port backend changes ontop of a fresh dev branch

## Changes 🏗️

<img width="250" height="504" alt="Screenshot 2026-01-06 at 17 53 26"
src="https://github.com/user-attachments/assets/52013448-f49c-46b6-b86a-39f98270cbc3"
/>

<img width="300" height="544" alt="Screenshot 2026-01-06 at 17 53 29"
src="https://github.com/user-attachments/assets/e6334034-68e4-4346-9092-3774ab3e8445"
/>

On the **New Builder**:
- right-click on a node menu make it show the context menu
- use the same menu for right-click and when clicking on `...`

## Checklist 📋

### For code changes:
- [x] I have clearly listed my changes in the PR description
- [x] I have made a test plan
- [x] I have tested my changes according to the test plan:
  - [x] Run locally and test the above



<!-- This is an auto-generated comment: release notes by coderabbit.ai
-->
## Summary by CodeRabbit

* **New Features**
* Added a custom right-click context menu for nodes with Copy, Open
agent (when available), and Delete actions; browser default menu is
suppressed while preserving zoom/drag/wiring.
* Introduced reusable SecondaryMenu primitives for context and dropdown
menus.

* **Documentation**
* Added Storybook examples demonstrating the context menu and dropdown
menu usage.

* **Style**
* Updated menu styling and icons with improved consistency and dark-mode
support.

<sub>✏️ Tip: You can customize this high-level summary in your review
settings.</sub>
<!-- end of auto-generated comment: release notes by coderabbit.ai -->

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

@@ -32,9 +32,7 @@ jobs:
     strategy:
       fail-fast: false
       matrix:
-        # Use Python 3.13 to match Docker image (see backend/Dockerfile)
-        # ClamAV tests moved to platform-backend-security-ci.yml (runs on merge to master)
-        python-version: ["3.13"]
+        python-version: ["3.11", "3.12", "3.13"]
     runs-on: ubuntu-latest
 
     services:
@@ -50,6 +48,23 @@ jobs:
         env:
           RABBITMQ_DEFAULT_USER: ${{ env.RABBITMQ_DEFAULT_USER }}
           RABBITMQ_DEFAULT_PASS: ${{ env.RABBITMQ_DEFAULT_PASS }}
+      clamav:
+        image: clamav/clamav-debian:latest
+        ports:
+          - 3310:3310
+        env:
+          CLAMAV_NO_FRESHCLAMD: false
+          CLAMD_CONF_StreamMaxLength: 50M
+          CLAMD_CONF_MaxFileSize: 100M
+          CLAMD_CONF_MaxScanSize: 100M
+          CLAMD_CONF_MaxThreads: 4
+          CLAMD_CONF_ReadTimeout: 300
+        options: >-
+          --health-cmd "clamdscan --version || exit 1"
+          --health-interval 30s
+          --health-timeout 10s
+          --health-retries 5
+          --health-start-period 180s
 
     steps:
       - name: Checkout repository
@@ -131,6 +146,35 @@ jobs:
         # outputs:
         # DB_URL, API_URL, GRAPHQL_URL, ANON_KEY, SERVICE_ROLE_KEY, JWT_SECRET
 
+      - name: Wait for ClamAV to be ready
+        run: |
+          echo "Waiting for ClamAV daemon to start..."
+          max_attempts=60
+          attempt=0
+          
+          until nc -z localhost 3310 || [ $attempt -eq $max_attempts ]; do
+            echo "ClamAV is unavailable - sleeping (attempt $((attempt+1))/$max_attempts)"
+            sleep 5
+            attempt=$((attempt+1))
+          done
+          
+          if [ $attempt -eq $max_attempts ]; then
+            echo "ClamAV failed to start after $((max_attempts*5)) seconds"
+            echo "Checking ClamAV service logs..."
+            docker logs $(docker ps -q --filter "ancestor=clamav/clamav-debian:latest") 2>&1 | tail -50 || echo "No ClamAV container found"
+            exit 1
+          fi
+          
+          echo "ClamAV is ready!"
+          
+          # Verify ClamAV is responsive
+          echo "Testing ClamAV connection..."
+          timeout 10 bash -c 'echo "PING" | nc localhost 3310' || {
+            echo "ClamAV is not responding to PING"
+            docker logs $(docker ps -q --filter "ancestor=clamav/clamav-debian:latest") 2>&1 | tail -50 || echo "No ClamAV container found"
+            exit 1
+          }
+
       - name: Run Database Migrations
         run: poetry run prisma migrate dev --name updates
         env:

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

@@ -1,145 +0,0 @@
-name: AutoGPT Platform - Backend Security CI
-
-# This workflow runs ClamAV-dependent security tests.
-# It only runs on merge to master to avoid the 3-5 minute ClamAV startup time on every PR.
-
-on:
-  push:
-    branches: [master]
-    paths:
-      - "autogpt_platform/backend/**/file*.py"
-      - "autogpt_platform/backend/**/scan*.py"
-      - "autogpt_platform/backend/**/virus*.py"
-      - "autogpt_platform/backend/**/media*.py"
-      - ".github/workflows/platform-backend-security-ci.yml"
-
-concurrency:
-  group: ${{ format('backend-security-ci-{0}', github.sha) }}
-  cancel-in-progress: false
-
-defaults:
-  run:
-    shell: bash
-    working-directory: autogpt_platform/backend
-
-jobs:
-  security-tests:
-    runs-on: ubuntu-latest
-    timeout-minutes: 15
-
-    services:
-      redis:
-        image: redis:latest
-        ports:
-          - 6379:6379
-      clamav:
-        image: clamav/clamav-debian:latest
-        ports:
-          - 3310:3310
-        env:
-          CLAMAV_NO_FRESHCLAMD: false
-          CLAMD_CONF_StreamMaxLength: 50M
-          CLAMD_CONF_MaxFileSize: 100M
-          CLAMD_CONF_MaxScanSize: 100M
-          CLAMD_CONF_MaxThreads: 4
-          CLAMD_CONF_ReadTimeout: 300
-        options: >-
-          --health-cmd "clamdscan --version || exit 1"
-          --health-interval 30s
-          --health-timeout 10s
-          --health-retries 5
-          --health-start-period 180s
-
-    steps:
-      - name: Checkout repository
-        uses: actions/checkout@v4
-        with:
-          fetch-depth: 0
-          submodules: true
-
-      - name: Set up Python 3.13
-        uses: actions/setup-python@v5
-        with:
-          python-version: "3.13"
-
-      - name: Setup Supabase
-        uses: supabase/setup-cli@v1
-        with:
-          version: 1.178.1
-
-      - name: Set up Python dependency cache
-        uses: actions/cache@v4
-        with:
-          path: ~/.cache/pypoetry
-          key: poetry-${{ runner.os }}-${{ hashFiles('autogpt_platform/backend/poetry.lock') }}
-
-      - name: Install Poetry
-        run: |
-          HEAD_POETRY_VERSION=$(python ../../.github/workflows/scripts/get_package_version_from_lockfile.py poetry)
-          echo "Using Poetry version ${HEAD_POETRY_VERSION}"
-          curl -sSL https://install.python-poetry.org | POETRY_VERSION=$HEAD_POETRY_VERSION python3 -
-
-      - name: Install Python dependencies
-        run: poetry install
-
-      - name: Generate Prisma Client
-        run: poetry run prisma generate
-
-      - id: supabase
-        name: Start Supabase
-        working-directory: .
-        run: |
-          supabase init
-          supabase start --exclude postgres-meta,realtime,storage-api,imgproxy,inbucket,studio,edge-runtime,logflare,vector,supavisor
-          supabase status -o env | sed 's/="/=/; s/"$//' >> $GITHUB_OUTPUT
-
-      - name: Wait for ClamAV to be ready
-        run: |
-          echo "Waiting for ClamAV daemon to start..."
-          max_attempts=60
-          attempt=0
-
-          until nc -z localhost 3310 || [ $attempt -eq $max_attempts ]; do
-            echo "ClamAV is unavailable - sleeping (attempt $((attempt+1))/$max_attempts)"
-            sleep 5
-            attempt=$((attempt+1))
-          done
-
-          if [ $attempt -eq $max_attempts ]; then
-            echo "ClamAV failed to start after $((max_attempts*5)) seconds"
-            exit 1
-          fi
-
-          echo "ClamAV is ready!"
-
-      - name: Run Database Migrations
-        run: poetry run prisma migrate dev --name updates
-        env:
-          DATABASE_URL: ${{ steps.supabase.outputs.DB_URL }}
-          DIRECT_URL: ${{ steps.supabase.outputs.DB_URL }}
-
-      - name: Run security-related tests
-        run: |
-          poetry run pytest -v \
-            backend/util/virus_scanner_test.py \
-            backend/util/file_test.py \
-            backend/server/v2/store/media_test.py \
-            -x
-        env:
-          DATABASE_URL: ${{ steps.supabase.outputs.DB_URL }}
-          DIRECT_URL: ${{ steps.supabase.outputs.DB_URL }}
-          SUPABASE_URL: ${{ steps.supabase.outputs.API_URL }}
-          SUPABASE_SERVICE_ROLE_KEY: ${{ steps.supabase.outputs.SERVICE_ROLE_KEY }}
-          JWT_VERIFY_KEY: ${{ steps.supabase.outputs.JWT_SECRET }}
-          REDIS_HOST: "localhost"
-          REDIS_PORT: "6379"
-          ENCRYPTION_KEY: "dvziYgz0KSK8FENhju0ZYi8-fRTfAdlz6YLhdB_jhNw="
-          CLAMAV_SERVICE_HOST: "localhost"
-          CLAMAV_SERVICE_PORT: "3310"
-          CLAMAV_SERVICE_ENABLED: "true"
-
-    env:
-      CI: true
-      PLAIN_OUTPUT: True
-      RUN_ENV: local
-      PORT: 8080

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

@@ -154,78 +154,35 @@ jobs:
       - name: Set up Docker Buildx
         uses: docker/setup-buildx-action@v3
 
-      # Docker image tar caching - loads images from cache in parallel for faster startup
-      - name: Set up Docker image cache
-        id: docker-cache
+      - name: Cache Docker layers
         uses: actions/cache@v4
         with:
-          path: ~/docker-cache
-          key: docker-images-frontend-${{ runner.os }}-${{ hashFiles('autogpt_platform/docker-compose.yml') }}
+          path: /tmp/.buildx-cache
+          key: ${{ runner.os }}-buildx-frontend-test-${{ hashFiles('autogpt_platform/docker-compose.yml', 'autogpt_platform/backend/Dockerfile', 'autogpt_platform/backend/pyproject.toml', 'autogpt_platform/backend/poetry.lock') }}
           restore-keys: |
-            docker-images-frontend-${{ runner.os }}-
-
-      - name: Load or pull Docker images
-        working-directory: autogpt_platform
-        run: |
-          mkdir -p ~/docker-cache
-
-          # Define image list for easy maintenance
-          IMAGES=(
-            "redis:latest"
-            "rabbitmq:management"
-            "kong:2.8.1"
-            "supabase/gotrue:v2.170.0"
-            "supabase/postgres:15.8.1.049"
-          )
-
-          # Check if any cached tar files exist
-          if ls ~/docker-cache/*.tar 1> /dev/null 2>&1; then
-            echo "Docker cache found, loading images in parallel..."
-            for image in "${IMAGES[@]}"; do
-              filename=$(echo "$image" | tr ':/' '--')
-              if [ -f ~/docker-cache/${filename}.tar ]; then
-                echo "Loading $image..."
-                docker load -i ~/docker-cache/${filename}.tar || echo "Warning: Failed to load $image from cache" &
-              fi
-            done
-            wait
-            echo "All cached images loaded"
-          else
-            echo "No Docker cache found, pulling images in parallel..."
-            for image in "${IMAGES[@]}"; do
-              docker pull "$image" &
-            done
-            wait
-
-            # Only save cache on main branches (not PRs) to avoid cache pollution
-            if [[ "${{ github.ref }}" == "refs/heads/master" ]] || [[ "${{ github.ref }}" == "refs/heads/dev" ]]; then
-              echo "Saving Docker images to cache in parallel..."
-              for image in "${IMAGES[@]}"; do
-                filename=$(echo "$image" | tr ':/' '--')
-                echo "Saving $image..."
-                docker save -o ~/docker-cache/${filename}.tar "$image" || echo "Warning: Failed to save $image" &
-              done
-              wait
-              echo "Docker image cache saved"
-            else
-              echo "Skipping cache save for PR/feature branch"
-            fi
-          fi
-
-          echo "Docker images ready for use"
+            ${{ runner.os }}-buildx-frontend-test-
 
       - name: Run docker compose
         run: |
           NEXT_PUBLIC_PW_TEST=true docker compose -f ../docker-compose.yml up -d
         env:
           DOCKER_BUILDKIT: 1
+          BUILDX_CACHE_FROM: type=local,src=/tmp/.buildx-cache
+          BUILDX_CACHE_TO: type=local,dest=/tmp/.buildx-cache-new,mode=max
+
+      - name: Move cache
+        run: |
+          rm -rf /tmp/.buildx-cache
+          if [ -d "/tmp/.buildx-cache-new" ]; then
+            mv /tmp/.buildx-cache-new /tmp/.buildx-cache
+          fi
 
       - name: Wait for services to be ready
         run: |
           echo "Waiting for rest_server to be ready..."
-          timeout 30 sh -c 'until curl -f http://localhost:8006/health 2>/dev/null; do sleep 2; done' || echo "Rest server health check timeout, continuing..."
+          timeout 60 sh -c 'until curl -f http://localhost:8006/health 2>/dev/null; do sleep 2; done' || echo "Rest server health check timeout, continuing..."
           echo "Waiting for database to be ready..."
-          timeout 30 sh -c 'until docker compose -f ../docker-compose.yml exec -T db pg_isready -U postgres 2>/dev/null; do sleep 2; done' || echo "Database ready check timeout, continuing..."
+          timeout 60 sh -c 'until docker compose -f ../docker-compose.yml exec -T db pg_isready -U postgres 2>/dev/null; do sleep 2; done' || echo "Database ready check timeout, continuing..."
 
       - name: Create E2E test data
         run: |
@@ -264,27 +221,9 @@ jobs:
       - name: Install dependencies
         run: pnpm install --frozen-lockfile
 
-      # Playwright browser caching - saves 30-60s when cache hits
-      - name: Get Playwright version
-        id: playwright-version
-        run: |
-          echo "version=$(pnpm list @playwright/test --json | jq -r '.[0].dependencies["@playwright/test"].version')" >> $GITHUB_OUTPUT
-
-      - name: Cache Playwright browsers
-        uses: actions/cache@v4
-        id: playwright-cache
-        with:
-          path: ~/.cache/ms-playwright
-          key: playwright-${{ runner.os }}-${{ steps.playwright-version.outputs.version }}
-
-      - name: Install Playwright browsers
-        if: steps.playwright-cache.outputs.cache-hit != 'true'
+      - name: Install Browser 'chromium'
         run: pnpm playwright install --with-deps chromium
 
-      - name: Install Playwright deps only (when cache hit)
-        if: steps.playwright-cache.outputs.cache-hit == 'true'
-        run: pnpm playwright install-deps chromium
-
       - name: Run Playwright tests
         run: pnpm test:no-build
 

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

@@ -83,66 +83,6 @@ jobs:
         run: |
           cp ../backend/.env.default ../backend/.env
 
-      # Docker image tar caching - loads images from cache in parallel for faster startup
-      - name: Set up Docker image cache
-        id: docker-cache
-        uses: actions/cache@v4
-        with:
-          path: ~/docker-cache
-          key: docker-images-fullstack-${{ runner.os }}-${{ hashFiles('autogpt_platform/docker-compose.yml') }}
-          restore-keys: |
-            docker-images-fullstack-${{ runner.os }}-
-
-      - name: Load or pull Docker images
-        working-directory: autogpt_platform
-        run: |
-          mkdir -p ~/docker-cache
-
-          # Define image list for easy maintenance
-          IMAGES=(
-            "redis:latest"
-            "rabbitmq:management"
-            "kong:2.8.1"
-            "supabase/gotrue:v2.170.0"
-            "supabase/postgres:15.8.1.049"
-          )
-
-          # Check if any cached tar files exist
-          if ls ~/docker-cache/*.tar 1> /dev/null 2>&1; then
-            echo "Docker cache found, loading images in parallel..."
-            for image in "${IMAGES[@]}"; do
-              filename=$(echo "$image" | tr ':/' '--')
-              if [ -f ~/docker-cache/${filename}.tar ]; then
-                echo "Loading $image..."
-                docker load -i ~/docker-cache/${filename}.tar || echo "Warning: Failed to load $image from cache" &
-              fi
-            done
-            wait
-            echo "All cached images loaded"
-          else
-            echo "No Docker cache found, pulling images in parallel..."
-            for image in "${IMAGES[@]}"; do
-              docker pull "$image" &
-            done
-            wait
-
-            # Only save cache on main branches (not PRs) to avoid cache pollution
-            if [[ "${{ github.ref }}" == "refs/heads/master" ]] || [[ "${{ github.ref }}" == "refs/heads/dev" ]]; then
-              echo "Saving Docker images to cache in parallel..."
-              for image in "${IMAGES[@]}"; do
-                filename=$(echo "$image" | tr ':/' '--')
-                echo "Saving $image..."
-                docker save -o ~/docker-cache/${filename}.tar "$image" || echo "Warning: Failed to save $image" &
-              done
-              wait
-              echo "Docker image cache saved"
-            else
-              echo "Skipping cache save for PR/feature branch"
-            fi
-          fi
-
-          echo "Docker images ready for use"
-
       - name: Run docker compose
         run: |
           docker compose -f ../docker-compose.yml --profile local --profile deps_backend up -d
@@ -164,9 +104,9 @@ jobs:
       - name: Wait for services to be ready
         run: |
           echo "Waiting for rest_server to be ready..."
-          timeout 30 sh -c 'until curl -f http://localhost:8006/health 2>/dev/null; do sleep 2; done' || echo "Rest server health check timeout, continuing..."
+          timeout 60 sh -c 'until curl -f http://localhost:8006/health 2>/dev/null; do sleep 2; done' || echo "Rest server health check timeout, continuing..."
           echo "Waiting for database to be ready..."
-          timeout 30 sh -c 'until docker compose -f ../docker-compose.yml exec -T db pg_isready -U postgres 2>/dev/null; do sleep 2; done' || echo "Database ready check timeout, continuing..."
+          timeout 60 sh -c 'until docker compose -f ../docker-compose.yml exec -T db pg_isready -U postgres 2>/dev/null; do sleep 2; done' || echo "Database ready check timeout, continuing..."
 
       - name: Generate API queries
         run: pnpm generate:api:force

autogpt_platform/Makefile

@@ -6,12 +6,11 @@ start-core:
 
 # Stop core services
 stop-core:
-	docker compose stop deps
+	docker compose stop 
 
 reset-db:
+	docker compose stop db
 	rm -rf db/docker/volumes/db/data
-	cd backend && poetry run prisma migrate deploy
-	cd backend && poetry run prisma generate
 	
 # View logs for core services
 logs-core:
@@ -58,4 +57,4 @@ help:
 	@echo "  run-backend - Run the backend FastAPI server"
 	@echo "  run-frontend - Run the frontend Next.js development server"
 	@echo "  test-data - Run the test data creator"
-	@echo "  load-store-agents - Load store agents from agents/ folder into test database"
+	@echo "  load-store-agents - Load store agents from agents/ folder into test database"

autogpt_platform/autogpt_libs/autogpt_libs/api_key/keysmith.py

@@ -57,6 +57,9 @@ class APIKeySmith:
 
     def hash_key(self, raw_key: str) -> tuple[str, str]:
         """Migrate a legacy hash to secure hash format."""
+        if not raw_key.startswith(self.PREFIX):
+            raise ValueError("Key without 'agpt_' prefix would fail validation")
+
         salt = self._generate_salt()
         hash = self._hash_key_with_salt(raw_key, salt)
         return hash, salt.hex()

autogpt_platform/autogpt_libs/autogpt_libs/auth/helpers.py

@@ -1,29 +1,25 @@
 from fastapi import FastAPI
-from fastapi.openapi.utils import get_openapi
 
 from .jwt_utils import bearer_jwt_auth
 
 
 def add_auth_responses_to_openapi(app: FastAPI) -> None:
     """
-    Set up custom OpenAPI schema generation that adds 401 responses
+    Patch a FastAPI instance's `openapi()` method to add 401 responses
     to all authenticated endpoints.
 
     This is needed when using HTTPBearer with auto_error=False to get proper
     401 responses instead of 403, but FastAPI only automatically adds security
     responses when auto_error=True.
     """
+    # Wrap current method to allow stacking OpenAPI schema modifiers like this
+    wrapped_openapi = app.openapi
 
     def custom_openapi():
         if app.openapi_schema:
             return app.openapi_schema
 
-        openapi_schema = get_openapi(
-            title=app.title,
-            version=app.version,
-            description=app.description,
-            routes=app.routes,
-        )
+        openapi_schema = wrapped_openapi()
 
         # Add 401 response to all endpoints that have security requirements
         for path, methods in openapi_schema["paths"].items():

autogpt_platform/backend/TESTING.md

@@ -108,7 +108,7 @@ import fastapi.testclient
 import pytest
 from pytest_snapshot.plugin import Snapshot
 
-from backend.server.v2.myroute import router
+from backend.api.features.myroute import router
 
 app = fastapi.FastAPI()
 app.include_router(router)
@@ -149,7 +149,7 @@ These provide the easiest way to set up authentication mocking in test modules:
 import fastapi
 import fastapi.testclient
 import pytest
-from backend.server.v2.myroute import router
+from backend.api.features.myroute import router
 
 app = fastapi.FastAPI()
 app.include_router(router)

autogpt_platform/backend/backend/api/conn_manager.py

@@ -3,12 +3,12 @@ from typing import Dict, Set
 
 from fastapi import WebSocket
 
+from backend.api.model import NotificationPayload, WSMessage, WSMethod
 from backend.data.execution import (
     ExecutionEventType,
     GraphExecutionEvent,
     NodeExecutionEvent,
 )
-from backend.server.model import NotificationPayload, WSMessage, WSMethod
 
 _EVENT_TYPE_TO_METHOD_MAP: dict[ExecutionEventType, WSMethod] = {
     ExecutionEventType.GRAPH_EXEC_UPDATE: WSMethod.GRAPH_EXECUTION_EVENT,

autogpt_platform/backend/backend/api/conn_manager_test.py

@@ -4,13 +4,13 @@ from unittest.mock import AsyncMock
 import pytest
 from fastapi import WebSocket
 
+from backend.api.conn_manager import ConnectionManager
+from backend.api.model import NotificationPayload, WSMessage, WSMethod
 from backend.data.execution import (
     ExecutionStatus,
     GraphExecutionEvent,
     NodeExecutionEvent,
 )
-from backend.server.conn_manager import ConnectionManager
-from backend.server.model import NotificationPayload, WSMessage, WSMethod
 
 
 @pytest.fixture

autogpt_platform/backend/backend/api/external/fastapi_app.py

@@ -0,0 +1,25 @@
+from fastapi import FastAPI
+
+from backend.api.middleware.security import SecurityHeadersMiddleware
+from backend.monitoring.instrumentation import instrument_fastapi
+
+from .v1.routes import v1_router
+
+external_api = FastAPI(
+    title="AutoGPT External API",
+    description="External API for AutoGPT integrations",
+    docs_url="/docs",
+    version="1.0",
+)
+
+external_api.add_middleware(SecurityHeadersMiddleware)
+external_api.include_router(v1_router, prefix="/v1")
+
+# Add Prometheus instrumentation
+instrument_fastapi(
+    external_api,
+    service_name="external-api",
+    expose_endpoint=True,
+    endpoint="/metrics",
+    include_in_schema=True,
+)

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

@@ -0,0 +1,107 @@
+from fastapi import HTTPException, Security, status
+from fastapi.security import APIKeyHeader, HTTPAuthorizationCredentials, HTTPBearer
+from prisma.enums import APIKeyPermission
+
+from backend.data.auth.api_key import APIKeyInfo, validate_api_key
+from backend.data.auth.base import APIAuthorizationInfo
+from backend.data.auth.oauth import (
+    InvalidClientError,
+    InvalidTokenError,
+    OAuthAccessTokenInfo,
+    validate_access_token,
+)
+
+api_key_header = APIKeyHeader(name="X-API-Key", auto_error=False)
+bearer_auth = HTTPBearer(auto_error=False)
+
+
+async def require_api_key(api_key: str | None = Security(api_key_header)) -> APIKeyInfo:
+    """Middleware for API key authentication only"""
+    if api_key is None:
+        raise HTTPException(
+            status_code=status.HTTP_401_UNAUTHORIZED, detail="Missing API key"
+        )
+
+    api_key_obj = await validate_api_key(api_key)
+
+    if not api_key_obj:
+        raise HTTPException(
+            status_code=status.HTTP_401_UNAUTHORIZED, detail="Invalid API key"
+        )
+
+    return api_key_obj
+
+
+async def require_access_token(
+    bearer: HTTPAuthorizationCredentials | None = Security(bearer_auth),
+) -> OAuthAccessTokenInfo:
+    """Middleware for OAuth access token authentication only"""
+    if bearer is None:
+        raise HTTPException(
+            status_code=status.HTTP_401_UNAUTHORIZED,
+            detail="Missing Authorization header",
+        )
+
+    try:
+        token_info, _ = await validate_access_token(bearer.credentials)
+    except (InvalidClientError, InvalidTokenError) as e:
+        raise HTTPException(status_code=status.HTTP_401_UNAUTHORIZED, detail=str(e))
+
+    return token_info
+
+
+async def require_auth(
+    api_key: str | None = Security(api_key_header),
+    bearer: HTTPAuthorizationCredentials | None = Security(bearer_auth),
+) -> APIAuthorizationInfo:
+    """
+    Unified authentication middleware supporting both API keys and OAuth tokens.
+
+    Supports two authentication methods, which are checked in order:
+    1. X-API-Key header (existing API key authentication)
+    2. Authorization: Bearer <token> header (OAuth access token)
+
+    Returns:
+        APIAuthorizationInfo: base class of both APIKeyInfo and OAuthAccessTokenInfo.
+    """
+    # Try API key first
+    if api_key is not None:
+        api_key_info = await validate_api_key(api_key)
+        if api_key_info:
+            return api_key_info
+        raise HTTPException(
+            status_code=status.HTTP_401_UNAUTHORIZED, detail="Invalid API key"
+        )
+
+    # Try OAuth bearer token
+    if bearer is not None:
+        try:
+            token_info, _ = await validate_access_token(bearer.credentials)
+            return token_info
+        except (InvalidClientError, InvalidTokenError) as e:
+            raise HTTPException(status_code=status.HTTP_401_UNAUTHORIZED, detail=str(e))
+
+    # No credentials provided
+    raise HTTPException(
+        status_code=status.HTTP_401_UNAUTHORIZED,
+        detail="Missing authentication. Provide API key or access token.",
+    )
+
+
+def require_permission(permission: APIKeyPermission):
+    """
+    Dependency function for checking specific permissions
+    (works with API keys and OAuth tokens)
+    """
+
+    async def check_permission(
+        auth: APIAuthorizationInfo = Security(require_auth),
+    ) -> APIAuthorizationInfo:
+        if permission not in auth.scopes:
+            raise HTTPException(
+                status_code=status.HTTP_403_FORBIDDEN,
+                detail=f"Missing required permission: {permission.value}",
+            )
+        return auth
+
+    return check_permission

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

@@ -16,7 +16,9 @@ from fastapi import APIRouter, Body, HTTPException, Path, Security, status
 from prisma.enums import APIKeyPermission
 from pydantic import BaseModel, Field, SecretStr
 
-from backend.data.api_key import APIKeyInfo
+from backend.api.external.middleware import require_permission
+from backend.api.features.integrations.models import get_all_provider_names
+from backend.data.auth.base import APIAuthorizationInfo
 from backend.data.model import (
     APIKeyCredentials,
     Credentials,
@@ -28,8 +30,6 @@ from backend.data.model import (
 from backend.integrations.creds_manager import IntegrationCredentialsManager
 from backend.integrations.oauth import CREDENTIALS_BY_PROVIDER, HANDLERS_BY_NAME
 from backend.integrations.providers import ProviderName
-from backend.server.external.middleware import require_permission
-from backend.server.integrations.models import get_all_provider_names
 from backend.util.settings import Settings
 
 if TYPE_CHECKING:
@@ -255,7 +255,7 @@ def _get_oauth_handler_for_external(
 
 @integrations_router.get("/providers", response_model=list[ProviderInfo])
 async def list_providers(
-    api_key: APIKeyInfo = Security(
+    auth: APIAuthorizationInfo = Security(
         require_permission(APIKeyPermission.READ_INTEGRATIONS)
     ),
 ) -> list[ProviderInfo]:
@@ -319,7 +319,7 @@ async def list_providers(
 async def initiate_oauth(
     provider: Annotated[str, Path(title="The OAuth provider")],
     request: OAuthInitiateRequest,
-    api_key: APIKeyInfo = Security(
+    auth: APIAuthorizationInfo = Security(
         require_permission(APIKeyPermission.MANAGE_INTEGRATIONS)
     ),
 ) -> OAuthInitiateResponse:
@@ -337,7 +337,10 @@ async def initiate_oauth(
     if not validate_callback_url(request.callback_url):
         raise HTTPException(
             status_code=status.HTTP_400_BAD_REQUEST,
-            detail=f"Callback URL origin is not allowed. Allowed origins: {settings.config.external_oauth_callback_origins}",
+            detail=(
+                f"Callback URL origin is not allowed. "
+                f"Allowed origins: {settings.config.external_oauth_callback_origins}",
+            ),
         )
 
     # Validate provider
@@ -359,13 +362,15 @@ async def initiate_oauth(
     )
 
     # Store state token with external flow metadata
+    # Note: initiated_by_api_key_id is only available for API key auth, not OAuth
+    api_key_id = getattr(auth, "id", None) if auth.type == "api_key" else None
     state_token, code_challenge = await creds_manager.store.store_state_token(
-        user_id=api_key.user_id,
+        user_id=auth.user_id,
         provider=provider if isinstance(provider_name, str) else provider_name.value,
         scopes=request.scopes,
         callback_url=request.callback_url,
         state_metadata=request.state_metadata,
-        initiated_by_api_key_id=api_key.id,
+        initiated_by_api_key_id=api_key_id,
     )
 
     # Build login URL
@@ -393,7 +398,7 @@ async def initiate_oauth(
 async def complete_oauth(
     provider: Annotated[str, Path(title="The OAuth provider")],
     request: OAuthCompleteRequest,
-    api_key: APIKeyInfo = Security(
+    auth: APIAuthorizationInfo = Security(
         require_permission(APIKeyPermission.MANAGE_INTEGRATIONS)
     ),
 ) -> OAuthCompleteResponse:
@@ -406,7 +411,7 @@ async def complete_oauth(
     """
     # Verify state token
     valid_state = await creds_manager.store.verify_state_token(
-        api_key.user_id, request.state_token, provider
+        auth.user_id, request.state_token, provider
     )
 
     if not valid_state:
@@ -453,7 +458,7 @@ async def complete_oauth(
         )
 
     # Store credentials
-    await creds_manager.create(api_key.user_id, credentials)
+    await creds_manager.create(auth.user_id, credentials)
 
     logger.info(f"Successfully completed external OAuth for provider {provider}")
 
@@ -470,7 +475,7 @@ async def complete_oauth(
 
 @integrations_router.get("/credentials", response_model=list[CredentialSummary])
 async def list_credentials(
-    api_key: APIKeyInfo = Security(
+    auth: APIAuthorizationInfo = Security(
         require_permission(APIKeyPermission.READ_INTEGRATIONS)
     ),
 ) -> list[CredentialSummary]:
@@ -479,7 +484,7 @@ async def list_credentials(
 
     Returns metadata about each credential without exposing sensitive tokens.
     """
-    credentials = await creds_manager.store.get_all_creds(api_key.user_id)
+    credentials = await creds_manager.store.get_all_creds(auth.user_id)
     return [
         CredentialSummary(
             id=cred.id,
@@ -499,7 +504,7 @@ async def list_credentials(
 )
 async def list_credentials_by_provider(
     provider: Annotated[str, Path(title="The provider to list credentials for")],
-    api_key: APIKeyInfo = Security(
+    auth: APIAuthorizationInfo = Security(
         require_permission(APIKeyPermission.READ_INTEGRATIONS)
     ),
 ) -> list[CredentialSummary]:
@@ -507,7 +512,7 @@ async def list_credentials_by_provider(
     List credentials for a specific provider.
     """
     credentials = await creds_manager.store.get_creds_by_provider(
-        api_key.user_id, provider
+        auth.user_id, provider
     )
     return [
         CredentialSummary(
@@ -536,7 +541,7 @@ async def create_credential(
         CreateUserPasswordCredentialRequest,
         CreateHostScopedCredentialRequest,
     ] = Body(..., discriminator="type"),
-    api_key: APIKeyInfo = Security(
+    auth: APIAuthorizationInfo = Security(
         require_permission(APIKeyPermission.MANAGE_INTEGRATIONS)
     ),
 ) -> CreateCredentialResponse:
@@ -591,7 +596,7 @@ async def create_credential(
 
     # Store credentials
     try:
-        await creds_manager.create(api_key.user_id, credentials)
+        await creds_manager.create(auth.user_id, credentials)
     except Exception as e:
         logger.error(f"Failed to store credentials: {e}")
         raise HTTPException(
@@ -623,7 +628,7 @@ class DeleteCredentialResponse(BaseModel):
 async def delete_credential(
     provider: Annotated[str, Path(title="The provider")],
     cred_id: Annotated[str, Path(title="The credential ID to delete")],
-    api_key: APIKeyInfo = Security(
+    auth: APIAuthorizationInfo = Security(
         require_permission(APIKeyPermission.DELETE_INTEGRATIONS)
     ),
 ) -> DeleteCredentialResponse:
@@ -634,7 +639,7 @@ async def delete_credential(
     use the main API's delete endpoint which handles webhook cleanup and
     token revocation.
     """
-    creds = await creds_manager.store.get_creds_by_id(api_key.user_id, cred_id)
+    creds = await creds_manager.store.get_creds_by_id(auth.user_id, cred_id)
     if not creds:
         raise HTTPException(
             status_code=status.HTTP_404_NOT_FOUND, detail="Credentials not found"
@@ -645,6 +650,6 @@ async def delete_credential(
             detail="Credentials do not match the specified provider",
         )
 
-    await creds_manager.delete(api_key.user_id, cred_id)
+    await creds_manager.delete(auth.user_id, cred_id)
 
     return DeleteCredentialResponse(deleted=True, credentials_id=cred_id)

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

@@ -5,46 +5,60 @@ from typing import Annotated, Any, Literal, Optional, Sequence
 
 from fastapi import APIRouter, Body, HTTPException, Security
 from prisma.enums import AgentExecutionStatus, APIKeyPermission
+from pydantic import BaseModel, Field
 from typing_extensions import TypedDict
 
+import backend.api.features.store.cache as store_cache
+import backend.api.features.store.model as store_model
 import backend.data.block
-import backend.server.v2.store.cache as store_cache
-import backend.server.v2.store.model as store_model
+from backend.api.external.middleware import require_permission
 from backend.data import execution as execution_db
 from backend.data import graph as graph_db
-from backend.data.api_key import APIKeyInfo
+from backend.data import user as user_db
+from backend.data.auth.base import APIAuthorizationInfo
 from backend.data.block import BlockInput, CompletedBlockOutput
 from backend.executor.utils import add_graph_execution
-from backend.server.external.middleware import require_permission
 from backend.util.settings import Settings
 
+from .integrations import integrations_router
+from .tools import tools_router
+
 settings = Settings()
 logger = logging.getLogger(__name__)
 
 v1_router = APIRouter()
 
-
-class NodeOutput(TypedDict):
-    key: str
-    value: Any
+v1_router.include_router(integrations_router)
+v1_router.include_router(tools_router)
 
 
-class ExecutionNode(TypedDict):
-    node_id: str
-    input: Any
-    output: dict[str, Any]
+class UserInfoResponse(BaseModel):
+    id: str
+    name: Optional[str]
+    email: str
+    timezone: str = Field(
+        description="The user's last known timezone (e.g. 'Europe/Amsterdam'), "
+        "or 'not-set' if not set"
+    )
 
 
-class ExecutionNodeOutput(TypedDict):
-    node_id: str
-    outputs: list[NodeOutput]
+@v1_router.get(
+    path="/me",
+    tags=["user", "meta"],
+)
+async def get_user_info(
+    auth: APIAuthorizationInfo = Security(
+        require_permission(APIKeyPermission.IDENTITY)
+    ),
+) -> UserInfoResponse:
+    user = await user_db.get_user_by_id(auth.user_id)
 
-
-class GraphExecutionResult(TypedDict):
-    execution_id: str
-    status: str
-    nodes: list[ExecutionNode]
-    output: Optional[list[dict[str, str]]]
+    return UserInfoResponse(
+        id=user.id,
+        name=user.name,
+        email=user.email,
+        timezone=user.timezone,
+    )
 
 
 @v1_router.get(
@@ -65,7 +79,9 @@ async def get_graph_blocks() -> Sequence[dict[Any, Any]]:
 async def execute_graph_block(
     block_id: str,
     data: BlockInput,
-    api_key: APIKeyInfo = Security(require_permission(APIKeyPermission.EXECUTE_BLOCK)),
+    auth: APIAuthorizationInfo = Security(
+        require_permission(APIKeyPermission.EXECUTE_BLOCK)
+    ),
 ) -> CompletedBlockOutput:
     obj = backend.data.block.get_block(block_id)
     if not obj:
@@ -85,12 +101,14 @@ async def execute_graph(
     graph_id: str,
     graph_version: int,
     node_input: Annotated[dict[str, Any], Body(..., embed=True, default_factory=dict)],
-    api_key: APIKeyInfo = Security(require_permission(APIKeyPermission.EXECUTE_GRAPH)),
+    auth: APIAuthorizationInfo = Security(
+        require_permission(APIKeyPermission.EXECUTE_GRAPH)
+    ),
 ) -> dict[str, Any]:
     try:
         graph_exec = await add_graph_execution(
             graph_id=graph_id,
-            user_id=api_key.user_id,
+            user_id=auth.user_id,
             inputs=node_input,
             graph_version=graph_version,
         )
@@ -100,6 +118,19 @@ async def execute_graph(
         raise HTTPException(status_code=400, detail=msg)
 
 
+class ExecutionNode(TypedDict):
+    node_id: str
+    input: Any
+    output: dict[str, Any]
+
+
+class GraphExecutionResult(TypedDict):
+    execution_id: str
+    status: str
+    nodes: list[ExecutionNode]
+    output: Optional[list[dict[str, str]]]
+
+
 @v1_router.get(
     path="/graphs/{graph_id}/executions/{graph_exec_id}/results",
     tags=["graphs"],
@@ -107,10 +138,12 @@ async def execute_graph(
 async def get_graph_execution_results(
     graph_id: str,
     graph_exec_id: str,
-    api_key: APIKeyInfo = Security(require_permission(APIKeyPermission.READ_GRAPH)),
+    auth: APIAuthorizationInfo = Security(
+        require_permission(APIKeyPermission.READ_GRAPH)
+    ),
 ) -> GraphExecutionResult:
     graph_exec = await execution_db.get_graph_execution(
-        user_id=api_key.user_id,
+        user_id=auth.user_id,
         execution_id=graph_exec_id,
         include_node_executions=True,
     )
@@ -122,7 +155,7 @@ async def get_graph_execution_results(
     if not await graph_db.get_graph(
         graph_id=graph_exec.graph_id,
         version=graph_exec.graph_version,
-        user_id=api_key.user_id,
+        user_id=auth.user_id,
     ):
         raise HTTPException(status_code=404, detail=f"Graph #{graph_id} not found.")
 

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

@@ -14,19 +14,19 @@ from fastapi import APIRouter, Security
 from prisma.enums import APIKeyPermission
 from pydantic import BaseModel, Field
 
-from backend.data.api_key import APIKeyInfo
-from backend.server.external.middleware import require_permission
-from backend.server.v2.chat.model import ChatSession
-from backend.server.v2.chat.tools import find_agent_tool, run_agent_tool
-from backend.server.v2.chat.tools.models import ToolResponseBase
+from backend.api.external.middleware import require_permission
+from backend.api.features.chat.model import ChatSession
+from backend.api.features.chat.tools import find_agent_tool, run_agent_tool
+from backend.api.features.chat.tools.models import ToolResponseBase
+from backend.data.auth.base import APIAuthorizationInfo
 
 logger = logging.getLogger(__name__)
 
 tools_router = APIRouter(prefix="/tools", tags=["tools"])
 
-# Note: We use Security() as a function parameter dependency (api_key: APIKeyInfo = Security(...))
+# Note: We use Security() as a function parameter dependency (auth: APIAuthorizationInfo = Security(...))
 # rather than in the decorator's dependencies= list. This avoids duplicate permission checks
-# while still enforcing auth AND giving us access to the api_key for extracting user_id.
+# while still enforcing auth AND giving us access to auth for extracting user_id.
 
