Upload 4 files

batch_query.py

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+from sdoc_request import get_tianshu_response
+import pandas as pd
+import time
+import json
+
+# 问题数据导入
+sdoc_df = pd.read_excel("sdoc直播观众提问和回复.xlsx")
+questions = sdoc_df["描述"].to_list()
+
+# AI智能分析
+categories = []
+modules = []
+summaries = []
+
+for qs in 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": ''}
+            print("not json!")
+    else:
+        result = {"类别":'', "模块":'', "问题归类": ''}
+    print("question:", qs)
+    print("answer:", result)
+    categories.append(result["类别"])
+    modules.append(result["模块"])
+    summaries.append(result["问题归类"])
+
+# 结果数据整理
+sdoc_df['类别'] = categories
+sdoc_df['模块'] = modules
+sdoc_df['问题归类'] = summaries
+
+sdoc_df.to_excel("smart_analysis.xlsx", index=0)

sdoc_request.py

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+from tianshu import AiHelperClient, generate_serial_number
+
+def get_tianshu_response(params):
+    # 请求地址
+    base_url = "https://api-aihelper.sheincorp.cn"
+    # 流水号，非必填，请求幂等处理，方便后续请求跟踪
+    out_id = generate_serial_number()
+    # 应用秘钥，必填
+    app_secret = "120a6f8685f8652ace71f7a2b0f2d395"
+    # 应用id，必填
+    scene_id = 7180
+    # 业务编码，对应系统编码或工号，必填
+    biz_code = "10270178"
+    # 构建请求客户端
+    client = AiHelperClient(base_url, app_secret, scene_id)
+    # 构建请求参数
+    # params = {"HOA_USERINPUT": "在线表格可以 @人吗"}
+
+
+    response = client.post("/open/v1/chat", {
+        # "out_id": out_id,
+        "scene_id": scene_id,
+        "biz_code": biz_code,
+        "params": params
+    })
+    result = response["info"].get("info")
+
+    return result
+
+
+# if response is not None:
+#     result = response["info"].get("info")
+#     try:
+#         json_result = json.loads(result)
+#         print(json_result["类别"])
+#         print(json_result["模块"])
+#     except json.JSONDecodeError:
+#         print("not json!")
+# else:
+#     print("request error!")
+
+params = {"question": "SDOC的表格，我已经建了个在线表格，我要插入一个本地EX表，从企微文档迁移过来是在的，但我在上面操作，上传不了新的"}
+get_tianshu_response(params)

streamlit_sdoc_analysis.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"
+        )
+    

tianshu.py

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+import requests
+import hashlib
+import hmac
+import base64
+import time
+import uuid
+import random
+  
+# 生成流水号
+def generate_serial_number():
+    uid = uuid.uuid4()
+    serial_number = uid.hex[:32]
+    return serial_number
+  
+# 获取随机码
+def generate_random_code(length=5):
+    characters = "abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789"
+    code = ""
+    for _ in range(length):
+        code += random.choice(characters)
+    return code
+  
+# 生成签名和时间戳
+def generate_signature(scene_id, request_path, app_secret, random_key):
+    timestamp = str(int(time.time() * 1000))
+    sign_string = f"{scene_id}&{timestamp}&{request_path}"
+    secret_key = app_secret + random_key
+    hmac_sha256 = hmac.new(
+      secret_key.encode(), 
+      sign_string.encode(),
+      hashlib.sha256
+    ).hexdigest().encode()
+    signature = random_key + base64.b64encode(hmac_sha256).decode()
+    return signature, timestamp
+  
+class AiHelperClient:
+    def __init__(self, base_url, app_secret, scene_id):
+        self.base_url = base_url
+        self.app_secret = app_secret
+        self.random_key = generate_random_code()
+        self.scene_id = scene_id
+        self.session = requests.Session()
+  
+    def post(self, endpoint, data):
+        signature, timestamp = generate_signature(
+            self.scene_id,
+            endpoint,
+            self.app_secret,
+            self.random_key
+        )
+  
+        url = f"{self.base_url}{endpoint}"
+        headers = {
+            'Content-Type': 'application/json',
+            'x-signature': signature,
+            'x-timestamp': timestamp
+        }
+  
+        try:
+            response = self.session.post(url, json=data, headers=headers)
+            response.raise_for_status()
+            return response.json()
+        except requests.RequestException as e:
+            return None