Merge branch 'dev' into refactor/remove-old-agent-library-view

Users can now search for existing feature requests and submit new ones
directly through the CoPilot chat interface. Requests are tracked in
Linear with customer need attribution.

### Changes 🏗️

**Backend:**
- Added `SearchFeatureRequestsTool` and `CreateFeatureRequestTool` to
the CoPilot chat tools registry
- Integrated with Linear GraphQL API for searching issues in the feature
requests project, creating new issues, upserting customers, and
attaching customer needs
- Added `linear_api_key` secret to settings for system-level Linear API
access
- Added response models (`FeatureRequestSearchResponse`,
`FeatureRequestCreatedResponse`, `FeatureRequestInfo`) to the tools
models

**Frontend:**
- Added `SearchFeatureRequestsTool` and `CreateFeatureRequestTool` UI
components with full streaming state handling (input-streaming,
input-available, output-available, output-error)
- Added helper utilities for output parsing, type guards, animation
text, and icon rendering
- Wired tools into `ChatMessagesContainer` for rendering in the chat
- Added styleguide examples covering all tool states

### Checklist 📋

#### For code changes:
- [x] I have clearly listed my changes in the PR description
- [x] I have made a test plan
- [x] I have tested my changes according to the test plan:
  - [x] Verified search returns matching feature requests from Linear
- [x] Verified creating a new feature request creates an issue and
customer need in Linear
- [x] Verified adding a need to an existing issue works via
`existing_issue_id`
  - [x] Verified error states render correctly in the UI
  - [x] Verified styleguide page renders all tool states

#### For configuration changes:
- [x] `.env.default` is updated or already compatible with my changes
- [x] I have included a list of my configuration changes in the PR
description (under **Changes**)

New secret: `LINEAR_API_KEY` — required for system-level Linear API
operations (defaults to empty string).

<!-- greptile_comment -->

<h2>Greptile Overview</h2>

<details><summary><h3>Greptile Summary</h3></summary>

Adds feature request search and creation tools to CoPilot chat,
integrating with Linear's GraphQL API to track user feedback. Users can
now search existing feature requests and submit new ones (or add their
need to existing issues) directly through conversation.

**Key changes:**
- Backend: `SearchFeatureRequestsTool` and `CreateFeatureRequestTool`
with Linear API integration via system-level `LINEAR_API_KEY`
- Frontend: React components with streaming state handling and accordion
UI for search results and creation confirmations
- Models: Added `FeatureRequestSearchResponse` and
`FeatureRequestCreatedResponse` to response types
- Customer need tracking: Upserts customers in Linear and attaches needs
to issues for better feedback attribution

**Issues found:**
- Missing `LINEAR_API_KEY` entry in `.env.default` (required per PR
description checklist)
- Hardcoded project/team IDs reduce maintainability
- Global singleton pattern could cause issues in async contexts
- Using `user_id` as customer name reduces readability in Linear
</details>


<details><summary><h3>Confidence Score: 4/5</h3></summary>

- Safe to merge with minor configuration fix required
- The implementation is well-structured with proper error handling, type
safety, and follows existing patterns in the codebase. The missing
`.env.default` entry is a straightforward configuration issue that must
be fixed before deployment but doesn't affect code quality. The other
findings are style improvements that don't impact functionality.
- Verify that `LINEAR_API_KEY` is added to `.env.default` before merging
</details>


<details><summary><h3>Sequence Diagram</h3></summary>

```mermaid
sequenceDiagram
    participant User
    participant CoPilot UI
    participant LLM
    participant FeatureRequestTool
    participant LinearClient
    participant Linear API

    User->>CoPilot UI: Request feature via chat
    CoPilot UI->>LLM: Send user message
    
    LLM->>FeatureRequestTool: search_feature_requests(query)
    FeatureRequestTool->>LinearClient: query(SEARCH_ISSUES_QUERY)
    LinearClient->>Linear API: POST /graphql (search)
    Linear API-->>LinearClient: searchIssues.nodes[]
    LinearClient-->>FeatureRequestTool: Feature request data
    FeatureRequestTool-->>LLM: FeatureRequestSearchResponse
    
    alt No existing requests found
        LLM->>FeatureRequestTool: create_feature_request(title, description)
        FeatureRequestTool->>LinearClient: mutate(CUSTOMER_UPSERT_MUTATION)
        LinearClient->>Linear API: POST /graphql (upsert customer)
        Linear API-->>LinearClient: customer {id, name}
        LinearClient-->>FeatureRequestTool: Customer data
        
        FeatureRequestTool->>LinearClient: mutate(ISSUE_CREATE_MUTATION)
        LinearClient->>Linear API: POST /graphql (create issue)
        Linear API-->>LinearClient: issue {id, identifier, url}
        LinearClient-->>FeatureRequestTool: Issue data
        
        FeatureRequestTool->>LinearClient: mutate(CUSTOMER_NEED_CREATE_MUTATION)
        LinearClient->>Linear API: POST /graphql (attach need)
        Linear API-->>LinearClient: need {id, issue}
        LinearClient-->>FeatureRequestTool: Need data
        FeatureRequestTool-->>LLM: FeatureRequestCreatedResponse
    else Existing request found
        LLM->>FeatureRequestTool: create_feature_request(title, description, existing_issue_id)
        FeatureRequestTool->>LinearClient: mutate(CUSTOMER_UPSERT_MUTATION)
        LinearClient->>Linear API: POST /graphql (upsert customer)
        Linear API-->>LinearClient: customer {id}
        LinearClient-->>FeatureRequestTool: Customer data
        
        FeatureRequestTool->>LinearClient: mutate(CUSTOMER_NEED_CREATE_MUTATION)
        LinearClient->>Linear API: POST /graphql (attach need to existing)
        Linear API-->>LinearClient: need {id, issue}
        LinearClient-->>FeatureRequestTool: Need data
        FeatureRequestTool-->>LLM: FeatureRequestCreatedResponse
    end
    
    LLM-->>CoPilot UI: Tool response + continuation
    CoPilot UI-->>User: Display result with accordion UI
```
</details>


<sub>Last reviewed commit: af2e093</sub>

<!-- greptile_other_comments_section -->

<!-- /greptile_comment -->

.dockerignore

@@ -5,42 +5,13 @@
 !docs/
 
 # Platform - Libs
-!autogpt_platform/autogpt_libs/autogpt_libs/
+!autogpt_platform/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/backend/
+!autogpt_platform/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/src/
+!autogpt_platform/frontend/
-!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/
@@ -64,6 +35,38 @@
 # Classic - Frontend
 !classic/frontend/build/web/
 
-# Explicitly re-ignore some folders
+# Explicitly re-ignore unwanted files from whitelisted directories
-.*
+# Note: These patterns MUST come after the whitelist rules to take effect
-**/__pycache__
+
+# Hidden files and directories (but keep frontend .env files needed for build)
+**/.*
+!autogpt_platform/frontend/.env
+!autogpt_platform/frontend/.env.default
+!autogpt_platform/frontend/.env.production
+
+# Python artifacts
+**/__pycache__/
+**/*.pyc
+**/*.pyo
+**/.venv/
+**/.ruff_cache/
+**/.pytest_cache/
+**/.coverage
+**/htmlcov/
+
+# Node artifacts
+**/node_modules/
+**/.next/
+**/storybook-static/
+**/playwright-report/
+**/test-results/
+
+# Build artifacts
+**/dist/
+**/build/
+!autogpt_platform/frontend/src/**/build/
+**/target/
+
+# Logs and temp files
+**/*.log
+**/*.tmp

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

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

.github/workflows/claude-dependabot.yml

@@ -77,27 +77,15 @@ jobs:
         run: poetry run prisma generate && poetry run gen-prisma-stub
 
       # Frontend Node.js/pnpm setup (mirrors platform-frontend-ci.yml)
+      - name: Enable corepack
+        run: corepack enable
+
       - name: Set up Node.js
         uses: actions/setup-node@v6
         with:
           node-version: "22"
-
+          cache: "pnpm"
-      - name: Enable corepack
+          cache-dependency-path: autogpt_platform/frontend/pnpm-lock.yaml
-        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

@@ -93,27 +93,15 @@ jobs:
         run: poetry run prisma generate && poetry run gen-prisma-stub
 
       # Frontend Node.js/pnpm setup (mirrors platform-frontend-ci.yml)
+      - name: Enable corepack
+        run: corepack enable
+
       - name: Set up Node.js
         uses: actions/setup-node@v6
         with:
           node-version: "22"
-
+          cache: "pnpm"
-      - name: Enable corepack
+          cache-dependency-path: autogpt_platform/frontend/pnpm-lock.yaml
-        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/platform-frontend-ci.yml

@@ -26,7 +26,6 @@ jobs:
   setup:
     runs-on: ubuntu-latest
     outputs:
-      cache-key: ${{ steps.cache-key.outputs.key }}
       components-changed: ${{ steps.filter.outputs.components }}
 
     steps:
@@ -41,28 +40,17 @@ jobs:
             components:
               - 'autogpt_platform/frontend/src/components/**'
 
-      - name: Set up Node.js
-        uses: actions/setup-node@v6
-        with:
-          node-version: "22.18.0"
-
       - name: Enable corepack
         run: corepack enable
 
-      - name: Generate cache key
+      - name: Set up Node
-        id: cache-key
+        uses: actions/setup-node@v6
-        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
+          node-version: "22.18.0"
-          key: ${{ steps.cache-key.outputs.key }}
+          cache: "pnpm"
-          restore-keys: |
+          cache-dependency-path: autogpt_platform/frontend/pnpm-lock.yaml
-            ${{ runner.os }}-pnpm-${{ hashFiles('autogpt_platform/frontend/pnpm-lock.yaml') }}
-            ${{ runner.os }}-pnpm-
 
-      - name: Install dependencies
+      - name: Install dependencies to populate cache
         run: pnpm install --frozen-lockfile
 
   lint:
@@ -73,22 +61,15 @@ jobs:
       - name: Checkout repository
         uses: actions/checkout@v6
 
-      - name: Set up Node.js
-        uses: actions/setup-node@v6
-        with:
-          node-version: "22.18.0"
-
       - name: Enable corepack
         run: corepack enable
 
-      - name: Restore dependencies cache
+      - name: Set up Node
-        uses: actions/cache@v5
+        uses: actions/setup-node@v6
         with:
-          path: ~/.pnpm-store
+          node-version: "22.18.0"
-          key: ${{ needs.setup.outputs.cache-key }}
+          cache: "pnpm"
-          restore-keys: |
+          cache-dependency-path: autogpt_platform/frontend/pnpm-lock.yaml
-            ${{ runner.os }}-pnpm-${{ hashFiles('autogpt_platform/frontend/pnpm-lock.yaml') }}
-            ${{ runner.os }}-pnpm-
 
       - name: Install dependencies
         run: pnpm install --frozen-lockfile
@@ -111,22 +92,15 @@ jobs:
         with:
           fetch-depth: 0
 
-      - name: Set up Node.js
-        uses: actions/setup-node@v6
-        with:
-          node-version: "22.18.0"
-
       - name: Enable corepack
         run: corepack enable
 
-      - name: Restore dependencies cache
+      - name: Set up Node
-        uses: actions/cache@v5
+        uses: actions/setup-node@v6
         with:
-          path: ~/.pnpm-store
+          node-version: "22.18.0"
-          key: ${{ needs.setup.outputs.cache-key }}
+          cache: "pnpm"
-          restore-keys: |
+          cache-dependency-path: autogpt_platform/frontend/pnpm-lock.yaml
-            ${{ runner.os }}-pnpm-${{ hashFiles('autogpt_platform/frontend/pnpm-lock.yaml') }}
-            ${{ runner.os }}-pnpm-
 
       - name: Install dependencies
         run: pnpm install --frozen-lockfile
@@ -141,10 +115,8 @@ jobs:
           exitOnceUploaded: true
 
   e2e_test:
+    name: end-to-end tests
     runs-on: big-boi
-    needs: setup
-    strategy:
-      fail-fast: false
 
     steps:
       - name: Checkout repository
@@ -152,19 +124,11 @@ jobs:
         with:
           submodules: recursive
 
-      - name: Set up Node.js
+      - name: Set up Platform - Copy default supabase .env
-        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: Copy backend .env and set OpenAI API key
+      - name: Set up Platform - Copy backend .env and set OpenAI API key
         run: |
           cp ../backend/.env.default ../backend/.env
           echo "OPENAI_INTERNAL_API_KEY=${{ secrets.OPENAI_API_KEY }}" >> ../backend/.env
@@ -172,77 +136,125 @@ jobs:
           # Used by E2E test data script to generate embeddings for approved store agents
           OPENAI_API_KEY: ${{ secrets.OPENAI_API_KEY }}
 
-      - name: Set up Docker Buildx
+      - name: Set up Platform - Set up Docker Buildx
         uses: docker/setup-buildx-action@v3
+        with:
+          driver: docker-container
+          driver-opts: network=host
 
-      - name: Cache Docker layers
+      - name: Set up Platform - Expose GHA cache to docker buildx CLI
+        uses: crazy-max/ghaction-github-runtime@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
         uses: actions/cache@v5
         with:
-          path: /tmp/.buildx-cache
+          path: /tmp/e2e_test_data.sql
-          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') }}
+          key: e2e-test-data-${{ hashFiles('autogpt_platform/backend/test/e2e_test_data.py', 'autogpt_platform/backend/migrations/**', '.github/workflows/platform-frontend-ci.yml') }}
-          restore-keys: |
-            ${{ runner.os }}-buildx-frontend-test-
 
-      - name: Run docker compose
+      - name: Set up Platform - Start Supabase DB + Auth
         run: |
-          NEXT_PUBLIC_PW_TEST=true docker compose -f ../docker-compose.yml up -d
+          docker compose -f ../docker-compose.resolved.yml up -d db auth --no-build
+          echo "Waiting for database to be ready..."
+          timeout 60 sh -c 'until docker compose -f ../docker-compose.resolved.yml exec -T db pg_isready -U postgres 2>/dev/null; do sleep 2; done'
+          echo "Waiting for auth service to be ready..."
+          timeout 60 sh -c 'until docker compose -f ../docker-compose.resolved.yml exec -T db psql -U postgres -d postgres -c "SELECT 1 FROM auth.users LIMIT 1" 2>/dev/null; do sleep 2; done' || echo "Auth schema check timeout, continuing..."
+
+      - name: Set up Platform - Run migrations
+        run: |
+          echo "Running migrations..."
+          docker compose -f ../docker-compose.resolved.yml run --rm migrate
+          echo "✅ Migrations completed"
         env:
-          DOCKER_BUILDKIT: 1
+          NEXT_PUBLIC_PW_TEST: true
-          BUILDX_CACHE_FROM: type=local,src=/tmp/.buildx-cache
-          BUILDX_CACHE_TO: type=local,dest=/tmp/.buildx-cache-new,mode=max
 
-      - name: Move cache
+      - name: Set up tests - Load cached E2E test data
+        if: steps.e2e-data-cache.outputs.cache-hit == 'true'
         run: |
-          rm -rf /tmp/.buildx-cache
+          echo "✅ Found cached E2E test data, restoring..."
-          if [ -d "/tmp/.buildx-cache-new" ]; then
+          {
-            mv /tmp/.buildx-cache-new /tmp/.buildx-cache
+            echo "SET session_replication_role = 'replica';"
-          fi
+            cat /tmp/e2e_test_data.sql
+            echo "SET session_replication_role = 'origin';"
+          } | docker compose -f ../docker-compose.resolved.yml exec -T db psql -U postgres -d postgres -b
+          # Refresh materialized views after restore
+          docker compose -f ../docker-compose.resolved.yml exec -T db \
+            psql -U postgres -d postgres -b -c "SET search_path TO platform; SELECT refresh_store_materialized_views();" || true
 
-      - name: Wait for services to be ready
+          echo "✅ E2E test data restored from cache"
+
+      - name: Set up Platform - Start (all other services)
         run: |
+          docker compose -f ../docker-compose.resolved.yml up -d --no-build
           echo "Waiting for rest_server to be ready..."
           timeout 60 sh -c 'until curl -f http://localhost:8006/health 2>/dev/null; do sleep 2; done' || echo "Rest server health check timeout, continuing..."
-          echo "Waiting for database to be ready..."
+        env:
-          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..."
+          NEXT_PUBLIC_PW_TEST: true
 
-      - name: Create E2E test data
+      - name: Set up tests - Create E2E test data
+        if: steps.e2e-data-cache.outputs.cache-hit != 'true'
         run: |
           echo "Creating E2E test data..."
-          # First try to run the script from inside the container
+          docker cp ../backend/test/e2e_test_data.py $(docker compose -f ../docker-compose.resolved.yml ps -q rest_server):/tmp/e2e_test_data.py
-          if docker compose -f ../docker-compose.yml exec -T rest_server test -f /app/autogpt_platform/backend/test/e2e_test_data.py; then
+          docker compose -f ../docker-compose.resolved.yml exec -T rest_server sh -c "cd /app/autogpt_platform && python /tmp/e2e_test_data.py" || {
-            echo "✅ Found e2e_test_data.py in container, running it..."
+            echo "❌ E2E test data creation failed!"
-            docker compose -f ../docker-compose.yml exec -T rest_server sh -c "cd /app/autogpt_platform && python backend/test/e2e_test_data.py" || {
+            docker compose -f ../docker-compose.resolved.yml logs --tail=50 rest_server
-              echo "❌ E2E test data creation failed!"
+            exit 1
-              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
 
-      - name: Restore dependencies cache
+          # Dump auth.users + platform schema for cache (two separate dumps)
-        uses: actions/cache@v5
+          echo "Dumping database for cache..."
+          {
+            docker compose -f ../docker-compose.resolved.yml exec -T db \
+              pg_dump -U postgres --data-only --column-inserts \
+              --table='auth.users' postgres
+            docker compose -f ../docker-compose.resolved.yml exec -T db \
+              pg_dump -U postgres --data-only --column-inserts \
+              --schema=platform \
+              --exclude-table='platform._prisma_migrations' \
+              --exclude-table='platform.apscheduler_jobs' \
+              --exclude-table='platform.apscheduler_jobs_batched_notifications' \
+              postgres
+          } > /tmp/e2e_test_data.sql
+
+          echo "✅ Database dump created for caching ($(wc -l < /tmp/e2e_test_data.sql) lines)"
+
+      - name: Set up tests - Enable corepack
+        run: corepack enable
+
+      - name: Set up tests - Set up Node
+        uses: actions/setup-node@v6
         with:
-          path: ~/.pnpm-store
+          node-version: "22.18.0"
-          key: ${{ needs.setup.outputs.cache-key }}
+          cache: "pnpm"
-          restore-keys: |
+          cache-dependency-path: autogpt_platform/frontend/pnpm-lock.yaml
-            ${{ runner.os }}-pnpm-${{ hashFiles('autogpt_platform/frontend/pnpm-lock.yaml') }}
-            ${{ runner.os }}-pnpm-
 
-      - name: Install dependencies
+      - name: Set up tests - Install dependencies
         run: pnpm install --frozen-lockfile
 
