# `src/app_controller.py` — Headless Orchestrator & State Hub

[Top](../Readme.md) | [Architecture](guide_architecture.md) | [Discussions](guide_discussions.md) | [State Lifecycle](guide_state_lifecycle.md) | [Context Aggregation](guide_context_aggregation.md) | [MMA](guide_mma.md) | [Testing](guide_testing.md)

---

## Overview

`src/app_controller.py` (~166KB) is the **headless controller** that owns the application's state and business logic. It decouples the GUI (`gui_2.py`) from the underlying subsystems (AI, presets, personas, RAG, history, MMA, paths, hot reload).

When `--enable-test-hooks` is passed, the controller also spins up the HookServer so external tests/scripts can drive the running app.

---

## Architecture

```
┌─────────────────────────────────────────────────┐
│  gui_2.py (App)                                   │
│  - Pure immediate-mode UI                        │
│  - Reads app_state for rendering                  │
│  - Calls controller methods for mutations         │
└─────────────────┬───────────────────────────────┘
                  │ delegates to
                  ▼
┌─────────────────────────────────────────────────┐
│  app_controller.py: AppController                 │
│  - State container (AppState)                     │
│  - Subsystem coordination (presets, personas, ...) │
│  - Headless mode: skips GUI init, starts hook     │
│    server on port 8999                            │
│  - Provides _predefined_callbacks and             │
│    _gettable_fields for the Hook API              │
└─────────────────┬───────────────────────────────┘
                  │ owns/uses
                  ▼
┌─────────────────────────────────────────────────┐
│  Subsystems                                       │
│  - PresetManager (src/presets.py)                  │
│  - PersonaManager (src/personas.py)                │
│  - ContextPresetManager (src/context_presets.py)   │
│  - ToolPresetManager (src/tool_presets.py)         │
│  - ToolBiasEngine (src/tool_bias.py)               │
│  - RAGEngine (src/rag_engine.py)                   │
│  - HistoryManager (src/history.py)                 │
│  - WorkspaceManager (src/workspace_manager.py)     │
│  - HookServer (src/api_hooks.py)                   │
│  - HotReloader (src/hot_reload.py)                 │
│  - PathManager (src/paths.py)                      │
└─────────────────────────────────────────────────┘
```

---

## The `AppController` Class

### `__init__(self, enable_test_hooks: bool = False)`

Initializes the controller. Key state:

```python
class AppController:
    def __init__(self, enable_test_hooks: bool = False):
        # 1. Path resolution (src/paths.py)
        self.paths = PathManager()

        # 2. State container
        self.app_state = AppState()

        # 3. Subsystem managers
        self.presets = PresetManager(self.paths)
        self.personas = PersonaManager(self.paths)
        self.context_presets = ContextPresetManager(self.paths)
        self.tool_presets = ToolPresetManager(self.paths)
        self.tool_bias = ToolBiasEngine()
        self.history = HistoryManager(self.paths)
        self.workspace = WorkspaceManager(self.paths)
        self.rag_engine = RAGEngine(self.paths)  # Lazy

        # 4. Hook API surface
        self._predefined_callbacks: dict[str, Callable] = {}
        self._gettable_fields: dict[str, str] = {}

        # 5. AI client (lazy)
        self.ai_client = None

        # 6. MMA conductor (lazy)
        self.mma_conductor = None

        # 7. Sync event queue (daemon <-> UI bridge)
        self.event_queue = SyncEventQueue()

        # 8. Optional hook server
        if enable_test_hooks:
            self.hook_server = HookServer()
            self.hook_server.start()
```

The `App` (in `gui_2.py`) then reads `controller.app_state`, `controller.presets`, etc. for rendering.

### `register_hooks(app: App)`

Called by `gui_2.py` after instantiation. The controller populates the predefined callbacks and gettable fields that the Hook API can invoke.

```python
def register_hooks(self, app: 'App') -> None:
    """Register App methods as predefined callbacks for the Hook API."""
    self._predefined_callbacks['_toggle_command_palette'] = app._toggle_command_palette
    self._predefined_callbacks['_open_command_palette'] = app._open_command_palette
    # ... etc, many more ...
    self._gettable_fields['show_command_palette'] = 'show_command_palette'
    self._gettable_fields['current_provider'] = 'current_provider'
    # ... etc ...
```

This is the **only** bridge between the GUI's app methods and the external Hook API. If a method is not in `_predefined_callbacks`, external callers cannot invoke it.

