Upload app.py

app.py

@@ -9,9 +9,11 @@
     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']})      
 
+
 '''
-# TODO：
+# TODO：solve the data analysi model issue. 
 
+import requests
 from codeinterpreterapi import CodeInterpreterSession, File
 import streamlit as st
 from codeinterpreterapi import CodeInterpreterSession
@@ -20,7 +22,6 @@ import os
 import matplotlib.pyplot as plt
 import xlrd
 import pandas as pd
-# from io import StringIO
 # import csv
 import tempfile
 from tempfile import NamedTemporaryFile
@@ -29,55 +30,66 @@ from pathlib import Path
 from matplotlib.font_manager import FontProperties
 import seaborn as sns
 
-
-os.environ["OPENAI_API_KEY"] = os.environ['user_token']
-openai.api_key = os.environ['user_token']
-os.environ["VERBOSE"] = "True"  # 可以看到具体的错误？
+os.environ["OPENAI_API_KEY"] = "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"
+openai.api_key = "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"
+# os.environ["OPENAI_API_KEY"] = "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" ## Carrie
+# openai.api_key = "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" ## Carrie
+# 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"
-# }
+openai.proxy = {
+    "http": "http://127.0.0.1:7890",
+            "https": "http://127.0.0.1:7890"
+}
 
 # layout settings.
 st.title("个人大语言模型商业智能中心")
 st.subheader("Artificial Intelligence Backend Center for Individuals")
-# col1, col2 = st.columns(spec=[1, 2])
-# radio_1 = col1.radio(label='ChatGPT版本', options=[
-#     'GPT-3.5', 'GPT-4.0'], horizontal=True, label_visibility='visible')
-# radio_2 = col2.radio(label='模式选择', options=[
-#     '核心模式', '联网模式', '数据模式'], horizontal=True, label_visibility='visible')
-
-uploaded_file = st.file_uploader(
-    "选择一个文件", type=(["csv", "xlsx", "xls"]))
-
-if uploaded_file is not None:
-    filename=uploaded_file.name
-    # st.write(filename) ## print out the whole file name to validate. 
-    try:
-        if '.csv' in filename:
-            csv_file = pd.read_csv(uploaded_file)
-            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)
-            st.write(xls_file[:3])
-    except Exception as e:
-        st.write(e)
-
-    uploaded_file_name = "File_provided"
-    temp_dir = tempfile.TemporaryDirectory()
-    # ! working.
-    uploaded_file_path = pathlib.Path(temp_dir.name) / uploaded_file_name
-    with open(uploaded_file_path, 'wb') as output_temporary_file:
-        # output_temporary_file.write(uploaded_file.read())
-        # ! 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())
-        st.write(uploaded_file_path)  # * 可以查看文件是否真实存在，然后是否可以
 
-import requests
-bing_search_api_key = os.environ['bing_api_key']
-bing_search_endpoint = 'https://api.bing.microsoft.com/v7.0/search' 
+# tab1, tab2 = st.tabs(["传统模式", "数据模型"])
+
+# with tab1:
+col1, col2 = st.columns(spec=[1, 2])
+radio_1 = col1.radio(label='ChatGPT版本', options=[
+    'GPT-3.5', 'GPT-4.0'], horizontal=True, label_visibility='visible')
+radio_2 = col2.radio(label='模式选择', options=[
+    '核心模式', '联网模式', '数据模式'], horizontal=True, label_visibility='visible')
+
+# with tab2:
+def upload_file(uploaded_file):
+    # uploaded_file = st.file_uploader(
+    #     "选择一个文件", type=(["csv", "xlsx", "xls"]))
+    if uploaded_file is not None:
+        filename = uploaded_file.name
+        st.write(filename) ## print out the whole file name to validate.
+        try:
+            if '.csv' in filename:
+                csv_file = pd.read_csv(uploaded_file)
+                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)
+                st.write(xls_file[:3])
+        except Exception as e:
+            st.write(e)
+
+        uploaded_file_name = "File_provided"
+        temp_dir = tempfile.TemporaryDirectory()
+        # ! working.
+        uploaded_file_path = pathlib.Path(temp_dir.name) / uploaded_file_name
+        with open(uploaded_file_path, 'wb') as output_temporary_file:
+            # output_temporary_file.write(uploaded_file.read())
+            # ! 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())
+            st.write(uploaded_file_path)  # * 可以查看文件是否真实存在，���后是否可以
+            output_temporary_file.close()
+
+            return uploaded_file_path
+
+
+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'
@@ -87,7 +99,8 @@ def search(query):
 
