Update app.py

app.py

@@ -6,22 +6,23 @@ import networkx as nx
 import matplotlib.pyplot as plt
 import csv
 import io
+import os
 
 # Sentence-BERT 모델 로드
 model = SentenceTransformer('all-MiniLM-L6-v2')
 
-# 추천 결과를 CSV 파일로 저장하는 함수 (StringIO로 수정)
-def save_recommendations_to_csv(recommendations):
-    output = io.StringIO()
-    writer = csv.writer(output)
-    writer.writerow(["Employee ID", "Employee Name", "Recommended Programs"])
-    
-    # 추천 결과 CSV 파일에 기록
-    for rec in recommendations:
-        writer.writerow(rec)
+# 추천 결과를 실제 파일로 저장하는 함수
+def save_recommendations_to_file(recommendations):
+    file_path = "recommendations.csv"
+    with open(file_path, mode='w', newline='', encoding='utf-8') as file:
+        writer = csv.writer(file)
+        writer.writerow(["Employee ID", "Employee Name", "Recommended Programs"])
+        
+        # 추천 결과 CSV 파일에 기록
+        for rec in recommendations:
+            writer.writerow(rec)
     
-    output.seek(0)
-    return output.getvalue()
+    return file_path
 
 # 자동으로 열을 매칭하는 함수
 def auto_match_columns(df, required_cols):
@@ -104,12 +105,13 @@ def analyze_data(employee_file, program_file):
     plt.title("직원과 프로그램 간의 관계", fontsize=14, fontweight='bold')
     plt.tight_layout()
 
-    csv_output = save_recommendations_to_csv(recommendation_rows)
+    # CSV 파일로 추천 결과 반환
+    csv_output = save_recommendations_to_file(recommendation_rows)
     
     return "\n".join(recommendations), plt.gcf(), csv_output
 
 # Gradio 블록
-with gr.Blocks(css=".gradio-button {background-color: #6c757d; color: white;} .gradio-textbox {border-color: #6c757d;}") as demo:
+with gr.Blocks(css=".gradio-button {background-color: #007bff; color: white;} .gradio-textbox {border-color: #6c757d;}") as demo:
     gr.Markdown("<h1 style='text-align: center; color: #2c3e50;'>💼 HybridRAG 시스템</h1>")
     
     with gr.Row():