHOOK_MANUAL in COPILOT_EXCLUDED_BLOCK_TYPES
        assert BlockType.NOTE in COPILOT_EXCLUDED_BLOCK_TYPES
        assert BlockType.HUMAN_IN_THE_LOOP in COPILOT_EXCLUDED_BLOCK_TYPES
        assert BlockType.AGENT in COPILOT_EXCLUDED_BLOCK_TYPES
    def test_excluded_block_ids_contains_smart_decision_maker(self):
        """Verify SmartDecisionMakerBlock is in COPILOT_EXCLUDED_BLOCK_IDS."""
        assert "3b191d9f-356f-482d-8238-ba04b6d18381" in COPILOT_EXCLUDED_BLOCK_IDS
    @pytest.mark.asyncio(loop_scope="session")
    async def test_excluded_block_type_filtered_from_results(self):
        """Verify blocks with excluded BlockTypes are filtered from search results."""
        session = make_session(user_id=_TEST_USER_ID)
        # Mock search returns an INPUT block (excluded) and a STANDARD block (included)
        search_results = [
            {"content_id": "input-block-id", "score": 0.9},
            {"content_id": "standard-block-id", "score": 0.8},
        ]
        input_block = make_mock_block("input-block-id", "Input Block", BlockType.INPUT)
        standard_block = make_mock_block(
            "standard-block-id", "HTTP Request", BlockType.STANDARD
        )
        def mock_get_block(block_id):
            return {
                "input-block-id": input_block,
                "standard-block-id": standard_block,
            }.get(block_id)
        with patch(
            "backend.api.features.chat.tools.find_block.unified_hybrid_search",
            new_callable=AsyncMock,
            return_value=(search_results, 2),
        ):
            with patch(
                "backend.api.features.chat.tools.find_block.get_block",
                side_effect=mock_get_block,
            ):
                tool = FindBlockTool()
                response = await tool._execute(
                    user_id=_TEST_USER_ID, session=session, query="test"
                )
        # Should only return the standard block, not the INPUT block
        assert isinstance(response, BlockListResponse)
        assert len(response.blocks) == 1
        assert response.blocks[0].id == "standard-block-id"
    @pytest.mark.asyncio(loop_scope="session")
    async def test_excluded_block_id_filtered_from_results(self):
        """Verify SmartDecisionMakerBlock is filtered from search results."""
        session = make_session(user_id=_TEST_USER_ID)
        smart_decision_id = "3b191d9f-356f-482d-8238-ba04b6d18381"
        search_results = [
            {"content_id": smart_decision_id, "score": 0.9},
            {"content_id": "normal-block-id", "score": 0.8},
        ]
        # SmartDecisionMakerBlock has STANDARD type but is excluded by ID
        smart_block = make_mock_block(
            smart_decision_id, "Smart Decision Maker", BlockType.STANDARD
        )
        normal_block = make_mock_block(
            "normal-block-id", "Normal Block", BlockType.STANDARD
        )
        def mock_get_block(block_id):
            return {
                smart_decision_id: smart_block,
                "normal-block-id": normal_block,
            }.get(block_id)
        with patch(
            "backend.api.features.chat.tools.find_block.unified_hybrid_search",
            new_callable=AsyncMock,
            return_value=(search_results, 2),
        ):
            with patch(
                "backend.api.features.chat.tools.find_block.get_block",
                side_effect=mock_get_block,
            ):
                tool = FindBlockTool()
                response = await tool._execute(
                    user_id=_TEST_USER_ID, session=session, query="decision"
                )
        # Should only return normal block, not SmartDecisionMakerBlock
        assert isinstance(response, BlockListResponse)
        assert len(response.blocks) == 1
        assert response.blocks[0].id == "normal-block-id"
--- a/autogpt_platform/backend/backend/api/features/chat/tools/helpers.py
+++ b/autogpt_platform/backend/backend/api/features/chat/tools/helpers.py
@@ -1,29 +0,0 @@
 """Shared helpers for chat tools."""
 from typing import Any
 def get_inputs_from_schema(
    input_schema: dict[str, Any],
    exclude_fields: set[str] | None = None,
 ) -> list[dict[str, Any]]:
    """Extract input field info from JSON schema."""
    if not isinstance(input_schema, dict):
        return []
    exclude = exclude_fields or set()
    properties = input_schema.get("properties", {})
    required = set(input_schema.get("required", []))
    return [
        {
            "name": name,
            "title": schema.get("title", name),
            "type": schema.get("type", "string"),
            "description": schema.get("description", ""),
            "required": name in required,
            "default": schema.get("default"),
        }
        for name, schema in properties.items()
        if name not in exclude
    ]
--- a/autogpt_platform/backend/backend/api/features/chat/tools/run_agent.py
+++ b/autogpt_platform/backend/backend/api/features/chat/tools/run_agent.py
@@ -24,7 +24,6 @@ from backend.util.timezone_utils import (
 )
 from .base import BaseTool
 from .helpers import get_inputs_from_schema
 from .models import (
    AgentDetails,
    AgentDetailsResponse,
@@ -262,7 +261,7 @@ class RunAgentTool(BaseTool):
                        ),
                        requirements={
                            "credentials": requirements_creds_list,
-                            "inputs": get_inputs_from_schema(graph.input_schema),
+                            "inputs": self._get_inputs_list(graph.input_schema),
                            "execution_modes": self._get_execution_modes(graph),
                        },
                    ),
@@ -370,6 +369,22 @@ class RunAgentTool(BaseTool):
                session_id=session_id,
            )
    def _get_inputs_list(self, input_schema: dict[str, Any]) -> list[dict[str, Any]]:
        """Extract inputs list from schema."""
        inputs_list = []
        if isinstance(input_schema, dict) and "properties" in input_schema:
            for field_name, field_schema in input_schema["properties"].items():
                inputs_list.append(
                    {
                        "name": field_name,
                        "title": field_schema.get("title", field_name),
                        "type": field_schema.get("type", "string"),
                        "description": field_schema.get("description", ""),
                        "required": field_name in input_schema.get("required", []),
                    }
                )
        return inputs_list
    def _get_execution_modes(self, graph: GraphModel) -> list[str]:
        """Get available execution modes for the graph."""
        trigger_info = graph.trigger_setup_info
@@ -383,7 +398,7 @@ class RunAgentTool(BaseTool):
        suffix: str,
    ) -> str:
        """Build a message describing available inputs for an agent."""