-      - name: Install Browser 'chromium'
+      - name: Set up tests - Install browser 'chromium'
         run: pnpm playwright install --with-deps chromium
 
       - name: Run Playwright tests
@@ -269,7 +281,7 @@ jobs:
 
       - name: Print Final Docker Compose logs
         if: always()
-        run: docker compose -f ../docker-compose.yml logs
+        run: docker compose -f ../docker-compose.resolved.yml logs
 
   integration_test:
     runs-on: ubuntu-latest
@@ -281,22 +293,15 @@ jobs:
         with:
           submodules: recursive
 
-      - name: Set up Node.js
-        uses: actions/setup-node@v6
-        with:
-          node-version: "22.18.0"
-
       - name: Enable corepack
         run: corepack enable
 
-      - name: Restore dependencies cache
+      - name: Set up Node
-        uses: actions/cache@v5
+        uses: actions/setup-node@v6
         with:
-          path: ~/.pnpm-store
+          node-version: "22.18.0"
-          key: ${{ needs.setup.outputs.cache-key }}
+          cache: "pnpm"
-          restore-keys: |
+          cache-dependency-path: autogpt_platform/frontend/pnpm-lock.yaml
-            ${{ runner.os }}-pnpm-${{ 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

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

autogpt_platform/CLAUDE.md

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

autogpt_platform/autogpt_libs/poetry.lock

@@ -448,61 +448,61 @@ toml = ["tomli ; python_full_version <= \"3.11.0a6\""]
 
 [[package]]
 name = "cryptography"
-version = "46.0.4"
+version = "46.0.5"
 description = "cryptography is a package which provides cryptographic recipes and primitives to Python developers."
 optional = false
 python-versions = "!=3.9.0,!=3.9.1,>=3.8"
 groups = ["main"]
 files = [
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+    {file = "cryptography-46.0.5-cp311-abi3-macosx_10_9_universal2.whl", hash = "sha256:351695ada9ea9618b3500b490ad54c739860883df6c1f555e088eaf25b1bbaad"},
-    {file = "cryptography-46.0.4-cp311-abi3-manylinux2014_aarch64.manylinux_2_17_aarch64.whl", hash = "sha256:5f14fba5bf6f4390d7ff8f086c566454bff0411f6d8aa7af79c88b6f9267aecc"},
+    {file = "cryptography-46.0.5-cp311-abi3-manylinux2014_aarch64.manylinux_2_17_aarch64.whl", hash = "sha256:c18ff11e86df2e28854939acde2d003f7984f721eba450b56a200ad90eeb0e6b"},
-    {file = "cryptography-46.0.4-cp311-abi3-manylinux2014_x86_64.manylinux_2_17_x86_64.whl", hash = "sha256:47bcd19517e6389132f76e2d5303ded6cf3f78903da2158a671be8de024f4cd0"},
+    {file = "cryptography-46.0.5-cp311-abi3-manylinux2014_x86_64.manylinux_2_17_x86_64.whl", hash = "sha256:4d7e3d356b8cd4ea5aff04f129d5f66ebdc7b6f8eae802b93739ed520c47c79b"},
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+    {file = "cryptography-46.0.5-cp311-abi3-manylinux_2_28_aarch64.whl", hash = "sha256:50bfb6925eff619c9c023b967d5b77a54e04256c4281b0e21336a130cd7fc263"},
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+    {file = "cryptography-46.0.5-cp311-abi3-manylinux_2_28_ppc64le.whl", hash = "sha256:803812e111e75d1aa73690d2facc295eaefd4439be1023fefc4995eaea2af90d"},
-    {file = "cryptography-46.0.4-cp311-abi3-manylinux_2_28_x86_64.whl", hash = "sha256:0a9ad24359fee86f131836a9ac3bffc9329e956624a2d379b613f8f8abaf5255"},
+    {file = "cryptography-46.0.5-cp311-abi3-manylinux_2_28_x86_64.whl", hash = "sha256:3ee190460e2fbe447175cda91b88b84ae8322a104fc27766ad09428754a618ed"},
-    {file = "cryptography-46.0.4-cp311-abi3-manylinux_2_31_armv7l.whl", hash = "sha256:dc1272e25ef673efe72f2096e92ae39dea1a1a450dd44918b15351f72c5a168e"},
+    {file = "cryptography-46.0.5-cp311-abi3-manylinux_2_31_armv7l.whl", hash = "sha256:f145bba11b878005c496e93e257c1e88f154d278d2638e6450d17e0f31e558d2"},
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+    {file = "cryptography-46.0.5-cp311-abi3-manylinux_2_34_aarch64.whl", hash = "sha256:e9251e3be159d1020c4030bd2e5f84d6a43fe54b6c19c12f51cde9542a2817b2"},
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 ]
 
 [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 (==46.0.4)", "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 (==46.0.5)", "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]]
@@ -570,24 +570,25 @@ tests = ["coverage", "coveralls", "dill", "mock", "nose"]
 
 [[package]]
 name = "fastapi"
-version = "0.128.0"
+version = "0.128.7"
 description = "FastAPI framework, high performance, easy to learn, fast to code, ready for production"
 optional = false
 python-versions = ">=3.9"
 groups = ["main"]
 files = [
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 ]
 
 [package.dependencies]
 annotated-doc = ">=0.0.2"
 pydantic = ">=2.7.0"
-starlette = ">=0.40.0,<0.51.0"
+starlette = ">=0.40.0,<1.0.0"
 typing-extensions = ">=4.8.0"
+typing-inspection = ">=0.4.2"
 
 [package.extras]
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+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)"]
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@@ -1062,14 +1063,14 @@ urllib3 = ">=1.26.0,<3"
 
 [[package]]
 name = "launchdarkly-server-sdk"
-version = "9.14.1"
+version = "9.15.0"
 description = "LaunchDarkly SDK for Python"
 optional = false
-python-versions = ">=3.9"
+python-versions = ">=3.10"
 groups = ["main"]
 files = [
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 ]
 
 [package.dependencies]
@@ -1478,14 +1479,14 @@ testing = ["coverage", "pytest", "pytest-benchmark"]
 
 [[package]]
 name = "postgrest"
-version = "2.27.2"
+version = "2.28.0"
 description = "PostgREST client for Python. This library provides an ORM interface to PostgREST."
 optional = false
 python-versions = ">=3.9"
 groups = ["main"]
 files = [
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+    {file = "postgrest-2.28.0.tar.gz", hash = "sha256:c36b38646d25ea4255321d3d924ce70f8d20ec7799cb42c1221d6a818d4f6515"},
 ]
 
 [package.dependencies]
@@ -2248,14 +2249,14 @@ cli = ["click (>=5.0)"]
 
 [[package]]
 name = "realtime"
-version = "2.27.2"
+version = "2.28.0"
 description = ""
 optional = false
 python-versions = ">=3.9"
 groups = ["main"]
 files = [
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+    {file = "realtime-2.28.0.tar.gz", hash = "sha256:d18cedcebd6a8f22fcd509bc767f639761eb218b7b2b6f14fc4205b6259b50fc"},
 ]
 
 [package.dependencies]
@@ -2436,14 +2437,14 @@ full = ["httpx (>=0.27.0,<0.29.0)", "itsdangerous", "jinja2", "python-multipart
 
 [[package]]
 name = "storage3"
-version = "2.27.2"
+version = "2.28.0"
 description = "Supabase Storage client for Python."
 optional = false
 python-versions = ">=3.9"
 groups = ["main"]
 files = [
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+    {file = "storage3-2.28.0-py3-none-any.whl", hash = "sha256:ecb50efd2ac71dabbdf97e99ad346eafa630c4c627a8e5a138ceb5fbbadae716"},
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+    {file = "storage3-2.28.0.tar.gz", hash = "sha256:bc1d008aff67de7a0f2bd867baee7aadbcdb6f78f5a310b4f7a38e8c13c19865"},
 ]
 
 [package.dependencies]
@@ -2487,35 +2488,35 @@ python-dateutil = ">=2.6.0"
 
 [[package]]
 name = "supabase"
-version = "2.27.2"
+version = "2.28.0"
 description = "Supabase client for Python."
 optional = false
 python-versions = ">=3.9"
 groups = ["main"]
 files = [
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+    {file = "supabase-2.28.0-py3-none-any.whl", hash = "sha256:42776971c7d0ccca16034df1ab96a31c50228eb1eb19da4249ad2f756fc20272"},
-    {file = "supabase-2.27.2.tar.gz", hash = "sha256:2aed40e4f3454438822442a1e94a47be6694c2c70392e7ae99b51a226d4293f7"},
+    {file = "supabase-2.28.0.tar.gz", hash = "sha256:aea299aaab2a2eed3c57e0be7fc035c6807214194cce795a3575add20268ece1"},
 ]
 
 [package.dependencies]
 httpx = ">=0.26,<0.29"
-postgrest = "2.27.2"
+postgrest = "2.28.0"
-realtime = "2.27.2"
+realtime = "2.28.0"
-storage3 = "2.27.2"
+storage3 = "2.28.0"
-supabase-auth = "2.27.2"
+supabase-auth = "2.28.0"
-supabase-functions = "2.27.2"
+supabase-functions = "2.28.0"
 yarl = ">=1.22.0"
 
 [[package]]
 name = "supabase-auth"
-version = "2.27.2"
+version = "2.28.0"
 description = "Python Client Library for Supabase Auth"
 optional = false
 python-versions = ">=3.9"
 groups = ["main"]
 files = [
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+    {file = "supabase_auth-2.28.0-py3-none-any.whl", hash = "sha256:2ac85026cc285054c7fa6d41924f3a333e9ec298c013e5b5e1754039ba7caec9"},
-    {file = "supabase_auth-2.27.2.tar.gz", hash = "sha256:0f5bcc79b3677cb42e9d321f3c559070cfa40d6a29a67672cc8382fb7dc2fe97"},
+    {file = "supabase_auth-2.28.0.tar.gz", hash = "sha256:2bb8f18ff39934e44b28f10918db965659f3735cd6fbfcc022fe0b82dbf8233e"},
 ]
 
 [package.dependencies]
@@ -2525,14 +2526,14 @@ pyjwt = {version = ">=2.10.1", extras = ["crypto"]}
 
 [[package]]
 name = "supabase-functions"
-version = "2.27.2"
+version = "2.28.0"
 description = "Library for Supabase Functions"
 optional = false
 python-versions = ">=3.9"
 groups = ["main"]
 files = [
-    {file = "supabase_functions-2.27.2-py3-none-any.whl", hash = "sha256:db480efc669d0bca07605b9b6f167312af43121adcc842a111f79bea416ef754"},
+    {file = "supabase_functions-2.28.0-py3-none-any.whl", hash = "sha256:30bf2d586f8df285faf0621bb5d5bb3ec3157234fc820553ca156f009475e4ae"},
-    {file = "supabase_functions-2.27.2.tar.gz", hash = "sha256:d0c8266207a94371cb3fd35ad3c7f025b78a97cf026861e04ccd35ac1775f80b"},
+    {file = "supabase_functions-2.28.0.tar.gz", hash = "sha256:db3dddfc37aca5858819eb461130968473bd8c75bd284581013958526dac718b"},
 ]
 
 [package.dependencies]
@@ -2911,4 +2912,4 @@ type = ["pytest-mypy"]
 [metadata]
 lock-version = "2.1"
 python-versions = ">=3.10,<4.0"
-content-hash = "40eae94995dc0a388fa832ed4af9b6137f28d5b5ced3aaea70d5f91d4d9a179d"
+content-hash = "9619cae908ad38fa2c48016a58bcf4241f6f5793aa0e6cc140276e91c433cbbb"

autogpt_platform/autogpt_libs/pyproject.toml

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

autogpt_platform/backend/.env.default

@@ -104,6 +104,12 @@ TWITTER_CLIENT_SECRET=
 # Make a new workspace for your OAuth APP -- trust me
 # https://linear.app/settings/api/applications/new
 # Callback URL: http://localhost:3000/auth/integrations/oauth_callback
+LINEAR_API_KEY=
+# Linear project and team IDs for the feature request tracker.
+# Find these in your Linear workspace URL: linear.app/<workspace>/project/<project-id>
+# and in team settings. Used by the chat copilot to file and search feature requests.
+LINEAR_FEATURE_REQUEST_PROJECT_ID=
+LINEAR_FEATURE_REQUEST_TEAM_ID=
 LINEAR_CLIENT_ID=
 LINEAR_CLIENT_SECRET=
 

autogpt_platform/backend/Dockerfile

@@ -1,3 +1,5 @@
+# ============================ DEPENDENCY BUILDER ============================ #
+
 FROM debian:13-slim AS builder
 
 # Set environment variables
@@ -51,7 +53,9 @@ COPY autogpt_platform/backend/backend/data/partial_types.py ./backend/data/parti
 COPY autogpt_platform/backend/gen_prisma_types_stub.py ./
 RUN poetry run prisma generate && poetry run gen-prisma-stub
 
-FROM debian:13-slim AS server_dependencies
+# ============================== BACKEND SERVER ============================== #
+
+FROM debian:13-slim AS server
 
 WORKDIR /app
 
@@ -63,15 +67,14 @@ ENV POETRY_HOME=/opt/poetry \
 ENV PATH=/opt/poetry/bin:$PATH
 
 # Install Python, FFmpeg, and ImageMagick (required for video processing blocks)
-RUN apt-get update && apt-get install -y \
+# Using --no-install-recommends saves ~650MB by skipping unnecessary deps like llvm, mesa, etc.
+RUN apt-get update && apt-get install -y --no-install-recommends \
     python3.13 \
     python3-pip \
     ffmpeg \
     imagemagick \
     && 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
@@ -81,30 +84,54 @@ 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
 
-ENV PATH="/app/autogpt_platform/backend/.venv/bin:$PATH"
-
-RUN mkdir -p /app/autogpt_platform/autogpt_libs
-RUN mkdir -p /app/autogpt_platform/backend
-
-COPY autogpt_platform/autogpt_libs /app/autogpt_platform/autogpt_libs
-
-COPY autogpt_platform/backend/poetry.lock autogpt_platform/backend/pyproject.toml /app/autogpt_platform/backend/
-
 WORKDIR /app/autogpt_platform/backend
 
-FROM server_dependencies AS migrate
+# Copy only the .venv from builder (not the entire /app directory)
+# The .venv includes the generated Prisma client
+COPY --from=builder /app/autogpt_platform/backend/.venv ./.venv
+ENV PATH="/app/autogpt_platform/backend/.venv/bin:$PATH"
 
-# Migration stage only needs schema and migrations - much lighter than full backend
+# Copy dependency files + autogpt_libs (path dependency)
-COPY autogpt_platform/backend/schema.prisma /app/autogpt_platform/backend/
+COPY autogpt_platform/autogpt_libs /app/autogpt_platform/autogpt_libs
-COPY autogpt_platform/backend/backend/data/partial_types.py /app/autogpt_platform/backend/backend/data/partial_types.py
+COPY autogpt_platform/backend/poetry.lock autogpt_platform/backend/pyproject.toml ./
-COPY autogpt_platform/backend/migrations /app/autogpt_platform/backend/migrations
 
-FROM server_dependencies AS server
+# Copy backend code + docs (for Copilot docs search)
-
+COPY autogpt_platform/backend ./
-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/routes.py

@@ -24,6 +24,7 @@ from .tools.models import (
     AgentPreviewResponse,
     AgentSavedResponse,
     AgentsFoundResponse,
+    BlockDetailsResponse,
     BlockListResponse,
     BlockOutputResponse,
     ClarificationNeededResponse,
@@ -971,6 +972,7 @@ ToolResponseUnion = (
     | AgentSavedResponse
     | ClarificationNeededResponse
     | BlockListResponse
+    | BlockDetailsResponse
     | BlockOutputResponse
     | DocSearchResultsResponse
     | DocPageResponse

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

@@ -1245,6 +1245,7 @@ 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
@@ -1260,12 +1261,27 @@ async def _stream_chat_chunks(
                     continue  # Retry the stream
                 else:
                     # Non-retryable error or max retries exceeded
-                    logger.error(
+                    _log_api_error(
-                        f"Error in stream (not retrying): {e!s}",
+                        error=e,
-                        exc_info=True,
+                        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,
                     )
                     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 = (
@@ -1282,9 +1298,13 @@ async def _stream_chat_chunks(
 
         # If we exit the retry loop without returning, it means we exhausted retries
         if last_error:
-            logger.error(
+            _log_api_error(
-                f"Max retries ({MAX_RETRIES}) exceeded. Last error: {last_error!s}",
+                error=last_error,
-                exc_info=True,
+                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,
             )
             yield StreamError(errorText=f"Max retries exceeded: {last_error!s}")
             yield StreamFinish()
@@ -1857,6 +1877,7 @@ 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(
@@ -1870,17 +1891,25 @@ async def _generate_llm_continuation(
                     await asyncio.sleep(delay)
                     continue
                 else:
-                    # Non-retryable error - log and exit gracefully
+                    # Non-retryable error - log details and exit gracefully
-                    logger.error(
+                    _log_api_error(
-                        f"Non-retryable error in LLM continuation: {e!s}",
+                        error=e,
-                        exc_info=True,
+                        context="LLM continuation (not retrying)",
+                        session_id=session_id,
+                        message_count=len(messages) if messages else None,
+                        model=config.model,
+                        retry_count=retry_count,
                     )
                     return
 
         if last_error:
-            logger.error(
+            _log_api_error(
-                f"Max retries ({MAX_RETRIES}) exceeded for LLM continuation. "
+                error=last_error,
-                f"Last error: {last_error!s}"
+                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,
             )
             return
 
@@ -1920,6 +1949,91 @@ 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/tools/__init__.py

@@ -12,6 +12,7 @@ from .base import BaseTool
 from .create_agent import CreateAgentTool
 from .customize_agent import CustomizeAgentTool
 from .edit_agent import EditAgentTool
+from .feature_requests import CreateFeatureRequestTool, SearchFeatureRequestsTool
 from .find_agent import FindAgentTool
 from .find_block import FindBlockTool
 from .find_library_agent import FindLibraryAgentTool
@@ -45,6 +46,9 @@ TOOL_REGISTRY: dict[str, BaseTool] = {
     "view_agent_output": AgentOutputTool(),
     "search_docs": SearchDocsTool(),
     "get_doc_page": GetDocPageTool(),
+    # Feature request tools
+    "search_feature_requests": SearchFeatureRequestsTool(),
+    "create_feature_request": CreateFeatureRequestTool(),
     # Workspace tools for CoPilot file operations
     "list_workspace_files": ListWorkspaceFilesTool(),
     "read_workspace_file": ReadWorkspaceFileTool(),

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

@@ -0,0 +1,448 @@
+"""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

@@ -0,0 +1,615 @@
+"""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

@@ -7,7 +7,6 @@ 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,
@@ -55,7 +54,8 @@ 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, required_inputs, and input_schema."
+            "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."
         )
 
     @property
@@ -124,7 +124,7 @@ class FindBlockTool(BaseTool):
                     session_id=session_id,
                 )
 
