Upload app.py

app.py

@@ -8,10 +8,13 @@
     from matplotlib.font_manager import FontProperties
     myfont=FontProperties(fname='/Users/yunshi/Downloads/360Data/Data Center/Working-On Task/演讲与培训/2023ChatGPT/Coding/code_interpreter/rawdata/SimHei.ttf')
     sns.set_style('whitegrid',{'font.sans-serif':['simhei','Arial']})      
-
+1. app.py:
+    1. openai key, bing key.
+    1. proxy
+    1. 
 
 '''
-# TODO：solve the data analysi model issue. 
+# TODO：1. remove the table display in the second round. 2. 
 
 import requests
 from codeinterpreterapi import CodeInterpreterSession, File
@@ -78,25 +81,8 @@ def upload_file(uploaded_file):
             # ! 必须用这种格式读入内容，然后才可以写入temporary文件夹中。
             # output_temporary_file.write(uploaded_file.getvalue())
             output_temporary_file.write(uploaded_file.getvalue())
-            # st.write(uploaded_file_path)  # * 可以查看文件是否真实存在，然后是否可以
-            
-            # output_temporary_file.close()
-            # new_file = tempfile.NamedTemporaryFile(delete=False)
-            # new_file.write(uploaded_file.getvalue())
-
-            # os.write(output_temporary_file, uploaded_file.getvalue())
-            # temp_file = tempfile.NamedTemporaryFile(dir=str(uploaded_file_path), delete=False)
-
 
-        st.write('Now file saved successfully.')
-        # sleep(1000)
-        # fd = os.open(uploaded_file_path, os.O_WRONLY)
-        # os.write(fd, uploaded_file.getvalue())
-        # os.close(fd)
-
-        # return uploaded_file_path
-        # return new_file
-        # return new_file
+        return None
 
 
 bing_search_api_key = os.environ['bing_api_key']
@@ -161,68 +147,6 @@ async def text_mode():
             message_placeholder = st.empty()
             full_response = ""
 
-            # if radio_2 == '数据分析模式':
-            #     print('数据分析模式启动！')
-            #     with st.chat_message("assistant"):
-            #         # message_placeholder = st.empty()
-            #         # full_response = ""
-            #         async with CodeInterpreterSession() as session:
-            #             # user_request = "对于文件中的'SepalLengthCm’数据给我一个'直方图'，提供图表，并给出分析结果"
-            #             #! 可以用设定dpi=300来输出高质量的图表。（注：图的解析度dpi设定为300）
-            #             environ_settings = """【背景要求】如果我没有告诉你任何定制化的要求，那么请你按照以下的默认要求来回答：
-            #             -------------------------------------------------------------------------
-            #             1. 你需要用提问的语言来回答（如：中文提问你就用中文来回答，英文提问你就用英文来回答）。
-            #             2. 如果要求你输出图表，那么图的解析度dpi需要设定为300。图尽量使用seaborn库。seaborn库的参数设定：sns.set(rc={'axes.facecolor':'#FFF9ED','figure.facecolor':'#FFF9ED'}, palette='dark'。
-            #             3. 如果需要显示中文，那么设置如下：
-            #                 3.1 首先，你需要安装中文字体：
-            #                     myfont=FontProperties(fname='/Users/yunshi/Downloads/360Data/Data Center/Working-On Task/演讲与培训/2023ChatGPT/Coding/code_interpreter/rawdata/SimHei.ttf')
-            #                 3.2 然后，你需要设定在matplotlib（plt）和seaborn（sns）中设定：
-            #                         sns.set_style({'font.sans-serif':['Arial','SimHei']})
-            #                         plt.rcParams['font.sans-serif'] = ['SimHei'] 
-            #                         plt.rcParams['font.family']='sans-serif'
-            #                         plt.title(fontsize = 18)
-            #             -------------------------------------------------------------------------
-            #             """  # seaborn中的palette参数可以设定图表的颜色,选项包括：deep, muted, pastel, bright, dark, colorblind，Spectral。更多参数可以参考：https://seaborn.pydata.org/generated/seaborn.color_palette.html。
-
-            #             uploaded_file_path = upload_file()
-                        
-            #             user_request = environ_settings + "\n\n" + \
-            #                 "你需要完成以下任务：\n\n" + prompt + \
-            #                 f"注：文件位置在{uploaded_file_path}"
-            #             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))]
-
-            #             with st.status('thinking...', expanded=True, state='running') as status:
-            #                 # generate the response
-            #                 response = await session.generate_response(
-            #                     user_request, files=files
-            #                 )
-
-            #                 # output to the user
-            #                 print("AI: ", response.content)
-            #                 full_response = response.content
-            #                 ### full_response = "this is full response"
-
-            #                 # for file in response.files:
-            #                 for i, file in enumerate(response.files):
-            #                     # await file.asave(f"/Users/yunshi/Downloads/360Data/Data Center/Working-On Task/演讲与培训/2023ChatGPT/Coding/code_interpreter/output{i}.png") ##working.
-            #                     # st.image(file.get_image()) #! working.
-            #                     # * 注意这里的设定，可以提高图片的精细程度。
-            #                     st.image(file.get_image(), width=None,
-            #                              output_format='PNG')
-
-            #                 # message_placeholder.markdown(full_response + "▌") ## orignal code.
-            #             # message_placeholder.markdown(full_response) ## orignal code.
-            #             st.write(full_response)
-            #             status.update(label='complete', state='complete')
-            #             # st.session_state.messages.append(
-            #             #     {"role": "assistant", "content": full_response})
-
-            #             await session.astop()  # ! 确认需要关闭。
-            #     # st.session_state.messages.append({"role": "assistant", "content": full_response})
-
             if radio_2 == '联网模式':
                 # print('联网模式入口，prompt:', prompt)
                 input_message = prompt
@@ -273,13 +197,12 @@ async def text_mode():
                 {"role": "assistant", "content": full_response})
 
