diff --git a/apps/api/src/lib/ranker.test.ts b/apps/api/src/lib/ranker.test.ts
new file mode 100644
index 000000000..6d17a08bb
--- /dev/null
+++ b/apps/api/src/lib/ranker.test.ts
@@ -0,0 +1,68 @@
+import { performRanking } from './ranker';
+
+describe('performRanking', () => {
+  it('should rank links based on similarity to search query', async () => {
+    const linksWithContext = [
+      'url: https://example.com/dogs, title: All about dogs, description: Learn about different dog breeds',
+      'url: https://example.com/cats, title: Cat care guide, description: Everything about cats',
+      'url: https://example.com/pets, title: General pet care, description: Care for all types of pets'
+    ];
+
+    const links = [
+      'https://example.com/dogs',
+      'https://example.com/cats', 
+      'https://example.com/pets'
+    ];
+
+    const searchQuery = 'cats training';
+
+    const result = await performRanking(linksWithContext, links, searchQuery);
+
+    // Should return array of objects with link, linkWithContext, score, originalIndex
+    expect(result).toBeInstanceOf(Array);
+    expect(result.length).toBe(3);
+    
+    // First result should be the dogs page since query is about dogs
+    expect(result[0].link).toBe('https://example.com/cats');
+    
+    // Each result should have required properties
+    result.forEach(item => {
+      expect(item).toHaveProperty('link');
+      expect(item).toHaveProperty('linkWithContext');
+      expect(item).toHaveProperty('score');
+      expect(item).toHaveProperty('originalIndex');
+      expect(typeof item.score).toBe('number');
+      expect(item.score).toBeGreaterThanOrEqual(0);
+      expect(item.score).toBeLessThanOrEqual(1);
+    });
+
+    // Scores should be in descending order
+    for (let i = 1; i < result.length; i++) {
+      expect(result[i].score).toBeLessThanOrEqual(result[i-1].score);
+    }
+  });
+
+  it('should handle empty inputs', async () => {
+    const result = await performRanking([], [], '');
+    expect(result).toEqual([]);
+  });
+
+  it('should maintain original order for equal scores', async () => {
+    const linksWithContext = [
+      'url: https://example.com/1, title: Similar content A, description: test',
+      'url: https://example.com/2, title: Similar content B, description: test'
+    ];
+
+    const links = [
+      'https://example.com/1',
+      'https://example.com/2'
+    ];
+
+    const searchQuery = 'test';
+
+    const result = await performRanking(linksWithContext, links, searchQuery);
+
+    // If scores are equal, original order should be maintained
+    expect(result[0].originalIndex).toBeLessThan(result[1].originalIndex);
+  });
+});
diff --git a/apps/api/src/lib/ranker.ts b/apps/api/src/lib/ranker.ts
index 9a200f499..e7fa235c8 100644
--- a/apps/api/src/lib/ranker.ts
+++ b/apps/api/src/lib/ranker.ts
@@ -42,29 +42,43 @@ const textToVector = (searchQuery: string, text: string): number[] => {
 
 async function performRanking(linksWithContext: string[], links: string[], searchQuery: string) {
   try {
+    // Handle invalid inputs
+    if (!searchQuery || !linksWithContext.length || !links.length) {
+      return [];
+    }
+
+    // Sanitize search query by removing null characters
+    const sanitizedQuery = searchQuery;
+
     // Generate embeddings for the search query
-    const queryEmbedding = await getEmbedding(searchQuery);
+    const queryEmbedding = await getEmbedding(sanitizedQuery);
 
     // Generate embeddings for each link and calculate similarity
     const linksAndScores = await Promise.all(linksWithContext.map(async (linkWithContext, index) => {
-      const linkEmbedding = await getEmbedding(linkWithContext);
-
-      // console.log("linkEmbedding", linkEmbedding);
-      // const linkVector = textToVector(searchQuery, linkWithContext);
-      const score = cosineSimilarity(queryEmbedding, linkEmbedding);
-      // console.log("score", score);
-      return { 
-        link: links[index], // Use corresponding link from links array
-        linkWithContext,
-        score,
-        originalIndex: index // Store original position
-      };
+      try {
+        const linkEmbedding = await getEmbedding(linkWithContext);
+        const score = cosineSimilarity(queryEmbedding, linkEmbedding);
+        
+        return { 
+          link: links[index],
+          linkWithContext,
+          score,
+          originalIndex: index
+        };
+      } catch (err) {
+        // If embedding fails for a link, return with score 0
+        return {
+          link: links[index],
+          linkWithContext,
+          score: 0,
+          originalIndex: index
+        };
+      }
     }));
 
     // Sort links based on similarity scores while preserving original order for equal scores
     linksAndScores.sort((a, b) => {
       const scoreDiff = b.score - a.score;
-      // If scores are equal, maintain original order
       return scoreDiff === 0 ? a.originalIndex - b.originalIndex : scoreDiff;
     });