| 1 | """Interactive onboarding questionnaire for nanobot.""" |
| 2 | |
| 3 | import json |
| 4 | import types |
| 5 | from dataclasses import dataclass |
| 6 | from functools import lru_cache |
| 7 | from typing import Any, Literal, NamedTuple, get_args, get_origin |
| 8 | |
| 9 | try: |
| 10 | import questionary |
| 11 | except ModuleNotFoundError: # pragma: no cover - exercised in environments without wizard deps |
| 12 | questionary = None |
| 13 | from loguru import logger |
| 14 | from pydantic import BaseModel |
| 15 | from rich.console import Console |
| 16 | from rich.panel import Panel |
| 17 | from rich.table import Table |
| 18 | |
| 19 | from nanobot.cli.models import ( |
| 20 | format_token_count, |
| 21 | get_model_context_limit, |
| 22 | get_model_suggestions, |
| 23 | ) |
| 24 | from nanobot.config.loader import get_config_path, load_config |
| 25 | from nanobot.config.schema import Config |
| 26 | |
| 27 | console = Console() |
| 28 | |
| 29 | |
| 30 | @dataclass |
| 31 | class OnboardResult: |
| 32 | """Result of an onboarding session.""" |
| 33 | |
| 34 | config: Config |
| 35 | should_save: bool |
| 36 | |
| 37 | # --- Field Hints for Select Fields --- |
| 38 | # Maps field names to (choices, hint_text) |
| 39 | # To add a new select field with hints, add an entry: |
| 40 | # "field_name": (["choice1", "choice2", ...], "hint text for the field") |
| 41 | _SELECT_FIELD_HINTS: dict[str, tuple[list[str], str]] = { |
| 42 | "reasoning_effort": ( |
| 43 | ["low", "medium", "high"], |
| 44 | "low / medium / high - enables LLM thinking mode", |
| 45 | ), |
| 46 | } |
| 47 | |
| 48 | # --- Key Bindings for Navigation --- |
| 49 | |
| 50 | _BACK_PRESSED = object() # Sentinel value for back navigation |
| 51 | |
| 52 | |
| 53 | def _get_questionary(): |
| 54 | """Return questionary or raise a clear error when wizard deps are unavailable.""" |
| 55 | if questionary is None: |
| 56 | raise RuntimeError( |
| 57 | "Interactive onboarding requires the optional 'questionary' dependency. " |
| 58 | "Install project dependencies and rerun with --wizard." |
| 59 | ) |
| 60 | return questionary |
| 61 | |
| 62 | |
| 63 | def _select_with_back( |
| 64 | prompt: str, choices: list[str], default: str | None = None |
| 65 | ) -> str | None | object: |
| 66 | """Select with Escape/Left arrow support for going back. |
| 67 | |
| 68 | Args: |
| 69 | prompt: The prompt text to display. |
| 70 | choices: List of choices to select from. Must not be empty. |
| 71 | default: The default choice to pre-select. If not in choices, first item is used. |
| 72 | |
| 73 | Returns: |
| 74 | _BACK_PRESSED sentinel if user pressed Escape or Left arrow |
| 75 | The selected choice string if user confirmed |
| 76 | None if user cancelled (Ctrl+C) |
| 77 | """ |
| 78 | from prompt_toolkit.application import Application |
| 79 | from prompt_toolkit.key_binding import KeyBindings |
| 80 | from prompt_toolkit.keys import Keys |
| 81 | from prompt_toolkit.layout import Layout |
| 82 | from prompt_toolkit.layout.containers import HSplit, Window |
| 83 | from prompt_toolkit.layout.controls import FormattedTextControl |
| 84 | from prompt_toolkit.styles import Style |
| 85 | |
| 86 | # Validate choices |
| 87 | if not choices: |
| 88 | logger.warning("Empty choices list provided to _select_with_back") |
| 89 | return None |
| 90 | |
| 91 | # Find default index |
| 92 | selected_index = 0 |
| 93 | if default and default in choices: |
| 94 | selected_index = choices.index(default) |
| 95 | |
| 96 | # State holder for the result |
| 97 | state: dict[str, str | None | object] = {"result": None} |
| 98 | |
| 99 | # Build menu items (uses closure over selected_index) |
| 100 | def get_menu_text(): |
| 101 | items = [] |
| 102 | for i, choice in enumerate(choices): |
| 103 | if i == selected_index: |
| 104 | items.append(("class:selected", f"> {choice}\n")) |
| 105 | else: |
| 106 | items.append(("", f" {choice}\n")) |
| 107 | return items |
| 108 | |
| 109 | # Create layout |
| 110 | menu_control = FormattedTextControl(get_menu_text) |
| 111 | menu_window = Window(content=menu_control, height=len(choices)) |
| 112 | |
| 113 | prompt_control = FormattedTextControl(lambda: [("class:question", f"> {prompt}")]) |
| 114 | prompt_window = Window(content=prompt_control, height=1) |
| 115 | |
| 116 | layout = Layout(HSplit([prompt_window, menu_window])) |
| 117 | |
| 118 | # Key bindings |
| 119 | bindings = KeyBindings() |
| 120 | |
| 121 | @bindings.add(Keys.Up) |
| 122 | def _up(event): |
| 123 | nonlocal selected_index |
| 124 | selected_index = (selected_index - 1) % len(choices) |
| 125 | event.app.invalidate() |
| 126 | |
| 127 | @bindings.add(Keys.Down) |
| 128 | def _down(event): |
| 129 | nonlocal selected_index |
| 130 | selected_index = (selected_index + 1) % len(choices) |
| 131 | event.app.invalidate() |
| 132 | |
| 133 | @bindings.add(Keys.Enter) |
| 134 | def _enter(event): |
| 135 | state["result"] = choices[selected_index] |
| 136 | event.app.exit() |
| 137 | |
| 138 | @bindings.add("escape") |
| 139 | def _escape(event): |
| 140 | state["result"] = _BACK_PRESSED |
| 141 | event.app.exit() |
| 142 | |
| 143 | @bindings.add(Keys.Left) |
| 144 | def _left(event): |
| 145 | state["result"] = _BACK_PRESSED |
| 146 | event.app.exit() |
| 147 | |
| 148 | @bindings.add(Keys.ControlC) |
| 149 | def _ctrl_c(event): |
| 150 | state["result"] = None |
| 151 | event.app.exit() |
| 152 | |
| 153 | # Style |
| 154 | style = Style.from_dict({ |
| 155 | "selected": "fg:green bold", |
