Merge branch 'dev' into fix/sheets-write-not-working-picker

Eliminates explicit Google Sheets API scopes from credentials fields in
all Google Sheets-related blocks. This change may be intended to
centralize or dynamically manage API scopes elsewhere, simplifying block
configuration.

<!-- Clearly explain the need for these changes: -->

### Changes 🏗️
- removes the scopes we aren't approved to use
<!-- Concisely describe all of the changes made in this pull request:
-->

### Checklist 📋

#### For code changes:
- [x] I have clearly listed my changes in the PR description
- [x] I have made a test plan
- [x] I have tested my changes according to the test plan:
  <!-- Put your test plan here: -->
  - [x] Bently tested it on his fresh account and it worked!

.github/workflows/claude-dependabot.yml

@@ -80,7 +80,7 @@ jobs:
       - name: Set up Node.js
         uses: actions/setup-node@v4
         with:
-          node-version: "21"
+          node-version: "22"
 
       - name: Enable corepack
         run: corepack enable

.github/workflows/claude.yml

@@ -90,7 +90,7 @@ jobs:
       - name: Set up Node.js
         uses: actions/setup-node@v4
         with:
-          node-version: "21"
+          node-version: "22"
 
       - name: Enable corepack
         run: corepack enable

.github/workflows/copilot-setup-steps.yml

@@ -78,7 +78,7 @@ jobs:
       - name: Set up Node.js
         uses: actions/setup-node@v4
         with:
-          node-version: "21"
+          node-version: "22"
 
       - name: Enable corepack
         run: corepack enable
@@ -299,4 +299,4 @@ jobs:
           echo "✅ AutoGPT Platform development environment setup complete!"
           echo "🚀 Ready for development with Docker services running"
           echo "📝 Backend server: poetry run serve (port 8000)"
-          echo "🌐 Frontend server: pnpm dev (port 3000)"
+          echo "🌐 Frontend server: pnpm dev (port 3000)"

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

@@ -30,7 +30,7 @@ jobs:
       - name: Set up Node.js
         uses: actions/setup-node@v4
         with:
-          node-version: "21"
+          node-version: "22.18.0"
 
       - name: Enable corepack
         run: corepack enable
@@ -62,7 +62,7 @@ jobs:
       - name: Set up Node.js
         uses: actions/setup-node@v4
         with:
-          node-version: "21"
+          node-version: "22.18.0"
 
       - name: Enable corepack
         run: corepack enable
@@ -97,7 +97,7 @@ jobs:
       - name: Set up Node.js
         uses: actions/setup-node@v4
         with:
-          node-version: "21"
+          node-version: "22.18.0"
 
       - name: Enable corepack
         run: corepack enable
@@ -138,7 +138,7 @@ jobs:
       - name: Set up Node.js
         uses: actions/setup-node@v4
         with:
-          node-version: "21"
+          node-version: "22.18.0"
 
       - name: Enable corepack
         run: corepack enable

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

@@ -30,7 +30,7 @@ jobs:
       - name: Set up Node.js
         uses: actions/setup-node@v4
         with:
-          node-version: "21"
+          node-version: "22.18.0"
 
       - name: Enable corepack
         run: corepack enable
@@ -66,7 +66,7 @@ jobs:
       - name: Set up Node.js
         uses: actions/setup-node@v4
         with:
-          node-version: "21"
+          node-version: "22.18.0"
 
       - name: Enable corepack
         run: corepack enable

.gitignore

@@ -178,3 +178,4 @@ autogpt_platform/backend/settings.py
 *.ign.*
 .test-contents
 .claude/settings.local.json
+/autogpt_platform/backend/logs

autogpt_platform/CLAUDE.md

@@ -192,6 +192,8 @@ Quick steps:
 Note: when making many new blocks analyze the interfaces for each of these blocks and picture if they would go well together in a graph based editor or would they struggle to connect productively?
 ex: do the inputs and outputs tie well together?
 
+If you get any pushback or hit complex block conditions check the new_blocks guide in the docs.
+
 **Modifying the API:**
 
 1. Update route in `/backend/backend/server/routers/`

autogpt_platform/autogpt_libs/autogpt_libs/auth/__init__.py

@@ -1,5 +1,10 @@
 from .config import verify_settings
-from .dependencies import get_user_id, requires_admin_user, requires_user
+from .dependencies import (
+    get_optional_user_id,
+    get_user_id,
+    requires_admin_user,
+    requires_user,
+)
 from .helpers import add_auth_responses_to_openapi
 from .models import User
 
@@ -8,6 +13,7 @@ __all__ = [
     "get_user_id",
     "requires_admin_user",
     "requires_user",
+    "get_optional_user_id",
     "add_auth_responses_to_openapi",
     "User",
 ]

autogpt_platform/autogpt_libs/autogpt_libs/auth/dependencies.py

@@ -4,11 +4,53 @@ FastAPI dependency functions for JWT-based authentication and authorization.
 These are the high-level dependency functions used in route definitions.
 """
 
+import logging
+
 import fastapi
+from fastapi.security import HTTPAuthorizationCredentials, HTTPBearer
 
 from .jwt_utils import get_jwt_payload, verify_user
 from .models import User
 
+optional_bearer = HTTPBearer(auto_error=False)
+
+# Header name for admin impersonation
+IMPERSONATION_HEADER_NAME = "X-Act-As-User-Id"
+
+logger = logging.getLogger(__name__)
+
+
+def get_optional_user_id(
+    credentials: HTTPAuthorizationCredentials | None = fastapi.Security(
+        optional_bearer
+    ),
+) -> str | None:
+    """
+    Attempts to extract the user ID ("sub" claim) from a Bearer JWT if provided.
+
+    This dependency allows for both authenticated and anonymous access. If a valid bearer token is
+    supplied, it parses the JWT and extracts the user ID. If the token is missing or invalid, it returns None,
+    treating the request as anonymous.
+
+    Args:
+        credentials: Optional HTTPAuthorizationCredentials object from FastAPI Security dependency.
+
+    Returns:
+        The user ID (str) extracted from the JWT "sub" claim, or None if no valid token is present.
+    """
+    if not credentials:
+        return None
+
+    try:
+        # Parse JWT token to get user ID
+        from autogpt_libs.auth.jwt_utils import parse_jwt_token
+
+        payload = parse_jwt_token(credentials.credentials)
+        return payload.get("sub")
+    except Exception as e:
+        logger.debug(f"Auth token validation failed (anonymous access): {e}")
+        return None
+
 
 async def requires_user(jwt_payload: dict = fastapi.Security(get_jwt_payload)) -> User:
     """
@@ -32,16 +74,44 @@ async def requires_admin_user(
     return verify_user(jwt_payload, admin_only=True)
 
 
-async def get_user_id(jwt_payload: dict = fastapi.Security(get_jwt_payload)) -> str:
+async def get_user_id(
+    request: fastapi.Request, jwt_payload: dict = fastapi.Security(get_jwt_payload)
+) -> str:
     """
     FastAPI dependency that returns the ID of the authenticated user.
 
+    Supports admin impersonation via X-Act-As-User-Id header:
+    - If the header is present and user is admin, returns the impersonated user ID
+    - Otherwise returns the authenticated user's own ID
+    - Logs all impersonation actions for audit trail
+
     Raises:
         HTTPException: 401 for authentication failures or missing user ID
+        HTTPException: 403 if non-admin tries to use impersonation
     """
+    # Get the authenticated user's ID from JWT
     user_id = jwt_payload.get("sub")
     if not user_id:
         raise fastapi.HTTPException(
             status_code=401, detail="User ID not found in token"
         )
+
+    # Check for admin impersonation header
+    impersonate_header = request.headers.get(IMPERSONATION_HEADER_NAME, "").strip()
+    if impersonate_header:
+        # Verify the authenticated user is an admin
+        authenticated_user = verify_user(jwt_payload, admin_only=False)
+        if authenticated_user.role != "admin":
+            raise fastapi.HTTPException(
+                status_code=403, detail="Only admin users can impersonate other users"
+            )
+
+        # Log the impersonation for audit trail
+        logger.info(
+            f"Admin impersonation: {authenticated_user.user_id} ({authenticated_user.email}) "
+            f"acting as user {impersonate_header} for requesting {request.method} {request.url}"
+        )
+
+        return impersonate_header
+
     return user_id

autogpt_platform/autogpt_libs/autogpt_libs/auth/dependencies_test.py

@@ -4,9 +4,10 @@ Tests the full authentication flow from HTTP requests to user validation.
 """
 
 import os
+from unittest.mock import Mock
 
 import pytest
-from fastapi import FastAPI, HTTPException, Security
+from fastapi import FastAPI, HTTPException, Request, Security
 from fastapi.testclient import TestClient
 from pytest_mock import MockerFixture
 
@@ -45,6 +46,7 @@ class TestAuthDependencies:
         """Create a test client."""
         return TestClient(app)
 
+    @pytest.mark.asyncio
     async def test_requires_user_with_valid_jwt_payload(self, mocker: MockerFixture):
         """Test requires_user with valid JWT payload."""
         jwt_payload = {"sub": "user-123", "role": "user", "email": "user@example.com"}
@@ -58,6 +60,7 @@ class TestAuthDependencies:
         assert user.user_id == "user-123"
         assert user.role == "user"
 
+    @pytest.mark.asyncio
     async def test_requires_user_with_admin_jwt_payload(self, mocker: MockerFixture):
         """Test requires_user accepts admin users."""
         jwt_payload = {
@@ -73,6 +76,7 @@ class TestAuthDependencies:
         assert user.user_id == "admin-456"
         assert user.role == "admin"
 
+    @pytest.mark.asyncio
     async def test_requires_user_missing_sub(self):
         """Test requires_user with missing user ID."""
         jwt_payload = {"role": "user", "email": "user@example.com"}
@@ -82,6 +86,7 @@ class TestAuthDependencies:
         assert exc_info.value.status_code == 401
         assert "User ID not found" in exc_info.value.detail
 
+    @pytest.mark.asyncio
     async def test_requires_user_empty_sub(self):
         """Test requires_user with empty user ID."""
         jwt_payload = {"sub": "", "role": "user"}
@@ -90,6 +95,7 @@ class TestAuthDependencies:
             await requires_user(jwt_payload)
         assert exc_info.value.status_code == 401
 
+    @pytest.mark.asyncio
     async def test_requires_admin_user_with_admin(self, mocker: MockerFixture):
         """Test requires_admin_user with admin role."""
         jwt_payload = {
@@ -105,6 +111,7 @@ class TestAuthDependencies:
         assert user.user_id == "admin-789"
         assert user.role == "admin"
 
+    @pytest.mark.asyncio
     async def test_requires_admin_user_with_regular_user(self):
         """Test requires_admin_user rejects regular users."""
         jwt_payload = {"sub": "user-123", "role": "user", "email": "user@example.com"}
@@ -114,6 +121,7 @@ class TestAuthDependencies:
         assert exc_info.value.status_code == 403
         assert "Admin access required" in exc_info.value.detail
 
+    @pytest.mark.asyncio
     async def test_requires_admin_user_missing_role(self):
         """Test requires_admin_user with missing role."""
         jwt_payload = {"sub": "user-123", "email": "user@example.com"}
@@ -121,31 +129,40 @@ class TestAuthDependencies:
         with pytest.raises(KeyError):
             await requires_admin_user(jwt_payload)
 
+    @pytest.mark.asyncio
     async def test_get_user_id_with_valid_payload(self, mocker: MockerFixture):
         """Test get_user_id extracts user ID correctly."""
+        request = Mock(spec=Request)
+        request.headers = {}
         jwt_payload = {"sub": "user-id-xyz", "role": "user"}
 
         mocker.patch(
             "autogpt_libs.auth.dependencies.get_jwt_payload", return_value=jwt_payload
         )
-        user_id = await get_user_id(jwt_payload)
+        user_id = await get_user_id(request, jwt_payload)
         assert user_id == "user-id-xyz"
 
+    @pytest.mark.asyncio
     async def test_get_user_id_missing_sub(self):
         """Test get_user_id with missing user ID."""
+        request = Mock(spec=Request)
+        request.headers = {}
         jwt_payload = {"role": "user"}
 
         with pytest.raises(HTTPException) as exc_info:
-            await get_user_id(jwt_payload)
+            await get_user_id(request, jwt_payload)
         assert exc_info.value.status_code == 401
         assert "User ID not found" in exc_info.value.detail
 
+    @pytest.mark.asyncio
     async def test_get_user_id_none_sub(self):
         """Test get_user_id with None user ID."""
+        request = Mock(spec=Request)
+        request.headers = {}
         jwt_payload = {"sub": None, "role": "user"}
 
         with pytest.raises(HTTPException) as exc_info:
-            await get_user_id(jwt_payload)
+            await get_user_id(request, jwt_payload)
         assert exc_info.value.status_code == 401
 
 
@@ -170,6 +187,7 @@ class TestAuthDependenciesIntegration:
 
         return _create_token
 
+    @pytest.mark.asyncio
     async def test_endpoint_auth_enabled_no_token(self):
         """Test endpoints require token when auth is enabled."""
         app = FastAPI()
@@ -184,6 +202,7 @@ class TestAuthDependenciesIntegration:
         response = client.get("/test")
         assert response.status_code == 401
 
+    @pytest.mark.asyncio
     async def test_endpoint_with_valid_token(self, create_token):
         """Test endpoint with valid JWT token."""
         app = FastAPI()
@@ -203,6 +222,7 @@ class TestAuthDependenciesIntegration:
         assert response.status_code == 200
         assert response.json()["user_id"] == "test-user"
 
+    @pytest.mark.asyncio
     async def test_admin_endpoint_requires_admin_role(self, create_token):
         """Test admin endpoint rejects non-admin users."""
         app = FastAPI()
@@ -240,6 +260,7 @@ class TestAuthDependenciesIntegration:
 class TestAuthDependenciesEdgeCases:
     """Edge case tests for authentication dependencies."""
 
+    @pytest.mark.asyncio
     async def test_dependency_with_complex_payload(self):
         """Test dependencies handle complex JWT payloads."""
         complex_payload = {
@@ -263,6 +284,7 @@ class TestAuthDependenciesEdgeCases:
         admin = await requires_admin_user(complex_payload)
         assert admin.role == "admin"
 
+    @pytest.mark.asyncio
     async def test_dependency_with_unicode_in_payload(self):
         """Test dependencies handle unicode in JWT payloads."""
         unicode_payload = {
@@ -276,6 +298,7 @@ class TestAuthDependenciesEdgeCases:
         assert "😀" in user.user_id
         assert user.email == "测试@example.com"
 
+    @pytest.mark.asyncio
     async def test_dependency_with_null_values(self):
         """Test dependencies handle null values in payload."""
         null_payload = {
@@ -290,6 +313,7 @@ class TestAuthDependenciesEdgeCases:
         assert user.user_id == "user-123"
         assert user.email is None
 
+    @pytest.mark.asyncio
     async def test_concurrent_requests_isolation(self):
         """Test that concurrent requests don't interfere with each other."""
         payload1 = {"sub": "user-1", "role": "user"}
@@ -314,6 +338,7 @@ class TestAuthDependenciesEdgeCases:
             ({"sub": "user", "role": "user"}, "Admin access required", True),
         ],
     )
+    @pytest.mark.asyncio
     async def test_dependency_error_cases(
         self, payload, expected_error: str, admin_only: bool
     ):
@@ -325,6 +350,7 @@ class TestAuthDependenciesEdgeCases:
             verify_user(payload, admin_only=admin_only)
         assert expected_error in exc_info.value.detail
 
+    @pytest.mark.asyncio
     async def test_dependency_valid_user(self):
         """Test valid user case for dependency."""
         # Import verify_user to test it directly since dependencies use FastAPI Security
@@ -333,3 +359,196 @@ class TestAuthDependenciesEdgeCases:
         # Valid case
         user = verify_user({"sub": "user", "role": "user"}, admin_only=False)
         assert user.user_id == "user"
+
+
+class TestAdminImpersonation:
+    """Test suite for admin user impersonation functionality."""
+
+    @pytest.mark.asyncio
+    async def test_admin_impersonation_success(self, mocker: MockerFixture):
+        """Test admin successfully impersonating another user."""
+        request = Mock(spec=Request)
+        request.headers = {"X-Act-As-User-Id": "target-user-123"}
+        jwt_payload = {
+            "sub": "admin-456",
+            "role": "admin",
+            "email": "admin@example.com",
+        }
+
+        # Mock verify_user to return admin user data
+        mock_verify_user = mocker.patch("autogpt_libs.auth.dependencies.verify_user")
+        mock_verify_user.return_value = Mock(
+            user_id="admin-456", email="admin@example.com", role="admin"
+        )
+
+        # Mock logger to verify audit logging
+        mock_logger = mocker.patch("autogpt_libs.auth.dependencies.logger")
+
+        mocker.patch(
+            "autogpt_libs.auth.dependencies.get_jwt_payload", return_value=jwt_payload
+        )
+
+        user_id = await get_user_id(request, jwt_payload)
+
+        # Should return the impersonated user ID
+        assert user_id == "target-user-123"
+
+        # Should log the impersonation attempt
+        mock_logger.info.assert_called_once()
+        log_call = mock_logger.info.call_args[0][0]
+        assert "Admin impersonation:" in log_call
+        assert "admin@example.com" in log_call
+        assert "target-user-123" in log_call
+
+    @pytest.mark.asyncio
+    async def test_non_admin_impersonation_attempt(self, mocker: MockerFixture):
+        """Test non-admin user attempting impersonation returns 403."""
+        request = Mock(spec=Request)
+        request.headers = {"X-Act-As-User-Id": "target-user-123"}
+        jwt_payload = {
+            "sub": "regular-user",
+            "role": "user",
+            "email": "user@example.com",
+        }
+
+        # Mock verify_user to return regular user data
+        mock_verify_user = mocker.patch("autogpt_libs.auth.dependencies.verify_user")
+        mock_verify_user.return_value = Mock(
+            user_id="regular-user", email="user@example.com", role="user"
+        )
+
+        mocker.patch(
+            "autogpt_libs.auth.dependencies.get_jwt_payload", return_value=jwt_payload
+        )
+
+        with pytest.raises(HTTPException) as exc_info:
+            await get_user_id(request, jwt_payload)
+
+        assert exc_info.value.status_code == 403
+        assert "Only admin users can impersonate other users" in exc_info.value.detail
+
+    @pytest.mark.asyncio
+    async def test_impersonation_empty_header(self, mocker: MockerFixture):
+        """Test impersonation with empty header falls back to regular user ID."""
+        request = Mock(spec=Request)
+        request.headers = {"X-Act-As-User-Id": ""}
+        jwt_payload = {
+            "sub": "admin-456",
+            "role": "admin",
+            "email": "admin@example.com",
+        }
+
+        mocker.patch(
+            "autogpt_libs.auth.dependencies.get_jwt_payload", return_value=jwt_payload
+        )
+
+        user_id = await get_user_id(request, jwt_payload)
+
+        # Should fall back to the admin's own user ID
+        assert user_id == "admin-456"
+
+    @pytest.mark.asyncio
+    async def test_impersonation_missing_header(self, mocker: MockerFixture):
+        """Test normal behavior when impersonation header is missing."""
+        request = Mock(spec=Request)
+        request.headers = {}  # No impersonation header
+        jwt_payload = {
+            "sub": "admin-456",
+            "role": "admin",
+            "email": "admin@example.com",
+        }
+
+        mocker.patch(
+            "autogpt_libs.auth.dependencies.get_jwt_payload", return_value=jwt_payload
+        )
+
+        user_id = await get_user_id(request, jwt_payload)
+
+        # Should return the admin's own user ID
+        assert user_id == "admin-456"
+
+    @pytest.mark.asyncio
+    async def test_impersonation_audit_logging_details(self, mocker: MockerFixture):
+        """Test that impersonation audit logging includes all required details."""
+        request = Mock(spec=Request)
+        request.headers = {"X-Act-As-User-Id": "victim-user-789"}
+        jwt_payload = {
+            "sub": "admin-999",
+            "role": "admin",
+            "email": "superadmin@company.com",
+        }
+
+        # Mock verify_user to return admin user data
+        mock_verify_user = mocker.patch("autogpt_libs.auth.dependencies.verify_user")
+        mock_verify_user.return_value = Mock(
+            user_id="admin-999", email="superadmin@company.com", role="admin"
+        )
+
+        # Mock logger to capture audit trail
+        mock_logger = mocker.patch("autogpt_libs.auth.dependencies.logger")
+
+        mocker.patch(
+            "autogpt_libs.auth.dependencies.get_jwt_payload", return_value=jwt_payload
+        )
+
+        user_id = await get_user_id(request, jwt_payload)
+
+        # Verify all audit details are logged
+        assert user_id == "victim-user-789"
+        mock_logger.info.assert_called_once()
+
+        log_message = mock_logger.info.call_args[0][0]
+        assert "Admin impersonation:" in log_message
+        assert "superadmin@company.com" in log_message
+        assert "victim-user-789" in log_message
+
+    @pytest.mark.asyncio
+    async def test_impersonation_header_case_sensitivity(self, mocker: MockerFixture):
+        """Test that impersonation header is case-sensitive."""
+        request = Mock(spec=Request)
+        # Use wrong case - should not trigger impersonation
+        request.headers = {"x-act-as-user-id": "target-user-123"}
+        jwt_payload = {
+            "sub": "admin-456",
+            "role": "admin",
+            "email": "admin@example.com",
+        }
+
+        mocker.patch(
+            "autogpt_libs.auth.dependencies.get_jwt_payload", return_value=jwt_payload
+        )
+
+        user_id = await get_user_id(request, jwt_payload)
+
+        # Should fall back to admin's own ID (header case mismatch)
+        assert user_id == "admin-456"
+
+    @pytest.mark.asyncio
+    async def test_impersonation_with_whitespace_header(self, mocker: MockerFixture):
+        """Test impersonation with whitespace in header value."""
+        request = Mock(spec=Request)
+        request.headers = {"X-Act-As-User-Id": "  target-user-123  "}
+        jwt_payload = {
+            "sub": "admin-456",
+            "role": "admin",
+            "email": "admin@example.com",
+        }
+
+        # Mock verify_user to return admin user data
+        mock_verify_user = mocker.patch("autogpt_libs.auth.dependencies.verify_user")
+        mock_verify_user.return_value = Mock(
+            user_id="admin-456", email="admin@example.com", role="admin"
+        )
+
+        # Mock logger
+        mock_logger = mocker.patch("autogpt_libs.auth.dependencies.logger")
+
+        mocker.patch(
+            "autogpt_libs.auth.dependencies.get_jwt_payload", return_value=jwt_payload
+        )
+
+        user_id = await get_user_id(request, jwt_payload)
+
+        # Should strip whitespace and impersonate successfully
+        assert user_id == "target-user-123"
+        mock_logger.info.assert_called_once()

autogpt_platform/backend/.env.default

@@ -134,13 +134,6 @@ POSTMARK_WEBHOOK_TOKEN=
 # Error Tracking
 SENTRY_DSN=
 
-# Cloudflare Turnstile (CAPTCHA) Configuration
-# Get these from the Cloudflare Turnstile dashboard: https://dash.cloudflare.com/?to=/:account/turnstile
-# This is the backend secret key
-TURNSTILE_SECRET_KEY=
-# This is the verify URL
-TURNSTILE_VERIFY_URL=https://challenges.cloudflare.com/turnstile/v0/siteverify
-
 # Feature Flags
 LAUNCH_DARKLY_SDK_KEY=
 

autogpt_platform/backend/backend/blocks/agent.py

@@ -7,6 +7,7 @@ from backend.data.block import (
     BlockInput,
     BlockOutput,
     BlockSchema,
+    BlockSchemaInput,
     BlockType,
     get_block,
 )
@@ -19,7 +20,7 @@ _logger = logging.getLogger(__name__)
 
 
 class AgentExecutorBlock(Block):
-    class Input(BlockSchema):
+    class Input(BlockSchemaInput):
         user_id: str = SchemaField(description="User ID")
         graph_id: str = SchemaField(description="Graph ID")
         graph_version: int = SchemaField(description="Graph Version")
@@ -53,6 +54,7 @@ class AgentExecutorBlock(Block):
             return validate_with_jsonschema(cls.get_input_schema(data), data)
 
     class Output(BlockSchema):
+        # Use BlockSchema to avoid automatic error field that could clash with graph outputs
         pass
 
     def __init__(self):
@@ -65,7 +67,13 @@ class AgentExecutorBlock(Block):
             categories={BlockCategory.AGENT},
         )
 
-    async def run(self, input_data: Input, **kwargs) -> BlockOutput:
+    async def run(
+        self,
+        input_data: Input,
+        *,
+        graph_exec_id: str,
+        **kwargs,
+    ) -> BlockOutput:
 
         from backend.executor import utils as execution_utils
 
@@ -75,6 +83,8 @@ class AgentExecutorBlock(Block):
             user_id=input_data.user_id,
             inputs=input_data.inputs,
             nodes_input_masks=input_data.nodes_input_masks,
+            parent_graph_exec_id=graph_exec_id,
+            is_sub_graph=True,  # AgentExecutorBlock executions are always sub-graphs
         )
 
         logger = execution_utils.LogMetadata(

autogpt_platform/backend/backend/blocks/ai_condition.py

@@ -10,7 +10,12 @@ from backend.blocks.llm import (
     LLMResponse,
     llm_call,
 )
-from backend.data.block import BlockCategory, BlockOutput, BlockSchema
+from backend.data.block import (
+    BlockCategory,
+    BlockOutput,
+    BlockSchemaInput,
+    BlockSchemaOutput,
+)
 from backend.data.model import APIKeyCredentials, NodeExecutionStats, SchemaField
 
 
@@ -23,7 +28,7 @@ class AIConditionBlock(AIBlockBase):
     It provides the same yes/no data pass-through functionality as the standard ConditionBlock.
     """
 
-    class Input(BlockSchema):
+    class Input(BlockSchemaInput):
         input_value: Any = SchemaField(
             description="The input value to evaluate with the AI condition",
             placeholder="Enter the value to be evaluated (text, number, or any data)",
@@ -50,7 +55,7 @@ class AIConditionBlock(AIBlockBase):
         )
         credentials: AICredentials = AICredentialsField()
 
-    class Output(BlockSchema):
+    class Output(BlockSchemaOutput):
         result: bool = SchemaField(
             description="The result of the AI condition evaluation (True or False)"
         )

autogpt_platform/backend/backend/blocks/ai_image_customizer.py

@@ -1,3 +1,4 @@
+import asyncio
 from enum import Enum
 from typing import Literal
 
@@ -5,7 +6,13 @@ from pydantic import SecretStr
 from replicate.client import Client as ReplicateClient
 from replicate.helpers import FileOutput
 
-from backend.data.block import Block, BlockCategory, BlockOutput, BlockSchema
+from backend.data.block import (
+    Block,
+    BlockCategory,
+    BlockOutput,
+    BlockSchemaInput,
+    BlockSchemaOutput,
+)
 from backend.data.model import (
     APIKeyCredentials,
     CredentialsField,
@@ -13,11 +20,26 @@ from backend.data.model import (
     SchemaField,
 )
 from backend.integrations.providers import ProviderName
-from backend.util.file import MediaFileType
+from backend.util.file import MediaFileType, store_media_file
 
 
 class GeminiImageModel(str, Enum):
     NANO_BANANA = "google/nano-banana"
+    NANO_BANANA_PRO = "google/nano-banana-pro"
+
+
+class AspectRatio(str, Enum):
+    MATCH_INPUT_IMAGE = "match_input_image"
+    ASPECT_1_1 = "1:1"
+    ASPECT_2_3 = "2:3"
+    ASPECT_3_2 = "3:2"
+    ASPECT_3_4 = "3:4"
+    ASPECT_4_3 = "4:3"
+    ASPECT_4_5 = "4:5"
+    ASPECT_5_4 = "5:4"
+    ASPECT_9_16 = "9:16"
+    ASPECT_16_9 = "16:9"
+    ASPECT_21_9 = "21:9"
 
 
 class OutputFormat(str, Enum):
@@ -42,7 +64,7 @@ TEST_CREDENTIALS_INPUT = {
 
 
 class AIImageCustomizerBlock(Block):
-    class Input(BlockSchema):
+    class Input(BlockSchemaInput):
         credentials: CredentialsMetaInput[
             Literal[ProviderName.REPLICATE], Literal["api_key"]
         ] = CredentialsField(
@@ -62,15 +84,19 @@ class AIImageCustomizerBlock(Block):
             default=[],
             title="Input Images",
         )
+        aspect_ratio: AspectRatio = SchemaField(
+            description="Aspect ratio of the generated image",
+            default=AspectRatio.MATCH_INPUT_IMAGE,
+            title="Aspect Ratio",
+        )
         output_format: OutputFormat = SchemaField(
             description="Format of the output image",
             default=OutputFormat.PNG,
             title="Output Format",
         )
 
-    class Output(BlockSchema):
+    class Output(BlockSchemaOutput):
         image_url: MediaFileType = SchemaField(description="URL of the generated image")
-        error: str = SchemaField(description="Error message if generation failed")
 
     def __init__(self):
         super().__init__(
@@ -86,6 +112,7 @@ class AIImageCustomizerBlock(Block):
                 "prompt": "Make the scene more vibrant and colorful",
                 "model": GeminiImageModel.NANO_BANANA,
                 "images": [],
+                "aspect_ratio": AspectRatio.MATCH_INPUT_IMAGE,
                 "output_format": OutputFormat.JPG,
                 "credentials": TEST_CREDENTIALS_INPUT,
             },
@@ -110,11 +137,25 @@ class AIImageCustomizerBlock(Block):
         **kwargs,
     ) -> BlockOutput:
         try:
+            # Convert local file paths to Data URIs (base64) so Replicate can access them
+            processed_images = await asyncio.gather(
+                *(
+                    store_media_file(
+                        graph_exec_id=graph_exec_id,
+                        file=img,
+                        user_id=user_id,
+                        return_content=True,
+                    )
+                    for img in input_data.images
+                )
+            )
+
             result = await self.run_model(
                 api_key=credentials.api_key,
                 model_name=input_data.model.value,
                 prompt=input_data.prompt,
-                images=input_data.images,
+                images=processed_images,
+                aspect_ratio=input_data.aspect_ratio.value,
                 output_format=input_data.output_format.value,
             )
             yield "image_url", result
@@ -127,12 +168,14 @@ class AIImageCustomizerBlock(Block):
         model_name: str,
         prompt: str,
         images: list[MediaFileType],
+        aspect_ratio: str,
         output_format: str,
     ) -> MediaFileType:
         client = ReplicateClient(api_token=api_key.get_secret_value())
 
         input_params: dict = {
             "prompt": prompt,
+            "aspect_ratio": aspect_ratio,
             "output_format": output_format,
         }
 

autogpt_platform/backend/backend/blocks/ai_image_generator_block.py

@@ -5,7 +5,7 @@ from pydantic import SecretStr
 from replicate.client import Client as ReplicateClient
 from replicate.helpers import FileOutput
 
-from backend.data.block import Block, BlockCategory, BlockSchema
+from backend.data.block import Block, BlockCategory, BlockSchemaInput, BlockSchemaOutput
 from backend.data.model import (
     APIKeyCredentials,
     CredentialsField,
@@ -60,6 +60,14 @@ SIZE_TO_RECRAFT_DIMENSIONS = {
     ImageSize.TALL: "1024x1536",
 }
 
+SIZE_TO_NANO_BANANA_RATIO = {
+    ImageSize.SQUARE: "1:1",
+    ImageSize.LANDSCAPE: "4:3",
+    ImageSize.PORTRAIT: "3:4",
+    ImageSize.WIDE: "16:9",
+    ImageSize.TALL: "9:16",
+}
+
 
 class ImageStyle(str, Enum):
     """
@@ -98,10 +106,11 @@ class ImageGenModel(str, Enum):
     FLUX_ULTRA = "Flux 1.1 Pro Ultra"
     RECRAFT = "Recraft v3"
     SD3_5 = "Stable Diffusion 3.5 Medium"
+    NANO_BANANA_PRO = "Nano Banana Pro"
 
 
 class AIImageGeneratorBlock(Block):
-    class Input(BlockSchema):
+    class Input(BlockSchemaInput):
         credentials: CredentialsMetaInput[
             Literal[ProviderName.REPLICATE], Literal["api_key"]
         ] = CredentialsField(
@@ -135,9 +144,8 @@ class AIImageGeneratorBlock(Block):
             title="Image Style",
         )
 
-    class Output(BlockSchema):
+    class Output(BlockSchemaOutput):
         image_url: str = SchemaField(description="URL of the generated image")
-        error: str = SchemaField(description="Error message if generation failed")
 
     def __init__(self):
         super().__init__(
@@ -262,6 +270,20 @@ class AIImageGeneratorBlock(Block):
                 )
                 return output
 
+            elif input_data.model == ImageGenModel.NANO_BANANA_PRO:
+                # Use Nano Banana Pro (Google Gemini 3 Pro Image)
+                input_params = {
+                    "prompt": modified_prompt,
+                    "aspect_ratio": SIZE_TO_NANO_BANANA_RATIO[input_data.size],
+                    "resolution": "2K",  # Default to 2K for good quality/cost balance
+                    "output_format": "jpg",
+                    "safety_filter_level": "block_only_high",  # Most permissive
+                }
+                output = await self._run_client(
+                    credentials, "google/nano-banana-pro", input_params
+                )
+                return output
+
         except Exception as e:
             raise RuntimeError(f"Failed to generate image: {str(e)}")
 

autogpt_platform/backend/backend/blocks/ai_music_generator.py

@@ -6,7 +6,13 @@ from typing import Literal
 from pydantic import SecretStr
 from replicate.client import Client as ReplicateClient
 
-from backend.data.block import Block, BlockCategory, BlockOutput, BlockSchema
+from backend.data.block import (
+    Block,
+    BlockCategory,
+    BlockOutput,
+    BlockSchemaInput,
+    BlockSchemaOutput,
+)
 from backend.data.model import (
     APIKeyCredentials,
     CredentialsField,
@@ -54,7 +60,7 @@ class NormalizationStrategy(str, Enum):
 
 
 class AIMusicGeneratorBlock(Block):
-    class Input(BlockSchema):
+    class Input(BlockSchemaInput):
         credentials: CredentialsMetaInput[
             Literal[ProviderName.REPLICATE], Literal["api_key"]
         ] = CredentialsField(
@@ -107,9 +113,8 @@ class AIMusicGeneratorBlock(Block):
             title="Normalization Strategy",
         )
 
-    class Output(BlockSchema):
+    class Output(BlockSchemaOutput):
         result: str = SchemaField(description="URL of the generated audio file")
-        error: str = SchemaField(description="Error message if the model run failed")
 
     def __init__(self):
         super().__init__(

autogpt_platform/backend/backend/blocks/ai_shortform_video_block.py

@@ -6,7 +6,13 @@ from typing import Literal
 
 from pydantic import SecretStr
 
-from backend.data.block import Block, BlockCategory, BlockOutput, BlockSchema
+from backend.data.block import (
+    Block,
+    BlockCategory,
+    BlockOutput,
+    BlockSchemaInput,
+    BlockSchemaOutput,
+)
 from backend.data.model import (
     APIKeyCredentials,
     CredentialsField,
@@ -148,7 +154,7 @@ logger = logging.getLogger(__name__)
 class AIShortformVideoCreatorBlock(Block):
     """Creates a short‑form text‑to‑video clip using stock or AI imagery."""
 
-    class Input(BlockSchema):
+    class Input(BlockSchemaInput):
         credentials: CredentialsMetaInput[
             Literal[ProviderName.REVID], Literal["api_key"]
         ] = CredentialsField(
@@ -187,9 +193,8 @@ class AIShortformVideoCreatorBlock(Block):
             placeholder=VisualMediaType.STOCK_VIDEOS,
         )
 
-    class Output(BlockSchema):
+    class Output(BlockSchemaOutput):
         video_url: str = SchemaField(description="The URL of the created video")
-        error: str = SchemaField(description="Error message if the request failed")
 
     async def create_webhook(self) -> tuple[str, str]:
         """Create a new webhook URL for receiving notifications."""
@@ -336,7 +341,7 @@ class AIShortformVideoCreatorBlock(Block):
 class AIAdMakerVideoCreatorBlock(Block):
     """Generates a 30‑second vertical AI advert using optional user‑supplied imagery."""
 
-    class Input(BlockSchema):
+    class Input(BlockSchemaInput):
         credentials: CredentialsMetaInput[
             Literal[ProviderName.REVID], Literal["api_key"]
         ] = CredentialsField(
@@ -364,9 +369,8 @@ class AIAdMakerVideoCreatorBlock(Block):
             description="Restrict visuals to supplied images only.", default=True
         )
 
-    class Output(BlockSchema):
+    class Output(BlockSchemaOutput):
         video_url: str = SchemaField(description="URL of the finished advert")
-        error: str = SchemaField(description="Error message on failure")
 
     async def create_webhook(self) -> tuple[str, str]:
         """Create a new webhook URL for receiving notifications."""
@@ -524,7 +528,7 @@ class AIAdMakerVideoCreatorBlock(Block):
 class AIScreenshotToVideoAdBlock(Block):
     """Creates an advert where the supplied screenshot is narrated by an AI avatar."""
 
-    class Input(BlockSchema):
+    class Input(BlockSchemaInput):
         credentials: CredentialsMetaInput[
             Literal[ProviderName.REVID], Literal["api_key"]
         ] = CredentialsField(description="Revid.ai API key")
@@ -542,9 +546,8 @@ class AIScreenshotToVideoAdBlock(Block):
             default=AudioTrack.DONT_STOP_ME_ABSTRACT_FUTURE_BASS
         )
 
-    class Output(BlockSchema):
+    class Output(BlockSchemaOutput):
         video_url: str = SchemaField(description="Rendered video URL")
-        error: str = SchemaField(description="Error, if encountered")
 
     async def create_webhook(self) -> tuple[str, str]:
         """Create a new webhook URL for receiving notifications."""

autogpt_platform/backend/backend/blocks/airtable/bases.py

@@ -9,7 +9,8 @@ from backend.sdk import (
     Block,
     BlockCategory,
     BlockOutput,
-    BlockSchema,
+    BlockSchemaInput,
+    BlockSchemaOutput,
     CredentialsMetaInput,
     SchemaField,
 )
@@ -23,7 +24,7 @@ class AirtableCreateBaseBlock(Block):
     Creates a new base in an Airtable workspace, or returns existing base if one with the same name exists.
     """
 
-    class Input(BlockSchema):
+    class Input(BlockSchemaInput):
         credentials: CredentialsMetaInput = airtable.credentials_field(
             description="Airtable API credentials"
         )
@@ -53,7 +54,7 @@ class AirtableCreateBaseBlock(Block):
             ],
         )
 
-    class Output(BlockSchema):
+    class Output(BlockSchemaOutput):
         base_id: str = SchemaField(description="The ID of the created or found base")
         tables: list[dict] = SchemaField(description="Array of table objects")
         table: dict = SchemaField(description="A single table object")
@@ -118,7 +119,7 @@ class AirtableListBasesBlock(Block):
     Lists all bases in an Airtable workspace that the user has access to.
     """
 
-    class Input(BlockSchema):
+    class Input(BlockSchemaInput):
         credentials: CredentialsMetaInput = airtable.credentials_field(
             description="Airtable API credentials"
         )
@@ -129,7 +130,7 @@ class AirtableListBasesBlock(Block):
             description="Pagination offset from previous request", default=""
         )
 
-    class Output(BlockSchema):
+    class Output(BlockSchemaOutput):
         bases: list[dict] = SchemaField(description="Array of base objects")
         offset: Optional[str] = SchemaField(
             description="Offset for next page (null if no more bases)", default=None

autogpt_platform/backend/backend/blocks/airtable/records.py

@@ -9,7 +9,8 @@ from backend.sdk import (
     Block,
     BlockCategory,
     BlockOutput,
-    BlockSchema,
+    BlockSchemaInput,
+    BlockSchemaOutput,
     CredentialsMetaInput,
     SchemaField,
 )
@@ -31,7 +32,7 @@ class AirtableListRecordsBlock(Block):
     Lists records from an Airtable table with optional filtering, sorting, and pagination.
     """
 
-    class Input(BlockSchema):
+    class Input(BlockSchemaInput):
         credentials: CredentialsMetaInput = airtable.credentials_field(
             description="Airtable API credentials"
         )
@@ -65,7 +66,7 @@ class AirtableListRecordsBlock(Block):
             default=False,
         )
 
-    class Output(BlockSchema):
+    class Output(BlockSchemaOutput):
         records: list[dict] = SchemaField(description="Array of record objects")
         offset: Optional[str] = SchemaField(
             description="Offset for next page (null if no more records)", default=None
@@ -137,7 +138,7 @@ class AirtableGetRecordBlock(Block):
     Retrieves a single record from an Airtable table by its ID.
     """
 
-    class Input(BlockSchema):
+    class Input(BlockSchemaInput):
         credentials: CredentialsMetaInput = airtable.credentials_field(
             description="Airtable API credentials"
         )
@@ -153,7 +154,7 @@ class AirtableGetRecordBlock(Block):
             default=False,
         )
 
-    class Output(BlockSchema):
+    class Output(BlockSchemaOutput):
         id: str = SchemaField(description="The record ID")
         fields: dict = SchemaField(description="The record fields")
         created_time: str = SchemaField(description="The record created time")
@@ -217,7 +218,7 @@ class AirtableCreateRecordsBlock(Block):
     Creates one or more records in an Airtable table.
     """
 
-    class Input(BlockSchema):
+    class Input(BlockSchemaInput):
         credentials: CredentialsMetaInput = airtable.credentials_field(
             description="Airtable API credentials"
         )
@@ -239,7 +240,7 @@ class AirtableCreateRecordsBlock(Block):
             default=None,
         )
 
-    class Output(BlockSchema):
+    class Output(BlockSchemaOutput):
         records: list[dict] = SchemaField(description="Array of created record objects")
         details: dict = SchemaField(description="Details of the created records")
 
@@ -290,7 +291,7 @@ class AirtableUpdateRecordsBlock(Block):
     Updates one or more existing records in an Airtable table.
     """
 
-    class Input(BlockSchema):
+    class Input(BlockSchemaInput):
         credentials: CredentialsMetaInput = airtable.credentials_field(
             description="Airtable API credentials"
         )
@@ -306,7 +307,7 @@ class AirtableUpdateRecordsBlock(Block):
             default=None,
         )
 
-    class Output(BlockSchema):
+    class Output(BlockSchemaOutput):
         records: list[dict] = SchemaField(description="Array of updated record objects")
 
     def __init__(self):
@@ -339,7 +340,7 @@ class AirtableDeleteRecordsBlock(Block):
     Deletes one or more records from an Airtable table.
     """
 
-    class Input(BlockSchema):
+    class Input(BlockSchemaInput):
         credentials: CredentialsMetaInput = airtable.credentials_field(
             description="Airtable API credentials"
         )
@@ -351,7 +352,7 @@ class AirtableDeleteRecordsBlock(Block):
             description="Array of upto 10 record IDs to delete"
         )
 
-    class Output(BlockSchema):
+    class Output(BlockSchemaOutput):
         records: list[dict] = SchemaField(description="Array of deletion results")
 
     def __init__(self):

autogpt_platform/backend/backend/blocks/airtable/schema.py

@@ -7,7 +7,8 @@ from backend.sdk import (
     Block,
     BlockCategory,
     BlockOutput,
-    BlockSchema,
+    BlockSchemaInput,
+    BlockSchemaOutput,
     CredentialsMetaInput,
     Requests,
     SchemaField,
@@ -23,13 +24,13 @@ class AirtableListSchemaBlock(Block):
     fields, and views.
     """
 
-    class Input(BlockSchema):
+    class Input(BlockSchemaInput):
         credentials: CredentialsMetaInput = airtable.credentials_field(
             description="Airtable API credentials"
         )
         base_id: str = SchemaField(description="The Airtable base ID")
 
-    class Output(BlockSchema):
+    class Output(BlockSchemaOutput):
         base_schema: dict = SchemaField(
             description="Complete base schema with tables, fields, and views"
         )
@@ -66,7 +67,7 @@ class AirtableCreateTableBlock(Block):
     Creates a new table in an Airtable base with specified fields and views.
     """
 
-    class Input(BlockSchema):
+    class Input(BlockSchemaInput):
         credentials: CredentialsMetaInput = airtable.credentials_field(
             description="Airtable API credentials"
         )
@@ -77,7 +78,7 @@ class AirtableCreateTableBlock(Block):
             default=[{"name": "Name", "type": "singleLineText"}],
         )
 
-    class Output(BlockSchema):
+    class Output(BlockSchemaOutput):
         table: dict = SchemaField(description="Created table object")
         table_id: str = SchemaField(description="ID of the created table")
 
@@ -109,7 +110,7 @@ class AirtableUpdateTableBlock(Block):
     Updates an existing table's properties such as name or description.
     """
 
-    class Input(BlockSchema):
+    class Input(BlockSchemaInput):
         credentials: CredentialsMetaInput = airtable.credentials_field(
             description="Airtable API credentials"
         )
@@ -125,7 +126,7 @@ class AirtableUpdateTableBlock(Block):
             description="The date dependency of the table to update", default=None
         )
 
-    class Output(BlockSchema):
+    class Output(BlockSchemaOutput):
         table: dict = SchemaField(description="Updated table object")
 
     def __init__(self):
@@ -157,7 +158,7 @@ class AirtableCreateFieldBlock(Block):
     Adds a new field (column) to an existing Airtable table.
     """
 
-    class Input(BlockSchema):
+    class Input(BlockSchemaInput):
         credentials: CredentialsMetaInput = airtable.credentials_field(
             description="Airtable API credentials"
         )
@@ -176,7 +177,7 @@ class AirtableCreateFieldBlock(Block):
             description="The options of the field to create", default=None
         )
 
-    class Output(BlockSchema):
+    class Output(BlockSchemaOutput):
         field: dict = SchemaField(description="Created field object")
         field_id: str = SchemaField(description="ID of the created field")
 
@@ -209,7 +210,7 @@ class AirtableUpdateFieldBlock(Block):
     Updates an existing field's properties in an Airtable table.
     """
 
-    class Input(BlockSchema):
+    class Input(BlockSchemaInput):
         credentials: CredentialsMetaInput = airtable.credentials_field(
             description="Airtable API credentials"
         )
@@ -225,7 +226,7 @@ class AirtableUpdateFieldBlock(Block):
             advanced=False,
         )
 
-    class Output(BlockSchema):
+    class Output(BlockSchemaOutput):
         field: dict = SchemaField(description="Updated field object")
 
     def __init__(self):

autogpt_platform/backend/backend/blocks/airtable/triggers.py

@@ -3,7 +3,8 @@ from backend.sdk import (
     Block,
     BlockCategory,
     BlockOutput,
-    BlockSchema,
+    BlockSchemaInput,
+    BlockSchemaOutput,
     BlockType,
     BlockWebhookConfig,
     CredentialsMetaInput,
@@ -32,7 +33,7 @@ class AirtableWebhookTriggerBlock(Block):
     Thin wrapper just forwards the payloads one at a time to the next block.
     """
 
-    class Input(BlockSchema):
+    class Input(BlockSchemaInput):
         credentials: CredentialsMetaInput = airtable.credentials_field(
             description="Airtable API credentials"
         )
@@ -43,7 +44,7 @@ class AirtableWebhookTriggerBlock(Block):
             description="Airtable webhook event filter"
         )
 
-    class Output(BlockSchema):
+    class Output(BlockSchemaOutput):
         payload: WebhookPayload = SchemaField(description="Airtable webhook payload")
 
     def __init__(self):

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

@@ -10,14 +10,20 @@ from backend.blocks.apollo.models import (
     PrimaryPhone,
     SearchOrganizationsRequest,
 )
-from backend.data.block import Block, BlockCategory, BlockOutput, BlockSchema
+from backend.data.block import (
+    Block,
+    BlockCategory,
+    BlockOutput,
+    BlockSchemaInput,
+    BlockSchemaOutput,
+)
 from backend.data.model import CredentialsField, SchemaField
 
 
 class SearchOrganizationsBlock(Block):
     """Search for organizations in Apollo"""
 
-    class Input(BlockSchema):
+    class Input(BlockSchemaInput):
         organization_num_employees_range: list[int] = SchemaField(
             description="""The number range of employees working for the company. This enables you to find companies based on headcount. You can add multiple ranges to expand your search results.
 
