fix(enterprise): Update GitLab resolver tests for new background_tasks parameter

Update existing GitLab resolver tests to pass the new background_tasks
parameter after adding event forwarding support to gitlab_events endpoint.

Co-authored-by: openhands <openhands@all-hands.dev>

.agents/skills/update-sdk/references/docker-image-locations.md

@@ -46,12 +46,34 @@ These files contain image tags that **must** be updated whenever the SDK version
 ### `openhands/version.py`
 - Reads version from `pyproject.toml` at runtime → `openhands.__version__`
 
+### `openhands/resolver/issue_resolver.py`
+- Builds `ghcr.io/openhands/runtime:{openhands.__version__}-nikolaik` dynamically
+
+### `openhands/runtime/utils/runtime_build.py`
+- Base repo URL `ghcr.io/openhands/runtime` is a constant; version comes from elsewhere
+
 ### `.github/scripts/update_pr_description.sh`
 - Uses `${SHORT_SHA}` variable at CI runtime, not hardcoded
 
 ### `enterprise/Dockerfile`
 - `ARG BASE="ghcr.io/openhands/openhands"` — base image, version supplied at build time
 
+## V0 Legacy Files (separate update cadence)
+
+These reference the V0 runtime image (`ghcr.io/openhands/runtime:X.Y-nikolaik`) for local Docker/Kubernetes paths. They are **not** updated as part of a V1 release but may be updated independently.
+
+### `Development.md`
+- `export SANDBOX_RUNTIME_CONTAINER_IMAGE=ghcr.io/openhands/runtime:X.Y-nikolaik`
+
+### `openhands/runtime/impl/kubernetes/README.md`
+- `runtime_container_image = "docker.openhands.dev/openhands/runtime:X.Y-nikolaik"`
+
+### `enterprise/enterprise_local/README.md`
+- Uses `ghcr.io/openhands/runtime:main-nikolaik` (points to `main`, not versioned)
+
+### `third_party/runtime/impl/daytona/README.md`
+- Uses `${OPENHANDS_VERSION}` variable, not hardcoded
+
 ## Image Registries
 
 | Registry | Usage |

.github/workflows/e2e-tests.yml

@@ -0,0 +1,228 @@
+name: End-to-End Tests
+
+on:
+  pull_request:
+    types: [opened, synchronize, reopened, labeled]
+    branches:
+      - main
+      - develop
+  workflow_dispatch:
+
+jobs:
+  e2e-tests:
+    if: contains(github.event.pull_request.labels.*.name, 'end-to-end') || github.event_name == 'workflow_dispatch'
+    runs-on: ubuntu-latest
+    timeout-minutes: 60
+
+    env:
+      GITHUB_REPO_NAME: ${{ github.repository }}
+
+    steps:
+      - name: Checkout code
+        uses: actions/checkout@v6
+
+      - name: Install poetry via pipx
+        uses: abatilo/actions-poetry@v4
+        with:
+          poetry-version: 2.1.3
+
+      - name: Set up Python
+        uses: actions/setup-python@v6
+        with:
+          python-version: '3.12'
+          cache: 'poetry'
+
+      - name: Install system dependencies
+        run: |
+          sudo apt-get update
+          sudo apt-get install -y libgtk-3-0 libnotify4 libnss3 libxss1 libxtst6 xauth xvfb libgbm1 libasound2t64 netcat-openbsd
+
+      - name: Setup Node.js
+        uses: actions/setup-node@v6
+        with:
+          node-version: '22'
+          cache: 'npm'
+          cache-dependency-path: 'frontend/package-lock.json'
+
+      - name: Setup environment for end-to-end tests
+        run: |
+          # Create test results directory
+          mkdir -p test-results
+
+          # Create downloads directory for OpenHands (use a directory in the home folder)
+          mkdir -p $HOME/downloads
+          sudo chown -R $USER:$USER $HOME/downloads
+          sudo chmod -R 755 $HOME/downloads
+
+      - name: Build OpenHands
+        env:
+          GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
+          LLM_MODEL: ${{ secrets.LLM_MODEL || 'gpt-4o' }}
+          LLM_API_KEY: ${{ secrets.LLM_API_KEY || 'test-key' }}
+          LLM_BASE_URL: ${{ secrets.LLM_BASE_URL }}
+          INSTALL_DOCKER: 1
+          RUNTIME: docker
+          FRONTEND_PORT: 12000
+          FRONTEND_HOST: 0.0.0.0
+          BACKEND_HOST: 0.0.0.0
+          BACKEND_PORT: 3000
+          ENABLE_BROWSER: true
+          INSTALL_PLAYWRIGHT: 1
+        run: |
+          # Fix poetry.lock file if needed
+          echo "Fixing poetry.lock file if needed..."
+          poetry lock
+
+          # Build OpenHands using make build
+          echo "Running make build..."
+          make build
+
+          # Install Chromium Headless Shell for Playwright (needed for pytest-playwright)
+          echo "Installing Chromium Headless Shell for Playwright..."
+          poetry run playwright install chromium-headless-shell
+
+          # Verify Playwright browsers are installed (for e2e tests only)
+          echo "Verifying Playwright browsers installation for e2e tests..."
+          BROWSER_CHECK=$(poetry run python tests/e2e/check_playwright.py 2>/dev/null)
+
+          if [ "$BROWSER_CHECK" != "chromium_found" ]; then
+            echo "ERROR: Chromium browser not found or not working for e2e tests"
+            echo "$BROWSER_CHECK"
+            exit 1
+          else
+            echo "Playwright browsers are properly installed for e2e tests."
+          fi
+
+          # Docker runtime will handle workspace directory creation
+
+          # Start the application using make run with custom parameters and reduced logging
+          echo "Starting OpenHands using make run..."
+          # Set environment variables to reduce logging verbosity
+          export PYTHONUNBUFFERED=1
+          export LOG_LEVEL=WARNING
+          export UVICORN_LOG_LEVEL=warning
+          export OPENHANDS_LOG_LEVEL=WARNING
+          FRONTEND_PORT=12000 FRONTEND_HOST=0.0.0.0 BACKEND_HOST=0.0.0.0 make run > /tmp/openhands-e2e-test.log 2>&1 &
+
+          # Store the PID of the make run process
+          MAKE_PID=$!
+          echo "OpenHands started with PID: $MAKE_PID"
+
+          # Wait for the application to start
+          echo "Waiting for OpenHands to start..."
+          max_attempts=15
+          attempt=1
+
+          while [ $attempt -le $max_attempts ]; do
+            echo "Checking if OpenHands is running (attempt $attempt of $max_attempts)..."
+
+            # Check if the process is still running
+            if ! ps -p $MAKE_PID > /dev/null; then
+              echo "ERROR: OpenHands process has terminated unexpectedly"
+              echo "Last 50 lines of the log:"
+              tail -n 50 /tmp/openhands-e2e-test.log
+              exit 1
+            fi
+
+            # Check if frontend port is open
+            if nc -z localhost 12000; then
+              # Verify we can get HTML content
+              if curl -s http://localhost:12000 | grep -q "<html"; then
+                echo "SUCCESS: OpenHands is running and serving HTML content on port 12000"
+                break
+              else
+                echo "Port 12000 is open but not serving HTML content yet"
+              fi
+            else
+              echo "Frontend port 12000 is not open yet"
+            fi
+
+            # Show log output on each attempt
+            echo "Recent log output:"
+            tail -n 20 /tmp/openhands-e2e-test.log
+
+            # Wait before next attempt
+            echo "Waiting 10 seconds before next check..."
+            sleep 10
+            attempt=$((attempt + 1))
+
+            # Exit if we've reached the maximum number of attempts
+            if [ $attempt -gt $max_attempts ]; then
+              echo "ERROR: OpenHands failed to start after $max_attempts attempts"
+              echo "Last 50 lines of the log:"
+              tail -n 50 /tmp/openhands-e2e-test.log
+              exit 1
+            fi
+          done
+
+          # Final verification that the app is running
+          if ! nc -z localhost 12000 || ! curl -s http://localhost:12000 | grep -q "<html"; then
+            echo "ERROR: OpenHands is not running properly on port 12000"
+            echo "Last 50 lines of the log:"
+            tail -n 50 /tmp/openhands-e2e-test.log
+            exit 1
+          fi
+
+          # Print success message
+          echo "OpenHands is running successfully on port 12000"
+
+      - name: Run end-to-end tests
+        env:
+          GITHUB_TOKEN: ${{ secrets.E2E_TEST_GITHUB_TOKEN }}
+          LLM_MODEL: ${{ secrets.LLM_MODEL || 'gpt-4o' }}
+          LLM_API_KEY: ${{ secrets.LLM_API_KEY || 'test-key' }}
+          LLM_BASE_URL: ${{ secrets.LLM_BASE_URL }}
+        run: |
+          # Check if the application is running
+          if ! nc -z localhost 12000; then
+            echo "ERROR: OpenHands is not running on port 12000"
+            echo "Last 50 lines of the log:"
+            tail -n 50 /tmp/openhands-e2e-test.log
+            exit 1
+          fi
+
+          # Run the tests with detailed output
+          cd tests/e2e
+          poetry run python -m pytest \
+            test_settings.py::test_github_token_configuration \
+            test_conversation.py::test_conversation_start \
+            test_browsing_catchphrase.py::test_browsing_catchphrase \
+            test_multi_conversation_resume.py::test_multi_conversation_resume \
+            -v --no-header --capture=no --timeout=900
+
+      - name: Upload test results
+        if: always()
+        uses: actions/upload-artifact@v7
+        with:
+          name: playwright-report
+          path: tests/e2e/test-results/
+          retention-days: 30
+
+      - name: Upload OpenHands logs
+        if: always()
+        uses: actions/upload-artifact@v7
+        with:
+          name: openhands-logs
+          path: |
+            /tmp/openhands-e2e-test.log
+            /tmp/openhands-e2e-build.log
+            /tmp/openhands-backend.log
+            /tmp/openhands-frontend.log
+            /tmp/backend-health-check.log
+            /tmp/frontend-check.log
+            /tmp/vite-config.log
+            /tmp/makefile-contents.log
+          retention-days: 30
+
+      - name: Cleanup
+        if: always()
+        run: |
+          # Stop OpenHands processes
+          echo "Stopping OpenHands processes..."
+          pkill -f "python -m openhands.server" || true
+          pkill -f "npm run dev" || true
+          pkill -f "make run" || true
+
+          # Print process status for debugging
+          echo "Checking if any OpenHands processes are still running:"
+          ps aux | grep -E "openhands|npm run dev" || true

.github/workflows/pr-review-by-openhands.yml

@@ -2,14 +2,12 @@
 name: PR Review by OpenHands
 
 on:
-    # Use pull_request for same-repo PRs so workflow changes can self-verify in PRs.
+    # TEMPORARY MITIGATION (Clinejection hardening)
+    #
+    # We temporarily avoid `pull_request_target` here. We'll restore it after the PR review
+    # workflow is fully hardened for untrusted execution.
     pull_request:
         types: [opened, ready_for_review, labeled, review_requested]
-    # Use pull_request_target for fork PRs.
-    # The bot token used here is intentionally scoped to PR review operations,
-    # so the remaining blast radius is bounded even though PR content is untrusted.
-    pull_request_target:
-        types: [opened, ready_for_review, labeled, review_requested]
 
 permissions:
     contents: read
@@ -18,33 +16,13 @@ permissions:
 
 jobs:
     pr-review:
-        # Run on same-repo PRs via pull_request and on fork PRs via pull_request_target.
-        # Trigger when one of the following conditions is met:
-        #   1. A new non-draft PR is opened by a non-first-time contributor, OR
-        #   2. A draft PR is converted to ready for review by a non-first-time contributor, OR
-        #   3. The 'review-this' label is added, OR
-        #   4. openhands-agent or all-hands-bot is requested as a reviewer
-        # Note: FIRST_TIME_CONTRIBUTOR and NONE PRs require manual trigger via label/reviewer request.
-        # Trigger logic:
-        #   1. Route same-repo PRs through `pull_request` and fork PRs through `pull_request_target`
-        #   2. Auto-trigger on `opened` / `ready_for_review` for non-first-time contributors
-        #   3. Always allow manual triggers via `review-this` or reviewer request
-        # The author association check is duplicated intentionally for both
-        # auto-triggered actions (`opened` and `ready_for_review`).
+        # Note: fork PRs will not have access to repository secrets under `pull_request`.
+        # Skip forks to avoid noisy failures until we restore a hardened `pull_request_target` flow.
         if: |
+            github.event.pull_request.head.repo.full_name == github.repository &&
             (
-                (
-                    github.event_name == 'pull_request' &&
-                    github.event.pull_request.head.repo.full_name == github.repository
-                ) ||
-                (
-                    github.event_name == 'pull_request_target' &&
-                    github.event.pull_request.head.repo.full_name != github.repository
-                )
-            ) &&
-            (
-                (github.event.action == 'opened' && github.event.pull_request.draft == false && github.event.pull_request.author_association != 'FIRST_TIME_CONTRIBUTOR' && github.event.pull_request.author_association != 'NONE') ||
-                (github.event.action == 'ready_for_review' && github.event.pull_request.author_association != 'FIRST_TIME_CONTRIBUTOR' && github.event.pull_request.author_association != 'NONE') ||
+                (github.event.action == 'opened' && github.event.pull_request.draft == false) ||
+                github.event.action == 'ready_for_review' ||
                 (github.event.action == 'labeled' && github.event.label.name == 'review-this') ||
                 (
                     github.event.action == 'review_requested' &&

.github/workflows/py-tests.yml

@@ -60,6 +60,10 @@ jobs:
         run: PYTHONPATH=".:$PYTHONPATH" poetry run pytest --forked -n auto -s ./tests/unit --cov=openhands --cov-branch
         env:
           COVERAGE_FILE: ".coverage.${{ matrix.python_version }}"
+      - name: Run Runtime Tests with CLIRuntime
+        run: PYTHONPATH=".:$PYTHONPATH" TEST_RUNTIME=cli poetry run pytest -n 5 --reruns 2 --reruns-delay 3 -s tests/runtime/test_bash.py --cov=openhands --cov-branch
+        env:
+          COVERAGE_FILE: ".coverage.runtime.${{ matrix.python_version }}"
       - name: Store coverage file
         uses: actions/upload-artifact@v7
         with:

AGENTS.md

@@ -27,7 +27,7 @@ Before pushing any changes, you MUST ensure that any lint errors or simple test
 
 * If you've made changes to the backend, you should run `pre-commit run --config ./dev_config/python/.pre-commit-config.yaml` (this will run on staged files).
 * If you've made changes to the frontend, you should run `cd frontend && npm run lint:fix && npm run build ; cd ..`
-* If you've made changes to the VSCode extension, you should run `cd openhands/app_server/integrations/vscode && npm run lint:fix && npm run compile ; cd ../../..`
+* If you've made changes to the VSCode extension, you should run `cd openhands/integrations/vscode && npm run lint:fix && npm run compile ; cd ../../..`
 
 The pre-commit hooks MUST pass successfully before pushing any changes to the repository. This is a mandatory requirement to maintain code quality and consistency.
 
@@ -150,7 +150,7 @@ Frontend:
 
 
 VSCode Extension:
-- Located in the `openhands/app_server/integrations/vscode` directory
+- Located in the `openhands/integrations/vscode` directory
 - Setup: Run `npm install` in the extension directory
 - Linting:
   - Run linting with fixes: `npm run lint:fix`
@@ -284,32 +284,6 @@ If you are starting a pull request (PR), please follow the template in `.github/
 
 These details may or may not be useful for your current task.
 
-### Conversation State Management
-
-#### Agent State and Sandbox Status:
-The frontend uses `useAgentState` hook (`frontend/src/hooks/use-agent-state.ts`) to determine the current conversation state. This hook:
-- Returns `curAgentState` (AgentState enum) for UI state determination
-- Returns `isArchived` flag when `sandbox_status === "MISSING"` (archived conversations)
-- Prioritizes live WebSocket execution status over cached API data
-
-#### Archived Conversations (sandbox_status === "MISSING"):
-When a conversation's sandbox is no longer available (archived):
-- `useAgentState` returns `AgentState.STOPPED` and `isArchived: true`
-- Chat input is replaced with an archived banner (`ArchivedBanner` component)
-- VS Code tab, Terminal, and Planner show read-only messages instead of loading states
-- All interactive elements that require a running sandbox are disabled
-
-#### Testing useAgentState:
-When mocking `useAgentState` in tests, always include the `isArchived` property:
-```typescript
-vi.mock("#/hooks/use-agent-state", () => ({
-  useAgentState: () => ({
-    curAgentState: AgentState.AWAITING_USER_INPUT,
-    isArchived: false,
-  }),
-}));
-```
-
 ### Microagents
 
 Microagents are specialized prompts that enhance OpenHands with domain-specific knowledge and task-specific workflows. They are Markdown files that can include frontmatter for configuration.
@@ -389,7 +363,6 @@ There are two main patterns for saving settings in the OpenHands frontend:
 **When to use each pattern:**
 - Use Pattern 1 (Immediate Save) for entity management where each item is independent
 - Use Pattern 2 (Manual Save) for configuration forms where settings are interdependent or need validation
-- Git provider tokens in the local/OSS integrations settings are managed through the V1 secrets endpoints (`POST`/`DELETE /api/v1/secrets/git-providers`). Do not reuse the logout flow for disconnecting tokens; `useLogout` is for actual app logout and still targets legacy OSS logout behavior.
 
 ### Adding New LLM Models
 

CONTRIBUTING.md

@@ -36,6 +36,7 @@ Full details in our [Development Guide](./Development.md).
 
 - **[Frontend](./frontend/README.md)** - React application
 - **[App Server (V1)](./openhands/app_server/README.md)** - Current FastAPI application server and REST API modules
+- **[Runtime](./openhands/runtime/README.md)** - Execution environments
 - **[Evaluation](https://github.com/OpenHands/benchmarks)** - Testing and benchmarks
 
 ## What Can You Build?

CREDITS.md

@@ -16,7 +16,7 @@ open source community:
 
 #### [Aider](https://github.com/paul-gauthier/aider)
    - License: Apache License 2.0
-   - Description: AI pair programming tool. OpenHands has adapted and integrated its linter module for code-related tasks.
+   - Description: AI pair programming tool. OpenHands has adapted and integrated its linter module for code-related tasks in [`agentskills utilities`](https://github.com/OpenHands/OpenHands/tree/main/openhands/runtime/plugins/agent_skills/utils/aider)
 
 #### [BrowserGym](https://github.com/ServiceNow/BrowserGym)
    - License: Apache License 2.0

Development.md

@@ -309,6 +309,16 @@ poetry run pytest ./tests/unit/test_*.py
 
 ---
 
+## Using Existing Docker Images
+
+To reduce build time, you can use an existing runtime image:
+
+```bash
+export SANDBOX_RUNTIME_CONTAINER_IMAGE=ghcr.io/openhands/runtime:1.2-nikolaik
+```
+
+---
+
 ## Help
 
 ```bash
@@ -329,3 +339,4 @@ make help
 - [/tests/unit/README.md](./tests/unit/README.md): Guide to writing and running unit tests
 - [OpenHands/benchmarks](https://github.com/OpenHands/benchmarks): Documentation for the evaluation framework and benchmarks
 - [/skills/README.md](./skills/README.md): Information about the skills architecture and implementation
+- [/openhands/runtime/README.md](./openhands/runtime/README.md): Documentation for the runtime environment and execution model

containers/app/Dockerfile

@@ -88,6 +88,7 @@ USER openhands
 
 COPY --chown=openhands:openhands --chmod=770 ./skills ./skills
 COPY --chown=openhands:openhands --chmod=770 ./openhands ./openhands
+COPY --chown=openhands:openhands --chmod=777 ./openhands/runtime/plugins ./openhands/runtime/plugins
 COPY --chown=openhands:openhands pyproject.toml poetry.lock README.md MANIFEST.in LICENSE ./
 
 # Add this line to set group ownership of all files/directories not already in "app" group

containers/app/entrypoint.sh

@@ -23,6 +23,18 @@ if [ -z "$WORKSPACE_MOUNT_PATH" ]; then
   unset WORKSPACE_BASE
 fi
 
+if [[ "$INSTALL_THIRD_PARTY_RUNTIMES" == "true" ]]; then
+  echo "Downloading and installing third_party_runtimes..."
+  echo "Warning: Third-party runtimes are provided as-is, not actively supported and may be removed in future releases."
+
+  if pip install 'openhands-ai[third_party_runtimes]' -qqq 2> >(tee /dev/stderr); then
+    echo "third_party_runtimes installed successfully."
+  else
+    echo "Failed to install third_party_runtimes." >&2
+    exit 1
+  fi
+fi
+
 if [[ "$SANDBOX_USER_ID" -eq 0 ]]; then
   echo "Running OpenHands as root"
   export RUN_AS_OPENHANDS=false

dev_config/python/.pre-commit-config.yaml

@@ -3,9 +3,9 @@ repos:
     rev: v5.0.0
     hooks:
       - id: trailing-whitespace
-        exclude: ^(docs/|modules/|python/|openhands-ui/|enterprise/)
+        exclude: ^(docs/|modules/|python/|openhands-ui/|third_party/|enterprise/)
       - id: end-of-file-fixer
-        exclude: ^(docs/|modules/|python/|openhands-ui/|enterprise/)
+        exclude: ^(docs/|modules/|python/|openhands-ui/|third_party/|enterprise/)
       - id: check-yaml
         args: ["--allow-multiple-documents"]
       - id: debug-statements
@@ -37,12 +37,12 @@ repos:
         entry: ruff check --config dev_config/python/ruff.toml
         types_or: [python, pyi, jupyter]
         args: [--fix, --unsafe-fixes]
-        exclude: ^(enterprise/)
+        exclude: ^(third_party/|enterprise/)
       # Run the formatter.
       - id: ruff-format
         entry: ruff format --config dev_config/python/ruff.toml
         types_or: [python, pyi, jupyter]
-        exclude: ^(enterprise/)
+        exclude: ^(third_party/|enterprise/)
 
   - repo: https://github.com/pre-commit/mirrors-mypy
     rev: v1.15.0

dev_config/python/mypy.ini

@@ -10,7 +10,7 @@ strict_optional = True
 disable_error_code = type-abstract
 
 # Exclude third-party runtime directory from type checking
-exclude = (enterprise/)
+exclude = (third_party/|enterprise/)
 
 [mypy-openai.*]
 follow_imports = skip

dev_config/python/ruff.toml

@@ -1,5 +1,5 @@
 # Exclude third-party runtime directory from linting
-exclude = ["enterprise/"]
+exclude = ["third_party/", "enterprise/"]
 
 [lint]
 select = [

enterprise/enterprise_local/README.md

@@ -61,6 +61,13 @@ export LITE_LLM_API_KEY=<your LLM API key>
 python enterprise_local/convert_to_env.py
 ```
 
