Enha (rag): query each doc

rag/rag.go

@@ -286,11 +286,14 @@ func (r *RAG) RefineQuery(query string) string {
 		return original
 	}
 	query = strings.ToLower(query)
+	words := strings.Fields(query)
+	if len(words) >= 3 {
 		for _, stopWord := range stopWords {
 			wordPattern := `\b` + stopWord + `\b`
 			re := regexp.MustCompile(wordPattern)
 			query = re.ReplaceAllString(query, "")
 		}
+	}
 	query = strings.TrimSpace(query)
 	if len(query) < 5 {
 		return original
@@ -340,6 +343,36 @@ func (r *RAG) GenerateQueryVariations(query string) []string {
 	if len(parts) == 0 {
 		return variations
 	}
+	// Get loaded filenames to filter out filename terms
+	filenames, err := r.storage.ListFiles()
+	if err == nil && len(filenames) > 0 {
+		// Convert to lowercase for case-insensitive matching
+		lowerFilenames := make([]string, len(filenames))
+		for i, f := range filenames {
+			lowerFilenames[i] = strings.ToLower(f)
+		}
+		filteredParts := make([]string, 0, len(parts))
+		for _, part := range parts {
+			partLower := strings.ToLower(part)
+			skip := false
+			for _, fn := range lowerFilenames {
+				if strings.Contains(fn, partLower) || strings.Contains(partLower, fn) {
+					skip = true
+					break
+				}
+			}
+			if !skip {
+				filteredParts = append(filteredParts, part)
+			}
+		}
+		// If filteredParts not empty and different from original, add filtered query
+		if len(filteredParts) > 0 && len(filteredParts) != len(parts) {
+			filteredQuery := strings.Join(filteredParts, " ")
+			if len(filteredQuery) >= 5 {
+				variations = append(variations, filteredQuery)
+			}
+		}
+	}
 	if len(parts) >= 2 {
 		trimmed := strings.Join(parts[:len(parts)-1], " ")
 		if len(trimmed) >= 5 {
@@ -403,9 +436,14 @@ func (r *RAG) RerankResults(results []models.VectorRow, query string) []models.V
 	})
 	unique := make([]models.VectorRow, 0)
 	seen := make(map[string]bool)
+	fileCounts := make(map[string]int)
 	for i := range scored {
 		if !seen[scored[i].row.Slug] {
+			if fileCounts[scored[i].row.FileName] >= 2 {
+				continue
+			}
 			seen[scored[i].row.Slug] = true
+			fileCounts[scored[i].row.FileName]++
 			unique = append(unique, scored[i].row)
 		}
 	}

rag/storage.go

@@ -1,6 +1,7 @@
 package rag
 
 import (
+	"database/sql"
 	"encoding/binary"
 	"fmt"
 	"gf-lt/models"
@@ -221,11 +222,41 @@ func (vs *VectorStorage) SearchKeyword(query string, limit int) ([]models.Vector
 				 WHERE fts_embeddings MATCH ? 
 				 ORDER BY score 
 				 LIMIT ?`
+
+	// Try original query first
 	rows, err := vs.sqlxDB.Query(ftsQuery, query, limit)
 	if err != nil {
 		return nil, fmt.Errorf("FTS search failed: %w", err)
 	}
-	defer rows.Close()
+	results, err := vs.scanRows(rows)
+	rows.Close()
+	if err != nil {
+		return nil, err
+	}
+
+	// If no results and query contains multiple terms, try OR fallback
+	if len(results) == 0 && strings.Contains(query, " ") && !strings.Contains(strings.ToUpper(query), " OR ") {
+		// Build OR query: term1 OR term2 OR term3
+		terms := strings.Fields(query)
+		if len(terms) > 1 {
+			orQuery := strings.Join(terms, " OR ")
+			rows, err := vs.sqlxDB.Query(ftsQuery, orQuery, limit)
+			if err != nil {
+				// Return original empty results rather than error
+				return results, nil
+			}
+			orResults, err := vs.scanRows(rows)
+			rows.Close()
+			if err == nil {
+				results = orResults
+			}
+		}
+	}
+	return results, nil
+}
+
+// scanRows converts SQL rows to VectorRow slice
+func (vs *VectorStorage) scanRows(rows *sql.Rows) ([]models.VectorRow, error) {
 	var results []models.VectorRow
 	for rows.Next() {
 		var slug, rawText, fileName string