refactor data manipulation blocks

The block library was missing two key capabilities that keep coming up
in real-world agent flows:

1. **Granular Mem0 filtering.** Agents often work side-by-side for the
same user, so memories must be scoped to a specific run or agent to
avoid crosstalk.
2. **First-class Google Sheets support.** Many community projects (e.g.,
data-collection, lightweight dashboards, no-code workflows) rely on
Sheets, but we only had a brittle REST call block.

This PR adds fine-grained filters to every Mem0 retrieval block and
introduces a complete, OAuth-ready Google Sheets suite so agents can
create, read, write, format, and manage spreadsheets safely.
:contentReference[oaicite:0]{index=0}

---

### Changes 🏗️
#### 📚 Mem0 block enhancements  
* Added `categories_filter`, `metadata_filter`, `limit_memory_to_run`,
and `limit_memory_to_agent` inputs to **SearchMemoryBlock**,
**GetAllMemoriesBlock**, and **GetLatestMemoryBlock**.
* Added identical scoping logic to **AddMemoryBlock** so newly-created
memories can be tied to run/agent IDs.

#### 📊 New Google Sheets blocks (`backend/blocks/google/sheets.py`)  
| Block | Purpose |
|-------|---------|
| `GoogleSheetsReadBlock` | Read a range |
| `GoogleSheetsWriteBlock` | Overwrite a range |
| `GoogleSheetsAppendBlock` | Append rows |
| `GoogleSheetsClearBlock` | Clear a range |
| `GoogleSheetsMetadataBlock` | Fetch spreadsheet + sheet info |
| `GoogleSheetsManageSheetBlock` | Create / delete / copy a sheet |
| `GoogleSheetsBatchOperationsBlock` | Batch update / clear |
| `GoogleSheetsFindReplaceBlock` | Find & replace text |
| `GoogleSheetsFormatBlock` | Cell formatting (bg/text colour, bold,
italic, font size) |
| `GoogleSheetsCreateSpreadsheetBlock` | Spin up a new spreadsheet |

* Each block has typed input/output schemas, built-in test mocks, and is
disabled in prod unless Google OAuth is configured.
* Added helper enums (`SheetOperation`, `BatchOperationType`) and
updated **CLAUDE.md** contributor guide with a UUID-generation step.
:contentReference[oaicite:2]{index=2}

---

### Checklist 📋

#### For code changes:
- [x] I have clearly listed my changes in the PR description
- [x] I have made a test plan
- [x] I have tested my changes according to the test plan:
  <!-- Put your test plan here: -->
- [x] Manual E2E run: agent writes chat summary to new spreadsheet,
reads it back, searches memory with run-scoped filter
- [x] Live Google API smoke-tests (read/write/append/clear/format) using
a disposable spreadsheet

.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-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:
@@ -50,6 +50,23 @@ jobs:
         env:
           RABBITMQ_DEFAULT_USER: ${{ env.RABBITMQ_DEFAULT_USER }}
           RABBITMQ_DEFAULT_PASS: ${{ env.RABBITMQ_DEFAULT_PASS }}
+      clamav:
+        image: clamav/clamav-debian:latest
+        ports:
+          - 3310:3310
+        env:
+          CLAMAV_NO_FRESHCLAMD: false
+          CLAMD_CONF_StreamMaxLength: 50M
+          CLAMD_CONF_MaxFileSize: 100M
+          CLAMD_CONF_MaxScanSize: 100M
+          CLAMD_CONF_MaxThreads: 4
+          CLAMD_CONF_ReadTimeout: 300
+        options: >-
+          --health-cmd "clamdscan --version || exit 1"
+          --health-interval 30s
+          --health-timeout 10s
+          --health-retries 5
+          --health-start-period 180s
 
     steps:
       - name: Checkout repository
@@ -81,12 +98,12 @@ jobs:
       - name: Install Poetry (Unix)
         run: |
           # Extract Poetry version from backend/poetry.lock
-          HEAD_POETRY_VERSION=$(head -n 1 poetry.lock | grep -oP '(?<=Poetry )[0-9]+\.[0-9]+\.[0-9]+')
+          HEAD_POETRY_VERSION=$(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) | head -n 1 | grep -oP '(?<=Poetry )[0-9]+\.[0-9]+\.[0-9]+')
+            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
@@ -131,6 +148,35 @@ jobs:
         # outputs:
         # DB_URL, API_URL, GRAPHQL_URL, ANON_KEY, SERVICE_ROLE_KEY, JWT_SECRET
 
+      - name: Wait for ClamAV to be ready
+        run: |
+          echo "Waiting for ClamAV daemon to start..."
+          max_attempts=60
+          attempt=0
+          
+          until nc -z localhost 3310 || [ $attempt -eq $max_attempts ]; do
+            echo "ClamAV is unavailable - sleeping (attempt $((attempt+1))/$max_attempts)"
+            sleep 5
+            attempt=$((attempt+1))
+          done
+          
+          if [ $attempt -eq $max_attempts ]; then
+            echo "ClamAV failed to start after $((max_attempts*5)) seconds"
+            echo "Checking ClamAV service logs..."
+            docker logs $(docker ps -q --filter "ancestor=clamav/clamav-debian:latest") 2>&1 | tail -50 || echo "No ClamAV container found"
+            exit 1
+          fi
+          
+          echo "ClamAV is ready!"
+          
+          # Verify ClamAV is responsive
+          echo "Testing ClamAV connection..."
+          timeout 10 bash -c 'echo "PING" | nc localhost 3310' || {
+            echo "ClamAV is not responding to PING"
+            docker logs $(docker ps -q --filter "ancestor=clamav/clamav-debian:latest") 2>&1 | tail -50 || echo "No ClamAV container found"
+            exit 1
+          }
+
       - name: Run Database Migrations
         run: poetry run prisma migrate dev --name updates
         env:
@@ -144,9 +190,9 @@ jobs:
       - name: Run pytest with coverage
         run: |
           if [[ "${{ runner.debug }}" == "1" ]]; then
-            poetry run pytest -s -vv -o log_cli=true -o log_cli_level=DEBUG test
+            poetry run pytest -s -vv -o log_cli=true -o log_cli_level=DEBUG
           else
-            poetry run pytest -s -vv test
+            poetry run pytest -s -vv
           fi
         if: success() || (failure() && steps.lint.outcome == 'failure')
         env:
@@ -159,6 +205,7 @@ jobs:
           REDIS_HOST: "localhost"
           REDIS_PORT: "6379"
           REDIS_PASSWORD: "testpassword"
+          ENCRYPTION_KEY: "dvziYgz0KSK8FENhju0ZYi8-fRTfAdlz6YLhdB_jhNw=" # DO NOT USE IN PRODUCTION!!
 
     env:
       CI: true

.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

@@ -18,49 +18,107 @@ defaults:
     working-directory: autogpt_platform/frontend
 
 jobs:
-  lint:
+  setup:
     runs-on: ubuntu-latest
-
+    outputs:
+      cache-key: ${{ steps.cache-key.outputs.key }}
+    
     steps:
-      - uses: actions/checkout@v4
+      - name: Checkout repository
+        uses: actions/checkout@v4
 
       - name: Set up Node.js
         uses: actions/setup-node@v4
         with:
           node-version: "21"
 
+      - name: Enable corepack
+        run: corepack enable
+
+      - name: Generate cache key
+        id: cache-key
+        run: echo "key=${{ runner.os }}-pnpm-${{ hashFiles('**/pnpm-lock.yaml') }}" >> $GITHUB_OUTPUT
+
+      - name: Cache dependencies
+        uses: actions/cache@v4
+        with:
+          path: ~/.pnpm-store
+          key: ${{ steps.cache-key.outputs.key }}
+          restore-keys: |
+            ${{ runner.os }}-pnpm-
+
       - name: Install dependencies
-        run: |
-          yarn install --frozen-lockfile
+        run: pnpm install --frozen-lockfile
+
+  lint:
+    runs-on: ubuntu-latest
+    needs: setup
+
+    steps:
+      - name: Checkout repository
+        uses: actions/checkout@v4
+
+      - name: Set up Node.js
+        uses: actions/setup-node@v4
+        with:
+          node-version: "21"
+
+      - name: Enable corepack
+        run: corepack enable
+
+      - name: Restore dependencies cache
+        uses: actions/cache@v4
+        with:
+          path: ~/.pnpm-store
+          key: ${{ needs.setup.outputs.cache-key }}
+          restore-keys: |
+            ${{ runner.os }}-pnpm-
+
+      - name: Install dependencies
+        run: pnpm install --frozen-lockfile
 
       - name: Run lint
-        run: |
-          yarn lint
+        run: pnpm lint
 
   type-check:
     runs-on: ubuntu-latest
+    needs: setup
 
     steps:
-      - uses: actions/checkout@v4
+      - name: Checkout repository
+        uses: actions/checkout@v4
 
       - name: Set up Node.js
         uses: actions/setup-node@v4
         with:
           node-version: "21"
 
+      - name: Enable corepack
+        run: corepack enable
+
+      - name: Restore dependencies cache
+        uses: actions/cache@v4
+        with:
+          path: ~/.pnpm-store
+          key: ${{ needs.setup.outputs.cache-key }}
+          restore-keys: |
+            ${{ runner.os }}-pnpm-
+
       - 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
 
-  design:
+  chromatic:
     runs-on: ubuntu-latest
-
+    needs: setup
+    # Only run on dev branch pushes or PRs targeting dev
+    if: github.ref == 'refs/heads/dev' || github.base_ref == 'dev'
+    
     steps:
-      - uses: actions/checkout@v4
+      - name: Checkout repository
+        uses: actions/checkout@v4
         with:
           fetch-depth: 0
 
@@ -69,19 +127,31 @@ jobs:
         with:
           node-version: "21"
 
+      - name: Enable corepack
+        run: corepack enable
+
+      - name: Restore dependencies cache
+        uses: actions/cache@v4
+        with:
+          path: ~/.pnpm-store
+          key: ${{ needs.setup.outputs.cache-key }}
+          restore-keys: |
+            ${{ runner.os }}-pnpm-
+
       - name: Install dependencies
-        run: |
-          yarn install --frozen-lockfile
+        run: pnpm install --frozen-lockfile
 
       - name: Run Chromatic
         uses: chromaui/action@latest
         with:
-          # ⚠️ Make sure to configure a `CHROMATIC_PROJECT_TOKEN` repository secret
-          projectToken: ${{ secrets.CHROMATIC_PROJECT_TOKEN }}
+          projectToken: chpt_9e7c1a76478c9c8
+          onlyChanged: true
           workingDir: autogpt_platform/frontend
+          token: ${{ secrets.GITHUB_TOKEN }}
 
   test:
     runs-on: ubuntu-latest
+    needs: setup
     strategy:
       fail-fast: false
       matrix:
@@ -98,6 +168,9 @@ jobs:
         with:
           node-version: "21"
 
+      - name: Enable corepack
+        run: corepack enable
+
       - name: Free Disk Space (Ubuntu)
         uses: jlumbroso/free-disk-space@main
         with:
@@ -116,26 +189,33 @@ jobs:
         run: |
           docker compose -f ../docker-compose.yml up -d
 
-      - name: Install dependencies
-        run: |
-          yarn install --frozen-lockfile
+      - name: Restore dependencies cache
+        uses: actions/cache@v4
+        with:
+          path: ~/.pnpm-store
+          key: ${{ needs.setup.outputs.cache-key }}
+          restore-keys: |
+            ${{ runner.os }}-pnpm-
 
-      - name: Setup Builder .env
-        run: |
-          cp .env.example .env
+      - name: Install dependencies
+        run: pnpm install --frozen-lockfile
+
+      - 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

@@ -165,7 +165,7 @@ package-lock.json
 
 # Allow for locally private items
 # private
-pri* 
+pri*
 # ignore
 ig*
 .github_access_token
@@ -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

README.md

@@ -15,8 +15,35 @@
 > 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.
 
+### 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.
+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/)
 
@@ -152,7 +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 +1,147 @@
+# 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, clamav)
+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
+# prefer format if you want to just "fix" it and only get the errors that can't be autofixed
+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
+- **Security**: Cache protection middleware prevents sensitive data caching in browsers/proxies
+
+### 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
+5. **Virus Scanning**: ClamAV integration for file upload security
+
+### 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
+6. Generate the block uuid using `uuid.uuid4()`
+
+**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
+
+### Security Implementation
+
+**Cache Protection Middleware:**
+- Located in `/backend/backend/server/middleware/security.py`
+- Default behavior: Disables caching for ALL endpoints with `Cache-Control: no-store, no-cache, must-revalidate, private`
+- Uses an allow list approach - only explicitly permitted paths can be cached
+- Cacheable paths include: static assets (`/static/*`, `/_next/static/*`), health checks, public store pages, documentation
+- Prevents sensitive data (auth tokens, API keys, user data) from being cached by browsers/proxies
+- To allow caching for a new endpoint, add it to `CACHEABLE_PATHS` in the middleware
+- Applied to both main API server and external API applications