-        inputs_list = get_inputs_from_schema(graph.input_schema)
+        inputs_list = self._get_inputs_list(graph.input_schema)
        required_names = [i["name"] for i in inputs_list if i["required"]]
        optional_names = [i["name"] for i in inputs_list if not i["required"]]
--- a/autogpt_platform/backend/backend/api/features/chat/tools/run_block.py
+++ b/autogpt_platform/backend/backend/api/features/chat/tools/run_block.py
@@ -8,19 +8,14 @@ from typing import Any
 from pydantic_core import PydanticUndefined
 from backend.api.features.chat.model import ChatSession
-from backend.api.features.chat.tools.find_block import (
+from backend.data.block import get_block
    COPILOT_EXCLUDED_BLOCK_IDS,
    COPILOT_EXCLUDED_BLOCK_TYPES,
 )
 from backend.data.block import AnyBlockSchema, get_block
 from backend.data.execution import ExecutionContext
-from backend.data.model import CredentialsFieldInfo, CredentialsMetaInput
+from backend.data.model import CredentialsMetaInput
 from backend.data.workspace import get_or_create_workspace
 from backend.integrations.creds_manager import IntegrationCredentialsManager
 from backend.util.exceptions import BlockError
 from .base import BaseTool
 from .helpers import get_inputs_from_schema
 from .models import (
    BlockOutputResponse,
    ErrorResponse,
@@ -29,10 +24,7 @@ from .models import (
    ToolResponseBase,
    UserReadiness,
 )
-from .utils import (
+from .utils import build_missing_credentials_from_field_info
    build_missing_credentials_from_field_info,
    match_credentials_to_requirements,
 )
 logger = logging.getLogger(__name__)
@@ -81,6 +73,91 @@ class RunBlockTool(BaseTool):
    def requires_auth(self) -> bool:
        return True
    async def _check_block_credentials(
        self,
        user_id: str,
        block: Any,
        input_data: dict[str, Any] | None = None,
    ) -> tuple[dict[str, CredentialsMetaInput], list[CredentialsMetaInput]]:
        """
        Check if user has required credentials for a block.
        Args:
            user_id: User ID
            block: Block to check credentials for
            input_data: Input data for the block (used to determine provider via discriminator)
        Returns:
            tuple[matched_credentials, missing_credentials]
        """
        matched_credentials: dict[str, CredentialsMetaInput] = {}
        missing_credentials: list[CredentialsMetaInput] = []
        input_data = input_data or {}
        # Get credential field info from block's input schema
        credentials_fields_info = block.input_schema.get_credentials_fields_info()
        if not credentials_fields_info:
            return matched_credentials, missing_credentials
        # Get user's available credentials
        creds_manager = IntegrationCredentialsManager()
        available_creds = await creds_manager.store.get_all_creds(user_id)
        for field_name, field_info in credentials_fields_info.items():
            effective_field_info = field_info
            if field_info.discriminator and field_info.discriminator_mapping:
                # Get discriminator from input, falling back to schema default
                discriminator_value = input_data.get(field_info.discriminator)
                if discriminator_value is None:
                    field = block.input_schema.model_fields.get(
                        field_info.discriminator
                    )
                    if field and field.default is not PydanticUndefined:
                        discriminator_value = field.default
                if (
                    discriminator_value
                    and discriminator_value in field_info.discriminator_mapping
                ):
                    effective_field_info = field_info.discriminate(discriminator_value)
                    logger.debug(
                        f"Discriminated provider for {field_name}: "
                        f"{discriminator_value} -> {effective_field_info.provider}"
                    )
            matching_cred = next(
                (
                    cred
                    for cred in available_creds
                    if cred.provider in effective_field_info.provider
                    and cred.type in effective_field_info.supported_types
                ),
                None,
            )
            if matching_cred:
                matched_credentials[field_name] = CredentialsMetaInput(
                    id=matching_cred.id,
                    provider=matching_cred.provider,  # type: ignore
                    type=matching_cred.type,
                    title=matching_cred.title,
                )
            else:
                # Create a placeholder for the missing credential
                provider = next(iter(effective_field_info.provider), "unknown")
                cred_type = next(iter(effective_field_info.supported_types), "api_key")
                missing_credentials.append(
                    CredentialsMetaInput(
                        id=field_name,
                        provider=provider,  # type: ignore
                        type=cred_type,  # type: ignore
                        title=field_name.replace("_", " ").title(),
                    )
                )
        return matched_credentials, missing_credentials
    async def _execute(
        self,
        user_id: str | None,
@@ -135,24 +212,11 @@ class RunBlockTool(BaseTool):
                session_id=session_id,
            )
        # Check if block is excluded from CoPilot (graph-only blocks)
        if (
            block.block_type in COPILOT_EXCLUDED_BLOCK_TYPES
            or block.id in COPILOT_EXCLUDED_BLOCK_IDS
        ):
            return ErrorResponse(
                message=(
                    f"Block '{block.name}' cannot be run directly in CoPilot. "
                    "This block is designed for use within graphs only."
                ),
                session_id=session_id,
            )
        logger.info(f"Executing block {block.name} ({block_id}) for user {user_id}")
        creds_manager = IntegrationCredentialsManager()
-        matched_credentials, missing_credentials = (
+        matched_credentials, missing_credentials = await self._check_block_credentials(
-            await self._resolve_block_credentials(user_id, block, input_data)
+            user_id, block, input_data
        )
        if missing_credentials:
@@ -281,75 +345,29 @@ class RunBlockTool(BaseTool):
                session_id=session_id,
            )
-    async def _resolve_block_credentials(
+    def _get_inputs_list(self, block: Any) -> list[dict[str, Any]]:
        self,
        user_id: str,
        block: AnyBlockSchema,
        input_data: dict[str, Any] | None = None,
    ) -> tuple[dict[str, CredentialsMetaInput], list[CredentialsMetaInput]]:
        """
        Resolve credentials for a block by matching user's available credentials.
        Args:
            user_id: User ID
            block: Block to resolve credentials for
            input_data: Input data for the block (used to determine provider via discriminator)
        Returns:
            tuple of (matched_credentials, missing_credentials) - matched credentials
            are used for block execution, missing ones indicate setup requirements.
        """
        input_data = input_data or {}
        requirements = self._resolve_discriminated_credentials(block, input_data)
        if not requirements:
            return {}, []
        return await match_credentials_to_requirements(user_id, requirements)
    def _get_inputs_list(self, block: AnyBlockSchema) -> list[dict[str, Any]]:
        """Extract non-credential inputs from block schema."""
        inputs_list = []
        schema = block.input_schema.jsonschema()
        properties = schema.get("properties", {})
        required_fields = set(schema.get("required", []))
        # Get credential field names to exclude
        credentials_fields = set(block.input_schema.get_credentials_fields().keys())
        return get_inputs_from_schema(schema, exclude_fields=credentials_fields)
-    def _resolve_discriminated_credentials(
+        for field_name, field_schema in properties.items():
-        self,
+            # Skip credential fields
-        block: AnyBlockSchema,
+            if field_name in credentials_fields:
-        input_data: dict[str, Any],
+                continue
    ) -> dict[str, CredentialsFieldInfo]:
        """Resolve credential requirements, applying discriminator logic where needed."""