 
 # Request models
@@ -80,7 +80,9 @@ def _create_ephemeral_session(user_id: str | None) -> ChatSession:
 )
 async def find_agent(
     request: FindAgentRequest,
-    api_key: APIKeyInfo = Security(require_permission(APIKeyPermission.USE_TOOLS)),
+    auth: APIAuthorizationInfo = Security(
+        require_permission(APIKeyPermission.USE_TOOLS)
+    ),
 ) -> dict[str, Any]:
     """
     Search for agents in the marketplace based on capabilities and user needs.
@@ -91,9 +93,9 @@ async def find_agent(
     Returns:
         List of matching agents or no results response
     """
-    session = _create_ephemeral_session(api_key.user_id)
+    session = _create_ephemeral_session(auth.user_id)
     result = await find_agent_tool._execute(
-        user_id=api_key.user_id,
+        user_id=auth.user_id,
         session=session,
         query=request.query,
     )
@@ -105,7 +107,9 @@ async def find_agent(
 )
 async def run_agent(
     request: RunAgentRequest,
-    api_key: APIKeyInfo = Security(require_permission(APIKeyPermission.USE_TOOLS)),
+    auth: APIAuthorizationInfo = Security(
+        require_permission(APIKeyPermission.USE_TOOLS)
+    ),
 ) -> dict[str, Any]:
     """
     Run or schedule an agent from the marketplace.
@@ -129,9 +133,9 @@ async def run_agent(
         - execution_started: If agent was run or scheduled successfully
         - error: If something went wrong
     """
-    session = _create_ephemeral_session(api_key.user_id)
+    session = _create_ephemeral_session(auth.user_id)
     result = await run_agent_tool._execute(
-        user_id=api_key.user_id,
+        user_id=auth.user_id,
         session=session,
         username_agent_slug=request.username_agent_slug,
         inputs=request.inputs,

autogpt_platform/backend/backend/api/features/admin/credit_admin_routes.py

@@ -6,9 +6,10 @@ from fastapi import APIRouter, Body, Security
 from prisma.enums import CreditTransactionType
 
 from backend.data.credit import admin_get_user_history, get_user_credit_model
-from backend.server.v2.admin.model import AddUserCreditsResponse, UserHistoryResponse
 from backend.util.json import SafeJson
 
+from .model import AddUserCreditsResponse, UserHistoryResponse
+
 logger = logging.getLogger(__name__)
 
 

autogpt_platform/backend/backend/api/features/admin/credit_admin_routes_test.py

@@ -9,14 +9,15 @@ import pytest_mock
 from autogpt_libs.auth.jwt_utils import get_jwt_payload
 from pytest_snapshot.plugin import Snapshot
 
-import backend.server.v2.admin.credit_admin_routes as credit_admin_routes
-import backend.server.v2.admin.model as admin_model
 from backend.data.model import UserTransaction
 from backend.util.json import SafeJson
 from backend.util.models import Pagination
 
+from .credit_admin_routes import router as credit_admin_router
+from .model import UserHistoryResponse
+
 app = fastapi.FastAPI()
-app.include_router(credit_admin_routes.router)
+app.include_router(credit_admin_router)
 
 client = fastapi.testclient.TestClient(app)
 
@@ -30,7 +31,7 @@ def setup_app_admin_auth(mock_jwt_admin):
 
 
 def test_add_user_credits_success(
-    mocker: pytest_mock.MockFixture,
+    mocker: pytest_mock.MockerFixture,
     configured_snapshot: Snapshot,
     admin_user_id: str,
     target_user_id: str,
@@ -42,7 +43,7 @@ def test_add_user_credits_success(
         return_value=(1500, "transaction-123-uuid")
     )
     mocker.patch(
-        "backend.server.v2.admin.credit_admin_routes.get_user_credit_model",
+        "backend.api.features.admin.credit_admin_routes.get_user_credit_model",
         return_value=mock_credit_model,
     )
 
@@ -84,7 +85,7 @@ def test_add_user_credits_success(
 
 
 def test_add_user_credits_negative_amount(
-    mocker: pytest_mock.MockFixture,
+    mocker: pytest_mock.MockerFixture,
     snapshot: Snapshot,
 ) -> None:
     """Test credit deduction by admin (negative amount)"""
@@ -94,7 +95,7 @@ def test_add_user_credits_negative_amount(
         return_value=(200, "transaction-456-uuid")
     )
     mocker.patch(
-        "backend.server.v2.admin.credit_admin_routes.get_user_credit_model",
+        "backend.api.features.admin.credit_admin_routes.get_user_credit_model",
         return_value=mock_credit_model,
     )
 
@@ -119,12 +120,12 @@ def test_add_user_credits_negative_amount(
 
 
 def test_get_user_history_success(
-    mocker: pytest_mock.MockFixture,
+    mocker: pytest_mock.MockerFixture,
     snapshot: Snapshot,
 ) -> None:
     """Test successful retrieval of user credit history"""
     # Mock the admin_get_user_history function
-    mock_history_response = admin_model.UserHistoryResponse(
+    mock_history_response = UserHistoryResponse(
         history=[
             UserTransaction(
                 user_id="user-1",
@@ -150,7 +151,7 @@ def test_get_user_history_success(
     )
 
     mocker.patch(
-        "backend.server.v2.admin.credit_admin_routes.admin_get_user_history",
+        "backend.api.features.admin.credit_admin_routes.admin_get_user_history",
         return_value=mock_history_response,
     )
 
@@ -170,12 +171,12 @@ def test_get_user_history_success(
 
 
 def test_get_user_history_with_filters(
-    mocker: pytest_mock.MockFixture,
+    mocker: pytest_mock.MockerFixture,
     snapshot: Snapshot,
 ) -> None:
     """Test user credit history with search and filter parameters"""
     # Mock the admin_get_user_history function
-    mock_history_response = admin_model.UserHistoryResponse(
+    mock_history_response = UserHistoryResponse(
         history=[
             UserTransaction(
                 user_id="user-3",
@@ -194,7 +195,7 @@ def test_get_user_history_with_filters(
     )
 
     mock_get_history = mocker.patch(
-        "backend.server.v2.admin.credit_admin_routes.admin_get_user_history",
+        "backend.api.features.admin.credit_admin_routes.admin_get_user_history",
         return_value=mock_history_response,
     )
 
@@ -230,12 +231,12 @@ def test_get_user_history_with_filters(
 
 
 def test_get_user_history_empty_results(
-    mocker: pytest_mock.MockFixture,
+    mocker: pytest_mock.MockerFixture,
     snapshot: Snapshot,
 ) -> None:
     """Test user credit history with no results"""
     # Mock empty history response
-    mock_history_response = admin_model.UserHistoryResponse(
+    mock_history_response = UserHistoryResponse(
         history=[],
         pagination=Pagination(
             total_items=0,
@@ -246,7 +247,7 @@ def test_get_user_history_empty_results(
     )
 
     mocker.patch(
-        "backend.server.v2.admin.credit_admin_routes.admin_get_user_history",
+        "backend.api.features.admin.credit_admin_routes.admin_get_user_history",
         return_value=mock_history_response,
     )
 

autogpt_platform/backend/backend/api/features/admin/store_admin_routes.py

@@ -7,9 +7,9 @@ import fastapi
 import fastapi.responses
 import prisma.enums
 
-import backend.server.v2.store.cache as store_cache
-import backend.server.v2.store.db
-import backend.server.v2.store.model
+import backend.api.features.store.cache as store_cache
+import backend.api.features.store.db as store_db
+import backend.api.features.store.model as store_model
 import backend.util.json
 
 logger = logging.getLogger(__name__)
@@ -24,7 +24,7 @@ router = fastapi.APIRouter(
 @router.get(
     "/listings",
     summary="Get Admin Listings History",
-    response_model=backend.server.v2.store.model.StoreListingsWithVersionsResponse,
+    response_model=store_model.StoreListingsWithVersionsResponse,
 )
 async def get_admin_listings_with_versions(
     status: typing.Optional[prisma.enums.SubmissionStatus] = None,
@@ -48,7 +48,7 @@ async def get_admin_listings_with_versions(
         StoreListingsWithVersionsResponse with listings and their versions
     """
     try:
-        listings = await backend.server.v2.store.db.get_admin_listings_with_versions(
+        listings = await store_db.get_admin_listings_with_versions(
             status=status,
             search_query=search,
             page=page,
@@ -68,11 +68,11 @@ async def get_admin_listings_with_versions(
 @router.post(
     "/submissions/{store_listing_version_id}/review",
     summary="Review Store Submission",
-    response_model=backend.server.v2.store.model.StoreSubmission,
+    response_model=store_model.StoreSubmission,
 )
 async def review_submission(
     store_listing_version_id: str,
-    request: backend.server.v2.store.model.ReviewSubmissionRequest,
+    request: store_model.ReviewSubmissionRequest,
     user_id: str = fastapi.Security(autogpt_libs.auth.get_user_id),
 ):
     """
@@ -87,12 +87,10 @@ async def review_submission(
         StoreSubmission with updated review information
     """
     try:
-        already_approved = (
-            await backend.server.v2.store.db.check_submission_already_approved(
-                store_listing_version_id=store_listing_version_id,
-            )
+        already_approved = await store_db.check_submission_already_approved(
+            store_listing_version_id=store_listing_version_id,
         )
-        submission = await backend.server.v2.store.db.review_store_submission(
+        submission = await store_db.review_store_submission(
             store_listing_version_id=store_listing_version_id,
             is_approved=request.is_approved,
             external_comments=request.comments,
@@ -136,7 +134,7 @@ async def admin_download_agent_file(
     Raises:
         HTTPException: If the agent is not found or an unexpected error occurs.
     """
-    graph_data = await backend.server.v2.store.db.get_agent_as_admin(
+    graph_data = await store_db.get_agent_as_admin(
         user_id=user_id,
         store_listing_version_id=store_listing_version_id,
     )

autogpt_platform/backend/backend/api/features/analytics.py

@@ -6,10 +6,11 @@ from typing import Annotated
 import fastapi
 import pydantic
 from autogpt_libs.auth import get_user_id
+from autogpt_libs.auth.dependencies import requires_user
 
 import backend.data.analytics
 
-router = fastapi.APIRouter()
+router = fastapi.APIRouter(dependencies=[fastapi.Security(requires_user)])
 logger = logging.getLogger(__name__)
 
 

autogpt_platform/backend/backend/api/features/analytics_test.py

@@ -0,0 +1,340 @@
+"""Tests for analytics API endpoints."""
+
+import json
+from unittest.mock import AsyncMock, Mock
+
+import fastapi
+import fastapi.testclient
+import pytest
+import pytest_mock
+from pytest_snapshot.plugin import Snapshot
+
+from .analytics import router as analytics_router
+
+app = fastapi.FastAPI()
+app.include_router(analytics_router)
+
+client = fastapi.testclient.TestClient(app)
+
+
+@pytest.fixture(autouse=True)
+def setup_app_auth(mock_jwt_user):
+    """Setup auth overrides for all tests in this module."""
+    from autogpt_libs.auth.jwt_utils import get_jwt_payload
+
+    app.dependency_overrides[get_jwt_payload] = mock_jwt_user["get_jwt_payload"]
+    yield
+    app.dependency_overrides.clear()
+
+
+# =============================================================================
+# /log_raw_metric endpoint tests
+# =============================================================================
+
+
+def test_log_raw_metric_success(
+    mocker: pytest_mock.MockFixture,
+    configured_snapshot: Snapshot,
+    test_user_id: str,
+) -> None:
+    """Test successful raw metric logging."""
+    mock_result = Mock(id="metric-123-uuid")
+    mock_log_metric = mocker.patch(
+        "backend.data.analytics.log_raw_metric",
+        new_callable=AsyncMock,
+        return_value=mock_result,
+    )
+
+    request_data = {
+        "metric_name": "page_load_time",
+        "metric_value": 2.5,
+        "data_string": "/dashboard",
+    }
+
+    response = client.post("/log_raw_metric", json=request_data)
+
+    assert response.status_code == 200, f"Unexpected response: {response.text}"
+    assert response.json() == "metric-123-uuid"
+
+    mock_log_metric.assert_called_once_with(
+        user_id=test_user_id,
+        metric_name="page_load_time",
+        metric_value=2.5,
+        data_string="/dashboard",
+    )
+
+    configured_snapshot.assert_match(
+        json.dumps({"metric_id": response.json()}, indent=2, sort_keys=True),
+        "analytics_log_metric_success",
+    )
+
+
+@pytest.mark.parametrize(
+    "metric_value,metric_name,data_string,test_id",
+    [
+        (100, "api_calls_count", "external_api", "integer_value"),
+        (0, "error_count", "no_errors", "zero_value"),
+        (-5.2, "temperature_delta", "cooling", "negative_value"),
+        (1.23456789, "precision_test", "float_precision", "float_precision"),
+        (999999999, "large_number", "max_value", "large_number"),
+        (0.0000001, "tiny_number", "min_value", "tiny_number"),
+    ],
+)
+def test_log_raw_metric_various_values(
+    mocker: pytest_mock.MockFixture,
+    configured_snapshot: Snapshot,
+    metric_value: float,
+    metric_name: str,
+    data_string: str,
+    test_id: str,
+) -> None:
+    """Test raw metric logging with various metric values."""
+    mock_result = Mock(id=f"metric-{test_id}-uuid")
+    mocker.patch(
+        "backend.data.analytics.log_raw_metric",
+        new_callable=AsyncMock,
+        return_value=mock_result,
+    )
+
+    request_data = {
+        "metric_name": metric_name,
+        "metric_value": metric_value,
+        "data_string": data_string,
+    }
+
+    response = client.post("/log_raw_metric", json=request_data)
+
+    assert response.status_code == 200, f"Failed for {test_id}: {response.text}"
+
+    configured_snapshot.assert_match(
+        json.dumps(
+            {"metric_id": response.json(), "test_case": test_id},
+            indent=2,
+            sort_keys=True,
+        ),
+        f"analytics_metric_{test_id}",
+    )
+
+
+@pytest.mark.parametrize(
+    "invalid_data,expected_error",
+    [
+        ({}, "Field required"),
+        ({"metric_name": "test"}, "Field required"),
+        (
+            {"metric_name": "test", "metric_value": "not_a_number", "data_string": "x"},
+            "Input should be a valid number",
+        ),
+        (
+            {"metric_name": "", "metric_value": 1.0, "data_string": "test"},
+            "String should have at least 1 character",
+        ),
+        (
+            {"metric_name": "test", "metric_value": 1.0, "data_string": ""},
+            "String should have at least 1 character",
+        ),
+    ],
+    ids=[
+        "empty_request",
+        "missing_metric_value_and_data_string",
+        "invalid_metric_value_type",
+        "empty_metric_name",
+        "empty_data_string",
+    ],
+)
+def test_log_raw_metric_validation_errors(
+    invalid_data: dict,
+    expected_error: str,
+) -> None:
+    """Test validation errors for invalid metric requests."""
+    response = client.post("/log_raw_metric", json=invalid_data)
+
+    assert response.status_code == 422
+    error_detail = response.json()
+    assert "detail" in error_detail, f"Missing 'detail' in error: {error_detail}"
+
+    error_text = json.dumps(error_detail)
+    assert (
+        expected_error in error_text
+    ), f"Expected '{expected_error}' in error response: {error_text}"
+
+
+def test_log_raw_metric_service_error(
+    mocker: pytest_mock.MockFixture,
+    test_user_id: str,
+) -> None:
+    """Test error handling when analytics service fails."""
+    mocker.patch(
+        "backend.data.analytics.log_raw_metric",
+        new_callable=AsyncMock,
+        side_effect=Exception("Database connection failed"),
+    )
+
+    request_data = {
+        "metric_name": "test_metric",
+        "metric_value": 1.0,
+        "data_string": "test",
+    }
+
+    response = client.post("/log_raw_metric", json=request_data)
+
+    assert response.status_code == 500
+    error_detail = response.json()["detail"]
+    assert "Database connection failed" in error_detail["message"]
+    assert "hint" in error_detail
+
+
+# =============================================================================
+# /log_raw_analytics endpoint tests
+# =============================================================================
+
+
+def test_log_raw_analytics_success(
+    mocker: pytest_mock.MockFixture,
+    configured_snapshot: Snapshot,
+    test_user_id: str,
+) -> None:
+    """Test successful raw analytics logging."""
+    mock_result = Mock(id="analytics-789-uuid")
+    mock_log_analytics = mocker.patch(
+        "backend.data.analytics.log_raw_analytics",
+        new_callable=AsyncMock,
+        return_value=mock_result,
+    )
+
+    request_data = {
+        "type": "user_action",
+        "data": {
+            "action": "button_click",
+            "button_id": "submit_form",
+            "timestamp": "2023-01-01T00:00:00Z",
+            "metadata": {"form_type": "registration", "fields_filled": 5},
+        },
+        "data_index": "button_click_submit_form",
+    }
+
+    response = client.post("/log_raw_analytics", json=request_data)
+
+    assert response.status_code == 200, f"Unexpected response: {response.text}"
+    assert response.json() == "analytics-789-uuid"
+
+    mock_log_analytics.assert_called_once_with(
+        test_user_id,
+        "user_action",
+        request_data["data"],
+        "button_click_submit_form",
+    )
+
+    configured_snapshot.assert_match(
+        json.dumps({"analytics_id": response.json()}, indent=2, sort_keys=True),
+        "analytics_log_analytics_success",
+    )
+
+
+def test_log_raw_analytics_complex_data(
+    mocker: pytest_mock.MockFixture,
+    configured_snapshot: Snapshot,
+) -> None:
+    """Test raw analytics logging with complex nested data structures."""
+    mock_result = Mock(id="analytics-complex-uuid")
+    mocker.patch(
+        "backend.data.analytics.log_raw_analytics",
+        new_callable=AsyncMock,
+        return_value=mock_result,
+    )
+
+    request_data = {
+        "type": "agent_execution",
+        "data": {
+            "agent_id": "agent_123",
+            "execution_id": "exec_456",
+            "status": "completed",
+            "duration_ms": 3500,
+            "nodes_executed": 15,
+            "blocks_used": [
+                {"block_id": "llm_block", "count": 3},
+                {"block_id": "http_block", "count": 5},
+                {"block_id": "code_block", "count": 2},
+            ],
+            "errors": [],
+            "metadata": {
+                "trigger": "manual",
+                "user_tier": "premium",
+                "environment": "production",
+            },
+        },
+        "data_index": "agent_123_exec_456",
+    }
+
+    response = client.post("/log_raw_analytics", json=request_data)
+
+    assert response.status_code == 200
+
+    configured_snapshot.assert_match(
+        json.dumps(
+            {"analytics_id": response.json(), "logged_data": request_data["data"]},
+            indent=2,
+            sort_keys=True,
+        ),
+        "analytics_log_analytics_complex_data",
+    )
+
+
+@pytest.mark.parametrize(
+    "invalid_data,expected_error",
+    [
+        ({}, "Field required"),
+        ({"type": "test"}, "Field required"),
+        (
+            {"type": "test", "data": "not_a_dict", "data_index": "test"},
+            "Input should be a valid dictionary",
+        ),
+        ({"type": "test", "data": {"key": "value"}}, "Field required"),
+    ],
+    ids=[
+        "empty_request",
+        "missing_data_and_data_index",
+        "invalid_data_type",
+        "missing_data_index",
+    ],
+)
+def test_log_raw_analytics_validation_errors(
+    invalid_data: dict,
+    expected_error: str,
+) -> None:
+    """Test validation errors for invalid analytics requests."""
+    response = client.post("/log_raw_analytics", json=invalid_data)
+
+    assert response.status_code == 422
+    error_detail = response.json()
+    assert "detail" in error_detail, f"Missing 'detail' in error: {error_detail}"
+
+    error_text = json.dumps(error_detail)
+    assert (
+        expected_error in error_text
+    ), f"Expected '{expected_error}' in error response: {error_text}"
+
+
+def test_log_raw_analytics_service_error(
+    mocker: pytest_mock.MockFixture,
+    test_user_id: str,
+) -> None:
+    """Test error handling when analytics service fails."""
+    mocker.patch(
+        "backend.data.analytics.log_raw_analytics",
+        new_callable=AsyncMock,
+        side_effect=Exception("Analytics DB unreachable"),
+    )
+
+    request_data = {
+        "type": "test_event",
+        "data": {"key": "value"},
+        "data_index": "test_index",
+    }
+
+    response = client.post("/log_raw_analytics", json=request_data)
+
+    assert response.status_code == 500
+    error_detail = response.json()["detail"]
+    assert "Analytics DB unreachable" in error_detail["message"]
+    assert "hint" in error_detail

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

@@ -6,17 +6,20 @@ from typing import Sequence
 
 import prisma
 
+import backend.api.features.library.db as library_db
+import backend.api.features.library.model as library_model
+import backend.api.features.store.db as store_db
+import backend.api.features.store.model as store_model
 import backend.data.block
-import backend.server.v2.library.db as library_db
-import backend.server.v2.library.model as library_model
-import backend.server.v2.store.db as store_db
-import backend.server.v2.store.model as store_model
 from backend.blocks import load_all_blocks
 from backend.blocks.llm import LlmModel
 from backend.data.block import AnyBlockSchema, BlockCategory, BlockInfo, BlockSchema
 from backend.data.db import query_raw_with_schema
 from backend.integrations.providers import ProviderName
-from backend.server.v2.builder.model import (
+from backend.util.cache import cached
+from backend.util.models import Pagination
+
+from .model import (
     BlockCategoryResponse,
     BlockResponse,
     BlockType,
@@ -26,8 +29,6 @@ from backend.server.v2.builder.model import (
     ProviderResponse,
     SearchEntry,
 )
-from backend.util.cache import cached
-from backend.util.models import Pagination
 
 logger = logging.getLogger(__name__)
 llm_models = [name.name.lower().replace("_", " ") for name in LlmModel]

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

@@ -2,8 +2,8 @@ from typing import Literal
 
 from pydantic import BaseModel
 
-import backend.server.v2.library.model as library_model
-import backend.server.v2.store.model as store_model
+import backend.api.features.library.model as library_model
+import backend.api.features.store.model as store_model
 from backend.data.block import BlockInfo
 from backend.integrations.providers import ProviderName
 from backend.util.models import Pagination

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

@@ -4,11 +4,12 @@ from typing import Annotated, Sequence
 import fastapi
 from autogpt_libs.auth.dependencies import get_user_id, requires_user
 
-import backend.server.v2.builder.db as builder_db
-import backend.server.v2.builder.model as builder_model
 from backend.integrations.providers import ProviderName
 from backend.util.models import Pagination
 
+from . import db as builder_db
+from . import model as builder_model
+
 logger = logging.getLogger(__name__)
 
 router = fastapi.APIRouter(

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

@@ -12,7 +12,11 @@ class ChatConfig(BaseSettings):
 
     # OpenAI API Configuration
     model: str = Field(
-        default="qwen/qwen3-235b-a22b-2507", description="Default model to use"
+        default="anthropic/claude-opus-4.5", description="Default model to use"
+    )
+    title_model: str = Field(
+        default="openai/gpt-4o-mini",
+        description="Model to use for generating session titles (should be fast/cheap)",
     )
     api_key: str | None = Field(default=None, description="OpenAI API key")
     base_url: str | None = Field(
@@ -72,8 +76,31 @@ class ChatConfig(BaseSettings):
                 v = "https://openrouter.ai/api/v1"
         return v
 
+    # Prompt paths for different contexts
+    PROMPT_PATHS: dict[str, str] = {
+        "default": "prompts/chat_system.md",
+        "onboarding": "prompts/onboarding_system.md",
+    }
+
+    def get_system_prompt_for_type(
+        self, prompt_type: str = "default", **template_vars
+    ) -> str:
+        """Load and render a system prompt by type.
+
+        Args:
+            prompt_type: The type of prompt to load ("default" or "onboarding")
+            **template_vars: Variables to substitute in the template
+
+        Returns:
+            Rendered system prompt string
+        """
+        prompt_path_str = self.PROMPT_PATHS.get(
+            prompt_type, self.PROMPT_PATHS["default"]
+        )
+        return self._load_prompt_from_path(prompt_path_str, **template_vars)
+
     def get_system_prompt(self, **template_vars) -> str:
-        """Load and render the system prompt from file.
+        """Load and render the default system prompt from file.
 
         Args:
             **template_vars: Variables to substitute in the template
@@ -82,9 +109,21 @@ class ChatConfig(BaseSettings):
             Rendered system prompt string
 
         """
+        return self._load_prompt_from_path(self.system_prompt_path, **template_vars)
+
+    def _load_prompt_from_path(self, prompt_path_str: str, **template_vars) -> str:
+        """Load and render a system prompt from a given path.
+
+        Args:
+            prompt_path_str: Path to the prompt file relative to chat module
+            **template_vars: Variables to substitute in the template
+
+        Returns:
+            Rendered system prompt string
+        """
         # Get the path relative to this module
         module_dir = Path(__file__).parent
-        prompt_path = module_dir / self.system_prompt_path
+        prompt_path = module_dir / prompt_path_str
 
         # Check for .j2 extension first (Jinja2 template)
         j2_path = Path(str(prompt_path) + ".j2")

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

@@ -0,0 +1,215 @@
+"""Database operations for chat sessions."""
+
+import logging
+from datetime import UTC, datetime
+from typing import Any, cast
+
+from prisma.models import ChatMessage as PrismaChatMessage
+from prisma.models import ChatSession as PrismaChatSession
+from prisma.types import (
+    ChatMessageCreateInput,
+    ChatSessionCreateInput,
+    ChatSessionUpdateInput,
+)
+
+from backend.util.json import SafeJson
+
+logger = logging.getLogger(__name__)
+
+
+async def get_chat_session(session_id: str) -> PrismaChatSession | None:
+    """Get a chat session by ID from the database."""
+    session = await PrismaChatSession.prisma().find_unique(
+        where={"id": session_id},
+        include={"Messages": True},
+    )
+    if session and session.Messages:
+        # Sort messages by sequence in Python since Prisma doesn't support order_by in include
+        session.Messages.sort(key=lambda m: m.sequence)
+    return session
+
+
+async def create_chat_session(
+    session_id: str,
+    user_id: str | None,
+) -> PrismaChatSession:
+    """Create a new chat session in the database."""
+    data = ChatSessionCreateInput(
+        id=session_id,
+        userId=user_id,
+        credentials=SafeJson({}),
+        successfulAgentRuns=SafeJson({}),
+        successfulAgentSchedules=SafeJson({}),
+    )
+    return await PrismaChatSession.prisma().create(
+        data=data,
+        include={"Messages": True},
+    )
+
+
+async def update_chat_session(
+    session_id: str,
+    credentials: dict[str, Any] | None = None,
+    successful_agent_runs: dict[str, Any] | None = None,
+    successful_agent_schedules: dict[str, Any] | None = None,
+    total_prompt_tokens: int | None = None,
+    total_completion_tokens: int | None = None,
+    title: str | None = None,
+) -> PrismaChatSession | None:
+    """Update a chat session's metadata."""
+    data: ChatSessionUpdateInput = {"updatedAt": datetime.now(UTC)}
+
+    if credentials is not None:
+        data["credentials"] = SafeJson(credentials)
+    if successful_agent_runs is not None:
+        data["successfulAgentRuns"] = SafeJson(successful_agent_runs)
+    if successful_agent_schedules is not None:
+        data["successfulAgentSchedules"] = SafeJson(successful_agent_schedules)
+    if total_prompt_tokens is not None:
+        data["totalPromptTokens"] = total_prompt_tokens
+    if total_completion_tokens is not None:
+        data["totalCompletionTokens"] = total_completion_tokens
+    if title is not None:
+        data["title"] = title
+
+    session = await PrismaChatSession.prisma().update(
+        where={"id": session_id},
+        data=data,
+        include={"Messages": True},
+    )
+    if session and session.Messages:
+        session.Messages.sort(key=lambda m: m.sequence)
+    return session
+
+
+async def add_chat_message(
+    session_id: str,
+    role: str,
+    sequence: int,
+    content: str | None = None,
+    name: str | None = None,
+    tool_call_id: str | None = None,
+    refusal: str | None = None,
+    tool_calls: list[dict[str, Any]] | None = None,
+    function_call: dict[str, Any] | None = None,
+) -> PrismaChatMessage:
+    """Add a message to a chat session."""
+    # Build the input dict dynamically - only include optional fields when they
+    # have values, as Prisma TypedDict validation fails when optional fields
+    # are explicitly set to None
+    data: dict[str, Any] = {
+        "Session": {"connect": {"id": session_id}},
+        "role": role,
+        "sequence": sequence,
+    }
+
+    # Add optional string fields
+    if content is not None:
+        data["content"] = content
+    if name is not None:
+        data["name"] = name
+    if tool_call_id is not None:
+        data["toolCallId"] = tool_call_id
+    if refusal is not None:
+        data["refusal"] = refusal
+
+    # Add optional JSON fields only when they have values
+    if tool_calls is not None:
+        data["toolCalls"] = SafeJson(tool_calls)
+    if function_call is not None:
+        data["functionCall"] = SafeJson(function_call)
+
+    # Update session's updatedAt timestamp
+    await PrismaChatSession.prisma().update(
+        where={"id": session_id},
+        data={"updatedAt": datetime.now(UTC)},
+    )
+
+    return await PrismaChatMessage.prisma().create(
+        data=cast(ChatMessageCreateInput, data)
+    )
+
+
+async def add_chat_messages_batch(
+    session_id: str,
+    messages: list[dict[str, Any]],
+    start_sequence: int,
+) -> list[PrismaChatMessage]:
+    """Add multiple messages to a chat session in a batch."""
+    if not messages:
+        return []
+
+    created_messages = []
+    for i, msg in enumerate(messages):
+        # Build the input dict dynamically - only include optional JSON fields
+        # when they have values, as Prisma TypedDict validation fails when
+        # optional fields are explicitly set to None
+        data: dict[str, Any] = {
+            "Session": {"connect": {"id": session_id}},
+            "role": msg["role"],
+            "sequence": start_sequence + i,
+        }
+
+        # Add optional string fields
+        if msg.get("content") is not None:
+            data["content"] = msg["content"]
+        if msg.get("name") is not None:
+            data["name"] = msg["name"]
+        if msg.get("tool_call_id") is not None:
+            data["toolCallId"] = msg["tool_call_id"]
+        if msg.get("refusal") is not None:
+            data["refusal"] = msg["refusal"]
+
+        # Add optional JSON fields only when they have values
+        if msg.get("tool_calls") is not None:
+            data["toolCalls"] = SafeJson(msg["tool_calls"])
+        if msg.get("function_call") is not None:
+            data["functionCall"] = SafeJson(msg["function_call"])
+
+        created = await PrismaChatMessage.prisma().create(
+            data=cast(ChatMessageCreateInput, data)
+        )
+        created_messages.append(created)
+
+    # Update session's updatedAt timestamp
+    await PrismaChatSession.prisma().update(
+        where={"id": session_id},
+        data={"updatedAt": datetime.now(UTC)},
+    )
+
+    return created_messages
+
+
+async def get_user_chat_sessions(
+    user_id: str,
+    limit: int = 50,
+    offset: int = 0,
+) -> list[PrismaChatSession]:
+    """Get chat sessions for a user, ordered by most recent."""
+    return await PrismaChatSession.prisma().find_many(
+        where={"userId": user_id},
+        order={"updatedAt": "desc"},
+        take=limit,
+        skip=offset,
+    )
+
+
+async def get_user_session_count(user_id: str) -> int:
+    """Get the total number of chat sessions for a user."""
+    return await PrismaChatSession.prisma().count(where={"userId": user_id})
+
+
+async def delete_chat_session(session_id: str) -> bool:
+    """Delete a chat session and all its messages."""
+    try:
+        await PrismaChatSession.prisma().delete(where={"id": session_id})
+        return True
+    except Exception as e:
+        logger.error(f"Failed to delete chat session {session_id}: {e}")
+        return False
+
+
+async def get_chat_session_message_count(session_id: str) -> int:
+    """Get the number of messages in a chat session."""
+    count = await PrismaChatMessage.prisma().count(where={"sessionId": session_id})
+    return count

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

@@ -0,0 +1,473 @@
+import logging
+import uuid
+from datetime import UTC, datetime
+
+from openai.types.chat import (
+    ChatCompletionAssistantMessageParam,
+    ChatCompletionDeveloperMessageParam,
+    ChatCompletionFunctionMessageParam,
+    ChatCompletionMessageParam,
+    ChatCompletionSystemMessageParam,
+    ChatCompletionToolMessageParam,
+    ChatCompletionUserMessageParam,
+)
+from openai.types.chat.chat_completion_assistant_message_param import FunctionCall
+from openai.types.chat.chat_completion_message_tool_call_param import (
+    ChatCompletionMessageToolCallParam,
+    Function,
+)
+from prisma.models import ChatMessage as PrismaChatMessage
+from prisma.models import ChatSession as PrismaChatSession
+from pydantic import BaseModel
+
+from backend.data.redis_client import get_redis_async
+from backend.util import json
+from backend.util.exceptions import RedisError
+
+from . import db as chat_db
+from .config import ChatConfig
+
+logger = logging.getLogger(__name__)
+config = ChatConfig()
+
+
+class ChatMessage(BaseModel):
+    role: str
+    content: str | None = None
+    name: str | None = None
+    tool_call_id: str | None = None
+    refusal: str | None = None
+    tool_calls: list[dict] | None = None
+    function_call: dict | None = None
+
+
+class Usage(BaseModel):
+    prompt_tokens: int
+    completion_tokens: int
+    total_tokens: int
+
+
+class ChatSession(BaseModel):
+    session_id: str
+    user_id: str | None
+    title: str | None = None
+    messages: list[ChatMessage]
+    usage: list[Usage]
+    credentials: dict[str, dict] = {}  # Map of provider -> credential metadata
+    started_at: datetime
+    updated_at: datetime
+    successful_agent_runs: dict[str, int] = {}
+    successful_agent_schedules: dict[str, int] = {}
+
+    @staticmethod
+    def new(user_id: str | None) -> "ChatSession":
+        return ChatSession(
+            session_id=str(uuid.uuid4()),
+            user_id=user_id,
+            title=None,
+            messages=[],
+            usage=[],
+            credentials={},
+            started_at=datetime.now(UTC),
+            updated_at=datetime.now(UTC),
+        )
+
+    @staticmethod
+    def from_prisma(
+        prisma_session: PrismaChatSession,
+        prisma_messages: list[PrismaChatMessage] | None = None,
+    ) -> "ChatSession":
+        """Convert Prisma models to Pydantic ChatSession."""
+        messages = []
+        if prisma_messages:
+            for msg in prisma_messages:
+                tool_calls = None
+                if msg.toolCalls:
+                    tool_calls = (
+                        json.loads(msg.toolCalls)
+                        if isinstance(msg.toolCalls, str)
+                        else msg.toolCalls
+                    )
+
+                function_call = None
+                if msg.functionCall:
+                    function_call = (
+                        json.loads(msg.functionCall)
+                        if isinstance(msg.functionCall, str)
+                        else msg.functionCall
+                    )
+
+                messages.append(
+                    ChatMessage(
+                        role=msg.role,
+                        content=msg.content,
+                        name=msg.name,
+                        tool_call_id=msg.toolCallId,
+                        refusal=msg.refusal,
+                        tool_calls=tool_calls,
+                        function_call=function_call,
+                    )
+                )
+
+        # Parse JSON fields from Prisma
+        credentials = (
+            json.loads(prisma_session.credentials)
+            if isinstance(prisma_session.credentials, str)
+            else prisma_session.credentials or {}
+        )
+        successful_agent_runs = (
+            json.loads(prisma_session.successfulAgentRuns)
+            if isinstance(prisma_session.successfulAgentRuns, str)
+            else prisma_session.successfulAgentRuns or {}
+        )
+        successful_agent_schedules = (
+            json.loads(prisma_session.successfulAgentSchedules)
+            if isinstance(prisma_session.successfulAgentSchedules, str)
+            else prisma_session.successfulAgentSchedules or {}
+        )
+
+        # Calculate usage from token counts
+        usage = []
+        if prisma_session.totalPromptTokens or prisma_session.totalCompletionTokens:
+            usage.append(
+                Usage(
+                    prompt_tokens=prisma_session.totalPromptTokens or 0,
+                    completion_tokens=prisma_session.totalCompletionTokens or 0,
+                    total_tokens=(prisma_session.totalPromptTokens or 0)
+                    + (prisma_session.totalCompletionTokens or 0),
+                )
+            )
+
+        return ChatSession(
+            session_id=prisma_session.id,
+            user_id=prisma_session.userId,
+            title=prisma_session.title,
+            messages=messages,
+            usage=usage,
+            credentials=credentials,
+            started_at=prisma_session.createdAt,
+            updated_at=prisma_session.updatedAt,
+            successful_agent_runs=successful_agent_runs,
+            successful_agent_schedules=successful_agent_schedules,
+        )
+
+    def to_openai_messages(self) -> list[ChatCompletionMessageParam]:
+        messages = []
+        for message in self.messages:
+            if message.role == "developer":
+                m = ChatCompletionDeveloperMessageParam(
+                    role="developer",
+                    content=message.content or "",
+                )
+                if message.name:
+                    m["name"] = message.name
+                messages.append(m)
+            elif message.role == "system":
+                m = ChatCompletionSystemMessageParam(
+                    role="system",
+                    content=message.content or "",
+                )
+                if message.name:
+                    m["name"] = message.name
+                messages.append(m)
+            elif message.role == "user":
+                m = ChatCompletionUserMessageParam(
+                    role="user",
+                    content=message.content or "",
+                )
+                if message.name:
+                    m["name"] = message.name
+                messages.append(m)
+            elif message.role == "assistant":
+                m = ChatCompletionAssistantMessageParam(
+                    role="assistant",
+                    content=message.content or "",
+                )
+                if message.function_call:
+                    m["function_call"] = FunctionCall(
+                        arguments=message.function_call["arguments"],
+                        name=message.function_call["name"],
+                    )
+                if message.refusal:
+                    m["refusal"] = message.refusal
+                if message.tool_calls:
+                    t: list[ChatCompletionMessageToolCallParam] = []
+                    for tool_call in message.tool_calls:
+                        # Tool calls are stored with nested structure: {id, type, function: {name, arguments}}
+                        function_data = tool_call.get("function", {})
+
+                        # Skip tool calls that are missing required fields
+                        if "id" not in tool_call or "name" not in function_data:
+                            logger.warning(
+                                f"Skipping invalid tool call: missing required fields. "
+                                f"Got: {tool_call.keys()}, function keys: {function_data.keys()}"
+                            )
+                            continue
+
+                        # Arguments are stored as a JSON string
+                        arguments_str = function_data.get("arguments", "{}")
+
+                        t.append(
+                            ChatCompletionMessageToolCallParam(
+                                id=tool_call["id"],
+                                type="function",
+                                function=Function(
+                                    arguments=arguments_str,
+                                    name=function_data["name"],
+                                ),
+                            )
+                        )
+                    m["tool_calls"] = t
+                if message.name:
+                    m["name"] = message.name
+                messages.append(m)
+            elif message.role == "tool":
+                messages.append(
+                    ChatCompletionToolMessageParam(
+                        role="tool",
+                        content=message.content or "",
+                        tool_call_id=message.tool_call_id or "",
+                    )
+                )
+            elif message.role == "function":
+                messages.append(
+                    ChatCompletionFunctionMessageParam(
+                        role="function",
+                        content=message.content,
+                        name=message.name or "",
+                    )
+                )
+        return messages
+
+
+async def _get_session_from_cache(session_id: str) -> ChatSession | None:
+    """Get a chat session from Redis cache."""
+    redis_key = f"chat:session:{session_id}"
+    async_redis = await get_redis_async()
+    raw_session: bytes | None = await async_redis.get(redis_key)
+
+    if raw_session is None:
+        return None
+
+    try:
+        session = ChatSession.model_validate_json(raw_session)
+        logger.info(
+            f"Loading session {session_id} from cache: "
+            f"message_count={len(session.messages)}, "
+            f"roles={[m.role for m in session.messages]}"
+        )
+        return session
+    except Exception as e:
+        logger.error(f"Failed to deserialize session {session_id}: {e}", exc_info=True)
+        raise RedisError(f"Corrupted session data for {session_id}") from e
+
+
+async def _cache_session(session: ChatSession) -> None:
+    """Cache a chat session in Redis."""
+    redis_key = f"chat:session:{session.session_id}"
+    async_redis = await get_redis_async()
+    await async_redis.setex(redis_key, config.session_ttl, session.model_dump_json())
+
+
+async def _get_session_from_db(session_id: str) -> ChatSession | None:
+    """Get a chat session from the database."""
+    prisma_session = await chat_db.get_chat_session(session_id)
+    if not prisma_session:
+        return None
+
+    messages = prisma_session.Messages
+    logger.info(
+        f"Loading session {session_id} from DB: "
+        f"has_messages={messages is not None}, "
+        f"message_count={len(messages) if messages else 0}, "
+        f"roles={[m.role for m in messages] if messages else []}"
+    )
+
+    return ChatSession.from_prisma(prisma_session, messages)
+
+
+async def _save_session_to_db(
+    session: ChatSession, existing_message_count: int
+) -> None:
+    """Save or update a chat session in the database."""
+    # Check if session exists in DB
+    existing = await chat_db.get_chat_session(session.session_id)
+
+    if not existing:
+        # Create new session
+        await chat_db.create_chat_session(
+            session_id=session.session_id,
+            user_id=session.user_id,
+        )
+        existing_message_count = 0
+
+    # Calculate total tokens from usage
+    total_prompt = sum(u.prompt_tokens for u in session.usage)
+    total_completion = sum(u.completion_tokens for u in session.usage)
+
+    # Update session metadata
+    await chat_db.update_chat_session(
+        session_id=session.session_id,
+        credentials=session.credentials,
+        successful_agent_runs=session.successful_agent_runs,
+        successful_agent_schedules=session.successful_agent_schedules,
+        total_prompt_tokens=total_prompt,
+        total_completion_tokens=total_completion,
+    )
+
+    # Add new messages (only those after existing count)
+    new_messages = session.messages[existing_message_count:]
+    if new_messages:
+        messages_data = []
+        for msg in new_messages:
+            messages_data.append(
+                {
+                    "role": msg.role,
+                    "content": msg.content,
+                    "name": msg.name,
+                    "tool_call_id": msg.tool_call_id,
+                    "refusal": msg.refusal,
+                    "tool_calls": msg.tool_calls,
+                    "function_call": msg.function_call,
+                }
+            )
+        logger.info(
+            f"Saving {len(new_messages)} new messages to DB for session {session.session_id}: "
+            f"roles={[m['role'] for m in messages_data]}, "
+            f"start_sequence={existing_message_count}"
+        )
+        await chat_db.add_chat_messages_batch(
+            session_id=session.session_id,
+            messages=messages_data,
+            start_sequence=existing_message_count,
+        )
+
+
+async def get_chat_session(
+    session_id: str,
+    user_id: str | None,
+) -> ChatSession | None:
+    """Get a chat session by ID.
+
+    Checks Redis cache first, falls back to database if not found.
+    Caches database results back to Redis.
+    """
+    # Try cache first
+    try:
+        session = await _get_session_from_cache(session_id)
+        if session:
+            # Verify user ownership
+            if session.user_id is not None and session.user_id != user_id:
+                logger.warning(
+                    f"Session {session_id} user id mismatch: {session.user_id} != {user_id}"
+                )
+                return None
+            return session
+    except RedisError:
+        logger.warning(f"Cache error for session {session_id}, trying database")
+    except Exception as e:
+        logger.warning(f"Unexpected cache error for session {session_id}: {e}")
+
+    # Fall back to database
+    logger.info(f"Session {session_id} not in cache, checking database")
+    session = await _get_session_from_db(session_id)
+
+    if session is None:
+        logger.warning(f"Session {session_id} not found in cache or database")
+        return None
+
+    # Verify user ownership
+    if session.user_id is not None and session.user_id != user_id:
+        logger.warning(
+            f"Session {session_id} user id mismatch: {session.user_id} != {user_id}"
+        )
+        return None
+
+    # Cache the session from DB
+    try:
+        await _cache_session(session)
+        logger.info(f"Cached session {session_id} from database")
+    except Exception as e:
+        logger.warning(f"Failed to cache session {session_id}: {e}")
+
+    return session
+
+
+async def upsert_chat_session(
+    session: ChatSession,
+) -> ChatSession:
+    """Update a chat session in both cache and database."""
+    # Get existing message count from DB for incremental saves
+    existing_message_count = await chat_db.get_chat_session_message_count(
+        session.session_id
+    )
+
+    # Save to database
+    try:
+        await _save_session_to_db(session, existing_message_count)
+    except Exception as e:
+        logger.error(f"Failed to save session {session.session_id} to database: {e}")
+        # Continue to cache even if DB fails
+
+    # Save to cache
+    try:
+        await _cache_session(session)
+    except Exception as e:
+        raise RedisError(
+            f"Failed to persist chat session {session.session_id} to Redis: {e}"
+        ) from e
+
+    return session
+
+
+async def create_chat_session(user_id: str | None) -> ChatSession:
+    """Create a new chat session and persist it."""
+    session = ChatSession.new(user_id)
+
+    # Create in database first
+    try:
+        await chat_db.create_chat_session(
+            session_id=session.session_id,
+            user_id=user_id,
+        )
+    except Exception as e:
+        logger.error(f"Failed to create session in database: {e}")
+        # Continue even if DB fails - cache will still work
+
+    # Cache the session
+    try:
+        await _cache_session(session)
+    except Exception as e:
+        logger.warning(f"Failed to cache new session: {e}")
+
+    return session
+
+
+async def get_user_sessions(
+    user_id: str,
+    limit: int = 50,
+    offset: int = 0,
+) -> list[ChatSession]:
+    """Get all chat sessions for a user from the database."""
+    prisma_sessions = await chat_db.get_user_chat_sessions(user_id, limit, offset)
+
+    sessions = []
+    for prisma_session in prisma_sessions:
+        # Convert without messages for listing (lighter weight)
+        sessions.append(ChatSession.from_prisma(prisma_session, None))
+
+    return sessions
+
+
+async def delete_chat_session(session_id: str) -> bool:
+    """Delete a chat session from both cache and database."""
+    # Delete from cache
+    try:
+        redis_key = f"chat:session:{session_id}"
+        async_redis = await get_redis_async()
+        await async_redis.delete(redis_key)
+    except Exception as e:
+        logger.warning(f"Failed to delete session {session_id} from cache: {e}")
+
+    # Delete from database
+    return await chat_db.delete_chat_session(session_id)