autogpt_platform/README.md

@@ -15,44 +15,63 @@ 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:
+
+   Generate the API client (this step is required before running the frontend):
+
    ```
-   yarn install && yarn dev
+   pnpm generate:api-client
+   ```
+
+   Then start the frontend application in development mode:
+
+   ```
+   pnpm dev
    ```
 
 7. Open your browser and navigate to `http://localhost:3000` to access the AutoGPT Platform frontend.
@@ -68,43 +87,52 @@ 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 +143,6 @@ 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:
@@ -143,3 +170,27 @@ To persist data for PostgreSQL and Redis, you can modify the `docker-compose.yml
 3. Save the file and run `docker compose up -d` to apply the changes.
 
 This configuration will create named volumes for PostgreSQL and Redis, ensuring that your data persists across container restarts.
+
+### API Client Generation
+
+The platform includes scripts for generating and managing the API client:
+
+- `pnpm fetch:openapi`: Fetches the OpenAPI specification from the backend service (requires backend to be running on port 8006)
+- `pnpm generate:api-client`: Generates the TypeScript API client from the OpenAPI specification using Orval
+- `pnpm generate:api-all`: Runs both fetch and generate commands in sequence
+
+#### Manual API Client Updates
+
+If you need to update the API client after making changes to the backend API:
+
+1. Ensure the backend services are running:
+   ```
+   docker compose up -d
+   ```
+
+2. Generate the updated API client:
+   ```
+   pnpm generate:api-all
+   ```
+
+This will fetch the latest OpenAPI specification and regenerate the TypeScript client code.

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/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"},
+    {file = "pydantic-2.11.4-py3-none-any.whl", hash = "sha256:d9615eaa9ac5a063471da949c8fc16376a84afb5024688b3ff885693506764eb"},
+    {file = "pydantic-2.11.4.tar.gz", hash = "sha256:32738d19d63a226a52eed76645a98ee07c1f410ee41d93b4afbfa85ed8111c2d"},
 ]
 
 [package.dependencies]
 annotated-types = ">=0.6.0"
-pydantic-core = "2.33.0"
+pydantic-core = "2.33.2"
 typing-extensions = ">=4.12.2"
 typing-inspection = ">=0.4.0"
 
@@ -1260,111 +1337,111 @@ timezone = ["tzdata ; python_version >= \"3.9\" and platform_system == \"Windows
 
 [[package]]
 name = "pydantic-core"
-version = "2.33.0"
+version = "2.33.2"
 description = "Core functionality for Pydantic validation and serialization"
 optional = false
 python-versions = ">=3.9"
 groups = ["main"]
 files = [
-    {file = "pydantic_core-2.33.0-cp310-cp310-macosx_10_12_x86_64.whl", hash = "sha256:71dffba8fe9ddff628c68f3abd845e91b028361d43c5f8e7b3f8b91d7d85413e"},
-    {file = "pydantic_core-2.33.0-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:abaeec1be6ed535a5d7ffc2e6c390083c425832b20efd621562fbb5bff6dc518"},
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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 = [
+    {file = "pyRFC3339-2.0.1-py3-none-any.whl", hash = "sha256:30b70a366acac3df7386b558c21af871522560ed7f3f73cf344b8c2cbb8b0c9d"},
+    {file = "pyrfc3339-2.0.1.tar.gz", hash = "sha256:e47843379ea35c1296c3b6c67a948a1a490ae0584edfcbdea0eaffb5dd29960b"},
+]
+
 [[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-py3-none-musllinux_1_2_x86_64.whl", hash = "sha256:3afead355f1d16d95630df28d4ba17fb2cb9c8dfac8d21ced14984121f639bad"},
+    {file = "ruff-0.11.10-py3-none-win32.whl", hash = "sha256:dc061a98d32a97211af7e7f3fa1d4ca2fcf919fb96c28f39551f35fc55bdbc19"},
+    {file = "ruff-0.11.10-py3-none-win_amd64.whl", hash = "sha256:5cc725fbb4d25b0f185cb42df07ab6b76c4489b4bfb740a175f3a59c70e8a224"},
+    {file = "ruff-0.11.10-py3-none-win_arm64.whl", hash = "sha256:ef69637b35fb8b210743926778d0e45e1bffa850a7c61e428c6b971549b5f5d1"},
+    {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 = [
-    {file = "supabase-2.15.0-py3-none-any.whl", hash = "sha256:a665c7ab6c8ad1d80609ab62ad657f66fdaf38070ec9e0db5c7887fd72b109c0"},
-    {file = "supabase-2.15.0.tar.gz", hash = "sha256:2e66289ad74ae9c4cb04a69f9de00cd2ce880cd890de23269a40ac5b69151d26"},
+    {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

@@ -13,7 +13,6 @@ PRISMA_SCHEMA="postgres/schema.prisma"
 
 # EXECUTOR
 NUM_GRAPH_WORKERS=10
-NUM_NODE_WORKERS=3
 
 BACKEND_CORS_ALLOW_ORIGINS=["http://localhost:3000"]
 
@@ -66,6 +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.
@@ -120,8 +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/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
@@ -10,22 +11,16 @@ 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, ".")
         for f in current_dir.rglob("*.py")
-        if f.is_file() and f.name != "__init__.py"
+        if f.is_file() and f.name != "__init__.py" and not f.name.startswith("test_")
     ]
     for module in modules:
         if not re.match("^[a-z0-9_.]+$", module):
@@ -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

@@ -1,5 +1,8 @@
+import asyncio
 import logging
-from typing import Any
+from typing import Any, Optional
+
+from pydantic import JsonValue
 
 from backend.data.block import (
     Block,
@@ -12,9 +15,9 @@ from backend.data.block import (
 )
 from backend.data.execution import ExecutionStatus
 from backend.data.model import SchemaField
-from backend.util import json
+from backend.util import json, retry
 
-logger = logging.getLogger(__name__)
+_logger = logging.getLogger(__name__)
 
 
 class AgentExecutorBlock(Block):
@@ -23,17 +26,21 @@ class AgentExecutorBlock(Block):
         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")
 
+        nodes_input_masks: Optional[dict[str, dict[str, JsonValue]]] = 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]:
@@ -57,36 +64,94 @@ 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:
+
         from backend.executor import utils as execution_utils
 
-        event_bus = execution_utils.get_execution_event_bus()
-
-        graph_exec = execution_utils.add_graph_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,
-            inputs=input_data.data,
+            inputs=input_data.inputs,
+            nodes_input_masks=input_data.nodes_input_masks,
+            use_db_query=False,
         )
-        log_id = f"Graph #{input_data.graph_id}-V{input_data.graph_version}, exec-id: {graph_exec.id}"
+
+        logger = execution_utils.LogMetadata(
+            logger=_logger,
+            user_id=input_data.user_id,
+            graph_eid=graph_exec.id,
+            graph_id=input_data.graph_id,
+            node_eid="*",
+            node_id="*",
+            block_name=self.name,
+        )
+
+        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,
+                logger=logger,
+            ):
+                yield name, data
+        except asyncio.CancelledError:
+            await self._stop(
+                graph_exec_id=graph_exec.id,
+                user_id=input_data.user_id,
+                logger=logger,
+            )
+            logger.warning(
+                f"Execution of graph {input_data.graph_id}v{input_data.graph_version} was cancelled."
+            )
+        except Exception as e:
+            await self._stop(
+                graph_exec_id=graph_exec.id,
+                user_id=input_data.user_id,
+                logger=logger,
+            )
+            logger.error(
+                f"Execution of graph {input_data.graph_id}v{input_data.graph_version} failed: {e}, execution is stopped."
+            )
+            raise
+
+    async def _run(
+        self,
+        graph_id: str,
+        graph_version: int,
+        graph_exec_id: str,
+        user_id: str,
+        logger,
+    ) -> 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.id,
+        async for event in event_bus.listen(
+            user_id=user_id,
+            graph_id=graph_id,
+            graph_exec_id=graph_exec_id,
         ):
+            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
+
             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 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}"
@@ -110,3 +175,25 @@ class AgentExecutorBlock(Block):
                     f"Execution {log_id} produced {output_name}: {output_data}"
                 )
                 yield output_name, output_data
+
+    @retry.func_retry
+    async def _stop(
+        self,
+        graph_exec_id: str,
+        user_id: str,
+        logger,
+    ) -> None:
+        from backend.executor import utils as execution_utils
+
+        log_id = f"Graph exec-id: {graph_exec_id}"
+        logger.info(f"Stopping execution of {log_id}")
+
+        try:
+            await execution_utils.stop_graph_execution(
+                graph_exec_id=graph_exec_id,
+                user_id=user_id,
+                use_db_query=False,
+            )
+            logger.info(f"Execution {log_id} stopped successfully.")
+        except Exception as e:
+            logger.error(f"Failed to stop execution {log_id}: {e}")

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",
@@ -52,6 +53,7 @@ class AudioTrack(str, Enum):
     REFRESHER = ("Refresher",)
     TOURIST = ("Tourist",)
     TWIN_TYCHES = ("Twin Tyches",)
+    DONT_STOP_ME_ABSTRACT_FUTURE_BASS = ("Dont Stop Me Abstract Future Bass",)
 
     @property
     def audio_url(self):
@@ -77,6 +79,7 @@ class AudioTrack(str, Enum):
             AudioTrack.REFRESHER: "https://cdn.tfrv.xyz/audio/refresher.mp3",
             AudioTrack.TOURIST: "https://cdn.tfrv.xyz/audio/tourist.mp3",
             AudioTrack.TWIN_TYCHES: "https://cdn.tfrv.xyz/audio/twin-tynches.mp3",
+            AudioTrack.DONT_STOP_ME_ABSTRACT_FUTURE_BASS: "https://cdn.revid.ai/audio/_dont-stop-me-abstract-future-bass.mp3",
         }
         return audio_urls[self]
 
@@ -104,6 +107,7 @@ class GenerationPreset(str, Enum):
     MOVIE = ("Movie",)
     STYLIZED_ILLUSTRATION = ("Stylized Illustration",)
     MANGA = ("Manga",)
+    DEFAULT = ("DEFAULT",)
 
 
 class Voice(str, Enum):
@@ -113,6 +117,7 @@ class Voice(str, Enum):
     JESSICA = "Jessica"
     CHARLOTTE = "Charlotte"
     CALLUM = "Callum"
+    EVA = "Eva"
 
     @property
     def voice_id(self):
@@ -123,6 +128,7 @@ class Voice(str, Enum):
             Voice.JESSICA: "cgSgspJ2msm6clMCkdW9",
             Voice.CHARLOTTE: "XB0fDUnXU5powFXDhCwa",
             Voice.CALLUM: "N2lVS1w4EtoT3dr4eOWO",
+            Voice.EVA: "FGY2WhTYpPnrIDTdsKH5",
         }
         return voice_id_map[self]
 
@@ -140,6 +146,8 @@ logger = logging.getLogger(__name__)
 
 
 class AIShortformVideoCreatorBlock(Block):
+    """Creates a short‑form text‑to‑video clip using stock or AI imagery."""
+
     class Input(BlockSchema):
         credentials: CredentialsMetaInput[
             Literal[ProviderName.REVID], Literal["api_key"]
@@ -183,6 +191,58 @@ class AIShortformVideoCreatorBlock(Block):
         video_url: str = SchemaField(description="The URL of the created video")
         error: str = SchemaField(description="Error message if the request failed")
 
+    async def create_webhook(self) -> tuple[str, str]:
+        """Create a new webhook URL for receiving notifications."""
+        url = "https://webhook.site/token"
+        headers = {"Accept": "application/json", "Content-Type": "application/json"}
+        response = await Requests().post(url, headers=headers)
+        webhook_data = response.json()
+        return webhook_data["uuid"], f"https://webhook.site/{webhook_data['uuid']}"
+
+    async def create_video(self, api_key: SecretStr, payload: dict) -> dict:
+        """Create a video using the Revid API."""
+        url = "https://www.revid.ai/api/public/v2/render"
+        headers = {"key": api_key.get_secret_value()}
+        response = await Requests().post(url, json=payload, headers=headers)
+        logger.debug(
+            f"API Response Status Code: {response.status}, Content: {response.text}"
+        )
+        return response.json()
+
+    async def check_video_status(self, api_key: SecretStr, pid: str) -> dict:
+        """Check the status of a video creation job."""
+        url = f"https://www.revid.ai/api/public/v2/status?pid={pid}"
+        headers = {"key": api_key.get_secret_value()}
+        response = await Requests().get(url, headers=headers)
+        return response.json()
+
+    async def wait_for_video(
+        self,
+        api_key: SecretStr,
+        pid: str,
+        max_wait_time: int = 1000,
+    ) -> str:
+        """Wait for video creation to complete and return the video URL."""
+        start_time = time.time()
+        while time.time() - start_time < max_wait_time:
+            status = await self.check_video_status(api_key, pid)
+            logger.debug(f"Video status: {status}")
+
+            if status.get("status") == "ready" and "videoUrl" in status:
+                return status["videoUrl"]
+            elif status.get("status") == "error":
+                error_message = status.get("error", "Unknown error occurred")
+                logger.error(f"Video creation failed: {error_message}")
+                raise ValueError(f"Video creation failed: {error_message}")
+            elif status.get("status") in ["FAILED", "CANCELED"]:
+                logger.error(f"Video creation failed: {status.get('message')}")
+                raise ValueError(f"Video creation failed: {status.get('message')}")
+
+            await asyncio.sleep(10)
+
+        logger.error("Video creation timed out")
+        raise TimeoutError("Video creation timed out")
+
     def __init__(self):
         super().__init__(
             id="361697fb-0c4f-4feb-aed3-8320c88c771b",
@@ -201,91 +261,41 @@ class AIShortformVideoCreatorBlock(Block):
                 "voice": Voice.LILY,
                 "video_style": VisualMediaType.STOCK_VIDEOS,
             },
-            test_output=(
-                "video_url",
-                "https://example.com/video.mp4",
-            ),
+            test_output=("video_url", "https://example.com/video.mp4"),
             test_mock={
-                "create_webhook": lambda: (
+                "create_webhook": lambda *args, **kwargs: (
                     "test_uuid",
                     "https://webhook.site/test_uuid",
                 ),
-                "create_video": lambda api_key, payload: {"pid": "test_pid"},
-                "wait_for_video": lambda api_key, pid, webhook_token, max_wait_time=1000: "https://example.com/video.mp4",
+                "create_video": lambda *args, **kwargs: {"pid": "test_pid"},
+                "check_video_status": lambda *args, **kwargs: {
+                    "status": "ready",
+                    "videoUrl": "https://example.com/video.mp4",
+                },
+                "wait_for_video": lambda *args, **kwargs: "https://example.com/video.mp4",
             },
             test_credentials=TEST_CREDENTIALS,
         )
 
-    def create_webhook(self):
-        url = "https://webhook.site/token"
-        headers = {"Accept": "application/json", "Content-Type": "application/json"}
-        response = 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:
-        url = "https://www.revid.ai/api/public/v2/render"
-        headers = {"key": api_key.get_secret_value()}
-        response = requests.post(url, json=payload, headers=headers)
-        logger.debug(
-            f"API Response Status Code: {response.status_code}, Content: {response.text}"
-        )
-        return response.json()
-
-    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)
-        return response.json()
-
-    def wait_for_video(
-        self,
-        api_key: SecretStr,
-        pid: str,
-        webhook_token: str,
-        max_wait_time: int = 1000,
-    ) -> str:
-        start_time = time.time()
-        while time.time() - start_time < max_wait_time:
-            status = self.check_video_status(api_key, pid)
-            logger.debug(f"Video status: {status}")
-
-            if status.get("status") == "ready" and "videoUrl" in status:
-                return status["videoUrl"]
-            elif status.get("status") == "error":
-                error_message = status.get("error", "Unknown error occurred")
-                logger.error(f"Video creation failed: {error_message}")
-                raise ValueError(f"Video creation failed: {error_message}")
-            elif status.get("status") in ["FAILED", "CANCELED"]:
-                logger.error(f"Video creation failed: {status.get('message')}")
-                raise ValueError(f"Video creation failed: {status.get('message')}")
-
-            time.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
-
         payload = {
             "frameRate": input_data.frame_rate,
             "resolution": input_data.resolution,
             "frameDurationMultiplier": 18,
-            "webhook": webhook_url,
+            "webhook": None,
             "creationParams": {
                 "mediaType": input_data.video_style,
                 "captionPresetName": "Wrap 1",
                 "selectedVoice": input_data.voice.voice_id,
                 "hasEnhancedGeneration": True,
                 "generationPreset": input_data.generation_preset.name,
-                "selectedAudio": input_data.background_music,
+                "selectedAudio": input_data.background_music.value,
                 "origin": "/create",
                 "inputText": input_data.script,
                 "flowType": "text-to-video",
@@ -301,12 +311,12 @@ class AIShortformVideoCreatorBlock(Block):
                 "selectedStoryStyle": {"value": "custom", "label": "Custom"},
                 "hasToGenerateVideos": input_data.video_style
                 != VisualMediaType.STOCK_VIDEOS,
-                "audioUrl": audio_url,
+                "audioUrl": input_data.background_music.audio_url,
             },
         }
 
         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 +328,370 @@ 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)
             logger.debug(f"Video ready: {video_url}")
             yield "video_url", video_url
+
+
+class AIAdMakerVideoCreatorBlock(Block):
+    """Generates a 30‑second vertical AI advert using optional user‑supplied imagery."""
+
+    class Input(BlockSchema):
+        credentials: CredentialsMetaInput[
+            Literal[ProviderName.REVID], Literal["api_key"]
+        ] = CredentialsField(
+            description="Credentials for Revid.ai API access.",
+        )
+        script: str = SchemaField(
+            description="Short advertising copy. Line breaks create new scenes.",
+            placeholder="Introducing Foobar – [show product photo] the gadget that does it all.",
+        )
+        ratio: str = SchemaField(description="Aspect ratio", default="9 / 16")
+        target_duration: int = SchemaField(
+            description="Desired length of the ad in seconds.", default=30
+        )
+        voice: Voice = SchemaField(
+            description="Narration voice", default=Voice.EVA, placeholder=Voice.EVA
+        )
+        background_music: AudioTrack = SchemaField(
+            description="Background track",
+            default=AudioTrack.DONT_STOP_ME_ABSTRACT_FUTURE_BASS,
+        )
+        input_media_urls: list[str] = SchemaField(
+            description="List of image URLs to feature in the advert.", default=[]
+        )
+        use_only_provided_media: bool = SchemaField(
+            description="Restrict visuals to supplied images only.", default=True
+        )
+
+    class Output(BlockSchema):
+        video_url: str = SchemaField(description="URL of the finished advert")
+        error: str = SchemaField(description="Error message on failure")
+
+    async def create_webhook(self) -> tuple[str, str]:
+        """Create a new webhook URL for receiving notifications."""
+        url = "https://webhook.site/token"
+        headers = {"Accept": "application/json", "Content-Type": "application/json"}
+        response = await Requests().post(url, headers=headers)
+        webhook_data = response.json()
+        return webhook_data["uuid"], f"https://webhook.site/{webhook_data['uuid']}"
+
+    async def create_video(self, api_key: SecretStr, payload: dict) -> dict:
+        """Create a video using the Revid API."""
+        url = "https://www.revid.ai/api/public/v2/render"
+        headers = {"key": api_key.get_secret_value()}
+        response = await Requests().post(url, json=payload, headers=headers)
+        logger.debug(
+            f"API Response Status Code: {response.status}, Content: {response.text}"
+        )
+        return response.json()
+
+    async def check_video_status(self, api_key: SecretStr, pid: str) -> dict:
+        """Check the status of a video creation job."""
+        url = f"https://www.revid.ai/api/public/v2/status?pid={pid}"
+        headers = {"key": api_key.get_secret_value()}
+        response = await Requests().get(url, headers=headers)
+        return response.json()
+
+    async def wait_for_video(
+        self,
+        api_key: SecretStr,
+        pid: str,
+        max_wait_time: int = 1000,
+    ) -> str:
+        """Wait for video creation to complete and return the video URL."""
+        start_time = time.time()
+        while time.time() - start_time < max_wait_time:
+            status = await self.check_video_status(api_key, pid)
+            logger.debug(f"Video status: {status}")
+
+            if status.get("status") == "ready" and "videoUrl" in status:
+                return status["videoUrl"]
+            elif status.get("status") == "error":
+                error_message = status.get("error", "Unknown error occurred")
+                logger.error(f"Video creation failed: {error_message}")
+                raise ValueError(f"Video creation failed: {error_message}")
+            elif status.get("status") in ["FAILED", "CANCELED"]:
+                logger.error(f"Video creation failed: {status.get('message')}")
+                raise ValueError(f"Video creation failed: {status.get('message')}")
+
+            await asyncio.sleep(10)
+
+        logger.error("Video creation timed out")
+        raise TimeoutError("Video creation timed out")
+
+    def __init__(self):
+        super().__init__(
+            id="58bd2a19-115d-4fd1-8ca4-13b9e37fa6a0",
+            description="Creates an AI‑generated 30‑second advert (text + images)",
+            categories={BlockCategory.MARKETING, BlockCategory.AI},
+            input_schema=AIAdMakerVideoCreatorBlock.Input,
+            output_schema=AIAdMakerVideoCreatorBlock.Output,
+            test_input={
+                "credentials": TEST_CREDENTIALS_INPUT,
+                "script": "Test product launch!",
+                "input_media_urls": [
+                    "https://cdn.revid.ai/uploads/1747076315114-image.png",
+                ],
+            },
+            test_output=("video_url", "https://example.com/ad.mp4"),
+            test_mock={
+                "create_webhook": lambda *args, **kwargs: (
+                    "test_uuid",
+                    "https://webhook.site/test_uuid",
+                ),
+                "create_video": lambda *args, **kwargs: {"pid": "test_pid"},
+                "check_video_status": lambda *args, **kwargs: {
+                    "status": "ready",
+                    "videoUrl": "https://example.com/ad.mp4",
+                },
+                "wait_for_video": lambda *args, **kwargs: "https://example.com/ad.mp4",
+            },
+            test_credentials=TEST_CREDENTIALS,
+        )
+
+    async def run(self, input_data: Input, *, credentials: APIKeyCredentials, **kwargs):
+        webhook_token, webhook_url = await self.create_webhook()
+
+        payload = {
+            "webhook": webhook_url,
+            "creationParams": {
+                "targetDuration": input_data.target_duration,
+                "ratio": input_data.ratio,
+                "mediaType": "aiVideo",
+                "inputText": input_data.script,
+                "flowType": "text-to-video",
+                "slug": "ai-ad-generator",
+                "slugNew": "",
+                "isCopiedFrom": False,
+                "hasToGenerateVoice": True,
+                "hasToTranscript": False,
+                "hasToSearchMedia": True,
+                "hasAvatar": False,
+                "hasWebsiteRecorder": False,
+                "hasTextSmallAtBottom": False,
+                "selectedAudio": input_data.background_music.value,
+                "selectedVoice": input_data.voice.voice_id,
+                "selectedAvatar": "https://cdn.revid.ai/avatars/young-woman.mp4",
+                "selectedAvatarType": "video/mp4",
+                "websiteToRecord": "",
+                "hasToGenerateCover": True,
+                "nbGenerations": 1,
+                "disableCaptions": False,
+                "mediaMultiplier": "medium",
+                "characters": [],
+                "captionPresetName": "Revid",
+                "sourceType": "contentScraping",
+                "selectedStoryStyle": {"value": "custom", "label": "General"},
+                "generationPreset": "DEFAULT",
+                "hasToGenerateMusic": False,
+                "isOptimizedForChinese": False,
+                "generationUserPrompt": "",
+                "enableNsfwFilter": False,
+                "addStickers": False,
+                "typeMovingImageAnim": "dynamic",
+                "hasToGenerateSoundEffects": False,
+                "forceModelType": "gpt-image-1",
+                "selectedCharacters": [],
+                "lang": "",
+                "voiceSpeed": 1,
+                "disableAudio": False,
+                "disableVoice": False,
+                "useOnlyProvidedMedia": input_data.use_only_provided_media,
+                "imageGenerationModel": "ultra",
+                "videoGenerationModel": "pro",
+                "hasEnhancedGeneration": True,
+                "hasEnhancedGenerationPro": True,
+                "inputMedias": [
+                    {"url": url, "title": "", "type": "image"}
+                    for url in input_data.input_media_urls
+                ],
+                "hasToGenerateVideos": True,
+                "audioUrl": input_data.background_music.audio_url,
+                "watermark": None,
+            },
+        }
+
+        response = await self.create_video(credentials.api_key, payload)
+        pid = response.get("pid")
+        if not pid:
+            raise RuntimeError("Failed to create video: No project ID returned")
+
+        video_url = await self.wait_for_video(credentials.api_key, pid)
+        yield "video_url", video_url
+
+
+class AIScreenshotToVideoAdBlock(Block):
+    """Creates an advert where the supplied screenshot is narrated by an AI avatar."""
+
+    class Input(BlockSchema):
+        credentials: CredentialsMetaInput[
+            Literal[ProviderName.REVID], Literal["api_key"]
+        ] = CredentialsField(description="Revid.ai API key")
+        script: str = SchemaField(
+            description="Narration that will accompany the screenshot.",
+            placeholder="Check out these amazing stats!",
+        )
+        screenshot_url: str = SchemaField(
+            description="Screenshot or image URL to showcase."
+        )
+        ratio: str = SchemaField(default="9 / 16")
+        target_duration: int = SchemaField(default=30)
+        voice: Voice = SchemaField(default=Voice.EVA)
+        background_music: AudioTrack = SchemaField(
+            default=AudioTrack.DONT_STOP_ME_ABSTRACT_FUTURE_BASS
+        )
+
+    class Output(BlockSchema):
+        video_url: str = SchemaField(description="Rendered video URL")
+        error: str = SchemaField(description="Error, if encountered")
+
+    async def create_webhook(self) -> tuple[str, str]:
+        """Create a new webhook URL for receiving notifications."""
+        url = "https://webhook.site/token"
+        headers = {"Accept": "application/json", "Content-Type": "application/json"}
+        response = await Requests().post(url, headers=headers)
+        webhook_data = response.json()
+        return webhook_data["uuid"], f"https://webhook.site/{webhook_data['uuid']}"
+
+    async def create_video(self, api_key: SecretStr, payload: dict) -> dict:
+        """Create a video using the Revid API."""
+        url = "https://www.revid.ai/api/public/v2/render"
+        headers = {"key": api_key.get_secret_value()}
+        response = await Requests().post(url, json=payload, headers=headers)
+        logger.debug(
+            f"API Response Status Code: {response.status}, Content: {response.text}"
+        )
+        return response.json()
+
+    async def check_video_status(self, api_key: SecretStr, pid: str) -> dict:
+        """Check the status of a video creation job."""
+        url = f"https://www.revid.ai/api/public/v2/status?pid={pid}"
+        headers = {"key": api_key.get_secret_value()}
+        response = await Requests().get(url, headers=headers)
+        return response.json()
+
+    async def wait_for_video(
+        self,
+        api_key: SecretStr,
+        pid: str,
+        max_wait_time: int = 1000,
+    ) -> str:
+        """Wait for video creation to complete and return the video URL."""
+        start_time = time.time()
+        while time.time() - start_time < max_wait_time:
+            status = await self.check_video_status(api_key, pid)
+            logger.debug(f"Video status: {status}")
+
+            if status.get("status") == "ready" and "videoUrl" in status:
+                return status["videoUrl"]
+            elif status.get("status") == "error":
+                error_message = status.get("error", "Unknown error occurred")
+                logger.error(f"Video creation failed: {error_message}")
+                raise ValueError(f"Video creation failed: {error_message}")
+            elif status.get("status") in ["FAILED", "CANCELED"]:
+                logger.error(f"Video creation failed: {status.get('message')}")
+                raise ValueError(f"Video creation failed: {status.get('message')}")
+
+            await asyncio.sleep(10)
+
+        logger.error("Video creation timed out")
+        raise TimeoutError("Video creation timed out")
+
+    def __init__(self):
+        super().__init__(
+            id="0f3e4635-e810-43d9-9e81-49e6f4e83b7c",
+            description="Turns a screenshot into an engaging, avatar‑narrated video advert.",
+            categories={BlockCategory.AI, BlockCategory.MARKETING},
+            input_schema=AIScreenshotToVideoAdBlock.Input,
+            output_schema=AIScreenshotToVideoAdBlock.Output,
+            test_input={
+                "credentials": TEST_CREDENTIALS_INPUT,
+                "script": "Amazing numbers!",
+                "screenshot_url": "https://cdn.revid.ai/uploads/1747080376028-image.png",
+            },
+            test_output=("video_url", "https://example.com/screenshot.mp4"),
+            test_mock={
+                "create_webhook": lambda *args, **kwargs: (
+                    "test_uuid",
+                    "https://webhook.site/test_uuid",
+                ),
+                "create_video": lambda *args, **kwargs: {"pid": "test_pid"},
+                "check_video_status": lambda *args, **kwargs: {
+                    "status": "ready",
+                    "videoUrl": "https://example.com/screenshot.mp4",
+                },
+                "wait_for_video": lambda *args, **kwargs: "https://example.com/screenshot.mp4",
+            },
+            test_credentials=TEST_CREDENTIALS,
+        )
+
+    async def run(self, input_data: Input, *, credentials: APIKeyCredentials, **kwargs):
+        webhook_token, webhook_url = await self.create_webhook()
+
+        payload = {
+            "webhook": webhook_url,
+            "creationParams": {
+                "targetDuration": input_data.target_duration,
+                "ratio": input_data.ratio,
+                "mediaType": "aiVideo",
+                "hasAvatar": True,