-            # Enrich results with full block information
+            # Enrich results with block information
             blocks: list[BlockInfoSummary] = []
             for result in results:
                 block_id = result["content_id"]
@@ -141,65 +141,11 @@ 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,
                     )
                 )
 
@@ -228,8 +174,7 @@ class FindBlockTool(BaseTool):
             return BlockListResponse(
                 message=(
                     f"Found {len(blocks)} block(s) matching '{query}'. "
-                    "To execute a block, use run_block with the block's 'id' field "
+                    "To see a block's inputs/outputs and execute it, use run_block with the block's 'id' - providing no inputs."
-                    "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

@@ -18,7 +18,13 @@ _TEST_USER_ID = "test-user-find-block"
 
 
 def make_mock_block(
-    block_id: str, name: str, block_type: BlockType, disabled: bool = False
+    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,
 ):
     """Create a mock block for testing."""
     mock = MagicMock()
@@ -28,10 +34,13 @@ def make_mock_block(
     mock.block_type = block_type
     mock.disabled = disabled
     mock.input_schema = MagicMock()
-    mock.input_schema.jsonschema.return_value = {"properties": {}, "required": []}
+    mock.input_schema.jsonschema.return_value = input_schema or {
-    mock.input_schema.get_credentials_fields.return_value = {}
+        "properties": {},
+        "required": [],
+    }
+    mock.input_schema.get_credentials_fields.return_value = credentials_fields or {}
     mock.output_schema = MagicMock()
-    mock.output_schema.jsonschema.return_value = {}
+    mock.output_schema.jsonschema.return_value = output_schema or {}
     mock.categories = []
     return mock
 
@@ -137,3 +146,241 @@ 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

@@ -25,6 +25,7 @@ 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"
@@ -40,6 +41,9 @@ 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"
 
 
 # Base response model
@@ -334,13 +338,6 @@ class BlockInfoSummary(BaseModel):
     id: str
     name: str
     description: str
-    categories: list[str]
-    input_schema: dict[str, Any]
-    output_schema: dict[str, Any]
-    required_inputs: list[BlockInputFieldInfo] = Field(
-        default_factory=list,
-        description="List of required input fields for this block",
-    )
 
 
 class BlockListResponse(ToolResponseBase):
@@ -350,10 +347,25 @@ class BlockListResponse(ToolResponseBase):
     blocks: list[BlockInfoSummary]
     count: int
     query: str
-    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 required fields from input_schema."
+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
 
 
 class BlockOutputResponse(ToolResponseBase):
@@ -421,3 +433,34 @@ class AsyncProcessingResponse(ToolResponseBase):
     status: str = "accepted"  # Must be "accepted" for detection
     operation_id: str | None = None
     task_id: str | None = None
+
+
+# Feature request models
+class FeatureRequestInfo(BaseModel):
+    """Information about a feature request issue."""
+
+    id: str
+    identifier: str
+    title: str
+    description: str | None = None
+
+
+class FeatureRequestSearchResponse(ToolResponseBase):
+    """Response for search_feature_requests 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

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

@@ -23,8 +23,11 @@ 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,
@@ -51,8 +54,8 @@ 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. "
-            "Use the 'id' from find_block results and provide input_data "
+            "On first attempt (without input_data), returns detailed schema showing "
-            "matching the block's required_inputs."
+            "required inputs and outputs. Then call again with proper input_data to execute."
         )
 
     @property
@@ -67,11 +70,19 @@ 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. Use the 'required_inputs' field "
+                        "Input values for the block. "
-                        "from find_block to see what fields are needed."
+                        "First call with empty {} to see the block's schema, "
+                        "then call again with proper values to execute."
                     ),
                 },
             },
@@ -156,6 +167,34 @@ 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()
@@ -188,6 +227,53 @@ 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

@@ -1,10 +1,15 @@
-"""Tests for block execution guards in RunBlockTool."""
+"""Tests for block execution guards and input validation in RunBlockTool."""
 
-from unittest.mock import MagicMock, patch
+from unittest.mock import AsyncMock, MagicMock, patch
 
 import pytest
 
-from backend.api.features.chat.tools.models import ErrorResponse
+from backend.api.features.chat.tools.models import (
+    BlockDetailsResponse,
+    BlockOutputResponse,
+    ErrorResponse,
+    InputValidationErrorResponse,
+)
 from backend.api.features.chat.tools.run_block import RunBlockTool
 from backend.blocks._base import BlockType
 
@@ -28,6 +33,39 @@ 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."""
 
@@ -104,3 +142,221 @@ 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/test_run_block_details.py

@@ -0,0 +1,153 @@
+"""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/blocks/llm.py

@@ -32,14 +32,6 @@ from backend.data.model import (
 from backend.integrations.providers import ProviderName
 from backend.util import json
 from backend.util.logging import TruncatedLogger
-from backend.util.openai_responses import (
-    convert_tools_to_responses_format,
-    extract_responses_content,
-    extract_responses_reasoning,
-    extract_responses_tool_calls,
-    extract_usage,
-    requires_responses_api,
-)
 from backend.util.prompt import compress_context, estimate_token_count
 from backend.util.text import TextFormatter
 
@@ -667,72 +659,38 @@ async def llm_call(
     max_tokens = max(min(available_tokens, model_max_output, user_max), 1)
 
     if provider == "openai":
+        tools_param = tools if tools else openai.NOT_GIVEN
         oai_client = openai.AsyncOpenAI(api_key=credentials.api_key.get_secret_value())
+        response_format = None
 
-        # Check if this model requires the Responses API (reasoning models: o1, o3, etc.)
+        parallel_tool_calls = get_parallel_tool_calls_param(
-        if requires_responses_api(llm_model.value):
+            llm_model, parallel_tool_calls
-            # Use responses.create for reasoning models
+        )
-            tools_converted = (
-                convert_tools_to_responses_format(tools) if tools else None
-            )
 
-            response = await oai_client.responses.create(
+        if force_json_output:
-                model=llm_model.value,
+            response_format = {"type": "json_object"}
-                input=prompt,  # type: ignore
-                tools=tools_converted,  # type: ignore
-                max_output_tokens=max_tokens,
-                store=False,  # Don't persist conversations
-            )
 
-            tool_calls = extract_responses_tool_calls(response)
+        response = await oai_client.chat.completions.create(
-            reasoning = extract_responses_reasoning(response)
+            model=llm_model.value,
-            content = extract_responses_content(response)
+            messages=prompt,  # type: ignore
-            prompt_tokens, completion_tokens = extract_usage(response, True)
+            response_format=response_format,  # type: ignore
+            max_completion_tokens=max_tokens,
+            tools=tools_param,  # type: ignore
+            parallel_tool_calls=parallel_tool_calls,
+        )
 
-            return LLMResponse(
+        tool_calls = extract_openai_tool_calls(response)
-                raw_response=response,
+        reasoning = extract_openai_reasoning(response)
-                prompt=prompt,
-                response=content,
-                tool_calls=tool_calls,
-                prompt_tokens=prompt_tokens,
-                completion_tokens=completion_tokens,
-                reasoning=reasoning,
-            )
-        else:
-            # Use chat.completions.create for standard models
-            tools_param = tools if tools else openai.NOT_GIVEN
-            response_format = None
 
-            parallel_tool_calls = get_parallel_tool_calls_param(
+        return LLMResponse(
-                llm_model, parallel_tool_calls
+            raw_response=response.choices[0].message,
-            )
+            prompt=prompt,
-
+            response=response.choices[0].message.content or "",
-            if force_json_output:
+            tool_calls=tool_calls,
-                response_format = {"type": "json_object"}
+            prompt_tokens=response.usage.prompt_tokens if response.usage else 0,
-
+            completion_tokens=response.usage.completion_tokens if response.usage else 0,
-            response = await oai_client.chat.completions.create(
+            reasoning=reasoning,
-                model=llm_model.value,
+        )
-                messages=prompt,  # type: ignore
-                response_format=response_format,  # type: ignore
-                max_completion_tokens=max_tokens,
-                tools=tools_param,  # type: ignore
-                parallel_tool_calls=parallel_tool_calls,
-            )
-
-            tool_calls = extract_openai_tool_calls(response)
-            reasoning = extract_openai_reasoning(response)
-
-            return LLMResponse(
-                raw_response=response.choices[0].message,
-                prompt=prompt,
-                response=response.choices[0].message.content or "",
-                tool_calls=tool_calls,
-                prompt_tokens=response.usage.prompt_tokens if response.usage else 0,
-                completion_tokens=(
-                    response.usage.completion_tokens if response.usage else 0
-                ),
-                reasoning=reasoning,
-            )
     elif provider == "anthropic":
 
         an_tools = convert_openai_tool_fmt_to_anthropic(tools)

autogpt_platform/backend/backend/util/openai_responses.py

@@ -1,185 +0,0 @@
-"""Helpers for OpenAI Responses API migration.
-
-This module provides utilities for conditionally using OpenAI's Responses API
-instead of Chat Completions for reasoning models (o1, o3, etc.) that require it.
-"""
-
-from typing import Any
-
-# Exact model identifiers that require the Responses API.
-# Use exact matching to avoid false positives on future models.
-# NOTE: Update this set when OpenAI releases new reasoning models.
-REASONING_MODELS = frozenset(
-    {
-        # O1 family
-        "o1",
-        "o1-mini",
-        "o1-preview",
-        "o1-2024-12-17",
-        # O3 family
-        "o3",
-        "o3-mini",
-        "o3-2025-04-16",
-        "o3-mini-2025-01-31",
-    }
-)
-
-
-def requires_responses_api(model: str) -> bool:
-    """Check if model requires the Responses API (exact match).
-
-    Args:
-        model: The model identifier string (e.g., "o3-mini", "gpt-4o")
-
-    Returns:
-        True if the model requires responses.create, False otherwise
-    """
-    return model in REASONING_MODELS
-
-
-def convert_tools_to_responses_format(tools: list[dict] | None) -> list[dict]:
-    """Convert Chat Completions tool format to Responses API format.
-
-    The Responses API uses internally-tagged polymorphism (flatter structure)
-    and functions are strict by default.
-
-    Chat Completions format:
-        {"type": "function", "function": {"name": "...", "parameters": {...}}}
-
-    Responses API format:
-        {"type": "function", "name": "...", "parameters": {...}}
-
-    Args:
-        tools: List of tools in Chat Completions format
-
-    Returns:
-        List of tools in Responses API format
-    """
-    if not tools:
-        return []
-
-    converted = []
-    for tool in tools:
-        if tool.get("type") == "function":
-            func = tool.get("function", {})
-            converted.append(
-                {
-                    "type": "function",
-                    "name": func.get("name"),
-                    "description": func.get("description"),
-                    "parameters": func.get("parameters"),
-                    # Note: strict=True is default in Responses API
-                }
-            )
-        else:
-            # Pass through non-function tools as-is
-            converted.append(tool)
-    return converted
-
-
-def extract_responses_tool_calls(response: Any) -> list[dict] | None:
-    """Extract tool calls from Responses API response.
-
-    The Responses API returns tool calls as separate items in the output array
-    with type="function_call".
-
-    Args:
-        response: The Responses API response object
-
-    Returns:
-        List of tool calls in a normalized format, or None if no tool calls
-    """
-    tool_calls = []
-    for item in response.output:
-        if getattr(item, "type", None) == "function_call":
-            tool_calls.append(
-                {
-                    "id": item.call_id,
-                    "type": "function",
-                    "function": {
-                        "name": item.name,
-                        "arguments": item.arguments,
-                    },
-                }
-            )
-    return tool_calls if tool_calls else None
-
-
-def extract_usage(response: Any, is_responses_api: bool) -> tuple[int, int]:
-    """Extract token usage from either API response.
-
-    The Responses API uses different field names for token counts:
-    - Chat Completions: prompt_tokens, completion_tokens
-    - Responses API: input_tokens, output_tokens
-
-    Args:
-        response: The API response object
-        is_responses_api: True if response is from Responses API
-
-    Returns:
-        Tuple of (prompt_tokens, completion_tokens)
-    """
-    if not response.usage:
-        return 0, 0
-
-    if is_responses_api:
-        # Responses API uses different field names
-        return (
-            getattr(response.usage, "input_tokens", 0),
-            getattr(response.usage, "output_tokens", 0),
-        )
-    else:
-        # Chat Completions API
-        return (
-            getattr(response.usage, "prompt_tokens", 0),
-            getattr(response.usage, "completion_tokens", 0),
-        )
-
-
-def extract_responses_content(response: Any) -> str:
-    """Extract text content from Responses API response.
-
-    Args:
-        response: The Responses API response object
-
-    Returns:
-        The text content from the response, or empty string if none
-    """
-    # The SDK provides a helper property
-    if hasattr(response, "output_text"):
-        return response.output_text or ""
-
-    # Fallback: manually extract from output items
-    for item in response.output:
-        if getattr(item, "type", None) == "message":
-            for content in getattr(item, "content", []):
-                if getattr(content, "type", None) == "output_text":
-                    return getattr(content, "text", "")
-    return ""
-
-
-def extract_responses_reasoning(response: Any) -> str | None:
-    """Extract reasoning content from Responses API response.
-
-    Reasoning models return their reasoning process in the response,
-    which can be useful for debugging or display.
-
-    Args:
-        response: The Responses API response object
-
-    Returns:
-        The reasoning text, or None if not present
-    """
-    for item in response.output:
-        if getattr(item, "type", None) == "reasoning":
-            # Reasoning items may have summary or content
-            summary = getattr(item, "summary", [])
-            if summary:
-                # Join summary items if present
-                texts = []
-                for s in summary:
-                    if hasattr(s, "text"):
-                        texts.append(s.text)
-                if texts:
-                    return "\n".join(texts)
-    return None

autogpt_platform/backend/backend/util/openai_responses_test.py

@@ -1,155 +0,0 @@
-"""Tests for OpenAI Responses API helpers."""
-
-import pytest
-
-from backend.util.openai_responses import (
-    REASONING_MODELS,
-    convert_tools_to_responses_format,
-    requires_responses_api,
-)
-
-
-class TestRequiresResponsesApi:
-    """Tests for the requires_responses_api function."""
-
-    def test_o1_models_require_responses_api(self):
-        """O1 family models should require the Responses API."""
-        assert requires_responses_api("o1") is True
-        assert requires_responses_api("o1-mini") is True
-        assert requires_responses_api("o1-preview") is True
-        assert requires_responses_api("o1-2024-12-17") is True
-
-    def test_o3_models_require_responses_api(self):
-        """O3 family models should require the Responses API."""
-        assert requires_responses_api("o3") is True
-        assert requires_responses_api("o3-mini") is True
-        assert requires_responses_api("o3-2025-04-16") is True
-        assert requires_responses_api("o3-mini-2025-01-31") is True
-
-    def test_gpt_models_do_not_require_responses_api(self):
-        """GPT models should NOT require the Responses API."""
-        assert requires_responses_api("gpt-4o") is False
-        assert requires_responses_api("gpt-4o-mini") is False
-        assert requires_responses_api("gpt-4-turbo") is False
-        assert requires_responses_api("gpt-3.5-turbo") is False
-        assert requires_responses_api("gpt-5") is False
-        assert requires_responses_api("gpt-5-mini") is False
-
-    def test_other_models_do_not_require_responses_api(self):
-        """Other provider models should NOT require the Responses API."""
-        assert requires_responses_api("claude-3-opus") is False
-        assert requires_responses_api("llama-3.3-70b") is False
-        assert requires_responses_api("gemini-pro") is False
-
-    def test_empty_string_does_not_require_responses_api(self):
-        """Empty string should not require the Responses API."""
-        assert requires_responses_api("") is False
-
-    def test_exact_matching_no_false_positives(self):
-        """Should not match models that just start with 'o1' or 'o3'."""
-        # These are hypothetical models that start with o1/o3 but aren't
-        # actually reasoning models
-        assert requires_responses_api("o1-turbo-hypothetical") is False
-        assert requires_responses_api("o3-fast-hypothetical") is False
-        assert requires_responses_api("o100") is False
-
-
-class TestConvertToolsToResponsesFormat:
-    """Tests for the convert_tools_to_responses_format function."""
-
-    def test_empty_tools_returns_empty_list(self):
-        """Empty or None tools should return empty list."""
-        assert convert_tools_to_responses_format(None) == []
-        assert convert_tools_to_responses_format([]) == []
-
-    def test_converts_function_tool_format(self):
-        """Should convert Chat Completions function format to Responses format."""
-        chat_completions_tools = [
-            {
-                "type": "function",
-                "function": {
-                    "name": "get_weather",
-                    "description": "Get the weather in a location",
-                    "parameters": {
-                        "type": "object",
-                        "properties": {
-                            "location": {"type": "string"},
-                        },
-                        "required": ["location"],
-                    },
-                },
-            }
-        ]
-
-        result = convert_tools_to_responses_format(chat_completions_tools)
-
-        assert len(result) == 1
-        assert result[0]["type"] == "function"
-        assert result[0]["name"] == "get_weather"
-        assert result[0]["description"] == "Get the weather in a location"
-        assert result[0]["parameters"] == {
-            "type": "object",
-            "properties": {
-                "location": {"type": "string"},
-            },
-            "required": ["location"],
-        }
-        # Should not have nested "function" key
-        assert "function" not in result[0]
-
-    def test_handles_multiple_tools(self):
-        """Should handle multiple tools."""
-        chat_completions_tools = [
-            {
-                "type": "function",
-                "function": {
-                    "name": "tool_1",
-                    "description": "First tool",
-                    "parameters": {"type": "object", "properties": {}},
-                },
-            },
-            {
-                "type": "function",
-                "function": {
-                    "name": "tool_2",
-                    "description": "Second tool",
-                    "parameters": {"type": "object", "properties": {}},
-                },
-            },
-        ]
-
-        result = convert_tools_to_responses_format(chat_completions_tools)
-
-        assert len(result) == 2
-        assert result[0]["name"] == "tool_1"
-        assert result[1]["name"] == "tool_2"
-
-    def test_passes_through_non_function_tools(self):
-        """Non-function tools should be passed through as-is."""
-        tools = [{"type": "web_search", "config": {"enabled": True}}]
-
-        result = convert_tools_to_responses_format(tools)
-
-        assert result == tools
-
-
-class TestReasoningModelsSet:
-    """Tests for the REASONING_MODELS constant."""
-
-    def test_reasoning_models_is_frozenset(self):
-        """REASONING_MODELS should be a frozenset (immutable)."""
-        assert isinstance(REASONING_MODELS, frozenset)
-
-    def test_contains_expected_models(self):
-        """Should contain all expected reasoning models."""
-        expected = {
-            "o1",
-            "o1-mini",
-            "o1-preview",
-            "o1-2024-12-17",
-            "o3",
-            "o3-mini",
-            "o3-2025-04-16",
-            "o3-mini-2025-01-31",
-        }
-        assert expected.issubset(REASONING_MODELS)

autogpt_platform/backend/backend/util/settings.py

@@ -662,6 +662,17 @@ 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 = "^0.128.0"
+fastapi = "^0.128.7"
 google-cloud-logging = "^3.13.0"
-launchdarkly-server-sdk = "^9.14.1"
+launchdarkly-server-sdk = "^9.15.0"
 pydantic = "^2.12.5"
 pydantic-settings = "^2.12.0"
 pyjwt = {version = "^2.11.0", extras = ["crypto"]}
 redis = "^6.2.0"
-supabase = "^2.27.2"
+supabase = "^2.28.0"
 uvicorn = "^0.40.0"
 
