editor: Improve fuzzy match bucket logic for code completions (#29442)
Add new test and improve fuzzy match bucket logic which results into far better balance between LSP and fuzzy search. Before: <img width="500" alt="before" src="https://github.com/user-attachments/assets/3e8900a6-c0ff-4f37-b88e-b0e3783b7e9a" /> After: <img width="500" alt="after" src="https://github.com/user-attachments/assets/738c074c-d446-4697-aac6-9814362e88db" /> Release Notes: - N/A
This commit is contained in:
Smit Barmase
GitHub
parent
8b910e1cd9
commit
3961d87ae0
2 changed files with 160 additions and 7 deletions
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@ -1006,3 +1006,152 @@ fn test_sort_matches_for_snippets(_cx: &mut TestAppContext) {
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"Match order not expected"
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);
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}
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#[gpui::test]
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fn test_sort_matches_for_exact_match(_cx: &mut TestAppContext) {
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// Case 1: "set_text"
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let query: Option<&str> = Some("set_text");
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let mut matches: Vec<SortableMatch<'_>> = vec![
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SortableMatch {
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string_match: StringMatch {
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candidate_id: 0,
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score: 1.0,
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positions: vec![],
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string: "set_text".to_string(),
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},
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is_snippet: false,
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sort_text: Some("7fffffff"),
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sort_key: (3, "set_text"),
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},
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SortableMatch {
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string_match: StringMatch {
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candidate_id: 0,
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score: 0.32000000000000006,
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positions: vec![],
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string: "set_placeholder_text".to_string(),
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},
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is_snippet: false,
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sort_text: Some("7fffffff"),
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sort_key: (3, "set_placeholder_text"),
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},
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SortableMatch {
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string_match: StringMatch {
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candidate_id: 0,
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score: 0.32,
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positions: vec![],
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string: "set_text_style_refinement".to_string(),
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},
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is_snippet: false,
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sort_text: Some("7fffffff"),
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sort_key: (3, "set_text_style_refinement"),
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},
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SortableMatch {
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string_match: StringMatch {
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candidate_id: 0,
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score: 0.16666666666666666,
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positions: vec![],
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string: "set_context_menu_options".to_string(),
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},
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is_snippet: false,
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sort_text: Some("7fffffff"),
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sort_key: (3, "set_context_menu_options"),
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},
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SortableMatch {
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string_match: StringMatch {
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candidate_id: 0,
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score: 0.08695652173913043,
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positions: vec![],
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string: "select_to_next_word_end".to_string(),
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},
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is_snippet: false,
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sort_text: Some("7fffffff"),
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sort_key: (3, "select_to_next_word_end"),
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},
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SortableMatch {
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string_match: StringMatch {
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candidate_id: 0,
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score: 0.07692307692307693,
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positions: vec![],
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string: "select_to_next_subword_end".to_string(),
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},
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is_snippet: false,
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sort_text: Some("7fffffff"),
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sort_key: (3, "select_to_next_subword_end"),
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},
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SortableMatch {
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string_match: StringMatch {
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candidate_id: 0,
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score: 0.06956521739130435,
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positions: vec![],
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string: "set_custom_context_menu".to_string(),
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},
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is_snippet: false,
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sort_text: Some("7fffffff"),
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sort_key: (3, "set_custom_context_menu"),
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},
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SortableMatch {
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string_match: StringMatch {
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candidate_id: 0,
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score: 0.06,
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positions: vec![],
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string: "select_to_end_of_excerpt".to_string(),
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},
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is_snippet: false,
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sort_text: Some("7fffffff"),
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sort_key: (3, "select_to_end_of_excerpt"),
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},
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SortableMatch {
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string_match: StringMatch {
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candidate_id: 0,
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score: 0.055384615384615386,
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positions: vec![],
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string: "select_to_start_of_excerpt".to_string(),
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},
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is_snippet: false,
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sort_text: Some("7fffffff"),
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sort_key: (3, "select_to_start_of_excerpt"),
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},
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SortableMatch {
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string_match: StringMatch {
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candidate_id: 0,
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score: 0.0464516129032258,
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positions: vec![],
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string: "select_to_start_of_next_excerpt".to_string(),
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},
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is_snippet: false,
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sort_text: Some("7fffffff"),
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sort_key: (3, "select_to_start_of_next_excerpt"),
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},
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SortableMatch {
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string_match: StringMatch {
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candidate_id: 0,
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score: 0.04363636363636363,
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positions: vec![],
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string: "select_to_end_of_previous_excerpt".to_string(),
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},
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is_snippet: false,
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sort_text: Some("7fffffff"),
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sort_key: (3, "select_to_end_of_previous_excerpt"),
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},
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];
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CompletionsMenu::sort_matches(&mut matches, query, SnippetSortOrder::Top);
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assert_eq!(
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matches
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.iter()
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.map(|m| m.string_match.string.as_str())
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.collect::<Vec<&str>>(),
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vec![
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"set_text",
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"set_context_menu_options",
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"set_placeholder_text",
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"set_text_style_refinement",
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"select_to_end_of_excerpt",
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"select_to_end_of_previous_excerpt",
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"select_to_next_subword_end",
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"select_to_next_word_end",
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"select_to_start_of_excerpt",
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"select_to_start_of_next_excerpt",
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"set_custom_context_menu"
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]
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);
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}
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@ -671,7 +671,7 @@ impl CompletionsMenu {
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#[derive(Debug, PartialEq, Eq, PartialOrd, Ord)]
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enum MatchTier<'a> {
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WordStartMatch {
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sort_score_int: Reverse<i32>,
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sort_bucket: Reverse<i32>,
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sort_snippet: Reverse<i32>,
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sort_text: Option<&'a str>,
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sort_key: (usize, &'a str),
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@ -684,11 +684,9 @@ impl CompletionsMenu {
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// Our goal here is to intelligently sort completion suggestions. We want to
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// balance the raw fuzzy match score with hints from the language server
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//
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// We first primary sort using fuzzy score by putting matches into two buckets
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// strong one and weak one. Among these buckets matches are then compared by
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// We first primary sort using fuzzy score by putting matches into multiple
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// buckets. Among these buckets matches are then compared by
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// various criteria like snippet, LSP hints, kind, label text etc.
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//
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const FUZZY_THRESHOLD: f64 = 0.1317;
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let query_start_lower = query
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.and_then(|q| q.chars().next())
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@ -712,14 +710,20 @@ impl CompletionsMenu {
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let sort_score = Reverse(OrderedFloat(score));
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MatchTier::OtherMatch { sort_score }
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} else {
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let sort_score_int = Reverse(if score >= FUZZY_THRESHOLD { 1 } else { 0 });
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// Convert fuzzy match score (0.0-1.0) to a priority bucket (0-3)
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let sort_bucket = Reverse(match (score * 10.0).floor() as i32 {
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s if s >= 7 => 3,
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s if s >= 1 => 2,
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s if s > 0 => 1,
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_ => 0,
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});
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let sort_snippet = match snippet_sort_order {
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SnippetSortOrder::Top => Reverse(if mat.is_snippet { 1 } else { 0 }),
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SnippetSortOrder::Bottom => Reverse(if mat.is_snippet { 0 } else { 1 }),
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SnippetSortOrder::Inline => Reverse(0),
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};
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MatchTier::WordStartMatch {
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sort_score_int,
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sort_bucket,
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sort_snippet,
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sort_text: mat.sort_text,
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sort_key: mat.sort_key,
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