+                "removeAvatarBackground": True,
+                "inputText": input_data.script,
+                "flowType": "text-to-video",
+                "slug": "ai-ad-generator",
+                "slugNew": "screenshot-to-video-ad",
+                "isCopiedFrom": "ai-ad-generator",
+                "hasToGenerateVoice": True,
+                "hasToTranscript": False,
+                "hasToSearchMedia": True,
+                "hasWebsiteRecorder": False,
+                "hasTextSmallAtBottom": False,
+                "selectedAudio": input_data.background_music.value,
+                "selectedVoice": input_data.voice.voice_id,
+                "selectedAvatar": "https://cdn.revid.ai/avatars/young-woman.mp4",
+                "selectedAvatarType": "video/mp4",
+                "websiteToRecord": "",
+                "hasToGenerateCover": True,
+                "nbGenerations": 1,
+                "disableCaptions": False,
+                "mediaMultiplier": "medium",
+                "characters": [],
+                "captionPresetName": "Revid",
+                "sourceType": "contentScraping",
+                "selectedStoryStyle": {"value": "custom", "label": "General"},
+                "generationPreset": "DEFAULT",
+                "hasToGenerateMusic": False,
+                "isOptimizedForChinese": False,
+                "generationUserPrompt": "",
+                "enableNsfwFilter": False,
+                "addStickers": False,
+                "typeMovingImageAnim": "dynamic",
+                "hasToGenerateSoundEffects": False,
+                "forceModelType": "gpt-image-1",
+                "selectedCharacters": [],
+                "lang": "",
+                "voiceSpeed": 1,
+                "disableAudio": False,
+                "disableVoice": False,
+                "useOnlyProvidedMedia": True,
+                "imageGenerationModel": "ultra",
+                "videoGenerationModel": "ultra",
+                "hasEnhancedGeneration": True,
+                "hasEnhancedGenerationPro": True,
+                "inputMedias": [
+                    {"url": input_data.screenshot_url, "title": "", "type": "image"}
+                ],
+                "hasToGenerateVideos": True,
+                "audioUrl": input_data.background_music.audio_url,
+                "watermark": None,
+            },
+        }
+
+        response = await self.create_video(credentials.api_key, payload)
+        pid = response.get("pid")
+        if not pid:
+            raise RuntimeError("Failed to create video: No project ID returned")
+
+        video_url = await self.wait_for_video(credentials.api_key, pid)
+        yield "video_url", video_url

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

@@ -4,6 +4,7 @@ from typing import List
 from backend.blocks.apollo._auth import ApolloCredentials
 from backend.blocks.apollo.models import (
     Contact,
+    EnrichPersonRequest,
     Organization,
     SearchOrganizationsRequest,
     SearchOrganizationsResponse,
@@ -27,14 +28,15 @@ 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.post(
             f"{self.API_URL}/mixed_people/search",
             headers=self._get_headers(),
-            params=query.model_dump(exclude={"credentials", "max_results"}),
+            json=query.model_dump(exclude={"max_results"}),
         )
-        parsed_response = SearchPeopleResponse(**response.json())
+        data = response.json()
+        parsed_response = SearchPeopleResponse(**data)
         if parsed_response.pagination.total_entries == 0:
             return []
 
@@ -52,27 +54,29 @@ class ApolloClient:
                 and len(parsed_response.people) > 0
             ):
                 query.page += 1
-                response = self.requests.get(
+                response = await self.requests.post(
                     f"{self.API_URL}/mixed_people/search",
                     headers=self._get_headers(),
-                    params=query.model_dump(exclude={"credentials", "max_results"}),
+                    json=query.model_dump(exclude={"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.post(
             f"{self.API_URL}/mixed_companies/search",
             headers=self._get_headers(),
-            params=query.model_dump(exclude={"credentials", "max_results"}),
+            json=query.model_dump(exclude={"max_results"}),
         )
-        parsed_response = SearchOrganizationsResponse(**response.json())
+        data = response.json()
+        parsed_response = SearchOrganizationsResponse(**data)
         if parsed_response.pagination.total_entries == 0:
             return []
 
@@ -90,12 +94,13 @@ class ApolloClient:
                 and len(parsed_response.organizations) > 0
             ):
                 query.page += 1
-                response = self.requests.get(
+                response = await self.requests.post(
                     f"{self.API_URL}/mixed_companies/search",
                     headers=self._get_headers(),
-                    params=query.model_dump(exclude={"credentials", "max_results"}),
+                    json=query.model_dump(exclude={"max_results"}),
                 )
-                parsed_response = SearchOrganizationsResponse(**response.json())
+                data = response.json()
+                parsed_response = SearchOrganizationsResponse(**data)
                 organizations.extend(
                     parsed_response.organizations[
                         : query.max_results - len(organizations)
@@ -106,3 +111,21 @@ class ApolloClient:
         return (
             organizations[: query.max_results] if query.max_results else organizations
         )
+
+    async def enrich_person(self, query: EnrichPersonRequest) -> Contact:
+        """Enrich a person's data including email & phone reveal"""
+        response = await self.requests.post(
+            f"{self.API_URL}/people/match",
+            headers=self._get_headers(),
+            json=query.model_dump(),
+            params={
+                "reveal_personal_emails": "true",
+            },
+        )
+        data = response.json()
+        if "person" not in data:
+            raise ValueError(f"Person not found or enrichment failed: {data}")
+
+        contact = Contact(**data["person"])
+        contact.email = contact.email or "-"
+        return contact

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

@@ -1,17 +1,31 @@
 from enum import Enum
 from typing import Any, Optional
 
-from pydantic import BaseModel, ConfigDict
+from pydantic import BaseModel as OriginalBaseModel
+from pydantic import ConfigDict
 
 from backend.data.model import SchemaField
 
 
+class BaseModel(OriginalBaseModel):
+    def model_dump(self, *args, exclude: set[str] | None = None, **kwargs):
+        if exclude is None:
+            exclude = set("credentials")
+        else:
+            exclude.add("credentials")
+
+        kwargs.setdefault("exclude_none", True)
+        kwargs.setdefault("exclude_unset", True)
+        kwargs.setdefault("exclude_defaults", True)
+        return super().model_dump(*args, exclude=exclude, **kwargs)
+
+
 class PrimaryPhone(BaseModel):
     """A primary phone in Apollo"""
 
-    number: str
-    source: str
-    sanitized_number: str
+    number: Optional[str] = ""
+    source: Optional[str] = ""
+    sanitized_number: Optional[str] = ""
 
 
 class SenorityLevels(str, Enum):
@@ -42,102 +56,102 @@ class ContactEmailStatuses(str, Enum):
 class RuleConfigStatus(BaseModel):
     """A rule config status in Apollo"""
 
-    _id: str
-    created_at: str
-    rule_action_config_id: str
-    rule_config_id: str
-    status_cd: str
-    updated_at: str
-    id: str
-    key: str
+    _id: Optional[str] = ""
+    created_at: Optional[str] = ""
+    rule_action_config_id: Optional[str] = ""
+    rule_config_id: Optional[str] = ""
+    status_cd: Optional[str] = ""
+    updated_at: Optional[str] = ""
+    id: Optional[str] = ""
+    key: Optional[str] = ""
 
 
 class ContactCampaignStatus(BaseModel):
     """A contact campaign status in Apollo"""
 
-    id: str
-    emailer_campaign_id: str
-    send_email_from_user_id: str
-    inactive_reason: str
-    status: str
-    added_at: str
-    added_by_user_id: str
-    finished_at: str
-    paused_at: str
-    auto_unpause_at: str
-    send_email_from_email_address: str
-    send_email_from_email_account_id: str
-    manually_set_unpause: str
-    failure_reason: str
-    current_step_id: str
-    in_response_to_emailer_message_id: str
-    cc_emails: str
-    bcc_emails: str
-    to_emails: str
+    id: Optional[str] = ""
+    emailer_campaign_id: Optional[str] = ""
+    send_email_from_user_id: Optional[str] = ""
+    inactive_reason: Optional[str] = ""
+    status: Optional[str] = ""
+    added_at: Optional[str] = ""
+    added_by_user_id: Optional[str] = ""
+    finished_at: Optional[str] = ""
+    paused_at: Optional[str] = ""
+    auto_unpause_at: Optional[str] = ""
+    send_email_from_email_address: Optional[str] = ""
+    send_email_from_email_account_id: Optional[str] = ""
+    manually_set_unpause: Optional[str] = ""
+    failure_reason: Optional[str] = ""
+    current_step_id: Optional[str] = ""
+    in_response_to_emailer_message_id: Optional[str] = ""
+    cc_emails: Optional[str] = ""
+    bcc_emails: Optional[str] = ""
+    to_emails: Optional[str] = ""
 
 
 class Account(BaseModel):
     """An account in Apollo"""
 
-    id: str
-    name: str
-    website_url: str
-    blog_url: str
-    angellist_url: str
-    linkedin_url: str
-    twitter_url: str
-    facebook_url: str
-    primary_phone: PrimaryPhone
-    languages: list[str]
-    alexa_ranking: int
-    phone: str
-    linkedin_uid: str
-    founded_year: int
-    publicly_traded_symbol: str
-    publicly_traded_exchange: str
-    logo_url: str
-    chrunchbase_url: str
-    primary_domain: str
-    domain: str
-    team_id: str
-    organization_id: str
-    account_stage_id: str
-    source: str
-    original_source: str
-    creator_id: str
-    owner_id: str
-    created_at: str
-    phone_status: str
-    hubspot_id: str
-    salesforce_id: str
-    crm_owner_id: str
-    parent_account_id: str
-    sanitized_phone: str
+    id: Optional[str] = ""
+    name: Optional[str] = ""
+    website_url: Optional[str] = ""
+    blog_url: Optional[str] = ""
+    angellist_url: Optional[str] = ""
+    linkedin_url: Optional[str] = ""
+    twitter_url: Optional[str] = ""
+    facebook_url: Optional[str] = ""
+    primary_phone: Optional[PrimaryPhone] = PrimaryPhone()
+    languages: Optional[list[str]] = []
+    alexa_ranking: Optional[int] = 0
+    phone: Optional[str] = ""
+    linkedin_uid: Optional[str] = ""
+    founded_year: Optional[int] = 0
+    publicly_traded_symbol: Optional[str] = ""
+    publicly_traded_exchange: Optional[str] = ""
+    logo_url: Optional[str] = ""
+    chrunchbase_url: Optional[str] = ""
+    primary_domain: Optional[str] = ""
+    domain: Optional[str] = ""
+    team_id: Optional[str] = ""
+    organization_id: Optional[str] = ""
+    account_stage_id: Optional[str] = ""
+    source: Optional[str] = ""
+    original_source: Optional[str] = ""
+    creator_id: Optional[str] = ""
+    owner_id: Optional[str] = ""
+    created_at: Optional[str] = ""
+    phone_status: Optional[str] = ""
+    hubspot_id: Optional[str] = ""
+    salesforce_id: Optional[str] = ""
+    crm_owner_id: Optional[str] = ""
+    parent_account_id: Optional[str] = ""
+    sanitized_phone: Optional[str] = ""
     # no listed type on the API docs
-    account_playbook_statues: list[Any]
-    account_rule_config_statuses: list[RuleConfigStatus]
-    existence_level: str
-    label_ids: list[str]
-    typed_custom_fields: Any
-    custom_field_errors: Any
-    modality: str
-    source_display_name: str
-    salesforce_record_id: str
-    crm_record_url: str
+    account_playbook_statues: Optional[list[Any]] = []
+    account_rule_config_statuses: Optional[list[RuleConfigStatus]] = []
+    existence_level: Optional[str] = ""
+    label_ids: Optional[list[str]] = []
+    typed_custom_fields: Optional[Any] = {}
+    custom_field_errors: Optional[Any] = {}
+    modality: Optional[str] = ""
+    source_display_name: Optional[str] = ""
+    salesforce_record_id: Optional[str] = ""
+    crm_record_url: Optional[str] = ""
 
 
 class ContactEmail(BaseModel):
     """A contact email in Apollo"""
 
-    email: str = ""
-    email_md5: str = ""
-    email_sha256: str = ""
-    email_status: str = ""
-    email_source: str = ""
-    extrapolated_email_confidence: str = ""
-    position: int = 0
-    email_from_customer: str = ""
-    free_domain: bool = True
+    email: Optional[str] = ""
+    email_md5: Optional[str] = ""
+    email_sha256: Optional[str] = ""
+    email_status: Optional[str] = ""
+    email_source: Optional[str] = ""
+    extrapolated_email_confidence: Optional[str] = ""
+    position: Optional[int] = 0
+    email_from_customer: Optional[str] = ""
+    free_domain: Optional[bool] = True
 
 
 class EmploymentHistory(BaseModel):
@@ -150,40 +164,40 @@ class EmploymentHistory(BaseModel):
         populate_by_name=True,
     )
 
-    _id: Optional[str] = None
-    created_at: Optional[str] = None
-    current: Optional[bool] = None
-    degree: Optional[str] = None
-    description: Optional[str] = None
-    emails: Optional[str] = None
-    end_date: Optional[str] = None
-    grade_level: Optional[str] = None
-    kind: Optional[str] = None
-    major: Optional[str] = None
-    organization_id: Optional[str] = None
-    organization_name: Optional[str] = None
-    raw_address: Optional[str] = None
-    start_date: Optional[str] = None
-    title: Optional[str] = None
-    updated_at: Optional[str] = None
-    id: Optional[str] = None
-    key: Optional[str] = None
+    _id: Optional[str] = ""
+    created_at: Optional[str] = ""
+    current: Optional[bool] = False
+    degree: Optional[str] = ""
+    description: Optional[str] = ""
+    emails: Optional[str] = ""
+    end_date: Optional[str] = ""
+    grade_level: Optional[str] = ""
+    kind: Optional[str] = ""
+    major: Optional[str] = ""
+    organization_id: Optional[str] = ""
+    organization_name: Optional[str] = ""
+    raw_address: Optional[str] = ""
+    start_date: Optional[str] = ""
+    title: Optional[str] = ""
+    updated_at: Optional[str] = ""
+    id: Optional[str] = ""
+    key: Optional[str] = ""
 
 
 class Breadcrumb(BaseModel):
     """A breadcrumb in Apollo"""
 
-    label: Optional[str] = "N/A"
-    signal_field_name: Optional[str] = "N/A"
-    value: str | list | None = "N/A"
-    display_name: Optional[str] = "N/A"
+    label: Optional[str] = ""
+    signal_field_name: Optional[str] = ""
+    value: str | list | None = ""
+    display_name: Optional[str] = ""
 
 
 class TypedCustomField(BaseModel):
     """A typed custom field in Apollo"""
 
-    id: Optional[str] = "N/A"
-    value: Optional[str] = "N/A"
+    id: Optional[str] = ""
+    value: Optional[str] = ""
 
 
 class Pagination(BaseModel):
@@ -205,23 +219,23 @@ class Pagination(BaseModel):
 class DialerFlags(BaseModel):
     """A dialer flags in Apollo"""
 
-    country_name: str
-    country_enabled: bool
-    high_risk_calling_enabled: bool
-    potential_high_risk_number: bool
+    country_name: Optional[str] = ""
+    country_enabled: Optional[bool] = True
+    high_risk_calling_enabled: Optional[bool] = True
+    potential_high_risk_number: Optional[bool] = True
 
 
 class PhoneNumber(BaseModel):
     """A phone number in Apollo"""
 
-    raw_number: str = ""
-    sanitized_number: str = ""
-    type: str = ""
-    position: int = 0
-    status: str = ""
-    dnc_status: str = ""
-    dnc_other_info: str = ""
-    dailer_flags: DialerFlags = DialerFlags(
+    raw_number: Optional[str] = ""
+    sanitized_number: Optional[str] = ""
+    type: Optional[str] = ""
+    position: Optional[int] = 0
+    status: Optional[str] = ""
+    dnc_status: Optional[str] = ""
+    dnc_other_info: Optional[str] = ""
+    dailer_flags: Optional[DialerFlags] = DialerFlags(
         country_name="",
         country_enabled=True,
         high_risk_calling_enabled=True,
@@ -239,33 +253,31 @@ class Organization(BaseModel):
         populate_by_name=True,
     )
 
-    id: Optional[str] = "N/A"
-    name: Optional[str] = "N/A"
-    website_url: Optional[str] = "N/A"
-    blog_url: Optional[str] = "N/A"
-    angellist_url: Optional[str] = "N/A"
-    linkedin_url: Optional[str] = "N/A"
-    twitter_url: Optional[str] = "N/A"
-    facebook_url: Optional[str] = "N/A"
-    primary_phone: Optional[PrimaryPhone] = PrimaryPhone(
-        number="N/A", source="N/A", sanitized_number="N/A"
-    )
-    languages: list[str] = []
+    id: Optional[str] = ""
+    name: Optional[str] = ""
+    website_url: Optional[str] = ""
+    blog_url: Optional[str] = ""
+    angellist_url: Optional[str] = ""
+    linkedin_url: Optional[str] = ""
+    twitter_url: Optional[str] = ""
+    facebook_url: Optional[str] = ""
+    primary_phone: Optional[PrimaryPhone] = PrimaryPhone()
+    languages: Optional[list[str]] = []
     alexa_ranking: Optional[int] = 0
-    phone: Optional[str] = "N/A"
-    linkedin_uid: Optional[str] = "N/A"
+    phone: Optional[str] = ""
+    linkedin_uid: Optional[str] = ""
     founded_year: Optional[int] = 0
-    publicly_traded_symbol: Optional[str] = "N/A"
-    publicly_traded_exchange: Optional[str] = "N/A"
-    logo_url: Optional[str] = "N/A"
-    chrunchbase_url: Optional[str] = "N/A"
-    primary_domain: Optional[str] = "N/A"
-    sanitized_phone: Optional[str] = "N/A"
-    owned_by_organization_id: Optional[str] = "N/A"
-    intent_strength: Optional[str] = "N/A"
-    show_intent: bool = True
+    publicly_traded_symbol: Optional[str] = ""
+    publicly_traded_exchange: Optional[str] = ""
+    logo_url: Optional[str] = ""
+    chrunchbase_url: Optional[str] = ""
+    primary_domain: Optional[str] = ""
+    sanitized_phone: Optional[str] = ""
+    owned_by_organization_id: Optional[str] = ""
+    intent_strength: Optional[str] = ""
+    show_intent: Optional[bool] = True
     has_intent_signal_account: Optional[bool] = True
-    intent_signal_account: Optional[str] = "N/A"
+    intent_signal_account: Optional[str] = ""
 
 
 class Contact(BaseModel):
@@ -278,95 +290,95 @@ class Contact(BaseModel):
         populate_by_name=True,
     )
 
-    contact_roles: list[Any] = []
-    id: Optional[str] = None
-    first_name: Optional[str] = None
-    last_name: Optional[str] = None
-    name: Optional[str] = None
-    linkedin_url: Optional[str] = None
-    title: Optional[str] = None
-    contact_stage_id: Optional[str] = None
-    owner_id: Optional[str] = None
-    creator_id: Optional[str] = None
-    person_id: Optional[str] = None
-    email_needs_tickling: bool = True
-    organization_name: Optional[str] = None
-    source: Optional[str] = None
-    original_source: Optional[str] = None
-    organization_id: Optional[str] = None
-    headline: Optional[str] = None
-    photo_url: Optional[str] = None
-    present_raw_address: Optional[str] = None
-    linkededin_uid: Optional[str] = None
-    extrapolated_email_confidence: Optional[float] = None
-    salesforce_id: Optional[str] = None
-    salesforce_lead_id: Optional[str] = None
-    salesforce_contact_id: Optional[str] = None
-    saleforce_account_id: Optional[str] = None
-    crm_owner_id: Optional[str] = None
-    created_at: Optional[str] = None
-    emailer_campaign_ids: list[str] = []
-    direct_dial_status: Optional[str] = None
-    direct_dial_enrichment_failed_at: Optional[str] = None
-    email_status: Optional[str] = None
-    email_source: Optional[str] = None
-    account_id: Optional[str] = None
-    last_activity_date: Optional[str] = None
-    hubspot_vid: Optional[str] = None
-    hubspot_company_id: Optional[str] = None
-    crm_id: Optional[str] = None
-    sanitized_phone: Optional[str] = None
-    merged_crm_ids: Optional[str] = None
-    updated_at: Optional[str] = None
-    queued_for_crm_push: bool = True
-    suggested_from_rule_engine_config_id: Optional[str] = None
-    email_unsubscribed: Optional[str] = None
-    label_ids: list[Any] = []
-    has_pending_email_arcgate_request: bool = True
-    has_email_arcgate_request: bool = True
-    existence_level: Optional[str] = None
-    email: Optional[str] = None
-    email_from_customer: Optional[str] = None
-    typed_custom_fields: list[TypedCustomField] = []
-    custom_field_errors: Any = None
-    salesforce_record_id: Optional[str] = None
-    crm_record_url: Optional[str] = None
-    email_status_unavailable_reason: Optional[str] = None
-    email_true_status: Optional[str] = None
-    updated_email_true_status: bool = True
-    contact_rule_config_statuses: list[RuleConfigStatus] = []
-    source_display_name: Optional[str] = None
-    twitter_url: Optional[str] = None
-    contact_campaign_statuses: list[ContactCampaignStatus] = []
-    state: Optional[str] = None
-    city: Optional[str] = None
-    country: Optional[str] = None
-    account: Optional[Account] = None
-    contact_emails: list[ContactEmail] = []
-    organization: Optional[Organization] = None
-    employment_history: list[EmploymentHistory] = []
-    time_zone: Optional[str] = None
-    intent_strength: Optional[str] = None
-    show_intent: bool = True
-    phone_numbers: list[PhoneNumber] = []
-    account_phone_note: Optional[str] = None
-    free_domain: bool = True
-    is_likely_to_engage: bool = True
-    email_domain_catchall: bool = True
-    contact_job_change_event: Optional[str] = None
+    contact_roles: Optional[list[Any]] = []
+    id: Optional[str] = ""
+    first_name: Optional[str] = ""
+    last_name: Optional[str] = ""
+    name: Optional[str] = ""
+    linkedin_url: Optional[str] = ""
+    title: Optional[str] = ""
+    contact_stage_id: Optional[str] = ""
+    owner_id: Optional[str] = ""
+    creator_id: Optional[str] = ""
+    person_id: Optional[str] = ""
+    email_needs_tickling: Optional[bool] = True
+    organization_name: Optional[str] = ""
+    source: Optional[str] = ""
+    original_source: Optional[str] = ""
+    organization_id: Optional[str] = ""
+    headline: Optional[str] = ""
+    photo_url: Optional[str] = ""
+    present_raw_address: Optional[str] = ""
+    linkededin_uid: Optional[str] = ""
+    extrapolated_email_confidence: Optional[float] = 0.0
+    salesforce_id: Optional[str] = ""
+    salesforce_lead_id: Optional[str] = ""
+    salesforce_contact_id: Optional[str] = ""
+    saleforce_account_id: Optional[str] = ""
+    crm_owner_id: Optional[str] = ""
+    created_at: Optional[str] = ""
+    emailer_campaign_ids: Optional[list[str]] = []
+    direct_dial_status: Optional[str] = ""
+    direct_dial_enrichment_failed_at: Optional[str] = ""
+    email_status: Optional[str] = ""
+    email_source: Optional[str] = ""
+    account_id: Optional[str] = ""
+    last_activity_date: Optional[str] = ""
+    hubspot_vid: Optional[str] = ""
+    hubspot_company_id: Optional[str] = ""
+    crm_id: Optional[str] = ""
+    sanitized_phone: Optional[str] = ""
+    merged_crm_ids: Optional[str] = ""
+    updated_at: Optional[str] = ""
+    queued_for_crm_push: Optional[bool] = True
+    suggested_from_rule_engine_config_id: Optional[str] = ""
+    email_unsubscribed: Optional[str] = ""
+    label_ids: Optional[list[Any]] = []
+    has_pending_email_arcgate_request: Optional[bool] = True
+    has_email_arcgate_request: Optional[bool] = True
+    existence_level: Optional[str] = ""
+    email: Optional[str] = ""
+    email_from_customer: Optional[str] = ""
+    typed_custom_fields: Optional[list[TypedCustomField]] = []
+    custom_field_errors: Optional[Any] = {}
+    salesforce_record_id: Optional[str] = ""
+    crm_record_url: Optional[str] = ""
+    email_status_unavailable_reason: Optional[str] = ""
+    email_true_status: Optional[str] = ""
+    updated_email_true_status: Optional[bool] = True
+    contact_rule_config_statuses: Optional[list[RuleConfigStatus]] = []
+    source_display_name: Optional[str] = ""
+    twitter_url: Optional[str] = ""
+    contact_campaign_statuses: Optional[list[ContactCampaignStatus]] = []
+    state: Optional[str] = ""
+    city: Optional[str] = ""
+    country: Optional[str] = ""
+    account: Optional[Account] = Account()
+    contact_emails: Optional[list[ContactEmail]] = []
+    organization: Optional[Organization] = Organization()
+    employment_history: Optional[list[EmploymentHistory]] = []
+    time_zone: Optional[str] = ""
+    intent_strength: Optional[str] = ""
+    show_intent: Optional[bool] = True
+    phone_numbers: Optional[list[PhoneNumber]] = []
+    account_phone_note: Optional[str] = ""
+    free_domain: Optional[bool] = True
+    is_likely_to_engage: Optional[bool] = True
+    email_domain_catchall: Optional[bool] = True
+    contact_job_change_event: Optional[str] = ""
 
 
 class SearchOrganizationsRequest(BaseModel):
     """Request for Apollo's search organizations API"""
 
-    organization_num_empoloyees_range: list[int] = SchemaField(
+    organization_num_employees_range: Optional[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=[0, 1000000],
     )
 
-    organization_locations: list[str] = SchemaField(
+    organization_locations: Optional[list[str]] = SchemaField(
         description="""The location of the company headquarters. You can search across cities, US states, and countries.
 
 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, any Boston-based companies will not appearch in your search results, even if they match other parameters.
@@ -375,28 +387,30 @@ To exclude companies based on location, use the organization_not_locations param
 """,
         default_factory=list,
     )
-    organizations_not_locations: list[str] = SchemaField(
+    organizations_not_locations: Optional[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_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."""
+    q_organization_keyword_tags: Optional[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_factory=list,
     )
-    q_organization_name: str = SchemaField(
+    q_organization_name: Optional[str] = SchemaField(
         description="""Filter search results to include a specific company name.
 
-If the value you enter for this parameter does not match with a company's name, the company will not appear in search results, even if it matches other parameters. Partial matches are accepted. For example, if you filter by the value marketing, a company called NY Marketing Unlimited would still be eligible as a search result, but NY Market Analysis would not be eligible."""
+If the value you enter for this parameter does not match with a company's name, the company will not appear in search results, even if it matches other parameters. Partial matches are accepted. For example, if you filter by the value marketing, a company called NY Marketing Unlimited would still be eligible as a search result, but NY Market Analysis would not be eligible.""",
+        default="",
     )
-    organization_ids: list[str] = SchemaField(
+    organization_ids: Optional[list[str]] = SchemaField(
         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_factory=list,
     )
-    max_results: int = SchemaField(
+    max_results: Optional[int] = SchemaField(
         description="""The maximum number of results to return. If you don't specify this parameter, the default is 100.""",
         default=100,
         ge=1,
@@ -421,11 +435,11 @@ Use the page parameter to search the different pages of data.""",
 class SearchOrganizationsResponse(BaseModel):
     """Response from Apollo's search organizations API"""
 
-    breadcrumbs: list[Breadcrumb] = []
-    partial_results_only: bool = True
-    has_join: bool = True
-    disable_eu_prospecting: bool = True
-    partial_results_limit: int = 0
+    breadcrumbs: Optional[list[Breadcrumb]] = []
+    partial_results_only: Optional[bool] = True
+    has_join: Optional[bool] = True
+    disable_eu_prospecting: Optional[bool] = True
+    partial_results_limit: Optional[int] = 0
     pagination: Pagination = Pagination(
         page=0, per_page=0, total_entries=0, total_pages=0
     )
@@ -433,14 +447,14 @@ class SearchOrganizationsResponse(BaseModel):
     accounts: list[Any] = []
     organizations: list[Organization] = []
     models_ids: list[str] = []
-    num_fetch_result: Optional[str] = "N/A"
-    derived_params: Optional[str] = "N/A"
+    num_fetch_result: Optional[str] = ""
+    derived_params: Optional[str] = ""
 
 
 class SearchPeopleRequest(BaseModel):
     """Request for Apollo's search people API"""
 
-    person_titles: list[str] = SchemaField(
+    person_titles: Optional[list[str]] = SchemaField(
         description="""Job titles held by the people you want to find. For a person to be included in search results, they only need to match 1 of the job titles you add. Adding more job titles expands your search results.
 
 Results also include job titles with the same terms, even if they are not exact matches. For example, searching for marketing manager might return people with the job title content marketing manager.
@@ -450,13 +464,13 @@ Use this parameter in combination with the person_seniorities[] parameter to fin
         default_factory=list,
         placeholder="marketing manager",
     )
-    person_locations: list[str] = SchemaField(
+    person_locations: Optional[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_factory=list,
     )
-    person_seniorities: list[SenorityLevels] = SchemaField(
+    person_seniorities: Optional[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.
 
 For a person to be included in search results, they only need to match 1 of the seniorities you add. Adding more seniorities expands your search results.
@@ -466,7 +480,7 @@ Searches only return results based on their current job title, so searching for
 Use this parameter in combination with the person_titles[] parameter to find people based on specific job functions and seniority levels.""",
         default_factory=list,
     )
-    organization_locations: list[str] = SchemaField(
+    organization_locations: Optional[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.
 
 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.
@@ -474,7 +488,7 @@ If a company has several office locations, results are still based on the headqu
 To find people based on their personal location, use the person_locations parameter.""",
         default_factory=list,
     )
-    q_organization_domains: list[str] = SchemaField(
+    q_organization_domains: Optional[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.
 
 You can add multiple domains to search across companies.
@@ -482,23 +496,23 @@ You can add multiple domains to search across companies.
   Examples: apollo.io and microsoft.com""",
         default_factory=list,
     )
-    contact_email_statuses: list[ContactEmailStatuses] = SchemaField(
+    contact_email_statuses: Optional[list[ContactEmailStatuses]] = SchemaField(
         description="""The email statuses for the people you want to find. You can add multiple statuses to expand your search.""",
         default_factory=list,
     )
-    organization_ids: list[str] = SchemaField(
+    organization_ids: Optional[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_factory=list,
     )
-    organization_num_empoloyees_range: list[int] = SchemaField(
+    organization_num_employees_range: Optional[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_factory=list,
     )
-    q_keywords: str = SchemaField(
+    q_keywords: Optional[str] = SchemaField(
         description="""A string of words over which we want to filter the results""",
         default="",
     )
@@ -514,7 +528,7 @@ Use this parameter in combination with the per_page parameter to make search res
 Use the page parameter to search the different pages of data.""",
         default=100,
     )
-    max_results: int = SchemaField(
