Coverage for little_loops / cli / loop / info.py: 4%

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1"""ll-loop info subcommands: list, history, show.""" 

2 

3from __future__ import annotations 

4 

5import argparse 

6import os 

7from datetime import datetime 

8from pathlib import Path 

9from typing import Any 

10 

11from little_loops.cli.loop._helpers import ( 

12 get_builtin_loops_dir, 

13 load_loop_with_spec, 

14 resolve_loop_path, 

15) 

16from little_loops.cli.loop.diagram_modes import resolve_facets 

17from little_loops.cli.loop.layout import ( # noqa: F401 

18 _EDGE_LABEL_COLORS, 

19 _box_inner_lines, 

20 _colorize_diagram_labels, 

21 _colorize_label, 

22 _render_fsm_diagram, 

23) 

24from little_loops.cli.output import colorize, print_json, strip_ansi, terminal_width 

25from little_loops.fsm import is_runnable_loop 

26from little_loops.fsm.schema import FSMLoop, StateConfig 

27from little_loops.fsm.validation import load_and_validate 

28from little_loops.logger import Logger 

29 

30 

31def _load_loop_meta(path: Path) -> dict[str, Any]: 

32 """Return metadata from a loop YAML file (description, category, labels).""" 

33 import yaml 

34 

35 try: 

36 with open(path) as f: 

37 spec = yaml.safe_load(f) or {} 

38 desc_raw = spec.get("description", "") or "" 

39 if desc_raw.strip(): 

40 raw_lines = desc_raw.splitlines() 

41 desc = raw_lines[0] 

42 if len(raw_lines) > 1: 

43 desc += "…" 

44 else: 

45 desc = "" 

46 category = spec.get("category", "") or "" 

47 labels: list[str] = spec.get("labels", []) or [] 

48 return {"description": desc, "category": category, "labels": labels} 

49 except Exception: 

50 return {"description": "", "category": "", "labels": []} 

51 

52 

53def cmd_list( 

54 args: argparse.Namespace, 

55 loops_dir: Path, 

56) -> int: 

57 """List loops.""" 

58 status_filter = getattr(args, "status", None) 

59 if getattr(args, "running", False) or status_filter: 

60 from little_loops.fsm.persistence import list_running_loops 

61 

62 states = list_running_loops(loops_dir) 

63 if status_filter: 

64 states = [s for s in states if s.status == status_filter] 

65 if not states: 

66 if status_filter: 

67 print(f"No loops with status: {status_filter}") 

68 return 1 

69 print("No running loops") 

70 return 0 

71 if getattr(args, "json", False): 

72 print_json([s.to_dict() for s in states]) 

73 return 0 

74 print(colorize("Running loops:", "1")) 

75 _STATUS_COLORS = {"running": "32", "interrupted": "33", "stopped": "2", "starting": "33"} 

76 

77 # Group by loop_name to avoid duplicate rows for multi-instance loops 

78 from collections import defaultdict 

79 

80 groups: dict[str, list] = defaultdict(list) 

81 for state in states: 

82 groups[state.loop_name].append(state) 

83 

84 for loop_name_key, group_states in groups.items(): 

85 if len(group_states) == 1: 

86 state = group_states[0] 

87 elapsed_s = (state.accumulated_ms or 0) // 1000 

88 elapsed_str = ( 

89 f"{elapsed_s}s" if elapsed_s < 60 else f"{elapsed_s // 60}m {elapsed_s % 60}s" 

90 ) 

91 name_str = colorize(state.loop_name, "1") 

92 state_str = colorize(state.current_state, "34") 

93 status_color = _STATUS_COLORS.get(state.status, "2") 

94 display_status = "paused" if state.status == "interrupted" else state.status 

95 status_str = colorize(f"[{display_status}]", status_color) 

96 elapsed_colored = colorize(elapsed_str, "2") 

97 print( 

98 f" {name_str}: {state_str} (iteration {state.iteration})" 

99 f" {status_str} {elapsed_colored}" 

100 ) 

101 else: 

102 # Multiple instances: show a grouped summary 

103 name_str = colorize(loop_name_key, "1") 

104 statuses = ", ".join( 

105 colorize( 

106 f"[{'paused' if s.status == 'interrupted' else s.status}]", 

107 _STATUS_COLORS.get(s.status, "2"), 

108 ) 

109 for s in group_states 

110 ) 

111 count_str = colorize(f"({len(group_states)} instances)", "2") 

112 print(f" {name_str}: {count_str} {statuses}") 

113 return 0 

114 

115 builtin_only = getattr(args, "builtin", False) 

116 

117 def _rel_key(path: Path, base: Path) -> str: 

118 """Relative-path identifier matching what `ll-loop run` accepts.""" 

119 return str(path.relative_to(base).with_suffix("")) 

120 

121 # Collect project loops (skipped when --builtin is set). Recurse into 

122 # subdirectories (e.g. oracles/) and filter to runnable FSM definitions so 

123 # library fragments under loops/lib/ stay hidden. 

124 project_names: set[str] = set() 

125 yaml_files: list[Path] = [] 

126 if not builtin_only and loops_dir.exists(): 

127 yaml_files = sorted(p for p in loops_dir.rglob("*.yaml") if is_runnable_loop(p)) 

128 project_names = {_rel_key(p, loops_dir) for p in yaml_files} 

129 

130 # Collect built-in loops (excluding those overridden by a project loop at 

131 # the same relative path). 