### Subsystem Coordination Methods

The controller has methods that span multiple subsystems:

- `reload_presets()` — re-reads preset TOML files from disk
- `reload_personas()` — same for personas
- `reload_context_presets()` — validates files exist
- `apply_persona(persona_name, target)` — switches model, system prompt, and tool weights for a target
- `dispatch_mma_track(track_id)` — kicks off a multi-agent track
- `reset_session()` — clears discussion history, resets UI state, etc.
- `save_state_to_disk()` / `load_state_from_disk()` — for historical session replay
- `inject_context_files(paths)` — adds files to the active context composition

---

## The `AppState` Dataclass

`app_state` is a flat dataclass holding all GUI-visible state. Examples:

```python
@dataclass
class AppState:
    current_provider: str = "gemini"
    current_model: str = "gemini-3-flash-preview"
    temperature: float = 0.7
    top_p: float = 0.95
    max_output_tokens: int = 8192
    system_prompt: str = ""
    discussion_history: list[DiscussionEntry] = field(default_factory=list)
    context_files: list[ContextFileEntry] = field(default_factory=list)
    context_screenshots: list[str] = field(default_factory=list)
    show_command_palette: bool = False
    show_preset_manager: bool = False
    show_persona_editor: bool = False
    show_context_preview: bool = False
    show_diagnostics: bool = False
    show_mma_dashboard: bool = False
    # ... many more
```

The `App` reads from `app_state` for rendering and writes back via setter methods. All setters are exposed to the Hook API via `_gettable_fields` and other "settable" registries.

---

## Preset & Persona Management

### `PresetManager` (in `src/presets.py`)

The controller delegates preset CRUD to `PresetManager`. The controller itself only coordinates when presets change (re-apply to active session, update system prompt, etc.).

```python
# In controller
def on_preset_changed(self, new_preset_name: str) -> None:
    preset = self.presets.get(new_preset_name)
    self.app_state.system_prompt = preset.full_text  # Base + persona
    self.app_state.temperature = preset.temperature
    self.app_state.top_p = preset.top_p
    self.app_state.max_output_tokens = preset.max_output_tokens
```

### `PersonaManager` (in `src/personas.py`)

Consolidates model settings + system prompt + tool weights into a single named entity.

```python
# In controller
def apply_persona(self, persona_name: str, target: str = "tier3") -> None:
    persona = self.personas.get(persona_name)
    if persona.model:
        self.app_state.current_model = persona.model
    if persona.system_prompt:
        self.app_state.system_prompt = persona.system_prompt
    if persona.tool_weights:
        self.tool_bias.apply_weights(persona.tool_weights, target=target)
    if persona.bias_profile:
        self.tool_bias.apply_profile(persona.bias_profile)
```

`target` is the MMA tier ("tier1", "tier2", "tier3", "tier4"). This is how MMA agents get isolated cognitive load.

### `ContextPresetManager` (in `src/context_presets.py`)

Saves/loads complete context compositions (files, screenshots, view modes). Validates that referenced files still exist on load.

### `ToolPresetManager` (in `src/tool_presets.py`)

Manages tool enable/disable + weights. Persisted to `tool_presets.toml`.

### `ToolBiasEngine` (in `src/tool_bias.py`)

Applies weights and global bias profiles. Generates the **"Tooling Strategy"** section appended to system prompts.

---

## History Management

`HistoryManager` (in `src/history.py`) implements the **non-provider undo/redo** system.

```python
def on_ui_state_change(self) -> None:
    """Called when the UI changes (e.g., text input). Pushes a snapshot."""
    snapshot = self.history.capture(self.app_state)
    self.history.push(snapshot)
    self.app_state.can_undo = self.history.can_undo()
    self.app_state.can_redo = self.history.can_redo()
```

Snapshots include:
- All text inputs (system prompt, AI input, code blocks)
- Model parameters (Temperature, Top-P, Max Output Tokens)
- Context (files, screenshots)
- Discussion history (for discussion mutations)

Capacity is fixed (default: 50 snapshots). Older entries are evicted.