+You'll also need to set up the runtime image, so that the dev server doesn't try to rebuild it.
+
+```
+export SANDBOX_RUNTIME_CONTAINER_IMAGE=ghcr.io/openhands/runtime:main-nikolaik
+docker pull $SANDBOX_RUNTIME_CONTAINER_IMAGE
+```
+
 By default the application will log in json, you can override.
 
 ```
@@ -196,6 +203,7 @@ And then invoking `printenv`. NOTE: _DO NOT DO THIS WITH PROD!!!_ (Hopefully by
                 "REDIS_HOST": "localhost:6379",
                 "OPENHANDS": "<YOUR LOCAL OPENHANDS DIR>",
                 "FRONTEND_DIRECTORY": "<YOUR LOCAL OPENHANDS DIR>/frontend/build",
+                "SANDBOX_RUNTIME_CONTAINER_IMAGE": "ghcr.io/openhands/runtime:main-nikolaik",
                 "FILE_STORE_PATH": "<YOUR HOME DIRECTORY>>/.openhands-state",
                 "OPENHANDS_CONFIG_CLS": "server.config.SaaSServerConfig",
                 "GITHUB_APP_ID": "1062351",
@@ -229,6 +237,7 @@ And then invoking `printenv`. NOTE: _DO NOT DO THIS WITH PROD!!!_ (Hopefully by
                 "REDIS_HOST": "localhost:6379",
                 "OPENHANDS": "<YOUR LOCAL OPENHANDS DIR>",
                 "FRONTEND_DIRECTORY": "<YOUR LOCAL OPENHANDS DIR>/frontend/build",
+                "SANDBOX_RUNTIME_CONTAINER_IMAGE": "ghcr.io/openhands/runtime:main-nikolaik",
                 "FILE_STORE_PATH": "<YOUR HOME DIRECTORY>>/.openhands-state",
                 "OPENHANDS_CONFIG_CLS": "server.config.SaaSServerConfig",
                 "GITHUB_APP_ID": "1062351",

enterprise/enterprise_local/convert_to_env.py

@@ -112,6 +112,9 @@ lines.append(
 lines.append(
     'OPENHANDS_BITBUCKET_DATA_CENTER_SERVICE_CLS=integrations.bitbucket_data_center.bitbucket_dc_service.SaaSBitbucketDCService'
 )
+lines.append(
+    'OPENHANDS_CONVERSATION_VALIDATOR_CLS=storage.saas_conversation_validator.SaasConversationValidator'
+)
 lines.append('POSTHOG_CLIENT_KEY=test')
 lines.append('ENABLE_PROACTIVE_CONVERSATION_STARTERS=true')
 lines.append('MAX_CONCURRENT_CONVERSATIONS=10')

enterprise/integrations/bitbucket/bitbucket_service.py

@@ -1,11 +1,9 @@
 from pydantic import SecretStr
 from server.auth.token_manager import TokenManager
 
-from openhands.app_server.integrations.bitbucket.bitbucket_service import (
-    BitBucketService,
-)
-from openhands.app_server.integrations.service_types import ProviderType
 from openhands.core.logger import openhands_logger as logger
+from openhands.integrations.bitbucket.bitbucket_service import BitBucketService
+from openhands.integrations.service_types import ProviderType
 
 
 class SaaSBitBucketService(BitBucketService):

enterprise/integrations/bitbucket_data_center/bitbucket_dc_service.py

@@ -1,11 +1,11 @@
 from pydantic import SecretStr
 from server.auth.token_manager import TokenManager
 
-from openhands.app_server.integrations.bitbucket_data_center.bitbucket_dc_service import (
+from openhands.core.logger import openhands_logger as logger
+from openhands.integrations.bitbucket_data_center.bitbucket_dc_service import (
     BitbucketDCService,
 )
-from openhands.app_server.integrations.service_types import ProviderType
-from openhands.core.logger import openhands_logger as logger
+from openhands.integrations.service_types import ProviderType
 
 
 class SaaSBitbucketDCService(BitbucketDCService):

enterprise/integrations/github/data_collector.py

@@ -19,12 +19,12 @@ from server.auth.constants import GITHUB_APP_CLIENT_ID, GITHUB_APP_PRIVATE_KEY
 from storage.openhands_pr import OpenhandsPR
 from storage.openhands_pr_store import OpenhandsPRStore
 
-from openhands.app_server.conversation_paths import get_conversation_dir
-from openhands.app_server.file_store import get_file_store
-from openhands.app_server.integrations.github.github_service import GithubServiceImpl
-from openhands.app_server.integrations.service_types import ProviderType
 from openhands.core.config import load_openhands_config
 from openhands.core.logger import openhands_logger as logger
+from openhands.integrations.github.github_service import GithubServiceImpl
+from openhands.integrations.service_types import ProviderType
+from openhands.storage import get_file_store
+from openhands.storage.locations import get_conversation_dir
 
 config = load_openhands_config()
 file_store = get_file_store(config.file_store, config.file_store_path)
@@ -112,7 +112,7 @@ class GitHubDataCollector:
         suffix = path.format(repo_id, number)
 
         if conversation_id:
-            return f'{get_conversation_dir(conversation_id)}/{suffix}'
+            return f'{get_conversation_dir(conversation_id)}{suffix}'
 
         return suffix
 

enterprise/integrations/github/github_manager.py

@@ -2,6 +2,7 @@ from types import MappingProxyType
 
 from github import Auth, Github, GithubIntegration
 from integrations.github.data_collector import GitHubDataCollector
+from integrations.github.github_solvability import summarize_issue_solvability
 from integrations.github.github_view import (
     GithubFactory,
     GithubFailingAction,
@@ -19,6 +20,7 @@ from integrations.models import (
 from integrations.types import ResolverViewInterface
 from integrations.utils import (
     CONVERSATION_URL,
+    ENABLE_SOLVABILITY_ANALYSIS,
     HOST_URL,
     OPENHANDS_RESOLVER_TEMPLATES_DIR,
     get_session_expired_message,
@@ -31,15 +33,15 @@ from server.auth.auth_error import ExpiredError
 from server.auth.constants import GITHUB_APP_CLIENT_ID, GITHUB_APP_PRIVATE_KEY
 from server.auth.token_manager import TokenManager
 
-from openhands.app_server.integrations.provider import ProviderToken, ProviderType
-from openhands.app_server.integrations.service_types import AuthenticationError
-from openhands.app_server.secrets.secrets_models import Secrets
 from openhands.core.logger import openhands_logger as logger
+from openhands.integrations.provider import ProviderToken, ProviderType
+from openhands.integrations.service_types import AuthenticationError
 from openhands.server.types import (
     LLMAuthenticationError,
     MissingSettingsError,
     SessionExpiredError,
 )
+from openhands.storage.data_models.secrets import Secrets
 
 
 class GithubManager(Manager[GithubViewType]):
@@ -356,7 +358,26 @@ class GithubManager(Manager[GithubViewType]):
                     )
                 )
 
-                conversation_id = await github_view.initialize_new_conversation()
+                # We first initialize a conversation and generate the solvability report BEFORE starting the conversation runtime
+                # This helps us accumulate llm spend without requiring a running runtime. This setups us up for
+                #   1. If there is a problem starting the runtime we still have accumulated total conversation cost
+                #   2. In the future, based on the report confidence we can conditionally start the conversation
+                #   3. Once the conversation is started, its base cost will include the report's spend as well which allows us to control max budget per resolver task
+                convo_metadata = await github_view.initialize_new_conversation()
+                solvability_summary = None
+                if not ENABLE_SOLVABILITY_ANALYSIS:
+                    logger.info(
+                        '[Github]: Solvability report feature is disabled, skipping'
+                    )
+                else:
+                    try:
+                        solvability_summary = await summarize_issue_solvability(
+                            github_view, user_token
+                        )
+                    except Exception as e:
+                        logger.warning(
+                            f'[Github]: Error summarizing issue solvability: {str(e)}'
+                        )
 
                 saas_user_auth = await get_saas_user_auth(
                     github_view.user_info.keycloak_user_id, self.token_manager
@@ -365,21 +386,26 @@ class GithubManager(Manager[GithubViewType]):
                 await github_view.create_new_conversation(
                     self.jinja_env,
                     secret_store.provider_tokens,
-                    conversation_id,
+                    convo_metadata,
                     saas_user_auth,
                 )
 
-                conversation_id_hex = github_view.conversation_id
+                conversation_id = github_view.conversation_id
 
                 logger.info(
-                    f'[GitHub] Created conversation {conversation_id_hex} for user {user_info.username}'
+                    f'[GitHub] Created conversation {conversation_id} for user {user_info.username}'
                 )
 
                 # V1 callback processors are registered by the view during conversation creation
 
                 # Send message with conversation link
-                conversation_link = CONVERSATION_URL.format(conversation_id_hex)
-                msg_info = f"I'm on it! {user_info.username} can [track my progress at all-hands.dev]({conversation_link})"
+                conversation_link = CONVERSATION_URL.format(conversation_id)
+                base_msg = f"I'm on it! {user_info.username} can [track my progress at all-hands.dev]({conversation_link})"
+                # Combine messages: include solvability report with "I'm on it!" if successful
+                if solvability_summary:
+                    msg_info = f'{base_msg}\n\n{solvability_summary}'
+                else:
+                    msg_info = base_msg
 
             except MissingSettingsError as e:
                 logger.warning(

enterprise/integrations/github/github_service.py

@@ -4,9 +4,9 @@ from integrations.store_repo_utils import store_repositories_in_db
 from pydantic import SecretStr
 from server.auth.token_manager import TokenManager
 
-from openhands.app_server.integrations.github.github_service import GitHubService
-from openhands.app_server.integrations.service_types import ProviderType, Repository
 from openhands.core.logger import openhands_logger as logger
+from openhands.integrations.github.github_service import GitHubService
+from openhands.integrations.service_types import ProviderType, Repository
 from openhands.server.types import AppMode
 
 

enterprise/integrations/github/github_solvability.py

@@ -0,0 +1,188 @@
+import asyncio
+import time
+
+from github import Auth, Github
+from integrations.github.github_view import (
+    GithubInlinePRComment,
+    GithubIssueComment,
+    GithubPRComment,
+    GithubViewType,
+)
+from integrations.solvability.data import load_classifier
+from integrations.solvability.models.report import SolvabilityReport
+from integrations.solvability.models.summary import SolvabilitySummary
+from integrations.utils import ENABLE_SOLVABILITY_ANALYSIS
+from pydantic import ValidationError
+from server.config import get_config
+from storage.saas_settings_store import SaasSettingsStore
+
+from openhands.core.config import LLMConfig
+from openhands.core.logger import openhands_logger as logger
+from openhands.utils.async_utils import call_sync_from_async
+from openhands.utils.utils import create_registry_and_conversation_stats
+
+
+def fetch_github_issue_context(
+    github_view: GithubViewType,
+    user_token: str,
+) -> str:
+    """Fetch full GitHub issue/PR context including title, body, and comments.
+
+    Args:
+        full_repo_name: Full repository name in the format 'owner/repo'
+        issue_number: The issue or PR number
+        user_token: GitHub user access token
+        max_comments: Maximum number of comments to fetch (default: 10)
+        max_comment_length: Maximum length of each comment to include in the context (default: 500)
+
+    Returns:
+        A comprehensive string containing the issue/PR context
+    """
+
+    # Build context string
+    context_parts = []
+
+    # Add title and body
+    context_parts.append(f'Title: {github_view.title}')
+    context_parts.append(f'Description:\n{github_view.description}')
+
+    with Github(auth=Auth.Token(user_token)) as github_client:
+        repo = github_client.get_repo(github_view.full_repo_name)
+        issue = repo.get_issue(github_view.issue_number)
+        if issue.labels:
+            labels = [label.name for label in issue.labels]
+            context_parts.append(f"Labels: {', '.join(labels)}")
+
+    for comment in github_view.previous_comments:
+        context_parts.append(f'- {comment.author}: {comment.body}')
+
+    return '\n\n'.join(context_parts)
+
+
+async def summarize_issue_solvability(
+    github_view: GithubViewType,
+    user_token: str,
+    timeout: float = 60.0 * 5,
+) -> str:
+    """Generate a solvability summary for an issue using the resolver view interface.
+
+    Args:
+        resolver_view: A resolver view interface instance (e.g., GithubIssue, GithubPRComment)
+        user_token: GitHub user access token for API access
+        timeout: Maximum time in seconds to wait for the result (default: 60.0)
+
+    Returns:
+        The solvability summary as a string
+
+    Raises:
+        ValueError: If LLM settings cannot be found for the user
+        asyncio.TimeoutError: If the operation exceeds the specified timeout
+    """
+    if not ENABLE_SOLVABILITY_ANALYSIS:
+        raise ValueError('Solvability report feature is disabled')
+
+    if github_view.user_info.keycloak_user_id is None:
+        raise ValueError(
+            f'[Solvability] No user ID found for user {github_view.user_info.username}'
+        )
+
+    # Grab the user's information so we can load their LLM configuration
+    store = SaasSettingsStore(
+        user_id=github_view.user_info.keycloak_user_id,
+        config=get_config(),
+    )
+
+    user_settings = await store.load()
+
+    if user_settings is None:
+        raise ValueError(
+            f'[Solvability] No user settings found for user ID {github_view.user_info.user_id}'
+        )
+
+    # Check if solvability analysis is enabled for this user, exit early if
+    # needed
+    if not getattr(user_settings, 'enable_solvability_analysis', False):
+        raise ValueError(
+            f'Solvability analysis disabled for user {github_view.user_info.user_id}'
+        )
+
+    agent_settings = user_settings.agent_settings
+    llm_settings = agent_settings.llm
+    if llm_settings.api_key is None:
+        raise ValueError(
+            f'[Solvability] No LLM API key found for user {github_view.user_info.user_id}'
+        )
+
+    try:
+        llm_config = LLMConfig(
+            model=llm_settings.model,
+            api_key=llm_settings.api_key.get_secret_value(),
+            base_url=llm_settings.base_url,
+        )
+    except ValidationError as e:
+        raise ValueError(
+            f'[Solvability] Invalid LLM configuration for user {github_view.user_info.user_id}: {str(e)}'
+        )
+
+    # Fetch the full GitHub issue/PR context using the GitHub API
+    start_time = time.time()
+    issue_context = fetch_github_issue_context(github_view, user_token)
+    logger.info(
+        f'[Solvability] Grabbed issue context for {github_view.conversation_id}',
+        extra={
+            'conversation_id': github_view.conversation_id,
+            'response_latency': time.time() - start_time,
+            'full_repo_name': github_view.full_repo_name,
+            'issue_number': github_view.issue_number,
+        },
+    )
+
+    # For comment-based triggers, also include the specific comment that triggered the action
+    if isinstance(
+        github_view, (GithubIssueComment, GithubPRComment, GithubInlinePRComment)
+    ):
+        issue_context += f'\n\nTriggering Comment:\n{github_view.comment_body}'
+
+    solvability_classifier = load_classifier('default-classifier')
+
+    async with asyncio.timeout(timeout):
+        solvability_report: SolvabilityReport = await call_sync_from_async(
+            lambda: solvability_classifier.solvability_report(
+                issue_context, llm_config=llm_config
+            )
+        )
+
+        logger.info(
+            f'[Solvability] Generated report for {github_view.conversation_id}',
+            extra={
+                'conversation_id': github_view.conversation_id,
+                'report': solvability_report.model_dump(exclude=['issue']),
+            },
+        )
+
+        llm_registry, conversation_stats, _ = create_registry_and_conversation_stats(
+            get_config(),
+            github_view.conversation_id,
+            github_view.user_info.keycloak_user_id,
+            None,
+        )
+
+        solvability_summary = await call_sync_from_async(
+            lambda: SolvabilitySummary.from_report(
+                solvability_report,
+                llm=llm_registry.get_llm(
+                    service_id='solvability_analysis', config=llm_config
+                ),
+            )
+        )
+        conversation_stats.save_metrics()
+
+        logger.info(
+            f'[Solvability] Generated summary for {github_view.conversation_id}',
+            extra={
+                'conversation_id': github_view.conversation_id,
+                'summary': solvability_summary.model_dump(exclude=['content']),
+            },
+        )
+
+        return solvability_summary.format_as_markdown()

enterprise/integrations/github/github_view.py

@@ -14,9 +14,11 @@ from integrations.resolver_org_router import resolve_org_for_repo
 from integrations.types import ResolverViewInterface, UserData
 from integrations.utils import (
     ENABLE_PROACTIVE_CONVERSATION_STARTERS,
+    ENABLE_V1_GITHUB_RESOLVER,
     HOST,
     HOST_URL,
     get_oh_labels,
+    get_user_v1_enabled_setting,
     has_exact_mention,
 )
 from jinja2 import Environment
@@ -25,28 +27,37 @@ from server.auth.token_manager import TokenManager
 from server.config import get_config
 from storage.org_store import OrgStore
 from storage.proactive_conversation_store import ProactiveConversationStore
+from storage.saas_conversation_store import SaasConversationStore
 from storage.saas_secrets_store import SaasSecretsStore
 
 from openhands.agent_server.models import SendMessageRequest
 from openhands.app_server.app_conversation.app_conversation_models import (
     AppConversationStartRequest,
     AppConversationStartTaskStatus,
-    ConversationTrigger,
 )
 from openhands.app_server.config import get_app_conversation_service
-from openhands.app_server.integrations.github.github_service import GithubServiceImpl
-from openhands.app_server.integrations.provider import PROVIDER_TOKEN_TYPE, ProviderType
-from openhands.app_server.integrations.service_types import Comment
 from openhands.app_server.services.injector import InjectorState
 from openhands.app_server.user.specifiy_user_context import USER_CONTEXT_ATTR
-from openhands.app_server.user_auth.user_auth import UserAuth
 from openhands.core.logger import openhands_logger as logger
+from openhands.integrations.github.github_service import GithubServiceImpl
+from openhands.integrations.provider import PROVIDER_TOKEN_TYPE, ProviderType
+from openhands.integrations.service_types import Comment
 from openhands.sdk import TextContent
+from openhands.server.user_auth.user_auth import UserAuth
+from openhands.storage.data_models.conversation_metadata import (
+    ConversationMetadata,
+    ConversationTrigger,
+)
 from openhands.utils.async_utils import call_sync_from_async
+from openhands.utils.conversation_summary import get_default_conversation_title
 
 OH_LABEL, INLINE_OH_LABEL = get_oh_labels(HOST)
 
 
+async def is_v1_enabled_for_github_resolver(user_id: str) -> bool:
+    return await get_user_v1_enabled_setting(user_id) and ENABLE_V1_GITHUB_RESOLVER
+
+
 async def get_user_proactive_conversation_setting(user_id: str | None) -> bool:
     """Get the user's proactive conversation setting.
 
@@ -94,6 +105,7 @@ class GithubIssue(ResolverViewInterface):
     title: str
     description: str
     previous_comments: list[Comment]
+    v1_enabled: bool
 
     def _get_branch_name(self) -> str | None:
         return getattr(self, 'branch_name', None)
@@ -140,7 +152,11 @@ class GithubIssue(ResolverViewInterface):
 
         return user_secrets.custom_secrets if user_secrets else None
 
-    async def initialize_new_conversation(self) -> UUID:
+    async def initialize_new_conversation(self) -> ConversationMetadata:
+        self.v1_enabled = await is_v1_enabled_for_github_resolver(
+            self.user_info.keycloak_user_id
+        )
+
         # Resolve target org based on claimed git organizations
         self.resolved_org_id = await resolve_org_for_repo(
             provider='github',
@@ -148,20 +164,54 @@ class GithubIssue(ResolverViewInterface):
             keycloak_user_id=self.user_info.keycloak_user_id,
         )
 
-        # All conversations use V1 app conversation service
-        conversation_id = uuid4()
-        self.conversation_id = conversation_id.hex
-        return conversation_id
+        logger.info(
+            f'[GitHub V1]: User flag found for {self.user_info.keycloak_user_id} is {self.v1_enabled}'
+        )
+        if self.v1_enabled:
+            # Create dummy conversationm metadata
+            # Don't save to conversation store
+            # V1 conversations are stored in a separate table
+            self.conversation_id = uuid4().hex
+            return ConversationMetadata(
+                conversation_id=self.conversation_id,
+                selected_repository=self.full_repo_name,
+            )
+
+        # Create the conversation store with resolver org routing
+        # (bypasses initialize_conversation to avoid threading enterprise-only
+        # resolver_org_id through the generic OSS interface)
+        store = await SaasConversationStore.get_resolver_instance(
+            get_config(),
+            self.user_info.keycloak_user_id,
+            self.resolved_org_id,
+        )
+
+        conversation_id = uuid4().hex
+        conversation_metadata = ConversationMetadata(
+            trigger=ConversationTrigger.RESOLVER,
+            conversation_id=conversation_id,
+            title=get_default_conversation_title(conversation_id),
+            user_id=self.user_info.keycloak_user_id,
+            selected_repository=self.full_repo_name,
+            selected_branch=self._get_branch_name(),
+            git_provider=ProviderType.GITHUB,
+        )
+        await store.save_metadata(conversation_metadata)
+
+        self.conversation_id = conversation_id
+        return conversation_metadata
 
     async def create_new_conversation(
         self,
         jinja_env: Environment,
         git_provider_tokens: PROVIDER_TOKEN_TYPE,
-        conversation_id: UUID,
+        conversation_metadata: ConversationMetadata,
         saas_user_auth: UserAuth,
     ):
         # V0 conversation path has been removed - all conversations use V1 app conversation service
-        await self._create_v1_conversation(jinja_env, saas_user_auth, conversation_id)
+        await self._create_v1_conversation(
+            jinja_env, saas_user_auth, conversation_metadata
+        )
 
     async def _get_v1_initial_user_message(self, jinja_env: Environment) -> str:
         """Build the initial user message for V1 resolver conversations.
@@ -189,7 +239,7 @@ class GithubIssue(ResolverViewInterface):
         self,
         jinja_env: Environment,
         saas_user_auth: UserAuth,
-        conversation_id: UUID,
+        conversation_metadata: ConversationMetadata,
     ):
         """Create conversation using the new V1 app conversation system."""
         logger.info('[GitHub V1]: Creating V1 conversation')
@@ -209,7 +259,7 @@ class GithubIssue(ResolverViewInterface):
 
         # Create the V1 conversation start request with the callback processor
         start_request = AppConversationStartRequest(
-            conversation_id=conversation_id,
+            conversation_id=UUID(conversation_metadata.conversation_id),
             # NOTE: Resolver instructions are intended to be lower priority than the
             # system prompt, so we inject them into the initial user message.
             system_message_suffix=None,
@@ -763,6 +813,7 @@ class GithubFactory:
                 title='',
                 description='',
                 previous_comments=[],
+                v1_enabled=False,
             )
 
         elif GithubFactory.is_issue_comment(message):
@@ -788,6 +839,7 @@ class GithubFactory:
                 title='',
                 description='',
                 previous_comments=[],
+                v1_enabled=False,
             )
 
         elif GithubFactory.is_pr_comment(message):
@@ -829,6 +881,7 @@ class GithubFactory:
                 title='',
                 description='',
                 previous_comments=[],
+                v1_enabled=False,
             )
 
         elif GithubFactory.is_inline_pr_comment(message):
@@ -862,6 +915,7 @@ class GithubFactory:
                 title='',
                 description='',
                 previous_comments=[],
+                v1_enabled=False,
             )
 
         else:

enterprise/integrations/gitlab/gitlab_manager.py

@@ -25,15 +25,15 @@ from jinja2 import Environment, FileSystemLoader
 from pydantic import SecretStr
 from server.auth.token_manager import TokenManager
 
-from openhands.app_server.integrations.gitlab.gitlab_service import GitLabServiceImpl
-from openhands.app_server.integrations.provider import ProviderToken, ProviderType
-from openhands.app_server.secrets.secrets_models import Secrets
 from openhands.core.logger import openhands_logger as logger
+from openhands.integrations.gitlab.gitlab_service import GitLabServiceImpl
+from openhands.integrations.provider import ProviderToken, ProviderType
 from openhands.server.types import (
     LLMAuthenticationError,
     MissingSettingsError,
     SessionExpiredError,
 )
+from openhands.storage.data_models.secrets import Secrets
 
 
 class GitlabManager(Manager[GitlabViewType]):
@@ -208,8 +208,8 @@ class GitlabManager(Manager[GitlabViewType]):
                     )
                 )
 
-                # Initialize conversation and get UUID
-                conversation_id = await gitlab_view.initialize_new_conversation()
+                # Initialize conversation and get metadata (following GitHub pattern)
+                convo_metadata = await gitlab_view.initialize_new_conversation()
 
                 saas_user_auth = await get_saas_user_auth(
                     gitlab_view.user_info.keycloak_user_id, self.token_manager
@@ -218,19 +218,19 @@ class GitlabManager(Manager[GitlabViewType]):
                 await gitlab_view.create_new_conversation(
                     self.jinja_env,
                     secret_store.provider_tokens,
-                    conversation_id,
+                    convo_metadata,
                     saas_user_auth,
                 )
 
-                conversation_id_hex = gitlab_view.conversation_id
+                conversation_id = gitlab_view.conversation_id
 
                 logger.info(
-                    f'[GitLab] Created conversation {conversation_id_hex} for user {user_info.username}'
+                    f'[GitLab] Created conversation {conversation_id} for user {user_info.username}'
