fix(backend/copilot): prevent double upload in timeout handling

Previous fix created NEW task after timeout, causing double upload:
- Original shielded task still running
- New task also uploading same transcript

Correct fix: Create task FIRST, then shield it. If timeout occurs,
track the SAME task (no double upload).

Fixes double-upload bug in b8c65e3d2

.dockerignore

@@ -5,42 +5,13 @@
 !docs/
 
 # Platform - Libs
-!autogpt_platform/autogpt_libs/autogpt_libs/
-!autogpt_platform/autogpt_libs/pyproject.toml
-!autogpt_platform/autogpt_libs/poetry.lock
-!autogpt_platform/autogpt_libs/README.md
+!autogpt_platform/autogpt_libs/
 
 # Platform - Backend
-!autogpt_platform/backend/backend/
-!autogpt_platform/backend/test/e2e_test_data.py
-!autogpt_platform/backend/migrations/
-!autogpt_platform/backend/schema.prisma
-!autogpt_platform/backend/pyproject.toml
-!autogpt_platform/backend/poetry.lock
-!autogpt_platform/backend/README.md
-!autogpt_platform/backend/.env
-!autogpt_platform/backend/gen_prisma_types_stub.py
-
-# Platform - Market
-!autogpt_platform/market/market/
-!autogpt_platform/market/scripts.py
-!autogpt_platform/market/schema.prisma
-!autogpt_platform/market/pyproject.toml
-!autogpt_platform/market/poetry.lock
-!autogpt_platform/market/README.md
+!autogpt_platform/backend/
 
 # Platform - Frontend
-!autogpt_platform/frontend/src/
-!autogpt_platform/frontend/public/
-!autogpt_platform/frontend/scripts/
-!autogpt_platform/frontend/package.json
-!autogpt_platform/frontend/pnpm-lock.yaml
-!autogpt_platform/frontend/tsconfig.json
-!autogpt_platform/frontend/README.md
-## config
-!autogpt_platform/frontend/*.config.*
-!autogpt_platform/frontend/.env.*
-!autogpt_platform/frontend/.env
+!autogpt_platform/frontend/
 
 # Classic - AutoGPT
 !classic/original_autogpt/autogpt/
@@ -64,6 +35,38 @@
 # Classic - Frontend
 !classic/frontend/build/web/
 
-# Explicitly re-ignore some folders
-.*
-**/__pycache__
+# Explicitly re-ignore unwanted files from whitelisted directories
+# Note: These patterns MUST come after the whitelist rules to take effect
+
+# Hidden files and directories (but keep frontend .env files needed for build)
+**/.*
+!autogpt_platform/frontend/.env
+!autogpt_platform/frontend/.env.default
+!autogpt_platform/frontend/.env.production
+
+# Python artifacts
+**/__pycache__/
+**/*.pyc
+**/*.pyo
+**/.venv/
+**/.ruff_cache/
+**/.pytest_cache/
+**/.coverage
+**/htmlcov/
+
+# Node artifacts
+**/node_modules/
+**/.next/
+**/storybook-static/
+**/playwright-report/
+**/test-results/
+
+# Build artifacts
+**/dist/
+**/build/
+!autogpt_platform/frontend/src/**/build/
+**/target/
+
+# Logs and temp files
+**/*.log
+**/*.tmp

.github/workflows/claude-ci-failure-auto-fix.yml

@@ -40,6 +40,48 @@ jobs:
           git checkout -b "$BRANCH_NAME"
           echo "branch_name=$BRANCH_NAME" >> $GITHUB_OUTPUT
 
+      # Backend Python/Poetry setup (so Claude can run linting/tests)
+      - name: Set up Python
+        uses: actions/setup-python@v5
+        with:
+          python-version: "3.11"
+
+      - name: Set up Python dependency cache
+        uses: actions/cache@v5
+        with:
+          path: ~/.cache/pypoetry
+          key: poetry-${{ runner.os }}-${{ hashFiles('autogpt_platform/backend/poetry.lock') }}
+
+      - name: Install Poetry
+        run: |
+          cd autogpt_platform/backend
+          HEAD_POETRY_VERSION=$(python3 ../../.github/workflows/scripts/get_package_version_from_lockfile.py poetry)
+          curl -sSL https://install.python-poetry.org | POETRY_VERSION=$HEAD_POETRY_VERSION python3 -
+          echo "$HOME/.local/bin" >> $GITHUB_PATH
+
+      - name: Install Python dependencies
+        working-directory: autogpt_platform/backend
+        run: poetry install
+
+      - name: Generate Prisma Client
+        working-directory: autogpt_platform/backend
+        run: poetry run prisma generate && poetry run gen-prisma-stub
+
+      # Frontend Node.js/pnpm setup (so Claude can run linting/tests)
+      - name: Enable corepack
+        run: corepack enable
+
+      - name: Set up Node.js
+        uses: actions/setup-node@v6
+        with:
+          node-version: "22"
+          cache: "pnpm"
+          cache-dependency-path: autogpt_platform/frontend/pnpm-lock.yaml
+
+      - name: Install JavaScript dependencies
+        working-directory: autogpt_platform/frontend
+        run: pnpm install --frozen-lockfile
+
       - name: Get CI failure details
         id: failure_details
         uses: actions/github-script@v8

.github/workflows/claude-dependabot.yml

@@ -77,27 +77,15 @@ jobs:
         run: poetry run prisma generate && poetry run gen-prisma-stub
 
       # Frontend Node.js/pnpm setup (mirrors platform-frontend-ci.yml)
+      - name: Enable corepack
+        run: corepack enable
+
       - name: Set up Node.js
         uses: actions/setup-node@v6
         with:
           node-version: "22"
-
-      - name: Enable corepack
-        run: corepack enable
-
-      - name: Set pnpm store directory
-        run: |
-          pnpm config set store-dir ~/.pnpm-store
-          echo "PNPM_HOME=$HOME/.pnpm-store" >> $GITHUB_ENV
-
-      - name: Cache frontend dependencies
-        uses: actions/cache@v5
-        with:
-          path: ~/.pnpm-store
-          key: ${{ runner.os }}-pnpm-${{ hashFiles('autogpt_platform/frontend/pnpm-lock.yaml', 'autogpt_platform/frontend/package.json') }}
-          restore-keys: |
-            ${{ runner.os }}-pnpm-${{ hashFiles('autogpt_platform/frontend/pnpm-lock.yaml') }}
-            ${{ runner.os }}-pnpm-
+          cache: "pnpm"
+          cache-dependency-path: autogpt_platform/frontend/pnpm-lock.yaml
 
       - name: Install JavaScript dependencies
         working-directory: autogpt_platform/frontend

.github/workflows/claude.yml

@@ -93,27 +93,15 @@ jobs:
         run: poetry run prisma generate && poetry run gen-prisma-stub
 
       # Frontend Node.js/pnpm setup (mirrors platform-frontend-ci.yml)
+      - name: Enable corepack
+        run: corepack enable
+
       - name: Set up Node.js
         uses: actions/setup-node@v6
         with:
           node-version: "22"
-
-      - name: Enable corepack
-        run: corepack enable
-
-      - name: Set pnpm store directory
-        run: |
-          pnpm config set store-dir ~/.pnpm-store
-          echo "PNPM_HOME=$HOME/.pnpm-store" >> $GITHUB_ENV
-
-      - name: Cache frontend dependencies
-        uses: actions/cache@v5
-        with:
-          path: ~/.pnpm-store
-          key: ${{ runner.os }}-pnpm-${{ hashFiles('autogpt_platform/frontend/pnpm-lock.yaml', 'autogpt_platform/frontend/package.json') }}
-          restore-keys: |
-            ${{ runner.os }}-pnpm-${{ hashFiles('autogpt_platform/frontend/pnpm-lock.yaml') }}
-            ${{ runner.os }}-pnpm-
+          cache: "pnpm"
+          cache-dependency-path: autogpt_platform/frontend/pnpm-lock.yaml
 
       - name: Install JavaScript dependencies
         working-directory: autogpt_platform/frontend

.github/workflows/codeql.yml

@@ -62,7 +62,7 @@ jobs:
 
     # Initializes the CodeQL tools for scanning.
     - name: Initialize CodeQL
-      uses: github/codeql-action/init@v3
+      uses: github/codeql-action/init@v4
       with:
         languages: ${{ matrix.language }}
         build-mode: ${{ matrix.build-mode }}
@@ -93,6 +93,6 @@ jobs:
         exit 1
 
     - name: Perform CodeQL Analysis
-      uses: github/codeql-action/analyze@v3
+      uses: github/codeql-action/analyze@v4
       with:
         category: "/language:${{matrix.language}}"

.github/workflows/docs-claude-review.yml

@@ -7,6 +7,10 @@ on:
       - "docs/integrations/**"
       - "autogpt_platform/backend/backend/blocks/**"
 
+concurrency:
+  group: claude-docs-review-${{ github.event.pull_request.number }}
+  cancel-in-progress: true
+
 jobs:
   claude-review:
     # Only run for PRs from members/collaborators
@@ -91,5 +95,35 @@ jobs:
             3. Read corresponding documentation files to verify accuracy
             4. Provide your feedback as a PR comment
 
+            ## IMPORTANT: Comment Marker
+            Start your PR comment with exactly this HTML comment marker on its own line:
+            <!-- CLAUDE_DOCS_REVIEW -->
+
+            This marker is used to identify and replace your comment on subsequent runs.
+
             Be constructive and specific. If everything looks good, say so!
             If there are issues, explain what's wrong and suggest how to fix it.
+
+      - name: Delete old Claude review comments
+        env:
+          GH_TOKEN: ${{ secrets.GITHUB_TOKEN }}
+        run: |
+          # Get all comment IDs with our marker, sorted by creation date (oldest first)
+          COMMENT_IDS=$(gh api \
+            repos/${{ github.repository }}/issues/${{ github.event.pull_request.number }}/comments \
+            --jq '[.[] | select(.body | contains("<!-- CLAUDE_DOCS_REVIEW -->"))] | sort_by(.created_at) | .[].id')
+
+          # Count comments
+          COMMENT_COUNT=$(echo "$COMMENT_IDS" | grep -c . || true)
+
+          if [ "$COMMENT_COUNT" -gt 1 ]; then
+            # Delete all but the last (newest) comment
+            echo "$COMMENT_IDS" | head -n -1 | while read -r COMMENT_ID; do
+              if [ -n "$COMMENT_ID" ]; then
+                echo "Deleting old review comment: $COMMENT_ID"
+                gh api -X DELETE repos/${{ github.repository }}/issues/comments/$COMMENT_ID
+              fi
+            done
+          else
+            echo "No old review comments to clean up"
+          fi

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

@@ -41,13 +41,18 @@ jobs:
         ports:
           - 6379:6379
       rabbitmq:
-        image: rabbitmq:3.12-management
+        image: rabbitmq:4.1.4
         ports:
           - 5672:5672
-          - 15672:15672
         env:
           RABBITMQ_DEFAULT_USER: ${{ env.RABBITMQ_DEFAULT_USER }}
           RABBITMQ_DEFAULT_PASS: ${{ env.RABBITMQ_DEFAULT_PASS }}
+        options: >-
+          --health-cmd "rabbitmq-diagnostics -q ping"
+          --health-interval 30s
+          --health-timeout 10s
+          --health-retries 5
+          --health-start-period 10s
       clamav:
         image: clamav/clamav-debian:latest
         ports:

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

@@ -6,10 +6,16 @@ on:
     paths:
       - ".github/workflows/platform-frontend-ci.yml"
       - "autogpt_platform/frontend/**"
+      - "autogpt_platform/backend/Dockerfile"
+      - "autogpt_platform/docker-compose.yml"
+      - "autogpt_platform/docker-compose.platform.yml"
   pull_request:
     paths:
       - ".github/workflows/platform-frontend-ci.yml"
       - "autogpt_platform/frontend/**"
+      - "autogpt_platform/backend/Dockerfile"
+      - "autogpt_platform/docker-compose.yml"
+      - "autogpt_platform/docker-compose.platform.yml"
   merge_group:
   workflow_dispatch:
 
@@ -26,7 +32,6 @@ jobs:
   setup:
     runs-on: ubuntu-latest
     outputs:
-      cache-key: ${{ steps.cache-key.outputs.key }}
       components-changed: ${{ steps.filter.outputs.components }}
 
     steps:
@@ -41,28 +46,17 @@ jobs:
             components:
               - 'autogpt_platform/frontend/src/components/**'
 
-      - name: Set up Node.js
-        uses: actions/setup-node@v6
-        with:
-          node-version: "22.18.0"
-
       - name: Enable corepack
         run: corepack enable
 
-      - name: Generate cache key
-        id: cache-key
-        run: echo "key=${{ runner.os }}-pnpm-${{ hashFiles('autogpt_platform/frontend/pnpm-lock.yaml', 'autogpt_platform/frontend/package.json') }}" >> $GITHUB_OUTPUT
-
-      - name: Cache dependencies
-        uses: actions/cache@v5
+      - name: Set up Node
+        uses: actions/setup-node@v6
         with:
-          path: ~/.pnpm-store
-          key: ${{ steps.cache-key.outputs.key }}
-          restore-keys: |
-            ${{ runner.os }}-pnpm-${{ hashFiles('autogpt_platform/frontend/pnpm-lock.yaml') }}
-            ${{ runner.os }}-pnpm-
+          node-version: "22.18.0"
+          cache: "pnpm"
+          cache-dependency-path: autogpt_platform/frontend/pnpm-lock.yaml
 
-      - name: Install dependencies
+      - name: Install dependencies to populate cache
         run: pnpm install --frozen-lockfile
 
   lint:
@@ -73,22 +67,15 @@ jobs:
       - name: Checkout repository
         uses: actions/checkout@v6
 
-      - name: Set up Node.js
-        uses: actions/setup-node@v6
-        with:
-          node-version: "22.18.0"
-
       - name: Enable corepack
         run: corepack enable
 
-      - name: Restore dependencies cache
-        uses: actions/cache@v5
+      - name: Set up Node
+        uses: actions/setup-node@v6
         with:
-          path: ~/.pnpm-store
-          key: ${{ needs.setup.outputs.cache-key }}
-          restore-keys: |
-            ${{ runner.os }}-pnpm-${{ hashFiles('autogpt_platform/frontend/pnpm-lock.yaml') }}
-            ${{ runner.os }}-pnpm-
+          node-version: "22.18.0"
+          cache: "pnpm"
+          cache-dependency-path: autogpt_platform/frontend/pnpm-lock.yaml
 
       - name: Install dependencies
         run: pnpm install --frozen-lockfile
@@ -111,22 +98,15 @@ jobs:
         with:
           fetch-depth: 0
 
-      - name: Set up Node.js
-        uses: actions/setup-node@v6
-        with:
-          node-version: "22.18.0"
-
       - name: Enable corepack
         run: corepack enable
 
-      - name: Restore dependencies cache
-        uses: actions/cache@v5
+      - name: Set up Node
+        uses: actions/setup-node@v6
         with:
-          path: ~/.pnpm-store
-          key: ${{ needs.setup.outputs.cache-key }}
-          restore-keys: |
-            ${{ runner.os }}-pnpm-${{ hashFiles('autogpt_platform/frontend/pnpm-lock.yaml') }}
-            ${{ runner.os }}-pnpm-
+          node-version: "22.18.0"
+          cache: "pnpm"
+          cache-dependency-path: autogpt_platform/frontend/pnpm-lock.yaml
 
       - name: Install dependencies
         run: pnpm install --frozen-lockfile
@@ -141,10 +121,8 @@ jobs:
           exitOnceUploaded: true
 
   e2e_test:
+    name: end-to-end tests
     runs-on: big-boi
-    needs: setup
-    strategy:
-      fail-fast: false
 
     steps:
       - name: Checkout repository
@@ -152,19 +130,11 @@ jobs:
         with:
           submodules: recursive
 
-      - name: Set up Node.js
-        uses: actions/setup-node@v6
-        with:
-          node-version: "22.18.0"
-
-      - name: Enable corepack
-        run: corepack enable
-
-      - name: Copy default supabase .env
+      - name: Set up Platform - Copy default supabase .env
         run: |
           cp ../.env.default ../.env
 
-      - name: Copy backend .env and set OpenAI API key
+      - name: Set up Platform - Copy backend .env and set OpenAI API key
         run: |
           cp ../backend/.env.default ../backend/.env
           echo "OPENAI_INTERNAL_API_KEY=${{ secrets.OPENAI_API_KEY }}" >> ../backend/.env
@@ -172,77 +142,125 @@ jobs:
           # Used by E2E test data script to generate embeddings for approved store agents
           OPENAI_API_KEY: ${{ secrets.OPENAI_API_KEY }}
 
-      - name: Set up Docker Buildx
+      - name: Set up Platform - Set up Docker Buildx
         uses: docker/setup-buildx-action@v3
+        with:
+          driver: docker-container
+          driver-opts: network=host
 
-      - name: Cache Docker layers
+      - name: Set up Platform - Expose GHA cache to docker buildx CLI
+        uses: crazy-max/ghaction-github-runtime@v4
+
+      - name: Set up Platform - Build Docker images (with cache)
+        working-directory: autogpt_platform
+        run: |
+          pip install pyyaml
+
+          # Resolve extends and generate a flat compose file that bake can understand
+          docker compose -f docker-compose.yml config > docker-compose.resolved.yml
+
+          # Add cache configuration to the resolved compose file
+          python ../.github/workflows/scripts/docker-ci-fix-compose-build-cache.py \
+            --source docker-compose.resolved.yml \
+            --cache-from "type=gha" \
+            --cache-to "type=gha,mode=max" \
+            --backend-hash "${{ hashFiles('autogpt_platform/backend/Dockerfile', 'autogpt_platform/backend/poetry.lock', 'autogpt_platform/backend/backend') }}" \
+            --frontend-hash "${{ hashFiles('autogpt_platform/frontend/Dockerfile', 'autogpt_platform/frontend/pnpm-lock.yaml', 'autogpt_platform/frontend/src') }}" \
+            --git-ref "${{ github.ref }}"
+
+          # Build with bake using the resolved compose file (now includes cache config)
+          docker buildx bake --allow=fs.read=.. -f docker-compose.resolved.yml --load
+        env:
+          NEXT_PUBLIC_PW_TEST: true
+
+      - name: Set up tests - Cache E2E test data
+        id: e2e-data-cache
         uses: actions/cache@v5
         with:
-          path: /tmp/.buildx-cache
-          key: ${{ runner.os }}-buildx-frontend-test-${{ hashFiles('autogpt_platform/docker-compose.yml', 'autogpt_platform/backend/Dockerfile', 'autogpt_platform/backend/pyproject.toml', 'autogpt_platform/backend/poetry.lock') }}
-          restore-keys: |
-            ${{ runner.os }}-buildx-frontend-test-
+          path: /tmp/e2e_test_data.sql
+          key: e2e-test-data-${{ hashFiles('autogpt_platform/backend/test/e2e_test_data.py', 'autogpt_platform/backend/migrations/**', '.github/workflows/platform-frontend-ci.yml') }}
 
-      - name: Run docker compose
+      - name: Set up Platform - Start Supabase DB + Auth
         run: |
-          NEXT_PUBLIC_PW_TEST=true docker compose -f ../docker-compose.yml up -d
+          docker compose -f ../docker-compose.resolved.yml up -d db auth --no-build
+          echo "Waiting for database to be ready..."
+          timeout 60 sh -c 'until docker compose -f ../docker-compose.resolved.yml exec -T db pg_isready -U postgres 2>/dev/null; do sleep 2; done'
+          echo "Waiting for auth service to be ready..."
+          timeout 60 sh -c 'until docker compose -f ../docker-compose.resolved.yml exec -T db psql -U postgres -d postgres -c "SELECT 1 FROM auth.users LIMIT 1" 2>/dev/null; do sleep 2; done' || echo "Auth schema check timeout, continuing..."
+
+      - name: Set up Platform - Run migrations
+        run: |
+          echo "Running migrations..."
+          docker compose -f ../docker-compose.resolved.yml run --rm migrate
+          echo "✅ Migrations completed"
         env:
-          DOCKER_BUILDKIT: 1
-          BUILDX_CACHE_FROM: type=local,src=/tmp/.buildx-cache
-          BUILDX_CACHE_TO: type=local,dest=/tmp/.buildx-cache-new,mode=max
+          NEXT_PUBLIC_PW_TEST: true
 
-      - name: Move cache
+      - name: Set up tests - Load cached E2E test data
+        if: steps.e2e-data-cache.outputs.cache-hit == 'true'
         run: |
-          rm -rf /tmp/.buildx-cache
-          if [ -d "/tmp/.buildx-cache-new" ]; then
-            mv /tmp/.buildx-cache-new /tmp/.buildx-cache
-          fi
+          echo "✅ Found cached E2E test data, restoring..."
+          {
+            echo "SET session_replication_role = 'replica';"
+            cat /tmp/e2e_test_data.sql
+            echo "SET session_replication_role = 'origin';"
+          } | docker compose -f ../docker-compose.resolved.yml exec -T db psql -U postgres -d postgres -b
+          # Refresh materialized views after restore
+          docker compose -f ../docker-compose.resolved.yml exec -T db \
+            psql -U postgres -d postgres -b -c "SET search_path TO platform; SELECT refresh_store_materialized_views();" || true
 
-      - name: Wait for services to be ready
+          echo "✅ E2E test data restored from cache"
+
+      - name: Set up Platform - Start (all other services)
         run: |
+          docker compose -f ../docker-compose.resolved.yml up -d --no-build
           echo "Waiting for rest_server to be ready..."
           timeout 60 sh -c 'until curl -f http://localhost:8006/health 2>/dev/null; do sleep 2; done' || echo "Rest server health check timeout, continuing..."
-          echo "Waiting for database to be ready..."
-          timeout 60 sh -c 'until docker compose -f ../docker-compose.yml exec -T db pg_isready -U postgres 2>/dev/null; do sleep 2; done' || echo "Database ready check timeout, continuing..."
+        env:
+          NEXT_PUBLIC_PW_TEST: true
 
-      - name: Create E2E test data
+      - name: Set up tests - Create E2E test data
+        if: steps.e2e-data-cache.outputs.cache-hit != 'true'
         run: |
           echo "Creating E2E test data..."
-          # First try to run the script from inside the container
-          if docker compose -f ../docker-compose.yml exec -T rest_server test -f /app/autogpt_platform/backend/test/e2e_test_data.py; then
-            echo "✅ Found e2e_test_data.py in container, running it..."
-            docker compose -f ../docker-compose.yml exec -T rest_server sh -c "cd /app/autogpt_platform && python backend/test/e2e_test_data.py" || {
-              echo "❌ E2E test data creation failed!"
-              docker compose -f ../docker-compose.yml logs --tail=50 rest_server
-              exit 1
-            }
-          else
-            echo "⚠️ e2e_test_data.py not found in container, copying and running..."
-            # Copy the script into the container and run it
-            docker cp ../backend/test/e2e_test_data.py $(docker compose -f ../docker-compose.yml ps -q rest_server):/tmp/e2e_test_data.py || {
-              echo "❌ Failed to copy script to container"
-              exit 1
-            }
-            docker compose -f ../docker-compose.yml exec -T rest_server sh -c "cd /app/autogpt_platform && python /tmp/e2e_test_data.py" || {
-              echo "❌ E2E test data creation failed!"
-              docker compose -f ../docker-compose.yml logs --tail=50 rest_server
-              exit 1
-            }
-          fi
+          docker cp ../backend/test/e2e_test_data.py $(docker compose -f ../docker-compose.resolved.yml ps -q rest_server):/tmp/e2e_test_data.py
+          docker compose -f ../docker-compose.resolved.yml exec -T rest_server sh -c "cd /app/autogpt_platform && python /tmp/e2e_test_data.py" || {
+            echo "❌ E2E test data creation failed!"
+            docker compose -f ../docker-compose.resolved.yml logs --tail=50 rest_server
+            exit 1
+          }
 
-      - name: Restore dependencies cache
-        uses: actions/cache@v5
+          # Dump auth.users + platform schema for cache (two separate dumps)
+          echo "Dumping database for cache..."
+          {
+            docker compose -f ../docker-compose.resolved.yml exec -T db \
+              pg_dump -U postgres --data-only --column-inserts \
+              --table='auth.users' postgres
+            docker compose -f ../docker-compose.resolved.yml exec -T db \
+              pg_dump -U postgres --data-only --column-inserts \
+              --schema=platform \
+              --exclude-table='platform._prisma_migrations' \
+              --exclude-table='platform.apscheduler_jobs' \
+              --exclude-table='platform.apscheduler_jobs_batched_notifications' \
+              postgres
+          } > /tmp/e2e_test_data.sql
+
+          echo "✅ Database dump created for caching ($(wc -l < /tmp/e2e_test_data.sql) lines)"
+
+      - name: Set up tests - Enable corepack
+        run: corepack enable
+
+      - name: Set up tests - Set up Node
+        uses: actions/setup-node@v6
         with:
-          path: ~/.pnpm-store
-          key: ${{ needs.setup.outputs.cache-key }}
-          restore-keys: |
-            ${{ runner.os }}-pnpm-${{ hashFiles('autogpt_platform/frontend/pnpm-lock.yaml') }}
-            ${{ runner.os }}-pnpm-
+          node-version: "22.18.0"
+          cache: "pnpm"
+          cache-dependency-path: autogpt_platform/frontend/pnpm-lock.yaml
 
-      - name: Install dependencies
+      - name: Set up tests - Install dependencies
         run: pnpm install --frozen-lockfile
 
-      - name: Install Browser 'chromium'
+      - name: Set up tests - Install browser 'chromium'
         run: pnpm playwright install --with-deps chromium
 
       - name: Run Playwright tests
@@ -269,7 +287,7 @@ jobs:
 
       - name: Print Final Docker Compose logs
         if: always()
-        run: docker compose -f ../docker-compose.yml logs
+        run: docker compose -f ../docker-compose.resolved.yml logs
 
   integration_test:
     runs-on: ubuntu-latest
@@ -281,22 +299,15 @@ jobs:
         with:
           submodules: recursive
 
-      - name: Set up Node.js
-        uses: actions/setup-node@v6
-        with:
-          node-version: "22.18.0"
-
       - name: Enable corepack
         run: corepack enable
 
-      - name: Restore dependencies cache
-        uses: actions/cache@v5
+      - name: Set up Node
+        uses: actions/setup-node@v6
         with:
-          path: ~/.pnpm-store
-          key: ${{ needs.setup.outputs.cache-key }}
-          restore-keys: |
-            ${{ runner.os }}-pnpm-${{ hashFiles('autogpt_platform/frontend/pnpm-lock.yaml') }}
-            ${{ runner.os }}-pnpm-
+          node-version: "22.18.0"
+          cache: "pnpm"
+          cache-dependency-path: autogpt_platform/frontend/pnpm-lock.yaml
 
       - name: Install dependencies
         run: pnpm install --frozen-lockfile

.github/workflows/pr-overlap-check.yml

@@ -0,0 +1,39 @@
+name: PR Overlap Detection
+
+on:
+  pull_request:
+    types: [opened, synchronize, reopened]
+    branches:
+      - dev
+      - master
+
+permissions:
+  contents: read
+  pull-requests: write
+
+jobs:
+  check-overlaps:
+    runs-on: ubuntu-latest
+    steps:
+      - name: Checkout repository
+        uses: actions/checkout@v4
+        with:
+          fetch-depth: 0  # Need full history for merge testing
+
+      - name: Set up Python
+        uses: actions/setup-python@v5
+        with:
+          python-version: '3.11'
+
+      - name: Configure git
+        run: |
+          git config user.email "github-actions[bot]@users.noreply.github.com"
+          git config user.name "github-actions[bot]"
+
+      - name: Run overlap detection
+        env:
+          GH_TOKEN: ${{ secrets.GITHUB_TOKEN }}
+        # Always succeed - this check informs contributors, it shouldn't block merging
+        continue-on-error: true
+        run: |
+          python .github/scripts/detect_overlaps.py ${{ github.event.pull_request.number }}

.github/workflows/scripts/docker-ci-fix-compose-build-cache.py

@@ -0,0 +1,195 @@
+#!/usr/bin/env python3
+"""
+Add cache configuration to a resolved docker-compose file for all services
+that have a build key, and ensure image names match what docker compose expects.
+"""
+
+import argparse
+
+import yaml
+
+
+DEFAULT_BRANCH = "dev"
+CACHE_BUILDS_FOR_COMPONENTS = ["backend", "frontend"]
+
+
+def main():
+    parser = argparse.ArgumentParser(
+        description="Add cache config to a resolved compose file"
+    )
+    parser.add_argument(
+        "--source",
+        required=True,
+        help="Source compose file to read (should be output of `docker compose config`)",
+    )
+    parser.add_argument(
+        "--cache-from",
+        default="type=gha",
+        help="Cache source configuration",
+    )
+    parser.add_argument(
+        "--cache-to",
+        default="type=gha,mode=max",
+        help="Cache destination configuration",
+    )
+    for component in CACHE_BUILDS_FOR_COMPONENTS:
+        parser.add_argument(
+            f"--{component}-hash",
+            default="",
+            help=f"Hash for {component} cache scope (e.g., from hashFiles())",
+        )
+    parser.add_argument(
+        "--git-ref",
+        default="",
+        help="Git ref for branch-based cache scope (e.g., refs/heads/master)",
+    )
+    args = parser.parse_args()
+
+    # Normalize git ref to a safe scope name (e.g., refs/heads/master -> master)
+    git_ref_scope = ""
+    if args.git_ref:
+        git_ref_scope = args.git_ref.replace("refs/heads/", "").replace("/", "-")
+
+    with open(args.source, "r") as f:
+        compose = yaml.safe_load(f)
+
+    # Get project name from compose file or default
+    project_name = compose.get("name", "autogpt_platform")
+
+    def get_image_name(dockerfile: str, target: str) -> str:
+        """Generate image name based on Dockerfile folder and build target."""
+        dockerfile_parts = dockerfile.replace("\\", "/").split("/")
+        if len(dockerfile_parts) >= 2:
+            folder_name = dockerfile_parts[-2]  # e.g., "backend" or "frontend"
+        else:
+            folder_name = "app"
+        return f"{project_name}-{folder_name}:{target}"
+
+    def get_build_key(dockerfile: str, target: str) -> str:
+        """Generate a unique key for a Dockerfile+target combination."""
+        return f"{dockerfile}:{target}"
+
+    def get_component(dockerfile: str) -> str | None:
+        """Get component name (frontend/backend) from dockerfile path."""
+        for component in CACHE_BUILDS_FOR_COMPONENTS:
+            if component in dockerfile:
+                return component
+        return None
+
+    # First pass: collect all services with build configs and identify duplicates
+    # Track which (dockerfile, target) combinations we've seen
+    build_key_to_first_service: dict[str, str] = {}
+    services_to_build: list[str] = []
+    services_to_dedupe: list[str] = []
+
+    for service_name, service_config in compose.get("services", {}).items():
+        if "build" not in service_config:
+            continue
+
+        build_config = service_config["build"]
+        dockerfile = build_config.get("dockerfile", "Dockerfile")
+        target = build_config.get("target", "default")
+        build_key = get_build_key(dockerfile, target)
+
+        if build_key not in build_key_to_first_service:
+            # First service with this build config - it will do the actual build
+            build_key_to_first_service[build_key] = service_name
+            services_to_build.append(service_name)
+        else:
+            # Duplicate - will just use the image from the first service
+            services_to_dedupe.append(service_name)
+
+    # Second pass: configure builds and deduplicate
+    modified_services = []
+    for service_name, service_config in compose.get("services", {}).items():
+        if "build" not in service_config:
+            continue
+
+        build_config = service_config["build"]
+        dockerfile = build_config.get("dockerfile", "Dockerfile")
+        target = build_config.get("target", "latest")
+        image_name = get_image_name(dockerfile, target)
+
+        # Set image name for all services (needed for both builders and deduped)
+        service_config["image"] = image_name
+
+        if service_name in services_to_dedupe:
+            # Remove build config - this service will use the pre-built image
+            del service_config["build"]
+            continue
+
+        # This service will do the actual build - add cache config
+        cache_from_list = []
+        cache_to_list = []
+
+        component = get_component(dockerfile)
+        if not component:
+            # Skip services that don't clearly match frontend/backend
+            continue
+
+        # Get the hash for this component
+        component_hash = getattr(args, f"{component}_hash")
+
+        # Scope format: platform-{component}-{target}-{hash|ref}
+        # Example: platform-backend-server-abc123
+
+        if "type=gha" in args.cache_from:
+            # 1. Primary: exact hash match (most specific)
+            if component_hash:
+                hash_scope = f"platform-{component}-{target}-{component_hash}"
+                cache_from_list.append(f"{args.cache_from},scope={hash_scope}")
+
+            # 2. Fallback: branch-based cache
+            if git_ref_scope:
+                ref_scope = f"platform-{component}-{target}-{git_ref_scope}"
+                cache_from_list.append(f"{args.cache_from},scope={ref_scope}")
+
+            # 3. Fallback: dev branch cache (for PRs/feature branches)
+            if git_ref_scope and git_ref_scope != DEFAULT_BRANCH:
+                master_scope = f"platform-{component}-{target}-{DEFAULT_BRANCH}"
+                cache_from_list.append(f"{args.cache_from},scope={master_scope}")
+
+        if "type=gha" in args.cache_to:
+            # Write to both hash-based and branch-based scopes
+            if component_hash:
+                hash_scope = f"platform-{component}-{target}-{component_hash}"
+                cache_to_list.append(f"{args.cache_to},scope={hash_scope}")
+
+            if git_ref_scope:
+                ref_scope = f"platform-{component}-{target}-{git_ref_scope}"
+                cache_to_list.append(f"{args.cache_to},scope={ref_scope}")
+
+        # Ensure we have at least one cache source/target
+        if not cache_from_list:
+            cache_from_list.append(args.cache_from)
+        if not cache_to_list:
+            cache_to_list.append(args.cache_to)
+
+        build_config["cache_from"] = cache_from_list
+        build_config["cache_to"] = cache_to_list
+        modified_services.append(service_name)
+
+    # Write back to the same file
+    with open(args.source, "w") as f:
+        yaml.dump(compose, f, default_flow_style=False, sort_keys=False)
+
+    print(f"Added cache config to {len(modified_services)} services in {args.source}:")
+    for svc in modified_services:
+        svc_config = compose["services"][svc]
+        build_cfg = svc_config.get("build", {})
+        cache_from_list = build_cfg.get("cache_from", ["none"])
+        cache_to_list = build_cfg.get("cache_to", ["none"])
+        print(f"  - {svc}")
+        print(f"      image: {svc_config.get('image', 'N/A')}")
+        print(f"      cache_from: {cache_from_list}")
+        print(f"      cache_to: {cache_to_list}")
+    if services_to_dedupe:
+        print(
+            f"Deduplicated {len(services_to_dedupe)} services (will use pre-built images):"
+        )
+        for svc in services_to_dedupe:
+            print(f"  - {svc} -> {compose['services'][svc].get('image', 'N/A')}")
+
+
+if __name__ == "__main__":
+    main()

.gitignore

@@ -180,4 +180,6 @@ autogpt_platform/backend/settings.py
 .claude/settings.local.json
 CLAUDE.local.md
 /autogpt_platform/backend/logs
-.next
+.next
+# Implementation plans (generated by AI agents)
+plans/

.nvmrc

@@ -0,0 +1 @@
+22

.pre-commit-config.yaml

@@ -1,3 +1,10 @@
+default_install_hook_types:
+  - pre-commit
+  - pre-push
+  - post-checkout
+
+default_stages: [pre-commit]
+
 repos:
   - repo: https://github.com/pre-commit/pre-commit-hooks
     rev: v4.4.0
@@ -17,6 +24,7 @@ repos:
         name: Detect secrets
         description: Detects high entropy strings that are likely to be passwords.
         files: ^autogpt_platform/
+        exclude: pnpm-lock\.yaml$
         stages: [pre-push]
 
   - repo: local
@@ -26,49 +34,106 @@ repos:
       - id: poetry-install
         name: Check & Install dependencies - AutoGPT Platform - Backend
         alias: poetry-install-platform-backend
-        entry: poetry -C autogpt_platform/backend install
         # include autogpt_libs source (since it's a path dependency)
-        files: ^autogpt_platform/(backend|autogpt_libs)/poetry\.lock$
-        types: [file]
+        entry: >
+          bash -c '
+          if [ -n "$PRE_COMMIT_FROM_REF" ]; then
+            git diff --name-only "$PRE_COMMIT_FROM_REF" "$PRE_COMMIT_TO_REF"
+          else
+            git diff --cached --name-only
+          fi | grep -qE "^autogpt_platform/(backend|autogpt_libs)/poetry\.lock$" || exit 0;
+          poetry -C autogpt_platform/backend install
+          '
+        always_run: true
         language: system
         pass_filenames: false
+        stages: [pre-commit, post-checkout]
 
       - id: poetry-install
         name: Check & Install dependencies - AutoGPT Platform - Libs
         alias: poetry-install-platform-libs
-        entry: poetry -C autogpt_platform/autogpt_libs install
-        files: ^autogpt_platform/autogpt_libs/poetry\.lock$
-        types: [file]
+        entry: >
+          bash -c '
+          if [ -n "$PRE_COMMIT_FROM_REF" ]; then
+            git diff --name-only "$PRE_COMMIT_FROM_REF" "$PRE_COMMIT_TO_REF"
+          else
+            git diff --cached --name-only
+          fi | grep -qE "^autogpt_platform/autogpt_libs/poetry\.lock$" || exit 0;
+          poetry -C autogpt_platform/autogpt_libs install
+          '
+        always_run: true
         language: system
         pass_filenames: false
+        stages: [pre-commit, post-checkout]
+
+      - id: pnpm-install
+        name: Check & Install dependencies - AutoGPT Platform - Frontend
+        alias: pnpm-install-platform-frontend
+        entry: >
+          bash -c '
+          if [ -n "$PRE_COMMIT_FROM_REF" ]; then
+            git diff --name-only "$PRE_COMMIT_FROM_REF" "$PRE_COMMIT_TO_REF"
+          else
+            git diff --cached --name-only
+          fi | grep -qE "^autogpt_platform/frontend/pnpm-lock\.yaml$" || exit 0;
+          pnpm --prefix autogpt_platform/frontend install
+          '
+        always_run: true
+        language: system
+        pass_filenames: false
+        stages: [pre-commit, post-checkout]
 
       - id: poetry-install
         name: Check & Install dependencies - Classic - AutoGPT
         alias: poetry-install-classic-autogpt
-        entry: poetry -C classic/original_autogpt install
+        entry: >
+          bash -c '
+          if [ -n "$PRE_COMMIT_FROM_REF" ]; then
+            git diff --name-only "$PRE_COMMIT_FROM_REF" "$PRE_COMMIT_TO_REF"
+          else
+            git diff --cached --name-only
+          fi | grep -qE "^classic/(original_autogpt|forge)/poetry\.lock$" || exit 0;
+          poetry -C classic/original_autogpt install
+          '
         # include forge source (since it's a path dependency)
-        files: ^classic/(original_autogpt|forge)/poetry\.lock$
-        types: [file]
+        always_run: true
         language: system
         pass_filenames: false
+        stages: [pre-commit, post-checkout]
 
       - id: poetry-install
         name: Check & Install dependencies - Classic - Forge
         alias: poetry-install-classic-forge
-        entry: poetry -C classic/forge install
-        files: ^classic/forge/poetry\.lock$
-        types: [file]
+        entry: >
+          bash -c '
+          if [ -n "$PRE_COMMIT_FROM_REF" ]; then
+            git diff --name-only "$PRE_COMMIT_FROM_REF" "$PRE_COMMIT_TO_REF"
+          else
+            git diff --cached --name-only
+          fi | grep -qE "^classic/forge/poetry\.lock$" || exit 0;
+          poetry -C classic/forge install
+          '
+        always_run: true
         language: system
         pass_filenames: false
+        stages: [pre-commit, post-checkout]
 
       - id: poetry-install
         name: Check & Install dependencies - Classic - Benchmark
         alias: poetry-install-classic-benchmark
-        entry: poetry -C classic/benchmark install
-        files: ^classic/benchmark/poetry\.lock$
-        types: [file]
+        entry: >
+          bash -c '
+          if [ -n "$PRE_COMMIT_FROM_REF" ]; then
+            git diff --name-only "$PRE_COMMIT_FROM_REF" "$PRE_COMMIT_TO_REF"
+          else
+            git diff --cached --name-only
+          fi | grep -qE "^classic/benchmark/poetry\.lock$" || exit 0;
+          poetry -C classic/benchmark install
+          '
+        always_run: true
         language: system
         pass_filenames: false
+        stages: [pre-commit, post-checkout]
 
   - repo: local
     # For proper type checking, Prisma client must be up-to-date.
@@ -76,12 +141,54 @@ repos:
       - id: prisma-generate
         name: Prisma Generate - AutoGPT Platform - Backend
         alias: prisma-generate-platform-backend
-        entry: bash -c 'cd autogpt_platform/backend && poetry run prisma generate'
+        entry: >
+          bash -c '
+          if [ -n "$PRE_COMMIT_FROM_REF" ]; then
+            git diff --name-only "$PRE_COMMIT_FROM_REF" "$PRE_COMMIT_TO_REF"
+          else
+            git diff --cached --name-only
+          fi | grep -qE "^autogpt_platform/((backend|autogpt_libs)/poetry\.lock|backend/schema\.prisma)$" || exit 0;
+          cd autogpt_platform/backend
+          && poetry run prisma generate
+          && poetry run gen-prisma-stub
+          '
         # include everything that triggers poetry install + the prisma schema
-        files: ^autogpt_platform/((backend|autogpt_libs)/poetry\.lock|backend/schema.prisma)$
-        types: [file]
+        always_run: true
         language: system
         pass_filenames: false
+        stages: [pre-commit, post-checkout]
+
+      - id: export-api-schema
+        name: Export API schema - AutoGPT Platform - Backend -> Frontend
+        alias: export-api-schema-platform
+        entry: >
+          bash -c '
+          cd autogpt_platform/backend
+          && poetry run export-api-schema --output ../frontend/src/app/api/openapi.json
+          && cd ../frontend
+          && pnpm prettier --write ./src/app/api/openapi.json
+          '
+        files: ^autogpt_platform/backend/
+        language: system
+        pass_filenames: false
+
+      - id: generate-api-client
+        name: Generate API client - AutoGPT Platform - Frontend
+        alias: generate-api-client-platform-frontend
+        entry: >
+          bash -c '
+          SCHEMA=autogpt_platform/frontend/src/app/api/openapi.json;
+          if [ -n "$PRE_COMMIT_FROM_REF" ]; then
+            git diff --quiet "$PRE_COMMIT_FROM_REF" "$PRE_COMMIT_TO_REF" -- "$SCHEMA" && exit 0
+          else
+            git diff --quiet HEAD -- "$SCHEMA" && exit 0
+          fi;
+          cd autogpt_platform/frontend && pnpm generate:api
+          '
+        always_run: true
+        language: system
+        pass_filenames: false
+        stages: [pre-commit, post-checkout]
 
   - repo: https://github.com/astral-sh/ruff-pre-commit
     rev: v0.7.2

autogpt_platform/.gitignore

@@ -1,2 +1,3 @@
 *.ignore.*
-*.ign.*
+*.ign.*
+.application.logs

autogpt_platform/CLAUDE.md

@@ -45,6 +45,11 @@ AutoGPT Platform is a monorepo containing:
 - Backend/Frontend services use YAML anchors for consistent configuration
 - Supabase services (`db/docker/docker-compose.yml`) follow the same pattern
 
+### Branching Strategy
+
+- **`dev`** is the main development branch. All PRs should target `dev`.
+- **`master`** is the production branch. Only used for production releases.
+
 ### Creating Pull Requests
 
 - Create the PR against the `dev` branch of the repository.

autogpt_platform/autogpt_libs/poetry.lock

@@ -448,61 +448,61 @@ toml = ["tomli ; python_full_version <= \"3.11.0a6\""]
 
 [[package]]
 name = "cryptography"
-version = "46.0.4"
+version = "46.0.5"
 description = "cryptography is a package which provides cryptographic recipes and primitives to Python developers."
 optional = false
 python-versions = "!=3.9.0,!=3.9.1,>=3.8"
 groups = ["main"]
 files = [
-    {file = "cryptography-46.0.4-cp311-abi3-macosx_10_9_universal2.whl", hash = "sha256:281526e865ed4166009e235afadf3a4c4cba6056f99336a99efba65336fd5485"},
-    {file = "cryptography-46.0.4-cp311-abi3-manylinux2014_aarch64.manylinux_2_17_aarch64.whl", hash = "sha256:5f14fba5bf6f4390d7ff8f086c566454bff0411f6d8aa7af79c88b6f9267aecc"},
-    {file = "cryptography-46.0.4-cp311-abi3-manylinux2014_x86_64.manylinux_2_17_x86_64.whl", hash = "sha256:47bcd19517e6389132f76e2d5303ded6cf3f78903da2158a671be8de024f4cd0"},
-    {file = "cryptography-46.0.4-cp311-abi3-manylinux_2_28_aarch64.whl", hash = "sha256:01df4f50f314fbe7009f54046e908d1754f19d0c6d3070df1e6268c5a4af09fa"},
-    {file = "cryptography-46.0.4-cp311-abi3-manylinux_2_28_ppc64le.whl", hash = "sha256:5aa3e463596b0087b3da0dbe2b2487e9fc261d25da85754e30e3b40637d61f81"},
-    {file = "cryptography-46.0.4-cp311-abi3-manylinux_2_28_x86_64.whl", hash = "sha256:0a9ad24359fee86f131836a9ac3bffc9329e956624a2d379b613f8f8abaf5255"},
-    {file = "cryptography-46.0.4-cp311-abi3-manylinux_2_31_armv7l.whl", hash = "sha256:dc1272e25ef673efe72f2096e92ae39dea1a1a450dd44918b15351f72c5a168e"},
-    {file = "cryptography-46.0.4-cp311-abi3-manylinux_2_34_aarch64.whl", hash = "sha256:de0f5f4ec8711ebc555f54735d4c673fc34b65c44283895f1a08c2b49d2fd99c"},
-    {file = "cryptography-46.0.4-cp311-abi3-manylinux_2_34_ppc64le.whl", hash = "sha256:eeeb2e33d8dbcccc34d64651f00a98cb41b2dc69cef866771a5717e6734dfa32"},
-    {file = "cryptography-46.0.4-cp311-abi3-manylinux_2_34_x86_64.whl", hash = "sha256:3d425eacbc9aceafd2cb429e42f4e5d5633c6f873f5e567077043ef1b9bbf616"},
-    {file = "cryptography-46.0.4-cp311-abi3-musllinux_1_2_aarch64.whl", hash = "sha256:91627ebf691d1ea3976a031b61fb7bac1ccd745afa03602275dda443e11c8de0"},
-    {file = "cryptography-46.0.4-cp311-abi3-musllinux_1_2_x86_64.whl", hash = "sha256:2d08bc22efd73e8854b0b7caff402d735b354862f1145d7be3b9c0f740fef6a0"},
-    {file = "cryptography-46.0.4-cp311-abi3-win32.whl", hash = "sha256:82a62483daf20b8134f6e92898da70d04d0ef9a75829d732ea1018678185f4f5"},
-    {file = "cryptography-46.0.4-cp311-abi3-win_amd64.whl", hash = "sha256:6225d3ebe26a55dbc8ead5ad1265c0403552a63336499564675b29eb3184c09b"},
-    {file = "cryptography-46.0.4-cp314-cp314t-macosx_10_9_universal2.whl", hash = "sha256:485e2b65d25ec0d901bca7bcae0f53b00133bf3173916d8e421f6fddde103908"},
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@@ -516,7 +516,7 @@ nox = ["nox[uv] (>=2024.4.15)"]
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 test-randomorder = ["pytest-randomly"]
 
 [[package]]
@@ -570,24 +570,25 @@ tests = ["coverage", "coveralls", "dill", "mock", "nose"]
 
 [[package]]
 name = "fastapi"
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+version = "0.128.7"
 description = "FastAPI framework, high performance, easy to learn, fast to code, ready for production"
 optional = false
 python-versions = ">=3.9"
 groups = ["main"]
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 pydantic = ">=2.7.0"
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+starlette = ">=0.40.0,<1.0.0"
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 [package.extras]
-all = ["email-validator (>=2.0.0)", "fastapi-cli[standard] (>=0.0.8)", "httpx (>=0.23.0,<1.0.0)", "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)"]
+all = ["email-validator (>=2.0.0)", "fastapi-cli[standard] (>=0.0.8)", "httpx (>=0.23.0,<1.0.0)", "itsdangerous (>=1.1.0)", "jinja2 (>=3.1.5)", "orjson (>=3.9.3)", "pydantic-extra-types (>=2.0.0)", "pydantic-settings (>=2.0.0)", "python-multipart (>=0.0.18)", "pyyaml (>=5.3.1)", "ujson (>=5.8.0)", "uvicorn[standard] (>=0.12.0)"]
 standard = ["email-validator (>=2.0.0)", "fastapi-cli[standard] (>=0.0.8)", "httpx (>=0.23.0,<1.0.0)", "jinja2 (>=3.1.5)", "pydantic-extra-types (>=2.0.0)", "pydantic-settings (>=2.0.0)", "python-multipart (>=0.0.18)", "uvicorn[standard] (>=0.12.0)"]
 standard-no-fastapi-cloud-cli = ["email-validator (>=2.0.0)", "fastapi-cli[standard-no-fastapi-cloud-cli] (>=0.0.8)", "httpx (>=0.23.0,<1.0.0)", "jinja2 (>=3.1.5)", "pydantic-extra-types (>=2.0.0)", "pydantic-settings (>=2.0.0)", "python-multipart (>=0.0.18)", "uvicorn[standard] (>=0.12.0)"]
 
@@ -1062,14 +1063,14 @@ urllib3 = ">=1.26.0,<3"
 
 [[package]]
 name = "launchdarkly-server-sdk"
-version = "9.14.1"
+version = "9.15.0"
 description = "LaunchDarkly SDK for Python"
 optional = false
-python-versions = ">=3.9"
+python-versions = ">=3.10"
 groups = ["main"]
 files = [
-    {file = "launchdarkly_server_sdk-9.14.1-py3-none-any.whl", hash = "sha256:a9e2bd9ecdef845cd631ae0d4334a1115e5b44257c42eb2349492be4bac7815c"},
-    {file = "launchdarkly_server_sdk-9.14.1.tar.gz", hash = "sha256:1df44baf0a0efa74d8c1dad7a00592b98bce7d19edded7f770da8dbc49922213"},
+    {file = "launchdarkly_server_sdk-9.15.0-py3-none-any.whl", hash = "sha256:c267e29bfa3fb5e2a06a208448ada6ed5557a2924979b8d79c970b45d227c668"},
+    {file = "launchdarkly_server_sdk-9.15.0.tar.gz", hash = "sha256:f31441b74bc1a69c381db57c33116509e407a2612628ad6dff0a7dbb39d5020b"},
 ]
 
 [package.dependencies]
@@ -1478,14 +1479,14 @@ testing = ["coverage", "pytest", "pytest-benchmark"]
 
 [[package]]
 name = "postgrest"
-version = "2.27.2"
+version = "2.28.0"
 description = "PostgREST client for Python. This library provides an ORM interface to PostgREST."
 optional = false
 python-versions = ">=3.9"
 groups = ["main"]
 files = [
-    {file = "postgrest-2.27.2-py3-none-any.whl", hash = "sha256:1666fef3de05ca097a314433dd5ae2f2d71c613cb7b233d0f468c4ffe37277da"},
-    {file = "postgrest-2.27.2.tar.gz", hash = "sha256:55407d530b5af3d64e883a71fec1f345d369958f723ce4a8ab0b7d169e313242"},
+    {file = "postgrest-2.28.0-py3-none-any.whl", hash = "sha256:7bca2f24dd1a1bf8a3d586c7482aba6cd41662da6733045fad585b63b7f7df75"},
+    {file = "postgrest-2.28.0.tar.gz", hash = "sha256:c36b38646d25ea4255321d3d924ce70f8d20ec7799cb42c1221d6a818d4f6515"},
 ]
 
 [package.dependencies]
@@ -2248,14 +2249,14 @@ cli = ["click (>=5.0)"]
 
 [[package]]
 name = "realtime"
-version = "2.27.2"
+version = "2.28.0"
 description = ""
 optional = false
 python-versions = ">=3.9"
 groups = ["main"]
 files = [
-    {file = "realtime-2.27.2-py3-none-any.whl", hash = "sha256:34a9cbb26a274e707e8fc9e3ee0a66de944beac0fe604dc336d1e985db2c830f"},
-    {file = "realtime-2.27.2.tar.gz", hash = "sha256:b960a90294d2cea1b3f1275ecb89204304728e08fff1c393cc1b3150739556b3"},
+    {file = "realtime-2.28.0-py3-none-any.whl", hash = "sha256:db1bd59bab9b1fcc9f9d3b1a073bed35bf4994d720e6751f10031a58d57a3836"},
+    {file = "realtime-2.28.0.tar.gz", hash = "sha256:d18cedcebd6a8f22fcd509bc767f639761eb218b7b2b6f14fc4205b6259b50fc"},
 ]
 
 [package.dependencies]
@@ -2436,14 +2437,14 @@ full = ["httpx (>=0.27.0,<0.29.0)", "itsdangerous", "jinja2", "python-multipart
 
 [[package]]
 name = "storage3"
-version = "2.27.2"
+version = "2.28.0"
 description = "Supabase Storage client for Python."
 optional = false
 python-versions = ">=3.9"
 groups = ["main"]
 files = [
-    {file = "storage3-2.27.2-py3-none-any.whl", hash = "sha256:e6f16e7a260729e7b1f46e9bf61746805a02e30f5e419ee1291007c432e3ec63"},
-    {file = "storage3-2.27.2.tar.gz", hash = "sha256:cb4807b7f86b4bb1272ac6fdd2f3cfd8ba577297046fa5f88557425200275af5"},
+    {file = "storage3-2.28.0-py3-none-any.whl", hash = "sha256:ecb50efd2ac71dabbdf97e99ad346eafa630c4c627a8e5a138ceb5fbbadae716"},
+    {file = "storage3-2.28.0.tar.gz", hash = "sha256:bc1d008aff67de7a0f2bd867baee7aadbcdb6f78f5a310b4f7a38e8c13c19865"},
 ]
 
 [package.dependencies]
@@ -2487,35 +2488,35 @@ python-dateutil = ">=2.6.0"
 
 [[package]]
 name = "supabase"
-version = "2.27.2"
+version = "2.28.0"
 description = "Supabase client for Python."
 optional = false
 python-versions = ">=3.9"
 groups = ["main"]
 files = [
-    {file = "supabase-2.27.2-py3-none-any.whl", hash = "sha256:d4dce00b3a418ee578017ec577c0e5be47a9a636355009c76f20ed2faa15bc54"},
-    {file = "supabase-2.27.2.tar.gz", hash = "sha256:2aed40e4f3454438822442a1e94a47be6694c2c70392e7ae99b51a226d4293f7"},
+    {file = "supabase-2.28.0-py3-none-any.whl", hash = "sha256:42776971c7d0ccca16034df1ab96a31c50228eb1eb19da4249ad2f756fc20272"},
+    {file = "supabase-2.28.0.tar.gz", hash = "sha256:aea299aaab2a2eed3c57e0be7fc035c6807214194cce795a3575add20268ece1"},
 ]
 
 [package.dependencies]
 httpx = ">=0.26,<0.29"
-postgrest = "2.27.2"
-realtime = "2.27.2"
-storage3 = "2.27.2"
-supabase-auth = "2.27.2"
-supabase-functions = "2.27.2"
+postgrest = "2.28.0"
+realtime = "2.28.0"
+storage3 = "2.28.0"
+supabase-auth = "2.28.0"
+supabase-functions = "2.28.0"
 yarl = ">=1.22.0"
 
 [[package]]
 name = "supabase-auth"
-version = "2.27.2"
+version = "2.28.0"
 description = "Python Client Library for Supabase Auth"
 optional = false
 python-versions = ">=3.9"
 groups = ["main"]
 files = [
-    {file = "supabase_auth-2.27.2-py3-none-any.whl", hash = "sha256:78ec25b11314d0a9527a7205f3b1c72560dccdc11b38392f80297ef98664ee91"},
-    {file = "supabase_auth-2.27.2.tar.gz", hash = "sha256:0f5bcc79b3677cb42e9d321f3c559070cfa40d6a29a67672cc8382fb7dc2fe97"},
+    {file = "supabase_auth-2.28.0-py3-none-any.whl", hash = "sha256:2ac85026cc285054c7fa6d41924f3a333e9ec298c013e5b5e1754039ba7caec9"},
+    {file = "supabase_auth-2.28.0.tar.gz", hash = "sha256:2bb8f18ff39934e44b28f10918db965659f3735cd6fbfcc022fe0b82dbf8233e"},
 ]
 
 [package.dependencies]
@@ -2525,14 +2526,14 @@ pyjwt = {version = ">=2.10.1", extras = ["crypto"]}
 
 [[package]]
 name = "supabase-functions"
-version = "2.27.2"
+version = "2.28.0"
 description = "Library for Supabase Functions"
 optional = false
 python-versions = ">=3.9"
 groups = ["main"]
 files = [
-    {file = "supabase_functions-2.27.2-py3-none-any.whl", hash = "sha256:db480efc669d0bca07605b9b6f167312af43121adcc842a111f79bea416ef754"},
-    {file = "supabase_functions-2.27.2.tar.gz", hash = "sha256:d0c8266207a94371cb3fd35ad3c7f025b78a97cf026861e04ccd35ac1775f80b"},
+    {file = "supabase_functions-2.28.0-py3-none-any.whl", hash = "sha256:30bf2d586f8df285faf0621bb5d5bb3ec3157234fc820553ca156f009475e4ae"},
+    {file = "supabase_functions-2.28.0.tar.gz", hash = "sha256:db3dddfc37aca5858819eb461130968473bd8c75bd284581013958526dac718b"},
 ]
 
 [package.dependencies]
@@ -2911,4 +2912,4 @@ type = ["pytest-mypy"]
 [metadata]
 lock-version = "2.1"
 python-versions = ">=3.10,<4.0"
-content-hash = "40eae94995dc0a388fa832ed4af9b6137f28d5b5ced3aaea70d5f91d4d9a179d"
+content-hash = "9619cae908ad38fa2c48016a58bcf4241f6f5793aa0e6cc140276e91c433cbbb"

autogpt_platform/autogpt_libs/pyproject.toml

@@ -11,14 +11,14 @@ python = ">=3.10,<4.0"
 colorama = "^0.4.6"
 cryptography = "^46.0"
 expiringdict = "^1.2.2"
-fastapi = "^0.128.0"
+fastapi = "^0.128.7"
 google-cloud-logging = "^3.13.0"
-launchdarkly-server-sdk = "^9.14.1"
+launchdarkly-server-sdk = "^9.15.0"
 pydantic = "^2.12.5"
 pydantic-settings = "^2.12.0"
 pyjwt = { version = "^2.11.0", extras = ["crypto"] }
 redis = "^6.2.0"
-supabase = "^2.27.2"
+supabase = "^2.28.0"
 uvicorn = "^0.40.0"
 
 [tool.poetry.group.dev.dependencies]

autogpt_platform/backend/.env.default

@@ -104,6 +104,12 @@ TWITTER_CLIENT_SECRET=
 # Make a new workspace for your OAuth APP -- trust me
 # https://linear.app/settings/api/applications/new
 # Callback URL: http://localhost:3000/auth/integrations/oauth_callback
+LINEAR_API_KEY=
+# Linear project and team IDs for the feature request tracker.
+# Find these in your Linear workspace URL: linear.app/<workspace>/project/<project-id>
+# and in team settings. Used by the chat copilot to file and search feature requests.
+LINEAR_FEATURE_REQUEST_PROJECT_ID=
+LINEAR_FEATURE_REQUEST_TEAM_ID=
 LINEAR_CLIENT_ID=
 LINEAR_CLIENT_SECRET=
 
@@ -184,5 +190,8 @@ ZEROBOUNCE_API_KEY=
 POSTHOG_API_KEY=
 POSTHOG_HOST=https://eu.i.posthog.com
 
+# Tally Form Integration (pre-populate business understanding on signup)
+TALLY_API_KEY=
+
 # Other Services
 AUTOMOD_API_KEY=

autogpt_platform/backend/Dockerfile

@@ -1,3 +1,5 @@
+# ============================ DEPENDENCY BUILDER ============================ #
+
 FROM debian:13-slim AS builder
 
 # Set environment variables
@@ -51,60 +53,106 @@ COPY autogpt_platform/backend/backend/data/partial_types.py ./backend/data/parti
 COPY autogpt_platform/backend/gen_prisma_types_stub.py ./
 RUN poetry run prisma generate && poetry run gen-prisma-stub
 
-FROM debian:13-slim AS server_dependencies
+# =============================== DB MIGRATOR =============================== #
+
+# Lightweight migrate stage - only needs Prisma CLI, not full Python environment
+FROM debian:13-slim AS migrate
+
+WORKDIR /app/autogpt_platform/backend
+
+ENV DEBIAN_FRONTEND=noninteractive
+
+# Install only what's needed for prisma migrate: Node.js and minimal Python for prisma-python
+RUN apt-get update && apt-get install -y --no-install-recommends \
+    python3.13 \
+    python3-pip \
+    ca-certificates \
+    && rm -rf /var/lib/apt/lists/*
+
+# Copy Node.js from builder (needed for Prisma CLI)
+COPY --from=builder /usr/bin/node /usr/bin/node
+COPY --from=builder /usr/lib/node_modules /usr/lib/node_modules
+COPY --from=builder /usr/bin/npm /usr/bin/npm
+
+# Copy Prisma binaries
+COPY --from=builder /root/.cache/prisma-python/binaries /root/.cache/prisma-python/binaries
+
+# Install prisma-client-py directly (much smaller than copying full venv)
+RUN pip3 install prisma>=0.15.0 --break-system-packages
+
+COPY autogpt_platform/backend/schema.prisma ./
+COPY autogpt_platform/backend/backend/data/partial_types.py ./backend/data/partial_types.py
+COPY autogpt_platform/backend/gen_prisma_types_stub.py ./
+COPY autogpt_platform/backend/migrations ./migrations
+
+# ============================== BACKEND SERVER ============================== #
+
+FROM debian:13-slim AS server
 
 WORKDIR /app
 
-ENV POETRY_HOME=/opt/poetry \
-    POETRY_NO_INTERACTION=1 \
-    POETRY_VIRTUALENVS_CREATE=true \
-    POETRY_VIRTUALENVS_IN_PROJECT=true \
-    DEBIAN_FRONTEND=noninteractive
-ENV PATH=/opt/poetry/bin:$PATH
+ENV DEBIAN_FRONTEND=noninteractive
 
-# Install Python, FFmpeg, and ImageMagick (required for video processing blocks)
-RUN apt-get update && apt-get install -y \
+# Install Python, FFmpeg, ImageMagick, and CLI tools for agent use.
+# bubblewrap provides OS-level sandbox (whitelist-only FS + no network)
+# for the bash_exec MCP tool (fallback when E2B is not configured).
+# Using --no-install-recommends saves ~650MB by skipping unnecessary deps like llvm, mesa, etc.
+RUN apt-get update && apt-get install -y --no-install-recommends \
     python3.13 \
     python3-pip \
     ffmpeg \
     imagemagick \
+    jq \
+    ripgrep \
+    tree \
+    bubblewrap \
     && rm -rf /var/lib/apt/lists/*
 
-# Copy only necessary files from builder
-COPY --from=builder /app /app
+# Copy poetry (build-time only, for `poetry install --only-root` to create entry points)
 COPY --from=builder /usr/local/lib/python3* /usr/local/lib/python3*
 COPY --from=builder /usr/local/bin/poetry /usr/local/bin/poetry
-# Copy Node.js installation for Prisma
+# Copy Node.js installation for Prisma and agent-browser.
+# npm/npx are symlinks in the builder (-> ../lib/node_modules/npm/bin/*-cli.js);
+# COPY resolves them to regular files, breaking require() paths.  Recreate as
+# proper symlinks so npm/npx can find their modules.
 COPY --from=builder /usr/bin/node /usr/bin/node
 COPY --from=builder /usr/lib/node_modules /usr/lib/node_modules
-COPY --from=builder /usr/bin/npm /usr/bin/npm
-COPY --from=builder /usr/bin/npx /usr/bin/npx
+RUN ln -s ../lib/node_modules/npm/bin/npm-cli.js /usr/bin/npm \
+    && ln -s ../lib/node_modules/npm/bin/npx-cli.js /usr/bin/npx
 COPY --from=builder /root/.cache/prisma-python/binaries /root/.cache/prisma-python/binaries
 
-ENV PATH="/app/autogpt_platform/backend/.venv/bin:$PATH"
-
-RUN mkdir -p /app/autogpt_platform/autogpt_libs
-RUN mkdir -p /app/autogpt_platform/backend
-
-COPY autogpt_platform/autogpt_libs /app/autogpt_platform/autogpt_libs
-
-COPY autogpt_platform/backend/poetry.lock autogpt_platform/backend/pyproject.toml /app/autogpt_platform/backend/
+# Install agent-browser (Copilot browser tool) + Chromium runtime dependencies.
+# These are the runtime libraries Chromium/Playwright needs on Debian 13 (trixie).
+RUN apt-get update && apt-get install -y --no-install-recommends \
+    libnss3 libnspr4 libatk1.0-0 libatk-bridge2.0-0 libcups2 libdrm2 \
+    libdbus-1-3 libxkbcommon0 libatspi2.0-0t64 libxcomposite1 libxdamage1 \
+    libxfixes3 libxrandr2 libgbm1 libasound2t64 libpango-1.0-0 libcairo2 \
+    libx11-6 libx11-xcb1 libxcb1 libxext6 libglib2.0-0t64 \
+    fonts-liberation libfontconfig1 \
+    && rm -rf /var/lib/apt/lists/* \
+    && npm install -g agent-browser \
+    && agent-browser install \
+    && rm -rf /tmp/* /root/.npm
 
 WORKDIR /app/autogpt_platform/backend
 
-FROM server_dependencies AS migrate
+# Copy only the .venv from builder (not the entire /app directory)
+# The .venv includes the generated Prisma client
+COPY --from=builder /app/autogpt_platform/backend/.venv ./.venv
+ENV PATH="/app/autogpt_platform/backend/.venv/bin:$PATH"
 
-# Migration stage only needs schema and migrations - much lighter than full backend
-COPY autogpt_platform/backend/schema.prisma /app/autogpt_platform/backend/
-COPY autogpt_platform/backend/backend/data/partial_types.py /app/autogpt_platform/backend/backend/data/partial_types.py
-COPY autogpt_platform/backend/migrations /app/autogpt_platform/backend/migrations
+# Copy dependency files + autogpt_libs (path dependency)
+COPY autogpt_platform/autogpt_libs /app/autogpt_platform/autogpt_libs
+COPY autogpt_platform/backend/poetry.lock autogpt_platform/backend/pyproject.toml ./
 
-FROM server_dependencies AS server
-
-COPY autogpt_platform/backend /app/autogpt_platform/backend
+# Copy backend code + docs (for Copilot docs search)
+COPY autogpt_platform/backend ./
 COPY docs /app/docs
-RUN poetry install --no-ansi --only-root
+# Install the project package to create entry point scripts in .venv/bin/
+# (e.g., rest, executor, ws, db, scheduler, notification - see [tool.poetry.scripts])
+RUN POETRY_VIRTUALENVS_CREATE=true POETRY_VIRTUALENVS_IN_PROJECT=true \
+    poetry install --no-ansi --only-root
 
