chore: changes ...

Dependabot will resolve any conflicts with this PR as long as you don't
alter it yourself. You can also trigger a rebase manually by commenting
`@dependabot rebase`.

[//]: # (dependabot-automerge-start)
[//]: # (dependabot-automerge-end)

---

<details>
<summary>Dependabot commands and options</summary>
<br />

You can trigger Dependabot actions by commenting on this PR:
- `@dependabot rebase` will rebase this PR
- `@dependabot recreate` will recreate this PR, overwriting any edits
that have been made to it
- `@dependabot merge` will merge this PR after your CI passes on it
- `@dependabot squash and merge` will squash and merge this PR after
your CI passes on it
- `@dependabot cancel merge` will cancel a previously requested merge
and block automerging
- `@dependabot reopen` will reopen this PR if it is closed
- `@dependabot close` will close this PR and stop Dependabot recreating
it. You can achieve the same result by closing it manually
- `@dependabot show <dependency name> ignore conditions` will show all
of the ignore conditions of the specified dependency
- `@dependabot ignore <dependency name> major version` will close this
group update PR and stop Dependabot creating any more for the specific
dependency's major version (unless you unignore this specific
dependency's major version or upgrade to it yourself)
- `@dependabot ignore <dependency name> minor version` will close this
group update PR and stop Dependabot creating any more for the specific
dependency's minor version (unless you unignore this specific
dependency's minor version or upgrade to it yourself)
- `@dependabot ignore <dependency name>` will close this group update PR
and stop Dependabot creating any more for the specific dependency
(unless you unignore this specific dependency or upgrade to it yourself)
- `@dependabot unignore <dependency name>` will remove all of the ignore
conditions of the specified dependency
- `@dependabot unignore <dependency name> <ignore condition>` will
remove the ignore condition of the specified dependency and ignore
conditions


</details>

Signed-off-by: dependabot[bot] <support@github.com>
Co-authored-by: dependabot[bot] <49699333+dependabot[bot]@users.noreply.github.com>

.dockerignore

@@ -27,7 +27,7 @@
 !autogpt_platform/frontend/src/
 !autogpt_platform/frontend/public/
 !autogpt_platform/frontend/package.json
-!autogpt_platform/frontend/yarn.lock
+!autogpt_platform/frontend/pnpm-lock.yaml
 !autogpt_platform/frontend/tsconfig.json
 !autogpt_platform/frontend/README.md
 ## config

.github/dependabot.yml

@@ -10,17 +10,19 @@ updates:
     commit-message:
       prefix: "chore(libs/deps)"
       prefix-development: "chore(libs/deps-dev)"
+    ignore:
+      - dependency-name: "poetry"
     groups:
       production-dependencies:
         dependency-type: "production"
         update-types:
-        - "minor"
-        - "patch"
+          - "minor"
+          - "patch"
       development-dependencies:
         dependency-type: "development"
         update-types:
-        - "minor"
-        - "patch"
+          - "minor"
+          - "patch"
 
   # backend (Poetry project)
   - package-ecosystem: "pip"
@@ -32,17 +34,19 @@ updates:
     commit-message:
       prefix: "chore(backend/deps)"
       prefix-development: "chore(backend/deps-dev)"
+    ignore:
+      - dependency-name: "poetry"
     groups:
       production-dependencies:
         dependency-type: "production"
         update-types:
-        - "minor"
-        - "patch"
+          - "minor"
+          - "patch"
       development-dependencies:
         dependency-type: "development"
         update-types:
-        - "minor"
-        - "patch"
+          - "minor"
+          - "patch"
 
   # frontend (Next.js project)
   - package-ecosystem: "npm"
@@ -58,13 +62,13 @@ updates:
       production-dependencies:
         dependency-type: "production"
         update-types:
-        - "minor"
-        - "patch"
+          - "minor"
+          - "patch"
       development-dependencies:
         dependency-type: "development"
         update-types:
-        - "minor"
-        - "patch"
+          - "minor"
+          - "patch"
 
   # infra (Terraform)
   - package-ecosystem: "terraform"
@@ -81,14 +85,13 @@ updates:
       production-dependencies:
         dependency-type: "production"
         update-types:
-        - "minor"
-        - "patch"
+          - "minor"
+          - "patch"
       development-dependencies:
         dependency-type: "development"
         update-types:
-        - "minor"
-        - "patch"
-
+          - "minor"
+          - "patch"
 
   # GitHub Actions
   - package-ecosystem: "github-actions"
@@ -101,14 +104,13 @@ updates:
       production-dependencies:
         dependency-type: "production"
         update-types:
-        - "minor"
-        - "patch"
+          - "minor"
+          - "patch"
       development-dependencies:
         dependency-type: "development"
         update-types:
-        - "minor"
-        - "patch"
-
+          - "minor"
+          - "patch"
 
   # Docker
   - package-ecosystem: "docker"
@@ -121,16 +123,16 @@ updates:
       production-dependencies:
         dependency-type: "production"
         update-types:
-        - "minor"
-        - "patch"
+          - "minor"
+          - "patch"
       development-dependencies:
         dependency-type: "development"
         update-types:
-        - "minor"
-        - "patch"
+          - "minor"
+          - "patch"
 
   # Docs
-  - package-ecosystem: 'pip'
+  - package-ecosystem: "pip"
     directory: "docs/"
     schedule:
       interval: "weekly"
@@ -142,10 +144,10 @@ updates:
       production-dependencies:
         dependency-type: "production"
         update-types:
-        - "minor"
-        - "patch"
+          - "minor"
+          - "patch"
       development-dependencies:
         dependency-type: "development"
         update-types:
-        - "minor"
-        - "patch"
+          - "minor"
+          - "patch"

.github/labeler.yml

@@ -24,8 +24,9 @@ platform/frontend:
 
 platform/backend:
 - changed-files:
-  - any-glob-to-any-file: autogpt_platform/backend/**
-  - all-globs-to-all-files: '!autogpt_platform/backend/backend/blocks/**'
+  - all-globs-to-any-file:
+    - autogpt_platform/backend/**
+    - '!autogpt_platform/backend/backend/blocks/**'
 
 platform/blocks:
 - changed-files:

.github/workflows/claude.yml

@@ -0,0 +1,47 @@
+name: Claude Code
+
+on:
+  issue_comment:
+    types: [created]
+  pull_request_review_comment:
+    types: [created]
+  issues:
+    types: [opened, assigned]
+  pull_request_review:
+    types: [submitted]
+
+jobs:
+  claude:
+    if: |
+      (
+        (github.event_name == 'issue_comment' && contains(github.event.comment.body, '@claude')) ||
+        (github.event_name == 'pull_request_review_comment' && contains(github.event.comment.body, '@claude')) ||
+        (github.event_name == 'pull_request_review' && contains(github.event.review.body, '@claude')) ||
+        (github.event_name == 'issues' && (contains(github.event.issue.body, '@claude') || contains(github.event.issue.title, '@claude')))
+      ) && (
+        github.event.comment.author_association == 'OWNER' ||
+        github.event.comment.author_association == 'MEMBER' ||
+        github.event.comment.author_association == 'COLLABORATOR' ||
+        github.event.review.author_association == 'OWNER' ||
+        github.event.review.author_association == 'MEMBER' ||
+        github.event.review.author_association == 'COLLABORATOR' ||
+        github.event.issue.author_association == 'OWNER' ||
+        github.event.issue.author_association == 'MEMBER' ||
+        github.event.issue.author_association == 'COLLABORATOR'
+      )
+    runs-on: ubuntu-latest
+    permissions:
+      contents: read
+      pull-requests: read
+      issues: read
+      id-token: write
+    steps:
+      - name: Checkout repository
+        uses: actions/checkout@v4
+        with:
+          fetch-depth: 1
+      - name: Run Claude Code
+        id: claude
+        uses: anthropics/claude-code-action@beta
+        with:
+          anthropic_api_key: ${{ secrets.ANTHROPIC_API_KEY }}

.github/workflows/platform-autgpt-deploy-prod.yml

@@ -34,6 +34,7 @@ jobs:
           python -m prisma migrate deploy
         env:
           DATABASE_URL: ${{ secrets.BACKEND_DATABASE_URL }}
+          DIRECT_URL: ${{ secrets.BACKEND_DATABASE_URL }}
 
           
   trigger:

.github/workflows/platform-autogpt-deploy-dev.yaml

@@ -36,6 +36,7 @@ jobs:
           python -m prisma migrate deploy
         env:
           DATABASE_URL: ${{ secrets.BACKEND_DATABASE_URL }}
+          DIRECT_URL: ${{ secrets.BACKEND_DATABASE_URL }}
 
   trigger:
     needs: migrate

.github/workflows/platform-backend-ci.yml

@@ -32,7 +32,7 @@ jobs:
     strategy:
       fail-fast: false
       matrix:
-        python-version: ["3.10"]
+        python-version: ["3.11"]
     runs-on: ubuntu-latest
 
     services:
@@ -80,18 +80,35 @@ jobs:
 
       - name: Install Poetry (Unix)
         run: |
-          curl -sSL https://install.python-poetry.org | python3 -
+          # Extract Poetry version from backend/poetry.lock
+          HEAD_POETRY_VERSION=$(python ../../.github/workflows/scripts/get_package_version_from_lockfile.py poetry)
+          echo "Found Poetry version ${HEAD_POETRY_VERSION} in backend/poetry.lock"
+
+          if [ -n "$BASE_REF" ]; then
+            BASE_BRANCH=${BASE_REF/refs\/heads\//}
+            BASE_POETRY_VERSION=$((git show "origin/$BASE_BRANCH":./poetry.lock; true) | python ../../.github/workflows/scripts/get_package_version_from_lockfile.py poetry -)
+            echo "Found Poetry version ${BASE_POETRY_VERSION} in backend/poetry.lock on ${BASE_REF}"
+            POETRY_VERSION=$(printf '%s\n' "$HEAD_POETRY_VERSION" "$BASE_POETRY_VERSION" | sort -V | tail -n1)
+          else
+            POETRY_VERSION=$HEAD_POETRY_VERSION
+          fi
+          echo "Using Poetry version ${POETRY_VERSION}"
+
+          # Install Poetry
+          curl -sSL https://install.python-poetry.org | POETRY_VERSION=$POETRY_VERSION python3 -
 
           if [ "${{ runner.os }}" = "macOS" ]; then
             PATH="$HOME/.local/bin:$PATH"
             echo "$HOME/.local/bin" >> $GITHUB_PATH
           fi
+        env:
+          BASE_REF: ${{ github.base_ref || github.event.merge_group.base_ref }}
 
       - name: Check poetry.lock
         run: |
           poetry lock
 
-          if ! git diff --quiet poetry.lock; then
+          if ! git diff --quiet --ignore-matching-lines="^# " poetry.lock; then
             echo "Error: poetry.lock not up to date."
             echo
             git diff poetry.lock
@@ -118,6 +135,7 @@ jobs:
         run: poetry run prisma migrate dev --name updates
         env:
           DATABASE_URL: ${{ steps.supabase.outputs.DB_URL }}
+          DIRECT_URL: ${{ steps.supabase.outputs.DB_URL }}
 
       - id: lint
         name: Run Linter
@@ -134,12 +152,13 @@ jobs:
         env:
           LOG_LEVEL: ${{ runner.debug && 'DEBUG' || 'INFO' }}
           DATABASE_URL: ${{ steps.supabase.outputs.DB_URL }}
+          DIRECT_URL: ${{ steps.supabase.outputs.DB_URL }}
           SUPABASE_URL: ${{ steps.supabase.outputs.API_URL }}
           SUPABASE_SERVICE_ROLE_KEY: ${{ steps.supabase.outputs.SERVICE_ROLE_KEY }}
           SUPABASE_JWT_SECRET: ${{ steps.supabase.outputs.JWT_SECRET }}
-          REDIS_HOST: 'localhost'
-          REDIS_PORT: '6379'
-          REDIS_PASSWORD: 'testpassword'
+          REDIS_HOST: "localhost"
+          REDIS_PORT: "6379"
+          REDIS_PASSWORD: "testpassword"
 
     env:
       CI: true
@@ -152,8 +171,8 @@ jobs:
       # If you want to replace this, you can do so by making our entire system generate
       # new credentials for each local user and update the environment variables in
       # the backend service, docker composes, and examples
-      RABBITMQ_DEFAULT_USER: 'rabbitmq_user_default'
-      RABBITMQ_DEFAULT_PASS: 'k0VMxyIJF9S35f3x2uaw5IWAl6Y536O7'
+      RABBITMQ_DEFAULT_USER: "rabbitmq_user_default"
+      RABBITMQ_DEFAULT_PASS: "k0VMxyIJF9S35f3x2uaw5IWAl6Y536O7"
 
       # - name: Upload coverage reports to Codecov
       #   uses: codecov/codecov-action@v4

.github/workflows/platform-dev-deploy-event-dispatcher.yml

@@ -0,0 +1,198 @@
+name: AutoGPT Platform - Dev Deploy PR Event Dispatcher
+
+on:
+  pull_request:
+    types: [closed]
+  issue_comment:
+    types: [created]
+
+permissions:
+  issues: write
+  pull-requests: write
+
+jobs:
+  dispatch:
+    runs-on: ubuntu-latest
+    steps:
+      - 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@v7
+        with:
+          script: |
+            const commentBody = context.payload.comment.body.trim();
+            const commentUser = context.payload.comment.user.login;
+            const prAuthor = context.payload.issue.user.login;
+            const authorAssociation = context.payload.comment.author_association;
+            
+            // Check permissions
+            const hasPermission = (
+              authorAssociation === 'OWNER' ||
+              authorAssociation === 'MEMBER' ||
+              authorAssociation === 'COLLABORATOR'
+            );
+            
+            core.setOutput('comment_body', commentBody);
+            core.setOutput('has_permission', hasPermission);
+            
+            if (!hasPermission && (commentBody === '!deploy' || commentBody === '!undeploy')) {
+              core.setOutput('permission_denied', 'true');
+              return;
+            }
+            
+            if (commentBody !== '!deploy' && commentBody !== '!undeploy') {
+              return;
+            }
+            
+            // Process deploy command
+            if (commentBody === '!deploy') {
+              core.setOutput('should_deploy', 'true');
+            }
+            // Process undeploy command
+            else if (commentBody === '!undeploy') {
+              core.setOutput('should_undeploy', 'true');
+            }
+
+      - name: Post permission denied comment
+        if: steps.check_status.outputs.permission_denied == 'true'
+        uses: actions/github-script@v7
+        with:
+          script: |
+            await github.rest.issues.createComment({
+              owner: context.repo.owner,
+              repo: context.repo.repo,
+              issue_number: context.issue.number,
+              body: `❌ **Permission denied**: Only the repository owners, members, or collaborators can use deployment commands.`
+            });
+
+      - 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@v7
+        with:
+          script: |
+            const pr = await github.rest.pulls.get({
+              owner: context.repo.owner,
+              repo: context.repo.repo,
+              pull_number: context.issue.number
+            });
+            core.setOutput('pr_number', pr.data.number);
+            core.setOutput('pr_title', pr.data.title);
+            core.setOutput('pr_state', pr.data.state);
+          
+      - name: Dispatch Deploy Event
+        if: steps.check_status.outputs.should_deploy == 'true'
+        uses: peter-evans/repository-dispatch@v3
+        with:
+          token: ${{ secrets.DISPATCH_TOKEN }}
+          repository: Significant-Gravitas/AutoGPT_cloud_infrastructure
+          event-type: pr-event
+          client-payload: |
+            {
+              "action": "deploy",
+              "pr_number": "${{ steps.pr_details.outputs.pr_number }}",
+              "pr_title": "${{ steps.pr_details.outputs.pr_title }}",
+              "pr_state": "${{ steps.pr_details.outputs.pr_state }}",
+              "repo": "${{ github.repository }}"
+            }
+
+      - name: Post deploy success comment
+        if: steps.check_status.outputs.should_deploy == 'true'
+        uses: actions/github-script@v7
+        with:
+          script: |
+            await github.rest.issues.createComment({
+              owner: context.repo.owner,
+              repo: context.repo.repo,
+              issue_number: context.issue.number,
+              body: `🚀 **Deploying PR #${{ steps.pr_details.outputs.pr_number }}** to development environment...`
+            });
+
+      - name: Dispatch Undeploy Event (from comment)
+        if: steps.check_status.outputs.should_undeploy == 'true'
+        uses: peter-evans/repository-dispatch@v3
+        with:
+          token: ${{ secrets.DISPATCH_TOKEN }}
+          repository: Significant-Gravitas/AutoGPT_cloud_infrastructure
+          event-type: pr-event
+          client-payload: |
+            {
+              "action": "undeploy",
+              "pr_number": "${{ steps.pr_details.outputs.pr_number }}",
+              "pr_title": "${{ steps.pr_details.outputs.pr_title }}",
+              "pr_state": "${{ steps.pr_details.outputs.pr_state }}",
+              "repo": "${{ github.repository }}"
+            }
+
+      - name: Post undeploy success comment
+        if: steps.check_status.outputs.should_undeploy == 'true'
+        uses: actions/github-script@v7
+        with:
+          script: |
+            await github.rest.issues.createComment({
+              owner: context.repo.owner,
+              repo: context.repo.repo,
+              issue_number: context.issue.number,
+              body: `🗑️ **Undeploying PR #${{ steps.pr_details.outputs.pr_number }}** from development environment...`
+            });
+
+      - 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@v7
+        with:
+          script: |
+            const comments = await github.rest.issues.listComments({
+              owner: context.repo.owner,
+              repo: context.repo.repo,
+              issue_number: context.issue.number
+            });
+            
+            let lastDeployIndex = -1;
+            let lastUndeployIndex = -1;
+            
+            comments.data.forEach((comment, index) => {
+              if (comment.body.trim() === '!deploy') {
+                lastDeployIndex = index;
+              } else if (comment.body.trim() === '!undeploy') {
+                lastUndeployIndex = index;
+              }
+            });
+            
+            // Should undeploy if there's a !deploy without a subsequent !undeploy
+            const shouldUndeploy = lastDeployIndex !== -1 && lastDeployIndex > lastUndeployIndex;
+            core.setOutput('should_undeploy', shouldUndeploy);
+            
+      - name: Dispatch Undeploy Event (PR closed with active deployment)
+        if: >-
+          github.event_name == 'pull_request' &&
+          github.event.action == 'closed' &&
+          steps.check_pr_close.outputs.should_undeploy == 'true'
+        uses: peter-evans/repository-dispatch@v3
+        with:
+          token: ${{ secrets.DISPATCH_TOKEN }}
+          repository: Significant-Gravitas/AutoGPT_cloud_infrastructure
+          event-type: pr-event
+          client-payload: |
+            {
+              "action": "undeploy",
+              "pr_number": "${{ github.event.pull_request.number }}",
+              "pr_title": "${{ github.event.pull_request.title }}",
+              "pr_state": "${{ github.event.pull_request.state }}",
+              "repo": "${{ github.repository }}"
+            }
+
+      - name: Post PR close undeploy comment
+        if: >-
+          github.event_name == 'pull_request' &&
+          github.event.action == 'closed' &&
+          steps.check_pr_close.outputs.should_undeploy == 'true'
+        uses: actions/github-script@v7
+        with:
+          script: |
+            await github.rest.issues.createComment({
+              owner: context.repo.owner,
+              repo: context.repo.repo,
+              issue_number: context.issue.number,
+              body: `🧹 **Auto-undeploying**: PR closed with active deployment. Cleaning up development environment for PR #${{ github.event.pull_request.number }}.`
+            });

.github/workflows/platform-frontend-ci.yml

@@ -29,13 +29,14 @@ jobs:
         with:
           node-version: "21"
 
+      - name: Enable corepack
+        run: corepack enable
+
       - name: Install dependencies
-        run: |
-          yarn install --frozen-lockfile
+        run: pnpm install --frozen-lockfile
 
       - name: Run lint
-        run: |
-          yarn lint
+        run: pnpm lint
 
   type-check:
     runs-on: ubuntu-latest
@@ -48,13 +49,14 @@ jobs:
         with:
           node-version: "21"
 
+      - name: Enable corepack
+        run: corepack enable
+
       - name: Install dependencies
-        run: |
-          yarn install --frozen-lockfile
+        run: pnpm install --frozen-lockfile
 
       - name: Run tsc check
-        run: |
-          yarn type-check
+        run: pnpm type-check
 
   test:
     runs-on: ubuntu-latest
@@ -74,6 +76,9 @@ jobs:
         with:
           node-version: "21"
 
+      - name: Enable corepack
+        run: corepack enable
+
       - name: Free Disk Space (Ubuntu)
         uses: jlumbroso/free-disk-space@main
         with:
@@ -93,25 +98,24 @@ jobs:
           docker compose -f ../docker-compose.yml up -d
 
       - name: Install dependencies
-        run: |
-          yarn install --frozen-lockfile
+        run: pnpm install --frozen-lockfile
 
-      - name: Setup Builder .env
-        run: |
-          cp .env.example .env
+      - name: Setup .env
+        run: cp .env.example .env
+
+      - name: Build frontend
+        run: pnpm build --turbo
+        # uses Turbopack, much faster and safe enough for a test pipeline
 
       - name: Install Browser '${{ matrix.browser }}'
-        run: yarn playwright install --with-deps ${{ matrix.browser }}
+        run: pnpm playwright install --with-deps ${{ matrix.browser }}
 
-      - name: Run tests
-        timeout-minutes: 20
-        run: |
-          yarn test --project=${{ matrix.browser }}
+      - name: Run Playwright tests
+        run: pnpm test:no-build --project=${{ matrix.browser }}
 
       - name: Print Final Docker Compose logs
         if: always()
-        run: |
-          docker compose -f ../docker-compose.yml logs
+        run: docker compose -f ../docker-compose.yml logs
 
       - uses: actions/upload-artifact@v4
         if: ${{ !cancelled() }}

.github/workflows/repo-close-stale-issues.yml

@@ -16,7 +16,7 @@ jobs:
           # operations-per-run: 5000
           stale-issue-message: >
             This issue has automatically been marked as _stale_ because it has not had
-            any activity in the last 50 days. You can _unstale_ it by commenting or
+            any activity in the last 170 days. You can _unstale_ it by commenting or
             removing the label. Otherwise, this issue will be closed in 10 days.
           stale-pr-message: >
             This pull request has automatically been marked as _stale_ because it has
@@ -25,7 +25,7 @@ jobs:
           close-issue-message: >
             This issue was closed automatically because it has been stale for 10 days
             with no activity.
-          days-before-stale: 100
+          days-before-stale: 170
           days-before-close: 10
           # Do not touch meta issues:
           exempt-issue-labels: meta,fridge,project management

.github/workflows/scripts/get_package_version_from_lockfile.py

@@ -0,0 +1,60 @@
+#!/usr/bin/env python3
+import sys
+
+if sys.version_info < (3, 11):
+    print("Python version 3.11 or higher required")
+    sys.exit(1)
+
+import tomllib
+
+
+def get_package_version(package_name: str, lockfile_path: str) -> str | None:
+    """Extract package version from poetry.lock file."""
+    try:
+        if lockfile_path == "-":
+            data = tomllib.load(sys.stdin.buffer)
+        else:
+            with open(lockfile_path, "rb") as f:
+                data = tomllib.load(f)
+    except FileNotFoundError:
+        print(f"Error: File '{lockfile_path}' not found", file=sys.stderr)
+        sys.exit(1)
+    except tomllib.TOMLDecodeError as e:
+        print(f"Error parsing TOML file: {e}", file=sys.stderr)
+        sys.exit(1)
+    except Exception as e:
+        print(f"Error reading file: {e}", file=sys.stderr)
+        sys.exit(1)
+
+    # Look for the package in the packages list
+    packages = data.get("package", [])
+    for package in packages:
+        if package.get("name", "").lower() == package_name.lower():
+            return package.get("version")
+
+    return None
+
+
+def main():
+    if len(sys.argv) not in (2, 3):
+        print(
+            "Usages: python get_package_version_from_lockfile.py <package name> [poetry.lock path]\n"
+            "        cat poetry.lock | python get_package_version_from_lockfile.py <package name> -",
+            file=sys.stderr,
+        )
+        sys.exit(1)
+
+    package_name = sys.argv[1]
+    lockfile_path = sys.argv[2] if len(sys.argv) == 3 else "poetry.lock"
+
+    version = get_package_version(package_name, lockfile_path)
+
+    if version:
+        print(version)
+    else:
+        print(f"Package '{package_name}' not found in {lockfile_path}", file=sys.stderr)
+        sys.exit(1)
+
+
+if __name__ == "__main__":
+    main()

.gitignore

@@ -176,3 +176,4 @@ autogpt_platform/backend/settings.py
 
 *.ign.*
 .test-contents
+.claude/settings.local.json

.pre-commit-config.yaml

@@ -17,7 +17,7 @@ repos:
         name: Detect secrets
         description: Detects high entropy strings that are likely to be passwords.
         files: ^autogpt_platform/
-        stages: [push]
+        stages: [pre-push]
 
   - repo: local
     # For proper type checking, all dependencies need to be up-to-date.
@@ -235,44 +235,44 @@ repos:
     hooks:
       - id: tsc
         name: Typecheck - AutoGPT Platform - Frontend
-        entry: bash -c 'cd autogpt_platform/frontend && npm run type-check'
+        entry: bash -c 'cd autogpt_platform/frontend && pnpm type-check'
         files: ^autogpt_platform/frontend/
         types: [file]
         language: system
         pass_filenames: false
 
-  - repo: local
-    hooks:
-      - id: pytest
-        name: Run tests - AutoGPT Platform - Backend
-        alias: pytest-platform-backend
-        entry: bash -c 'cd autogpt_platform/backend && poetry run pytest'
-        # include autogpt_libs source (since it's a path dependency) but exclude *_test.py files:
-        files: ^autogpt_platform/(backend/((backend|test)/|poetry\.lock$)|autogpt_libs/(autogpt_libs/.*(?<!_test)\.py|poetry\.lock)$)
-        language: system
-        pass_filenames: false
+  # - repo: local
+  #   hooks:
+  #     - id: pytest
+  #       name: Run tests - AutoGPT Platform - Backend
+  #       alias: pytest-platform-backend
+  #       entry: bash -c 'cd autogpt_platform/backend && poetry run pytest'
+  #       # include autogpt_libs source (since it's a path dependency) but exclude *_test.py files:
+  #       files: ^autogpt_platform/(backend/((backend|test)/|poetry\.lock$)|autogpt_libs/(autogpt_libs/.*(?<!_test)\.py|poetry\.lock)$)
+  #       language: system
+  #       pass_filenames: false
 
-      - id: pytest
-        name: Run tests - Classic - AutoGPT (excl. slow tests)
-        alias: pytest-classic-autogpt
-        entry: bash -c 'cd classic/original_autogpt && poetry run pytest --cov=autogpt -m "not slow" tests/unit tests/integration'
-        # include forge source (since it's a path dependency) but exclude *_test.py files:
-        files: ^(classic/original_autogpt/((autogpt|tests)/|poetry\.lock$)|classic/forge/(forge/.*(?<!_test)\.py|poetry\.lock)$)
-        language: system
-        pass_filenames: false
+  #     - id: pytest
+  #       name: Run tests - Classic - AutoGPT (excl. slow tests)
+  #       alias: pytest-classic-autogpt
+  #       entry: bash -c 'cd classic/original_autogpt && poetry run pytest --cov=autogpt -m "not slow" tests/unit tests/integration'
+  #       # include forge source (since it's a path dependency) but exclude *_test.py files:
+  #       files: ^(classic/original_autogpt/((autogpt|tests)/|poetry\.lock$)|classic/forge/(forge/.*(?<!_test)\.py|poetry\.lock)$)
+  #       language: system
+  #       pass_filenames: false
 
-      - id: pytest
-        name: Run tests - Classic - Forge (excl. slow tests)
-        alias: pytest-classic-forge
-        entry: bash -c 'cd classic/forge && poetry run pytest --cov=forge -m "not slow"'
-        files: ^classic/forge/(forge/|tests/|poetry\.lock$)
-        language: system
-        pass_filenames: false
+  #     - id: pytest
+  #       name: Run tests - Classic - Forge (excl. slow tests)
+  #       alias: pytest-classic-forge
+  #       entry: bash -c 'cd classic/forge && poetry run pytest --cov=forge -m "not slow"'
+  #       files: ^classic/forge/(forge/|tests/|poetry\.lock$)
+  #       language: system
+  #       pass_filenames: false
 
-      - id: pytest
-        name: Run tests - Classic - Benchmark
-        alias: pytest-classic-benchmark
-        entry: bash -c 'cd classic/benchmark && poetry run pytest --cov=benchmark'
-        files: ^classic/benchmark/(agbenchmark/|tests/|poetry\.lock$)
-        language: system
-        pass_filenames: false
+  #     - id: pytest
+  #       name: Run tests - Classic - Benchmark
+  #       alias: pytest-classic-benchmark
+  #       entry: bash -c 'cd classic/benchmark && poetry run pytest --cov=benchmark'
+  #       files: ^classic/benchmark/(agbenchmark/|tests/|poetry\.lock$)
+  #       language: system
+  #       pass_filenames: false

.vscode/launch.json

@@ -32,9 +32,9 @@
       "type": "debugpy",
       "request": "launch",
       "module": "backend.app",
-      // "env": {
-      //   "ENV": "dev"
-      // },
+      "env": {
+        "OBJC_DISABLE_INITIALIZE_FORK_SAFETY": "YES"
+      },
       "envFile": "${workspaceFolder}/backend/.env",
       "justMyCode": false,
       "cwd": "${workspaceFolder}/autogpt_platform/backend"

AGENTS.md

@@ -0,0 +1,53 @@
+# AutoGPT Platform Contribution Guide
+
+This guide provides context for Codex when updating the **autogpt_platform** folder.
+
+## Directory overview
+
+- `autogpt_platform/backend` – FastAPI based backend service.
+- `autogpt_platform/autogpt_libs` – Shared Python libraries.
+- `autogpt_platform/frontend` – Next.js + Typescript frontend.
+- `autogpt_platform/docker-compose.yml` – development stack.
+
+See `docs/content/platform/getting-started.md` for setup instructions.
+
+## Code style
+
+- Format Python code with `poetry run format`.
+- Format frontend code using `pnpm format`.
+
+## Testing
+
+- Backend: `poetry run test` (runs pytest with a docker based postgres + prisma).
+- Frontend: `pnpm test` or `pnpm test-ui` for Playwright tests. See `docs/content/platform/contributing/tests.md` for tips.
+
+Always run the relevant linters and tests before committing.
+Use conventional commit messages for all commits (e.g. `feat(backend): add API`).
+  Types:
+    - feat
+    - fix
+    - refactor
+    - ci
+    - dx (developer experience)
+  Scopes:
+    - platform
+      - platform/library
+      - platform/marketplace
+      - backend
+        - backend/executor
+      - frontend
+        - frontend/library
+        - frontend/marketplace
+      - blocks
+
+## Pull requests
+
+- Use the template in `.github/PULL_REQUEST_TEMPLATE.md`.
+- Rely on the pre-commit checks for linting and formatting
+- Fill out the **Changes** section and the checklist.
+- Use conventional commit titles with a scope (e.g. `feat(frontend): add feature`).
+- Keep out-of-scope changes under 20% of the PR.
+- Ensure PR descriptions are complete.
+- For changes touching `data/*.py`, validate user ID checks or explain why not needed.
+- If adding protected frontend routes, update `frontend/lib/supabase/middleware.ts`.
+- Use the linear ticket branch structure if given codex/open-1668-resume-dropped-runs

LICENSE

@@ -1,8 +1,5 @@
-All portions of this repository are under one of two licenses.
-
-The all files outside of the autogpt_platform folder are under the MIT License below. 
-
-The autogpt_platform folder is under the Polyform Shield License below.
+All portions of this repository are under one of two licenses. The majority of the AutoGPT repository is under the MIT License below. The autogpt_platform folder is under the
+Polyform Shield License. 
 
 
 MIT License
@@ -30,169 +27,3 @@ AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
 LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
 OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
 SOFTWARE.
-
-
-# PolyForm Shield License 1.0.0
-
-<https://polyformproject.org/licenses/shield/1.0.0>
-
-## Acceptance
-
-In order to get any license under these terms, you must agree
-to them as both strict obligations and conditions to all
-your licenses.
-
-## Copyright License
-
-The licensor grants you a copyright license for the
-software to do everything you might do with the software
-that would otherwise infringe the licensor's copyright
-in it for any permitted purpose.  However, you may
-only distribute the software according to [Distribution
-License](#distribution-license) and make changes or new works
-based on the software according to [Changes and New Works
-License](#changes-and-new-works-license).
-
-## Distribution License
-
-The licensor grants you an additional copyright license
-to distribute copies of the software.  Your license
-to distribute covers distributing the software with
-changes and new works permitted by [Changes and New Works
-License](#changes-and-new-works-license).
-
-## Notices
-
-You must ensure that anyone who gets a copy of any part of
-the software from you also gets a copy of these terms or the
-URL for them above, as well as copies of any plain-text lines
-beginning with `Required Notice:` that the licensor provided
-with the software.  For example:
-
-> Required Notice: Copyright Yoyodyne, Inc. (http://example.com)
-
-## Changes and New Works License
-
-The licensor grants you an additional copyright license to
-make changes and new works based on the software for any
-permitted purpose.
-
-## Patent License
-
-The licensor grants you a patent license for the software that
-covers patent claims the licensor can license, or becomes able
-to license, that you would infringe by using the software.
-
-## Noncompete
-
-Any purpose is a permitted purpose, except for providing any
-product that competes with the software or any product the
-licensor or any of its affiliates provides using the software.
-
-## Competition
-
-Goods and services compete even when they provide functionality
-through different kinds of interfaces or for different technical
-platforms.  Applications can compete with services, libraries
-with plugins, frameworks with development tools, and so on,
-even if they're written in different programming languages
-or for different computer architectures.  Goods and services
-compete even when provided free of charge.  If you market a
-product as a practical substitute for the software or another
-product, it definitely competes.
-
-## New Products
-
-If you are using the software to provide a product that does
-not compete, but the licensor or any of its affiliates brings
-your product into competition by providing a new version of
-the software or another product using the software, you may
-continue using versions of the software available under these
-terms beforehand to provide your competing product, but not
-any later versions.
-
-## Discontinued Products
-
-You may begin using the software to compete with a product
-or service that the licensor or any of its affiliates has
-stopped providing, unless the licensor includes a plain-text
-line beginning with `Licensor Line of Business:` with the
-software that mentions that line of business.  For example:
-
-> Licensor Line of Business: YoyodyneCMS Content Management
-System (http://example.com/cms)
-
-## Sales of Business
-
-If the licensor or any of its affiliates sells a line of
-business developing the software or using the software
-to provide a product, the buyer can also enforce
-[Noncompete](#noncompete) for that product.
-
-## Fair Use
-
-You may have "fair use" rights for the software under the
-law. These terms do not limit them.
-
-## No Other Rights
-
-These terms do not allow you to sublicense or transfer any of
-your licenses to anyone else, or prevent the licensor from
-granting licenses to anyone else.  These terms do not imply
-any other licenses.
-
-## Patent Defense
-
-If you make any written claim that the software infringes or
-contributes to infringement of any patent, your patent license
-for the software granted under these terms ends immediately. If
-your company makes such a claim, your patent license ends
-immediately for work on behalf of your company.
-
-## Violations
-
-The first time you are notified in writing that you have
-violated any of these terms, or done anything with the software
-not covered by your licenses, your licenses can nonetheless
-continue if you come into full compliance with these terms,
-and take practical steps to correct past violations, within
-32 days of receiving notice.  Otherwise, all your licenses
-end immediately.
-
-## No Liability
-
-***As far as the law allows, the software comes as is, without
-any warranty or condition, and the licensor will not be liable
-to you for any damages arising out of these terms or the use
-or nature of the software, under any kind of legal claim.***
-
-## Definitions
-
-The **licensor** is the individual or entity offering these
-terms, and the **software** is the software the licensor makes
-available under these terms.
-
-A **product** can be a good or service, or a combination
-of them.
-
-**You** refers to the individual or entity agreeing to these
-terms.
-
-**Your company** is any legal entity, sole proprietorship,
-or other kind of organization that you work for, plus all
-its affiliates.
-
-**Affiliates** means the other organizations than an
-organization has control over, is under the control of, or is
-under common control with.
-
-**Control** means ownership of substantially all the assets of
-an entity, or the power to direct its management and policies
-by vote, contract, or otherwise.  Control can be direct or
-indirect.
-
-**Your licenses** are all the licenses granted to you for the
-software under these terms.
-
-**Use** means anything you do with the software requiring one
-of your licenses.

README.md

@@ -2,6 +2,7 @@
 
 [![Discord Follow](https://dcbadge.vercel.app/api/server/autogpt?style=flat)](https://discord.gg/autogpt)  
 [![Twitter Follow](https://img.shields.io/twitter/follow/Auto_GPT?style=social)](https://twitter.com/Auto_GPT)  
+[![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg)](https://opensource.org/licenses/MIT)
 
 **AutoGPT** is a powerful platform that allows you to create, deploy, and manage continuous AI agents that automate complex workflows. 
 
@@ -14,7 +15,38 @@
 > Setting up and hosting the AutoGPT Platform yourself is a technical process. 
 > If you'd rather something that just works, we recommend [joining the waitlist](https://bit.ly/3ZDijAI) for the cloud-hosted beta.
 
-https://github.com/user-attachments/assets/d04273a5-b36a-4a37-818e-f631ce72d603
+### System Requirements
+
+Before proceeding with the installation, ensure your system meets the following requirements:
+
+#### Hardware Requirements
+- CPU: 4+ cores recommended
+- RAM: Minimum 8GB, 16GB recommended
+- Storage: At least 10GB of free space
+
+#### Software Requirements
+- Operating Systems:
+  - Linux (Ubuntu 20.04 or newer recommended)
+  - macOS (10.15 or newer)
+  - Windows 10/11 with WSL2
+- Required Software (with minimum versions):
+  - Docker Engine (20.10.0 or newer)
+  - Docker Compose (2.0.0 or newer)
+  - Git (2.30 or newer)
+  - Node.js (16.x or newer)
+  - npm (8.x or newer)
+  - VSCode (1.60 or newer) or any modern code editor
+
+#### Network Requirements
+- Stable internet connection
+- Access to required ports (will be configured in Docker)
+- Ability to make outbound HTTPS connections
+
+### Updated Setup Instructions:
+We've moved to a fully maintained and regularly updated documentation site.
+
+👉 [Follow the official self-hosting guide here](https://docs.agpt.co/platform/getting-started/)
+
 
 This tutorial assumes you have Docker, VSCode, git and npm installed.
 
@@ -79,7 +111,7 @@ Be part of the revolution! **AutoGPT** is here to stay, at the forefront of AI i
 
 **Licensing:**
 
-MIT License: All files outside of autogpt_platform folder are under the MIT License.
+MIT License: The majority of the AutoGPT repository is under the MIT License.
 