+    max_results: Optional[int] = SchemaField(
         description="""The maximum number of results to return. If you don't specify this parameter, the default is 100.""",
         default=100,
         ge=1,
@@ -533,16 +547,61 @@ class SearchPeopleResponse(BaseModel):
         populate_by_name=True,
     )
 
-    breadcrumbs: list[Breadcrumb] = []
-    partial_results_only: bool = True
-    has_join: bool = True
-    disable_eu_prospecting: bool = True
-    partial_results_limit: int = 0
+    breadcrumbs: Optional[list[Breadcrumb]] = []
+    partial_results_only: Optional[bool] = True
+    has_join: Optional[bool] = True
+    disable_eu_prospecting: Optional[bool] = True
+    partial_results_limit: Optional[int] = 0
     pagination: Pagination = Pagination(
         page=0, per_page=0, total_entries=0, total_pages=0
     )
     contacts: list[Contact] = []
     people: list[Contact] = []
     model_ids: list[str] = []
-    num_fetch_result: Optional[str] = "N/A"
-    derived_params: Optional[str] = "N/A"
+    num_fetch_result: Optional[str] = ""
+    derived_params: Optional[str] = ""
+
+
+class EnrichPersonRequest(BaseModel):
+    """Request for Apollo's person enrichment API"""
+
+    person_id: Optional[str] = SchemaField(
+        description="Apollo person ID to enrich (most accurate method)",
+        default="",
+    )
+    first_name: Optional[str] = SchemaField(
+        description="First name of the person to enrich",
+        default="",
+    )
+    last_name: Optional[str] = SchemaField(
+        description="Last name of the person to enrich",
+        default="",
+    )
+    name: Optional[str] = SchemaField(
+        description="Full name of the person to enrich",
+        default="",
+    )
+    email: Optional[str] = SchemaField(
+        description="Email address of the person to enrich",
+        default="",
+    )
+    domain: Optional[str] = SchemaField(
+        description="Company domain of the person to enrich",
+        default="",
+    )
+    company: Optional[str] = SchemaField(
+        description="Company name of the person to enrich",
+        default="",
+    )
+    linkedin_url: Optional[str] = SchemaField(
+        description="LinkedIn URL of the person to enrich",
+        default="",
+    )
+    organization_id: Optional[str] = SchemaField(
+        description="Apollo organization ID of the person's company",
+        default="",
+    )
+    title: Optional[str] = SchemaField(
+        description="Job title of the person to enrich",
+        default="",
+    )

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

@@ -11,14 +11,14 @@ from backend.blocks.apollo.models import (
     SearchOrganizationsRequest,
 )
 from backend.data.block import Block, BlockCategory, BlockOutput, BlockSchema
-from backend.data.model import SchemaField
+from backend.data.model import CredentialsField, SchemaField
 
 
 class SearchOrganizationsBlock(Block):
     """Search for organizations in Apollo"""
 
     class Input(BlockSchema):
-        organization_num_empoloyees_range: list[int] = SchemaField(
+        organization_num_employees_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.""",
@@ -65,7 +65,7 @@ To find IDs, identify the values for organization_id when you call this endpoint
             le=50000,
             advanced=True,
         )
-        credentials: ApolloCredentialsInput = SchemaField(
+        credentials: ApolloCredentialsInput = CredentialsField(
             description="Apollo credentials",
         )
 
@@ -201,19 +201,17 @@ 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)
+        query = SearchOrganizationsRequest(**input_data.model_dump())
+        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

@@ -1,3 +1,5 @@
+import asyncio
+
 from backend.blocks.apollo._api import ApolloClient
 from backend.blocks.apollo._auth import (
     TEST_CREDENTIALS,
@@ -8,11 +10,12 @@ from backend.blocks.apollo._auth import (
 from backend.blocks.apollo.models import (
     Contact,
     ContactEmailStatuses,
+    EnrichPersonRequest,
     SearchPeopleRequest,
     SenorityLevels,
 )
 from backend.data.block import Block, BlockCategory, BlockOutput, BlockSchema
-from backend.data.model import SchemaField
+from backend.data.model import CredentialsField, SchemaField
 
 
 class SearchPeopleBlock(Block):
@@ -77,7 +80,7 @@ class SearchPeopleBlock(Block):
             default_factory=list,
             advanced=False,
         )
-        organization_num_empoloyees_range: list[int] = SchemaField(
+        organization_num_employees_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.""",
@@ -90,14 +93,19 @@ class SearchPeopleBlock(Block):
             advanced=False,
         )
         max_results: int = SchemaField(
-            description="""The maximum number of results to return. If you don't specify this parameter, the default is 100.""",
-            default=100,
+            description="""The maximum number of results to return. If you don't specify this parameter, the default is 25. Limited to 500 to prevent overspending.""",
+            default=25,
             ge=1,
-            le=50000,
+            le=500,
+            advanced=True,
+        )
+        enrich_info: bool = SchemaField(
+            description="""Whether to enrich contacts with detailed information including real email addresses. This will double the search cost.""",
+            default=False,
             advanced=True,
         )
 
-        credentials: ApolloCredentialsInput = SchemaField(
+        credentials: ApolloCredentialsInput = CredentialsField(
             description="Apollo credentials",
         )
 
@@ -106,9 +114,6 @@ class SearchPeopleBlock(Block):
             description="List of people found",
             default_factory=list,
         )
-        person: Contact = SchemaField(
-            description="Each found person, one at a time",
-        )
         error: str = SchemaField(
             description="Error message if the search failed",
             default="",
@@ -124,87 +129,6 @@ class SearchPeopleBlock(Block):
             test_credentials=TEST_CREDENTIALS,
             test_input={"credentials": TEST_CREDENTIALS_INPUT},
             test_output=[
-                (
-                    "person",
-                    Contact(
-                        contact_roles=[],
-                        id="1",
-                        name="John Doe",
-                        first_name="John",
-                        last_name="Doe",
-                        linkedin_url="https://www.linkedin.com/in/johndoe",
-                        title="Software Engineer",
-                        organization_name="Google",
-                        organization_id="123456",
-                        contact_stage_id="1",
-                        owner_id="1",
-                        creator_id="1",
-                        person_id="1",
-                        email_needs_tickling=True,
-                        source="apollo",
-                        original_source="apollo",
-                        headline="Software Engineer",
-                        photo_url="https://www.linkedin.com/in/johndoe",
-                        present_raw_address="123 Main St, Anytown, USA",
-                        linkededin_uid="123456",
-                        extrapolated_email_confidence=0.8,
-                        salesforce_id="123456",
-                        salesforce_lead_id="123456",
-                        salesforce_contact_id="123456",
-                        saleforce_account_id="123456",
-                        crm_owner_id="123456",
-                        created_at="2021-01-01",
-                        emailer_campaign_ids=[],
-                        direct_dial_status="active",
-                        direct_dial_enrichment_failed_at="2021-01-01",
-                        email_status="active",
-                        email_source="apollo",
-                        account_id="123456",
-                        last_activity_date="2021-01-01",
-                        hubspot_vid="123456",
-                        hubspot_company_id="123456",
-                        crm_id="123456",
-                        sanitized_phone="123456",
-                        merged_crm_ids="123456",
-                        updated_at="2021-01-01",
-                        queued_for_crm_push=True,
-                        suggested_from_rule_engine_config_id="123456",
-                        email_unsubscribed=None,
-                        label_ids=[],
-                        has_pending_email_arcgate_request=True,
-                        has_email_arcgate_request=True,
-                        existence_level=None,
-                        email=None,
-                        email_from_customer=None,
-                        typed_custom_fields=[],
-                        custom_field_errors=None,
-                        salesforce_record_id=None,
-                        crm_record_url=None,
-                        email_status_unavailable_reason=None,
-                        email_true_status=None,
-                        updated_email_true_status=True,
-                        contact_rule_config_statuses=[],
-                        source_display_name=None,
-                        twitter_url=None,
-                        contact_campaign_statuses=[],
-                        state=None,
-                        city=None,
-                        country=None,
-                        account=None,
-                        contact_emails=[],
-                        organization=None,
-                        employment_history=[],
-                        time_zone=None,
-                        intent_strength=None,
-                        show_intent=True,
-                        phone_numbers=[],
-                        account_phone_note=None,
-                        free_domain=True,
-                        is_likely_to_engage=True,
-                        email_domain_catchall=True,
-                        contact_job_change_event=None,
-                    ),
-                ),
                 (
                     "people",
                     [
@@ -373,13 +297,41 @@ 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(
+    @staticmethod
+    async def enrich_person(
+        query: EnrichPersonRequest, credentials: ApolloCredentials
+    ) -> Contact:
+        client = ApolloClient(credentials)
+        return await client.enrich_person(query)
+
+    @staticmethod
+    def merge_contact_data(original: Contact, enriched: Contact) -> Contact:
+        """
+        Merge contact data from original search with enriched data.
+        Enriched data complements original data, only filling in missing values.
+        """
+        merged_data = original.model_dump()
+        enriched_data = enriched.model_dump()
+
+        # Only update fields that are None, empty string, empty list, or default values in original
+        for key, enriched_value in enriched_data.items():
+            # Skip if enriched value is None, empty string, or empty list
+            if enriched_value is None or enriched_value == "" or enriched_value == []:
+                continue
+
+            # Update if original value is None, empty string, empty list, or zero
+            if enriched_value:
+                merged_data[key] = enriched_value
+
+        return Contact(**merged_data)
+
+    async def run(
         self,
         input_data: Input,
         *,
@@ -387,8 +339,25 @@ class SearchPeopleBlock(Block):
         **kwargs,
     ) -> BlockOutput:
 
-        query = SearchPeopleRequest(**input_data.model_dump(exclude={"credentials"}))
-        people = self.search_people(query, credentials)
-        for person in people:
-            yield "person", person
+        query = SearchPeopleRequest(**input_data.model_dump())
+        people = await self.search_people(query, credentials)
+
+        # Enrich with detailed info if requested
+        if input_data.enrich_info:
+
+            async def enrich_or_fallback(person: Contact):
+                try:
+                    enrich_query = EnrichPersonRequest(person_id=person.id)
+                    enriched_person = await self.enrich_person(
+                        enrich_query, credentials
+                    )
+                    # Merge enriched data with original data, complementing instead of replacing
+                    return self.merge_contact_data(person, enriched_person)
+                except Exception:
+                    return person  # If enrichment fails, use original person data
+
+            people = await asyncio.gather(
+                *(enrich_or_fallback(person) for person in people)
+            )
+
         yield "people", people

autogpt_platform/backend/backend/blocks/apollo/person.py

@@ -0,0 +1,138 @@
+from backend.blocks.apollo._api import ApolloClient
+from backend.blocks.apollo._auth import (
+    TEST_CREDENTIALS,
+    TEST_CREDENTIALS_INPUT,
+    ApolloCredentials,
+    ApolloCredentialsInput,
+)
+from backend.blocks.apollo.models import Contact, EnrichPersonRequest
+from backend.data.block import Block, BlockCategory, BlockOutput, BlockSchema
+from backend.data.model import CredentialsField, SchemaField
+
+
+class GetPersonDetailBlock(Block):
+    """Get detailed person data with Apollo API, including email reveal"""
+
+    class Input(BlockSchema):
+        person_id: str = SchemaField(
+            description="Apollo person ID to enrich (most accurate method)",
+            default="",
+            advanced=False,
+        )
+        first_name: str = SchemaField(
+            description="First name of the person to enrich",
+            default="",
+            advanced=False,
+        )
+        last_name: str = SchemaField(
+            description="Last name of the person to enrich",
+            default="",
+            advanced=False,
+        )
+        name: str = SchemaField(
+            description="Full name of the person to enrich (alternative to first_name + last_name)",
+            default="",
+            advanced=False,
+        )
+        email: str = SchemaField(
+            description="Known email address of the person (helps with matching)",
+            default="",
+            advanced=False,
+        )
+        domain: str = SchemaField(
+            description="Company domain of the person (e.g., 'google.com')",
+            default="",
+            advanced=False,
+        )
+        company: str = SchemaField(
+            description="Company name of the person",
+            default="",
+            advanced=False,
+        )
+        linkedin_url: str = SchemaField(
+            description="LinkedIn URL of the person",
+            default="",
+            advanced=False,
+        )
+        organization_id: str = SchemaField(
+            description="Apollo organization ID of the person's company",
+            default="",
+            advanced=True,
+        )
+        title: str = SchemaField(
+            description="Job title of the person to enrich",
+            default="",
+            advanced=True,
+        )
+        credentials: ApolloCredentialsInput = CredentialsField(
+            description="Apollo credentials",
+        )
+
+    class Output(BlockSchema):
+        contact: Contact = SchemaField(
+            description="Enriched contact information",
+        )
+        error: str = SchemaField(
+            description="Error message if enrichment failed",
+            default="",
+        )
+
+    def __init__(self):
+        super().__init__(
+            id="3b18d46c-3db6-42ae-a228-0ba441bdd176",
+            description="Get detailed person data with Apollo API, including email reveal",
+            categories={BlockCategory.SEARCH},
+            input_schema=GetPersonDetailBlock.Input,
+            output_schema=GetPersonDetailBlock.Output,
+            test_credentials=TEST_CREDENTIALS,
+            test_input={
+                "credentials": TEST_CREDENTIALS_INPUT,
+                "first_name": "John",
+                "last_name": "Doe",
+                "company": "Google",
+            },
+            test_output=[
+                (
+                    "contact",
+                    Contact(
+                        id="1",
+                        name="John Doe",
+                        first_name="John",
+                        last_name="Doe",
+                        email="john.doe@gmail.com",
+                        title="Software Engineer",
+                        organization_name="Google",
+                        linkedin_url="https://www.linkedin.com/in/johndoe",
+                    ),
+                ),
+            ],
+            test_mock={
+                "enrich_person": lambda query, credentials: Contact(
+                    id="1",
+                    name="John Doe",
+                    first_name="John",
+                    last_name="Doe",
+                    email="john.doe@gmail.com",
+                    title="Software Engineer",
+                    organization_name="Google",
+                    linkedin_url="https://www.linkedin.com/in/johndoe",
+                )
+            },
+        )
+
+    @staticmethod
+    async def enrich_person(
+        query: EnrichPersonRequest, credentials: ApolloCredentials
+    ) -> Contact:
+        client = ApolloClient(credentials)
+        return await client.enrich_person(query)
+
+    async def run(
+        self,
+        input_data: Input,
+        *,
+        credentials: ApolloCredentials,
+        **kwargs,
+    ) -> BlockOutput:
+        query = EnrichPersonRequest(**input_data.model_dump())
+        yield "contact", await self.enrich_person(query, credentials)

autogpt_platform/backend/backend/blocks/basic.py

@@ -1,11 +1,9 @@
 import enum
-from typing import Any, List
+from typing import Any
 
 from backend.data.block import Block, BlockCategory, BlockOutput, BlockSchema, BlockType
 from backend.data.model import SchemaField
-from backend.util import json
 from backend.util.file import store_media_file
-from backend.util.mock import MockObject
 from backend.util.type import MediaFileType, convert
 
 
@@ -14,6 +12,12 @@ class FileStoreBlock(Block):
         file_in: MediaFileType = SchemaField(
             description="The file to store in the temporary directory, it can be a URL, data URI, or local path."
         )
+        base_64: bool = SchemaField(
+            description="Whether produce an output in base64 format (not recommended, you can pass the string path just fine accross blocks).",
+            default=False,
+            advanced=True,
+            title="Produce Base64 Output",
+        )
 
     class Output(BlockSchema):
         file_out: MediaFileType = SchemaField(
@@ -30,19 +34,18 @@ 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(
+        yield "file_out", await store_media_file(
             graph_exec_id=graph_exec_id,
             file=input_data.file_in,
-            return_content=False,
+            return_content=input_data.base_64,
         )
-        yield "file_out", file_path
 
 
 class StoreValueBlock(Block):
@@ -84,268 +87,35 @@ 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 FindInDictionaryBlock(Block):
+class PrintToConsoleBlock(Block):
     class Input(BlockSchema):
-        input: Any = SchemaField(description="Dictionary to lookup from")
-        key: str | int = SchemaField(description="Key to lookup in the dictionary")
+        text: Any = SchemaField(description="The data to print to the console.")
 
     class Output(BlockSchema):
-        output: Any = SchemaField(description="Value found for the given key")
-        missing: Any = SchemaField(
-            description="Value of the input that missing the key"
-        )
+        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="0e50422c-6dee-4145-83d6-3a5a392f65de",
-            description="Lookup the given key in the input dictionary/object/list and return the value.",
-            input_schema=FindInDictionaryBlock.Input,
-            output_schema=FindInDictionaryBlock.Output,
-            test_input=[
-                {"input": {"apple": 1, "banana": 2, "cherry": 3}, "key": "banana"},
-                {"input": {"x": 10, "y": 20, "z": 30}, "key": "w"},
-                {"input": [1, 2, 3], "key": 1},
-                {"input": [1, 2, 3], "key": 3},
-                {"input": MockObject(value="!!", key="key"), "key": "key"},
-                {"input": [{"k1": "v1"}, {"k2": "v2"}, {"k1": "v3"}], "key": "k1"},
-            ],
-            test_output=[
-                ("output", 2),
-                ("missing", {"x": 10, "y": 20, "z": 30}),
-                ("output", 2),
-                ("missing", [1, 2, 3]),
-                ("output", "key"),
-                ("output", ["v1", "v3"]),
-            ],
+            id="f3b1c1b2-4c4f-4f0d-8d2f-4c4f0d8d2f4c",
+            description="Print the given text to the console, this is used for a debugging purpose.",
             categories={BlockCategory.BASIC},
-        )
-
-    def run(self, input_data: Input, **kwargs) -> BlockOutput:
-        obj = input_data.input
-        key = input_data.key
-
-        if isinstance(obj, str):
-            obj = json.loads(obj)
-
-        if isinstance(obj, dict) and key in obj:
-            yield "output", obj[key]
-        elif isinstance(obj, list) and isinstance(key, int) and 0 <= key < len(obj):
-            yield "output", obj[key]
-        elif isinstance(obj, list) and isinstance(key, str):
-            if len(obj) == 0:
-                yield "output", []
-            elif isinstance(obj[0], dict) and key in obj[0]:
-                yield "output", [item[key] for item in obj if key in item]
-            else:
-                yield "output", [getattr(val, key) for val in obj if hasattr(val, key)]
-        elif isinstance(obj, object) and isinstance(key, str) and hasattr(obj, key):
-            yield "output", getattr(obj, key)
-        else:
-            yield "missing", input_data.input
-
-
-class AddToDictionaryBlock(Block):
-    class Input(BlockSchema):
-        dictionary: dict[Any, Any] = SchemaField(
-            default_factory=dict,
-            description="The dictionary to add the entry to. If not provided, a new dictionary will be created.",
-        )
-        key: str = SchemaField(
-            default="",
-            description="The key for the new entry.",
-            placeholder="new_key",
-            advanced=False,
-        )
-        value: Any = SchemaField(
-            default=None,
-            description="The value for the new entry.",
-            placeholder="new_value",
-            advanced=False,
-        )
-        entries: dict[Any, Any] = SchemaField(
-            default_factory=dict,
-            description="The entries to add to the dictionary. This is the batch version of the `key` and `value` fields.",
-            advanced=True,
-        )
-
-    class Output(BlockSchema):
-        updated_dictionary: dict = SchemaField(
-            description="The dictionary with the new entry added."
-        )
-        error: str = SchemaField(description="Error message if the operation failed.")
-
-    def __init__(self):
-        super().__init__(
-            id="31d1064e-7446-4693-a7d4-65e5ca1180d1",
-            description="Adds a new key-value pair to a dictionary. If no dictionary is provided, a new one is created.",
-            categories={BlockCategory.BASIC},
-            input_schema=AddToDictionaryBlock.Input,
-            output_schema=AddToDictionaryBlock.Output,
-            test_input=[
-                {
-                    "dictionary": {"existing_key": "existing_value"},
-                    "key": "new_key",
-                    "value": "new_value",
-                },
-                {"key": "first_key", "value": "first_value"},
-                {
-                    "dictionary": {"existing_key": "existing_value"},
-                    "entries": {"new_key": "new_value", "first_key": "first_value"},
-                },
-            ],
+            input_schema=PrintToConsoleBlock.Input,
+            output_schema=PrintToConsoleBlock.Output,
+            test_input={"text": "Hello, World!"},
             test_output=[
-                (
-                    "updated_dictionary",
-                    {"existing_key": "existing_value", "new_key": "new_value"},
-                ),
-                ("updated_dictionary", {"first_key": "first_value"}),
-                (
-                    "updated_dictionary",
-                    {
-                        "existing_key": "existing_value",
-                        "new_key": "new_value",
-                        "first_key": "first_value",
-                    },
-                ),
+                ("output", "Hello, World!"),
+                ("status", "printed"),
             ],
         )
 
-    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:
-            updated_dict[input_data.key] = input_data.value
-
-        for key, value in input_data.entries.items():
-            updated_dict[key] = value
-
-        yield "updated_dictionary", updated_dict
-
-
-class AddToListBlock(Block):
-    class Input(BlockSchema):
-        list: List[Any] = SchemaField(
-            default_factory=list,
-            advanced=False,
-            description="The list to add the entry to. If not provided, a new list will be created.",
-        )
-        entry: Any = SchemaField(
-            description="The entry to add to the list. Can be of any type (string, int, dict, etc.).",
-            advanced=False,
-            default=None,
-        )
-        entries: List[Any] = SchemaField(
-            default_factory=lambda: list(),
-            description="The entries to add to the list. This is the batch version of the `entry` field.",
-            advanced=True,
-        )
-        position: int | None = SchemaField(
-            default=None,
-            description="The position to insert the new entry. If not provided, the entry will be appended to the end of the list.",
-        )
-
-    class Output(BlockSchema):
-        updated_list: List[Any] = SchemaField(
-            description="The list with the new entry added."
-        )
-        error: str = SchemaField(description="Error message if the operation failed.")
-
-    def __init__(self):
-        super().__init__(
-            id="aeb08fc1-2fc1-4141-bc8e-f758f183a822",
-            description="Adds a new entry to a list. The entry can be of any type. If no list is provided, a new one is created.",
-            categories={BlockCategory.BASIC},
-            input_schema=AddToListBlock.Input,
-            output_schema=AddToListBlock.Output,
-            test_input=[
-                {
-                    "list": [1, "string", {"existing_key": "existing_value"}],
-                    "entry": {"new_key": "new_value"},
-                    "position": 1,
-                },
-                {"entry": "first_entry"},
-                {"list": ["a", "b", "c"], "entry": "d"},
-                {
-                    "entry": "e",
-                    "entries": ["f", "g"],
-                    "list": ["a", "b"],
-                    "position": 1,
-                },
-            ],
-            test_output=[
-                (
-                    "updated_list",
-                    [
-                        1,
-                        {"new_key": "new_value"},
-                        "string",
-                        {"existing_key": "existing_value"},
-                    ],
-                ),
-                ("updated_list", ["first_entry"]),
-                ("updated_list", ["a", "b", "c", "d"]),
-                ("updated_list", ["a", "f", "g", "e", "b"]),
-            ],
-        )
-
-    def run(self, input_data: Input, **kwargs) -> BlockOutput:
-        entries_added = input_data.entries.copy()
-        if input_data.entry:
-            entries_added.append(input_data.entry)
-
-        updated_list = input_data.list.copy()
-        if (pos := input_data.position) is not None:
-            updated_list = updated_list[:pos] + entries_added + updated_list[pos:]
-        else:
-            updated_list += entries_added
-
-        yield "updated_list", updated_list
-
-
-class FindInListBlock(Block):
-    class Input(BlockSchema):
-        list: List[Any] = SchemaField(description="The list to search in.")
-        value: Any = SchemaField(description="The value to search for.")
-
-    class Output(BlockSchema):
-        index: int = SchemaField(description="The index of the value in the list.")
-        found: bool = SchemaField(
-            description="Whether the value was found in the list."
-        )
-        not_found_value: Any = SchemaField(
-            description="The value that was not found in the list."
-        )
-
-    def __init__(self):
-        super().__init__(
-            id="5e2c6d0a-1e37-489f-b1d0-8e1812b23333",
-            description="Finds the index of the value in the list.",
-            categories={BlockCategory.BASIC},
-            input_schema=FindInListBlock.Input,
-            output_schema=FindInListBlock.Output,
-            test_input=[
-                {"list": [1, 2, 3, 4, 5], "value": 3},
-                {"list": [1, 2, 3, 4, 5], "value": 6},
-            ],
-            test_output=[
-                ("index", 2),
-                ("found", True),
-                ("found", False),
-                ("not_found_value", 6),
-            ],
-        )
-
-    def run(self, input_data: Input, **kwargs) -> BlockOutput:
-        try:
-            yield "index", input_data.list.index(input_data.value)
-            yield "found", True
-        except ValueError:
-            yield "found", False
-            yield "not_found_value", input_data.value
+    async def run(self, input_data: Input, **kwargs) -> BlockOutput:
+        yield "output", input_data.text
+        yield "status", "printed"
 
 
 class NoteBlock(Block):
@@ -369,108 +139,10 @@ 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
 
 
-class CreateDictionaryBlock(Block):
-    class Input(BlockSchema):
-        values: dict[str, Any] = SchemaField(
-            description="Key-value pairs to create the dictionary with",
-            placeholder="e.g., {'name': 'Alice', 'age': 25}",
-        )
-
-    class Output(BlockSchema):
-        dictionary: dict[str, Any] = SchemaField(
-            description="The created dictionary containing the specified key-value pairs"
-        )
-        error: str = SchemaField(
-            description="Error message if dictionary creation failed"
-        )
-
-    def __init__(self):
-        super().__init__(
-            id="b924ddf4-de4f-4b56-9a85-358930dcbc91",
-            description="Creates a dictionary with the specified key-value pairs. Use this when you know all the values you want to add upfront.",
-            categories={BlockCategory.DATA},
-            input_schema=CreateDictionaryBlock.Input,
-            output_schema=CreateDictionaryBlock.Output,
-            test_input=[
-                {
-                    "values": {"name": "Alice", "age": 25, "city": "New York"},
-                },
-                {
-                    "values": {"numbers": [1, 2, 3], "active": True, "score": 95.5},
-                },
-            ],
-            test_output=[
-                (
-                    "dictionary",
-                    {"name": "Alice", "age": 25, "city": "New York"},
-                ),
-                (
-                    "dictionary",
-                    {"numbers": [1, 2, 3], "active": True, "score": 95.5},
-                ),
-            ],
-        )
-
-    def run(self, input_data: Input, **kwargs) -> BlockOutput:
-        try:
-            # The values are already validated by Pydantic schema
-            yield "dictionary", input_data.values
-        except Exception as e:
