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refactor: increase minimum confidence threshold in search strategies
- Updated the minimum confidence level from 0.95 to 0.97 to enhance the accuracy of search results. - Adjusted confidence calculation in the findLevenshteinMatch function to ensure more reliable matching.
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@@ -10,7 +10,7 @@ export type SearchResult = {
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};
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};
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//TODO: this should be configurable
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//TODO: this should be configurable
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const MIN_CONFIDENCE = 0.95;
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const MIN_CONFIDENCE = 0.97;
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// Helper function to prepare search string from context
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// Helper function to prepare search string from context
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export function prepareSearchString(changes: Change[]): string {
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export function prepareSearchString(changes: Change[]): string {
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@@ -74,7 +74,6 @@ export function validateEditResult(hunk: Hunk, result: string, strategy: string)
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console.log('expectedSimilarity', strategy, expectedSimilarity);
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console.log('expectedSimilarity', strategy, expectedSimilarity);
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// Scale between 0.98 and 1.0 (4% impact) based on expected similarity
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// Scale between 0.98 and 1.0 (4% impact) based on expected similarity
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const multiplier =
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const multiplier =
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expectedSimilarity < MIN_CONFIDENCE ? 0.96 + 0.04 * expectedSimilarity : 1;
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expectedSimilarity < MIN_CONFIDENCE ? 0.96 + 0.04 * expectedSimilarity : 1;
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@@ -183,11 +182,10 @@ export function findLevenshteinMatch(
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const index = startIndex + candidates.indexOf(closestMatch);
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const index = startIndex + candidates.indexOf(closestMatch);
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const similarity = getDMPSimilarity(searchStr, closestMatch);
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const similarity = getDMPSimilarity(searchStr, closestMatch);
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const contextSimilarity = validateContextLines(searchStr, closestMatch);
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const contextSimilarity = validateContextLines(searchStr, closestMatch);
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const confidence = Math.min(similarity, contextSimilarity) * 0.7; // Still apply Levenshtein penalty
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const confidence = Math.min(similarity, contextSimilarity)
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return {
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return {
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index,
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index,
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confidence,
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confidence: index !== -1 ? confidence : 0,
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strategy: 'levenshtein',
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strategy: 'levenshtein',
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};
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};
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}
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}
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