 Polyform Shield License: This license applies to the autogpt_platform folder. 
 
@@ -147,7 +179,7 @@ Just clone the repo, install dependencies with `./run setup`, and you should be
 
 [![Join us on Discord](https://invidget.switchblade.xyz/autogpt)](https://discord.gg/autogpt)
 
-To report a bug or request a feature, create a [GitHub Issue](https://github.com/Significant-Gravitas/AutoGPT/issues/new/choose). Please ensure someone else hasn’t created an issue for the same topic.
+To report a bug or request a feature, create a [GitHub Issue](https://github.com/Significant-Gravitas/AutoGPT/issues/new/choose). Please ensure someone else hasn't created an issue for the same topic.
 
 ## 🤝 Sister projects
 

autogpt_platform/CLAUDE.md

@@ -0,0 +1,132 @@
+# CLAUDE.md
+
+This file provides guidance to Claude Code (claude.ai/code) when working with code in this repository.
+
+## Repository Overview
+
+AutoGPT Platform is a monorepo containing:
+- **Backend** (`/backend`): Python FastAPI server with async support
+- **Frontend** (`/frontend`): Next.js React application
+- **Shared Libraries** (`/autogpt_libs`): Common Python utilities
+
+## Essential Commands
+
+### Backend Development
+```bash
+# Install dependencies
+cd backend && poetry install
+
+# Run database migrations
+poetry run prisma migrate dev
+
+# Start all services (database, redis, rabbitmq)
+docker compose up -d
+
+# Run the backend server
+poetry run serve
+
+# Run tests
+poetry run test
+
+# Run specific test
+poetry run pytest path/to/test_file.py::test_function_name
+
+# Lint and format
+poetry run format  # Black + isort
+poetry run lint    # ruff
+```
+More details can be found in TESTING.md
+
+#### Creating/Updating Snapshots
+
+When you first write a test or when the expected output changes:
+
+```bash
+poetry run pytest path/to/test.py --snapshot-update
+```
+
+⚠️ **Important**: Always review snapshot changes before committing! Use `git diff` to verify the changes are expected.
+
+
+### Frontend Development
+```bash
+# Install dependencies
+cd frontend && npm install
+
+# Start development server
+npm run dev
+
+# Run E2E tests
+npm run test
+
+# Run Storybook for component development
+npm run storybook
+
+# Build production
+npm run build
+
+# Type checking
+npm run type-check
+```
+
+## Architecture Overview
+
+### Backend Architecture
+- **API Layer**: FastAPI with REST and WebSocket endpoints
+- **Database**: PostgreSQL with Prisma ORM, includes pgvector for embeddings
+- **Queue System**: RabbitMQ for async task processing
+- **Execution Engine**: Separate executor service processes agent workflows
+- **Authentication**: JWT-based with Supabase integration
+
+### Frontend Architecture
+- **Framework**: Next.js App Router with React Server Components
+- **State Management**: React hooks + Supabase client for real-time updates
+- **Workflow Builder**: Visual graph editor using @xyflow/react
+- **UI Components**: Radix UI primitives with Tailwind CSS styling
+- **Feature Flags**: LaunchDarkly integration
+
+### Key Concepts
+1. **Agent Graphs**: Workflow definitions stored as JSON, executed by the backend
+2. **Blocks**: Reusable components in `/backend/blocks/` that perform specific tasks
+3. **Integrations**: OAuth and API connections stored per user
+4. **Store**: Marketplace for sharing agent templates
+
+### Testing Approach
+- Backend uses pytest with snapshot testing for API responses
+- Test files are colocated with source files (`*_test.py`)
+- Frontend uses Playwright for E2E tests
+- Component testing via Storybook
+
+### Database Schema
+Key models (defined in `/backend/schema.prisma`):
+- `User`: Authentication and profile data
+- `AgentGraph`: Workflow definitions with version control
+- `AgentGraphExecution`: Execution history and results
+- `AgentNode`: Individual nodes in a workflow
+- `StoreListing`: Marketplace listings for sharing agents
+
+### Environment Configuration
+- Backend: `.env` file in `/backend`
+- Frontend: `.env.local` file in `/frontend`
+- Both require Supabase credentials and API keys for various services
+
+### Common Development Tasks
+
+**Adding a new block:**
+1. Create new file in `/backend/backend/blocks/`
+2. Inherit from `Block` base class
+3. Define input/output schemas
+4. Implement `run` method
+5. Register in block registry
+
+**Modifying the API:**
+1. Update route in `/backend/backend/server/routers/`
+2. Add/update Pydantic models in same directory
+3. Write tests alongside the route file
+4. Run `poetry run test` to verify
+
+**Frontend feature development:**
+1. Components go in `/frontend/src/components/`
+2. Use existing UI components from `/frontend/src/components/ui/`
+3. Add Storybook stories for new components
+4. Test with Playwright if user-facing

autogpt_platform/Contributor License Agreement (CLA).md

@@ -2,7 +2,7 @@
 
 **Contributor License Agreement (“Agreement”)**
 
-Thank you for your interest in the AutoGPT project at [https://github.com/Significant-Gravitas/AutoGPT](https://github.com/Significant-Gravitas/AutoGPT) stewarded by Determinist Ltd (“**Determinist**”), with offices at 3rd Floor 1 Ashley Road, Altrincham, Cheshire, WA14 2DT, United Kingdom. The form of license below is a document that clarifies the terms under which You, the person listed below, may contribute software code described below (the “**Contribution**”) to the project.  We appreciate your participation in our project, and your help in improving our products, so we want you to understand what will be done with the Contributions.  This license is for your protection as well as the protection of Determinist and its licensees; it does not change your rights to use your own Contributions for any other purpose.        
+Thank you for your interest in the AutoGPT open source project at [https://github.com/Significant-Gravitas/AutoGPT](https://github.com/Significant-Gravitas/AutoGPT) stewarded by Determinist Ltd (“**Determinist**”), with offices at 3rd Floor 1 Ashley Road, Altrincham, Cheshire, WA14 2DT, United Kingdom. The form of license below is a document that clarifies the terms under which You, the person listed below, may contribute software code described below (the “**Contribution**”) to the project.  We appreciate your participation in our project, and your help in improving our products, so we want you to understand what will be done with the Contributions.  This license is for your protection as well as the protection of Determinist and its licensees; it does not change your rights to use your own Contributions for any other purpose.        
 
 By submitting a Pull Request which modifies the content of the “autogpt\_platform” folder at [https://github.com/Significant-Gravitas/AutoGPT/tree/master/autogpt\_platform](https://github.com/Significant-Gravitas/AutoGPT/tree/master/autogpt_platform), You hereby agree:  
 

autogpt_platform/README.md

@@ -15,44 +15,57 @@ Welcome to the AutoGPT Platform - a powerful system for creating and running AI
 To run the AutoGPT Platform, follow these steps:
 
 1. Clone this repository to your local machine and navigate to the `autogpt_platform` directory within the repository:
+
    ```
    git clone <https://github.com/Significant-Gravitas/AutoGPT.git | git@github.com:Significant-Gravitas/AutoGPT.git>
    cd AutoGPT/autogpt_platform
    ```
 
 2. Run the following command:
+
    ```
    cp .env.example .env
    ```
+
    This command will copy the `.env.example` file to `.env`. You can modify the `.env` file to add your own environment variables.
 
 3. Run the following command:
+
    ```
    docker compose up -d
    ```
+
    This command will start all the necessary backend services defined in the `docker-compose.yml` file in detached mode.
 
 4. Navigate to `frontend` within the `autogpt_platform` directory:
+
    ```
    cd frontend
    ```
+
    You will need to run your frontend application separately on your local machine.
 
-5. Run the following command: 
+5. Run the following command:
+
    ```
    cp .env.example .env.local
    ```
+
    This command will copy the `.env.example` file to `.env.local` in the `frontend` directory. You can modify the `.env.local` within this folder to add your own environment variables for the frontend application.
 
 6. Run the following command:
+
+   Enable corepack and install dependencies by running:
+
    ```
-   npm install
-   npm run dev
+   corepack enable
+   pnpm i
    ```
-   This command will install the necessary dependencies and start the frontend application in development mode.
-   If you are using Yarn, you can run the following commands instead:
+
+   Then start the frontend application in development mode:
+
    ```
-   yarn install && yarn dev
+   pnpm dev
    ```
 
 7. Open your browser and navigate to `http://localhost:3000` to access the AutoGPT Platform frontend.
@@ -68,43 +81,52 @@ Here are some useful Docker Compose commands for managing your AutoGPT Platform:
 - `docker compose down`: Stop and remove containers, networks, and volumes.
 - `docker compose watch`: Watch for changes in your services and automatically update them.
 
-
 ### Sample Scenarios
 
 Here are some common scenarios where you might use multiple Docker Compose commands:
 
 1. Updating and restarting a specific service:
+
    ```
    docker compose build api_srv
    docker compose up -d --no-deps api_srv
    ```
+
    This rebuilds the `api_srv` service and restarts it without affecting other services.
 
 2. Viewing logs for troubleshooting:
+
    ```
    docker compose logs -f api_srv ws_srv
    ```
+
    This shows and follows the logs for both `api_srv` and `ws_srv` services.
 
 3. Scaling a service for increased load:
+
    ```
    docker compose up -d --scale executor=3
    ```
+
    This scales the `executor` service to 3 instances to handle increased load.
 
 4. Stopping the entire system for maintenance:
+
    ```
    docker compose stop
    docker compose rm -f
    docker compose pull
    docker compose up -d
    ```
+
    This stops all services, removes containers, pulls the latest images, and restarts the system.
 
 5. Developing with live updates:
+
    ```
    docker compose watch
    ```
+
    This watches for changes in your code and automatically updates the relevant services.
 
 6. Checking the status of services:
@@ -115,7 +137,6 @@ Here are some common scenarios where you might use multiple Docker Compose comma
 
 These scenarios demonstrate how to use Docker Compose commands in combination to manage your AutoGPT Platform effectively.
 
-
 ### Persisting Data
 
 To persist data for PostgreSQL and Redis, you can modify the `docker-compose.yml` file to add volumes. Here's how:

autogpt_platform/autogpt_libs/README.md

@@ -1,3 +1,3 @@
 # AutoGPT Libs
 
-This is a new project to store shared functionality across different services in NextGen AutoGPT (e.g. authentication)
+This is a new project to store shared functionality across different services in the AutoGPT Platform (e.g. authentication)

autogpt_platform/autogpt_libs/autogpt_libs/api_key/key_manager.py

@@ -31,4 +31,5 @@ class APIKeyManager:
         """Verify if a provided API key matches the stored hash."""
         if not provided_key.startswith(self.PREFIX):
             return False
-        return hashlib.sha256(provided_key.encode()).hexdigest() == stored_hash
+        provided_hash = hashlib.sha256(provided_key.encode()).hexdigest()
+        return secrets.compare_digest(provided_hash, stored_hash)

autogpt_platform/autogpt_libs/autogpt_libs/auth/middleware.py

@@ -1,5 +1,6 @@
 import inspect
 import logging
+import secrets
 from typing import Any, Callable, Optional
 
 from fastapi import HTTPException, Request, Security
@@ -16,7 +17,7 @@ logger = logging.getLogger(__name__)
 async def auth_middleware(request: Request):
     if not settings.ENABLE_AUTH:
         # If authentication is disabled, allow the request to proceed
-        logger.warn("Auth disabled")
+        logger.warning("Auth disabled")
         return {}
 
     security = HTTPBearer()
@@ -93,7 +94,11 @@ class APIKeyValidator:
         self.error_message = error_message
 
     async def default_validator(self, api_key: str) -> bool:
-        return api_key == self.expected_token
+        if not self.expected_token:
+            raise ValueError(
+                "Expected Token Required to be set when uisng API Key Validator default validation"
+            )
+        return secrets.compare_digest(api_key, self.expected_token)
 
     async def __call__(
         self, request: Request, api_key: str = Security(APIKeyHeader)

autogpt_platform/autogpt_libs/autogpt_libs/logging/config.py

@@ -8,7 +8,7 @@ from pydantic import Field, field_validator
 from pydantic_settings import BaseSettings, SettingsConfigDict
 
 from .filters import BelowLevelFilter
-from .formatters import AGPTFormatter, StructuredLoggingFormatter
+from .formatters import AGPTFormatter
 
 LOG_DIR = Path(__file__).parent.parent.parent.parent / "logs"
 LOG_FILE = "activity.log"
@@ -81,9 +81,26 @@ def configure_logging(force_cloud_logging: bool = False) -> None:
     """
 
     config = LoggingConfig()
-
     log_handlers: list[logging.Handler] = []
 
+    # Console output handlers
+    stdout = logging.StreamHandler(stream=sys.stdout)
+    stdout.setLevel(config.level)
+    stdout.addFilter(BelowLevelFilter(logging.WARNING))
+    if config.level == logging.DEBUG:
+        stdout.setFormatter(AGPTFormatter(DEBUG_LOG_FORMAT))
+    else:
+        stdout.setFormatter(AGPTFormatter(SIMPLE_LOG_FORMAT))
+
+    stderr = logging.StreamHandler()
+    stderr.setLevel(logging.WARNING)
+    if config.level == logging.DEBUG:
+        stderr.setFormatter(AGPTFormatter(DEBUG_LOG_FORMAT))
+    else:
+        stderr.setFormatter(AGPTFormatter(SIMPLE_LOG_FORMAT))
+
+    log_handlers += [stdout, stderr]
+
     # Cloud logging setup
     if config.enable_cloud_logging or force_cloud_logging:
         import google.cloud.logging
@@ -97,26 +114,7 @@ def configure_logging(force_cloud_logging: bool = False) -> None:
             transport=SyncTransport,
         )
         cloud_handler.setLevel(config.level)
-        cloud_handler.setFormatter(StructuredLoggingFormatter())
         log_handlers.append(cloud_handler)
-    else:
-        # Console output handlers
-        stdout = logging.StreamHandler(stream=sys.stdout)
-        stdout.setLevel(config.level)
-        stdout.addFilter(BelowLevelFilter(logging.WARNING))
-        if config.level == logging.DEBUG:
-            stdout.setFormatter(AGPTFormatter(DEBUG_LOG_FORMAT))
-        else:
-            stdout.setFormatter(AGPTFormatter(SIMPLE_LOG_FORMAT))
-
-        stderr = logging.StreamHandler()
-        stderr.setLevel(logging.WARNING)
-        if config.level == logging.DEBUG:
-            stderr.setFormatter(AGPTFormatter(DEBUG_LOG_FORMAT))
-        else:
-            stderr.setFormatter(AGPTFormatter(SIMPLE_LOG_FORMAT))
-
-        log_handlers += [stdout, stderr]
 
     # File logging setup
     if config.enable_file_logging:

autogpt_platform/autogpt_libs/autogpt_libs/logging/formatters.py

@@ -1,7 +1,6 @@
 import logging
 
 from colorama import Fore, Style
-from google.cloud.logging_v2.handlers import CloudLoggingFilter, StructuredLogHandler
 
 from .utils import remove_color_codes
 
@@ -80,16 +79,3 @@ class AGPTFormatter(FancyConsoleFormatter):
             return remove_color_codes(super().format(record))
         else:
             return super().format(record)
-
-
-class StructuredLoggingFormatter(StructuredLogHandler, logging.Formatter):
-    def __init__(self):
-        # Set up CloudLoggingFilter to add diagnostic info to the log records
-        self.cloud_logging_filter = CloudLoggingFilter()
-
-        # Init StructuredLogHandler
-        super().__init__()
-
-    def format(self, record: logging.LogRecord) -> str:
-        self.cloud_logging_filter.filter(record)
-        return super().format(record)

autogpt_platform/autogpt_libs/autogpt_libs/logging/utils.py

@@ -2,6 +2,7 @@ import logging
 import re
 from typing import Any
 
+import uvicorn.config
 from colorama import Fore
 
 
@@ -25,3 +26,14 @@ def print_attribute(
             "color": value_color,
         },
     )
+
+
+def generate_uvicorn_config():
+    """
+    Generates a uvicorn logging config that silences uvicorn's default logging and tells it to use the native logging module.
+    """
+    log_config = dict(uvicorn.config.LOGGING_CONFIG)
+    log_config["loggers"]["uvicorn"] = {"handlers": []}
+    log_config["loggers"]["uvicorn.error"] = {"handlers": []}
+    log_config["loggers"]["uvicorn.access"] = {"handlers": []}
+    return log_config

autogpt_platform/autogpt_libs/autogpt_libs/utils/cache.py

@@ -1,20 +1,59 @@
+import inspect
 import threading
-from typing import Callable, ParamSpec, TypeVar
+from typing import Awaitable, Callable, ParamSpec, TypeVar, cast, overload
 
 P = ParamSpec("P")
 R = TypeVar("R")
 
 
-def thread_cached(func: Callable[P, R]) -> Callable[P, R]:
+@overload
+def thread_cached(func: Callable[P, Awaitable[R]]) -> Callable[P, Awaitable[R]]: ...
+
+
+@overload
+def thread_cached(func: Callable[P, R]) -> Callable[P, R]: ...
+
+
+def thread_cached(
+    func: Callable[P, R] | Callable[P, Awaitable[R]],
+) -> Callable[P, R] | Callable[P, Awaitable[R]]:
     thread_local = threading.local()
 
-    def wrapper(*args: P.args, **kwargs: P.kwargs) -> R:
-        cache = getattr(thread_local, "cache", None)
-        if cache is None:
-            cache = thread_local.cache = {}
-        key = (args, tuple(sorted(kwargs.items())))
-        if key not in cache:
-            cache[key] = func(*args, **kwargs)
-        return cache[key]
+    def _clear():
+        if hasattr(thread_local, "cache"):
+            del thread_local.cache
 
-    return wrapper
+    if inspect.iscoroutinefunction(func):
+
+        async def async_wrapper(*args: P.args, **kwargs: P.kwargs) -> R:
+            cache = getattr(thread_local, "cache", None)
+            if cache is None:
+                cache = thread_local.cache = {}
+            key = (args, tuple(sorted(kwargs.items())))
+            if key not in cache:
+                cache[key] = await cast(Callable[P, Awaitable[R]], func)(
+                    *args, **kwargs
+                )
+            return cache[key]
+
+        setattr(async_wrapper, "clear_cache", _clear)
+        return async_wrapper
+
+    else:
+
+        def sync_wrapper(*args: P.args, **kwargs: P.kwargs) -> R:
+            cache = getattr(thread_local, "cache", None)
+            if cache is None:
+                cache = thread_local.cache = {}
+            key = (args, tuple(sorted(kwargs.items())))
+            if key not in cache:
+                cache[key] = func(*args, **kwargs)
+            return cache[key]
+
+        setattr(sync_wrapper, "clear_cache", _clear)
+        return sync_wrapper
+
+
+def clear_thread_cache(func: Callable) -> None:
+    if clear := getattr(func, "clear_cache", None):
+        clear()

autogpt_platform/autogpt_libs/autogpt_libs/utils/synchronize.py

@@ -1,15 +1,15 @@
-from contextlib import contextmanager
-from threading import Lock
+import asyncio
+from contextlib import asynccontextmanager
 from typing import TYPE_CHECKING, Any
 
 from expiringdict import ExpiringDict
 
 if TYPE_CHECKING:
-    from redis import Redis
-    from redis.lock import Lock as RedisLock
+    from redis.asyncio import Redis as AsyncRedis
+    from redis.asyncio.lock import Lock as AsyncRedisLock
 
 
-class RedisKeyedMutex:
+class AsyncRedisKeyedMutex:
     """
     This class provides a mutex that can be locked and unlocked by a specific key,
     using Redis as a distributed locking provider.
@@ -17,41 +17,45 @@ class RedisKeyedMutex:
     in case the key is not unlocked for a specified duration, to prevent memory leaks.
     """
 
-    def __init__(self, redis: "Redis", timeout: int | None = 60):
+    def __init__(self, redis: "AsyncRedis", timeout: int | None = 60):
         self.redis = redis
         self.timeout = timeout
-        self.locks: dict[Any, "RedisLock"] = ExpiringDict(
+        self.locks: dict[Any, "AsyncRedisLock"] = ExpiringDict(
             max_len=6000, max_age_seconds=self.timeout
         )
-        self.locks_lock = Lock()
+        self.locks_lock = asyncio.Lock()
 
-    @contextmanager
-    def locked(self, key: Any):
-        lock = self.acquire(key)
+    @asynccontextmanager
+    async def locked(self, key: Any):
+        lock = await self.acquire(key)
         try:
             yield
         finally:
-            if lock.locked():
-                lock.release()
+            if (await lock.locked()) and (await lock.owned()):
+                await lock.release()
 
-    def acquire(self, key: Any) -> "RedisLock":
+    async def acquire(self, key: Any) -> "AsyncRedisLock":
         """Acquires and returns a lock with the given key"""
-        with self.locks_lock:
+        async with self.locks_lock:
             if key not in self.locks:
                 self.locks[key] = self.redis.lock(
                     str(key), self.timeout, thread_local=False
                 )
             lock = self.locks[key]
-        lock.acquire()
+        await lock.acquire()
         return lock
 
-    def release(self, key: Any):
-        if (lock := self.locks.get(key)) and lock.locked() and lock.owned():
-            lock.release()
+    async def release(self, key: Any):
+        if (
+            (lock := self.locks.get(key))
+            and (await lock.locked())
+            and (await lock.owned())
+        ):
+            await lock.release()
 
-    def release_all_locks(self):
+    async def release_all_locks(self):
         """Call this on process termination to ensure all locks are released"""
-        self.locks_lock.acquire(blocking=False)
-        for lock in self.locks.values():
-            if lock.locked() and lock.owned():
-                lock.release()
+        async with self.locks_lock:
+            for lock in self.locks.values():
+                if (await lock.locked()) and (await lock.owned()):
+                    await lock.release()

autogpt_platform/autogpt_libs/poetry.lock

@@ -323,6 +323,21 @@ files = [
     {file = "charset_normalizer-3.3.2-py3-none-any.whl", hash = "sha256:3e4d1f6587322d2788836a99c69062fbb091331ec940e02d12d179c1d53e25fc"},
 ]
 
+[[package]]
+name = "click"
+version = "8.2.1"
+description = "Composable command line interface toolkit"
+optional = false
+python-versions = ">=3.10"
+groups = ["main"]
+files = [
+    {file = "click-8.2.1-py3-none-any.whl", hash = "sha256:61a3265b914e850b85317d0b3109c7f8cd35a670f963866005d6ef1d5175a12b"},
+    {file = "click-8.2.1.tar.gz", hash = "sha256:27c491cc05d968d271d5a1db13e3b5a184636d9d930f148c50b038f0d0646202"},
+]
+
+[package.dependencies]
+colorama = {version = "*", markers = "platform_system == \"Windows\""}
+
 [[package]]
 name = "colorama"
 version = "0.4.6"
@@ -399,6 +414,27 @@ files = [
 [package.extras]
 tests = ["coverage", "coveralls", "dill", "mock", "nose"]
 
+[[package]]
+name = "fastapi"
+version = "0.115.12"
+description = "FastAPI framework, high performance, easy to learn, fast to code, ready for production"
+optional = false
+python-versions = ">=3.8"
+groups = ["main"]
+files = [
+    {file = "fastapi-0.115.12-py3-none-any.whl", hash = "sha256:e94613d6c05e27be7ffebdd6ea5f388112e5e430c8f7d6494a9d1d88d43e814d"},
+    {file = "fastapi-0.115.12.tar.gz", hash = "sha256:1e2c2a2646905f9e83d32f04a3f86aff4a286669c6c950ca95b5fd68c2602681"},
+]
+
+[package.dependencies]
+pydantic = ">=1.7.4,<1.8 || >1.8,<1.8.1 || >1.8.1,<2.0.0 || >2.0.0,<2.0.1 || >2.0.1,<2.1.0 || >2.1.0,<3.0.0"
+starlette = ">=0.40.0,<0.47.0"
+typing-extensions = ">=4.8.0"
+
+[package.extras]
+all = ["email-validator (>=2.0.0)", "fastapi-cli[standard] (>=0.0.5)", "httpx (>=0.23.0)", "itsdangerous (>=1.1.0)", "jinja2 (>=3.1.5)", "orjson (>=3.2.1)", "pydantic-extra-types (>=2.0.0)", "pydantic-settings (>=2.0.0)", "python-multipart (>=0.0.18)", "pyyaml (>=5.3.1)", "ujson (>=4.0.1,!=4.0.2,!=4.1.0,!=4.2.0,!=4.3.0,!=5.0.0,!=5.1.0)", "uvicorn[standard] (>=0.12.0)"]
+standard = ["email-validator (>=2.0.0)", "fastapi-cli[standard] (>=0.0.5)", "httpx (>=0.23.0)", "jinja2 (>=3.1.5)", "python-multipart (>=0.0.18)", "uvicorn[standard] (>=0.12.0)"]
+
 [[package]]
 name = "frozenlist"
 version = "1.4.1"
@@ -562,19 +598,19 @@ protobuf = ">=3.20.2,<4.21.0 || >4.21.0,<4.21.1 || >4.21.1,<4.21.2 || >4.21.2,<4
 
 [[package]]
 name = "google-cloud-audit-log"
-version = "0.3.0"
+version = "0.3.2"
 description = "Google Cloud Audit Protos"
 optional = false
 python-versions = ">=3.7"
 groups = ["main"]
 files = [
-    {file = "google_cloud_audit_log-0.3.0-py2.py3-none-any.whl", hash = "sha256:8340793120a1d5aa143605def8704ecdcead15106f754ef1381ae3bab533722f"},
-    {file = "google_cloud_audit_log-0.3.0.tar.gz", hash = "sha256:901428b257020d8c1d1133e0fa004164a555e5a395c7ca3cdbb8486513df3a65"},
+    {file = "google_cloud_audit_log-0.3.2-py3-none-any.whl", hash = "sha256:daaedfb947a0d77f524e1bd2b560242ab4836fe1afd6b06b92f152b9658554ed"},
+    {file = "google_cloud_audit_log-0.3.2.tar.gz", hash = "sha256:2598f1533a7d7cdd6c7bf448c12e5519c1d53162d78784e10bcdd1df67791bc3"},
 ]
 
 [package.dependencies]
-googleapis-common-protos = ">=1.56.2,<2.0dev"
-protobuf = ">=3.20.2,<4.21.1 || >4.21.1,<4.21.2 || >4.21.2,<4.21.3 || >4.21.3,<4.21.4 || >4.21.4,<4.21.5 || >4.21.5,<6.0.0dev"
+googleapis-common-protos = ">=1.56.2,<2.0.0"
+protobuf = ">=3.20.2,<4.21.1 || >4.21.1,<4.21.2 || >4.21.2,<4.21.3 || >4.21.3,<4.21.4 || >4.21.4,<4.21.5 || >4.21.5,<7.0.0"
 
 [[package]]
 name = "google-cloud-core"
@@ -597,30 +633,30 @@ grpc = ["grpcio (>=1.38.0,<2.0dev)", "grpcio-status (>=1.38.0,<2.0.dev0)"]
 
 [[package]]
 name = "google-cloud-logging"
-version = "3.11.4"
+version = "3.12.1"
 description = "Stackdriver Logging API client library"
 optional = false
 python-versions = ">=3.7"
 groups = ["main"]
 files = [
-    {file = "google_cloud_logging-3.11.4-py2.py3-none-any.whl", hash = "sha256:1d465ac62df29fb94bba4d6b4891035e57d573d84541dd8a40eebbc74422b2f0"},
-    {file = "google_cloud_logging-3.11.4.tar.gz", hash = "sha256:32305d989323f3c58603044e2ac5d9cf23e9465ede511bbe90b4309270d3195c"},
+    {file = "google_cloud_logging-3.12.1-py2.py3-none-any.whl", hash = "sha256:6817878af76ec4e7568976772839ab2c43ddfd18fbbf2ce32b13ef549cd5a862"},
+    {file = "google_cloud_logging-3.12.1.tar.gz", hash = "sha256:36efc823985055b203904e83e1c8f9f999b3c64270bcda39d57386ca4effd678"},
 ]
 
 [package.dependencies]
-google-api-core = {version = ">=1.34.1,<2.0.dev0 || >=2.11.dev0,<3.0.0dev", extras = ["grpc"]}
-google-auth = ">=2.14.1,<2.24.0 || >2.24.0,<2.25.0 || >2.25.0,<3.0.0dev"
-google-cloud-appengine-logging = ">=0.1.3,<2.0.0dev"
-google-cloud-audit-log = ">=0.2.4,<1.0.0dev"
-google-cloud-core = ">=2.0.0,<3.0.0dev"
-grpc-google-iam-v1 = ">=0.12.4,<1.0.0dev"
+google-api-core = {version = ">=1.34.1,<2.0.dev0 || >=2.11.dev0,<3.0.0", extras = ["grpc"]}
+google-auth = ">=2.14.1,<2.24.0 || >2.24.0,<2.25.0 || >2.25.0,<3.0.0"
+google-cloud-appengine-logging = ">=0.1.3,<2.0.0"
+google-cloud-audit-log = ">=0.3.1,<1.0.0"
+google-cloud-core = ">=2.0.0,<3.0.0"
+grpc-google-iam-v1 = ">=0.12.4,<1.0.0"
 opentelemetry-api = ">=1.9.0"
 proto-plus = [
-    {version = ">=1.25.0,<2.0.0dev", markers = "python_version >= \"3.13\""},
-    {version = ">=1.22.2,<2.0.0dev", markers = "python_version >= \"3.11\" and python_version < \"3.13\""},
-    {version = ">=1.22.0,<2.0.0dev", markers = "python_version < \"3.11\""},
+    {version = ">=1.25.0,<2.0.0", markers = "python_version >= \"3.13\""},
+    {version = ">=1.22.2,<2.0.0", markers = "python_version >= \"3.11\" and python_version < \"3.13\""},
+    {version = ">=1.22.0,<2.0.0", markers = "python_version < \"3.11\""},
 ]
-protobuf = ">=3.20.2,<4.21.0 || >4.21.0,<4.21.1 || >4.21.1,<4.21.2 || >4.21.2,<4.21.3 || >4.21.3,<4.21.4 || >4.21.4,<4.21.5 || >4.21.5,<6.0.0dev"
+protobuf = ">=3.20.2,<4.21.0 || >4.21.0,<4.21.1 || >4.21.1,<4.21.2 || >4.21.2,<4.21.3 || >4.21.3,<4.21.4 || >4.21.4,<4.21.5 || >4.21.5,<7.0.0"
 
 [[package]]
 name = "googleapis-common-protos"
@@ -895,6 +931,47 @@ files = [
     {file = "iniconfig-2.0.0.tar.gz", hash = "sha256:2d91e135bf72d31a410b17c16da610a82cb55f6b0477d1a902134b24a455b8b3"},
 ]
 
+[[package]]
+name = "launchdarkly-eventsource"
+version = "1.2.4"
+description = "LaunchDarkly SSE Client"
+optional = false
+python-versions = ">=3.8"
+groups = ["main"]
+files = [
+    {file = "launchdarkly_eventsource-1.2.4-py3-none-any.whl", hash = "sha256:048ef8c4440d0d8219778661ee4d4b5e12aa6ed2c29a3004417ede44c2386e8c"},
+    {file = "launchdarkly_eventsource-1.2.4.tar.gz", hash = "sha256:b8b9342681f55e1d35c56243431cbbaca4eb9812d6785f8de204af322104e066"},
+]
+
+[package.dependencies]
+urllib3 = ">=1.26.0,<3"
+
+[[package]]
+name = "launchdarkly-server-sdk"
+version = "9.11.1"
+description = "LaunchDarkly SDK for Python"
+optional = false
+python-versions = ">=3.8"
+groups = ["main"]
+files = [
+    {file = "launchdarkly_server_sdk-9.11.1-py3-none-any.whl", hash = "sha256:128569cebf666dd115cc0ba03c48ff75f6acc9788301a7e2c3a54d06107e445a"},
+    {file = "launchdarkly_server_sdk-9.11.1.tar.gz", hash = "sha256:150e29656cb8c506d1967f3c59e62b69310d345ec27217640a6146dd1db5d250"},
+]
+
+[package.dependencies]
+certifi = ">=2018.4.16"
+expiringdict = ">=1.1.4"
+launchdarkly-eventsource = ">=1.2.4,<2.0.0"
+pyRFC3339 = ">=1.0"
+semver = ">=2.10.2"
+urllib3 = ">=1.26.0,<3"
+
+[package.extras]
+consul = ["python-consul (>=1.0.1)"]
+dynamodb = ["boto3 (>=1.9.71)"]
+redis = ["redis (>=2.10.5)"]
+test-filesource = ["pyyaml (>=5.3.1)", "watchdog (>=3.0.0)"]
+
 [[package]]
 name = "multidict"
 version = "6.1.0"
@@ -1238,19 +1315,19 @@ pyasn1 = ">=0.4.6,<0.7.0"
 
 [[package]]
 name = "pydantic"
-version = "2.11.1"
+version = "2.11.4"
 description = "Data validation using Python type hints"
 optional = false
 python-versions = ">=3.9"
 groups = ["main"]
 files = [
-    {file = "pydantic-2.11.1-py3-none-any.whl", hash = "sha256:5b6c415eee9f8123a14d859be0c84363fec6b1feb6b688d6435801230b56e0b8"},
-    {file = "pydantic-2.11.1.tar.gz", hash = "sha256:442557d2910e75c991c39f4b4ab18963d57b9b55122c8b2a9cd176d8c29ce968"},
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 ]
 
 [package.dependencies]
@@ -1372,22 +1449,25 @@ typing-extensions = ">=4.6.0,<4.7.0 || >4.7.0"
 
 [[package]]
 name = "pydantic-settings"
-version = "2.8.1"
+version = "2.9.1"
 description = "Settings management using Pydantic"
 optional = false
-python-versions = ">=3.8"
+python-versions = ">=3.9"
 groups = ["main"]
 files = [
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+    {file = "pydantic_settings-2.9.1.tar.gz", hash = "sha256:c509bf79d27563add44e8446233359004ed85066cd096d8b510f715e6ef5d268"},
 ]
 
 [package.dependencies]
 pydantic = ">=2.7.0"
 python-dotenv = ">=0.21.0"
+typing-inspection = ">=0.4.0"
 
 [package.extras]
+aws-secrets-manager = ["boto3 (>=1.35.0)", "boto3-stubs[secretsmanager]"]
 azure-key-vault = ["azure-identity (>=1.16.0)", "azure-keyvault-secrets (>=4.8.0)"]
+gcp-secret-manager = ["google-cloud-secret-manager (>=2.23.1)"]
 toml = ["tomli (>=2.0.1)"]
 yaml = ["pyyaml (>=6.0.1)"]
 
@@ -1409,6 +1489,18 @@ dev = ["coverage[toml] (==5.0.4)", "cryptography (>=3.4.0)", "pre-commit", "pyte
 docs = ["sphinx", "sphinx-rtd-theme", "zope.interface"]
 tests = ["coverage[toml] (==5.0.4)", "pytest (>=6.0.0,<7.0.0)"]
 
+[[package]]
+name = "pyrfc3339"
+version = "2.0.1"
+description = "Generate and parse RFC 3339 timestamps"
+optional = false
+python-versions = "*"
+groups = ["main"]
+files = [
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+]
+
 [[package]]
 name = "pytest"
 version = "8.3.3"
@@ -1575,30 +1667,42 @@ pyasn1 = ">=0.1.3"
 
 [[package]]
 name = "ruff"
-version = "0.11.2"
+version = "0.11.10"
 description = "An extremely fast Python linter and code formatter, written in Rust."
 optional = false
 python-versions = ">=3.7"
 groups = ["dev"]
 files = [
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+    {file = "ruff-0.11.10.tar.gz", hash = "sha256:d522fb204b4959909ecac47da02830daec102eeb100fb50ea9554818d47a5fa6"},
+]
+
+[[package]]
+name = "semver"
+version = "3.0.4"
+description = "Python helper for Semantic Versioning (https://semver.org)"
+optional = false
+python-versions = ">=3.7"
+groups = ["main"]
+files = [
+    {file = "semver-3.0.4-py3-none-any.whl", hash = "sha256:9c824d87ba7f7ab4a1890799cec8596f15c1241cb473404ea1cb0c55e4b04746"},
+    {file = "semver-3.0.4.tar.gz", hash = "sha256:afc7d8c584a5ed0a11033af086e8af226a9c0b206f313e0301f8dd7b6b589602"},
 ]
 
 [[package]]
@@ -1625,6 +1729,24 @@ files = [
     {file = "sniffio-1.3.1.tar.gz", hash = "sha256:f4324edc670a0f49750a81b895f35c3adb843cca46f0530f79fc1babb23789dc"},
 ]
 
+[[package]]
+name = "starlette"
+version = "0.46.2"
+description = "The little ASGI library that shines."
+optional = false
+python-versions = ">=3.9"
+groups = ["main"]
+files = [
+    {file = "starlette-0.46.2-py3-none-any.whl", hash = "sha256:595633ce89f8ffa71a015caed34a5b2dc1c0cdb3f0f1fbd1e69339cf2abeec35"},
+    {file = "starlette-0.46.2.tar.gz", hash = "sha256:7f7361f34eed179294600af672f565727419830b54b7b084efe44bb82d2fccd5"},
+]
+
+[package.dependencies]
+anyio = ">=3.6.2,<5"
+
+[package.extras]
+full = ["httpx (>=0.27.0,<0.29.0)", "itsdangerous", "jinja2", "python-multipart (>=0.0.18)", "pyyaml"]
+
 [[package]]
 name = "storage3"
 version = "0.11.0"
@@ -1660,14 +1782,14 @@ test = ["pylint", "pytest", "pytest-black", "pytest-cov", "pytest-pylint"]
 
 [[package]]
 name = "supabase"
-version = "2.15.0"
+version = "2.15.1"
 description = "Supabase client for Python."
 optional = false
 python-versions = "<4.0,>=3.9"
 groups = ["main"]
 files = [
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+    {file = "supabase-2.15.1-py3-none-any.whl", hash = "sha256:749299cdd74ecf528f52045c1e60d9dba81cc2054656f754c0ca7fba0dd34827"},
+    {file = "supabase-2.15.1.tar.gz", hash = "sha256:66e847dab9346062aa6a25b4e81ac786b972c5d4299827c57d1d5bd6a0346070"},
 ]
 
 [package.dependencies]
@@ -1752,6 +1874,26 @@ h2 = ["h2 (>=4,<5)"]
 socks = ["pysocks (>=1.5.6,!=1.5.7,<2.0)"]
 zstd = ["zstandard (>=0.18.0)"]
 
