fix(chat/sdk): resolve relative paths in security hooks and unify workspace access

The security hook's path validation blocked SDK Read/Write tools because
it didn't resolve relative paths against sdk_cwd. Since the SDK sets cwd,
Claude naturally uses relative paths like "test.txt" which failed the
absolute path prefix check. Now relative paths are joined with sdk_cwd
before validation, and denial messages include the allowed workspace path.

Also clarifies the workspace model: SDK Read/Write + bash_exec share the
same ephemeral session directory, while workspace_file tools provide
persistent cloud storage across sessions.

.dockerignore

@@ -5,13 +5,42 @@
 !docs/
 
 # Platform - Libs
-!autogpt_platform/autogpt_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
 
 # Platform - Backend
-!autogpt_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
 
 # Platform - Frontend
-!autogpt_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
 
 # Classic - AutoGPT
 !classic/original_autogpt/autogpt/
@@ -35,38 +64,6 @@
 # Classic - Frontend
 !classic/frontend/build/web/
 
-# 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
+# Explicitly re-ignore some folders
+.*
+**/__pycache__

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

@@ -40,48 +40,6 @@ 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

@@ -77,15 +77,27 @@ 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"
-          cache: "pnpm"
-          cache-dependency-path: autogpt_platform/frontend/pnpm-lock.yaml
+
+      - 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-
 
       - name: Install JavaScript dependencies
         working-directory: autogpt_platform/frontend

.github/workflows/claude.yml

@@ -93,15 +93,27 @@ 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"
-          cache: "pnpm"
-          cache-dependency-path: autogpt_platform/frontend/pnpm-lock.yaml
+
+      - 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-
 
       - 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@v4
+      uses: github/codeql-action/init@v3
       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@v4
+      uses: github/codeql-action/analyze@v3
       with:
         category: "/language:${{matrix.language}}"

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

@@ -26,6 +26,7 @@ jobs:
   setup:
     runs-on: ubuntu-latest
     outputs:
+      cache-key: ${{ steps.cache-key.outputs.key }}
       components-changed: ${{ steps.filter.outputs.components }}
 
     steps:
@@ -40,17 +41,28 @@ jobs:
             components:
               - 'autogpt_platform/frontend/src/components/**'
 
-      - name: Enable corepack
-        run: corepack enable
-
-      - name: Set up Node
+      - name: Set up Node.js
         uses: actions/setup-node@v6
         with:
           node-version: "22.18.0"
-          cache: "pnpm"
-          cache-dependency-path: autogpt_platform/frontend/pnpm-lock.yaml
 
-      - name: Install dependencies to populate cache
+      - 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
+        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-
+
+      - name: Install dependencies
         run: pnpm install --frozen-lockfile
 
   lint:
@@ -61,15 +73,22 @@ jobs:
       - name: Checkout repository
         uses: actions/checkout@v6
 
-      - name: Enable corepack
-        run: corepack enable
-
-      - name: Set up Node
+      - name: Set up Node.js
         uses: actions/setup-node@v6
         with:
           node-version: "22.18.0"
-          cache: "pnpm"
-          cache-dependency-path: autogpt_platform/frontend/pnpm-lock.yaml
+
+      - name: Enable corepack
+        run: corepack enable
+
+      - name: Restore dependencies cache
+        uses: actions/cache@v5
+        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-
 
       - name: Install dependencies
         run: pnpm install --frozen-lockfile
@@ -92,15 +111,22 @@ jobs:
         with:
           fetch-depth: 0
 
-      - name: Enable corepack
-        run: corepack enable
-
-      - name: Set up Node
+      - name: Set up Node.js
         uses: actions/setup-node@v6
         with:
           node-version: "22.18.0"
-          cache: "pnpm"
-          cache-dependency-path: autogpt_platform/frontend/pnpm-lock.yaml
+
+      - name: Enable corepack
+        run: corepack enable
+
+      - name: Restore dependencies cache
+        uses: actions/cache@v5
+        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-
 
       - name: Install dependencies
         run: pnpm install --frozen-lockfile
@@ -115,8 +141,10 @@ jobs:
           exitOnceUploaded: true
 
   e2e_test:
-    name: end-to-end tests
     runs-on: big-boi
+    needs: setup
+    strategy:
+      fail-fast: false
 
     steps:
       - name: Checkout repository
@@ -124,11 +152,19 @@ jobs:
         with:
           submodules: recursive
 
-      - name: Set up Platform - Copy default supabase .env
+      - 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
         run: |
           cp ../.env.default ../.env
 
-      - name: Set up Platform - Copy backend .env and set OpenAI API key
+      - name: 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
@@ -136,125 +172,77 @@ jobs:
           # Used by E2E test data script to generate embeddings for approved store agents
           OPENAI_API_KEY: ${{ secrets.OPENAI_API_KEY }}
 
-      - name: Set up Platform - Set up Docker Buildx
+      - name: Set up Docker Buildx
         uses: docker/setup-buildx-action@v3
-        with:
-          driver: docker-container
-          driver-opts: network=host
 
-      - name: Set up Platform - Expose GHA cache to docker buildx CLI
-        uses: crazy-max/ghaction-github-runtime@v3
-
-      - 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 "${{ github.ref }}"
-
-          # Build with bake using the resolved compose file (now includes cache config)
-          docker buildx bake --allow=fs.read=.. -f docker-compose.resolved.yml --load
-        env:
-          NEXT_PUBLIC_PW_TEST: true
-
-      - name: Set up tests - Cache E2E test data
-        id: e2e-data-cache
+      - name: Cache Docker layers
         uses: actions/cache@v5
         with:
-          path: /tmp/e2e_test_data.sql
-          key: e2e-test-data-${{ hashFiles('autogpt_platform/backend/test/e2e_test_data.py', 'autogpt_platform/backend/migrations/**', '.github/workflows/platform-frontend-ci.yml') }}
+          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-
 
-      - name: Set up Platform - Start Supabase DB + Auth
+      - name: Run docker compose
         run: |
-          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"
+          NEXT_PUBLIC_PW_TEST=true docker compose -f ../docker-compose.yml up -d
         env:
-          NEXT_PUBLIC_PW_TEST: true
+          DOCKER_BUILDKIT: 1
+          BUILDX_CACHE_FROM: type=local,src=/tmp/.buildx-cache
+          BUILDX_CACHE_TO: type=local,dest=/tmp/.buildx-cache-new,mode=max
 
-      - name: Set up tests - Load cached E2E test data
-        if: steps.e2e-data-cache.outputs.cache-hit == 'true'
+      - name: Move cache
         run: |
-          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
+          rm -rf /tmp/.buildx-cache
+          if [ -d "/tmp/.buildx-cache-new" ]; then
+            mv /tmp/.buildx-cache-new /tmp/.buildx-cache
+          fi
 
-          echo "✅ E2E test data restored from cache"
-
-      - name: Set up Platform - Start (all other services)
+      - name: Wait for services to be ready
         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..."
-        env:
-          NEXT_PUBLIC_PW_TEST: true
+          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..."
 
-      - name: Set up tests - Create E2E test data
-        if: steps.e2e-data-cache.outputs.cache-hit != 'true'
+      - name: Create E2E test data
         run: |
           echo "Creating E2E test data..."
-          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
-          }
+          # 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
 
-          # 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
+      - name: Restore dependencies cache
+        uses: actions/cache@v5
         with:
-          node-version: "22.18.0"
-          cache: "pnpm"
-          cache-dependency-path: autogpt_platform/frontend/pnpm-lock.yaml
+          path: ~/.pnpm-store
+          key: ${{ needs.setup.outputs.cache-key }}
+          restore-keys: |
+            ${{ runner.os }}-pnpm-${{ hashFiles('autogpt_platform/frontend/pnpm-lock.yaml') }}
+            ${{ runner.os }}-pnpm-
 
-      - name: Set up tests - Install dependencies
+      - name: Install dependencies
         run: pnpm install --frozen-lockfile
 
-      - name: Set up tests - Install browser 'chromium'
+      - name: Install Browser 'chromium'
         run: pnpm playwright install --with-deps chromium
 
       - name: Run Playwright tests
@@ -281,7 +269,7 @@ jobs:
 
       - name: Print Final Docker Compose logs
         if: always()
-        run: docker compose -f ../docker-compose.resolved.yml logs
+        run: docker compose -f ../docker-compose.yml logs
 
   integration_test:
     runs-on: ubuntu-latest
@@ -293,15 +281,22 @@ jobs:
         with:
           submodules: recursive
 
-      - name: Enable corepack
-        run: corepack enable
-
-      - name: Set up Node
+      - name: Set up Node.js
         uses: actions/setup-node@v6
         with:
           node-version: "22.18.0"
-          cache: "pnpm"
-          cache-dependency-path: autogpt_platform/frontend/pnpm-lock.yaml
+
+      - name: Enable corepack
+        run: corepack enable
+
+      - name: Restore dependencies cache
+        uses: actions/cache@v5
+        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-
 
       - name: Install dependencies
         run: pnpm install --frozen-lockfile

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

@@ -1,195 +0,0 @@
-#!/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()

autogpt_platform/CLAUDE.md

@@ -45,11 +45,6 @@ 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 = "46.0.5"
+version = "46.0.4"
 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"]
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+    {file = "cryptography-46.0.4-pp311-pypy311_pp73-manylinux_2_28_aarch64.whl", hash = "sha256:c236a44acfb610e70f6b3e1c3ca20ff24459659231ef2f8c48e879e2d32b73da"},
+    {file = "cryptography-46.0.4-pp311-pypy311_pp73-manylinux_2_28_x86_64.whl", hash = "sha256:8a15fb869670efa8f83cbffbc8753c1abf236883225aed74cd179b720ac9ec80"},
+    {file = "cryptography-46.0.4-pp311-pypy311_pp73-manylinux_2_34_aarch64.whl", hash = "sha256:fdc3daab53b212472f1524d070735b2f0c214239df131903bae1d598016fa822"},
+    {file = "cryptography-46.0.4-pp311-pypy311_pp73-manylinux_2_34_x86_64.whl", hash = "sha256:44cc0675b27cadb71bdbb96099cca1fa051cd11d2ade09e5cd3a2edb929ed947"},
+    {file = "cryptography-46.0.4-pp311-pypy311_pp73-win_amd64.whl", hash = "sha256:be8c01a7d5a55f9a47d1888162b76c8f49d62b234d88f0ff91a9fbebe32ffbc3"},
+    {file = "cryptography-46.0.4.tar.gz", hash = "sha256:bfd019f60f8abc2ed1b9be4ddc21cfef059c841d86d710bb69909a688cbb8f59"},
 ]
 
 [package.dependencies]
@@ -516,7 +516,7 @@ nox = ["nox[uv] (>=2024.4.15)"]
 pep8test = ["check-sdist", "click (>=8.0.1)", "mypy (>=1.14)", "ruff (>=0.11.11)"]
 sdist = ["build (>=1.0.0)"]
 ssh = ["bcrypt (>=3.1.5)"]
-test = ["certifi (>=2024)", "cryptography-vectors (==46.0.5)", "pretend (>=0.7)", "pytest (>=7.4.0)", "pytest-benchmark (>=4.0)", "pytest-cov (>=2.10.1)", "pytest-xdist (>=3.5.0)"]
+test = ["certifi (>=2024)", "cryptography-vectors (==46.0.4)", "pretend (>=0.7)", "pytest (>=7.4.0)", "pytest-benchmark (>=4.0)", "pytest-cov (>=2.10.1)", "pytest-xdist (>=3.5.0)"]
 test-randomorder = ["pytest-randomly"]
 
 [[package]]
@@ -570,25 +570,24 @@ tests = ["coverage", "coveralls", "dill", "mock", "nose"]
 
 [[package]]
 name = "fastapi"
-version = "0.128.7"
+version = "0.128.0"
 description = "FastAPI framework, high performance, easy to learn, fast to code, ready for production"
 optional = false
 python-versions = ">=3.9"
 groups = ["main"]
 files = [
-    {file = "fastapi-0.128.7-py3-none-any.whl", hash = "sha256:6bd9bd31cb7047465f2d3fa3ba3f33b0870b17d4eaf7cdb36d1576ab060ad662"},
-    {file = "fastapi-0.128.7.tar.gz", hash = "sha256:783c273416995486c155ad2c0e2b45905dedfaf20b9ef8d9f6a9124670639a24"},
+    {file = "fastapi-0.128.0-py3-none-any.whl", hash = "sha256:aebd93f9716ee3b4f4fcfe13ffb7cf308d99c9f3ab5622d8877441072561582d"},
+    {file = "fastapi-0.128.0.tar.gz", hash = "sha256:1cc179e1cef10a6be60ffe429f79b829dce99d8de32d7acb7e6c8dfdf7f2645a"},
 ]
 
 [package.dependencies]
 annotated-doc = ">=0.0.2"
 pydantic = ">=2.7.0"
-starlette = ">=0.40.0,<1.0.0"
+starlette = ">=0.40.0,<0.51.0"
 typing-extensions = ">=4.8.0"
-typing-inspection = ">=0.4.2"
 
 [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 (>=3.9.3)", "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)"]
+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)"]
 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)"]
 
@@ -1063,14 +1062,14 @@ urllib3 = ">=1.26.0,<3"
 
 [[package]]
 name = "launchdarkly-server-sdk"
-version = "9.15.0"
+version = "9.14.1"
 description = "LaunchDarkly SDK for Python"
 optional = false
-python-versions = ">=3.10"
+python-versions = ">=3.9"
 groups = ["main"]
 files = [
-    {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"},
+    {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"},
 ]
 
 [package.dependencies]
@@ -1479,14 +1478,14 @@ testing = ["coverage", "pytest", "pytest-benchmark"]
 
 [[package]]
 name = "postgrest"
-version = "2.28.0"
+version = "2.27.2"
 description = "PostgREST client for Python. This library provides an ORM interface to PostgREST."
 optional = false
 python-versions = ">=3.9"
 groups = ["main"]
 files = [
-    {file = "postgrest-2.28.0-py3-none-any.whl", hash = "sha256:7bca2f24dd1a1bf8a3d586c7482aba6cd41662da6733045fad585b63b7f7df75"},
-    {file = "postgrest-2.28.0.tar.gz", hash = "sha256:c36b38646d25ea4255321d3d924ce70f8d20ec7799cb42c1221d6a818d4f6515"},
+    {file = "postgrest-2.27.2-py3-none-any.whl", hash = "sha256:1666fef3de05ca097a314433dd5ae2f2d71c613cb7b233d0f468c4ffe37277da"},
+    {file = "postgrest-2.27.2.tar.gz", hash = "sha256:55407d530b5af3d64e883a71fec1f345d369958f723ce4a8ab0b7d169e313242"},
 ]
 
 [package.dependencies]
@@ -2249,14 +2248,14 @@ cli = ["click (>=5.0)"]
 
 [[package]]
 name = "realtime"
-version = "2.28.0"
+version = "2.27.2"
 description = ""
 optional = false
 python-versions = ">=3.9"
 groups = ["main"]
 files = [
-    {file = "realtime-2.28.0-py3-none-any.whl", hash = "sha256:db1bd59bab9b1fcc9f9d3b1a073bed35bf4994d720e6751f10031a58d57a3836"},
-    {file = "realtime-2.28.0.tar.gz", hash = "sha256:d18cedcebd6a8f22fcd509bc767f639761eb218b7b2b6f14fc4205b6259b50fc"},
+    {file = "realtime-2.27.2-py3-none-any.whl", hash = "sha256:34a9cbb26a274e707e8fc9e3ee0a66de944beac0fe604dc336d1e985db2c830f"},
+    {file = "realtime-2.27.2.tar.gz", hash = "sha256:b960a90294d2cea1b3f1275ecb89204304728e08fff1c393cc1b3150739556b3"},
 ]
 
 [package.dependencies]
@@ -2437,14 +2436,14 @@ full = ["httpx (>=0.27.0,<0.29.0)", "itsdangerous", "jinja2", "python-multipart
 
 [[package]]
 name = "storage3"
-version = "2.28.0"
+version = "2.27.2"
 description = "Supabase Storage client for Python."
 optional = false
 python-versions = ">=3.9"
 groups = ["main"]
 files = [
-    {file = "storage3-2.28.0-py3-none-any.whl", hash = "sha256:ecb50efd2ac71dabbdf97e99ad346eafa630c4c627a8e5a138ceb5fbbadae716"},
-    {file = "storage3-2.28.0.tar.gz", hash = "sha256:bc1d008aff67de7a0f2bd867baee7aadbcdb6f78f5a310b4f7a38e8c13c19865"},
+    {file = "storage3-2.27.2-py3-none-any.whl", hash = "sha256:e6f16e7a260729e7b1f46e9bf61746805a02e30f5e419ee1291007c432e3ec63"},
+    {file = "storage3-2.27.2.tar.gz", hash = "sha256:cb4807b7f86b4bb1272ac6fdd2f3cfd8ba577297046fa5f88557425200275af5"},
 ]
 
 [package.dependencies]
@@ -2488,35 +2487,35 @@ python-dateutil = ">=2.6.0"
 
 [[package]]
 name = "supabase"
-version = "2.28.0"
+version = "2.27.2"
 description = "Supabase client for Python."
 optional = false
 python-versions = ">=3.9"
 groups = ["main"]
 files = [
-    {file = "supabase-2.28.0-py3-none-any.whl", hash = "sha256:42776971c7d0ccca16034df1ab96a31c50228eb1eb19da4249ad2f756fc20272"},
-    {file = "supabase-2.28.0.tar.gz", hash = "sha256:aea299aaab2a2eed3c57e0be7fc035c6807214194cce795a3575add20268ece1"},
+    {file = "supabase-2.27.2-py3-none-any.whl", hash = "sha256:d4dce00b3a418ee578017ec577c0e5be47a9a636355009c76f20ed2faa15bc54"},
+    {file = "supabase-2.27.2.tar.gz", hash = "sha256:2aed40e4f3454438822442a1e94a47be6694c2c70392e7ae99b51a226d4293f7"},
 ]
 
 [package.dependencies]
 httpx = ">=0.26,<0.29"
-postgrest = "2.28.0"
-realtime = "2.28.0"
-storage3 = "2.28.0"
-supabase-auth = "2.28.0"
-supabase-functions = "2.28.0"
+postgrest = "2.27.2"
+realtime = "2.27.2"
+storage3 = "2.27.2"
+supabase-auth = "2.27.2"
+supabase-functions = "2.27.2"
 yarl = ">=1.22.0"
 
 [[package]]
 name = "supabase-auth"
-version = "2.28.0"
+version = "2.27.2"
 description = "Python Client Library for Supabase Auth"
 optional = false
 python-versions = ">=3.9"
 groups = ["main"]
 files = [
-    {file = "supabase_auth-2.28.0-py3-none-any.whl", hash = "sha256:2ac85026cc285054c7fa6d41924f3a333e9ec298c013e5b5e1754039ba7caec9"},
-    {file = "supabase_auth-2.28.0.tar.gz", hash = "sha256:2bb8f18ff39934e44b28f10918db965659f3735cd6fbfcc022fe0b82dbf8233e"},
+    {file = "supabase_auth-2.27.2-py3-none-any.whl", hash = "sha256:78ec25b11314d0a9527a7205f3b1c72560dccdc11b38392f80297ef98664ee91"},
+    {file = "supabase_auth-2.27.2.tar.gz", hash = "sha256:0f5bcc79b3677cb42e9d321f3c559070cfa40d6a29a67672cc8382fb7dc2fe97"},
 ]
 
 [package.dependencies]
@@ -2526,14 +2525,14 @@ pyjwt = {version = ">=2.10.1", extras = ["crypto"]}
 
 [[package]]
 name = "supabase-functions"
-version = "2.28.0"
+version = "2.27.2"
 description = "Library for Supabase Functions"
 optional = false
 python-versions = ">=3.9"
 groups = ["main"]
 files = [
-    {file = "supabase_functions-2.28.0-py3-none-any.whl", hash = "sha256:30bf2d586f8df285faf0621bb5d5bb3ec3157234fc820553ca156f009475e4ae"},
-    {file = "supabase_functions-2.28.0.tar.gz", hash = "sha256:db3dddfc37aca5858819eb461130968473bd8c75bd284581013958526dac718b"},
+    {file = "supabase_functions-2.27.2-py3-none-any.whl", hash = "sha256:db480efc669d0bca07605b9b6f167312af43121adcc842a111f79bea416ef754"},
+    {file = "supabase_functions-2.27.2.tar.gz", hash = "sha256:d0c8266207a94371cb3fd35ad3c7f025b78a97cf026861e04ccd35ac1775f80b"},
 ]
 
 [package.dependencies]
@@ -2912,4 +2911,4 @@ type = ["pytest-mypy"]
 [metadata]
 lock-version = "2.1"
 python-versions = ">=3.10,<4.0"
-content-hash = "9619cae908ad38fa2c48016a58bcf4241f6f5793aa0e6cc140276e91c433cbbb"
+content-hash = "40eae94995dc0a388fa832ed4af9b6137f28d5b5ced3aaea70d5f91d4d9a179d"

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 = "^0.128.7"
+fastapi = "^0.128.0"
 google-cloud-logging = "^3.13.0"
-launchdarkly-server-sdk = "^9.15.0"
+launchdarkly-server-sdk = "^9.14.1"
 pydantic = "^2.12.5"
 pydantic-settings = "^2.12.0"
 pyjwt = { version = "^2.11.0", extras = ["crypto"] }
 redis = "^6.2.0"
-supabase = "^2.28.0"
+supabase = "^2.27.2"
 uvicorn = "^0.40.0"
 
 [tool.poetry.group.dev.dependencies]

autogpt_platform/backend/.env.default

@@ -104,12 +104,6 @@ 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=
 

autogpt_platform/backend/Dockerfile

@@ -1,5 +1,3 @@
-# ============================ DEPENDENCY BUILDER ============================ #
-
 FROM debian:13-slim AS builder
 
 # Set environment variables
@@ -53,9 +51,7 @@ 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
 
-# ============================== BACKEND SERVER ============================== #
-
-FROM debian:13-slim AS server
+FROM debian:13-slim AS server_dependencies
 
 WORKDIR /app
 
@@ -66,15 +62,22 @@ ENV POETRY_HOME=/opt/poetry \
     DEBIAN_FRONTEND=noninteractive
 ENV PATH=/opt/poetry/bin:$PATH
 
-# Install Python, FFmpeg, and ImageMagick (required for video processing blocks)
-# 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 \
+# 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.
+RUN apt-get update && apt-get install -y \
     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 --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
@@ -84,54 +87,30 @@ COPY --from=builder /usr/bin/npm /usr/bin/npm
 COPY --from=builder /usr/bin/npx /usr/bin/npx
 COPY --from=builder /root/.cache/prisma-python/binaries /root/.cache/prisma-python/binaries
 
-WORKDIR /app/autogpt_platform/backend
-
-# 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"
 
-# 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 ./
+RUN mkdir -p /app/autogpt_platform/autogpt_libs
+RUN mkdir -p /app/autogpt_platform/backend
 
-# Copy backend code + docs (for Copilot docs search)
-COPY 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/
+
+WORKDIR /app/autogpt_platform/backend
+
+FROM server_dependencies AS migrate
+
+# 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
+
+FROM server_dependencies AS server
+
+COPY autogpt_platform/backend /app/autogpt_platform/backend
 COPY docs /app/docs
 RUN poetry install --no-ansi --only-root
 
 ENV PORT=8000
 
 CMD ["poetry", "run", "rest"]
-
-# =============================== 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

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

@@ -27,12 +27,11 @@ class ChatConfig(BaseSettings):
     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_retries: int = Field(
+        default=3,
+        description="Max retries for fallback path (SDK handles retries internally)",
+    )
     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"
@@ -93,6 +92,26 @@ class ChatConfig(BaseSettings):
         description="Name of the prompt in Langfuse to fetch",
     )
 
+    # Claude Agent SDK Configuration
+    use_claude_agent_sdk: bool = Field(
+        default=True,
+        description="Use Claude Agent SDK for chat completions",
+    )
+    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 sub-agent Tasks the SDK can spawn per session.",
+    )
+
     # Extended thinking configuration for Claude models
     thinking_enabled: bool = Field(
         default=True,
@@ -138,6 +157,17 @@ class ChatConfig(BaseSettings):
             v = os.getenv("CHAT_INTERNAL_API_KEY")
         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
+
     # Prompt paths for different contexts
     PROMPT_PATHS: dict[str, str] = {
         "default": "prompts/chat_system.md",

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

@@ -334,9 +334,8 @@ async def _get_session_from_cache(session_id: str) -> ChatSession | 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]}"
+            f"[CACHE] Loaded session {session_id}: {len(session.messages)} messages, "
+            f"last_roles={[m.role for m in session.messages[-3:]]}"  # Last 3 roles
         )
         return session
     except Exception as e:
@@ -378,11 +377,9 @@ async def _get_session_from_db(session_id: str) -> ChatSession | None:
         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 []}"
+    logger.debug(
+        f"[DB] Loaded session {session_id}: {len(messages) if messages else 0} messages, "
+        f"roles={[m.role for m in messages[-3:]] if messages else []}"  # Last 3 roles
     )
 
     return ChatSession.from_db(prisma_session, messages)
@@ -433,10 +430,9 @@ async def _save_session_to_db(
                     "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}"
+        logger.debug(
+            f"[DB] Saving {len(new_messages)} messages to session {session.session_id}, "
+            f"roles={[m['role'] for m in messages_data]}"
         )
         await chat_db.add_chat_messages_batch(
             session_id=session.session_id,
@@ -476,7 +472,7 @@ 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:
@@ -493,7 +489,6 @@ async def get_chat_session(
     # Cache the session from DB
     try:
         await _cache_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}")
 
@@ -558,6 +553,40 @@ async def upsert_chat_session(
         return session
 
 
+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_chat_session_message_count(
+            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_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.
 
@@ -664,13 +693,19 @@ async def update_session_title(session_id: str, title: str) -> bool:
             logger.warning(f"Session {session_id} not found for title update")
             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_session(cached)
         except Exception as e:
-            logger.warning(f"Failed to invalidate cache for session {session_id}: {e}")
+            # Not critical - title will be correct on next full cache refresh
+            logger.warning(
+                f"Failed to update title in cache for session {session_id}: {e}"
+            )
 
         return True
     except Exception as e:

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

@@ -1,5 +1,6 @@
 """Chat API routes for chat session management and streaming via SSE."""
 
+import asyncio
 import logging
 import uuid as uuid_module
 from collections.abc import AsyncGenerator
@@ -11,20 +12,28 @@ from fastapi.responses import StreamingResponse
 from pydantic import BaseModel
 
 from backend.util.exceptions import NotFoundError
+from backend.util.feature_flag import Flag, is_feature_enabled
 
 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 .model import (
+    ChatMessage,
+    ChatSession,
+    append_and_save_message,
+    create_chat_session,
+    get_chat_session,
+    get_user_sessions,
+)
+from .response_model import StreamError, StreamFinish, StreamHeartbeat, StreamStart
+from .sdk import service as sdk_service
 from .tools.models import (
     AgentDetailsResponse,
     AgentOutputResponse,
     AgentPreviewResponse,
     AgentSavedResponse,
     AgentsFoundResponse,
-    BlockDetailsResponse,
     BlockListResponse,
     BlockOutputResponse,
     ClarificationNeededResponse,
@@ -41,6 +50,7 @@ from .tools.models import (
     SetupRequirementsResponse,
     UnderstandingUpdatedResponse,
 )
+from .tracking import track_user_message
 
 config = ChatConfig()
 
@@ -232,6 +242,10 @@ async def get_session(
     active_task, last_message_id = await stream_registry.get_active_task_for_session(
         session_id, user_id
     )
+    logger.info(
+        f"[GET_SESSION] session={session_id}, active_task={active_task is not None}, "
+        f"msg_count={len(messages)}, last_role={messages[-1].get('role') if messages else 'none'}"
+    )
     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
@@ -301,10 +315,9 @@ 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)
     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,
@@ -313,6 +326,25 @@ async def stream_chat_post(
         },
     )
 
+    # 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}")
+        session = 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
     task_id = str(uuid_module.uuid4())
     operation_id = str(uuid_module.uuid4())
@@ -328,7 +360,7 @@ async def stream_chat_post(
         operation_id=operation_id,
     )
     logger.info(
-        f"[TIMING] create_task completed in {(time.perf_counter() - task_create_start)*1000:.1f}ms",
+        f"[TIMING] create_task completed in {(time.perf_counter() - task_create_start) * 1000:.1f}ms",
         extra={
             "json_fields": {
                 **log_meta,
@@ -349,15 +381,47 @@ async def stream_chat_post(
         first_chunk_time, ttfc = None, None
         chunk_count = 0
         try:
-            async for chunk in chat_service.stream_chat_completion(
+            # Emit a start event with task_id for reconnection
+            start_chunk = StreamStart(messageId=task_id, taskId=task_id)
+            await stream_registry.publish_chunk(task_id, start_chunk)
+            logger.info(
+                f"[TIMING] StreamStart published at {(time_module.perf_counter() - gen_start_time) * 1000:.1f}ms",
+                extra={
+                    "json_fields": {
+                        **log_meta,
+                        "elapsed_ms": (time_module.perf_counter() - gen_start_time)
+                        * 1000,
+                    }
+                },
+            )
+
+            # Choose service based on LaunchDarkly flag (falls back to config default)
+            use_sdk = await is_feature_enabled(
+                Flag.COPILOT_SDK,
+                user_id or "anonymous",
+                default=config.use_claude_agent_sdk,
+            )
+            stream_fn = (
+                sdk_service.stream_chat_completion_sdk
+                if use_sdk
+                else chat_service.stream_chat_completion
+            )
+            logger.info(
+                f"[TIMING] Calling {'sdk' if use_sdk else 'standard'} stream_chat_completion",
+                extra={"json_fields": log_meta},
+            )
+            # Pass message=None since we already added it to the session above
+            async for chunk in stream_fn(
                 session_id,
-                request.message,
+                None,  # Message already in session
                 is_user_message=request.is_user_message,
                 user_id=user_id,
-                session=session,  # Pass pre-fetched session to avoid double-fetch
+                session=session,  # Pass session with message already added
                 context=request.context,
-                _task_id=task_id,  # Pass task_id so service emits start with taskId for reconnection
             ):
+                # Skip duplicate StreamStart — we already published one above
+                if isinstance(chunk, StreamStart):
+                    continue
                 chunk_count += 1
                 if first_chunk_time is None:
                     first_chunk_time = time_module.perf_counter()
@@ -378,7 +442,7 @@ async def stream_chat_post(
             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"[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={
@@ -405,6 +469,17 @@ async def stream_chat_post(
                     }
                 },
             )
+            # Publish a StreamError so the frontend can display an error message
+            try:
+                await stream_registry.publish_chunk(
+                    task_id,
+                    StreamError(
+                        errorText="An error occurred. Please try again.",
+                        code="stream_error",
+                    ),
+                )
+            except Exception:
+                pass  # Best-effort; mark_task_completed will publish StreamFinish
             await stream_registry.mark_task_completed(task_id, "failed")
 
     # Start the AI generation in a background task
@@ -507,8 +582,14 @@ 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(
@@ -752,8 +833,6 @@ async def stream_task(
         )
 
     async def event_generator() -> AsyncGenerator[str, None]:
-        import asyncio
-
         heartbeat_interval = 15.0  # Send heartbeat every 15 seconds
         try:
             while True:
@@ -972,7 +1051,6 @@ ToolResponseUnion = (
     | AgentSavedResponse
     | ClarificationNeededResponse
     | BlockListResponse
-    | BlockDetailsResponse
     | BlockOutputResponse
     | DocSearchResultsResponse
     | DocPageResponse

autogpt_platform/backend/backend/api/features/chat/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/api/features/chat/sdk/response_adapter.py

@@ -0,0 +1,198 @@
+"""Response adapter for converting Claude Agent SDK messages to Vercel AI SDK format.
+
+This module provides the adapter layer that converts streaming messages from
+the Claude Agent SDK into the Vercel AI SDK UI Stream Protocol format that
+the frontend expects.
+"""
+
+import json
+import logging
+import uuid
+
+from claude_agent_sdk import (
+    AssistantMessage,
+    Message,
+    ResultMessage,
+    SystemMessage,
+    TextBlock,
+    ToolResultBlock,
+    ToolUseBlock,
+    UserMessage,
+)
+
+from backend.api.features.chat.response_model import (
+    StreamBaseResponse,
+    StreamError,
+    StreamFinish,
+    StreamFinishStep,
+    StreamStart,
+    StreamStartStep,
+    StreamTextDelta,
+    StreamTextEnd,
+    StreamTextStart,
+    StreamToolInputAvailable,
+    StreamToolInputStart,
+    StreamToolOutputAvailable,
+)
+from backend.api.features.chat.sdk.tool_adapter import (
+    MCP_TOOL_PREFIX,
+    pop_pending_tool_output,
+)
+
+logger = logging.getLogger(__name__)
+
+
+class SDKResponseAdapter:
+    """Adapter for converting Claude Agent SDK messages to Vercel AI SDK format.
+
+    This class maintains state during a streaming session to properly track
+    text blocks, tool calls, and message lifecycle.
+    """
+
+    def __init__(self, message_id: str | None = None):
+        self.message_id = message_id or str(uuid.uuid4())
+        self.text_block_id = str(uuid.uuid4())
+        self.has_started_text = False
+        self.has_ended_text = False
+        self.current_tool_calls: dict[str, dict[str, str]] = {}
+        self.task_id: str | None = None
+        self.step_open = False
+
+    def set_task_id(self, task_id: str) -> None:
+        """Set the task ID for reconnection support."""
+        self.task_id = task_id
+
+    def convert_message(self, sdk_message: Message) -> list[StreamBaseResponse]:
+        """Convert a single SDK message to Vercel AI SDK format."""
+        responses: list[StreamBaseResponse] = []
+
+        if isinstance(sdk_message, SystemMessage):
+            if sdk_message.subtype == "init":
+                responses.append(
+                    StreamStart(messageId=self.message_id, taskId=self.task_id)
+                )
+                # Open the first step (matches non-SDK: StreamStart then StreamStartStep)
+                responses.append(StreamStartStep())
+                self.step_open = True
+
+        elif isinstance(sdk_message, AssistantMessage):
+            # After tool results, the SDK sends a new AssistantMessage for the
+            # next LLM turn. Open a new step if the previous one was closed.
+            if not self.step_open:
+                responses.append(StreamStartStep())
+                self.step_open = True
+
+            for block in sdk_message.content:
+                if isinstance(block, TextBlock):
+                    if block.text:
+                        self._ensure_text_started(responses)
+                        responses.append(
+                            StreamTextDelta(id=self.text_block_id, delta=block.text)
+                        )
+
+                elif isinstance(block, ToolUseBlock):
+                    self._end_text_if_open(responses)
+
+                    # Strip MCP prefix so frontend sees "find_block"
+                    # instead of "mcp__copilot__find_block".
+                    tool_name = block.name.removeprefix(MCP_TOOL_PREFIX)
+
+                    responses.append(
+                        StreamToolInputStart(toolCallId=block.id, toolName=tool_name)
+                    )
+                    responses.append(
+                        StreamToolInputAvailable(
+                            toolCallId=block.id,
+                            toolName=tool_name,
+                            input=block.input,
+                        )
+                    )
+                    self.current_tool_calls[block.id] = {"name": tool_name}
+
+        elif isinstance(sdk_message, UserMessage):
+            # UserMessage carries tool results back from tool execution.
+            content = sdk_message.content
+            blocks = content if isinstance(content, list) else []
+            for block in blocks:
+                if isinstance(block, ToolResultBlock) and block.tool_use_id:
+                    tool_info = self.current_tool_calls.get(block.tool_use_id, {})
+                    tool_name = tool_info.get("name", "unknown")
+
+                    # Prefer the stashed full output over the SDK's
+                    # (potentially truncated) ToolResultBlock content.
+                    # The SDK truncates large results, writing them to disk,
+                    # which breaks frontend widget parsing.
+                    output = pop_pending_tool_output(tool_name) or (
+                        _extract_tool_output(block.content)
+                    )
+
+                    responses.append(
+                        StreamToolOutputAvailable(
+                            toolCallId=block.tool_use_id,
+                            toolName=tool_name,
+                            output=output,
+                            success=not (block.is_error or False),
+                        )
+                    )
+
+            # Close the current step after tool results — the next
+            # AssistantMessage will open a new step for the continuation.
+            if self.step_open:
+                responses.append(StreamFinishStep())
+                self.step_open = False
+
+        elif isinstance(sdk_message, ResultMessage):
+            self._end_text_if_open(responses)
+            # Close the step before finishing.
+            if self.step_open:
+                responses.append(StreamFinishStep())
+                self.step_open = False
+
+            if sdk_message.subtype == "success":
+                responses.append(StreamFinish())
+            elif sdk_message.subtype in ("error", "error_during_execution"):
+                error_msg = getattr(sdk_message, "result", None) or "Unknown error"
+                responses.append(
+                    StreamError(errorText=str(error_msg), code="sdk_error")
+                )
+                responses.append(StreamFinish())
+
+        else:
+            logger.debug(f"Unhandled SDK message type: {type(sdk_message).__name__}")
+
+        return responses
+
+    def _ensure_text_started(self, responses: list[StreamBaseResponse]) -> None:
+        """Start (or restart) a text block if needed."""
+        if not self.has_started_text or self.has_ended_text:
+            if self.has_ended_text:
+                self.text_block_id = str(uuid.uuid4())
+                self.has_ended_text = False
+            responses.append(StreamTextStart(id=self.text_block_id))
+            self.has_started_text = True
+
+    def _end_text_if_open(self, responses: list[StreamBaseResponse]) -> None:
+        """End the current text block if one is open."""
+        if self.has_started_text and not self.has_ended_text:
+            responses.append(StreamTextEnd(id=self.text_block_id))
+            self.has_ended_text = True
+
+
+def _extract_tool_output(content: str | list[dict[str, str]] | None) -> str:
+    """Extract a string output from a ToolResultBlock's content field."""
+    if isinstance(content, str):
+        return content
+    if isinstance(content, list):
+        parts = [item.get("text", "") for item in content if item.get("type") == "text"]
+        if parts:
+            return "".join(parts)
+        try:
+            return json.dumps(content)
+        except (TypeError, ValueError):
+            return str(content)
+    if content is None:
+        return ""
+    try:
+        return json.dumps(content)
+    except (TypeError, ValueError):
+        return str(content)

