Create app.py

app.py

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+import streamlit as st
+from sdoc_request import get_tianshu_response
+import pandas as pd
+import time
+import json
+
+# 设置页面标题
+st.title("SDoc 问题智能分析")
+
+# 创建文件上传组件
+st.text("1. 少量问题，请访问链接提问。")
+st.markdown("https://aiapi.sheincorp.cn/llm/#/scene/general_app/7180")
+
+uploaded_file = st.file_uploader("2. 大量问题，请上传 Excel 文件，必须含有【问题描述】字段。", type=["xlsx"])
+
+if uploaded_file is not None:
+    # 读取上传的 Excel 文件
+    sdoc_df = pd.read_excel(uploaded_file)
+    questions = sdoc_df["问题描述"].to_list()
+
+    # AI 智能分析
+    categories = []
+    modules = []
+    summaries = []
+
+    # 创建进度条
+    progress_bar = st.progress(0)
+    total_questions = len(questions)
+
+    for i, qs in enumerate(questions):
+        if qs and len(qs) > 0:
+            time.sleep(1)
+            params = {"HOA_USERINPUT": qs}
+            temp_result = get_tianshu_response(params)
+            try:
+                result = json.loads(temp_result)
+            except json.JSONDecodeError:
+                result = {"类别": '', "模块": '', "问题归类": ''}
+                st.warning(f"问题 '{qs}' 的返回结果不是有效的 JSON 格式。")
+        else:
+            result = {"类别": '', "模块": '', "问题归类": ''}
+
+        st.write(f"问题{i+1}: {qs}")
+        st.write(f"答案: {result}")
+
+        categories.append(result.get("类别"))
+        modules.append(result.get("模块"))
+        summaries.append(result.get("问题归类"))
+
+        # 更新进度条
+        progress_bar.progress((i + 1) / total_questions)
+
+    # 结果数据整理
+    sdoc_df['类别'] = categories
+    sdoc_df['模块'] = modules
+    sdoc_df['问题归类'] = summaries
+
+    # 将结果保存为 Excel 文件
+    output_file = "smart_analysis.xlsx"
+    sdoc_df.to_excel(output_file, index=0)
+
+    # 创建下载链接
+    with open(output_file, "rb") as file:
+        btn = st.download_button(
+            label="下载分析结果",
+            data=file,
+            file_name="smart_analysis.xlsx",
+            mime="application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
+        )
+