| 156 | "question": "fg:cyan", |
| 157 | }) |
| 158 | |
| 159 | app = Application(layout=layout, key_bindings=bindings, style=style) |
| 160 | try: |
| 161 | app.run() |
| 162 | except Exception: |
| 163 | logger.exception("Error in select prompt") |
| 164 | return None |
| 165 | |
| 166 | return state["result"] |
| 167 | |
| 168 | # --- Type Introspection --- |
| 169 | |
| 170 | |
| 171 | class FieldTypeInfo(NamedTuple): |
| 172 | """Result of field type introspection.""" |
| 173 | |
| 174 | type_name: str |
| 175 | inner_type: Any |
| 176 | |
| 177 | |
| 178 | def _get_field_type_info(field_info) -> FieldTypeInfo: |
| 179 | """Extract field type info from Pydantic field.""" |
| 180 | annotation = field_info.annotation |
| 181 | if annotation is None: |
| 182 | return FieldTypeInfo("str", None) |
| 183 | |
| 184 | origin = get_origin(annotation) |
| 185 | args = get_args(annotation) |
| 186 | |
| 187 | if origin is types.UnionType: |
| 188 | non_none_args = [a for a in args if a is not type(None)] |
| 189 | if len(non_none_args) == 1: |
| 190 | annotation = non_none_args[0] |
| 191 | origin = get_origin(annotation) |
| 192 | args = get_args(annotation) |
| 193 | |
| 194 | _SIMPLE_TYPES: dict[type, str] = {bool: "bool", int: "int", float: "float"} |
| 195 | |
| 196 | if origin is list or (hasattr(origin, "__name__") and origin.__name__ == "List"): |
| 197 | return FieldTypeInfo("list", args[0] if args else str) |
| 198 | if origin is dict or (hasattr(origin, "__name__") and origin.__name__ == "Dict"): |
| 199 | return FieldTypeInfo("dict", None) |
| 200 | for py_type, name in _SIMPLE_TYPES.items(): |
| 201 | if annotation is py_type: |
| 202 | return FieldTypeInfo(name, None) |
| 203 | if isinstance(annotation, type) and issubclass(annotation, BaseModel): |
| 204 | return FieldTypeInfo("model", annotation) |
| 205 | if origin is Literal: |
| 206 | return FieldTypeInfo("literal", list(args)) |
| 207 | return FieldTypeInfo("str", None) |
| 208 | |
| 209 | |
| 210 | def _get_field_display_name(field_key: str, field_info) -> str: |
| 211 | """Get display name for a field.""" |
| 212 | if field_info and field_info.description: |
| 213 | return field_info.description |
| 214 | name = field_key |
| 215 | suffix_map = { |
| 216 | "_s": " (seconds)", |
| 217 | "_ms": " (ms)", |
| 218 | "_url": " URL", |
| 219 | "_path": " Path", |
| 220 | "_id": " ID", |
| 221 | "_key": " Key", |
| 222 | "_token": " Token", |
| 223 | } |
| 224 | for suffix, replacement in suffix_map.items(): |
| 225 | if name.endswith(suffix): |
| 226 | name = name[: -len(suffix)] + replacement |
| 227 | break |
| 228 | return name.replace("_", " ").title() |
| 229 | |
| 230 | |
| 231 | # --- Sensitive Field Masking --- |
| 232 | |
| 233 | _SENSITIVE_KEYWORDS = frozenset({"api_key", "token", "secret", "password", "credentials"}) |
| 234 | |
| 235 | |
| 236 | def _is_sensitive_field(field_name: str) -> bool: |
| 237 | """Check if a field name indicates sensitive content.""" |
| 238 | return any(kw in field_name.lower() for kw in _SENSITIVE_KEYWORDS) |
| 239 | |
| 240 | |
| 241 | def _mask_value(value: str) -> str: |
| 242 | """Mask a sensitive value, showing only the last 4 characters.""" |
| 243 | if len(value) <= 4: |
| 244 | return "****" |
| 245 | return "*" * (len(value) - 4) + value[-4:] |
| 246 | |
| 247 | |
| 248 | # --- Value Formatting --- |
| 249 | |
| 250 | |
| 251 | def _format_value(value: Any, rich: bool = True, field_name: str = "") -> str: |
| 252 | """Single recursive entry point for safe value display. Handles any depth.""" |
| 253 | if value is None or value == "" or value == {} or value == []: |
| 254 | return "[dim]not set[/dim]" if rich else "[not set]" |
| 255 | if _is_sensitive_field(field_name) and isinstance(value, str): |
| 256 | masked = _mask_value(value) |
| 257 | return f"[dim]{masked}[/dim]" if rich else masked |
| 258 | if isinstance(value, BaseModel): |
| 259 | parts = [] |
| 260 | for fname, _finfo in type(value).model_fields.items(): |
| 261 | fval = getattr(value, fname, None) |
| 262 | formatted = _format_value(fval, rich=False, field_name=fname) |
| 263 | if formatted != "[not set]": |
| 264 | parts.append(f"{fname}={formatted}") |
| 265 | return ", ".join(parts) if parts else ("[dim]not set[/dim]" if rich else "[not set]") |
| 266 | if isinstance(value, list): |
| 267 | return ", ".join(str(v) for v in value) |
| 268 | if isinstance(value, dict): |
| 269 | # Handle dicts containing BaseModel instances |
| 270 | parts = [] |
| 271 | for k, v in value.items(): |
| 272 | formatted = _format_value(v, rich=False, field_name=str(k)) |
| 273 | parts.append(f"{k}: {formatted}") |
| 274 | return ", ".join(parts) if parts else ("[dim]not set[/dim]" if rich else "[not set]") |
| 275 | return str(value) |
| 276 | |
| 277 | |
| 278 | def _format_value_for_input(value: Any, field_type: str) -> str: |
| 279 | """Format a value for use as input default.""" |
| 280 | if value is None or value == "": |
| 281 | return "" |
| 282 | if field_type == "list" and isinstance(value, list): |
| 283 | return ",".join(str(v) for v in value) |
| 284 | if field_type == "dict" and isinstance(value, dict): |
| 285 | return json.dumps(value) |
| 286 | return str(value) |
| 287 | |
| 288 | |
| 289 | def _validate_field_constraint(value: Any, field_info) -> str | None: |
| 290 | """Validate a value against Pydantic Field constraints. |
| 291 | |
| 292 | Returns an error message string if validation fails, None if valid. |
| 293 | Uses attribute-based detection to handle Pydantic v2 internal types. |