-            yield "error", f"Failed to create dictionary: {str(e)}"
-
-
-class CreateListBlock(Block):
-    class Input(BlockSchema):
-        values: List[Any] = SchemaField(
-            description="A list of values to be combined into a new list.",
-            placeholder="e.g., ['Alice', 25, True]",
-        )
-
-    class Output(BlockSchema):
-        list: List[Any] = SchemaField(
-            description="The created list containing the specified values."
-        )
-        error: str = SchemaField(description="Error message if list creation failed.")
-
-    def __init__(self):
-        super().__init__(
-            id="a912d5c7-6e00-4542-b2a9-8034136930e4",
-            description="Creates a list with the specified values. Use this when you know all the values you want to add upfront.",
-            categories={BlockCategory.DATA},
-            input_schema=CreateListBlock.Input,
-            output_schema=CreateListBlock.Output,
-            test_input=[
-                {
-                    "values": ["Alice", 25, True],
-                },
-                {
-                    "values": [1, 2, 3, "four", {"key": "value"}],
-                },
-            ],
-            test_output=[
-                (
-                    "list",
-                    ["Alice", 25, True],
-                ),
-                (
-                    "list",
-                    [1, 2, 3, "four", {"key": "value"}],
-                ),
-            ],
-        )
-
-    def run(self, input_data: Input, **kwargs) -> BlockOutput:
-        try:
-            # The values are already validated by Pydantic schema
-            yield "list", input_data.values
-        except Exception as e:
-            yield "error", f"Failed to create list: {str(e)}"
-
-
 class TypeOptions(enum.Enum):
     STRING = "string"
     NUMBER = "number"
@@ -488,6 +160,7 @@ class UniversalTypeConverterBlock(Block):
 
     class Output(BlockSchema):
         value: Any = SchemaField(description="The converted value.")
+        error: str = SchemaField(description="Error message if conversion failed.")
 
     def __init__(self):
         super().__init__(
@@ -498,7 +171,7 @@ 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

@@ -3,6 +3,7 @@ from typing import Any
 
 from backend.data.block import Block, BlockCategory, BlockOutput, BlockSchema
 from backend.data.model import SchemaField
+from backend.util.type import convert
 
 
 class ComparisonOperator(Enum):
@@ -70,7 +71,7 @@ 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
@@ -163,7 +164,7 @@ class IfInputMatchesBlock(Block):
                 },
                 {
                     "input": 10,
-                    "value": None,
+                    "value": "None",
                     "yes_value": "Yes",
                     "no_value": "No",
                 },
@@ -180,8 +181,24 @@ class IfInputMatchesBlock(Block):
             ],
         )
 
-    def run(self, input_data: Input, **kwargs) -> BlockOutput:
-        if input_data.input == input_data.value or input_data.input is input_data.value:
+    async def run(self, input_data: Input, **kwargs) -> BlockOutput:
+
+        # If input_data.value is not matching input_data.input, convert value to type of input
+        if (
+            input_data.input != input_data.value
+            and input_data.input is not input_data.value
+        ):
+            try:
+                # Only attempt conversion if input is not None and value is not None
+                if input_data.input is not None and input_data.value is not None:
+                    input_type = type(input_data.input)
+                    # Avoid converting if input_type is Any or object
+                    if input_type not in (Any, object):
+                        input_data.value = convert(input_data.value, input_type)
+            except Exception:
+                pass  # If conversion fails, just leave value as is
+
+        if input_data.input == input_data.value:
             yield "result", True
             yield "yes_output", input_data.yes_value
         else:

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
@@ -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,
@@ -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

@@ -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/data_manipulation.py

@@ -0,0 +1,652 @@
+from typing import Any, List
+
+from backend.data.block import Block, BlockCategory, BlockOutput, BlockSchema
+from backend.data.model import SchemaField
+from backend.util.json import loads
+from backend.util.mock import MockObject
+
+# =============================================================================
+# Dictionary Manipulation Blocks
+# =============================================================================
+
+
+class CreateDictionaryBlock(Block):
+    class Input(BlockSchema):
+        values: dict[str, Any] = SchemaField(
+            description="Key-value pairs to create the dictionary with",
+            placeholder="e.g., {'name': 'Alice', 'age': 25}",
+        )
+
+    class Output(BlockSchema):
+        dictionary: dict[str, Any] = SchemaField(
+            description="The created dictionary containing the specified key-value pairs"
+        )
+        error: str = SchemaField(
+            description="Error message if dictionary creation failed"
+        )
+
+    def __init__(self):
+        super().__init__(
+            id="b924ddf4-de4f-4b56-9a85-358930dcbc91",
+            description="Creates a dictionary with the specified key-value pairs. Use this when you know all the values you want to add upfront.",
+            categories={BlockCategory.DATA},
+            input_schema=CreateDictionaryBlock.Input,
+            output_schema=CreateDictionaryBlock.Output,
+            test_input=[
+                {
+                    "values": {"name": "Alice", "age": 25, "city": "New York"},
+                },
+                {
+                    "values": {"numbers": [1, 2, 3], "active": True, "score": 95.5},
+                },
+            ],
+            test_output=[
+                (
+                    "dictionary",
+                    {"name": "Alice", "age": 25, "city": "New York"},
+                ),
+                (
+                    "dictionary",
+                    {"numbers": [1, 2, 3], "active": True, "score": 95.5},
+                ),
+            ],
+        )
+
+    async def run(self, input_data: Input, **kwargs) -> BlockOutput:
+        try:
+            # The values are already validated by Pydantic schema
+            yield "dictionary", input_data.values
+        except Exception as e:
+            yield "error", f"Failed to create dictionary: {str(e)}"
+
+
+class AddToDictionaryBlock(Block):
+    class Input(BlockSchema):
+        dictionary: dict[Any, Any] = SchemaField(
+            default_factory=dict,
+            description="The dictionary to add the entry to. If not provided, a new dictionary will be created.",
+        )
+        key: str = SchemaField(
+            default="",
+            description="The key for the new entry.",
+            placeholder="new_key",
+            advanced=False,
+        )
+        value: Any = SchemaField(
+            default=None,
+            description="The value for the new entry.",
+            placeholder="new_value",
+            advanced=False,
+        )
+        entries: dict[Any, Any] = SchemaField(
+            default_factory=dict,
+            description="The entries to add to the dictionary. This is the batch version of the `key` and `value` fields.",
+            advanced=True,
+        )
+
+    class Output(BlockSchema):
+        updated_dictionary: dict = SchemaField(
+            description="The dictionary with the new entry added."
+        )
+        error: str = SchemaField(description="Error message if the operation failed.")
+
+    def __init__(self):
+        super().__init__(
+            id="31d1064e-7446-4693-a7d4-65e5ca1180d1",
+            description="Adds a new key-value pair to a dictionary. If no dictionary is provided, a new one is created.",
+            categories={BlockCategory.BASIC},
+            input_schema=AddToDictionaryBlock.Input,
+            output_schema=AddToDictionaryBlock.Output,
+            test_input=[
+                {
+                    "dictionary": {"existing_key": "existing_value"},
+                    "key": "new_key",
+                    "value": "new_value",
+                },
+                {"key": "first_key", "value": "first_value"},
+                {
+                    "dictionary": {"existing_key": "existing_value"},
+                    "entries": {"new_key": "new_value", "first_key": "first_value"},
+                },
+            ],
+            test_output=[
+                (
+                    "updated_dictionary",
+                    {"existing_key": "existing_value", "new_key": "new_value"},
+                ),
+                ("updated_dictionary", {"first_key": "first_value"}),
+                (
+                    "updated_dictionary",
+                    {
+                        "existing_key": "existing_value",
+                        "new_key": "new_value",
+                        "first_key": "first_value",
+                    },
+                ),
+            ],
+        )
+
+    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:
+            updated_dict[input_data.key] = input_data.value
+
+        for key, value in input_data.entries.items():
+            updated_dict[key] = value
+
+        yield "updated_dictionary", updated_dict
+
+
+class FindInDictionaryBlock(Block):
+    class Input(BlockSchema):
+        input: Any = SchemaField(description="Dictionary to lookup from")
+        key: str | int = SchemaField(description="Key to lookup in the dictionary")
+
+    class Output(BlockSchema):
+        output: Any = SchemaField(description="Value found for the given key")
+        missing: Any = SchemaField(
+            description="Value of the input that missing the key"
+        )
+
+    def __init__(self):
+        super().__init__(
+            id="0e50422c-6dee-4145-83d6-3a5a392f65de",
+            description="Lookup the given key in the input dictionary/object/list and return the value.",
+            input_schema=FindInDictionaryBlock.Input,
+            output_schema=FindInDictionaryBlock.Output,
+            test_input=[
+                {"input": {"apple": 1, "banana": 2, "cherry": 3}, "key": "banana"},
+                {"input": {"x": 10, "y": 20, "z": 30}, "key": "w"},
+                {"input": [1, 2, 3], "key": 1},
+                {"input": [1, 2, 3], "key": 3},
+                {"input": MockObject(value="!!", key="key"), "key": "key"},
+                {"input": [{"k1": "v1"}, {"k2": "v2"}, {"k1": "v3"}], "key": "k1"},
+            ],
+            test_output=[
+                ("output", 2),
+                ("missing", {"x": 10, "y": 20, "z": 30}),
+                ("output", 2),
+                ("missing", [1, 2, 3]),
+                ("output", "key"),
+                ("output", ["v1", "v3"]),
+            ],
+            categories={BlockCategory.BASIC},
+        )
+
+    async def run(self, input_data: Input, **kwargs) -> BlockOutput:
+        obj = input_data.input
+        key = input_data.key
+
+        if isinstance(obj, str):
+            obj = loads(obj)
+
+        if isinstance(obj, dict) and key in obj:
+            yield "output", obj[key]
+        elif isinstance(obj, list) and isinstance(key, int) and 0 <= key < len(obj):
+            yield "output", obj[key]
+        elif isinstance(obj, list) and isinstance(key, str):
+            if len(obj) == 0:
+                yield "output", []
+            elif isinstance(obj[0], dict) and key in obj[0]:
+                yield "output", [item[key] for item in obj if key in item]
+            else:
+                yield "output", [getattr(val, key) for val in obj if hasattr(val, key)]
+        elif isinstance(obj, object) and isinstance(key, str) and hasattr(obj, key):
+            yield "output", getattr(obj, key)
+        else:
+            yield "missing", input_data.input
+
+
+class RemoveFromDictionaryBlock(Block):
+    class Input(BlockSchema):
+        dictionary: dict[Any, Any] = SchemaField(
+            description="The dictionary to modify."
+        )
+        key: str | int = SchemaField(description="Key to remove from the dictionary.")
+        return_value: bool = SchemaField(
+            default=False, description="Whether to return the removed value."
+        )
+
+    class Output(BlockSchema):
+        updated_dictionary: dict[Any, Any] = SchemaField(
+            description="The dictionary after removal."
+        )
+        removed_value: Any = SchemaField(description="The removed value if requested.")
+        error: str = SchemaField(description="Error message if the operation failed.")
+
+    def __init__(self):
+        super().__init__(
+            id="46afe2ea-c613-43f8-95ff-6692c3ef6876",
+            description="Removes a key-value pair from a dictionary.",
+            categories={BlockCategory.BASIC},
+            input_schema=RemoveFromDictionaryBlock.Input,
+            output_schema=RemoveFromDictionaryBlock.Output,
+            test_input=[
+                {
+                    "dictionary": {"a": 1, "b": 2, "c": 3},
+                    "key": "b",
+                    "return_value": True,
+                },
+                {"dictionary": {"x": "hello", "y": "world"}, "key": "x"},
+            ],
+            test_output=[
+                ("updated_dictionary", {"a": 1, "c": 3}),
+                ("removed_value", 2),
+                ("updated_dictionary", {"y": "world"}),
+            ],
+        )
+
+    async def run(self, input_data: Input, **kwargs) -> BlockOutput:
+        updated_dict = input_data.dictionary.copy()
+        try:
+            removed_value = updated_dict.pop(input_data.key)
+            yield "updated_dictionary", updated_dict
+            if input_data.return_value:
+                yield "removed_value", removed_value
+        except KeyError:
+            yield "error", f"Key '{input_data.key}' not found in dictionary"
+
+
+class ReplaceDictionaryValueBlock(Block):
+    class Input(BlockSchema):
+        dictionary: dict[Any, Any] = SchemaField(
+            description="The dictionary to modify."
+        )
+        key: str | int = SchemaField(description="Key to replace the value for.")
+        value: Any = SchemaField(description="The new value for the given key.")
+
+    class Output(BlockSchema):
+        updated_dictionary: dict[Any, Any] = SchemaField(
+            description="The dictionary after replacement."
+        )
+        old_value: Any = SchemaField(description="The value that was replaced.")
+        error: str = SchemaField(description="Error message if the operation failed.")
+
+    def __init__(self):
+        super().__init__(
+            id="27e31876-18b6-44f3-ab97-f6226d8b3889",
+            description="Replaces the value for a specified key in a dictionary.",
+            categories={BlockCategory.BASIC},
+            input_schema=ReplaceDictionaryValueBlock.Input,
+            output_schema=ReplaceDictionaryValueBlock.Output,
+            test_input=[
+                {"dictionary": {"a": 1, "b": 2, "c": 3}, "key": "b", "value": 99},
+                {
+                    "dictionary": {"x": "hello", "y": "world"},
+                    "key": "y",
+                    "value": "universe",
+                },
+            ],
+            test_output=[
+                ("updated_dictionary", {"a": 1, "b": 99, "c": 3}),
+                ("old_value", 2),
+                ("updated_dictionary", {"x": "hello", "y": "universe"}),
+                ("old_value", "world"),
+            ],
+        )
+
+    async def run(self, input_data: Input, **kwargs) -> BlockOutput:
+        updated_dict = input_data.dictionary.copy()
+        try:
+            old_value = updated_dict[input_data.key]
+            updated_dict[input_data.key] = input_data.value
+            yield "updated_dictionary", updated_dict
+            yield "old_value", old_value
+        except KeyError:
+            yield "error", f"Key '{input_data.key}' not found in dictionary"
+
+
+class DictionaryIsEmptyBlock(Block):
+    class Input(BlockSchema):
+        dictionary: dict[Any, Any] = SchemaField(description="The dictionary to check.")
+
+    class Output(BlockSchema):
+        is_empty: bool = SchemaField(description="True if the dictionary is empty.")
+
+    def __init__(self):
+        super().__init__(
+            id="a3cf3f64-6bb9-4cc6-9900-608a0b3359b0",
+            description="Checks if a dictionary is empty.",
+            categories={BlockCategory.BASIC},
+            input_schema=DictionaryIsEmptyBlock.Input,
+            output_schema=DictionaryIsEmptyBlock.Output,
+            test_input=[{"dictionary": {}}, {"dictionary": {"a": 1}}],
+            test_output=[("is_empty", True), ("is_empty", False)],
+        )
+
+    async def run(self, input_data: Input, **kwargs) -> BlockOutput:
+        yield "is_empty", len(input_data.dictionary) == 0
+
+
+# =============================================================================
+# List Manipulation Blocks
+# =============================================================================
+
+
+class CreateListBlock(Block):
+    class Input(BlockSchema):
+        values: List[Any] = SchemaField(
+            description="A list of values to be combined into a new list.",
+            placeholder="e.g., ['Alice', 25, True]",
+        )
+
+    class Output(BlockSchema):
+        list: List[Any] = SchemaField(
+            description="The created list containing the specified values."
+        )
+        error: str = SchemaField(description="Error message if list creation failed.")
+
+    def __init__(self):
+        super().__init__(
+            id="a912d5c7-6e00-4542-b2a9-8034136930e4",
+            description="Creates a list with the specified values. Use this when you know all the values you want to add upfront.",
+            categories={BlockCategory.DATA},
+            input_schema=CreateListBlock.Input,
+            output_schema=CreateListBlock.Output,
+            test_input=[
+                {
+                    "values": ["Alice", 25, True],
+                },
+                {
+                    "values": [1, 2, 3, "four", {"key": "value"}],
+                },
+            ],
+            test_output=[
+                (
+                    "list",
+                    ["Alice", 25, True],
+                ),
+                (
+                    "list",
+                    [1, 2, 3, "four", {"key": "value"}],
+                ),
+            ],
+        )
+
+    async def run(self, input_data: Input, **kwargs) -> BlockOutput:
+        try:
+            yield "list", input_data.values
+        except Exception as e:
+            yield "error", f"Failed to create list: {str(e)}"
+
+
+class AddToListBlock(Block):
+    class Input(BlockSchema):
+        list: List[Any] = SchemaField(
+            default_factory=list,
+            advanced=False,
+            description="The list to add the entry to. If not provided, a new list will be created.",
+        )
+        entry: Any = SchemaField(
+            description="The entry to add to the list. Can be of any type (string, int, dict, etc.).",
+            advanced=False,
+            default=None,
+        )
+        entries: List[Any] = SchemaField(
+            default_factory=lambda: list(),
+            description="The entries to add to the list. This is the batch version of the `entry` field.",
+            advanced=True,
+        )
+        position: int | None = SchemaField(
+            default=None,
+            description="The position to insert the new entry. If not provided, the entry will be appended to the end of the list.",
+        )
+
+    class Output(BlockSchema):
+        updated_list: List[Any] = SchemaField(
+            description="The list with the new entry added."
+        )
+        error: str = SchemaField(description="Error message if the operation failed.")
+
+    def __init__(self):
+        super().__init__(
+            id="aeb08fc1-2fc1-4141-bc8e-f758f183a822",
+            description="Adds a new entry to a list. The entry can be of any type. If no list is provided, a new one is created.",
+            categories={BlockCategory.BASIC},
+            input_schema=AddToListBlock.Input,
+            output_schema=AddToListBlock.Output,
+            test_input=[
+                {
+                    "list": [1, "string", {"existing_key": "existing_value"}],
+                    "entry": {"new_key": "new_value"},
+                    "position": 1,
+                },
+                {"entry": "first_entry"},
+                {"list": ["a", "b", "c"], "entry": "d"},
+                {
+                    "entry": "e",
+                    "entries": ["f", "g"],
+                    "list": ["a", "b"],
+                    "position": 1,
+                },
+            ],
+            test_output=[
+                (
+                    "updated_list",
+                    [
+                        1,
+                        {"new_key": "new_value"},
+                        "string",
+                        {"existing_key": "existing_value"},
+                    ],
+                ),
+                ("updated_list", ["first_entry"]),
+                ("updated_list", ["a", "b", "c", "d"]),
+                ("updated_list", ["a", "f", "g", "e", "b"]),
+            ],
+        )
+
+    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)
+
+        updated_list = input_data.list.copy()
+        if (pos := input_data.position) is not None:
+            updated_list = updated_list[:pos] + entries_added + updated_list[pos:]
+        else:
+            updated_list += entries_added
+
+        yield "updated_list", updated_list
+
+
+class FindInListBlock(Block):
+    class Input(BlockSchema):
+        list: List[Any] = SchemaField(description="The list to search in.")
+        value: Any = SchemaField(description="The value to search for.")
+
+    class Output(BlockSchema):
+        index: int = SchemaField(description="The index of the value in the list.")
+        found: bool = SchemaField(
+            description="Whether the value was found in the list."
+        )
+        not_found_value: Any = SchemaField(
+            description="The value that was not found in the list."
+        )
+
+    def __init__(self):
+        super().__init__(
+            id="5e2c6d0a-1e37-489f-b1d0-8e1812b23333",
+            description="Finds the index of the value in the list.",
+            categories={BlockCategory.BASIC},
+            input_schema=FindInListBlock.Input,
+            output_schema=FindInListBlock.Output,
+            test_input=[
+                {"list": [1, 2, 3, 4, 5], "value": 3},
+                {"list": [1, 2, 3, 4, 5], "value": 6},
+            ],
+            test_output=[
+                ("index", 2),
+                ("found", True),
+                ("found", False),
+                ("not_found_value", 6),
+            ],
+        )
+
+    async def run(self, input_data: Input, **kwargs) -> BlockOutput:
+        try:
+            yield "index", input_data.list.index(input_data.value)
+            yield "found", True
+        except ValueError:
+            yield "found", False
+            yield "not_found_value", input_data.value
+
+
+class GetListItemBlock(Block):
+    class Input(BlockSchema):
+        list: List[Any] = SchemaField(description="The list to get the item from.")
+        index: int = SchemaField(
+            description="The 0-based index of the item (supports negative indices)."
+        )
+
+    class Output(BlockSchema):
+        item: Any = SchemaField(description="The item at the specified index.")
+        error: str = SchemaField(description="Error message if the operation failed.")
+
+    def __init__(self):
+        super().__init__(
+            id="262ca24c-1025-43cf-a578-534e23234e97",
+            description="Returns the element at the given index.",
+            categories={BlockCategory.BASIC},
+            input_schema=GetListItemBlock.Input,
+            output_schema=GetListItemBlock.Output,
+            test_input=[
+                {"list": [1, 2, 3], "index": 1},
+                {"list": [1, 2, 3], "index": -1},
+            ],
+            test_output=[
+                ("item", 2),
+                ("item", 3),
+            ],
+        )
+
+    async def run(self, input_data: Input, **kwargs) -> BlockOutput:
+        try:
+            yield "item", input_data.list[input_data.index]
+        except IndexError:
+            yield "error", "Index out of range"
+
+
+class RemoveFromListBlock(Block):
+    class Input(BlockSchema):
+        list: List[Any] = SchemaField(description="The list to modify.")
+        value: Any = SchemaField(
+            default=None, description="Value to remove from the list."
+        )
+        index: int | None = SchemaField(
+            default=None,
+            description="Index of the item to pop (supports negative indices).",
+        )
+        return_item: bool = SchemaField(
+            default=False, description="Whether to return the removed item."
+        )
+
+    class Output(BlockSchema):
+        updated_list: List[Any] = SchemaField(description="The list after removal.")
+        removed_item: Any = SchemaField(description="The removed item if requested.")
+        error: str = SchemaField(description="Error message if the operation failed.")
+
+    def __init__(self):
+        super().__init__(
+            id="d93c5a93-ac7e-41c1-ae5c-ef67e6e9b826",
+            description="Removes an item from a list by value or index.",
+            categories={BlockCategory.BASIC},
+            input_schema=RemoveFromListBlock.Input,
+            output_schema=RemoveFromListBlock.Output,
+            test_input=[
+                {"list": [1, 2, 3], "index": 1, "return_item": True},
+                {"list": ["a", "b", "c"], "value": "b"},
+            ],
+            test_output=[
+                ("updated_list", [1, 3]),
+                ("removed_item", 2),
+                ("updated_list", ["a", "c"]),
+            ],
+        )
+
+    async def run(self, input_data: Input, **kwargs) -> BlockOutput:
+        lst = input_data.list.copy()
+        removed = None
+        try:
+            if input_data.index is not None:
+                removed = lst.pop(input_data.index)
+            elif input_data.value is not None:
+                lst.remove(input_data.value)
+                removed = input_data.value
+            else:
+                raise ValueError("No index or value provided for removal")
+        except (IndexError, ValueError):
+            yield "error", "Index or value not found"
+            return
+
+        yield "updated_list", lst
+        if input_data.return_item:
+            yield "removed_item", removed
+
+
+class ReplaceListItemBlock(Block):
+    class Input(BlockSchema):
+        list: List[Any] = SchemaField(description="The list to modify.")
+        index: int = SchemaField(
+            description="Index of the item to replace (supports negative indices)."
+        )
+        value: Any = SchemaField(description="The new value for the given index.")
+
+    class Output(BlockSchema):
+        updated_list: List[Any] = SchemaField(description="The list after replacement.")
+        old_item: Any = SchemaField(description="The item that was replaced.")
+        error: str = SchemaField(description="Error message if the operation failed.")
+
+    def __init__(self):
+        super().__init__(
+            id="fbf62922-bea1-4a3d-8bac-23587f810b38",
+            description="Replaces an item at the specified index.",
+            categories={BlockCategory.BASIC},
+            input_schema=ReplaceListItemBlock.Input,
+            output_schema=ReplaceListItemBlock.Output,
+            test_input=[
+                {"list": [1, 2, 3], "index": 1, "value": 99},
+                {"list": ["a", "b"], "index": -1, "value": "c"},
+            ],
+            test_output=[
+                ("updated_list", [1, 99, 3]),
+                ("old_item", 2),
+                ("updated_list", ["a", "c"]),
+                ("old_item", "b"),
+            ],
+        )
+
+    async def run(self, input_data: Input, **kwargs) -> BlockOutput:
+        lst = input_data.list.copy()
+        try:
+            old = lst[input_data.index]
+            lst[input_data.index] = input_data.value
+        except IndexError:
+            yield "error", "Index out of range"
+            return
+
+        yield "updated_list", lst
+        yield "old_item", old
+
+
+class ListIsEmptyBlock(Block):
+    class Input(BlockSchema):
+        list: List[Any] = SchemaField(description="The list to check.")
+
+    class Output(BlockSchema):
+        is_empty: bool = SchemaField(description="True if the list is empty.")
+
+    def __init__(self):
+        super().__init__(
+            id="896ed73b-27d0-41be-813c-c1c1dc856c03",
+            description="Checks if a list is empty.",
+            categories={BlockCategory.BASIC},
+            input_schema=ListIsEmptyBlock.Input,
+            output_schema=ListIsEmptyBlock.Output,
+            test_input=[{"list": []}, {"list": [1]}],
+            test_output=[("is_empty", True), ("is_empty", False)],
+        )
+
+    async def run(self, input_data: Input, **kwargs) -> BlockOutput:
+        yield "is_empty", len(input_data.list) == 0

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):
@@ -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):
@@ -78,6 +78,9 @@ class ExaSearchBlock(Block):
             description="List of search results",
             default_factory=list,
         )
+        error: str = SchemaField(
+            description="Error message if the request failed",
+        )
 
     def __init__(self):
         super().__init__(
@@ -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
 
@@ -67,6 +67,7 @@ class ExaFindSimilarBlock(Block):
             description="List of similar documents with title, URL, published date, author, and score",
             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):
@@ -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 +1,183 @@
+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, store_media_file
+
+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": "data:image/png;base64,MQ==",
+                "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,
+        graph_exec_id: str,
+        **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_b64=(
+                await store_media_file(
+                    graph_exec_id=graph_exec_id,
+                    file=input_data.input_image,
+                    return_content=True,
+                )
+                if input_data.input_image
+                else None
+            ),
+            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_b64: Optional[str],
+        aspect_ratio: str,
+        seed: Optional[int],
+    ) -> MediaFileType:
+        client = ReplicateClient(api_token=api_key.get_secret_value())
+        input_params = {
+            "prompt": prompt,
+            "input_image": input_image_b64,
+            "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

@@ -46,6 +46,6 @@ class GenericWebhookTriggerBlock(Block):
             ],
         )
 
-    def run(self, input_data: Input, **kwargs) -> BlockOutput:
+    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 +245,55 @@ 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}")
+            status: str = file.get("status", "")
+            diff: str = file.get("patch", "")
+            if status != "removed":
+                is_filename: str = file.get("filename", "")
+                was_filename: str = (
