fix(autocomplete): reduce tag search overhead (#895)

py/routes/handlers/misc_handlers.py

@@ -13,6 +13,7 @@ import contextlib
 import io
 import json
 import logging
+import time
 import os
 import platform
 import re
@@ -2433,6 +2434,7 @@ class CustomWordsHandler:
                       even without category filtering.
         """
         try:
+            started_at = time.perf_counter()
             search_term = request.query.get("search", "")
             limit = int(request.query.get("limit", "20"))
             offset = max(0, int(request.query.get("offset", "0")))
@@ -2444,6 +2446,16 @@ class CustomWordsHandler:
             if category_param:
                 categories = self._parse_category_param(category_param)
 
+            logger.info(
+                "LM custom words request search=%r category_param=%r categories=%s limit=%s offset=%s enriched=%s",
+                search_term,
+                category_param,
+                categories,
+                limit,
+                offset,
+                enriched_param,
+            )
+
             results = self._service.search_words(
                 search_term,
                 limit,
@@ -2452,6 +2464,14 @@ class CustomWordsHandler:
                 enriched=enriched_param,
             )
 
+            elapsed_ms = (time.perf_counter() - started_at) * 1000
+            logger.info(
+                "LM custom words response search=%r result_count=%s elapsed_ms=%.2f",
+                search_term,
+                len(results),
+                elapsed_ms,
+            )
+
             return web.json_response({"success": True, "words": results})
         except Exception as exc:
             logger.error("Error searching custom words: %s", exc, exc_info=True)

py/services/custom_words_service.py

@@ -7,11 +7,13 @@ with category filtering and enriched results including post counts.
 from __future__ import annotations
 
 import logging
+import re
 from typing import List, Dict, Any, Optional
 
 logger = logging.getLogger(__name__)
 
 
+_EMBEDDED_COMMAND_PATTERN = re.compile(r"\s/\w")
 class CustomWordsService:
     """Service for autocomplete via TagFTSIndex.
 
@@ -77,10 +79,47 @@ class CustomWordsService:
         Returns:
             List of dicts with tag_name, category, and post_count.
         """
+        normalized_search = search_term.strip()
+        if not normalized_search:
+            return []
+
+        # Prompt widgets should only send the active token, but guard against
+        # accidental full-prompt queries reaching the FTS path.
+        if (
+            "__" in normalized_search
+            or "," in normalized_search
+            or ">" in normalized_search
+            or "\n" in normalized_search
+            or "\r" in normalized_search
+            or _EMBEDDED_COMMAND_PATTERN.search(normalized_search)
+        ):
+            logger.debug("Skipping prompt-like custom words query: %s", normalized_search)
+            return []
+
+        logger.info(
+            "LM custom words service start search=%r categories=%s limit=%s offset=%s enriched=%s",
+            normalized_search,
+            categories,
+            limit,
+            offset,
+            enriched,
+        )
+
         tag_index = self._get_tag_index()
         if tag_index is not None:
+            logger.info(
+                "LM custom words service tag_index ready=%s indexing=%s",
+                getattr(tag_index, "is_ready", lambda: "unknown")(),
+                getattr(tag_index, "is_indexing", lambda: "unknown")(),
+            )
+
             results = tag_index.search(
-                search_term, categories=categories, limit=limit, offset=offset
+                normalized_search, categories=categories, limit=limit, offset=offset
+            )
+            logger.info(
+                "LM custom words service done search=%r result_count=%s",
+                normalized_search,
+                len(results),
             )
             return results
 

py/services/tag_fts_index.py

@@ -450,9 +450,9 @@ class TagFTSIndex:
         the tag_name, the result will include a "matched_alias" field.
 
