Update app.py

app.py

@@ -1,24 +1,21 @@
-import gradio as gr
-import os
+import gradio as gr, os
+from transformers import BartForConditionalGeneration
 
-model = gr.load("models/fnlp/bart-base-chinese")
+# 加载 BART 模型
+model = BartForConditionalGeneration.from_pretrained("models/fnlp/bart-base-chinese")
 
 def generate_summary(file):
+    # 重置文件指针位置
+    file.seek(0)
+    
     # 读取上传的文本文件内容
-    with open(file.name, 'r', encoding='utf-8') as f:
-        text_content = f.read()
-        print("File Content:", text_content)  # 添加此行进行调试
+    text_content = file.read()
 
-    # 使用模型进行处理（在这里是摘要生成，你可以替换为你的具体模型处理逻辑）
-    result = model.predict(text_content)
-    
-    return result
+    # 使用模型进行处理（摘要生成）
+    summary_ids = model.generate(text_content, max_length=150, min_length=50, length_penalty=2.0, num_beams=4, early_stopping=True)
+    summary = model.decode(summary_ids[0], skip_special_tokens=True)
 
-def read_file_content(file):
-    # 读取上传的文本文件内容
-    with open(file.name, 'r', encoding='utf-8') as f:
-        text_content = f.read()
-        return text_content
+    return summary
 
 demo = gr.Interface(
     fn=generate_summary,
@@ -27,13 +24,5 @@ demo = gr.Interface(
     live=False
 )
 
-# 增加一个上传文件后读取文件内容的接口
-file_reader = gr.Interface(
-    fn=read_file_content,
-    inputs=gr.File(),
-    outputs="text",
-    live=False
-)
-
 # 启动应用
 demo.launch(share=True)