132 builtin_dir = get_builtin_loops_dir() 

133 builtin_files: list[Path] = [] 

134 if builtin_dir.exists(): 

135 builtin_files = [ 

136 f 

137 for f in sorted(builtin_dir.rglob("*.yaml")) 

138 if is_runnable_loop(f) and _rel_key(f, builtin_dir) not in project_names 

139 ] 

140 

141 if not yaml_files and not builtin_files: 

142 if getattr(args, "json", False): 

143 print_json([]) 

144 return 0 

145 print("No loops available") 

146 return 0 

147 

148 # Build combined metadata list 

149 all_loops: list[dict[str, Any]] = [] 

150 for path in yaml_files: 

151 meta = _load_loop_meta(path) 

152 all_loops.append( 

153 {"name": _rel_key(path, loops_dir), "path": path, "builtin": False, **meta} 

154 ) 

155 for path in builtin_files: 

156 meta = _load_loop_meta(path) 

157 all_loops.append( 

158 {"name": _rel_key(path, builtin_dir), "path": path, "builtin": True, **meta} 

159 ) 

160 

161 # Apply --category filter 

162 category_filter = getattr(args, "category", None) 

163 if category_filter: 

164 all_loops = [lp for lp in all_loops if lp["category"] == category_filter] 

165 

166 # Apply --label filter (action="append" → list or None) 

167 label_filters: list[str] = getattr(args, "label", None) or [] 

168 if label_filters: 

169 all_loops = [ 

170 lp 

171 for lp in all_loops 

172 if any(lf.lower() in [lb.lower() for lb in lp["labels"]] for lf in label_filters) 

173 ] 

174 

175 if not all_loops: 

176 if getattr(args, "json", False): 

177 print_json([]) 

178 return 0 

179 print("No loops match the given filters") 

180 return 0 

181 

182 if getattr(args, "json", False): 

183 items: list[dict[str, Any]] = [] 

184 for lp in all_loops: 

185 item: dict[str, Any] = { 

186 "name": lp["name"], 

187 "path": str(lp["path"]), 

188 "category": lp["category"], 

189 "labels": lp["labels"], 

190 "description": lp["description"], 

191 } 

192 if lp["builtin"]: 

193 item["built_in"] = True 

194 items.append(item) 

195 print_json(items) 

196 return 0 

197 

198 # Human-readable: group by category 

199 buckets: dict[str, list[dict[str, Any]]] = {} 

200 for lp in all_loops: 

201 cat = lp["category"] or "uncategorized" 

202 if cat not in buckets: 

203 buckets[cat] = [] 

204 buckets[cat].append(lp) 

205 

206 # Sort categories; "uncategorized" always last 

207 sorted_cats = sorted(c for c in buckets if c != "uncategorized") 

208 if "uncategorized" in buckets: 

209 sorted_cats.append("uncategorized") 

210 

211 # Compute max name width for column alignment 

212 max_name_len = max((len(lp["name"]) for lp in all_loops), default=0) 

213 name_col = max_name_len + 2 # padding after longest name 

214 tw = terminal_width() 

215 

216 cats_printed = False 

217 for cat in sorted_cats: 

218 group = buckets[cat] 

219 if cats_printed: 

220 print() # blank line between category groups 

221 cats_printed = True 

222 print(colorize(f"{cat} ({len(group)}):", "1")) 

223 for lp in group: 

224 # Name: project loops get bold cyan, built-in loops get dimmer cyan 

225 name_color = "36" if lp["builtin"] else "36;1" 

226 name_str = colorize(lp["name"].ljust(name_col), name_color) 

227 

228 # Suffix: labels + [built-in] tag 

229 suffix_parts: list[str] = [] 

230 if lp["labels"]: 

231 for label in lp["labels"]: 

232 suffix_parts.append(colorize(f"[{label}]", "2")) 

233 if lp["builtin"]: 

234 suffix_parts.append(colorize("[built-in]", "2")) 

235 

236 if suffix_parts: 

237 suffix_raw = " " + " ".join(suffix_parts) 

238 suffix_visible = len(strip_ansi(suffix_raw)) 

239 else: 

240 suffix_raw = "" 

241 suffix_visible = 0 

242 

243 # Available width for description: indent + name_col + " " + desc + suffix 

244 avail = tw - 2 - name_col - 2 - suffix_visible 

245 desc_text = lp["description"] or "" 

246 if desc_text and avail < len(desc_text): 

247 desc_text = _truncate(desc_text, max(avail, 20)) 

248 desc_str = f" {colorize(desc_text, '2')}" if desc_text else "" 

249 

250 print(f" {name_str}{desc_str}{suffix_raw}") 

251 return 0 

252 

253 

254_EVENT_TYPE_WIDTH = 16 # width of "handoff_detected" 

255 

256 

257def _truncate(text: str, max_len: int) -> str: 

258 """Truncate text to max_len with ellipsis.""" 

259 if max_len < 1: 

260 return "" 

261 if len(text) <= max_len: 

262 return text 

263 return text[: max_len - 1] + "\u2026" 

264 

265 

266def _format_history_event( 

267 event: dict[str, Any], verbose: bool, width: int, full: bool = False 

268) -> str | None: 

269 """Format a single history event. Returns None to skip the event.""" 

270 raw_ts = event.get("ts", "") 

271 try: 

272 ts = datetime.fromisoformat(raw_ts).strftime("%H:%M:%S") 

273 except (ValueError, TypeError): 

274 ts = raw_ts[:8] if len(raw_ts) >= 8 else raw_ts.ljust(8) 

275 

276 event_type = event.get("event", "unknown") 

277 

278 if event_type == "action_output" and not verbose: 

279 return None 

280 

281 ts_str = colorize(ts, "2") 

282 etype_padded = event_type.ljust(_EVENT_TYPE_WIDTH) 

283 etype_color = "0" 

284 detail = "" 

285 extra_lines: list[str] = [] 

286 

287 # Indentation prefix for verbose sub-lines (aligns under event detail column) 

288 _indent = " " * (8 + 2 + _EVENT_TYPE_WIDTH + 2) 

289 

290 if event_type == "loop_start": 

291 etype_color = "1" 

292 detail = event.get("loop", "") 

293 

294 elif event_type == "loop_complete": 

295 etype_color = "1" 

296 final_state = event.get("final_state", "") 

297 iterations = event.get("iterations", "") 

298 terminated_by = event.get("terminated_by", "") 

299 detail = f"{final_state} {iterations} iter [{terminated_by}]" 

300 

301 elif event_type == "loop_resume": 

302 etype_color = "1" 

303 from_state = event.get("from_state", "") 

304 iteration = event.get("iteration", "") 

305 detail = f"from={from_state} iter={iteration}" 

306 

307 elif event_type == "state_enter": 

308 etype_color = "34" 

309 state = event.get("state", "") 

310 iteration = event.get("iteration", "") 

311 detail = f"{colorize(state, '1')} (iter {iteration})" 

312 

313 elif event_type == "action_start": 

314 action = event.get("action", "") 

315 is_prompt = event.get("is_prompt", False) 

316 kind_label = "prompt" if is_prompt else "shell" 

317 kind_str = colorize(f"[{kind_label}]", "2") 