autogpt_platform/backend/backend/api/features/chat/sdk/response_adapter_test.py

@@ -0,0 +1,366 @@
+"""Unit tests for the SDK response adapter."""
+
+from claude_agent_sdk import (
+    AssistantMessage,
+    ResultMessage,
+    SystemMessage,
+    TextBlock,
+    ToolResultBlock,
+    ToolUseBlock,
+    UserMessage,
+)
+
+from backend.api.features.chat.response_model import (
+    StreamBaseResponse,
+    StreamError,
+    StreamFinish,
+    StreamFinishStep,
+    StreamStart,
+    StreamStartStep,
+    StreamTextDelta,
+    StreamTextEnd,
+    StreamTextStart,
+    StreamToolInputAvailable,
+    StreamToolInputStart,
+    StreamToolOutputAvailable,
+)
+
+from .response_adapter import SDKResponseAdapter
+from .tool_adapter import MCP_TOOL_PREFIX
+
+
+def _adapter() -> SDKResponseAdapter:
+    a = SDKResponseAdapter(message_id="msg-1")
+    a.set_task_id("task-1")
+    return a
+
+
+# -- SystemMessage -----------------------------------------------------------
+
+
+def test_system_init_emits_start_and_step():
+    adapter = _adapter()
+    results = adapter.convert_message(SystemMessage(subtype="init", data={}))
+    assert len(results) == 2
+    assert isinstance(results[0], StreamStart)
+    assert results[0].messageId == "msg-1"
+    assert results[0].taskId == "task-1"
+    assert isinstance(results[1], StreamStartStep)
+
+
+def test_system_non_init_emits_nothing():
+    adapter = _adapter()
+    results = adapter.convert_message(SystemMessage(subtype="other", data={}))
+    assert results == []
+
+
+# -- AssistantMessage with TextBlock -----------------------------------------
+
+
+def test_text_block_emits_step_start_and_delta():
+    adapter = _adapter()
+    msg = AssistantMessage(content=[TextBlock(text="hello")], model="test")
+    results = adapter.convert_message(msg)
+    assert len(results) == 3
+    assert isinstance(results[0], StreamStartStep)
+    assert isinstance(results[1], StreamTextStart)
+    assert isinstance(results[2], StreamTextDelta)
+    assert results[2].delta == "hello"
+
+
+def test_empty_text_block_emits_only_step():
+    adapter = _adapter()
+    msg = AssistantMessage(content=[TextBlock(text="")], model="test")
+    results = adapter.convert_message(msg)
+    # Empty text skipped, but step still opens
+    assert len(results) == 1
+    assert isinstance(results[0], StreamStartStep)
+
+
+def test_multiple_text_deltas_reuse_block_id():
+    adapter = _adapter()
+    msg1 = AssistantMessage(content=[TextBlock(text="a")], model="test")
+    msg2 = AssistantMessage(content=[TextBlock(text="b")], model="test")
+    r1 = adapter.convert_message(msg1)
+    r2 = adapter.convert_message(msg2)
+    # First gets step+start+delta, second only delta (block & step already started)
+    assert len(r1) == 3
+    assert isinstance(r1[0], StreamStartStep)
+    assert isinstance(r1[1], StreamTextStart)
+    assert len(r2) == 1
+    assert isinstance(r2[0], StreamTextDelta)
+    assert r1[1].id == r2[0].id  # same block ID
+
+
+# -- AssistantMessage with ToolUseBlock --------------------------------------
+
+
+def test_tool_use_emits_input_start_and_available():
+    """Tool names arrive with MCP prefix and should be stripped for the frontend."""
+    adapter = _adapter()
+    msg = AssistantMessage(
+        content=[
+            ToolUseBlock(
+                id="tool-1",
+                name=f"{MCP_TOOL_PREFIX}find_agent",
+                input={"q": "x"},
+            )
+        ],
+        model="test",
+    )
+    results = adapter.convert_message(msg)
+    assert len(results) == 3
+    assert isinstance(results[0], StreamStartStep)
+    assert isinstance(results[1], StreamToolInputStart)
+    assert results[1].toolCallId == "tool-1"
+    assert results[1].toolName == "find_agent"  # prefix stripped
+    assert isinstance(results[2], StreamToolInputAvailable)
+    assert results[2].toolName == "find_agent"  # prefix stripped
+    assert results[2].input == {"q": "x"}
+
+
+def test_text_then_tool_ends_text_block():
+    adapter = _adapter()
+    text_msg = AssistantMessage(content=[TextBlock(text="thinking...")], model="test")
+    tool_msg = AssistantMessage(
+        content=[ToolUseBlock(id="t1", name=f"{MCP_TOOL_PREFIX}tool", input={})],
+        model="test",
+    )
+    adapter.convert_message(text_msg)  # opens step + text
+    results = adapter.convert_message(tool_msg)
+    # Step already open, so: TextEnd, ToolInputStart, ToolInputAvailable
+    assert len(results) == 3
+    assert isinstance(results[0], StreamTextEnd)
+    assert isinstance(results[1], StreamToolInputStart)
+
+
+# -- UserMessage with ToolResultBlock ----------------------------------------
+
+
+def test_tool_result_emits_output_and_finish_step():
+    adapter = _adapter()
+    # First register the tool call (opens step) — SDK sends prefixed name
+    tool_msg = AssistantMessage(
+        content=[ToolUseBlock(id="t1", name=f"{MCP_TOOL_PREFIX}find_agent", input={})],
+        model="test",
+    )
+    adapter.convert_message(tool_msg)
+
+    # Now send tool result
+    result_msg = UserMessage(
+        content=[ToolResultBlock(tool_use_id="t1", content="found 3 agents")]
+    )
+    results = adapter.convert_message(result_msg)
+    assert len(results) == 2
+    assert isinstance(results[0], StreamToolOutputAvailable)
+    assert results[0].toolCallId == "t1"
+    assert results[0].toolName == "find_agent"  # prefix stripped
+    assert results[0].output == "found 3 agents"
+    assert results[0].success is True
+    assert isinstance(results[1], StreamFinishStep)
+
+
+def test_tool_result_error():
+    adapter = _adapter()
+    adapter.convert_message(
+        AssistantMessage(
+            content=[
+                ToolUseBlock(id="t1", name=f"{MCP_TOOL_PREFIX}run_agent", input={})
+            ],
+            model="test",
+        )
+    )
+    result_msg = UserMessage(
+        content=[ToolResultBlock(tool_use_id="t1", content="timeout", is_error=True)]
+    )
+    results = adapter.convert_message(result_msg)
+    assert isinstance(results[0], StreamToolOutputAvailable)
+    assert results[0].success is False
+    assert isinstance(results[1], StreamFinishStep)
+
+
+def test_tool_result_list_content():
+    adapter = _adapter()
+    adapter.convert_message(
+        AssistantMessage(
+            content=[ToolUseBlock(id="t1", name=f"{MCP_TOOL_PREFIX}tool", input={})],
+            model="test",
+        )
+    )
+    result_msg = UserMessage(
+        content=[
+            ToolResultBlock(
+                tool_use_id="t1",
+                content=[
+                    {"type": "text", "text": "line1"},
+                    {"type": "text", "text": "line2"},
+                ],
+            )
+        ]
+    )
+    results = adapter.convert_message(result_msg)
+    assert isinstance(results[0], StreamToolOutputAvailable)
+    assert results[0].output == "line1line2"
+    assert isinstance(results[1], StreamFinishStep)
+
+
+def test_string_user_message_ignored():
+    """A plain string UserMessage (not tool results) produces no output."""
+    adapter = _adapter()
+    results = adapter.convert_message(UserMessage(content="hello"))
+    assert results == []
+
+
+# -- ResultMessage -----------------------------------------------------------
+
+
+def test_result_success_emits_finish_step_and_finish():
+    adapter = _adapter()
+    # Start some text first (opens step)
+    adapter.convert_message(
+        AssistantMessage(content=[TextBlock(text="done")], model="test")
+    )
+    msg = ResultMessage(
+        subtype="success",
+        duration_ms=100,
+        duration_api_ms=50,
+        is_error=False,
+        num_turns=1,
+        session_id="s1",
+    )
+    results = adapter.convert_message(msg)
+    # TextEnd + FinishStep + StreamFinish
+    assert len(results) == 3
+    assert isinstance(results[0], StreamTextEnd)
+    assert isinstance(results[1], StreamFinishStep)
+    assert isinstance(results[2], StreamFinish)
+
+
+def test_result_error_emits_error_and_finish():
+    adapter = _adapter()
+    msg = ResultMessage(
+        subtype="error",
+        duration_ms=100,
+        duration_api_ms=50,
+        is_error=True,
+        num_turns=0,
+        session_id="s1",
+        result="API rate limited",
+    )
+    results = adapter.convert_message(msg)
+    # No step was open, so no FinishStep — just Error + Finish
+    assert len(results) == 2
+    assert isinstance(results[0], StreamError)
+    assert "API rate limited" in results[0].errorText
+    assert isinstance(results[1], StreamFinish)
+
+
+# -- Text after tools (new block ID) ----------------------------------------
+
+
+def test_text_after_tool_gets_new_block_id():
+    adapter = _adapter()
+    # Text -> Tool -> ToolResult -> Text should get a new text block ID and step
+    adapter.convert_message(
+        AssistantMessage(content=[TextBlock(text="before")], model="test")
+    )
+    adapter.convert_message(
+        AssistantMessage(
+            content=[ToolUseBlock(id="t1", name=f"{MCP_TOOL_PREFIX}tool", input={})],
+            model="test",
+        )
+    )
+    # Send tool result (closes step)
+    adapter.convert_message(
+        UserMessage(content=[ToolResultBlock(tool_use_id="t1", content="ok")])
+    )
+    results = adapter.convert_message(
+        AssistantMessage(content=[TextBlock(text="after")], model="test")
+    )
+    # Should get StreamStartStep (new step) + StreamTextStart (new block) + StreamTextDelta
+    assert len(results) == 3
+    assert isinstance(results[0], StreamStartStep)
+    assert isinstance(results[1], StreamTextStart)
+    assert isinstance(results[2], StreamTextDelta)
+    assert results[2].delta == "after"
+
+
+# -- Full conversation flow --------------------------------------------------
+
+
+def test_full_conversation_flow():
+    """Simulate a complete conversation: init -> text -> tool -> result -> text -> finish."""
+    adapter = _adapter()
+    all_responses: list[StreamBaseResponse] = []
+
+    # 1. Init
+    all_responses.extend(
+        adapter.convert_message(SystemMessage(subtype="init", data={}))
+    )
+    # 2. Assistant text
+    all_responses.extend(
+        adapter.convert_message(
+            AssistantMessage(content=[TextBlock(text="Let me search")], model="test")
+        )
+    )
+    # 3. Tool use
+    all_responses.extend(
+        adapter.convert_message(
+            AssistantMessage(
+                content=[
+                    ToolUseBlock(
+                        id="t1",
+                        name=f"{MCP_TOOL_PREFIX}find_agent",
+                        input={"query": "email"},
+                    )
+                ],
+                model="test",
+            )
+        )
+    )
+    # 4. Tool result
+    all_responses.extend(
+        adapter.convert_message(
+            UserMessage(
+                content=[ToolResultBlock(tool_use_id="t1", content="Found 2 agents")]
+            )
+        )
+    )
+    # 5. More text
+    all_responses.extend(
+        adapter.convert_message(
+            AssistantMessage(content=[TextBlock(text="I found 2")], model="test")
+        )
+    )
+    # 6. Result
+    all_responses.extend(
+        adapter.convert_message(
+            ResultMessage(
+                subtype="success",
+                duration_ms=500,
+                duration_api_ms=400,
+                is_error=False,
+                num_turns=2,
+                session_id="s1",
+            )
+        )
+    )
+
+    types = [type(r).__name__ for r in all_responses]
+    assert types == [
+        "StreamStart",
+        "StreamStartStep",  # step 1: text + tool call
+        "StreamTextStart",
+        "StreamTextDelta",  # "Let me search"
+        "StreamTextEnd",  # closed before tool
+        "StreamToolInputStart",
+        "StreamToolInputAvailable",
+        "StreamToolOutputAvailable",  # tool result
+        "StreamFinishStep",  # step 1 closed after tool result
+        "StreamStartStep",  # step 2: continuation text
+        "StreamTextStart",  # new block after tool
+        "StreamTextDelta",  # "I found 2"
+        "StreamTextEnd",  # closed by result
+        "StreamFinishStep",  # step 2 closed
+        "StreamFinish",
+    ]

autogpt_platform/backend/backend/api/features/chat/sdk/security_hooks.py

@@ -0,0 +1,299 @@
+"""Security hooks for Claude Agent SDK integration.
+
+This module provides security hooks that validate tool calls before execution,
+ensuring multi-user isolation and preventing unauthorized operations.
+"""
+
+import json
+import logging
+import os
+import re
+from typing import Any, cast
+
+from backend.api.features.chat.sdk.tool_adapter import MCP_TOOL_PREFIX
+
+logger = logging.getLogger(__name__)
+
+# Tools that are blocked entirely (CLI/system access).
+# "Bash" (capital) is the SDK built-in — it's NOT in allowed_tools but blocked
+# here as defence-in-depth.  The agent uses mcp__copilot__bash_exec instead,
+# which has kernel-level network isolation (unshare --net).
+BLOCKED_TOOLS = {
+    "Bash",
+    "bash",
+    "shell",
+    "exec",
+    "terminal",
+    "command",
+}
+
+# Tools allowed only when their path argument stays within the SDK workspace.
+# The SDK uses these to handle oversized tool results (writes to tool-results/
+# files, then reads them back) and for workspace file operations.
+WORKSPACE_SCOPED_TOOLS = {"Read", "Write", "Edit", "Glob", "Grep"}
+
+# Dangerous patterns in tool inputs
+DANGEROUS_PATTERNS = [
+    r"sudo",
+    r"rm\s+-rf",
+    r"dd\s+if=",
+    r"/etc/passwd",
+    r"/etc/shadow",
+    r"chmod\s+777",
+    r"curl\s+.*\|.*sh",
+    r"wget\s+.*\|.*sh",
+    r"eval\s*\(",
+    r"exec\s*\(",
+    r"__import__",
+    r"os\.system",
+    r"subprocess",
+]
+
+
+def _deny(reason: str) -> dict[str, Any]:
+    """Return a hook denial response."""
+    return {
+        "hookSpecificOutput": {
+            "hookEventName": "PreToolUse",
+            "permissionDecision": "deny",
+            "permissionDecisionReason": reason,
+        }
+    }
+
+
+def _validate_workspace_path(
+    tool_name: str, tool_input: dict[str, Any], sdk_cwd: str | None
+) -> dict[str, Any]:
+    """Validate that a workspace-scoped tool only accesses allowed paths.
+
+    Allowed directories:
+    - The SDK working directory (``/tmp/copilot-<session>/``)
+    - The SDK tool-results directory (``~/.claude/projects/…/tool-results/``)
+    """
+    path = tool_input.get("file_path") or tool_input.get("path") or ""
+    if not path:
+        # Glob/Grep without a path default to cwd which is already sandboxed
+        return {}
+
+    # Resolve relative paths against sdk_cwd (the SDK sets cwd so the LLM
+    # naturally uses relative paths like "test.txt" instead of absolute ones).
+    # Tilde paths (~/) are home-dir references, not relative — expand first.
+    if path.startswith("~"):
+        resolved = os.path.normpath(os.path.expanduser(path))
+    elif not os.path.isabs(path) and sdk_cwd:
+        resolved = os.path.normpath(os.path.join(sdk_cwd, path))
+    else:
+        resolved = os.path.normpath(path)
+
+    # Allow access within the SDK working directory
+    if sdk_cwd:
+        norm_cwd = os.path.normpath(sdk_cwd)
+        if resolved.startswith(norm_cwd + os.sep) or resolved == norm_cwd:
+            return {}
+
+    # Allow access to ~/.claude/projects/*/tool-results/ (big tool results)
+    claude_dir = os.path.normpath(os.path.expanduser("~/.claude/projects"))
+    if resolved.startswith(claude_dir + os.sep) and "tool-results" in resolved:
+        return {}
+
+    logger.warning(
+        f"Blocked {tool_name} outside workspace: {path} (resolved={resolved})"
+    )
+    workspace_hint = f" Allowed workspace: {sdk_cwd}" if sdk_cwd else ""
+    return _deny(
+        f"[SECURITY] Tool '{tool_name}' can only access files within the workspace "
+        f"directory.{workspace_hint} "
+        "This is enforced by the platform and cannot be bypassed."
+    )
+
+
+def _validate_tool_access(
+    tool_name: str, tool_input: dict[str, Any], sdk_cwd: str | None = None
+) -> dict[str, Any]:
+    """Validate that a tool call is allowed.
+
+    Returns:
+        Empty dict to allow, or dict with hookSpecificOutput to deny
+    """
+    # Block forbidden tools
+    if tool_name in BLOCKED_TOOLS:
+        logger.warning(f"Blocked tool access attempt: {tool_name}")
+        return _deny(
+            f"[SECURITY] Tool '{tool_name}' is blocked for security. "
+            "This is enforced by the platform and cannot be bypassed. "
+            "Use the CoPilot-specific MCP tools instead."
+        )
+
+    # Workspace-scoped tools: allowed only within the SDK workspace directory
+    if tool_name in WORKSPACE_SCOPED_TOOLS:
+        return _validate_workspace_path(tool_name, tool_input, sdk_cwd)
+
+    # Check for dangerous patterns in tool input
+    # Use json.dumps for predictable format (str() produces Python repr)
+    input_str = json.dumps(tool_input) if tool_input else ""
+
+    for pattern in DANGEROUS_PATTERNS:
+        if re.search(pattern, input_str, re.IGNORECASE):
+            logger.warning(
+                f"Blocked dangerous pattern in tool input: {pattern} in {tool_name}"
+            )
+            return _deny(
+                "[SECURITY] Input contains a blocked pattern. "
+                "This is enforced by the platform and cannot be bypassed."
+            )
+
+    return {}
+
+
+def _validate_user_isolation(
+    tool_name: str, tool_input: dict[str, Any], user_id: str | None
+) -> dict[str, Any]:
+    """Validate that tool calls respect user isolation."""
+    # For workspace file tools, ensure path doesn't escape
+    if "workspace" in tool_name.lower():
+        path = tool_input.get("path", "") or tool_input.get("file_path", "")
+        if path:
+            # Check for path traversal
+            if ".." in path or path.startswith("/"):
+                logger.warning(
+                    f"Blocked path traversal attempt: {path} by user {user_id}"
+                )
+                return {
+                    "hookSpecificOutput": {
+                        "hookEventName": "PreToolUse",
+                        "permissionDecision": "deny",
+                        "permissionDecisionReason": "Path traversal not allowed",
+                    }
+                }
+
+    return {}
+
+
+def create_security_hooks(
+    user_id: str | None,
+    sdk_cwd: str | None = None,
+    max_subtasks: int = 3,
+) -> dict[str, Any]:
+    """Create the security hooks configuration for Claude Agent SDK.
+
+    Includes security validation and observability hooks:
+    - PreToolUse: Security validation before tool execution
+    - PostToolUse: Log successful tool executions
+    - PostToolUseFailure: Log and handle failed tool executions
+    - PreCompact: Log context compaction events (SDK handles compaction automatically)
+
+    Args:
+        user_id: Current user ID for isolation validation
+        sdk_cwd: SDK working directory for workspace-scoped tool validation
+        max_subtasks: Maximum Task (sub-agent) spawns allowed per session
+
+    Returns:
+        Hooks configuration dict for ClaudeAgentOptions
+    """
+    try:
+        from claude_agent_sdk import HookMatcher
+        from claude_agent_sdk.types import HookContext, HookInput, SyncHookJSONOutput
+
+        # Per-session counter for Task sub-agent spawns
+        task_spawn_count = 0
+
+        async def pre_tool_use_hook(
+            input_data: HookInput,
+            tool_use_id: str | None,
+            context: HookContext,
+        ) -> SyncHookJSONOutput:
+            """Combined pre-tool-use validation hook."""
+            nonlocal task_spawn_count
+            _ = context  # unused but required by signature
+            tool_name = cast(str, input_data.get("tool_name", ""))
+            tool_input = cast(dict[str, Any], input_data.get("tool_input", {}))
+
+            # Rate-limit Task (sub-agent) spawns per session
+            if tool_name == "Task":
+                task_spawn_count += 1
+                if task_spawn_count > max_subtasks:
+                    logger.warning(
+                        f"[SDK] Task limit reached ({max_subtasks}), user={user_id}"
+                    )
+                    return cast(
+                        SyncHookJSONOutput,
+                        _deny(
+                            f"Maximum {max_subtasks} sub-tasks per session. "
+                            "Please continue in the main conversation."
+                        ),
+                    )
+
+            # Strip MCP prefix for consistent validation
+            is_copilot_tool = tool_name.startswith(MCP_TOOL_PREFIX)
+            clean_name = tool_name.removeprefix(MCP_TOOL_PREFIX)
+
+            # Only block non-CoPilot tools; our MCP-registered tools
+            # (including Read for oversized results) are already sandboxed.
+            if not is_copilot_tool:
+                result = _validate_tool_access(clean_name, tool_input, sdk_cwd)
+                if result:
+                    return cast(SyncHookJSONOutput, result)
+
+            # Validate user isolation
+            result = _validate_user_isolation(clean_name, tool_input, user_id)
+            if result:
+                return cast(SyncHookJSONOutput, result)
+
+            logger.debug(f"[SDK] Tool start: {tool_name}, user={user_id}")
+            return cast(SyncHookJSONOutput, {})
+
+        async def post_tool_use_hook(
+            input_data: HookInput,
+            tool_use_id: str | None,
+            context: HookContext,
+        ) -> SyncHookJSONOutput:
+            """Log successful tool executions for observability."""
+            _ = context
+            tool_name = cast(str, input_data.get("tool_name", ""))
+            logger.debug(f"[SDK] Tool success: {tool_name}, tool_use_id={tool_use_id}")
+            return cast(SyncHookJSONOutput, {})
+
+        async def post_tool_failure_hook(
+            input_data: HookInput,
+            tool_use_id: str | None,
+            context: HookContext,
+        ) -> SyncHookJSONOutput:
+            """Log failed tool executions for debugging."""
+            _ = context
+            tool_name = cast(str, input_data.get("tool_name", ""))
+            error = input_data.get("error", "Unknown error")
+            logger.warning(
+                f"[SDK] Tool failed: {tool_name}, error={error}, "
+                f"user={user_id}, tool_use_id={tool_use_id}"
+            )
+            return cast(SyncHookJSONOutput, {})
+
+        async def pre_compact_hook(
+            input_data: HookInput,
+            tool_use_id: str | None,
+            context: HookContext,
+        ) -> SyncHookJSONOutput:
+            """Log when SDK triggers context compaction.
+
+            The SDK automatically compacts conversation history when it grows too large.
+            This hook provides visibility into when compaction happens.
+            """
+            _ = context, tool_use_id
+            trigger = input_data.get("trigger", "auto")
+            logger.info(
+                f"[SDK] Context compaction triggered: {trigger}, user={user_id}"
+            )
+            return cast(SyncHookJSONOutput, {})
+
+        return {
+            "PreToolUse": [HookMatcher(matcher="*", hooks=[pre_tool_use_hook])],
+            "PostToolUse": [HookMatcher(matcher="*", hooks=[post_tool_use_hook])],
+            "PostToolUseFailure": [
+                HookMatcher(matcher="*", hooks=[post_tool_failure_hook])
+            ],
+            "PreCompact": [HookMatcher(matcher="*", hooks=[pre_compact_hook])],
+        }
+    except ImportError:
+        # Fallback for when SDK isn't available - return empty hooks
+        logger.warning("claude-agent-sdk not available, security hooks disabled")
+        return {}

autogpt_platform/backend/backend/api/features/chat/sdk/security_hooks_test.py

@@ -0,0 +1,165 @@
+"""Unit tests for SDK security hooks."""
+
+import os
+
+from .security_hooks import _validate_tool_access, _validate_user_isolation
+
+SDK_CWD = "/tmp/copilot-abc123"
+
+
+def _is_denied(result: dict) -> bool:
+    hook = result.get("hookSpecificOutput", {})
+    return hook.get("permissionDecision") == "deny"
+
+
+# -- Blocked tools -----------------------------------------------------------
+
+
+def test_blocked_tools_denied():
+    for tool in ("bash", "shell", "exec", "terminal", "command"):
+        result = _validate_tool_access(tool, {})
+        assert _is_denied(result), f"{tool} should be blocked"
+
+
+def test_unknown_tool_allowed():
+    result = _validate_tool_access("SomeCustomTool", {})
+    assert result == {}
+
+
+# -- Workspace-scoped tools --------------------------------------------------
+
+
+def test_read_within_workspace_allowed():
+    result = _validate_tool_access(
+        "Read", {"file_path": f"{SDK_CWD}/file.txt"}, sdk_cwd=SDK_CWD
+    )
+    assert result == {}
+
+
+def test_write_within_workspace_allowed():
+    result = _validate_tool_access(
+        "Write", {"file_path": f"{SDK_CWD}/output.json"}, sdk_cwd=SDK_CWD
+    )
+    assert result == {}
+
+
+def test_edit_within_workspace_allowed():
+    result = _validate_tool_access(
+        "Edit", {"file_path": f"{SDK_CWD}/src/main.py"}, sdk_cwd=SDK_CWD
+    )
+    assert result == {}
+
+
+def test_glob_within_workspace_allowed():
+    result = _validate_tool_access("Glob", {"path": f"{SDK_CWD}/src"}, sdk_cwd=SDK_CWD)
+    assert result == {}
+
+
+def test_grep_within_workspace_allowed():
+    result = _validate_tool_access("Grep", {"path": f"{SDK_CWD}/src"}, sdk_cwd=SDK_CWD)
+    assert result == {}
+
+
+def test_read_outside_workspace_denied():
+    result = _validate_tool_access(
+        "Read", {"file_path": "/etc/passwd"}, sdk_cwd=SDK_CWD
+    )
+    assert _is_denied(result)
+
+
+def test_write_outside_workspace_denied():
+    result = _validate_tool_access(
+        "Write", {"file_path": "/home/user/secrets.txt"}, sdk_cwd=SDK_CWD
+    )
+    assert _is_denied(result)
+
+
+def test_traversal_attack_denied():
+    result = _validate_tool_access(
+        "Read",
+        {"file_path": f"{SDK_CWD}/../../etc/passwd"},
+        sdk_cwd=SDK_CWD,
+    )
+    assert _is_denied(result)
+
+
+def test_no_path_allowed():
+    """Glob/Grep without a path argument defaults to cwd — should pass."""
+    result = _validate_tool_access("Glob", {}, sdk_cwd=SDK_CWD)
+    assert result == {}
+
+
+def test_read_no_cwd_denies_absolute():
+    """If no sdk_cwd is set, absolute paths are denied."""
+    result = _validate_tool_access("Read", {"file_path": "/tmp/anything"})
+    assert _is_denied(result)
+
+
+# -- Tool-results directory --------------------------------------------------
+
+
+def test_read_tool_results_allowed():
+    home = os.path.expanduser("~")
+    path = f"{home}/.claude/projects/-tmp-copilot-abc123/tool-results/12345.txt"
+    result = _validate_tool_access("Read", {"file_path": path}, sdk_cwd=SDK_CWD)
+    assert result == {}
+
+
+def test_read_claude_projects_without_tool_results_denied():
+    home = os.path.expanduser("~")
+    path = f"{home}/.claude/projects/-tmp-copilot-abc123/settings.json"
+    result = _validate_tool_access("Read", {"file_path": path}, sdk_cwd=SDK_CWD)
+    assert _is_denied(result)
+
+
+# -- Built-in Bash is blocked (use bash_exec MCP tool instead) ---------------
+
+
+def test_bash_builtin_always_blocked():
+    """SDK built-in Bash is blocked — bash_exec MCP tool with bubblewrap is used instead."""
+    result = _validate_tool_access("Bash", {"command": "echo hello"}, sdk_cwd=SDK_CWD)
+    assert _is_denied(result)
+
+
+# -- Dangerous patterns ------------------------------------------------------
+
+
+def test_dangerous_pattern_blocked():
+    result = _validate_tool_access("SomeTool", {"cmd": "sudo rm -rf /"})
+    assert _is_denied(result)
+
+
+def test_subprocess_pattern_blocked():
+    result = _validate_tool_access("SomeTool", {"code": "subprocess.run(...)"})
+    assert _is_denied(result)
+
+
+# -- User isolation ----------------------------------------------------------
+
+
+def test_workspace_path_traversal_blocked():
+    result = _validate_user_isolation(
+        "workspace_read", {"path": "../../../etc/shadow"}, user_id="user-1"
+    )
+    assert _is_denied(result)
+
+
+def test_workspace_absolute_path_blocked():
+    result = _validate_user_isolation(
+        "workspace_read", {"path": "/etc/passwd"}, user_id="user-1"
+    )
+    assert _is_denied(result)
+
+
+def test_workspace_normal_path_allowed():
+    result = _validate_user_isolation(
+        "workspace_read", {"path": "src/main.py"}, user_id="user-1"
+    )
+    assert result == {}
+
+
+def test_non_workspace_tool_passes_isolation():
+    result = _validate_user_isolation(
+        "find_agent", {"query": "email"}, user_id="user-1"
+    )
+    assert result == {}

autogpt_platform/backend/backend/api/features/chat/sdk/service.py

@@ -0,0 +1,668 @@
+"""Claude Agent SDK service layer for CoPilot chat completions."""
+
+import asyncio
+import json
+import logging
+import os
+import uuid
+from collections.abc import AsyncGenerator
+from typing import Any
+
+from backend.util.exceptions import NotFoundError
+
+from .. import stream_registry
+from ..config import ChatConfig
+from ..model import (
+    ChatMessage,
+    ChatSession,
+    get_chat_session,
+    update_session_title,
+    upsert_chat_session,
+)
+from ..response_model import (
+    StreamBaseResponse,
+    StreamError,
+    StreamFinish,
+    StreamStart,
+    StreamTextDelta,
+    StreamToolInputAvailable,
+    StreamToolOutputAvailable,
+)
+from ..service import (
+    _build_system_prompt,
+    _execute_long_running_tool_with_streaming,
+    _generate_session_title,
+)
+from ..tools.models import OperationPendingResponse, OperationStartedResponse
+from ..tools.sandbox import WORKSPACE_PREFIX, make_session_path
+from ..tracking import track_user_message
+from .response_adapter import SDKResponseAdapter
+from .security_hooks import create_security_hooks
+from .tool_adapter import (
+    COPILOT_TOOL_NAMES,
+    LongRunningCallback,
+    create_copilot_mcp_server,
+    set_execution_context,
+)
+
+logger = logging.getLogger(__name__)
+config = ChatConfig()
+
+# Set to hold background tasks to prevent garbage collection
+_background_tasks: set[asyncio.Task[Any]] = set()
+
+
+_SDK_CWD_PREFIX = WORKSPACE_PREFIX
+
+# Appended to the system prompt to inform the agent about available tools.
+# The SDK built-in Bash is NOT available — use mcp__copilot__bash_exec instead,
+# which has kernel-level network isolation (unshare --net).
+_SDK_TOOL_SUPPLEMENT = """
+
+## Tool notes
+
+- The SDK built-in Bash tool is NOT available.  Use the `bash_exec` MCP tool
+  for shell commands — it runs in a network-isolated sandbox.
+- **Shared workspace**: The SDK Read/Write tools and `bash_exec` share the
+  same working directory. Files created by one are readable by the other.
+  These files are **ephemeral** — they exist only for the current session.
+- **Persistent storage**: Use `write_workspace_file` / `read_workspace_file`
+  for files that should persist across sessions (stored in cloud storage).
+- Long-running tools (create_agent, edit_agent, etc.) are handled
+  asynchronously.  You will receive an immediate response; the actual result
+  is delivered to the user via a background stream.
+"""
+
+
+def _build_long_running_callback(user_id: str | None) -> LongRunningCallback:
+    """Build a callback that delegates long-running tools to the non-SDK infrastructure.
+
+    Long-running tools (create_agent, edit_agent, etc.) are delegated to the
+    existing background infrastructure: stream_registry (Redis Streams),
+    database persistence, and SSE reconnection.  This means results survive
+    page refreshes / pod restarts, and the frontend shows the proper loading
+    widget with progress updates.
+
+    The returned callback matches the ``LongRunningCallback`` signature:
+    ``(tool_name, args, session) -> MCP response dict``.
+    """
+
+    async def _callback(
+        tool_name: str, args: dict[str, Any], session: ChatSession
+    ) -> dict[str, Any]:
+        operation_id = str(uuid.uuid4())
+        task_id = str(uuid.uuid4())
+        tool_call_id = f"sdk-{uuid.uuid4().hex[:12]}"
+        session_id = session.session_id
+
+        # --- Build user-friendly messages (matches non-SDK service) ---
+        if tool_name == "create_agent":
+            desc = args.get("description", "")
+            desc_preview = (desc[:100] + "...") if len(desc) > 100 else desc
+            pending_msg = (
+                f"Creating your agent: {desc_preview}"
+                if desc_preview
+                else "Creating agent... This may take a few minutes."
+            )
+            started_msg = (
+                "Agent creation started. You can close this tab - "
+                "check your library in a few minutes."
+            )
+        elif tool_name == "edit_agent":
+            changes = args.get("changes", "")
+            changes_preview = (changes[:100] + "...") if len(changes) > 100 else changes
+            pending_msg = (
+                f"Editing agent: {changes_preview}"
+                if changes_preview
+                else "Editing agent... This may take a few minutes."
+            )
+            started_msg = (
+                "Agent edit started. You can close this tab - "
+                "check your library in a few minutes."
+            )
+        else:
+            pending_msg = f"Running {tool_name}... This may take a few minutes."
+            started_msg = (
+                f"{tool_name} started. You can close this tab - "
+                "check back in a few minutes."
+            )
+
+        # --- Register task in Redis for SSE reconnection ---
+        await stream_registry.create_task(
+            task_id=task_id,
+            session_id=session_id,
+            user_id=user_id,
+            tool_call_id=tool_call_id,
+            tool_name=tool_name,
+            operation_id=operation_id,
+        )
+
+        # --- Save OperationPendingResponse to chat history ---
+        pending_message = ChatMessage(
+            role="tool",
+            content=OperationPendingResponse(
+                message=pending_msg,
+                operation_id=operation_id,
+                tool_name=tool_name,
+            ).model_dump_json(),
+            tool_call_id=tool_call_id,
+        )
+        session.messages.append(pending_message)
+        await upsert_chat_session(session)
+
+        # --- Spawn background task (reuses non-SDK infrastructure) ---
+        bg_task = asyncio.create_task(
+            _execute_long_running_tool_with_streaming(
+                tool_name=tool_name,
+                parameters=args,
+                tool_call_id=tool_call_id,
+                operation_id=operation_id,
+                task_id=task_id,
+                session_id=session_id,
+                user_id=user_id,
+            )
+        )
+        _background_tasks.add(bg_task)
+        bg_task.add_done_callback(_background_tasks.discard)
+        await stream_registry.set_task_asyncio_task(task_id, bg_task)
+
+        logger.info(
+            f"[SDK] Long-running tool {tool_name} delegated to background "
+            f"(operation_id={operation_id}, task_id={task_id})"
+        )
+
+        # --- Return OperationStartedResponse as MCP tool result ---
+        # This flows through SDK → response adapter → frontend, triggering
+        # the loading widget with SSE reconnection support.
+        started_json = OperationStartedResponse(
+            message=started_msg,
+            operation_id=operation_id,
+            tool_name=tool_name,
+            task_id=task_id,
+        ).model_dump_json()
+
+        return {
+            "content": [{"type": "text", "text": started_json}],
+            "isError": False,
+        }
+
+    return _callback
+
+
+def _resolve_sdk_model() -> str | None:
+    """Resolve the model name for the Claude Agent SDK CLI.
+
+    Uses ``config.claude_agent_model`` if set, otherwise derives from
+    ``config.model`` by stripping the OpenRouter provider prefix (e.g.,
+    ``"anthropic/claude-opus-4.6"`` → ``"claude-opus-4.6"``).
+    """
+    if config.claude_agent_model:
+        return config.claude_agent_model
+    model = config.model
+    if "/" in model:
+        return model.split("/", 1)[1]
+    return model
+
+
+def _build_sdk_env() -> dict[str, str]:
+    """Build env vars for the SDK CLI process.
+
+    Routes API calls through OpenRouter (or a custom base_url) using
+    the same ``config.api_key`` / ``config.base_url`` as the non-SDK path.
+    This gives per-call token and cost tracking on the OpenRouter dashboard.
+
+    Only overrides ``ANTHROPIC_API_KEY`` when a valid proxy URL and auth
+    token are both present — otherwise returns an empty dict so the SDK
+    falls back to its default credentials.
+    """
+    env: dict[str, str] = {}
+    if config.api_key and config.base_url:
+        # Strip /v1 suffix — SDK expects the base URL without a version path
+        base = config.base_url.rstrip("/")
+        if base.endswith("/v1"):
+            base = base[:-3]
+        if not base or not base.startswith("http"):
+            # Invalid base_url — don't override SDK defaults
+            return env
+        env["ANTHROPIC_BASE_URL"] = base
+        env["ANTHROPIC_AUTH_TOKEN"] = config.api_key
+        # Must be explicitly empty so the CLI uses AUTH_TOKEN instead
+        env["ANTHROPIC_API_KEY"] = ""
+    return env
+
+
+def _make_sdk_cwd(session_id: str) -> str:
+    """Create a safe, session-specific working directory path.
+
+    Delegates to :func:`~backend.api.features.chat.tools.sandbox.make_session_path`
+    (single source of truth for path sanitization) and adds a defence-in-depth
+    assertion.
+    """
+    cwd = make_session_path(session_id)
+    # Defence-in-depth: normpath + startswith is a CodeQL-recognised sanitizer
+    cwd = os.path.normpath(cwd)
+    if not cwd.startswith(_SDK_CWD_PREFIX):
+        raise ValueError(f"SDK cwd escaped prefix: {cwd}")
+    return cwd
+
+
+def _cleanup_sdk_tool_results(cwd: str) -> None:
+    """Remove SDK tool-result files for a specific session working directory.
+
+    The SDK creates tool-result files under ~/.claude/projects/<encoded-cwd>/tool-results/.
+    We clean only the specific cwd's results to avoid race conditions between
+    concurrent sessions.
+
+    Security: cwd MUST be created by _make_sdk_cwd() which sanitizes session_id.
+    """
+    import shutil
+
+    # Security check 1: Validate cwd is under the expected prefix
+    normalized = os.path.normpath(cwd)
+    if not normalized.startswith(_SDK_CWD_PREFIX):
+        logger.warning(f"[SDK] Rejecting cleanup for invalid path: {cwd}")
+        return
+
+    # Security check 2: Ensure no path traversal in the normalized path
+    if ".." in normalized:
+        logger.warning(f"[SDK] Rejecting cleanup for traversal attempt: {cwd}")
+        return
+
+    # SDK encodes the cwd path by replacing '/' with '-'
+    encoded_cwd = normalized.replace("/", "-")
+
+    # Construct the project directory path (known-safe home expansion)
+    claude_projects = os.path.expanduser("~/.claude/projects")
+    project_dir = os.path.join(claude_projects, encoded_cwd)
+
+    # Security check 3: Validate project_dir is under ~/.claude/projects
+    project_dir = os.path.normpath(project_dir)
+    if not project_dir.startswith(claude_projects):
+        logger.warning(
+            f"[SDK] Rejecting cleanup for escaped project path: {project_dir}"
+        )
+        return
+
+    results_dir = os.path.join(project_dir, "tool-results")
+    if os.path.isdir(results_dir):
+        for filename in os.listdir(results_dir):
+            file_path = os.path.join(results_dir, filename)
+            try:
+                if os.path.isfile(file_path):
+                    os.remove(file_path)
+            except OSError:
+                pass
+
+    # Also clean up the temp cwd directory itself
+    try:
+        shutil.rmtree(normalized, ignore_errors=True)
+    except OSError:
+        pass
+
+
+async def _compress_conversation_history(
+    session: ChatSession,
+) -> list[ChatMessage]:
+    """Compress prior conversation messages if they exceed the token threshold.
+
+    Uses the shared compress_context() from prompt.py which supports:
+    - LLM summarization of old messages (keeps recent ones intact)
+    - Progressive content truncation as fallback
+    - Middle-out deletion as last resort
+
+    Returns the compressed prior messages (everything except the current message).
+    """
+    prior = session.messages[:-1]
+    if len(prior) < 2:
+        return prior
+
+    from backend.util.prompt import compress_context
+
+    # Convert ChatMessages to dicts for compress_context
+    messages_dict = []
+    for msg in prior:
+        msg_dict: dict[str, Any] = {"role": msg.role}
+        if msg.content:
+            msg_dict["content"] = msg.content
+        if msg.tool_calls:
+            msg_dict["tool_calls"] = msg.tool_calls
+        if msg.tool_call_id:
+            msg_dict["tool_call_id"] = msg.tool_call_id
+        messages_dict.append(msg_dict)
+
+    try:
+        import openai
+
+        async with openai.AsyncOpenAI(
+            api_key=config.api_key, base_url=config.base_url, timeout=30.0
+        ) as client:
+            result = await compress_context(
+                messages=messages_dict,
+                model=config.model,
+                client=client,
+            )
+    except Exception as e:
+        logger.warning(f"[SDK] Context compression with LLM failed: {e}")
+        # Fall back to truncation-only (no LLM summarization)
+        result = await compress_context(
+            messages=messages_dict,
+            model=config.model,
+            client=None,
+        )
+
+    if result.was_compacted:
+        logger.info(
+            f"[SDK] Context compacted: {result.original_token_count} -> "
+            f"{result.token_count} tokens "
+            f"({result.messages_summarized} summarized, "
+            f"{result.messages_dropped} dropped)"
+        )
+        # Convert compressed dicts back to ChatMessages
+        return [
+            ChatMessage(
+                role=m["role"],
+                content=m.get("content"),
+                tool_calls=m.get("tool_calls"),
+                tool_call_id=m.get("tool_call_id"),
+            )
+            for m in result.messages
+        ]
+
+    return prior
+
+
+def _format_conversation_context(messages: list[ChatMessage]) -> str | None:
+    """Format conversation messages into a context prefix for the user message.
+
+    Returns a string like:
+        <conversation_history>
+        User: hello
+        You responded: Hi! How can I help?
+        </conversation_history>
+
+    Returns None if there are no messages to format.
+    """
+    if not messages:
+        return None
+
+    lines: list[str] = []
+    for msg in messages:
+        if not msg.content:
+            continue
+        if msg.role == "user":
+            lines.append(f"User: {msg.content}")
+        elif msg.role == "assistant":
+            lines.append(f"You responded: {msg.content}")
+        # Skip tool messages — they're internal details
+
+    if not lines:
+        return None
+
+    return "<conversation_history>\n" + "\n".join(lines) + "\n</conversation_history>"
+
+
+async def stream_chat_completion_sdk(
+    session_id: str,
+    message: str | None = None,
+    tool_call_response: str | None = None,  # noqa: ARG001
+    is_user_message: bool = True,
+    user_id: str | None = None,
+    retry_count: int = 0,  # noqa: ARG001
+    session: ChatSession | None = None,
+    context: dict[str, str] | None = None,  # noqa: ARG001
+) -> AsyncGenerator[StreamBaseResponse, None]:
+    """Stream chat completion using Claude Agent SDK.
+
+    Drop-in replacement for stream_chat_completion with improved reliability.
+    """
+
+    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."
+        )
+
+    if message:
+        session.messages.append(
+            ChatMessage(
+                role="user" if is_user_message else "assistant", 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 (first user message)
+    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)
+
+    # Build system prompt (reuses non-SDK path with Langfuse support)
+    has_history = len(session.messages) > 1
+    system_prompt, _ = await _build_system_prompt(
+        user_id, has_conversation_history=has_history
+    )
+    system_prompt += _SDK_TOOL_SUPPLEMENT
+    message_id = str(uuid.uuid4())
+    task_id = str(uuid.uuid4())
+
+    yield StreamStart(messageId=message_id, taskId=task_id)
+
+    stream_completed = False
+    # Initialise sdk_cwd before the try so the finally can reference it
+    # even if _make_sdk_cwd raises (in that case it stays as "").
+    sdk_cwd = ""
+
+    try:
+        # Use a session-specific temp dir to avoid cleanup race conditions
+        # between concurrent sessions.
+        sdk_cwd = _make_sdk_cwd(session_id)
+        os.makedirs(sdk_cwd, exist_ok=True)
+
+        set_execution_context(
+            user_id,
+            session,
+            long_running_callback=_build_long_running_callback(user_id),
+        )
+        try:
+            from claude_agent_sdk import ClaudeAgentOptions, ClaudeSDKClient
+
+            # Fail fast when no API credentials are available at all
+            sdk_env = _build_sdk_env()
+            if not sdk_env and not os.environ.get("ANTHROPIC_API_KEY"):
+                raise RuntimeError(
+                    "No API key configured. Set OPEN_ROUTER_API_KEY "
+                    "(or CHAT_API_KEY) for OpenRouter routing, "
+                    "or ANTHROPIC_API_KEY for direct Anthropic access."
+                )
+
+            mcp_server = create_copilot_mcp_server()
+
+            sdk_model = _resolve_sdk_model()
+
+            security_hooks = create_security_hooks(
+                user_id,
+                sdk_cwd=sdk_cwd,
+                max_subtasks=config.claude_agent_max_subtasks,
+            )
+
+            options = ClaudeAgentOptions(
+                system_prompt=system_prompt,
+                mcp_servers={"copilot": mcp_server},  # type: ignore[arg-type]
+                allowed_tools=COPILOT_TOOL_NAMES,
+                hooks=security_hooks,  # type: ignore[arg-type]
+                cwd=sdk_cwd,
+                max_buffer_size=config.claude_agent_max_buffer_size,
+                # Only pass model/env when OpenRouter is configured
+                **({"model": sdk_model, "env": sdk_env} if sdk_env else {}),
+            )
+
+            adapter = SDKResponseAdapter(message_id=message_id)
+            adapter.set_task_id(task_id)
+
+            async with ClaudeSDKClient(options=options) as client:
+                current_message = message or ""
+                if not current_message and session.messages:
+                    last_user = [m for m in session.messages if m.role == "user"]
+                    if last_user:
+                        current_message = last_user[-1].content or ""
+
+                if not current_message.strip():
+                    yield StreamError(
+                        errorText="Message cannot be empty.",
+                        code="empty_prompt",
+                    )
+                    yield StreamFinish()
+                    return
+
+                # Build query with conversation history context.
+                # Compress history first to handle long conversations.
+                query_message = current_message
+                if len(session.messages) > 1:
+                    compressed = await _compress_conversation_history(session)
+                    history_context = _format_conversation_context(compressed)
+                    if history_context:
+                        query_message = (
+                            f"{history_context}\n\n"
+                            f"Now, the user says:\n{current_message}"
+                        )
+
+                logger.info(
+                    f"[SDK] Sending query: {current_message[:80]!r}"
+                    f" ({len(session.messages)} msgs in session)"
+                )
+                await client.query(query_message, session_id=session_id)
+
+                assistant_response = ChatMessage(role="assistant", content="")
+                accumulated_tool_calls: list[dict[str, Any]] = []
+                has_appended_assistant = False
+                has_tool_results = False
+
+                async for sdk_msg in client.receive_messages():
+                    logger.debug(
+                        f"[SDK] Received: {type(sdk_msg).__name__} "
+                        f"{getattr(sdk_msg, 'subtype', '')}"
+                    )
+                    for response in adapter.convert_message(sdk_msg):
+                        if isinstance(response, StreamStart):
+                            continue
+
+                        yield response
+
+                        if isinstance(response, StreamTextDelta):
+                            delta = response.delta or ""
+                            # After tool results, start a new assistant
+                            # message for the post-tool text.
+                            if has_tool_results and has_appended_assistant:
+                                assistant_response = ChatMessage(
+                                    role="assistant", content=delta
+                                )
+                                accumulated_tool_calls = []
+                                has_appended_assistant = False
+                                has_tool_results = False
+                                session.messages.append(assistant_response)
+                                has_appended_assistant = True
+                            else:
+                                assistant_response.content = (
+                                    assistant_response.content or ""
+                                ) + delta
+                                if not has_appended_assistant:
+                                    session.messages.append(assistant_response)
+                                    has_appended_assistant = True
+
+                        elif isinstance(response, StreamToolInputAvailable):
+                            accumulated_tool_calls.append(
+                                {
+                                    "id": response.toolCallId,
+                                    "type": "function",
+                                    "function": {
+                                        "name": response.toolName,
+                                        "arguments": json.dumps(response.input or {}),
+                                    },
+                                }
+                            )
+                            assistant_response.tool_calls = accumulated_tool_calls
+                            if not has_appended_assistant:
+                                session.messages.append(assistant_response)
+                                has_appended_assistant = True
+
+                        elif isinstance(response, StreamToolOutputAvailable):
+                            session.messages.append(
+                                ChatMessage(
+                                    role="tool",
+                                    content=(
+                                        response.output
+                                        if isinstance(response.output, str)
+                                        else str(response.output)
+                                    ),
+                                    tool_call_id=response.toolCallId,
+                                )
+                            )
+                            has_tool_results = True
+
+                        elif isinstance(response, StreamFinish):
+                            stream_completed = True
+
+                    if stream_completed:
+                        break
+
+                if (
+                    assistant_response.content or assistant_response.tool_calls
+                ) and not has_appended_assistant:
+                    session.messages.append(assistant_response)
+
+        except ImportError:
+            raise RuntimeError(
+                "claude-agent-sdk is not installed. "
+                "Disable SDK mode (CHAT_USE_CLAUDE_AGENT_SDK=false) "
+                "to use the OpenAI-compatible fallback."
+            )
+
+        await upsert_chat_session(session)
+        logger.debug(
+            f"[SDK] Session {session_id} saved with {len(session.messages)} messages"
+        )
+        if not stream_completed:
+            yield StreamFinish()
+
+    except Exception as e:
+        logger.error(f"[SDK] Error: {e}", exc_info=True)
+        try:
+            await upsert_chat_session(session)
+        except Exception as save_err:
+            logger.error(f"[SDK] Failed to save session on error: {save_err}")
+        yield StreamError(
+            errorText="An error occurred. Please try again.",
+            code="sdk_error",
+        )
+        yield StreamFinish()
+    finally:
+        if sdk_cwd:
+            _cleanup_sdk_tool_results(sdk_cwd)
+
+
+async def _update_title_async(
+    session_id: str, message: str, user_id: str | None = None
+) -> None:
+    """Background task to update session title."""
+    try:
+        title = await _generate_session_title(
+            message, user_id=user_id, session_id=session_id
+        )
+        if title:
+            await update_session_title(session_id, title)
+            logger.debug(f"[SDK] Generated title for {session_id}: {title}")
+    except Exception as e:
+        logger.warning(f"[SDK] Failed to update session title: {e}")