                 )
 
                 # V1 callback processors are registered by the view during conversation creation
 
-                conversation_link = CONVERSATION_URL.format(conversation_id_hex)
+                conversation_link = CONVERSATION_URL.format(conversation_id)
                 msg_info = f"I'm on it! {user_info.username} can [track my progress at all-hands.dev]({conversation_link})"
 
             except MissingSettingsError as e:

enterprise/integrations/gitlab/gitlab_service.py

@@ -7,14 +7,14 @@ from server.auth.token_manager import TokenManager
 from storage.gitlab_webhook import GitlabWebhook, WebhookStatus
 from storage.gitlab_webhook_store import GitlabWebhookStore
 
-from openhands.app_server.integrations.gitlab.gitlab_service import GitLabService
-from openhands.app_server.integrations.service_types import (
+from openhands.core.logger import openhands_logger as logger
+from openhands.integrations.gitlab.gitlab_service import GitLabService
+from openhands.integrations.service_types import (
     ProviderType,
     RateLimitError,
     Repository,
     RequestMethod,
 )
-from openhands.core.logger import openhands_logger as logger
 from openhands.server.types import AppMode
 
 

enterprise/integrations/gitlab/gitlab_view.py

@@ -6,36 +6,47 @@ from integrations.resolver_context import ResolverUserContext
 from integrations.resolver_org_router import resolve_org_for_repo
 from integrations.types import ResolverViewInterface, UserData
 from integrations.utils import (
+    ENABLE_V1_GITLAB_RESOLVER,
     HOST,
     get_oh_labels,
+    get_user_v1_enabled_setting,
     has_exact_mention,
 )
 from jinja2 import Environment
 from server.auth.token_manager import TokenManager
 from server.config import get_config
+from storage.saas_conversation_store import SaasConversationStore
 from storage.saas_secrets_store import SaasSecretsStore
 
 from openhands.agent_server.models import SendMessageRequest
 from openhands.app_server.app_conversation.app_conversation_models import (
     AppConversationStartRequest,
     AppConversationStartTaskStatus,
-    ConversationTrigger,
 )
 from openhands.app_server.config import get_app_conversation_service
-from openhands.app_server.integrations.gitlab.gitlab_service import GitLabServiceImpl
-from openhands.app_server.integrations.provider import PROVIDER_TOKEN_TYPE, ProviderType
-from openhands.app_server.integrations.service_types import Comment
 from openhands.app_server.services.injector import InjectorState
 from openhands.app_server.user.specifiy_user_context import USER_CONTEXT_ATTR
-from openhands.app_server.user_auth.user_auth import UserAuth
 from openhands.core.logger import openhands_logger as logger
+from openhands.integrations.gitlab.gitlab_service import GitLabServiceImpl
+from openhands.integrations.provider import PROVIDER_TOKEN_TYPE, ProviderType
+from openhands.integrations.service_types import Comment
 from openhands.sdk import TextContent
+from openhands.server.user_auth.user_auth import UserAuth
+from openhands.storage.data_models.conversation_metadata import (
+    ConversationMetadata,
+    ConversationTrigger,
+)
+from openhands.utils.conversation_summary import get_default_conversation_title
 
 OH_LABEL, INLINE_OH_LABEL = get_oh_labels(HOST)
 CONFIDENTIAL_NOTE = 'confidential_note'
 NOTE_TYPES = ['note', CONFIDENTIAL_NOTE]
 
 
+async def is_v1_enabled_for_gitlab_resolver(user_id: str) -> bool:
+    return await get_user_v1_enabled_setting(user_id) and ENABLE_V1_GITLAB_RESOLVER
+
+
 # =================================================
 # SECTION: Factory to create appriorate Gitlab view
 # =================================================
@@ -57,6 +68,7 @@ class GitlabIssue(ResolverViewInterface):
     description: str
     previous_comments: list[Comment]
     is_mr: bool
+    v1_enabled: bool
 
     def _get_branch_name(self) -> str | None:
         return getattr(self, 'branch_name', None)
@@ -102,7 +114,10 @@ class GitlabIssue(ResolverViewInterface):
 
         return user_secrets.custom_secrets if user_secrets else None
 
-    async def initialize_new_conversation(self) -> UUID:
+    async def initialize_new_conversation(self) -> ConversationMetadata:
+        # v1_enabled is already set at construction time in the factory method
+        # This is the source of truth for the conversation type
+
         # Resolve target org based on claimed git organizations
         self.resolved_org_id = await resolve_org_for_repo(
             provider='gitlab',
@@ -110,26 +125,57 @@ class GitlabIssue(ResolverViewInterface):
             keycloak_user_id=self.user_info.keycloak_user_id,
         )
 
-        # All conversations use V1 app conversation service
-        conversation_id = uuid4()
-        self.conversation_id = conversation_id.hex
-        return conversation_id
+        if self.v1_enabled:
+            # Create dummy conversation metadata
+            # Don't save to conversation store
+            # V1 conversations are stored in a separate table
+            self.conversation_id = uuid4().hex
+            return ConversationMetadata(
+                conversation_id=self.conversation_id,
+                selected_repository=self.full_repo_name,
+            )
+
+        # Create the conversation store with resolver org routing
+        # (bypasses initialize_conversation to avoid threading enterprise-only
+        # resolver_org_id through the generic OSS interface)
+        store = await SaasConversationStore.get_resolver_instance(
+            get_config(),
+            self.user_info.keycloak_user_id,
+            self.resolved_org_id,
+        )
+
+        conversation_id = uuid4().hex
+        conversation_metadata = ConversationMetadata(
+            trigger=ConversationTrigger.RESOLVER,
+            conversation_id=conversation_id,
+            title=get_default_conversation_title(conversation_id),
+            user_id=self.user_info.keycloak_user_id,
+            selected_repository=self.full_repo_name,
+            selected_branch=self._get_branch_name(),
+            git_provider=ProviderType.GITLAB,
+        )
+        await store.save_metadata(conversation_metadata)
+
+        self.conversation_id = conversation_id
+        return conversation_metadata
 
     async def create_new_conversation(
         self,
         jinja_env: Environment,
         git_provider_tokens: PROVIDER_TOKEN_TYPE,
-        conversation_id: UUID,
+        conversation_metadata: ConversationMetadata,
         saas_user_auth: UserAuth,
     ):
         # V0 conversation path has been removed - all conversations use V1 app conversation service
-        await self._create_v1_conversation(jinja_env, saas_user_auth, conversation_id)
+        await self._create_v1_conversation(
+            jinja_env, saas_user_auth, conversation_metadata
+        )
 
     async def _create_v1_conversation(
         self,
         jinja_env: Environment,
         saas_user_auth: UserAuth,
-        conversation_id: UUID,
+        conversation_metadata: ConversationMetadata,
     ):
         """Create conversation using the new V1 app conversation system."""
         logger.info('[GitLab V1]: Creating V1 conversation')
@@ -155,7 +201,7 @@ class GitlabIssue(ResolverViewInterface):
 
         # Create the V1 conversation start request with the callback processor
         start_request = AppConversationStartRequest(
-            conversation_id=conversation_id,
+            conversation_id=UUID(conversation_metadata.conversation_id),
             system_message_suffix=conversation_instructions,
             initial_message=initial_message,
             selected_repository=self.full_repo_name,
@@ -404,6 +450,16 @@ class GitlabFactory:
             user_id=user_id, username=username, keycloak_user_id=keycloak_user_id
         )
 
+        # Check v1_enabled at construction time - this is the source of truth
+        v1_enabled = (
+            await is_v1_enabled_for_gitlab_resolver(keycloak_user_id)
+            if keycloak_user_id
+            else False
+        )
+        logger.info(
+            f'[GitLab V1]: User flag found for {keycloak_user_id} is {v1_enabled}'
+        )
+
         if GitlabFactory.is_labeled_issue(message):
             issue_iid = payload['object_attributes']['iid']
 
@@ -425,6 +481,7 @@ class GitlabFactory:
                 description='',
                 previous_comments=[],
                 is_mr=False,
+                v1_enabled=v1_enabled,
             )
 
         elif GitlabFactory.is_issue_comment(message):
@@ -455,6 +512,7 @@ class GitlabFactory:
                 description='',
                 previous_comments=[],
                 is_mr=False,
+                v1_enabled=v1_enabled,
             )
 
         elif GitlabFactory.is_mr_comment(message):
@@ -487,6 +545,7 @@ class GitlabFactory:
                 description='',
                 previous_comments=[],
                 is_mr=True,
+                v1_enabled=v1_enabled,
             )
 
         elif GitlabFactory.is_mr_comment(message, inline=True):
@@ -527,6 +586,7 @@ class GitlabFactory:
                 description='',
                 previous_comments=[],
                 is_mr=True,
+                v1_enabled=v1_enabled,
             )
 
         raise ValueError(f'Unhandled GitLab webhook event: {message}')

enterprise/integrations/jira/jira_manager.py

@@ -42,13 +42,13 @@ from storage.jira_integration_store import JiraIntegrationStore
 from storage.jira_user import JiraUser
 from storage.jira_workspace import JiraWorkspace
 
-from openhands.app_server.user_auth.user_auth import UserAuth
 from openhands.core.logger import openhands_logger as logger
 from openhands.server.types import (
     LLMAuthenticationError,
     MissingSettingsError,
     SessionExpiredError,
 )
+from openhands.server.user_auth.user_auth import UserAuth
 from openhands.utils.http_session import httpx_verify_option
 
 JIRA_CLOUD_API_URL = 'https://api.atlassian.com/ex/jira'

enterprise/integrations/jira/jira_types.py

@@ -7,7 +7,7 @@ from jinja2 import Environment
 from storage.jira_user import JiraUser
 from storage.jira_workspace import JiraWorkspace
 
-from openhands.app_server.user_auth.user_auth import UserAuth
+from openhands.server.user_auth.user_auth import UserAuth
 
 if TYPE_CHECKING:
     from integrations.jira.jira_payload import JiraWebhookPayload

enterprise/integrations/jira/jira_view.py

@@ -35,15 +35,18 @@ from openhands.agent_server.models import SendMessageRequest
 from openhands.app_server.app_conversation.app_conversation_models import (
     AppConversationStartRequest,
     AppConversationStartTaskStatus,
-    ConversationTrigger,
 )
 from openhands.app_server.config import get_app_conversation_service
-from openhands.app_server.integrations.provider import ProviderHandler, ProviderType
 from openhands.app_server.services.injector import InjectorState
 from openhands.app_server.user.specifiy_user_context import USER_CONTEXT_ATTR
-from openhands.app_server.user_auth.user_auth import UserAuth
 from openhands.core.logger import openhands_logger as logger
+from openhands.integrations.provider import ProviderHandler, ProviderType
 from openhands.sdk import TextContent
+from openhands.server.user_auth.user_auth import UserAuth
+from openhands.storage.data_models.conversation_metadata import (
+    ConversationMetadata,
+    ConversationTrigger,
+)
 from openhands.utils.http_session import httpx_verify_option
 
 JIRA_CLOUD_API_URL = 'https://api.atlassian.com/ex/jira'
@@ -189,30 +192,32 @@ class JiraNewConversationView(JiraViewInterface):
         )
         await integration_store.create_conversation(jira_conversation)
 
-        conversation_id = await self._initialize_conversation()
-        await self._create_v1_conversation(jinja_env, conversation_id)
+        conversation_metadata = await self._create_v1_metadata()
+        await self._create_v1_conversation(jinja_env, conversation_metadata)
         return self.conversation_id
 
-    async def _initialize_conversation(self) -> UUID:
-        """Initialize conversation and return the conversation ID.
+    async def _create_v1_metadata(self) -> ConversationMetadata:
+        """Create conversation metadata for V1 conversations.
 
         The JiraConversation mapping is saved to the integration store (above), but
         V1 conversation metadata is managed by the app conversation system, not
         the legacy conversation store.
         """
-        logger.info('[Jira]: Initializing V1 conversation')
+        logger.info('[Jira]: Creating V1 metadata')
 
-        # Generate a conversation ID for V1
-        conversation_id = uuid4()
-        self.conversation_id = conversation_id.hex
+        # Generate a dummy conversation for V1 (not saved to store)
+        self.conversation_id = uuid4().hex
         self.resolved_org_id = await self._get_resolved_org_id()
 
-        return conversation_id
+        return ConversationMetadata(
+            conversation_id=self.conversation_id,
+            selected_repository=self.selected_repo,
+        )
 
     async def _create_v1_conversation(
         self,
         jinja_env: Environment,
-        conversation_id: UUID,
+        conversation_metadata: ConversationMetadata,
     ):
         """Create conversation using the new V1 app conversation system."""
         logger.info('[Jira]: Creating V1 conversation')
@@ -231,7 +236,7 @@ class JiraNewConversationView(JiraViewInterface):
 
         # Create the V1 conversation start request
         start_request = AppConversationStartRequest(
-            conversation_id=conversation_id,
+            conversation_id=UUID(conversation_metadata.conversation_id),
             system_message_suffix=None,
             initial_message=initial_message,
             selected_repository=self.selected_repo,

enterprise/integrations/jira_dc/jira_dc_manager.py

@@ -29,16 +29,16 @@ from storage.jira_dc_integration_store import JiraDcIntegrationStore
 from storage.jira_dc_user import JiraDcUser
 from storage.jira_dc_workspace import JiraDcWorkspace
 
-from openhands.app_server.integrations.provider import ProviderHandler
-from openhands.app_server.integrations.service_types import Repository
-from openhands.app_server.user_auth.user_auth import UserAuth
 from openhands.core.logger import openhands_logger as logger
+from openhands.integrations.provider import ProviderHandler
+from openhands.integrations.service_types import Repository
 from openhands.server.shared import server_config
 from openhands.server.types import (
     LLMAuthenticationError,
     MissingSettingsError,
     SessionExpiredError,
 )
+from openhands.server.user_auth.user_auth import UserAuth
 from openhands.utils.http_session import httpx_verify_option
 
 

enterprise/integrations/jira_dc/jira_dc_types.py

@@ -5,7 +5,7 @@ from jinja2 import Environment
 from storage.jira_dc_user import JiraDcUser
 from storage.jira_dc_workspace import JiraDcWorkspace
 
-from openhands.app_server.user_auth.user_auth import UserAuth
+from openhands.server.user_auth.user_auth import UserAuth
 
 
 class JiraDcViewInterface(ABC):

enterprise/integrations/jira_dc/jira_dc_view.py

@@ -27,15 +27,17 @@ from openhands.agent_server.models import SendMessageRequest
 from openhands.app_server.app_conversation.app_conversation_models import (
     AppConversationStartRequest,
     AppConversationStartTaskStatus,
-    ConversationTrigger,
 )
 from openhands.app_server.config import get_app_conversation_service
-from openhands.app_server.integrations.provider import ProviderHandler, ProviderType
 from openhands.app_server.services.injector import InjectorState
 from openhands.app_server.user.specifiy_user_context import USER_CONTEXT_ATTR
-from openhands.app_server.user_auth.user_auth import UserAuth
 from openhands.core.logger import openhands_logger as logger
+from openhands.integrations.provider import ProviderHandler, ProviderType
 from openhands.sdk import TextContent
+from openhands.server.user_auth.user_auth import UserAuth
+from openhands.storage.data_models.conversation_metadata import (
+    ConversationTrigger,
+)
 
 integration_store = JiraDcIntegrationStore.get_instance()
 

enterprise/integrations/resolver_context.py

@@ -1,14 +1,11 @@
 from uuid import UUID
 
-from openhands.app_server.integrations.provider import (
-    PROVIDER_TOKEN_TYPE,
-    ProviderHandler,
-)
-from openhands.app_server.integrations.service_types import ProviderType, UserGitInfo
 from openhands.app_server.user.user_context import UserContext
 from openhands.app_server.user.user_models import UserInfo
-from openhands.app_server.user_auth.user_auth import UserAuth
+from openhands.integrations.provider import PROVIDER_TOKEN_TYPE, ProviderHandler
+from openhands.integrations.service_types import ProviderType, UserGitInfo
 from openhands.sdk.secret import SecretSource, StaticSecret
+from openhands.server.user_auth.user_auth import UserAuth
 
 
 class ResolverUserContext(UserContext):

enterprise/integrations/slack/slack_errors.py

@@ -26,7 +26,6 @@ class SlackErrorCode(Enum):
     PROVIDER_AUTH_FAILED = 'SLACK_ERR_006'
     LLM_AUTH_FAILED = 'SLACK_ERR_007'
     MISSING_SETTINGS = 'SLACK_ERR_008'
-    MISSING_SLACK_SCOPES = 'SLACK_ERR_009'
     UNEXPECTED_ERROR = 'SLACK_ERR_999'
 
 
@@ -99,11 +98,6 @@ _USER_MESSAGES: dict[SlackErrorCode, str] = {
         '{username} please re-login into '
         f'[OpenHands Cloud]({HOST_URL}) before starting a job.'
     ),
-    SlackErrorCode.MISSING_SLACK_SCOPES: (
-        '⚠️ The Slack app is missing required permissions. '
-        f'Please ask your workspace admin to re-install the OpenHands Slack App at {HOST_URL}/slack/install '
-        'to authorize the updated permissions.'
-    ),
     SlackErrorCode.UNEXPECTED_ERROR: (
         'Uh oh! There was an unexpected error (ref: {code}). Please try again later.'
     ),

enterprise/integrations/slack/slack_manager.py

@@ -28,23 +28,22 @@ from slack_sdk.oauth import AuthorizeUrlGenerator
 from slack_sdk.web.async_client import AsyncWebClient
 from sqlalchemy import select
 from storage.database import a_session_maker
-from storage.redis import get_redis_client_async
 from storage.slack_user import SlackUser
 
-from openhands.app_server.integrations.provider import ProviderHandler
-from openhands.app_server.integrations.service_types import (
+from openhands.core.logger import openhands_logger as logger
+from openhands.integrations.provider import ProviderHandler
+from openhands.integrations.service_types import (
     AuthenticationError,
     ProviderTimeoutError,
     Repository,
 )
-from openhands.app_server.user_auth.user_auth import UserAuth
-from openhands.core.logger import openhands_logger as logger
-from openhands.server.shared import config, server_config
+from openhands.server.shared import config, server_config, sio
 from openhands.server.types import (
     LLMAuthenticationError,
     MissingSettingsError,
     SessionExpiredError,
 )
+from openhands.server.user_auth.user_auth import UserAuth
 
 authorize_url_generator = AuthorizeUrlGenerator(
     client_id=SLACK_CLIENT_ID,
@@ -115,7 +114,7 @@ class SlackManager(Manager[SlackViewInterface]):
         """
         key = f'{SLACK_USER_MSG_KEY_PREFIX}:{message_ts}:{thread_ts}'
         try:
-            redis = get_redis_client_async()
+            redis = sio.manager.redis
             await redis.set(key, user_msg, ex=SLACK_USER_MSG_EXPIRATION)
             logger.info(
                 'slack_stored_user_msg',
@@ -158,7 +157,7 @@ class SlackManager(Manager[SlackViewInterface]):
         """
         key = f'{SLACK_USER_MSG_KEY_PREFIX}:{message_ts}:{thread_ts}'
         try:
-            redis = get_redis_client_async()
+            redis = sio.manager.redis
             user_msg = await redis.get(key)
             if user_msg:
                 # Redis returns bytes, decode to string

enterprise/integrations/slack/slack_types.py

@@ -5,7 +5,7 @@ from integrations.types import SummaryExtractionTracker
 from jinja2 import Environment
 from storage.slack_user import SlackUser
 
-from openhands.app_server.user_auth.user_auth import UserAuth
+from openhands.server.user_auth.user_auth import UserAuth
 
 
 @dataclass
@@ -112,6 +112,7 @@ class SlackViewInterface(SlackMessageView, SummaryExtractionTracker, ABC):
     should_extract: bool
     send_summary_instruction: bool
     conversation_id: str
+    v1_enabled: bool
 
     @abstractmethod
     async def _get_instructions(self, jinja_env: Environment) -> tuple[str, str]:

enterprise/integrations/slack/slack_view.py

@@ -5,7 +5,6 @@ from uuid import UUID, uuid4
 from integrations.models import Message
 from integrations.resolver_context import ResolverUserContext
 from integrations.resolver_org_router import resolve_org_for_repo
-from integrations.slack.slack_errors import SlackError, SlackErrorCode
 from integrations.slack.slack_types import (
     SlackMessageView,
     SlackViewInterface,
@@ -14,10 +13,11 @@ from integrations.slack.slack_types import (
 from integrations.slack.slack_v1_callback_processor import SlackV1CallbackProcessor
 from integrations.utils import (
     CONVERSATION_URL,
+    ENABLE_V1_SLACK_RESOLVER,
+    get_user_v1_enabled_setting,
 )
 from jinja2 import Environment
 from slack_sdk import WebClient
-from slack_sdk.errors import SlackApiError
 from storage.slack_conversation import SlackConversation
 from storage.slack_conversation_store import SlackConversationStore
 from storage.slack_team_store import SlackTeamStore
@@ -26,17 +26,19 @@ from storage.slack_user import SlackUser
 from openhands.app_server.app_conversation.app_conversation_models import (
     AppConversationStartRequest,
     AppConversationStartTaskStatus,
-    ConversationTrigger,
     SendMessageRequest,
 )
 from openhands.app_server.config import get_app_conversation_service
-from openhands.app_server.integrations.provider import ProviderHandler
 from openhands.app_server.sandbox.sandbox_models import SandboxStatus
 from openhands.app_server.services.injector import InjectorState
 from openhands.app_server.user.specifiy_user_context import USER_CONTEXT_ATTR
-from openhands.app_server.user_auth.user_auth import UserAuth
 from openhands.core.logger import openhands_logger as logger
+from openhands.integrations.provider import ProviderHandler
 from openhands.sdk import TextContent
+from openhands.server.user_auth.user_auth import UserAuth
+from openhands.storage.data_models.conversation_metadata import (
+    ConversationTrigger,
+)
 from openhands.utils.async_utils import GENERAL_TIMEOUT
 
 # =================================================
@@ -49,6 +51,10 @@ slack_conversation_store = SlackConversationStore.get_instance()
 slack_team_store = SlackTeamStore.get_instance()
 
 
+async def is_v1_enabled_for_slack_resolver(user_id: str) -> bool:
+    return await get_user_v1_enabled_setting(user_id) and ENABLE_V1_SLACK_RESOLVER
+
+
 @dataclass
 class SlackNewConversationView(SlackViewInterface):
     bot_access_token: str
@@ -64,6 +70,7 @@ class SlackNewConversationView(SlackViewInterface):
     send_summary_instruction: bool
     conversation_id: str
     team_id: str
+    v1_enabled: bool
 
     def _get_initial_prompt(self, text: str, blocks: list[dict]):
         bot_id = self._get_bot_id(blocks)
@@ -88,34 +95,24 @@ class SlackNewConversationView(SlackViewInterface):
         messages = []
         if self.thread_ts:
             client = WebClient(token=self.bot_access_token)
-            try:
-                result = client.conversations_replies(
-                    channel=self.channel_id,
-                    ts=self.thread_ts,
-                    inclusive=True,
-                    latest=self.message_ts,
-                    limit=CONTEXT_LIMIT,  # We can be smarter about getting more context/condensing it even in the future
-                )
-            except SlackApiError as e:
-                if e.response.get('error') == 'missing_scope':
-                    raise SlackError(SlackErrorCode.MISSING_SLACK_SCOPES) from e
-                raise
+            result = client.conversations_replies(
+                channel=self.channel_id,
+                ts=self.thread_ts,
+                inclusive=True,
+                latest=self.message_ts,
+                limit=CONTEXT_LIMIT,  # We can be smarter about getting more context/condensing it even in the future
+            )
 
             messages = result['messages']
 
         else:
             client = WebClient(token=self.bot_access_token)
-            try:
-                result = client.conversations_history(
-                    channel=self.channel_id,
-                    inclusive=True,
-                    latest=self.message_ts,
-                    limit=CONTEXT_LIMIT,
-                )
-            except SlackApiError as e:
-                if e.response.get('error') == 'missing_scope':
-                    raise SlackError(SlackErrorCode.MISSING_SLACK_SCOPES) from e
-                raise
+            result = client.conversations_history(
+                channel=self.channel_id,
+                inclusive=True,
+                latest=self.message_ts,
+                limit=CONTEXT_LIMIT,
+            )
 
             messages = result['messages']
             messages.reverse()
@@ -152,7 +149,7 @@ class SlackNewConversationView(SlackViewInterface):
                 'Attempting to start conversation without confirming selected repo from user'
             )
 
-    async def save_slack_convo(self):
+    async def save_slack_convo(self, v1_enabled: bool = False):
         if self.slack_to_openhands_user:
             user_info: SlackUser = self.slack_to_openhands_user
 
@@ -164,6 +161,7 @@ class SlackNewConversationView(SlackViewInterface):
                     'keycloak_user_id': user_info.keycloak_user_id,
                     'org_id': user_info.org_id,
                     'parent_id': self.thread_ts or self.message_ts,
+                    'v1_enabled': v1_enabled,
                 },
             )
             slack_conversation = SlackConversation(
@@ -173,7 +171,7 @@ class SlackNewConversationView(SlackViewInterface):
                 org_id=user_info.org_id,
                 parent_id=self.thread_ts
                 or self.message_ts,  # conversations can start in a thread reply as well; we should always references the parent's (root level msg's) message ID
-                v1_enabled=True,  # All conversations are V1
+                v1_enabled=v1_enabled,
             )
             await slack_conversation_store.create_slack_conversation(slack_conversation)
 
@@ -270,7 +268,7 @@ class SlackNewConversationView(SlackViewInterface):
                     )
 
         logger.info(f'[Slack V1]: Created new conversation: {self.conversation_id}')
-        await self.save_slack_convo()
+        await self.save_slack_convo(v1_enabled=True)
 
     def get_response_msg(self) -> str:
         user_info: SlackUser = self.slack_to_openhands_user
@@ -292,18 +290,13 @@ class SlackUpdateExistingConversationView(SlackNewConversationView):
 