+[[package]]
+name = "uvicorn"
+version = "0.34.3"
+description = "The lightning-fast ASGI server."
+optional = false
+python-versions = ">=3.9"
+groups = ["main"]
+files = [
+    {file = "uvicorn-0.34.3-py3-none-any.whl", hash = "sha256:16246631db62bdfbf069b0645177d6e8a77ba950cfedbfd093acef9444e4d885"},
+    {file = "uvicorn-0.34.3.tar.gz", hash = "sha256:35919a9a979d7a59334b6b10e05d77c1d0d574c50e0fc98b8b1a0f165708b55a"},
+]
+
+[package.dependencies]
+click = ">=7.0"
+h11 = ">=0.8"
+typing-extensions = {version = ">=4.0", markers = "python_version < \"3.11\""}
+
+[package.extras]
+standard = ["colorama (>=0.4) ; sys_platform == \"win32\"", "httptools (>=0.6.3)", "python-dotenv (>=0.13)", "pyyaml (>=5.1)", "uvloop (>=0.15.1) ; sys_platform != \"win32\" and sys_platform != \"cygwin\" and platform_python_implementation != \"PyPy\"", "watchfiles (>=0.13)", "websockets (>=10.4)"]
+
 [[package]]
 name = "websockets"
 version = "12.0"
@@ -2034,4 +2176,4 @@ type = ["pytest-mypy"]
 [metadata]
 lock-version = "2.1"
 python-versions = ">=3.10,<4.0"
-content-hash = "c8e23c0609cae0717447f575849b658bee9203b784ec7270b62629cddbbbd9ca"
+content-hash = "d92143928a88ca3a56ac200c335910eafac938940022fed8bd0d17c95040b54f"

autogpt_platform/autogpt_libs/pyproject.toml

@@ -7,20 +7,23 @@ readme = "README.md"
 packages = [{ include = "autogpt_libs" }]
 
 [tool.poetry.dependencies]
+python = ">=3.10,<4.0"
 colorama = "^0.4.6"
 expiringdict = "^1.2.2"
-google-cloud-logging = "^3.11.4"
-pydantic = "^2.11.1"
-pydantic-settings = "^2.8.1"
+google-cloud-logging = "^3.12.1"
+pydantic = "^2.11.4"
+pydantic-settings = "^2.9.1"
 pyjwt = "^2.10.1"
 pytest-asyncio = "^0.26.0"
 pytest-mock = "^3.14.0"
-python = ">=3.10,<4.0"
-supabase = "^2.15.0"
+supabase = "^2.15.1"
+launchdarkly-server-sdk = "^9.11.1"
+fastapi = "^0.115.12"
+uvicorn = "^0.34.3"
 
 [tool.poetry.group.dev.dependencies]
 redis = "^5.2.1"
-ruff = "^0.11.0"
+ruff = "^0.11.10"
 
 [build-system]
 requires = ["poetry-core"]

autogpt_platform/backend/.env.example

@@ -8,11 +8,11 @@ DB_CONNECT_TIMEOUT=60
 DB_POOL_TIMEOUT=300
 DB_SCHEMA=platform
 DATABASE_URL="postgresql://${DB_USER}:${DB_PASS}@${DB_HOST}:${DB_PORT}/${DB_NAME}?schema=${DB_SCHEMA}&connect_timeout=${DB_CONNECT_TIMEOUT}"
+DIRECT_URL="postgresql://${DB_USER}:${DB_PASS}@${DB_HOST}:${DB_PORT}/${DB_NAME}?schema=${DB_SCHEMA}&connect_timeout=${DB_CONNECT_TIMEOUT}"
 PRISMA_SCHEMA="postgres/schema.prisma"
 
 # EXECUTOR
 NUM_GRAPH_WORKERS=10
-NUM_NODE_WORKERS=3
 
 BACKEND_CORS_ALLOW_ORIGINS=["http://localhost:3000"]
 
@@ -65,6 +65,13 @@ MEDIA_GCS_BUCKET_NAME=
 ## and tunnel it to your locally running backend.
 PLATFORM_BASE_URL=http://localhost:3000
 
+## Cloudflare Turnstile (CAPTCHA) Configuration
+## Get these from the Cloudflare Turnstile dashboard: https://dash.cloudflare.com/?to=/:account/turnstile
+## This is the backend secret key
+TURNSTILE_SECRET_KEY=
+## This is the verify URL
+TURNSTILE_VERIFY_URL=https://challenges.cloudflare.com/turnstile/v0/siteverify
+
 ## == INTEGRATION CREDENTIALS == ##
 # Each set of server side credentials is required for the corresponding 3rd party
 # integration to work.
@@ -119,8 +126,10 @@ TODOIST_CLIENT_SECRET=
 # LLM
 OPENAI_API_KEY=
 ANTHROPIC_API_KEY=
+AIML_API_KEY=
 GROQ_API_KEY=
 OPEN_ROUTER_API_KEY=
+LLAMA_API_KEY=
 
 # Reddit
 # Go to https://www.reddit.com/prefs/apps and create a new app

autogpt_platform/backend/Dockerfile

@@ -73,7 +73,6 @@ FROM server_dependencies AS server
 COPY autogpt_platform/backend /app/autogpt_platform/backend
 RUN poetry install --no-ansi --only-root
 
-ENV DATABASE_URL=""
 ENV PORT=8000
 
 CMD ["poetry", "run", "rest"]

autogpt_platform/backend/TESTING.md

@@ -0,0 +1,237 @@
+# Backend Testing Guide
+
+This guide covers testing practices for the AutoGPT Platform backend, with a focus on snapshot testing for API endpoints.
+
+## Table of Contents
+- [Overview](#overview)
+- [Running Tests](#running-tests)
+- [Snapshot Testing](#snapshot-testing)
+- [Writing Tests for API Routes](#writing-tests-for-api-routes)
+- [Best Practices](#best-practices)
+
+## Overview
+
+The backend uses pytest for testing with the following key libraries:
+- `pytest` - Test framework
+- `pytest-asyncio` - Async test support
+- `pytest-mock` - Mocking support
+- `pytest-snapshot` - Snapshot testing for API responses
+
+## Running Tests
+
+### Run all tests
+```bash
+poetry run test
+```
+
+### Run specific test file
+```bash
+poetry run pytest path/to/test_file.py
+```
+
+### Run with verbose output
+```bash
+poetry run pytest -v
+```
+
+### Run with coverage
+```bash
+poetry run pytest --cov=backend
+```
+
+## Snapshot Testing
+
+Snapshot testing captures the output of your code and compares it against previously saved snapshots. This is particularly useful for testing API responses.
+
+### How Snapshot Testing Works
+
+1. First run: Creates snapshot files in `snapshots/` directories
+2. Subsequent runs: Compares output against saved snapshots
+3. Changes detected: Test fails if output differs from snapshot
+
+### Creating/Updating Snapshots
+
+When you first write a test or when the expected output changes:
+
+```bash
+poetry run pytest path/to/test.py --snapshot-update
+```
+
+⚠️ **Important**: Always review snapshot changes before committing! Use `git diff` to verify the changes are expected.
+
+### Snapshot Test Example
+
+```python
+import json
+from pytest_snapshot.plugin import Snapshot
+
+def test_api_endpoint(snapshot: Snapshot):
+    response = client.get("/api/endpoint")
+    
+    # Snapshot the response
+    snapshot.snapshot_dir = "snapshots"
+snapshot.assert_match(
+        json.dumps(response.json(), indent=2, sort_keys=True),
+        "endpoint_response"
+    )
+```
+
+### Best Practices for Snapshots
+
+1. **Use descriptive names**: `"user_list_response"` not `"response1"`
+2. **Sort JSON keys**: Ensures consistent snapshots
+3. **Format JSON**: Use `indent=2` for readable diffs
+4. **Exclude dynamic data**: Remove timestamps, IDs, etc. that change between runs
+
+Example of excluding dynamic data:
+```python
+response_data = response.json()
+# Remove dynamic fields for snapshot
+response_data.pop("created_at", None)
+response_data.pop("id", None)
+
+snapshot.snapshot_dir = "snapshots"
+snapshot.assert_match(
+    json.dumps(response_data, indent=2, sort_keys=True),
+    "static_response_data"
+)
+```
+
+## Writing Tests for API Routes
+
+### Basic Structure
+
+```python
+import json
+import fastapi
+import fastapi.testclient
+import pytest
+from pytest_snapshot.plugin import Snapshot
+
+from backend.server.v2.myroute import router
+
+app = fastapi.FastAPI()
+app.include_router(router)
+client = fastapi.testclient.TestClient(app)
+
+def test_endpoint_success(snapshot: Snapshot):
+    response = client.get("/endpoint")
+    assert response.status_code == 200
+    
+    # Test specific fields
+    data = response.json()
+    assert data["status"] == "success"
+    
+    # Snapshot the full response
+    snapshot.snapshot_dir = "snapshots"
+    snapshot.assert_match(
+        json.dumps(data, indent=2, sort_keys=True),
+        "endpoint_success_response"
+    )
+```
+
+### Testing with Authentication
+
+```python
+def override_auth_middleware():
+    return {"sub": "test-user-id"}
+
+def override_get_user_id():
+    return "test-user-id"
+
+app.dependency_overrides[auth_middleware] = override_auth_middleware
+app.dependency_overrides[get_user_id] = override_get_user_id
+```
+
+### Mocking External Services
+
+```python
+def test_external_api_call(mocker, snapshot):
+    # Mock external service
+    mock_response = {"external": "data"}
+    mocker.patch(
+        "backend.services.external_api.call",
+        return_value=mock_response
+    )
+    
+    response = client.post("/api/process")
+    assert response.status_code == 200
+    
+    snapshot.snapshot_dir = "snapshots"
+    snapshot.assert_match(
+        json.dumps(response.json(), indent=2, sort_keys=True),
+        "process_with_external_response"
+    )
+```
+
+## Best Practices
+
+### 1. Test Organization
+- Place tests next to the code: `routes.py` → `routes_test.py`
+- Use descriptive test names: `test_create_user_with_invalid_email`
+- Group related tests in classes when appropriate
+
+### 2. Test Coverage
+- Test happy path and error cases
+- Test edge cases (empty data, invalid formats)
+- Test authentication and authorization
+
+### 3. Snapshot Testing Guidelines
+- Review all snapshot changes carefully
+- Don't snapshot sensitive data
+- Keep snapshots focused and minimal
+- Update snapshots intentionally, not accidentally
+
+### 4. Async Testing
+- Use regular `def` for FastAPI TestClient tests
+- Use `async def` with `@pytest.mark.asyncio` for testing async functions directly
+
+### 5. Fixtures
+Create reusable fixtures for common test data:
+
+```python
+@pytest.fixture
+def sample_user():
+    return {
+        "email": "test@example.com",
+        "name": "Test User"
+    }
+
+def test_create_user(sample_user, snapshot):
+    response = client.post("/users", json=sample_user)
+    # ... test implementation
+```
+
+## CI/CD Integration
+
+The GitHub Actions workflow automatically runs tests on:
+- Pull requests
+- Pushes to main branch
+
+Snapshot tests work in CI by:
+1. Committing snapshot files to the repository
+2. CI compares against committed snapshots
+3. Fails if snapshots don't match
+
+## Troubleshooting
+
+### Snapshot Mismatches
+- Review the diff carefully
+- If changes are expected: `poetry run pytest --snapshot-update`
+- If changes are unexpected: Fix the code causing the difference
+
+### Async Test Issues
+- Ensure async functions use `@pytest.mark.asyncio`
+- Use `AsyncMock` for mocking async functions
+- FastAPI TestClient handles async automatically
+
+### Import Errors
+- Check that all dependencies are in `pyproject.toml`
+- Run `poetry install` to ensure dependencies are installed
+- Verify import paths are correct
+
+## Summary
+
+Snapshot testing provides a powerful way to ensure API responses remain consistent. Combined with traditional assertions, it creates a robust test suite that catches regressions while remaining maintainable.
+
+Remember: Good tests are as important as good code!

autogpt_platform/backend/backend/blocks/__init__.py

@@ -1,3 +1,4 @@
+import functools
 import importlib
 import os
 import re
@@ -10,17 +11,11 @@ if TYPE_CHECKING:
 T = TypeVar("T")
 
 
-_AVAILABLE_BLOCKS: dict[str, type["Block"]] = {}
-
-
+@functools.cache
 def load_all_blocks() -> dict[str, type["Block"]]:
     from backend.data.block import Block
 
-    if _AVAILABLE_BLOCKS:
-        return _AVAILABLE_BLOCKS
-
     # Dynamically load all modules under backend.blocks
-    AVAILABLE_MODULES = []
     current_dir = Path(__file__).parent
     modules = [
         str(f.relative_to(current_dir))[:-3].replace(os.path.sep, ".")
@@ -35,9 +30,9 @@ def load_all_blocks() -> dict[str, type["Block"]]:
             )
 
         importlib.import_module(f".{module}", package=__name__)
-        AVAILABLE_MODULES.append(module)
 
     # Load all Block instances from the available modules
+    available_blocks: dict[str, type["Block"]] = {}
     for block_cls in all_subclasses(Block):
         class_name = block_cls.__name__
 
@@ -58,7 +53,7 @@ def load_all_blocks() -> dict[str, type["Block"]]:
                 f"Block ID {block.name} error: {block.id} is not a valid UUID"
             )
 
-        if block.id in _AVAILABLE_BLOCKS:
+        if block.id in available_blocks:
             raise ValueError(
                 f"Block ID {block.name} error: {block.id} is already in use"
             )
@@ -89,9 +84,9 @@ def load_all_blocks() -> dict[str, type["Block"]]:
                     f"{block.name} has a boolean field with no default value"
                 )
 
-        _AVAILABLE_BLOCKS[block.id] = block_cls
+        available_blocks[block.id] = block_cls
 
-    return _AVAILABLE_BLOCKS
+    return available_blocks
 
 
 __all__ = ["load_all_blocks"]

autogpt_platform/backend/backend/blocks/agent.py

@@ -1,7 +1,6 @@
+import asyncio
 import logging
-from typing import Any
-
-from autogpt_libs.utils.cache import thread_cached
+from typing import Any, Optional
 
 from backend.data.block import (
     Block,
@@ -13,44 +12,33 @@ from backend.data.block import (
     get_block,
 )
 from backend.data.execution import ExecutionStatus
-from backend.data.model import SchemaField
+from backend.data.model import CredentialsMetaInput, SchemaField
 from backend.util import json
 
 logger = logging.getLogger(__name__)
 
 
-@thread_cached
-def get_executor_manager_client():
-    from backend.executor import ExecutionManager
-    from backend.util.service import get_service_client
-
-    return get_service_client(ExecutionManager)
-
-
-@thread_cached
-def get_event_bus():
-    from backend.data.execution import RedisExecutionEventBus
-
-    return RedisExecutionEventBus()
-
-
 class AgentExecutorBlock(Block):
     class Input(BlockSchema):
         user_id: str = SchemaField(description="User ID")
         graph_id: str = SchemaField(description="Graph ID")
         graph_version: int = SchemaField(description="Graph Version")
 
-        data: BlockInput = SchemaField(description="Input data for the graph")
+        inputs: BlockInput = SchemaField(description="Input data for the graph")
         input_schema: dict = SchemaField(description="Input schema for the graph")
         output_schema: dict = SchemaField(description="Output schema for the graph")
 
+        node_credentials_input_map: Optional[
+            dict[str, dict[str, CredentialsMetaInput]]
+        ] = SchemaField(default=None, hidden=True)
+
         @classmethod
         def get_input_schema(cls, data: BlockInput) -> dict[str, Any]:
             return data.get("input_schema", {})
 
         @classmethod
         def get_input_defaults(cls, data: BlockInput) -> BlockInput:
-            return data.get("data", {})
+            return data.get("inputs", {})
 
         @classmethod
         def get_missing_input(cls, data: BlockInput) -> set[str]:
@@ -74,38 +62,80 @@ class AgentExecutorBlock(Block):
             categories={BlockCategory.AGENT},
         )
 
-    def run(self, input_data: Input, **kwargs) -> BlockOutput:
-        from backend.data.execution import ExecutionEventType
+    async def run(self, input_data: Input, **kwargs) -> BlockOutput:
 
-        executor_manager = get_executor_manager_client()
-        event_bus = get_event_bus()
+        from backend.executor import utils as execution_utils
 
-        graph_exec = executor_manager.add_execution(
+        graph_exec = await execution_utils.add_graph_execution(
             graph_id=input_data.graph_id,
             graph_version=input_data.graph_version,
             user_id=input_data.user_id,
-            data=input_data.data,
+            inputs=input_data.inputs,
+            node_credentials_input_map=input_data.node_credentials_input_map,
+            use_db_query=False,
         )
-        log_id = f"Graph #{input_data.graph_id}-V{input_data.graph_version}, exec-id: {graph_exec.graph_exec_id}"
+
+        try:
+            async for name, data in self._run(
+                graph_id=input_data.graph_id,
+                graph_version=input_data.graph_version,
+                graph_exec_id=graph_exec.id,
+                user_id=input_data.user_id,
+            ):
+                yield name, data
+        except asyncio.CancelledError:
+            logger.warning(
+                f"Execution of graph {input_data.graph_id} version {input_data.graph_version} was cancelled."
+            )
+            await execution_utils.stop_graph_execution(
+                graph_exec.id, use_db_query=False
+            )
+        except Exception as e:
+            logger.error(
+                f"Execution of graph {input_data.graph_id} version {input_data.graph_version} failed: {e}, stopping execution."
+            )
+            await execution_utils.stop_graph_execution(
+                graph_exec.id, use_db_query=False
+            )
+            raise
+
+    async def _run(
+        self,
+        graph_id: str,
+        graph_version: int,
+        graph_exec_id: str,
+        user_id: str,
+    ) -> BlockOutput:
+
+        from backend.data.execution import ExecutionEventType
+        from backend.executor import utils as execution_utils
+
+        event_bus = execution_utils.get_async_execution_event_bus()
+
+        log_id = f"Graph #{graph_id}-V{graph_version}, exec-id: {graph_exec_id}"
         logger.info(f"Starting execution of {log_id}")
 
-        for event in event_bus.listen(
-            user_id=graph_exec.user_id,
-            graph_id=graph_exec.graph_id,
-            graph_exec_id=graph_exec.graph_exec_id,
+        async for event in event_bus.listen(
+            user_id=user_id,
+            graph_id=graph_id,
+            graph_exec_id=graph_exec_id,
         ):
-            if event.event_type == ExecutionEventType.GRAPH_EXEC_UPDATE:
-                if event.status in [
-                    ExecutionStatus.COMPLETED,
-                    ExecutionStatus.TERMINATED,
-                    ExecutionStatus.FAILED,
-                ]:
-                    logger.info(f"Execution {log_id} ended with status {event.status}")
-                    break
-                else:
-                    continue
+            if event.status not in [
+                ExecutionStatus.COMPLETED,
+                ExecutionStatus.TERMINATED,
+                ExecutionStatus.FAILED,
+            ]:
+                logger.debug(
+                    f"Execution {log_id} received event {event.event_type} with status {event.status}"
+                )
+                continue
 
-            logger.info(
+            if event.event_type == ExecutionEventType.GRAPH_EXEC_UPDATE:
+                # If the graph execution is COMPLETED, TERMINATED, or FAILED,
+                # we can stop listening for further events.
+                break
+
+            logger.debug(
                 f"Execution {log_id} produced input {event.input_data} output {event.output_data}"
             )
 
@@ -123,5 +153,7 @@ class AgentExecutorBlock(Block):
                 continue
 
             for output_data in event.output_data.get("output", []):
-                logger.info(f"Execution {log_id} produced {output_name}: {output_data}")
+                logger.debug(
+                    f"Execution {log_id} produced {output_name}: {output_data}"
+                )
                 yield output_name, output_data

autogpt_platform/backend/backend/blocks/ai_image_generator_block.py

@@ -1,8 +1,8 @@
 from enum import Enum
 from typing import Literal
 
-import replicate
 from pydantic import SecretStr
+from replicate.client import Client as ReplicateClient
 from replicate.helpers import FileOutput
 
 from backend.data.block import Block, BlockCategory, BlockSchema
@@ -165,15 +165,15 @@ class AIImageGeneratorBlock(Block):
             },
         )
 
-    def _run_client(
+    async def _run_client(
         self, credentials: APIKeyCredentials, model_name: str, input_params: dict
     ):
         try:
             # Initialize Replicate client
-            client = replicate.Client(api_token=credentials.api_key.get_secret_value())
+            client = ReplicateClient(api_token=credentials.api_key.get_secret_value())
 
             # Run the model with input parameters
-            output = client.run(model_name, input=input_params, wait=False)
+            output = await client.async_run(model_name, input=input_params, wait=False)
 
             # Process output
             if isinstance(output, list) and len(output) > 0:
@@ -195,7 +195,7 @@ class AIImageGeneratorBlock(Block):
         except Exception as e:
             raise RuntimeError(f"Unexpected error during model execution: {e}")
 
-    def generate_image(self, input_data: Input, credentials: APIKeyCredentials):
+    async def generate_image(self, input_data: Input, credentials: APIKeyCredentials):
         try:
             # Handle style-based prompt modification for models without native style support
             modified_prompt = input_data.prompt
@@ -213,7 +213,7 @@ class AIImageGeneratorBlock(Block):
                     "steps": 40,
                     "cfg_scale": 7.0,
                 }
-                output = self._run_client(
+                output = await self._run_client(
                     credentials,
                     "stability-ai/stable-diffusion-3.5-medium",
                     input_params,
@@ -231,7 +231,7 @@ class AIImageGeneratorBlock(Block):
                     "output_format": "jpg",  # Set to jpg for Flux models
                     "output_quality": 90,
                 }
-                output = self._run_client(
+                output = await self._run_client(
                     credentials, "black-forest-labs/flux-1.1-pro", input_params
                 )
                 return output
@@ -246,7 +246,7 @@ class AIImageGeneratorBlock(Block):
                     "output_format": "jpg",
                     "output_quality": 90,
                 }
-                output = self._run_client(
+                output = await self._run_client(
                     credentials, "black-forest-labs/flux-1.1-pro-ultra", input_params
                 )
                 return output
@@ -257,7 +257,7 @@ class AIImageGeneratorBlock(Block):
                     "size": SIZE_TO_RECRAFT_DIMENSIONS[input_data.size],
                     "style": input_data.style.value,
                 }
-                output = self._run_client(
+                output = await self._run_client(
                     credentials, "recraft-ai/recraft-v3", input_params
                 )
                 return output
@@ -296,9 +296,9 @@ class AIImageGeneratorBlock(Block):
         style_text = style_map.get(style, "")
         return f"{style_text} of" if style_text else ""
 
-    def run(self, input_data: Input, *, credentials: APIKeyCredentials, **kwargs):
+    async def run(self, input_data: Input, *, credentials: APIKeyCredentials, **kwargs):
         try:
-            url = self.generate_image(input_data, credentials)
+            url = await self.generate_image(input_data, credentials)
             if url:
                 yield "image_url", url
             else:

autogpt_platform/backend/backend/blocks/ai_music_generator.py

@@ -1,10 +1,10 @@
+import asyncio
 import logging
-import time
 from enum import Enum
 from typing import Literal
 
-import replicate
 from pydantic import SecretStr
+from replicate.client import Client as ReplicateClient
 
 from backend.data.block import Block, BlockCategory, BlockOutput, BlockSchema
 from backend.data.model import (
@@ -142,7 +142,7 @@ class AIMusicGeneratorBlock(Block):
             test_credentials=TEST_CREDENTIALS,
         )
 
-    def run(
+    async def run(
         self, input_data: Input, *, credentials: APIKeyCredentials, **kwargs
     ) -> BlockOutput:
         max_retries = 3
@@ -154,7 +154,7 @@ class AIMusicGeneratorBlock(Block):
                 logger.debug(
                     f"[AIMusicGeneratorBlock] - Running model (attempt {attempt + 1})"
                 )
-                result = self.run_model(
+                result = await self.run_model(
                     api_key=credentials.api_key,
                     music_gen_model_version=input_data.music_gen_model_version,
                     prompt=input_data.prompt,
@@ -176,13 +176,13 @@ class AIMusicGeneratorBlock(Block):
                 last_error = f"Unexpected error: {str(e)}"
                 logger.error(f"[AIMusicGeneratorBlock] - Error: {last_error}")
                 if attempt < max_retries - 1:
-                    time.sleep(retry_delay)
+                    await asyncio.sleep(retry_delay)
                     continue
 
         # If we've exhausted all retries, yield the error
         yield "error", f"Failed after {max_retries} attempts. Last error: {last_error}"
 
-    def run_model(
+    async def run_model(
         self,
         api_key: SecretStr,
         music_gen_model_version: MusicGenModelVersion,
@@ -196,10 +196,10 @@ class AIMusicGeneratorBlock(Block):
         normalization_strategy: NormalizationStrategy,
     ):
         # Initialize Replicate client with the API key
-        client = replicate.Client(api_token=api_key.get_secret_value())
+        client = ReplicateClient(api_token=api_key.get_secret_value())
 
         # Run the model with parameters
-        output = client.run(
+        output = await client.async_run(
             "meta/musicgen:671ac645ce5e552cc63a54a2bbff63fcf798043055d2dac5fc9e36a837eedcfb",
             input={
                 "prompt": prompt,

autogpt_platform/backend/backend/blocks/ai_shortform_video_block.py

@@ -1,3 +1,4 @@
+import asyncio
 import logging
 import time
 from enum import Enum
@@ -13,7 +14,7 @@ from backend.data.model import (
     SchemaField,
 )
 from backend.integrations.providers import ProviderName
-from backend.util.request import requests
+from backend.util.request import Requests
 
 TEST_CREDENTIALS = APIKeyCredentials(
     id="01234567-89ab-cdef-0123-456789abcdef",
@@ -216,29 +217,29 @@ class AIShortformVideoCreatorBlock(Block):
             test_credentials=TEST_CREDENTIALS,
         )
 
-    def create_webhook(self):
+    async def create_webhook(self):
         url = "https://webhook.site/token"
         headers = {"Accept": "application/json", "Content-Type": "application/json"}
-        response = requests.post(url, headers=headers)
+        response = await Requests().post(url, headers=headers)
         webhook_data = response.json()
         return webhook_data["uuid"], f"https://webhook.site/{webhook_data['uuid']}"
 
-    def create_video(self, api_key: SecretStr, payload: dict) -> dict:
+    async def create_video(self, api_key: SecretStr, payload: dict) -> dict:
         url = "https://www.revid.ai/api/public/v2/render"
         headers = {"key": api_key.get_secret_value()}
-        response = requests.post(url, json=payload, headers=headers)
+        response = await Requests().post(url, json=payload, headers=headers)
         logger.debug(
-            f"API Response Status Code: {response.status_code}, Content: {response.text}"
+            f"API Response Status Code: {response.status}, Content: {response.text}"
         )
         return response.json()
 
-    def check_video_status(self, api_key: SecretStr, pid: str) -> dict:
+    async def check_video_status(self, api_key: SecretStr, pid: str) -> dict:
         url = f"https://www.revid.ai/api/public/v2/status?pid={pid}"
         headers = {"key": api_key.get_secret_value()}
-        response = requests.get(url, headers=headers)
+        response = await Requests().get(url, headers=headers)
         return response.json()
 
-    def wait_for_video(
+    async def wait_for_video(
         self,
         api_key: SecretStr,
         pid: str,
@@ -247,7 +248,7 @@ class AIShortformVideoCreatorBlock(Block):
     ) -> str:
         start_time = time.time()
         while time.time() - start_time < max_wait_time:
-            status = self.check_video_status(api_key, pid)
+            status = await self.check_video_status(api_key, pid)
             logger.debug(f"Video status: {status}")
 
             if status.get("status") == "ready" and "videoUrl" in status:
@@ -260,16 +261,16 @@ class AIShortformVideoCreatorBlock(Block):
                 logger.error(f"Video creation failed: {status.get('message')}")
                 raise ValueError(f"Video creation failed: {status.get('message')}")
 
-            time.sleep(10)
+            await asyncio.sleep(10)
 
         logger.error("Video creation timed out")
         raise TimeoutError("Video creation timed out")
 
-    def run(
+    async def run(
         self, input_data: Input, *, credentials: APIKeyCredentials, **kwargs
     ) -> BlockOutput:
         # Create a new Webhook.site URL
-        webhook_token, webhook_url = self.create_webhook()
+        webhook_token, webhook_url = await self.create_webhook()
         logger.debug(f"Webhook URL: {webhook_url}")
 
         audio_url = input_data.background_music.audio_url
@@ -306,7 +307,7 @@ class AIShortformVideoCreatorBlock(Block):
         }
 
         logger.debug("Creating video...")
-        response = self.create_video(credentials.api_key, payload)
+        response = await self.create_video(credentials.api_key, payload)
         pid = response.get("pid")
 
         if not pid:
@@ -318,6 +319,8 @@ class AIShortformVideoCreatorBlock(Block):
             logger.debug(
                 f"Video created with project ID: {pid}. Waiting for completion..."
             )
-            video_url = self.wait_for_video(credentials.api_key, pid, webhook_token)
+            video_url = await self.wait_for_video(
+                credentials.api_key, pid, webhook_token
+            )
             logger.debug(f"Video ready: {video_url}")
             yield "video_url", video_url

autogpt_platform/backend/backend/blocks/apollo/_api.py

@@ -27,14 +27,15 @@ class ApolloClient:
     def _get_headers(self) -> dict[str, str]:
         return {"x-api-key": self.credentials.api_key.get_secret_value()}
 
-    def search_people(self, query: SearchPeopleRequest) -> List[Contact]:
+    async def search_people(self, query: SearchPeopleRequest) -> List[Contact]:
         """Search for people in Apollo"""
-        response = self.requests.get(
+        response = await self.requests.get(
             f"{self.API_URL}/mixed_people/search",
             headers=self._get_headers(),
             params=query.model_dump(exclude={"credentials", "max_results"}),
         )
-        parsed_response = SearchPeopleResponse(**response.json())
+        data = response.json()
+        parsed_response = SearchPeopleResponse(**data)
         if parsed_response.pagination.total_entries == 0:
             return []
 
@@ -52,27 +53,29 @@ class ApolloClient:
                 and len(parsed_response.people) > 0
             ):
                 query.page += 1
-                response = self.requests.get(
+                response = await self.requests.get(
                     f"{self.API_URL}/mixed_people/search",
                     headers=self._get_headers(),
                     params=query.model_dump(exclude={"credentials", "max_results"}),
                 )
-                parsed_response = SearchPeopleResponse(**response.json())
+                data = response.json()
+                parsed_response = SearchPeopleResponse(**data)
                 people.extend(parsed_response.people[: query.max_results - len(people)])
 
         logger.info(f"Found {len(people)} people")
         return people[: query.max_results] if query.max_results else people
 
-    def search_organizations(
+    async def search_organizations(
         self, query: SearchOrganizationsRequest
     ) -> List[Organization]:
         """Search for organizations in Apollo"""
-        response = self.requests.get(
+        response = await self.requests.get(
             f"{self.API_URL}/mixed_companies/search",
             headers=self._get_headers(),
             params=query.model_dump(exclude={"credentials", "max_results"}),
         )
-        parsed_response = SearchOrganizationsResponse(**response.json())
+        data = response.json()
+        parsed_response = SearchOrganizationsResponse(**data)
         if parsed_response.pagination.total_entries == 0:
             return []
 
@@ -90,12 +93,13 @@ class ApolloClient:
                 and len(parsed_response.organizations) > 0
             ):
                 query.page += 1
-                response = self.requests.get(
+                response = await self.requests.get(
                     f"{self.API_URL}/mixed_companies/search",
                     headers=self._get_headers(),
                     params=query.model_dump(exclude={"credentials", "max_results"}),
                 )
-                parsed_response = SearchOrganizationsResponse(**response.json())
+                data = response.json()
+                parsed_response = SearchOrganizationsResponse(**data)
                 organizations.extend(
                     parsed_response.organizations[
                         : query.max_results - len(organizations)

autogpt_platform/backend/backend/blocks/apollo/models.py

@@ -1,7 +1,7 @@
 from enum import Enum
 from typing import Any, Optional
 
-from pydantic import BaseModel
+from pydantic import BaseModel, ConfigDict
 
 from backend.data.model import SchemaField
 
@@ -143,11 +143,12 @@ class ContactEmail(BaseModel):
 class EmploymentHistory(BaseModel):
     """An employment history in Apollo"""
 
-    class Config:
-        extra = "allow"
-        arbitrary_types_allowed = True
-        from_attributes = True
-        populate_by_name = True
+    model_config = ConfigDict(
+        extra="allow",
+        arbitrary_types_allowed=True,
+        from_attributes=True,
+        populate_by_name=True,
+    )
 
     _id: Optional[str] = None
     created_at: Optional[str] = None
@@ -188,11 +189,12 @@ class TypedCustomField(BaseModel):
 class Pagination(BaseModel):
     """Pagination in Apollo"""
 
-    class Config:
-        extra = "allow"  # Allow extra fields
-        arbitrary_types_allowed = True  # Allow any type
-        from_attributes = True  # Allow from_orm
-        populate_by_name = True  # Allow field aliases to work both ways
+    model_config = ConfigDict(
+        extra="allow",
+        arbitrary_types_allowed=True,
+        from_attributes=True,
+        populate_by_name=True,
+    )
 
     page: int = 0
     per_page: int = 0
@@ -230,11 +232,12 @@ class PhoneNumber(BaseModel):
 class Organization(BaseModel):
     """An organization in Apollo"""
 
-    class Config:
-        extra = "allow"
-        arbitrary_types_allowed = True
-        from_attributes = True
-        populate_by_name = True
+    model_config = ConfigDict(
+        extra="allow",
+        arbitrary_types_allowed=True,
+        from_attributes=True,
+        populate_by_name=True,
+    )
 
     id: Optional[str] = "N/A"
     name: Optional[str] = "N/A"
@@ -268,11 +271,12 @@ class Organization(BaseModel):
 class Contact(BaseModel):
     """A contact in Apollo"""
 
-    class Config:
-        extra = "allow"
-        arbitrary_types_allowed = True
-        from_attributes = True
-        populate_by_name = True
+    model_config = ConfigDict(
+        extra="allow",
+        arbitrary_types_allowed=True,
+        from_attributes=True,
+        populate_by_name=True,
+    )
 
     contact_roles: list[Any] = []
     id: Optional[str] = None
@@ -369,14 +373,14 @@ If a company has several office locations, results are still based on the headqu
 
 To exclude companies based on location, use the organization_not_locations parameter.
 """,
-        default=[],
+        default_factory=list,
     )
     organizations_not_locations: list[str] = SchemaField(
         description="""Exclude companies from search results based on the location of the company headquarters. You can use cities, US states, and countries as locations to exclude.
 
 This parameter is useful for ensuring you do not prospect in an undesirable territory. For example, if you use ireland as a value, no Ireland-based companies will appear in your search results.
 """,
-        default=[],
+        default_factory=list,
     )
     q_organization_keyword_tags: list[str] = SchemaField(
         description="""Filter search results based on keywords associated with companies. For example, you can enter mining as a value to return only companies that have an association with the mining industry."""
@@ -390,7 +394,7 @@ If the value you enter for this parameter does not match with a company's name,
         description="""The Apollo IDs for the companies you want to include in your search results. Each company in the Apollo database is assigned a unique ID.
 
 To find IDs, identify the values for organization_id when you call this endpoint.""",
-        default=[],
+        default_factory=list,
     )
     max_results: int = SchemaField(
         description="""The maximum number of results to return. If you don't specify this parameter, the default is 100.""",
@@ -443,14 +447,14 @@ Results also include job titles with the same terms, even if they are not exact
 
 Use this parameter in combination with the person_seniorities[] parameter to find people based on specific job functions and seniority levels.
 """,
-        default=[],
+        default_factory=list,
         placeholder="marketing manager",
     )
     person_locations: list[str] = SchemaField(
         description="""The location where people live. You can search across cities, US states, and countries.
 
 To find people based on the headquarters locations of their current employer, use the organization_locations parameter.""",
-        default=[],
+        default_factory=list,
     )
     person_seniorities: list[SenorityLevels] = SchemaField(
         description="""The job seniority that people hold within their current employer. This enables you to find people that currently hold positions at certain reporting levels, such as Director level or senior IC level.
@@ -460,7 +464,7 @@ For a person to be included in search results, they only need to match 1 of the
 Searches only return results based on their current job title, so searching for Director-level employees only returns people that currently hold a Director-level title. If someone was previously a Director, but is currently a VP, they would not be included in your search results.
 
 Use this parameter in combination with the person_titles[] parameter to find people based on specific job functions and seniority levels.""",
-        default=[],
+        default_factory=list,
     )
     organization_locations: list[str] = SchemaField(
         description="""The location of the company headquarters for a person's current employer. You can search across cities, US states, and countries.
@@ -468,7 +472,7 @@ Use this parameter in combination with the person_titles[] parameter to find peo
 If a company has several office locations, results are still based on the headquarters location. For example, if you search chicago but a company's HQ location is in boston, people that work for the Boston-based company will not appear in your results, even if they match other parameters.
 
 To find people based on their personal location, use the person_locations parameter.""",
-        default=[],
+        default_factory=list,
     )
     q_organization_domains: list[str] = SchemaField(
         description="""The domain name for the person's employer. This can be the current employer or a previous employer. Do not include www., the @ symbol, or similar.
@@ -476,23 +480,23 @@ To find people based on their personal location, use the person_locations parame
 You can add multiple domains to search across companies.
 
   Examples: apollo.io and microsoft.com""",
-        default=[],
+        default_factory=list,
     )
     contact_email_statuses: list[ContactEmailStatuses] = SchemaField(
         description="""The email statuses for the people you want to find. You can add multiple statuses to expand your search.""",
-        default=[],
+        default_factory=list,
     )
     organization_ids: list[str] = SchemaField(
         description="""The Apollo IDs for the companies (employers) you want to include in your search results. Each company in the Apollo database is assigned a unique ID.
 
 To find IDs, call the Organization Search endpoint and identify the values for organization_id.""",
-        default=[],
+        default_factory=list,
     )
     organization_num_empoloyees_range: list[int] = SchemaField(
         description="""The number range of employees working for the company. This enables you to find companies based on headcount. You can add multiple ranges to expand your search results.
 
 Each range you add needs to be a string, with the upper and lower numbers of the range separated only by a comma.""",
-        default=[],
+        default_factory=list,
     )
     q_keywords: str = SchemaField(
         description="""A string of words over which we want to filter the results""",
@@ -522,11 +526,12 @@ Use the page parameter to search the different pages of data.""",
 class SearchPeopleResponse(BaseModel):
     """Response from Apollo's search people API"""
 
-    class Config:
-        extra = "allow"  # Allow extra fields
-        arbitrary_types_allowed = True  # Allow any type
-        from_attributes = True  # Allow from_orm
-        populate_by_name = True  # Allow field aliases to work both ways
+    model_config = ConfigDict(
+        extra="allow",
+        arbitrary_types_allowed=True,
+        from_attributes=True,
+        populate_by_name=True,
+    )
 
     breadcrumbs: list[Breadcrumb] = []
     partial_results_only: bool = True

autogpt_platform/backend/backend/blocks/apollo/organization.py

@@ -32,18 +32,18 @@ If a company has several office locations, results are still based on the headqu
 
 To exclude companies based on location, use the organization_not_locations parameter.
 """,
-            default=[],
+            default_factory=list,
         )
         organizations_not_locations: list[str] = SchemaField(
             description="""Exclude companies from search results based on the location of the company headquarters. You can use cities, US states, and countries as locations to exclude.
 