autogpt_platform/backend/backend/api/features/chat/sdk/tool_adapter.py

@@ -0,0 +1,320 @@
+"""Tool adapter for wrapping existing CoPilot tools as Claude Agent SDK MCP tools.
+
+This module provides the adapter layer that converts existing BaseTool implementations
+into in-process MCP tools that can be used with the Claude Agent SDK.
+
+Long-running tools (``is_long_running=True``) are delegated to the non-SDK
+background infrastructure (stream_registry, Redis persistence, SSE reconnection)
+via a callback provided by the service layer.  This avoids wasteful SDK polling
+and makes results survive page refreshes.
+"""
+
+import json
+import logging
+import os
+import uuid
+from collections.abc import Awaitable, Callable
+from contextvars import ContextVar
+from typing import Any
+
+from backend.api.features.chat.model import ChatSession
+from backend.api.features.chat.tools import TOOL_REGISTRY
+from backend.api.features.chat.tools.base import BaseTool
+
+logger = logging.getLogger(__name__)
+
+# Allowed base directory for the Read tool (SDK saves oversized tool results here).
+# Restricted to ~/.claude/projects/ and further validated to require "tool-results"
+# in the path — prevents reading settings, credentials, or other sensitive files.
+_SDK_PROJECTS_DIR = os.path.expanduser("~/.claude/projects/")
+
+# MCP server naming - the SDK prefixes tool names as "mcp__{server_name}__{tool}"
+MCP_SERVER_NAME = "copilot"
+MCP_TOOL_PREFIX = f"mcp__{MCP_SERVER_NAME}__"
+
+# Context variables to pass user/session info to tool execution
+_current_user_id: ContextVar[str | None] = ContextVar("current_user_id", default=None)
+_current_session: ContextVar[ChatSession | None] = ContextVar(
+    "current_session", default=None
+)
+# Stash for MCP tool outputs before the SDK potentially truncates them.
+# Keyed by tool_name → full output string. Consumed (popped) by the
+# response adapter when it builds StreamToolOutputAvailable.
+_pending_tool_outputs: ContextVar[dict[str, str]] = ContextVar(
+    "pending_tool_outputs", default=None  # type: ignore[arg-type]
+)
+
+# Callback type for delegating long-running tools to the non-SDK infrastructure.
+# Args: (tool_name, arguments, session) → MCP-formatted response dict.
+LongRunningCallback = Callable[
+    [str, dict[str, Any], ChatSession], Awaitable[dict[str, Any]]
+]
+
+# ContextVar so the service layer can inject the callback per-request.
+_long_running_callback: ContextVar[LongRunningCallback | None] = ContextVar(
+    "long_running_callback", default=None
+)
+
+
+def set_execution_context(
+    user_id: str | None,
+    session: ChatSession,
+    long_running_callback: LongRunningCallback | None = None,
+) -> None:
+    """Set the execution context for tool calls.
+
+    This must be called before streaming begins to ensure tools have access
+    to user_id and session information.
+
+    Args:
+        user_id: Current user's ID.
+        session: Current chat session.
+        long_running_callback: Optional callback to delegate long-running tools
+            to the non-SDK background infrastructure (stream_registry + Redis).
+    """
+    _current_user_id.set(user_id)
+    _current_session.set(session)
+    _pending_tool_outputs.set({})
+    _long_running_callback.set(long_running_callback)
+
+
+def get_execution_context() -> tuple[str | None, ChatSession | None]:
+    """Get the current execution context."""
+    return (
+        _current_user_id.get(),
+        _current_session.get(),
+    )
+
+
+def pop_pending_tool_output(tool_name: str) -> str | None:
+    """Pop and return the stashed full output for *tool_name*.
+
+    The SDK CLI may truncate large tool results (writing them to disk and
+    replacing the content with a file reference). This stash keeps the
+    original MCP output so the response adapter can forward it to the
+    frontend for proper widget rendering.
+
+    Returns ``None`` if nothing was stashed for *tool_name*.
+    """
+    pending = _pending_tool_outputs.get(None)
+    if pending is None:
+        return None
+    return pending.pop(tool_name, None)
+
+
+async def _execute_tool_sync(
+    base_tool: BaseTool,
+    user_id: str | None,
+    session: ChatSession,
+    args: dict[str, Any],
+) -> dict[str, Any]:
+    """Execute a tool synchronously and return MCP-formatted response."""
+    effective_id = f"sdk-{uuid.uuid4().hex[:12]}"
+    result = await base_tool.execute(
+        user_id=user_id,
+        session=session,
+        tool_call_id=effective_id,
+        **args,
+    )
+
+    text = (
+        result.output if isinstance(result.output, str) else json.dumps(result.output)
+    )
+
+    # Stash the full output before the SDK potentially truncates it.
+    pending = _pending_tool_outputs.get(None)
+    if pending is not None:
+        pending[base_tool.name] = text
+
+    return {
+        "content": [{"type": "text", "text": text}],
+        "isError": not result.success,
+    }
+
+
+def _mcp_error(message: str) -> dict[str, Any]:
+    return {
+        "content": [
+            {"type": "text", "text": json.dumps({"error": message, "type": "error"})}
+        ],
+        "isError": True,
+    }
+
+
+def create_tool_handler(base_tool: BaseTool):
+    """Create an async handler function for a BaseTool.
+
+    This wraps the existing BaseTool._execute method to be compatible
+    with the Claude Agent SDK MCP tool format.
+
+    Long-running tools (``is_long_running=True``) are delegated to the
+    non-SDK background infrastructure via a callback set in the execution
+    context.  The callback persists the operation in Redis (stream_registry)
+    so results survive page refreshes and pod restarts.
+    """
+
+    async def tool_handler(args: dict[str, Any]) -> dict[str, Any]:
+        """Execute the wrapped tool and return MCP-formatted response."""
+        user_id, session = get_execution_context()
+
+        if session is None:
+            return _mcp_error("No session context available")
+
+        # --- Long-running: delegate to non-SDK background infrastructure ---
+        if base_tool.is_long_running:
+            callback = _long_running_callback.get(None)
+            if callback:
+                try:
+                    return await callback(base_tool.name, args, session)
+                except Exception as e:
+                    logger.error(
+                        f"Long-running callback failed for {base_tool.name}: {e}",
+                        exc_info=True,
+                    )
+                    return _mcp_error(f"Failed to start {base_tool.name}: {e}")
+            # No callback — fall through to synchronous execution
+            logger.warning(
+                f"[SDK] No long-running callback for {base_tool.name}, "
+                f"executing synchronously (may block)"
+            )
+
+        # --- Normal (fast) tool: execute synchronously ---
+        try:
+            return await _execute_tool_sync(base_tool, user_id, session, args)
+        except Exception as e:
+            logger.error(f"Error executing tool {base_tool.name}: {e}", exc_info=True)
+            return _mcp_error(f"Failed to execute {base_tool.name}: {e}")
+
+    return tool_handler
+
+
+def _build_input_schema(base_tool: BaseTool) -> dict[str, Any]:
+    """Build a JSON Schema input schema for a tool."""
+    return {
+        "type": "object",
+        "properties": base_tool.parameters.get("properties", {}),
+        "required": base_tool.parameters.get("required", []),
+    }
+
+
+async def _read_file_handler(args: dict[str, Any]) -> dict[str, Any]:
+    """Read a file with optional offset/limit. Restricted to SDK working directory.
+
+    After reading, the file is deleted to prevent accumulation in long-running pods.
+    """
+    file_path = args.get("file_path", "")
+    offset = args.get("offset", 0)
+    limit = args.get("limit", 2000)
+
+    # Security: only allow reads under ~/.claude/projects/**/tool-results/
+    real_path = os.path.realpath(file_path)
+    if not real_path.startswith(_SDK_PROJECTS_DIR) or "tool-results" not in real_path:
+        return {
+            "content": [{"type": "text", "text": f"Access denied: {file_path}"}],
+            "isError": True,
+        }
+
+    try:
+        with open(real_path) as f:
+            lines = f.readlines()
+        selected = lines[offset : offset + limit]
+        content = "".join(selected)
+        return {"content": [{"type": "text", "text": content}], "isError": False}
+    except FileNotFoundError:
+        return {
+            "content": [{"type": "text", "text": f"File not found: {file_path}"}],
+            "isError": True,
+        }
+    except Exception as e:
+        return {
+            "content": [{"type": "text", "text": f"Error reading file: {e}"}],
+            "isError": True,
+        }
+
+
+_READ_TOOL_NAME = "Read"
+_READ_TOOL_DESCRIPTION = (
+    "Read a file from the local filesystem. "
+    "Use offset and limit to read specific line ranges for large files."
+)
+_READ_TOOL_SCHEMA = {
+    "type": "object",
+    "properties": {
+        "file_path": {
+            "type": "string",
+            "description": "The absolute path to the file to read",
+        },
+        "offset": {
+            "type": "integer",
+            "description": "Line number to start reading from (0-indexed). Default: 0",
+        },
+        "limit": {
+            "type": "integer",
+            "description": "Number of lines to read. Default: 2000",
+        },
+    },
+    "required": ["file_path"],
+}
+
+
+# Create the MCP server configuration
+def create_copilot_mcp_server():
+    """Create an in-process MCP server configuration for CoPilot tools.
+
+    This can be passed to ClaudeAgentOptions.mcp_servers.
+
+    Note: The actual SDK MCP server creation depends on the claude-agent-sdk
+    package being available. This function returns the configuration that
+    can be used with the SDK.
+    """
+    try:
+        from claude_agent_sdk import create_sdk_mcp_server, tool
+
+        # Create decorated tool functions
+        sdk_tools = []
+
+        for tool_name, base_tool in TOOL_REGISTRY.items():
+            handler = create_tool_handler(base_tool)
+            decorated = tool(
+                tool_name,
+                base_tool.description,
+                _build_input_schema(base_tool),
+            )(handler)
+            sdk_tools.append(decorated)
+
+        # Add the Read tool so the SDK can read back oversized tool results
+        read_tool = tool(
+            _READ_TOOL_NAME,
+            _READ_TOOL_DESCRIPTION,
+            _READ_TOOL_SCHEMA,
+        )(_read_file_handler)
+        sdk_tools.append(read_tool)
+
+        server = create_sdk_mcp_server(
+            name=MCP_SERVER_NAME,
+            version="1.0.0",
+            tools=sdk_tools,
+        )
+
+        return server
+
+    except ImportError:
+        # Let ImportError propagate so service.py handles the fallback
+        raise
+
+
+# SDK built-in tools allowed within the workspace directory.
+# Security hooks validate that file paths stay within sdk_cwd.
+# Bash is NOT included — use the sandboxed MCP bash_exec tool instead,
+# which provides kernel-level network isolation via unshare --net.
+# Task allows spawning sub-agents (rate-limited by security hooks).
+_SDK_BUILTIN_TOOLS = ["Read", "Write", "Edit", "Glob", "Grep", "Task"]
+
+# List of tool names for allowed_tools configuration
+# Include MCP tools, the MCP Read tool for oversized results,
+# and SDK built-in file tools for workspace operations.
+COPILOT_TOOL_NAMES = [
+    *[f"{MCP_TOOL_PREFIX}{name}" for name in TOOL_REGISTRY.keys()],
+    f"{MCP_TOOL_PREFIX}{_READ_TOOL_NAME}",
+    *_SDK_BUILTIN_TOOLS,
+]

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

@@ -245,12 +245,16 @@ async def _get_system_prompt_template(context: str) -> str:
     return DEFAULT_SYSTEM_PROMPT.format(users_information=context)
 
 
-async def _build_system_prompt(user_id: str | None) -> tuple[str, Any]:
+async def _build_system_prompt(
+    user_id: str | None, has_conversation_history: bool = False
+) -> tuple[str, Any]:
     """Build the full system prompt including business understanding if available.
 
     Args:
-        user_id: The user ID for fetching business understanding
-                     If "default" and this is the user's first session, will use "onboarding" instead.
+        user_id: The user ID for fetching business understanding.
+        has_conversation_history: Whether there's existing conversation history.
+            If True, we don't tell the model to greet/introduce (since they're
+            already in a conversation).
 
     Returns:
         Tuple of (compiled prompt string, business understanding object)
@@ -266,6 +270,8 @@ async def _build_system_prompt(user_id: str | None) -> tuple[str, Any]:
 
     if understanding:
         context = format_understanding_for_prompt(understanding)
+    elif has_conversation_history:
+        context = "No prior understanding saved yet. Continue the existing conversation naturally."
     else:
         context = "This is the first time you are meeting the user. Greet them and introduce them to the platform"
 
@@ -374,7 +380,6 @@ async def stream_chat_completion(
 
     Raises:
         NotFoundError: If session_id is invalid
-        ValueError: If max_context_messages is exceeded
 
     """
     completion_start = time.monotonic()
@@ -459,8 +464,9 @@ async def stream_chat_completion(
 
     # Generate title for new sessions on first user message (non-blocking)
     # Check: is_user_message, no title yet, and this is the first user message
-    if is_user_message and message and not session.title:
-        user_messages = [m for m in session.messages if m.role == "user"]
+    user_messages = [m for m in session.messages if m.role == "user"]
+    first_user_msg = message or (user_messages[0].content if user_messages else None)
+    if is_user_message and first_user_msg and not session.title:
         if len(user_messages) == 1:
             # First user message - generate title in background
             import asyncio
@@ -468,7 +474,7 @@ async def stream_chat_completion(
             # Capture only the values we need (not the session object) to avoid
             # stale data issues when the main flow modifies the session
             captured_session_id = session_id
-            captured_message = message
+            captured_message = first_user_msg
             captured_user_id = user_id
 
             async def _update_title():
@@ -1237,7 +1243,7 @@ async def _stream_chat_chunks(
 
                 total_time = (time_module.perf_counter() - stream_chunks_start) * 1000
                 logger.info(
-                    f"[TIMING] _stream_chat_chunks COMPLETED in {total_time/1000:.1f}s; "
+                    f"[TIMING] _stream_chat_chunks COMPLETED in {total_time / 1000:.1f}s; "
                     f"session={session.session_id}, user={session.user_id}",
                     extra={"json_fields": {**log_meta, "total_time_ms": total_time}},
                 )
@@ -1245,7 +1251,6 @@ async def _stream_chat_chunks(
                 return
             except Exception as e:
                 last_error = e
-
                 if _is_retryable_error(e) and retry_count < MAX_RETRIES:
                     retry_count += 1
                     # Calculate delay with exponential backoff
@@ -1261,27 +1266,12 @@ async def _stream_chat_chunks(
                     continue  # Retry the stream
                 else:
                     # Non-retryable error or max retries exceeded
-                    _log_api_error(
-                        error=e,
-                        context="stream (not retrying)",
-                        session_id=session.session_id if session else None,
-                        message_count=len(messages) if messages else None,
-                        model=model,
-                        retry_count=retry_count,
+                    logger.error(
+                        f"Error in stream (not retrying): {e!s}",
+                        exc_info=True,
                     )
                     error_code = None
                     error_text = str(e)
-
-                    error_details = _extract_api_error_details(e)
-                    if error_details.get("response_body"):
-                        body = error_details["response_body"]
-                        if isinstance(body, dict):
-                            err = body.get("error")
-                            if isinstance(err, dict) and err.get("message"):
-                                error_text = err["message"]
-                            elif body.get("message"):
-                                error_text = body["message"]
-
                     if _is_region_blocked_error(e):
                         error_code = "MODEL_NOT_AVAILABLE_REGION"
                         error_text = (
@@ -1298,13 +1288,9 @@ async def _stream_chat_chunks(
 
         # If we exit the retry loop without returning, it means we exhausted retries
         if last_error:
-            _log_api_error(
-                error=last_error,
-                context=f"stream (max retries {MAX_RETRIES} exceeded)",
-                session_id=session.session_id if session else None,
-                message_count=len(messages) if messages else None,
-                model=model,
-                retry_count=MAX_RETRIES,
+            logger.error(
+                f"Max retries ({MAX_RETRIES}) exceeded. Last error: {last_error!s}",
+                exc_info=True,
             )
             yield StreamError(errorText=f"Max retries exceeded: {last_error!s}")
             yield StreamFinish()
@@ -1877,7 +1863,6 @@ async def _generate_llm_continuation(
                 break  # Success, exit retry loop
             except Exception as e:
                 last_error = e
-
                 if _is_retryable_error(e) and retry_count < MAX_RETRIES:
                     retry_count += 1
                     delay = min(
@@ -1891,25 +1876,17 @@ async def _generate_llm_continuation(
                     await asyncio.sleep(delay)
                     continue
                 else:
-                    # Non-retryable error - log details and exit gracefully
-                    _log_api_error(
-                        error=e,
-                        context="LLM continuation (not retrying)",
-                        session_id=session_id,
-                        message_count=len(messages) if messages else None,
-                        model=config.model,
-                        retry_count=retry_count,
+                    # Non-retryable error - log and exit gracefully
+                    logger.error(
+                        f"Non-retryable error in LLM continuation: {e!s}",
+                        exc_info=True,
                     )
                     return
 
         if last_error:
-            _log_api_error(
-                error=last_error,
-                context=f"LLM continuation (max retries {MAX_RETRIES} exceeded)",
-                session_id=session_id,
-                message_count=len(messages) if messages else None,
-                model=config.model,
-                retry_count=MAX_RETRIES,
+            logger.error(
+                f"Max retries ({MAX_RETRIES}) exceeded for LLM continuation. "
+                f"Last error: {last_error!s}"
             )
             return
 
@@ -1949,91 +1926,6 @@ async def _generate_llm_continuation(
         logger.error(f"Failed to generate LLM continuation: {e}", exc_info=True)
 
 
-def _log_api_error(
-    error: Exception,
-    context: str,
-    session_id: str | None = None,
-    message_count: int | None = None,
-    model: str | None = None,
-    retry_count: int = 0,
-) -> None:
-    """Log detailed API error information for debugging."""
-    details = _extract_api_error_details(error)
-    details["context"] = context
-    details["session_id"] = session_id
-    details["message_count"] = message_count
-    details["model"] = model
-    details["retry_count"] = retry_count
-
-    if isinstance(error, RateLimitError):
-        logger.warning(f"Rate limit error in {context}: {details}", exc_info=error)
-    elif isinstance(error, APIConnectionError):
-        logger.warning(f"API connection error in {context}: {details}", exc_info=error)
-    elif isinstance(error, APIStatusError) and error.status_code >= 500:
-        logger.error(f"API server error (5xx) in {context}: {details}", exc_info=error)
-    else:
-        logger.error(f"API error in {context}: {details}", exc_info=error)
-
-
-def _extract_api_error_details(error: Exception) -> dict[str, Any]:
-    """Extract detailed information from OpenAI/OpenRouter API errors."""
-    error_msg = str(error)
-    details: dict[str, Any] = {
-        "error_type": type(error).__name__,
-        "error_message": error_msg[:500] + "..." if len(error_msg) > 500 else error_msg,
-    }
-
-    if hasattr(error, "code"):
-        details["code"] = getattr(error, "code", None)
-    if hasattr(error, "param"):
-        details["param"] = getattr(error, "param", None)
-
-    if isinstance(error, APIStatusError):
-        details["status_code"] = error.status_code
-        details["request_id"] = getattr(error, "request_id", None)
-
-        if hasattr(error, "body") and error.body:
-            details["response_body"] = _sanitize_error_body(error.body)
-
-        if hasattr(error, "response") and error.response:
-            headers = error.response.headers
-            details["openrouter_provider"] = headers.get("x-openrouter-provider")
-            details["openrouter_model"] = headers.get("x-openrouter-model")
-            details["retry_after"] = headers.get("retry-after")
-            details["rate_limit_remaining"] = headers.get("x-ratelimit-remaining")
-
-    return details
-
-
-def _sanitize_error_body(
-    body: Any, max_length: int = 2000
-) -> dict[str, Any] | str | None:
-    """Extract only safe fields from error response body to avoid logging sensitive data."""
-    if not isinstance(body, dict):
-        # Non-dict bodies (e.g., HTML error pages) - return truncated string
-        if body is not None:
-            body_str = str(body)
-            if len(body_str) > max_length:
-                return body_str[:max_length] + "...[truncated]"
-            return body_str
-        return None
-
-    safe_fields = ("message", "type", "code", "param", "error")
-    sanitized: dict[str, Any] = {}
-
-    for field in safe_fields:
-        if field in body:
-            value = body[field]
-            if field == "error" and isinstance(value, dict):
-                sanitized[field] = _sanitize_error_body(value, max_length)
-            elif isinstance(value, str) and len(value) > max_length:
-                sanitized[field] = value[:max_length] + "...[truncated]"
-            else:
-                sanitized[field] = value
-
-    return sanitized if sanitized else None
-
-
 async def _generate_llm_continuation_with_streaming(
     session_id: str,
     user_id: str | None,

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

@@ -814,6 +814,28 @@ async def get_active_task_for_session(
                 if task_user_id and user_id != task_user_id:
                     continue
 
+                # Auto-expire stale tasks that exceeded stream_timeout
+                created_at_str = meta.get("created_at", "")
+                if created_at_str:
+                    try:
+                        created_at = datetime.fromisoformat(created_at_str)
+                        age_seconds = (
+                            datetime.now(timezone.utc) - created_at
+                        ).total_seconds()
+                        if age_seconds > config.stream_timeout:
+                            logger.warning(
+                                f"[TASK_LOOKUP] Auto-expiring stale task {task_id[:8]}... "
+                                f"(age={age_seconds:.0f}s > timeout={config.stream_timeout}s)"
+                            )
+                            await mark_task_completed(task_id, "failed")
+                            continue
+                    except (ValueError, TypeError):
+                        pass
+
+                logger.info(
+                    f"[TASK_LOOKUP] Found running task {task_id[:8]}... for session {session_id[:8]}..."
+                )
+
                 # Get the last message ID from Redis Stream
                 stream_key = _get_task_stream_key(task_id)
                 last_id = "0-0"

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

@@ -9,6 +9,8 @@ from backend.api.features.chat.tracking import track_tool_called
 from .add_understanding import AddUnderstandingTool
 from .agent_output import AgentOutputTool
 from .base import BaseTool
+from .bash_exec import BashExecTool
+from .check_operation_status import CheckOperationStatusTool
 from .create_agent import CreateAgentTool
 from .customize_agent import CustomizeAgentTool
 from .edit_agent import EditAgentTool
@@ -19,6 +21,7 @@ from .get_doc_page import GetDocPageTool
 from .run_agent import RunAgentTool
 from .run_block import RunBlockTool
 from .search_docs import SearchDocsTool
+from .web_fetch import WebFetchTool
 from .workspace_files import (
     DeleteWorkspaceFileTool,
     ListWorkspaceFilesTool,
@@ -43,47 +46,20 @@ TOOL_REGISTRY: dict[str, BaseTool] = {
     "run_agent": RunAgentTool(),
     "run_block": RunBlockTool(),
     "view_agent_output": AgentOutputTool(),
+    "check_operation_status": CheckOperationStatusTool(),
     "search_docs": SearchDocsTool(),
     "get_doc_page": GetDocPageTool(),
-    # Workspace tools for CoPilot file operations
+    # Web fetch for safe URL retrieval
+    "web_fetch": WebFetchTool(),
+    # Sandboxed code execution (bubblewrap)
+    "bash_exec": BashExecTool(),
+    # Persistent workspace tools (cloud storage, survives across sessions)
     "list_workspace_files": ListWorkspaceFilesTool(),
     "read_workspace_file": ReadWorkspaceFileTool(),
     "write_workspace_file": WriteWorkspaceFileTool(),
     "delete_workspace_file": DeleteWorkspaceFileTool(),
 }
 
-
-def _register_feature_request_tools() -> None:
-    """Register feature request tools only if Linear configuration is available."""
-    from backend.util.settings import Settings
-
-    try:
-        secrets = Settings().secrets
-    except Exception:
-        logger.warning("Feature request tools disabled: failed to load settings")
-        return
-
-    if not (
-        secrets.linear_api_key
-        and secrets.linear_feature_request_project_id
-        and secrets.linear_feature_request_team_id
-    ):
-        logger.info(
-            "Feature request tools disabled: LINEAR_API_KEY, "
-            "LINEAR_FEATURE_REQUEST_PROJECT_ID, or "
-            "LINEAR_FEATURE_REQUEST_TEAM_ID is not configured"
-        )
-        return
-
-    from .feature_requests import CreateFeatureRequestTool, SearchFeatureRequestsTool
-
-    TOOL_REGISTRY["search_feature_requests"] = SearchFeatureRequestsTool()
-    TOOL_REGISTRY["create_feature_request"] = CreateFeatureRequestTool()
-    logger.info("Feature request tools enabled")
-
-
-_register_feature_request_tools()
-
 # Export individual tool instances for backwards compatibility
 find_agent_tool = TOOL_REGISTRY["find_agent"]
 run_agent_tool = TOOL_REGISTRY["run_agent"]

autogpt_platform/backend/backend/api/features/chat/tools/agent_generator/dummy.py

@@ -1,154 +0,0 @@
-"""Dummy Agent Generator for testing.
-
-Returns mock responses matching the format expected from the external service.
-Enable via AGENTGENERATOR_USE_DUMMY=true in settings.
-
-WARNING: This is for testing only. Do not use in production.
-"""
-
-import asyncio
-import logging
-import uuid
-from typing import Any
-
-logger = logging.getLogger(__name__)
-
-# Dummy decomposition result (instructions type)
-DUMMY_DECOMPOSITION_RESULT: dict[str, Any] = {
-    "type": "instructions",
-    "steps": [
-        {
-            "description": "Get input from user",
-            "action": "input",
-            "block_name": "AgentInputBlock",
-        },
-        {
-            "description": "Process the input",
-            "action": "process",
-            "block_name": "TextFormatterBlock",
-        },
-        {
-            "description": "Return output to user",
-            "action": "output",
-            "block_name": "AgentOutputBlock",
-        },
-    ],
-}
-
-# Block IDs from backend/blocks/io.py
-AGENT_INPUT_BLOCK_ID = "c0a8e994-ebf1-4a9c-a4d8-89d09c86741b"
-AGENT_OUTPUT_BLOCK_ID = "363ae599-353e-4804-937e-b2ee3cef3da4"
-
-
-def _generate_dummy_agent_json() -> dict[str, Any]:
-    """Generate a minimal valid agent JSON for testing."""
-    input_node_id = str(uuid.uuid4())
-    output_node_id = str(uuid.uuid4())
-
-    return {
-        "id": str(uuid.uuid4()),
-        "version": 1,
-        "is_active": True,
-        "name": "Dummy Test Agent",
-        "description": "A dummy agent generated for testing purposes",
-        "nodes": [
-            {
-                "id": input_node_id,
-                "block_id": AGENT_INPUT_BLOCK_ID,
-                "input_default": {
-                    "name": "input",
-                    "title": "Input",
-                    "description": "Enter your input",
-                    "placeholder_values": [],
-                },
-                "metadata": {"position": {"x": 0, "y": 0}},
-            },
-            {
-                "id": output_node_id,
-                "block_id": AGENT_OUTPUT_BLOCK_ID,
-                "input_default": {
-                    "name": "output",
-                    "title": "Output",
-                    "description": "Agent output",
-                    "format": "{output}",
-                },
-                "metadata": {"position": {"x": 400, "y": 0}},
-            },
-        ],
-        "links": [
-            {
-                "id": str(uuid.uuid4()),
-                "source_id": input_node_id,
-                "sink_id": output_node_id,
-                "source_name": "result",
-                "sink_name": "value",
-                "is_static": False,
-            },
-        ],
-    }
-
-
-async def decompose_goal_dummy(
-    description: str,
-    context: str = "",
-    library_agents: list[dict[str, Any]] | None = None,
-) -> dict[str, Any]:
-    """Return dummy decomposition result."""
-    logger.info("Using dummy agent generator for decompose_goal")
-    return DUMMY_DECOMPOSITION_RESULT.copy()
-
-
-async def generate_agent_dummy(
-    instructions: dict[str, Any],
-    library_agents: list[dict[str, Any]] | None = None,
-    operation_id: str | None = None,
-    task_id: str | None = None,
-) -> dict[str, Any]:
-    """Return dummy agent JSON after a simulated delay."""
-    logger.info("Using dummy agent generator for generate_agent (30s delay)")
-    await asyncio.sleep(30)
-    return _generate_dummy_agent_json()
-
-
-async def generate_agent_patch_dummy(
-    update_request: str,
-    current_agent: dict[str, Any],
-    library_agents: list[dict[str, Any]] | None = None,
-    operation_id: str | None = None,
-    task_id: str | None = None,
-) -> dict[str, Any]:
-    """Return dummy patched agent (returns the current agent with updated description)."""
-    logger.info("Using dummy agent generator for generate_agent_patch")
-    patched = current_agent.copy()
-    patched["description"] = (
-        f"{current_agent.get('description', '')} (updated: {update_request})"
-    )
-    return patched
-
-
-async def customize_template_dummy(
-    template_agent: dict[str, Any],
-    modification_request: str,
-    context: str = "",
-) -> dict[str, Any]:
-    """Return dummy customized template (returns template with updated description)."""
-    logger.info("Using dummy agent generator for customize_template")
-    customized = template_agent.copy()
-    customized["description"] = (
-        f"{template_agent.get('description', '')} (customized: {modification_request})"
-    )
-    return customized
-
-
-async def get_blocks_dummy() -> list[dict[str, Any]]:
-    """Return dummy blocks list."""
-    logger.info("Using dummy agent generator for get_blocks")
-    return [
-        {"id": AGENT_INPUT_BLOCK_ID, "name": "AgentInputBlock"},
-        {"id": AGENT_OUTPUT_BLOCK_ID, "name": "AgentOutputBlock"},
-    ]
-
-
-async def health_check_dummy() -> bool:
-    """Always returns healthy for dummy service."""
-    return True

autogpt_platform/backend/backend/api/features/chat/tools/agent_generator/service.py

@@ -12,19 +12,8 @@ import httpx
 
 from backend.util.settings import Settings
 
-from .dummy import (
-    customize_template_dummy,
-    decompose_goal_dummy,
-    generate_agent_dummy,
-    generate_agent_patch_dummy,
-    get_blocks_dummy,
-    health_check_dummy,
-)
-
 logger = logging.getLogger(__name__)
 
-_dummy_mode_warned = False
-
 
 def _create_error_response(
     error_message: str,
@@ -101,26 +90,10 @@ def _get_settings() -> Settings:
     return _settings
 