     # Call the API
     try:
-        response = requests.get(bing_search_endpoint, headers=headers, params=params)
+        response = requests.get(bing_search_endpoint,
+                                headers=headers, params=params)
         response.raise_for_status()
         json = response.json()
         return json["webPages"]["value"]
@@ -99,18 +112,12 @@ def search(query):
 # openai.api_key = st.secrets["OPENAI_API_KEY"]
 
 # async def main():
-async def main():
-    col1, col2 = st.columns(spec=[1, 2])
-    radio_1 = col1.radio(label='ChatGPT版本', options=[
-    'GPT-3.5', 'GPT-4.0'], horizontal=True, label_visibility='visible')
-    radio_2 = col2.radio(label='模式选择', options=[
-    '核心模式', '联网模式', '数据模式'], horizontal=True, label_visibility='visible')
-
-    ## Set a default model
+async def text_mode():
+    # Set a default model
     if "openai_model" not in st.session_state:
         st.session_state["openai_model"] = "gpt-3.5-turbo-16k"
-
     if radio_1 == 'GPT-3.5':
+        # print('----------'*5)
         print('radio_1: GPT-3.5 starts!')
         st.session_state["openai_model"] = "gpt-3.5-turbo-16k"
     else:
@@ -127,7 +134,12 @@ async def main():
             st.markdown(message["content"])
 
     # Display assistant response in chat message container
-    if prompt := st.chat_input("Ask something?"):
+    # if prompt := st.chat_input("Say something"):
+    prompt = st.chat_input("Say something")
+    print('prompt now:', prompt)
+    print('----------'*5)
+    # if prompt:
+    if prompt:
         st.session_state.messages.append({"role": "user", "content": prompt})
         with st.chat_message("user"):
             st.markdown(prompt)
@@ -136,79 +148,81 @@ async def main():
             message_placeholder = st.empty()
             full_response = ""
 
-            if radio_2 == '数据分析模式':
-                print('数据分析模式启动！')
-
-                # clear cache to avoid any potential history problems. 
-                st.cache_resource.clear()
-
-                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。
-
-                        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('processing...', 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})
-
-            elif radio_2 == '联网模式':
+            # 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
                 internet_search_result = search(input_message)
-                search_prompt = [f"Source:\nTitle: {result['name']}\nURL: {result['url']}\nContent: {result['snippet']}" for result in internet_search_result]
-                prompt = "基于如下的互联网公开信息, 回答问题:\n\n" + "\n\n".join(search_prompt[:3]) + "\n\n问题: " + input_message + "你需要注意的是回答问题时必须用提问的语言（如英文或者中文）来提示：'答案基于互联网公开信息。'" + "\n\n答案: " ## 限制了只有3个搜索结果。
-                # prompt = "Use these sources to answer the question:\n\n" + "\n\n".join(search_prompt[0:3]) + "\n\nQuestion: " + input_message + "（注意：回答问题时请提示'以下答案基于互联网公开信息。'）\n\n" + "\n\nAnswer: " 
+                search_prompt = [
+                    f"Source:\nTitle: {result['name']}\nURL: {result['url']}\nContent: {result['snippet']}" for result in internet_search_result]
+                prompt = "基于如下的互联网公开信息, 回答问题:\n\n" + \
+                    "\n\n".join(search_prompt[:3]) + "\n\n问题: " + input_message + \
+                    "你需要注意的是回答问题时必须用提问的语言（如英文或者中文）来提示：'答案基于互联网公开信息。'" + "\n\n答案: "  # 限制了只有3个搜索结果。
+                # prompt = "Use these sources to answer the question:\n\n" + "\n\n".join(search_prompt[0:3]) + "\n\nQuestion: " + input_message + "（注意：回答问题时请提示'以下答案基于互联网公开信息。'）\n\n" + "\n\nAnswer: "
 