 [package.source]
@@ -1382,14 +1382,14 @@ tzdata = "*"
 
 [[package]]
 name = "fastapi"
-version = "0.128.6"
+version = "0.128.7"
 description = "FastAPI framework, high performance, easy to learn, fast to code, ready for production"
 optional = false
 python-versions = ">=3.9"
 groups = ["main"]
 files = [
-    {file = "fastapi-0.128.6-py3-none-any.whl", hash = "sha256:bb1c1ef87d6086a7132d0ab60869d6f1ee67283b20fbf84ec0003bd335099509"},
+    {file = "fastapi-0.128.7-py3-none-any.whl", hash = "sha256:6bd9bd31cb7047465f2d3fa3ba3f33b0870b17d4eaf7cdb36d1576ab060ad662"},
-    {file = "fastapi-0.128.6.tar.gz", hash = "sha256:0cb3946557e792d731b26a42b04912f16367e3c3135ea8290f620e234f2b604f"},
+    {file = "fastapi-0.128.7.tar.gz", hash = "sha256:783c273416995486c155ad2c0e2b45905dedfaf20b9ef8d9f6a9124670639a24"},
 ]
 
 [package.dependencies]
@@ -3117,14 +3117,14 @@ urllib3 = ">=1.26.0,<3"
 
 [[package]]
 name = "launchdarkly-server-sdk"
-version = "9.14.1"
+version = "9.15.0"
 description = "LaunchDarkly SDK for Python"
 optional = false
-python-versions = ">=3.9"
+python-versions = ">=3.10"
 groups = ["main"]
 files = [
-    {file = "launchdarkly_server_sdk-9.14.1-py3-none-any.whl", hash = "sha256:a9e2bd9ecdef845cd631ae0d4334a1115e5b44257c42eb2349492be4bac7815c"},
+    {file = "launchdarkly_server_sdk-9.15.0-py3-none-any.whl", hash = "sha256:c267e29bfa3fb5e2a06a208448ada6ed5557a2924979b8d79c970b45d227c668"},
-    {file = "launchdarkly_server_sdk-9.14.1.tar.gz", hash = "sha256:1df44baf0a0efa74d8c1dad7a00592b98bce7d19edded7f770da8dbc49922213"},
+    {file = "launchdarkly_server_sdk-9.15.0.tar.gz", hash = "sha256:f31441b74bc1a69c381db57c33116509e407a2612628ad6dff0a7dbb39d5020b"},
 ]
 
 [package.dependencies]
@@ -4728,14 +4728,14 @@ tests = ["coverage-conditional-plugin (>=0.9.0)", "portalocker[redis]", "pytest
 
 [[package]]
 name = "postgrest"
-version = "2.27.3"
+version = "2.28.0"
 description = "PostgREST client for Python. This library provides an ORM interface to PostgREST."
 optional = false
 python-versions = ">=3.9"
 groups = ["main"]
 files = [
-    {file = "postgrest-2.27.3-py3-none-any.whl", hash = "sha256:ed79123af7127edd78d538bfe8351d277e45b1a36994a4dbf57ae27dde87a7b7"},
+    {file = "postgrest-2.28.0-py3-none-any.whl", hash = "sha256:7bca2f24dd1a1bf8a3d586c7482aba6cd41662da6733045fad585b63b7f7df75"},
-    {file = "postgrest-2.27.3.tar.gz", hash = "sha256:c2e2679addfc8eaab23197bad7ddaee6cbb4cbe8c483ebd2d2e5219543037cc3"},
+    {file = "postgrest-2.28.0.tar.gz", hash = "sha256:c36b38646d25ea4255321d3d924ce70f8d20ec7799cb42c1221d6a818d4f6515"},
 ]
 
 [package.dependencies]
@@ -6260,14 +6260,14 @@ all = ["numpy"]
 
 [[package]]
 name = "realtime"
-version = "2.27.3"
+version = "2.28.0"
 description = ""
 optional = false
 python-versions = ">=3.9"
 groups = ["main"]
 files = [
-    {file = "realtime-2.27.3-py3-none-any.whl", hash = "sha256:f571115f86988e33c41c895cb3fba2eaa1b693aeaede3617288f44274ca90f43"},
+    {file = "realtime-2.28.0-py3-none-any.whl", hash = "sha256:db1bd59bab9b1fcc9f9d3b1a073bed35bf4994d720e6751f10031a58d57a3836"},
-    {file = "realtime-2.27.3.tar.gz", hash = "sha256:02b082243107656a5ef3fb63e8e2ab4c40bc199abb45adb8a42ed63f089a1041"},
+    {file = "realtime-2.28.0.tar.gz", hash = "sha256:d18cedcebd6a8f22fcd509bc767f639761eb218b7b2b6f14fc4205b6259b50fc"},
 ]
 
 [package.dependencies]
@@ -7024,14 +7024,14 @@ full = ["httpx (>=0.27.0,<0.29.0)", "itsdangerous", "jinja2", "python-multipart
 
 [[package]]
 name = "storage3"
-version = "2.27.3"
+version = "2.28.0"
 description = "Supabase Storage client for Python."
 optional = false
 python-versions = ">=3.9"
 groups = ["main"]
 files = [
-    {file = "storage3-2.27.3-py3-none-any.whl", hash = "sha256:11a05b7da84bccabeeea12d940bca3760cf63fe6ca441868677335cfe4fdfbe0"},
+    {file = "storage3-2.28.0-py3-none-any.whl", hash = "sha256:ecb50efd2ac71dabbdf97e99ad346eafa630c4c627a8e5a138ceb5fbbadae716"},
-    {file = "storage3-2.27.3.tar.gz", hash = "sha256:dc1a4a010cf36d5482c5cb6c1c28fc5f00e23284342b89e4ae43b5eae8501ddb"},
+    {file = "storage3-2.28.0.tar.gz", hash = "sha256:bc1d008aff67de7a0f2bd867baee7aadbcdb6f78f5a310b4f7a38e8c13c19865"},
 ]
 
 [package.dependencies]
@@ -7091,35 +7091,35 @@ typing-extensions = {version = ">=4.5.0", markers = "python_version >= \"3.7\""}
 
 [[package]]
 name = "supabase"
-version = "2.27.3"
+version = "2.28.0"
 description = "Supabase client for Python."
 optional = false
 python-versions = ">=3.9"
 groups = ["main"]
 files = [
-    {file = "supabase-2.27.3-py3-none-any.whl", hash = "sha256:082a74642fcf9954693f1ce8c251baf23e4bda26ffdbc8dcd4c99c82e60d69ff"},
+    {file = "supabase-2.28.0-py3-none-any.whl", hash = "sha256:42776971c7d0ccca16034df1ab96a31c50228eb1eb19da4249ad2f756fc20272"},
-    {file = "supabase-2.27.3.tar.gz", hash = "sha256:5e5a348232ac4315c1032ddd687278f0b982465471f0cbb52bca7e6a66495ff3"},
+    {file = "supabase-2.28.0.tar.gz", hash = "sha256:aea299aaab2a2eed3c57e0be7fc035c6807214194cce795a3575add20268ece1"},
 ]
 
 [package.dependencies]
 httpx = ">=0.26,<0.29"
-postgrest = "2.27.3"
+postgrest = "2.28.0"
-realtime = "2.27.3"
+realtime = "2.28.0"
-storage3 = "2.27.3"
+storage3 = "2.28.0"
-supabase-auth = "2.27.3"
+supabase-auth = "2.28.0"
-supabase-functions = "2.27.3"
+supabase-functions = "2.28.0"
 yarl = ">=1.22.0"
 
 [[package]]
 name = "supabase-auth"
-version = "2.27.3"
+version = "2.28.0"
 description = "Python Client Library for Supabase Auth"
 optional = false
 python-versions = ">=3.9"
 groups = ["main"]
 files = [
-    {file = "supabase_auth-2.27.3-py3-none-any.whl", hash = "sha256:82a4262eaad85383319d394dab0eea11fcf3ebd774062aef8ea3874ae2f02579"},
+    {file = "supabase_auth-2.28.0-py3-none-any.whl", hash = "sha256:2ac85026cc285054c7fa6d41924f3a333e9ec298c013e5b5e1754039ba7caec9"},
-    {file = "supabase_auth-2.27.3.tar.gz", hash = "sha256:39894d4bc60b6f23b5cff4d0d7d4c1659e5d69563cadf014d4896f780ca8ca78"},
+    {file = "supabase_auth-2.28.0.tar.gz", hash = "sha256:2bb8f18ff39934e44b28f10918db965659f3735cd6fbfcc022fe0b82dbf8233e"},
 ]
 
 [package.dependencies]
@@ -7129,14 +7129,14 @@ pyjwt = {version = ">=2.10.1", extras = ["crypto"]}
 
 [[package]]
 name = "supabase-functions"
-version = "2.27.3"
+version = "2.28.0"
 description = "Library for Supabase Functions"
 optional = false
 python-versions = ">=3.9"
 groups = ["main"]
 files = [
-    {file = "supabase_functions-2.27.3-py3-none-any.whl", hash = "sha256:9d14a931d49ede1c6cf5fbfceb11c44061535ba1c3f310f15384964d86a83d9e"},
+    {file = "supabase_functions-2.28.0-py3-none-any.whl", hash = "sha256:30bf2d586f8df285faf0621bb5d5bb3ec3157234fc820553ca156f009475e4ae"},
-    {file = "supabase_functions-2.27.3.tar.gz", hash = "sha256:e954f1646da8ca6e7e16accef58d0884a5f97b25956ee98e7d4927a210ed92f9"},
+    {file = "supabase_functions-2.28.0.tar.gz", hash = "sha256:db3dddfc37aca5858819eb461130968473bd8c75bd284581013958526dac718b"},
 ]
 
 [package.dependencies]
@@ -8440,4 +8440,4 @@ 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 = "c06e96ad49388ba7a46786e9ea55ea2c1a57408e15613237b4bee40a592a12af"
+content-hash = "fa9c5deadf593e815dd2190f58e22152373900603f5f244b9616cd721de84d2f"

autogpt_platform/backend/pyproject.toml

@@ -65,7 +65,7 @@ sentry-sdk = {extras = ["anthropic", "fastapi", "launchdarkly", "openai", "sqlal
 sqlalchemy = "^2.0.40"
 strenum = "^0.4.9"
 stripe = "^11.5.0"
-supabase = "2.27.3"
+supabase = "2.28.0"
 tenacity = "^9.1.4"
 todoist-api-python = "^2.1.7"
 tweepy = "^4.16.0"

autogpt_platform/docker-compose.platform.yml

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

autogpt_platform/frontend/src/app/(platform)/build/components/BuilderActions/components/RunGraph/useRunGraph.ts

@@ -4,7 +4,7 @@ import {
 } from "@/app/api/__generated__/endpoints/graphs/graphs";
 import { useToast } from "@/components/molecules/Toast/use-toast";
 import { parseAsInteger, parseAsString, useQueryStates } from "nuqs";
-import { GraphExecutionMeta } from "@/app/(platform)/library/agents/[id]/components/OldAgentLibraryView/use-agent-runs";
+import { GraphExecutionMeta } from "@/app/api/__generated__/models/graphExecutionMeta";
 import { useGraphStore } from "@/app/(platform)/build/stores/graphStore";
 import { useShallow } from "zustand/react/shallow";
 import { useEffect, useState } from "react";

autogpt_platform/frontend/src/app/(platform)/build/components/legacy-builder/RunnerInputUI.tsx

@@ -1,6 +1,6 @@
 import { useCallback } from "react";
 
-import { AgentRunDraftView } from "@/app/(platform)/library/agents/[id]/components/OldAgentLibraryView/components/agent-run-draft-view";
+import { AgentRunDraftView } from "@/app/(platform)/build/components/legacy-builder/agent-run-draft-view";
 import { Dialog } from "@/components/molecules/Dialog/Dialog";
 import type {
   CredentialsMetaInput,

autogpt_platform/frontend/src/app/(platform)/build/components/legacy-builder/SaveControl.tsx

@@ -18,7 +18,7 @@ import {
 import { useToast } from "@/components/molecules/Toast/use-toast";
 import { useQueryClient } from "@tanstack/react-query";
 import { getGetV2ListMySubmissionsQueryKey } from "@/app/api/__generated__/endpoints/store/store";
-import { CronExpressionDialog } from "@/app/(platform)/library/agents/[id]/components/OldAgentLibraryView/components/cron-scheduler-dialog";
+import { CronExpressionDialog } from "@/components/contextual/CronScheduler/cron-scheduler-dialog";
 import { humanizeCronExpression } from "@/lib/cron-expression-utils";
 import { CalendarClockIcon } from "lucide-react";
 

autogpt_platform/frontend/src/app/(platform)/build/components/legacy-builder/agent-run-draft-view.tsx

@@ -20,7 +20,7 @@ import {
 import { useBackendAPI } from "@/lib/autogpt-server-api/context";
 
 import { RunAgentInputs } from "@/app/(platform)/library/agents/[id]/components/NewAgentLibraryView/components/modals/RunAgentInputs/RunAgentInputs";
-import { ScheduleTaskDialog } from "@/app/(platform)/library/agents/[id]/components/OldAgentLibraryView/components/cron-scheduler-dialog";
+import { ScheduleTaskDialog } from "@/components/contextual/CronScheduler/cron-scheduler-dialog";
 import ActionButtonGroup from "@/components/__legacy__/action-button-group";
 import type { ButtonAction } from "@/components/__legacy__/types";
 import {
@@ -53,7 +53,10 @@ import { ClockIcon, CopyIcon, InfoIcon } from "@phosphor-icons/react";
 import { CalendarClockIcon, Trash2Icon } from "lucide-react";
 
 import { analytics } from "@/services/analytics";
-import { AgentStatus, AgentStatusChip } from "./agent-status-chip";
+import {
+  AgentStatus,
+  AgentStatusChip,
+} from "@/app/(platform)/build/components/legacy-builder/agent-status-chip";
 
 export function AgentRunDraftView({
   graph,

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

@@ -15,6 +15,10 @@ 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";
@@ -254,6 +258,20 @@ 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:
                       return null;
                   }

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

@@ -14,6 +14,10 @@ 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";
@@ -45,6 +49,8 @@ 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;
 
@@ -1421,6 +1427,235 @@ 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/FeatureRequests/FeatureRequests.tsx

@@ -0,0 +1,227 @@
+"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

@@ -0,0 +1,271 @@
+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/RunBlock/RunBlock.tsx

@@ -3,6 +3,7 @@
 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";
@@ -11,6 +12,7 @@ import {
   getAnimationText,
   getRunBlockToolOutput,
   isRunBlockBlockOutput,
+  isRunBlockDetailsOutput,
   isRunBlockErrorOutput,
   isRunBlockSetupRequirementsOutput,
   ToolIcon,
@@ -41,6 +43,7 @@ export function RunBlockTool({ part }: Props) {
     part.state === "output-available" &&
     !!output &&
     (isRunBlockBlockOutput(output) ||
+      isRunBlockDetailsOutput(output) ||
       isRunBlockSetupRequirementsOutput(output) ||
       isRunBlockErrorOutput(output));
 
@@ -58,6 +61,10 @@ 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

@@ -0,0 +1,188 @@
+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

@@ -0,0 +1,103 @@
+"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

@@ -10,18 +10,37 @@ 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,
 ]);
@@ -35,6 +54,15 @@ 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 {
@@ -64,6 +92,7 @@ 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;
@@ -84,17 +113,25 @@ 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();
-  const blockText = blockId ? ` "${blockId}"` : "";
+  // Prefer block_name if available, otherwise fall back to block_id
+  const blockText = blockName
+    ? ` "${blockName}"`
+    : blockId
+      ? ` "${blockId}"`
+      : "";
 
   switch (part.state) {
     case "input-streaming":
     case "input-available":
-      return `Running the block${blockText}`;
+      return `Running${blockText}`;
     case "output-available": {
       const output = parseOutput(part.output);
-      if (!output) return `Running the block${blockText}`;
+      if (!output) return `Running${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}"`;
       }
@@ -158,6 +195,21 @@ 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)/library/agents/[id]/components/OldAgentLibraryView/OldAgentLibraryView.tsx