 
-def _is_dummy_mode() -> bool:
-    """Check if dummy mode is enabled for testing."""
-    global _dummy_mode_warned
-    settings = _get_settings()
-    is_dummy = bool(settings.config.agentgenerator_use_dummy)
-    if is_dummy and not _dummy_mode_warned:
-        logger.warning(
-            "Agent Generator running in DUMMY MODE - returning mock responses. "
-            "Do not use in production!"
-        )
-        _dummy_mode_warned = True
-    return is_dummy
-
-
 def is_external_service_configured() -> bool:
-    """Check if external Agent Generator service is configured (or dummy mode)."""
+    """Check if external Agent Generator service is configured."""
     settings = _get_settings()
-    return bool(settings.config.agentgenerator_host) or bool(
-        settings.config.agentgenerator_use_dummy
-    )
+    return bool(settings.config.agentgenerator_host)
 
 
 def _get_base_url() -> str:
@@ -164,9 +137,6 @@ async def decompose_goal_external(
         - {"type": "error", "error": "...", "error_type": "..."} on error
         Or None on unexpected error
     """
-    if _is_dummy_mode():
-        return await decompose_goal_dummy(description, context, library_agents)
-
     client = _get_client()
 
     if context:
@@ -256,11 +226,6 @@ async def generate_agent_external(
     Returns:
         Agent JSON dict, {"status": "accepted"} for async, or error dict {"type": "error", ...} on error
     """
-    if _is_dummy_mode():
-        return await generate_agent_dummy(
-            instructions, library_agents, operation_id, task_id
-        )
-
     client = _get_client()
 
     # Build request payload
@@ -332,11 +297,6 @@ async def generate_agent_patch_external(
     Returns:
         Updated agent JSON, clarifying questions dict, {"status": "accepted"} for async, or error dict on error
     """
-    if _is_dummy_mode():
-        return await generate_agent_patch_dummy(
-            update_request, current_agent, library_agents, operation_id, task_id
-        )
-
     client = _get_client()
 
     # Build request payload
@@ -423,11 +383,6 @@ async def customize_template_external(
     Returns:
         Customized agent JSON, clarifying questions dict, or error dict on error
     """
-    if _is_dummy_mode():
-        return await customize_template_dummy(
-            template_agent, modification_request, context
-        )
-
     client = _get_client()
 
     request = modification_request
@@ -490,9 +445,6 @@ async def get_blocks_external() -> list[dict[str, Any]] | None:
     Returns:
         List of block info dicts or None on error
     """
-    if _is_dummy_mode():
-        return await get_blocks_dummy()
-
     client = _get_client()
 
     try:
@@ -526,9 +478,6 @@ async def health_check() -> bool:
     if not is_external_service_configured():
         return False
 
-    if _is_dummy_mode():
-        return await health_check_dummy()
-
     client = _get_client()
 
     try:

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

@@ -0,0 +1,131 @@
+"""Bash execution tool — run shell commands in a bubblewrap sandbox.
+
+Full Bash scripting is allowed (loops, conditionals, pipes, functions, etc.).
+Safety comes from OS-level isolation (bubblewrap): only system dirs visible
+read-only, writable workspace only, clean env, no network.
+
+Requires bubblewrap (``bwrap``) — the tool is disabled when bwrap is not
+available (e.g. macOS development).
+"""
+
+import logging
+from typing import Any
+
+from backend.api.features.chat.model import ChatSession
+from backend.api.features.chat.tools.base import BaseTool
+from backend.api.features.chat.tools.models import (
+    BashExecResponse,
+    ErrorResponse,
+    ToolResponseBase,
+)
+from backend.api.features.chat.tools.sandbox import (
+    get_workspace_dir,
+    has_full_sandbox,
+    run_sandboxed,
+)
+
+logger = logging.getLogger(__name__)
+
+
+class BashExecTool(BaseTool):
+    """Execute Bash commands in a bubblewrap sandbox."""
+
+    @property
+    def name(self) -> str:
+        return "bash_exec"
+
+    @property
+    def description(self) -> str:
+        if not has_full_sandbox():
+            return (
+                "Bash execution is DISABLED — bubblewrap sandbox is not "
+                "available on this platform. Do not call this tool."
+            )
+        return (
+            "Execute a Bash command or script in a bubblewrap sandbox. "
+            "Full Bash scripting is supported (loops, conditionals, pipes, "
+            "functions, etc.). "
+            "The sandbox shares the same working directory as the SDK Read/Write "
+            "tools — files created by either are accessible to both. "
+            "SECURITY: Only system directories (/usr, /bin, /lib, /etc) are "
+            "visible read-only, the per-session workspace is the only writable "
+            "path, environment variables are wiped (no secrets), all network "
+            "access is blocked at the kernel level, and resource limits are "
+            "enforced (max 64 processes, 512MB memory, 50MB file size). "
+            "Application code, configs, and other directories are NOT accessible. "
+            "To fetch web content, use the web_fetch tool instead. "
+            "Execution is killed after the timeout (default 30s, max 120s). "
+            "Returns stdout and stderr. "
+            "Useful for file manipulation, data processing with Unix tools "
+            "(grep, awk, sed, jq, etc.), and running shell scripts."
+        )
+
+    @property
+    def parameters(self) -> dict[str, Any]:
+        return {
+            "type": "object",
+            "properties": {
+                "command": {
+                    "type": "string",
+                    "description": "Bash command or script to execute.",
+                },
+                "timeout": {
+                    "type": "integer",
+                    "description": (
+                        "Max execution time in seconds (default 30, max 120)."
+                    ),
+                    "default": 30,
+                },
+            },
+            "required": ["command"],
+        }
+
+    @property
+    def requires_auth(self) -> bool:
+        return False
+
+    async def _execute(
+        self,
+        user_id: str | None,
+        session: ChatSession,
+        **kwargs: Any,
+    ) -> ToolResponseBase:
+        session_id = session.session_id if session else None
+
+        if not has_full_sandbox():
+            return ErrorResponse(
+                message="bash_exec requires bubblewrap sandbox (Linux only).",
+                error="sandbox_unavailable",
+                session_id=session_id,
+            )
+
+        command: str = (kwargs.get("command") or "").strip()
+        timeout: int = kwargs.get("timeout", 30)
+
+        if not command:
+            return ErrorResponse(
+                message="No command provided.",
+                error="empty_command",
+                session_id=session_id,
+            )
+
+        workspace = get_workspace_dir(session_id or "default")
+
+        stdout, stderr, exit_code, timed_out = await run_sandboxed(
+            command=["bash", "-c", command],
+            cwd=workspace,
+            timeout=timeout,
+        )
+
+        return BashExecResponse(
+            message=(
+                "Execution timed out"
+                if timed_out
+                else f"Command executed (exit {exit_code})"
+            ),
+            stdout=stdout,
+            stderr=stderr,
+            exit_code=exit_code,
+            timed_out=timed_out,
+            session_id=session_id,
+        )

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

@@ -0,0 +1,127 @@
+"""CheckOperationStatusTool — query the status of a long-running operation."""
+
+import logging
+from typing import Any
+
+from backend.api.features.chat.model import ChatSession
+from backend.api.features.chat.tools.base import BaseTool
+from backend.api.features.chat.tools.models import (
+    ErrorResponse,
+    ResponseType,
+    ToolResponseBase,
+)
+
+logger = logging.getLogger(__name__)
+
+
+class OperationStatusResponse(ToolResponseBase):
+    """Response for check_operation_status tool."""
+
+    type: ResponseType = ResponseType.OPERATION_STATUS
+    task_id: str
+    operation_id: str
+    status: str  # "running", "completed", "failed"
+    tool_name: str | None = None
+    message: str = ""
+
+
+class CheckOperationStatusTool(BaseTool):
+    """Check the status of a long-running operation (create_agent, edit_agent, etc.).
+
+    The CoPilot uses this tool to report back to the user whether an
+    operation that was started earlier has completed, failed, or is still
+    running.
+    """
+
+    @property
+    def name(self) -> str:
+        return "check_operation_status"
+
+    @property
+    def description(self) -> str:
+        return (
+            "Check the current status of a long-running operation such as "
+            "create_agent or edit_agent. Accepts either an operation_id or "
+            "task_id from a previous operation_started response. "
+            "Returns the current status: running, completed, or failed."
+        )
+
+    @property
+    def parameters(self) -> dict[str, Any]:
+        return {
+            "type": "object",
+            "properties": {
+                "operation_id": {
+                    "type": "string",
+                    "description": (
+                        "The operation_id from an operation_started response."
+                    ),
+                },
+                "task_id": {
+                    "type": "string",
+                    "description": (
+                        "The task_id from an operation_started response. "
+                        "Used as fallback if operation_id is not provided."
+                    ),
+                },
+            },
+            "required": [],
+        }
+
+    @property
+    def requires_auth(self) -> bool:
+        return False
+
+    async def _execute(
+        self,
+        user_id: str | None,
+        session: ChatSession,
+        **kwargs,
+    ) -> ToolResponseBase:
+        from backend.api.features.chat import stream_registry
+
+        operation_id: str = kwargs.get("operation_id", "").strip()
+        task_id: str = kwargs.get("task_id", "").strip()
+
+        if not operation_id and not task_id:
+            return ErrorResponse(
+                message="Please provide an operation_id or task_id.",
+                error="missing_parameter",
+            )
+
+        task = None
+        if operation_id:
+            task = await stream_registry.find_task_by_operation_id(operation_id)
+        if task is None and task_id:
+            task = await stream_registry.get_task(task_id)
+
+        if task is None:
+            # Task not in Redis — it may have already expired (TTL).
+            # Check conversation history for the result instead.
+            return ErrorResponse(
+                message=(
+                    "Operation not found — it may have already completed and "
+                    "expired from the status tracker. Check the conversation "
+                    "history for the result."
+                ),
+                error="not_found",
+            )
+
+        status_messages = {
+            "running": (
+                f"The {task.tool_name or 'operation'} is still running. "
+                "Please wait for it to complete."
+            ),
+            "completed": (
+                f"The {task.tool_name or 'operation'} has completed successfully."
+            ),
+            "failed": f"The {task.tool_name or 'operation'} has failed.",
+        }
+
+        return OperationStatusResponse(
+            task_id=task.task_id,
+            operation_id=task.operation_id,
+            status=task.status,
+            tool_name=task.tool_name,
+            message=status_messages.get(task.status, f"Status: {task.status}"),
+        )

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

@@ -1,448 +0,0 @@
-"""Feature request tools - search and create feature requests via Linear."""
-
-import logging
-from typing import Any
-
-from pydantic import SecretStr
-
-from backend.api.features.chat.model import ChatSession
-from backend.api.features.chat.tools.base import BaseTool
-from backend.api.features.chat.tools.models import (
-    ErrorResponse,
-    FeatureRequestCreatedResponse,
-    FeatureRequestInfo,
-    FeatureRequestSearchResponse,
-    NoResultsResponse,
-    ToolResponseBase,
-)
-from backend.blocks.linear._api import LinearClient
-from backend.data.model import APIKeyCredentials
-from backend.data.user import get_user_email_by_id
-from backend.util.settings import Settings
-
-logger = logging.getLogger(__name__)
-
-MAX_SEARCH_RESULTS = 10
-
-# GraphQL queries/mutations
-SEARCH_ISSUES_QUERY = """
-query SearchFeatureRequests($term: String!, $filter: IssueFilter, $first: Int) {
-  searchIssues(term: $term, filter: $filter, first: $first) {
-    nodes {
-      id
-      identifier
-      title
-      description
-    }
-  }
-}
-"""
-
-CUSTOMER_UPSERT_MUTATION = """
-mutation CustomerUpsert($input: CustomerUpsertInput!) {
-  customerUpsert(input: $input) {
-    success
-    customer {
-      id
-      name
-      externalIds
-    }
-  }
-}
-"""
-
-ISSUE_CREATE_MUTATION = """
-mutation IssueCreate($input: IssueCreateInput!) {
-  issueCreate(input: $input) {
-    success
-    issue {
-      id
-      identifier
-      title
-      url
-    }
-  }
-}
-"""
-
-CUSTOMER_NEED_CREATE_MUTATION = """
-mutation CustomerNeedCreate($input: CustomerNeedCreateInput!) {
-  customerNeedCreate(input: $input) {
-    success
-    need {
-      id
-      body
-      customer {
-        id
-        name
-      }
-      issue {
-        id
-        identifier
-        title
-        url
-      }
-    }
-  }
-}
-"""
-
-
-_settings: Settings | None = None
-
-
-def _get_settings() -> Settings:
-    global _settings
-    if _settings is None:
-        _settings = Settings()
-    return _settings
-
-
-def _get_linear_config() -> tuple[LinearClient, str, str]:
-    """Return a configured Linear client, project ID, and team ID.
-
-    Raises RuntimeError if any required setting is missing.
-    """
-    secrets = _get_settings().secrets
-    if not secrets.linear_api_key:
-        raise RuntimeError("LINEAR_API_KEY is not configured")
-    if not secrets.linear_feature_request_project_id:
-        raise RuntimeError("LINEAR_FEATURE_REQUEST_PROJECT_ID is not configured")
-    if not secrets.linear_feature_request_team_id:
-        raise RuntimeError("LINEAR_FEATURE_REQUEST_TEAM_ID is not configured")
-
-    credentials = APIKeyCredentials(
-        id="system-linear",
-        provider="linear",
-        api_key=SecretStr(secrets.linear_api_key),
-        title="System Linear API Key",
-    )
-    client = LinearClient(credentials=credentials)
-    return (
-        client,
-        secrets.linear_feature_request_project_id,
-        secrets.linear_feature_request_team_id,
-    )
-
-
-class SearchFeatureRequestsTool(BaseTool):
-    """Tool for searching existing feature requests in Linear."""
-
-    @property
-    def name(self) -> str:
-        return "search_feature_requests"
-
-    @property
-    def description(self) -> str:
-        return (
-            "Search existing feature requests to check if a similar request "
-            "already exists before creating a new one. Returns matching feature "
-            "requests with their ID, title, and description."
-        )
-
-    @property
-    def parameters(self) -> dict[str, Any]:
-        return {
-            "type": "object",
-            "properties": {
-                "query": {
-                    "type": "string",
-                    "description": "Search term to find matching feature requests.",
-                },
-            },
-            "required": ["query"],
-        }
-
-    @property
-    def requires_auth(self) -> bool:
-        return True
-
-    async def _execute(
-        self,
-        user_id: str | None,
-        session: ChatSession,
-        **kwargs,
-    ) -> ToolResponseBase:
-        query = kwargs.get("query", "").strip()
-        session_id = session.session_id if session else None
-
-        if not query:
-            return ErrorResponse(
-                message="Please provide a search query.",
-                error="Missing query parameter",
-                session_id=session_id,
-            )
-
-        try:
-            client, project_id, _team_id = _get_linear_config()
-            data = await client.query(
-                SEARCH_ISSUES_QUERY,
-                {
-                    "term": query,
-                    "filter": {
-                        "project": {"id": {"eq": project_id}},
-                    },
-                    "first": MAX_SEARCH_RESULTS,
-                },
-            )
-
-            nodes = data.get("searchIssues", {}).get("nodes", [])
-
-            if not nodes:
-                return NoResultsResponse(
-                    message=f"No feature requests found matching '{query}'.",
-                    suggestions=[
-                        "Try different keywords",
-                        "Use broader search terms",
-                        "You can create a new feature request if none exists",
-                    ],
-                    session_id=session_id,
-                )
-
-            results = [
-                FeatureRequestInfo(
-                    id=node["id"],
-                    identifier=node["identifier"],
-                    title=node["title"],
-                    description=node.get("description"),
-                )
-                for node in nodes
-            ]
-
-            return FeatureRequestSearchResponse(
-                message=f"Found {len(results)} feature request(s) matching '{query}'.",
-                results=results,
-                count=len(results),
-                query=query,
-                session_id=session_id,
-            )
-        except Exception as e:
-            logger.exception("Failed to search feature requests")
-            return ErrorResponse(
-                message="Failed to search feature requests.",
-                error=str(e),
-                session_id=session_id,
-            )
-
-
-class CreateFeatureRequestTool(BaseTool):
-    """Tool for creating feature requests (or adding needs to existing ones)."""
-
-    @property
-    def name(self) -> str:
-        return "create_feature_request"
-
-    @property
-    def description(self) -> str:
-        return (
-            "Create a new feature request or add a customer need to an existing one. "
-            "Always search first with search_feature_requests to avoid duplicates. "
-            "If a matching request exists, pass its ID as existing_issue_id to add "
-            "the user's need to it instead of creating a duplicate."
-        )
-
-    @property
-    def parameters(self) -> dict[str, Any]:
-        return {
-            "type": "object",
-            "properties": {
-                "title": {
-                    "type": "string",
-                    "description": "Title for the feature request.",
-                },
-                "description": {
-                    "type": "string",
-                    "description": "Detailed description of what the user wants and why.",
-                },
-                "existing_issue_id": {
-                    "type": "string",
-                    "description": (
-                        "If adding a need to an existing feature request, "
-                        "provide its Linear issue ID (from search results). "
-                        "Omit to create a new feature request."
-                    ),
-                },
-            },
-            "required": ["title", "description"],
-        }
-
-    @property
-    def requires_auth(self) -> bool:
-        return True
-
-    async def _find_or_create_customer(
-        self, client: LinearClient, user_id: str, name: str
-    ) -> dict:
-        """Find existing customer by user_id or create a new one via upsert.
-
-        Args:
-            client: Linear API client.
-            user_id: Stable external ID used to deduplicate customers.
-            name: Human-readable display name (e.g. the user's email).
-        """
-        data = await client.mutate(
-            CUSTOMER_UPSERT_MUTATION,
-            {
-                "input": {
-                    "name": name,
-                    "externalId": user_id,
-                },
-            },
-        )
-        result = data.get("customerUpsert", {})
-        if not result.get("success"):
-            raise RuntimeError(f"Failed to upsert customer: {data}")
-        return result["customer"]
-
-    async def _execute(
-        self,
-        user_id: str | None,
-        session: ChatSession,
-        **kwargs,
-    ) -> ToolResponseBase:
-        title = kwargs.get("title", "").strip()
-        description = kwargs.get("description", "").strip()
-        existing_issue_id = kwargs.get("existing_issue_id")
-        session_id = session.session_id if session else None
-
-        if not title or not description:
-            return ErrorResponse(
-                message="Both title and description are required.",
-                error="Missing required parameters",
-                session_id=session_id,
-            )
-
-        if not user_id:
-            return ErrorResponse(
-                message="Authentication required to create feature requests.",
-                error="Missing user_id",
-                session_id=session_id,
-            )
-
-        try:
-            client, project_id, team_id = _get_linear_config()
-        except Exception as e:
-            logger.exception("Failed to initialize Linear client")
-            return ErrorResponse(
-                message="Failed to create feature request.",
-                error=str(e),
-                session_id=session_id,
-            )
-
-        # Resolve a human-readable name (email) for the Linear customer record.
-        # Fall back to user_id if the lookup fails or returns None.
-        try:
-            customer_display_name = await get_user_email_by_id(user_id) or user_id
-        except Exception:
-            customer_display_name = user_id
-
-        # Step 1: Find or create customer for this user
-        try:
-            customer = await self._find_or_create_customer(
-                client, user_id, customer_display_name
-            )
-            customer_id = customer["id"]
-            customer_name = customer["name"]
-        except Exception as e:
-            logger.exception("Failed to upsert customer in Linear")
-            return ErrorResponse(
-                message="Failed to create feature request.",
-                error=str(e),
-                session_id=session_id,
-            )
-
-        # Step 2: Create or reuse issue
-        issue_id: str | None = None
-        issue_identifier: str | None = None
-        if existing_issue_id:
-            # Add need to existing issue - we still need the issue details for response
-            is_new_issue = False
-            issue_id = existing_issue_id
-        else:
-            # Create new issue in the feature requests project
-            try:
-                data = await client.mutate(
-                    ISSUE_CREATE_MUTATION,
-                    {
-                        "input": {
-                            "title": title,
-                            "description": description,
-                            "teamId": team_id,
-                            "projectId": project_id,
-                        },
-                    },
-                )
-                result = data.get("issueCreate", {})
-                if not result.get("success"):
-                    return ErrorResponse(
-                        message="Failed to create feature request issue.",
-                        error=str(data),
-                        session_id=session_id,
-                    )
-                issue = result["issue"]
-                issue_id = issue["id"]
-                issue_identifier = issue.get("identifier")
-            except Exception as e:
-                logger.exception("Failed to create feature request issue")
-                return ErrorResponse(
-                    message="Failed to create feature request.",
-                    error=str(e),
-                    session_id=session_id,
-                )
-            is_new_issue = True
-
-        # Step 3: Create customer need on the issue
-        try:
-            data = await client.mutate(
-                CUSTOMER_NEED_CREATE_MUTATION,
-                {
-                    "input": {
-                        "customerId": customer_id,
-                        "issueId": issue_id,
-                        "body": description,
-                        "priority": 0,
-                    },
-                },
-            )
-            need_result = data.get("customerNeedCreate", {})
-            if not need_result.get("success"):
-                orphaned = (
-                    {"issue_id": issue_id, "issue_identifier": issue_identifier}
-                    if is_new_issue
-                    else None
-                )
-                return ErrorResponse(
-                    message="Failed to attach customer need to the feature request.",
-                    error=str(data),
-                    details=orphaned,
-                    session_id=session_id,
-                )
-            need = need_result["need"]
-            issue_info = need["issue"]
-        except Exception as e:
-            logger.exception("Failed to create customer need")
-            orphaned = (
-                {"issue_id": issue_id, "issue_identifier": issue_identifier}
-                if is_new_issue
-                else None
-            )
-            return ErrorResponse(
-                message="Failed to attach customer need to the feature request.",
-                error=str(e),
-                details=orphaned,
-                session_id=session_id,
-            )
-
-        return FeatureRequestCreatedResponse(
-            message=(
-                f"{'Created new feature request' if is_new_issue else 'Added your request to existing feature request'}: "
-                f"{issue_info['title']}."
-            ),
-            issue_id=issue_info["id"],
-            issue_identifier=issue_info["identifier"],
-            issue_title=issue_info["title"],
-            issue_url=issue_info.get("url", ""),
-            is_new_issue=is_new_issue,
-            customer_name=customer_name,
-            session_id=session_id,
-        )

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

@@ -1,615 +0,0 @@
-"""Tests for SearchFeatureRequestsTool and CreateFeatureRequestTool."""
-
-from unittest.mock import AsyncMock, patch
-
-import pytest
-
-from backend.api.features.chat.tools.feature_requests import (
-    CreateFeatureRequestTool,
-    SearchFeatureRequestsTool,
-)
-from backend.api.features.chat.tools.models import (
-    ErrorResponse,
-    FeatureRequestCreatedResponse,
-    FeatureRequestSearchResponse,
-    NoResultsResponse,
-)
-
-from ._test_data import make_session
-
-_TEST_USER_ID = "test-user-feature-requests"
-_TEST_USER_EMAIL = "testuser@example.com"
-
-
-# ---------------------------------------------------------------------------
-# Helpers
-# ---------------------------------------------------------------------------
-
-
-_FAKE_PROJECT_ID = "test-project-id"
-_FAKE_TEAM_ID = "test-team-id"
-
-
-def _mock_linear_config(*, query_return=None, mutate_return=None):
-    """Return a patched _get_linear_config that yields a mock LinearClient."""
-    client = AsyncMock()
-    if query_return is not None:
-        client.query.return_value = query_return
-    if mutate_return is not None:
-        client.mutate.return_value = mutate_return
-    return (
-        patch(
-            "backend.api.features.chat.tools.feature_requests._get_linear_config",
-            return_value=(client, _FAKE_PROJECT_ID, _FAKE_TEAM_ID),
-        ),
-        client,
-    )
-
-
-def _search_response(nodes: list[dict]) -> dict:
-    return {"searchIssues": {"nodes": nodes}}
-
-
-def _customer_upsert_response(
-    customer_id: str = "cust-1", name: str = _TEST_USER_EMAIL, success: bool = True
-) -> dict:
-    return {
-        "customerUpsert": {
-            "success": success,
-            "customer": {"id": customer_id, "name": name, "externalIds": [name]},
-        }
-    }
-
-
-def _issue_create_response(
-    issue_id: str = "issue-1",
-    identifier: str = "FR-1",
-    title: str = "New Feature",
-    success: bool = True,
-) -> dict:
-    return {
-        "issueCreate": {
-            "success": success,
-            "issue": {
-                "id": issue_id,
-                "identifier": identifier,
-                "title": title,
-                "url": f"https://linear.app/issue/{identifier}",
-            },
-        }
-    }
-
-
-def _need_create_response(
-    need_id: str = "need-1",
-    issue_id: str = "issue-1",
-    identifier: str = "FR-1",
-    title: str = "New Feature",
-    success: bool = True,
-) -> dict:
-    return {
-        "customerNeedCreate": {
-            "success": success,
-            "need": {
-                "id": need_id,
-                "body": "description",
-                "customer": {"id": "cust-1", "name": _TEST_USER_EMAIL},
-                "issue": {
-                    "id": issue_id,
-                    "identifier": identifier,
-                    "title": title,
-                    "url": f"https://linear.app/issue/{identifier}",
-                },
-            },
-        }
-    }
-
-
-# ===========================================================================
-# SearchFeatureRequestsTool
-# ===========================================================================
-
-
-class TestSearchFeatureRequestsTool:
-    """Tests for SearchFeatureRequestsTool._execute."""
-
-    @pytest.mark.asyncio(loop_scope="session")
-    async def test_successful_search(self):
-        session = make_session(user_id=_TEST_USER_ID)
-        nodes = [
-            {
-                "id": "id-1",
-                "identifier": "FR-1",
-                "title": "Dark mode",
-                "description": "Add dark mode support",
-            },
-            {
-                "id": "id-2",
-                "identifier": "FR-2",
-                "title": "Dark theme",
-                "description": None,
-            },
-        ]
-        patcher, _ = _mock_linear_config(query_return=_search_response(nodes))
-        with patcher:
-            tool = SearchFeatureRequestsTool()
-            resp = await tool._execute(
-                user_id=_TEST_USER_ID, session=session, query="dark mode"
-            )
-
-        assert isinstance(resp, FeatureRequestSearchResponse)
-        assert resp.count == 2
-        assert resp.results[0].id == "id-1"
-        assert resp.results[1].identifier == "FR-2"
-        assert resp.query == "dark mode"
-
-    @pytest.mark.asyncio(loop_scope="session")
-    async def test_no_results(self):
-        session = make_session(user_id=_TEST_USER_ID)
-        patcher, _ = _mock_linear_config(query_return=_search_response([]))
-        with patcher:
-            tool = SearchFeatureRequestsTool()
-            resp = await tool._execute(
-                user_id=_TEST_USER_ID, session=session, query="nonexistent"
-            )
-
-        assert isinstance(resp, NoResultsResponse)
-        assert "nonexistent" in resp.message
-
-    @pytest.mark.asyncio(loop_scope="session")
-    async def test_empty_query_returns_error(self):
-        session = make_session(user_id=_TEST_USER_ID)
-        tool = SearchFeatureRequestsTool()
-        resp = await tool._execute(user_id=_TEST_USER_ID, session=session, query="   ")
-
-        assert isinstance(resp, ErrorResponse)
-        assert resp.error is not None
-        assert "query" in resp.error.lower()
-
-    @pytest.mark.asyncio(loop_scope="session")
-    async def test_missing_query_returns_error(self):
-        session = make_session(user_id=_TEST_USER_ID)
-        tool = SearchFeatureRequestsTool()
-        resp = await tool._execute(user_id=_TEST_USER_ID, session=session)
-
-        assert isinstance(resp, ErrorResponse)
-
-    @pytest.mark.asyncio(loop_scope="session")
-    async def test_api_failure(self):
-        session = make_session(user_id=_TEST_USER_ID)
-        patcher, client = _mock_linear_config()
-        client.query.side_effect = RuntimeError("Linear API down")
-        with patcher:
-            tool = SearchFeatureRequestsTool()
-            resp = await tool._execute(
-                user_id=_TEST_USER_ID, session=session, query="test"
-            )
-
-        assert isinstance(resp, ErrorResponse)
-        assert resp.error is not None
-        assert "Linear API down" in resp.error
-
-    @pytest.mark.asyncio(loop_scope="session")
-    async def test_malformed_node_returns_error(self):
-        """A node missing required keys should be caught by the try/except."""
-        session = make_session(user_id=_TEST_USER_ID)
-        # Node missing 'identifier' key
-        bad_nodes = [{"id": "id-1", "title": "Missing identifier"}]
-        patcher, _ = _mock_linear_config(query_return=_search_response(bad_nodes))
-        with patcher:
-            tool = SearchFeatureRequestsTool()
-            resp = await tool._execute(
-                user_id=_TEST_USER_ID, session=session, query="test"
-            )
-
-        assert isinstance(resp, ErrorResponse)
-
-    @pytest.mark.asyncio(loop_scope="session")
-    async def test_linear_client_init_failure(self):
-        session = make_session(user_id=_TEST_USER_ID)
-        with patch(
-            "backend.api.features.chat.tools.feature_requests._get_linear_config",
-            side_effect=RuntimeError("No API key"),
-        ):
-            tool = SearchFeatureRequestsTool()
-            resp = await tool._execute(
-                user_id=_TEST_USER_ID, session=session, query="test"
-            )
-
-        assert isinstance(resp, ErrorResponse)
-        assert resp.error is not None
-        assert "No API key" in resp.error
-
-
-# ===========================================================================
-# CreateFeatureRequestTool
-# ===========================================================================
-
-
-class TestCreateFeatureRequestTool:
-    """Tests for CreateFeatureRequestTool._execute."""
-
-    @pytest.fixture(autouse=True)
-    def _patch_email_lookup(self):
-        with patch(
-            "backend.api.features.chat.tools.feature_requests.get_user_email_by_id",
-            new_callable=AsyncMock,
-            return_value=_TEST_USER_EMAIL,
-        ):
-            yield
-
-    # ---- Happy paths -------------------------------------------------------
-
-    @pytest.mark.asyncio(loop_scope="session")
-    async def test_create_new_issue(self):
-        """Full happy path: upsert customer -> create issue -> attach need."""
-        session = make_session(user_id=_TEST_USER_ID)
-
-        patcher, client = _mock_linear_config()
-        client.mutate.side_effect = [
-            _customer_upsert_response(),
-            _issue_create_response(),
-            _need_create_response(),
-        ]
-
-        with patcher:
-            tool = CreateFeatureRequestTool()
-            resp = await tool._execute(
-                user_id=_TEST_USER_ID,
-                session=session,
-                title="New Feature",
-                description="Please add this",
-            )
-
-        assert isinstance(resp, FeatureRequestCreatedResponse)
-        assert resp.is_new_issue is True
-        assert resp.issue_identifier == "FR-1"
-        assert resp.customer_name == _TEST_USER_EMAIL
-        assert client.mutate.call_count == 3
-
-    @pytest.mark.asyncio(loop_scope="session")
-    async def test_add_need_to_existing_issue(self):
-        """When existing_issue_id is provided, skip issue creation."""
-        session = make_session(user_id=_TEST_USER_ID)
-
-        patcher, client = _mock_linear_config()
-        client.mutate.side_effect = [
-            _customer_upsert_response(),
-            _need_create_response(issue_id="existing-1", identifier="FR-99"),
-        ]
-
-        with patcher:
-            tool = CreateFeatureRequestTool()
-            resp = await tool._execute(
-                user_id=_TEST_USER_ID,
-                session=session,
-                title="Existing Feature",
-                description="Me too",
-                existing_issue_id="existing-1",
-            )
-
-        assert isinstance(resp, FeatureRequestCreatedResponse)
-        assert resp.is_new_issue is False
-        assert resp.issue_id == "existing-1"
-        # Only 2 mutations: customer upsert + need create (no issue create)
-        assert client.mutate.call_count == 2
-
-    # ---- Validation errors -------------------------------------------------
-
-    @pytest.mark.asyncio(loop_scope="session")
-    async def test_missing_title(self):
-        session = make_session(user_id=_TEST_USER_ID)
-        tool = CreateFeatureRequestTool()
-        resp = await tool._execute(
-            user_id=_TEST_USER_ID,
-            session=session,
-            title="",
-            description="some desc",
-        )
-
-        assert isinstance(resp, ErrorResponse)
-        assert resp.error is not None
-        assert "required" in resp.error.lower()
-
-    @pytest.mark.asyncio(loop_scope="session")
-    async def test_missing_description(self):
-        session = make_session(user_id=_TEST_USER_ID)
-        tool = CreateFeatureRequestTool()
-        resp = await tool._execute(
-            user_id=_TEST_USER_ID,
-            session=session,
-            title="Some title",
-            description="",
-        )
-
-        assert isinstance(resp, ErrorResponse)
-        assert resp.error is not None
-        assert "required" in resp.error.lower()
-
-    @pytest.mark.asyncio(loop_scope="session")
-    async def test_missing_user_id(self):
-        session = make_session(user_id=_TEST_USER_ID)
-        tool = CreateFeatureRequestTool()
-        resp = await tool._execute(
-            user_id=None,
-            session=session,
-            title="Some title",
-            description="Some desc",
-        )
-
-        assert isinstance(resp, ErrorResponse)
-        assert resp.error is not None
-        assert "user_id" in resp.error.lower()
-
-    # ---- Linear client init failure ----------------------------------------
-
-    @pytest.mark.asyncio(loop_scope="session")
-    async def test_linear_client_init_failure(self):
-        session = make_session(user_id=_TEST_USER_ID)
-        with patch(
-            "backend.api.features.chat.tools.feature_requests._get_linear_config",
-            side_effect=RuntimeError("No API key"),
-        ):
-            tool = CreateFeatureRequestTool()
-            resp = await tool._execute(
-                user_id=_TEST_USER_ID,
-                session=session,
-                title="Title",
-                description="Desc",
-            )
-
-        assert isinstance(resp, ErrorResponse)
-        assert resp.error is not None
-        assert "No API key" in resp.error
-
-    # ---- Customer upsert failures ------------------------------------------
-
-    @pytest.mark.asyncio(loop_scope="session")
-    async def test_customer_upsert_api_error(self):
-        session = make_session(user_id=_TEST_USER_ID)
-        patcher, client = _mock_linear_config()
-        client.mutate.side_effect = RuntimeError("Customer API error")
-
-        with patcher:
-            tool = CreateFeatureRequestTool()
-            resp = await tool._execute(
-                user_id=_TEST_USER_ID,
-                session=session,
-                title="Title",
-                description="Desc",
-            )
-
-        assert isinstance(resp, ErrorResponse)
-        assert resp.error is not None
-        assert "Customer API error" in resp.error
-
-    @pytest.mark.asyncio(loop_scope="session")
-    async def test_customer_upsert_not_success(self):
-        session = make_session(user_id=_TEST_USER_ID)
-        patcher, client = _mock_linear_config()
-        client.mutate.return_value = _customer_upsert_response(success=False)
-
-        with patcher:
-            tool = CreateFeatureRequestTool()
-            resp = await tool._execute(
-                user_id=_TEST_USER_ID,
-                session=session,
-                title="Title",
-                description="Desc",
-            )
-
-        assert isinstance(resp, ErrorResponse)
-
-    @pytest.mark.asyncio(loop_scope="session")
-    async def test_customer_malformed_response(self):
-        """Customer dict missing 'id' key should be caught."""
-        session = make_session(user_id=_TEST_USER_ID)
-        patcher, client = _mock_linear_config()
-        # success=True but customer has no 'id'
-        client.mutate.return_value = {
-            "customerUpsert": {
-                "success": True,
-                "customer": {"name": _TEST_USER_ID},
-            }
-        }
-
-        with patcher:
-            tool = CreateFeatureRequestTool()
-            resp = await tool._execute(
-                user_id=_TEST_USER_ID,
-                session=session,
-                title="Title",
-                description="Desc",
-            )
-
-        assert isinstance(resp, ErrorResponse)
-
-    # ---- Issue creation failures -------------------------------------------
-
-    @pytest.mark.asyncio(loop_scope="session")
-    async def test_issue_create_api_error(self):
-        session = make_session(user_id=_TEST_USER_ID)
-        patcher, client = _mock_linear_config()
-        client.mutate.side_effect = [
-            _customer_upsert_response(),
-            RuntimeError("Issue create failed"),
-        ]
-
-        with patcher:
-            tool = CreateFeatureRequestTool()
-            resp = await tool._execute(
-                user_id=_TEST_USER_ID,
-                session=session,
-                title="Title",
-                description="Desc",
-            )
-
-        assert isinstance(resp, ErrorResponse)
-        assert resp.error is not None
-        assert "Issue create failed" in resp.error
-
-    @pytest.mark.asyncio(loop_scope="session")
-    async def test_issue_create_not_success(self):
-        session = make_session(user_id=_TEST_USER_ID)
-        patcher, client = _mock_linear_config()
-        client.mutate.side_effect = [
-            _customer_upsert_response(),
-            _issue_create_response(success=False),
-        ]
-
-        with patcher:
-            tool = CreateFeatureRequestTool()
-            resp = await tool._execute(
-                user_id=_TEST_USER_ID,
-                session=session,
-                title="Title",
-                description="Desc",
-            )
-
-        assert isinstance(resp, ErrorResponse)
-        assert "Failed to create feature request issue" in resp.message
-
-    @pytest.mark.asyncio(loop_scope="session")
-    async def test_issue_create_malformed_response(self):
-        """issueCreate success=True but missing 'issue' key."""
-        session = make_session(user_id=_TEST_USER_ID)
-        patcher, client = _mock_linear_config()
-        client.mutate.side_effect = [
-            _customer_upsert_response(),
-            {"issueCreate": {"success": True}},  # no 'issue' key
-        ]
-
-        with patcher:
-            tool = CreateFeatureRequestTool()
-            resp = await tool._execute(
-                user_id=_TEST_USER_ID,
-                session=session,
-                title="Title",
-                description="Desc",
-            )
-
-        assert isinstance(resp, ErrorResponse)
-
-    # ---- Customer need attachment failures ---------------------------------
-
-    @pytest.mark.asyncio(loop_scope="session")
-    async def test_need_create_api_error_new_issue(self):
-        """Need creation fails after new issue was created -> orphaned issue info."""
-        session = make_session(user_id=_TEST_USER_ID)
-        patcher, client = _mock_linear_config()
-        client.mutate.side_effect = [
-            _customer_upsert_response(),
-            _issue_create_response(issue_id="orphan-1", identifier="FR-10"),
-            RuntimeError("Need attach failed"),
-        ]
-
-        with patcher:
-            tool = CreateFeatureRequestTool()
-            resp = await tool._execute(
-                user_id=_TEST_USER_ID,
-                session=session,
-                title="Title",
-                description="Desc",
-            )
-
-        assert isinstance(resp, ErrorResponse)
-        assert resp.error is not None
-        assert "Need attach failed" in resp.error
-        assert resp.details is not None
-        assert resp.details["issue_id"] == "orphan-1"
-        assert resp.details["issue_identifier"] == "FR-10"
-
-    @pytest.mark.asyncio(loop_scope="session")
-    async def test_need_create_api_error_existing_issue(self):
-        """Need creation fails on existing issue -> no orphaned info."""
-        session = make_session(user_id=_TEST_USER_ID)
-        patcher, client = _mock_linear_config()
-        client.mutate.side_effect = [
-            _customer_upsert_response(),
-            RuntimeError("Need attach failed"),
-        ]
-
-        with patcher:
-            tool = CreateFeatureRequestTool()
-            resp = await tool._execute(
-                user_id=_TEST_USER_ID,
-                session=session,
-                title="Title",
-                description="Desc",
-                existing_issue_id="existing-1",
-            )
-
-        assert isinstance(resp, ErrorResponse)
-        assert resp.details is None
-
-    @pytest.mark.asyncio(loop_scope="session")
-    async def test_need_create_not_success_includes_orphaned_info(self):
-        """customerNeedCreate returns success=False -> includes orphaned issue."""
-        session = make_session(user_id=_TEST_USER_ID)
-        patcher, client = _mock_linear_config()
-        client.mutate.side_effect = [
-            _customer_upsert_response(),
-            _issue_create_response(issue_id="orphan-2", identifier="FR-20"),
-            _need_create_response(success=False),
-        ]
-
-        with patcher:
-            tool = CreateFeatureRequestTool()
-            resp = await tool._execute(
-                user_id=_TEST_USER_ID,
-                session=session,
-                title="Title",
-                description="Desc",
-            )
-
-        assert isinstance(resp, ErrorResponse)
-        assert resp.details is not None
-        assert resp.details["issue_id"] == "orphan-2"
-        assert resp.details["issue_identifier"] == "FR-20"
-
-    @pytest.mark.asyncio(loop_scope="session")
-    async def test_need_create_not_success_existing_issue_no_details(self):
-        """customerNeedCreate fails on existing issue -> no orphaned info."""
-        session = make_session(user_id=_TEST_USER_ID)
-        patcher, client = _mock_linear_config()
-        client.mutate.side_effect = [
-            _customer_upsert_response(),
-            _need_create_response(success=False),
-        ]
-
-        with patcher:
-            tool = CreateFeatureRequestTool()
-            resp = await tool._execute(
-                user_id=_TEST_USER_ID,
-                session=session,
-                title="Title",
-                description="Desc",
-                existing_issue_id="existing-1",
-            )
-
-        assert isinstance(resp, ErrorResponse)
-        assert resp.details is None
-
-    @pytest.mark.asyncio(loop_scope="session")
-    async def test_need_create_malformed_response(self):
-        """need_result missing 'need' key after success=True."""
-        session = make_session(user_id=_TEST_USER_ID)
-        patcher, client = _mock_linear_config()
-        client.mutate.side_effect = [
-            _customer_upsert_response(),
-            _issue_create_response(),
-            {"customerNeedCreate": {"success": True}},  # no 'need' key
-        ]
-
-        with patcher:
-            tool = CreateFeatureRequestTool()
-            resp = await tool._execute(
-                user_id=_TEST_USER_ID,
-                session=session,
-                title="Title",
-                description="Desc",
-            )
-
-        assert isinstance(resp, ErrorResponse)
-        assert resp.details is not None
-        assert resp.details["issue_id"] == "issue-1"