318 first_line = ( 

319 next((ln.strip() for ln in action.splitlines() if ln.strip()), "") 

320 if is_prompt 

321 else action 

322 ) 

323 avail = width - 8 - 2 - _EVENT_TYPE_WIDTH - 2 - len(kind_label) - 2 - 2 

324 detail = f"{_truncate(first_line, max(avail, 20))} {kind_str}" 

325 

326 elif event_type == "action_output": 

327 # Only reached in verbose mode 

328 etype_color = "2" 

329 detail = colorize("\u2502 " + event.get("line", ""), "2") 

330 

331 elif event_type == "action_complete": 

332 exit_code = event.get("exit_code", 0) 

333 duration_ms = event.get("duration_ms", 0) 

334 if exit_code == 0: 

335 etype_color = "2" 

336 status_str = colorize("\u2713", "32") 

337 else: 

338 etype_color = "38;5;208" 

339 status_str = colorize(f"\u2717 exit={exit_code}", "38;5;208") 

340 detail = f"{status_str} {duration_ms}ms" 

341 is_prompt = event.get("is_prompt", False) 

342 session_jsonl = event.get("session_jsonl") if is_prompt else None 

343 if session_jsonl: 

344 session_display = session_jsonl if verbose else os.path.basename(session_jsonl) 

345 detail += f" session={colorize(session_display, '2')}" 

346 if verbose: 

347 output_preview = event.get("output_preview", "") 

348 if output_preview: 

349 avail_w = width - len(_indent) - 2 

350 preview_text = ( 

351 output_preview if full else _truncate(output_preview, max(avail_w, 40)) 

352 ) 

353 for preview_line in preview_text.splitlines()[:5]: 

354 extra_lines.append(colorize(_indent + "\u2502 " + preview_line, "2")) 

355 

356 elif event_type == "evaluate": 

357 verdict = event.get("verdict", "") 

358 confidence = event.get("confidence", "") 

359 reason = event.get("reason", "") 

360 if verdict == "yes": 

361 etype_color = "32" 

362 verdict_str = colorize("\u2713 yes", "32") 

363 else: 

364 etype_color = "38;5;208" 

365 verdict_str = colorize(f"\u2717 {verdict}", "38;5;208") 

366 conf_part = f" confidence={confidence}" if confidence != "" else "" 

367 avail = width - 8 - 2 - _EVENT_TYPE_WIDTH - 2 - len("\u2713 yes") - len(conf_part) - 2 

368 reason_part = f" {_truncate(reason, max(avail, 20))}" if reason else "" 

369 detail = f"{verdict_str}{conf_part}{reason_part}" 

370 if verbose: 

371 llm_model = event.get("llm_model", "") 

372 llm_latency_ms = event.get("llm_latency_ms", "") 

373 llm_prompt = event.get("llm_prompt", "") 

374 llm_raw_output = event.get("llm_raw_output", "") 

375 if llm_model or llm_prompt: 

376 meta_parts = [] 

377 if llm_model: 

378 meta_parts.append(f"model={llm_model}") 

379 if llm_latency_ms != "": 

380 meta_parts.append(f"latency={llm_latency_ms}ms") 

381 meta_str = " ".join(meta_parts) 

382 extra_lines.append( 

383 colorize(_indent + colorize("LLM Call", "2") + " " + meta_str, "2") 

384 ) 

385 avail_w = width - len(_indent) - len("Prompt: ") - 2 

386 if llm_prompt: 

387 prompt_text = llm_prompt if full else _truncate(llm_prompt, max(avail_w, 40)) 

388 extra_lines.append(colorize(_indent + "Prompt: " + prompt_text, "2")) 

389 if llm_raw_output: 

390 resp_text = ( 

391 llm_raw_output if full else _truncate(llm_raw_output, max(avail_w, 40)) 

392 ) 

393 extra_lines.append(colorize(_indent + "Response: " + resp_text, "2")) 

394 

395 elif event_type == "route": 

396 etype_color = "2" 

397 from_state = event.get("from", "") 

398 to_state = event.get("to", "") 

399 detail = f"{from_state} \u2192 {colorize(to_state, '34')}" 

400 

401 elif event_type == "handoff_detected": 

402 etype_color = "33" 

403 detail = f"state={event.get('state', '')} iter={event.get('iteration', '')}" 

404 

405 else: 

406 details = {k: v for k, v in event.items() if k not in ("event", "ts")} 

407 detail = " ".join(f"{k}={v}" for k, v in details.items()) 

408 

409 etype_str = colorize(etype_padded, etype_color) 

410 main_line = f"{ts_str} {etype_str} {detail}" 

411 if extra_lines: 

412 return "\n".join([main_line] + extra_lines) 

413 return main_line 

414 

415 

416def _format_duration(ms: int) -> str: 

417 """Format milliseconds as a human-readable duration.""" 

418 if ms < 1000: 

419 return f"{ms}ms" 

420 s = ms // 1000 

421 if s < 60: 

422 return f"{s}s" 

423 m, s = divmod(s, 60) 

424 if m < 60: 

425 return f"{m}m{s:02d}s" 

426 h, m = divmod(m, 60) 

427 return f"{h}h{m:02d}m{s:02d}s" 

428 

429 

430def _list_archived_runs(loop_name: str, loops_dir: Path, as_json: bool) -> int: 

431 """List archived runs for a loop.""" 

432 import json as _json 

433 

434 from little_loops.fsm.persistence import HISTORY_DIR, LoopState 

435 

436 history_base = loops_dir / HISTORY_DIR 

437 if not history_base.exists(): 

438 print(f"No history for: {loop_name}") 

439 return 0 

440 

441 # Flat layout: run dirs are <run_id>-<loop_name> directly under .history/ 

442 suffix = f"-{loop_name}" 

443 runs: list[tuple[str, LoopState | None]] = [] 

444 for run_dir in sorted(history_base.iterdir(), key=lambda d: d.name, reverse=True): 

445 if not run_dir.is_dir() or not run_dir.name.endswith(suffix): 

446 continue 

447 run_id = run_dir.name[: -len(suffix)] 

448 state_file = run_dir / "state.json" 

449 state: LoopState | None = None 

450 if state_file.exists(): 

451 try: 

452 data = _json.loads(state_file.read_text()) 

453 state = LoopState.from_dict(data) 

454 except (ValueError, KeyError): 

