refactor: split backend into harness (deerflow.*) and app (app.*) (#1131)

* refactor: extract shared utils to break harness→app cross-layer imports

Move _validate_skill_frontmatter to src/skills/validation.py and
CONVERTIBLE_EXTENSIONS + convert_file_to_markdown to src/utils/file_conversion.py.
This eliminates the two reverse dependencies from client.py (harness layer)
into gateway/routers/ (app layer), preparing for the harness/app package split.

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>

* refactor: split backend/src into harness (deerflow.*) and app (app.*)

Physically split the monolithic backend/src/ package into two layers:

- **Harness** (`packages/harness/deerflow/`): publishable agent framework
  package with import prefix `deerflow.*`. Contains agents, sandbox, tools,
  models, MCP, skills, config, and all core infrastructure.

- **App** (`app/`): unpublished application code with import prefix `app.*`.
  Contains gateway (FastAPI REST API) and channels (IM integrations).

Key changes:
- Move 13 harness modules to packages/harness/deerflow/ via git mv
- Move gateway + channels to app/ via git mv
- Rename all imports: src.* → deerflow.* (harness) / app.* (app layer)
- Set up uv workspace with deerflow-harness as workspace member
- Update langgraph.json, config.example.yaml, all scripts, Docker files
- Add build-system (hatchling) to harness pyproject.toml
- Add PYTHONPATH=. to gateway startup commands for app.* resolution
- Update ruff.toml with known-first-party for import sorting
- Update all documentation to reflect new directory structure

Boundary rule enforced: harness code never imports from app.
All 429 tests pass. Lint clean.

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>

* chore: add harness→app boundary check test and update docs

Add test_harness_boundary.py that scans all Python files in
packages/harness/deerflow/ and fails if any `from app.*` or
`import app.*` statement is found. This enforces the architectural
rule that the harness layer never depends on the app layer.

Update CLAUDE.md to document the harness/app split architecture,
import conventions, and the boundary enforcement test.

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>

* feat: add config versioning with auto-upgrade on startup

When config.example.yaml schema changes, developers' local config.yaml
files can silently become outdated. This adds a config_version field and
auto-upgrade mechanism so breaking changes (like src.* → deerflow.*
renames) are applied automatically before services start.

- Add config_version: 1 to config.example.yaml
- Add startup version check warning in AppConfig.from_file()
- Add scripts/config-upgrade.sh with migration registry for value replacements
- Add `make config-upgrade` target
- Auto-run config-upgrade in serve.sh and start-daemon.sh before starting services
- Add config error hints in service failure messages

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>

* fix comments

* fix: update src.* import in test_sandbox_tools_security to deerflow.*

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>

* fix: handle empty config and search parent dirs for config.example.yaml

Address Copilot review comments on PR #1131:
- Guard against yaml.safe_load() returning None for empty config files
- Search parent directories for config.example.yaml instead of only
  looking next to config.yaml, fixing detection in common setups

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>

* fix: correct skills root path depth and config_version type coercion

- loader.py: fix get_skills_root_path() to use 5 parent levels (was 3)
  after harness split, file lives at packages/harness/deerflow/skills/
  so parent×3 resolved to backend/packages/harness/ instead of backend/
- app_config.py: coerce config_version to int() before comparison in
  _check_config_version() to prevent TypeError when YAML stores value
  as string (e.g. config_version: "1")
- tests: add regression tests for both fixes

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>

* fix: update test imports from src.* to deerflow.*/app.* after harness refactor

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>

---------

Co-authored-by: Claude Opus 4.6 <noreply@anthropic.com>

backend/packages/harness/deerflow/sandbox/local/local_sandbox_provider.py

@@ -0,0 +1,60 @@
+from deerflow.sandbox.local.local_sandbox import LocalSandbox
+from deerflow.sandbox.sandbox import Sandbox
+from deerflow.sandbox.sandbox_provider import SandboxProvider
+
+_singleton: LocalSandbox | None = None
+
+
+class LocalSandboxProvider(SandboxProvider):
+    def __init__(self):
+        """Initialize the local sandbox provider with path mappings."""
+        self._path_mappings = self._setup_path_mappings()
+
+    def _setup_path_mappings(self) -> dict[str, str]:
+        """
+        Setup path mappings for local sandbox.
+
+        Maps container paths to actual local paths, including skills directory.
+
+        Returns:
+            Dictionary of path mappings
+        """
+        mappings = {}
+
+        # Map skills container path to local skills directory
+        try:
+            from deerflow.config import get_app_config
+
+            config = get_app_config()
+            skills_path = config.skills.get_skills_path()
+            container_path = config.skills.container_path
+
+            # Only add mapping if skills directory exists
+            if skills_path.exists():
+                mappings[container_path] = str(skills_path)
+        except Exception as e:
+            # Log but don't fail if config loading fails
+            print(f"Warning: Could not setup skills path mapping: {e}")
+
+        return mappings
+
+    def acquire(self, thread_id: str | None = None) -> str:
+        global _singleton
+        if _singleton is None:
+            _singleton = LocalSandbox("local", path_mappings=self._path_mappings)
+        return _singleton.id
+
+    def get(self, sandbox_id: str) -> Sandbox | None:
+        if sandbox_id == "local":
+            if _singleton is None:
+                self.acquire()
+            return _singleton
+        return None
+
+    def release(self, sandbox_id: str) -> None:
+        # LocalSandbox uses singleton pattern - no cleanup needed.
+        # Note: This method is intentionally not called by SandboxMiddleware
+        # to allow sandbox reuse across multiple turns in a thread.
+        # For Docker-based providers (e.g., AioSandboxProvider), cleanup
+        # happens at application shutdown via the shutdown() method.
+        pass