 ENV PORT=8000
 
-CMD ["poetry", "run", "rest"]
+CMD ["rest"]

autogpt_platform/backend/backend/api/conftest.py

@@ -1,4 +1,9 @@
-"""Common test fixtures for server tests."""
+"""Common test fixtures for server tests.
+
+Note: Common fixtures like test_user_id, admin_user_id, target_user_id,
+setup_test_user, and setup_admin_user are defined in the parent conftest.py
+(backend/conftest.py) and are available here automatically.
+"""
 
 import pytest
 from pytest_snapshot.plugin import Snapshot
@@ -11,54 +16,6 @@ def configured_snapshot(snapshot: Snapshot) -> Snapshot:
     return snapshot
 
 
-@pytest.fixture
-def test_user_id() -> str:
-    """Test user ID fixture."""
-    return "3e53486c-cf57-477e-ba2a-cb02dc828e1a"
-
-
-@pytest.fixture
-def admin_user_id() -> str:
-    """Admin user ID fixture."""
-    return "4e53486c-cf57-477e-ba2a-cb02dc828e1b"
-
-
-@pytest.fixture
-def target_user_id() -> str:
-    """Target user ID fixture."""
-    return "5e53486c-cf57-477e-ba2a-cb02dc828e1c"
-
-
-@pytest.fixture
-async def setup_test_user(test_user_id):
-    """Create test user in database before tests."""
-    from backend.data.user import get_or_create_user
-
-    # Create the test user in the database using JWT token format
-    user_data = {
-        "sub": test_user_id,
-        "email": "test@example.com",
-        "user_metadata": {"name": "Test User"},
-    }
-    await get_or_create_user(user_data)
-    return test_user_id
-
-
-@pytest.fixture
-async def setup_admin_user(admin_user_id):
-    """Create admin user in database before tests."""
-    from backend.data.user import get_or_create_user
-
-    # Create the admin user in the database using JWT token format
-    user_data = {
-        "sub": admin_user_id,
-        "email": "test-admin@example.com",
-        "user_metadata": {"name": "Test Admin"},
-    }
-    await get_or_create_user(user_data)
-    return admin_user_id
-
-
 @pytest.fixture
 def mock_jwt_user(test_user_id):
     """Provide mock JWT payload for regular user testing."""

autogpt_platform/backend/backend/api/external/middleware.py

@@ -88,20 +88,23 @@ async def require_auth(
     )
 
 
-def require_permission(permission: APIKeyPermission):
+def require_permission(*permissions: APIKeyPermission):
     """
-    Dependency function for checking specific permissions
+    Dependency function for checking required permissions.
+    All listed permissions must be present.
     (works with API keys and OAuth tokens)
     """
 
-    async def check_permission(
+    async def check_permissions(
         auth: APIAuthorizationInfo = Security(require_auth),
     ) -> APIAuthorizationInfo:
-        if permission not in auth.scopes:
+        missing = [p for p in permissions if p not in auth.scopes]
+        if missing:
             raise HTTPException(
                 status_code=status.HTTP_403_FORBIDDEN,
-                detail=f"Missing required permission: {permission.value}",
+                detail=f"Missing required permission(s): "
+                f"{', '.join(p.value for p in missing)}",
             )
         return auth
 
-    return check_permission
+    return check_permissions

autogpt_platform/backend/backend/api/external/v1/routes.py

@@ -18,6 +18,7 @@ from backend.data import user as user_db
 from backend.data.auth.base import APIAuthorizationInfo
 from backend.data.block import BlockInput, CompletedBlockOutput
 from backend.executor.utils import add_graph_execution
+from backend.integrations.webhooks.graph_lifecycle_hooks import on_graph_activate
 from backend.util.settings import Settings
 
 from .integrations import integrations_router
@@ -95,6 +96,43 @@ async def execute_graph_block(
     return output
 
 
+@v1_router.post(
+    path="/graphs",
+    tags=["graphs"],
+    status_code=201,
+    dependencies=[
+        Security(
+            require_permission(
+                APIKeyPermission.WRITE_GRAPH, APIKeyPermission.WRITE_LIBRARY
+            )
+        )
+    ],
+)
+async def create_graph(
+    graph: graph_db.Graph,
+    auth: APIAuthorizationInfo = Security(
+        require_permission(APIKeyPermission.WRITE_GRAPH, APIKeyPermission.WRITE_LIBRARY)
+    ),
+) -> graph_db.GraphModel:
+    """
+    Create a new agent graph.
+
+    The graph will be validated and assigned a new ID.
+    It is automatically added to the user's library.
+    """
+    from backend.api.features.library import db as library_db
+
+    graph_model = graph_db.make_graph_model(graph, auth.user_id)
+    graph_model.reassign_ids(user_id=auth.user_id, reassign_graph_id=True)
+    graph_model.validate_graph(for_run=False)
+
+    await graph_db.create_graph(graph_model, user_id=auth.user_id)
+    await library_db.create_library_agent(graph_model, auth.user_id)
+    activated_graph = await on_graph_activate(graph_model, user_id=auth.user_id)
+
+    return activated_graph
+
+
 @v1_router.post(
     path="/graphs/{graph_id}/execute/{graph_version}",
     tags=["graphs"],

autogpt_platform/backend/backend/api/external/v1/tools.py

@@ -15,9 +15,9 @@ from prisma.enums import APIKeyPermission
 from pydantic import BaseModel, Field
 
 from backend.api.external.middleware import require_permission
-from backend.api.features.chat.model import ChatSession
-from backend.api.features.chat.tools import find_agent_tool, run_agent_tool
-from backend.api.features.chat.tools.models import ToolResponseBase
+from backend.copilot.model import ChatSession
+from backend.copilot.tools import find_agent_tool, run_agent_tool
+from backend.copilot.tools.models import ToolResponseBase
 from backend.data.auth.base import APIAuthorizationInfo
 
 logger = logging.getLogger(__name__)

autogpt_platform/backend/backend/api/features/builder/db.py

@@ -1,15 +1,17 @@
 import logging
 from dataclasses import dataclass
-from datetime import datetime, timedelta, timezone
 from difflib import SequenceMatcher
-from typing import Sequence
+from typing import Any, Sequence, get_args, get_origin
 
 import prisma
+from prisma.enums import ContentType
+from prisma.models import mv_suggested_blocks
 
 import backend.api.features.library.db as library_db
 import backend.api.features.library.model as library_model
 import backend.api.features.store.db as store_db
 import backend.api.features.store.model as store_model
+from backend.api.features.store.hybrid_search import unified_hybrid_search
 from backend.blocks import load_all_blocks
 from backend.blocks._base import (
     AnyBlockSchema,
@@ -19,7 +21,6 @@ from backend.blocks._base import (
     BlockType,
 )
 from backend.blocks.llm import LlmModel
-from backend.data.db import query_raw_with_schema
 from backend.integrations.providers import ProviderName
 from backend.util.cache import cached
 from backend.util.models import Pagination
@@ -42,6 +43,16 @@ MAX_LIBRARY_AGENT_RESULTS = 100
 MAX_MARKETPLACE_AGENT_RESULTS = 100
 MIN_SCORE_FOR_FILTERED_RESULTS = 10.0
 
+# Boost blocks over marketplace agents in search results
+BLOCK_SCORE_BOOST = 50.0
+
+# Block IDs to exclude from search results
+EXCLUDED_BLOCK_IDS = frozenset(
+    {
+        "e189baac-8c20-45a1-94a7-55177ea42565",  # AgentExecutorBlock
+    }
+)
+
 SearchResultItem = BlockInfo | library_model.LibraryAgent | store_model.StoreAgent
 
 
@@ -64,8 +75,8 @@ def get_block_categories(category_blocks: int = 3) -> list[BlockCategoryResponse
 
     for block_type in load_all_blocks().values():
         block: AnyBlockSchema = block_type()
-        # Skip disabled blocks
-        if block.disabled:
+        # Skip disabled and excluded blocks
+        if block.disabled or block.id in EXCLUDED_BLOCK_IDS:
             continue
         # Skip blocks that don't have categories (all should have at least one)
         if not block.categories:
@@ -116,6 +127,9 @@ def get_blocks(
         # Skip disabled blocks
         if block.disabled:
             continue
+        # Skip excluded blocks
+        if block.id in EXCLUDED_BLOCK_IDS:
+            continue
         # Skip blocks that don't match the category
         if category and category not in {c.name.lower() for c in block.categories}:
             continue
@@ -255,14 +269,25 @@ async def _build_cached_search_results(
         "my_agents": 0,
     }
 
-    block_results, block_total, integration_total = _collect_block_results(
-        normalized_query=normalized_query,
-        include_blocks=include_blocks,
-        include_integrations=include_integrations,
-    )
-    scored_items.extend(block_results)
-    total_items["blocks"] = block_total
-    total_items["integrations"] = integration_total
+    # Use hybrid search when query is present, otherwise list all blocks
+    if (include_blocks or include_integrations) and normalized_query:
+        block_results, block_total, integration_total = await _hybrid_search_blocks(
+            query=search_query,
+            include_blocks=include_blocks,
+            include_integrations=include_integrations,
+        )
+        scored_items.extend(block_results)
+        total_items["blocks"] = block_total
+        total_items["integrations"] = integration_total
+    elif include_blocks or include_integrations:
+        # No query - list all blocks using in-memory approach
+        block_results, block_total, integration_total = _collect_block_results(
+            include_blocks=include_blocks,
+            include_integrations=include_integrations,
+        )
+        scored_items.extend(block_results)
+        total_items["blocks"] = block_total
+        total_items["integrations"] = integration_total
 
     if include_library_agents:
         library_response = await library_db.list_library_agents(
@@ -307,10 +332,14 @@ async def _build_cached_search_results(
 
 def _collect_block_results(
     *,
-    normalized_query: str,
     include_blocks: bool,
     include_integrations: bool,
 ) -> tuple[list[_ScoredItem], int, int]:
+    """
+    Collect all blocks for listing (no search query).
+
+    All blocks get BLOCK_SCORE_BOOST to prioritize them over marketplace agents.
+    """
     results: list[_ScoredItem] = []
     block_count = 0
     integration_count = 0
@@ -323,6 +352,10 @@ def _collect_block_results(
         if block.disabled:
             continue
 
+        # Skip excluded blocks
+        if block.id in EXCLUDED_BLOCK_IDS:
+            continue
+
         block_info = block.get_info()
         credentials = list(block.input_schema.get_credentials_fields().values())
         is_integration = len(credentials) > 0
@@ -332,10 +365,6 @@ def _collect_block_results(
         if not is_integration and not include_blocks:
             continue
 
-        score = _score_block(block, block_info, normalized_query)
-        if not _should_include_item(score, normalized_query):
-            continue
-
         filter_type: FilterType = "integrations" if is_integration else "blocks"
         if is_integration:
             integration_count += 1
@@ -346,8 +375,122 @@ def _collect_block_results(
             _ScoredItem(
                 item=block_info,
                 filter_type=filter_type,
-                score=score,
-                sort_key=_get_item_name(block_info),
+                score=BLOCK_SCORE_BOOST,
+                sort_key=block_info.name.lower(),
+            )
+        )
+
+    return results, block_count, integration_count
+
+
+async def _hybrid_search_blocks(
+    *,
+    query: str,
+    include_blocks: bool,
+    include_integrations: bool,
+) -> tuple[list[_ScoredItem], int, int]:
+    """
+    Search blocks using hybrid search with builder-specific filtering.
+
+    Uses unified_hybrid_search for semantic + lexical search, then applies
+    post-filtering for block/integration types and scoring adjustments.
+
+    Scoring:
+        - Base: hybrid relevance score (0-1) scaled to 0-100, plus BLOCK_SCORE_BOOST
+          to prioritize blocks over marketplace agents in combined results
+        - +30 for exact name match, +15 for prefix name match
+        - +20 if the block has an LlmModel field and the query matches an LLM model name
+
+    Args:
+        query: The search query string
+        include_blocks: Whether to include regular blocks
+        include_integrations: Whether to include integration blocks
+
+    Returns:
+        Tuple of (scored_items, block_count, integration_count)
+    """
+    results: list[_ScoredItem] = []
+    block_count = 0
+    integration_count = 0
+
+    if not include_blocks and not include_integrations:
+        return results, block_count, integration_count
+
+    normalized_query = query.strip().lower()
+
+    # Fetch more results to account for post-filtering
+    search_results, _ = await unified_hybrid_search(
+        query=query,
+        content_types=[ContentType.BLOCK],
+        page=1,
+        page_size=150,
+        min_score=0.10,
+    )
+
+    # Load all blocks for getting BlockInfo
+    all_blocks = load_all_blocks()
+
+    for result in search_results:
+        block_id = result["content_id"]
+
+        # Skip excluded blocks
+        if block_id in EXCLUDED_BLOCK_IDS:
+            continue
+
+        metadata = result.get("metadata", {})
+        hybrid_score = result.get("relevance", 0.0)
+
+        # Get the actual block class
+        if block_id not in all_blocks:
+            continue
+
+        block_cls = all_blocks[block_id]
+        block: AnyBlockSchema = block_cls()
+
+        if block.disabled:
+            continue
+
+        # Check block/integration filter using metadata
+        is_integration = metadata.get("is_integration", False)
+
+        if is_integration and not include_integrations:
+            continue
+        if not is_integration and not include_blocks:
+            continue
+
+        # Get block info
+        block_info = block.get_info()
+
+        # Calculate final score: scale hybrid score and add builder-specific bonuses
+        # Hybrid scores are 0-1, builder scores were 0-200+
+        # Add BLOCK_SCORE_BOOST to prioritize blocks over marketplace agents
+        final_score = hybrid_score * 100 + BLOCK_SCORE_BOOST
+
+        # Add LLM model match bonus
+        has_llm_field = metadata.get("has_llm_model_field", False)
+        if has_llm_field and _matches_llm_model(block.input_schema, normalized_query):
+            final_score += 20
+
+        # Add exact/prefix match bonus for deterministic tie-breaking
+        name = block_info.name.lower()
+        if name == normalized_query:
+            final_score += 30
+        elif name.startswith(normalized_query):
+            final_score += 15
+
+        # Track counts
+        filter_type: FilterType = "integrations" if is_integration else "blocks"
+        if is_integration:
+            integration_count += 1
+        else:
+            block_count += 1
+
+        results.append(
+            _ScoredItem(
+                item=block_info,
+                filter_type=filter_type,
+                score=final_score,
+                sort_key=name,
             )
         )
 
@@ -472,6 +615,8 @@ async def _get_static_counts():
         block: AnyBlockSchema = block_type()
         if block.disabled:
             continue
+        if block.id in EXCLUDED_BLOCK_IDS:
+            continue
 
         all_blocks += 1
 
@@ -498,47 +643,25 @@ async def _get_static_counts():
     }
 
 
+def _contains_type(annotation: Any, target: type) -> bool:
+    """Check if an annotation is or contains the target type (handles Optional/Union/Annotated)."""
+    if annotation is target:
+        return True
+    origin = get_origin(annotation)
+    if origin is None:
+        return False
+    return any(_contains_type(arg, target) for arg in get_args(annotation))
+
+
 def _matches_llm_model(schema_cls: type[BlockSchema], query: str) -> bool:
     for field in schema_cls.model_fields.values():
-        if field.annotation == LlmModel:
+        if _contains_type(field.annotation, LlmModel):
             # Check if query matches any value in llm_models
             if any(query in name for name in llm_models):
                 return True
     return False
 
 
-def _score_block(
-    block: AnyBlockSchema,
-    block_info: BlockInfo,
-    normalized_query: str,
-) -> float:
-    if not normalized_query:
-        return 0.0
-
-    name = block_info.name.lower()
-    description = block_info.description.lower()
-    score = _score_primary_fields(name, description, normalized_query)
-
-    category_text = " ".join(
-        category.get("category", "").lower() for category in block_info.categories
-    )
-    score += _score_additional_field(category_text, normalized_query, 12, 6)
-
-    credentials_info = block.input_schema.get_credentials_fields_info().values()
-    provider_names = [
-        provider.value.lower()
-        for info in credentials_info
-        for provider in info.provider
-    ]
-    provider_text = " ".join(provider_names)
-    score += _score_additional_field(provider_text, normalized_query, 15, 6)
-
-    if _matches_llm_model(block.input_schema, normalized_query):
-        score += 20
-
-    return score
-
-
 def _score_library_agent(
     agent: library_model.LibraryAgent,
     normalized_query: str,
@@ -645,31 +768,20 @@ def _get_all_providers() -> dict[ProviderName, Provider]:
     return providers
 
 
-@cached(ttl_seconds=3600)
+@cached(ttl_seconds=3600, shared_cache=True)
 async def get_suggested_blocks(count: int = 5) -> list[BlockInfo]:
-    suggested_blocks = []
-    # Sum the number of executions for each block type
-    # Prisma cannot group by nested relations, so we do a raw query
-    # Calculate the cutoff timestamp
-    timestamp_threshold = datetime.now(timezone.utc) - timedelta(days=30)
+    """Return the most-executed blocks from the last 14 days.
 
-    results = await query_raw_with_schema(
-        """
-        SELECT
-            agent_node."agentBlockId" AS block_id,
-            COUNT(execution.id) AS execution_count
-        FROM {schema_prefix}"AgentNodeExecution" execution
-        JOIN {schema_prefix}"AgentNode" agent_node ON execution."agentNodeId" = agent_node.id
-        WHERE execution."endedTime" >= $1::timestamp
-        GROUP BY agent_node."agentBlockId"
-        ORDER BY execution_count DESC;
-        """,
-        timestamp_threshold,
-    )
+    Queries the mv_suggested_blocks materialized view (refreshed hourly via pg_cron)
+    and returns the top `count` blocks sorted by execution count, excluding
+    Input/Output/Agent block types and blocks in EXCLUDED_BLOCK_IDS.
+    """
+    results = await mv_suggested_blocks.prisma().find_many()
 
     # Get the top blocks based on execution count
-    # But ignore Input and Output blocks
+    # But ignore Input, Output, Agent, and excluded blocks
     blocks: list[tuple[BlockInfo, int]] = []
+    execution_counts = {row.block_id: row.execution_count for row in results}
 
     for block_type in load_all_blocks().values():
         block: AnyBlockSchema = block_type()
@@ -679,11 +791,9 @@ async def get_suggested_blocks(count: int = 5) -> list[BlockInfo]:
             BlockType.AGENT,
         ):
             continue
-        # Find the execution count for this block
-        execution_count = next(
-            (row["execution_count"] for row in results if row["block_id"] == block.id),
-            0,
-        )
+        if block.id in EXCLUDED_BLOCK_IDS:
+            continue
+        execution_count = execution_counts.get(block.id, 0)
         blocks.append((block.get_info(), execution_count))
     # Sort blocks by execution count
     blocks.sort(key=lambda x: x[1], reverse=True)

autogpt_platform/backend/backend/api/features/builder/model.py

@@ -27,7 +27,6 @@ class SearchEntry(BaseModel):
 
 # Suggestions
 class SuggestionsResponse(BaseModel):
-    otto_suggestions: list[str]
     recent_searches: list[SearchEntry]
     providers: list[ProviderName]
     top_blocks: list[BlockInfo]

autogpt_platform/backend/backend/api/features/builder/routes.py

@@ -1,5 +1,5 @@
 import logging
-from typing import Annotated, Sequence
+from typing import Annotated, Sequence, cast, get_args
 
 import fastapi
 from autogpt_libs.auth.dependencies import get_user_id, requires_user
@@ -10,6 +10,8 @@ from backend.util.models import Pagination
 from . import db as builder_db
 from . import model as builder_model
 
+VALID_FILTER_VALUES = get_args(builder_model.FilterType)
+
 logger = logging.getLogger(__name__)
 
 router = fastapi.APIRouter(
@@ -49,11 +51,6 @@ async def get_suggestions(
     Get all suggestions for the Blocks Menu.
     """
     return builder_model.SuggestionsResponse(
-        otto_suggestions=[
-            "What blocks do I need to get started?",
-            "Help me create a list",
-            "Help me feed my data to Google Maps",
-        ],
         recent_searches=await builder_db.get_recent_searches(user_id),
         providers=[
             ProviderName.TWITTER,
@@ -151,7 +148,7 @@ async def get_providers(
 async def search(
     user_id: Annotated[str, fastapi.Security(get_user_id)],
     search_query: Annotated[str | None, fastapi.Query()] = None,
-    filter: Annotated[list[builder_model.FilterType] | None, fastapi.Query()] = None,
+    filter: Annotated[str | None, fastapi.Query()] = None,
     search_id: Annotated[str | None, fastapi.Query()] = None,
     by_creator: Annotated[list[str] | None, fastapi.Query()] = None,
     page: Annotated[int, fastapi.Query()] = 1,
@@ -160,9 +157,20 @@ async def search(
     """
     Search for blocks (including integrations), marketplace agents, and user library agents.
     """
-    # If no filters are provided, then we will return all types
-    if not filter:
-        filter = [
+    # Parse and validate filter parameter
+    filters: list[builder_model.FilterType]
+    if filter:
+        filter_values = [f.strip() for f in filter.split(",")]
+        invalid_filters = [f for f in filter_values if f not in VALID_FILTER_VALUES]
+        if invalid_filters:
+            raise fastapi.HTTPException(
+                status_code=400,
+                detail=f"Invalid filter value(s): {', '.join(invalid_filters)}. "
+                f"Valid values are: {', '.join(VALID_FILTER_VALUES)}",
+            )
+        filters = cast(list[builder_model.FilterType], filter_values)
+    else:
+        filters = [
             "blocks",
             "integrations",
             "marketplace_agents",
@@ -174,7 +182,7 @@ async def search(
     cached_results = await builder_db.get_sorted_search_results(
         user_id=user_id,
         search_query=search_query,
-        filters=filter,
+        filters=filters,
         by_creator=by_creator,
     )
 
@@ -196,7 +204,7 @@ async def search(
         user_id,
         builder_model.SearchEntry(
             search_query=search_query,
-            filter=filter,
+            filter=filters,
             by_creator=by_creator,
             search_id=search_id,
         ),

autogpt_platform/backend/backend/api/features/chat/completion_consumer.py

@@ -1,368 +0,0 @@
-"""Redis Streams consumer for operation completion messages.
-
-This module provides a consumer (ChatCompletionConsumer) that listens for
-completion notifications (OperationCompleteMessage) from external services
-(like Agent Generator) and triggers the appropriate stream registry and
-chat service updates via process_operation_success/process_operation_failure.
-
-Why Redis Streams instead of RabbitMQ?
---------------------------------------
-While the project typically uses RabbitMQ for async task queues (e.g., execution
-queue), Redis Streams was chosen for chat completion notifications because:
-
-1. **Unified Infrastructure**: The SSE reconnection feature already uses Redis
-   Streams (via stream_registry) for message persistence and replay. Using Redis
-   Streams for completion notifications keeps all chat streaming infrastructure
-   in one system, simplifying operations and reducing cross-system coordination.
-
-2. **Message Replay**: Redis Streams support XREAD with arbitrary message IDs,
-   allowing consumers to replay missed messages after reconnection. This aligns
-   with the SSE reconnection pattern where clients can resume from last_message_id.
-
-3. **Consumer Groups with XAUTOCLAIM**: Redis consumer groups provide automatic
-   load balancing across pods with explicit message claiming (XAUTOCLAIM) for
-   recovering from dead consumers - ideal for the completion callback pattern.
-
-4. **Lower Latency**: For real-time SSE updates, Redis (already in-memory for
-   stream_registry) provides lower latency than an additional RabbitMQ hop.
-
-5. **Atomicity with Task State**: Completion processing often needs to update
-   task metadata stored in Redis. Keeping both in Redis enables simpler
-   transactional semantics without distributed coordination.
-
-The consumer uses Redis Streams with consumer groups for reliable message
-processing across multiple platform pods, with XAUTOCLAIM for reclaiming
-stale pending messages from dead consumers.
-"""
-
-import asyncio
-import logging
-import os
-import uuid
-from typing import Any
-
-import orjson
-from prisma import Prisma
-from pydantic import BaseModel
-from redis.exceptions import ResponseError
-
-from backend.data.redis_client import get_redis_async
-
-from . import stream_registry
-from .completion_handler import process_operation_failure, process_operation_success
-from .config import ChatConfig
-
-logger = logging.getLogger(__name__)
-config = ChatConfig()
-
-
-class OperationCompleteMessage(BaseModel):
-    """Message format for operation completion notifications."""
-
-    operation_id: str
-    task_id: str
-    success: bool
-    result: dict | str | None = None
-    error: str | None = None
-
-
-class ChatCompletionConsumer:
-    """Consumer for chat operation completion messages from Redis Streams.
-
-    This consumer initializes its own Prisma client in start() to ensure
-    database operations work correctly within this async context.
-
-    Uses Redis consumer groups to allow multiple platform pods to consume
-    messages reliably with automatic redelivery on failure.
-    """
-
-    def __init__(self):
-        self._consumer_task: asyncio.Task | None = None
-        self._running = False
-        self._prisma: Prisma | None = None
-        self._consumer_name = f"consumer-{uuid.uuid4().hex[:8]}"
-
-    async def start(self) -> None:
-        """Start the completion consumer."""
-        if self._running:
-            logger.warning("Completion consumer already running")
-            return
-
-        # Create consumer group if it doesn't exist
-        try:
-            redis = await get_redis_async()
-            await redis.xgroup_create(
-                config.stream_completion_name,
-                config.stream_consumer_group,
-                id="0",
-                mkstream=True,
-            )
-            logger.info(
-                f"Created consumer group '{config.stream_consumer_group}' "
-                f"on stream '{config.stream_completion_name}'"
-            )
-        except ResponseError as e:
-            if "BUSYGROUP" in str(e):
-                logger.debug(
-                    f"Consumer group '{config.stream_consumer_group}' already exists"
-                )
-            else:
-                raise
-
-        self._running = True
-        self._consumer_task = asyncio.create_task(self._consume_messages())
-        logger.info(
-            f"Chat completion consumer started (consumer: {self._consumer_name})"
-        )
-
-    async def _ensure_prisma(self) -> Prisma:
-        """Lazily initialize Prisma client on first use."""
-        if self._prisma is None:
-            database_url = os.getenv("DATABASE_URL", "postgresql://localhost:5432")
-            self._prisma = Prisma(datasource={"url": database_url})
-            await self._prisma.connect()
-            logger.info("[COMPLETION] Consumer Prisma client connected (lazy init)")
-        return self._prisma
-
-    async def stop(self) -> None:
-        """Stop the completion consumer."""
-        self._running = False
-
-        if self._consumer_task:
-            self._consumer_task.cancel()
-            try:
-                await self._consumer_task
-            except asyncio.CancelledError:
-                pass
-            self._consumer_task = None
-
-        if self._prisma:
-            await self._prisma.disconnect()
-            self._prisma = None
-            logger.info("[COMPLETION] Consumer Prisma client disconnected")
-
-        logger.info("Chat completion consumer stopped")
-
-    async def _consume_messages(self) -> None:
-        """Main message consumption loop with retry logic."""
-        max_retries = 10
-        retry_delay = 5  # seconds
-        retry_count = 0
-        block_timeout = 5000  # milliseconds
-
-        while self._running and retry_count < max_retries:
-            try:
-                redis = await get_redis_async()
-
-                # Reset retry count on successful connection
-                retry_count = 0
-
-                while self._running:
-                    # First, claim any stale pending messages from dead consumers
-                    # Redis does NOT auto-redeliver pending messages; we must explicitly
-                    # claim them using XAUTOCLAIM
-                    try:
-                        claimed_result = await redis.xautoclaim(
-                            name=config.stream_completion_name,
-                            groupname=config.stream_consumer_group,
-                            consumername=self._consumer_name,
-                            min_idle_time=config.stream_claim_min_idle_ms,
-                            start_id="0-0",
-                            count=10,
-                        )
-                        # xautoclaim returns: (next_start_id, [(id, data), ...], [deleted_ids])
-                        if claimed_result and len(claimed_result) >= 2:
-                            claimed_entries = claimed_result[1]
-                            if claimed_entries:
-                                logger.info(
-                                    f"Claimed {len(claimed_entries)} stale pending messages"
-                                )
-                                for entry_id, data in claimed_entries:
-                                    if not self._running:
-                                        return
-                                    await self._process_entry(redis, entry_id, data)
-                    except Exception as e:
-                        logger.warning(f"XAUTOCLAIM failed (non-fatal): {e}")
-
-                    # Read new messages from the stream
-                    messages = await redis.xreadgroup(
-                        groupname=config.stream_consumer_group,
-                        consumername=self._consumer_name,
-                        streams={config.stream_completion_name: ">"},
-                        block=block_timeout,
-                        count=10,
-                    )
-
-                    if not messages:
-                        continue
-
-                    for stream_name, entries in messages:
-                        for entry_id, data in entries:
-                            if not self._running:
-                                return
-                            await self._process_entry(redis, entry_id, data)
-
-            except asyncio.CancelledError:
-                logger.info("Consumer cancelled")
-                return
-            except Exception as e:
-                retry_count += 1
-                logger.error(
-                    f"Consumer error (retry {retry_count}/{max_retries}): {e}",
-                    exc_info=True,
-                )
-                if self._running and retry_count < max_retries:
-                    await asyncio.sleep(retry_delay)
-                else:
-                    logger.error("Max retries reached, stopping consumer")
-                    return
-
-    async def _process_entry(
-        self, redis: Any, entry_id: str, data: dict[str, Any]
-    ) -> None:
-        """Process a single stream entry and acknowledge it on success.
-
-        Args:
-            redis: Redis client connection
-            entry_id: The stream entry ID
-            data: The entry data dict
-        """
-        try:
-            # Handle the message
-            message_data = data.get("data")
-            if message_data:
-                await self._handle_message(
-                    message_data.encode()
-                    if isinstance(message_data, str)
-                    else message_data
-                )
-
-            # Acknowledge the message after successful processing
-            await redis.xack(
-                config.stream_completion_name,
-                config.stream_consumer_group,
-                entry_id,
-            )
-        except Exception as e:
-            logger.error(
-                f"Error processing completion message {entry_id}: {e}",
-                exc_info=True,
-            )
-            # Message remains in pending state and will be claimed by
-            # XAUTOCLAIM after min_idle_time expires
-
-    async def _handle_message(self, body: bytes) -> None:
-        """Handle a completion message using our own Prisma client."""
-        try:
-            data = orjson.loads(body)
-            message = OperationCompleteMessage(**data)
-        except Exception as e:
-            logger.error(f"Failed to parse completion message: {e}")
-            return
-
-        logger.info(
-            f"[COMPLETION] Received completion for operation {message.operation_id} "
-            f"(task_id={message.task_id}, success={message.success})"
-        )
-
-        # Find task in registry
-        task = await stream_registry.find_task_by_operation_id(message.operation_id)
-        if task is None:
-            task = await stream_registry.get_task(message.task_id)
-
-        if task is None:
-            logger.warning(
-                f"[COMPLETION] Task not found for operation {message.operation_id} "
-                f"(task_id={message.task_id})"
-            )
-            return
-
-        logger.info(
-            f"[COMPLETION] Found task: task_id={task.task_id}, "
-            f"session_id={task.session_id}, tool_call_id={task.tool_call_id}"
-        )
-
-        # Guard against empty task fields
-        if not task.task_id or not task.session_id or not task.tool_call_id:
-            logger.error(
-                f"[COMPLETION] Task has empty critical fields! "
-                f"task_id={task.task_id!r}, session_id={task.session_id!r}, "
-                f"tool_call_id={task.tool_call_id!r}"
-            )
-            return
-
-        if message.success:
-            await self._handle_success(task, message)
-        else:
-            await self._handle_failure(task, message)
-
-    async def _handle_success(
-        self,
-        task: stream_registry.ActiveTask,
-        message: OperationCompleteMessage,
-    ) -> None:
-        """Handle successful operation completion."""
-        prisma = await self._ensure_prisma()
-        await process_operation_success(task, message.result, prisma)
-
-    async def _handle_failure(
-        self,
-        task: stream_registry.ActiveTask,
-        message: OperationCompleteMessage,
-    ) -> None:
-        """Handle failed operation completion."""
-        prisma = await self._ensure_prisma()
-        await process_operation_failure(task, message.error, prisma)
-
-
-# Module-level consumer instance
-_consumer: ChatCompletionConsumer | None = None
-
-
-async def start_completion_consumer() -> None:
-    """Start the global completion consumer."""
-    global _consumer
-    if _consumer is None:
-        _consumer = ChatCompletionConsumer()
-    await _consumer.start()
-
-
-async def stop_completion_consumer() -> None:
-    """Stop the global completion consumer."""
-    global _consumer
-    if _consumer:
-        await _consumer.stop()
-        _consumer = None
-
-
-async def publish_operation_complete(
-    operation_id: str,
-    task_id: str,
-    success: bool,
-    result: dict | str | None = None,
-    error: str | None = None,
-) -> None:
-    """Publish an operation completion message to Redis Streams.
-
-    Args:
-        operation_id: The operation ID that completed.
-        task_id: The task ID associated with the operation.
-        success: Whether the operation succeeded.
-        result: The result data (for success).
-        error: The error message (for failure).
-    """
-    message = OperationCompleteMessage(
-        operation_id=operation_id,
-        task_id=task_id,
-        success=success,
-        result=result,
-        error=error,
-    )
-
-    redis = await get_redis_async()
-    await redis.xadd(
-        config.stream_completion_name,
-        {"data": message.model_dump_json()},
-        maxlen=config.stream_max_length,
-    )
-    logger.info(f"Published completion for operation {operation_id}")

autogpt_platform/backend/backend/api/features/chat/completion_handler.py

@@ -1,344 +0,0 @@
-"""Shared completion handling for operation success and failure.
-
-This module provides common logic for handling operation completion from both:
-- The Redis Streams consumer (completion_consumer.py)
-- The HTTP webhook endpoint (routes.py)
-"""
-
-import logging
-from typing import Any
-
-import orjson
-from prisma import Prisma
-
-from . import service as chat_service
-from . import stream_registry
-from .response_model import StreamError, StreamToolOutputAvailable
-from .tools.models import ErrorResponse
-
-logger = logging.getLogger(__name__)
-
-# Tools that produce agent_json that needs to be saved to library
-AGENT_GENERATION_TOOLS = {"create_agent", "edit_agent"}
-
-# Keys that should be stripped from agent_json when returning in error responses
-SENSITIVE_KEYS = frozenset(
-    {
-        "api_key",
-        "apikey",
-        "api_secret",
-        "password",
-        "secret",
-        "credentials",
-        "credential",
-        "token",
-        "access_token",
-        "refresh_token",
-        "private_key",
-        "privatekey",
-        "auth",
-        "authorization",
-    }
-)
-
-
-def _sanitize_agent_json(obj: Any) -> Any:
-    """Recursively sanitize agent_json by removing sensitive keys.
-
-    Args:
-        obj: The object to sanitize (dict, list, or primitive)
-
-    Returns:
-        Sanitized copy with sensitive keys removed/redacted
-    """
-    if isinstance(obj, dict):
-        return {
-            k: "[REDACTED]" if k.lower() in SENSITIVE_KEYS else _sanitize_agent_json(v)
-            for k, v in obj.items()
-        }
-    elif isinstance(obj, list):
-        return [_sanitize_agent_json(item) for item in obj]
-    else:
-        return obj
-
-
-class ToolMessageUpdateError(Exception):
-    """Raised when updating a tool message in the database fails."""
-
-    pass
-
-
-async def _update_tool_message(
-    session_id: str,
-    tool_call_id: str,
-    content: str,
-    prisma_client: Prisma | None,
-) -> None:
-    """Update tool message in database.
-
-    Args:
-        session_id: The session ID
-        tool_call_id: The tool call ID to update
-        content: The new content for the message
-        prisma_client: Optional Prisma client. If None, uses chat_service.
-
-    Raises:
-        ToolMessageUpdateError: If the database update fails. The caller should
-            handle this to avoid marking the task as completed with inconsistent state.
-    """
-    try:
-        if prisma_client:
-            # Use provided Prisma client (for consumer with its own connection)
-            updated_count = await prisma_client.chatmessage.update_many(
-                where={
-                    "sessionId": session_id,
-                    "toolCallId": tool_call_id,
-                },
-                data={"content": content},
-            )
-            # Check if any rows were updated - 0 means message not found
-            if updated_count == 0:
-                raise ToolMessageUpdateError(
-                    f"No message found with tool_call_id={tool_call_id} in session {session_id}"
-                )
-        else:
-            # Use service function (for webhook endpoint)
-            await chat_service._update_pending_operation(
-                session_id=session_id,
-                tool_call_id=tool_call_id,
-                result=content,
-            )
-    except ToolMessageUpdateError:
-        raise
-    except Exception as e:
-        logger.error(f"[COMPLETION] Failed to update tool message: {e}", exc_info=True)
-        raise ToolMessageUpdateError(
-            f"Failed to update tool message for tool_call_id={tool_call_id}: {e}"
-        ) from e
-
-
-def serialize_result(result: dict | list | str | int | float | bool | None) -> str:
-    """Serialize result to JSON string with sensible defaults.
-
-    Args:
-        result: The result to serialize. Can be a dict, list, string,
-            number, boolean, or None.
-
-    Returns:
-        JSON string representation of the result. Returns '{"status": "completed"}'
-        only when result is explicitly None.
-    """
-    if isinstance(result, str):
-        return result
-    if result is None:
-        return '{"status": "completed"}'
-    return orjson.dumps(result).decode("utf-8")
-
-
-async def _save_agent_from_result(
-    result: dict[str, Any],
-    user_id: str | None,
-    tool_name: str,
-) -> dict[str, Any]:
-    """Save agent to library if result contains agent_json.
-
-    Args:
-        result: The result dict that may contain agent_json
-        user_id: The user ID to save the agent for
-        tool_name: The tool name (create_agent or edit_agent)
-
-    Returns:
-        Updated result dict with saved agent details, or original result if no agent_json
-    """
-    if not user_id:
-        logger.warning("[COMPLETION] Cannot save agent: no user_id in task")
-        return result
-
-    agent_json = result.get("agent_json")
-    if not agent_json:
-        logger.warning(
-            f"[COMPLETION] {tool_name} completed but no agent_json in result"
-        )
-        return result
-
-    try:
-        from .tools.agent_generator import save_agent_to_library
-
-        is_update = tool_name == "edit_agent"
-        created_graph, library_agent = await save_agent_to_library(
-            agent_json, user_id, is_update=is_update
-        )
-
-        logger.info(
-            f"[COMPLETION] Saved agent '{created_graph.name}' to library "
-            f"(graph_id={created_graph.id}, library_agent_id={library_agent.id})"
-        )
-
-        # Return a response similar to AgentSavedResponse
-        return {
-            "type": "agent_saved",
-            "message": f"Agent '{created_graph.name}' has been saved to your library!",
-            "agent_id": created_graph.id,
-            "agent_name": created_graph.name,
-            "library_agent_id": library_agent.id,
-            "library_agent_link": f"/library/agents/{library_agent.id}",
-            "agent_page_link": f"/build?flowID={created_graph.id}",
-        }
-    except Exception as e:
-        logger.error(
-            f"[COMPLETION] Failed to save agent to library: {e}",
-            exc_info=True,
-        )
-        # Return error but don't fail the whole operation
-        # Sanitize agent_json to remove sensitive keys before returning
-        return {
-            "type": "error",
-            "message": f"Agent was generated but failed to save: {str(e)}",
-            "error": str(e),
-            "agent_json": _sanitize_agent_json(agent_json),
-        }
-
-
-async def process_operation_success(
-    task: stream_registry.ActiveTask,
-    result: dict | str | None,
-    prisma_client: Prisma | None = None,
-) -> None:
-    """Handle successful operation completion.
-
-    Publishes the result to the stream registry, updates the database,
-    generates LLM continuation, and marks the task as completed.
-
-    Args:
-        task: The active task that completed
-        result: The result data from the operation
-        prisma_client: Optional Prisma client for database operations.
-            If None, uses chat_service._update_pending_operation instead.
-
-    Raises:
-        ToolMessageUpdateError: If the database update fails. The task will be
-            marked as failed instead of completed to avoid inconsistent state.
-    """
-    # For agent generation tools, save the agent to library
-    if task.tool_name in AGENT_GENERATION_TOOLS and isinstance(result, dict):
-        result = await _save_agent_from_result(result, task.user_id, task.tool_name)
-
-    # Serialize result for output (only substitute default when result is exactly None)
-    result_output = result if result is not None else {"status": "completed"}
-    output_str = (
-        result_output
-        if isinstance(result_output, str)
-        else orjson.dumps(result_output).decode("utf-8")
-    )
-
-    # Publish result to stream registry
-    await stream_registry.publish_chunk(
-        task.task_id,
-        StreamToolOutputAvailable(
-            toolCallId=task.tool_call_id,
-            toolName=task.tool_name,
-            output=output_str,
-            success=True,
-        ),
-    )
-
-    # Update pending operation in database
-    # If this fails, we must not continue to mark the task as completed
-    result_str = serialize_result(result)
-    try:
-        await _update_tool_message(
-            session_id=task.session_id,
-            tool_call_id=task.tool_call_id,
-            content=result_str,
-            prisma_client=prisma_client,
-        )
-    except ToolMessageUpdateError:
-        # DB update failed - mark task as failed to avoid inconsistent state
-        logger.error(
-            f"[COMPLETION] DB update failed for task {task.task_id}, "
-            "marking as failed instead of completed"
-        )
-        await stream_registry.publish_chunk(
-            task.task_id,
-            StreamError(errorText="Failed to save operation result to database"),
-        )
-        await stream_registry.mark_task_completed(task.task_id, status="failed")
-        raise
-
-    # Generate LLM continuation with streaming
-    try:
-        await chat_service._generate_llm_continuation_with_streaming(
-            session_id=task.session_id,
-            user_id=task.user_id,
-            task_id=task.task_id,
-        )
-    except Exception as e:
-        logger.error(
-            f"[COMPLETION] Failed to generate LLM continuation: {e}",
-            exc_info=True,
-        )
-
-    # Mark task as completed and release Redis lock
-    await stream_registry.mark_task_completed(task.task_id, status="completed")
-    try:
-        await chat_service._mark_operation_completed(task.tool_call_id)
-    except Exception as e:
-        logger.error(f"[COMPLETION] Failed to mark operation completed: {e}")
-
-    logger.info(
-        f"[COMPLETION] Successfully processed completion for task {task.task_id}"
-    )
-
-
-async def process_operation_failure(
-    task: stream_registry.ActiveTask,
-    error: str | None,
-    prisma_client: Prisma | None = None,
-) -> None:
-    """Handle failed operation completion.
-
-    Publishes the error to the stream registry, updates the database with
-    the error response, and marks the task as failed.
-
-    Args:
-        task: The active task that failed
-        error: The error message from the operation
-        prisma_client: Optional Prisma client for database operations.
-            If None, uses chat_service._update_pending_operation instead.
-    """
-    error_msg = error or "Operation failed"
-
-    # Publish error to stream registry
-    await stream_registry.publish_chunk(
-        task.task_id,
-        StreamError(errorText=error_msg),
-    )
-
-    # Update pending operation with error
-    # If this fails, we still continue to mark the task as failed
-    error_response = ErrorResponse(
-        message=error_msg,
-        error=error,
-    )
-    try:
-        await _update_tool_message(
-            session_id=task.session_id,
-            tool_call_id=task.tool_call_id,
-            content=error_response.model_dump_json(),
-            prisma_client=prisma_client,
-        )
-    except ToolMessageUpdateError:
-        # DB update failed - log but continue with cleanup
-        logger.error(
-            f"[COMPLETION] DB update failed while processing failure for task {task.task_id}, "
-            "continuing with cleanup"
-        )
-
-    # Mark task as failed and release Redis lock
-    await stream_registry.mark_task_completed(task.task_id, status="failed")
-    try:
-        await chat_service._mark_operation_completed(task.tool_call_id)
-    except Exception as e:
-        logger.error(f"[COMPLETION] Failed to mark operation completed: {e}")
-
-    logger.info(f"[COMPLETION] Processed failure for task {task.task_id}: {error_msg}")

autogpt_platform/backend/backend/api/features/chat/config.py

@@ -1,152 +0,0 @@
-"""Configuration management for chat system."""
-
-import os
-
-from pydantic import Field, field_validator
-from pydantic_settings import BaseSettings
-
-
-class ChatConfig(BaseSettings):
-    """Configuration for the chat system."""
-
-    # OpenAI API Configuration
-    model: str = Field(
-        default="anthropic/claude-opus-4.6", description="Default model to use"
-    )
-    title_model: str = Field(
-        default="openai/gpt-4o-mini",
-        description="Model to use for generating session titles (should be fast/cheap)",
-    )
-    api_key: str | None = Field(default=None, description="OpenAI API key")
-    base_url: str | None = Field(
-        default="https://openrouter.ai/api/v1",
-        description="Base URL for API (e.g., for OpenRouter)",
-    )
-
-    # Session TTL Configuration - 12 hours
-    session_ttl: int = Field(default=43200, description="Session TTL in seconds")
-
-    # Streaming Configuration
-    max_context_messages: int = Field(
-        default=50, ge=1, le=200, description="Maximum context messages"
-    )
-
-    stream_timeout: int = Field(default=300, description="Stream timeout in seconds")
-    max_retries: int = Field(default=3, description="Maximum number of retries")
-    max_agent_runs: int = Field(default=30, description="Maximum number of agent runs")
-    max_agent_schedules: int = Field(
-        default=30, description="Maximum number of agent schedules"
-    )
-
-    # Long-running operation configuration
-    long_running_operation_ttl: int = Field(
-        default=600,
-        description="TTL in seconds for long-running operation tracking in Redis (safety net if pod dies)",
-    )
-
-    # Stream registry configuration for SSE reconnection
-    stream_ttl: int = Field(
-        default=3600,
-        description="TTL in seconds for stream data in Redis (1 hour)",
-    )
-    stream_max_length: int = Field(
-        default=10000,
-        description="Maximum number of messages to store per stream",
-    )
-
-    # Redis Streams configuration for completion consumer
-    stream_completion_name: str = Field(
-        default="chat:completions",
-        description="Redis Stream name for operation completions",
-    )
-    stream_consumer_group: str = Field(
-        default="chat_consumers",
-        description="Consumer group name for completion stream",
-    )
-    stream_claim_min_idle_ms: int = Field(
-        default=60000,
-        description="Minimum idle time in milliseconds before claiming pending messages from dead consumers",
-    )
-
-    # Redis key prefixes for stream registry
-    task_meta_prefix: str = Field(
-        default="chat:task:meta:",
-        description="Prefix for task metadata hash keys",
-    )
-    task_stream_prefix: str = Field(
-        default="chat:stream:",
-        description="Prefix for task message stream keys",
-    )
-    task_op_prefix: str = Field(
-        default="chat:task:op:",
-        description="Prefix for operation ID to task ID mapping keys",
-    )
-    internal_api_key: str | None = Field(
-        default=None,
-        description="API key for internal webhook callbacks (env: CHAT_INTERNAL_API_KEY)",
-    )
-
-    # Langfuse Prompt Management Configuration
-    # Note: Langfuse credentials are in Settings().secrets (settings.py)
-    langfuse_prompt_name: str = Field(
-        default="CoPilot Prompt",
-        description="Name of the prompt in Langfuse to fetch",
-    )
-
-    # Extended thinking configuration for Claude models
-    thinking_enabled: bool = Field(
-        default=True,
-        description="Enable adaptive thinking for Claude models via OpenRouter",
-    )
-
-    @field_validator("api_key", mode="before")
-    @classmethod
-    def get_api_key(cls, v):
-        """Get API key from environment if not provided."""
-        if v is None:
-            # Try to get from environment variables
-            # First check for CHAT_API_KEY (Pydantic prefix)
-            v = os.getenv("CHAT_API_KEY")
-            if not v:
-                # Fall back to OPEN_ROUTER_API_KEY
-                v = os.getenv("OPEN_ROUTER_API_KEY")
-            if not v:
-                # Fall back to OPENAI_API_KEY
-                v = os.getenv("OPENAI_API_KEY")
-        return v
-
-    @field_validator("base_url", mode="before")
-    @classmethod
-    def get_base_url(cls, v):
-        """Get base URL from environment if not provided."""
-        if v is None:
-            # Check for OpenRouter or custom base URL
-            v = os.getenv("CHAT_BASE_URL")
-            if not v:
-                v = os.getenv("OPENROUTER_BASE_URL")
-            if not v:
-                v = os.getenv("OPENAI_BASE_URL")
-            if not v:
-                v = "https://openrouter.ai/api/v1"
-        return v
-
-    @field_validator("internal_api_key", mode="before")
-    @classmethod
-    def get_internal_api_key(cls, v):
-        """Get internal API key from environment if not provided."""
-        if v is None:
-            v = os.getenv("CHAT_INTERNAL_API_KEY")
-        return v
-
-    # Prompt paths for different contexts
-    PROMPT_PATHS: dict[str, str] = {
-        "default": "prompts/chat_system.md",
-        "onboarding": "prompts/onboarding_system.md",
-    }
-
-    class Config:
-        """Pydantic config."""
-
-        env_file = ".env"
-        env_file_encoding = "utf-8"
-        extra = "ignore"  # Ignore extra environment variables

autogpt_platform/backend/backend/api/features/chat/db.py

@@ -1,288 +0,0 @@
-"""Database operations for chat sessions."""
-
-import asyncio
-import logging
-from datetime import UTC, datetime
-from typing import Any, cast
-
-from prisma.models import ChatMessage as PrismaChatMessage
-from prisma.models import ChatSession as PrismaChatSession
-from prisma.types import (
-    ChatMessageCreateInput,
-    ChatSessionCreateInput,
-    ChatSessionUpdateInput,
-    ChatSessionWhereInput,
-)
-
-from backend.data.db import transaction
-from backend.util.json import SafeJson
-
-logger = logging.getLogger(__name__)
-
-
-async def get_chat_session(session_id: str) -> PrismaChatSession | None:
-    """Get a chat session by ID from the database."""
-    session = await PrismaChatSession.prisma().find_unique(
-        where={"id": session_id},
-        include={"Messages": True},
-    )
-    if session and session.Messages:
-        # Sort messages by sequence in Python - Prisma Python client doesn't support
-        # order_by in include clauses (unlike Prisma JS), so we sort after fetching
-        session.Messages.sort(key=lambda m: m.sequence)
-    return session
-
-
-async def create_chat_session(
-    session_id: str,
-    user_id: str,
-) -> PrismaChatSession:
-    """Create a new chat session in the database."""
-    data = ChatSessionCreateInput(
-        id=session_id,
-        userId=user_id,
-        credentials=SafeJson({}),
-        successfulAgentRuns=SafeJson({}),
-        successfulAgentSchedules=SafeJson({}),
-    )
-    return await PrismaChatSession.prisma().create(data=data)
-
-
-async def update_chat_session(
-    session_id: str,
-    credentials: dict[str, Any] | None = None,
-    successful_agent_runs: dict[str, Any] | None = None,
-    successful_agent_schedules: dict[str, Any] | None = None,
-    total_prompt_tokens: int | None = None,
-    total_completion_tokens: int | None = None,
-    title: str | None = None,
-) -> PrismaChatSession | None:
-    """Update a chat session's metadata."""
-    data: ChatSessionUpdateInput = {"updatedAt": datetime.now(UTC)}
-
-    if credentials is not None:
-        data["credentials"] = SafeJson(credentials)
-    if successful_agent_runs is not None:
-        data["successfulAgentRuns"] = SafeJson(successful_agent_runs)
-    if successful_agent_schedules is not None:
-        data["successfulAgentSchedules"] = SafeJson(successful_agent_schedules)
-    if total_prompt_tokens is not None:
-        data["totalPromptTokens"] = total_prompt_tokens
-    if total_completion_tokens is not None:
-        data["totalCompletionTokens"] = total_completion_tokens
-    if title is not None:
-        data["title"] = title
-
-    session = await PrismaChatSession.prisma().update(
-        where={"id": session_id},
-        data=data,
-        include={"Messages": True},
-    )
-    if session and session.Messages:
-        # Sort in Python - Prisma Python doesn't support order_by in include clauses
-        session.Messages.sort(key=lambda m: m.sequence)
-    return session
-
-
-async def add_chat_message(
-    session_id: str,
-    role: str,
-    sequence: int,
-    content: str | None = None,
-    name: str | None = None,
-    tool_call_id: str | None = None,
-    refusal: str | None = None,
-    tool_calls: list[dict[str, Any]] | None = None,
-    function_call: dict[str, Any] | None = None,
-) -> PrismaChatMessage:
-    """Add a message to a chat session."""
-    # Build input dict dynamically rather than using ChatMessageCreateInput directly
-    # because Prisma's TypedDict validation rejects optional fields set to None.
-    # We only include fields that have values, then cast at the end.
-    data: dict[str, Any] = {
-        "Session": {"connect": {"id": session_id}},
-        "role": role,
-        "sequence": sequence,
-    }
-
-    # Add optional string fields
-    if content is not None:
-        data["content"] = content
-    if name is not None:
-        data["name"] = name
-    if tool_call_id is not None:
-        data["toolCallId"] = tool_call_id
-    if refusal is not None:
-        data["refusal"] = refusal
-
-    # Add optional JSON fields only when they have values
-    if tool_calls is not None:
-        data["toolCalls"] = SafeJson(tool_calls)
-    if function_call is not None:
-        data["functionCall"] = SafeJson(function_call)
-
-    # Run message create and session timestamp update in parallel for lower latency
-    _, message = await asyncio.gather(
-        PrismaChatSession.prisma().update(
-            where={"id": session_id},
-            data={"updatedAt": datetime.now(UTC)},
-        ),
-        PrismaChatMessage.prisma().create(data=cast(ChatMessageCreateInput, data)),
-    )
-    return message
-
-
-async def add_chat_messages_batch(
-    session_id: str,
-    messages: list[dict[str, Any]],
-    start_sequence: int,
-) -> list[PrismaChatMessage]:
-    """Add multiple messages to a chat session in a batch.
-
-    Uses a transaction for atomicity - if any message creation fails,
-    the entire batch is rolled back.
-    """
-    if not messages:
-        return []
-
-    created_messages = []
-
-    async with transaction() as tx:
-        for i, msg in enumerate(messages):
-            # Build input dict dynamically rather than using ChatMessageCreateInput
-            # directly because Prisma's TypedDict validation rejects optional fields
-            # set to None. We only include fields that have values, then cast.
-            data: dict[str, Any] = {
-                "Session": {"connect": {"id": session_id}},
-                "role": msg["role"],
-                "sequence": start_sequence + i,
-            }
-
-            # Add optional string fields
-            if msg.get("content") is not None:
-                data["content"] = msg["content"]
-            if msg.get("name") is not None:
-                data["name"] = msg["name"]
-            if msg.get("tool_call_id") is not None:
-                data["toolCallId"] = msg["tool_call_id"]
-            if msg.get("refusal") is not None:
-                data["refusal"] = msg["refusal"]
-
-            # Add optional JSON fields only when they have values
-            if msg.get("tool_calls") is not None:
-                data["toolCalls"] = SafeJson(msg["tool_calls"])
-            if msg.get("function_call") is not None:
-                data["functionCall"] = SafeJson(msg["function_call"])
-
-            created = await PrismaChatMessage.prisma(tx).create(
-                data=cast(ChatMessageCreateInput, data)
-            )
-            created_messages.append(created)
-
-        # Update session's updatedAt timestamp within the same transaction.
-        # Note: Token usage (total_prompt_tokens, total_completion_tokens) is updated
-        # separately via update_chat_session() after streaming completes.
-        await PrismaChatSession.prisma(tx).update(
-            where={"id": session_id},
-            data={"updatedAt": datetime.now(UTC)},
-        )
-
-    return created_messages
-
-
-async def get_user_chat_sessions(
-    user_id: str,
-    limit: int = 50,
-    offset: int = 0,
-) -> list[PrismaChatSession]:
-    """Get chat sessions for a user, ordered by most recent."""
-    return await PrismaChatSession.prisma().find_many(
-        where={"userId": user_id},
-        order={"updatedAt": "desc"},
-        take=limit,
-        skip=offset,
-    )
-
-
-async def get_user_session_count(user_id: str) -> int:
-    """Get the total number of chat sessions for a user."""
-    return await PrismaChatSession.prisma().count(where={"userId": user_id})
-
-
-async def delete_chat_session(session_id: str, user_id: str | None = None) -> bool:
-    """Delete a chat session and all its messages.
-
-    Args:
-        session_id: The session ID to delete.
-        user_id: If provided, validates that the session belongs to this user
-            before deletion. This prevents unauthorized deletion of other
-            users' sessions.
-
-    Returns:
-        True if deleted successfully, False otherwise.
-    """
-    try:
-        # Build typed where clause with optional user_id validation
-        where_clause: ChatSessionWhereInput = {"id": session_id}
-        if user_id is not None:
-            where_clause["userId"] = user_id
-
-        result = await PrismaChatSession.prisma().delete_many(where=where_clause)
-        if result == 0:
-            logger.warning(
-                f"No session deleted for {session_id} "
-                f"(user_id validation: {user_id is not None})"
-            )
-            return False
-        return True
-    except Exception as e:
-        logger.error(f"Failed to delete chat session {session_id}: {e}")
-        return False
-
-
-async def get_chat_session_message_count(session_id: str) -> int:
-    """Get the number of messages in a chat session."""
-    count = await PrismaChatMessage.prisma().count(where={"sessionId": session_id})
-    return count
-
-
-async def update_tool_message_content(
-    session_id: str,
-    tool_call_id: str,
-    new_content: str,
-) -> bool:
-    """Update the content of a tool message in chat history.
-
-    Used by background tasks to update pending operation messages with final results.
-
-    Args:
-        session_id: The chat session ID.
-        tool_call_id: The tool call ID to find the message.
-        new_content: The new content to set.
-
-    Returns:
-        True if a message was updated, False otherwise.
-    """
-    try:
-        result = await PrismaChatMessage.prisma().update_many(
-            where={
-                "sessionId": session_id,
-                "toolCallId": tool_call_id,
-            },
-            data={
-                "content": new_content,
-            },
-        )
-        if result == 0:
-            logger.warning(
-                f"No message found to update for session {session_id}, "
-                f"tool_call_id {tool_call_id}"
-            )
-            return False
-        return True
-    except Exception as e:
-        logger.error(
-            f"Failed to update tool message for session {session_id}, "
-            f"tool_call_id {tool_call_id}: {e}"
-        )
-        return False

autogpt_platform/backend/backend/api/features/chat/routes.py

@@ -1,29 +1,40 @@
 """Chat API routes for chat session management and streaming via SSE."""
 
+import asyncio
 import logging
-import uuid as uuid_module
+import re
 from collections.abc import AsyncGenerator
 from typing import Annotated
+from uuid import uuid4
 
 from autogpt_libs import auth
-from fastapi import APIRouter, Depends, Header, HTTPException, Query, Response, Security
+from fastapi import APIRouter, Depends, HTTPException, Query, Response, Security
 from fastapi.responses import StreamingResponse
-from pydantic import BaseModel
+from prisma.models import UserWorkspaceFile
+from pydantic import BaseModel, Field, field_validator
 
-from backend.util.exceptions import NotFoundError
-
-from . import service as chat_service
-from . import stream_registry
-from .completion_handler import process_operation_failure, process_operation_success
-from .config import ChatConfig
-from .model import ChatSession, create_chat_session, get_chat_session, get_user_sessions
-from .response_model import StreamFinish, StreamHeartbeat
-from .tools.models import (
+from backend.copilot import service as chat_service
+from backend.copilot import stream_registry
+from backend.copilot.config import ChatConfig
+from backend.copilot.executor.utils import enqueue_cancel_task, enqueue_copilot_turn
+from backend.copilot.model import (
+    ChatMessage,
+    ChatSession,
+    append_and_save_message,
+    create_chat_session,
+    delete_chat_session,
+    get_chat_session,
+    get_user_sessions,
+    update_session_title,
+)
+from backend.copilot.response_model import StreamError, StreamFinish, StreamHeartbeat
+from backend.copilot.tools.models import (
     AgentDetailsResponse,
     AgentOutputResponse,
     AgentPreviewResponse,
     AgentSavedResponse,
     AgentsFoundResponse,
+    BlockDetailsResponse,
     BlockListResponse,
     BlockOutputResponse,
     ClarificationNeededResponse,
@@ -32,17 +43,23 @@ from .tools.models import (
     ErrorResponse,
     ExecutionStartedResponse,
     InputValidationErrorResponse,
+    MCPToolOutputResponse,
+    MCPToolsDiscoveredResponse,
     NeedLoginResponse,
     NoResultsResponse,
-    OperationInProgressResponse,
-    OperationPendingResponse,
-    OperationStartedResponse,
     SetupRequirementsResponse,
+    SuggestedGoalResponse,
     UnderstandingUpdatedResponse,
 )
+from backend.copilot.tracking import track_user_message
+from backend.data.workspace import get_or_create_workspace
+from backend.util.exceptions import NotFoundError
 
 config = ChatConfig()
 
+_UUID_RE = re.compile(
+    r"^[0-9a-f]{8}-[0-9a-f]{4}-[0-9a-f]{4}-[0-9a-f]{4}-[0-9a-f]{12}$", re.I
+)
 
 logger = logging.getLogger(__name__)
 
@@ -71,6 +88,9 @@ class StreamChatRequest(BaseModel):
     message: str
     is_user_message: bool = True
     context: dict[str, str] | None = None  # {url: str, content: str}
+    file_ids: list[str] | None = Field(
+        default=None, max_length=20
+    )  # Workspace file IDs attached to this message
 
 
 class CreateSessionResponse(BaseModel):
@@ -84,10 +104,8 @@ class CreateSessionResponse(BaseModel):
 class ActiveStreamInfo(BaseModel):
     """Information about an active stream for reconnection."""
 
-    task_id: str
+    turn_id: str
     last_message_id: str  # Redis Stream message ID for resumption
-    operation_id: str  # Operation ID for completion tracking
-    tool_name: str  # Name of the tool being executed
 
 
 class SessionDetailResponse(BaseModel):
@@ -117,12 +135,25 @@ class ListSessionsResponse(BaseModel):
     total: int
 
 
-class OperationCompleteRequest(BaseModel):
-    """Request model for external completion webhook."""
+class CancelSessionResponse(BaseModel):
+    """Response model for the cancel session endpoint."""
 
-    success: bool
-    result: dict | str | None = None
-    error: str | None = None
+    cancelled: bool
+    reason: str | None = None
+
+
+class UpdateSessionTitleRequest(BaseModel):
+    """Request model for updating a session's title."""
+
+    title: str
+
+    @field_validator("title")
+    @classmethod
+    def title_must_not_be_blank(cls, v: str) -> str:
+        stripped = v.strip()
+        if not stripped:
+            raise ValueError("Title must not be blank")
+        return stripped
 
 
 # ========== Routes ==========
@@ -199,6 +230,92 @@ async def create_session(
     )
 
 
+@router.delete(
+    "/sessions/{session_id}",
+    dependencies=[Security(auth.requires_user)],
+    status_code=204,
+    responses={404: {"description": "Session not found or access denied"}},
+)
+async def delete_session(
+    session_id: str,
+    user_id: Annotated[str, Security(auth.get_user_id)],
+) -> Response:
+    """
+    Delete a chat session.
+
+    Permanently removes a chat session and all its messages.
+    Only the owner can delete their sessions.
+
+    Args:
+        session_id: The session ID to delete.
+        user_id: The authenticated user's ID.
+
+    Returns:
+        204 No Content on success.
+
+    Raises:
+        HTTPException: 404 if session not found or not owned by user.
+    """
+    deleted = await delete_chat_session(session_id, user_id)
+
+    if not deleted:
+        raise HTTPException(
+            status_code=404,
+            detail=f"Session {session_id} not found or access denied",
+        )
+
+    # Best-effort cleanup of the E2B sandbox (if any).
+    config = ChatConfig()
+    if config.use_e2b_sandbox and config.e2b_api_key:
+        from backend.copilot.tools.e2b_sandbox import kill_sandbox
+
+        try:
+            await kill_sandbox(session_id, config.e2b_api_key)
+        except Exception:
+            logger.warning(
+                "[E2B] Failed to kill sandbox for session %s", session_id[:12]
+            )
+
+    return Response(status_code=204)
+
+
+@router.patch(
+    "/sessions/{session_id}/title",
+    summary="Update session title",
+    dependencies=[Security(auth.requires_user)],
+    status_code=200,
+    responses={404: {"description": "Session not found or access denied"}},
+)
+async def update_session_title_route(
+    session_id: str,
+    request: UpdateSessionTitleRequest,
+    user_id: Annotated[str, Security(auth.get_user_id)],
+) -> dict:
+    """
+    Update the title of a chat session.
+
+    Allows the user to rename their chat session.
+
+    Args:
+        session_id: The session ID to update.
+        request: Request body containing the new title.
+        user_id: The authenticated user's ID.
+
+    Returns:
+        dict: Status of the update.
+
+    Raises:
+        HTTPException: 404 if session not found or not owned by user.
+    """
+    success = await update_session_title(session_id, user_id, request.title)
+    if not success:
+        raise HTTPException(
+            status_code=404,
+            detail=f"Session {session_id} not found or access denied",
+        )
+    return {"status": "ok"}
+
+
 @router.get(
     "/sessions/{session_id}",
 )
@@ -210,7 +327,7 @@ async def get_session(
     Retrieve the details of a specific chat session.
 
     Looks up a chat session by ID for the given user (if authenticated) and returns all session data including messages.
-    If there's an active stream for this session, returns the task_id for reconnection.
+    If there's an active stream for this session, returns active_stream info for reconnection.
 