        credentials_fields_info = block.input_schema.get_credentials_fields_info()
        if not credentials_fields_info:
            return {}
-        resolved: dict[str, CredentialsFieldInfo] = {}
+            inputs_list.append(
                {
                    "name": field_name,
                    "title": field_schema.get("title", field_name),
                    "type": field_schema.get("type", "string"),
                    "description": field_schema.get("description", ""),
                    "required": field_name in required_fields,
                }
            )
-        for field_name, field_info in credentials_fields_info.items():
+        return inputs_list
            effective_field_info = field_info
            if field_info.discriminator and field_info.discriminator_mapping:
                discriminator_value = input_data.get(field_info.discriminator)
                if discriminator_value is None:
                    field = block.input_schema.model_fields.get(
                        field_info.discriminator
                    )
                    if field and field.default is not PydanticUndefined:
                        discriminator_value = field.default
                if (
                    discriminator_value
                    and discriminator_value in field_info.discriminator_mapping
                ):
                    effective_field_info = field_info.discriminate(discriminator_value)
                    # For host-scoped credentials, add the discriminator value
                    # (e.g., URL) so _credential_is_for_host can match it
                    effective_field_info.discriminator_values.add(discriminator_value)
                    logger.debug(
                        f"Discriminated provider for {field_name}: "
                        f"{discriminator_value} -> {effective_field_info.provider}"
                    )
            resolved[field_name] = effective_field_info
        return resolved
--- a/autogpt_platform/backend/backend/api/features/chat/tools/run_block_test.py
+++ b/autogpt_platform/backend/backend/api/features/chat/tools/run_block_test.py
@@ -1,106 +0,0 @@
 """Tests for block execution guards in RunBlockTool."""
 from unittest.mock import MagicMock, patch
 import pytest
 from backend.api.features.chat.tools.models import ErrorResponse
 from backend.api.features.chat.tools.run_block import RunBlockTool
 from backend.data.block import BlockType
 from ._test_data import make_session
 _TEST_USER_ID = "test-user-run-block"
 def make_mock_block(
    block_id: str, name: str, block_type: BlockType, disabled: bool = False
 ):
    """Create a mock block for testing."""
    mock = MagicMock()
    mock.id = block_id
    mock.name = name
    mock.block_type = block_type
    mock.disabled = disabled
    mock.input_schema = MagicMock()
    mock.input_schema.jsonschema.return_value = {"properties": {}, "required": []}
    mock.input_schema.get_credentials_fields_info.return_value = []
    return mock
 class TestRunBlockFiltering:
    """Tests for block execution guards in RunBlockTool."""
    @pytest.mark.asyncio(loop_scope="session")
    async def test_excluded_block_type_returns_error(self):
        """Attempting to execute a block with excluded BlockType returns error."""
        session = make_session(user_id=_TEST_USER_ID)
        input_block = make_mock_block("input-block-id", "Input Block", BlockType.INPUT)
        with patch(
            "backend.api.features.chat.tools.run_block.get_block",
            return_value=input_block,
        ):
            tool = RunBlockTool()
            response = await tool._execute(
                user_id=_TEST_USER_ID,
                session=session,
                block_id="input-block-id",
                input_data={},
            )
        assert isinstance(response, ErrorResponse)
        assert "cannot be run directly in CoPilot" in response.message
        assert "designed for use within graphs only" in response.message
    @pytest.mark.asyncio(loop_scope="session")
    async def test_excluded_block_id_returns_error(self):
        """Attempting to execute SmartDecisionMakerBlock returns error."""
        session = make_session(user_id=_TEST_USER_ID)
        smart_decision_id = "3b191d9f-356f-482d-8238-ba04b6d18381"
        smart_block = make_mock_block(
            smart_decision_id, "Smart Decision Maker", BlockType.STANDARD
        )
        with patch(
            "backend.api.features.chat.tools.run_block.get_block",
            return_value=smart_block,
        ):
            tool = RunBlockTool()
            response = await tool._execute(
                user_id=_TEST_USER_ID,
                session=session,
                block_id=smart_decision_id,
                input_data={},
            )
        assert isinstance(response, ErrorResponse)
        assert "cannot be run directly in CoPilot" in response.message
    @pytest.mark.asyncio(loop_scope="session")
    async def test_non_excluded_block_passes_guard(self):
        """Non-excluded blocks pass the filtering guard (may fail later for other reasons)."""
        session = make_session(user_id=_TEST_USER_ID)
        standard_block = make_mock_block(
            "standard-id", "HTTP Request", BlockType.STANDARD
        )
        with patch(
            "backend.api.features.chat.tools.run_block.get_block",
            return_value=standard_block,
        ):
            tool = RunBlockTool()
            response = await tool._execute(
                user_id=_TEST_USER_ID,
                session=session,
                block_id="standard-id",
                input_data={},
            )
        # Should NOT be an ErrorResponse about CoPilot exclusion
        # (may be other errors like missing credentials, but not the exclusion guard)
        if isinstance(response, ErrorResponse):
            assert "cannot be run directly in CoPilot" not in response.message
--- a/autogpt_platform/backend/backend/api/features/chat/tools/utils.py
+++ b/autogpt_platform/backend/backend/api/features/chat/tools/utils.py
@@ -8,7 +8,6 @@ from backend.api.features.library import model as library_model
 from backend.api.features.store import db as store_db
 from backend.data.graph import GraphModel
 from backend.data.model import (
    Credentials,
    CredentialsFieldInfo,
    CredentialsMetaInput,
    HostScopedCredentials,
@@ -224,99 +223,6 @@ async def get_or_create_library_agent(
    return library_agents[0]
 async def match_credentials_to_requirements(
    user_id: str,
    requirements: dict[str, CredentialsFieldInfo],
 ) -> tuple[dict[str, CredentialsMetaInput], list[CredentialsMetaInput]]:
    """
    Match user's credentials against a dictionary of credential requirements.
    This is the core matching logic shared by both graph and block credential matching.
    """
    matched: dict[str, CredentialsMetaInput] = {}
    missing: list[CredentialsMetaInput] = []
    if not requirements:
        return matched, missing
    available_creds = await get_user_credentials(user_id)
    for field_name, field_info in requirements.items():
        matching_cred = find_matching_credential(available_creds, field_info)
        if matching_cred:
            try:
                matched[field_name] = create_credential_meta_from_match(matching_cred)
            except Exception as e:
                logger.error(
                    f"Failed to create CredentialsMetaInput for field '{field_name}': "
                    f"provider={matching_cred.provider}, type={matching_cred.type}, "
                    f"credential_id={matching_cred.id}",
                    exc_info=True,
                )
                provider = next(iter(field_info.provider), "unknown")
                cred_type = next(iter(field_info.supported_types), "api_key")
                missing.append(
                    CredentialsMetaInput(
                        id=field_name,
                        provider=provider,  # type: ignore
                        type=cred_type,  # type: ignore
                        title=f"{field_name} (validation failed: {e})",
                    )
                )
        else:
            provider = next(iter(field_info.provider), "unknown")
            cred_type = next(iter(field_info.supported_types), "api_key")
            missing.append(
                CredentialsMetaInput(
                    id=field_name,
                    provider=provider,  # type: ignore
                    type=cred_type,  # type: ignore
                    title=field_name.replace("_", " ").title(),
                )
            )
    return matched, missing
 async def get_user_credentials(user_id: str) -> list[Credentials]:
    """Get all available credentials for a user."""
    creds_manager = IntegrationCredentialsManager()
    return await creds_manager.store.get_all_creds(user_id)
 def find_matching_credential(
    available_creds: list[Credentials],
    field_info: CredentialsFieldInfo,
 ) -> Credentials | None:
    """Find a credential that matches the required provider, type, scopes, and host."""
    for cred in available_creds:
        if cred.provider not in field_info.provider:
            continue
        if cred.type not in field_info.supported_types:
            continue
        if cred.type == "oauth2" and not _credential_has_required_scopes(
            cred, field_info
        ):
            continue
        if cred.type == "host_scoped" and not _credential_is_for_host(cred, field_info):
            continue
        return cred
    return None
 def create_credential_meta_from_match(
    matching_cred: Credentials,
 ) -> CredentialsMetaInput:
    """Create a CredentialsMetaInput from a matched credential."""
    return CredentialsMetaInput(
        id=matching_cred.id,
        provider=matching_cred.provider,  # type: ignore
        type=matching_cred.type,
        title=matching_cred.title,
    )
 async def match_user_credentials_to_graph(
    user_id: str,
    graph: GraphModel,
@@ -425,6 +331,8 @@ def _credential_has_required_scopes(
    # If no scopes are required, any credential matches
    if not requirements.required_scopes:
        return True
    # Check that credential scopes are a superset of required scopes
    return set(credential.scopes).issuperset(requirements.required_scopes)
--- a/autogpt_platform/backend/backend/api/features/store/hybrid_search.py
+++ b/autogpt_platform/backend/backend/api/features/store/hybrid_search.py
@@ -8,7 +8,6 @@ Includes BM25 reranking for improved lexical relevance.
 import logging
 import re
 import time
 from dataclasses import dataclass
 from typing import Any, Literal
@@ -363,11 +362,7 @@ async def unified_hybrid_search(
        LIMIT {limit_param} OFFSET {offset_param}
    """
-    try:
+    results = await query_raw_with_schema(sql_query, *params)
        results = await query_raw_with_schema(sql_query, *params)
    except Exception as e:
        await _log_vector_error_diagnostics(e)
        raise
    total = results[0]["total_count"] if results else 0
    # Apply BM25 reranking
@@ -691,11 +686,7 @@ async def hybrid_search(
        LIMIT {limit_param} OFFSET {offset_param}
    """
-    try:
+    results = await query_raw_with_schema(sql_query, *params)
        results = await query_raw_with_schema(sql_query, *params)
    except Exception as e:
        await _log_vector_error_diagnostics(e)
        raise
    total = results[0]["total_count"] if results else 0
@@ -727,87 +718,6 @@ async def hybrid_search_simple(
    return await hybrid_search(query=query, page=page, page_size=page_size)
 # ============================================================================
 # Diagnostics
 # ============================================================================
 # Rate limit: only log vector error diagnostics once per this interval
 _VECTOR_DIAG_INTERVAL_SECONDS = 60
 _last_vector_diag_time: float = 0
 async def _log_vector_error_diagnostics(error: Exception) -> None:
    """Log diagnostic info when 'type vector does not exist' error occurs.
    Note: Diagnostic queries use query_raw_with_schema which may run on a different
    pooled connection than the one that failed. Session-level search_path can differ,
    so these diagnostics show cluster-wide state, not necessarily the failed session.
    Includes rate limiting to avoid log spam - only logs once per minute.
    Caller should re-raise the error after calling this function.
    """
    global _last_vector_diag_time
    # Check if this is the vector type error
    error_str = str(error).lower()
    if not (
        "type" in error_str and "vector" in error_str and "does not exist" in error_str
    ):
        return
    # Rate limit: only log once per interval
    now = time.time()
    if now - _last_vector_diag_time < _VECTOR_DIAG_INTERVAL_SECONDS:
        return
    _last_vector_diag_time = now
    try:
        diagnostics: dict[str, object] = {}
        try:
            search_path_result = await query_raw_with_schema("SHOW search_path")
            diagnostics["search_path"] = search_path_result
        except Exception as e:
            diagnostics["search_path"] = f"Error: {e}"
        try:
            schema_result = await query_raw_with_schema("SELECT current_schema()")
            diagnostics["current_schema"] = schema_result
        except Exception as e:
            diagnostics["current_schema"] = f"Error: {e}"
        try:
            user_result = await query_raw_with_schema(
                "SELECT current_user, session_user, current_database()"
            )
            diagnostics["user_info"] = user_result
        except Exception as e:
            diagnostics["user_info"] = f"Error: {e}"
        try:
            # Check pgvector extension installation (cluster-wide, stable info)
            ext_result = await query_raw_with_schema(
                "SELECT extname, extversion, nspname as schema "
                "FROM pg_extension e "
                "JOIN pg_namespace n ON e.extnamespace = n.oid "
                "WHERE extname = 'vector'"
            )
            diagnostics["pgvector_extension"] = ext_result
        except Exception as e:
            diagnostics["pgvector_extension"] = f"Error: {e}"
        logger.error(
            f"Vector type error diagnostics:\n"
            f"  Error: {error}\n"
            f"  search_path: {diagnostics.get('search_path')}\n"
            f"  current_schema: {diagnostics.get('current_schema')}\n"
            f"  user_info: {diagnostics.get('user_info')}\n"
            f"  pgvector_extension: {diagnostics.get('pgvector_extension')}"
        )
    except Exception as diag_error:
        logger.error(f"Failed to collect vector error diagnostics: {diag_error}")
 # Backward compatibility alias - HybridSearchWeights maps to StoreAgentSearchWeights
 # for existing code that expects the popularity parameter
 HybridSearchWeights = StoreAgentSearchWeights
--- a/autogpt_platform/backend/backend/blocks/llm.py
+++ b/autogpt_platform/backend/backend/blocks/llm.py
@@ -531,12 +531,12 @@ class LLMResponse(BaseModel):
 def convert_openai_tool_fmt_to_anthropic(
    openai_tools: list[dict] | None = None,
-) -> Iterable[ToolParam] | anthropic.Omit:
+) -> Iterable[ToolParam] | anthropic.NotGiven:
    """
    Convert OpenAI tool format to Anthropic tool format.
    """
    if not openai_tools or len(openai_tools) == 0:
-        return anthropic.omit
+        return anthropic.NOT_GIVEN
    anthropic_tools = []
    for tool in openai_tools:
--- a/autogpt_platform/backend/backend/data/execution_queue_test.py
+++ b/autogpt_platform/backend/backend/data/execution_queue_test.py
@@ -3,6 +3,8 @@
 import queue
 import threading
 import pytest
 from backend.data.execution import ExecutionQueue
--- a/autogpt_platform/backend/backend/data/rabbitmq.py
+++ b/autogpt_platform/backend/backend/data/rabbitmq.py
@@ -1,4 +1,3 @@
 import asyncio
 import logging
 from abc import ABC, abstractmethod
 from enum import Enum
@@ -226,10 +225,6 @@ class SyncRabbitMQ(RabbitMQBase):
 class AsyncRabbitMQ(RabbitMQBase):
    """Asynchronous RabbitMQ client"""
    def __init__(self, config: RabbitMQConfig):
        super().__init__(config)
        self._reconnect_lock: asyncio.Lock | None = None
    @property
    def is_connected(self) -> bool:
        return bool(self._connection and not self._connection.is_closed)
@@ -240,17 +235,7 @@ class AsyncRabbitMQ(RabbitMQBase):
    @conn_retry("AsyncRabbitMQ", "Acquiring async connection")
    async def connect(self):
-        if self.is_connected and self._channel and not self._channel.is_closed:
+        if self.is_connected:
            return
        if (
            self.is_connected
            and self._connection
            and (self._channel is None or self._channel.is_closed)
        ):
            self._channel = await self._connection.channel()
            await self._channel.set_qos(prefetch_count=1)
            await self.declare_infrastructure()
            return
        self._connection = await aio_pika.connect_robust(
@@ -306,46 +291,24 @@ class AsyncRabbitMQ(RabbitMQBase):
                    exchange, routing_key=queue.routing_key or queue.name
                )
-    @property
+    @func_retry
-    def _lock(self) -> asyncio.Lock:
+    async def publish_message(
        if self._reconnect_lock is None:
            self._reconnect_lock = asyncio.Lock()
        return self._reconnect_lock
    async def _ensure_channel(self) -> aio_pika.abc.AbstractChannel:
        """Get a valid channel, reconnecting if the current one is stale.
        Uses a lock to prevent concurrent reconnection attempts from racing.
        """
        if self.is_ready:
            return self._channel  # type: ignore  # is_ready guarantees non-None
        async with self._lock:
            # Double-check after acquiring lock
            if self.is_ready:
                return self._channel  # type: ignore
            self._channel = None
            await self.connect()
            if self._channel is None:
                raise RuntimeError("Channel should be established after connect")
            return self._channel
    async def _publish_once(
        self,
        routing_key: str,
        message: str,
        exchange: Optional[Exchange] = None,
        persistent: bool = True,
    ) -> None:
-        channel = await self._ensure_channel()
+        if not self.is_ready:
            await self.connect()
        if self._channel is None:
            raise RuntimeError("Channel should be established after connect")
        if exchange:
-            exchange_obj = await channel.get_exchange(exchange.name)
+            exchange_obj = await self._channel.get_exchange(exchange.name)
        else:
-            exchange_obj = channel.default_exchange
+            exchange_obj = self._channel.default_exchange
        await exchange_obj.publish(
            aio_pika.Message(
@@ -359,23 +322,9 @@ class AsyncRabbitMQ(RabbitMQBase):
            routing_key=routing_key,
        )
    @func_retry
    async def publish_message(
        self,
        routing_key: str,
        message: str,
        exchange: Optional[Exchange] = None,
        persistent: bool = True,
    ) -> None:
        try:
            await self._publish_once(routing_key, message, exchange, persistent)
        except aio_pika.exceptions.ChannelInvalidStateError:
            logger.warning(
                "RabbitMQ channel invalid, forcing reconnect and retrying publish"
            )
            async with self._lock:
                self._channel = None
            await self._publish_once(routing_key, message, exchange, persistent)
    async def get_channel(self) -> aio_pika.abc.AbstractChannel:
-        return await self._ensure_channel()
+        if not self.is_ready:
            await self.connect()
        if self._channel is None:
            raise RuntimeError("Channel should be established after connect")
        return self._channel
--- a/autogpt_platform/backend/backend/util/file.py
+++ b/autogpt_platform/backend/backend/util/file.py
@@ -342,14 +342,6 @@ async def store_media_file(
        if not target_path.is_file():
            raise ValueError(f"Local file does not exist: {target_path}")
        # Virus scan the local file before any further processing
        local_content = target_path.read_bytes()
        if len(local_content) > MAX_FILE_SIZE_BYTES:
            raise ValueError(
                f"File too large: {len(local_content)} bytes > {MAX_FILE_SIZE_BYTES} bytes"
            )
        await scan_content_safe(local_content, filename=sanitized_file)
    # Return based on requested format
    if return_format == "for_local_processing":
        # Use when processing files locally with tools like ffmpeg, MoviePy, PIL
--- a/autogpt_platform/backend/backend/util/file_test.py
+++ b/autogpt_platform/backend/backend/util/file_test.py
@@ -247,100 +247,3 @@ class TestFileCloudIntegration:
                    execution_context=make_test_context(graph_exec_id=graph_exec_id),
                    return_format="for_local_processing",
                )
    @pytest.mark.asyncio
    async def test_store_media_file_local_path_scanned(self):
        """Test that local file paths are scanned for viruses."""
        graph_exec_id = "test-exec-123"
        local_file = "test_video.mp4"
        file_content = b"fake video content"
        with patch(
            "backend.util.file.get_cloud_storage_handler"
        ) as mock_handler_getter, patch(
            "backend.util.file.scan_content_safe"
        ) as mock_scan, patch(
            "backend.util.file.Path"
        ) as mock_path_class:
            # Mock cloud storage handler - not a cloud path
            mock_handler = MagicMock()
            mock_handler.is_cloud_path.return_value = False
            mock_handler_getter.return_value = mock_handler
            # Mock virus scanner
            mock_scan.return_value = None
            # Mock file system operations
            mock_base_path = MagicMock()
            mock_target_path = MagicMock()
            mock_resolved_path = MagicMock()
            mock_path_class.return_value = mock_base_path
            mock_base_path.mkdir = MagicMock()
            mock_base_path.__truediv__ = MagicMock(return_value=mock_target_path)
            mock_target_path.resolve.return_value = mock_resolved_path
            mock_resolved_path.is_relative_to.return_value = True
            mock_resolved_path.is_file.return_value = True
            mock_resolved_path.read_bytes.return_value = file_content
            mock_resolved_path.relative_to.return_value = Path(local_file)
            mock_resolved_path.name = local_file
            result = await store_media_file(
                file=MediaFileType(local_file),
                execution_context=make_test_context(graph_exec_id=graph_exec_id),
                return_format="for_local_processing",
            )
            # Verify virus scan was called for local file
            mock_scan.assert_called_once_with(file_content, filename=local_file)
            # Result should be the relative path
            assert str(result) == local_file
    @pytest.mark.asyncio
    async def test_store_media_file_local_path_virus_detected(self):
        """Test that infected local files raise VirusDetectedError."""
        from backend.api.features.store.exceptions import VirusDetectedError
        graph_exec_id = "test-exec-123"
        local_file = "infected.exe"
        file_content = b"malicious content"
        with patch(
            "backend.util.file.get_cloud_storage_handler"
        ) as mock_handler_getter, patch(
            "backend.util.file.scan_content_safe"
        ) as mock_scan, patch(
            "backend.util.file.Path"
        ) as mock_path_class:
            # Mock cloud storage handler - not a cloud path
            mock_handler = MagicMock()
            mock_handler.is_cloud_path.return_value = False
            mock_handler_getter.return_value = mock_handler
            # Mock virus scanner to detect virus
            mock_scan.side_effect = VirusDetectedError(
                "EICAR-Test-File", "File rejected due to virus detection"
            )
            # Mock file system operations
            mock_base_path = MagicMock()
            mock_target_path = MagicMock()
            mock_resolved_path = MagicMock()
            mock_path_class.return_value = mock_base_path
            mock_base_path.mkdir = MagicMock()
            mock_base_path.__truediv__ = MagicMock(return_value=mock_target_path)
            mock_target_path.resolve.return_value = mock_resolved_path
            mock_resolved_path.is_relative_to.return_value = True
            mock_resolved_path.is_file.return_value = True
            mock_resolved_path.read_bytes.return_value = file_content
            with pytest.raises(VirusDetectedError):
                await store_media_file(
                    file=MediaFileType(local_file),
                    execution_context=make_test_context(graph_exec_id=graph_exec_id),
                    return_format="for_local_processing",
                )
--- a/autogpt_platform/backend/poetry.lock
+++ b/autogpt_platform/backend/poetry.lock
@@ -269,20 +269,19 @@ files = [
 [[package]]
 name = "anthropic"
-version = "0.79.0"
+version = "0.59.0"
 description = "The official Python library for the anthropic API"
 optional = false
-python-versions = ">=3.9"
+python-versions = ">=3.8"
 groups = ["main"]
 files = [
-    {file = "anthropic-0.79.0-py3-none-any.whl", hash = "sha256:04cbd473b6bbda4ca2e41dd670fe2f829a911530f01697d0a1e37321eb75f3cf"},
+    {file = "anthropic-0.59.0-py3-none-any.whl", hash = "sha256:cbc8b3dccef66ad6435c4fa1d317e5ebb092399a4b88b33a09dc4bf3944c3183"},
-    {file = "anthropic-0.79.0.tar.gz", hash = "sha256:8707aafb3b1176ed6c13e2b1c9fb3efddce90d17aee5d8b83a86c70dcdcca871"},
+    {file = "anthropic-0.59.0.tar.gz", hash = "sha256:d710d1ef0547ebbb64b03f219e44ba078e83fc83752b96a9b22e9726b523fd8f"},
 ]
 [package.dependencies]
 anyio = ">=3.5.0,<5"
 distro = ">=1.7.0,<2"
 docstring-parser = ">=0.15,<1"
 httpx = ">=0.25.0,<1"
 jiter = ">=0.4.0,<1"
 pydantic = ">=1.9.0,<3"
@@ -290,7 +289,7 @@ sniffio = "*"
 typing-extensions = ">=4.10,<5"
 [package.extras]
-aiohttp = ["aiohttp", "httpx-aiohttp (>=0.1.9)"]
+aiohttp = ["aiohttp", "httpx-aiohttp (>=0.1.8)"]
 bedrock = ["boto3 (>=1.28.57)", "botocore (>=1.31.57)"]
 vertex = ["google-auth[requests] (>=2,<3)"]
@@ -439,7 +438,7 @@ develop = true
 [package.dependencies]
 colorama = "^0.4.6"
-cryptography = "^46.0"
+cryptography = "^45.0"
 expiringdict = "^1.2.2"
 fastapi = "^0.128.0"
 google-cloud-logging = "^3.13.0"
@@ -971,75 +970,62 @@ pytz = ">2021.1"
 [[package]]
 name = "cryptography"
-version = "46.0.4"
+version = "45.0.7"
 description = "cryptography is a package which provides cryptographic recipes and primitives to Python developers."
 optional = false
-python-versions = "!=3.9.0,!=3.9.1,>=3.8"
+python-versions = "!=3.9.0,!=3.9.1,>=3.7"
 groups = ["main"]
 files = [
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+    {file = "cryptography-45.0.7-cp311-abi3-macosx_10_9_universal2.whl", hash = "sha256:3be4f21c6245930688bd9e162829480de027f8bf962ede33d4f8ba7d67a00cee"},
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 [[package]]
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 wmi = ["wmi (>=1.5.1) ; platform_system == \"Windows\""]
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 [[package]]
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 [[package]]
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 [[package]]
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 [package.extras]
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@@ -4728,14 +4697,14 @@ tests = ["coverage-conditional-plugin (>=0.9.0)", "portalocker[redis]", "pytest
 [[package]]
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 [[package]]
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 [[package]]
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 [[package]]
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 [[package]]
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 description = "A streaming multipart parser for Python"
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 [[package]]
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@@ -6672,30 +6639,31 @@ pyasn1 = ">=0.1.3"
 [[package]]
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+version = "0.14.14"
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-    {file = "tiktoken-0.12.0-cp313-cp313t-macosx_10_13_x86_64.whl", hash = "sha256:d5f89ea5680066b68bcb797ae85219c72916c922ef0fcdd3480c7d2315ffff16"},
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-    {file = "tiktoken-0.12.0-cp313-cp313t-macosx_11_0_arm64.whl", hash = "sha256:b4e7ed1c6a7a8a60a3230965bdedba8cc58f68926b835e519341413370e0399a"},
+    {file = "tiktoken-0.9.0-cp39-cp39-win_amd64.whl", hash = "sha256:26242ca9dc8b58e875ff4ca078b9a94d2f0813e6a535dcd2205df5d49d927cc7"},
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+    {file = "tiktoken-0.9.0.tar.gz", hash = "sha256:d02a5ca6a938e0490e1ff957bc48c8b078c88cb83977be1625b1fd8aac792c5d"},
    {file = "tiktoken-0.12.0-cp313-cp313t-manylinux_2_28_x86_64.whl", hash = "sha256:06a9f4f49884139013b138920a4c393aa6556b2f8f536345f11819389c703ebb"},
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    {file = "tiktoken-0.12.0-cp39-cp39-musllinux_1_2_aarch64.whl", hash = "sha256:20cf97135c9a50de0b157879c3c4accbb29116bcf001283d26e073ff3b345946"},
    {file = "tiktoken-0.12.0-cp39-cp39-musllinux_1_2_x86_64.whl", hash = "sha256:15d875454bbaa3728be39880ddd11a5a2a9e548c29418b41e8fd8a767172b5ec"},
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    {file = "tiktoken-0.12.0.tar.gz", hash = "sha256:b18ba7ee2b093863978fcb14f74b3707cdc8d4d4d3836853ce7ec60772139931"},
 ]
 [package.dependencies]
@@ -8440,4 +8382,4 @@ cffi = ["cffi (>=1.17,<2.0) ; platform_python_implementation != \"PyPy\" and pyt
 [metadata]
 lock-version = "2.1"
 python-versions = ">=3.10,<3.14"
-content-hash = "14686ee0e2dc446a75d0db145b08dc410dc31c357e25085bb0f9b0174711c4b1"
+content-hash = "40b2c87c3c86bd10214bd30ad291cead75da5060ab894105025ee4c0a3b3828e"
--- a/autogpt_platform/backend/pyproject.toml
+++ b/autogpt_platform/backend/pyproject.toml
@@ -12,16 +12,16 @@ python = ">=3.10,<3.14"
 aio-pika = "^9.5.5"
 aiohttp = "^3.10.0"
 aiodns = "^3.5.0"
-anthropic = "^0.79.0"
+anthropic = "^0.59.0"
 apscheduler = "^3.11.1"
 autogpt-libs = { path = "../autogpt_libs", develop = true }
 bleach = { extras = ["css"], version = "^6.2.0" }
 click = "^8.2.0"
-cryptography = "^46.0"
+cryptography = "^45.0"
 discord-py = "^2.5.2"
 e2b-code-interpreter = "^1.5.2"
 elevenlabs = "^1.50.0"
-fastapi = "^0.128.5"
+fastapi = "^0.128.0"
 feedparser = "^6.0.11"
 flake8 = "^7.3.0"
 google-api-python-client = "^2.177.0"
@@ -38,7 +38,7 @@ langfuse = "^3.11.0"
 launchdarkly-server-sdk = "^9.14.1"
 mem0ai = "^0.1.115"
 moviepy = "^2.1.2"
-ollama = "^0.6.1"
+ollama = "^0.5.1"
 openai = "^1.97.1"
 orjson = "^3.10.0"
 pika = "^1.3.2"
@@ -48,7 +48,7 @@ postmarker = "^1.0"
 praw = "~7.8.1"
 prisma = "^0.15.0"
 rank-bm25 = "^0.2.2"
-prometheus-client = "^0.24.1"
+prometheus-client = "^0.22.1"
 prometheus-fastapi-instrumentator = "^7.0.0"
 psutil = "^7.0.0"
 psycopg2-binary = "^2.9.10"
@@ -57,7 +57,7 @@ pydantic-settings = "^2.12.0"
 pytest = "^8.4.1"
 pytest-asyncio = "^1.1.0"
 python-dotenv = "^1.1.1"
-python-multipart = "^0.0.22"
+python-multipart = "^0.0.20"
 redis = "^6.2.0"
 regex = "^2025.9.18"
 replicate = "^1.0.6"
@@ -65,8 +65,8 @@ sentry-sdk = {extras = ["anthropic", "fastapi", "launchdarkly", "openai", "sqlal
 sqlalchemy = "^2.0.40"
 strenum = "^0.4.9"
 stripe = "^11.5.0"
-supabase = "2.27.3"
+supabase = "2.27.2"
-tenacity = "^9.1.4"
+tenacity = "^9.1.2"
 todoist-api-python = "^2.1.7"
 tweepy = "^4.16.0"
 uvicorn = { extras = ["standard"], version = "^0.40.0" }
@@ -77,7 +77,7 @@ zerobouncesdk = "^1.1.2"
 # NOTE: please insert new dependencies in their alphabetical location
 pytest-snapshot = "^0.9.0"
 aiofiles = "^24.1.0"
-tiktoken = "^0.12.0"
+tiktoken = "^0.9.0"
 aioclamd = "^1.0.0"
 setuptools = "^80.9.0"
 gcloud-aio-storage = "^9.5.0"
@@ -95,13 +95,13 @@ black = "^24.10.0"
 faker = "^38.2.0"
 httpx = "^0.28.1"
 isort = "^5.13.2"
-poethepoet = "^0.41.0"
+poethepoet = "^0.37.0"
 pre-commit = "^4.4.0"
 pyright = "^1.1.407"
 pytest-mock = "^3.15.1"
-pytest-watcher = "^0.6.3"
+pytest-watcher = "^0.4.2"
 requests = "^2.32.5"
-ruff = "^0.15.0"
+ruff = "^0.14.5"
 # NOTE: please insert new dependencies in their alphabetical location
 [build-system]
--- a/autogpt_platform/frontend/package.json
+++ b/autogpt_platform/frontend/package.json
@@ -102,7 +102,7 @@
    "react-markdown": "9.0.3",
    "react-modal": "3.16.3",
    "react-shepherd": "6.1.9",
-    "react-window": "2.2.0",
+    "react-window": "1.8.11",
    "recharts": "3.3.0",
    "rehype-autolink-headings": "7.1.0",
    "rehype-highlight": "7.0.2",
@@ -140,7 +140,7 @@
    "@types/react": "18.3.17",
    "@types/react-dom": "18.3.5",
    "@types/react-modal": "3.16.3",
-    "@types/react-window": "2.0.0",
+    "@types/react-window": "1.8.8",
    "@vitejs/plugin-react": "5.1.2",
    "axe-playwright": "2.2.2",
    "chromatic": "13.3.3",
--- a/autogpt_platform/frontend/pnpm-lock.yaml
+++ b/autogpt_platform/frontend/pnpm-lock.yaml
@@ -228,8 +228,8 @@ importers:
        specifier: 6.1.9
        version: 6.1.9(react-dom@18.3.1(react@18.3.1))(react@18.3.1)(typescript@5.9.3)
      react-window:
-        specifier: 2.2.0
+        specifier: 1.8.11
-        version: 2.2.0(react-dom@18.3.1(react@18.3.1))(react@18.3.1)
+        version: 1.8.11(react-dom@18.3.1(react@18.3.1))(react@18.3.1)
      recharts:
        specifier: 3.3.0
        version: 3.3.0(@types/react@18.3.17)(react-dom@18.3.1(react@18.3.1))(react-is@18.3.1)(react@18.3.1)(redux@5.0.1)
@@ -337,8 +337,8 @@ importers:
        specifier: 3.16.3
        version: 3.16.3
      '@types/react-window':
-        specifier: 2.0.0
+        specifier: 1.8.8
-        version: 2.0.0(react-dom@18.3.1(react@18.3.1))(react@18.3.1)
+        version: 1.8.8
      '@vitejs/plugin-react':
        specifier: 5.1.2
        version: 5.1.2(vite@7.3.1(@types/node@24.10.0)(jiti@2.6.1)(terser@5.44.1)(yaml@2.8.2))
@@ -3469,9 +3469,8 @@ packages:
  '@types/react-modal@3.16.3':
    resolution: {integrity: sha512-xXuGavyEGaFQDgBv4UVm8/ZsG+qxeQ7f77yNrW3n+1J6XAstUy5rYHeIHPh1KzsGc6IkCIdu6lQ2xWzu1jBTLg==}
-  '@types/react-window@2.0.0':
+  '@types/react-window@1.8.8':
-    resolution: {integrity: sha512-E8hMDtImEpMk1SjswSvqoSmYvk7GEtyVaTa/GJV++FdDNuMVVEzpAClyJ0nqeKYBrMkGiyH6M1+rPLM0Nu1exQ==}
+    resolution: {integrity: sha512-8Ls660bHR1AUA2kuRvVG9D/4XpRC6wjAaPT9dil7Ckc76eP9TKWZwwmgfq8Q1LANX3QNDnoU4Zp48A3w+zK69Q==}
    deprecated: This is a stub types definition. react-window provides its own type definitions, so you do not need this installed.
  '@types/react@18.3.17':
    resolution: {integrity: sha512-opAQ5no6LqJNo9TqnxBKsgnkIYHozW9KSTlFVoSUJYh1Fl/sswkEoqIugRSm7tbh6pABtYjGAjW+GOS23j8qbw==}
@@ -5977,6 +5976,9 @@ packages:
    resolution: {integrity: sha512-UERzLsxzllchadvbPs5aolHh65ISpKpM+ccLbOJ8/vvpBKmAWf+la7dXFy7Mr0ySHbdHrFv5kGFCUHHe6GFEmw==}
    engines: {node: '>= 4.0.0'}
  memoize-one@5.2.1:
    resolution: {integrity: sha512-zYiwtZUcYyXKo/np96AGZAckk+FWWsUdJ3cHGGmld7+AhvcWmQyGCYUh1hc4Q/pkOhb65dQR/pqCyK0cOaHz4Q==}
  merge-stream@2.0.0:
    resolution: {integrity: sha512-abv/qOcuPfk3URPfDzmZU1LKmuw8kT+0nIHvKrKgFrwifol/doWcdA4ZqsWQ8ENrFKkd67Mfpo/LovbIUsbt3w==}
@@ -6889,11 +6891,12 @@ packages:
      '@types/react':
        optional: true
-  react-window@2.2.0:
+  react-window@1.8.11:
-    resolution: {integrity: sha512-Y2L7yonHq6K1pQA2P98wT5QdIsEcjBTB7T8o6Mub12hH9eYppXoYu6vgClmcjlh3zfNcW2UrXiJJJqDxUY7GVw==}
+    resolution: {integrity: sha512-+SRbUVT2scadgFSWx+R1P754xHPEqvcfSfVX10QYg6POOz+WNgkN48pS+BtZNIMGiL1HYrSEiCkwsMS15QogEQ==}
    engines: {node: '>8.0.0'}
    peerDependencies:
-      react: ^18.0.0 || ^19.0.0
+      react: ^15.0.0 || ^16.0.0 || ^17.0.0 || ^18.0.0 || ^19.0.0
-      react-dom: ^18.0.0 || ^19.0.0
+      react-dom: ^15.0.0 || ^16.0.0 || ^17.0.0 || ^18.0.0 || ^19.0.0
  react@18.3.1:
    resolution: {integrity: sha512-wS+hAgJShR0KhEvPJArfuPVN1+Hz1t0Y6n5jLrGQbkb4urgPE/0Rve+1kMB1v/oWgHgm4WIcV+i7F2pTVj+2iQ==}
@@ -11600,12 +11603,9 @@ snapshots:
    dependencies:
      '@types/react': 18.3.17
-  '@types/react-window@2.0.0(react-dom@18.3.1(react@18.3.1))(react@18.3.1)':
+  '@types/react-window@1.8.8':
    dependencies:
-      react-window: 2.2.0(react-dom@18.3.1(react@18.3.1))(react@18.3.1)
+      '@types/react': 18.3.17
    transitivePeerDependencies:
      - react
      - react-dom
  '@types/react@18.3.17':
    dependencies:
@@ -14545,6 +14545,8 @@ snapshots:
    dependencies:
      fs-monkey: 1.1.0
  memoize-one@5.2.1: {}
  merge-stream@2.0.0: {}
  merge2@1.4.1: {}
@@ -15590,8 +15592,10 @@ snapshots:
    optionalDependencies:
      '@types/react': 18.3.17
-  react-window@2.2.0(react-dom@18.3.1(react@18.3.1))(react@18.3.1):
+  react-window@1.8.11(react-dom@18.3.1(react@18.3.1))(react@18.3.1):
    dependencies:
      '@babel/runtime': 7.28.4
      memoize-one: 5.2.1
      react: 18.3.1
      react-dom: 18.3.1(react@18.3.1)
--- a/autogpt_platform/frontend/src/components/atoms/FileInput/FileInput.tsx
+++ b/autogpt_platform/frontend/src/components/atoms/FileInput/FileInput.tsx
@@ -104,31 +104,7 @@ export function FileInput(props: Props) {
    return false;
  }
-  const getFileLabelFromValue = (val: unknown): string => {
+  const getFileLabelFromValue = (val: string) => {
    // Handle object format from external API: { name, type, size, data }
    if (val && typeof val === "object") {
      const obj = val as Record<string, unknown>;
      if (typeof obj.name === "string") {
        return getFileLabel(
          obj.name,
          typeof obj.type === "string" ? obj.type : "",
        );
      }
      if (typeof obj.type === "string") {
        const mimeParts = obj.type.split("/");
        if (mimeParts.length > 1) {
          return `${mimeParts[1].toUpperCase()} file`;
        }
        return `${obj.type} file`;
      }
      return "File";
    }
    // Handle string values (data URIs or file paths)
    if (typeof val !== "string") {
      return "File";
    }
    if (val.startsWith("data:")) {
      const matches = val.match(/^data:([^;]+);/);
      if (matches?.[1]) {
--- a/autogpt_platform/frontend/src/components/layout/Navbar/components/AgentActivityDropdown/components/ActivityDropdown/ActivityDropdown.tsx
+++ b/autogpt_platform/frontend/src/components/layout/Navbar/components/AgentActivityDropdown/components/ActivityDropdown/ActivityDropdown.tsx
@@ -4,7 +4,7 @@ import { Button } from "@/components/atoms/Button/Button";
 import { Input } from "@/components/atoms/Input/Input";
 import { Text } from "@/components/atoms/Text/Text";
 import { Bell, MagnifyingGlass, X } from "@phosphor-icons/react";
-import { List, type RowComponentProps } from "react-window";
+import { FixedSizeList as List } from "react-window";
 import { AgentExecutionWithInfo } from "../../helpers";
 import { ActivityItem } from "../ActivityItem";
 import styles from "./styles.module.css";
@@ -19,16 +19,14 @@ interface Props {
  recentFailures: AgentExecutionWithInfo[];
 }
-interface ActivityRowProps {
+interface VirtualizedItemProps {
-  executions: AgentExecutionWithInfo[];
+  index: number;
  style: React.CSSProperties;
  data: AgentExecutionWithInfo[];
 }
-function VirtualizedActivityItem({
+function VirtualizedActivityItem({ index, style, data }: VirtualizedItemProps) {
-  index,
+  const execution = data[index];
  style,
  executions,
 }: RowComponentProps<ActivityRowProps>) {
  const execution = executions[index];
  return (
    <div style={style}>
      <ActivityItem execution={execution} />
@@ -131,13 +129,14 @@ export function ActivityDropdown({
      >
        {filteredExecutions.length > 0 ? (
          <List
-            defaultHeight={listHeight}
+            height={listHeight}
-            rowCount={filteredExecutions.length}
+            width={320} // Match dropdown width (w-80 = 20rem = 320px)
-            rowHeight={itemHeight}
+            itemCount={filteredExecutions.length}
-            rowProps={{ executions: filteredExecutions }}
+            itemSize={itemHeight}
-            rowComponent={VirtualizedActivityItem}
+            itemData={filteredExecutions}
-            style={{ width: 320, height: listHeight }}
+          >
-          />
+            {VirtualizedActivityItem}
          </List>
        ) : (
          <div className="flex h-full flex-col items-center justify-center gap-5 pb-8 pt-6">
            <div className="mx-auto inline-flex flex-col items-center justify-center rounded-full bg-bgLightGrey p-6">