@@ -1,631 +0,0 @@
-"use client";
-import { useParams, useRouter } from "next/navigation";
-import { useQueryState } from "nuqs";
-import React, {
-  useCallback,
-  useEffect,
-  useMemo,
-  useRef,
-  useState,
-} from "react";
-
-import {
-  Graph,
-  GraphExecution,
-  GraphExecutionID,
-  GraphExecutionMeta,
-  GraphID,
-  LibraryAgent,
-  LibraryAgentID,
-  LibraryAgentPreset,
-  LibraryAgentPresetID,
-  Schedule,
-  ScheduleID,
-} from "@/lib/autogpt-server-api";
-import { useBackendAPI } from "@/lib/autogpt-server-api/context";
-import { exportAsJSONFile } from "@/lib/utils";
-
-import DeleteConfirmDialog from "@/components/__legacy__/delete-confirm-dialog";
-import type { ButtonAction } from "@/components/__legacy__/types";
-import { Button } from "@/components/__legacy__/ui/button";
-import {
-  Dialog,
-  DialogContent,
-  DialogDescription,
-  DialogFooter,
-  DialogHeader,
-  DialogTitle,
-} from "@/components/__legacy__/ui/dialog";
-import LoadingBox, { LoadingSpinner } from "@/components/__legacy__/ui/loading";
-import {
-  useToast,
-  useToastOnFail,
-} from "@/components/molecules/Toast/use-toast";
-import { AgentRunDetailsView } from "./components/agent-run-details-view";
-import { AgentRunDraftView } from "./components/agent-run-draft-view";
-import { CreatePresetDialog } from "./components/create-preset-dialog";
-import { useAgentRunsInfinite } from "./use-agent-runs";
-import { AgentRunsSelectorList } from "./components/agent-runs-selector-list";
-import { AgentScheduleDetailsView } from "./components/agent-schedule-details-view";
-
-export function OldAgentLibraryView() {
-  const { id: agentID }: { id: LibraryAgentID } = useParams();
-  const [executionId, setExecutionId] = useQueryState("executionId");
-  const toastOnFail = useToastOnFail();
-  const { toast } = useToast();
-  const router = useRouter();
-  const api = useBackendAPI();
-
-  // ============================ STATE =============================
-
-  const [graph, setGraph] = useState<Graph | null>(null); // Graph version corresponding to LibraryAgent
-  const [agent, setAgent] = useState<LibraryAgent | null>(null);
-  const agentRunsQuery = useAgentRunsInfinite(graph?.id); // only runs once graph.id is known
-  const agentRuns = agentRunsQuery.agentRuns;
-  const [agentPresets, setAgentPresets] = useState<LibraryAgentPreset[]>([]);
-  const [schedules, setSchedules] = useState<Schedule[]>([]);
-  const [selectedView, selectView] = useState<
-    | { type: "run"; id?: GraphExecutionID }
-    | { type: "preset"; id: LibraryAgentPresetID }
-    | { type: "schedule"; id: ScheduleID }
-  >({ type: "run" });
-  const [selectedRun, setSelectedRun] = useState<
-    GraphExecution | GraphExecutionMeta | null
-  >(null);
-  const selectedSchedule =
-    selectedView.type == "schedule"
-      ? schedules.find((s) => s.id == selectedView.id)
-      : null;
-  const [isFirstLoad, setIsFirstLoad] = useState<boolean>(true);
-  const [agentDeleteDialogOpen, setAgentDeleteDialogOpen] =
-    useState<boolean>(false);
-  const [confirmingDeleteAgentRun, setConfirmingDeleteAgentRun] =
-    useState<GraphExecutionMeta | null>(null);
-  const [confirmingDeleteAgentPreset, setConfirmingDeleteAgentPreset] =
-    useState<LibraryAgentPresetID | null>(null);
-  const [copyAgentDialogOpen, setCopyAgentDialogOpen] = useState(false);
-  const [creatingPresetFromExecutionID, setCreatingPresetFromExecutionID] =
-    useState<GraphExecutionID | null>(null);
-
-  // Set page title with agent name
-  useEffect(() => {
-    if (agent) {
-      document.title = `${agent.name} - Library - AutoGPT Platform`;
-    }
-  }, [agent]);
-
-  const openRunDraftView = useCallback(() => {
-    selectView({ type: "run" });
-  }, []);
-
-  const selectRun = useCallback((id: GraphExecutionID) => {
-    selectView({ type: "run", id });
-  }, []);
-
-  const selectPreset = useCallback((id: LibraryAgentPresetID) => {
-    selectView({ type: "preset", id });
-  }, []);
-
-  const selectSchedule = useCallback((id: ScheduleID) => {
-    selectView({ type: "schedule", id });
-  }, []);
-
-  const graphVersions = useRef<Record<number, Graph>>({});
-  const loadingGraphVersions = useRef<Record<number, Promise<Graph>>>({});
-  const getGraphVersion = useCallback(
-    async (graphID: GraphID, version: number) => {
-      if (version in graphVersions.current)
-        return graphVersions.current[version];
-      if (version in loadingGraphVersions.current)
-        return loadingGraphVersions.current[version];
-
-      const pendingGraph = api.getGraph(graphID, version).then((graph) => {
-        graphVersions.current[version] = graph;
-        return graph;
-      });
-      // Cache promise as well to avoid duplicate requests
-      loadingGraphVersions.current[version] = pendingGraph;
-      return pendingGraph;
-    },
-    [api, graphVersions, loadingGraphVersions],
-  );
-
-  const lastRefresh = useRef<number>(0);
-  const refreshPageData = useCallback(() => {
-    if (Date.now() - lastRefresh.current < 2e3) return; // 2 second debounce
-    lastRefresh.current = Date.now();
-
-    api.getLibraryAgent(agentID).then((agent) => {
-      setAgent(agent);
-
-      getGraphVersion(agent.graph_id, agent.graph_version).then(
-        (_graph) =>
-          (graph && graph.version == _graph.version) || setGraph(_graph),
-      );
-      Promise.all([
-        agentRunsQuery.refetchRuns(),
-        api.listLibraryAgentPresets({
-          graph_id: agent.graph_id,
-          page_size: 100,
-        }),
-      ]).then(([runsQueryResult, presets]) => {
-        setAgentPresets(presets.presets);
-
-        const newestAgentRunsResponse = runsQueryResult.data?.pages[0];
-        if (!newestAgentRunsResponse || newestAgentRunsResponse.status != 200)
-          return;
-        const newestAgentRuns = newestAgentRunsResponse.data.executions;
-        // Preload the corresponding graph versions for the latest 10 runs
-        new Set(
-          newestAgentRuns.slice(0, 10).map((run) => run.graph_version),
-        ).forEach((version) => getGraphVersion(agent.graph_id, version));
-      });
-    });
-  }, [api, agentID, getGraphVersion, graph]);
-
-  // On first load: select the latest run
-  useEffect(() => {
-    // Only for first load or first execution
-    if (selectedView.id || !isFirstLoad) return;
-    if (agentRuns.length == 0 && agentPresets.length == 0) return;
-
-    setIsFirstLoad(false);
-    if (agentRuns.length > 0) {
-      // select latest run
-      const latestRun = agentRuns.reduce((latest, current) => {
-        if (!latest.started_at && !current.started_at) return latest;
-        if (!latest.started_at) return current;
-        if (!current.started_at) return latest;
-        return latest.started_at > current.started_at ? latest : current;
-      }, agentRuns[0]);
-      selectRun(latestRun.id as GraphExecutionID);
-    } else {
-      // select top preset
-      const latestPreset = agentPresets.toSorted(
-        (a, b) => b.updated_at.getTime() - a.updated_at.getTime(),
-      )[0];
-      selectPreset(latestPreset.id);
-    }
-  }, [
-    isFirstLoad,
-    selectedView.id,
-    agentRuns,
-    agentPresets,
-    selectRun,
-    selectPreset,
-  ]);
-
-  useEffect(() => {
-    if (executionId) {
-      selectRun(executionId as GraphExecutionID);
-      setExecutionId(null);
-    }
-  }, [executionId, selectRun, setExecutionId]);
-
-  // Initial load
-  useEffect(() => {
-    refreshPageData();
-
-    // Show a toast when the WebSocket connection disconnects
-    let connectionToast: ReturnType<typeof toast> | null = null;
-    const cancelDisconnectHandler = api.onWebSocketDisconnect(() => {
-      connectionToast ??= toast({
-        title: "Connection to server was lost",
-        variant: "destructive",
-        description: (
-          <div className="flex items-center">
-            Trying to reconnect...
-            <LoadingSpinner className="ml-1.5 size-3.5" />
-          </div>
-        ),
-        duration: Infinity,
-        dismissable: true,
-      });
-    });
-    const cancelConnectHandler = api.onWebSocketConnect(() => {
-      if (connectionToast)
-        connectionToast.update({
-          id: connectionToast.id,
-          title: "✅ Connection re-established",
-          variant: "default",
-          description: (
-            <div className="flex items-center">
-              Refreshing data...
-              <LoadingSpinner className="ml-1.5 size-3.5" />
-            </div>
-          ),
-          duration: 2000,
-          dismissable: true,
-        });
-      connectionToast = null;
-    });
-    return () => {
-      cancelDisconnectHandler();
-      cancelConnectHandler();
-    };
-  }, []);
-
-  // Subscribe to WebSocket updates for agent runs
-  useEffect(() => {
-    if (!agent?.graph_id) return;
-
-    return api.onWebSocketConnect(() => {
-      refreshPageData(); // Sync up on (re)connect
-
-      // Subscribe to all executions for this agent
-      api.subscribeToGraphExecutions(agent.graph_id);
-    });
-  }, [api, agent?.graph_id, refreshPageData]);
-
-  // Handle execution updates
-  useEffect(() => {
-    const detachExecUpdateHandler = api.onWebSocketMessage(
-      "graph_execution_event",
-      (data) => {
-        if (data.graph_id != agent?.graph_id) return;
-
-        agentRunsQuery.upsertAgentRun(data);
-        if (data.id === selectedView.id) {
-          // Update currently viewed run
-          setSelectedRun(data);
-        }
-      },
-    );
-
-    return () => {
-      detachExecUpdateHandler();
-    };
-  }, [api, agent?.graph_id, selectedView.id]);
-
-  // Pre-load selectedRun based on selectedView
-  useEffect(() => {
-    if (selectedView.type != "run" || !selectedView.id) return;
-
-    const newSelectedRun = agentRuns.find((run) => run.id == selectedView.id);
-    if (selectedView.id !== selectedRun?.id) {
-      // Pull partial data from "cache" while waiting for the rest to load
-      setSelectedRun((newSelectedRun as GraphExecutionMeta) ?? null);
-    }
-  }, [api, selectedView, agentRuns, selectedRun?.id]);
-
-  // Load selectedRun based on selectedView; refresh on agent refresh
-  useEffect(() => {
-    if (selectedView.type != "run" || !selectedView.id || !agent) return;
-
-    api
-      .getGraphExecutionInfo(agent.graph_id, selectedView.id)
-      .then(async (run) => {
-        // Ensure corresponding graph version is available before rendering I/O
-        await getGraphVersion(run.graph_id, run.graph_version);
-        setSelectedRun(run);
-      });
-  }, [api, selectedView, agent, getGraphVersion]);
-
-  const fetchSchedules = useCallback(async () => {
-    if (!agent) return;
-
-    setSchedules(await api.listGraphExecutionSchedules(agent.graph_id));
-  }, [api, agent?.graph_id]);
-
-  useEffect(() => {
-    fetchSchedules();
-  }, [fetchSchedules]);
-
-  // =========================== ACTIONS ============================
-
-  const deleteRun = useCallback(
-    async (run: GraphExecutionMeta) => {
-      if (run.status == "RUNNING" || run.status == "QUEUED") {
-        await api.stopGraphExecution(run.graph_id, run.id);
-      }
-      await api.deleteGraphExecution(run.id);
-
-      setConfirmingDeleteAgentRun(null);
-      if (selectedView.type == "run" && selectedView.id == run.id) {
-        openRunDraftView();
-      }
-      agentRunsQuery.removeAgentRun(run.id);
-    },
-    [api, selectedView, openRunDraftView],
-  );
-
-  const deletePreset = useCallback(
-    async (presetID: LibraryAgentPresetID) => {
-      await api.deleteLibraryAgentPreset(presetID);
-
-      setConfirmingDeleteAgentPreset(null);
-      if (selectedView.type == "preset" && selectedView.id == presetID) {
-        openRunDraftView();
-      }
-      setAgentPresets((presets) => presets.filter((p) => p.id !== presetID));
-    },
-    [api, selectedView, openRunDraftView],
-  );
-
-  const deleteSchedule = useCallback(
-    async (scheduleID: ScheduleID) => {
-      const removedSchedule =
-        await api.deleteGraphExecutionSchedule(scheduleID);
-
-      setSchedules((schedules) => {
-        const newSchedules = schedules.filter(
-          (s) => s.id !== removedSchedule.id,
-        );
-        if (
-          selectedView.type == "schedule" &&
-          selectedView.id == removedSchedule.id
-        ) {
-          if (newSchedules.length > 0) {
-            // Select next schedule if available
-            selectSchedule(newSchedules[0].id);
-          } else {
-            // Reset to draft view if current schedule was deleted
-            openRunDraftView();
-          }
-        }
-        return newSchedules;
-      });
-      openRunDraftView();
-    },
-    [schedules, api],
-  );
-
-  const handleCreatePresetFromRun = useCallback(
-    async (name: string, description: string) => {
-      if (!creatingPresetFromExecutionID) return;
-
-      await api
-        .createLibraryAgentPreset({
-          name,
-          description,
-          graph_execution_id: creatingPresetFromExecutionID,
-        })
-        .then((preset) => {
-          setAgentPresets((prev) => [...prev, preset]);
-          selectPreset(preset.id);
-          setCreatingPresetFromExecutionID(null);
-        })
-        .catch(toastOnFail("create a preset"));
-    },
-    [api, creatingPresetFromExecutionID, selectPreset, toast],
-  );
-
-  const downloadGraph = useCallback(
-    async () =>
-      agent &&
-      // Export sanitized graph from backend
-      api
-        .getGraph(agent.graph_id, agent.graph_version, true)
-        .then((graph) =>
-          exportAsJSONFile(graph, `${graph.name}_v${graph.version}.json`),
-        ),
-    [api, agent],
-  );
-
-  const copyAgent = useCallback(async () => {
-    setCopyAgentDialogOpen(false);
-    api
-      .forkLibraryAgent(agentID)
-      .then((newAgent) => {
-        router.push(`/library/agents/${newAgent.id}`);
-      })
-      .catch((error) => {
-        console.error("Error copying agent:", error);
-        toast({
-          title: "Error copying agent",
-          description: `An error occurred while copying the agent: ${error.message}`,
-          variant: "destructive",
-        });
-      });
-  }, [agentID, api, router, toast]);
-
-  const agentActions: ButtonAction[] = useMemo(
-    () => [
-      {
-        label: "Customize agent",
-        href: `/build?flowID=${agent?.graph_id}&flowVersion=${agent?.graph_version}`,
-        disabled: !agent?.can_access_graph,
-      },
-      { label: "Export agent to file", callback: downloadGraph },
-      ...(!agent?.can_access_graph
-        ? [
-            {
-              label: "Edit a copy",
-              callback: () => setCopyAgentDialogOpen(true),
-            },
-          ]
-        : []),
-      {
-        label: "Delete agent",
-        callback: () => setAgentDeleteDialogOpen(true),
-      },
-    ],
-    [agent, downloadGraph],
-  );
-
-  const runGraph =
-    graphVersions.current[selectedRun?.graph_version ?? 0] ?? graph;
-
-  const onCreateSchedule = useCallback(
-    (schedule: Schedule) => {
-      setSchedules((prev) => [...prev, schedule]);
-      selectSchedule(schedule.id);
-    },
-    [selectView],
-  );
-
-  const onCreatePreset = useCallback(
-    (preset: LibraryAgentPreset) => {
-      setAgentPresets((prev) => [...prev, preset]);
-      selectPreset(preset.id);
-    },
-    [selectPreset],
-  );
-
-  const onUpdatePreset = useCallback(
-    (updated: LibraryAgentPreset) => {
-      setAgentPresets((prev) =>
-        prev.map((p) => (p.id === updated.id ? updated : p)),
-      );
-      selectPreset(updated.id);
-    },
-    [selectPreset],
-  );
-
-  if (!agent || !graph) {
-    return <LoadingBox className="h-[90vh]" />;
-  }
-
-  return (
-    <div className="container justify-stretch p-0 pt-16 lg:flex">
-      {/* Sidebar w/ list of runs */}
-      {/* TODO: render this below header in sm and md layouts */}
-      <AgentRunsSelectorList
-        className="agpt-div w-full border-b pb-2 lg:w-auto lg:border-b-0 lg:border-r lg:pb-0"
-        agent={agent}
-        agentRunsQuery={agentRunsQuery}
-        agentPresets={agentPresets}
-        schedules={schedules}
-        selectedView={selectedView}
-        onSelectRun={selectRun}
-        onSelectPreset={selectPreset}
-        onSelectSchedule={selectSchedule}
-        onSelectDraftNewRun={openRunDraftView}
-        doDeleteRun={setConfirmingDeleteAgentRun}
-        doDeletePreset={setConfirmingDeleteAgentPreset}
-        doDeleteSchedule={deleteSchedule}
-        doCreatePresetFromRun={setCreatingPresetFromExecutionID}
-      />
-
-      <div className="flex-1">
-        {/* Header */}
-        <div className="agpt-div w-full border-b">
-          <h1
-            data-testid="agent-title"
-            className="font-poppins text-3xl font-medium"
-          >
-            {
-              agent.name /* TODO: use dynamic/custom run title - https://github.com/Significant-Gravitas/AutoGPT/issues/9184 */
-            }
-          </h1>
-        </div>
-
-        {/* Run / Schedule views */}
-        {(selectedView.type == "run" && selectedView.id ? (
-          selectedRun && runGraph ? (
-            <AgentRunDetailsView
-              agent={agent}
-              graph={runGraph}
-              run={selectedRun}
-              agentActions={agentActions}
-              onRun={selectRun}
-              doDeleteRun={() => setConfirmingDeleteAgentRun(selectedRun)}
-              doCreatePresetFromRun={() =>
-                setCreatingPresetFromExecutionID(selectedRun.id)
-              }
-            />
-          ) : null
-        ) : selectedView.type == "run" ? (
-          /* Draft new runs / Create new presets */
-          <AgentRunDraftView
-            graph={graph}
-            onRun={selectRun}
-            onCreateSchedule={onCreateSchedule}
-            onCreatePreset={onCreatePreset}
-            agentActions={agentActions}
-            recommendedScheduleCron={agent?.recommended_schedule_cron || null}
-          />
-        ) : selectedView.type == "preset" ? (
-          /* Edit & update presets */
-          <AgentRunDraftView
-            graph={graph}
-            agentPreset={
-              agentPresets.find((preset) => preset.id == selectedView.id)!
-            }
-            onRun={selectRun}
-            recommendedScheduleCron={agent?.recommended_schedule_cron || null}
-            onCreateSchedule={onCreateSchedule}
-            onUpdatePreset={onUpdatePreset}
-            doDeletePreset={setConfirmingDeleteAgentPreset}
-            agentActions={agentActions}
-          />
-        ) : selectedView.type == "schedule" ? (
-          selectedSchedule &&
-          graph && (
-            <AgentScheduleDetailsView
-              graph={graph}
-              schedule={selectedSchedule}
-              // agent={agent}
-              agentActions={agentActions}
-              onForcedRun={selectRun}
-              doDeleteSchedule={deleteSchedule}
-            />
-          )
-        ) : null) || <LoadingBox className="h-[70vh]" />}
-
-        <DeleteConfirmDialog
-          entityType="agent"
-          open={agentDeleteDialogOpen}
-          onOpenChange={setAgentDeleteDialogOpen}
-          onDoDelete={() =>
-            agent &&
-            api.deleteLibraryAgent(agent.id).then(() => router.push("/library"))
-          }
-        />
-
-        <DeleteConfirmDialog
-          entityType="agent run"
-          open={!!confirmingDeleteAgentRun}
-          onOpenChange={(open) => !open && setConfirmingDeleteAgentRun(null)}
-          onDoDelete={() =>
-            confirmingDeleteAgentRun && deleteRun(confirmingDeleteAgentRun)
-          }
-        />
-        <DeleteConfirmDialog
-          entityType={agent.has_external_trigger ? "trigger" : "agent preset"}
-          open={!!confirmingDeleteAgentPreset}
-          onOpenChange={(open) => !open && setConfirmingDeleteAgentPreset(null)}
-          onDoDelete={() =>
-            confirmingDeleteAgentPreset &&
-            deletePreset(confirmingDeleteAgentPreset)
-          }
-        />
-        {/* Copy agent confirmation dialog */}
-        <Dialog
-          onOpenChange={setCopyAgentDialogOpen}
-          open={copyAgentDialogOpen}
-        >
-          <DialogContent>
-            <DialogHeader>
-              <DialogTitle>You&apos;re making an editable copy</DialogTitle>
-              <DialogDescription className="pt-2">
-                The original Marketplace agent stays the same and cannot be
-                edited. We&apos;ll save a new version of this agent to your
-                Library. From there, you can customize it however you&apos;d
-                like by clicking &quot;Customize agent&quot; — this will open
-                the builder where you can see and modify the inner workings.
-              </DialogDescription>
-            </DialogHeader>
-            <DialogFooter className="justify-end">
-              <Button
-                type="button"
-                variant="outline"
-                onClick={() => setCopyAgentDialogOpen(false)}
-              >
-                Cancel
-              </Button>
-              <Button type="button" onClick={copyAgent}>
-                Continue
-              </Button>
-            </DialogFooter>
-          </DialogContent>
-        </Dialog>
-        <CreatePresetDialog
-          open={!!creatingPresetFromExecutionID}
-          onOpenChange={() => setCreatingPresetFromExecutionID(null)}
-          onConfirm={handleCreatePresetFromRun}
-        />
-      </div>
-    </div>
-  );
-}

autogpt_platform/frontend/src/app/(platform)/library/agents/[id]/components/OldAgentLibraryView/components/agent-run-details-view.tsx