455 pass 

456 runs.append((run_id, state)) 

457 

458 if not runs: 

459 print(f"No history for: {loop_name}") 

460 return 0 

461 

462 if as_json: 

463 print( 

464 _json.dumps( 

465 [ 

466 { 

467 "run_id": rid, 

468 "status": s.status if s else None, 

469 "started_at": s.started_at if s else None, 

470 "iterations": s.iteration if s else None, 

471 "duration_ms": s.accumulated_ms if s else None, 

472 } 

473 for rid, s in runs 

474 ], 

475 indent=2, 

476 ) 

477 ) 

478 return 0 

479 

480 status_colors = { 

481 "completed": "\033[32m", 

482 "failed": "\033[31m", 

483 "interrupted": "\033[33m", 

484 "awaiting_continuation": "\033[36m", 

485 "timed_out": "\033[33m", 

486 "running": "\033[34m", 

487 } 

488 reset = "\033[0m" 

489 

490 print(f"Archived runs for: {loop_name} ({len(runs)} total)") 

491 print() 

492 

493 for run_id, state in runs: 

494 if state is not None: 

495 color = status_colors.get(state.status, "") 

496 status_str = f"{color}{state.status}{reset}" 

497 duration_str = _format_duration(state.accumulated_ms) if state.accumulated_ms else "?" 

498 started = state.started_at[:19].replace("T", " ") if state.started_at else "?" 

499 iters = f"{state.iteration} iters" 

500 else: 

501 status_str = "unknown" 

502 duration_str = "?" 

503 started = "?" 

504 iters = "?" 

505 print(f" {run_id} {status_str} {started} {iters} {duration_str}") 

506 

507 print() 

508 print(f"To view events: ll-loop history {loop_name} <run-id>") 

509 return 0 

510 

511 

512def cmd_history( 

513 loop_name: str, 

514 run_id: str | None, 

515 args: argparse.Namespace, 

516 loops_dir: Path, 

517) -> int: 

518 """Show loop history. 

519 

520 Without run_id: lists all archived runs with status and duration. 

521 With run_id: shows events for that specific archived run. 

522 """ 

523 tail = getattr(args, "tail", 50) 

524 full = getattr(args, "full", False) 

525 verbose = getattr(args, "verbose", False) or full 

526 as_json = getattr(args, "json", False) 

527 

528 if run_id is None: 

529 return _list_archived_runs(loop_name, loops_dir, as_json) 

530 

531 # Show events for a specific archived run 

532 from little_loops.fsm.persistence import get_archived_events 

533 

534 events = get_archived_events(loop_name, run_id, loops_dir) 

535 

536 if not events: 

537 print(f"No events found for run {run_id} of loop {loop_name}") 

538 return 1 

539 

540 w = terminal_width() 

541 if not verbose: 

542 events = [e for e in events if e.get("event") != "action_output"] 

543 

544 # Apply optional filters (before --tail slice) 

545 event_filter = getattr(args, "event", None) 

546 if event_filter: 

547 events = [e for e in events if e.get("event") == event_filter] 

548 

549 state_filter = getattr(args, "state", None) 

550 if state_filter: 

551 events = [ 

552 e 

553 for e in events 

554 if ( 

555 e.get("state") == state_filter 

556 or e.get("from") == state_filter 

557 or e.get("to") == state_filter 

558 ) 

559 ] 

560 

561 since_str = getattr(args, "since", None) 

562 if since_str: 

563 from datetime import timedelta 

564 

565 from little_loops.text_utils import parse_duration 

566 

567 cutoff = datetime.now() - timedelta(seconds=parse_duration(since_str)) 

568 events = [ 

569 e 

570 for e in events 

571 if datetime.fromisoformat(e["ts"].replace("Z", "+00:00")).replace(tzinfo=None) >= cutoff 

572 ] 

573 

574 if as_json: 

575 print_json(events[-tail:]) 

576 return 0 

577 for event in events[-tail:]: 

578 line = _format_history_event(event, verbose, w, full=full) 

579 if line is not None: 

580 print(line) 

581 

582 return 0 

583 

584 

585def cmd_audit_meta(loop_name: str, args: argparse.Namespace, loops_dir: Path) -> int: 

586 """Summarize meta-eval.jsonl agreement stats from all archived runs of a loop. 

587 

588 Reads meta-eval.jsonl from each archived run, computes: 

589 - Total iterations with llm_structured evaluate events 

590 - Agreement rate (agreed / total) 

591 - Mean diff size (files_changed) per verdict 

592 - Divergence flags: 

593 - agreed=false streak >=3 → "LLM optimistic drift detected" 

594 - agreed=true with files_changed==0 streak >=3 → "Trivial agreement detected" 

595 

596 Returns 0 if no flags triggered, 1 if any threshold crossed. 

597 """ 

598 import json as _json 

599 

600 from little_loops.fsm.persistence import HISTORY_DIR 

601 

602 history_root = loops_dir / HISTORY_DIR 

603 if not history_root.exists(): 

604 print(f"No history for: {loop_name}") 

605 return 0 

606 

607 suffix = f"-{loop_name}" 

608 all_entries: list[dict[str, Any]] = [] 

609 

610 for run_dir in sorted(history_root.iterdir(), key=lambda d: d.name): 

611 if not run_dir.is_dir() or not run_dir.name.endswith(suffix): 

612 continue 

613 meta_eval_file = run_dir / "meta-eval.jsonl" 

614 if not meta_eval_file.exists(): 

615 continue 

616 for line in meta_eval_file.read_text(encoding="utf-8").splitlines(): 

617 line = line.strip() 

618 if line: 

619 try: 

620 all_entries.append(_json.loads(line)) 

621 except _json.JSONDecodeError: 

622 pass 

623 

624 if not all_entries: 

625 print(f"No meta-eval data for: {loop_name}") 

626 return 0 

627 

628 total = len(all_entries) 

629 agreed_count = sum(1 for e in all_entries if e.get("agreed") is True) 

630 agreement_rate = agreed_count / total if total else 0.0 

631 

632 # Mean diff size per verdict 

633 agreed_sizes = [ 

634 e.get("diff_stats", {}).get("files_changed", 0) or 0 

635 for e in all_entries 

636 if e.get("agreed") is True 

637 ] 

