"""Tests for the ranked fuzzy scorer used by the searchable curses pickers.""" from hermes_cli.curses_ui import ( _SearchState, _filter_indices, _fuzzy_score, _handle_active_search_key, _is_boundary, _token_score, ) class _FakeCurses: KEY_BACKSPACE = 263 KEY_DOWN = 258 KEY_ENTER = 343 def test_fuzzy_score_matches_subsequence(): assert _fuzzy_score("gpt-4o", "g4o") is not None assert _fuzzy_score("gpt-4o", "4o") is not None assert _fuzzy_score("gpt-4o", "o4g") is None assert _fuzzy_score("gpt-4o", "xyz") is None def test_scorer_matches_typescript_reference(): """Score parity with ui-tui/web fuzzy.ts. These exact values are produced by the TS fuzzyScoreMulti for the same inputs (verified via a cross-language harness); keep the Python port byte-identical so all three surfaces rank consistently. If you change the scoring constants, update the TS copies too. """ cases = { ("gpt-4o", "g4o"): 15.94, ("gpt-4o", "gpt"): 28.94, ("claude-sonnet-4", "sonnet"): 33.85, ("claude-sonnet-4", "clad snnt"): 30.70, ("GptO", "gpto"): 57.96, # camelCase boundary on the original-case 'O' } for (label, query), expected in cases.items(): score = _fuzzy_score(label, query) assert score is not None assert round(score, 2) == expected, f"{label!r}/{query!r}: {score} != {expected}" def test_is_boundary_camelcase_and_separators(): assert _is_boundary("gpt-4o", 0) is True # start assert _is_boundary("gpt-4o", 4) is True # after '-' assert _is_boundary("gpt-4o", 2) is False # mid-word assert _is_boundary("GptO", 3) is True # lower->upper transition def test_token_score_takes_orig_and_lower(): # Exact match (lower == token) earns the +20 bonus over a prefix. exact = _token_score("sonnet", "sonnet", "sonnet") prefix = _token_score("sonnet-x", "sonnet-x", "sonnet") assert exact is not None and prefix is not None assert exact > prefix def test_esc_clears_query_and_signals_changed(): # Esc during active search clears the filter (restores full list) and # signals `changed` so the driver resets scroll/cursor. search = _SearchState(active=True, query="gpt") handled, confirm, changed = _handle_active_search_key(_FakeCurses, 27, search) assert (handled, confirm, changed) == (True, False, True) assert search.active is False assert search.query == "" # Esc with no query: still stops search, but nothing changed. search2 = _SearchState(active=True, query="") assert _handle_active_search_key(_FakeCurses, 27, search2) == (True, False, False) def test_high_byte_keys_ignored(): # Bytes 128-255 must NOT append Latin-1 mojibake to the query. search = _SearchState(active=True, query="ab") handled, _, changed = _handle_active_search_key(_FakeCurses, 200, search) assert (handled, changed) == (False, False) assert search.query == "ab" def test_fuzzy_score_empty_query_is_zero(): assert _fuzzy_score("anything", "") == 0 assert _fuzzy_score("anything", " ") == 0 def test_fuzzy_score_prefix_beats_scattered(): prefix = _fuzzy_score("gpt-4o-mini", "gpt") scattered = _fuzzy_score("a-g-p-t", "gpt") assert prefix is not None and scattered is not None assert prefix > scattered def test_fuzzy_score_exact_and_shorter_rank_higher(): exact = _fuzzy_score("sonnet", "sonnet") longer = _fuzzy_score("sonnet-extended", "sonnet") assert exact is not None and longer is not None # Same prefix match, but the shorter id wins on the length tiebreak. assert exact > longer def test_filter_indices_ranks_best_first(): models = ["gpt-4o", "gpt-4o-mini", "claude-sonnet-4", "claude-haiku", "o1-preview"] # g4o matches both gpt-4o variants; the shorter exact-ish one ranks first. ranked = _filter_indices(models, "g4o") assert [models[i] for i in ranked] == ["gpt-4o", "gpt-4o-mini"] # son4 surfaces the sonnet model. assert [models[i] for i in _filter_indices(models, "son4")] == ["claude-sonnet-4"] # Multi-token AND. assert [models[i] for i in _filter_indices(models, "clad snnt")] == ["claude-sonnet-4"] # No match drops everything. assert _filter_indices(models, "zzz") == [] def test_filter_indices_blank_query_preserves_order(): models = ["b", "a", "c"] assert _filter_indices(models, "") == [0, 1, 2] assert _filter_indices(models, " ") == [0, 1, 2] def test_filter_indices_stable_for_equal_scores(): # Identical labels score identically; original order is the tiebreak. items = ["ab", "ab", "ab"] assert _filter_indices(items, "ab") == [0, 1, 2]