         Ranking is based on a combination of:
-        1. FTS5 bm25 relevance score (how well the text matches)
+        1. Exact prefix match boost (tag_name starts with query)
-        2. Post count (popularity)
+        2. Post count to preserve expected autocomplete ordering
-        3. Exact prefix match boost (tag_name starts with query)
+        3. FTS5 bm25 relevance score as a deterministic tie-breaker
 
         Args:
             query: The search query string.
@@ -464,6 +464,17 @@ class TagFTSIndex:
             List of dictionaries with tag_name, category, post_count,
             rank_score, and optionally matched_alias.
         """
+        search_started_at = time.perf_counter()
+        logger.info(
+            "LM tag FTS search start query=%r categories=%s limit=%s offset=%s ready=%s indexing=%s",
+            query,
+            categories,
+            limit,
+            offset,
+            self.is_ready(),
+            self.is_indexing(),
+        )
+
         # Ensure index is ready (lazy initialization)
         if not self.ensure_ready():
             if not self._warned_not_ready:
@@ -478,71 +489,44 @@ class TagFTSIndex:
         if not fts_query:
             return []
 
+        logger.info(
+            "LM tag FTS search built query=%r fts_query=%r",
+            query,
+            fts_query,
+        )
+
         query_lower = query.lower().strip()
 
         try:
+            logger.info("LM tag FTS search waiting_for_lock query=%r", query)
             with self._lock:
+                logger.info("LM tag FTS search acquired_lock query=%r", query)
                 conn = self._connect(readonly=True)
                 try:
-                    # Build the SQL query with bm25 ranking
+                    sql, params = self._build_search_statement(
-                    # FTS5 bm25() returns negative scores, lower is better
+                        query_lower=query_lower,
-                    # We use -bm25() to get higher=better scores
+                        fts_query=fts_query,
-                    # Weights: -100.0 for exact matches, 1.0 for others
+                        categories=categories,
-                    # Add LOG10(post_count) weighting to boost popular tags
+                        limit=limit,
-                    # Use CASE to boost tag_name prefix matches above alias matches
+                        offset=offset,
-                    if categories:
-                        placeholders = ",".join("?" * len(categories))
-                        sql = f"""
-                            SELECT t.tag_name, t.category, t.post_count, t.aliases,
-                                   CASE 
-                                       WHEN t.tag_name LIKE ? ESCAPE '\\' THEN 1
-                                       ELSE 0
-                                   END AS is_tag_name_match,
-                                   bm25(tag_fts, -100.0, 1.0, 1.0) + LOG10(t.post_count + 1) * 10.0 AS rank_score
-                            FROM tag_fts
-                            JOIN tags t ON tag_fts.rowid = t.rowid
-                            WHERE tag_fts.searchable_text MATCH ?
-                            AND t.category IN ({placeholders})
-                            ORDER BY is_tag_name_match DESC, rank_score DESC
-                            LIMIT ? OFFSET ?
-                        """
-                        # Escape special LIKE characters and add wildcard
-                        query_escaped = (
-                            query_lower.lstrip("/")
-                            .replace("\\", "\\\\")
-                            .replace("%", "\\%")
-                            .replace("_", "\\_")
                     )
-                        params = (
-                            [query_escaped + "%", fts_query]
-                            + categories
-                            + [limit, offset]
-                        )
-                    else:
-                        sql = """
-                            SELECT t.tag_name, t.category, t.post_count, t.aliases,
-                                   CASE 
-                                       WHEN t.tag_name LIKE ? ESCAPE '\\' THEN 1
-                                       ELSE 0
-                                   END AS is_tag_name_match,
-                                   bm25(tag_fts, -100.0, 1.0, 1.0) + LOG10(t.post_count + 1) * 10.0 AS rank_score
-                            FROM tag_fts
-                            JOIN tags t ON tag_fts.rowid = t.rowid
-                            WHERE tag_fts.searchable_text MATCH ?
-                            ORDER BY is_tag_name_match DESC, rank_score DESC
-                            LIMIT ? OFFSET ?
-                        """
-                        query_escaped = (
-                            query_lower.lstrip("/")
-                            .replace("\\", "\\\\")
-                            .replace("%", "\\%")
-                            .replace("_", "\\_")
-                        )
-                        params = [query_escaped + "%", fts_query, limit, offset]
 
+                    logger.info(
+                        "LM tag FTS search executing_sql query=%r query_len=%s category_count=%s",
+                        query,
+                        len(query_lower),
+                        len(categories) if categories else 0,
+                    )
                     cursor = conn.execute(sql, params)
+                    logger.info("LM tag FTS search execute_returned query=%r", query)
+                    rows = cursor.fetchall()
+                    logger.info(
+                        "LM tag FTS search fetchall_returned query=%r row_count=%s",
+                        query,
+                        len(rows),
+                    )
                     results = []
-                    for row in cursor.fetchall():
+                    for row in rows:
                         result = {
                             "tag_name": row[0],
                             "category": row[1],
@@ -564,6 +548,13 @@ class TagFTSIndex:
                             result["matched_alias"] = matched_alias
 