@@ -1,445 +0,0 @@
-"use client";
-import { format, formatDistanceToNow, formatDistanceStrict } from "date-fns";
-import React, { useCallback, useMemo, useEffect } from "react";
-
-import {
-  Graph,
-  GraphExecution,
-  GraphExecutionID,
-  GraphExecutionMeta,
-  LibraryAgent,
-} from "@/lib/autogpt-server-api";
-import { useBackendAPI } from "@/lib/autogpt-server-api/context";
-
-import ActionButtonGroup from "@/components/__legacy__/action-button-group";
-import type { ButtonAction } from "@/components/__legacy__/types";
-import {
-  Card,
-  CardContent,
-  CardHeader,
-  CardTitle,
-} from "@/components/__legacy__/ui/card";
-import {
-  IconRefresh,
-  IconSquare,
-  IconCircleAlert,
-} from "@/components/__legacy__/ui/icons";
-import { Input } from "@/components/__legacy__/ui/input";
-import LoadingBox from "@/components/__legacy__/ui/loading";
-import {
-  Tooltip,
-  TooltipContent,
-  TooltipProvider,
-  TooltipTrigger,
-} from "@/components/atoms/Tooltip/BaseTooltip";
-import { useToastOnFail } from "@/components/molecules/Toast/use-toast";
-
-import { AgentRunStatus, agentRunStatusMap } from "./agent-run-status-chip";
-import useCredits from "@/hooks/useCredits";
-import { AgentRunOutputView } from "./agent-run-output-view";
-import { analytics } from "@/services/analytics";
-import { PendingReviewsList } from "@/components/organisms/PendingReviewsList/PendingReviewsList";
-import { usePendingReviewsForExecution } from "@/hooks/usePendingReviews";
-
-export function AgentRunDetailsView({
-  agent,
-  graph,
-  run,
-  agentActions,
-  onRun,
-  doDeleteRun,
-  doCreatePresetFromRun,
-}: {
-  agent: LibraryAgent;
-  graph: Graph;
-  run: GraphExecution | GraphExecutionMeta;
-  agentActions: ButtonAction[];
-  onRun: (runID: GraphExecutionID) => void;
-  doDeleteRun: () => void;
-  doCreatePresetFromRun: () => void;
-}): React.ReactNode {
-  const api = useBackendAPI();
-  const { formatCredits } = useCredits();
-
-  const runStatus: AgentRunStatus = useMemo(
-    () => agentRunStatusMap[run.status],
-    [run],
-  );
-
-  const {
-    pendingReviews,
-    isLoading: reviewsLoading,
-    refetch: refetchReviews,
-  } = usePendingReviewsForExecution(run.id);
-
-  const toastOnFail = useToastOnFail();
-
-  // Refetch pending reviews when execution status changes to REVIEW
-  useEffect(() => {
-    if (runStatus === "review" && run.id) {
-      refetchReviews();
-    }
-  }, [runStatus, run.id, refetchReviews]);
-
-  const infoStats: { label: string; value: React.ReactNode }[] = useMemo(() => {
-    if (!run) return [];
-    return [
-      {
-        label: "Status",
-        value: runStatus.charAt(0).toUpperCase() + runStatus.slice(1),
-      },
-      {
-        label: "Started",
-        value: run.started_at
-          ? `${formatDistanceToNow(run.started_at, { addSuffix: true })}, ${format(run.started_at, "HH:mm")}`
-          : "—",
-      },
-      ...(run.stats
-        ? [
-            {
-              label: "Duration",
-              value: formatDistanceStrict(0, run.stats.duration * 1000),
-            },
-            { label: "Steps", value: run.stats.node_exec_count },
-            { label: "Cost", value: formatCredits(run.stats.cost) },
-          ]
-        : []),
-    ];
-  }, [run, runStatus, formatCredits]);
-
-  const agentRunInputs:
-    | Record<
-        string,
-        {
-          title?: string;
-          /* type: BlockIOSubType; */
-          value: string | number | undefined;
-        }
-      >
-    | undefined = useMemo(() => {
-    if (!run.inputs) return undefined;
-    // TODO: show (link to) preset - https://github.com/Significant-Gravitas/AutoGPT/issues/9168
-
-    // Add type info from agent input schema
-    return Object.fromEntries(
-      Object.entries(run.inputs).map(([k, v]) => [
-        k,
-        {
-          title: graph.input_schema.properties[k]?.title,
-          // type: graph.input_schema.properties[k].type, // TODO: implement typed graph inputs
-          value: typeof v == "object" ? JSON.stringify(v, undefined, 2) : v,
-        },
-      ]),
-    );
-  }, [graph, run]);
-
-  const runAgain = useCallback(() => {
-    if (
-      !run.inputs ||
-      !(graph.credentials_input_schema?.required ?? []).every(
-        (k) => k in (run.credential_inputs ?? {}),
-      )
-    )
-      return;
-
-    if (run.preset_id) {
-      return api
-        .executeLibraryAgentPreset(
-          run.preset_id,
-          run.inputs!,
-          run.credential_inputs!,
-        )
-        .then(({ id }) => {
-          analytics.sendDatafastEvent("run_agent", {
-            name: graph.name,
-            id: graph.id,
-          });
-          onRun(id);
-        })
-        .catch(toastOnFail("execute agent preset"));
-    }
-
-    return api
-      .executeGraph(
-        graph.id,
-        graph.version,
-        run.inputs!,
-        run.credential_inputs!,
-        "library",
-      )
-      .then(({ id }) => {
-        analytics.sendDatafastEvent("run_agent", {
-          name: graph.name,
-          id: graph.id,
-        });
-        onRun(id);
-      })
-      .catch(toastOnFail("execute agent"));
-  }, [api, graph, run, onRun, toastOnFail]);
-
-  const stopRun = useCallback(
-    () => api.stopGraphExecution(graph.id, run.id),
-    [api, graph.id, run.id],
-  );
-
-  const agentRunOutputs:
-    | Record<
-        string,
-        {
-          title?: string;
-          /* type: BlockIOSubType; */
-          values: Array<React.ReactNode>;
-        }
-      >
-    | null
-    | undefined = useMemo(() => {
-    if (!("outputs" in run)) return undefined;
-    if (!["running", "success", "failed", "stopped"].includes(runStatus))
-      return null;
-
-    // Add type info from agent input schema
-    return Object.fromEntries(
-      Object.entries(run.outputs).map(([k, vv]) => [
-        k,
-        {
-          title: graph.output_schema.properties[k].title,
-          /* type: agent.output_schema.properties[k].type */
-          values: vv.map((v) =>
-            typeof v == "object" ? JSON.stringify(v, undefined, 2) : v,
-          ),
-        },
-      ]),
-    );
-  }, [graph, run, runStatus]);
-
-  const runActions: ButtonAction[] = useMemo(
-    () => [
-      ...(["running", "queued"].includes(runStatus)
-        ? ([
-            {
-              label: (
-                <>
-                  <IconSquare className="mr-2 size-4" />
-                  Stop run
-                </>
-              ),
-              variant: "secondary",
-              callback: stopRun,
-            },
-          ] satisfies ButtonAction[])
-        : []),
-      ...(["success", "failed", "stopped"].includes(runStatus) &&
-      !graph.has_external_trigger &&
-      (graph.credentials_input_schema?.required ?? []).every(
-        (k) => k in (run.credential_inputs ?? {}),
-      )
-        ? [
-            {
-              label: (
-                <>
-                  <IconRefresh className="mr-2 size-4" />
-                  Run again
-                </>
-              ),
-              callback: runAgain,
-              dataTestId: "run-again-button",
-            },
-          ]
-        : []),
-      ...(agent.can_access_graph
-        ? [
-            {
-              label: "Open run in builder",
-              href: `/build?flowID=${run.graph_id}&flowVersion=${run.graph_version}&flowExecutionID=${run.id}`,
-            },
-          ]
-        : []),
-      { label: "Create preset from run", callback: doCreatePresetFromRun },
-      { label: "Delete run", variant: "secondary", callback: doDeleteRun },
-    ],
-    [
-      runStatus,
-      runAgain,
-      stopRun,
-      doDeleteRun,
-      doCreatePresetFromRun,
-      graph.has_external_trigger,
-      graph.credentials_input_schema?.required,
-      agent.can_access_graph,
-      run.graph_id,
-      run.graph_version,
-      run.id,
-    ],
-  );
-
-  return (
-    <div className="agpt-div flex gap-6">
-      <div className="flex flex-1 flex-col gap-4">
-        <Card className="agpt-box">
-          <CardHeader>
-            <CardTitle className="font-poppins text-lg">Info</CardTitle>
-          </CardHeader>
-
-          <CardContent>
-            <div className="flex justify-stretch gap-4">
-              {infoStats.map(({ label, value }) => (
-                <div key={label} className="flex-1">
-                  <p className="text-sm font-medium text-black">{label}</p>
-                  <p className="text-sm text-neutral-600">{value}</p>
-                </div>
-              ))}
-            </div>
-            {run.status === "FAILED" && (
-              <div className="mt-4 rounded-md border border-red-200 bg-red-50 p-3 dark:border-red-800 dark:bg-red-900/20">
-                <p className="text-sm text-red-800 dark:text-red-200">
-                  <strong>Error:</strong>{" "}
-                  {run.stats?.error ||
-                    "The execution failed due to an internal error. You can re-run the agent to retry."}
-                </p>
-              </div>
-            )}
-          </CardContent>
-        </Card>
-
-        {/* Smart Agent Execution Summary */}
-        {run.stats?.activity_status && (
-          <Card className="agpt-box">
-            <CardHeader>
-              <CardTitle className="flex items-center gap-2 font-poppins text-lg">
-                Task Summary
-                <TooltipProvider>
-                  <Tooltip>
-                    <TooltipTrigger asChild>
-                      <IconCircleAlert className="size-4 cursor-help text-neutral-500 hover:text-neutral-700" />
-                    </TooltipTrigger>
-                    <TooltipContent>
-                      <p className="max-w-xs">
-                        This AI-generated summary describes how the agent
-                        handled your task. It’s an experimental feature and may
-                        occasionally be inaccurate.
-                      </p>
-                    </TooltipContent>
-                  </Tooltip>
-                </TooltipProvider>
-              </CardTitle>
-            </CardHeader>
-            <CardContent className="space-y-4">
-              <p className="text-sm leading-relaxed text-neutral-700">
-                {run.stats.activity_status}
-              </p>
-
-              {/* Correctness Score */}
-              {typeof run.stats.correctness_score === "number" && (
-                <div className="flex items-center gap-3 rounded-lg bg-neutral-50 p-3">
-                  <div className="flex items-center gap-2">
-                    <span className="text-sm font-medium text-neutral-600">
-                      Success Estimate:
-                    </span>
-                    <div className="flex items-center gap-2">
-                      <div className="relative h-2 w-16 overflow-hidden rounded-full bg-neutral-200">
-                        <div
-                          className={`h-full transition-all ${
-                            run.stats.correctness_score >= 0.8
-                              ? "bg-green-500"
-                              : run.stats.correctness_score >= 0.6
-                                ? "bg-yellow-500"
-                                : run.stats.correctness_score >= 0.4
-                                  ? "bg-orange-500"
-                                  : "bg-red-500"
-                          }`}
-                          style={{
-                            width: `${Math.round(run.stats.correctness_score * 100)}%`,
-                          }}
-                        />
-                      </div>
-                      <span className="text-sm font-medium">
-                        {Math.round(run.stats.correctness_score * 100)}%
-                      </span>
-                    </div>
-                  </div>
-                  <TooltipProvider>
-                    <Tooltip>
-                      <TooltipTrigger asChild>
-                        <IconCircleAlert className="size-4 cursor-help text-neutral-400 hover:text-neutral-600" />
-                      </TooltipTrigger>
-                      <TooltipContent>
-                        <p className="max-w-xs">
-                          AI-generated estimate of how well this execution
-                          achieved its intended purpose. This score indicates
-                          {run.stats.correctness_score >= 0.8
-                            ? " the agent was highly successful."
-                            : run.stats.correctness_score >= 0.6
-                              ? " the agent was mostly successful with minor issues."
-                              : run.stats.correctness_score >= 0.4
-                                ? " the agent was partially successful with some gaps."
-                                : " the agent had limited success with significant issues."}
-                        </p>
-                      </TooltipContent>
-                    </Tooltip>
-                  </TooltipProvider>
-                </div>
-              )}
-            </CardContent>
-          </Card>
-        )}
-
-        {agentRunOutputs !== null && (
-          <AgentRunOutputView agentRunOutputs={agentRunOutputs} />
-        )}
-
-        {/* Pending Reviews Section */}
-        {runStatus === "review" && (
-          <Card className="agpt-box">
-            <CardHeader>
-              <CardTitle className="font-poppins text-lg">
-                Pending Reviews ({pendingReviews.length})
-              </CardTitle>
-            </CardHeader>
-            <CardContent>
-              {reviewsLoading ? (
-                <LoadingBox spinnerSize={12} className="h-24" />
-              ) : pendingReviews.length > 0 ? (
-                <PendingReviewsList
-                  reviews={pendingReviews}
-                  onReviewComplete={refetchReviews}
-                  emptyMessage="No pending reviews for this execution"
-                />
-              ) : (
-                <div className="py-4 text-neutral-600">
-                  No pending reviews for this execution
-                </div>
-              )}
-            </CardContent>
-          </Card>
-        )}
-
-        <Card className="agpt-box">
-          <CardHeader>
-            <CardTitle className="font-poppins text-lg">Input</CardTitle>
-          </CardHeader>
-          <CardContent className="flex flex-col gap-4">
-            {agentRunInputs !== undefined ? (
-              Object.entries(agentRunInputs).map(([key, { title, value }]) => (
-                <div key={key} className="flex flex-col gap-1.5">
-                  <label className="text-sm font-medium">{title || key}</label>
-                  <Input value={value} className="rounded-full" disabled />
-                </div>
-              ))
-            ) : (
-              <LoadingBox spinnerSize={12} className="h-24" />
-            )}
-          </CardContent>
-        </Card>
-      </div>
-
-      {/* Run / Agent Actions */}
-      <aside className="w-48 xl:w-56">
-        <div className="flex flex-col gap-8">
-          <ActionButtonGroup title="Run actions" actions={runActions} />
-
-          <ActionButtonGroup title="Agent actions" actions={agentActions} />
-        </div>
-      </aside>
-    </div>
-  );
-}

autogpt_platform/frontend/src/app/(platform)/library/agents/[id]/components/OldAgentLibraryView/components/agent-run-output-view.tsx

@@ -1,178 +0,0 @@
-"use client";
-
-import { Flag, useGetFlag } from "@/services/feature-flags/use-get-flag";
-import React, { useMemo } from "react";
-
-import {
-  Card,
-  CardContent,
-  CardHeader,
-  CardTitle,
-} from "@/components/__legacy__/ui/card";
-
-import LoadingBox from "@/components/__legacy__/ui/loading";
-import type { OutputMetadata } from "../../../../../../../../components/contextual/OutputRenderers";
-import {
-  globalRegistry,
-  OutputActions,
-  OutputItem,
-} from "../../../../../../../../components/contextual/OutputRenderers";
-
-export function AgentRunOutputView({
-  agentRunOutputs,
-}: {
-  agentRunOutputs:
-    | Record<
-        string,
-        {
-          title?: string;
-          /* type: BlockIOSubType; */
-          values: Array<React.ReactNode>;
-        }
-      >
-    | undefined;
-}) {
-  const enableEnhancedOutputHandling = useGetFlag(
-    Flag.ENABLE_ENHANCED_OUTPUT_HANDLING,
-  );
-
-  // Prepare items for the renderer system
-  const outputItems = useMemo(() => {
-    if (!agentRunOutputs) return [];
-
-    const items: Array<{
-      key: string;
-      label: string;
-      value: unknown;
-      metadata?: OutputMetadata;
-      renderer: any;
-    }> = [];
-
-    Object.entries(agentRunOutputs).forEach(([key, { title, values }]) => {
-      values.forEach((value, index) => {
-        // Enhanced metadata extraction
-        const metadata: OutputMetadata = {};
-
-        // Type guard to safely access properties
-        if (
-          typeof value === "object" &&
-          value !== null &&
-          !React.isValidElement(value)
-        ) {
-          const objValue = value as any;
-          if (objValue.type) metadata.type = objValue.type;
-          if (objValue.mimeType) metadata.mimeType = objValue.mimeType;
-          if (objValue.filename) metadata.filename = objValue.filename;
-        }
-
-        const renderer = globalRegistry.getRenderer(value, metadata);
-        if (renderer) {
-          items.push({
-            key: `${key}-${index}`,
-            label: index === 0 ? title || key : "",
-            value,
-            metadata,
-            renderer,
-          });
-        } else {
-          const textRenderer = globalRegistry
-            .getAllRenderers()
-            .find((r) => r.name === "TextRenderer");
-          if (textRenderer) {
-            items.push({
-              key: `${key}-${index}`,
-              label: index === 0 ? title || key : "",
-              value: JSON.stringify(value, null, 2),
-              metadata,
-              renderer: textRenderer,
-            });
-          }
-        }
-      });
-    });
-
-    return items;
-  }, [agentRunOutputs]);
-
-  return (
-    <>
-      {enableEnhancedOutputHandling ? (
-        <Card className="agpt-box" style={{ maxWidth: "950px" }}>
-          <CardHeader>
-            <div className="flex items-center justify-between">
-              <CardTitle className="font-poppins text-lg">Output</CardTitle>
-              {outputItems.length > 0 && (
-                <OutputActions
-                  items={outputItems.map((item) => ({
-                    value: item.value,
-                    metadata: item.metadata,
-                    renderer: item.renderer,
-                  }))}
-                />
-              )}
-            </div>
-          </CardHeader>
-
-          <CardContent
-            className="flex flex-col gap-4"
-            style={{ maxWidth: "660px" }}
-          >
-            {agentRunOutputs !== undefined ? (
-              outputItems.length > 0 ? (
-                outputItems.map((item) => (
-                  <OutputItem
-                    key={item.key}
-                    value={item.value}
-                    metadata={item.metadata}
-                    renderer={item.renderer}
-                    label={item.label}
-                  />
-                ))
-              ) : (
-                <p className="text-sm text-muted-foreground">
-                  No outputs to display
-                </p>
-              )
-            ) : (
-              <LoadingBox spinnerSize={12} className="h-24" />
-            )}
-          </CardContent>
-        </Card>
-      ) : (
-        <Card className="agpt-box" style={{ maxWidth: "950px" }}>
-          <CardHeader>
-            <CardTitle className="font-poppins text-lg">Output</CardTitle>
-          </CardHeader>
-
-          <CardContent
-            className="flex flex-col gap-4"
-            style={{ maxWidth: "660px" }}
-          >
-            {agentRunOutputs !== undefined ? (
-              Object.entries(agentRunOutputs).map(
-                ([key, { title, values }]) => (
-                  <div key={key} className="flex flex-col gap-1.5">
-                    <label className="text-sm font-medium">
-                      {title || key}
-                    </label>
-                    {values.map((value, i) => (
-                      <p
-                        className="resize-none overflow-x-auto whitespace-pre-wrap break-words border-none text-sm text-neutral-700 disabled:cursor-not-allowed"
-                        key={i}
-                      >
-                        {value}
-                      </p>
-                    ))}
-                    {/* TODO: pretty type-dependent rendering */}
-                  </div>
-                ),
-              )
-            ) : (
-              <LoadingBox spinnerSize={12} className="h-24" />
-            )}
-          </CardContent>
-        </Card>
-      )}
-    </>
-  );
-}

autogpt_platform/frontend/src/app/(platform)/library/agents/[id]/components/OldAgentLibraryView/components/agent-run-status-chip.tsx