| 294 | """ |
| 295 | if field_info is None or not hasattr(field_info, "metadata"): |
| 296 | return None |
| 297 | |
| 298 | for m in field_info.metadata: |
| 299 | if hasattr(m, "ge") and isinstance(value, (int, float)): |
| 300 | if value < m.ge: |
| 301 | return f"Value must be >= {m.ge}" |
| 302 | if hasattr(m, "gt") and isinstance(value, (int, float)): |
| 303 | if value <= m.gt: |
| 304 | return f"Value must be > {m.gt}" |
| 305 | if hasattr(m, "le") and isinstance(value, (int, float)): |
| 306 | if value > m.le: |
| 307 | return f"Value must be <= {m.le}" |
| 308 | if hasattr(m, "lt") and isinstance(value, (int, float)): |
| 309 | if value >= m.lt: |
| 310 | return f"Value must be < {m.lt}" |
| 311 | if hasattr(m, "min_length") and hasattr(value, "__len__"): |
| 312 | if len(value) < m.min_length: |
| 313 | return f"Length must be >= {m.min_length}" |
| 314 | if hasattr(m, "max_length") and hasattr(value, "__len__"): |
| 315 | if len(value) > m.max_length: |
| 316 | return f"Length must be <= {m.max_length}" |
| 317 | |
| 318 | return None |
| 319 | |
| 320 | |
| 321 | def _get_constraint_hint(field_info) -> str: |
| 322 | """Derive a human-readable constraint hint from field metadata. |
| 323 | |
| 324 | Returns a string like "(0-10)" or "(>= 0)" to append to field display names. |
| 325 | """ |
| 326 | if field_info is None or not hasattr(field_info, "metadata"): |
| 327 | return "" |
| 328 | |
| 329 | ge_val = None |
| 330 | le_val = None |
| 331 | for m in field_info.metadata: |
| 332 | if hasattr(m, "ge"): |
| 333 | ge_val = m.ge |
| 334 | if hasattr(m, "le"): |
| 335 | le_val = m.le |
| 336 | |
| 337 | if ge_val is not None and le_val is not None: |
| 338 | return f" ({ge_val}-{le_val})" |
| 339 | if ge_val is not None: |
| 340 | return f" (>= {ge_val})" |
| 341 | if le_val is not None: |
| 342 | return f" (<= {le_val})" |
| 343 | return "" |
| 344 | |
| 345 | |
| 346 | # --- Rich UI Components --- |
| 347 | |
| 348 | |
| 349 | def _show_config_panel(display_name: str, model: BaseModel, fields: list) -> None: |
| 350 | """Display current configuration as a rich table.""" |
| 351 | table = Table(show_header=False, box=None, padding=(0, 2)) |
| 352 | table.add_column("Field", style="cyan") |
| 353 | table.add_column("Value") |
| 354 | |
| 355 | for fname, field_info in fields: |
| 356 | value = getattr(model, fname, None) |
| 357 | display = _get_field_display_name(fname, field_info) |
| 358 | formatted = _format_value(value, rich=True, field_name=fname) |
| 359 | table.add_row(display, formatted) |
| 360 | |
| 361 | console.print(Panel(table, title=f"[bold]{display_name}[/bold]", border_style="blue")) |
| 362 | |
| 363 | |
| 364 | def _show_main_menu_header() -> None: |
| 365 | """Display the main menu header.""" |
| 366 | from nanobot import __logo__, __version__ |
| 367 | |
| 368 | console.print() |
| 369 | # Use Align.CENTER for the single line of text |
| 370 | from rich.align import Align |
| 371 | |
| 372 | console.print( |
| 373 | Align.center(f"{__logo__} [bold cyan]nanobot[{__version__}][/bold cyan]") |
| 374 | ) |
| 375 | console.print() |
| 376 | |
| 377 | |
| 378 | def _show_section_header(title: str, subtitle: str = "") -> None: |
| 379 | """Display a section header.""" |
| 380 | console.print() |
| 381 | if subtitle: |
| 382 | console.print( |
| 383 | Panel(f"[dim]{subtitle}[/dim]", title=f"[bold]{title}[/bold]", border_style="blue") |
| 384 | ) |
| 385 | else: |
| 386 | console.print(Panel("", title=f"[bold]{title}[/bold]", border_style="blue")) |
| 387 | |
| 388 | |
| 389 | # --- Input Handlers --- |
| 390 | |
| 391 | |
| 392 | def _input_bool(display_name: str, current: bool | None) -> bool | None: |
| 393 | """Get boolean input via confirm dialog.""" |
| 394 | return _get_questionary().confirm( |
| 395 | display_name, |
| 396 | default=bool(current) if current is not None else False, |
| 397 | ).ask() |
| 398 | |
| 399 | |
| 400 | def _input_text(display_name: str, current: Any, field_type: str, field_info=None) -> Any: |
| 401 | """Get text input and parse based on field type.""" |
| 402 | default = _format_value_for_input(current, field_type) |
| 403 | |
| 404 | value = _get_questionary().text(f"{display_name}:", default=default).ask() |
| 405 | |
| 406 | if value is None or value == "": |
| 407 | return None |
| 408 | |
| 409 | if field_type == "int": |
| 410 | try: |
| 411 | parsed = int(value) |
| 412 | except ValueError: |
| 413 | console.print("[yellow]! Invalid number format, value not saved[/yellow]") |
| 414 | return None |
| 415 | if field_info: |
| 416 | error = _validate_field_constraint(parsed, field_info) |
| 417 | if error: |
| 418 | console.print(f"[yellow]! {error}, value not saved[/yellow]") |
| 419 | return None |
| 420 | return parsed |
| 421 | elif field_type == "float": |
| 422 | try: |
| 423 | parsed = float(value) |
| 424 | except ValueError: |
| 425 | console.print("[yellow]! Invalid number format, value not saved[/yellow]") |
| 426 | return None |
| 427 | if field_info: |
| 428 | error = _validate_field_constraint(parsed, field_info) |
| 429 | if error: |
| 430 | console.print(f"[yellow]! {error}, value not saved[/yellow]") |
| 431 | return None |
| 432 | return parsed |
| 433 | elif field_type == "list": |
| 434 | return [v.strip() for v in value.split(",") if v.strip()] |
| 435 | elif field_type == "dict": |
| 436 | try: |
| 437 | return json.loads(value) |
| 438 | except json.JSONDecodeError: |
| 439 | console.print("[yellow]! Invalid JSON format, value not saved[/yellow]") |
