Update main.py

main.py

@@ -1,4 +1,4 @@
-from flask import Flask, request, jsonify
+ffrom flask import Flask, request, jsonify
 from langchain_community.llms import LlamaCpp
 from sentence_transformers import SentenceTransformer
 from transformers import AutoTokenizer, AutoModel
@@ -97,3 +97,57 @@ def compare_jop():
 
 if __name__ == '__main__':
     app.run()
+
+
+# Endpoint to compare between employee skills and job skills
+@app.route('/compare', methods=['POST'])
+def compare():
+    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")
+
+    if not isinstance(jobs_skills, list) or not all(isinstance(skill, str) for skill in jobs_skills):
+        raise ValueError("jobs_skills must be a list of strings")
+
+    job_embeddings = model.encode(jobs_skills)
+    employee_embeddings = model.encode(employee_skills)
+
+    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.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')
+
+    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")
+
+    if not isinstance(jobs_skills, list) or not all(isinstance(skill, str) for skill in jobs_skills):
+        raise ValueError("jobs_skills must be a list of strings")
+
+    job_embeddings = model.encode(jobs_skills)
+    employee_embeddings = model.encode(employee_skills)
+
+    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.tolist()[0]})
+
+    return jsonify(similarity_scores)
+
+if __name__ == '__main__':
+    app.run()