Update app.py

app.py

@@ -1,6 +1,7 @@
 import gradio as gr
 import random
 import os
+import pandas as pd
 from huggingface_hub import InferenceClient
 
 MODELS = {
@@ -28,6 +29,10 @@ def call_api(model, content, system_message, max_tokens, temperature, top_p):
 def generate_text(model, user_message, system_message, max_tokens, temperature, top_p):
     return call_api(model, user_message, system_message, max_tokens, temperature, top_p)
 
+def upload_excel(file):
+    df = pd.read_excel(file.name)
+    return df.head().to_string()
+
 title = "AI 텍스트 생성기"
 
 with gr.Blocks() as demo:
@@ -36,17 +41,31 @@ with gr.Blocks() as demo:
     model = gr.Radio(choices=list(MODELS.keys()), label="언어 모델 선택", value="Zephyr 7B Beta")
     user_message = gr.Textbox(label="사용자 메시지", lines=5)
     system_message = gr.Textbox(label="시스템 메시지 (프롬프트)", lines=10)
+
+    # 입력창 2개 추가
+    input1 = gr.Textbox(label="입력창 1")
+    input2 = gr.Textbox(label="입력창 2")
+    
+    # 출력창 2개 추가
+    output1 = gr.Textbox(label="출력창 1", lines=10)
+    output2 = gr.Textbox(label="출력창 2", lines=10)
     
+    # 엑셀 업로드 기능 추가
+    excel_input = gr.File(label="엑셀 파일 업로드", file_types=[".xls", ".xlsx"])
+    excel_output = gr.Textbox(label="엑셀 내용 미리보기", lines=10)
+
     with gr.Accordion("고급 설정", open=False):
         max_tokens = gr.Slider(label="Max Tokens", minimum=0, maximum=4000, value=500, step=100)
         temperature = gr.Slider(label="Temperature", minimum=0.1, maximum=1.0, value=0.75, step=0.05)
         top_p = gr.Slider(label="Top P", minimum=0.1, maximum=1.0, value=0.95, step=0.05)
     
+    # 실행 버튼 추가
     generate_btn = gr.Button("텍스트 생성하기")
-    output = gr.Textbox(label="생성된 텍스트", lines=10)
     
     generate_btn.click(fn=generate_text, 
                        inputs=[model, user_message, system_message, max_tokens, temperature, top_p], 
-                       outputs=[output])
+                       outputs=[output1, output2])
+    
+    excel_input.upload(upload_excel, inputs=[excel_input], outputs=[excel_output])
 
-demo.launch()
+demo.launch()