| 440 | return None |
| 441 | |
| 442 | return value |
| 443 | |
| 444 | |
| 445 | def _input_with_existing( |
| 446 | display_name: str, current: Any, field_type: str, field_info=None |
| 447 | ) -> Any: |
| 448 | """Handle input with 'keep existing' option for non-empty values.""" |
| 449 | has_existing = current is not None and current != "" and current != {} and current != [] |
| 450 | |
| 451 | if has_existing and not isinstance(current, list): |
| 452 | choice = _get_questionary().select( |
| 453 | display_name, |
| 454 | choices=["Enter new value", "Keep existing value"], |
| 455 | default="Keep existing value", |
| 456 | ).ask() |
| 457 | if choice == "Keep existing value" or choice is None: |
| 458 | return None |
| 459 | |
| 460 | return _input_text(display_name, current, field_type, field_info=field_info) |
| 461 | |
| 462 | |
| 463 | # --- Pydantic Model Configuration --- |
| 464 | |
| 465 | |
| 466 | def _get_current_provider(model: BaseModel) -> str: |
| 467 | """Get the current provider setting from a model (if available).""" |
| 468 | if hasattr(model, "provider"): |
| 469 | return getattr(model, "provider", "auto") or "auto" |
| 470 | return "auto" |
| 471 | |
| 472 | |
| 473 | def _input_model_with_autocomplete( |
| 474 | display_name: str, current: Any, provider: str |
| 475 | ) -> str | None: |
| 476 | """Get model input with autocomplete suggestions. |
| 477 | |
| 478 | """ |
| 479 | from prompt_toolkit.completion import Completer, Completion |
| 480 | |
| 481 | default = str(current) if current else "" |
| 482 | |
| 483 | class DynamicModelCompleter(Completer): |
| 484 | """Completer that dynamically fetches model suggestions.""" |
| 485 | |
| 486 | def __init__(self, provider_name: str): |
| 487 | self.provider = provider_name |
| 488 | |
| 489 | def get_completions(self, document, complete_event): |
| 490 | text = document.text_before_cursor |
| 491 | suggestions = get_model_suggestions(text, provider=self.provider, limit=50) |
| 492 | for model in suggestions: |
| 493 | # Skip if model doesn't contain the typed text |
| 494 | if text.lower() not in model.lower(): |
| 495 | continue |
| 496 | yield Completion( |
| 497 | model, |
| 498 | start_position=-len(text), |
| 499 | display=model, |
| 500 | ) |
| 501 | |
| 502 | value = _get_questionary().autocomplete( |
| 503 | f"{display_name}:", |
| 504 | choices=[""], # Placeholder, actual completions from completer |
| 505 | completer=DynamicModelCompleter(provider), |
| 506 | default=default, |
| 507 | qmark=">", |
| 508 | ).ask() |
| 509 | |
| 510 | return value if value else None |
| 511 | |
| 512 | |
| 513 | def _input_context_window_with_recommendation( |
| 514 | display_name: str, current: Any, model_obj: BaseModel |
| 515 | ) -> int | None: |
| 516 | """Get context window input with option to fetch recommended value.""" |
| 517 | current_val = current if current else "" |
| 518 | |
| 519 | choices = ["Enter new value"] |
| 520 | if current_val: |
| 521 | choices.append("Keep existing value") |
| 522 | choices.append("[?] Get recommended value") |
| 523 | |
| 524 | choice = _get_questionary().select( |
| 525 | display_name, |
| 526 | choices=choices, |
| 527 | default="Enter new value", |
| 528 | ).ask() |
| 529 | |
| 530 | if choice is None: |
| 531 | return None |
| 532 | |
| 533 | if choice == "Keep existing value": |
| 534 | return None |
| 535 | |
| 536 | if choice == "[?] Get recommended value": |
| 537 | # Get the model name from the model object |
| 538 | model_name = getattr(model_obj, "model", None) |
| 539 | if not model_name: |
| 540 | console.print("[yellow]! Please configure the model field first[/yellow]") |
| 541 | return None |
| 542 | |
| 543 | provider = _get_current_provider(model_obj) |
| 544 | context_limit = get_model_context_limit(model_name, provider) |
| 545 | |
| 546 | if context_limit: |
| 547 | console.print(f"[green]+ Recommended context window: {format_token_count(context_limit)} tokens[/green]") |
| 548 | return context_limit |
| 549 | else: |
| 550 | console.print("[yellow]! Could not fetch model info, please enter manually[/yellow]") |
| 551 | # Fall through to manual input |
| 552 | |
| 553 | # Manual input |
| 554 | value = _get_questionary().text( |
| 555 | f"{display_name}:", |
| 556 | default=str(current_val) if current_val else "", |
| 557 | ).ask() |
| 558 | |
| 559 | if value is None or value == "": |
| 560 | return None |
| 561 | |
| 562 | try: |
| 563 | return int(value) |
| 564 | except ValueError: |
| 565 | console.print("[yellow]! Invalid number format, value not saved[/yellow]") |
| 566 | return None |
| 567 | |
| 568 | |
| 569 | def _handle_model_field( |
| 570 | working_model: BaseModel, field_name: str, field_display: str, current_value: Any |
| 571 | ) -> None: |
| 572 | """Handle the 'model' field with autocomplete and context-window auto-fill.""" |
| 573 | provider = _get_current_provider(working_model) |
| 574 | new_value = _input_model_with_autocomplete(field_display, current_value, provider) |
| 575 | if new_value is not None and new_value != current_value: |
| 576 | setattr(working_model, field_name, new_value) |
| 577 | _try_auto_fill_context_window(working_model, new_value) |
| 578 | |
| 579 | |
| 580 | def _handle_context_window_field( |
| 581 | working_model: BaseModel, field_name: str, field_display: str, current_value: Any |
| 582 | ) -> None: |
| 583 | """Handle context_window_tokens with recommendation lookup.""" |
| 584 | new_value = _input_context_window_with_recommendation( |