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

@@ -0,0 +1,117 @@
+import pytest
+
+from .model import (
+    ChatMessage,
+    ChatSession,
+    Usage,
+    get_chat_session,
+    upsert_chat_session,
+)
+
+messages = [
+    ChatMessage(content="Hello, how are you?", role="user"),
+    ChatMessage(
+        content="I'm fine, thank you!",
+        role="assistant",
+        tool_calls=[
+            {
+                "id": "t123",
+                "type": "function",
+                "function": {
+                    "name": "get_weather",
+                    "arguments": '{"city": "New York"}',
+                },
+            }
+        ],
+    ),
+    ChatMessage(
+        content="I'm using the tool to get the weather",
+        role="tool",
+        tool_call_id="t123",
+    ),
+]
+
+
+@pytest.mark.asyncio(loop_scope="session")
+async def test_chatsession_serialization_deserialization():
+    s = ChatSession.new(user_id="abc123")
+    s.messages = messages
+    s.usage = [Usage(prompt_tokens=100, completion_tokens=200, total_tokens=300)]
+    serialized = s.model_dump_json()
+    s2 = ChatSession.model_validate_json(serialized)
+    assert s2.model_dump() == s.model_dump()
+
+
+@pytest.mark.asyncio(loop_scope="session")
+async def test_chatsession_redis_storage():
+
+    s = ChatSession.new(user_id=None)
+    s.messages = messages
+
+    s = await upsert_chat_session(s)
+
+    s2 = await get_chat_session(
+        session_id=s.session_id,
+        user_id=s.user_id,
+    )
+
+    assert s2 == s
+
+
+@pytest.mark.asyncio(loop_scope="session")
+async def test_chatsession_redis_storage_user_id_mismatch():
+
+    s = ChatSession.new(user_id="abc123")
+    s.messages = messages
+    s = await upsert_chat_session(s)
+
+    s2 = await get_chat_session(s.session_id, None)
+
+    assert s2 is None
+
+
+@pytest.mark.asyncio(loop_scope="session")
+async def test_chatsession_db_storage():
+    """Test that messages are correctly saved to and loaded from DB (not cache)."""
+    from backend.data.redis_client import get_redis_async
+
+    # Create session with messages including assistant message
+    s = ChatSession.new(user_id=None)
+    s.messages = messages  # Contains user, assistant, and tool messages
+    assert s.session_id is not None, "Session id is not set"
+    # Upsert to save to both cache and DB
+    s = await upsert_chat_session(s)
+
+    # Clear the Redis cache to force DB load
+    redis_key = f"chat:session:{s.session_id}"
+    async_redis = await get_redis_async()
+    await async_redis.delete(redis_key)
+
+    # Load from DB (cache was cleared)
+    s2 = await get_chat_session(
+        session_id=s.session_id,
+        user_id=s.user_id,
+    )
+
+    assert s2 is not None, "Session not found after loading from DB"
+    assert len(s2.messages) == len(
+        s.messages
+    ), f"Message count mismatch: expected {len(s.messages)}, got {len(s2.messages)}"
+
+    # Verify all roles are present
+    roles = [m.role for m in s2.messages]
+    assert "user" in roles, f"User message missing. Roles found: {roles}"
+    assert "assistant" in roles, f"Assistant message missing. Roles found: {roles}"
+    assert "tool" in roles, f"Tool message missing. Roles found: {roles}"
+
+    # Verify message content
+    for orig, loaded in zip(s.messages, s2.messages):
+        assert orig.role == loaded.role, f"Role mismatch: {orig.role} != {loaded.role}"
+        assert (
+            orig.content == loaded.content
+        ), f"Content mismatch for {orig.role}: {orig.content} != {loaded.content}"
+        if orig.tool_calls:
+            assert (
+                loaded.tool_calls is not None
+            ), f"Tool calls missing for {orig.role} message"
+            assert len(orig.tool_calls) == len(loaded.tool_calls)

autogpt_platform/backend/backend/api/features/chat/prompts/chat_system.md

@@ -0,0 +1,192 @@
+You are Otto, an AI Co-Pilot and Forward Deployed Engineer for AutoGPT, an AI Business Automation tool. Your mission is to help users quickly find, create, and set up AutoGPT agents to solve their business problems.
+
+Here are the functions available to you:
+
+<functions>
+**Understanding & Discovery:**
+1. **add_understanding** - Save information about the user's business context (use this as you learn about them)
+2. **find_agent** - Search the marketplace for pre-built agents that solve the user's problem
+3. **find_library_agent** - Search the user's personal library of saved agents
+4. **find_block** - Search for individual blocks (building components for agents)
+5. **search_platform_docs** - Search AutoGPT documentation for help
+
+**Agent Creation & Editing:**
+6. **create_agent** - Create a new custom agent from scratch based on user requirements
+7. **edit_agent** - Modify an existing agent (add/remove blocks, change configuration)
+
+**Execution & Output:**
+8. **run_agent** - Run or schedule an agent (automatically handles setup)
+9. **run_block** - Run a single block directly without creating an agent
+10. **agent_output** - Get the output/results from a running or completed agent execution
+</functions>
+
+## ALWAYS GET THE USER'S NAME
+
+**This is critical:** If you don't know the user's name, ask for it in your first response. Use a friendly, natural approach:
+- "Hi! I'm Otto. What's your name?"
+- "Hey there! Before we dive in, what should I call you?"
+
+Once you have their name, immediately save it with `add_understanding(user_name="...")` and use it throughout the conversation.
+
+## BUILDING USER UNDERSTANDING
+
+**If no User Business Context is provided below**, gather information naturally during conversation - don't interrogate them.
+
+**Key information to gather (in priority order):**
+1. Their name (ALWAYS first if unknown)
+2. Their job title and role
+3. Their business/company and industry
+4. Pain points and what they want to automate
+5. Tools they currently use
+
+**How to gather this information:**
+- Ask naturally as part of helping them (e.g., "What's your role?" or "What industry are you in?")
+- When they share information, immediately save it using `add_understanding`
+- Don't ask all questions at once - spread them across the conversation
+- Prioritize understanding their immediate problem first
+
+**Example:**
+```
+User: "I need help automating my social media"
+Otto: I can help with that! I'm Otto - what's your name?
+User: "I'm Sarah"
+Otto: [calls add_understanding with user_name="Sarah"]
+Nice to meet you, Sarah! What's your role - are you a social media manager or business owner?
+User: "I'm the marketing director at a fintech startup"
+Otto: [calls add_understanding with job_title="Marketing Director", industry="fintech", business_size="startup"]
+Great! Let me find social media automation agents for you.
+[calls find_agent with query="social media automation marketing"]
+```
+
+## WHEN TO USE WHICH TOOL
+
+**Finding existing agents:**
+- `find_agent` - Search the marketplace for pre-built agents others have created
+- `find_library_agent` - Search agents the user has already saved to their library
+
+**Creating/editing agents:**
+- `create_agent` - When user wants a custom agent that doesn't exist, or has specific requirements
+- `edit_agent` - When user wants to modify an existing agent (change inputs, add blocks, etc.)
+
+**Running agents:**
+- `run_agent` - To execute an agent (handles credentials and inputs automatically)
+- `agent_output` - To check the results of a running or completed agent execution
+
+**Direct execution:**
+- `run_block` - Run a single block directly without needing a full agent
+
+## HOW run_agent WORKS
+
+The `run_agent` tool automatically handles the entire setup flow:
+
+1. **First call** (no inputs) → Returns available inputs so user can decide what values to use
+2. **Credentials check** → If missing, UI automatically prompts user to add them (you don't need to mention this)
+3. **Execution** → Runs when you provide `inputs` OR set `use_defaults=true`
+
+Parameters:
+- `username_agent_slug` (required): Agent identifier like "creator/agent-name"
+- `inputs`: Object with input values for the agent
+- `use_defaults`: Set to `true` to run with default values (only after user confirms)
+- `schedule_name` + `cron`: For scheduled execution
+
+## HOW create_agent WORKS
+
+Use `create_agent` when the user wants to build a custom automation:
+- Describe what the agent should do
+- The tool will create the agent structure with appropriate blocks
+- Returns the agent ID for further editing or running
+
+## HOW agent_output WORKS
+
+Use `agent_output` to get results from agent executions:
+- Pass the execution_id from a run_agent response
+- Returns the current status and any outputs produced
+- Useful for checking if an agent has completed and what it produced
+
+## WORKFLOW
+
+1. **Get their name** - If unknown, ask for it first
+2. **Understand context** - Ask 1-2 questions about their problem while helping
+3. **Find or create** - Use find_agent for existing solutions, create_agent for custom needs
+4. **Set up and run** - Use run_agent to execute, agent_output to get results
+
+## YOUR APPROACH
+
+**Step 1: Greet and Identify**
+- If you don't know their name, ask for it
+- Be friendly and conversational
+
+**Step 2: Understand the Problem**
+- Ask maximum 1-2 targeted questions
+- Focus on: What business problem are they solving?
+- If they want to create/edit an agent, understand what it should do
+
+**Step 3: Find or Create**
+- For existing solutions: Use `find_agent` with relevant keywords
+- For custom needs: Use `create_agent` with their requirements
+- For modifications: Use `edit_agent` on an existing agent
+
+**Step 4: Execute**
+- Call `run_agent` without inputs first to see what's available
+- Ask user what values they want or if defaults are okay
+- Call `run_agent` again with inputs or `use_defaults=true`
+- Use `agent_output` to check results when needed
+
+## USING add_understanding
+
+Call `add_understanding` whenever you learn something about the user:
+
+**User info:** `user_name`, `job_title`
+**Business:** `business_name`, `industry`, `business_size` (1-10, 11-50, 51-200, 201-1000, 1000+), `user_role` (decision maker, implementer, end user)
+**Processes:** `key_workflows` (array), `daily_activities` (array)
+**Pain points:** `pain_points` (array), `bottlenecks` (array), `manual_tasks` (array), `automation_goals` (array)
+**Tools:** `current_software` (array), `existing_automation` (array)
+**Other:** `additional_notes`
+
+Example: `add_understanding(user_name="Sarah", job_title="Marketing Director", industry="fintech")`
+
+## KEY RULES
+
+**What You DON'T Do:**
+- Don't help with login (frontend handles this)
+- Don't mention or explain credentials to the user (frontend handles this automatically)
+- Don't run agents without first showing available inputs to the user
+- Don't use `use_defaults=true` without user explicitly confirming
+- Don't write responses longer than 3 sentences
+- Don't interrogate users with many questions - gather info naturally
+
+**What You DO:**
+- ALWAYS ask for user's name if you don't have it
+- Save user information with `add_understanding` as you learn it
+- Use their name when addressing them
+- Always call run_agent first without inputs to see what's available
+- Ask user what values they want OR if they want to use defaults
+- Keep all responses to maximum 3 sentences
+- Include the agent link in your response after successful execution
+
+**Error Handling:**
+- Authentication needed → "Please sign in via the interface"
+- Credentials missing → The UI handles this automatically. Focus on asking the user about input values instead.
+
+## RESPONSE STRUCTURE
+
+Before responding, wrap your analysis in <thinking> tags to systematically plan your approach:
+- Check if you know the user's name - if not, ask for it
+- Check if you have user context - if not, plan to gather some naturally
+- Extract the key business problem or request from the user's message
+- Determine what function call (if any) you need to make next
+- Plan your response to stay under the 3-sentence maximum
+
+Example interaction:
+```
+User: "Hi, I want to build an agent that monitors my competitors"
+Otto: <thinking>I don't know this user's name. I should ask for it while acknowledging their request.</thinking>
+Hi! I'm Otto and I'd love to help you build a competitor monitoring agent. What's your name?
+User: "I'm Mike"
+Otto: [calls add_understanding with user_name="Mike"]
+<thinking>Now I know Mike wants competitor monitoring. I should search for existing agents first.</thinking>
+Great to meet you, Mike! Let me search for competitor monitoring agents.
+[calls find_agent with query="competitor monitoring analysis"]
+```
+
+KEEP ANSWERS TO 3 SENTENCES

autogpt_platform/backend/backend/api/features/chat/prompts/onboarding_system.md

@@ -0,0 +1,155 @@
+You are Otto, an AI Co-Pilot helping new users get started with AutoGPT, an AI Business Automation platform. Your mission is to welcome them, learn about their needs, and help them run their first successful agent.
+
+Here are the functions available to you:
+
+<functions>
+**Understanding & Discovery:**
+1. **add_understanding** - Save information about the user's business context (use this as you learn about them)
+2. **find_agent** - Search the marketplace for pre-built agents that solve the user's problem
+3. **find_library_agent** - Search the user's personal library of saved agents
+4. **find_block** - Search for individual blocks (building components for agents)
+5. **search_platform_docs** - Search AutoGPT documentation for help
+
+**Agent Creation & Editing:**
+6. **create_agent** - Create a new custom agent from scratch based on user requirements
+7. **edit_agent** - Modify an existing agent (add/remove blocks, change configuration)
+
+**Execution & Output:**
+8. **run_agent** - Run or schedule an agent (automatically handles setup)
+9. **run_block** - Run a single block directly without creating an agent
+10. **agent_output** - Get the output/results from a running or completed agent execution
+</functions>
+
+## YOUR ONBOARDING MISSION
+
+You are guiding a new user through their first experience with AutoGPT. Your goal is to:
+1. Welcome them warmly and get their name
+2. Learn about them and their business
+3. Find or create an agent that solves a real problem for them
+4. Get that agent running successfully
+5. Celebrate their success and point them to next steps
+
+## PHASE 1: WELCOME & INTRODUCTION
+
+**Start every conversation by:**
+- Giving a warm, friendly greeting
+- Introducing yourself as Otto, their AI assistant
+- Asking for their name immediately
+
+**Example opening:**
+```
+Hi! I'm Otto, your AI assistant. Welcome to AutoGPT! I'm here to help you set up your first automation. What's your name?
+```
+
+Once you have their name, save it immediately with `add_understanding(user_name="...")` and use it throughout.
+
+## PHASE 2: DISCOVERY
+
+**After getting their name, learn about them:**
+- What's their role/job title?
+- What industry/business are they in?
+- What's one thing they'd love to automate?
+
+**Keep it conversational - don't interrogate. Example:**
+```
+Nice to meet you, Sarah! What do you do for work, and what's one task you wish you could automate?
+```
+
+Save everything you learn with `add_understanding`.
+
+## PHASE 3: FIND OR CREATE AN AGENT
+
+**Once you understand their need:**
+- Search for existing agents with `find_agent`
+- Present the best match and explain how it helps them
+- If nothing fits, offer to create a custom agent with `create_agent`
+
+**Be enthusiastic about the solution:**
+```
+I found a great agent for you! The "Social Media Scheduler" can automatically post to your accounts on a schedule. Want to try it?
+```
+
+## PHASE 4: SETUP & RUN
+
+**Guide them through running the agent:**
+1. Call `run_agent` without inputs first to see what's needed
+2. Explain each input in simple terms
+3. Ask what values they want to use
+4. Run the agent with their inputs or defaults
+
+**Don't mention credentials** - the UI handles that automatically.
+
+## PHASE 5: CELEBRATE & HANDOFF
+
+**After successful execution:**
+- Congratulate them on their first automation!
+- Tell them where to find this agent (their Library)
+- Mention they can explore more agents in the Marketplace
+- Offer to help with anything else
+
+**Example:**
+```
+You did it! Your first agent is running. You can find it anytime in your Library. Ready to explore more automations?
+```
+
+## KEY RULES
+
+**What You DON'T Do:**
+- Don't help with login (frontend handles this)
+- Don't mention credentials (UI handles automatically)
+- Don't run agents without showing inputs first
+- Don't use `use_defaults=true` without explicit confirmation
+- Don't write responses longer than 3 sentences
+- Don't overwhelm with too many questions at once
+
+**What You DO:**
+- ALWAYS get the user's name first
+- Be warm, encouraging, and celebratory
+- Save info with `add_understanding` as you learn it
+- Use their name when addressing them
+- Keep responses to maximum 3 sentences
+- Make them feel successful at each step
+
+## USING add_understanding
+
+Save information as you learn it:
+
+**User info:** `user_name`, `job_title`
+**Business:** `business_name`, `industry`, `business_size`, `user_role`
+**Pain points:** `pain_points`, `manual_tasks`, `automation_goals`
+**Tools:** `current_software`
+
+Example: `add_understanding(user_name="Sarah", job_title="Marketing Manager", automation_goals=["social media scheduling"])`
+
+## HOW run_agent WORKS
+
+1. **First call** (no inputs) → Shows available inputs
+2. **Credentials** → UI handles automatically (don't mention)
+3. **Execution** → Run with `inputs={...}` or `use_defaults=true`
+
+## RESPONSE STRUCTURE
+
+Before responding, plan your approach in <thinking> tags:
+- What phase am I in? (Welcome/Discovery/Find/Setup/Celebrate)
+- Do I know their name? If not, ask for it
+- What's the next step to move them forward?
+- Keep response under 3 sentences
+
+**Example flow:**
+```
+User: "Hi"
+Otto: <thinking>Phase 1 - I need to welcome them and get their name.</thinking>
+Hi! I'm Otto, welcome to AutoGPT! I'm here to help you set up your first automation - what's your name?
+
+User: "I'm Alex"
+Otto: [calls add_understanding with user_name="Alex"]
+<thinking>Got their name. Phase 2 - learn about them.</thinking>
+Great to meet you, Alex! What do you do for work, and what's one task you'd love to automate?
+
+User: "I run an e-commerce store and spend hours on customer support emails"
+Otto: [calls add_understanding with industry="e-commerce", pain_points=["customer support emails"]]
+<thinking>Phase 3 - search for agents.</thinking>
+[calls find_agent with query="customer support email automation"]
+```
+
+KEEP ANSWERS TO 3 SENTENCES - Be warm, helpful, and focused on their success!

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

@@ -0,0 +1,472 @@
+"""Chat API routes for chat session management and streaming via SSE."""
+
+import logging
+from collections.abc import AsyncGenerator
+from typing import Annotated
+
+from autogpt_libs import auth
+from fastapi import APIRouter, Depends, Query, Security
+from fastapi.responses import StreamingResponse
+from pydantic import BaseModel
+
+from backend.util.exceptions import NotFoundError
+
+from . import service as chat_service
+from .config import ChatConfig
+
+config = ChatConfig()
+
+
+logger = logging.getLogger(__name__)
+
+router = APIRouter(
+    tags=["chat"],
+)
+
+# ========== Request/Response Models ==========
+
+
+class StreamChatRequest(BaseModel):
+    """Request model for streaming chat with optional context."""
+
+    message: str
+    is_user_message: bool = True
+    context: dict[str, str] | None = None  # {url: str, content: str}
+
+
+class CreateSessionResponse(BaseModel):
+    """Response model containing information on a newly created chat session."""
+
+    id: str
+    created_at: str
+    user_id: str | None
+
+
+class SessionDetailResponse(BaseModel):
+    """Response model providing complete details for a chat session, including messages."""
+
+    id: str
+    created_at: str
+    updated_at: str
+    user_id: str | None
+    messages: list[dict]
+
+
+class SessionSummaryResponse(BaseModel):
+    """Response model for a session summary (without messages)."""
+
+    id: str
+    created_at: str
+    updated_at: str
+    title: str | None = None
+
+
+class ListSessionsResponse(BaseModel):
+    """Response model for listing chat sessions."""
+
+    sessions: list[SessionSummaryResponse]
+    total: int
+
+
+# ========== Routes ==========
+
+
+@router.get(
+    "/sessions",
+    dependencies=[Security(auth.requires_user)],
+)
+async def list_sessions(
+    user_id: Annotated[str, Security(auth.get_user_id)],
+    limit: int = Query(default=50, ge=1, le=100),
+    offset: int = Query(default=0, ge=0),
+) -> ListSessionsResponse:
+    """
+    List chat sessions for the authenticated user.
+
+    Returns a paginated list of chat sessions belonging to the current user,
+    ordered by most recently updated.
+
+    Args:
+        user_id: The authenticated user's ID.
+        limit: Maximum number of sessions to return (1-100).
+        offset: Number of sessions to skip for pagination.
+
+    Returns:
+        ListSessionsResponse: List of session summaries and total count.
+    """
+    sessions = await chat_service.get_user_sessions(user_id, limit, offset)
+
+    return ListSessionsResponse(
+        sessions=[
+            SessionSummaryResponse(
+                id=session.session_id,
+                created_at=session.started_at.isoformat(),
+                updated_at=session.updated_at.isoformat(),
+                title=None,  # TODO: Add title support
+            )
+            for session in sessions
+        ],
+        total=len(sessions),
+    )
+
+
+@router.post(
+    "/sessions",
+)
+async def create_session(
+    user_id: Annotated[str | None, Depends(auth.get_user_id)],
+) -> CreateSessionResponse:
+    """
+    Create a new chat session.
+
+    Initiates a new chat session for either an authenticated or anonymous user.
+
+    Args:
+        user_id: The optional authenticated user ID parsed from the JWT. If missing, creates an anonymous session.
+
+    Returns:
+        CreateSessionResponse: Details of the created session.
+
+    """
+    logger.info(
+        f"Creating session with user_id: "
+        f"...{user_id[-8:] if user_id and len(user_id) > 8 else '<redacted>'}"
+    )
+
+    session = await chat_service.create_chat_session(user_id)
+
+    return CreateSessionResponse(
+        id=session.session_id,
+        created_at=session.started_at.isoformat(),
+        user_id=session.user_id or None,
+    )
+
+
+@router.get(
+    "/sessions/{session_id}",
+)
+async def get_session(
+    session_id: str,
+    user_id: Annotated[str | None, Depends(auth.get_user_id)],
+) -> SessionDetailResponse:
+    """
+    Retrieve the details of a specific chat session.
+
+    Looks up a chat session by ID for the given user (if authenticated) and returns all session data including messages.
+
+    Args:
+        session_id: The unique identifier for the desired chat session.
+        user_id: The optional authenticated user ID, or None for anonymous access.
+
+    Returns:
+        SessionDetailResponse: Details for the requested session; raises NotFoundError if not found.
+
+    """
+    session = await chat_service.get_session(session_id, user_id)
+    if not session:
+        raise NotFoundError(f"Session {session_id} not found")
+
+    messages = [message.model_dump() for message in session.messages]
+    logger.info(
+        f"Returning session {session_id}: "
+        f"message_count={len(messages)}, "
+        f"roles={[m.get('role') for m in messages]}"
+    )
+
+    return SessionDetailResponse(
+        id=session.session_id,
+        created_at=session.started_at.isoformat(),
+        updated_at=session.updated_at.isoformat(),
+        user_id=session.user_id or None,
+        messages=messages,
+    )
+
+
+@router.post(
+    "/sessions/{session_id}/stream",
+)
+async def stream_chat_post(
+    session_id: str,
+    request: StreamChatRequest,
+    user_id: str | None = Depends(auth.get_user_id),
+):
+    """
+    Stream chat responses for a session (POST with context support).
+
+    Streams the AI/completion responses in real time over Server-Sent Events (SSE), including:
+      - Text fragments as they are generated
+      - Tool call UI elements (if invoked)
+      - Tool execution results
+
+    Args:
+        session_id: The chat session identifier to associate with the streamed messages.
+        request: Request body containing message, is_user_message, and optional context.
+        user_id: Optional authenticated user ID.
+    Returns:
+        StreamingResponse: SSE-formatted response chunks.
+
+    """
+    # Validate session exists before starting the stream
+    # This prevents errors after the response has already started
+    session = await chat_service.get_session(session_id, user_id)
+
+    if not session:
+        raise NotFoundError(f"Session {session_id} not found. ")
+    if session.user_id is None and user_id is not None:
+        session = await chat_service.assign_user_to_session(session_id, user_id)
+
+    async def event_generator() -> AsyncGenerator[str, None]:
+        async for chunk in chat_service.stream_chat_completion(
+            session_id,
+            request.message,
+            is_user_message=request.is_user_message,
+            user_id=user_id,
+            session=session,  # Pass pre-fetched session to avoid double-fetch
+            context=request.context,
+        ):
+            yield chunk.to_sse()
+
+    return StreamingResponse(
+        event_generator(),
+        media_type="text/event-stream",
+        headers={
+            "Cache-Control": "no-cache",
+            "Connection": "keep-alive",
+            "X-Accel-Buffering": "no",  # Disable nginx buffering
+        },
+    )
+
+
+@router.get(
+    "/sessions/{session_id}/stream",
+)
+async def stream_chat_get(
+    session_id: str,
+    message: Annotated[str, Query(min_length=1, max_length=10000)],
+    user_id: str | None = Depends(auth.get_user_id),
+    is_user_message: bool = Query(default=True),
+):
+    """
+    Stream chat responses for a session (GET - legacy endpoint).
+
+    Streams the AI/completion responses in real time over Server-Sent Events (SSE), including:
+      - Text fragments as they are generated
+      - Tool call UI elements (if invoked)
+      - Tool execution results
+
+    Args:
+        session_id: The chat session identifier to associate with the streamed messages.
+        message: The user's new message to process.
+        user_id: Optional authenticated user ID.
+        is_user_message: Whether the message is a user message.
+    Returns:
+        StreamingResponse: SSE-formatted response chunks.
+
+    """
+    # Validate session exists before starting the stream
+    # This prevents errors after the response has already started
+    session = await chat_service.get_session(session_id, user_id)
+
+    if not session:
+        raise NotFoundError(f"Session {session_id} not found. ")
+    if session.user_id is None and user_id is not None:
+        session = await chat_service.assign_user_to_session(session_id, user_id)
+
+    async def event_generator() -> AsyncGenerator[str, None]:
+        async for chunk in chat_service.stream_chat_completion(
+            session_id,
+            message,
+            is_user_message=is_user_message,
+            user_id=user_id,
+            session=session,  # Pass pre-fetched session to avoid double-fetch
+        ):
+            yield chunk.to_sse()
+
+    return StreamingResponse(
+        event_generator(),
+        media_type="text/event-stream",
+        headers={
+            "Cache-Control": "no-cache",
+            "Connection": "keep-alive",
+            "X-Accel-Buffering": "no",  # Disable nginx buffering
+        },
+    )
+
+
+@router.patch(
+    "/sessions/{session_id}/assign-user",
+    dependencies=[Security(auth.requires_user)],
+    status_code=200,
+)
+async def session_assign_user(
+    session_id: str,
+    user_id: Annotated[str, Security(auth.get_user_id)],
+) -> dict:
+    """
+    Assign an authenticated user to a chat session.
+
+    Used (typically post-login) to claim an existing anonymous session as the current authenticated user.
+
+    Args:
+        session_id: The identifier for the (previously anonymous) session.
+        user_id: The authenticated user's ID to associate with the session.
+
+    Returns:
+        dict: Status of the assignment.
+
+    """
+    await chat_service.assign_user_to_session(session_id, user_id)
+    return {"status": "ok"}
+
+
+# ========== Onboarding Routes ==========
+# These routes use a specialized onboarding system prompt
+
+
+@router.post(
+    "/onboarding/sessions",
+)
+async def create_onboarding_session(
+    user_id: Annotated[str | None, Depends(auth.get_user_id)],
+) -> CreateSessionResponse:
+    """
+    Create a new onboarding chat session.
+
+    Initiates a new chat session specifically for user onboarding,
+    using a specialized prompt that guides users through their first
+    experience with AutoGPT.
+
+    Args:
+        user_id: The optional authenticated user ID parsed from the JWT.
+
+    Returns:
+        CreateSessionResponse: Details of the created onboarding session.
+    """
+    logger.info(
+        f"Creating onboarding session with user_id: "
+        f"...{user_id[-8:] if user_id and len(user_id) > 8 else '<redacted>'}"
+    )
+
+    session = await chat_service.create_chat_session(user_id)
+
+    return CreateSessionResponse(
+        id=session.session_id,
+        created_at=session.started_at.isoformat(),
+        user_id=session.user_id or None,
+    )
+
+
+@router.get(
+    "/onboarding/sessions/{session_id}",
+)
+async def get_onboarding_session(
+    session_id: str,
+    user_id: Annotated[str | None, Depends(auth.get_user_id)],
+) -> SessionDetailResponse:
+    """
+    Retrieve the details of an onboarding chat session.
+
+    Args:
+        session_id: The unique identifier for the onboarding session.
+        user_id: The optional authenticated user ID.
+
+    Returns:
+        SessionDetailResponse: Details for the requested session.
+    """
+    session = await chat_service.get_session(session_id, user_id)
+    if not session:
+        raise NotFoundError(f"Session {session_id} not found")
+
+    messages = [message.model_dump() for message in session.messages]
+    logger.info(
+        f"Returning onboarding session {session_id}: "
+        f"message_count={len(messages)}, "
+        f"roles={[m.get('role') for m in messages]}"
+    )
+
+    return SessionDetailResponse(
+        id=session.session_id,
+        created_at=session.started_at.isoformat(),
+        updated_at=session.updated_at.isoformat(),
+        user_id=session.user_id or None,
+        messages=messages,
+    )
+
+
+@router.post(
+    "/onboarding/sessions/{session_id}/stream",
+)
+async def stream_onboarding_chat(
+    session_id: str,
+    request: StreamChatRequest,
+    user_id: str | None = Depends(auth.get_user_id),
+):
+    """
+    Stream onboarding chat responses for a session.
+
+    Uses the specialized onboarding system prompt to guide new users
+    through their first experience with AutoGPT. Streams AI responses
+    in real time over Server-Sent Events (SSE).
+
+    Args:
+        session_id: The onboarding session identifier.
+        request: Request body containing message and optional context.
+        user_id: Optional authenticated user ID.
+
+    Returns:
+        StreamingResponse: SSE-formatted response chunks.
+    """
+    session = await chat_service.get_session(session_id, user_id)
+
+    if not session:
+        raise NotFoundError(f"Session {session_id} not found.")
+    if session.user_id is None and user_id is not None:
+        session = await chat_service.assign_user_to_session(session_id, user_id)
+
+    async def event_generator() -> AsyncGenerator[str, None]:
+        async for chunk in chat_service.stream_chat_completion(
+            session_id,
+            request.message,
+            is_user_message=request.is_user_message,
+            user_id=user_id,
+            session=session,
+            context=request.context,
+            prompt_type="onboarding",  # Use onboarding system prompt
+        ):
+            yield chunk.to_sse()
+
+    return StreamingResponse(
+        event_generator(),
+        media_type="text/event-stream",
+        headers={
+            "Cache-Control": "no-cache",
+            "Connection": "keep-alive",
+            "X-Accel-Buffering": "no",
+        },
+    )
+
+
+# ========== Health Check ==========
+
+
+@router.get("/health", status_code=200)
+async def health_check() -> dict:
+    """
+    Health check endpoint for the chat service.
+
+    Performs a full cycle test of session creation, assignment, and retrieval. Should always return healthy
+    if the service and data layer are operational.
+
+    Returns:
+        dict: A status dictionary indicating health, service name, and API version.
+
+    """
+    session = await chat_service.create_chat_session(None)
+    await chat_service.assign_user_to_session(session.session_id, "test_user")
+    await chat_service.get_session(session.session_id, "test_user")
+
+    return {
+        "status": "healthy",
+        "service": "chat",
+        "version": "0.1.0",
+    }

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

@@ -1,4 +1,3 @@
-import functools
 import logging
 from collections.abc import AsyncGenerator
 from datetime import UTC, datetime
@@ -8,15 +7,18 @@ import orjson
 from openai import AsyncOpenAI
 from openai.types.chat import ChatCompletionChunk, ChatCompletionToolParam
 
-import backend.server.v2.chat.config
-from backend.server.v2.chat.model import (
-    ChatMessage,
-    ChatSession,
-    Usage,
-    get_chat_session,
-    upsert_chat_session,
+from backend.data.understanding import (
+    format_understanding_for_prompt,
+    get_business_understanding,
 )
-from backend.server.v2.chat.response_model import (
+from backend.util.exceptions import NotFoundError
+
+from . import db as chat_db
+from .config import ChatConfig
+from .model import ChatMessage, ChatSession, Usage
+from .model import create_chat_session as model_create_chat_session
+from .model import get_chat_session, upsert_chat_session
+from .response_model import (
     StreamBaseResponse,
     StreamEnd,
     StreamError,
@@ -27,18 +29,108 @@ from backend.server.v2.chat.response_model import (
     StreamToolExecutionResult,
     StreamUsage,
 )
-from backend.server.v2.chat.tools import execute_tool, tools
-from backend.util.exceptions import NotFoundError
+from .tools import execute_tool, tools
 
 logger = logging.getLogger(__name__)
 
-config = backend.server.v2.chat.config.ChatConfig()
+config = ChatConfig()
+client = AsyncOpenAI(api_key=config.api_key, base_url=config.base_url)
 
 
-@functools.cache
-def get_openai_client() -> AsyncOpenAI:
-    """Lazily create the OpenAI client singleton."""
-    return AsyncOpenAI(api_key=config.api_key, base_url=config.base_url)
+async def _is_first_session(user_id: str) -> bool:
+    """Check if this is the user's first chat session.
+
+    Returns True if the user has 1 or fewer sessions (meaning this is their first).
+    """
+    try:
+        session_count = await chat_db.get_user_session_count(user_id)
+        return session_count <= 1
+    except Exception as e:
+        logger.warning(f"Failed to check session count for user {user_id}: {e}")
+        return False  # Default to non-onboarding if we can't check
+
+
+async def _build_system_prompt(
+    user_id: str | None, prompt_type: str = "default"
+) -> str:
+    """Build the full system prompt including business understanding if available.
+
+    Args:
+        user_id: The user ID for fetching business understanding
+        prompt_type: The type of prompt to load ("default" or "onboarding")
+                     If "default" and this is the user's first session, will use "onboarding" instead.
+
+    Returns:
+        The full system prompt with business understanding context if available
+    """
+    # Auto-detect: if using default prompt and this is user's first session, use onboarding
+    effective_prompt_type = prompt_type
+    if prompt_type == "default" and user_id:
+        if await _is_first_session(user_id):
+            logger.info("First session detected for user, using onboarding prompt")
+            effective_prompt_type = "onboarding"
+
+    # Start with the base system prompt for the specified type
+    base_prompt = config.get_system_prompt_for_type(effective_prompt_type)
+
+    # If user is authenticated, try to fetch their business understanding
+    if user_id:
+        try:
+            understanding = await get_business_understanding(user_id)
+            if understanding:
+                context = format_understanding_for_prompt(understanding)
+                if context:
+                    return (
+                        f"{base_prompt}\n\n---\n\n"
+                        f"{context}\n\n"
+                        "Use this context to provide more personalized recommendations "
+                        "and to better understand the user's business needs when "
+                        "suggesting agents and automations."
+                    )
+        except Exception as e:
+            logger.warning(f"Failed to fetch business understanding: {e}")
+
+    return base_prompt
+
+
+async def _generate_session_title(message: str) -> str | None:
+    """Generate a concise title for a chat session based on the first message.
+
+    Args:
+        message: The first user message in the session
+
+    Returns:
+        A short title (3-6 words) or None if generation fails
+    """
+    try:
+        response = await client.chat.completions.create(
+            model=config.title_model,
+            messages=[
+                {
+                    "role": "system",
+                    "content": (
+                        "Generate a very short title (3-6 words) for a chat conversation "
+                        "based on the user's first message. The title should capture the "
+                        "main topic or intent. Return ONLY the title, no quotes or punctuation."
+                    ),
+                },
+                {"role": "user", "content": message[:500]},  # Limit input length
+            ],
+            max_tokens=20,
+            temperature=0.7,
+        )
+        title = response.choices[0].message.content
+        if title:
+            # Clean up the title
+            title = title.strip().strip("\"'")
+            # Limit length
+            if len(title) > 50:
+                title = title[:47] + "..."
+            return title
+        return None
+    except Exception as e:
+        logger.warning(f"Failed to generate session title: {e}")
+        return None
 
 
 async def create_chat_session(
@@ -47,9 +139,7 @@ async def create_chat_session(
     """
     Create a new chat session and persist it to the database.
     """
-    session = ChatSession.new(user_id)
-    # Persist the session immediately so it can be used for streaming
-    return await upsert_chat_session(session)
+    return await model_create_chat_session(user_id)
 
 
 async def get_session(
@@ -62,6 +152,19 @@ async def get_session(
     return await get_chat_session(session_id, user_id)
 
 
+async def get_user_sessions(
+    user_id: str,
+    limit: int = 50,
+    offset: int = 0,
+) -> list[ChatSession]:
+    """
+    Get all chat sessions for a user.
+    """
+    from .model import get_user_sessions as model_get_user_sessions
+
+    return await model_get_user_sessions(user_id, limit, offset)
+
+
 async def assign_user_to_session(
     session_id: str,
     user_id: str,
@@ -83,6 +186,8 @@ async def stream_chat_completion(
     user_id: str | None = None,
     retry_count: int = 0,
     session: ChatSession | None = None,
+    context: dict[str, str] | None = None,  # {url: str, content: str}
+    prompt_type: str = "default",
 ) -> AsyncGenerator[StreamBaseResponse, None]:
     """Main entry point for streaming chat completions with database handling.
 
@@ -94,6 +199,7 @@ async def stream_chat_completion(
         user_message: User's input message
         user_id: User ID for authentication (None for anonymous)
         session: Optional pre-loaded session object (for recursive calls to avoid Redis refetch)
+        prompt_type: The type of prompt to use ("default" or "onboarding")
 
     Yields:
         StreamBaseResponse objects formatted as SSE
@@ -126,9 +232,18 @@ async def stream_chat_completion(
         )
 
     if message:
+        # Build message content with context if provided
+        message_content = message
+        if context and context.get("url") and context.get("content"):
+            context_text = f"Page URL: {context['url']}\n\nPage Content:\n{context['content']}\n\n---\n\nUser Message: {message}"
+            message_content = context_text
+            logger.info(
+                f"Including page context: URL={context['url']}, content_length={len(context['content'])}"
+            )
+
         session.messages.append(
             ChatMessage(
-                role="user" if is_user_message else "assistant", content=message
+                role="user" if is_user_message else "assistant", content=message_content
             )
         )
         logger.info(
@@ -146,6 +261,32 @@ async def stream_chat_completion(
     session = await upsert_chat_session(session)
     assert session, "Session not found"
 
+    # Generate title for new sessions on first user message (non-blocking)
+    # Check: is_user_message, no title yet, and this is the first user message
+    if is_user_message and message and not session.title:
+        user_messages = [m for m in session.messages if m.role == "user"]
+        if len(user_messages) == 1:
+            # First user message - generate title in background
+            import asyncio
+
+            async def _update_title():
+                try:
+                    title = await _generate_session_title(message)
+                    if title:
+                        session.title = title
+                        await upsert_chat_session(session)
+                        logger.info(
+                            f"Generated title for session {session_id}: {title}"
+                        )
+                except Exception as e:
+                    logger.warning(f"Failed to update session title: {e}")
+
+            # Fire and forget - don't block the chat response
+            asyncio.create_task(_update_title())
+
+    # Build system prompt with business understanding
+    system_prompt = await _build_system_prompt(user_id, prompt_type)
+
     assistant_response = ChatMessage(
         role="assistant",
         content="",
@@ -164,6 +305,7 @@ async def stream_chat_completion(
         async for chunk in _stream_chat_chunks(
             session=session,
             tools=tools,
+            system_prompt=system_prompt,
         ):
 
             if isinstance(chunk, StreamTextChunk):
@@ -284,6 +426,7 @@ async def stream_chat_completion(
             user_id=user_id,
             retry_count=retry_count + 1,
             session=session,
+            prompt_type=prompt_type,
         ):
             yield chunk
         return  # Exit after retry to avoid double-saving in finally block
@@ -329,6 +472,7 @@ async def stream_chat_completion(
             session_id=session.session_id,
             user_id=user_id,
             session=session,  # Pass session object to avoid Redis refetch
+            prompt_type=prompt_type,
         ):
             yield chunk
 
@@ -336,6 +480,7 @@ async def stream_chat_completion(
 async def _stream_chat_chunks(
     session: ChatSession,
     tools: list[ChatCompletionToolParam],
+    system_prompt: str | None = None,
 ) -> AsyncGenerator[StreamBaseResponse, None]:
     """
     Pure streaming function for OpenAI chat completions with tool calling.
@@ -343,9 +488,9 @@ async def _stream_chat_chunks(
     This function is database-agnostic and focuses only on streaming logic.
 
     Args:
-        messages: Conversation context as ChatCompletionMessageParam list
-        session_id: Session ID
-        user_id: User ID for tool execution
+        session: Chat session with conversation history
+        tools: Available tools for the model
+        system_prompt: System prompt to prepend to messages
 
     Yields:
         SSE formatted JSON response objects
@@ -355,15 +500,26 @@ async def _stream_chat_chunks(
 
     logger.info("Starting pure chat stream")
 
+    # Build messages with system prompt prepended
+    messages = session.to_openai_messages()
+    if system_prompt:
+        from openai.types.chat import ChatCompletionSystemMessageParam
+
+        system_message = ChatCompletionSystemMessageParam(
+            role="system",
+            content=system_prompt,
+        )
+        messages = [system_message] + messages
+
     # Loop to handle tool calls and continue conversation
     while True:
         try:
             logger.info("Creating OpenAI chat completion stream...")
 
             # Create the stream with proper types
-            stream = await get_openai_client().chat.completions.create(
+            stream = await client.chat.completions.create(
                 model=model,
-                messages=session.to_openai_messages(),
+                messages=messages,
                 tools=tools,
                 tool_choice="auto",
                 stream=True,
@@ -507,8 +663,12 @@ async def _yield_tool_call(
     """
     logger.info(f"Yielding tool call: {tool_calls[yield_idx]}")
 
-    # Parse tool call arguments - exceptions will propagate to caller
-    arguments = orjson.loads(tool_calls[yield_idx]["function"]["arguments"])
+    # Parse tool call arguments - handle empty arguments gracefully
+    raw_arguments = tool_calls[yield_idx]["function"]["arguments"]
+    if raw_arguments:
+        arguments = orjson.loads(raw_arguments)
+    else:
+        arguments = {}
 
     yield StreamToolCall(
         tool_id=tool_calls[yield_idx]["id"],

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

@@ -3,8 +3,8 @@ from os import getenv
 
 import pytest
 
-import backend.server.v2.chat.service as chat_service
-from backend.server.v2.chat.response_model import (
+from . import service as chat_service
+from .response_model import (
     StreamEnd,
     StreamError,
     StreamTextChunk,

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

@@ -2,23 +2,32 @@ from typing import TYPE_CHECKING, Any
 
 from openai.types.chat import ChatCompletionToolParam
 
-from backend.server.v2.chat.model import ChatSession
+from backend.api.features.chat.model import ChatSession
 
+from .add_understanding import AddUnderstandingTool
+from .agent_output import AgentOutputTool
 from .base import BaseTool
 from .find_agent import FindAgentTool
+from .find_library_agent import FindLibraryAgentTool
 from .run_agent import RunAgentTool
 
 if TYPE_CHECKING:
-    from backend.server.v2.chat.response_model import StreamToolExecutionResult
+    from backend.api.features.chat.response_model import StreamToolExecutionResult
 
 # Initialize tool instances
+add_understanding_tool = AddUnderstandingTool()
 find_agent_tool = FindAgentTool()
+find_library_agent_tool = FindLibraryAgentTool()
 run_agent_tool = RunAgentTool()
+agent_output_tool = AgentOutputTool()
 
 # Export tools as OpenAI format
 tools: list[ChatCompletionToolParam] = [
+    add_understanding_tool.as_openai_tool(),
     find_agent_tool.as_openai_tool(),
+    find_library_agent_tool.as_openai_tool(),
     run_agent_tool.as_openai_tool(),
+    agent_output_tool.as_openai_tool(),
 ]
 
 
@@ -31,8 +40,11 @@ async def execute_tool(
 ) -> "StreamToolExecutionResult":
 
     tool_map: dict[str, BaseTool] = {
+        "add_understanding": add_understanding_tool,
         "find_agent": find_agent_tool,
+        "find_library_agent": find_library_agent_tool,
         "run_agent": run_agent_tool,
+        "agent_output": agent_output_tool,
     }
     if tool_name not in tool_map:
         raise ValueError(f"Tool {tool_name} not found")

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

@@ -3,8 +3,11 @@ from datetime import UTC, datetime
 from os import getenv
 
 import pytest
+from prisma.types import ProfileCreateInput
 from pydantic import SecretStr
 
+from backend.api.features.chat.model import ChatSession
+from backend.api.features.store import db as store_db
 from backend.blocks.firecrawl.scrape import FirecrawlScrapeBlock
 from backend.blocks.io import AgentInputBlock, AgentOutputBlock
 from backend.blocks.llm import AITextGeneratorBlock
@@ -13,8 +16,6 @@ from backend.data.graph import Graph, Link, Node, create_graph
 from backend.data.model import APIKeyCredentials
 from backend.data.user import get_or_create_user
 from backend.integrations.credentials_store import IntegrationCredentialsStore
-from backend.server.v2.chat.model import ChatSession
-from backend.server.v2.store import db as store_db
 
 
 def make_session(user_id: str | None = None):
@@ -49,13 +50,13 @@ async def setup_test_data():
     # 1b. Create a profile with username for the user (required for store agent lookup)
     username = user.email.split("@")[0]
     await prisma.profile.create(
-        data={
-            "userId": user.id,
-            "username": username,
-            "name": f"Test User {username}",
-            "description": "Test user profile",
-            "links": [],  # Required field - empty array for test profiles
-        }
+        data=ProfileCreateInput(
+            userId=user.id,
+            username=username,
+            name=f"Test User {username}",
+            description="Test user profile",
+            links=[],  # Required field - empty array for test profiles
+        )
     )
 
     # 2. Create a test graph with agent input -> agent output
@@ -172,13 +173,13 @@ async def setup_llm_test_data():
     # 1b. Create a profile with username for the user (required for store agent lookup)
     username = user.email.split("@")[0]
     await prisma.profile.create(
-        data={
-            "userId": user.id,
-            "username": username,
-            "name": f"Test User {username}",
-            "description": "Test user profile for LLM tests",
-            "links": [],  # Required field - empty array for test profiles
-        }
+        data=ProfileCreateInput(
+            userId=user.id,
+            username=username,
+            name=f"Test User {username}",
+            description="Test user profile for LLM tests",
+            links=[],  # Required field - empty array for test profiles
+        )
     )
 
     # 2. Create test OpenAI credentials for the user
@@ -332,13 +333,13 @@ async def setup_firecrawl_test_data():
     # 1b. Create a profile with username for the user (required for store agent lookup)
     username = user.email.split("@")[0]
     await prisma.profile.create(
-        data={
-            "userId": user.id,
-            "username": username,
-            "name": f"Test User {username}",
-            "description": "Test user profile for Firecrawl tests",
-            "links": [],  # Required field - empty array for test profiles
-        }
+        data=ProfileCreateInput(
+            userId=user.id,
+            username=username,
+            name=f"Test User {username}",
+            description="Test user profile for Firecrawl tests",
+            links=[],  # Required field - empty array for test profiles
+        )
     )
 
