Upload app.py

app.py

@@ -24,7 +24,7 @@ from deta import Deta  # pip3 install deta
 import requests
 from codeinterpreterapi import CodeInterpreterSession, File
 import streamlit as st
-from codeinterpreterapi import CodeInterpreterSession
+# from codeinterpreterapi import CodeInterpreterSession
 import openai
 import os
 import matplotlib.pyplot as plt
@@ -50,15 +50,15 @@ import PyPDF2 ## read the local_KB PDF file.
 import save_database_info
 from datetime import datetime
 
-os.environ["OPENAI_API_KEY"] = os.environ['user_token']
-openai.api_key = os.environ['user_token']
+os.environ["OPENAI_API_KEY"] = "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"
+openai.api_key = "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"
 # os.environ["VERBOSE"] = "True"  # 可以看到具体的错误？
 
-# #* 如果碰到接口问题，可以启用如下设置。
-# openai.proxy = {
-#     "http": "http://127.0.0.1:7890",
-#             "https": "http://127.0.0.1:7890"
-# }
+#* 如果碰到接口问题，可以启用如下设置。
+openai.proxy = {
+    "http": "http://127.0.0.1:7890",
+            "https": "http://127.0.0.1:7890"
+}
 
 
 # layout settings.
@@ -146,11 +146,9 @@ def clear_all():
 
 #         return None
 
-
-bing_search_api_key = os.environ['bing_api_key']
+bing_search_api_key = '1fbcda1fb09547efbcdae7cb83a367b5'
 bing_search_endpoint = 'https://api.bing.microsoft.com/v7.0/search'
 
-
 def search(query):
     # Construct a request
     # mkt = 'en-EN'
@@ -264,10 +262,11 @@ async def text_mode():
 # async def localKB_mode():
 def localKB_mode(username):
     ### clear all the prior conversation.
-    st.session_state.conversation = None
-    st.session_state.chat_history = None
-    st.session_state.messages = []
-    message_placeholder = st.empty()
+    # st.session_state.conversation = None
+    # st.session_state.chat_history = None
+    # st.session_state.messages = []
+    # message_placeholder = st.empty()
+    clear_all() ## reset the conversation.
 
     print('now starts the local KB version of ChatGPT')
     # Initialize chat history
@@ -346,12 +345,16 @@ def localKB_mode(username):
 
 async def data_mode():
     print('数据分析模式启动！')
+    clear_all() ## reset the conversation.
     # uploaded_file_path = './upload.csv'
-    # uploaded_file_path = f'./{joejoe}_upload.csv'
     uploaded_file_path = f'./{username}_upload.csv'
-    # # st.write(f"passed file path in data_mode: {uploaded_file_path}")
-    # tmp1 = pd.read_csv('./upload.csv')
-    # st.write(tmp1[:5])
+    # uploaded_file_path = "/Users/yunshi/Downloads/360Data/Data Center/Working-On Task/演讲与培训/2023ChatGPT/Coding/code_interpreter/test_upload.csv"
+    print('file path:', uploaded_file_path)
+    
+    # st.write(f"passed file path in data_mode: {uploaded_file_path}")
+    tmp1 = pd.read_csv(uploaded_file_path)
+    st.markdown('成功启动数据模式，以下是加载的文件内容')
+    st.write(tmp1[:5])
 
     # Initialize chat history
     if "messages" not in st.session_state:
@@ -395,17 +398,21 @@ async def data_mode():
 
                 user_request = environ_settings + "\n\n" + \
                     "你需要完成以下任务：\n\n" + prompt + "\n\n" \
-                    f"注：文件位置在{uploaded_file_path}"
+                    f"注：文件位置在 {uploaded_file_path}"
+                user_request = str(prompt)
                 print('user_request: \n', user_request)
 
                 # 加载上传的文件，主要路径在上面代码中。
-                files = [File.from_path(str(uploaded_file_path))]
+                # files = [File.from_path(str(uploaded_file_path))]
+                files = [File.from_path("/Users/yunshi/Downloads/360Data/Data Center/Working-On Task/演讲与培训/2023ChatGPT/Coding/code_interpreter/rawdata/short_csv.csv")]
+                st.write(pd.DataFrame(files))
+                # print('session.__init__', session.__init__)
+                # print('session', session.__init__)
 
                 with st.status('Thinking...', expanded=True, state='running') as status:
                     # generate the response
-                    response = await session.generate_response(
-                        user_request, files=files
-                    )
+                    # response = await session.generate_response(user_msg=user_request, files=files, detailed_error=True)
+                    response = await session.generate_response(user_msg=user_request, files=files, detailed_error=True)
 
                     # output to the user
                     print("AI: ", response.content)
@@ -436,7 +443,7 @@ async def data_mode():
 ### authentication with a local yaml file.
 import yaml
 from yaml.loader import SafeLoader
-with open('./config.yaml') as file:
+with open('/Users/yunshi/Downloads/360Data/Data Center/Working-On Task/演讲与培训/2023ChatGPT/Coding/code_interpreter/config.yaml') as file:
     config = yaml.load(file, Loader=SafeLoader)
 authenticator = stauth.Authenticate(
     config['credentials'],
@@ -609,24 +616,25 @@ def upload_file(uploaded_file):
                     import localKB_construct
                     # st.write(upload_file)
                     localKB_construct.process_file(uploaded_file, username)
+                    ## 在屏幕上展示当前知识库的信息，包括名字和加载日期。
                     save_database_info.save_database_info(f'./{username}/database_name.csv', filename, str(datetime.now().strftime("%Y-%m-%d %H:%M")))
-                    st.markdown('新知识库解析成功，请务必刷新页面，然后开启对话 🔁')
+                    st.markdown('新知识库解析成功，请务必刷新页面，然后开启对话 🔃')
                     # spinner = st.empty()
 
             else:
                 if '.csv' in filename:
                     csv_file = pd.read_csv(uploaded_file)
-                    csv_file.to_csv(f'./{username}/upload.csv', encoding='utf-8', index=False)
+                    csv_file.to_csv(f'./{username}_upload.csv', encoding='utf-8', index=False)
                     st.write(csv_file[:3])  # 这里只是显示文件，后面需要定位文件所在的绝对路径。
                 else:
                     xls_file = pd.read_excel(uploaded_file)
-                    xls_file.to_csv(f'./{username}/upload.csv', index=False)
+                    xls_file.to_csv(f'./{username}_upload.csv', index=False)
                     st.write(xls_file[:3])
 
                 uploaded_file_name = "File_provided"
                 temp_dir = tempfile.TemporaryDirectory()
                 # ! working.
-                uploaded_file_path = pathlib.Path(temp_dir.name) / uploaded_file_name
+                # uploaded_file_path = pathlib.Path(temp_dir.name) / uploaded_file_name
                 # with open('./upload.csv', 'wb') as output_temporary_file:
                 with open(f'./{username}_upload.csv', 'wb') as output_temporary_file:
                     # print(f'./{name}_upload.csv')
@@ -685,9 +693,6 @@ if __name__ == "__main__":
             if uploaded_file is not None:
                 # uploaded_file_path = upload_file(uploaded_file)
                 upload_file(uploaded_file)
-                # st.write('PDF file uploaded sucessfully!')
-                # clear_all()
-                # spinner = st.empty()
 
             localKB_mode(username)
             # asyncio.run(localKB_mode())