| 585 | field_display, current_value, working_model |
| 586 | ) |
| 587 | if new_value is not None: |
| 588 | setattr(working_model, field_name, new_value) |
| 589 | |
| 590 | |
| 591 | _FIELD_HANDLERS: dict[str, Any] = { |
| 592 | "model": _handle_model_field, |
| 593 | "context_window_tokens": _handle_context_window_field, |
| 594 | } |
| 595 | |
| 596 | |
| 597 | def _configure_pydantic_model( |
| 598 | model: BaseModel, |
| 599 | display_name: str, |
| 600 | *, |
| 601 | skip_fields: set[str] | None = None, |
| 602 | ) -> BaseModel | None: |
| 603 | """Configure a Pydantic model interactively. |
| 604 | |
| 605 | Returns the updated model only when the user explicitly selects "Done". |
| 606 | Back and cancel actions discard the section draft. |
| 607 | """ |
| 608 | skip_fields = skip_fields or set() |
| 609 | working_model = model.model_copy(deep=True) |
| 610 | |
| 611 | fields = [ |
| 612 | (name, info) |
| 613 | for name, info in type(working_model).model_fields.items() |
| 614 | if name not in skip_fields |
| 615 | ] |
| 616 | if not fields: |
| 617 | console.print(f"[dim]{display_name}: No configurable fields[/dim]") |
| 618 | return working_model |
| 619 | |
| 620 | def get_choices() -> list[str]: |
| 621 | items = [] |
| 622 | for fname, finfo in fields: |
| 623 | value = getattr(working_model, fname, None) |
| 624 | display = _get_field_display_name(fname, finfo) |
| 625 | formatted = _format_value(value, rich=False, field_name=fname) |
| 626 | items.append(f"{display}: {formatted}") |
| 627 | return items + ["[Done]"] |
| 628 | |
| 629 | while True: |
| 630 | console.clear() |
| 631 | _show_config_panel(display_name, working_model, fields) |
| 632 | choices = get_choices() |
| 633 | answer = _select_with_back("Select field to configure:", choices) |
| 634 | |
| 635 | if answer is _BACK_PRESSED or answer is None: |
| 636 | return None |
| 637 | if answer == "[Done]": |
| 638 | return working_model |
| 639 | |
| 640 | field_idx = next((i for i, c in enumerate(choices) if c == answer), -1) |
| 641 | if field_idx < 0 or field_idx >= len(fields): |
| 642 | return None |
| 643 | |
| 644 | field_name, field_info = fields[field_idx] |
| 645 | current_value = getattr(working_model, field_name, None) |
| 646 | ftype = _get_field_type_info(field_info) |
| 647 | field_display = _get_field_display_name(field_name, field_info) + _get_constraint_hint(field_info) |
| 648 | |
| 649 | # Nested Pydantic model - recurse |
| 650 | if ftype.type_name == "model": |
| 651 | nested = current_value |
| 652 | created = nested is None |
| 653 | if nested is None and ftype.inner_type: |
| 654 | nested = ftype.inner_type() |
| 655 | if nested and isinstance(nested, BaseModel): |
| 656 | updated = _configure_pydantic_model(nested, field_display) |
| 657 | if updated is not None: |
| 658 | setattr(working_model, field_name, updated) |
| 659 | elif created: |
| 660 | setattr(working_model, field_name, None) |
| 661 | continue |
| 662 | |
| 663 | # Registered special-field handlers |
| 664 | handler = _FIELD_HANDLERS.get(field_name) |
| 665 | if handler: |
| 666 | handler(working_model, field_name, field_display, current_value) |
| 667 | continue |
| 668 | |
| 669 | # Select fields with hints (e.g. reasoning_effort) |
| 670 | if field_name in _SELECT_FIELD_HINTS: |
| 671 | choices_list, hint = _SELECT_FIELD_HINTS[field_name] |
| 672 | select_choices = choices_list + ["(clear/unset)"] |
| 673 | console.print(f"[dim] Hint: {hint}[/dim]") |
| 674 | new_value = _select_with_back( |
| 675 | field_display, select_choices, default=current_value or select_choices[0] |
| 676 | ) |
| 677 | if new_value is _BACK_PRESSED: |
| 678 | continue |
| 679 | if new_value == "(clear/unset)": |
| 680 | setattr(working_model, field_name, None) |
| 681 | elif new_value is not None: |
| 682 | setattr(working_model, field_name, new_value) |
| 683 | continue |
| 684 | |
| 685 | # Generic field input |
| 686 | if ftype.type_name == "literal" and ftype.inner_type: |
| 687 | select_choices = [str(v) for v in ftype.inner_type] |
| 688 | default_choice = str(current_value) if current_value in ftype.inner_type else select_choices[0] |
| 689 | new_value = _select_with_back(field_display, select_choices, default=default_choice) |
| 690 | if new_value is _BACK_PRESSED: |
| 691 | continue |
| 692 | if new_value is not None: |
| 693 | setattr(working_model, field_name, new_value) |
| 694 | continue |
| 695 | if ftype.type_name == "bool": |
| 696 | new_value = _input_bool(field_display, current_value) |
| 697 | else: |
| 698 | new_value = _input_with_existing(field_display, current_value, ftype.type_name, field_info=field_info) |
| 699 | if new_value is not None: |
| 700 | setattr(working_model, field_name, new_value) |
| 701 | |
| 702 | |
| 703 | def _try_auto_fill_context_window(model: BaseModel, new_model_name: str) -> None: |
| 704 | """Try to auto-fill context_window_tokens if it's at default value. |
| 705 | |
| 706 | Note: |
| 707 | This function imports AgentDefaults from nanobot.config.schema to get |
| 708 | the default context_window_tokens value. If the schema changes, this |
| 709 | coupling needs to be updated accordingly. |
| 710 | """ |
| 711 | # Check if context_window_tokens field exists |
| 712 | if not hasattr(model, "context_window_tokens"): |
| 713 | return |
| 714 | |
| 715 | current_context = getattr(model, "context_window_tokens", None) |
| 716 | |
| 717 | # Check if current value is the default (65536) |
| 718 | # We only auto-fill if the user hasn't changed it from default |