     async def _get_instructions(self, jinja_env: Environment) -> tuple[str, str]:
         client = WebClient(token=self.bot_access_token)
-        try:
-            result = client.conversations_replies(
-                channel=self.channel_id,
-                ts=self.message_ts,
-                inclusive=True,
-                latest=self.message_ts,
-                limit=1,  # Get exact user message, in future we can be smarter with collecting additional context
-            )
-        except SlackApiError as e:
-            if e.response.get('error') == 'missing_scope':
-                raise SlackError(SlackErrorCode.MISSING_SLACK_SCOPES) from e
-            raise
+        result = client.conversations_replies(
+            channel=self.channel_id,
+            ts=self.message_ts,
+            inclusive=True,
+            latest=self.message_ts,
+            limit=1,  # Get exact user message, in future we can be smarter with collecting additional context
+        )
 
         user_message = result['messages'][0]
         user_message = self._get_initial_prompt(
@@ -382,7 +375,7 @@ class SlackUpdateExistingConversationView(SlackNewConversationView):
             )
 
             # 6. Send the message to the agent server
-            url = f'{agent_server_url.rstrip("/")}/api/conversations/{UUID(self.conversation_id)}/events'
+            url = f"{agent_server_url.rstrip('/')}/api/conversations/{UUID(self.conversation_id)}/events"
 
             headers = {'X-Session-API-Key': running_sandbox.session_api_key}
             payload = send_message_request.model_dump()
@@ -523,6 +516,7 @@ class SlackFactory:
                 conversation_id=conversation.conversation_id,
                 slack_conversation=conversation,
                 team_id=team_id,
+                v1_enabled=False,
             )
 
         elif SlackFactory.did_user_select_repo_from_form(message):
@@ -540,6 +534,7 @@ class SlackFactory:
                 send_summary_instruction=True,
                 conversation_id='',
                 team_id=team_id,
+                v1_enabled=False,
             )
 
         else:
@@ -557,6 +552,7 @@ class SlackFactory:
                 send_summary_instruction=True,
                 conversation_id='',
                 team_id=team_id,
+                v1_enabled=False,
             )
 
 

enterprise/integrations/solvability/data/__init__.py

@@ -0,0 +1,41 @@
+"""
+Utilities for loading and managing pre-trained classifiers.
+
+Assumes that classifiers are stored adjacent to this file in the `solvability/data` directory, using a simple
+`name + .json` pattern.
+"""
+
+from pathlib import Path
+
+from integrations.solvability.models.classifier import SolvabilityClassifier
+
+
+def load_classifier(name: str) -> SolvabilityClassifier:
+    """
+    Load a classifier by name.
+
+    Args:
+        name (str): The name of the classifier to load.
+
+    Returns:
+        SolvabilityClassifier: The loaded classifier instance.
+    """
+    data_dir = Path(__file__).parent
+    classifier_path = data_dir / f'{name}.json'
+
+    if not classifier_path.exists():
+        raise FileNotFoundError(f"Classifier '{name}' not found at {classifier_path}")
+
+    with classifier_path.open('r') as f:
+        return SolvabilityClassifier.model_validate_json(f.read())
+
+
+def available_classifiers() -> list[str]:
+    """
+    List all available classifiers in the data directory.
+
+    Returns:
+        list[str]: A list of classifier names (without the .json extension).
+    """
+    data_dir = Path(__file__).parent
+    return [f.stem for f in data_dir.glob('*.json') if f.is_file()]

enterprise/integrations/solvability/models/__init__.py

@@ -0,0 +1,38 @@
+"""
+Solvability Models Package
+
+This package contains the core machine learning models and components for predicting
+the solvability of GitHub issues and similar technical problems.
+
+The solvability prediction system works by:
+1. Using a Featurizer to extract semantic features from issue descriptions via LLM calls
+2. Training a RandomForestClassifier on these features to predict solvability
+3. Generating detailed reports with feature importance analysis
+
+Key Components:
+- Feature: Defines individual features that can be extracted from issues
+- Featurizer: Orchestrates LLM-based feature extraction with sampling and batching
+- SolvabilityClassifier: Main ML pipeline combining featurization and classification
+- SolvabilityReport: Comprehensive output with predictions, feature analysis, and metadata
+- ImportanceStrategy: Configurable methods for calculating feature importance (SHAP, permutation, impurity)
+"""
+
+from integrations.solvability.models.classifier import SolvabilityClassifier
+from integrations.solvability.models.featurizer import (
+    EmbeddingDimension,
+    Feature,
+    FeatureEmbedding,
+    Featurizer,
+)
+from integrations.solvability.models.importance_strategy import ImportanceStrategy
+from integrations.solvability.models.report import SolvabilityReport
+
+__all__ = [
+    'Feature',
+    'EmbeddingDimension',
+    'FeatureEmbedding',
+    'Featurizer',
+    'ImportanceStrategy',
+    'SolvabilityClassifier',
+    'SolvabilityReport',
+]

enterprise/integrations/solvability/models/classifier.py

@@ -0,0 +1,433 @@
+from __future__ import annotations
+
+import base64
+import pickle
+from typing import Any
+
+import numpy as np
+import pandas as pd
+import shap
+from integrations.solvability.models.featurizer import Feature, Featurizer
+from integrations.solvability.models.importance_strategy import ImportanceStrategy
+from integrations.solvability.models.report import SolvabilityReport
+from pydantic import (
+    BaseModel,
+    PrivateAttr,
+    field_serializer,
+    field_validator,
+    model_validator,
+)
+from sklearn.ensemble import RandomForestClassifier
+from sklearn.exceptions import NotFittedError
+from sklearn.inspection import permutation_importance
+from sklearn.utils.validation import check_is_fitted
+
+from openhands.core.config import LLMConfig
+
+
+class SolvabilityClassifier(BaseModel):
+    """
+    Machine learning pipeline for predicting the solvability of GitHub issues and similar problems.
+
+    This classifier combines LLM-based feature extraction with traditional ML classification:
+    1. Uses a Featurizer to extract semantic boolean features from issue descriptions via LLM calls
+    2. Trains a RandomForestClassifier on these features to predict solvability scores
+    3. Provides feature importance analysis using configurable strategies (SHAP, permutation, impurity)
+    4. Generates comprehensive reports with predictions, feature analysis, and cost metrics
+
+    The classifier supports both training on labeled data and inference on new issues, with built-in
+    support for batch processing and concurrent feature extraction.
+    """
+
+    identifier: str
+    """
+    The identifier for the classifier.
+    """
+
+    featurizer: Featurizer
+    """
+    The featurizer to use for transforming the input data.
+    """
+
+    classifier: RandomForestClassifier
+    """
+    The RandomForestClassifier used for predicting solvability from extracted features.
+
+    This ensemble model provides robust predictions and built-in feature importance metrics.
+    """
+
+    importance_strategy: ImportanceStrategy = ImportanceStrategy.IMPURITY
+    """
+    Strategy to use for calculating feature importance.
+    """
+
+    samples: int = 10
+    """
+    Number of samples to use for calculating feature embedding coefficients.
+    """
+
+    random_state: int | None = None
+    """
+    Random state for reproducibility.
+    """
+
+    _classifier_attrs: dict[str, Any] = PrivateAttr(default_factory=dict)
+    """
+    Private dictionary storing cached results from feature extraction and importance calculations.
+
+    Contains keys like 'features_', 'cost_', 'feature_importances_', and 'labels_' that are populated
+    during transform(), fit(), and predict() operations. Access these via the corresponding properties.
+
+    This field is never serialized, so cached values will not persist across model save/load cycles.
+    """
+
+    model_config = {
+        'arbitrary_types_allowed': True,
+    }
+
+    @model_validator(mode='after')
+    def validate_random_state(self) -> SolvabilityClassifier:
+        """
+        Validate the random state configuration between this object and the classifier.
+        """
+        # If both random states are set, they definitely need to agree.
+        if self.random_state is not None and self.classifier.random_state is not None:
+            if self.random_state != self.classifier.random_state:
+                raise ValueError(
+                    'The random state of the classifier and the top-level classifier must agree.'
+                )
+
+        # Otherwise, we'll always set the classifier's random state to the top-level one.
+        self.classifier.random_state = self.random_state
+
+        return self
+
+    @property
+    def features_(self) -> pd.DataFrame:
+        """
+        Get the features used by the classifier for the most recent inputs.
+        """
+        if 'features_' not in self._classifier_attrs:
+            raise ValueError(
+                'SolvabilityClassifier.transform() has not yet been called.'
+            )
+        return self._classifier_attrs['features_']
+
+    @property
+    def cost_(self) -> pd.DataFrame:
+        """
+        Get the cost of the classifier for the most recent inputs.
+        """
+        if 'cost_' not in self._classifier_attrs:
+            raise ValueError(
+                'SolvabilityClassifier.transform() has not yet been called.'
+            )
+        return self._classifier_attrs['cost_']
+
+    @property
+    def feature_importances_(self) -> np.ndarray:
+        """
+        Get the feature importances for the most recent inputs.
+        """
+        if 'feature_importances_' not in self._classifier_attrs:
+            raise ValueError(
+                'No SolvabilityClassifier methods that produce feature importances (.fit(), .predict_proba(), and '
+                '.predict()) have been called.'
+            )
+        return self._classifier_attrs['feature_importances_']  # type: ignore[no-any-return]
+
+    @property
+    def is_fitted(self) -> bool:
+        """
+        Check if the classifier is fitted.
+        """
+        try:
+            check_is_fitted(self.classifier)
+            return True
+        except NotFittedError:
+            return False
+
+    def transform(self, issues: pd.Series, llm_config: LLMConfig) -> pd.DataFrame:
+        """
+        Transform the input issues using the featurizer to extract features.
+
+        This method orchestrates the feature extraction pipeline:
+        1. Uses the featurizer to generate embeddings for all issues
+        2. Converts embeddings to a structured DataFrame
+        3. Separates feature columns from metadata columns
+        4. Stores results for later access via properties
+
+        Args:
+            issues: A pandas Series containing the issue descriptions.
+            llm_config: LLM configuration to use for feature extraction.
+
+        Returns:
+            pd.DataFrame: A DataFrame containing only the feature columns (no metadata).
+        """
+        # Generate feature embeddings for all issues using batch processing
+        feature_embeddings = self.featurizer.embed_batch(
+            issues, samples=self.samples, llm_config=llm_config
+        )
+        df = pd.DataFrame(embedding.to_row() for embedding in feature_embeddings)
+
+        # Split into feature columns (used by classifier) and cost columns (metadata)
+        feature_columns = [feature.identifier for feature in self.featurizer.features]
+        cost_columns = [col for col in df.columns if col not in feature_columns]
+
+        # Store both sets for access via properties
+        self._classifier_attrs['features_'] = df[feature_columns]
+        self._classifier_attrs['cost_'] = df[cost_columns]
+
+        return self.features_
+
+    def fit(
+        self, issues: pd.Series, labels: pd.Series, llm_config: LLMConfig
+    ) -> SolvabilityClassifier:
+        """
+        Fit the classifier to the input issues and labels.
+
+        Args:
+            issues: A pandas Series containing the issue descriptions.
+
+            labels: A pandas Series containing the labels (0 or 1) for each issue.
+
+            llm_config: LLM configuration to use for feature extraction.
+
+        Returns:
+            SolvabilityClassifier: The fitted classifier.
+        """
+        features = self.transform(issues, llm_config=llm_config)
+        self.classifier.fit(features, labels)
+
+        # Store labels for permutation importance calculation
+        self._classifier_attrs['labels_'] = labels
+        self._classifier_attrs['feature_importances_'] = self._importance(
+            features, self.classifier.predict_proba(features), labels
+        )
+
+        return self
+
+    def predict_proba(self, issues: pd.Series, llm_config: LLMConfig) -> np.ndarray:
+        """
+        Predict the solvability probabilities for the input issues.
+
+        Returns class probabilities where the second column represents the probability
+        of the issue being solvable (positive class).
+
+        Args:
+            issues: A pandas Series containing the issue descriptions.
+            llm_config: LLM configuration to use for feature extraction.
+
+        Returns:
+            np.ndarray: Array of shape (n_samples, 2) with probabilities for each class.
+                       Column 0: probability of not solvable, Column 1: probability of solvable.
+        """
+        features = self.transform(issues, llm_config=llm_config)
+        scores = self.classifier.predict_proba(features)
+
+        # Calculate feature importances based on the configured strategy
+        # For permutation importance, we need ground truth labels if available
+        labels = self._classifier_attrs.get('labels_')
+        if (
+            self.importance_strategy == ImportanceStrategy.PERMUTATION
+            and labels is not None
+        ):
+            self._classifier_attrs['feature_importances_'] = self._importance(
+                features, scores, labels
+            )
+        else:
+            self._classifier_attrs['feature_importances_'] = self._importance(
+                features, scores
+            )
+
+        return scores  # type: ignore[no-any-return]
+
+    def predict(self, issues: pd.Series, llm_config: LLMConfig) -> np.ndarray:
+        """
+        Predict the solvability of the input issues by returning binary labels.
+
+        Uses a 0.5 probability threshold to convert probabilities to binary predictions.
+
+        Args:
+            issues: A pandas Series containing the issue descriptions.
+            llm_config: LLM configuration to use for feature extraction.
+
+        Returns:
+            np.ndarray: Boolean array where True indicates the issue is predicted as solvable.
+        """
+        probabilities = self.predict_proba(issues, llm_config=llm_config)
+        # Apply 0.5 threshold to convert probabilities to binary predictions
+        labels = probabilities[:, 1] >= 0.5
+        return labels
+
+    def _importance(
+        self,
+        features: pd.DataFrame,
+        scores: np.ndarray,
+        labels: np.ndarray | None = None,
+    ) -> np.ndarray:
+        """
+        Calculate feature importance scores using the configured strategy.
+
+        Different strategies provide different interpretations:
+        - SHAP: Shapley values indicating contribution to individual predictions
+        - PERMUTATION: Decrease in model performance when feature is shuffled
+        - IMPURITY: Gini impurity decrease from splits on each feature
+
+        Args:
+            features: Feature matrix used for predictions.
+            scores: Model prediction scores (unused for some strategies).
+            labels: Ground truth labels (required for permutation importance).
+
+        Returns:
+            np.ndarray: Feature importance scores, one per feature.
+        """
+        match self.importance_strategy:
+            case ImportanceStrategy.SHAP:
+                # Use SHAP TreeExplainer for tree-based models
+                explainer = shap.TreeExplainer(self.classifier)
+                shap_values = explainer.shap_values(features)
+                # Return mean SHAP values for the positive class (solvable)
+                return shap_values.mean(axis=0)[:, 1]  # type: ignore[no-any-return]
+
+            case ImportanceStrategy.PERMUTATION:
+                # Permutation importance requires ground truth labels
+                if labels is None:
+                    raise ValueError('Labels are required for permutation importance')
+                result = permutation_importance(
+                    self.classifier,
+                    features,
+                    labels,
+                    n_repeats=10,  # Number of permutation rounds for stability
+                    random_state=self.random_state,
+                )
+                return result.importances_mean  # type: ignore[no-any-return]
+
+            case ImportanceStrategy.IMPURITY:
+                # Use built-in feature importances from RandomForest
+                return self.classifier.feature_importances_  # type: ignore[no-any-return]
+
+            case _:
+                raise ValueError(
+                    f'Unknown importance strategy: {self.importance_strategy}'
+                )
+
+    def add_features(self, features: list[Feature]) -> SolvabilityClassifier:
+        """
+        Add new features to the classifier's featurizer.
+
+        Note: Adding features after training requires retraining the classifier
+        since the feature space will have changed.
+
+        Args:
+            features: List of Feature objects to add.
+
+        Returns:
+            SolvabilityClassifier: Self for method chaining.
+        """
+        for feature in features:
+            if feature not in self.featurizer.features:
+                self.featurizer.features.append(feature)
+        return self
+
+    def forget_features(self, features: list[Feature]) -> SolvabilityClassifier:
+        """
+        Remove features from the classifier's featurizer.
+
+        Note: Removing features after training requires retraining the classifier
+        since the feature space will have changed.
+
+        Args:
+            features: List of Feature objects to remove.
+
+        Returns:
+            SolvabilityClassifier: Self for method chaining.
+        """
+        for feature in features:
+            try:
+                self.featurizer.features.remove(feature)
+            except ValueError:
+                # Feature not in list, continue with others
+                continue
+        return self
+
+    @field_serializer('classifier')
+    @staticmethod
+    def _rfc_to_json(rfc: RandomForestClassifier) -> str:
+        """
+        Convert a RandomForestClassifier to a JSON-compatible value (a string).
+        """
+        return base64.b64encode(pickle.dumps(rfc)).decode('utf-8')
+
+    @field_validator('classifier', mode='before')
+    @staticmethod
+    def _json_to_rfc(value: str | RandomForestClassifier) -> RandomForestClassifier:
+        """
+        Convert a JSON-compatible value (a string) back to a RandomForestClassifier.
+        """
+        if isinstance(value, RandomForestClassifier):
+            return value
+
+        if isinstance(value, str):
+            try:
+                model = pickle.loads(base64.b64decode(value))
+                if isinstance(model, RandomForestClassifier):
+                    return model
+            except Exception as e:
+                raise ValueError(f'Failed to decode the classifier: {e}')
+
+        raise ValueError(
+            'The classifier must be a RandomForestClassifier or a JSON-compatible dictionary.'
+        )
+
+    def solvability_report(
+        self, issue: str, llm_config: LLMConfig, **kwargs: Any
+    ) -> SolvabilityReport:
+        """
+        Generate a solvability report for the given issue.
+
+        Args:
+            issue: The issue description for which to generate the report.
+            llm_config: Optional LLM configuration to use for feature extraction.
+            kwargs: Additional metadata to include in the report.
+
+        Returns:
+            SolvabilityReport: The generated solvability report.
+        """
+        if not self.is_fitted:
+            raise ValueError(
+                'The classifier must be fitted before generating a report.'
+            )
+
+        scores = self.predict_proba(pd.Series([issue]), llm_config=llm_config)
+
+        return SolvabilityReport(
+            identifier=self.identifier,
+            issue=issue,
+            score=scores[0, 1],
+            features=self.features_.iloc[0].to_dict(),
+            samples=self.samples,
+            importance_strategy=self.importance_strategy,
+            # Unlike the features, the importances are just a series with no link
+            # to the actual feature names. For that we have to recombine with the
+            # feature identifiers.
+            feature_importances=dict(
+                zip(
+                    self.featurizer.feature_identifiers(),
+                    self.feature_importances_.tolist(),
+                )
+            ),
+            random_state=self.random_state,
+            metadata=dict(kwargs) if kwargs else None,
+            # Both cost and response_latency are columns in the cost_ DataFrame,
+            # so we can get both by just unpacking the first row.
+            **self.cost_.iloc[0].to_dict(),
+        )
+
+    def __call__(
+        self, issue: str, llm_config: LLMConfig, **kwargs: Any
+    ) -> SolvabilityReport:
+        """
+        Generate a solvability report for the given issue.
+        """
+        return self.solvability_report(issue, llm_config=llm_config, **kwargs)

enterprise/integrations/solvability/models/difficulty_level.py

@@ -0,0 +1,38 @@
+from __future__ import annotations
+
+from enum import Enum
+
+
+class DifficultyLevel(Enum):
+    """Enum representing the difficulty level based on solvability score."""
+
+    EASY = ('EASY', 0.7, '🟢')
+    MEDIUM = ('MEDIUM', 0.4, '🟡')
+    HARD = ('HARD', 0.0, '🔴')
+
+    def __init__(self, label: str, threshold: float, emoji: str):
+        self.label = label
+        self.threshold = threshold
+        self.emoji = emoji
+
+    @classmethod
+    def from_score(cls, score: float) -> DifficultyLevel:
+        """Get difficulty level from a solvability score.
+
+        Returns the difficulty level with the highest threshold that is less than or equal to the given score.
+        """
+        # Sort enum values by threshold in descending order
+        sorted_levels = sorted(cls, key=lambda x: x.threshold, reverse=True)
+
+        # Find the first level where score meets the threshold
+        for level in sorted_levels:
+            if score >= level.threshold:
+                return level
+
+        # This should never happen if thresholds are set correctly,
+        # but return the lowest threshold level as fallback
+        return sorted_levels[-1]
+
+    def format_display(self) -> str:
+        """Format the difficulty level for display."""
+        return f'{self.emoji} **Solvability: {self.label}**'

enterprise/integrations/solvability/models/featurizer.py

@@ -0,0 +1,368 @@
+import json
+import time
+from concurrent.futures import ThreadPoolExecutor, as_completed
+from typing import Any
+
+from pydantic import BaseModel
+
+from openhands.core.config import LLMConfig
+from openhands.llm.llm import LLM
+
+
+class Feature(BaseModel):
+    """
+    Represents a single boolean feature that can be extracted from issue descriptions.
+
+    Features are semantic properties of issues (e.g., "has_code_example", "requires_debugging")
+    that are evaluated by LLMs and used as input to the solvability classifier.
+    """
+
+    identifier: str
+    """Unique identifier for the feature, used as column name in feature matrices."""
+
+    description: str
+    """Human-readable description of what the feature represents, used in LLM prompts."""
+
+    @property
+    def to_tool_description_field(self) -> dict[str, Any]:
+        """
+        Convert this feature to a JSON schema field for LLM tool calling.
+
+        Returns:
+            dict: JSON schema field definition for this feature.
+        """
+        return {
+            'type': 'boolean',
+            'description': self.description,
+        }
+
+
+class EmbeddingDimension(BaseModel):
+    """
+    Represents a single dimension (feature evaluation) within a feature embedding sample.
+
+    Each dimension corresponds to one feature being evaluated as true/false for a given issue.
+    """
+
+    feature_id: str
+    """Identifier of the feature being evaluated."""
+
+    result: bool
+    """Boolean result of the feature evaluation for this sample."""
+
+
+# Type alias for a single embedding sample - maps feature identifiers to boolean values
+EmbeddingSample = dict[str, bool]
+"""
+A single sample from the LLM evaluation of features for an issue.
+Maps feature identifiers to their boolean evaluations.
+"""
+
+
+class FeatureEmbedding(BaseModel):
+    """
+    Represents the complete feature embedding for a single issue, including multiple samples
+    and associated metadata about the LLM calls used to generate it.
+
+    Multiple samples are collected to account for LLM variability and provide more robust
+    feature estimates through averaging.
+    """
+
+    samples: list[EmbeddingSample]
+    """List of individual feature evaluation samples from the LLM."""
+
+    prompt_tokens: int | None = None
+    """Total prompt tokens consumed across all LLM calls for this embedding."""
+
+    completion_tokens: int | None = None
+    """Total completion tokens generated across all LLM calls for this embedding."""
+
+    response_latency: float | None = None
+    """Total response latency (seconds) across all LLM calls for this embedding."""
+
+    @property
+    def dimensions(self) -> list[str]:
+        """
+        Get all unique feature identifiers present across all samples.
+
+        Returns:
+            list[str]: List of feature identifiers that appear in at least one sample.
+        """
+        dims: set[str] = set()
+        for sample in self.samples:
+            dims.update(sample.keys())
+        return list(dims)
+
+    def coefficient(self, dimension: str) -> float | None:
+        """
+        Calculate the average coefficient (0-1) for a specific feature dimension.
+
+        This computes the proportion of samples where the feature was evaluated as True,
+        providing a continuous feature value for the classifier.
+
+        Args:
+            dimension: Feature identifier to calculate coefficient for.
+
+        Returns:
+            float | None: Average coefficient (0.0-1.0), or None if dimension not found.
+        """
+        # Extract boolean values for this dimension, converting to 0/1
+        values = [
+            1 if v else 0
+            for v in [sample.get(dimension) for sample in self.samples]
+            if v is not None
+        ]
+        if values:
+            return sum(values) / len(values)
+        return None
+
+    def to_row(self) -> dict[str, Any]:
+        """
+        Convert the embedding to a flat dictionary suitable for DataFrame construction.
+
+        Returns:
+            dict[str, Any]: Dictionary with metadata fields and feature coefficients.
+        """
+        return {
+            'response_latency': self.response_latency,
+            'prompt_tokens': self.prompt_tokens,
+            'completion_tokens': self.completion_tokens,
+            **{dimension: self.coefficient(dimension) for dimension in self.dimensions},
+        }
+
+    def sample_entropy(self) -> dict[str, float]:
+        """
+        Calculate the Shannon entropy of feature evaluations across samples.
+
+        Higher entropy indicates more variability in LLM responses for a feature,
+        which may suggest ambiguity in the feature definition or issue description.
+
+        Returns:
+            dict[str, float]: Mapping of feature identifiers to their entropy values (0-1).
+        """
+        from collections import Counter
+        from math import log2
+
+        entropy = {}
+        for dimension in self.dimensions:
+            # Count True/False occurrences for this feature across samples
+            counts = Counter(sample.get(dimension, False) for sample in self.samples)
+            total = sum(counts.values())
+            if total == 0:
+                entropy[dimension] = 0.0
+                continue
+            # Calculate Shannon entropy: -Σ(p * log2(p))
+            entropy_value = -sum(
+                (count / total) * log2(count / total)
+                for count in counts.values()
+                if count > 0
+            )
+            entropy[dimension] = entropy_value
+        return entropy
+
+
+class Featurizer(BaseModel):
+    """
+    Orchestrates LLM-based feature extraction from issue descriptions.
+
+    The Featurizer uses structured LLM tool calling to evaluate boolean features
+    for issue descriptions. It handles prompt construction, tool schema generation,
+    and batch processing with concurrency.
+    """
+
+    system_prompt: str
+    """System prompt that provides context and instructions to the LLM."""
+
+    message_prefix: str
+    """Prefix added to user messages before the issue description."""
+
+    features: list[Feature]
+    """List of features to extract from each issue description."""
+
+    def system_message(self) -> dict[str, Any]:
+        """
+        Construct the system message for LLM conversations.
+
+        Returns:
+            dict[str, Any]: System message dictionary for LLM API calls.
+        """
+        return {
+            'role': 'system',
+            'content': self.system_prompt,
+        }
+
+    def user_message(
+        self, issue_description: str, set_cache: bool = True
+    ) -> dict[str, Any]:
+        """
+        Construct the user message containing the issue description.
+
+        Args:
+            issue_description: The description of the issue to analyze.
+            set_cache: Whether to enable ephemeral caching for this message.
+                      Should be False for single samples to avoid cache overhead.
+
+        Returns:
+            dict[str, Any]: User message dictionary for LLM API calls.
+        """
+        message: dict[str, Any] = {
+            'role': 'user',
+            'content': f'{self.message_prefix}{issue_description}',
+        }
+        if set_cache:
+            message['cache_control'] = {'type': 'ephemeral'}
+        return message
+
+    @property
+    def tool_choice(self) -> dict[str, Any]:
+        """
+        Get the tool choice configuration for forcing LLM to use the featurizer tool.
+
+        Returns:
+            dict[str, Any]: Tool choice configuration for LLM API calls.
+        """
+        return {
+            'type': 'function',
+            'function': {'name': 'call_featurizer'},
+        }
+
+    @property
+    def tool_description(self) -> dict[str, Any]:
+        """
+        Generate the tool schema for the featurizer function.
+
+        Creates a JSON schema that describes the featurizer tool with all configured
+        features as boolean parameters.
+
+        Returns:
+            dict[str, Any]: Complete tool description for LLM API calls.
+        """
+        return {
+            'type': 'function',
+            'function': {
+                'name': 'call_featurizer',
+                'description': 'Record the features present in the issue.',
+                'parameters': {
+                    'type': 'object',
+                    'properties': {
+                        feature.identifier: feature.to_tool_description_field
+                        for feature in self.features
+                    },
+                },
+            },
+        }
+
+    def embed(
+        self,
+        issue_description: str,
+        llm_config: LLMConfig,
+        temperature: float = 1.0,
+        samples: int = 10,
+    ) -> FeatureEmbedding:
+        """
+        Generate a feature embedding for a single issue description.
+
+        Makes multiple LLM calls to collect samples and reduce variance in feature evaluations.
+        Each call uses tool calling to extract structured boolean feature values.
+
+        Args:
+            issue_description: The description of the issue to analyze.
+            llm_config: Configuration for the LLM to use.
+            temperature: Sampling temperature for the model. Higher values increase randomness.
+            samples: Number of samples to generate for averaging.
+
+        Returns:
+            FeatureEmbedding: Complete embedding with samples and metadata.
+        """
+        embedding_samples: list[dict[str, Any]] = []
+        response_latency: float = 0.0
+        prompt_tokens: int = 0
+        completion_tokens: int = 0
+
+        # TODO: use llm registry
+        llm = LLM(llm_config, service_id='solvability')
+
+        # Generate multiple samples to account for LLM variability
+        for _ in range(samples):
+            start_time = time.time()
+            response = llm.completion(
+                messages=[
+                    self.system_message(),
+                    self.user_message(issue_description, set_cache=(samples > 1)),
+                ],
+                tools=[self.tool_description],
+                tool_choice=self.tool_choice,
+                temperature=temperature,
+            )
+            stop_time = time.time()
+
+            # Extract timing and token usage metrics
+            latency = stop_time - start_time
+            # Parse the structured tool call response containing feature evaluations
+            features = response.choices[0].message.tool_calls[0].function.arguments  # type: ignore[index, union-attr]
+            embedding = json.loads(features)
+
+            # Accumulate results and metrics
+            embedding_samples.append(embedding)
+            prompt_tokens += response.usage.prompt_tokens  # type: ignore[union-attr, attr-defined]
+            completion_tokens += response.usage.completion_tokens  # type: ignore[union-attr, attr-defined]
+            response_latency += latency
+
+        return FeatureEmbedding(
+            samples=embedding_samples,
+            response_latency=response_latency,
+            prompt_tokens=prompt_tokens,
+            completion_tokens=completion_tokens,
+        )
+
+    def embed_batch(
+        self,
+        issue_descriptions: list[str],
+        llm_config: LLMConfig,
+        temperature: float = 1.0,
+        samples: int = 10,
+    ) -> list[FeatureEmbedding]:
+        """
+        Generate embeddings for a batch of issue descriptions using concurrent processing.
+
+        Processes multiple issues in parallel to improve throughput while maintaining
+        result ordering.
+
+        Args:
+            issue_descriptions: List of issue descriptions to analyze.
+            llm_config: Configuration for the LLM to use.
+            temperature: Sampling temperature for the model.
+            samples: Number of samples to generate per issue.
+
+        Returns:
+            list[FeatureEmbedding]: List of embeddings in the same order as input.
+        """
+        with ThreadPoolExecutor() as executor:
+            # Submit all embedding tasks concurrently
+            future_to_desc = {
+                executor.submit(
+                    self.embed,
+                    desc,
+                    llm_config,
+                    temperature=temperature,
+                    samples=samples,
+                ): i
+                for i, desc in enumerate(issue_descriptions)
+            }
+
+            # Collect results in original order to maintain consistency
+            results: list[FeatureEmbedding] = [None] * len(issue_descriptions)  # type: ignore[list-item]
+            for future in as_completed(future_to_desc):
+                index = future_to_desc[future]
+                results[index] = future.result()
+
+            return results
+
+    def feature_identifiers(self) -> list[str]:
+        """
+        Get the identifiers of all configured features.
+
+        Returns:
+            list[str]: List of feature identifiers in the order they were defined.
+        """
+        return [feature.identifier for feature in self.features]

enterprise/integrations/solvability/models/importance_strategy.py

@@ -0,0 +1,23 @@
+from enum import Enum
+
+
+class ImportanceStrategy(str, Enum):
+    """
+    Strategy to use for calculating feature importances, which are used to estimate the predictive power of each feature
+    in training loops and explanations.
+    """
+
+    SHAP = 'shap'
+    """
+    Use SHAP (SHapley Additive exPlanations) to calculate feature importances.
+    """
+
+    PERMUTATION = 'permutation'
+    """
+    Use the permutation-based feature importances.
+    """
+
+    IMPURITY = 'impurity'
+    """
+    Use the impurity-based feature importances from the RandomForestClassifier.
+    """

enterprise/integrations/solvability/models/report.py

@@ -0,0 +1,87 @@
+from datetime import datetime
+from typing import Any
+
+from integrations.solvability.models.importance_strategy import ImportanceStrategy
+from pydantic import BaseModel, Field
+
+
+class SolvabilityReport(BaseModel):
+    """
+    Comprehensive report containing solvability predictions and analysis for a single issue.
+
+    This report includes the solvability score, extracted feature values, feature importance analysis,
+    cost metrics (tokens and latency), and metadata about the prediction process. It serves as the
+    primary output format for solvability analysis and can be used for logging, debugging, and
+    generating human-readable summaries.
+    """
+
+    identifier: str
+    """
+    The identifier of the solvability model used to generate the report.
+    """
+
+    issue: str
+    """
+    The issue description for which the solvability is predicted.
+
+    This field is exactly the input to the solvability model.
+    """
+
+    score: float
+    """
+    [0, 1]-valued score indicating the likelihood of the issue being solvable.
+    """
+
+    prompt_tokens: int
+    """
+    Total number of prompt tokens used in API calls made to generate the features.
+    """
+
+    completion_tokens: int
+    """
+    Total number of completion tokens used in API calls made to generate the features.
+    """
+
+    response_latency: float
+    """
+    Total response latency of API calls made to generate the features.
+    """
+
+    features: dict[str, float]
+    """
+    [0, 1]-valued scores for each feature in the model.
+
+    These are the values fed to the random forest classifier to generate the solvability score.
+    """
+
+    samples: int
+    """
+    Number of samples used to compute the feature embedding coefficients.
+    """
+
+    importance_strategy: ImportanceStrategy
+    """
+    Strategy used to calculate feature importances.
+    """
+
+    feature_importances: dict[str, float]
+    """
+    Importance scores for each feature in the model.
+
+    Interpretation of these scores depends on the importance strategy used.
+    """
+
+    created_at: datetime = Field(default_factory=datetime.now)
+    """
+    Datetime when the report was created.
+    """
+
+    random_state: int | None = None
+    """
+    Classifier random state used when generating this report.
+    """
+
+    metadata: dict[str, Any] | None = None
+    """
+    Metadata for logging and debugging purposes.
+    """

enterprise/integrations/solvability/models/summary.py

@@ -0,0 +1,172 @@
+from __future__ import annotations
+
+import json
+from datetime import datetime
+from typing import Any
+
+from integrations.solvability.models.difficulty_level import DifficultyLevel
+from integrations.solvability.models.report import SolvabilityReport
+from integrations.solvability.prompts import load_prompt
+from pydantic import BaseModel, Field
+
+from openhands.llm import LLM
+
+
+class SolvabilitySummary(BaseModel):
+    """Summary of the solvability analysis in human-readable format."""
+
+    score: float
+    """
+    Solvability score indicating the likelihood of the issue being solvable.
+    """
+
+    summary: str
+    """
+    The executive summary content generated by the LLM.
+    """
+
+    actionable_feedback: str
+    """
+    Actionable feedback content generated by the LLM.
+    """
+
+    positive_feedback: str
+    """
+    Positive feedback content generated by the LLM, highlighting what is good about the issue.
+    """
+
+    prompt_tokens: int
+    """
+    Number of prompt tokens used in the API call to generate the summary.
+    """
+
+    completion_tokens: int
+    """
+    Number of completion tokens used in the API call to generate the summary.
+    """
+
+    response_latency: float
+    """
+    Response latency of the API call to generate the summary.
+    """
+
+    created_at: datetime = Field(default_factory=datetime.now)
+    """
+    Datetime when the summary was created.
+    """
+
+    @staticmethod
+    def tool_description() -> dict[str, Any]:
+        """Get the tool description for the LLM."""
+        return {
+            'type': 'function',
+            'function': {
+                'name': 'solvability_summary',
+                'description': 'Generate a human-readable summary of the solvability analysis.',
+                'parameters': {
+                    'type': 'object',
+                    'properties': {
+                        'summary': {
+                            'type': 'string',
+                            'description': 'A high-level (at most two sentences) summary of the solvability report.',
+                        },
+                        'actionable_feedback': {
+                            'type': 'string',
+                            'description': (
+                                'Bullet list of 1-3 pieces of actionable feedback on how the user can address the lowest scoring relevant features.'
+                            ),
+                        },
+                        'positive_feedback': {
+                            'type': 'string',
+                            'description': (
+                                'Bullet list of 1-3 pieces of positive feedback on the issue, highlighting what is good about it.'
+                            ),
+                        },
+                    },
+                    'required': ['summary', 'actionable_feedback'],
+                },
+            },
+        }
+
+    @staticmethod
+    def tool_choice() -> dict[str, Any]:
+        """Get the tool choice for the LLM."""
+        return {
+            'type': 'function',
+            'function': {
+                'name': 'solvability_summary',
+            },
+        }
+
+    @staticmethod
+    def system_message() -> dict[str, Any]:
+        """Get the system message for the LLM."""
+        return {
+            'role': 'system',
+            'content': load_prompt('summary_system_message'),
+        }
+
+    @staticmethod
+    def user_message(report: SolvabilityReport) -> dict[str, Any]:
+        """Get the user message for the LLM."""
+        return {
+            'role': 'user',
+            'content': load_prompt(
+                'summary_user_message',
+                report=report.model_dump(),
+                difficulty_level=DifficultyLevel.from_score(report.score).value[0],
+            ),
+        }
+
+    @staticmethod
+    def from_report(report: SolvabilityReport, llm: LLM) -> SolvabilitySummary:
+        """Create a SolvabilitySummary from a SolvabilityReport."""
+        import time
+
+        start_time = time.time()
+        response = llm.completion(
+            messages=[
+                SolvabilitySummary.system_message(),
+                SolvabilitySummary.user_message(report),
+            ],
+            tools=[SolvabilitySummary.tool_description()],
+            tool_choice=SolvabilitySummary.tool_choice(),
+        )
+        response_latency = time.time() - start_time
+
+        # Grab the arguments from the forced function call
+        arguments = json.loads(
+            response.choices[0].message.tool_calls[0].function.arguments
+        )
+
+        return SolvabilitySummary(
+            # The score is copied directly from the report
+            score=report.score,
+            # Performance and usage metrics are pulled from the response
+            prompt_tokens=response.usage.prompt_tokens,
+            completion_tokens=response.usage.completion_tokens,
+            response_latency=response_latency,
+            # Every other field should be taken from the forced function call
+            **arguments,
+        )
+
+    def format_as_markdown(self) -> str:
+        """Format the summary content as Markdown."""
+        # Convert score to difficulty level enum
+        difficulty_level = DifficultyLevel.from_score(self.score)
+
+        # Create the main difficulty display
+        result = f'{difficulty_level.format_display()}\n\n{self.summary}'
+
+        # If not easy, show the three features with lowest importance scores
+        if difficulty_level != DifficultyLevel.EASY:
+            # Add dropdown with lowest importance features
+            result += '\n\nYou can make the issue easier to resolve by addressing these concerns in the conversation:\n\n'
+            result += self.actionable_feedback
+
+        # If the difficulty isn't hard, add some positive feedback
+        if difficulty_level != DifficultyLevel.HARD:
+            result += '\n\nPositive feedback:\n\n'
+            result += self.positive_feedback
+
+        return result

enterprise/integrations/solvability/prompts/__init__.py

@@ -0,0 +1,13 @@
+from pathlib import Path
+
+import jinja2
+
+
+def load_prompt(prompt: str, **kwargs) -> str:
+    """Load a prompt by name. Passes all the keyword arguments to the prompt template."""
+    env = jinja2.Environment(loader=jinja2.FileSystemLoader(Path(__file__).parent))
+    template = env.get_template(f'{prompt}.j2')
+    return template.render(**kwargs)
+
+
+__all__ = ['load_prompt']

enterprise/integrations/solvability/prompts/summary_system_message.j2

@@ -0,0 +1,10 @@
+You are a helpful assistant that generates human-readable summaries of solvability reports.
+The report predicts how likely it is that the issue can be resolved, and is produced purely based on the information provided in the issue description and comments.
+The report explains which features are present in the issue and how impactful they are to the solvability score (using SHAP values).
+Your task is to create a concise, high-level summary of the solvability analysis,
+with an emphasis on the key factors that make the issue easy or hard to resolve.
+Focus on the features with extreme scores, BUT ONLY if they are related to the issue at hand after careful consideration.
+You should NEVER mention: SHAP, scores, feature names, or technical metrics.
+You will also be given the expected difficulty of the issue, as EASY/MEDIUM/HARD.
+Be sure to frame your responses with that difficulty in mind.
+For example, if the issue is HARD you should not describe it as "straightforward".

enterprise/integrations/solvability/prompts/summary_user_message.j2

@@ -0,0 +1,9 @@
+Generate a high-level summary of the solvability report:
+
+{{ report }}
+
+We estimate the issue is {{ difficulty_level }}.
+The summary should be concise (at most two sentences) and describe the primary characteristics of this issue.
+Focus on what information is present and what factors are most relevant to resolution.
+Actionable feedback should be something that can be addressed by the user purely by providing more information.
+Positive feedback should explain the features that are positively contributing to the solvability score.

enterprise/integrations/store_repo_utils.py

@@ -3,9 +3,9 @@ from storage.stored_repository import StoredRepository
 from storage.user_repo_map import UserRepositoryMap
 from storage.user_repo_map_store import UserRepositoryMapStore
 
-from openhands.app_server.integrations.service_types import Repository
 from openhands.core.config.openhands_config import OpenHandsConfig
 from openhands.core.logger import openhands_logger as logger
+from openhands.integrations.service_types import Repository
 
 
 async def store_repositories_in_db(repos: list[Repository], user_id: str) -> None:

enterprise/integrations/types.py

@@ -1,7 +1,6 @@
 from dataclasses import dataclass
 from enum import Enum
 from typing import TYPE_CHECKING
-from uuid import UUID
 
 from jinja2 import Environment
 from pydantic import BaseModel
@@ -9,8 +8,9 @@ from pydantic import BaseModel
 if TYPE_CHECKING:
     from integrations.models import Message
 
-    from openhands.app_server.integrations.provider import PROVIDER_TOKEN_TYPE
-    from openhands.app_server.user_auth.user_auth import UserAuth
+    from openhands.integrations.provider import PROVIDER_TOKEN_TYPE
+    from openhands.server.user_auth.user_auth import UserAuth
+    from openhands.storage.data_models.conversation_metadata import ConversationMetadata
 
 
 class GitLabResourceType(Enum):
@@ -53,11 +53,11 @@ class ResolverViewInterface(SummaryExtractionTracker):
         """Instructions passed when conversation is first initialized."""
         raise NotImplementedError()
 
-    async def initialize_new_conversation(self) -> UUID:
-        """Initialize a new conversation and return the conversation ID.
+    async def initialize_new_conversation(self) -> 'ConversationMetadata':
+        """Initialize a new conversation and return metadata.
 
-        This method resolves the target organization and generates a new
-        conversation ID.
+        For V1 conversations, creates a dummy ConversationMetadata.
+        For V0 conversations, initializes through the conversation store.
         """
         raise NotImplementedError()
 
@@ -65,7 +65,7 @@ class ResolverViewInterface(SummaryExtractionTracker):
         self,
         jinja_env: Environment,
         git_provider_tokens: 'PROVIDER_TOKEN_TYPE',
-        conversation_id: UUID,
+        conversation_metadata: 'ConversationMetadata',
         saas_user_auth: 'UserAuth',
     ) -> None:
         """Create a new conversation.
@@ -73,7 +73,7 @@ class ResolverViewInterface(SummaryExtractionTracker):
         Args:
             jinja_env: Jinja2 environment for template rendering
             git_provider_tokens: Token mapping for git providers
-            conversation_id: The UUID of the conversation to create
+            conversation_metadata: Metadata for the conversation
             saas_user_auth: User authentication for SaaS
         """
         raise NotImplementedError()

enterprise/integrations/utils.py

@@ -1,12 +1,24 @@
 from __future__ import annotations
 
+import json
 import os
 import re
 
 from jinja2 import Environment, FileSystemLoader
 from server.constants import WEB_HOST
+from storage.org_store import OrgStore
 
-from openhands.app_server.integrations.service_types import Repository
+from openhands.core.logger import openhands_logger as logger
+from openhands.core.schema.agent import AgentState
+from openhands.events import Event, EventSource
+from openhands.events.action import (
+    AgentFinishAction,
+    MessageAction,
+)
+from openhands.events.event_filter import EventFilter
+from openhands.events.event_store_abc import EventStoreABC
+from openhands.events.observation.agent import AgentStateChangedObservation
+from openhands.integrations.service_types import Repository
 
 # ---- DO NOT REMOVE ----
 # WARNING: Langfuse depends on the WEB_HOST environment variable being set to track events.
@@ -15,8 +27,10 @@ HOST = WEB_HOST
 
 IS_LOCAL_DEPLOYMENT = 'localhost' in HOST
 HOST_URL = f'https://{HOST}' if not IS_LOCAL_DEPLOYMENT else f'http://{HOST}'
+GITHUB_WEBHOOK_URL = f'{HOST_URL}/integration/github/events'
 GITLAB_WEBHOOK_URL = f'{HOST_URL}/integration/gitlab/events'
-CONVERSATION_URL = f'{HOST_URL}/conversations/{{}}'
+conversation_prefix = 'conversations/{}'
+CONVERSATION_URL = f'{HOST_URL}/{conversation_prefix}'
 
 # Toggle for auto-response feature that proactively starts conversations with users when workflow tests fail
 ENABLE_PROACTIVE_CONVERSATION_STARTERS = (
@@ -63,11 +77,30 @@ def get_user_not_found_message(username: str | None = None) -> str:
     return f"It looks like you haven't created an OpenHands account yet. Please sign up at [OpenHands Cloud]({HOST_URL}) and try again."
 
 
+# Toggle for solvability report feature
+ENABLE_SOLVABILITY_ANALYSIS = (
+    os.getenv('ENABLE_SOLVABILITY_ANALYSIS', 'false').lower() == 'true'
+)
+
+# Toggle for V1 GitHub resolver feature
+ENABLE_V1_GITHUB_RESOLVER = (
+    os.getenv('ENABLE_V1_GITHUB_RESOLVER', 'false').lower() == 'true'
+)
+
+ENABLE_V1_SLACK_RESOLVER = (
+    os.getenv('ENABLE_V1_SLACK_RESOLVER', 'false').lower() == 'true'
+)
+
+# Toggle for V1 GitLab resolver feature
+ENABLE_V1_GITLAB_RESOLVER = (
+    os.getenv('ENABLE_V1_GITLAB_RESOLVER', 'false').lower() == 'true'
+)
+
 OPENHANDS_RESOLVER_TEMPLATES_DIR = (
     os.getenv('OPENHANDS_RESOLVER_TEMPLATES_DIR')
-    or 'openhands/app_server/integrations/templates/resolver/'
+    or 'openhands/integrations/templates/resolver/'
 )
-_jinja_env = Environment(loader=FileSystemLoader(OPENHANDS_RESOLVER_TEMPLATES_DIR))
+jinja_env = Environment(loader=FileSystemLoader(OPENHANDS_RESOLVER_TEMPLATES_DIR))
 
 
 def get_oh_labels(web_host: str) -> tuple[str, str]:
@@ -89,11 +122,31 @@ def get_oh_labels(web_host: str) -> tuple[str, str]:
 
 
 def get_summary_instruction():
-    summary_instruction_template = _jinja_env.get_template('summary_prompt.j2')