+                    file.get("previous_filename", is_filename)
+                    if status != "added"
+                    else ""
+                )
+            else:
+                is_filename = ""
+                was_filename: str = file.get("filename", "")
+
+            patch_header = ""
+            if was_filename:
+                patch_header += f"--- {was_filename}\n"
+            if is_filename:
+                patch_header += f"+++ {is_filename}\n"
+            changes.append(patch_header + diff)
         return "\n\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 +302,7 @@ 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 +349,16 @@ 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 +366,7 @@ 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 +416,16 @@ 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 +433,7 @@ 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 +496,12 @@ 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 +509,18 @@ 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

@@ -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 +1,12 @@
+import asyncio
+from enum import Enum
+
 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,
@@ -14,6 +17,102 @@ from ._auth import (
     GoogleCredentialsInput,
 )
 
+settings = Settings()
+GOOGLE_SHEETS_DISABLED = (
+    not GOOGLE_OAUTH_IS_CONFIGURED
+    or settings.config.app_env == AppEnvironment.PRODUCTION
+)
+
+
+def parse_a1_notation(a1: str) -> tuple[str | None, str]:
+    """Split an A1‑notation string into *(sheet_name, cell_range)*.
+
+    Examples
+    --------
+    >>> parse_a1_notation("Sheet1!A1:B2")
+    ("Sheet1", "A1:B2")
+    >>> parse_a1_notation("A1:B2")
+    (None, "A1:B2")
+    """
+
+    if "!" in a1:
+        sheet, cell_range = a1.split("!", 1)
+        return sheet, cell_range
+    return None, a1
+
+
+def _first_sheet_meta(service, spreadsheet_id: str) -> tuple[str, int]:
+    """Return *(title, sheetId)* for the first sheet in *spreadsheet_id*."""
+
+    meta = (
+        service.spreadsheets()
+        .get(spreadsheetId=spreadsheet_id, includeGridData=False)
+        .execute()
+    )
+    first = meta["sheets"][0]["properties"]
+    return first["title"], first["sheetId"]
+
+
+def resolve_sheet_name(service, spreadsheet_id: str, sheet_name: str | None) -> str:
+    """Resolve *sheet_name*, falling back to the workbook's first sheet if empty."""
+
+    if sheet_name:
+        return sheet_name
+    title, _ = _first_sheet_meta(service, spreadsheet_id)
+    return title
+
+
+def sheet_id_by_name(service, spreadsheet_id: str, sheet_name: str) -> int | None:
+    """Return the *sheetId* for *sheet_name* (or `None` if not found)."""
+
+    meta = service.spreadsheets().get(spreadsheetId=spreadsheet_id).execute()
+    for sh in meta.get("sheets", []):
+        if sh.get("properties", {}).get("title") == sheet_name:
+            return sh["properties"]["sheetId"]
+    return None
+
+
+def _build_sheets_service(credentials: GoogleCredentials):
+    settings = Settings()
+    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("sheets", "v4", credentials=creds)
+
+
+class SheetOperation(str, Enum):
+    CREATE = "create"
+    DELETE = "delete"
+    COPY = "copy"
+
+
+class BatchOperationType(str, Enum):
+    UPDATE = "update"
+    CLEAR = "clear"
+
+
+class BatchOperation(BlockSchema):
+    type: BatchOperationType = SchemaField(
+        description="The type of operation to perform"
+    )
+    range: str = SchemaField(description="The A1 notation range for the operation")
+    values: list[list[str]] = SchemaField(
+        description="Values to update (only for UPDATE)", default=[]
+    )
+
 
 class GoogleSheetsReadBlock(Block):
     class Input(BlockSchema):
@@ -42,7 +141,7 @@ class GoogleSheetsReadBlock(Block):
             categories={BlockCategory.DATA},
             input_schema=GoogleSheetsReadBlock.Input,
             output_schema=GoogleSheetsReadBlock.Output,
-            disabled=not GOOGLE_OAUTH_IS_CONFIGURED,
+            disabled=GOOGLE_SHEETS_DISABLED,
             test_input={
                 "spreadsheet_id": "1BxiMVs0XRA5nFMdKvBdBZjgmUUqptlbs74OgvE2upms",
                 "range": "Sheet1!A1:B2",
@@ -66,32 +165,14 @@ 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)
-        yield "result", data
-
-    @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,
+        service = _build_sheets_service(credentials)
+        data = await asyncio.to_thread(
+            self._read_sheet, service, input_data.spreadsheet_id, input_data.range
         )
-        return build("sheets", "v4", credentials=creds)
+        yield "result", data
 
     def _read_sheet(self, service, spreadsheet_id: str, range: str) -> list[list[str]]:
         sheet = service.spreadsheets()
@@ -129,7 +210,7 @@ class GoogleSheetsWriteBlock(Block):
             categories={BlockCategory.DATA},
             input_schema=GoogleSheetsWriteBlock.Input,
             output_schema=GoogleSheetsWriteBlock.Output,
-            disabled=not GOOGLE_OAUTH_IS_CONFIGURED,
+            disabled=GOOGLE_SHEETS_DISABLED,
             test_input={
                 "spreadsheet_id": "1BxiMVs0XRA5nFMdKvBdBZjgmUUqptlbs74OgvE2upms",
                 "range": "Sheet1!A1:B2",
@@ -155,11 +236,12 @@ 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(
+        service = _build_sheets_service(credentials)
+        result = await asyncio.to_thread(
+            self._write_sheet,
             service,
             input_data.spreadsheet_id,
             input_data.range,
@@ -183,3 +265,790 @@ class GoogleSheetsWriteBlock(Block):
             .execute()
         )
         return result
+
+
+class GoogleSheetsAppendBlock(Block):
+    class Input(BlockSchema):
+        credentials: GoogleCredentialsInput = GoogleCredentialsField(
+            ["https://www.googleapis.com/auth/spreadsheets"]
+        )
+        spreadsheet_id: str = SchemaField(description="Spreadsheet ID")
+        sheet_name: str = SchemaField(
+            description="Optional sheet to append to (defaults to first sheet)",
+            default="",
+        )
+        values: list[list[str]] = SchemaField(description="Rows to append")
+
+    class Output(BlockSchema):
+        result: dict = SchemaField(description="Append API response")
+        error: str = SchemaField(description="Error message, if any")
+
+    def __init__(self):
+        super().__init__(
+            id="531d50c0-d6b9-4cf9-a013-7bf783d313c7",
+            description="Append data to a Google Sheet (sheet optional)",
+            categories={BlockCategory.DATA},
+            input_schema=GoogleSheetsAppendBlock.Input,
+            output_schema=GoogleSheetsAppendBlock.Output,
+            disabled=GOOGLE_SHEETS_DISABLED,
+            test_input={
+                "spreadsheet_id": "1BxiMVs0XRA5nFMdKvBdBZjgmUUqptlbs74OgvE2upms",
+                "values": [["Charlie", "95"]],
+                "credentials": TEST_CREDENTIALS_INPUT,
+            },
+            test_credentials=TEST_CREDENTIALS,
+            test_output=[
+                ("result", {"updatedCells": 2, "updatedColumns": 2, "updatedRows": 1}),
+            ],
+            test_mock={
+                "_append_sheet": lambda *args, **kwargs: {
+                    "updatedCells": 2,
+                    "updatedColumns": 2,
+                    "updatedRows": 1,
+                },
+            },
+        )
+
+    async def run(
+        self, input_data: Input, *, credentials: GoogleCredentials, **kwargs
+    ) -> BlockOutput:
+        service = _build_sheets_service(credentials)
+        result = await asyncio.to_thread(
+            self._append_sheet,
+            service,
+            input_data.spreadsheet_id,
+            input_data.sheet_name,
+            input_data.values,
+        )
+        yield "result", result
+
+    def _append_sheet(
+        self,
+        service,
+        spreadsheet_id: str,
+        sheet_name: str,
+        values: list[list[str]],
+    ) -> dict:
+        target_sheet = resolve_sheet_name(service, spreadsheet_id, sheet_name)
+        body = {"values": values}
+        return (
+            service.spreadsheets()
+            .values()
+            .append(
+                spreadsheetId=spreadsheet_id,
+                range=f"{target_sheet}!A:A",
+                valueInputOption="USER_ENTERED",
+                insertDataOption="INSERT_ROWS",
+                body=body,
+            )
+            .execute()
+        )
+
+
+class GoogleSheetsClearBlock(Block):
+    class Input(BlockSchema):
+        credentials: GoogleCredentialsInput = GoogleCredentialsField(
+            ["https://www.googleapis.com/auth/spreadsheets"]
+        )
+        spreadsheet_id: str = SchemaField(
+            description="The ID of the spreadsheet to clear",
+        )
+        range: str = SchemaField(
+            description="The A1 notation of the range to clear",
+        )
+
+    class Output(BlockSchema):
+        result: dict = SchemaField(
+            description="The result of the clear operation",
+        )
+        error: str = SchemaField(
+            description="Error message if any",
+        )
+
+    def __init__(self):
+        super().__init__(
+            id="84938266-0fc7-46e5-9369-adb0f6ae8015",
+            description="This block clears data from a specified range in a Google Sheets spreadsheet.",
+            categories={BlockCategory.DATA},
+            input_schema=GoogleSheetsClearBlock.Input,
+            output_schema=GoogleSheetsClearBlock.Output,
+            disabled=GOOGLE_SHEETS_DISABLED,
+            test_input={
+                "spreadsheet_id": "1BxiMVs0XRA5nFMdKvBdBZjgmUUqptlbs74OgvE2upms",
+                "range": "Sheet1!A1:B2",
+                "credentials": TEST_CREDENTIALS_INPUT,
+            },
+            test_credentials=TEST_CREDENTIALS,
+            test_output=[
+                ("result", {"clearedRange": "Sheet1!A1:B2"}),
+            ],
+            test_mock={
+                "_clear_range": lambda *args, **kwargs: {
+                    "clearedRange": "Sheet1!A1:B2"
+                },
+            },
+        )
+
+    async def run(
+        self, input_data: Input, *, credentials: GoogleCredentials, **kwargs
+    ) -> BlockOutput:
+        service = _build_sheets_service(credentials)
+        result = await asyncio.to_thread(
+            self._clear_range,
+            service,
+            input_data.spreadsheet_id,
+            input_data.range,
+        )
+        yield "result", result
+
+    def _clear_range(self, service, spreadsheet_id: str, range: str) -> dict:
+        result = (
+            service.spreadsheets()
+            .values()
+            .clear(spreadsheetId=spreadsheet_id, range=range)
+            .execute()
+        )
+        return result
+
+
+class GoogleSheetsMetadataBlock(Block):
+    class Input(BlockSchema):
+        credentials: GoogleCredentialsInput = GoogleCredentialsField(
+            ["https://www.googleapis.com/auth/spreadsheets.readonly"]
+        )
+        spreadsheet_id: str = SchemaField(
+            description="The ID of the spreadsheet to get metadata for",
+        )
+
+    class Output(BlockSchema):
+        result: dict = SchemaField(
+            description="The metadata of the spreadsheet including sheets info",
+        )
+        error: str = SchemaField(
+            description="Error message if any",
+        )
+
+    def __init__(self):
+        super().__init__(
+            id="6a0be6ee-7a0d-4c92-819b-500630846ad0",
+            description="This block retrieves metadata about a Google Sheets spreadsheet including sheet names and properties.",
+            categories={BlockCategory.DATA},
+            input_schema=GoogleSheetsMetadataBlock.Input,
+            output_schema=GoogleSheetsMetadataBlock.Output,
+            disabled=GOOGLE_SHEETS_DISABLED,
+            test_input={
+                "spreadsheet_id": "1BxiMVs0XRA5nFMdKvBdBZjgmUUqptlbs74OgvE2upms",
+                "credentials": TEST_CREDENTIALS_INPUT,
+            },
+            test_credentials=TEST_CREDENTIALS,
+            test_output=[
+                (
+                    "result",
+                    {
+                        "title": "Test Spreadsheet",
+                        "sheets": [{"title": "Sheet1", "sheetId": 0}],
+                    },
+                ),
+            ],
+            test_mock={
+                "_get_metadata": lambda *args, **kwargs: {
+                    "title": "Test Spreadsheet",
+                    "sheets": [{"title": "Sheet1", "sheetId": 0}],
+                },
+            },
+        )
+
+    async def run(
+        self, input_data: Input, *, credentials: GoogleCredentials, **kwargs
+    ) -> BlockOutput:
+        service = _build_sheets_service(credentials)
+        result = await asyncio.to_thread(
+            self._get_metadata,
+            service,
+            input_data.spreadsheet_id,
+        )
+        yield "result", result
+
+    def _get_metadata(self, service, spreadsheet_id: str) -> dict:
+        result = (
+            service.spreadsheets()
+            .get(spreadsheetId=spreadsheet_id, includeGridData=False)
+            .execute()
+        )
+        return {
+            "title": result.get("properties", {}).get("title"),
+            "sheets": [
+                {
+                    "title": sheet.get("properties", {}).get("title"),
+                    "sheetId": sheet.get("properties", {}).get("sheetId"),
+                    "gridProperties": sheet.get("properties", {}).get(
+                        "gridProperties", {}
+                    ),
+                }
+                for sheet in result.get("sheets", [])
+            ],
+        }
+
+
+class GoogleSheetsManageSheetBlock(Block):
+    class Input(BlockSchema):
+        credentials: GoogleCredentialsInput = GoogleCredentialsField(
+            ["https://www.googleapis.com/auth/spreadsheets"]
+        )
+        spreadsheet_id: str = SchemaField(description="Spreadsheet ID")
+        operation: SheetOperation = SchemaField(description="Operation to perform")
+        sheet_name: str = SchemaField(
+            description="Target sheet name (defaults to first sheet for delete)",
+            default="",
+        )
+        source_sheet_id: int = SchemaField(
+            description="Source sheet ID for copy", default=0
+        )
+        destination_sheet_name: str = SchemaField(
+            description="New sheet name for copy", default=""
+        )
+
+    class Output(BlockSchema):
+        result: dict = SchemaField(description="Operation result")
+        error: str = SchemaField(description="Error message, if any")
+
+    def __init__(self):
+        super().__init__(
+            id="7940189d-b137-4ef1-aa18-3dd9a5bde9f3",
+            description="Create, delete, or copy sheets (sheet optional)",
+            categories={BlockCategory.DATA},
+            input_schema=GoogleSheetsManageSheetBlock.Input,
+            output_schema=GoogleSheetsManageSheetBlock.Output,
+            disabled=GOOGLE_SHEETS_DISABLED,
+            test_input={
+                "spreadsheet_id": "1BxiMVs0XRA5nFMdKvBdBZjgmUUqptlbs74OgvE2upms",
+                "operation": SheetOperation.CREATE,
+                "sheet_name": "NewSheet",
+                "credentials": TEST_CREDENTIALS_INPUT,
+            },
+            test_credentials=TEST_CREDENTIALS,
+            test_output=[("result", {"success": True, "sheetId": 123})],
+            test_mock={
+                "_manage_sheet": lambda *args, **kwargs: {
+                    "success": True,
+                    "sheetId": 123,
+                }
+            },
+        )
+
+    async def run(
+        self, input_data: Input, *, credentials: GoogleCredentials, **kwargs
+    ) -> BlockOutput:
+        service = _build_sheets_service(credentials)
+        result = await asyncio.to_thread(
+            self._manage_sheet,
+            service,
+            input_data.spreadsheet_id,
+            input_data.operation,
+            input_data.sheet_name,
+            input_data.source_sheet_id,
+            input_data.destination_sheet_name,
+        )
+        yield "result", result
+
+    def _manage_sheet(
+        self,
+        service,
+        spreadsheet_id: str,
+        operation: SheetOperation,
+        sheet_name: str,
+        source_sheet_id: int,
+        destination_sheet_name: str,
+    ) -> dict:
+        requests = []
+
+        # Ensure a target sheet name when needed
+        target_name = resolve_sheet_name(service, spreadsheet_id, sheet_name)
+
+        if operation == SheetOperation.CREATE:
+            requests.append({"addSheet": {"properties": {"title": target_name}}})
+        elif operation == SheetOperation.DELETE:
+            sid = sheet_id_by_name(service, spreadsheet_id, target_name)
+            if sid is None:
+                return {"error": f"Sheet '{target_name}' not found"}
+            requests.append({"deleteSheet": {"sheetId": sid}})
+        elif operation == SheetOperation.COPY:
+            requests.append(
+                {
+                    "duplicateSheet": {
+                        "sourceSheetId": source_sheet_id,
+                        "newSheetName": destination_sheet_name
+                        or f"Copy of {source_sheet_id}",
+                    }
+                }
+            )
+        else:
+            return {"error": f"Unknown operation: {operation}"}
+
+        body = {"requests": requests}
+        result = (
+            service.spreadsheets()
+            .batchUpdate(spreadsheetId=spreadsheet_id, body=body)
+            .execute()
+        )
+        return {"success": True, "result": result}
+
+
+class GoogleSheetsBatchOperationsBlock(Block):
+    class Input(BlockSchema):
+        credentials: GoogleCredentialsInput = GoogleCredentialsField(
+            ["https://www.googleapis.com/auth/spreadsheets"]
+        )
+        spreadsheet_id: str = SchemaField(
+            description="The ID of the spreadsheet to perform batch operations on",
+        )
+        operations: list[BatchOperation] = SchemaField(
+            description="List of operations to perform",
+        )
+
+    class Output(BlockSchema):
+        result: dict = SchemaField(
+            description="The result of the batch operations",
+        )
+        error: str = SchemaField(
+            description="Error message if any",
+        )
+
+    def __init__(self):
+        super().__init__(
+            id="a4078584-6fe5-46e0-997e-d5126cdd112a",
+            description="This block performs multiple operations on a Google Sheets spreadsheet in a single batch request.",
+            categories={BlockCategory.DATA},
+            input_schema=GoogleSheetsBatchOperationsBlock.Input,
+            output_schema=GoogleSheetsBatchOperationsBlock.Output,
+            disabled=GOOGLE_SHEETS_DISABLED,
+            test_input={
+                "spreadsheet_id": "1BxiMVs0XRA5nFMdKvBdBZjgmUUqptlbs74OgvE2upms",
+                "operations": [
+                    {
+                        "type": BatchOperationType.UPDATE,
+                        "range": "A1:B1",
+                        "values": [["Header1", "Header2"]],
+                    },
+                    {
+                        "type": BatchOperationType.UPDATE,
+                        "range": "A2:B2",
+                        "values": [["Data1", "Data2"]],
+                    },
+                ],
+                "credentials": TEST_CREDENTIALS_INPUT,
+            },
+            test_credentials=TEST_CREDENTIALS,
+            test_output=[
+                ("result", {"totalUpdatedCells": 4, "replies": []}),
+            ],
+            test_mock={
+                "_batch_operations": lambda *args, **kwargs: {
+                    "totalUpdatedCells": 4,
+                    "replies": [],
+                },
+            },
+        )
+
+    async def run(
+        self, input_data: Input, *, credentials: GoogleCredentials, **kwargs
+    ) -> BlockOutput:
+        service = _build_sheets_service(credentials)
+        result = await asyncio.to_thread(
+            self._batch_operations,
+            service,
+            input_data.spreadsheet_id,
+            input_data.operations,
+        )
+        yield "result", result
+
+    def _batch_operations(
+        self, service, spreadsheet_id: str, operations: list[BatchOperation]
+    ) -> dict:
+        update_data = []
+        clear_ranges = []
+
+        for op in operations:
+            if op.type == BatchOperationType.UPDATE:
+                update_data.append(
+                    {
+                        "range": op.range,
+                        "values": op.values,
+                    }
+                )
+            elif op.type == BatchOperationType.CLEAR:
+                clear_ranges.append(op.range)
+
+        results = {}
+
+        # Perform updates if any
+        if update_data:
+            update_body = {
+                "valueInputOption": "USER_ENTERED",
+                "data": update_data,
+            }
+            update_result = (
+                service.spreadsheets()
+                .values()
+                .batchUpdate(spreadsheetId=spreadsheet_id, body=update_body)
+                .execute()
+            )
+            results["updateResult"] = update_result
+
+        # Perform clears if any
+        if clear_ranges:
+            clear_body = {"ranges": clear_ranges}
+            clear_result = (
+                service.spreadsheets()
+                .values()
+                .batchClear(spreadsheetId=spreadsheet_id, body=clear_body)
+                .execute()
+            )
+            results["clearResult"] = clear_result
+
+        return results
+
+
+class GoogleSheetsFindReplaceBlock(Block):
+    class Input(BlockSchema):
+        credentials: GoogleCredentialsInput = GoogleCredentialsField(
+            ["https://www.googleapis.com/auth/spreadsheets"]
+        )
+        spreadsheet_id: str = SchemaField(
+            description="The ID of the spreadsheet to perform find/replace on",
+        )
+        find_text: str = SchemaField(
+            description="The text to find",
+        )
+        replace_text: str = SchemaField(
+            description="The text to replace with",
+        )
+        sheet_id: int = SchemaField(
+            description="The ID of the specific sheet to search (optional, searches all sheets if not provided)",
+            default=-1,
+        )
+        match_case: bool = SchemaField(
+            description="Whether to match case",
+            default=False,
+        )
+        match_entire_cell: bool = SchemaField(
+            description="Whether to match entire cell",
+            default=False,
+        )
+
+    class Output(BlockSchema):
+        result: dict = SchemaField(
+            description="The result of the find/replace operation including number of replacements",
+        )
+        error: str = SchemaField(
+            description="Error message if any",
+        )
+
+    def __init__(self):
+        super().__init__(
+            id="accca760-8174-4656-b55e-5f0e82fee986",
+            description="This block finds and replaces text in a Google Sheets spreadsheet.",
+            categories={BlockCategory.DATA},
+            input_schema=GoogleSheetsFindReplaceBlock.Input,
+            output_schema=GoogleSheetsFindReplaceBlock.Output,
+            disabled=GOOGLE_SHEETS_DISABLED,
+            test_input={
+                "spreadsheet_id": "1BxiMVs0XRA5nFMdKvBdBZjgmUUqptlbs74OgvE2upms",
+                "find_text": "old_value",
+                "replace_text": "new_value",
+                "match_case": False,
+                "match_entire_cell": False,
+                "credentials": TEST_CREDENTIALS_INPUT,
+            },
+            test_credentials=TEST_CREDENTIALS,
+            test_output=[
+                ("result", {"occurrencesChanged": 5}),
+            ],
+            test_mock={
+                "_find_replace": lambda *args, **kwargs: {"occurrencesChanged": 5},
+            },
+        )
+
+    async def run(
+        self, input_data: Input, *, credentials: GoogleCredentials, **kwargs
+    ) -> BlockOutput:
+        service = _build_sheets_service(credentials)
+        result = await asyncio.to_thread(
+            self._find_replace,
+            service,
+            input_data.spreadsheet_id,
+            input_data.find_text,
+            input_data.replace_text,
+            input_data.sheet_id,
+            input_data.match_case,
+            input_data.match_entire_cell,
+        )
+        yield "result", result
+
+    def _find_replace(
+        self,
+        service,
+        spreadsheet_id: str,
+        find_text: str,
+        replace_text: str,
+        sheet_id: int,
+        match_case: bool,
+        match_entire_cell: bool,
+    ) -> dict:
+        find_replace_request = {
+            "find": find_text,
+            "replacement": replace_text,
+            "matchCase": match_case,
+            "matchEntireCell": match_entire_cell,
+        }
+
+        if sheet_id >= 0:
+            find_replace_request["sheetId"] = sheet_id
+
+        requests = [{"findReplace": find_replace_request}]
+        body = {"requests": requests}
+
+        result = (
+            service.spreadsheets()
+            .batchUpdate(spreadsheetId=spreadsheet_id, body=body)
+            .execute()
+        )
+
+        return result
+
+
+class GoogleSheetsFormatBlock(Block):
+    class Input(BlockSchema):
+        credentials: GoogleCredentialsInput = GoogleCredentialsField(
+            ["https://www.googleapis.com/auth/spreadsheets"]
+        )
+        spreadsheet_id: str = SchemaField(description="Spreadsheet ID")
+        range: str = SchemaField(description="A1 notation – sheet optional")
+        background_color: dict = SchemaField(default={})
+        text_color: dict = SchemaField(default={})
+        bold: bool = SchemaField(default=False)
+        italic: bool = SchemaField(default=False)
+        font_size: int = SchemaField(default=10)
+
+    class Output(BlockSchema):
+        result: dict = SchemaField(description="API response or success flag")
+        error: str = SchemaField(description="Error message, if any")
+
+    def __init__(self):
+        super().__init__(
+            id="270f2384-8089-4b5b-b2e3-fe2ea3d87c02",
+            description="Format a range in a Google Sheet (sheet optional)",
+            categories={BlockCategory.DATA},
+            input_schema=GoogleSheetsFormatBlock.Input,
+            output_schema=GoogleSheetsFormatBlock.Output,
+            disabled=GOOGLE_SHEETS_DISABLED,
+            test_input={
+                "spreadsheet_id": "1BxiMVs0XRA5nFMdKvBdBZjgmUUqptlbs74OgvE2upms",
+                "range": "A1:B2",
+                "background_color": {"red": 1.0, "green": 0.9, "blue": 0.9},
+                "bold": True,
+                "credentials": TEST_CREDENTIALS_INPUT,
+            },
+            test_credentials=TEST_CREDENTIALS,
+            test_output=[("result", {"success": True})],
+            test_mock={"_format_cells": lambda *args, **kwargs: {"success": True}},
+        )
+
+    async def run(
+        self, input_data: Input, *, credentials: GoogleCredentials, **kwargs
+    ) -> BlockOutput:
+        service = _build_sheets_service(credentials)
+        result = await asyncio.to_thread(
+            self._format_cells,
+            service,
+            input_data.spreadsheet_id,
+            input_data.range,
+            input_data.background_color,
+            input_data.text_color,
+            input_data.bold,
+            input_data.italic,
+            input_data.font_size,
+        )
+        if "error" in result:
+            yield "error", result["error"]
+        else:
+            yield "result", result
+
+    def _format_cells(
+        self,
+        service,
+        spreadsheet_id: str,
+        a1_range: str,
+        background_color: dict,
+        text_color: dict,
+        bold: bool,
+        italic: bool,
+        font_size: int,
+    ) -> dict:
+        sheet_name, cell_range = parse_a1_notation(a1_range)
+        sheet_name = resolve_sheet_name(service, spreadsheet_id, sheet_name)
+
+        sheet_id = sheet_id_by_name(service, spreadsheet_id, sheet_name)
+        if sheet_id is None:
+            return {"error": f"Sheet '{sheet_name}' not found"}
+
+        try:
+            start_cell, end_cell = cell_range.split(":")
+            start_col = ord(start_cell[0].upper()) - ord("A")
+            start_row = int(start_cell[1:]) - 1
+            end_col = ord(end_cell[0].upper()) - ord("A") + 1
+            end_row = int(end_cell[1:])
+        except (ValueError, IndexError):
+            return {"error": f"Invalid range format: {a1_range}"}
+
+        cell_format: dict = {"userEnteredFormat": {}}
+        if background_color:
+            cell_format["userEnteredFormat"]["backgroundColor"] = background_color
+
+        text_format: dict = {}
+        if text_color:
+            text_format["foregroundColor"] = text_color
+        if bold:
+            text_format["bold"] = True
+        if italic:
+            text_format["italic"] = True
+        if font_size != 10:
+            text_format["fontSize"] = font_size
+        if text_format:
+            cell_format["userEnteredFormat"]["textFormat"] = text_format
+
+        body = {
+            "requests": [
+                {
+                    "repeatCell": {
+                        "range": {
+                            "sheetId": sheet_id,
+                            "startRowIndex": start_row,
+                            "endRowIndex": end_row,
+                            "startColumnIndex": start_col,
+                            "endColumnIndex": end_col,
+                        },
+                        "cell": cell_format,
+                        "fields": "userEnteredFormat(backgroundColor,textFormat)",
+                    }
+                }
+            ]
+        }
+
+        service.spreadsheets().batchUpdate(
+            spreadsheetId=spreadsheet_id, body=body
+        ).execute()
+        return {"success": True}
+
+
+class GoogleSheetsCreateSpreadsheetBlock(Block):
+    class Input(BlockSchema):
+        credentials: GoogleCredentialsInput = GoogleCredentialsField(
+            ["https://www.googleapis.com/auth/spreadsheets"]
+        )
+        title: str = SchemaField(
+            description="The title of the new spreadsheet",
+        )
+        sheet_names: list[str] = SchemaField(
+            description="List of sheet names to create (optional, defaults to single 'Sheet1')",
+            default=["Sheet1"],
+        )
+
+    class Output(BlockSchema):
+        result: dict = SchemaField(
+            description="The result containing spreadsheet ID and URL",
+        )
+        spreadsheet_id: str = SchemaField(
+            description="The ID of the created spreadsheet",
+        )
+        spreadsheet_url: str = SchemaField(
+            description="The URL of the created spreadsheet",
+        )
+        error: str = SchemaField(
+            description="Error message if any",
+        )
+
+    def __init__(self):
+        super().__init__(
+            id="c8d4c0d3-c76e-4c2a-8c66-4119817ea3d1",
+            description="This block creates a new Google Sheets spreadsheet with specified sheets.",
+            categories={BlockCategory.DATA},
+            input_schema=GoogleSheetsCreateSpreadsheetBlock.Input,
+            output_schema=GoogleSheetsCreateSpreadsheetBlock.Output,
+            disabled=GOOGLE_SHEETS_DISABLED,
+            test_input={
+                "title": "Test Spreadsheet",
+                "sheet_names": ["Sheet1", "Data", "Summary"],
+                "credentials": TEST_CREDENTIALS_INPUT,
+            },
+            test_credentials=TEST_CREDENTIALS,
+            test_output=[