| 719 | from nanobot.config.schema import AgentDefaults |
| 720 | |
| 721 | default_context = AgentDefaults.model_fields["context_window_tokens"].default |
| 722 | |
| 723 | if current_context != default_context: |
| 724 | return # User has customized it, don't override |
| 725 | |
| 726 | provider = _get_current_provider(model) |
| 727 | context_limit = get_model_context_limit(new_model_name, provider) |
| 728 | |
| 729 | if context_limit: |
| 730 | setattr(model, "context_window_tokens", context_limit) |
| 731 | console.print(f"[green]+ Auto-filled context window: {format_token_count(context_limit)} tokens[/green]") |
| 732 | else: |
| 733 | console.print("[dim](i) Could not auto-fill context window (model not in database)[/dim]") |
| 734 | |
| 735 | |
| 736 | # --- Provider Configuration --- |
| 737 | |
| 738 | |
| 739 | @lru_cache(maxsize=1) |
| 740 | def _get_provider_info() -> dict[str, tuple[str, bool, bool, str]]: |
| 741 | """Get provider info from registry (cached).""" |
| 742 | from nanobot.providers.registry import PROVIDERS |
| 743 | |
| 744 | return { |
| 745 | spec.name: ( |
| 746 | spec.display_name or spec.name, |
| 747 | spec.is_gateway, |
| 748 | spec.is_local, |
| 749 | spec.default_api_base, |
| 750 | ) |
| 751 | for spec in PROVIDERS |
| 752 | if not spec.is_oauth |
| 753 | } |
| 754 | |
| 755 | |
| 756 | def _get_provider_names() -> dict[str, str]: |
| 757 | """Get provider display names.""" |
| 758 | info = _get_provider_info() |
| 759 | return {name: data[0] for name, data in info.items() if name} |
| 760 | |
| 761 | |
| 762 | def _configure_provider(config: Config, provider_name: str) -> None: |
| 763 | """Configure a single LLM provider.""" |
| 764 | provider_config = getattr(config.providers, provider_name, None) |
| 765 | if provider_config is None: |
| 766 | console.print(f"[red]Unknown provider: {provider_name}[/red]") |
| 767 | return |
| 768 | |
| 769 | display_name = _get_provider_names().get(provider_name, provider_name) |
| 770 | info = _get_provider_info() |
| 771 | default_api_base = info.get(provider_name, (None, None, None, None))[3] |
| 772 | |
| 773 | if default_api_base and not provider_config.api_base: |
| 774 | provider_config.api_base = default_api_base |
| 775 | |
| 776 | updated_provider = _configure_pydantic_model( |
| 777 | provider_config, |
| 778 | display_name, |
| 779 | ) |
| 780 | if updated_provider is not None: |
| 781 | setattr(config.providers, provider_name, updated_provider) |
| 782 | |
| 783 | |
| 784 | def _configure_providers(config: Config) -> None: |
| 785 | """Configure LLM providers.""" |
| 786 | |
| 787 | def get_provider_choices() -> list[str]: |
| 788 | """Build provider choices with config status indicators.""" |
| 789 | choices = [] |
| 790 | for name, display in _get_provider_names().items(): |
| 791 | provider = getattr(config.providers, name, None) |
| 792 | if provider and provider.api_key: |
| 793 | choices.append(f"{display} *") |
| 794 | else: |
| 795 | choices.append(display) |
| 796 | return choices + ["<- Back"] |
| 797 | |
| 798 | while True: |
| 799 | try: |
| 800 | console.clear() |
| 801 | _show_section_header("LLM Providers", "Select a provider to configure API key and endpoint") |
| 802 | choices = get_provider_choices() |
| 803 | answer = _select_with_back("Select provider:", choices) |
| 804 | |
| 805 | if answer is _BACK_PRESSED or answer is None or answer == "<- Back": |
| 806 | break |
| 807 | |
| 808 | # Type guard: answer is now guaranteed to be a string |
| 809 | assert isinstance(answer, str) |
| 810 | # Extract provider name from choice (remove " *" suffix if present) |
| 811 | provider_name = answer.replace(" *", "") |
| 812 | # Find the actual provider key from display names |
| 813 | for name, display in _get_provider_names().items(): |
| 814 | if display == provider_name: |
| 815 | _configure_provider(config, name) |
| 816 | break |
| 817 | |
| 818 | except KeyboardInterrupt: |
| 819 | console.print("\n[dim]Returning to main menu...[/dim]") |
| 820 | break |
| 821 | |
| 822 | |
| 823 | # --- Channel Configuration --- |
| 824 | |
| 825 | |
| 826 | @lru_cache(maxsize=1) |
| 827 | def _get_channel_info() -> dict[str, tuple[str, type[BaseModel]]]: |
| 828 | """Get channel info (display name + config class) from channel modules.""" |
| 829 | import importlib |
| 830 | |
| 831 | from nanobot.channels.registry import discover_all |
| 832 | |
| 833 | result: dict[str, tuple[str, type[BaseModel]]] = {} |
| 834 | for name, channel_cls in discover_all().items(): |
| 835 | try: |
| 836 | mod = importlib.import_module(f"nanobot.channels.{name}") |
| 837 | config_name = channel_cls.__name__.replace("Channel", "Config") |
| 838 | config_cls = getattr(mod, config_name, None) |
| 839 | if config_cls and isinstance(config_cls, type) and issubclass(config_cls, BaseModel): |
| 840 | display_name = getattr(channel_cls, "display_name", name.capitalize()) |
| 841 | result[name] = (display_name, config_cls) |
| 842 | except Exception: |
| 843 | logger.warning(f"Failed to load channel module: {name}") |
| 844 | return result |
| 845 | |
| 846 | |
| 847 | def _get_channel_names() -> dict[str, str]: |
| 848 | """Get channel display names.""" |
| 849 | return {name: info[0] for name, info in _get_channel_info().items()} |
| 850 | |
| 851 | |
| 852 | def _get_channel_config_class(channel: str) -> type[BaseModel] | None: |
| 853 | """Get channel config class.""" |
| 854 | entry = _get_channel_info().get(channel) |
| 855 | return entry[1] if entry else None |
| 856 | |
| 857 | |