 This parameter is useful for ensuring you do not prospect in an undesirable territory. For example, if you use ireland as a value, no Ireland-based companies will appear in your search results.
 """,
-            default=[],
+            default_factory=list,
         )
         q_organization_keyword_tags: list[str] = SchemaField(
             description="""Filter search results based on keywords associated with companies. For example, you can enter mining as a value to return only companies that have an association with the mining industry.""",
-            default=[],
+            default_factory=list,
         )
         q_organization_name: str = SchemaField(
             description="""Filter search results to include a specific company name.
@@ -56,7 +56,7 @@ If the value you enter for this parameter does not match with a company's name,
             description="""The Apollo IDs for the companies you want to include in your search results. Each company in the Apollo database is assigned a unique ID.
 
 To find IDs, identify the values for organization_id when you call this endpoint.""",
-            default=[],
+            default_factory=list,
         )
         max_results: int = SchemaField(
             description="""The maximum number of results to return. If you don't specify this parameter, the default is 100.""",
@@ -72,7 +72,7 @@ To find IDs, identify the values for organization_id when you call this endpoint
     class Output(BlockSchema):
         organizations: list[Organization] = SchemaField(
             description="List of organizations found",
-            default=[],
+            default_factory=list,
         )
         organization: Organization = SchemaField(
             description="Each found organization, one at a time",
@@ -201,19 +201,19 @@ To find IDs, identify the values for organization_id when you call this endpoint
         )
 
     @staticmethod
-    def search_organizations(
+    async def search_organizations(
         query: SearchOrganizationsRequest, credentials: ApolloCredentials
     ) -> list[Organization]:
         client = ApolloClient(credentials)
-        return client.search_organizations(query)
+        return await client.search_organizations(query)
 
-    def run(
+    async def run(
         self, input_data: Input, *, credentials: ApolloCredentials, **kwargs
     ) -> BlockOutput:
         query = SearchOrganizationsRequest(
             **input_data.model_dump(exclude={"credentials"})
         )
-        organizations = self.search_organizations(query, credentials)
+        organizations = await self.search_organizations(query, credentials)
         for organization in organizations:
             yield "organization", organization
         yield "organizations", organizations

autogpt_platform/backend/backend/blocks/apollo/people.py

@@ -26,14 +26,14 @@ class SearchPeopleBlock(Block):
 
         Use this parameter in combination with the person_seniorities[] parameter to find people based on specific job functions and seniority levels.
         """,
-            default=[],
+            default_factory=list,
             advanced=False,
         )
         person_locations: list[str] = SchemaField(
             description="""The location where people live. You can search across cities, US states, and countries.
 
         To find people based on the headquarters locations of their current employer, use the organization_locations parameter.""",
-            default=[],
+            default_factory=list,
             advanced=False,
         )
         person_seniorities: list[SenorityLevels] = SchemaField(
@@ -44,7 +44,7 @@ class SearchPeopleBlock(Block):
         Searches only return results based on their current job title, so searching for Director-level employees only returns people that currently hold a Director-level title. If someone was previously a Director, but is currently a VP, they would not be included in your search results.
 
         Use this parameter in combination with the person_titles[] parameter to find people based on specific job functions and seniority levels.""",
-            default=[],
+            default_factory=list,
             advanced=False,
         )
         organization_locations: list[str] = SchemaField(
@@ -53,7 +53,7 @@ class SearchPeopleBlock(Block):
         If a company has several office locations, results are still based on the headquarters location. For example, if you search chicago but a company's HQ location is in boston, people that work for the Boston-based company will not appear in your results, even if they match other parameters.
 
         To find people based on their personal location, use the person_locations parameter.""",
-            default=[],
+            default_factory=list,
             advanced=False,
         )
         q_organization_domains: list[str] = SchemaField(
@@ -62,26 +62,26 @@ class SearchPeopleBlock(Block):
         You can add multiple domains to search across companies.
 
           Examples: apollo.io and microsoft.com""",
-            default=[],
+            default_factory=list,
             advanced=False,
         )
         contact_email_statuses: list[ContactEmailStatuses] = SchemaField(
             description="""The email statuses for the people you want to find. You can add multiple statuses to expand your search.""",
-            default=[],
+            default_factory=list,
             advanced=False,
         )
         organization_ids: list[str] = SchemaField(
             description="""The Apollo IDs for the companies (employers) you want to include in your search results. Each company in the Apollo database is assigned a unique ID.
 
         To find IDs, call the Organization Search endpoint and identify the values for organization_id.""",
-            default=[],
+            default_factory=list,
             advanced=False,
         )
         organization_num_empoloyees_range: list[int] = SchemaField(
             description="""The number range of employees working for the company. This enables you to find companies based on headcount. You can add multiple ranges to expand your search results.
 
         Each range you add needs to be a string, with the upper and lower numbers of the range separated only by a comma.""",
-            default=[],
+            default_factory=list,
             advanced=False,
         )
         q_keywords: str = SchemaField(
@@ -104,7 +104,7 @@ class SearchPeopleBlock(Block):
     class Output(BlockSchema):
         people: list[Contact] = SchemaField(
             description="List of people found",
-            default=[],
+            default_factory=list,
         )
         person: Contact = SchemaField(
             description="Each found person, one at a time",
@@ -373,13 +373,13 @@ class SearchPeopleBlock(Block):
         )
 
     @staticmethod
-    def search_people(
+    async def search_people(
         query: SearchPeopleRequest, credentials: ApolloCredentials
     ) -> list[Contact]:
         client = ApolloClient(credentials)
-        return client.search_people(query)
+        return await client.search_people(query)
 
-    def run(
+    async def run(
         self,
         input_data: Input,
         *,
@@ -388,7 +388,7 @@ class SearchPeopleBlock(Block):
     ) -> BlockOutput:
 
         query = SearchPeopleRequest(**input_data.model_dump(exclude={"credentials"}))
-        people = self.search_people(query, credentials)
+        people = await self.search_people(query, credentials)
         for person in people:
             yield "person", person
         yield "people", people

autogpt_platform/backend/backend/blocks/basic.py

@@ -30,14 +30,14 @@ class FileStoreBlock(Block):
             static_output=True,
         )
 
-    def run(
+    async def run(
         self,
         input_data: Input,
         *,
         graph_exec_id: str,
         **kwargs,
     ) -> BlockOutput:
-        file_path = store_media_file(
+        file_path = await store_media_file(
             graph_exec_id=graph_exec_id,
             file=input_data.file_in,
             return_content=False,
@@ -84,10 +84,37 @@ class StoreValueBlock(Block):
             static_output=True,
         )
 
-    def run(self, input_data: Input, **kwargs) -> BlockOutput:
+    async def run(self, input_data: Input, **kwargs) -> BlockOutput:
         yield "output", input_data.data or input_data.input
 
 
+class PrintToConsoleBlock(Block):
+    class Input(BlockSchema):
+        text: Any = SchemaField(description="The data to print to the console.")
+
+    class Output(BlockSchema):
+        output: Any = SchemaField(description="The data printed to the console.")
+        status: str = SchemaField(description="The status of the print operation.")
+
+    def __init__(self):
+        super().__init__(
+            id="f3b1c1b2-4c4f-4f0d-8d2f-4c4f0d8d2f4c",
+            description="Print the given text to the console, this is used for a debugging purpose.",
+            categories={BlockCategory.BASIC},
+            input_schema=PrintToConsoleBlock.Input,
+            output_schema=PrintToConsoleBlock.Output,
+            test_input={"text": "Hello, World!"},
+            test_output=[
+                ("output", "Hello, World!"),
+                ("status", "printed"),
+            ],
+        )
+
+    async def run(self, input_data: Input, **kwargs) -> BlockOutput:
+        yield "output", input_data.text
+        yield "status", "printed"
+
+
 class FindInDictionaryBlock(Block):
     class Input(BlockSchema):
         input: Any = SchemaField(description="Dictionary to lookup from")
@@ -124,7 +151,7 @@ class FindInDictionaryBlock(Block):
             categories={BlockCategory.BASIC},
         )
 
-    def run(self, input_data: Input, **kwargs) -> BlockOutput:
+    async def run(self, input_data: Input, **kwargs) -> BlockOutput:
         obj = input_data.input
         key = input_data.key
 
@@ -151,7 +178,7 @@ class FindInDictionaryBlock(Block):
 class AddToDictionaryBlock(Block):
     class Input(BlockSchema):
         dictionary: dict[Any, Any] = SchemaField(
-            default={},
+            default_factory=dict,
             description="The dictionary to add the entry to. If not provided, a new dictionary will be created.",
         )
         key: str = SchemaField(
@@ -167,7 +194,7 @@ class AddToDictionaryBlock(Block):
             advanced=False,
         )
         entries: dict[Any, Any] = SchemaField(
-            default={},
+            default_factory=dict,
             description="The entries to add to the dictionary. This is the batch version of the `key` and `value` fields.",
             advanced=True,
         )
@@ -214,7 +241,7 @@ class AddToDictionaryBlock(Block):
             ],
         )
 
-    def run(self, input_data: Input, **kwargs) -> BlockOutput:
+    async def run(self, input_data: Input, **kwargs) -> BlockOutput:
         updated_dict = input_data.dictionary.copy()
 
         if input_data.value is not None and input_data.key:
@@ -229,7 +256,7 @@ class AddToDictionaryBlock(Block):
 class AddToListBlock(Block):
     class Input(BlockSchema):
         list: List[Any] = SchemaField(
-            default=[],
+            default_factory=list,
             advanced=False,
             description="The list to add the entry to. If not provided, a new list will be created.",
         )
@@ -239,7 +266,7 @@ class AddToListBlock(Block):
             default=None,
         )
         entries: List[Any] = SchemaField(
-            default=[],
+            default_factory=lambda: list(),
             description="The entries to add to the list. This is the batch version of the `entry` field.",
             advanced=True,
         )
@@ -292,7 +319,7 @@ class AddToListBlock(Block):
             ],
         )
 
-    def run(self, input_data: Input, **kwargs) -> BlockOutput:
+    async def run(self, input_data: Input, **kwargs) -> BlockOutput:
         entries_added = input_data.entries.copy()
         if input_data.entry:
             entries_added.append(input_data.entry)
@@ -339,7 +366,7 @@ class FindInListBlock(Block):
             ],
         )
 
-    def run(self, input_data: Input, **kwargs) -> BlockOutput:
+    async def run(self, input_data: Input, **kwargs) -> BlockOutput:
         try:
             yield "index", input_data.list.index(input_data.value)
             yield "found", True
@@ -369,7 +396,7 @@ class NoteBlock(Block):
             block_type=BlockType.NOTE,
         )
 
-    def run(self, input_data: Input, **kwargs) -> BlockOutput:
+    async def run(self, input_data: Input, **kwargs) -> BlockOutput:
         yield "output", input_data.text
 
 
@@ -415,7 +442,7 @@ class CreateDictionaryBlock(Block):
             ],
         )
 
-    def run(self, input_data: Input, **kwargs) -> BlockOutput:
+    async def run(self, input_data: Input, **kwargs) -> BlockOutput:
         try:
             # The values are already validated by Pydantic schema
             yield "dictionary", input_data.values
@@ -463,7 +490,7 @@ class CreateListBlock(Block):
             ],
         )
 
-    def run(self, input_data: Input, **kwargs) -> BlockOutput:
+    async def run(self, input_data: Input, **kwargs) -> BlockOutput:
         try:
             # The values are already validated by Pydantic schema
             yield "list", input_data.values
@@ -498,7 +525,7 @@ class UniversalTypeConverterBlock(Block):
             output_schema=UniversalTypeConverterBlock.Output,
         )
 
-    def run(self, input_data: Input, **kwargs) -> BlockOutput:
+    async def run(self, input_data: Input, **kwargs) -> BlockOutput:
         try:
             converted_value = convert(
                 input_data.value,

autogpt_platform/backend/backend/blocks/block.py

@@ -38,7 +38,7 @@ class BlockInstallationBlock(Block):
             disabled=True,
         )
 
-    def run(self, input_data: Input, **kwargs) -> BlockOutput:
+    async def run(self, input_data: Input, **kwargs) -> BlockOutput:
         code = input_data.code
 
         if search := re.search(r"class (\w+)\(Block\):", code):
@@ -64,7 +64,7 @@ class BlockInstallationBlock(Block):
 
             from backend.util.test import execute_block_test
 
-            execute_block_test(block)
+            await execute_block_test(block)
             yield "success", "Block installed successfully."
         except Exception as e:
             os.remove(file_path)

autogpt_platform/backend/backend/blocks/branching.py

@@ -70,7 +70,7 @@ class ConditionBlock(Block):
             ],
         )
 
-    def run(self, input_data: Input, **kwargs) -> BlockOutput:
+    async def run(self, input_data: Input, **kwargs) -> BlockOutput:
         operator = input_data.operator
 
         value1 = input_data.value1
@@ -180,7 +180,7 @@ class IfInputMatchesBlock(Block):
             ],
         )
 
-    def run(self, input_data: Input, **kwargs) -> BlockOutput:
+    async def run(self, input_data: Input, **kwargs) -> BlockOutput:
         if input_data.input == input_data.value or input_data.input is input_data.value:
             yield "result", True
             yield "yes_output", input_data.yes_value

autogpt_platform/backend/backend/blocks/code_executor.py

@@ -1,7 +1,7 @@
 from enum import Enum
 from typing import Literal
 
-from e2b_code_interpreter import Sandbox
+from e2b_code_interpreter import AsyncSandbox
 from pydantic import SecretStr
 
 from backend.data.block import Block, BlockCategory, BlockOutput, BlockSchema
@@ -55,7 +55,7 @@ class CodeExecutionBlock(Block):
                 "These commands are executed with `sh`, in the foreground."
             ),
             placeholder="pip install cowsay",
-            default=[],
+            default_factory=list,
             advanced=False,
         )
 
@@ -123,7 +123,7 @@ class CodeExecutionBlock(Block):
             },
         )
 
-    def execute_code(
+    async def execute_code(
         self,
         code: str,
         language: ProgrammingLanguage,
@@ -135,21 +135,21 @@ class CodeExecutionBlock(Block):
         try:
             sandbox = None
             if template_id:
-                sandbox = Sandbox(
+                sandbox = await AsyncSandbox.create(
                     template=template_id, api_key=api_key, timeout=timeout
                 )
             else:
-                sandbox = Sandbox(api_key=api_key, timeout=timeout)
+                sandbox = await AsyncSandbox.create(api_key=api_key, timeout=timeout)
 
             if not sandbox:
                 raise Exception("Sandbox not created")
 
             # Running setup commands
             for cmd in setup_commands:
-                sandbox.commands.run(cmd)
+                await sandbox.commands.run(cmd)
 
             # Executing the code
-            execution = sandbox.run_code(
+            execution = await sandbox.run_code(
                 code,
                 language=language.value,
                 on_error=lambda e: sandbox.kill(),  # Kill the sandbox if there is an error
@@ -167,11 +167,11 @@ class CodeExecutionBlock(Block):
         except Exception as e:
             raise e
 
-    def run(
+    async def run(
         self, input_data: Input, *, credentials: APIKeyCredentials, **kwargs
     ) -> BlockOutput:
         try:
-            response, stdout_logs, stderr_logs = self.execute_code(
+            response, stdout_logs, stderr_logs = await self.execute_code(
                 input_data.code,
                 input_data.language,
                 input_data.setup_commands,
@@ -207,7 +207,7 @@ class InstantiationBlock(Block):
                 "These commands are executed with `sh`, in the foreground."
             ),
             placeholder="pip install cowsay",
-            default=[],
+            default_factory=list,
             advanced=False,
         )
 
@@ -278,11 +278,11 @@ class InstantiationBlock(Block):
             },
         )
 
-    def run(
+    async def run(
         self, input_data: Input, *, credentials: APIKeyCredentials, **kwargs
     ) -> BlockOutput:
         try:
-            sandbox_id, response, stdout_logs, stderr_logs = self.execute_code(
+            sandbox_id, response, stdout_logs, stderr_logs = await self.execute_code(
                 input_data.setup_code,
                 input_data.language,
                 input_data.setup_commands,
@@ -303,7 +303,7 @@ class InstantiationBlock(Block):
         except Exception as e:
             yield "error", str(e)
 
-    def execute_code(
+    async def execute_code(
         self,
         code: str,
         language: ProgrammingLanguage,
@@ -315,21 +315,21 @@ class InstantiationBlock(Block):
         try:
             sandbox = None
             if template_id:
-                sandbox = Sandbox(
+                sandbox = await AsyncSandbox.create(
                     template=template_id, api_key=api_key, timeout=timeout
                 )
             else:
-                sandbox = Sandbox(api_key=api_key, timeout=timeout)
+                sandbox = await AsyncSandbox.create(api_key=api_key, timeout=timeout)
 
             if not sandbox:
                 raise Exception("Sandbox not created")
 
             # Running setup commands
             for cmd in setup_commands:
-                sandbox.commands.run(cmd)
+                await sandbox.commands.run(cmd)
 
             # Executing the code
-            execution = sandbox.run_code(
+            execution = await sandbox.run_code(
                 code,
                 language=language.value,
                 on_error=lambda e: sandbox.kill(),  # Kill the sandbox if there is an error
@@ -409,7 +409,7 @@ class StepExecutionBlock(Block):
             },
         )
 
-    def execute_step_code(
+    async def execute_step_code(
         self,
         sandbox_id: str,
         code: str,
@@ -417,12 +417,12 @@ class StepExecutionBlock(Block):
         api_key: str,
     ):
         try:
-            sandbox = Sandbox.connect(sandbox_id=sandbox_id, api_key=api_key)
+            sandbox = await AsyncSandbox.connect(sandbox_id=sandbox_id, api_key=api_key)
             if not sandbox:
                 raise Exception("Sandbox not found")
 
             # Executing the code
-            execution = sandbox.run_code(code, language=language.value)
+            execution = await sandbox.run_code(code, language=language.value)
 
             if execution.error:
                 raise Exception(execution.error)
@@ -436,11 +436,11 @@ class StepExecutionBlock(Block):
         except Exception as e:
             raise e
 
-    def run(
+    async def run(
         self, input_data: Input, *, credentials: APIKeyCredentials, **kwargs
     ) -> BlockOutput:
         try:
-            response, stdout_logs, stderr_logs = self.execute_step_code(
+            response, stdout_logs, stderr_logs = await self.execute_step_code(
                 input_data.sandbox_id,
                 input_data.step_code,
                 input_data.language,

autogpt_platform/backend/backend/blocks/code_extraction_block.py

@@ -49,7 +49,7 @@ class CodeExtractionBlock(Block):
             ],
         )
 
-    def run(self, input_data: Input, **kwargs) -> BlockOutput:
+    async def run(self, input_data: Input, **kwargs) -> BlockOutput:
         # List of supported programming languages with mapped aliases
         language_aliases = {
             "html": ["html", "htm"],

autogpt_platform/backend/backend/blocks/compass/triggers.py

@@ -56,5 +56,5 @@ class CompassAITriggerBlock(Block):
             # ],
         )
 
-    def run(self, input_data: Input, **kwargs) -> BlockOutput:
+    async def run(self, input_data: Input, **kwargs) -> BlockOutput:
         yield "transcription", input_data.payload.transcription

autogpt_platform/backend/backend/blocks/count_words_and_char_block.py

@@ -30,7 +30,7 @@ class WordCharacterCountBlock(Block):
             test_output=[("word_count", 4), ("character_count", 19)],
         )
 
-    def run(self, input_data: Input, **kwargs) -> BlockOutput:
+    async def run(self, input_data: Input, **kwargs) -> BlockOutput:
         try:
             text = input_data.text
             word_count = len(text.split())

autogpt_platform/backend/backend/blocks/csv.py

@@ -34,7 +34,7 @@ class ReadCsvBlock(Block):
         )
         skip_columns: list[str] = SchemaField(
             description="The columns to skip from the start of the row",
-            default=[],
+            default_factory=list,
         )
 
     class Output(BlockSchema):
@@ -69,7 +69,7 @@ class ReadCsvBlock(Block):
             ],
         )
 
-    def run(self, input_data: Input, **kwargs) -> BlockOutput:
+    async def run(self, input_data: Input, **kwargs) -> BlockOutput:
         import csv
         from io import StringIO
 

autogpt_platform/backend/backend/blocks/decoder_block.py

@@ -34,6 +34,6 @@ This is a "quoted" string.""",
             ],
         )
 
-    def run(self, input_data: Input, **kwargs) -> BlockOutput:
+    async def run(self, input_data: Input, **kwargs) -> BlockOutput:
         decoded_text = codecs.decode(input_data.text, "unicode_escape")
         yield "decoded_text", decoded_text

autogpt_platform/backend/backend/blocks/discord.py

@@ -1,4 +1,3 @@
-import asyncio
 from typing import Literal
 
 import aiohttp
@@ -74,7 +73,11 @@ class ReadDiscordMessagesBlock(Block):
                 ("username", "test_user"),
             ],
             test_mock={
-                "run_bot": lambda token: asyncio.Future()  # Create a Future object for mocking
+                "run_bot": lambda token: {
+                    "output_data": "Hello!\n\nFile from user: example.txt\nContent: This is the content of the file.",
+                    "channel_name": "general",
+                    "username": "test_user",
+                }
             },
         )
 
@@ -106,37 +109,24 @@ class ReadDiscordMessagesBlock(Block):
                 if attachment.filename.endswith((".txt", ".py")):
                     async with aiohttp.ClientSession() as session:
                         async with session.get(attachment.url) as response:
-                            file_content = await response.text()
+                            file_content = response.text()
                             self.output_data += f"\n\nFile from user: {attachment.filename}\nContent: {file_content}"
 
             await client.close()
 
         await client.start(token.get_secret_value())
 
-    def run(
+    async def run(
         self, input_data: Input, *, credentials: APIKeyCredentials, **kwargs
     ) -> BlockOutput:
-        while True:
-            for output_name, output_value in self.__run(input_data, credentials):
-                yield output_name, output_value
-            break
+        async for output_name, output_value in self.__run(input_data, credentials):
+            yield output_name, output_value
 
-    def __run(self, input_data: Input, credentials: APIKeyCredentials) -> BlockOutput:
+    async def __run(
+        self, input_data: Input, credentials: APIKeyCredentials
+    ) -> BlockOutput:
         try:
-            loop = asyncio.get_event_loop()
-            future = self.run_bot(credentials.api_key)
-
-            # If it's a Future (mock), set the result
-            if isinstance(future, asyncio.Future):
-                future.set_result(
-                    {
-                        "output_data": "Hello!\n\nFile from user: example.txt\nContent: This is the content of the file.",
-                        "channel_name": "general",
-                        "username": "test_user",
-                    }
-                )
-
-            result = loop.run_until_complete(future)
+            result = await self.run_bot(credentials.api_key)
 
             # For testing purposes, use the mocked result
             if isinstance(result, dict):
@@ -190,7 +180,7 @@ class SendDiscordMessageBlock(Block):
             },
             test_output=[("status", "Message sent")],
             test_mock={
-                "send_message": lambda token, channel_name, message_content: asyncio.Future()
+                "send_message": lambda token, channel_name, message_content: "Message sent"
             },
             test_credentials=TEST_CREDENTIALS,
         )
@@ -222,23 +212,16 @@ class SendDiscordMessageBlock(Block):
         """Splits a message into chunks not exceeding the Discord limit."""
         return [message[i : i + limit] for i in range(0, len(message), limit)]
 
-    def run(
+    async def run(
         self, input_data: Input, *, credentials: APIKeyCredentials, **kwargs
     ) -> BlockOutput:
         try:
-            loop = asyncio.get_event_loop()
-            future = self.send_message(
+            result = await self.send_message(
                 credentials.api_key.get_secret_value(),
                 input_data.channel_name,
                 input_data.message_content,
             )
 
-            # If it's a Future (mock), set the result
-            if isinstance(future, asyncio.Future):
-                future.set_result("Message sent")
-
-            result = loop.run_until_complete(future)
-
             # For testing purposes, use the mocked result
             if isinstance(result, str):
                 self.output_data = result

autogpt_platform/backend/backend/blocks/email_block.py

@@ -121,7 +121,7 @@ class SendEmailBlock(Block):
 
         return "Email sent successfully"
 
-    def run(
+    async def run(
         self, input_data: Input, *, credentials: SMTPCredentials, **kwargs
     ) -> BlockOutput:
         yield "status", self.send_email(

autogpt_platform/backend/backend/blocks/exa/contents.py

@@ -9,7 +9,7 @@ from backend.blocks.exa._auth import (
 )
 from backend.data.block import Block, BlockCategory, BlockOutput, BlockSchema
 from backend.data.model import SchemaField
-from backend.util.request import requests
+from backend.util.request import Requests
 
 
 class ContentRetrievalSettings(BaseModel):
@@ -49,7 +49,7 @@ class ExaContentsBlock(Block):
     class Output(BlockSchema):
         results: list = SchemaField(
             description="List of document contents",
-            default=[],
+            default_factory=list,
         )
         error: str = SchemaField(description="Error message if the request failed")
 
@@ -62,7 +62,7 @@ class ExaContentsBlock(Block):
             output_schema=ExaContentsBlock.Output,
         )
 
-    def run(
+    async def run(
         self, input_data: Input, *, credentials: ExaCredentials, **kwargs
     ) -> BlockOutput:
         url = "https://api.exa.ai/contents"
@@ -79,10 +79,8 @@ class ExaContentsBlock(Block):
         }
 
         try:
-            response = requests.post(url, headers=headers, json=payload)
-            response.raise_for_status()
+            response = await Requests().post(url, headers=headers, json=payload)
             data = response.json()
             yield "results", data.get("results", [])
         except Exception as e:
             yield "error", str(e)
-            yield "results", []

autogpt_platform/backend/backend/blocks/exa/search.py

@@ -9,7 +9,7 @@ from backend.blocks.exa._auth import (
 from backend.blocks.exa.helpers import ContentSettings
 from backend.data.block import Block, BlockCategory, BlockOutput, BlockSchema
 from backend.data.model import SchemaField
-from backend.util.request import requests
+from backend.util.request import Requests
 
 
 class ExaSearchBlock(Block):
@@ -38,11 +38,11 @@ class ExaSearchBlock(Block):
         )
         include_domains: List[str] = SchemaField(
             description="Domains to include in search",
-            default=[],
+            default_factory=list,
         )
         exclude_domains: List[str] = SchemaField(
             description="Domains to exclude from search",
-            default=[],
+            default_factory=list,
             advanced=True,
         )
         start_crawl_date: datetime = SchemaField(
@@ -59,12 +59,12 @@ class ExaSearchBlock(Block):
         )
         include_text: List[str] = SchemaField(
             description="Text patterns to include",
-            default=[],
+            default_factory=list,
             advanced=True,
         )
         exclude_text: List[str] = SchemaField(
             description="Text patterns to exclude",
-            default=[],
+            default_factory=list,
             advanced=True,
         )
         contents: ContentSettings = SchemaField(
@@ -76,7 +76,10 @@ class ExaSearchBlock(Block):
     class Output(BlockSchema):
         results: list = SchemaField(
             description="List of search results",
-            default=[],
+            default_factory=list,
+        )
+        error: str = SchemaField(
+            description="Error message if the request failed",
         )
 
     def __init__(self):
@@ -88,7 +91,7 @@ class ExaSearchBlock(Block):
             output_schema=ExaSearchBlock.Output,
         )
 
-    def run(
+    async def run(
         self, input_data: Input, *, credentials: ExaCredentials, **kwargs
     ) -> BlockOutput:
         url = "https://api.exa.ai/search"
@@ -133,11 +136,9 @@ class ExaSearchBlock(Block):
                 payload[api_field] = value
 
         try:
-            response = requests.post(url, headers=headers, json=payload)
-            response.raise_for_status()
+            response = await Requests().post(url, headers=headers, json=payload)
             data = response.json()
             # Extract just the results array from the response
             yield "results", data.get("results", [])
         except Exception as e:
             yield "error", str(e)
-            yield "results", []

autogpt_platform/backend/backend/blocks/exa/similar.py

@@ -8,7 +8,7 @@ from backend.blocks.exa._auth import (
 )
 from backend.data.block import Block, BlockCategory, BlockOutput, BlockSchema
 from backend.data.model import SchemaField
-from backend.util.request import requests
+from backend.util.request import Requests
 
 from .helpers import ContentSettings
 
@@ -26,12 +26,12 @@ class ExaFindSimilarBlock(Block):
         )
         include_domains: List[str] = SchemaField(
             description="Domains to include in search",
-            default=[],
+            default_factory=list,
             advanced=True,
         )
         exclude_domains: List[str] = SchemaField(
             description="Domains to exclude from search",
-            default=[],
+            default_factory=list,
             advanced=True,
         )
         start_crawl_date: datetime = SchemaField(
@@ -48,12 +48,12 @@ class ExaFindSimilarBlock(Block):
         )
         include_text: List[str] = SchemaField(
             description="Text patterns to include (max 1 string, up to 5 words)",
-            default=[],
+            default_factory=list,
             advanced=True,
         )
         exclude_text: List[str] = SchemaField(
             description="Text patterns to exclude (max 1 string, up to 5 words)",
-            default=[],
+            default_factory=list,
             advanced=True,
         )
         contents: ContentSettings = SchemaField(
@@ -65,8 +65,9 @@ class ExaFindSimilarBlock(Block):
     class Output(BlockSchema):
         results: List[Any] = SchemaField(
             description="List of similar documents with title, URL, published date, author, and score",
-            default=[],
+            default_factory=list,
         )
+        error: str = SchemaField(description="Error message if the request failed")
 
     def __init__(self):
         super().__init__(
@@ -77,7 +78,7 @@ class ExaFindSimilarBlock(Block):
             output_schema=ExaFindSimilarBlock.Output,
         )
 
-    def run(
+    async def run(
         self, input_data: Input, *, credentials: ExaCredentials, **kwargs
     ) -> BlockOutput:
         url = "https://api.exa.ai/findSimilar"
@@ -119,10 +120,8 @@ class ExaFindSimilarBlock(Block):
                 payload[api_field] = value.strftime("%Y-%m-%dT%H:%M:%S.000Z")
 
         try:
-            response = requests.post(url, headers=headers, json=payload)
-            response.raise_for_status()
+            response = await Requests().post(url, headers=headers, json=payload)
             data = response.json()
             yield "results", data.get("results", [])
         except Exception as e:
             yield "error", str(e)
-            yield "results", []

autogpt_platform/backend/backend/blocks/fal/ai_video_generator.py

@@ -1,10 +1,8 @@
+import asyncio
 import logging
-import time
 from enum import Enum
 from typing import Any
 
-import httpx
-
 from backend.blocks.fal._auth import (
     TEST_CREDENTIALS,
     TEST_CREDENTIALS_INPUT,
@@ -14,6 +12,7 @@ from backend.blocks.fal._auth import (
 )
 from backend.data.block import Block, BlockCategory, BlockOutput, BlockSchema
 from backend.data.model import SchemaField
+from backend.util.request import ClientResponseError, Requests
 
 logger = logging.getLogger(__name__)
 
@@ -21,6 +20,7 @@ logger = logging.getLogger(__name__)
 class FalModel(str, Enum):
     MOCHI = "fal-ai/mochi-v1"
     LUMA = "fal-ai/luma-dream-machine"
+    VEO3 = "fal-ai/veo3"
 
 
 class AIVideoGeneratorBlock(Block):
@@ -42,7 +42,7 @@ class AIVideoGeneratorBlock(Block):
             description="Error message if video generation failed."
         )
         logs: list[str] = SchemaField(
-            description="Generation progress logs.", optional=True
+            description="Generation progress logs.",
         )
 
     def __init__(self):
@@ -65,35 +65,37 @@ class AIVideoGeneratorBlock(Block):
         )
 
     def _get_headers(self, api_key: str) -> dict[str, str]:
-        """Get headers for FAL API requests."""
+        """Get headers for FAL API Requests."""
         return {
             "Authorization": f"Key {api_key}",
             "Content-Type": "application/json",
         }
 
-    def _submit_request(
+    async def _submit_request(
         self, url: str, headers: dict[str, str], data: dict[str, Any]
     ) -> dict[str, Any]:
         """Submit a request to the FAL API."""
         try:
-            response = httpx.post(url, headers=headers, json=data)
-            response.raise_for_status()
+            response = await Requests().post(url, headers=headers, json=data)
             return response.json()
-        except httpx.HTTPError as e:
+        except ClientResponseError as e:
             logger.error(f"FAL API request failed: {str(e)}")
             raise RuntimeError(f"Failed to submit request: {str(e)}")
 
-    def _poll_status(self, status_url: str, headers: dict[str, str]) -> dict[str, Any]:
+    async def _poll_status(
+        self, status_url: str, headers: dict[str, str]
+    ) -> dict[str, Any]:
         """Poll the status endpoint until completion or failure."""
         try:
-            response = httpx.get(status_url, headers=headers)
-            response.raise_for_status()
+            response = await Requests().get(status_url, headers=headers)
             return response.json()
-        except httpx.HTTPError as e:
+        except ClientResponseError as e:
             logger.error(f"Failed to get status: {str(e)}")
             raise RuntimeError(f"Failed to get status: {str(e)}")
 
-    def generate_video(self, input_data: Input, credentials: FalCredentials) -> str:
+    async def generate_video(
+        self, input_data: Input, credentials: FalCredentials
+    ) -> str:
         """Generate video using the specified FAL model."""
         base_url = "https://queue.fal.run"
         api_key = credentials.api_key.get_secret_value()
@@ -102,13 +104,16 @@ class AIVideoGeneratorBlock(Block):
         # Submit generation request
         submit_url = f"{base_url}/{input_data.model.value}"
         submit_data = {"prompt": input_data.prompt}
+        if input_data.model == FalModel.VEO3:
+            submit_data["generate_audio"] = True  # type: ignore
 
         seen_logs = set()
 
         try:
             # Submit request to queue
-            submit_response = httpx.post(submit_url, headers=headers, json=submit_data)
-            submit_response.raise_for_status()
+            submit_response = await Requests().post(
+                submit_url, headers=headers, json=submit_data
+            )
             request_data = submit_response.json()
 
             # Get request_id and urls from initial response
@@ -119,14 +124,23 @@ class AIVideoGeneratorBlock(Block):
             if not all([request_id, status_url, result_url]):
                 raise ValueError("Missing required data in submission response")
 
+            # Ensure status_url is a string
+            if not isinstance(status_url, str):
+                raise ValueError("Invalid status URL format")
+
+            # Ensure result_url is a string
+            if not isinstance(result_url, str):
+                raise ValueError("Invalid result URL format")
+
             # Poll for status with exponential backoff
             max_attempts = 30
             attempt = 0
             base_wait_time = 5
 
             while attempt < max_attempts:
-                status_response = httpx.get(f"{status_url}?logs=1", headers=headers)
-                status_response.raise_for_status()
+                status_response = await Requests().get(
+                    f"{status_url}?logs=1", headers=headers
+                )
                 status_data = status_response.json()
 
                 # Process new logs only
@@ -149,8 +163,7 @@ class AIVideoGeneratorBlock(Block):
                 status = status_data.get("status")
                 if status == "COMPLETED":
                     # Get the final result
-                    result_response = httpx.get(result_url, headers=headers)
-                    result_response.raise_for_status()
+                    result_response = await Requests().get(result_url, headers=headers)
                     result_data = result_response.json()
 
                     if "video" not in result_data or not isinstance(
@@ -159,8 +172,8 @@ class AIVideoGeneratorBlock(Block):
                         raise ValueError("Invalid response format - missing video data")
 
                     video_url = result_data["video"].get("url")
-                    if not video_url:
-                        raise ValueError("No video URL in response")
+                    if not video_url or not isinstance(video_url, str):
+                        raise ValueError("No valid video URL in response")
 
                     return video_url
 
@@ -180,19 +193,19 @@ class AIVideoGeneratorBlock(Block):
                     logger.info(f"[FAL Generation] Status: Unknown status: {status}")
 
                 wait_time = min(base_wait_time * (2**attempt), 60)  # Cap at 60 seconds
-                time.sleep(wait_time)
+                await asyncio.sleep(wait_time)
                 attempt += 1
 
             raise RuntimeError("Maximum polling attempts reached")
 
-        except httpx.HTTPError as e:
+        except ClientResponseError as e:
             raise RuntimeError(f"API request failed: {str(e)}")
 