 
-async def data_mode(uploaded_file_path):
-    print('数据分析模式启动！')
+async def data_mode():
+    # print('数据分析模式启动！')
     uploaded_file_path = './upload.csv'
-    ## TODO: validate the existence of uploaded file. 
     # st.write(f"passed file path in data_mode: {uploaded_file_path}")
-    tmp1 = pd.read_csv('./upload.csv')
-    st.write(tmp1[:5])
+    # tmp1 = pd.read_csv('./upload.csv')
+    # st.write(tmp1[:5])
 
     # Initialize chat history
     if "messages" not in st.session_state:
@@ -309,14 +232,7 @@ async def data_mode(uploaded_file_path):
                 -------------------------------------------------------------------------
                 1. 你需要用提问的语言来回答（如：中文提问你就用中文来回答，英文提问你就用英文来回答）。
                 2. 如果要求你输出图表，那么图的解析度dpi需要设定为300。图尽量使用seaborn库。seaborn库的参数设定：sns.set(rc={'axes.facecolor':'#FFF9ED','figure.facecolor':'#FFF9ED'}, palette='dark'。
-                3. 如果需要显示中文，那么设置如下：
-                    3.1 首先，你需要安装中文字体：
-                        myfont=FontProperties(fname='/Users/yunshi/Downloads/360Data/Data Center/Working-On Task/演讲与培训/2023ChatGPT/Coding/code_interpreter/rawdata/SimHei.ttf')
-                    3.2 然后，你需要设定在matplotlib（plt）和seaborn（sns）中设定：
-                            sns.set_style({'font.sans-serif':['Arial','SimHei']})
-                            plt.rcParams['font.sans-serif'] = ['SimHei'] 
-                            plt.rcParams['font.family']='sans-serif'
-                            plt.title(fontsize = 18)
+                3. 表上的字体全部用<英文English>来表示。
                 -------------------------------------------------------------------------
                 """  # seaborn中的palette参数可以设定图表的颜色,选项包括：deep, muted, pastel, bright, dark, colorblind，Spectral。更多参数可以参考：https://seaborn.pydata.org/generated/seaborn.color_palette.html。
 
@@ -371,7 +287,7 @@ if __name__ == "__main__":
         ## 默认状态下没有上传文件，None，会报错。需要判断。
         if uploaded_file is not None:
             uploaded_file_path = upload_file(uploaded_file)
-            asyncio.run(data_mode(uploaded_file_path))
+            asyncio.run(data_mode())