Update app.py

app.py

@@ -18,8 +18,10 @@ def call_api(content, system_message, max_tokens, temperature, top_p):
     response = client.chat_completion(messages=messages, max_tokens=max_tokens, temperature=temperature, top_p=top_p, seed=random_seed)
     return response.choices[0].message.content
 
-def generate_text(user_message, system_message, max_tokens, temperature, top_p):
-    return call_api(user_message, system_message, max_tokens, temperature, top_p)
+# 긍정리뷰와 부정리뷰 분석을 위해 LLM 호출
+def analyze_reviews(reviews, prompt, max_tokens, temperature, top_p):
+    reviews_text = "\n".join(reviews)
+    return call_api(reviews_text, prompt, max_tokens, temperature, top_p)
 
 # 엑셀 업로드 후 처리 기능 추가
 def upload_excel(file):
@@ -106,4 +108,26 @@ with gr.Blocks() as demo:
     # 엑셀 파일 업로드 후 긍정리뷰 10개와 부정리뷰 10개를 출력
     excel_input.upload(upload_excel, inputs=[excel_input], outputs=[excel_output_positive, excel_output_negative])
 
+    # 긍정리뷰분석 실행 (LLM 호출)
+    def analyze_positive_reviews(positive_reviews, prompt, max_tokens, temperature, top_p):
+        reviews = positive_reviews.splitlines()
+        return analyze_reviews(reviews, prompt, max_tokens, temperature, top_p)
+    
+    # 부정리뷰분석 실행 (LLM 호출)
+    def analyze_negative_reviews(negative_reviews, prompt, max_tokens, temperature, top_p):
+        reviews = negative_reviews.splitlines()
+        return analyze_reviews(reviews, prompt, max_tokens, temperature, top_p)
+
+    # LLM 분석 버튼 추가 (긍정리뷰분석)
+    analyze_positive_btn = gr.Button("긍정리뷰 분석하기")
+    analyze_positive_btn.click(fn=analyze_positive_reviews, 
+                               inputs=[excel_output_positive, system_message, max_tokens, temperature, top_p], 
+                               outputs=[output1])
+
+    # LLM 분석 버튼 추가 (부정리뷰분석)
+    analyze_negative_btn = gr.Button("부정리뷰 분석하기")
+    analyze_negative_btn.click(fn=analyze_negative_reviews, 
+                               inputs=[excel_output_negative, input2, max_tokens, temperature, top_p], 
+                               outputs=[output2])
+
 demo.launch()