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

@@ -7,6 +7,7 @@ from backend.api.features.chat.model import ChatSession
 from backend.api.features.chat.tools.base import BaseTool, ToolResponseBase
 from backend.api.features.chat.tools.models import (
     BlockInfoSummary,
+    BlockInputFieldInfo,
     BlockListResponse,
     ErrorResponse,
     NoResultsResponse,
@@ -54,8 +55,7 @@ class FindBlockTool(BaseTool):
             "Blocks are reusable components that perform specific tasks like "
             "sending emails, making API calls, processing text, etc. "
             "IMPORTANT: Use this tool FIRST to get the block's 'id' before calling run_block. "
-            "The response includes each block's id, name, and description. "
-            "Call run_block with the block's id **with no inputs** to see detailed inputs/outputs and execute it."
+            "The response includes each block's id, required_inputs, and input_schema."
         )
 
     @property
@@ -124,7 +124,7 @@ class FindBlockTool(BaseTool):
                     session_id=session_id,
                 )
 
-            # Enrich results with block information
+            # Enrich results with full block information
             blocks: list[BlockInfoSummary] = []
             for result in results:
                 block_id = result["content_id"]
@@ -141,11 +141,65 @@ class FindBlockTool(BaseTool):
                 ):
                     continue
 
+                # Get input/output schemas
+                input_schema = {}
+                output_schema = {}
+                try:
+                    input_schema = block.input_schema.jsonschema()
+                except Exception as e:
+                    logger.debug(
+                        "Failed to generate input schema for block %s: %s",
+                        block_id,
+                        e,
+                    )
+                try:
+                    output_schema = block.output_schema.jsonschema()
+                except Exception as e:
+                    logger.debug(
+                        "Failed to generate output schema for block %s: %s",
+                        block_id,
+                        e,
+                    )
+
+                # Get categories from block instance
+                categories = []
+                if hasattr(block, "categories") and block.categories:
+                    categories = [cat.value for cat in block.categories]
+
+                # Extract required inputs for easier use
+                required_inputs: list[BlockInputFieldInfo] = []
+                if input_schema:
+                    properties = input_schema.get("properties", {})
+                    required_fields = set(input_schema.get("required", []))
+                    # Get credential field names to exclude from required inputs
+                    credentials_fields = set(
+                        block.input_schema.get_credentials_fields().keys()
+                    )
+
+                    for field_name, field_schema in properties.items():
+                        # Skip credential fields - they're handled separately
+                        if field_name in credentials_fields:
+                            continue
+
+                        required_inputs.append(
+                            BlockInputFieldInfo(
+                                name=field_name,
+                                type=field_schema.get("type", "string"),
+                                description=field_schema.get("description", ""),
+                                required=field_name in required_fields,
+                                default=field_schema.get("default"),
+                            )
+                        )
+
                 blocks.append(
                     BlockInfoSummary(
                         id=block_id,
                         name=block.name,
                         description=block.description or "",
+                        categories=categories,
+                        input_schema=input_schema,
+                        output_schema=output_schema,
+                        required_inputs=required_inputs,
                     )
                 )
 
@@ -174,7 +228,8 @@ class FindBlockTool(BaseTool):
             return BlockListResponse(
                 message=(
                     f"Found {len(blocks)} block(s) matching '{query}'. "
-                    "To see a block's inputs/outputs and execute it, use run_block with the block's 'id' - providing no inputs."
+                    "To execute a block, use run_block with the block's 'id' field "
+                    "and provide 'input_data' matching the block's input_schema."
                 ),
                 blocks=blocks,
                 count=len(blocks),

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

@@ -18,13 +18,7 @@ _TEST_USER_ID = "test-user-find-block"
 
 
 def make_mock_block(
-    block_id: str,
-    name: str,
-    block_type: BlockType,
-    disabled: bool = False,
-    input_schema: dict | None = None,
-    output_schema: dict | None = None,
-    credentials_fields: dict | None = None,
+    block_id: str, name: str, block_type: BlockType, disabled: bool = False
 ):
     """Create a mock block for testing."""
     mock = MagicMock()
@@ -34,13 +28,10 @@ def make_mock_block(
     mock.block_type = block_type
     mock.disabled = disabled
     mock.input_schema = MagicMock()
-    mock.input_schema.jsonschema.return_value = input_schema or {
-        "properties": {},
-        "required": [],
-    }
-    mock.input_schema.get_credentials_fields.return_value = credentials_fields or {}
+    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 = output_schema or {}
+    mock.output_schema.jsonschema.return_value = {}
     mock.categories = []
     return mock
 
@@ -146,241 +137,3 @@ class TestFindBlockFiltering:
         assert isinstance(response, BlockListResponse)
         assert len(response.blocks) == 1
         assert response.blocks[0].id == "normal-block-id"
-
-    @pytest.mark.asyncio(loop_scope="session")
-    async def test_response_size_average_chars_per_block(self):
-        """Measure average chars per block in the serialized response."""
-        session = make_session(user_id=_TEST_USER_ID)
-
-        # Realistic block definitions modeled after real blocks
-        block_defs = [
-            {
-                "id": "http-block-id",
-                "name": "Send Web Request",
-                "input_schema": {
-                    "properties": {
-                        "url": {
-                            "type": "string",
-                            "description": "The URL to send the request to",
-                        },
-                        "method": {
-                            "type": "string",
-                            "description": "The HTTP method to use",
-                        },
-                        "headers": {
-                            "type": "object",
-                            "description": "Headers to include in the request",
-                        },
-                        "json_format": {
-                            "type": "boolean",
-                            "description": "If true, send the body as JSON",
-                        },
-                        "body": {
-                            "type": "object",
-                            "description": "Form/JSON body payload",
-                        },
-                        "credentials": {
-                            "type": "object",
-                            "description": "HTTP credentials",
-                        },
-                    },
-                    "required": ["url", "method"],
-                },
-                "output_schema": {
-                    "properties": {
-                        "response": {
-                            "type": "object",
-                            "description": "The response from the server",
-                        },
-                        "client_error": {
-                            "type": "object",
-                            "description": "Errors on 4xx status codes",
-                        },
-                        "server_error": {
-                            "type": "object",
-                            "description": "Errors on 5xx status codes",
-                        },
-                        "error": {
-                            "type": "string",
-                            "description": "Errors for all other exceptions",
-                        },
-                    },
-                },
-                "credentials_fields": {"credentials": True},
-            },
-            {
-                "id": "email-block-id",
-                "name": "Send Email",
-                "input_schema": {
-                    "properties": {
-                        "to_email": {
-                            "type": "string",
-                            "description": "Recipient email address",
-                        },
-                        "subject": {
-                            "type": "string",
-                            "description": "Subject of the email",
-                        },
-                        "body": {
-                            "type": "string",
-                            "description": "Body of the email",
-                        },
-                        "config": {
-                            "type": "object",
-                            "description": "SMTP Config",
-                        },
-                        "credentials": {
-                            "type": "object",
-                            "description": "SMTP credentials",
-                        },
-                    },
-                    "required": ["to_email", "subject", "body", "credentials"],
-                },
-                "output_schema": {
-                    "properties": {
-                        "status": {
-                            "type": "string",
-                            "description": "Status of the email sending operation",
-                        },
-                        "error": {
-                            "type": "string",
-                            "description": "Error message if sending failed",
-                        },
-                    },
-                },
-                "credentials_fields": {"credentials": True},
-            },
-            {
-                "id": "claude-code-block-id",
-                "name": "Claude Code",
-                "input_schema": {
-                    "properties": {
-                        "e2b_credentials": {
-                            "type": "object",
-                            "description": "API key for E2B platform",
-                        },
-                        "anthropic_credentials": {
-                            "type": "object",
-                            "description": "API key for Anthropic",
-                        },
-                        "prompt": {
-                            "type": "string",
-                            "description": "Task or instruction for Claude Code",
-                        },
-                        "timeout": {
-                            "type": "integer",
-                            "description": "Sandbox timeout in seconds",
-                        },
-                        "setup_commands": {
-                            "type": "array",
-                            "description": "Shell commands to run before execution",
-                        },
-                        "working_directory": {
-                            "type": "string",
-                            "description": "Working directory for Claude Code",
-                        },
-                        "session_id": {
-                            "type": "string",
-                            "description": "Session ID to resume a conversation",
-                        },
-                        "sandbox_id": {
-                            "type": "string",
-                            "description": "Sandbox ID to reconnect to",
-                        },
-                        "conversation_history": {
-                            "type": "string",
-                            "description": "Previous conversation history",
-                        },
-                        "dispose_sandbox": {
-                            "type": "boolean",
-                            "description": "Whether to dispose sandbox after execution",
-                        },
-                    },
-                    "required": [
-                        "e2b_credentials",
-                        "anthropic_credentials",
-                        "prompt",
-                    ],
-                },
-                "output_schema": {
-                    "properties": {
-                        "response": {
-                            "type": "string",
-                            "description": "Output from Claude Code execution",
-                        },
-                        "files": {
-                            "type": "array",
-                            "description": "Files created/modified by Claude Code",
-                        },
-                        "conversation_history": {
-                            "type": "string",
-                            "description": "Full conversation history",
-                        },
-                        "session_id": {
-                            "type": "string",
-                            "description": "Session ID for this conversation",
-                        },
-                        "sandbox_id": {
-                            "type": "string",
-                            "description": "ID of the sandbox instance",
-                        },
-                        "error": {
-                            "type": "string",
-                            "description": "Error message if execution failed",
-                        },
-                    },
-                },
-                "credentials_fields": {
-                    "e2b_credentials": True,
-                    "anthropic_credentials": True,
-                },
-            },
-        ]
-
-        search_results = [
-            {"content_id": d["id"], "score": 0.9 - i * 0.1}
-            for i, d in enumerate(block_defs)
-        ]
-        mock_blocks = {
-            d["id"]: make_mock_block(
-                block_id=d["id"],
-                name=d["name"],
-                block_type=BlockType.STANDARD,
-                input_schema=d["input_schema"],
-                output_schema=d["output_schema"],
-                credentials_fields=d["credentials_fields"],
-            )
-            for d in block_defs
-        }
-
-        with patch(
-            "backend.api.features.chat.tools.find_block.unified_hybrid_search",
-            new_callable=AsyncMock,
-            return_value=(search_results, len(search_results)),
-        ), patch(
-            "backend.api.features.chat.tools.find_block.get_block",
-            side_effect=lambda bid: mock_blocks.get(bid),
-        ):
-            tool = FindBlockTool()
-            response = await tool._execute(
-                user_id=_TEST_USER_ID, session=session, query="test"
-            )
-
-        assert isinstance(response, BlockListResponse)
-        assert response.count == len(block_defs)
-
-        total_chars = len(response.model_dump_json())
-        avg_chars = total_chars // response.count
-
-        # Print for visibility in test output
-        print(f"\nTotal response size: {total_chars} chars")
-        print(f"Number of blocks: {response.count}")
-        print(f"Average chars per block: {avg_chars}")
-
-        # The old response was ~90K for 10 blocks (~9K per block).
-        # Previous optimization reduced it to ~1.5K per block (no raw JSON schemas).
-        # Now with only id/name/description, we expect ~300 chars per block.
-        assert avg_chars < 500, (
-            f"Average chars per block ({avg_chars}) exceeds 500. "
-            f"Total response: {total_chars} chars for {response.count} blocks."
-        )

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

@@ -25,7 +25,6 @@ class ResponseType(str, Enum):
     AGENT_SAVED = "agent_saved"
     CLARIFICATION_NEEDED = "clarification_needed"
     BLOCK_LIST = "block_list"
-    BLOCK_DETAILS = "block_details"
     BLOCK_OUTPUT = "block_output"
     DOC_SEARCH_RESULTS = "doc_search_results"
     DOC_PAGE = "doc_page"
@@ -41,9 +40,12 @@ class ResponseType(str, Enum):
     OPERATION_IN_PROGRESS = "operation_in_progress"
     # Input validation
     INPUT_VALIDATION_ERROR = "input_validation_error"
-    # Feature request types
-    FEATURE_REQUEST_SEARCH = "feature_request_search"
-    FEATURE_REQUEST_CREATED = "feature_request_created"
+    # Web fetch
+    WEB_FETCH = "web_fetch"
+    # Code execution
+    BASH_EXEC = "bash_exec"
+    # Operation status check
+    OPERATION_STATUS = "operation_status"
 
 
 # Base response model
@@ -338,6 +340,19 @@ class BlockInfoSummary(BaseModel):
     id: str
     name: str
     description: str
+    categories: list[str]
+    input_schema: dict[str, Any] = Field(
+        default_factory=dict,
+        description="Full JSON schema for block inputs",
+    )
+    output_schema: dict[str, Any] = Field(
+        default_factory=dict,
+        description="Full JSON schema for block outputs",
+    )
+    required_inputs: list[BlockInputFieldInfo] = Field(
+        default_factory=list,
+        description="List of input fields for this block",
+    )
 
 
 class BlockListResponse(ToolResponseBase):
@@ -347,25 +362,10 @@ class BlockListResponse(ToolResponseBase):
     blocks: list[BlockInfoSummary]
     count: int
     query: str
-
-
-class BlockDetails(BaseModel):
-    """Detailed block information."""
-
-    id: str
-    name: str
-    description: str
-    inputs: dict[str, Any] = {}
-    outputs: dict[str, Any] = {}
-    credentials: list[CredentialsMetaInput] = []
-
-
-class BlockDetailsResponse(ToolResponseBase):
-    """Response for block details (first run_block attempt)."""
-
-    type: ResponseType = ResponseType.BLOCK_DETAILS
-    block: BlockDetails
-    user_authenticated: bool = False
+    usage_hint: str = Field(
+        default="To execute a block, call run_block with block_id set to the block's "
+        "'id' field and input_data containing the fields listed in required_inputs."
+    )
 
 
 class BlockOutputResponse(ToolResponseBase):
@@ -435,32 +435,22 @@ class AsyncProcessingResponse(ToolResponseBase):
     task_id: str | None = None
 
 
-# Feature request models
-class FeatureRequestInfo(BaseModel):
-    """Information about a feature request issue."""
+class WebFetchResponse(ToolResponseBase):
+    """Response for web_fetch tool."""
 
-    id: str
-    identifier: str
-    title: str
-    description: str | None = None
+    type: ResponseType = ResponseType.WEB_FETCH
+    url: str
+    status_code: int
+    content_type: str
+    content: str
+    truncated: bool = False
 
 
-class FeatureRequestSearchResponse(ToolResponseBase):
-    """Response for search_feature_requests tool."""
+class BashExecResponse(ToolResponseBase):
+    """Response for bash_exec tool."""
 
-    type: ResponseType = ResponseType.FEATURE_REQUEST_SEARCH
-    results: list[FeatureRequestInfo]
-    count: int
-    query: str
-
-
-class FeatureRequestCreatedResponse(ToolResponseBase):
-    """Response for create_feature_request tool."""
-
-    type: ResponseType = ResponseType.FEATURE_REQUEST_CREATED
-    issue_id: str
-    issue_identifier: str
-    issue_title: str
-    issue_url: str
-    is_new_issue: bool  # False if added to existing
-    customer_name: str
+    type: ResponseType = ResponseType.BASH_EXEC
+    stdout: str
+    stderr: str
+    exit_code: int
+    timed_out: bool = False

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

@@ -23,11 +23,8 @@ from backend.util.exceptions import BlockError
 from .base import BaseTool
 from .helpers import get_inputs_from_schema
 from .models import (
-    BlockDetails,
-    BlockDetailsResponse,
     BlockOutputResponse,
     ErrorResponse,
-    InputValidationErrorResponse,
     SetupInfo,
     SetupRequirementsResponse,
     ToolResponseBase,
@@ -54,8 +51,8 @@ class RunBlockTool(BaseTool):
             "Execute a specific block with the provided input data. "
             "IMPORTANT: You MUST call find_block first to get the block's 'id' - "
             "do NOT guess or make up block IDs. "
-            "On first attempt (without input_data), returns detailed schema showing "
-            "required inputs and outputs. Then call again with proper input_data to execute."
+            "Use the 'id' from find_block results and provide input_data "
+            "matching the block's required_inputs."
         )
 
     @property
@@ -70,19 +67,11 @@ class RunBlockTool(BaseTool):
                         "NEVER guess this - always get it from find_block first."
                     ),
                 },
-                "block_name": {
-                    "type": "string",
-                    "description": (
-                        "The block's human-readable name from find_block results. "
-                        "Used for display purposes in the UI."
-                    ),
-                },
                 "input_data": {
                     "type": "object",
                     "description": (
-                        "Input values for the block. "
-                        "First call with empty {} to see the block's schema, "
-                        "then call again with proper values to execute."
+                        "Input values for the block. Use the 'required_inputs' field "
+                        "from find_block to see what fields are needed."
                     ),
                 },
             },
@@ -167,34 +156,6 @@ class RunBlockTool(BaseTool):
             await self._resolve_block_credentials(user_id, block, input_data)
         )
 
-        # Get block schemas for details/validation
-        try:
-            input_schema: dict[str, Any] = block.input_schema.jsonschema()
-        except Exception as e:
-            logger.warning(
-                "Failed to generate input schema for block %s: %s",
-                block_id,
-                e,
-            )
-            return ErrorResponse(
-                message=f"Block '{block.name}' has an invalid input schema",
-                error=str(e),
-                session_id=session_id,
-            )
-        try:
-            output_schema: dict[str, Any] = block.output_schema.jsonschema()
-        except Exception as e:
-            logger.warning(
-                "Failed to generate output schema for block %s: %s",
-                block_id,
-                e,
-            )
-            return ErrorResponse(
-                message=f"Block '{block.name}' has an invalid output schema",
-                error=str(e),
-                session_id=session_id,
-            )
-
         if missing_credentials:
             # Return setup requirements response with missing credentials
             credentials_fields_info = block.input_schema.get_credentials_fields_info()
@@ -227,53 +188,6 @@ class RunBlockTool(BaseTool):
                 graph_version=None,
             )
 
-        # Check if this is a first attempt (required inputs missing)
-        # Return block details so user can see what inputs are needed
-        credentials_fields = set(block.input_schema.get_credentials_fields().keys())
-        required_keys = set(input_schema.get("required", []))
-        required_non_credential_keys = required_keys - credentials_fields
-        provided_input_keys = set(input_data.keys()) - credentials_fields
-
-        # Check for unknown input fields
-        valid_fields = (
-            set(input_schema.get("properties", {}).keys()) - credentials_fields
-        )
-        unrecognized_fields = provided_input_keys - valid_fields
-        if unrecognized_fields:
-            return InputValidationErrorResponse(
-                message=(
-                    f"Unknown input field(s) provided: {', '.join(sorted(unrecognized_fields))}. "
-                    f"Block was not executed. Please use the correct field names from the schema."
-                ),
-                session_id=session_id,
-                unrecognized_fields=sorted(unrecognized_fields),
-                inputs=input_schema,
-            )
-
-        # Show details when not all required non-credential inputs are provided
-        if not (required_non_credential_keys <= provided_input_keys):
-            # Get credentials info for the response
-            credentials_meta = []
-            for field_name, cred_meta in matched_credentials.items():
-                credentials_meta.append(cred_meta)
-
-            return BlockDetailsResponse(
-                message=(
-                    f"Block '{block.name}' details. "
-                    "Provide input_data matching the inputs schema to execute the block."
-                ),
-                session_id=session_id,
-                block=BlockDetails(
-                    id=block_id,
-                    name=block.name,
-                    description=block.description or "",
-                    inputs=input_schema,
-                    outputs=output_schema,
-                    credentials=credentials_meta,
-                ),
-                user_authenticated=True,
-            )
-
         try:
             # Get or create user's workspace for CoPilot file operations
             workspace = await get_or_create_workspace(user_id)

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

@@ -1,15 +1,10 @@
-"""Tests for block execution guards and input validation in RunBlockTool."""
+"""Tests for block execution guards in RunBlockTool."""
 
-from unittest.mock import AsyncMock, MagicMock, patch
+from unittest.mock import MagicMock, patch
 
 import pytest
 
-from backend.api.features.chat.tools.models import (
-    BlockDetailsResponse,
-    BlockOutputResponse,
-    ErrorResponse,
-    InputValidationErrorResponse,
-)
+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
 
@@ -33,39 +28,6 @@ def make_mock_block(
     return mock
 
 
-def make_mock_block_with_schema(
-    block_id: str,
-    name: str,
-    input_properties: dict,
-    required_fields: list[str],
-    output_properties: dict | None = None,
-):
-    """Create a mock block with a defined input/output schema for validation tests."""
-    mock = MagicMock()
-    mock.id = block_id
-    mock.name = name
-    mock.block_type = BlockType.STANDARD
-    mock.disabled = False
-    mock.description = f"Test block: {name}"
-
-    input_schema = {
-        "properties": input_properties,
-        "required": required_fields,
-    }
-    mock.input_schema = MagicMock()
-    mock.input_schema.jsonschema.return_value = input_schema
-    mock.input_schema.get_credentials_fields_info.return_value = {}
-    mock.input_schema.get_credentials_fields.return_value = {}
-
-    output_schema = {
-        "properties": output_properties or {"result": {"type": "string"}},
-    }
-    mock.output_schema = MagicMock()
-    mock.output_schema.jsonschema.return_value = output_schema
-
-    return mock
-
-
 class TestRunBlockFiltering:
     """Tests for block execution guards in RunBlockTool."""
 
@@ -142,221 +104,3 @@ class TestRunBlockFiltering:
         # (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
-
-
-class TestRunBlockInputValidation:
-    """Tests for input field validation in RunBlockTool.
-
-    run_block rejects unknown input field names with InputValidationErrorResponse,
-    preventing silent failures where incorrect keys would be ignored and the block
-    would execute with default values instead of the caller's intended values.
-    """
-
-    @pytest.mark.asyncio(loop_scope="session")
-    async def test_unknown_input_fields_are_rejected(self):
-        """run_block rejects unknown input fields instead of silently ignoring them.
-
-        Scenario: The AI Text Generator block has a field called 'model' (for LLM model
-        selection), but the LLM calling the tool guesses wrong and sends 'LLM_Model'
-        instead. The block should reject the request and return the valid schema.
-        """
-        session = make_session(user_id=_TEST_USER_ID)
-
-        mock_block = make_mock_block_with_schema(
-            block_id="ai-text-gen-id",
-            name="AI Text Generator",
-            input_properties={
-                "prompt": {"type": "string", "description": "The prompt to send"},
-                "model": {
-                    "type": "string",
-                    "description": "The LLM model to use",
-                    "default": "gpt-4o-mini",
-                },
-                "sys_prompt": {
-                    "type": "string",
-                    "description": "System prompt",
-                    "default": "",
-                },
-            },
-            required_fields=["prompt"],
-            output_properties={"response": {"type": "string"}},
-        )
-
-        with patch(
-            "backend.api.features.chat.tools.run_block.get_block",
-            return_value=mock_block,
-        ):
-            tool = RunBlockTool()
-
-            # Provide 'prompt' (correct) but 'LLM_Model' instead of 'model' (wrong key)
-            response = await tool._execute(
-                user_id=_TEST_USER_ID,
-                session=session,
-                block_id="ai-text-gen-id",
-                input_data={
-                    "prompt": "Write a haiku about coding",
-                    "LLM_Model": "claude-opus-4-6",  # WRONG KEY - should be 'model'
-                },
-            )
-
-        assert isinstance(response, InputValidationErrorResponse)
-        assert "LLM_Model" in response.unrecognized_fields
-        assert "Block was not executed" in response.message
-        assert "inputs" in response.model_dump()  # valid schema included
-
-    @pytest.mark.asyncio(loop_scope="session")
-    async def test_multiple_wrong_keys_are_all_reported(self):
-        """All unrecognized field names are reported in a single error response."""
-        session = make_session(user_id=_TEST_USER_ID)
-
-        mock_block = make_mock_block_with_schema(
-            block_id="ai-text-gen-id",
-            name="AI Text Generator",
-            input_properties={
-                "prompt": {"type": "string"},
-                "model": {"type": "string", "default": "gpt-4o-mini"},
-                "sys_prompt": {"type": "string", "default": ""},
-                "retry": {"type": "integer", "default": 3},
-            },
-            required_fields=["prompt"],
-        )
-
-        with patch(
-            "backend.api.features.chat.tools.run_block.get_block",
-            return_value=mock_block,
-        ):
-            tool = RunBlockTool()
-
-            response = await tool._execute(
-                user_id=_TEST_USER_ID,
-                session=session,
-                block_id="ai-text-gen-id",
-                input_data={
-                    "prompt": "Hello",  # correct
-                    "llm_model": "claude-opus-4-6",  # WRONG - should be 'model'
-                    "system_prompt": "Be helpful",  # WRONG - should be 'sys_prompt'
-                    "retries": 5,  # WRONG - should be 'retry'
-                },
-            )
-
-        assert isinstance(response, InputValidationErrorResponse)
-        assert set(response.unrecognized_fields) == {
-            "llm_model",
-            "system_prompt",
-            "retries",
-        }
-        assert "Block was not executed" in response.message
-
-    @pytest.mark.asyncio(loop_scope="session")
-    async def test_unknown_fields_rejected_even_with_missing_required(self):
-        """Unknown fields are caught before the missing-required-fields check."""
-        session = make_session(user_id=_TEST_USER_ID)
-
-        mock_block = make_mock_block_with_schema(
-            block_id="ai-text-gen-id",
-            name="AI Text Generator",
-            input_properties={
-                "prompt": {"type": "string"},
-                "model": {"type": "string", "default": "gpt-4o-mini"},
-            },
-            required_fields=["prompt"],
-        )
-
-        with patch(
-            "backend.api.features.chat.tools.run_block.get_block",
-            return_value=mock_block,
-        ):
-            tool = RunBlockTool()
-
-            # 'prompt' is missing AND 'LLM_Model' is an unknown field
-            response = await tool._execute(
-                user_id=_TEST_USER_ID,
-                session=session,
-                block_id="ai-text-gen-id",
-                input_data={
-                    "LLM_Model": "claude-opus-4-6",  # wrong key, and 'prompt' is missing
-                },
-            )
-
-        # Unknown fields are caught first
-        assert isinstance(response, InputValidationErrorResponse)
-        assert "LLM_Model" in response.unrecognized_fields
-
-    @pytest.mark.asyncio(loop_scope="session")
-    async def test_correct_inputs_still_execute(self):
-        """Correct input field names pass validation and the block executes."""
-        session = make_session(user_id=_TEST_USER_ID)
-
-        mock_block = make_mock_block_with_schema(
-            block_id="ai-text-gen-id",
-            name="AI Text Generator",
-            input_properties={
-                "prompt": {"type": "string"},
-                "model": {"type": "string", "default": "gpt-4o-mini"},
-            },
-            required_fields=["prompt"],
-        )
-
-        async def mock_execute(input_data, **kwargs):
-            yield "response", "Generated text"
-
-        mock_block.execute = mock_execute
-
-        with (
-            patch(
-                "backend.api.features.chat.tools.run_block.get_block",
-                return_value=mock_block,
-            ),
-            patch(
-                "backend.api.features.chat.tools.run_block.get_or_create_workspace",
-                new_callable=AsyncMock,
-                return_value=MagicMock(id="test-workspace-id"),
-            ),
-        ):
-            tool = RunBlockTool()
-
-            response = await tool._execute(
-                user_id=_TEST_USER_ID,
-                session=session,
-                block_id="ai-text-gen-id",
-                input_data={
-                    "prompt": "Write a haiku",
-                    "model": "gpt-4o-mini",  # correct field name
-                },
-            )
-
-        assert isinstance(response, BlockOutputResponse)
-        assert response.success is True
-
-    @pytest.mark.asyncio(loop_scope="session")
-    async def test_missing_required_fields_returns_details(self):
-        """Missing required fields returns BlockDetailsResponse with schema."""
-        session = make_session(user_id=_TEST_USER_ID)
-
-        mock_block = make_mock_block_with_schema(
-            block_id="ai-text-gen-id",
-            name="AI Text Generator",
-            input_properties={
-                "prompt": {"type": "string"},
-                "model": {"type": "string", "default": "gpt-4o-mini"},
-            },
-            required_fields=["prompt"],
-        )
-
-        with patch(
-            "backend.api.features.chat.tools.run_block.get_block",
-            return_value=mock_block,
-        ):
-            tool = RunBlockTool()
-
-            # Only provide valid optional field, missing required 'prompt'
-            response = await tool._execute(
-                user_id=_TEST_USER_ID,
-                session=session,
-                block_id="ai-text-gen-id",
-                input_data={
-                    "model": "gpt-4o-mini",  # valid but optional
-                },
-            )
-
-        assert isinstance(response, BlockDetailsResponse)

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

@@ -0,0 +1,267 @@
+"""Sandbox execution utilities for code execution tools.
+
+Provides filesystem + network isolated command execution using **bubblewrap**
+(``bwrap``): whitelist-only filesystem (only system dirs visible read-only),
+writable workspace only, clean environment, network blocked.
+
+Tools that call :func:`run_sandboxed` must first check :func:`has_full_sandbox`
+and refuse to run if bubblewrap is not available.
+"""
+
+import asyncio
+import logging
+import os
+import platform
+import shutil
+
+logger = logging.getLogger(__name__)
+
+# Output limits — prevent blowing up LLM context
+_MAX_OUTPUT_CHARS = 50_000
+_DEFAULT_TIMEOUT = 30
+_MAX_TIMEOUT = 120
+
+
+# ---------------------------------------------------------------------------
+# Sandbox capability detection (cached at first call)
+# ---------------------------------------------------------------------------
+
+_BWRAP_AVAILABLE: bool | None = None
+
+
+def has_full_sandbox() -> bool:
+    """Return True if bubblewrap is available (filesystem + network isolation).
+
+    On non-Linux platforms (macOS), always returns False.
+    """
+    global _BWRAP_AVAILABLE
+    if _BWRAP_AVAILABLE is None:
+        _BWRAP_AVAILABLE = (
+            platform.system() == "Linux" and shutil.which("bwrap") is not None
+        )
+    return _BWRAP_AVAILABLE
+
+
+WORKSPACE_PREFIX = "/tmp/copilot-"
+
+
+def make_session_path(session_id: str) -> str:
+    """Build a sanitized, session-specific path under :data:`WORKSPACE_PREFIX`.
+
+    Shared by both the SDK working-directory setup and the sandbox tools so
+    they always resolve to the same directory for a given session.
+
+    Steps:
+        1. Strip all characters except ``[A-Za-z0-9-]``.
+        2. Construct ``/tmp/copilot-<safe_id>``.
+        3. Validate via ``os.path.normpath`` + ``startswith`` (CodeQL-recognised
+           sanitizer) to prevent path traversal.
+
+    Raises:
+        ValueError: If the resulting path escapes the prefix.
+    """
+    import re
+
+    safe_id = re.sub(r"[^A-Za-z0-9-]", "", session_id)
+    if not safe_id:
+        safe_id = "default"
+    path = os.path.normpath(f"{WORKSPACE_PREFIX}{safe_id}")
+    if not path.startswith(WORKSPACE_PREFIX):
+        raise ValueError(f"Session path escaped prefix: {path}")
+    return path
+
+
+def get_workspace_dir(session_id: str) -> str:
+    """Get or create the workspace directory for a session.
+
+    Uses :func:`make_session_path` — the same path the SDK uses — so that
+    bash_exec shares the workspace with the SDK file tools.
+    """
+    workspace = make_session_path(session_id)
+    os.makedirs(workspace, exist_ok=True)
+    return workspace
+
+
+# ---------------------------------------------------------------------------
+# Bubblewrap command builder
+# ---------------------------------------------------------------------------
+
+# System directories mounted read-only inside the sandbox.
+# ONLY these are visible — /app, /root, /home, /opt, /var etc. are NOT accessible.
+_SYSTEM_RO_BINDS = [
+    "/usr",  # binaries, libraries, Python interpreter
+    "/etc",  # system config: ld.so, locale, passwd, alternatives
+]
+
+# Compat paths: symlinks to /usr/* on modern Debian, real dirs on older systems.
+# On Debian 13 these are symlinks (e.g. /bin -> usr/bin).  bwrap --ro-bind
+# can't create a symlink target, so we detect and use --symlink instead.
+# /lib64 is critical: the ELF dynamic linker lives at /lib64/ld-linux-x86-64.so.2.
+_COMPAT_PATHS = [
+    ("/bin", "usr/bin"),  # -> /usr/bin on Debian 13
+    ("/sbin", "usr/sbin"),  # -> /usr/sbin on Debian 13
+    ("/lib", "usr/lib"),  # -> /usr/lib on Debian 13
+    ("/lib64", "usr/lib64"),  # 64-bit libraries / ELF interpreter
+]
+
+# Resource limits to prevent fork bombs, memory exhaustion, and disk abuse.
+# Applied via ulimit inside the sandbox before exec'ing the user command.
+_RESOURCE_LIMITS = (
+    "ulimit -u 64"  # max 64 processes  (prevents fork bombs)
+    " -v 524288"  # 512 MB virtual memory
+    " -f 51200"  # 50 MB max file size  (1024-byte blocks)
+    " -n 256"  # 256 open file descriptors
+    " 2>/dev/null"
+)
+
+
+def _build_bwrap_command(
+    command: list[str], cwd: str, env: dict[str, str]
+) -> list[str]:
+    """Build a bubblewrap command with strict filesystem + network isolation.
+
+    Security model:
+    - **Whitelist-only filesystem**: only system directories (``/usr``, ``/etc``,
+      ``/bin``, ``/lib``) are mounted read-only.  Application code (``/app``),
+      home directories, ``/var``, ``/opt``, etc. are NOT accessible at all.
+    - **Writable workspace only**: the per-session workspace is the sole
+      writable path.
+    - **Clean environment**: ``--clearenv`` wipes all inherited env vars.
+      Only the explicitly-passed safe env vars are set inside the sandbox.
+    - **Network isolation**: ``--unshare-net`` blocks all network access.
+    - **Resource limits**: ulimit caps on processes (64), memory (512MB),
+      file size (50MB), and open FDs (256) to prevent fork bombs and abuse.
+    - **New session**: prevents terminal control escape.
+    - **Die with parent**: prevents orphaned sandbox processes.
+    """
+    cmd = [
+        "bwrap",
+        # Create a new user namespace so bwrap can set up sandboxing
+        # inside unprivileged Docker containers (no CAP_SYS_ADMIN needed).
+        "--unshare-user",
+        # Wipe all inherited environment variables (API keys, secrets, etc.)
+        "--clearenv",
+    ]
+
+    # Set only the safe env vars inside the sandbox
+    for key, value in env.items():
+        cmd.extend(["--setenv", key, value])
+
+    # System directories: read-only
+    for path in _SYSTEM_RO_BINDS:
+        cmd.extend(["--ro-bind", path, path])
+
+    # Compat paths: use --symlink when host path is a symlink (Debian 13),
+    # --ro-bind when it's a real directory (older distros).
+    for path, symlink_target in _COMPAT_PATHS:
+        if os.path.islink(path):
+            cmd.extend(["--symlink", symlink_target, path])
+        elif os.path.exists(path):
+            cmd.extend(["--ro-bind", path, path])
+
+    # Wrap the user command with resource limits:
+    #   sh -c 'ulimit ...; exec "$@"' -- <original command>
+    # `exec "$@"` replaces the shell so there's no extra process overhead,
+    # and properly handles arguments with spaces.
+    limited_command = [
+        "sh",
+        "-c",
+        f'{_RESOURCE_LIMITS}; exec "$@"',
+        "--",
+        *command,
+    ]
+
+    cmd.extend(
+        [
+            # Fresh virtual filesystems
+            "--dev",
+            "/dev",
+            "--proc",
+            "/proc",
+            "--tmpfs",
+            "/tmp",
+            # Workspace bind AFTER --tmpfs /tmp so it's visible through the tmpfs.
+            # (workspace lives under /tmp/copilot-<session>)
+            "--bind",
+            cwd,
+            cwd,
+            # Isolation
+            "--unshare-net",
+            "--die-with-parent",
+            "--new-session",
+            "--chdir",
+            cwd,
+            "--",
+            *limited_command,
+        ]
+    )
+
+    return cmd
+
+
+# ---------------------------------------------------------------------------
+# Public API
+# ---------------------------------------------------------------------------
+
+
+async def run_sandboxed(
+    command: list[str],
+    cwd: str,
+    timeout: int = _DEFAULT_TIMEOUT,
+    env: dict[str, str] | None = None,
+) -> tuple[str, str, int, bool]:
+    """Run a command inside a bubblewrap sandbox.
+
+    Callers **must** check :func:`has_full_sandbox` before calling this
+    function.  If bubblewrap is not available, this function raises
+    :class:`RuntimeError` rather than running unsandboxed.
+
+    Returns:
+        (stdout, stderr, exit_code, timed_out)
+    """
+    if not has_full_sandbox():
+        raise RuntimeError(
+            "run_sandboxed() requires bubblewrap but bwrap is not available. "
+            "Callers must check has_full_sandbox() before calling this function."
+        )
+
+    timeout = min(max(timeout, 1), _MAX_TIMEOUT)
+
+    safe_env = {
+        "PATH": "/usr/local/bin:/usr/bin:/bin",
+        "HOME": cwd,
+        "TMPDIR": cwd,
+        "LANG": "en_US.UTF-8",
+        "PYTHONDONTWRITEBYTECODE": "1",
+        "PYTHONIOENCODING": "utf-8",
+    }
+    if env:
+        safe_env.update(env)
+
+    full_command = _build_bwrap_command(command, cwd, safe_env)
+
+    try:
+        proc = await asyncio.create_subprocess_exec(
+            *full_command,
+            stdout=asyncio.subprocess.PIPE,
+            stderr=asyncio.subprocess.PIPE,
+            cwd=cwd,
+            env=safe_env,
+        )
+
+        try:
+            stdout_bytes, stderr_bytes = await asyncio.wait_for(
+                proc.communicate(), timeout=timeout
+            )
+            stdout = stdout_bytes.decode("utf-8", errors="replace")[:_MAX_OUTPUT_CHARS]
+            stderr = stderr_bytes.decode("utf-8", errors="replace")[:_MAX_OUTPUT_CHARS]
+            return stdout, stderr, proc.returncode or 0, False
+        except asyncio.TimeoutError:
+            proc.kill()
+            await proc.communicate()
+            return "", f"Execution timed out after {timeout}s", -1, True
+
+    except RuntimeError:
+        raise
+    except Exception as e:
+        return "", f"Sandbox error: {e}", -1, False