### Branching History ("Takes")

`HistoryManager` also tracks **timeline branching**. When the user reverts and then takes a new action, a new "take" is created. The full history graph is preserved for back-navigation.

---

## RAG Engine Integration

`RAGEngine` (in `src/rag_engine.py`) is owned by the controller but **lazy-loaded** on first use:

```python
def get_rag_engine(self) -> RAGEngine:
    if self._rag_engine is None:
        from src.rag_engine import RAGEngine
        self._rag_engine = RAGEngine(self.paths)
    return self._rag_engine
```

The GUI exposes a RAG settings panel that calls `controller.get_rag_engine().set_provider(...)`, `set_chunk_size(...)`, etc.

### RAG Lifecycle

1. **Indexing**: `controller.index_project()` walks the project workspace, chunks files, embeds them, writes to ChromaDB (or external MCP).
2. **Search**: `controller.search_context_files(query)` returns top-k fragments with source paths.
3. **Injection**: Fragments are prepended to the AI's prompt via `ai_client.send(...)`. The controller orchestrates the flow.

---

## MMA Conductor Integration

`MultiAgentConductor` (in `src/multi_agent_conductor.py`) is also lazy-loaded:

```python
def get_mma_conductor(self) -> 'MultiAgentConductor':
    if self._mma_conductor is None:
        from src.multi_agent_conductor import MultiAgentConductor
        self._mma_conductor = MultiAgentConductor(self)
    return self._mma_conductor
```

The controller passes itself into the conductor so workers can access presets/personas/RAG during execution.

### Dispatch Flow

```
controller.dispatch_mma_track(track_id)
  -> conductor.load_track(track_id)
  -> conductor.start_workers(track)
  -> workers run in parallel via WorkerPool
  -> workers call back into controller (presets, personas, etc.)
  -> results pushed to controller.app_state.discussion_history
  -> conductor emits events to controller.event_queue
```

The `event_queue` is consumed by the GUI on the main thread to update display.

---

## Hot Reload

The controller can hot-reload Python modules while preserving state. This is critical for GUI iteration:

```python
def hot_reload(self, module_name: str) -> None:
    """Reload a module and re-apply its render functions to the app."""
    from src.hot_reload import HotReloader
    reloader = HotReloader(self.app)
    reloader.reload(module_name)
```

`gui_2.py` registers all its render functions with the reloader at startup. On reload, the reloader swaps the function references without losing app state.

See **[docs/guide_hot_reload.md](guide_hot_reload.md)** for the full mechanism.

---

## The `SyncEventQueue`

A `queue.Queue`-based bridge between the daemon threads (AI workers, MMA workers) and the GUI main thread.

```python
class SyncEventQueue:
    def put(self, event: Event) -> None: ...
    def get_nowait(self) -> Event | None: ...
    def get_all(self) -> list[Event]: ...
```

The GUI polls `controller.event_queue.get_all()` once per frame and dispatches events to render functions.

### Event Types

- `MMA_TICKET_COMPLETED`
- `MMA_LOG_MESSAGE`
- `AI_RESPONSE_CHUNK`
- `AI_RESPONSE_COMPLETE`
- `TOOL_CALL_STARTED`
- `TOOL_CALL_COMPLETED`
- `PERSONA_APPLIED`
- `WORKSPACE_LOADED`
- `RAG_INDEX_COMPLETE`
- `HOOK_CALLBACK_RECEIVED`

The controller translates subsystem-specific events into these generic types.

---

## The Headless Mode

When `sloppy.py` is launched with `--headless`, the controller is instantiated without an `App`:

```python
# In sloppy.py --headless
controller = AppController(enable_test_hooks=True)
# ... run server-only logic ...
# No GUI, no ImGui context, but full subsystem access
```

This is the **Headless Backend Service** mode. The controller still listens on `:8999` and serves all Hook API endpoints. Tests and external scripts can drive the headless service.

