Update main.py

main.py

@@ -61,15 +61,18 @@ def compare():
     employee_embeddings = model.encode(employee_skills)
 
     # Computing cosine similarity between employee skills and each job
-    similarity_scores = []
-    employee_embeddings_tensor = torch.from_numpy(employee_embeddings).unsqueeze(0)
+     similarity_scores = []
+employee_embeddings_tensor = torch.from_numpy(employee_embeddings).unsqueeze(0)
 
-    for i, job_e in enumerate(job_embeddings):
-        job_e_tensor = torch.from_numpy(job_e).unsqueeze(0)
-        similarity_score = cosine_similarity(employee_embeddings_tensor, job_e_tensor, dim=1)
-        similarity_scores.append({"job": jobs_skills[i], "similarity_score": similarity_score.item()})
+for i, job_e in enumerate(job_embeddings):
+    job_e_tensor = torch.from_numpy(job_e).unsqueeze(0)
+    similarity_score = cosine_similarity(employee_embeddings_tensor, job_e_tensor, dim=1)
+    
+    # Append all similarity scores for each job
+    similarity_scores.append({"job": jobs_skills[i], "similarity_scores": similarity_score.tolist()})
+
+return jsonify(similarity_scores)
 
-    return jsonify(similarity_scores)
 
 
 if __name__ == '__main__':