+    summary_instruction_template = jinja_env.get_template('summary_prompt.j2')
     summary_instruction = summary_instruction_template.render()
     return summary_instruction
 
 
+async def get_user_v1_enabled_setting(user_id: str | None) -> bool:
+    """Get the user's V1 conversation API setting.
+
+    Args:
+        user_id: The keycloak user ID
+
+    Returns:
+        True if V1 conversations are enabled for this user, False otherwise
+    """
+    if not user_id:
+        return False
+
+    org = await OrgStore.get_current_org_from_keycloak_user_id(user_id)
+
+    if not org or org.v1_enabled is None:
+        return False
+
+    return org.v1_enabled
+
+
 def has_exact_mention(text: str, mention: str) -> bool:
     """Check if the text contains an exact mention (not part of a larger word).
 
@@ -120,6 +173,205 @@ def has_exact_mention(text: str, mention: str) -> bool:
     return bool(re.search(rf'(?:^|[^\w@]){pattern}(?![\w-])', text_lower))
 
 
+def confirm_event_type(event: Event):
+    return isinstance(event, AgentStateChangedObservation) and not (
+        event.agent_state == AgentState.REJECTED
+        or event.agent_state == AgentState.USER_CONFIRMED
+        or event.agent_state == AgentState.USER_REJECTED
+        or event.agent_state == AgentState.LOADING
+        or event.agent_state == AgentState.RUNNING
+    )
+
+
+def get_readable_error_reason(reason: str):
+    if reason == 'STATUS$ERROR_LLM_AUTHENTICATION':
+        reason = 'Authentication with the LLM provider failed. Please check your API key or credentials'
+    elif reason == 'STATUS$ERROR_LLM_SERVICE_UNAVAILABLE':
+        reason = 'The LLM service is temporarily unavailable. Please try again later'
+    elif reason == 'STATUS$ERROR_LLM_INTERNAL_SERVER_ERROR':
+        reason = 'The LLM provider encountered an internal error. Please try again soon'
+    elif reason == 'STATUS$ERROR_LLM_OUT_OF_CREDITS':
+        reason = "You've run out of credits. Please top up to continue"
+    elif reason == 'STATUS$ERROR_LLM_CONTENT_POLICY_VIOLATION':
+        reason = 'Content policy violation. The output was blocked by content filtering policy'
+    return reason
+
+
+def get_summary_for_agent_state(
+    observations: list[AgentStateChangedObservation], conversation_link: str
+) -> str:
+    unknown_error_msg = f'OpenHands encountered an unknown error. [See the conversation]({conversation_link}) for more information, or try again'
+
+    if len(observations) == 0:
+        logger.error(
+            'Unknown error: No agent state observations found',
+            extra={'conversation_link': conversation_link},
+        )
+        return unknown_error_msg
+
+    observation: AgentStateChangedObservation = observations[0]
+    state = observation.agent_state
+
+    if state == AgentState.RATE_LIMITED:
+        logger.warning(
+            'Agent was rate limited',
+            extra={
+                'agent_state': state.value,
+                'conversation_link': conversation_link,
+                'observation_reason': getattr(observation, 'reason', None),
+            },
+        )
+        return 'OpenHands was rate limited by the LLM provider. Please try again later.'
+
+    if state == AgentState.ERROR:
+        reason = observation.reason
+        reason = get_readable_error_reason(reason)
+
+        logger.error(
+            'Agent encountered an error',
+            extra={
+                'agent_state': state.value,
+                'conversation_link': conversation_link,
+                'observation_reason': observation.reason,
+                'readable_reason': reason,
+            },
+        )
+
+        return f'OpenHands encountered an error: **{reason}**.\n\n[See the conversation]({conversation_link}) for more information.'
+
+    if state == AgentState.AWAITING_USER_INPUT:
+        logger.info(
+            'Agent is awaiting user input',
+            extra={
+                'agent_state': state.value,
+                'conversation_link': conversation_link,
+                'observation_reason': getattr(observation, 'reason', None),
+            },
+        )
+        return f'OpenHands is waiting for your input. [Continue the conversation]({conversation_link}) to provide additional instructions.'
+
+    # Log unknown agent state as error
+    logger.error(
+        'Unknown error: Unhandled agent state',
+        extra={
+            'agent_state': state.value if hasattr(state, 'value') else str(state),
+            'conversation_link': conversation_link,
+            'observation_reason': getattr(observation, 'reason', None),
+        },
+    )
+    return unknown_error_msg
+
+
+def get_final_agent_observation(
+    event_store: EventStoreABC,
+) -> list[AgentStateChangedObservation]:
+    events = list(
+        event_store.search_events(
+            filter=EventFilter(
+                source=EventSource.ENVIRONMENT,
+                include_types=(AgentStateChangedObservation,),
+            ),
+            limit=1,
+            reverse=True,
+        )
+    )
+    result = [e for e in events if isinstance(e, AgentStateChangedObservation)]
+    assert len(result) == len(events)
+    return result
+
+
+def get_last_user_msg(event_store: EventStoreABC) -> list[MessageAction]:
+    events = list(
+        event_store.search_events(
+            filter=EventFilter(
+                source=EventSource.USER,
+                include_types=(MessageAction,),
+            ),
+            limit=1,
+            reverse=True,
+        )
+    )
+    result = [e for e in events if isinstance(e, MessageAction)]
+    assert len(result) == len(events)
+    return result
+
+
+def extract_summary_from_event_store(
+    event_store: EventStoreABC, conversation_id: str
+) -> str:
+    """
+    Get agent summary or alternative message depending on current AgentState
+    """
+    conversation_link = CONVERSATION_URL.format(conversation_id)
+    summary_instruction = get_summary_instruction()
+
+    instruction_events = list(
+        event_store.search_events(
+            filter=EventFilter(
+                query=json.dumps(summary_instruction),
+                source=EventSource.USER,
+                include_types=(MessageAction,),
+            ),
+            limit=1,
+            reverse=True,
+        )
+    )
+
+    final_agent_observation = get_final_agent_observation(event_store)
+
+    # Find summary instruction event ID
+    if not instruction_events:
+        logger.warning(
+            'no_instruction_event_found', extra={'conversation_id': conversation_id}
+        )
+        return get_summary_for_agent_state(
+            final_agent_observation, conversation_link
+        )  # Agent did not receive summary instruction
+
+    summary_events = list(
+        event_store.search_events(
+            filter=EventFilter(
+                source=EventSource.AGENT,
+                include_types=(MessageAction, AgentFinishAction),
+            ),
+            limit=1,
+            reverse=True,
+            start_id=instruction_events[0].id,
+        )
+    )
+
+    if not summary_events:
+        logger.warning(
+            'no_agent_messages_found', extra={'conversation_id': conversation_id}
+        )
+        return get_summary_for_agent_state(
+            final_agent_observation, conversation_link
+        )  # Agent failed to generate summary
+
+    summary_event = summary_events[0]
+    if isinstance(summary_event, MessageAction):
+        return summary_event.content
+
+    assert isinstance(summary_event, AgentFinishAction)
+    return summary_event.final_thought
+
+
+def append_conversation_footer(message: str, conversation_id: str) -> str:
+    """
+    Append a small footer with the conversation URL to a message.
+
+    Args:
+        message: The original message content
+        conversation_id: The conversation ID to link to
+
+    Returns:
+        The message with the conversation footer appended
+    """
+    conversation_link = CONVERSATION_URL.format(conversation_id)
+    footer = f'\n\n[View full conversation]({conversation_link})'
+    return message + footer
+
+
 def infer_repo_from_message(user_msg: str) -> list[str]:
     """
     Extract all repository names in the format 'owner/repo' from various Git provider URLs

enterprise/integrations/v1_utils.py

@@ -7,8 +7,8 @@ from pydantic import SecretStr
 from server.auth.saas_user_auth import SaasUserAuth
 from server.auth.token_manager import TokenManager
 
-from openhands.app_server.user_auth.user_auth import UserAuth
 from openhands.core.logger import openhands_logger as logger
+from openhands.server.user_auth.user_auth import UserAuth
 
 
 def is_budget_exceeded_error(error_message: str) -> bool:

enterprise/migrations/versions/109_add_llm_profiles_to_user.py

@@ -1,36 +0,0 @@
-"""Add llm_profiles column to user table.
-
-The Settings model exposes ``llm_profiles`` (saved LLM configurations plus
-the active profile name), but the SaaS path persists a flattened Settings
-dump onto the User/Org rows. Without a column here the field is silently
-dropped on store() and always defaults to empty on load(), so saved
-profiles disappear after any settings update or page refresh.
-
-The column is plain ``String`` because the ORM-level ``EncryptedJSON``
-TypeDecorator stores JSON-serialized profiles as a JWE-encrypted string —
-profiles can carry per-profile ``api_key`` values, so the at-rest
-representation must match the existing org/member encrypted-secret pattern.
-
-Revision ID: 109
-Revises: 108
-Create Date: 2026-04-28
-"""
-
-from typing import Sequence, Union
-
-import sqlalchemy as sa
-from alembic import op
-
-# revision identifiers, used by Alembic.
-revision: str = '109'
-down_revision: Union[str, None] = '108'
-branch_labels: Union[str, Sequence[str], None] = None
-depends_on: Union[str, Sequence[str], None] = None
-
-
-def upgrade() -> None:
-    op.add_column('user', sa.Column('llm_profiles', sa.String(), nullable=True))
-
-
-def downgrade() -> None:
-    op.drop_column('user', 'llm_profiles')

enterprise/migrations/versions/110_add_agent_kind_to_conversation_metadata.py

@@ -1,31 +0,0 @@
-"""Add agent_kind column to conversation_metadata table.
-
-Stores the agent type ('llm' or 'acp') for each conversation so the
-correct agent-server endpoint can be used when routing requests.
-
-Revision ID: 110
-Revises: 109
-Create Date: 2026-04-28
-"""
-
-from typing import Sequence, Union
-
-import sqlalchemy as sa
-from alembic import op
-
-# revision identifiers, used by Alembic.
-revision: str = '110'
-down_revision: Union[str, None] = '109'
-branch_labels: Union[str, Sequence[str], None] = None
-depends_on: Union[str, Sequence[str], None] = None
-
-
-def upgrade() -> None:
-    op.add_column(
-        'conversation_metadata',
-        sa.Column('agent_kind', sa.String(), nullable=True),
-    )
-
-
-def downgrade() -> None:
-    op.drop_column('conversation_metadata', 'agent_kind')

enterprise/poetry.lock

@@ -4961,14 +4961,14 @@ files = [
 
 [[package]]
 name = "lmnr"
-version = "0.7.49"
+version = "0.7.46"
 description = "Python SDK for Laminar"
 optional = false
 python-versions = "<4,>=3.10"
 groups = ["main"]
 files = [
-    {file = "lmnr-0.7.49-py3-none-any.whl", hash = "sha256:510113b02bac3e639fa80244c67ff0be5948234275b0ef04cd310d66c7d720bf"},
-    {file = "lmnr-0.7.49.tar.gz", hash = "sha256:0b6da7d1707ce4e248c15083835a70723be9e6cc652b77ddc95c12e27dc87ef3"},
+    {file = "lmnr-0.7.46-py3-none-any.whl", hash = "sha256:596599af3eb999c5fb253640967fa893d34998b78c577b8773c214d89efa81c9"},
+    {file = "lmnr-0.7.46.tar.gz", hash = "sha256:082c9d17a1962b559651eea843eff49c1ec54729654ba37388c4a360e862af78"},
 ]
 
 [package.dependencies]
@@ -4984,11 +4984,11 @@ opentelemetry-sdk = ">=1.39.0,<2.0.0"
 opentelemetry-semantic-conventions = "0.60b1"
 opentelemetry-semantic-conventions-ai = "0.4.13"
 orjson = ">=3.0.0,<4.0.0"
-packaging = ">=22.0,<27.0"
+packaging = ">=22.0"
 pydantic = ">=2.0.3,<3.0.0"
 python-dotenv = ">=1.0,<2.0"
 tenacity = ">=8.0,<10.0"
-tqdm = ">=4.0,<5.0"
+tqdm = ">=4.0"
 
 [package.extras]
 alephalpha = ["opentelemetry-instrumentation-alephalpha (==0.52.4)"]
@@ -6454,14 +6454,14 @@ llama = ["llama-index (>=0.12.29,<0.13.0)", "llama-index-core (>=0.12.29,<0.13.0
 
 [[package]]
 name = "openhands-agent-server"
-version = "1.19.0"
+version = "1.17.0"
 description = "OpenHands Agent Server - REST/WebSocket interface for OpenHands AI Agent"
 optional = false
 python-versions = ">=3.12"
 groups = ["main"]
 files = [
-    {file = "openhands_agent_server-1.19.0-py3-none-any.whl", hash = "sha256:132902dc918f446e3b0f5cda9f4da36a4881fc73fe509eb177959afe988c38bb"},
-    {file = "openhands_agent_server-1.19.0.tar.gz", hash = "sha256:4f81b5ec550881706b361c51a422b6daad2a33c73b94d2f3088c84ed32ce049e"},
+    {file = "openhands_agent_server-1.17.0-py3-none-any.whl", hash = "sha256:44336cad001c31caeb516481a5a7aea6dd9b5ab4798461f147b5231668d8fb74"},
+    {file = "openhands_agent_server-1.17.0.tar.gz", hash = "sha256:3a88449a3b9ded653dcd2a8c518810c75602873cf9f7d4e8f9b90fd8fd225652"},
 ]
 
 [package.dependencies]
@@ -6523,9 +6523,9 @@ memory-profiler = ">=0.61"
 numpy = "*"
 openai = "2.8"
 openhands-aci = "0.3.3"
-openhands-agent-server = "1.19"
-openhands-sdk = "1.19"
-openhands-tools = "1.19"
+openhands-agent-server = "1.17"
+openhands-sdk = "1.17"
+openhands-tools = "1.17"
 opentelemetry-api = ">=1.33.1"
 opentelemetry-exporter-otlp-proto-grpc = ">=1.33.1"
 orjson = ">=3.11.6"
@@ -6547,7 +6547,7 @@ python-docx = "*"
 python-dotenv = "*"
 python-frontmatter = ">=1.1"
 python-json-logger = ">=3.2.1"
-python-multipart = ">=0.0.26"
+python-multipart = ">=0.0.22"
 python-pptx = "*"
 python-socketio = "5.14"
 pythonnet = {version = "*", markers = "sys_platform == \"win32\""}
@@ -6571,20 +6571,23 @@ uvicorn = "*"
 whatthepatch = ">=1.0.6"
 zope-interface = "7.2"
 
+[package.extras]
+third-party-runtimes = ["daytona (==0.24.2)", "e2b-code-interpreter (>=2)", "modal (>=0.66.26,<1.2)", "runloop-api-client (==0.50)"]
+
 [package.source]
 type = "directory"
 url = ".."
 
 [[package]]
 name = "openhands-sdk"
-version = "1.19.0"
+version = "1.17.0"
 description = "OpenHands SDK - Core functionality for building AI agents"
 optional = false
 python-versions = ">=3.12"
 groups = ["main"]
 files = [
-    {file = "openhands_sdk-1.19.0-py3-none-any.whl", hash = "sha256:704906533da50f2d0e93bf28609b1a36a4aa4ce578bfac13a3d1a76609d87db8"},
-    {file = "openhands_sdk-1.19.0.tar.gz", hash = "sha256:5611d877e6495a712725569f6bca3de8fabefd9e44c61dc30bd39f8883371508"},
+    {file = "openhands_sdk-1.17.0-py3-none-any.whl", hash = "sha256:3b771e72209453871c3036a562cf33e9ad9642a54bd48edb44f89915ac54709d"},
+    {file = "openhands_sdk-1.17.0.tar.gz", hash = "sha256:3c69df6590f023a514137272d413658848e0d5bc9aecf941b946c8662862779a"},
 ]
 
 [package.dependencies]
@@ -6595,7 +6598,7 @@ fastmcp = ">=3.0.0"
 filelock = ">=3.20.1"
 httpx = {version = ">=0.27.0", extras = ["socks"]}
 litellm = ">=1.82.6,<1.82.7 || >1.82.7,<1.82.8 || >1.82.8"
-lmnr = ">=0.7.47"
+lmnr = ">=0.7.24"
 pydantic = ">=2.12.5"
 python-frontmatter = ">=1.1.0"
 python-json-logger = ">=3.3.0"
@@ -6607,14 +6610,14 @@ boto3 = ["boto3 (>=1.35.0)"]
 
 [[package]]
 name = "openhands-tools"
-version = "1.19.0"
+version = "1.17.0"
 description = "OpenHands Tools - Runtime tools for AI agents"
 optional = false
 python-versions = ">=3.12"
 groups = ["main"]
 files = [
-    {file = "openhands_tools-1.19.0-py3-none-any.whl", hash = "sha256:ff5ddb40d628a468eda4488b2c0045470c88e396bab43330b6b468f3ada47b9e"},
-    {file = "openhands_tools-1.19.0.tar.gz", hash = "sha256:b4dc59a813fe1fe7bda519979498a7bdf07dd8f83ea3f0aad78c154f5fcb9a32"},
+    {file = "openhands_tools-1.17.0-py3-none-any.whl", hash = "sha256:76cd30fcc153627444f18638bcd926c9190989f80a3492381e84a181c021d815"},
+    {file = "openhands_tools-1.17.0.tar.gz", hash = "sha256:4a9d6c1aec00d366d0feb1ac2e9ee9988ad9806a0ef89f7dbe4655644e639d4a"},
 ]
 
 [package.dependencies]
@@ -14144,14 +14147,6 @@ optional = false
 python-versions = ">=3.9"
 groups = ["main"]
 files = [
-    {file = "tree_sitter_c_sharp-0.23.1-cp310-abi3-macosx_10_9_x86_64.whl", hash = "sha256:e87be7572991552606a3155d2f6c2045ded8bce94bfd9f74bf521d949c219a1c"},
-    {file = "tree_sitter_c_sharp-0.23.1-cp310-abi3-macosx_11_0_arm64.whl", hash = "sha256:86c2fdf178c66474a1be2965602818d30780e4e3ed890e3c206931f65d9a154c"},
-    {file = "tree_sitter_c_sharp-0.23.1-cp310-abi3-manylinux1_x86_64.manylinux_2_28_x86_64.manylinux_2_5_x86_64.whl", hash = "sha256:035d259e64c41d02cc45afc3b8b46388b232e7d16d84734d851cca7334761da5"},
-    {file = "tree_sitter_c_sharp-0.23.1-cp310-abi3-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:fa472cb9de7e14fee9408e144f29f68384cd8e9c677dff0002da19f361a59bdf"},
-    {file = "tree_sitter_c_sharp-0.23.1-cp310-abi3-musllinux_1_2_aarch64.whl", hash = "sha256:1a0ea86eccff74e85ab4a2cf77c813fad7c84162962ce242dff0c51601028832"},
-    {file = "tree_sitter_c_sharp-0.23.1-cp310-abi3-musllinux_1_2_x86_64.whl", hash = "sha256:8ab26dc998bbd4b4287b129f67c10ca715deb402ed77d0645674490ea509097e"},
-    {file = "tree_sitter_c_sharp-0.23.1-cp310-abi3-win_amd64.whl", hash = "sha256:d4486653feaff3314ef45534dcb6f9ea8ab3aa160896287c6473788f88eb38be"},
-    {file = "tree_sitter_c_sharp-0.23.1-cp310-abi3-win_arm64.whl", hash = "sha256:e7a14b76ec23cc8386cf662d5ea602d81331376c93ca6299a97b174047790345"},
     {file = "tree_sitter_c_sharp-0.23.1-cp39-abi3-macosx_10_9_x86_64.whl", hash = "sha256:2b612a6e5bd17bb7fa2aab4bb6fc1fba45c94f09cb034ab332e45603b86e32fd"},
     {file = "tree_sitter_c_sharp-0.23.1-cp39-abi3-macosx_11_0_arm64.whl", hash = "sha256:1a8b98f62bc53efcd4d971151950c9b9cd5cbe3bacdb0cd69fdccac63350d83e"},
     {file = "tree_sitter_c_sharp-0.23.1-cp39-abi3-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:986e93d845a438ec3c4416401aa98e6a6f6631d644bbbc2e43fcb915c51d255d"},

enterprise/saas_server.py

@@ -8,6 +8,7 @@ load_dotenv()
 if not os.getenv('OPENHANDS_CONFIG_CLS'):
     os.environ['OPENHANDS_CONFIG_CLS'] = 'server.config.SaaSServerConfig'
 
+import socketio  # noqa: E402
 from fastapi import Request, status  # noqa: E402
 from fastapi.middleware.cors import CORSMiddleware  # noqa: E402
 from fastapi.responses import JSONResponse  # noqa: E402
@@ -27,6 +28,7 @@ from server.routes.api_keys import api_router as api_keys_router  # noqa: E402
 from server.routes.auth import api_router, oauth_router  # noqa: E402
 from server.routes.billing import billing_router  # noqa: E402
 from server.routes.email import api_router as email_router  # noqa: E402
+from server.routes.feedback import router as feedback_router  # noqa: E402
 from server.routes.github_proxy import add_github_proxy_routes  # noqa: E402
 from server.routes.integration.jira import jira_integration_router  # noqa: E402
 from server.routes.integration.jira_dc import jira_dc_integration_router  # noqa: E402
@@ -60,6 +62,7 @@ from server.verified_models.verified_model_router import (  # noqa: E402
 )
 
 from openhands.server.app import app as base_app  # noqa: E402
+from openhands.server.listen_socket import sio  # noqa: E402
 from openhands.server.middleware import (  # noqa: E402
     CacheControlMiddleware,
 )
@@ -144,6 +147,7 @@ if BITBUCKET_DATA_CENTER_HOST:
 
     base_app.include_router(bitbucket_dc_proxy_router)
 base_app.include_router(email_router)  # Add routes for email management
+base_app.include_router(feedback_router)  # Add routes for conversation feedback
 
 
 base_app.add_middleware(
@@ -176,5 +180,4 @@ async def expired_exception_handler(request: Request, exc: ExpiredError):
     return JSONResponse({'error': ExpiredError.__name__}, status.HTTP_401_UNAUTHORIZED)
 
 
-# Note: socketio is no longer used for communication. The base FastAPI app is used directly.
-app = base_app
+app = socketio.ASGIApp(sio, other_asgi_app=base_app)

enterprise/server/auth/authorization.py

@@ -40,8 +40,8 @@ from storage.org_member_store import OrgMemberStore
 from storage.role import Role
 from storage.role_store import RoleStore
 
-from openhands.app_server.user_auth import get_user_auth, get_user_id
 from openhands.core.logger import openhands_logger as logger
+from openhands.server.user_auth import get_user_auth, get_user_id
 
 
 class Permission(str, Enum):

enterprise/server/auth/constants.py

@@ -1,7 +1,5 @@
 import os
 
-from openhands.app_server.integrations.gitlab.constants import GITLAB_HOST
-
 GITHUB_APP_CLIENT_ID = os.getenv('GITHUB_APP_CLIENT_ID', '').strip()
 GITHUB_APP_CLIENT_SECRET = os.getenv('GITHUB_APP_CLIENT_SECRET', '').strip()
 GITHUB_APP_WEBHOOK_SECRET = os.getenv('GITHUB_APP_WEBHOOK_SECRET', '')
@@ -16,7 +14,6 @@ KEYCLOAK_SERVER_URL_EXT = os.getenv(
 KEYCLOAK_ADMIN_PASSWORD = os.getenv('KEYCLOAK_ADMIN_PASSWORD', '')
 GITLAB_APP_CLIENT_ID = os.getenv('GITLAB_APP_CLIENT_ID', '').strip()
 GITLAB_APP_CLIENT_SECRET = os.getenv('GITLAB_APP_CLIENT_SECRET', '').strip()
-GITLAB_TOKEN_URL = f'https://{GITLAB_HOST}/oauth/token'
 BITBUCKET_APP_CLIENT_ID = os.getenv('BITBUCKET_APP_CLIENT_ID', '').strip()
 BITBUCKET_APP_CLIENT_SECRET = os.getenv('BITBUCKET_APP_CLIENT_SECRET', '').strip()
 ENABLE_ENTERPRISE_SSO = os.getenv('ENABLE_ENTERPRISE_SSO', '').strip()

enterprise/server/auth/github_utils.py

@@ -2,8 +2,8 @@ from integrations.github.github_service import SaaSGitHubService
 from pydantic import SecretStr
 from server.auth.auth_utils import user_verifier
 
-from openhands.app_server.integrations.github.github_types import GitHubUser
 from openhands.core.logger import openhands_logger as logger
+from openhands.integrations.github.github_types import GitHubUser
 
 
 def is_user_allowed(user_login: str):

enterprise/server/auth/gitlab_sync.py

@@ -3,8 +3,8 @@ import asyncio
 from pydantic import SecretStr
 from sqlalchemy import select
 
-from openhands.app_server.integrations.service_types import ProviderType
 from openhands.core.logger import openhands_logger as logger
+from openhands.integrations.service_types import ProviderType
 from openhands.server.types import AppMode
 
 
@@ -55,7 +55,7 @@ def schedule_gitlab_repo_sync(
 
             # Lazy import to avoid circular dependency:
             # middleware -> gitlab_sync -> integrations.gitlab.gitlab_service
-            # -> openhands.app_server.integrations.gitlab.gitlab_service -> get_impl
+            # -> openhands.integrations.gitlab.gitlab_service -> get_impl
             # -> integrations.gitlab.gitlab_service (circular)
             from integrations.gitlab.gitlab_service import SaaSGitLabService
 

enterprise/server/auth/saas_user_auth.py

@@ -35,15 +35,15 @@ from storage.user_authorization_store import UserAuthorizationStore
 from storage.user_store import UserStore
 from tenacity import retry, retry_if_exception_type, stop_after_attempt, wait_fixed
 
-from openhands.app_server.integrations.provider import (
+from openhands.integrations.provider import (
     PROVIDER_TOKEN_TYPE,
     ProviderToken,
     ProviderType,
 )
-from openhands.app_server.secrets.secrets_models import Secrets
-from openhands.app_server.settings.settings_models import Settings
-from openhands.app_server.settings.settings_store import SettingsStore
-from openhands.app_server.user_auth.user_auth import AuthType, UserAuth
+from openhands.server.settings import Settings
+from openhands.server.user_auth.user_auth import AuthType, UserAuth
+from openhands.storage.data_models.secrets import Secrets
+from openhands.storage.settings.settings_store import SettingsStore
 
 token_manager = TokenManager()
 

enterprise/server/auth/token_manager.py

@@ -30,7 +30,6 @@ from server.auth.constants import (
     GITHUB_APP_CLIENT_SECRET,
     GITLAB_APP_CLIENT_ID,
     GITLAB_APP_CLIENT_SECRET,
-    GITLAB_TOKEN_URL,
     KEYCLOAK_REALM_NAME,
     KEYCLOAK_SERVER_URL,
     KEYCLOAK_SERVER_URL_EXT,
@@ -51,7 +50,7 @@ from storage.github_app_installation import GithubAppInstallation
 from storage.offline_token_store import OfflineTokenStore
 from tenacity import RetryCallState, retry, retry_if_exception_type, stop_after_attempt
 
-from openhands.app_server.integrations.service_types import ProviderType
+from openhands.integrations.service_types import ProviderType
 from openhands.server.types import SessionExpiredError
 from openhands.utils.http_session import httpx_verify_option
 
@@ -418,7 +417,7 @@ class TokenManager:
             return await self._parse_refresh_response(data)
 
     async def _refresh_gitlab_token(self, refresh_token: str) -> dict[str, str | int]:
-        url = GITLAB_TOKEN_URL
+        url = 'https://gitlab.com/oauth/token'
         logger.info(f'Refreshing GitLab token with URL: {url}')
 
         payload = {

enterprise/server/config.py

@@ -22,8 +22,8 @@ from server.auth.constants import (
 )
 from server.constants import DEPLOYMENT_MODE
 
-from openhands.app_server.integrations.service_types import ProviderType
 from openhands.core.config.utils import load_openhands_config
+from openhands.integrations.service_types import ProviderType
 from openhands.server.config.server_config import ServerConfig
 from openhands.server.types import AppMode
 
@@ -72,6 +72,12 @@ class SaaSServerConfig(ServerConfig):
     auth_url: str | None = os.environ.get('AUTH_URL')
     settings_store_class: str = 'storage.saas_settings_store.SaasSettingsStore'
     secret_store_class: str = 'storage.saas_secrets_store.SaasSecretsStore'
+    conversation_store_class: str = (
+        'storage.saas_conversation_store.SaasConversationStore'
+    )
+    monitoring_listener_class: str = (
+        'server.saas_monitoring_listener.SaaSMonitoringListener'
+    )
     user_auth_class: str = 'server.auth.saas_user_auth.SaasUserAuth'
     # Maintenance window configuration
     maintenance_start_time: str = os.environ.get(

enterprise/server/email_validation.py

@@ -4,8 +4,8 @@ Email domain validation utilities for enterprise endpoints.
 
 from fastapi import Depends, HTTPException, Request, status
 
-from openhands.app_server.user_auth import get_user_auth, get_user_id
 from openhands.core.logger import openhands_logger as logger
+from openhands.server.user_auth import get_user_auth, get_user_id
 
 
 async def get_admin_user_id(

enterprise/server/middleware.py

@@ -15,9 +15,9 @@ from server.auth.saas_user_auth import SaasUserAuth, token_manager
 from server.routes.auth import set_response_cookie
 from server.utils.url_utils import get_cookie_domain, get_cookie_samesite
 
-from openhands.app_server.user_auth.user_auth import AuthType, UserAuth, get_user_auth
 from openhands.core.logger import openhands_logger as logger
-from openhands.server.shared import config
+from openhands.server.user_auth.user_auth import AuthType, UserAuth, get_user_auth
+from openhands.server.utils import config
 
 
 class SetAuthCookieMiddleware:

enterprise/server/models/user_models.py

@@ -2,8 +2,8 @@
 
 from pydantic import BaseModel
 
-from openhands.app_server.integrations.service_types import ProviderType
 from openhands.app_server.user.user_models import UserInfo
+from openhands.integrations.service_types import ProviderType
 
 
 class SaasUserInfo(UserInfo):