+                ("spreadsheet_id", "1BxiMVs0XRA5nFMdKvBdBZjgmUUqptlbs74OgvE2upms"),
+                (
+                    "spreadsheet_url",
+                    "https://docs.google.com/spreadsheets/d/1BxiMVs0XRA5nFMdKvBdBZjgmUUqptlbs74OgvE2upms/edit",
+                ),
+                ("result", {"success": True}),
+            ],
+            test_mock={
+                "_create_spreadsheet": lambda *args, **kwargs: {
+                    "spreadsheetId": "1BxiMVs0XRA5nFMdKvBdBZjgmUUqptlbs74OgvE2upms",
+                    "spreadsheetUrl": "https://docs.google.com/spreadsheets/d/1BxiMVs0XRA5nFMdKvBdBZjgmUUqptlbs74OgvE2upms/edit",
+                },
+            },
+        )
+
+    async def run(
+        self, input_data: Input, *, credentials: GoogleCredentials, **kwargs
+    ) -> BlockOutput:
+        service = _build_sheets_service(credentials)
+        result = await asyncio.to_thread(
+            self._create_spreadsheet,
+            service,
+            input_data.title,
+            input_data.sheet_names,
+        )
+
+        if "error" in result:
+            yield "error", result["error"]
+        else:
+            yield "spreadsheet_id", result["spreadsheetId"]
+            yield "spreadsheet_url", result["spreadsheetUrl"]
+            yield "result", {"success": True}
+
+    def _create_spreadsheet(self, service, title: str, sheet_names: list[str]) -> dict:
+        try:
+            # Create the initial spreadsheet
+            spreadsheet_body = {
+                "properties": {"title": title},
+                "sheets": [
+                    {
+                        "properties": {
+                            "title": sheet_names[0] if sheet_names else "Sheet1"
+                        }
+                    }
+                ],
+            }
+
+            result = service.spreadsheets().create(body=spreadsheet_body).execute()
+            spreadsheet_id = result["spreadsheetId"]
+            spreadsheet_url = result["spreadsheetUrl"]
+
+            # Add additional sheets if requested
+            if len(sheet_names) > 1:
+                requests = []
+                for sheet_name in sheet_names[1:]:
+                    requests.append({"addSheet": {"properties": {"title": sheet_name}}})
+
+                if requests:
+                    batch_body = {"requests": requests}
+                    service.spreadsheets().batchUpdate(
+                        spreadsheetId=spreadsheet_id, body=batch_body
+                    ).execute()
+
+            return {
+                "spreadsheetId": spreadsheet_id,
+                "spreadsheetUrl": spreadsheet_url,
+            }
+        except Exception as e:
+            return {"error": str(e)}

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

@@ -1,17 +1,56 @@
 import json
 import logging
 from enum import Enum
-from typing import Any
+from io import BytesIO
+from pathlib import Path
+from typing import Literal
 
-from requests.exceptions import HTTPError, RequestException
+import aiofiles
+from pydantic import SecretStr
 
 from backend.data.block import Block, BlockCategory, BlockOutput, BlockSchema
-from backend.data.model import SchemaField
-from backend.util.request import requests
+from backend.data.model import (
+    CredentialsField,
+    CredentialsMetaInput,
+    HostScopedCredentials,
+    SchemaField,
+)
+from backend.integrations.providers import ProviderName
+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__)
 
 
+# Host-scoped credentials for HTTP requests
+HttpCredentials = CredentialsMetaInput[
+    Literal[ProviderName.HTTP], Literal["host_scoped"]
+]
+
+
+TEST_CREDENTIALS = HostScopedCredentials(
+    id="01234567-89ab-cdef-0123-456789abcdef",
+    provider="http",
+    host="api.example.com",
+    headers={
+        "Authorization": SecretStr("Bearer test-token"),
+        "X-API-Key": SecretStr("test-api-key"),
+    },
+    title="Mock HTTP Host-Scoped Credentials",
+)
+TEST_CREDENTIALS_INPUT = {
+    "provider": TEST_CREDENTIALS.provider,
+    "id": TEST_CREDENTIALS.id,
+    "type": TEST_CREDENTIALS.type,
+    "title": TEST_CREDENTIALS.title,
+}
+
+
 class HttpMethod(Enum):
     GET = "GET"
     POST = "POST"
@@ -38,13 +77,21 @@ class SendWebRequestBlock(Block):
         )
         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 +102,161 @@ 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
+        elif 400 <= response.status < 500:
+            yield "client_error", result
+        else:
+            yield "server_error", 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
+class SendAuthenticatedWebRequestBlock(SendWebRequestBlock):
+    class Input(SendWebRequestBlock.Input):
+        credentials: HttpCredentials = CredentialsField(
+            description="HTTP host-scoped credentials for automatic header injection",
+            discriminator="url",
+        )
 
-        except RequestException as e:
-            # Handle other request-related exceptions
-            yield "error", str(e)
+    def __init__(self):
+        Block.__init__(
+            self,
+            id="fff86bcd-e001-4bad-a7f6-2eae4720c8dc",
+            description="Make an authenticated HTTP request with host-scoped credentials (JSON / form / multipart).",
+            categories={BlockCategory.OUTPUT},
+            input_schema=SendAuthenticatedWebRequestBlock.Input,
+            output_schema=SendWebRequestBlock.Output,
+            test_credentials=TEST_CREDENTIALS,
+        )
 
-        except Exception as e:
-            # Catch any other unexpected exceptions
-            yield "error", str(e)
+    async def run(  # type: ignore[override]
+        self,
+        input_data: Input,
+        *,
+        graph_exec_id: str,
+        credentials: HostScopedCredentials,
+        **kwargs,
+    ) -> BlockOutput:
+        # Create SendWebRequestBlock.Input from our input (removing credentials field)
+        base_input = SendWebRequestBlock.Input(
+            url=input_data.url,
+            method=input_data.method,
+            headers=input_data.headers,
+            json_format=input_data.json_format,
+            body=input_data.body,
+            files_name=input_data.files_name,
+            files=input_data.files,
+        )
+
+        # Apply host-scoped credentials to headers
+        extra_headers = {}
+        if credentials.matches_url(input_data.url):
+            logger.debug(
+                f"Applying host-scoped credentials {credentials.id} for URL {input_data.url}"
+            )
+            extra_headers.update(credentials.get_headers_dict())
+        else:
+            logger.warning(
+                f"Host-scoped credentials {credentials.id} do not match URL {input_data.url}"
+            )
+
+        # Merge with user-provided headers (user headers take precedence)
+        base_input.headers = {**extra_headers, **input_data.headers}
+
+        # Use parent class run method
+        async for output_name, output_data in super().run(
+            base_input, graph_exec_id=graph_exec_id, **kwargs
+        ):
+            yield output_name, output_data

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):
@@ -35,7 +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"
@@ -45,7 +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()
@@ -67,14 +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={
@@ -91,10 +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):
@@ -35,7 +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"
@@ -45,7 +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()
@@ -53,7 +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": [
@@ -68,13 +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={
@@ -91,10 +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):
@@ -42,7 +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"
@@ -66,7 +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"
@@ -80,7 +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

@@ -95,7 +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
 
@@ -186,7 +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.
@@ -413,6 +413,12 @@ class AgentFileInputBlock(AgentInputBlock):
             advanced=False,
             title="Default Value",
         )
+        base_64: bool = SchemaField(
+            description="Whether produce an output in base64 format (not recommended, you can pass the string path just fine accross blocks).",
+            default=False,
+            advanced=True,
+            title="Produce Base64 Output",
+        )
 
     class Output(AgentInputBlock.Output):
         result: str = SchemaField(description="File reference/path result.")
@@ -436,7 +442,7 @@ class AgentFileInputBlock(AgentInputBlock):
             ],
         )
 
-    def run(
+    async def run(
         self,
         input_data: Input,
         *,
@@ -446,12 +452,11 @@ class AgentFileInputBlock(AgentInputBlock):
         if not input_data.value:
             return
 
-        file_path = store_media_file(
+        yield "result", await store_media_file(
             graph_exec_id=graph_exec_id,
             file=input_data.value,
-            return_content=False,
+            return_content=input_data.base_64,
         )
-        yield "result", file_path
 
 
 class AgentDropdownInputBlock(AgentInputBlock):

autogpt_platform/backend/backend/blocks/iteration.py

@@ -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):
@@ -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

@@ -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

@@ -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

@@ -3,14 +3,13 @@ import logging
 from abc import ABC
 from enum import Enum, EnumMeta
 from json import JSONDecodeError
-from types import MappingProxyType
 from typing import Any, Iterable, List, Literal, NamedTuple, Optional
 
 import anthropic
 import ollama
 import openai
 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
@@ -23,23 +22,26 @@ from backend.data.model import (
 )
 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.prompt import compress_prompt, estimate_token_count
 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"]]
 
 TEST_CREDENTIALS = APIKeyCredentials(
-    id="ed55ac19-356e-4243-a6cb-bc599e9b716f",
+    id="769f6af7-820b-4d5d-9b7a-ab82bbc165f",
     provider="openai",
     api_key=SecretStr("mock-openai-api-key"),
     title="Mock OpenAI API key",
@@ -70,20 +72,7 @@ class ModelMetadata(NamedTuple):
 
 
 class LlmModelMeta(EnumMeta):
-    @property
-    def __members__(self) -> MappingProxyType:
-        if Settings().config.behave_as == BehaveAs.LOCAL:
-            members = super().__members__
-            return MappingProxyType(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):
@@ -99,10 +88,18 @@ class LlmModel(str, Enum, metaclass=LlmModelMeta):
     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"
@@ -140,6 +137,11 @@ class LlmModel(str, Enum, metaclass=LlmModelMeta):
     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:
@@ -177,6 +179,12 @@ 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
@@ -189,6 +197,12 @@ 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),
@@ -229,6 +243,11 @@ MODEL_METADATA = {
     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:
@@ -288,7 +307,7 @@ def convert_openai_tool_fmt_to_anthropic(
     return anthropic_tools
 
 
-def llm_call(
+async def llm_call(
     credentials: APIKeyCredentials,
     llm_model: LlmModel,
     prompt: list[dict],
@@ -296,7 +315,8 @@ def llm_call(
     max_tokens: int | None,
     tools: list[dict] | None = None,
     ollama_host: str = "localhost:11434",
-    parallel_tool_calls: bool | None = None,
+    parallel_tool_calls=None,
+    compress_prompt_to_fit: bool = True,
 ) -> LLMResponse:
     """
     Make a call to a language model.
@@ -319,32 +339,40 @@ 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
+    context_window = llm_model.context_window
+
+    if compress_prompt_to_fit:
+        prompt = compress_prompt(
+            messages=prompt,
+            target_tokens=llm_model.context_window // 2,
+            lossy_ok=True,
+        )
+
+    # Calculate available tokens based on context window and input length
+    estimated_input_tokens = estimate_token_count(prompt)
+    model_max_output = llm_model.max_output_tokens or int(2**15)
+    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), 1)
 
     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]:
-            sys_messages = [p["content"] for p in prompt if p["role"] == "system"]
-            usr_messages = [p["content"] for p in prompt if p["role"] != "system"]
-            prompt = [
-                {"role": "user", "content": "\n".join(sys_messages)},
-                {"role": "user", "content": "\n".join(usr_messages)},
-            ]
-        elif json_format:
+        if llm_model.startswith("o") or parallel_tool_calls is None:
+            parallel_tool_calls = openai.NOT_GIVEN
+
+        if 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
-            ),
+            parallel_tool_calls=parallel_tool_calls,
         )
 
         if response.choices[0].message.tool_calls:
@@ -392,9 +420,11 @@ 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,
@@ -425,7 +455,7 @@ 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(
@@ -448,9 +478,9 @@ 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
@@ -468,13 +498,14 @@ 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 "",
@@ -486,12 +517,12 @@ 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",
@@ -500,9 +531,6 @@ def llm_call(
             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
@@ -534,6 +562,79 @@ 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}")
 
@@ -558,6 +659,11 @@ class AIStructuredResponseGeneratorBlock(AIBlockBase):
             description="Expected format of the response. If provided, the response will be validated against this format. "
             "The keys should be the expected fields in the response, and the values should be the description of the field.",
         )
+        list_result: bool = SchemaField(
+            title="List Result",
+            default=False,
+            description="Whether the response should be a list of objects in the expected format.",
+        )
         model: LlmModel = SchemaField(
             title="LLM Model",
             default=LlmModel.GPT4O,
@@ -589,7 +695,11 @@ class AIStructuredResponseGeneratorBlock(AIBlockBase):
             default=None,
             description="The maximum number of tokens to generate in the chat completion.",
         )
-
+        compress_prompt_to_fit: bool = SchemaField(
+            advanced=True,
+            default=True,
+            description="Whether to compress the prompt to fit within the model's context window.",
+        )
         ollama_host: str = SchemaField(
             advanced=True,
             default="localhost:11434",
@@ -597,7 +707,7 @@ class AIStructuredResponseGeneratorBlock(AIBlockBase):
         )
 
     class Output(BlockSchema):
-        response: dict[str, Any] = SchemaField(
+        response: dict[str, Any] | list[dict[str, Any]] = SchemaField(
             description="The response object generated by the language model."
         )
         prompt: list = SchemaField(description="The prompt sent to the language model.")
@@ -641,12 +751,13 @@ class AIStructuredResponseGeneratorBlock(AIBlockBase):
             },
         )
 
-    def llm_call(
+    async def llm_call(
         self,
         credentials: APIKeyCredentials,
         llm_model: LlmModel,
         prompt: list[dict],
         json_format: bool,
+        compress_prompt_to_fit: bool,
         max_tokens: int | None,
         tools: list[dict] | None = None,
         ollama_host: str = "localhost:11434",
@@ -656,7 +767,7 @@ class AIStructuredResponseGeneratorBlock(AIBlockBase):
         so that it can be mocked withing the block testing framework.
         """
         self.prompt = prompt
-        return llm_call(
+        return await llm_call(
             credentials=credentials,
             llm_model=llm_model,
             prompt=prompt,
@@ -664,9 +775,10 @@ class AIStructuredResponseGeneratorBlock(AIBlockBase):
             max_tokens=max_tokens,
             tools=tools,
             ollama_host=ollama_host,
+            compress_prompt_to_fit=compress_prompt_to_fit,
         )
 
-    def run(
+    async def run(
         self, input_data: Input, *, credentials: APIKeyCredentials, **kwargs
     ) -> BlockOutput:
         logger.debug(f"Calling LLM with input data: {input_data}")
@@ -688,13 +800,22 @@ class AIStructuredResponseGeneratorBlock(AIBlockBase):
             expected_format = [
                 f'"{k}": "{v}"' for k, v in input_data.expected_format.items()
             ]
-            format_prompt = ",\n  ".join(expected_format)
+            if input_data.list_result:
+                format_prompt = (
+                    f'"results": [\n  {{\n  {", ".join(expected_format)}\n  }}\n]'
+                )
+            else:
+                format_prompt = "\n  ".join(expected_format)
+
             sys_prompt = trim_prompt(
                 f"""
                   |Reply strictly only in the following JSON format:
                   |{{
                   |  {format_prompt}
                   |}}
+                  |
+                  |Ensure the response is valid JSON. Do not include any additional text outside of the JSON.
+                  |If you cannot provide all the keys, provide an empty string for the values you cannot answer.
                 """
             )
             prompt.append({"role": "system", "content": sys_prompt})
@@ -702,28 +823,28 @@ class AIStructuredResponseGeneratorBlock(AIBlockBase):
         if input_data.prompt:
             prompt.append({"role": "user", "content": input_data.prompt})
 
-        def parse_response(resp: str) -> tuple[dict[str, Any], str | None]:
+        def validate_response(parsed: object) -> str | None:
             try:
-                parsed = json.loads(resp)
                 if not isinstance(parsed, dict):
-                    return {}, f"Expected a dictionary, but got {type(parsed)}"
+                    return f"Expected a dictionary, but got {type(parsed)}"
                 miss_keys = set(input_data.expected_format.keys()) - set(parsed.keys())
                 if miss_keys:
-                    return parsed, f"Missing keys: {miss_keys}"
-                return parsed, None
+                    return f"Missing keys: {miss_keys}"
+                return None
             except JSONDecodeError as e:
-                return {}, f"JSON decode error: {e}"
+                return f"JSON decode error: {e}"
 
-        logger.info(f"LLM request: {prompt}")
+        logger.debug(f"LLM request: {prompt}")
         retry_prompt = ""
         llm_model = input_data.model
 
         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,
+                    compress_prompt_to_fit=input_data.compress_prompt_to_fit,
                     json_format=bool(input_data.expected_format),
                     ollama_host=input_data.ollama_host,
                     max_tokens=input_data.max_tokens,
@@ -735,21 +856,32 @@ class AIStructuredResponseGeneratorBlock(AIBlockBase):
                         output_token_count=llm_response.completion_tokens,
                     )
                 )
-                logger.info(f"LLM attempt-{retry_count} response: {response_text}")
+                logger.debug(f"LLM attempt-{retry_count} response: {response_text}")
 
                 if input_data.expected_format:
-                    parsed_dict, parsed_error = parse_response(response_text)
-                    if not parsed_error:
-                        yield "response", {
-                            k: (
-                                json.loads(v)
-                                if isinstance(v, str)
-                                and v.startswith("[")
-                                and v.endswith("]")
-                                else (", ".join(v) if isinstance(v, list) else v)
+
+                    response_obj = json.loads(response_text)
+
+                    if input_data.list_result and isinstance(response_obj, dict):
+                        if "results" in response_obj:
+                            response_obj = response_obj.get("results", [])
+                        elif len(response_obj) == 1:
+                            response_obj = list(response_obj.values())
+
+                    response_error = "\n".join(
+                        [
+                            validation_error
+                            for response_item in (
+                                response_obj
+                                if isinstance(response_obj, list)
+                                else [response_obj]
                             )
-                            for k, v in parsed_dict.items()
-                        }
+                            if (validation_error := validate_response(response_item))
+                        ]
+                    )
+
+                    if not response_error:
+                        yield "response", response_obj
                         yield "prompt", self.prompt
                         return
                 else:
@@ -766,13 +898,23 @@ class AIStructuredResponseGeneratorBlock(AIBlockBase):
                   |
                   |And this is the error:
                   |--
-                  |{parsed_error}
+                  |{response_error}
                   |--
                 """
                 )
                 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(
@@ -850,17 +992,17 @@ class AITextGeneratorBlock(AIBlockBase):
             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(
@@ -870,7 +1012,8 @@ class AITextGeneratorBlock(AIBlockBase):
             },
             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
 
 
@@ -952,23 +1095,27 @@ 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
 
@@ -984,22 +1131,22 @@ 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,
@@ -1011,7 +1158,7 @@ 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)
@@ -1019,7 +1166,7 @@ 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,
@@ -1034,7 +1181,8 @@ 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,
@@ -1042,10 +1190,9 @@ 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):
@@ -1116,20 +1263,20 @@ class AIConversationBlock(AIBlockBase):
             },
         )
 
-    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=input_data.prompt,
                 credentials=input_data.credentials,
@@ -1141,7 +1288,6 @@ class AIConversationBlock(AIBlockBase):
             ),
             credentials=credentials,
         )
-
         yield "response", response
         yield "prompt", self.prompt
 
@@ -1235,13 +1381,15 @@ 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
 
@@ -1264,7 +1412,7 @@ 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}")
@@ -1330,7 +1478,7 @@ 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

@@ -13,7 +13,7 @@ from backend.data.model import (
 from backend.integrations.providers import ProviderName
 
 TEST_CREDENTIALS = APIKeyCredentials(
-    id="ed55ac19-356e-4243-a6cb-bc599e9b716f",
+    id="8cc8b2c5-d3e4-4b1c-84ad-e1e9fe2a0122",
     provider="mem0",
     api_key=SecretStr("mock-mem0-api-key"),
     title="Mock Mem0 API key",
@@ -67,12 +67,11 @@ class AddMemoryBlock(Block, Mem0Base):
         metadata: dict[str, Any] = SchemaField(
             description="Optional metadata for the memory", default_factory=dict
         )
-
         limit_memory_to_run: bool = SchemaField(
             description="Limit the memory to the run", default=False
         )
         limit_memory_to_agent: bool = SchemaField(
-            description="Limit the memory to the agent", default=False
+            description="Limit the memory to the agent", default=True
         )
 
     class Output(BlockSchema):
@@ -104,12 +103,17 @@ class AddMemoryBlock(Block, Mem0Base):
                     "credentials": TEST_CREDENTIALS_INPUT,
                 },
             ],
-            test_output=[("action", "NO_CHANGE"), ("action", "NO_CHANGE")],
+            test_output=[
+                ("action", "CREATED"),
+                ("memory", "test memory"),
+                ("action", "CREATED"),
+                ("memory", "test memory"),
+            ],
             test_credentials=TEST_CREDENTIALS,
             test_mock={"_get_client": lambda credentials: MockMemoryClient()},
         )
 
-    def run(
+    async def run(
         self,
         input_data: Input,
         *,
@@ -117,15 +121,17 @@ class AddMemoryBlock(Block, Mem0Base):
         user_id: str,
         graph_id: str,
         graph_exec_id: str,
-        **kwargs
+        **kwargs,
     ) -> BlockOutput:
         try:
             client = self._get_client(credentials)
 
             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 +158,7 @@ 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):
@@ -176,6 +182,10 @@ class SearchMemoryBlock(Block, Mem0Base):
             default_factory=list,
             advanced=True,
         )
+        metadata_filter: Optional[dict[str, Any]] = SchemaField(
+            description="Optional metadata filters to apply",
+            default=None,
+        )
         limit_memory_to_run: bool = SchemaField(
             description="Limit the memory to the run", default=False
         )
@@ -206,7 +216,7 @@ class SearchMemoryBlock(Block, Mem0Base):
             test_mock={"_get_client": lambda credentials: MockMemoryClient()},
         )
 
-    def run(
+    async def run(
         self,
         input_data: Input,
         *,
@@ -214,7 +224,7 @@ class SearchMemoryBlock(Block, Mem0Base):
         user_id: str,
         graph_id: str,
         graph_exec_id: str,
-        **kwargs
+        **kwargs,
     ) -> BlockOutput:
         try:
             client = self._get_client(credentials)
@@ -233,6 +243,8 @@ class SearchMemoryBlock(Block, Mem0Base):
                 filters["AND"].append({"run_id": graph_exec_id})
             if input_data.limit_memory_to_agent:
                 filters["AND"].append({"agent_id": graph_id})
+            if input_data.metadata_filter:
+                filters["AND"].append({"metadata": input_data.metadata_filter})
 
             result: list[dict[str, Any]] = client.search(
                 input_data.query, version="v2", filters=filters
@@ -258,11 +270,15 @@ class GetAllMemoriesBlock(Block, Mem0Base):
         categories: Optional[list[str]] = SchemaField(
             description="Filter by categories", default=None
         )
+        metadata_filter: Optional[dict[str, Any]] = SchemaField(
+            description="Optional metadata filters to apply",
+            default=None,
+        )
         limit_memory_to_run: bool = SchemaField(
             description="Limit the memory to the run", default=False
         )
         limit_memory_to_agent: bool = SchemaField(
-            description="Limit the memory to the agent", default=False
+            description="Limit the memory to the agent", default=True
         )
 
     class Output(BlockSchema):
@@ -272,11 +288,11 @@ class GetAllMemoriesBlock(Block, Mem0Base):
     def __init__(self):
         super().__init__(
             id="45aee5bf-4767-45d1-a28b-e01c5aae9fc1",
-            description="Retrieve all memories from Mem0 with pagination",
+            description="Retrieve all memories from Mem0 with optional conversation filtering",
             input_schema=GetAllMemoriesBlock.Input,
             output_schema=GetAllMemoriesBlock.Output,
             test_input={
-                "user_id": "test_user",
+                "metadata_filter": {"type": "test"},
                 "credentials": TEST_CREDENTIALS_INPUT,
             },
             test_output=[
@@ -286,7 +302,7 @@ class GetAllMemoriesBlock(Block, Mem0Base):
             test_mock={"_get_client": lambda credentials: MockMemoryClient()},
         )
 
-    def run(
+    async def run(
         self,
         input_data: Input,
         *,
@@ -294,7 +310,7 @@ class GetAllMemoriesBlock(Block, Mem0Base):
         user_id: str,
         graph_id: str,
         graph_exec_id: str,
-        **kwargs
+        **kwargs,
     ) -> BlockOutput:
         try:
             client = self._get_client(credentials)
@@ -312,6 +328,8 @@ class GetAllMemoriesBlock(Block, Mem0Base):
                 filters["AND"].append(
                     {"categories": {"contains": input_data.categories}}
                 )
+            if input_data.metadata_filter:
+                filters["AND"].append({"metadata": input_data.metadata_filter})
 
             memories: list[dict[str, Any]] = client.get_all(
                 filters=filters,
@@ -324,14 +342,116 @@ class GetAllMemoriesBlock(Block, Mem0Base):
             yield "error", str(e)
 
 
+class GetLatestMemoryBlock(Block, Mem0Base):
+    """Block for retrieving the latest memory from Mem0"""
+
+    class Input(BlockSchema):
+        credentials: CredentialsMetaInput[
+            Literal[ProviderName.MEM0], Literal["api_key"]
+        ] = CredentialsField(description="Mem0 API key credentials")
+        trigger: bool = SchemaField(
+            description="An unused field that is used to trigger the block when you have no other inputs",
+            default=False,
+            advanced=False,
+        )
+        categories: Optional[list[str]] = SchemaField(
+            description="Filter by categories", default=None
+        )
+        conversation_id: Optional[str] = SchemaField(
+            description="Optional conversation ID to retrieve the latest memory from (uses run_id)",
+            default=None,
+        )
+        metadata_filter: Optional[dict[str, Any]] = SchemaField(
+            description="Optional metadata filters to apply",
+            default=None,
+        )
+        limit_memory_to_run: bool = SchemaField(
+            description="Limit the memory to the run", default=False
+        )
+        limit_memory_to_agent: bool = SchemaField(
+            description="Limit the memory to the agent", default=True
+        )
+
+    class Output(BlockSchema):
+        memory: Optional[dict[str, Any]] = SchemaField(
+            description="Latest memory if found"
+        )
+        found: bool = SchemaField(description="Whether a memory was found")
+        error: str = SchemaField(description="Error message if operation fails")
+
+    def __init__(self):
+        super().__init__(
+            id="0f9d81b5-a145-4c23-b87f-01d6bf37b677",
+            description="Retrieve the latest memory from Mem0 with optional key filtering",
+            input_schema=GetLatestMemoryBlock.Input,
+            output_schema=GetLatestMemoryBlock.Output,
+            test_input={
+                "metadata_filter": {"type": "test"},
+                "credentials": TEST_CREDENTIALS_INPUT,
+            },
+            test_output=[
+                ("memory", {"id": "test-memory", "content": "test content"}),
+                ("found", True),
+            ],
+            test_credentials=TEST_CREDENTIALS,
+            test_mock={"_get_client": lambda credentials: MockMemoryClient()},
+        )
+
+    async def run(
+        self,
+        input_data: Input,
+        *,
+        credentials: APIKeyCredentials,
+        user_id: str,
+        graph_id: str,
+        graph_exec_id: str,
+        **kwargs,
+    ) -> BlockOutput:
+        try:
+            client = self._get_client(credentials)
+
+            filters: Filter = {
+                "AND": [
+                    {"user_id": user_id},
+                ]
+            }
+            if input_data.limit_memory_to_run:
+                filters["AND"].append({"run_id": graph_exec_id})
+            if input_data.limit_memory_to_agent:
+                filters["AND"].append({"agent_id": graph_id})
+            if input_data.categories:
+                filters["AND"].append(