     Args:
         session_id: The unique identifier for the desired chat session.
@@ -228,24 +345,21 @@ async def get_session(
 
     # Check if there's an active stream for this session
     active_stream_info = None
-    active_task, last_message_id = await stream_registry.get_active_task_for_session(
+    active_session, last_message_id = await stream_registry.get_active_session(
         session_id, user_id
     )
-    if active_task:
-        # Filter out the in-progress assistant message from the session response.
-        # The client will receive the complete assistant response through the SSE
-        # stream replay instead, preventing duplicate content.
-        if messages and messages[-1].get("role") == "assistant":
-            messages = messages[:-1]
-
-        # Use "0-0" as last_message_id to replay the stream from the beginning.
-        # Since we filtered out the cached assistant message, the client needs
-        # the full stream to reconstruct the response.
+    logger.info(
+        f"[GET_SESSION] session={session_id}, active_session={active_session is not None}, "
+        f"msg_count={len(messages)}, last_role={messages[-1].get('role') if messages else 'none'}"
+    )
+    if active_session:
+        # Keep the assistant message (including tool_calls) so the frontend can
+        # render the correct tool UI (e.g. CreateAgent with mini game).
+        # convertChatSessionToUiMessages handles isComplete=false by setting
+        # tool parts without output to state "input-available".
         active_stream_info = ActiveStreamInfo(
-            task_id=active_task.task_id,
-            last_message_id="0-0",
-            operation_id=active_task.operation_id,
-            tool_name=active_task.tool_name,
+            turn_id=active_session.turn_id,
+            last_message_id=last_message_id,
         )
 
     return SessionDetailResponse(
@@ -258,6 +372,51 @@ async def get_session(
     )
 
 
+@router.post(
+    "/sessions/{session_id}/cancel",
+    status_code=200,
+)
+async def cancel_session_task(
+    session_id: str,
+    user_id: Annotated[str | None, Depends(auth.get_user_id)],
+) -> CancelSessionResponse:
+    """Cancel the active streaming task for a session.
+
+    Publishes a cancel event to the executor via RabbitMQ FANOUT, then
+    polls Redis until the task status flips from ``running`` or a timeout
+    (5 s) is reached.  Returns only after the cancellation is confirmed.
+    """
+    await _validate_and_get_session(session_id, user_id)
+
+    active_session, _ = await stream_registry.get_active_session(session_id, user_id)
+    if not active_session:
+        return CancelSessionResponse(cancelled=True, reason="no_active_session")
+
+    await enqueue_cancel_task(session_id)
+    logger.info(f"[CANCEL] Published cancel for session ...{session_id[-8:]}")
+
+    # Poll until the executor confirms the task is no longer running.
+    poll_interval = 0.5
+    max_wait = 5.0
+    waited = 0.0
+    while waited < max_wait:
+        await asyncio.sleep(poll_interval)
+        waited += poll_interval
+        session_state = await stream_registry.get_session(session_id)
+        if session_state is None or session_state.status != "running":
+            logger.info(
+                f"[CANCEL] Session ...{session_id[-8:]} confirmed stopped "
+                f"(status={session_state.status if session_state else 'gone'}) after {waited:.1f}s"
+            )
+            return CancelSessionResponse(cancelled=True)
+
+    logger.warning(
+        f"[CANCEL] Session ...{session_id[-8:]} not confirmed after {max_wait}s, force-completing"
+    )
+    await stream_registry.mark_session_completed(session_id, error_message="Cancelled")
+    return CancelSessionResponse(cancelled=True)
+
+
 @router.post(
     "/sessions/{session_id}/stream",
 )
@@ -275,16 +434,15 @@ async def stream_chat_post(
       - Tool execution results
 
     The AI generation runs in a background task that continues even if the client disconnects.
-    All chunks are written to Redis for reconnection support. If the client disconnects,
-    they can reconnect using GET /tasks/{task_id}/stream to resume from where they left off.
+    All chunks are written to a per-turn Redis stream for reconnection support. If the client
+    disconnects, they can reconnect using GET /sessions/{session_id}/stream to resume.
 
     Args:
         session_id: The chat session identifier to associate with the streamed messages.
         request: Request body containing message, is_user_message, and optional context.
         user_id: Optional authenticated user ID.
     Returns:
-        StreamingResponse: SSE-formatted response chunks. First chunk is a "start" event
-        containing the task_id for reconnection.
+        StreamingResponse: SSE-formatted response chunks.
 
     """
     import asyncio
@@ -300,10 +458,9 @@ async def stream_chat_post(
         f"user={user_id}, message_len={len(request.message)}",
         extra={"json_fields": log_meta},
     )
-
-    session = await _validate_and_get_session(session_id, user_id)
+    await _validate_and_get_session(session_id, user_id)
     logger.info(
-        f"[TIMING] session validated in {(time.perf_counter() - stream_start_time)*1000:.1f}ms",
+        f"[TIMING] session validated in {(time.perf_counter() - stream_start_time) * 1000:.1f}ms",
         extra={
             "json_fields": {
                 **log_meta,
@@ -312,106 +469,95 @@ async def stream_chat_post(
         },
     )
 
-    # Create a task in the stream registry for reconnection support
-    task_id = str(uuid_module.uuid4())
-    operation_id = str(uuid_module.uuid4())
-    log_meta["task_id"] = task_id
+    # Enrich message with file metadata if file_ids are provided.
+    # Also sanitise file_ids so only validated, workspace-scoped IDs are
+    # forwarded downstream (e.g. to the executor via enqueue_copilot_turn).
+    sanitized_file_ids: list[str] | None = None
+    if request.file_ids and user_id:
+        # Filter to valid UUIDs only to prevent DB abuse
+        valid_ids = [fid for fid in request.file_ids if _UUID_RE.match(fid)]
 
-    task_create_start = time.perf_counter()
-    await stream_registry.create_task(
-        task_id=task_id,
+        if valid_ids:
+            workspace = await get_or_create_workspace(user_id)
+            # Batch query instead of N+1
+            files = await UserWorkspaceFile.prisma().find_many(
+                where={
+                    "id": {"in": valid_ids},
+                    "workspaceId": workspace.id,
+                    "isDeleted": False,
+                }
+            )
+            # Only keep IDs that actually exist in the user's workspace
+            sanitized_file_ids = [wf.id for wf in files] or None
+            file_lines: list[str] = [
+                f"- {wf.name} ({wf.mimeType}, {round(wf.sizeBytes / 1024, 1)} KB), file_id={wf.id}"
+                for wf in files
+            ]
+            if file_lines:
+                files_block = (
+                    "\n\n[Attached files]\n"
+                    + "\n".join(file_lines)
+                    + "\nUse read_workspace_file with the file_id to access file contents."
+                )
+                request.message += files_block
+
+    # Atomically append user message to session BEFORE creating task to avoid
+    # race condition where GET_SESSION sees task as "running" but message isn't
+    # saved yet.  append_and_save_message re-fetches inside a lock to prevent
+    # message loss from concurrent requests.
+    if request.message:
+        message = ChatMessage(
+            role="user" if request.is_user_message else "assistant",
+            content=request.message,
+        )
+        if request.is_user_message:
+            track_user_message(
+                user_id=user_id,
+                session_id=session_id,
+                message_length=len(request.message),
+            )
+        logger.info(f"[STREAM] Saving user message to session {session_id}")
+        await append_and_save_message(session_id, message)
+        logger.info(f"[STREAM] User message saved for session {session_id}")
+
+    # Create a task in the stream registry for reconnection support
+    turn_id = str(uuid4())
+    log_meta["turn_id"] = turn_id
+
+    session_create_start = time.perf_counter()
+    await stream_registry.create_session(
         session_id=session_id,
         user_id=user_id,
-        tool_call_id="chat_stream",  # Not a tool call, but needed for the model
+        tool_call_id="chat_stream",
         tool_name="chat",
-        operation_id=operation_id,
+        turn_id=turn_id,
     )
     logger.info(
-        f"[TIMING] create_task completed in {(time.perf_counter() - task_create_start)*1000:.1f}ms",
+        f"[TIMING] create_session completed in {(time.perf_counter() - session_create_start) * 1000:.1f}ms",
         extra={
             "json_fields": {
                 **log_meta,
-                "duration_ms": (time.perf_counter() - task_create_start) * 1000,
+                "duration_ms": (time.perf_counter() - session_create_start) * 1000,
             }
         },
     )
 
-    # Background task that runs the AI generation independently of SSE connection
-    async def run_ai_generation():
-        import time as time_module
+    # Per-turn stream is always fresh (unique turn_id), subscribe from beginning
+    subscribe_from_id = "0-0"
 
-        gen_start_time = time_module.perf_counter()
-        logger.info(
-            f"[TIMING] run_ai_generation STARTED, task={task_id}, session={session_id}, user={user_id}",
-            extra={"json_fields": log_meta},
-        )
-        first_chunk_time, ttfc = None, None
-        chunk_count = 0
-        try:
-            async for chunk in chat_service.stream_chat_completion(
-                session_id,
-                request.message,
-                is_user_message=request.is_user_message,
-                user_id=user_id,
-                session=session,  # Pass pre-fetched session to avoid double-fetch
-                context=request.context,
-                _task_id=task_id,  # Pass task_id so service emits start with taskId for reconnection
-            ):
-                chunk_count += 1
-                if first_chunk_time is None:
-                    first_chunk_time = time_module.perf_counter()
-                    ttfc = first_chunk_time - gen_start_time
-                    logger.info(
-                        f"[TIMING] FIRST AI CHUNK at {ttfc:.2f}s, type={type(chunk).__name__}",
-                        extra={
-                            "json_fields": {
-                                **log_meta,
-                                "chunk_type": type(chunk).__name__,
-                                "time_to_first_chunk_ms": ttfc * 1000,
-                            }
-                        },
-                    )
-                # Write to Redis (subscribers will receive via XREAD)
-                await stream_registry.publish_chunk(task_id, chunk)
+    await enqueue_copilot_turn(
+        session_id=session_id,
+        user_id=user_id,
+        message=request.message,
+        turn_id=turn_id,
+        is_user_message=request.is_user_message,
+        context=request.context,
+        file_ids=sanitized_file_ids,
+    )
 
-            gen_end_time = time_module.perf_counter()
-            total_time = (gen_end_time - gen_start_time) * 1000
-            logger.info(
-                f"[TIMING] run_ai_generation FINISHED in {total_time/1000:.1f}s; "
-                f"task={task_id}, session={session_id}, "
-                f"ttfc={ttfc or -1:.2f}s, n_chunks={chunk_count}",
-                extra={
-                    "json_fields": {
-                        **log_meta,
-                        "total_time_ms": total_time,
-                        "time_to_first_chunk_ms": (
-                            ttfc * 1000 if ttfc is not None else None
-                        ),
-                        "n_chunks": chunk_count,
-                    }
-                },
-            )
-            await stream_registry.mark_task_completed(task_id, "completed")
-        except Exception as e:
-            elapsed = time_module.perf_counter() - gen_start_time
-            logger.error(
-                f"[TIMING] run_ai_generation ERROR after {elapsed:.2f}s: {e}",
-                extra={
-                    "json_fields": {
-                        **log_meta,
-                        "elapsed_ms": elapsed * 1000,
-                        "error": str(e),
-                    }
-                },
-            )
-            await stream_registry.mark_task_completed(task_id, "failed")
-
-    # Start the AI generation in a background task
-    bg_task = asyncio.create_task(run_ai_generation())
-    await stream_registry.set_task_asyncio_task(task_id, bg_task)
     setup_time = (time.perf_counter() - stream_start_time) * 1000
     logger.info(
-        f"[TIMING] Background task started, setup={setup_time:.1f}ms",
+        f"[TIMING] Task enqueued to RabbitMQ, setup={setup_time:.1f}ms",
         extra={"json_fields": {**log_meta, "setup_time_ms": setup_time}},
     )
 
@@ -421,7 +567,7 @@ async def stream_chat_post(
 
         event_gen_start = time_module.perf_counter()
         logger.info(
-            f"[TIMING] event_generator STARTED, task={task_id}, session={session_id}, "
+            f"[TIMING] event_generator STARTED, turn={turn_id}, session={session_id}, "
             f"user={user_id}",
             extra={"json_fields": log_meta},
         )
@@ -429,11 +575,12 @@ async def stream_chat_post(
         first_chunk_yielded = False
         chunks_yielded = 0
         try:
-            # Subscribe to the task stream (this replays existing messages + live updates)
-            subscriber_queue = await stream_registry.subscribe_to_task(
-                task_id=task_id,
+            # Subscribe from the position we captured before enqueuing
+            # This avoids replaying old messages while catching all new ones
+            subscriber_queue = await stream_registry.subscribe_to_session(
+                session_id=session_id,
                 user_id=user_id,
-                last_message_id="0-0",  # Get all messages from the beginning
+                last_message_id=subscribe_from_id,
             )
 
             if subscriber_queue is None:
@@ -448,7 +595,7 @@ async def stream_chat_post(
             )
             while True:
                 try:
-                    chunk = await asyncio.wait_for(subscriber_queue.get(), timeout=30.0)
+                    chunk = await asyncio.wait_for(subscriber_queue.get(), timeout=10.0)
                     chunks_yielded += 1
 
                     if not first_chunk_yielded:
@@ -506,23 +653,29 @@ async def stream_chat_post(
                     "json_fields": {**log_meta, "elapsed_ms": elapsed, "error": str(e)}
                 },
             )
+            # Surface error to frontend so it doesn't appear stuck
+            yield StreamError(
+                errorText="An error occurred. Please try again.",
+                code="stream_error",
+            ).to_sse()
+            yield StreamFinish().to_sse()
         finally:
-            # Unsubscribe when client disconnects or stream ends to prevent resource leak
+            # Unsubscribe when client disconnects or stream ends
             if subscriber_queue is not None:
                 try:
-                    await stream_registry.unsubscribe_from_task(
-                        task_id, subscriber_queue
+                    await stream_registry.unsubscribe_from_session(
+                        session_id, subscriber_queue
                     )
                 except Exception as unsub_err:
                     logger.error(
-                        f"Error unsubscribing from task {task_id}: {unsub_err}",
+                        f"Error unsubscribing from session {session_id}: {unsub_err}",
                         exc_info=True,
                     )
             # AI SDK protocol termination - always yield even if unsubscribe fails
             total_time = time_module.perf_counter() - event_gen_start
             logger.info(
                 f"[TIMING] event_generator FINISHED in {total_time:.2f}s; "
-                f"task={task_id}, session={session_id}, n_chunks={chunks_yielded}",
+                f"turn={turn_id}, session={session_id}, n_chunks={chunks_yielded}",
                 extra={
                     "json_fields": {
                         **log_meta,
@@ -569,17 +722,21 @@ async def resume_session_stream(
     """
     import asyncio
 
-    active_task, _last_id = await stream_registry.get_active_task_for_session(
+    active_session, last_message_id = await stream_registry.get_active_session(
         session_id, user_id
     )
 
-    if not active_task:
+    if not active_session:
         return Response(status_code=204)
 
-    subscriber_queue = await stream_registry.subscribe_to_task(
-        task_id=active_task.task_id,
+    # Always replay from the beginning ("0-0") on resume.
+    # We can't use last_message_id because it's the latest ID in the backend
+    # stream, not the latest the frontend received — the gap causes lost
+    # messages. The frontend deduplicates replayed content.
+    subscriber_queue = await stream_registry.subscribe_to_session(
+        session_id=session_id,
         user_id=user_id,
-        last_message_id="0-0",  # Full replay so useChat rebuilds the message
+        last_message_id="0-0",
     )
 
     if subscriber_queue is None:
@@ -591,7 +748,7 @@ async def resume_session_stream(
         try:
             while True:
                 try:
-                    chunk = await asyncio.wait_for(subscriber_queue.get(), timeout=30.0)
+                    chunk = await asyncio.wait_for(subscriber_queue.get(), timeout=10.0)
                     if chunk_count < 3:
                         logger.info(
                             "Resume stream chunk",
@@ -615,12 +772,12 @@ async def resume_session_stream(
             logger.error(f"Error in resume stream for session {session_id}: {e}")
         finally:
             try:
-                await stream_registry.unsubscribe_from_task(
-                    active_task.task_id, subscriber_queue
+                await stream_registry.unsubscribe_from_session(
+                    session_id, subscriber_queue
                 )
             except Exception as unsub_err:
                 logger.error(
-                    f"Error unsubscribing from task {active_task.task_id}: {unsub_err}",
+                    f"Error unsubscribing from session {active_session.session_id}: {unsub_err}",
                     exc_info=True,
                 )
             logger.info(
@@ -671,231 +828,6 @@ async def session_assign_user(
     return {"status": "ok"}
 
 
-# ========== Task Streaming (SSE Reconnection) ==========
-
-
-@router.get(
-    "/tasks/{task_id}/stream",
-)
-async def stream_task(
-    task_id: str,
-    user_id: str | None = Depends(auth.get_user_id),
-    last_message_id: str = Query(
-        default="0-0",
-        description="Last Redis Stream message ID received (e.g., '1706540123456-0'). Use '0-0' for full replay.",
-    ),
-):
-    """
-    Reconnect to a long-running task's SSE stream.
-
-    When a long-running operation (like agent generation) starts, the client
-    receives a task_id. If the connection drops, the client can reconnect
-    using this endpoint to resume receiving updates.
-
-    Args:
-        task_id: The task ID from the operation_started response.
-        user_id: Authenticated user ID for ownership validation.
-        last_message_id: Last Redis Stream message ID received ("0-0" for full replay).
-
-    Returns:
-        StreamingResponse: SSE-formatted response chunks starting after last_message_id.
-
-    Raises:
-        HTTPException: 404 if task not found, 410 if task expired, 403 if access denied.
-    """
-    # Check task existence and expiry before subscribing
-    task, error_code = await stream_registry.get_task_with_expiry_info(task_id)
-
-    if error_code == "TASK_EXPIRED":
-        raise HTTPException(
-            status_code=410,
-            detail={
-                "code": "TASK_EXPIRED",
-                "message": "This operation has expired. Please try again.",
-            },
-        )
-
-    if error_code == "TASK_NOT_FOUND":
-        raise HTTPException(
-            status_code=404,
-            detail={
-                "code": "TASK_NOT_FOUND",
-                "message": f"Task {task_id} not found.",
-            },
-        )
-
-    # Validate ownership if task has an owner
-    if task and task.user_id and user_id != task.user_id:
-        raise HTTPException(
-            status_code=403,
-            detail={
-                "code": "ACCESS_DENIED",
-                "message": "You do not have access to this task.",
-            },
-        )
-
-    # Get subscriber queue from stream registry
-    subscriber_queue = await stream_registry.subscribe_to_task(
-        task_id=task_id,
-        user_id=user_id,
-        last_message_id=last_message_id,
-    )
-
-    if subscriber_queue is None:
-        raise HTTPException(
-            status_code=404,
-            detail={
-                "code": "TASK_NOT_FOUND",
-                "message": f"Task {task_id} not found or access denied.",
-            },
-        )
-
-    async def event_generator() -> AsyncGenerator[str, None]:
-        import asyncio
-
-        heartbeat_interval = 15.0  # Send heartbeat every 15 seconds
-        try:
-            while True:
-                try:
-                    # Wait for next chunk with timeout for heartbeats
-                    chunk = await asyncio.wait_for(
-                        subscriber_queue.get(), timeout=heartbeat_interval
-                    )
-                    yield chunk.to_sse()
-
-                    # Check for finish signal
-                    if isinstance(chunk, StreamFinish):
-                        break
-                except asyncio.TimeoutError:
-                    # Send heartbeat to keep connection alive
-                    yield StreamHeartbeat().to_sse()
-        except Exception as e:
-            logger.error(f"Error in task stream {task_id}: {e}", exc_info=True)
-        finally:
-            # Unsubscribe when client disconnects or stream ends
-            try:
-                await stream_registry.unsubscribe_from_task(task_id, subscriber_queue)
-            except Exception as unsub_err:
-                logger.error(
-                    f"Error unsubscribing from task {task_id}: {unsub_err}",
-                    exc_info=True,
-                )
-            # AI SDK protocol termination - always yield even if unsubscribe fails
-            yield "data: [DONE]\n\n"
-
-    return StreamingResponse(
-        event_generator(),
-        media_type="text/event-stream",
-        headers={
-            "Cache-Control": "no-cache",
-            "Connection": "keep-alive",
-            "X-Accel-Buffering": "no",
-            "x-vercel-ai-ui-message-stream": "v1",
-        },
-    )
-
-
-@router.get(
-    "/tasks/{task_id}",
-)
-async def get_task_status(
-    task_id: str,
-    user_id: str | None = Depends(auth.get_user_id),
-) -> dict:
-    """
-    Get the status of a long-running task.
-
-    Args:
-        task_id: The task ID to check.
-        user_id: Authenticated user ID for ownership validation.
-
-    Returns:
-        dict: Task status including task_id, status, tool_name, and operation_id.
-
-    Raises:
-        NotFoundError: If task_id is not found or user doesn't have access.
-    """
-    task = await stream_registry.get_task(task_id)
-
-    if task is None:
-        raise NotFoundError(f"Task {task_id} not found.")
-
-    # Validate ownership - if task has an owner, requester must match
-    if task.user_id and user_id != task.user_id:
-        raise NotFoundError(f"Task {task_id} not found.")
-
-    return {
-        "task_id": task.task_id,
-        "session_id": task.session_id,
-        "status": task.status,
-        "tool_name": task.tool_name,
-        "operation_id": task.operation_id,
-        "created_at": task.created_at.isoformat(),
-    }
-
-
-# ========== External Completion Webhook ==========
-
-
-@router.post(
-    "/operations/{operation_id}/complete",
-    status_code=200,
-)
-async def complete_operation(
-    operation_id: str,
-    request: OperationCompleteRequest,
-    x_api_key: str | None = Header(default=None),
-) -> dict:
-    """
-    External completion webhook for long-running operations.
-
-    Called by Agent Generator (or other services) when an operation completes.
-    This triggers the stream registry to publish completion and continue LLM generation.
-
-    Args:
-        operation_id: The operation ID to complete.
-        request: Completion payload with success status and result/error.
-        x_api_key: Internal API key for authentication.
-
-    Returns:
-        dict: Status of the completion.
-
-    Raises:
-        HTTPException: If API key is invalid or operation not found.
-    """
-    # Validate internal API key - reject if not configured or invalid
-    if not config.internal_api_key:
-        logger.error(
-            "Operation complete webhook rejected: CHAT_INTERNAL_API_KEY not configured"
-        )
-        raise HTTPException(
-            status_code=503,
-            detail="Webhook not available: internal API key not configured",
-        )
-    if x_api_key != config.internal_api_key:
-        raise HTTPException(status_code=401, detail="Invalid API key")
-
-    # Find task by operation_id
-    task = await stream_registry.find_task_by_operation_id(operation_id)
-    if task is None:
-        raise HTTPException(
-            status_code=404,
-            detail=f"Operation {operation_id} not found",
-        )
-
-    logger.info(
-        f"Received completion webhook for operation {operation_id} "
-        f"(task_id={task.task_id}, success={request.success})"
-    )
-
-    if request.success:
-        await process_operation_success(task, request.result)
-    else:
-        await process_operation_failure(task, request.error)
-
-    return {"status": "ok", "task_id": task.task_id}
-
-
 # ========== Configuration ==========
 
 
@@ -970,13 +902,14 @@ ToolResponseUnion = (
     | AgentPreviewResponse
     | AgentSavedResponse
     | ClarificationNeededResponse
+    | SuggestedGoalResponse
     | BlockListResponse
+    | BlockDetailsResponse
     | BlockOutputResponse
     | DocSearchResultsResponse
     | DocPageResponse
-    | OperationStartedResponse
-    | OperationPendingResponse
-    | OperationInProgressResponse
+    | MCPToolsDiscoveredResponse
+    | MCPToolOutputResponse
 )
 
 

autogpt_platform/backend/backend/api/features/chat/routes_test.py

@@ -0,0 +1,251 @@
+"""Tests for chat API routes: session title update and file attachment validation."""
+
+from unittest.mock import AsyncMock
+
+import fastapi
+import fastapi.testclient
+import pytest
+import pytest_mock
+
+from backend.api.features.chat import routes as chat_routes
+
+app = fastapi.FastAPI()
+app.include_router(chat_routes.router)
+
+client = fastapi.testclient.TestClient(app)
+
+TEST_USER_ID = "3e53486c-cf57-477e-ba2a-cb02dc828e1a"
+
+
+@pytest.fixture(autouse=True)
+def setup_app_auth(mock_jwt_user):
+    """Setup auth overrides for all tests in this module"""
+    from autogpt_libs.auth.jwt_utils import get_jwt_payload
+
+    app.dependency_overrides[get_jwt_payload] = mock_jwt_user["get_jwt_payload"]
+    yield
+    app.dependency_overrides.clear()
+
+
+def _mock_update_session_title(
+    mocker: pytest_mock.MockerFixture, *, success: bool = True
+):
+    """Mock update_session_title."""
+    return mocker.patch(
+        "backend.api.features.chat.routes.update_session_title",
+        new_callable=AsyncMock,
+        return_value=success,
+    )
+
+
+# ─── Update title: success ─────────────────────────────────────────────
+
+
+def test_update_title_success(
+    mocker: pytest_mock.MockerFixture,
+    test_user_id: str,
+) -> None:
+    mock_update = _mock_update_session_title(mocker, success=True)
+
+    response = client.patch(
+        "/sessions/sess-1/title",
+        json={"title": "My project"},
+    )
+
+    assert response.status_code == 200
+    assert response.json() == {"status": "ok"}
+    mock_update.assert_called_once_with("sess-1", test_user_id, "My project")
+
+
+def test_update_title_trims_whitespace(
+    mocker: pytest_mock.MockerFixture,
+    test_user_id: str,
+) -> None:
+    mock_update = _mock_update_session_title(mocker, success=True)
+
+    response = client.patch(
+        "/sessions/sess-1/title",
+        json={"title": "  trimmed  "},
+    )
+
+    assert response.status_code == 200
+    mock_update.assert_called_once_with("sess-1", test_user_id, "trimmed")
+
+
+# ─── Update title: blank / whitespace-only → 422 ──────────────────────
+
+
+def test_update_title_blank_rejected(
+    test_user_id: str,
+) -> None:
+    """Whitespace-only titles must be rejected before hitting the DB."""
+    response = client.patch(
+        "/sessions/sess-1/title",
+        json={"title": "   "},
+    )
+
+    assert response.status_code == 422
+
+
+def test_update_title_empty_rejected(
+    test_user_id: str,
+) -> None:
+    response = client.patch(
+        "/sessions/sess-1/title",
+        json={"title": ""},
+    )
+
+    assert response.status_code == 422
+
+
+# ─── Update title: session not found or wrong user → 404 ──────────────
+
+
+def test_update_title_not_found(
+    mocker: pytest_mock.MockerFixture,
+    test_user_id: str,
+) -> None:
+    _mock_update_session_title(mocker, success=False)
+
+    response = client.patch(
+        "/sessions/sess-1/title",
+        json={"title": "New name"},
+    )
+
+    assert response.status_code == 404
+
+
+# ─── file_ids Pydantic validation ─────────────────────────────────────
+
+
+def test_stream_chat_rejects_too_many_file_ids():
+    """More than 20 file_ids should be rejected by Pydantic validation (422)."""
+    response = client.post(
+        "/sessions/sess-1/stream",
+        json={
+            "message": "hello",
+            "file_ids": [f"00000000-0000-0000-0000-{i:012d}" for i in range(21)],
+        },
+    )
+    assert response.status_code == 422
+
+
+def _mock_stream_internals(mocker: pytest_mock.MockFixture):
+    """Mock the async internals of stream_chat_post so tests can exercise
+    validation and enrichment logic without needing Redis/RabbitMQ."""
+    mocker.patch(
+        "backend.api.features.chat.routes._validate_and_get_session",
+        return_value=None,
+    )
+    mocker.patch(
+        "backend.api.features.chat.routes.append_and_save_message",
+        return_value=None,
+    )
+    mock_registry = mocker.MagicMock()
+    mock_registry.create_session = mocker.AsyncMock(return_value=None)
+    mocker.patch(
+        "backend.api.features.chat.routes.stream_registry",
+        mock_registry,
+    )
+    mocker.patch(
+        "backend.api.features.chat.routes.enqueue_copilot_turn",
+        return_value=None,
+    )
+    mocker.patch(
+        "backend.api.features.chat.routes.track_user_message",
+        return_value=None,
+    )
+
+
+def test_stream_chat_accepts_20_file_ids(mocker: pytest_mock.MockFixture):
+    """Exactly 20 file_ids should be accepted (not rejected by validation)."""
+    _mock_stream_internals(mocker)
+    # Patch workspace lookup as imported by the routes module
+    mocker.patch(
+        "backend.api.features.chat.routes.get_or_create_workspace",
+        return_value=type("W", (), {"id": "ws-1"})(),
+    )
+    mock_prisma = mocker.MagicMock()
+    mock_prisma.find_many = mocker.AsyncMock(return_value=[])
+    mocker.patch(
+        "prisma.models.UserWorkspaceFile.prisma",
+        return_value=mock_prisma,
+    )
+
+    response = client.post(
+        "/sessions/sess-1/stream",
+        json={
+            "message": "hello",
+            "file_ids": [f"00000000-0000-0000-0000-{i:012d}" for i in range(20)],
+        },
+    )
+    # Should get past validation — 200 streaming response expected
+    assert response.status_code == 200
+
+
+# ─── UUID format filtering ─────────────────────────────────────────────
+
+
+def test_file_ids_filters_invalid_uuids(mocker: pytest_mock.MockFixture):
+    """Non-UUID strings in file_ids should be silently filtered out
+    and NOT passed to the database query."""
+    _mock_stream_internals(mocker)
+    mocker.patch(
+        "backend.api.features.chat.routes.get_or_create_workspace",
+        return_value=type("W", (), {"id": "ws-1"})(),
+    )
+
+    mock_prisma = mocker.MagicMock()
+    mock_prisma.find_many = mocker.AsyncMock(return_value=[])
+    mocker.patch(
+        "prisma.models.UserWorkspaceFile.prisma",
+        return_value=mock_prisma,
+    )
+
+    valid_id = "aaaaaaaa-bbbb-cccc-dddd-eeeeeeeeeeee"
+    client.post(
+        "/sessions/sess-1/stream",
+        json={
+            "message": "hello",
+            "file_ids": [
+                valid_id,
+                "not-a-uuid",
+                "../../../etc/passwd",
+                "",
+            ],
+        },
+    )
+
+    # The find_many call should only receive the one valid UUID
+    mock_prisma.find_many.assert_called_once()
+    call_kwargs = mock_prisma.find_many.call_args[1]
+    assert call_kwargs["where"]["id"]["in"] == [valid_id]
+
+
+# ─── Cross-workspace file_ids ─────────────────────────────────────────
+
+
+def test_file_ids_scoped_to_workspace(mocker: pytest_mock.MockFixture):
+    """The batch query should scope to the user's workspace."""
+    _mock_stream_internals(mocker)
+    mocker.patch(
+        "backend.api.features.chat.routes.get_or_create_workspace",
+        return_value=type("W", (), {"id": "my-workspace-id"})(),
+    )
+
+    mock_prisma = mocker.MagicMock()
+    mock_prisma.find_many = mocker.AsyncMock(return_value=[])
+    mocker.patch(
+        "prisma.models.UserWorkspaceFile.prisma",
+        return_value=mock_prisma,
+    )
+
+    fid = "aaaaaaaa-bbbb-cccc-dddd-eeeeeeeeeeee"
+    client.post(
+        "/sessions/sess-1/stream",
+        json={"message": "hi", "file_ids": [fid]},
+    )
+
+    call_kwargs = mock_prisma.find_many.call_args[1]
+    assert call_kwargs["where"]["workspaceId"] == "my-workspace-id"
+    assert call_kwargs["where"]["isDeleted"] is False

autogpt_platform/backend/backend/api/features/chat/service_test.py

@@ -1,82 +0,0 @@
-import logging
-from os import getenv
-
-import pytest
-
-from . import service as chat_service
-from .model import create_chat_session, get_chat_session, upsert_chat_session
-from .response_model import (
-    StreamError,
-    StreamFinish,
-    StreamTextDelta,
-    StreamToolOutputAvailable,
-)
-
-logger = logging.getLogger(__name__)
-
-
-@pytest.mark.asyncio(loop_scope="session")
-async def test_stream_chat_completion(setup_test_user, test_user_id):
-    """
-    Test the stream_chat_completion function.
-    """
-    api_key: str | None = getenv("OPEN_ROUTER_API_KEY")
-    if not api_key:
-        return pytest.skip("OPEN_ROUTER_API_KEY is not set, skipping test")
-
-    session = await create_chat_session(test_user_id)
-
-    has_errors = False
-    has_ended = False
-    assistant_message = ""
-    async for chunk in chat_service.stream_chat_completion(
-        session.session_id, "Hello, how are you?", user_id=session.user_id
-    ):
-        logger.info(chunk)
-        if isinstance(chunk, StreamError):
-            has_errors = True
-        if isinstance(chunk, StreamTextDelta):
-            assistant_message += chunk.delta
-        if isinstance(chunk, StreamFinish):
-            has_ended = True
-
-    assert has_ended, "Chat completion did not end"
-    assert not has_errors, "Error occurred while streaming chat completion"
-    assert assistant_message, "Assistant message is empty"
-
-
-@pytest.mark.asyncio(loop_scope="session")
-async def test_stream_chat_completion_with_tool_calls(setup_test_user, test_user_id):
-    """
-    Test the stream_chat_completion function.
-    """
-    api_key: str | None = getenv("OPEN_ROUTER_API_KEY")
-    if not api_key:
-        return pytest.skip("OPEN_ROUTER_API_KEY is not set, skipping test")
-
-    session = await create_chat_session(test_user_id)
-    session = await upsert_chat_session(session)
-
-    has_errors = False
-    has_ended = False
-    had_tool_calls = False
-    async for chunk in chat_service.stream_chat_completion(
-        session.session_id,
-        "Please find me an agent that can help me with my business. Use the query 'moneny printing agent'",
-        user_id=session.user_id,
-    ):
-        logger.info(chunk)
-        if isinstance(chunk, StreamError):
-            has_errors = True
-
-        if isinstance(chunk, StreamFinish):
-            has_ended = True
-        if isinstance(chunk, StreamToolOutputAvailable):
-            had_tool_calls = True
-
-    assert has_ended, "Chat completion did not end"
-    assert not has_errors, "Error occurred while streaming chat completion"
-    assert had_tool_calls, "Tool calls did not occur"
-    session = await get_chat_session(session.session_id)
-    assert session, "Session not found"
-    assert session.usage, "Usage is empty"

autogpt_platform/backend/backend/api/features/chat/tools/base.py

@@ -1,129 +0,0 @@
-"""Base classes and shared utilities for chat tools."""
-
-import logging
-from typing import Any
-
-from openai.types.chat import ChatCompletionToolParam
-
-from backend.api.features.chat.model import ChatSession
-from backend.api.features.chat.response_model import StreamToolOutputAvailable
-
-from .models import ErrorResponse, NeedLoginResponse, ToolResponseBase
-
-logger = logging.getLogger(__name__)
-
-
-class BaseTool:
-    """Base class for all chat tools."""
-
-    @property
-    def name(self) -> str:
-        """Tool name for OpenAI function calling."""
-        raise NotImplementedError
-
-    @property
-    def description(self) -> str:
-        """Tool description for OpenAI."""
-        raise NotImplementedError
-
-    @property
-    def parameters(self) -> dict[str, Any]:
-        """Tool parameters schema for OpenAI."""
-        raise NotImplementedError
-
-    @property
-    def requires_auth(self) -> bool:
-        """Whether this tool requires authentication."""
-        return False
-
-    @property
-    def is_long_running(self) -> bool:
-        """Whether this tool is long-running and should execute in background.
-
-        Long-running tools (like agent generation) are executed via background
-        tasks to survive SSE disconnections. The result is persisted to chat
-        history and visible when the user refreshes.
-        """
-        return False
-
-    def as_openai_tool(self) -> ChatCompletionToolParam:
-        """Convert to OpenAI tool format."""
-        return ChatCompletionToolParam(
-            type="function",
-            function={
-                "name": self.name,
-                "description": self.description,
-                "parameters": self.parameters,
-            },
-        )
-
-    async def execute(
-        self,
-        user_id: str | None,
-        session: ChatSession,
-        tool_call_id: str,
-        **kwargs,
-    ) -> StreamToolOutputAvailable:
-        """Execute the tool with authentication check.
-
-        Args:
-            user_id: User ID (may be anonymous like "anon_123")
-            session_id: Chat session ID
-            **kwargs: Tool-specific parameters
-
-        Returns:
-            Pydantic response object
-
-        """
-        if self.requires_auth and not user_id:
-            logger.error(
-                f"Attempted tool call for {self.name} but user not authenticated"
-            )
-            return StreamToolOutputAvailable(
-                toolCallId=tool_call_id,
-                toolName=self.name,
-                output=NeedLoginResponse(
-                    message=f"Please sign in to use {self.name}",
-                    session_id=session.session_id,
-                ).model_dump_json(),
-                success=False,
-            )
-
-        try:
-            result = await self._execute(user_id, session, **kwargs)
-            return StreamToolOutputAvailable(
-                toolCallId=tool_call_id,
-                toolName=self.name,
-                output=result.model_dump_json(),
-            )
-        except Exception as e:
-            logger.error(f"Error in {self.name}: {e}", exc_info=True)
-            return StreamToolOutputAvailable(
-                toolCallId=tool_call_id,
-                toolName=self.name,
-                output=ErrorResponse(
-                    message=f"An error occurred while executing {self.name}",
-                    error=str(e),
-                    session_id=session.session_id,
-                ).model_dump_json(),
-                success=False,
-            )
-
-    async def _execute(
-        self,
-        user_id: str | None,
-        session: ChatSession,
-        **kwargs,
-    ) -> ToolResponseBase:
-        """Internal execution logic to be implemented by subclasses.
-
-        Args:
-            user_id: User ID (authenticated or anonymous)
-            session_id: Chat session ID
-            **kwargs: Tool-specific parameters
-
-        Returns:
-            Pydantic response object
-
-        """
-        raise NotImplementedError

autogpt_platform/backend/backend/api/features/chat/tools/find_block_test.py

@@ -1,139 +0,0 @@
-"""Tests for block filtering in FindBlockTool."""
-
-from unittest.mock import AsyncMock, MagicMock, patch
-
-import pytest
-
-from backend.api.features.chat.tools.find_block import (
-    COPILOT_EXCLUDED_BLOCK_IDS,
-    COPILOT_EXCLUDED_BLOCK_TYPES,
-    FindBlockTool,
-)
-from backend.api.features.chat.tools.models import BlockListResponse
-from backend.blocks._base import BlockType
-
-from ._test_data import make_session
-
-_TEST_USER_ID = "test-user-find-block"
-
-
-def make_mock_block(
-    block_id: str, name: str, block_type: BlockType, disabled: bool = False
-):
-    """Create a mock block for testing."""
-    mock = MagicMock()
-    mock.id = block_id
-    mock.name = name
-    mock.description = f"{name} description"
-    mock.block_type = block_type
-    mock.disabled = disabled
-    mock.input_schema = MagicMock()
-    mock.input_schema.jsonschema.return_value = {"properties": {}, "required": []}
-    mock.input_schema.get_credentials_fields.return_value = {}
-    mock.output_schema = MagicMock()
-    mock.output_schema.jsonschema.return_value = {}
-    mock.categories = []
-    return mock
-
-
-class TestFindBlockFiltering:
-    """Tests for block filtering in FindBlockTool."""
-
-    def test_excluded_block_types_contains_expected_types(self):
-        """Verify COPILOT_EXCLUDED_BLOCK_TYPES contains all graph-only types."""
-        assert BlockType.INPUT in COPILOT_EXCLUDED_BLOCK_TYPES
-        assert BlockType.OUTPUT in COPILOT_EXCLUDED_BLOCK_TYPES
-        assert BlockType.WEBHOOK in COPILOT_EXCLUDED_BLOCK_TYPES
-        assert BlockType.WEBHOOK_MANUAL in COPILOT_EXCLUDED_BLOCK_TYPES
-        assert BlockType.NOTE in COPILOT_EXCLUDED_BLOCK_TYPES
-        assert BlockType.HUMAN_IN_THE_LOOP in COPILOT_EXCLUDED_BLOCK_TYPES
-        assert BlockType.AGENT in COPILOT_EXCLUDED_BLOCK_TYPES
-
-    def test_excluded_block_ids_contains_smart_decision_maker(self):
-        """Verify SmartDecisionMakerBlock is in COPILOT_EXCLUDED_BLOCK_IDS."""
-        assert "3b191d9f-356f-482d-8238-ba04b6d18381" in COPILOT_EXCLUDED_BLOCK_IDS
-
-    @pytest.mark.asyncio(loop_scope="session")
-    async def test_excluded_block_type_filtered_from_results(self):
-        """Verify blocks with excluded BlockTypes are filtered from search results."""
-        session = make_session(user_id=_TEST_USER_ID)
-
-        # Mock search returns an INPUT block (excluded) and a STANDARD block (included)
-        search_results = [
-            {"content_id": "input-block-id", "score": 0.9},
-            {"content_id": "standard-block-id", "score": 0.8},
-        ]
-
-        input_block = make_mock_block("input-block-id", "Input Block", BlockType.INPUT)
-        standard_block = make_mock_block(
-            "standard-block-id", "HTTP Request", BlockType.STANDARD
-        )
-
-        def mock_get_block(block_id):
-            return {
-                "input-block-id": input_block,
-                "standard-block-id": standard_block,
-            }.get(block_id)
-
-        with patch(
-            "backend.api.features.chat.tools.find_block.unified_hybrid_search",
-            new_callable=AsyncMock,
-            return_value=(search_results, 2),
-        ):
-            with patch(
-                "backend.api.features.chat.tools.find_block.get_block",
-                side_effect=mock_get_block,
-            ):
-                tool = FindBlockTool()
-                response = await tool._execute(
-                    user_id=_TEST_USER_ID, session=session, query="test"
-                )
-
-        # Should only return the standard block, not the INPUT block
-        assert isinstance(response, BlockListResponse)
-        assert len(response.blocks) == 1
-        assert response.blocks[0].id == "standard-block-id"
-
-    @pytest.mark.asyncio(loop_scope="session")
-    async def test_excluded_block_id_filtered_from_results(self):
-        """Verify SmartDecisionMakerBlock is filtered from search results."""
-        session = make_session(user_id=_TEST_USER_ID)
-
-        smart_decision_id = "3b191d9f-356f-482d-8238-ba04b6d18381"
-        search_results = [
-            {"content_id": smart_decision_id, "score": 0.9},
-            {"content_id": "normal-block-id", "score": 0.8},
-        ]
-
-        # SmartDecisionMakerBlock has STANDARD type but is excluded by ID
-        smart_block = make_mock_block(
-            smart_decision_id, "Smart Decision Maker", BlockType.STANDARD
-        )
-        normal_block = make_mock_block(
-            "normal-block-id", "Normal Block", BlockType.STANDARD
-        )
-
-        def mock_get_block(block_id):
-            return {
-                smart_decision_id: smart_block,
-                "normal-block-id": normal_block,
-            }.get(block_id)
-
-        with patch(
-            "backend.api.features.chat.tools.find_block.unified_hybrid_search",
-            new_callable=AsyncMock,
-            return_value=(search_results, 2),
-        ):
-            with patch(
-                "backend.api.features.chat.tools.find_block.get_block",
-                side_effect=mock_get_block,
-            ):
-                tool = FindBlockTool()
-                response = await tool._execute(
-                    user_id=_TEST_USER_ID, session=session, query="decision"
-                )
-
-        # Should only return normal block, not SmartDecisionMakerBlock
-        assert isinstance(response, BlockListResponse)
-        assert len(response.blocks) == 1
-        assert response.blocks[0].id == "normal-block-id"

autogpt_platform/backend/backend/api/features/chat/tools/run_block_test.py

@@ -1,106 +0,0 @@
-"""Tests for block execution guards in RunBlockTool."""
-
-from unittest.mock import MagicMock, patch
-
-import pytest
-
-from backend.api.features.chat.tools.models import ErrorResponse
-from backend.api.features.chat.tools.run_block import RunBlockTool
-from backend.blocks._base import BlockType
-
-from ._test_data import make_session
-
-_TEST_USER_ID = "test-user-run-block"
-
-
-def make_mock_block(
-    block_id: str, name: str, block_type: BlockType, disabled: bool = False
-):
-    """Create a mock block for testing."""
-    mock = MagicMock()
-    mock.id = block_id
-    mock.name = name
-    mock.block_type = block_type
-    mock.disabled = disabled
-    mock.input_schema = MagicMock()
-    mock.input_schema.jsonschema.return_value = {"properties": {}, "required": []}
-    mock.input_schema.get_credentials_fields_info.return_value = []
-    return mock
-
-
-class TestRunBlockFiltering:
-    """Tests for block execution guards in RunBlockTool."""
-
-    @pytest.mark.asyncio(loop_scope="session")
-    async def test_excluded_block_type_returns_error(self):
-        """Attempting to execute a block with excluded BlockType returns error."""
-        session = make_session(user_id=_TEST_USER_ID)
-
-        input_block = make_mock_block("input-block-id", "Input Block", BlockType.INPUT)
-
-        with patch(
-            "backend.api.features.chat.tools.run_block.get_block",
-            return_value=input_block,
-        ):
-            tool = RunBlockTool()
-            response = await tool._execute(
-                user_id=_TEST_USER_ID,
-                session=session,
-                block_id="input-block-id",
-                input_data={},
-            )
-
-        assert isinstance(response, ErrorResponse)
-        assert "cannot be run directly in CoPilot" in response.message
-        assert "designed for use within graphs only" in response.message
-
-    @pytest.mark.asyncio(loop_scope="session")
-    async def test_excluded_block_id_returns_error(self):
-        """Attempting to execute SmartDecisionMakerBlock returns error."""
-        session = make_session(user_id=_TEST_USER_ID)
-
-        smart_decision_id = "3b191d9f-356f-482d-8238-ba04b6d18381"
-        smart_block = make_mock_block(
-            smart_decision_id, "Smart Decision Maker", BlockType.STANDARD
-        )
-
-        with patch(
-            "backend.api.features.chat.tools.run_block.get_block",
-            return_value=smart_block,
-        ):
-            tool = RunBlockTool()
-            response = await tool._execute(
-                user_id=_TEST_USER_ID,
-                session=session,
-                block_id=smart_decision_id,
-                input_data={},
-            )
-
-        assert isinstance(response, ErrorResponse)
-        assert "cannot be run directly in CoPilot" in response.message
-
-    @pytest.mark.asyncio(loop_scope="session")
-    async def test_non_excluded_block_passes_guard(self):
-        """Non-excluded blocks pass the filtering guard (may fail later for other reasons)."""
-        session = make_session(user_id=_TEST_USER_ID)
-
-        standard_block = make_mock_block(
-            "standard-id", "HTTP Request", BlockType.STANDARD
-        )
-
-        with patch(
-            "backend.api.features.chat.tools.run_block.get_block",
-            return_value=standard_block,
-        ):
-            tool = RunBlockTool()
-            response = await tool._execute(
-                user_id=_TEST_USER_ID,
-                session=session,
-                block_id="standard-id",
-                input_data={},
-            )
-
-        # Should NOT be an ErrorResponse about CoPilot exclusion
-        # (may be other errors like missing credentials, but not the exclusion guard)
-        if isinstance(response, ErrorResponse):
-            assert "cannot be run directly in CoPilot" not in response.message

autogpt_platform/backend/backend/api/features/chat/tools/workspace_files.py

@@ -1,620 +0,0 @@
-"""CoPilot tools for workspace file operations."""
-
-import base64
-import logging
-from typing import Any, Optional
-
-from pydantic import BaseModel
-
-from backend.api.features.chat.model import ChatSession
-from backend.data.workspace import get_or_create_workspace
-from backend.util.settings import Config
-from backend.util.virus_scanner import scan_content_safe
-from backend.util.workspace import WorkspaceManager
-
-from .base import BaseTool
-from .models import ErrorResponse, ResponseType, ToolResponseBase
-
-logger = logging.getLogger(__name__)
-
-
-class WorkspaceFileInfoData(BaseModel):
-    """Data model for workspace file information (not a response itself)."""
-
-    file_id: str
-    name: str
-    path: str
-    mime_type: str
-    size_bytes: int
-
-
-class WorkspaceFileListResponse(ToolResponseBase):
-    """Response containing list of workspace files."""
-
-    type: ResponseType = ResponseType.WORKSPACE_FILE_LIST
-    files: list[WorkspaceFileInfoData]
-    total_count: int
-
-
-class WorkspaceFileContentResponse(ToolResponseBase):
-    """Response containing workspace file content (legacy, for small text files)."""
-
-    type: ResponseType = ResponseType.WORKSPACE_FILE_CONTENT
-    file_id: str
-    name: str
-    path: str
-    mime_type: str
-    content_base64: str
-
-
-class WorkspaceFileMetadataResponse(ToolResponseBase):
-    """Response containing workspace file metadata and download URL (prevents context bloat)."""
-
-    type: ResponseType = ResponseType.WORKSPACE_FILE_METADATA
-    file_id: str
-    name: str
-    path: str
-    mime_type: str
-    size_bytes: int
-    download_url: str
-    preview: str | None = None  # First 500 chars for text files
-
-
-class WorkspaceWriteResponse(ToolResponseBase):
-    """Response after writing a file to workspace."""
-
-    type: ResponseType = ResponseType.WORKSPACE_FILE_WRITTEN
-    file_id: str
-    name: str
-    path: str
-    size_bytes: int
-
-
-class WorkspaceDeleteResponse(ToolResponseBase):
-    """Response after deleting a file from workspace."""
-
-    type: ResponseType = ResponseType.WORKSPACE_FILE_DELETED
-    file_id: str
-    success: bool
-
-
-class ListWorkspaceFilesTool(BaseTool):
-    """Tool for listing files in user's workspace."""
-
-    @property
-    def name(self) -> str:
-        return "list_workspace_files"
-
-    @property
-    def description(self) -> str:
-        return (
-            "List files in the user's workspace. "
-            "Returns file names, paths, sizes, and metadata. "
-            "Optionally filter by path prefix."
-        )
-
-    @property
-    def parameters(self) -> dict[str, Any]:
-        return {
-            "type": "object",
-            "properties": {
-                "path_prefix": {
-                    "type": "string",
-                    "description": (
-                        "Optional path prefix to filter files "
-                        "(e.g., '/documents/' to list only files in documents folder). "
-                        "By default, only files from the current session are listed."
-                    ),
-                },
-                "limit": {
-                    "type": "integer",
-                    "description": "Maximum number of files to return (default 50, max 100)",
-                    "minimum": 1,
-                    "maximum": 100,
-                },
-                "include_all_sessions": {
-                    "type": "boolean",
-                    "description": (
-                        "If true, list files from all sessions. "
-                        "Default is false (only current session's files)."
-                    ),
-                },
-            },
-            "required": [],
-        }
-
-    @property
-    def requires_auth(self) -> bool:
-        return True
-
-    async def _execute(
-        self,
-        user_id: str | None,
-        session: ChatSession,
-        **kwargs,
-    ) -> ToolResponseBase:
-        session_id = session.session_id
-
-        if not user_id:
-            return ErrorResponse(
-                message="Authentication required",
-                session_id=session_id,
-            )
-
-        path_prefix: Optional[str] = kwargs.get("path_prefix")
-        limit = min(kwargs.get("limit", 50), 100)
-        include_all_sessions: bool = kwargs.get("include_all_sessions", False)
-
-        try:
-            workspace = await get_or_create_workspace(user_id)
-            # Pass session_id for session-scoped file access
-            manager = WorkspaceManager(user_id, workspace.id, session_id)
-
-            files = await manager.list_files(
-                path=path_prefix,
-                limit=limit,
-                include_all_sessions=include_all_sessions,
-            )
-            total = await manager.get_file_count(
-                path=path_prefix,
-                include_all_sessions=include_all_sessions,
-            )
-
-            file_infos = [
-                WorkspaceFileInfoData(
-                    file_id=f.id,
-                    name=f.name,
-                    path=f.path,
-                    mime_type=f.mimeType,
-                    size_bytes=f.sizeBytes,
-                )
-                for f in files
-            ]
-
-            scope_msg = "all sessions" if include_all_sessions else "current session"
-            return WorkspaceFileListResponse(
-                files=file_infos,
-                total_count=total,
-                message=f"Found {len(files)} files in workspace ({scope_msg})",
-                session_id=session_id,
-            )
-
-        except Exception as e:
-            logger.error(f"Error listing workspace files: {e}", exc_info=True)
-            return ErrorResponse(
-                message=f"Failed to list workspace files: {str(e)}",
-                error=str(e),
-                session_id=session_id,
-            )
-
-
-class ReadWorkspaceFileTool(BaseTool):
-    """Tool for reading file content from workspace."""
-
-    # Size threshold for returning full content vs metadata+URL
-    # Files larger than this return metadata with download URL to prevent context bloat
-    MAX_INLINE_SIZE_BYTES = 32 * 1024  # 32KB
-    # Preview size for text files
-    PREVIEW_SIZE = 500
-
-    @property
-    def name(self) -> str:
-        return "read_workspace_file"
-
-    @property
-    def description(self) -> str:
-        return (
-            "Read a file from the user's workspace. "
-            "Specify either file_id or path to identify the file. "
-            "For small text files, returns content directly. "
-            "For large or binary files, returns metadata and a download URL. "
-            "Paths are scoped to the current session by default. "
-            "Use /sessions/<session_id>/... for cross-session access."
-        )
-
-    @property
-    def parameters(self) -> dict[str, Any]:
-        return {
-            "type": "object",
-            "properties": {
-                "file_id": {
-                    "type": "string",
-                    "description": "The file's unique ID (from list_workspace_files)",
-                },
-                "path": {
-                    "type": "string",
-                    "description": (
-                        "The virtual file path (e.g., '/documents/report.pdf'). "
-                        "Scoped to current session by default."
-                    ),
-                },
-                "force_download_url": {
-                    "type": "boolean",
-                    "description": (
-                        "If true, always return metadata+URL instead of inline content. "
-                        "Default is false (auto-selects based on file size/type)."
-                    ),
-                },
-            },
-            "required": [],  # At least one must be provided
-        }
-
-    @property
-    def requires_auth(self) -> bool:
-        return True
-
-    def _is_text_mime_type(self, mime_type: str) -> bool:
-        """Check if the MIME type is a text-based type."""
-        text_types = [
-            "text/",
-            "application/json",
-            "application/xml",
-            "application/javascript",
-            "application/x-python",
-            "application/x-sh",
-        ]
-        return any(mime_type.startswith(t) for t in text_types)
-
-    async def _execute(
-        self,
-        user_id: str | None,
-        session: ChatSession,
-        **kwargs,
-    ) -> ToolResponseBase:
-        session_id = session.session_id
-
-        if not user_id:
-            return ErrorResponse(
-                message="Authentication required",
-                session_id=session_id,
-            )
-
-        file_id: Optional[str] = kwargs.get("file_id")
-        path: Optional[str] = kwargs.get("path")
-        force_download_url: bool = kwargs.get("force_download_url", False)
-
-        if not file_id and not path:
-            return ErrorResponse(
-                message="Please provide either file_id or path",
-                session_id=session_id,
-            )
-
-        try:
-            workspace = await get_or_create_workspace(user_id)
-            # Pass session_id for session-scoped file access
-            manager = WorkspaceManager(user_id, workspace.id, session_id)
-
-            # Get file info
-            if file_id:
-                file_info = await manager.get_file_info(file_id)
-                if file_info is None:
-                    return ErrorResponse(
-                        message=f"File not found: {file_id}",
-                        session_id=session_id,
-                    )
-                target_file_id = file_id
-            else:
-                # path is guaranteed to be non-None here due to the check above
-                assert path is not None
-                file_info = await manager.get_file_info_by_path(path)
-                if file_info is None:
-                    return ErrorResponse(
-                        message=f"File not found at path: {path}",
-                        session_id=session_id,
-                    )
-                target_file_id = file_info.id
-
-            # Decide whether to return inline content or metadata+URL
-            is_small_file = file_info.sizeBytes <= self.MAX_INLINE_SIZE_BYTES
-            is_text_file = self._is_text_mime_type(file_info.mimeType)
-
-            # Return inline content for small text files (unless force_download_url)
-            if is_small_file and is_text_file and not force_download_url:
-                content = await manager.read_file_by_id(target_file_id)
-                content_b64 = base64.b64encode(content).decode("utf-8")
-
-                return WorkspaceFileContentResponse(
-                    file_id=file_info.id,
-                    name=file_info.name,
-                    path=file_info.path,
-                    mime_type=file_info.mimeType,
-                    content_base64=content_b64,
-                    message=f"Successfully read file: {file_info.name}",
-                    session_id=session_id,
-                )
-
-            # Return metadata + workspace:// reference for large or binary files
-            # This prevents context bloat (100KB file = ~133KB as base64)
-            # Use workspace:// format so frontend urlTransform can add proxy prefix
-            download_url = f"workspace://{target_file_id}"
-
-            # Generate preview for text files
-            preview: str | None = None
-            if is_text_file:
-                try:
-                    content = await manager.read_file_by_id(target_file_id)
-                    preview_text = content[: self.PREVIEW_SIZE].decode(
-                        "utf-8", errors="replace"
-                    )
-                    if len(content) > self.PREVIEW_SIZE:
-                        preview_text += "..."
-                    preview = preview_text
-                except Exception:
-                    pass  # Preview is optional
-
-            return WorkspaceFileMetadataResponse(
-                file_id=file_info.id,
-                name=file_info.name,
-                path=file_info.path,
-                mime_type=file_info.mimeType,
-                size_bytes=file_info.sizeBytes,
-                download_url=download_url,
-                preview=preview,
-                message=f"File: {file_info.name} ({file_info.sizeBytes} bytes). Use download_url to retrieve content.",
-                session_id=session_id,
-            )
-
-        except FileNotFoundError as e:
-            return ErrorResponse(
-                message=str(e),
-                session_id=session_id,
-            )
-        except Exception as e:
-            logger.error(f"Error reading workspace file: {e}", exc_info=True)
-            return ErrorResponse(
-                message=f"Failed to read workspace file: {str(e)}",
-                error=str(e),
-                session_id=session_id,
-            )
-
-
-class WriteWorkspaceFileTool(BaseTool):
-    """Tool for writing files to workspace."""
-
-    @property
-    def name(self) -> str:
-        return "write_workspace_file"
-
-    @property
-    def description(self) -> str:
-        return (
-            "Write or create a file in the user's workspace. "
-            "Provide the content as a base64-encoded string. "
-            f"Maximum file size is {Config().max_file_size_mb}MB. "
-            "Files are saved to the current session's folder by default. "
-            "Use /sessions/<session_id>/... for cross-session access."
-        )
-
-    @property
-    def parameters(self) -> dict[str, Any]:
-        return {
-            "type": "object",
-            "properties": {
-                "filename": {
-                    "type": "string",
-                    "description": "Name for the file (e.g., 'report.pdf')",
-                },
-                "content_base64": {
-                    "type": "string",
-                    "description": "Base64-encoded file content",
-                },
-                "path": {
-                    "type": "string",
-                    "description": (
-                        "Optional virtual path where to save the file "
-                        "(e.g., '/documents/report.pdf'). "
-                        "Defaults to '/{filename}'. Scoped to current session."
-                    ),
-                },
-                "mime_type": {
-                    "type": "string",
-                    "description": (
-                        "Optional MIME type of the file. "
-                        "Auto-detected from filename if not provided."
-                    ),
-                },
-                "overwrite": {
-                    "type": "boolean",
-                    "description": "Whether to overwrite if file exists at path (default: false)",
-                },
-            },
-            "required": ["filename", "content_base64"],
-        }
-
-    @property
-    def requires_auth(self) -> bool:
-        return True
-
-    async def _execute(
-        self,
-        user_id: str | None,
-        session: ChatSession,
-        **kwargs,
-    ) -> ToolResponseBase:
-        session_id = session.session_id
-
-        if not user_id:
-            return ErrorResponse(
-                message="Authentication required",
-                session_id=session_id,
-            )
-
-        filename: str = kwargs.get("filename", "")
-        content_b64: str = kwargs.get("content_base64", "")
-        path: Optional[str] = kwargs.get("path")
-        mime_type: Optional[str] = kwargs.get("mime_type")
-        overwrite: bool = kwargs.get("overwrite", False)
-
-        if not filename:
-            return ErrorResponse(
-                message="Please provide a filename",
-                session_id=session_id,
-            )
-
-        if not content_b64:
-            return ErrorResponse(
-                message="Please provide content_base64",
-                session_id=session_id,
-            )
-
-        # Decode content
-        try:
-            content = base64.b64decode(content_b64)
-        except Exception:
-            return ErrorResponse(
-                message="Invalid base64-encoded content",
-                session_id=session_id,
-            )
-
-        # Check size
-        max_file_size = Config().max_file_size_mb * 1024 * 1024
-        if len(content) > max_file_size:
-            return ErrorResponse(
-                message=f"File too large. Maximum size is {Config().max_file_size_mb}MB",
-                session_id=session_id,
-            )
-
-        try:
-            # Virus scan
-            await scan_content_safe(content, filename=filename)
-
-            workspace = await get_or_create_workspace(user_id)
-            # Pass session_id for session-scoped file access
-            manager = WorkspaceManager(user_id, workspace.id, session_id)
-
-            file_record = await manager.write_file(
-                content=content,
-                filename=filename,
-                path=path,
-                mime_type=mime_type,
-                overwrite=overwrite,
-            )
-
-            return WorkspaceWriteResponse(
-                file_id=file_record.id,
-                name=file_record.name,
-                path=file_record.path,
-                size_bytes=file_record.sizeBytes,
-                message=f"Successfully wrote file: {file_record.name}",
-                session_id=session_id,
-            )
-
-        except ValueError as e:
-            return ErrorResponse(
-                message=str(e),
-                session_id=session_id,
-            )
-        except Exception as e:
-            logger.error(f"Error writing workspace file: {e}", exc_info=True)
-            return ErrorResponse(
-                message=f"Failed to write workspace file: {str(e)}",
-                error=str(e),
-                session_id=session_id,
-            )
-
-
-class DeleteWorkspaceFileTool(BaseTool):
-    """Tool for deleting files from workspace."""
-
-    @property
-    def name(self) -> str:
-        return "delete_workspace_file"
-
-    @property
-    def description(self) -> str:
-        return (
-            "Delete a file from the user's workspace. "
-            "Specify either file_id or path to identify the file. "
-            "Paths are scoped to the current session by default. "
-            "Use /sessions/<session_id>/... for cross-session access."
-        )
-
-    @property
-    def parameters(self) -> dict[str, Any]:
-        return {
-            "type": "object",
-            "properties": {
-                "file_id": {
-                    "type": "string",
-                    "description": "The file's unique ID (from list_workspace_files)",
-                },
-                "path": {
-                    "type": "string",
-                    "description": (
-                        "The virtual file path (e.g., '/documents/report.pdf'). "
-                        "Scoped to current session by default."
-                    ),
-                },
-            },
-            "required": [],  # At least one must be provided
-        }
-
-    @property
-    def requires_auth(self) -> bool:
-        return True
-
-    async def _execute(
-        self,
-        user_id: str | None,
-        session: ChatSession,
-        **kwargs,
-    ) -> ToolResponseBase:
-        session_id = session.session_id
-
-        if not user_id:
-            return ErrorResponse(
-                message="Authentication required",
-                session_id=session_id,
-            )
-
-        file_id: Optional[str] = kwargs.get("file_id")
-        path: Optional[str] = kwargs.get("path")
-
-        if not file_id and not path:
-            return ErrorResponse(
-                message="Please provide either file_id or path",
-                session_id=session_id,
-            )
-
-        try:
-            workspace = await get_or_create_workspace(user_id)
-            # Pass session_id for session-scoped file access
-            manager = WorkspaceManager(user_id, workspace.id, session_id)
-
-            # Determine the file_id to delete
-            target_file_id: str
-            if file_id:
-                target_file_id = file_id
-            else:
-                # path is guaranteed to be non-None here due to the check above
-                assert path is not None
-                file_info = await manager.get_file_info_by_path(path)
-                if file_info is None:
-                    return ErrorResponse(
-                        message=f"File not found at path: {path}",
-                        session_id=session_id,
-                    )
-                target_file_id = file_info.id
-
-            success = await manager.delete_file(target_file_id)
-
-            if not success:
-                return ErrorResponse(
-                    message=f"File not found: {target_file_id}",
-                    session_id=session_id,
-                )
-
-            return WorkspaceDeleteResponse(
-                file_id=target_file_id,
-                success=True,
-                message="File deleted successfully",
-                session_id=session_id,
-            )
-
-        except Exception as e:
-            logger.error(f"Error deleting workspace file: {e}", exc_info=True)
-            return ErrorResponse(
-                message=f"Failed to delete workspace file: {str(e)}",
-                error=str(e),
-                session_id=session_id,
-            )

autogpt_platform/backend/backend/api/features/executions/review/routes.py

@@ -22,6 +22,7 @@ from backend.data.human_review import (
 )
 from backend.data.model import USER_TIMEZONE_NOT_SET
 from backend.data.user import get_user_by_id
+from backend.data.workspace import get_or_create_workspace
 from backend.executor.utils import add_graph_execution
 
 from .model import PendingHumanReviewModel, ReviewRequest, ReviewResponse
@@ -321,10 +322,13 @@ async def process_review_action(
                     user.timezone if user.timezone != USER_TIMEZONE_NOT_SET else "UTC"
                 )
 
+                workspace = await get_or_create_workspace(user_id)
+
                 execution_context = ExecutionContext(
                     human_in_the_loop_safe_mode=settings.human_in_the_loop_safe_mode,
                     sensitive_action_safe_mode=settings.sensitive_action_safe_mode,
                     user_timezone=user_timezone,
+                    workspace_id=workspace.id,
                 )
 
                 await add_graph_execution(

autogpt_platform/backend/backend/api/features/integrations/router.py

@@ -1,7 +1,7 @@
 import asyncio
 import logging
 from datetime import datetime, timedelta, timezone
-from typing import TYPE_CHECKING, Annotated, List, Literal
+from typing import TYPE_CHECKING, Annotated, Any, List, Literal
 
 from autogpt_libs.auth import get_user_id
 from fastapi import (
@@ -14,7 +14,7 @@ from fastapi import (
     Security,
     status,
 )
-from pydantic import BaseModel, Field, SecretStr
+from pydantic import BaseModel, Field, SecretStr, model_validator
 from starlette.status import HTTP_500_INTERNAL_SERVER_ERROR, HTTP_502_BAD_GATEWAY
 
 from backend.api.features.library.db import set_preset_webhook, update_preset
@@ -39,7 +39,11 @@ from backend.data.onboarding import OnboardingStep, complete_onboarding_step
 from backend.data.user import get_user_integrations
 from backend.executor.utils import add_graph_execution
 from backend.integrations.ayrshare import AyrshareClient, SocialPlatform
-from backend.integrations.creds_manager import IntegrationCredentialsManager
+from backend.integrations.credentials_store import provider_matches
+from backend.integrations.creds_manager import (
+    IntegrationCredentialsManager,
+    create_mcp_oauth_handler,
+)
 from backend.integrations.oauth import CREDENTIALS_BY_PROVIDER, HANDLERS_BY_NAME
 from backend.integrations.providers import ProviderName
 from backend.integrations.webhooks import get_webhook_manager
@@ -102,9 +106,37 @@ class CredentialsMetaResponse(BaseModel):
     scopes: list[str] | None
     username: str | None
     host: str | None = Field(
-        default=None, description="Host pattern for host-scoped credentials"
+        default=None,
+        description="Host pattern for host-scoped or MCP server URL for MCP credentials",
     )
 
+    @model_validator(mode="before")
+    @classmethod
+    def _normalize_provider(cls, data: Any) -> Any:
+        """Fix ``ProviderName.X`` format from Python 3.13 ``str(Enum)`` bug."""
+        if isinstance(data, dict):
+            prov = data.get("provider", "")
+            if isinstance(prov, str) and prov.startswith("ProviderName."):
+                member = prov.removeprefix("ProviderName.")
+                try:
+                    data = {**data, "provider": ProviderName[member].value}
+                except KeyError:
+                    pass
+        return data
+
+    @staticmethod
+    def get_host(cred: Credentials) -> str | None:
+        """Extract host from credential: HostScoped host or MCP server URL."""
+        if isinstance(cred, HostScopedCredentials):
+            return cred.host
+        if isinstance(cred, OAuth2Credentials) and cred.provider in (
+            ProviderName.MCP,
+            ProviderName.MCP.value,
+            "ProviderName.MCP",
+        ):
+            return (cred.metadata or {}).get("mcp_server_url")
+        return None
+
 
 @router.post("/{provider}/callback", summary="Exchange OAuth code for tokens")
 async def callback(
@@ -179,9 +211,7 @@ async def callback(
         title=credentials.title,
         scopes=credentials.scopes,
         username=credentials.username,
-        host=(
-            credentials.host if isinstance(credentials, HostScopedCredentials) else None
-        ),
+        host=(CredentialsMetaResponse.get_host(credentials)),
     )
 
 
@@ -199,7 +229,7 @@ async def list_credentials(
             title=cred.title,
             scopes=cred.scopes if isinstance(cred, OAuth2Credentials) else None,
             username=cred.username if isinstance(cred, OAuth2Credentials) else None,
-            host=cred.host if isinstance(cred, HostScopedCredentials) else None,
+            host=CredentialsMetaResponse.get_host(cred),
         )
         for cred in credentials
     ]
@@ -222,7 +252,7 @@ async def list_credentials_by_provider(
             title=cred.title,
             scopes=cred.scopes if isinstance(cred, OAuth2Credentials) else None,
             username=cred.username if isinstance(cred, OAuth2Credentials) else None,
-            host=cred.host if isinstance(cred, HostScopedCredentials) else None,
+            host=CredentialsMetaResponse.get_host(cred),
         )
         for cred in credentials
     ]
@@ -322,7 +352,11 @@ async def delete_credentials(
 
     tokens_revoked = None
     if isinstance(creds, OAuth2Credentials):
-        handler = _get_provider_oauth_handler(request, provider)
+        if provider_matches(provider.value, ProviderName.MCP.value):
+            # MCP uses dynamic per-server OAuth — create handler from metadata
+            handler = create_mcp_oauth_handler(creds)
+        else:
+            handler = _get_provider_oauth_handler(request, provider)
         tokens_revoked = await handler.revoke_tokens(creds)
 
     return CredentialsDeletionResponse(revoked=tokens_revoked)

autogpt_platform/backend/backend/api/features/library/db_test.py

@@ -144,6 +144,7 @@ async def test_add_agent_to_library(mocker):
     )
 
     mock_library_agent = mocker.patch("prisma.models.LibraryAgent.prisma")
+    mock_library_agent.return_value.find_first = mocker.AsyncMock(return_value=None)
     mock_library_agent.return_value.find_unique = mocker.AsyncMock(return_value=None)
     mock_library_agent.return_value.create = mocker.AsyncMock(
         return_value=mock_library_agent_data
@@ -178,7 +179,6 @@ async def test_add_agent_to_library(mocker):
                 "agentGraphVersion": 1,
             }
         },
-        include={"AgentGraph": True},
     )
     # Check that create was called with the expected data including settings
     create_call_args = mock_library_agent.return_value.create.call_args

autogpt_platform/backend/backend/api/features/library/exceptions.py

@@ -0,0 +1,10 @@
+class FolderValidationError(Exception):
+    """Raised when folder operations fail validation."""
+
+    pass
+
+
+class FolderAlreadyExistsError(FolderValidationError):
+    """Raised when a folder with the same name already exists in the location."""
+
+    pass

autogpt_platform/backend/backend/api/features/library/model.py

@@ -26,6 +26,95 @@ class LibraryAgentStatus(str, Enum):
     ERROR = "ERROR"
 
 
+# === Folder Models ===
+
+
+class LibraryFolder(pydantic.BaseModel):
+    """Represents a folder for organizing library agents."""
+
+    id: str
+    user_id: str
+    name: str
+    icon: str | None = None
+    color: str | None = None
+    parent_id: str | None = None
+    created_at: datetime.datetime
+    updated_at: datetime.datetime
+    agent_count: int = 0  # Direct agents in folder
+    subfolder_count: int = 0  # Direct child folders
+
+    @staticmethod
+    def from_db(
+        folder: prisma.models.LibraryFolder,
+        agent_count: int = 0,
+        subfolder_count: int = 0,
+    ) -> "LibraryFolder":
+        """Factory method that constructs a LibraryFolder from a Prisma model."""
+        return LibraryFolder(
+            id=folder.id,
+            user_id=folder.userId,
+            name=folder.name,
+            icon=folder.icon,
+            color=folder.color,
+            parent_id=folder.parentId,
+            created_at=folder.createdAt,
+            updated_at=folder.updatedAt,
+            agent_count=agent_count,
+            subfolder_count=subfolder_count,
+        )
+
+
+class LibraryFolderTree(LibraryFolder):
+    """Folder with nested children for tree view."""
+
+    children: list["LibraryFolderTree"] = []
+
+
+class FolderCreateRequest(pydantic.BaseModel):
+    """Request model for creating a folder."""
+
+    name: str = pydantic.Field(..., min_length=1, max_length=100)
+    icon: str | None = None
+    color: str | None = pydantic.Field(
+        None, pattern=r"^#[0-9A-Fa-f]{6}$", description="Hex color code (#RRGGBB)"
+    )
+    parent_id: str | None = None
+
+
+class FolderUpdateRequest(pydantic.BaseModel):
+    """Request model for updating a folder."""
+
+    name: str | None = pydantic.Field(None, min_length=1, max_length=100)
+    icon: str | None = None
+    color: str | None = None
+
+
+class FolderMoveRequest(pydantic.BaseModel):
+    """Request model for moving a folder to a new parent."""
+
+    target_parent_id: str | None = None  # None = move to root
+
+
+class BulkMoveAgentsRequest(pydantic.BaseModel):
+    """Request model for moving multiple agents to a folder."""
+
+    agent_ids: list[str]
+    folder_id: str | None = None  # None = move to root
+
+
+class FolderListResponse(pydantic.BaseModel):
+    """Response schema for a list of folders."""
+
+    folders: list[LibraryFolder]
+    pagination: Pagination
+
+
+class FolderTreeResponse(pydantic.BaseModel):
+    """Response schema for folder tree structure."""
+
+    tree: list[LibraryFolderTree]
+
+
 class MarketplaceListingCreator(pydantic.BaseModel):
     """Creator information for a marketplace listing."""
 
@@ -120,6 +209,9 @@ class LibraryAgent(pydantic.BaseModel):
     can_access_graph: bool
     is_latest_version: bool
     is_favorite: bool
+    folder_id: str | None = None
+    folder_name: str | None = None  # Denormalized for display
+
     recommended_schedule_cron: str | None = None
     settings: GraphSettings = pydantic.Field(default_factory=GraphSettings)
     marketplace_listing: Optional["MarketplaceListing"] = None
@@ -259,6 +351,8 @@ class LibraryAgent(pydantic.BaseModel):
             can_access_graph=can_access_graph,
             is_latest_version=is_latest_version,
             is_favorite=agent.isFavorite,
+            folder_id=agent.folderId,
+            folder_name=agent.Folder.name if agent.Folder else None,
             recommended_schedule_cron=agent.AgentGraph.recommendedScheduleCron,
             settings=_parse_settings(agent.settings),
             marketplace_listing=marketplace_listing_data,
@@ -470,3 +564,7 @@ class LibraryAgentUpdateRequest(pydantic.BaseModel):
     settings: Optional[GraphSettings] = pydantic.Field(
         default=None, description="User-specific settings for this library agent"
     )
+    folder_id: Optional[str] = pydantic.Field(
+        default=None,
+        description="Folder ID to move agent to (None to move to root)",
+    )

autogpt_platform/backend/backend/api/features/library/routes/__init__.py

@@ -1,9 +1,11 @@
 import fastapi
 
 from .agents import router as agents_router
+from .folders import router as folders_router
 from .presets import router as presets_router
 
 router = fastapi.APIRouter()
 
 router.include_router(presets_router)
+router.include_router(folders_router)
 router.include_router(agents_router)

autogpt_platform/backend/backend/api/features/library/routes/agents.py

@@ -41,6 +41,14 @@ async def list_library_agents(
         ge=1,
         description="Number of agents per page (must be >= 1)",
     ),
+    folder_id: Optional[str] = Query(
+        None,
+        description="Filter by folder ID",
+    ),
+    include_root_only: bool = Query(
+        False,
+        description="Only return agents without a folder (root-level agents)",
+    ),
 ) -> library_model.LibraryAgentResponse:
     """
     Get all agents in the user's library (both created and saved).
@@ -51,6 +59,8 @@ async def list_library_agents(
         sort_by=sort_by,
         page=page,
         page_size=page_size,
+        folder_id=folder_id,
+        include_root_only=include_root_only,
     )
 
 
@@ -168,6 +178,7 @@ async def update_library_agent(
         is_favorite=payload.is_favorite,
         is_archived=payload.is_archived,
         settings=payload.settings,
+        folder_id=payload.folder_id,
     )
 
 

autogpt_platform/backend/backend/api/features/library/routes/folders.py

@@ -0,0 +1,287 @@
+from typing import Optional
+
+import autogpt_libs.auth as autogpt_auth_lib
+from fastapi import APIRouter, Query, Security, status
+from fastapi.responses import Response
+
+from .. import db as library_db
+from .. import model as library_model
+
+router = APIRouter(
+    prefix="/folders",
+    tags=["library", "folders", "private"],
+    dependencies=[Security(autogpt_auth_lib.requires_user)],
+)
+
+
+@router.get(
+    "",
+    summary="List Library Folders",
+    response_model=library_model.FolderListResponse,
+    responses={
+        200: {"description": "List of folders"},
+        500: {"description": "Server error"},
+    },
+)
+async def list_folders(
+    user_id: str = Security(autogpt_auth_lib.get_user_id),
+    parent_id: Optional[str] = Query(
+        None,
+        description="Filter by parent folder ID. If not provided, returns root-level folders.",
+    ),
+    include_relations: bool = Query(
+        True,
+        description="Include agent and subfolder relations (for counts)",
+    ),
+) -> library_model.FolderListResponse:
+    """
+    List folders for the authenticated user.
+
+    Args:
+        user_id: ID of the authenticated user.
+        parent_id: Optional parent folder ID to filter by.
+        include_relations: Whether to include agent and subfolder relations for counts.
+
+    Returns:
+        A FolderListResponse containing folders.
+    """
+    folders = await library_db.list_folders(
+        user_id=user_id,
+        parent_id=parent_id,
+        include_relations=include_relations,
+    )
+    return library_model.FolderListResponse(
+        folders=folders,
+        pagination=library_model.Pagination(
+            total_items=len(folders),
+            total_pages=1,
+            current_page=1,
+            page_size=len(folders),
+        ),
+    )
+
+
+@router.get(
+    "/tree",
+    summary="Get Folder Tree",
+    response_model=library_model.FolderTreeResponse,
+    responses={
+        200: {"description": "Folder tree structure"},
+        500: {"description": "Server error"},
+    },
+)
+async def get_folder_tree(
+    user_id: str = Security(autogpt_auth_lib.get_user_id),
+) -> library_model.FolderTreeResponse:
+    """
+    Get the full folder tree for the authenticated user.
+
+    Args:
+        user_id: ID of the authenticated user.
+
+    Returns:
+        A FolderTreeResponse containing the nested folder structure.
+    """
+    tree = await library_db.get_folder_tree(user_id=user_id)
+    return library_model.FolderTreeResponse(tree=tree)
+
+
+@router.get(
+    "/{folder_id}",
+    summary="Get Folder",
+    response_model=library_model.LibraryFolder,
+    responses={
+        200: {"description": "Folder details"},
+        404: {"description": "Folder not found"},
+        500: {"description": "Server error"},
+    },
+)
+async def get_folder(
+    folder_id: str,
+    user_id: str = Security(autogpt_auth_lib.get_user_id),
+) -> library_model.LibraryFolder:
+    """
+    Get a specific folder.
+
+    Args:
+        folder_id: ID of the folder to retrieve.
+        user_id: ID of the authenticated user.
+
+    Returns:
+        The requested LibraryFolder.
+    """
+    return await library_db.get_folder(folder_id=folder_id, user_id=user_id)
+
+
+@router.post(
+    "",
+    summary="Create Folder",
+    status_code=status.HTTP_201_CREATED,
+    response_model=library_model.LibraryFolder,
+    responses={
+        201: {"description": "Folder created successfully"},
+        400: {"description": "Validation error"},
+        404: {"description": "Parent folder not found"},
+        409: {"description": "Folder name conflict"},
+        500: {"description": "Server error"},
+    },
+)
+async def create_folder(
+    payload: library_model.FolderCreateRequest,
+    user_id: str = Security(autogpt_auth_lib.get_user_id),
+) -> library_model.LibraryFolder:
+    """
+    Create a new folder.
+
+    Args:
+        payload: The folder creation request.
+        user_id: ID of the authenticated user.
+
+    Returns:
+        The created LibraryFolder.
+    """
+    return await library_db.create_folder(
+        user_id=user_id,
+        name=payload.name,
+        parent_id=payload.parent_id,
+        icon=payload.icon,
+        color=payload.color,
+    )
+
+
+@router.patch(
+    "/{folder_id}",
+    summary="Update Folder",
+    response_model=library_model.LibraryFolder,
+    responses={
+        200: {"description": "Folder updated successfully"},
+        400: {"description": "Validation error"},
+        404: {"description": "Folder not found"},
+        409: {"description": "Folder name conflict"},
+        500: {"description": "Server error"},
+    },
+)
+async def update_folder(
+    folder_id: str,
+    payload: library_model.FolderUpdateRequest,
+    user_id: str = Security(autogpt_auth_lib.get_user_id),
+) -> library_model.LibraryFolder:
+    """
+    Update a folder's properties.
+
+    Args:
+        folder_id: ID of the folder to update.
+        payload: The folder update request.
+        user_id: ID of the authenticated user.
+
+    Returns:
+        The updated LibraryFolder.
+    """
+    return await library_db.update_folder(
+        folder_id=folder_id,
+        user_id=user_id,
+        name=payload.name,
+        icon=payload.icon,
+        color=payload.color,
+    )
+
+
+@router.post(
+    "/{folder_id}/move",
+    summary="Move Folder",
+    response_model=library_model.LibraryFolder,
+    responses={
+        200: {"description": "Folder moved successfully"},
+        400: {"description": "Validation error (circular reference)"},
+        404: {"description": "Folder or target parent not found"},
+        409: {"description": "Folder name conflict in target location"},
+        500: {"description": "Server error"},
+    },
+)
+async def move_folder(
+    folder_id: str,
+    payload: library_model.FolderMoveRequest,
+    user_id: str = Security(autogpt_auth_lib.get_user_id),
+) -> library_model.LibraryFolder:
+    """
+    Move a folder to a new parent.
+
+    Args:
+        folder_id: ID of the folder to move.
+        payload: The move request with target parent.
+        user_id: ID of the authenticated user.
+
+    Returns:
+        The moved LibraryFolder.
+    """
+    return await library_db.move_folder(
+        folder_id=folder_id,
+        user_id=user_id,
+        target_parent_id=payload.target_parent_id,
+    )
+
+
+@router.delete(
+    "/{folder_id}",
+    summary="Delete Folder",
+    status_code=status.HTTP_204_NO_CONTENT,
+    responses={
+        204: {"description": "Folder deleted successfully"},
+        404: {"description": "Folder not found"},
+        500: {"description": "Server error"},
+    },
+)
+async def delete_folder(
+    folder_id: str,
+    user_id: str = Security(autogpt_auth_lib.get_user_id),
+) -> Response:
+    """
+    Soft-delete a folder and all its contents.
+
+    Args:
+        folder_id: ID of the folder to delete.
+        user_id: ID of the authenticated user.
+
+    Returns:
+        204 No Content if successful.
+    """
+    await library_db.delete_folder(
+        folder_id=folder_id,
+        user_id=user_id,
+        soft_delete=True,
+    )
+    return Response(status_code=status.HTTP_204_NO_CONTENT)
+
+
+# === Bulk Agent Operations ===
+
+
+@router.post(
+    "/agents/bulk-move",
+    summary="Bulk Move Agents",
+    response_model=list[library_model.LibraryAgent],
+    responses={
+        200: {"description": "Agents moved successfully"},
+        404: {"description": "Folder not found"},
+        500: {"description": "Server error"},
+    },
+)
+async def bulk_move_agents(
+    payload: library_model.BulkMoveAgentsRequest,
+    user_id: str = Security(autogpt_auth_lib.get_user_id),
+) -> list[library_model.LibraryAgent]:
+    """
+    Move multiple agents to a folder.
+
+    Args:
+        payload: The bulk move request with agent IDs and target folder.
+        user_id: ID of the authenticated user.
+
+    Returns:
+        The updated LibraryAgents.
+    """
+    return await library_db.bulk_move_agents_to_folder(
+        agent_ids=payload.agent_ids,
+        folder_id=payload.folder_id,
+        user_id=user_id,
+    )

autogpt_platform/backend/backend/api/features/library/routes_test.py

@@ -115,6 +115,8 @@ async def test_get_library_agents_success(
         sort_by=library_model.LibraryAgentSort.UPDATED_AT,
         page=1,
         page_size=15,
+        folder_id=None,
+        include_root_only=False,
     )
 
 

autogpt_platform/backend/backend/api/features/mcp/routes.py

@@ -0,0 +1,511 @@
+"""
+MCP (Model Context Protocol) API routes.
+
+Provides endpoints for MCP tool discovery and OAuth authentication so the
+frontend can list available tools on an MCP server before placing a block.
+"""
+
+import logging
+from typing import Annotated, Any
+
+import fastapi
+from autogpt_libs.auth import get_user_id
+from fastapi import Security
+from pydantic import BaseModel, Field, SecretStr
+
+from backend.api.features.integrations.router import CredentialsMetaResponse
+from backend.blocks.mcp.client import MCPClient, MCPClientError
+from backend.blocks.mcp.helpers import (
+    auto_lookup_mcp_credential,
+    normalize_mcp_url,
+    server_host,
+)
+from backend.blocks.mcp.oauth import MCPOAuthHandler
+from backend.data.model import OAuth2Credentials
+from backend.integrations.creds_manager import IntegrationCredentialsManager
+from backend.integrations.providers import ProviderName
+from backend.util.request import HTTPClientError, Requests, validate_url
+from backend.util.settings import Settings
+
+logger = logging.getLogger(__name__)
+
+settings = Settings()
+router = fastapi.APIRouter(tags=["mcp"])
+creds_manager = IntegrationCredentialsManager()
+
+
+# ====================== Tool Discovery ====================== #
+
+
+class DiscoverToolsRequest(BaseModel):
+    """Request to discover tools on an MCP server."""
+
+    server_url: str = Field(description="URL of the MCP server")
+    auth_token: str | None = Field(
+        default=None,
+        description="Optional Bearer token for authenticated MCP servers",
+    )
+
+
+class MCPToolResponse(BaseModel):
+    """A single MCP tool returned by discovery."""
+
+    name: str
+    description: str
+    input_schema: dict[str, Any]
+
+
+class DiscoverToolsResponse(BaseModel):
+    """Response containing the list of tools available on an MCP server."""
+
+    tools: list[MCPToolResponse]
+    server_name: str | None = None
+    protocol_version: str | None = None
+
+
+@router.post(
+    "/discover-tools",
+    summary="Discover available tools on an MCP server",
+    response_model=DiscoverToolsResponse,
+)
+async def discover_tools(
+    request: DiscoverToolsRequest,
+    user_id: Annotated[str, Security(get_user_id)],
+) -> DiscoverToolsResponse:
+    """
+    Connect to an MCP server and return its available tools.
+
+    If the user has a stored MCP credential for this server URL, it will be
+    used automatically — no need to pass an explicit auth token.
+    """
+    # Validate URL to prevent SSRF — blocks loopback and private IP ranges.
+    try:
+        await validate_url(request.server_url, trusted_origins=[])
+    except ValueError as e:
+        raise fastapi.HTTPException(status_code=400, detail=f"Invalid server URL: {e}")
+
+    auth_token = request.auth_token
+
+    # Auto-use stored MCP credential when no explicit token is provided.
+    if not auth_token:
+        best_cred = await auto_lookup_mcp_credential(
+            user_id, normalize_mcp_url(request.server_url)
+        )
+        if best_cred:
+            auth_token = best_cred.access_token.get_secret_value()
+
+    client = MCPClient(request.server_url, auth_token=auth_token)
+
+    try:
+        init_result = await client.initialize()
+        tools = await client.list_tools()
+    except HTTPClientError as e:
+        if e.status_code in (401, 403):
+            raise fastapi.HTTPException(
+                status_code=401,
+                detail="This MCP server requires authentication. "
+                "Please provide a valid auth token.",
+            )
+        raise fastapi.HTTPException(status_code=502, detail=str(e))
+    except MCPClientError as e:
+        raise fastapi.HTTPException(status_code=502, detail=str(e))
+    except Exception as e:
+        raise fastapi.HTTPException(
+            status_code=502,
+            detail=f"Failed to connect to MCP server: {e}",
+        )
+
+    return DiscoverToolsResponse(
+        tools=[
+            MCPToolResponse(
+                name=t.name,
+                description=t.description,
+                input_schema=t.input_schema,
+            )
+            for t in tools
+        ],
+        server_name=(
+            init_result.get("serverInfo", {}).get("name")
+            or server_host(request.server_url)
+            or "MCP"
+        ),
+        protocol_version=init_result.get("protocolVersion"),
+    )
+
+
+# ======================== OAuth Flow ======================== #
+
+
+class MCPOAuthLoginRequest(BaseModel):
+    """Request to start an OAuth flow for an MCP server."""
+
+    server_url: str = Field(description="URL of the MCP server that requires OAuth")
+
+
+class MCPOAuthLoginResponse(BaseModel):
+    """Response with the OAuth login URL for the user to authenticate."""
+
+    login_url: str
+    state_token: str
+
+
+@router.post(
+    "/oauth/login",
+    summary="Initiate OAuth login for an MCP server",
+)
+async def mcp_oauth_login(
+    request: MCPOAuthLoginRequest,
+    user_id: Annotated[str, Security(get_user_id)],
+) -> MCPOAuthLoginResponse:
+    """
+    Discover OAuth metadata from the MCP server and return a login URL.
+
+    1. Discovers the protected-resource metadata (RFC 9728)
+    2. Fetches the authorization server metadata (RFC 8414)
+    3. Performs Dynamic Client Registration (RFC 7591) if available
+    4. Returns the authorization URL for the frontend to open in a popup
+    """
+    # Validate URL to prevent SSRF — blocks loopback and private IP ranges.
+    try:
+        await validate_url(request.server_url, trusted_origins=[])
+    except ValueError as e:
+        raise fastapi.HTTPException(status_code=400, detail=f"Invalid server URL: {e}")
+
+    # Normalize the URL so that credentials stored here are matched consistently
+    # by auto_lookup_mcp_credential (which also uses normalized URLs).
+    server_url = normalize_mcp_url(request.server_url)
+    client = MCPClient(server_url)
+
+    # Step 1: Discover protected-resource metadata (RFC 9728)
+    protected_resource = await client.discover_auth()
+
+    metadata: dict[str, Any] | None = None
+
+    if protected_resource and protected_resource.get("authorization_servers"):
+        auth_server_url = protected_resource["authorization_servers"][0]
+        resource_url = protected_resource.get("resource", server_url)
+
+        # Validate the auth server URL from metadata to prevent SSRF.
+        try:
+            await validate_url(auth_server_url, trusted_origins=[])
+        except ValueError as e:
+            raise fastapi.HTTPException(
+                status_code=400,
+                detail=f"Invalid authorization server URL in metadata: {e}",
+            )
+
+        # Step 2a: Discover auth-server metadata (RFC 8414)
+        metadata = await client.discover_auth_server_metadata(auth_server_url)
+    else:
+        # Fallback: Some MCP servers (e.g. Linear) are their own auth server
+        # and serve OAuth metadata directly without protected-resource metadata.
+        # Don't assume a resource_url — omitting it lets the auth server choose
+        # the correct audience for the token (RFC 8707 resource is optional).
+        resource_url = None
+        metadata = await client.discover_auth_server_metadata(server_url)
+
+    if (
+        not metadata
+        or "authorization_endpoint" not in metadata
+        or "token_endpoint" not in metadata
+    ):
+        raise fastapi.HTTPException(
+            status_code=400,
+            detail="This MCP server does not advertise OAuth support. "
+            "You may need to provide an auth token manually.",
+        )
+
+    authorize_url = metadata["authorization_endpoint"]
+    token_url = metadata["token_endpoint"]
+    registration_endpoint = metadata.get("registration_endpoint")
+    revoke_url = metadata.get("revocation_endpoint")
+
+    # Step 3: Dynamic Client Registration (RFC 7591) if available
+    frontend_base_url = settings.config.frontend_base_url
+    if not frontend_base_url:
+        raise fastapi.HTTPException(
+            status_code=500,
+            detail="Frontend base URL is not configured.",
+        )
+    redirect_uri = f"{frontend_base_url}/auth/integrations/mcp_callback"
+
+    client_id = ""
+    client_secret = ""
+    if registration_endpoint:
+        # Validate the registration endpoint to prevent SSRF via metadata.
+        try:
+            await validate_url(registration_endpoint, trusted_origins=[])
+        except ValueError:
+            pass  # Skip registration, fall back to default client_id
+        else:
+            reg_result = await _register_mcp_client(
+                registration_endpoint, redirect_uri, server_url
+            )
+            if reg_result:
+                client_id = reg_result.get("client_id", "")
+                client_secret = reg_result.get("client_secret", "")
+
+    if not client_id:
+        client_id = "autogpt-platform"
+
+    # Step 4: Store state token with OAuth metadata for the callback
+    scopes = (protected_resource or {}).get("scopes_supported") or metadata.get(
+        "scopes_supported", []
+    )
+    state_token, code_challenge = await creds_manager.store.store_state_token(
+        user_id,
+        ProviderName.MCP.value,
+        scopes,
+        state_metadata={
+            "authorize_url": authorize_url,
+            "token_url": token_url,
+            "revoke_url": revoke_url,
+            "resource_url": resource_url,
+            "server_url": server_url,
+            "client_id": client_id,
+            "client_secret": client_secret,
+        },
+    )
+
+    # Step 5: Build and return the login URL
+    handler = MCPOAuthHandler(
+        client_id=client_id,
+        client_secret=client_secret,
+        redirect_uri=redirect_uri,
+        authorize_url=authorize_url,
+        token_url=token_url,
+        resource_url=resource_url,
+    )
+    login_url = handler.get_login_url(
+        scopes, state_token, code_challenge=code_challenge
+    )
+
+    return MCPOAuthLoginResponse(login_url=login_url, state_token=state_token)
+
+
+class MCPOAuthCallbackRequest(BaseModel):
+    """Request to exchange an OAuth code for tokens."""
+
+    code: str = Field(description="Authorization code from OAuth callback")
+    state_token: str = Field(description="State token for CSRF verification")
+
+
+class MCPOAuthCallbackResponse(BaseModel):
+    """Response after successfully storing OAuth credentials."""
+
+    credential_id: str
+
+
+@router.post(
+    "/oauth/callback",
+    summary="Exchange OAuth code for MCP tokens",
+)
+async def mcp_oauth_callback(
+    request: MCPOAuthCallbackRequest,
+    user_id: Annotated[str, Security(get_user_id)],
+) -> CredentialsMetaResponse:
+    """
+    Exchange the authorization code for tokens and store the credential.
+
+    The frontend calls this after receiving the OAuth code from the popup.
+    On success, subsequent ``/discover-tools`` calls for the same server URL
+    will automatically use the stored credential.
+    """
+    valid_state = await creds_manager.store.verify_state_token(
+        user_id, request.state_token, ProviderName.MCP.value
+    )
+    if not valid_state:
+        raise fastapi.HTTPException(
+            status_code=400,
+            detail="Invalid or expired state token.",
+        )
+
+    meta = valid_state.state_metadata
+    frontend_base_url = settings.config.frontend_base_url
+    if not frontend_base_url:
+        raise fastapi.HTTPException(
+            status_code=500,
+            detail="Frontend base URL is not configured.",
+        )
+    redirect_uri = f"{frontend_base_url}/auth/integrations/mcp_callback"
+
+    handler = MCPOAuthHandler(
+        client_id=meta["client_id"],
+        client_secret=meta.get("client_secret", ""),
+        redirect_uri=redirect_uri,
+        authorize_url=meta["authorize_url"],
+        token_url=meta["token_url"],
+        revoke_url=meta.get("revoke_url"),
+        resource_url=meta.get("resource_url"),
+    )
+
+    try:
+        credentials = await handler.exchange_code_for_tokens(
+            request.code, valid_state.scopes, valid_state.code_verifier
+        )
+    except Exception as e:
+        raise fastapi.HTTPException(
+            status_code=400,
+            detail=f"OAuth token exchange failed: {e}",
+        )
+
+    # Enrich credential metadata for future lookup and token refresh
+    if credentials.metadata is None:
+        credentials.metadata = {}
+    credentials.metadata["mcp_server_url"] = meta["server_url"]
+    credentials.metadata["mcp_client_id"] = meta["client_id"]
+    credentials.metadata["mcp_client_secret"] = meta.get("client_secret", "")
+    credentials.metadata["mcp_token_url"] = meta["token_url"]
+    credentials.metadata["mcp_resource_url"] = meta.get("resource_url", "")
+
+    hostname = server_host(meta["server_url"])
+    credentials.title = f"MCP: {hostname}"
+
+    # Remove old MCP credentials for the same server to prevent stale token buildup.
+    try:
+        old_creds = await creds_manager.store.get_creds_by_provider(
+            user_id, ProviderName.MCP.value
+        )
+        for old in old_creds:
+            if (
+                isinstance(old, OAuth2Credentials)
+                and (old.metadata or {}).get("mcp_server_url") == meta["server_url"]
+            ):
+                await creds_manager.store.delete_creds_by_id(user_id, old.id)
+                logger.info(
+                    "Removed old MCP credential %s for %s",
+                    old.id,
+                    server_host(meta["server_url"]),
+                )
+    except Exception:
+        logger.debug("Could not clean up old MCP credentials", exc_info=True)
+
+    await creds_manager.create(user_id, credentials)
+
+    return CredentialsMetaResponse(
+        id=credentials.id,
+        provider=credentials.provider,
+        type=credentials.type,
+        title=credentials.title,
+        scopes=credentials.scopes,
+        username=credentials.username,
+        host=credentials.metadata.get("mcp_server_url"),
+    )
+
+
+# ======================== Bearer Token ======================== #
+
+
+class MCPStoreTokenRequest(BaseModel):
+    """Request to store a bearer token for an MCP server that doesn't support OAuth."""
+
+    server_url: str = Field(
+        description="MCP server URL the token authenticates against"
+    )
+    token: SecretStr = Field(
+        min_length=1, description="Bearer token / API key for the MCP server"
+    )
+
+
+@router.post(
+    "/token",
+    summary="Store a bearer token for an MCP server",
+)
+async def mcp_store_token(
+    request: MCPStoreTokenRequest,
+    user_id: Annotated[str, Security(get_user_id)],
+) -> CredentialsMetaResponse:
+    """
+    Store a manually provided bearer token as an MCP credential.
+
+    Used by the Copilot MCPSetupCard when the server doesn't support the MCP
+    OAuth discovery flow (returns 400 from /oauth/login).  Subsequent
+    ``run_mcp_tool`` calls will automatically pick up the token via
+    ``_auto_lookup_credential``.
+    """
+    token = request.token.get_secret_value().strip()
+    if not token:
+        raise fastapi.HTTPException(status_code=422, detail="Token must not be blank.")
+
+    # Validate URL to prevent SSRF — blocks loopback and private IP ranges.
+    try:
+        await validate_url(request.server_url, trusted_origins=[])
+    except ValueError as e:
+        raise fastapi.HTTPException(status_code=400, detail=f"Invalid server URL: {e}")
+
+    # Normalize URL so trailing-slash variants match existing credentials.
+    server_url = normalize_mcp_url(request.server_url)
+    hostname = server_host(server_url)
+
+    # Collect IDs of old credentials to clean up after successful create.
+    old_cred_ids: list[str] = []
+    try:
+        old_creds = await creds_manager.store.get_creds_by_provider(
+            user_id, ProviderName.MCP.value
+        )
+        old_cred_ids = [
+            old.id
+            for old in old_creds
+            if isinstance(old, OAuth2Credentials)
+            and normalize_mcp_url((old.metadata or {}).get("mcp_server_url", ""))
+            == server_url
+        ]
+    except Exception:
+        logger.debug("Could not query old MCP token credentials", exc_info=True)
+
+    credentials = OAuth2Credentials(
+        provider=ProviderName.MCP.value,
+        title=f"MCP: {hostname}",
+        access_token=SecretStr(token),
+        scopes=[],
+        metadata={"mcp_server_url": server_url},
+    )
+    await creds_manager.create(user_id, credentials)
+
+    # Only delete old credentials after the new one is safely stored.
+    for old_id in old_cred_ids:
+        try:
+            await creds_manager.store.delete_creds_by_id(user_id, old_id)
+        except Exception:
+            logger.debug("Could not clean up old MCP token credential", exc_info=True)
+
+    return CredentialsMetaResponse(
+        id=credentials.id,
+        provider=credentials.provider,
+        type=credentials.type,
+        title=credentials.title,
+        scopes=credentials.scopes,
+        username=credentials.username,
+        host=hostname,
+    )
+
+
+# ======================== Helpers ======================== #
+
+
+async def _register_mcp_client(
+    registration_endpoint: str,
+    redirect_uri: str,
+    server_url: str,
+) -> dict[str, Any] | None:
+    """Attempt Dynamic Client Registration (RFC 7591) with an MCP auth server."""
+    try:
+        response = await Requests(raise_for_status=True).post(
+            registration_endpoint,
+            json={
+                "client_name": "AutoGPT Platform",
+                "redirect_uris": [redirect_uri],
+                "grant_types": ["authorization_code"],
+                "response_types": ["code"],
+                "token_endpoint_auth_method": "client_secret_post",
+            },
+        )
+        data = response.json()
+        if isinstance(data, dict) and "client_id" in data:
+            return data
+        return None
+    except Exception as e:
+        logger.warning(
+            "Dynamic client registration failed for %s: %s", server_host(server_url), e
+        )
+        return None

autogpt_platform/backend/backend/api/features/mcp/test_routes.py

@@ -0,0 +1,572 @@
+"""Tests for MCP API routes.
+
+Uses httpx.AsyncClient with ASGITransport instead of fastapi.testclient.TestClient
+to avoid creating blocking portals that can corrupt pytest-asyncio's session event loop.
+"""
+
+from unittest.mock import AsyncMock, patch
+
+import fastapi
+import httpx
+import pytest
+import pytest_asyncio
+from autogpt_libs.auth import get_user_id
+from pydantic import SecretStr
+
+from backend.api.features.mcp.routes import router
+from backend.blocks.mcp.client import MCPClientError, MCPTool
+from backend.data.model import OAuth2Credentials
+from backend.util.request import HTTPClientError
+
+app = fastapi.FastAPI()
+app.include_router(router)
+app.dependency_overrides[get_user_id] = lambda: "test-user-id"
+
+
+@pytest_asyncio.fixture(scope="module")
+async def client():
+    transport = httpx.ASGITransport(app=app)
+    async with httpx.AsyncClient(transport=transport, base_url="http://test") as c:
+        yield c
+
+
+@pytest.fixture(autouse=True)
+def _bypass_ssrf_validation():
+    """Bypass validate_url in all route tests (test URLs don't resolve)."""
+    with patch(
+        "backend.api.features.mcp.routes.validate_url",
+        new_callable=AsyncMock,
+    ):
+        yield
+
+
+class TestDiscoverTools:
+    @pytest.mark.asyncio(loop_scope="session")
+    async def test_discover_tools_success(self, client):
+        mock_tools = [
+            MCPTool(
+                name="get_weather",
+                description="Get weather for a city",
+                input_schema={
+                    "type": "object",
+                    "properties": {"city": {"type": "string"}},
+                    "required": ["city"],
+                },
+            ),
+            MCPTool(
+                name="add_numbers",
+                description="Add two numbers",
+                input_schema={
+                    "type": "object",
+                    "properties": {
+                        "a": {"type": "number"},
+                        "b": {"type": "number"},
+                    },
+                },
+            ),
+        ]
+
+        with (
+            patch("backend.api.features.mcp.routes.MCPClient") as MockClient,
+            patch(
+                "backend.api.features.mcp.routes.auto_lookup_mcp_credential",
+                new_callable=AsyncMock,
+                return_value=None,
+            ),
+        ):
+            instance = MockClient.return_value
+            instance.initialize = AsyncMock(
+                return_value={
+                    "protocolVersion": "2025-03-26",
+                    "serverInfo": {"name": "test-server"},
+                }
+            )
+            instance.list_tools = AsyncMock(return_value=mock_tools)
+
+            response = await client.post(
+                "/discover-tools",
+                json={"server_url": "https://mcp.example.com/mcp"},
+            )
+
+        assert response.status_code == 200
+        data = response.json()
+        assert len(data["tools"]) == 2
+        assert data["tools"][0]["name"] == "get_weather"
+        assert data["tools"][1]["name"] == "add_numbers"
+        assert data["server_name"] == "test-server"
+        assert data["protocol_version"] == "2025-03-26"
+
+    @pytest.mark.asyncio(loop_scope="session")
+    async def test_discover_tools_with_auth_token(self, client):
+        with patch("backend.api.features.mcp.routes.MCPClient") as MockClient:
+            instance = MockClient.return_value
+            instance.initialize = AsyncMock(
+                return_value={"serverInfo": {}, "protocolVersion": "2025-03-26"}
+            )
+            instance.list_tools = AsyncMock(return_value=[])
+
+            response = await client.post(
+                "/discover-tools",
+                json={
+                    "server_url": "https://mcp.example.com/mcp",
+                    "auth_token": "my-secret-token",
+                },
+            )
+
+        assert response.status_code == 200
+        MockClient.assert_called_once_with(
+            "https://mcp.example.com/mcp",
+            auth_token="my-secret-token",
+        )
+
+    @pytest.mark.asyncio(loop_scope="session")
+    async def test_discover_tools_auto_uses_stored_credential(self, client):
+        """When no explicit token is given, stored MCP credentials are used."""
+        stored_cred = OAuth2Credentials(
+            provider="mcp",
+            title="MCP: example.com",
+            access_token=SecretStr("stored-token-123"),
+            refresh_token=None,
+            access_token_expires_at=None,
+            refresh_token_expires_at=None,
+            scopes=[],
+            metadata={"mcp_server_url": "https://mcp.example.com/mcp"},
+        )
+
+        with (
+            patch("backend.api.features.mcp.routes.MCPClient") as MockClient,
+            patch(
+                "backend.api.features.mcp.routes.auto_lookup_mcp_credential",
+                new_callable=AsyncMock,
+                return_value=stored_cred,
+            ),
+        ):
+            instance = MockClient.return_value
+            instance.initialize = AsyncMock(
+                return_value={"serverInfo": {}, "protocolVersion": "2025-03-26"}
+            )
+            instance.list_tools = AsyncMock(return_value=[])
+
+            response = await client.post(
+                "/discover-tools",
+                json={"server_url": "https://mcp.example.com/mcp"},
+            )
+
+        assert response.status_code == 200
+        MockClient.assert_called_once_with(
+            "https://mcp.example.com/mcp",
+            auth_token="stored-token-123",
+        )
+
+    @pytest.mark.asyncio(loop_scope="session")
+    async def test_discover_tools_mcp_error(self, client):
+        with (
+            patch("backend.api.features.mcp.routes.MCPClient") as MockClient,
+            patch(
+                "backend.api.features.mcp.routes.auto_lookup_mcp_credential",
+                new_callable=AsyncMock,
+                return_value=None,
+            ),
+        ):
+            instance = MockClient.return_value
+            instance.initialize = AsyncMock(
+                side_effect=MCPClientError("Connection refused")
+            )
+
+            response = await client.post(
+                "/discover-tools",
+                json={"server_url": "https://bad-server.example.com/mcp"},
+            )
+
+        assert response.status_code == 502
+        assert "Connection refused" in response.json()["detail"]
+
+    @pytest.mark.asyncio(loop_scope="session")
+    async def test_discover_tools_generic_error(self, client):
+        with (
+            patch("backend.api.features.mcp.routes.MCPClient") as MockClient,
+            patch(
+                "backend.api.features.mcp.routes.auto_lookup_mcp_credential",
+                new_callable=AsyncMock,
+                return_value=None,
+            ),
+        ):
+            instance = MockClient.return_value
+            instance.initialize = AsyncMock(side_effect=Exception("Network timeout"))
+
+            response = await client.post(
+                "/discover-tools",
+                json={"server_url": "https://timeout.example.com/mcp"},
+            )
+
+        assert response.status_code == 502
+        assert "Failed to connect" in response.json()["detail"]
+
+    @pytest.mark.asyncio(loop_scope="session")
+    async def test_discover_tools_auth_required(self, client):
+        with (
+            patch("backend.api.features.mcp.routes.MCPClient") as MockClient,
+            patch(
+                "backend.api.features.mcp.routes.auto_lookup_mcp_credential",
+                new_callable=AsyncMock,
+                return_value=None,
+            ),
+        ):
+            instance = MockClient.return_value
+            instance.initialize = AsyncMock(
+                side_effect=HTTPClientError("HTTP 401 Error: Unauthorized", 401)
+            )
+
+            response = await client.post(
+                "/discover-tools",
+                json={"server_url": "https://auth-server.example.com/mcp"},
+            )
+
+        assert response.status_code == 401
+        assert "requires authentication" in response.json()["detail"]
+
+    @pytest.mark.asyncio(loop_scope="session")
+    async def test_discover_tools_forbidden(self, client):
+        with (
+            patch("backend.api.features.mcp.routes.MCPClient") as MockClient,
+            patch(
+                "backend.api.features.mcp.routes.auto_lookup_mcp_credential",
+                new_callable=AsyncMock,
+                return_value=None,
+            ),
+        ):
+            instance = MockClient.return_value
+            instance.initialize = AsyncMock(
+                side_effect=HTTPClientError("HTTP 403 Error: Forbidden", 403)
+            )
+
+            response = await client.post(
+                "/discover-tools",
+                json={"server_url": "https://auth-server.example.com/mcp"},
+            )
+
+        assert response.status_code == 401
+        assert "requires authentication" in response.json()["detail"]
+
+    @pytest.mark.asyncio(loop_scope="session")
+    async def test_discover_tools_missing_url(self, client):
+        response = await client.post("/discover-tools", json={})
+        assert response.status_code == 422
+
+
+class TestOAuthLogin:
+    @pytest.mark.asyncio(loop_scope="session")
+    async def test_oauth_login_success(self, client):
+        with (
+            patch("backend.api.features.mcp.routes.MCPClient") as MockClient,
+            patch("backend.api.features.mcp.routes.creds_manager") as mock_cm,
+            patch("backend.api.features.mcp.routes.settings") as mock_settings,
+            patch(
+                "backend.api.features.mcp.routes._register_mcp_client"
+            ) as mock_register,
+        ):
+            instance = MockClient.return_value
+            instance.discover_auth = AsyncMock(
+                return_value={
+                    "authorization_servers": ["https://auth.sentry.io"],
+                    "resource": "https://mcp.sentry.dev/mcp",
+                    "scopes_supported": ["openid"],
+                }
+            )
+            instance.discover_auth_server_metadata = AsyncMock(
+                return_value={
+                    "authorization_endpoint": "https://auth.sentry.io/authorize",
+                    "token_endpoint": "https://auth.sentry.io/token",
+                    "registration_endpoint": "https://auth.sentry.io/register",
+                }
+            )
+            mock_register.return_value = {
+                "client_id": "registered-client-id",
+                "client_secret": "registered-secret",
+            }
+            mock_cm.store.store_state_token = AsyncMock(
+                return_value=("state-token-123", "code-challenge-abc")
+            )
+            mock_settings.config.frontend_base_url = "http://localhost:3000"
+
+            response = await client.post(
+                "/oauth/login",
+                json={"server_url": "https://mcp.sentry.dev/mcp"},
+            )
+
+        assert response.status_code == 200
+        data = response.json()
+        assert "login_url" in data
+        assert data["state_token"] == "state-token-123"
+        assert "auth.sentry.io/authorize" in data["login_url"]
+        assert "registered-client-id" in data["login_url"]
+
+    @pytest.mark.asyncio(loop_scope="session")
+    async def test_oauth_login_no_oauth_support(self, client):
+        with patch("backend.api.features.mcp.routes.MCPClient") as MockClient:
+            instance = MockClient.return_value
+            instance.discover_auth = AsyncMock(return_value=None)
+            instance.discover_auth_server_metadata = AsyncMock(return_value=None)
+
+            response = await client.post(
+                "/oauth/login",
+                json={"server_url": "https://simple-server.example.com/mcp"},
+            )
+
+        assert response.status_code == 400
+        assert "does not advertise OAuth" in response.json()["detail"]
+
+    @pytest.mark.asyncio(loop_scope="session")
+    async def test_oauth_login_fallback_to_public_client(self, client):
+        """When DCR is unavailable, falls back to default public client ID."""
+        with (
+            patch("backend.api.features.mcp.routes.MCPClient") as MockClient,
+            patch("backend.api.features.mcp.routes.creds_manager") as mock_cm,
+            patch("backend.api.features.mcp.routes.settings") as mock_settings,
+        ):
+            instance = MockClient.return_value
+            instance.discover_auth = AsyncMock(
+                return_value={
+                    "authorization_servers": ["https://auth.example.com"],
+                    "resource": "https://mcp.example.com/mcp",
+                }
+            )
+            instance.discover_auth_server_metadata = AsyncMock(
+                return_value={
+                    "authorization_endpoint": "https://auth.example.com/authorize",
+                    "token_endpoint": "https://auth.example.com/token",
+                    # No registration_endpoint
+                }
+            )
+            mock_cm.store.store_state_token = AsyncMock(
+                return_value=("state-abc", "challenge-xyz")
+            )
+            mock_settings.config.frontend_base_url = "http://localhost:3000"
+
+            response = await client.post(
+                "/oauth/login",
+                json={"server_url": "https://mcp.example.com/mcp"},
+            )
+
+        assert response.status_code == 200
+        data = response.json()
+        assert "autogpt-platform" in data["login_url"]
+
+
+class TestOAuthCallback:
+    @pytest.mark.asyncio(loop_scope="session")
+    async def test_oauth_callback_success(self, client):
+        mock_creds = OAuth2Credentials(
+            provider="mcp",
+            title=None,
+            access_token=SecretStr("access-token-xyz"),
+            refresh_token=None,
+            access_token_expires_at=None,
+            refresh_token_expires_at=None,
+            scopes=[],
+            metadata={
+                "mcp_token_url": "https://auth.sentry.io/token",
+                "mcp_resource_url": "https://mcp.sentry.dev/mcp",
+            },
+        )
+
+        with (
+            patch("backend.api.features.mcp.routes.creds_manager") as mock_cm,
+            patch("backend.api.features.mcp.routes.settings") as mock_settings,
+            patch("backend.api.features.mcp.routes.MCPOAuthHandler") as MockHandler,
+        ):
+            mock_settings.config.frontend_base_url = "http://localhost:3000"
+
+            # Mock state verification
+            mock_state = AsyncMock()
+            mock_state.state_metadata = {
+                "authorize_url": "https://auth.sentry.io/authorize",
+                "token_url": "https://auth.sentry.io/token",
+                "client_id": "test-client-id",
+                "client_secret": "test-secret",
+                "server_url": "https://mcp.sentry.dev/mcp",
+            }
+            mock_state.scopes = ["openid"]
+            mock_state.code_verifier = "verifier-123"
+            mock_cm.store.verify_state_token = AsyncMock(return_value=mock_state)
+            mock_cm.create = AsyncMock()
+
+            handler_instance = MockHandler.return_value
+            handler_instance.exchange_code_for_tokens = AsyncMock(
+                return_value=mock_creds
+            )
+
+            # Mock old credential cleanup
+            mock_cm.store.get_creds_by_provider = AsyncMock(return_value=[])
+
+            response = await client.post(
+                "/oauth/callback",
+                json={"code": "auth-code-abc", "state_token": "state-token-123"},
+            )
+
+        assert response.status_code == 200
+        data = response.json()
+        assert "id" in data
+        assert data["provider"] == "mcp"
+        assert data["type"] == "oauth2"
+        mock_cm.create.assert_called_once()
+
+    @pytest.mark.asyncio(loop_scope="session")
+    async def test_oauth_callback_invalid_state(self, client):
+        with patch("backend.api.features.mcp.routes.creds_manager") as mock_cm:
+            mock_cm.store.verify_state_token = AsyncMock(return_value=None)
+
+            response = await client.post(
+                "/oauth/callback",
+                json={"code": "auth-code", "state_token": "bad-state"},
+            )
+
+        assert response.status_code == 400
+        assert "Invalid or expired" in response.json()["detail"]
+
+    @pytest.mark.asyncio(loop_scope="session")
+    async def test_oauth_callback_token_exchange_fails(self, client):
+        with (
+            patch("backend.api.features.mcp.routes.creds_manager") as mock_cm,
+            patch("backend.api.features.mcp.routes.settings") as mock_settings,
+            patch("backend.api.features.mcp.routes.MCPOAuthHandler") as MockHandler,
+        ):
+            mock_settings.config.frontend_base_url = "http://localhost:3000"
+            mock_state = AsyncMock()
+            mock_state.state_metadata = {
+                "authorize_url": "https://auth.example.com/authorize",
+                "token_url": "https://auth.example.com/token",
+                "client_id": "cid",
+                "server_url": "https://mcp.example.com/mcp",
+            }
+            mock_state.scopes = []
+            mock_state.code_verifier = "v"
+            mock_cm.store.verify_state_token = AsyncMock(return_value=mock_state)
+
+            handler_instance = MockHandler.return_value
+            handler_instance.exchange_code_for_tokens = AsyncMock(
+                side_effect=RuntimeError("Token exchange failed")
+            )
+
+            response = await client.post(
+                "/oauth/callback",
+                json={"code": "bad-code", "state_token": "state"},
+            )
+
+        assert response.status_code == 400
+        assert "token exchange failed" in response.json()["detail"].lower()
+
+
+class TestStoreToken:
+    @pytest.mark.asyncio(loop_scope="session")
+    async def test_store_token_success(self, client):
+        with patch("backend.api.features.mcp.routes.creds_manager") as mock_cm:
+            mock_cm.store.get_creds_by_provider = AsyncMock(return_value=[])
+            mock_cm.create = AsyncMock()
+
+            response = await client.post(
+                "/token",
+                json={
+                    "server_url": "https://mcp.example.com/mcp",
+                    "token": "my-api-key-123",
+                },
+            )
+
+        assert response.status_code == 200
+        data = response.json()
+        assert data["provider"] == "mcp"
+        assert data["type"] == "oauth2"
+        assert data["host"] == "mcp.example.com"
+        mock_cm.create.assert_called_once()
+
+    @pytest.mark.asyncio(loop_scope="session")
+    async def test_store_token_blank_rejected(self, client):
+        """Blank token string (after stripping) should return 422."""
+        response = await client.post(
+            "/token",
+            json={
+                "server_url": "https://mcp.example.com/mcp",
+                "token": "   ",
+            },
+        )
+        # Pydantic min_length=1 catches the whitespace-only token
+        assert response.status_code == 422
+
+    @pytest.mark.asyncio(loop_scope="session")
+    async def test_store_token_replaces_old_credential(self, client):
+        old_cred = OAuth2Credentials(
+            provider="mcp",
+            title="MCP: mcp.example.com",
+            access_token=SecretStr("old-token"),
+            scopes=[],
+            metadata={"mcp_server_url": "https://mcp.example.com/mcp"},
+        )
+        with patch("backend.api.features.mcp.routes.creds_manager") as mock_cm:
+            mock_cm.store.get_creds_by_provider = AsyncMock(return_value=[old_cred])
+            mock_cm.create = AsyncMock()
+            mock_cm.store.delete_creds_by_id = AsyncMock()
+
+            response = await client.post(
+                "/token",
+                json={
+                    "server_url": "https://mcp.example.com/mcp",
+                    "token": "new-token",
+                },
+            )
+
+        assert response.status_code == 200
+        mock_cm.store.delete_creds_by_id.assert_called_once_with(
+            "test-user-id", old_cred.id
+        )
+
+
+class TestSSRFValidation:
+    """Verify that validate_url is enforced on all endpoints."""
+
+    @pytest.mark.asyncio(loop_scope="session")
+    async def test_discover_tools_ssrf_blocked(self, client):
+        with patch(
+            "backend.api.features.mcp.routes.validate_url",
+            new_callable=AsyncMock,
+            side_effect=ValueError("blocked loopback"),
+        ):
+            response = await client.post(
+                "/discover-tools",
+                json={"server_url": "http://localhost/mcp"},
+            )
+
+        assert response.status_code == 400
+        assert "blocked loopback" in response.json()["detail"].lower()
+
+    @pytest.mark.asyncio(loop_scope="session")
+    async def test_oauth_login_ssrf_blocked(self, client):
+        with patch(
+            "backend.api.features.mcp.routes.validate_url",
+            new_callable=AsyncMock,
+            side_effect=ValueError("blocked private IP"),
+        ):
+            response = await client.post(
+                "/oauth/login",
+                json={"server_url": "http://10.0.0.1/mcp"},
+            )
+
+        assert response.status_code == 400
+        assert "blocked private ip" in response.json()["detail"].lower()
+
+    @pytest.mark.asyncio(loop_scope="session")
+    async def test_store_token_ssrf_blocked(self, client):
+        with patch(
+            "backend.api.features.mcp.routes.validate_url",
+            new_callable=AsyncMock,
+            side_effect=ValueError("blocked loopback"),
+        ):
+            response = await client.post(
+                "/token",
+                json={
+                    "server_url": "http://127.0.0.1/mcp",
+                    "token": "some-token",
+                },
+            )
+
+        assert response.status_code == 400
+        assert "blocked loopback" in response.json()["detail"].lower()

autogpt_platform/backend/backend/api/features/store/content_handlers.py

@@ -9,15 +9,26 @@ import logging
 from abc import ABC, abstractmethod
 from dataclasses import dataclass
 from pathlib import Path
-from typing import Any
+from typing import Any, get_args, get_origin
 
 from prisma.enums import ContentType
 
+from backend.blocks.llm import LlmModel
 from backend.data.db import query_raw_with_schema
 
 logger = logging.getLogger(__name__)
 
 
+def _contains_type(annotation: Any, target: type) -> bool:
+    """Check if an annotation is or contains the target type (handles Optional/Union/Annotated)."""
+    if annotation is target:
+        return True
+    origin = get_origin(annotation)
+    if origin is None:
+        return False
+    return any(_contains_type(arg, target) for arg in get_args(annotation))
+
+
 @dataclass
 class ContentItem:
     """Represents a piece of content to be embedded."""
@@ -188,45 +199,51 @@ class BlockHandler(ContentHandler):
             try:
                 block_instance = block_cls()
 
-                # Skip disabled blocks - they shouldn't be indexed
                 if block_instance.disabled:
                     continue
 
                 # Build searchable text from block metadata
                 parts = []
-                if hasattr(block_instance, "name") and block_instance.name:
+                if block_instance.name:
                     parts.append(block_instance.name)
-                if (
-                    hasattr(block_instance, "description")
-                    and block_instance.description
-                ):
+                if block_instance.description:
                     parts.append(block_instance.description)
-                if hasattr(block_instance, "categories") and block_instance.categories:
-                    # Convert BlockCategory enum to strings
+                if block_instance.categories:
                     parts.append(
                         " ".join(str(cat.value) for cat in block_instance.categories)
                     )
 
-                # Add input/output schema info
-                if hasattr(block_instance, "input_schema"):
-                    schema = block_instance.input_schema
-                    if hasattr(schema, "model_json_schema"):
-                        schema_dict = schema.model_json_schema()
-                        if "properties" in schema_dict:
-                            for prop_name, prop_info in schema_dict[
-                                "properties"
-                            ].items():
-                                if "description" in prop_info:
-                                    parts.append(
-                                        f"{prop_name}: {prop_info['description']}"
-                                    )
+                # Add input schema field descriptions
+                block_input_fields = block_instance.input_schema.model_fields
+                parts += [
+                    f"{field_name}: {field_info.description}"
+                    for field_name, field_info in block_input_fields.items()
+                    if field_info.description
+                ]
 
                 searchable_text = " ".join(parts)
 
-                # Convert categories set of enums to list of strings for JSON serialization
-                categories = getattr(block_instance, "categories", set())
                 categories_list = (
-                    [cat.value for cat in categories] if categories else []
+                    [cat.value for cat in block_instance.categories]
+                    if block_instance.categories
+                    else []
+                )
+
+                # Extract provider names from credentials fields
+                credentials_info = (
+                    block_instance.input_schema.get_credentials_fields_info()
+                )
+                is_integration = len(credentials_info) > 0
+                provider_names = [
+                    provider.value.lower()
+                    for info in credentials_info.values()
+                    for provider in info.provider
+                ]
+
+                # Check if block has LlmModel field in input schema
+                has_llm_model_field = any(
+                    _contains_type(field.annotation, LlmModel)
+                    for field in block_instance.input_schema.model_fields.values()
                 )
 
                 items.append(
@@ -235,8 +252,11 @@ class BlockHandler(ContentHandler):
                         content_type=ContentType.BLOCK,
                         searchable_text=searchable_text,
                         metadata={
-                            "name": getattr(block_instance, "name", ""),
+                            "name": block_instance.name,
                             "categories": categories_list,
+                            "providers": provider_names,
+                            "has_llm_model_field": has_llm_model_field,
+                            "is_integration": is_integration,
                         },
                         user_id=None,  # Blocks are public
                     )

autogpt_platform/backend/backend/api/features/store/content_handlers_test.py

@@ -82,9 +82,10 @@ async def test_block_handler_get_missing_items(mocker):
     mock_block_instance.description = "Performs calculations"
     mock_block_instance.categories = [MagicMock(value="MATH")]
     mock_block_instance.disabled = False
-    mock_block_instance.input_schema.model_json_schema.return_value = {
-        "properties": {"expression": {"description": "Math expression to evaluate"}}
-    }
+    mock_field = MagicMock()
+    mock_field.description = "Math expression to evaluate"
+    mock_block_instance.input_schema.model_fields = {"expression": mock_field}
+    mock_block_instance.input_schema.get_credentials_fields_info.return_value = {}
     mock_block_class.return_value = mock_block_instance
 
     mock_blocks = {"block-uuid-1": mock_block_class}
@@ -309,19 +310,19 @@ async def test_content_handlers_registry():
 
 
 @pytest.mark.asyncio(loop_scope="session")
-async def test_block_handler_handles_missing_attributes():
-    """Test BlockHandler gracefully handles blocks with missing attributes."""
+async def test_block_handler_handles_empty_attributes():
+    """Test BlockHandler handles blocks with empty/falsy attribute values."""
     handler = BlockHandler()
 
-    # Mock block with minimal attributes
+    # Mock block with empty values (all attributes exist but are falsy)
     mock_block_class = MagicMock()
     mock_block_instance = MagicMock()
     mock_block_instance.name = "Minimal Block"
     mock_block_instance.disabled = False
-    # No description, categories, or schema
-    del mock_block_instance.description
-    del mock_block_instance.categories
-    del mock_block_instance.input_schema
+    mock_block_instance.description = ""
+    mock_block_instance.categories = set()
+    mock_block_instance.input_schema.model_fields = {}
+    mock_block_instance.input_schema.get_credentials_fields_info.return_value = {}
     mock_block_class.return_value = mock_block_instance
 
     mock_blocks = {"block-minimal": mock_block_class}
@@ -352,6 +353,8 @@ async def test_block_handler_skips_failed_blocks():
     good_instance.description = "Works fine"
     good_instance.categories = []
     good_instance.disabled = False
+    good_instance.input_schema.model_fields = {}
+    good_instance.input_schema.get_credentials_fields_info.return_value = {}
     good_block.return_value = good_instance
 
     bad_block = MagicMock()

autogpt_platform/backend/backend/api/features/v1.py

@@ -126,6 +126,9 @@ v1_router = APIRouter()
 ########################################################
 
 
+_tally_background_tasks: set[asyncio.Task] = set()
+
+
 @v1_router.post(
     "/auth/user",
     summary="Get or create user",
@@ -134,6 +137,24 @@ v1_router = APIRouter()
 )
 async def get_or_create_user_route(user_data: dict = Security(get_jwt_payload)):
     user = await get_or_create_user(user_data)
+
+    # Fire-and-forget: populate business understanding from Tally form.
+    # We use created_at proximity instead of an is_new flag because
+    # get_or_create_user is cached — a separate is_new return value would be
+    # unreliable on repeated calls within the cache TTL.
+    age_seconds = (datetime.now(timezone.utc) - user.created_at).total_seconds()
+    if age_seconds < 30:
+        try:
+            from backend.data.tally import populate_understanding_from_tally
+
+            task = asyncio.create_task(
+                populate_understanding_from_tally(user.id, user.email)
+            )
+            _tally_background_tasks.add(task)
+            task.add_done_callback(_tally_background_tasks.discard)
+        except Exception:
+            logger.debug("Failed to start Tally population task", exc_info=True)
+
     return user.model_dump()
 
 

autogpt_platform/backend/backend/api/features/v1_test.py

@@ -1,5 +1,5 @@
 import json
-from datetime import datetime
+from datetime import datetime, timezone
 from io import BytesIO
 from unittest.mock import AsyncMock, Mock, patch
 
@@ -43,6 +43,7 @@ def test_get_or_create_user_route(
 ) -> None:
     """Test get or create user endpoint"""
     mock_user = Mock()
+    mock_user.created_at = datetime.now(timezone.utc)
     mock_user.model_dump.return_value = {
         "id": test_user_id,
         "email": "test@example.com",

autogpt_platform/backend/backend/api/features/workspace/routes.py

@@ -3,15 +3,29 @@ Workspace API routes for managing user file storage.
 """
 
 import logging
+import os
 import re
 from typing import Annotated
 from urllib.parse import quote
 
 import fastapi
 from autogpt_libs.auth.dependencies import get_user_id, requires_user
+from fastapi import Query, UploadFile
 from fastapi.responses import Response
+from pydantic import BaseModel
 
-from backend.data.workspace import get_workspace, get_workspace_file
+from backend.data.workspace import (
+    WorkspaceFile,
+    count_workspace_files,
+    get_or_create_workspace,
+    get_workspace,
+    get_workspace_file,
+    get_workspace_total_size,
+    soft_delete_workspace_file,
+)
+from backend.util.settings import Config
+from backend.util.virus_scanner import scan_content_safe
+from backend.util.workspace import WorkspaceManager
 from backend.util.workspace_storage import get_workspace_storage
 
 
@@ -44,11 +58,11 @@ router = fastapi.APIRouter(
 )
 
 
-def _create_streaming_response(content: bytes, file) -> Response:
+def _create_streaming_response(content: bytes, file: WorkspaceFile) -> Response:
     """Create a streaming response for file content."""
     return Response(
         content=content,
-        media_type=file.mimeType,
+        media_type=file.mime_type,
         headers={
             "Content-Disposition": _sanitize_filename_for_header(file.name),
             "Content-Length": str(len(content)),
@@ -56,7 +70,7 @@ def _create_streaming_response(content: bytes, file) -> Response:
     )
 
 
-async def _create_file_download_response(file) -> Response:
+async def _create_file_download_response(file: WorkspaceFile) -> Response:
     """
     Create a download response for a workspace file.
 
@@ -66,38 +80,57 @@ async def _create_file_download_response(file) -> Response:
     storage = await get_workspace_storage()
 
     # For local storage, stream the file directly
-    if file.storagePath.startswith("local://"):
-        content = await storage.retrieve(file.storagePath)
+    if file.storage_path.startswith("local://"):
+        content = await storage.retrieve(file.storage_path)
         return _create_streaming_response(content, file)
 
     # For GCS, try to redirect to signed URL, fall back to streaming
     try:
-        url = await storage.get_download_url(file.storagePath, expires_in=300)
+        url = await storage.get_download_url(file.storage_path, expires_in=300)
         # If we got back an API path (fallback), stream directly instead
         if url.startswith("/api/"):
-            content = await storage.retrieve(file.storagePath)
+            content = await storage.retrieve(file.storage_path)
             return _create_streaming_response(content, file)
         return fastapi.responses.RedirectResponse(url=url, status_code=302)
     except Exception as e:
         # Log the signed URL failure with context
         logger.error(
             f"Failed to get signed URL for file {file.id} "
-            f"(storagePath={file.storagePath}): {e}",
+            f"(storagePath={file.storage_path}): {e}",
             exc_info=True,
         )
         # Fall back to streaming directly from GCS
         try:
-            content = await storage.retrieve(file.storagePath)
+            content = await storage.retrieve(file.storage_path)
             return _create_streaming_response(content, file)
         except Exception as fallback_error:
             logger.error(
                 f"Fallback streaming also failed for file {file.id} "
-                f"(storagePath={file.storagePath}): {fallback_error}",
+                f"(storagePath={file.storage_path}): {fallback_error}",
                 exc_info=True,
             )
             raise
 
 
+class UploadFileResponse(BaseModel):
+    file_id: str
+    name: str
+    path: str
+    mime_type: str
+    size_bytes: int
+
+
+class DeleteFileResponse(BaseModel):
+    deleted: bool
+
+
+class StorageUsageResponse(BaseModel):
+    used_bytes: int
+    limit_bytes: int
+    used_percent: float
+    file_count: int
+
+
 @router.get(
     "/files/{file_id}/download",
     summary="Download file by ID",
@@ -120,3 +153,148 @@ async def download_file(
         raise fastapi.HTTPException(status_code=404, detail="File not found")
 
     return await _create_file_download_response(file)
+
+
+@router.delete(
+    "/files/{file_id}",
+    summary="Delete a workspace file",
+)
+async def delete_workspace_file(
+    user_id: Annotated[str, fastapi.Security(get_user_id)],
+    file_id: str,
+) -> DeleteFileResponse:
+    """
+    Soft-delete a workspace file and attempt to remove it from storage.
+
+    Used when a user clears a file input in the builder.
+    """
+    workspace = await get_workspace(user_id)
+    if workspace is None:
+        raise fastapi.HTTPException(status_code=404, detail="Workspace not found")
+
+    manager = WorkspaceManager(user_id, workspace.id)
+    deleted = await manager.delete_file(file_id)
+    if not deleted:
+        raise fastapi.HTTPException(status_code=404, detail="File not found")
+
+    return DeleteFileResponse(deleted=True)
+
+
+@router.post(
+    "/files/upload",
+    summary="Upload file to workspace",
+)
+async def upload_file(
+    user_id: Annotated[str, fastapi.Security(get_user_id)],
+    file: UploadFile,
+    session_id: str | None = Query(default=None),
+) -> UploadFileResponse:
+    """
+    Upload a file to the user's workspace.
+
+    Files are stored in session-scoped paths when session_id is provided,
+    so the agent's session-scoped tools can discover them automatically.
+    """
+    config = Config()
+
+    # Sanitize filename — strip any directory components
+    filename = os.path.basename(file.filename or "upload") or "upload"
+
+    # Read file content with early abort on size limit
+    max_file_bytes = config.max_file_size_mb * 1024 * 1024
+    chunks: list[bytes] = []
+    total_size = 0
+    while chunk := await file.read(64 * 1024):  # 64KB chunks
+        total_size += len(chunk)
+        if total_size > max_file_bytes:
+            raise fastapi.HTTPException(
+                status_code=413,
+                detail=f"File exceeds maximum size of {config.max_file_size_mb} MB",
+            )
+        chunks.append(chunk)
+    content = b"".join(chunks)
+
+    # Get or create workspace
+    workspace = await get_or_create_workspace(user_id)
+
+    # Pre-write storage cap check (soft check — final enforcement is post-write)
+    storage_limit_bytes = config.max_workspace_storage_mb * 1024 * 1024
+    current_usage = await get_workspace_total_size(workspace.id)
+    if storage_limit_bytes and current_usage + len(content) > storage_limit_bytes:
+        used_percent = (current_usage / storage_limit_bytes) * 100
+        raise fastapi.HTTPException(
+            status_code=413,
+            detail={
+                "message": "Storage limit exceeded",
+                "used_bytes": current_usage,
+                "limit_bytes": storage_limit_bytes,
+                "used_percent": round(used_percent, 1),
+            },
+        )
+
+    # Warn at 80% usage
+    if (
+        storage_limit_bytes
+        and (usage_ratio := (current_usage + len(content)) / storage_limit_bytes) >= 0.8
+    ):
+        logger.warning(
+            f"User {user_id} workspace storage at {usage_ratio * 100:.1f}% "
+            f"({current_usage + len(content)} / {storage_limit_bytes} bytes)"
+        )
+
+    # Virus scan
+    await scan_content_safe(content, filename=filename)
+
+    # Write file via WorkspaceManager
+    manager = WorkspaceManager(user_id, workspace.id, session_id)
+    try:
+        workspace_file = await manager.write_file(content, filename)
+    except ValueError as e:
+        raise fastapi.HTTPException(status_code=409, detail=str(e)) from e
+
+    # Post-write storage check — eliminates TOCTOU race on the quota.
+    # If a concurrent upload pushed us over the limit, undo this write.
+    new_total = await get_workspace_total_size(workspace.id)
+    if storage_limit_bytes and new_total > storage_limit_bytes:
+        await soft_delete_workspace_file(workspace_file.id, workspace.id)
+        raise fastapi.HTTPException(
+            status_code=413,
+            detail={
+                "message": "Storage limit exceeded (concurrent upload)",
+                "used_bytes": new_total,
+                "limit_bytes": storage_limit_bytes,
+            },
+        )
+
+    return UploadFileResponse(
+        file_id=workspace_file.id,
+        name=workspace_file.name,
+        path=workspace_file.path,
+        mime_type=workspace_file.mime_type,
+        size_bytes=workspace_file.size_bytes,
+    )
+
+
+@router.get(
+    "/storage/usage",
+    summary="Get workspace storage usage",
+)
+async def get_storage_usage(
+    user_id: Annotated[str, fastapi.Security(get_user_id)],
+) -> StorageUsageResponse:
+    """
+    Get storage usage information for the user's workspace.
+    """
+    config = Config()
+    workspace = await get_or_create_workspace(user_id)
+
+    used_bytes = await get_workspace_total_size(workspace.id)
+    file_count = await count_workspace_files(workspace.id)
+    limit_bytes = config.max_workspace_storage_mb * 1024 * 1024
+
+    return StorageUsageResponse(
+        used_bytes=used_bytes,
+        limit_bytes=limit_bytes,
+        used_percent=round((used_bytes / limit_bytes) * 100, 1) if limit_bytes else 0,
+        file_count=file_count,
+    )

autogpt_platform/backend/backend/api/features/workspace/routes_test.py

@@ -0,0 +1,359 @@
+"""Tests for workspace file upload and download routes."""
+
+import io
+from datetime import datetime, timezone
+
+import fastapi
+import fastapi.testclient
+import pytest
+import pytest_mock
+
+from backend.api.features.workspace import routes as workspace_routes
+from backend.data.workspace import WorkspaceFile
+
+app = fastapi.FastAPI()
+app.include_router(workspace_routes.router)
+
+
+@app.exception_handler(ValueError)
+async def _value_error_handler(
+    request: fastapi.Request, exc: ValueError
+) -> fastapi.responses.JSONResponse:
+    """Mirror the production ValueError → 400 mapping from rest_api.py."""
+    return fastapi.responses.JSONResponse(status_code=400, content={"detail": str(exc)})
+
+
+client = fastapi.testclient.TestClient(app)
+
+TEST_USER_ID = "3e53486c-cf57-477e-ba2a-cb02dc828e1a"
+
+MOCK_WORKSPACE = type("W", (), {"id": "ws-1"})()
+
+_NOW = datetime(2023, 1, 1, tzinfo=timezone.utc)
+
+MOCK_FILE = WorkspaceFile(
+    id="file-aaa-bbb",
+    workspace_id="ws-1",
+    created_at=_NOW,
+    updated_at=_NOW,
+    name="hello.txt",
+    path="/session/hello.txt",
+    mime_type="text/plain",
+    size_bytes=13,
+    storage_path="local://hello.txt",
+)
+
+
+@pytest.fixture(autouse=True)
+def setup_app_auth(mock_jwt_user):
+    from autogpt_libs.auth.jwt_utils import get_jwt_payload
+
+    app.dependency_overrides[get_jwt_payload] = mock_jwt_user["get_jwt_payload"]
+    yield
+    app.dependency_overrides.clear()
+
+
+def _upload(
+    filename: str = "hello.txt",
+    content: bytes = b"Hello, world!",
+    content_type: str = "text/plain",
+):
+    """Helper to POST a file upload."""
+    return client.post(
+        "/files/upload?session_id=sess-1",
+        files={"file": (filename, io.BytesIO(content), content_type)},
+    )
+
+
+# ---- Happy path ----
+
+
+def test_upload_happy_path(mocker: pytest_mock.MockFixture):
+    mocker.patch(
+        "backend.api.features.workspace.routes.get_or_create_workspace",
+        return_value=MOCK_WORKSPACE,
+    )
+    mocker.patch(
+        "backend.api.features.workspace.routes.get_workspace_total_size",
+        return_value=0,
+    )
+    mocker.patch(
+        "backend.api.features.workspace.routes.scan_content_safe",
+        return_value=None,
+    )
+    mock_manager = mocker.MagicMock()
+    mock_manager.write_file = mocker.AsyncMock(return_value=MOCK_FILE)
+    mocker.patch(
+        "backend.api.features.workspace.routes.WorkspaceManager",
+        return_value=mock_manager,
+    )
+
+    response = _upload()
+    assert response.status_code == 200
+    data = response.json()
+    assert data["file_id"] == "file-aaa-bbb"
+    assert data["name"] == "hello.txt"
+    assert data["size_bytes"] == 13
+
+
+# ---- Per-file size limit ----
+
+
+def test_upload_exceeds_max_file_size(mocker: pytest_mock.MockFixture):
+    """Files larger than max_file_size_mb should be rejected with 413."""
+    cfg = mocker.patch("backend.api.features.workspace.routes.Config")
+    cfg.return_value.max_file_size_mb = 0  # 0 MB → any content is too big
+    cfg.return_value.max_workspace_storage_mb = 500
+
+    response = _upload(content=b"x" * 1024)
+    assert response.status_code == 413
+
+
+# ---- Storage quota exceeded ----
+
+
+def test_upload_storage_quota_exceeded(mocker: pytest_mock.MockFixture):
+    mocker.patch(
+        "backend.api.features.workspace.routes.get_or_create_workspace",
+        return_value=MOCK_WORKSPACE,
+    )
+    # Current usage already at limit
+    mocker.patch(
+        "backend.api.features.workspace.routes.get_workspace_total_size",
+        return_value=500 * 1024 * 1024,
+    )
+
+    response = _upload()
+    assert response.status_code == 413
+    assert "Storage limit exceeded" in response.text
+
+
+# ---- Post-write quota race (B2) ----
+
+
+def test_upload_post_write_quota_race(mocker: pytest_mock.MockFixture):
+    """If a concurrent upload tips the total over the limit after write,
+    the file should be soft-deleted and 413 returned."""
+    mocker.patch(
+        "backend.api.features.workspace.routes.get_or_create_workspace",
+        return_value=MOCK_WORKSPACE,
+    )
+    # Pre-write check passes (under limit), but post-write check fails
+    mocker.patch(
+        "backend.api.features.workspace.routes.get_workspace_total_size",
+        side_effect=[0, 600 * 1024 * 1024],  # first call OK, second over limit
+    )
+    mocker.patch(
+        "backend.api.features.workspace.routes.scan_content_safe",
+        return_value=None,
+    )
+    mock_manager = mocker.MagicMock()
+    mock_manager.write_file = mocker.AsyncMock(return_value=MOCK_FILE)
+    mocker.patch(
+        "backend.api.features.workspace.routes.WorkspaceManager",
+        return_value=mock_manager,
+    )
+    mock_delete = mocker.patch(
+        "backend.api.features.workspace.routes.soft_delete_workspace_file",
+        return_value=None,
+    )
+
+    response = _upload()
+    assert response.status_code == 413
+    mock_delete.assert_called_once_with("file-aaa-bbb", "ws-1")
+
+
+# ---- Any extension accepted (no allowlist) ----
+
+
+def test_upload_any_extension(mocker: pytest_mock.MockFixture):
+    """Any file extension should be accepted — ClamAV is the security layer."""
+    mocker.patch(
+        "backend.api.features.workspace.routes.get_or_create_workspace",
+        return_value=MOCK_WORKSPACE,
+    )
+    mocker.patch(
+        "backend.api.features.workspace.routes.get_workspace_total_size",
+        return_value=0,
+    )
+    mocker.patch(
+        "backend.api.features.workspace.routes.scan_content_safe",
+        return_value=None,
+    )
+    mock_manager = mocker.MagicMock()
+    mock_manager.write_file = mocker.AsyncMock(return_value=MOCK_FILE)
+    mocker.patch(
+        "backend.api.features.workspace.routes.WorkspaceManager",
+        return_value=mock_manager,
+    )
+
+    response = _upload(filename="data.xyz", content=b"arbitrary")
+    assert response.status_code == 200
+
+
+# ---- Virus scan rejection ----
+
+
+def test_upload_blocked_by_virus_scan(mocker: pytest_mock.MockFixture):
+    """Files flagged by ClamAV should be rejected and never written to storage."""
+    from backend.api.features.store.exceptions import VirusDetectedError
+
+    mocker.patch(
+        "backend.api.features.workspace.routes.get_or_create_workspace",
+        return_value=MOCK_WORKSPACE,
+    )
+    mocker.patch(
+        "backend.api.features.workspace.routes.get_workspace_total_size",
+        return_value=0,
+    )
+    mocker.patch(
+        "backend.api.features.workspace.routes.scan_content_safe",
+        side_effect=VirusDetectedError("Eicar-Test-Signature"),
+    )
+    mock_manager = mocker.MagicMock()
+    mock_manager.write_file = mocker.AsyncMock(return_value=MOCK_FILE)
+    mocker.patch(
+        "backend.api.features.workspace.routes.WorkspaceManager",
+        return_value=mock_manager,
+    )
+
+    response = _upload(filename="evil.exe", content=b"X5O!P%@AP...")
+    assert response.status_code == 400
+    assert "Virus detected" in response.text
+    mock_manager.write_file.assert_not_called()
+
+
+# ---- No file extension ----
+
+
+def test_upload_file_without_extension(mocker: pytest_mock.MockFixture):
+    """Files without an extension should be accepted and stored as-is."""
+    mocker.patch(
+        "backend.api.features.workspace.routes.get_or_create_workspace",
+        return_value=MOCK_WORKSPACE,
+    )
+    mocker.patch(
+        "backend.api.features.workspace.routes.get_workspace_total_size",
+        return_value=0,
+    )
+    mocker.patch(
+        "backend.api.features.workspace.routes.scan_content_safe",
+        return_value=None,
+    )
+    mock_manager = mocker.MagicMock()
+    mock_manager.write_file = mocker.AsyncMock(return_value=MOCK_FILE)
+    mocker.patch(
+        "backend.api.features.workspace.routes.WorkspaceManager",
+        return_value=mock_manager,
+    )
+
+    response = _upload(
+        filename="Makefile",
+        content=b"all:\n\techo hello",
+        content_type="application/octet-stream",
+    )
+    assert response.status_code == 200
+    mock_manager.write_file.assert_called_once()
+    assert mock_manager.write_file.call_args[0][1] == "Makefile"
+
+
+# ---- Filename sanitization (SF5) ----
+
+
+def test_upload_strips_path_components(mocker: pytest_mock.MockFixture):
+    """Path-traversal filenames should be reduced to their basename."""
+    mocker.patch(
+        "backend.api.features.workspace.routes.get_or_create_workspace",
+        return_value=MOCK_WORKSPACE,
+    )
+    mocker.patch(
+        "backend.api.features.workspace.routes.get_workspace_total_size",
+        return_value=0,
+    )
+    mocker.patch(
+        "backend.api.features.workspace.routes.scan_content_safe",
+        return_value=None,
+    )
+    mock_manager = mocker.MagicMock()
+    mock_manager.write_file = mocker.AsyncMock(return_value=MOCK_FILE)
+    mocker.patch(
+        "backend.api.features.workspace.routes.WorkspaceManager",
+        return_value=mock_manager,
+    )
+
+    # Filename with traversal
+    _upload(filename="../../etc/passwd.txt")
+
+    # write_file should have been called with just the basename
+    mock_manager.write_file.assert_called_once()
+    call_args = mock_manager.write_file.call_args
+    assert call_args[0][1] == "passwd.txt"
+
+
+# ---- Download ----
+
+
+def test_download_file_not_found(mocker: pytest_mock.MockFixture):
+    mocker.patch(
+        "backend.api.features.workspace.routes.get_workspace",
+        return_value=MOCK_WORKSPACE,
+    )
+    mocker.patch(
+        "backend.api.features.workspace.routes.get_workspace_file",
+        return_value=None,
+    )
+
+    response = client.get("/files/some-file-id/download")
+    assert response.status_code == 404
+
+
+# ---- Delete ----
+
+
+def test_delete_file_success(mocker: pytest_mock.MockFixture):
+    """Deleting an existing file should return {"deleted": true}."""
+    mocker.patch(
+        "backend.api.features.workspace.routes.get_workspace",
+        return_value=MOCK_WORKSPACE,
+    )
+    mock_manager = mocker.MagicMock()
+    mock_manager.delete_file = mocker.AsyncMock(return_value=True)
+    mocker.patch(
+        "backend.api.features.workspace.routes.WorkspaceManager",
+        return_value=mock_manager,
+    )
+
+    response = client.delete("/files/file-aaa-bbb")
+    assert response.status_code == 200
+    assert response.json() == {"deleted": True}
+    mock_manager.delete_file.assert_called_once_with("file-aaa-bbb")
+
+
+def test_delete_file_not_found(mocker: pytest_mock.MockFixture):
+    """Deleting a non-existent file should return 404."""
+    mocker.patch(
+        "backend.api.features.workspace.routes.get_workspace",
+        return_value=MOCK_WORKSPACE,
+    )
+    mock_manager = mocker.MagicMock()
+    mock_manager.delete_file = mocker.AsyncMock(return_value=False)
+    mocker.patch(
+        "backend.api.features.workspace.routes.WorkspaceManager",
+        return_value=mock_manager,
+    )
+
+    response = client.delete("/files/nonexistent-id")
+    assert response.status_code == 404
+    assert "File not found" in response.text
+
+
+def test_delete_file_no_workspace(mocker: pytest_mock.MockFixture):
+    """Deleting when user has no workspace should return 404."""
+    mocker.patch(
+        "backend.api.features.workspace.routes.get_workspace",
+        return_value=None,
+    )
+
+    response = client.delete("/files/file-aaa-bbb")
+    assert response.status_code == 404
+    assert "Workspace not found" in response.text

autogpt_platform/backend/backend/api/rest_api.py

@@ -26,6 +26,7 @@ import backend.api.features.executions.review.routes
 import backend.api.features.library.db
 import backend.api.features.library.model
 import backend.api.features.library.routes
+import backend.api.features.mcp.routes as mcp_routes
 import backend.api.features.oauth
 import backend.api.features.otto.routes
 import backend.api.features.postmark.postmark
@@ -40,9 +41,9 @@ import backend.data.user
 import backend.integrations.webhooks.utils
 import backend.util.service
 import backend.util.settings
-from backend.api.features.chat.completion_consumer import (
-    start_completion_consumer,
-    stop_completion_consumer,
+from backend.api.features.library.exceptions import (
+    FolderAlreadyExistsError,
+    FolderValidationError,
 )
 from backend.blocks.llm import DEFAULT_LLM_MODEL
 from backend.data.model import Credentials
@@ -122,21 +123,9 @@ async def lifespan_context(app: fastapi.FastAPI):
     await backend.data.graph.migrate_llm_models(DEFAULT_LLM_MODEL)
     await backend.integrations.webhooks.utils.migrate_legacy_triggered_graphs()
 
-    # Start chat completion consumer for Redis Streams notifications
-    try:
-        await start_completion_consumer()
-    except Exception as e:
-        logger.warning(f"Could not start chat completion consumer: {e}")
-
     with launch_darkly_context():
         yield
 
-    # Stop chat completion consumer
-    try:
-        await stop_completion_consumer()
-    except Exception as e:
-        logger.warning(f"Error stopping chat completion consumer: {e}")
-
     try:
         await shutdown_cloud_storage_handler()
     except Exception as e:
@@ -276,6 +265,10 @@ async def validation_error_handler(
 
 
 app.add_exception_handler(PrismaError, handle_internal_http_error(500))
+app.add_exception_handler(
+    FolderAlreadyExistsError, handle_internal_http_error(409, False)
+)
+app.add_exception_handler(FolderValidationError, handle_internal_http_error(400, False))
 app.add_exception_handler(NotFoundError, handle_internal_http_error(404, False))
 app.add_exception_handler(NotAuthorizedError, handle_internal_http_error(403, False))
 app.add_exception_handler(RequestValidationError, validation_error_handler)
@@ -343,6 +336,11 @@ app.include_router(
     tags=["workspace"],
     prefix="/api/workspace",
 )
+app.include_router(
+    mcp_routes.router,
+    tags=["v2", "mcp"],
+    prefix="/api/mcp",
+)
 app.include_router(
     backend.api.features.oauth.router,
     tags=["oauth"],

autogpt_platform/backend/backend/app.py

@@ -24,7 +24,7 @@ def run_processes(*processes: "AppProcess", **kwargs):
         # Run the last process in the foreground.
         processes[-1].start(background=False, **kwargs)
     finally:
-        for process in processes:
+        for process in reversed(processes):
             try:
                 process.stop()
             except Exception as e:
@@ -38,7 +38,9 @@ def main(**kwargs):
 
     from backend.api.rest_api import AgentServer
     from backend.api.ws_api import WebsocketServer
-    from backend.executor import DatabaseManager, ExecutionManager, Scheduler
+    from backend.copilot.executor.manager import CoPilotExecutor
+    from backend.data.db_manager import DatabaseManager
+    from backend.executor import ExecutionManager, Scheduler
     from backend.notifications import NotificationManager
 
     run_processes(
@@ -48,6 +50,7 @@ def main(**kwargs):
         WebsocketServer(),
         AgentServer(),
         ExecutionManager(),
+        CoPilotExecutor(),
         **kwargs,
     )
 

autogpt_platform/backend/backend/blocks/_base.py

@@ -64,6 +64,7 @@ class BlockType(Enum):
     AI = "AI"
     AYRSHARE = "Ayrshare"
     HUMAN_IN_THE_LOOP = "Human In The Loop"
+    MCP_TOOL = "MCP Tool"
 
 
 class BlockCategory(Enum):

autogpt_platform/backend/backend/blocks/basic.py

@@ -126,6 +126,7 @@ class PrintToConsoleBlock(Block):
             output_schema=PrintToConsoleBlock.Output,
             test_input={"text": "Hello, World!"},
             is_sensitive_action=True,
+            disabled=True,  # Disabled per Nick Tindle's request (OPEN-3000)
             test_output=[
                 ("output", "Hello, World!"),
                 ("status", "printed"),

autogpt_platform/backend/backend/blocks/data_manipulation.py

@@ -682,17 +682,219 @@ class ListIsEmptyBlock(Block):
         yield "is_empty", len(input_data.list) == 0
 
 
+# =============================================================================
+# List Concatenation Helpers
+# =============================================================================
+
+
+def _validate_list_input(item: Any, index: int) -> str | None:
+    """Validate that an item is a list. Returns error message or None."""
+    if item is None:
+        return None  # None is acceptable, will be skipped
+    if not isinstance(item, list):
+        return (
+            f"Invalid input at index {index}: expected a list, "
+            f"got {type(item).__name__}. "
+            f"All items in 'lists' must be lists (e.g., [[1, 2], [3, 4]])."
+        )
+    return None
+
+
+def _validate_all_lists(lists: List[Any]) -> str | None:
+    """Validate that all items in a sequence are lists. Returns first error or None."""
+    for idx, item in enumerate(lists):
+        error = _validate_list_input(item, idx)
+        if error is not None and item is not None:
+            return error
+    return None
+
+
+def _concatenate_lists_simple(lists: List[List[Any]]) -> List[Any]:
+    """Concatenate a sequence of lists into a single list, skipping None values."""
+    result: List[Any] = []
+    for lst in lists:
+        if lst is None:
+            continue
+        result.extend(lst)
+    return result
+
+
+def _flatten_nested_list(nested: List[Any], max_depth: int = -1) -> List[Any]:
+    """
+    Recursively flatten a nested list structure.
+
+    Args:
+        nested: The list to flatten.
+        max_depth: Maximum recursion depth. -1 means unlimited.
+
+    Returns:
+        A flat list with all nested elements extracted.
+    """
+    result: List[Any] = []
+    _flatten_recursive(nested, result, current_depth=0, max_depth=max_depth)
+    return result
+
+
+_MAX_FLATTEN_DEPTH = 1000
+
+
+def _flatten_recursive(
+    items: List[Any],
+    result: List[Any],
+    current_depth: int,
+    max_depth: int,
+) -> None:
+    """Internal recursive helper for flattening nested lists."""
+    if current_depth > _MAX_FLATTEN_DEPTH:
+        raise RecursionError(
+            f"Flattening exceeded maximum depth of {_MAX_FLATTEN_DEPTH} levels. "
+            "Input may be too deeply nested."
+        )
+    for item in items:
+        if isinstance(item, list) and (max_depth == -1 or current_depth < max_depth):
+            _flatten_recursive(item, result, current_depth + 1, max_depth)
+        else:
+            result.append(item)
+
+
+def _deduplicate_list(items: List[Any]) -> List[Any]:
+    """
+    Remove duplicate elements from a list, preserving order of first occurrences.
+
+    Args:
+        items: The list to deduplicate.
+
+    Returns:
+        A list with duplicates removed, maintaining original order.
+    """
+    seen: set = set()
+    result: List[Any] = []
+    for item in items:
+        item_id = _make_hashable(item)
+        if item_id not in seen:
+            seen.add(item_id)
+            result.append(item)
+    return result
+
+
+def _make_hashable(item: Any):
+    """
+    Create a hashable representation of any item for deduplication.
+    Converts unhashable types (dicts, lists) into deterministic tuple structures.
+    """
+    if isinstance(item, dict):
+        return tuple(
+            sorted(
+                ((_make_hashable(k), _make_hashable(v)) for k, v in item.items()),
+                key=lambda x: (str(type(x[0])), str(x[0])),
+            )
+        )
+    if isinstance(item, (list, tuple)):
+        return tuple(_make_hashable(i) for i in item)
+    if isinstance(item, set):
+        return frozenset(_make_hashable(i) for i in item)
+    return item
+
+
+def _filter_none_values(items: List[Any]) -> List[Any]:
+    """Remove None values from a list."""
+    return [item for item in items if item is not None]
+
+
+def _compute_nesting_depth(
+    items: Any, current: int = 0, max_depth: int = _MAX_FLATTEN_DEPTH
+) -> int:
+    """
+    Compute the maximum nesting depth of a list structure using iteration to avoid RecursionError.
+
+    Uses a stack-based approach to handle deeply nested structures without hitting Python's
+    recursion limit (~1000 levels).
+    """
+    if not isinstance(items, list):
+        return current
+
+    # Stack contains tuples of (item, depth)
+    stack = [(items, current)]
+    max_observed_depth = current
+
+    while stack:
+        item, depth = stack.pop()
+
+        if depth > max_depth:
+            return depth
+
+        if not isinstance(item, list):
+            max_observed_depth = max(max_observed_depth, depth)
+            continue
+
+        if len(item) == 0:
+            max_observed_depth = max(max_observed_depth, depth + 1)
+            continue
+
+        # Add all children to stack with incremented depth
+        for child in item:
+            stack.append((child, depth + 1))
+
+    return max_observed_depth
+
+
+def _interleave_lists(lists: List[List[Any]]) -> List[Any]:
+    """
+    Interleave elements from multiple lists in round-robin fashion.
+    Example: [[1,2,3], [a,b], [x,y,z]] -> [1, a, x, 2, b, y, 3, z]
+    """
+    if not lists:
+        return []
+    filtered = [lst for lst in lists if lst is not None]
+    if not filtered:
+        return []
+    result: List[Any] = []
+    max_len = max(len(lst) for lst in filtered)
+    for i in range(max_len):
+        for lst in filtered:
+            if i < len(lst):
+                result.append(lst[i])
+    return result
+
+
+# =============================================================================
+# List Concatenation Blocks
+# =============================================================================
+
+
 class ConcatenateListsBlock(Block):
+    """
+    Concatenates two or more lists into a single list.
+
+    This block accepts a list of lists and combines all their elements
+    in order into one flat output list. It supports options for
+    deduplication and None-filtering to provide flexible list merging
+    capabilities for workflow pipelines.
+    """
+
     class Input(BlockSchemaInput):
         lists: List[List[Any]] = SchemaField(
             description="A list of lists to concatenate together. All lists will be combined in order into a single list.",
             placeholder="e.g., [[1, 2], [3, 4], [5, 6]]",
         )
+        deduplicate: bool = SchemaField(
+            description="If True, remove duplicate elements from the concatenated result while preserving order.",
+            default=False,
+            advanced=True,
+        )
+        remove_none: bool = SchemaField(
+            description="If True, remove None values from the concatenated result.",
+            default=False,
+            advanced=True,
+        )
 
     class Output(BlockSchemaOutput):
         concatenated_list: List[Any] = SchemaField(
             description="The concatenated list containing all elements from all input lists in order."
         )
+        length: int = SchemaField(
+            description="The total number of elements in the concatenated list."
+        )
         error: str = SchemaField(
             description="Error message if concatenation failed due to invalid input types."
         )
@@ -700,7 +902,7 @@ class ConcatenateListsBlock(Block):
     def __init__(self):
         super().__init__(
             id="3cf9298b-5817-4141-9d80-7c2cc5199c8e",
-            description="Concatenates multiple lists into a single list. All elements from all input lists are combined in order.",
+            description="Concatenates multiple lists into a single list. All elements from all input lists are combined in order. Supports optional deduplication and None removal.",
             categories={BlockCategory.BASIC},
             input_schema=ConcatenateListsBlock.Input,
             output_schema=ConcatenateListsBlock.Output,
@@ -709,29 +911,497 @@ class ConcatenateListsBlock(Block):
                 {"lists": [["a", "b"], ["c"], ["d", "e", "f"]]},
                 {"lists": [[1, 2], []]},
                 {"lists": []},
+                {"lists": [[1, 2, 2, 3], [3, 4]], "deduplicate": True},
+                {"lists": [[1, None, 2], [None, 3]], "remove_none": True},
             ],
             test_output=[
                 ("concatenated_list", [1, 2, 3, 4, 5, 6]),
+                ("length", 6),
                 ("concatenated_list", ["a", "b", "c", "d", "e", "f"]),
+                ("length", 6),
                 ("concatenated_list", [1, 2]),
+                ("length", 2),
                 ("concatenated_list", []),
+                ("length", 0),
+                ("concatenated_list", [1, 2, 3, 4]),
+                ("length", 4),
+                ("concatenated_list", [1, 2, 3]),
+                ("length", 3),
             ],
         )
 
+    def _validate_inputs(self, lists: List[Any]) -> str | None:
+        return _validate_all_lists(lists)
+
+    def _perform_concatenation(self, lists: List[List[Any]]) -> List[Any]:
+        return _concatenate_lists_simple(lists)
+
+    def _apply_deduplication(self, items: List[Any]) -> List[Any]:
+        return _deduplicate_list(items)
+
+    def _apply_none_removal(self, items: List[Any]) -> List[Any]:
+        return _filter_none_values(items)
+
+    def _post_process(
+        self, items: List[Any], deduplicate: bool, remove_none: bool
+    ) -> List[Any]:
+        """Apply all post-processing steps to the concatenated result."""
+        result = items
+        if remove_none:
+            result = self._apply_none_removal(result)
+        if deduplicate:
+            result = self._apply_deduplication(result)
+        return result
+
     async def run(self, input_data: Input, **kwargs) -> BlockOutput:
-        concatenated = []
-        for idx, lst in enumerate(input_data.lists):
-            if lst is None:
-                # Skip None values to avoid errors
-                continue
-            if not isinstance(lst, list):
-                # Type validation: each item must be a list
-                # Strings are iterable and would cause extend() to iterate character-by-character
-                # Non-iterable types would raise TypeError
-                yield "error", (
-                    f"Invalid input at index {idx}: expected a list, got {type(lst).__name__}. "
-                    f"All items in 'lists' must be lists (e.g., [[1, 2], [3, 4]])."
-                )
-                return
-            concatenated.extend(lst)
-        yield "concatenated_list", concatenated
+        # Validate all inputs are lists
+        validation_error = self._validate_inputs(input_data.lists)
+        if validation_error is not None:
+            yield "error", validation_error
+            return
+
+        # Perform concatenation
+        concatenated = self._perform_concatenation(input_data.lists)
+
+        # Apply post-processing
+        result = self._post_process(
+            concatenated, input_data.deduplicate, input_data.remove_none
+        )
+
+        yield "concatenated_list", result
+        yield "length", len(result)
+
+
+class FlattenListBlock(Block):
+    """
+    Flattens a nested list structure into a single flat list.
+
+    This block takes a list that may contain nested lists at any depth
+    and produces a single-level list with all leaf elements. Useful
+    for normalizing data structures from multiple sources that may
+    have varying levels of nesting.
+    """
+
+    class Input(BlockSchemaInput):
+        nested_list: List[Any] = SchemaField(
+            description="A potentially nested list to flatten into a single-level list.",
+            placeholder="e.g., [[1, [2, 3]], [4, [5, [6]]]]",
+        )
+        max_depth: int = SchemaField(
+            description="Maximum depth to flatten. -1 means flatten completely. 1 means flatten only one level.",
+            default=-1,
+            advanced=True,
+        )
+
+    class Output(BlockSchemaOutput):
+        flattened_list: List[Any] = SchemaField(
+            description="The flattened list with all nested elements extracted."
+        )
+        length: int = SchemaField(
+            description="The number of elements in the flattened list."
+        )
+        original_depth: int = SchemaField(
+            description="The maximum nesting depth of the original input list."
+        )
+        error: str = SchemaField(description="Error message if flattening failed.")
+
+    def __init__(self):
+        super().__init__(
+            id="cc45bb0f-d035-4756-96a7-fe3e36254b4d",
+            description="Flattens a nested list structure into a single flat list. Supports configurable maximum flattening depth.",
+            categories={BlockCategory.BASIC},
+            input_schema=FlattenListBlock.Input,
+            output_schema=FlattenListBlock.Output,
+            test_input=[
+                {"nested_list": [[1, 2], [3, [4, 5]]]},
+                {"nested_list": [1, [2, [3, [4]]]]},
+                {"nested_list": [1, [2, [3, [4]]], 5], "max_depth": 1},
+                {"nested_list": []},
+                {"nested_list": [1, 2, 3]},
+            ],
+            test_output=[
+                ("flattened_list", [1, 2, 3, 4, 5]),
+                ("length", 5),
+                ("original_depth", 3),
+                ("flattened_list", [1, 2, 3, 4]),
+                ("length", 4),
+                ("original_depth", 4),
+                ("flattened_list", [1, 2, [3, [4]], 5]),
+                ("length", 4),
+                ("original_depth", 4),
+                ("flattened_list", []),
+                ("length", 0),
+                ("original_depth", 1),
+                ("flattened_list", [1, 2, 3]),
+                ("length", 3),
+                ("original_depth", 1),
+            ],
+        )
+
+    def _compute_depth(self, items: List[Any]) -> int:
+        """Compute the nesting depth of the input list."""
+        return _compute_nesting_depth(items)
+
+    def _flatten(self, items: List[Any], max_depth: int) -> List[Any]:
+        """Flatten the list to the specified depth."""
+        return _flatten_nested_list(items, max_depth=max_depth)
+
+    def _validate_max_depth(self, max_depth: int) -> str | None:
+        """Validate the max_depth parameter."""
+        if max_depth < -1:
+            return f"max_depth must be -1 (unlimited) or a non-negative integer, got {max_depth}"
+        return None
+
+    async def run(self, input_data: Input, **kwargs) -> BlockOutput:
+        # Validate max_depth
+        depth_error = self._validate_max_depth(input_data.max_depth)
+        if depth_error is not None:
+            yield "error", depth_error
+            return
+
+        original_depth = self._compute_depth(input_data.nested_list)
+        flattened = self._flatten(input_data.nested_list, input_data.max_depth)
+
+        yield "flattened_list", flattened
+        yield "length", len(flattened)
+        yield "original_depth", original_depth
+
+
+class InterleaveListsBlock(Block):
+    """
+    Interleaves elements from multiple lists in round-robin fashion.
+
+    Given multiple input lists, this block takes one element from each
+    list in turn, producing an output where elements alternate between
+    sources. Lists of different lengths are handled gracefully - shorter
+    lists simply stop contributing once exhausted.
+    """
+
+    class Input(BlockSchemaInput):
+        lists: List[List[Any]] = SchemaField(
+            description="A list of lists to interleave. Elements will be taken in round-robin order.",
+            placeholder="e.g., [[1, 2, 3], ['a', 'b', 'c']]",
+        )
+
+    class Output(BlockSchemaOutput):
+        interleaved_list: List[Any] = SchemaField(
+            description="The interleaved list with elements alternating from each input list."
+        )
+        length: int = SchemaField(
+            description="The total number of elements in the interleaved list."
+        )
+        error: str = SchemaField(description="Error message if interleaving failed.")
+
+    def __init__(self):
+        super().__init__(
+            id="9f616084-1d9f-4f8e-bc00-5b9d2a75cd75",
+            description="Interleaves elements from multiple lists in round-robin fashion, alternating between sources.",
+            categories={BlockCategory.BASIC},
+            input_schema=InterleaveListsBlock.Input,
+            output_schema=InterleaveListsBlock.Output,
+            test_input=[
+                {"lists": [[1, 2, 3], ["a", "b", "c"]]},
+                {"lists": [[1, 2, 3], ["a", "b"], ["x", "y", "z"]]},
+                {"lists": [[1], [2], [3]]},
+                {"lists": []},
+            ],
+            test_output=[
+                ("interleaved_list", [1, "a", 2, "b", 3, "c"]),
+                ("length", 6),
+                ("interleaved_list", [1, "a", "x", 2, "b", "y", 3, "z"]),
+                ("length", 8),
+                ("interleaved_list", [1, 2, 3]),
+                ("length", 3),
+                ("interleaved_list", []),
+                ("length", 0),
+            ],
+        )
+
+    def _validate_inputs(self, lists: List[Any]) -> str | None:
+        return _validate_all_lists(lists)
+
+    def _interleave(self, lists: List[List[Any]]) -> List[Any]:
+        return _interleave_lists(lists)
+
+    async def run(self, input_data: Input, **kwargs) -> BlockOutput:
+        validation_error = self._validate_inputs(input_data.lists)
+        if validation_error is not None:
+            yield "error", validation_error
+            return
+
+        result = self._interleave(input_data.lists)
+        yield "interleaved_list", result
+        yield "length", len(result)
+
+
+class ZipListsBlock(Block):
+    """
+    Zips multiple lists together into a list of grouped tuples/lists.
+
+    Takes two or more input lists and combines corresponding elements
+    into sub-lists. For example, zipping [1,2,3] and ['a','b','c']
+    produces [[1,'a'], [2,'b'], [3,'c']]. Supports both truncating
+    to shortest list and padding to longest list with a fill value.
+    """
+
+    class Input(BlockSchemaInput):
+        lists: List[List[Any]] = SchemaField(
+            description="A list of lists to zip together. Corresponding elements will be grouped.",
+            placeholder="e.g., [[1, 2, 3], ['a', 'b', 'c']]",
+        )
+        pad_to_longest: bool = SchemaField(
+            description="If True, pad shorter lists with fill_value to match the longest list. If False, truncate to shortest.",
+            default=False,
+            advanced=True,
+        )
+        fill_value: Any = SchemaField(
+            description="Value to use for padding when pad_to_longest is True.",
+            default=None,
+            advanced=True,
+        )
+
+    class Output(BlockSchemaOutput):
+        zipped_list: List[List[Any]] = SchemaField(
+            description="The zipped list of grouped elements."
+        )
+        length: int = SchemaField(
+            description="The number of groups in the zipped result."
+        )
+        error: str = SchemaField(description="Error message if zipping failed.")
+
+    def __init__(self):
+        super().__init__(
+            id="0d0e684f-5cb9-4c4b-b8d1-47a0860e0c07",
+            description="Zips multiple lists together into a list of grouped elements. Supports padding to longest or truncating to shortest.",
+            categories={BlockCategory.BASIC},
+            input_schema=ZipListsBlock.Input,
+            output_schema=ZipListsBlock.Output,
+            test_input=[
+                {"lists": [[1, 2, 3], ["a", "b", "c"]]},
+                {"lists": [[1, 2, 3], ["a", "b"]]},
+                {
+                    "lists": [[1, 2], ["a", "b", "c"]],
+                    "pad_to_longest": True,
+                    "fill_value": 0,
+                },
+                {"lists": []},
+            ],
+            test_output=[
+                ("zipped_list", [[1, "a"], [2, "b"], [3, "c"]]),
+                ("length", 3),
+                ("zipped_list", [[1, "a"], [2, "b"]]),
+                ("length", 2),
+                ("zipped_list", [[1, "a"], [2, "b"], [0, "c"]]),
+                ("length", 3),
+                ("zipped_list", []),
+                ("length", 0),
+            ],
+        )
+
+    def _validate_inputs(self, lists: List[Any]) -> str | None:
+        return _validate_all_lists(lists)
+
+    def _zip_truncate(self, lists: List[List[Any]]) -> List[List[Any]]:
+        """Zip lists, truncating to shortest."""
+        filtered = [lst for lst in lists if lst is not None]
+        if not filtered:
+            return []
+        return [list(group) for group in zip(*filtered)]
+
+    def _zip_pad(self, lists: List[List[Any]], fill_value: Any) -> List[List[Any]]:
+        """Zip lists, padding shorter ones with fill_value."""
+        if not lists:
+            return []
+        lists = [lst for lst in lists if lst is not None]
+        if not lists:
+            return []
+        max_len = max(len(lst) for lst in lists)
+        result: List[List[Any]] = []
+        for i in range(max_len):
+            group: List[Any] = []
+            for lst in lists:
+                if i < len(lst):
+                    group.append(lst[i])
+                else:
+                    group.append(fill_value)
+            result.append(group)
+        return result
+
+    async def run(self, input_data: Input, **kwargs) -> BlockOutput:
+        validation_error = self._validate_inputs(input_data.lists)
+        if validation_error is not None:
+            yield "error", validation_error
+            return
+
+        if not input_data.lists:
+            yield "zipped_list", []
+            yield "length", 0
+            return
+
+        if input_data.pad_to_longest:
+            result = self._zip_pad(input_data.lists, input_data.fill_value)
+        else:
+            result = self._zip_truncate(input_data.lists)
+
+        yield "zipped_list", result
+        yield "length", len(result)
+
+
+class ListDifferenceBlock(Block):
+    """
+    Computes the difference between two lists (elements in the first
+    list that are not in the second list).
+
+    This is useful for finding items that exist in one dataset but
+    not in another, such as finding new items, missing items, or
+    items that need to be processed.
+    """
+
+    class Input(BlockSchemaInput):
+        list_a: List[Any] = SchemaField(
+            description="The primary list to check elements from.",
+            placeholder="e.g., [1, 2, 3, 4, 5]",
+        )
+        list_b: List[Any] = SchemaField(
+            description="The list to subtract. Elements found here will be removed from list_a.",
+            placeholder="e.g., [3, 4, 5, 6]",
+        )
+        symmetric: bool = SchemaField(
+            description="If True, compute symmetric difference (elements in either list but not both).",
+            default=False,
+            advanced=True,
+        )
+
+    class Output(BlockSchemaOutput):
+        difference: List[Any] = SchemaField(
+            description="Elements from list_a not found in list_b (or symmetric difference if enabled)."
+        )
+        length: int = SchemaField(
+            description="The number of elements in the difference result."
+        )
+        error: str = SchemaField(description="Error message if the operation failed.")
+
+    def __init__(self):
+        super().__init__(
+            id="05309873-9d61-447e-96b5-b804e2511829",
+            description="Computes the difference between two lists. Returns elements in the first list not found in the second, or symmetric difference.",
+            categories={BlockCategory.BASIC},
+            input_schema=ListDifferenceBlock.Input,
+            output_schema=ListDifferenceBlock.Output,
+            test_input=[
+                {"list_a": [1, 2, 3, 4, 5], "list_b": [3, 4, 5, 6, 7]},
+                {
+                    "list_a": [1, 2, 3, 4, 5],
+                    "list_b": [3, 4, 5, 6, 7],
+                    "symmetric": True,
+                },
+                {"list_a": ["a", "b", "c"], "list_b": ["b"]},
+                {"list_a": [], "list_b": [1, 2, 3]},
+            ],
+            test_output=[
+                ("difference", [1, 2]),
+                ("length", 2),
+                ("difference", [1, 2, 6, 7]),
+                ("length", 4),
+                ("difference", ["a", "c"]),
+                ("length", 2),
+                ("difference", []),
+                ("length", 0),
+            ],
+        )
+
+    def _compute_difference(self, list_a: List[Any], list_b: List[Any]) -> List[Any]:
+        """Compute elements in list_a not in list_b."""
+        b_hashes = {_make_hashable(item) for item in list_b}
+        return [item for item in list_a if _make_hashable(item) not in b_hashes]
+
+    def _compute_symmetric_difference(
+        self, list_a: List[Any], list_b: List[Any]
+    ) -> List[Any]:
+        """Compute elements in either list but not both."""
+        a_hashes = {_make_hashable(item) for item in list_a}
+        b_hashes = {_make_hashable(item) for item in list_b}
+        only_in_a = [item for item in list_a if _make_hashable(item) not in b_hashes]
+        only_in_b = [item for item in list_b if _make_hashable(item) not in a_hashes]
+        return only_in_a + only_in_b
+
+    async def run(self, input_data: Input, **kwargs) -> BlockOutput:
+        if input_data.symmetric:
+            result = self._compute_symmetric_difference(
+                input_data.list_a, input_data.list_b
+            )
+        else:
+            result = self._compute_difference(input_data.list_a, input_data.list_b)
+
+        yield "difference", result
+        yield "length", len(result)
+
+
+class ListIntersectionBlock(Block):
+    """
+    Computes the intersection of two lists (elements present in both lists).
+
+    This is useful for finding common items between two datasets,
+    such as shared tags, mutual connections, or overlapping categories.
+    """
+
+    class Input(BlockSchemaInput):
+        list_a: List[Any] = SchemaField(
+            description="The first list to intersect.",
+            placeholder="e.g., [1, 2, 3, 4, 5]",
+        )
+        list_b: List[Any] = SchemaField(
+            description="The second list to intersect.",
+            placeholder="e.g., [3, 4, 5, 6, 7]",
+        )
+
+    class Output(BlockSchemaOutput):
+        intersection: List[Any] = SchemaField(
+            description="Elements present in both list_a and list_b."
+        )
+        length: int = SchemaField(
+            description="The number of elements in the intersection."
+        )
+        error: str = SchemaField(description="Error message if the operation failed.")
+
+    def __init__(self):
+        super().__init__(
+            id="b6eb08b6-dbe3-411b-b9b4-2508cb311a1f",
+            description="Computes the intersection of two lists, returning only elements present in both.",
+            categories={BlockCategory.BASIC},
+            input_schema=ListIntersectionBlock.Input,
+            output_schema=ListIntersectionBlock.Output,
+            test_input=[
+                {"list_a": [1, 2, 3, 4, 5], "list_b": [3, 4, 5, 6, 7]},
+                {"list_a": ["a", "b", "c"], "list_b": ["c", "d", "e"]},
+                {"list_a": [1, 2], "list_b": [3, 4]},
+                {"list_a": [], "list_b": [1, 2, 3]},
+            ],
+            test_output=[
+                ("intersection", [3, 4, 5]),
+                ("length", 3),
+                ("intersection", ["c"]),
+                ("length", 1),
+                ("intersection", []),
+                ("length", 0),
+                ("intersection", []),
+                ("length", 0),
+            ],
+        )
+
+    def _compute_intersection(self, list_a: List[Any], list_b: List[Any]) -> List[Any]:
+        """Compute elements present in both lists, preserving order from list_a."""
+        b_hashes = {_make_hashable(item) for item in list_b}
+        seen: set = set()
+        result: List[Any] = []
+        for item in list_a:
+            h = _make_hashable(item)
+            if h in b_hashes and h not in seen:
+                result.append(item)
+                seen.add(h)
+        return result
+
+    async def run(self, input_data: Input, **kwargs) -> BlockOutput:
+        result = self._compute_intersection(input_data.list_a, input_data.list_b)
+        yield "intersection", result
+        yield "length", len(result)

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

@@ -17,6 +17,7 @@ from backend.blocks.jina._auth import (
 from backend.blocks.search import GetRequest
 from backend.data.model import SchemaField
 from backend.util.exceptions import BlockExecutionError
+from backend.util.request import HTTPClientError, HTTPServerError, validate_url
 
 
 class SearchTheWebBlock(Block, GetRequest):
@@ -110,7 +111,12 @@ class ExtractWebsiteContentBlock(Block, GetRequest):
         self, input_data: Input, *, credentials: JinaCredentials, **kwargs
     ) -> BlockOutput:
         if input_data.raw_content:
-            url = input_data.url
+            try:
+                parsed_url, _, _ = await validate_url(input_data.url, [])
+                url = parsed_url.geturl()
+            except ValueError as e:
+                yield "error", f"Invalid URL: {e}"
+                return
             headers = {}
         else:
             url = f"https://r.jina.ai/{input_data.url}"
@@ -119,5 +125,20 @@ class ExtractWebsiteContentBlock(Block, GetRequest):
                 "Authorization": f"Bearer {credentials.api_key.get_secret_value()}",
             }
 
-        content = await self.get_request(url, json=False, headers=headers)
+        try:
+            content = await self.get_request(url, json=False, headers=headers)
+        except HTTPClientError as e:
+            yield "error", f"Client error ({e.status_code}) fetching {input_data.url}: {e}"
+            return
+        except HTTPServerError as e:
+            yield "error", f"Server error ({e.status_code}) fetching {input_data.url}: {e}"
+            return
+        except Exception as e:
+            yield "error", f"Failed to fetch {input_data.url}: {e}"
+            return
+
+        if not content:
+            yield "error", f"No content returned for {input_data.url}"
+            return
+
         yield "content", content

autogpt_platform/backend/backend/blocks/llm.py

@@ -116,6 +116,7 @@ class LlmModel(str, Enum, metaclass=LlmModelMeta):
     CLAUDE_4_5_SONNET = "claude-sonnet-4-5-20250929"
     CLAUDE_4_5_HAIKU = "claude-haiku-4-5-20251001"
     CLAUDE_4_6_OPUS = "claude-opus-4-6"
+    CLAUDE_4_6_SONNET = "claude-sonnet-4-6"
     CLAUDE_3_HAIKU = "claude-3-haiku-20240307"
     # AI/ML API models
     AIML_API_QWEN2_5_72B = "Qwen/Qwen2.5-72B-Instruct-Turbo"
@@ -274,6 +275,9 @@ MODEL_METADATA = {
     LlmModel.CLAUDE_4_6_OPUS: ModelMetadata(
         "anthropic", 200000, 128000, "Claude Opus 4.6", "Anthropic", "Anthropic", 3
     ),  # claude-opus-4-6
+    LlmModel.CLAUDE_4_6_SONNET: ModelMetadata(
+        "anthropic", 200000, 64000, "Claude Sonnet 4.6", "Anthropic", "Anthropic", 3
+    ),  # claude-sonnet-4-6
     LlmModel.CLAUDE_4_5_OPUS: ModelMetadata(
         "anthropic", 200000, 64000, "Claude Opus 4.5", "Anthropic", "Anthropic", 3
     ),  # claude-opus-4-5-20251101

autogpt_platform/backend/backend/blocks/mcp/block.py

@@ -0,0 +1,253 @@
+"""
+MCP (Model Context Protocol) Tool Block.
+
+A single dynamic block that can connect to any MCP server, discover available tools,
+and execute them. Works like AgentExecutorBlock — the user selects a tool from a
+dropdown and the input/output schema adapts dynamically.
+"""
+
+import logging
+from typing import Any, Literal
+
+from pydantic import SecretStr
+
+from backend.blocks._base import (
+    Block,
+    BlockCategory,
+    BlockSchemaInput,
+    BlockSchemaOutput,
+    BlockType,
+)
+from backend.blocks.mcp.client import MCPClient, MCPClientError
+from backend.blocks.mcp.helpers import (
+    auto_lookup_mcp_credential,
+    normalize_mcp_url,
+    parse_mcp_content,
+)
+from backend.data.block import BlockInput, BlockOutput
+from backend.data.model import (
+    CredentialsField,
+    CredentialsMetaInput,
+    OAuth2Credentials,
+    SchemaField,
+)
+from backend.integrations.providers import ProviderName
+from backend.util.json import validate_with_jsonschema
+
+logger = logging.getLogger(__name__)
+
+TEST_CREDENTIALS = OAuth2Credentials(
+    id="test-mcp-cred",
+    provider="mcp",
+    access_token=SecretStr("mock-mcp-token"),
+    refresh_token=SecretStr("mock-refresh"),
+    scopes=[],
+    title="Mock MCP credential",
+)
+TEST_CREDENTIALS_INPUT = {
+    "provider": TEST_CREDENTIALS.provider,
+    "id": TEST_CREDENTIALS.id,
+    "type": TEST_CREDENTIALS.type,
+    "title": TEST_CREDENTIALS.title,
+}
+
+
+MCPCredentials = CredentialsMetaInput[Literal[ProviderName.MCP], Literal["oauth2"]]
+
+
+class MCPToolBlock(Block):
+    """
+    A block that connects to an MCP server, lets the user pick a tool,
+    and executes it with dynamic input/output schema.
+
+    The flow:
+    1. User provides an MCP server URL (and optional credentials)
+    2. Frontend calls the backend to get tool list from that URL
+    3. User selects a tool from a dropdown (available_tools)
+    4. The block's input schema updates to reflect the selected tool's parameters
+    5. On execution, the block calls the MCP server to run the tool
+    """
+
+    class Input(BlockSchemaInput):
+        server_url: str = SchemaField(
+            description="URL of the MCP server (Streamable HTTP endpoint)",
+            placeholder="https://mcp.example.com/mcp",
+        )
+        credentials: MCPCredentials = CredentialsField(
+            discriminator="server_url",
+            description="MCP server OAuth credentials",
+            default={},
+        )
+        selected_tool: str = SchemaField(
+            description="The MCP tool to execute",
+            placeholder="Select a tool",
+            default="",
+        )
+        tool_input_schema: dict[str, Any] = SchemaField(
+            description="JSON Schema for the selected tool's input parameters. "
+            "Populated automatically when a tool is selected.",
+            default={},
+            hidden=True,
+        )
+
+        tool_arguments: dict[str, Any] = SchemaField(
+            description="Arguments to pass to the selected MCP tool. "
+            "The fields here are defined by the tool's input schema.",
+            default={},
+        )
+
+        @classmethod
+        def get_input_schema(cls, data: BlockInput) -> dict[str, Any]:
+            """Return the tool's input schema so the builder UI renders dynamic fields."""
+            return data.get("tool_input_schema", {})
+
+        @classmethod
+        def get_input_defaults(cls, data: BlockInput) -> BlockInput:
+            """Return the current tool_arguments as defaults for the dynamic fields."""
+            return data.get("tool_arguments", {})
+
+        @classmethod
+        def get_missing_input(cls, data: BlockInput) -> set[str]:
+            """Check which required tool arguments are missing."""
+            required_fields = cls.get_input_schema(data).get("required", [])
+            tool_arguments = data.get("tool_arguments", {})
+            return set(required_fields) - set(tool_arguments)
+
+        @classmethod
+        def get_mismatch_error(cls, data: BlockInput) -> str | None:
+            """Validate tool_arguments against the tool's input schema."""
+            tool_schema = cls.get_input_schema(data)
+            if not tool_schema:
+                return None
+            tool_arguments = data.get("tool_arguments", {})
+            return validate_with_jsonschema(tool_schema, tool_arguments)
+
+    class Output(BlockSchemaOutput):
+        result: Any = SchemaField(description="The result returned by the MCP tool")
+        error: str = SchemaField(description="Error message if the tool call failed")
+
+    def __init__(self):
+        super().__init__(
+            id="a0a4b1c2-d3e4-4f56-a7b8-c9d0e1f2a3b4",
+            description="Connect to any MCP server and execute its tools. "
+            "Provide a server URL, select a tool, and pass arguments dynamically.",
+            categories={BlockCategory.DEVELOPER_TOOLS},
+            input_schema=MCPToolBlock.Input,
+            output_schema=MCPToolBlock.Output,
+            block_type=BlockType.MCP_TOOL,
+            test_credentials=TEST_CREDENTIALS,
+            test_input={
+                "server_url": "https://mcp.example.com/mcp",
+                "credentials": TEST_CREDENTIALS_INPUT,
+                "selected_tool": "get_weather",
+                "tool_input_schema": {
+                    "type": "object",
+                    "properties": {"city": {"type": "string"}},
+                    "required": ["city"],
+                },
+                "tool_arguments": {"city": "London"},
+            },
+            test_output=[
+                (
+                    "result",
+                    {"weather": "sunny", "temperature": 20},
+                ),
+            ],
+            test_mock={
+                "_call_mcp_tool": lambda *a, **kw: {
+                    "weather": "sunny",
+                    "temperature": 20,
+                },
+            },
+        )
+
+    async def _call_mcp_tool(
+        self,
+        server_url: str,
+        tool_name: str,
+        arguments: dict[str, Any],
+        auth_token: str | None = None,
+    ) -> Any:
+        """Call a tool on the MCP server. Extracted for easy mocking in tests."""
+        client = MCPClient(server_url, auth_token=auth_token)
+        await client.initialize()
+        result = await client.call_tool(tool_name, arguments)
+
+        if result.is_error:
+            error_text = ""
+            for item in result.content:
+                if item.get("type") == "text":
+                    error_text += item.get("text", "")
+            raise MCPClientError(
+                f"MCP tool '{tool_name}' returned an error: "
+                f"{error_text or 'Unknown error'}"
+            )
+
+        return parse_mcp_content(result.content)
+
+    @staticmethod
+    async def _auto_lookup_credential(
+        user_id: str, server_url: str
+    ) -> "OAuth2Credentials | None":
+        """Auto-lookup stored MCP credential for a server URL.
+
+        Delegates to :func:`~backend.blocks.mcp.helpers.auto_lookup_mcp_credential`.
+        The caller should pass a normalized URL.
+        """
+        return await auto_lookup_mcp_credential(user_id, server_url)
+
+    async def run(
+        self,
+        input_data: Input,
+        *,
+        user_id: str,
+        credentials: OAuth2Credentials | None = None,
+        **kwargs,
+    ) -> BlockOutput:
+        if not input_data.server_url:
+            yield "error", "MCP server URL is required"
+            return
+
+        if not input_data.selected_tool:
+            yield "error", "No tool selected. Please select a tool from the dropdown."
+            return
+
+        # Validate required tool arguments before calling the server.
+        # The executor-level validation is bypassed for MCP blocks because
+        # get_input_defaults() flattens tool_arguments, stripping tool_input_schema
+        # from the validation context.
+        required = set(input_data.tool_input_schema.get("required", []))
+        if required:
+            missing = required - set(input_data.tool_arguments.keys())
+            if missing:
+                yield "error", (
+                    f"Missing required argument(s): {', '.join(sorted(missing))}. "
+                    f"Please fill in all required fields marked with * in the block form."
+                )
+                return
+
+        # If no credentials were injected by the executor (e.g. legacy nodes
+        # that don't have the credentials field set), try to auto-lookup
+        # the stored MCP credential for this server URL.
+        if credentials is None:
+            credentials = await self._auto_lookup_credential(
+                user_id, normalize_mcp_url(input_data.server_url)
+            )
+
+        auth_token = (
+            credentials.access_token.get_secret_value() if credentials else None
+        )
+
+        try:
+            result = await self._call_mcp_tool(
+                server_url=input_data.server_url,
+                tool_name=input_data.selected_tool,
+                arguments=input_data.tool_arguments,
+                auth_token=auth_token,
+            )
+            yield "result", result
+        except MCPClientError as e:
+            yield "error", str(e)
+        except Exception as e:
+            logger.exception(f"MCP tool call failed: {e}")
+            yield "error", f"MCP tool call failed: {str(e)}"

autogpt_platform/backend/backend/blocks/mcp/client.py

@@ -0,0 +1,325 @@
+"""
+MCP (Model Context Protocol) HTTP client.
+
+Implements the MCP Streamable HTTP transport for listing tools and calling tools
+on remote MCP servers. Uses JSON-RPC 2.0 over HTTP POST.
+
+Handles both JSON and SSE (text/event-stream) response formats per the MCP spec.
+
+Reference: https://modelcontextprotocol.io/specification/2025-03-26/basic/transports
+"""
+
+import json
+import logging
+from dataclasses import dataclass, field
+from typing import Any
+
+from backend.util.request import Requests
+
+logger = logging.getLogger(__name__)
+
+
+@dataclass
+class MCPTool:
+    """Represents an MCP tool discovered from a server."""
+
+    name: str
+    description: str
+    input_schema: dict[str, Any]
+
+
+@dataclass
+class MCPCallResult:
+    """Result from calling an MCP tool."""
+
+    content: list[dict[str, Any]] = field(default_factory=list)
+    is_error: bool = False
+
+
+class MCPClientError(Exception):
+    """Raised when an MCP protocol error occurs."""
+
+    pass
+
+
+class MCPClient:
+    """
+    Async HTTP client for the MCP Streamable HTTP transport.
+
+    Communicates with MCP servers using JSON-RPC 2.0 over HTTP POST.
+    Supports optional Bearer token authentication.
+    """
+
+    def __init__(
+        self,
+        server_url: str,
+        auth_token: str | None = None,
+    ):
+        from backend.blocks.mcp.helpers import normalize_mcp_url
+
+        self.server_url = normalize_mcp_url(server_url)
+        self.auth_token = auth_token
+        self._request_id = 0
+        self._session_id: str | None = None
+
+    def _next_id(self) -> int:
+        self._request_id += 1
+        return self._request_id
+
+    def _build_headers(self) -> dict[str, str]:
+        headers = {
+            "Content-Type": "application/json",
+            "Accept": "application/json, text/event-stream",
+        }
+        if self.auth_token:
+            headers["Authorization"] = f"Bearer {self.auth_token}"
+        if self._session_id:
+            headers["Mcp-Session-Id"] = self._session_id
+        return headers
+
+    def _build_jsonrpc_request(
+        self, method: str, params: dict[str, Any] | None = None
+    ) -> dict[str, Any]:
+        req: dict[str, Any] = {
+            "jsonrpc": "2.0",
+            "method": method,
+            "id": self._next_id(),
+        }
+        if params is not None:
+            req["params"] = params
+        return req
+
+    @staticmethod
+    def _parse_sse_response(text: str) -> dict[str, Any]:
+        """Parse an SSE (text/event-stream) response body into JSON-RPC data.
+
+        MCP servers may return responses as SSE with format:
+            event: message
+            data: {"jsonrpc":"2.0","result":{...},"id":1}
+
+        We extract the last `data:` line that contains a JSON-RPC response
+        (i.e. has an "id" field), which is the reply to our request.
+        """
+        last_data: dict[str, Any] | None = None
+        for line in text.splitlines():
+            stripped = line.strip()
+            if stripped.startswith("data:"):
+                payload = stripped[len("data:") :].strip()
+                if not payload:
+                    continue
+                try:
+                    parsed = json.loads(payload)
+                    # Only keep JSON-RPC responses (have "id"), skip notifications
+                    if isinstance(parsed, dict) and "id" in parsed:
+                        last_data = parsed
+                except (json.JSONDecodeError, ValueError):
+                    continue
+        if last_data is None:
+            raise MCPClientError("No JSON-RPC response found in SSE stream")
+        return last_data
+
+    async def _send_request(
+        self, method: str, params: dict[str, Any] | None = None
+    ) -> Any:
+        """Send a JSON-RPC request to the MCP server and return the result.
+
+        Handles both ``application/json`` and ``text/event-stream`` responses
+        as required by the MCP Streamable HTTP transport specification.
+        """
+        payload = self._build_jsonrpc_request(method, params)
+        headers = self._build_headers()
+
+        requests = Requests(
+            raise_for_status=True,
+            extra_headers=headers,
+        )
+        response = await requests.post(self.server_url, json=payload)
+
+        # Capture session ID from response (MCP Streamable HTTP transport)
+        session_id = response.headers.get("Mcp-Session-Id")
+        if session_id:
+            self._session_id = session_id
+
+        content_type = response.headers.get("content-type", "")
+        if "text/event-stream" in content_type:
+            body = self._parse_sse_response(response.text())
+        else:
+            try:
+                body = response.json()
+            except Exception as e:
+                raise MCPClientError(
+                    f"MCP server returned non-JSON response: {e}"
+                ) from e
+
+        if not isinstance(body, dict):
+            raise MCPClientError(
+                f"MCP server returned unexpected JSON type: {type(body).__name__}"
+            )
+
+        # Handle JSON-RPC error
+        if "error" in body:
+            error = body["error"]
+            if isinstance(error, dict):
+                raise MCPClientError(
+                    f"MCP server error [{error.get('code', '?')}]: "
+                    f"{error.get('message', 'Unknown error')}"
+                )
+            raise MCPClientError(f"MCP server error: {error}")
+
+        return body.get("result")
+
+    async def _send_notification(self, method: str) -> None:
+        """Send a JSON-RPC notification (no id, no response expected)."""
+        headers = self._build_headers()
+        notification = {"jsonrpc": "2.0", "method": method}
+        requests = Requests(
+            raise_for_status=False,
+            extra_headers=headers,
+        )
+        await requests.post(self.server_url, json=notification)
+
+    async def discover_auth(self) -> dict[str, Any] | None:
+        """Probe the MCP server's OAuth metadata (RFC 9728 / MCP spec).
+
+        Returns ``None`` if the server doesn't require auth, otherwise returns
+        a dict with:
+          - ``authorization_servers``: list of authorization server URLs
+          - ``resource``: the resource indicator URL (usually the MCP endpoint)
+          - ``scopes_supported``: optional list of supported scopes
+
+        The caller can then fetch the authorization server metadata to get
+        ``authorization_endpoint``, ``token_endpoint``, etc.
+        """
+        from urllib.parse import urlparse
+
+        parsed = urlparse(self.server_url)
+        base = f"{parsed.scheme}://{parsed.netloc}"
+
+        # Build candidates for protected-resource metadata (per RFC 9728)
+        path = parsed.path.rstrip("/")
+        candidates = []
+        if path and path != "/":
+            candidates.append(f"{base}/.well-known/oauth-protected-resource{path}")
+        candidates.append(f"{base}/.well-known/oauth-protected-resource")
+
+        requests = Requests(
+            raise_for_status=False,
+        )
+        for url in candidates:
+            try:
+                resp = await requests.get(url)
+                if resp.status == 200:
+                    data = resp.json()
+                    if isinstance(data, dict) and "authorization_servers" in data:
+                        return data
+            except Exception:
+                continue
+
+        return None
+
+    async def discover_auth_server_metadata(
+        self, auth_server_url: str
+    ) -> dict[str, Any] | None:
+        """Fetch the OAuth Authorization Server Metadata (RFC 8414).
+
+        Given an authorization server URL, returns a dict with:
+          - ``authorization_endpoint``
+          - ``token_endpoint``
+          - ``registration_endpoint`` (for dynamic client registration)
+          - ``scopes_supported``
+          - ``code_challenge_methods_supported``
+          - etc.
+        """
+        from urllib.parse import urlparse
+
+        parsed = urlparse(auth_server_url)
+        base = f"{parsed.scheme}://{parsed.netloc}"
+        path = parsed.path.rstrip("/")
+
+        # Try standard metadata endpoints (RFC 8414 and OpenID Connect)
+        candidates = []
+        if path and path != "/":
+            candidates.append(f"{base}/.well-known/oauth-authorization-server{path}")
+        candidates.append(f"{base}/.well-known/oauth-authorization-server")
+        candidates.append(f"{base}/.well-known/openid-configuration")
+
+        requests = Requests(
+            raise_for_status=False,
+        )
+        for url in candidates:
+            try:
+                resp = await requests.get(url)
+                if resp.status == 200:
+                    data = resp.json()
+                    if isinstance(data, dict) and "authorization_endpoint" in data:
+                        return data
+            except Exception:
+                continue
+
+        return None
+
+    async def initialize(self) -> dict[str, Any]:
+        """
+        Send the MCP initialize request.
+
+        This is required by the MCP protocol before any other requests.
+        Returns the server's capabilities.
+        """
+        result = await self._send_request(
+            "initialize",
+            {
+                "protocolVersion": "2025-03-26",
+                "capabilities": {},
+                "clientInfo": {"name": "AutoGPT-Platform", "version": "1.0.0"},
+            },
+        )
+        # Send initialized notification (no response expected)
+        await self._send_notification("notifications/initialized")
+
+        return result or {}
+
+    async def list_tools(self) -> list[MCPTool]:
+        """
+        Discover available tools from the MCP server.
+
+        Returns a list of MCPTool objects with name, description, and input schema.
+        """
+        result = await self._send_request("tools/list")
+        if not result or "tools" not in result:
+            return []
+
+        tools = []
+        for tool_data in result["tools"]:
+            tools.append(
+                MCPTool(
+                    name=tool_data.get("name", ""),
+                    description=tool_data.get("description", ""),
+                    input_schema=tool_data.get("inputSchema", {}),
+                )
+            )
+        return tools
+
+    async def call_tool(
+        self, tool_name: str, arguments: dict[str, Any]
+    ) -> MCPCallResult:
+        """
+        Call a tool on the MCP server.
+
+        Args:
+            tool_name: The name of the tool to call.
+            arguments: The arguments to pass to the tool.
+
+        Returns:
+            MCPCallResult with the tool's response content.
+        """
+        result = await self._send_request(
+            "tools/call",
+            {"name": tool_name, "arguments": arguments},
+        )
+        if not result:
+            return MCPCallResult(is_error=True)
+
+        return MCPCallResult(
+            content=result.get("content", []),
+            is_error=result.get("isError", False),
+        )

autogpt_platform/backend/backend/blocks/mcp/helpers.py

@@ -0,0 +1,117 @@
+"""Shared MCP helpers used by blocks, copilot tools, and API routes."""
+
+from __future__ import annotations
+
+import json
+import logging
+from typing import TYPE_CHECKING, Any
+from urllib.parse import urlparse
+
+if TYPE_CHECKING:
+    from backend.data.model import OAuth2Credentials
+
+logger = logging.getLogger(__name__)
+
+
+def normalize_mcp_url(url: str) -> str:
+    """Normalize an MCP server URL for consistent credential matching.
+
+    Strips leading/trailing whitespace and a single trailing slash so that
+    ``https://mcp.example.com/`` and ``https://mcp.example.com`` resolve to
+    the same stored credential.
+    """
+    return url.strip().rstrip("/")
+
+
+def server_host(server_url: str) -> str:
+    """Extract the hostname from a server URL for display purposes.
+
+    Uses ``parsed.hostname`` (never ``netloc``) to strip any embedded
+    username/password before surfacing the value in UI messages.
+    """
+    try:
+        parsed = urlparse(server_url)
+        return parsed.hostname or server_url
+    except Exception:
+        return server_url
+
+
+def parse_mcp_content(content: list[dict[str, Any]]) -> Any:
+    """Parse MCP tool response content into a plain Python value.
+
+    - text items: parsed as JSON when possible, kept as str otherwise
+    - image items: kept as ``{type, data, mimeType}`` dict for frontend rendering
+    - resource items: unwrapped to their resource payload dict
+
+    Single-item responses are unwrapped from the list; multiple items are
+    returned as a list; empty content returns ``None``.
+    """
+    output_parts: list[Any] = []
+    for item in content:
+        item_type = item.get("type")
+        if item_type == "text":
+            text = item.get("text", "")
+            try:
+                output_parts.append(json.loads(text))
+            except (json.JSONDecodeError, ValueError):
+                output_parts.append(text)
+        elif item_type == "image":
+            output_parts.append(
+                {
+                    "type": "image",
+                    "data": item.get("data"),
+                    "mimeType": item.get("mimeType"),
+                }
+            )
+        elif item_type == "resource":
+            output_parts.append(item.get("resource", {}))
+
+    if len(output_parts) == 1:
+        return output_parts[0]
+    return output_parts or None
+
+
+async def auto_lookup_mcp_credential(
+    user_id: str, server_url: str
+) -> OAuth2Credentials | None:
+    """Look up the best stored MCP credential for *server_url*.
+
+    The caller should pass a **normalized** URL (via :func:`normalize_mcp_url`)
+    so the comparison with ``mcp_server_url`` in credential metadata matches.
+
+    Returns the credential with the latest ``access_token_expires_at``, refreshed
+    if needed, or ``None`` when no match is found.
+    """
+    from backend.data.model import OAuth2Credentials
+    from backend.integrations.creds_manager import IntegrationCredentialsManager
+    from backend.integrations.providers import ProviderName
+
+    try:
+        mgr = IntegrationCredentialsManager()
+        mcp_creds = await mgr.store.get_creds_by_provider(
+            user_id, ProviderName.MCP.value
+        )
+        # Collect all matching credentials and pick the best one.
+        # Primary sort: latest access_token_expires_at (tokens with expiry
+        # are preferred over non-expiring ones).  Secondary sort: last in
+        # iteration order, which corresponds to the most recently created
+        # row — this acts as a tiebreaker when multiple bearer tokens have
+        # no expiry (e.g. after a failed old-credential cleanup).
+        best: OAuth2Credentials | None = None
+        for cred in mcp_creds:
+            if (
+                isinstance(cred, OAuth2Credentials)
+                and (cred.metadata or {}).get("mcp_server_url") == server_url
+            ):
+                if best is None or (
+                    (cred.access_token_expires_at or 0)
+                    >= (best.access_token_expires_at or 0)
+                ):
+                    best = cred
+        if best:
+            best = await mgr.refresh_if_needed(user_id, best)
+            logger.info("Auto-resolved MCP credential %s for %s", best.id, server_url)
+        return best
+    except Exception:
+        logger.warning("Auto-lookup MCP credential failed", exc_info=True)
+        return None

autogpt_platform/backend/backend/blocks/mcp/oauth.py

@@ -0,0 +1,204 @@
+"""
+MCP OAuth handler for MCP servers that use OAuth 2.1 authorization.
+
+Unlike other OAuth handlers (GitHub, Google, etc.) where endpoints are fixed,
+MCP servers have dynamic endpoints discovered via RFC 9728 / RFC 8414 metadata.
+This handler accepts those endpoints at construction time.
+"""
+
+import logging
+import time
+import urllib.parse
+from typing import ClassVar, Optional
+
+from pydantic import SecretStr
+
+from backend.data.model import OAuth2Credentials
+from backend.integrations.oauth.base import BaseOAuthHandler
+from backend.integrations.providers import ProviderName
+from backend.util.request import Requests
+
+logger = logging.getLogger(__name__)
+
+
+class MCPOAuthHandler(BaseOAuthHandler):
+    """
+    OAuth handler for MCP servers with dynamically-discovered endpoints.
+
+    Construction requires the authorization and token endpoint URLs,
+    which are obtained via MCP OAuth metadata discovery
+    (``MCPClient.discover_auth`` + ``discover_auth_server_metadata``).
+    """
+
+    PROVIDER_NAME: ClassVar[ProviderName | str] = ProviderName.MCP
+    DEFAULT_SCOPES: ClassVar[list[str]] = []
+
+    def __init__(
+        self,
+        client_id: str,
+        client_secret: str,
+        redirect_uri: str,
+        *,
+        authorize_url: str,
+        token_url: str,
+        revoke_url: str | None = None,
+        resource_url: str | None = None,
+    ):
+        self.client_id = client_id
+        self.client_secret = client_secret
+        self.redirect_uri = redirect_uri
+        self.authorize_url = authorize_url
+        self.token_url = token_url
+        self.revoke_url = revoke_url
+        self.resource_url = resource_url
+
+    def get_login_url(
+        self,
+        scopes: list[str],
+        state: str,
+        code_challenge: Optional[str],
+    ) -> str:
+        scopes = self.handle_default_scopes(scopes)
+
+        params: dict[str, str] = {
+            "response_type": "code",
+            "client_id": self.client_id,
+            "redirect_uri": self.redirect_uri,
+            "state": state,
+        }
+        if scopes:
+            params["scope"] = " ".join(scopes)
+        # PKCE (S256) — included when the caller provides a code_challenge
+        if code_challenge:
+            params["code_challenge"] = code_challenge
+            params["code_challenge_method"] = "S256"
+        # MCP spec requires resource indicator (RFC 8707)
+        if self.resource_url:
+            params["resource"] = self.resource_url
+
+        return f"{self.authorize_url}?{urllib.parse.urlencode(params)}"
+
+    async def exchange_code_for_tokens(
+        self,
+        code: str,
+        scopes: list[str],
+        code_verifier: Optional[str],
+    ) -> OAuth2Credentials:
+        data: dict[str, str] = {
+            "grant_type": "authorization_code",
+            "code": code,
+            "redirect_uri": self.redirect_uri,
+            "client_id": self.client_id,
+        }
+        if self.client_secret:
+            data["client_secret"] = self.client_secret
+        if code_verifier:
+            data["code_verifier"] = code_verifier
+        if self.resource_url:
+            data["resource"] = self.resource_url
+
+        response = await Requests(raise_for_status=True).post(
+            self.token_url,
+            data=data,
+            headers={"Content-Type": "application/x-www-form-urlencoded"},
+        )
+        tokens = response.json()
+
+        if "error" in tokens:
+            raise RuntimeError(
+                f"Token exchange failed: {tokens.get('error_description', tokens['error'])}"
+            )
+
+        if "access_token" not in tokens:
+            raise RuntimeError("OAuth token response missing 'access_token' field")
+
+        now = int(time.time())
+        expires_in = tokens.get("expires_in")
+
+        return OAuth2Credentials(
+            provider=self.PROVIDER_NAME,
+            title=None,
+            access_token=SecretStr(tokens["access_token"]),
+            refresh_token=(
+                SecretStr(tokens["refresh_token"])
+                if tokens.get("refresh_token")
+                else None
+            ),
+            access_token_expires_at=now + expires_in if expires_in else None,
+            refresh_token_expires_at=None,
+            scopes=scopes,
+            metadata={
+                "mcp_token_url": self.token_url,
+                "mcp_resource_url": self.resource_url,
+            },
+        )
+
+    async def _refresh_tokens(
+        self, credentials: OAuth2Credentials
+    ) -> OAuth2Credentials:
+        if not credentials.refresh_token:
+            raise ValueError("No refresh token available for MCP OAuth credentials")
+
+        data: dict[str, str] = {
+            "grant_type": "refresh_token",
+            "refresh_token": credentials.refresh_token.get_secret_value(),
+            "client_id": self.client_id,
+        }
+        if self.client_secret:
+            data["client_secret"] = self.client_secret
+        if self.resource_url:
+            data["resource"] = self.resource_url
+
+        response = await Requests(raise_for_status=True).post(
+            self.token_url,
+            data=data,
+            headers={"Content-Type": "application/x-www-form-urlencoded"},
+        )
+        tokens = response.json()
+
+        if "error" in tokens:
+            raise RuntimeError(
+                f"Token refresh failed: {tokens.get('error_description', tokens['error'])}"
+            )
+
+        if "access_token" not in tokens:
+            raise RuntimeError("OAuth refresh response missing 'access_token' field")
+
+        now = int(time.time())
+        expires_in = tokens.get("expires_in")
+
+        return OAuth2Credentials(
+            id=credentials.id,
+            provider=self.PROVIDER_NAME,
+            title=credentials.title,
+            access_token=SecretStr(tokens["access_token"]),
+            refresh_token=(
+                SecretStr(tokens["refresh_token"])
+                if tokens.get("refresh_token")
+                else credentials.refresh_token
+            ),
+            access_token_expires_at=now + expires_in if expires_in else None,
+            refresh_token_expires_at=credentials.refresh_token_expires_at,
+            scopes=credentials.scopes,
+            metadata=credentials.metadata,
+        )
+
+    async def revoke_tokens(self, credentials: OAuth2Credentials) -> bool:
+        if not self.revoke_url:
+            return False
+
+        try:
+            data = {
+                "token": credentials.access_token.get_secret_value(),
+                "token_type_hint": "access_token",
+                "client_id": self.client_id,
+            }
+            await Requests().post(
+                self.revoke_url,
+                data=data,
+                headers={"Content-Type": "application/x-www-form-urlencoded"},
+            )
+            return True
+        except Exception:
+            logger.warning("Failed to revoke MCP OAuth tokens", exc_info=True)
+            return False

autogpt_platform/backend/backend/blocks/mcp/test_e2e.py

@@ -0,0 +1,109 @@
+"""
+End-to-end tests against a real public MCP server.
+
+These tests hit the OpenAI docs MCP server (https://developers.openai.com/mcp)
+which is publicly accessible without authentication and returns SSE responses.
+
+Mark: These are tagged with ``@pytest.mark.e2e`` so they can be run/skipped
+independently of the rest of the test suite (they require network access).
+"""
+
+import json
+import os
+
+import pytest
+
+from backend.blocks.mcp.client import MCPClient
+
+# Public MCP server that requires no authentication
+OPENAI_DOCS_MCP_URL = "https://developers.openai.com/mcp"
+
+# Skip all tests in this module unless RUN_E2E env var is set
+pytestmark = pytest.mark.skipif(
+    not os.environ.get("RUN_E2E"), reason="set RUN_E2E=1 to run e2e tests"
+)
+
+
+class TestRealMCPServer:
+    """Tests against the live OpenAI docs MCP server."""
+
+    @pytest.mark.asyncio(loop_scope="session")
+    async def test_initialize(self):
+        """Verify we can complete the MCP handshake with a real server."""
+        client = MCPClient(OPENAI_DOCS_MCP_URL)
+        result = await client.initialize()
+
+        assert result["protocolVersion"] == "2025-03-26"
+        assert "serverInfo" in result
+        assert result["serverInfo"]["name"] == "openai-docs-mcp"
+        assert "tools" in result.get("capabilities", {})
+
+    @pytest.mark.asyncio(loop_scope="session")
+    async def test_list_tools(self):
+        """Verify we can discover tools from a real MCP server."""
+        client = MCPClient(OPENAI_DOCS_MCP_URL)
+        await client.initialize()
+        tools = await client.list_tools()
+
+        assert len(tools) >= 3  # server has at least 5 tools as of writing
+
+        tool_names = {t.name for t in tools}
+        # These tools are documented and should be stable
+        assert "search_openai_docs" in tool_names
+        assert "list_openai_docs" in tool_names
+        assert "fetch_openai_doc" in tool_names
+
+        # Verify schema structure
+        search_tool = next(t for t in tools if t.name == "search_openai_docs")
+        assert "query" in search_tool.input_schema.get("properties", {})
+        assert "query" in search_tool.input_schema.get("required", [])
+
+    @pytest.mark.asyncio(loop_scope="session")
+    async def test_call_tool_list_api_endpoints(self):
+        """Call the list_api_endpoints tool and verify we get real data."""
+        client = MCPClient(OPENAI_DOCS_MCP_URL)
+        await client.initialize()
+        result = await client.call_tool("list_api_endpoints", {})
+
+        assert not result.is_error
+        assert len(result.content) >= 1
+        assert result.content[0]["type"] == "text"
+
+        data = json.loads(result.content[0]["text"])
+        assert "paths" in data or "urls" in data
+        # The OpenAI API should have many endpoints
+        total = data.get("total", len(data.get("paths", [])))
+        assert total > 50
+
+    @pytest.mark.asyncio(loop_scope="session")
+    async def test_call_tool_search(self):
+        """Search for docs and verify we get results."""
+        client = MCPClient(OPENAI_DOCS_MCP_URL)
+        await client.initialize()
+        result = await client.call_tool(
+            "search_openai_docs", {"query": "chat completions", "limit": 3}
+        )
+
+        assert not result.is_error
+        assert len(result.content) >= 1
+
+    @pytest.mark.asyncio(loop_scope="session")
+    async def test_sse_response_handling(self):
+        """Verify the client correctly handles SSE responses from a real server.
+
+        This is the key test — our local test server returns JSON,
+        but real MCP servers typically return SSE. This proves the
+        SSE parsing works end-to-end.
+        """
+        client = MCPClient(OPENAI_DOCS_MCP_URL)
+        # initialize() internally calls _send_request which must parse SSE
+        result = await client.initialize()
+
+        # If we got here without error, SSE parsing works
+        assert isinstance(result, dict)
+        assert "protocolVersion" in result
+
+        # Also verify list_tools works (another SSE response)
+        tools = await client.list_tools()
+        assert len(tools) > 0
+        assert all(hasattr(t, "name") for t in tools)

autogpt_platform/backend/backend/blocks/mcp/test_helpers.py

@@ -0,0 +1,98 @@
+"""Unit tests for the shared MCP helpers."""
+
+from backend.blocks.mcp.helpers import normalize_mcp_url, parse_mcp_content, server_host
+
+# ---------------------------------------------------------------------------
+# normalize_mcp_url
+# ---------------------------------------------------------------------------
+
+
+def test_normalize_trailing_slash():
+    assert normalize_mcp_url("https://mcp.example.com/") == "https://mcp.example.com"
+
+
+def test_normalize_whitespace():
+    assert normalize_mcp_url("  https://mcp.example.com  ") == "https://mcp.example.com"
+
+
+def test_normalize_both():
+    assert (
+        normalize_mcp_url("  https://mcp.example.com/  ") == "https://mcp.example.com"
+    )
+
+
+def test_normalize_noop():
+    assert normalize_mcp_url("https://mcp.example.com") == "https://mcp.example.com"
+
+
+def test_normalize_path_with_trailing_slash():
+    assert (
+        normalize_mcp_url("https://mcp.example.com/path/")
+        == "https://mcp.example.com/path"
+    )
+
+
+# ---------------------------------------------------------------------------
+# server_host
+# ---------------------------------------------------------------------------
+
+
+def test_server_host_standard_url():
+    assert server_host("https://mcp.example.com/mcp") == "mcp.example.com"
+
+
+def test_server_host_strips_credentials():
+    """hostname must not expose user:pass."""
+    assert server_host("https://user:secret@mcp.example.com/mcp") == "mcp.example.com"
+
+
+def test_server_host_with_port():
+    """Port should not appear in hostname (hostname strips it)."""
+    assert server_host("https://mcp.example.com:8080/mcp") == "mcp.example.com"
+
+
+def test_server_host_fallback():
+    """Falls back to the raw string for un-parseable URLs."""
+    assert server_host("not-a-url") == "not-a-url"
+
+
+# ---------------------------------------------------------------------------
+# parse_mcp_content
+# ---------------------------------------------------------------------------
+
+
+def test_parse_text_plain():
+    assert parse_mcp_content([{"type": "text", "text": "hello world"}]) == "hello world"
+
+
+def test_parse_text_json():
+    content = [{"type": "text", "text": '{"status": "ok", "count": 42}'}]
+    assert parse_mcp_content(content) == {"status": "ok", "count": 42}
+
+
+def test_parse_image():
+    content = [{"type": "image", "data": "abc123==", "mimeType": "image/png"}]
+    assert parse_mcp_content(content) == {
+        "type": "image",
+        "data": "abc123==",
+        "mimeType": "image/png",
+    }
+
+
+def test_parse_resource():
+    content = [
+        {"type": "resource", "resource": {"uri": "file:///tmp/out.txt", "text": "hi"}}
+    ]
+    assert parse_mcp_content(content) == {"uri": "file:///tmp/out.txt", "text": "hi"}
+
+
+def test_parse_multi_item():
+    content = [
+        {"type": "text", "text": "first"},
+        {"type": "text", "text": "second"},
+    ]
+    assert parse_mcp_content(content) == ["first", "second"]
+
+
+def test_parse_empty():
+    assert parse_mcp_content([]) is None

autogpt_platform/backend/backend/blocks/mcp/test_integration.py

@@ -0,0 +1,389 @@
+"""
+Integration tests for MCP client and MCPToolBlock against a real HTTP server.
+
+These tests spin up a local MCP test server and run the full client/block flow
+against it — no mocking, real HTTP requests.
+"""
+
+import asyncio
+import json
+import threading
+from unittest.mock import patch
+
+import pytest
+from aiohttp import web
+from pydantic import SecretStr
+
+from backend.blocks.mcp.block import MCPToolBlock
+from backend.blocks.mcp.client import MCPClient
+from backend.blocks.mcp.test_server import create_test_mcp_app
+from backend.data.model import OAuth2Credentials
+
+MOCK_USER_ID = "test-user-integration"
+
+
+class _MCPTestServer:
+    """
+    Run an MCP test server in a background thread with its own event loop.
+    This avoids event loop conflicts with pytest-asyncio.
+    """
+
+    def __init__(self, auth_token: str | None = None):
+        self.auth_token = auth_token
+        self.url: str = ""
+        self._runner: web.AppRunner | None = None
+        self._loop: asyncio.AbstractEventLoop | None = None
+        self._thread: threading.Thread | None = None
+        self._started = threading.Event()
+
+    def _run(self):
+        self._loop = asyncio.new_event_loop()
+        asyncio.set_event_loop(self._loop)
+        self._loop.run_until_complete(self._start())
+        self._started.set()
+        self._loop.run_forever()
+
+    async def _start(self):
+        app = create_test_mcp_app(auth_token=self.auth_token)
+        self._runner = web.AppRunner(app)
+        await self._runner.setup()
+        site = web.TCPSite(self._runner, "127.0.0.1", 0)
+        await site.start()
+        port = site._server.sockets[0].getsockname()[1]  # type: ignore[union-attr]
+        self.url = f"http://127.0.0.1:{port}/mcp"
+
+    def start(self):
+        self._thread = threading.Thread(target=self._run, daemon=True)
+        self._thread.start()
+        if not self._started.wait(timeout=5):
+            raise RuntimeError("MCP test server failed to start within 5 seconds")
+        return self
+
+    def stop(self):
+        if self._loop and self._runner:
+            asyncio.run_coroutine_threadsafe(self._runner.cleanup(), self._loop).result(
+                timeout=5
+            )
+            self._loop.call_soon_threadsafe(self._loop.stop)
+        if self._thread:
+            self._thread.join(timeout=5)
+
+
+@pytest.fixture(scope="module")
+def mcp_server():
+    """Start a local MCP test server in a background thread."""
+    server = _MCPTestServer()
+    server.start()
+    yield server.url
+    server.stop()
+
+
+@pytest.fixture(scope="module")
+def mcp_server_with_auth():
+    """Start a local MCP test server with auth in a background thread."""
+    server = _MCPTestServer(auth_token="test-secret-token")
+    server.start()
+    yield server.url, "test-secret-token"
+    server.stop()
+
+
+@pytest.fixture(autouse=True)
+def _allow_localhost():
+    """
+    Allow 127.0.0.1 through SSRF protection for integration tests.
+
+    The Requests class blocks private IPs by default. We patch the Requests
+    constructor to always include 127.0.0.1 as a trusted origin so the local
+    test server is reachable.
+    """
+    from backend.util.request import Requests
+
+    original_init = Requests.__init__
+
+    def patched_init(self, *args, **kwargs):
+        trusted = list(kwargs.get("trusted_origins") or [])
+        trusted.append("http://127.0.0.1")
+        kwargs["trusted_origins"] = trusted
+        original_init(self, *args, **kwargs)
+
+    with patch.object(Requests, "__init__", patched_init):
+        yield
+
+
+def _make_client(url: str, auth_token: str | None = None) -> MCPClient:
+    """Create an MCPClient for integration tests."""
+    return MCPClient(url, auth_token=auth_token)
+
+
+# ── MCPClient integration tests ──────────────────────────────────────
+
+
+class TestMCPClientIntegration:
+    """Test MCPClient against a real local MCP server."""
+
+    @pytest.mark.asyncio(loop_scope="session")
+    async def test_initialize(self, mcp_server):
+        client = _make_client(mcp_server)
+        result = await client.initialize()
+
+        assert result["protocolVersion"] == "2025-03-26"
+        assert result["serverInfo"]["name"] == "test-mcp-server"
+        assert "tools" in result["capabilities"]
+
+    @pytest.mark.asyncio(loop_scope="session")
+    async def test_list_tools(self, mcp_server):
+        client = _make_client(mcp_server)
+        await client.initialize()
+        tools = await client.list_tools()
+
+        assert len(tools) == 3
+
+        tool_names = {t.name for t in tools}
+        assert tool_names == {"get_weather", "add_numbers", "echo"}
+
+        # Check get_weather schema
+        weather = next(t for t in tools if t.name == "get_weather")
+        assert weather.description == "Get current weather for a city"
+        assert "city" in weather.input_schema["properties"]
+        assert weather.input_schema["required"] == ["city"]
+
+        # Check add_numbers schema
+        add = next(t for t in tools if t.name == "add_numbers")
+        assert "a" in add.input_schema["properties"]
+        assert "b" in add.input_schema["properties"]
+
+    @pytest.mark.asyncio(loop_scope="session")
+    async def test_call_tool_get_weather(self, mcp_server):
+        client = _make_client(mcp_server)
+        await client.initialize()
+        result = await client.call_tool("get_weather", {"city": "London"})
+
+        assert not result.is_error
+        assert len(result.content) == 1
+        assert result.content[0]["type"] == "text"
+
+        data = json.loads(result.content[0]["text"])
+        assert data["city"] == "London"
+        assert data["temperature"] == 22
+        assert data["condition"] == "sunny"
+
+    @pytest.mark.asyncio(loop_scope="session")
+    async def test_call_tool_add_numbers(self, mcp_server):
+        client = _make_client(mcp_server)
+        await client.initialize()
+        result = await client.call_tool("add_numbers", {"a": 3, "b": 7})
+
+        assert not result.is_error
+        data = json.loads(result.content[0]["text"])
+        assert data["result"] == 10
+
+    @pytest.mark.asyncio(loop_scope="session")
+    async def test_call_tool_echo(self, mcp_server):
+        client = _make_client(mcp_server)
+        await client.initialize()
+        result = await client.call_tool("echo", {"message": "Hello MCP!"})
+
+        assert not result.is_error
+        assert result.content[0]["text"] == "Hello MCP!"
+
+    @pytest.mark.asyncio(loop_scope="session")
+    async def test_call_unknown_tool(self, mcp_server):
+        client = _make_client(mcp_server)
+        await client.initialize()
+        result = await client.call_tool("nonexistent_tool", {})
+
+        assert result.is_error
+        assert "Unknown tool" in result.content[0]["text"]
+
+    @pytest.mark.asyncio(loop_scope="session")
+    async def test_auth_success(self, mcp_server_with_auth):
+        url, token = mcp_server_with_auth
+        client = _make_client(url, auth_token=token)
+        result = await client.initialize()
+
+        assert result["protocolVersion"] == "2025-03-26"
+
+        tools = await client.list_tools()
+        assert len(tools) == 3
+
+    @pytest.mark.asyncio(loop_scope="session")
+    async def test_auth_failure(self, mcp_server_with_auth):
+        url, _ = mcp_server_with_auth
+        client = _make_client(url, auth_token="wrong-token")
+
+        with pytest.raises(Exception):
+            await client.initialize()
+
+    @pytest.mark.asyncio(loop_scope="session")
+    async def test_auth_missing(self, mcp_server_with_auth):
+        url, _ = mcp_server_with_auth
+        client = _make_client(url)
+
+        with pytest.raises(Exception):
+            await client.initialize()
+
+
+# ── MCPToolBlock integration tests ───────────────────────────────────
+
+
+class TestMCPToolBlockIntegration:
+    """Test MCPToolBlock end-to-end against a real local MCP server."""
+
+    @pytest.mark.asyncio(loop_scope="session")
+    async def test_full_flow_get_weather(self, mcp_server):
+        """Full flow: discover tools, select one, execute it."""
+        # Step 1: Discover tools (simulating what the frontend/API would do)
+        client = _make_client(mcp_server)
+        await client.initialize()
+        tools = await client.list_tools()
+        assert len(tools) == 3
+
+        # Step 2: User selects "get_weather" and we get its schema
+        weather_tool = next(t for t in tools if t.name == "get_weather")
+
+        # Step 3: Execute the block — no credentials (public server)
+        block = MCPToolBlock()
+        input_data = MCPToolBlock.Input(
+            server_url=mcp_server,
+            selected_tool="get_weather",
+            tool_input_schema=weather_tool.input_schema,
+            tool_arguments={"city": "Paris"},
+        )
+
+        outputs = []
+        async for name, data in block.run(input_data, user_id=MOCK_USER_ID):
+            outputs.append((name, data))
+
+        assert len(outputs) == 1
+        assert outputs[0][0] == "result"
+        result = outputs[0][1]
+        assert result["city"] == "Paris"
+        assert result["temperature"] == 22
+        assert result["condition"] == "sunny"
+
+    @pytest.mark.asyncio(loop_scope="session")
+    async def test_full_flow_add_numbers(self, mcp_server):
+        """Full flow for add_numbers tool."""
+        client = _make_client(mcp_server)
+        await client.initialize()
+        tools = await client.list_tools()
+        add_tool = next(t for t in tools if t.name == "add_numbers")
+
+        block = MCPToolBlock()
+        input_data = MCPToolBlock.Input(
+            server_url=mcp_server,
+            selected_tool="add_numbers",
+            tool_input_schema=add_tool.input_schema,
+            tool_arguments={"a": 42, "b": 58},
+        )
+
+        outputs = []
+        async for name, data in block.run(input_data, user_id=MOCK_USER_ID):
+            outputs.append((name, data))
+
+        assert len(outputs) == 1
+        assert outputs[0][0] == "result"
+        assert outputs[0][1]["result"] == 100
+
+    @pytest.mark.asyncio(loop_scope="session")
+    async def test_full_flow_echo_plain_text(self, mcp_server):
+        """Verify plain text (non-JSON) responses work."""
+        block = MCPToolBlock()
+        input_data = MCPToolBlock.Input(
+            server_url=mcp_server,
+            selected_tool="echo",
+            tool_input_schema={
+                "type": "object",
+                "properties": {"message": {"type": "string"}},
+                "required": ["message"],
+            },
+            tool_arguments={"message": "Hello from AutoGPT!"},
+        )
+
+        outputs = []
+        async for name, data in block.run(input_data, user_id=MOCK_USER_ID):
+            outputs.append((name, data))
+
+        assert len(outputs) == 1
+        assert outputs[0][0] == "result"
+        assert outputs[0][1] == "Hello from AutoGPT!"
+
+    @pytest.mark.asyncio(loop_scope="session")
+    async def test_full_flow_unknown_tool_yields_error(self, mcp_server):
+        """Calling an unknown tool should yield an error output."""
+        block = MCPToolBlock()
+        input_data = MCPToolBlock.Input(
+            server_url=mcp_server,
+            selected_tool="nonexistent_tool",
+            tool_arguments={},
+        )
+
+        outputs = []
+        async for name, data in block.run(input_data, user_id=MOCK_USER_ID):
+            outputs.append((name, data))
+
+        assert len(outputs) == 1
+        assert outputs[0][0] == "error"
+        assert "returned an error" in outputs[0][1]
+
+    @pytest.mark.asyncio(loop_scope="session")
+    async def test_full_flow_with_auth(self, mcp_server_with_auth):
+        """Full flow with authentication via credentials kwarg."""
+        url, token = mcp_server_with_auth
+
+        block = MCPToolBlock()
+        input_data = MCPToolBlock.Input(
+            server_url=url,
+            selected_tool="echo",
+            tool_input_schema={
+                "type": "object",
+                "properties": {"message": {"type": "string"}},
+                "required": ["message"],
+            },
+            tool_arguments={"message": "Authenticated!"},
+        )
+
+        # Pass credentials via the standard kwarg (as the executor would)
+        test_creds = OAuth2Credentials(
+            id="test-cred",
+            provider="mcp",
+            access_token=SecretStr(token),
+            refresh_token=SecretStr(""),
+            scopes=[],
+            title="Test MCP credential",
+        )
+
+        outputs = []
+        async for name, data in block.run(
+            input_data, user_id=MOCK_USER_ID, credentials=test_creds
+        ):
+            outputs.append((name, data))
+
+        assert len(outputs) == 1
+        assert outputs[0][0] == "result"
+        assert outputs[0][1] == "Authenticated!"
+
+    @pytest.mark.asyncio(loop_scope="session")
+    async def test_no_credentials_runs_without_auth(self, mcp_server):
+        """Block runs without auth when no credentials are provided."""
+        block = MCPToolBlock()
+        input_data = MCPToolBlock.Input(
+            server_url=mcp_server,
+            selected_tool="echo",
+            tool_input_schema={
+                "type": "object",
+                "properties": {"message": {"type": "string"}},
+                "required": ["message"],
+            },
+            tool_arguments={"message": "No auth needed"},
+        )
+
+        outputs = []
+        async for name, data in block.run(
+            input_data, user_id=MOCK_USER_ID, credentials=None
+        ):
+            outputs.append((name, data))
+
+        assert len(outputs) == 1
+        assert outputs[0][0] == "result"
+        assert outputs[0][1] == "No auth needed"

autogpt_platform/backend/backend/blocks/mcp/test_mcp.py

@@ -0,0 +1,619 @@
+"""
+Tests for MCP client and MCPToolBlock.
+"""
+
+import json
+from unittest.mock import AsyncMock, patch
+
+import pytest
+
+from backend.blocks.mcp.block import MCPToolBlock
+from backend.blocks.mcp.client import MCPCallResult, MCPClient, MCPClientError
+from backend.util.test import execute_block_test
+
+# ── SSE parsing unit tests ───────────────────────────────────────────
+
+
+class TestSSEParsing:
+    """Tests for SSE (text/event-stream) response parsing."""
+
+    def test_parse_sse_simple(self):
+        sse = (
+            "event: message\n"
+            'data: {"jsonrpc":"2.0","result":{"tools":[]},"id":1}\n'
+            "\n"
+        )
+        body = MCPClient._parse_sse_response(sse)
+        assert body["result"] == {"tools": []}
+        assert body["id"] == 1
+
+    def test_parse_sse_with_notifications(self):
+        """SSE streams can contain notifications (no id) before the response."""
+        sse = (
+            "event: message\n"
+            'data: {"jsonrpc":"2.0","method":"some/notification"}\n'
+            "\n"
+            "event: message\n"
+            'data: {"jsonrpc":"2.0","result":{"ok":true},"id":2}\n'
+            "\n"
+        )
+        body = MCPClient._parse_sse_response(sse)
+        assert body["result"] == {"ok": True}
+        assert body["id"] == 2
+
+    def test_parse_sse_error_response(self):
+        sse = (
+            "event: message\n"
+            'data: {"jsonrpc":"2.0","error":{"code":-32600,"message":"Bad Request"},"id":1}\n'
+        )
+        body = MCPClient._parse_sse_response(sse)
+        assert "error" in body
+        assert body["error"]["code"] == -32600
+
+    def test_parse_sse_no_data_raises(self):
+        with pytest.raises(MCPClientError, match="No JSON-RPC response found"):
+            MCPClient._parse_sse_response("event: message\n\n")
+
+    def test_parse_sse_empty_raises(self):
+        with pytest.raises(MCPClientError, match="No JSON-RPC response found"):
+            MCPClient._parse_sse_response("")
+
+    def test_parse_sse_ignores_non_data_lines(self):
+        sse = (
+            ": comment line\n"
+            "event: message\n"
+            "id: 123\n"
+            'data: {"jsonrpc":"2.0","result":"ok","id":1}\n'
+            "\n"
+        )
+        body = MCPClient._parse_sse_response(sse)
+        assert body["result"] == "ok"
+
+    def test_parse_sse_uses_last_response(self):
+        """If multiple responses exist, use the last one."""
+        sse = (
+            'data: {"jsonrpc":"2.0","result":"first","id":1}\n'
+            "\n"
+            'data: {"jsonrpc":"2.0","result":"second","id":2}\n'
+            "\n"
+        )
+        body = MCPClient._parse_sse_response(sse)
+        assert body["result"] == "second"
+
+
+# ── MCPClient unit tests ─────────────────────────────────────────────
+
+
+class TestMCPClient:
+    """Tests for the MCP HTTP client."""
+
+    def test_build_headers_without_auth(self):
+        client = MCPClient("https://mcp.example.com")
+        headers = client._build_headers()
+        assert "Authorization" not in headers
+        assert headers["Content-Type"] == "application/json"
+
+    def test_build_headers_with_auth(self):
+        client = MCPClient("https://mcp.example.com", auth_token="my-token")
+        headers = client._build_headers()
+        assert headers["Authorization"] == "Bearer my-token"
+
+    def test_build_jsonrpc_request(self):
+        client = MCPClient("https://mcp.example.com")
+        req = client._build_jsonrpc_request("tools/list")
+        assert req["jsonrpc"] == "2.0"
+        assert req["method"] == "tools/list"
+        assert "id" in req
+        assert "params" not in req
+
+    def test_build_jsonrpc_request_with_params(self):
+        client = MCPClient("https://mcp.example.com")
+        req = client._build_jsonrpc_request(
+            "tools/call", {"name": "test", "arguments": {"x": 1}}
+        )
+        assert req["params"] == {"name": "test", "arguments": {"x": 1}}
+
+    def test_request_id_increments(self):
+        client = MCPClient("https://mcp.example.com")
+        req1 = client._build_jsonrpc_request("tools/list")
+        req2 = client._build_jsonrpc_request("tools/list")
+        assert req2["id"] > req1["id"]
+
+    def test_server_url_trailing_slash_stripped(self):
+        client = MCPClient("https://mcp.example.com/mcp/")
+        assert client.server_url == "https://mcp.example.com/mcp"
+
+    @pytest.mark.asyncio(loop_scope="session")
+    async def test_send_request_success(self):
+        client = MCPClient("https://mcp.example.com")
+
+        mock_response = AsyncMock()
+        mock_response.json.return_value = {
+            "jsonrpc": "2.0",
+            "result": {"tools": []},
+            "id": 1,
+        }
+
+        with patch.object(client, "_send_request", return_value={"tools": []}):
+            result = await client._send_request("tools/list")
+            assert result == {"tools": []}
+
+    @pytest.mark.asyncio(loop_scope="session")
+    async def test_send_request_error(self):
+        client = MCPClient("https://mcp.example.com")
+
+        async def mock_send(*args, **kwargs):
+            raise MCPClientError("MCP server error [-32600]: Invalid Request")
+
+        with patch.object(client, "_send_request", side_effect=mock_send):
+            with pytest.raises(MCPClientError, match="Invalid Request"):
+                await client._send_request("tools/list")
+
+    @pytest.mark.asyncio(loop_scope="session")
+    async def test_list_tools(self):
+        client = MCPClient("https://mcp.example.com")
+
+        mock_result = {
+            "tools": [
+                {
+                    "name": "get_weather",
+                    "description": "Get current weather for a city",
+                    "inputSchema": {
+                        "type": "object",
+                        "properties": {"city": {"type": "string"}},
+                        "required": ["city"],
+                    },
+                },
+                {
+                    "name": "search",
+                    "description": "Search the web",
+                    "inputSchema": {
+                        "type": "object",
+                        "properties": {"query": {"type": "string"}},
+                        "required": ["query"],
+                    },
+                },
+            ]
+        }
+
+        with patch.object(client, "_send_request", return_value=mock_result):
+            tools = await client.list_tools()
+
+        assert len(tools) == 2
+        assert tools[0].name == "get_weather"
+        assert tools[0].description == "Get current weather for a city"
+        assert tools[0].input_schema["properties"]["city"]["type"] == "string"
+        assert tools[1].name == "search"
+
+    @pytest.mark.asyncio(loop_scope="session")
+    async def test_list_tools_empty(self):
+        client = MCPClient("https://mcp.example.com")
+
+        with patch.object(client, "_send_request", return_value={"tools": []}):
+            tools = await client.list_tools()
+
+        assert tools == []
+
+    @pytest.mark.asyncio(loop_scope="session")
+    async def test_list_tools_none_result(self):
+        client = MCPClient("https://mcp.example.com")
+
+        with patch.object(client, "_send_request", return_value=None):
+            tools = await client.list_tools()
+
+        assert tools == []
+
+    @pytest.mark.asyncio(loop_scope="session")
+    async def test_call_tool_success(self):
+        client = MCPClient("https://mcp.example.com")
+
+        mock_result = {
+            "content": [
+                {"type": "text", "text": json.dumps({"temp": 20, "city": "London"})}
+            ],
+            "isError": False,
+        }
+
+        with patch.object(client, "_send_request", return_value=mock_result):
+            result = await client.call_tool("get_weather", {"city": "London"})
+
+        assert not result.is_error
+        assert len(result.content) == 1
+        assert result.content[0]["type"] == "text"
+
+    @pytest.mark.asyncio(loop_scope="session")
+    async def test_call_tool_error(self):
+        client = MCPClient("https://mcp.example.com")
+
+        mock_result = {
+            "content": [{"type": "text", "text": "City not found"}],
+            "isError": True,
+        }
+
+        with patch.object(client, "_send_request", return_value=mock_result):
+            result = await client.call_tool("get_weather", {"city": "???"})
+
+        assert result.is_error
+
+    @pytest.mark.asyncio(loop_scope="session")
+    async def test_call_tool_none_result(self):
+        client = MCPClient("https://mcp.example.com")
+
+        with patch.object(client, "_send_request", return_value=None):
+            result = await client.call_tool("get_weather", {"city": "London"})
+
+        assert result.is_error
+
+    @pytest.mark.asyncio(loop_scope="session")
+    async def test_initialize(self):
+        client = MCPClient("https://mcp.example.com")
+
+        mock_result = {
+            "protocolVersion": "2025-03-26",
+            "capabilities": {"tools": {}},
+            "serverInfo": {"name": "test-server", "version": "1.0.0"},
+        }
+
+        with (
+            patch.object(client, "_send_request", return_value=mock_result) as mock_req,
+            patch.object(client, "_send_notification") as mock_notif,
+        ):
+            result = await client.initialize()
+
+        mock_req.assert_called_once()
+        mock_notif.assert_called_once_with("notifications/initialized")
+        assert result["protocolVersion"] == "2025-03-26"
+
+
+# ── MCPToolBlock unit tests ──────────────────────────────────────────
+
+MOCK_USER_ID = "test-user-123"
+
+
+class TestMCPToolBlock:
+    """Tests for the MCPToolBlock."""
+
+    def test_block_instantiation(self):
+        block = MCPToolBlock()
+        assert block.id == "a0a4b1c2-d3e4-4f56-a7b8-c9d0e1f2a3b4"
+        assert block.name == "MCPToolBlock"
+
+    def test_input_schema_has_required_fields(self):
+        block = MCPToolBlock()
+        schema = block.input_schema.jsonschema()
+        props = schema.get("properties", {})
+        assert "server_url" in props
+        assert "selected_tool" in props
+        assert "tool_arguments" in props
+        assert "credentials" in props
+
+    def test_output_schema(self):
+        block = MCPToolBlock()
+        schema = block.output_schema.jsonschema()
+        props = schema.get("properties", {})
+        assert "result" in props
+        assert "error" in props
+
+    def test_get_input_schema_with_tool_schema(self):
+        tool_schema = {
+            "type": "object",
+            "properties": {"query": {"type": "string"}},
+            "required": ["query"],
+        }
+        data = {"tool_input_schema": tool_schema}
+        result = MCPToolBlock.Input.get_input_schema(data)
+        assert result == tool_schema
+
+    def test_get_input_schema_without_tool_schema(self):
+        result = MCPToolBlock.Input.get_input_schema({})
+        assert result == {}
+
+    def test_get_input_defaults(self):
+        data = {"tool_arguments": {"city": "London"}}
+        result = MCPToolBlock.Input.get_input_defaults(data)
+        assert result == {"city": "London"}
+
+    def test_get_missing_input(self):
+        data = {
+            "tool_input_schema": {
+                "type": "object",
+                "properties": {
+                    "city": {"type": "string"},
+                    "units": {"type": "string"},
+                },
+                "required": ["city", "units"],
+            },
+            "tool_arguments": {"city": "London"},
+        }
+        missing = MCPToolBlock.Input.get_missing_input(data)
+        assert missing == {"units"}
+
+    def test_get_missing_input_all_present(self):
+        data = {
+            "tool_input_schema": {
+                "type": "object",
+                "properties": {"city": {"type": "string"}},
+                "required": ["city"],
+            },
+            "tool_arguments": {"city": "London"},
+        }
+        missing = MCPToolBlock.Input.get_missing_input(data)
+        assert missing == set()
+
+    @pytest.mark.asyncio(loop_scope="session")
+    async def test_run_with_mock(self):
+        """Test the block using the built-in test infrastructure."""
+        block = MCPToolBlock()
+        await execute_block_test(block)
+
+    @pytest.mark.asyncio(loop_scope="session")
+    async def test_run_missing_server_url(self):
+        block = MCPToolBlock()
+        input_data = MCPToolBlock.Input(
+            server_url="",
+            selected_tool="test",
+        )
+        outputs = []
+        async for name, data in block.run(input_data, user_id=MOCK_USER_ID):
+            outputs.append((name, data))
+        assert outputs == [("error", "MCP server URL is required")]
+
+    @pytest.mark.asyncio(loop_scope="session")
+    async def test_run_missing_tool(self):
+        block = MCPToolBlock()
+        input_data = MCPToolBlock.Input(
+            server_url="https://mcp.example.com/mcp",
+            selected_tool="",
+        )
+        outputs = []
+        async for name, data in block.run(input_data, user_id=MOCK_USER_ID):
+            outputs.append((name, data))
+        assert outputs == [
+            ("error", "No tool selected. Please select a tool from the dropdown.")
+        ]
+
+    @pytest.mark.asyncio(loop_scope="session")
+    async def test_run_success(self):
+        block = MCPToolBlock()
+        input_data = MCPToolBlock.Input(
+            server_url="https://mcp.example.com/mcp",
+            selected_tool="get_weather",
+            tool_input_schema={
+                "type": "object",
+                "properties": {"city": {"type": "string"}},
+            },
+            tool_arguments={"city": "London"},
+        )
+
+        async def mock_call(*args, **kwargs):
+            return {"temp": 20, "city": "London"}
+
+        block._call_mcp_tool = mock_call  # type: ignore
+
+        outputs = []
+        async for name, data in block.run(input_data, user_id=MOCK_USER_ID):
+            outputs.append((name, data))
+
+        assert len(outputs) == 1
+        assert outputs[0][0] == "result"
+        assert outputs[0][1] == {"temp": 20, "city": "London"}
+
+    @pytest.mark.asyncio(loop_scope="session")
+    async def test_run_mcp_error(self):
+        block = MCPToolBlock()
+        input_data = MCPToolBlock.Input(
+            server_url="https://mcp.example.com/mcp",
+            selected_tool="bad_tool",
+        )
+
+        async def mock_call(*args, **kwargs):
+            raise MCPClientError("Tool not found")
+
+        block._call_mcp_tool = mock_call  # type: ignore
+
+        outputs = []
+        async for name, data in block.run(input_data, user_id=MOCK_USER_ID):
+            outputs.append((name, data))
+
+        assert outputs[0][0] == "error"
+        assert "Tool not found" in outputs[0][1]
+
+    @pytest.mark.asyncio(loop_scope="session")
+    async def test_call_mcp_tool_parses_json_text(self):
+        block = MCPToolBlock()
+
+        mock_result = MCPCallResult(
+            content=[
+                {"type": "text", "text": '{"temp": 20}'},
+            ],
+            is_error=False,
+        )
+
+        async def mock_init(self):
+            return {}
+
+        async def mock_call(self, name, args):
+            return mock_result
+
+        with (
+            patch.object(MCPClient, "initialize", mock_init),
+            patch.object(MCPClient, "call_tool", mock_call),
+        ):
+            result = await block._call_mcp_tool(
+                "https://mcp.example.com", "test_tool", {}
+            )
+
+        assert result == {"temp": 20}
+
+    @pytest.mark.asyncio(loop_scope="session")
+    async def test_call_mcp_tool_plain_text(self):
+        block = MCPToolBlock()
+
+        mock_result = MCPCallResult(
+            content=[
+                {"type": "text", "text": "Hello, world!"},
+            ],
+            is_error=False,
+        )
+
+        async def mock_init(self):
+            return {}
+
+        async def mock_call(self, name, args):
+            return mock_result
+
+        with (
+            patch.object(MCPClient, "initialize", mock_init),
+            patch.object(MCPClient, "call_tool", mock_call),
+        ):
+            result = await block._call_mcp_tool(
+                "https://mcp.example.com", "test_tool", {}
+            )
+
+        assert result == "Hello, world!"
+
+    @pytest.mark.asyncio(loop_scope="session")
+    async def test_call_mcp_tool_multiple_content(self):
+        block = MCPToolBlock()
+
+        mock_result = MCPCallResult(
+            content=[
+                {"type": "text", "text": "Part 1"},
+                {"type": "text", "text": '{"part": 2}'},
+            ],
+            is_error=False,
+        )
+
+        async def mock_init(self):
+            return {}
+
+        async def mock_call(self, name, args):
+            return mock_result
+
+        with (
+            patch.object(MCPClient, "initialize", mock_init),
+            patch.object(MCPClient, "call_tool", mock_call),
+        ):
+            result = await block._call_mcp_tool(
+                "https://mcp.example.com", "test_tool", {}
+            )
+
+        assert result == ["Part 1", {"part": 2}]
+
+    @pytest.mark.asyncio(loop_scope="session")
+    async def test_call_mcp_tool_error_result(self):
+        block = MCPToolBlock()
+
+        mock_result = MCPCallResult(
+            content=[{"type": "text", "text": "Something went wrong"}],
+            is_error=True,
+        )
+
+        async def mock_init(self):
+            return {}
+
+        async def mock_call(self, name, args):
+            return mock_result
+
+        with (
+            patch.object(MCPClient, "initialize", mock_init),
+            patch.object(MCPClient, "call_tool", mock_call),
+        ):
+            with pytest.raises(MCPClientError, match="returned an error"):
+                await block._call_mcp_tool("https://mcp.example.com", "test_tool", {})
+
+    @pytest.mark.asyncio(loop_scope="session")
+    async def test_call_mcp_tool_image_content(self):
+        block = MCPToolBlock()
+
+        mock_result = MCPCallResult(
+            content=[
+                {
+                    "type": "image",
+                    "data": "base64data==",
+                    "mimeType": "image/png",
+                }
+            ],
+            is_error=False,
+        )
+
+        async def mock_init(self):
+            return {}
+
+        async def mock_call(self, name, args):
+            return mock_result
+
+        with (
+            patch.object(MCPClient, "initialize", mock_init),
+            patch.object(MCPClient, "call_tool", mock_call),
+        ):
+            result = await block._call_mcp_tool(
+                "https://mcp.example.com", "test_tool", {}
+            )
+
+        assert result == {
+            "type": "image",
+            "data": "base64data==",
+            "mimeType": "image/png",
+        }
+
+    @pytest.mark.asyncio(loop_scope="session")
+    async def test_run_with_credentials(self):
+        """Verify the block uses OAuth2Credentials and passes auth token."""
+        from pydantic import SecretStr
+
+        from backend.data.model import OAuth2Credentials
+
+        block = MCPToolBlock()
+        input_data = MCPToolBlock.Input(
+            server_url="https://mcp.example.com/mcp",
+            selected_tool="test_tool",
+        )
+
+        captured_tokens: list[str | None] = []
+
+        async def mock_call(server_url, tool_name, arguments, auth_token=None):
+            captured_tokens.append(auth_token)
+            return "ok"
+
+        block._call_mcp_tool = mock_call  # type: ignore
+
+        test_creds = OAuth2Credentials(
+            id="cred-123",
+            provider="mcp",
+            access_token=SecretStr("resolved-token"),
+            refresh_token=SecretStr(""),
+            scopes=[],
+            title="Test MCP credential",
+        )
+
+        async for _ in block.run(
+            input_data, user_id=MOCK_USER_ID, credentials=test_creds
+        ):
+            pass
+
+        assert captured_tokens == ["resolved-token"]
+
+    @pytest.mark.asyncio(loop_scope="session")
+    async def test_run_without_credentials(self):
+        """Verify the block works without credentials (public server)."""
+        block = MCPToolBlock()
+        input_data = MCPToolBlock.Input(
+            server_url="https://mcp.example.com/mcp",
+            selected_tool="test_tool",
+        )
+
+        captured_tokens: list[str | None] = []
+
+        async def mock_call(server_url, tool_name, arguments, auth_token=None):
+            captured_tokens.append(auth_token)
+            return "ok"
+
+        block._call_mcp_tool = mock_call  # type: ignore
+
+        outputs = []
+        async for name, data in block.run(input_data, user_id=MOCK_USER_ID):
+            outputs.append((name, data))
+
+        assert captured_tokens == [None]
+        assert outputs == [("result", "ok")]

autogpt_platform/backend/backend/blocks/mcp/test_oauth.py

@@ -0,0 +1,242 @@
+"""
+Tests for MCP OAuth handler.
+"""
+
+from unittest.mock import AsyncMock, MagicMock, patch
+
+import pytest
+from pydantic import SecretStr
+
+from backend.blocks.mcp.client import MCPClient
+from backend.blocks.mcp.oauth import MCPOAuthHandler
+from backend.data.model import OAuth2Credentials
+
+
+def _mock_response(json_data: dict, status: int = 200) -> MagicMock:
+    """Create a mock Response with synchronous json() (matching Requests.Response)."""
+    resp = MagicMock()
+    resp.status = status
+    resp.ok = 200 <= status < 300
+    resp.json.return_value = json_data
+    return resp
+
+
+class TestMCPOAuthHandler:
+    """Tests for the MCPOAuthHandler."""
+
+    def _make_handler(self, **overrides) -> MCPOAuthHandler:
+        defaults = {
+            "client_id": "test-client-id",
+            "client_secret": "test-client-secret",
+            "redirect_uri": "https://app.example.com/callback",
+            "authorize_url": "https://auth.example.com/authorize",
+            "token_url": "https://auth.example.com/token",
+        }
+        defaults.update(overrides)
+        return MCPOAuthHandler(**defaults)
+
+    def test_get_login_url_basic(self):
+        handler = self._make_handler()
+        url = handler.get_login_url(
+            scopes=["read", "write"],
+            state="random-state-token",
+            code_challenge="S256-challenge-value",
+        )
+
+        assert "https://auth.example.com/authorize?" in url
+        assert "response_type=code" in url
+        assert "client_id=test-client-id" in url
+        assert "state=random-state-token" in url
+        assert "code_challenge=S256-challenge-value" in url
+        assert "code_challenge_method=S256" in url
+        assert "scope=read+write" in url
+
+    def test_get_login_url_with_resource(self):
+        handler = self._make_handler(resource_url="https://mcp.example.com/mcp")
+        url = handler.get_login_url(
+            scopes=[], state="state", code_challenge="challenge"
+        )
+
+        assert "resource=https" in url
+
+    def test_get_login_url_without_pkce(self):
+        handler = self._make_handler()
+        url = handler.get_login_url(scopes=["read"], state="state", code_challenge=None)
+
+        assert "code_challenge" not in url
+        assert "code_challenge_method" not in url
+
+    @pytest.mark.asyncio(loop_scope="session")
+    async def test_exchange_code_for_tokens(self):
+        handler = self._make_handler()
+
+        resp = _mock_response(
+            {
+                "access_token": "new-access-token",
+                "refresh_token": "new-refresh-token",
+                "expires_in": 3600,
+                "token_type": "Bearer",
+            }
+        )
+
+        with patch("backend.blocks.mcp.oauth.Requests") as MockRequests:
+            instance = MockRequests.return_value
+            instance.post = AsyncMock(return_value=resp)
+
+            creds = await handler.exchange_code_for_tokens(
+                code="auth-code",
+                scopes=["read"],
+                code_verifier="pkce-verifier",
+            )
+
+        assert isinstance(creds, OAuth2Credentials)
+        assert creds.access_token.get_secret_value() == "new-access-token"
+        assert creds.refresh_token is not None
+        assert creds.refresh_token.get_secret_value() == "new-refresh-token"
+        assert creds.scopes == ["read"]
+        assert creds.access_token_expires_at is not None
+
+    @pytest.mark.asyncio(loop_scope="session")
+    async def test_refresh_tokens(self):
+        handler = self._make_handler()
+
+        existing_creds = OAuth2Credentials(
+            id="existing-id",
+            provider="mcp",
+            access_token=SecretStr("old-token"),
+            refresh_token=SecretStr("old-refresh"),
+            scopes=["read"],
+            title="test",
+        )
+
+        resp = _mock_response(
+            {
+                "access_token": "refreshed-token",
+                "refresh_token": "new-refresh",
+                "expires_in": 3600,
+            }
+        )
+
+        with patch("backend.blocks.mcp.oauth.Requests") as MockRequests:
+            instance = MockRequests.return_value
+            instance.post = AsyncMock(return_value=resp)
+
+            refreshed = await handler._refresh_tokens(existing_creds)
+
+        assert refreshed.id == "existing-id"
+        assert refreshed.access_token.get_secret_value() == "refreshed-token"
+        assert refreshed.refresh_token is not None
+        assert refreshed.refresh_token.get_secret_value() == "new-refresh"
+
+    @pytest.mark.asyncio(loop_scope="session")
+    async def test_refresh_tokens_no_refresh_token(self):
+        handler = self._make_handler()
+
+        creds = OAuth2Credentials(
+            provider="mcp",
+            access_token=SecretStr("token"),
+            scopes=["read"],
+            title="test",
+        )
+
+        with pytest.raises(ValueError, match="No refresh token"):
+            await handler._refresh_tokens(creds)
+
+    @pytest.mark.asyncio(loop_scope="session")
+    async def test_revoke_tokens_no_url(self):
+        handler = self._make_handler(revoke_url=None)
+
+        creds = OAuth2Credentials(
+            provider="mcp",
+            access_token=SecretStr("token"),
+            scopes=[],
+            title="test",
+        )
+
+        result = await handler.revoke_tokens(creds)
+        assert result is False
+
+    @pytest.mark.asyncio(loop_scope="session")
+    async def test_revoke_tokens_with_url(self):
+        handler = self._make_handler(revoke_url="https://auth.example.com/revoke")
+
+        creds = OAuth2Credentials(
+            provider="mcp",
+            access_token=SecretStr("token"),
+            scopes=[],
+            title="test",
+        )
+
+        resp = _mock_response({}, status=200)
+
+        with patch("backend.blocks.mcp.oauth.Requests") as MockRequests:
+            instance = MockRequests.return_value
+            instance.post = AsyncMock(return_value=resp)
+
+            result = await handler.revoke_tokens(creds)
+
+        assert result is True
+
+
+class TestMCPClientDiscovery:
+    """Tests for MCPClient OAuth metadata discovery."""
+
+    @pytest.mark.asyncio(loop_scope="session")
+    async def test_discover_auth_found(self):
+        client = MCPClient("https://mcp.example.com/mcp")
+
+        metadata = {
+            "authorization_servers": ["https://auth.example.com"],
+            "resource": "https://mcp.example.com/mcp",
+        }
+
+        resp = _mock_response(metadata, status=200)
+
+        with patch("backend.blocks.mcp.client.Requests") as MockRequests:
+            instance = MockRequests.return_value
+            instance.get = AsyncMock(return_value=resp)
+
+            result = await client.discover_auth()
+
+        assert result is not None
+        assert result["authorization_servers"] == ["https://auth.example.com"]
+
+    @pytest.mark.asyncio(loop_scope="session")
+    async def test_discover_auth_not_found(self):
+        client = MCPClient("https://mcp.example.com/mcp")
+
+        resp = _mock_response({}, status=404)
+
+        with patch("backend.blocks.mcp.client.Requests") as MockRequests:
+            instance = MockRequests.return_value
+            instance.get = AsyncMock(return_value=resp)
+
+            result = await client.discover_auth()
+
+        assert result is None
+
+    @pytest.mark.asyncio(loop_scope="session")
+    async def test_discover_auth_server_metadata(self):
+        client = MCPClient("https://mcp.example.com/mcp")
+
+        server_metadata = {
+            "issuer": "https://auth.example.com",
+            "authorization_endpoint": "https://auth.example.com/authorize",
+            "token_endpoint": "https://auth.example.com/token",
+            "registration_endpoint": "https://auth.example.com/register",
+            "code_challenge_methods_supported": ["S256"],
+        }
+
+        resp = _mock_response(server_metadata, status=200)
+
+        with patch("backend.blocks.mcp.client.Requests") as MockRequests:
+            instance = MockRequests.return_value
+            instance.get = AsyncMock(return_value=resp)
+
+            result = await client.discover_auth_server_metadata(
+                "https://auth.example.com"
+            )
+
+        assert result is not None
+        assert result["authorization_endpoint"] == "https://auth.example.com/authorize"
+        assert result["token_endpoint"] == "https://auth.example.com/token"

autogpt_platform/backend/backend/blocks/mcp/test_server.py

@@ -0,0 +1,162 @@
+"""
+Minimal MCP server for integration testing.
+
+Implements the MCP Streamable HTTP transport (JSON-RPC 2.0 over HTTP POST)
+with a few sample tools. Runs on localhost with a random available port.
+"""
+
+import json
+import logging
+
+from aiohttp import web
+
+logger = logging.getLogger(__name__)
+
+# Sample tools this test server exposes
+TEST_TOOLS = [
+    {
+        "name": "get_weather",
+        "description": "Get current weather for a city",
+        "inputSchema": {
+            "type": "object",
+            "properties": {
+                "city": {
+                    "type": "string",
+                    "description": "City name",
+                },
+            },
+            "required": ["city"],
+        },
+    },
+    {
+        "name": "add_numbers",
+        "description": "Add two numbers together",
+        "inputSchema": {
+            "type": "object",
+            "properties": {
+                "a": {"type": "number", "description": "First number"},
+                "b": {"type": "number", "description": "Second number"},
+            },
+            "required": ["a", "b"],
+        },
+    },
+    {
+        "name": "echo",
+        "description": "Echo back the input message",
+        "inputSchema": {
+            "type": "object",
+            "properties": {
+                "message": {"type": "string", "description": "Message to echo"},
+            },
+            "required": ["message"],
+        },
+    },
+]
+
+
+def _handle_initialize(params: dict) -> dict:
+    return {
+        "protocolVersion": "2025-03-26",
+        "capabilities": {"tools": {"listChanged": False}},
+        "serverInfo": {"name": "test-mcp-server", "version": "1.0.0"},
+    }
+
+
+def _handle_tools_list(params: dict) -> dict:
+    return {"tools": TEST_TOOLS}
+
+
+def _handle_tools_call(params: dict) -> dict:
+    tool_name = params.get("name", "")
+    arguments = params.get("arguments", {})
+
+    if tool_name == "get_weather":
+        city = arguments.get("city", "Unknown")
+        return {
+            "content": [
+                {
+                    "type": "text",
+                    "text": json.dumps(
+                        {"city": city, "temperature": 22, "condition": "sunny"}
+                    ),
+                }
+            ],
+        }
+
+    elif tool_name == "add_numbers":
+        a = arguments.get("a", 0)
+        b = arguments.get("b", 0)
+        return {
+            "content": [{"type": "text", "text": json.dumps({"result": a + b})}],
+        }
+
+    elif tool_name == "echo":
+        message = arguments.get("message", "")
+        return {
+            "content": [{"type": "text", "text": message}],
+        }
+
+    else:
+        return {
+            "content": [{"type": "text", "text": f"Unknown tool: {tool_name}"}],
+            "isError": True,
+        }
+
+
+HANDLERS = {
+    "initialize": _handle_initialize,
+    "tools/list": _handle_tools_list,
+    "tools/call": _handle_tools_call,
+}
+
+
+async def handle_mcp_request(request: web.Request) -> web.Response:
+    """Handle incoming MCP JSON-RPC 2.0 requests."""
+    # Check auth if configured
+    expected_token = request.app.get("auth_token")
+    if expected_token:
+        auth_header = request.headers.get("Authorization", "")
+        if auth_header != f"Bearer {expected_token}":
+            return web.json_response(
+                {
+                    "jsonrpc": "2.0",
+                    "error": {"code": -32001, "message": "Unauthorized"},
+                    "id": None,
+                },
+                status=401,
+            )
+
+    body = await request.json()
+
+    # Handle notifications (no id field) — just acknowledge
+    if "id" not in body:
+        return web.Response(status=202)
+
+    method = body.get("method", "")
+    params = body.get("params", {})
+    request_id = body.get("id")
+
+    handler = HANDLERS.get(method)
+    if not handler:
+        return web.json_response(
+            {
+                "jsonrpc": "2.0",
+                "error": {
+                    "code": -32601,
+                    "message": f"Method not found: {method}",
+                },
+                "id": request_id,
+            }
+        )
+
+    result = handler(params)
+    return web.json_response({"jsonrpc": "2.0", "result": result, "id": request_id})
+
+
+def create_test_mcp_app(auth_token: str | None = None) -> web.Application:
+    """Create an aiohttp app that acts as an MCP server."""
+    app = web.Application()
+    app.router.add_post("/mcp", handle_mcp_request)
+    if auth_token:
+        app["auth_token"] = auth_token
+    return app

autogpt_platform/backend/backend/blocks/stagehand/blocks.py

@@ -83,7 +83,8 @@ class StagehandRecommendedLlmModel(str, Enum):
     GPT41_MINI = "gpt-4.1-mini-2025-04-14"
 
     # Anthropic
-    CLAUDE_4_5_SONNET = "claude-sonnet-4-5-20250929"
+    CLAUDE_4_5_SONNET = "claude-sonnet-4-5-20250929"  # Keep for backwards compat
+    CLAUDE_4_6_SONNET = "claude-sonnet-4-6"
 
