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- **App** (`app/`): unpublished application code with import prefix `app.*`.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files can silently become outdated.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/docs/plan_mode_usage.md

@@ -19,7 +19,7 @@ Plan mode is controlled via **runtime configuration** through the `is_plan_mode`
 
 ```python
 from langchain_core.runnables import RunnableConfig
-from src.agents.lead_agent.agent import make_lead_agent
+from deerflow.agents.lead_agent.agent import make_lead_agent
 
 # Enable plan mode via runtime configuration
 config = RunnableConfig(
@@ -72,7 +72,7 @@ The agent will skip using the todo list for:
 
 ```python
 from langchain_core.runnables import RunnableConfig
-from src.agents.lead_agent.agent import make_lead_agent
+from deerflow.agents.lead_agent.agent import make_lead_agent
 
 # Create agent with plan mode ENABLED
 config_with_plan_mode = RunnableConfig(
@@ -101,7 +101,7 @@ You can enable/disable plan mode dynamically for different conversations or task
 
 ```python
 from langchain_core.runnables import RunnableConfig
-from src.agents.lead_agent.agent import make_lead_agent
+from deerflow.agents.lead_agent.agent import make_lead_agent
 
 def create_agent_for_task(task_complexity: str):
     """Create agent with plan mode based on task complexity."""
@@ -154,7 +154,7 @@ make_lead_agent(config)
 ## Implementation Details
 
 ### Agent Module
-- **Location**: `src/agents/lead_agent/agent.py`
+- **Location**: `packages/harness/deerflow/agents/lead_agent/agent.py`
 - **Function**: `_create_todo_list_middleware(is_plan_mode: bool)` - Creates TodoListMiddleware if plan mode is enabled
 - **Function**: `_build_middlewares(config: RunnableConfig)` - Builds middleware chain based on runtime config
 - **Function**: `make_lead_agent(config: RunnableConfig)` - Creates agent with appropriate middlewares
@@ -194,7 +194,7 @@ DeerFlow uses custom `system_prompt` and `tool_description` for the TodoListMidd
 - Comprehensive best practices section
 - Task completion requirements to prevent premature marking
 
-The custom prompts are defined in `_create_todo_list_middleware()` in `/Users/hetao/workspace/deer-flow/backend/src/agents/lead_agent/agent.py:57`.
+The custom prompts are defined in `_create_todo_list_middleware()` in `/Users/hetao/workspace/deer-flow/backend/packages/harness/deerflow/agents/lead_agent/agent.py:57`.
 
 ## Notes