     # NOTE: We deliberately do NOT create Firecrawl credentials for this user

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

@@ -0,0 +1,202 @@
+"""Tool for capturing user business understanding incrementally."""
+
+import logging
+from typing import Any
+
+from backend.api.features.chat.model import ChatSession
+from backend.data.understanding import (
+    BusinessUnderstandingInput,
+    upsert_business_understanding,
+)
+
+from .base import BaseTool
+from .models import ErrorResponse, ToolResponseBase, UnderstandingUpdatedResponse
+
+logger = logging.getLogger(__name__)
+
+
+class AddUnderstandingTool(BaseTool):
+    """Tool for capturing user's business understanding incrementally."""
+
+    @property
+    def name(self) -> str:
+        return "add_understanding"
+
+    @property
+    def description(self) -> str:
+        return """Capture and store information about the user's business context,
+workflows, pain points, and automation goals. Call this tool whenever the user
+shares information about their business. Each call incrementally adds to the
+existing understanding - you don't need to provide all fields at once.
+
+Use this to build a comprehensive profile that helps recommend better agents
+and automations for the user's specific needs."""
+
+    @property
+    def parameters(self) -> dict[str, Any]:
+        return {
+            "type": "object",
+            "properties": {
+                "user_name": {
+                    "type": "string",
+                    "description": "The user's name",
+                },
+                "job_title": {
+                    "type": "string",
+                    "description": "The user's job title (e.g., 'Marketing Manager', 'CEO', 'Software Engineer')",
+                },
+                "business_name": {
+                    "type": "string",
+                    "description": "Name of the user's business or organization",
+                },
+                "industry": {
+                    "type": "string",
+                    "description": "Industry or sector (e.g., 'e-commerce', 'healthcare', 'finance')",
+                },
+                "business_size": {
+                    "type": "string",
+                    "description": "Company size: '1-10', '11-50', '51-200', '201-1000', or '1000+'",
+                },
+                "user_role": {
+                    "type": "string",
+                    "description": "User's role in organization context (e.g., 'decision maker', 'implementer', 'end user')",
+                },
+                "key_workflows": {
+                    "type": "array",
+                    "items": {"type": "string"},
+                    "description": "Key business workflows (e.g., 'lead qualification', 'content publishing')",
+                },
+                "daily_activities": {
+                    "type": "array",
+                    "items": {"type": "string"},
+                    "description": "Regular daily activities the user performs",
+                },
+                "pain_points": {
+                    "type": "array",
+                    "items": {"type": "string"},
+                    "description": "Current pain points or challenges",
+                },
+                "bottlenecks": {
+                    "type": "array",
+                    "items": {"type": "string"},
+                    "description": "Process bottlenecks slowing things down",
+                },
+                "manual_tasks": {
+                    "type": "array",
+                    "items": {"type": "string"},
+                    "description": "Manual or repetitive tasks that could be automated",
+                },
+                "automation_goals": {
+                    "type": "array",
+                    "items": {"type": "string"},
+                    "description": "Desired automation outcomes or goals",
+                },
+                "current_software": {
+                    "type": "array",
+                    "items": {"type": "string"},
+                    "description": "Software and tools currently in use",
+                },
+                "existing_automation": {
+                    "type": "array",
+                    "items": {"type": "string"},
+                    "description": "Any existing automations or integrations",
+                },
+                "additional_notes": {
+                    "type": "string",
+                    "description": "Any other relevant context or notes",
+                },
+            },
+            "required": [],
+        }
+
+    @property
+    def requires_auth(self) -> bool:
+        """Requires authentication to store user-specific data."""
+        return True
+
+    async def _execute(
+        self,
+        user_id: str | None,
+        session: ChatSession,
+        **kwargs,
+    ) -> ToolResponseBase:
+        """
+        Capture and store business understanding incrementally.
+
+        Each call merges new data with existing understanding:
+        - String fields are overwritten if provided
+        - List fields are appended (with deduplication)
+        """
+        session_id = session.session_id
+
+        if not user_id:
+            return ErrorResponse(
+                message="Authentication required to save business understanding.",
+                session_id=session_id,
+            )
+
+        # Check if any data was provided
+        if not any(v is not None for v in kwargs.values()):
+            return ErrorResponse(
+                message="Please provide at least one field to update.",
+                session_id=session_id,
+            )
+
+        # Build input model
+        input_data = BusinessUnderstandingInput(
+            user_name=kwargs.get("user_name"),
+            job_title=kwargs.get("job_title"),
+            business_name=kwargs.get("business_name"),
+            industry=kwargs.get("industry"),
+            business_size=kwargs.get("business_size"),
+            user_role=kwargs.get("user_role"),
+            key_workflows=kwargs.get("key_workflows"),
+            daily_activities=kwargs.get("daily_activities"),
+            pain_points=kwargs.get("pain_points"),
+            bottlenecks=kwargs.get("bottlenecks"),
+            manual_tasks=kwargs.get("manual_tasks"),
+            automation_goals=kwargs.get("automation_goals"),
+            current_software=kwargs.get("current_software"),
+            existing_automation=kwargs.get("existing_automation"),
+            additional_notes=kwargs.get("additional_notes"),
+        )
+
+        # Track which fields were updated
+        updated_fields = [k for k, v in kwargs.items() if v is not None]
+
+        # Upsert with merge
+        understanding = await upsert_business_understanding(user_id, input_data)
+
+        # Build current understanding summary for the response
+        current_understanding = {
+            "user_name": understanding.user_name,
+            "job_title": understanding.job_title,
+            "business_name": understanding.business_name,
+            "industry": understanding.industry,
+            "business_size": understanding.business_size,
+            "user_role": understanding.user_role,
+            "key_workflows": understanding.key_workflows,
+            "daily_activities": understanding.daily_activities,
+            "pain_points": understanding.pain_points,
+            "bottlenecks": understanding.bottlenecks,
+            "manual_tasks": understanding.manual_tasks,
+            "automation_goals": understanding.automation_goals,
+            "current_software": understanding.current_software,
+            "existing_automation": understanding.existing_automation,
+            "additional_notes": understanding.additional_notes,
+        }
+
+        # Filter out empty values for cleaner response
+        current_understanding = {
+            k: v
+            for k, v in current_understanding.items()
+            if v is not None and v != [] and v != ""
+        }
+
+        return UnderstandingUpdatedResponse(
+            message=f"Updated understanding with: {', '.join(updated_fields)}. "
+            "I now have a better picture of your business context.",
+            session_id=session_id,
+            updated_fields=updated_fields,
+            current_understanding=current_understanding,
+        )

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

@@ -0,0 +1,455 @@
+"""Tool for retrieving agent execution outputs from user's library."""
+
+import logging
+import re
+from datetime import datetime, timedelta, timezone
+from typing import Any
+
+from pydantic import BaseModel, field_validator
+
+from backend.api.features.chat.model import ChatSession
+from backend.api.features.library import db as library_db
+from backend.api.features.library.model import LibraryAgent
+from backend.data import execution as execution_db
+from backend.data.execution import ExecutionStatus, GraphExecution, GraphExecutionMeta
+
+from .base import BaseTool
+from .models import (
+    AgentOutputResponse,
+    ErrorResponse,
+    ExecutionOutputInfo,
+    NoResultsResponse,
+    ToolResponseBase,
+)
+from .utils import fetch_graph_from_store_slug
+
+logger = logging.getLogger(__name__)
+
+
+class AgentOutputInput(BaseModel):
+    """Input parameters for the agent_output tool."""
+
+    agent_name: str = ""
+    library_agent_id: str = ""
+    store_slug: str = ""
+    execution_id: str = ""
+    run_time: str = "latest"
+
+    @field_validator(
+        "agent_name",
+        "library_agent_id",
+        "store_slug",
+        "execution_id",
+        "run_time",
+        mode="before",
+    )
+    @classmethod
+    def strip_strings(cls, v: Any) -> Any:
+        """Strip whitespace from string fields."""
+        return v.strip() if isinstance(v, str) else v
+
+
+def parse_time_expression(
+    time_expr: str | None,
+) -> tuple[datetime | None, datetime | None]:
+    """
+    Parse time expression into datetime range (start, end).
+
+    Supports:
+    - "latest" or None -> returns (None, None) to get most recent
+    - "yesterday" -> 24h window for yesterday
+    - "today" -> Today from midnight
+    - "last week" / "last 7 days" -> 7 day window
+    - "last month" / "last 30 days" -> 30 day window
+    - ISO date "YYYY-MM-DD" -> 24h window for that date
+    """
+    if not time_expr or time_expr.lower() == "latest":
+        return None, None
+
+    now = datetime.now(timezone.utc)
+    expr = time_expr.lower().strip()
+
+    # Relative expressions
+    if expr == "yesterday":
+        end = now.replace(hour=0, minute=0, second=0, microsecond=0)
+        start = end - timedelta(days=1)
+        return start, end
+
+    if expr in ("last week", "last 7 days"):
+        return now - timedelta(days=7), now
+
+    if expr in ("last month", "last 30 days"):
+        return now - timedelta(days=30), now
+
+    if expr == "today":
+        start = now.replace(hour=0, minute=0, second=0, microsecond=0)
+        return start, now
+
+    # Try ISO date format (YYYY-MM-DD)
+    date_match = re.match(r"^(\d{4})-(\d{2})-(\d{2})$", expr)
+    if date_match:
+        year, month, day = map(int, date_match.groups())
+        start = datetime(year, month, day, 0, 0, 0, tzinfo=timezone.utc)
+        end = start + timedelta(days=1)
+        return start, end
+
+    # Try ISO datetime
+    try:
+        parsed = datetime.fromisoformat(expr.replace("Z", "+00:00"))
+        if parsed.tzinfo is None:
+            parsed = parsed.replace(tzinfo=timezone.utc)
+        # Return +/- 1 hour window around the specified time
+        return parsed - timedelta(hours=1), parsed + timedelta(hours=1)
+    except ValueError:
+        pass
+
+    # Fallback: treat as "latest"
+    return None, None
+
+
+class AgentOutputTool(BaseTool):
+    """Tool for retrieving execution outputs from user's library agents."""
+
+    @property
+    def name(self) -> str:
+        return "agent_output"
+
+    @property
+    def description(self) -> str:
+        return """Retrieve execution outputs from agents in the user's library.
+
+        Identify the agent using one of:
+        - agent_name: Fuzzy search in user's library
+        - library_agent_id: Exact library agent ID
+        - store_slug: Marketplace format 'username/agent-name'
+
+        Select which run to retrieve using:
+        - execution_id: Specific execution ID
+        - run_time: 'latest' (default), 'yesterday', 'last week', or ISO date 'YYYY-MM-DD'
+        """
+
+    @property
+    def parameters(self) -> dict[str, Any]:
+        return {
+            "type": "object",
+            "properties": {
+                "agent_name": {
+                    "type": "string",
+                    "description": "Agent name to search for in user's library (fuzzy match)",
+                },
+                "library_agent_id": {
+                    "type": "string",
+                    "description": "Exact library agent ID",
+                },
+                "store_slug": {
+                    "type": "string",
+                    "description": "Marketplace identifier: 'username/agent-slug'",
+                },
+                "execution_id": {
+                    "type": "string",
+                    "description": "Specific execution ID to retrieve",
+                },
+                "run_time": {
+                    "type": "string",
+                    "description": (
+                        "Time filter: 'latest', 'yesterday', 'last week', or 'YYYY-MM-DD'"
+                    ),
+                },
+            },
+            "required": [],
+        }
+
+    @property
+    def requires_auth(self) -> bool:
+        return True
+
+    async def _resolve_agent(
+        self,
+        user_id: str,
+        agent_name: str | None,
+        library_agent_id: str | None,
+        store_slug: str | None,
+    ) -> tuple[LibraryAgent | None, str | None]:
+        """
+        Resolve agent from provided identifiers.
+        Returns (library_agent, error_message).
+        """
+        # Priority 1: Exact library agent ID
+        if library_agent_id:
+            try:
+                agent = await library_db.get_library_agent(library_agent_id, user_id)
+                return agent, None
+            except Exception as e:
+                logger.warning(f"Failed to get library agent by ID: {e}")
+                return None, f"Library agent '{library_agent_id}' not found"
+
+        # Priority 2: Store slug (username/agent-name)
+        if store_slug and "/" in store_slug:
+            username, agent_slug = store_slug.split("/", 1)
+            graph, _ = await fetch_graph_from_store_slug(username, agent_slug)
+            if not graph:
+                return None, f"Agent '{store_slug}' not found in marketplace"
+
+            # Find in user's library by graph_id
+            agent = await library_db.get_library_agent_by_graph_id(user_id, graph.id)
+            if not agent:
+                return (
+                    None,
+                    f"Agent '{store_slug}' is not in your library. "
+                    "Add it first to see outputs.",
+                )
+            return agent, None
+
+        # Priority 3: Fuzzy name search in library
+        if agent_name:
+            try:
+                response = await library_db.list_library_agents(
+                    user_id=user_id,
+                    search_term=agent_name,
+                    page_size=5,
+                )
+                if not response.agents:
+                    return (
+                        None,
+                        f"No agents matching '{agent_name}' found in your library",
+                    )
+
+                # Return best match (first result from search)
+                return response.agents[0], None
+            except Exception as e:
+                logger.error(f"Error searching library agents: {e}")
+                return None, f"Error searching for agent: {e}"
+
+        return (
+            None,
+            "Please specify an agent name, library_agent_id, or store_slug",
+        )
+
+    async def _get_execution(
+        self,
+        user_id: str,
+        graph_id: str,
+        execution_id: str | None,
+        time_start: datetime | None,
+        time_end: datetime | None,
+    ) -> tuple[GraphExecution | None, list[GraphExecutionMeta], str | None]:
+        """
+        Fetch execution(s) based on filters.
+        Returns (single_execution, available_executions_meta, error_message).
+        """
+        # If specific execution_id provided, fetch it directly
+        if execution_id:
+            execution = await execution_db.get_graph_execution(
+                user_id=user_id,
+                execution_id=execution_id,
+                include_node_executions=False,
+            )
+            if not execution:
+                return None, [], f"Execution '{execution_id}' not found"
+            return execution, [], None
+
+        # Get completed executions with time filters
+        executions = await execution_db.get_graph_executions(
+            graph_id=graph_id,
+            user_id=user_id,
+            statuses=[ExecutionStatus.COMPLETED],
+            created_time_gte=time_start,
+            created_time_lte=time_end,
+            limit=10,
+        )
+
+        if not executions:
+            return None, [], None  # No error, just no executions
+
+        # If only one execution, fetch full details
+        if len(executions) == 1:
+            full_execution = await execution_db.get_graph_execution(
+                user_id=user_id,
+                execution_id=executions[0].id,
+                include_node_executions=False,
+            )
+            return full_execution, [], None
+
+        # Multiple executions - return latest with full details, plus list of available
+        full_execution = await execution_db.get_graph_execution(
+            user_id=user_id,
+            execution_id=executions[0].id,
+            include_node_executions=False,
+        )
+        return full_execution, executions, None
+
+    def _build_response(
+        self,
+        agent: LibraryAgent,
+        execution: GraphExecution | None,
+        available_executions: list[GraphExecutionMeta],
+        session_id: str | None,
+    ) -> AgentOutputResponse:
+        """Build the response based on execution data."""
+        library_agent_link = f"/library/agents/{agent.id}"
+
+        if not execution:
+            return AgentOutputResponse(
+                message=f"No completed executions found for agent '{agent.name}'",
+                session_id=session_id,
+                agent_name=agent.name,
+                agent_id=agent.graph_id,
+                library_agent_id=agent.id,
+                library_agent_link=library_agent_link,
+                total_executions=0,
+            )
+
+        execution_info = ExecutionOutputInfo(
+            execution_id=execution.id,
+            status=execution.status.value,
+            started_at=execution.started_at,
+            ended_at=execution.ended_at,
+            outputs=dict(execution.outputs),
+            inputs_summary=execution.inputs if execution.inputs else None,
+        )
+
+        available_list = None
+        if len(available_executions) > 1:
+            available_list = [
+                {
+                    "id": e.id,
+                    "status": e.status.value,
+                    "started_at": e.started_at.isoformat() if e.started_at else None,
+                }
+                for e in available_executions[:5]
+            ]
+
+        message = f"Found execution outputs for agent '{agent.name}'"
+        if len(available_executions) > 1:
+            message += (
+                f". Showing latest of {len(available_executions)} matching executions."
+            )
+
+        return AgentOutputResponse(
+            message=message,
+            session_id=session_id,
+            agent_name=agent.name,
+            agent_id=agent.graph_id,
+            library_agent_id=agent.id,
+            library_agent_link=library_agent_link,
+            execution=execution_info,
+            available_executions=available_list,
+            total_executions=len(available_executions) if available_executions else 1,
+        )
+
+    async def _execute(
+        self,
+        user_id: str | None,
+        session: ChatSession,
+        **kwargs,
+    ) -> ToolResponseBase:
+        """Execute the agent_output tool."""
+        session_id = session.session_id
+
+        # Parse and validate input
+        try:
+            input_data = AgentOutputInput(**kwargs)
+        except Exception as e:
+            logger.error(f"Invalid input: {e}")
+            return ErrorResponse(
+                message="Invalid input parameters",
+                error=str(e),
+                session_id=session_id,
+            )
+
+        # Ensure user_id is present (should be guaranteed by requires_auth)
+        if not user_id:
+            return ErrorResponse(
+                message="User authentication required",
+                session_id=session_id,
+            )
+
+        # Check if at least one identifier is provided
+        if not any(
+            [
+                input_data.agent_name,
+                input_data.library_agent_id,
+                input_data.store_slug,
+                input_data.execution_id,
+            ]
+        ):
+            return ErrorResponse(
+                message=(
+                    "Please specify at least one of: agent_name, "
+                    "library_agent_id, store_slug, or execution_id"
+                ),
+                session_id=session_id,
+            )
+
+        # If only execution_id provided, we need to find the agent differently
+        if (
+            input_data.execution_id
+            and not input_data.agent_name
+            and not input_data.library_agent_id
+            and not input_data.store_slug
+        ):
+            # Fetch execution directly to get graph_id
+            execution = await execution_db.get_graph_execution(
+                user_id=user_id,
+                execution_id=input_data.execution_id,
+                include_node_executions=False,
+            )
+            if not execution:
+                return ErrorResponse(
+                    message=f"Execution '{input_data.execution_id}' not found",
+                    session_id=session_id,
+                )
+
+            # Find library agent by graph_id
+            agent = await library_db.get_library_agent_by_graph_id(
+                user_id, execution.graph_id
+            )
+            if not agent:
+                return NoResultsResponse(
+                    message=(
+                        f"Execution found but agent not in your library. "
+                        f"Graph ID: {execution.graph_id}"
+                    ),
+                    session_id=session_id,
+                    suggestions=["Add the agent to your library to see more details"],
+                )
+
+            return self._build_response(agent, execution, [], session_id)
+
+        # Resolve agent from identifiers
+        agent, error = await self._resolve_agent(
+            user_id=user_id,
+            agent_name=input_data.agent_name or None,
+            library_agent_id=input_data.library_agent_id or None,
+            store_slug=input_data.store_slug or None,
+        )
+
+        if error or not agent:
+            return NoResultsResponse(
+                message=error or "Agent not found",
+                session_id=session_id,
+                suggestions=[
+                    "Check the agent name or ID",
+                    "Make sure the agent is in your library",
+                ],
+            )
+
+        # Parse time expression
+        time_start, time_end = parse_time_expression(input_data.run_time)
+
+        # Fetch execution(s)
+        execution, available_executions, exec_error = await self._get_execution(
+            user_id=user_id,
+            graph_id=agent.graph_id,
+            execution_id=input_data.execution_id or None,
+            time_start=time_start,
+            time_end=time_end,
+        )
+
+        if exec_error:
+            return ErrorResponse(
+                message=exec_error,
+                session_id=session_id,
+            )
+
+        return self._build_response(agent, execution, available_executions, session_id)

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

@@ -5,8 +5,8 @@ from typing import Any
 
 from openai.types.chat import ChatCompletionToolParam
 
-from backend.server.v2.chat.model import ChatSession
-from backend.server.v2.chat.response_model import StreamToolExecutionResult
+from backend.api.features.chat.model import ChatSession
+from backend.api.features.chat.response_model import StreamToolExecutionResult
 
 from .models import ErrorResponse, NeedLoginResponse, ToolResponseBase
 

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

@@ -3,17 +3,18 @@
 import logging
 from typing import Any
 
-from backend.server.v2.chat.model import ChatSession
-from backend.server.v2.chat.tools.base import BaseTool
-from backend.server.v2.chat.tools.models import (
+from backend.api.features.chat.model import ChatSession
+from backend.api.features.store import db as store_db
+from backend.util.exceptions import DatabaseError, NotFoundError
+
+from .base import BaseTool
+from .models import (
     AgentCarouselResponse,
     AgentInfo,
     ErrorResponse,
     NoResultsResponse,
     ToolResponseBase,
 )
-from backend.server.v2.store import db as store_db
-from backend.util.exceptions import DatabaseError, NotFoundError
 
 logger = logging.getLogger(__name__)
 

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

@@ -0,0 +1,157 @@
+"""Tool for searching agents in the user's library."""
+
+import logging
+from typing import Any
+
+from backend.api.features.chat.model import ChatSession
+from backend.api.features.library import db as library_db
+from backend.util.exceptions import DatabaseError
+
+from .base import BaseTool
+from .models import (
+    AgentCarouselResponse,
+    AgentInfo,
+    ErrorResponse,
+    NoResultsResponse,
+    ToolResponseBase,
+)
+
+logger = logging.getLogger(__name__)
+
+
+class FindLibraryAgentTool(BaseTool):
+    """Tool for searching agents in the user's library."""
+
+    @property
+    def name(self) -> str:
+        return "find_library_agent"
+
+    @property
+    def description(self) -> str:
+        return (
+            "Search for agents in the user's library. Use this to find agents "
+            "the user has already added to their library, including agents they "
+            "created or added from the marketplace."
+        )
+
+    @property
+    def parameters(self) -> dict[str, Any]:
+        return {
+            "type": "object",
+            "properties": {
+                "query": {
+                    "type": "string",
+                    "description": (
+                        "Search query to find agents by name or description. "
+                        "Use keywords for best results."
+                    ),
+                },
+            },
+            "required": ["query"],
+        }
+
+    @property
+    def requires_auth(self) -> bool:
+        return True
+
+    async def _execute(
+        self,
+        user_id: str | None,
+        session: ChatSession,
+        **kwargs,
+    ) -> ToolResponseBase:
+        """Search for agents in the user's library.
+
+        Args:
+            user_id: User ID (required)
+            session: Chat session
+            query: Search query
+
+        Returns:
+            AgentCarouselResponse: List of agents found in the library
+            NoResultsResponse: No agents found
+            ErrorResponse: Error message
+        """
+        query = kwargs.get("query", "").strip()
+        session_id = session.session_id
+
+        if not query:
+            return ErrorResponse(
+                message="Please provide a search query",
+                session_id=session_id,
+            )
+
+        if not user_id:
+            return ErrorResponse(
+                message="User authentication required to search library",
+                session_id=session_id,
+            )
+
+        agents = []
+        try:
+            logger.info(f"Searching user library for: {query}")
+            library_results = await library_db.list_library_agents(
+                user_id=user_id,
+                search_term=query,
+                page_size=10,
+            )
+
+            logger.info(
+                f"Find library agents tool found {len(library_results.agents)} agents"
+            )
+
+            for agent in library_results.agents:
+                agents.append(
+                    AgentInfo(
+                        id=agent.id,
+                        name=agent.name,
+                        description=agent.description or "",
+                        source="library",
+                        in_library=True,
+                        creator=agent.creator_name,
+                        status=agent.status.value,
+                        can_access_graph=agent.can_access_graph,
+                        has_external_trigger=agent.has_external_trigger,
+                        new_output=agent.new_output,
+                        graph_id=agent.graph_id,
+                    ),
+                )
+
+        except DatabaseError as e:
+            logger.error(f"Error searching library agents: {e}", exc_info=True)
+            return ErrorResponse(
+                message="Failed to search library. Please try again.",
+                error=str(e),
+                session_id=session_id,
+            )
+
+        if not agents:
+            return NoResultsResponse(
+                message=(
+                    f"No agents found matching '{query}' in your library. "
+                    "Try different keywords or use find_agent to search the marketplace."
+                ),
+                session_id=session_id,
+                suggestions=[
+                    "Try more general terms",
+                    "Use find_agent to search the marketplace",
+                    "Check your library at /library",
+                ],
+            )
+
+        title = (
+            f"Found {len(agents)} agent{'s' if len(agents) != 1 else ''} "
+            f"in your library for '{query}'"
+        )
+
+        return AgentCarouselResponse(
+            message=(
+                "Found agents in the user's library. You can provide a link to "
+                "view an agent at: /library/agents/{agent_id}. "
+                "Use agent_output to get execution results, or run_agent to execute."
+            ),
+            title=title,
+            agents=agents,
+            count=len(agents),
+            session_id=session_id,
+        )

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

@@ -1,5 +1,6 @@
 """Pydantic models for tool responses."""
 
+from datetime import datetime
 from enum import Enum
 from typing import Any
 
@@ -19,6 +20,15 @@ class ResponseType(str, Enum):
     ERROR = "error"
     NO_RESULTS = "no_results"
     SUCCESS = "success"
+    DOC_SEARCH_RESULTS = "doc_search_results"
+    AGENT_OUTPUT = "agent_output"
+    BLOCK_LIST = "block_list"
+    BLOCK_OUTPUT = "block_output"
+    UNDERSTANDING_UPDATED = "understanding_updated"
+    # Agent generation responses
+    AGENT_PREVIEW = "agent_preview"
+    AGENT_SAVED = "agent_saved"
+    CLARIFICATION_NEEDED = "clarification_needed"
 
 
 # Base response model
@@ -173,3 +183,128 @@ class ErrorResponse(ToolResponseBase):
     type: ResponseType = ResponseType.ERROR
     error: str | None = None
     details: dict[str, Any] | None = None
+
+
+# Documentation search models
+class DocSearchResult(BaseModel):
+    """A single documentation search result."""
+
+    title: str
+    path: str
+    section: str
+    snippet: str  # Short excerpt for UI display
+    content: str  # Full text content for LLM to read and understand
+    score: float
+    doc_url: str | None = None
+
+
+class DocSearchResultsResponse(ToolResponseBase):
+    """Response for search_docs tool."""
+
+    type: ResponseType = ResponseType.DOC_SEARCH_RESULTS
+    results: list[DocSearchResult]
+    count: int
+    query: str
+
+
+# Agent output models
+class ExecutionOutputInfo(BaseModel):
+    """Summary of a single execution's outputs."""
+
+    execution_id: str
+    status: str
+    started_at: datetime | None = None
+    ended_at: datetime | None = None
+    outputs: dict[str, list[Any]]
+    inputs_summary: dict[str, Any] | None = None
+
+
+class AgentOutputResponse(ToolResponseBase):
+    """Response for agent_output tool."""
+
+    type: ResponseType = ResponseType.AGENT_OUTPUT
+    agent_name: str
+    agent_id: str
+    library_agent_id: str | None = None
+    library_agent_link: str | None = None
+    execution: ExecutionOutputInfo | None = None
+    available_executions: list[dict[str, Any]] | None = None
+    total_executions: int = 0
+
+
+# Block models
+class BlockInfoSummary(BaseModel):
+    """Summary of a block for search results."""
+
+    id: str
+    name: str
+    description: str
+    categories: list[str]
+    input_schema: dict[str, Any]
+    output_schema: dict[str, Any]
+
+
+class BlockListResponse(ToolResponseBase):
+    """Response for find_block tool."""
+
+    type: ResponseType = ResponseType.BLOCK_LIST
+    blocks: list[BlockInfoSummary]
+    count: int
+    query: str
+
+
+class BlockOutputResponse(ToolResponseBase):
+    """Response for run_block tool."""
+
+    type: ResponseType = ResponseType.BLOCK_OUTPUT
+    block_id: str
+    block_name: str
+    outputs: dict[str, list[Any]]
+    success: bool = True
+
+
+# Business understanding models
+class UnderstandingUpdatedResponse(ToolResponseBase):
+    """Response for add_understanding tool."""
+
+    type: ResponseType = ResponseType.UNDERSTANDING_UPDATED
+    updated_fields: list[str] = Field(default_factory=list)
+    current_understanding: dict[str, Any] = Field(default_factory=dict)
+
+
+# Agent generation models
+class ClarifyingQuestion(BaseModel):
+    """A question that needs user clarification."""
+
+    question: str
+    keyword: str
+    example: str | None = None
+
+
+class AgentPreviewResponse(ToolResponseBase):
+    """Response for previewing a generated agent before saving."""
+
+    type: ResponseType = ResponseType.AGENT_PREVIEW
+    agent_json: dict[str, Any]
+    agent_name: str
+    description: str
+    node_count: int
+    link_count: int = 0
+
+
+class AgentSavedResponse(ToolResponseBase):
+    """Response when an agent is saved to the library."""
+
+    type: ResponseType = ResponseType.AGENT_SAVED
+    agent_id: str
+    agent_name: str
+    library_agent_id: str
+    library_agent_link: str
+    agent_page_link: str  # Link to the agent builder/editor page
+
+
+class ClarificationNeededResponse(ToolResponseBase):
+    """Response when the LLM needs more information from the user."""
+
+    type: ResponseType = ResponseType.CLARIFICATION_NEEDED
+    questions: list[ClarifyingQuestion] = Field(default_factory=list)

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

@@ -5,14 +5,22 @@ from typing import Any
 
 from pydantic import BaseModel, Field, field_validator
 
+from backend.api.features.chat.config import ChatConfig
+from backend.api.features.chat.model import ChatSession
+from backend.api.features.library import db as library_db
 from backend.data.graph import GraphModel
 from backend.data.model import CredentialsMetaInput
 from backend.data.user import get_user_by_id
 from backend.executor import utils as execution_utils
-from backend.server.v2.chat.config import ChatConfig
-from backend.server.v2.chat.model import ChatSession
-from backend.server.v2.chat.tools.base import BaseTool
-from backend.server.v2.chat.tools.models import (
+from backend.util.clients import get_scheduler_client
+from backend.util.exceptions import DatabaseError, NotFoundError
+from backend.util.timezone_utils import (
+    convert_utc_time_to_user_timezone,
+    get_user_timezone_or_utc,
+)
+
+from .base import BaseTool
+from .models import (
     AgentDetails,
     AgentDetailsResponse,
     ErrorResponse,
@@ -23,19 +31,13 @@ from backend.server.v2.chat.tools.models import (
     ToolResponseBase,
     UserReadiness,
 )
-from backend.server.v2.chat.tools.utils import (
+from .utils import (
     check_user_has_required_credentials,
     extract_credentials_from_schema,
     fetch_graph_from_store_slug,
     get_or_create_library_agent,
     match_user_credentials_to_graph,
 )
-from backend.util.clients import get_scheduler_client
-from backend.util.exceptions import DatabaseError, NotFoundError
-from backend.util.timezone_utils import (
-    convert_utc_time_to_user_timezone,
-    get_user_timezone_or_utc,
-)
 
 logger = logging.getLogger(__name__)
 config = ChatConfig()
@@ -56,6 +58,7 @@ class RunAgentInput(BaseModel):
     """Input parameters for the run_agent tool."""
 
     username_agent_slug: str = ""
+    library_agent_id: str = ""
     inputs: dict[str, Any] = Field(default_factory=dict)
     use_defaults: bool = False
     schedule_name: str = ""
@@ -63,7 +66,12 @@ class RunAgentInput(BaseModel):
     timezone: str = "UTC"
 
     @field_validator(
-        "username_agent_slug", "schedule_name", "cron", "timezone", mode="before"
+        "username_agent_slug",
+        "library_agent_id",
+        "schedule_name",
+        "cron",
+        "timezone",
+        mode="before",
     )
     @classmethod
     def strip_strings(cls, v: Any) -> Any:
@@ -89,7 +97,7 @@ class RunAgentTool(BaseTool):
 
     @property
     def description(self) -> str:
-        return """Run or schedule an agent from the marketplace.
+        return """Run or schedule an agent from the marketplace or user's library.
 
         The tool automatically handles the setup flow:
         - Returns missing inputs if required fields are not provided
@@ -97,6 +105,10 @@ class RunAgentTool(BaseTool):
         - Executes immediately if all requirements are met
         - Schedules execution if cron expression is provided
 
+        Identify the agent using either:
+        - username_agent_slug: Marketplace format 'username/agent-name'
+        - library_agent_id: ID of an agent in the user's library
+
         For scheduled execution, provide: schedule_name, cron, and optionally timezone."""
 
     @property
@@ -108,6 +120,10 @@ class RunAgentTool(BaseTool):
                     "type": "string",
                     "description": "Agent identifier in format 'username/agent-name'",
                 },
+                "library_agent_id": {
+                    "type": "string",
+                    "description": "Library agent ID from user's library",
+                },
                 "inputs": {
                     "type": "object",
                     "description": "Input values for the agent",
@@ -130,7 +146,7 @@ class RunAgentTool(BaseTool):
                     "description": "IANA timezone for schedule (default: UTC)",
                 },
             },
-            "required": ["username_agent_slug"],
+            "required": [],
         }
 
     @property
@@ -148,10 +164,16 @@ class RunAgentTool(BaseTool):
         params = RunAgentInput(**kwargs)
         session_id = session.session_id
 
-        # Validate agent slug format
-        if not params.username_agent_slug or "/" not in params.username_agent_slug:
+        # Validate at least one identifier is provided
+        has_slug = params.username_agent_slug and "/" in params.username_agent_slug
+        has_library_id = bool(params.library_agent_id)
+
+        if not has_slug and not has_library_id:
             return ErrorResponse(
-                message="Please provide an agent slug in format 'username/agent-name'",
+                message=(
+                    "Please provide either a username_agent_slug "
+                    "(format 'username/agent-name') or a library_agent_id"
+                ),
                 session_id=session_id,
             )
 
@@ -166,13 +188,41 @@ class RunAgentTool(BaseTool):
         is_schedule = bool(params.schedule_name or params.cron)
 
         try:
-            # Step 1: Fetch agent details (always happens first)
-            username, agent_name = params.username_agent_slug.split("/", 1)
-            graph, store_agent = await fetch_graph_from_store_slug(username, agent_name)
+            # Step 1: Fetch agent details
+            graph: GraphModel | None = None
+            library_agent = None
+
+            # Priority: library_agent_id if provided
+            if has_library_id:
+                library_agent = await library_db.get_library_agent(
+                    params.library_agent_id, user_id
+                )
+                if not library_agent:
+                    return ErrorResponse(
+                        message=f"Library agent '{params.library_agent_id}' not found",
+                        session_id=session_id,
+                    )
+                # Get the graph from the library agent
+                from backend.data.graph import get_graph
+
+                graph = await get_graph(
+                    library_agent.graph_id,
+                    library_agent.graph_version,
+                    user_id=user_id,
+                )
+            else:
+                # Fetch from marketplace slug
+                username, agent_name = params.username_agent_slug.split("/", 1)
+                graph, _ = await fetch_graph_from_store_slug(username, agent_name)
 
             if not graph:
+                identifier = (
+                    params.library_agent_id
+                    if has_library_id
+                    else params.username_agent_slug
+                )
                 return ErrorResponse(
-                    message=f"Agent '{params.username_agent_slug}' not found in marketplace",
+                    message=f"Agent '{identifier}' not found",
                     session_id=session_id,
                 )
 

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

@@ -3,13 +3,13 @@ import uuid
 import orjson
 import pytest
 
-from backend.server.v2.chat.tools._test_data import (
+from ._test_data import (
     make_session,
     setup_firecrawl_test_data,
     setup_llm_test_data,
     setup_test_data,
 )
-from backend.server.v2.chat.tools.run_agent import RunAgentTool
+from .run_agent import RunAgentTool
 
 # This is so the formatter doesn't remove the fixture imports
 setup_llm_test_data = setup_llm_test_data

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

@@ -3,13 +3,13 @@
 import logging
 from typing import Any
 
+from backend.api.features.library import db as library_db
+from backend.api.features.library import model as library_model
+from backend.api.features.store import db as store_db
 from backend.data import graph as graph_db
 from backend.data.graph import GraphModel
 from backend.data.model import CredentialsMetaInput
 from backend.integrations.creds_manager import IntegrationCredentialsManager
-from backend.server.v2.library import db as library_db
-from backend.server.v2.library import model as library_model
-from backend.server.v2.store import db as store_db
 from backend.util.exceptions import NotFoundError
 
 logger = logging.getLogger(__name__)

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

@@ -7,9 +7,10 @@ import pytest_mock
 from prisma.enums import ReviewStatus
 from pytest_snapshot.plugin import Snapshot
 
-from backend.server.rest_api import handle_internal_http_error
-from backend.server.v2.executions.review.model import PendingHumanReviewModel
-from backend.server.v2.executions.review.routes import router
+from backend.api.rest_api import handle_internal_http_error
+
+from .model import PendingHumanReviewModel
+from .routes import router
 
 # Using a fixed timestamp for reproducible tests
 FIXED_NOW = datetime.datetime(2023, 1, 1, 0, 0, 0, tzinfo=datetime.timezone.utc)
@@ -54,13 +55,13 @@ def sample_pending_review(test_user_id: str) -> PendingHumanReviewModel:
 
 
 def test_get_pending_reviews_empty(
-    mocker: pytest_mock.MockFixture,
+    mocker: pytest_mock.MockerFixture,
     snapshot: Snapshot,
     test_user_id: str,
 ) -> None:
     """Test getting pending reviews when none exist"""
     mock_get_reviews = mocker.patch(
-        "backend.server.v2.executions.review.routes.get_pending_reviews_for_user"
+        "backend.api.features.executions.review.routes.get_pending_reviews_for_user"
     )
     mock_get_reviews.return_value = []
 
@@ -72,14 +73,14 @@ def test_get_pending_reviews_empty(
 
 
 def test_get_pending_reviews_with_data(
-    mocker: pytest_mock.MockFixture,
+    mocker: pytest_mock.MockerFixture,
     sample_pending_review: PendingHumanReviewModel,
     snapshot: Snapshot,
     test_user_id: str,
 ) -> None:
     """Test getting pending reviews with data"""
     mock_get_reviews = mocker.patch(
-        "backend.server.v2.executions.review.routes.get_pending_reviews_for_user"
+        "backend.api.features.executions.review.routes.get_pending_reviews_for_user"
     )
     mock_get_reviews.return_value = [sample_pending_review]
 
@@ -94,14 +95,14 @@ def test_get_pending_reviews_with_data(
 
 
 def test_get_pending_reviews_for_execution_success(
-    mocker: pytest_mock.MockFixture,
+    mocker: pytest_mock.MockerFixture,
     sample_pending_review: PendingHumanReviewModel,
     snapshot: Snapshot,
     test_user_id: str,
 ) -> None:
     """Test getting pending reviews for specific execution"""
     mock_get_graph_execution = mocker.patch(
-        "backend.server.v2.executions.review.routes.get_graph_execution_meta"
+        "backend.api.features.executions.review.routes.get_graph_execution_meta"
     )
     mock_get_graph_execution.return_value = {
         "id": "test_graph_exec_456",
@@ -109,7 +110,7 @@ def test_get_pending_reviews_for_execution_success(
     }
 
     mock_get_reviews = mocker.patch(
-        "backend.server.v2.executions.review.routes.get_pending_reviews_for_execution"
+        "backend.api.features.executions.review.routes.get_pending_reviews_for_execution"
     )
     mock_get_reviews.return_value = [sample_pending_review]
 
@@ -121,24 +122,23 @@ def test_get_pending_reviews_for_execution_success(
     assert data[0]["graph_exec_id"] == "test_graph_exec_456"
 
 
-def test_get_pending_reviews_for_execution_access_denied(
-    mocker: pytest_mock.MockFixture,
-    test_user_id: str,
+def test_get_pending_reviews_for_execution_not_available(
+    mocker: pytest_mock.MockerFixture,
 ) -> None:
     """Test access denied when user doesn't own the execution"""
     mock_get_graph_execution = mocker.patch(
-        "backend.server.v2.executions.review.routes.get_graph_execution_meta"
+        "backend.api.features.executions.review.routes.get_graph_execution_meta"
     )
     mock_get_graph_execution.return_value = None
 
     response = client.get("/api/review/execution/test_graph_exec_456")
 
-    assert response.status_code == 403
-    assert "Access denied" in response.json()["detail"]
+    assert response.status_code == 404
+    assert "not found" in response.json()["detail"]
 
 
 def test_process_review_action_approve_success(
-    mocker: pytest_mock.MockFixture,
+    mocker: pytest_mock.MockerFixture,
     sample_pending_review: PendingHumanReviewModel,
     test_user_id: str,
 ) -> None:
@@ -146,12 +146,12 @@ def test_process_review_action_approve_success(
     # Mock the route functions
 
     mock_get_reviews_for_execution = mocker.patch(
-        "backend.server.v2.executions.review.routes.get_pending_reviews_for_execution"
+        "backend.api.features.executions.review.routes.get_pending_reviews_for_execution"
     )
     mock_get_reviews_for_execution.return_value = [sample_pending_review]
 
     mock_process_all_reviews = mocker.patch(
-        "backend.server.v2.executions.review.routes.process_all_reviews_for_execution"
+        "backend.api.features.executions.review.routes.process_all_reviews_for_execution"
     )
     # Create approved review for return
     approved_review = PendingHumanReviewModel(
@@ -174,11 +174,11 @@ def test_process_review_action_approve_success(
     mock_process_all_reviews.return_value = {"test_node_123": approved_review}
 
     mock_has_pending = mocker.patch(
-        "backend.server.v2.executions.review.routes.has_pending_reviews_for_graph_exec"
+        "backend.api.features.executions.review.routes.has_pending_reviews_for_graph_exec"
     )
     mock_has_pending.return_value = False
 
-    mocker.patch("backend.server.v2.executions.review.routes.add_graph_execution")
+    mocker.patch("backend.api.features.executions.review.routes.add_graph_execution")
 
     request_data = {
         "reviews": [
@@ -202,7 +202,7 @@ def test_process_review_action_approve_success(
 
 
 def test_process_review_action_reject_success(
-    mocker: pytest_mock.MockFixture,
+    mocker: pytest_mock.MockerFixture,
     sample_pending_review: PendingHumanReviewModel,
     test_user_id: str,
 ) -> None:
@@ -210,12 +210,12 @@ def test_process_review_action_reject_success(
     # Mock the route functions
 
     mock_get_reviews_for_execution = mocker.patch(
-        "backend.server.v2.executions.review.routes.get_pending_reviews_for_execution"
+        "backend.api.features.executions.review.routes.get_pending_reviews_for_execution"
     )
     mock_get_reviews_for_execution.return_value = [sample_pending_review]
 
     mock_process_all_reviews = mocker.patch(
-        "backend.server.v2.executions.review.routes.process_all_reviews_for_execution"
+        "backend.api.features.executions.review.routes.process_all_reviews_for_execution"
     )
     rejected_review = PendingHumanReviewModel(
         node_exec_id="test_node_123",
@@ -237,7 +237,7 @@ def test_process_review_action_reject_success(
     mock_process_all_reviews.return_value = {"test_node_123": rejected_review}
 
     mock_has_pending = mocker.patch(
-        "backend.server.v2.executions.review.routes.has_pending_reviews_for_graph_exec"
+        "backend.api.features.executions.review.routes.has_pending_reviews_for_graph_exec"
     )
     mock_has_pending.return_value = False
 
@@ -262,7 +262,7 @@ def test_process_review_action_reject_success(
 
 
 def test_process_review_action_mixed_success(
-    mocker: pytest_mock.MockFixture,
+    mocker: pytest_mock.MockerFixture,
     sample_pending_review: PendingHumanReviewModel,
     test_user_id: str,
 ) -> None:
@@ -289,12 +289,12 @@ def test_process_review_action_mixed_success(
     # Mock the route functions
 
     mock_get_reviews_for_execution = mocker.patch(
-        "backend.server.v2.executions.review.routes.get_pending_reviews_for_execution"
+        "backend.api.features.executions.review.routes.get_pending_reviews_for_execution"
     )
     mock_get_reviews_for_execution.return_value = [sample_pending_review, second_review]
 
     mock_process_all_reviews = mocker.patch(
-        "backend.server.v2.executions.review.routes.process_all_reviews_for_execution"
+        "backend.api.features.executions.review.routes.process_all_reviews_for_execution"
     )
     # Create approved version of first review
     approved_review = PendingHumanReviewModel(
@@ -338,7 +338,7 @@ def test_process_review_action_mixed_success(
     }
 
     mock_has_pending = mocker.patch(
-        "backend.server.v2.executions.review.routes.has_pending_reviews_for_graph_exec"
+        "backend.api.features.executions.review.routes.has_pending_reviews_for_graph_exec"
     )
     mock_has_pending.return_value = False
 
@@ -369,7 +369,7 @@ def test_process_review_action_mixed_success(
 
 
 def test_process_review_action_empty_request(
-    mocker: pytest_mock.MockFixture,
+    mocker: pytest_mock.MockerFixture,
     test_user_id: str,
 ) -> None:
     """Test error when no reviews provided"""
@@ -386,19 +386,19 @@ def test_process_review_action_empty_request(
 
 
 def test_process_review_action_review_not_found(
-    mocker: pytest_mock.MockFixture,
+    mocker: pytest_mock.MockerFixture,
     test_user_id: str,
 ) -> None:
     """Test error when review is not found"""
     # Mock the functions that extract graph execution ID from the request
     mock_get_reviews_for_execution = mocker.patch(
-        "backend.server.v2.executions.review.routes.get_pending_reviews_for_execution"
+        "backend.api.features.executions.review.routes.get_pending_reviews_for_execution"
     )
     mock_get_reviews_for_execution.return_value = []  # No reviews found
 
     # Mock process_all_reviews to simulate not finding reviews
     mock_process_all_reviews = mocker.patch(
-        "backend.server.v2.executions.review.routes.process_all_reviews_for_execution"
+        "backend.api.features.executions.review.routes.process_all_reviews_for_execution"
     )
     # This should raise a ValueError with "Reviews not found" message based on the data/human_review.py logic
     mock_process_all_reviews.side_effect = ValueError(
@@ -422,20 +422,20 @@ def test_process_review_action_review_not_found(
 
 
 def test_process_review_action_partial_failure(
-    mocker: pytest_mock.MockFixture,
+    mocker: pytest_mock.MockerFixture,
     sample_pending_review: PendingHumanReviewModel,
     test_user_id: str,
 ) -> None:
     """Test handling of partial failures in review processing"""
     # Mock the route functions
     mock_get_reviews_for_execution = mocker.patch(
-        "backend.server.v2.executions.review.routes.get_pending_reviews_for_execution"
+        "backend.api.features.executions.review.routes.get_pending_reviews_for_execution"
     )
     mock_get_reviews_for_execution.return_value = [sample_pending_review]
 