                         results.append(result)
+                    elapsed_ms = (time.perf_counter() - search_started_at) * 1000
+                    logger.info(
+                        "LM tag FTS search done query=%r result_count=%s elapsed_ms=%.2f",
+                        query,
+                        len(results),
+                        elapsed_ms,
+                    )
                     return results
                 finally:
                     conn.close()
@@ -571,6 +562,62 @@ class TagFTSIndex:
             logger.debug("Tag FTS search error for query '%s': %s", query, exc)
             return []
 
+    def _build_search_statement(
+        self,
+        query_lower: str,
+        fts_query: str,
+        categories: Optional[List[int]],
+        limit: int,
+        offset: int,
+    ) -> tuple[str, list[object]]:
+        """Build the SQL statement and params for a tag search."""
+        # Escape special LIKE characters and add wildcard
+        query_escaped = (
+            query_lower.lstrip("/")
+            .replace("\\", "\\\\")
+            .replace("%", "\\%")
+            .replace("_", "\\_")
+        )
+
+        # FTS5 bm25() returns negative scores, lower is better.
+        # We use -bm25() to get higher=better scores, but keep post_count as the
+        # primary sort within tag-name prefix matches so autocomplete ordering
+        # remains aligned with the existing popularity-first behavior.
+        if categories:
+            placeholders = ",".join("?" * len(categories))
+            sql = f"""
+                SELECT t.tag_name, t.category, t.post_count, t.aliases,
+                       CASE
+                           WHEN t.tag_name LIKE ? ESCAPE '\\' THEN 1
+                           ELSE 0
+                       END AS is_tag_name_match,
+                       bm25(tag_fts, -100.0, 1.0, 1.0) AS rank_score
+                FROM tag_fts
+                CROSS JOIN tags t ON t.rowid = tag_fts.rowid
+                WHERE tag_fts.searchable_text MATCH ?
+                  AND t.category IN ({placeholders})
+                ORDER BY is_tag_name_match DESC, t.post_count DESC, rank_score DESC
+                LIMIT ? OFFSET ?
+            """
+            params = [query_escaped + "%", fts_query] + categories + [limit, offset]
+        else:
+            sql = """
+                SELECT t.tag_name, t.category, t.post_count, t.aliases,
+                       CASE
+                           WHEN t.tag_name LIKE ? ESCAPE '\\' THEN 1
+                           ELSE 0
+                       END AS is_tag_name_match,
+                       bm25(tag_fts, -100.0, 1.0, 1.0) AS rank_score
+                FROM tag_fts
+                JOIN tags t ON tag_fts.rowid = t.rowid
+                WHERE tag_fts.searchable_text MATCH ?
+                ORDER BY is_tag_name_match DESC, t.post_count DESC, rank_score DESC
+                LIMIT ? OFFSET ?
+            """
+            params = [query_escaped + "%", fts_query, limit, offset]
+
+        return sql, params
+
     def _find_matched_alias(
         self, query: str, tag_name: str, aliases_str: str
     ) -> Optional[str]:

tests/frontend/components/autocomplete.behavior.test.js

@@ -126,6 +126,31 @@ describe('AutoComplete widget interactions', () => {
     expect(caretHelperInstance.getCursorOffset).toHaveBeenCalled();
   });
 