638 disagreed_sizes = [ 

639 e.get("diff_stats", {}).get("files_changed", 0) or 0 

640 for e in all_entries 

641 if e.get("agreed") is False 

642 ] 

643 mean_agreed = sum(agreed_sizes) / len(agreed_sizes) if agreed_sizes else 0.0 

644 mean_disagreed = sum(disagreed_sizes) / len(disagreed_sizes) if disagreed_sizes else 0.0 

645 

646 # Detect streaks 

647 flags: list[str] = [] 

648 optimistic_streak = 0 

649 trivial_streak = 0 

650 max_optimistic = 0 

651 max_trivial = 0 

652 

653 for entry in all_entries: 

654 agreed = entry.get("agreed") 

655 files_changed = (entry.get("diff_stats") or {}).get("files_changed", 0) or 0 

656 

657 if agreed is False: 

658 optimistic_streak += 1 

659 trivial_streak = 0 

660 elif agreed is True and files_changed == 0: 

661 trivial_streak += 1 

662 optimistic_streak = 0 

663 else: 

664 optimistic_streak = 0 

665 trivial_streak = 0 

666 

667 max_optimistic = max(max_optimistic, optimistic_streak) 

668 max_trivial = max(max_trivial, trivial_streak) 

669 

670 if max_optimistic >= 3: 

671 flags.append(f"LLM optimistic drift detected (streak={max_optimistic})") 

672 if max_trivial >= 3: 

673 flags.append(f"Trivial agreement detected (streak={max_trivial})") 

674 

675 as_json = getattr(args, "json", False) 

676 if as_json: 

677 result = { 

678 "loop": loop_name, 

679 "total_entries": total, 

680 "agreed_count": agreed_count, 

681 "agreement_rate": round(agreement_rate, 4), 

682 "mean_files_changed_when_agreed": round(mean_agreed, 2), 

683 "mean_files_changed_when_disagreed": round(mean_disagreed, 2), 

684 "max_optimistic_streak": max_optimistic, 

685 "max_trivial_streak": max_trivial, 

686 "flags": flags, 

687 } 

688 print_json(result) 

689 else: 

690 print(f"Meta-eval audit: {loop_name}") 

691 print(f" Total entries: {total}") 

692 print(f" Agreed: {agreed_count}/{total} ({agreement_rate:.0%})") 

693 print(f" Mean Δfiles agreed: {mean_agreed:.1f}") 

694 print(f" Mean Δfiles disagreed: {mean_disagreed:.1f}") 

695 if flags: 

696 print() 

697 for flag in flags: 

698 print(f"{flag}") 

699 else: 

700 print(" No divergence flags.") 

701 

702 if as_json: 

703 return 0 # let caller inspect JSON for flags; non-zero kills provider.runCli 

704 return 1 if flags else 0 

705 

706 

707def cmd_diagnose_evaluators(loop_name: str, args: argparse.Namespace, loops_dir: Path) -> int: 

708 """Detect non-discriminating evaluators from run history. 

709 

710 Walks .loops/.history/*-{loop_name}/events.jsonl, computes per-state 

711 Bernoulli variance p*(1-p) on verdicts, flags states below threshold 

712 with pattern-matched recommendations. 

713 

714 Returns 0 if no states flagged, 1 if any low-variance evaluators found. 

715 """ 

716 from little_loops.analytics.variance import compute_evaluator_variance 

717 

718 threshold = getattr(args, "threshold", 0.05) 

719 min_runs = getattr(args, "min_runs", 10) 

720 as_json = getattr(args, "json", False) 

721 

722 report = compute_evaluator_variance(loop_name, loops_dir, threshold, min_runs) 

723 

724 if report is None: 

725 if not (loops_dir / ".history").exists(): 

726 print(f"No history for: {loop_name}") 

727 elif len(list((loops_dir / ".history").glob(f"*-{loop_name}"))) < min_runs: 

728 runs_found = len(list((loops_dir / ".history").glob(f"*-{loop_name}"))) 

729 print( 

730 f"Insufficient history for: {loop_name} " 

731 f"(found {runs_found} run(s), need {min_runs})" 

732 ) 

733 else: 

734 print(f"No evaluate events for: {loop_name}") 

735 return 0 

736 

737 flagged = [s for s in report.states if s.variance < threshold] 

738 

739 if as_json: 

740 print_json(report.to_dict()) 

741 else: 

742 print(f"Evaluator Variance Report (n={report.total_runs} runs)") 

743 if not report.states: 

744 print(" No evaluator states found in run history.") 

745 for state in report.states: 

746 disc_label = "✓ discriminating" if state.variance >= threshold else "⚠ low variance" 

747 print( 

748 f" {state.state:20s} pass_rate={state.pass_rate:.2f} " 

749 f"variance={state.variance:.2f} {disc_label}" 

750 ) 

751 if state.recommendation: 

752 for line in state.recommendation.split("\n"): 

753 print(f" {line.strip()}") 

754 

755 if as_json: 

756 return 0 

757 return 1 if flagged else 0 

758 

759 

760def cmd_promote_baseline(loop_name: str, args: argparse.Namespace, loops_dir: Path) -> int: 

761 """Promote the latest run's action output as the new comparator baseline. 

762 

763 Reads action_output events from the most recent .history entry and writes 

764 the concatenated output to .loops/baselines/<loop>/output.txt. 

765 """ 

766 import json as _json 

767 

768 history_base = loops_dir / ".history" 

769 if not history_base.exists(): 

770 print(f"No history for: {loop_name}") 

771 return 1 

772 

773 suffix = f"-{loop_name}" 

774 matched = sorted( 

775 [d for d in history_base.iterdir() if d.is_dir() and d.name.endswith(suffix)], 

776 key=lambda d: d.name, 

777 reverse=True, 

778 ) 

779 if not matched: 

780 print(f"No history for: {loop_name}") 

781 return 1 

782 

783 latest = matched[0] 

784 events_file = latest / "events.jsonl" 

785 if not events_file.exists(): 

786 print(f"No events.jsonl in latest run: {latest.name}") 

787 return 1 

788 

789 lines = [] 

790 with open(events_file) as f: 

791 for raw in f: 

792 raw = raw.strip() 

793 if not raw: 

794 continue 

795 try: 

796 event = _json.loads(raw) 

797 except _json.JSONDecodeError: 

798 continue 

799 if event.get("type") == "action_output": 

800 line = event.get("line", "") 

801 if line: 

802 lines.append(line) 

803 

804 if not lines: 

805 print(f"No action_output events in latest run: {latest.name}") 

806 return 1 

807 

808 target = Path(loops_dir) / "baselines" / loop_name / "output.txt" 

809 target.parent.mkdir(parents=True, exist_ok=True) 

810 target.write_text("\n".join(lines)) 

811 print(f"Promoted baseline for {loop_name}: {target}") 

812 return 0 

813 

814 

815# --------------------------------------------------------------------------- 

816# FSM diagram renderer — delegated to layout module (re-exported above) 

817# --------------------------------------------------------------------------- 

818 

819 

820# --------------------------------------------------------------------------- 

821# State overview table 

822# --------------------------------------------------------------------------- 

823 

824 

825def _compact_transitions(state: StateConfig) -> str: 

826 """Return a compact transition string for the overview table.""" 

