Upload app.py

app.py

@@ -412,16 +412,18 @@ class Reader:
             chat_summary_text = self.chat_summary(text=text, key=str(key))           
             htmls.append(chat_summary_text)
             
-            # TODO 往md文档中插入论文里的像素最大的一张图片，这个方案可以弄的更加智能一些：
-            first_image, ext = paper.get_image_path()
-            if first_image is None or self.gitee_key == '':
-                pass
-            else:                
-                image_title = self.validateTitle(paper.title)
-                image_url = self.upload_gitee(image_path=first_image, image_name=image_title, ext=ext)
-                htmls.append("\n")
-                htmls.append("![Fig]("+image_url+")")
-                htmls.append("\n")
+            # # TODO 往md文档中插入论文里的像素最大的一张图片，这个方案可以弄的更加智能一些：
+            # first_image, ext = paper.get_image_path()
+            # if first_image is None or self.gitee_key == '':
+            #     pass
+            # else:
+            #     image_title = self.validateTitle(paper.title)
+            #     image_url = self.upload_gitee(image_path=first_image, image_name=image_title, ext=ext)
+            #     htmls.append("\n")
+            #     htmls.append("![Fig]("+image_url+")")
+            #     htmls.append("\n")
+            #
+
             # 第二步总结方法：
             # TODO，由于有些文章的方法章节名是算法名，所以简单的通过关键词来筛选，很难获取，后面需要用其他的方案去优化。
             method_key = ''
@@ -469,6 +471,23 @@ class Reader:
             # chat_conclusion_text = self.chat_conclusion(text=text, key=str(key))
             # htmls.append(chat_conclusion_text)
             # htmls.append("\n")
+            experiment_text = ''
+            experiment_key = ''
+            review_text = "<summary>" + chat_summary_text + "\n <Method summary>:\n" + chat_method_text
+            for parse_key in paper.section_text_dict.keys():
+                if 'Experiments' in parse_key.lower() or 'Results' in parse_key.lower():
+                    experiment_key = parse_key
+                    break
+            if experiment_key != '':
+                # conclusion
+                experiment_text += paper.section_text_dict[experiment_key]
+                max_token = 2500 * 4
+                text = review_text + "\n <Experiments>:\n" + experiment_text
+            else:
+                text = review_text
+            text = text[:max_token]
+
+
             chat_review_text = self.chat_review(text=text, key=str(key))
             htmls.append(chat_review_text)
             htmls.append("\n")