-    def run(
+    async def run(
         self, input_data: Input, *, credentials: FalCredentials, **kwargs
     ) -> BlockOutput:
         try:
-            video_url = self.generate_video(input_data, credentials)
+            video_url = await self.generate_video(input_data, credentials)
             yield "video_url", video_url
         except Exception as e:
             error_message = str(e)

autogpt_platform/backend/backend/blocks/flux_kontext.py

@@ -0,0 +1,174 @@
+from enum import Enum
+from typing import Literal, Optional
+
+from pydantic import SecretStr
+from replicate.client import Client as ReplicateClient
+from replicate.helpers import FileOutput
+
+from backend.data.block import Block, BlockCategory, BlockOutput, BlockSchema
+from backend.data.model import (
+    APIKeyCredentials,
+    CredentialsField,
+    CredentialsMetaInput,
+    SchemaField,
+)
+from backend.integrations.providers import ProviderName
+from backend.util.file import MediaFileType
+
+TEST_CREDENTIALS = APIKeyCredentials(
+    id="01234567-89ab-cdef-0123-456789abcdef",
+    provider="replicate",
+    api_key=SecretStr("mock-replicate-api-key"),
+    title="Mock Replicate API key",
+    expires_at=None,
+)
+TEST_CREDENTIALS_INPUT = {
+    "provider": TEST_CREDENTIALS.provider,
+    "id": TEST_CREDENTIALS.id,
+    "type": TEST_CREDENTIALS.type,
+    "title": TEST_CREDENTIALS.type,
+}
+
+
+class FluxKontextModelName(str, Enum):
+    PRO = "Flux Kontext Pro"
+    MAX = "Flux Kontext Max"
+
+    @property
+    def api_name(self) -> str:
+        return f"black-forest-labs/flux-kontext-{self.name.lower()}"
+
+
+class AspectRatio(str, Enum):
+    MATCH_INPUT_IMAGE = "match_input_image"
+    ASPECT_1_1 = "1:1"
+    ASPECT_16_9 = "16:9"
+    ASPECT_9_16 = "9:16"
+    ASPECT_4_3 = "4:3"
+    ASPECT_3_4 = "3:4"
+    ASPECT_3_2 = "3:2"
+    ASPECT_2_3 = "2:3"
+    ASPECT_4_5 = "4:5"
+    ASPECT_5_4 = "5:4"
+    ASPECT_21_9 = "21:9"
+    ASPECT_9_21 = "9:21"
+    ASPECT_2_1 = "2:1"
+    ASPECT_1_2 = "1:2"
+
+
+class AIImageEditorBlock(Block):
+    class Input(BlockSchema):
+        credentials: CredentialsMetaInput[
+            Literal[ProviderName.REPLICATE], Literal["api_key"]
+        ] = CredentialsField(
+            description="Replicate API key with permissions for Flux Kontext models",
+        )
+        prompt: str = SchemaField(
+            description="Text instruction describing the desired edit",
+            title="Prompt",
+        )
+        input_image: Optional[MediaFileType] = SchemaField(
+            description="Reference image URI (jpeg, png, gif, webp)",
+            default=None,
+            title="Input Image",
+        )
+        aspect_ratio: AspectRatio = SchemaField(
+            description="Aspect ratio of the generated image",
+            default=AspectRatio.MATCH_INPUT_IMAGE,
+            title="Aspect Ratio",
+            advanced=False,
+        )
+        seed: Optional[int] = SchemaField(
+            description="Random seed. Set for reproducible generation",
+            default=None,
+            title="Seed",
+            advanced=True,
+        )
+        model: FluxKontextModelName = SchemaField(
+            description="Model variant to use",
+            default=FluxKontextModelName.PRO,
+            title="Model",
+        )
+
+    class Output(BlockSchema):
+        output_image: MediaFileType = SchemaField(
+            description="URL of the transformed image"
+        )
+        error: str = SchemaField(description="Error message if generation failed")
+
+    def __init__(self):
+        super().__init__(
+            id="3fd9c73d-4370-4925-a1ff-1b86b99fabfa",
+            description=(
+                "Edit images using BlackForest Labs' Flux Kontext models. Provide a prompt "
+                "and optional reference image to generate a modified image."
+            ),
+            categories={BlockCategory.AI, BlockCategory.MULTIMEDIA},
+            input_schema=AIImageEditorBlock.Input,
+            output_schema=AIImageEditorBlock.Output,
+            test_input={
+                "prompt": "Add a hat to the cat",
+                "input_image": "https://example.com/cat.png",
+                "aspect_ratio": AspectRatio.MATCH_INPUT_IMAGE,
+                "seed": None,
+                "model": FluxKontextModelName.PRO,
+                "credentials": TEST_CREDENTIALS_INPUT,
+            },
+            test_output=[
+                ("output_image", "https://replicate.com/output/edited-image.png"),
+            ],
+            test_mock={
+                "run_model": lambda *args, **kwargs: "https://replicate.com/output/edited-image.png",
+            },
+            test_credentials=TEST_CREDENTIALS,
+        )
+
+    async def run(
+        self,
+        input_data: Input,
+        *,
+        credentials: APIKeyCredentials,
+        **kwargs,
+    ) -> BlockOutput:
+        result = await self.run_model(
+            api_key=credentials.api_key,
+            model_name=input_data.model.api_name,
+            prompt=input_data.prompt,
+            input_image=input_data.input_image,
+            aspect_ratio=input_data.aspect_ratio.value,
+            seed=input_data.seed,
+        )
+        yield "output_image", result
+
+    async def run_model(
+        self,
+        api_key: SecretStr,
+        model_name: str,
+        prompt: str,
+        input_image: Optional[MediaFileType],
+        aspect_ratio: str,
+        seed: Optional[int],
+    ) -> MediaFileType:
+        client = ReplicateClient(api_token=api_key.get_secret_value())
+        input_params = {
+            "prompt": prompt,
+            "input_image": input_image,
+            "aspect_ratio": aspect_ratio,
+            **({"seed": seed} if seed is not None else {}),
+        }
+
+        output: FileOutput | list[FileOutput] = await client.async_run(  # type: ignore
+            model_name,
+            input=input_params,
+            wait=False,
+        )
+
+        if isinstance(output, list) and output:
+            output = output[0]
+
+        if isinstance(output, FileOutput):
+            return MediaFileType(output.url)
+        if isinstance(output, str):
+            return MediaFileType(output)
+
+        raise ValueError("No output received")

autogpt_platform/backend/backend/blocks/generic_webhook/triggers.py

@@ -0,0 +1,51 @@
+from backend.data.block import (
+    Block,
+    BlockCategory,
+    BlockManualWebhookConfig,
+    BlockOutput,
+    BlockSchema,
+)
+from backend.data.model import SchemaField
+from backend.integrations.providers import ProviderName
+from backend.integrations.webhooks.generic import GenericWebhookType
+
+
+class GenericWebhookTriggerBlock(Block):
+    class Input(BlockSchema):
+        payload: dict = SchemaField(hidden=True, default_factory=dict)
+        constants: dict = SchemaField(
+            description="The constants to be set when the block is put on the graph",
+            default_factory=dict,
+        )
+
+    class Output(BlockSchema):
+        payload: dict = SchemaField(
+            description="The complete webhook payload that was received from the generic webhook."
+        )
+        constants: dict = SchemaField(
+            description="The constants to be set when the block is put on the graph"
+        )
+
+    example_payload = {"message": "Hello, World!"}
+
+    def __init__(self):
+        super().__init__(
+            id="8fa8c167-2002-47ce-aba8-97572fc5d387",
+            description="This block will output the contents of the generic input for the webhook.",
+            categories={BlockCategory.INPUT},
+            input_schema=GenericWebhookTriggerBlock.Input,
+            output_schema=GenericWebhookTriggerBlock.Output,
+            webhook_config=BlockManualWebhookConfig(
+                provider=ProviderName.GENERIC_WEBHOOK,
+                webhook_type=GenericWebhookType.PLAIN,
+            ),
+            test_input={"constants": {"key": "value"}, "payload": self.example_payload},
+            test_output=[
+                ("constants", {"key": "value"}),
+                ("payload", self.example_payload),
+            ],
+        )
+
+    async def run(self, input_data: Input, **kwargs) -> BlockOutput:
+        yield "constants", input_data.constants
+        yield "payload", input_data.payload

autogpt_platform/backend/backend/blocks/github/_api.py

@@ -1,19 +1,30 @@
+from typing import overload
 from urllib.parse import urlparse
 
 from backend.blocks.github._auth import (
     GithubCredentials,
     GithubFineGrainedAPICredentials,
 )
-from backend.util.request import Requests
+from backend.util.request import URL, Requests
 
 
-def _convert_to_api_url(url: str) -> str:
+@overload
+def _convert_to_api_url(url: str) -> str: ...
+
+
+@overload
+def _convert_to_api_url(url: URL) -> URL: ...
+
+
+def _convert_to_api_url(url: str | URL) -> str | URL:
     """
     Converts a standard GitHub URL to the corresponding GitHub API URL.
     Handles repository URLs, issue URLs, pull request URLs, and more.
     """
-    parsed_url = urlparse(url)
-    path_parts = parsed_url.path.strip("/").split("/")
+    if url_as_str := isinstance(url, str):
+        url = urlparse(url)
+
+    path_parts = url.path.strip("/").split("/")
 
     if len(path_parts) >= 2:
         owner, repo = path_parts[0], path_parts[1]
@@ -28,7 +39,7 @@ def _convert_to_api_url(url: str) -> str:
     else:
         raise ValueError("Invalid GitHub URL format.")
 
-    return api_url
+    return api_url if url_as_str else urlparse(api_url)
 
 
 def _get_headers(credentials: GithubCredentials) -> dict[str, str]:

autogpt_platform/backend/backend/blocks/github/checks.py

@@ -129,7 +129,7 @@ class GithubCreateCheckRunBlock(Block):
         )
 
     @staticmethod
-    def create_check_run(
+    async def create_check_run(
         credentials: GithubCredentials,
         repo_url: str,
         name: str,
@@ -172,7 +172,7 @@ class GithubCreateCheckRunBlock(Block):
             data.output = output_data
 
         check_runs_url = f"{repo_url}/check-runs"
-        response = api.post(
+        response = await api.post(
             check_runs_url, data=data.model_dump_json(exclude_none=True)
         )
         result = response.json()
@@ -183,7 +183,7 @@ class GithubCreateCheckRunBlock(Block):
             "status": result["status"],
         }
 
-    def run(
+    async def run(
         self,
         input_data: Input,
         *,
@@ -191,7 +191,7 @@ class GithubCreateCheckRunBlock(Block):
         **kwargs,
     ) -> BlockOutput:
         try:
-            result = self.create_check_run(
+            result = await self.create_check_run(
                 credentials=credentials,
                 repo_url=input_data.repo_url,
                 name=input_data.name,
@@ -292,7 +292,7 @@ class GithubUpdateCheckRunBlock(Block):
         )
 
     @staticmethod
-    def update_check_run(
+    async def update_check_run(
         credentials: GithubCredentials,
         repo_url: str,
         check_run_id: int,
@@ -325,7 +325,7 @@ class GithubUpdateCheckRunBlock(Block):
             data.output = output_data
 
         check_run_url = f"{repo_url}/check-runs/{check_run_id}"
-        response = api.patch(
+        response = await api.patch(
             check_run_url, data=data.model_dump_json(exclude_none=True)
         )
         result = response.json()
@@ -337,7 +337,7 @@ class GithubUpdateCheckRunBlock(Block):
             "conclusion": result.get("conclusion"),
         }
 
-    def run(
+    async def run(
         self,
         input_data: Input,
         *,
@@ -345,7 +345,7 @@ class GithubUpdateCheckRunBlock(Block):
         **kwargs,
     ) -> BlockOutput:
         try:
-            result = self.update_check_run(
+            result = await self.update_check_run(
                 credentials=credentials,
                 repo_url=input_data.repo_url,
                 check_run_id=input_data.check_run_id,

autogpt_platform/backend/backend/blocks/github/issues.py

@@ -80,7 +80,7 @@ class GithubCommentBlock(Block):
         )
 
     @staticmethod
-    def post_comment(
+    async def post_comment(
         credentials: GithubCredentials, issue_url: str, body_text: str
     ) -> tuple[int, str]:
         api = get_api(credentials)
@@ -88,18 +88,18 @@ class GithubCommentBlock(Block):
         if "pull" in issue_url:
             issue_url = issue_url.replace("pull", "issues")
         comments_url = issue_url + "/comments"
-        response = api.post(comments_url, json=data)
+        response = await api.post(comments_url, json=data)
         comment = response.json()
         return comment["id"], comment["html_url"]
 
-    def run(
+    async def run(
         self,
         input_data: Input,
         *,
         credentials: GithubCredentials,
         **kwargs,
     ) -> BlockOutput:
-        id, url = self.post_comment(
+        id, url = await self.post_comment(
             credentials,
             input_data.issue_url,
             input_data.comment,
@@ -171,7 +171,7 @@ class GithubUpdateCommentBlock(Block):
         )
 
     @staticmethod
-    def update_comment(
+    async def update_comment(
         credentials: GithubCredentials, comment_url: str, body_text: str
     ) -> tuple[int, str]:
         api = get_api(credentials, convert_urls=False)
@@ -179,11 +179,11 @@ class GithubUpdateCommentBlock(Block):
         url = convert_comment_url_to_api_endpoint(comment_url)
 
         logger.info(url)
-        response = api.patch(url, json=data)
+        response = await api.patch(url, json=data)
         comment = response.json()
         return comment["id"], comment["html_url"]
 
-    def run(
+    async def run(
         self,
         input_data: Input,
         *,
@@ -209,7 +209,7 @@ class GithubUpdateCommentBlock(Block):
             raise ValueError(
                 "Must provide either comment_url or comment_id and issue_url"
             )
-        id, url = self.update_comment(
+        id, url = await self.update_comment(
             credentials,
             input_data.comment_url,
             input_data.comment,
@@ -288,7 +288,7 @@ class GithubListCommentsBlock(Block):
         )
 
     @staticmethod
-    def list_comments(
+    async def list_comments(
         credentials: GithubCredentials, issue_url: str
     ) -> list[Output.CommentItem]:
         parsed_url = urlparse(issue_url)
@@ -305,7 +305,7 @@ class GithubListCommentsBlock(Block):
 
         # Set convert_urls=False since we're already providing an API URL
         api = get_api(credentials, convert_urls=False)
-        response = api.get(api_url)
+        response = await api.get(api_url)
         comments = response.json()
         parsed_comments: list[GithubListCommentsBlock.Output.CommentItem] = [
             {
@@ -318,18 +318,19 @@ class GithubListCommentsBlock(Block):
         ]
         return parsed_comments
 
-    def run(
+    async def run(
         self,
         input_data: Input,
         *,
         credentials: GithubCredentials,
         **kwargs,
     ) -> BlockOutput:
-        comments = self.list_comments(
+        comments = await self.list_comments(
             credentials,
             input_data.issue_url,
         )
-        yield from (("comment", comment) for comment in comments)
+        for comment in comments:
+            yield "comment", comment
         yield "comments", comments
 
 
@@ -381,24 +382,24 @@ class GithubMakeIssueBlock(Block):
         )
 
     @staticmethod
-    def create_issue(
+    async def create_issue(
         credentials: GithubCredentials, repo_url: str, title: str, body: str
     ) -> tuple[int, str]:
         api = get_api(credentials)
         data = {"title": title, "body": body}
         issues_url = repo_url + "/issues"
-        response = api.post(issues_url, json=data)
+        response = await api.post(issues_url, json=data)
         issue = response.json()
         return issue["number"], issue["html_url"]
 
-    def run(
+    async def run(
         self,
         input_data: Input,
         *,
         credentials: GithubCredentials,
         **kwargs,
     ) -> BlockOutput:
-        number, url = self.create_issue(
+        number, url = await self.create_issue(
             credentials,
             input_data.repo_url,
             input_data.title,
@@ -451,25 +452,25 @@ class GithubReadIssueBlock(Block):
         )
 
     @staticmethod
-    def read_issue(
+    async def read_issue(
         credentials: GithubCredentials, issue_url: str
     ) -> tuple[str, str, str]:
         api = get_api(credentials)
-        response = api.get(issue_url)
+        response = await api.get(issue_url)
         data = response.json()
         title = data.get("title", "No title found")
         body = data.get("body", "No body content found")
         user = data.get("user", {}).get("login", "No user found")
         return title, body, user
 
-    def run(
+    async def run(
         self,
         input_data: Input,
         *,
         credentials: GithubCredentials,
         **kwargs,
     ) -> BlockOutput:
-        title, body, user = self.read_issue(
+        title, body, user = await self.read_issue(
             credentials,
             input_data.issue_url,
         )
@@ -531,30 +532,30 @@ class GithubListIssuesBlock(Block):
         )
 
     @staticmethod
-    def list_issues(
+    async def list_issues(
         credentials: GithubCredentials, repo_url: str
     ) -> list[Output.IssueItem]:
         api = get_api(credentials)
         issues_url = repo_url + "/issues"
-        response = api.get(issues_url)
+        response = await api.get(issues_url)
         data = response.json()
         issues: list[GithubListIssuesBlock.Output.IssueItem] = [
             {"title": issue["title"], "url": issue["html_url"]} for issue in data
         ]
         return issues
 
-    def run(
+    async def run(
         self,
         input_data: Input,
         *,
         credentials: GithubCredentials,
         **kwargs,
     ) -> BlockOutput:
-        issues = self.list_issues(
+        for issue in await self.list_issues(
             credentials,
             input_data.repo_url,
-        )
-        yield from (("issue", issue) for issue in issues)
+        ):
+            yield "issue", issue
 
 
 class GithubAddLabelBlock(Block):
@@ -593,21 +594,23 @@ class GithubAddLabelBlock(Block):
         )
 
     @staticmethod
-    def add_label(credentials: GithubCredentials, issue_url: str, label: str) -> str:
+    async def add_label(
+        credentials: GithubCredentials, issue_url: str, label: str
+    ) -> str:
         api = get_api(credentials)
         data = {"labels": [label]}
         labels_url = issue_url + "/labels"
-        api.post(labels_url, json=data)
+        await api.post(labels_url, json=data)
         return "Label added successfully"
 
-    def run(
+    async def run(
         self,
         input_data: Input,
         *,
         credentials: GithubCredentials,
         **kwargs,
     ) -> BlockOutput:
-        status = self.add_label(
+        status = await self.add_label(
             credentials,
             input_data.issue_url,
             input_data.label,
@@ -653,20 +656,22 @@ class GithubRemoveLabelBlock(Block):
         )
 
     @staticmethod
-    def remove_label(credentials: GithubCredentials, issue_url: str, label: str) -> str:
+    async def remove_label(
+        credentials: GithubCredentials, issue_url: str, label: str
+    ) -> str:
         api = get_api(credentials)
         label_url = issue_url + f"/labels/{label}"
-        api.delete(label_url)
+        await api.delete(label_url)
         return "Label removed successfully"
 
-    def run(
+    async def run(
         self,
         input_data: Input,
         *,
         credentials: GithubCredentials,
         **kwargs,
     ) -> BlockOutput:
-        status = self.remove_label(
+        status = await self.remove_label(
             credentials,
             input_data.issue_url,
             input_data.label,
@@ -714,7 +719,7 @@ class GithubAssignIssueBlock(Block):
         )
 
     @staticmethod
-    def assign_issue(
+    async def assign_issue(
         credentials: GithubCredentials,
         issue_url: str,
         assignee: str,
@@ -722,17 +727,17 @@ class GithubAssignIssueBlock(Block):
         api = get_api(credentials)
         assignees_url = issue_url + "/assignees"
         data = {"assignees": [assignee]}
-        api.post(assignees_url, json=data)
+        await api.post(assignees_url, json=data)
         return "Issue assigned successfully"
 
-    def run(
+    async def run(
         self,
         input_data: Input,
         *,
         credentials: GithubCredentials,
         **kwargs,
     ) -> BlockOutput:
-        status = self.assign_issue(
+        status = await self.assign_issue(
             credentials,
             input_data.issue_url,
             input_data.assignee,
@@ -780,7 +785,7 @@ class GithubUnassignIssueBlock(Block):
         )
 
     @staticmethod
-    def unassign_issue(
+    async def unassign_issue(
         credentials: GithubCredentials,
         issue_url: str,
         assignee: str,
@@ -788,17 +793,17 @@ class GithubUnassignIssueBlock(Block):
         api = get_api(credentials)
         assignees_url = issue_url + "/assignees"
         data = {"assignees": [assignee]}
-        api.delete(assignees_url, json=data)
+        await api.delete(assignees_url, json=data)
         return "Issue unassigned successfully"
 
-    def run(
+    async def run(
         self,
         input_data: Input,
         *,
         credentials: GithubCredentials,
         **kwargs,
     ) -> BlockOutput:
-        status = self.unassign_issue(
+        status = await self.unassign_issue(
             credentials,
             input_data.issue_url,
             input_data.assignee,

autogpt_platform/backend/backend/blocks/github/pull_requests.py

@@ -65,28 +65,31 @@ class GithubListPullRequestsBlock(Block):
         )
 
     @staticmethod
-    def list_prs(credentials: GithubCredentials, repo_url: str) -> list[Output.PRItem]:
+    async def list_prs(
+        credentials: GithubCredentials, repo_url: str
+    ) -> list[Output.PRItem]:
         api = get_api(credentials)
         pulls_url = repo_url + "/pulls"
-        response = api.get(pulls_url)
+        response = await api.get(pulls_url)
         data = response.json()
         pull_requests: list[GithubListPullRequestsBlock.Output.PRItem] = [
             {"title": pr["title"], "url": pr["html_url"]} for pr in data
         ]
         return pull_requests
 
-    def run(
+    async def run(
         self,
         input_data: Input,
         *,
         credentials: GithubCredentials,
         **kwargs,
     ) -> BlockOutput:
-        pull_requests = self.list_prs(
+        pull_requests = await self.list_prs(
             credentials,
             input_data.repo_url,
         )
-        yield from (("pull_request", pr) for pr in pull_requests)
+        for pr in pull_requests:
+            yield "pull_request", pr
 
 
 class GithubMakePullRequestBlock(Block):
@@ -153,7 +156,7 @@ class GithubMakePullRequestBlock(Block):
         )
 
     @staticmethod
-    def create_pr(
+    async def create_pr(
         credentials: GithubCredentials,
         repo_url: str,
         title: str,
@@ -164,11 +167,11 @@ class GithubMakePullRequestBlock(Block):
         api = get_api(credentials)
         pulls_url = repo_url + "/pulls"
         data = {"title": title, "body": body, "head": head, "base": base}
-        response = api.post(pulls_url, json=data)
+        response = await api.post(pulls_url, json=data)
         pr_data = response.json()
         return pr_data["number"], pr_data["html_url"]
 
-    def run(
+    async def run(
         self,
         input_data: Input,
         *,
@@ -176,7 +179,7 @@ class GithubMakePullRequestBlock(Block):
         **kwargs,
     ) -> BlockOutput:
         try:
-            number, url = self.create_pr(
+            number, url = await self.create_pr(
                 credentials,
                 input_data.repo_url,
                 input_data.title,
@@ -242,39 +245,39 @@ class GithubReadPullRequestBlock(Block):
         )
 
     @staticmethod
-    def read_pr(credentials: GithubCredentials, pr_url: str) -> tuple[str, str, str]:
+    async def read_pr(
+        credentials: GithubCredentials, pr_url: str
+    ) -> tuple[str, str, str]:
         api = get_api(credentials)
-        # Adjust the URL to access the issue endpoint for PR metadata
         issue_url = pr_url.replace("/pull/", "/issues/")
-        response = api.get(issue_url)
+        response = await api.get(issue_url)
         data = response.json()
         title = data.get("title", "No title found")
         body = data.get("body", "No body content found")
-        author = data.get("user", {}).get("login", "No user found")
+        author = data.get("user", {}).get("login", "Unknown author")
         return title, body, author
 
     @staticmethod
-    def read_pr_changes(credentials: GithubCredentials, pr_url: str) -> str:
+    async def read_pr_changes(credentials: GithubCredentials, pr_url: str) -> str:
         api = get_api(credentials)
         files_url = prepare_pr_api_url(pr_url=pr_url, path="files")
-        response = api.get(files_url)
+        response = await api.get(files_url)
         files = response.json()
         changes = []
         for file in files:
-            filename = file.get("filename")
-            patch = file.get("patch")
-            if filename and patch:
-                changes.append(f"File: {filename}\n{patch}")
-        return "\n\n".join(changes)
+            filename = file.get("filename", "")
+            status = file.get("status", "")
+            changes.append(f"{filename}: {status}")
+        return "\n".join(changes)
 
-    def run(
+    async def run(
         self,
         input_data: Input,
         *,
         credentials: GithubCredentials,
         **kwargs,
     ) -> BlockOutput:
-        title, body, author = self.read_pr(
+        title, body, author = await self.read_pr(
             credentials,
             input_data.pr_url,
         )
@@ -283,7 +286,7 @@ class GithubReadPullRequestBlock(Block):
         yield "author", author
 
         if input_data.include_pr_changes:
-            changes = self.read_pr_changes(
+            changes = await self.read_pr_changes(
                 credentials,
                 input_data.pr_url,
             )
@@ -330,16 +333,16 @@ class GithubAssignPRReviewerBlock(Block):
         )
 
     @staticmethod
-    def assign_reviewer(
+    async def assign_reviewer(
         credentials: GithubCredentials, pr_url: str, reviewer: str
     ) -> str:
         api = get_api(credentials)
         reviewers_url = prepare_pr_api_url(pr_url=pr_url, path="requested_reviewers")
         data = {"reviewers": [reviewer]}
-        api.post(reviewers_url, json=data)
+        await api.post(reviewers_url, json=data)
         return "Reviewer assigned successfully"
 
-    def run(
+    async def run(
         self,
         input_data: Input,
         *,
@@ -347,7 +350,7 @@ class GithubAssignPRReviewerBlock(Block):
         **kwargs,
     ) -> BlockOutput:
         try:
-            status = self.assign_reviewer(
+            status = await self.assign_reviewer(
                 credentials,
                 input_data.pr_url,
                 input_data.reviewer,
@@ -397,16 +400,16 @@ class GithubUnassignPRReviewerBlock(Block):
         )
 
     @staticmethod
-    def unassign_reviewer(
+    async def unassign_reviewer(
         credentials: GithubCredentials, pr_url: str, reviewer: str
     ) -> str:
         api = get_api(credentials)
         reviewers_url = prepare_pr_api_url(pr_url=pr_url, path="requested_reviewers")
         data = {"reviewers": [reviewer]}
-        api.delete(reviewers_url, json=data)
+        await api.delete(reviewers_url, json=data)
         return "Reviewer unassigned successfully"
 
-    def run(
+    async def run(
         self,
         input_data: Input,
         *,
@@ -414,7 +417,7 @@ class GithubUnassignPRReviewerBlock(Block):
         **kwargs,
     ) -> BlockOutput:
         try:
-            status = self.unassign_reviewer(
+            status = await self.unassign_reviewer(
                 credentials,
                 input_data.pr_url,
                 input_data.reviewer,
@@ -477,12 +480,12 @@ class GithubListPRReviewersBlock(Block):
         )
 
     @staticmethod
-    def list_reviewers(
+    async def list_reviewers(
         credentials: GithubCredentials, pr_url: str
     ) -> list[Output.ReviewerItem]:
         api = get_api(credentials)
         reviewers_url = prepare_pr_api_url(pr_url=pr_url, path="requested_reviewers")
-        response = api.get(reviewers_url)
+        response = await api.get(reviewers_url)
         data = response.json()
         reviewers: list[GithubListPRReviewersBlock.Output.ReviewerItem] = [
             {"username": reviewer["login"], "url": reviewer["html_url"]}
@@ -490,18 +493,18 @@ class GithubListPRReviewersBlock(Block):
         ]
         return reviewers
 
-    def run(
+    async def run(
         self,
         input_data: Input,
         *,
         credentials: GithubCredentials,
         **kwargs,
     ) -> BlockOutput:
-        reviewers = self.list_reviewers(
+        for reviewer in await self.list_reviewers(
             credentials,
             input_data.pr_url,
-        )
-        yield from (("reviewer", reviewer) for reviewer in reviewers)
+        ):
+            yield "reviewer", reviewer
 
 
 def prepare_pr_api_url(pr_url: str, path: str) -> str:

autogpt_platform/backend/backend/blocks/github/repo.py

@@ -65,12 +65,12 @@ class GithubListTagsBlock(Block):
         )
 
     @staticmethod
-    def list_tags(
+    async def list_tags(
         credentials: GithubCredentials, repo_url: str
     ) -> list[Output.TagItem]:
         api = get_api(credentials)
         tags_url = repo_url + "/tags"
-        response = api.get(tags_url)
+        response = await api.get(tags_url)
         data = response.json()
         repo_path = repo_url.replace("https://github.com/", "")
         tags: list[GithubListTagsBlock.Output.TagItem] = [
@@ -82,18 +82,19 @@ class GithubListTagsBlock(Block):
         ]
         return tags
 
-    def run(
+    async def run(
         self,
         input_data: Input,
         *,
         credentials: GithubCredentials,
         **kwargs,
     ) -> BlockOutput:
-        tags = self.list_tags(
+        tags = await self.list_tags(
             credentials,
             input_data.repo_url,
         )
-        yield from (("tag", tag) for tag in tags)
+        for tag in tags:
+            yield "tag", tag
 
 
 class GithubListBranchesBlock(Block):
@@ -147,12 +148,12 @@ class GithubListBranchesBlock(Block):
         )
 
     @staticmethod
-    def list_branches(
+    async def list_branches(
         credentials: GithubCredentials, repo_url: str
     ) -> list[Output.BranchItem]:
         api = get_api(credentials)
         branches_url = repo_url + "/branches"
-        response = api.get(branches_url)
+        response = await api.get(branches_url)
         data = response.json()
         repo_path = repo_url.replace("https://github.com/", "")
         branches: list[GithubListBranchesBlock.Output.BranchItem] = [
@@ -164,18 +165,19 @@ class GithubListBranchesBlock(Block):
         ]
         return branches
 
-    def run(
+    async def run(
         self,
         input_data: Input,
         *,
         credentials: GithubCredentials,
         **kwargs,
     ) -> BlockOutput:
-        branches = self.list_branches(
+        branches = await self.list_branches(
             credentials,
             input_data.repo_url,
         )
-        yield from (("branch", branch) for branch in branches)
+        for branch in branches:
+            yield "branch", branch
 
 
 class GithubListDiscussionsBlock(Block):
@@ -234,7 +236,7 @@ class GithubListDiscussionsBlock(Block):
         )
 
     @staticmethod
-    def list_discussions(
+    async def list_discussions(
         credentials: GithubCredentials, repo_url: str, num_discussions: int
     ) -> list[Output.DiscussionItem]:
         api = get_api(credentials)
@@ -254,7 +256,7 @@ class GithubListDiscussionsBlock(Block):
         }
         """
         variables = {"owner": owner, "repo": repo, "num": num_discussions}
-        response = api.post(
+        response = await api.post(
             "https://api.github.com/graphql",
             json={"query": query, "variables": variables},
         )
@@ -265,17 +267,20 @@ class GithubListDiscussionsBlock(Block):
         ]
         return discussions
 
-    def run(
+    async def run(
         self,
         input_data: Input,
         *,
         credentials: GithubCredentials,
         **kwargs,
     ) -> BlockOutput:
-        discussions = self.list_discussions(
-            credentials, input_data.repo_url, input_data.num_discussions
+        discussions = await self.list_discussions(
+            credentials,
+            input_data.repo_url,
+            input_data.num_discussions,
         )
-        yield from (("discussion", discussion) for discussion in discussions)
+        for discussion in discussions:
+            yield "discussion", discussion
 
 
 class GithubListReleasesBlock(Block):
@@ -329,30 +334,31 @@ class GithubListReleasesBlock(Block):
         )
 
     @staticmethod
-    def list_releases(
+    async def list_releases(
         credentials: GithubCredentials, repo_url: str
     ) -> list[Output.ReleaseItem]:
         api = get_api(credentials)
         releases_url = repo_url + "/releases"
-        response = api.get(releases_url)
+        response = await api.get(releases_url)
         data = response.json()
         releases: list[GithubListReleasesBlock.Output.ReleaseItem] = [
             {"name": release["name"], "url": release["html_url"]} for release in data
         ]
         return releases
 
-    def run(
+    async def run(
         self,
         input_data: Input,
         *,
         credentials: GithubCredentials,
         **kwargs,
     ) -> BlockOutput:
-        releases = self.list_releases(
+        releases = await self.list_releases(
             credentials,
             input_data.repo_url,
         )
-        yield from (("release", release) for release in releases)
+        for release in releases:
+            yield "release", release
 
 
 class GithubReadFileBlock(Block):
@@ -405,40 +411,40 @@ class GithubReadFileBlock(Block):
         )
 
     @staticmethod
-    def read_file(
+    async def read_file(
         credentials: GithubCredentials, repo_url: str, file_path: str, branch: str
     ) -> tuple[str, int]:
         api = get_api(credentials)
         content_url = repo_url + f"/contents/{file_path}?ref={branch}"
-        response = api.get(content_url)
-        content = response.json()
+        response = await api.get(content_url)
+        data = response.json()
 
-        if isinstance(content, list):
+        if isinstance(data, list):
             # Multiple entries of different types exist at this path
-            if not (file := next((f for f in content if f["type"] == "file"), None)):
+            if not (file := next((f for f in data if f["type"] == "file"), None)):
                 raise TypeError("Not a file")
-            content = file
+            data = file
 
-        if content["type"] != "file":
+        if data["type"] != "file":
             raise TypeError("Not a file")
 
-        return content["content"], content["size"]
+        return data["content"], data["size"]
 
-    def run(
+    async def run(
         self,
         input_data: Input,
         *,
         credentials: GithubCredentials,
         **kwargs,
     ) -> BlockOutput:
-        raw_content, size = self.read_file(
+        content, size = await self.read_file(
             credentials,
             input_data.repo_url,
-            input_data.file_path.lstrip("/"),
+            input_data.file_path,
             input_data.branch,
         )
-        yield "raw_content", raw_content
-        yield "text_content", base64.b64decode(raw_content).decode("utf-8")
+        yield "raw_content", content
+        yield "text_content", base64.b64decode(content).decode("utf-8")
         yield "size", size
 
 
@@ -515,52 +521,55 @@ class GithubReadFolderBlock(Block):
         )
 
     @staticmethod
-    def read_folder(
+    async def read_folder(
         credentials: GithubCredentials, repo_url: str, folder_path: str, branch: str
     ) -> tuple[list[Output.FileEntry], list[Output.DirEntry]]:
         api = get_api(credentials)
         contents_url = repo_url + f"/contents/{folder_path}?ref={branch}"
-        response = api.get(contents_url)
-        content = response.json()
+        response = await api.get(contents_url)
+        data = response.json()
 
-        if not isinstance(content, list):
+        if not isinstance(data, list):
             raise TypeError("Not a folder")
 
-        files = [
+        files: list[GithubReadFolderBlock.Output.FileEntry] = [
             GithubReadFolderBlock.Output.FileEntry(
                 name=entry["name"],
                 path=entry["path"],
                 size=entry["size"],
             )
-            for entry in content
+            for entry in data
             if entry["type"] == "file"
         ]
-        dirs = [
+
+        dirs: list[GithubReadFolderBlock.Output.DirEntry] = [
             GithubReadFolderBlock.Output.DirEntry(
                 name=entry["name"],
                 path=entry["path"],
             )
-            for entry in content
+            for entry in data
             if entry["type"] == "dir"
         ]
 
         return files, dirs
 
-    def run(
+    async def run(
         self,
         input_data: Input,
         *,
         credentials: GithubCredentials,
         **kwargs,
     ) -> BlockOutput:
-        files, dirs = self.read_folder(
+        files, dirs = await self.read_folder(
             credentials,
             input_data.repo_url,
             input_data.folder_path.lstrip("/"),
             input_data.branch,
         )
-        yield from (("file", file) for file in files)
-        yield from (("dir", dir) for dir in dirs)
+        for file in files:
+            yield "file", file
+        for dir in dirs:
+            yield "dir", dir
 
 
 class GithubMakeBranchBlock(Block):
@@ -606,32 +615,35 @@ class GithubMakeBranchBlock(Block):
         )
 
     @staticmethod
-    def create_branch(
+    async def create_branch(
         credentials: GithubCredentials,
         repo_url: str,
         new_branch: str,
         source_branch: str,
     ) -> str:
         api = get_api(credentials)
-        # Get the SHA of the source branch
         ref_url = repo_url + f"/git/refs/heads/{source_branch}"
-        response = api.get(ref_url)
-        sha = response.json()["object"]["sha"]
+        response = await api.get(ref_url)
+        data = response.json()
+        sha = data["object"]["sha"]
 
         # Create the new branch
-        create_ref_url = repo_url + "/git/refs"
-        data = {"ref": f"refs/heads/{new_branch}", "sha": sha}
-        response = api.post(create_ref_url, json=data)
+        new_ref_url = repo_url + "/git/refs"
+        data = {
+            "ref": f"refs/heads/{new_branch}",
+            "sha": sha,
+        }
+        response = await api.post(new_ref_url, json=data)
         return "Branch created successfully"
 
-    def run(
+    async def run(
         self,
         input_data: Input,
         *,
         credentials: GithubCredentials,
         **kwargs,
     ) -> BlockOutput:
-        status = self.create_branch(
+        status = await self.create_branch(
             credentials,
             input_data.repo_url,
             input_data.new_branch,
@@ -678,22 +690,22 @@ class GithubDeleteBranchBlock(Block):
         )
 
     @staticmethod
-    def delete_branch(
+    async def delete_branch(
         credentials: GithubCredentials, repo_url: str, branch: str
     ) -> str:
         api = get_api(credentials)
         ref_url = repo_url + f"/git/refs/heads/{branch}"
-        api.delete(ref_url)
+        await api.delete(ref_url)
         return "Branch deleted successfully"
 
-    def run(
+    async def run(
         self,
         input_data: Input,
         *,
         credentials: GithubCredentials,
         **kwargs,
     ) -> BlockOutput:
-        status = self.delete_branch(
+        status = await self.delete_branch(
             credentials,
             input_data.repo_url,
             input_data.branch,
@@ -761,7 +773,7 @@ class GithubCreateFileBlock(Block):
         )
 
     @staticmethod
-    def create_file(
+    async def create_file(
         credentials: GithubCredentials,
         repo_url: str,
         file_path: str,
@@ -770,23 +782,18 @@ class GithubCreateFileBlock(Block):
         commit_message: str,
     ) -> tuple[str, str]:
         api = get_api(credentials)
-        # Convert content to base64
-        content_bytes = content.encode("utf-8")
-        content_base64 = base64.b64encode(content_bytes).decode("utf-8")
-
-        # Create the file using the GitHub API
-        contents_url = f"{repo_url}/contents/{file_path}"
+        contents_url = repo_url + f"/contents/{file_path}"
+        content_base64 = base64.b64encode(content.encode()).decode()
         data = {
             "message": commit_message,
             "content": content_base64,
             "branch": branch,
         }
-        response = api.put(contents_url, json=data)
-        result = response.json()
+        response = await api.put(contents_url, json=data)
+        data = response.json()
+        return data["content"]["html_url"], data["commit"]["sha"]
 
-        return result["content"]["html_url"], result["commit"]["sha"]
-
-    def run(
+    async def run(
         self,
         input_data: Input,
         *,
@@ -794,7 +801,7 @@ class GithubCreateFileBlock(Block):
         **kwargs,
     ) -> BlockOutput:
         try:
-            url, sha = self.create_file(
+            url, sha = await self.create_file(
                 credentials,
                 input_data.repo_url,
                 input_data.file_path,
@@ -866,7 +873,7 @@ class GithubUpdateFileBlock(Block):
         )
 
     @staticmethod
-    def update_file(
+    async def update_file(
         credentials: GithubCredentials,
         repo_url: str,
         file_path: str,
@@ -875,30 +882,24 @@ class GithubUpdateFileBlock(Block):
         commit_message: str,
     ) -> tuple[str, str]:
         api = get_api(credentials)
-
-        # First get the current file to get its SHA
-        contents_url = f"{repo_url}/contents/{file_path}"
+        contents_url = repo_url + f"/contents/{file_path}"
         params = {"ref": branch}
-        response = api.get(contents_url, params=params)
-        current_file = response.json()
+        response = await api.get(contents_url, params=params)
+        data = response.json()
 
         # Convert new content to base64
-        content_bytes = content.encode("utf-8")
-        content_base64 = base64.b64encode(content_bytes).decode("utf-8")
-
-        # Update the file
+        content_base64 = base64.b64encode(content.encode()).decode()
         data = {
             "message": commit_message,
             "content": content_base64,
-            "sha": current_file["sha"],
+            "sha": data["sha"],
             "branch": branch,
         }
-        response = api.put(contents_url, json=data)
-        result = response.json()
+        response = await api.put(contents_url, json=data)
+        data = response.json()
+        return data["content"]["html_url"], data["commit"]["sha"]
 
-        return result["content"]["html_url"], result["commit"]["sha"]
-
-    def run(
+    async def run(
         self,
         input_data: Input,
         *,
@@ -906,7 +907,7 @@ class GithubUpdateFileBlock(Block):
         **kwargs,
     ) -> BlockOutput:
         try:
-            url, sha = self.update_file(
+            url, sha = await self.update_file(
                 credentials,
                 input_data.repo_url,
                 input_data.file_path,
@@ -981,7 +982,7 @@ class GithubCreateRepositoryBlock(Block):
         )
 
     @staticmethod
-    def create_repository(
+    async def create_repository(
         credentials: GithubCredentials,
         name: str,
         description: str,
@@ -989,24 +990,19 @@ class GithubCreateRepositoryBlock(Block):
         auto_init: bool,
         gitignore_template: str,
     ) -> tuple[str, str]:
-        api = get_api(credentials, convert_urls=False)  # Disable URL conversion
+        api = get_api(credentials)
         data = {
             "name": name,
             "description": description,
             "private": private,
             "auto_init": auto_init,
+            "gitignore_template": gitignore_template,
         }
+        response = await api.post("https://api.github.com/user/repos", json=data)
+        data = response.json()
+        return data["html_url"], data["clone_url"]
 
-        if gitignore_template:
-            data["gitignore_template"] = gitignore_template
-
-        # Create repository using the user endpoint
-        response = api.post("https://api.github.com/user/repos", json=data)
-        result = response.json()
-
-        return result["html_url"], result["clone_url"]
-
-    def run(
+    async def run(
         self,
         input_data: Input,
         *,
@@ -1014,7 +1010,7 @@ class GithubCreateRepositoryBlock(Block):
         **kwargs,
     ) -> BlockOutput:
         try:
-            url, clone_url = self.create_repository(
+            url, clone_url = await self.create_repository(
                 credentials,
                 input_data.name,
                 input_data.description,
@@ -1081,17 +1077,13 @@ class GithubListStargazersBlock(Block):
         )
 
     @staticmethod
-    def list_stargazers(
+    async def list_stargazers(
         credentials: GithubCredentials, repo_url: str
     ) -> list[Output.StargazerItem]:
         api = get_api(credentials)
-        # Add /stargazers to the repo URL to get stargazers endpoint
-        stargazers_url = f"{repo_url}/stargazers"
-        # Set accept header to get starred_at timestamp
-        headers = {"Accept": "application/vnd.github.star+json"}
-        response = api.get(stargazers_url, headers=headers)
+        stargazers_url = repo_url + "/stargazers"
+        response = await api.get(stargazers_url)
         data = response.json()
-
         stargazers: list[GithubListStargazersBlock.Output.StargazerItem] = [
             {
                 "username": stargazer["login"],
@@ -1101,18 +1093,16 @@ class GithubListStargazersBlock(Block):
         ]
         return stargazers
 
-    def run(
+    async def run(
         self,
         input_data: Input,
         *,
         credentials: GithubCredentials,
         **kwargs,
     ) -> BlockOutput:
-        try:
-            stargazers = self.list_stargazers(
-                credentials,
-                input_data.repo_url,
-            )
-            yield from (("stargazer", stargazer) for stargazer in stargazers)
-        except Exception as e:
-            yield "error", str(e)
+        stargazers = await self.list_stargazers(
+            credentials,
+            input_data.repo_url,
+        )
+        for stargazer in stargazers:
+            yield "stargazer", stargazer

autogpt_platform/backend/backend/blocks/github/statuses.py

@@ -115,7 +115,7 @@ class GithubCreateStatusBlock(Block):
         )
 
     @staticmethod
-    def create_status(
+    async def create_status(
         credentials: GithubFineGrainedAPICredentials,
         repo_url: str,
         sha: str,
@@ -144,7 +144,9 @@ class GithubCreateStatusBlock(Block):
             data.description = description
 
         status_url = f"{repo_url}/statuses/{sha}"
-        response = api.post(status_url, data=data.model_dump_json(exclude_none=True))
+        response = await api.post(
+            status_url, data=data.model_dump_json(exclude_none=True)
+        )
         result = response.json()
 
         return {
@@ -158,7 +160,7 @@ class GithubCreateStatusBlock(Block):
             "updated_at": result["updated_at"],
         }
 
-    def run(
+    async def run(
         self,
         input_data: Input,
         *,
@@ -166,7 +168,7 @@ class GithubCreateStatusBlock(Block):
         **kwargs,
     ) -> BlockOutput:
         try:
-            result = self.create_status(
+            result = await self.create_status(
                 credentials=credentials,
                 repo_url=input_data.repo_url,
                 sha=input_data.sha,

autogpt_platform/backend/backend/blocks/github/triggers.py

@@ -37,7 +37,7 @@ class GitHubTriggerBase:
             placeholder="{owner}/{repo}",
         )
         # --8<-- [start:example-payload-field]
-        payload: dict = SchemaField(hidden=True, default={})
+        payload: dict = SchemaField(hidden=True, default_factory=dict)
         # --8<-- [end:example-payload-field]
 
     class Output(BlockSchema):
@@ -53,7 +53,7 @@ class GitHubTriggerBase:
             description="Error message if the payload could not be processed"
         )
 
-    def run(self, input_data: Input, **kwargs) -> BlockOutput:
+    async def run(self, input_data: Input, **kwargs) -> BlockOutput:
         yield "payload", input_data.payload
         yield "triggered_by_user", input_data.payload["sender"]
 
@@ -148,8 +148,9 @@ class GithubPullRequestTriggerBlock(GitHubTriggerBase, Block):
             ],
         )
 
-    def run(self, input_data: Input, **kwargs) -> BlockOutput:  # type: ignore
-        yield from super().run(input_data, **kwargs)
+    async def run(self, input_data: Input, **kwargs) -> BlockOutput:  # type: ignore
+        async for name, value in super().run(input_data, **kwargs):
+            yield name, value
         yield "event", input_data.payload["action"]
         yield "number", input_data.payload["number"]
         yield "pull_request", input_data.payload["pull_request"]

autogpt_platform/backend/backend/blocks/google/calendar.py

@@ -0,0 +1,603 @@
+import asyncio
+import enum
+import uuid
+from datetime import datetime, timedelta, timezone
+from typing import Literal
+
+from google.oauth2.credentials import Credentials
+from googleapiclient.discovery import build
+from pydantic import BaseModel
+
+from backend.data.block import Block, BlockCategory, BlockOutput, BlockSchema
+from backend.data.model import SchemaField
+from backend.util.settings import AppEnvironment, Settings
+
+from ._auth import (
+    GOOGLE_OAUTH_IS_CONFIGURED,
+    TEST_CREDENTIALS,
+    TEST_CREDENTIALS_INPUT,
+    GoogleCredentials,
+    GoogleCredentialsField,
+    GoogleCredentialsInput,
+)
+
+
+class CalendarEvent(BaseModel):
+    """Structured representation of a Google Calendar event."""
+
+    id: str
+    title: str
+    start_time: str
+    end_time: str
+    is_all_day: bool
+    location: str | None
+    description: str | None
+    organizer: str | None
+    attendees: list[str]
+    has_video_call: bool
+    video_link: str | None
+    calendar_link: str
+    is_recurring: bool
+
+
+class GoogleCalendarReadEventsBlock(Block):
+    class Input(BlockSchema):
+        credentials: GoogleCredentialsInput = GoogleCredentialsField(
+            ["https://www.googleapis.com/auth/calendar.readonly"]
+        )
+        calendar_id: str = SchemaField(
+            description="Calendar ID (use 'primary' for your main calendar)",
+            default="primary",
+        )
+        max_events: int = SchemaField(
+            description="Maximum number of events to retrieve", default=10
+        )
+        start_time: datetime = SchemaField(
+            description="Retrieve events starting from this time",
+            default_factory=lambda: datetime.now(tz=timezone.utc),
+        )
+        time_range_days: int = SchemaField(
+            description="Number of days to look ahead for events", default=30
+        )
+        search_term: str | None = SchemaField(
+            description="Optional search term to filter events by", default=None
+        )
+
+        page_token: str | None = SchemaField(
+            description="Page token from previous request to get the next batch of events. You can use this if you have lots of events you want to process in a loop",
+            default=None,
+        )
+        include_declined_events: bool = SchemaField(
+            description="Include events you've declined", default=False
+        )
+
+    class Output(BlockSchema):
+        events: list[CalendarEvent] = SchemaField(
+            description="List of calendar events in the requested time range",
+            default_factory=list,
+        )
+        event: CalendarEvent = SchemaField(
+            description="One of the calendar events in the requested time range"
+        )
+        next_page_token: str | None = SchemaField(
+            description="Token for retrieving the next page of events if more exist",
+            default=None,
+        )
+        error: str = SchemaField(
+            description="Error message if the request failed",
+        )
+
+    def __init__(self):
+        settings = Settings()
+
+        # Create realistic test data for events
+        test_now = datetime.now(tz=timezone.utc)
+        test_tomorrow = test_now + timedelta(days=1)
+
+        test_event_dict = {
+            "id": "event1id",
+            "title": "Team Meeting",
+            "start_time": test_tomorrow.strftime("%Y-%m-%d %H:%M"),
+            "end_time": (test_tomorrow + timedelta(hours=1)).strftime("%Y-%m-%d %H:%M"),
+            "is_all_day": False,
+            "location": "Conference Room A",
+            "description": "Weekly team sync",
+            "organizer": "manager@example.com",
+            "attendees": ["colleague1@example.com", "colleague2@example.com"],
+            "has_video_call": True,
+            "video_link": "https://meet.google.com/abc-defg-hij",
+            "calendar_link": "https://calendar.google.com/calendar/event?eid=event1id",
+            "is_recurring": True,
+        }
+
+        super().__init__(
+            id="80bc3ed1-e9a4-449e-8163-a8fc86f74f6a",
+            description="Retrieves upcoming events from a Google Calendar with filtering options",
+            categories={BlockCategory.PRODUCTIVITY, BlockCategory.DATA},
+            input_schema=GoogleCalendarReadEventsBlock.Input,
+            output_schema=GoogleCalendarReadEventsBlock.Output,
+            disabled=not GOOGLE_OAUTH_IS_CONFIGURED
+            or settings.config.app_env == AppEnvironment.PRODUCTION,
+            test_input={
+                "credentials": TEST_CREDENTIALS_INPUT,
+                "calendar_id": "primary",
+                "max_events": 5,
+                "start_time": test_now.isoformat(),
+                "time_range_days": 7,
+                "search_term": None,
+                "include_declined_events": False,
+                "page_token": None,
+            },
+            test_credentials=TEST_CREDENTIALS,
+            test_output=[
+                ("event", test_event_dict),
+                ("events", [test_event_dict]),
+            ],
+            test_mock={
+                "_read_calendar": lambda *args, **kwargs: {
+                    "items": [
+                        {
+                            "id": "event1id",
+                            "summary": "Team Meeting",
+                            "start": {
+                                "dateTime": test_tomorrow.isoformat(),
+                                "timeZone": "UTC",
+                            },
+                            "end": {
+                                "dateTime": (
+                                    test_tomorrow + timedelta(hours=1)
+                                ).isoformat(),
+                                "timeZone": "UTC",
+                            },
+                            "location": "Conference Room A",
+                            "description": "Weekly team sync",
+                            "organizer": {"email": "manager@example.com"},
+                            "attendees": [
+                                {"email": "colleague1@example.com"},
+                                {"email": "colleague2@example.com"},
+                            ],
+                            "conferenceData": {
+                                "conferenceUrl": "https://meet.google.com/abc-defg-hij"
+                            },
+                            "htmlLink": "https://calendar.google.com/calendar/event?eid=event1id",
+                            "recurrence": ["RRULE:FREQ=WEEKLY;COUNT=10"],
+                        }
+                    ],
+                    "nextPageToken": None,
+                },
+                "_format_events": lambda *args, **kwargs: [test_event_dict],
+            },
+        )
+
+    async def run(
+        self, input_data: Input, *, credentials: GoogleCredentials, **kwargs
+    ) -> BlockOutput:
+        try:
+            service = self._build_service(credentials, **kwargs)
+
+            # Calculate end time based on start time and time range
+            end_time = input_data.start_time + timedelta(
+                days=input_data.time_range_days
+            )
+
+            # Call Google Calendar API
+            result = await asyncio.to_thread(
+                self._read_calendar,
+                service=service,
+                calendarId=input_data.calendar_id,
+                time_min=input_data.start_time.isoformat(),
+                time_max=end_time.isoformat(),
+                max_results=input_data.max_events,
+                single_events=True,
+                search_term=input_data.search_term,
+                show_deleted=False,
+                show_hidden=input_data.include_declined_events,
+                page_token=input_data.page_token,
+            )
+
+            # Format events into a user-friendly structure
+            formatted_events = self._format_events(result.get("items", []))
+
+            # Include next page token if available
+            if next_page_token := result.get("nextPageToken"):
+                yield "next_page_token", next_page_token
+
+            for event in formatted_events:
+                yield "event", event
+
+            yield "events", formatted_events
+
+        except Exception as e:
+            yield "error", str(e)
+
+    @staticmethod
+    def _build_service(credentials: GoogleCredentials, **kwargs):
+        creds = Credentials(
+            token=(
+                credentials.access_token.get_secret_value()
+                if credentials.access_token
+                else None
+            ),
+            refresh_token=(
+                credentials.refresh_token.get_secret_value()
+                if credentials.refresh_token
+                else None
+            ),
+            token_uri="https://oauth2.googleapis.com/token",
+            client_id=Settings().secrets.google_client_id,
+            client_secret=Settings().secrets.google_client_secret,
+            scopes=credentials.scopes,
+        )
+        return build("calendar", "v3", credentials=creds)
+
+    def _read_calendar(
+        self,
+        service,
+        calendarId: str,
+        time_min: str,
+        time_max: str,
+        max_results: int,
+        single_events: bool,
+        search_term: str | None = None,
+        show_deleted: bool = False,
+        show_hidden: bool = False,
+        page_token: str | None = None,
+    ) -> dict:
+        """Read calendar events with optional filtering."""
+        calendar = service.events()
+
+        # Build query parameters
+        params = {
+            "calendarId": calendarId,
+            "timeMin": time_min,
+            "timeMax": time_max,
+            "maxResults": max_results,
+            "singleEvents": single_events,
+            "orderBy": "startTime",
+            "showDeleted": show_deleted,
+            "showHiddenInvitations": show_hidden,
+            **({"pageToken": page_token} if page_token else {}),
+        }
+
+        # Add search term if provided
+        if search_term:
+            params["q"] = search_term
+
+        result = calendar.list(**params).execute()
+        return result
+
+    def _format_events(self, events: list[dict]) -> list[CalendarEvent]:
+        """Format Google Calendar API events into user-friendly structure."""
+        formatted_events = []
+
+        for event in events:
+            # Determine if all-day event
+            is_all_day = "date" in event.get("start", {})
+
+            # Format start and end times
+            if is_all_day:
+                start_time = event.get("start", {}).get("date", "")
+                end_time = event.get("end", {}).get("date", "")
+            else:
+                # Convert ISO format to more readable format
+                start_datetime = datetime.fromisoformat(
+                    event.get("start", {}).get("dateTime", "").replace("Z", "+00:00")
+                )
+                end_datetime = datetime.fromisoformat(
+                    event.get("end", {}).get("dateTime", "").replace("Z", "+00:00")
+                )
+                start_time = start_datetime.strftime("%Y-%m-%d %H:%M")
+                end_time = end_datetime.strftime("%Y-%m-%d %H:%M")
+
+            # Extract attendees
+            attendees = []
+            for attendee in event.get("attendees", []):
+                if email := attendee.get("email"):
+                    attendees.append(email)
+
+            # Check for video call link
+            has_video_call = False
+            video_link = None
+            if conf_data := event.get("conferenceData"):
+                if conf_url := conf_data.get("conferenceUrl"):
+                    has_video_call = True
+                    video_link = conf_url
+                elif entry_points := conf_data.get("entryPoints", []):
+                    for entry in entry_points:
+                        if entry.get("entryPointType") == "video":
+                            has_video_call = True
+                            video_link = entry.get("uri")
+                            break
+
+            # Create formatted event
+            formatted_event = CalendarEvent(
+                id=event.get("id", ""),
+                title=event.get("summary", "Untitled Event"),
+                start_time=start_time,
+                end_time=end_time,
+                is_all_day=is_all_day,
+                location=event.get("location"),
+                description=event.get("description"),
+                organizer=event.get("organizer", {}).get("email"),
+                attendees=attendees,
+                has_video_call=has_video_call,
+                video_link=video_link,
+                calendar_link=event.get("htmlLink", ""),
+                is_recurring=bool(event.get("recurrence")),
+            )
+
+            formatted_events.append(formatted_event)
+
+        return formatted_events
+
+
+class ReminderPreset(enum.Enum):
+    """Common reminder times before an event."""
+
+    TEN_MINUTES = 10
+    THIRTY_MINUTES = 30
+    ONE_HOUR = 60
+    ONE_DAY = 1440  # 24 hours in minutes
+
+
+class RecurrenceFrequency(enum.Enum):
+    """Frequency options for recurring events."""
+
+    DAILY = "DAILY"
+    WEEKLY = "WEEKLY"
+    MONTHLY = "MONTHLY"
+    YEARLY = "YEARLY"
+
+
+class ExactTiming(BaseModel):
+    """Model for specifying start and end times."""
+
+    discriminator: Literal["exact_timing"]
+    start_datetime: datetime
+    end_datetime: datetime
+
+
+class DurationTiming(BaseModel):
+    """Model for specifying start time and duration."""
+
+    discriminator: Literal["duration_timing"]
+    start_datetime: datetime
+    duration_minutes: int
+
+
+class OneTimeEvent(BaseModel):
+    """Model for a one-time event."""
+
+    discriminator: Literal["one_time"]
+
+
+class RecurringEvent(BaseModel):
+    """Model for a recurring event."""
+
+    discriminator: Literal["recurring"]
+    frequency: RecurrenceFrequency
+    count: int
+
+
+class GoogleCalendarCreateEventBlock(Block):
+    class Input(BlockSchema):
+        credentials: GoogleCredentialsInput = GoogleCredentialsField(
+            ["https://www.googleapis.com/auth/calendar"]
+        )
+        # Event Details
+        event_title: str = SchemaField(description="Title of the event")
+        location: str | None = SchemaField(
+            description="Location of the event", default=None
+        )
+        description: str | None = SchemaField(
+            description="Description of the event", default=None
+        )
+
+        # Timing
+        timing: ExactTiming | DurationTiming = SchemaField(
+            discriminator="discriminator",
+            advanced=False,
+            description="Specify when the event starts and ends",
+            default_factory=lambda: DurationTiming(
+                discriminator="duration_timing",
+                start_datetime=datetime.now().replace(microsecond=0, second=0, minute=0)
+                + timedelta(hours=1),
+                duration_minutes=60,
+            ),
+        )
+
+        # Calendar selection
+        calendar_id: str = SchemaField(
+            description="Calendar ID (use 'primary' for your main calendar)",
+            default="primary",
+        )
+
+        # Guests
+        guest_emails: list[str] = SchemaField(
+            description="Email addresses of guests to invite", default_factory=list
+        )
+        send_notifications: bool = SchemaField(
+            description="Send email notifications to guests", default=True
+        )
+
+        # Extras
+        add_google_meet: bool = SchemaField(
+            description="Include a Google Meet video conference link", default=False
+        )
+        recurrence: OneTimeEvent | RecurringEvent = SchemaField(
+            discriminator="discriminator",
+            description="Whether the event repeats",
+            default_factory=lambda: OneTimeEvent(discriminator="one_time"),
+        )
+        reminder_minutes: list[ReminderPreset] = SchemaField(
+            description="When to send reminders before the event",
+            default_factory=lambda: [ReminderPreset.TEN_MINUTES],
+        )
+
+    class Output(BlockSchema):
+        event_id: str = SchemaField(description="ID of the created event")
+        event_link: str = SchemaField(
+            description="Link to view the event in Google Calendar"
+        )
+        error: str = SchemaField(description="Error message if event creation failed")
+
+    def __init__(self):
+        settings = Settings()
+
+        super().__init__(
+            id="ed2ec950-fbff-4204-94c0-023fb1d625e0",
+            description="This block creates a new event in Google Calendar with customizable parameters.",
+            categories={BlockCategory.PRODUCTIVITY},
+            input_schema=GoogleCalendarCreateEventBlock.Input,
+            output_schema=GoogleCalendarCreateEventBlock.Output,
+            disabled=not GOOGLE_OAUTH_IS_CONFIGURED
+            or settings.config.app_env == AppEnvironment.PRODUCTION,
+            test_input={
+                "credentials": TEST_CREDENTIALS_INPUT,
+                "event_title": "Team Meeting",
+                "location": "Conference Room A",
+                "description": "Weekly team sync-up",
+                "calendar_id": "primary",
+                "guest_emails": ["colleague1@example.com", "colleague2@example.com"],
+                "add_google_meet": True,
+                "send_notifications": True,
+                "reminder_minutes": [
+                    ReminderPreset.TEN_MINUTES.value,
+                    ReminderPreset.ONE_HOUR.value,
+                ],
+            },
+            test_credentials=TEST_CREDENTIALS,
+            test_output=[
+                ("event_id", "abc123event_id"),
+                ("event_link", "https://calendar.google.com/calendar/event?eid=abc123"),
+            ],
+            test_mock={
+                "_create_event": lambda *args, **kwargs: {
+                    "id": "abc123event_id",
+                    "htmlLink": "https://calendar.google.com/calendar/event?eid=abc123",
+                }
+            },
+        )
+
+    async def run(
+        self, input_data: Input, *, credentials: GoogleCredentials, **kwargs
+    ) -> BlockOutput:
+        try:
+            service = self._build_service(credentials, **kwargs)
+
+            # Create event body
+            # Get start and end times based on the timing option
+            if input_data.timing.discriminator == "exact_timing":
+                start_datetime = input_data.timing.start_datetime
+                end_datetime = input_data.timing.end_datetime
+            else:  # duration_timing
+                start_datetime = input_data.timing.start_datetime
+                end_datetime = start_datetime + timedelta(
+                    minutes=input_data.timing.duration_minutes
+                )
+
+            # Format datetimes for Google Calendar API
+            start_time_str = start_datetime.isoformat()
+            end_time_str = end_datetime.isoformat()
+
+            # Build the event body
+            event_body = {
+                "summary": input_data.event_title,
+                "start": {"dateTime": start_time_str},
+                "end": {"dateTime": end_time_str},
+            }
+
+            # Add optional fields
+            if input_data.location:
+                event_body["location"] = input_data.location
+
+            if input_data.description:
+                event_body["description"] = input_data.description
+
+            # Add guests
+            if input_data.guest_emails:
+                event_body["attendees"] = [
+                    {"email": email} for email in input_data.guest_emails
+                ]
+
+            # Add reminders
+            if input_data.reminder_minutes:
+                event_body["reminders"] = {
+                    "useDefault": False,
+                    "overrides": [
+                        {"method": "popup", "minutes": reminder.value}
+                        for reminder in input_data.reminder_minutes
+                    ],
+                }
+
+            # Add Google Meet
+            if input_data.add_google_meet:
+                event_body["conferenceData"] = {
+                    "createRequest": {
+                        "requestId": f"meet-{uuid.uuid4()}",
+                        "conferenceSolutionKey": {"type": "hangoutsMeet"},
+                    }
+                }
+
+            # Add recurrence
+            if input_data.recurrence.discriminator == "recurring":
+                rule = f"RRULE:FREQ={input_data.recurrence.frequency.value}"
+                rule += f";COUNT={input_data.recurrence.count}"
+                event_body["recurrence"] = [rule]
+
+            # Create the event
+            result = await asyncio.to_thread(
+                self._create_event,
+                service=service,
+                calendar_id=input_data.calendar_id,
+                event_body=event_body,
+                send_notifications=input_data.send_notifications,
+                conference_data_version=1 if input_data.add_google_meet else 0,
+            )
+
+            yield "event_id", result["id"]
+            yield "event_link", result["htmlLink"]
+
+        except Exception as e:
+            yield "error", str(e)
+
+    @staticmethod
+    def _build_service(credentials: GoogleCredentials, **kwargs):
+        creds = Credentials(
+            token=(
+                credentials.access_token.get_secret_value()
+                if credentials.access_token
+                else None
+            ),
+            refresh_token=(
+                credentials.refresh_token.get_secret_value()
+                if credentials.refresh_token
+                else None
+            ),
+            token_uri="https://oauth2.googleapis.com/token",
+            client_id=Settings().secrets.google_client_id,
+            client_secret=Settings().secrets.google_client_secret,
+            scopes=credentials.scopes,
+        )
+        return build("calendar", "v3", credentials=creds)
+
+    def _create_event(
+        self,
+        service,
+        calendar_id: str,
+        event_body: dict,
+        send_notifications: bool = False,
+        conference_data_version: int = 0,
+    ) -> dict:
+        """Create a new event in Google Calendar."""
+        calendar = service.events()
+
+        # Make the API call
+        result = calendar.insert(
+            calendarId=calendar_id,
+            body=event_body,
+            sendNotifications=send_notifications,
+            conferenceDataVersion=conference_data_version,
+        ).execute()
+
+        return result

autogpt_platform/backend/backend/blocks/google/gmail.py

@@ -1,3 +1,4 @@
+import asyncio
 import base64
 from email.utils import parseaddr
 from typing import List
@@ -128,11 +129,13 @@ class GmailReadBlock(Block):
             },
         )
 
-    def run(
+    async def run(
         self, input_data: Input, *, credentials: GoogleCredentials, **kwargs
     ) -> BlockOutput:
-        service = self._build_service(credentials, **kwargs)
-        messages = self._read_emails(service, input_data.query, input_data.max_results)
+        service = GmailReadBlock._build_service(credentials, **kwargs)
+        messages = await asyncio.to_thread(
+            self._read_emails, service, input_data.query, input_data.max_results
+        )
         for email in messages:
             yield "email", email
         yield "emails", messages
@@ -286,14 +289,18 @@ class GmailSendBlock(Block):
             },
         )
 
-    def run(
+    async def run(
         self, input_data: Input, *, credentials: GoogleCredentials, **kwargs
     ) -> BlockOutput:
         service = GmailReadBlock._build_service(credentials, **kwargs)
-        send_result = self._send_email(
-            service, input_data.to, input_data.subject, input_data.body
+        result = await asyncio.to_thread(
+            self._send_email,
+            service,
+            input_data.to,
+            input_data.subject,
+            input_data.body,
         )
-        yield "result", send_result
+        yield "result", result
 
     def _send_email(self, service, to: str, subject: str, body: str) -> dict:
         if not to or not subject or not body:
@@ -358,12 +365,12 @@ class GmailListLabelsBlock(Block):
             },
         )
 
-    def run(
+    async def run(
         self, input_data: Input, *, credentials: GoogleCredentials, **kwargs
     ) -> BlockOutput:
         service = GmailReadBlock._build_service(credentials, **kwargs)
-        labels = self._list_labels(service)
-        yield "result", labels
+        result = await asyncio.to_thread(self._list_labels, service)
+        yield "result", result
 
     def _list_labels(self, service) -> list[dict]:
         results = service.users().labels().list(userId="me").execute()
@@ -419,11 +426,13 @@ class GmailAddLabelBlock(Block):
             },
         )
 
-    def run(
+    async def run(
         self, input_data: Input, *, credentials: GoogleCredentials, **kwargs
     ) -> BlockOutput:
         service = GmailReadBlock._build_service(credentials, **kwargs)
-        result = self._add_label(service, input_data.message_id, input_data.label_name)
+        result = await asyncio.to_thread(
+            self._add_label, service, input_data.message_id, input_data.label_name
+        )
         yield "result", result
 
     def _add_label(self, service, message_id: str, label_name: str) -> dict:
@@ -502,12 +511,12 @@ class GmailRemoveLabelBlock(Block):
             },
         )
 
-    def run(
+    async def run(
         self, input_data: Input, *, credentials: GoogleCredentials, **kwargs
     ) -> BlockOutput:
         service = GmailReadBlock._build_service(credentials, **kwargs)
-        result = self._remove_label(
-            service, input_data.message_id, input_data.label_name
+        result = await asyncio.to_thread(
+            self._remove_label, service, input_data.message_id, input_data.label_name
         )
         yield "result", result
 

autogpt_platform/backend/backend/blocks/google/sheets.py

@@ -1,9 +1,11 @@
+import asyncio
+
 from google.oauth2.credentials import Credentials
 from googleapiclient.discovery import build
 
 from backend.data.block import Block, BlockCategory, BlockOutput, BlockSchema
 from backend.data.model import SchemaField
-from backend.util.settings import Settings
+from backend.util.settings import AppEnvironment, Settings
 
 from ._auth import (
     GOOGLE_OAUTH_IS_CONFIGURED,
@@ -36,13 +38,15 @@ class GoogleSheetsReadBlock(Block):
         )
 
     def __init__(self):
+        settings = Settings()
         super().__init__(
             id="5724e902-3635-47e9-a108-aaa0263a4988",
             description="This block reads data from a Google Sheets spreadsheet.",
             categories={BlockCategory.DATA},
             input_schema=GoogleSheetsReadBlock.Input,
             output_schema=GoogleSheetsReadBlock.Output,
-            disabled=not GOOGLE_OAUTH_IS_CONFIGURED,
+            disabled=not GOOGLE_OAUTH_IS_CONFIGURED
+            or settings.config.app_env == AppEnvironment.PRODUCTION,
             test_input={
                 "spreadsheet_id": "1BxiMVs0XRA5nFMdKvBdBZjgmUUqptlbs74OgvE2upms",
                 "range": "Sheet1!A1:B2",
@@ -66,11 +70,13 @@ class GoogleSheetsReadBlock(Block):
             },
         )
 
-    def run(
+    async def run(
         self, input_data: Input, *, credentials: GoogleCredentials, **kwargs
     ) -> BlockOutput:
         service = self._build_service(credentials, **kwargs)
-        data = self._read_sheet(service, input_data.spreadsheet_id, input_data.range)
+        data = await asyncio.to_thread(
+            self._read_sheet, service, input_data.spreadsheet_id, input_data.range
+        )
         yield "result", data
 
     @staticmethod
@@ -155,11 +161,12 @@ class GoogleSheetsWriteBlock(Block):
             },
         )
 
-    def run(
+    async def run(
         self, input_data: Input, *, credentials: GoogleCredentials, **kwargs
     ) -> BlockOutput:
         service = GoogleSheetsReadBlock._build_service(credentials, **kwargs)
-        result = self._write_sheet(
+        result = await asyncio.to_thread(
+            self._write_sheet,
             service,
             input_data.spreadsheet_id,
             input_data.range,

autogpt_platform/backend/backend/blocks/google_maps.py

@@ -103,7 +103,7 @@ class GoogleMapsSearchBlock(Block):
             test_credentials=TEST_CREDENTIALS,
         )
 
-    def run(
+    async def run(
         self, input_data: Input, *, credentials: APIKeyCredentials, **kwargs
     ) -> BlockOutput:
         places = self.search_places(

autogpt_platform/backend/backend/blocks/helpers/http.py

@@ -1,14 +1,17 @@
 from typing import Any, Optional
 
-from backend.util.request import requests
+from backend.util.request import Requests
 
 
 class GetRequest:
     @classmethod
-    def get_request(
+    async def get_request(
         cls, url: str, headers: Optional[dict] = None, json: bool = False
     ) -> Any:
         if headers is None:
             headers = {}
-        response = requests.get(url, headers=headers)
-        return response.json() if json else response.text
+        response = await Requests().get(url, headers=headers)
+        if json:
+            return response.json()
+        else:
+            return response.text()

autogpt_platform/backend/backend/blocks/http.py

@@ -1,13 +1,20 @@
 import json
 import logging
 from enum import Enum
-from typing import Any
+from io import BytesIO
+from pathlib import Path
 
-from requests.exceptions import HTTPError, RequestException
+import aiofiles
 
 from backend.data.block import Block, BlockCategory, BlockOutput, BlockSchema
 from backend.data.model import SchemaField
-from backend.util.request import requests
+from backend.util.file import (
+    MediaFileType,
+    get_exec_file_path,
+    get_mime_type,
+    store_media_file,
+)
+from backend.util.request import Requests
 
 logger = logging.getLogger(name=__name__)
 
@@ -34,17 +41,25 @@ class SendWebRequestBlock(Block):
         )
         headers: dict[str, str] = SchemaField(
             description="The headers to include in the request",
-            default={},
+            default_factory=dict,
         )
         json_format: bool = SchemaField(
             title="JSON format",
-            description="Whether to send and receive body as JSON",
+            description="If true, send the body as JSON (unless files are also present).",
             default=True,
         )
-        body: Any = SchemaField(
-            description="The body of the request",
+        body: dict | None = SchemaField(
+            description="Form/JSON body payload. If files are supplied, this must be a mapping of form‑fields.",
             default=None,
         )
+        files_name: str = SchemaField(
+            description="The name of the file field in the form data.",
+            default="file",
+        )
+        files: list[MediaFileType] = SchemaField(
+            description="Mapping of *form field name* → Image url / path / base64 url.",
+            default_factory=list,
+        )
 
     class Output(BlockSchema):
         response: object = SchemaField(description="The response from the server")
@@ -55,59 +70,102 @@ class SendWebRequestBlock(Block):
     def __init__(self):
         super().__init__(
             id="6595ae1f-b924-42cb-9a41-551a0611c4b4",
-            description="This block makes an HTTP request to the given URL.",
+            description="Make an HTTP request (JSON / form / multipart).",
             categories={BlockCategory.OUTPUT},
             input_schema=SendWebRequestBlock.Input,
             output_schema=SendWebRequestBlock.Output,
         )
 
-    def run(self, input_data: Input, **kwargs) -> BlockOutput:
-        body = input_data.body
+    @staticmethod
+    async def _prepare_files(
+        graph_exec_id: str,
+        files_name: str,
+        files: list[MediaFileType],
+    ) -> list[tuple[str, tuple[str, BytesIO, str]]]:
+        """
+        Prepare files for the request by storing them and reading their content.
+        Returns a list of tuples in the format:
+        (files_name, (filename, BytesIO, mime_type))
+        """
+        files_payload: list[tuple[str, tuple[str, BytesIO, str]]] = []
 
-        if input_data.json_format:
-            if isinstance(body, str):
-                try:
-                    # Try to parse as JSON first
-                    body = json.loads(body)
-                except json.JSONDecodeError:
-                    # If it's not valid JSON and just plain text,
-                    # we should send it as plain text instead
+        for media in files:
+            # Normalise to a list so we can repeat the same key
+            rel_path = await store_media_file(
+                graph_exec_id, media, return_content=False
+            )
+            abs_path = get_exec_file_path(graph_exec_id, rel_path)
+            async with aiofiles.open(abs_path, "rb") as f:
+                content = await f.read()
+                handle = BytesIO(content)
+                mime = get_mime_type(abs_path)
+                files_payload.append((files_name, (Path(abs_path).name, handle, mime)))
+
+        return files_payload
+
+    async def run(
+        self, input_data: Input, *, graph_exec_id: str, **kwargs
+    ) -> BlockOutput:
+        # ─── Parse/normalise body ────────────────────────────────────
+        body = input_data.body
+        if isinstance(body, str):
+            try:
+                # Validate JSON string length to prevent DoS attacks
+                if len(body) > 10_000_000:  # 10MB limit
+                    raise ValueError("JSON body too large")
+
+                parsed_body = json.loads(body)
+
+                # Validate that parsed JSON is safe (basic object/array/primitive types)
+                if (
+                    isinstance(parsed_body, (dict, list, str, int, float, bool))
+                    or parsed_body is None
+                ):
+                    body = parsed_body
+                else:
+                    # Unexpected type, treat as plain text
                     input_data.json_format = False
 
-        try:
-            response = requests.request(
-                input_data.method.value,
-                input_data.url,
-                headers=input_data.headers,
-                json=body if input_data.json_format else None,
-                data=body if not input_data.json_format else None,
+            except (json.JSONDecodeError, ValueError):
+                # Invalid JSON or too large – treat as form‑field value instead
+                input_data.json_format = False
+
+        # ─── Prepare files (if any) ──────────────────────────────────
+        use_files = bool(input_data.files)
+        files_payload: list[tuple[str, tuple[str, BytesIO, str]]] = []
+        if use_files:
+            files_payload = await self._prepare_files(
+                graph_exec_id, input_data.files_name, input_data.files
             )
-            result = response.json() if input_data.json_format else response.text
+
+        # Enforce body format rules
+        if use_files and input_data.json_format:
+            raise ValueError(
+                "json_format=True cannot be combined with file uploads; set json_format=False and put form fields in `body`."
+            )
+
+        # ─── Execute request ─────────────────────────────────────────
+        response = await Requests().request(
+            input_data.method.value,
+            input_data.url,
+            headers=input_data.headers,
+            files=files_payload if use_files else None,
+            # * If files → multipart ⇒ pass form‑fields via data=
+            data=body if not input_data.json_format else None,
+            # * Else, choose JSON vs url‑encoded based on flag
+            json=body if (input_data.json_format and not use_files) else None,
+        )
+
+        # Decide how to parse the response
+        if response.headers.get("content-type", "").startswith("application/json"):
+            result = None if response.status == 204 else response.json()
+        else:
+            result = response.text()
+
+        # Yield according to status code bucket
+        if 200 <= response.status < 300:
             yield "response", result
-
-        except HTTPError as e:
-            # Handle error responses
-            try:
-                result = e.response.json() if input_data.json_format else str(e)
-            except json.JSONDecodeError:
-                result = str(e)
-
-            if 400 <= e.response.status_code < 500:
-                yield "client_error", result
-            elif 500 <= e.response.status_code < 600:
-                yield "server_error", result
-            else:
-                error_msg = (
-                    "Unexpected status code "
-                    f"{e.response.status_code} '{e.response.reason}'"
-                )
-                logger.warning(error_msg)
-                yield "error", error_msg
-
-        except RequestException as e:
-            # Handle other request-related exceptions
-            yield "error", str(e)
-
-        except Exception as e:
-            # Catch any other unexpected exceptions
-            yield "error", str(e)
+        elif 400 <= response.status < 500:
+            yield "client_error", result
+        else:
+            yield "server_error", result

autogpt_platform/backend/backend/blocks/hubspot/company.py

@@ -5,7 +5,7 @@ from backend.blocks.hubspot._auth import (
 )
 from backend.data.block import Block, BlockCategory, BlockOutput, BlockSchema
 from backend.data.model import SchemaField
-from backend.util.request import requests
+from backend.util.request import Requests
 
 
 class HubSpotCompanyBlock(Block):
@@ -15,7 +15,8 @@ class HubSpotCompanyBlock(Block):
             description="Operation to perform (create, update, get)", default="get"
         )
         company_data: dict = SchemaField(
-            description="Company data for create/update operations", default={}
+            description="Company data for create/update operations",
+            default_factory=dict,
         )
         domain: str = SchemaField(
             description="Company domain for get/update operations", default=""
@@ -34,7 +35,7 @@ class HubSpotCompanyBlock(Block):
             output_schema=HubSpotCompanyBlock.Output,
         )
 