827 raw: list[tuple[str, str]] = [] 

828 for label, target in [ 

829 ("yes", state.on_yes), 

830 ("no", state.on_no), 

831 ("error", state.on_error), 

832 ("partial", state.on_partial), 

833 ("next", state.next), 

834 ]: 

835 if target: 

836 raw.append((label, target)) 

837 if state.route: 

838 for verdict, target in state.route.routes.items(): 

839 raw.append((verdict, target)) 

840 if state.route.default: 

841 raw.append(("_", state.route.default)) 

842 if not raw: 

843 return "\u2014" 

844 # Group by target, preserving first-seen order 

845 seen: list[str] = [] 

846 by_target: dict[str, list[str]] = {} 

847 for label, target in raw: 

848 if target not in by_target: 

849 seen.append(target) 

850 by_target[target] = [] 

851 by_target[target].append(label) 

852 return ", ".join(f"{'/'.join(by_target[t])}\u2192{t}" for t in seen) 

853 

854 

855def _print_state_overview_table(fsm: FSMLoop) -> None: 

856 """Print a compact summary table of all states.""" 

857 rows: list[tuple[str, str, str, str]] = [] 

858 for name, state in fsm.states.items(): 

859 # State name column 

860 state_col = f"\u2192 {name}" if name == fsm.initial else f" {name}" 

861 

862 # Type column 

863 if state.terminal: 

864 type_col = "\u2014" 

865 elif state.action_type: 

866 type_col = state.action_type 

867 elif state.action: 

868 type_col = "shell" 

869 else: 

870 type_col = "\u2014" 

871 

872 # Action preview column 

873 if state.terminal: 

874 action_col = "(terminal)" 

875 elif state.action: 

876 src_lines = [ln.rstrip() for ln in state.action.strip().splitlines() if ln.rstrip()] 

877 action_col = src_lines[0] if src_lines else "\u2014" 

878 else: 

879 action_col = "\u2014" 

880 

881 # Transitions column 

882 trans_col = _compact_transitions(state) 

883 rows.append((state_col, type_col, action_col, trans_col)) 

884 

885 if not rows: 

886 return 

887 

888 tw = terminal_width() 

889 headers = ("State", "Type", "Action Preview", "Transitions") 

890 col0_w = max(len(headers[0]), max(len(r[0]) for r in rows)) 

891 col1_w = max(len(headers[1]), max(len(r[1]) for r in rows)) 

892 # Remaining width split between action preview and transitions 

893 fixed = col0_w + col1_w + 10 # margins + separators 

894 remaining = max(20, tw - fixed) 

895 col2_w = min(50, max(len(headers[2]), max(len(r[2]) for r in rows)), remaining * 3 // 5) 

896 col2_w = max(10, col2_w) 

897 col3_w = max(10, remaining - col2_w) 

898 

899 print(f" {headers[0]:<{col0_w}} {headers[1]:<{col1_w}} {headers[2]:<{col2_w}} {headers[3]}") 

900 dash = "\u2500" 

901 print(f" {dash * col0_w} {dash * col1_w} {dash * col2_w} {dash * col3_w}") 

902 for state_col, type_col, action_col, trans_col in rows: 

903 if len(action_col) > col2_w: 

904 action_col = action_col[: col2_w - 1] + "\u2026" 

905 if len(trans_col) > col3_w: 

906 trans_col = trans_col[: col3_w - 1] + "\u2026" 

907 colored_type = colorize(type_col, "2") if type_col == "\u2014" else type_col 

908 print( 

909 f" {state_col:<{col0_w}} {colored_type:<{col1_w}} " 

910 f"{action_col:<{col2_w}} {trans_col}" 

911 ) 

912 

913 

914# --------------------------------------------------------------------------- 

915# cmd_show 

916# --------------------------------------------------------------------------- 

917 

918_EVALUATE_TYPE_DISPLAY: dict[str, str] = { 

919 "llm": "LLM", 

920 "llm_structured": "LLM (structured)", 

921 "exit_code": "exit code", 

922 "output_numeric": "numeric", 

923 "output_contains": "contains", 

924 "output_json": "JSON", 

925 "convergence": "convergence", 

926 "diff_stall": "diff stall", 

927 "action_stall": "action stall", 

928 "comparator": "blind comparator", 

929} 

930 

931 

932def _humanize_evaluate_type(ev_type: str) -> str: 

933 return _EVALUATE_TYPE_DISPLAY.get(ev_type, ev_type) 

934 

935 

936def cmd_show( 

937 loop_name: str, 

938 args: argparse.Namespace, 

939 loops_dir: Path, 

940 logger: Logger, 

941) -> int: 

942 """Show loop details and structure.""" 