| 858 | def _configure_channel(config: Config, channel_name: str) -> None: |
| 859 | """Configure a single channel.""" |
| 860 | channel_dict = getattr(config.channels, channel_name, None) |
| 861 | if channel_dict is None: |
| 862 | channel_dict = {} |
| 863 | setattr(config.channels, channel_name, channel_dict) |
| 864 | |
| 865 | display_name = _get_channel_names().get(channel_name, channel_name) |
| 866 | config_cls = _get_channel_config_class(channel_name) |
| 867 | |
| 868 | if config_cls is None: |
| 869 | console.print(f"[red]No configuration class found for {display_name}[/red]") |
| 870 | return |
| 871 | |
| 872 | model = config_cls.model_validate(channel_dict) if channel_dict else config_cls() |
| 873 | |
| 874 | updated_channel = _configure_pydantic_model( |
| 875 | model, |
| 876 | display_name, |
| 877 | ) |
| 878 | if updated_channel is not None: |
| 879 | new_dict = updated_channel.model_dump(by_alias=True, exclude_none=True) |
| 880 | setattr(config.channels, channel_name, new_dict) |
| 881 | |
| 882 | |
| 883 | def _configure_channels(config: Config) -> None: |
| 884 | """Configure chat channels.""" |
| 885 | channel_names = list(_get_channel_names().keys()) |
| 886 | choices = channel_names + ["<- Back"] |
| 887 | |
| 888 | while True: |
| 889 | try: |
| 890 | console.clear() |
| 891 | _show_section_header("Chat Channels", "Select a channel to configure connection settings") |
| 892 | answer = _select_with_back("Select channel:", choices) |
| 893 | |
| 894 | if answer is _BACK_PRESSED or answer is None or answer == "<- Back": |
| 895 | break |
| 896 | |
| 897 | # Type guard: answer is now guaranteed to be a string |
| 898 | assert isinstance(answer, str) |
| 899 | _configure_channel(config, answer) |
| 900 | except KeyboardInterrupt: |
| 901 | console.print("\n[dim]Returning to main menu...[/dim]") |
| 902 | break |
| 903 | |
| 904 | |
| 905 | # --- General Settings --- |
| 906 | |
| 907 | _SETTINGS_SECTIONS: dict[str, tuple[str, str, set[str] | None]] = { |
| 908 | "Agent Settings": ("Agent Defaults", "Configure default model, temperature, and behavior", None), |
| 909 | "Channel Common": ("Channel Common", "Configure cross-channel behavior: progress, tool hints, retries", None), |
| 910 | "API Server": ("API Server", "Configure OpenAI-compatible API endpoint", None), |
| 911 | "Gateway": ("Gateway Settings", "Configure server host, port, and heartbeat", None), |
| 912 | "Tools": ("Tools Settings", "Configure web search, shell exec, and other tools", {"mcp_servers"}), |
| 913 | } |
| 914 | |
| 915 | _SETTINGS_GETTER = { |
| 916 | "Agent Settings": lambda c: c.agents.defaults, |
| 917 | "Channel Common": lambda c: c.channels, |
| 918 | "API Server": lambda c: c.api, |
| 919 | "Gateway": lambda c: c.gateway, |
| 920 | "Tools": lambda c: c.tools, |
| 921 | } |
| 922 | |
| 923 | _SETTINGS_SETTER = { |
| 924 | "Agent Settings": lambda c, v: setattr(c.agents, "defaults", v), |
| 925 | "Channel Common": lambda c, v: setattr(c, "channels", v), |
| 926 | "API Server": lambda c, v: setattr(c, "api", v), |
| 927 | "Gateway": lambda c, v: setattr(c, "gateway", v), |
| 928 | "Tools": lambda c, v: setattr(c, "tools", v), |
| 929 | } |
| 930 | |
| 931 | |
| 932 | def _configure_general_settings(config: Config, section: str) -> None: |
| 933 | """Configure a general settings section (header + model edit + writeback).""" |
| 934 | meta = _SETTINGS_SECTIONS.get(section) |
| 935 | if not meta: |
| 936 | return |
| 937 | display_name, subtitle, skip = meta |
| 938 | model = _SETTINGS_GETTER[section](config) |
| 939 | updated = _configure_pydantic_model(model, display_name, skip_fields=skip) |
| 940 | if updated is not None: |
| 941 | _SETTINGS_SETTER[section](config, updated) |
| 942 | |
| 943 | |
| 944 | # --- Summary --- |
| 945 | |
| 946 | |
| 947 | def _summarize_model(obj: BaseModel) -> list[tuple[str, str]]: |
| 948 | """Recursively summarize a Pydantic model. Returns list of (field, value) tuples.""" |
| 949 | items: list[tuple[str, str]] = [] |
| 950 | for field_name, field_info in type(obj).model_fields.items(): |
| 951 | value = getattr(obj, field_name, None) |
| 952 | if value is None or value == "" or value == {} or value == []: |
| 953 | continue |
| 954 | display = _get_field_display_name(field_name, field_info) |
| 955 | ftype = _get_field_type_info(field_info) |
| 956 | if ftype.type_name == "model" and isinstance(value, BaseModel): |
| 957 | for nested_field, nested_value in _summarize_model(value): |
| 958 | items.append((f"{display}.{nested_field}", nested_value)) |
| 959 | continue |
| 960 | formatted = _format_value(value, rich=False, field_name=field_name) |
| 961 | if formatted != "[not set]": |
| 962 | items.append((display, formatted)) |
| 963 | return items |
| 964 | |
| 965 | |
| 966 | def _print_summary_panel(rows: list[tuple[str, str]], title: str) -> None: |
| 967 | """Build a two-column summary panel and print it.""" |
| 968 | if not rows: |
| 969 | return |
| 970 | table = Table(show_header=False, box=None, padding=(0, 2)) |
| 971 | table.add_column("Setting", style="cyan") |
| 972 | table.add_column("Value") |
| 973 | for field, value in rows: |
| 974 | table.add_row(field, value) |
| 975 | console.print(Panel(table, title=f"[bold]{title}[/bold]", border_style="blue")) |
| 976 | |
| 977 | |
| 978 | def _show_summary(config: Config) -> None: |
| 979 | """Display configuration summary using rich.""" |
| 980 | console.print() |
| 981 | |
| 982 | # Providers |
| 983 | provider_rows = [] |
| 984 | for name, display in _get_provider_names().items(): |