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

@@ -1,153 +0,0 @@
-"""Tests for BlockDetailsResponse in RunBlockTool."""
-
-from unittest.mock import AsyncMock, MagicMock, patch
-
-import pytest
-
-from backend.api.features.chat.tools.models import BlockDetailsResponse
-from backend.api.features.chat.tools.run_block import RunBlockTool
-from backend.blocks._base import BlockType
-from backend.data.model import CredentialsMetaInput
-from backend.integrations.providers import ProviderName
-
-from ._test_data import make_session
-
-_TEST_USER_ID = "test-user-run-block-details"
-
-
-def make_mock_block_with_inputs(
-    block_id: str, name: str, description: str = "Test description"
-):
-    """Create a mock block with input/output schemas for testing."""
-    mock = MagicMock()
-    mock.id = block_id
-    mock.name = name
-    mock.description = description
-    mock.block_type = BlockType.STANDARD
-    mock.disabled = False
-
-    # Input schema with non-credential fields
-    mock.input_schema = MagicMock()
-    mock.input_schema.jsonschema.return_value = {
-        "properties": {
-            "url": {"type": "string", "description": "URL to fetch"},
-            "method": {"type": "string", "description": "HTTP method"},
-        },
-        "required": ["url"],
-    }
-    mock.input_schema.get_credentials_fields.return_value = {}
-    mock.input_schema.get_credentials_fields_info.return_value = {}
-
-    # Output schema
-    mock.output_schema = MagicMock()
-    mock.output_schema.jsonschema.return_value = {
-        "properties": {
-            "response": {"type": "object", "description": "HTTP response"},
-            "error": {"type": "string", "description": "Error message"},
-        }
-    }
-
-    return mock
-
-
-@pytest.mark.asyncio(loop_scope="session")
-async def test_run_block_returns_details_when_no_input_provided():
-    """When run_block is called without input_data, it should return BlockDetailsResponse."""
-    session = make_session(user_id=_TEST_USER_ID)
-
-    # Create a block with inputs
-    http_block = make_mock_block_with_inputs(
-        "http-block-id", "HTTP Request", "Send HTTP requests"
-    )
-
-    with patch(
-        "backend.api.features.chat.tools.run_block.get_block",
-        return_value=http_block,
-    ):
-        # Mock credentials check to return no missing credentials
-        with patch.object(
-            RunBlockTool,
-            "_resolve_block_credentials",
-            new_callable=AsyncMock,
-            return_value=({}, []),  # (matched_credentials, missing_credentials)
-        ):
-            tool = RunBlockTool()
-            response = await tool._execute(
-                user_id=_TEST_USER_ID,
-                session=session,
-                block_id="http-block-id",
-                input_data={},  # Empty input data
-            )
-
-    # Should return BlockDetailsResponse showing the schema
-    assert isinstance(response, BlockDetailsResponse)
-    assert response.block.id == "http-block-id"
-    assert response.block.name == "HTTP Request"
-    assert response.block.description == "Send HTTP requests"
-    assert "url" in response.block.inputs["properties"]
-    assert "method" in response.block.inputs["properties"]
-    assert "response" in response.block.outputs["properties"]
-    assert response.user_authenticated is True
-
-
-@pytest.mark.asyncio(loop_scope="session")
-async def test_run_block_returns_details_when_only_credentials_provided():
-    """When only credentials are provided (no actual input), should return details."""
-    session = make_session(user_id=_TEST_USER_ID)
-
-    # Create a block with both credential and non-credential inputs
-    mock = MagicMock()
-    mock.id = "api-block-id"
-    mock.name = "API Call"
-    mock.description = "Make API calls"
-    mock.block_type = BlockType.STANDARD
-    mock.disabled = False
-
-    mock.input_schema = MagicMock()
-    mock.input_schema.jsonschema.return_value = {
-        "properties": {
-            "credentials": {"type": "object", "description": "API credentials"},
-            "endpoint": {"type": "string", "description": "API endpoint"},
-        },
-        "required": ["credentials", "endpoint"],
-    }
-    mock.input_schema.get_credentials_fields.return_value = {"credentials": True}
-    mock.input_schema.get_credentials_fields_info.return_value = {}
-
-    mock.output_schema = MagicMock()
-    mock.output_schema.jsonschema.return_value = {
-        "properties": {"result": {"type": "object"}}
-    }
-
-    with patch(
-        "backend.api.features.chat.tools.run_block.get_block",
-        return_value=mock,
-    ):
-        with patch.object(
-            RunBlockTool,
-            "_resolve_block_credentials",
-            new_callable=AsyncMock,
-            return_value=(
-                {
-                    "credentials": CredentialsMetaInput(
-                        id="cred-id",
-                        provider=ProviderName("test_provider"),
-                        type="api_key",
-                        title="Test Credential",
-                    )
-                },
-                [],
-            ),
-        ):
-            tool = RunBlockTool()
-            response = await tool._execute(
-                user_id=_TEST_USER_ID,
-                session=session,
-                block_id="api-block-id",
-                input_data={"credentials": {"some": "cred"}},  # Only credential
-            )
-
-    # Should return details because no non-credential inputs provided
-    assert isinstance(response, BlockDetailsResponse)
-    assert response.block.id == "api-block-id"
-    assert response.block.name == "API Call"

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

@@ -0,0 +1,156 @@
+"""Web fetch tool — safely retrieve public web page content."""
+
+import logging
+from typing import Any
+
+import aiohttp
+import html2text
+
+from backend.api.features.chat.model import ChatSession
+from backend.api.features.chat.tools.base import BaseTool
+from backend.api.features.chat.tools.models import (
+    ErrorResponse,
+    ToolResponseBase,
+    WebFetchResponse,
+)
+from backend.util.request import Requests
+
+logger = logging.getLogger(__name__)
+
+# Limits
+_MAX_CONTENT_BYTES = 102_400  # 100 KB download cap
+_MAX_OUTPUT_CHARS = 50_000  # 50K char truncation for LLM context
+_REQUEST_TIMEOUT = aiohttp.ClientTimeout(total=15)
+
+# Content types we'll read as text
+_TEXT_CONTENT_TYPES = {
+    "text/html",
+    "text/plain",
+    "text/xml",
+    "text/csv",
+    "text/markdown",
+    "application/json",
+    "application/xml",
+    "application/xhtml+xml",
+    "application/rss+xml",
+    "application/atom+xml",
+}
+
+
+def _is_text_content(content_type: str) -> bool:
+    base = content_type.split(";")[0].strip().lower()
+    return base in _TEXT_CONTENT_TYPES or base.startswith("text/")
+
+
+def _html_to_text(html: str) -> str:
+    h = html2text.HTML2Text()
+    h.ignore_links = False
+    h.ignore_images = True
+    h.body_width = 0
+    return h.handle(html)
+
+
+class WebFetchTool(BaseTool):
+    """Safely fetch content from a public URL using SSRF-protected HTTP."""
+
+    @property
+    def name(self) -> str:
+        return "web_fetch"
+
+    @property
+    def description(self) -> str:
+        return (
+            "Fetch the content of a public web page by URL. "
+            "Returns readable text extracted from HTML by default. "
+            "Useful for reading documentation, articles, and API responses. "
+            "Only supports HTTP/HTTPS GET requests to public URLs "
+            "(private/internal network addresses are blocked)."
+        )
+
+    @property
+    def parameters(self) -> dict[str, Any]:
+        return {
+            "type": "object",
+            "properties": {
+                "url": {
+                    "type": "string",
+                    "description": "The public HTTP/HTTPS URL to fetch.",
+                },
+                "extract_text": {
+                    "type": "boolean",
+                    "description": (
+                        "If true (default), extract readable text from HTML. "
+                        "If false, return raw content."
+                    ),
+                    "default": True,
+                },
+            },
+            "required": ["url"],
+        }
+
+    @property
+    def requires_auth(self) -> bool:
+        return False
+
+    async def _execute(
+        self,
+        user_id: str | None,
+        session: ChatSession,
+        **kwargs: Any,
+    ) -> ToolResponseBase:
+        url: str = (kwargs.get("url") or "").strip()
+        extract_text: bool = kwargs.get("extract_text", True)
+        session_id = session.session_id if session else None
+
+        if not url:
+            return ErrorResponse(
+                message="Please provide a URL to fetch.",
+                error="missing_url",
+                session_id=session_id,
+            )
+
+        try:
+            client = Requests(raise_for_status=False, retry_max_attempts=1)
+            response = await client.get(url, timeout=_REQUEST_TIMEOUT)
+        except ValueError as e:
+            # validate_url raises ValueError for SSRF / blocked IPs
+            return ErrorResponse(
+                message=f"URL blocked: {e}",
+                error="url_blocked",
+                session_id=session_id,
+            )
+        except Exception as e:
+            logger.warning(f"[web_fetch] Request failed for {url}: {e}")
+            return ErrorResponse(
+                message=f"Failed to fetch URL: {e}",
+                error="fetch_failed",
+                session_id=session_id,
+            )
+
+        content_type = response.headers.get("content-type", "")
+        if not _is_text_content(content_type):
+            return ErrorResponse(
+                message=f"Non-text content type: {content_type.split(';')[0]}",
+                error="unsupported_content_type",
+                session_id=session_id,
+            )
+
+        raw = response.content[:_MAX_CONTENT_BYTES]
+        text = raw.decode("utf-8", errors="replace")
+
+        if extract_text and "html" in content_type.lower():
+            text = _html_to_text(text)
+
+        truncated = len(text) > _MAX_OUTPUT_CHARS
+        if truncated:
+            text = text[:_MAX_OUTPUT_CHARS]
+
+        return WebFetchResponse(
+            message=f"Fetched {url}" + (" (truncated)" if truncated else ""),
+            url=response.url,
+            status_code=response.status,
+            content_type=content_type.split(";")[0].strip(),
+            content=text,
+            truncated=truncated,
+            session_id=session_id,
+        )

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

@@ -88,7 +88,9 @@ class ListWorkspaceFilesTool(BaseTool):
     @property
     def description(self) -> str:
         return (
-            "List files in the user's workspace. "
+            "List files in the user's persistent workspace (cloud storage). "
+            "These files survive across sessions. "
+            "For ephemeral session files, use the SDK Read/Glob tools instead. "
             "Returns file names, paths, sizes, and metadata. "
             "Optionally filter by path prefix."
         )
@@ -204,7 +206,9 @@ class ReadWorkspaceFileTool(BaseTool):
     @property
     def description(self) -> str:
         return (
-            "Read a file from the user's workspace. "
+            "Read a file from the user's persistent workspace (cloud storage). "
+            "These files survive across sessions. "
+            "For ephemeral session files, use the SDK Read tool instead. "
             "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. "
@@ -378,7 +382,9 @@ class WriteWorkspaceFileTool(BaseTool):
     @property
     def description(self) -> str:
         return (
-            "Write or create a file in the user's workspace. "
+            "Write or create a file in the user's persistent workspace (cloud storage). "
+            "These files survive across sessions. "
+            "For ephemeral session files, use the SDK Write tool instead. "
             "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. "
@@ -523,7 +529,7 @@ class DeleteWorkspaceFileTool(BaseTool):
     @property
     def description(self) -> str:
         return (
-            "Delete a file from the user's workspace. "
+            "Delete a file from the user's persistent workspace (cloud storage). "
             "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."

autogpt_platform/backend/backend/blocks/basic.py

@@ -126,7 +126,6 @@ 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/util/feature_flag.py

@@ -38,6 +38,7 @@ class Flag(str, Enum):
     AGENT_ACTIVITY = "agent-activity"
     ENABLE_PLATFORM_PAYMENT = "enable-platform-payment"
     CHAT = "chat"
+    COPILOT_SDK = "copilot-sdk"
 
 
 def is_configured() -> bool:

autogpt_platform/backend/backend/util/settings.py

@@ -368,10 +368,6 @@ class Config(UpdateTrackingModel["Config"], BaseSettings):
         default=600,
         description="The timeout in seconds for Agent Generator service requests (includes retries for rate limits)",
     )
-    agentgenerator_use_dummy: bool = Field(
-        default=False,
-        description="Use dummy agent generator responses for testing (bypasses external service)",
-    )
 
     enable_example_blocks: bool = Field(
         default=False,
@@ -662,17 +658,6 @@ class Secrets(UpdateTrackingModel["Secrets"], BaseSettings):
     mem0_api_key: str = Field(default="", description="Mem0 API key")
     elevenlabs_api_key: str = Field(default="", description="ElevenLabs API key")
 
-    linear_api_key: str = Field(
-        default="", description="Linear API key for system-level operations"
-    )
-    linear_feature_request_project_id: str = Field(
-        default="",
-        description="Linear project ID where feature requests are tracked",
-    )
-    linear_feature_request_team_id: str = Field(
-        default="",
-        description="Linear team ID used when creating feature request issues",
-    )
     linear_client_id: str = Field(default="", description="Linear client ID")
     linear_client_secret: str = Field(default="", description="Linear client secret")
 

autogpt_platform/backend/poetry.lock

@@ -441,14 +441,14 @@ develop = true
 colorama = "^0.4.6"
 cryptography = "^46.0"
 expiringdict = "^1.2.2"
-fastapi = "^0.128.7"
+fastapi = "^0.128.0"
 google-cloud-logging = "^3.13.0"
-launchdarkly-server-sdk = "^9.15.0"
+launchdarkly-server-sdk = "^9.14.1"
 pydantic = "^2.12.5"
 pydantic-settings = "^2.12.0"
 pyjwt = {version = "^2.11.0", extras = ["crypto"]}
 redis = "^6.2.0"
-supabase = "^2.28.0"
+supabase = "^2.27.2"
 uvicorn = "^0.40.0"
 
 [package.source]
@@ -897,6 +897,29 @@ files = [
     {file = "charset_normalizer-3.4.4.tar.gz", hash = "sha256:94537985111c35f28720e43603b8e7b43a6ecfb2ce1d3058bbe955b73404e21a"},
 ]
 
+[[package]]
+name = "claude-agent-sdk"
+version = "0.1.35"
+description = "Python SDK for Claude Code"
+optional = false
+python-versions = ">=3.10"
+groups = ["main"]
+files = [
+    {file = "claude_agent_sdk-0.1.35-py3-none-macosx_11_0_arm64.whl", hash = "sha256:df67f4deade77b16a9678b3a626c176498e40417f33b04beda9628287f375591"},
+    {file = "claude_agent_sdk-0.1.35-py3-none-manylinux_2_17_aarch64.whl", hash = "sha256:14963944f55ded7c8ed518feebfa5b4284aa6dd8d81aeff2e5b21a962ce65097"},
+    {file = "claude_agent_sdk-0.1.35-py3-none-manylinux_2_17_x86_64.whl", hash = "sha256:84344dcc535d179c1fc8a11c6f34c37c3b583447bdf09d869effb26514fd7a65"},
+    {file = "claude_agent_sdk-0.1.35-py3-none-win_amd64.whl", hash = "sha256:1b3d54b47448c93f6f372acd4d1757f047c3c1e8ef5804be7a1e3e53e2c79a5f"},
+    {file = "claude_agent_sdk-0.1.35.tar.gz", hash = "sha256:0f98e2b3c71ca85abfc042e7a35c648df88e87fda41c52e6779ef7b038dcbb52"},
+]
+
+[package.dependencies]
+anyio = ">=4.0.0"
+mcp = ">=0.1.0"
+typing-extensions = {version = ">=4.0.0", markers = "python_version < \"3.11\""}
+
+[package.extras]
+dev = ["anyio[trio] (>=4.0.0)", "mypy (>=1.0.0)", "pytest (>=7.0.0)", "pytest-asyncio (>=0.20.0)", "pytest-cov (>=4.0.0)", "ruff (>=0.1.0)"]
+
 [[package]]
 name = "cleo"
 version = "2.1.0"
@@ -1382,14 +1405,14 @@ tzdata = "*"
 
 [[package]]
 name = "fastapi"
-version = "0.128.7"
+version = "0.128.6"
 description = "FastAPI framework, high performance, easy to learn, fast to code, ready for production"
 optional = false
 python-versions = ">=3.9"
 groups = ["main"]
 files = [
-    {file = "fastapi-0.128.7-py3-none-any.whl", hash = "sha256:6bd9bd31cb7047465f2d3fa3ba3f33b0870b17d4eaf7cdb36d1576ab060ad662"},
-    {file = "fastapi-0.128.7.tar.gz", hash = "sha256:783c273416995486c155ad2c0e2b45905dedfaf20b9ef8d9f6a9124670639a24"},
+    {file = "fastapi-0.128.6-py3-none-any.whl", hash = "sha256:bb1c1ef87d6086a7132d0ab60869d6f1ee67283b20fbf84ec0003bd335099509"},
+    {file = "fastapi-0.128.6.tar.gz", hash = "sha256:0cb3946557e792d731b26a42b04912f16367e3c3135ea8290f620e234f2b604f"},
 ]
 
 [package.dependencies]
@@ -2593,6 +2616,18 @@ http2 = ["h2 (>=3,<5)"]
 socks = ["socksio (==1.*)"]
 zstd = ["zstandard (>=0.18.0)"]
 
+[[package]]
+name = "httpx-sse"
+version = "0.4.3"
+description = "Consume Server-Sent Event (SSE) messages with HTTPX."
+optional = false
+python-versions = ">=3.9"
+groups = ["main"]
+files = [
+    {file = "httpx_sse-0.4.3-py3-none-any.whl", hash = "sha256:0ac1c9fe3c0afad2e0ebb25a934a59f4c7823b60792691f779fad2c5568830fc"},
+    {file = "httpx_sse-0.4.3.tar.gz", hash = "sha256:9b1ed0127459a66014aec3c56bebd93da3c1bc8bb6618c8082039a44889a755d"},
+]
+
 [[package]]
 name = "huggingface-hub"
 version = "1.4.1"
@@ -3117,14 +3152,14 @@ urllib3 = ">=1.26.0,<3"
 
 [[package]]
 name = "launchdarkly-server-sdk"
-version = "9.15.0"
+version = "9.14.1"
 description = "LaunchDarkly SDK for Python"
 optional = false
-python-versions = ">=3.10"
+python-versions = ">=3.9"
 groups = ["main"]
 files = [
-    {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"},
+    {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"},
 ]
 
 [package.dependencies]
@@ -3310,6 +3345,39 @@ files = [
     {file = "mccabe-0.7.0.tar.gz", hash = "sha256:348e0240c33b60bbdf4e523192ef919f28cb2c3d7d5c7794f74009290f236325"},
 ]
 
+[[package]]
+name = "mcp"
+version = "1.26.0"
+description = "Model Context Protocol SDK"
+optional = false
+python-versions = ">=3.10"
+groups = ["main"]
+files = [
+    {file = "mcp-1.26.0-py3-none-any.whl", hash = "sha256:904a21c33c25aa98ddbeb47273033c435e595bbacfdb177f4bd87f6dceebe1ca"},
+    {file = "mcp-1.26.0.tar.gz", hash = "sha256:db6e2ef491eecc1a0d93711a76f28dec2e05999f93afd48795da1c1137142c66"},
+]
+
+[package.dependencies]
+anyio = ">=4.5"
+httpx = ">=0.27.1"
+httpx-sse = ">=0.4"
+jsonschema = ">=4.20.0"
+pydantic = ">=2.11.0,<3.0.0"
+pydantic-settings = ">=2.5.2"
+pyjwt = {version = ">=2.10.1", extras = ["crypto"]}
+python-multipart = ">=0.0.9"
+pywin32 = {version = ">=310", markers = "sys_platform == \"win32\""}
+sse-starlette = ">=1.6.1"
+starlette = ">=0.27"
+typing-extensions = ">=4.9.0"
+typing-inspection = ">=0.4.1"
+uvicorn = {version = ">=0.31.1", markers = "sys_platform != \"emscripten\""}
+
+[package.extras]
+cli = ["python-dotenv (>=1.0.0)", "typer (>=0.16.0)"]
+rich = ["rich (>=13.9.4)"]
+ws = ["websockets (>=15.0.1)"]
+
 [[package]]
 name = "mdurl"
 version = "0.1.2"
@@ -4728,14 +4796,14 @@ tests = ["coverage-conditional-plugin (>=0.9.0)", "portalocker[redis]", "pytest
 
 [[package]]
 name = "postgrest"
-version = "2.28.0"
+version = "2.27.3"
 description = "PostgREST client for Python. This library provides an ORM interface to PostgREST."
 optional = false
 python-versions = ">=3.9"
 groups = ["main"]
 files = [
-    {file = "postgrest-2.28.0-py3-none-any.whl", hash = "sha256:7bca2f24dd1a1bf8a3d586c7482aba6cd41662da6733045fad585b63b7f7df75"},
-    {file = "postgrest-2.28.0.tar.gz", hash = "sha256:c36b38646d25ea4255321d3d924ce70f8d20ec7799cb42c1221d6a818d4f6515"},
+    {file = "postgrest-2.27.3-py3-none-any.whl", hash = "sha256:ed79123af7127edd78d538bfe8351d277e45b1a36994a4dbf57ae27dde87a7b7"},
+    {file = "postgrest-2.27.3.tar.gz", hash = "sha256:c2e2679addfc8eaab23197bad7ddaee6cbb4cbe8c483ebd2d2e5219543037cc3"},
 ]
 
 [package.dependencies]
@@ -5994,7 +6062,7 @@ description = "Python for Window Extensions"
 optional = false
 python-versions = "*"
 groups = ["main"]
-markers = "platform_system == \"Windows\""
+markers = "sys_platform == \"win32\" or platform_system == \"Windows\""
 files = [
     {file = "pywin32-311-cp310-cp310-win32.whl", hash = "sha256:d03ff496d2a0cd4a5893504789d4a15399133fe82517455e78bad62efbb7f0a3"},
     {file = "pywin32-311-cp310-cp310-win_amd64.whl", hash = "sha256:797c2772017851984b97180b0bebe4b620bb86328e8a884bb626156295a63b3b"},
@@ -6260,14 +6328,14 @@ all = ["numpy"]
 
 [[package]]
 name = "realtime"
-version = "2.28.0"
+version = "2.27.3"
 description = ""
 optional = false
 python-versions = ">=3.9"
 groups = ["main"]
 files = [
-    {file = "realtime-2.28.0-py3-none-any.whl", hash = "sha256:db1bd59bab9b1fcc9f9d3b1a073bed35bf4994d720e6751f10031a58d57a3836"},
-    {file = "realtime-2.28.0.tar.gz", hash = "sha256:d18cedcebd6a8f22fcd509bc767f639761eb218b7b2b6f14fc4205b6259b50fc"},
+    {file = "realtime-2.27.3-py3-none-any.whl", hash = "sha256:f571115f86988e33c41c895cb3fba2eaa1b693aeaede3617288f44274ca90f43"},
+    {file = "realtime-2.27.3.tar.gz", hash = "sha256:02b082243107656a5ef3fb63e8e2ab4c40bc199abb45adb8a42ed63f089a1041"},
 ]
 
 [package.dependencies]
@@ -6974,6 +7042,28 @@ postgresql-psycopgbinary = ["psycopg[binary] (>=3.0.7)"]
 pymysql = ["pymysql"]
 sqlcipher = ["sqlcipher3_binary"]
 
+[[package]]
+name = "sse-starlette"
+version = "3.2.0"
+description = "SSE plugin for Starlette"
+optional = false
+python-versions = ">=3.9"
+groups = ["main"]
+files = [
+    {file = "sse_starlette-3.2.0-py3-none-any.whl", hash = "sha256:5876954bd51920fc2cd51baee47a080eb88a37b5b784e615abb0b283f801cdbf"},
+    {file = "sse_starlette-3.2.0.tar.gz", hash = "sha256:8127594edfb51abe44eac9c49e59b0b01f1039d0c7461c6fd91d4e03b70da422"},
+]
+
+[package.dependencies]
+anyio = ">=4.7.0"
+starlette = ">=0.49.1"
+
+[package.extras]
+daphne = ["daphne (>=4.2.0)"]
+examples = ["aiosqlite (>=0.21.0)", "fastapi (>=0.115.12)", "sqlalchemy[asyncio] (>=2.0.41)", "uvicorn (>=0.34.0)"]
+granian = ["granian (>=2.3.1)"]
+uvicorn = ["uvicorn (>=0.34.0)"]
+
 [[package]]
 name = "stagehand"
 version = "0.5.9"
@@ -7024,14 +7114,14 @@ full = ["httpx (>=0.27.0,<0.29.0)", "itsdangerous", "jinja2", "python-multipart
 
 [[package]]
 name = "storage3"
-version = "2.28.0"
+version = "2.27.3"
 description = "Supabase Storage client for Python."
 optional = false
 python-versions = ">=3.9"
 groups = ["main"]
 files = [
-    {file = "storage3-2.28.0-py3-none-any.whl", hash = "sha256:ecb50efd2ac71dabbdf97e99ad346eafa630c4c627a8e5a138ceb5fbbadae716"},
-    {file = "storage3-2.28.0.tar.gz", hash = "sha256:bc1d008aff67de7a0f2bd867baee7aadbcdb6f78f5a310b4f7a38e8c13c19865"},
+    {file = "storage3-2.27.3-py3-none-any.whl", hash = "sha256:11a05b7da84bccabeeea12d940bca3760cf63fe6ca441868677335cfe4fdfbe0"},
+    {file = "storage3-2.27.3.tar.gz", hash = "sha256:dc1a4a010cf36d5482c5cb6c1c28fc5f00e23284342b89e4ae43b5eae8501ddb"},
 ]
 
 [package.dependencies]
@@ -7091,35 +7181,35 @@ typing-extensions = {version = ">=4.5.0", markers = "python_version >= \"3.7\""}
 
 [[package]]
 name = "supabase"
-version = "2.28.0"
+version = "2.27.3"
 description = "Supabase client for Python."
 optional = false
 python-versions = ">=3.9"
 groups = ["main"]
 files = [
-    {file = "supabase-2.28.0-py3-none-any.whl", hash = "sha256:42776971c7d0ccca16034df1ab96a31c50228eb1eb19da4249ad2f756fc20272"},
-    {file = "supabase-2.28.0.tar.gz", hash = "sha256:aea299aaab2a2eed3c57e0be7fc035c6807214194cce795a3575add20268ece1"},
+    {file = "supabase-2.27.3-py3-none-any.whl", hash = "sha256:082a74642fcf9954693f1ce8c251baf23e4bda26ffdbc8dcd4c99c82e60d69ff"},
+    {file = "supabase-2.27.3.tar.gz", hash = "sha256:5e5a348232ac4315c1032ddd687278f0b982465471f0cbb52bca7e6a66495ff3"},
 ]
 
 [package.dependencies]
 httpx = ">=0.26,<0.29"
-postgrest = "2.28.0"
-realtime = "2.28.0"
-storage3 = "2.28.0"
-supabase-auth = "2.28.0"
-supabase-functions = "2.28.0"
+postgrest = "2.27.3"
+realtime = "2.27.3"
+storage3 = "2.27.3"
+supabase-auth = "2.27.3"
+supabase-functions = "2.27.3"
 yarl = ">=1.22.0"
 
 [[package]]
 name = "supabase-auth"
-version = "2.28.0"
+version = "2.27.3"
 description = "Python Client Library for Supabase Auth"
 optional = false
 python-versions = ">=3.9"
 groups = ["main"]
 files = [
-    {file = "supabase_auth-2.28.0-py3-none-any.whl", hash = "sha256:2ac85026cc285054c7fa6d41924f3a333e9ec298c013e5b5e1754039ba7caec9"},
-    {file = "supabase_auth-2.28.0.tar.gz", hash = "sha256:2bb8f18ff39934e44b28f10918db965659f3735cd6fbfcc022fe0b82dbf8233e"},
+    {file = "supabase_auth-2.27.3-py3-none-any.whl", hash = "sha256:82a4262eaad85383319d394dab0eea11fcf3ebd774062aef8ea3874ae2f02579"},
+    {file = "supabase_auth-2.27.3.tar.gz", hash = "sha256:39894d4bc60b6f23b5cff4d0d7d4c1659e5d69563cadf014d4896f780ca8ca78"},
 ]
 
 [package.dependencies]
@@ -7129,14 +7219,14 @@ pyjwt = {version = ">=2.10.1", extras = ["crypto"]}
 
 [[package]]
 name = "supabase-functions"
-version = "2.28.0"
+version = "2.27.3"
 description = "Library for Supabase Functions"
 optional = false
 python-versions = ">=3.9"
 groups = ["main"]
 files = [
-    {file = "supabase_functions-2.28.0-py3-none-any.whl", hash = "sha256:30bf2d586f8df285faf0621bb5d5bb3ec3157234fc820553ca156f009475e4ae"},
-    {file = "supabase_functions-2.28.0.tar.gz", hash = "sha256:db3dddfc37aca5858819eb461130968473bd8c75bd284581013958526dac718b"},
+    {file = "supabase_functions-2.27.3-py3-none-any.whl", hash = "sha256:9d14a931d49ede1c6cf5fbfceb11c44061535ba1c3f310f15384964d86a83d9e"},
+    {file = "supabase_functions-2.27.3.tar.gz", hash = "sha256:e954f1646da8ca6e7e16accef58d0884a5f97b25956ee98e7d4927a210ed92f9"},
 ]
 
 [package.dependencies]
@@ -8440,4 +8530,4 @@ cffi = ["cffi (>=1.17,<2.0) ; platform_python_implementation != \"PyPy\" and pyt
 [metadata]
 lock-version = "2.1"
 python-versions = ">=3.10,<3.14"
-content-hash = "fa9c5deadf593e815dd2190f58e22152373900603f5f244b9616cd721de84d2f"
+content-hash = "942dea6daf671c3be65a22f3445feda26c1af9409d7173765e9a0742f0aa05dc"

autogpt_platform/backend/pyproject.toml

@@ -16,6 +16,7 @@ anthropic = "^0.79.0"
 apscheduler = "^3.11.1"
 autogpt-libs = { path = "../autogpt_libs", develop = true }
 bleach = { extras = ["css"], version = "^6.2.0" }
+claude-agent-sdk = "^0.1.0"
 click = "^8.2.0"
 cryptography = "^46.0"
 discord-py = "^2.5.2"
@@ -65,7 +66,7 @@ sentry-sdk = {extras = ["anthropic", "fastapi", "launchdarkly", "openai", "sqlal
 sqlalchemy = "^2.0.40"
 strenum = "^0.4.9"
 stripe = "^11.5.0"
-supabase = "2.28.0"
+supabase = "2.27.3"
 tenacity = "^9.1.4"
 todoist-api-python = "^2.1.7"
 tweepy = "^4.16.0"

autogpt_platform/backend/test/agent_generator/test_service.py

@@ -25,7 +25,6 @@ class TestServiceConfiguration:
         """Test that external service is not configured when host is empty."""
         mock_settings = MagicMock()
         mock_settings.config.agentgenerator_host = ""
-        mock_settings.config.agentgenerator_use_dummy = False
 
         with patch.object(service, "_get_settings", return_value=mock_settings):
             assert service.is_external_service_configured() is False

autogpt_platform/backend/test/chat/test_security_hooks.py

@@ -0,0 +1,133 @@
+"""Tests for SDK security hooks — workspace paths, tool access, and deny messages.
+
+These are pure unit tests with no external dependencies (no SDK, no DB, no server).
+They validate that the security hooks correctly block unauthorized paths,
+tool access, and dangerous input patterns.
+
+Note: Bash command validation was removed — the SDK built-in Bash tool is not in
+allowed_tools, and the bash_exec MCP tool has kernel-level network isolation
+(unshare --net) making command-level parsing unnecessary.
+"""
+
+from backend.api.features.chat.sdk.security_hooks import (
+    _validate_tool_access,
+    _validate_workspace_path,
+)
+
+SDK_CWD = "/tmp/copilot-test-session"
+
+
+def _is_denied(result: dict) -> bool:
+    hook = result.get("hookSpecificOutput", {})
+    return hook.get("permissionDecision") == "deny"
+
+
+def _reason(result: dict) -> str:
+    return result.get("hookSpecificOutput", {}).get("permissionDecisionReason", "")
+
+
+# ============================================================
+# Workspace path validation (Read, Write, Edit, etc.)
+# ============================================================
+
+
+class TestWorkspacePathValidation:
+    def test_path_in_workspace(self):
+        result = _validate_workspace_path(
+            "Read", {"file_path": f"{SDK_CWD}/file.txt"}, SDK_CWD
+        )
+        assert not _is_denied(result)
+
+    def test_path_outside_workspace(self):
+        result = _validate_workspace_path("Read", {"file_path": "/etc/passwd"}, SDK_CWD)
+        assert _is_denied(result)
+
+    def test_tool_results_allowed(self):
+        result = _validate_workspace_path(
+            "Read",
+            {"file_path": "~/.claude/projects/abc/tool-results/out.txt"},
+            SDK_CWD,
+        )
+        assert not _is_denied(result)
+
+    def test_claude_settings_blocked(self):
+        result = _validate_workspace_path(
+            "Read", {"file_path": "~/.claude/settings.json"}, SDK_CWD
+        )
+        assert _is_denied(result)
+
+    def test_claude_projects_without_tool_results(self):
+        result = _validate_workspace_path(
+            "Read", {"file_path": "~/.claude/projects/abc/credentials.json"}, SDK_CWD
+        )
+        assert _is_denied(result)
+
+    def test_no_path_allowed(self):
+        """Glob/Grep without path defaults to cwd — should be allowed."""
+        result = _validate_workspace_path("Grep", {"pattern": "foo"}, SDK_CWD)
+        assert not _is_denied(result)
+
+    def test_path_traversal_with_dotdot(self):
+        result = _validate_workspace_path(
+            "Read", {"file_path": f"{SDK_CWD}/../../../etc/passwd"}, SDK_CWD
+        )
+        assert _is_denied(result)
+
+
+# ============================================================
+# Tool access validation
+# ============================================================
+
+
+class TestToolAccessValidation:
+    def test_blocked_tools(self):
+        for tool in ("bash", "shell", "exec", "terminal", "command"):
+            result = _validate_tool_access(tool, {})
+            assert _is_denied(result), f"Tool '{tool}' should be blocked"
+
+    def test_bash_builtin_blocked(self):
+        """SDK built-in Bash (capital) is blocked as defence-in-depth."""
+        result = _validate_tool_access("Bash", {"command": "echo hello"}, SDK_CWD)
+        assert _is_denied(result)
+        assert "Bash" in _reason(result)
+
+    def test_workspace_tools_delegate(self):
+        result = _validate_tool_access(
+            "Read", {"file_path": f"{SDK_CWD}/file.txt"}, SDK_CWD
+        )
+        assert not _is_denied(result)
+
+    def test_dangerous_pattern_blocked(self):
+        result = _validate_tool_access("SomeUnknownTool", {"data": "sudo rm -rf /"})
+        assert _is_denied(result)
+
+    def test_safe_unknown_tool_allowed(self):
+        result = _validate_tool_access("SomeSafeTool", {"data": "hello world"})
+        assert not _is_denied(result)
+
+
+# ============================================================
+# Deny message quality (ntindle feedback)
+# ============================================================
+
+
+class TestDenyMessageClarity:
+    """Deny messages must include [SECURITY] and 'cannot be bypassed'
+    so the model knows the restriction is enforced, not a suggestion."""
+
+    def test_blocked_tool_message(self):
+        reason = _reason(_validate_tool_access("bash", {}))
+        assert "[SECURITY]" in reason
+        assert "cannot be bypassed" in reason
+
+    def test_bash_builtin_blocked_message(self):
+        reason = _reason(_validate_tool_access("Bash", {"command": "echo hello"}))
+        assert "[SECURITY]" in reason
+        assert "cannot be bypassed" in reason
+
+    def test_workspace_path_message(self):
+        reason = _reason(
+            _validate_workspace_path("Read", {"file_path": "/etc/passwd"}, SDK_CWD)
+        )
+        assert "[SECURITY]" in reason
+        assert "cannot be bypassed" in reason

autogpt_platform/docker-compose.platform.yml

@@ -37,7 +37,7 @@ services:
       context: ../
       dockerfile: autogpt_platform/backend/Dockerfile
       target: migrate
-    command: ["sh", "-c", "prisma generate && python3 gen_prisma_types_stub.py && prisma migrate deploy"]
+    command: ["sh", "-c", "poetry run prisma generate && poetry run gen-prisma-stub && poetry run prisma migrate deploy"]
     develop:
       watch:
         - path: ./
@@ -56,7 +56,7 @@ services:
       test:
         [
           "CMD-SHELL",
-          "prisma migrate status | grep -q 'No pending migrations' || exit 1",
+          "poetry run prisma migrate status | grep -q 'No pending migrations' || exit 1",
         ]
       interval: 30s
       timeout: 10s

autogpt_platform/frontend/instrumentation-client.ts

@@ -22,11 +22,6 @@ Sentry.init({
 
   enabled: shouldEnable,
 
-  // Suppress cross-origin stylesheet errors from Sentry Replay (rrweb)
-  // serializing DOM snapshots with cross-origin stylesheets
-  // (e.g., from browser extensions or CDN-loaded CSS)
-  ignoreErrors: [/Not allowed to access cross-origin stylesheet/],
-
   // Add optional integrations for additional features
   integrations: [
     Sentry.captureConsoleIntegration(),

autogpt_platform/frontend/src/app/(platform)/copilot/components/ChatMessagesContainer/ChatMessagesContainer.tsx

@@ -15,15 +15,12 @@ import { ToolUIPart, UIDataTypes, UIMessage, UITools } from "ai";
 import { useEffect, useRef, useState } from "react";
 import { CreateAgentTool } from "../../tools/CreateAgent/CreateAgent";
 import { EditAgentTool } from "../../tools/EditAgent/EditAgent";
-import {
-  CreateFeatureRequestTool,
-  SearchFeatureRequestsTool,
-} from "../../tools/FeatureRequests/FeatureRequests";
 import { FindAgentsTool } from "../../tools/FindAgents/FindAgents";
 import { FindBlocksTool } from "../../tools/FindBlocks/FindBlocks";
 import { RunAgentTool } from "../../tools/RunAgent/RunAgent";
 import { RunBlockTool } from "../../tools/RunBlock/RunBlock";
 import { SearchDocsTool } from "../../tools/SearchDocs/SearchDocs";
+import { GenericTool } from "../../tools/GenericTool/GenericTool";
 import { ViewAgentOutputTool } from "../../tools/ViewAgentOutput/ViewAgentOutput";
 
 // ---------------------------------------------------------------------------
@@ -258,21 +255,17 @@ export const ChatMessagesContainer = ({
                           part={part as ToolUIPart}
                         />
                       );
-                    case "tool-search_feature_requests":
-                      return (
-                        <SearchFeatureRequestsTool
-                          key={`${message.id}-${i}`}
-                          part={part as ToolUIPart}
-                        />
-                      );
-                    case "tool-create_feature_request":
-                      return (
-                        <CreateFeatureRequestTool
-                          key={`${message.id}-${i}`}
-                          part={part as ToolUIPart}
-                        />
-                      );
                     default:
+                      // Render a generic tool indicator for SDK built-in
+                      // tools (Read, Glob, Grep, etc.) or any unrecognized tool
+                      if (part.type.startsWith("tool-")) {
+                        return (
+                          <GenericTool
+                            key={`${message.id}-${i}`}
+                            part={part as ToolUIPart}
+                          />
+                        );
+                      }
                       return null;
                   }
                 })}

autogpt_platform/frontend/src/app/(platform)/copilot/hooks/Untitled

@@ -0,0 +1,10 @@
+import { parseAsString, useQueryState } from "nuqs";
+
+export function useCopilotSessionId() {
+  const [urlSessionId, setUrlSessionId] = useQueryState(
+    "sessionId",
+    parseAsString,
+  );
+
+  return { urlSessionId, setUrlSessionId };
+}

autogpt_platform/frontend/src/app/(platform)/copilot/hooks/useLongRunningToolPolling.ts