+  it('deduplicates duplicate-equivalent query variations before issuing requests', async () => {
+    vi.useFakeTimers();
+
+    fetchApiMock.mockResolvedValue({
+      json: () => Promise.resolve({ success: true, words: [] }),
+    });
+
+    caretHelperInstance.getBeforeCursor.mockReturnValue('Example');
+
+    const input = document.createElement('textarea');
+    document.body.append(input);
+
+    const { AutoComplete } = await import(AUTOCOMPLETE_MODULE);
+    new AutoComplete(input, 'prompt', { debounceDelay: 0, showPreview: false, minChars: 1 });
+
+    input.value = 'Example';
+    input.dispatchEvent(new Event('input', { bubbles: true }));
+
+    await vi.runAllTimersAsync();
+    await Promise.resolve();
+
+    expect(fetchApiMock).toHaveBeenCalledTimes(1);
+    expect(fetchApiMock).toHaveBeenCalledWith('/lm/custom-words/search?enriched=true&search=Example&limit=100');
+  });
+
   it('inserts the selected LoRA with usage tip strengths and restores focus', async () => {
     fetchApiMock.mockImplementation((url) => {
       if (url.includes('usage-tips-by-path')) {
@@ -244,6 +269,55 @@ describe('AutoComplete widget interactions', () => {
     expect(inputListener).not.toHaveBeenCalled();
   });
 
+  it('shows the full command list when typing a single slash', async () => {
+    const input = document.createElement('textarea');
+    input.value = '/';
+    input.selectionStart = input.value.length;
+    document.body.append(input);
+
+    caretHelperInstance.getBeforeCursor.mockReturnValue('/');
+    caretHelperInstance.getCursorOffset.mockReturnValue({ left: 15, top: 25 });
+
+    const { AutoComplete } = await import(AUTOCOMPLETE_MODULE);
+    const autoComplete = new AutoComplete(input,'prompt', { showPreview: false, minChars: 1 });
+
+    input.dispatchEvent(new Event('input', { bubbles: true }));
+
+    const commandNames = autoComplete.items.map((item) => item.command);
+
+    expect(commandNames).toContain('/character');
+    expect(commandNames).toContain('/char');
+    expect(commandNames).toContain('/artist');
+    expect(commandNames).toContain('/general');
+    expect(commandNames).toContain('/copyright');
+    expect(commandNames).toContain('/meta');
+    expect(commandNames).toContain('/species');
+    expect(commandNames).toContain('/lore');
+    expect(commandNames).toContain('/emb');
+    expect(commandNames).toContain('/embedding');
+    expect(commandNames).toContain('/wild');
+    expect(commandNames).toContain('/wildcard');
+  });
+
+  it('renders every command item when slash opens the command list', async () => {
+    const input = document.createElement('textarea');
+    input.value = '/';
+    input.selectionStart = input.value.length;
+    document.body.append(input);
+
+    caretHelperInstance.getBeforeCursor.mockReturnValue('/');
+    caretHelperInstance.getCursorOffset.mockReturnValue({ left: 15, top: 25 });
+
+    const { AutoComplete } = await import(AUTOCOMPLETE_MODULE);
+    const autoComplete = new AutoComplete(input, 'prompt', { showPreview: false, minChars: 1 });
+
+    input.dispatchEvent(new Event('input', { bubbles: true }));
+
+    const renderedCommands = autoComplete.contentContainer.querySelectorAll('.lm-autocomplete-command-name');
+
+    expect(renderedCommands).toHaveLength(autoComplete.items.length);
+  });
+
   it('accepts the selected suggestion with Enter', async () => {
     caretHelperInstance.getBeforeCursor.mockReturnValue('example');
 
@@ -1095,6 +1169,7 @@ describe('AutoComplete widget interactions', () => {
       minChars: 1,
     });
 
+    fetchApiMock.mockClear();
     input.dispatchEvent(new Event('input', { bubbles: true }));
     await vi.runAllTimersAsync();
     await Promise.resolve();
@@ -1133,6 +1208,61 @@ describe('AutoComplete widget interactions', () => {
     expect(input.setSelectionRange).toHaveBeenCalled();
   });
 