     @property
     def provider_name(self) -> str:
@@ -137,7 +138,7 @@ class StagehandObserveBlock(Block):
         model: StagehandRecommendedLlmModel = SchemaField(
             title="LLM Model",
             description="LLM to use for Stagehand (provider is inferred)",
-            default=StagehandRecommendedLlmModel.CLAUDE_4_5_SONNET,
+            default=StagehandRecommendedLlmModel.CLAUDE_4_6_SONNET,
             advanced=False,
         )
         model_credentials: AICredentials = AICredentialsField()
@@ -227,7 +228,7 @@ class StagehandActBlock(Block):
         model: StagehandRecommendedLlmModel = SchemaField(
             title="LLM Model",
             description="LLM to use for Stagehand (provider is inferred)",
-            default=StagehandRecommendedLlmModel.CLAUDE_4_5_SONNET,
+            default=StagehandRecommendedLlmModel.CLAUDE_4_6_SONNET,
             advanced=False,
         )
         model_credentials: AICredentials = AICredentialsField()
@@ -324,7 +325,7 @@ class StagehandExtractBlock(Block):
         model: StagehandRecommendedLlmModel = SchemaField(
             title="LLM Model",
             description="LLM to use for Stagehand (provider is inferred)",
-            default=StagehandRecommendedLlmModel.CLAUDE_4_5_SONNET,
+            default=StagehandRecommendedLlmModel.CLAUDE_4_6_SONNET,
             advanced=False,
         )
         model_credentials: AICredentials = AICredentialsField()

autogpt_platform/backend/backend/blocks/telegram/_api.py

@@ -0,0 +1,182 @@
+"""
+Telegram Bot API helper functions.
+
+Provides utilities for making authenticated requests to the Telegram Bot API.
+"""
+
+import logging
+from io import BytesIO
+from typing import Any, Optional
+
+from pydantic import BaseModel
+
+from backend.data.model import APIKeyCredentials
+from backend.util.request import Requests
+
+logger = logging.getLogger(__name__)
+
+TELEGRAM_API_BASE = "https://api.telegram.org"
+
+
+class TelegramMessageResult(BaseModel, extra="allow"):
+    """Result from Telegram send/edit message API calls."""
+
+    message_id: int = 0
+    chat: dict[str, Any] = {}
+    date: int = 0
+    text: str = ""
+
+
+class TelegramFileResult(BaseModel, extra="allow"):
+    """Result from Telegram getFile API call."""
+
+    file_id: str = ""
+    file_unique_id: str = ""
+    file_size: int = 0
+    file_path: str = ""
+
+
+class TelegramAPIException(ValueError):
+    """Exception raised for Telegram API errors."""
+
+    def __init__(self, message: str, error_code: int = 0):
+        super().__init__(message)
+        self.error_code = error_code
+
+
+def get_bot_api_url(bot_token: str, method: str) -> str:
+    """Construct Telegram Bot API URL for a method."""
+    return f"{TELEGRAM_API_BASE}/bot{bot_token}/{method}"
+
+
+def get_file_url(bot_token: str, file_path: str) -> str:
+    """Construct Telegram file download URL."""
+    return f"{TELEGRAM_API_BASE}/file/bot{bot_token}/{file_path}"
+
+
+async def call_telegram_api(
+    credentials: APIKeyCredentials,
+    method: str,
+    data: Optional[dict[str, Any]] = None,
+) -> TelegramMessageResult:
+    """
+    Make a request to the Telegram Bot API.
+
+    Args:
+        credentials: Bot token credentials
+        method: API method name (e.g., "sendMessage", "getFile")
+        data: Request parameters
+
+    Returns:
+        API response result
+
+    Raises:
+        TelegramAPIException: If the API returns an error
+    """
+    token = credentials.api_key.get_secret_value()
+    url = get_bot_api_url(token, method)
+
+    response = await Requests().post(url, json=data or {})
+    result = response.json()
+
+    if not result.get("ok"):
+        error_code = result.get("error_code", 0)
+        description = result.get("description", "Unknown error")
+        raise TelegramAPIException(description, error_code)
+
+    return TelegramMessageResult(**result.get("result", {}))
+
+
+async def call_telegram_api_with_file(
+    credentials: APIKeyCredentials,
+    method: str,
+    file_field: str,
+    file_data: bytes,
+    filename: str,
+    content_type: str,
+    data: Optional[dict[str, Any]] = None,
+) -> TelegramMessageResult:
+    """
+    Make a multipart/form-data request to the Telegram Bot API with a file upload.
+
+    Args:
+        credentials: Bot token credentials
+        method: API method name (e.g., "sendPhoto", "sendVoice")
+        file_field: Form field name for the file (e.g., "photo", "voice")
+        file_data: Raw file bytes
+        filename: Filename for the upload
+        content_type: MIME type of the file
+        data: Additional form parameters
+
+    Returns:
+        API response result
+
+    Raises:
+        TelegramAPIException: If the API returns an error
+    """
+    token = credentials.api_key.get_secret_value()
+    url = get_bot_api_url(token, method)
+
+    files = [(file_field, (filename, BytesIO(file_data), content_type))]
+
+    response = await Requests().post(url, files=files, data=data or {})
+    result = response.json()
+
+    if not result.get("ok"):
+        error_code = result.get("error_code", 0)
+        description = result.get("description", "Unknown error")
+        raise TelegramAPIException(description, error_code)
+
+    return TelegramMessageResult(**result.get("result", {}))
+
+
+async def get_file_info(
+    credentials: APIKeyCredentials, file_id: str
+) -> TelegramFileResult:
+    """
+    Get file information from Telegram.
+
+    Args:
+        credentials: Bot token credentials
+        file_id: Telegram file_id from message
+
+    Returns:
+        File info dict containing file_id, file_unique_id, file_size, file_path
+    """
+    result = await call_telegram_api(credentials, "getFile", {"file_id": file_id})
+    return TelegramFileResult(**result.model_dump())
+
+
+async def get_file_download_url(credentials: APIKeyCredentials, file_id: str) -> str:
+    """
+    Get the download URL for a Telegram file.
+
+    Args:
+        credentials: Bot token credentials
+        file_id: Telegram file_id from message
+
+    Returns:
+        Full download URL
+    """
+    token = credentials.api_key.get_secret_value()
+    result = await get_file_info(credentials, file_id)
+    file_path = result.file_path
+    if not file_path:
+        raise TelegramAPIException("No file_path returned from getFile")
+    return get_file_url(token, file_path)
+
+
+async def download_telegram_file(credentials: APIKeyCredentials, file_id: str) -> bytes:
+    """
+    Download a file from Telegram servers.
+
+    Args:
+        credentials: Bot token credentials
+        file_id: Telegram file_id
+
+    Returns:
+        File content as bytes
+    """
+    url = await get_file_download_url(credentials, file_id)
+    response = await Requests().get(url)
+    return response.content

autogpt_platform/backend/backend/blocks/telegram/_auth.py

@@ -0,0 +1,43 @@
+"""
+Telegram Bot credentials handling.
+
+Telegram bots use an API key (bot token) obtained from @BotFather.
+"""
+
+from typing import Literal
+
+from pydantic import SecretStr
+
+from backend.data.model import APIKeyCredentials, CredentialsField, CredentialsMetaInput
+from backend.integrations.providers import ProviderName
+
+# Bot token credentials (API key style)
+TelegramCredentials = APIKeyCredentials
+TelegramCredentialsInput = CredentialsMetaInput[
+    Literal[ProviderName.TELEGRAM], Literal["api_key"]
+]
+
+
+def TelegramCredentialsField() -> TelegramCredentialsInput:
+    """Creates a Telegram bot token credentials field."""
+    return CredentialsField(
+        description="Telegram Bot API token from @BotFather. "
+        "Create a bot at https://t.me/BotFather to get your token."
+    )
+
+
+# Test credentials for unit tests
+TEST_CREDENTIALS = APIKeyCredentials(
+    id="01234567-89ab-cdef-0123-456789abcdef",
+    provider="telegram",
+    api_key=SecretStr("test_telegram_bot_token"),
+    title="Mock Telegram Bot Token",
+    expires_at=None,
+)
+
+TEST_CREDENTIALS_INPUT = {
+    "provider": TEST_CREDENTIALS.provider,
+    "id": TEST_CREDENTIALS.id,
+    "type": TEST_CREDENTIALS.type,
+    "title": TEST_CREDENTIALS.title,
+}

autogpt_platform/backend/backend/blocks/telegram/triggers.py

@@ -0,0 +1,377 @@
+"""
+Telegram trigger blocks for receiving messages via webhooks.
+"""
+
+import logging
+
+from pydantic import BaseModel
+
+from backend.blocks._base import (
+    Block,
+    BlockCategory,
+    BlockOutput,
+    BlockSchemaInput,
+    BlockSchemaOutput,
+    BlockWebhookConfig,
+)
+from backend.data.model import SchemaField
+from backend.integrations.providers import ProviderName
+from backend.integrations.webhooks.telegram import TelegramWebhookType
+
+from ._auth import (
+    TEST_CREDENTIALS,
+    TEST_CREDENTIALS_INPUT,
+    TelegramCredentialsField,
+    TelegramCredentialsInput,
+)
+
+logger = logging.getLogger(__name__)
+
+
+# Example payload for testing
+EXAMPLE_MESSAGE_PAYLOAD = {
+    "update_id": 123456789,
+    "message": {
+        "message_id": 1,
+        "from": {
+            "id": 12345678,
+            "is_bot": False,
+            "first_name": "John",
+            "last_name": "Doe",
+            "username": "johndoe",
+            "language_code": "en",
+        },
+        "chat": {
+            "id": 12345678,
+            "first_name": "John",
+            "last_name": "Doe",
+            "username": "johndoe",
+            "type": "private",
+        },
+        "date": 1234567890,
+        "text": "Hello, bot!",
+    },
+}
+
+
+class TelegramTriggerBase:
+    """Base class for Telegram trigger blocks."""
+
+    class Input(BlockSchemaInput):
+        credentials: TelegramCredentialsInput = TelegramCredentialsField()
+        payload: dict = SchemaField(hidden=True, default_factory=dict)
+
+
+class TelegramMessageTriggerBlock(TelegramTriggerBase, Block):
+    """
+    Triggers when a message is received or edited in your Telegram bot.
+
+    Supports text, photos, voice messages, audio files, documents, and videos.
+    Connect the outputs to other blocks to process messages and send responses.
+    """
+
+    class Input(TelegramTriggerBase.Input):
+        class EventsFilter(BaseModel):
+            """Filter for message types to receive."""
+
+            text: bool = True
+            photo: bool = False
+            voice: bool = False
+            audio: bool = False
+            document: bool = False
+            video: bool = False
+            edited_message: bool = False
+
+        events: EventsFilter = SchemaField(
+            title="Message Types", description="Types of messages to receive"
+        )
+
+    class Output(BlockSchemaOutput):
+        payload: dict = SchemaField(
+            description="The complete webhook payload from Telegram"
+        )
+        chat_id: int = SchemaField(
+            description="The chat ID where the message was received. "
+            "Use this to send replies."
+        )
+        message_id: int = SchemaField(description="The unique message ID")
+        user_id: int = SchemaField(description="The user ID who sent the message")
+        username: str = SchemaField(description="Username of the sender (may be empty)")
+        first_name: str = SchemaField(description="First name of the sender")
+        event: str = SchemaField(
+            description="The message type (text, photo, voice, audio, etc.)"
+        )
+        text: str = SchemaField(
+            description="Text content of the message (for text messages)"
+        )
+        photo_file_id: str = SchemaField(
+            description="File ID of the photo (for photo messages). "
+            "Use GetTelegramFileBlock to download."
+        )
+        voice_file_id: str = SchemaField(
+            description="File ID of the voice message (for voice messages). "
+            "Use GetTelegramFileBlock to download."
+        )
+        audio_file_id: str = SchemaField(
+            description="File ID of the audio file (for audio messages). "
+            "Use GetTelegramFileBlock to download."
+        )
+        file_id: str = SchemaField(
+            description="File ID for document/video messages. "
+            "Use GetTelegramFileBlock to download."
+        )
+        file_name: str = SchemaField(
+            description="Original filename (for document/audio messages)"
+        )
+        caption: str = SchemaField(description="Caption for media messages")
+        is_edited: bool = SchemaField(
+            description="Whether this is an edit of a previously sent message"
+        )
+
+    def __init__(self):
+        super().__init__(
+            id="4435e4e0-df6e-4301-8f35-ad70b12fc9ec",
+            description="Triggers when a message is received or edited in your Telegram bot. "
+            "Supports text, photos, voice messages, audio files, documents, and videos.",
+            categories={BlockCategory.SOCIAL},
+            input_schema=TelegramMessageTriggerBlock.Input,
+            output_schema=TelegramMessageTriggerBlock.Output,
+            webhook_config=BlockWebhookConfig(
+                provider=ProviderName.TELEGRAM,
+                webhook_type=TelegramWebhookType.BOT,
+                resource_format="bot",
+                event_filter_input="events",
+                event_format="message.{event}",
+            ),
+            test_input={
+                "events": {"text": True, "photo": True},
+                "credentials": TEST_CREDENTIALS_INPUT,
+                "payload": EXAMPLE_MESSAGE_PAYLOAD,
+            },
+            test_credentials=TEST_CREDENTIALS,
+            test_output=[
+                ("payload", EXAMPLE_MESSAGE_PAYLOAD),
+                ("chat_id", 12345678),
+                ("message_id", 1),
+                ("user_id", 12345678),
+                ("username", "johndoe"),
+                ("first_name", "John"),
+                ("is_edited", False),
+                ("event", "text"),
+                ("text", "Hello, bot!"),
+                ("photo_file_id", ""),
+                ("voice_file_id", ""),
+                ("audio_file_id", ""),
+                ("file_id", ""),
+                ("file_name", ""),
+                ("caption", ""),
+            ],
+        )
+
+    async def run(self, input_data: Input, **kwargs) -> BlockOutput:
+        payload = input_data.payload
+        is_edited = "edited_message" in payload
+        message = payload.get("message") or payload.get("edited_message", {})
+
+        # Extract common fields
+        chat = message.get("chat", {})
+        sender = message.get("from", {})
+
+        yield "payload", payload
+        yield "chat_id", chat.get("id", 0)
+        yield "message_id", message.get("message_id", 0)
+        yield "user_id", sender.get("id", 0)
+        yield "username", sender.get("username", "")
+        yield "first_name", sender.get("first_name", "")
+        yield "is_edited", is_edited
+
+        # For edited messages, yield event as "edited_message" and extract
+        # all content fields from the edited message body
+        if is_edited:
+            yield "event", "edited_message"
+            yield "text", message.get("text", "")
+            photos = message.get("photo", [])
+            yield "photo_file_id", photos[-1].get("file_id", "") if photos else ""
+            voice = message.get("voice", {})
+            yield "voice_file_id", voice.get("file_id", "")
+            audio = message.get("audio", {})
+            yield "audio_file_id", audio.get("file_id", "")
+            document = message.get("document", {})
+            video = message.get("video", {})
+            yield "file_id", (document.get("file_id", "") or video.get("file_id", ""))
+            yield "file_name", (
+                document.get("file_name", "") or audio.get("file_name", "")
+            )
+            yield "caption", message.get("caption", "")
+        # Determine message type and extract content
+        elif "text" in message:
+            yield "event", "text"
+            yield "text", message.get("text", "")
+            yield "photo_file_id", ""
+            yield "voice_file_id", ""
+            yield "audio_file_id", ""
+            yield "file_id", ""
+            yield "file_name", ""
+            yield "caption", ""
+        elif "photo" in message:
+            # Get the largest photo (last in array)
+            photos = message.get("photo", [])
+            photo_fid = photos[-1].get("file_id", "") if photos else ""
+            yield "event", "photo"
+            yield "text", ""
+            yield "photo_file_id", photo_fid
+            yield "voice_file_id", ""
+            yield "audio_file_id", ""
+            yield "file_id", ""
+            yield "file_name", ""
+            yield "caption", message.get("caption", "")
+        elif "voice" in message:
+            voice = message.get("voice", {})
+            yield "event", "voice"
+            yield "text", ""
+            yield "photo_file_id", ""
+            yield "voice_file_id", voice.get("file_id", "")
+            yield "audio_file_id", ""
+            yield "file_id", ""
+            yield "file_name", ""
+            yield "caption", message.get("caption", "")
+        elif "audio" in message:
+            audio = message.get("audio", {})
+            yield "event", "audio"
+            yield "text", ""
+            yield "photo_file_id", ""
+            yield "voice_file_id", ""
+            yield "audio_file_id", audio.get("file_id", "")
+            yield "file_id", ""
+            yield "file_name", audio.get("file_name", "")
+            yield "caption", message.get("caption", "")
+        elif "document" in message:
+            document = message.get("document", {})
+            yield "event", "document"
+            yield "text", ""
+            yield "photo_file_id", ""
+            yield "voice_file_id", ""
+            yield "audio_file_id", ""
+            yield "file_id", document.get("file_id", "")
+            yield "file_name", document.get("file_name", "")
+            yield "caption", message.get("caption", "")
+        elif "video" in message:
+            video = message.get("video", {})
+            yield "event", "video"
+            yield "text", ""
+            yield "photo_file_id", ""
+            yield "voice_file_id", ""
+            yield "audio_file_id", ""
+            yield "file_id", video.get("file_id", "")
+            yield "file_name", video.get("file_name", "")
+            yield "caption", message.get("caption", "")
+        else:
+            yield "event", "other"
+            yield "text", ""
+            yield "photo_file_id", ""
+            yield "voice_file_id", ""
+            yield "audio_file_id", ""
+            yield "file_id", ""
+            yield "file_name", ""
+            yield "caption", ""
+
+
+# Example payload for reaction trigger testing
+EXAMPLE_REACTION_PAYLOAD = {
+    "update_id": 123456790,
+    "message_reaction": {
+        "chat": {
+            "id": 12345678,
+            "first_name": "John",
+            "last_name": "Doe",
+            "username": "johndoe",
+            "type": "private",
+        },
+        "message_id": 42,
+        "user": {
+            "id": 12345678,
+            "is_bot": False,
+            "first_name": "John",
+            "username": "johndoe",
+        },
+        "date": 1234567890,
+        "new_reaction": [{"type": "emoji", "emoji": "👍"}],
+        "old_reaction": [],
+    },
+}
+
+
+class TelegramMessageReactionTriggerBlock(TelegramTriggerBase, Block):
+    """
+    Triggers when a reaction to a message is changed.
+
+    Works automatically in private chats. In group chats, the bot must be
+    an administrator to receive reaction updates.
+    """
+
+    class Input(TelegramTriggerBase.Input):
+        pass
+
+    class Output(BlockSchemaOutput):
+        payload: dict = SchemaField(
+            description="The complete webhook payload from Telegram"
+        )
+        chat_id: int = SchemaField(
+            description="The chat ID where the reaction occurred"
+        )
+        message_id: int = SchemaField(description="The message ID that was reacted to")
+        user_id: int = SchemaField(description="The user ID who changed the reaction")
+        username: str = SchemaField(description="Username of the user (may be empty)")
+        new_reactions: list = SchemaField(
+            description="List of new reactions on the message"
+        )
+        old_reactions: list = SchemaField(
+            description="List of previous reactions on the message"
+        )
+
+    def __init__(self):
+        super().__init__(
+            id="82525328-9368-4966-8f0c-cd78e80181fd",
+            description="Triggers when a reaction to a message is changed. "
+            "Works in private chats automatically. "
+            "In groups, the bot must be an administrator.",
+            categories={BlockCategory.SOCIAL},
+            input_schema=TelegramMessageReactionTriggerBlock.Input,
+            output_schema=TelegramMessageReactionTriggerBlock.Output,
+            webhook_config=BlockWebhookConfig(
+                provider=ProviderName.TELEGRAM,
+                webhook_type=TelegramWebhookType.BOT,
+                resource_format="bot",
+                event_filter_input="",
+                event_format="message_reaction",
+            ),
+            test_input={
+                "credentials": TEST_CREDENTIALS_INPUT,
+                "payload": EXAMPLE_REACTION_PAYLOAD,
+            },
+            test_credentials=TEST_CREDENTIALS,
+            test_output=[
+                ("payload", EXAMPLE_REACTION_PAYLOAD),
+                ("chat_id", 12345678),
+                ("message_id", 42),
+                ("user_id", 12345678),
+                ("username", "johndoe"),
+                ("new_reactions", [{"type": "emoji", "emoji": "👍"}]),
+                ("old_reactions", []),
+            ],
+        )
+
+    async def run(self, input_data: Input, **kwargs) -> BlockOutput:
+        payload = input_data.payload
+        reaction = payload.get("message_reaction", {})
+
+        chat = reaction.get("chat", {})
+        user = reaction.get("user", {})
+
+        yield "payload", payload
+        yield "chat_id", chat.get("id", 0)
+        yield "message_id", reaction.get("message_id", 0)
+        yield "user_id", user.get("id", 0)
+        yield "username", user.get("username", "")
+        yield "new_reactions", reaction.get("new_reaction", [])
+        yield "old_reactions", reaction.get("old_reaction", [])

autogpt_platform/backend/backend/cli/generate_openapi_json.py

@@ -34,10 +34,12 @@ def main(output: Path, pretty: bool):
     """Generate and output the OpenAPI JSON specification."""
     openapi_schema = get_openapi_schema()
 
-    json_output = json.dumps(openapi_schema, indent=2 if pretty else None)
+    json_output = json.dumps(
+        openapi_schema, indent=2 if pretty else None, ensure_ascii=False
+    )
 
     if output:
-        output.write_text(json_output)
+        output.write_text(json_output, encoding="utf-8")
         click.echo(f"✅ OpenAPI specification written to {output}\n\nPreview:")
         click.echo(f"\n{json_output[:500]} ...")
     else:

autogpt_platform/backend/backend/conftest.py

@@ -1,6 +1,7 @@
 import logging
 import os
 
+import pytest
 import pytest_asyncio
 from dotenv import load_dotenv
 
@@ -27,6 +28,54 @@ async def server():
         yield server
 
 
+@pytest.fixture
+def test_user_id() -> str:
+    """Test user ID fixture."""
+    return "3e53486c-cf57-477e-ba2a-cb02dc828e1a"
+
+
+@pytest.fixture
+def admin_user_id() -> str:
+    """Admin user ID fixture."""
+    return "4e53486c-cf57-477e-ba2a-cb02dc828e1b"
+
+
+@pytest.fixture
+def target_user_id() -> str:
+    """Target user ID fixture."""
+    return "5e53486c-cf57-477e-ba2a-cb02dc828e1c"
+
+
+@pytest.fixture
+async def setup_test_user(test_user_id):
+    """Create test user in database before tests."""
+    from backend.data.user import get_or_create_user
+
+    # Create the test user in the database using JWT token format
+    user_data = {
+        "sub": test_user_id,
+        "email": "test@example.com",
+        "user_metadata": {"name": "Test User"},
+    }
+    await get_or_create_user(user_data)
+    return test_user_id
+
+
+@pytest.fixture
+async def setup_admin_user(admin_user_id):
+    """Create admin user in database before tests."""
+    from backend.data.user import get_or_create_user
+
+    # Create the admin user in the database using JWT token format
+    user_data = {
+        "sub": admin_user_id,
+        "email": "test-admin@example.com",
+        "user_metadata": {"name": "Test Admin"},
+    }
+    await get_or_create_user(user_data)
+    return admin_user_id
+
+
 @pytest_asyncio.fixture(scope="session", loop_scope="session", autouse=True)
 async def graph_cleanup(server):
     created_graph_ids = []

autogpt_platform/backend/backend/copilot/__init__.py

@@ -0,0 +1 @@
+

autogpt_platform/backend/backend/copilot/baseline/__init__.py

@@ -0,0 +1,3 @@
+from .service import stream_chat_completion_baseline
+
+__all__ = ["stream_chat_completion_baseline"]

autogpt_platform/backend/backend/copilot/baseline/service.py

@@ -0,0 +1,420 @@
+"""Baseline LLM fallback — OpenAI-compatible streaming with tool calling.
+
+Used when ``CHAT_USE_CLAUDE_AGENT_SDK=false``, e.g. as a fallback when the
+Claude Agent SDK / Anthropic API is unavailable.  Routes through any
+OpenAI-compatible provider (OpenRouter by default) and reuses the same
+shared tool registry as the SDK path.
+"""
+
+import asyncio
+import logging
+import uuid
+from collections.abc import AsyncGenerator
+from typing import Any
+
+import orjson
+from langfuse import propagate_attributes
+
+from backend.copilot.model import (
+    ChatMessage,
+    ChatSession,
+    get_chat_session,
+    update_session_title,
+    upsert_chat_session,
+)
+from backend.copilot.response_model import (
+    StreamBaseResponse,
+    StreamError,
+    StreamFinish,
+    StreamFinishStep,
+    StreamStart,
+    StreamStartStep,
+    StreamTextDelta,
+    StreamTextEnd,
+    StreamTextStart,
+    StreamToolInputAvailable,
+    StreamToolInputStart,
+    StreamToolOutputAvailable,
+)
+from backend.copilot.service import (
+    _build_system_prompt,
+    _generate_session_title,
+    client,
+    config,
+)
+from backend.copilot.tools import execute_tool, get_available_tools
+from backend.copilot.tracking import track_user_message
+from backend.util.exceptions import NotFoundError
+from backend.util.prompt import compress_context
+
+logger = logging.getLogger(__name__)
+
+# Set to hold background tasks to prevent garbage collection
+_background_tasks: set[asyncio.Task[Any]] = set()
+
+# Maximum number of tool-call rounds before forcing a text response.
+_MAX_TOOL_ROUNDS = 30
+
+
+async def _update_title_async(
+    session_id: str, message: str, user_id: str | None
+) -> None:
+    """Generate and persist a session title in the background."""
+    try:
+        title = await _generate_session_title(message, user_id, session_id)
+        if title and user_id:
+            await update_session_title(session_id, user_id, title, only_if_empty=True)
+    except Exception as e:
+        logger.warning("[Baseline] Failed to update session title: %s", e)
+
+
+async def _compress_session_messages(
+    messages: list[ChatMessage],
+) -> list[ChatMessage]:
+    """Compress session messages if they exceed the model's token limit.
+
+    Uses the shared compress_context() utility which supports LLM-based
+    summarization of older messages while keeping recent ones intact,
+    with progressive truncation and middle-out deletion as fallbacks.
+    """
+    messages_dict = []
+    for msg in messages:
+        msg_dict: dict[str, Any] = {"role": msg.role}
+        if msg.content:
+            msg_dict["content"] = msg.content
+        messages_dict.append(msg_dict)
+
+    try:
+        result = await compress_context(
+            messages=messages_dict,
+            model=config.model,
+            client=client,
+        )
+    except Exception as e:
+        logger.warning("[Baseline] Context compression with LLM failed: %s", e)
+        result = await compress_context(
+            messages=messages_dict,
+            model=config.model,
+            client=None,
+        )
+
+    if result.was_compacted:
+        logger.info(
+            "[Baseline] Context compacted: %d -> %d tokens "
+            "(%d summarized, %d dropped)",
+            result.original_token_count,
+            result.token_count,
+            result.messages_summarized,
+            result.messages_dropped,
+        )
+        return [
+            ChatMessage(role=m["role"], content=m.get("content"))
+            for m in result.messages
+        ]
+
+    return messages
+
+
+async def stream_chat_completion_baseline(
+    session_id: str,
+    message: str | None = None,
+    is_user_message: bool = True,
+    user_id: str | None = None,
+    session: ChatSession | None = None,
+    **_kwargs: Any,
+) -> AsyncGenerator[StreamBaseResponse, None]:
+    """Baseline LLM with tool calling via OpenAI-compatible API.
+
+    Designed as a fallback when the Claude Agent SDK is unavailable.
+    Uses the same tool registry as the SDK path but routes through any
+    OpenAI-compatible provider (e.g. OpenRouter).
+
+    Flow: stream response -> if tool_calls, execute them -> feed results back -> repeat.
+    """
+    if session is None:
+        session = await get_chat_session(session_id, user_id)
+
+    if not session:
+        raise NotFoundError(
+            f"Session {session_id} not found. Please create a new session first."
+        )
+
+    # Append user message
+    new_role = "user" if is_user_message else "assistant"
+    if message and (
+        len(session.messages) == 0
+        or not (
+            session.messages[-1].role == new_role
+            and session.messages[-1].content == message
+        )
+    ):
+        session.messages.append(ChatMessage(role=new_role, content=message))
+        if is_user_message:
+            track_user_message(
+                user_id=user_id,
+                session_id=session_id,
+                message_length=len(message),
+            )
+
+    session = await upsert_chat_session(session)
+
+    # Generate title for new sessions
+    if is_user_message and not session.title:
+        user_messages = [m for m in session.messages if m.role == "user"]
+        if len(user_messages) == 1:
+            first_message = user_messages[0].content or message or ""
+            if first_message:
+                task = asyncio.create_task(
+                    _update_title_async(session_id, first_message, user_id)
+                )
+                _background_tasks.add(task)
+                task.add_done_callback(_background_tasks.discard)
+
+    message_id = str(uuid.uuid4())
+
+    # Build system prompt only on the first turn to avoid mid-conversation
+    # changes from concurrent chats updating business understanding.
+    is_first_turn = len(session.messages) <= 1
+    if is_first_turn:
+        system_prompt, _ = await _build_system_prompt(
+            user_id, has_conversation_history=False
+        )
+    else:
+        system_prompt, _ = await _build_system_prompt(
+            user_id=None, has_conversation_history=True
+        )
+
+    # Compress context if approaching the model's token limit
+    messages_for_context = await _compress_session_messages(session.messages)
+
+    # Build OpenAI message list from session history
+    openai_messages: list[dict[str, Any]] = [
+        {"role": "system", "content": system_prompt}
+    ]
+    for msg in messages_for_context:
+        if msg.role in ("user", "assistant") and msg.content:
+            openai_messages.append({"role": msg.role, "content": msg.content})
+
+    tools = get_available_tools()
+
+    yield StreamStart(messageId=message_id, sessionId=session_id)
+
+    # Propagate user/session context to Langfuse so all LLM calls within
+    # this request are grouped under a single trace with proper attribution.
+    _trace_ctx: Any = None
+    try:
+        _trace_ctx = propagate_attributes(
+            user_id=user_id,
+            session_id=session_id,
+            trace_name="copilot-baseline",
+            tags=["baseline"],
+        )
+        _trace_ctx.__enter__()
+    except Exception:
+        logger.warning("[Baseline] Langfuse trace context setup failed")
+
+    assistant_text = ""
+    text_block_id = str(uuid.uuid4())
+    text_started = False
+    step_open = False
+    try:
+        for _round in range(_MAX_TOOL_ROUNDS):
+            # Open a new step for each LLM round
+            yield StreamStartStep()
+            step_open = True
+
+            # Stream a response from the model
+            create_kwargs: dict[str, Any] = dict(
+                model=config.model,
+                messages=openai_messages,
+                stream=True,
+            )
+            if tools:
+                create_kwargs["tools"] = tools
+            response = await client.chat.completions.create(**create_kwargs)  # type: ignore[arg-type]  # dynamic kwargs
+
+            # Accumulate streamed response (text + tool calls)
+            round_text = ""
+            tool_calls_by_index: dict[int, dict[str, str]] = {}
+
+            async for chunk in response:
+                delta = chunk.choices[0].delta if chunk.choices else None
+                if not delta:
+                    continue
+
+                # Text content
+                if delta.content:
+                    if not text_started:
+                        yield StreamTextStart(id=text_block_id)
+                        text_started = True
+                    round_text += delta.content
+                    yield StreamTextDelta(id=text_block_id, delta=delta.content)
+
+                # Tool call fragments (streamed incrementally)
+                if delta.tool_calls:
+                    for tc in delta.tool_calls:
+                        idx = tc.index
+                        if idx not in tool_calls_by_index:
+                            tool_calls_by_index[idx] = {
+                                "id": "",
+                                "name": "",
+                                "arguments": "",
+                            }
+                        entry = tool_calls_by_index[idx]
+                        if tc.id:
+                            entry["id"] = tc.id
+                        if tc.function and tc.function.name:
+                            entry["name"] = tc.function.name
+                        if tc.function and tc.function.arguments:
+                            entry["arguments"] += tc.function.arguments
+
+            # Close text block if we had one this round
+            if text_started:
+                yield StreamTextEnd(id=text_block_id)
+                text_started = False
+                text_block_id = str(uuid.uuid4())
+
+            # Accumulate text for session persistence
+            assistant_text += round_text
+
+            # No tool calls -> model is done
+            if not tool_calls_by_index:
+                yield StreamFinishStep()
+                step_open = False
+                break
+
+            # Close step before tool execution
+            yield StreamFinishStep()
+            step_open = False
+
+            # Append the assistant message with tool_calls to context.
+            assistant_msg: dict[str, Any] = {"role": "assistant"}
+            if round_text:
+                assistant_msg["content"] = round_text
+            assistant_msg["tool_calls"] = [
+                {
+                    "id": tc["id"],
+                    "type": "function",
+                    "function": {
+                        "name": tc["name"],
+                        "arguments": tc["arguments"] or "{}",
+                    },
+                }
+                for tc in tool_calls_by_index.values()
+            ]
+            openai_messages.append(assistant_msg)
+
+            # Execute each tool call and stream events
+            for tc in tool_calls_by_index.values():
+                tool_call_id = tc["id"]
+                tool_name = tc["name"]
+                raw_args = tc["arguments"] or "{}"
+                try:
+                    tool_args = orjson.loads(raw_args)
+                except orjson.JSONDecodeError as parse_err:
+                    parse_error = (
+                        f"Invalid JSON arguments for tool '{tool_name}': {parse_err}"
+                    )
+                    logger.warning("[Baseline] %s", parse_error)
+                    yield StreamToolOutputAvailable(
+                        toolCallId=tool_call_id,
+                        toolName=tool_name,
+                        output=parse_error,
+                        success=False,
+                    )
+                    openai_messages.append(
+                        {
+                            "role": "tool",
+                            "tool_call_id": tool_call_id,
+                            "content": parse_error,
+                        }
+                    )
+                    continue
+
+                yield StreamToolInputStart(toolCallId=tool_call_id, toolName=tool_name)
+                yield StreamToolInputAvailable(
+                    toolCallId=tool_call_id,
+                    toolName=tool_name,
+                    input=tool_args,
+                )
+
+                # Execute via shared tool registry
+                try:
+                    result: StreamToolOutputAvailable = await execute_tool(
+                        tool_name=tool_name,
+                        parameters=tool_args,
+                        user_id=user_id,
+                        session=session,
+                        tool_call_id=tool_call_id,
+                    )
+                    yield result
+                    tool_output = (
+                        result.output
+                        if isinstance(result.output, str)
+                        else str(result.output)
+                    )
+                except Exception as e:
+                    error_output = f"Tool execution error: {e}"
+                    logger.error(
+                        "[Baseline] Tool %s failed: %s",
+                        tool_name,
+                        error_output,
+                        exc_info=True,
+                    )
+                    yield StreamToolOutputAvailable(
+                        toolCallId=tool_call_id,
+                        toolName=tool_name,
+                        output=error_output,
+                        success=False,
+                    )
+                    tool_output = error_output
+
+                # Append tool result to context for next round
+                openai_messages.append(
+                    {
+                        "role": "tool",
+                        "tool_call_id": tool_call_id,
+                        "content": tool_output,
+                    }
+                )
+        else:
+            # for-loop exhausted without break -> tool-round limit hit
+            limit_msg = (
+                f"Exceeded {_MAX_TOOL_ROUNDS} tool-call rounds "
+                "without a final response."
+            )
+            logger.error("[Baseline] %s", limit_msg)
+            yield StreamError(
+                errorText=limit_msg,
+                code="baseline_tool_round_limit",
+            )
+
+    except Exception as e:
+        error_msg = str(e) or type(e).__name__
+        logger.error("[Baseline] Streaming error: %s", error_msg, exc_info=True)
+        # Close any open text/step before emitting error
+        if text_started:
+            yield StreamTextEnd(id=text_block_id)
+        if step_open:
+            yield StreamFinishStep()
+        yield StreamError(errorText=error_msg, code="baseline_error")
+        # Still persist whatever we got
+    finally:
+        # Close Langfuse trace context
+        if _trace_ctx is not None:
+            try:
+                _trace_ctx.__exit__(None, None, None)
+            except Exception:
+                logger.warning("[Baseline] Langfuse trace context teardown failed")
+
+        # Persist assistant response
+        if assistant_text:
+            session.messages.append(
+                ChatMessage(role="assistant", content=assistant_text)
+            )
+        try:
+            await upsert_chat_session(session)
+        except Exception as persist_err:
+            logger.error("[Baseline] Failed to persist session: %s", persist_err)
+
+    yield StreamFinish()

autogpt_platform/backend/backend/copilot/baseline/service_test.py

@@ -0,0 +1,99 @@
+import logging
+from os import getenv
+
+import pytest
+
+from backend.copilot.baseline import stream_chat_completion_baseline
+from backend.copilot.model import (
+    create_chat_session,
+    get_chat_session,
+    upsert_chat_session,
+)
+from backend.copilot.response_model import (
+    StreamError,
+    StreamFinish,
+    StreamStart,
+    StreamTextDelta,
+)
+
+logger = logging.getLogger(__name__)
+
+
+@pytest.mark.asyncio(loop_scope="session")
+async def test_baseline_multi_turn(setup_test_user, test_user_id):
+    """Test that the baseline LLM path streams responses and maintains history.
+
+    Turn 1: Send a message with a unique keyword.
+    Turn 2: Ask the model to recall the keyword — proving conversation history
+    is correctly passed to the single-call LLM.
+    """
+    api_key: str | None = getenv("OPEN_ROUTER_API_KEY")
+    if not api_key:
+        return pytest.skip("OPEN_ROUTER_API_KEY is not set, skipping test")
+
+    session = await create_chat_session(test_user_id)
+    session = await upsert_chat_session(session)
+
+    # --- Turn 1: send a message with a unique keyword ---
+    keyword = "QUASAR99"
+    turn1_msg = (
+        f"Please remember this special keyword: {keyword}. "
+        "Just confirm you've noted it, keep your response brief."
+    )
+    turn1_text = ""
+    turn1_errors: list[str] = []
+    got_start = False
+    got_finish = False
+
+    async for chunk in stream_chat_completion_baseline(
+        session.session_id,
+        turn1_msg,
+        user_id=test_user_id,
+    ):
+        if isinstance(chunk, StreamStart):
+            got_start = True
+        elif isinstance(chunk, StreamTextDelta):
+            turn1_text += chunk.delta
+        elif isinstance(chunk, StreamError):
+            turn1_errors.append(chunk.errorText)
+        elif isinstance(chunk, StreamFinish):
+            got_finish = True
+
+    assert got_start, "Turn 1 did not yield StreamStart"
+    assert got_finish, "Turn 1 did not yield StreamFinish"
+    assert not turn1_errors, f"Turn 1 errors: {turn1_errors}"
+    assert turn1_text, "Turn 1 produced no text"
+    logger.info(f"Turn 1 response: {turn1_text[:100]}")
+
+    # Reload session for turn 2
+    session = await get_chat_session(session.session_id, test_user_id)
+    assert session, "Session not found after turn 1"
+
+    # Verify messages were persisted (user + assistant)
+    assert (
+        len(session.messages) >= 2
+    ), f"Expected at least 2 messages after turn 1, got {len(session.messages)}"
+
+    # --- Turn 2: ask model to recall the keyword ---
+    turn2_msg = "What was the special keyword I asked you to remember?"
+    turn2_text = ""
+    turn2_errors: list[str] = []
+
+    async for chunk in stream_chat_completion_baseline(
+        session.session_id,
+        turn2_msg,
+        user_id=test_user_id,
+        session=session,
+    ):
+        if isinstance(chunk, StreamTextDelta):
+            turn2_text += chunk.delta
+        elif isinstance(chunk, StreamError):
+            turn2_errors.append(chunk.errorText)
+
+    assert not turn2_errors, f"Turn 2 errors: {turn2_errors}"
+    assert turn2_text, "Turn 2 produced no text"
+    assert keyword in turn2_text, (
+        f"Model did not recall keyword '{keyword}' in turn 2. "
+        f"Response: {turn2_text[:200]}"
+    )
+    logger.info(f"Turn 2 recalled keyword successfully: {turn2_text[:100]}")

autogpt_platform/backend/backend/copilot/config.py

@@ -0,0 +1,201 @@
+"""Configuration management for chat system."""
+
+import os
+
+from pydantic import Field, field_validator
+from pydantic_settings import BaseSettings
+
+
+class ChatConfig(BaseSettings):
+    """Configuration for the chat system."""
+
+    # OpenAI API Configuration
+    model: str = Field(
+        default="anthropic/claude-opus-4.6", description="Default model to use"
+    )
+    title_model: str = Field(
+        default="openai/gpt-4o-mini",
+        description="Model to use for generating session titles (should be fast/cheap)",
+    )
+    api_key: str | None = Field(default=None, description="OpenAI API key")
+    base_url: str | None = Field(
+        default="https://openrouter.ai/api/v1",
+        description="Base URL for API (e.g., for OpenRouter)",
+    )
+
+    # Session TTL Configuration - 12 hours
+    session_ttl: int = Field(default=43200, description="Session TTL in seconds")
+
+    max_agent_runs: int = Field(default=30, description="Maximum number of agent runs")
+    max_agent_schedules: int = Field(
+        default=30, description="Maximum number of agent schedules"
+    )
+
+    # Stream registry configuration for SSE reconnection
+    stream_ttl: int = Field(
+        default=3600,
+        description="TTL in seconds for stream data in Redis (1 hour)",
+    )
+    stream_lock_ttl: int = Field(
+        default=120,
+        description="TTL in seconds for stream lock (2 minutes). Short timeout allows "
+        "reconnection after refresh/crash without long waits.",
+    )
+    stream_max_length: int = Field(
+        default=10000,
+        description="Maximum number of messages to store per stream",
+    )
+
+    # Redis key prefixes for stream registry
+    session_meta_prefix: str = Field(
+        default="chat:task:meta:",
+        description="Prefix for session metadata hash keys",
+    )
+    turn_stream_prefix: str = Field(
+        default="chat:stream:",
+        description="Prefix for turn message stream keys",
+    )
+
+    # Langfuse Prompt Management Configuration
+    # Note: Langfuse credentials are in Settings().secrets (settings.py)
+    langfuse_prompt_name: str = Field(
+        default="CoPilot Prompt",
+        description="Name of the prompt in Langfuse to fetch",
+    )
+    langfuse_prompt_cache_ttl: int = Field(
+        default=300,
+        description="Cache TTL in seconds for Langfuse prompt (0 to disable caching)",
+    )
+
+    # Claude Agent SDK Configuration
+    use_claude_agent_sdk: bool = Field(
+        default=True,
+        description="Use Claude Agent SDK (True) or OpenAI-compatible LLM baseline (False)",
+    )
+    claude_agent_model: str | None = Field(
+        default=None,
+        description="Model for the Claude Agent SDK path. If None, derives from "
+        "the `model` field by stripping the OpenRouter provider prefix.",
+    )
+    claude_agent_max_buffer_size: int = Field(
+        default=10 * 1024 * 1024,  # 10MB (default SDK is 1MB)
+        description="Max buffer size in bytes for Claude Agent SDK JSON message parsing. "
+        "Increase if tool outputs exceed the limit.",
+    )
+    claude_agent_max_subtasks: int = Field(
+        default=10,
+        description="Max number of concurrent sub-agent Tasks the SDK can run per session.",
+    )
+    claude_agent_use_resume: bool = Field(
+        default=True,
+        description="Use --resume for multi-turn conversations instead of "
+        "history compression. Falls back to compression when unavailable.",
+    )
+    use_claude_code_subscription: bool = Field(
+        default=False,
+        description="For personal/dev use: use Claude Code CLI subscription auth instead of API keys. Requires `claude login` on the host. Only works with SDK mode.",
+    )
+
+    # E2B Sandbox Configuration
+    use_e2b_sandbox: bool = Field(
+        default=True,
+        description="Use E2B cloud sandboxes for persistent bash/python execution. "
+        "When enabled, bash_exec routes commands to E2B and SDK file tools "
+        "operate directly on the sandbox via E2B's filesystem API.",
+    )
+    e2b_api_key: str | None = Field(
+        default=None,
+        description="E2B API key. Falls back to E2B_API_KEY environment variable.",
+    )
+    e2b_sandbox_template: str = Field(
+        default="base",
+        description="E2B sandbox template to use for copilot sessions.",
+    )
+    e2b_sandbox_timeout: int = Field(
+        default=43200,  # 12 hours — same as session_ttl
+        description="E2B sandbox keepalive timeout in seconds.",
+    )
+
+    @field_validator("use_e2b_sandbox", mode="before")
+    @classmethod
+    def get_use_e2b_sandbox(cls, v):
+        """Get use_e2b_sandbox from environment if not provided."""
+        env_val = os.getenv("CHAT_USE_E2B_SANDBOX", "").lower()
+        if env_val:
+            return env_val in ("true", "1", "yes", "on")
+        return True if v is None else v
+
+    @field_validator("e2b_api_key", mode="before")
+    @classmethod
+    def get_e2b_api_key(cls, v):
+        """Get E2B API key from environment if not provided."""
+        if not v:
+            v = os.getenv("CHAT_E2B_API_KEY") or os.getenv("E2B_API_KEY")
+        return v
+
+    @field_validator("api_key", mode="before")
+    @classmethod
+    def get_api_key(cls, v):
+        """Get API key from environment if not provided."""
+        if not v:
+            # Try to get from environment variables
+            # First check for CHAT_API_KEY (Pydantic prefix)
+            v = os.getenv("CHAT_API_KEY")
+            if not v:
+                # Fall back to OPEN_ROUTER_API_KEY
+                v = os.getenv("OPEN_ROUTER_API_KEY")
+            if not v:
+                # Fall back to OPENAI_API_KEY
+                v = os.getenv("OPENAI_API_KEY")
+            # Note: ANTHROPIC_API_KEY is intentionally NOT included here.
+            # The SDK CLI picks it up from the env directly. Including it
+            # would pair it with the OpenRouter base_url, causing auth failures.
+        return v
+
+    @field_validator("base_url", mode="before")
+    @classmethod
+    def get_base_url(cls, v):
+        """Get base URL from environment if not provided."""
+        if not v:
+            # Check for OpenRouter or custom base URL
+            v = os.getenv("CHAT_BASE_URL")
+            if not v:
+                v = os.getenv("OPENROUTER_BASE_URL")
+            if not v:
+                v = os.getenv("OPENAI_BASE_URL")
+            if not v:
+                v = "https://openrouter.ai/api/v1"
+        return v
+
+    @field_validator("use_claude_agent_sdk", mode="before")
+    @classmethod
+    def get_use_claude_agent_sdk(cls, v):
+        """Get use_claude_agent_sdk from environment if not provided."""
+        # Check environment variable - default to True if not set
+        env_val = os.getenv("CHAT_USE_CLAUDE_AGENT_SDK", "").lower()
+        if env_val:
+            return env_val in ("true", "1", "yes", "on")
+        # Default to True (SDK enabled by default)
+        return True if v is None else v
+
+    @field_validator("use_claude_code_subscription", mode="before")
+    @classmethod
+    def get_use_claude_code_subscription(cls, v):
+        """Get use_claude_code_subscription from environment if not provided."""
+        env_val = os.getenv("CHAT_USE_CLAUDE_CODE_SUBSCRIPTION", "").lower()
+        if env_val:
+            return env_val in ("true", "1", "yes", "on")
+        return False if v is None else v
+
+    # Prompt paths for different contexts
+    PROMPT_PATHS: dict[str, str] = {
+        "default": "prompts/chat_system.md",
+        "onboarding": "prompts/onboarding_system.md",
+    }
+
+    class Config:
+        """Pydantic config."""
+
+        env_file = ".env"
+        env_file_encoding = "utf-8"
+        extra = "ignore"  # Ignore extra environment variables

autogpt_platform/backend/backend/copilot/constants.py

@@ -0,0 +1,11 @@
+"""Shared constants for the CoPilot module."""
+
+# Special message prefixes for text-based markers (parsed by frontend).
+# The hex suffix makes accidental LLM generation of these strings virtually
+# impossible, avoiding false-positive marker detection in normal conversation.
+COPILOT_ERROR_PREFIX = "[__COPILOT_ERROR_f7a1__]"  # Renders as ErrorCard
+COPILOT_SYSTEM_PREFIX = "[__COPILOT_SYSTEM_e3b0__]"  # Renders as system info message
+
+# Compaction notice messages shown to users.
+COMPACTION_DONE_MSG = "Earlier messages were summarized to fit within context limits."
+COMPACTION_TOOL_NAME = "context_compaction"

autogpt_platform/backend/backend/copilot/db.py

@@ -0,0 +1,361 @@
+"""Database operations for chat sessions."""
+
+import asyncio
+import logging
+from datetime import UTC, datetime
+from typing import Any
+
+from prisma.errors import UniqueViolationError
+from prisma.models import ChatMessage as PrismaChatMessage
+from prisma.models import ChatSession as PrismaChatSession
+from prisma.types import (
+    ChatMessageCreateInput,
+    ChatSessionCreateInput,
+    ChatSessionUpdateInput,
+    ChatSessionWhereInput,
+)
+
+from backend.data import db
+from backend.util.json import SafeJson, sanitize_string
+
+from .model import ChatMessage, ChatSession, ChatSessionInfo
+
+logger = logging.getLogger(__name__)
+
+
+async def get_chat_session(session_id: str) -> ChatSession | None:
+    """Get a chat session by ID from the database."""
+    session = await PrismaChatSession.prisma().find_unique(
+        where={"id": session_id},
+        include={"Messages": {"order_by": {"sequence": "asc"}}},
+    )
+    return ChatSession.from_db(session) if session else None
+
+
+async def create_chat_session(
+    session_id: str,
+    user_id: str,
+) -> ChatSessionInfo:
+    """Create a new chat session in the database."""
+    data = ChatSessionCreateInput(
+        id=session_id,
+        userId=user_id,
+        credentials=SafeJson({}),
+        successfulAgentRuns=SafeJson({}),
+        successfulAgentSchedules=SafeJson({}),
+    )
+    prisma_session = await PrismaChatSession.prisma().create(data=data)
+    return ChatSessionInfo.from_db(prisma_session)
+
+
+async def update_chat_session(
+    session_id: str,
+    credentials: dict[str, Any] | None = None,
+    successful_agent_runs: dict[str, Any] | None = None,
+    successful_agent_schedules: dict[str, Any] | None = None,
+    total_prompt_tokens: int | None = None,
+    total_completion_tokens: int | None = None,
+    title: str | None = None,
+) -> ChatSession | None:
+    """Update a chat session's metadata."""
+    data: ChatSessionUpdateInput = {"updatedAt": datetime.now(UTC)}
+
+    if credentials is not None:
+        data["credentials"] = SafeJson(credentials)
+    if successful_agent_runs is not None:
+        data["successfulAgentRuns"] = SafeJson(successful_agent_runs)
+    if successful_agent_schedules is not None:
+        data["successfulAgentSchedules"] = SafeJson(successful_agent_schedules)
+    if total_prompt_tokens is not None:
+        data["totalPromptTokens"] = total_prompt_tokens
+    if total_completion_tokens is not None:
+        data["totalCompletionTokens"] = total_completion_tokens
+    if title is not None:
+        data["title"] = title
+
+    session = await PrismaChatSession.prisma().update(
+        where={"id": session_id},
+        data=data,
+        include={"Messages": {"order_by": {"sequence": "asc"}}},
+    )
+    return ChatSession.from_db(session) if session else None
+
+
+async def update_chat_session_title(
+    session_id: str,
+    user_id: str,
+    title: str,
+    *,
+    only_if_empty: bool = False,
+) -> bool:
+    """Update the title of a chat session, scoped to the owning user.
+
+    Always filters by (session_id, user_id) so callers cannot mutate another
+    user's session even when they know the session_id.
+
+    Args:
+        only_if_empty: When True, uses an atomic ``UPDATE WHERE title IS NULL``
+            guard so auto-generated titles never overwrite a user-set title.
+
+    Returns True if a row was updated, False otherwise (session not found,
+    wrong user, or — when only_if_empty — title was already set).
+    """
+    where: ChatSessionWhereInput = {"id": session_id, "userId": user_id}
+    if only_if_empty:
+        where["title"] = None
+    result = await PrismaChatSession.prisma().update_many(
+        where=where,
+        data={"title": title, "updatedAt": datetime.now(UTC)},
+    )
+    return result > 0
+
+
+async def add_chat_message(
+    session_id: str,
+    role: str,
+    sequence: int,
+    content: str | None = None,
+    name: str | None = None,
+    tool_call_id: str | None = None,
+    refusal: str | None = None,
+    tool_calls: list[dict[str, Any]] | None = None,
+    function_call: dict[str, Any] | None = None,
+) -> ChatMessage:
+    """Add a message to a chat session."""
+    # Build ChatMessageCreateInput with only non-None values
+    # (Prisma TypedDict rejects optional fields set to None)
+    data: ChatMessageCreateInput = {
+        "Session": {"connect": {"id": session_id}},
+        "role": role,
+        "sequence": sequence,
+    }
+
+    # Add optional string fields — sanitize to strip PostgreSQL-incompatible
+    # control characters (null bytes etc.) that may appear in tool outputs.
+    if content is not None:
+        data["content"] = sanitize_string(content)
+    if name is not None:
+        data["name"] = name
+    if tool_call_id is not None:
+        data["toolCallId"] = tool_call_id
+    if refusal is not None:
+        data["refusal"] = sanitize_string(refusal)
+
+    # Add optional JSON fields only when they have values
+    if tool_calls is not None:
+        data["toolCalls"] = SafeJson(tool_calls)
+    if function_call is not None:
+        data["functionCall"] = SafeJson(function_call)
+
+    # Run message create and session timestamp update in parallel for lower latency
+    _, message = await asyncio.gather(
+        PrismaChatSession.prisma().update(
+            where={"id": session_id},
+            data={"updatedAt": datetime.now(UTC)},
+        ),
+        PrismaChatMessage.prisma().create(data=data),
+    )
+    return ChatMessage.from_db(message)
+
+
+async def add_chat_messages_batch(
+    session_id: str,
+    messages: list[dict[str, Any]],
+    start_sequence: int,
+) -> int:
+    """Add multiple messages to a chat session in a batch.
+
+    Uses collision detection with retry: tries to create messages starting
+    at start_sequence. If a unique constraint violation occurs (e.g., the
+    streaming loop and long-running callback race), queries the latest
+    sequence and retries with the correct offset. This avoids unnecessary
+    upserts and DB queries in the common case (no collision).
+
+    Returns:
+        Next sequence number for the next message to be inserted. This equals
+        start_sequence + len(messages) and allows callers to update their
+        counters even when collision detection adjusts start_sequence.
+    """
+    if not messages:
+        # No messages to add - return current count
+        return start_sequence
+
+    max_retries = 5
+    for attempt in range(max_retries):
+        try:
+            # Single timestamp for all messages and session update
+            now = datetime.now(UTC)
+
+            async with db.transaction() as tx:
+                # Build all message data
+                messages_data = []
+                for i, msg in enumerate(messages):
+                    # Build ChatMessageCreateInput with only non-None values
+                    # (Prisma TypedDict rejects optional fields set to None)
+                    # Note: create_many doesn't support nested creates, use sessionId directly
+                    data: ChatMessageCreateInput = {
+                        "sessionId": session_id,
+                        "role": msg["role"],
+                        "sequence": start_sequence + i,
+                        "createdAt": now,
+                    }
+
+                    # Add optional string fields — sanitize to strip
+                    # PostgreSQL-incompatible control characters.
+                    if msg.get("content") is not None:
+                        data["content"] = sanitize_string(msg["content"])
+                    if msg.get("name") is not None:
+                        data["name"] = msg["name"]
+                    if msg.get("tool_call_id") is not None:
+                        data["toolCallId"] = msg["tool_call_id"]
+                    if msg.get("refusal") is not None:
+                        data["refusal"] = sanitize_string(msg["refusal"])
+
+                    # Add optional JSON fields only when they have values
+                    if msg.get("tool_calls") is not None:
+                        data["toolCalls"] = SafeJson(msg["tool_calls"])
+                    if msg.get("function_call") is not None:
+                        data["functionCall"] = SafeJson(msg["function_call"])
+
+                    messages_data.append(data)
+
+                # Run create_many and session update in parallel within transaction
+                # Both use the same timestamp for consistency
+                await asyncio.gather(
+                    PrismaChatMessage.prisma(tx).create_many(data=messages_data),
+                    PrismaChatSession.prisma(tx).update(
+                        where={"id": session_id},
+                        data={"updatedAt": now},
+                    ),
+                )
+
+            # Return next sequence number for counter sync
+            return start_sequence + len(messages)
+
+        except UniqueViolationError:
+            if attempt < max_retries - 1:
+                # Collision detected - query MAX(sequence)+1 and retry with correct offset
+                logger.info(
+                    f"Collision detected for session {session_id} at sequence "
+                    f"{start_sequence}, querying DB for latest sequence"
+                )
+                start_sequence = await get_next_sequence(session_id)
+                logger.info(
+                    f"Retrying batch insert with start_sequence={start_sequence}"
+                )
+                continue
+            else:
+                # Max retries exceeded - propagate error
+                raise
+
+    # Should never reach here due to raise in exception handler
+    raise RuntimeError(f"Failed to insert messages after {max_retries} attempts")
+
+
+async def get_user_chat_sessions(
+    user_id: str,
+    limit: int = 50,
+    offset: int = 0,
+) -> list[ChatSessionInfo]:
+    """Get chat sessions for a user, ordered by most recent."""
+    prisma_sessions = await PrismaChatSession.prisma().find_many(
+        where={"userId": user_id},
+        order={"updatedAt": "desc"},
+        take=limit,
+        skip=offset,
+    )
+    return [ChatSessionInfo.from_db(s) for s in prisma_sessions]
+
+
+async def get_user_session_count(user_id: str) -> int:
+    """Get the total number of chat sessions for a user."""
+    return await PrismaChatSession.prisma().count(where={"userId": user_id})
+
+
+async def delete_chat_session(session_id: str, user_id: str | None = None) -> bool:
+    """Delete a chat session and all its messages.
+
+    Args:
+        session_id: The session ID to delete.
+        user_id: If provided, validates that the session belongs to this user
+            before deletion. This prevents unauthorized deletion of other
+            users' sessions.
+
+    Returns:
+        True if deleted successfully, False otherwise.
+    """
+    try:
+        # Build typed where clause with optional user_id validation
+        where_clause: ChatSessionWhereInput = {"id": session_id}
+        if user_id is not None:
+            where_clause["userId"] = user_id
+
+        result = await PrismaChatSession.prisma().delete_many(where=where_clause)
+        if result == 0:
+            logger.warning(
+                f"No session deleted for {session_id} "
+                f"(user_id validation: {user_id is not None})"
+            )
+            return False
+        return True
+    except Exception as e:
+        logger.error(f"Failed to delete chat session {session_id}: {e}")
+        return False
+
+
+async def get_next_sequence(session_id: str) -> int:
+    """Get the next sequence number for a new message in this session.
+
+    Uses MAX(sequence) + 1 for robustness. Returns 0 if no messages exist.
+    More robust than COUNT(*) because it's immune to deleted messages.
+
+    Optimized to select only the sequence column using raw SQL.
+    The unique index on (sessionId, sequence) makes this query fast.
+    """
+    results = await db.query_raw_with_schema(
+        'SELECT "sequence" FROM {schema_prefix}"ChatMessage" WHERE "sessionId" = $1 ORDER BY "sequence" DESC LIMIT 1',
+        session_id,
+    )
+    return 0 if not results else results[0]["sequence"] + 1
+
+
+async def update_tool_message_content(
+    session_id: str,
+    tool_call_id: str,
+    new_content: str,
+) -> bool:
+    """Update the content of a tool message in chat history.
+
+    Used by background tasks to update pending operation messages with final results.
+
+    Args:
+        session_id: The chat session ID.
+        tool_call_id: The tool call ID to find the message.
+        new_content: The new content to set.
+
+    Returns:
+        True if a message was updated, False otherwise.
+    """
+    try:
+        result = await PrismaChatMessage.prisma().update_many(
+            where={
+                "sessionId": session_id,
+                "toolCallId": tool_call_id,
+            },
+            data={
+                "content": sanitize_string(new_content),
+            },
+        )
+        if result == 0:
+            logger.warning(
+                f"No message found to update for session {session_id}, "
+                f"tool_call_id {tool_call_id}"
+            )
+            return False
+        return True
+    except Exception as e:
+        logger.error(
+            f"Failed to update tool message for session {session_id}, "
+            f"tool_call_id {tool_call_id}: {e}"
+        )
+        return False

autogpt_platform/backend/backend/copilot/executor/__main__.py

@@ -0,0 +1,18 @@
+"""Entry point for running the CoPilot Executor service.
+
+Usage:
+    python -m backend.copilot.executor
+"""
+
+from backend.app import run_processes
+
+from .manager import CoPilotExecutor
+
+
+def main():
+    """Run the CoPilot Executor service."""
+    run_processes(CoPilotExecutor())
+
+
+if __name__ == "__main__":
+    main()

autogpt_platform/backend/backend/copilot/executor/manager.py

@@ -0,0 +1,526 @@
+"""CoPilot Executor Manager - main service for CoPilot task execution.
+
+This module contains the CoPilotExecutor class that consumes chat tasks from
+RabbitMQ and processes them using a thread pool, following the graph executor pattern.
+"""
+
+import asyncio
+import logging
+import os
+import threading
+import time
+import uuid
+from concurrent.futures import Future, ThreadPoolExecutor
+
+from pika.adapters.blocking_connection import BlockingChannel
+from pika.exceptions import AMQPChannelError, AMQPConnectionError
+from pika.spec import Basic, BasicProperties
+from prometheus_client import Gauge, start_http_server
+
+from backend.data import redis_client as redis
+from backend.data.rabbitmq import SyncRabbitMQ
+from backend.executor.cluster_lock import ClusterLock
+from backend.util.decorator import error_logged
+from backend.util.logging import TruncatedLogger
+from backend.util.process import AppProcess
+from backend.util.retry import continuous_retry
+from backend.util.settings import Settings
+
+from .processor import execute_copilot_turn, init_worker
+from .utils import (
+    COPILOT_CANCEL_QUEUE_NAME,
+    COPILOT_EXECUTION_QUEUE_NAME,
+    GRACEFUL_SHUTDOWN_TIMEOUT_SECONDS,
+    CancelCoPilotEvent,
+    CoPilotExecutionEntry,
+    create_copilot_queue_config,
+)
+
+logger = TruncatedLogger(logging.getLogger(__name__), prefix="[CoPilotExecutor]")
+settings = Settings()
+
+# Prometheus metrics
+active_tasks_gauge = Gauge(
+    "copilot_executor_active_tasks",
+    "Number of active CoPilot tasks",
+)
+pool_size_gauge = Gauge(
+    "copilot_executor_pool_size",
+    "Maximum number of CoPilot executor workers",
+)
+utilization_gauge = Gauge(
+    "copilot_executor_utilization_ratio",
+    "Ratio of active tasks to pool size",
+)
+
+
+class CoPilotExecutor(AppProcess):
+    """CoPilot Executor service for processing chat generation tasks.
+
+    This service consumes tasks from RabbitMQ, processes them using a thread pool,
+    and publishes results to Redis Streams. It follows the graph executor pattern
+    for reliable message handling and graceful shutdown.
+
+    Key features:
+    - RabbitMQ-based task distribution with manual acknowledgment
+    - Thread pool executor for concurrent task processing
+    - Cluster lock for duplicate prevention across pods
+    - Graceful shutdown with timeout for in-flight tasks
+    - FANOUT exchange for cancellation broadcast
+    """
+
+    def __init__(self):
+        super().__init__()
+        self.pool_size = settings.config.num_copilot_workers
+        self.active_tasks: dict[str, tuple[Future, threading.Event]] = {}
+        self.executor_id = str(uuid.uuid4())
+
+        self._executor = None
+        self._stop_consuming = None
+
+        self._cancel_thread = None
+        self._cancel_client = None
+        self._run_thread = None
+        self._run_client = None
+
+        self._task_locks: dict[str, ClusterLock] = {}
+        self._active_tasks_lock = threading.Lock()
+
+    # ============ Main Entry Points (AppProcess interface) ============ #
+
+    def run(self):
+        """Main service loop - consume from RabbitMQ."""
+        logger.info(f"Pod assigned executor_id: {self.executor_id}")
+        logger.info(f"Spawn max-{self.pool_size} workers...")
+
+        pool_size_gauge.set(self.pool_size)
+        self._update_metrics()
+        start_http_server(settings.config.copilot_executor_port)
+
+        self.cancel_thread.start()
+        self.run_thread.start()
+
+        while True:
+            time.sleep(1e5)
+
+    def cleanup(self):
+        """Graceful shutdown with active execution waiting."""
+        pid = os.getpid()
+        logger.info(f"[cleanup {pid}] Starting graceful shutdown...")
+
+        # Signal the consumer thread to stop
+        try:
+            self.stop_consuming.set()
+            run_channel = self.run_client.get_channel()
+            run_channel.connection.add_callback_threadsafe(
+                lambda: run_channel.stop_consuming()
+            )
+            logger.info(f"[cleanup {pid}] Consumer has been signaled to stop")
+        except Exception as e:
+            logger.error(f"[cleanup {pid}] Error stopping consumer: {e}")
+
+        # Wait for active executions to complete
+        if self.active_tasks:
+            logger.info(
+                f"[cleanup {pid}] Waiting for {len(self.active_tasks)} active tasks to complete (timeout: {GRACEFUL_SHUTDOWN_TIMEOUT_SECONDS}s)..."
+            )
+
+            start_time = time.monotonic()
+            last_refresh = start_time
+            lock_refresh_interval = settings.config.cluster_lock_timeout / 10
+
+            while (
+                self.active_tasks
+                and (time.monotonic() - start_time) < GRACEFUL_SHUTDOWN_TIMEOUT_SECONDS
+            ):
+                self._cleanup_completed_tasks()
+                if not self.active_tasks:
+                    break
+
+                # Refresh cluster locks periodically
+                current_time = time.monotonic()
+                if current_time - last_refresh >= lock_refresh_interval:
+                    for lock in list(self._task_locks.values()):
+                        try:
+                            lock.refresh()
+                        except Exception as e:
+                            logger.warning(
+                                f"[cleanup {pid}] Failed to refresh lock: {e}"
+                            )
+                    last_refresh = current_time
+
+                logger.info(
+                    f"[cleanup {pid}] {len(self.active_tasks)} tasks still active, waiting..."
+                )
+                time.sleep(10.0)
+
+        # Stop message consumers
+        if self._run_thread:
+            self._stop_message_consumers(
+                self._run_thread, self.run_client, "[cleanup][run]"
+            )
+        if self._cancel_thread:
+            self._stop_message_consumers(
+                self._cancel_thread, self.cancel_client, "[cleanup][cancel]"
+            )
+
+        # Clean up worker threads (closes per-loop workspace storage sessions)
+        if self._executor:
+            from .processor import cleanup_worker
+
+            logger.info(f"[cleanup {pid}] Cleaning up workers...")
+            futures = []
+            for _ in range(self._executor._max_workers):
+                futures.append(self._executor.submit(cleanup_worker))
+            for f in futures:
+                try:
+                    f.result(timeout=10)
+                except Exception as e:
+                    logger.warning(f"[cleanup {pid}] Worker cleanup error: {e}")
+
+            logger.info(f"[cleanup {pid}] Shutting down executor...")
+            self._executor.shutdown(wait=False)
+
+        # Release any remaining locks
+        for session_id, lock in list(self._task_locks.items()):
+            try:
+                lock.release()
+                logger.info(f"[cleanup {pid}] Released lock for {session_id}")
+            except Exception as e:
+                logger.error(
+                    f"[cleanup {pid}] Failed to release lock for {session_id}: {e}"
+                )
+
+        logger.info(f"[cleanup {pid}] Graceful shutdown completed")
+
+    # ============ RabbitMQ Consumer Methods ============ #
+
+    @continuous_retry()
+    def _consume_cancel(self):
+        """Consume cancellation messages from FANOUT exchange."""
+        if self.stop_consuming.is_set() and not self.active_tasks:
+            logger.info("Stop reconnecting cancel consumer - service cleaned up")
+            return
+
+        if not self.cancel_client.is_ready:
+            self.cancel_client.disconnect()
+        self.cancel_client.connect()
+
+        # Check again after connect - shutdown may have been requested
+        if self.stop_consuming.is_set() and not self.active_tasks:
+            logger.info("Stop consuming requested during reconnect - disconnecting")
+            self.cancel_client.disconnect()
+            return
+
+        cancel_channel = self.cancel_client.get_channel()
+        cancel_channel.basic_consume(
+            queue=COPILOT_CANCEL_QUEUE_NAME,
+            on_message_callback=self._handle_cancel_message,
+            auto_ack=True,
+        )
+        logger.info("Starting to consume cancel messages...")
+        cancel_channel.start_consuming()
+        if not self.stop_consuming.is_set() or self.active_tasks:
+            raise RuntimeError("Cancel message consumer stopped unexpectedly")
+        logger.info("Cancel message consumer stopped gracefully")
+
+    @continuous_retry()
+    def _consume_run(self):
+        """Consume run messages from DIRECT exchange."""
+        if self.stop_consuming.is_set():
+            logger.info("Stop reconnecting run consumer - service cleaned up")
+            return
+
+        if not self.run_client.is_ready:
+            self.run_client.disconnect()
+        self.run_client.connect()
+
+        # Check again after connect - shutdown may have been requested
+        if self.stop_consuming.is_set():
+            logger.info("Stop consuming requested during reconnect - disconnecting")
+            self.run_client.disconnect()
+            return
+
+        run_channel = self.run_client.get_channel()
+        run_channel.basic_qos(prefetch_count=self.pool_size)
+
+        run_channel.basic_consume(
+            queue=COPILOT_EXECUTION_QUEUE_NAME,
+            on_message_callback=self._handle_run_message,
+            auto_ack=False,
+            consumer_tag="copilot_execution_consumer",
+        )
+        logger.info("Starting to consume run messages...")
+        run_channel.start_consuming()
+        if not self.stop_consuming.is_set():
+            raise RuntimeError("Run message consumer stopped unexpectedly")
+        logger.info("Run message consumer stopped gracefully")
+
+    # ============ Message Handlers ============ #
+
+    @error_logged(swallow=True)
+    def _handle_cancel_message(
+        self,
+        _channel: BlockingChannel,
+        _method: Basic.Deliver,
+        _properties: BasicProperties,
+        body: bytes,
+    ):
+        """Handle cancel message from FANOUT exchange."""
+        request = CancelCoPilotEvent.model_validate_json(body)
+        session_id = request.session_id
+        if not session_id:
+            logger.warning("Cancel message missing 'session_id'")
+            return
+        if session_id not in self.active_tasks:
+            logger.debug(f"Cancel received for {session_id} but not active")
+            return
+
+        _, cancel_event = self.active_tasks[session_id]
+        logger.info(f"Received cancel for {session_id}")
+        if not cancel_event.is_set():
+            cancel_event.set()
+        else:
+            logger.debug(f"Cancel already set for {session_id}")
+
+    def _handle_run_message(
+        self,
+        _channel: BlockingChannel,
+        method: Basic.Deliver,
+        _properties: BasicProperties,
+        body: bytes,
+    ):
+        """Handle run message from DIRECT exchange."""
+        delivery_tag = method.delivery_tag
+        # Capture the channel used at message delivery time to ensure we ack
+        # on the correct channel. Delivery tags are channel-scoped and become
+        # invalid if the channel is recreated after reconnection.
+        delivery_channel = _channel
+
+        def ack_message(reject: bool, requeue: bool):
+            """Acknowledge or reject the message.
+
+            Uses the channel from the original message delivery. If the channel
+            is no longer open (e.g., after reconnection), logs a warning and
+            skips the ack - RabbitMQ will redeliver the message automatically.
+            """
+            try:
+                if not delivery_channel.is_open:
+                    logger.warning(
+                        f"Channel closed, cannot ack delivery_tag={delivery_tag}. "
+                        "Message will be redelivered by RabbitMQ."
+                    )
+                    return
+
+                if reject:
+                    delivery_channel.connection.add_callback_threadsafe(
+                        lambda: delivery_channel.basic_nack(
+                            delivery_tag, requeue=requeue
+                        )
+                    )
+                else:
+                    delivery_channel.connection.add_callback_threadsafe(
+                        lambda: delivery_channel.basic_ack(delivery_tag)
+                    )
+            except (AMQPChannelError, AMQPConnectionError) as e:
+                # Channel/connection errors indicate stale delivery tag - don't retry
+                logger.warning(
+                    f"Cannot ack delivery_tag={delivery_tag} due to channel/connection "
+                    f"error: {e}. Message will be redelivered by RabbitMQ."
+                )
+            except Exception as e:
+                # Other errors might be transient, but log and skip to avoid blocking
+                logger.error(
+                    f"Unexpected error acking delivery_tag={delivery_tag}: {e}"
+                )
+
+        # Check if we're shutting down
+        if self.stop_consuming.is_set():
+            logger.info("Rejecting new task during shutdown")
+            ack_message(reject=True, requeue=True)
+            return
+
+        # Check if we can accept more tasks
+        self._cleanup_completed_tasks()
+        if len(self.active_tasks) >= self.pool_size:
+            ack_message(reject=True, requeue=True)
+            return
+
+        try:
+            entry = CoPilotExecutionEntry.model_validate_json(body)
+        except Exception as e:
+            logger.error(f"Could not parse run message: {e}, body={body}")
+            ack_message(reject=True, requeue=False)
+            return
+
+        session_id = entry.session_id
+
+        # Check for local duplicate - session is already running on this executor
+        if session_id in self.active_tasks:
+            logger.warning(
+                f"Session {session_id} already running locally, rejecting duplicate"
+            )
+            ack_message(reject=True, requeue=False)
+            return
+
+        # Try to acquire cluster-wide lock
+        cluster_lock = ClusterLock(
+            redis=redis.get_redis(),
+            key=f"copilot:session:{session_id}:lock",
+            owner_id=self.executor_id,
+            timeout=settings.config.cluster_lock_timeout,
+        )
+        current_owner = cluster_lock.try_acquire()
+        if current_owner != self.executor_id:
+            if current_owner is not None:
+                logger.warning(
+                    f"Session {session_id} already running on pod {current_owner}"
+                )
+                ack_message(reject=True, requeue=False)
+            else:
+                logger.warning(
+                    f"Could not acquire lock for {session_id} - Redis unavailable"
+                )
+                ack_message(reject=True, requeue=True)
+            return
+
+        # Execute the task
+        try:
+            self._task_locks[session_id] = cluster_lock
+
+            logger.info(
+                f"Acquired cluster lock for {session_id}, "
+                f"executor_id={self.executor_id}"
+            )
+
+            cancel_event = threading.Event()
+            future = self.executor.submit(
+                execute_copilot_turn, entry, cancel_event, cluster_lock
+            )
+            self.active_tasks[session_id] = (future, cancel_event)
+        except Exception as e:
+            logger.warning(f"Failed to setup execution for {session_id}: {e}")
+            cluster_lock.release()
+            if session_id in self._task_locks:
+                del self._task_locks[session_id]
+            ack_message(reject=True, requeue=True)
+            return
+
+        self._update_metrics()
+
+        def on_run_done(f: Future):
+            logger.info(f"Run completed for {session_id}")
+            error_msg = None
+            try:
+                if exec_error := f.exception():
+                    error_msg = str(exec_error) or type(exec_error).__name__
+                    logger.error(f"Execution for {session_id} failed: {error_msg}")
+                    ack_message(reject=True, requeue=False)
+                else:
+                    ack_message(reject=False, requeue=False)
+            except asyncio.CancelledError:
+                logger.info(f"Run completion callback cancelled for {session_id}")
+            except BaseException as e:
+                error_msg = str(e) or type(e).__name__
+                logger.exception(f"Error in run completion callback: {error_msg}")
+            finally:
+                # Release the cluster lock
+                if session_id in self._task_locks:
+                    logger.info(f"Releasing cluster lock for {session_id}")
+                    self._task_locks[session_id].release()
+                    del self._task_locks[session_id]
+                self._cleanup_completed_tasks()
+
+        future.add_done_callback(on_run_done)
+
+    # ============ Helper Methods ============ #
+
+    def _cleanup_completed_tasks(self) -> list[str]:
+        """Remove completed futures from active_tasks and update metrics."""
+        completed_tasks = []
+        with self._active_tasks_lock:
+            for session_id, (future, _) in list(self.active_tasks.items()):
+                if future.done():
+                    completed_tasks.append(session_id)
+                    self.active_tasks.pop(session_id, None)
+                    logger.info(f"Cleaned up completed session {session_id}")
+
+        self._update_metrics()
+        return completed_tasks
+
+    def _update_metrics(self):
+        """Update Prometheus metrics."""
+        active_count = len(self.active_tasks)
+        active_tasks_gauge.set(active_count)
+        if self.stop_consuming.is_set():
+            utilization_gauge.set(1.0)
+        else:
+            utilization_gauge.set(
+                active_count / self.pool_size if self.pool_size > 0 else 0
+            )
+
+    def _stop_message_consumers(
+        self, thread: threading.Thread, client: SyncRabbitMQ, prefix: str
+    ):
+        """Stop a message consumer thread."""
+        try:
+            channel = client.get_channel()
+            channel.connection.add_callback_threadsafe(lambda: channel.stop_consuming())
+
+            thread.join(timeout=300)
+            if thread.is_alive():
+                logger.error(
+                    f"{prefix} Thread did not finish in time, forcing disconnect"
+                )
+
+            client.disconnect()
+            logger.info(f"{prefix} Client disconnected")
+        except Exception as e:
+            logger.error(f"{prefix} Error disconnecting client: {e}")
+
+    # ============ Lazy-initialized Properties ============ #
+
+    @property
+    def cancel_thread(self) -> threading.Thread:
+        if self._cancel_thread is None:
+            self._cancel_thread = threading.Thread(
+                target=lambda: self._consume_cancel(),
+                daemon=True,
+            )
+        return self._cancel_thread
+
+    @property
+    def run_thread(self) -> threading.Thread:
+        if self._run_thread is None:
+            self._run_thread = threading.Thread(
+                target=lambda: self._consume_run(),
+                daemon=True,
+            )
+        return self._run_thread
+
+    @property
+    def stop_consuming(self) -> threading.Event:
+        if self._stop_consuming is None:
+            self._stop_consuming = threading.Event()
+        return self._stop_consuming
+
+    @property
+    def executor(self) -> ThreadPoolExecutor:
+        if self._executor is None:
+            self._executor = ThreadPoolExecutor(
+                max_workers=self.pool_size,
+                initializer=init_worker,
+            )
+        return self._executor
+
+    @property
+    def cancel_client(self) -> SyncRabbitMQ:
+        if self._cancel_client is None:
+            self._cancel_client = SyncRabbitMQ(create_copilot_queue_config())
+        return self._cancel_client
+
+    @property
+    def run_client(self) -> SyncRabbitMQ:
+        if self._run_client is None:
+            self._run_client = SyncRabbitMQ(create_copilot_queue_config())
+        return self._run_client