---

## Hook API Surface (Defined Here)

The controller is the **single source of truth** for what the Hook API can do. Three registries:

### `_predefined_callbacks: dict[str, Callable]`

Maps hook name → App method. Populated by `register_hooks(app)`.

```python
self._predefined_callbacks['_toggle_command_palette'] = app._toggle_command_palette
self._predefined_callbacks['_open_command_palette'] = app._open_command_palette
self._predefined_callbacks['save_context_preset'] = app.save_context_preset
self._predefined_callbacks['load_context_preset'] = app.load_context_preset
# ... ~30 entries
```

### `_gettable_fields: dict[str, str]`

Maps hook name → AppState field name. Used by `get_value` Hook API action.

```python
self._gettable_fields['show_command_palette'] = 'show_command_palette'
self._gettable_fields['current_provider'] = 'current_provider'
self._gettable_fields['current_model'] = 'current_model'
# ... etc
```

### `_action_handlers: dict[str, Callable]`

Maps action name (e.g., `"click"`, `"set_value"`, `"custom_callback"`) → handler.

```python
self._action_handlers['click'] = self._handle_click
self._action_handlers['set_value'] = self._handle_set_value
self._action_handlers['custom_callback'] = self._handle_custom_callback
# ... etc
```

The HookServer in `src/api_hooks.py` consumes these registries to route incoming requests.

---

## Testing

The controller is tested via the `live_gui` fixture (full integration) and targeted unit tests.

### Unit Tests

- `tests/test_app_controller_init.py` — instantiation, subsystem wiring
- `tests/test_preset_manager.py` — preset CRUD
- `tests/test_persona_manager.py` — persona CRUD + application
- `tests/test_context_presets.py` — context preset CRUD + file validation
- `tests/test_history.py` — undo/redo
- `tests/test_workspace_manager.py` — workspace profile CRUD

### Integration Tests (live_gui)

Use the `ApiHookClient` to drive the controller and verify state mutations.

```python
def test_apply_persona(live_gui):
    client = ApiHookClient()
    client.push_event("custom_callback", {"callback": "apply_persona", "args": ["code-reviewer"]})
    time.sleep(0.5)
    model = client.get_value("current_model")
    assert "code" in model.lower() or model == "code-reviewer-model"
```

---

## Common Pitfalls

1. **Don't instantiate `AppController` twice in the same process**: The singleton holds RAG engine, MMA conductor, hook server. A second instance would conflict.
2. **Don't read `app_state` from a daemon thread without locking**: Use `event_queue` for cross-thread communication.
3. **Always go through the controller for subsystem changes**: Don't call `self.presets.save(...)` from the GUI directly; call `controller.save_preset(...)` so the event is broadcast.
4. **When adding a new Hook API callback, register it in BOTH `_predefined_callbacks` AND `register_hooks`**: The latter is what populates the registry from an App instance.

---

## See Also

- **[guide_architecture.md](guide_architecture.md)** — Threading and event flow
- **[guide_mma.md](guide_mma.md)** — How MMA workers use the controller
- **[guide_ai_client.md](guide_ai_client.md)** — How `ai_client` integrates
- **[guide_api_hooks.md](guide_api_hooks.md)** — The Hook API the controller exposes
- **[guide_hot_reload.md](guide_hot_reload.md)** — How the controller supports state-preserving reloads
- **[guide_discussions.md](guide_discussions.md)** — The Discussion system (Takes, branching, `_switch_discussion`, `_branch_discussion`, `_rename_discussion`, `_delete_discussion`, `_flush_disc_entries_to_project`)
- **[guide_state_lifecycle.md](guide_state_lifecycle.md)** — The `_handle_reset_session` and `_handle_compress_discussion` flows, the `App.__getattr__`/`__setattr__` state delegation pattern, and the `HistoryManager` integration
- **[guide_context_aggregation.md](guide_context_aggregation.md)** — The `aggregate.py` pipeline that the controller calls per send (per-provider + Tier 3 worker)
- **`src/presets.py`, `src/personas.py`, `src/context_presets.py`, `src/tool_presets.py`, `src/tool_bias.py`** — Subsystem managers
- **`src/history.py`** — `HistoryManager`
- **`src/rag_engine.py`** — `RAGEngine`
- **`src/multi_agent_conductor.py`** — `MultiAgentConductor`
- **`src/hot_reload.py`** — `HotReloader`
- **`src/api_hooks.py`** — `HookServer` (uses the controller's registries)
- **`src/paths.py`** — `PathManager`
- **[conductor/tracks/nagent_review_20260608/report.md](../conductor/tracks/nagent_review_20260608/report.md)** — Deep-dive analysis of the controller's per-provider history globals and other state patterns