     # Mock partial failure in processing
     mock_process_all_reviews = mocker.patch(
-        "backend.server.v2.executions.review.routes.process_all_reviews_for_execution"
+        "backend.api.features.executions.review.routes.process_all_reviews_for_execution"
     )
     mock_process_all_reviews.side_effect = ValueError("Some reviews failed validation")
 
@@ -456,20 +456,20 @@ def test_process_review_action_partial_failure(
 
 
 def test_process_review_action_invalid_node_exec_id(
-    mocker: pytest_mock.MockFixture,
+    mocker: pytest_mock.MockerFixture,
     sample_pending_review: PendingHumanReviewModel,
     test_user_id: str,
 ) -> None:
     """Test failure when trying to process review with invalid node execution ID"""
     # Mock the route functions
     mock_get_reviews_for_execution = mocker.patch(
-        "backend.server.v2.executions.review.routes.get_pending_reviews_for_execution"
+        "backend.api.features.executions.review.routes.get_pending_reviews_for_execution"
     )
     mock_get_reviews_for_execution.return_value = [sample_pending_review]
 
     # Mock validation failure - this should return 400, not 500
     mock_process_all_reviews = mocker.patch(
-        "backend.server.v2.executions.review.routes.process_all_reviews_for_execution"
+        "backend.api.features.executions.review.routes.process_all_reviews_for_execution"
     )
     mock_process_all_reviews.side_effect = ValueError(
         "Invalid node execution ID format"

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

@@ -13,11 +13,8 @@ from backend.data.human_review import (
     process_all_reviews_for_execution,
 )
 from backend.executor.utils import add_graph_execution
-from backend.server.v2.executions.review.model import (
-    PendingHumanReviewModel,
-    ReviewRequest,
-    ReviewResponse,
-)
+
+from .model import PendingHumanReviewModel, ReviewRequest, ReviewResponse
 
 logger = logging.getLogger(__name__)
 
@@ -70,8 +67,7 @@ async def list_pending_reviews(
     response_model=List[PendingHumanReviewModel],
     responses={
         200: {"description": "List of pending reviews for the execution"},
-        400: {"description": "Invalid graph execution ID"},
-        403: {"description": "Access denied to graph execution"},
+        404: {"description": "Graph execution not found"},
         500: {"description": "Server error", "content": {"application/json": {}}},
     },
 )
@@ -94,7 +90,7 @@ async def list_pending_reviews_for_execution(
 
     Raises:
         HTTPException:
-            - 403: If user doesn't own the graph execution
+            - 404: If the graph execution doesn't exist or isn't owned by this user
             - 500: If authentication fails or database error occurs
 
     Note:
@@ -108,8 +104,8 @@ async def list_pending_reviews_for_execution(
     )
     if not graph_exec:
         raise HTTPException(
-            status_code=status.HTTP_403_FORBIDDEN,
-            detail="Access denied to graph execution",
+            status_code=status.HTTP_404_NOT_FOUND,
+            detail=f"Graph execution #{graph_exec_id} not found",
         )
 
     return await get_pending_reviews_for_execution(graph_exec_id, user_id)

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

@@ -17,6 +17,8 @@ from fastapi import (
 from pydantic import BaseModel, Field, SecretStr
 from starlette.status import HTTP_500_INTERNAL_SERVER_ERROR, HTTP_502_BAD_GATEWAY
 
+from backend.api.features.library.db import set_preset_webhook, update_preset
+from backend.api.features.library.model import LibraryAgentPreset
 from backend.data.graph import NodeModel, get_graph, set_node_webhook
 from backend.data.integrations import (
     WebhookEvent,
@@ -45,13 +47,6 @@ from backend.integrations.creds_manager import IntegrationCredentialsManager
 from backend.integrations.oauth import CREDENTIALS_BY_PROVIDER, HANDLERS_BY_NAME
 from backend.integrations.providers import ProviderName
 from backend.integrations.webhooks import get_webhook_manager
-from backend.server.integrations.models import (
-    ProviderConstants,
-    ProviderNamesResponse,
-    get_all_provider_names,
-)
-from backend.server.v2.library.db import set_preset_webhook, update_preset
-from backend.server.v2.library.model import LibraryAgentPreset
 from backend.util.exceptions import (
     GraphNotInLibraryError,
     MissingConfigError,
@@ -60,6 +55,8 @@ from backend.util.exceptions import (
 )
 from backend.util.settings import Settings
 
+from .models import ProviderConstants, ProviderNamesResponse, get_all_provider_names
+
 if TYPE_CHECKING:
     from backend.integrations.oauth import BaseOAuthHandler
 

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

@@ -4,16 +4,14 @@ from typing import Literal, Optional
 
 import fastapi
 import prisma.errors
-import prisma.fields
 import prisma.models
 import prisma.types
 
+import backend.api.features.store.exceptions as store_exceptions
+import backend.api.features.store.image_gen as store_image_gen
+import backend.api.features.store.media as store_media
 import backend.data.graph as graph_db
 import backend.data.integrations as integrations_db
-import backend.server.v2.library.model as library_model
-import backend.server.v2.store.exceptions as store_exceptions
-import backend.server.v2.store.image_gen as store_image_gen
-import backend.server.v2.store.media as store_media
 from backend.data.block import BlockInput
 from backend.data.db import transaction
 from backend.data.execution import get_graph_execution
@@ -28,6 +26,8 @@ from backend.util.json import SafeJson
 from backend.util.models import Pagination
 from backend.util.settings import Config
 
+from . import model as library_model
+
 logger = logging.getLogger(__name__)
 config = Config()
 integration_creds_manager = IntegrationCredentialsManager()
@@ -538,6 +538,7 @@ async def update_library_agent(
     library_agent_id: str,
     user_id: str,
     auto_update_version: Optional[bool] = None,
+    graph_version: Optional[int] = None,
     is_favorite: Optional[bool] = None,
     is_archived: Optional[bool] = None,
     is_deleted: Optional[Literal[False]] = None,
@@ -550,6 +551,7 @@ async def update_library_agent(
         library_agent_id: The ID of the LibraryAgent to update.
         user_id: The owner of this LibraryAgent.
         auto_update_version: Whether the agent should auto-update to active version.
+        graph_version: Specific graph version to update to.
         is_favorite: Whether this agent is marked as a favorite.
         is_archived: Whether this agent is archived.
         settings: User-specific settings for this library agent.
@@ -563,8 +565,8 @@ async def update_library_agent(
     """
     logger.debug(
         f"Updating library agent {library_agent_id} for user {user_id} with "
-        f"auto_update_version={auto_update_version}, is_favorite={is_favorite}, "
-        f"is_archived={is_archived}, settings={settings}"
+        f"auto_update_version={auto_update_version}, graph_version={graph_version}, "
+        f"is_favorite={is_favorite}, is_archived={is_archived}, settings={settings}"
     )
     update_fields: prisma.types.LibraryAgentUpdateManyMutationInput = {}
     if auto_update_version is not None:
@@ -581,10 +583,23 @@ async def update_library_agent(
         update_fields["isDeleted"] = is_deleted
     if settings is not None:
         update_fields["settings"] = SafeJson(settings.model_dump())
-    if not update_fields:
-        raise ValueError("No values were passed to update")
 
     try:
+        # If graph_version is provided, update to that specific version
+        if graph_version is not None:
+            # Get the current agent to find its graph_id
+            agent = await get_library_agent(id=library_agent_id, user_id=user_id)
+            # Update to the specified version using existing function
+            return await update_agent_version_in_library(
+                user_id=user_id,
+                agent_graph_id=agent.graph_id,
+                agent_graph_version=graph_version,
+            )
+
+        # Otherwise, just update the simple fields
+        if not update_fields:
+            raise ValueError("No values were passed to update")
+
         n_updated = await prisma.models.LibraryAgent.prisma().update_many(
             where={"id": library_agent_id, "userId": user_id},
             data=update_fields,

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

@@ -1,16 +1,15 @@
 from datetime import datetime
 
 import prisma.enums
-import prisma.errors
 import prisma.models
-import prisma.types
 import pytest
 
-import backend.server.v2.library.db as db
-import backend.server.v2.store.exceptions
+import backend.api.features.store.exceptions
 from backend.data.db import connect
 from backend.data.includes import library_agent_include
 
+from . import db
+
 
 @pytest.mark.asyncio
 async def test_get_library_agents(mocker):
@@ -88,7 +87,7 @@ async def test_add_agent_to_library(mocker):
     await connect()
 
     # Mock the transaction context
-    mock_transaction = mocker.patch("backend.server.v2.library.db.transaction")
+    mock_transaction = mocker.patch("backend.api.features.library.db.transaction")
     mock_transaction.return_value.__aenter__ = mocker.AsyncMock(return_value=None)
     mock_transaction.return_value.__aexit__ = mocker.AsyncMock(return_value=None)
     # Mock data
@@ -151,7 +150,7 @@ async def test_add_agent_to_library(mocker):
     )
 
     # Mock graph_db.get_graph function that's called to check for HITL blocks
-    mock_graph_db = mocker.patch("backend.server.v2.library.db.graph_db")
+    mock_graph_db = mocker.patch("backend.api.features.library.db.graph_db")
     mock_graph_model = mocker.Mock()
     mock_graph_model.nodes = (
         []
@@ -159,7 +158,9 @@ async def test_add_agent_to_library(mocker):
     mock_graph_db.get_graph = mocker.AsyncMock(return_value=mock_graph_model)
 
     # Mock the model conversion
-    mock_from_db = mocker.patch("backend.server.v2.library.model.LibraryAgent.from_db")
+    mock_from_db = mocker.patch(
+        "backend.api.features.library.model.LibraryAgent.from_db"
+    )
     mock_from_db.return_value = mocker.Mock()
 
     # Call function
@@ -217,7 +218,7 @@ async def test_add_agent_to_library_not_found(mocker):
     )
 
     # Call function and verify exception
-    with pytest.raises(backend.server.v2.store.exceptions.AgentNotFoundError):
+    with pytest.raises(backend.api.features.store.exceptions.AgentNotFoundError):
         await db.add_store_agent_to_library("version123", "test-user")
 
     # Verify mock called correctly

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

@@ -385,6 +385,9 @@ class LibraryAgentUpdateRequest(pydantic.BaseModel):
     auto_update_version: Optional[bool] = pydantic.Field(
         default=None, description="Auto-update the agent version"
     )
+    graph_version: Optional[int] = pydantic.Field(
+        default=None, description="Specific graph version to update to"
+    )
     is_favorite: Optional[bool] = pydantic.Field(
         default=None, description="Mark the agent as a favorite"
     )

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

@@ -3,7 +3,7 @@ import datetime
 import prisma.models
 import pytest
 
-import backend.server.v2.library.model as library_model
+from . import model as library_model
 
 
 @pytest.mark.asyncio

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

@@ -6,12 +6,13 @@ from fastapi import APIRouter, Body, HTTPException, Query, Security, status
 from fastapi.responses import Response
 from prisma.enums import OnboardingStep
 
-import backend.server.v2.library.db as library_db
-import backend.server.v2.library.model as library_model
-import backend.server.v2.store.exceptions as store_exceptions
+import backend.api.features.store.exceptions as store_exceptions
 from backend.data.onboarding import complete_onboarding_step
 from backend.util.exceptions import DatabaseError, NotFoundError
 
+from .. import db as library_db
+from .. import model as library_model
+
 logger = logging.getLogger(__name__)
 
 router = APIRouter(
@@ -284,6 +285,7 @@ async def update_library_agent(
             library_agent_id=library_agent_id,
             user_id=user_id,
             auto_update_version=payload.auto_update_version,
+            graph_version=payload.graph_version,
             is_favorite=payload.is_favorite,
             is_archived=payload.is_archived,
             settings=payload.settings,

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

@@ -4,8 +4,6 @@ from typing import Any, Optional
 import autogpt_libs.auth as autogpt_auth_lib
 from fastapi import APIRouter, Body, HTTPException, Query, Security, status
 
-import backend.server.v2.library.db as db
-import backend.server.v2.library.model as models
 from backend.data.execution import GraphExecutionMeta
 from backend.data.graph import get_graph
 from backend.data.integrations import get_webhook
@@ -17,6 +15,9 @@ from backend.integrations.webhooks import get_webhook_manager
 from backend.integrations.webhooks.utils import setup_webhook_for_block
 from backend.util.exceptions import NotFoundError
 
+from .. import db
+from .. import model as models
+
 logger = logging.getLogger(__name__)
 
 credentials_manager = IntegrationCredentialsManager()

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

@@ -7,10 +7,11 @@ import pytest
 import pytest_mock
 from pytest_snapshot.plugin import Snapshot
 
-import backend.server.v2.library.model as library_model
-from backend.server.v2.library.routes import router as library_router
 from backend.util.models import Pagination
 
+from . import model as library_model
+from .routes import router as library_router
+
 app = fastapi.FastAPI()
 app.include_router(library_router)
 
@@ -86,7 +87,7 @@ async def test_get_library_agents_success(
             total_items=2, total_pages=1, current_page=1, page_size=50
         ),
     )
-    mock_db_call = mocker.patch("backend.server.v2.library.db.list_library_agents")
+    mock_db_call = mocker.patch("backend.api.features.library.db.list_library_agents")
     mock_db_call.return_value = mocked_value
 
     response = client.get("/agents?search_term=test")
@@ -112,7 +113,7 @@ async def test_get_library_agents_success(
 
 
 def test_get_library_agents_error(mocker: pytest_mock.MockFixture, test_user_id: str):
-    mock_db_call = mocker.patch("backend.server.v2.library.db.list_library_agents")
+    mock_db_call = mocker.patch("backend.api.features.library.db.list_library_agents")
     mock_db_call.side_effect = Exception("Test error")
 
     response = client.get("/agents?search_term=test")
@@ -161,7 +162,7 @@ async def test_get_favorite_library_agents_success(
         ),
     )
     mock_db_call = mocker.patch(
-        "backend.server.v2.library.db.list_favorite_library_agents"
+        "backend.api.features.library.db.list_favorite_library_agents"
     )
     mock_db_call.return_value = mocked_value
 
@@ -184,7 +185,7 @@ def test_get_favorite_library_agents_error(
     mocker: pytest_mock.MockFixture, test_user_id: str
 ):
     mock_db_call = mocker.patch(
-        "backend.server.v2.library.db.list_favorite_library_agents"
+        "backend.api.features.library.db.list_favorite_library_agents"
     )
     mock_db_call.side_effect = Exception("Test error")
 
@@ -223,11 +224,11 @@ def test_add_agent_to_library_success(
     )
 
     mock_db_call = mocker.patch(
-        "backend.server.v2.library.db.add_store_agent_to_library"
+        "backend.api.features.library.db.add_store_agent_to_library"
     )
     mock_db_call.return_value = mock_library_agent
     mock_complete_onboarding = mocker.patch(
-        "backend.server.v2.library.routes.agents.complete_onboarding_step",
+        "backend.api.features.library.routes.agents.complete_onboarding_step",
         new_callable=AsyncMock,
     )
 
@@ -249,7 +250,7 @@ def test_add_agent_to_library_success(
 
 def test_add_agent_to_library_error(mocker: pytest_mock.MockFixture, test_user_id: str):
     mock_db_call = mocker.patch(
-        "backend.server.v2.library.db.add_store_agent_to_library"
+        "backend.api.features.library.db.add_store_agent_to_library"
     )
     mock_db_call.side_effect = Exception("Test error")
 

autogpt_platform/backend/backend/api/features/oauth.py

@@ -0,0 +1,833 @@
+"""
+OAuth 2.0 Provider Endpoints
+
+Implements OAuth 2.0 Authorization Code flow with PKCE support.
+
+Flow:
+1. User clicks "Login with AutoGPT" in 3rd party app
+2. App redirects user to /auth/authorize with client_id, redirect_uri, scope, state
+3. User sees consent screen (if not already logged in, redirects to login first)
+4. User approves → backend creates authorization code
+5. User redirected back to app with code
+6. App exchanges code for access/refresh tokens at /api/oauth/token
+7. App uses access token to call external API endpoints
+"""
+
+import io
+import logging
+import os
+import uuid
+from datetime import datetime
+from typing import Literal, Optional
+from urllib.parse import urlencode
+
+from autogpt_libs.auth import get_user_id
+from fastapi import APIRouter, Body, HTTPException, Security, UploadFile, status
+from gcloud.aio import storage as async_storage
+from PIL import Image
+from prisma.enums import APIKeyPermission
+from pydantic import BaseModel, Field
+
+from backend.data.auth.oauth import (
+    InvalidClientError,
+    InvalidGrantError,
+    OAuthApplicationInfo,
+    TokenIntrospectionResult,
+    consume_authorization_code,
+    create_access_token,
+    create_authorization_code,
+    create_refresh_token,
+    get_oauth_application,
+    get_oauth_application_by_id,
+    introspect_token,
+    list_user_oauth_applications,
+    refresh_tokens,
+    revoke_access_token,
+    revoke_refresh_token,
+    update_oauth_application,
+    validate_client_credentials,
+    validate_redirect_uri,
+    validate_scopes,
+)
+from backend.util.settings import Settings
+from backend.util.virus_scanner import scan_content_safe
+
+settings = Settings()
+logger = logging.getLogger(__name__)
+
+router = APIRouter()
+
+
+# ============================================================================
+# Request/Response Models
+# ============================================================================
+
+
+class TokenResponse(BaseModel):
+    """OAuth 2.0 token response"""
+
+    token_type: Literal["Bearer"] = "Bearer"
+    access_token: str
+    access_token_expires_at: datetime
+    refresh_token: str
+    refresh_token_expires_at: datetime
+    scopes: list[str]
+
+
+class ErrorResponse(BaseModel):
+    """OAuth 2.0 error response"""
+
+    error: str
+    error_description: Optional[str] = None
+
+
+class OAuthApplicationPublicInfo(BaseModel):
+    """Public information about an OAuth application (for consent screen)"""
+
+    name: str
+    description: Optional[str] = None
+    logo_url: Optional[str] = None
+    scopes: list[str]
+
+
+# ============================================================================
+# Application Info Endpoint
+# ============================================================================
+
+
+@router.get(
+    "/app/{client_id}",
+    responses={
+        404: {"description": "Application not found or disabled"},
+    },
+)
+async def get_oauth_app_info(
+    client_id: str, user_id: str = Security(get_user_id)
+) -> OAuthApplicationPublicInfo:
+    """
+    Get public information about an OAuth application.
+
+    This endpoint is used by the consent screen to display application details
+    to the user before they authorize access.
+
+    Returns:
+    - name: Application name
+    - description: Application description (if provided)
+    - scopes: List of scopes the application is allowed to request
+    """
+    app = await get_oauth_application(client_id)
+    if not app or not app.is_active:
+        raise HTTPException(
+            status_code=status.HTTP_404_NOT_FOUND,
+            detail="Application not found",
+        )
+
+    return OAuthApplicationPublicInfo(
+        name=app.name,
+        description=app.description,
+        logo_url=app.logo_url,
+        scopes=[s.value for s in app.scopes],
+    )
+
+
+# ============================================================================
+# Authorization Endpoint
+# ============================================================================
+
+
+class AuthorizeRequest(BaseModel):
+    """OAuth 2.0 authorization request"""
+
+    client_id: str = Field(description="Client identifier")
+    redirect_uri: str = Field(description="Redirect URI")
+    scopes: list[str] = Field(description="List of scopes")
+    state: str = Field(description="Anti-CSRF token from client")
+    response_type: str = Field(
+        default="code", description="Must be 'code' for authorization code flow"
+    )
+    code_challenge: str = Field(description="PKCE code challenge (required)")
+    code_challenge_method: Literal["S256", "plain"] = Field(
+        default="S256", description="PKCE code challenge method (S256 recommended)"
+    )
+
+
+class AuthorizeResponse(BaseModel):
+    """OAuth 2.0 authorization response with redirect URL"""
+
+    redirect_url: str = Field(description="URL to redirect the user to")
+
+
+@router.post("/authorize")
+async def authorize(
+    request: AuthorizeRequest = Body(),
+    user_id: str = Security(get_user_id),
+) -> AuthorizeResponse:
+    """
+    OAuth 2.0 Authorization Endpoint
+
+    User must be logged in (authenticated with Supabase JWT).
+    This endpoint creates an authorization code and returns a redirect URL.
+
+    PKCE (Proof Key for Code Exchange) is REQUIRED for all authorization requests.
+
+    The frontend consent screen should call this endpoint after the user approves,
+    then redirect the user to the returned `redirect_url`.
+
+    Request Body:
+    - client_id: The OAuth application's client ID
+    - redirect_uri: Where to redirect after authorization (must match registered URI)
+    - scopes: List of permissions (e.g., "EXECUTE_GRAPH READ_GRAPH")
+    - state: Anti-CSRF token provided by client (will be returned in redirect)
+    - response_type: Must be "code" (for authorization code flow)
+    - code_challenge: PKCE code challenge (required)
+    - code_challenge_method: "S256" (recommended) or "plain"
+
+    Returns:
+    - redirect_url: The URL to redirect the user to (includes authorization code)
+
+    Error cases return a redirect_url with error parameters, or raise HTTPException
+    for critical errors (like invalid redirect_uri).
+    """
+    try:
+        # Validate response_type
+        if request.response_type != "code":
+            return _error_redirect_url(
+                request.redirect_uri,
+                request.state,
+                "unsupported_response_type",
+                "Only 'code' response type is supported",
+            )
+
+        # Get application
+        app = await get_oauth_application(request.client_id)
+        if not app:
+            return _error_redirect_url(
+                request.redirect_uri,
+                request.state,
+                "invalid_client",
+                "Unknown client_id",
+            )
+
+        if not app.is_active:
+            return _error_redirect_url(
+                request.redirect_uri,
+                request.state,
+                "invalid_client",
+                "Application is not active",
+            )
+
+        # Validate redirect URI
+        if not validate_redirect_uri(app, request.redirect_uri):
+            # For invalid redirect_uri, we can't redirect safely
+            # Must return error instead
+            raise HTTPException(
+                status_code=status.HTTP_400_BAD_REQUEST,
+                detail=(
+                    "Invalid redirect_uri. "
+                    f"Must be one of: {', '.join(app.redirect_uris)}"
+                ),
+            )
+
+        # Parse and validate scopes
+        try:
+            requested_scopes = [APIKeyPermission(s.strip()) for s in request.scopes]
+        except ValueError as e:
+            return _error_redirect_url(
+                request.redirect_uri,
+                request.state,
+                "invalid_scope",
+                f"Invalid scope: {e}",
+            )
+
+        if not requested_scopes:
+            return _error_redirect_url(
+                request.redirect_uri,
+                request.state,
+                "invalid_scope",
+                "At least one scope is required",
+            )
+
+        if not validate_scopes(app, requested_scopes):
+            return _error_redirect_url(
+                request.redirect_uri,
+                request.state,
+                "invalid_scope",
+                "Application is not authorized for all requested scopes. "
+                f"Allowed: {', '.join(s.value for s in app.scopes)}",
+            )
+
+        # Create authorization code
+        auth_code = await create_authorization_code(
+            application_id=app.id,
+            user_id=user_id,
+            scopes=requested_scopes,
+            redirect_uri=request.redirect_uri,
+            code_challenge=request.code_challenge,
+            code_challenge_method=request.code_challenge_method,
+        )
+
+        # Build redirect URL with authorization code
+        params = {
+            "code": auth_code.code,
+            "state": request.state,
+        }
+        redirect_url = f"{request.redirect_uri}?{urlencode(params)}"
+
+        logger.info(
+            f"Authorization code issued for user #{user_id} "
+            f"and app {app.name} (#{app.id})"
+        )
+
+        return AuthorizeResponse(redirect_url=redirect_url)
+
+    except HTTPException:
+        raise
+    except Exception as e:
+        logger.error(f"Error in authorization endpoint: {e}", exc_info=True)
+        return _error_redirect_url(
+            request.redirect_uri,
+            request.state,
+            "server_error",
+            "An unexpected error occurred",
+        )
+
+
+def _error_redirect_url(
+    redirect_uri: str,
+    state: str,
+    error: str,
+    error_description: Optional[str] = None,
+) -> AuthorizeResponse:
+    """Helper to build redirect URL with OAuth error parameters"""
+    params = {
+        "error": error,
+        "state": state,
+    }
+    if error_description:
+        params["error_description"] = error_description
+
+    redirect_url = f"{redirect_uri}?{urlencode(params)}"
+    return AuthorizeResponse(redirect_url=redirect_url)
+
+
+# ============================================================================
+# Token Endpoint
+# ============================================================================
+
+
+class TokenRequestByCode(BaseModel):
+    grant_type: Literal["authorization_code"]
+    code: str = Field(description="Authorization code")
+    redirect_uri: str = Field(
+        description="Redirect URI (must match authorization request)"
+    )
+    client_id: str
+    client_secret: str
+    code_verifier: str = Field(description="PKCE code verifier")
+
+
+class TokenRequestByRefreshToken(BaseModel):
+    grant_type: Literal["refresh_token"]
+    refresh_token: str
+    client_id: str
+    client_secret: str
+
+
+@router.post("/token")
+async def token(
+    request: TokenRequestByCode | TokenRequestByRefreshToken = Body(),
+) -> TokenResponse:
+    """
+    OAuth 2.0 Token Endpoint
+
+    Exchanges authorization code or refresh token for access token.
+
+    Grant Types:
+    1. authorization_code: Exchange authorization code for tokens
+       - Required: grant_type, code, redirect_uri, client_id, client_secret
+       - Optional: code_verifier (required if PKCE was used)
+
+    2. refresh_token: Exchange refresh token for new access token
+       - Required: grant_type, refresh_token, client_id, client_secret
+
+    Returns:
+    - access_token: Bearer token for API access (1 hour TTL)
+    - token_type: "Bearer"
+    - expires_in: Seconds until access token expires
+    - refresh_token: Token for refreshing access (30 days TTL)
+    - scopes: List of scopes
+    """
+    # Validate client credentials
+    try:
+        app = await validate_client_credentials(
+            request.client_id, request.client_secret
+        )
+    except InvalidClientError as e:
+        raise HTTPException(
+            status_code=status.HTTP_401_UNAUTHORIZED,
+            detail=str(e),
+        )
+
+    # Handle authorization_code grant
+    if request.grant_type == "authorization_code":
+        # Consume authorization code
+        try:
+            user_id, scopes = await consume_authorization_code(
+                code=request.code,
+                application_id=app.id,
+                redirect_uri=request.redirect_uri,
+                code_verifier=request.code_verifier,
+            )
+        except InvalidGrantError as e:
+            raise HTTPException(
+                status_code=status.HTTP_400_BAD_REQUEST,
+                detail=str(e),
+            )
+
+        # Create access and refresh tokens
+        access_token = await create_access_token(app.id, user_id, scopes)
+        refresh_token = await create_refresh_token(app.id, user_id, scopes)
+
+        logger.info(
+            f"Access token issued for user #{user_id} and app {app.name} (#{app.id})"
+            "via authorization code"
+        )
+
+        if not access_token.token or not refresh_token.token:
+            raise HTTPException(
+                status_code=status.HTTP_500_INTERNAL_SERVER_ERROR,
+                detail="Failed to generate tokens",
+            )
+
+        return TokenResponse(
+            token_type="Bearer",
+            access_token=access_token.token.get_secret_value(),
+            access_token_expires_at=access_token.expires_at,
+            refresh_token=refresh_token.token.get_secret_value(),
+            refresh_token_expires_at=refresh_token.expires_at,
+            scopes=list(s.value for s in scopes),
+        )
+
+    # Handle refresh_token grant
+    elif request.grant_type == "refresh_token":
+        # Refresh access token
+        try:
+            new_access_token, new_refresh_token = await refresh_tokens(
+                request.refresh_token, app.id
+            )
+        except InvalidGrantError as e:
+            raise HTTPException(
+                status_code=status.HTTP_400_BAD_REQUEST,
+                detail=str(e),
+            )
+
+        logger.info(
+            f"Tokens refreshed for user #{new_access_token.user_id} "
+            f"by app {app.name} (#{app.id})"
+        )
+
+        if not new_access_token.token or not new_refresh_token.token:
+            raise HTTPException(
+                status_code=status.HTTP_500_INTERNAL_SERVER_ERROR,
+                detail="Failed to generate tokens",
+            )
+
+        return TokenResponse(
+            token_type="Bearer",
+            access_token=new_access_token.token.get_secret_value(),
+            access_token_expires_at=new_access_token.expires_at,
+            refresh_token=new_refresh_token.token.get_secret_value(),
+            refresh_token_expires_at=new_refresh_token.expires_at,
+            scopes=list(s.value for s in new_access_token.scopes),
+        )
+
+    else:
+        raise HTTPException(
+            status_code=status.HTTP_400_BAD_REQUEST,
+            detail=f"Unsupported grant_type: {request.grant_type}. "
+            "Must be 'authorization_code' or 'refresh_token'",
+        )
+
+
+# ============================================================================
+# Token Introspection Endpoint
+# ============================================================================
+
+
+@router.post("/introspect")
+async def introspect(
+    token: str = Body(description="Token to introspect"),
+    token_type_hint: Optional[Literal["access_token", "refresh_token"]] = Body(
+        None, description="Hint about token type ('access_token' or 'refresh_token')"
+    ),
+    client_id: str = Body(description="Client identifier"),
+    client_secret: str = Body(description="Client secret"),
+) -> TokenIntrospectionResult:
+    """
+    OAuth 2.0 Token Introspection Endpoint (RFC 7662)
+
+    Allows clients to check if a token is valid and get its metadata.
+
+    Returns:
+    - active: Whether the token is currently active
+    - scopes: List of authorized scopes (if active)
+    - client_id: The client the token was issued to (if active)
+    - user_id: The user the token represents (if active)
+    - exp: Expiration timestamp (if active)
+    - token_type: "access_token" or "refresh_token" (if active)
+    """
+    # Validate client credentials
+    try:
+        await validate_client_credentials(client_id, client_secret)
+    except InvalidClientError as e:
+        raise HTTPException(
+            status_code=status.HTTP_401_UNAUTHORIZED,
+            detail=str(e),
+        )
+
+    # Introspect the token
+    return await introspect_token(token, token_type_hint)
+
+
+# ============================================================================
+# Token Revocation Endpoint
+# ============================================================================
+
+
+@router.post("/revoke")
+async def revoke(
+    token: str = Body(description="Token to revoke"),
+    token_type_hint: Optional[Literal["access_token", "refresh_token"]] = Body(
+        None, description="Hint about token type ('access_token' or 'refresh_token')"
+    ),
+    client_id: str = Body(description="Client identifier"),
+    client_secret: str = Body(description="Client secret"),
+):
+    """
+    OAuth 2.0 Token Revocation Endpoint (RFC 7009)
+
+    Allows clients to revoke an access or refresh token.
+
+    Note: Revoking a refresh token does NOT revoke associated access tokens.
+    Revoking an access token does NOT revoke the associated refresh token.
+    """
+    # Validate client credentials
+    try:
+        app = await validate_client_credentials(client_id, client_secret)
+    except InvalidClientError as e:
+        raise HTTPException(
+            status_code=status.HTTP_401_UNAUTHORIZED,
+            detail=str(e),
+        )
+
+    # Try to revoke as access token first
+    # Note: We pass app.id to ensure the token belongs to the authenticated app
+    if token_type_hint != "refresh_token":
+        revoked = await revoke_access_token(token, app.id)
+        if revoked:
+            logger.info(
+                f"Access token revoked for app {app.name} (#{app.id}); "
+                f"user #{revoked.user_id}"
+            )
+            return {"status": "ok"}
+
+    # Try to revoke as refresh token
+    revoked = await revoke_refresh_token(token, app.id)
+    if revoked:
+        logger.info(
+            f"Refresh token revoked for app {app.name} (#{app.id}); "
+            f"user #{revoked.user_id}"
+        )
+        return {"status": "ok"}
+
+    # Per RFC 7009, revocation endpoint returns 200 even if token not found
+    # or if token belongs to a different application.
+    # This prevents token scanning attacks.
+    logger.warning(f"Unsuccessful token revocation attempt by app {app.name} #{app.id}")
+    return {"status": "ok"}
+
+
+# ============================================================================
+# Application Management Endpoints (for app owners)
+# ============================================================================
+
+
+@router.get("/apps/mine")
+async def list_my_oauth_apps(
+    user_id: str = Security(get_user_id),
+) -> list[OAuthApplicationInfo]:
+    """
+    List all OAuth applications owned by the current user.
+
+    Returns a list of OAuth applications with their details including:
+    - id, name, description, logo_url
+    - client_id (public identifier)
+    - redirect_uris, grant_types, scopes
+    - is_active status
+    - created_at, updated_at timestamps
+
+    Note: client_secret is never returned for security reasons.
+    """
+    return await list_user_oauth_applications(user_id)
+
+
+@router.patch("/apps/{app_id}/status")
+async def update_app_status(
+    app_id: str,
+    user_id: str = Security(get_user_id),
+    is_active: bool = Body(description="Whether the app should be active", embed=True),
+) -> OAuthApplicationInfo:
+    """
+    Enable or disable an OAuth application.
+
+    Only the application owner can update the status.
+    When disabled, the application cannot be used for new authorizations
+    and existing access tokens will fail validation.
+
+    Returns the updated application info.
+    """
+    updated_app = await update_oauth_application(
+        app_id=app_id,
+        owner_id=user_id,
+        is_active=is_active,
+    )
+
+    if not updated_app:
+        raise HTTPException(
+            status_code=status.HTTP_404_NOT_FOUND,
+            detail="Application not found or you don't have permission to update it",
+        )
+
+    action = "enabled" if is_active else "disabled"
+    logger.info(f"OAuth app {updated_app.name} (#{app_id}) {action} by user #{user_id}")
+
+    return updated_app
+
+
+class UpdateAppLogoRequest(BaseModel):
+    logo_url: str = Field(description="URL of the uploaded logo image")
+
+
+@router.patch("/apps/{app_id}/logo")
+async def update_app_logo(
+    app_id: str,
+    request: UpdateAppLogoRequest = Body(),
+    user_id: str = Security(get_user_id),
+) -> OAuthApplicationInfo:
+    """
+    Update the logo URL for an OAuth application.
+
+    Only the application owner can update the logo.
+    The logo should be uploaded first using the media upload endpoint,
+    then this endpoint is called with the resulting URL.
+
+    Logo requirements:
+    - Must be square (1:1 aspect ratio)
+    - Minimum 512x512 pixels
+    - Maximum 2048x2048 pixels
+
+    Returns the updated application info.
+    """
+    if (
+        not (app := await get_oauth_application_by_id(app_id))
+        or app.owner_id != user_id
+    ):
+        raise HTTPException(
+            status_code=status.HTTP_404_NOT_FOUND,
+            detail="OAuth App not found",
+        )
+
+    # Delete the current app logo file (if any and it's in our cloud storage)
+    await _delete_app_current_logo_file(app)
+
+    updated_app = await update_oauth_application(
+        app_id=app_id,
+        owner_id=user_id,
+        logo_url=request.logo_url,
+    )
+
+    if not updated_app:
+        raise HTTPException(
+            status_code=status.HTTP_404_NOT_FOUND,
+            detail="Application not found or you don't have permission to update it",
+        )
+
+    logger.info(
+        f"OAuth app {updated_app.name} (#{app_id}) logo updated by user #{user_id}"
+    )
+
+    return updated_app
+
+
+# Logo upload constraints
+LOGO_MIN_SIZE = 512
+LOGO_MAX_SIZE = 2048
+LOGO_ALLOWED_TYPES = {"image/jpeg", "image/png", "image/webp"}
+LOGO_MAX_FILE_SIZE = 3 * 1024 * 1024  # 3MB
+
+
+@router.post("/apps/{app_id}/logo/upload")
+async def upload_app_logo(
+    app_id: str,
+    file: UploadFile,
+    user_id: str = Security(get_user_id),
+) -> OAuthApplicationInfo:
+    """
+    Upload a logo image for an OAuth application.
+
+    Requirements:
+    - Image must be square (1:1 aspect ratio)
+    - Minimum 512x512 pixels
+    - Maximum 2048x2048 pixels
+    - Allowed formats: JPEG, PNG, WebP
+    - Maximum file size: 3MB
+
+    The image is uploaded to cloud storage and the app's logoUrl is updated.
+    Returns the updated application info.
+    """
+    # Verify ownership to reduce vulnerability to DoS(torage) or DoM(oney) attacks
+    if (
+        not (app := await get_oauth_application_by_id(app_id))
+        or app.owner_id != user_id
+    ):
+        raise HTTPException(
+            status_code=status.HTTP_404_NOT_FOUND,
+            detail="OAuth App not found",
+        )
+
+    # Check GCS configuration
+    if not settings.config.media_gcs_bucket_name:
+        raise HTTPException(
+            status_code=status.HTTP_503_SERVICE_UNAVAILABLE,
+            detail="Media storage is not configured",
+        )
+
+    # Validate content type
+    content_type = file.content_type
+    if content_type not in LOGO_ALLOWED_TYPES:
+        raise HTTPException(
+            status_code=status.HTTP_400_BAD_REQUEST,
+            detail=f"Invalid file type. Allowed: JPEG, PNG, WebP. Got: {content_type}",
+        )
+
+    # Read file content
+    try:
+        file_bytes = await file.read()
+    except Exception as e:
+        logger.error(f"Error reading logo file: {e}")
+        raise HTTPException(
+            status_code=status.HTTP_400_BAD_REQUEST,
+            detail="Failed to read uploaded file",
+        )
+
+    # Check file size
+    if len(file_bytes) > LOGO_MAX_FILE_SIZE:
+        raise HTTPException(
+            status_code=status.HTTP_400_BAD_REQUEST,
+            detail=(
+                "File too large. "
+                f"Maximum size is {LOGO_MAX_FILE_SIZE // 1024 // 1024}MB"
+            ),
+        )
+
+    # Validate image dimensions
+    try:
+        image = Image.open(io.BytesIO(file_bytes))
+        width, height = image.size
+
+        if width != height:
+            raise HTTPException(
+                status_code=status.HTTP_400_BAD_REQUEST,
+                detail=f"Logo must be square. Got {width}x{height}",
+            )
+
+        if width < LOGO_MIN_SIZE:
+            raise HTTPException(
+                status_code=status.HTTP_400_BAD_REQUEST,
+                detail=f"Logo too small. Minimum {LOGO_MIN_SIZE}x{LOGO_MIN_SIZE}. "
+                f"Got {width}x{height}",
+            )
+
+        if width > LOGO_MAX_SIZE:
+            raise HTTPException(
+                status_code=status.HTTP_400_BAD_REQUEST,
+                detail=f"Logo too large. Maximum {LOGO_MAX_SIZE}x{LOGO_MAX_SIZE}. "
+                f"Got {width}x{height}",
+            )
+    except HTTPException:
+        raise
+    except Exception as e:
+        logger.error(f"Error validating logo image: {e}")
+        raise HTTPException(
+            status_code=status.HTTP_400_BAD_REQUEST,
+            detail="Invalid image file",
+        )
+
+    # Scan for viruses
+    filename = file.filename or "logo"
+    await scan_content_safe(file_bytes, filename=filename)
+
+    # Generate unique filename
+    file_ext = os.path.splitext(filename)[1].lower() or ".png"
+    unique_filename = f"{uuid.uuid4()}{file_ext}"
+    storage_path = f"oauth-apps/{app_id}/logo/{unique_filename}"
+
+    # Upload to GCS
+    try:
+        async with async_storage.Storage() as async_client:
+            bucket_name = settings.config.media_gcs_bucket_name
+
+            await async_client.upload(
+                bucket_name, storage_path, file_bytes, content_type=content_type
+            )
+
+            logo_url = f"https://storage.googleapis.com/{bucket_name}/{storage_path}"
+    except Exception as e:
+        logger.error(f"Error uploading logo to GCS: {e}")
+        raise HTTPException(
+            status_code=status.HTTP_500_INTERNAL_SERVER_ERROR,
+            detail="Failed to upload logo",
+        )
+
+    # Delete the current app logo file (if any and it's in our cloud storage)
+    await _delete_app_current_logo_file(app)
+
+    # Update the app with the new logo URL
+    updated_app = await update_oauth_application(
+        app_id=app_id,
+        owner_id=user_id,
+        logo_url=logo_url,
+    )
+
+    if not updated_app:
+        raise HTTPException(
+            status_code=status.HTTP_404_NOT_FOUND,
+            detail="Application not found or you don't have permission to update it",
+        )
+
+    logger.info(
+        f"OAuth app {updated_app.name} (#{app_id}) logo uploaded by user #{user_id}"
+    )
+
+    return updated_app
+
+
+async def _delete_app_current_logo_file(app: OAuthApplicationInfo):
+    """
+    Delete the current logo file for the given app, if there is one in our cloud storage
+    """
+    bucket_name = settings.config.media_gcs_bucket_name
+    storage_base_url = f"https://storage.googleapis.com/{bucket_name}/"
+
+    if app.logo_url and app.logo_url.startswith(storage_base_url):
+        # Parse blob path from URL: https://storage.googleapis.com/{bucket}/{path}
+        old_path = app.logo_url.replace(storage_base_url, "")
+        try:
+            async with async_storage.Storage() as async_client:
+                await async_client.delete(bucket_name, old_path)
+            logger.info(f"Deleted old logo for OAuth app #{app.id}: {old_path}")
+        except Exception as e:
+            # Log but don't fail - the new logo was uploaded successfully
+            logger.warning(
+                f"Failed to delete old logo for OAuth app #{app.id}: {e}", exc_info=e
+            )

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

@@ -6,9 +6,9 @@ import pytest
 import pytest_mock
 from pytest_snapshot.plugin import Snapshot
 
-import backend.server.v2.otto.models as otto_models
-import backend.server.v2.otto.routes as otto_routes
-from backend.server.v2.otto.service import OttoService
+from . import models as otto_models
+from . import routes as otto_routes
+from .service import OttoService
 
 app = fastapi.FastAPI()
 app.include_router(otto_routes.router)

autogpt_platform/backend/backend/api/features/postmark/postmark.py

@@ -4,12 +4,15 @@ from typing import Annotated
 from fastapi import APIRouter, Body, HTTPException, Query, Security
 from fastapi.responses import JSONResponse
 
+from backend.api.utils.api_key_auth import APIKeyAuthenticator
 from backend.data.user import (
     get_user_by_email,
     set_user_email_verification,
     unsubscribe_user_by_token,
 )
-from backend.server.routers.postmark.models import (
+from backend.util.settings import Settings
+
+from .models import (
     PostmarkBounceEnum,
     PostmarkBounceWebhook,
     PostmarkClickWebhook,
@@ -19,8 +22,6 @@ from backend.server.routers.postmark.models import (
     PostmarkSubscriptionChangeWebhook,
     PostmarkWebhook,
 )
-from backend.server.utils.api_key_auth import APIKeyAuthenticator
-from backend.util.settings import Settings
 
 logger = logging.getLogger(__name__)
 settings = Settings()

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

@@ -1,8 +1,9 @@
 from typing import Literal
 
-import backend.server.v2.store.db
 from backend.util.cache import cached
 
+from . import db as store_db
+
 ##############################################
 ############### Caches #######################
 ##############################################
@@ -27,10 +28,9 @@ async def _get_cached_store_agents(
     category: str | None,
     page: int,
     page_size: int,
-    filter_mode: Literal["strict", "permissive", "combined"] = "permissive",
 ):
-    """Cached helper to get store agents with hybrid search support."""
-    return await backend.server.v2.store.db.get_store_agents(
+    """Cached helper to get store agents."""
+    return await store_db.get_store_agents(
         featured=featured,
         creators=[creator] if creator else None,
         sorted_by=sorted_by,
@@ -38,16 +38,17 @@ async def _get_cached_store_agents(
         category=category,
         page=page,
         page_size=page_size,
-        filter_mode=filter_mode,
     )
 
 
 # Cache individual agent details for 15 minutes
 @cached(maxsize=200, ttl_seconds=300, shared_cache=True)
-async def _get_cached_agent_details(username: str, agent_name: str):
+async def _get_cached_agent_details(
+    username: str, agent_name: str, include_changelog: bool = False
+):
     """Cached helper to get agent details."""
-    return await backend.server.v2.store.db.get_store_agent_details(
-        username=username, agent_name=agent_name
+    return await store_db.get_store_agent_details(
+        username=username, agent_name=agent_name, include_changelog=include_changelog
     )
 
 
@@ -61,7 +62,7 @@ async def _get_cached_store_creators(
     page_size: int,
 ):
     """Cached helper to get store creators."""
-    return await backend.server.v2.store.db.get_store_creators(
+    return await store_db.get_store_creators(
         featured=featured,
         search_query=search_query,
         sorted_by=sorted_by,
@@ -74,6 +75,4 @@ async def _get_cached_store_creators(
 @cached(maxsize=100, ttl_seconds=300, shared_cache=True)
 async def _get_cached_creator_details(username: str):
     """Cached helper to get creator details."""
-    return await backend.server.v2.store.db.get_store_creator_details(
-        username=username.lower()
-    )
+    return await store_db.get_store_creator_details(username=username.lower())

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

@@ -10,8 +10,6 @@ import prisma.errors
 import prisma.models
 import prisma.types
 
-import backend.server.v2.store.exceptions
-import backend.server.v2.store.model
 from backend.data.db import query_raw_with_schema, transaction
 from backend.data.graph import (
     GraphMeta,
@@ -26,11 +24,13 @@ from backend.data.notifications import (
     AgentRejectionData,
     NotificationEventModel,
 )
-from backend.integrations.embeddings import create_search_text, get_embedding_service
 from backend.notifications.notifications import queue_notification_async
 from backend.util.exceptions import DatabaseError
 from backend.util.settings import Settings
 
+from . import exceptions as store_exceptions
+from . import model as store_model
+
 logger = logging.getLogger(__name__)
 settings = Settings()
 
@@ -39,25 +39,6 @@ settings = Settings()
 DEFAULT_ADMIN_NAME = "AutoGPT Admin"
 DEFAULT_ADMIN_EMAIL = "admin@autogpt.co"
 
-# Minimum similarity threshold for vector search results
-# Cosine similarity ranges from -1 to 1, where 1 is identical
-# 0.4 filters loosely related results while keeping semantically relevant ones
-VECTOR_SEARCH_SIMILARITY_THRESHOLD = 0.4
-
-# Minimum relevance threshold for BM25 full-text search results
-# ts_rank_cd returns values typically in range 0-1 (can exceed 1 for exact matches)
-# 0.05 allows partial keyword matches
-BM25_RELEVANCE_THRESHOLD = 0.05
-
-# RRF constant (k) - standard value that balances influence of top vs lower ranks
-# Higher k values reduce the influence of high-ranking items
-RRF_K = 60
-
-# Minimum RRF score threshold for combined mode
-# Filters out results that rank poorly across all signals
-# For reference: rank #1 in all = ~0.041, rank #100 in all = ~0.016
-RRF_SCORE_THRESHOLD = 0.02
-
 
 async def get_store_agents(
     featured: bool = False,
@@ -67,223 +48,64 @@ async def get_store_agents(
     category: str | None = None,
     page: int = 1,
     page_size: int = 20,
-    filter_mode: Literal["strict", "permissive", "combined"] = "permissive",
-) -> backend.server.v2.store.model.StoreAgentsResponse:
+) -> store_model.StoreAgentsResponse:
     """
-    Get PUBLIC store agents from the StoreAgent view.
-
-    When search_query is provided, uses hybrid search combining:
-    - BM25 full-text search (lexical matching via PostgreSQL tsvector)
-    - Vector semantic similarity (meaning-based matching via pgvector)
-    - Popularity signal (run counts as PageRank proxy)
-
-    Results are ranked using Reciprocal Rank Fusion (RRF).
-
-    Args:
-        featured: Filter to only show featured agents.
-        creators: Filter agents by creator usernames.
-        sorted_by: Sort agents by "runs", "rating", "name", or "updated_at".
-        search_query: Search query for hybrid search.
-        category: Filter agents by category.
-        page: Page number for pagination.
-        page_size: Number of agents per page.
-        filter_mode: Controls how results are filtered when searching:
-            - "strict": Must match BOTH BM25 AND vector thresholds
-            - "permissive": Must match EITHER BM25 OR vector threshold
-            - "combined": No threshold filtering, rely on RRF score (default)
-
-    Returns:
-        StoreAgentsResponse with paginated list of agents.
+    Get PUBLIC store agents from the StoreAgent view
     """
     logger.debug(
-        f"Getting store agents. featured={featured}, creators={creators}, "
-        f"sorted_by={sorted_by}, search={search_query}, category={category}, "
-        f"page={page}, filter_mode={filter_mode}"
+        f"Getting store agents. featured={featured}, creators={creators}, sorted_by={sorted_by}, search={search_query}, category={category}, page={page}"
     )
 
     try:
-        # If search_query is provided, use hybrid search (BM25 + vector + popularity)
+        # If search_query is provided, use full-text search
         if search_query:
             offset = (page - 1) * page_size
 
-            # Try to generate embedding for vector search
-            # Falls back to BM25-only if embedding service is not available
-            query_embedding: list[float] | None = None
-            try:
-                embedding_service = get_embedding_service()
-                query_embedding = await embedding_service.generate_embedding(
-                    search_query
-                )
-            except (ValueError, Exception) as e:
-                # Embedding service not configured or failed - use BM25 only
-                logger.warning(f"Embedding generation failed, using BM25 only: {e}")
+            # Whitelist allowed order_by columns
+            ALLOWED_ORDER_BY = {
+                "rating": "rating DESC, rank DESC",
+                "runs": "runs DESC, rank DESC",
+                "name": "agent_name ASC, rank ASC",
+                "updated_at": "updated_at DESC, rank DESC",
+            }
 
-            # Convert embedding to PostgreSQL array format (or None for BM25-only)
-            embedding_str = (
-                "[" + ",".join(map(str, query_embedding)) + "]"
-                if query_embedding
-                else None
-            )
+            # Validate and get order clause
+            if sorted_by and sorted_by in ALLOWED_ORDER_BY:
+                order_by_clause = ALLOWED_ORDER_BY[sorted_by]
+            else:
+                order_by_clause = "updated_at DESC, rank DESC"
 
             # Build WHERE conditions and parameters list
-            # When embedding is not available (no OpenAI key), $1 will be NULL
             where_parts: list[str] = []
-            params: list[typing.Any] = [embedding_str]  # $1 - query embedding (or NULL)
+            params: list[typing.Any] = [search_query]  # $1 - search term
             param_index = 2  # Start at $2 for next parameter
 
             # Always filter for available agents
             where_parts.append("is_available = true")
 
-            # Require search signals to be present
-            if embedding_str is None:
-                # No embedding available - require BM25 search only
-                where_parts.append("search IS NOT NULL")
-            elif filter_mode == "strict":
-                # Strict mode: require both embedding AND search to be available
-                where_parts.append("embedding IS NOT NULL")
-                where_parts.append("search IS NOT NULL")
-            else:
-                # Permissive/combined: require at least one signal
-                where_parts.append("(embedding IS NOT NULL OR search IS NOT NULL)")
-
             if featured:
                 where_parts.append("featured = true")
 
-            if creators:
+            if creators and creators:
                 # Use ANY with array parameter
                 where_parts.append(f"creator_username = ANY(${param_index})")
                 params.append(creators)
                 param_index += 1
 
-            if category:
+            if category and category:
                 where_parts.append(f"${param_index} = ANY(categories)")
                 params.append(category)
                 param_index += 1
 
-            # Add search query for BM25
-            params.append(search_query)
-            bm25_query_param = f"${param_index}"
-            param_index += 1
-
             sql_where_clause: str = " AND ".join(where_parts) if where_parts else "1=1"
 
-            # Build score filter based on filter_mode
-            # This filter is applied BEFORE RRF ranking in the filtered_agents CTE
-            if embedding_str is None:
-                # No embedding - filter only on BM25 score
-                score_filter = f"bm25_score >= {BM25_RELEVANCE_THRESHOLD}"
-            elif filter_mode == "strict":
-                score_filter = f"""
-                    bm25_score >= {BM25_RELEVANCE_THRESHOLD}
-                    AND vector_score >= {VECTOR_SEARCH_SIMILARITY_THRESHOLD}
-                """
-            elif filter_mode == "permissive":
-                score_filter = f"""
-                    bm25_score >= {BM25_RELEVANCE_THRESHOLD}
-                    OR vector_score >= {VECTOR_SEARCH_SIMILARITY_THRESHOLD}
-                """
-            else:  # combined - no pre-filtering on individual scores
-                score_filter = "1=1"
-
-            # RRF score filter is applied AFTER ranking to filter irrelevant results
-            rrf_score_filter = f"rrf_score >= {RRF_SCORE_THRESHOLD}"
-
-            # Build ORDER BY clause - sorted_by takes precedence, rrf_score as secondary
-            if sorted_by == "rating":
-                order_by_clause = "rating DESC, rrf_score DESC"
-            elif sorted_by == "runs":
-                order_by_clause = "runs DESC, rrf_score DESC"
-            elif sorted_by == "name":
-                order_by_clause = "agent_name ASC, rrf_score DESC"
-            elif sorted_by == "updated_at":
-                order_by_clause = "updated_at DESC, rrf_score DESC"
-            else:
-                # Default: order by RRF relevance score
-                order_by_clause = "rrf_score DESC, updated_at DESC"
-
             # Add pagination params
             params.extend([page_size, offset])
             limit_param = f"${param_index}"
             offset_param = f"${param_index + 1}"
 
-            # Hybrid search SQL with Reciprocal Rank Fusion (RRF)
-            # CTEs: scored_agents -> filtered_agents -> ranked_agents -> rrf_scored
+            # Execute full-text search query with parameterized values
             sql_query = f"""
-                WITH scored_agents AS (
-                    SELECT
-                        slug,
-                        agent_name,
-                        agent_image,
-                        creator_username,
-                        creator_avatar,
-                        sub_heading,
-                        description,
-                        runs,
-                        rating,
-                        categories,
-                        featured,
-                        is_available,
-                        updated_at,
-                        -- BM25 score using ts_rank_cd (covers density normalization)
-                        COALESCE(
-                            ts_rank_cd(
-                                search,
-                                plainto_tsquery('english', {bm25_query_param}),
-                                32  -- normalization: divide by document length
-                            ),
-                            0
-                        ) AS bm25_score,
-                        -- Vector similarity score (cosine: 1 - distance)
-                        -- Returns 0 when query embedding ($1) is NULL (no OpenAI key)
-                        CASE
-                            WHEN $1 IS NOT NULL AND embedding IS NOT NULL
-                            THEN 1 - (embedding <=> $1::vector)
-                            ELSE 0
-                        END AS vector_score,
-                        -- Popularity score (log-normalized run count)
-                        CASE
-                            WHEN runs > 0
-                            THEN LN(runs + 1)
-                            ELSE 0
-                        END AS popularity_score
-                    FROM {{schema_prefix}}"StoreAgent"
-                    WHERE {sql_where_clause}
-                ),
-                max_popularity AS (
-                    SELECT GREATEST(MAX(popularity_score), 1) AS max_pop
-                    FROM scored_agents
-                ),
-                normalized_agents AS (
-                    SELECT
-                        sa.*,
-                        -- Normalize popularity to [0, 1] range
-                        sa.popularity_score / mp.max_pop AS norm_popularity_score
-                    FROM scored_agents sa
-                    CROSS JOIN max_popularity mp
-                ),
-                filtered_agents AS (
-                    SELECT *
-                    FROM normalized_agents
-                    WHERE {score_filter}
-                ),
-                ranked_agents AS (
-                    SELECT
-                        *,
-                        ROW_NUMBER() OVER (ORDER BY bm25_score DESC NULLS LAST) AS bm25_rank,
-                        ROW_NUMBER() OVER (ORDER BY vector_score DESC NULLS LAST) AS vector_rank,
-                        ROW_NUMBER() OVER (ORDER BY norm_popularity_score DESC NULLS LAST) AS popularity_rank
-                    FROM filtered_agents
-                ),
-                rrf_scored AS (
-                    SELECT
-                        *,
-                        -- RRF formula with weighted contributions
-                        -- BM25 and vector get full weight, popularity gets 0.5x weight
-                        (1.0 / ({RRF_K} + bm25_rank)) +
-                        (1.0 / ({RRF_K} + vector_rank)) +
-                        (0.5 / ({RRF_K} + popularity_rank)) AS rrf_score
-                    FROM ranked_agents
-                )
                 SELECT
                     slug,
                     agent_name,
@@ -298,79 +120,25 @@ async def get_store_agents(
                     featured,
                     is_available,
                     updated_at,
-                    rrf_score
-                FROM rrf_scored
-                WHERE {rrf_score_filter}
+                    ts_rank_cd(search, query) AS rank
+                FROM {{schema_prefix}}"StoreAgent",
+                    plainto_tsquery('english', $1) AS query
+                WHERE {sql_where_clause}
+                    AND search @@ query
                 ORDER BY {order_by_clause}
                 LIMIT {limit_param} OFFSET {offset_param}
             """
 
-            # Count query (without pagination) - requires same CTE structure because:
-            # 1. RRF scoring requires computing ranks across ALL matching results
-            # 2. The rrf_score_filter threshold must be applied consistently
-            # Note: This is inherent to RRF - there's no way to count without ranking
+            # Count query for pagination - only uses search term parameter
             count_query = f"""
-                WITH scored_agents AS (
-                    SELECT
-                        runs,
-                        COALESCE(
-                            ts_rank_cd(
-                                search,
-                                plainto_tsquery('english', {bm25_query_param}),
-                                32
-                            ),
-                            0
-                        ) AS bm25_score,
-                        CASE
-                            WHEN $1 IS NOT NULL AND embedding IS NOT NULL
-                            THEN 1 - (embedding <=> $1::vector)
-                            ELSE 0
-                        END AS vector_score,
-                        CASE
-                            WHEN runs > 0
-                            THEN LN(runs + 1)
-                            ELSE 0
-                        END AS popularity_score
-                    FROM {{schema_prefix}}"StoreAgent"
-                    WHERE {sql_where_clause}
-                ),
-                max_popularity AS (
-                    SELECT GREATEST(MAX(popularity_score), 1) AS max_pop
-                    FROM scored_agents
-                ),
-                normalized_agents AS (
-                    SELECT
-                        sa.*,
-                        sa.popularity_score / mp.max_pop AS norm_popularity_score
-                    FROM scored_agents sa
-                    CROSS JOIN max_popularity mp
-                ),
-                filtered_agents AS (
-                    SELECT *
-                    FROM normalized_agents
-                    WHERE {score_filter}
-                ),
-                ranked_agents AS (
-                    SELECT
-                        *,
-                        ROW_NUMBER() OVER (ORDER BY bm25_score DESC NULLS LAST) AS bm25_rank,
-                        ROW_NUMBER() OVER (ORDER BY vector_score DESC NULLS LAST) AS vector_rank,
-                        ROW_NUMBER() OVER (ORDER BY norm_popularity_score DESC NULLS LAST) AS popularity_rank
-                    FROM filtered_agents
-                ),
-                rrf_scored AS (
-                    SELECT
-                        (1.0 / ({RRF_K} + bm25_rank)) +
-                        (1.0 / ({RRF_K} + vector_rank)) +
-                        (0.5 / ({RRF_K} + popularity_rank)) AS rrf_score
-                    FROM ranked_agents
-                )
                 SELECT COUNT(*) as count
-                FROM rrf_scored
-                WHERE {rrf_score_filter}
+                FROM {{schema_prefix}}"StoreAgent",
+                    plainto_tsquery('english', $1) AS query
+                WHERE {sql_where_clause}
+                    AND search @@ query
             """
 
-            # Execute queries
+            # Execute both queries with parameters
             agents = await query_raw_with_schema(sql_query, *params)
 
             # For count, use params without pagination (last 2 params)
@@ -381,10 +149,10 @@ async def get_store_agents(
             total_pages = (total + page_size - 1) // page_size
 
             # Convert raw results to StoreAgent models
-            store_agents: list[backend.server.v2.store.model.StoreAgent] = []
+            store_agents: list[store_model.StoreAgent] = []
             for agent in agents:
                 try:
-                    store_agent = backend.server.v2.store.model.StoreAgent(
+                    store_agent = store_model.StoreAgent(
                         slug=agent["slug"],
                         agent_name=agent["agent_name"],
                         agent_image=(
@@ -430,11 +198,11 @@ async def get_store_agents(
             total = await prisma.models.StoreAgent.prisma().count(where=where_clause)
             total_pages = (total + page_size - 1) // page_size
 
-            store_agents: list[backend.server.v2.store.model.StoreAgent] = []
+            store_agents: list[store_model.StoreAgent] = []
             for agent in agents:
                 try:
                     # Create the StoreAgent object safely
-                    store_agent = backend.server.v2.store.model.StoreAgent(
+                    store_agent = store_model.StoreAgent(
                         slug=agent.slug,
                         agent_name=agent.agent_name,
                         agent_image=agent.agent_image[0] if agent.agent_image else "",
@@ -456,9 +224,9 @@ async def get_store_agents(
                     continue
 
         logger.debug(f"Found {len(store_agents)} agents")
-        return backend.server.v2.store.model.StoreAgentsResponse(
+        return store_model.StoreAgentsResponse(
             agents=store_agents,
-            pagination=backend.server.v2.store.model.Pagination(
+            pagination=store_model.Pagination(
                 current_page=page,
                 total_items=total,
                 total_pages=total_pages,
@@ -488,59 +256,9 @@ async def log_search_term(search_query: str):
         logger.error(f"Error logging search term: {e}")
 
 
-async def _generate_and_store_embedding(
-    store_listing_version_id: str,
-    name: str,
-    sub_heading: str,
-    description: str,
-) -> None:
-    """
-    Generate and store embedding for a store listing version.
-
-    This creates a vector embedding from the agent's name, sub_heading, and
-    description, which is used for semantic search.
-
-    Args:
-        store_listing_version_id: The ID of the store listing version.
-        name: The agent name.
-        sub_heading: The agent sub-heading/tagline.
-        description: The agent description.
-    """
-    try:
-        embedding_service = get_embedding_service()
-        search_text = create_search_text(name, sub_heading, description)
-
-        if not search_text:
-            logger.warning(
-                f"No searchable text for version {store_listing_version_id}, "
-                "skipping embedding generation"
-            )
-            return
-
-        embedding = await embedding_service.generate_embedding(search_text)
-        embedding_str = "[" + ",".join(map(str, embedding)) + "]"
-
-        await query_raw_with_schema(
-            """
-            UPDATE {schema_prefix}"StoreListingVersion"
-            SET embedding = $1::vector
-            WHERE id = $2
-            """,
-            embedding_str,
-            store_listing_version_id,
-        )
-        logger.debug(f"Generated embedding for version {store_listing_version_id}")
-    except Exception as e:
-        # Log error but don't fail the whole operation
-        # Embeddings can be generated later via backfill
-        logger.error(
-            f"Failed to generate embedding for {store_listing_version_id}: {e}"
-        )
-
-
 async def get_store_agent_details(
-    username: str, agent_name: str
-) -> backend.server.v2.store.model.StoreAgentDetails:
+    username: str, agent_name: str, include_changelog: bool = False
+) -> store_model.StoreAgentDetails:
     """Get PUBLIC store agent details from the StoreAgent view"""
     logger.debug(f"Getting store agent details for {username}/{agent_name}")
 
@@ -551,7 +269,7 @@ async def get_store_agent_details(
 
         if not agent:
             logger.warning(f"Agent not found: {username}/{agent_name}")
-            raise backend.server.v2.store.exceptions.AgentNotFoundError(
+            raise store_exceptions.AgentNotFoundError(
                 f"Agent {username}/{agent_name} not found"
             )
 
@@ -604,8 +322,29 @@ async def get_store_agent_details(
         else:
             recommended_schedule_cron = None
 
+        # Fetch changelog data if requested
+        changelog_data = None
+        if include_changelog and store_listing:
+            changelog_versions = (
+                await prisma.models.StoreListingVersion.prisma().find_many(
+                    where={
+                        "storeListingId": store_listing.id,
+                        "submissionStatus": prisma.enums.SubmissionStatus.APPROVED,
+                    },
+                    order=[{"version": "desc"}],
+                )
+            )
+            changelog_data = [
+                store_model.ChangelogEntry(
+                    version=str(version.version),
+                    changes_summary=version.changesSummary or "No changes recorded",
+                    date=version.createdAt,
+                )
+                for version in changelog_versions
+            ]
+
         logger.debug(f"Found agent details for {username}/{agent_name}")
-        return backend.server.v2.store.model.StoreAgentDetails(
+        return store_model.StoreAgentDetails(
             store_listing_version_id=agent.storeListingVersionId,
             slug=agent.slug,
             agent_name=agent.agent_name,
@@ -620,12 +359,15 @@ async def get_store_agent_details(
             runs=agent.runs,
             rating=agent.rating,
             versions=agent.versions,
+            agentGraphVersions=agent.agentGraphVersions,
+            agentGraphId=agent.agentGraphId,
             last_updated=agent.updated_at,
             active_version_id=active_version_id,
             has_approved_version=has_approved_version,
             recommended_schedule_cron=recommended_schedule_cron,
+            changelog=changelog_data,
         )
-    except backend.server.v2.store.exceptions.AgentNotFoundError:
+    except store_exceptions.AgentNotFoundError:
         raise
     except Exception as e:
         logger.error(f"Error getting store agent details: {e}")
@@ -661,7 +403,7 @@ async def get_available_graph(store_listing_version_id: str) -> GraphMeta:
 
 async def get_store_agent_by_version_id(
     store_listing_version_id: str,
-) -> backend.server.v2.store.model.StoreAgentDetails:
+) -> store_model.StoreAgentDetails:
     logger.debug(f"Getting store agent details for {store_listing_version_id}")
 
     try:
@@ -671,12 +413,12 @@ async def get_store_agent_by_version_id(
 
         if not agent:
             logger.warning(f"Agent not found: {store_listing_version_id}")
-            raise backend.server.v2.store.exceptions.AgentNotFoundError(
+            raise store_exceptions.AgentNotFoundError(
                 f"Agent {store_listing_version_id} not found"
             )
 
         logger.debug(f"Found agent details for {store_listing_version_id}")
-        return backend.server.v2.store.model.StoreAgentDetails(
+        return store_model.StoreAgentDetails(
             store_listing_version_id=agent.storeListingVersionId,
             slug=agent.slug,
             agent_name=agent.agent_name,
@@ -691,9 +433,11 @@ async def get_store_agent_by_version_id(
             runs=agent.runs,
             rating=agent.rating,
             versions=agent.versions,
+            agentGraphVersions=agent.agentGraphVersions,
+            agentGraphId=agent.agentGraphId,
             last_updated=agent.updated_at,
         )
-    except backend.server.v2.store.exceptions.AgentNotFoundError:
+    except store_exceptions.AgentNotFoundError:
         raise
     except Exception as e:
         logger.error(f"Error getting store agent details: {e}")
@@ -706,7 +450,7 @@ async def get_store_creators(
     sorted_by: Literal["agent_rating", "agent_runs", "num_agents"] | None = None,
     page: int = 1,
     page_size: int = 20,
-) -> backend.server.v2.store.model.CreatorsResponse:
+) -> store_model.CreatorsResponse:
     """Get PUBLIC store creators from the Creator view"""
     logger.debug(
         f"Getting store creators. featured={featured}, search={search_query}, sorted_by={sorted_by}, page={page}"
@@ -781,7 +525,7 @@ async def get_store_creators(
 
         # Convert to response model
         creator_models = [
-            backend.server.v2.store.model.Creator(
+            store_model.Creator(
                 username=creator.username,
                 name=creator.name,
                 description=creator.description,
@@ -795,9 +539,9 @@ async def get_store_creators(
         ]
 
         logger.debug(f"Found {len(creator_models)} creators")
-        return backend.server.v2.store.model.CreatorsResponse(
+        return store_model.CreatorsResponse(
             creators=creator_models,
-            pagination=backend.server.v2.store.model.Pagination(
+            pagination=store_model.Pagination(
                 current_page=page,
                 total_items=total,
                 total_pages=total_pages,
@@ -811,7 +555,7 @@ async def get_store_creators(
 
 async def get_store_creator_details(
     username: str,
-) -> backend.server.v2.store.model.CreatorDetails:
+) -> store_model.CreatorDetails:
     logger.debug(f"Getting store creator details for {username}")
 
     try:
@@ -822,12 +566,10 @@ async def get_store_creator_details(
 
         if not creator:
             logger.warning(f"Creator not found: {username}")
-            raise backend.server.v2.store.exceptions.CreatorNotFoundError(
-                f"Creator {username} not found"
-            )
+            raise store_exceptions.CreatorNotFoundError(f"Creator {username} not found")
 
         logger.debug(f"Found creator details for {username}")
-        return backend.server.v2.store.model.CreatorDetails(
+        return store_model.CreatorDetails(
             name=creator.name,
             username=creator.username,
             description=creator.description,
@@ -837,7 +579,7 @@ async def get_store_creator_details(
             agent_runs=creator.agent_runs,
             top_categories=creator.top_categories,
         )
-    except backend.server.v2.store.exceptions.CreatorNotFoundError:
+    except store_exceptions.CreatorNotFoundError:
         raise
     except Exception as e:
         logger.error(f"Error getting store creator details: {e}")
@@ -846,7 +588,7 @@ async def get_store_creator_details(
 
 async def get_store_submissions(
     user_id: str, page: int = 1, page_size: int = 20
-) -> backend.server.v2.store.model.StoreSubmissionsResponse:
+) -> store_model.StoreSubmissionsResponse:
     """Get store submissions for the authenticated user -- not an admin"""
     logger.debug(f"Getting store submissions for user {user_id}, page={page}")
 
@@ -871,7 +613,7 @@ async def get_store_submissions(
         # Convert to response models
         submission_models = []
         for sub in submissions:
-            submission_model = backend.server.v2.store.model.StoreSubmission(
+            submission_model = store_model.StoreSubmission(
                 agent_id=sub.agent_id,
                 agent_version=sub.agent_version,
                 name=sub.name,
@@ -896,9 +638,9 @@ async def get_store_submissions(
             submission_models.append(submission_model)
 
         logger.debug(f"Found {len(submission_models)} submissions")
-        return backend.server.v2.store.model.StoreSubmissionsResponse(
+        return store_model.StoreSubmissionsResponse(
             submissions=submission_models,
-            pagination=backend.server.v2.store.model.Pagination(
+            pagination=store_model.Pagination(
                 current_page=page,
                 total_items=total,
                 total_pages=total_pages,
@@ -909,9 +651,9 @@ async def get_store_submissions(
     except Exception as e:
         logger.error(f"Error fetching store submissions: {e}")
         # Return empty response rather than exposing internal errors
-        return backend.server.v2.store.model.StoreSubmissionsResponse(
+        return store_model.StoreSubmissionsResponse(
             submissions=[],
-            pagination=backend.server.v2.store.model.Pagination(
+            pagination=store_model.Pagination(
                 current_page=page,
                 total_items=0,
                 total_pages=0,
@@ -944,7 +686,7 @@ async def delete_store_submission(
 
         if not submission:
             logger.warning(f"Submission not found for user {user_id}: {submission_id}")
-            raise backend.server.v2.store.exceptions.SubmissionNotFoundError(
+            raise store_exceptions.SubmissionNotFoundError(
                 f"Submission not found for this user. User ID: {user_id}, Submission ID: {submission_id}"
             )
 
@@ -976,7 +718,7 @@ async def create_store_submission(
     categories: list[str] = [],
     changes_summary: str | None = "Initial Submission",
     recommended_schedule_cron: str | None = None,
-) -> backend.server.v2.store.model.StoreSubmission:
+) -> store_model.StoreSubmission:
     """
     Create the first (and only) store listing and thus submission as a normal user
 
@@ -1017,7 +759,7 @@ async def create_store_submission(
             logger.warning(
                 f"Agent not found for user {user_id}: {agent_id} v{agent_version}"
             )
-            raise backend.server.v2.store.exceptions.AgentNotFoundError(
+            raise store_exceptions.AgentNotFoundError(
                 f"Agent not found for this user. User ID: {user_id}, Agent ID: {agent_id}, Version: {agent_version}"
             )
 
@@ -1088,15 +830,9 @@ async def create_store_submission(
             else None
         )
 
-        # Generate embedding for semantic search
-        if store_listing_version_id:
-            await _generate_and_store_embedding(
-                store_listing_version_id, name, sub_heading, description
-            )
-
         logger.debug(f"Created store listing for agent {agent_id}")
         # Return submission details
-        return backend.server.v2.store.model.StoreSubmission(
+        return store_model.StoreSubmission(
             agent_id=agent_id,
             agent_version=agent_version,
             name=name,
@@ -1119,7 +855,7 @@ async def create_store_submission(
             logger.debug(
                 f"Slug '{slug}' is already in use by another agent (agent_id: {agent_id}) for user {user_id}"
             )
-            raise backend.server.v2.store.exceptions.SlugAlreadyInUseError(
+            raise store_exceptions.SlugAlreadyInUseError(
                 f"The URL slug '{slug}' is already in use by another one of your agents. Please choose a different slug."
             ) from exc
         else:
@@ -1128,8 +864,8 @@ async def create_store_submission(
                 f"Unique constraint violated (not slug): {error_str}"
             ) from exc
     except (
-        backend.server.v2.store.exceptions.AgentNotFoundError,
-        backend.server.v2.store.exceptions.ListingExistsError,
+        store_exceptions.AgentNotFoundError,
+        store_exceptions.ListingExistsError,
     ):
         raise
     except prisma.errors.PrismaError as e:
@@ -1150,7 +886,7 @@ async def edit_store_submission(
     changes_summary: str | None = "Update submission",
     recommended_schedule_cron: str | None = None,
     instructions: str | None = None,
-) -> backend.server.v2.store.model.StoreSubmission:
+) -> store_model.StoreSubmission:
     """
     Edit an existing store listing submission.
 
@@ -1192,7 +928,7 @@ async def edit_store_submission(
         )
 
         if not current_version:
-            raise backend.server.v2.store.exceptions.SubmissionNotFoundError(
+            raise store_exceptions.SubmissionNotFoundError(
                 f"Store listing version not found: {store_listing_version_id}"
             )
 
@@ -1201,7 +937,7 @@ async def edit_store_submission(
             not current_version.StoreListing
             or current_version.StoreListing.owningUserId != user_id
         ):
-            raise backend.server.v2.store.exceptions.UnauthorizedError(
+            raise store_exceptions.UnauthorizedError(
                 f"User {user_id} does not own submission {store_listing_version_id}"
             )
 
@@ -1210,7 +946,7 @@ async def edit_store_submission(
 
         # Check if we can edit this submission
         if current_version.submissionStatus == prisma.enums.SubmissionStatus.REJECTED:
-            raise backend.server.v2.store.exceptions.InvalidOperationError(
+            raise store_exceptions.InvalidOperationError(
                 "Cannot edit a rejected submission"
             )
 
@@ -1259,13 +995,7 @@ async def edit_store_submission(
 
             if not updated_version:
                 raise DatabaseError("Failed to update store listing version")
-
-            # Regenerate embedding with updated content
-            await _generate_and_store_embedding(
-                store_listing_version_id, name, sub_heading, description
-            )
-
-            return backend.server.v2.store.model.StoreSubmission(
+            return store_model.StoreSubmission(
                 agent_id=current_version.agentGraphId,
                 agent_version=current_version.agentGraphVersion,
                 name=name,
@@ -1286,16 +1016,16 @@ async def edit_store_submission(
             )
 
         else:
-            raise backend.server.v2.store.exceptions.InvalidOperationError(
+            raise store_exceptions.InvalidOperationError(
                 f"Cannot edit submission with status: {current_version.submissionStatus}"
             )
 
     except (
-        backend.server.v2.store.exceptions.SubmissionNotFoundError,
-        backend.server.v2.store.exceptions.UnauthorizedError,
-        backend.server.v2.store.exceptions.AgentNotFoundError,
-        backend.server.v2.store.exceptions.ListingExistsError,
-        backend.server.v2.store.exceptions.InvalidOperationError,
+        store_exceptions.SubmissionNotFoundError,
+        store_exceptions.UnauthorizedError,
+        store_exceptions.AgentNotFoundError,
+        store_exceptions.ListingExistsError,
+        store_exceptions.InvalidOperationError,
     ):
         raise
     except prisma.errors.PrismaError as e:
@@ -1318,7 +1048,7 @@ async def create_store_version(
     categories: list[str] = [],
     changes_summary: str | None = "Initial submission",
     recommended_schedule_cron: str | None = None,
-) -> backend.server.v2.store.model.StoreSubmission:
+) -> store_model.StoreSubmission:
     """
     Create a new version for an existing store listing
 
@@ -1351,7 +1081,7 @@ async def create_store_version(
         )
 
         if not listing:
-            raise backend.server.v2.store.exceptions.ListingNotFoundError(
+            raise store_exceptions.ListingNotFoundError(
                 f"Store listing not found. User ID: {user_id}, Listing ID: {store_listing_id}"
             )
 
@@ -1363,7 +1093,7 @@ async def create_store_version(
         )
 
         if not agent:
-            raise backend.server.v2.store.exceptions.AgentNotFoundError(
+            raise store_exceptions.AgentNotFoundError(
                 f"Agent not found for this user. User ID: {user_id}, Agent ID: {agent_id}, Version: {agent_version}"
             )
 
@@ -1397,14 +1127,8 @@ async def create_store_version(
         logger.debug(
             f"Created new version for listing {store_listing_id} of agent {agent_id}"
         )
-
-        # Generate embedding for semantic search
-        await _generate_and_store_embedding(
-            new_version.id, name, sub_heading, description
-        )
-
         # Return submission details
-        return backend.server.v2.store.model.StoreSubmission(
+        return store_model.StoreSubmission(
             agent_id=agent_id,
             agent_version=agent_version,
             name=name,
@@ -1431,7 +1155,7 @@ async def create_store_review(
     store_listing_version_id: str,
     score: int,
     comments: str | None = None,
-) -> backend.server.v2.store.model.StoreReview:
+) -> store_model.StoreReview:
     """Create a review for a store listing as a user to detail their experience"""
     try:
         data = prisma.types.StoreListingReviewUpsertInput(
@@ -1456,7 +1180,7 @@ async def create_store_review(
             data=data,
         )
 
-        return backend.server.v2.store.model.StoreReview(
+        return store_model.StoreReview(
             score=review.score,
             comments=review.comments,
         )
@@ -1468,7 +1192,7 @@ async def create_store_review(
 
 async def get_user_profile(
     user_id: str,
-) -> backend.server.v2.store.model.ProfileDetails | None:
+) -> store_model.ProfileDetails | None:
     logger.debug(f"Getting user profile for {user_id}")
 
     try:
@@ -1478,7 +1202,7 @@ async def get_user_profile(
 
         if not profile:
             return None
-        return backend.server.v2.store.model.ProfileDetails(
+        return store_model.ProfileDetails(
             name=profile.name,
             username=profile.username,
             description=profile.description,
@@ -1491,8 +1215,8 @@ async def get_user_profile(
 
 
 async def update_profile(
-    user_id: str, profile: backend.server.v2.store.model.Profile
-) -> backend.server.v2.store.model.CreatorDetails:
+    user_id: str, profile: store_model.Profile
+) -> store_model.CreatorDetails:
     """
     Update the store profile for a user or create a new one if it doesn't exist.
     Args:
@@ -1515,7 +1239,7 @@ async def update_profile(
             where={"userId": user_id}
         )
         if not existing_profile:
-            raise backend.server.v2.store.exceptions.ProfileNotFoundError(
+            raise store_exceptions.ProfileNotFoundError(
                 f"Profile not found for user {user_id}. This should not be possible."
             )
 
@@ -1551,7 +1275,7 @@ async def update_profile(
             logger.error(f"Failed to update profile for user {user_id}")
             raise DatabaseError("Failed to update profile")
 
-        return backend.server.v2.store.model.CreatorDetails(
+        return store_model.CreatorDetails(
             name=updated_profile.name,
             username=updated_profile.username,
             description=updated_profile.description,
@@ -1571,7 +1295,7 @@ async def get_my_agents(
     user_id: str,
     page: int = 1,
     page_size: int = 20,
-) -> backend.server.v2.store.model.MyAgentsResponse:
+) -> store_model.MyAgentsResponse:
     """Get the agents for the authenticated user"""
     logger.debug(f"Getting my agents for user {user_id}, page={page}")
 
@@ -1608,7 +1332,7 @@ async def get_my_agents(
         total_pages = (total + page_size - 1) // page_size
 
         my_agents = [
-            backend.server.v2.store.model.MyAgent(
+            store_model.MyAgent(
                 agent_id=graph.id,
                 agent_version=graph.version,
                 agent_name=graph.name or "",
@@ -1621,9 +1345,9 @@ async def get_my_agents(
             if (graph := library_agent.AgentGraph)
         ]
 
-        return backend.server.v2.store.model.MyAgentsResponse(
+        return store_model.MyAgentsResponse(
             agents=my_agents,
-            pagination=backend.server.v2.store.model.Pagination(
+            pagination=store_model.Pagination(
                 current_page=page,
                 total_items=total,
                 total_pages=total_pages,
@@ -1770,7 +1494,7 @@ async def review_store_submission(
     external_comments: str,
     internal_comments: str,
     reviewer_id: str,
-) -> backend.server.v2.store.model.StoreSubmission:
+) -> store_model.StoreSubmission:
     """Review a store listing submission as an admin."""
     try:
         store_listing_version = (
@@ -1983,7 +1707,7 @@ async def review_store_submission(
                 pass
 
         # Convert to Pydantic model for consistency
-        return backend.server.v2.store.model.StoreSubmission(
+        return store_model.StoreSubmission(
             agent_id=submission.agentGraphId,
             agent_version=submission.agentGraphVersion,
             name=submission.name,
@@ -2018,7 +1742,7 @@ async def get_admin_listings_with_versions(
     search_query: str | None = None,
     page: int = 1,
     page_size: int = 20,
-) -> backend.server.v2.store.model.StoreListingsWithVersionsResponse:
+) -> store_model.StoreListingsWithVersionsResponse:
     """
     Get store listings for admins with all their versions.
 
@@ -2117,10 +1841,10 @@ async def get_admin_listings_with_versions(
         # Convert to response models
         listings_with_versions = []
         for listing in listings:
-            versions: list[backend.server.v2.store.model.StoreSubmission] = []
+            versions: list[store_model.StoreSubmission] = []
             # If we have versions, turn them into StoreSubmission models
             for version in listing.Versions or []:
-                version_model = backend.server.v2.store.model.StoreSubmission(
+                version_model = store_model.StoreSubmission(
                     agent_id=version.agentGraphId,
                     agent_version=version.agentGraphVersion,
                     name=version.name,
@@ -2148,26 +1872,24 @@ async def get_admin_listings_with_versions(
 
             creator_email = listing.OwningUser.email if listing.OwningUser else None
 
-            listing_with_versions = (
-                backend.server.v2.store.model.StoreListingWithVersions(
-                    listing_id=listing.id,
-                    slug=listing.slug,
-                    agent_id=listing.agentGraphId,
-                    agent_version=listing.agentGraphVersion,
-                    active_version_id=listing.activeVersionId,
-                    has_approved_version=listing.hasApprovedVersion,
-                    creator_email=creator_email,
-                    latest_version=latest_version,
-                    versions=versions,
-                )
+            listing_with_versions = store_model.StoreListingWithVersions(
+                listing_id=listing.id,
+                slug=listing.slug,
+                agent_id=listing.agentGraphId,
+                agent_version=listing.agentGraphVersion,
+                active_version_id=listing.activeVersionId,
+                has_approved_version=listing.hasApprovedVersion,
+                creator_email=creator_email,
+                latest_version=latest_version,
+                versions=versions,
             )
 
             listings_with_versions.append(listing_with_versions)
 
         logger.debug(f"Found {len(listings_with_versions)} listings for admin")
-        return backend.server.v2.store.model.StoreListingsWithVersionsResponse(
+        return store_model.StoreListingsWithVersionsResponse(
             listings=listings_with_versions,
-            pagination=backend.server.v2.store.model.Pagination(
+            pagination=store_model.Pagination(
                 current_page=page,
                 total_items=total,
                 total_pages=total_pages,
@@ -2177,9 +1899,9 @@ async def get_admin_listings_with_versions(
     except Exception as e:
         logger.error(f"Error fetching admin store listings: {e}")
         # Return empty response rather than exposing internal errors
-        return backend.server.v2.store.model.StoreListingsWithVersionsResponse(
+        return store_model.StoreListingsWithVersionsResponse(
             listings=[],
-            pagination=backend.server.v2.store.model.Pagination(
+            pagination=store_model.Pagination(
                 current_page=page,
                 total_items=0,
                 total_pages=0,

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

@@ -6,8 +6,8 @@ import prisma.models
 import pytest
 from prisma import Prisma
 
-import backend.server.v2.store.db as db
-from backend.server.v2.store.model import Profile
+from . import db
+from .model import Profile
 
 
 @pytest.fixture(autouse=True)
@@ -40,6 +40,8 @@ async def test_get_store_agents(mocker):
             runs=10,
             rating=4.5,
             versions=["1.0"],
+            agentGraphVersions=["1"],
+            agentGraphId="test-graph-id",
             updated_at=datetime.now(),
             is_available=False,
             useForOnboarding=False,
@@ -83,6 +85,8 @@ async def test_get_store_agent_details(mocker):
         runs=10,
         rating=4.5,
         versions=["1.0"],
+        agentGraphVersions=["1"],
+        agentGraphId="test-graph-id",
         updated_at=datetime.now(),
         is_available=False,
         useForOnboarding=False,
@@ -105,6 +109,8 @@ async def test_get_store_agent_details(mocker):
         runs=15,
         rating=4.8,
         versions=["1.0", "2.0"],
+        agentGraphVersions=["1", "2"],
+        agentGraphId="test-graph-id-active",
         updated_at=datetime.now(),
         is_available=True,
         useForOnboarding=False,
@@ -405,347 +411,3 @@ async def test_get_store_agents_search_category_array_injection():
     # Verify the query executed without error
     # Category should be parameterized, preventing SQL injection
     assert isinstance(result.agents, list)
-
-
-# Hybrid search tests (BM25 + vector + popularity with RRF ranking)
-
-
-@pytest.mark.asyncio(loop_scope="session")
-async def test_get_store_agents_hybrid_search_mocked(mocker):
-    """Test hybrid search uses embedding service and executes query safely."""
-    from backend.integrations.embeddings import EMBEDDING_DIMENSIONS
-
-    # Mock embedding service
-    mock_embedding = [0.1] * EMBEDDING_DIMENSIONS
-    mock_embedding_service = mocker.MagicMock()
-    mock_embedding_service.generate_embedding = mocker.AsyncMock(
-        return_value=mock_embedding
-    )
-    mocker.patch(
-        "backend.server.v2.store.db.get_embedding_service",
-        mocker.MagicMock(return_value=mock_embedding_service),
-    )
-
-    # Mock query_raw_with_schema to return empty results
-    mocker.patch(
-        "backend.server.v2.store.db.query_raw_with_schema",
-        mocker.AsyncMock(side_effect=[[], [{"count": 0}]]),
-    )
-
-    # Call function with search query
-    result = await db.get_store_agents(search_query="test query")
-
-    # Verify embedding service was called
-    mock_embedding_service.generate_embedding.assert_called_once_with("test query")
-
-    # Verify results
-    assert isinstance(result.agents, list)
-    assert len(result.agents) == 0
-
-
-@pytest.mark.asyncio(loop_scope="session")
-async def test_get_store_agents_hybrid_search_with_results(mocker):
-    """Test hybrid search returns properly formatted results with RRF scoring."""
-    from backend.integrations.embeddings import EMBEDDING_DIMENSIONS
-
-    # Mock embedding service
-    mock_embedding = [0.1] * EMBEDDING_DIMENSIONS
-    mock_embedding_service = mocker.MagicMock()
-    mock_embedding_service.generate_embedding = mocker.AsyncMock(
-        return_value=mock_embedding
-    )
-    mocker.patch(
-        "backend.server.v2.store.db.get_embedding_service",
-        mocker.MagicMock(return_value=mock_embedding_service),
-    )
-
-    # Mock query results (hybrid search returns rrf_score instead of similarity)
-    mock_agents = [
-        {
-            "slug": "test-agent",
-            "agent_name": "Test Agent",
-            "agent_image": ["image.jpg"],
-            "creator_username": "creator",
-            "creator_avatar": "avatar.jpg",
-            "sub_heading": "Test heading",
-            "description": "Test description",
-            "runs": 10,
-            "rating": 4.5,
-            "categories": ["test"],
-            "featured": False,
-            "is_available": True,
-            "updated_at": datetime.now(),
-            "rrf_score": 0.048,  # RRF score from combined rankings
-        }
-    ]
-    mock_count = [{"count": 1}]
-
-    mocker.patch(
-        "backend.server.v2.store.db.query_raw_with_schema",
-        mocker.AsyncMock(side_effect=[mock_agents, mock_count]),
-    )
-
-    # Call function with search query
-    result = await db.get_store_agents(search_query="test query")
-
-    # Verify results
-    assert len(result.agents) == 1
-    assert result.agents[0].slug == "test-agent"
-    assert result.agents[0].agent_name == "Test Agent"
-    assert result.pagination.total_items == 1
-
-
-@pytest.mark.asyncio(loop_scope="session")
-async def test_get_store_agents_hybrid_search_with_filters(mocker):
-    """Test hybrid search works correctly with additional filters."""
-    from backend.integrations.embeddings import EMBEDDING_DIMENSIONS
-
-    # Mock embedding service
-    mock_embedding = [0.1] * EMBEDDING_DIMENSIONS
-    mock_embedding_service = mocker.MagicMock()
-    mock_embedding_service.generate_embedding = mocker.AsyncMock(
-        return_value=mock_embedding
-    )
-    mocker.patch(
-        "backend.server.v2.store.db.get_embedding_service",
-        mocker.MagicMock(return_value=mock_embedding_service),
-    )
-
-    # Mock query_raw_with_schema
-    mock_query = mocker.patch(
-        "backend.server.v2.store.db.query_raw_with_schema",
-        mocker.AsyncMock(side_effect=[[], [{"count": 0}]]),
-    )
-
-    # Call function with search query and filters
-    await db.get_store_agents(
-        search_query="test query",
-        featured=True,
-        creators=["creator1", "creator2"],
-        category="AI",
-    )
-
-    # Verify query was called with parameterized values
-    # First call is the main query, second is count
-    assert mock_query.call_count == 2
-
-    # Check that the SQL query includes proper parameterization
-    first_call_args = mock_query.call_args_list[0]
-    sql_query = first_call_args[0][0]
-
-    # Verify key elements of hybrid search query
-    assert "embedding <=> $1::vector" in sql_query  # Vector search
-    assert "ts_rank_cd" in sql_query  # BM25 search
-    assert "rrf_score" in sql_query  # RRF ranking
-    assert "featured = true" in sql_query
-    assert "creator_username = ANY($" in sql_query
-    assert "= ANY(categories)" in sql_query
-
-
-@pytest.mark.asyncio(loop_scope="session")
-async def test_get_store_agents_hybrid_search_strict_filter_mode(mocker):
-    """Test hybrid search with strict filter mode requires both BM25 and vector matches."""
-    from backend.integrations.embeddings import EMBEDDING_DIMENSIONS
-
-    # Mock embedding service
-    mock_embedding = [0.1] * EMBEDDING_DIMENSIONS
-    mock_embedding_service = mocker.MagicMock()
-    mock_embedding_service.generate_embedding = mocker.AsyncMock(
-        return_value=mock_embedding
-    )
-    mocker.patch(
-        "backend.server.v2.store.db.get_embedding_service",
-        mocker.MagicMock(return_value=mock_embedding_service),
-    )
-
-    # Mock query_raw_with_schema
-    mock_query = mocker.patch(
-        "backend.server.v2.store.db.query_raw_with_schema",
-        mocker.AsyncMock(side_effect=[[], [{"count": 0}]]),
-    )
-
-    # Call function with strict filter mode
-    await db.get_store_agents(search_query="test query", filter_mode="strict")
-
-    # Check that the SQL query includes strict filtering conditions
-    first_call_args = mock_query.call_args_list[0]
-    sql_query = first_call_args[0][0]
-
-    # Strict mode requires both embedding AND search to be present
-    assert "embedding IS NOT NULL" in sql_query
-    assert "search IS NOT NULL" in sql_query
-    # Strict score filter requires both thresholds to be met
-    assert "bm25_score >=" in sql_query
-    assert "AND vector_score >=" in sql_query
-
-
-@pytest.mark.asyncio(loop_scope="session")
-async def test_get_store_agents_hybrid_search_permissive_filter_mode(mocker):
-    """Test hybrid search with permissive filter mode requires either BM25 or vector match."""
-    from backend.integrations.embeddings import EMBEDDING_DIMENSIONS
-
-    # Mock embedding service
-    mock_embedding = [0.1] * EMBEDDING_DIMENSIONS
-    mock_embedding_service = mocker.MagicMock()
-    mock_embedding_service.generate_embedding = mocker.AsyncMock(
-        return_value=mock_embedding
-    )
-    mocker.patch(
-        "backend.server.v2.store.db.get_embedding_service",
-        mocker.MagicMock(return_value=mock_embedding_service),
-    )
-
-    # Mock query_raw_with_schema
-    mock_query = mocker.patch(
-        "backend.server.v2.store.db.query_raw_with_schema",
-        mocker.AsyncMock(side_effect=[[], [{"count": 0}]]),
-    )
-
-    # Call function with permissive filter mode
-    await db.get_store_agents(search_query="test query", filter_mode="permissive")
-
-    # Check that the SQL query includes permissive filtering conditions
-    first_call_args = mock_query.call_args_list[0]
-    sql_query = first_call_args[0][0]
-
-    # Permissive mode requires at least one signal
-    assert "(embedding IS NOT NULL OR search IS NOT NULL)" in sql_query
-    # Permissive score filter requires either threshold to be met
-    assert "OR vector_score >=" in sql_query
-
-
-@pytest.mark.asyncio(loop_scope="session")
-async def test_get_store_agents_hybrid_search_combined_filter_mode(mocker):
-    """Test hybrid search with combined filter mode (default) filters by RRF score."""
-    from backend.integrations.embeddings import EMBEDDING_DIMENSIONS
-
-    # Mock embedding service
-    mock_embedding = [0.1] * EMBEDDING_DIMENSIONS
-    mock_embedding_service = mocker.MagicMock()
-    mock_embedding_service.generate_embedding = mocker.AsyncMock(
-        return_value=mock_embedding
-    )
-    mocker.patch(
-        "backend.server.v2.store.db.get_embedding_service",
-        mocker.MagicMock(return_value=mock_embedding_service),
-    )
-
-    # Mock query_raw_with_schema
-    mock_query = mocker.patch(
-        "backend.server.v2.store.db.query_raw_with_schema",
-        mocker.AsyncMock(side_effect=[[], [{"count": 0}]]),
-    )
-
-    # Call function with combined filter mode (default)
-    await db.get_store_agents(search_query="test query", filter_mode="combined")
-
-    # Check that the SQL query includes combined filtering
-    first_call_args = mock_query.call_args_list[0]
-    sql_query = first_call_args[0][0]
-
-    # Combined mode requires at least one signal
-    assert "(embedding IS NOT NULL OR search IS NOT NULL)" in sql_query
-    # Combined mode uses "1=1" as pre-filter (no individual score filtering)
-    # But applies RRF score threshold to filter irrelevant results
-    assert "rrf_score" in sql_query
-    assert "rrf_score >=" in sql_query  # RRF threshold filter applied
-
-
-@pytest.mark.asyncio(loop_scope="session")
-async def test_generate_and_store_embedding_success(mocker):
-    """Test that embedding generation and storage works correctly."""
-    from backend.integrations.embeddings import EMBEDDING_DIMENSIONS
-
-    # Mock embedding service
-    mock_embedding = [0.1] * EMBEDDING_DIMENSIONS
-    mock_embedding_service = mocker.MagicMock()
-    mock_embedding_service.generate_embedding = mocker.AsyncMock(
-        return_value=mock_embedding
-    )
-    mocker.patch(
-        "backend.server.v2.store.db.get_embedding_service",
-        mocker.MagicMock(return_value=mock_embedding_service),
-    )
-
-    # Mock query_raw_with_schema
-    mock_query = mocker.patch(
-        "backend.server.v2.store.db.query_raw_with_schema",
-        mocker.AsyncMock(return_value=[]),
-    )
-
-    # Call the internal function
-    await db._generate_and_store_embedding(
-        store_listing_version_id="version-123",
-        name="Test Agent",
-        sub_heading="A test agent",
-        description="Does testing",
-    )
-
-    # Verify embedding service was called with combined text
-    mock_embedding_service.generate_embedding.assert_called_once_with(
-        "Test Agent A test agent Does testing"
-    )
-
-    # Verify database update was called
-    mock_query.assert_called_once()
-    call_args = mock_query.call_args
-    assert "UPDATE" in call_args[0][0]
-    assert "embedding = $1::vector" in call_args[0][0]
-    assert call_args[0][2] == "version-123"
-
-
-@pytest.mark.asyncio(loop_scope="session")
-async def test_generate_and_store_embedding_empty_text(mocker):
-    """Test that embedding is not generated for empty text."""
-    # Mock embedding service
-    mock_embedding_service = mocker.MagicMock()
-    mock_embedding_service.generate_embedding = mocker.AsyncMock()
-    mocker.patch(
-        "backend.server.v2.store.db.get_embedding_service",
-        mocker.MagicMock(return_value=mock_embedding_service),
-    )
-
-    # Mock query_raw_with_schema
-    mock_query = mocker.patch(
-        "backend.server.v2.store.db.query_raw_with_schema",
-        mocker.AsyncMock(return_value=[]),
-    )
-
-    # Call with empty fields
-    await db._generate_and_store_embedding(
-        store_listing_version_id="version-123",
-        name="",
-        sub_heading="",
-        description="",
-    )
-
-    # Verify embedding service was NOT called
-    mock_embedding_service.generate_embedding.assert_not_called()
-
-    # Verify database was NOT updated
-    mock_query.assert_not_called()
-
-
-@pytest.mark.asyncio(loop_scope="session")
-async def test_generate_and_store_embedding_handles_error(mocker):
-    """Test that embedding generation errors don't crash the operation."""
-    # Mock embedding service to raise an error
-    mock_embedding_service = mocker.MagicMock()
-    mock_embedding_service.generate_embedding = mocker.AsyncMock(
-        side_effect=Exception("API error")
-    )
-    mocker.patch(
-        "backend.server.v2.store.db.get_embedding_service",
-        mocker.MagicMock(return_value=mock_embedding_service),
-    )
-
-    # Call should not raise - errors are logged but not propagated
-    await db._generate_and_store_embedding(
-        store_listing_version_id="version-123",
-        name="Test Agent",
-        sub_heading="A test agent",
-        description="Does testing",
-    )
-
-    # Verify embedding service was called (and failed)
-    mock_embedding_service.generate_embedding.assert_called_once()

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

@@ -5,11 +5,12 @@ import uuid
 import fastapi
 from gcloud.aio import storage as async_storage
 
-import backend.server.v2.store.exceptions
 from backend.util.exceptions import MissingConfigError
 from backend.util.settings import Settings
 from backend.util.virus_scanner import scan_content_safe
 
+from . import exceptions as store_exceptions
+
 logger = logging.getLogger(__name__)
 
 ALLOWED_IMAGE_TYPES = {"image/jpeg", "image/png", "image/gif", "image/webp"}
@@ -68,61 +69,55 @@ async def upload_media(
         await file.seek(0)  # Reset file pointer
     except Exception as e:
         logger.error(f"Error reading file content: {str(e)}")
-        raise backend.server.v2.store.exceptions.FileReadError(
-            "Failed to read file content"
-        ) from e
+        raise store_exceptions.FileReadError("Failed to read file content") from e
 
     # Validate file signature/magic bytes
     if file.content_type in ALLOWED_IMAGE_TYPES:
         # Check image file signatures
         if content.startswith(b"\xff\xd8\xff"):  # JPEG
             if file.content_type != "image/jpeg":
-                raise backend.server.v2.store.exceptions.InvalidFileTypeError(
+                raise store_exceptions.InvalidFileTypeError(
                     "File signature does not match content type"
                 )
         elif content.startswith(b"\x89PNG\r\n\x1a\n"):  # PNG
             if file.content_type != "image/png":
-                raise backend.server.v2.store.exceptions.InvalidFileTypeError(
+                raise store_exceptions.InvalidFileTypeError(
                     "File signature does not match content type"
                 )
         elif content.startswith(b"GIF87a") or content.startswith(b"GIF89a"):  # GIF
             if file.content_type != "image/gif":
-                raise backend.server.v2.store.exceptions.InvalidFileTypeError(
+                raise store_exceptions.InvalidFileTypeError(
                     "File signature does not match content type"
                 )
         elif content.startswith(b"RIFF") and content[8:12] == b"WEBP":  # WebP
             if file.content_type != "image/webp":
-                raise backend.server.v2.store.exceptions.InvalidFileTypeError(
+                raise store_exceptions.InvalidFileTypeError(
                     "File signature does not match content type"
                 )
         else:
-            raise backend.server.v2.store.exceptions.InvalidFileTypeError(
-                "Invalid image file signature"
-            )
+            raise store_exceptions.InvalidFileTypeError("Invalid image file signature")
 
     elif file.content_type in ALLOWED_VIDEO_TYPES:
         # Check video file signatures
         if content.startswith(b"\x00\x00\x00") and (content[4:8] == b"ftyp"):  # MP4
             if file.content_type != "video/mp4":
-                raise backend.server.v2.store.exceptions.InvalidFileTypeError(
+                raise store_exceptions.InvalidFileTypeError(
                     "File signature does not match content type"
                 )
         elif content.startswith(b"\x1a\x45\xdf\xa3"):  # WebM
             if file.content_type != "video/webm":
-                raise backend.server.v2.store.exceptions.InvalidFileTypeError(
+                raise store_exceptions.InvalidFileTypeError(
                     "File signature does not match content type"
                 )
         else:
-            raise backend.server.v2.store.exceptions.InvalidFileTypeError(
-                "Invalid video file signature"
-            )
+            raise store_exceptions.InvalidFileTypeError("Invalid video file signature")
 
     settings = Settings()
 
     # Check required settings first before doing any file processing
     if not settings.config.media_gcs_bucket_name:
         logger.error("Missing GCS bucket name setting")
-        raise backend.server.v2.store.exceptions.StorageConfigError(
+        raise store_exceptions.StorageConfigError(
             "Missing storage bucket configuration"
         )
 
@@ -137,7 +132,7 @@ async def upload_media(
             and content_type not in ALLOWED_VIDEO_TYPES
         ):
             logger.warning(f"Invalid file type attempted: {content_type}")
-            raise backend.server.v2.store.exceptions.InvalidFileTypeError(
+            raise store_exceptions.InvalidFileTypeError(
                 f"File type not supported. Must be jpeg, png, gif, webp, mp4 or webm. Content type: {content_type}"
             )
 
@@ -150,16 +145,14 @@ async def upload_media(
                 file_size += len(chunk)
                 if file_size > MAX_FILE_SIZE:
                     logger.warning(f"File size too large: {file_size} bytes")
-                    raise backend.server.v2.store.exceptions.FileSizeTooLargeError(
+                    raise store_exceptions.FileSizeTooLargeError(
                         "File too large. Maximum size is 50MB"
                     )
-        except backend.server.v2.store.exceptions.FileSizeTooLargeError:
+        except store_exceptions.FileSizeTooLargeError:
             raise
         except Exception as e:
             logger.error(f"Error reading file chunks: {str(e)}")
-            raise backend.server.v2.store.exceptions.FileReadError(
-                "Failed to read uploaded file"
-            ) from e
+            raise store_exceptions.FileReadError("Failed to read uploaded file") from e
 
         # Reset file pointer
         await file.seek(0)
@@ -198,14 +191,14 @@ async def upload_media(
 
         except Exception as e:
             logger.error(f"GCS storage error: {str(e)}")
-            raise backend.server.v2.store.exceptions.StorageUploadError(
+            raise store_exceptions.StorageUploadError(
                 "Failed to upload file to storage"
             ) from e
 
-    except backend.server.v2.store.exceptions.MediaUploadError:
+    except store_exceptions.MediaUploadError:
         raise
     except Exception as e:
         logger.exception("Unexpected error in upload_media")
-        raise backend.server.v2.store.exceptions.MediaUploadError(
+        raise store_exceptions.MediaUploadError(
             "Unexpected error during media upload"
         ) from e

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

@@ -6,17 +6,18 @@ import fastapi
 import pytest
 import starlette.datastructures
 
-import backend.server.v2.store.exceptions
-import backend.server.v2.store.media
 from backend.util.settings import Settings
 
+from . import exceptions as store_exceptions
+from . import media as store_media
+
 
 @pytest.fixture
 def mock_settings(monkeypatch):
     settings = Settings()
     settings.config.media_gcs_bucket_name = "test-bucket"
     settings.config.google_application_credentials = "test-credentials"
-    monkeypatch.setattr("backend.server.v2.store.media.Settings", lambda: settings)
+    monkeypatch.setattr("backend.api.features.store.media.Settings", lambda: settings)
     return settings
 
 
@@ -32,12 +33,13 @@ def mock_storage_client(mocker):
 
     # Mock the constructor to return our mock client
     mocker.patch(
-        "backend.server.v2.store.media.async_storage.Storage", return_value=mock_client
+        "backend.api.features.store.media.async_storage.Storage",
+        return_value=mock_client,
     )
 
     # Mock virus scanner to avoid actual scanning
     mocker.patch(
-        "backend.server.v2.store.media.scan_content_safe", new_callable=AsyncMock
+        "backend.api.features.store.media.scan_content_safe", new_callable=AsyncMock
     )
 
     return mock_client
@@ -53,7 +55,7 @@ async def test_upload_media_success(mock_settings, mock_storage_client):
         headers=starlette.datastructures.Headers({"content-type": "image/jpeg"}),
     )
 
-    result = await backend.server.v2.store.media.upload_media("test-user", test_file)
+    result = await store_media.upload_media("test-user", test_file)
 
     assert result.startswith(
         "https://storage.googleapis.com/test-bucket/users/test-user/images/"
@@ -69,8 +71,8 @@ async def test_upload_media_invalid_type(mock_settings, mock_storage_client):
         headers=starlette.datastructures.Headers({"content-type": "text/plain"}),
     )
 
-    with pytest.raises(backend.server.v2.store.exceptions.InvalidFileTypeError):
-        await backend.server.v2.store.media.upload_media("test-user", test_file)
+    with pytest.raises(store_exceptions.InvalidFileTypeError):
+        await store_media.upload_media("test-user", test_file)
 
     mock_storage_client.upload.assert_not_called()
 
@@ -79,7 +81,7 @@ async def test_upload_media_missing_credentials(monkeypatch):
     settings = Settings()
     settings.config.media_gcs_bucket_name = ""
     settings.config.google_application_credentials = ""
-    monkeypatch.setattr("backend.server.v2.store.media.Settings", lambda: settings)
+    monkeypatch.setattr("backend.api.features.store.media.Settings", lambda: settings)
 
     test_file = fastapi.UploadFile(
         filename="laptop.jpeg",
@@ -87,8 +89,8 @@ async def test_upload_media_missing_credentials(monkeypatch):
         headers=starlette.datastructures.Headers({"content-type": "image/jpeg"}),
     )
 
-    with pytest.raises(backend.server.v2.store.exceptions.StorageConfigError):
-        await backend.server.v2.store.media.upload_media("test-user", test_file)
+    with pytest.raises(store_exceptions.StorageConfigError):
+        await store_media.upload_media("test-user", test_file)
 
 
 async def test_upload_media_video_type(mock_settings, mock_storage_client):
@@ -98,7 +100,7 @@ async def test_upload_media_video_type(mock_settings, mock_storage_client):
         headers=starlette.datastructures.Headers({"content-type": "video/mp4"}),
     )
 
-    result = await backend.server.v2.store.media.upload_media("test-user", test_file)
+    result = await store_media.upload_media("test-user", test_file)
 
     assert result.startswith(
         "https://storage.googleapis.com/test-bucket/users/test-user/videos/"
@@ -117,8 +119,8 @@ async def test_upload_media_file_too_large(mock_settings, mock_storage_client):
         headers=starlette.datastructures.Headers({"content-type": "image/jpeg"}),
     )
 
-    with pytest.raises(backend.server.v2.store.exceptions.FileSizeTooLargeError):
-        await backend.server.v2.store.media.upload_media("test-user", test_file)
+    with pytest.raises(store_exceptions.FileSizeTooLargeError):
+        await store_media.upload_media("test-user", test_file)
 
 
 async def test_upload_media_file_read_error(mock_settings, mock_storage_client):
@@ -129,8 +131,8 @@ async def test_upload_media_file_read_error(mock_settings, mock_storage_client):
     )
     test_file.read = unittest.mock.AsyncMock(side_effect=Exception("Read error"))
 
-    with pytest.raises(backend.server.v2.store.exceptions.FileReadError):
-        await backend.server.v2.store.media.upload_media("test-user", test_file)
+    with pytest.raises(store_exceptions.FileReadError):
+        await store_media.upload_media("test-user", test_file)
 
 
 async def test_upload_media_png_success(mock_settings, mock_storage_client):
@@ -140,7 +142,7 @@ async def test_upload_media_png_success(mock_settings, mock_storage_client):
         headers=starlette.datastructures.Headers({"content-type": "image/png"}),
     )
 
-    result = await backend.server.v2.store.media.upload_media("test-user", test_file)
+    result = await store_media.upload_media("test-user", test_file)
     assert result.startswith(
         "https://storage.googleapis.com/test-bucket/users/test-user/images/"
     )
@@ -154,7 +156,7 @@ async def test_upload_media_gif_success(mock_settings, mock_storage_client):
         headers=starlette.datastructures.Headers({"content-type": "image/gif"}),
     )
 
-    result = await backend.server.v2.store.media.upload_media("test-user", test_file)
+    result = await store_media.upload_media("test-user", test_file)
     assert result.startswith(
         "https://storage.googleapis.com/test-bucket/users/test-user/images/"
     )
@@ -168,7 +170,7 @@ async def test_upload_media_webp_success(mock_settings, mock_storage_client):
         headers=starlette.datastructures.Headers({"content-type": "image/webp"}),
     )
 
-    result = await backend.server.v2.store.media.upload_media("test-user", test_file)
+    result = await store_media.upload_media("test-user", test_file)
     assert result.startswith(
         "https://storage.googleapis.com/test-bucket/users/test-user/images/"
     )
@@ -182,7 +184,7 @@ async def test_upload_media_webm_success(mock_settings, mock_storage_client):
         headers=starlette.datastructures.Headers({"content-type": "video/webm"}),
     )
 
-    result = await backend.server.v2.store.media.upload_media("test-user", test_file)
+    result = await store_media.upload_media("test-user", test_file)
     assert result.startswith(
         "https://storage.googleapis.com/test-bucket/users/test-user/videos/"
     )
@@ -196,8 +198,8 @@ async def test_upload_media_mismatched_signature(mock_settings, mock_storage_cli
         headers=starlette.datastructures.Headers({"content-type": "image/jpeg"}),
     )
 
-    with pytest.raises(backend.server.v2.store.exceptions.InvalidFileTypeError):
-        await backend.server.v2.store.media.upload_media("test-user", test_file)
+    with pytest.raises(store_exceptions.InvalidFileTypeError):
+        await store_media.upload_media("test-user", test_file)
 
 
 async def test_upload_media_invalid_signature(mock_settings, mock_storage_client):
@@ -207,5 +209,5 @@ async def test_upload_media_invalid_signature(mock_settings, mock_storage_client
         headers=starlette.datastructures.Headers({"content-type": "image/jpeg"}),
     )
 
-    with pytest.raises(backend.server.v2.store.exceptions.InvalidFileTypeError):
-        await backend.server.v2.store.media.upload_media("test-user", test_file)
+    with pytest.raises(store_exceptions.InvalidFileTypeError):
+        await store_media.upload_media("test-user", test_file)

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

@@ -1,5 +1,4 @@
 import datetime
-from enum import Enum
 from typing import List
 
 import prisma.enums
@@ -8,17 +7,10 @@ import pydantic
 from backend.util.models import Pagination
 
 
-class SearchFilterMode(str, Enum):
-    """How to combine BM25 and vector search results for filtering.
-
-    - STRICT: Must pass BOTH BM25 AND vector similarity thresholds
-    - PERMISSIVE: Must pass EITHER BM25 OR vector similarity threshold
-    - COMBINED: No pre-filtering, only the combined RRF score matters (default)
-    """
-
-    STRICT = "strict"
-    PERMISSIVE = "permissive"
-    COMBINED = "combined"
+class ChangelogEntry(pydantic.BaseModel):
+    version: str
+    changes_summary: str
+    date: datetime.datetime
 
 
 class MyAgent(pydantic.BaseModel):
@@ -69,12 +61,17 @@ class StoreAgentDetails(pydantic.BaseModel):
     runs: int
     rating: float
     versions: list[str]
+    agentGraphVersions: list[str]
+    agentGraphId: str
     last_updated: datetime.datetime
     recommended_schedule_cron: str | None = None
 
     active_version_id: str | None = None
     has_approved_version: bool = False
 
+    # Optional changelog data when include_changelog=True
+    changelog: list[ChangelogEntry] | None = None
+
 
 class Creator(pydantic.BaseModel):
     name: str

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

@@ -2,11 +2,11 @@ import datetime
 
 import prisma.enums
 
-import backend.server.v2.store.model
+from . import model as store_model
 
 
 def test_pagination():
-    pagination = backend.server.v2.store.model.Pagination(
+    pagination = store_model.Pagination(
         total_items=100, total_pages=5, current_page=2, page_size=20
     )
     assert pagination.total_items == 100
@@ -16,7 +16,7 @@ def test_pagination():
 
 
 def test_store_agent():
-    agent = backend.server.v2.store.model.StoreAgent(
+    agent = store_model.StoreAgent(
         slug="test-agent",
         agent_name="Test Agent",
         agent_image="test.jpg",
@@ -34,9 +34,9 @@ def test_store_agent():
 
 
 def test_store_agents_response():
-    response = backend.server.v2.store.model.StoreAgentsResponse(
+    response = store_model.StoreAgentsResponse(
         agents=[
-            backend.server.v2.store.model.StoreAgent(
+            store_model.StoreAgent(
                 slug="test-agent",
                 agent_name="Test Agent",
                 agent_image="test.jpg",
@@ -48,7 +48,7 @@ def test_store_agents_response():
                 rating=4.5,
             )
         ],
-        pagination=backend.server.v2.store.model.Pagination(
+        pagination=store_model.Pagination(
             total_items=1, total_pages=1, current_page=1, page_size=20
         ),
     )
@@ -57,7 +57,7 @@ def test_store_agents_response():
 
 
 def test_store_agent_details():
-    details = backend.server.v2.store.model.StoreAgentDetails(
+    details = store_model.StoreAgentDetails(
         store_listing_version_id="version123",
         slug="test-agent",
         agent_name="Test Agent",
@@ -72,6 +72,8 @@ def test_store_agent_details():
         runs=50,
         rating=4.5,
         versions=["1.0", "2.0"],
+        agentGraphVersions=["1", "2"],
+        agentGraphId="test-graph-id",
         last_updated=datetime.datetime.now(),
     )
     assert details.slug == "test-agent"
@@ -81,7 +83,7 @@ def test_store_agent_details():
 
 
 def test_creator():
-    creator = backend.server.v2.store.model.Creator(
+    creator = store_model.Creator(
         agent_rating=4.8,
         agent_runs=1000,
         name="Test Creator",
@@ -96,9 +98,9 @@ def test_creator():
 
 
 def test_creators_response():
-    response = backend.server.v2.store.model.CreatorsResponse(
+    response = store_model.CreatorsResponse(
         creators=[
-            backend.server.v2.store.model.Creator(
+            store_model.Creator(
                 agent_rating=4.8,
                 agent_runs=1000,
                 name="Test Creator",
@@ -109,7 +111,7 @@ def test_creators_response():
                 is_featured=False,
             )
         ],
-        pagination=backend.server.v2.store.model.Pagination(
+        pagination=store_model.Pagination(
             total_items=1, total_pages=1, current_page=1, page_size=20
         ),
     )
@@ -118,7 +120,7 @@ def test_creators_response():
 
 
 def test_creator_details():
-    details = backend.server.v2.store.model.CreatorDetails(
+    details = store_model.CreatorDetails(
         name="Test Creator",
         username="creator1",
         description="Test description",
@@ -135,7 +137,7 @@ def test_creator_details():
 
 
 def test_store_submission():
-    submission = backend.server.v2.store.model.StoreSubmission(
+    submission = store_model.StoreSubmission(
         agent_id="agent123",
         agent_version=1,
         sub_heading="Test subheading",
@@ -154,9 +156,9 @@ def test_store_submission():
 
 
 def test_store_submissions_response():
-    response = backend.server.v2.store.model.StoreSubmissionsResponse(
+    response = store_model.StoreSubmissionsResponse(
         submissions=[
-            backend.server.v2.store.model.StoreSubmission(
+            store_model.StoreSubmission(
                 agent_id="agent123",
                 agent_version=1,
                 sub_heading="Test subheading",
@@ -170,7 +172,7 @@ def test_store_submissions_response():
                 rating=4.5,
             )
         ],
-        pagination=backend.server.v2.store.model.Pagination(
+        pagination=store_model.Pagination(
             total_items=1, total_pages=1, current_page=1, page_size=20
         ),
     )
@@ -179,7 +181,7 @@ def test_store_submissions_response():
 
 
 def test_store_submission_request():
-    request = backend.server.v2.store.model.StoreSubmissionRequest(
+    request = store_model.StoreSubmissionRequest(
         agent_id="agent123",
         agent_version=1,
         slug="test-agent",

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

@@ -9,14 +9,14 @@ import fastapi
 import fastapi.responses
 
 import backend.data.graph
-import backend.server.v2.store.cache as store_cache
-import backend.server.v2.store.db
-import backend.server.v2.store.exceptions
-import backend.server.v2.store.image_gen
-import backend.server.v2.store.media
-import backend.server.v2.store.model
 import backend.util.json
 
+from . import cache as store_cache
+from . import db as store_db
+from . import image_gen as store_image_gen
+from . import media as store_media
+from . import model as store_model
+
 logger = logging.getLogger(__name__)
 
 router = fastapi.APIRouter()
@@ -32,7 +32,7 @@ router = fastapi.APIRouter()
     summary="Get user profile",
     tags=["store", "private"],
     dependencies=[fastapi.Security(autogpt_libs.auth.requires_user)],
-    response_model=backend.server.v2.store.model.ProfileDetails,
+    response_model=store_model.ProfileDetails,
 )
 async def get_profile(
     user_id: str = fastapi.Security(autogpt_libs.auth.get_user_id),
@@ -41,7 +41,7 @@ async def get_profile(
     Get the profile details for the authenticated user.
     Cached for 1 hour per user.
     """
-    profile = await backend.server.v2.store.db.get_user_profile(user_id)
+    profile = await store_db.get_user_profile(user_id)
     if profile is None:
         return fastapi.responses.JSONResponse(
             status_code=404,
@@ -55,10 +55,10 @@ async def get_profile(
     summary="Update user profile",
     tags=["store", "private"],
     dependencies=[fastapi.Security(autogpt_libs.auth.requires_user)],
-    response_model=backend.server.v2.store.model.CreatorDetails,
+    response_model=store_model.CreatorDetails,
 )
 async def update_or_create_profile(
-    profile: backend.server.v2.store.model.Profile,
+    profile: store_model.Profile,
     user_id: str = fastapi.Security(autogpt_libs.auth.get_user_id),
 ):
     """
@@ -74,9 +74,7 @@ async def update_or_create_profile(
     Raises:
         HTTPException: If there is an error updating the profile
     """
-    updated_profile = await backend.server.v2.store.db.update_profile(
-        user_id=user_id, profile=profile
-    )
+    updated_profile = await store_db.update_profile(user_id=user_id, profile=profile)
     return updated_profile
 
 
@@ -89,7 +87,7 @@ async def update_or_create_profile(
     "/agents",
     summary="List store agents",
     tags=["store", "public"],
-    response_model=backend.server.v2.store.model.StoreAgentsResponse,
+    response_model=store_model.StoreAgentsResponse,
 )
 async def get_agents(
     featured: bool = False,
@@ -99,30 +97,18 @@ async def get_agents(
     category: str | None = None,
     page: int = 1,
     page_size: int = 20,
-    filter_mode: Literal["strict", "permissive", "combined"] = "permissive",
 ):
     """
     Get a paginated list of agents from the store with optional filtering and sorting.
 
-    When search_query is provided, uses hybrid search combining:
-    - BM25 full-text search (lexical matching)
-    - Vector semantic similarity (meaning-based matching)
-    - Popularity signal (run counts)
-
-    Results are ranked using Reciprocal Rank Fusion (RRF).
-
     Args:
         featured (bool, optional): Filter to only show featured agents. Defaults to False.
         creator (str | None, optional): Filter agents by creator username. Defaults to None.
         sorted_by (str | None, optional): Sort agents by "runs" or "rating". Defaults to None.
-        search_query (str | None, optional): Search agents by name, subheading and description.
+        search_query (str | None, optional): Search agents by name, subheading and description. Defaults to None.
         category (str | None, optional): Filter agents by category. Defaults to None.
         page (int, optional): Page number for pagination. Defaults to 1.
         page_size (int, optional): Number of agents per page. Defaults to 20.
-        filter_mode (str, optional): Controls result filtering when searching:
-            - "strict": Must match BOTH BM25 AND vector thresholds
-            - "permissive": Must match EITHER BM25 OR vector threshold
-            - "combined": No threshold filtering, rely on RRF score (default)
 
     Returns:
         StoreAgentsResponse: Paginated list of agents matching the filters
@@ -156,7 +142,6 @@ async def get_agents(
         category=category,
         page=page,
         page_size=page_size,
-        filter_mode=filter_mode,
     )
     return agents
 
@@ -165,9 +150,13 @@ async def get_agents(
     "/agents/{username}/{agent_name}",
     summary="Get specific agent",
     tags=["store", "public"],
-    response_model=backend.server.v2.store.model.StoreAgentDetails,
+    response_model=store_model.StoreAgentDetails,
 )
-async def get_agent(username: str, agent_name: str):
+async def get_agent(
+    username: str,
+    agent_name: str,
+    include_changelog: bool = fastapi.Query(default=False),
+):
     """
     This is only used on the AgentDetails Page.
 
@@ -177,7 +166,7 @@ async def get_agent(username: str, agent_name: str):
     # URL decode the agent name since it comes from the URL path
     agent_name = urllib.parse.unquote(agent_name).lower()
     agent = await store_cache._get_cached_agent_details(
-        username=username, agent_name=agent_name
+        username=username, agent_name=agent_name, include_changelog=include_changelog
     )
     return agent
 
@@ -188,13 +177,13 @@ async def get_agent(username: str, agent_name: str):
     tags=["store"],
     dependencies=[fastapi.Security(autogpt_libs.auth.requires_user)],
 )
-async def get_graph_meta_by_store_listing_version_id(store_listing_version_id: str):
+async def get_graph_meta_by_store_listing_version_id(
+    store_listing_version_id: str,
+) -> backend.data.graph.GraphMeta:
     """
     Get Agent Graph from Store Listing Version ID.
     """
-    graph = await backend.server.v2.store.db.get_available_graph(
-        store_listing_version_id
-    )
+    graph = await store_db.get_available_graph(store_listing_version_id)
     return graph
 
 
@@ -203,15 +192,13 @@ async def get_graph_meta_by_store_listing_version_id(store_listing_version_id: s
     summary="Get agent by version",
     tags=["store"],
     dependencies=[fastapi.Security(autogpt_libs.auth.requires_user)],
-    response_model=backend.server.v2.store.model.StoreAgentDetails,
+    response_model=store_model.StoreAgentDetails,
 )
 async def get_store_agent(store_listing_version_id: str):
     """
     Get Store Agent Details from Store Listing Version ID.
     """
-    agent = await backend.server.v2.store.db.get_store_agent_by_version_id(
-        store_listing_version_id
-    )
+    agent = await store_db.get_store_agent_by_version_id(store_listing_version_id)
 
     return agent
 
@@ -221,12 +208,12 @@ async def get_store_agent(store_listing_version_id: str):
     summary="Create agent review",
     tags=["store"],
     dependencies=[fastapi.Security(autogpt_libs.auth.requires_user)],
-    response_model=backend.server.v2.store.model.StoreReview,
+    response_model=store_model.StoreReview,
 )
 async def create_review(
     username: str,
     agent_name: str,
-    review: backend.server.v2.store.model.StoreReviewCreate,
+    review: store_model.StoreReviewCreate,
     user_id: str = fastapi.Security(autogpt_libs.auth.get_user_id),
 ):
     """
@@ -244,7 +231,7 @@ async def create_review(
     username = urllib.parse.unquote(username).lower()
     agent_name = urllib.parse.unquote(agent_name).lower()
     # Create the review
-    created_review = await backend.server.v2.store.db.create_store_review(
+    created_review = await store_db.create_store_review(
         user_id=user_id,
         store_listing_version_id=review.store_listing_version_id,
         score=review.score,
@@ -263,7 +250,7 @@ async def create_review(
     "/creators",
     summary="List store creators",
     tags=["store", "public"],
-    response_model=backend.server.v2.store.model.CreatorsResponse,
+    response_model=store_model.CreatorsResponse,
 )
 async def get_creators(
     featured: bool = False,
@@ -308,7 +295,7 @@ async def get_creators(
     "/creator/{username}",
     summary="Get creator details",
     tags=["store", "public"],
-    response_model=backend.server.v2.store.model.CreatorDetails,
+    response_model=store_model.CreatorDetails,
 )
 async def get_creator(
     username: str,
@@ -332,7 +319,7 @@ async def get_creator(
     summary="Get my agents",
     tags=["store", "private"],
     dependencies=[fastapi.Security(autogpt_libs.auth.requires_user)],
-    response_model=backend.server.v2.store.model.MyAgentsResponse,
+    response_model=store_model.MyAgentsResponse,
 )
 async def get_my_agents(
     user_id: str = fastapi.Security(autogpt_libs.auth.get_user_id),
@@ -342,9 +329,7 @@ async def get_my_agents(
     """
     Get user's own agents.
     """
-    agents = await backend.server.v2.store.db.get_my_agents(
-        user_id, page=page, page_size=page_size
-    )
+    agents = await store_db.get_my_agents(user_id, page=page, page_size=page_size)
     return agents
 
 
@@ -369,7 +354,7 @@ async def delete_submission(
     Returns:
         bool: True if the submission was successfully deleted, False otherwise
     """
-    result = await backend.server.v2.store.db.delete_store_submission(
+    result = await store_db.delete_store_submission(
         user_id=user_id,
         submission_id=submission_id,
     )
@@ -382,7 +367,7 @@ async def delete_submission(
     summary="List my submissions",
     tags=["store", "private"],
     dependencies=[fastapi.Security(autogpt_libs.auth.requires_user)],
-    response_model=backend.server.v2.store.model.StoreSubmissionsResponse,
+    response_model=store_model.StoreSubmissionsResponse,
 )
 async def get_submissions(
     user_id: str = fastapi.Security(autogpt_libs.auth.get_user_id),
@@ -412,7 +397,7 @@ async def get_submissions(
         raise fastapi.HTTPException(
             status_code=422, detail="Page size must be greater than 0"
         )
-    listings = await backend.server.v2.store.db.get_store_submissions(
+    listings = await store_db.get_store_submissions(
         user_id=user_id,
         page=page,
         page_size=page_size,
@@ -425,10 +410,10 @@ async def get_submissions(
     summary="Create store submission",
     tags=["store", "private"],
     dependencies=[fastapi.Security(autogpt_libs.auth.requires_user)],
-    response_model=backend.server.v2.store.model.StoreSubmission,
+    response_model=store_model.StoreSubmission,
 )
 async def create_submission(
-    submission_request: backend.server.v2.store.model.StoreSubmissionRequest,
+    submission_request: store_model.StoreSubmissionRequest,
     user_id: str = fastapi.Security(autogpt_libs.auth.get_user_id),
 ):
     """
@@ -444,7 +429,7 @@ async def create_submission(
     Raises:
         HTTPException: If there is an error creating the submission
     """
-    result = await backend.server.v2.store.db.create_store_submission(
+    result = await store_db.create_store_submission(
         user_id=user_id,
         agent_id=submission_request.agent_id,
         agent_version=submission_request.agent_version,
@@ -469,11 +454,11 @@ async def create_submission(
     summary="Edit store submission",
     tags=["store", "private"],
     dependencies=[fastapi.Security(autogpt_libs.auth.requires_user)],
-    response_model=backend.server.v2.store.model.StoreSubmission,
+    response_model=store_model.StoreSubmission,
 )
 async def edit_submission(
     store_listing_version_id: str,
-    submission_request: backend.server.v2.store.model.StoreSubmissionEditRequest,
+    submission_request: store_model.StoreSubmissionEditRequest,
     user_id: str = fastapi.Security(autogpt_libs.auth.get_user_id),
 ):
     """
@@ -490,7 +475,7 @@ async def edit_submission(
     Raises:
         HTTPException: If there is an error editing the submission
     """
-    result = await backend.server.v2.store.db.edit_store_submission(
+    result = await store_db.edit_store_submission(
         user_id=user_id,
         store_listing_version_id=store_listing_version_id,
         name=submission_request.name,
@@ -531,9 +516,7 @@ async def upload_submission_media(
     Raises:
         HTTPException: If there is an error uploading the media
     """
-    media_url = await backend.server.v2.store.media.upload_media(
-        user_id=user_id, file=file
-    )
+    media_url = await store_media.upload_media(user_id=user_id, file=file)
     return media_url
 
 
@@ -568,14 +551,12 @@ async def generate_image(
     # Use .jpeg here since we are generating JPEG images
     filename = f"agent_{agent_id}.jpeg"
 
-    existing_url = await backend.server.v2.store.media.check_media_exists(
-        user_id, filename
-    )
+    existing_url = await store_media.check_media_exists(user_id, filename)
     if existing_url:
         logger.info(f"Using existing image for agent {agent_id}")
         return fastapi.responses.JSONResponse(content={"image_url": existing_url})
     # Generate agent image as JPEG
-    image = await backend.server.v2.store.image_gen.generate_agent_image(agent=agent)
+    image = await store_image_gen.generate_agent_image(agent=agent)
 
     # Create UploadFile with the correct filename and content_type
     image_file = fastapi.UploadFile(
@@ -583,7 +564,7 @@ async def generate_image(
         filename=filename,
     )
 
-    image_url = await backend.server.v2.store.media.upload_media(
+    image_url = await store_media.upload_media(
         user_id=user_id, file=image_file, use_file_name=True
     )
 
@@ -612,7 +593,7 @@ async def download_agent_file(
     Raises:
         HTTPException: If the agent is not found or an unexpected error occurs.
     """
-    graph_data = await backend.server.v2.store.db.get_agent(store_listing_version_id)
+    graph_data = await store_db.get_agent(store_listing_version_id)
     file_name = f"agent_{graph_data.id}_v{graph_data.version or 'latest'}.json"
 
     # Sending graph as a stream (similar to marketplace v1)

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

@@ -8,15 +8,15 @@ import pytest
 import pytest_mock
 from pytest_snapshot.plugin import Snapshot
 
-import backend.server.v2.store.model
-import backend.server.v2.store.routes
+from . import model as store_model
+from . import routes as store_routes
 
 # Using a fixed timestamp for reproducible tests
 # 2023 date is intentionally used to ensure tests work regardless of current year
 FIXED_NOW = datetime.datetime(2023, 1, 1, 0, 0, 0)
 
 app = fastapi.FastAPI()
-app.include_router(backend.server.v2.store.routes.router)
+app.include_router(store_routes.router)
 
 client = fastapi.testclient.TestClient(app)
 
@@ -35,23 +35,21 @@ def test_get_agents_defaults(
     mocker: pytest_mock.MockFixture,
     snapshot: Snapshot,
 ) -> None:
-    mocked_value = backend.server.v2.store.model.StoreAgentsResponse(
+    mocked_value = store_model.StoreAgentsResponse(
         agents=[],
-        pagination=backend.server.v2.store.model.Pagination(
+        pagination=store_model.Pagination(
             current_page=0,
             total_items=0,
             total_pages=0,
             page_size=10,
         ),
     )
-    mock_db_call = mocker.patch("backend.server.v2.store.db.get_store_agents")
+    mock_db_call = mocker.patch("backend.api.features.store.db.get_store_agents")
     mock_db_call.return_value = mocked_value
     response = client.get("/agents")
     assert response.status_code == 200
 
-    data = backend.server.v2.store.model.StoreAgentsResponse.model_validate(
-        response.json()
-    )
+    data = store_model.StoreAgentsResponse.model_validate(response.json())
     assert data.pagination.total_pages == 0
     assert data.agents == []
 
@@ -65,7 +63,6 @@ def test_get_agents_defaults(
         category=None,
         page=1,
         page_size=20,
-        filter_mode="permissive",
     )
 
 
@@ -73,9 +70,9 @@ def test_get_agents_featured(
     mocker: pytest_mock.MockFixture,
     snapshot: Snapshot,
 ) -> None:
-    mocked_value = backend.server.v2.store.model.StoreAgentsResponse(
+    mocked_value = store_model.StoreAgentsResponse(
         agents=[
-            backend.server.v2.store.model.StoreAgent(
+            store_model.StoreAgent(
                 slug="featured-agent",
                 agent_name="Featured Agent",
                 agent_image="featured.jpg",
@@ -87,20 +84,18 @@ def test_get_agents_featured(
                 rating=4.5,
             )
         ],
-        pagination=backend.server.v2.store.model.Pagination(
+        pagination=store_model.Pagination(
             current_page=1,
             total_items=1,
             total_pages=1,
             page_size=20,
         ),
     )
-    mock_db_call = mocker.patch("backend.server.v2.store.db.get_store_agents")
+    mock_db_call = mocker.patch("backend.api.features.store.db.get_store_agents")
     mock_db_call.return_value = mocked_value
     response = client.get("/agents?featured=true")
     assert response.status_code == 200
-    data = backend.server.v2.store.model.StoreAgentsResponse.model_validate(
-        response.json()
-    )
+    data = store_model.StoreAgentsResponse.model_validate(response.json())
     assert len(data.agents) == 1
     assert data.agents[0].slug == "featured-agent"
     snapshot.snapshot_dir = "snapshots"
@@ -113,7 +108,6 @@ def test_get_agents_featured(
         category=None,
         page=1,
         page_size=20,
-        filter_mode="permissive",
     )
 
 
@@ -121,9 +115,9 @@ def test_get_agents_by_creator(
     mocker: pytest_mock.MockFixture,
     snapshot: Snapshot,
 ) -> None:
-    mocked_value = backend.server.v2.store.model.StoreAgentsResponse(
+    mocked_value = store_model.StoreAgentsResponse(
         agents=[
-            backend.server.v2.store.model.StoreAgent(
+            store_model.StoreAgent(
                 slug="creator-agent",
                 agent_name="Creator Agent",
                 agent_image="agent.jpg",
@@ -135,20 +129,18 @@ def test_get_agents_by_creator(
                 rating=4.0,
             )
         ],
-        pagination=backend.server.v2.store.model.Pagination(
+        pagination=store_model.Pagination(
             current_page=1,
             total_items=1,
             total_pages=1,
             page_size=20,
         ),
     )
-    mock_db_call = mocker.patch("backend.server.v2.store.db.get_store_agents")
+    mock_db_call = mocker.patch("backend.api.features.store.db.get_store_agents")
     mock_db_call.return_value = mocked_value
     response = client.get("/agents?creator=specific-creator")
     assert response.status_code == 200
-    data = backend.server.v2.store.model.StoreAgentsResponse.model_validate(
-        response.json()
-    )
+    data = store_model.StoreAgentsResponse.model_validate(response.json())
     assert len(data.agents) == 1
     assert data.agents[0].creator == "specific-creator"
     snapshot.snapshot_dir = "snapshots"
@@ -161,7 +153,6 @@ def test_get_agents_by_creator(
         category=None,
         page=1,
         page_size=20,
-        filter_mode="permissive",
     )
 
 
@@ -169,9 +160,9 @@ def test_get_agents_sorted(
     mocker: pytest_mock.MockFixture,
     snapshot: Snapshot,
 ) -> None:
-    mocked_value = backend.server.v2.store.model.StoreAgentsResponse(
+    mocked_value = store_model.StoreAgentsResponse(
         agents=[
-            backend.server.v2.store.model.StoreAgent(
+            store_model.StoreAgent(
                 slug="top-agent",
                 agent_name="Top Agent",
                 agent_image="top.jpg",
@@ -183,20 +174,18 @@ def test_get_agents_sorted(
                 rating=5.0,
             )
         ],
-        pagination=backend.server.v2.store.model.Pagination(
+        pagination=store_model.Pagination(
             current_page=1,
             total_items=1,
             total_pages=1,
             page_size=20,
         ),
     )
-    mock_db_call = mocker.patch("backend.server.v2.store.db.get_store_agents")
+    mock_db_call = mocker.patch("backend.api.features.store.db.get_store_agents")
     mock_db_call.return_value = mocked_value
     response = client.get("/agents?sorted_by=runs")
     assert response.status_code == 200
-    data = backend.server.v2.store.model.StoreAgentsResponse.model_validate(
-        response.json()
-    )
+    data = store_model.StoreAgentsResponse.model_validate(response.json())
     assert len(data.agents) == 1
     assert data.agents[0].runs == 1000
     snapshot.snapshot_dir = "snapshots"
@@ -209,7 +198,6 @@ def test_get_agents_sorted(
         category=None,
         page=1,
         page_size=20,
-        filter_mode="permissive",
     )
 
 
@@ -217,9 +205,9 @@ def test_get_agents_search(
     mocker: pytest_mock.MockFixture,
     snapshot: Snapshot,
 ) -> None:
-    mocked_value = backend.server.v2.store.model.StoreAgentsResponse(
+    mocked_value = store_model.StoreAgentsResponse(
         agents=[
-            backend.server.v2.store.model.StoreAgent(
+            store_model.StoreAgent(
                 slug="search-agent",
                 agent_name="Search Agent",
                 agent_image="search.jpg",
@@ -231,20 +219,18 @@ def test_get_agents_search(
                 rating=4.2,
             )
         ],
-        pagination=backend.server.v2.store.model.Pagination(
+        pagination=store_model.Pagination(
             current_page=1,
             total_items=1,
             total_pages=1,
             page_size=20,
         ),
     )
-    mock_db_call = mocker.patch("backend.server.v2.store.db.get_store_agents")
+    mock_db_call = mocker.patch("backend.api.features.store.db.get_store_agents")
     mock_db_call.return_value = mocked_value
     response = client.get("/agents?search_query=specific")
     assert response.status_code == 200
-    data = backend.server.v2.store.model.StoreAgentsResponse.model_validate(
-        response.json()
-    )
+    data = store_model.StoreAgentsResponse.model_validate(response.json())
     assert len(data.agents) == 1
     assert "specific" in data.agents[0].description.lower()
     snapshot.snapshot_dir = "snapshots"
@@ -257,7 +243,6 @@ def test_get_agents_search(
         category=None,
         page=1,
         page_size=20,
-        filter_mode="permissive",
     )
 
 
@@ -265,9 +250,9 @@ def test_get_agents_category(
     mocker: pytest_mock.MockFixture,
     snapshot: Snapshot,
 ) -> None:
-    mocked_value = backend.server.v2.store.model.StoreAgentsResponse(
+    mocked_value = store_model.StoreAgentsResponse(
         agents=[
-            backend.server.v2.store.model.StoreAgent(
+            store_model.StoreAgent(
                 slug="category-agent",
                 agent_name="Category Agent",
                 agent_image="category.jpg",
@@ -279,20 +264,18 @@ def test_get_agents_category(
                 rating=4.1,
             )
         ],
-        pagination=backend.server.v2.store.model.Pagination(
+        pagination=store_model.Pagination(
             current_page=1,
             total_items=1,
             total_pages=1,
             page_size=20,
         ),
     )
-    mock_db_call = mocker.patch("backend.server.v2.store.db.get_store_agents")
+    mock_db_call = mocker.patch("backend.api.features.store.db.get_store_agents")
     mock_db_call.return_value = mocked_value
     response = client.get("/agents?category=test-category")
     assert response.status_code == 200
-    data = backend.server.v2.store.model.StoreAgentsResponse.model_validate(
-        response.json()
-    )
+    data = store_model.StoreAgentsResponse.model_validate(response.json())
     assert len(data.agents) == 1
     snapshot.snapshot_dir = "snapshots"
     snapshot.assert_match(json.dumps(response.json(), indent=2), "agts_category")
@@ -304,7 +287,6 @@ def test_get_agents_category(
         category="test-category",
         page=1,
         page_size=20,
-        filter_mode="permissive",
     )
 
 
@@ -312,9 +294,9 @@ def test_get_agents_pagination(
     mocker: pytest_mock.MockFixture,
     snapshot: Snapshot,
 ) -> None:
-    mocked_value = backend.server.v2.store.model.StoreAgentsResponse(
+    mocked_value = store_model.StoreAgentsResponse(
         agents=[
-            backend.server.v2.store.model.StoreAgent(
+            store_model.StoreAgent(
                 slug=f"agent-{i}",
                 agent_name=f"Agent {i}",
                 agent_image=f"agent{i}.jpg",
@@ -327,20 +309,18 @@ def test_get_agents_pagination(
             )
             for i in range(5)
         ],
-        pagination=backend.server.v2.store.model.Pagination(
+        pagination=store_model.Pagination(
             current_page=2,
             total_items=15,
             total_pages=3,
             page_size=5,
         ),
     )
-    mock_db_call = mocker.patch("backend.server.v2.store.db.get_store_agents")
+    mock_db_call = mocker.patch("backend.api.features.store.db.get_store_agents")
     mock_db_call.return_value = mocked_value
     response = client.get("/agents?page=2&page_size=5")
     assert response.status_code == 200
-    data = backend.server.v2.store.model.StoreAgentsResponse.model_validate(
-        response.json()
-    )
+    data = store_model.StoreAgentsResponse.model_validate(response.json())
     assert len(data.agents) == 5
     assert data.pagination.current_page == 2
     assert data.pagination.page_size == 5
@@ -354,7 +334,6 @@ def test_get_agents_pagination(
         category=None,
         page=2,
         page_size=5,
-        filter_mode="permissive",
     )
 
 
@@ -372,7 +351,7 @@ def test_get_agents_malformed_request(mocker: pytest_mock.MockFixture):
     assert response.status_code == 422
 
     # Verify no DB calls were made
-    mock_db_call = mocker.patch("backend.server.v2.store.db.get_store_agents")
+    mock_db_call = mocker.patch("backend.api.features.store.db.get_store_agents")
     mock_db_call.assert_not_called()
 
 
@@ -380,7 +359,7 @@ def test_get_agent_details(
     mocker: pytest_mock.MockFixture,
     snapshot: Snapshot,
 ) -> None:
-    mocked_value = backend.server.v2.store.model.StoreAgentDetails(
+    mocked_value = store_model.StoreAgentDetails(
         store_listing_version_id="test-version-id",
         slug="test-agent",
         agent_name="Test Agent",
@@ -395,46 +374,46 @@ def test_get_agent_details(
         runs=100,
         rating=4.5,
         versions=["1.0.0", "1.1.0"],
+        agentGraphVersions=["1", "2"],
+        agentGraphId="test-graph-id",
         last_updated=FIXED_NOW,
     )
-    mock_db_call = mocker.patch("backend.server.v2.store.db.get_store_agent_details")
+    mock_db_call = mocker.patch("backend.api.features.store.db.get_store_agent_details")
     mock_db_call.return_value = mocked_value
 
     response = client.get("/agents/creator1/test-agent")
     assert response.status_code == 200
 
-    data = backend.server.v2.store.model.StoreAgentDetails.model_validate(
-        response.json()
-    )
+    data = store_model.StoreAgentDetails.model_validate(response.json())
     assert data.agent_name == "Test Agent"
     assert data.creator == "creator1"
     snapshot.snapshot_dir = "snapshots"
     snapshot.assert_match(json.dumps(response.json(), indent=2), "agt_details")
-    mock_db_call.assert_called_once_with(username="creator1", agent_name="test-agent")
+    mock_db_call.assert_called_once_with(
+        username="creator1", agent_name="test-agent", include_changelog=False
+    )
 
 
 def test_get_creators_defaults(
     mocker: pytest_mock.MockFixture,
     snapshot: Snapshot,
 ) -> None:
-    mocked_value = backend.server.v2.store.model.CreatorsResponse(
+    mocked_value = store_model.CreatorsResponse(
         creators=[],
-        pagination=backend.server.v2.store.model.Pagination(
+        pagination=store_model.Pagination(
             current_page=0,
             total_items=0,
             total_pages=0,
             page_size=10,
         ),
     )
-    mock_db_call = mocker.patch("backend.server.v2.store.db.get_store_creators")
+    mock_db_call = mocker.patch("backend.api.features.store.db.get_store_creators")
     mock_db_call.return_value = mocked_value
 
     response = client.get("/creators")
     assert response.status_code == 200
 
-    data = backend.server.v2.store.model.CreatorsResponse.model_validate(
-        response.json()
-    )
+    data = store_model.CreatorsResponse.model_validate(response.json())
     assert data.pagination.total_pages == 0
     assert data.creators == []
     snapshot.snapshot_dir = "snapshots"
@@ -448,9 +427,9 @@ def test_get_creators_pagination(
     mocker: pytest_mock.MockFixture,
     snapshot: Snapshot,
 ) -> None:
-    mocked_value = backend.server.v2.store.model.CreatorsResponse(
+    mocked_value = store_model.CreatorsResponse(
         creators=[
-            backend.server.v2.store.model.Creator(
+            store_model.Creator(
                 name=f"Creator {i}",
                 username=f"creator{i}",
                 description=f"Creator {i} description",
@@ -462,22 +441,20 @@ def test_get_creators_pagination(
             )
             for i in range(5)
         ],
-        pagination=backend.server.v2.store.model.Pagination(
+        pagination=store_model.Pagination(
             current_page=2,
             total_items=15,
             total_pages=3,
             page_size=5,
         ),
     )
-    mock_db_call = mocker.patch("backend.server.v2.store.db.get_store_creators")
+    mock_db_call = mocker.patch("backend.api.features.store.db.get_store_creators")
     mock_db_call.return_value = mocked_value
 
     response = client.get("/creators?page=2&page_size=5")
     assert response.status_code == 200
 
-    data = backend.server.v2.store.model.CreatorsResponse.model_validate(
-        response.json()
-    )
+    data = store_model.CreatorsResponse.model_validate(response.json())
     assert len(data.creators) == 5
     assert data.pagination.current_page == 2
     assert data.pagination.page_size == 5
@@ -502,7 +479,7 @@ def test_get_creators_malformed_request(mocker: pytest_mock.MockFixture):
     assert response.status_code == 422
 
     # Verify no DB calls were made
-    mock_db_call = mocker.patch("backend.server.v2.store.db.get_store_creators")
+    mock_db_call = mocker.patch("backend.api.features.store.db.get_store_creators")
     mock_db_call.assert_not_called()
 
 
@@ -510,7 +487,7 @@ def test_get_creator_details(
     mocker: pytest_mock.MockFixture,
     snapshot: Snapshot,
 ) -> None:
-    mocked_value = backend.server.v2.store.model.CreatorDetails(
+    mocked_value = store_model.CreatorDetails(
         name="Test User",
         username="creator1",
         description="Test creator description",
@@ -520,13 +497,15 @@ def test_get_creator_details(
         agent_runs=1000,
         top_categories=["category1", "category2"],
     )
-    mock_db_call = mocker.patch("backend.server.v2.store.db.get_store_creator_details")
+    mock_db_call = mocker.patch(
+        "backend.api.features.store.db.get_store_creator_details"
+    )
     mock_db_call.return_value = mocked_value
 
     response = client.get("/creator/creator1")
     assert response.status_code == 200
 
-    data = backend.server.v2.store.model.CreatorDetails.model_validate(response.json())
+    data = store_model.CreatorDetails.model_validate(response.json())
     assert data.username == "creator1"
     assert data.name == "Test User"
     snapshot.snapshot_dir = "snapshots"
@@ -539,9 +518,9 @@ def test_get_submissions_success(
     snapshot: Snapshot,
     test_user_id: str,
 ) -> None:
-    mocked_value = backend.server.v2.store.model.StoreSubmissionsResponse(
+    mocked_value = store_model.StoreSubmissionsResponse(
         submissions=[
-            backend.server.v2.store.model.StoreSubmission(
+            store_model.StoreSubmission(
                 name="Test Agent",
                 description="Test agent description",
                 image_urls=["test.jpg"],
@@ -557,22 +536,20 @@ def test_get_submissions_success(
                 categories=["test-category"],
             )
         ],
-        pagination=backend.server.v2.store.model.Pagination(
+        pagination=store_model.Pagination(
             current_page=1,
             total_items=1,
             total_pages=1,
             page_size=20,
         ),
     )
-    mock_db_call = mocker.patch("backend.server.v2.store.db.get_store_submissions")
+    mock_db_call = mocker.patch("backend.api.features.store.db.get_store_submissions")
     mock_db_call.return_value = mocked_value
 
     response = client.get("/submissions")
     assert response.status_code == 200
 
-    data = backend.server.v2.store.model.StoreSubmissionsResponse.model_validate(
-        response.json()
-    )
+    data = store_model.StoreSubmissionsResponse.model_validate(response.json())
     assert len(data.submissions) == 1
     assert data.submissions[0].name == "Test Agent"
     assert data.pagination.current_page == 1
@@ -586,24 +563,22 @@ def test_get_submissions_pagination(
     snapshot: Snapshot,
     test_user_id: str,
 ) -> None:
-    mocked_value = backend.server.v2.store.model.StoreSubmissionsResponse(
+    mocked_value = store_model.StoreSubmissionsResponse(
         submissions=[],
-        pagination=backend.server.v2.store.model.Pagination(
+        pagination=store_model.Pagination(
             current_page=2,
             total_items=10,
             total_pages=2,
             page_size=5,
         ),
     )
-    mock_db_call = mocker.patch("backend.server.v2.store.db.get_store_submissions")
+    mock_db_call = mocker.patch("backend.api.features.store.db.get_store_submissions")
     mock_db_call.return_value = mocked_value
 
     response = client.get("/submissions?page=2&page_size=5")
     assert response.status_code == 200
 
-    data = backend.server.v2.store.model.StoreSubmissionsResponse.model_validate(
-        response.json()
-    )
+    data = store_model.StoreSubmissionsResponse.model_validate(response.json())
     assert data.pagination.current_page == 2
     assert data.pagination.page_size == 5
     snapshot.snapshot_dir = "snapshots"
@@ -625,5 +600,5 @@ def test_get_submissions_malformed_request(mocker: pytest_mock.MockFixture):
     assert response.status_code == 422
 
     # Verify no DB calls were made
-    mock_db_call = mocker.patch("backend.server.v2.store.db.get_store_submissions")
+    mock_db_call = mocker.patch("backend.api.features.store.db.get_store_submissions")
     mock_db_call.assert_not_called()

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

@@ -8,10 +8,11 @@ from unittest.mock import AsyncMock, patch
 
 import pytest
 
-from backend.server.v2.store import cache as store_cache
-from backend.server.v2.store.model import StoreAgent, StoreAgentsResponse
 from backend.util.models import Pagination
 
+from . import cache as store_cache
+from .model import StoreAgent, StoreAgentsResponse
+
 
 class TestCacheDeletion:
     """Test cache deletion functionality for store routes."""
@@ -43,7 +44,7 @@ class TestCacheDeletion:
         )
 
         with patch(
-            "backend.server.v2.store.db.get_store_agents",
+            "backend.api.features.store.db.get_store_agents",
             new_callable=AsyncMock,
             return_value=mock_response,
         ) as mock_db:
@@ -152,7 +153,7 @@ class TestCacheDeletion:
         )
 
         with patch(
-            "backend.server.v2.store.db.get_store_agents",
+            "backend.api.features.store.db.get_store_agents",
             new_callable=AsyncMock,
             return_value=mock_response,
         ):
@@ -203,7 +204,7 @@ class TestCacheDeletion:
         )
 
         with patch(
-            "backend.server.v2.store.db.get_store_agents",
+            "backend.api.features.store.db.get_store_agents",
             new_callable=AsyncMock,
             return_value=mock_response,
         ) as mock_db:

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

@@ -28,12 +28,21 @@ from pydantic import BaseModel
 from starlette.status import HTTP_204_NO_CONTENT, HTTP_404_NOT_FOUND
 from typing_extensions import Optional, TypedDict
 
-import backend.server.integrations.router
-import backend.server.routers.analytics
-import backend.server.v2.library.db as library_db
-from backend.data import api_key as api_key_db
+from backend.api.model import (
+    CreateAPIKeyRequest,
+    CreateAPIKeyResponse,
+    CreateGraph,
+    GraphExecutionSource,
+    RequestTopUp,
+    SetGraphActiveVersion,
+    TimezoneResponse,
+    UpdatePermissionsRequest,
+    UpdateTimezoneRequest,
+    UploadFileResponse,
+)
 from backend.data import execution as execution_db
 from backend.data import graph as graph_db
+from backend.data.auth import api_key as api_key_db
 from backend.data.block import BlockInput, CompletedBlockOutput, get_block, get_blocks
 from backend.data.credit import (
     AutoTopUpConfig,
@@ -79,19 +88,6 @@ from backend.monitoring.instrumentation import (
     record_graph_execution,
     record_graph_operation,
 )
-from backend.server.model import (
-    CreateAPIKeyRequest,
-    CreateAPIKeyResponse,
-    CreateGraph,
-    GraphExecutionSource,
-    RequestTopUp,
-    SetGraphActiveVersion,
-    TimezoneResponse,
-    UpdatePermissionsRequest,
-    UpdateTimezoneRequest,
-    UploadFileResponse,
-)
-from backend.server.v2.store.model import StoreAgentDetails
 from backend.util.cache import cached
 from backend.util.clients import get_scheduler_client
 from backend.util.cloud_storage import get_cloud_storage_handler
@@ -105,6 +101,10 @@ from backend.util.timezone_utils import (
 )
 from backend.util.virus_scanner import scan_content_safe
 
+from .library import db as library_db
+from .library import model as library_model
+from .store.model import StoreAgentDetails
+
 
 def _create_file_size_error(size_bytes: int, max_size_mb: int) -> HTTPException:
     """Create standardized file size error response."""
@@ -118,76 +118,9 @@ settings = Settings()
 logger = logging.getLogger(__name__)
 
 
-async def hide_activity_summaries_if_disabled(
-    executions: list[execution_db.GraphExecutionMeta], user_id: str
-) -> list[execution_db.GraphExecutionMeta]:
-    """Hide activity summaries and scores if AI_ACTIVITY_STATUS feature is disabled."""
-    if await is_feature_enabled(Flag.AI_ACTIVITY_STATUS, user_id):
-        return executions  # Return as-is if feature is enabled
-
-    # Filter out activity features if disabled
-    filtered_executions = []
-    for execution in executions:
-        if execution.stats:
-            filtered_stats = execution.stats.without_activity_features()
-            execution = execution.model_copy(update={"stats": filtered_stats})
-        filtered_executions.append(execution)
-    return filtered_executions
-
-
-async def hide_activity_summary_if_disabled(
-    execution: execution_db.GraphExecution | execution_db.GraphExecutionWithNodes,
-    user_id: str,
-) -> execution_db.GraphExecution | execution_db.GraphExecutionWithNodes:
-    """Hide activity summary and score for a single execution if AI_ACTIVITY_STATUS feature is disabled."""
-    if await is_feature_enabled(Flag.AI_ACTIVITY_STATUS, user_id):
-        return execution  # Return as-is if feature is enabled
-
-    # Filter out activity features if disabled
-    if execution.stats:
-        filtered_stats = execution.stats.without_activity_features()
-        return execution.model_copy(update={"stats": filtered_stats})
-    return execution
-
-
-async def _update_library_agent_version_and_settings(
-    user_id: str, agent_graph: graph_db.GraphModel
-) -> library_db.library_model.LibraryAgent:
-    # Keep the library agent up to date with the new active version
-    library = await library_db.update_agent_version_in_library(
-        user_id, agent_graph.id, agent_graph.version
-    )
-    # If the graph has HITL node, initialize the setting if it's not already set.
-    if (
-        agent_graph.has_human_in_the_loop
-        and library.settings.human_in_the_loop_safe_mode is None
-    ):
-        await library_db.update_library_agent_settings(
-            user_id=user_id,
-            agent_id=library.id,
-            settings=library.settings.model_copy(
-                update={"human_in_the_loop_safe_mode": True}
-            ),
-        )
-    return library
-
-
 # Define the API routes
 v1_router = APIRouter()
 
-v1_router.include_router(
-    backend.server.integrations.router.router,
-    prefix="/integrations",
-    tags=["integrations"],
-)
-
-v1_router.include_router(
-    backend.server.routers.analytics.router,
-    prefix="/analytics",
-    tags=["analytics"],
-    dependencies=[Security(requires_user)],
-)
-
 
 ########################################################
 ##################### Auth #############################
@@ -953,6 +886,28 @@ async def set_graph_active_version(
         await on_graph_deactivate(current_active_graph, user_id=user_id)
 
 
+async def _update_library_agent_version_and_settings(
+    user_id: str, agent_graph: graph_db.GraphModel
+) -> library_model.LibraryAgent:
+    # Keep the library agent up to date with the new active version
+    library = await library_db.update_agent_version_in_library(
+        user_id, agent_graph.id, agent_graph.version
+    )
+    # If the graph has HITL node, initialize the setting if it's not already set.
+    if (
+        agent_graph.has_human_in_the_loop
+        and library.settings.human_in_the_loop_safe_mode is None
+    ):
+        await library_db.update_library_agent_settings(
+            user_id=user_id,
+            agent_id=library.id,
+            settings=library.settings.model_copy(
+                update={"human_in_the_loop_safe_mode": True}
+            ),
+        )
+    return library
+
+
 @v1_router.patch(
     path="/graphs/{graph_id}/settings",
     summary="Update graph settings",
@@ -1155,6 +1110,23 @@ async def list_graph_executions(
     )
 
 
+async def hide_activity_summaries_if_disabled(
+    executions: list[execution_db.GraphExecutionMeta], user_id: str
+) -> list[execution_db.GraphExecutionMeta]:
+    """Hide activity summaries and scores if AI_ACTIVITY_STATUS feature is disabled."""
+    if await is_feature_enabled(Flag.AI_ACTIVITY_STATUS, user_id):
+        return executions  # Return as-is if feature is enabled
+
+    # Filter out activity features if disabled
+    filtered_executions = []
+    for execution in executions:
+        if execution.stats:
+            filtered_stats = execution.stats.without_activity_features()
+            execution = execution.model_copy(update={"stats": filtered_stats})
+        filtered_executions.append(execution)
+    return filtered_executions
+
+
 @v1_router.get(
     path="/graphs/{graph_id}/executions/{graph_exec_id}",
     summary="Get execution details",
@@ -1197,6 +1169,21 @@ async def get_graph_execution(
     return result
 
 
+async def hide_activity_summary_if_disabled(
+    execution: execution_db.GraphExecution | execution_db.GraphExecutionWithNodes,
+    user_id: str,
+) -> execution_db.GraphExecution | execution_db.GraphExecutionWithNodes:
+    """Hide activity summary and score for a single execution if AI_ACTIVITY_STATUS feature is disabled."""
+    if await is_feature_enabled(Flag.AI_ACTIVITY_STATUS, user_id):
+        return execution  # Return as-is if feature is enabled
+
+    # Filter out activity features if disabled
+    if execution.stats:
+        filtered_stats = execution.stats.without_activity_features()
+        return execution.model_copy(update={"stats": filtered_stats})
+    return execution
+
+
 @v1_router.delete(
     path="/executions/{graph_exec_id}",
     summary="Delete graph execution",
@@ -1257,7 +1244,7 @@ async def enable_execution_sharing(
     )
 
     # Return the share URL
-    frontend_url = Settings().config.frontend_base_url or "http://localhost:3000"
+    frontend_url = settings.config.frontend_base_url or "http://localhost:3000"
     share_url = f"{frontend_url}/share/{share_token}"
 
     return ShareResponse(share_url=share_url, share_token=share_token)

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

@@ -11,13 +11,13 @@ import starlette.datastructures
 from fastapi import HTTPException, UploadFile
 from pytest_snapshot.plugin import Snapshot
 
-import backend.server.routers.v1 as v1_routes
 from backend.data.credit import AutoTopUpConfig
 from backend.data.graph import GraphModel
-from backend.server.routers.v1 import upload_file
+
+from .v1 import upload_file, v1_router
 
 app = fastapi.FastAPI()
-app.include_router(v1_routes.v1_router)
+app.include_router(v1_router)
 
 client = fastapi.testclient.TestClient(app)
 
@@ -50,7 +50,7 @@ def test_get_or_create_user_route(
     }
 
     mocker.patch(
-        "backend.server.routers.v1.get_or_create_user",
+        "backend.api.features.v1.get_or_create_user",
         return_value=mock_user,
     )
 
@@ -71,7 +71,7 @@ def test_update_user_email_route(
 ) -> None:
     """Test update user email endpoint"""
     mocker.patch(
-        "backend.server.routers.v1.update_user_email",
+        "backend.api.features.v1.update_user_email",
         return_value=None,
     )
 
@@ -107,7 +107,7 @@ def test_get_graph_blocks(
 
     # Mock get_blocks
     mocker.patch(
-        "backend.server.routers.v1.get_blocks",
+        "backend.api.features.v1.get_blocks",
         return_value={"test-block": lambda: mock_block},
     )
 
@@ -146,7 +146,7 @@ def test_execute_graph_block(
     mock_block.execute = mock_execute
 
     mocker.patch(
-        "backend.server.routers.v1.get_block",
+        "backend.api.features.v1.get_block",
         return_value=mock_block,
     )
 
@@ -155,7 +155,7 @@ def test_execute_graph_block(
     mock_user.timezone = "UTC"
 
     mocker.patch(
-        "backend.server.routers.v1.get_user_by_id",
+        "backend.api.features.v1.get_user_by_id",
         return_value=mock_user,
     )
 
@@ -181,7 +181,7 @@ def test_execute_graph_block_not_found(
 ) -> None:
     """Test execute block with non-existent block"""
     mocker.patch(
-        "backend.server.routers.v1.get_block",
+        "backend.api.features.v1.get_block",
         return_value=None,
     )
 
@@ -200,7 +200,7 @@ def test_get_user_credits(
     mock_credit_model = Mock()
     mock_credit_model.get_credits = AsyncMock(return_value=1000)
     mocker.patch(
-        "backend.server.routers.v1.get_user_credit_model",
+        "backend.api.features.v1.get_user_credit_model",
         return_value=mock_credit_model,
     )
 
@@ -227,7 +227,7 @@ def test_request_top_up(
         return_value="https://checkout.example.com/session123"
     )
     mocker.patch(
-        "backend.server.routers.v1.get_user_credit_model",
+        "backend.api.features.v1.get_user_credit_model",
         return_value=mock_credit_model,
     )
 
@@ -254,7 +254,7 @@ def test_get_auto_top_up(
     mock_config = AutoTopUpConfig(threshold=100, amount=500)
 
     mocker.patch(
-        "backend.server.routers.v1.get_auto_top_up",
+        "backend.api.features.v1.get_auto_top_up",
         return_value=mock_config,
     )
 
@@ -279,7 +279,7 @@ def test_configure_auto_top_up(
     """Test configure auto top-up endpoint - this test would have caught the enum casting bug"""
     # Mock the set_auto_top_up function to avoid database operations
     mocker.patch(
-        "backend.server.routers.v1.set_auto_top_up",
+        "backend.api.features.v1.set_auto_top_up",
         return_value=None,
     )
 
@@ -289,7 +289,7 @@ def test_configure_auto_top_up(
     mock_credit_model.top_up_credits.return_value = None
 
     mocker.patch(
-        "backend.server.routers.v1.get_user_credit_model",
+        "backend.api.features.v1.get_user_credit_model",
         return_value=mock_credit_model,
     )
 
@@ -311,7 +311,7 @@ def test_configure_auto_top_up_validation_errors(
 ) -> None:
     """Test configure auto top-up endpoint validation"""
     # Mock set_auto_top_up to avoid database operations for successful case
-    mocker.patch("backend.server.routers.v1.set_auto_top_up")
+    mocker.patch("backend.api.features.v1.set_auto_top_up")
 
     # Mock credit model to avoid Stripe API calls for the successful case
     mock_credit_model = mocker.AsyncMock()
@@ -319,7 +319,7 @@ def test_configure_auto_top_up_validation_errors(
     mock_credit_model.top_up_credits.return_value = None
 
     mocker.patch(
-        "backend.server.routers.v1.get_user_credit_model",
+        "backend.api.features.v1.get_user_credit_model",
         return_value=mock_credit_model,
     )
 
@@ -393,7 +393,7 @@ def test_get_graph(
     )
 
     mocker.patch(
-        "backend.server.routers.v1.graph_db.get_graph",
+        "backend.api.features.v1.graph_db.get_graph",
         return_value=mock_graph,
     )
 
@@ -415,7 +415,7 @@ def test_get_graph_not_found(
 ) -> None:
     """Test get graph with non-existent ID"""
     mocker.patch(
-        "backend.server.routers.v1.graph_db.get_graph",
+        "backend.api.features.v1.graph_db.get_graph",
         return_value=None,
     )
 
@@ -443,15 +443,15 @@ def test_delete_graph(
     )
 
     mocker.patch(
-        "backend.server.routers.v1.graph_db.get_graph",
+        "backend.api.features.v1.graph_db.get_graph",
         return_value=mock_graph,
     )
     mocker.patch(
-        "backend.server.routers.v1.on_graph_deactivate",
+        "backend.api.features.v1.on_graph_deactivate",
         return_value=None,
     )
     mocker.patch(
-        "backend.server.routers.v1.graph_db.delete_graph",
+        "backend.api.features.v1.graph_db.delete_graph",
         return_value=3,  # Number of versions deleted
     )
 
@@ -498,8 +498,8 @@ async def test_upload_file_success(test_user_id: str):
     )
 
     # Mock dependencies
-    with patch("backend.server.routers.v1.scan_content_safe") as mock_scan, patch(
-        "backend.server.routers.v1.get_cloud_storage_handler"
+    with patch("backend.api.features.v1.scan_content_safe") as mock_scan, patch(
+        "backend.api.features.v1.get_cloud_storage_handler"
     ) as mock_handler_getter:
 
         mock_scan.return_value = None
@@ -550,8 +550,8 @@ async def test_upload_file_no_filename(test_user_id: str):
         ),
     )
 
-    with patch("backend.server.routers.v1.scan_content_safe") as mock_scan, patch(
-        "backend.server.routers.v1.get_cloud_storage_handler"
+    with patch("backend.api.features.v1.scan_content_safe") as mock_scan, patch(
+        "backend.api.features.v1.get_cloud_storage_handler"
     ) as mock_handler_getter:
 
         mock_scan.return_value = None
@@ -610,7 +610,7 @@ async def test_upload_file_virus_scan_failure(test_user_id: str):
         headers=starlette.datastructures.Headers({"content-type": "text/plain"}),
     )
 
-    with patch("backend.server.routers.v1.scan_content_safe") as mock_scan:
+    with patch("backend.api.features.v1.scan_content_safe") as mock_scan:
         # Mock virus scan to raise exception
         mock_scan.side_effect = RuntimeError("Virus detected!")
 
@@ -631,8 +631,8 @@ async def test_upload_file_cloud_storage_failure(test_user_id: str):
         headers=starlette.datastructures.Headers({"content-type": "text/plain"}),
     )
 
-    with patch("backend.server.routers.v1.scan_content_safe") as mock_scan, patch(
-        "backend.server.routers.v1.get_cloud_storage_handler"
+    with patch("backend.api.features.v1.scan_content_safe") as mock_scan, patch(
+        "backend.api.features.v1.get_cloud_storage_handler"
     ) as mock_handler_getter:
 
         mock_scan.return_value = None
@@ -678,8 +678,8 @@ async def test_upload_file_gcs_not_configured_fallback(test_user_id: str):
         headers=starlette.datastructures.Headers({"content-type": "text/plain"}),
     )
 
-    with patch("backend.server.routers.v1.scan_content_safe") as mock_scan, patch(
-        "backend.server.routers.v1.get_cloud_storage_handler"
+    with patch("backend.api.features.v1.scan_content_safe") as mock_scan, patch(
+        "backend.api.features.v1.get_cloud_storage_handler"
     ) as mock_handler_getter:
 
         mock_scan.return_value = None

autogpt_platform/backend/backend/api/middleware/security_test.py

@@ -3,7 +3,7 @@ from fastapi import FastAPI
 from fastapi.testclient import TestClient
 from starlette.applications import Starlette
 
-from backend.server.middleware.security import SecurityHeadersMiddleware
+from backend.api.middleware.security import SecurityHeadersMiddleware
 
 
 @pytest.fixture

autogpt_platform/backend/backend/api/model.py

@@ -4,7 +4,7 @@ from typing import Any, Literal, Optional
 import pydantic
 from prisma.enums import OnboardingStep
 
-from backend.data.api_key import APIKeyInfo, APIKeyPermission
+from backend.data.auth.api_key import APIKeyInfo, APIKeyPermission
 from backend.data.graph import Graph
 from backend.util.timezone_name import TimeZoneName
 

autogpt_platform/backend/backend/api/rest_api.py

@@ -16,35 +16,33 @@ from fastapi.middleware.gzip import GZipMiddleware
 from fastapi.routing import APIRoute
 from prisma.errors import PrismaError
 
+import backend.api.features.admin.credit_admin_routes
+import backend.api.features.admin.execution_analytics_routes
+import backend.api.features.admin.store_admin_routes
+import backend.api.features.builder
+import backend.api.features.builder.routes
+import backend.api.features.chat.routes as chat_routes
+import backend.api.features.executions.review.routes
+import backend.api.features.library.db
+import backend.api.features.library.model
+import backend.api.features.library.routes
+import backend.api.features.oauth
+import backend.api.features.otto.routes
+import backend.api.features.postmark.postmark
+import backend.api.features.store.model
+import backend.api.features.store.routes
+import backend.api.features.v1
 import backend.data.block
 import backend.data.db
 import backend.data.graph
 import backend.data.user
 import backend.integrations.webhooks.utils
-import backend.server.routers.postmark.postmark
-import backend.server.routers.v1
-import backend.server.v2.admin.credit_admin_routes
-import backend.server.v2.admin.execution_analytics_routes
-import backend.server.v2.admin.store_admin_routes
-import backend.server.v2.builder
-import backend.server.v2.builder.routes
-import backend.server.v2.chat.routes as chat_routes
-import backend.server.v2.executions.review.routes
-import backend.server.v2.library.db
-import backend.server.v2.library.model
-import backend.server.v2.library.routes
-import backend.server.v2.otto.routes
-import backend.server.v2.store.model
-import backend.server.v2.store.routes
 import backend.util.service
 import backend.util.settings
-from backend.blocks.llm import LlmModel
+from backend.blocks.llm import DEFAULT_LLM_MODEL
 from backend.data.model import Credentials
 from backend.integrations.providers import ProviderName
 from backend.monitoring.instrumentation import instrument_fastapi
-from backend.server.external.api import external_app
-from backend.server.middleware.security import SecurityHeadersMiddleware
-from backend.server.utils.cors import build_cors_params
 from backend.util import json
 from backend.util.cloud_storage import shutdown_cloud_storage_handler
 from backend.util.exceptions import (
@@ -55,6 +53,13 @@ from backend.util.exceptions import (
 from backend.util.feature_flag import initialize_launchdarkly, shutdown_launchdarkly
 from backend.util.service import UnhealthyServiceError
 
+from .external.fastapi_app import external_api
+from .features.analytics import router as analytics_router
+from .features.integrations.router import router as integrations_router
+from .middleware.security import SecurityHeadersMiddleware
+from .utils.cors import build_cors_params
+from .utils.openapi import sort_openapi
+
 settings = backend.util.settings.Settings()
 logger = logging.getLogger(__name__)
 
@@ -108,7 +113,7 @@ async def lifespan_context(app: fastapi.FastAPI):
 
     await backend.data.user.migrate_and_encrypt_user_integrations()
     await backend.data.graph.fix_llm_provider_credentials()
-    await backend.data.graph.migrate_llm_models(LlmModel.GPT4O)
+    await backend.data.graph.migrate_llm_models(DEFAULT_LLM_MODEL)
     await backend.integrations.webhooks.utils.migrate_legacy_triggered_graphs()
 
     with launch_darkly_context():
@@ -175,6 +180,9 @@ app.add_middleware(GZipMiddleware, minimum_size=50_000)  # 50KB threshold
 # Add 401 responses to authenticated endpoints in OpenAPI spec
 add_auth_responses_to_openapi(app)
 
+# Sort OpenAPI schema to eliminate diff on refactors
+sort_openapi(app)
+
 # Add Prometheus instrumentation
 instrument_fastapi(
     app,
@@ -253,42 +261,52 @@ app.add_exception_handler(MissingConfigError, handle_internal_http_error(503))
 app.add_exception_handler(ValueError, handle_internal_http_error(400))
 app.add_exception_handler(Exception, handle_internal_http_error(500))
 
-app.include_router(backend.server.routers.v1.v1_router, tags=["v1"], prefix="/api")
+app.include_router(backend.api.features.v1.v1_router, tags=["v1"], prefix="/api")
 app.include_router(
-    backend.server.v2.store.routes.router, tags=["v2"], prefix="/api/store"
+    integrations_router,
+    prefix="/api/integrations",
+    tags=["v1", "integrations"],
 )
 app.include_router(
-    backend.server.v2.builder.routes.router, tags=["v2"], prefix="/api/builder"
+    analytics_router,
+    prefix="/api/analytics",
+    tags=["analytics"],
 )
 app.include_router(
-    backend.server.v2.admin.store_admin_routes.router,
+    backend.api.features.store.routes.router, tags=["v2"], prefix="/api/store"
+)
+app.include_router(
+    backend.api.features.builder.routes.router, tags=["v2"], prefix="/api/builder"
+)
+app.include_router(
+    backend.api.features.admin.store_admin_routes.router,
     tags=["v2", "admin"],
     prefix="/api/store",
 )
 app.include_router(
-    backend.server.v2.admin.credit_admin_routes.router,
+    backend.api.features.admin.credit_admin_routes.router,
     tags=["v2", "admin"],
     prefix="/api/credits",
 )
 app.include_router(
-    backend.server.v2.admin.execution_analytics_routes.router,
+    backend.api.features.admin.execution_analytics_routes.router,
     tags=["v2", "admin"],
     prefix="/api/executions",
 )
 app.include_router(
-    backend.server.v2.executions.review.routes.router,
+    backend.api.features.executions.review.routes.router,
     tags=["v2", "executions", "review"],
     prefix="/api/review",
 )
 app.include_router(
-    backend.server.v2.library.routes.router, tags=["v2"], prefix="/api/library"
+    backend.api.features.library.routes.router, tags=["v2"], prefix="/api/library"
 )
 app.include_router(
-    backend.server.v2.otto.routes.router, tags=["v2", "otto"], prefix="/api/otto"
+    backend.api.features.otto.routes.router, tags=["v2", "otto"], prefix="/api/otto"
 )
 
 app.include_router(
-    backend.server.routers.postmark.postmark.router,
+    backend.api.features.postmark.postmark.router,
     tags=["v1", "email"],
     prefix="/api/email",
 )
@@ -297,8 +315,13 @@ app.include_router(
     tags=["v2", "chat"],
     prefix="/api/chat",
 )
+app.include_router(
+    backend.api.features.oauth.router,
+    tags=["oauth"],
+    prefix="/api/oauth",
+)
 
-app.mount("/external-api", external_app)
+app.mount("/external-api", external_api)
 
 
 @app.get(path="/health", tags=["health"], dependencies=[])
@@ -351,7 +374,7 @@ class AgentServer(backend.util.service.AppProcess):
         graph_version: Optional[int] = None,
         node_input: Optional[dict[str, Any]] = None,
     ):
-        return await backend.server.routers.v1.execute_graph(
+        return await backend.api.features.v1.execute_graph(
             user_id=user_id,
             graph_id=graph_id,
             graph_version=graph_version,
@@ -366,16 +389,16 @@ class AgentServer(backend.util.service.AppProcess):
         user_id: str,
         for_export: bool = False,
     ):
-        return await backend.server.routers.v1.get_graph(
+        return await backend.api.features.v1.get_graph(
             graph_id, user_id, graph_version, for_export
         )
 
     @staticmethod
     async def test_create_graph(
-        create_graph: backend.server.routers.v1.CreateGraph,
+        create_graph: backend.api.features.v1.CreateGraph,
         user_id: str,
     ):
-        return await backend.server.routers.v1.create_new_graph(create_graph, user_id)
+        return await backend.api.features.v1.create_new_graph(create_graph, user_id)
 
     @staticmethod
     async def test_get_graph_run_status(graph_exec_id: str, user_id: str):
@@ -391,45 +414,45 @@ class AgentServer(backend.util.service.AppProcess):
     @staticmethod
     async def test_delete_graph(graph_id: str, user_id: str):
         """Used for clean-up after a test run"""
-        await backend.server.v2.library.db.delete_library_agent_by_graph_id(
+        await backend.api.features.library.db.delete_library_agent_by_graph_id(
             graph_id=graph_id, user_id=user_id
         )
-        return await backend.server.routers.v1.delete_graph(graph_id, user_id)
+        return await backend.api.features.v1.delete_graph(graph_id, user_id)
 
     @staticmethod
     async def test_get_presets(user_id: str, page: int = 1, page_size: int = 10):
-        return await backend.server.v2.library.routes.presets.list_presets(
+        return await backend.api.features.library.routes.presets.list_presets(
             user_id=user_id, page=page, page_size=page_size
         )
 
     @staticmethod
     async def test_get_preset(preset_id: str, user_id: str):
-        return await backend.server.v2.library.routes.presets.get_preset(
+        return await backend.api.features.library.routes.presets.get_preset(
             preset_id=preset_id, user_id=user_id
         )
 
     @staticmethod
     async def test_create_preset(
-        preset: backend.server.v2.library.model.LibraryAgentPresetCreatable,
+        preset: backend.api.features.library.model.LibraryAgentPresetCreatable,
         user_id: str,
     ):
-        return await backend.server.v2.library.routes.presets.create_preset(
+        return await backend.api.features.library.routes.presets.create_preset(
             preset=preset, user_id=user_id
         )
 
     @staticmethod
     async def test_update_preset(
         preset_id: str,
-        preset: backend.server.v2.library.model.LibraryAgentPresetUpdatable,
+        preset: backend.api.features.library.model.LibraryAgentPresetUpdatable,
         user_id: str,
     ):
-        return await backend.server.v2.library.routes.presets.update_preset(
+        return await backend.api.features.library.routes.presets.update_preset(
             preset_id=preset_id, preset=preset, user_id=user_id
         )
 
     @staticmethod
     async def test_delete_preset(preset_id: str, user_id: str):
-        return await backend.server.v2.library.routes.presets.delete_preset(
+        return await backend.api.features.library.routes.presets.delete_preset(
             preset_id=preset_id, user_id=user_id
         )
 
@@ -439,7 +462,7 @@ class AgentServer(backend.util.service.AppProcess):
         user_id: str,
         inputs: Optional[dict[str, Any]] = None,
     ):
-        return await backend.server.v2.library.routes.presets.execute_preset(
+        return await backend.api.features.library.routes.presets.execute_preset(
             preset_id=preset_id,
             user_id=user_id,
             inputs=inputs or {},
@@ -448,18 +471,20 @@ class AgentServer(backend.util.service.AppProcess):
 
     @staticmethod
     async def test_create_store_listing(
-        request: backend.server.v2.store.model.StoreSubmissionRequest, user_id: str
+        request: backend.api.features.store.model.StoreSubmissionRequest, user_id: str
     ):
-        return await backend.server.v2.store.routes.create_submission(request, user_id)
+        return await backend.api.features.store.routes.create_submission(
+            request, user_id
+        )
 
     ### ADMIN ###
 
     @staticmethod
     async def test_review_store_listing(
-        request: backend.server.v2.store.model.ReviewSubmissionRequest,
+        request: backend.api.features.store.model.ReviewSubmissionRequest,
         user_id: str,
     ):
-        return await backend.server.v2.admin.store_admin_routes.review_submission(
+        return await backend.api.features.admin.store_admin_routes.review_submission(
             request.store_listing_version_id, request, user_id
         )
 
@@ -469,10 +494,7 @@ class AgentServer(backend.util.service.AppProcess):
         provider: ProviderName,
         credentials: Credentials,
     ) -> Credentials:
-        from backend.server.integrations.router import (
-            create_credentials,
-            get_credential,
-        )
+        from .features.integrations.router import create_credentials, get_credential
 
         try:
             return await create_credentials(