ChatGPT Code Interpreterクローンを試す（SlashGPT編）

$ pyenv virtualenv 3.10.11 SlashGPT
$ git clone https://github.com/snakajima/SlashGPT && cd SlashGPT
$ pyenv local SlashGPT
$ pip install -r requirements.txt

Collecting pyobjc-framework-CoreData==9.2
(snip)
      FileNotFoundError: [Errno 2] No such file or directory: '/usr/bin/sw_vers'
      [end of output]

pyobjc; sys_platform == 'darwin' 

$ pip install -r requirements.txt

OPENAI_API_KEY=XXXXX

$ ./SlashGPT.py
playsound is relying on another python subprocess. Please use `pip install pygobject` if you want playsound to run more efficiently.
System Slashes: /root, /bye, /new, /prompt, /sample, /help, ...
Activating: Main Dispatcher
Dispatcher: I am a dispatcher agent. I will find the right agent for your question, and let it answer.
You(dispatcher):

You(dispatcher): /help

/root:      Start from the scratch (going back to dispatcher)
/bye:       Terminate the app
/new:       Start a new chat session
/prompt:    Display the current prompt
/history:   Display the chat history
/sample:    Make the sample request
/gpt3:      Switch the model to gpt-3.5-turbo-0613
/gpt31:     Switch the model to gpt-3.5-turbo-16k-0613
/gpt4:      Switch the model to gpt-4-0613
/palm:      Switch the model to Google PaLM
/llama2:    Switch the model to LlaMA2 7b
/llama270:  Switch the model to LlaMA2 70b
/vicuna:    Switch the model to Vicuna 16b
/verbose:   Toggle verbose switch
/roles1:    Switch the manifest set to ones in prompts (original)
/roles2:    Switch the manifest set to ones in roles2

Agents:
/aiagents     AI Agents
/browser      Internet Browser
/cal          Calendar
/cook         Home Cooking System
/currency     Currency Converter
/definitive   Definitive Facts
/dispatcher   Main Dispatcher
/dot          DOT language expert
/drone2       Drone Pilot
/home2        Home Automation
/jupyter      Jupyter Notebook with GPT3.5
/jupyter2     Jupyter Notebook with Llamma2
/jupyter_map  Jupyter Notebook with GPT3.5
/jupyter_vicu Jupyter Notebook with Vicuna 16b
/jupyterp     Jupyter Notebook with Palm
/kayak        Kayak (not accessible yet)
/names        名前判別
/news2        News News
/noteable     WIP: Noteable
/weather      Open Weather
/webpilot     Web Pilot AI
/wolfram      Wolfram
/worldnews    World News

You(dispatcher): こんにちは
Dispatcher: こんにちは！ご質問やお困りごとがありましたら、どうぞお気軽にお聞きください。

You(jupyter): pythonで簡単なグラフを書いてください。
{
  "name": "run_python_code",
  "arguments": {
    "code": [
      "import matplotlib.pyplot as plt\n",
      "\n",
      "x = [1, 2, 3, 4, 5]\n",
      "y = [2, 4, 6, 8, 10]\n",
      "\n",
      "plt.plot(x, y)\n",
      "plt.xlabel('X-axis')\n",
      "plt.ylabel('Y-axis')\n",
      "plt.title('Simple Graph')\n",
      "plt.show()"
    ],
    "query": "Simple graph"
  }
}
You(jupyter): グラフの描画はplotlyを使うようにしてください
{
  "name": "run_python_code",
  "arguments": {
    "code": [
      "import plotly.graph_objects as go",
      "",
      "x = [1, 2, 3, 4, 5]",
      "y = [2, 4, 6, 8, 10]",
      "",
      "fig = go.Figure(data=go.Scatter(x=x, y=y))",
      "fig.update_layout(title='Simple Graph', xaxis_title='X-axis', yaxis_title='Y-axis')",
      "fig.show()"
    ],
    "query": "Plot a simple graph using Plotly"
  }
}
function(run_python_code): ---------------------------------------------------------------------------
ModuleNotFoundError                       Traceback (most recent call last)
File <ipython-input-1-1e8f2813b45d>:1
----> 1 import plotly.graph_objects as go
      3 x = [1, 2, 3, 4, 5]
      4 y = [2, 4, 6, 8, 10]