autogpt_platform/backend/backend/copilot/executor/processor.py

@@ -0,0 +1,313 @@
+"""CoPilot execution processor - per-worker execution logic.
+
+This module contains the processor class that handles CoPilot session execution
+in a thread-local context, following the graph executor pattern.
+"""
+
+import asyncio
+import logging
+import os
+import subprocess
+import threading
+import time
+
+from backend.copilot import stream_registry
+from backend.copilot.baseline import stream_chat_completion_baseline
+from backend.copilot.config import ChatConfig
+from backend.copilot.response_model import StreamFinish
+from backend.copilot.sdk import service as sdk_service
+from backend.executor.cluster_lock import ClusterLock
+from backend.util.decorator import error_logged
+from backend.util.feature_flag import Flag, is_feature_enabled
+from backend.util.logging import TruncatedLogger, configure_logging
+from backend.util.process import set_service_name
+from backend.util.retry import func_retry
+
+from .utils import CoPilotExecutionEntry, CoPilotLogMetadata
+
+logger = TruncatedLogger(logging.getLogger(__name__), prefix="[CoPilotExecutor]")
+
+
+# ============ Module Entry Points ============ #
+
+# Thread-local storage for processor instances
+_tls = threading.local()
+
+
+def execute_copilot_turn(
+    entry: CoPilotExecutionEntry,
+    cancel: threading.Event,
+    cluster_lock: ClusterLock,
+):
+    """Execute a single CoPilot turn (user message → AI response).
+
+    This function is the entry point called by the thread pool executor.
+
+    Args:
+        entry: The turn payload
+        cancel: Threading event to signal cancellation
+        cluster_lock: Distributed lock for this execution
+    """
+    processor: CoPilotProcessor = _tls.processor
+    return processor.execute(entry, cancel, cluster_lock)
+
+
+def init_worker():
+    """Initialize the processor for the current worker thread.
+
+    This function is called by the thread pool executor when a new worker
+    thread is created. It ensures each worker has its own processor instance.
+    """
+    _tls.processor = CoPilotProcessor()
+    _tls.processor.on_executor_start()
+
+
+def cleanup_worker():
+    """Clean up the processor for the current worker thread.
+
+    Should be called before the worker thread's event loop is destroyed so
+    that event-loop-bound resources (e.g. ``aiohttp.ClientSession``) are
+    closed on the correct loop.
+    """
+    processor: CoPilotProcessor | None = getattr(_tls, "processor", None)
+    if processor is not None:
+        processor.cleanup()
+
+
+# ============ Processor Class ============ #
+
+
+class CoPilotProcessor:
+    """Per-worker execution logic for CoPilot sessions.
+
+    This class is instantiated once per worker thread and handles the execution
+    of CoPilot chat generation sessions. It maintains an async event loop for
+    running the async service code.
+
+    The execution flow:
+        1. Session entry is picked from RabbitMQ queue
+        2. Manager submits to thread pool
+        3. Processor executes in its event loop
+        4. Results are published to Redis Streams
+    """
+
+    @func_retry
+    def on_executor_start(self):
+        """Initialize the processor when the worker thread starts.
+
+        This method is called once per worker thread to set up the async event
+        loop and initialize any required resources.
+
+        Database is accessed only through DatabaseManager, so we don't need to connect
+        to Prisma directly.
+        """
+        configure_logging()
+        set_service_name("CoPilotExecutor")
+        self.tid = threading.get_ident()
+        self.execution_loop = asyncio.new_event_loop()
+        self.execution_thread = threading.Thread(
+            target=self.execution_loop.run_forever, daemon=True
+        )
+        self.execution_thread.start()
+
+        # Skip the SDK's per-request CLI version check — the bundled CLI is
+        # already version-matched to the SDK package.
+        os.environ.setdefault("CLAUDE_AGENT_SDK_SKIP_VERSION_CHECK", "1")
+
+        # Pre-warm the bundled CLI binary so the OS page-caches the ~185 MB
+        # executable.  First spawn pays ~1.2 s; subsequent spawns ~0.65 s.
+        self._prewarm_cli()
+
+        logger.info(f"[CoPilotExecutor] Worker {self.tid} started")
+
+    def _prewarm_cli(self) -> None:
+        """Run the bundled CLI binary once to warm OS page caches."""
+        try:
+            from claude_agent_sdk._internal.transport.subprocess_cli import (
+                SubprocessCLITransport,
+            )
+
+            cli_path = SubprocessCLITransport._find_bundled_cli(None)  # type: ignore[arg-type]
+            if cli_path:
+                result = subprocess.run(
+                    [cli_path, "-v"],
+                    capture_output=True,
+                    timeout=10,
+                )
+                if result.returncode == 0:
+                    logger.info(f"[CoPilotExecutor] CLI pre-warm done: {cli_path}")
+                else:
+                    logger.warning(
+                        "[CoPilotExecutor] CLI pre-warm failed (rc=%d): %s",
+                        result.returncode,  # type: ignore[reportCallIssue]
+                        cli_path,
+                    )
+        except Exception as e:
+            logger.debug(f"[CoPilotExecutor] CLI pre-warm skipped: {e}")
+
+    def cleanup(self):
+        """Clean up event-loop-bound resources before the loop is destroyed.
+
+        Shuts down the workspace storage instance that belongs to this
+        worker's event loop, ensuring ``aiohttp.ClientSession.close()``
+        runs on the same loop that created the session.
+        """
+        from backend.util.workspace_storage import shutdown_workspace_storage
+
+        coro = shutdown_workspace_storage()
+        try:
+            future = asyncio.run_coroutine_threadsafe(coro, self.execution_loop)
+            future.result(timeout=5)
+        except Exception as e:
+            coro.close()  # Prevent "coroutine was never awaited" warning
+            error_msg = str(e) or type(e).__name__
+            logger.warning(
+                f"[CoPilotExecutor] Worker {self.tid} cleanup error: {error_msg}"
+            )
+
+        # Stop the event loop
+        self.execution_loop.call_soon_threadsafe(self.execution_loop.stop)
+        self.execution_thread.join(timeout=5)
+        logger.info(f"[CoPilotExecutor] Worker {self.tid} cleaned up")
+
+    @error_logged(swallow=False)
+    def execute(
+        self,
+        entry: CoPilotExecutionEntry,
+        cancel: threading.Event,
+        cluster_lock: ClusterLock,
+    ):
+        """Execute a CoPilot turn.
+
+        Runs the async logic in the worker's event loop and handles errors.
+
+        Args:
+            entry: The turn payload containing session and message info
+            cancel: Threading event to signal cancellation
+            cluster_lock: Distributed lock to prevent duplicate execution
+        """
+        log = CoPilotLogMetadata(
+            logging.getLogger(__name__),
+            session_id=entry.session_id,
+            user_id=entry.user_id,
+        )
+        log.info("Starting execution")
+
+        start_time = time.monotonic()
+
+        # Run the async execution in our event loop
+        future = asyncio.run_coroutine_threadsafe(
+            self._execute_async(entry, cancel, cluster_lock, log),
+            self.execution_loop,
+        )
+
+        # Wait for completion, checking cancel periodically
+        while not future.done():
+            try:
+                future.result(timeout=1.0)
+            except asyncio.TimeoutError:
+                if cancel.is_set():
+                    log.info("Cancellation requested")
+                    future.cancel()
+                    break
+                # Refresh cluster lock to maintain ownership
+                cluster_lock.refresh()
+
+        if not future.cancelled():
+            # Get result to propagate any exceptions
+            future.result()
+
+        elapsed = time.monotonic() - start_time
+        log.info(f"Execution completed in {elapsed:.2f}s")
+
+    async def _execute_async(
+        self,
+        entry: CoPilotExecutionEntry,
+        cancel: threading.Event,
+        cluster_lock: ClusterLock,
+        log: CoPilotLogMetadata,
+    ):
+        """Async execution logic for a CoPilot turn.
+
+        Calls the chat completion service (SDK or baseline) and publishes
+        results to the stream registry.
+
+        Args:
+            entry: The turn payload
+            cancel: Threading event to signal cancellation
+            cluster_lock: Distributed lock for refresh
+            log: Structured logger
+        """
+        last_refresh = time.monotonic()
+        refresh_interval = 30.0  # Refresh lock every 30 seconds
+        error_msg = None
+
+        try:
+            # Choose service based on LaunchDarkly flag.
+            # Claude Code subscription forces SDK mode (CLI subprocess auth).
+            config = ChatConfig()
+            use_sdk = config.use_claude_code_subscription or await is_feature_enabled(
+                Flag.COPILOT_SDK,
+                entry.user_id or "anonymous",
+                default=config.use_claude_agent_sdk,
+            )
+            stream_fn = (
+                sdk_service.stream_chat_completion_sdk
+                if use_sdk
+                else stream_chat_completion_baseline
+            )
+            log.info(f"Using {'SDK' if use_sdk else 'baseline'} service")
+
+            # Stream chat completion and publish chunks to Redis.
+            async for chunk in stream_fn(
+                session_id=entry.session_id,
+                message=entry.message if entry.message else None,
+                is_user_message=entry.is_user_message,
+                user_id=entry.user_id,
+                context=entry.context,
+                file_ids=entry.file_ids,
+            ):
+                if cancel.is_set():
+                    log.info("Cancel requested, breaking stream")
+                    break
+
+                current_time = time.monotonic()
+                if current_time - last_refresh >= refresh_interval:
+                    cluster_lock.refresh()
+                    last_refresh = current_time
+
+                # Skip StreamFinish — mark_session_completed publishes it.
+                if isinstance(chunk, StreamFinish):
+                    continue
+
+                try:
+                    await stream_registry.publish_chunk(entry.turn_id, chunk)
+                except Exception as e:
+                    log.error(
+                        f"Error publishing chunk {type(chunk).__name__}: {e}",
+                        exc_info=True,
+                    )
+
+            # Stream loop completed
+            if cancel.is_set():
+                log.info("Stream cancelled by user")
+
+        except BaseException as e:
+            # Handle all exceptions (including CancelledError) with appropriate logging
+            if isinstance(e, asyncio.CancelledError):
+                log.info("Turn cancelled")
+                error_msg = "Operation cancelled"
+            else:
+                error_msg = str(e) or type(e).__name__
+                log.error(f"Turn failed: {error_msg}")
+            raise
+        finally:
+            # If no exception but user cancelled, still mark as cancelled
+            if not error_msg and cancel.is_set():
+                error_msg = "Operation cancelled"
+            try:
+                await stream_registry.mark_session_completed(
+                    entry.session_id, error_message=error_msg
+                )
+            except Exception as mark_err:
+                log.error(f"Failed to mark session completed: {mark_err}")

autogpt_platform/backend/backend/copilot/executor/utils.py

@@ -0,0 +1,224 @@
+"""RabbitMQ queue configuration for CoPilot executor.
+
+Defines two exchanges and queues following the graph executor pattern:
+- 'copilot_execution' (DIRECT) for chat generation tasks
+- 'copilot_cancel' (FANOUT) for cancellation requests
+"""
+
+import logging
+
+from pydantic import BaseModel
+
+from backend.data.rabbitmq import Exchange, ExchangeType, Queue, RabbitMQConfig
+from backend.util.logging import TruncatedLogger, is_structured_logging_enabled
+
+logger = logging.getLogger(__name__)
+
+
+# ============ Logging Helper ============ #
+
+
+class CoPilotLogMetadata(TruncatedLogger):
+    """Structured logging helper for CoPilot executor.
+
+    In cloud environments (structured logging enabled), uses a simple prefix
+    and passes metadata via json_fields. In local environments, uses a detailed
+    prefix with all metadata key-value pairs for easier debugging.
+
+    Args:
+        logger: The underlying logger instance
+        max_length: Maximum log message length before truncation
+        **kwargs: Metadata key-value pairs (e.g., session_id="xyz", turn_id="abc")
+            These are added to json_fields in cloud mode, or to the prefix in local mode.
+    """
+
+    def __init__(
+        self,
+        logger: logging.Logger,
+        max_length: int = 1000,
+        **kwargs: str | None,
+    ):
+        # Filter out None values
+        metadata = {k: v for k, v in kwargs.items() if v is not None}
+        metadata["component"] = "CoPilotExecutor"
+
+        if is_structured_logging_enabled():
+            prefix = "[CoPilotExecutor]"
+        else:
+            # Build prefix from metadata key-value pairs
+            meta_parts = "|".join(
+                f"{k}:{v}" for k, v in metadata.items() if k != "component"
+            )
+            prefix = (
+                f"[CoPilotExecutor|{meta_parts}]" if meta_parts else "[CoPilotExecutor]"
+            )
+
+        super().__init__(
+            logger,
+            max_length=max_length,
+            prefix=prefix,
+            metadata=metadata,
+        )
+
+
+# ============ Exchange and Queue Configuration ============ #
+
+COPILOT_EXECUTION_EXCHANGE = Exchange(
+    name="copilot_execution",
+    type=ExchangeType.DIRECT,
+    durable=True,
+    auto_delete=False,
+)
+COPILOT_EXECUTION_QUEUE_NAME = "copilot_execution_queue"
+COPILOT_EXECUTION_ROUTING_KEY = "copilot.run"
+
+COPILOT_CANCEL_EXCHANGE = Exchange(
+    name="copilot_cancel",
+    type=ExchangeType.FANOUT,
+    durable=True,
+    auto_delete=False,
+)
+COPILOT_CANCEL_QUEUE_NAME = "copilot_cancel_queue"
+
+# CoPilot operations can include extended thinking and agent generation
+# which may take 30+ minutes to complete
+COPILOT_CONSUMER_TIMEOUT_SECONDS = 60 * 60  # 1 hour
+
+# Graceful shutdown timeout - allow in-flight operations to complete
+GRACEFUL_SHUTDOWN_TIMEOUT_SECONDS = 30 * 60  # 30 minutes
+
+
+def create_copilot_queue_config() -> RabbitMQConfig:
+    """Create RabbitMQ configuration for CoPilot executor.
+
+    Defines two exchanges and queues:
+    - 'copilot_execution' (DIRECT) for chat generation tasks
+    - 'copilot_cancel' (FANOUT) for cancellation requests
+
+    Returns:
+        RabbitMQConfig with exchanges and queues defined
+    """
+    run_queue = Queue(
+        name=COPILOT_EXECUTION_QUEUE_NAME,
+        exchange=COPILOT_EXECUTION_EXCHANGE,
+        routing_key=COPILOT_EXECUTION_ROUTING_KEY,
+        durable=True,
+        auto_delete=False,
+        arguments={
+            # Extended consumer timeout for long-running LLM operations
+            # Default 30-minute timeout is insufficient for extended thinking
+            # and agent generation which can take 30+ minutes
+            "x-consumer-timeout": COPILOT_CONSUMER_TIMEOUT_SECONDS
+            * 1000,
+        },
+    )
+    cancel_queue = Queue(
+        name=COPILOT_CANCEL_QUEUE_NAME,
+        exchange=COPILOT_CANCEL_EXCHANGE,
+        routing_key="",  # not used for FANOUT
+        durable=True,
+        auto_delete=False,
+    )
+    return RabbitMQConfig(
+        vhost="/",
+        exchanges=[COPILOT_EXECUTION_EXCHANGE, COPILOT_CANCEL_EXCHANGE],
+        queues=[run_queue, cancel_queue],
+    )
+
+
+# ============ Message Models ============ #
+
+
+class CoPilotExecutionEntry(BaseModel):
+    """Task payload for CoPilot AI generation.
+
+    This model represents a chat generation task to be processed by the executor.
+    """
+
+    session_id: str
+    """Chat session ID (also used for dedup/locking)"""
+
+    turn_id: str = ""
+    """Per-turn UUID for Redis stream isolation"""
+
+    user_id: str | None
+    """User ID (may be None for anonymous users)"""
+
+    message: str
+    """User's message to process"""
+
+    is_user_message: bool = True
+    """Whether the message is from the user (vs system/assistant)"""
+
+    context: dict[str, str] | None = None
+    """Optional context for the message (e.g., {url: str, content: str})"""
+
+    file_ids: list[str] | None = None
+    """Workspace file IDs attached to the user's message"""
+
+
+class CancelCoPilotEvent(BaseModel):
+    """Event to cancel a CoPilot operation."""
+
+    session_id: str
+    """Session ID to cancel"""
+
+
+# ============ Queue Publishing Helpers ============ #
+
+
+async def enqueue_copilot_turn(
+    session_id: str,
+    user_id: str | None,
+    message: str,
+    turn_id: str,
+    is_user_message: bool = True,
+    context: dict[str, str] | None = None,
+    file_ids: list[str] | None = None,
+) -> None:
+    """Enqueue a CoPilot task for processing by the executor service.
+
+    Args:
+        session_id: Chat session ID (also used for dedup/locking)
+        user_id: User ID (may be None for anonymous users)
+        message: User's message to process
+        turn_id: Per-turn UUID for Redis stream isolation
+        is_user_message: Whether the message is from the user (vs system/assistant)
+        context: Optional context for the message (e.g., {url: str, content: str})
+        file_ids: Optional workspace file IDs attached to the user's message
+    """
+    from backend.util.clients import get_async_copilot_queue
+
+    entry = CoPilotExecutionEntry(
+        session_id=session_id,
+        turn_id=turn_id,
+        user_id=user_id,
+        message=message,
+        is_user_message=is_user_message,
+        context=context,
+        file_ids=file_ids,
+    )
+
+    queue_client = await get_async_copilot_queue()
+    await queue_client.publish_message(
+        routing_key=COPILOT_EXECUTION_ROUTING_KEY,
+        message=entry.model_dump_json(),
+        exchange=COPILOT_EXECUTION_EXCHANGE,
+    )
+
+
+async def enqueue_cancel_task(session_id: str) -> None:
+    """Publish a cancel request for a running CoPilot session.
+
+    Sends a ``CancelCoPilotEvent`` to the FANOUT exchange so all executor
+    pods receive the cancellation signal.
+    """
+    from backend.util.clients import get_async_copilot_queue
+
+    event = CancelCoPilotEvent(session_id=session_id)
+    queue_client = await get_async_copilot_queue()
+    await queue_client.publish_message(
+        routing_key="",  # FANOUT ignores routing key
+        message=event.model_dump_json(),
+        exchange=COPILOT_CANCEL_EXCHANGE,
+    )

autogpt_platform/backend/backend/copilot/model.py

@@ -2,7 +2,7 @@ import asyncio
 import logging
 import uuid
 from datetime import UTC, datetime
-from typing import Any, cast
+from typing import Any, Self, cast
 from weakref import WeakValueDictionary
 
 from openai.types.chat import (
@@ -23,26 +23,17 @@ from prisma.models import ChatMessage as PrismaChatMessage
 from prisma.models import ChatSession as PrismaChatSession
 from pydantic import BaseModel
 
+from backend.data.db_accessors import chat_db
 from backend.data.redis_client import get_redis_async
 from backend.util import json
 from backend.util.exceptions import DatabaseError, RedisError
 
-from . import db as chat_db
 from .config import ChatConfig
 
 logger = logging.getLogger(__name__)
 config = ChatConfig()
 
 
-def _parse_json_field(value: str | dict | list | None, default: Any = None) -> Any:
-    """Parse a JSON field that may be stored as string or already parsed."""
-    if value is None:
-        return default
-    if isinstance(value, str):
-        return json.loads(value)
-    return value
-
-
 # Redis cache key prefix for chat sessions
 CHAT_SESSION_CACHE_PREFIX = "chat:session:"
 
@@ -52,28 +43,7 @@ def _get_session_cache_key(session_id: str) -> str:
     return f"{CHAT_SESSION_CACHE_PREFIX}{session_id}"
 
 
-# Session-level locks to prevent race conditions during concurrent upserts.
-# Uses WeakValueDictionary to automatically garbage collect locks when no longer referenced,
-# preventing unbounded memory growth while maintaining lock semantics for active sessions.
-# Invalidation: Locks are auto-removed by GC when no coroutine holds a reference (after
-# async with lock: completes). Explicit cleanup also occurs in delete_chat_session().
-_session_locks: WeakValueDictionary[str, asyncio.Lock] = WeakValueDictionary()
-_session_locks_mutex = asyncio.Lock()
-
-
-async def _get_session_lock(session_id: str) -> asyncio.Lock:
-    """Get or create a lock for a specific session to prevent concurrent upserts.
-
-    Uses WeakValueDictionary for automatic cleanup: locks are garbage collected
-    when no coroutine holds a reference to them, preventing memory leaks from
-    unbounded growth of session locks.
-    """
-    async with _session_locks_mutex:
-        lock = _session_locks.get(session_id)
-        if lock is None:
-            lock = asyncio.Lock()
-            _session_locks[session_id] = lock
-        return lock
+# ===================== Chat data models ===================== #
 
 
 class ChatMessage(BaseModel):
@@ -85,6 +55,19 @@ class ChatMessage(BaseModel):
     tool_calls: list[dict] | None = None
     function_call: dict | None = None
 
+    @staticmethod
+    def from_db(prisma_message: PrismaChatMessage) -> "ChatMessage":
+        """Convert a Prisma ChatMessage to a Pydantic ChatMessage."""
+        return ChatMessage(
+            role=prisma_message.role,
+            content=prisma_message.content,
+            name=prisma_message.name,
+            tool_call_id=prisma_message.toolCallId,
+            refusal=prisma_message.refusal,
+            tool_calls=_parse_json_field(prisma_message.toolCalls),
+            function_call=_parse_json_field(prisma_message.functionCall),
+        )
+
 
 class Usage(BaseModel):
     prompt_tokens: int
@@ -92,11 +75,10 @@ class Usage(BaseModel):
     total_tokens: int
 
 
-class ChatSession(BaseModel):
+class ChatSessionInfo(BaseModel):
     session_id: str
     user_id: str
     title: str | None = None
-    messages: list[ChatMessage]
     usage: list[Usage]
     credentials: dict[str, dict] = {}  # Map of provider -> credential metadata
     started_at: datetime
@@ -104,60 +86,9 @@ class ChatSession(BaseModel):
     successful_agent_runs: dict[str, int] = {}
     successful_agent_schedules: dict[str, int] = {}
 
-    def add_tool_call_to_current_turn(self, tool_call: dict) -> None:
-        """Attach a tool_call to the current turn's assistant message.
-
-        Searches backwards for the most recent assistant message (stopping at
-        any user message boundary). If found, appends the tool_call to it.
-        Otherwise creates a new assistant message with the tool_call.
-        """
-        for msg in reversed(self.messages):
-            if msg.role == "user":
-                break
-            if msg.role == "assistant":
-                if not msg.tool_calls:
-                    msg.tool_calls = []
-                msg.tool_calls.append(tool_call)
-                return
-
-        self.messages.append(
-            ChatMessage(role="assistant", content="", tool_calls=[tool_call])
-        )
-
-    @staticmethod
-    def new(user_id: str) -> "ChatSession":
-        return ChatSession(
-            session_id=str(uuid.uuid4()),
-            user_id=user_id,
-            title=None,
-            messages=[],
-            usage=[],
-            credentials={},
-            started_at=datetime.now(UTC),
-            updated_at=datetime.now(UTC),
-        )
-
-    @staticmethod
-    def from_db(
-        prisma_session: PrismaChatSession,
-        prisma_messages: list[PrismaChatMessage] | None = None,
-    ) -> "ChatSession":
-        """Convert Prisma models to Pydantic ChatSession."""
-        messages = []
-        if prisma_messages:
-            for msg in prisma_messages:
-                messages.append(
-                    ChatMessage(
-                        role=msg.role,
-                        content=msg.content,
-                        name=msg.name,
-                        tool_call_id=msg.toolCallId,
-                        refusal=msg.refusal,
-                        tool_calls=_parse_json_field(msg.toolCalls),
-                        function_call=_parse_json_field(msg.functionCall),
-                    )
-                )
-
+    @classmethod
+    def from_db(cls, prisma_session: PrismaChatSession) -> Self:
+        """Convert Prisma ChatSession to Pydantic ChatSession."""
         # Parse JSON fields from Prisma
         credentials = _parse_json_field(prisma_session.credentials, default={})
         successful_agent_runs = _parse_json_field(
@@ -179,11 +110,10 @@ class ChatSession(BaseModel):
                 )
             )
 
-        return ChatSession(
+        return cls(
             session_id=prisma_session.id,
             user_id=prisma_session.userId,
             title=prisma_session.title,
-            messages=messages,
             usage=usage,
             credentials=credentials,
             started_at=prisma_session.createdAt,
@@ -192,46 +122,55 @@ class ChatSession(BaseModel):
             successful_agent_schedules=successful_agent_schedules,
         )
 
-    @staticmethod
-    def _merge_consecutive_assistant_messages(
-        messages: list[ChatCompletionMessageParam],
-    ) -> list[ChatCompletionMessageParam]:
-        """Merge consecutive assistant messages into single messages.
 
-        Long-running tool flows can create split assistant messages: one with
-        text content and another with tool_calls. Anthropic's API requires
-        tool_result blocks to reference a tool_use in the immediately preceding
-        assistant message, so these splits cause 400 errors via OpenRouter.
+class ChatSession(ChatSessionInfo):
+    messages: list[ChatMessage]
+
+    @classmethod
+    def new(cls, user_id: str) -> Self:
+        return cls(
+            session_id=str(uuid.uuid4()),
+            user_id=user_id,
+            title=None,
+            messages=[],
+            usage=[],
+            credentials={},
+            started_at=datetime.now(UTC),
+            updated_at=datetime.now(UTC),
+        )
+
+    @classmethod
+    def from_db(cls, prisma_session: PrismaChatSession) -> Self:
+        """Convert Prisma ChatSession to Pydantic ChatSession."""
+        if prisma_session.Messages is None:
+            raise ValueError(
+                f"Prisma session {prisma_session.id} is missing Messages relation"
+            )
+
+        return cls(
+            **ChatSessionInfo.from_db(prisma_session).model_dump(),
+            messages=[ChatMessage.from_db(m) for m in prisma_session.Messages],
+        )
+
+    def add_tool_call_to_current_turn(self, tool_call: dict) -> None:
+        """Attach a tool_call to the current turn's assistant message.
+
+        Searches backwards for the most recent assistant message (stopping at
+        any user message boundary). If found, appends the tool_call to it.
+        Otherwise creates a new assistant message with the tool_call.
         """
-        if len(messages) < 2:
-            return messages
+        for msg in reversed(self.messages):
+            if msg.role == "user":
+                break
+            if msg.role == "assistant":
+                if not msg.tool_calls:
+                    msg.tool_calls = []
+                msg.tool_calls.append(tool_call)
+                return
 
-        result: list[ChatCompletionMessageParam] = [messages[0]]
-        for msg in messages[1:]:
-            prev = result[-1]
-            if prev.get("role") != "assistant" or msg.get("role") != "assistant":
-                result.append(msg)
-                continue
-
-            prev = cast(ChatCompletionAssistantMessageParam, prev)
-            curr = cast(ChatCompletionAssistantMessageParam, msg)
-
-            curr_content = curr.get("content") or ""
-            if curr_content:
-                prev_content = prev.get("content") or ""
-                prev["content"] = (
-                    f"{prev_content}\n{curr_content}" if prev_content else curr_content
-                )
-
-            curr_tool_calls = curr.get("tool_calls")
-            if curr_tool_calls:
-                prev_tool_calls = prev.get("tool_calls")
-                prev["tool_calls"] = (
-                    list(prev_tool_calls) + list(curr_tool_calls)
-                    if prev_tool_calls
-                    else list(curr_tool_calls)
-                )
-        return result
+        self.messages.append(
+            ChatMessage(role="assistant", content="", tool_calls=[tool_call])
+        )
 
     def to_openai_messages(self) -> list[ChatCompletionMessageParam]:
         messages = []
@@ -321,39 +260,68 @@ class ChatSession(BaseModel):
                 )
         return self._merge_consecutive_assistant_messages(messages)
 
+    @staticmethod
+    def _merge_consecutive_assistant_messages(
+        messages: list[ChatCompletionMessageParam],
+    ) -> list[ChatCompletionMessageParam]:
+        """Merge consecutive assistant messages into single messages.
 
-async def _get_session_from_cache(session_id: str) -> ChatSession | None:
-    """Get a chat session from Redis cache."""
-    redis_key = _get_session_cache_key(session_id)
-    async_redis = await get_redis_async()
-    raw_session: bytes | None = await async_redis.get(redis_key)
+        Long-running tool flows can create split assistant messages: one with
+        text content and another with tool_calls. Anthropic's API requires
+        tool_result blocks to reference a tool_use in the immediately preceding
+        assistant message, so these splits cause 400 errors via OpenRouter.
+        """
+        if len(messages) < 2:
+            return messages
 
-    if raw_session is None:
-        return None
+        result: list[ChatCompletionMessageParam] = [messages[0]]
+        for msg in messages[1:]:
+            prev = result[-1]
+            if prev.get("role") != "assistant" or msg.get("role") != "assistant":
+                result.append(msg)
+                continue
 
-    try:
-        session = ChatSession.model_validate_json(raw_session)
-        logger.info(
-            f"Loading session {session_id} from cache: "
-            f"message_count={len(session.messages)}, "
-            f"roles={[m.role for m in session.messages]}"
-        )
-        return session
-    except Exception as e:
-        logger.error(f"Failed to deserialize session {session_id}: {e}", exc_info=True)
-        raise RedisError(f"Corrupted session data for {session_id}") from e
+            prev = cast(ChatCompletionAssistantMessageParam, prev)
+            curr = cast(ChatCompletionAssistantMessageParam, msg)
+
+            curr_content = curr.get("content") or ""
+            if curr_content:
+                prev_content = prev.get("content") or ""
+                prev["content"] = (
+                    f"{prev_content}\n{curr_content}" if prev_content else curr_content
+                )
+
+            curr_tool_calls = curr.get("tool_calls")
+            if curr_tool_calls:
+                prev_tool_calls = prev.get("tool_calls")
+                prev["tool_calls"] = (
+                    list(prev_tool_calls) + list(curr_tool_calls)
+                    if prev_tool_calls
+                    else list(curr_tool_calls)
+                )
+        return result
 
 
-async def _cache_session(session: ChatSession) -> None:
-    """Cache a chat session in Redis."""
-    redis_key = _get_session_cache_key(session.session_id)
-    async_redis = await get_redis_async()
-    await async_redis.setex(redis_key, config.session_ttl, session.model_dump_json())
+def _parse_json_field(value: str | dict | list | None, default: Any = None) -> Any:
+    """Parse a JSON field that may be stored as string or already parsed."""
+    if value is None:
+        return default
+    if isinstance(value, str):
+        return json.loads(value)
+    return value
+
+
+# ================ Chat cache + DB operations ================ #
+
+# NOTE: Database calls are automatically routed through DatabaseManager if Prisma is not
+#       connected directly.
 
 
 async def cache_chat_session(session: ChatSession) -> None:
-    """Cache a chat session without persisting to the database."""
-    await _cache_session(session)
+    """Cache a chat session in Redis (without persisting to the database)."""
+    redis_key = _get_session_cache_key(session.session_id)
+    async_redis = await get_redis_async()
+    await async_redis.setex(redis_key, config.session_ttl, session.model_dump_json())
 
 
 async def invalidate_session_cache(session_id: str) -> None:
@@ -371,80 +339,6 @@ async def invalidate_session_cache(session_id: str) -> None:
         logger.warning(f"Failed to invalidate session cache for {session_id}: {e}")
 
 
-async def _get_session_from_db(session_id: str) -> ChatSession | None:
-    """Get a chat session from the database."""
-    prisma_session = await chat_db.get_chat_session(session_id)
-    if not prisma_session:
-        return None
-
-    messages = prisma_session.Messages
-    logger.info(
-        f"Loading session {session_id} from DB: "
-        f"has_messages={messages is not None}, "
-        f"message_count={len(messages) if messages else 0}, "
-        f"roles={[m.role for m in messages] if messages else []}"
-    )
-
-    return ChatSession.from_db(prisma_session, messages)
-
-
-async def _save_session_to_db(
-    session: ChatSession, existing_message_count: int
-) -> None:
-    """Save or update a chat session in the database."""
-    # Check if session exists in DB
-    existing = await chat_db.get_chat_session(session.session_id)
-
-    if not existing:
-        # Create new session
-        await chat_db.create_chat_session(
-            session_id=session.session_id,
-            user_id=session.user_id,
-        )
-        existing_message_count = 0
-
-    # Calculate total tokens from usage
-    total_prompt = sum(u.prompt_tokens for u in session.usage)
-    total_completion = sum(u.completion_tokens for u in session.usage)
-
-    # Update session metadata
-    await chat_db.update_chat_session(
-        session_id=session.session_id,
-        credentials=session.credentials,
-        successful_agent_runs=session.successful_agent_runs,
-        successful_agent_schedules=session.successful_agent_schedules,
-        total_prompt_tokens=total_prompt,
-        total_completion_tokens=total_completion,
-    )
-
-    # Add new messages (only those after existing count)
-    new_messages = session.messages[existing_message_count:]
-    if new_messages:
-        messages_data = []
-        for msg in new_messages:
-            messages_data.append(
-                {
-                    "role": msg.role,
-                    "content": msg.content,
-                    "name": msg.name,
-                    "tool_call_id": msg.tool_call_id,
-                    "refusal": msg.refusal,
-                    "tool_calls": msg.tool_calls,
-                    "function_call": msg.function_call,
-                }
-            )
-        logger.info(
-            f"Saving {len(new_messages)} new messages to DB for session {session.session_id}: "
-            f"roles={[m['role'] for m in messages_data]}, "
-            f"start_sequence={existing_message_count}"
-        )
-        await chat_db.add_chat_messages_batch(
-            session_id=session.session_id,
-            messages=messages_data,
-            start_sequence=existing_message_count,
-        )
-
-
 async def get_chat_session(
     session_id: str,
     user_id: str | None = None,
@@ -476,7 +370,7 @@ async def get_chat_session(
         logger.warning(f"Unexpected cache error for session {session_id}: {e}")
 
     # Fall back to database
-    logger.info(f"Session {session_id} not in cache, checking database")
+    logger.debug(f"Session {session_id} not in cache, checking database")
     session = await _get_session_from_db(session_id)
 
     if session is None:
@@ -492,7 +386,7 @@ async def get_chat_session(
 
     # Cache the session from DB
     try:
-        await _cache_session(session)
+        await cache_chat_session(session)
         logger.info(f"Cached session {session_id} from database")
     except Exception as e:
         logger.warning(f"Failed to cache session {session_id}: {e}")
@@ -500,6 +394,44 @@ async def get_chat_session(
     return session
 
 
+async def _get_session_from_cache(session_id: str) -> ChatSession | None:
+    """Get a chat session from Redis cache."""
+    redis_key = _get_session_cache_key(session_id)
+    async_redis = await get_redis_async()
+    raw_session: bytes | None = await async_redis.get(redis_key)
+
+    if raw_session is None:
+        return None
+
+    try:
+        session = ChatSession.model_validate_json(raw_session)
+        logger.info(
+            f"Loading session {session_id} from cache: "
+            f"message_count={len(session.messages)}, "
+            f"roles={[m.role for m in session.messages]}"
+        )
+        return session
+    except Exception as e:
+        logger.error(f"Failed to deserialize session {session_id}: {e}", exc_info=True)
+        raise RedisError(f"Corrupted session data for {session_id}") from e
+
+
+async def _get_session_from_db(session_id: str) -> ChatSession | None:
+    """Get a chat session from the database."""
+    session = await chat_db().get_chat_session(session_id)
+    if not session:
+        return None
+
+    logger.info(
+        f"Loaded session {session_id} from DB: "
+        f"has_messages={bool(session.messages)}, "
+        f"message_count={len(session.messages)}, "
+        f"roles={[m.role for m in session.messages]}"
+    )
+
+    return session
+
+
 async def upsert_chat_session(
     session: ChatSession,
 ) -> ChatSession:
@@ -519,25 +451,35 @@ async def upsert_chat_session(
     lock = await _get_session_lock(session.session_id)
 
     async with lock:
-        # Get existing message count from DB for incremental saves
-        existing_message_count = await chat_db.get_chat_session_message_count(
-            session.session_id
-        )
+        # Always query DB for existing message count to ensure consistency
+        existing_message_count = await chat_db().get_next_sequence(session.session_id)
 
         db_error: Exception | None = None
 
         # Save to database (primary storage)
         try:
-            await _save_session_to_db(session, existing_message_count)
+            await _save_session_to_db(
+                session,
+                existing_message_count,
+                skip_existence_check=existing_message_count > 0,
+            )
         except Exception as e:
             logger.error(
                 f"Failed to save session {session.session_id} to database: {e}"
             )
             db_error = e
 
-        # Save to cache (best-effort, even if DB failed)
+        # Save to cache (best-effort, even if DB failed).
+        # Title updates (update_session_title) run *outside* this lock because
+        # they only touch the title field, not messages.  So a concurrent rename
+        # or auto-title may have written a newer title to Redis while this
+        # upsert was in progress.  Always prefer the cached title to avoid
+        # overwriting it with the stale in-memory copy.
         try:
-            await _cache_session(session)
+            existing_cached = await _get_session_from_cache(session.session_id)
+            if existing_cached and existing_cached.title:
+                session = session.model_copy(update={"title": existing_cached.title})
+            await cache_chat_session(session)
         except Exception as e:
             # If DB succeeded but cache failed, raise cache error
             if db_error is None:
@@ -558,6 +500,107 @@ async def upsert_chat_session(
         return session
 
 
+async def _save_session_to_db(
+    session: ChatSession,
+    existing_message_count: int,
+    *,
+    skip_existence_check: bool = False,
+) -> None:
+    """Save or update a chat session in the database.
+
+    Args:
+        skip_existence_check: When True, skip the ``get_chat_session`` query
+            and assume the session row already exists.  Saves one DB round trip
+            for incremental saves during streaming.
+    """
+    db = chat_db()
+
+    if not skip_existence_check:
+        # Check if session exists in DB
+        existing = await db.get_chat_session(session.session_id)
+
+        if not existing:
+            # Create new session
+            await db.create_chat_session(
+                session_id=session.session_id,
+                user_id=session.user_id,
+            )
+            existing_message_count = 0
+
+    # Calculate total tokens from usage
+    total_prompt = sum(u.prompt_tokens for u in session.usage)
+    total_completion = sum(u.completion_tokens for u in session.usage)
+
+    # Update session metadata
+    await db.update_chat_session(
+        session_id=session.session_id,
+        credentials=session.credentials,
+        successful_agent_runs=session.successful_agent_runs,
+        successful_agent_schedules=session.successful_agent_schedules,
+        total_prompt_tokens=total_prompt,
+        total_completion_tokens=total_completion,
+    )
+
+    # Add new messages (only those after existing count)
+    new_messages = session.messages[existing_message_count:]
+    if new_messages:
+        messages_data = []
+        for msg in new_messages:
+            messages_data.append(
+                {
+                    "role": msg.role,
+                    "content": msg.content,
+                    "name": msg.name,
+                    "tool_call_id": msg.tool_call_id,
+                    "refusal": msg.refusal,
+                    "tool_calls": msg.tool_calls,
+                    "function_call": msg.function_call,
+                }
+            )
+        logger.info(
+            f"Saving {len(new_messages)} new messages to DB for session {session.session_id}: "
+            f"roles={[m['role'] for m in messages_data]}, "
+            f"start_sequence={existing_message_count}"
+        )
+        await db.add_chat_messages_batch(
+            session_id=session.session_id,
+            messages=messages_data,
+            start_sequence=existing_message_count,
+        )
+
+
+async def append_and_save_message(session_id: str, message: ChatMessage) -> ChatSession:
+    """Atomically append a message to a session and persist it.
+
+    Acquires the session lock, re-fetches the latest session state,
+    appends the message, and saves — preventing message loss when
+    concurrent requests modify the same session.
+    """
+    lock = await _get_session_lock(session_id)
+
+    async with lock:
+        session = await get_chat_session(session_id)
+        if session is None:
+            raise ValueError(f"Session {session_id} not found")
+
+        session.messages.append(message)
+        existing_message_count = await chat_db().get_next_sequence(session_id)
+
+        try:
+            await _save_session_to_db(session, existing_message_count)
+        except Exception as e:
+            raise DatabaseError(
+                f"Failed to persist message to session {session_id}"
+            ) from e
+
+        try:
+            await cache_chat_session(session)
+        except Exception as e:
+            logger.warning(f"Cache write failed for session {session_id}: {e}")
+
+        return session
+
+
 async def create_chat_session(user_id: str) -> ChatSession:
     """Create a new chat session and persist it.
 
@@ -570,7 +613,7 @@ async def create_chat_session(user_id: str) -> ChatSession:
 
     # Create in database first - fail fast if this fails
     try:
-        await chat_db.create_chat_session(
+        await chat_db().create_chat_session(
             session_id=session.session_id,
             user_id=user_id,
         )
@@ -582,7 +625,7 @@ async def create_chat_session(user_id: str) -> ChatSession:
 
     # Cache the session (best-effort optimization, DB is source of truth)
     try:
-        await _cache_session(session)
+        await cache_chat_session(session)
     except Exception as e:
         logger.warning(f"Failed to cache new session {session.session_id}: {e}")
 
@@ -593,20 +636,16 @@ async def get_user_sessions(
     user_id: str,
     limit: int = 50,
     offset: int = 0,
-) -> tuple[list[ChatSession], int]:
+) -> tuple[list[ChatSessionInfo], int]:
     """Get chat sessions for a user from the database with total count.
 
     Returns:
         A tuple of (sessions, total_count) where total_count is the overall
         number of sessions for the user (not just the current page).
     """
-    prisma_sessions = await chat_db.get_user_chat_sessions(user_id, limit, offset)
-    total_count = await chat_db.get_user_session_count(user_id)
-
-    sessions = []
-    for prisma_session in prisma_sessions:
-        # Convert without messages for listing (lighter weight)
-        sessions.append(ChatSession.from_db(prisma_session, None))
+    db = chat_db()
+    sessions = await db.get_user_chat_sessions(user_id, limit, offset)
+    total_count = await db.get_user_session_count(user_id)
 
     return sessions, total_count
 
@@ -624,7 +663,7 @@ async def delete_chat_session(session_id: str, user_id: str | None = None) -> bo
     """
     # Delete from database first (with optional user_id validation)
     # This confirms ownership before invalidating cache
-    deleted = await chat_db.delete_chat_session(session_id, user_id)
+    deleted = await chat_db().delete_chat_session(session_id, user_id)
 
     if not deleted:
         return False
@@ -641,38 +680,89 @@ async def delete_chat_session(session_id: str, user_id: str | None = None) -> bo
     async with _session_locks_mutex:
         _session_locks.pop(session_id, None)
 
+    # Shut down any local browser daemon for this session (best-effort).
+    # Inline import required: all tool modules import ChatSession from this
+    # module, so any top-level import from tools.* would create a cycle.
+    try:
+        from .tools.agent_browser import close_browser_session
+
+        await close_browser_session(session_id, user_id=user_id)
+    except Exception as e:
+        logger.debug(f"Browser cleanup for session {session_id}: {e}")
+
     return True
 
 
-async def update_session_title(session_id: str, title: str) -> bool:
-    """Update only the title of a chat session.
+async def update_session_title(
+    session_id: str,
+    user_id: str,
+    title: str,
+    *,
+    only_if_empty: bool = False,
+) -> bool:
+    """Update the title of a chat session, scoped to the owning user.
 
-    This is a lightweight operation that doesn't touch messages, avoiding
-    race conditions with concurrent message updates. Use this for background
-    title generation instead of upsert_chat_session.
+    Lightweight operation that doesn't touch messages, avoiding race conditions
+    with concurrent message updates.
 
     Args:
         session_id: The session ID to update.
+        user_id: Owning user — the DB query filters on this.
         title: The new title to set.
+        only_if_empty: When True, uses an atomic ``UPDATE WHERE title IS NULL``
+            so auto-generated titles never overwrite a user-set title.
 
     Returns:
-        True if updated successfully, False otherwise.
+        True if updated successfully, False otherwise (not found, wrong user,
+        or — when only_if_empty — title was already set).
     """
     try:
-        result = await chat_db.update_chat_session(session_id=session_id, title=title)
-        if result is None:
-            logger.warning(f"Session {session_id} not found for title update")
+        updated = await chat_db().update_chat_session_title(
+            session_id, user_id, title, only_if_empty=only_if_empty
+        )
+        if not updated:
             return False
 
-        # Invalidate cache so next fetch gets updated title
+        # Update title in cache if it exists (instead of invalidating).
+        # This prevents race conditions where cache invalidation causes
+        # the frontend to see stale DB data while streaming is still in progress.
         try:
-            redis_key = _get_session_cache_key(session_id)
-            async_redis = await get_redis_async()
-            await async_redis.delete(redis_key)
+            cached = await _get_session_from_cache(session_id)
+            if cached:
+                cached.title = title
+                await cache_chat_session(cached)
         except Exception as e:
-            logger.warning(f"Failed to invalidate cache for session {session_id}: {e}")
+            logger.warning(
+                f"Cache title update failed for session {session_id} (non-critical): {e}"
+            )
 
         return True
     except Exception as e:
         logger.error(f"Failed to update title for session {session_id}: {e}")
         return False
+
+
+# ==================== Chat session locks ==================== #
+
+_session_locks: WeakValueDictionary[str, asyncio.Lock] = WeakValueDictionary()
+_session_locks_mutex = asyncio.Lock()
+
+
+async def _get_session_lock(session_id: str) -> asyncio.Lock:
+    """Get or create a lock for a specific session to prevent concurrent upserts.
+
+    This was originally added to solve the specific problem of race conditions between
+    the session title thread and the conversation thread, which always occurs on the
+    same instance as we prevent rapid request sends on the frontend.
+
+    Uses WeakValueDictionary for automatic cleanup: locks are garbage collected
+    when no coroutine holds a reference to them, preventing memory leaks from
+    unbounded growth of session locks. Explicit cleanup also occurs
+    in `delete_chat_session()`.
+    """
+    async with _session_locks_mutex:
+        lock = _session_locks.get(session_id)
+        if lock is None:
+            lock = asyncio.Lock()
+            _session_locks[session_id] = lock
+        return lock

autogpt_platform/backend/backend/copilot/model_test.py

@@ -331,3 +331,96 @@ def test_to_openai_messages_merges_split_assistants():
     tc_list = merged.get("tool_calls")
     assert tc_list is not None and len(list(tc_list)) == 1
     assert list(tc_list)[0]["id"] == "tc1"
+
+
+# --------------------------------------------------------------------------- #
+#  Concurrent save collision detection                                        #
+# --------------------------------------------------------------------------- #
+
+
+@pytest.mark.asyncio(loop_scope="session")
+async def test_concurrent_saves_collision_detection(setup_test_user, test_user_id):
+    """Test that concurrent saves from streaming loop and callback handle collisions correctly.
+
+    Simulates the race condition where:
+    1. Streaming loop starts with saved_msg_count=5
+    2. Long-running callback appends message #5 and saves
+    3. Streaming loop tries to save with stale count=5
+
+    The collision detection should handle this gracefully.
+    """
+    import asyncio
+
+    # Create a session with initial messages
+    session = ChatSession.new(user_id=test_user_id)
+    for i in range(3):
+        session.messages.append(
+            ChatMessage(
+                role="user" if i % 2 == 0 else "assistant", content=f"Message {i}"
+            )
+        )
+
+    # Save initial messages
+    session = await upsert_chat_session(session)
+
+    # Simulate streaming loop and callback saving concurrently
+    async def streaming_loop_save():
+        """Simulates streaming loop saving messages."""
+        # Add 2 messages
+        session.messages.append(ChatMessage(role="user", content="Streaming message 1"))
+        session.messages.append(
+            ChatMessage(role="assistant", content="Streaming message 2")
+        )
+
+        # Wait a bit to let callback potentially save first
+        await asyncio.sleep(0.01)
+
+        # Save (will query DB for existing count)
+        return await upsert_chat_session(session)
+
+    async def callback_save():
+        """Simulates long-running callback saving a message."""
+        # Add 1 message
+        session.messages.append(
+            ChatMessage(role="tool", content="Callback result", tool_call_id="tc1")
+        )
+
+        # Save immediately (will query DB for existing count)
+        return await upsert_chat_session(session)
+
+    # Run both saves concurrently - one will hit collision detection
+    results = await asyncio.gather(streaming_loop_save(), callback_save())
+
+    # Both should succeed
+    assert all(r is not None for r in results)
+
+    # Reload session from DB to verify
+    from backend.data.redis_client import get_redis_async
+
+    redis_key = f"chat:session:{session.session_id}"
+    async_redis = await get_redis_async()
+    await async_redis.delete(redis_key)  # Clear cache to force DB load
+
+    loaded_session = await get_chat_session(session.session_id, test_user_id)
+    assert loaded_session is not None
+
+    # Should have all 6 messages (3 initial + 2 streaming + 1 callback)
+    assert len(loaded_session.messages) == 6
+
+    # Verify no duplicate sequences
+    sequences = []
+    for i, msg in enumerate(loaded_session.messages):
+        # Messages should have sequential sequence numbers starting from 0
+        sequences.append(i)
+
+    # All sequences should be unique and sequential
+    assert sequences == list(range(6))
+
+    # Verify message content is preserved
+    contents = [m.content for m in loaded_session.messages]
+    assert "Message 0" in contents
+    assert "Message 1" in contents
+    assert "Message 2" in contents
+    assert "Streaming message 1" in contents
+    assert "Streaming message 2" in contents
+    assert "Callback result" in contents

autogpt_platform/backend/backend/copilot/response_model.py

@@ -5,12 +5,17 @@ This module implements the AI SDK UI Stream Protocol (v1) for streaming chat res
 See: https://ai-sdk.dev/docs/ai-sdk-ui/stream-protocol
 """
 
+import json
+import logging
 from enum import Enum
 from typing import Any
 
 from pydantic import BaseModel, Field
 
 from backend.util.json import dumps as json_dumps
+from backend.util.truncate import truncate
+
+logger = logging.getLogger(__name__)
 
 
 class ResponseType(str, Enum):
@@ -47,7 +52,8 @@ class StreamBaseResponse(BaseModel):
 
     def to_sse(self) -> str:
         """Convert to SSE format."""
-        return f"data: {self.model_dump_json()}\n\n"
+        json_str = self.model_dump_json(exclude_none=True)
+        return f"data: {json_str}\n\n"
 
 
 # ========== Message Lifecycle ==========
@@ -58,15 +64,13 @@ class StreamStart(StreamBaseResponse):
 
     type: ResponseType = ResponseType.START
     messageId: str = Field(..., description="Unique message ID")
-    taskId: str | None = Field(
+    sessionId: str | None = Field(
         default=None,
-        description="Task ID for SSE reconnection. Clients can reconnect using GET /tasks/{taskId}/stream",
+        description="Session ID for SSE reconnection.",
     )
 
     def to_sse(self) -> str:
-        """Convert to SSE format, excluding non-protocol fields like taskId."""
-        import json
-
+        """Convert to SSE format, excluding non-protocol fields like sessionId."""
         data: dict[str, Any] = {
             "type": self.type.value,
             "messageId": self.messageId,
@@ -147,6 +151,9 @@ class StreamToolInputAvailable(StreamBaseResponse):
     )
 
 
+_MAX_TOOL_OUTPUT_SIZE = 100_000  # ~100 KB; truncate to avoid bloating SSE/DB
+
+
 class StreamToolOutputAvailable(StreamBaseResponse):
     """Tool execution result."""
 
@@ -161,10 +168,12 @@ class StreamToolOutputAvailable(StreamBaseResponse):
         default=True, description="Whether the tool execution succeeded"
     )
 
+    def model_post_init(self, __context: Any) -> None:
+        """Truncate oversized outputs after construction."""
+        self.output = truncate(self.output, _MAX_TOOL_OUTPUT_SIZE)
+
     def to_sse(self) -> str:
         """Convert to SSE format, excluding non-spec fields."""
-        import json
-
         data = {
             "type": self.type.value,
             "toolCallId": self.toolCallId,

autogpt_platform/backend/backend/copilot/sdk/__init__.py

@@ -0,0 +1,14 @@
+"""Claude Agent SDK integration for CoPilot.
+
+This module provides the integration layer between the Claude Agent SDK
+and the existing CoPilot tool system, enabling drop-in replacement of
+the current LLM orchestration with the battle-tested Claude Agent SDK.
+"""
+
+from .service import stream_chat_completion_sdk
+from .tool_adapter import create_copilot_mcp_server
+
+__all__ = [
+    "stream_chat_completion_sdk",
+    "create_copilot_mcp_server",
+]

autogpt_platform/backend/backend/copilot/sdk/compaction.py

@@ -0,0 +1,239 @@
+"""Compaction tracking for SDK-based chat sessions.
+
+Encapsulates the state machine and event emission for context compaction,
+both pre-query (history compressed before SDK query) and SDK-internal
+(PreCompact hook fires mid-stream).
+
+All compaction-related helpers live here: event builders, message filtering,
+persistence, and the ``CompactionTracker`` state machine.
+"""
+
+import asyncio
+import logging
+import uuid
+from collections.abc import Callable
+
+from ..constants import COMPACTION_DONE_MSG, COMPACTION_TOOL_NAME
+from ..model import ChatMessage, ChatSession
+from ..response_model import (
+    StreamBaseResponse,
+    StreamFinishStep,
+    StreamStartStep,
+    StreamToolInputAvailable,
+    StreamToolInputStart,
+    StreamToolOutputAvailable,
+)
+
+logger = logging.getLogger(__name__)
+
+
+# ---------------------------------------------------------------------------
+# Event builders (private — use CompactionTracker or compaction_events)
+# ---------------------------------------------------------------------------
+
+
+def _start_events(tool_call_id: str) -> list[StreamBaseResponse]:
+    """Build the opening events for a compaction tool call."""
+    return [
+        StreamStartStep(),
+        StreamToolInputStart(toolCallId=tool_call_id, toolName=COMPACTION_TOOL_NAME),
+        StreamToolInputAvailable(
+            toolCallId=tool_call_id, toolName=COMPACTION_TOOL_NAME, input={}
+        ),
+    ]
+
+
+def _end_events(tool_call_id: str, message: str) -> list[StreamBaseResponse]:
+    """Build the closing events for a compaction tool call."""
+    return [
+        StreamToolOutputAvailable(
+            toolCallId=tool_call_id,
+            toolName=COMPACTION_TOOL_NAME,
+            output=message,
+        ),
+        StreamFinishStep(),
+    ]
+
+
+def _new_tool_call_id() -> str:
+    return f"compaction-{uuid.uuid4().hex[:12]}"
+
+
+# ---------------------------------------------------------------------------
+# Public event builder
+# ---------------------------------------------------------------------------
+
+
+def emit_compaction(session: ChatSession) -> list[StreamBaseResponse]:
+    """Create, persist, and return a self-contained compaction tool call.
+
+    Convenience for callers that don't use ``CompactionTracker`` (e.g. the
+    legacy non-SDK streaming path in ``service.py``).
+    """
+    tc_id = _new_tool_call_id()
+    evts = compaction_events(COMPACTION_DONE_MSG, tool_call_id=tc_id)
+    _persist(session, tc_id, COMPACTION_DONE_MSG)
+    return evts
+
+
+def compaction_events(
+    message: str, tool_call_id: str | None = None
+) -> list[StreamBaseResponse]:
+    """Emit a self-contained compaction tool call (already completed).
+
+    When *tool_call_id* is provided it is reused (e.g. for persistence that
+    must match an already-streamed start event).  Otherwise a new ID is
+    generated.
+    """
+    tc_id = tool_call_id or _new_tool_call_id()
+    return _start_events(tc_id) + _end_events(tc_id, message)
+
+
+# ---------------------------------------------------------------------------
+# Message filtering
+# ---------------------------------------------------------------------------
+
+
+def filter_compaction_messages(
+    messages: list[ChatMessage],
+) -> list[ChatMessage]:
+    """Remove synthetic compaction tool-call messages (UI-only artifacts).
+
+    Strips assistant messages whose only tool calls are compaction calls,
+    and their corresponding tool-result messages.
+    """
+    compaction_ids: set[str] = set()
+    filtered: list[ChatMessage] = []
+    for msg in messages:
+        if msg.role == "assistant" and msg.tool_calls:
+            for tc in msg.tool_calls:
+                if tc.get("function", {}).get("name") == COMPACTION_TOOL_NAME:
+                    compaction_ids.add(tc.get("id", ""))
+            real_calls = [
+                tc
+                for tc in msg.tool_calls
+                if tc.get("function", {}).get("name") != COMPACTION_TOOL_NAME
+            ]
+            if not real_calls and not msg.content:
+                continue
+        if msg.role == "tool" and msg.tool_call_id in compaction_ids:
+            continue
+        filtered.append(msg)
+    return filtered
+
+
+# ---------------------------------------------------------------------------
+# Persistence
+# ---------------------------------------------------------------------------
+
+
+def _persist(session: ChatSession, tool_call_id: str, message: str) -> None:
+    """Append compaction tool-call + result to session messages.
+
+    Compaction events are synthetic so they bypass the normal adapter
+    accumulation.  This explicitly records them so they survive a page refresh.
+    """
+    session.messages.append(
+        ChatMessage(
+            role="assistant",
+            content="",
+            tool_calls=[
+                {
+                    "id": tool_call_id,
+                    "type": "function",
+                    "function": {
+                        "name": COMPACTION_TOOL_NAME,
+                        "arguments": "{}",
+                    },
+                }
+            ],
+        )
+    )
+    session.messages.append(
+        ChatMessage(role="tool", content=message, tool_call_id=tool_call_id)
+    )
+
+
+# ---------------------------------------------------------------------------
+# CompactionTracker — state machine for streaming sessions
+# ---------------------------------------------------------------------------
+
+
+class CompactionTracker:
+    """Tracks compaction state and yields UI events.
+
+    Two compaction paths:
+
+    1. **Pre-query** — history compressed before the SDK query starts.
+       Call :meth:`emit_pre_query` to yield a self-contained tool call.
+
+    2. **SDK-internal** — ``PreCompact`` hook fires mid-stream.
+       Call :meth:`emit_start_if_ready` on heartbeat ticks and
+       :meth:`emit_end_if_ready` when a message arrives.
+    """
+
+    def __init__(self) -> None:
+        self._compact_start = asyncio.Event()
+        self._start_emitted = False
+        self._done = False
+        self._tool_call_id = ""
+
+    @property
+    def on_compact(self) -> Callable[[], None]:
+        """Callback for the PreCompact hook."""
+        return self._compact_start.set
+
+    # ------------------------------------------------------------------
+    # Pre-query compaction
+    # ------------------------------------------------------------------
+
+    def emit_pre_query(self, session: ChatSession) -> list[StreamBaseResponse]:
+        """Emit + persist a self-contained compaction tool call."""
+        self._done = True
+        return emit_compaction(session)
+
+    # ------------------------------------------------------------------
+    # SDK-internal compaction
+    # ------------------------------------------------------------------
+
+    def reset_for_query(self) -> None:
+        """Reset per-query state before a new SDK query."""
+        self._done = False
+        self._start_emitted = False
+        self._tool_call_id = ""
+
+    def emit_start_if_ready(self) -> list[StreamBaseResponse]:
+        """If the PreCompact hook fired, emit start events (spinning tool)."""
+        if self._compact_start.is_set() and not self._start_emitted and not self._done:
+            self._compact_start.clear()
+            self._start_emitted = True
+            self._tool_call_id = _new_tool_call_id()
+            return _start_events(self._tool_call_id)
+        return []
+
+    async def emit_end_if_ready(self, session: ChatSession) -> list[StreamBaseResponse]:
+        """If compaction is in progress, emit end events and persist."""
+        # Yield so pending hook tasks can set compact_start
+        await asyncio.sleep(0)
+
+        if self._done:
+            return []
+        if not self._start_emitted and not self._compact_start.is_set():
+            return []
+
+        if self._start_emitted:
+            # Close the open spinner
+            done_events = _end_events(self._tool_call_id, COMPACTION_DONE_MSG)
+            persist_id = self._tool_call_id
+        else:
+            # PreCompact fired but start never emitted — self-contained
+            persist_id = _new_tool_call_id()
+            done_events = compaction_events(
+                COMPACTION_DONE_MSG, tool_call_id=persist_id
+            )
+
+        self._compact_start.clear()
+        self._start_emitted = False
+        self._done = True
+        _persist(session, persist_id, COMPACTION_DONE_MSG)
+        return done_events