943 try: 

944 path = resolve_loop_path(loop_name, loops_dir) 

945 fsm, spec = load_loop_with_spec(loop_name, loops_dir, logger) 

946 except FileNotFoundError as e: 

947 logger.error(str(e)) 

948 return 1 

949 except ValueError as e: 

950 logger.error(f"Invalid loop: {e}") 

951 return 1 

952 

953 if getattr(args, "json", False) and getattr(args, "show_diagrams", None) is not None: 

954 logger.error("--json and --show-diagrams are mutually exclusive") 

955 return 1 

956 

957 if getattr(args, "json", False): 

958 data = fsm.to_dict() 

959 if getattr(args, "resolved", False): 

960 for state in data.get("states", {}).values(): 

961 if "loop" in state: 

962 try: 

963 child_path = resolve_loop_path(state["loop"], loops_dir) 

964 child_fsm, _ = load_and_validate(child_path) 

965 state["_subloop"] = child_fsm.to_dict().get("states", {}) 

966 except (FileNotFoundError, ValueError): 

967 pass 

968 print_json(data) 

969 return 0 

970 

971 tw = terminal_width() 

972 

973 # Compute stats for header 

974 n_states = len(fsm.states) 

975 n_transitions = sum( 

976 bool(s.on_yes) 

977 + bool(s.on_no) 

978 + bool(s.on_error) 

979 + bool(s.on_partial) 

980 + bool(s.next) 

981 + bool(s.on_maintain) 

982 + (len(s.route.routes) + bool(s.route.default) if s.route else 0) 

983 for s in fsm.states.values() 

984 ) 

985 

986 # --- Compact metadata header --- 

987 # Line 1: ── name ───────── N states · M transitions ── 

988 stats_parts: list[str] = [] 

989 stats_parts.append(f"{n_states} states") 

990 stats_parts.append(f"{n_transitions} transitions") 

991 stats_str = " \u00b7 ".join(stats_parts) 

992 

993 header_left = f"\u2500\u2500 {loop_name} " 

994 header_right = f" {stats_str} \u2500\u2500" 

995 dashes = "\u2500" * max(0, tw - len(header_left) - len(header_right)) 

996 print(f"{header_left}{dashes}{header_right}") 

997 

998 # Line 2: source · max: N iter · handoff: X [· optional fields] 

999 config_parts: list[str] = [str(path), f"max: {fsm.max_iterations} iter"] 

1000 config_parts.append(f"handoff: {fsm.on_handoff}") 

1001 if fsm.on_max_iterations is not None: 

1002 config_parts.append(f"on_max_iterations: {fsm.on_max_iterations}") 

1003 if fsm.timeout: 

1004 config_parts.append(f"timeout: {fsm.timeout}s") 

1005 if fsm.backoff: 

1006 config_parts.append(f"backoff: {fsm.backoff}s") 

1007 if fsm.maintain: 

1008 config_parts.append("maintain: yes") 

1009 if fsm.context: 

1010 config_parts.append(f"context: {', '.join(fsm.context.keys())}") 

1011 if fsm.scope: 

1012 config_parts.append(f"scope: {', '.join(fsm.scope)}") 

1013 llm = fsm.llm 

1014 llm_parts = [] 

1015 if llm.model != "sonnet": 

1016 llm_parts.append(f"model={llm.model}") 

1017 if llm.max_tokens != 256: 

1018 llm_parts.append(f"max_tokens={llm.max_tokens}") 

1019 if llm.timeout != 30: 

1020 llm_parts.append(f"timeout={llm.timeout}s") 

1021 if llm_parts: 

1022 config_parts.append(f"llm: {', '.join(llm_parts)}") 

1023 if fsm.config is not None: 

1024 cfg_parts = [] 

1025 if fsm.config.handoff_threshold is not None: 

1026 cfg_parts.append(f"handoff_threshold={fsm.config.handoff_threshold}") 

1027 if fsm.config.readiness_threshold is not None: 

1028 cfg_parts.append(f"readiness_threshold={fsm.config.readiness_threshold}") 

1029 if fsm.config.outcome_threshold is not None: 

1030 cfg_parts.append(f"outcome_threshold={fsm.config.outcome_threshold}") 

1031 if fsm.config.max_continuations is not None: 

1032 cfg_parts.append(f"max_continuations={fsm.config.max_continuations}") 

1033 if cfg_parts: 

1034 config_parts.append(f"config: {', '.join(cfg_parts)}") 

1035 imports = spec.get("import", []) 

1036 if imports: 

1037 config_parts.append(f"imports: {', '.join(imports)}") 

1038 print(" " + " \u00b7 ".join(config_parts)) 

1039 

1040 # --- Description --- 

1041 description = spec.get("description", "").strip() 

1042 if description: 

1043 print() 

1044 print("Description:") 

1045 for line in description.splitlines(): 

1046 print(f" {line}") 

1047 

1048 # --- ASCII FSM Diagram --- 

1049 verbose = getattr(args, "verbose", False) 

1050 from pathlib import Path 

1051 

1052 from little_loops.config import BRConfig 

1053 

1054 badges = BRConfig(Path.cwd()).loops.glyphs.to_dict() 

1055 facets = resolve_facets(args) 

1056 print() 

1057 print("Diagram:") 

1058 if facets is None: 

1059 diagram = _render_fsm_diagram(fsm, verbose=verbose, badges=badges) 

1060 else: 

1061 diagram = _render_fsm_diagram( 

1062 fsm, 

1063 badges=badges, 

1064 mode=facets.scope, 

1065 suppress_labels=not facets.edge_labels, 

1066 title_only=facets.state_detail == "title", 

1067 ) 

1068 if diagram: 

1069 print(diagram) 

1070 

1071 # --- State overview table --- 

1072 print() 

1073 _print_state_overview_table(fsm) 

1074 

1075 # --- States & Transitions (verbose only) --- 

1076 if verbose: 

1077 print() 

1078 print("States:") 

1079 first_state = True 

1080 for name, state in fsm.states.items(): 

1081 if not first_state: 

1082 print() 

1083 first_state = False 

1084 

1085 # Improved state section header: ── name ──── MARKERS · type ── 

1086 right_parts = [] 

1087 if name == fsm.initial: 

1088 right_parts.append("INITIAL") 

1089 if state.terminal: 

1090 right_parts.append("TERMINAL") 

1091 if state.action_type: 

1092 right_parts.append(state.action_type) 

1093 right_info = " \u00b7 ".join(right_parts) 

1094 inner_left = f"\u2500\u2500 {name} " 

1095 inner_right = f" {right_info} \u2500\u2500" if right_info else " \u2500\u2500" 

1096 fill = "\u2500" * max(0, tw - 2 - len(inner_left) - len(inner_right)) 

1097 print(f" {inner_left}{fill}{inner_right}") 

1098 

1099 if state.action: 

1100 if verbose: 

1101 indented = "\n ".join(state.action.strip().splitlines()) 

1102 print(f" action:\n {indented}") 

1103 elif state.action_type == "prompt": 

1104 lines_act = state.action.strip().splitlines() 

1105 preview = "\n ".join(lines_act[:3]) 

1106 if len(lines_act) > 3 or len(state.action) > 200: 

1107 preview += " ..." 