+                    {"categories": {"contains": input_data.categories}}
+                )
+            if input_data.metadata_filter:
+                filters["AND"].append({"metadata": input_data.metadata_filter})
+
+            memories: list[dict[str, Any]] = client.get_all(
+                filters=filters,
+                version="v2",
+            )
+
+            if memories:
+                # Return the latest memory (first in the list as they're sorted by recency)
+                latest_memory = memories[0]
+                yield "memory", latest_memory
+                yield "found", True
+            else:
+                yield "memory", None
+                yield "found", False
+
+        except Exception as e:
+            yield "error", str(e)
+
+
 # Mock client for testing
 class MockMemoryClient:
     """Mock Mem0 client for testing"""
 
     def add(self, *args, **kwargs):
-        return {"memory_id": "test-memory-id", "status": "success"}
+        return {"results": [{"event": "CREATED", "memory": "test memory"}]}
 
-    def search(self, *args, **kwargs) -> list[dict[str, str]]:
+    def search(self, *args, **kwargs) -> list[dict[str, Any]]:
         return [{"id": "test-memory", "content": "test content"}]
 
     def get_all(self, *args, **kwargs) -> list[dict[str, str]]:

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/persistence.py

@@ -0,0 +1,154 @@
+import logging
+from typing import Any, Literal
+
+from autogpt_libs.utils.cache import thread_cached
+
+from backend.data.block import Block, BlockCategory, BlockOutput, BlockSchema
+from backend.data.model import SchemaField
+
+logger = logging.getLogger(__name__)
+
+
+@thread_cached
+def get_database_manager_client():
+    from backend.executor import DatabaseManagerAsyncClient
+    from backend.util.service import get_service_client
+
+    return get_service_client(DatabaseManagerAsyncClient, health_check=False)
+
+
+StorageScope = Literal["within_agent", "across_agents"]
+
+
+def get_storage_key(key: str, scope: StorageScope, graph_id: str) -> str:
+    """Generate the storage key based on scope"""
+    if scope == "across_agents":
+        return f"global#{key}"
+    else:
+        return f"agent#{graph_id}#{key}"
+
+
+class PersistInformationBlock(Block):
+    """Block for persisting key-value data for the current user with configurable scope"""
+
+    class Input(BlockSchema):
+        key: str = SchemaField(description="Key to store the information under")
+        value: Any = SchemaField(description="Value to store")
+        scope: StorageScope = SchemaField(
+            description="Scope of persistence: within_agent (shared across all runs of this agent) or across_agents (shared across all agents for this user)",
+            default="within_agent",
+        )
+
+    class Output(BlockSchema):
+        value: Any = SchemaField(description="Value that was stored")
+
+    def __init__(self):
+        super().__init__(
+            id="1d055e55-a2b9-4547-8311-907d05b0304d",
+            description="Persist key-value information for the current user",
+            categories={BlockCategory.DATA},
+            input_schema=PersistInformationBlock.Input,
+            output_schema=PersistInformationBlock.Output,
+            test_input={
+                "key": "user_preference",
+                "value": {"theme": "dark", "language": "en"},
+                "scope": "within_agent",
+            },
+            test_output=[
+                ("value", {"theme": "dark", "language": "en"}),
+            ],
+            test_mock={
+                "_store_data": lambda *args, **kwargs: {
+                    "theme": "dark",
+                    "language": "en",
+                }
+            },
+        )
+
+    async def run(
+        self,
+        input_data: Input,
+        *,
+        user_id: str,
+        graph_id: str,
+        node_exec_id: str,
+        **kwargs,
+    ) -> BlockOutput:
+        # Determine the storage key based on scope
+        storage_key = get_storage_key(input_data.key, input_data.scope, graph_id)
+
+        # Store the data
+        yield "value", await self._store_data(
+            user_id=user_id,
+            node_exec_id=node_exec_id,
+            key=storage_key,
+            data=input_data.value,
+        )
+
+    async def _store_data(
+        self, user_id: str, node_exec_id: str, key: str, data: Any
+    ) -> Any | None:
+        return await get_database_manager_client().set_execution_kv_data(
+            user_id=user_id,
+            node_exec_id=node_exec_id,
+            key=key,
+            data=data,
+        )
+
+
+class RetrieveInformationBlock(Block):
+    """Block for retrieving key-value data for the current user with configurable scope"""
+
+    class Input(BlockSchema):
+        key: str = SchemaField(description="Key to retrieve the information for")
+        scope: StorageScope = SchemaField(
+            description="Scope of persistence: within_agent (shared across all runs of this agent) or across_agents (shared across all agents for this user)",
+            default="within_agent",
+        )
+        default_value: Any = SchemaField(
+            description="Default value to return if key is not found", default=None
+        )
+
+    class Output(BlockSchema):
+        value: Any = SchemaField(description="Retrieved value or default value")
+
+    def __init__(self):
+        super().__init__(
+            id="d8710fc9-6e29-481e-a7d5-165eb16f8471",
+            description="Retrieve key-value information for the current user",
+            categories={BlockCategory.DATA},
+            input_schema=RetrieveInformationBlock.Input,
+            output_schema=RetrieveInformationBlock.Output,
+            test_input={
+                "key": "user_preference",
+                "scope": "within_agent",
+                "default_value": {"theme": "light", "language": "en"},
+            },
+            test_output=[
+                ("value", {"theme": "light", "language": "en"}),
+            ],
+            test_mock={"_retrieve_data": lambda *args, **kwargs: None},
+        )
+
+    async def run(
+        self, input_data: Input, *, user_id: str, graph_id: str, **kwargs
+    ) -> BlockOutput:
+        # Determine the storage key based on scope
+        storage_key = get_storage_key(input_data.key, input_data.scope, graph_id)
+
+        # Retrieve the data
+        stored_value = await self._retrieve_data(
+            user_id=user_id,
+            key=storage_key,
+        )
+
+        if stored_value is not None:
+            yield "value", stored_value
+        else:
+            yield "value", input_data.default_value
+
+    async def _retrieve_data(self, user_id: str, key: str) -> Any | None:
+        return await get_database_manager_client().get_execution_kv_data(
+            user_id=user_id,
+            key=key,
+        )

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,
         *,
@@ -195,7 +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"])

autogpt_platform/backend/backend/blocks/slant3d/base.py

@@ -1,7 +1,7 @@
 from typing import Any, Dict
 
 from backend.data.block import Block
-from backend.util.request import requests
+from backend.util.request import Requests
 
 from ._api import Color, CustomerDetails, OrderItem, Profile
 
@@ -14,20 +14,25 @@ class Slant3DBlockBase(Block):
     def _get_headers(self, api_key: str) -> Dict[str, str]:
         return {"api-key": api_key, "Content-Type": "application/json"}
 
-    def _make_request(self, method: str, endpoint: str, api_key: str, **kwargs) -> Dict:
+    async def _make_request(
+        self, method: str, endpoint: str, api_key: str, **kwargs
+    ) -> Dict:
         url = f"{self.BASE_URL}/{endpoint}"
-        response = requests.request(
+        response = await Requests().request(
             method=method, url=url, headers=self._get_headers(api_key), **kwargs
         )
+        resp = response.json()
 
         if not response.ok:
-            error_msg = response.json().get("error", "Unknown error")
+            error_msg = resp.get("error", "Unknown error")
             raise RuntimeError(f"API request failed: {error_msg}")
 
-        return response.json()
+        return resp
 
-    def _check_valid_color(self, profile: Profile, color: Color, api_key: str) -> str:
-        response = self._make_request(
+    async def _check_valid_color(
+        self, profile: Profile, color: Color, api_key: str
+    ) -> str:
+        response = await self._make_request(
             "GET",
             "filament",
             api_key,
@@ -48,10 +53,12 @@ Valid colors for {profile.value} are:
             )
         return color_tag
 
-    def _convert_to_color(self, profile: Profile, color: Color, api_key: str) -> str:
-        return self._check_valid_color(profile, color, api_key)
+    async def _convert_to_color(
+        self, profile: Profile, color: Color, api_key: str
+    ) -> str:
+        return await self._check_valid_color(profile, color, api_key)
 
-    def _format_order_data(
+    async def _format_order_data(
         self,
         customer: CustomerDetails,
         order_number: str,
@@ -61,6 +68,7 @@ Valid colors for {profile.value} are:
         """Helper function to format order data for API requests"""
         orders = []
         for item in items:
+            color_tag = await self._convert_to_color(item.profile, item.color, api_key)
             order_data = {
                 "email": customer.email,
                 "phone": customer.phone,
@@ -85,9 +93,7 @@ Valid colors for {profile.value} are:
                 "order_quantity": item.quantity,
                 "order_image_url": "",
                 "order_sku": "NOT_USED",
-                "order_item_color": self._convert_to_color(
-                    item.profile, item.color, api_key
-                ),
+                "order_item_color": color_tag,
                 "profile": item.profile.value,
             }
             orders.append(order_data)

autogpt_platform/backend/backend/blocks/slant3d/filament.py

@@ -72,11 +72,11 @@ class Slant3DFilamentBlock(Slant3DBlockBase):
             },
         )
 
-    def run(
+    async def run(
         self, input_data: Input, *, credentials: APIKeyCredentials, **kwargs
     ) -> BlockOutput:
         try:
-            result = self._make_request(
+            result = await self._make_request(
                 "GET", "filament", credentials.api_key.get_secret_value()
             )
             yield "filaments", result["filaments"]

autogpt_platform/backend/backend/blocks/slant3d/order.py

@@ -1,8 +1,6 @@
 import uuid
 from typing import List
 
-import requests as baserequests
-
 from backend.data.block import BlockOutput, BlockSchema
 from backend.data.model import APIKeyCredentials, SchemaField
 from backend.util import settings
@@ -76,17 +74,17 @@ class Slant3DCreateOrderBlock(Slant3DBlockBase):
             },
         )
 
-    def run(
+    async def run(
         self, input_data: Input, *, credentials: APIKeyCredentials, **kwargs
     ) -> BlockOutput:
         try:
-            order_data = self._format_order_data(
+            order_data = await self._format_order_data(
                 input_data.customer,
                 input_data.order_number,
                 input_data.items,
                 credentials.api_key.get_secret_value(),
             )
-            result = self._make_request(
+            result = await self._make_request(
                 "POST", "order", credentials.api_key.get_secret_value(), json=order_data
             )
             yield "order_id", result["orderId"]
@@ -162,28 +160,24 @@ class Slant3DEstimateOrderBlock(Slant3DBlockBase):
             },
         )
 
-    def run(
+    async def run(
         self, input_data: Input, *, credentials: APIKeyCredentials, **kwargs
     ) -> BlockOutput:
-        order_data = self._format_order_data(
+        order_data = await self._format_order_data(
             input_data.customer,
             input_data.order_number,
             input_data.items,
             credentials.api_key.get_secret_value(),
         )
-        try:
-            result = self._make_request(
-                "POST",
-                "order/estimate",
-                credentials.api_key.get_secret_value(),
-                json=order_data,
-            )
-            yield "total_price", result["totalPrice"]
-            yield "shipping_cost", result["shippingCost"]
-            yield "printing_cost", result["printingCost"]
-        except baserequests.HTTPError as e:
-            yield "error", str(f"Error estimating order: {e} {e.response.text}")
-            raise
+        result = await self._make_request(
+            "POST",
+            "order/estimate",
+            credentials.api_key.get_secret_value(),
+            json=order_data,
+        )
+        yield "total_price", result["totalPrice"]
+        yield "shipping_cost", result["shippingCost"]
+        yield "printing_cost", result["printingCost"]
 
 
 class Slant3DEstimateShippingBlock(Slant3DBlockBase):
@@ -246,17 +240,17 @@ class Slant3DEstimateShippingBlock(Slant3DBlockBase):
             },
         )
 
-    def run(
+    async def run(
         self, input_data: Input, *, credentials: APIKeyCredentials, **kwargs
     ) -> BlockOutput:
         try:
-            order_data = self._format_order_data(
+            order_data = await self._format_order_data(
                 input_data.customer,
                 input_data.order_number,
                 input_data.items,
                 credentials.api_key.get_secret_value(),
             )
-            result = self._make_request(
+            result = await self._make_request(
                 "POST",
                 "order/estimateShipping",
                 credentials.api_key.get_secret_value(),
@@ -312,11 +306,11 @@ class Slant3DGetOrdersBlock(Slant3DBlockBase):
             },
         )
 
-    def run(
+    async def run(
         self, input_data: Input, *, credentials: APIKeyCredentials, **kwargs
     ) -> BlockOutput:
         try:
-            result = self._make_request(
+            result = await self._make_request(
                 "GET", "order", credentials.api_key.get_secret_value()
             )
             yield "orders", [str(order["orderId"]) for order in result["ordersData"]]
@@ -359,11 +353,11 @@ class Slant3DTrackingBlock(Slant3DBlockBase):
             },
         )
 
-    def run(
+    async def run(
         self, input_data: Input, *, credentials: APIKeyCredentials, **kwargs
     ) -> BlockOutput:
         try:
-            result = self._make_request(
+            result = await self._make_request(
                 "GET",
                 f"order/{input_data.order_id}/get-tracking",
                 credentials.api_key.get_secret_value(),
@@ -403,11 +397,11 @@ class Slant3DCancelOrderBlock(Slant3DBlockBase):
             },
         )
 
-    def run(
+    async def run(
         self, input_data: Input, *, credentials: APIKeyCredentials, **kwargs
     ) -> BlockOutput:
         try:
-            result = self._make_request(
+            result = await self._make_request(
                 "DELETE",
                 f"order/{input_data.order_id}",
                 credentials.api_key.get_secret_value(),

autogpt_platform/backend/backend/blocks/slant3d/slicing.py

@@ -44,11 +44,11 @@ class Slant3DSlicerBlock(Slant3DBlockBase):
             },
         )
 
-    def run(
+    async def run(
         self, input_data: Input, *, credentials: APIKeyCredentials, **kwargs
     ) -> BlockOutput:
         try:
-            result = self._make_request(
+            result = await self._make_request(
                 "POST",
                 "slicer",
                 credentials.api_key.get_secret_value(),

autogpt_platform/backend/backend/blocks/slant3d/webhook.py

@@ -37,7 +37,7 @@ class Slant3DTriggerBase:
             description="Error message if payload processing failed"
         )
 
-    def run(self, input_data: Input, **kwargs) -> BlockOutput:
+    async def run(self, input_data: Input, **kwargs) -> BlockOutput:
         yield "payload", input_data.payload
         yield "order_id", input_data.payload["orderId"]
 
@@ -117,8 +117,9 @@ class Slant3DOrderWebhookBlock(Slant3DTriggerBase, 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
 
         # Extract and normalize values from the payload
         yield "status", input_data.payload["status"]

autogpt_platform/backend/backend/blocks/smart_decision_maker.py

@@ -26,10 +26,10 @@ logger = logging.getLogger(__name__)
 
 @thread_cached
 def get_database_manager_client():
-    from backend.executor import DatabaseManager
+    from backend.executor import DatabaseManagerAsyncClient
     from backend.util.service import get_service_client
 
-    return get_service_client(DatabaseManager)
+    return get_service_client(DatabaseManagerAsyncClient, health_check=False)
 
 
 def _get_tool_requests(entry: dict[str, Any]) -> list[str]:
@@ -85,7 +85,7 @@ def _get_tool_responses(entry: dict[str, Any]) -> list[str]:
     return tool_call_ids
 
 
-def _create_tool_response(call_id: str, output: dict[str, Any]) -> dict[str, Any]:
+def _create_tool_response(call_id: str, output: Any) -> dict[str, Any]:
     """
     Create a tool response message for either OpenAI or Anthropics,
     based on the tool_id format.
@@ -142,6 +142,12 @@ class SmartDecisionMakerBlock(Block):
             advanced=False,
         )
         credentials: llm.AICredentials = llm.AICredentialsField()
+        multiple_tool_calls: bool = SchemaField(
+            title="Multiple Tool Calls",
+            default=False,
+            description="Whether to allow multiple tool calls in a single response.",
+            advanced=True,
+        )
         sys_prompt: str = SchemaField(
             title="System Prompt",
             default="Thinking carefully step by step decide which function to call. "
@@ -150,7 +156,7 @@ class SmartDecisionMakerBlock(Block):
             "matching the required jsonschema signature, no missing argument is allowed. "
             "If you have already completed the task objective, you can end the task "
             "by providing the end result of your work as a finish message. "
-            "Only provide EXACTLY one function call, multiple tool calls is strictly prohibited.",
+            "Function parameters that has no default value and not optional typed has to be provided. ",
             description="The system prompt to provide additional context to the model.",
         )
         conversation_history: list[dict] = SchemaField(
@@ -206,6 +212,15 @@ class SmartDecisionMakerBlock(Block):
                     "link like the output of `StoreValue` or `AgentInput` block"
                 )
 
+            # Check that both conversation_history and last_tool_output are connected together
+            if any(link.sink_name == "conversation_history" for link in links) != any(
+                link.sink_name == "last_tool_output" for link in links
+            ):
+                raise ValueError(
+                    "Last Tool Output is needed when Conversation History is used, "
+                    "and vice versa. Please connect both inputs together."
+                )
+
             return missing_links
 
         @classmethod
@@ -216,8 +231,15 @@ class SmartDecisionMakerBlock(Block):
             conversation_history = data.get("conversation_history", [])
             pending_tool_calls = get_pending_tool_calls(conversation_history)
             last_tool_output = data.get("last_tool_output")
-            if not last_tool_output and pending_tool_calls:
+
+            # Tool call is pending, wait for the tool output to be provided.
+            if last_tool_output is None and pending_tool_calls:
                 return {"last_tool_output"}
+
+            # No tool call is pending, wait for the conversation history to be updated.
+            if last_tool_output is not None and not pending_tool_calls:
+                return {"conversation_history"}
+
             return set()
 
     class Output(BlockSchema):
@@ -247,7 +269,11 @@ class SmartDecisionMakerBlock(Block):
         )
 
     @staticmethod
-    def _create_block_function_signature(
+    def cleanup(s: str):
+        return re.sub(r"[^a-zA-Z0-9_-]", "_", s).lower()
+
+    @staticmethod
+    async def _create_block_function_signature(
         sink_node: "Node", links: list["Link"]
     ) -> dict[str, Any]:
         """
@@ -266,38 +292,27 @@ class SmartDecisionMakerBlock(Block):
         block = sink_node.block
 
         tool_function: dict[str, Any] = {
-            "name": re.sub(r"[^a-zA-Z0-9_-]", "_", block.name).lower(),
+            "name": SmartDecisionMakerBlock.cleanup(block.name),
             "description": block.description,
         }
-
+        sink_block_input_schema = block.input_schema
         properties = {}
-        required = []
 
         for link in links:
-            sink_block_input_schema = block.input_schema
-            description = (
-                sink_block_input_schema.model_fields[link.sink_name].description
-                if link.sink_name in sink_block_input_schema.model_fields
-                and sink_block_input_schema.model_fields[link.sink_name].description
-                else f"The {link.sink_name} of the tool"
+            sink_name = SmartDecisionMakerBlock.cleanup(link.sink_name)
+            properties[sink_name] = sink_block_input_schema.get_field_schema(
+                link.sink_name
             )
-            properties[link.sink_name.lower()] = {
-                "type": "string",
-                "description": description,
-            }
 
         tool_function["parameters"] = {
-            "type": "object",
+            **block.input_schema.jsonschema(),
             "properties": properties,
-            "required": required,
-            "additionalProperties": False,
-            "strict": True,
         }
 
         return {"type": "function", "function": tool_function}
 
     @staticmethod
-    def _create_agent_function_signature(
+    async def _create_agent_function_signature(
         sink_node: "Node", links: list["Link"]
     ) -> dict[str, Any]:
         """
@@ -319,37 +334,39 @@ class SmartDecisionMakerBlock(Block):
             raise ValueError("Graph ID or Graph Version not found in sink node.")
 
         db_client = get_database_manager_client()
-        sink_graph_meta = db_client.get_graph_metadata(graph_id, graph_version)
+        sink_graph_meta = await db_client.get_graph_metadata(graph_id, graph_version)
         if not sink_graph_meta:
             raise ValueError(
                 f"Sink graph metadata not found: {graph_id} {graph_version}"
             )
 
         tool_function: dict[str, Any] = {
-            "name": re.sub(r"[^a-zA-Z0-9_-]", "_", sink_graph_meta.name).lower(),
+            "name": SmartDecisionMakerBlock.cleanup(sink_graph_meta.name),
             "description": sink_graph_meta.description,
         }
 
         properties = {}
-        required = []
 
         for link in links:
             sink_block_input_schema = sink_node.input_default["input_schema"]
+            sink_block_properties = sink_block_input_schema.get("properties", {}).get(
+                link.sink_name, {}
+            )
+            sink_name = SmartDecisionMakerBlock.cleanup(link.sink_name)
             description = (
-                sink_block_input_schema["properties"][link.sink_name]["description"]
-                if "description"
-                in sink_block_input_schema["properties"][link.sink_name]
+                sink_block_properties["description"]
+                if "description" in sink_block_properties
                 else f"The {link.sink_name} of the tool"
             )
-            properties[link.sink_name.lower()] = {
+            properties[sink_name] = {
                 "type": "string",
                 "description": description,
+                "default": json.dumps(sink_block_properties.get("default", None)),
             }
 
         tool_function["parameters"] = {
             "type": "object",
             "properties": properties,
-            "required": required,
             "additionalProperties": False,
             "strict": True,
         }
@@ -357,7 +374,7 @@ class SmartDecisionMakerBlock(Block):
         return {"type": "function", "function": tool_function}
 
     @staticmethod
-    def _create_function_signature(node_id: str) -> list[dict[str, Any]]:
+    async def _create_function_signature(node_id: str) -> list[dict[str, Any]]:
         """
         Creates function signatures for tools linked to a specified node within a graph.
 
@@ -379,13 +396,13 @@ class SmartDecisionMakerBlock(Block):
         db_client = get_database_manager_client()
         tools = [
             (link, node)
-            for link, node in db_client.get_connected_output_nodes(node_id)
+            for link, node in await db_client.get_connected_output_nodes(node_id)
             if link.source_name.startswith("tools_^_") and link.source_id == node_id
         ]
         if not tools:
             raise ValueError("There is no next node to execute.")
 
-        return_tool_functions = []
+        return_tool_functions: list[dict[str, Any]] = []
 
         grouped_tool_links: dict[str, tuple["Node", list["Link"]]] = {}
         for link, node in tools:
@@ -400,20 +417,20 @@ class SmartDecisionMakerBlock(Block):
 
             if sink_node.block_id == AgentExecutorBlock().id:
                 return_tool_functions.append(
-                    SmartDecisionMakerBlock._create_agent_function_signature(
+                    await SmartDecisionMakerBlock._create_agent_function_signature(
                         sink_node, links
                     )
                 )
             else:
                 return_tool_functions.append(
-                    SmartDecisionMakerBlock._create_block_function_signature(
+                    await SmartDecisionMakerBlock._create_block_function_signature(
                         sink_node, links
                     )
                 )
 
         return return_tool_functions
 
-    def run(
+    async def run(
         self,
         input_data: Input,
         *,
@@ -425,13 +442,14 @@ class SmartDecisionMakerBlock(Block):
         user_id: str,
         **kwargs,
     ) -> BlockOutput:
-        tool_functions = self._create_function_signature(node_id)
+        tool_functions = await self._create_function_signature(node_id)
+        yield "tool_functions", json.dumps(tool_functions)
 
         input_data.conversation_history = input_data.conversation_history or []
         prompt = [json.to_dict(p) for p in input_data.conversation_history if p]
 
         pending_tool_calls = get_pending_tool_calls(input_data.conversation_history)
-        if pending_tool_calls and not input_data.last_tool_output:
+        if pending_tool_calls and input_data.last_tool_output is None:
             raise ValueError(f"Tool call requires an output for {pending_tool_calls}")
 
         # Prefill all missing tool calls with the last tool output/
@@ -465,6 +483,10 @@ class SmartDecisionMakerBlock(Block):
             )
 
         prompt.extend(tool_output)
+        if input_data.multiple_tool_calls:
+            input_data.sys_prompt += "\nYou can call a tool (different tools) multiple times in a single response."
+        else:
+            input_data.sys_prompt += "\nOnly provide EXACTLY one function call, multiple tool calls is strictly prohibited."
 
         values = input_data.prompt_values
         if values:
@@ -483,7 +505,7 @@ class SmartDecisionMakerBlock(Block):
         ):
             prompt.append({"role": "user", "content": prefix + input_data.prompt})
 
-        response = llm.llm_call(
+        response = await llm.llm_call(
             credentials=credentials,
             llm_model=input_data.model,
             prompt=prompt,
@@ -491,7 +513,7 @@ class SmartDecisionMakerBlock(Block):
             max_tokens=input_data.max_tokens,
             tools=tool_functions,
             ollama_host=input_data.ollama_host,
-            parallel_tool_calls=False,
+            parallel_tool_calls=input_data.multiple_tool_calls,
         )
 
         if not response.tool_calls:
@@ -502,8 +524,31 @@ class SmartDecisionMakerBlock(Block):
             tool_name = tool_call.function.name
             tool_args = json.loads(tool_call.function.arguments)
 
-            for arg_name, arg_value in tool_args.items():
-                yield f"tools_^_{tool_name}_{arg_name}".lower(), arg_value
+            # Find the tool definition to get the expected arguments
+            tool_def = next(
+                (
+                    tool
+                    for tool in tool_functions
+                    if tool["function"]["name"] == tool_name
+                ),
+                None,
+            )
+
+            if (
+                tool_def
+                and "function" in tool_def
+                and "parameters" in tool_def["function"]
+            ):
+                expected_args = tool_def["function"]["parameters"].get("properties", {})
+            else:
+                expected_args = tool_args.keys()
+
+            # Yield provided arguments and None for missing ones
+            for arg_name in expected_args:
+                if arg_name in tool_args:
+                    yield f"tools_^_{tool_name}_~_{arg_name}", tool_args[arg_name]
+                else:
+                    yield f"tools_^_{tool_name}_~_{arg_name}", None
 
         response.prompt.append(response.raw_response)
         yield "conversations", response.prompt

autogpt_platform/backend/backend/blocks/smartlead/_api.py

@@ -27,9 +27,11 @@ class SmartLeadClient:
     def _handle_error(self, e: Exception) -> str:
         return e.__str__().replace(self.api_key, "API KEY")
 
-    def create_campaign(self, request: CreateCampaignRequest) -> CreateCampaignResponse:
+    async def create_campaign(
+        self, request: CreateCampaignRequest
+    ) -> CreateCampaignResponse:
         try:
-            response = self.requests.post(
+            response = await self.requests.post(
                 self._add_auth_to_url(f"{self.API_URL}/campaigns/create"),
                 json=request.model_dump(),
             )
@@ -40,11 +42,11 @@ class SmartLeadClient:
         except Exception as e:
             raise ValueError(f"Failed to create campaign: {self._handle_error(e)}")
 
-    def add_leads_to_campaign(
+    async def add_leads_to_campaign(
         self, request: AddLeadsRequest
     ) -> AddLeadsToCampaignResponse:
         try:
-            response = self.requests.post(
+            response = await self.requests.post(
                 self._add_auth_to_url(
                     f"{self.API_URL}/campaigns/{request.campaign_id}/leads"
                 ),
@@ -64,7 +66,7 @@ class SmartLeadClient:
                 f"Failed to add leads to campaign: {self._handle_error(e)}"
             )
 
-    def save_campaign_sequences(
+    async def save_campaign_sequences(
         self, campaign_id: int, request: SaveSequencesRequest
     ) -> SaveSequencesResponse:
         """
@@ -84,13 +86,13 @@ class SmartLeadClient:
             - MANUAL_PERCENTAGE: Requires variant_distribution_percentage in seq_variants
         """
         try:
-            response = self.requests.post(
+            response = await self.requests.post(
                 self._add_auth_to_url(
                     f"{self.API_URL}/campaigns/{campaign_id}/sequences"
                 ),
                 json=request.model_dump(exclude_none=True),
             )
-            return SaveSequencesResponse(**response.json())
+            return SaveSequencesResponse(**(response.json()))
         except Exception as e:
             raise ValueError(
                 f"Failed to save campaign sequences: {e.__str__().replace(self.api_key, 'API KEY')}"