@@ -1,126 +0,0 @@
-import { getGetV2GetSessionQueryKey } from "@/app/api/__generated__/endpoints/chat/chat";
-import { useQueryClient } from "@tanstack/react-query";
-import type { UIDataTypes, UIMessage, UITools } from "ai";
-import { useCallback, useEffect, useRef } from "react";
-import { convertChatSessionMessagesToUiMessages } from "../helpers/convertChatSessionToUiMessages";
-
-const OPERATING_TYPES = new Set([
-  "operation_started",
-  "operation_pending",
-  "operation_in_progress",
-]);
-
-const POLL_INTERVAL_MS = 1_500;
-
-/**
- * Detects whether any message contains a tool part whose output indicates
- * a long-running operation is still in progress.
- */
-function hasOperatingTool(
-  messages: UIMessage<unknown, UIDataTypes, UITools>[],
-) {
-  for (const msg of messages) {
-    for (const part of msg.parts) {
-      if (!part.type.startsWith("tool-")) continue;
-      const toolPart = part as { output?: unknown };
-      if (!toolPart.output) continue;
-      const output =
-        typeof toolPart.output === "string"
-          ? safeParse(toolPart.output)
-          : toolPart.output;
-      if (
-        output &&
-        typeof output === "object" &&
-        "type" in output &&
-        OPERATING_TYPES.has((output as { type: string }).type)
-      ) {
-        return true;
-      }
-    }
-  }
-  return false;
-}
-
-function safeParse(value: string): unknown {
-  try {
-    return JSON.parse(value);
-  } catch {
-    return null;
-  }
-}
-
-/**
- * Polls the session endpoint while any tool is in an "operating" state
- * (operation_started / operation_pending / operation_in_progress).
- *
- * When the session data shows the tool output has changed (e.g. to
- * agent_saved), it calls `setMessages` with the updated messages.
- */
-export function useLongRunningToolPolling(
-  sessionId: string | null,
-  messages: UIMessage<unknown, UIDataTypes, UITools>[],
-  setMessages: (
-    updater: (
-      prev: UIMessage<unknown, UIDataTypes, UITools>[],
-    ) => UIMessage<unknown, UIDataTypes, UITools>[],
-  ) => void,
-) {
-  const queryClient = useQueryClient();
-  const intervalRef = useRef<ReturnType<typeof setInterval> | null>(null);
-
-  const stopPolling = useCallback(() => {
-    if (intervalRef.current) {
-      clearInterval(intervalRef.current);
-      intervalRef.current = null;
-    }
-  }, []);
-
-  const poll = useCallback(async () => {
-    if (!sessionId) return;
-
-    // Invalidate the query cache so the next fetch gets fresh data
-    await queryClient.invalidateQueries({
-      queryKey: getGetV2GetSessionQueryKey(sessionId),
-    });
-
-    // Fetch fresh session data
-    const data = queryClient.getQueryData<{
-      status: number;
-      data: { messages?: unknown[] };
-    }>(getGetV2GetSessionQueryKey(sessionId));
-
-    if (data?.status !== 200 || !data.data.messages) return;
-
-    const freshMessages = convertChatSessionMessagesToUiMessages(
-      sessionId,
-      data.data.messages,
-    );
-
-    if (!freshMessages || freshMessages.length === 0) return;
-
-    // Update when the long-running tool completed
-    if (!hasOperatingTool(freshMessages)) {
-      setMessages(() => freshMessages);
-      stopPolling();
-    }
-  }, [sessionId, queryClient, setMessages, stopPolling]);
-
-  useEffect(() => {
-    const shouldPoll = hasOperatingTool(messages);
-
-    // Always clear any previous interval first so we never leak timers
-    // when the effect re-runs due to dependency changes (e.g. messages
-    // updating as the LLM streams text after the tool call).
-    stopPolling();
-
-    if (shouldPoll && sessionId) {
-      intervalRef.current = setInterval(() => {
-        poll();
-      }, POLL_INTERVAL_MS);
-    }
-
-    return () => {
-      stopPolling();
-    };
-  }, [messages, sessionId, poll, stopPolling]);
-}

autogpt_platform/frontend/src/app/(platform)/copilot/styleguide/page.tsx

@@ -14,10 +14,6 @@ import { Text } from "@/components/atoms/Text/Text";
 import { CopilotChatActionsProvider } from "../components/CopilotChatActionsProvider/CopilotChatActionsProvider";
 import { CreateAgentTool } from "../tools/CreateAgent/CreateAgent";
 import { EditAgentTool } from "../tools/EditAgent/EditAgent";
-import {
-  CreateFeatureRequestTool,
-  SearchFeatureRequestsTool,
-} from "../tools/FeatureRequests/FeatureRequests";
 import { FindAgentsTool } from "../tools/FindAgents/FindAgents";
 import { FindBlocksTool } from "../tools/FindBlocks/FindBlocks";
 import { RunAgentTool } from "../tools/RunAgent/RunAgent";
@@ -49,8 +45,6 @@ const SECTIONS = [
   "Tool: Create Agent",
   "Tool: Edit Agent",
   "Tool: View Agent Output",
-  "Tool: Search Feature Requests",
-  "Tool: Create Feature Request",
   "Full Conversation Example",
 ] as const;
 
@@ -1427,235 +1421,6 @@ export default function StyleguidePage() {
               </SubSection>
             </Section>
 
-            {/* ============================================================= */}
-            {/* SEARCH FEATURE REQUESTS                                        */}
-            {/* ============================================================= */}
-
-            <Section title="Tool: Search Feature Requests">
-              <SubSection label="Input streaming">
-                <SearchFeatureRequestsTool
-                  part={{
-                    type: "tool-search_feature_requests",
-                    toolCallId: uid(),
-                    state: "input-streaming",
-                    input: { query: "dark mode" },
-                  }}
-                />
-              </SubSection>
-
-              <SubSection label="Input available">
-                <SearchFeatureRequestsTool
-                  part={{
-                    type: "tool-search_feature_requests",
-                    toolCallId: uid(),
-                    state: "input-available",
-                    input: { query: "dark mode" },
-                  }}
-                />
-              </SubSection>
-
-              <SubSection label="Output available (with results)">
-                <SearchFeatureRequestsTool
-                  part={{
-                    type: "tool-search_feature_requests",
-                    toolCallId: uid(),
-                    state: "output-available",
-                    input: { query: "dark mode" },
-                    output: {
-                      type: "feature_request_search",
-                      message:
-                        'Found 2 feature request(s) matching "dark mode".',
-                      query: "dark mode",
-                      count: 2,
-                      results: [
-                        {
-                          id: "fr-001",
-                          identifier: "INT-42",
-                          title: "Add dark mode to the platform",
-                          description:
-                            "Users have requested a dark mode option for the builder and copilot interfaces to reduce eye strain during long sessions.",
-                        },
-                        {
-                          id: "fr-002",
-                          identifier: "INT-87",
-                          title: "Dark theme for agent output viewer",
-                          description:
-                            "Specifically requesting dark theme support for the agent output/execution viewer panel.",
-                        },
-                      ],
-                    },
-                  }}
-                />
-              </SubSection>
-
-              <SubSection label="Output available (no results)">
-                <SearchFeatureRequestsTool
-                  part={{
-                    type: "tool-search_feature_requests",
-                    toolCallId: uid(),
-                    state: "output-available",
-                    input: { query: "teleportation" },
-                    output: {
-                      type: "no_results",
-                      message:
-                        "No feature requests found matching 'teleportation'.",
-                      suggestions: [
-                        "Try different keywords",
-                        "Use broader search terms",
-                        "You can create a new feature request if none exists",
-                      ],
-                    },
-                  }}
-                />
-              </SubSection>
-
-              <SubSection label="Output available (error)">
-                <SearchFeatureRequestsTool
-                  part={{
-                    type: "tool-search_feature_requests",
-                    toolCallId: uid(),
-                    state: "output-available",
-                    input: { query: "dark mode" },
-                    output: {
-                      type: "error",
-                      message: "Failed to search feature requests.",
-                      error: "LINEAR_API_KEY environment variable is not set",
-                    },
-                  }}
-                />
-              </SubSection>
-
-              <SubSection label="Output error">
-                <SearchFeatureRequestsTool
-                  part={{
-                    type: "tool-search_feature_requests",
-                    toolCallId: uid(),
-                    state: "output-error",
-                    input: { query: "dark mode" },
-                  }}
-                />
-              </SubSection>
-            </Section>
-
-            {/* ============================================================= */}
-            {/* CREATE FEATURE REQUEST                                         */}
-            {/* ============================================================= */}
-
-            <Section title="Tool: Create Feature Request">
-              <SubSection label="Input streaming">
-                <CreateFeatureRequestTool
-                  part={{
-                    type: "tool-create_feature_request",
-                    toolCallId: uid(),
-                    state: "input-streaming",
-                    input: {
-                      title: "Add dark mode",
-                      description: "I would love dark mode for the platform.",
-                    },
-                  }}
-                />
-              </SubSection>
-
-              <SubSection label="Input available">
-                <CreateFeatureRequestTool
-                  part={{
-                    type: "tool-create_feature_request",
-                    toolCallId: uid(),
-                    state: "input-available",
-                    input: {
-                      title: "Add dark mode",
-                      description: "I would love dark mode for the platform.",
-                    },
-                  }}
-                />
-              </SubSection>
-
-              <SubSection label="Output available (new issue created)">
-                <CreateFeatureRequestTool
-                  part={{
-                    type: "tool-create_feature_request",
-                    toolCallId: uid(),
-                    state: "output-available",
-                    input: {
-                      title: "Add dark mode",
-                      description: "I would love dark mode for the platform.",
-                    },
-                    output: {
-                      type: "feature_request_created",
-                      message:
-                        "Created new feature request [INT-105] Add dark mode.",
-                      issue_id: "issue-new-123",
-                      issue_identifier: "INT-105",
-                      issue_title: "Add dark mode",
-                      issue_url:
-                        "https://linear.app/autogpt/issue/INT-105/add-dark-mode",
-                      is_new_issue: true,
-                      customer_name: "user-abc-123",
-                    },
-                  }}
-                />
-              </SubSection>
-
-              <SubSection label="Output available (added to existing issue)">
-                <CreateFeatureRequestTool
-                  part={{
-                    type: "tool-create_feature_request",
-                    toolCallId: uid(),
-                    state: "output-available",
-                    input: {
-                      title: "Dark mode support",
-                      description:
-                        "Please add dark mode, it would help with long sessions.",
-                      existing_issue_id: "fr-001",
-                    },
-                    output: {
-                      type: "feature_request_created",
-                      message:
-                        "Added your request to existing feature request [INT-42] Add dark mode to the platform.",
-                      issue_id: "fr-001",
-                      issue_identifier: "INT-42",
-                      issue_title: "Add dark mode to the platform",
-                      issue_url:
-                        "https://linear.app/autogpt/issue/INT-42/add-dark-mode-to-the-platform",
-                      is_new_issue: false,
-                      customer_name: "user-xyz-789",
-                    },
-                  }}
-                />
-              </SubSection>
-
-              <SubSection label="Output available (error)">
-                <CreateFeatureRequestTool
-                  part={{
-                    type: "tool-create_feature_request",
-                    toolCallId: uid(),
-                    state: "output-available",
-                    input: {
-                      title: "Add dark mode",
-                      description: "I would love dark mode.",
-                    },
-                    output: {
-                      type: "error",
-                      message:
-                        "Failed to attach customer need to the feature request.",
-                      error: "Linear API request failed (500): Internal error",
-                    },
-                  }}
-                />
-              </SubSection>
-
-              <SubSection label="Output error">
-                <CreateFeatureRequestTool
-                  part={{
-                    type: "tool-create_feature_request",
-                    toolCallId: uid(),
-                    state: "output-error",
-                    input: { title: "Add dark mode" },
-                  }}
-                />
-              </SubSection>
-            </Section>
-
             {/* ============================================================= */}
             {/* FULL CONVERSATION EXAMPLE                                      */}
             {/* ============================================================= */}

autogpt_platform/frontend/src/app/(platform)/copilot/tools/CreateAgent/CreateAgent.tsx

@@ -1,30 +1,24 @@
 "use client";
 
-import { Button } from "@/components/atoms/Button/Button";
-import { Text } from "@/components/atoms/Text/Text";
-import {
-  BookOpenIcon,
-  CheckFatIcon,
-  PencilSimpleIcon,
-  WarningDiamondIcon,
-} from "@phosphor-icons/react";
+import { WarningDiamondIcon } from "@phosphor-icons/react";
 import type { ToolUIPart } from "ai";
-import NextLink from "next/link";
 import { useCopilotChatActions } from "../../components/CopilotChatActionsProvider/useCopilotChatActions";
 import { MorphingTextAnimation } from "../../components/MorphingTextAnimation/MorphingTextAnimation";
+import { ProgressBar } from "../../components/ProgressBar/ProgressBar";
 import {
   ContentCardDescription,
   ContentCodeBlock,
   ContentGrid,
   ContentHint,
+  ContentLink,
   ContentMessage,
 } from "../../components/ToolAccordion/AccordionContent";
 import { ToolAccordion } from "../../components/ToolAccordion/ToolAccordion";
+import { useAsymptoticProgress } from "../../hooks/useAsymptoticProgress";
 import {
   ClarificationQuestionsCard,
   ClarifyingQuestion,
 } from "./components/ClarificationQuestionsCard";
-import { MiniGame } from "./components/MiniGame/MiniGame";
 import {
   AccordionIcon,
   formatMaybeJson,
@@ -58,7 +52,7 @@ function getAccordionMeta(output: CreateAgentToolOutput) {
   const icon = <AccordionIcon />;
 
   if (isAgentSavedOutput(output)) {
-    return { icon, title: output.agent_name, expanded: true };
+    return { icon, title: output.agent_name };
   }
   if (isAgentPreviewOutput(output)) {
     return {
@@ -84,7 +78,6 @@ function getAccordionMeta(output: CreateAgentToolOutput) {
     return {
       icon,
       title: "Creating agent, this may take a few minutes. Sit back and relax.",
-      expanded: true,
     };
   }
   return {
@@ -114,6 +107,8 @@ export function CreateAgentTool({ part }: Props) {
       isOperationPendingOutput(output) ||
       isOperationInProgressOutput(output));
 
+  const progress = useAsymptoticProgress(isOperating);
+
   const hasExpandableContent =
     part.state === "output-available" &&
     !!output &&
@@ -157,53 +152,31 @@ export function CreateAgentTool({ part }: Props) {
         <ToolAccordion {...getAccordionMeta(output)}>
           {isOperating && (
             <ContentGrid>
-              <MiniGame />
+              <ProgressBar value={progress} className="max-w-[280px]" />
               <ContentHint>
-                This could take a few minutes — play while you wait!
+                This could take a few minutes, grab a coffee ☕
               </ContentHint>
             </ContentGrid>
           )}
 
           {isAgentSavedOutput(output) && (
-            <div className="rounded-xl border border-border/60 bg-card p-4 shadow-sm">
-              <div className="flex items-baseline gap-2">
-                <CheckFatIcon
-                  size={18}
-                  weight="regular"
-                  className="relative top-1 text-green-500"
-                />
-                <Text
-                  variant="body-medium"
-                  className="text-blacks mb-2 text-[16px]"
-                >
-                  {output.message}
-                </Text>
+            <ContentGrid>
+              <ContentMessage>{output.message}</ContentMessage>
+              <div className="flex flex-wrap gap-2">
+                <ContentLink href={output.library_agent_link}>
+                  Open in library
+                </ContentLink>
+                <ContentLink href={output.agent_page_link}>
+                  Open in builder
+                </ContentLink>
               </div>
-              <div className="mt-3 flex flex-wrap gap-4">
-                <Button variant="outline" size="small">
-                  <NextLink
-                    href={output.library_agent_link}
-                    className="inline-flex items-center gap-1.5"
-                    target="_blank"
-                    rel="noopener noreferrer"
-                  >
-                    <BookOpenIcon size={14} weight="regular" />
-                    Open in library
-                  </NextLink>
-                </Button>
-                <Button variant="outline" size="small">
-                  <NextLink
-                    href={output.agent_page_link}
-                    target="_blank"
-                    rel="noopener noreferrer"
-                    className="inline-flex items-center gap-1.5"
-                  >
-                    <PencilSimpleIcon size={14} weight="regular" />
-                    Open in builder
-                  </NextLink>
-                </Button>
-              </div>
-            </div>
+              <ContentCodeBlock>
+                {truncateText(
+                  formatMaybeJson({ agent_id: output.agent_id }),
+                  800,
+                )}
+              </ContentCodeBlock>
+            </ContentGrid>
           )}
 
           {isAgentPreviewOutput(output) && (

autogpt_platform/frontend/src/app/(platform)/copilot/tools/CreateAgent/components/MiniGame/MiniGame.tsx

@@ -1,21 +0,0 @@
-"use client";
-
-import { useMiniGame } from "./useMiniGame";
-
-export function MiniGame() {
-  const { canvasRef } = useMiniGame();
-
-  return (
-    <div
-      className="w-full overflow-hidden rounded-md bg-background text-foreground"
-      style={{ border: "1px solid #d17fff" }}
-    >
-      <canvas
-        ref={canvasRef}
-        tabIndex={0}
-        className="block w-full outline-none"
-        style={{ imageRendering: "pixelated" }}
-      />
-    </div>
-  );
-}

autogpt_platform/frontend/src/app/(platform)/copilot/tools/CreateAgent/components/MiniGame/useMiniGame.ts

@@ -1,579 +0,0 @@
-import { useEffect, useRef } from "react";
-
-/* ------------------------------------------------------------------ */
-/*  Constants                                                         */
-/* ------------------------------------------------------------------ */
-
-const CANVAS_HEIGHT = 150;
-const GRAVITY = 0.55;
-const JUMP_FORCE = -9.5;
-const BASE_SPEED = 3;
-const SPEED_INCREMENT = 0.0008;
-const SPAWN_MIN = 70;
-const SPAWN_MAX = 130;
-const CHAR_SIZE = 18;
-const CHAR_X = 50;
-const GROUND_PAD = 20;
-const STORAGE_KEY = "copilot-minigame-highscore";
-
-// Colors
-const COLOR_BG = "#E8EAF6";
-const COLOR_CHAR = "#263238";
-const COLOR_BOSS = "#F50057";
-
-// Boss
-const BOSS_SIZE = 36;
-const BOSS_ENTER_SPEED = 2;
-const BOSS_LEAVE_SPEED = 3;
-const BOSS_SHOOT_COOLDOWN = 90;
-const BOSS_SHOTS_TO_EVADE = 5;
-const BOSS_INTERVAL = 20; // every N score
-const PROJ_SPEED = 4.5;
-const PROJ_SIZE = 12;
-
-/* ------------------------------------------------------------------ */
-/*  Types                                                             */
-/* ------------------------------------------------------------------ */
-
-interface Obstacle {
-  x: number;
-  width: number;
-  height: number;
-  scored: boolean;
-}
-
-interface Projectile {
-  x: number;
-  y: number;
-  speed: number;
-  evaded: boolean;
-  type: "low" | "high";
-}
-
-interface BossState {
-  phase: "inactive" | "entering" | "fighting" | "leaving";
-  x: number;
-  targetX: number;
-  shotsEvaded: number;
-  cooldown: number;
-  projectiles: Projectile[];
-  bob: number;
-}
-
-interface GameState {
-  charY: number;
-  vy: number;
-  obstacles: Obstacle[];
-  score: number;
-  highScore: number;
-  speed: number;
-  frame: number;
-  nextSpawn: number;
-  running: boolean;
-  over: boolean;
-  groundY: number;
-  boss: BossState;
-  bossThreshold: number;
-}
-
-/* ------------------------------------------------------------------ */
-/*  Helpers                                                           */
-/* ------------------------------------------------------------------ */
-
-function randInt(min: number, max: number) {
-  return Math.floor(Math.random() * (max - min + 1)) + min;
-}
-
-function readHighScore(): number {
-  try {
-    return parseInt(localStorage.getItem(STORAGE_KEY) || "0", 10) || 0;
-  } catch {
-    return 0;
-  }
-}
-
-function writeHighScore(score: number) {
-  try {
-    localStorage.setItem(STORAGE_KEY, String(score));
-  } catch {
-    /* noop */
-  }
-}
-
-function makeBoss(): BossState {
-  return {
-    phase: "inactive",
-    x: 0,
-    targetX: 0,
-    shotsEvaded: 0,
-    cooldown: 0,
-    projectiles: [],
-    bob: 0,
-  };
-}
-
-function makeState(groundY: number): GameState {
-  return {
-    charY: groundY - CHAR_SIZE,
-    vy: 0,
-    obstacles: [],
-    score: 0,
-    highScore: readHighScore(),
-    speed: BASE_SPEED,
-    frame: 0,
-    nextSpawn: randInt(SPAWN_MIN, SPAWN_MAX),
-    running: false,
-    over: false,
-    groundY,
-    boss: makeBoss(),
-    bossThreshold: BOSS_INTERVAL,
-  };
-}
-
-function gameOver(s: GameState) {
-  s.running = false;
-  s.over = true;
-  if (s.score > s.highScore) {
-    s.highScore = s.score;
-    writeHighScore(s.score);
-  }
-}
-
-/* ------------------------------------------------------------------ */
-/*  Projectile collision — shared between fighting & leaving phases   */
-/* ------------------------------------------------------------------ */
-
-/** Returns true if the player died. */
-function tickProjectiles(s: GameState): boolean {
-  const boss = s.boss;
-
-  for (const p of boss.projectiles) {
-    p.x -= p.speed;
-
-    if (!p.evaded && p.x + PROJ_SIZE < CHAR_X) {
-      p.evaded = true;
-      boss.shotsEvaded++;
-    }
-
-    // Collision
-    if (
-      !p.evaded &&
-      CHAR_X + CHAR_SIZE > p.x &&
-      CHAR_X < p.x + PROJ_SIZE &&
-      s.charY + CHAR_SIZE > p.y &&
-      s.charY < p.y + PROJ_SIZE
-    ) {
-      gameOver(s);
-      return true;
-    }
-  }
-
-  boss.projectiles = boss.projectiles.filter((p) => p.x + PROJ_SIZE > -20);
-  return false;
-}
-
-/* ------------------------------------------------------------------ */
-/*  Update                                                            */
-/* ------------------------------------------------------------------ */
-
-function update(s: GameState, canvasWidth: number) {
-  if (!s.running) return;
-
-  s.frame++;
-
-  // Speed only ramps during regular play
-  if (s.boss.phase === "inactive") {
-    s.speed = BASE_SPEED + s.frame * SPEED_INCREMENT;
-  }
-
-  // ---- Character physics (always active) ---- //
-  s.vy += GRAVITY;
-  s.charY += s.vy;
-  if (s.charY + CHAR_SIZE >= s.groundY) {
-    s.charY = s.groundY - CHAR_SIZE;
-    s.vy = 0;
-  }
-
-  // ---- Trigger boss ---- //
-  if (s.boss.phase === "inactive" && s.score >= s.bossThreshold) {
-    s.boss.phase = "entering";
-    s.boss.x = canvasWidth + 10;
-    s.boss.targetX = canvasWidth - BOSS_SIZE - 40;
-    s.boss.shotsEvaded = 0;
-    s.boss.cooldown = BOSS_SHOOT_COOLDOWN;
-    s.boss.projectiles = [];
-    s.obstacles = [];
-  }
-
-  // ---- Boss: entering ---- //
-  if (s.boss.phase === "entering") {
-    s.boss.bob = Math.sin(s.frame * 0.05) * 3;
-    s.boss.x -= BOSS_ENTER_SPEED;
-    if (s.boss.x <= s.boss.targetX) {
-      s.boss.x = s.boss.targetX;
-      s.boss.phase = "fighting";
-    }
-    return; // no obstacles while entering
-  }
-
-  // ---- Boss: fighting ---- //
-  if (s.boss.phase === "fighting") {
-    s.boss.bob = Math.sin(s.frame * 0.05) * 3;
-
-    // Shoot
-    s.boss.cooldown--;
-    if (s.boss.cooldown <= 0) {
-      const isLow = Math.random() < 0.5;
-      s.boss.projectiles.push({
-        x: s.boss.x - PROJ_SIZE,
-        y: isLow ? s.groundY - 14 : s.groundY - 70,
-        speed: PROJ_SPEED,
-        evaded: false,
-        type: isLow ? "low" : "high",
-      });
-      s.boss.cooldown = BOSS_SHOOT_COOLDOWN;
-    }
-
-    if (tickProjectiles(s)) return;
-
-    // Boss defeated?
-    if (s.boss.shotsEvaded >= BOSS_SHOTS_TO_EVADE) {
-      s.boss.phase = "leaving";
-      s.score += 5; // bonus
-      s.bossThreshold = s.score + BOSS_INTERVAL;
-    }
-    return;
-  }
-
-  // ---- Boss: leaving ---- //
-  if (s.boss.phase === "leaving") {
-    s.boss.bob = Math.sin(s.frame * 0.05) * 3;
-    s.boss.x += BOSS_LEAVE_SPEED;
-
-    // Still check in-flight projectiles
-    if (tickProjectiles(s)) return;
-
-    if (s.boss.x > canvasWidth + 50) {
-      s.boss = makeBoss();
-      s.nextSpawn = s.frame + randInt(SPAWN_MIN / 2, SPAWN_MAX / 2);
-    }
-    return;
-  }
-
-  // ---- Regular obstacle play ---- //
-  if (s.frame >= s.nextSpawn) {
-    s.obstacles.push({
-      x: canvasWidth + 10,
-      width: randInt(10, 16),
-      height: randInt(20, 48),
-      scored: false,
-    });
-    s.nextSpawn = s.frame + randInt(SPAWN_MIN, SPAWN_MAX);
-  }
-
-  for (const o of s.obstacles) {
-    o.x -= s.speed;
-    if (!o.scored && o.x + o.width < CHAR_X) {
-      o.scored = true;
-      s.score++;
-    }
-  }
-
-  s.obstacles = s.obstacles.filter((o) => o.x + o.width > -20);
-
-  for (const o of s.obstacles) {
-    const oY = s.groundY - o.height;
-    if (
-      CHAR_X + CHAR_SIZE > o.x &&
-      CHAR_X < o.x + o.width &&
-      s.charY + CHAR_SIZE > oY
-    ) {
-      gameOver(s);
-      return;
-    }
-  }
-}
-
-/* ------------------------------------------------------------------ */
-/*  Drawing                                                           */
-/* ------------------------------------------------------------------ */
-
-function drawBoss(ctx: CanvasRenderingContext2D, s: GameState, bg: string) {
-  const bx = s.boss.x;
-  const by = s.groundY - BOSS_SIZE + s.boss.bob;
-
-  // Body
-  ctx.save();
-  ctx.fillStyle = COLOR_BOSS;
-  ctx.globalAlpha = 0.9;
-  ctx.beginPath();
-  ctx.roundRect(bx, by, BOSS_SIZE, BOSS_SIZE, 4);
-  ctx.fill();
-  ctx.restore();
-
-  // Eyes
-  ctx.save();
-  ctx.fillStyle = bg;
-  const eyeY = by + 13;
-  ctx.beginPath();
-  ctx.arc(bx + 10, eyeY, 4, 0, Math.PI * 2);
-  ctx.fill();
-  ctx.beginPath();
-  ctx.arc(bx + 26, eyeY, 4, 0, Math.PI * 2);
-  ctx.fill();
-  ctx.restore();
-
-  // Angry eyebrows
-  ctx.save();
-  ctx.strokeStyle = bg;
-  ctx.lineWidth = 2;
-  ctx.beginPath();
-  ctx.moveTo(bx + 5, eyeY - 7);
-  ctx.lineTo(bx + 14, eyeY - 4);
-  ctx.stroke();
-  ctx.beginPath();
-  ctx.moveTo(bx + 31, eyeY - 7);
-  ctx.lineTo(bx + 22, eyeY - 4);
-  ctx.stroke();
-  ctx.restore();
-
-  // Zigzag mouth
-  ctx.save();
-  ctx.strokeStyle = bg;
-  ctx.lineWidth = 1.5;
-  ctx.beginPath();
-  ctx.moveTo(bx + 10, by + 27);
-  ctx.lineTo(bx + 14, by + 24);
-  ctx.lineTo(bx + 18, by + 27);
-  ctx.lineTo(bx + 22, by + 24);
-  ctx.lineTo(bx + 26, by + 27);
-  ctx.stroke();
-  ctx.restore();
-}
-
-function drawProjectiles(ctx: CanvasRenderingContext2D, boss: BossState) {
-  ctx.save();
-  ctx.fillStyle = COLOR_BOSS;
-  ctx.globalAlpha = 0.8;
-  for (const p of boss.projectiles) {
-    if (p.evaded) continue;
-    ctx.beginPath();
-    ctx.arc(
-      p.x + PROJ_SIZE / 2,
-      p.y + PROJ_SIZE / 2,
-      PROJ_SIZE / 2,
-      0,
-      Math.PI * 2,
-    );
-    ctx.fill();
-  }
-  ctx.restore();
-}
-
-function draw(
-  ctx: CanvasRenderingContext2D,
-  s: GameState,
-  w: number,
-  h: number,
-  fg: string,
-  started: boolean,
-) {
-  ctx.fillStyle = COLOR_BG;
-  ctx.fillRect(0, 0, w, h);
-
-  // Ground
-  ctx.save();
-  ctx.strokeStyle = fg;
-  ctx.globalAlpha = 0.15;
-  ctx.setLineDash([4, 4]);
-  ctx.beginPath();
-  ctx.moveTo(0, s.groundY);
-  ctx.lineTo(w, s.groundY);
-  ctx.stroke();
-  ctx.restore();
-
-  // Character
-  ctx.save();
-  ctx.fillStyle = COLOR_CHAR;
-  ctx.globalAlpha = 0.85;
-  ctx.beginPath();
-  ctx.roundRect(CHAR_X, s.charY, CHAR_SIZE, CHAR_SIZE, 3);
-  ctx.fill();
-  ctx.restore();
-
-  // Eyes
-  ctx.save();
-  ctx.fillStyle = COLOR_BG;
-  ctx.beginPath();
-  ctx.arc(CHAR_X + 6, s.charY + 7, 2.5, 0, Math.PI * 2);
-  ctx.fill();
-  ctx.beginPath();
-  ctx.arc(CHAR_X + 12, s.charY + 7, 2.5, 0, Math.PI * 2);
-  ctx.fill();
-  ctx.restore();
-
-  // Obstacles
-  ctx.save();
-  ctx.fillStyle = fg;
-  ctx.globalAlpha = 0.55;
-  for (const o of s.obstacles) {
-    ctx.fillRect(o.x, s.groundY - o.height, o.width, o.height);
-  }
-  ctx.restore();
-
-  // Boss + projectiles
-  if (s.boss.phase !== "inactive") {
-    drawBoss(ctx, s, COLOR_BG);
-    drawProjectiles(ctx, s.boss);
-  }
-
-  // Score HUD
-  ctx.save();
-  ctx.fillStyle = fg;
-  ctx.globalAlpha = 0.5;
-  ctx.font = "bold 11px monospace";
-  ctx.textAlign = "right";
-  ctx.fillText(`Score: ${s.score}`, w - 12, 20);
-  ctx.fillText(`Best: ${s.highScore}`, w - 12, 34);
-  if (s.boss.phase === "fighting") {
-    ctx.fillText(
-      `Evade: ${s.boss.shotsEvaded}/${BOSS_SHOTS_TO_EVADE}`,
-      w - 12,
-      48,
-    );
-  }
-  ctx.restore();
-
-  // Prompts
-  if (!started && !s.running && !s.over) {
-    ctx.save();
-    ctx.fillStyle = fg;
-    ctx.globalAlpha = 0.5;
-    ctx.font = "12px sans-serif";
-    ctx.textAlign = "center";
-    ctx.fillText("Click or press Space to play while you wait", w / 2, h / 2);
-    ctx.restore();
-  }
-
-  if (s.over) {
-    ctx.save();
-    ctx.fillStyle = fg;
-    ctx.globalAlpha = 0.7;
-    ctx.font = "bold 13px sans-serif";
-    ctx.textAlign = "center";
-    ctx.fillText("Game Over", w / 2, h / 2 - 8);
-    ctx.font = "11px sans-serif";
-    ctx.fillText("Click or Space to restart", w / 2, h / 2 + 10);
-    ctx.restore();
-  }
-}
-
-/* ------------------------------------------------------------------ */
-/*  Hook                                                              */
-/* ------------------------------------------------------------------ */
-
-export function useMiniGame() {
-  const canvasRef = useRef<HTMLCanvasElement>(null);
-  const stateRef = useRef<GameState | null>(null);
-  const rafRef = useRef(0);
-  const startedRef = useRef(false);
-
-  useEffect(() => {
-    const canvas = canvasRef.current;
-    if (!canvas) return;
-
-    const container = canvas.parentElement;
-    if (container) {
-      canvas.width = container.clientWidth;
-      canvas.height = CANVAS_HEIGHT;
-    }
-
-    const groundY = canvas.height - GROUND_PAD;
-    stateRef.current = makeState(groundY);
-
-    const style = getComputedStyle(canvas);
-    let fg = style.color || "#71717a";
-
-    // -------------------------------------------------------------- //
-    //  Jump                                                           //
-    // -------------------------------------------------------------- //
-    function jump() {
-      const s = stateRef.current;
-      if (!s) return;
-
-      if (s.over) {
-        const hs = s.highScore;
-        const gy = s.groundY;
-        stateRef.current = makeState(gy);
-        stateRef.current.highScore = hs;
-        stateRef.current.running = true;
-        startedRef.current = true;
-        return;
-      }
-
-      if (!s.running) {
-        s.running = true;
-        startedRef.current = true;
-        return;
-      }
-
-      // Only jump when on the ground
-      if (s.charY + CHAR_SIZE >= s.groundY) {
-        s.vy = JUMP_FORCE;
-      }
-    }
-
-    function onKey(e: KeyboardEvent) {
-      if (e.code === "Space" || e.key === " ") {
-        e.preventDefault();
-        jump();
-      }
-    }
-
-    function onClick() {
-      canvas?.focus();
-      jump();
-    }
-
-    // -------------------------------------------------------------- //
-    //  Loop                                                           //
-    // -------------------------------------------------------------- //
-    function loop() {
-      const s = stateRef.current;
-      if (!canvas || !s) return;
-      const ctx = canvas.getContext("2d");
-      if (!ctx) return;
-
-      update(s, canvas.width);
-      draw(ctx, s, canvas.width, canvas.height, fg, startedRef.current);
-      rafRef.current = requestAnimationFrame(loop);
-    }
-
-    rafRef.current = requestAnimationFrame(loop);
-
-    canvas.addEventListener("click", onClick);
-    canvas.addEventListener("keydown", onKey);
-
-    const observer = new ResizeObserver((entries) => {
-      for (const entry of entries) {
-        canvas.width = entry.contentRect.width;
-        canvas.height = CANVAS_HEIGHT;
-        if (stateRef.current) {
-          stateRef.current.groundY = canvas.height - GROUND_PAD;
-        }
-        const cs = getComputedStyle(canvas);
-        fg = cs.color || fg;
-      }
-    });
-    if (container) observer.observe(container);
-
-    return () => {
-      cancelAnimationFrame(rafRef.current);
-      canvas.removeEventListener("click", onClick);
-      canvas.removeEventListener("keydown", onKey);
-      observer.disconnect();
-    };
-  }, []);
-
-  return { canvasRef };
-}

autogpt_platform/frontend/src/app/(platform)/copilot/tools/FeatureRequests/FeatureRequests.tsx

@@ -1,227 +0,0 @@
-"use client";
-
-import type { ToolUIPart } from "ai";
-import { useMemo } from "react";
-
-import { MorphingTextAnimation } from "../../components/MorphingTextAnimation/MorphingTextAnimation";
-import {
-  ContentBadge,
-  ContentCard,
-  ContentCardDescription,
-  ContentCardHeader,
-  ContentCardTitle,
-  ContentGrid,
-  ContentMessage,
-  ContentSuggestionsList,
-} from "../../components/ToolAccordion/AccordionContent";
-import { ToolAccordion } from "../../components/ToolAccordion/ToolAccordion";
-import {
-  AccordionIcon,
-  getAccordionTitle,
-  getAnimationText,
-  getFeatureRequestOutput,
-  isCreatedOutput,
-  isErrorOutput,
-  isNoResultsOutput,
-  isSearchResultsOutput,
-  ToolIcon,
-  type FeatureRequestToolType,
-} from "./helpers";
-
-export interface FeatureRequestToolPart {
-  type: FeatureRequestToolType;
-  toolCallId: string;
-  state: ToolUIPart["state"];
-  input?: unknown;
-  output?: unknown;
-}
-
-interface Props {
-  part: FeatureRequestToolPart;
-}
-
-function truncate(text: string, maxChars: number): string {
-  const trimmed = text.trim();
-  if (trimmed.length <= maxChars) return trimmed;
-  return `${trimmed.slice(0, maxChars).trimEnd()}…`;
-}
-
-export function SearchFeatureRequestsTool({ part }: Props) {
-  const output = getFeatureRequestOutput(part);
-  const text = getAnimationText(part);
-  const isStreaming =
-    part.state === "input-streaming" || part.state === "input-available";
-  const isError =
-    part.state === "output-error" || (!!output && isErrorOutput(output));
-
-  const normalized = useMemo(() => {
-    if (!output) return null;
-    return { title: getAccordionTitle(part.type, output) };
-  }, [output, part.type]);
-
-  const isOutputAvailable = part.state === "output-available" && !!output;
-
-  const searchOutput =
-    isOutputAvailable && output && isSearchResultsOutput(output)
-      ? output
-      : null;
-  const noResultsOutput =
-    isOutputAvailable && output && isNoResultsOutput(output) ? output : null;
-  const errorOutput =
-    isOutputAvailable && output && isErrorOutput(output) ? output : null;
-
-  const hasExpandableContent =
-    isOutputAvailable &&
-    ((!!searchOutput && searchOutput.count > 0) ||
-      !!noResultsOutput ||
-      !!errorOutput);
-
-  const accordionDescription =
-    hasExpandableContent && searchOutput
-      ? `Found ${searchOutput.count} result${searchOutput.count === 1 ? "" : "s"} for "${searchOutput.query}"`
-      : hasExpandableContent && (noResultsOutput || errorOutput)
-        ? ((noResultsOutput ?? errorOutput)?.message ?? null)
-        : null;
-
-  return (
-    <div className="py-2">
-      <div className="flex items-center gap-2 text-sm text-muted-foreground">
-        <ToolIcon
-          toolType={part.type}
-          isStreaming={isStreaming}
-          isError={isError}
-        />
-        <MorphingTextAnimation
-          text={text}
-          className={isError ? "text-red-500" : undefined}
-        />
-      </div>
-
-      {hasExpandableContent && normalized && (
-        <ToolAccordion
-          icon={<AccordionIcon toolType={part.type} />}
-          title={normalized.title}
-          description={accordionDescription}
-        >
-          {searchOutput && (
-            <ContentGrid>
-              {searchOutput.results.map((r) => (
-                <ContentCard key={r.id}>
-                  <ContentCardHeader>
-                    <ContentCardTitle>{r.title}</ContentCardTitle>
-                  </ContentCardHeader>
-                  {r.description && (
-                    <ContentCardDescription>
-                      {truncate(r.description, 200)}
-                    </ContentCardDescription>
-                  )}
-                </ContentCard>
-              ))}
-            </ContentGrid>
-          )}
-
-          {noResultsOutput && (
-            <div>
-              <ContentMessage>{noResultsOutput.message}</ContentMessage>
-              {noResultsOutput.suggestions &&
-                noResultsOutput.suggestions.length > 0 && (
-                  <ContentSuggestionsList items={noResultsOutput.suggestions} />
-                )}
-            </div>
-          )}
-
-          {errorOutput && (
-            <div>
-              <ContentMessage>{errorOutput.message}</ContentMessage>
-              {errorOutput.error && (
-                <ContentCardDescription>
-                  {errorOutput.error}
-                </ContentCardDescription>
-              )}
-            </div>
-          )}
-        </ToolAccordion>
-      )}
-    </div>
-  );
-}
-
-export function CreateFeatureRequestTool({ part }: Props) {
-  const output = getFeatureRequestOutput(part);
-  const text = getAnimationText(part);
-  const isStreaming =
-    part.state === "input-streaming" || part.state === "input-available";
-  const isError =
-    part.state === "output-error" || (!!output && isErrorOutput(output));
-
-  const normalized = useMemo(() => {
-    if (!output) return null;
-    return { title: getAccordionTitle(part.type, output) };
-  }, [output, part.type]);
-
-  const isOutputAvailable = part.state === "output-available" && !!output;
-
-  const createdOutput =
-    isOutputAvailable && output && isCreatedOutput(output) ? output : null;
-  const errorOutput =
-    isOutputAvailable && output && isErrorOutput(output) ? output : null;
-
-  const hasExpandableContent =
-    isOutputAvailable && (!!createdOutput || !!errorOutput);
-
-  const accordionDescription =
-    hasExpandableContent && createdOutput
-      ? createdOutput.issue_title
-      : hasExpandableContent && errorOutput
-        ? errorOutput.message
-        : null;
-
-  return (
-    <div className="py-2">
-      <div className="flex items-center gap-2 text-sm text-muted-foreground">
-        <ToolIcon
-          toolType={part.type}
-          isStreaming={isStreaming}
-          isError={isError}
-        />
-        <MorphingTextAnimation
-          text={text}
-          className={isError ? "text-red-500" : undefined}
-        />
-      </div>
-
-      {hasExpandableContent && normalized && (
-        <ToolAccordion
-          icon={<AccordionIcon toolType={part.type} />}
-          title={normalized.title}
-          description={accordionDescription}
-        >
-          {createdOutput && (
-            <ContentCard>
-              <ContentCardHeader>
-                <ContentCardTitle>{createdOutput.issue_title}</ContentCardTitle>
-              </ContentCardHeader>
-              <div className="mt-2 flex items-center gap-2">
-                <ContentBadge>
-                  {createdOutput.is_new_issue ? "New" : "Existing"}
-                </ContentBadge>
-              </div>
-              <ContentMessage>{createdOutput.message}</ContentMessage>
-            </ContentCard>
-          )}
-
-          {errorOutput && (
-            <div>
-              <ContentMessage>{errorOutput.message}</ContentMessage>
-              {errorOutput.error && (
-                <ContentCardDescription>
-                  {errorOutput.error}
-                </ContentCardDescription>
-              )}
-            </div>
-          )}
-        </ToolAccordion>
-      )}
-    </div>
-  );
-}

autogpt_platform/frontend/src/app/(platform)/copilot/tools/FeatureRequests/helpers.tsx