@@ -69,7 +75,7 @@ To find IDs, identify the values for organization_id when you call this endpoint
             description="Apollo credentials",
         )
 
-    class Output(BlockSchema):
+    class Output(BlockSchemaOutput):
         organizations: list[Organization] = SchemaField(
             description="List of organizations found",
             default_factory=list,

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

@@ -14,14 +14,20 @@ from backend.blocks.apollo.models import (
     SearchPeopleRequest,
     SenorityLevels,
 )
-from backend.data.block import Block, BlockCategory, BlockOutput, BlockSchema
+from backend.data.block import (
+    Block,
+    BlockCategory,
+    BlockOutput,
+    BlockSchemaInput,
+    BlockSchemaOutput,
+)
 from backend.data.model import CredentialsField, SchemaField
 
 
 class SearchPeopleBlock(Block):
     """Search for people in Apollo"""
 
-    class Input(BlockSchema):
+    class Input(BlockSchemaInput):
         person_titles: list[str] = SchemaField(
             description="""Job titles held by the people you want to find. For a person to be included in search results, they only need to match 1 of the job titles you add. Adding more job titles expands your search results.
 
@@ -109,7 +115,7 @@ class SearchPeopleBlock(Block):
             description="Apollo credentials",
         )
 
-    class Output(BlockSchema):
+    class Output(BlockSchemaOutput):
         people: list[Contact] = SchemaField(
             description="List of people found",
             default_factory=list,

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

@@ -6,14 +6,20 @@ from backend.blocks.apollo._auth import (
     ApolloCredentialsInput,
 )
 from backend.blocks.apollo.models import Contact, EnrichPersonRequest
-from backend.data.block import Block, BlockCategory, BlockOutput, BlockSchema
+from backend.data.block import (
+    Block,
+    BlockCategory,
+    BlockOutput,
+    BlockSchemaInput,
+    BlockSchemaOutput,
+)
 from backend.data.model import CredentialsField, SchemaField
 
 
 class GetPersonDetailBlock(Block):
     """Get detailed person data with Apollo API, including email reveal"""
 
-    class Input(BlockSchema):
+    class Input(BlockSchemaInput):
         person_id: str = SchemaField(
             description="Apollo person ID to enrich (most accurate method)",
             default="",
@@ -68,7 +74,7 @@ class GetPersonDetailBlock(Block):
             description="Apollo credentials",
         )
 
-    class Output(BlockSchema):
+    class Output(BlockSchemaOutput):
         contact: Contact = SchemaField(
             description="Enriched contact information",
         )

autogpt_platform/backend/backend/blocks/ayrshare/_util.py

@@ -3,7 +3,7 @@ from typing import Optional
 
 from pydantic import BaseModel, Field
 
-from backend.data.block import BlockSchema
+from backend.data.block import BlockSchemaInput
 from backend.data.model import SchemaField, UserIntegrations
 from backend.integrations.ayrshare import AyrshareClient
 from backend.util.clients import get_database_manager_async_client
@@ -17,7 +17,7 @@ async def get_profile_key(user_id: str):
     return user_integrations.managed_credentials.ayrshare_profile_key
 
 
-class BaseAyrshareInput(BlockSchema):
+class BaseAyrshareInput(BlockSchemaInput):
     """Base input model for Ayrshare social media posts with common fields."""
 
     post: str = SchemaField(

autogpt_platform/backend/backend/blocks/ayrshare/post_to_bluesky.py

@@ -3,7 +3,7 @@ from backend.sdk import (
     Block,
     BlockCategory,
     BlockOutput,
-    BlockSchema,
+    BlockSchemaOutput,
     BlockType,
     SchemaField,
 )
@@ -38,7 +38,7 @@ class PostToBlueskyBlock(Block):
             advanced=True,
         )
 
-    class Output(BlockSchema):
+    class Output(BlockSchemaOutput):
         post_result: PostResponse = SchemaField(description="The result of the post")
         post: PostIds = SchemaField(description="The result of the post")
 

autogpt_platform/backend/backend/blocks/ayrshare/post_to_facebook.py

@@ -3,7 +3,7 @@ from backend.sdk import (
     Block,
     BlockCategory,
     BlockOutput,
-    BlockSchema,
+    BlockSchemaOutput,
     BlockType,
     SchemaField,
 )
@@ -101,7 +101,7 @@ class PostToFacebookBlock(Block):
             description="URL for custom link preview", default="", advanced=True
         )
 
-    class Output(BlockSchema):
+    class Output(BlockSchemaOutput):
         post_result: PostResponse = SchemaField(description="The result of the post")
         post: PostIds = SchemaField(description="The result of the post")
 

autogpt_platform/backend/backend/blocks/ayrshare/post_to_gmb.py

@@ -3,7 +3,7 @@ from backend.sdk import (
     Block,
     BlockCategory,
     BlockOutput,
-    BlockSchema,
+    BlockSchemaOutput,
     BlockType,
     SchemaField,
 )
@@ -94,7 +94,7 @@ class PostToGMBBlock(Block):
             advanced=True,
         )
 
-    class Output(BlockSchema):
+    class Output(BlockSchemaOutput):
         post_result: PostResponse = SchemaField(description="The result of the post")
         post: PostIds = SchemaField(description="The result of the post")
 

autogpt_platform/backend/backend/blocks/ayrshare/post_to_instagram.py

@@ -5,7 +5,7 @@ from backend.sdk import (
     Block,
     BlockCategory,
     BlockOutput,
-    BlockSchema,
+    BlockSchemaOutput,
     BlockType,
     SchemaField,
 )
@@ -94,7 +94,7 @@ class PostToInstagramBlock(Block):
             advanced=True,
         )
 
-    class Output(BlockSchema):
+    class Output(BlockSchemaOutput):
         post_result: PostResponse = SchemaField(description="The result of the post")
         post: PostIds = SchemaField(description="The result of the post")
 

autogpt_platform/backend/backend/blocks/ayrshare/post_to_linkedin.py

@@ -3,7 +3,7 @@ from backend.sdk import (
     Block,
     BlockCategory,
     BlockOutput,
-    BlockSchema,
+    BlockSchemaOutput,
     BlockType,
     SchemaField,
 )
@@ -94,7 +94,7 @@ class PostToLinkedInBlock(Block):
             advanced=True,
         )
 
-    class Output(BlockSchema):
+    class Output(BlockSchemaOutput):
         post_result: PostResponse = SchemaField(description="The result of the post")
         post: PostIds = SchemaField(description="The result of the post")
 

autogpt_platform/backend/backend/blocks/ayrshare/post_to_pinterest.py

@@ -3,7 +3,7 @@ from backend.sdk import (
     Block,
     BlockCategory,
     BlockOutput,
-    BlockSchema,
+    BlockSchemaOutput,
     BlockType,
     SchemaField,
 )
@@ -73,7 +73,7 @@ class PostToPinterestBlock(Block):
             advanced=True,
         )
 
-    class Output(BlockSchema):
+    class Output(BlockSchemaOutput):
         post_result: PostResponse = SchemaField(description="The result of the post")
         post: PostIds = SchemaField(description="The result of the post")
 

autogpt_platform/backend/backend/blocks/ayrshare/post_to_reddit.py

@@ -3,7 +3,7 @@ from backend.sdk import (
     Block,
     BlockCategory,
     BlockOutput,
-    BlockSchema,
+    BlockSchemaOutput,
     BlockType,
     SchemaField,
 )
@@ -19,7 +19,7 @@ class PostToRedditBlock(Block):
 
         pass  # Uses all base fields
 
-    class Output(BlockSchema):
+    class Output(BlockSchemaOutput):
         post_result: PostResponse = SchemaField(description="The result of the post")
         post: PostIds = SchemaField(description="The result of the post")
 

autogpt_platform/backend/backend/blocks/ayrshare/post_to_snapchat.py

@@ -3,7 +3,7 @@ from backend.sdk import (
     Block,
     BlockCategory,
     BlockOutput,
-    BlockSchema,
+    BlockSchemaOutput,
     BlockType,
     SchemaField,
 )
@@ -43,7 +43,7 @@ class PostToSnapchatBlock(Block):
             advanced=True,
         )
 
-    class Output(BlockSchema):
+    class Output(BlockSchemaOutput):
         post_result: PostResponse = SchemaField(description="The result of the post")
         post: PostIds = SchemaField(description="The result of the post")
 

autogpt_platform/backend/backend/blocks/ayrshare/post_to_telegram.py

@@ -3,7 +3,7 @@ from backend.sdk import (
     Block,
     BlockCategory,
     BlockOutput,
-    BlockSchema,
+    BlockSchemaOutput,
     BlockType,
     SchemaField,
 )
@@ -38,7 +38,7 @@ class PostToTelegramBlock(Block):
             advanced=True,
         )
 
-    class Output(BlockSchema):
+    class Output(BlockSchemaOutput):
         post_result: PostResponse = SchemaField(description="The result of the post")
         post: PostIds = SchemaField(description="The result of the post")
 

autogpt_platform/backend/backend/blocks/ayrshare/post_to_threads.py

@@ -3,7 +3,7 @@ from backend.sdk import (
     Block,
     BlockCategory,
     BlockOutput,
-    BlockSchema,
+    BlockSchemaOutput,
     BlockType,
     SchemaField,
 )
@@ -31,7 +31,7 @@ class PostToThreadsBlock(Block):
             advanced=False,
         )
 
-    class Output(BlockSchema):
+    class Output(BlockSchemaOutput):
         post_result: PostResponse = SchemaField(description="The result of the post")
         post: PostIds = SchemaField(description="The result of the post")
 

autogpt_platform/backend/backend/blocks/ayrshare/post_to_tiktok.py

@@ -5,7 +5,7 @@ from backend.sdk import (
     Block,
     BlockCategory,
     BlockOutput,
-    BlockSchema,
+    BlockSchemaOutput,
     BlockType,
     SchemaField,
 )
@@ -98,7 +98,7 @@ class PostToTikTokBlock(Block):
             advanced=True,
         )
 
-    class Output(BlockSchema):
+    class Output(BlockSchemaOutput):
         post_result: PostResponse = SchemaField(description="The result of the post")
         post: PostIds = SchemaField(description="The result of the post")
 

autogpt_platform/backend/backend/blocks/ayrshare/post_to_x.py

@@ -3,7 +3,7 @@ from backend.sdk import (
     Block,
     BlockCategory,
     BlockOutput,
-    BlockSchema,
+    BlockSchemaOutput,
     BlockType,
     SchemaField,
 )
@@ -97,7 +97,7 @@ class PostToXBlock(Block):
             advanced=True,
         )
 
-    class Output(BlockSchema):
+    class Output(BlockSchemaOutput):
         post_result: PostResponse = SchemaField(description="The result of the post")
         post: PostIds = SchemaField(description="The result of the post")
 

autogpt_platform/backend/backend/blocks/ayrshare/post_to_youtube.py

@@ -6,7 +6,7 @@ from backend.sdk import (
     Block,
     BlockCategory,
     BlockOutput,
-    BlockSchema,
+    BlockSchemaOutput,
     BlockType,
     SchemaField,
 )
@@ -119,7 +119,7 @@ class PostToYouTubeBlock(Block):
             advanced=True,
         )
 
-    class Output(BlockSchema):
+    class Output(BlockSchemaOutput):
         post_result: PostResponse = SchemaField(description="The result of the post")
         post: PostIds = SchemaField(description="The result of the post")
 

autogpt_platform/backend/backend/blocks/baas/bots.py

@@ -9,7 +9,8 @@ from backend.sdk import (
     Block,
     BlockCategory,
     BlockOutput,
-    BlockSchema,
+    BlockSchemaInput,
+    BlockSchemaOutput,
     CredentialsMetaInput,
     SchemaField,
 )
@@ -23,7 +24,7 @@ class BaasBotJoinMeetingBlock(Block):
     Deploy a bot immediately or at a scheduled start_time to join and record a meeting.
     """
 
-    class Input(BlockSchema):
+    class Input(BlockSchemaInput):
         credentials: CredentialsMetaInput = baas.credentials_field(
             description="Meeting BaaS API credentials"
         )
@@ -57,7 +58,7 @@ class BaasBotJoinMeetingBlock(Block):
             description="Custom metadata to attach to the bot", default={}
         )
 
-    class Output(BlockSchema):
+    class Output(BlockSchemaOutput):
         bot_id: str = SchemaField(description="UUID of the deployed bot")
         join_response: dict = SchemaField(
             description="Full response from join operation"
@@ -103,13 +104,13 @@ class BaasBotLeaveMeetingBlock(Block):
     Force the bot to exit the call.
     """
 
-    class Input(BlockSchema):
+    class Input(BlockSchemaInput):
         credentials: CredentialsMetaInput = baas.credentials_field(
             description="Meeting BaaS API credentials"
         )
         bot_id: str = SchemaField(description="UUID of the bot to remove from meeting")
 
-    class Output(BlockSchema):
+    class Output(BlockSchemaOutput):
         left: bool = SchemaField(description="Whether the bot successfully left")
 
     def __init__(self):
@@ -138,7 +139,7 @@ class BaasBotFetchMeetingDataBlock(Block):
     Pull MP4 URL, transcript & metadata for a completed meeting.
     """
 
-    class Input(BlockSchema):
+    class Input(BlockSchemaInput):
         credentials: CredentialsMetaInput = baas.credentials_field(
             description="Meeting BaaS API credentials"
         )
@@ -147,7 +148,7 @@ class BaasBotFetchMeetingDataBlock(Block):
             description="Include transcript data in response", default=True
         )
 
-    class Output(BlockSchema):
+    class Output(BlockSchemaOutput):
         mp4_url: str = SchemaField(
             description="URL to download the meeting recording (time-limited)"
         )
@@ -185,13 +186,13 @@ class BaasBotDeleteRecordingBlock(Block):
     Purge MP4 + transcript data for privacy or storage management.
     """
 
-    class Input(BlockSchema):
+    class Input(BlockSchemaInput):
         credentials: CredentialsMetaInput = baas.credentials_field(
             description="Meeting BaaS API credentials"
         )
         bot_id: str = SchemaField(description="UUID of the bot whose data to delete")
 
-    class Output(BlockSchema):
+    class Output(BlockSchemaOutput):
         deleted: bool = SchemaField(
             description="Whether the data was successfully deleted"
         )

autogpt_platform/backend/backend/blocks/bannerbear/text_overlay.py

@@ -11,7 +11,8 @@ from backend.sdk import (
     Block,
     BlockCategory,
     BlockOutput,
-    BlockSchema,
+    BlockSchemaInput,
+    BlockSchemaOutput,
     CredentialsMetaInput,
     Requests,
     SchemaField,
@@ -27,7 +28,7 @@ TEST_CREDENTIALS = APIKeyCredentials(
 )
 
 
-class TextModification(BlockSchema):
+class TextModification(BlockSchemaInput):
     name: str = SchemaField(
         description="The name of the layer to modify in the template"
     )
@@ -60,7 +61,7 @@ class TextModification(BlockSchema):
 
 
 class BannerbearTextOverlayBlock(Block):
-    class Input(BlockSchema):
+    class Input(BlockSchemaInput):
         credentials: CredentialsMetaInput = bannerbear.credentials_field(
             description="API credentials for Bannerbear"
         )
@@ -96,7 +97,7 @@ class BannerbearTextOverlayBlock(Block):
             advanced=True,
         )
 
-    class Output(BlockSchema):
+    class Output(BlockSchemaOutput):
         success: bool = SchemaField(
             description="Whether the image generation was successfully initiated"
         )
@@ -105,7 +106,6 @@ class BannerbearTextOverlayBlock(Block):
         )
         uid: str = SchemaField(description="Unique identifier for the generated image")
         status: str = SchemaField(description="Status of the image generation")
-        error: str = SchemaField(description="Error message if the operation failed")
 
     def __init__(self):
         super().__init__(

autogpt_platform/backend/backend/blocks/basic.py

@@ -1,14 +1,21 @@
 import enum
 from typing import Any
 
-from backend.data.block import Block, BlockCategory, BlockOutput, BlockSchema, BlockType
+from backend.data.block import (
+    Block,
+    BlockCategory,
+    BlockOutput,
+    BlockSchemaInput,
+    BlockSchemaOutput,
+    BlockType,
+)
 from backend.data.model import SchemaField
 from backend.util.file import store_media_file
 from backend.util.type import MediaFileType, convert
 
 
 class FileStoreBlock(Block):
-    class Input(BlockSchema):
+    class Input(BlockSchemaInput):
         file_in: MediaFileType = SchemaField(
             description="The file to store in the temporary directory, it can be a URL, data URI, or local path."
         )
@@ -19,7 +26,7 @@ class FileStoreBlock(Block):
             title="Produce Base64 Output",
         )
 
-    class Output(BlockSchema):
+    class Output(BlockSchemaOutput):
         file_out: MediaFileType = SchemaField(
             description="The relative path to the stored file in the temporary directory."
         )
@@ -57,7 +64,7 @@ class StoreValueBlock(Block):
     The block output will be static, the output can be consumed multiple times.
     """
 
-    class Input(BlockSchema):
+    class Input(BlockSchemaInput):
         input: Any = SchemaField(
             description="Trigger the block to produce the output. "
             "The value is only used when `data` is None."
@@ -68,7 +75,7 @@ class StoreValueBlock(Block):
             default=None,
         )
 
-    class Output(BlockSchema):
+    class Output(BlockSchemaOutput):
         output: Any = SchemaField(description="The stored data retained in the block.")
 
     def __init__(self):
@@ -94,10 +101,10 @@ class StoreValueBlock(Block):
 
 
 class PrintToConsoleBlock(Block):
-    class Input(BlockSchema):
+    class Input(BlockSchemaInput):
         text: Any = SchemaField(description="The data to print to the console.")
 
-    class Output(BlockSchema):
+    class Output(BlockSchemaOutput):
         output: Any = SchemaField(description="The data printed to the console.")
         status: str = SchemaField(description="The status of the print operation.")
 
@@ -121,10 +128,10 @@ class PrintToConsoleBlock(Block):
 
 
 class NoteBlock(Block):
-    class Input(BlockSchema):
+    class Input(BlockSchemaInput):
         text: str = SchemaField(description="The text to display in the sticky note.")
 
-    class Output(BlockSchema):
+    class Output(BlockSchemaOutput):
         output: str = SchemaField(description="The text to display in the sticky note.")
 
     def __init__(self):
@@ -154,15 +161,14 @@ class TypeOptions(enum.Enum):
 
 
 class UniversalTypeConverterBlock(Block):
-    class Input(BlockSchema):
+    class Input(BlockSchemaInput):
         value: Any = SchemaField(
             description="The value to convert to a universal type."
         )
         type: TypeOptions = SchemaField(description="The type to convert the value to.")
 
-    class Output(BlockSchema):
+    class Output(BlockSchemaOutput):
         value: Any = SchemaField(description="The converted value.")
-        error: str = SchemaField(description="Error message if conversion failed.")
 
     def __init__(self):
         super().__init__(
@@ -195,10 +201,10 @@ class ReverseListOrderBlock(Block):
     A block which takes in a list and returns it in the opposite order.
     """
 
-    class Input(BlockSchema):
+    class Input(BlockSchemaInput):
         input_list: list[Any] = SchemaField(description="The list to reverse")
 
-    class Output(BlockSchema):
+    class Output(BlockSchemaOutput):
         reversed_list: list[Any] = SchemaField(description="The list in reversed order")
 
     def __init__(self):

autogpt_platform/backend/backend/blocks/block.py

@@ -2,7 +2,13 @@ import os
 import re
 from typing import Type
 
-from backend.data.block import Block, BlockCategory, BlockOutput, BlockSchema
+from backend.data.block import (
+    Block,
+    BlockCategory,
+    BlockOutput,
+    BlockSchemaInput,
+    BlockSchemaOutput,
+)
 from backend.data.model import SchemaField
 
 
@@ -15,12 +21,12 @@ class BlockInstallationBlock(Block):
         for development purposes only.
     """
 
-    class Input(BlockSchema):
+    class Input(BlockSchemaInput):
         code: str = SchemaField(
             description="Python code of the block to be installed",
         )
 
-    class Output(BlockSchema):
+    class Output(BlockSchemaOutput):
         success: str = SchemaField(
             description="Success message if the block is installed successfully",
         )

autogpt_platform/backend/backend/blocks/branching.py

@@ -1,7 +1,13 @@
 from enum import Enum
 from typing import Any
 
-from backend.data.block import Block, BlockCategory, BlockOutput, BlockSchema
+from backend.data.block import (
+    Block,
+    BlockCategory,
+    BlockOutput,
+    BlockSchemaInput,
+    BlockSchemaOutput,
+)
 from backend.data.model import SchemaField
 from backend.util.type import convert
 
@@ -16,7 +22,7 @@ class ComparisonOperator(Enum):
 
 
 class ConditionBlock(Block):
-    class Input(BlockSchema):
+    class Input(BlockSchemaInput):
         value1: Any = SchemaField(
             description="Enter the first value for comparison",
             placeholder="For example: 10 or 'hello' or True",
@@ -40,7 +46,7 @@ class ConditionBlock(Block):
             default=None,
         )
 
-    class Output(BlockSchema):
+    class Output(BlockSchemaOutput):
         result: bool = SchemaField(
             description="The result of the condition evaluation (True or False)"
         )
@@ -111,7 +117,7 @@ class ConditionBlock(Block):
 
 
 class IfInputMatchesBlock(Block):
-    class Input(BlockSchema):
+    class Input(BlockSchemaInput):
         input: Any = SchemaField(
             description="The input to match against",
             placeholder="For example: 10 or 'hello' or True",
@@ -131,7 +137,7 @@ class IfInputMatchesBlock(Block):
             default=None,
         )
 
-    class Output(BlockSchema):
+    class Output(BlockSchemaOutput):
         result: bool = SchemaField(
             description="The result of the condition evaluation (True or False)"
         )

autogpt_platform/backend/backend/blocks/code_executor.py

@@ -4,9 +4,15 @@ from typing import Any, Literal, Optional
 from e2b_code_interpreter import AsyncSandbox
 from e2b_code_interpreter import Result as E2BExecutionResult
 from e2b_code_interpreter.charts import Chart as E2BExecutionResultChart
-from pydantic import BaseModel, JsonValue, SecretStr
+from pydantic import BaseModel, Field, JsonValue, SecretStr
 
-from backend.data.block import Block, BlockCategory, BlockOutput, BlockSchema
+from backend.data.block import (
+    Block,
+    BlockCategory,
+    BlockOutput,
+    BlockSchemaInput,
+    BlockSchemaOutput,
+)
 from backend.data.model import (
     APIKeyCredentials,
     CredentialsField,
@@ -61,7 +67,7 @@ class MainCodeExecutionResult(BaseModel):
     jpeg: Optional[str] = None
     pdf: Optional[str] = None
     latex: Optional[str] = None
-    json: Optional[JsonValue] = None  # type: ignore (reportIncompatibleMethodOverride)
+    json_data: Optional[JsonValue] = Field(None, alias="json")
     javascript: Optional[str] = None
     data: Optional[dict] = None
     chart: Optional[Chart] = None
@@ -159,7 +165,7 @@ class ExecuteCodeBlock(Block, BaseE2BExecutorMixin):
     # TODO : Add support to upload and download files
     # NOTE: Currently, you can only customize the CPU and Memory
     #       by creating a pre customized sandbox template
-    class Input(BlockSchema):
+    class Input(BlockSchemaInput):
         credentials: CredentialsMetaInput[
             Literal[ProviderName.E2B], Literal["api_key"]
         ] = CredentialsField(
@@ -217,7 +223,7 @@ class ExecuteCodeBlock(Block, BaseE2BExecutorMixin):
             advanced=True,
         )
 
-    class Output(BlockSchema):
+    class Output(BlockSchemaOutput):
         main_result: MainCodeExecutionResult = SchemaField(
             title="Main Result", description="The main result from the code execution"
         )
@@ -232,7 +238,6 @@ class ExecuteCodeBlock(Block, BaseE2BExecutorMixin):
             description="Standard output logs from execution"
         )
         stderr_logs: str = SchemaField(description="Standard error logs from execution")
-        error: str = SchemaField(description="Error message if execution failed")
 
     def __init__(self):
         super().__init__(
@@ -296,7 +301,7 @@ class ExecuteCodeBlock(Block, BaseE2BExecutorMixin):
 
 
 class InstantiateCodeSandboxBlock(Block, BaseE2BExecutorMixin):
-    class Input(BlockSchema):
+    class Input(BlockSchemaInput):
         credentials: CredentialsMetaInput[
             Literal[ProviderName.E2B], Literal["api_key"]
         ] = CredentialsField(
@@ -346,7 +351,7 @@ class InstantiateCodeSandboxBlock(Block, BaseE2BExecutorMixin):
             advanced=True,
         )
 
-    class Output(BlockSchema):
+    class Output(BlockSchemaOutput):
         sandbox_id: str = SchemaField(description="ID of the sandbox instance")
         response: str = SchemaField(
             title="Text Result",
@@ -356,7 +361,6 @@ class InstantiateCodeSandboxBlock(Block, BaseE2BExecutorMixin):
             description="Standard output logs from execution"
         )
         stderr_logs: str = SchemaField(description="Standard error logs from execution")
-        error: str = SchemaField(description="Error message if execution failed")
 
     def __init__(self):
         super().__init__(
@@ -421,7 +425,7 @@ class InstantiateCodeSandboxBlock(Block, BaseE2BExecutorMixin):
 
 
 class ExecuteCodeStepBlock(Block, BaseE2BExecutorMixin):
-    class Input(BlockSchema):
+    class Input(BlockSchemaInput):
         credentials: CredentialsMetaInput[
             Literal[ProviderName.E2B], Literal["api_key"]
         ] = CredentialsField(
@@ -454,7 +458,7 @@ class ExecuteCodeStepBlock(Block, BaseE2BExecutorMixin):
             default=False,
         )
 
-    class Output(BlockSchema):
+    class Output(BlockSchemaOutput):
         main_result: MainCodeExecutionResult = SchemaField(
             title="Main Result", description="The main result from the code execution"
         )
@@ -469,7 +473,6 @@ class ExecuteCodeStepBlock(Block, BaseE2BExecutorMixin):
             description="Standard output logs from execution"
         )
         stderr_logs: str = SchemaField(description="Standard error logs from execution")
-        error: str = SchemaField(description="Error message if execution failed")
 
     def __init__(self):
         super().__init__(

autogpt_platform/backend/backend/blocks/code_extraction_block.py

@@ -1,17 +1,23 @@
 import re
 
-from backend.data.block import Block, BlockCategory, BlockOutput, BlockSchema
+from backend.data.block import (
+    Block,
+    BlockCategory,
+    BlockOutput,
+    BlockSchemaInput,
+    BlockSchemaOutput,
+)
 from backend.data.model import SchemaField
 
 
 class CodeExtractionBlock(Block):
-    class Input(BlockSchema):
+    class Input(BlockSchemaInput):
         text: str = SchemaField(
             description="Text containing code blocks to extract (e.g., AI response)",
             placeholder="Enter text containing code blocks",
         )
 
-    class Output(BlockSchema):
+    class Output(BlockSchemaOutput):
         html: str = SchemaField(description="Extracted HTML code")
         css: str = SchemaField(description="Extracted CSS code")
         javascript: str = SchemaField(description="Extracted JavaScript code")

autogpt_platform/backend/backend/blocks/codex.py

@@ -0,0 +1,224 @@
+from dataclasses import dataclass
+from enum import Enum
+from typing import Any, Literal
+
+from openai import AsyncOpenAI
+from openai.types.responses import Response as OpenAIResponse
+from pydantic import SecretStr
+
+from backend.data.block import (
+    Block,
+    BlockCategory,
+    BlockOutput,
+    BlockSchemaInput,
+    BlockSchemaOutput,
+)
+from backend.data.model import (
+    APIKeyCredentials,
+    CredentialsField,
+    CredentialsMetaInput,
+    NodeExecutionStats,
+    SchemaField,
+)
+from backend.integrations.providers import ProviderName
+
+
+@dataclass
+class CodexCallResult:
+    """Structured response returned by Codex invocations."""
+
+    response: str
+    reasoning: str
+    response_id: str
+
+
+class CodexModel(str, Enum):
+    """Codex-capable OpenAI models."""
+
+    GPT5_1_CODEX = "gpt-5.1-codex"
+
+
+class CodexReasoningEffort(str, Enum):
+    """Configuration for the Responses API reasoning effort."""
+
+    NONE = "none"
+    LOW = "low"
+    MEDIUM = "medium"
+    HIGH = "high"
+
+
+CodexCredentials = CredentialsMetaInput[
+    Literal[ProviderName.OPENAI], Literal["api_key"]
+]
+
+TEST_CREDENTIALS = APIKeyCredentials(
+    id="e2fcb203-3f2d-4ad4-a344-8df3bc7db36b",
+    provider="openai",
+    api_key=SecretStr("mock-openai-api-key"),
+    title="Mock OpenAI API key",
+    expires_at=None,
+)
+TEST_CREDENTIALS_INPUT = {
+    "provider": TEST_CREDENTIALS.provider,
+    "id": TEST_CREDENTIALS.id,
+    "type": TEST_CREDENTIALS.type,
+    "title": TEST_CREDENTIALS.title,
+}
+
+
+def CodexCredentialsField() -> CodexCredentials:
+    return CredentialsField(
+        description="OpenAI API key with access to Codex models (Responses API).",
+    )
+
+
+class CodeGenerationBlock(Block):
+    """Block that talks to Codex models via the OpenAI Responses API."""
+
+    class Input(BlockSchemaInput):
+        prompt: str = SchemaField(
+            description="Primary coding request passed to the Codex model.",
+            placeholder="Generate a Python function that reverses a list.",
+        )
+        system_prompt: str = SchemaField(
+            title="System Prompt",
+            default=(
+                "You are Codex, an elite software engineer. "
+                "Favor concise, working code and highlight important caveats."
+            ),
+            description="Optional instructions injected via the Responses API instructions field.",
+            advanced=True,
+        )
+        model: CodexModel = SchemaField(
+            title="Codex Model",
+            default=CodexModel.GPT5_1_CODEX,
+            description="Codex-optimized model served via the Responses API.",
+            advanced=False,
+        )
+        reasoning_effort: CodexReasoningEffort = SchemaField(
+            title="Reasoning Effort",
+            default=CodexReasoningEffort.MEDIUM,
+            description="Controls the Responses API reasoning budget. Select 'none' to skip reasoning configs.",
+            advanced=True,
+        )
+        max_output_tokens: int | None = SchemaField(
+            title="Max Output Tokens",
+            default=2048,
+            description="Upper bound for generated tokens (hard limit 128,000). Leave blank to let OpenAI decide.",
+            advanced=True,
+        )
+        credentials: CodexCredentials = CodexCredentialsField()
+
+    class Output(BlockSchemaOutput):
+        response: str = SchemaField(
+            description="Code-focused response returned by the Codex model."
+        )
+        reasoning: str = SchemaField(
+            description="Reasoning summary returned by the model, if available.",
+            default="",
+        )
+        response_id: str = SchemaField(
+            description="ID of the Responses API call for auditing/debugging.",
+            default="",
+        )
+
+    def __init__(self):
+        super().__init__(
+            id="86a2a099-30df-47b4-b7e4-34ae5f83e0d5",
+            description="Generate or refactor code using OpenAI's Codex (Responses API).",
+            categories={BlockCategory.AI, BlockCategory.DEVELOPER_TOOLS},
+            input_schema=CodeGenerationBlock.Input,
+            output_schema=CodeGenerationBlock.Output,
+            test_input=[
+                {
+                    "prompt": "Write a TypeScript function that deduplicates an array.",
+                    "credentials": TEST_CREDENTIALS_INPUT,
+                }
+            ],
+            test_output=[
+                ("response", str),
+                ("reasoning", str),
+                ("response_id", str),
+            ],
+            test_mock={
+                "call_codex": lambda *_args, **_kwargs: CodexCallResult(
+                    response="function dedupe<T>(items: T[]): T[] { return [...new Set(items)]; }",
+                    reasoning="Used Set to remove duplicates in O(n).",
+                    response_id="resp_test",
+                )
+            },
+            test_credentials=TEST_CREDENTIALS,
+        )
+        self.execution_stats = NodeExecutionStats()
+
+    async def call_codex(
+        self,
+        *,
+        credentials: APIKeyCredentials,
+        model: CodexModel,
+        prompt: str,
+        system_prompt: str,
+        max_output_tokens: int | None,
+        reasoning_effort: CodexReasoningEffort,
+    ) -> CodexCallResult:
+        """Invoke the OpenAI Responses API."""
+        client = AsyncOpenAI(api_key=credentials.api_key.get_secret_value())
+
+        request_payload: dict[str, Any] = {
+            "model": model.value,
+            "input": prompt,
+        }
+        if system_prompt:
+            request_payload["instructions"] = system_prompt
+        if max_output_tokens is not None:
+            request_payload["max_output_tokens"] = max_output_tokens
+        if reasoning_effort != CodexReasoningEffort.NONE:
+            request_payload["reasoning"] = {"effort": reasoning_effort.value}
+
+        response = await client.responses.create(**request_payload)
+        if not isinstance(response, OpenAIResponse):
+            raise TypeError(f"Expected OpenAIResponse, got {type(response).__name__}")
+
+        # Extract data directly from typed response
+        text_output = response.output_text or ""
+        reasoning_summary = (
+            str(response.reasoning.summary)
+            if response.reasoning and response.reasoning.summary
+            else ""
+        )
+        response_id = response.id or ""
+
+        # Update usage stats
+        self.execution_stats.input_token_count = (
+            response.usage.input_tokens if response.usage else 0
+        )
+        self.execution_stats.output_token_count = (
+            response.usage.output_tokens if response.usage else 0
+        )
+        self.execution_stats.llm_call_count += 1
+
+        return CodexCallResult(
+            response=text_output,
+            reasoning=reasoning_summary,
+            response_id=response_id,
+        )
+
+    async def run(
+        self,
+        input_data: Input,
+        *,
+        credentials: APIKeyCredentials,
+        **_kwargs,
+    ) -> BlockOutput:
+        result = await self.call_codex(
+            credentials=credentials,
+            model=input_data.model,
+            prompt=input_data.prompt,
+            system_prompt=input_data.system_prompt,
+            max_output_tokens=input_data.max_output_tokens,
+            reasoning_effort=input_data.reasoning_effort,
+        )
+
+        yield "response", result.response
+        yield "reasoning", result.reasoning
+        yield "response_id", result.response_id

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

@@ -5,7 +5,8 @@ from backend.data.block import (
     BlockCategory,
     BlockManualWebhookConfig,
     BlockOutput,
-    BlockSchema,
+    BlockSchemaInput,
+    BlockSchemaOutput,
 )
 from backend.data.model import SchemaField
 from backend.integrations.providers import ProviderName
@@ -27,10 +28,10 @@ class TranscriptionDataModel(BaseModel):
 
 
 class CompassAITriggerBlock(Block):
-    class Input(BlockSchema):
+    class Input(BlockSchemaInput):
         payload: TranscriptionDataModel = SchemaField(hidden=True)
 
-    class Output(BlockSchema):
+    class Output(BlockSchemaOutput):
         transcription: str = SchemaField(
             description="The contents of the compass transcription."
         )

autogpt_platform/backend/backend/blocks/count_words_and_char_block.py

@@ -1,16 +1,22 @@
-from backend.data.block import Block, BlockCategory, BlockOutput, BlockSchema
+from backend.data.block import (
+    Block,
+    BlockCategory,
+    BlockOutput,
+    BlockSchemaInput,
+    BlockSchemaOutput,
+)
 from backend.data.model import SchemaField
 
 
 class WordCharacterCountBlock(Block):
-    class Input(BlockSchema):
+    class Input(BlockSchemaInput):
         text: str = SchemaField(
             description="Input text to count words and characters",
             placeholder="Enter your text here",
             advanced=False,
         )
 
-    class Output(BlockSchema):
+    class Output(BlockSchemaOutput):
         word_count: int = SchemaField(description="Number of words in the input text")
         character_count: int = SchemaField(
             description="Number of characters in the input text"

autogpt_platform/backend/backend/blocks/data_manipulation.py

@@ -1,6 +1,12 @@
 from typing import Any, List
 
-from backend.data.block import Block, BlockCategory, BlockOutput, BlockSchema
+from backend.data.block import (
+    Block,
+    BlockCategory,
+    BlockOutput,
+    BlockSchemaInput,
+    BlockSchemaOutput,
+)
 from backend.data.model import SchemaField
 from backend.util.json import loads
 from backend.util.mock import MockObject
@@ -12,13 +18,13 @@ from backend.util.prompt import estimate_token_count_str
 
 
 class CreateDictionaryBlock(Block):
-    class Input(BlockSchema):
+    class Input(BlockSchemaInput):
         values: dict[str, Any] = SchemaField(
             description="Key-value pairs to create the dictionary with",
             placeholder="e.g., {'name': 'Alice', 'age': 25}",
         )
 
-    class Output(BlockSchema):
+    class Output(BlockSchemaOutput):
         dictionary: dict[str, Any] = SchemaField(
             description="The created dictionary containing the specified key-value pairs"
         )
@@ -62,7 +68,7 @@ class CreateDictionaryBlock(Block):
 
 
 class AddToDictionaryBlock(Block):
-    class Input(BlockSchema):
+    class Input(BlockSchemaInput):
         dictionary: dict[Any, Any] = SchemaField(
             default_factory=dict,
             description="The dictionary to add the entry to. If not provided, a new dictionary will be created.",
@@ -86,11 +92,10 @@ class AddToDictionaryBlock(Block):
             advanced=True,
         )
 
-    class Output(BlockSchema):
+    class Output(BlockSchemaOutput):
         updated_dictionary: dict = SchemaField(
             description="The dictionary with the new entry added."
         )
-        error: str = SchemaField(description="Error message if the operation failed.")
 
     def __init__(self):
         super().__init__(
@@ -141,11 +146,11 @@ class AddToDictionaryBlock(Block):
 
 
 class FindInDictionaryBlock(Block):
-    class Input(BlockSchema):
+    class Input(BlockSchemaInput):
         input: Any = SchemaField(description="Dictionary to lookup from")
         key: str | int = SchemaField(description="Key to lookup in the dictionary")
 
-    class Output(BlockSchema):
+    class Output(BlockSchemaOutput):
         output: Any = SchemaField(description="Value found for the given key")
         missing: Any = SchemaField(
             description="Value of the input that missing the key"
@@ -201,7 +206,7 @@ class FindInDictionaryBlock(Block):
 
 
 class RemoveFromDictionaryBlock(Block):
-    class Input(BlockSchema):
+    class Input(BlockSchemaInput):
         dictionary: dict[Any, Any] = SchemaField(
             description="The dictionary to modify."
         )
@@ -210,12 +215,11 @@ class RemoveFromDictionaryBlock(Block):
             default=False, description="Whether to return the removed value."
         )
 
-    class Output(BlockSchema):
+    class Output(BlockSchemaOutput):
         updated_dictionary: dict[Any, Any] = SchemaField(
             description="The dictionary after removal."
         )
         removed_value: Any = SchemaField(description="The removed value if requested.")
-        error: str = SchemaField(description="Error message if the operation failed.")
 
     def __init__(self):
         super().__init__(
@@ -251,19 +255,18 @@ class RemoveFromDictionaryBlock(Block):
 
 
 class ReplaceDictionaryValueBlock(Block):
-    class Input(BlockSchema):
+    class Input(BlockSchemaInput):
         dictionary: dict[Any, Any] = SchemaField(
             description="The dictionary to modify."
         )
         key: str | int = SchemaField(description="Key to replace the value for.")
         value: Any = SchemaField(description="The new value for the given key.")
 
-    class Output(BlockSchema):
+    class Output(BlockSchemaOutput):
         updated_dictionary: dict[Any, Any] = SchemaField(
             description="The dictionary after replacement."
         )
         old_value: Any = SchemaField(description="The value that was replaced.")
-        error: str = SchemaField(description="Error message if the operation failed.")
 
     def __init__(self):
         super().__init__(
@@ -300,10 +303,10 @@ class ReplaceDictionaryValueBlock(Block):
 
 
 class DictionaryIsEmptyBlock(Block):
-    class Input(BlockSchema):
+    class Input(BlockSchemaInput):
         dictionary: dict[Any, Any] = SchemaField(description="The dictionary to check.")
 
-    class Output(BlockSchema):
+    class Output(BlockSchemaOutput):
         is_empty: bool = SchemaField(description="True if the dictionary is empty.")
 
     def __init__(self):
@@ -327,7 +330,7 @@ class DictionaryIsEmptyBlock(Block):
 
 
 class CreateListBlock(Block):
-    class Input(BlockSchema):
+    class Input(BlockSchemaInput):
         values: List[Any] = SchemaField(
             description="A list of values to be combined into a new list.",
             placeholder="e.g., ['Alice', 25, True]",
@@ -343,11 +346,10 @@ class CreateListBlock(Block):
             advanced=True,
         )
 
-    class Output(BlockSchema):
+    class Output(BlockSchemaOutput):
         list: List[Any] = SchemaField(
             description="The created list containing the specified values."
         )
-        error: str = SchemaField(description="Error message if list creation failed.")
 
     def __init__(self):
         super().__init__(
@@ -404,7 +406,7 @@ class CreateListBlock(Block):
 
 
 class AddToListBlock(Block):
-    class Input(BlockSchema):
+    class Input(BlockSchemaInput):
         list: List[Any] = SchemaField(
             default_factory=list,
             advanced=False,
@@ -425,11 +427,10 @@ class AddToListBlock(Block):
             description="The position to insert the new entry. If not provided, the entry will be appended to the end of the list.",
         )
 
-    class Output(BlockSchema):
+    class Output(BlockSchemaOutput):
         updated_list: List[Any] = SchemaField(
             description="The list with the new entry added."
         )
-        error: str = SchemaField(description="Error message if the operation failed.")
 
     def __init__(self):
         super().__init__(
@@ -484,11 +485,11 @@ class AddToListBlock(Block):
 
 
 class FindInListBlock(Block):
-    class Input(BlockSchema):
+    class Input(BlockSchemaInput):
         list: List[Any] = SchemaField(description="The list to search in.")
         value: Any = SchemaField(description="The value to search for.")
 
-    class Output(BlockSchema):
+    class Output(BlockSchemaOutput):
         index: int = SchemaField(description="The index of the value in the list.")
         found: bool = SchemaField(
             description="Whether the value was found in the list."
@@ -526,15 +527,14 @@ class FindInListBlock(Block):
 
 
 class GetListItemBlock(Block):
-    class Input(BlockSchema):
+    class Input(BlockSchemaInput):
         list: List[Any] = SchemaField(description="The list to get the item from.")
         index: int = SchemaField(
             description="The 0-based index of the item (supports negative indices)."
         )
 
-    class Output(BlockSchema):
+    class Output(BlockSchemaOutput):
         item: Any = SchemaField(description="The item at the specified index.")
-        error: str = SchemaField(description="Error message if the operation failed.")
 
     def __init__(self):
         super().__init__(
@@ -561,7 +561,7 @@ class GetListItemBlock(Block):
 
 
 class RemoveFromListBlock(Block):
-    class Input(BlockSchema):
+    class Input(BlockSchemaInput):
         list: List[Any] = SchemaField(description="The list to modify.")
         value: Any = SchemaField(
             default=None, description="Value to remove from the list."
@@ -574,10 +574,9 @@ class RemoveFromListBlock(Block):
             default=False, description="Whether to return the removed item."
         )
 
-    class Output(BlockSchema):
+    class Output(BlockSchemaOutput):
         updated_list: List[Any] = SchemaField(description="The list after removal.")
         removed_item: Any = SchemaField(description="The removed item if requested.")
-        error: str = SchemaField(description="Error message if the operation failed.")
 
     def __init__(self):
         super().__init__(
@@ -618,17 +617,16 @@ class RemoveFromListBlock(Block):
 
 
 class ReplaceListItemBlock(Block):
-    class Input(BlockSchema):
+    class Input(BlockSchemaInput):
         list: List[Any] = SchemaField(description="The list to modify.")
         index: int = SchemaField(
             description="Index of the item to replace (supports negative indices)."
         )
         value: Any = SchemaField(description="The new value for the given index.")
 
-    class Output(BlockSchema):
+    class Output(BlockSchemaOutput):
         updated_list: List[Any] = SchemaField(description="The list after replacement.")
         old_item: Any = SchemaField(description="The item that was replaced.")
-        error: str = SchemaField(description="Error message if the operation failed.")
 
     def __init__(self):
         super().__init__(
@@ -663,10 +661,10 @@ class ReplaceListItemBlock(Block):
 
 
 class ListIsEmptyBlock(Block):
-    class Input(BlockSchema):
+    class Input(BlockSchemaInput):
         list: List[Any] = SchemaField(description="The list to check.")
 
-    class Output(BlockSchema):
+    class Output(BlockSchemaOutput):
         is_empty: bool = SchemaField(description="True if the list is empty.")
 
     def __init__(self):

autogpt_platform/backend/backend/blocks/dataforseo/keyword_suggestions.py

@@ -8,7 +8,8 @@ from backend.sdk import (
     Block,
     BlockCategory,
     BlockOutput,
-    BlockSchema,
+    BlockSchemaInput,
+    BlockSchemaOutput,
     CredentialsMetaInput,
     SchemaField,
     UserPasswordCredentials,
@@ -18,7 +19,7 @@ from ._api import DataForSeoClient
 from ._config import dataforseo
 
 
-class KeywordSuggestion(BlockSchema):
+class KeywordSuggestion(BlockSchemaInput):
     """Schema for a keyword suggestion result."""
 
     keyword: str = SchemaField(description="The keyword suggestion")
@@ -45,7 +46,7 @@ class KeywordSuggestion(BlockSchema):
 class DataForSeoKeywordSuggestionsBlock(Block):
     """Block for getting keyword suggestions from DataForSEO Labs."""
 
-    class Input(BlockSchema):
+    class Input(BlockSchemaInput):
         credentials: CredentialsMetaInput = dataforseo.credentials_field(
             description="DataForSEO credentials (username and password)"
         )
@@ -77,7 +78,7 @@ class DataForSeoKeywordSuggestionsBlock(Block):
             le=3000,
         )
 
-    class Output(BlockSchema):
+    class Output(BlockSchemaOutput):
         suggestions: List[KeywordSuggestion] = SchemaField(
             description="List of keyword suggestions with metrics"
         )
@@ -90,7 +91,6 @@ class DataForSeoKeywordSuggestionsBlock(Block):
         seed_keyword: str = SchemaField(
             description="The seed keyword used for the query"
         )
-        error: str = SchemaField(description="Error message if the API call failed")
 
     def __init__(self):
         super().__init__(
@@ -213,12 +213,12 @@ class DataForSeoKeywordSuggestionsBlock(Block):
 class KeywordSuggestionExtractorBlock(Block):
     """Extracts individual fields from a KeywordSuggestion object."""
 