@@ -1,68 +0,0 @@
-import React from "react";
-
-import { Badge } from "@/components/__legacy__/ui/badge";
-
-import { GraphExecutionMeta } from "@/lib/autogpt-server-api/types";
-
-export type AgentRunStatus =
-  | "success"
-  | "failed"
-  | "queued"
-  | "running"
-  | "stopped"
-  | "scheduled"
-  | "draft"
-  | "review";
-
-export const agentRunStatusMap: Record<
-  GraphExecutionMeta["status"],
-  AgentRunStatus
-> = {
-  INCOMPLETE: "draft",
-  COMPLETED: "success",
-  FAILED: "failed",
-  QUEUED: "queued",
-  RUNNING: "running",
-  TERMINATED: "stopped",
-  REVIEW: "review",
-};
-
-const statusData: Record<
-  AgentRunStatus,
-  { label: string; variant: keyof typeof statusStyles }
-> = {
-  success: { label: "Success", variant: "success" },
-  running: { label: "Running", variant: "info" },
-  failed: { label: "Failed", variant: "destructive" },
-  queued: { label: "Queued", variant: "warning" },
-  draft: { label: "Draft", variant: "secondary" },
-  stopped: { label: "Stopped", variant: "secondary" },
-  scheduled: { label: "Scheduled", variant: "secondary" },
-  review: { label: "In Review", variant: "warning" },
-};
-
-const statusStyles = {
-  success:
-    "bg-green-100 text-green-800 hover:bg-green-100 hover:text-green-800",
-  destructive: "bg-red-100 text-red-800 hover:bg-red-100 hover:text-red-800",
-  warning:
-    "bg-yellow-100 text-yellow-800 hover:bg-yellow-100 hover:text-yellow-800",
-  info: "bg-blue-100 text-blue-800 hover:bg-blue-100 hover:text-blue-800",
-  secondary:
-    "bg-slate-100 text-slate-800 hover:bg-slate-100 hover:text-slate-800",
-};
-
-export function AgentRunStatusChip({
-  status,
-}: {
-  status: AgentRunStatus;
-}): React.ReactElement {
-  return (
-    <Badge
-      variant="secondary"
-      className={`text-xs font-medium ${statusStyles[statusData[status]?.variant]} rounded-[45px] px-[9px] py-[3px]`}
-    >
-      {statusData[status]?.label}
-    </Badge>
-  );
-}

autogpt_platform/frontend/src/app/(platform)/library/agents/[id]/components/OldAgentLibraryView/components/agent-run-summary-card.tsx

@@ -1,130 +0,0 @@
-import React from "react";
-import { formatDistanceToNow, isPast } from "date-fns";
-
-import { cn } from "@/lib/utils";
-
-import { Link2Icon, Link2OffIcon, MoreVertical } from "lucide-react";
-import { Card, CardContent } from "@/components/__legacy__/ui/card";
-import { Button } from "@/components/__legacy__/ui/button";
-import {
-  DropdownMenu,
-  DropdownMenuContent,
-  DropdownMenuItem,
-  DropdownMenuTrigger,
-} from "@/components/__legacy__/ui/dropdown-menu";
-
-import { AgentStatus, AgentStatusChip } from "./agent-status-chip";
-import { AgentRunStatus, AgentRunStatusChip } from "./agent-run-status-chip";
-import { PushPinSimpleIcon } from "@phosphor-icons/react";
-
-export type AgentRunSummaryProps = (
-  | {
-      type: "run";
-      status: AgentRunStatus;
-    }
-  | {
-      type: "preset";
-      status?: undefined;
-    }
-  | {
-      type: "preset.triggered";
-      status: AgentStatus;
-    }
-  | {
-      type: "schedule";
-      status: "scheduled";
-    }
-) & {
-  title: string;
-  timestamp?: number | Date;
-  selected?: boolean;
-  onClick?: () => void;
-  // onRename: () => void;
-  onDelete: () => void;
-  onPinAsPreset?: () => void;
-  className?: string;
-};
-
-export function AgentRunSummaryCard({
-  type,
-  status,
-  title,
-  timestamp,
-  selected = false,
-  onClick,
-  // onRename,
-  onDelete,
-  onPinAsPreset,
-  className,
-}: AgentRunSummaryProps): React.ReactElement {
-  return (
-    <Card
-      className={cn(
-        "agpt-rounded-card cursor-pointer border-zinc-300",
-        selected ? "agpt-card-selected" : "",
-        className,
-      )}
-      onClick={onClick}
-    >
-      <CardContent className="relative p-2.5 lg:p-4">
-        {(type == "run" || type == "schedule") && (
-          <AgentRunStatusChip status={status} />
-        )}
-        {type == "preset" && (
-          <div className="flex items-center text-sm font-medium text-neutral-700">
-            <PushPinSimpleIcon className="mr-1 size-4 text-foreground" /> Preset
-          </div>
-        )}
-        {type == "preset.triggered" && (
-          <div className="flex items-center justify-between">
-            <AgentStatusChip status={status} />
-
-            <div className="flex items-center text-sm font-medium text-neutral-700">
-              {status == "inactive" ? (
-                <Link2OffIcon className="mr-1 size-4 text-foreground" />
-              ) : (
-                <Link2Icon className="mr-1 size-4 text-foreground" />
-              )}{" "}
-              Trigger
-            </div>
-          </div>
-        )}
-
-        <div className="mt-5 flex items-center justify-between">
-          <h3 className="truncate pr-2 text-base font-medium text-neutral-900">
-            {title}
-          </h3>
-
-          <DropdownMenu>
-            <DropdownMenuTrigger asChild>
-              <Button variant="ghost" className="h-5 w-5 p-0">
-                <MoreVertical className="h-5 w-5" />
-              </Button>
-            </DropdownMenuTrigger>
-            <DropdownMenuContent>
-              {onPinAsPreset && (
-                <DropdownMenuItem onClick={onPinAsPreset}>
-                  Pin as a preset
-                </DropdownMenuItem>
-              )}
-
-              {/* <DropdownMenuItem onClick={onRename}>Rename</DropdownMenuItem> */}
-
-              <DropdownMenuItem onClick={onDelete}>Delete</DropdownMenuItem>
-            </DropdownMenuContent>
-          </DropdownMenu>
-        </div>
-
-        {timestamp && (
-          <p
-            className="mt-1 text-sm font-normal text-neutral-500"
-            title={new Date(timestamp).toString()}
-          >
-            {isPast(timestamp) ? "Ran" : "Runs in"}{" "}
-            {formatDistanceToNow(timestamp, { addSuffix: true })}
-          </p>
-        )}
-      </CardContent>
-    </Card>
-  );
-}

autogpt_platform/frontend/src/app/(platform)/library/agents/[id]/components/OldAgentLibraryView/components/agent-runs-selector-list.tsx

@@ -1,237 +0,0 @@
-"use client";
-import { Plus } from "lucide-react";
-import React, { useEffect, useState } from "react";
-
-import {
-  GraphExecutionID,
-  GraphExecutionMeta,
-  LibraryAgent,
-  LibraryAgentPreset,
-  LibraryAgentPresetID,
-  Schedule,
-  ScheduleID,
-} from "@/lib/autogpt-server-api";
-import { cn } from "@/lib/utils";
-
-import { Badge } from "@/components/__legacy__/ui/badge";
-import { Button } from "@/components/atoms/Button/Button";
-import LoadingBox, { LoadingSpinner } from "@/components/__legacy__/ui/loading";
-import { Separator } from "@/components/__legacy__/ui/separator";
-import { ScrollArea } from "@/components/__legacy__/ui/scroll-area";
-import { InfiniteScroll } from "@/components/contextual/InfiniteScroll/InfiniteScroll";
-import { AgentRunsQuery } from "../use-agent-runs";
-import { agentRunStatusMap } from "./agent-run-status-chip";
-import { AgentRunSummaryCard } from "./agent-run-summary-card";
-
-interface AgentRunsSelectorListProps {
-  agent: LibraryAgent;
-  agentRunsQuery: AgentRunsQuery;
-  agentPresets: LibraryAgentPreset[];
-  schedules: Schedule[];
-  selectedView: { type: "run" | "preset" | "schedule"; id?: string };
-  allowDraftNewRun?: boolean;
-  onSelectRun: (id: GraphExecutionID) => void;
-  onSelectPreset: (preset: LibraryAgentPresetID) => void;
-  onSelectSchedule: (id: ScheduleID) => void;
-  onSelectDraftNewRun: () => void;
-  doDeleteRun: (id: GraphExecutionMeta) => void;
-  doDeletePreset: (id: LibraryAgentPresetID) => void;
-  doDeleteSchedule: (id: ScheduleID) => void;
-  doCreatePresetFromRun?: (id: GraphExecutionID) => void;
-  className?: string;
-}
-
-export function AgentRunsSelectorList({
-  agent,
-  agentRunsQuery: {
-    agentRuns,
-    agentRunCount,
-    agentRunsLoading,
-    hasMoreRuns,
-    fetchMoreRuns,
-    isFetchingMoreRuns,
-  },
-  agentPresets,
-  schedules,
-  selectedView,
-  allowDraftNewRun = true,
-  onSelectRun,
-  onSelectPreset,
-  onSelectSchedule,
-  onSelectDraftNewRun,
-  doDeleteRun,
-  doDeletePreset,
-  doDeleteSchedule,
-  doCreatePresetFromRun,
-  className,
-}: AgentRunsSelectorListProps): React.ReactElement {
-  const [activeListTab, setActiveListTab] = useState<"runs" | "scheduled">(
-    "runs",
-  );
-
-  useEffect(() => {
-    if (selectedView.type === "schedule") {
-      setActiveListTab("scheduled");
-    } else {
-      setActiveListTab("runs");
-    }
-  }, [selectedView]);
-
-  const listItemClasses = "h-28 w-72 lg:w-full lg:h-32";
-
-  return (
-    <aside className={cn("flex flex-col gap-4", className)}>
-      {allowDraftNewRun ? (
-        <Button
-          className={"mb-4 hidden lg:flex"}
-          onClick={onSelectDraftNewRun}
-          leftIcon={<Plus className="h-6 w-6" />}
-        >
-          New {agent.has_external_trigger ? "trigger" : "run"}
-        </Button>
-      ) : null}
-
-      <div className="flex gap-2">
-        <Badge
-          variant={activeListTab === "runs" ? "secondary" : "outline"}
-          className="cursor-pointer gap-2 rounded-full text-base"
-          onClick={() => setActiveListTab("runs")}
-        >
-          <span>Runs</span>
-          <span className="text-neutral-600">
-            {agentRunCount ?? <LoadingSpinner className="size-4" />}
-          </span>
-        </Badge>
-
-        <Badge
-          variant={activeListTab === "scheduled" ? "secondary" : "outline"}
-          className="cursor-pointer gap-2 rounded-full text-base"
-          onClick={() => setActiveListTab("scheduled")}
-        >
-          <span>Scheduled</span>
-          <span className="text-neutral-600">{schedules.length}</span>
-        </Badge>
-      </div>
-
-      {/* Runs / Schedules list */}
-      {agentRunsLoading && activeListTab === "runs" ? (
-        <LoadingBox className="h-28 w-full lg:h-[calc(100vh-300px)] lg:w-72 xl:w-80" />
-      ) : (
-        <ScrollArea
-          className="w-full lg:h-[calc(100vh-300px)] lg:w-72 xl:w-80"
-          orientation={window.innerWidth >= 1024 ? "vertical" : "horizontal"}
-        >
-          <InfiniteScroll
-            direction={window.innerWidth >= 1024 ? "vertical" : "horizontal"}
-            hasNextPage={hasMoreRuns}
-            fetchNextPage={fetchMoreRuns}
-            isFetchingNextPage={isFetchingMoreRuns}
-          >
-            <div className="flex items-center gap-2 lg:flex-col">
-              {/* New Run button - only in small layouts */}
-              {allowDraftNewRun && (
-                <Button
-                  size="large"
-                  className={
-                    "flex h-12 w-40 items-center gap-2 py-6 lg:hidden " +
-                    (selectedView.type == "run" && !selectedView.id
-                      ? "agpt-card-selected text-accent"
-                      : "")
-                  }
-                  onClick={onSelectDraftNewRun}
-                  leftIcon={<Plus className="h-6 w-6" />}
-                >
-                  New {agent.has_external_trigger ? "trigger" : "run"}
-                </Button>
-              )}
-
-              {activeListTab === "runs" ? (
-                <>
-                  {agentPresets
-                    .filter((preset) => preset.webhook) // Triggers
-                    .toSorted(
-                      (a, b) => b.updated_at.getTime() - a.updated_at.getTime(),
-                    )
-                    .map((preset) => (
-                      <AgentRunSummaryCard
-                        className={cn(listItemClasses, "lg:h-auto")}
-                        key={preset.id}
-                        type="preset.triggered"
-                        status={preset.is_active ? "active" : "inactive"}
-                        title={preset.name}
-                        // timestamp={preset.last_run_time} // TODO: implement this
-                        selected={selectedView.id === preset.id}
-                        onClick={() => onSelectPreset(preset.id)}
-                        onDelete={() => doDeletePreset(preset.id)}
-                      />
-                    ))}
-                  {agentPresets
-                    .filter((preset) => !preset.webhook) // Presets
-                    .toSorted(
-                      (a, b) => b.updated_at.getTime() - a.updated_at.getTime(),
-                    )
-                    .map((preset) => (
-                      <AgentRunSummaryCard
-                        className={cn(listItemClasses, "lg:h-auto")}
-                        key={preset.id}
-                        type="preset"
-                        title={preset.name}
-                        // timestamp={preset.last_run_time} // TODO: implement this
-                        selected={selectedView.id === preset.id}
-                        onClick={() => onSelectPreset(preset.id)}
-                        onDelete={() => doDeletePreset(preset.id)}
-                      />
-                    ))}
-                  {agentPresets.length > 0 && <Separator className="my-1" />}
-                  {agentRuns
-                    .toSorted((a, b) => {
-                      const aTime = a.started_at?.getTime() ?? 0;
-                      const bTime = b.started_at?.getTime() ?? 0;
-                      return bTime - aTime;
-                    })
-                    .map((run) => (
-                      <AgentRunSummaryCard
-                        className={listItemClasses}
-                        key={run.id}
-                        type="run"
-                        status={agentRunStatusMap[run.status]}
-                        title={
-                          (run.preset_id
-                            ? agentPresets.find((p) => p.id == run.preset_id)
-                                ?.name
-                            : null) ?? agent.name
-                        }
-                        timestamp={run.started_at ?? undefined}
-                        selected={selectedView.id === run.id}
-                        onClick={() => onSelectRun(run.id)}
-                        onDelete={() => doDeleteRun(run as GraphExecutionMeta)}
-                        onPinAsPreset={
-                          doCreatePresetFromRun
-                            ? () => doCreatePresetFromRun(run.id)
-                            : undefined
-                        }
-                      />
-                    ))}
-                </>
-              ) : (
-                schedules.map((schedule) => (
-                  <AgentRunSummaryCard
-                    className={listItemClasses}
-                    key={schedule.id}
-                    type="schedule"
-                    status="scheduled" // TODO: implement active/inactive status for schedules
-                    title={schedule.name}
-                    timestamp={schedule.next_run_time}
-                    selected={selectedView.id === schedule.id}
-                    onClick={() => onSelectSchedule(schedule.id)}
-                    onDelete={() => doDeleteSchedule(schedule.id)}
-                  />
-                ))
-              )}
-            </div>
-          </InfiniteScroll>
-        </ScrollArea>
-      )}
-    </aside>
-  );
-}

autogpt_platform/frontend/src/app/(platform)/library/agents/[id]/components/OldAgentLibraryView/components/agent-schedule-details-view.tsx