-    def run(
+    async def run(
         self, input_data: Input, *, credentials: HubSpotCredentials, **kwargs
     ) -> BlockOutput:
         base_url = "https://api.hubapi.com/crm/v3/objects/companies"
@@ -44,7 +45,7 @@ class HubSpotCompanyBlock(Block):
         }
 
         if input_data.operation == "create":
-            response = requests.post(
+            response = await Requests().post(
                 base_url, headers=headers, json={"properties": input_data.company_data}
             )
             result = response.json()
@@ -66,14 +67,16 @@ class HubSpotCompanyBlock(Block):
                     }
                 ]
             }
-            response = requests.post(search_url, headers=headers, json=search_data)
-            result = response.json()
-            yield "company", result.get("results", [{}])[0]
+            search_response = await Requests().post(
+                search_url, headers=headers, json=search_data
+            )
+            search_result = search_response.json()
+            yield "search_company", search_result.get("results", [{}])[0]
             yield "status", "retrieved"
 
         elif input_data.operation == "update":
             # First get company ID by domain
-            search_response = requests.post(
+            search_response = await Requests().post(
                 f"{base_url}/search",
                 headers=headers,
                 json={
@@ -90,10 +93,11 @@ class HubSpotCompanyBlock(Block):
                     ]
                 },
             )
-            company_id = search_response.json().get("results", [{}])[0].get("id")
+            search_result = search_response.json()
+            company_id = search_result.get("results", [{}])[0].get("id")
 
             if company_id:
-                response = requests.patch(
+                response = await Requests().patch(
                     f"{base_url}/{company_id}",
                     headers=headers,
                     json={"properties": input_data.company_data},

autogpt_platform/backend/backend/blocks/hubspot/contact.py

@@ -5,7 +5,7 @@ from backend.blocks.hubspot._auth import (
 )
 from backend.data.block import Block, BlockCategory, BlockOutput, BlockSchema
 from backend.data.model import SchemaField
-from backend.util.request import requests
+from backend.util.request import Requests
 
 
 class HubSpotContactBlock(Block):
@@ -15,7 +15,8 @@ class HubSpotContactBlock(Block):
             description="Operation to perform (create, update, get)", default="get"
         )
         contact_data: dict = SchemaField(
-            description="Contact data for create/update operations", default={}
+            description="Contact data for create/update operations",
+            default_factory=dict,
         )
         email: str = SchemaField(
             description="Email address for get/update operations", default=""
@@ -34,7 +35,7 @@ class HubSpotContactBlock(Block):
             output_schema=HubSpotContactBlock.Output,
         )
 
-    def run(
+    async def run(
         self, input_data: Input, *, credentials: HubSpotCredentials, **kwargs
     ) -> BlockOutput:
         base_url = "https://api.hubapi.com/crm/v3/objects/contacts"
@@ -44,7 +45,7 @@ class HubSpotContactBlock(Block):
         }
 
         if input_data.operation == "create":
-            response = requests.post(
+            response = await Requests().post(
                 base_url, headers=headers, json={"properties": input_data.contact_data}
             )
             result = response.json()
@@ -52,7 +53,6 @@ class HubSpotContactBlock(Block):
             yield "status", "created"
 
         elif input_data.operation == "get":
-            # Search for contact by email
             search_url = f"{base_url}/search"
             search_data = {
                 "filterGroups": [
@@ -67,13 +67,15 @@ class HubSpotContactBlock(Block):
                     }
                 ]
             }
-            response = requests.post(search_url, headers=headers, json=search_data)
+            response = await Requests().post(
+                search_url, headers=headers, json=search_data
+            )
             result = response.json()
             yield "contact", result.get("results", [{}])[0]
             yield "status", "retrieved"
 
         elif input_data.operation == "update":
-            search_response = requests.post(
+            search_response = await Requests().post(
                 f"{base_url}/search",
                 headers=headers,
                 json={
@@ -90,10 +92,11 @@ class HubSpotContactBlock(Block):
                     ]
                 },
             )
-            contact_id = search_response.json().get("results", [{}])[0].get("id")
+            search_result = search_response.json()
+            contact_id = search_result.get("results", [{}])[0].get("id")
 
             if contact_id:
-                response = requests.patch(
+                response = await Requests().patch(
                     f"{base_url}/{contact_id}",
                     headers=headers,
                     json={"properties": input_data.contact_data},

autogpt_platform/backend/backend/blocks/hubspot/engagement.py

@@ -7,7 +7,7 @@ from backend.blocks.hubspot._auth import (
 )
 from backend.data.block import Block, BlockCategory, BlockOutput, BlockSchema
 from backend.data.model import SchemaField
-from backend.util.request import requests
+from backend.util.request import Requests
 
 
 class HubSpotEngagementBlock(Block):
@@ -19,7 +19,7 @@ class HubSpotEngagementBlock(Block):
         )
         email_data: dict = SchemaField(
             description="Email data including recipient, subject, content",
-            default={},
+            default_factory=dict,
         )
         contact_id: str = SchemaField(
             description="Contact ID for engagement tracking", default=""
@@ -27,7 +27,6 @@ class HubSpotEngagementBlock(Block):
         timeframe_days: int = SchemaField(
             description="Number of days to look back for engagement",
             default=30,
-            optional=True,
         )
 
     class Output(BlockSchema):
@@ -43,7 +42,7 @@ class HubSpotEngagementBlock(Block):
             output_schema=HubSpotEngagementBlock.Output,
         )
 
-    def run(
+    async def run(
         self, input_data: Input, *, credentials: HubSpotCredentials, **kwargs
     ) -> BlockOutput:
         base_url = "https://api.hubapi.com"
@@ -67,7 +66,9 @@ class HubSpotEngagementBlock(Block):
                 }
             }
 
-            response = requests.post(email_url, headers=headers, json=email_data)
+            response = await Requests().post(
+                email_url, headers=headers, json=email_data
+            )
             result = response.json()
             yield "result", result
             yield "status", "email_sent"
@@ -81,7 +82,9 @@ class HubSpotEngagementBlock(Block):
 
             params = {"limit": 100, "after": from_date.isoformat()}
 
-            response = requests.get(engagement_url, headers=headers, params=params)
+            response = await Requests().get(
+                engagement_url, headers=headers, params=params
+            )
             engagements = response.json()
 
             # Process engagement metrics

autogpt_platform/backend/backend/blocks/ideogram.py

@@ -12,7 +12,7 @@ from backend.data.model import (
     SchemaField,
 )
 from backend.integrations.providers import ProviderName
-from backend.util.request import requests
+from backend.util.request import Requests
 
 TEST_CREDENTIALS = APIKeyCredentials(
     id="01234567-89ab-cdef-0123-456789abcdef",
@@ -196,13 +196,13 @@ class IdeogramModelBlock(Block):
             test_credentials=TEST_CREDENTIALS,
         )
 
-    def run(
+    async def run(
         self, input_data: Input, *, credentials: APIKeyCredentials, **kwargs
     ) -> BlockOutput:
         seed = input_data.seed
 
         # Step 1: Generate the image
-        result = self.run_model(
+        result = await self.run_model(
             api_key=credentials.api_key,
             model_name=input_data.ideogram_model_name.value,
             prompt=input_data.prompt,
@@ -217,14 +217,14 @@ class IdeogramModelBlock(Block):
 
         # Step 2: Upscale the image if requested
         if input_data.upscale == UpscaleOption.AI_UPSCALE:
-            result = self.upscale_image(
+            result = await self.upscale_image(
                 api_key=credentials.api_key,
                 image_url=result,
             )
 
         yield "result", result
 
-    def run_model(
+    async def run_model(
         self,
         api_key: SecretStr,
         model_name: str,
@@ -267,12 +267,12 @@ class IdeogramModelBlock(Block):
             }
 
         try:
-            response = requests.post(url, json=data, headers=headers)
+            response = await Requests().post(url, headers=headers, json=data)
             return response.json()["data"][0]["url"]
         except RequestException as e:
             raise Exception(f"Failed to fetch image: {str(e)}")
 
-    def upscale_image(self, api_key: SecretStr, image_url: str):
+    async def upscale_image(self, api_key: SecretStr, image_url: str):
         url = "https://api.ideogram.ai/upscale"
         headers = {
             "Api-Key": api_key.get_secret_value(),
@@ -280,21 +280,22 @@ class IdeogramModelBlock(Block):
 
         try:
             # Step 1: Download the image from the provided URL
-            image_response = requests.get(image_url)
+            response = await Requests().get(image_url)
+            image_content = response.content
 
             # Step 2: Send the downloaded image to the upscale API
             files = {
-                "image_file": ("image.png", image_response.content, "image/png"),
+                "image_file": ("image.png", image_content, "image/png"),
             }
 
-            response = requests.post(
+            response = await Requests().post(
                 url,
                 headers=headers,
                 data={"image_request": "{}"},
                 files=files,
             )
 
-            return response.json()["data"][0]["url"]
+            return (response.json())["data"][0]["url"]
 
         except RequestException as e:
             raise Exception(f"Failed to upscale image: {str(e)}")

autogpt_platform/backend/backend/blocks/io.py

@@ -1,3 +1,4 @@
+import copy
 from datetime import date, time
 from typing import Any, Optional
 
@@ -38,7 +39,7 @@ class AgentInputBlock(Block):
         )
         placeholder_values: list = SchemaField(
             description="The placeholder values to be passed as input.",
-            default=[],
+            default_factory=list,
             advanced=True,
             hidden=True,
         )
@@ -54,7 +55,7 @@ class AgentInputBlock(Block):
         )
 
         def generate_schema(self):
-            schema = self.get_field_schema("value")
+            schema = copy.deepcopy(self.get_field_schema("value"))
             if possible_values := self.placeholder_values:
                 schema["enum"] = possible_values
             return schema
@@ -94,7 +95,7 @@ class AgentInputBlock(Block):
             }
         )
 
-    def run(self, input_data: Input, *args, **kwargs) -> BlockOutput:
+    async def run(self, input_data: Input, *args, **kwargs) -> BlockOutput:
         if input_data.value is not None:
             yield "result", input_data.value
 
@@ -185,7 +186,7 @@ class AgentOutputBlock(Block):
             static_output=True,
         )
 
-    def run(self, input_data: Input, *args, **kwargs) -> BlockOutput:
+    async def run(self, input_data: Input, *args, **kwargs) -> BlockOutput:
         """
         Attempts to format the recorded_value using the fmt_string if provided.
         If formatting fails or no fmt_string is given, returns the original recorded_value.
@@ -435,7 +436,7 @@ class AgentFileInputBlock(AgentInputBlock):
             ],
         )
 
-    def run(
+    async def run(
         self,
         input_data: Input,
         *,
@@ -445,7 +446,7 @@ class AgentFileInputBlock(AgentInputBlock):
         if not input_data.value:
             return
 
-        file_path = store_media_file(
+        file_path = await store_media_file(
             graph_exec_id=graph_exec_id,
             file=input_data.value,
             return_content=False,
@@ -467,7 +468,7 @@ class AgentDropdownInputBlock(AgentInputBlock):
         )
         placeholder_values: list = SchemaField(
             description="Possible values for the dropdown.",
-            default=[],
+            default_factory=list,
             advanced=False,
             title="Dropdown Options",
         )

autogpt_platform/backend/backend/blocks/iteration.py

@@ -11,13 +11,13 @@ class StepThroughItemsBlock(Block):
             advanced=False,
             description="The list or dictionary of items to iterate over",
             placeholder="[1, 2, 3, 4, 5] or {'key1': 'value1', 'key2': 'value2'}",
-            default=[],
+            default_factory=list,
         )
         items_object: dict = SchemaField(
             advanced=False,
             description="The list or dictionary of items to iterate over",
             placeholder="[1, 2, 3, 4, 5] or {'key1': 'value1', 'key2': 'value2'}",
-            default={},
+            default_factory=dict,
         )
         items_str: str = SchemaField(
             advanced=False,
@@ -53,7 +53,7 @@ class StepThroughItemsBlock(Block):
             test_mock={},
         )
 
-    def run(self, input_data: Input, **kwargs) -> BlockOutput:
+    async def run(self, input_data: Input, **kwargs) -> BlockOutput:
         for data in [input_data.items, input_data.items_object, input_data.items_str]:
             if not data:
                 continue

autogpt_platform/backend/backend/blocks/jina/chunking.py

@@ -5,7 +5,7 @@ from backend.blocks.jina._auth import (
 )
 from backend.data.block import Block, BlockCategory, BlockOutput, BlockSchema
 from backend.data.model import SchemaField
-from backend.util.request import requests
+from backend.util.request import Requests
 
 
 class JinaChunkingBlock(Block):
@@ -23,7 +23,7 @@ class JinaChunkingBlock(Block):
     class Output(BlockSchema):
         chunks: list = SchemaField(description="List of chunked texts")
         tokens: list = SchemaField(
-            description="List of token information for each chunk", optional=True
+            description="List of token information for each chunk",
         )
 
     def __init__(self):
@@ -35,7 +35,7 @@ class JinaChunkingBlock(Block):
             output_schema=JinaChunkingBlock.Output,
         )
 
-    def run(
+    async def run(
         self, input_data: Input, *, credentials: JinaCredentials, **kwargs
     ) -> BlockOutput:
         url = "https://segment.jina.ai/"
@@ -55,7 +55,7 @@ class JinaChunkingBlock(Block):
                 "max_chunk_length": str(input_data.max_chunk_length),
             }
 
-            response = requests.post(url, headers=headers, json=data)
+            response = await Requests().post(url, headers=headers, json=data)
             result = response.json()
 
             all_chunks.extend(result.get("chunks", []))

autogpt_platform/backend/backend/blocks/jina/embeddings.py

@@ -5,7 +5,7 @@ from backend.blocks.jina._auth import (
 )
 from backend.data.block import Block, BlockCategory, BlockOutput, BlockSchema
 from backend.data.model import SchemaField
-from backend.util.request import requests
+from backend.util.request import Requests
 
 
 class JinaEmbeddingBlock(Block):
@@ -29,7 +29,7 @@ class JinaEmbeddingBlock(Block):
             output_schema=JinaEmbeddingBlock.Output,
         )
 
-    def run(
+    async def run(
         self, input_data: Input, *, credentials: JinaCredentials, **kwargs
     ) -> BlockOutput:
         url = "https://api.jina.ai/v1/embeddings"
@@ -38,6 +38,6 @@ class JinaEmbeddingBlock(Block):
             "Authorization": f"Bearer {credentials.api_key.get_secret_value()}",
         }
         data = {"input": input_data.texts, "model": input_data.model}
-        response = requests.post(url, headers=headers, json=data)
+        response = await Requests().post(url, headers=headers, json=data)
         embeddings = [e["embedding"] for e in response.json()["data"]]
         yield "embeddings", embeddings

autogpt_platform/backend/backend/blocks/jina/fact_checker.py

@@ -1,7 +1,5 @@
 from urllib.parse import quote
 
-import requests
-
 from backend.blocks.jina._auth import (
     JinaCredentials,
     JinaCredentialsField,
@@ -9,6 +7,7 @@ from backend.blocks.jina._auth import (
 )
 from backend.data.block import Block, BlockCategory, BlockOutput, BlockSchema
 from backend.data.model import SchemaField
+from backend.util.request import Requests
 
 
 class FactCheckerBlock(Block):
@@ -35,7 +34,7 @@ class FactCheckerBlock(Block):
             output_schema=FactCheckerBlock.Output,
         )
 
-    def run(
+    async def run(
         self, input_data: Input, *, credentials: JinaCredentials, **kwargs
     ) -> BlockOutput:
         encoded_statement = quote(input_data.statement)
@@ -46,8 +45,7 @@ class FactCheckerBlock(Block):
             "Authorization": f"Bearer {credentials.api_key.get_secret_value()}",
         }
 
-        response = requests.get(url, headers=headers)
-        response.raise_for_status()
+        response = await Requests().get(url, headers=headers)
         data = response.json()
 
         if "data" in data:

autogpt_platform/backend/backend/blocks/jina/search.py

@@ -1,4 +1,4 @@
-from groq._utils._utils import quote
+from urllib.parse import quote
 
 from backend.blocks.jina._auth import (
     TEST_CREDENTIALS,
@@ -39,7 +39,7 @@ class SearchTheWebBlock(Block, GetRequest):
             test_mock={"get_request": lambda *args, **kwargs: "search content"},
         )
 
-    def run(
+    async def run(
         self, input_data: Input, *, credentials: JinaCredentials, **kwargs
     ) -> BlockOutput:
         # Encode the search query
@@ -51,7 +51,7 @@ class SearchTheWebBlock(Block, GetRequest):
 
         # Prepend the Jina Search URL to the encoded query
         jina_search_url = f"https://s.jina.ai/{encoded_query}"
-        results = self.get_request(jina_search_url, headers=headers, json=False)
+        results = await self.get_request(jina_search_url, headers=headers, json=False)
 
         # Output the search results
         yield "results", results
@@ -90,7 +90,7 @@ class ExtractWebsiteContentBlock(Block, GetRequest):
             test_mock={"get_request": lambda *args, **kwargs: "scraped content"},
         )
 
-    def run(
+    async def run(
         self, input_data: Input, *, credentials: JinaCredentials, **kwargs
     ) -> BlockOutput:
         if input_data.raw_content:
@@ -103,5 +103,5 @@ class ExtractWebsiteContentBlock(Block, GetRequest):
                 "Authorization": f"Bearer {credentials.api_key.get_secret_value()}",
             }
 
-        content = self.get_request(url, json=False, headers=headers)
+        content = await self.get_request(url, json=False, headers=headers)
         yield "content", content

autogpt_platform/backend/backend/blocks/linear/_api.py

@@ -48,7 +48,7 @@ class LinearClient:
                 raise_for_status=False,
             )
 
-    def _execute_graphql_request(
+    async def _execute_graphql_request(
         self, query: str, variables: dict | None = None
     ) -> Any:
         """
@@ -65,19 +65,18 @@ class LinearClient:
         if variables:
             payload["variables"] = variables
 
-        response = self._requests.post(self.API_URL, json=payload)
+        response = await self._requests.post(self.API_URL, json=payload)
 
         if not response.ok:
-
             try:
                 error_data = response.json()
                 error_message = error_data.get("errors", [{}])[0].get("message", "")
             except json.JSONDecodeError:
-                error_message = response.text
+                error_message = response.text()
 
             raise LinearAPIException(
-                f"Linear API request failed ({response.status_code}): {error_message}",
-                response.status_code,
+                f"Linear API request failed ({response.status}): {error_message}",
+                response.status,
             )
 
         response_data = response.json()
@@ -88,12 +87,12 @@ class LinearClient:
             ]
             raise LinearAPIException(
                 f"Linear API returned errors: {', '.join(error_messages)}",
-                response.status_code,
+                response.status,
             )
 
         return response_data["data"]
 
-    def query(self, query: str, variables: Optional[dict] = None) -> dict:
+    async def query(self, query: str, variables: Optional[dict] = None) -> dict:
         """Executes a GraphQL query.
 
         Args:
@@ -103,9 +102,9 @@ class LinearClient:
         Returns:
              The response data.
         """
-        return self._execute_graphql_request(query, variables)
+        return await self._execute_graphql_request(query, variables)
 
-    def mutate(self, mutation: str, variables: Optional[dict] = None) -> dict:
+    async def mutate(self, mutation: str, variables: Optional[dict] = None) -> dict:
         """Executes a GraphQL mutation.
 
         Args:
@@ -115,9 +114,11 @@ class LinearClient:
         Returns:
             The response data.
         """
-        return self._execute_graphql_request(mutation, variables)
+        return await self._execute_graphql_request(mutation, variables)
 
-    def try_create_comment(self, issue_id: str, comment: str) -> CreateCommentResponse:
+    async def try_create_comment(
+        self, issue_id: str, comment: str
+    ) -> CreateCommentResponse:
         try:
             mutation = """
                 mutation CommentCreate($input: CommentCreateInput!) {
@@ -138,13 +139,13 @@ class LinearClient:
                 }
             }
 
-            added_comment = self.mutate(mutation, variables)
+            added_comment = await self.mutate(mutation, variables)
             # Select the commentCreate field from the mutation response
             return CreateCommentResponse(**added_comment["commentCreate"])
         except LinearAPIException as e:
             raise e
 
-    def try_get_team_by_name(self, team_name: str) -> str:
+    async def try_get_team_by_name(self, team_name: str) -> str:
         try:
             query = """
             query GetTeamId($searchTerm: String!) {
@@ -167,12 +168,12 @@ class LinearClient:
                 "searchTerm": team_name,
             }
 
-            team_id = self.query(query, variables)
+            team_id = await self.query(query, variables)
             return team_id["teams"]["nodes"][0]["id"]
         except LinearAPIException as e:
             raise e
 
-    def try_create_issue(
+    async def try_create_issue(
         self,
         team_id: str,
         title: str,
@@ -211,12 +212,12 @@ class LinearClient:
             if priority:
                 variables["input"]["priority"] = priority
 
-            added_issue = self.mutate(mutation, variables)
+            added_issue = await self.mutate(mutation, variables)
             return CreateIssueResponse(**added_issue["issueCreate"])
         except LinearAPIException as e:
             raise e
 
-    def try_search_projects(self, term: str) -> list[Project]:
+    async def try_search_projects(self, term: str) -> list[Project]:
         try:
             query = """
                 query SearchProjects($term: String!, $includeComments: Boolean!) {
@@ -238,14 +239,14 @@ class LinearClient:
                 "includeComments": True,
             }
 
-            projects = self.query(query, variables)
+            projects = await self.query(query, variables)
             return [
                 Project(**project) for project in projects["searchProjects"]["nodes"]
             ]
         except LinearAPIException as e:
             raise e
 
-    def try_search_issues(self, term: str) -> list[Issue]:
+    async def try_search_issues(self, term: str) -> list[Issue]:
         try:
             query = """
                 query SearchIssues($term: String!, $includeComments: Boolean!) {
@@ -266,7 +267,7 @@ class LinearClient:
                 "includeComments": True,
             }
 
-            issues = self.query(query, variables)
+            issues = await self.query(query, variables)
             return [Issue(**issue) for issue in issues["searchIssues"]["nodes"]]
         except LinearAPIException as e:
             raise e

autogpt_platform/backend/backend/blocks/linear/comment.py

@@ -54,21 +54,21 @@ class LinearCreateCommentBlock(Block):
         )
 
     @staticmethod
-    def create_comment(
+    async def create_comment(
         credentials: LinearCredentials, issue_id: str, comment: str
     ) -> tuple[str, str]:
         client = LinearClient(credentials=credentials)
-        response: CreateCommentResponse = client.try_create_comment(
+        response: CreateCommentResponse = await client.try_create_comment(
             issue_id=issue_id, comment=comment
         )
         return response.comment.id, response.comment.body
 
-    def run(
+    async def run(
         self, input_data: Input, *, credentials: LinearCredentials, **kwargs
     ) -> BlockOutput:
         """Execute the comment creation"""
         try:
-            comment_id, comment_body = self.create_comment(
+            comment_id, comment_body = await self.create_comment(
                 credentials=credentials,
                 issue_id=input_data.issue_id,
                 comment=input_data.comment,

autogpt_platform/backend/backend/blocks/linear/issues.py

@@ -28,8 +28,8 @@ class LinearCreateIssueBlock(Block):
         priority: int | None = SchemaField(
             description="Priority of the issue",
             default=None,
-            minimum=0,
-            maximum=4,
+            ge=0,
+            le=4,
         )
         project_name: str | None = SchemaField(
             description="Name of the project to create the issue on",
@@ -67,7 +67,7 @@ class LinearCreateIssueBlock(Block):
         )
 
     @staticmethod
-    def create_issue(
+    async def create_issue(
         credentials: LinearCredentials,
         team_name: str,
         title: str,
@@ -76,15 +76,15 @@ class LinearCreateIssueBlock(Block):
         project_name: str | None = None,
     ) -> tuple[str, str]:
         client = LinearClient(credentials=credentials)
-        team_id = client.try_get_team_by_name(team_name=team_name)
+        team_id = await client.try_get_team_by_name(team_name=team_name)
         project_id: str | None = None
         if project_name:
-            projects = client.try_search_projects(term=project_name)
+            projects = await client.try_search_projects(term=project_name)
             if projects:
                 project_id = projects[0].id
             else:
                 raise LinearAPIException("Project not found", status_code=404)
-        response: CreateIssueResponse = client.try_create_issue(
+        response: CreateIssueResponse = await client.try_create_issue(
             team_id=team_id,
             title=title,
             description=description,
@@ -93,12 +93,12 @@ class LinearCreateIssueBlock(Block):
         )
         return response.issue.identifier, response.issue.title
 
-    def run(
+    async def run(
         self, input_data: Input, *, credentials: LinearCredentials, **kwargs
     ) -> BlockOutput:
         """Execute the issue creation"""
         try:
-            issue_id, issue_title = self.create_issue(
+            issue_id, issue_title = await self.create_issue(
                 credentials=credentials,
                 team_name=input_data.team_name,
                 title=input_data.title,
@@ -168,20 +168,22 @@ class LinearSearchIssuesBlock(Block):
         )
 
     @staticmethod
-    def search_issues(
+    async def search_issues(
         credentials: LinearCredentials,
         term: str,
     ) -> list[Issue]:
         client = LinearClient(credentials=credentials)
-        response: list[Issue] = client.try_search_issues(term=term)
+        response: list[Issue] = await client.try_search_issues(term=term)
         return response
 
-    def run(
+    async def run(
         self, input_data: Input, *, credentials: LinearCredentials, **kwargs
     ) -> BlockOutput:
         """Execute the issue search"""
         try:
-            issues = self.search_issues(credentials=credentials, term=input_data.term)
+            issues = await self.search_issues(
+                credentials=credentials, term=input_data.term
+            )
             yield "issues", issues
         except LinearAPIException as e:
             yield "error", str(e)

autogpt_platform/backend/backend/blocks/linear/projects.py

@@ -69,20 +69,20 @@ class LinearSearchProjectsBlock(Block):
         )
 
     @staticmethod
-    def search_projects(
+    async def search_projects(
         credentials: LinearCredentials,
         term: str,
     ) -> list[Project]:
         client = LinearClient(credentials=credentials)
-        response: list[Project] = client.try_search_projects(term=term)
+        response: list[Project] = await client.try_search_projects(term=term)
         return response
 
-    def run(
+    async def run(
         self, input_data: Input, *, credentials: LinearCredentials, **kwargs
     ) -> BlockOutput:
         """Execute the project search"""
         try:
-            projects = self.search_projects(
+            projects = await self.search_projects(
                 credentials=credentials,
                 term=input_data.term,
             )

autogpt_platform/backend/backend/blocks/llm.py

@@ -3,44 +3,39 @@ import logging
 from abc import ABC
 from enum import Enum, EnumMeta
 from json import JSONDecodeError
-from types import MappingProxyType
-from typing import TYPE_CHECKING, Any, Iterable, List, Literal, NamedTuple, Optional
-
-from pydantic import BaseModel, SecretStr
-
-from backend.data.model import NodeExecutionStats
-from backend.integrations.providers import ProviderName
-
-if TYPE_CHECKING:
-    from enum import _EnumMemberT
+from typing import Any, Iterable, List, Literal, NamedTuple, Optional
 
 import anthropic
 import ollama
 import openai
-from anthropic._types import NotGiven
 from anthropic.types import ToolParam
-from groq import Groq
+from groq import AsyncGroq
+from pydantic import BaseModel, SecretStr
 
 from backend.data.block import Block, BlockCategory, BlockOutput, BlockSchema
 from backend.data.model import (
     APIKeyCredentials,
     CredentialsField,
     CredentialsMetaInput,
+    NodeExecutionStats,
     SchemaField,
 )
+from backend.integrations.providers import ProviderName
 from backend.util import json
-from backend.util.settings import BehaveAs, Settings
+from backend.util.logging import TruncatedLogger
 from backend.util.text import TextFormatter
 
-logger = logging.getLogger(__name__)
+logger = TruncatedLogger(logging.getLogger(__name__), "[LLM-Block]")
 fmt = TextFormatter()
 
 LLMProviderName = Literal[
+    ProviderName.AIML_API,
     ProviderName.ANTHROPIC,
     ProviderName.GROQ,
     ProviderName.OLLAMA,
     ProviderName.OPENAI,
     ProviderName.OPEN_ROUTER,
+    ProviderName.LLAMA_API,
 ]
 AICredentials = CredentialsMetaInput[LLMProviderName, Literal["api_key"]]
 
@@ -76,38 +71,34 @@ class ModelMetadata(NamedTuple):
 
 
 class LlmModelMeta(EnumMeta):
-    @property
-    def __members__(
-        self: type["_EnumMemberT"],
-    ) -> MappingProxyType[str, "_EnumMemberT"]:
-        if Settings().config.behave_as == BehaveAs.LOCAL:
-            members = super().__members__
-            return members
-        else:
-            removed_providers = ["ollama"]
-            existing_members = super().__members__
-            members = {
-                name: member
-                for name, member in existing_members.items()
-                if LlmModel[name].provider not in removed_providers
-            }
-            return MappingProxyType(members)
+    pass
 
 
 class LlmModel(str, Enum, metaclass=LlmModelMeta):
     # OpenAI models
     O3_MINI = "o3-mini"
+    O3 = "o3-2025-04-16"
     O1 = "o1"
     O1_PREVIEW = "o1-preview"
     O1_MINI = "o1-mini"
+    GPT41 = "gpt-4.1-2025-04-14"
     GPT4O_MINI = "gpt-4o-mini"
     GPT4O = "gpt-4o"
     GPT4_TURBO = "gpt-4-turbo"
     GPT3_5_TURBO = "gpt-3.5-turbo"
     # Anthropic models
+    CLAUDE_4_OPUS = "claude-opus-4-20250514"
+    CLAUDE_4_SONNET = "claude-sonnet-4-20250514"
+    CLAUDE_3_7_SONNET = "claude-3-7-sonnet-20250219"
     CLAUDE_3_5_SONNET = "claude-3-5-sonnet-latest"
     CLAUDE_3_5_HAIKU = "claude-3-5-haiku-latest"
     CLAUDE_3_HAIKU = "claude-3-haiku-20240307"
+    # AI/ML API models
+    AIML_API_QWEN2_5_72B = "Qwen/Qwen2.5-72B-Instruct-Turbo"
+    AIML_API_LLAMA3_1_70B = "nvidia/llama-3.1-nemotron-70b-instruct"
+    AIML_API_LLAMA3_3_70B = "meta-llama/Llama-3.3-70B-Instruct-Turbo"
+    AIML_API_META_LLAMA_3_1_70B = "meta-llama/Meta-Llama-3.1-70B-Instruct-Turbo"
+    AIML_API_LLAMA_3_2_3B = "meta-llama/Llama-3.2-3B-Instruct-Turbo"
     # Groq models
     GEMMA2_9B = "gemma2-9b-it"
     LLAMA3_3_70B = "llama-3.3-70b-versatile"
@@ -125,6 +116,7 @@ class LlmModel(str, Enum, metaclass=LlmModelMeta):
     OLLAMA_DOLPHIN = "dolphin-mistral:latest"
     # OpenRouter models
     GEMINI_FLASH_1_5 = "google/gemini-flash-1.5"
+    GEMINI_2_5_PRO = "google/gemini-2.5-pro-preview-03-25"
     GROK_BETA = "x-ai/grok-beta"
     MISTRAL_NEMO = "mistralai/mistral-nemo"
     COHERE_COMMAND_R_08_2024 = "cohere/command-r-08-2024"
@@ -142,6 +134,13 @@ class LlmModel(str, Enum, metaclass=LlmModelMeta):
     AMAZON_NOVA_PRO_V1 = "amazon/nova-pro-v1"
     MICROSOFT_WIZARDLM_2_8X22B = "microsoft/wizardlm-2-8x22b"
     GRYPHE_MYTHOMAX_L2_13B = "gryphe/mythomax-l2-13b"
+    META_LLAMA_4_SCOUT = "meta-llama/llama-4-scout"
+    META_LLAMA_4_MAVERICK = "meta-llama/llama-4-maverick"
+    # Llama API models
+    LLAMA_API_LLAMA_4_SCOUT = "Llama-4-Scout-17B-16E-Instruct-FP8"
+    LLAMA_API_LLAMA4_MAVERICK = "Llama-4-Maverick-17B-128E-Instruct-FP8"
+    LLAMA_API_LLAMA3_3_8B = "Llama-3.3-8B-Instruct"
+    LLAMA_API_LLAMA3_3_70B = "Llama-3.3-70B-Instruct"
 
     @property
     def metadata(self) -> ModelMetadata:
@@ -162,12 +161,14 @@ class LlmModel(str, Enum, metaclass=LlmModelMeta):
 
 MODEL_METADATA = {
     # https://platform.openai.com/docs/models
+    LlmModel.O3: ModelMetadata("openai", 200000, 100000),
     LlmModel.O3_MINI: ModelMetadata("openai", 200000, 100000),  # o3-mini-2025-01-31
     LlmModel.O1: ModelMetadata("openai", 200000, 100000),  # o1-2024-12-17
     LlmModel.O1_PREVIEW: ModelMetadata(
         "openai", 128000, 32768
     ),  # o1-preview-2024-09-12
     LlmModel.O1_MINI: ModelMetadata("openai", 128000, 65536),  # o1-mini-2024-09-12
+    LlmModel.GPT41: ModelMetadata("openai", 1047576, 32768),
     LlmModel.GPT4O_MINI: ModelMetadata(
         "openai", 128000, 16384
     ),  # gpt-4o-mini-2024-07-18
@@ -177,6 +178,15 @@ MODEL_METADATA = {
     ),  # gpt-4-turbo-2024-04-09
     LlmModel.GPT3_5_TURBO: ModelMetadata("openai", 16385, 4096),  # gpt-3.5-turbo-0125
     # https://docs.anthropic.com/en/docs/about-claude/models
+    LlmModel.CLAUDE_4_OPUS: ModelMetadata(
+        "anthropic", 200000, 8192
+    ),  # claude-4-opus-20250514
+    LlmModel.CLAUDE_4_SONNET: ModelMetadata(
+        "anthropic", 200000, 8192
+    ),  # claude-4-sonnet-20250514
+    LlmModel.CLAUDE_3_7_SONNET: ModelMetadata(
+        "anthropic", 200000, 8192
+    ),  # claude-3-7-sonnet-20250219
     LlmModel.CLAUDE_3_5_SONNET: ModelMetadata(
         "anthropic", 200000, 8192
     ),  # claude-3-5-sonnet-20241022
@@ -186,6 +196,12 @@ MODEL_METADATA = {
     LlmModel.CLAUDE_3_HAIKU: ModelMetadata(
         "anthropic", 200000, 4096
     ),  # claude-3-haiku-20240307
+    # https://docs.aimlapi.com/api-overview/model-database/text-models
+    LlmModel.AIML_API_QWEN2_5_72B: ModelMetadata("aiml_api", 32000, 8000),
+    LlmModel.AIML_API_LLAMA3_1_70B: ModelMetadata("aiml_api", 128000, 40000),
+    LlmModel.AIML_API_LLAMA3_3_70B: ModelMetadata("aiml_api", 128000, None),
+    LlmModel.AIML_API_META_LLAMA_3_1_70B: ModelMetadata("aiml_api", 131000, 2000),
+    LlmModel.AIML_API_LLAMA_3_2_3B: ModelMetadata("aiml_api", 128000, None),
     # https://console.groq.com/docs/models
     LlmModel.GEMMA2_9B: ModelMetadata("groq", 8192, None),
     LlmModel.LLAMA3_3_70B: ModelMetadata("groq", 128000, 32768),
@@ -202,6 +218,7 @@ MODEL_METADATA = {
     LlmModel.OLLAMA_DOLPHIN: ModelMetadata("ollama", 32768, None),
     # https://openrouter.ai/models
     LlmModel.GEMINI_FLASH_1_5: ModelMetadata("open_router", 1000000, 8192),
+    LlmModel.GEMINI_2_5_PRO: ModelMetadata("open_router", 1050000, 8192),
     LlmModel.GROK_BETA: ModelMetadata("open_router", 131072, 131072),
     LlmModel.MISTRAL_NEMO: ModelMetadata("open_router", 128000, 4096),
     LlmModel.COHERE_COMMAND_R_08_2024: ModelMetadata("open_router", 128000, 4096),
@@ -223,6 +240,13 @@ MODEL_METADATA = {
     LlmModel.AMAZON_NOVA_PRO_V1: ModelMetadata("open_router", 300000, 5120),
     LlmModel.MICROSOFT_WIZARDLM_2_8X22B: ModelMetadata("open_router", 65536, 4096),
     LlmModel.GRYPHE_MYTHOMAX_L2_13B: ModelMetadata("open_router", 4096, 4096),
+    LlmModel.META_LLAMA_4_SCOUT: ModelMetadata("open_router", 131072, 131072),
+    LlmModel.META_LLAMA_4_MAVERICK: ModelMetadata("open_router", 1048576, 1000000),
+    # Llama API models
+    LlmModel.LLAMA_API_LLAMA_4_SCOUT: ModelMetadata("llama_api", 128000, 4028),
+    LlmModel.LLAMA_API_LLAMA4_MAVERICK: ModelMetadata("llama_api", 128000, 4028),
+    LlmModel.LLAMA_API_LLAMA3_3_8B: ModelMetadata("llama_api", 128000, 4028),
+    LlmModel.LLAMA_API_LLAMA3_3_70B: ModelMetadata("llama_api", 128000, 4028),
 }
 
 for model in LlmModel:
@@ -252,7 +276,7 @@ class LLMResponse(BaseModel):
 
 def convert_openai_tool_fmt_to_anthropic(
     openai_tools: list[dict] | None = None,
-) -> Iterable[ToolParam] | NotGiven:
+) -> Iterable[ToolParam] | anthropic.NotGiven:
     """
     Convert OpenAI tool format to Anthropic tool format.
     """
@@ -282,7 +306,14 @@ def convert_openai_tool_fmt_to_anthropic(
     return anthropic_tools
 
 
-def llm_call(
+def estimate_token_count(prompt_messages: list[dict]) -> int:
+    char_count = sum(len(str(msg.get("content", ""))) for msg in prompt_messages)
+    message_overhead = len(prompt_messages) * 4
+    estimated_tokens = (char_count // 4) + message_overhead
+    return int(estimated_tokens * 1.2)
+
+
+async def llm_call(
     credentials: APIKeyCredentials,
     llm_model: LlmModel,
     prompt: list[dict],
@@ -290,6 +321,7 @@ def llm_call(
     max_tokens: int | None,
     tools: list[dict] | None = None,
     ollama_host: str = "localhost:11434",
+    parallel_tool_calls: bool | None = None,
 ) -> LLMResponse:
     """
     Make a call to a language model.
@@ -312,11 +344,18 @@ def llm_call(
             - completion_tokens: The number of tokens used in the completion.
     """
     provider = llm_model.metadata.provider
-    max_tokens = max_tokens or llm_model.max_output_tokens or 4096
+
+    # Calculate available tokens based on context window and input length
+    estimated_input_tokens = estimate_token_count(prompt)
+    context_window = llm_model.context_window
+    model_max_output = llm_model.max_output_tokens or 4096
+    user_max = max_tokens or model_max_output
+    available_tokens = max(context_window - estimated_input_tokens, 0)
+    max_tokens = max(min(available_tokens, model_max_output, user_max), 0)
 
     if provider == "openai":
         tools_param = tools if tools else openai.NOT_GIVEN
-        oai_client = openai.OpenAI(api_key=credentials.api_key.get_secret_value())
+        oai_client = openai.AsyncOpenAI(api_key=credentials.api_key.get_secret_value())
         response_format = None
 
         if llm_model in [LlmModel.O1_MINI, LlmModel.O1_PREVIEW]:
@@ -329,12 +368,15 @@ def llm_call(
         elif json_format:
             response_format = {"type": "json_object"}
 
-        response = oai_client.chat.completions.create(
+        response = await oai_client.chat.completions.create(
             model=llm_model.value,
             messages=prompt,  # type: ignore
             response_format=response_format,  # type: ignore
             max_completion_tokens=max_tokens,
             tools=tools_param,  # type: ignore
+            parallel_tool_calls=(
+                openai.NOT_GIVEN if parallel_tool_calls is None else parallel_tool_calls
+            ),
         )
 
         if response.choices[0].message.tool_calls:
@@ -382,9 +424,11 @@ def llm_call(
                     messages.append({"role": p["role"], "content": p["content"]})
                     last_role = p["role"]
 
-        client = anthropic.Anthropic(api_key=credentials.api_key.get_secret_value())
+        client = anthropic.AsyncAnthropic(
+            api_key=credentials.api_key.get_secret_value()
+        )
         try:
-            resp = client.messages.create(
+            resp = await client.messages.create(
                 model=llm_model.value,
                 system=sysprompt,
                 messages=messages,
@@ -415,7 +459,7 @@ def llm_call(
 
             if not tool_calls and resp.stop_reason == "tool_use":
                 logger.warning(
-                    "Tool use stop reason but no tool calls found in content. %s", resp
+                    f"Tool use stop reason but no tool calls found in content. {resp}"
                 )
 
             return LLMResponse(
@@ -424,7 +468,7 @@ def llm_call(
                 response=(
                     resp.content[0].name
                     if isinstance(resp.content[0], anthropic.types.ToolUseBlock)
-                    else resp.content[0].text
+                    else getattr(resp.content[0], "text", "")
                 ),
                 tool_calls=tool_calls,
                 prompt_tokens=resp.usage.input_tokens,
@@ -438,9 +482,9 @@ def llm_call(
         if tools:
             raise ValueError("Groq does not support tools.")
 