+  it('does not reopen autocomplete on blur after inserting a wildcard literal', async () => {
+    const input = document.createElement('textarea');
+    input.value = '__flower__,';
+    input.selectionStart = input.value.length;
+    document.body.append(input);
+
+    caretHelperInstance.getBeforeCursor.mockReturnValue('__flower__,');
+
+    const { AutoComplete } = await import(AUTOCOMPLETE_MODULE);
+    const autoComplete = new AutoComplete(input,'prompt', {
+      debounceDelay: 0,
+      showPreview: false,
+      minChars: 1,
+    });
+
+    const hideSpy = vi.spyOn(autoComplete, 'hide');
+    input.dispatchEvent(new Event('blur', { bubbles: true }));
+
+    expect(fetchApiMock).not.toHaveBeenCalled();
+    expect(hideSpy).toHaveBeenCalled();
+    expect(autoComplete.isVisible).toBe(false);
+  });
+
+  it('treats a command after a wildcard literal as the active token', async () => {
+    vi.useFakeTimers();
+
+    fetchApiMock.mockResolvedValue({
+      json: () => Promise.resolve({
+        success: true,
+        words: [{ tag_name: 'flower_field', category: 4, post_count: 1234 }],
+      }),
+    });
+
+    const input = document.createElement('textarea');
+    input.value = '__flower__ /character f';
+    input.selectionStart = input.value.length;
+    document.body.append(input);
+
+    caretHelperInstance.getBeforeCursor.mockReturnValue('__flower__ /character f');
+    caretHelperInstance.getCursorOffset.mockReturnValue({ left: 15, top: 25 });
+
+    const { AutoComplete } = await import(AUTOCOMPLETE_MODULE);
+    const autoComplete = new AutoComplete(input,'prompt', {
+      debounceDelay: 0,
+      showPreview: false,
+      minChars: 1,
+    });
+
+    input.dispatchEvent(new Event('input', { bubbles: true }));
+    await vi.runAllTimersAsync();
+    await Promise.resolve();
+
+    expect(autoComplete.getSearchTerm(input.value)).toBe('/character f');
+  });
+
   it('invalidates stale autocomplete metadata and falls back to delimiter-based matching', async () => {
     settingGetMock.mockImplementation((key) => {
       if (key === 'loramanager.autocomplete_append_comma') {

tests/test_custom_words_service.py

@@ -94,6 +94,19 @@ class TestCustomWordsService:
         results = service.search_words("test")
         assert mock_tag_index.called
 
+    def test_search_words_skips_prompt_like_queries(self):
+        service = CustomWordsService.__new__(CustomWordsService)
+        mock_tag_index = MockTagFTSIndex()
+
+        def mock_get_index():
+            return mock_tag_index
+
+        service._get_tag_index = mock_get_index
+
+        results = service.search_words("__flower__ /character f")
+
+        assert results == []
+        assert mock_tag_index.called is False
 
 class MockTagFTSIndex:
     """Mock TagFTSIndex for testing."""

tests/test_tag_fts_index.py

@@ -1,6 +1,7 @@
 """Tests for TagFTSIndex functionality."""
 
 import os
+import sqlite3
 import tempfile
 from typing import List
 
@@ -173,6 +174,40 @@ class TestTagFTSIndexSearch:
         assert len(results) >= 1
         assert all(r["category"] in [4, 11] for r in results)
 
+    def test_search_with_category_filter_uses_fts_first_plan(self, populated_fts):
+        """Category-filtered searches should start from FTS hits, not category scans."""
+        sql, params = populated_fts._build_search_statement(
+            query_lower="f",
+            fts_query="f*",
+            categories=[4, 11],
+            limit=20,
+            offset=0,
+        )
+
+        conn = sqlite3.connect(f"file:{populated_fts.get_database_path()}?mode=ro", uri=True)
+        try:
+            plan_rows = conn.execute(f"EXPLAIN QUERY PLAN {sql}", params).fetchall()
+        finally:
+            conn.close()
+
+        plan_details = [row[3] for row in plan_rows]
+        assert any(detail.startswith("SCAN tag_fts VIRTUAL TABLE INDEX") for detail in plan_details)
+        assert any("SEARCH t USING INTEGER PRIMARY KEY" in detail for detail in plan_details)
+        assert not any("SEARCH t USING INDEX idx_tags_category" in detail for detail in plan_details)
+
+    def test_search_statement_uses_post_count_as_tie_breaker(self, populated_fts):
+        """Search ranking should use popularity as a secondary sort key."""
+        sql, _ = populated_fts._build_search_statement(
+            query_lower="f",
+            fts_query="f*",
+            categories=[4, 11],
+            limit=20,
+            offset=0,
+        )
+
+        assert "ORDER BY is_tag_name_match DESC, t.post_count DESC, rank_score DESC" in sql
+        assert "LOG10" not in sql
+
     def test_search_with_category_filter_excludes_others(self, populated_fts):
         """Test that category filter excludes other categories."""
         # Search for "hi" but only in general category

web/comfyui/autocomplete.js

@@ -366,6 +366,7 @@ class AutoComplete {
         this.previewTooltip = null;
         this.previewTooltipPromise = null;
         this.searchType = null;
+        this.suppressAutocompleteOnce = false;
 