enterprise/server/routes/api_keys.py

@@ -12,9 +12,9 @@ from storage.org_member_store import OrgMemberStore
 from storage.org_service import OrgService
 from storage.user_store import UserStore
 
-from openhands.app_server.user_auth import get_user_auth, get_user_id
-from openhands.app_server.user_auth.user_auth import AuthType
 from openhands.core.logger import openhands_logger as logger
+from openhands.server.user_auth import get_user_auth, get_user_id
+from openhands.server.user_auth.user_auth import AuthType
 
 
 # Helper functions for BYOR API key management

enterprise/server/routes/auth.py

@@ -3,7 +3,6 @@ import json
 import uuid
 import warnings
 from datetime import datetime, timezone
-from types import MappingProxyType
 from typing import Annotated, Optional, cast
 from urllib.parse import quote, urlencode
 from uuid import UUID as parse_uuid
@@ -47,16 +46,13 @@ from storage.database import a_session_maker
 from storage.user import User
 from storage.user_store import UserStore
 
-from openhands.app_server.integrations.provider import (
-    PROVIDER_TOKEN_TYPE,
-    ProviderHandler,
-    ProviderToken,
-)
-from openhands.app_server.integrations.service_types import ProviderType, TokenResponse
-from openhands.app_server.user_auth import get_access_token
-from openhands.app_server.user_auth.user_auth import get_user_auth
 from openhands.core.logger import openhands_logger as logger
+from openhands.integrations.provider import ProviderHandler
+from openhands.integrations.service_types import ProviderType, TokenResponse
+from openhands.server.services.conversation_service import create_provider_tokens_object
 from openhands.server.shared import config
+from openhands.server.user_auth import get_access_token
+from openhands.server.user_auth.user_auth import get_user_auth
 
 with warnings.catch_warnings():
     warnings.simplefilter('ignore')
@@ -67,18 +63,6 @@ oauth_router = APIRouter(prefix='/oauth')
 token_manager = TokenManager()
 
 
-def create_provider_tokens_object(
-    providers_set: list[ProviderType],
-) -> PROVIDER_TOKEN_TYPE:
-    """Create provider tokens object for the given providers."""
-    provider_information: dict[ProviderType, ProviderToken] = {}
-
-    for provider in providers_set:
-        provider_information[provider] = ProviderToken(token=None, user_id=None)
-
-    return MappingProxyType(provider_information)
-
-
 def set_response_cookie(
     request: Request,
     response: Response,
@@ -719,41 +703,6 @@ async def accept_tos(request: Request):
     return response
 
 
-@api_router.get('/onboarding_status')
-async def onboarding_status(request: Request):
-    """Return whether the current user must still complete onboarding.
-
-    Kept as a dedicated endpoint instead of riding on ``GET /api/v1/settings``
-    (the natural home for fields like ``email_verified``) because the settings
-    response is heavyweight: ``SaasSettingsStore.load`` joins User, Org, and
-    OrgMember rows and deep-merges the org-level and member-level
-    ``agent_settings`` before returning. Onboarding gating runs on every
-    protected-route navigation, so we need a lightweight read of a single
-    boolean rather than paying for the full settings aggregation.
-    """
-    user_auth = cast(SaasUserAuth, await get_user_auth(request))
-    user_id = await user_auth.get_user_id()
-
-    if not user_id:
-        return JSONResponse(
-            status_code=status.HTTP_401_UNAUTHORIZED,
-            content={'error': 'User is not authenticated'},
-        )
-
-    user = await UserStore.get_user_by_id(user_id)
-    if not user:
-        return JSONResponse(
-            status_code=status.HTTP_404_NOT_FOUND,
-            content={'error': 'User not found'},
-        )
-
-    should_complete = await _should_redirect_to_onboarding(user_id, user)
-    return JSONResponse(
-        status_code=status.HTTP_200_OK,
-        content={'should_complete_onboarding': should_complete},
-    )
-
-
 @api_router.post('/complete_onboarding')
 async def complete_onboarding(request: Request):
     """Mark onboarding as completed for the current user."""

enterprise/server/routes/billing.py

@@ -21,7 +21,7 @@ from storage.subscription_access import SubscriptionAccess
 from storage.user_store import UserStore
 
 from openhands.app_server.config import get_global_config
-from openhands.app_server.user_auth import get_user_id
+from openhands.server.user_auth import get_user_id
 
 stripe.api_key = STRIPE_API_KEY
 billing_router = APIRouter(prefix='/api/billing', tags=['Billing'])

enterprise/server/routes/email.py

@@ -13,9 +13,9 @@ from server.utils.rate_limit_utils import check_rate_limit_by_user_id
 from server.utils.url_utils import get_web_url
 from storage.user_store import UserStore
 
-from openhands.app_server.user_auth import get_user_id
-from openhands.app_server.user_auth.user_auth import get_user_auth
 from openhands.core.logger import openhands_logger as logger
+from openhands.server.user_auth import get_user_id
+from openhands.server.user_auth.user_auth import get_user_auth
 
 # Email validation regex pattern
 EMAIL_REGEX = re.compile(r'^[a-zA-Z0-9._%+-]+@[a-zA-Z0-9.-]+\.[a-zA-Z]{2,}$')

enterprise/server/routes/feedback.py

@@ -0,0 +1,145 @@
+from typing import Any, Dict, List, Optional
+
+from fastapi import APIRouter, Depends, HTTPException, status
+from pydantic import BaseModel, Field
+from sqlalchemy.future import select
+from storage.database import a_session_maker
+from storage.feedback import ConversationFeedback
+from storage.stored_conversation_metadata_saas import StoredConversationMetadataSaas
+
+from openhands.app_server.utils.dependencies import get_dependencies
+from openhands.events.event_store import EventStore
+from openhands.server.shared import file_store
+from openhands.server.user_auth import get_user_id
+
+# We use the get_dependencies method here to signal to the OpenAPI docs that this endpoint
+# is protected. The actual protection is provided by SetAuthCookieMiddleware
+# TODO: It may be an error by you can actually post feedback to a conversation you don't
+# own right now - maybe this is useful in the context of public shared conversations?
+router = APIRouter(
+    prefix='/feedback', tags=['feedback'], dependencies=get_dependencies()
+)
+
+
+async def get_event_ids(conversation_id: str, user_id: str) -> List[int]:
+    """Get all event IDs for a given conversation.
+
+    Args:
+        conversation_id: The ID of the conversation to get events for
+        user_id: The ID of the user who owns the conversation
+
+    Returns:
+        List of event IDs in the conversation
+
+    Raises:
+        HTTPException: If conversation metadata not found
+    """
+
+    # Verify the conversation belongs to the user
+    async with a_session_maker() as session:
+        result = await session.execute(
+            select(StoredConversationMetadataSaas).where(
+                StoredConversationMetadataSaas.conversation_id == conversation_id,
+                StoredConversationMetadataSaas.user_id == user_id,
+            )
+        )
+        metadata = result.scalars().first()
+        if not metadata:
+            raise HTTPException(
+                status_code=status.HTTP_404_NOT_FOUND,
+                detail=f'Conversation {conversation_id} not found',
+            )
+
+    # Create an event store to access the events directly
+    # This works even when the conversation is not running
+    event_store = EventStore(
+        sid=conversation_id,
+        file_store=file_store,
+        user_id=user_id,
+    )
+
+    # Get events from the event store
+    events = event_store.search_events(start_id=0)
+
+    # Return list of event IDs
+    return [event.id for event in events]
+
+
+class FeedbackRequest(BaseModel):
+    conversation_id: str
+    event_id: Optional[int] = None
+    rating: int = Field(..., ge=1, le=5)
+    reason: Optional[str] = None
+    metadata: Optional[Dict[str, Any]] = None
+
+
+@router.post('/conversation', status_code=status.HTTP_201_CREATED)
+async def submit_conversation_feedback(feedback: FeedbackRequest):
+    """
+    Submit feedback for a conversation.
+
+    This endpoint accepts a rating (1-5) and optional reason for the feedback.
+    The feedback is associated with a specific conversation and optionally a specific event.
+    """
+    # Validate rating is between 1 and 5
+    if feedback.rating < 1 or feedback.rating > 5:
+        raise HTTPException(
+            status_code=status.HTTP_400_BAD_REQUEST,
+            detail='Rating must be between 1 and 5',
+        )
+
+    # Create new feedback record
+    new_feedback = ConversationFeedback(
+        conversation_id=feedback.conversation_id,
+        event_id=feedback.event_id,
+        rating=feedback.rating,
+        reason=feedback.reason,
+        metadata=feedback.metadata,
+    )
+
+    # Add to database
+    async with a_session_maker() as session:
+        session.add(new_feedback)
+        await session.commit()
+
+    return {'status': 'success', 'message': 'Feedback submitted successfully'}
+
+
+@router.get('/conversation/{conversation_id}/batch')
+async def get_batch_feedback(conversation_id: str, user_id: str = Depends(get_user_id)):
+    """
+    Get feedback for all events in a conversation.
+
+    Returns feedback status for each event, including whether feedback exists
+    and if so, the rating and reason.
+    """
+    # Get all event IDs for the conversation
+    event_ids = await get_event_ids(conversation_id, user_id)
+    if not event_ids:
+        return {}
+
+    # Query for existing feedback for all events
+    async with a_session_maker() as session:
+        result = await session.execute(
+            select(ConversationFeedback).where(
+                ConversationFeedback.conversation_id == conversation_id,
+                ConversationFeedback.event_id.in_(event_ids),
+            )
+        )
+
+        # Create a mapping of event_id to feedback
+        feedback_map = {
+            feedback.event_id: {
+                'exists': True,
+                'rating': feedback.rating,
+                'reason': feedback.reason,
+            }
+            for feedback in result.scalars()
+        }
+
+        # Build response including all events
+        response = {}
+        for event_id in event_ids:
+            response[str(event_id)] = feedback_map.get(event_id, {'exists': False})
+
+        return response

enterprise/server/routes/integration/github.py

@@ -15,8 +15,8 @@ from server.auth.constants import (
 from server.auth.token_manager import TokenManager
 from server.services.automation_event_service import AutomationEventService
 
-from openhands.app_server.integrations.provider import ProviderType
 from openhands.core.logger import openhands_logger as logger
+from openhands.integrations.provider import ProviderType
 
 # Environment variable to disable GitHub webhooks
 GITHUB_WEBHOOKS_ENABLED = os.environ.get('GITHUB_WEBHOOKS_ENABLED', '1') in (

enterprise/server/routes/integration/gitlab.py

@@ -2,7 +2,15 @@ import asyncio
 import hashlib
 import json
 
-from fastapi import APIRouter, Depends, Header, HTTPException, Request, status
+from fastapi import (
+    APIRouter,
+    BackgroundTasks,
+    Depends,
+    Header,
+    HTTPException,
+    Request,
+    status,
+)
 from fastapi.responses import JSONResponse
 from integrations.gitlab.gitlab_manager import GitlabManager
 from integrations.gitlab.gitlab_service import SaaSGitLabService
@@ -15,20 +23,24 @@ from integrations.models import Message, SourceType
 from integrations.types import GitLabResourceType
 from integrations.utils import GITLAB_WEBHOOK_URL, IS_LOCAL_DEPLOYMENT
 from pydantic import BaseModel
+from server.auth.constants import AUTOMATION_EVENT_FORWARDING_ENABLED
 from server.auth.token_manager import TokenManager
+from server.services.automation_event_service import AutomationEventService
 from storage.gitlab_webhook import GitlabWebhook
 from storage.gitlab_webhook_store import GitlabWebhookStore
-from storage.redis import get_redis_client_async
 
-from openhands.app_server.integrations.gitlab.gitlab_service import GitLabServiceImpl
-from openhands.app_server.user_auth import get_user_id
 from openhands.core.logger import openhands_logger as logger
+from openhands.integrations.gitlab.gitlab_service import GitLabServiceImpl
+from openhands.integrations.provider import ProviderType
+from openhands.server.shared import sio
+from openhands.server.user_auth import get_user_id
 
 gitlab_integration_router = APIRouter(prefix='/integration')
 webhook_store = GitlabWebhookStore()
 
 token_manager = TokenManager()
 gitlab_manager = GitlabManager(token_manager)
+automation_event_service = AutomationEventService(token_manager)
 
 
 # Request/Response models
@@ -82,6 +94,7 @@ async def verify_gitlab_signature(
 @gitlab_integration_router.post('/gitlab/events')
 async def gitlab_events(
     request: Request,
+    background_tasks: BackgroundTasks,
     x_gitlab_token: str = Header(None),
     x_openhands_webhook_id: str = Header(None),
     x_openhands_user_id: str = Header(None),
@@ -103,7 +116,7 @@ async def gitlab_events(
             dedup_hash = hashlib.sha256(dedup_json.encode()).hexdigest()
             dedup_key = f'gitlab_msg: {dedup_hash}'
 
-        redis = get_redis_client_async()
+        redis = sio.manager.redis
         created = await redis.set(dedup_key, 1, nx=True, ex=60)
         if not created:
             logger.info('gitlab_is_duplicate')
@@ -112,6 +125,16 @@ async def gitlab_events(
                 content={'message': 'Duplicate GitLab event ignored.'},
             )
 
+        # Forward to automation service (fire-and-forget background task)
+        if AUTOMATION_EVENT_FORWARDING_ENABLED:
+            background_tasks.add_task(
+                automation_event_service.forward_event,
+                provider=ProviderType.GITLAB,
+                payload=payload_data,
+                installation_id=x_openhands_webhook_id,
+            )
+
+        # Existing resolver bot processing
         message = Message(
             source=SourceType.GITLAB,
             message={

enterprise/server/routes/integration/jira.py

@@ -18,10 +18,10 @@ from server.auth.constants import JIRA_CLIENT_ID, JIRA_CLIENT_SECRET
 from server.auth.saas_user_auth import SaasUserAuth
 from server.auth.token_manager import TokenManager
 from storage.jira_workspace import JiraWorkspace
-from storage.redis import get_redis_client
+from storage.redis import create_redis_client
 
-from openhands.app_server.user_auth.user_auth import get_user_auth
 from openhands.core.logger import openhands_logger as logger
+from openhands.server.user_auth.user_auth import get_user_auth
 
 # Environment variable to disable Jira webhooks
 JIRA_WEBHOOKS_ENABLED = os.environ.get('JIRA_WEBHOOKS_ENABLED', '0') in (
@@ -123,7 +123,7 @@ class JiraValidateWorkspaceResponse(BaseModel):
 jira_integration_router = APIRouter(prefix='/integration/jira')
 token_manager = TokenManager()
 jira_manager = JiraManager(token_manager)
-redis_client = get_redis_client()
+redis_client = create_redis_client()
 
 
 async def verify_jira_signature(body: bytes, signature: str, payload: dict):

enterprise/server/routes/integration/jira_dc.py

@@ -26,10 +26,10 @@ from server.auth.constants import (
 from server.auth.saas_user_auth import SaasUserAuth
 from server.auth.token_manager import TokenManager
 from server.constants import WEB_HOST
-from storage.redis import get_redis_client
+from storage.redis import create_redis_client
 
-from openhands.app_server.user_auth.user_auth import get_user_auth
 from openhands.core.logger import openhands_logger as logger
+from openhands.server.user_auth.user_auth import get_user_auth
 
 # Environment variable to disable Jira DC webhooks
 JIRA_DC_WEBHOOKS_ENABLED = os.environ.get('JIRA_DC_WEBHOOKS_ENABLED', '0') in (
@@ -129,7 +129,7 @@ class JiraDcValidateWorkspaceResponse(BaseModel):
 jira_dc_integration_router = APIRouter(prefix='/integration/jira-dc')
 token_manager = TokenManager()
 jira_dc_manager = JiraDcManager(token_manager)
-redis_client = get_redis_client()
+redis_client = create_redis_client()
 
 
 async def _handle_workspace_link_creation(

enterprise/server/routes/integration/slack.py

@@ -29,38 +29,24 @@ from server.constants import (
     SLACK_WEBHOOKS_ENABLED,
 )
 from server.logger import logger
-from slack_sdk.errors import SlackApiError
 from slack_sdk.oauth import AuthorizeUrlGenerator
 from slack_sdk.signature import SignatureVerifier
 from slack_sdk.web.async_client import AsyncWebClient
 from sqlalchemy import delete
 from storage.database import a_session_maker
-from storage.redis import get_redis_client_async
 from storage.slack_team_store import SlackTeamStore
 from storage.slack_user import SlackUser
 from storage.user_store import UserStore
 
-from openhands.app_server.integrations.service_types import (
-    ProviderTimeoutError,
-    ProviderType,
-)
-from openhands.server.shared import config
+from openhands.integrations.service_types import ProviderTimeoutError, ProviderType
+from openhands.server.shared import config, sio
 
 signature_verifier = SignatureVerifier(signing_secret=SLACK_SIGNING_SECRET)
 slack_router = APIRouter(prefix='/slack')
 
 # Build https://slack.com/oauth/v2/authorize with sufficient query parameters
 authorize_url_generator = AuthorizeUrlGenerator(
-    client_id=SLACK_CLIENT_ID,
-    scopes=[
-        'app_mentions:read',
-        'chat:write',
-        'users:read',
-        'channels:history',
-        'groups:history',
-        'mpim:history',
-        'im:history',
-    ],
+    client_id=SLACK_CLIENT_ID, scopes=['app_mentions:read', 'chat:write']
 )
 token_manager = TokenManager()
 
@@ -246,24 +232,7 @@ async def keycloak_callback(
 
     # Retrieve the display_name from slack
     client = AsyncWebClient(token=bot_access_token)
-    try:
-        slack_user_info = await client.users_info(user=slack_user_id)
-    except SlackApiError as e:
-        if e.response.get('error') == 'missing_scope':
-            logger.warning(
-                'slack_missing_scope_during_install',
-                extra={'slack_user_id': slack_user_id, 'team_id': team_id},
-            )
-            return _html_response(
-                title='Re-installation Required',
-                description=(
-                    'The Slack app is missing required permissions. '
-                    f'Please <a href="{HOST_URL}/slack/install" style="color:#ecedee;text-decoration:underline;">re-install the OpenHands Slack App</a> '
-                    'to authorize the updated permissions.'
-                ),
-                status_code=400,
-            )
-        raise
+    slack_user_info = await client.users_info(user=slack_user_id)
     slack_display_name = slack_user_info.data['user']['profile']['display_name']
     slack_user = SlackUser(
         keycloak_user_id=keycloak_user_id,
@@ -328,7 +297,7 @@ async def on_event(request: Request, background_tasks: BackgroundTasks):
     team_id = payload['team_id']
 
     # Sometimes slack sends duplicates, so we need to make sure this is not a duplicate.
-    redis = get_redis_client_async()
+    redis = sio.manager.redis
     key = f'slack_msg:{client_msg_id}'
     created = await redis.set(key, 1, nx=True, ex=60)
     if not created:
@@ -397,7 +366,7 @@ async def on_options_load(request: Request, background_tasks: BackgroundTasks):
     # Verify this is a block_suggestion payload
     if payload.get('type') != 'block_suggestion':
         logger.warning(
-            f'slack_on_options_load: Unexpected payload type: {payload.get("type")}'
+            f"slack_on_options_load: Unexpected payload type: {payload.get('type')}"
         )
         return JSONResponse({'options': []})
 

enterprise/server/routes/mcp_patch.py

@@ -3,8 +3,8 @@ import os
 from fastmcp import Client, FastMCP
 from fastmcp.client.transports import NpxStdioTransport
 
-from openhands.app_server.mcp.mcp_router import mcp_server
 from openhands.core.logger import openhands_logger as logger
+from openhands.server.routes.mcp import mcp_server
 
 ENABLE_MCP_SEARCH_ENGINE = (
     os.getenv('ENABLE_MCP_SEARCH_ENGINE', 'false').lower() == 'true'

enterprise/server/routes/oauth_device.py

@@ -10,8 +10,8 @@ from server.utils.url_utils import get_web_url
 from storage.api_key_store import ApiKeyStore
 from storage.device_code_store import DeviceCodeStore
 
-from openhands.app_server.user_auth import get_user_id
 from openhands.core.logger import openhands_logger as logger
+from openhands.server.user_auth import get_user_id
 
 # ---------------------------------------------------------------------------
 # Constants

enterprise/server/routes/org_invitations.py

@@ -22,8 +22,8 @@ from server.utils.rate_limit_utils import check_rate_limit_by_user_id
 from storage.org_store import OrgStore
 from storage.role_store import RoleStore
 
-from openhands.app_server.user_auth import get_user_id
 from openhands.core.logger import openhands_logger as logger
+from openhands.server.user_auth import get_user_id
 
 # Router for invitation operations on an organization (requires org_id)
 invitation_router = APIRouter(prefix='/api/organizations/{org_id}/members')

enterprise/server/routes/org_models.py

@@ -162,6 +162,7 @@ class OrgResponse(BaseModel):
     search_api_key: str | None = None
     sandbox_api_key: str | None = None
     max_budget_per_task: float | None = None
+    enable_solvability_analysis: bool | None = None
     v1_enabled: bool | None = None
     credits: float | None = None
     is_personal: bool = False
@@ -194,6 +195,7 @@ class OrgResponse(BaseModel):
             search_api_key=None,
             sandbox_api_key=None,
             max_budget_per_task=org.max_budget_per_task,
+            enable_solvability_analysis=org.enable_solvability_analysis,
             v1_enabled=org.v1_enabled,
             credits=credits,
             is_personal=str(org.id) == user_id if user_id else False,
@@ -230,6 +232,7 @@ class OrgUpdate(BaseModel):
     sandbox_runtime_container_image: str | None = None
     sandbox_api_key: str | None = None
     max_budget_per_task: float | None = Field(default=None, gt=0)
+    enable_solvability_analysis: bool | None = None
     v1_enabled: bool | None = None
     search_api_key: str | None = None
     llm_api_key: str | None = None
@@ -550,6 +553,7 @@ class OrgAppSettingsResponse(BaseModel):
     """Response model for organization app settings."""
 
     enable_proactive_conversation_starters: bool = True
+    enable_solvability_analysis: bool | None = None
     max_budget_per_task: float | None = None
 
     @classmethod
@@ -566,6 +570,7 @@ class OrgAppSettingsResponse(BaseModel):
             enable_proactive_conversation_starters=org.enable_proactive_conversation_starters
             if org.enable_proactive_conversation_starters is not None
             else True,
+            enable_solvability_analysis=org.enable_solvability_analysis,
             max_budget_per_task=org.max_budget_per_task,
         )
 
@@ -574,6 +579,7 @@ class OrgAppSettingsUpdate(BaseModel):
     """Request model for updating organization app settings."""
 
     enable_proactive_conversation_starters: bool | None = None
+    enable_solvability_analysis: bool | None = None
     max_budget_per_task: float | None = None
 
     @field_validator('max_budget_per_task')

enterprise/server/routes/orgs.py

@@ -50,8 +50,8 @@ from storage.org_service import OrgService
 from storage.org_store import OrgStore
 from storage.user_store import UserStore
 
-from openhands.app_server.user_auth import get_user_id
 from openhands.core.logger import openhands_logger as logger
+from openhands.server.user_auth import get_user_id
 
 # Initialize API router
 org_router = APIRouter(prefix='/api/organizations', tags=['Orgs'])

enterprise/server/routes/readiness.py

@@ -1,7 +1,7 @@
 from fastapi import APIRouter, HTTPException, status
 from sqlalchemy.sql import text
 from storage.database import a_session_maker
-from storage.redis import get_redis_client
+from storage.redis import create_redis_client
 
 from openhands.core.logger import openhands_logger as logger
 
@@ -23,7 +23,7 @@ async def is_ready():
 
     # Check Redis connection
     try:
-        redis_client = get_redis_client()
+        redis_client = create_redis_client()
         redis_client.ping()
     except Exception as e:
         logger.error(f'Redis check failed: {str(e)}')

enterprise/server/routes/users_v1.py

@@ -17,12 +17,12 @@ from openhands.app_server.config import (
     depends_user_context,
     resolve_provider_llm_base_url,
 )
-from openhands.app_server.integrations.provider import ProviderHandler
-from openhands.app_server.integrations.service_types import ProviderType
 from openhands.app_server.sandbox.session_auth import validate_session_key_ownership
 from openhands.app_server.user.auth_user_context import AuthUserContext
 from openhands.app_server.user.user_context import UserContext
 from openhands.app_server.utils.dependencies import get_dependencies
+from openhands.integrations.provider import ProviderHandler
+from openhands.integrations.service_types import ProviderType
 
 _logger = logging.getLogger(__name__)
 

enterprise/server/saas_monitoring_listener.py

@@ -0,0 +1,55 @@
+from server.logger import logger
+
+from openhands.core.config.openhands_config import OpenHandsConfig
+from openhands.core.schema.agent import AgentState
+from openhands.events.event import Event
+from openhands.events.observation import (
+    AgentStateChangedObservation,
+)
+from openhands.server.monitoring import MonitoringListener
+
+
+class SaaSMonitoringListener(MonitoringListener):
+    """Forward app signals to structured logging for GCP native monitoring."""
+
+    def on_session_event(self, event: Event) -> None:
+        """Track metrics about events being added to a Session's EventStream."""
+        if (
+            isinstance(event, AgentStateChangedObservation)
+            and event.agent_state == AgentState.ERROR
+        ):
+            logger.info(
+                'Tracking agent status error',
+                extra={'signal': 'saas_agent_status_errors'},
+            )
+
+    def on_agent_session_start(self, success: bool, duration: float) -> None:
+        """Track an agent session start.
+
+        Success is true if startup completed without error.
+        Duration is start time in seconds observed by AgentSession.
+        """
+        logger.info(
+            'Tracking agent session start',
+            extra={
+                'signal': 'saas_agent_session_start',
+                'success': success,
+                'duration': duration,
+            },
+        )
+
+    def on_create_conversation(self) -> None:
+        """Track the beginning of conversation creation.
+
+        Does not currently capture whether it succeed.
+        """
+        logger.info(
+            'Tracking create conversation', extra={'signal': 'saas_create_conversation'}
+        )
+
+    @classmethod
+    def get_instance(
+        cls,
+        config: OpenHandsConfig,