-        client = Groq(api_key=credentials.api_key.get_secret_value())
+        client = AsyncGroq(api_key=credentials.api_key.get_secret_value())
         response_format = {"type": "json_object"} if json_format else None
-        response = client.chat.completions.create(
+        response = await client.chat.completions.create(
             model=llm_model.value,
             messages=prompt,  # type: ignore
             response_format=response_format,  # type: ignore
@@ -458,13 +502,14 @@ def llm_call(
         if tools:
             raise ValueError("Ollama does not support tools.")
 
-        client = ollama.Client(host=ollama_host)
+        client = ollama.AsyncClient(host=ollama_host)
         sys_messages = [p["content"] for p in prompt if p["role"] == "system"]
         usr_messages = [p["content"] for p in prompt if p["role"] != "system"]
-        response = client.generate(
+        response = await client.generate(
             model=llm_model.value,
             prompt=f"{sys_messages}\n\n{usr_messages}",
             stream=False,
+            options={"num_ctx": max_tokens},
         )
         return LLMResponse(
             raw_response=response.get("response") or "",
@@ -476,12 +521,12 @@ def llm_call(
         )
     elif provider == "open_router":
         tools_param = tools if tools else openai.NOT_GIVEN
-        client = openai.OpenAI(
+        client = openai.AsyncOpenAI(
             base_url="https://openrouter.ai/api/v1",
             api_key=credentials.api_key.get_secret_value(),
         )
 
-        response = client.chat.completions.create(
+        response = await client.chat.completions.create(
             extra_headers={
                 "HTTP-Referer": "https://agpt.co",
                 "X-Title": "AutoGPT",
@@ -521,6 +566,79 @@ def llm_call(
             prompt_tokens=response.usage.prompt_tokens if response.usage else 0,
             completion_tokens=response.usage.completion_tokens if response.usage else 0,
         )
+    elif provider == "llama_api":
+        tools_param = tools if tools else openai.NOT_GIVEN
+        client = openai.AsyncOpenAI(
+            base_url="https://api.llama.com/compat/v1/",
+            api_key=credentials.api_key.get_secret_value(),
+        )
+
+        response = await client.chat.completions.create(
+            extra_headers={
+                "HTTP-Referer": "https://agpt.co",
+                "X-Title": "AutoGPT",
+            },
+            model=llm_model.value,
+            messages=prompt,  # type: ignore
+            max_tokens=max_tokens,
+            tools=tools_param,  # type: ignore
+            parallel_tool_calls=(
+                openai.NOT_GIVEN if parallel_tool_calls is None else parallel_tool_calls
+            ),
+        )
+
+        # If there's no response, raise an error
+        if not response.choices:
+            if response:
+                raise ValueError(f"Llama API error: {response}")
+            else:
+                raise ValueError("No response from Llama API.")
+
+        if response.choices[0].message.tool_calls:
+            tool_calls = [
+                ToolContentBlock(
+                    id=tool.id,
+                    type=tool.type,
+                    function=ToolCall(
+                        name=tool.function.name, arguments=tool.function.arguments
+                    ),
+                )
+                for tool in response.choices[0].message.tool_calls
+            ]
+        else:
+            tool_calls = None
+
+        return LLMResponse(
+            raw_response=response.choices[0].message,
+            prompt=prompt,
+            response=response.choices[0].message.content or "",
+            tool_calls=tool_calls,
+            prompt_tokens=response.usage.prompt_tokens if response.usage else 0,
+            completion_tokens=response.usage.completion_tokens if response.usage else 0,
+        )
+    elif provider == "aiml_api":
+        client = openai.OpenAI(
+            base_url="https://api.aimlapi.com/v2",
+            api_key=credentials.api_key.get_secret_value(),
+            default_headers={"X-Project": "AutoGPT"},
+        )
+
+        completion = client.chat.completions.create(
+            model=llm_model.value,
+            messages=prompt,  # type: ignore
+            max_tokens=max_tokens,
+        )
+
+        return LLMResponse(
+            raw_response=completion.choices[0].message,
+            prompt=prompt,
+            response=completion.choices[0].message.content or "",
+            tool_calls=None,
+            prompt_tokens=completion.usage.prompt_tokens if completion.usage else 0,
+            completion_tokens=(
+                completion.usage.completion_tokens if completion.usage else 0
+            ),
+        )
     else:
         raise ValueError(f"Unsupported LLM provider: {provider}")
 
@@ -528,7 +646,7 @@ def llm_call(
 class AIBlockBase(Block, ABC):
     def __init__(self, *args, **kwargs):
         super().__init__(*args, **kwargs)
-        self.prompt = ""
+        self.prompt = []
 
     def merge_llm_stats(self, block: "AIBlockBase"):
         self.merge_stats(block.execution_stats)
@@ -558,7 +676,7 @@ class AIStructuredResponseGeneratorBlock(AIBlockBase):
             description="The system prompt to provide additional context to the model.",
         )
         conversation_history: list[dict] = SchemaField(
-            default=[],
+            default_factory=list,
             description="The conversation history to provide context for the prompt.",
         )
         retry: int = SchemaField(
@@ -568,7 +686,7 @@ class AIStructuredResponseGeneratorBlock(AIBlockBase):
         )
         prompt_values: dict[str, str] = SchemaField(
             advanced=False,
-            default={},
+            default_factory=dict,
             description="Values used to fill in the prompt. The values can be used in the prompt by putting them in a double curly braces, e.g. {{variable_name}}.",
         )
         max_tokens: int | None = SchemaField(
@@ -587,7 +705,7 @@ class AIStructuredResponseGeneratorBlock(AIBlockBase):
         response: dict[str, Any] = SchemaField(
             description="The response object generated by the language model."
         )
-        prompt: str = SchemaField(description="The prompt sent to the language model.")
+        prompt: list = SchemaField(description="The prompt sent to the language model.")
         error: str = SchemaField(description="Error message if the API call failed.")
 
     def __init__(self):
@@ -609,7 +727,7 @@ class AIStructuredResponseGeneratorBlock(AIBlockBase):
             test_credentials=TEST_CREDENTIALS,
             test_output=[
                 ("response", {"key1": "key1Value", "key2": "key2Value"}),
-                ("prompt", str),
+                ("prompt", list),
             ],
             test_mock={
                 "llm_call": lambda *args, **kwargs: LLMResponse(
@@ -628,7 +746,7 @@ class AIStructuredResponseGeneratorBlock(AIBlockBase):
             },
         )
 
-    def llm_call(
+    async def llm_call(
         self,
         credentials: APIKeyCredentials,
         llm_model: LlmModel,
@@ -642,7 +760,8 @@ class AIStructuredResponseGeneratorBlock(AIBlockBase):
         Test mocks work only on class functions, this wraps the llm_call function
         so that it can be mocked withing the block testing framework.
         """
-        return llm_call(
+        self.prompt = prompt
+        return await llm_call(
             credentials=credentials,
             llm_model=llm_model,
             prompt=prompt,
@@ -652,7 +771,7 @@ class AIStructuredResponseGeneratorBlock(AIBlockBase):
             ollama_host=ollama_host,
         )
 
-    def run(
+    async def run(
         self, input_data: Input, *, credentials: APIKeyCredentials, **kwargs
     ) -> BlockOutput:
         logger.debug(f"Calling LLM with input data: {input_data}")
@@ -706,7 +825,7 @@ class AIStructuredResponseGeneratorBlock(AIBlockBase):
 
         for retry_count in range(input_data.retry):
             try:
-                llm_response = self.llm_call(
+                llm_response = await self.llm_call(
                     credentials=credentials,
                     llm_model=llm_model,
                     prompt=prompt,
@@ -759,6 +878,16 @@ class AIStructuredResponseGeneratorBlock(AIBlockBase):
                 prompt.append({"role": "user", "content": retry_prompt})
             except Exception as e:
                 logger.exception(f"Error calling LLM: {e}")
+                if (
+                    "maximum context length" in str(e).lower()
+                    or "token limit" in str(e).lower()
+                ):
+                    if input_data.max_tokens is None:
+                        input_data.max_tokens = llm_model.max_output_tokens or 4096
+                    input_data.max_tokens = int(input_data.max_tokens * 0.85)
+                    logger.debug(
+                        f"Reducing max_tokens to {input_data.max_tokens} for next attempt"
+                    )
                 retry_prompt = f"Error calling LLM: {e}"
             finally:
                 self.merge_stats(
@@ -796,7 +925,7 @@ class AITextGeneratorBlock(AIBlockBase):
         )
         prompt_values: dict[str, str] = SchemaField(
             advanced=False,
-            default={},
+            default_factory=dict,
             description="Values used to fill in the prompt. The values can be used in the prompt by putting them in a double curly braces, e.g. {{variable_name}}.",
         )
         ollama_host: str = SchemaField(
@@ -814,7 +943,7 @@ class AITextGeneratorBlock(AIBlockBase):
         response: str = SchemaField(
             description="The response generated by the language model."
         )
-        prompt: str = SchemaField(description="The prompt sent to the language model.")
+        prompt: list = SchemaField(description="The prompt sent to the language model.")
         error: str = SchemaField(description="Error message if the API call failed.")
 
     def __init__(self):
@@ -831,29 +960,33 @@ class AITextGeneratorBlock(AIBlockBase):
             test_credentials=TEST_CREDENTIALS,
             test_output=[
                 ("response", "Response text"),
-                ("prompt", str),
+                ("prompt", list),
             ],
             test_mock={"llm_call": lambda *args, **kwargs: "Response text"},
         )
 
-    def llm_call(
+    async def llm_call(
         self,
         input_data: AIStructuredResponseGeneratorBlock.Input,
         credentials: APIKeyCredentials,
-    ) -> str:
+    ) -> dict:
         block = AIStructuredResponseGeneratorBlock()
-        response = block.run_once(input_data, "response", credentials=credentials)
+        response = await block.run_once(input_data, "response", credentials=credentials)
         self.merge_llm_stats(block)
         return response["response"]
 
-    def run(
+    async def run(
         self, input_data: Input, *, credentials: APIKeyCredentials, **kwargs
     ) -> BlockOutput:
         object_input_data = AIStructuredResponseGeneratorBlock.Input(
-            **{attr: getattr(input_data, attr) for attr in input_data.model_fields},
+            **{
+                attr: getattr(input_data, attr)
+                for attr in AITextGeneratorBlock.Input.model_fields
+            },
             expected_format={},
         )
-        yield "response", self.llm_call(object_input_data, credentials)
+        response = await self.llm_call(object_input_data, credentials)
+        yield "response", response
         yield "prompt", self.prompt
 
 
@@ -907,7 +1040,7 @@ class AITextSummarizerBlock(AIBlockBase):
 
     class Output(BlockSchema):
         summary: str = SchemaField(description="The final summary of the text.")
-        prompt: str = SchemaField(description="The prompt sent to the language model.")
+        prompt: list = SchemaField(description="The prompt sent to the language model.")
         error: str = SchemaField(description="Error message if the API call failed.")
 
     def __init__(self):
@@ -924,7 +1057,7 @@ class AITextSummarizerBlock(AIBlockBase):
             test_credentials=TEST_CREDENTIALS,
             test_output=[
                 ("summary", "Final summary of a long text"),
-                ("prompt", str),
+                ("prompt", list),
             ],
             test_mock={
                 "llm_call": lambda input_data, credentials: (
@@ -935,23 +1068,27 @@ class AITextSummarizerBlock(AIBlockBase):
             },
         )
 
-    def run(
+    async def run(
         self, input_data: Input, *, credentials: APIKeyCredentials, **kwargs
     ) -> BlockOutput:
-        for output in self._run(input_data, credentials):
-            yield output
+        async for output_name, output_data in self._run(input_data, credentials):
+            yield output_name, output_data
 
-    def _run(self, input_data: Input, credentials: APIKeyCredentials) -> BlockOutput:
+    async def _run(
+        self, input_data: Input, credentials: APIKeyCredentials
+    ) -> BlockOutput:
         chunks = self._split_text(
             input_data.text, input_data.max_tokens, input_data.chunk_overlap
         )
         summaries = []
 
         for chunk in chunks:
-            chunk_summary = self._summarize_chunk(chunk, input_data, credentials)
+            chunk_summary = await self._summarize_chunk(chunk, input_data, credentials)
             summaries.append(chunk_summary)
 
-        final_summary = self._combine_summaries(summaries, input_data, credentials)
+        final_summary = await self._combine_summaries(
+            summaries, input_data, credentials
+        )
         yield "summary", final_summary
         yield "prompt", self.prompt
 
@@ -967,22 +1104,22 @@ class AITextSummarizerBlock(AIBlockBase):
 
         return chunks
 
-    def llm_call(
+    async def llm_call(
         self,
         input_data: AIStructuredResponseGeneratorBlock.Input,
         credentials: APIKeyCredentials,
     ) -> dict:
         block = AIStructuredResponseGeneratorBlock()
-        response = block.run_once(input_data, "response", credentials=credentials)
+        response = await block.run_once(input_data, "response", credentials=credentials)
         self.merge_llm_stats(block)
         return response
 
-    def _summarize_chunk(
+    async def _summarize_chunk(
         self, chunk: str, input_data: Input, credentials: APIKeyCredentials
     ) -> str:
         prompt = f"Summarize the following text in a {input_data.style} form. Focus your summary on the topic of `{input_data.focus}` if present, otherwise just provide a general summary:\n\n```{chunk}```"
 
-        llm_response = self.llm_call(
+        llm_response = await self.llm_call(
             AIStructuredResponseGeneratorBlock.Input(
                 prompt=prompt,
                 credentials=input_data.credentials,
@@ -994,7 +1131,7 @@ class AITextSummarizerBlock(AIBlockBase):
 
         return llm_response["summary"]
 
-    def _combine_summaries(
+    async def _combine_summaries(
         self, summaries: list[str], input_data: Input, credentials: APIKeyCredentials
     ) -> str:
         combined_text = "\n\n".join(summaries)
@@ -1002,7 +1139,7 @@ class AITextSummarizerBlock(AIBlockBase):
         if len(combined_text.split()) <= input_data.max_tokens:
             prompt = f"Provide a final summary of the following section summaries in a {input_data.style} form, focus your summary on the topic of `{input_data.focus}` if present:\n\n ```{combined_text}```\n\n Just respond with the final_summary in the format specified."
 
-            llm_response = self.llm_call(
+            llm_response = await self.llm_call(
                 AIStructuredResponseGeneratorBlock.Input(
                     prompt=prompt,
                     credentials=input_data.credentials,
@@ -1017,7 +1154,8 @@ class AITextSummarizerBlock(AIBlockBase):
             return llm_response["final_summary"]
         else:
             # If combined summaries are still too long, recursively summarize
-            return self._run(
+            block = AITextSummarizerBlock()
+            return await block.run_once(
                 AITextSummarizerBlock.Input(
                     text=combined_text,
                     credentials=input_data.credentials,
@@ -1025,16 +1163,21 @@ class AITextSummarizerBlock(AIBlockBase):
                     max_tokens=input_data.max_tokens,
                     chunk_overlap=input_data.chunk_overlap,
                 ),
+                "summary",
                 credentials=credentials,
-            ).send(None)[
-                1
-            ]  # Get the first yielded value
+            )
 
 
 class AIConversationBlock(AIBlockBase):
     class Input(BlockSchema):
+        prompt: str = SchemaField(
+            description="The prompt to send to the language model.",
+            placeholder="Enter your prompt here...",
+            default="",
+            advanced=False,
+        )
         messages: List[Any] = SchemaField(
-            description="List of messages in the conversation.", min_length=1
+            description="List of messages in the conversation.",
         )
         model: LlmModel = SchemaField(
             title="LLM Model",
@@ -1057,7 +1200,7 @@ class AIConversationBlock(AIBlockBase):
         response: str = SchemaField(
             description="The model's response to the conversation."
         )
-        prompt: str = SchemaField(description="The prompt sent to the language model.")
+        prompt: list = SchemaField(description="The prompt sent to the language model.")
         error: str = SchemaField(description="Error message if the API call failed.")
 
     def __init__(self):
@@ -1086,29 +1229,29 @@ class AIConversationBlock(AIBlockBase):
                     "response",
                     "The 2020 World Series was played at Globe Life Field in Arlington, Texas.",
                 ),
-                ("prompt", str),
+                ("prompt", list),
             ],
             test_mock={
                 "llm_call": lambda *args, **kwargs: "The 2020 World Series was played at Globe Life Field in Arlington, Texas."
             },
         )
 
-    def llm_call(
+    async def llm_call(
         self,
         input_data: AIStructuredResponseGeneratorBlock.Input,
         credentials: APIKeyCredentials,
-    ) -> str:
+    ) -> dict:
         block = AIStructuredResponseGeneratorBlock()
-        response = block.run_once(input_data, "response", credentials=credentials)
+        response = await block.run_once(input_data, "response", credentials=credentials)
         self.merge_llm_stats(block)
-        return response["response"]
+        return response
 
-    def run(
+    async def run(
         self, input_data: Input, *, credentials: APIKeyCredentials, **kwargs
     ) -> BlockOutput:
-        response = self.llm_call(
+        response = await self.llm_call(
             AIStructuredResponseGeneratorBlock.Input(
-                prompt="",
+                prompt=input_data.prompt,
                 credentials=input_data.credentials,
                 model=input_data.model,
                 conversation_history=input_data.messages,
@@ -1118,7 +1261,6 @@ class AIConversationBlock(AIBlockBase):
             ),
             credentials=credentials,
         )
-
         yield "response", response
         yield "prompt", self.prompt
 
@@ -1166,7 +1308,7 @@ class AIListGeneratorBlock(AIBlockBase):
         list_item: str = SchemaField(
             description="Each individual item in the list.",
         )
-        prompt: str = SchemaField(description="The prompt sent to the language model.")
+        prompt: list = SchemaField(description="The prompt sent to the language model.")
         error: str = SchemaField(
             description="Error message if the list generation failed."
         )
@@ -1198,7 +1340,7 @@ class AIListGeneratorBlock(AIBlockBase):
                     "generated_list",
                     ["Zylora Prime", "Kharon-9", "Vortexia", "Oceara", "Draknos"],
                 ),
-                ("prompt", str),
+                ("prompt", list),
                 ("list_item", "Zylora Prime"),
                 ("list_item", "Kharon-9"),
                 ("list_item", "Vortexia"),
@@ -1212,13 +1354,15 @@ class AIListGeneratorBlock(AIBlockBase):
             },
         )
 
-    def llm_call(
+    async def llm_call(
         self,
         input_data: AIStructuredResponseGeneratorBlock.Input,
         credentials: APIKeyCredentials,
     ) -> dict[str, str]:
         llm_block = AIStructuredResponseGeneratorBlock()
-        response = llm_block.run_once(input_data, "response", credentials=credentials)
+        response = await llm_block.run_once(
+            input_data, "response", credentials=credentials
+        )
         self.merge_llm_stats(llm_block)
         return response
 
@@ -1241,7 +1385,7 @@ class AIListGeneratorBlock(AIBlockBase):
             logger.error(f"Failed to convert string to list: {e}")
             raise ValueError("Invalid list format. Could not convert to list.")
 
-    def run(
+    async def run(
         self, input_data: Input, *, credentials: APIKeyCredentials, **kwargs
     ) -> BlockOutput:
         logger.debug(f"Starting AIListGeneratorBlock.run with input data: {input_data}")
@@ -1307,7 +1451,7 @@ class AIListGeneratorBlock(AIBlockBase):
         for attempt in range(input_data.max_retries):
             try:
                 logger.debug("Calling LLM")
-                llm_response = self.llm_call(
+                llm_response = await self.llm_call(
                     AIStructuredResponseGeneratorBlock.Input(
                         sys_prompt=sys_prompt,
                         prompt=prompt,

autogpt_platform/backend/backend/blocks/maths.py

@@ -52,7 +52,7 @@ class CalculatorBlock(Block):
             ],
         )
 
-    def run(self, input_data: Input, **kwargs) -> BlockOutput:
+    async def run(self, input_data: Input, **kwargs) -> BlockOutput:
         operation = input_data.operation
         a = input_data.a
         b = input_data.b
@@ -107,7 +107,7 @@ class CountItemsBlock(Block):
             ],
         )
 
-    def run(self, input_data: Input, **kwargs) -> BlockOutput:
+    async def run(self, input_data: Input, **kwargs) -> BlockOutput:
         collection = input_data.collection
 
         try:

autogpt_platform/backend/backend/blocks/media.py

@@ -39,7 +39,7 @@ class MediaDurationBlock(Block):
             output_schema=MediaDurationBlock.Output,
         )
 
-    def run(
+    async def run(
         self,
         input_data: Input,
         *,
@@ -47,7 +47,7 @@ class MediaDurationBlock(Block):
         **kwargs,
     ) -> BlockOutput:
         # 1) Store the input media locally
-        local_media_path = store_media_file(
+        local_media_path = await store_media_file(
             graph_exec_id=graph_exec_id,
             file=input_data.media_in,
             return_content=False,
@@ -105,7 +105,7 @@ class LoopVideoBlock(Block):
             output_schema=LoopVideoBlock.Output,
         )
 
-    def run(
+    async def run(
         self,
         input_data: Input,
         *,
@@ -114,7 +114,7 @@ class LoopVideoBlock(Block):
         **kwargs,
     ) -> BlockOutput:
         # 1) Store the input video locally
-        local_video_path = store_media_file(
+        local_video_path = await store_media_file(
             graph_exec_id=graph_exec_id,
             file=input_data.video_in,
             return_content=False,
@@ -146,7 +146,7 @@ class LoopVideoBlock(Block):
         looped_clip.write_videofile(output_abspath, codec="libx264", audio_codec="aac")
 
         # Return as data URI
-        video_out = store_media_file(
+        video_out = await store_media_file(
             graph_exec_id=graph_exec_id,
             file=output_filename,
             return_content=input_data.output_return_type == "data_uri",
@@ -194,7 +194,7 @@ class AddAudioToVideoBlock(Block):
             output_schema=AddAudioToVideoBlock.Output,
         )
 
-    def run(
+    async def run(
         self,
         input_data: Input,
         *,
@@ -203,12 +203,12 @@ class AddAudioToVideoBlock(Block):
         **kwargs,
     ) -> BlockOutput:
         # 1) Store the inputs locally
-        local_video_path = store_media_file(
+        local_video_path = await store_media_file(
             graph_exec_id=graph_exec_id,
             file=input_data.video_in,
             return_content=False,
         )
-        local_audio_path = store_media_file(
+        local_audio_path = await store_media_file(
             graph_exec_id=graph_exec_id,
             file=input_data.audio_in,
             return_content=False,
@@ -236,7 +236,7 @@ class AddAudioToVideoBlock(Block):
         final_clip.write_videofile(output_abspath, codec="libx264", audio_codec="aac")
 
         # 5) Return either path or data URI
-        video_out = store_media_file(
+        video_out = await store_media_file(
             graph_exec_id=graph_exec_id,
             file=output_filename,
             return_content=input_data.output_return_type == "data_uri",

autogpt_platform/backend/backend/blocks/medium.py

@@ -13,7 +13,7 @@ from backend.data.model import (
     SecretField,
 )
 from backend.integrations.providers import ProviderName
-from backend.util.request import requests
+from backend.util.request import Requests
 
 TEST_CREDENTIALS = APIKeyCredentials(
     id="01234567-89ab-cdef-0123-456789abcdef",
@@ -130,7 +130,7 @@ class PublishToMediumBlock(Block):
             test_credentials=TEST_CREDENTIALS,
         )
 
-    def create_post(
+    async def create_post(
         self,
         api_key: SecretStr,
         author_id,
@@ -160,18 +160,17 @@ class PublishToMediumBlock(Block):
             "notifyFollowers": notify_followers,
         }
 
-        response = requests.post(
+        response = await Requests().post(
             f"https://api.medium.com/v1/users/{author_id}/posts",
             headers=headers,
             json=data,
         )
-
         return response.json()
 
-    def run(
+    async def run(
         self, input_data: Input, *, credentials: APIKeyCredentials, **kwargs
     ) -> BlockOutput:
-        response = self.create_post(
+        response = await self.create_post(
             credentials.api_key,
             input_data.author_id.get_secret_value(),
             input_data.title,

autogpt_platform/backend/backend/blocks/mem0.py

@@ -65,7 +65,7 @@ class AddMemoryBlock(Block, Mem0Base):
             default=Content(discriminator="content", content="I'm a vegetarian"),
         )
         metadata: dict[str, Any] = SchemaField(
-            description="Optional metadata for the memory", default={}
+            description="Optional metadata for the memory", default_factory=dict
         )
 
         limit_memory_to_run: bool = SchemaField(
@@ -109,7 +109,7 @@ class AddMemoryBlock(Block, Mem0Base):
             test_mock={"_get_client": lambda credentials: MockMemoryClient()},
         )
 
-    def run(
+    async def run(
         self,
         input_data: Input,
         *,
@@ -124,8 +124,10 @@ class AddMemoryBlock(Block, Mem0Base):
 
             if isinstance(input_data.content, Conversation):
                 messages = input_data.content.messages
+            elif isinstance(input_data.content, Content):
+                messages = [{"role": "user", "content": input_data.content.content}]
             else:
-                messages = [{"role": "user", "content": input_data.content}]
+                messages = [{"role": "user", "content": str(input_data.content)}]
 
             params = {
                 "user_id": user_id,
@@ -152,7 +154,7 @@ class AddMemoryBlock(Block, Mem0Base):
                 yield "action", "NO_CHANGE"
 
         except Exception as e:
-            yield "error", str(object=e)
+            yield "error", str(e)
 
 
 class SearchMemoryBlock(Block, Mem0Base):
@@ -173,7 +175,7 @@ class SearchMemoryBlock(Block, Mem0Base):
         )
         categories_filter: list[str] = SchemaField(
             description="Categories to filter by",
-            default=[],
+            default_factory=list,
             advanced=True,
         )
         limit_memory_to_run: bool = SchemaField(
@@ -206,7 +208,7 @@ class SearchMemoryBlock(Block, Mem0Base):
             test_mock={"_get_client": lambda credentials: MockMemoryClient()},
         )
 
-    def run(
+    async def run(
         self,
         input_data: Input,
         *,
@@ -286,7 +288,7 @@ class GetAllMemoriesBlock(Block, Mem0Base):
             test_mock={"_get_client": lambda credentials: MockMemoryClient()},
         )
 
-    def run(
+    async def run(
         self,
         input_data: Input,
         *,

autogpt_platform/backend/backend/blocks/nvidia/deepfake.py

@@ -5,7 +5,7 @@ from backend.blocks.nvidia._auth import (
 )
 from backend.data.block import Block, BlockCategory, BlockOutput, BlockSchema
 from backend.data.model import SchemaField
-from backend.util.request import requests
+from backend.util.request import Requests
 from backend.util.type import MediaFileType
 
 
@@ -40,7 +40,7 @@ class NvidiaDeepfakeDetectBlock(Block):
             output_schema=NvidiaDeepfakeDetectBlock.Output,
         )
 
-    def run(
+    async def run(
         self, input_data: Input, *, credentials: NvidiaCredentials, **kwargs
     ) -> BlockOutput:
         url = "https://ai.api.nvidia.com/v1/cv/hive/deepfake-image-detection"
@@ -59,8 +59,7 @@ class NvidiaDeepfakeDetectBlock(Block):
         }
 
         try:
-            response = requests.post(url, headers=headers, json=payload)
-            response.raise_for_status()
+            response = await Requests().post(url, headers=headers, json=payload)
             data = response.json()
 
             result = data.get("data", [{}])[0]

autogpt_platform/backend/backend/blocks/pinecone.py

@@ -56,7 +56,7 @@ class PineconeInitBlock(Block):
             output_schema=PineconeInitBlock.Output,
         )
 
-    def run(
+    async def run(
         self, input_data: Input, *, credentials: APIKeyCredentials, **kwargs
     ) -> BlockOutput:
         pc = Pinecone(api_key=credentials.api_key.get_secret_value())
@@ -117,7 +117,7 @@ class PineconeQueryBlock(Block):
             output_schema=PineconeQueryBlock.Output,
         )
 
-    def run(
+    async def run(
         self,
         input_data: Input,
         *,
@@ -177,7 +177,8 @@ class PineconeInsertBlock(Block):
             description="Namespace to use in Pinecone", default=""
         )
         metadata: dict = SchemaField(
-            description="Additional metadata to store with each vector", default={}
+            description="Additional metadata to store with each vector",
+            default_factory=dict,
         )
 
     class Output(BlockSchema):
@@ -194,7 +195,7 @@ class PineconeInsertBlock(Block):
             output_schema=PineconeInsertBlock.Output,
         )
 
-    def run(
+    async def run(
         self,
         input_data: Input,
         *,

autogpt_platform/backend/backend/blocks/reddit.py

@@ -146,7 +146,7 @@ class GetRedditPostsBlock(Block):
         subreddit = client.subreddit(input_data.subreddit)
         return subreddit.new(limit=input_data.post_limit or 10)
 
-    def run(
+    async def run(
         self, input_data: Input, *, credentials: RedditCredentials, **kwargs
     ) -> BlockOutput:
         current_time = datetime.now(tz=timezone.utc)
@@ -207,7 +207,7 @@ class PostRedditCommentBlock(Block):
             raise ValueError("Failed to post comment.")
         return new_comment.id
 
-    def run(
+    async def run(
         self, input_data: Input, *, credentials: RedditCredentials, **kwargs
     ) -> BlockOutput:
         yield "comment_id", self.reply_post(credentials, input_data.data)

autogpt_platform/backend/backend/blocks/replicate_flux_advanced.py

@@ -2,8 +2,8 @@ import os
 from enum import Enum
 from typing import Literal
 
-import replicate
 from pydantic import SecretStr
+from replicate.client import Client as ReplicateClient
 from replicate.helpers import FileOutput
 
 from backend.data.block import Block, BlockCategory, BlockOutput, BlockSchema
@@ -159,7 +159,7 @@ class ReplicateFluxAdvancedModelBlock(Block):
             test_credentials=TEST_CREDENTIALS,
         )
 
-    def run(
+    async def run(
         self, input_data: Input, *, credentials: APIKeyCredentials, **kwargs
     ) -> BlockOutput:
         # If the seed is not provided, generate a random seed
@@ -168,7 +168,7 @@ class ReplicateFluxAdvancedModelBlock(Block):
             seed = int.from_bytes(os.urandom(4), "big")
 
         # Run the model using the provided inputs
-        result = self.run_model(
+        result = await self.run_model(
             api_key=credentials.api_key,
             model_name=input_data.replicate_model_name.api_name,
             prompt=input_data.prompt,
@@ -183,7 +183,7 @@ class ReplicateFluxAdvancedModelBlock(Block):
         )
         yield "result", result
 
-    def run_model(
+    async def run_model(
         self,
         api_key: SecretStr,
         model_name,
@@ -198,10 +198,10 @@ class ReplicateFluxAdvancedModelBlock(Block):
         safety_tolerance,
     ):
         # Initialize Replicate client with the API key
-        client = replicate.Client(api_token=api_key.get_secret_value())
+        client = ReplicateClient(api_token=api_key.get_secret_value())
 
         # Run the model with additional parameters
-        output: FileOutput | list[FileOutput] = client.run(  # type: ignore This is because they changed the return type, and didn't update the type hint! It should be overloaded depending on the value of `use_file_output` to `FileOutput | list[FileOutput]` but it's `Any | Iterator[Any]`
+        output: FileOutput | list[FileOutput] = await client.async_run(  # type: ignore This is because they changed the return type, and didn't update the type hint! It should be overloaded depending on the value of `use_file_output` to `FileOutput | list[FileOutput]` but it's `Any | Iterator[Any]`
             f"{model_name}",
             input={
                 "prompt": prompt,

autogpt_platform/backend/backend/blocks/rss.py

@@ -1,4 +1,4 @@
-import time
+import asyncio
 from datetime import datetime, timedelta, timezone
 from typing import Any
 
@@ -87,7 +87,7 @@ class ReadRSSFeedBlock(Block):
     def parse_feed(url: str) -> dict[str, Any]:
         return feedparser.parse(url)  # type: ignore
 
-    def run(self, input_data: Input, **kwargs) -> BlockOutput:
+    async def run(self, input_data: Input, **kwargs) -> BlockOutput:
         keep_going = True
         start_time = datetime.now(timezone.utc) - timedelta(
             minutes=input_data.time_period
@@ -113,4 +113,4 @@ class ReadRSSFeedBlock(Block):
                         ),
                     )
 
-            time.sleep(input_data.polling_rate)
+            await asyncio.sleep(input_data.polling_rate)

autogpt_platform/backend/backend/blocks/sampling.py

@@ -93,7 +93,7 @@ class DataSamplingBlock(Block):
         )
         self.accumulated_data = []
 
-    def run(self, input_data: Input, **kwargs) -> BlockOutput:
+    async def run(self, input_data: Input, **kwargs) -> BlockOutput:
         if input_data.accumulate:
             if isinstance(input_data.data, dict):
                 self.accumulated_data.append(input_data.data)

autogpt_platform/backend/backend/blocks/screenshotone.py

@@ -105,7 +105,7 @@ class ScreenshotWebPageBlock(Block):
         )
 
     @staticmethod
-    def take_screenshot(
+    async def take_screenshot(
         credentials: APIKeyCredentials,
         graph_exec_id: str,
         url: str,
@@ -121,11 +121,10 @@ class ScreenshotWebPageBlock(Block):
         """
         Takes a screenshot using the ScreenshotOne API
         """
-        api = Requests(trusted_origins=["https://api.screenshotone.com"])
+        api = Requests()
 
-        # Build API URL with parameters
+        # Build API parameters
         params = {
-            "access_key": credentials.api_key.get_secret_value(),
             "url": url,
             "viewport_width": viewport_width,
             "viewport_height": viewport_height,
@@ -137,19 +136,28 @@ class ScreenshotWebPageBlock(Block):
             "cache": str(cache).lower(),
         }
 
-        response = api.get("https://api.screenshotone.com/take", params=params)
+        # Make the API request
+        # Use header-based authentication instead of query parameter
+        headers = {
+            "X-Access-Key": credentials.api_key.get_secret_value(),
+        }
+
+        response = await api.get(
+            "https://api.screenshotone.com/take", params=params, headers=headers
+        )
+        content = response.content
 
         return {
-            "image": store_media_file(
+            "image": await store_media_file(
                 graph_exec_id=graph_exec_id,
                 file=MediaFileType(
-                    f"data:image/{format.value};base64,{b64encode(response.content).decode('utf-8')}"
+                    f"data:image/{format.value};base64,{b64encode(content).decode('utf-8')}"
                 ),
                 return_content=True,
             )
         }
 
-    def run(
+    async def run(
         self,
         input_data: Input,
         *,
@@ -158,7 +166,7 @@ class ScreenshotWebPageBlock(Block):
         **kwargs,
     ) -> BlockOutput:
         try:
-            screenshot_data = self.take_screenshot(
+            screenshot_data = await self.take_screenshot(
                 credentials=credentials,
                 graph_exec_id=graph_exec_id,
                 url=input_data.url,

autogpt_platform/backend/backend/blocks/search.py

@@ -36,10 +36,10 @@ class GetWikipediaSummaryBlock(Block, GetRequest):
             test_mock={"get_request": lambda url, json: {"extract": "summary content"}},
         )
 
-    def run(self, input_data: Input, **kwargs) -> BlockOutput:
+    async def run(self, input_data: Input, **kwargs) -> BlockOutput:
         topic = input_data.topic
         url = f"https://en.wikipedia.org/api/rest_v1/page/summary/{topic}"
-        response = self.get_request(url, json=True)
+        response = await self.get_request(url, json=True)
         if "extract" not in response:
             raise RuntimeError(f"Unable to parse Wikipedia response: {response}")
         yield "summary", response["extract"]
@@ -113,14 +113,14 @@ class GetWeatherInformationBlock(Block, GetRequest):
             test_credentials=TEST_CREDENTIALS,
         )
 
-    def run(
+    async def run(
         self, input_data: Input, *, credentials: APIKeyCredentials, **kwargs
     ) -> BlockOutput:
         units = "metric" if input_data.use_celsius else "imperial"
         api_key = credentials.api_key
         location = input_data.location
         url = f"http://api.openweathermap.org/data/2.5/weather?q={quote(location)}&appid={api_key}&units={units}"
-        weather_data = self.get_request(url, json=True)
+        weather_data = await self.get_request(url, json=True)
 
         if "main" in weather_data and "weather" in weather_data:
             yield "temperature", str(weather_data["main"]["temp"])