@@ -1,180 +0,0 @@
-"use client";
-import React, { useCallback, useMemo } from "react";
-
-import {
-  Graph,
-  GraphExecutionID,
-  Schedule,
-  ScheduleID,
-} from "@/lib/autogpt-server-api";
-import { useBackendAPI } from "@/lib/autogpt-server-api/context";
-
-import ActionButtonGroup from "@/components/__legacy__/action-button-group";
-import type { ButtonAction } from "@/components/__legacy__/types";
-import {
-  Card,
-  CardContent,
-  CardHeader,
-  CardTitle,
-} from "@/components/__legacy__/ui/card";
-import { IconCross } from "@/components/__legacy__/ui/icons";
-import { Input } from "@/components/__legacy__/ui/input";
-import LoadingBox from "@/components/__legacy__/ui/loading";
-import { useToastOnFail } from "@/components/molecules/Toast/use-toast";
-import { humanizeCronExpression } from "@/lib/cron-expression-utils";
-import { formatScheduleTime } from "@/lib/timezone-utils";
-import { useUserTimezone } from "@/lib/hooks/useUserTimezone";
-import { PlayIcon } from "lucide-react";
-
-import { AgentRunStatus } from "./agent-run-status-chip";
-
-export function AgentScheduleDetailsView({
-  graph,
-  schedule,
-  agentActions,
-  onForcedRun,
-  doDeleteSchedule,
-}: {
-  graph: Graph;
-  schedule: Schedule;
-  agentActions: ButtonAction[];
-  onForcedRun: (runID: GraphExecutionID) => void;
-  doDeleteSchedule: (scheduleID: ScheduleID) => void;
-}): React.ReactNode {
-  const api = useBackendAPI();
-
-  const selectedRunStatus: AgentRunStatus = "scheduled";
-
-  const toastOnFail = useToastOnFail();
-
-  // Get user's timezone for displaying schedule times
-  const userTimezone = useUserTimezone();
-
-  const infoStats: { label: string; value: React.ReactNode }[] = useMemo(() => {
-    return [
-      {
-        label: "Status",
-        value:
-          selectedRunStatus.charAt(0).toUpperCase() +
-          selectedRunStatus.slice(1),
-      },
-      {
-        label: "Schedule",
-        value: humanizeCronExpression(schedule.cron),
-      },
-      {
-        label: "Next run",
-        value: formatScheduleTime(schedule.next_run_time, userTimezone),
-      },
-    ];
-  }, [schedule, selectedRunStatus, userTimezone]);
-
-  const agentRunInputs: Record<
-    string,
-    { title?: string; /* type: BlockIOSubType; */ value: any }
-  > = useMemo(() => {
-    // TODO: show (link to) preset - https://github.com/Significant-Gravitas/AutoGPT/issues/9168
-
-    // Add type info from agent input schema
-    return Object.fromEntries(
-      Object.entries(schedule.input_data).map(([k, v]) => [
-        k,
-        {
-          title: graph.input_schema.properties[k].title,
-          /* TODO: type: agent.input_schema.properties[k].type */
-          value: v,
-        },
-      ]),
-    );
-  }, [graph, schedule]);
-
-  const runNow = useCallback(
-    () =>
-      api
-        .executeGraph(
-          graph.id,
-          graph.version,
-          schedule.input_data,
-          schedule.input_credentials,
-          "library",
-        )
-        .then((run) => onForcedRun(run.id))
-        .catch(toastOnFail("execute agent")),
-    [api, graph, schedule, onForcedRun, toastOnFail],
-  );
-
-  const runActions: ButtonAction[] = useMemo(
-    () => [
-      {
-        label: (
-          <>
-            <PlayIcon className="mr-2 size-4" />
-            Run now
-          </>
-        ),
-        callback: runNow,
-      },
-      {
-        label: (
-          <>
-            <IconCross className="mr-2 size-4 px-0.5" />
-            Delete schedule
-          </>
-        ),
-        callback: () => doDeleteSchedule(schedule.id),
-        variant: "destructive",
-      },
-    ],
-    [runNow],
-  );
-
-  return (
-    <div className="agpt-div flex gap-6">
-      <div className="flex flex-1 flex-col gap-4">
-        <Card className="agpt-box">
-          <CardHeader>
-            <CardTitle className="font-poppins text-lg">Info</CardTitle>
-          </CardHeader>
-
-          <CardContent>
-            <div className="flex justify-stretch gap-4">
-              {infoStats.map(({ label, value }) => (
-                <div key={label} className="flex-1">
-                  <p className="text-sm font-medium text-black">{label}</p>
-                  <p className="text-sm text-neutral-600">{value}</p>
-                </div>
-              ))}
-            </div>
-          </CardContent>
-        </Card>
-
-        <Card className="agpt-box">
-          <CardHeader>
-            <CardTitle className="font-poppins text-lg">Input</CardTitle>
-          </CardHeader>
-          <CardContent className="flex flex-col gap-4">
-            {agentRunInputs !== undefined ? (
-              Object.entries(agentRunInputs).map(([key, { title, value }]) => (
-                <div key={key} className="flex flex-col gap-1.5">
-                  <label className="text-sm font-medium">{title || key}</label>
-                  <Input value={value} className="rounded-full" disabled />
-                </div>
-              ))
-            ) : (
-              <LoadingBox spinnerSize={12} className="h-24" />
-            )}
-          </CardContent>
-        </Card>
-      </div>
-
-      {/* Run / Agent Actions */}
-      <aside className="w-48 xl:w-56">
-        <div className="flex flex-col gap-8">
-          <ActionButtonGroup title="Run actions" actions={runActions} />
-
-          <ActionButtonGroup title="Agent actions" actions={agentActions} />
-        </div>
-      </aside>
-    </div>
-  );
-}

autogpt_platform/frontend/src/app/(platform)/library/agents/[id]/components/OldAgentLibraryView/components/create-preset-dialog.tsx

@@ -1,100 +0,0 @@
-"use client";
-
-import React, { useState } from "react";
-import { Button } from "@/components/__legacy__/ui/button";
-import {
-  Dialog,
-  DialogContent,
-  DialogDescription,
-  DialogFooter,
-  DialogHeader,
-  DialogTitle,
-} from "@/components/__legacy__/ui/dialog";
-import { Input } from "@/components/__legacy__/ui/input";
-import { Textarea } from "@/components/__legacy__/ui/textarea";
-
-interface CreatePresetDialogProps {
-  open: boolean;
-  onOpenChange: (open: boolean) => void;
-  onConfirm: (name: string, description: string) => Promise<void> | void;
-}
-
-export function CreatePresetDialog({
-  open,
-  onOpenChange,
-  onConfirm,
-}: CreatePresetDialogProps) {
-  const [name, setName] = useState("");
-  const [description, setDescription] = useState("");
-
-  const handleSubmit = async () => {
-    if (name.trim()) {
-      await onConfirm(name.trim(), description.trim());
-      setName("");
-      setDescription("");
-      onOpenChange(false);
-    }
-  };
-
-  const handleCancel = () => {
-    setName("");
-    setDescription("");
-    onOpenChange(false);
-  };
-
-  const handleKeyDown = (e: React.KeyboardEvent) => {
-    if (e.key === "Enter" && (e.metaKey || e.ctrlKey)) {
-      e.preventDefault();
-      handleSubmit();
-    }
-  };
-
-  return (
-    <Dialog open={open} onOpenChange={onOpenChange}>
-      <DialogContent className="sm:max-w-[425px]">
-        <DialogHeader>
-          <DialogTitle>Create Preset</DialogTitle>
-          <DialogDescription>
-            Give your preset a name and description to help identify it later.
-          </DialogDescription>
-        </DialogHeader>
-        <div className="grid gap-4 py-4">
-          <div className="grid gap-2">
-            <label htmlFor="preset-name" className="text-sm font-medium">
-              Name *
-            </label>
-            <Input
-              id="preset-name"
-              placeholder="Enter preset name"
-              value={name}
-              onChange={(e) => setName(e.target.value)}
-              onKeyDown={handleKeyDown}
-              autoFocus
-            />
-          </div>
-          <div className="grid gap-2">
-            <label htmlFor="preset-description" className="text-sm font-medium">
-              Description
-            </label>
-            <Textarea
-              id="preset-description"
-              placeholder="Optional description"
-              value={description}
-              onChange={(e) => setDescription(e.target.value)}
-              onKeyDown={handleKeyDown}
-              rows={3}
-            />
-          </div>
-        </div>
-        <DialogFooter>
-          <Button variant="outline" onClick={handleCancel}>
-            Cancel
-          </Button>
-          <Button onClick={handleSubmit} disabled={!name.trim()}>
-            Create Preset
-          </Button>
-        </DialogFooter>
-      </DialogContent>
-    </Dialog>
-  );
-}

autogpt_platform/frontend/src/app/(platform)/library/agents/[id]/components/OldAgentLibraryView/use-agent-runs.ts

@@ -1,210 +0,0 @@
-import {
-  GraphExecutionMeta as LegacyGraphExecutionMeta,
-  GraphID,
-  GraphExecutionID,
-} from "@/lib/autogpt-server-api";
-import { getQueryClient } from "@/lib/react-query/queryClient";
-import {
-  getPaginatedTotalCount,
-  getPaginationNextPageNumber,
-  unpaginate,
-} from "@/app/api/helpers";
-import {
-  getV1ListGraphExecutionsResponse,
-  getV1ListGraphExecutionsResponse200,
-  useGetV1ListGraphExecutionsInfinite,
-} from "@/app/api/__generated__/endpoints/graphs/graphs";
-import { GraphExecutionsPaginated } from "@/app/api/__generated__/models/graphExecutionsPaginated";
-import { GraphExecutionMeta as RawGraphExecutionMeta } from "@/app/api/__generated__/models/graphExecutionMeta";
-
-export type GraphExecutionMeta = Omit<
-  RawGraphExecutionMeta,
-  "id" | "user_id" | "graph_id" | "preset_id" | "stats"
-> &
-  Pick<
-    LegacyGraphExecutionMeta,
-    "id" | "user_id" | "graph_id" | "preset_id" | "stats"
-  >;
-
-/** Hook to fetch runs for a specific graph, with support for infinite scroll.
- *
- * @param graphID - The ID of the graph to fetch agent runs for. This parameter is
- *                  optional in the sense that the hook doesn't run unless it is passed.
- *                  This way, it can be used in components where the graph ID is not
- *                  immediately available.
- */
-export const useAgentRunsInfinite = (graphID?: GraphID) => {
-  const queryClient = getQueryClient();
-  const {
-    data: queryResults,
-    refetch: refetchRuns,
-    isPending: agentRunsLoading,
-    isRefetching: agentRunsReloading,
-    hasNextPage: hasMoreRuns,
-    fetchNextPage: fetchMoreRuns,
-    isFetchingNextPage: isFetchingMoreRuns,
-    queryKey,
-  } = useGetV1ListGraphExecutionsInfinite(
-    graphID!,
-    { page: 1, page_size: 20 },
-    {
-      query: {
-        getNextPageParam: getPaginationNextPageNumber,
-
-        // Prevent query from running if graphID is not available (yet)
-        ...(!graphID
-          ? {
-              enabled: false,
-              queryFn: () =>
-                // Fake empty response if graphID is not available (yet)
-                Promise.resolve({
-                  status: 200,
-                  data: {
-                    executions: [],
-                    pagination: {
-                      current_page: 1,
-                      page_size: 20,
-                      total_items: 0,
-                      total_pages: 0,
-                    },
-                  },
-                  headers: new Headers(),
-                } satisfies getV1ListGraphExecutionsResponse),
-            }
-          : {}),
-      },
-    },
-    queryClient,
-  );
-
-  const agentRuns = queryResults ? unpaginate(queryResults, "executions") : [];
-  const agentRunCount = getPaginatedTotalCount(queryResults);
-
-  const upsertAgentRun = (newAgentRun: GraphExecutionMeta) => {
-    queryClient.setQueryData(
-      queryKey,
-      (currentQueryData: typeof queryResults) => {
-        if (!currentQueryData?.pages || agentRunCount === undefined)
-          return currentQueryData;
-
-        const exists = currentQueryData.pages.some((page) => {
-          if (page.status !== 200) return false;
-
-          const response = page.data;
-          return response.executions.some((run) => run.id === newAgentRun.id);
-        });
-        if (exists) {
-          // If the run already exists, we update it
-          return {
-            ...currentQueryData,
-            pages: currentQueryData.pages.map((page) => {
-              if (page.status !== 200) return page;
-              const response = page.data;
-              const executions = response.executions;
-
-              const index = executions.findIndex(
-                (run) => run.id === newAgentRun.id,
-              );
-              if (index === -1) return page;
-
-              const newExecutions = [...executions];
-              newExecutions[index] = newAgentRun;
-
-              return {
-                ...page,
-                data: {
-                  ...response,
-                  executions: newExecutions,
-                },
-              } satisfies getV1ListGraphExecutionsResponse;
-            }),
-          };
-        }
-
-        // If the run does not exist, we add it to the first page
-        const page = currentQueryData
-          .pages[0] as getV1ListGraphExecutionsResponse200 & {
-          headers: Headers;
-        };
-        const updatedExecutions = [newAgentRun, ...page.data.executions];
-        const updatedPage = {
-          ...page,
-          data: {
-            ...page.data,
-            executions: updatedExecutions,
-          },
-        } satisfies getV1ListGraphExecutionsResponse;
-        const updatedPages = [updatedPage, ...currentQueryData.pages.slice(1)];
-        return {
-          ...currentQueryData,
-          pages: updatedPages.map(
-            // Increment the total runs count in the pagination info of all pages
-            (page) =>
-              page.status === 200
-                ? {
-                    ...page,
-                    data: {
-                      ...page.data,
-                      pagination: {
-                        ...page.data.pagination,
-                        total_items: agentRunCount + 1,
-                      },
-                    },
-                  }
-                : page,
-          ),
-        };
-      },
-    );
-  };
-
-  const removeAgentRun = (runID: GraphExecutionID) => {
-    queryClient.setQueryData(
-      [queryKey, { page: 1, page_size: 20 }],
-      (currentQueryData: typeof queryResults) => {
-        if (!currentQueryData?.pages) return currentQueryData;
-
-        let found = false;
-        return {
-          ...currentQueryData,
-          pages: currentQueryData.pages.map((page) => {
-            const response = page.data as GraphExecutionsPaginated;
-            const filteredExecutions = response.executions.filter(
-              (run) => run.id !== runID,
-            );
-            if (filteredExecutions.length < response.executions.length) {
-              found = true;
-            }
-
-            return {
-              ...page,
-              data: {
-                ...response,
-                executions: filteredExecutions,
-                pagination: {
-                  ...response.pagination,
-                  total_items:
-                    response.pagination.total_items - (found ? 1 : 0),
-                },
-              },
-            };
-          }),
-        };
-      },
-    );
-  };
-
-  return {
-    agentRuns: agentRuns as GraphExecutionMeta[],
-    refetchRuns,
-    agentRunCount,
-    agentRunsLoading: agentRunsLoading || agentRunsReloading,
-    hasMoreRuns,
-    fetchMoreRuns,
-    isFetchingMoreRuns,
-    upsertAgentRun,
-    removeAgentRun,
-  };
-};
-
-export type AgentRunsQuery = ReturnType<typeof useAgentRunsInfinite>;

autogpt_platform/frontend/src/app/(platform)/library/legacy/[id]/page.tsx

@@ -1,7 +0,0 @@
-"use client";
-
-import { OldAgentLibraryView } from "../../agents/[id]/components/OldAgentLibraryView/OldAgentLibraryView";
-
-export default function OldAgentLibraryPage() {
-  return <OldAgentLibraryView />;
-}

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

@@ -1053,6 +1053,7 @@
                       "$ref": "#/components/schemas/ClarificationNeededResponse"
                     },
                     { "$ref": "#/components/schemas/BlockListResponse" },
+                    { "$ref": "#/components/schemas/BlockDetailsResponse" },
                     { "$ref": "#/components/schemas/BlockOutputResponse" },
                     { "$ref": "#/components/schemas/DocSearchResultsResponse" },
                     { "$ref": "#/components/schemas/DocPageResponse" },
@@ -6958,6 +6959,58 @@
         "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": { "$ref": "#/components/schemas/BlockDetails" },
+          "user_authenticated": {
+            "type": "boolean",
+            "title": "User Authenticated",
+            "default": false
+          }
+        },
+        "type": "object",
+        "required": ["message", "block"],
+        "title": "BlockDetailsResponse",
+        "description": "Response for block details (first run_block attempt)."
+      },
       "BlockInfo": {
         "properties": {
           "id": { "type": "string", "title": "Id" },
@@ -7013,62 +7066,13 @@
         "properties": {
           "id": { "type": "string", "title": "Id" },
           "name": { "type": "string", "title": "Name" },
-          "description": { "type": "string", "title": "Description" },
+          "description": { "type": "string", "title": "Description" }
-          "categories": {
-            "items": { "type": "string" },
-            "type": "array",
-            "title": "Categories"
-          },
-          "input_schema": {
-            "additionalProperties": true,
-            "type": "object",
-            "title": "Input Schema"
-          },
-          "output_schema": {
-            "additionalProperties": true,
-            "type": "object",
-            "title": "Output Schema"
-          },
-          "required_inputs": {
-            "items": { "$ref": "#/components/schemas/BlockInputFieldInfo" },
-            "type": "array",
-            "title": "Required Inputs",
-            "description": "List of required input fields for this block"
-          }
         },
         "type": "object",
-        "required": [
+        "required": ["id", "name", "description"],
-          "id",
-          "name",
-          "description",
-          "categories",
-          "input_schema",
-          "output_schema"
-        ],
         "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": {
@@ -7086,12 +7090,7 @@
             "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 required fields from input_schema."
-          }
         },
         "type": "object",
         "required": ["message", "blocks", "count", "query"],
@@ -10484,6 +10483,7 @@
           "agent_saved",
           "clarification_needed",
           "block_list",
+          "block_details",
           "block_output",
           "doc_search_results",
           "doc_page",
@@ -10495,7 +10495,9 @@
           "operation_started",
           "operation_pending",
           "operation_in_progress",
-          "input_validation_error"
+          "input_validation_error",
+          "feature_request_search",
+          "feature_request_created"
         ],
         "title": "ResponseType",
         "description": "Types of tool responses."

autogpt_platform/frontend/src/components/contextual/CronScheduler/cron-scheduler-dialog.tsx

@@ -2,7 +2,7 @@ import { useEffect, useState } from "react";
 import { Input } from "@/components/__legacy__/ui/input";
 import { Button } from "@/components/__legacy__/ui/button";
 import { useToast } from "@/components/molecules/Toast/use-toast";
-import { CronScheduler } from "@/app/(platform)/library/agents/[id]/components/OldAgentLibraryView/components/cron-scheduler";
+import { CronScheduler } from "@/components/contextual/CronScheduler/cron-scheduler";
 import { Dialog } from "@/components/molecules/Dialog/Dialog";
 import { getTimezoneDisplayName } from "@/lib/timezone-utils";
 import { useUserTimezone } from "@/lib/hooks/useUserTimezone";

autogpt_platform/frontend/src/components/contextual/PublishAgentModal/components/AgentInfoStep/AgentInfoStep.tsx

@@ -1,6 +1,6 @@
 "use client";
 
-import { CronExpressionDialog } from "@/app/(platform)/library/agents/[id]/components/OldAgentLibraryView/components/cron-scheduler-dialog";
+import { CronExpressionDialog } from "@/components/contextual/CronScheduler/cron-scheduler-dialog";
 import { Form, FormField } from "@/components/__legacy__/ui/form";
 import { Button } from "@/components/atoms/Button/Button";
 import { Input } from "@/components/atoms/Input/Input";

autogpt_platform/frontend/src/services/feature-flags/use-get-flag.ts

@@ -7,7 +7,6 @@ import { useFlags } from "launchdarkly-react-client-sdk";
 export enum Flag {
   BETA_BLOCKS = "beta-blocks",
   NEW_BLOCK_MENU = "new-block-menu",
-  NEW_AGENT_RUNS = "new-agent-runs",
   GRAPH_SEARCH = "graph-search",
   ENABLE_ENHANCED_OUTPUT_HANDLING = "enable-enhanced-output-handling",
   SHARE_EXECUTION_RESULTS = "share-execution-results",
@@ -22,7 +21,6 @@ const isPwMockEnabled = process.env.NEXT_PUBLIC_PW_TEST === "true";
 const defaultFlags = {
   [Flag.BETA_BLOCKS]: [],
   [Flag.NEW_BLOCK_MENU]: false,
-  [Flag.NEW_AGENT_RUNS]: false,
   [Flag.GRAPH_SEARCH]: false,
   [Flag.ENABLE_ENHANCED_OUTPUT_HANDLING]: false,
   [Flag.SHARE_EXECUTION_RESULTS]: false,

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

@@ -0,0 +1,165 @@
+# 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.