@@ -1,271 +0,0 @@
-import {
-  CheckCircleIcon,
-  LightbulbIcon,
-  MagnifyingGlassIcon,
-  PlusCircleIcon,
-} from "@phosphor-icons/react";
-import type { ToolUIPart } from "ai";
-
-/* ------------------------------------------------------------------ */
-/*  Types (local until API client is regenerated)                      */
-/* ------------------------------------------------------------------ */
-
-interface FeatureRequestInfo {
-  id: string;
-  identifier: string;
-  title: string;
-  description?: string | null;
-}
-
-export interface FeatureRequestSearchResponse {
-  type: "feature_request_search";
-  message: string;
-  results: FeatureRequestInfo[];
-  count: number;
-  query: string;
-}
-
-export interface FeatureRequestCreatedResponse {
-  type: "feature_request_created";
-  message: string;
-  issue_id: string;
-  issue_identifier: string;
-  issue_title: string;
-  issue_url: string;
-  is_new_issue: boolean;
-  customer_name: string;
-}
-
-interface NoResultsResponse {
-  type: "no_results";
-  message: string;
-  suggestions?: string[];
-}
-
-interface ErrorResponse {
-  type: "error";
-  message: string;
-  error?: string;
-}
-
-export type FeatureRequestOutput =
-  | FeatureRequestSearchResponse
-  | FeatureRequestCreatedResponse
-  | NoResultsResponse
-  | ErrorResponse;
-
-export type FeatureRequestToolType =
-  | "tool-search_feature_requests"
-  | "tool-create_feature_request"
-  | string;
-
-/* ------------------------------------------------------------------ */
-/*  Output parsing                                                     */
-/* ------------------------------------------------------------------ */
-
-function parseOutput(output: unknown): FeatureRequestOutput | null {
-  if (!output) return null;
-  if (typeof output === "string") {
-    const trimmed = output.trim();
-    if (!trimmed) return null;
-    try {
-      return parseOutput(JSON.parse(trimmed) as unknown);
-    } catch {
-      return null;
-    }
-  }
-  if (typeof output === "object") {
-    const type = (output as { type?: unknown }).type;
-    if (
-      type === "feature_request_search" ||
-      type === "feature_request_created" ||
-      type === "no_results" ||
-      type === "error"
-    ) {
-      return output as FeatureRequestOutput;
-    }
-    // Fallback structural checks
-    if ("results" in output && "query" in output)
-      return output as FeatureRequestSearchResponse;
-    if ("issue_identifier" in output)
-      return output as FeatureRequestCreatedResponse;
-    if ("suggestions" in output && !("error" in output))
-      return output as NoResultsResponse;
-    if ("error" in output || "details" in output)
-      return output as ErrorResponse;
-  }
-  return null;
-}
-
-export function getFeatureRequestOutput(
-  part: unknown,
-): FeatureRequestOutput | null {
-  if (!part || typeof part !== "object") return null;
-  return parseOutput((part as { output?: unknown }).output);
-}
-
-/* ------------------------------------------------------------------ */
-/*  Type guards                                                        */
-/* ------------------------------------------------------------------ */
-
-export function isSearchResultsOutput(
-  output: FeatureRequestOutput,
-): output is FeatureRequestSearchResponse {
-  return (
-    output.type === "feature_request_search" ||
-    ("results" in output && "query" in output)
-  );
-}
-
-export function isCreatedOutput(
-  output: FeatureRequestOutput,
-): output is FeatureRequestCreatedResponse {
-  return (
-    output.type === "feature_request_created" || "issue_identifier" in output
-  );
-}
-
-export function isNoResultsOutput(
-  output: FeatureRequestOutput,
-): output is NoResultsResponse {
-  return (
-    output.type === "no_results" ||
-    ("suggestions" in output && !("error" in output))
-  );
-}
-
-export function isErrorOutput(
-  output: FeatureRequestOutput,
-): output is ErrorResponse {
-  return output.type === "error" || "error" in output;
-}
-
-/* ------------------------------------------------------------------ */
-/*  Accordion metadata                                                 */
-/* ------------------------------------------------------------------ */
-
-export function getAccordionTitle(
-  toolType: FeatureRequestToolType,
-  output: FeatureRequestOutput,
-): string {
-  if (toolType === "tool-search_feature_requests") {
-    if (isSearchResultsOutput(output)) return "Feature requests";
-    if (isNoResultsOutput(output)) return "No feature requests found";
-    return "Feature request search error";
-  }
-  if (isCreatedOutput(output)) {
-    return output.is_new_issue
-      ? "Feature request created"
-      : "Added to feature request";
-  }
-  if (isErrorOutput(output)) return "Feature request error";
-  return "Feature request";
-}
-
-/* ------------------------------------------------------------------ */
-/*  Animation text                                                     */
-/* ------------------------------------------------------------------ */
-
-interface AnimationPart {
-  type: FeatureRequestToolType;
-  state: ToolUIPart["state"];
-  input?: unknown;
-  output?: unknown;
-}
-
-export function getAnimationText(part: AnimationPart): string {
-  if (part.type === "tool-search_feature_requests") {
-    const query = (part.input as { query?: string } | undefined)?.query?.trim();
-    const queryText = query ? ` for "${query}"` : "";
-
-    switch (part.state) {
-      case "input-streaming":
-      case "input-available":
-        return `Searching feature requests${queryText}`;
-      case "output-available": {
-        const output = parseOutput(part.output);
-        if (!output) return `Searching feature requests${queryText}`;
-        if (isSearchResultsOutput(output)) {
-          return `Found ${output.count} feature request${output.count === 1 ? "" : "s"}${queryText}`;
-        }
-        if (isNoResultsOutput(output))
-          return `No feature requests found${queryText}`;
-        return `Error searching feature requests${queryText}`;
-      }
-      case "output-error":
-        return `Error searching feature requests${queryText}`;
-      default:
-        return "Searching feature requests";
-    }
-  }
-
-  // create_feature_request
-  const title = (part.input as { title?: string } | undefined)?.title?.trim();
-  const titleText = title ? ` "${title}"` : "";
-
-  switch (part.state) {
-    case "input-streaming":
-    case "input-available":
-      return `Creating feature request${titleText}`;
-    case "output-available": {
-      const output = parseOutput(part.output);
-      if (!output) return `Creating feature request${titleText}`;
-      if (isCreatedOutput(output)) {
-        return output.is_new_issue
-          ? "Feature request created"
-          : "Added to existing feature request";
-      }
-      if (isErrorOutput(output)) return "Error creating feature request";
-      return `Created feature request${titleText}`;
-    }
-    case "output-error":
-      return "Error creating feature request";
-    default:
-      return "Creating feature request";
-  }
-}
-
-/* ------------------------------------------------------------------ */
-/*  Icons                                                              */
-/* ------------------------------------------------------------------ */
-
-export function ToolIcon({
-  toolType,
-  isStreaming,
-  isError,
-}: {
-  toolType: FeatureRequestToolType;
-  isStreaming?: boolean;
-  isError?: boolean;
-}) {
-  const IconComponent =
-    toolType === "tool-create_feature_request"
-      ? PlusCircleIcon
-      : MagnifyingGlassIcon;
-
-  return (
-    <IconComponent
-      size={14}
-      weight="regular"
-      className={
-        isError
-          ? "text-red-500"
-          : isStreaming
-            ? "text-neutral-500"
-            : "text-neutral-400"
-      }
-    />
-  );
-}
-
-export function AccordionIcon({
-  toolType,
-}: {
-  toolType: FeatureRequestToolType;
-}) {
-  const IconComponent =
-    toolType === "tool-create_feature_request"
-      ? CheckCircleIcon
-      : LightbulbIcon;
-  return <IconComponent size={32} weight="light" />;
-}

autogpt_platform/frontend/src/app/(platform)/copilot/tools/GenericTool/GenericTool.tsx

@@ -0,0 +1,63 @@
+"use client";
+
+import { ToolUIPart } from "ai";
+import { GearIcon } from "@phosphor-icons/react";
+import { MorphingTextAnimation } from "../../components/MorphingTextAnimation/MorphingTextAnimation";
+
+interface Props {
+  part: ToolUIPart;
+}
+
+function extractToolName(part: ToolUIPart): string {
+  // ToolUIPart.type is "tool-{name}", extract the name portion.
+  return part.type.replace(/^tool-/, "");
+}
+
+function formatToolName(name: string): string {
+  // "search_docs" → "Search docs", "Read" → "Read"
+  return name.replace(/_/g, " ").replace(/^\w/, (c) => c.toUpperCase());
+}
+
+function getAnimationText(part: ToolUIPart): string {
+  const label = formatToolName(extractToolName(part));
+
+  switch (part.state) {
+    case "input-streaming":
+    case "input-available":
+      return `Running ${label}…`;
+    case "output-available":
+      return `${label} completed`;
+    case "output-error":
+      return `${label} failed`;
+    default:
+      return `Running ${label}…`;
+  }
+}
+
+export function GenericTool({ part }: Props) {
+  const isStreaming =
+    part.state === "input-streaming" || part.state === "input-available";
+  const isError = part.state === "output-error";
+
+  return (
+    <div className="py-2">
+      <div className="flex items-center gap-2 text-sm text-muted-foreground">
+        <GearIcon
+          size={14}
+          weight="regular"
+          className={
+            isError
+              ? "text-red-500"
+              : isStreaming
+                ? "animate-spin text-neutral-500"
+                : "text-neutral-400"
+          }
+        />
+        <MorphingTextAnimation
+          text={getAnimationText(part)}
+          className={isError ? "text-red-500" : undefined}
+        />
+      </div>
+    </div>
+  );
+}

autogpt_platform/frontend/src/app/(platform)/copilot/tools/RunBlock/RunBlock.tsx

@@ -3,7 +3,6 @@
 import type { ToolUIPart } from "ai";
 import { MorphingTextAnimation } from "../../components/MorphingTextAnimation/MorphingTextAnimation";
 import { ToolAccordion } from "../../components/ToolAccordion/ToolAccordion";
-import { BlockDetailsCard } from "./components/BlockDetailsCard/BlockDetailsCard";
 import { BlockOutputCard } from "./components/BlockOutputCard/BlockOutputCard";
 import { ErrorCard } from "./components/ErrorCard/ErrorCard";
 import { SetupRequirementsCard } from "./components/SetupRequirementsCard/SetupRequirementsCard";
@@ -12,7 +11,6 @@ import {
   getAnimationText,
   getRunBlockToolOutput,
   isRunBlockBlockOutput,
-  isRunBlockDetailsOutput,
   isRunBlockErrorOutput,
   isRunBlockSetupRequirementsOutput,
   ToolIcon,
@@ -43,7 +41,6 @@ export function RunBlockTool({ part }: Props) {
     part.state === "output-available" &&
     !!output &&
     (isRunBlockBlockOutput(output) ||
-      isRunBlockDetailsOutput(output) ||
       isRunBlockSetupRequirementsOutput(output) ||
       isRunBlockErrorOutput(output));
 
@@ -61,10 +58,6 @@ export function RunBlockTool({ part }: Props) {
         <ToolAccordion {...getAccordionMeta(output)}>
           {isRunBlockBlockOutput(output) && <BlockOutputCard output={output} />}
 
-          {isRunBlockDetailsOutput(output) && (
-            <BlockDetailsCard output={output} />
-          )}
-
           {isRunBlockSetupRequirementsOutput(output) && (
             <SetupRequirementsCard output={output} />
           )}

autogpt_platform/frontend/src/app/(platform)/copilot/tools/RunBlock/components/BlockDetailsCard/BlockDetailsCard.stories.tsx

@@ -1,188 +0,0 @@
-import type { Meta, StoryObj } from "@storybook/nextjs";
-import { ResponseType } from "@/app/api/__generated__/models/responseType";
-import type { BlockDetailsResponse } from "../../helpers";
-import { BlockDetailsCard } from "./BlockDetailsCard";
-
-const meta: Meta<typeof BlockDetailsCard> = {
-  title: "Copilot/RunBlock/BlockDetailsCard",
-  component: BlockDetailsCard,
-  parameters: {
-    layout: "centered",
-  },
-  tags: ["autodocs"],
-  decorators: [
-    (Story) => (
-      <div style={{ maxWidth: 480 }}>
-        <Story />
-      </div>
-    ),
-  ],
-};
-
-export default meta;
-type Story = StoryObj<typeof meta>;
-
-const baseBlock: BlockDetailsResponse = {
-  type: ResponseType.block_details,
-  message:
-    "Here are the details for the GetWeather block. Provide the required inputs to run it.",
-  session_id: "session-123",
-  user_authenticated: true,
-  block: {
-    id: "block-abc-123",
-    name: "GetWeather",
-    description: "Fetches current weather data for a given location.",
-    inputs: {
-      type: "object",
-      properties: {
-        location: {
-          title: "Location",
-          type: "string",
-          description:
-            "City name or coordinates (e.g. 'London' or '51.5,-0.1')",
-        },
-        units: {
-          title: "Units",
-          type: "string",
-          description: "Temperature units: 'metric' or 'imperial'",
-        },
-      },
-      required: ["location"],
-    },
-    outputs: {
-      type: "object",
-      properties: {
-        temperature: {
-          title: "Temperature",
-          type: "number",
-          description: "Current temperature in the requested units",
-        },
-        condition: {
-          title: "Condition",
-          type: "string",
-          description: "Weather condition description (e.g. 'Sunny', 'Rain')",
-        },
-      },
-    },
-    credentials: [],
-  },
-};
-
-export const Default: Story = {
-  args: {
-    output: baseBlock,
-  },
-};
-
-export const InputsOnly: Story = {
-  args: {
-    output: {
-      ...baseBlock,
-      message: "This block requires inputs. No outputs are defined.",
-      block: {
-        ...baseBlock.block,
-        outputs: {},
-      },
-    },
-  },
-};
-
-export const OutputsOnly: Story = {
-  args: {
-    output: {
-      ...baseBlock,
-      message: "This block has no required inputs.",
-      block: {
-        ...baseBlock.block,
-        inputs: {},
-      },
-    },
-  },
-};
-
-export const ManyFields: Story = {
-  args: {
-    output: {
-      ...baseBlock,
-      message: "Block with many input and output fields.",
-      block: {
-        ...baseBlock.block,
-        name: "SendEmail",
-        description: "Sends an email via SMTP.",
-        inputs: {
-          type: "object",
-          properties: {
-            to: {
-              title: "To",
-              type: "string",
-              description: "Recipient email address",
-            },
-            subject: {
-              title: "Subject",
-              type: "string",
-              description: "Email subject line",
-            },
-            body: {
-              title: "Body",
-              type: "string",
-              description: "Email body content",
-            },
-            cc: {
-              title: "CC",
-              type: "string",
-              description: "CC recipients (comma-separated)",
-            },
-            bcc: {
-              title: "BCC",
-              type: "string",
-              description: "BCC recipients (comma-separated)",
-            },
-          },
-          required: ["to", "subject", "body"],
-        },
-        outputs: {
-          type: "object",
-          properties: {
-            message_id: {
-              title: "Message ID",
-              type: "string",
-              description: "Unique ID of the sent email",
-            },
-            status: {
-              title: "Status",
-              type: "string",
-              description: "Delivery status",
-            },
-          },
-        },
-      },
-    },
-  },
-};
-
-export const NoFieldDescriptions: Story = {
-  args: {
-    output: {
-      ...baseBlock,
-      message: "Fields without descriptions.",
-      block: {
-        ...baseBlock.block,
-        name: "SimpleBlock",
-        inputs: {
-          type: "object",
-          properties: {
-            input_a: { title: "Input A", type: "string" },
-            input_b: { title: "Input B", type: "number" },
-          },
-          required: ["input_a"],
-        },
-        outputs: {
-          type: "object",
-          properties: {
-            result: { title: "Result", type: "string" },
-          },
-        },
-      },
-    },
-  },
-};

autogpt_platform/frontend/src/app/(platform)/copilot/tools/RunBlock/components/BlockDetailsCard/BlockDetailsCard.tsx

@@ -1,103 +0,0 @@
-"use client";
-
-import type { BlockDetailsResponse } from "../../helpers";
-import {
-  ContentBadge,
-  ContentCard,
-  ContentCardDescription,
-  ContentCardTitle,
-  ContentGrid,
-  ContentMessage,
-} from "../../../../components/ToolAccordion/AccordionContent";
-
-interface Props {
-  output: BlockDetailsResponse;
-}
-
-function SchemaFieldList({
-  title,
-  properties,
-  required,
-}: {
-  title: string;
-  properties: Record<string, unknown>;
-  required?: string[];
-}) {
-  const entries = Object.entries(properties);
-  if (entries.length === 0) return null;
-
-  const requiredSet = new Set(required ?? []);
-
-  return (
-    <ContentCard>
-      <ContentCardTitle className="text-xs">{title}</ContentCardTitle>
-      <div className="mt-2 grid gap-2">
-        {entries.map(([name, schema]) => {
-          const field = schema as Record<string, unknown> | undefined;
-          const fieldTitle =
-            typeof field?.title === "string" ? field.title : name;
-          const fieldType =
-            typeof field?.type === "string" ? field.type : "unknown";
-          const description =
-            typeof field?.description === "string"
-              ? field.description
-              : undefined;
-
-          return (
-            <div key={name} className="rounded-xl border p-2">
-              <div className="flex items-center justify-between gap-2">
-                <ContentCardTitle className="text-xs">
-                  {fieldTitle}
-                </ContentCardTitle>
-                <div className="flex gap-1">
-                  <ContentBadge>{fieldType}</ContentBadge>
-                  {requiredSet.has(name) && (
-                    <ContentBadge>Required</ContentBadge>
-                  )}
-                </div>
-              </div>
-              {description && (
-                <ContentCardDescription className="mt-1 text-xs">
-                  {description}
-                </ContentCardDescription>
-              )}
-            </div>
-          );
-        })}
-      </div>
-    </ContentCard>
-  );
-}
-
-export function BlockDetailsCard({ output }: Props) {
-  const inputs = output.block.inputs as {
-    properties?: Record<string, unknown>;
-    required?: string[];
-  } | null;
-  const outputs = output.block.outputs as {
-    properties?: Record<string, unknown>;
-    required?: string[];
-  } | null;
-
-  return (
-    <ContentGrid>
-      <ContentMessage>{output.message}</ContentMessage>
-
-      {inputs?.properties && Object.keys(inputs.properties).length > 0 && (
-        <SchemaFieldList
-          title="Inputs"
-          properties={inputs.properties}
-          required={inputs.required}
-        />
-      )}
-
-      {outputs?.properties && Object.keys(outputs.properties).length > 0 && (
-        <SchemaFieldList
-          title="Outputs"
-          properties={outputs.properties}
-          required={outputs.required}
-        />
-      )}
-    </ContentGrid>
-  );
-}

autogpt_platform/frontend/src/app/(platform)/copilot/tools/RunBlock/helpers.tsx

@@ -10,37 +10,18 @@ import {
 import type { ToolUIPart } from "ai";
 import { OrbitLoader } from "../../components/OrbitLoader/OrbitLoader";
 
-/** Block details returned on first run_block attempt (before input_data provided). */
-export interface BlockDetailsResponse {
-  type: typeof ResponseType.block_details;
-  message: string;
-  session_id?: string | null;
-  block: {
-    id: string;
-    name: string;
-    description: string;
-    inputs: Record<string, unknown>;
-    outputs: Record<string, unknown>;
-    credentials: unknown[];
-  };
-  user_authenticated: boolean;
-}
-
 export interface RunBlockInput {
   block_id?: string;
-  block_name?: string;
   input_data?: Record<string, unknown>;
 }
 
 export type RunBlockToolOutput =
   | SetupRequirementsResponse
-  | BlockDetailsResponse
   | BlockOutputResponse
   | ErrorResponse;
 
 const RUN_BLOCK_OUTPUT_TYPES = new Set<string>([
   ResponseType.setup_requirements,
-  ResponseType.block_details,
   ResponseType.block_output,
   ResponseType.error,
 ]);
@@ -54,15 +35,6 @@ export function isRunBlockSetupRequirementsOutput(
   );
 }
 
-export function isRunBlockDetailsOutput(
-  output: RunBlockToolOutput,
-): output is BlockDetailsResponse {
-  return (
-    output.type === ResponseType.block_details ||
-    ("block" in output && typeof output.block === "object")
-  );
-}
-
 export function isRunBlockBlockOutput(
   output: RunBlockToolOutput,
 ): output is BlockOutputResponse {
@@ -92,7 +64,6 @@ function parseOutput(output: unknown): RunBlockToolOutput | null {
       return output as RunBlockToolOutput;
     }
     if ("block_id" in output) return output as BlockOutputResponse;
-    if ("block" in output) return output as BlockDetailsResponse;
     if ("setup_info" in output) return output as SetupRequirementsResponse;
     if ("error" in output || "details" in output)
       return output as ErrorResponse;
@@ -113,25 +84,17 @@ export function getAnimationText(part: {
   output?: unknown;
 }): string {
   const input = part.input as RunBlockInput | undefined;
-  const blockName = input?.block_name?.trim();
   const blockId = input?.block_id?.trim();
-  // Prefer block_name if available, otherwise fall back to block_id
-  const blockText = blockName
-    ? ` "${blockName}"`
-    : blockId
-      ? ` "${blockId}"`
-      : "";
+  const blockText = blockId ? ` "${blockId}"` : "";
 
   switch (part.state) {
     case "input-streaming":
     case "input-available":
-      return `Running${blockText}`;
+      return `Running the block${blockText}`;
     case "output-available": {
       const output = parseOutput(part.output);
-      if (!output) return `Running${blockText}`;
+      if (!output) return `Running the block${blockText}`;
       if (isRunBlockBlockOutput(output)) return `Ran "${output.block_name}"`;
-      if (isRunBlockDetailsOutput(output))
-        return `Details for "${output.block.name}"`;
       if (isRunBlockSetupRequirementsOutput(output)) {
         return `Setup needed for "${output.setup_info.agent_name}"`;
       }
@@ -195,21 +158,6 @@ export function getAccordionMeta(output: RunBlockToolOutput): {
     };
   }
 
-  if (isRunBlockDetailsOutput(output)) {
-    const inputKeys = Object.keys(
-      (output.block.inputs as { properties?: Record<string, unknown> })
-        ?.properties ?? {},
-    );
-    return {
-      icon,
-      title: output.block.name,
-      description:
-        inputKeys.length > 0
-          ? `${inputKeys.length} input field${inputKeys.length === 1 ? "" : "s"} available`
-          : output.message,
-    };
-  }
-
   if (isRunBlockSetupRequirementsOutput(output)) {
     const missingCredsCount = Object.keys(
       (output.setup_info.user_readiness?.missing_credentials ?? {}) as Record<

autogpt_platform/frontend/src/app/(platform)/copilot/useCopilotPage.ts

@@ -1,14 +1,10 @@
 import { useGetV2ListSessions } from "@/app/api/__generated__/endpoints/chat/chat";
-import { toast } from "@/components/molecules/Toast/use-toast";
 import { useBreakpoint } from "@/lib/hooks/useBreakpoint";
 import { useSupabase } from "@/lib/supabase/hooks/useSupabase";
 import { useChat } from "@ai-sdk/react";
 import { DefaultChatTransport } from "ai";
-import { useEffect, useMemo, useRef, useState } from "react";
+import { useEffect, useMemo, useState } from "react";
 import { useChatSession } from "./useChatSession";
-import { useLongRunningToolPolling } from "./hooks/useLongRunningToolPolling";
-
-const STREAM_START_TIMEOUT_MS = 12_000;
 
 export function useCopilotPage() {
   const { isUserLoading, isLoggedIn } = useSupabase();
@@ -56,24 +52,6 @@ export function useCopilotPage() {
     transport: transport ?? undefined,
   });
 
-  // Abort the stream if the backend doesn't start sending data within 12s.
-  const stopRef = useRef(stop);
-  stopRef.current = stop;
-  useEffect(() => {
-    if (status !== "submitted") return;
-
-    const timer = setTimeout(() => {
-      stopRef.current();
-      toast({
-        title: "Stream timed out",
-        description: "The server took too long to respond. Please try again.",
-        variant: "destructive",
-      });
-    }, STREAM_START_TIMEOUT_MS);
-
-    return () => clearTimeout(timer);
-  }, [status]);
-
   useEffect(() => {
     if (!hydratedMessages || hydratedMessages.length === 0) return;
     setMessages((prev) => {
@@ -82,11 +60,6 @@ export function useCopilotPage() {
     });
   }, [hydratedMessages, setMessages]);
 
-  // Poll session endpoint when a long-running tool (create_agent, edit_agent)
-  // is in progress. When the backend completes, the session data will contain
-  // the final tool output — this hook detects the change and updates messages.
-  useLongRunningToolPolling(sessionId, messages, setMessages);
-
   // Clear messages when session is null
   useEffect(() => {
     if (!sessionId) setMessages([]);

autogpt_platform/frontend/src/app/(platform)/library/agents/[id]/components/NewAgentLibraryView/components/sidebar/SidebarRunsList/components/ScheduleListItem.tsx

@@ -29,7 +29,6 @@ export function ScheduleListItem({
       description={formatDistanceToNow(schedule.next_run_time, {
         addSuffix: true,
       })}
-      descriptionTitle={new Date(schedule.next_run_time).toString()}
       onClick={onClick}
       selected={selected}
       icon={

autogpt_platform/frontend/src/app/(platform)/library/agents/[id]/components/NewAgentLibraryView/components/sidebar/SidebarRunsList/components/SidebarItemCard.tsx

@@ -7,7 +7,6 @@ import React from "react";
 interface Props {
   title: string;
   description?: string;
-  descriptionTitle?: string;
   icon?: React.ReactNode;
   selected?: boolean;
   onClick?: () => void;
@@ -17,7 +16,6 @@ interface Props {
 export function SidebarItemCard({
   title,
   description,
-  descriptionTitle,
   icon,
   selected,
   onClick,
@@ -40,11 +38,7 @@ export function SidebarItemCard({
           >
             {title}
           </Text>
-          <Text
-            variant="body"
-            className="leading-tight !text-zinc-500"
-            title={descriptionTitle}
-          >
+          <Text variant="body" className="leading-tight !text-zinc-500">
             {description}
           </Text>
         </div>

autogpt_platform/frontend/src/app/(platform)/library/agents/[id]/components/NewAgentLibraryView/components/sidebar/SidebarRunsList/components/TaskListItem.tsx

@@ -81,9 +81,6 @@ export function TaskListItem({
           ? formatDistanceToNow(run.started_at, { addSuffix: true })
           : "—"
       }
-      descriptionTitle={
-        run.started_at ? new Date(run.started_at).toString() : undefined
-      }
       onClick={onClick}
       selected={selected}
       actions={

autogpt_platform/frontend/src/app/api/openapi.json

@@ -1053,7 +1053,6 @@
                       "$ref": "#/components/schemas/ClarificationNeededResponse"
                     },
                     { "$ref": "#/components/schemas/BlockListResponse" },
-                    { "$ref": "#/components/schemas/BlockDetailsResponse" },
                     { "$ref": "#/components/schemas/BlockOutputResponse" },
                     { "$ref": "#/components/schemas/DocSearchResultsResponse" },
                     { "$ref": "#/components/schemas/DocPageResponse" },
@@ -6959,58 +6958,6 @@
         "enum": ["run", "byte", "second"],
         "title": "BlockCostType"
       },
-      "BlockDetails": {
-        "properties": {
-          "id": { "type": "string", "title": "Id" },
-          "name": { "type": "string", "title": "Name" },
-          "description": { "type": "string", "title": "Description" },
-          "inputs": {
-            "additionalProperties": true,
-            "type": "object",
-            "title": "Inputs",
-            "default": {}
-          },
-          "outputs": {
-            "additionalProperties": true,
-            "type": "object",
-            "title": "Outputs",
-            "default": {}
-          },
-          "credentials": {
-            "items": { "$ref": "#/components/schemas/CredentialsMetaInput" },
-            "type": "array",
-            "title": "Credentials",
-            "default": []
-          }
-        },
-        "type": "object",
-        "required": ["id", "name", "description"],
-        "title": "BlockDetails",
-        "description": "Detailed block information."
-      },
-      "BlockDetailsResponse": {
-        "properties": {
-          "type": {
-            "$ref": "#/components/schemas/ResponseType",
-            "default": "block_details"
-          },
-          "message": { "type": "string", "title": "Message" },
-          "session_id": {
-            "anyOf": [{ "type": "string" }, { "type": "null" }],
-            "title": "Session Id"
-          },
-          "block": { "$ref": "#/components/schemas/BlockDetails" },
-          "user_authenticated": {
-            "type": "boolean",
-            "title": "User Authenticated",
-            "default": false
-          }
-        },
-        "type": "object",
-        "required": ["message", "block"],
-        "title": "BlockDetailsResponse",
-        "description": "Response for block details (first run_block attempt)."
-      },
       "BlockInfo": {
         "properties": {
           "id": { "type": "string", "title": "Id" },
@@ -7066,13 +7013,57 @@
         "properties": {
           "id": { "type": "string", "title": "Id" },
           "name": { "type": "string", "title": "Name" },
-          "description": { "type": "string", "title": "Description" }
+          "description": { "type": "string", "title": "Description" },
+          "categories": {
+            "items": { "type": "string" },
+            "type": "array",
+            "title": "Categories"
+          },
+          "input_schema": {
+            "additionalProperties": true,
+            "type": "object",
+            "title": "Input Schema",
+            "description": "Full JSON schema for block inputs"
+          },
+          "output_schema": {
+            "additionalProperties": true,
+            "type": "object",
+            "title": "Output Schema",
+            "description": "Full JSON schema for block outputs"
+          },
+          "required_inputs": {
+            "items": { "$ref": "#/components/schemas/BlockInputFieldInfo" },
+            "type": "array",
+            "title": "Required Inputs",
+            "description": "List of input fields for this block"
+          }
         },
         "type": "object",
-        "required": ["id", "name", "description"],
+        "required": ["id", "name", "description", "categories"],
         "title": "BlockInfoSummary",
         "description": "Summary of a block for search results."
       },
+      "BlockInputFieldInfo": {
+        "properties": {
+          "name": { "type": "string", "title": "Name" },
+          "type": { "type": "string", "title": "Type" },
+          "description": {
+            "type": "string",
+            "title": "Description",
+            "default": ""
+          },
+          "required": {
+            "type": "boolean",
+            "title": "Required",
+            "default": false
+          },
+          "default": { "anyOf": [{}, { "type": "null" }], "title": "Default" }
+        },
+        "type": "object",
+        "required": ["name", "type"],
+        "title": "BlockInputFieldInfo",
+        "description": "Information about a block input field."
+      },
       "BlockListResponse": {
         "properties": {
           "type": {
@@ -7090,7 +7081,12 @@
             "title": "Blocks"
           },
           "count": { "type": "integer", "title": "Count" },
-          "query": { "type": "string", "title": "Query" }
+          "query": { "type": "string", "title": "Query" },
+          "usage_hint": {
+            "type": "string",
+            "title": "Usage Hint",
+            "default": "To execute a block, call run_block with block_id set to the block's 'id' field and input_data containing the fields listed in required_inputs."
+          }
         },
         "type": "object",
         "required": ["message", "blocks", "count", "query"],
@@ -10483,7 +10479,6 @@
           "agent_saved",
           "clarification_needed",
           "block_list",
-          "block_details",
           "block_output",
           "doc_search_results",
           "doc_page",
@@ -10496,8 +10491,9 @@
           "operation_pending",
           "operation_in_progress",
           "input_validation_error",
-          "feature_request_search",
-          "feature_request_created"
+          "web_fetch",
+          "bash_exec",
+          "operation_status"
         ],
         "title": "ResponseType",
         "description": "Types of tool responses."

autogpt_platform/frontend/src/app/globals.css

@@ -180,14 +180,3 @@ body[data-google-picker-open="true"] [data-dialog-content] {
   z-index: 1 !important;
   pointer-events: none !important;
 }
-
-/* CoPilot chat table styling — remove left/right borders, increase padding */
-[data-streamdown="table-wrapper"] table {
-  border-left: none;
-  border-right: none;
-}
-
-[data-streamdown="table-wrapper"] th,
-[data-streamdown="table-wrapper"] td {
-  padding: 0.875rem 1rem; /* py-3.5 px-4 */
-}

autogpt_platform/frontend/src/components/contextual/OutputRenderers/renderers/MarkdownRenderer.tsx

@@ -226,7 +226,7 @@ function renderMarkdown(
           table: ({ children, ...props }) => (
             <div className="my-4 overflow-x-auto">
               <table
-                className="min-w-full divide-y divide-gray-200 border-y border-gray-200 dark:divide-gray-700 dark:border-gray-700"
+                className="min-w-full divide-y divide-gray-200 rounded-lg border border-gray-200 dark:divide-gray-700 dark:border-gray-700"
                 {...props}
               >
                 {children}
@@ -235,7 +235,7 @@ function renderMarkdown(
           ),
           th: ({ children, ...props }) => (
             <th
-              className="bg-gray-50 px-4 py-3.5 text-left text-xs font-semibold uppercase tracking-wider text-gray-700 dark:bg-gray-800 dark:text-gray-300"
+              className="bg-gray-50 px-4 py-3 text-left text-xs font-semibold uppercase tracking-wider text-gray-700 dark:bg-gray-800 dark:text-gray-300"
               {...props}
             >
               {children}
@@ -243,7 +243,7 @@ function renderMarkdown(
           ),
           td: ({ children, ...props }) => (
             <td
-              className="border-t border-gray-200 px-4 py-3.5 text-sm text-gray-600 dark:border-gray-700 dark:text-gray-400"
+              className="border-t border-gray-200 px-4 py-3 text-sm text-gray-600 dark:border-gray-700 dark:text-gray-400"
               {...props}
             >
               {children}

plans/SECRT-1950-claude-ci-optimizations.md

@@ -1,165 +0,0 @@
-# Implementation Plan: SECRT-1950 - Apply E2E CI Optimizations to Claude Code Workflows
-
-## Ticket
-[SECRT-1950](https://linear.app/autogpt/issue/SECRT-1950)
-
-## Summary
-Apply Pwuts's CI performance optimizations from PR #12090 to Claude Code workflows.
-
-## Reference PR
-https://github.com/Significant-Gravitas/AutoGPT/pull/12090
-
----
-
-## Analysis
-
-### Current State (claude.yml)
-
-**pnpm caching (lines 104-118):**
-```yaml
-- 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-
-```
-
-**Docker setup (lines 134-165):**
-- Uses `docker-buildx-action@v3` 
-- Has manual Docker image caching via `actions/cache`
-- Runs `docker compose up` without buildx bake optimization
-
-### Pwuts's Optimizations (PR #12090)
-
-1. **Simplified pnpm caching** - Use `setup-node` built-in cache:
-```yaml
-- name: Enable corepack
-  run: corepack enable
-
-- name: Set up Node
-  uses: actions/setup-node@v6
-  with:
-    node-version: "22.18.0"
-    cache: "pnpm"
-    cache-dependency-path: autogpt_platform/frontend/pnpm-lock.yaml
-```
-
-2. **Docker build caching via buildx bake**:
-```yaml
-- name: Set up Docker Buildx
-  uses: docker/setup-buildx-action@v3
-  with:
-    driver: docker-container
-    driver-opts: network=host
-
-- name: Expose GHA cache to docker buildx CLI
-  uses: crazy-max/ghaction-github-runtime@v3
-
-- name: Build Docker images (with cache)
-  run: |
-    pip install pyyaml
-    docker compose -f docker-compose.yml config > docker-compose.resolved.yml
-    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" \
-      ...
-    docker buildx bake --allow=fs.read=.. -f docker-compose.resolved.yml --load
-```
-
----
-
-## Proposed Changes
-
-### 1. Update pnpm caching in `claude.yml`
-
-**Before:**
-- Manual cache key generation
-- Separate `actions/cache` step
-- Manual pnpm store directory config
-
-**After:**
-- Use `setup-node` built-in `cache: "pnpm"` option
-- Remove manual cache step
-- Keep `corepack enable` before `setup-node`
-
-### 2. Update Docker build in `claude.yml`
-
-**Before:**
-- Manual Docker layer caching via `actions/cache` with `/tmp/.buildx-cache`
-- Simple `docker compose build`
-
-**After:**
-- Use `crazy-max/ghaction-github-runtime@v3` to expose GHA cache
-- Use `docker-ci-fix-compose-build-cache.py` script
-- Build with `docker buildx bake`
-
-### 3. Apply same changes to other Claude workflows
-
-- `claude-dependabot.yml` - Check if it has similar patterns
-- `claude-ci-failure-auto-fix.yml` - Check if it has similar patterns
-- `copilot-setup-steps.yml` - Reusable workflow, may be the source of truth
-
----
-
-## Files to Modify
-
-1. `.github/workflows/claude.yml`
-2. `.github/workflows/claude-dependabot.yml` (if applicable)
-3. `.github/workflows/claude-ci-failure-auto-fix.yml` (if applicable)
-
-## Dependencies
-
-- PR #12090 must be merged first (provides the `docker-ci-fix-compose-build-cache.py` script)
-- Backend Dockerfile optimizations (already in PR #12090)
-
----
-
-## Test Plan
-
-1. Create PR with changes
-2. Trigger Claude workflow manually or via `@claude` mention on a test issue
-3. Compare CI runtime before/after
-4. Verify Claude agent still works correctly (can checkout, build, run tests)
-
----
-
-## Risk Assessment
-
-**Low risk:**
-- These are CI infrastructure changes, not code changes
-- If caching fails, builds fall back to uncached (slower but works)
-- Changes mirror proven patterns from PR #12090
-
----
-
-## Questions for Reviewer
-
-1. Should we wait for PR #12090 to merge before creating this PR?
-2. Does `copilot-setup-steps.yml` need updating, or is it a separate concern?
-3. Any concerns about cache key collisions between frontend E2E and Claude workflows?
-
----
-
-## Verified
-
-- ✅ **`claude-dependabot.yml`**: Has same pnpm caching pattern as `claude.yml` (manual `actions/cache`) — NEEDS UPDATE
-- ✅ **`claude-ci-failure-auto-fix.yml`**: Simple workflow with no pnpm or Docker caching — NO CHANGES NEEDED
-- ✅ **Script path**: `docker-ci-fix-compose-build-cache.py` will be at `.github/workflows/scripts/` after PR #12090 merges
-- ✅ **Test seed caching**: NOT APPLICABLE — Claude workflows spin up a dev environment but don't run E2E tests with pre-seeded data. The seed caching in PR #12090 is specific to the frontend E2E test suite which needs consistent test data. Claude just needs the services running.