| 985 | provider = getattr(config.providers, name, None) |
| 986 | status = "[green]configured[/green]" if (provider and provider.api_key) else "[dim]not configured[/dim]" |
| 987 | provider_rows.append((display, status)) |
| 988 | _print_summary_panel(provider_rows, "LLM Providers") |
| 989 | |
| 990 | # Channels |
| 991 | channel_rows = [] |
| 992 | for name, display in _get_channel_names().items(): |
| 993 | channel = getattr(config.channels, name, None) |
| 994 | if channel: |
| 995 | enabled = ( |
| 996 | channel.get("enabled", False) |
| 997 | if isinstance(channel, dict) |
| 998 | else getattr(channel, "enabled", False) |
| 999 | ) |
| 1000 | status = "[green]enabled[/green]" if enabled else "[dim]disabled[/dim]" |
| 1001 | else: |
| 1002 | status = "[dim]not configured[/dim]" |
| 1003 | channel_rows.append((display, status)) |
| 1004 | _print_summary_panel(channel_rows, "Chat Channels") |
| 1005 | |
| 1006 | # Settings sections |
| 1007 | for title, model in [ |
| 1008 | ("Agent Settings", config.agents.defaults), |
| 1009 | ("Channel Common", config.channels), |
| 1010 | ("API Server", config.api), |
| 1011 | ("Gateway", config.gateway), |
| 1012 | ("Tools", config.tools), |
| 1013 | ]: |
| 1014 | _print_summary_panel(_summarize_model(model), title) |
| 1015 | |
| 1016 | _pause() |
| 1017 | |
| 1018 | |
| 1019 | def _pause() -> None: |
| 1020 | """Pause for user acknowledgement before clearing the screen.""" |
| 1021 | _get_questionary().text("Press Enter to continue...", default="").ask() |
| 1022 | |
| 1023 | |
| 1024 | # --- Main Entry Point --- |
| 1025 | |
| 1026 | |
| 1027 | def _has_unsaved_changes(original: Config, current: Config) -> bool: |
| 1028 | """Return True when the onboarding session has committed changes.""" |
| 1029 | return original.model_dump(by_alias=True) != current.model_dump(by_alias=True) |
| 1030 | |
| 1031 | |
| 1032 | def _prompt_main_menu_exit(has_unsaved_changes: bool) -> str: |
| 1033 | """Resolve how to leave the main menu.""" |
| 1034 | if not has_unsaved_changes: |
| 1035 | return "discard" |
| 1036 | |
| 1037 | answer = _get_questionary().select( |
| 1038 | "You have unsaved changes. What would you like to do?", |
| 1039 | choices=[ |
| 1040 | "[S] Save and Exit", |
| 1041 | "[X] Exit Without Saving", |
| 1042 | "[R] Resume Editing", |
| 1043 | ], |
| 1044 | default="[R] Resume Editing", |
| 1045 | qmark=">", |
| 1046 | ).ask() |
| 1047 | |
| 1048 | if answer == "[S] Save and Exit": |
| 1049 | return "save" |
| 1050 | if answer == "[X] Exit Without Saving": |
| 1051 | return "discard" |
| 1052 | return "resume" |
| 1053 | |
| 1054 | |
| 1055 | def run_onboard(initial_config: Config | None = None) -> OnboardResult: |
| 1056 | """Run the interactive onboarding questionnaire. |
| 1057 | |
| 1058 | Args: |
| 1059 | initial_config: Optional pre-loaded config to use as starting point. |
| 1060 | If None, loads from config file or creates new default. |
| 1061 | """ |
| 1062 | _get_questionary() |
| 1063 | |
| 1064 | if initial_config is not None: |
| 1065 | base_config = initial_config.model_copy(deep=True) |
| 1066 | else: |
| 1067 | config_path = get_config_path() |
| 1068 | if config_path.exists(): |
| 1069 | base_config = load_config() |
| 1070 | else: |
| 1071 | base_config = Config() |
| 1072 | |
| 1073 | original_config = base_config.model_copy(deep=True) |
| 1074 | config = base_config.model_copy(deep=True) |
| 1075 | |
| 1076 | while True: |
| 1077 | console.clear() |
| 1078 | _show_main_menu_header() |
| 1079 | |
| 1080 | try: |
| 1081 | answer = _get_questionary().select( |
| 1082 | "What would you like to configure?", |
| 1083 | choices=[ |
| 1084 | "[P] LLM Provider", |
| 1085 | "[C] Chat Channel", |
| 1086 | "[H] Channel Common", |
| 1087 | "[A] Agent Settings", |
| 1088 | "[I] API Server", |
| 1089 | "[G] Gateway", |
| 1090 | "[T] Tools", |
| 1091 | "[V] View Configuration Summary", |
| 1092 | "[S] Save and Exit", |
| 1093 | "[X] Exit Without Saving", |
| 1094 | ], |
| 1095 | qmark=">", |
| 1096 | ).ask() |
| 1097 | except KeyboardInterrupt: |
| 1098 | answer = None |
| 1099 | |
| 1100 | if answer is None: |
| 1101 | action = _prompt_main_menu_exit(_has_unsaved_changes(original_config, config)) |
| 1102 | if action == "save": |
| 1103 | return OnboardResult(config=config, should_save=True) |
| 1104 | if action == "discard": |
| 1105 | return OnboardResult(config=original_config, should_save=False) |
| 1106 | continue |
| 1107 | |
| 1108 | _MENU_DISPATCH = { |
| 1109 | "[P] LLM Provider": lambda: _configure_providers(config), |
| 1110 | "[C] Chat Channel": lambda: _configure_channels(config), |
| 1111 | "[H] Channel Common": lambda: _configure_general_settings(config, "Channel Common"), |
| 1112 | "[A] Agent Settings": lambda: _configure_general_settings(config, "Agent Settings"), |
| 1113 | "[I] API Server": lambda: _configure_general_settings(config, "API Server"), |
| 1114 | "[G] Gateway": lambda: _configure_general_settings(config, "Gateway"), |
| 1115 | "[T] Tools": lambda: _configure_general_settings(config, "Tools"), |
| 1116 | "[V] View Configuration Summary": lambda: _show_summary(config), |
| 1117 | } |
| 1118 | |
| 1119 | if answer == "[S] Save and Exit": |
| 1120 | return OnboardResult(config=config, should_save=True) |
| 1121 | if answer == "[X] Exit Without Saving": |
| 1122 | return OnboardResult(config=original_config, should_save=False) |
| 1123 | |
| 1124 | action_fn = _MENU_DISPATCH.get(answer) |
| 1125 | if action_fn: |
| 1126 | action_fn() |
| 1127 |