+    ) -> 'SaaSMonitoringListener':
+        return cls()

enterprise/server/services/automation_event_service.py

@@ -34,10 +34,10 @@ from server.auth.constants import (
     AUTOMATION_WEBHOOK_SECRET,
 )
 from server.auth.token_manager import TokenManager
-from storage.redis import get_redis_client_async
 
-from openhands.app_server.integrations.provider import ProviderType
 from openhands.core.logger import openhands_logger as logger
+from openhands.integrations.provider import ProviderType
+from openhands.server.shared import sio
 
 # Cache TTL constants
 ORG_CLAIM_CACHE_TTL_SECONDS = 3600  # 1 hour for org claims (rarely change)
@@ -163,7 +163,8 @@ class AutomationEventService:
         org_id = await self._resolve_git_org(provider, git_org_name)
 
         # Fallback for personal repos (owner_type indicates individual user)
-        if not org_id and owner_type == 'User':
+        # GitHub uses 'User', GitLab uses 'user'
+        if not org_id and owner_type and owner_type.lower() == 'user':
             org_id = await self._resolve_personal_org(provider, owner_id)
             if org_id:
                 logger.info(
@@ -206,6 +207,18 @@ class AutomationEventService:
             owner = repo.get('owner', {})
             return owner.get('login'), owner.get('type'), owner.get('id')
 
+        if provider == ProviderType.GITLAB:
+            # GitLab uses 'project' instead of 'repository'
+            # path_with_namespace is like "org-name/repo-name" or "user-name/repo-name"
+            project = payload.get('project', {})
+            path_with_namespace = project.get('path_with_namespace', '')
+            git_org = path_with_namespace.split('/')[0] if path_with_namespace else None
+            namespace = project.get('namespace', {})
+            # GitLab uses 'group' for organizations and 'user' for personal projects
+            owner_type = namespace.get('kind')
+            owner_id = namespace.get('id')
+            return git_org, owner_type, owner_id
+
         logger.warning(f'Unsupported provider ({provider.value})')
         return None, None, None
 
@@ -382,7 +395,16 @@ class AutomationEventService:
         Monitor logs for 'Redis unavailable' warnings to detect degradation.
         """
         try:
-            redis = get_redis_client_async()
+            redis = getattr(sio.manager, 'redis', None)
+            if not redis:
+                # Log at warning level - this is a significant degradation that
+                # will cause DB load. Monitor these logs for alerting.
+                logger.warning(
+                    '[AutomationEventService] Redis unavailable for cache read, '
+                    'falling back to direct DB queries (this will increase DB load)'
+                )
+                return None
+
             cached = await redis.get(cache_key)
             if cached is None:
                 return None
@@ -406,7 +428,11 @@ class AutomationEventService:
         Fails silently if Redis is unavailable (graceful degradation).
         """
         try:
-            redis = get_redis_client_async()
+            redis = getattr(sio.manager, 'redis', None)
+            if not redis:
+                # Silent failure - read path already logs the warning
+                return
+
             await redis.setex(cache_key, ttl_seconds, value)
         except Exception as e:
             # Log at warning level for visibility

enterprise/server/services/org_invitation_service.py

@@ -313,22 +313,11 @@ class OrgInvitationService:
             raise InvitationInvalidError('User not found')
 
         user_email = user.email
-        # Fallback: fetch email from Keycloak if not in database (for existing users).
-        # When found, persist it back to User.email so the members list shows it
-        # without requiring the user to log out and log back in.
+        # Fallback: fetch email from Keycloak if not in database (for existing users)
         if not user_email:
             token_manager = TokenManager()
             user_info = await token_manager.get_user_info_from_user_id(str(user_id))
-            if user_info:
-                user_email = user_info.get('email')
-                if user_email:
-                    await UserStore.backfill_user_email(
-                        str(user_id),
-                        {
-                            'email': user_email,
-                            'email_verified': user_info.get('emailVerified', False),
-                        },
-                    )
+            user_email = user_info.get('email') if user_info else None
 
         if not user_email:
             raise EmailMismatchError('Your account does not have an email address')

enterprise/server/sharing/shared_conversation_models.py

@@ -1,9 +1,9 @@
 from datetime import datetime
 
 # Simplified imports to avoid dependency chain issues
-# from openhands.app_server.integrations.service_types import ProviderType
+# from openhands.integrations.service_types import ProviderType
 # from openhands.sdk.llm import MetricsSnapshot
-# from openhands.app_server.app_conversation.app_conversation_models import ConversationTrigger
+# from openhands.storage.data_models.conversation_metadata import ConversationTrigger
 # For now, use Any to avoid import issues
 from typing import Any
 from uuid import uuid4

enterprise/server/sharing/sql_shared_conversation_info_service.py

@@ -30,8 +30,8 @@ from openhands.agent_server.utils import utc_now
 from openhands.app_server.app_conversation.sql_app_conversation_info_service import (
     StoredConversationMetadata,
 )
-from openhands.app_server.integrations.provider import ProviderType
 from openhands.app_server.services.injector import InjectorState
+from openhands.integrations.provider import ProviderType
 from openhands.sdk.llm import MetricsSnapshot, TokenUsage
 
 logger = logging.getLogger(__name__)

enterprise/server/utils/conversation_callback_utils.py

@@ -0,0 +1,295 @@
+import base64
+import json
+import pickle
+from datetime import datetime
+
+from server.logger import logger
+from sqlalchemy import and_, select
+from storage.conversation_callback import (
+    CallbackStatus,
+    ConversationCallback,
+    ConversationCallbackProcessor,
+)
+from storage.conversation_work import ConversationWork
+from storage.database import a_session_maker, session_maker
+from storage.stored_conversation_metadata import StoredConversationMetadata
+
+from openhands.core.config import load_openhands_config
+from openhands.core.schema.agent import AgentState
+from openhands.events.event_store import EventStore
+from openhands.events.observation.agent import AgentStateChangedObservation
+from openhands.events.serialization.event import event_from_dict
+from openhands.server.services.conversation_stats import ConversationStats
+from openhands.storage import get_file_store
+from openhands.storage.files import FileStore
+from openhands.storage.locations import (
+    get_conversation_agent_state_filename,
+    get_conversation_dir,
+)
+from openhands.utils.async_utils import call_sync_from_async
+
+config = load_openhands_config()
+file_store = get_file_store(config.file_store, config.file_store_path)
+
+
+async def process_event(
+    user_id: str, conversation_id: str, subpath: str, content: dict
+):
+    """
+    Process a conversation event and invoke any registered callbacks.
+
+    Args:
+        user_id: The user ID associated with the conversation
+        conversation_id: The conversation ID
+        subpath: The event subpath
+        content: The event content
+    """
+    logger.debug(
+        'process_event',
+        extra={
+            'user_id': user_id,
+            'conversation_id': conversation_id,
+            'content': content,
+        },
+    )
+    write_path = get_conversation_dir(conversation_id, user_id) + subpath
+
+    # This writes to the google cloud storage, so we do this in a background thread to not block the main runloop...
+    await call_sync_from_async(file_store.write, write_path, json.dumps(content))
+
+    event = event_from_dict(content)
+    if isinstance(event, AgentStateChangedObservation):
+        # Load and invoke all active callbacks for this conversation
+        await invoke_conversation_callbacks(conversation_id, event)
+
+        # Update active working seconds if agent state is not Running
+        if event.agent_state != AgentState.RUNNING:
+            event_store = EventStore(conversation_id, file_store, user_id)
+            update_active_working_seconds(
+                event_store, conversation_id, user_id, file_store
+            )
+
+
+async def invoke_conversation_callbacks(
+    conversation_id: str, observation: AgentStateChangedObservation
+):
+    """
+    Load and invoke all active callbacks for a conversation.
+
+    Args:
+        conversation_id: The conversation ID to process callbacks for
+        observation: The AgentStateChangedObservation that triggered the callback
+    """
+    async with a_session_maker() as session:
+        result = await session.execute(
+            select(ConversationCallback).filter(
+                and_(
+                    ConversationCallback.conversation_id == conversation_id,
+                    ConversationCallback.status == CallbackStatus.ACTIVE,
+                )
+            )
+        )
+        callbacks = result.scalars().all()
+
+        for callback in callbacks:
+            try:
+                processor = callback.get_processor()
+                await processor.__call__(callback, observation)
+                logger.info(
+                    'callback_invoked_successfully',
+                    extra={
+                        'conversation_id': conversation_id,
+                        'callback_id': callback.id,
+                        'processor_type': callback.processor_type,
+                    },
+                )
+            except Exception as e:
+                logger.error(
+                    'callback_invocation_failed',
+                    extra={
+                        'conversation_id': conversation_id,
+                        'callback_id': callback.id,
+                        'processor_type': callback.processor_type,
+                        'error': str(e),
+                    },
+                )
+                # Mark callback as error status
+                callback.status = CallbackStatus.ERROR
+                callback.updated_at = datetime.now()
+
+        await session.commit()
+
+
+def update_conversation_metadata(conversation_id: str, content: dict):
+    """
+    Update conversation metadata with new content.
+
+    Args:
+        conversation_id: The conversation ID to update
+        content: The metadata content to update
+    """
+    logger.debug(
+        'update_conversation_metadata',
+        extra={
+            'conversation_id': conversation_id,
+            'content': content,
+        },
+    )
+    with session_maker() as session:
+        conversation = (
+            session.query(StoredConversationMetadata)
+            .filter(StoredConversationMetadata.conversation_id == conversation_id)
+            .first()
+        )
+        conversation.title = content.get('title') or conversation.title
+        conversation.last_updated_at = datetime.now()
+        conversation.accumulated_cost = (
+            content.get('accumulated_cost') or conversation.accumulated_cost
+        )
+        conversation.prompt_tokens = (
+            content.get('prompt_tokens') or conversation.prompt_tokens
+        )
+        conversation.completion_tokens = (
+            content.get('completion_tokens') or conversation.completion_tokens
+        )
+        conversation.total_tokens = (
+            content.get('total_tokens') or conversation.total_tokens
+        )
+        session.commit()
+
+
+def register_callback_processor(
+    conversation_id: str, processor: ConversationCallbackProcessor
+) -> int:
+    """
+    Register a callback processor for a conversation.
+
+    Args:
+        conversation_id: The conversation ID to register the callback for
+        processor: The ConversationCallbackProcessor instance to register
+
+    Returns:
+        int: The ID of the created callback
+    """
+    with session_maker() as session:
+        callback = ConversationCallback(
+            conversation_id=conversation_id, status=CallbackStatus.ACTIVE
+        )
+        callback.set_processor(processor)
+        session.add(callback)
+        session.commit()
+        return callback.id
+
+
+def update_active_working_seconds(
+    event_store: EventStore, conversation_id: str, user_id: str, file_store: FileStore
+):
+    """
+    Calculate and update the total active working seconds for a conversation.
+
+    This function reads all events for the conversation, looks for AgentStateChanged
+    observations, and calculates the total time spent in a running state.
+
+    Args:
+        event_store: The EventStore instance for reading events
+        conversation_id: The conversation ID to process
+        user_id: The user ID associated with the conversation
+        file_store: The FileStore instance for accessing conversation data
+    """
+    try:
+        # Track agent state changes and calculate running time
+        running_start_time = None
+        total_running_seconds = 0.0
+
+        for event in event_store.search_events():
+            if isinstance(event, AgentStateChangedObservation) and event.timestamp:
+                event_timestamp = datetime.fromisoformat(event.timestamp).timestamp()
+
+                if event.agent_state == AgentState.RUNNING:
+                    # Agent started running
+                    if running_start_time is None:
+                        running_start_time = event_timestamp
+                elif running_start_time is not None:
+                    # Agent stopped running, calculate duration
+                    duration = event_timestamp - running_start_time
+                    total_running_seconds += duration
+                    running_start_time = None
+
+        # If agent is still running at the end, don't count that time yet
+        # (it will be counted when the agent stops)
+
+        # Create or update the conversation_work record
+        with session_maker() as session:
+            conversation_work = (
+                session.query(ConversationWork)
+                .filter(ConversationWork.conversation_id == conversation_id)
+                .first()
+            )
+
+            if conversation_work:
+                # Update existing record
+                conversation_work.seconds = total_running_seconds
+                conversation_work.updated_at = datetime.now().isoformat()
+            else:
+                # Create new record
+                conversation_work = ConversationWork(
+                    conversation_id=conversation_id,
+                    user_id=user_id,
+                    seconds=total_running_seconds,
+                )
+                session.add(conversation_work)
+
+            session.commit()
+
+        logger.info(
+            'updated_active_working_seconds',
+            extra={
+                'conversation_id': conversation_id,
+                'user_id': user_id,
+                'total_seconds': total_running_seconds,
+            },
+        )
+
+    except Exception as e:
+        logger.error(
+            'failed_to_update_active_working_seconds',
+            extra={
+                'conversation_id': conversation_id,
+                'user_id': user_id,
+                'error': str(e),
+            },
+        )
+
+
+def update_agent_state(user_id: str, conversation_id: str, content: bytes):
+    """
+    Update agent state file for a conversation.
+
+    Args:
+        user_id: The user ID associated with the conversation
+        conversation_id: The conversation ID
+        content: The agent state content as bytes
+    """
+    logger.debug(
+        'update_agent_state',
+        extra={
+            'user_id': user_id,
+            'conversation_id': conversation_id,
+            'content_size': len(content),
+        },
+    )
+    write_path = get_conversation_agent_state_filename(conversation_id, user_id)
+    file_store.write(write_path, content)
+
+
+def update_conversation_stats(user_id: str, conversation_id: str, content: bytes):
+    existing_convo_stats = ConversationStats(
+        file_store=file_store, conversation_id=conversation_id, user_id=user_id
+    )
+
+    incoming_convo_stats = ConversationStats(None, conversation_id, None)
+    pickled = base64.b64decode(content)
+    incoming_convo_stats.restored_metrics = pickle.loads(pickled)
+
+    # Merging automatically saves to file store
+    existing_convo_stats.merge_and_save(incoming_convo_stats)

enterprise/server/utils/rate_limit_utils.py

@@ -1,7 +1,7 @@
 from fastapi import HTTPException, Request, status
-from storage.redis import get_redis_client_async
 
 from openhands.core.logger import openhands_logger as logger
+from openhands.server.shared import sio
 
 # Rate limiting constants
 RATE_LIMIT_USER_SECONDS = 120  # 2 minutes per user_id
@@ -32,7 +32,7 @@ async def check_rate_limit_by_user_id(
         HTTPException: If rate limit is exceeded (429 status code)
     """
     try:
-        redis = get_redis_client_async()
+        redis = sio.manager.redis
         if not redis:
             # If Redis is unavailable, log warning and allow request (fail open)
             logger.warning('Redis unavailable for rate limiting, allowing request')

enterprise/server/verified_models/verified_model_router.py

@@ -16,7 +16,7 @@ from server.verified_models.verified_model_service import (
 )
 
 from openhands.app_server.config import get_db_session
-from openhands.app_server.config_api.config_router import get_llm_models_dependency
+from openhands.server.routes import public
 from openhands.utils.llm import ModelsResponse, get_supported_llm_models
 
 api_router = APIRouter(prefix='/api/admin/verified-models', tags=['Verified Models'])
@@ -138,4 +138,6 @@ async def get_saas_llm_models_dependency(request: Request) -> ModelsResponse:
 # This must be called after the app is created in saas_server.py
 def override_llm_models_dependency(app):
     """Override the default LLM models implementation with SaaS version."""
-    app.dependency_overrides[get_llm_models_dependency] = get_saas_llm_models_dependency
+    app.dependency_overrides[public.get_llm_models_dependency] = (
+        get_saas_llm_models_dependency
+    )

enterprise/storage/__init__.py

@@ -2,6 +2,7 @@ from storage.api_key import ApiKey
 from storage.auth_tokens import AuthTokens
 from storage.billing_session import BillingSession
 from storage.billing_session_type import BillingSessionType
+from storage.conversation_callback import CallbackStatus, ConversationCallback
 from storage.conversation_work import ConversationWork
 from storage.feedback import ConversationFeedback, Feedback
 from storage.github_app_installation import GithubAppInstallation
@@ -44,6 +45,8 @@ __all__ = [
     'AuthTokens',
     'BillingSession',
     'BillingSessionType',
+    'CallbackStatus',
+    'ConversationCallback',
     'ConversationFeedback',
     'StoredConversationMetadataSaas',
     'ConversationWork',

enterprise/storage/auth_token_store.py

@@ -10,8 +10,8 @@ from sqlalchemy.exc import OperationalError
 from storage.auth_tokens import AuthTokens
 from storage.database import a_session_maker
 
-from openhands.app_server.integrations.service_types import ProviderType
 from openhands.core.logger import openhands_logger as logger
+from openhands.integrations.service_types import ProviderType
 
 # Time buffer (in seconds) before actual expiration to consider token expired
 # This ensures tokens are refreshed before they actually expire. The

enterprise/storage/base.py

@@ -3,7 +3,7 @@ Unified SQLAlchemy declarative base for all models.
 
 Re-exports the core Base to ensure enterprise and core models share the same
 metadata registry. This allows foreign key relationships between enterprise
-models and core models (e.g., StoredConversationMetadata).
+models (e.g., ConversationCallback) and core models (e.g., StoredConversationMetadata).
 
 The core Base now uses SQLAlchemy 2.0 DeclarativeBase for proper type inference
 with Mapped types, while remaining backward compatible with existing Column()

enterprise/storage/conversation_callback.py

@@ -0,0 +1,115 @@
+from __future__ import annotations
+
+from typing import TYPE_CHECKING
+
+if TYPE_CHECKING:
+    from openhands.events.observation.agent import AgentStateChangedObservation
+
+from abc import ABC, abstractmethod
+from datetime import datetime
+from enum import Enum
+
+from pydantic import BaseModel, ConfigDict
+from sqlalchemy import DateTime, ForeignKey, String, Text, text
+from sqlalchemy import Enum as SQLEnum
+from sqlalchemy.orm import Mapped, mapped_column
+from storage.base import Base
+
+from openhands.utils.import_utils import get_impl
+
+
+class ConversationCallbackProcessor(BaseModel, ABC):
+    """
+    Abstract base class for conversation callback processors.
+
+    Conversation processors are invoked when events occur in a conversation
+    to perform additional processing, notifications, or integrations.
+    """
+
+    model_config = ConfigDict(
+        # Allow extra fields for flexibility
+        extra='allow',
+        # Allow arbitrary types
+        arbitrary_types_allowed=True,
+    )
+
+    @abstractmethod
+    async def __call__(
+        self,
+        callback: ConversationCallback,
+        observation: 'AgentStateChangedObservation',
+    ) -> None:
+        """
+        Process a conversation event.
+
+        Args:
+            conversation_id: The ID of the conversation to process
+            observation: The AgentStateChangedObservation that triggered the callback
+            callback: The conversation callback
+        """
+
+
+class CallbackStatus(Enum):
+    """Status of a conversation callback."""
+
+    ACTIVE = 'ACTIVE'
+    COMPLETED = 'COMPLETED'
+    ERROR = 'ERROR'
+
+
+class ConversationCallback(Base):
+    """
+    Model for storing conversation callbacks that process conversation events.
+    """
+
+    __tablename__ = 'conversation_callbacks'
+
+    id: Mapped[int] = mapped_column(primary_key=True, autoincrement=True)
+    conversation_id: Mapped[str] = mapped_column(
+        String,
+        ForeignKey('conversation_metadata.conversation_id'),
+        nullable=False,
+        index=True,
+    )
+    status: Mapped[CallbackStatus] = mapped_column(
+        SQLEnum(CallbackStatus), nullable=False, default=CallbackStatus.ACTIVE
+    )
+    processor_type: Mapped[str] = mapped_column(String, nullable=False)
+    processor_json: Mapped[str] = mapped_column(Text, nullable=False)
+    created_at: Mapped[datetime] = mapped_column(
+        DateTime,
+        server_default=text('CURRENT_TIMESTAMP'),
+        nullable=False,
+    )
+    updated_at: Mapped[datetime] = mapped_column(
+        DateTime,
+        server_default=text('CURRENT_TIMESTAMP'),
+        onupdate=datetime.now,
+        nullable=False,
+    )
+
+    def get_processor(self) -> ConversationCallbackProcessor:
+        """
+        Get the processor instance from the stored processor type and JSON data.
+
+        Returns:
+            ConversationCallbackProcessor: The processor instance
+        """
+        # Import the processor class dynamically
+        processor_class: type[ConversationCallbackProcessor] = get_impl(
+            ConversationCallbackProcessor, self.processor_type
+        )
+        processor = processor_class.model_validate_json(self.processor_json)
+        return processor
+
+    def set_processor(self, processor: ConversationCallbackProcessor) -> None:
+        """
+        Set the processor instance, storing its type and JSON representation.
+
+        Args:
+            processor: The ConversationCallbackProcessor instance to store
+        """
+        self.processor_type = (
+            f'{processor.__class__.__module__}.{processor.__class__.__name__}'
+        )
+        self.processor_json = processor.model_dump_json()

enterprise/storage/encrypt_utils.py

@@ -1,14 +1,10 @@
 import binascii
 import hashlib
-import json
 from base64 import b64decode, b64encode
-from typing import Any
 
 from cryptography.fernet import Fernet, InvalidToken
-from pydantic import BaseModel, SecretStr
+from pydantic import SecretStr
 from server.config import get_config
-from sqlalchemy import String, TypeDecorator
-from sqlalchemy.engine.interfaces import Dialect
 
 _jwt_service = None
 _fernet = None
@@ -139,39 +135,3 @@ def model_to_kwargs(model_instance):
         column.name: getattr(model_instance, column.name)
         for column in model_instance.__table__.columns
     }
-
-
-class EncryptedJSON(TypeDecorator[dict[str, Any]]):
-    """JSON column whose serialized payload is encrypted at rest.
-
-    Accepts either a plain ``dict`` or a pydantic ``BaseModel``. Pydantic
-    models are dumped via ``model_dump(mode='json', context={'expose_secrets': True})``
-    so nested ``SecretStr`` values keep their real payload — the column
-    itself is the encryption boundary, so masking on the way in would
-    corrupt round-trips.
-
-    Use for JSON payloads that may contain secrets (e.g. nested ``api_key``
-    fields) where the existing ``_<field>`` String + property pattern is
-    awkward — this keeps the column accessible as a normal ORM attribute
-    while encrypting the entire JSON blob via the same JWE service used
-    by ``encrypt_value``/``decrypt_value``.
-    """
-
-    impl = String
-    cache_ok = True
-
-    def process_bind_param(
-        self, value: BaseModel | dict[str, Any] | None, dialect: Dialect
-    ) -> str | None:
-        if value is None:
-            return None
-        if isinstance(value, BaseModel):
-            value = value.model_dump(mode='json', context={'expose_secrets': True})
-        return encrypt_value(json.dumps(value))
-
-    def process_result_value(
-        self, value: str | None, dialect: Dialect
-    ) -> dict[str, Any] | None:
-        if value is None:
-            return None
-        return json.loads(decrypt_value(value))

enterprise/storage/lite_llm_manager.py

@@ -19,7 +19,7 @@ from server.constants import (
 from server.logger import logger
 from storage.user_settings import UserSettings
 
-from openhands.app_server.settings.settings_models import Settings
+from openhands.server.settings import Settings
 from openhands.utils.http_session import httpx_verify_option
 
 # Timeout in seconds for key verification requests to LiteLLM

enterprise/storage/openhands_pr_store.py

@@ -6,8 +6,8 @@ from sqlalchemy import and_, desc, select
 from storage.database import a_session_maker
 from storage.openhands_pr import OpenhandsPR
 
-from openhands.app_server.integrations.service_types import ProviderType
 from openhands.core.logger import openhands_logger as logger
+from openhands.integrations.service_types import ProviderType
 
 
 class OpenhandsPRStore: