Create embeddings.py

embeddings.py

@@ -0,0 +1,26 @@
+# Requires transformers>=4.51.0
+import torch
+from sentence_transformers import SentenceTransformer
+
+model = SentenceTransformer("Qwen/Qwen3-Embedding-0.6B")
+
+# queries = "hey"
+# documents = [
+#     "The capital of China is Beijing.",
+#     "Gravity is a force that attracts two bodies towards each other. It gives weight to physical objects and is responsible for the movement of planets around the sun.",
+# ]
+
+def rank_resume(job_description, resumes):
+    task = "Given a resume, retrieve relevant job description that is suitable for the resume"
+
+    queries = resumes
+    documents = job_description
+
+    print("[QUERIES]", query)
+    print("[DOCUMENTS]", documents)
+
+    query_embeddings = model.encode(queries, prompt=task)
+    document_embeddings = model.encode(documents)
+    similarity = model.similarity(query_embeddings, document_embeddings)
+
+    return documents, similarity[0].tolist()