Update main.py

main.py

@@ -66,15 +66,15 @@ def compare():
     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()})
+        similarity_scores.append({"job": jobs_skills[i], "similarity_score": similarity_score.tolist()[0]})
 
     return jsonify(similarity_scores)
 
 # Endpoint to compare job posts with employee skills
 @app.route('/compare_jop', methods=['POST'])
 def compare_jop():
-    employee_skills = request.json.get('post')
-    jobs_skills = request.json.get('employee_skills')
+    employee_skills = request.json.get('employee_skills')
+    jobs_skills = request.json.get('jobs_skills')
 
     if not isinstance(employee_skills, list) or not all(isinstance(skill, str) for skill in employee_skills):
         raise ValueError("employee_skills must be a list of strings")
@@ -91,7 +91,7 @@ def compare_jop():
     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()})
+        similarity_scores.append({"job": jobs_skills[i], "similarity_score": similarity_score.tolist()[0]})
 
     return jsonify(similarity_scores)