         // Virtual scrolling state
         this.virtualScrollOffset = 0;
@@ -505,6 +506,11 @@ class AutoComplete {
     bindEvents() {
         // Handle input changes
         this.onInput = (e) => {
+            if (this.suppressAutocompleteOnce) {
+                this.suppressAutocompleteOnce = false;
+                this.hide();
+                return;
+            }
             this.handleInput(e.target.value);
         };
         this.inputElement.addEventListener('input', this.onInput);
@@ -521,6 +527,7 @@ class AutoComplete {
                 const formattedValue = formatAutocompleteTextOnBlur(this.inputElement.value);
                 if (formattedValue !== this.inputElement.value) {
                     this.inputElement.value = formattedValue;
+                    this.suppressAutocompleteOnce = true;
                     this.inputElement.dispatchEvent(new Event('input', { bubbles: true }));
                 }
             }
@@ -725,9 +732,24 @@ class AutoComplete {
         }
 
         const rawText = beforeCursor.substring(start);
-        const text = rawText.trim();
         const leadingWhitespaceLength = rawText.length - rawText.trimStart().length;
         const trimmedStart = start + leadingWhitespaceLength;
+        const text = rawText.trim();
+
+        if (this.modelType === 'prompt') {
+            const tokenRange = this._getPromptTokenRange(rawText, trimmedStart, caretPos);
+            if (tokenRange) {
+                return {
+                    start: tokenRange.start,
+                    trimmedStart: tokenRange.trimmedStart,
+                    end: caretPos,
+                    beforeCursor,
+                    rawText: tokenRange.rawText,
+                    text: tokenRange.text,
+                    tokenType: tokenRange.tokenType,
+                };
+            }
+        }
 
         return {
             start,
@@ -739,6 +761,73 @@ class AutoComplete {
         };
     }
 
+    _getPromptTokenRange(rawText = '', trimmedStart = 0, caretPos = 0) {
+        const trimmedText = rawText.trim();
+        if (!trimmedText) {
+            return {
+                start: trimmedStart,
+                trimmedStart,
+                rawText: '',
+                text: '',
+                tokenType: 'empty',
+            };
+        }
+
+        const commandOffset = trimmedText.startsWith('/')
+            ? 0
+            : trimmedText.lastIndexOf(' /');
+        if (commandOffset !== -1) {
+            const normalizedCommandOffset = commandOffset === 0 ? 0 : commandOffset + 1;
+            const commandText = trimmedText.slice(normalizedCommandOffset);
+            const commandStart = trimmedStart + normalizedCommandOffset;
+            return {
+                start: commandStart,
+                trimmedStart: commandStart,
+                rawText: commandText,
+                text: commandText,
+                tokenType: commandText === '/' ? 'empty_command_trigger' : 'command',
+            };
+        }
+
+        const wildcardMatch = trimmedText.match(/(?:^|\s)(__[\w\s.\-+/*\\]+?__)$/);
+        if (wildcardMatch) {
+            const wildcardText = wildcardMatch[1];
+            const wildcardOffset = trimmedText.lastIndexOf(wildcardText);
+            const wildcardStart = trimmedStart + wildcardOffset;
+            return {
+                start: wildcardStart,
+                trimmedStart: wildcardStart,
+                rawText: wildcardText,
+                text: '',
+                tokenType: 'wildcard_literal',
+            };
+        }
+
+        const embeddingOffset = trimmedText.search(/(?:^|\s)emb:[^\s]*$/i);
+        if (embeddingOffset !== -1) {
+            const normalizedEmbeddingOffset = trimmedText.slice(embeddingOffset).startsWith(' ')
+                ? embeddingOffset + 1
+                : embeddingOffset;
+            const embeddingText = trimmedText.slice(normalizedEmbeddingOffset);
+            const embeddingStart = trimmedStart + normalizedEmbeddingOffset;
+            return {
+                start: embeddingStart,
+                trimmedStart: embeddingStart,
+                rawText: embeddingText,
+                text: embeddingText,
+                tokenType: 'embedding_literal',
+            };
+        }
+
+        return {
+            start: trimmedStart,
+            trimmedStart,
+            rawText,
+            text: trimmedText,
+            tokenType: 'tag_text',
+        };
+    }
+
     _getHardBoundaryStart(beforeCursor = '') {
         const lastComma = beforeCursor.lastIndexOf(',');
         const lastAngle = beforeCursor.lastIndexOf('>');
@@ -890,6 +979,32 @@ class AutoComplete {
         return Array.from(variations).filter(v => v.length >= this.options.minChars);
     }
 