-    class Input(BlockSchema):
+    class Input(BlockSchemaInput):
         suggestion: KeywordSuggestion = SchemaField(
             description="The keyword suggestion object to extract fields from"
         )
 
-    class Output(BlockSchema):
+    class Output(BlockSchemaOutput):
         keyword: str = SchemaField(description="The keyword suggestion")
         search_volume: Optional[int] = SchemaField(
             description="Monthly search volume", default=None

autogpt_platform/backend/backend/blocks/dataforseo/related_keywords.py

@@ -8,7 +8,8 @@ from backend.sdk import (
     Block,
     BlockCategory,
     BlockOutput,
-    BlockSchema,
+    BlockSchemaInput,
+    BlockSchemaOutput,
     CredentialsMetaInput,
     SchemaField,
     UserPasswordCredentials,
@@ -18,7 +19,7 @@ from ._api import DataForSeoClient
 from ._config import dataforseo
 
 
-class RelatedKeyword(BlockSchema):
+class RelatedKeyword(BlockSchemaInput):
     """Schema for a related keyword result."""
 
     keyword: str = SchemaField(description="The related keyword")
@@ -45,7 +46,7 @@ class RelatedKeyword(BlockSchema):
 class DataForSeoRelatedKeywordsBlock(Block):
     """Block for getting related keywords from DataForSEO Labs."""
 
-    class Input(BlockSchema):
+    class Input(BlockSchemaInput):
         credentials: CredentialsMetaInput = dataforseo.credentials_field(
             description="DataForSEO credentials (username and password)"
         )
@@ -85,7 +86,7 @@ class DataForSeoRelatedKeywordsBlock(Block):
             le=4,
         )
 
-    class Output(BlockSchema):
+    class Output(BlockSchemaOutput):
         related_keywords: List[RelatedKeyword] = SchemaField(
             description="List of related keywords with metrics"
         )
@@ -98,7 +99,6 @@ class DataForSeoRelatedKeywordsBlock(Block):
         seed_keyword: str = SchemaField(
             description="The seed keyword used for the query"
         )
-        error: str = SchemaField(description="Error message if the API call failed")
 
     def __init__(self):
         super().__init__(
@@ -231,12 +231,12 @@ class DataForSeoRelatedKeywordsBlock(Block):
 class RelatedKeywordExtractorBlock(Block):
     """Extracts individual fields from a RelatedKeyword object."""
 
-    class Input(BlockSchema):
+    class Input(BlockSchemaInput):
         related_keyword: RelatedKeyword = SchemaField(
             description="The related keyword object to extract fields from"
         )
 
-    class Output(BlockSchema):
+    class Output(BlockSchemaOutput):
         keyword: str = SchemaField(description="The related keyword")
         search_volume: Optional[int] = SchemaField(
             description="Monthly search volume", default=None

autogpt_platform/backend/backend/blocks/decoder_block.py

@@ -1,17 +1,23 @@
 import codecs
 
-from backend.data.block import Block, BlockCategory, BlockOutput, BlockSchema
+from backend.data.block import (
+    Block,
+    BlockCategory,
+    BlockOutput,
+    BlockSchemaInput,
+    BlockSchemaOutput,
+)
 from backend.data.model import SchemaField
 
 
 class TextDecoderBlock(Block):
-    class Input(BlockSchema):
+    class Input(BlockSchemaInput):
         text: str = SchemaField(
             description="A string containing escaped characters to be decoded",
             placeholder='Your entire text block with \\n and \\" escaped characters',
         )
 
-    class Output(BlockSchema):
+    class Output(BlockSchemaOutput):
         decoded_text: str = SchemaField(
             description="The decoded text with escape sequences processed"
         )

autogpt_platform/backend/backend/blocks/discord/bot_blocks.py

@@ -7,7 +7,13 @@ from typing import Any
 import discord
 from pydantic import SecretStr
 
-from backend.data.block import Block, BlockCategory, BlockOutput, BlockSchema
+from backend.data.block import (
+    Block,
+    BlockCategory,
+    BlockOutput,
+    BlockSchemaInput,
+    BlockSchemaOutput,
+)
 from backend.data.model import APIKeyCredentials, SchemaField
 from backend.util.file import store_media_file
 from backend.util.request import Requests
@@ -28,10 +34,10 @@ TEST_CREDENTIALS_INPUT = TEST_BOT_CREDENTIALS_INPUT
 
 
 class ReadDiscordMessagesBlock(Block):
-    class Input(BlockSchema):
+    class Input(BlockSchemaInput):
         credentials: DiscordCredentials = DiscordCredentialsField()
 
-    class Output(BlockSchema):
+    class Output(BlockSchemaOutput):
         message_content: str = SchemaField(
             description="The content of the message received"
         )
@@ -164,7 +170,7 @@ class ReadDiscordMessagesBlock(Block):
 
 
 class SendDiscordMessageBlock(Block):
-    class Input(BlockSchema):
+    class Input(BlockSchemaInput):
         credentials: DiscordCredentials = DiscordCredentialsField()
         message_content: str = SchemaField(
             description="The content of the message to send"
@@ -178,7 +184,7 @@ class SendDiscordMessageBlock(Block):
             default="",
         )
 
-    class Output(BlockSchema):
+    class Output(BlockSchemaOutput):
         status: str = SchemaField(
             description="The status of the operation (e.g., 'Message sent', 'Error')"
         )
@@ -310,7 +316,7 @@ class SendDiscordMessageBlock(Block):
 
 
 class SendDiscordDMBlock(Block):
-    class Input(BlockSchema):
+    class Input(BlockSchemaInput):
         credentials: DiscordCredentials = DiscordCredentialsField()
         user_id: str = SchemaField(
             description="The Discord user ID to send the DM to (e.g., '123456789012345678')"
@@ -319,7 +325,7 @@ class SendDiscordDMBlock(Block):
             description="The content of the direct message to send"
         )
 
-    class Output(BlockSchema):
+    class Output(BlockSchemaOutput):
         status: str = SchemaField(description="The status of the operation")
         message_id: str = SchemaField(description="The ID of the sent message")
 
@@ -399,7 +405,7 @@ class SendDiscordDMBlock(Block):
 
 
 class SendDiscordEmbedBlock(Block):
-    class Input(BlockSchema):
+    class Input(BlockSchemaInput):
         credentials: DiscordCredentials = DiscordCredentialsField()
         channel_identifier: str = SchemaField(
             description="Channel ID or channel name to send the embed to"
@@ -436,7 +442,7 @@ class SendDiscordEmbedBlock(Block):
             default=[],
         )
 
-    class Output(BlockSchema):
+    class Output(BlockSchemaOutput):
         status: str = SchemaField(description="Operation status")
         message_id: str = SchemaField(description="ID of the sent embed message")
 
@@ -586,7 +592,7 @@ class SendDiscordEmbedBlock(Block):
 
 
 class SendDiscordFileBlock(Block):
-    class Input(BlockSchema):
+    class Input(BlockSchemaInput):
         credentials: DiscordCredentials = DiscordCredentialsField()
         channel_identifier: str = SchemaField(
             description="Channel ID or channel name to send the file to"
@@ -607,7 +613,7 @@ class SendDiscordFileBlock(Block):
             description="Optional message to send with the file", default=""
         )
 
-    class Output(BlockSchema):
+    class Output(BlockSchemaOutput):
         status: str = SchemaField(description="Operation status")
         message_id: str = SchemaField(description="ID of the sent message")
 
@@ -788,7 +794,7 @@ class SendDiscordFileBlock(Block):
 
 
 class ReplyToDiscordMessageBlock(Block):
-    class Input(BlockSchema):
+    class Input(BlockSchemaInput):
         credentials: DiscordCredentials = DiscordCredentialsField()
         channel_id: str = SchemaField(
             description="The channel ID where the message to reply to is located"
@@ -799,7 +805,7 @@ class ReplyToDiscordMessageBlock(Block):
             description="Whether to mention the original message author", default=True
         )
 
-    class Output(BlockSchema):
+    class Output(BlockSchemaOutput):
         status: str = SchemaField(description="Operation status")
         reply_id: str = SchemaField(description="ID of the reply message")
 
@@ -913,13 +919,13 @@ class ReplyToDiscordMessageBlock(Block):
 
 
 class DiscordUserInfoBlock(Block):
-    class Input(BlockSchema):
+    class Input(BlockSchemaInput):
         credentials: DiscordCredentials = DiscordCredentialsField()
         user_id: str = SchemaField(
             description="The Discord user ID to get information about"
         )
 
-    class Output(BlockSchema):
+    class Output(BlockSchemaOutput):
         user_id: str = SchemaField(
             description="The user's ID (passed through for chaining)"
         )
@@ -1030,7 +1036,7 @@ class DiscordUserInfoBlock(Block):
 
 
 class DiscordChannelInfoBlock(Block):
-    class Input(BlockSchema):
+    class Input(BlockSchemaInput):
         credentials: DiscordCredentials = DiscordCredentialsField()
         channel_identifier: str = SchemaField(
             description="Channel name or channel ID to look up"
@@ -1041,7 +1047,7 @@ class DiscordChannelInfoBlock(Block):
             default="",
         )
 
-    class Output(BlockSchema):
+    class Output(BlockSchemaOutput):
         channel_id: str = SchemaField(description="The channel's ID")
         channel_name: str = SchemaField(description="The channel's name")
         server_id: str = SchemaField(description="The server's ID")

autogpt_platform/backend/backend/blocks/discord/oauth_blocks.py

@@ -2,7 +2,13 @@
 Discord OAuth-based blocks.
 """
 
-from backend.data.block import Block, BlockCategory, BlockOutput, BlockSchema
+from backend.data.block import (
+    Block,
+    BlockCategory,
+    BlockOutput,
+    BlockSchemaInput,
+    BlockSchemaOutput,
+)
 from backend.data.model import OAuth2Credentials, SchemaField
 
 from ._api import DiscordOAuthUser, get_current_user
@@ -21,12 +27,12 @@ class DiscordGetCurrentUserBlock(Block):
     This block requires Discord OAuth2 credentials (not bot tokens).
     """
 
-    class Input(BlockSchema):
+    class Input(BlockSchemaInput):
         credentials: DiscordOAuthCredentialsInput = DiscordOAuthCredentialsField(
             ["identify"]
         )
 
-    class Output(BlockSchema):
+    class Output(BlockSchemaOutput):
         user_id: str = SchemaField(description="The authenticated user's Discord ID")
         username: str = SchemaField(description="The user's username")
         avatar_url: str = SchemaField(description="URL to the user's avatar image")

autogpt_platform/backend/backend/blocks/email_block.py

@@ -1,11 +1,19 @@
 import smtplib
+import socket
+import ssl
 from email.mime.multipart import MIMEMultipart
 from email.mime.text import MIMEText
 from typing import Literal
 
 from pydantic import BaseModel, ConfigDict, SecretStr
 
-from backend.data.block import Block, BlockCategory, BlockOutput, BlockSchema
+from backend.data.block import (
+    Block,
+    BlockCategory,
+    BlockOutput,
+    BlockSchemaInput,
+    BlockSchemaOutput,
+)
 from backend.data.model import (
     CredentialsField,
     CredentialsMetaInput,
@@ -42,16 +50,14 @@ def SMTPCredentialsField() -> SMTPCredentialsInput:
 
 
 class SMTPConfig(BaseModel):
-    smtp_server: str = SchemaField(
-        default="smtp.example.com", description="SMTP server address"
-    )
+    smtp_server: str = SchemaField(description="SMTP server address")
     smtp_port: int = SchemaField(default=25, description="SMTP port number")
 
     model_config = ConfigDict(title="SMTP Config")
 
 
 class SendEmailBlock(Block):
-    class Input(BlockSchema):
+    class Input(BlockSchemaInput):
         to_email: str = SchemaField(
             description="Recipient email address", placeholder="recipient@example.com"
         )
@@ -61,13 +67,10 @@ class SendEmailBlock(Block):
         body: str = SchemaField(
             description="Body of the email", placeholder="Enter the email body"
         )
-        config: SMTPConfig = SchemaField(
-            description="SMTP Config",
-            default=SMTPConfig(),
-        )
+        config: SMTPConfig = SchemaField(description="SMTP Config")
         credentials: SMTPCredentialsInput = SMTPCredentialsField()
 
-    class Output(BlockSchema):
+    class Output(BlockSchemaOutput):
         status: str = SchemaField(description="Status of the email sending operation")
         error: str = SchemaField(
             description="Error message if the email sending failed"
@@ -114,7 +117,7 @@ class SendEmailBlock(Block):
         msg["Subject"] = subject
         msg.attach(MIMEText(body, "plain"))
 
-        with smtplib.SMTP(smtp_server, smtp_port) as server:
+        with smtplib.SMTP(smtp_server, smtp_port, timeout=30) as server:
             server.starttls()
             server.login(smtp_username, smtp_password)
             server.sendmail(smtp_username, to_email, msg.as_string())
@@ -124,10 +127,59 @@ class SendEmailBlock(Block):
     async def run(
         self, input_data: Input, *, credentials: SMTPCredentials, **kwargs
     ) -> BlockOutput:
-        yield "status", self.send_email(
-            config=input_data.config,
-            to_email=input_data.to_email,
-            subject=input_data.subject,
-            body=input_data.body,
-            credentials=credentials,
-        )
+        try:
+            status = self.send_email(
+                config=input_data.config,
+                to_email=input_data.to_email,
+                subject=input_data.subject,
+                body=input_data.body,
+                credentials=credentials,
+            )
+            yield "status", status
+        except socket.gaierror:
+            yield "error", (
+                f"Cannot connect to SMTP server '{input_data.config.smtp_server}'. "
+                "Please verify the server address is correct."
+            )
+        except socket.timeout:
+            yield "error", (
+                f"Connection timeout to '{input_data.config.smtp_server}' "
+                f"on port {input_data.config.smtp_port}. "
+                "The server may be down or unreachable."
+            )
+        except ConnectionRefusedError:
+            yield "error", (
+                f"Connection refused to '{input_data.config.smtp_server}' "
+                f"on port {input_data.config.smtp_port}. "
+                "Common SMTP ports are: 587 (TLS), 465 (SSL), 25 (plain). "
+                "Please verify the port is correct."
+            )
+        except smtplib.SMTPNotSupportedError:
+            yield "error", (
+                f"STARTTLS not supported by server '{input_data.config.smtp_server}'. "
+                "Try using port 465 for SSL or port 25 for unencrypted connection."
+            )
+        except ssl.SSLError as e:
+            yield "error", (
+                f"SSL/TLS error when connecting to '{input_data.config.smtp_server}': {str(e)}. "
+                "The server may require a different security protocol."
+            )
+        except smtplib.SMTPAuthenticationError:
+            yield "error", (
+                "Authentication failed. Please verify your username and password are correct."
+            )
+        except smtplib.SMTPRecipientsRefused:
+            yield "error", (
+                f"Recipient email address '{input_data.to_email}' was rejected by the server. "
+                "Please verify the email address is valid."
+            )
+        except smtplib.SMTPSenderRefused:
+            yield "error", (
+                "Sender email address defined in the credentials that where used"
+                "was rejected by the server. "
+                "Please verify your account is authorized to send emails."
+            )
+        except smtplib.SMTPDataError as e:
+            yield "error", f"Email data rejected by server: {str(e)}"
+        except Exception as e:
+            raise e

autogpt_platform/backend/backend/blocks/enrichlayer/linkedin.py

@@ -8,7 +8,13 @@ which provides access to LinkedIn profile data and related information.
 import logging
 from typing import Optional
 
-from backend.data.block import Block, BlockCategory, BlockOutput, BlockSchema
+from backend.data.block import (
+    Block,
+    BlockCategory,
+    BlockOutput,
+    BlockSchemaInput,
+    BlockSchemaOutput,
+)
 from backend.data.model import APIKeyCredentials, CredentialsField, SchemaField
 from backend.util.type import MediaFileType
 
@@ -29,7 +35,7 @@ logger = logging.getLogger(__name__)
 class GetLinkedinProfileBlock(Block):
     """Block to fetch LinkedIn profile data using Enrichlayer API."""
 
-    class Input(BlockSchema):
+    class Input(BlockSchemaInput):
         """Input schema for GetLinkedinProfileBlock."""
 
         linkedin_url: str = SchemaField(
@@ -80,13 +86,12 @@ class GetLinkedinProfileBlock(Block):
             description="Enrichlayer API credentials"
         )
 
-    class Output(BlockSchema):
+    class Output(BlockSchemaOutput):
         """Output schema for GetLinkedinProfileBlock."""
 
         profile: PersonProfileResponse = SchemaField(
             description="LinkedIn profile data"
         )
-        error: str = SchemaField(description="Error message if the request failed")
 
     def __init__(self):
         """Initialize GetLinkedinProfileBlock."""
@@ -199,7 +204,7 @@ class GetLinkedinProfileBlock(Block):
 class LinkedinPersonLookupBlock(Block):
     """Block to look up LinkedIn profiles by person's information using Enrichlayer API."""
 
-    class Input(BlockSchema):
+    class Input(BlockSchemaInput):
         """Input schema for LinkedinPersonLookupBlock."""
 
         first_name: str = SchemaField(
@@ -242,13 +247,12 @@ class LinkedinPersonLookupBlock(Block):
             description="Enrichlayer API credentials"
         )
 
-    class Output(BlockSchema):
+    class Output(BlockSchemaOutput):
         """Output schema for LinkedinPersonLookupBlock."""
 
         lookup_result: PersonLookupResponse = SchemaField(
             description="LinkedIn profile lookup result"
         )
-        error: str = SchemaField(description="Error message if the request failed")
 
     def __init__(self):
         """Initialize LinkedinPersonLookupBlock."""
@@ -346,7 +350,7 @@ class LinkedinPersonLookupBlock(Block):
 class LinkedinRoleLookupBlock(Block):
     """Block to look up LinkedIn profiles by role in a company using Enrichlayer API."""
 
-    class Input(BlockSchema):
+    class Input(BlockSchemaInput):
         """Input schema for LinkedinRoleLookupBlock."""
 
         role: str = SchemaField(
@@ -366,13 +370,12 @@ class LinkedinRoleLookupBlock(Block):
             description="Enrichlayer API credentials"
         )
 
-    class Output(BlockSchema):
+    class Output(BlockSchemaOutput):
         """Output schema for LinkedinRoleLookupBlock."""
 
         role_lookup_result: RoleLookupResponse = SchemaField(
             description="LinkedIn role lookup result"
         )
-        error: str = SchemaField(description="Error message if the request failed")
 
     def __init__(self):
         """Initialize LinkedinRoleLookupBlock."""
@@ -449,7 +452,7 @@ class LinkedinRoleLookupBlock(Block):
 class GetLinkedinProfilePictureBlock(Block):
     """Block to get LinkedIn profile pictures using Enrichlayer API."""
 
-    class Input(BlockSchema):
+    class Input(BlockSchemaInput):
         """Input schema for GetLinkedinProfilePictureBlock."""
 
         linkedin_profile_url: str = SchemaField(
@@ -460,13 +463,12 @@ class GetLinkedinProfilePictureBlock(Block):
             description="Enrichlayer API credentials"
         )
 
-    class Output(BlockSchema):
+    class Output(BlockSchemaOutput):
         """Output schema for GetLinkedinProfilePictureBlock."""
 
         profile_picture_url: MediaFileType = SchemaField(
             description="LinkedIn profile picture URL"
         )
-        error: str = SchemaField(description="Error message if the request failed")
 
     def __init__(self):
         """Initialize GetLinkedinProfilePictureBlock."""

autogpt_platform/backend/backend/blocks/exa/_test.py

@@ -0,0 +1,22 @@
+"""
+Test credentials and helpers for Exa blocks.
+"""
+
+from pydantic import SecretStr
+
+from backend.data.model import APIKeyCredentials
+
+TEST_CREDENTIALS = APIKeyCredentials(
+    id="01234567-89ab-cdef-0123-456789abcdef",
+    provider="exa",
+    api_key=SecretStr("mock-exa-api-key"),
+    title="Mock Exa API key",
+    expires_at=None,
+)
+
+TEST_CREDENTIALS_INPUT = {
+    "provider": TEST_CREDENTIALS.provider,
+    "id": TEST_CREDENTIALS.id,
+    "type": TEST_CREDENTIALS.type,
+    "title": TEST_CREDENTIALS.title,
+}

autogpt_platform/backend/backend/blocks/exa/answers.py

@@ -1,55 +1,59 @@
+from typing import Optional
+
+from exa_py import AsyncExa
+from exa_py.api import AnswerResponse
+from pydantic import BaseModel
+
 from backend.sdk import (
     APIKeyCredentials,
-    BaseModel,
     Block,
     BlockCategory,
     BlockOutput,
-    BlockSchema,
+    BlockSchemaInput,
+    BlockSchemaOutput,
     CredentialsMetaInput,
-    Requests,
+    MediaFileType,
     SchemaField,
 )
 
 from ._config import exa
 
 
-class CostBreakdown(BaseModel):
-    keywordSearch: float
-    neuralSearch: float
-    contentText: float
-    contentHighlight: float
-    contentSummary: float
+class AnswerCitation(BaseModel):
+    """Citation model for answer endpoint."""
 
+    id: str = SchemaField(description="The temporary ID for the document")
+    url: str = SchemaField(description="The URL of the search result")
+    title: Optional[str] = SchemaField(description="The title of the search result")
+    author: Optional[str] = SchemaField(description="The author of the content")
+    publishedDate: Optional[str] = SchemaField(
+        description="An estimate of the creation date"
+    )
+    text: Optional[str] = SchemaField(description="The full text content of the source")
+    image: Optional[MediaFileType] = SchemaField(
+        description="The URL of the image associated with the result"
+    )
+    favicon: Optional[MediaFileType] = SchemaField(
+        description="The URL of the favicon for the domain"
+    )
 
-class SearchBreakdown(BaseModel):
-    search: float
-    contents: float
-    breakdown: CostBreakdown
-
-
-class PerRequestPrices(BaseModel):
-    neuralSearch_1_25_results: float
-    neuralSearch_26_100_results: float
-    neuralSearch_100_plus_results: float
-    keywordSearch_1_100_results: float
-    keywordSearch_100_plus_results: float
-
-
-class PerPagePrices(BaseModel):
-    contentText: float
-    contentHighlight: float
-    contentSummary: float
-
-
-class CostDollars(BaseModel):
-    total: float
-    breakDown: list[SearchBreakdown]
-    perRequestPrices: PerRequestPrices
-    perPagePrices: PerPagePrices
+    @classmethod
+    def from_sdk(cls, sdk_citation) -> "AnswerCitation":
+        """Convert SDK AnswerResult (dataclass) to our Pydantic model."""
+        return cls(
+            id=getattr(sdk_citation, "id", ""),
+            url=getattr(sdk_citation, "url", ""),
+            title=getattr(sdk_citation, "title", None),
+            author=getattr(sdk_citation, "author", None),
+            publishedDate=getattr(sdk_citation, "published_date", None),
+            text=getattr(sdk_citation, "text", None),
+            image=getattr(sdk_citation, "image", None),
+            favicon=getattr(sdk_citation, "favicon", None),
+        )
 
 
 class ExaAnswerBlock(Block):
-    class Input(BlockSchema):
+    class Input(BlockSchemaInput):
         credentials: CredentialsMetaInput = exa.credentials_field(
             description="The Exa integration requires an API Key."
         )
@@ -58,31 +62,21 @@ class ExaAnswerBlock(Block):
             placeholder="What is the latest valuation of SpaceX?",
         )
         text: bool = SchemaField(
-            default=False,
-            description="If true, the response includes full text content in the search results",
-            advanced=True,
-        )
-        model: str = SchemaField(
-            default="exa",
-            description="The search model to use (exa or exa-pro)",
-            placeholder="exa",
-            advanced=True,
+            description="Include full text content in the search results used for the answer",
+            default=True,
         )
 
-    class Output(BlockSchema):
+    class Output(BlockSchemaOutput):
         answer: str = SchemaField(
             description="The generated answer based on search results"
         )
-        citations: list[dict] = SchemaField(
-            description="Search results used to generate the answer",
-            default_factory=list,
+        citations: list[AnswerCitation] = SchemaField(
+            description="Search results used to generate the answer"
         )
-        cost_dollars: CostDollars = SchemaField(
-            description="Cost breakdown of the request"
-        )
-        error: str = SchemaField(
-            description="Error message if the request failed", default=""
+        citation: AnswerCitation = SchemaField(
+            description="Individual citation from the answer"
         )
+        error: str = SchemaField(description="Error message if the request failed")
 
     def __init__(self):
         super().__init__(
@@ -96,26 +90,24 @@ class ExaAnswerBlock(Block):
     async def run(
         self, input_data: Input, *, credentials: APIKeyCredentials, **kwargs
     ) -> BlockOutput:
-        url = "https://api.exa.ai/answer"
-        headers = {
-            "Content-Type": "application/json",
-            "x-api-key": credentials.api_key.get_secret_value(),
-        }
+        aexa = AsyncExa(api_key=credentials.api_key.get_secret_value())
 
-        # Build the payload
-        payload = {
-            "query": input_data.query,
-            "text": input_data.text,
-            "model": input_data.model,
-        }
+        # Get answer using SDK (stream=False for blocks) - this IS async, needs await
+        response = await aexa.answer(
+            query=input_data.query, text=input_data.text, stream=False
+        )
 
-        try:
-            response = await Requests().post(url, headers=headers, json=payload)
-            data = response.json()
+        # this should remain true as long as they don't start defaulting to streaming only.
+        # provides a bit of safety for sdk updates.
+        assert type(response) is AnswerResponse
 
-            yield "answer", data.get("answer", "")
-            yield "citations", data.get("citations", [])
-            yield "cost_dollars", data.get("costDollars", {})
+        yield "answer", response.answer
 
-        except Exception as e:
-            yield "error", str(e)
+        citations = [
+            AnswerCitation.from_sdk(sdk_citation)
+            for sdk_citation in response.citations or []
+        ]
+
+        yield "citations", citations
+        for citation in citations:
+            yield "citation", citation

autogpt_platform/backend/backend/blocks/exa/code_context.py

@@ -0,0 +1,118 @@
+"""
+Exa Code Context Block
+
+Provides code search capabilities to find relevant code snippets and examples
+from open source repositories, documentation, and Stack Overflow.
+"""
+
+from typing import Union
+
+from pydantic import BaseModel
+
+from backend.sdk import (
+    APIKeyCredentials,
+    Block,
+    BlockCategory,
+    BlockOutput,
+    BlockSchemaInput,
+    BlockSchemaOutput,
+    CredentialsMetaInput,
+    Requests,
+    SchemaField,
+)
+
+from ._config import exa
+
+
+class CodeContextResponse(BaseModel):
+    """Stable output model for code context responses."""
+
+    request_id: str
+    query: str
+    response: str
+    results_count: int
+    cost_dollars: str
+    search_time: float
+    output_tokens: int
+
+    @classmethod
+    def from_api(cls, data: dict) -> "CodeContextResponse":
+        """Convert API response to our stable model."""
+        return cls(
+            request_id=data.get("requestId", ""),
+            query=data.get("query", ""),
+            response=data.get("response", ""),
+            results_count=data.get("resultsCount", 0),
+            cost_dollars=data.get("costDollars", ""),
+            search_time=data.get("searchTime", 0.0),
+            output_tokens=data.get("outputTokens", 0),
+        )
+
+
+class ExaCodeContextBlock(Block):
+    """Get relevant code snippets and examples from open source repositories."""
+
+    class Input(BlockSchemaInput):
+        credentials: CredentialsMetaInput = exa.credentials_field(
+            description="The Exa integration requires an API Key."
+        )
+        query: str = SchemaField(
+            description="Search query to find relevant code snippets. Describe what you're trying to do or what code you're looking for.",
+            placeholder="how to use React hooks for state management",
+        )
+        tokens_num: Union[str, int] = SchemaField(
+            default="dynamic",
+            description="Token limit for response. Use 'dynamic' for automatic sizing, 5000 for standard queries, or 10000 for comprehensive examples.",
+            placeholder="dynamic",
+        )
+
+    class Output(BlockSchemaOutput):
+        request_id: str = SchemaField(description="Unique identifier for this request")
+        query: str = SchemaField(description="The search query used")
+        response: str = SchemaField(
+            description="Formatted code snippets and contextual examples with sources"
+        )
+        results_count: int = SchemaField(
+            description="Number of code sources found and included"
+        )
+        cost_dollars: str = SchemaField(description="Cost of this request in dollars")
+        search_time: float = SchemaField(
+            description="Time taken to search in milliseconds"
+        )
+        output_tokens: int = SchemaField(description="Number of tokens in the response")
+
+    def __init__(self):
+        super().__init__(
+            id="8f9e0d1c-2b3a-4567-8901-23456789abcd",
+            description="Search billions of GitHub repos, docs, and Stack Overflow for relevant code examples",
+            categories={BlockCategory.SEARCH, BlockCategory.DEVELOPER_TOOLS},
+            input_schema=ExaCodeContextBlock.Input,
+            output_schema=ExaCodeContextBlock.Output,
+        )
+
+    async def run(
+        self, input_data: Input, *, credentials: APIKeyCredentials, **kwargs
+    ) -> BlockOutput:
+        url = "https://api.exa.ai/context"
+        headers = {
+            "Content-Type": "application/json",
+            "x-api-key": credentials.api_key.get_secret_value(),
+        }
+
+        payload = {
+            "query": input_data.query,
+            "tokensNum": input_data.tokens_num,
+        }
+
+        response = await Requests().post(url, headers=headers, json=payload)
+        data = response.json()
+
+        context = CodeContextResponse.from_api(data)
+
+        yield "request_id", context.request_id
+        yield "query", context.query
+        yield "response", context.response
+        yield "results_count", context.results_count
+        yield "cost_dollars", context.cost_dollars
+        yield "search_time", context.search_time
+        yield "output_tokens", context.output_tokens

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

@@ -1,39 +1,127 @@
+from enum import Enum
+from typing import Optional
+
+from exa_py import AsyncExa
+from pydantic import BaseModel
+
 from backend.sdk import (
     APIKeyCredentials,
     Block,
     BlockCategory,
     BlockOutput,
-    BlockSchema,
+    BlockSchemaInput,
+    BlockSchemaOutput,
     CredentialsMetaInput,
-    Requests,
     SchemaField,
 )
 
 from ._config import exa
-from .helpers import ContentSettings
+from .helpers import (
+    CostDollars,
+    ExaSearchResults,
+    ExtrasSettings,
+    HighlightSettings,
+    LivecrawlTypes,
+    SummarySettings,
+)
+
+
+class ContentStatusTag(str, Enum):
+    CRAWL_NOT_FOUND = "CRAWL_NOT_FOUND"
+    CRAWL_TIMEOUT = "CRAWL_TIMEOUT"
+    CRAWL_LIVECRAWL_TIMEOUT = "CRAWL_LIVECRAWL_TIMEOUT"
+    SOURCE_NOT_AVAILABLE = "SOURCE_NOT_AVAILABLE"
+    CRAWL_UNKNOWN_ERROR = "CRAWL_UNKNOWN_ERROR"
+
+
+class ContentError(BaseModel):
+    tag: Optional[ContentStatusTag] = SchemaField(
+        default=None, description="Specific error type"
+    )
+    httpStatusCode: Optional[int] = SchemaField(
+        default=None, description="The corresponding HTTP status code"
+    )
+
+
+class ContentStatus(BaseModel):
+    id: str = SchemaField(description="The URL that was requested")
+    status: str = SchemaField(
+        description="Status of the content fetch operation (success or error)"
+    )
+    error: Optional[ContentError] = SchemaField(
+        default=None, description="Error details, only present when status is 'error'"
+    )
 
 
 class ExaContentsBlock(Block):
-    class Input(BlockSchema):
+    class Input(BlockSchemaInput):
         credentials: CredentialsMetaInput = exa.credentials_field(
             description="The Exa integration requires an API Key."
         )
-        ids: list[str] = SchemaField(
-            description="Array of document IDs obtained from searches"
+        urls: list[str] = SchemaField(
+            description="Array of URLs to crawl (preferred over 'ids')",
+            default_factory=list,
+            advanced=False,
         )
-        contents: ContentSettings = SchemaField(
-            description="Content retrieval settings",
-            default=ContentSettings(),
+        ids: list[str] = SchemaField(
+            description="[DEPRECATED - use 'urls' instead] Array of document IDs obtained from searches",
+            default_factory=list,
+            advanced=True,
+        )
+        text: bool = SchemaField(
+            description="Retrieve text content from pages",
+            default=True,
+        )
+        highlights: HighlightSettings = SchemaField(
+            description="Text snippets most relevant from each page",
+            default=HighlightSettings(),
+        )
+        summary: SummarySettings = SchemaField(
+            description="LLM-generated summary of the webpage",
+            default=SummarySettings(),
+        )
+        livecrawl: Optional[LivecrawlTypes] = SchemaField(
+            description="Livecrawling options: never, fallback (default), always, preferred",
+            default=LivecrawlTypes.FALLBACK,
+            advanced=True,
+        )
+        livecrawl_timeout: Optional[int] = SchemaField(
+            description="Timeout for livecrawling in milliseconds",
+            default=10000,
+            advanced=True,
+        )
+        subpages: Optional[int] = SchemaField(
+            description="Number of subpages to crawl", default=0, ge=0, advanced=True
+        )
+        subpage_target: Optional[str | list[str]] = SchemaField(
+            description="Keyword(s) to find specific subpages of search results",
+            default=None,
+            advanced=True,
+        )
+        extras: ExtrasSettings = SchemaField(
+            description="Extra parameters for additional content",
+            default=ExtrasSettings(),
             advanced=True,
         )
 
-    class Output(BlockSchema):
-        results: list = SchemaField(
-            description="List of document contents", default_factory=list
+    class Output(BlockSchemaOutput):
+        results: list[ExaSearchResults] = SchemaField(
+            description="List of document contents with metadata"
         )
-        error: str = SchemaField(
-            description="Error message if the request failed", default=""
+        result: ExaSearchResults = SchemaField(
+            description="Single document content result"
         )
+        context: str = SchemaField(
+            description="A formatted string of the results ready for LLMs"
+        )
+        request_id: str = SchemaField(description="Unique identifier for the request")
+        statuses: list[ContentStatus] = SchemaField(
+            description="Status information for each requested URL"
+        )
+        cost_dollars: Optional[CostDollars] = SchemaField(
+            description="Cost breakdown for the request"
+        )
+        error: str = SchemaField(description="Error message if the request failed")
 
     def __init__(self):
         super().__init__(
@@ -47,23 +135,91 @@ class ExaContentsBlock(Block):
     async def run(
         self, input_data: Input, *, credentials: APIKeyCredentials, **kwargs
     ) -> BlockOutput:
-        url = "https://api.exa.ai/contents"
-        headers = {
-            "Content-Type": "application/json",
-            "x-api-key": credentials.api_key.get_secret_value(),
-        }
+        if not input_data.urls and not input_data.ids:
+            raise ValueError("Either 'urls' or 'ids' must be provided")
 
-        # Convert ContentSettings to API format
-        payload = {
-            "ids": input_data.ids,
-            "text": input_data.contents.text,
-            "highlights": input_data.contents.highlights,
-            "summary": input_data.contents.summary,
-        }
+        sdk_kwargs = {}
 
-        try:
-            response = await Requests().post(url, headers=headers, json=payload)
-            data = response.json()
-            yield "results", data.get("results", [])
-        except Exception as e:
-            yield "error", str(e)
+        # Prefer urls over ids
+        if input_data.urls:
+            sdk_kwargs["urls"] = input_data.urls
+        elif input_data.ids:
+            sdk_kwargs["ids"] = input_data.ids
+
+        if input_data.text:
+            sdk_kwargs["text"] = {"includeHtmlTags": True}
+
+        # Handle highlights - only include if modified from defaults
+        if input_data.highlights and (
+            input_data.highlights.num_sentences != 1
+            or input_data.highlights.highlights_per_url != 1
+            or input_data.highlights.query is not None
+        ):
+            highlights_dict = {}
+            highlights_dict["numSentences"] = input_data.highlights.num_sentences
+            highlights_dict["highlightsPerUrl"] = (
+                input_data.highlights.highlights_per_url
+            )
+            if input_data.highlights.query:
+                highlights_dict["query"] = input_data.highlights.query
+            sdk_kwargs["highlights"] = highlights_dict
+
+        # Handle summary - only include if modified from defaults
+        if input_data.summary and (
+            input_data.summary.query is not None
+            or input_data.summary.schema is not None
+        ):
+            summary_dict = {}
+            if input_data.summary.query:
+                summary_dict["query"] = input_data.summary.query
+            if input_data.summary.schema:
+                summary_dict["schema"] = input_data.summary.schema
+            sdk_kwargs["summary"] = summary_dict
+
+        if input_data.livecrawl:
+            sdk_kwargs["livecrawl"] = input_data.livecrawl.value
+
+        if input_data.livecrawl_timeout is not None:
+            sdk_kwargs["livecrawl_timeout"] = input_data.livecrawl_timeout
+
+        if input_data.subpages is not None:
+            sdk_kwargs["subpages"] = input_data.subpages
+
+        if input_data.subpage_target:
+            sdk_kwargs["subpage_target"] = input_data.subpage_target
+
+        # Handle extras - only include if modified from defaults
+        if input_data.extras and (
+            input_data.extras.links > 0 or input_data.extras.image_links > 0
+        ):
+            extras_dict = {}
+            if input_data.extras.links:
+                extras_dict["links"] = input_data.extras.links
+            if input_data.extras.image_links:
+                extras_dict["image_links"] = input_data.extras.image_links
+            sdk_kwargs["extras"] = extras_dict
+
+        # Always enable context for LLM-ready output
+        sdk_kwargs["context"] = True
+
+        aexa = AsyncExa(api_key=credentials.api_key.get_secret_value())
+        response = await aexa.get_contents(**sdk_kwargs)
+
+        converted_results = [
+            ExaSearchResults.from_sdk(sdk_result)
+            for sdk_result in response.results or []
+        ]
+
+        yield "results", converted_results
+
+        for result in converted_results:
+            yield "result", result
+
+        if response.context:
+            yield "context", response.context
+
+        if response.statuses:
+            yield "statuses", response.statuses
+
+        if response.cost_dollars:
+            yield "cost_dollars", response.cost_dollars

autogpt_platform/backend/backend/blocks/exa/helpers.py

@@ -1,51 +1,150 @@
-from typing import Optional
+from enum import Enum
+from typing import Any, Dict, Literal, Optional, Union
 
-from backend.sdk import BaseModel, SchemaField
+from backend.sdk import BaseModel, MediaFileType, SchemaField
 
 
-class TextSettings(BaseModel):
-    max_characters: int = SchemaField(
-        default=1000,
+class LivecrawlTypes(str, Enum):
+    NEVER = "never"
+    FALLBACK = "fallback"
+    ALWAYS = "always"
+    PREFERRED = "preferred"
+
+
+class TextEnabled(BaseModel):
+    discriminator: Literal["enabled"] = "enabled"
+
+
+class TextDisabled(BaseModel):
+    discriminator: Literal["disabled"] = "disabled"
+
+
+class TextAdvanced(BaseModel):
+    discriminator: Literal["advanced"] = "advanced"
+    max_characters: Optional[int] = SchemaField(
+        default=None,
         description="Maximum number of characters to return",
         placeholder="1000",
     )
     include_html_tags: bool = SchemaField(
         default=False,
-        description="Whether to include HTML tags in the text",
+        description="Include HTML tags in the response, helps LLMs understand text structure",
         placeholder="False",
     )
 
 
 class HighlightSettings(BaseModel):
     num_sentences: int = SchemaField(
-        default=3,
+        default=1,
         description="Number of sentences per highlight",
-        placeholder="3",
+        placeholder="1",
+        ge=1,
     )
     highlights_per_url: int = SchemaField(
-        default=3,
+        default=1,
         description="Number of highlights per URL",
-        placeholder="3",
+        placeholder="1",
+        ge=1,
+    )
+    query: Optional[str] = SchemaField(
+        default=None,
+        description="Custom query to direct the LLM's selection of highlights",
+        placeholder="Key advancements",
     )
 
 
 class SummarySettings(BaseModel):
     query: Optional[str] = SchemaField(
-        default="",
-        description="Query string for summarization",
-        placeholder="Enter query",
+        default=None,
+        description="Custom query for the LLM-generated summary",
+        placeholder="Main developments",
+    )
+    schema: Optional[dict] = SchemaField(  # type: ignore
+        default=None,
+        description="JSON schema for structured output from summary",
+        advanced=True,
+    )
+
+
+class ExtrasSettings(BaseModel):
+    links: int = SchemaField(
+        default=0,
+        description="Number of URLs to return from each webpage",
+        placeholder="1",
+        ge=0,
+    )
+    image_links: int = SchemaField(
+        default=0,
+        description="Number of images to return for each result",
+        placeholder="1",
+        ge=0,
+    )
+
+
+class ContextEnabled(BaseModel):
+    discriminator: Literal["enabled"] = "enabled"
+
+
+class ContextDisabled(BaseModel):
+    discriminator: Literal["disabled"] = "disabled"
+
+
+class ContextAdvanced(BaseModel):
+    discriminator: Literal["advanced"] = "advanced"
+    max_characters: Optional[int] = SchemaField(
+        default=None,
+        description="Maximum character limit for context string",
+        placeholder="10000",
     )
 
 
 class ContentSettings(BaseModel):
-    text: TextSettings = SchemaField(
-        default=TextSettings(),
+    text: Optional[Union[bool, TextEnabled, TextDisabled, TextAdvanced]] = SchemaField(
+        default=None,
+        description="Text content retrieval. Boolean for simple enable/disable or object for advanced settings",
     )
-    highlights: HighlightSettings = SchemaField(
-        default=HighlightSettings(),
+    highlights: Optional[HighlightSettings] = SchemaField(
+        default=None,
+        description="Text snippets most relevant from each page",
     )
-    summary: SummarySettings = SchemaField(
-        default=SummarySettings(),
+    summary: Optional[SummarySettings] = SchemaField(
+        default=None,
+        description="LLM-generated summary of the webpage",
+    )
+    livecrawl: Optional[LivecrawlTypes] = SchemaField(
+        default=None,
+        description="Livecrawling options: never, fallback, always, preferred",
+        advanced=True,
+    )
+    livecrawl_timeout: Optional[int] = SchemaField(
+        default=None,
+        description="Timeout for livecrawling in milliseconds",
+        placeholder="10000",
+        advanced=True,
+    )
+    subpages: Optional[int] = SchemaField(
+        default=None,
+        description="Number of subpages to crawl",
+        placeholder="0",
+        ge=0,
+        advanced=True,
+    )
+    subpage_target: Optional[Union[str, list[str]]] = SchemaField(
+        default=None,
+        description="Keyword(s) to find specific subpages of search results",
+        advanced=True,
+    )
+    extras: Optional[ExtrasSettings] = SchemaField(
+        default=None,
+        description="Extra parameters for additional content",
+        advanced=True,
+    )
+    context: Optional[Union[bool, ContextEnabled, ContextDisabled, ContextAdvanced]] = (
+        SchemaField(
+            default=None,
+            description="Format search results into a context string for LLMs",
+            advanced=True,
+        )
     )
 
 
@@ -127,3 +226,225 @@ class WebsetEnrichmentConfig(BaseModel):
         default=None,
         description="Options for the enrichment",
     )
+
+
+# Shared result models
+class ExaSearchExtras(BaseModel):
+    links: list[str] = SchemaField(
+        default_factory=list, description="Array of links from the search result"
+    )
+    imageLinks: list[str] = SchemaField(
+        default_factory=list, description="Array of image links from the search result"
+    )
+
+
+class ExaSearchResults(BaseModel):
+    title: str | None = None
+    url: str | None = None
+    publishedDate: str | None = None
+    author: str | None = None
+    id: str
+    image: MediaFileType | None = None
+    favicon: MediaFileType | None = None
+    text: str | None = None
+    highlights: list[str] = SchemaField(default_factory=list)
+    highlightScores: list[float] = SchemaField(default_factory=list)
+    summary: str | None = None
+    subpages: list[dict] = SchemaField(default_factory=list)
+    extras: ExaSearchExtras | None = None
+
+    @classmethod
+    def from_sdk(cls, sdk_result) -> "ExaSearchResults":
+        """Convert SDK Result (dataclass) to our Pydantic model."""
+        return cls(
+            id=getattr(sdk_result, "id", ""),
+            url=getattr(sdk_result, "url", None),
+            title=getattr(sdk_result, "title", None),
+            author=getattr(sdk_result, "author", None),
+            publishedDate=getattr(sdk_result, "published_date", None),
+            text=getattr(sdk_result, "text", None),
+            highlights=getattr(sdk_result, "highlights", None) or [],
+            highlightScores=getattr(sdk_result, "highlight_scores", None) or [],
+            summary=getattr(sdk_result, "summary", None),
+            subpages=getattr(sdk_result, "subpages", None) or [],
+            image=getattr(sdk_result, "image", None),
+            favicon=getattr(sdk_result, "favicon", None),
+            extras=getattr(sdk_result, "extras", None),
+        )
+
+
+# Cost tracking models
+class CostBreakdown(BaseModel):
+    keywordSearch: float = SchemaField(default=0.0)
+    neuralSearch: float = SchemaField(default=0.0)
+    contentText: float = SchemaField(default=0.0)
+    contentHighlight: float = SchemaField(default=0.0)
+    contentSummary: float = SchemaField(default=0.0)
+
+
+class CostBreakdownItem(BaseModel):
+    search: float = SchemaField(default=0.0)
+    contents: float = SchemaField(default=0.0)
+    breakdown: CostBreakdown = SchemaField(default_factory=CostBreakdown)
+
+
+class PerRequestPrices(BaseModel):
+    neuralSearch_1_25_results: float = SchemaField(default=0.005)
+    neuralSearch_26_100_results: float = SchemaField(default=0.025)
+    neuralSearch_100_plus_results: float = SchemaField(default=1.0)
+    keywordSearch_1_100_results: float = SchemaField(default=0.0025)
+    keywordSearch_100_plus_results: float = SchemaField(default=3.0)
+
+
+class PerPagePrices(BaseModel):
+    contentText: float = SchemaField(default=0.001)
+    contentHighlight: float = SchemaField(default=0.001)
+    contentSummary: float = SchemaField(default=0.001)
+
+
+class CostDollars(BaseModel):
+    total: float = SchemaField(description="Total dollar cost for your request")
+    breakDown: list[CostBreakdownItem] = SchemaField(
+        default_factory=list, description="Breakdown of costs by operation type"
+    )
+    perRequestPrices: PerRequestPrices = SchemaField(
+        default_factory=PerRequestPrices,
+        description="Standard price per request for different operations",
+    )
+    perPagePrices: PerPagePrices = SchemaField(
+        default_factory=PerPagePrices,
+        description="Standard price per page for different content operations",
+    )
+
+
+# Helper functions for payload processing
+def process_text_field(
+    text: Union[bool, TextEnabled, TextDisabled, TextAdvanced, None]
+) -> Optional[Union[bool, Dict[str, Any]]]:
+    """Process text field for API payload."""
+    if text is None:
+        return None
+
+    # Handle backward compatibility with boolean
+    if isinstance(text, bool):
+        return text
+    elif isinstance(text, TextDisabled):
+        return False
+    elif isinstance(text, TextEnabled):
+        return True
+    elif isinstance(text, TextAdvanced):
+        text_dict = {}
+        if text.max_characters:
+            text_dict["maxCharacters"] = text.max_characters
+        if text.include_html_tags:
+            text_dict["includeHtmlTags"] = text.include_html_tags
+        return text_dict if text_dict else True
+    return None
+
+
+def process_contents_settings(contents: Optional[ContentSettings]) -> Dict[str, Any]:
+    """Process ContentSettings into API payload format."""
+    if not contents:
+        return {}
+
+    content_settings = {}
+
+    # Handle text field (can be boolean or object)
+    text_value = process_text_field(contents.text)
+    if text_value is not None:
+        content_settings["text"] = text_value
+
+    # Handle highlights
+    if contents.highlights:
+        highlights_dict: Dict[str, Any] = {
+            "numSentences": contents.highlights.num_sentences,
+            "highlightsPerUrl": contents.highlights.highlights_per_url,
+        }
+        if contents.highlights.query:
+            highlights_dict["query"] = contents.highlights.query
+        content_settings["highlights"] = highlights_dict
+
+    if contents.summary:
+        summary_dict = {}
+        if contents.summary.query:
+            summary_dict["query"] = contents.summary.query
+        if contents.summary.schema:
+            summary_dict["schema"] = contents.summary.schema
+        content_settings["summary"] = summary_dict
+
+    if contents.livecrawl:
+        content_settings["livecrawl"] = contents.livecrawl.value
+
+    if contents.livecrawl_timeout is not None:
+        content_settings["livecrawlTimeout"] = contents.livecrawl_timeout
+
+    if contents.subpages is not None:
+        content_settings["subpages"] = contents.subpages
+
+    if contents.subpage_target:
+        content_settings["subpageTarget"] = contents.subpage_target
+
+    if contents.extras:
+        extras_dict = {}
+        if contents.extras.links:
+            extras_dict["links"] = contents.extras.links
+        if contents.extras.image_links:
+            extras_dict["imageLinks"] = contents.extras.image_links
+        content_settings["extras"] = extras_dict
+
+    context_value = process_context_field(contents.context)
+    if context_value is not None:
+        content_settings["context"] = context_value
+
+    return content_settings
+
+
+def process_context_field(
+    context: Union[bool, dict, ContextEnabled, ContextDisabled, ContextAdvanced, None]
+) -> Optional[Union[bool, Dict[str, int]]]:
+    """Process context field for API payload."""
+    if context is None:
+        return None
+
+    # Handle backward compatibility with boolean
+    if isinstance(context, bool):
+        return context if context else None
+    elif isinstance(context, dict) and "maxCharacters" in context:
+        return {"maxCharacters": context["maxCharacters"]}
+    elif isinstance(context, ContextDisabled):
+        return None  # Don't send context field at all when disabled
+    elif isinstance(context, ContextEnabled):
+        return True
+    elif isinstance(context, ContextAdvanced):
+        if context.max_characters:
+            return {"maxCharacters": context.max_characters}
+        return True
+    return None
+
+
+def format_date_fields(
+    input_data: Any, date_field_mapping: Dict[str, str]
+) -> Dict[str, str]:
+    """Format datetime fields for API payload."""
+    formatted_dates = {}
+    for input_field, api_field in date_field_mapping.items():
+        value = getattr(input_data, input_field, None)
+        if value:
+            formatted_dates[api_field] = value.strftime("%Y-%m-%dT%H:%M:%S.000Z")
+    return formatted_dates
+
+
+def add_optional_fields(
+    input_data: Any,
+    field_mapping: Dict[str, str],
+    payload: Dict[str, Any],
+    process_enums: bool = False,
+) -> None:
+    """Add optional fields to payload if they have values."""
+    for input_field, api_field in field_mapping.items():
+        value = getattr(input_data, input_field, None)
+        if value:  # Only add non-empty values
+            if process_enums and hasattr(value, "value"):
+                payload[api_field] = value.value
+            else:
+                payload[api_field] = value

autogpt_platform/backend/backend/blocks/exa/model.py

@@ -1,247 +0,0 @@
-from datetime import datetime
-from enum import Enum
-from typing import Any, Dict, List, Optional
-
-from pydantic import BaseModel, Field
-
-
-# Enum definitions based on available options
-class WebsetStatus(str, Enum):
-    IDLE = "idle"
-    PENDING = "pending"
-    RUNNING = "running"
-    PAUSED = "paused"
-
-
-class WebsetSearchStatus(str, Enum):
-    CREATED = "created"
-    # Add more if known, based on example it's "created"
-
-
-class ImportStatus(str, Enum):
-    PENDING = "pending"
-    # Add more if known
-
-
-class ImportFormat(str, Enum):
-    CSV = "csv"
-    # Add more if known
-
-
-class EnrichmentStatus(str, Enum):
-    PENDING = "pending"
-    # Add more if known
-
-
-class EnrichmentFormat(str, Enum):
-    TEXT = "text"
-    # Add more if known
-
-
-class MonitorStatus(str, Enum):
-    ENABLED = "enabled"
-    # Add more if known
-
-
-class MonitorBehaviorType(str, Enum):
-    SEARCH = "search"
-    # Add more if known
-
-
-class MonitorRunStatus(str, Enum):
-    CREATED = "created"
-    # Add more if known
-
-
-class CanceledReason(str, Enum):
-    WEBSET_DELETED = "webset_deleted"
-    # Add more if known
-
-
-class FailedReason(str, Enum):
-    INVALID_FORMAT = "invalid_format"
-    # Add more if known
-
-
-class Confidence(str, Enum):
-    HIGH = "high"
-    # Add more if known
-
-
-# Nested models
-
-
-class Entity(BaseModel):
-    type: str
-
-
-class Criterion(BaseModel):
-    description: str
-    successRate: Optional[int] = None
-
-
-class ExcludeItem(BaseModel):
-    source: str = Field(default="import")
-    id: str
-
-
-class Relationship(BaseModel):
-    definition: str
-    limit: Optional[float] = None
-
-
-class ScopeItem(BaseModel):
-    source: str = Field(default="import")
-    id: str
-    relationship: Optional[Relationship] = None
-
-
-class Progress(BaseModel):
-    found: int
-    analyzed: int
-    completion: int
-    timeLeft: int
-
-
-class Bounds(BaseModel):
-    min: int
-    max: int
-
-
-class Expected(BaseModel):
-    total: int
-    confidence: str = Field(default="high")  # Use str or Confidence enum
-    bounds: Bounds
-
-
-class Recall(BaseModel):
-    expected: Expected
-    reasoning: str
-
-
-class WebsetSearch(BaseModel):
-    id: str
-    object: str = Field(default="webset_search")
-    status: str = Field(default="created")  # Or use WebsetSearchStatus
-    websetId: str
-    query: str
-    entity: Entity
-    criteria: List[Criterion]
-    count: int
-    behavior: str = Field(default="override")
-    exclude: List[ExcludeItem]
-    scope: List[ScopeItem]
-    progress: Progress
-    recall: Recall
-    metadata: Dict[str, Any] = Field(default_factory=dict)
-    canceledAt: Optional[datetime] = None
-    canceledReason: Optional[str] = Field(default=None)  # Or use CanceledReason
-    createdAt: datetime
-    updatedAt: datetime
-
-
-class ImportEntity(BaseModel):
-    type: str
-
-
-class Import(BaseModel):
-    id: str
-    object: str = Field(default="import")
-    status: str = Field(default="pending")  # Or use ImportStatus
-    format: str = Field(default="csv")  # Or use ImportFormat
-    entity: ImportEntity
-    title: str
-    count: int
-    metadata: Dict[str, Any] = Field(default_factory=dict)
-    failedReason: Optional[str] = Field(default=None)  # Or use FailedReason
-    failedAt: Optional[datetime] = None
-    failedMessage: Optional[str] = None
-    createdAt: datetime
-    updatedAt: datetime
-
-
-class Option(BaseModel):
-    label: str
-
-
-class WebsetEnrichment(BaseModel):
-    id: str
-    object: str = Field(default="webset_enrichment")
-    status: str = Field(default="pending")  # Or use EnrichmentStatus
-    websetId: str
-    title: str
-    description: str
-    format: str = Field(default="text")  # Or use EnrichmentFormat
-    options: List[Option]
-    instructions: str
-    metadata: Dict[str, Any] = Field(default_factory=dict)
-    createdAt: datetime
-    updatedAt: datetime
-
-
-class Cadence(BaseModel):
-    cron: str
-    timezone: str = Field(default="Etc/UTC")
-
-
-class BehaviorConfig(BaseModel):
-    query: Optional[str] = None
-    criteria: Optional[List[Criterion]] = None
-    entity: Optional[Entity] = None
-    count: Optional[int] = None
-    behavior: Optional[str] = Field(default=None)
-
-
-class Behavior(BaseModel):
-    type: str = Field(default="search")  # Or use MonitorBehaviorType
-    config: BehaviorConfig
-
-
-class MonitorRun(BaseModel):
-    id: str
-    object: str = Field(default="monitor_run")
-    status: str = Field(default="created")  # Or use MonitorRunStatus
-    monitorId: str
-    type: str = Field(default="search")
-    completedAt: Optional[datetime] = None
-    failedAt: Optional[datetime] = None
-    failedReason: Optional[str] = None
-    canceledAt: Optional[datetime] = None
-    createdAt: datetime
-    updatedAt: datetime
-
-
-class Monitor(BaseModel):
-    id: str
-    object: str = Field(default="monitor")
-    status: str = Field(default="enabled")  # Or use MonitorStatus
-    websetId: str
-    cadence: Cadence
-    behavior: Behavior
-    lastRun: Optional[MonitorRun] = None
-    nextRunAt: Optional[datetime] = None
-    metadata: Dict[str, Any] = Field(default_factory=dict)
-    createdAt: datetime
-    updatedAt: datetime
-
-
-class Webset(BaseModel):
-    id: str
-    object: str = Field(default="webset")
-    status: WebsetStatus
-    externalId: Optional[str] = None
-    title: Optional[str] = None
-    searches: List[WebsetSearch]
-    imports: List[Import]
-    enrichments: List[WebsetEnrichment]
-    monitors: List[Monitor]
-    streams: List[Any]
-    createdAt: datetime
-    updatedAt: datetime
-    metadata: Dict[str, Any] = Field(default_factory=dict)
-
-
-class ListWebsets(BaseModel):
-    data: List[Webset]
-    hasMore: bool
-    nextCursor: Optional[str] = None

autogpt_platform/backend/backend/blocks/exa/research.py

@@ -0,0 +1,518 @@
+"""
+Exa Research Task Blocks
+
+Provides asynchronous research capabilities that explore the web, gather sources,
+synthesize findings, and return structured results with citations.
+"""
+
+import asyncio
+import time
+from enum import Enum
+from typing import Any, Dict, List, Optional
+
+from pydantic import BaseModel
+
+from backend.sdk import (
+    APIKeyCredentials,
+    Block,
+    BlockCategory,
+    BlockOutput,
+    BlockSchemaInput,
+    BlockSchemaOutput,
+    CredentialsMetaInput,
+    Requests,
+    SchemaField,
+)
+
+from ._config import exa
+
+
+class ResearchModel(str, Enum):
+    """Available research models."""
+
+    FAST = "exa-research-fast"
+    STANDARD = "exa-research"
+    PRO = "exa-research-pro"
+
+
+class ResearchStatus(str, Enum):
+    """Research task status."""
+
+    PENDING = "pending"
+    RUNNING = "running"
+    COMPLETED = "completed"
+    CANCELED = "canceled"
+    FAILED = "failed"
+
+
+class ResearchCostModel(BaseModel):
+    """Cost breakdown for a research request."""
+
+    total: float
+    num_searches: int
+    num_pages: int
+    reasoning_tokens: int
+
+    @classmethod
+    def from_api(cls, data: dict) -> "ResearchCostModel":
+        """Convert API response, rounding fractional counts to integers."""
+        return cls(
+            total=data.get("total", 0.0),
+            num_searches=int(round(data.get("numSearches", 0))),
+            num_pages=int(round(data.get("numPages", 0))),
+            reasoning_tokens=int(round(data.get("reasoningTokens", 0))),
+        )
+
+
+class ResearchOutputModel(BaseModel):
+    """Research output with content and optional structured data."""
+
+    content: str
+    parsed: Optional[Dict[str, Any]] = None
+
+
+class ResearchTaskModel(BaseModel):
+    """Stable output model for research tasks."""
+
+    research_id: str
+    created_at: int
+    model: str
+    instructions: str
+    status: str
+    output_schema: Optional[Dict[str, Any]] = None
+    output: Optional[ResearchOutputModel] = None
+    cost_dollars: Optional[ResearchCostModel] = None
+    finished_at: Optional[int] = None
+    error: Optional[str] = None
+
+    @classmethod
+    def from_api(cls, data: dict) -> "ResearchTaskModel":
+        """Convert API response to our stable model."""
+        output_data = data.get("output")
+        output = None
+        if output_data:
+            output = ResearchOutputModel(
+                content=output_data.get("content", ""),
+                parsed=output_data.get("parsed"),
+            )
+
+        cost_data = data.get("costDollars")
+        cost = None
+        if cost_data:
+            cost = ResearchCostModel.from_api(cost_data)
+
+        return cls(
+            research_id=data.get("researchId", ""),
+            created_at=data.get("createdAt", 0),
+            model=data.get("model", "exa-research"),
+            instructions=data.get("instructions", ""),
+            status=data.get("status", "pending"),
+            output_schema=data.get("outputSchema"),
+            output=output,
+            cost_dollars=cost,
+            finished_at=data.get("finishedAt"),
+            error=data.get("error"),
+        )
+
+
+class ExaCreateResearchBlock(Block):
+    """Create an asynchronous research task that explores the web and synthesizes findings."""
+
+    class Input(BlockSchemaInput):
+        credentials: CredentialsMetaInput = exa.credentials_field(
+            description="The Exa integration requires an API Key."
+        )
+        instructions: str = SchemaField(
+            description="Research instructions - clearly define what information to find, how to conduct research, and desired output format.",
+            placeholder="Research the top 5 AI coding assistants, their features, pricing, and user reviews",
+        )
+        model: ResearchModel = SchemaField(
+            default=ResearchModel.STANDARD,
+            description="Research model: 'fast' for quick results, 'standard' for balanced quality, 'pro' for thorough analysis",
+        )
+        output_schema: Optional[dict] = SchemaField(
+            default=None,
+            description="JSON Schema to enforce structured output. When provided, results are validated and returned as parsed JSON.",
+            advanced=True,
+        )
+        wait_for_completion: bool = SchemaField(
+            default=True,
+            description="Wait for research to complete before returning. Ensures you get results immediately.",
+        )
+        polling_timeout: int = SchemaField(
+            default=600,
+            description="Maximum time to wait for completion in seconds (only if wait_for_completion is True)",
+            advanced=True,
+            ge=1,
+            le=3600,
+        )
+
+    class Output(BlockSchemaOutput):
+        research_id: str = SchemaField(
+            description="Unique identifier for tracking this research request"
+        )
+        status: str = SchemaField(description="Final status of the research")
+        model: str = SchemaField(description="The research model used")
+        instructions: str = SchemaField(
+            description="The research instructions provided"
+        )
+        created_at: int = SchemaField(
+            description="When the research was created (Unix timestamp in ms)"
+        )
+        output_content: Optional[str] = SchemaField(
+            description="Research output as text (only if wait_for_completion was True and completed)"
+        )
+        output_parsed: Optional[dict] = SchemaField(
+            description="Structured JSON output (only if wait_for_completion and outputSchema were provided)"
+        )
+        cost_total: Optional[float] = SchemaField(
+            description="Total cost in USD (only if wait_for_completion was True and completed)"
+        )
+        elapsed_time: Optional[float] = SchemaField(
+            description="Time taken to complete in seconds (only if wait_for_completion was True)"
+        )
+
+    def __init__(self):
+        super().__init__(
+            id="a1f2e3d4-c5b6-4a78-9012-3456789abcde",
+            description="Create research task with optional waiting - explores web and synthesizes findings with citations",
+            categories={BlockCategory.SEARCH, BlockCategory.AI},
+            input_schema=ExaCreateResearchBlock.Input,
+            output_schema=ExaCreateResearchBlock.Output,
+        )
+
+    async def run(
+        self, input_data: Input, *, credentials: APIKeyCredentials, **kwargs
+    ) -> BlockOutput:
+        url = "https://api.exa.ai/research/v1"
+        headers = {
+            "Content-Type": "application/json",
+            "x-api-key": credentials.api_key.get_secret_value(),
+        }
+
+        payload: Dict[str, Any] = {
+            "model": input_data.model.value,
+            "instructions": input_data.instructions,
+        }
+
+        if input_data.output_schema:
+            payload["outputSchema"] = input_data.output_schema
+
+        response = await Requests().post(url, headers=headers, json=payload)
+        data = response.json()
+
+        research_id = data.get("researchId", "")
+
+        if input_data.wait_for_completion:
+            start_time = time.time()
+            get_url = f"https://api.exa.ai/research/v1/{research_id}"
+            get_headers = {"x-api-key": credentials.api_key.get_secret_value()}
+            check_interval = 10
+
+            while time.time() - start_time < input_data.polling_timeout:
+                poll_response = await Requests().get(url=get_url, headers=get_headers)
+                poll_data = poll_response.json()
+
+                status = poll_data.get("status", "")
+
+                if status in ["completed", "failed", "canceled"]:
+                    elapsed = time.time() - start_time
+                    research = ResearchTaskModel.from_api(poll_data)
+
+                    yield "research_id", research.research_id
+                    yield "status", research.status
+                    yield "model", research.model
+                    yield "instructions", research.instructions
+                    yield "created_at", research.created_at
+                    yield "elapsed_time", elapsed
+
+                    if research.output:
+                        yield "output_content", research.output.content
+                        yield "output_parsed", research.output.parsed
+
+                    if research.cost_dollars:
+                        yield "cost_total", research.cost_dollars.total
+                    return
+
+                await asyncio.sleep(check_interval)
+
+            raise ValueError(
+                f"Research did not complete within {input_data.polling_timeout} seconds"
+            )
+        else:
+            yield "research_id", research_id
+            yield "status", data.get("status", "pending")
+            yield "model", data.get("model", input_data.model.value)
+            yield "instructions", data.get("instructions", input_data.instructions)
+            yield "created_at", data.get("createdAt", 0)
+
+
+class ExaGetResearchBlock(Block):
+    """Get the status and results of a research task."""
+
+    class Input(BlockSchemaInput):
+        credentials: CredentialsMetaInput = exa.credentials_field(
+            description="The Exa integration requires an API Key."
+        )
+        research_id: str = SchemaField(
+            description="The ID of the research task to retrieve",
+            placeholder="01jszdfs0052sg4jc552sg4jc5",
+        )
+        include_events: bool = SchemaField(
+            default=False,
+            description="Include detailed event log of research operations",
+            advanced=True,
+        )
+
+    class Output(BlockSchemaOutput):
+        research_id: str = SchemaField(description="The research task identifier")
+        status: str = SchemaField(
+            description="Current status: pending, running, completed, canceled, or failed"
+        )
+        instructions: str = SchemaField(
+            description="The original research instructions"
+        )
+        model: str = SchemaField(description="The research model used")
+        created_at: int = SchemaField(
+            description="When research was created (Unix timestamp in ms)"
+        )
+        finished_at: Optional[int] = SchemaField(
+            description="When research finished (Unix timestamp in ms, if completed/canceled/failed)"
+        )
+        output_content: Optional[str] = SchemaField(
+            description="Research output as text (if completed)"
+        )
+        output_parsed: Optional[dict] = SchemaField(
+            description="Structured JSON output matching outputSchema (if provided and completed)"
+        )
+        cost_total: Optional[float] = SchemaField(
+            description="Total cost in USD (if completed)"
+        )
+        cost_searches: Optional[int] = SchemaField(
+            description="Number of searches performed (if completed)"
+        )
+        cost_pages: Optional[int] = SchemaField(
+            description="Number of pages crawled (if completed)"
+        )
+        cost_reasoning_tokens: Optional[int] = SchemaField(
+            description="AI tokens used for reasoning (if completed)"
+        )
+        error_message: Optional[str] = SchemaField(
+            description="Error message if research failed"
+        )
+        events: Optional[List[dict]] = SchemaField(
+            description="Detailed event log (if include_events was True)"
+        )
+
+    def __init__(self):
+        super().__init__(
+            id="b2e3f4a5-6789-4bcd-9012-3456789abcde",
+            description="Get status and results of a research task",
+            categories={BlockCategory.SEARCH},
+            input_schema=ExaGetResearchBlock.Input,
+            output_schema=ExaGetResearchBlock.Output,
+        )
+
+    async def run(
+        self, input_data: Input, *, credentials: APIKeyCredentials, **kwargs
+    ) -> BlockOutput:
+        url = f"https://api.exa.ai/research/v1/{input_data.research_id}"
+        headers = {
+            "x-api-key": credentials.api_key.get_secret_value(),
+        }
+
+        params = {}
+        if input_data.include_events:
+            params["events"] = "true"
+
+        response = await Requests().get(url, headers=headers, params=params)
+        data = response.json()
+
+        research = ResearchTaskModel.from_api(data)
+
+        yield "research_id", research.research_id
+        yield "status", research.status
+        yield "instructions", research.instructions
+        yield "model", research.model
+        yield "created_at", research.created_at
+        yield "finished_at", research.finished_at
+
+        if research.output:
+            yield "output_content", research.output.content
+            yield "output_parsed", research.output.parsed
+
+        if research.cost_dollars:
+            yield "cost_total", research.cost_dollars.total
+            yield "cost_searches", research.cost_dollars.num_searches
+            yield "cost_pages", research.cost_dollars.num_pages
+            yield "cost_reasoning_tokens", research.cost_dollars.reasoning_tokens
+
+        yield "error_message", research.error
+
+        if input_data.include_events:
+            yield "events", data.get("events", [])
+
+
+class ExaWaitForResearchBlock(Block):
+    """Wait for a research task to complete with progress tracking."""
+
+    class Input(BlockSchemaInput):
+        credentials: CredentialsMetaInput = exa.credentials_field(
+            description="The Exa integration requires an API Key."
+        )
+        research_id: str = SchemaField(
+            description="The ID of the research task to wait for",
+            placeholder="01jszdfs0052sg4jc552sg4jc5",
+        )
+        timeout: int = SchemaField(
+            default=600,
+            description="Maximum time to wait in seconds",
+            ge=1,
+            le=3600,
+        )
+        check_interval: int = SchemaField(
+            default=10,
+            description="Seconds between status checks",
+            advanced=True,
+            ge=1,
+            le=60,
+        )
+
+    class Output(BlockSchemaOutput):
+        research_id: str = SchemaField(description="The research task identifier")
+        final_status: str = SchemaField(description="Final status when polling stopped")
+        output_content: Optional[str] = SchemaField(
+            description="Research output as text (if completed)"
+        )
+        output_parsed: Optional[dict] = SchemaField(
+            description="Structured JSON output (if outputSchema was provided and completed)"
+        )
+        cost_total: Optional[float] = SchemaField(description="Total cost in USD")
+        elapsed_time: float = SchemaField(description="Total time waited in seconds")
+        timed_out: bool = SchemaField(
+            description="Whether polling timed out before completion"
+        )
+
+    def __init__(self):
+        super().__init__(
+            id="c3d4e5f6-7890-4abc-9012-3456789abcde",
+            description="Wait for a research task to complete with configurable timeout",
+            categories={BlockCategory.SEARCH},
+            input_schema=ExaWaitForResearchBlock.Input,
+            output_schema=ExaWaitForResearchBlock.Output,
+        )
+
+    async def run(
+        self, input_data: Input, *, credentials: APIKeyCredentials, **kwargs
+    ) -> BlockOutput:
+        start_time = time.time()
+        url = f"https://api.exa.ai/research/v1/{input_data.research_id}"
+        headers = {
+            "x-api-key": credentials.api_key.get_secret_value(),
+        }
+
+        while time.time() - start_time < input_data.timeout:
+            response = await Requests().get(url, headers=headers)
+            data = response.json()
+
+            status = data.get("status", "")
+
+            if status in ["completed", "failed", "canceled"]:
+                elapsed = time.time() - start_time
+                research = ResearchTaskModel.from_api(data)
+
+                yield "research_id", research.research_id
+                yield "final_status", research.status
+                yield "elapsed_time", elapsed
+                yield "timed_out", False
+
+                if research.output:
+                    yield "output_content", research.output.content
+                    yield "output_parsed", research.output.parsed
+
+                if research.cost_dollars:
+                    yield "cost_total", research.cost_dollars.total
+
+                return
+
+            await asyncio.sleep(input_data.check_interval)
+
+        elapsed = time.time() - start_time
+        response = await Requests().get(url, headers=headers)
+        data = response.json()
+
+        yield "research_id", input_data.research_id
+        yield "final_status", data.get("status", "unknown")
+        yield "elapsed_time", elapsed
+        yield "timed_out", True
+
+
+class ExaListResearchBlock(Block):
+    """List all research tasks with pagination support."""
+
+    class Input(BlockSchemaInput):
+        credentials: CredentialsMetaInput = exa.credentials_field(
+            description="The Exa integration requires an API Key."
+        )
+        cursor: Optional[str] = SchemaField(
+            default=None,
+            description="Cursor for pagination through results",
+            advanced=True,
+        )
+        limit: int = SchemaField(
+            default=10,
+            description="Number of research tasks to return (1-50)",
+            ge=1,
+            le=50,
+            advanced=True,
+        )
+
+    class Output(BlockSchemaOutput):
+        research_tasks: List[ResearchTaskModel] = SchemaField(
+            description="List of research tasks ordered by creation time (newest first)"
+        )
+        research_task: ResearchTaskModel = SchemaField(
+            description="Individual research task (yielded for each task)"
+        )
+        has_more: bool = SchemaField(
+            description="Whether there are more tasks to paginate through"
+        )
+        next_cursor: Optional[str] = SchemaField(
+            description="Cursor for the next page of results"
+        )
+
+    def __init__(self):
+        super().__init__(
+            id="d4e5f6a7-8901-4bcd-9012-3456789abcde",
+            description="List all research tasks with pagination support",
+            categories={BlockCategory.SEARCH},
+            input_schema=ExaListResearchBlock.Input,
+            output_schema=ExaListResearchBlock.Output,
+        )
+
+    async def run(
+        self, input_data: Input, *, credentials: APIKeyCredentials, **kwargs
+    ) -> BlockOutput:
+        url = "https://api.exa.ai/research/v1"
+        headers = {
+            "x-api-key": credentials.api_key.get_secret_value(),
+        }
+
+        params: Dict[str, Any] = {
+            "limit": input_data.limit,
+        }
+        if input_data.cursor:
+            params["cursor"] = input_data.cursor
+
+        response = await Requests().get(url, headers=headers, params=params)
+        data = response.json()
+
+        tasks = [ResearchTaskModel.from_api(task) for task in data.get("data", [])]
+
+        yield "research_tasks", tasks
+
+        for task in tasks:
+            yield "research_task", task
+
+        yield "has_more", data.get("hasMore", False)
+        yield "next_cursor", data.get("nextCursor")

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

@@ -1,32 +1,66 @@
 from datetime import datetime
+from enum import Enum
+from typing import Optional
+
+from exa_py import AsyncExa
 
 from backend.sdk import (
     APIKeyCredentials,
     Block,
     BlockCategory,
     BlockOutput,
-    BlockSchema,
+    BlockSchemaInput,
+    BlockSchemaOutput,
     CredentialsMetaInput,
-    Requests,
     SchemaField,
 )
 
 from ._config import exa
-from .helpers import ContentSettings
+from .helpers import (
+    ContentSettings,
+    CostDollars,
+    ExaSearchResults,
+    process_contents_settings,
+)
+
+
+class ExaSearchTypes(Enum):
+    KEYWORD = "keyword"
+    NEURAL = "neural"
+    FAST = "fast"
+    AUTO = "auto"
+
+
+class ExaSearchCategories(Enum):
+    COMPANY = "company"
+    RESEARCH_PAPER = "research paper"
+    NEWS = "news"
+    PDF = "pdf"
+    GITHUB = "github"
+    TWEET = "tweet"
+    PERSONAL_SITE = "personal site"
+    LINKEDIN_PROFILE = "linkedin profile"
+    FINANCIAL_REPORT = "financial report"
 
 
 class ExaSearchBlock(Block):
-    class Input(BlockSchema):
+    class Input(BlockSchemaInput):
         credentials: CredentialsMetaInput = exa.credentials_field(
             description="The Exa integration requires an API Key."
         )
         query: str = SchemaField(description="The search query")
-        use_auto_prompt: bool = SchemaField(
-            description="Whether to use autoprompt", default=True, advanced=True
+        type: ExaSearchTypes = SchemaField(
+            description="Type of search", default=ExaSearchTypes.AUTO, advanced=True
         )
-        type: str = SchemaField(description="Type of search", default="", advanced=True)
-        category: str = SchemaField(
-            description="Category to search within", default="", advanced=True
+        category: ExaSearchCategories | None = SchemaField(
+            description="Category to search within: company, research paper, news, pdf, github, tweet, personal site, linkedin profile, financial report",
+            default=None,
+            advanced=True,
+        )
+        user_location: str | None = SchemaField(
+            description="The two-letter ISO country code of the user (e.g., 'US')",
+            default=None,
+            advanced=True,
         )
         number_of_results: int = SchemaField(
             description="Number of results to return", default=10, advanced=True
@@ -39,17 +73,17 @@ class ExaSearchBlock(Block):
             default_factory=list,
             advanced=True,
         )
-        start_crawl_date: datetime = SchemaField(
-            description="Start date for crawled content"
+        start_crawl_date: datetime | None = SchemaField(
+            description="Start date for crawled content", advanced=True, default=None
         )
-        end_crawl_date: datetime = SchemaField(
-            description="End date for crawled content"
+        end_crawl_date: datetime | None = SchemaField(
+            description="End date for crawled content", advanced=True, default=None
         )
-        start_published_date: datetime = SchemaField(
-            description="Start date for published content"
+        start_published_date: datetime | None = SchemaField(
+            description="Start date for published content", advanced=True, default=None
         )
-        end_published_date: datetime = SchemaField(
-            description="End date for published content"
+        end_published_date: datetime | None = SchemaField(
+            description="End date for published content", advanced=True, default=None
         )
         include_text: list[str] = SchemaField(
             description="Text patterns to include", default_factory=list, advanced=True
@@ -62,14 +96,30 @@ class ExaSearchBlock(Block):
             default=ContentSettings(),
             advanced=True,
         )
+        moderation: bool = SchemaField(
+            description="Enable content moderation to filter unsafe content from search results",
+            default=False,
+            advanced=True,
+        )
 
-    class Output(BlockSchema):
-        results: list = SchemaField(
-            description="List of search results", default_factory=list
+    class Output(BlockSchemaOutput):
+        results: list[ExaSearchResults] = SchemaField(
+            description="List of search results"
         )
-        error: str = SchemaField(
-            description="Error message if the request failed",
+        result: ExaSearchResults = SchemaField(description="Single search result")
+        context: str = SchemaField(
+            description="A formatted string of the search results ready for LLMs."
         )
+        search_type: str = SchemaField(
+            description="For auto searches, indicates which search type was selected."
+        )
+        resolved_search_type: str = SchemaField(
+            description="The search type that was actually used for this request (neural or keyword)"
+        )
+        cost_dollars: Optional[CostDollars] = SchemaField(
+            description="Cost breakdown for the request"
+        )
+        error: str = SchemaField(description="Error message if the request failed")
 
     def __init__(self):
         super().__init__(
@@ -83,51 +133,76 @@ class ExaSearchBlock(Block):
     async def run(
         self, input_data: Input, *, credentials: APIKeyCredentials, **kwargs
     ) -> BlockOutput:
-        url = "https://api.exa.ai/search"
-        headers = {
-            "Content-Type": "application/json",
-            "x-api-key": credentials.api_key.get_secret_value(),
-        }
-
-        payload = {
+        sdk_kwargs = {
             "query": input_data.query,
-            "useAutoprompt": input_data.use_auto_prompt,
-            "numResults": input_data.number_of_results,
-            "contents": input_data.contents.model_dump(),
+            "num_results": input_data.number_of_results,
         }
 
-        date_field_mapping = {
-            "start_crawl_date": "startCrawlDate",
-            "end_crawl_date": "endCrawlDate",
-            "start_published_date": "startPublishedDate",
-            "end_published_date": "endPublishedDate",
-        }
+        if input_data.type:
+            sdk_kwargs["type"] = input_data.type.value
 
-        # Add dates if they exist
-        for input_field, api_field in date_field_mapping.items():
-            value = getattr(input_data, input_field, None)
-            if value:
-                payload[api_field] = value.strftime("%Y-%m-%dT%H:%M:%S.000Z")
+        if input_data.category:
+            sdk_kwargs["category"] = input_data.category.value
 
-        optional_field_mapping = {
-            "type": "type",
-            "category": "category",
-            "include_domains": "includeDomains",
-            "exclude_domains": "excludeDomains",
-            "include_text": "includeText",
-            "exclude_text": "excludeText",
-        }
+        if input_data.user_location:
+            sdk_kwargs["user_location"] = input_data.user_location
 
-        # Add other fields
-        for input_field, api_field in optional_field_mapping.items():
-            value = getattr(input_data, input_field)
-            if value:  # Only add non-empty values
-                payload[api_field] = value
+        # Handle domains
+        if input_data.include_domains:
+            sdk_kwargs["include_domains"] = input_data.include_domains
+        if input_data.exclude_domains:
+            sdk_kwargs["exclude_domains"] = input_data.exclude_domains
 
-        try:
-            response = await Requests().post(url, headers=headers, json=payload)
-            data = response.json()
-            # Extract just the results array from the response
-            yield "results", data.get("results", [])
-        except Exception as e:
-            yield "error", str(e)
+        # Handle dates
+        if input_data.start_crawl_date:
+            sdk_kwargs["start_crawl_date"] = input_data.start_crawl_date.isoformat()
+        if input_data.end_crawl_date:
+            sdk_kwargs["end_crawl_date"] = input_data.end_crawl_date.isoformat()
+        if input_data.start_published_date:
+            sdk_kwargs["start_published_date"] = (
+                input_data.start_published_date.isoformat()
+            )
+        if input_data.end_published_date:
+            sdk_kwargs["end_published_date"] = input_data.end_published_date.isoformat()
+
+        # Handle text filters
+        if input_data.include_text:
+            sdk_kwargs["include_text"] = input_data.include_text
+        if input_data.exclude_text:
+            sdk_kwargs["exclude_text"] = input_data.exclude_text
+
+        if input_data.moderation:
+            sdk_kwargs["moderation"] = input_data.moderation
+
+        # heck if we need to use search_and_contents
+        content_settings = process_contents_settings(input_data.contents)
+
+        aexa = AsyncExa(api_key=credentials.api_key.get_secret_value())
+
+        if content_settings:
+            sdk_kwargs["text"] = content_settings.get("text", False)
+            if "highlights" in content_settings:
+                sdk_kwargs["highlights"] = content_settings["highlights"]
+            if "summary" in content_settings:
+                sdk_kwargs["summary"] = content_settings["summary"]
+            response = await aexa.search_and_contents(**sdk_kwargs)
+        else:
+            response = await aexa.search(**sdk_kwargs)
+
+        converted_results = [
+            ExaSearchResults.from_sdk(sdk_result)
+            for sdk_result in response.results or []
+        ]
+
+        yield "results", converted_results
+        for result in converted_results:
+            yield "result", result
+
+        if response.context:
+            yield "context", response.context
+
+        if response.resolved_search_type:
+            yield "resolved_search_type", response.resolved_search_type
+
+        if response.cost_dollars:
+            yield "cost_dollars", response.cost_dollars

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

@@ -1,23 +1,30 @@
 from datetime import datetime
-from typing import Any
+from typing import Optional
+
+from exa_py import AsyncExa
 
 from backend.sdk import (
     APIKeyCredentials,
     Block,
     BlockCategory,
     BlockOutput,
-    BlockSchema,
+    BlockSchemaInput,
+    BlockSchemaOutput,
     CredentialsMetaInput,
-    Requests,
     SchemaField,
 )
 
 from ._config import exa
-from .helpers import ContentSettings
+from .helpers import (
+    ContentSettings,
+    CostDollars,
+    ExaSearchResults,
+    process_contents_settings,
+)
 
 
 class ExaFindSimilarBlock(Block):
-    class Input(BlockSchema):
+    class Input(BlockSchemaInput):
         credentials: CredentialsMetaInput = exa.credentials_field(
             description="The Exa integration requires an API Key."
         )
@@ -28,7 +35,7 @@ class ExaFindSimilarBlock(Block):
             description="Number of results to return", default=10, advanced=True
         )
         include_domains: list[str] = SchemaField(
-            description="Domains to include in search",
+            description="List of domains to include in the search. If specified, results will only come from these domains.",
             default_factory=list,
             advanced=True,
         )
@@ -37,17 +44,17 @@ class ExaFindSimilarBlock(Block):
             default_factory=list,
             advanced=True,
         )
-        start_crawl_date: datetime = SchemaField(
-            description="Start date for crawled content"
+        start_crawl_date: Optional[datetime] = SchemaField(
+            description="Start date for crawled content", advanced=True, default=None
         )
-        end_crawl_date: datetime = SchemaField(
-            description="End date for crawled content"
+        end_crawl_date: Optional[datetime] = SchemaField(
+            description="End date for crawled content", advanced=True, default=None
         )
-        start_published_date: datetime = SchemaField(
-            description="Start date for published content"
+        start_published_date: Optional[datetime] = SchemaField(
+            description="Start date for published content", advanced=True, default=None
         )
-        end_published_date: datetime = SchemaField(
-            description="End date for published content"
+        end_published_date: Optional[datetime] = SchemaField(
+            description="End date for published content", advanced=True, default=None
         )
         include_text: list[str] = SchemaField(
             description="Text patterns to include (max 1 string, up to 5 words)",
@@ -64,15 +71,27 @@ class ExaFindSimilarBlock(Block):
             default=ContentSettings(),
             advanced=True,
         )
+        moderation: bool = SchemaField(
+            description="Enable content moderation to filter unsafe content from search results",
+            default=False,
+            advanced=True,
+        )
 
-    class Output(BlockSchema):
-        results: list[Any] = SchemaField(
-            description="List of similar documents with title, URL, published date, author, and score",
-            default_factory=list,
+    class Output(BlockSchemaOutput):
+        results: list[ExaSearchResults] = SchemaField(
+            description="List of similar documents with metadata and content"
         )
-        error: str = SchemaField(
-            description="Error message if the request failed", default=""
+        result: ExaSearchResults = SchemaField(
+            description="Single similar document result"
         )
+        context: str = SchemaField(
+            description="A formatted string of the results ready for LLMs."
+        )
+        request_id: str = SchemaField(description="Unique identifier for the request")
+        cost_dollars: Optional[CostDollars] = SchemaField(
+            description="Cost breakdown for the request"
+        )
+        error: str = SchemaField(description="Error message if the request failed")
 
     def __init__(self):
         super().__init__(
@@ -86,47 +105,65 @@ class ExaFindSimilarBlock(Block):
     async def run(
         self, input_data: Input, *, credentials: APIKeyCredentials, **kwargs
     ) -> BlockOutput:
-        url = "https://api.exa.ai/findSimilar"
-        headers = {
-            "Content-Type": "application/json",
-            "x-api-key": credentials.api_key.get_secret_value(),
-        }
-
-        payload = {
+        sdk_kwargs = {
             "url": input_data.url,
-            "numResults": input_data.number_of_results,
-            "contents": input_data.contents.model_dump(),
+            "num_results": input_data.number_of_results,
         }
 
-        optional_field_mapping = {
-            "include_domains": "includeDomains",
-            "exclude_domains": "excludeDomains",
-            "include_text": "includeText",
-            "exclude_text": "excludeText",
-        }
+        # Handle domains
+        if input_data.include_domains:
+            sdk_kwargs["include_domains"] = input_data.include_domains
+        if input_data.exclude_domains:
+            sdk_kwargs["exclude_domains"] = input_data.exclude_domains
 
-        # Add optional fields if they have values
-        for input_field, api_field in optional_field_mapping.items():
-            value = getattr(input_data, input_field)
-            if value:  # Only add non-empty values
-                payload[api_field] = value
+        # Handle dates
+        if input_data.start_crawl_date:
+            sdk_kwargs["start_crawl_date"] = input_data.start_crawl_date.isoformat()
+        if input_data.end_crawl_date:
+            sdk_kwargs["end_crawl_date"] = input_data.end_crawl_date.isoformat()
+        if input_data.start_published_date:
+            sdk_kwargs["start_published_date"] = (
+                input_data.start_published_date.isoformat()
+            )
+        if input_data.end_published_date:
+            sdk_kwargs["end_published_date"] = input_data.end_published_date.isoformat()
 
-        date_field_mapping = {
-            "start_crawl_date": "startCrawlDate",
-            "end_crawl_date": "endCrawlDate",
-            "start_published_date": "startPublishedDate",
-            "end_published_date": "endPublishedDate",
-        }
+        # Handle text filters
+        if input_data.include_text:
+            sdk_kwargs["include_text"] = input_data.include_text
+        if input_data.exclude_text:
+            sdk_kwargs["exclude_text"] = input_data.exclude_text
 
-        # Add dates if they exist
-        for input_field, api_field in date_field_mapping.items():
-            value = getattr(input_data, input_field, None)
-            if value:
-                payload[api_field] = value.strftime("%Y-%m-%dT%H:%M:%S.000Z")
+        if input_data.moderation:
+            sdk_kwargs["moderation"] = input_data.moderation
 
-        try:
-            response = await Requests().post(url, headers=headers, json=payload)
-            data = response.json()
-            yield "results", data.get("results", [])
-        except Exception as e:
-            yield "error", str(e)
+        # check if we need to use find_similar_and_contents
+        content_settings = process_contents_settings(input_data.contents)
+
+        aexa = AsyncExa(api_key=credentials.api_key.get_secret_value())
+
+        if content_settings:
+            # Use find_similar_and_contents when contents are requested
+            sdk_kwargs["text"] = content_settings.get("text", False)
+            if "highlights" in content_settings:
+                sdk_kwargs["highlights"] = content_settings["highlights"]
+            if "summary" in content_settings:
+                sdk_kwargs["summary"] = content_settings["summary"]
+            response = await aexa.find_similar_and_contents(**sdk_kwargs)
+        else:
+            response = await aexa.find_similar(**sdk_kwargs)
+
+        converted_results = [
+            ExaSearchResults.from_sdk(sdk_result)
+            for sdk_result in response.results or []
+        ]
+
+        yield "results", converted_results
+        for result in converted_results:
+            yield "result", result
+
+        if response.context:
+            yield "context", response.context
+
+        if response.cost_dollars:
+            yield "cost_dollars", response.cost_dollars

autogpt_platform/backend/backend/blocks/exa/webhook_blocks.py

@@ -9,7 +9,8 @@ from backend.sdk import (
     Block,
     BlockCategory,
     BlockOutput,
-    BlockSchema,
+    BlockSchemaInput,
+    BlockSchemaOutput,
     BlockType,
     BlockWebhookConfig,
     CredentialsMetaInput,
@@ -84,7 +85,7 @@ class ExaWebsetWebhookBlock(Block):
     including creation, updates, searches, and exports.
     """
 
-    class Input(BlockSchema):
+    class Input(BlockSchemaInput):
         credentials: CredentialsMetaInput = exa.credentials_field(
             description="Exa API credentials for webhook management"
         )
@@ -104,7 +105,7 @@ class ExaWebsetWebhookBlock(Block):
             description="Webhook payload data", default={}, hidden=True
         )
 
-    class Output(BlockSchema):
+    class Output(BlockSchemaOutput):
         event_type: str = SchemaField(description="Type of event that occurred")
         event_id: str = SchemaField(description="Unique identifier for this event")
         webset_id: str = SchemaField(description="ID of the affected webset")
@@ -131,45 +132,33 @@ class ExaWebsetWebhookBlock(Block):
 
     async def run(self, input_data: Input, **kwargs) -> BlockOutput:
         """Process incoming Exa webhook payload."""
-        try:
-            payload = input_data.payload
+        payload = input_data.payload
 
-            # Extract event details
-            event_type = payload.get("eventType", "unknown")
-            event_id = payload.get("eventId", "")
+        # Extract event details
+        event_type = payload.get("eventType", "unknown")
+        event_id = payload.get("eventId", "")
 
-            # Get webset ID from payload or input
-            webset_id = payload.get("websetId", input_data.webset_id)
+        # Get webset ID from payload or input
+        webset_id = payload.get("websetId", input_data.webset_id)
 
-            # Check if we should process this event based on filter
-            should_process = self._should_process_event(
-                event_type, input_data.event_filter
-            )
+        # Check if we should process this event based on filter
+        should_process = self._should_process_event(event_type, input_data.event_filter)
 
-            if not should_process:
-                # Skip events that don't match our filter
-                return
+        if not should_process:
+            # Skip events that don't match our filter
+            return
 
-            # Extract event data
-            event_data = payload.get("data", {})
-            timestamp = payload.get("occurredAt", payload.get("createdAt", ""))
-            metadata = payload.get("metadata", {})
+        # Extract event data
+        event_data = payload.get("data", {})
+        timestamp = payload.get("occurredAt", payload.get("createdAt", ""))
+        metadata = payload.get("metadata", {})
 
-            yield "event_type", event_type
-            yield "event_id", event_id
-            yield "webset_id", webset_id
-            yield "data", event_data
-            yield "timestamp", timestamp
-            yield "metadata", metadata
-
-        except Exception as e:
-            # Handle errors gracefully
-            yield "event_type", "error"
-            yield "event_id", ""
-            yield "webset_id", input_data.webset_id
-            yield "data", {"error": str(e)}
-            yield "timestamp", ""
-            yield "metadata", {}
+        yield "event_type", event_type
+        yield "event_id", event_id
+        yield "webset_id", webset_id
+        yield "data", event_data
+        yield "timestamp", timestamp
+        yield "metadata", metadata
 
     def _should_process_event(
         self, event_type: str, event_filter: WebsetEventFilter

autogpt_platform/backend/backend/blocks/exa/websets_enrichment.py

@@ -0,0 +1,554 @@
+"""
+Exa Websets Enrichment Management Blocks
+
+This module provides blocks for creating and managing enrichments on webset items,
+allowing extraction of additional structured data from existing items.
+"""
+
+from enum import Enum
+from typing import Any, Dict, List, Optional
+
+from exa_py import AsyncExa
+from exa_py.websets.types import WebsetEnrichment as SdkWebsetEnrichment
+from pydantic import BaseModel
+
+from backend.sdk import (
+    APIKeyCredentials,
+    Block,
+    BlockCategory,
+    BlockOutput,
+    BlockSchemaInput,
+    BlockSchemaOutput,
+    CredentialsMetaInput,
+    Requests,
+    SchemaField,
+)
+
+from ._config import exa
+
+
+# Mirrored model for stability
+class WebsetEnrichmentModel(BaseModel):
+    """Stable output model mirroring SDK WebsetEnrichment."""
+
+    id: str
+    webset_id: str
+    status: str
+    title: Optional[str]
+    description: str
+    format: str
+    options: List[str]
+    instructions: Optional[str]
+    metadata: Dict[str, Any]
+    created_at: str
+    updated_at: str
+
+    @classmethod
+    def from_sdk(cls, enrichment: SdkWebsetEnrichment) -> "WebsetEnrichmentModel":
+        """Convert SDK WebsetEnrichment to our stable model."""
+        # Extract options
+        options_list = []
+        if enrichment.options:
+            for option in enrichment.options:
+                option_dict = option.model_dump(by_alias=True)
+                options_list.append(option_dict.get("label", ""))
+
+        return cls(
+            id=enrichment.id,
+            webset_id=enrichment.webset_id,
+            status=(
+                enrichment.status.value
+                if hasattr(enrichment.status, "value")
+                else str(enrichment.status)
+            ),
+            title=enrichment.title,
+            description=enrichment.description,
+            format=(
+                enrichment.format.value
+                if enrichment.format and hasattr(enrichment.format, "value")
+                else "text"
+            ),
+            options=options_list,
+            instructions=enrichment.instructions,
+            metadata=enrichment.metadata if enrichment.metadata else {},
+            created_at=(
+                enrichment.created_at.isoformat() if enrichment.created_at else ""
+            ),
+            updated_at=(
+                enrichment.updated_at.isoformat() if enrichment.updated_at else ""
+            ),
+        )
+
+
+class EnrichmentFormat(str, Enum):
+    """Format types for enrichment responses."""
+
+    TEXT = "text"  # Free text response
+    DATE = "date"  # Date/datetime format
+    NUMBER = "number"  # Numeric value
+    OPTIONS = "options"  # Multiple choice from provided options
+    EMAIL = "email"  # Email address format
+    PHONE = "phone"  # Phone number format
+
+
+class ExaCreateEnrichmentBlock(Block):
+    """Create a new enrichment to extract additional data from webset items."""
+
+    class Input(BlockSchemaInput):
+        credentials: CredentialsMetaInput = exa.credentials_field(
+            description="The Exa integration requires an API Key."
+        )
+        webset_id: str = SchemaField(
+            description="The ID or external ID of the Webset",
+            placeholder="webset-id-or-external-id",
+        )
+        description: str = SchemaField(
+            description="What data to extract from each item",
+            placeholder="Extract the company's main product or service offering",
+        )
+        title: Optional[str] = SchemaField(
+            default=None,
+            description="Short title for this enrichment (auto-generated if not provided)",
+            placeholder="Main Product",
+        )
+        format: EnrichmentFormat = SchemaField(
+            default=EnrichmentFormat.TEXT,
+            description="Expected format of the extracted data",
+        )
+        options: list[str] = SchemaField(
+            default_factory=list,
+            description="Available options when format is 'options'",
+            placeholder='["B2B", "B2C", "Both", "Unknown"]',
+            advanced=True,
+        )
+        apply_to_existing: bool = SchemaField(
+            default=True,
+            description="Apply this enrichment to existing items in the webset",
+        )
+        metadata: Optional[dict] = SchemaField(
+            default=None,
+            description="Metadata to attach to the enrichment",
+            advanced=True,
+        )
+        wait_for_completion: bool = SchemaField(
+            default=False,
+            description="Wait for the enrichment to complete on existing items",
+        )
+        polling_timeout: int = SchemaField(
+            default=300,
+            description="Maximum time to wait for completion in seconds",
+            advanced=True,
+            ge=1,
+            le=600,
+        )
+
+    class Output(BlockSchemaOutput):
+        enrichment_id: str = SchemaField(
+            description="The unique identifier for the created enrichment"
+        )
+        webset_id: str = SchemaField(
+            description="The webset this enrichment belongs to"
+        )
+        status: str = SchemaField(description="Current status of the enrichment")
+        title: str = SchemaField(description="Title of the enrichment")
+        description: str = SchemaField(
+            description="Description of what data is extracted"
+        )
+        format: str = SchemaField(description="Format of the extracted data")
+        instructions: str = SchemaField(
+            description="Generated instructions for the enrichment"
+        )
+        items_enriched: Optional[int] = SchemaField(
+            description="Number of items enriched (if wait_for_completion was True)"
+        )
+        completion_time: Optional[float] = SchemaField(
+            description="Time taken to complete in seconds (if wait_for_completion was True)"
+        )
+
+    def __init__(self):
+        super().__init__(
+            id="71146ae8-0cb1-4a15-8cde-eae30de71cb6",
+            description="Create enrichments to extract additional structured data from webset items",
+            categories={BlockCategory.AI, BlockCategory.SEARCH},
+            input_schema=ExaCreateEnrichmentBlock.Input,
+            output_schema=ExaCreateEnrichmentBlock.Output,
+        )
+
+    async def run(
+        self, input_data: Input, *, credentials: APIKeyCredentials, **kwargs
+    ) -> BlockOutput:
+        import time
+
+        # Build the payload
+        payload: dict[str, Any] = {
+            "description": input_data.description,
+            "format": input_data.format.value,
+        }
+
+        # Add title if provided
+        if input_data.title:
+            payload["title"] = input_data.title
+
+        # Add options for 'options' format
+        if input_data.format == EnrichmentFormat.OPTIONS and input_data.options:
+            payload["options"] = [{"label": opt} for opt in input_data.options]
+
+        # Add metadata if provided
+        if input_data.metadata:
+            payload["metadata"] = input_data.metadata
+
+        start_time = time.time()
+
+        # Use AsyncExa SDK
+        aexa = AsyncExa(api_key=credentials.api_key.get_secret_value())
+
+        sdk_enrichment = aexa.websets.enrichments.create(
+            webset_id=input_data.webset_id, params=payload
+        )
+
+        enrichment_id = sdk_enrichment.id
+        status = (
+            sdk_enrichment.status.value
+            if hasattr(sdk_enrichment.status, "value")
+            else str(sdk_enrichment.status)
+        )
+
+        # If wait_for_completion is True and apply_to_existing is True, poll for completion
+        if input_data.wait_for_completion and input_data.apply_to_existing:
+            import asyncio
+
+            poll_interval = 5
+            max_interval = 30
+            poll_start = time.time()
+            items_enriched = 0
+
+            while time.time() - poll_start < input_data.polling_timeout:
+                current_enrich = aexa.websets.enrichments.get(
+                    webset_id=input_data.webset_id, id=enrichment_id
+                )
+                current_status = (
+                    current_enrich.status.value
+                    if hasattr(current_enrich.status, "value")
+                    else str(current_enrich.status)
+                )
+
+                if current_status in ["completed", "failed", "cancelled"]:
+                    # Estimate items from webset searches
+                    webset = aexa.websets.get(id=input_data.webset_id)
+                    if webset.searches:
+                        for search in webset.searches:
+                            if search.progress:
+                                items_enriched += search.progress.found
+                    completion_time = time.time() - start_time
+
+                    yield "enrichment_id", enrichment_id
+                    yield "webset_id", input_data.webset_id
+                    yield "status", current_status
+                    yield "title", sdk_enrichment.title
+                    yield "description", input_data.description
+                    yield "format", input_data.format.value
+                    yield "instructions", sdk_enrichment.instructions
+                    yield "items_enriched", items_enriched
+                    yield "completion_time", completion_time
+                    return
+
+                await asyncio.sleep(poll_interval)
+                poll_interval = min(poll_interval * 1.5, max_interval)
+
+            # Timeout
+            completion_time = time.time() - start_time
+            yield "enrichment_id", enrichment_id
+            yield "webset_id", input_data.webset_id
+            yield "status", status
+            yield "title", sdk_enrichment.title
+            yield "description", input_data.description
+            yield "format", input_data.format.value
+            yield "instructions", sdk_enrichment.instructions
+            yield "items_enriched", 0
+            yield "completion_time", completion_time
+        else:
+            yield "enrichment_id", enrichment_id
+            yield "webset_id", input_data.webset_id
+            yield "status", status
+            yield "title", sdk_enrichment.title
+            yield "description", input_data.description
+            yield "format", input_data.format.value
+            yield "instructions", sdk_enrichment.instructions
+
+
+class ExaGetEnrichmentBlock(Block):
+    """Get the status and details of a webset enrichment."""
+
+    class Input(BlockSchemaInput):
+        credentials: CredentialsMetaInput = exa.credentials_field(
+            description="The Exa integration requires an API Key."
+        )
+        webset_id: str = SchemaField(
+            description="The ID or external ID of the Webset",
+            placeholder="webset-id-or-external-id",
+        )
+        enrichment_id: str = SchemaField(
+            description="The ID of the enrichment to retrieve",
+            placeholder="enrichment-id",
+        )
+
+    class Output(BlockSchemaOutput):
+        enrichment_id: str = SchemaField(
+            description="The unique identifier for the enrichment"
+        )
+        status: str = SchemaField(description="Current status of the enrichment")
+        title: str = SchemaField(description="Title of the enrichment")
+        description: str = SchemaField(
+            description="Description of what data is extracted"
+        )
+        format: str = SchemaField(description="Format of the extracted data")
+        options: list[str] = SchemaField(
+            description="Available options (for 'options' format)"
+        )
+        instructions: str = SchemaField(
+            description="Generated instructions for the enrichment"
+        )
+        created_at: str = SchemaField(description="When the enrichment was created")
+        updated_at: str = SchemaField(
+            description="When the enrichment was last updated"
+        )
+        metadata: dict = SchemaField(description="Metadata attached to the enrichment")
+
+    def __init__(self):
+        super().__init__(
+            id="b8c9d0e1-f2a3-4567-89ab-cdef01234567",
+            description="Get the status and details of a webset enrichment",
+            categories={BlockCategory.SEARCH},
+            input_schema=ExaGetEnrichmentBlock.Input,
+            output_schema=ExaGetEnrichmentBlock.Output,
+        )
+
+    async def run(
+        self, input_data: Input, *, credentials: APIKeyCredentials, **kwargs
+    ) -> BlockOutput:
+        # Use AsyncExa SDK
+        aexa = AsyncExa(api_key=credentials.api_key.get_secret_value())
+
+        sdk_enrichment = aexa.websets.enrichments.get(
+            webset_id=input_data.webset_id, id=input_data.enrichment_id
+        )
+
+        enrichment = WebsetEnrichmentModel.from_sdk(sdk_enrichment)
+
+        yield "enrichment_id", enrichment.id
+        yield "status", enrichment.status
+        yield "title", enrichment.title
+        yield "description", enrichment.description
+        yield "format", enrichment.format
+        yield "options", enrichment.options
+        yield "instructions", enrichment.instructions
+        yield "created_at", enrichment.created_at
+        yield "updated_at", enrichment.updated_at
+        yield "metadata", enrichment.metadata
+
+
+class ExaUpdateEnrichmentBlock(Block):
+    """Update an existing enrichment configuration."""
+
+    class Input(BlockSchemaInput):
+        credentials: CredentialsMetaInput = exa.credentials_field(
+            description="The Exa integration requires an API Key."
+        )
+        webset_id: str = SchemaField(
+            description="The ID or external ID of the Webset",
+            placeholder="webset-id-or-external-id",
+        )
+        enrichment_id: str = SchemaField(
+            description="The ID of the enrichment to update",
+            placeholder="enrichment-id",
+        )
+        description: Optional[str] = SchemaField(
+            default=None,
+            description="New description for what data to extract",
+        )
+        format: Optional[EnrichmentFormat] = SchemaField(
+            default=None,
+            description="New format for the extracted data",
+        )
+        options: Optional[list[str]] = SchemaField(
+            default=None,
+            description="New options when format is 'options'",
+        )
+        metadata: Optional[dict] = SchemaField(
+            default=None,
+            description="New metadata to attach to the enrichment",
+        )
+
+    class Output(BlockSchemaOutput):
+        enrichment_id: str = SchemaField(
+            description="The unique identifier for the enrichment"
+        )
+        status: str = SchemaField(description="Current status of the enrichment")
+        title: str = SchemaField(description="Title of the enrichment")
+        description: str = SchemaField(description="Updated description")
+        format: str = SchemaField(description="Updated format")
+        success: str = SchemaField(description="Whether the update was successful")
+
+    def __init__(self):
+        super().__init__(
+            id="c8d5c5fb-9684-4a29-bd2a-5b38d71776c9",
+            description="Update an existing enrichment configuration",
+            categories={BlockCategory.SEARCH},
+            input_schema=ExaUpdateEnrichmentBlock.Input,
+            output_schema=ExaUpdateEnrichmentBlock.Output,
+        )
+
+    async def run(
+        self, input_data: Input, *, credentials: APIKeyCredentials, **kwargs
+    ) -> BlockOutput:
+        url = f"https://api.exa.ai/websets/v0/websets/{input_data.webset_id}/enrichments/{input_data.enrichment_id}"
+        headers = {
+            "Content-Type": "application/json",
+            "x-api-key": credentials.api_key.get_secret_value(),
+        }
+
+        # Build the update payload
+        payload = {}
+
+        if input_data.description is not None:
+            payload["description"] = input_data.description
+
+        if input_data.format is not None:
+            payload["format"] = input_data.format.value
+
+        if input_data.options is not None:
+            payload["options"] = [{"label": opt} for opt in input_data.options]
+
+        if input_data.metadata is not None:
+            payload["metadata"] = input_data.metadata
+
+        try:
+            response = await Requests().patch(url, headers=headers, json=payload)
+            data = response.json()
+
+            yield "enrichment_id", data.get("id", "")
+            yield "status", data.get("status", "")
+            yield "title", data.get("title", "")
+            yield "description", data.get("description", "")
+            yield "format", data.get("format", "")
+            yield "success", "true"
+
+        except ValueError as e:
+            # Re-raise user input validation errors
+            raise ValueError(f"Failed to update enrichment: {e}") from e
+        # Let all other exceptions propagate naturally
+
+
+class ExaDeleteEnrichmentBlock(Block):
+    """Delete an enrichment from a webset."""
+
+    class Input(BlockSchemaInput):
+        credentials: CredentialsMetaInput = exa.credentials_field(
+            description="The Exa integration requires an API Key."
+        )
+        webset_id: str = SchemaField(
+            description="The ID or external ID of the Webset",
+            placeholder="webset-id-or-external-id",
+        )
+        enrichment_id: str = SchemaField(
+            description="The ID of the enrichment to delete",
+            placeholder="enrichment-id",
+        )
+
+    class Output(BlockSchemaOutput):
+        enrichment_id: str = SchemaField(description="The ID of the deleted enrichment")
+        success: str = SchemaField(description="Whether the deletion was successful")
+
+    def __init__(self):
+        super().__init__(
+            id="b250de56-2ca6-4237-a7b8-b5684892189f",
+            description="Delete an enrichment from a webset",
+            categories={BlockCategory.SEARCH},
+            input_schema=ExaDeleteEnrichmentBlock.Input,
+            output_schema=ExaDeleteEnrichmentBlock.Output,
+        )
+
+    async def run(
+        self, input_data: Input, *, credentials: APIKeyCredentials, **kwargs
+    ) -> BlockOutput:
+        # Use AsyncExa SDK
+        aexa = AsyncExa(api_key=credentials.api_key.get_secret_value())
+
+        deleted_enrichment = aexa.websets.enrichments.delete(
+            webset_id=input_data.webset_id, id=input_data.enrichment_id
+        )
+
+        yield "enrichment_id", deleted_enrichment.id
+        yield "success", "true"
+
+
+class ExaCancelEnrichmentBlock(Block):
+    """Cancel a running enrichment operation."""
+
+    class Input(BlockSchemaInput):
+        credentials: CredentialsMetaInput = exa.credentials_field(
+            description="The Exa integration requires an API Key."
+        )
+        webset_id: str = SchemaField(
+            description="The ID or external ID of the Webset",
+            placeholder="webset-id-or-external-id",
+        )
+        enrichment_id: str = SchemaField(
+            description="The ID of the enrichment to cancel",
+            placeholder="enrichment-id",
+        )
+
+    class Output(BlockSchemaOutput):
+        enrichment_id: str = SchemaField(
+            description="The ID of the canceled enrichment"
+        )
+        status: str = SchemaField(description="Status after cancellation")
+        items_enriched_before_cancel: int = SchemaField(
+            description="Approximate number of items enriched before cancellation"
+        )
+        success: str = SchemaField(
+            description="Whether the cancellation was successful"
+        )
+
+    def __init__(self):
+        super().__init__(
+            id="7e1f8f0f-b6ab-43b3-bd1d-0c534a649295",
+            description="Cancel a running enrichment operation",
+            categories={BlockCategory.SEARCH},
+            input_schema=ExaCancelEnrichmentBlock.Input,
+            output_schema=ExaCancelEnrichmentBlock.Output,
+        )
+
+    async def run(
+        self, input_data: Input, *, credentials: APIKeyCredentials, **kwargs
+    ) -> BlockOutput:
+        # Use AsyncExa SDK
+        aexa = AsyncExa(api_key=credentials.api_key.get_secret_value())
+
+        canceled_enrichment = aexa.websets.enrichments.cancel(
+            webset_id=input_data.webset_id, id=input_data.enrichment_id
+        )
+
+        # Try to estimate how many items were enriched before cancellation
+        items_enriched = 0
+        items_response = aexa.websets.items.list(
+            webset_id=input_data.webset_id, limit=100
+        )
+
+        for sdk_item in items_response.data:
+            # Check if this enrichment is present
+            for enrich_result in sdk_item.enrichments:
+                if enrich_result.enrichment_id == input_data.enrichment_id:
+                    items_enriched += 1
+                    break
+
+        status = (
+            canceled_enrichment.status.value
+            if hasattr(canceled_enrichment.status, "value")
+            else str(canceled_enrichment.status)
+        )
+
+        yield "enrichment_id", canceled_enrichment.id
+        yield "status", status
+        yield "items_enriched_before_cancel", items_enriched
+        yield "success", "true"

autogpt_platform/backend/backend/blocks/exa/websets_import_export.py

@@ -0,0 +1,676 @@
+"""
+Exa Websets Import/Export Management Blocks
+
+This module provides blocks for importing data into websets from CSV files
+and exporting webset data in various formats.
+"""
+
+import csv
+import json
+from enum import Enum
+from io import StringIO
+from typing import Optional, Union
+
+from exa_py import AsyncExa
+from exa_py.websets.types import CreateImportResponse
+from exa_py.websets.types import Import as SdkImport
+from pydantic import BaseModel
+
+from backend.sdk import (
+    APIKeyCredentials,
+    Block,
+    BlockCategory,
+    BlockOutput,
+    BlockSchemaInput,
+    BlockSchemaOutput,
+    CredentialsMetaInput,
+    SchemaField,
+)
+
+from ._config import exa
+from ._test import TEST_CREDENTIALS, TEST_CREDENTIALS_INPUT
+
+
+# Mirrored model for stability - don't use SDK types directly in block outputs
+class ImportModel(BaseModel):
+    """Stable output model mirroring SDK Import."""
+
+    id: str
+    status: str
+    title: str
+    format: str
+    entity_type: str
+    count: int
+    upload_url: Optional[str]  # Only in CreateImportResponse
+    upload_valid_until: Optional[str]  # Only in CreateImportResponse
+    failed_reason: str
+    failed_message: str
+    metadata: dict
+    created_at: str
+    updated_at: str
+
+    @classmethod
+    def from_sdk(
+        cls, import_obj: Union[SdkImport, CreateImportResponse]
+    ) -> "ImportModel":
+        """Convert SDK Import or CreateImportResponse to our stable model."""
+        # Extract entity type from union (may be None)
+        entity_type = "unknown"
+        if import_obj.entity:
+            entity_dict = import_obj.entity.model_dump(by_alias=True, exclude_none=True)
+            entity_type = entity_dict.get("type", "unknown")
+
+        # Handle status enum
+        status_str = (
+            import_obj.status.value
+            if hasattr(import_obj.status, "value")
+            else str(import_obj.status)
+        )
+
+        # Handle format enum
+        format_str = (
+            import_obj.format.value
+            if hasattr(import_obj.format, "value")
+            else str(import_obj.format)
+        )
+
+        # Handle failed_reason enum (may be None or enum)
+        failed_reason_str = ""
+        if import_obj.failed_reason:
+            failed_reason_str = (
+                import_obj.failed_reason.value
+                if hasattr(import_obj.failed_reason, "value")
+                else str(import_obj.failed_reason)
+            )
+
+        return cls(
+            id=import_obj.id,
+            status=status_str,
+            title=import_obj.title or "",
+            format=format_str,
+            entity_type=entity_type,
+            count=int(import_obj.count or 0),
+            upload_url=getattr(
+                import_obj, "upload_url", None
+            ),  # Only in CreateImportResponse
+            upload_valid_until=getattr(
+                import_obj, "upload_valid_until", None
+            ),  # Only in CreateImportResponse
+            failed_reason=failed_reason_str,
+            failed_message=import_obj.failed_message or "",
+            metadata=import_obj.metadata or {},
+            created_at=(
+                import_obj.created_at.isoformat() if import_obj.created_at else ""
+            ),
+            updated_at=(
+                import_obj.updated_at.isoformat() if import_obj.updated_at else ""
+            ),
+        )
+
+
+class ImportFormat(str, Enum):
+    """Supported import formats."""
+
+    CSV = "csv"
+    # JSON = "json"  # Future support
+
+
+class ImportEntityType(str, Enum):
+    """Entity types for imports."""
+
+    COMPANY = "company"
+    PERSON = "person"
+    ARTICLE = "article"
+    RESEARCH_PAPER = "research_paper"
+    CUSTOM = "custom"
+
+
+class ExportFormat(str, Enum):
+    """Supported export formats."""
+
+    JSON = "json"
+    CSV = "csv"
+    JSON_LINES = "jsonl"
+
+
+class ExaCreateImportBlock(Block):
+    """Create an import to load external data that can be used with websets."""
+
+    class Input(BlockSchemaInput):
+        credentials: CredentialsMetaInput = exa.credentials_field(
+            description="The Exa integration requires an API Key."
+        )
+        title: str = SchemaField(
+            description="Title for this import",
+            placeholder="Customer List Import",
+        )
+        csv_data: str = SchemaField(
+            description="CSV data to import (as a string)",
+            placeholder="name,url\nAcme Corp,https://acme.com\nExample Inc,https://example.com",
+        )
+        entity_type: ImportEntityType = SchemaField(
+            default=ImportEntityType.COMPANY,
+            description="Type of entities being imported",
+        )
+        entity_description: Optional[str] = SchemaField(
+            default=None,
+            description="Description for custom entity type",
+            advanced=True,
+        )
+        identifier_column: int = SchemaField(
+            default=0,
+            description="Column index containing the identifier (0-based)",
+            ge=0,
+        )
+        url_column: Optional[int] = SchemaField(
+            default=None,
+            description="Column index containing URLs (optional)",
+            ge=0,
+            advanced=True,
+        )
+        metadata: Optional[dict] = SchemaField(
+            default=None,
+            description="Metadata to attach to the import",
+            advanced=True,
+        )
+
+    class Output(BlockSchemaOutput):
+        import_id: str = SchemaField(
+            description="The unique identifier for the created import"
+        )
+        status: str = SchemaField(description="Current status of the import")
+        title: str = SchemaField(description="Title of the import")
+        count: int = SchemaField(description="Number of items in the import")
+        entity_type: str = SchemaField(description="Type of entities imported")
+        upload_url: Optional[str] = SchemaField(
+            description="Upload URL for CSV data (only if csv_data not provided in request)"
+        )
+        upload_valid_until: Optional[str] = SchemaField(
+            description="Expiration time for upload URL (only if upload_url is provided)"
+        )
+        created_at: str = SchemaField(description="When the import was created")
+
+    def __init__(self):
+        super().__init__(
+            id="020a35d8-8a53-4e60-8b60-1de5cbab1df3",
+            description="Import CSV data to use with websets for targeted searches",
+            categories={BlockCategory.DATA},
+            input_schema=ExaCreateImportBlock.Input,
+            output_schema=ExaCreateImportBlock.Output,
+            test_input={
+                "credentials": TEST_CREDENTIALS_INPUT,
+                "title": "Test Import",
+                "csv_data": "name,url\nAcme,https://acme.com",
+                "entity_type": ImportEntityType.COMPANY,
+                "identifier_column": 0,
+            },
+            test_output=[
+                ("import_id", "import-123"),
+                ("status", "pending"),
+                ("title", "Test Import"),
+                ("count", 1),
+                ("entity_type", "company"),
+                ("upload_url", None),
+                ("upload_valid_until", None),
+                ("created_at", "2024-01-01T00:00:00"),
+            ],
+            test_credentials=TEST_CREDENTIALS,
+            test_mock=self._create_test_mock(),
+        )
+
+    @staticmethod
+    def _create_test_mock():
+        """Create test mocks for the AsyncExa SDK."""
+        from datetime import datetime
+        from unittest.mock import MagicMock
+
+        # Create mock SDK import object
+        mock_import = MagicMock()
+        mock_import.id = "import-123"
+        mock_import.status = MagicMock(value="pending")
+        mock_import.title = "Test Import"
+        mock_import.format = MagicMock(value="csv")
+        mock_import.count = 1
+        mock_import.upload_url = None
+        mock_import.upload_valid_until = None
+        mock_import.failed_reason = None
+        mock_import.failed_message = ""
+        mock_import.metadata = {}
+        mock_import.created_at = datetime.fromisoformat("2024-01-01T00:00:00")
+        mock_import.updated_at = datetime.fromisoformat("2024-01-01T00:00:00")
+
+        # Mock entity
+        mock_entity = MagicMock()
+        mock_entity.model_dump = MagicMock(return_value={"type": "company"})
+        mock_import.entity = mock_entity
+
+        return {
+            "_get_client": lambda *args, **kwargs: MagicMock(
+                websets=MagicMock(
+                    imports=MagicMock(create=lambda *args, **kwargs: mock_import)
+                )
+            )
+        }
+
+    def _get_client(self, api_key: str) -> AsyncExa:
+        """Get Exa client (separated for testing)."""
+        return AsyncExa(api_key=api_key)
+
+    async def run(
+        self, input_data: Input, *, credentials: APIKeyCredentials, **kwargs
+    ) -> BlockOutput:
+        aexa = self._get_client(credentials.api_key.get_secret_value())
+
+        csv_reader = csv.reader(StringIO(input_data.csv_data))
+        rows = list(csv_reader)
+        count = len(rows) - 1 if len(rows) > 1 else 0
+
+        size = len(input_data.csv_data.encode("utf-8"))
+
+        payload = {
+            "title": input_data.title,
+            "format": ImportFormat.CSV.value,
+            "count": count,
+            "size": size,
+            "csv": {
+                "identifier": input_data.identifier_column,
+            },
+        }
+
+        # Add URL column if specified
+        if input_data.url_column is not None:
+            payload["csv"]["url"] = input_data.url_column
+
+        # Add entity configuration
+        entity = {"type": input_data.entity_type.value}
+        if (
+            input_data.entity_type == ImportEntityType.CUSTOM
+            and input_data.entity_description
+        ):
+            entity["description"] = input_data.entity_description
+        payload["entity"] = entity
+
+        # Add metadata if provided
+        if input_data.metadata:
+            payload["metadata"] = input_data.metadata
+
+        sdk_import = aexa.websets.imports.create(
+            params=payload, csv_data=input_data.csv_data
+        )
+
+        import_obj = ImportModel.from_sdk(sdk_import)
+
+        yield "import_id", import_obj.id
+        yield "status", import_obj.status
+        yield "title", import_obj.title
+        yield "count", import_obj.count
+        yield "entity_type", import_obj.entity_type
+        yield "upload_url", import_obj.upload_url
+        yield "upload_valid_until", import_obj.upload_valid_until
+        yield "created_at", import_obj.created_at
+
+
+class ExaGetImportBlock(Block):
+    """Get the status and details of an import."""
+
+    class Input(BlockSchemaInput):
+        credentials: CredentialsMetaInput = exa.credentials_field(
+            description="The Exa integration requires an API Key."
+        )
+        import_id: str = SchemaField(
+            description="The ID of the import to retrieve",
+            placeholder="import-id",
+        )
+
+    class Output(BlockSchemaOutput):
+        import_id: str = SchemaField(description="The unique identifier for the import")
+        status: str = SchemaField(description="Current status of the import")
+        title: str = SchemaField(description="Title of the import")
+        format: str = SchemaField(description="Format of the imported data")
+        entity_type: str = SchemaField(description="Type of entities imported")
+        count: int = SchemaField(description="Number of items imported")
+        upload_url: Optional[str] = SchemaField(
+            description="Upload URL for CSV data (if import not yet uploaded)"
+        )
+        upload_valid_until: Optional[str] = SchemaField(
+            description="Expiration time for upload URL (if applicable)"
+        )
+        failed_reason: Optional[str] = SchemaField(
+            description="Reason for failure (if applicable)"
+        )
+        failed_message: Optional[str] = SchemaField(
+            description="Detailed failure message (if applicable)"
+        )
+        created_at: str = SchemaField(description="When the import was created")
+        updated_at: str = SchemaField(description="When the import was last updated")
+        metadata: dict = SchemaField(description="Metadata attached to the import")
+
+    def __init__(self):
+        super().__init__(
+            id="236663c8-a8dc-45f7-a050-2676bb0a3dd2",
+            description="Get the status and details of an import",
+            categories={BlockCategory.DATA},
+            input_schema=ExaGetImportBlock.Input,
+            output_schema=ExaGetImportBlock.Output,
+        )
+
+    async def run(
+        self, input_data: Input, *, credentials: APIKeyCredentials, **kwargs
+    ) -> BlockOutput:
+        # Use AsyncExa SDK
+        aexa = AsyncExa(api_key=credentials.api_key.get_secret_value())
+
+        sdk_import = aexa.websets.imports.get(import_id=input_data.import_id)
+
+        import_obj = ImportModel.from_sdk(sdk_import)
+
+        # Yield all fields
+        yield "import_id", import_obj.id
+        yield "status", import_obj.status
+        yield "title", import_obj.title
+        yield "format", import_obj.format
+        yield "entity_type", import_obj.entity_type
+        yield "count", import_obj.count
+        yield "upload_url", import_obj.upload_url
+        yield "upload_valid_until", import_obj.upload_valid_until
+        yield "failed_reason", import_obj.failed_reason
+        yield "failed_message", import_obj.failed_message
+        yield "created_at", import_obj.created_at
+        yield "updated_at", import_obj.updated_at
+        yield "metadata", import_obj.metadata
+
+
+class ExaListImportsBlock(Block):
+    """List all imports with pagination."""
+
+    class Input(BlockSchemaInput):
+        credentials: CredentialsMetaInput = exa.credentials_field(
+            description="The Exa integration requires an API Key."
+        )
+        limit: int = SchemaField(
+            default=25,
+            description="Number of imports to return",
+            ge=1,
+            le=100,
+        )
+        cursor: Optional[str] = SchemaField(
+            default=None,
+            description="Cursor for pagination",
+            advanced=True,
+        )
+
+    class Output(BlockSchemaOutput):
+        imports: list[dict] = SchemaField(description="List of imports")
+        import_item: dict = SchemaField(
+            description="Individual import (yielded for each import)"
+        )
+        has_more: bool = SchemaField(
+            description="Whether there are more imports to paginate through"
+        )
+        next_cursor: Optional[str] = SchemaField(
+            description="Cursor for the next page of results"
+        )
+
+    def __init__(self):
+        super().__init__(
+            id="65323630-f7e9-4692-a624-184ba14c0686",
+            description="List all imports with pagination support",
+            categories={BlockCategory.DATA},
+            input_schema=ExaListImportsBlock.Input,
+            output_schema=ExaListImportsBlock.Output,
+        )
+
+    async def run(
+        self, input_data: Input, *, credentials: APIKeyCredentials, **kwargs
+    ) -> BlockOutput:
+        # Use AsyncExa SDK
+        aexa = AsyncExa(api_key=credentials.api_key.get_secret_value())
+
+        response = aexa.websets.imports.list(
+            cursor=input_data.cursor,
+            limit=input_data.limit,
+        )
+
+        # Convert SDK imports to our stable models
+        imports = [ImportModel.from_sdk(i) for i in response.data]
+
+        yield "imports", [i.model_dump() for i in imports]
+
+        for import_obj in imports:
+            yield "import_item", import_obj.model_dump()
+
+        yield "has_more", response.has_more
+        yield "next_cursor", response.next_cursor
+
+
+class ExaDeleteImportBlock(Block):
+    """Delete an import."""
+
+    class Input(BlockSchemaInput):
+        credentials: CredentialsMetaInput = exa.credentials_field(
+            description="The Exa integration requires an API Key."
+        )
+        import_id: str = SchemaField(
+            description="The ID of the import to delete",
+            placeholder="import-id",
+        )
+
+    class Output(BlockSchemaOutput):
+        import_id: str = SchemaField(description="The ID of the deleted import")
+        success: str = SchemaField(description="Whether the deletion was successful")
+
+    def __init__(self):
+        super().__init__(
+            id="81ae30ed-c7ba-4b5d-8483-b726846e570c",
+            description="Delete an import",
+            categories={BlockCategory.DATA},
+            input_schema=ExaDeleteImportBlock.Input,
+            output_schema=ExaDeleteImportBlock.Output,
+        )
+
+    async def run(
+        self, input_data: Input, *, credentials: APIKeyCredentials, **kwargs
+    ) -> BlockOutput:
+        # Use AsyncExa SDK
+        aexa = AsyncExa(api_key=credentials.api_key.get_secret_value())
+
+        deleted_import = aexa.websets.imports.delete(import_id=input_data.import_id)
+
+        yield "import_id", deleted_import.id
+        yield "success", "true"
+
+
+class ExaExportWebsetBlock(Block):
+    """Export all data from a webset in various formats."""
+
+    class Input(BlockSchemaInput):
+        credentials: CredentialsMetaInput = exa.credentials_field(
+            description="The Exa integration requires an API Key."
+        )
+        webset_id: str = SchemaField(
+            description="The ID or external ID of the Webset to export",
+            placeholder="webset-id-or-external-id",
+        )
+        format: ExportFormat = SchemaField(
+            default=ExportFormat.JSON,
+            description="Export format",
+        )
+        include_content: bool = SchemaField(
+            default=True,
+            description="Include full content in export",
+        )
+        include_enrichments: bool = SchemaField(
+            default=True,
+            description="Include enrichment data in export",
+        )
+        max_items: int = SchemaField(
+            default=100,
+            description="Maximum number of items to export",
+            ge=1,
+            le=100,
+        )
+
+    class Output(BlockSchemaOutput):
+        export_data: str = SchemaField(
+            description="Exported data in the requested format"
+        )
+        item_count: int = SchemaField(description="Number of items exported")
+        total_items: int = SchemaField(
+            description="Total number of items in the webset"
+        )
+        truncated: bool = SchemaField(
+            description="Whether the export was truncated due to max_items limit"
+        )
+        format: str = SchemaField(description="Format of the exported data")
+
+    def __init__(self):
+        super().__init__(
+            id="5da9d0fd-4b5b-4318-8302-8f71d0ccce9d",
+            description="Export webset data in JSON, CSV, or JSON Lines format",
+            categories={BlockCategory.DATA},
+            input_schema=ExaExportWebsetBlock.Input,
+            output_schema=ExaExportWebsetBlock.Output,
+            test_input={
+                "credentials": TEST_CREDENTIALS_INPUT,
+                "webset_id": "test-webset",
+                "format": ExportFormat.JSON,
+                "include_content": True,
+                "include_enrichments": True,
+                "max_items": 10,
+            },
+            test_output=[
+                ("export_data", str),
+                ("item_count", 2),
+                ("total_items", 2),
+                ("truncated", False),
+                ("format", "json"),
+            ],
+            test_credentials=TEST_CREDENTIALS,
+            test_mock=self._create_test_mock(),
+        )
+
+    @staticmethod
+    def _create_test_mock():
+        """Create test mocks for the AsyncExa SDK."""
+        from unittest.mock import MagicMock
+
+        # Create mock webset items
+        mock_item1 = MagicMock()
+        mock_item1.model_dump = MagicMock(
+            return_value={
+                "id": "item-1",
+                "url": "https://example.com",
+                "title": "Test Item 1",
+            }
+        )
+
+        mock_item2 = MagicMock()
+        mock_item2.model_dump = MagicMock(
+            return_value={
+                "id": "item-2",
+                "url": "https://example.org",
+                "title": "Test Item 2",
+            }
+        )
+
+        # Create mock iterator
+        mock_items = [mock_item1, mock_item2]
+
+        return {
+            "_get_client": lambda *args, **kwargs: MagicMock(
+                websets=MagicMock(
+                    items=MagicMock(list_all=lambda *args, **kwargs: iter(mock_items))
+                )
+            )
+        }
+
+    def _get_client(self, api_key: str) -> AsyncExa:
+        """Get Exa client (separated for testing)."""
+        return AsyncExa(api_key=api_key)
+
+    async def run(
+        self, input_data: Input, *, credentials: APIKeyCredentials, **kwargs
+    ) -> BlockOutput:
+        # Use AsyncExa SDK
+        aexa = self._get_client(credentials.api_key.get_secret_value())
+
+        try:
+            all_items = []
+
+            # Use SDK's list_all iterator to fetch items
+            item_iterator = aexa.websets.items.list_all(
+                webset_id=input_data.webset_id, limit=input_data.max_items
+            )
+
+            for sdk_item in item_iterator:
+                if len(all_items) >= input_data.max_items:
+                    break
+
+                # Convert to dict for export
+                item_dict = sdk_item.model_dump(by_alias=True, exclude_none=True)
+                all_items.append(item_dict)
+
+            # Calculate total and truncated
+            total_items = len(all_items)  # SDK doesn't provide total count
+            truncated = len(all_items) >= input_data.max_items
+
+            # Process items based on include flags
+            if not input_data.include_content:
+                for item in all_items:
+                    item.pop("content", None)
+
+            if not input_data.include_enrichments:
+                for item in all_items:
+                    item.pop("enrichments", None)
+
+            # Format the export data
+            export_data = ""
+
+            if input_data.format == ExportFormat.JSON:
+                export_data = json.dumps(all_items, indent=2, default=str)
+
+            elif input_data.format == ExportFormat.JSON_LINES:
+                lines = [json.dumps(item, default=str) for item in all_items]
+                export_data = "\n".join(lines)
+
+            elif input_data.format == ExportFormat.CSV:
+                # Extract all unique keys for CSV headers
+                all_keys = set()
+                for item in all_items:
+                    all_keys.update(self._flatten_dict(item).keys())
+
+                # Create CSV
+                output = StringIO()
+                writer = csv.DictWriter(output, fieldnames=sorted(all_keys))
+                writer.writeheader()
+
+                for item in all_items:
+                    flat_item = self._flatten_dict(item)
+                    writer.writerow(flat_item)
+
+                export_data = output.getvalue()
+
+            yield "export_data", export_data
+            yield "item_count", len(all_items)
+            yield "total_items", total_items
+            yield "truncated", truncated
+            yield "format", input_data.format.value
+
+        except ValueError as e:
+            # Re-raise user input validation errors
+            raise ValueError(f"Failed to export webset: {e}") from e
+        # Let all other exceptions propagate naturally
+
+    def _flatten_dict(self, d: dict, parent_key: str = "", sep: str = "_") -> dict:
+        """Flatten nested dictionaries for CSV export."""
+        items = []
+        for k, v in d.items():
+            new_key = f"{parent_key}{sep}{k}" if parent_key else k
+            if isinstance(v, dict):
+                items.extend(self._flatten_dict(v, new_key, sep=sep).items())
+            elif isinstance(v, list):
+                # Convert lists to JSON strings for CSV
+                items.append((new_key, json.dumps(v, default=str)))
+            else:
+                items.append((new_key, v))
+        return dict(items)

autogpt_platform/backend/backend/blocks/exa/websets_items.py

@@ -0,0 +1,591 @@
+"""
+Exa Websets Item Management Blocks
+
+This module provides blocks for managing items within Exa websets, including
+retrieving, listing, deleting, and bulk operations on webset items.
+"""
+
+from typing import Any, Dict, List, Optional
+
+from exa_py import AsyncExa
+from exa_py.websets.types import WebsetItem as SdkWebsetItem
+from exa_py.websets.types import (
+    WebsetItemArticleProperties,
+    WebsetItemCompanyProperties,
+    WebsetItemCustomProperties,
+    WebsetItemPersonProperties,
+    WebsetItemResearchPaperProperties,
+)
+from pydantic import AnyUrl, BaseModel
+
+from backend.sdk import (
+    APIKeyCredentials,
+    Block,
+    BlockCategory,
+    BlockOutput,
+    BlockSchemaInput,
+    BlockSchemaOutput,
+    CredentialsMetaInput,
+    SchemaField,
+)
+
+from ._config import exa
+
+
+# Mirrored model for enrichment results
+class EnrichmentResultModel(BaseModel):
+    """Stable output model mirroring SDK EnrichmentResult."""
+
+    enrichment_id: str
+    format: str
+    result: Optional[List[str]]
+    reasoning: Optional[str]
+    references: List[Dict[str, Any]]
+
+    @classmethod
+    def from_sdk(cls, sdk_enrich) -> "EnrichmentResultModel":
+        """Convert SDK EnrichmentResult to our model."""
+        format_str = (
+            sdk_enrich.format.value
+            if hasattr(sdk_enrich.format, "value")
+            else str(sdk_enrich.format)
+        )
+
+        # Convert references to dicts
+        references_list = []
+        if sdk_enrich.references:
+            for ref in sdk_enrich.references:
+                references_list.append(ref.model_dump(by_alias=True, exclude_none=True))
+
+        return cls(
+            enrichment_id=sdk_enrich.enrichment_id,
+            format=format_str,
+            result=sdk_enrich.result,
+            reasoning=sdk_enrich.reasoning,
+            references=references_list,
+        )
+
+
+# Mirrored model for stability - don't use SDK types directly in block outputs
+class WebsetItemModel(BaseModel):
+    """Stable output model mirroring SDK WebsetItem."""
+
+    id: str
+    url: Optional[AnyUrl]
+    title: str
+    content: str
+    entity_data: Dict[str, Any]
+    enrichments: Dict[str, EnrichmentResultModel]
+    created_at: str
+    updated_at: str
+
+    @classmethod
+    def from_sdk(cls, item: SdkWebsetItem) -> "WebsetItemModel":
+        """Convert SDK WebsetItem to our stable model."""
+        # Extract properties from the union type
+        properties_dict = {}
+        url_value = None
+        title = ""
+        content = ""
+
+        if hasattr(item, "properties") and item.properties:
+            properties_dict = item.properties.model_dump(
+                by_alias=True, exclude_none=True
+            )
+
+            # URL is always available on all property types
+            url_value = item.properties.url
+
+            # Extract title using isinstance checks on the union type
+            if isinstance(item.properties, WebsetItemPersonProperties):
+                title = item.properties.person.name
+                content = ""  # Person type has no content
+            elif isinstance(item.properties, WebsetItemCompanyProperties):
+                title = item.properties.company.name
+                content = item.properties.content or ""
+            elif isinstance(item.properties, WebsetItemArticleProperties):
+                title = item.properties.description
+                content = item.properties.content or ""
+            elif isinstance(item.properties, WebsetItemResearchPaperProperties):
+                title = item.properties.description
+                content = item.properties.content or ""
+            elif isinstance(item.properties, WebsetItemCustomProperties):
+                title = item.properties.description
+                content = item.properties.content or ""
+            else:
+                # Fallback
+                title = item.properties.description
+                content = getattr(item.properties, "content", "")
+
+        # Convert enrichments from list to dict keyed by enrichment_id using Pydantic models
+        enrichments_dict: Dict[str, EnrichmentResultModel] = {}
+        if hasattr(item, "enrichments") and item.enrichments:
+            for sdk_enrich in item.enrichments:
+                enrich_model = EnrichmentResultModel.from_sdk(sdk_enrich)
+                enrichments_dict[enrich_model.enrichment_id] = enrich_model
+
+        return cls(
+            id=item.id,
+            url=url_value,
+            title=title,
+            content=content or "",
+            entity_data=properties_dict,
+            enrichments=enrichments_dict,
+            created_at=item.created_at.isoformat() if item.created_at else "",
+            updated_at=item.updated_at.isoformat() if item.updated_at else "",
+        )
+
+
+class ExaGetWebsetItemBlock(Block):
+    """Get a specific item from a webset by its ID."""
+
+    class Input(BlockSchemaInput):
+        credentials: CredentialsMetaInput = exa.credentials_field(
+            description="The Exa integration requires an API Key."
+        )
+        webset_id: str = SchemaField(
+            description="The ID or external ID of the Webset",
+            placeholder="webset-id-or-external-id",
+        )
+        item_id: str = SchemaField(
+            description="The ID of the specific item to retrieve",
+            placeholder="item-id",
+        )
+
+    class Output(BlockSchemaOutput):
+        item_id: str = SchemaField(description="The unique identifier for the item")
+        url: str = SchemaField(description="The URL of the original source")
+        title: str = SchemaField(description="The title of the item")
+        content: str = SchemaField(description="The main content of the item")
+        entity_data: dict = SchemaField(description="Entity-specific structured data")
+        enrichments: dict = SchemaField(description="Enrichment data added to the item")
+        created_at: str = SchemaField(
+            description="When the item was added to the webset"
+        )
+        updated_at: str = SchemaField(description="When the item was last updated")
+
+    def __init__(self):
+        super().__init__(
+            id="c4a7d9e2-8f3b-4a6c-9d8e-a5b6c7d8e9f0",
+            description="Get a specific item from a webset by its ID",
+            categories={BlockCategory.SEARCH},
+            input_schema=ExaGetWebsetItemBlock.Input,
+            output_schema=ExaGetWebsetItemBlock.Output,
+        )
+
+    async def run(
+        self, input_data: Input, *, credentials: APIKeyCredentials, **kwargs
+    ) -> BlockOutput:
+        aexa = AsyncExa(api_key=credentials.api_key.get_secret_value())
+
+        sdk_item = aexa.websets.items.get(
+            webset_id=input_data.webset_id, id=input_data.item_id
+        )
+
+        item = WebsetItemModel.from_sdk(sdk_item)
+
+        yield "item_id", item.id
+        yield "url", item.url
+        yield "title", item.title
+        yield "content", item.content
+        yield "entity_data", item.entity_data
+        yield "enrichments", item.enrichments
+        yield "created_at", item.created_at
+        yield "updated_at", item.updated_at
+
+
+class ExaListWebsetItemsBlock(Block):
+    """List items in a webset with pagination and optional filtering."""
+
+    class Input(BlockSchemaInput):
+        credentials: CredentialsMetaInput = exa.credentials_field(
+            description="The Exa integration requires an API Key."
+        )
+        webset_id: str = SchemaField(
+            description="The ID or external ID of the Webset",
+            placeholder="webset-id-or-external-id",
+        )
+        limit: int = SchemaField(
+            default=25,
+            description="Number of items to return (1-100)",
+            ge=1,
+            le=100,
+        )
+        cursor: Optional[str] = SchemaField(
+            default=None,
+            description="Cursor for pagination through results",
+            advanced=True,
+        )
+        wait_for_items: bool = SchemaField(
+            default=False,
+            description="Wait for items to be available if webset is still processing",
+            advanced=True,
+        )
+        wait_timeout: int = SchemaField(
+            default=60,
+            description="Maximum time to wait for items in seconds",
+            advanced=True,
+            ge=1,
+            le=300,
+        )
+
+    class Output(BlockSchemaOutput):
+        items: list[WebsetItemModel] = SchemaField(
+            description="List of webset items",
+        )
+        webset_id: str = SchemaField(
+            description="The ID of the webset",
+        )
+        item: WebsetItemModel = SchemaField(
+            description="Individual item (yielded for each item in the list)",
+        )
+        has_more: bool = SchemaField(
+            description="Whether there are more items to paginate through",
+        )
+        next_cursor: Optional[str] = SchemaField(
+            description="Cursor for the next page of results",
+        )
+
+    def __init__(self):
+        super().__init__(
+            id="7b5e8c9f-01a2-43c4-95e6-f7a8b9c0d1e2",
+            description="List items in a webset with pagination support",
+            categories={BlockCategory.SEARCH},
+            input_schema=ExaListWebsetItemsBlock.Input,
+            output_schema=ExaListWebsetItemsBlock.Output,
+        )
+
+    async def run(
+        self, input_data: Input, *, credentials: APIKeyCredentials, **kwargs
+    ) -> BlockOutput:
+        aexa = AsyncExa(api_key=credentials.api_key.get_secret_value())
+
+        if input_data.wait_for_items:
+            import asyncio
+            import time
+
+            start_time = time.time()
+            interval = 2
+            response = None
+
+            while time.time() - start_time < input_data.wait_timeout:
+                response = aexa.websets.items.list(
+                    webset_id=input_data.webset_id,
+                    cursor=input_data.cursor,
+                    limit=input_data.limit,
+                )
+
+                if response.data:
+                    break
+
+                await asyncio.sleep(interval)
+                interval = min(interval * 1.2, 10)
+
+            if not response:
+                response = aexa.websets.items.list(
+                    webset_id=input_data.webset_id,
+                    cursor=input_data.cursor,
+                    limit=input_data.limit,
+                )
+        else:
+            response = aexa.websets.items.list(
+                webset_id=input_data.webset_id,
+                cursor=input_data.cursor,
+                limit=input_data.limit,
+            )
+
+        items = [WebsetItemModel.from_sdk(item) for item in response.data]
+
+        yield "items", items
+
+        for item in items:
+            yield "item", item
+
+        yield "has_more", response.has_more
+        yield "next_cursor", response.next_cursor
+        yield "webset_id", input_data.webset_id
+
+
+class ExaDeleteWebsetItemBlock(Block):
+    """Delete a specific item from a webset."""
+
+    class Input(BlockSchemaInput):
+        credentials: CredentialsMetaInput = exa.credentials_field(
+            description="The Exa integration requires an API Key."
+        )
+        webset_id: str = SchemaField(
+            description="The ID or external ID of the Webset",
+            placeholder="webset-id-or-external-id",
+        )
+        item_id: str = SchemaField(
+            description="The ID of the item to delete",
+            placeholder="item-id",
+        )
+
+    class Output(BlockSchemaOutput):
+        item_id: str = SchemaField(description="The ID of the deleted item")
+        success: str = SchemaField(description="Whether the deletion was successful")
+
+    def __init__(self):
+        super().__init__(
+            id="12c57fbe-c270-4877-a2b6-d2d05529ba79",
+            description="Delete a specific item from a webset",
+            categories={BlockCategory.SEARCH},
+            input_schema=ExaDeleteWebsetItemBlock.Input,
+            output_schema=ExaDeleteWebsetItemBlock.Output,
+        )
+
+    async def run(
+        self, input_data: Input, *, credentials: APIKeyCredentials, **kwargs
+    ) -> BlockOutput:
+        aexa = AsyncExa(api_key=credentials.api_key.get_secret_value())
+
+        deleted_item = aexa.websets.items.delete(
+            webset_id=input_data.webset_id, id=input_data.item_id
+        )
+
+        yield "item_id", deleted_item.id
+        yield "success", "true"
+
+
+class ExaBulkWebsetItemsBlock(Block):
+    """Get all items from a webset in a single operation (with size limits)."""
+
+    class Input(BlockSchemaInput):
+        credentials: CredentialsMetaInput = exa.credentials_field(
+            description="The Exa integration requires an API Key."
+        )
+        webset_id: str = SchemaField(
+            description="The ID or external ID of the Webset",
+            placeholder="webset-id-or-external-id",
+        )
+        max_items: int = SchemaField(
+            default=100,
+            description="Maximum number of items to retrieve (1-1000). Note: Large values may take longer.",
+            ge=1,
+            le=1000,
+        )
+        include_enrichments: bool = SchemaField(
+            default=True,
+            description="Include enrichment data for each item",
+        )
+        include_content: bool = SchemaField(
+            default=True,
+            description="Include full content for each item",
+        )
+
+    class Output(BlockSchemaOutput):
+        items: list[WebsetItemModel] = SchemaField(
+            description="All items from the webset"
+        )
+        item: WebsetItemModel = SchemaField(
+            description="Individual item (yielded for each item)"
+        )
+        total_retrieved: int = SchemaField(
+            description="Total number of items retrieved"
+        )
+        truncated: bool = SchemaField(
+            description="Whether results were truncated due to max_items limit"
+        )
+
+    def __init__(self):
+        super().__init__(
+            id="dbd619f5-476e-4395-af9a-a7a7c0fb8c4e",
+            description="Get all items from a webset in bulk (with configurable limits)",
+            categories={BlockCategory.SEARCH},
+            input_schema=ExaBulkWebsetItemsBlock.Input,
+            output_schema=ExaBulkWebsetItemsBlock.Output,
+        )
+
+    async def run(
+        self, input_data: Input, *, credentials: APIKeyCredentials, **kwargs
+    ) -> BlockOutput:
+        # Use AsyncExa SDK
+        aexa = AsyncExa(api_key=credentials.api_key.get_secret_value())
+
+        all_items: List[WebsetItemModel] = []
+        item_iterator = aexa.websets.items.list_all(
+            webset_id=input_data.webset_id, limit=input_data.max_items
+        )
+
+        for sdk_item in item_iterator:
+            if len(all_items) >= input_data.max_items:
+                break
+
+            item = WebsetItemModel.from_sdk(sdk_item)
+
+            if not input_data.include_enrichments:
+                item.enrichments = {}
+            if not input_data.include_content:
+                item.content = ""
+
+            all_items.append(item)
+
+        yield "items", all_items
+
+        for item in all_items:
+            yield "item", item
+
+        yield "total_retrieved", len(all_items)
+        yield "truncated", len(all_items) >= input_data.max_items
+
+
+class ExaWebsetItemsSummaryBlock(Block):
+    """Get a summary of items in a webset without retrieving all data."""
+
+    class Input(BlockSchemaInput):
+        credentials: CredentialsMetaInput = exa.credentials_field(
+            description="The Exa integration requires an API Key."
+        )
+        webset_id: str = SchemaField(
+            description="The ID or external ID of the Webset",
+            placeholder="webset-id-or-external-id",
+        )
+        sample_size: int = SchemaField(
+            default=5,
+            description="Number of sample items to include",
+            ge=0,
+            le=10,
+        )
+
+    class Output(BlockSchemaOutput):
+        total_items: int = SchemaField(
+            description="Total number of items in the webset"
+        )
+        entity_type: str = SchemaField(description="Type of entities in the webset")
+        sample_items: list[WebsetItemModel] = SchemaField(
+            description="Sample of items from the webset"
+        )
+        enrichment_columns: list[str] = SchemaField(
+            description="List of enrichment columns available"
+        )
+
+    def __init__(self):
+        super().__init__(
+            id="db7813ad-10bd-4652-8623-5667d6fecdd5",
+            description="Get a summary of webset items without retrieving all data",
+            categories={BlockCategory.SEARCH},
+            input_schema=ExaWebsetItemsSummaryBlock.Input,
+            output_schema=ExaWebsetItemsSummaryBlock.Output,
+        )
+
+    async def run(
+        self, input_data: Input, *, credentials: APIKeyCredentials, **kwargs
+    ) -> BlockOutput:
+        # Use AsyncExa SDK
+        aexa = AsyncExa(api_key=credentials.api_key.get_secret_value())
+
+        webset = aexa.websets.get(id=input_data.webset_id)
+
+        entity_type = "unknown"
+        if webset.searches:
+            first_search = webset.searches[0]
+            if first_search.entity:
+                # The entity is a union type, extract type field
+                entity_dict = first_search.entity.model_dump(by_alias=True)
+                entity_type = entity_dict.get("type", "unknown")
+
+        # Get enrichment columns
+        enrichment_columns = []
+        if webset.enrichments:
+            enrichment_columns = [
+                e.title if e.title else e.description for e in webset.enrichments
+            ]
+
+        # Get sample items if requested
+        sample_items: List[WebsetItemModel] = []
+        if input_data.sample_size > 0:
+            items_response = aexa.websets.items.list(
+                webset_id=input_data.webset_id, limit=input_data.sample_size
+            )
+            # Convert to our stable models
+            sample_items = [
+                WebsetItemModel.from_sdk(item) for item in items_response.data
+            ]
+
+        total_items = 0
+        if webset.searches:
+            for search in webset.searches:
+                if search.progress:
+                    total_items += search.progress.found
+
+        yield "total_items", total_items
+        yield "entity_type", entity_type
+        yield "sample_items", sample_items
+        yield "enrichment_columns", enrichment_columns
+
+
+class ExaGetNewItemsBlock(Block):
+    """Get items added to a webset since a specific cursor (incremental processing helper)."""
+
+    class Input(BlockSchemaInput):
+        credentials: CredentialsMetaInput = exa.credentials_field(
+            description="The Exa integration requires an API Key."
+        )
+        webset_id: str = SchemaField(
+            description="The ID or external ID of the Webset",
+            placeholder="webset-id-or-external-id",
+        )
+        since_cursor: Optional[str] = SchemaField(
+            default=None,
+            description="Cursor from previous run - only items after this will be returned. Leave empty on first run.",
+            placeholder="cursor-from-previous-run",
+        )
+        max_items: int = SchemaField(
+            default=100,
+            description="Maximum number of new items to retrieve",
+            ge=1,
+            le=1000,
+        )
+
+    class Output(BlockSchemaOutput):
+        new_items: list[WebsetItemModel] = SchemaField(
+            description="Items added since the cursor"
+        )
+        item: WebsetItemModel = SchemaField(
+            description="Individual item (yielded for each new item)"
+        )
+        count: int = SchemaField(description="Number of new items found")
+        next_cursor: Optional[str] = SchemaField(
+            description="Save this cursor for the next run to get only newer items"
+        )
+        has_more: bool = SchemaField(
+            description="Whether there are more new items beyond max_items"
+        )
+
+    def __init__(self):
+        super().__init__(
+            id="3ff9bdf5-9613-4d21-8a60-90eb8b69c414",
+            description="Get items added since a cursor - enables incremental processing without reprocessing",
+            categories={BlockCategory.SEARCH, BlockCategory.DATA},
+            input_schema=ExaGetNewItemsBlock.Input,
+            output_schema=ExaGetNewItemsBlock.Output,
+        )
+
+    async def run(
+        self, input_data: Input, *, credentials: APIKeyCredentials, **kwargs
+    ) -> BlockOutput:
+        # Use AsyncExa SDK
+        aexa = AsyncExa(api_key=credentials.api_key.get_secret_value())
+
+        # Get items starting from cursor
+        response = aexa.websets.items.list(
+            webset_id=input_data.webset_id,
+            cursor=input_data.since_cursor,
+            limit=input_data.max_items,
+        )
+
+        # Convert SDK items to our stable models
+        new_items = [WebsetItemModel.from_sdk(item) for item in response.data]
+
+        # Yield the full list
+        yield "new_items", new_items
+
+        # Yield individual items for processing
+        for item in new_items:
+            yield "item", item
+
+        # Yield metadata for next run
+        yield "count", len(new_items)
+        yield "next_cursor", response.next_cursor
+        yield "has_more", response.has_more

autogpt_platform/backend/backend/blocks/exa/websets_monitor.py

@@ -0,0 +1,600 @@
+"""
+Exa Websets Monitor Management Blocks
+
+This module provides blocks for creating and managing monitors that automatically
+keep websets updated with fresh data on a schedule.
+"""
+
+from enum import Enum
+from typing import Optional
+
+from exa_py import AsyncExa
+from exa_py.websets.types import Monitor as SdkMonitor
+from pydantic import BaseModel
+
+from backend.sdk import (
+    APIKeyCredentials,
+    Block,
+    BlockCategory,
+    BlockOutput,
+    BlockSchemaInput,
+    BlockSchemaOutput,
+    CredentialsMetaInput,
+    SchemaField,
+)
+
+from ._config import exa
+from ._test import TEST_CREDENTIALS, TEST_CREDENTIALS_INPUT
+
+
+# Mirrored model for stability - don't use SDK types directly in block outputs
+class MonitorModel(BaseModel):
+    """Stable output model mirroring SDK Monitor."""
+
+    id: str
+    status: str
+    webset_id: str
+    behavior_type: str
+    behavior_config: dict
+    cron_expression: str
+    timezone: str
+    next_run_at: str
+    last_run: dict
+    metadata: dict
+    created_at: str
+    updated_at: str
+
+    @classmethod
+    def from_sdk(cls, monitor: SdkMonitor) -> "MonitorModel":
+        """Convert SDK Monitor to our stable model."""
+        # Extract behavior information
+        behavior_dict = monitor.behavior.model_dump(by_alias=True, exclude_none=True)
+        behavior_type = behavior_dict.get("type", "unknown")
+        behavior_config = behavior_dict.get("config", {})
+
+        # Extract cadence information
+        cadence_dict = monitor.cadence.model_dump(by_alias=True, exclude_none=True)
+        cron_expr = cadence_dict.get("cron", "")
+        timezone = cadence_dict.get("timezone", "Etc/UTC")
+
+        # Extract last run information
+        last_run_dict = {}
+        if monitor.last_run:
+            last_run_dict = monitor.last_run.model_dump(
+                by_alias=True, exclude_none=True
+            )
+
+        # Handle status enum
+        status_str = (
+            monitor.status.value
+            if hasattr(monitor.status, "value")
+            else str(monitor.status)
+        )
+
+        return cls(
+            id=monitor.id,
+            status=status_str,
+            webset_id=monitor.webset_id,
+            behavior_type=behavior_type,
+            behavior_config=behavior_config,
+            cron_expression=cron_expr,
+            timezone=timezone,
+            next_run_at=monitor.next_run_at.isoformat() if monitor.next_run_at else "",
+            last_run=last_run_dict,
+            metadata=monitor.metadata or {},
+            created_at=monitor.created_at.isoformat() if monitor.created_at else "",
+            updated_at=monitor.updated_at.isoformat() if monitor.updated_at else "",
+        )
+
+
+class MonitorStatus(str, Enum):
+    """Status of a monitor."""
+
+    ENABLED = "enabled"
+    DISABLED = "disabled"
+    PAUSED = "paused"
+
+
+class MonitorBehaviorType(str, Enum):
+    """Type of behavior for a monitor."""
+
+    SEARCH = "search"  # Run new searches
+    REFRESH = "refresh"  # Refresh existing items
+
+
+class SearchBehavior(str, Enum):
+    """How search results interact with existing items."""
+
+    APPEND = "append"
+    OVERRIDE = "override"
+
+
+class ExaCreateMonitorBlock(Block):
+    """Create a monitor to automatically keep a webset updated on a schedule."""
+
+    class Input(BlockSchemaInput):
+        credentials: CredentialsMetaInput = exa.credentials_field(
+            description="The Exa integration requires an API Key."
+        )
+        webset_id: str = SchemaField(
+            description="The ID or external ID of the Webset to monitor",
+            placeholder="webset-id-or-external-id",
+        )
+
+        # Schedule configuration
+        cron_expression: str = SchemaField(
+            description="Cron expression for scheduling (5 fields, max once per day)",
+            placeholder="0 9 * * 1",  # Every Monday at 9 AM
+        )
+        timezone: str = SchemaField(
+            default="Etc/UTC",
+            description="IANA timezone for the schedule",
+            placeholder="America/New_York",
+            advanced=True,
+        )
+
+        # Behavior configuration
+        behavior_type: MonitorBehaviorType = SchemaField(
+            default=MonitorBehaviorType.SEARCH,
+            description="Type of monitor behavior (search for new items or refresh existing)",
+        )
+
+        # Search configuration (for SEARCH behavior)
+        search_query: Optional[str] = SchemaField(
+            default=None,
+            description="Search query for finding new items (required for search behavior)",
+            placeholder="AI startups that raised funding in the last week",
+        )
+        search_count: int = SchemaField(
+            default=10,
+            description="Number of items to find in each search",
+            ge=1,
+            le=100,
+        )
+        search_criteria: list[str] = SchemaField(
+            default_factory=list,
+            description="Criteria that items must meet",
+            advanced=True,
+        )
+        search_behavior: SearchBehavior = SchemaField(
+            default=SearchBehavior.APPEND,
+            description="How new results interact with existing items",
+            advanced=True,
+        )
+        entity_type: Optional[str] = SchemaField(
+            default=None,
+            description="Type of entity to search for (company, person, etc.)",
+            advanced=True,
+        )
+
+        # Refresh configuration (for REFRESH behavior)
+        refresh_content: bool = SchemaField(
+            default=True,
+            description="Refresh content from source URLs (for refresh behavior)",
+            advanced=True,
+        )
+        refresh_enrichments: bool = SchemaField(
+            default=True,
+            description="Re-run enrichments on items (for refresh behavior)",
+            advanced=True,
+        )
+
+        # Metadata
+        metadata: Optional[dict] = SchemaField(
+            default=None,
+            description="Metadata to attach to the monitor",
+            advanced=True,
+        )
+
+    class Output(BlockSchemaOutput):
+        monitor_id: str = SchemaField(
+            description="The unique identifier for the created monitor"
+        )
+        webset_id: str = SchemaField(description="The webset this monitor belongs to")
+        status: str = SchemaField(description="Status of the monitor")
+        behavior_type: str = SchemaField(description="Type of monitor behavior")
+        next_run_at: Optional[str] = SchemaField(
+            description="When the monitor will next run"
+        )
+        cron_expression: str = SchemaField(description="The schedule cron expression")
+        timezone: str = SchemaField(description="The timezone for scheduling")
+        created_at: str = SchemaField(description="When the monitor was created")
+
+    def __init__(self):
+        super().__init__(
+            id="f8a9b0c1-d2e3-4567-890a-bcdef1234567",
+            description="Create automated monitors to keep websets updated with fresh data on a schedule",
+            categories={BlockCategory.SEARCH},
+            input_schema=ExaCreateMonitorBlock.Input,
+            output_schema=ExaCreateMonitorBlock.Output,
+            test_input={
+                "credentials": TEST_CREDENTIALS_INPUT,
+                "webset_id": "test-webset",
+                "cron_expression": "0 9 * * 1",
+                "behavior_type": MonitorBehaviorType.SEARCH,
+                "search_query": "AI startups",
+                "search_count": 10,
+            },
+            test_output=[
+                ("monitor_id", "monitor-123"),
+                ("webset_id", "test-webset"),
+                ("status", "enabled"),
+                ("behavior_type", "search"),
+                ("next_run_at", "2024-01-01T00:00:00"),
+                ("cron_expression", "0 9 * * 1"),
+                ("timezone", "Etc/UTC"),
+                ("created_at", "2024-01-01T00:00:00"),
+            ],
+            test_credentials=TEST_CREDENTIALS,
+            test_mock=self._create_test_mock(),
+        )
+
+    @staticmethod
+    def _create_test_mock():
+        """Create test mocks for the AsyncExa SDK."""
+        from datetime import datetime
+        from unittest.mock import MagicMock
+
+        # Create mock SDK monitor object
+        mock_monitor = MagicMock()
+        mock_monitor.id = "monitor-123"
+        mock_monitor.status = MagicMock(value="enabled")
+        mock_monitor.webset_id = "test-webset"
+        mock_monitor.next_run_at = datetime.fromisoformat("2024-01-01T00:00:00")
+        mock_monitor.created_at = datetime.fromisoformat("2024-01-01T00:00:00")
+        mock_monitor.updated_at = datetime.fromisoformat("2024-01-01T00:00:00")
+        mock_monitor.metadata = {}
+        mock_monitor.last_run = None
+
+        # Mock behavior
+        mock_behavior = MagicMock()
+        mock_behavior.model_dump = MagicMock(
+            return_value={"type": "search", "config": {}}
+        )
+        mock_monitor.behavior = mock_behavior
+
+        # Mock cadence
+        mock_cadence = MagicMock()
+        mock_cadence.model_dump = MagicMock(
+            return_value={"cron": "0 9 * * 1", "timezone": "Etc/UTC"}
+        )
+        mock_monitor.cadence = mock_cadence
+
+        return {
+            "_get_client": lambda *args, **kwargs: MagicMock(
+                websets=MagicMock(
+                    monitors=MagicMock(create=lambda *args, **kwargs: mock_monitor)
+                )
+            )
+        }
+
+    def _get_client(self, api_key: str) -> AsyncExa:
+        """Get Exa client (separated for testing)."""
+        return AsyncExa(api_key=api_key)
+
+    async def run(
+        self, input_data: Input, *, credentials: APIKeyCredentials, **kwargs
+    ) -> BlockOutput:
+        aexa = self._get_client(credentials.api_key.get_secret_value())
+
+        # Build the payload
+        payload = {
+            "websetId": input_data.webset_id,
+            "cadence": {
+                "cron": input_data.cron_expression,
+                "timezone": input_data.timezone,
+            },
+        }
+
+        # Build behavior configuration based on type
+        if input_data.behavior_type == MonitorBehaviorType.SEARCH:
+            behavior_config = {
+                "query": input_data.search_query or "",
+                "count": input_data.search_count,
+                "behavior": input_data.search_behavior.value,
+            }
+
+            if input_data.search_criteria:
+                behavior_config["criteria"] = [
+                    {"description": c} for c in input_data.search_criteria
+                ]
+
+            if input_data.entity_type:
+                behavior_config["entity"] = {"type": input_data.entity_type}
+
+            payload["behavior"] = {
+                "type": "search",
+                "config": behavior_config,
+            }
+        else:
+            # REFRESH behavior
+            payload["behavior"] = {
+                "type": "refresh",
+                "config": {
+                    "content": input_data.refresh_content,
+                    "enrichments": input_data.refresh_enrichments,
+                },
+            }
+
+        # Add metadata if provided
+        if input_data.metadata:
+            payload["metadata"] = input_data.metadata
+
+        sdk_monitor = aexa.websets.monitors.create(params=payload)
+
+        monitor = MonitorModel.from_sdk(sdk_monitor)
+
+        # Yield all fields
+        yield "monitor_id", monitor.id
+        yield "webset_id", monitor.webset_id
+        yield "status", monitor.status
+        yield "behavior_type", monitor.behavior_type
+        yield "next_run_at", monitor.next_run_at
+        yield "cron_expression", monitor.cron_expression
+        yield "timezone", monitor.timezone
+        yield "created_at", monitor.created_at
+
+
+class ExaGetMonitorBlock(Block):
+    """Get the details and status of a monitor."""
+
+    class Input(BlockSchemaInput):
+        credentials: CredentialsMetaInput = exa.credentials_field(
+            description="The Exa integration requires an API Key."
+        )
+        monitor_id: str = SchemaField(
+            description="The ID of the monitor to retrieve",
+            placeholder="monitor-id",
+        )
+
+    class Output(BlockSchemaOutput):
+        monitor_id: str = SchemaField(
+            description="The unique identifier for the monitor"
+        )
+        webset_id: str = SchemaField(description="The webset this monitor belongs to")
+        status: str = SchemaField(description="Current status of the monitor")
+        behavior_type: str = SchemaField(description="Type of monitor behavior")
+        behavior_config: dict = SchemaField(
+            description="Configuration for the monitor behavior"
+        )
+        cron_expression: str = SchemaField(description="The schedule cron expression")
+        timezone: str = SchemaField(description="The timezone for scheduling")
+        next_run_at: Optional[str] = SchemaField(
+            description="When the monitor will next run"
+        )
+        last_run: Optional[dict] = SchemaField(
+            description="Information about the last run"
+        )
+        created_at: str = SchemaField(description="When the monitor was created")
+        updated_at: str = SchemaField(description="When the monitor was last updated")
+        metadata: dict = SchemaField(description="Metadata attached to the monitor")
+
+    def __init__(self):
+        super().__init__(
+            id="5c852a2d-d505-4a56-b711-7def8dd14e72",
+            description="Get the details and status of a webset monitor",
+            categories={BlockCategory.SEARCH},
+            input_schema=ExaGetMonitorBlock.Input,
+            output_schema=ExaGetMonitorBlock.Output,
+        )
+
+    async def run(
+        self, input_data: Input, *, credentials: APIKeyCredentials, **kwargs
+    ) -> BlockOutput:
+        # Use AsyncExa SDK
+        aexa = AsyncExa(api_key=credentials.api_key.get_secret_value())
+
+        sdk_monitor = aexa.websets.monitors.get(monitor_id=input_data.monitor_id)
+
+        monitor = MonitorModel.from_sdk(sdk_monitor)
+
+        # Yield all fields
+        yield "monitor_id", monitor.id
+        yield "webset_id", monitor.webset_id
+        yield "status", monitor.status
+        yield "behavior_type", monitor.behavior_type
+        yield "behavior_config", monitor.behavior_config
+        yield "cron_expression", monitor.cron_expression
+        yield "timezone", monitor.timezone
+        yield "next_run_at", monitor.next_run_at
+        yield "last_run", monitor.last_run
+        yield "created_at", monitor.created_at
+        yield "updated_at", monitor.updated_at
+        yield "metadata", monitor.metadata
+
+
+class ExaUpdateMonitorBlock(Block):
+    """Update a monitor's configuration."""
+
+    class Input(BlockSchemaInput):
+        credentials: CredentialsMetaInput = exa.credentials_field(
+            description="The Exa integration requires an API Key."
+        )
+        monitor_id: str = SchemaField(
+            description="The ID of the monitor to update",
+            placeholder="monitor-id",
+        )
+        status: Optional[MonitorStatus] = SchemaField(
+            default=None,
+            description="New status for the monitor",
+        )
+        cron_expression: Optional[str] = SchemaField(
+            default=None,
+            description="New cron expression for scheduling",
+        )
+        timezone: Optional[str] = SchemaField(
+            default=None,
+            description="New timezone for the schedule",
+            advanced=True,
+        )
+        metadata: Optional[dict] = SchemaField(
+            default=None,
+            description="New metadata for the monitor",
+            advanced=True,
+        )
+
+    class Output(BlockSchemaOutput):
+        monitor_id: str = SchemaField(
+            description="The unique identifier for the monitor"
+        )
+        status: str = SchemaField(description="Updated status of the monitor")
+        next_run_at: Optional[str] = SchemaField(
+            description="When the monitor will next run"
+        )
+        updated_at: str = SchemaField(description="When the monitor was updated")
+        success: str = SchemaField(description="Whether the update was successful")
+
+    def __init__(self):
+        super().__init__(
+            id="245102c3-6af3-4515-a308-c2210b7939d2",
+            description="Update a monitor's status, schedule, or metadata",
+            categories={BlockCategory.SEARCH},
+            input_schema=ExaUpdateMonitorBlock.Input,
+            output_schema=ExaUpdateMonitorBlock.Output,
+        )
+
+    async def run(
+        self, input_data: Input, *, credentials: APIKeyCredentials, **kwargs
+    ) -> BlockOutput:
+        # Use AsyncExa SDK
+        aexa = AsyncExa(api_key=credentials.api_key.get_secret_value())
+
+        # Build update payload
+        payload = {}
+
+        if input_data.status is not None:
+            payload["status"] = input_data.status.value
+
+        if input_data.cron_expression is not None or input_data.timezone is not None:
+            cadence = {}
+            if input_data.cron_expression:
+                cadence["cron"] = input_data.cron_expression
+            if input_data.timezone:
+                cadence["timezone"] = input_data.timezone
+            payload["cadence"] = cadence
+
+        if input_data.metadata is not None:
+            payload["metadata"] = input_data.metadata
+
+        sdk_monitor = aexa.websets.monitors.update(
+            monitor_id=input_data.monitor_id, params=payload
+        )
+
+        # Convert to our stable model
+        monitor = MonitorModel.from_sdk(sdk_monitor)
+
+        # Yield fields
+        yield "monitor_id", monitor.id
+        yield "status", monitor.status
+        yield "next_run_at", monitor.next_run_at
+        yield "updated_at", monitor.updated_at
+        yield "success", "true"
+
+
+class ExaDeleteMonitorBlock(Block):
+    """Delete a monitor from a webset."""
+
+    class Input(BlockSchemaInput):
+        credentials: CredentialsMetaInput = exa.credentials_field(
+            description="The Exa integration requires an API Key."
+        )
+        monitor_id: str = SchemaField(
+            description="The ID of the monitor to delete",
+            placeholder="monitor-id",
+        )
+
+    class Output(BlockSchemaOutput):
+        monitor_id: str = SchemaField(description="The ID of the deleted monitor")
+        success: str = SchemaField(description="Whether the deletion was successful")
+
+    def __init__(self):
+        super().__init__(
+            id="f16f9b10-0c4d-4db8-997d-7b96b6026094",
+            description="Delete a monitor from a webset",
+            categories={BlockCategory.SEARCH},
+            input_schema=ExaDeleteMonitorBlock.Input,
+            output_schema=ExaDeleteMonitorBlock.Output,
+        )
+
+    async def run(
+        self, input_data: Input, *, credentials: APIKeyCredentials, **kwargs
+    ) -> BlockOutput:
+        # Use AsyncExa SDK
+        aexa = AsyncExa(api_key=credentials.api_key.get_secret_value())
+
+        deleted_monitor = aexa.websets.monitors.delete(monitor_id=input_data.monitor_id)
+
+        yield "monitor_id", deleted_monitor.id
+        yield "success", "true"
+
+
+class ExaListMonitorsBlock(Block):
+    """List all monitors with pagination."""
+
+    class Input(BlockSchemaInput):
+        credentials: CredentialsMetaInput = exa.credentials_field(
+            description="The Exa integration requires an API Key."
+        )
+        webset_id: Optional[str] = SchemaField(
+            default=None,
+            description="Filter monitors by webset ID",
+            placeholder="webset-id",
+        )
+        limit: int = SchemaField(
+            default=25,
+            description="Number of monitors to return",
+            ge=1,
+            le=100,
+        )
+        cursor: Optional[str] = SchemaField(
+            default=None,
+            description="Cursor for pagination",
+            advanced=True,
+        )
+
+    class Output(BlockSchemaOutput):
+        monitors: list[dict] = SchemaField(description="List of monitors")
+        monitor: dict = SchemaField(
+            description="Individual monitor (yielded for each monitor)"
+        )
+        has_more: bool = SchemaField(
+            description="Whether there are more monitors to paginate through"
+        )
+        next_cursor: Optional[str] = SchemaField(
+            description="Cursor for the next page of results"
+        )
+
+    def __init__(self):
+        super().__init__(
+            id="f06e2b38-5397-4e8f-aa85-491149dd98df",
+            description="List all monitors with optional webset filtering",
+            categories={BlockCategory.SEARCH},
+            input_schema=ExaListMonitorsBlock.Input,
+            output_schema=ExaListMonitorsBlock.Output,
+        )
+
+    async def run(
+        self, input_data: Input, *, credentials: APIKeyCredentials, **kwargs
+    ) -> BlockOutput:
+        # Use AsyncExa SDK
+        aexa = AsyncExa(api_key=credentials.api_key.get_secret_value())
+
+        response = aexa.websets.monitors.list(
+            cursor=input_data.cursor,
+            limit=input_data.limit,
+            webset_id=input_data.webset_id,
+        )
+
+        # Convert SDK monitors to our stable models
+        monitors = [MonitorModel.from_sdk(m) for m in response.data]
+
+        # Yield the full list
+        yield "monitors", [m.model_dump() for m in monitors]
+
+        # Yield individual monitors for graph chaining
+        for monitor in monitors:
+            yield "monitor", monitor.model_dump()
+
+        # Yield pagination metadata
+        yield "has_more", response.has_more
+        yield "next_cursor", response.next_cursor

autogpt_platform/backend/backend/blocks/exa/websets_polling.py

@@ -0,0 +1,600 @@
+"""
+Exa Websets Polling Blocks
+
+This module provides dedicated polling blocks for waiting on webset operations
+to complete, with progress tracking and timeout management.
+"""
+
+import asyncio
+import time
+from enum import Enum
+from typing import Any, Dict
+
+from exa_py import AsyncExa
+from pydantic import BaseModel
+
+from backend.sdk import (
+    APIKeyCredentials,
+    Block,
+    BlockCategory,
+    BlockOutput,
+    BlockSchemaInput,
+    BlockSchemaOutput,
+    CredentialsMetaInput,
+    SchemaField,
+)
+
+from ._config import exa
+
+# Import WebsetItemModel for use in enrichment samples
+# This is safe as websets_items doesn't import from websets_polling
+from .websets_items import WebsetItemModel
+
+
+# Model for sample enrichment data
+class SampleEnrichmentModel(BaseModel):
+    """Sample enrichment result for display."""
+
+    item_id: str
+    item_title: str
+    enrichment_data: Dict[str, Any]
+
+
+class WebsetTargetStatus(str, Enum):
+    IDLE = "idle"
+    COMPLETED = "completed"
+    RUNNING = "running"
+    PAUSED = "paused"
+    ANY_COMPLETE = "any_complete"  # Either idle or completed
+
+
+class ExaWaitForWebsetBlock(Block):
+    """Wait for a webset to reach a specific status with progress tracking."""
+
+    class Input(BlockSchemaInput):
+        credentials: CredentialsMetaInput = exa.credentials_field(
+            description="The Exa integration requires an API Key."
+        )
+        webset_id: str = SchemaField(
+            description="The ID or external ID of the Webset to monitor",
+            placeholder="webset-id-or-external-id",
+        )
+        target_status: WebsetTargetStatus = SchemaField(
+            default=WebsetTargetStatus.IDLE,
+            description="Status to wait for (idle=all operations complete, completed=search done, running=actively processing)",
+        )
+        timeout: int = SchemaField(
+            default=300,
+            description="Maximum time to wait in seconds",
+            ge=1,
+            le=1800,  # 30 minutes max
+        )
+        check_interval: int = SchemaField(
+            default=5,
+            description="Initial interval between status checks in seconds",
+            advanced=True,
+            ge=1,
+            le=60,
+        )
+        max_interval: int = SchemaField(
+            default=30,
+            description="Maximum interval between checks (for exponential backoff)",
+            advanced=True,
+            ge=5,
+            le=120,
+        )
+        include_progress: bool = SchemaField(
+            default=True,
+            description="Include detailed progress information in output",
+        )
+
+    class Output(BlockSchemaOutput):
+        webset_id: str = SchemaField(description="The webset ID that was monitored")
+        final_status: str = SchemaField(description="The final status of the webset")
+        elapsed_time: float = SchemaField(description="Total time elapsed in seconds")
+        item_count: int = SchemaField(description="Number of items found")
+        search_progress: dict = SchemaField(
+            description="Detailed search progress information"
+        )
+        enrichment_progress: dict = SchemaField(
+            description="Detailed enrichment progress information"
+        )
+        timed_out: bool = SchemaField(description="Whether the operation timed out")
+
+    def __init__(self):
+        super().__init__(
+            id="619d71e8-b72a-434d-8bd4-23376dd0342c",
+            description="Wait for a webset to reach a specific status with progress tracking",
+            categories={BlockCategory.SEARCH},
+            input_schema=ExaWaitForWebsetBlock.Input,
+            output_schema=ExaWaitForWebsetBlock.Output,
+        )
+
+    async def run(
+        self, input_data: Input, *, credentials: APIKeyCredentials, **kwargs
+    ) -> BlockOutput:
+        start_time = time.time()
+        aexa = AsyncExa(api_key=credentials.api_key.get_secret_value())
+
+        try:
+            if input_data.target_status in [
+                WebsetTargetStatus.IDLE,
+                WebsetTargetStatus.ANY_COMPLETE,
+            ]:
+                final_webset = aexa.websets.wait_until_idle(
+                    id=input_data.webset_id,
+                    timeout=input_data.timeout,
+                    poll_interval=input_data.check_interval,
+                )
+
+                elapsed = time.time() - start_time
+
+                status_str = (
+                    final_webset.status.value
+                    if hasattr(final_webset.status, "value")
+                    else str(final_webset.status)
+                )
+
+                item_count = 0
+                if final_webset.searches:
+                    for search in final_webset.searches:
+                        if search.progress:
+                            item_count += search.progress.found
+
+                # Extract progress if requested
+                search_progress = {}
+                enrichment_progress = {}
+                if input_data.include_progress:
+                    webset_dict = final_webset.model_dump(
+                        by_alias=True, exclude_none=True
+                    )
+                    search_progress = self._extract_search_progress(webset_dict)
+                    enrichment_progress = self._extract_enrichment_progress(webset_dict)
+
+                yield "webset_id", input_data.webset_id
+                yield "final_status", status_str
+                yield "elapsed_time", elapsed
+                yield "item_count", item_count
+                if input_data.include_progress:
+                    yield "search_progress", search_progress
+                    yield "enrichment_progress", enrichment_progress
+                yield "timed_out", False
+            else:
+                # For other status targets, manually poll
+                interval = input_data.check_interval
+                while time.time() - start_time < input_data.timeout:
+                    # Get current webset status
+                    webset = aexa.websets.get(id=input_data.webset_id)
+                    current_status = (
+                        webset.status.value
+                        if hasattr(webset.status, "value")
+                        else str(webset.status)
+                    )
+
+                    # Check if target status reached
+                    if current_status == input_data.target_status.value:
+                        elapsed = time.time() - start_time
+
+                        # Estimate item count from search progress
+                        item_count = 0
+                        if webset.searches:
+                            for search in webset.searches:
+                                if search.progress:
+                                    item_count += search.progress.found
+
+                        search_progress = {}
+                        enrichment_progress = {}
+                        if input_data.include_progress:
+                            webset_dict = webset.model_dump(
+                                by_alias=True, exclude_none=True
+                            )
+                            search_progress = self._extract_search_progress(webset_dict)
+                            enrichment_progress = self._extract_enrichment_progress(
+                                webset_dict
+                            )
+
+                        yield "webset_id", input_data.webset_id
+                        yield "final_status", current_status
+                        yield "elapsed_time", elapsed
+                        yield "item_count", item_count
+                        if input_data.include_progress:
+                            yield "search_progress", search_progress
+                            yield "enrichment_progress", enrichment_progress
+                        yield "timed_out", False
+                        return
+
+                    # Wait before next check with exponential backoff
+                    await asyncio.sleep(interval)
+                    interval = min(interval * 1.5, input_data.max_interval)
+
+                # Timeout reached
+                elapsed = time.time() - start_time
+                webset = aexa.websets.get(id=input_data.webset_id)
+                final_status = (
+                    webset.status.value
+                    if hasattr(webset.status, "value")
+                    else str(webset.status)
+                )
+
+                item_count = 0
+                if webset.searches:
+                    for search in webset.searches:
+                        if search.progress:
+                            item_count += search.progress.found
+
+                search_progress = {}
+                enrichment_progress = {}
+                if input_data.include_progress:
+                    webset_dict = webset.model_dump(by_alias=True, exclude_none=True)
+                    search_progress = self._extract_search_progress(webset_dict)
+                    enrichment_progress = self._extract_enrichment_progress(webset_dict)
+
+                yield "webset_id", input_data.webset_id
+                yield "final_status", final_status
+                yield "elapsed_time", elapsed
+                yield "item_count", item_count
+                if input_data.include_progress:
+                    yield "search_progress", search_progress
+                    yield "enrichment_progress", enrichment_progress
+                yield "timed_out", True
+
+        except asyncio.TimeoutError:
+            raise ValueError(
+                f"Polling timed out after {input_data.timeout} seconds"
+            ) from None
+
+    def _extract_search_progress(self, webset_data: dict) -> dict:
+        """Extract search progress information from webset data."""
+        progress = {}
+        searches = webset_data.get("searches", [])
+
+        for idx, search in enumerate(searches):
+            search_id = search.get("id", f"search_{idx}")
+            search_progress = search.get("progress", {})
+
+            progress[search_id] = {
+                "status": search.get("status", "unknown"),
+                "found": search_progress.get("found", 0),
+                "analyzed": search_progress.get("analyzed", 0),
+                "completion": search_progress.get("completion", 0),
+                "time_left": search_progress.get("timeLeft", 0),
+            }
+
+        return progress
+
+    def _extract_enrichment_progress(self, webset_data: dict) -> dict:
+        """Extract enrichment progress information from webset data."""
+        progress = {}
+        enrichments = webset_data.get("enrichments", [])
+
+        for idx, enrichment in enumerate(enrichments):
+            enrich_id = enrichment.get("id", f"enrichment_{idx}")
+
+            progress[enrich_id] = {
+                "status": enrichment.get("status", "unknown"),
+                "title": enrichment.get("title", ""),
+                "description": enrichment.get("description", ""),
+            }
+
+        return progress
+
+
+class ExaWaitForSearchBlock(Block):
+    """Wait for a specific webset search to complete with progress tracking."""
+
+    class Input(BlockSchemaInput):
+        credentials: CredentialsMetaInput = exa.credentials_field(
+            description="The Exa integration requires an API Key."
+        )
+        webset_id: str = SchemaField(
+            description="The ID or external ID of the Webset",
+            placeholder="webset-id-or-external-id",
+        )
+        search_id: str = SchemaField(
+            description="The ID of the search to monitor",
+            placeholder="search-id",
+        )
+        timeout: int = SchemaField(
+            default=300,
+            description="Maximum time to wait in seconds",
+            ge=1,
+            le=1800,
+        )
+        check_interval: int = SchemaField(
+            default=5,
+            description="Initial interval between status checks in seconds",
+            advanced=True,
+            ge=1,
+            le=60,
+        )
+
+    class Output(BlockSchemaOutput):
+        search_id: str = SchemaField(description="The search ID that was monitored")
+        final_status: str = SchemaField(description="The final status of the search")
+        items_found: int = SchemaField(
+            description="Number of items found by the search"
+        )
+        items_analyzed: int = SchemaField(description="Number of items analyzed")
+        completion_percentage: int = SchemaField(
+            description="Completion percentage (0-100)"
+        )
+        elapsed_time: float = SchemaField(description="Total time elapsed in seconds")
+        recall_info: dict = SchemaField(
+            description="Information about expected results and confidence"
+        )
+        timed_out: bool = SchemaField(description="Whether the operation timed out")
+
+    def __init__(self):
+        super().__init__(
+            id="14da21ae-40a1-41bc-a111-c8e5c9ef012b",
+            description="Wait for a specific webset search to complete with progress tracking",
+            categories={BlockCategory.SEARCH},
+            input_schema=ExaWaitForSearchBlock.Input,
+            output_schema=ExaWaitForSearchBlock.Output,
+        )
+
+    async def run(
+        self, input_data: Input, *, credentials: APIKeyCredentials, **kwargs
+    ) -> BlockOutput:
+        start_time = time.time()
+        interval = input_data.check_interval
+        max_interval = 30
+        # Use AsyncExa SDK
+        aexa = AsyncExa(api_key=credentials.api_key.get_secret_value())
+
+        try:
+            while time.time() - start_time < input_data.timeout:
+                # Get current search status using SDK
+                search = aexa.websets.searches.get(
+                    webset_id=input_data.webset_id, id=input_data.search_id
+                )
+
+                # Extract status
+                status = (
+                    search.status.value
+                    if hasattr(search.status, "value")
+                    else str(search.status)
+                )
+
+                # Check if search is complete
+                if status in ["completed", "failed", "canceled"]:
+                    elapsed = time.time() - start_time
+
+                    # Extract progress information
+                    progress_dict = {}
+                    if search.progress:
+                        progress_dict = search.progress.model_dump(
+                            by_alias=True, exclude_none=True
+                        )
+
+                    # Extract recall information
+                    recall_info = {}
+                    if search.recall:
+                        recall_dict = search.recall.model_dump(
+                            by_alias=True, exclude_none=True
+                        )
+                        expected = recall_dict.get("expected", {})
+                        recall_info = {
+                            "expected_total": expected.get("total", 0),
+                            "confidence": expected.get("confidence", ""),
+                            "min_expected": expected.get("bounds", {}).get("min", 0),
+                            "max_expected": expected.get("bounds", {}).get("max", 0),
+                            "reasoning": recall_dict.get("reasoning", ""),
+                        }
+
+                    yield "search_id", input_data.search_id
+                    yield "final_status", status
+                    yield "items_found", progress_dict.get("found", 0)
+                    yield "items_analyzed", progress_dict.get("analyzed", 0)
+                    yield "completion_percentage", progress_dict.get("completion", 0)
+                    yield "elapsed_time", elapsed
+                    yield "recall_info", recall_info
+                    yield "timed_out", False
+
+                    return
+
+                # Wait before next check with exponential backoff
+                await asyncio.sleep(interval)
+                interval = min(interval * 1.5, max_interval)
+
+            # Timeout reached
+            elapsed = time.time() - start_time
+
+            # Get last known status
+            search = aexa.websets.searches.get(
+                webset_id=input_data.webset_id, id=input_data.search_id
+            )
+            final_status = (
+                search.status.value
+                if hasattr(search.status, "value")
+                else str(search.status)
+            )
+
+            progress_dict = {}
+            if search.progress:
+                progress_dict = search.progress.model_dump(
+                    by_alias=True, exclude_none=True
+                )
+
+            yield "search_id", input_data.search_id
+            yield "final_status", final_status
+            yield "items_found", progress_dict.get("found", 0)
+            yield "items_analyzed", progress_dict.get("analyzed", 0)
+            yield "completion_percentage", progress_dict.get("completion", 0)
+            yield "elapsed_time", elapsed
+            yield "timed_out", True
+
+        except asyncio.TimeoutError:
+            raise ValueError(
+                f"Search polling timed out after {input_data.timeout} seconds"
+            ) from None
+
+
+class ExaWaitForEnrichmentBlock(Block):
+    """Wait for a webset enrichment to complete with progress tracking."""
+
+    class Input(BlockSchemaInput):
+        credentials: CredentialsMetaInput = exa.credentials_field(
+            description="The Exa integration requires an API Key."
+        )
+        webset_id: str = SchemaField(
+            description="The ID or external ID of the Webset",
+            placeholder="webset-id-or-external-id",
+        )
+        enrichment_id: str = SchemaField(
+            description="The ID of the enrichment to monitor",
+            placeholder="enrichment-id",
+        )
+        timeout: int = SchemaField(
+            default=300,
+            description="Maximum time to wait in seconds",
+            ge=1,
+            le=1800,
+        )
+        check_interval: int = SchemaField(
+            default=5,
+            description="Initial interval between status checks in seconds",
+            advanced=True,
+            ge=1,
+            le=60,
+        )
+        sample_results: bool = SchemaField(
+            default=True,
+            description="Include sample enrichment results in output",
+        )
+
+    class Output(BlockSchemaOutput):
+        enrichment_id: str = SchemaField(
+            description="The enrichment ID that was monitored"
+        )
+        final_status: str = SchemaField(
+            description="The final status of the enrichment"
+        )
+        items_enriched: int = SchemaField(
+            description="Number of items successfully enriched"
+        )
+        enrichment_title: str = SchemaField(
+            description="Title/description of the enrichment"
+        )
+        elapsed_time: float = SchemaField(description="Total time elapsed in seconds")
+        sample_data: list[SampleEnrichmentModel] = SchemaField(
+            description="Sample of enriched data (if requested)"
+        )
+        timed_out: bool = SchemaField(description="Whether the operation timed out")
+
+    def __init__(self):
+        super().__init__(
+            id="a11865c3-ac80-4721-8a40-ac4e3b71a558",
+            description="Wait for a webset enrichment to complete with progress tracking",
+            categories={BlockCategory.SEARCH},
+            input_schema=ExaWaitForEnrichmentBlock.Input,
+            output_schema=ExaWaitForEnrichmentBlock.Output,
+        )
+
+    async def run(
+        self, input_data: Input, *, credentials: APIKeyCredentials, **kwargs
+    ) -> BlockOutput:
+        start_time = time.time()
+        interval = input_data.check_interval
+        max_interval = 30
+        # Use AsyncExa SDK
+        aexa = AsyncExa(api_key=credentials.api_key.get_secret_value())
+
+        try:
+            while time.time() - start_time < input_data.timeout:
+                # Get current enrichment status using SDK
+                enrichment = aexa.websets.enrichments.get(
+                    webset_id=input_data.webset_id, id=input_data.enrichment_id
+                )
+
+                # Extract status
+                status = (
+                    enrichment.status.value
+                    if hasattr(enrichment.status, "value")
+                    else str(enrichment.status)
+                )
+
+                # Check if enrichment is complete
+                if status in ["completed", "failed", "canceled"]:
+                    elapsed = time.time() - start_time
+
+                    # Get sample enriched items if requested
+                    sample_data = []
+                    items_enriched = 0
+
+                    if input_data.sample_results and status == "completed":
+                        sample_data, items_enriched = (
+                            await self._get_sample_enrichments(
+                                input_data.webset_id, input_data.enrichment_id, aexa
+                            )
+                        )
+
+                    yield "enrichment_id", input_data.enrichment_id
+                    yield "final_status", status
+                    yield "items_enriched", items_enriched
+                    yield "enrichment_title", enrichment.title or enrichment.description or ""
+                    yield "elapsed_time", elapsed
+                    if input_data.sample_results:
+                        yield "sample_data", sample_data
+                    yield "timed_out", False
+
+                    return
+
+                # Wait before next check with exponential backoff
+                await asyncio.sleep(interval)
+                interval = min(interval * 1.5, max_interval)
+
+            # Timeout reached
+            elapsed = time.time() - start_time
+
+            # Get last known status
+            enrichment = aexa.websets.enrichments.get(
+                webset_id=input_data.webset_id, id=input_data.enrichment_id
+            )
+            final_status = (
+                enrichment.status.value
+                if hasattr(enrichment.status, "value")
+                else str(enrichment.status)
+            )
+            title = enrichment.title or enrichment.description or ""
+
+            yield "enrichment_id", input_data.enrichment_id
+            yield "final_status", final_status
+            yield "items_enriched", 0
+            yield "enrichment_title", title
+            yield "elapsed_time", elapsed
+            yield "timed_out", True
+
+        except asyncio.TimeoutError:
+            raise ValueError(
+                f"Enrichment polling timed out after {input_data.timeout} seconds"
+            ) from None
+
+    async def _get_sample_enrichments(
+        self, webset_id: str, enrichment_id: str, aexa: AsyncExa
+    ) -> tuple[list[SampleEnrichmentModel], int]:
+        """Get sample enriched data and count."""
+        # Get a few items to see enrichment results using SDK
+        response = aexa.websets.items.list(webset_id=webset_id, limit=5)
+
+        sample_data: list[SampleEnrichmentModel] = []
+        enriched_count = 0
+
+        for sdk_item in response.data:
+            # Convert to our WebsetItemModel first
+            item = WebsetItemModel.from_sdk(sdk_item)
+
+            # Check if this item has the enrichment we're looking for
+            if enrichment_id in item.enrichments:
+                enriched_count += 1
+                enrich_model = item.enrichments[enrichment_id]
+
+                # Create sample using our typed model
+                sample = SampleEnrichmentModel(
+                    item_id=item.id,
+                    item_title=item.title,
+                    enrichment_data=enrich_model.model_dump(exclude_none=True),
+                )
+                sample_data.append(sample)
+
+        return sample_data, enriched_count

autogpt_platform/backend/backend/blocks/exa/websets_search.py

@@ -0,0 +1,650 @@
+"""
+Exa Websets Search Management Blocks
+
+This module provides blocks for creating and managing searches within websets,
+including adding new searches, checking status, and canceling operations.
+"""
+
+from enum import Enum
+from typing import Any, Dict, List, Optional
+
+from exa_py import AsyncExa
+from exa_py.websets.types import WebsetSearch as SdkWebsetSearch
+from pydantic import BaseModel
+
+from backend.sdk import (
+    APIKeyCredentials,
+    Block,
+    BlockCategory,
+    BlockOutput,
+    BlockSchemaInput,
+    BlockSchemaOutput,
+    CredentialsMetaInput,
+    SchemaField,
+)
+
+from ._config import exa
+
+
+# Mirrored model for stability
+class WebsetSearchModel(BaseModel):
+    """Stable output model mirroring SDK WebsetSearch."""
+
+    id: str
+    webset_id: str
+    status: str
+    query: str
+    entity_type: str
+    criteria: List[Dict[str, Any]]
+    count: int
+    behavior: str
+    progress: Dict[str, Any]
+    recall: Optional[Dict[str, Any]]
+    created_at: str
+    updated_at: str
+    canceled_at: Optional[str]
+    canceled_reason: Optional[str]
+    metadata: Dict[str, Any]
+
+    @classmethod
+    def from_sdk(cls, search: SdkWebsetSearch) -> "WebsetSearchModel":
+        """Convert SDK WebsetSearch to our stable model."""
+        # Extract entity type
+        entity_type = "auto"
+        if search.entity:
+            entity_dict = search.entity.model_dump(by_alias=True)
+            entity_type = entity_dict.get("type", "auto")
+
+        # Convert criteria
+        criteria = [c.model_dump(by_alias=True) for c in search.criteria]
+
+        # Convert progress
+        progress_dict = {}
+        if search.progress:
+            progress_dict = search.progress.model_dump(by_alias=True)
+
+        # Convert recall
+        recall_dict = None
+        if search.recall:
+            recall_dict = search.recall.model_dump(by_alias=True)
+
+        return cls(
+            id=search.id,
+            webset_id=search.webset_id,
+            status=(
+                search.status.value
+                if hasattr(search.status, "value")
+                else str(search.status)
+            ),
+            query=search.query,
+            entity_type=entity_type,
+            criteria=criteria,
+            count=search.count,
+            behavior=search.behavior.value if search.behavior else "override",
+            progress=progress_dict,
+            recall=recall_dict,
+            created_at=search.created_at.isoformat() if search.created_at else "",
+            updated_at=search.updated_at.isoformat() if search.updated_at else "",
+            canceled_at=search.canceled_at.isoformat() if search.canceled_at else None,
+            canceled_reason=(
+                search.canceled_reason.value if search.canceled_reason else None
+            ),
+            metadata=search.metadata if search.metadata else {},
+        )
+
+
+class SearchBehavior(str, Enum):
+    """Behavior for how new search results interact with existing items."""
+
+    OVERRIDE = "override"  # Replace existing items
+    APPEND = "append"  # Add to existing items
+    MERGE = "merge"  # Merge with existing items
+
+
+class SearchEntityType(str, Enum):
+    COMPANY = "company"
+    PERSON = "person"
+    ARTICLE = "article"
+    RESEARCH_PAPER = "research_paper"
+    CUSTOM = "custom"
+    AUTO = "auto"
+
+
+class ExaCreateWebsetSearchBlock(Block):
+    """Add a new search to an existing webset."""
+
+    class Input(BlockSchemaInput):
+        credentials: CredentialsMetaInput = exa.credentials_field(
+            description="The Exa integration requires an API Key."
+        )
+        webset_id: str = SchemaField(
+            description="The ID or external ID of the Webset",
+            placeholder="webset-id-or-external-id",
+        )
+        query: str = SchemaField(
+            description="Search query describing what to find",
+            placeholder="Engineering managers at Fortune 500 companies",
+        )
+        count: int = SchemaField(
+            default=10,
+            description="Number of items to find",
+            ge=1,
+            le=1000,
+        )
+
+        # Entity configuration
+        entity_type: SearchEntityType = SchemaField(
+            default=SearchEntityType.AUTO,
+            description="Type of entity to search for",
+        )
+        entity_description: Optional[str] = SchemaField(
+            default=None,
+            description="Description for custom entity type",
+            advanced=True,
+        )
+
+        # Criteria for verification
+        criteria: list[str] = SchemaField(
+            default_factory=list,
+            description="List of criteria that items must meet. If not provided, auto-detected from query.",
+            advanced=True,
+        )
+
+        # Advanced search options
+        behavior: SearchBehavior = SchemaField(
+            default=SearchBehavior.APPEND,
+            description="How new results interact with existing items",
+            advanced=True,
+        )
+        recall: bool = SchemaField(
+            default=True,
+            description="Enable recall estimation for expected results",
+            advanced=True,
+        )
+
+        # Exclude sources
+        exclude_source_ids: list[str] = SchemaField(
+            default_factory=list,
+            description="IDs of imports/websets to exclude from results",
+            advanced=True,
+        )
+        exclude_source_types: list[str] = SchemaField(
+            default_factory=list,
+            description="Types of sources to exclude ('import' or 'webset')",
+            advanced=True,
+        )
+
+        # Scope sources
+        scope_source_ids: list[str] = SchemaField(
+            default_factory=list,
+            description="IDs of imports/websets to limit search scope to",
+            advanced=True,
+        )
+        scope_source_types: list[str] = SchemaField(
+            default_factory=list,
+            description="Types of scope sources ('import' or 'webset')",
+            advanced=True,
+        )
+        scope_relationships: list[str] = SchemaField(
+            default_factory=list,
+            description="Relationship definitions for hop searches",
+            advanced=True,
+        )
+        scope_relationship_limits: list[int] = SchemaField(
+            default_factory=list,
+            description="Limits on related entities to find",
+            advanced=True,
+        )
+
+        metadata: Optional[dict] = SchemaField(
+            default=None,
+            description="Metadata to attach to the search",
+            advanced=True,
+        )
+
+        # Polling options
+        wait_for_completion: bool = SchemaField(
+            default=False,
+            description="Wait for the search to complete before returning",
+        )
+        polling_timeout: int = SchemaField(
+            default=300,
+            description="Maximum time to wait for completion in seconds",
+            advanced=True,
+            ge=1,
+            le=600,
+        )
+
+    class Output(BlockSchemaOutput):
+        search_id: str = SchemaField(
+            description="The unique identifier for the created search"
+        )
+        webset_id: str = SchemaField(description="The webset this search belongs to")
+        status: str = SchemaField(description="Current status of the search")
+        query: str = SchemaField(description="The search query")
+        expected_results: dict = SchemaField(
+            description="Recall estimation of expected results"
+        )
+        items_found: Optional[int] = SchemaField(
+            description="Number of items found (if wait_for_completion was True)"
+        )
+        completion_time: Optional[float] = SchemaField(
+            description="Time taken to complete in seconds (if wait_for_completion was True)"
+        )
+
+    def __init__(self):
+        super().__init__(
+            id="342ff776-2e2c-4cdb-b392-4eeb34b21d5f",
+            description="Add a new search to an existing webset to find more items",
+            categories={BlockCategory.SEARCH},
+            input_schema=ExaCreateWebsetSearchBlock.Input,
+            output_schema=ExaCreateWebsetSearchBlock.Output,
+        )
+
+    async def run(
+        self, input_data: Input, *, credentials: APIKeyCredentials, **kwargs
+    ) -> BlockOutput:
+        import time
+
+        # Build the payload
+        payload = {
+            "query": input_data.query,
+            "count": input_data.count,
+            "behavior": input_data.behavior.value,
+            "recall": input_data.recall,
+        }
+
+        # Add entity configuration
+        if input_data.entity_type != SearchEntityType.AUTO:
+            entity = {"type": input_data.entity_type.value}
+            if (
+                input_data.entity_type == SearchEntityType.CUSTOM
+                and input_data.entity_description
+            ):
+                entity["description"] = input_data.entity_description
+            payload["entity"] = entity
+
+        # Add criteria if provided
+        if input_data.criteria:
+            payload["criteria"] = [{"description": c} for c in input_data.criteria]
+
+        # Add exclude sources
+        if input_data.exclude_source_ids:
+            exclude_list = []
+            for idx, src_id in enumerate(input_data.exclude_source_ids):
+                src_type = "import"
+                if input_data.exclude_source_types and idx < len(
+                    input_data.exclude_source_types
+                ):
+                    src_type = input_data.exclude_source_types[idx]
+                exclude_list.append({"source": src_type, "id": src_id})
+            payload["exclude"] = exclude_list
+
+        # Add scope sources
+        if input_data.scope_source_ids:
+            scope_list: list[dict[str, Any]] = []
+            for idx, src_id in enumerate(input_data.scope_source_ids):
+                scope_item: dict[str, Any] = {"source": "import", "id": src_id}
+
+                if input_data.scope_source_types and idx < len(
+                    input_data.scope_source_types
+                ):
+                    scope_item["source"] = input_data.scope_source_types[idx]
+
+                # Add relationship if provided
+                if input_data.scope_relationships and idx < len(
+                    input_data.scope_relationships
+                ):
+                    relationship: dict[str, Any] = {
+                        "definition": input_data.scope_relationships[idx]
+                    }
+                    if input_data.scope_relationship_limits and idx < len(
+                        input_data.scope_relationship_limits
+                    ):
+                        relationship["limit"] = input_data.scope_relationship_limits[
+                            idx
+                        ]
+                    scope_item["relationship"] = relationship
+
+                scope_list.append(scope_item)
+            payload["scope"] = scope_list
+
+        # Add metadata if provided
+        if input_data.metadata:
+            payload["metadata"] = input_data.metadata
+
+        start_time = time.time()
+
+        aexa = AsyncExa(api_key=credentials.api_key.get_secret_value())
+
+        sdk_search = aexa.websets.searches.create(
+            webset_id=input_data.webset_id, params=payload
+        )
+
+        search_id = sdk_search.id
+        status = (
+            sdk_search.status.value
+            if hasattr(sdk_search.status, "value")
+            else str(sdk_search.status)
+        )
+
+        # Extract expected results from recall
+        expected_results = {}
+        if sdk_search.recall:
+            recall_dict = sdk_search.recall.model_dump(by_alias=True)
+            expected = recall_dict.get("expected", {})
+            expected_results = {
+                "total": expected.get("total", 0),
+                "confidence": expected.get("confidence", ""),
+                "min": expected.get("bounds", {}).get("min", 0),
+                "max": expected.get("bounds", {}).get("max", 0),
+                "reasoning": recall_dict.get("reasoning", ""),
+            }
+
+        # If wait_for_completion is True, poll for completion
+        if input_data.wait_for_completion:
+            import asyncio
+
+            poll_interval = 5
+            max_interval = 30
+            poll_start = time.time()
+
+            while time.time() - poll_start < input_data.polling_timeout:
+                current_search = aexa.websets.searches.get(
+                    webset_id=input_data.webset_id, id=search_id
+                )
+                current_status = (
+                    current_search.status.value
+                    if hasattr(current_search.status, "value")
+                    else str(current_search.status)
+                )
+
+                if current_status in ["completed", "failed", "cancelled"]:
+                    items_found = 0
+                    if current_search.progress:
+                        items_found = current_search.progress.found
+                    completion_time = time.time() - start_time
+
+                    yield "search_id", search_id
+                    yield "webset_id", input_data.webset_id
+                    yield "status", current_status
+                    yield "query", input_data.query
+                    yield "expected_results", expected_results
+                    yield "items_found", items_found
+                    yield "completion_time", completion_time
+                    return
+
+                await asyncio.sleep(poll_interval)
+                poll_interval = min(poll_interval * 1.5, max_interval)
+
+            # Timeout - yield what we have
+            yield "search_id", search_id
+            yield "webset_id", input_data.webset_id
+            yield "status", status
+            yield "query", input_data.query
+            yield "expected_results", expected_results
+            yield "items_found", 0
+            yield "completion_time", time.time() - start_time
+        else:
+            yield "search_id", search_id
+            yield "webset_id", input_data.webset_id
+            yield "status", status
+            yield "query", input_data.query
+            yield "expected_results", expected_results
+
+
+class ExaGetWebsetSearchBlock(Block):
+    """Get the status and details of a webset search."""
+
+    class Input(BlockSchemaInput):
+        credentials: CredentialsMetaInput = exa.credentials_field(
+            description="The Exa integration requires an API Key."
+        )
+        webset_id: str = SchemaField(
+            description="The ID or external ID of the Webset",
+            placeholder="webset-id-or-external-id",
+        )
+        search_id: str = SchemaField(
+            description="The ID of the search to retrieve",
+            placeholder="search-id",
+        )
+
+    class Output(BlockSchemaOutput):
+        search_id: str = SchemaField(description="The unique identifier for the search")
+        status: str = SchemaField(description="Current status of the search")
+        query: str = SchemaField(description="The search query")
+        entity_type: str = SchemaField(description="Type of entity being searched")
+        criteria: list[dict] = SchemaField(description="Criteria used for verification")
+        progress: dict = SchemaField(description="Search progress information")
+        recall: dict = SchemaField(description="Recall estimation information")
+        created_at: str = SchemaField(description="When the search was created")
+        updated_at: str = SchemaField(description="When the search was last updated")
+        canceled_at: Optional[str] = SchemaField(
+            description="When the search was canceled (if applicable)"
+        )
+        canceled_reason: Optional[str] = SchemaField(
+            description="Reason for cancellation (if applicable)"
+        )
+        metadata: dict = SchemaField(description="Metadata attached to the search")
+
+    def __init__(self):
+        super().__init__(
+            id="4fa3e627-a0ff-485f-8732-52148051646c",
+            description="Get the status and details of a webset search",
+            categories={BlockCategory.SEARCH},
+            input_schema=ExaGetWebsetSearchBlock.Input,
+            output_schema=ExaGetWebsetSearchBlock.Output,
+        )
+
+    async def run(
+        self, input_data: Input, *, credentials: APIKeyCredentials, **kwargs
+    ) -> BlockOutput:
+        # Use AsyncExa SDK
+        aexa = AsyncExa(api_key=credentials.api_key.get_secret_value())
+
+        sdk_search = aexa.websets.searches.get(
+            webset_id=input_data.webset_id, id=input_data.search_id
+        )
+
+        search = WebsetSearchModel.from_sdk(sdk_search)
+
+        # Extract progress information
+        progress_info = {
+            "found": search.progress.get("found", 0),
+            "analyzed": search.progress.get("analyzed", 0),
+            "completion": search.progress.get("completion", 0),
+            "time_left": search.progress.get("timeLeft", 0),
+        }
+
+        # Extract recall information
+        recall_data = {}
+        if search.recall:
+            expected = search.recall.get("expected", {})
+            recall_data = {
+                "expected_total": expected.get("total", 0),
+                "confidence": expected.get("confidence", ""),
+                "min_expected": expected.get("bounds", {}).get("min", 0),
+                "max_expected": expected.get("bounds", {}).get("max", 0),
+                "reasoning": search.recall.get("reasoning", ""),
+            }
+
+        yield "search_id", search.id
+        yield "status", search.status
+        yield "query", search.query
+        yield "entity_type", search.entity_type
+        yield "criteria", search.criteria
+        yield "progress", progress_info
+        yield "recall", recall_data
+        yield "created_at", search.created_at
+        yield "updated_at", search.updated_at
+        yield "canceled_at", search.canceled_at
+        yield "canceled_reason", search.canceled_reason
+        yield "metadata", search.metadata
+
+
+class ExaCancelWebsetSearchBlock(Block):
+    """Cancel a running webset search."""
+
+    class Input(BlockSchemaInput):
+        credentials: CredentialsMetaInput = exa.credentials_field(
+            description="The Exa integration requires an API Key."
+        )
+        webset_id: str = SchemaField(
+            description="The ID or external ID of the Webset",
+            placeholder="webset-id-or-external-id",
+        )
+        search_id: str = SchemaField(
+            description="The ID of the search to cancel",
+            placeholder="search-id",
+        )
+
+    class Output(BlockSchemaOutput):
+        search_id: str = SchemaField(description="The ID of the canceled search")
+        status: str = SchemaField(description="Status after cancellation")
+        items_found_before_cancel: int = SchemaField(
+            description="Number of items found before cancellation"
+        )
+        success: str = SchemaField(
+            description="Whether the cancellation was successful"
+        )
+
+    def __init__(self):
+        super().__init__(
+            id="74ef9f1e-ae89-4c7f-9d7d-d217214815b4",
+            description="Cancel a running webset search",
+            categories={BlockCategory.SEARCH},
+            input_schema=ExaCancelWebsetSearchBlock.Input,
+            output_schema=ExaCancelWebsetSearchBlock.Output,
+        )
+
+    async def run(
+        self, input_data: Input, *, credentials: APIKeyCredentials, **kwargs
+    ) -> BlockOutput:
+        # Use AsyncExa SDK
+        aexa = AsyncExa(api_key=credentials.api_key.get_secret_value())
+
+        canceled_search = aexa.websets.searches.cancel(
+            webset_id=input_data.webset_id, id=input_data.search_id
+        )
+
+        # Extract items found before cancellation
+        items_found = 0
+        if canceled_search.progress:
+            items_found = canceled_search.progress.found
+
+        status = (
+            canceled_search.status.value
+            if hasattr(canceled_search.status, "value")
+            else str(canceled_search.status)
+        )
+
+        yield "search_id", canceled_search.id
+        yield "status", status
+        yield "items_found_before_cancel", items_found
+        yield "success", "true"
+
+
+class ExaFindOrCreateSearchBlock(Block):
+    """Find existing search by query or create new one (prevents duplicate searches)."""
+
+    class Input(BlockSchemaInput):
+        credentials: CredentialsMetaInput = exa.credentials_field(
+            description="The Exa integration requires an API Key."
+        )
+        webset_id: str = SchemaField(
+            description="The ID or external ID of the Webset",
+            placeholder="webset-id-or-external-id",
+        )
+        query: str = SchemaField(
+            description="Search query to find or create",
+            placeholder="AI companies in San Francisco",
+        )
+        count: int = SchemaField(
+            default=10,
+            description="Number of items to find (only used if creating new search)",
+            ge=1,
+            le=1000,
+        )
+        entity_type: SearchEntityType = SchemaField(
+            default=SearchEntityType.AUTO,
+            description="Entity type (only used if creating)",
+            advanced=True,
+        )
+        behavior: SearchBehavior = SchemaField(
+            default=SearchBehavior.OVERRIDE,
+            description="Search behavior (only used if creating)",
+            advanced=True,
+        )
+
+    class Output(BlockSchemaOutput):
+        search_id: str = SchemaField(description="The search ID (existing or new)")
+        webset_id: str = SchemaField(description="The webset ID")
+        status: str = SchemaField(description="Current search status")
+        query: str = SchemaField(description="The search query")
+        was_created: bool = SchemaField(
+            description="True if search was newly created, False if already existed"
+        )
+        items_found: int = SchemaField(
+            description="Number of items found (0 if still running)"
+        )
+
+    def __init__(self):
+        super().__init__(
+            id="cbdb05ac-cb73-4b03-a493-6d34e9a011da",
+            description="Find existing search by query or create new - prevents duplicate searches in workflows",
+            categories={BlockCategory.SEARCH},
+            input_schema=ExaFindOrCreateSearchBlock.Input,
+            output_schema=ExaFindOrCreateSearchBlock.Output,
+        )
+
+    async def run(
+        self, input_data: Input, *, credentials: APIKeyCredentials, **kwargs
+    ) -> BlockOutput:
+        # Use AsyncExa SDK
+        aexa = AsyncExa(api_key=credentials.api_key.get_secret_value())
+
+        # Get webset to check existing searches
+        webset = aexa.websets.get(id=input_data.webset_id)
+
+        # Look for existing search with same query
+        existing_search = None
+        if webset.searches:
+            for search in webset.searches:
+                if search.query.strip().lower() == input_data.query.strip().lower():
+                    existing_search = search
+                    break
+
+        if existing_search:
+            # Found existing search
+            search = WebsetSearchModel.from_sdk(existing_search)
+
+            yield "search_id", search.id
+            yield "webset_id", input_data.webset_id
+            yield "status", search.status
+            yield "query", search.query
+            yield "was_created", False
+            yield "items_found", search.progress.get("found", 0)
+        else:
+            # Create new search
+            payload: Dict[str, Any] = {
+                "query": input_data.query,
+                "count": input_data.count,
+                "behavior": input_data.behavior.value,
+            }
+
+            # Add entity if not auto
+            if input_data.entity_type != SearchEntityType.AUTO:
+                payload["entity"] = {"type": input_data.entity_type.value}
+
+            sdk_search = aexa.websets.searches.create(
+                webset_id=input_data.webset_id, params=payload
+            )
+
+            search = WebsetSearchModel.from_sdk(sdk_search)
+
+            yield "search_id", search.id
+            yield "webset_id", input_data.webset_id
+            yield "status", search.status
+            yield "query", search.query
+            yield "was_created", True
+            yield "items_found", 0  # Newly created, no items yet

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

@@ -10,7 +10,13 @@ from backend.blocks.fal._auth import (
     FalCredentialsField,
     FalCredentialsInput,
 )
-from backend.data.block import Block, BlockCategory, BlockOutput, BlockSchema
+from backend.data.block import (
+    Block,
+    BlockCategory,
+    BlockOutput,
+    BlockSchemaInput,
+    BlockSchemaOutput,
+)
 from backend.data.model import SchemaField
 from backend.util.request import ClientResponseError, Requests
 
@@ -24,7 +30,7 @@ class FalModel(str, Enum):
 
 
 class AIVideoGeneratorBlock(Block):
-    class Input(BlockSchema):
+    class Input(BlockSchemaInput):
         prompt: str = SchemaField(
             description="Description of the video to generate.",
             placeholder="A dog running in a field.",
@@ -36,7 +42,7 @@ class AIVideoGeneratorBlock(Block):
         )
         credentials: FalCredentialsInput = FalCredentialsField()
 
-    class Output(BlockSchema):
+    class Output(BlockSchemaOutput):
         video_url: str = SchemaField(description="The URL of the generated video.")
         error: str = SchemaField(
             description="Error message if video generation failed."

autogpt_platform/backend/backend/blocks/firecrawl/crawl.py

@@ -9,7 +9,8 @@ from backend.sdk import (
     Block,
     BlockCategory,
     BlockOutput,
-    BlockSchema,
+    BlockSchemaInput,
+    BlockSchemaOutput,
     CredentialsMetaInput,
     SchemaField,
 )
@@ -19,7 +20,7 @@ from ._format_utils import convert_to_format_options
 
 
 class FirecrawlCrawlBlock(Block):
-    class Input(BlockSchema):
+    class Input(BlockSchemaInput):
         credentials: CredentialsMetaInput = firecrawl.credentials_field()
         url: str = SchemaField(description="The URL to crawl")
         limit: int = SchemaField(description="The number of pages to crawl", default=10)
@@ -39,7 +40,7 @@ class FirecrawlCrawlBlock(Block):
             description="The format of the crawl", default=[ScrapeFormat.MARKDOWN]
         )
 
-    class Output(BlockSchema):
+    class Output(BlockSchemaOutput):
         data: list[dict[str, Any]] = SchemaField(description="The result of the crawl")
         markdown: str = SchemaField(description="The markdown of the crawl")
         html: str = SchemaField(description="The html of the crawl")
@@ -55,6 +56,10 @@ class FirecrawlCrawlBlock(Block):
         change_tracking: dict[str, Any] = SchemaField(
             description="The change tracking of the crawl"
         )
+        error: str = SchemaField(
+            description="Error message if the crawl failed",
+            default="",
+        )
 
     def __init__(self):
         super().__init__(

autogpt_platform/backend/backend/blocks/firecrawl/extract.py

@@ -9,7 +9,8 @@ from backend.sdk import (
     BlockCost,
     BlockCostType,
     BlockOutput,
-    BlockSchema,
+    BlockSchemaInput,
+    BlockSchemaOutput,
     CredentialsMetaInput,
     SchemaField,
     cost,
@@ -20,7 +21,7 @@ from ._config import firecrawl
 
 @cost(BlockCost(2, BlockCostType.RUN))
 class FirecrawlExtractBlock(Block):
-    class Input(BlockSchema):
+    class Input(BlockSchemaInput):
         credentials: CredentialsMetaInput = firecrawl.credentials_field()
         urls: list[str] = SchemaField(
             description="The URLs to crawl - at least one is required. Wildcards are supported. (/*)"
@@ -37,8 +38,12 @@ class FirecrawlExtractBlock(Block):
             default=False,
         )
 
-    class Output(BlockSchema):
+    class Output(BlockSchemaOutput):
         data: dict[str, Any] = SchemaField(description="The result of the crawl")
+        error: str = SchemaField(
+            description="Error message if the extraction failed",
+            default="",
+        )
 
     def __init__(self):
         super().__init__(

autogpt_platform/backend/backend/blocks/firecrawl/map.py

@@ -7,7 +7,8 @@ from backend.sdk import (
     Block,
     BlockCategory,
     BlockOutput,
-    BlockSchema,
+    BlockSchemaInput,
+    BlockSchemaOutput,
     CredentialsMetaInput,
     SchemaField,
 )
@@ -16,16 +17,20 @@ from ._config import firecrawl
 
 
 class FirecrawlMapWebsiteBlock(Block):
-    class Input(BlockSchema):
+    class Input(BlockSchemaInput):
         credentials: CredentialsMetaInput = firecrawl.credentials_field()
 
         url: str = SchemaField(description="The website url to map")
 
-    class Output(BlockSchema):
+    class Output(BlockSchemaOutput):
         links: list[str] = SchemaField(description="List of URLs found on the website")
         results: list[dict[str, Any]] = SchemaField(
             description="List of search results with url, title, and description"
         )
+        error: str = SchemaField(
+            description="Error message if the map failed",
+            default="",
+        )
 
     def __init__(self):
         super().__init__(

autogpt_platform/backend/backend/blocks/firecrawl/scrape.py

@@ -8,7 +8,8 @@ from backend.sdk import (
     Block,
     BlockCategory,
     BlockOutput,
-    BlockSchema,
+    BlockSchemaInput,
+    BlockSchemaOutput,
     CredentialsMetaInput,
     SchemaField,
 )
@@ -18,7 +19,7 @@ from ._format_utils import convert_to_format_options
 
 
 class FirecrawlScrapeBlock(Block):
-    class Input(BlockSchema):
+    class Input(BlockSchemaInput):
         credentials: CredentialsMetaInput = firecrawl.credentials_field()
         url: str = SchemaField(description="The URL to crawl")
         limit: int = SchemaField(description="The number of pages to crawl", default=10)
@@ -38,7 +39,7 @@ class FirecrawlScrapeBlock(Block):
             description="The format of the crawl", default=[ScrapeFormat.MARKDOWN]
         )
 
-    class Output(BlockSchema):
+    class Output(BlockSchemaOutput):
         data: dict[str, Any] = SchemaField(description="The result of the crawl")
         markdown: str = SchemaField(description="The markdown of the crawl")
         html: str = SchemaField(description="The html of the crawl")
@@ -54,6 +55,10 @@ class FirecrawlScrapeBlock(Block):
         change_tracking: dict[str, Any] = SchemaField(
             description="The change tracking of the crawl"
         )
+        error: str = SchemaField(
+            description="Error message if the scrape failed",
+            default="",
+        )
 
     def __init__(self):
         super().__init__(

autogpt_platform/backend/backend/blocks/firecrawl/search.py

@@ -9,7 +9,8 @@ from backend.sdk import (
     Block,
     BlockCategory,
     BlockOutput,
-    BlockSchema,
+    BlockSchemaInput,
+    BlockSchemaOutput,
     CredentialsMetaInput,
     SchemaField,
 )
@@ -19,7 +20,7 @@ from ._format_utils import convert_to_format_options
 
 
 class FirecrawlSearchBlock(Block):
-    class Input(BlockSchema):
+    class Input(BlockSchemaInput):
         credentials: CredentialsMetaInput = firecrawl.credentials_field()
         query: str = SchemaField(description="The query to search for")
         limit: int = SchemaField(description="The number of pages to crawl", default=10)
@@ -35,9 +36,13 @@ class FirecrawlSearchBlock(Block):
             description="Returns the content of the search if specified", default=[]
         )
 
-    class Output(BlockSchema):
+    class Output(BlockSchemaOutput):
         data: dict[str, Any] = SchemaField(description="The result of the search")
         site: dict[str, Any] = SchemaField(description="The site of the search")
+        error: str = SchemaField(
+            description="Error message if the search failed",
+            default="",
+        )
 
     def __init__(self):
         super().__init__(

autogpt_platform/backend/backend/blocks/flux_kontext.py

@@ -5,7 +5,13 @@ from pydantic import SecretStr
 from replicate.client import Client as ReplicateClient
 from replicate.helpers import FileOutput
 
-from backend.data.block import Block, BlockCategory, BlockOutput, BlockSchema
+from backend.data.block import (
+    Block,
+    BlockCategory,
+    BlockOutput,
+    BlockSchemaInput,
+    BlockSchemaOutput,
+)
 from backend.data.model import (
     APIKeyCredentials,
     CredentialsField,
@@ -57,7 +63,7 @@ class AspectRatio(str, Enum):
 
 
 class AIImageEditorBlock(Block):
-    class Input(BlockSchema):
+    class Input(BlockSchemaInput):
         credentials: CredentialsMetaInput[
             Literal[ProviderName.REPLICATE], Literal["api_key"]
         ] = CredentialsField(
@@ -90,11 +96,10 @@ class AIImageEditorBlock(Block):
             title="Model",
         )
 
-    class Output(BlockSchema):
+    class Output(BlockSchemaOutput):
         output_image: MediaFileType = SchemaField(
             description="URL of the transformed image"
         )
-        error: str = SchemaField(description="Error message if generation failed")
 
     def __init__(self):
         super().__init__(

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

@@ -3,7 +3,8 @@ from backend.sdk import (
     BlockCategory,
     BlockManualWebhookConfig,
     BlockOutput,
-    BlockSchema,
+    BlockSchemaInput,
+    BlockSchemaOutput,
     ProviderBuilder,
     ProviderName,
     SchemaField,
@@ -19,14 +20,14 @@ generic_webhook = (
 
 
 class GenericWebhookTriggerBlock(Block):
-    class Input(BlockSchema):
+    class Input(BlockSchemaInput):
         payload: dict = SchemaField(hidden=True, default_factory=dict)
         constants: dict = SchemaField(
             description="The constants to be set when the block is put on the graph",
             default_factory=dict,
         )
 
-    class Output(BlockSchema):
+    class Output(BlockSchemaOutput):
         payload: dict = SchemaField(
             description="The complete webhook payload that was received from the generic webhook."
         )

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

@@ -3,7 +3,13 @@ from typing import Optional
 
 from pydantic import BaseModel
 
-from backend.data.block import Block, BlockCategory, BlockOutput, BlockSchema
+from backend.data.block import (
+    Block,
+    BlockCategory,
+    BlockOutput,
+    BlockSchemaInput,
+    BlockSchemaOutput,
+)
 from backend.data.model import SchemaField
 
 from ._api import get_api
@@ -39,7 +45,7 @@ class ChecksConclusion(Enum):
 class GithubCreateCheckRunBlock(Block):
     """Block for creating a new check run on a GitHub repository."""
 
-    class Input(BlockSchema):
+    class Input(BlockSchemaInput):
         credentials: GithubCredentialsInput = GithubCredentialsField("repo:status")
         repo_url: str = SchemaField(
             description="URL of the GitHub repository",
@@ -76,7 +82,7 @@ class GithubCreateCheckRunBlock(Block):
             default="",
         )
 
-    class Output(BlockSchema):
+    class Output(BlockSchemaOutput):
         class CheckRunResult(BaseModel):
             id: int
             html_url: str
@@ -211,7 +217,7 @@ class GithubCreateCheckRunBlock(Block):
 class GithubUpdateCheckRunBlock(Block):
     """Block for updating an existing check run on a GitHub repository."""
 
-    class Input(BlockSchema):
+    class Input(BlockSchemaInput):
         credentials: GithubCredentialsInput = GithubCredentialsField("repo:status")
         repo_url: str = SchemaField(
             description="URL of the GitHub repository",
@@ -239,7 +245,7 @@ class GithubUpdateCheckRunBlock(Block):
             default=None,
         )
 
-    class Output(BlockSchema):
+    class Output(BlockSchemaOutput):
         class CheckRunResult(BaseModel):
             id: int
             html_url: str
@@ -249,7 +255,6 @@ class GithubUpdateCheckRunBlock(Block):
         check_run: CheckRunResult = SchemaField(
             description="Details of the updated check run"
         )
-        error: str = SchemaField(description="Error message if check run update failed")
 
     def __init__(self):
         super().__init__(

autogpt_platform/backend/backend/blocks/github/ci.py

@@ -5,7 +5,13 @@ from typing import Optional
 
 from typing_extensions import TypedDict
 
-from backend.data.block import Block, BlockCategory, BlockOutput, BlockSchema
+from backend.data.block import (
+    Block,
+    BlockCategory,
+    BlockOutput,
+    BlockSchemaInput,
+    BlockSchemaOutput,
+)
 from backend.data.model import SchemaField
 
 from ._api import get_api
@@ -37,7 +43,7 @@ class CheckRunConclusion(Enum):
 
 
 class GithubGetCIResultsBlock(Block):
-    class Input(BlockSchema):
+    class Input(BlockSchemaInput):
         credentials: GithubCredentialsInput = GithubCredentialsField("repo")
         repo: str = SchemaField(
             description="GitHub repository",
@@ -60,7 +66,7 @@ class GithubGetCIResultsBlock(Block):
             advanced=True,
         )
 
-    class Output(BlockSchema):
+    class Output(BlockSchemaOutput):
         class CheckRunItem(TypedDict, total=False):
             id: int
             name: str
@@ -104,7 +110,6 @@ class GithubGetCIResultsBlock(Block):
         total_checks: int = SchemaField(description="Total number of CI checks")
         passed_checks: int = SchemaField(description="Number of passed checks")
         failed_checks: int = SchemaField(description="Number of failed checks")
-        error: str = SchemaField(description="Error message if the operation failed")
 
     def __init__(self):
         super().__init__(

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

@@ -3,7 +3,13 @@ from urllib.parse import urlparse
 
 from typing_extensions import TypedDict
 
-from backend.data.block import Block, BlockCategory, BlockOutput, BlockSchema
+from backend.data.block import (
+    Block,
+    BlockCategory,
+    BlockOutput,
+    BlockSchemaInput,
+    BlockSchemaOutput,
+)
 from backend.data.model import SchemaField
 
 from ._api import convert_comment_url_to_api_endpoint, get_api
@@ -24,7 +30,7 @@ def is_github_url(url: str) -> bool:
 
 # --8<-- [start:GithubCommentBlockExample]
 class GithubCommentBlock(Block):
-    class Input(BlockSchema):
+    class Input(BlockSchemaInput):
         credentials: GithubCredentialsInput = GithubCredentialsField("repo")
         issue_url: str = SchemaField(
             description="URL of the GitHub issue or pull request",
@@ -35,7 +41,7 @@ class GithubCommentBlock(Block):
             placeholder="Enter your comment",
         )
 
-    class Output(BlockSchema):
+    class Output(BlockSchemaOutput):
         id: int = SchemaField(description="ID of the created comment")
         url: str = SchemaField(description="URL to the comment on GitHub")
         error: str = SchemaField(
@@ -112,7 +118,7 @@ class GithubCommentBlock(Block):
 
 
 class GithubUpdateCommentBlock(Block):
-    class Input(BlockSchema):
+    class Input(BlockSchemaInput):
         credentials: GithubCredentialsInput = GithubCredentialsField("repo")
         comment_url: str = SchemaField(
             description="URL of the GitHub comment",
@@ -135,7 +141,7 @@ class GithubUpdateCommentBlock(Block):
             placeholder="Enter your comment",
         )
 
-    class Output(BlockSchema):
+    class Output(BlockSchemaOutput):
         id: int = SchemaField(description="ID of the updated comment")
         url: str = SchemaField(description="URL to the comment on GitHub")
         error: str = SchemaField(
@@ -219,14 +225,14 @@ class GithubUpdateCommentBlock(Block):
 
 
 class GithubListCommentsBlock(Block):
-    class Input(BlockSchema):
+    class Input(BlockSchemaInput):
         credentials: GithubCredentialsInput = GithubCredentialsField("repo")
         issue_url: str = SchemaField(
             description="URL of the GitHub issue or pull request",
             placeholder="https://github.com/owner/repo/issues/1",
         )
 
-    class Output(BlockSchema):
+    class Output(BlockSchemaOutput):
         class CommentItem(TypedDict):
             id: int
             body: str
@@ -239,7 +245,6 @@ class GithubListCommentsBlock(Block):
         comments: list[CommentItem] = SchemaField(
             description="List of comments with their ID, body, user, and URL"
         )
-        error: str = SchemaField(description="Error message if listing comments failed")
 
     def __init__(self):
         super().__init__(
@@ -335,7 +340,7 @@ class GithubListCommentsBlock(Block):
 
 
 class GithubMakeIssueBlock(Block):
-    class Input(BlockSchema):
+    class Input(BlockSchemaInput):
         credentials: GithubCredentialsInput = GithubCredentialsField("repo")
         repo_url: str = SchemaField(
             description="URL of the GitHub repository",
@@ -348,7 +353,7 @@ class GithubMakeIssueBlock(Block):
             description="Body of the issue", placeholder="Enter the issue body"
         )
 
-    class Output(BlockSchema):
+    class Output(BlockSchemaOutput):
         number: int = SchemaField(description="Number of the created issue")
         url: str = SchemaField(description="URL of the created issue")
         error: str = SchemaField(
@@ -410,14 +415,14 @@ class GithubMakeIssueBlock(Block):
 
 
 class GithubReadIssueBlock(Block):
-    class Input(BlockSchema):
+    class Input(BlockSchemaInput):
         credentials: GithubCredentialsInput = GithubCredentialsField("repo")
         issue_url: str = SchemaField(
             description="URL of the GitHub issue",
             placeholder="https://github.com/owner/repo/issues/1",
         )
 
-    class Output(BlockSchema):
+    class Output(BlockSchemaOutput):
         title: str = SchemaField(description="Title of the issue")
         body: str = SchemaField(description="Body of the issue")
         user: str = SchemaField(description="User who created the issue")
@@ -483,14 +488,14 @@ class GithubReadIssueBlock(Block):
 
 
 class GithubListIssuesBlock(Block):
-    class Input(BlockSchema):
+    class Input(BlockSchemaInput):
         credentials: GithubCredentialsInput = GithubCredentialsField("repo")
         repo_url: str = SchemaField(
             description="URL of the GitHub repository",
             placeholder="https://github.com/owner/repo",
         )
 
-    class Output(BlockSchema):
+    class Output(BlockSchemaOutput):
         class IssueItem(TypedDict):
             title: str
             url: str
@@ -501,7 +506,6 @@ class GithubListIssuesBlock(Block):
         issues: list[IssueItem] = SchemaField(
             description="List of issues with their title and URL"
         )
-        error: str = SchemaField(description="Error message if listing issues failed")
 
     def __init__(self):
         super().__init__(
@@ -573,7 +577,7 @@ class GithubListIssuesBlock(Block):
 
 
 class GithubAddLabelBlock(Block):
-    class Input(BlockSchema):
+    class Input(BlockSchemaInput):
         credentials: GithubCredentialsInput = GithubCredentialsField("repo")
         issue_url: str = SchemaField(
             description="URL of the GitHub issue or pull request",
@@ -584,7 +588,7 @@ class GithubAddLabelBlock(Block):
             placeholder="Enter the label",
         )
 
-    class Output(BlockSchema):
+    class Output(BlockSchemaOutput):
         status: str = SchemaField(description="Status of the label addition operation")
         error: str = SchemaField(
             description="Error message if the label addition failed"
@@ -633,7 +637,7 @@ class GithubAddLabelBlock(Block):
 
 
 class GithubRemoveLabelBlock(Block):
-    class Input(BlockSchema):
+    class Input(BlockSchemaInput):
         credentials: GithubCredentialsInput = GithubCredentialsField("repo")
         issue_url: str = SchemaField(
             description="URL of the GitHub issue or pull request",
@@ -644,7 +648,7 @@ class GithubRemoveLabelBlock(Block):
             placeholder="Enter the label",
         )
 
-    class Output(BlockSchema):
+    class Output(BlockSchemaOutput):
         status: str = SchemaField(description="Status of the label removal operation")
         error: str = SchemaField(
             description="Error message if the label removal failed"
@@ -694,7 +698,7 @@ class GithubRemoveLabelBlock(Block):
 
 
 class GithubAssignIssueBlock(Block):
-    class Input(BlockSchema):
+    class Input(BlockSchemaInput):
         credentials: GithubCredentialsInput = GithubCredentialsField("repo")
         issue_url: str = SchemaField(
             description="URL of the GitHub issue",
@@ -705,7 +709,7 @@ class GithubAssignIssueBlock(Block):
             placeholder="Enter the username",
         )
 
-    class Output(BlockSchema):
+    class Output(BlockSchemaOutput):
         status: str = SchemaField(
             description="Status of the issue assignment operation"
         )
@@ -760,7 +764,7 @@ class GithubAssignIssueBlock(Block):
 
 
 class GithubUnassignIssueBlock(Block):
-    class Input(BlockSchema):
+    class Input(BlockSchemaInput):
         credentials: GithubCredentialsInput = GithubCredentialsField("repo")
         issue_url: str = SchemaField(
             description="URL of the GitHub issue",
@@ -771,7 +775,7 @@ class GithubUnassignIssueBlock(Block):
             placeholder="Enter the username",
         )
 
-    class Output(BlockSchema):
+    class Output(BlockSchemaOutput):
         status: str = SchemaField(
             description="Status of the issue unassignment operation"
         )

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

@@ -2,7 +2,13 @@ import re
 
 from typing_extensions import TypedDict
 
-from backend.data.block import Block, BlockCategory, BlockOutput, BlockSchema
+from backend.data.block import (
+    Block,
+    BlockCategory,
+    BlockOutput,
+    BlockSchemaInput,
+    BlockSchemaOutput,
+)
 from backend.data.model import SchemaField
 
 from ._api import get_api
@@ -16,14 +22,14 @@ from ._auth import (
 
 
 class GithubListPullRequestsBlock(Block):
-    class Input(BlockSchema):
+    class Input(BlockSchemaInput):
         credentials: GithubCredentialsInput = GithubCredentialsField("repo")
         repo_url: str = SchemaField(
             description="URL of the GitHub repository",
             placeholder="https://github.com/owner/repo",
         )
 
-    class Output(BlockSchema):
+    class Output(BlockSchemaOutput):
         class PRItem(TypedDict):
             title: str
             url: str
@@ -108,7 +114,7 @@ class GithubListPullRequestsBlock(Block):
 
 
 class GithubMakePullRequestBlock(Block):
-    class Input(BlockSchema):
+    class Input(BlockSchemaInput):
         credentials: GithubCredentialsInput = GithubCredentialsField("repo")
         repo_url: str = SchemaField(
             description="URL of the GitHub repository",
@@ -135,7 +141,7 @@ class GithubMakePullRequestBlock(Block):
             placeholder="Enter the base branch",
         )
 
-    class Output(BlockSchema):
+    class Output(BlockSchemaOutput):
         number: int = SchemaField(description="Number of the created pull request")
         url: str = SchemaField(description="URL of the created pull request")
         error: str = SchemaField(
@@ -209,7 +215,7 @@ class GithubMakePullRequestBlock(Block):
 
 
 class GithubReadPullRequestBlock(Block):
-    class Input(BlockSchema):
+    class Input(BlockSchemaInput):
         credentials: GithubCredentialsInput = GithubCredentialsField("repo")
         pr_url: str = SchemaField(
             description="URL of the GitHub pull request",
@@ -221,7 +227,7 @@ class GithubReadPullRequestBlock(Block):
             advanced=False,
         )
 
-    class Output(BlockSchema):
+    class Output(BlockSchemaOutput):
         title: str = SchemaField(description="Title of the pull request")
         body: str = SchemaField(description="Body of the pull request")
         author: str = SchemaField(description="User who created the pull request")
@@ -325,7 +331,7 @@ class GithubReadPullRequestBlock(Block):
 
 
 class GithubAssignPRReviewerBlock(Block):
-    class Input(BlockSchema):
+    class Input(BlockSchemaInput):
         credentials: GithubCredentialsInput = GithubCredentialsField("repo")
         pr_url: str = SchemaField(
             description="URL of the GitHub pull request",
@@ -336,7 +342,7 @@ class GithubAssignPRReviewerBlock(Block):
             placeholder="Enter the reviewer's username",
         )
 
-    class Output(BlockSchema):
+    class Output(BlockSchemaOutput):
         status: str = SchemaField(
             description="Status of the reviewer assignment operation"
         )
@@ -392,7 +398,7 @@ class GithubAssignPRReviewerBlock(Block):
 
 
 class GithubUnassignPRReviewerBlock(Block):
-    class Input(BlockSchema):
+    class Input(BlockSchemaInput):
         credentials: GithubCredentialsInput = GithubCredentialsField("repo")
         pr_url: str = SchemaField(
             description="URL of the GitHub pull request",
@@ -403,7 +409,7 @@ class GithubUnassignPRReviewerBlock(Block):
             placeholder="Enter the reviewer's username",
         )
 
-    class Output(BlockSchema):
+    class Output(BlockSchemaOutput):
         status: str = SchemaField(
             description="Status of the reviewer unassignment operation"
         )
@@ -459,14 +465,14 @@ class GithubUnassignPRReviewerBlock(Block):
 
 
 class GithubListPRReviewersBlock(Block):
-    class Input(BlockSchema):
+    class Input(BlockSchemaInput):
         credentials: GithubCredentialsInput = GithubCredentialsField("repo")
         pr_url: str = SchemaField(
             description="URL of the GitHub pull request",
             placeholder="https://github.com/owner/repo/pull/1",
         )
 
-    class Output(BlockSchema):
+    class Output(BlockSchemaOutput):
         class ReviewerItem(TypedDict):
             username: str
             url: str

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

@@ -2,7 +2,13 @@ import base64
 
 from typing_extensions import TypedDict
 
-from backend.data.block import Block, BlockCategory, BlockOutput, BlockSchema
+from backend.data.block import (
+    Block,
+    BlockCategory,
+    BlockOutput,
+    BlockSchemaInput,
+    BlockSchemaOutput,
+)
 from backend.data.model import SchemaField
 
 from ._api import get_api
@@ -16,14 +22,14 @@ from ._auth import (
 
 
 class GithubListTagsBlock(Block):
-    class Input(BlockSchema):
+    class Input(BlockSchemaInput):
         credentials: GithubCredentialsInput = GithubCredentialsField("repo")
         repo_url: str = SchemaField(
             description="URL of the GitHub repository",
             placeholder="https://github.com/owner/repo",
         )
 
-    class Output(BlockSchema):
+    class Output(BlockSchemaOutput):
         class TagItem(TypedDict):
             name: str
             url: str
@@ -34,7 +40,6 @@ class GithubListTagsBlock(Block):
         tags: list[TagItem] = SchemaField(
             description="List of tags with their name and file tree browser URL"
         )
-        error: str = SchemaField(description="Error message if listing tags failed")
 
     def __init__(self):
         super().__init__(
@@ -111,14 +116,14 @@ class GithubListTagsBlock(Block):
 
 
 class GithubListBranchesBlock(Block):
-    class Input(BlockSchema):
+    class Input(BlockSchemaInput):
         credentials: GithubCredentialsInput = GithubCredentialsField("repo")
         repo_url: str = SchemaField(
             description="URL of the GitHub repository",
             placeholder="https://github.com/owner/repo",
         )
 
-    class Output(BlockSchema):
+    class Output(BlockSchemaOutput):
         class BranchItem(TypedDict):
             name: str
             url: str
@@ -130,7 +135,6 @@ class GithubListBranchesBlock(Block):
         branches: list[BranchItem] = SchemaField(
             description="List of branches with their name and file tree browser URL"
         )
-        error: str = SchemaField(description="Error message if listing branches failed")
 
     def __init__(self):
         super().__init__(
@@ -207,7 +211,7 @@ class GithubListBranchesBlock(Block):
 
 
 class GithubListDiscussionsBlock(Block):
-    class Input(BlockSchema):
+    class Input(BlockSchemaInput):
         credentials: GithubCredentialsInput = GithubCredentialsField("repo")
         repo_url: str = SchemaField(
             description="URL of the GitHub repository",
@@ -217,7 +221,7 @@ class GithubListDiscussionsBlock(Block):
             description="Number of discussions to fetch", default=5
         )
 
-    class Output(BlockSchema):
+    class Output(BlockSchemaOutput):
         class DiscussionItem(TypedDict):
             title: str
             url: str
@@ -323,14 +327,14 @@ class GithubListDiscussionsBlock(Block):
 
 
 class GithubListReleasesBlock(Block):
-    class Input(BlockSchema):
+    class Input(BlockSchemaInput):
         credentials: GithubCredentialsInput = GithubCredentialsField("repo")
         repo_url: str = SchemaField(
             description="URL of the GitHub repository",
             placeholder="https://github.com/owner/repo",
         )
 
-    class Output(BlockSchema):
+    class Output(BlockSchemaOutput):
         class ReleaseItem(TypedDict):
             name: str
             url: str
@@ -342,7 +346,6 @@ class GithubListReleasesBlock(Block):
         releases: list[ReleaseItem] = SchemaField(
             description="List of releases with their name and file tree browser URL"
         )
-        error: str = SchemaField(description="Error message if listing releases failed")
 
     def __init__(self):
         super().__init__(
@@ -414,7 +417,7 @@ class GithubListReleasesBlock(Block):
 
 
 class GithubReadFileBlock(Block):
-    class Input(BlockSchema):
+    class Input(BlockSchemaInput):
         credentials: GithubCredentialsInput = GithubCredentialsField("repo")
         repo_url: str = SchemaField(
             description="URL of the GitHub repository",
@@ -430,7 +433,7 @@ class GithubReadFileBlock(Block):
             default="master",
         )
 
-    class Output(BlockSchema):
+    class Output(BlockSchemaOutput):
         text_content: str = SchemaField(
             description="Content of the file (decoded as UTF-8 text)"
         )
@@ -438,7 +441,6 @@ class GithubReadFileBlock(Block):
             description="Raw base64-encoded content of the file"
         )
         size: int = SchemaField(description="The size of the file (in bytes)")
-        error: str = SchemaField(description="Error message if the file reading failed")
 
     def __init__(self):
         super().__init__(
@@ -501,7 +503,7 @@ class GithubReadFileBlock(Block):
 
 
 class GithubReadFolderBlock(Block):
-    class Input(BlockSchema):
+    class Input(BlockSchemaInput):
         credentials: GithubCredentialsInput = GithubCredentialsField("repo")
         repo_url: str = SchemaField(
             description="URL of the GitHub repository",
@@ -517,7 +519,7 @@ class GithubReadFolderBlock(Block):
             default="master",
         )
 
-    class Output(BlockSchema):
+    class Output(BlockSchemaOutput):
         class DirEntry(TypedDict):
             name: str
             path: str
@@ -625,7 +627,7 @@ class GithubReadFolderBlock(Block):
 
 
 class GithubMakeBranchBlock(Block):
-    class Input(BlockSchema):
+    class Input(BlockSchemaInput):
         credentials: GithubCredentialsInput = GithubCredentialsField("repo")
         repo_url: str = SchemaField(
             description="URL of the GitHub repository",
@@ -640,7 +642,7 @@ class GithubMakeBranchBlock(Block):
             placeholder="source_branch_name",
         )
 
-    class Output(BlockSchema):
+    class Output(BlockSchemaOutput):
         status: str = SchemaField(description="Status of the branch creation operation")
         error: str = SchemaField(
             description="Error message if the branch creation failed"
@@ -705,7 +707,7 @@ class GithubMakeBranchBlock(Block):
 
 
 class GithubDeleteBranchBlock(Block):
-    class Input(BlockSchema):
+    class Input(BlockSchemaInput):
         credentials: GithubCredentialsInput = GithubCredentialsField("repo")
         repo_url: str = SchemaField(
             description="URL of the GitHub repository",
@@ -716,7 +718,7 @@ class GithubDeleteBranchBlock(Block):
             placeholder="branch_name",
         )
 
-    class Output(BlockSchema):
+    class Output(BlockSchemaOutput):
         status: str = SchemaField(description="Status of the branch deletion operation")
         error: str = SchemaField(
             description="Error message if the branch deletion failed"
@@ -766,7 +768,7 @@ class GithubDeleteBranchBlock(Block):
 
 
 class GithubCreateFileBlock(Block):
-    class Input(BlockSchema):
+    class Input(BlockSchemaInput):
         credentials: GithubCredentialsInput = GithubCredentialsField("repo")
         repo_url: str = SchemaField(
             description="URL of the GitHub repository",
@@ -789,7 +791,7 @@ class GithubCreateFileBlock(Block):
             default="Create new file",
         )
 
-    class Output(BlockSchema):
+    class Output(BlockSchemaOutput):
         url: str = SchemaField(description="URL of the created file")
         sha: str = SchemaField(description="SHA of the commit")
         error: str = SchemaField(
@@ -868,7 +870,7 @@ class GithubCreateFileBlock(Block):
 
 
 class GithubUpdateFileBlock(Block):
-    class Input(BlockSchema):
+    class Input(BlockSchemaInput):
         credentials: GithubCredentialsInput = GithubCredentialsField("repo")
         repo_url: str = SchemaField(
             description="URL of the GitHub repository",
@@ -891,10 +893,9 @@ class GithubUpdateFileBlock(Block):
             default="Update file",
         )
 
-    class Output(BlockSchema):
+    class Output(BlockSchemaOutput):
         url: str = SchemaField(description="URL of the updated file")
         sha: str = SchemaField(description="SHA of the commit")
-        error: str = SchemaField(description="Error message if the file update failed")
 
     def __init__(self):
         super().__init__(
@@ -974,7 +975,7 @@ class GithubUpdateFileBlock(Block):
 
 
 class GithubCreateRepositoryBlock(Block):
-    class Input(BlockSchema):
+    class Input(BlockSchemaInput):
         credentials: GithubCredentialsInput = GithubCredentialsField("repo")
         name: str = SchemaField(
             description="Name of the repository to create",
@@ -998,7 +999,7 @@ class GithubCreateRepositoryBlock(Block):
             default="",
         )
 
-    class Output(BlockSchema):
+    class Output(BlockSchemaOutput):
         url: str = SchemaField(description="URL of the created repository")
         clone_url: str = SchemaField(description="Git clone URL of the repository")
         error: str = SchemaField(
@@ -1077,14 +1078,14 @@ class GithubCreateRepositoryBlock(Block):
 
 
 class GithubListStargazersBlock(Block):
-    class Input(BlockSchema):
+    class Input(BlockSchemaInput):
         credentials: GithubCredentialsInput = GithubCredentialsField("repo")
         repo_url: str = SchemaField(
             description="URL of the GitHub repository",
             placeholder="https://github.com/owner/repo",
         )
 
-    class Output(BlockSchema):
+    class Output(BlockSchemaOutput):
         class StargazerItem(TypedDict):
             username: str
             url: str

autogpt_platform/backend/backend/blocks/github/reviews.py

@@ -4,7 +4,13 @@ from typing import Any, List, Optional
 
 from typing_extensions import TypedDict
 
-from backend.data.block import Block, BlockCategory, BlockOutput, BlockSchema
+from backend.data.block import (
+    Block,
+    BlockCategory,
+    BlockOutput,
+    BlockSchemaInput,
+    BlockSchemaOutput,
+)
 from backend.data.model import SchemaField
 
 from ._api import get_api
@@ -26,7 +32,7 @@ class ReviewEvent(Enum):
 
 
 class GithubCreatePRReviewBlock(Block):
-    class Input(BlockSchema):
+    class Input(BlockSchemaInput):
         class ReviewComment(TypedDict, total=False):
             path: str
             position: Optional[int]
@@ -61,7 +67,7 @@ class GithubCreatePRReviewBlock(Block):
             advanced=True,
         )
 
-    class Output(BlockSchema):
+    class Output(BlockSchemaOutput):
         review_id: int = SchemaField(description="ID of the created review")
         state: str = SchemaField(
             description="State of the review (e.g., PENDING, COMMENTED, APPROVED, CHANGES_REQUESTED)"
@@ -197,7 +203,7 @@ class GithubCreatePRReviewBlock(Block):
 
 
 class GithubListPRReviewsBlock(Block):
-    class Input(BlockSchema):
+    class Input(BlockSchemaInput):
         credentials: GithubCredentialsInput = GithubCredentialsField("repo")
         repo: str = SchemaField(
             description="GitHub repository",
@@ -208,7 +214,7 @@ class GithubListPRReviewsBlock(Block):
             placeholder="123",
         )
 
-    class Output(BlockSchema):
+    class Output(BlockSchemaOutput):
         class ReviewItem(TypedDict):
             id: int
             user: str
@@ -223,7 +229,6 @@ class GithubListPRReviewsBlock(Block):
         reviews: list[ReviewItem] = SchemaField(
             description="List of all reviews on the pull request"
         )
-        error: str = SchemaField(description="Error message if listing reviews failed")
 
     def __init__(self):
         super().__init__(
@@ -317,7 +322,7 @@ class GithubListPRReviewsBlock(Block):
 
 
 class GithubSubmitPendingReviewBlock(Block):
-    class Input(BlockSchema):
+    class Input(BlockSchemaInput):
         credentials: GithubCredentialsInput = GithubCredentialsField("repo")
         repo: str = SchemaField(
             description="GitHub repository",
@@ -336,7 +341,7 @@ class GithubSubmitPendingReviewBlock(Block):
             default=ReviewEvent.COMMENT,
         )
 
-    class Output(BlockSchema):
+    class Output(BlockSchemaOutput):
         state: str = SchemaField(description="State of the submitted review")
         html_url: str = SchemaField(description="URL of the submitted review")
         error: str = SchemaField(
@@ -415,7 +420,7 @@ class GithubSubmitPendingReviewBlock(Block):
 
 
 class GithubResolveReviewDiscussionBlock(Block):
-    class Input(BlockSchema):
+    class Input(BlockSchemaInput):
         credentials: GithubCredentialsInput = GithubCredentialsField("repo")
         repo: str = SchemaField(
             description="GitHub repository",
@@ -434,9 +439,8 @@ class GithubResolveReviewDiscussionBlock(Block):
             default=True,
         )
 
-    class Output(BlockSchema):
+    class Output(BlockSchemaOutput):
         success: bool = SchemaField(description="Whether the operation was successful")
-        error: str = SchemaField(description="Error message if the operation failed")
 
     def __init__(self):
         super().__init__(
@@ -579,7 +583,7 @@ class GithubResolveReviewDiscussionBlock(Block):
 
 
 class GithubGetPRReviewCommentsBlock(Block):
-    class Input(BlockSchema):
+    class Input(BlockSchemaInput):
         credentials: GithubCredentialsInput = GithubCredentialsField("repo")
         repo: str = SchemaField(
             description="GitHub repository",
@@ -596,7 +600,7 @@ class GithubGetPRReviewCommentsBlock(Block):
             advanced=True,
         )
 
-    class Output(BlockSchema):
+    class Output(BlockSchemaOutput):
         class CommentItem(TypedDict):
             id: int
             user: str
@@ -616,7 +620,6 @@ class GithubGetPRReviewCommentsBlock(Block):
         comments: list[CommentItem] = SchemaField(
             description="List of all review comments on the pull request"
         )
-        error: str = SchemaField(description="Error message if getting comments failed")
 
     def __init__(self):
         super().__init__(
@@ -744,7 +747,7 @@ class GithubGetPRReviewCommentsBlock(Block):
 
 
 class GithubCreateCommentObjectBlock(Block):
-    class Input(BlockSchema):
+    class Input(BlockSchemaInput):
         path: str = SchemaField(
             description="The file path to comment on",
             placeholder="src/main.py",
@@ -781,7 +784,7 @@ class GithubCreateCommentObjectBlock(Block):
             advanced=True,
         )
 
-    class Output(BlockSchema):
+    class Output(BlockSchemaOutput):
         comment_object: dict = SchemaField(
             description="The comment object formatted for GitHub API"
         )

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

@@ -3,7 +3,13 @@ from typing import Optional
 
 from pydantic import BaseModel
 
-from backend.data.block import Block, BlockCategory, BlockOutput, BlockSchema
+from backend.data.block import (
+    Block,
+    BlockCategory,
+    BlockOutput,
+    BlockSchemaInput,
+    BlockSchemaOutput,
+)
 from backend.data.model import SchemaField
 
 from ._api import get_api
@@ -26,7 +32,7 @@ class StatusState(Enum):
 class GithubCreateStatusBlock(Block):
     """Block for creating a commit status on a GitHub repository."""
 
-    class Input(BlockSchema):
+    class Input(BlockSchemaInput):
         credentials: GithubFineGrainedAPICredentialsInput = (
             GithubFineGrainedAPICredentialsField("repo:status")
         )
@@ -54,7 +60,7 @@ class GithubCreateStatusBlock(Block):
             advanced=False,
         )
 
-    class Output(BlockSchema):
+    class Output(BlockSchemaOutput):
         class StatusResult(BaseModel):
             id: int
             url: str
@@ -66,7 +72,6 @@ class GithubCreateStatusBlock(Block):
             updated_at: str
 
         status: StatusResult = SchemaField(description="Details of the created status")
-        error: str = SchemaField(description="Error message if status creation failed")
 
     def __init__(self):
         super().__init__(

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

@@ -8,7 +8,8 @@ from backend.data.block import (
     Block,
     BlockCategory,
     BlockOutput,
-    BlockSchema,
+    BlockSchemaInput,
+    BlockSchemaOutput,
     BlockWebhookConfig,
 )
 from backend.data.model import SchemaField
@@ -26,7 +27,7 @@ logger = logging.getLogger(__name__)
 
 # --8<-- [start:GithubTriggerExample]
 class GitHubTriggerBase:
-    class Input(BlockSchema):
+    class Input(BlockSchemaInput):
         credentials: GithubCredentialsInput = GithubCredentialsField("repo")
         repo: str = SchemaField(
             description=(
@@ -40,7 +41,7 @@ class GitHubTriggerBase:
         payload: dict = SchemaField(hidden=True, default_factory=dict)
         # --8<-- [end:example-payload-field]
 
-    class Output(BlockSchema):
+    class Output(BlockSchemaOutput):
         payload: dict = SchemaField(
             description="The complete webhook payload that was received from GitHub. "
             "Includes information about the affected resource (e.g. pull request), "

autogpt_platform/backend/backend/blocks/google/_drive.py

@@ -0,0 +1,194 @@
+import asyncio
+import mimetypes
+import uuid
+from pathlib import Path
+from typing import Any, Literal, Optional
+
+from pydantic import BaseModel, ConfigDict, Field
+
+from backend.data.model import SchemaField
+from backend.util.file import get_exec_file_path
+from backend.util.request import Requests
+from backend.util.type import MediaFileType
+from backend.util.virus_scanner import scan_content_safe
+
+AttachmentView = Literal[
+    "DOCS",
+    "DOCUMENTS",
+    "SPREADSHEETS",
+    "PRESENTATIONS",
+    "DOCS_IMAGES",
+    "FOLDERS",
+]
+ATTACHMENT_VIEWS: tuple[AttachmentView, ...] = (
+    "DOCS",
+    "DOCUMENTS",
+    "SPREADSHEETS",
+    "PRESENTATIONS",
+    "DOCS_IMAGES",
+    "FOLDERS",
+)
+
+
+class GoogleDriveFile(BaseModel):
+    """Represents a single file/folder picked from Google Drive"""
+
+    model_config = ConfigDict(populate_by_name=True)
+
+    id: str = Field(description="Google Drive file/folder ID")
+    name: Optional[str] = Field(None, description="File/folder name")
+    mime_type: Optional[str] = Field(
+        None,
+        alias="mimeType",
+        description="MIME type (e.g., application/vnd.google-apps.document)",
+    )
+    url: Optional[str] = Field(None, description="URL to open the file")
+    icon_url: Optional[str] = Field(None, alias="iconUrl", description="Icon URL")
+    is_folder: Optional[bool] = Field(
+        None, alias="isFolder", description="Whether this is a folder"
+    )
+
+
+def GoogleDrivePickerField(
+    multiselect: bool = False,
+    allow_folder_selection: bool = False,
+    allowed_views: Optional[list[AttachmentView]] = None,
+    allowed_mime_types: Optional[list[str]] = None,
+    scopes: Optional[list[str]] = None,
+    title: Optional[str] = None,
+    description: Optional[str] = None,
+    placeholder: Optional[str] = None,
+    **kwargs,
+) -> Any:
+    """
+    Creates a Google Drive Picker input field.
+
+    Args:
+        multiselect: Allow selecting multiple files/folders (default: False)
+        allow_folder_selection: Allow selecting folders (default: False)
+        allowed_views: List of view types to show in picker (default: ["DOCS"])
+        allowed_mime_types: Filter by MIME types (e.g., ["application/pdf"])
+        title: Field title shown in UI
+        description: Field description/help text
+        placeholder: Placeholder text for the button
+        **kwargs: Additional SchemaField arguments (advanced, hidden, etc.)
+
+    Returns:
+        Field definition that produces:
+        - Single GoogleDriveFile when multiselect=False
+        - list[GoogleDriveFile] when multiselect=True
+
+    Example:
+        >>> class MyBlock(Block):
+        ...     class Input(BlockSchema):
+        ...         document: GoogleDriveFile = GoogleDrivePickerField(
+        ...             title="Select Document",
+        ...             allowed_views=["DOCUMENTS"],
+        ...         )
+        ...
+        ...         files: list[GoogleDriveFile] = GoogleDrivePickerField(
+        ...             title="Select Multiple Files",
+        ...             multiselect=True,
+        ...             allow_folder_selection=True,
+        ...         )
+    """
+    # Build configuration that will be sent to frontend
+    picker_config = {
+        "multiselect": multiselect,
+        "allow_folder_selection": allow_folder_selection,
+        "allowed_views": list(allowed_views) if allowed_views else ["DOCS"],
+    }
+
+    # Add optional configurations
+    if allowed_mime_types:
+        picker_config["allowed_mime_types"] = list(allowed_mime_types)
+
+    # Determine required scopes based on config
+    base_scopes = scopes if scopes is not None else []
+    picker_scopes: set[str] = set(base_scopes)
+    if allow_folder_selection:
+        picker_scopes.add("https://www.googleapis.com/auth/drive")
+    else:
+        # Use drive.file for minimal scope - only access files selected by user in picker
+        # This scope is sufficient for the picker to work. The actual API operations
+        # (read/write) use the block's credentials field which has the appropriate scopes.
+        picker_scopes.add("https://www.googleapis.com/auth/drive.file")
+
+    picker_config["scopes"] = sorted(picker_scopes)
+
+    # Set appropriate default value
+    default_value = [] if multiselect else None
+
+    # Use SchemaField to handle format properly
+    return SchemaField(
+        default=default_value,
+        title=title,
+        description=description,
+        placeholder=placeholder or "Choose from Google Drive",
+        format="google-drive-picker",
+        advanced=False,
+        json_schema_extra={
+            "google_drive_picker_config": picker_config,
+            **kwargs,
+        },
+    )
+
+
+DRIVE_API_URL = "https://www.googleapis.com/drive/v3/files"
+_requests = Requests(trusted_origins=["https://www.googleapis.com"])
+
+
+def GoogleDriveAttachmentField(
+    *,
+    title: str,
+    description: str | None = None,
+    placeholder: str | None = None,
+    multiselect: bool = True,
+    allowed_mime_types: list[str] | None = None,
+    **extra: Any,
+) -> Any:
+    return GoogleDrivePickerField(
+        multiselect=multiselect,
+        allowed_views=list(ATTACHMENT_VIEWS),
+        allowed_mime_types=allowed_mime_types,
+        title=title,
+        description=description,
+        placeholder=placeholder or "Choose files from Google Drive",
+        **extra,
+    )
+
+
+async def drive_file_to_media_file(
+    drive_file: GoogleDriveFile, *, graph_exec_id: str, access_token: str
+) -> MediaFileType:
+    if drive_file.is_folder:
+        raise ValueError("Google Drive selection must be a file.")
+    if not access_token:
+        raise ValueError("Google Drive access token is required for file download.")
+
+    url = f"{DRIVE_API_URL}/{drive_file.id}?alt=media"
+    response = await _requests.get(
+        url, headers={"Authorization": f"Bearer {access_token}"}
+    )
+
+    mime_type = drive_file.mime_type or response.headers.get(
+        "content-type", "application/octet-stream"
+    )
+
+    MAX_FILE_SIZE = 100 * 1024 * 1024
+    if len(response.content) > MAX_FILE_SIZE:
+        raise ValueError(
+            f"File too large: {len(response.content)} bytes > {MAX_FILE_SIZE} bytes"
+        )
+
+    base_path = Path(get_exec_file_path(graph_exec_id, ""))
+    base_path.mkdir(parents=True, exist_ok=True)
+
+    extension = mimetypes.guess_extension(mime_type, strict=False) or ".bin"
+    filename = f"{uuid.uuid4()}{extension}"
+    target_path = base_path / filename
+
+    await scan_content_safe(response.content, filename=filename)
+    await asyncio.to_thread(target_path.write_bytes, response.content)
+
+    return MediaFileType(str(target_path.relative_to(base_path)))

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

@@ -8,7 +8,13 @@ from google.oauth2.credentials import Credentials
 from googleapiclient.discovery import build
 from pydantic import BaseModel
 
-from backend.data.block import Block, BlockCategory, BlockOutput, BlockSchema
+from backend.data.block import (
+    Block,
+    BlockCategory,
+    BlockOutput,
+    BlockSchemaInput,
+    BlockSchemaOutput,
+)
 from backend.data.model import SchemaField
 from backend.util.settings import Settings
 
@@ -43,7 +49,7 @@ class CalendarEvent(BaseModel):
 
 
 class GoogleCalendarReadEventsBlock(Block):
-    class Input(BlockSchema):
+    class Input(BlockSchemaInput):
         credentials: GoogleCredentialsInput = GoogleCredentialsField(
             ["https://www.googleapis.com/auth/calendar.readonly"]
         )
@@ -73,7 +79,7 @@ class GoogleCalendarReadEventsBlock(Block):
             description="Include events you've declined", default=False
         )
 
-    class Output(BlockSchema):
+    class Output(BlockSchemaOutput):
         events: list[CalendarEvent] = SchemaField(
             description="List of calendar events in the requested time range",
             default_factory=list,
@@ -379,7 +385,7 @@ class RecurringEvent(BaseModel):
 
 
 class GoogleCalendarCreateEventBlock(Block):
-    class Input(BlockSchema):
+    class Input(BlockSchemaInput):
         credentials: GoogleCredentialsInput = GoogleCredentialsField(
             ["https://www.googleapis.com/auth/calendar"]
         )
@@ -433,12 +439,11 @@ class GoogleCalendarCreateEventBlock(Block):
             default_factory=lambda: [ReminderPreset.TEN_MINUTES],
         )
 
-    class Output(BlockSchema):
+    class Output(BlockSchemaOutput):
         event_id: str = SchemaField(description="ID of the created event")
         event_link: str = SchemaField(
             description="Link to view the event in Google Calendar"
         )
-        error: str = SchemaField(description="Error message if event creation failed")
 
     def __init__(self):
         super().__init__(

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

@@ -14,7 +14,13 @@ from google.oauth2.credentials import Credentials
 from googleapiclient.discovery import build
 from pydantic import BaseModel, Field
 
-from backend.data.block import Block, BlockCategory, BlockOutput, BlockSchema
+from backend.data.block import (
+    Block,
+    BlockCategory,
+    BlockOutput,
+    BlockSchemaInput,
+    BlockSchemaOutput,
+)
 from backend.data.model import SchemaField
 from backend.util.file import MediaFileType, get_exec_file_path, store_media_file
 from backend.util.settings import Settings
@@ -320,7 +326,7 @@ class GmailBase(Block, ABC):
 
 
 class GmailReadBlock(GmailBase):
-    class Input(BlockSchema):
+    class Input(BlockSchemaInput):
         credentials: GoogleCredentialsInput = GoogleCredentialsField(
             ["https://www.googleapis.com/auth/gmail.readonly"]
         )
@@ -333,7 +339,7 @@ class GmailReadBlock(GmailBase):
             default=10,
         )
 
-    class Output(BlockSchema):
+    class Output(BlockSchemaOutput):
         email: Email = SchemaField(
             description="Email data",
         )
@@ -516,7 +522,7 @@ class GmailSendBlock(GmailBase):
     - Attachment support for multiple files
     """
 
-    class Input(BlockSchema):
+    class Input(BlockSchemaInput):
         credentials: GoogleCredentialsInput = GoogleCredentialsField(
             ["https://www.googleapis.com/auth/gmail.send"]
         )
@@ -540,7 +546,7 @@ class GmailSendBlock(GmailBase):
             description="Files to attach", default_factory=list, advanced=True
         )
 
-    class Output(BlockSchema):
+    class Output(BlockSchemaOutput):
         result: GmailSendResult = SchemaField(
             description="Send confirmation",
         )
@@ -618,7 +624,7 @@ class GmailCreateDraftBlock(GmailBase):
     - Attachment support for multiple files
     """
 
-    class Input(BlockSchema):
+    class Input(BlockSchemaInput):
         credentials: GoogleCredentialsInput = GoogleCredentialsField(
             ["https://www.googleapis.com/auth/gmail.modify"]
         )
@@ -642,7 +648,7 @@ class GmailCreateDraftBlock(GmailBase):
             description="Files to attach", default_factory=list, advanced=True
         )
 
-    class Output(BlockSchema):
+    class Output(BlockSchemaOutput):
         result: GmailDraftResult = SchemaField(
             description="Draft creation result",
         )
@@ -721,12 +727,12 @@ class GmailCreateDraftBlock(GmailBase):
 
 
 class GmailListLabelsBlock(GmailBase):
-    class Input(BlockSchema):
+    class Input(BlockSchemaInput):
         credentials: GoogleCredentialsInput = GoogleCredentialsField(
             ["https://www.googleapis.com/auth/gmail.labels"]
         )
 
-    class Output(BlockSchema):
+    class Output(BlockSchemaOutput):
         result: list[dict] = SchemaField(
             description="List of labels",
         )
@@ -779,7 +785,7 @@ class GmailListLabelsBlock(GmailBase):
 
 
 class GmailAddLabelBlock(GmailBase):
-    class Input(BlockSchema):
+    class Input(BlockSchemaInput):
         credentials: GoogleCredentialsInput = GoogleCredentialsField(
             ["https://www.googleapis.com/auth/gmail.modify"]
         )
@@ -790,7 +796,7 @@ class GmailAddLabelBlock(GmailBase):
             description="Label name to add",
         )
 
-    class Output(BlockSchema):
+    class Output(BlockSchemaOutput):
         result: GmailLabelResult = SchemaField(
             description="Label addition result",
         )
@@ -865,7 +871,7 @@ class GmailAddLabelBlock(GmailBase):
 
 
 class GmailRemoveLabelBlock(GmailBase):
-    class Input(BlockSchema):
+    class Input(BlockSchemaInput):
         credentials: GoogleCredentialsInput = GoogleCredentialsField(
             ["https://www.googleapis.com/auth/gmail.modify"]
         )
@@ -876,7 +882,7 @@ class GmailRemoveLabelBlock(GmailBase):
             description="Label name to remove",
         )
 
-    class Output(BlockSchema):
+    class Output(BlockSchemaOutput):
         result: GmailLabelResult = SchemaField(
             description="Label removal result",
         )
@@ -941,17 +947,16 @@ class GmailRemoveLabelBlock(GmailBase):
 
 
 class GmailGetThreadBlock(GmailBase):
-    class Input(BlockSchema):
+    class Input(BlockSchemaInput):
         credentials: GoogleCredentialsInput = GoogleCredentialsField(
             ["https://www.googleapis.com/auth/gmail.readonly"]
         )
         threadId: str = SchemaField(description="Gmail thread ID")
 
-    class Output(BlockSchema):
+    class Output(BlockSchemaOutput):
         thread: Thread = SchemaField(
             description="Gmail thread with decoded message bodies"
         )
-        error: str = SchemaField(description="Error message if any")
 
     def __init__(self):
         super().__init__(
@@ -1218,7 +1223,7 @@ class GmailReplyBlock(GmailBase):
     - Full Unicode/emoji support with UTF-8 encoding
     """
 
-    class Input(BlockSchema):
+    class Input(BlockSchemaInput):
         credentials: GoogleCredentialsInput = GoogleCredentialsField(
             [
                 "https://www.googleapis.com/auth/gmail.send",
@@ -1246,14 +1251,13 @@ class GmailReplyBlock(GmailBase):
             description="Files to attach", default_factory=list, advanced=True
         )
 
-    class Output(BlockSchema):
+    class Output(BlockSchemaOutput):
         messageId: str = SchemaField(description="Sent message ID")
         threadId: str = SchemaField(description="Thread ID")
         message: dict = SchemaField(description="Raw Gmail message object")
         email: Email = SchemaField(
             description="Parsed email object with decoded body and attachments"
         )
-        error: str = SchemaField(description="Error message if any")
 
     def __init__(self):
         super().__init__(
@@ -1368,7 +1372,7 @@ class GmailDraftReplyBlock(GmailBase):
     - Full Unicode/emoji support with UTF-8 encoding
     """
 
-    class Input(BlockSchema):
+    class Input(BlockSchemaInput):
         credentials: GoogleCredentialsInput = GoogleCredentialsField(
             [
                 "https://www.googleapis.com/auth/gmail.modify",
@@ -1396,12 +1400,11 @@ class GmailDraftReplyBlock(GmailBase):
             description="Files to attach", default_factory=list, advanced=True
         )
 
-    class Output(BlockSchema):
+    class Output(BlockSchemaOutput):
         draftId: str = SchemaField(description="Created draft ID")
         messageId: str = SchemaField(description="Draft message ID")
         threadId: str = SchemaField(description="Thread ID")
         status: str = SchemaField(description="Draft creation status")
-        error: str = SchemaField(description="Error message if any")
 
     def __init__(self):
         super().__init__(
@@ -1482,14 +1485,13 @@ class GmailDraftReplyBlock(GmailBase):
 
 
 class GmailGetProfileBlock(GmailBase):
-    class Input(BlockSchema):
+    class Input(BlockSchemaInput):
         credentials: GoogleCredentialsInput = GoogleCredentialsField(
             ["https://www.googleapis.com/auth/gmail.readonly"]
         )
 
-    class Output(BlockSchema):
+    class Output(BlockSchemaOutput):
         profile: Profile = SchemaField(description="Gmail user profile information")
-        error: str = SchemaField(description="Error message if any")
 
     def __init__(self):
         super().__init__(
@@ -1555,7 +1557,7 @@ class GmailForwardBlock(GmailBase):
     - Manual content type override option
     """
 
-    class Input(BlockSchema):
+    class Input(BlockSchemaInput):
         credentials: GoogleCredentialsInput = GoogleCredentialsField(
             [
                 "https://www.googleapis.com/auth/gmail.send",
@@ -1589,11 +1591,10 @@ class GmailForwardBlock(GmailBase):
             advanced=True,
         )
 
-    class Output(BlockSchema):
+    class Output(BlockSchemaOutput):
         messageId: str = SchemaField(description="Forwarded message ID")
         threadId: str = SchemaField(description="Thread ID")
         status: str = SchemaField(description="Forward status")
-        error: str = SchemaField(description="Error message if any")
 
     def __init__(self):
         super().__init__(

autogpt_platform/backend/backend/blocks/google_maps.py

@@ -3,7 +3,13 @@ from typing import Literal
 import googlemaps
 from pydantic import BaseModel, SecretStr
 
-from backend.data.block import Block, BlockCategory, BlockOutput, BlockSchema
+from backend.data.block import (
+    Block,
+    BlockCategory,
+    BlockOutput,
+    BlockSchemaInput,
+    BlockSchemaOutput,
+)
 from backend.data.model import (
     APIKeyCredentials,
     CredentialsField,
@@ -37,7 +43,7 @@ class Place(BaseModel):
 
 
 class GoogleMapsSearchBlock(Block):
-    class Input(BlockSchema):
+    class Input(BlockSchemaInput):
         credentials: CredentialsMetaInput[
             Literal[ProviderName.GOOGLE_MAPS], Literal["api_key"]
         ] = CredentialsField(description="Google Maps API Key")
@@ -58,9 +64,8 @@ class GoogleMapsSearchBlock(Block):
             le=60,
         )
 
-    class Output(BlockSchema):
+    class Output(BlockSchemaOutput):
         place: Place = SchemaField(description="Place found")
-        error: str = SchemaField(description="Error message if the search failed")
 
     def __init__(self):
         super().__init__(

autogpt_platform/backend/backend/blocks/http.py

@@ -8,7 +8,13 @@ from typing import Literal
 import aiofiles
 from pydantic import SecretStr
 
-from backend.data.block import Block, BlockCategory, BlockOutput, BlockSchema
+from backend.data.block import (
+    Block,
+    BlockCategory,
+    BlockOutput,
+    BlockSchemaInput,
+    BlockSchemaOutput,
+)
 from backend.data.model import (
     CredentialsField,
     CredentialsMetaInput,
@@ -62,7 +68,7 @@ class HttpMethod(Enum):
 
 
 class SendWebRequestBlock(Block):
-    class Input(BlockSchema):
+    class Input(BlockSchemaInput):
         url: str = SchemaField(
             description="The URL to send the request to",
             placeholder="https://api.example.com",
@@ -93,7 +99,7 @@ class SendWebRequestBlock(Block):
             default_factory=list,
         )
 
-    class Output(BlockSchema):
+    class Output(BlockSchemaOutput):
         response: object = SchemaField(description="The response from the server")
         client_error: object = SchemaField(description="Errors on 4xx status codes")
         server_error: object = SchemaField(description="Errors on 5xx status codes")

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

@@ -3,13 +3,19 @@ from backend.blocks.hubspot._auth import (
     HubSpotCredentialsField,
     HubSpotCredentialsInput,
 )
-from backend.data.block import Block, BlockCategory, BlockOutput, BlockSchema
+from backend.data.block import (
+    Block,
+    BlockCategory,
+    BlockOutput,
+    BlockSchemaInput,
+    BlockSchemaOutput,
+)
 from backend.data.model import SchemaField
 from backend.util.request import Requests
 
 
 class HubSpotCompanyBlock(Block):
-    class Input(BlockSchema):
+    class Input(BlockSchemaInput):
         credentials: HubSpotCredentialsInput = HubSpotCredentialsField()
         operation: str = SchemaField(
             description="Operation to perform (create, update, get)", default="get"
@@ -22,7 +28,7 @@ class HubSpotCompanyBlock(Block):
             description="Company domain for get/update operations", default=""
         )
 
-    class Output(BlockSchema):
+    class Output(BlockSchemaOutput):
         company: dict = SchemaField(description="Company information")
         status: str = SchemaField(description="Operation status")
 

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

@@ -3,13 +3,19 @@ from backend.blocks.hubspot._auth import (
     HubSpotCredentialsField,
     HubSpotCredentialsInput,
 )
-from backend.data.block import Block, BlockCategory, BlockOutput, BlockSchema
+from backend.data.block import (
+    Block,
+    BlockCategory,
+    BlockOutput,
+    BlockSchemaInput,
+    BlockSchemaOutput,
+)
 from backend.data.model import SchemaField
 from backend.util.request import Requests
 
 
 class HubSpotContactBlock(Block):
-    class Input(BlockSchema):
+    class Input(BlockSchemaInput):
         credentials: HubSpotCredentialsInput = HubSpotCredentialsField()
         operation: str = SchemaField(
             description="Operation to perform (create, update, get)", default="get"
@@ -22,7 +28,7 @@ class HubSpotContactBlock(Block):
             description="Email address for get/update operations", default=""
         )
 
-    class Output(BlockSchema):
+    class Output(BlockSchemaOutput):
         contact: dict = SchemaField(description="Contact information")
         status: str = SchemaField(description="Operation status")
 

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

@@ -5,13 +5,19 @@ from backend.blocks.hubspot._auth import (
     HubSpotCredentialsField,
     HubSpotCredentialsInput,
 )
-from backend.data.block import Block, BlockCategory, BlockOutput, BlockSchema
+from backend.data.block import (
+    Block,
+    BlockCategory,
+    BlockOutput,
+    BlockSchemaInput,
+    BlockSchemaOutput,
+)
 from backend.data.model import SchemaField
 from backend.util.request import Requests
 
 
 class HubSpotEngagementBlock(Block):
-    class Input(BlockSchema):
+    class Input(BlockSchemaInput):
         credentials: HubSpotCredentialsInput = HubSpotCredentialsField()
         operation: str = SchemaField(
             description="Operation to perform (send_email, track_engagement)",
@@ -29,7 +35,7 @@ class HubSpotEngagementBlock(Block):
             default=30,
         )
 
-    class Output(BlockSchema):
+    class Output(BlockSchemaOutput):
         result: dict = SchemaField(description="Operation result")
         status: str = SchemaField(description="Operation status")
 

autogpt_platform/backend/backend/blocks/human_in_the_loop.py

@@ -0,0 +1,160 @@
+import logging
+from typing import Any, Literal
+
+from prisma.enums import ReviewStatus
+
+from backend.data.block import (
+    Block,
+    BlockCategory,
+    BlockOutput,
+    BlockSchemaInput,
+    BlockSchemaOutput,
+)
+from backend.data.execution import ExecutionStatus
+from backend.data.human_review import ReviewResult
+from backend.data.model import SchemaField
+from backend.executor.manager import async_update_node_execution_status
+from backend.util.clients import get_database_manager_async_client
+
+logger = logging.getLogger(__name__)
+
+
+class HumanInTheLoopBlock(Block):
+    """
+    This block pauses execution and waits for human approval or modification of the data.
+
+    When executed, it creates a pending review entry and sets the node execution status
+    to REVIEW. The execution will remain paused until a human user either:
+    - Approves the data (with or without modifications)
+    - Rejects the data
+
+    This is useful for workflows that require human validation or intervention before
+    proceeding to the next steps.
+    """
+
+    class Input(BlockSchemaInput):
+        data: Any = SchemaField(description="The data to be reviewed by a human user")
+        name: str = SchemaField(
+            description="A descriptive name for what this data represents",
+        )
+        editable: bool = SchemaField(
+            description="Whether the human reviewer can edit the data",
+            default=True,
+            advanced=True,
+        )
+
+    class Output(BlockSchemaOutput):
+        reviewed_data: Any = SchemaField(
+            description="The data after human review (may be modified)"
+        )
+        status: Literal["approved", "rejected"] = SchemaField(
+            description="Status of the review: 'approved' or 'rejected'"
+        )
+        review_message: str = SchemaField(
+            description="Any message provided by the reviewer", default=""
+        )
+
+    def __init__(self):
+        super().__init__(
+            id="8b2a7b3c-6e9d-4a5f-8c1b-2e3f4a5b6c7d",
+            description="Pause execution and wait for human approval or modification of data",
+            categories={BlockCategory.BASIC},
+            input_schema=HumanInTheLoopBlock.Input,
+            output_schema=HumanInTheLoopBlock.Output,
+            test_input={
+                "data": {"name": "John Doe", "age": 30},
+                "name": "User profile data",
+                "editable": True,
+            },
+            test_output=[
+                ("reviewed_data", {"name": "John Doe", "age": 30}),
+                ("status", "approved"),
+                ("review_message", ""),
+            ],
+            test_mock={
+                "get_or_create_human_review": lambda *_args, **_kwargs: ReviewResult(
+                    data={"name": "John Doe", "age": 30},
+                    status=ReviewStatus.APPROVED,
+                    message="",
+                    processed=False,
+                    node_exec_id="test-node-exec-id",
+                ),
+                "update_node_execution_status": lambda *_args, **_kwargs: None,
+            },
+        )
+
+    async def run(
+        self,
+        input_data: Input,
+        *,
+        user_id: str,
+        node_exec_id: str,
+        graph_exec_id: str,
+        graph_id: str,
+        graph_version: int,
+        **kwargs,
+    ) -> BlockOutput:
+        """
+        Execute the Human In The Loop block.
+
+        This method uses one function to handle the complete workflow - checking existing reviews
+        and creating pending ones as needed.
+        """
+        try:
+            logger.debug(f"HITL block executing for node {node_exec_id}")
+
+            # Use the data layer to handle the complete workflow
+            db_client = get_database_manager_async_client()
+            result = await db_client.get_or_create_human_review(
+                user_id=user_id,
+                node_exec_id=node_exec_id,
+                graph_exec_id=graph_exec_id,
+                graph_id=graph_id,
+                graph_version=graph_version,
+                input_data=input_data.data,
+                message=input_data.name,
+                editable=input_data.editable,
+            )
+        except Exception as e:
+            logger.error(f"Error in HITL block for node {node_exec_id}: {str(e)}")
+            raise
+
+        # Check if we're waiting for human input
+        if result is None:
+            logger.info(
+                f"HITL block pausing execution for node {node_exec_id} - awaiting human review"
+            )
+            try:
+                # Set node status to REVIEW so execution manager can't mark it as COMPLETED
+                # The VALID_STATUS_TRANSITIONS will then prevent any unwanted status changes
+                # Use the proper wrapper function to ensure websocket events are published
+                await async_update_node_execution_status(
+                    db_client=db_client,
+                    exec_id=node_exec_id,
+                    status=ExecutionStatus.REVIEW,
+                )
+                # Execution pauses here until API routes process the review
+                return
+            except Exception as e:
+                logger.error(
+                    f"Failed to update node status for HITL block {node_exec_id}: {str(e)}"
+                )
+                raise
+
+        # Review is complete (approved or rejected) - check if unprocessed
+        if not result.processed:
+            # Mark as processed before yielding
+            await db_client.update_review_processed_status(
+                node_exec_id=node_exec_id, processed=True
+            )
+
+            if result.status == ReviewStatus.APPROVED:
+                yield "status", "approved"
+                yield "reviewed_data", result.data
+                if result.message:
+                    yield "review_message", result.message
+
+            elif result.status == ReviewStatus.REJECTED:
+                yield "status", "rejected"
+                if result.message:
+                    yield "review_message", result.message

autogpt_platform/backend/backend/blocks/ideogram.py

@@ -4,7 +4,13 @@ from typing import Any, Dict, Literal, Optional
 from pydantic import SecretStr
 from requests.exceptions import RequestException
 
-from backend.data.block import Block, BlockCategory, BlockOutput, BlockSchema
+from backend.data.block import (
+    Block,
+    BlockCategory,
+    BlockOutput,
+    BlockSchemaInput,
+    BlockSchemaOutput,
+)
 from backend.data.model import (
     APIKeyCredentials,
     CredentialsField,
@@ -84,7 +90,7 @@ class UpscaleOption(str, Enum):
 
 
 class IdeogramModelBlock(Block):
-    class Input(BlockSchema):
+    class Input(BlockSchemaInput):
         credentials: CredentialsMetaInput[
             Literal[ProviderName.IDEOGRAM], Literal["api_key"]
         ] = CredentialsField(
@@ -154,9 +160,8 @@ class IdeogramModelBlock(Block):
             advanced=True,
         )
 
-    class Output(BlockSchema):
+    class Output(BlockSchemaOutput):
         result: str = SchemaField(description="Generated image URL")
-        error: str = SchemaField(description="Error message if the model run failed")
 
     def __init__(self):
         super().__init__(