Update main.py

main.py

@@ -63,7 +63,7 @@ def compare():
     
     # Encode job skills
     job_embeddings = [model.encode(skill) for skill in jobs_skills]
-    job_embeddings_tensor = torch.tensor(job_embeddings)
+    job_embeddings_tensor = torch.tensor(job_embeddings, dtype=torch.float32)
     
     # Initialize a dictionary to store similarities for each employee
     all_similarities = {}
@@ -71,7 +71,7 @@ def compare():
     for idx, employee_skills in enumerate(employees_skills):
         # Encode employee skills
         employee_embedding = model.encode(employee_skills)
-        employee_embedding_tensor = torch.tensor(employee_embedding).unsqueeze(0)
+        employee_embedding_tensor = torch.tensor(employee_embedding, dtype=torch.float32).unsqueeze(0)
         
         # Calculate cosine similarity
         similarities = cosine_similarity(employee_embedding_tensor, job_embeddings_tensor)[0]
@@ -80,8 +80,8 @@ def compare():
         max_similarity_index = similarities.argmax()
         max_similarity_job = jobs_skills[max_similarity_index]
         
-        # Store similarities in the dictionary
-        similarities_dict = {job: similarity for job, similarity in zip(jobs_skills, similarities)}
+        # Convert similarities to float for JSON serialization
+        similarities_dict = {job: float(similarity) for job, similarity in zip(jobs_skills, similarities)}
         all_similarities[f'employee_{idx+1}'] = {
             'job': max_similarity_job,
             'similarities': similarities_dict