-                st.session_state.messages.append({"role": "user", "content": prompt})
+                st.session_state.messages.append(
+                    {"role": "user", "content": prompt})
 
                 for response in openai.ChatCompletion.create(
                     model=st.session_state["openai_model"],
@@ -218,34 +232,134 @@ async def main():
                     ],
                     stream=True,
                 ):
-                    full_response += response.choices[0].delta.get("content", "")
+                    full_response += response.choices[0].delta.get(
+                        "content", "")
                     message_placeholder.markdown(full_response + "▌")
                 message_placeholder.markdown(full_response)
                 st.session_state.messages.append(
                     {"role": "assistant", "content": full_response})
 
-            elif radio_2 == '核心模式':
+            if radio_2 == '核心模式':
                 print('GPT only starts!!!')
-                print('st.session_state now:', st.session_state)
-                # st.session_state.messages.append({"role": "system", "content": 'You are a helpful AI assistant: ChatGPT.'})
-                
+                print('messages:', st.session_state['messages'])
                 for response in openai.ChatCompletion.create(
                     model=st.session_state["openai_model"],
-                    messages=[
-                        {"role": m["role"], "content": m["content"]}
-                        for m in st.session_state.messages
-                    ],
+                    # messages=[
+                    #     {"role": m["role"], "content": m["content"]}
+                    #     for m in st.session_state.messages
+                    # ],
+                    messages=[{'role': 'system', 'content': 'you are ChatGPT'}, {'role': 'user', 'content': prompt}],
                     stream=True,
                 ):
-                    # if len(response)>0:
-                    full_response += response.choices[0].delta.get("content", "")
+                    full_response += response.choices[0].delta.get(
+                        "content", "")
                     message_placeholder.markdown(full_response + "▌")
+                    print('session completed!')
                 message_placeholder.markdown(full_response)
             st.session_state.messages.append(
                 {"role": "assistant", "content": full_response})
+
+
+async def data_mode(uploaded_file_path):
+    print('数据分析模式启动！')
+
+    ## TODO: validate the existence of uploaded file. 
+    st.write(uploaded_file_path)
+    tmp1 = pd.read_csv(str(uploaded_file_path))
+    st.write(tmp1[:5])
+
+    # Initialize chat history
+    if "messages" not in st.session_state:
+        st.session_state.messages = []
+
+    # Display chat messages from history on app rerun
+    for message in st.session_state.messages:
+        with st.chat_message(message["role"]):
+            st.markdown(message["content"])
+
+    # Display assistant response in chat message container
+    # if prompt := st.chat_input("Say something"):
+    prompt = st.chat_input("Say something")
+    print('prompt now:', prompt)
+    print('----------'*5)
+    # if prompt:
+    if prompt:
+        st.session_state.messages.append({"role": "user", "content": prompt})
+        with st.chat_message("user"):
+            st.markdown(prompt)
+
+        with st.chat_message("assistant"):
+            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 + "\n\n" \
+                    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 __name__ == "__main__":
     import asyncio
-    # * 也可以用命令执行这个python文件。’streamlit run frontend/app.py‘
-    asyncio.run(main())
+    if radio_2 != "数据模式":
+        # * 也可以用命令执行这个python文件。’streamlit run frontend/app.py‘
+        asyncio.run(text_mode())
+        # upload_file()
+    elif radio_2 == "数据模式":
+        uploaded_file = st.file_uploader(
+        "选择一个文件", type=(["csv", "xlsx", "xls"]))
+        ## 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))
+        
+
+
+