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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"
)
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