1108 print(f" action:\n {preview}") 

1109 else: # shell, slash_command, or None 

1110 action_display = ( 

1111 state.action[:70] + "..." if len(state.action) > 70 else state.action 

1112 ) 

1113 print(f" action: {action_display}") 

1114 if state.evaluate: 

1115 ev = state.evaluate 

1116 print(f" evaluate: {_humanize_evaluate_type(ev.type)}") 

1117 if ev.prompt: 

1118 if verbose: 

1119 print(" prompt:") 

1120 for line in ev.prompt.strip().splitlines(): 

1121 print(f" \u2502 {line}") 

1122 else: 

1123 ev_lines = ev.prompt.strip().splitlines() 

1124 preview = ev_lines[0][:100] + ( 

1125 " ..." if len(ev_lines) > 1 or len(ev_lines[0]) > 100 else "" 

1126 ) 

1127 print(f" prompt: {preview}") 

1128 if ev.min_confidence != 0.5: 

1129 print(f" min_confidence: {ev.min_confidence}") 

1130 if ev.operator: 

1131 print(f" operator: {ev.operator} {ev.target}") 

1132 if ev.pattern: 

1133 print(f" pattern: {ev.pattern}") 

1134 if state.capture: 

1135 print(f" capture: {state.capture}") 

1136 if state.timeout: 

1137 print(f" timeout: {state.timeout}s") 

1138 # Collect (label, target) pairs 

1139 raw_transitions: list[tuple[str, str]] = [] 

1140 for label, target in [ 

1141 ("yes", state.on_yes), 

1142 ("no", state.on_no), 

1143 ("error", state.on_error), 

1144 ("partial", state.on_partial), 

1145 ("next", state.next), 

1146 ("maintain", state.on_maintain), 

1147 ]: 

1148 if target: 

1149 raw_transitions.append((label, target)) 

1150 if state.route: 

1151 for verdict, target in state.route.routes.items(): 

1152 raw_transitions.append((verdict, target)) 

1153 if state.route.default: 

1154 raw_transitions.append(("_", state.route.default)) 

1155 # Group by target, preserving first-seen order 

1156 target_labels: dict[str, list[str]] = {} 

1157 seen_targets: list[str] = [] 

1158 for label, target in raw_transitions: 

1159 if target not in target_labels: 

1160 target_labels[target] = [] 

1161 seen_targets.append(target) 

1162 target_labels[target].append(label) 

1163 transitions = [ 

1164 f"{_colorize_label('/'.join(target_labels[t]))} \u2500\u2500\u2192 {t}" 

1165 for t in seen_targets 

1166 ] 

1167 if transitions: 

1168 print(" Transitions:") 

1169 for t in transitions: 

1170 print(f" {t}") 

1171 

1172 # --- Commands --- 

1173 print() 

1174 print("Commands:") 

1175 if fsm.commands: 

1176 cmds = [(e.cmd, e.comment) for e in fsm.commands] 

1177 else: 

1178 cmds = [ 

1179 (f"ll-loop run {loop_name}", "run"), 

1180 (f"ll-loop test {loop_name}", "single test iteration"), 

1181 (f"ll-loop stop {loop_name}", "stop a running loop"), 

1182 (f"ll-loop status {loop_name}", "check if running"), 

1183 (f"ll-loop history {loop_name}", "execution history"), 

1184 ] 

1185 col_width = max(len(c) for c, _ in cmds) + 2 

1186 for cmd, comment in cmds: 

1187 print(f" {cmd:<{col_width}} # {comment}") 

1188 

1189 return 0 

1190 

1191 

1192def cmd_fragments( 

1193 lib_path: str, 

1194 args: argparse.Namespace, 

1195 loops_dir: Path, 

1196 logger: Logger, 

1197) -> int: 

1198 """List fragments in a library file with their descriptions. 

1199 

1200 Resolves the library path relative to loops_dir or the built-in loops directory, 

1201 then prints a table of fragment names and their description fields. 

1202 """ 

1203 import yaml 

1204 

1205 # Resolve path: absolute/direct → loops_dir-relative → builtin 

1206 p = Path(lib_path) 

1207 if not p.exists(): 

1208 candidate = loops_dir / lib_path 

1209 if candidate.exists(): 

1210 p = candidate 

1211 else: 

1212 builtin_candidate = get_builtin_loops_dir() / lib_path 

1213 if builtin_candidate.exists(): 

1214 p = builtin_candidate 

1215 else: 

1216 logger.error(f"Fragment library not found: {lib_path}") 

1217 return 1 

1218 

1219 try: 

1220 with open(p) as f: 

1221 data = yaml.safe_load(f) or {} 

1222 except Exception as e: 

1223 logger.error(f"Failed to load library: {e}") 

1224 return 1 

1225 

1226 fragments: dict[str, Any] = data.get("fragments", {}) 

1227 if not fragments: 

1228 print(f"No fragments defined in: {p}") 

1229 return 0 

1230 

1231 tw = terminal_width() 

1232 print(colorize(f"Fragments in {p.name} ({len(fragments)}):", "1")) 

1233 print() 

1234 

1235 max_name_len = max(len(name) for name in fragments) 

1236 name_col_w = max(max_name_len, 8) 

1237 desc_col_w = max(20, tw - name_col_w - 6) 

1238 

1239 header_name = "Fragment".ljust(name_col_w) 

1240 print(f" {colorize(header_name, '1')} Description") 

1241 print(f" {'─' * name_col_w} {'─' * desc_col_w}") 

1242 

1243 for name, frag in fragments.items(): 

1244 raw_desc = frag.get("description", "") if isinstance(frag, dict) else "" 

1245 raw_desc = raw_desc.strip() 

1246 first_line = raw_desc.splitlines()[0] if raw_desc else "" 

1247 if first_line and len(first_line) > desc_col_w: 

1248 first_line = first_line[: desc_col_w - 1] + "\u2026" 

1249 desc_str = first_line if first_line else colorize("(no description)", "2") 

1250 padded_name = name.ljust(name_col_w) 

1251 print(f" {colorize(padded_name, '36;1')} {desc_str}") 

1252 

1253 return 0