Create app.py

app.py

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+import pandas as pd
+import gradio as gr
+import pymssql
+import csv
+
+from sentence_transformers import SentenceTransformer
+from sklearn.metrics.pairwise import cosine_similarity #유사도 검색 기능을 사용하기 위함
+import glob
+
+df = pd.read_csv('./data/real/_UnivSample_20231113.csv')
+
+encoder = SentenceTransformer('jhgan/ko-sroberta-multitask') # 선택 모델 (ko가 붙은건 한국어 지원)
+
+df['embedding'] = pd.Series([[]] * len(df)) # dummy
+df['embedding'] = df['query'].map(lambda x: list(encoder.encode(x))) 
+
+# 챗봇의 답변을 처리하는 함수
+def respond(message, chat_history):
+    
+    embedding = encoder.encode(message)
+
+    df['distance'] = df['embedding'].map(lambda x: cosine_similarity([embedding], [x]).squeeze())
+    answer = df.loc[df['distance'].idxmax()]
+
+    chat_history.append([message, answer['answer']])
+    
+    historySave(message=message, answer=str(answer['answer']).replace("'",""))
+    # historySave(message=message, answer="")
+    
+    return "", chat_history
+
+# def historySave(message, answer):
+
+#     conn = pymssql.connect(host=r"(local)", database='Chatbot_Manage', charset='utf8')
+#     conn.autocommit(True) # 오토 커밋 활성화
+#     # Connection 으로부터 Cursor 생성
+#     cursor = conn.cursor()
+
+#     SystemType = "SentenceModel"
+    
+#     # SQL문 실행'
+#     _sql = "EXEC ChatHistory_InsUpd '" + SystemType + "','" + message + "', '" + answer + "'"
+#     cursor.execute(_sql)
+    
+#     conn.close()    ## 연결 끊기
+
+# 챗봇 설명
+title = """
+<div style="text-align: center; max-width: 500px; margin: 0 auto;">
+    <div>
+        <h1>Woody's Chatbot V2</h1>
+    </div>
+    <p style="margin-bottom: 10px; font-size: 94%">
+        sentence_transformers를 이용한 Chatbot
+    </p>
+</div>
+"""
+
+# 꾸미기
+css="""
+#col-container {max-width: 700px; margin-left: auto; margin-right: auto;}
+"""
+with gr.Blocks(css=css) as UnivChatbot:
+    with gr.Column(elem_id="col-container"):
+        gr.HTML(title)
+
+        chatbot = gr.Chatbot(label="대학 챗봇시스템(LLM Sentence)", elem_id="chatbot") # 상단 좌측 
+                
+        with gr.Row():
+            with gr.Column(scale=9):
+                msg = gr.Textbox(label="입력", placeholder="궁금하신 내역을 입력하여 주세요.", elem_id="InputQuery", show_label=False, container=False)
+            
+        with gr.Row():
+            with gr.Column(scale=1):
+                submit = gr.Button("전송", variant="primary")
+            with gr.Column(scale=1):
+                clear = gr.Button("초기화", variant="stop")
+                
+
+    # 사용자의 입력을 제출(submit)하면 respond 함수가 호출.
+    msg.submit(respond, [msg, chatbot], [msg, chatbot])
+
+    submit.click(respond, [msg, chatbot], [msg, chatbot])
+
+    # '초기화' 버튼을 클릭하면 채팅 기록을 초기화.
+    clear.click(lambda: None, None, chatbot, queue=False)
+    
+UnivChatbot.launch()
+