+    _normalizeQueryForRequest(term = '') {
+        return term.trim().toLowerCase();
+    }
+
+    _getQueriesToExecute(term = '') {
+        const queryVariations = this._generateQueryVariations(term);
+        const uniqueQueries = [];
+        const seen = new Set();
+
+        for (const query of queryVariations) {
+            const normalized = this._normalizeQueryForRequest(query);
+            if (!normalized || seen.has(normalized)) {
+                continue;
+            }
+
+            seen.add(normalized);
+            uniqueQueries.push(query);
+
+            if (uniqueQueries.length >= 4) {
+                break;
+            }
+        }
+
+        return uniqueQueries;
+    }
+
     /**
      * Get display text for an item (without extension for models)
      * @param {string|Object} item - Item to get display text from
@@ -1041,18 +1156,17 @@ class AutoComplete {
                 endpoint = `/lm/${this.modelType}/relative-paths`;
             }
 
-            // Generate multiple query variations for better matching
+            // Generate multiple query variations for better matching, but avoid
-            const queryVariations = this._generateQueryVariations(term);
+            // sending duplicate-equivalent requests that normalize to the same
+            // backend search term.
+            const queriesToExecute = this._getQueriesToExecute(term);
 
-            if (queryVariations.length === 0) {
+            if (queriesToExecute.length === 0) {
                 this.items = [];
                 this.hide();
                 return;
             }
 
-            // Limit the number of parallel queries to avoid overwhelming the server
-            const queriesToExecute = queryVariations.slice(0, 4);
-
             // Execute all queries in parallel
             const searchPromises = queriesToExecute.map(async (query) => {
                 const url = endpoint.includes('?')
@@ -1190,20 +1304,15 @@ class AutoComplete {
         
         const filterLower = filter.toLowerCase();
 
-        // Get unique commands (avoid duplicates like /char and /character)
-        const seenLabels = new Set();
         const commands = [];
 
         for (const [cmd, info] of Object.entries(TAG_COMMANDS)) {
-            if (seenLabels.has(info.label)) continue;
-
             // Filter out toggle commands that don't meet their condition
             if (info.type === 'toggle_setting' && info.condition) {
                 if (!info.condition()) continue;
             }
 
             if (!filter || cmd.slice(1).startsWith(filterLower)) {
-                seenLabels.add(info.label);
                 commands.push({ command: cmd, ...info });
             }
         }
@@ -1288,9 +1397,17 @@ class AutoComplete {
         }
 
         // Auto-select immediately so accept keys remain stable.
+        // In virtual-scroll mode, calling selectItem() before the dropdown is
+        // visible can see a zero-height container and incorrectly replace the
+        // full command list with a partially virtualized slice.
         if (this.items.length > 0) {
+            this.selectedIndex = 0;
+            if (this.contentContainer) {
+                this._applyItemSelection(0);
+            } else {
                 this.selectItem(0);
             }
+        }
         
         // Update virtual scroll height for virtual scrolling mode
         if (this.contentContainer) {
@@ -1635,8 +1752,7 @@ class AutoComplete {
                 }
             }
 
-            const queryVariations = this._generateQueryVariations(this.currentSearchTerm);
+            const queriesToExecute = this._getQueriesToExecute(this.currentSearchTerm);
-            const queriesToExecute = queryVariations.slice(0, 4);
             const offset = this.items.length;
 
             // Execute all queries in parallel with offset