ModuleNotFoundError: No module named 'plotly'

Jupyter: 申し訳ありませんが、現在の環境ではPlotlyがインストールされていないため、使用することができません。Matplotlibを使用してグラフを描画する方法を提供します。以下のコードをお試しください。

```Python
import matplotlib.pyplot as plt

x = [1, 2, 3, 4, 5]
y = [2, 4, 6, 8, 10]

plt.plot(x, y)
plt.xlabel('X-axis')
plt.ylabel('Y-axis')
plt.title('Simple Graph')
plt.show()
```
You(jupyter): plotlyをインストールしてください
Function python: Failed to load arguments as json
{
  "name": "python",
  "arguments": "!pip install plotly"
}
python function was called
function(python): Collecting plotly
  Using cached plotly-5.15.0-py2.py3-none-any.whl (15.5 MB)
Requirement already satisfied: packaging in /home/kun432/.pyenv/versions/3.10.11/envs/SlashGPT/lib/python3.10/site-packages (from plotly) (23.1)
Collecting tenacity>=6.2.0
  Using cached tenacity-8.2.2-py3-none-any.whl (24 kB)
Installing collected packages: tenacity, plotly
Successfully installed plotly-5.15.0 tenacity-8.2.2

[notice] A new release of pip is available: 23.0.1 -> 23.2.1
[notice] To update, run: python3.10 -m pip install --upgrade pip

Jupyter: Plotlyがインストールされましたので、以下のコードでグラフを描画できます。

```Python
import plotly.graph_objects as go

x = [1, 2, 3, 4, 5]
y = [2, 4, 6, 8, 10]

fig = go.Figure(data=go.Scatter(x=x, y=y))
fig.update_layout(title='Simple Graph', xaxis_title='X-axis', yaxis_title='Y-axis')
fig.show()
```
You(jupyter): では再度グラフの描画はplotlyを使うようにしてください
Function python: Failed to load arguments as json
{
  "name": "python",
  "arguments": "import plotly.graph_objects as go\n\nx = [1, 2, 3, 4, 5]\ny = [2, 4, 6, 8, 10]\n\nfig = go.Figure(data=go.Scatter(x=x, y=y))\nfig.update_layout(title='Simple Graph', xaxis_title='X-axis', yaxis_title='Y-axis')\nfig.show()"
}
python function was called

You(jupyter): /aiagents
Activating: AI Agents
You(aiagents): 明日の天気は
{
  "name": "aiagent",
  "arguments": {
    "goal": "\u660e\u65e5\u306e\u5929\u6c17\u3092\u6559\u3048\u3066\u304f\u3060\u3055\u3044"
  }
}
Got 500:<!doctype html>
<html lang=en>
<title>500 Internal Server Error</title>
<h1>Internal Server Error</h1>
<p>The server encountered an internal error and was unable to complete your request. Either the server is overloaded or there is an error in the application.</p>
 from https://ai-agents-plugin.vercel.app/aiagent?goal=%E6%98%8E%E6%97%A5%E3%81%AE%E5%A4%A9%E6%B0%97%E3%82%92%E6%95%99%E3%81%88%E3%81%A6%E3%81%8F%E3%81%A0%E3%81%95%E3%81%84
You(aiagents): 明日の天気は
{
  "name": "aiagent",
  "arguments": {
    "goal": "\u660e\u65e5\u306e\u5929\u6c17\u3092\u6559\u3048\u3066\u304f\u3060\u3055\u3044"
  }
}
function(aiagent): {"instructions":"READ the REQUEST and the RESPONSE. Perform the instructions specified in the RESPONSE based on the REQUEST given. Show the RESPONSE as well to the user.","request":"GOAL: \u660e\u65e5\u306e\u5929\u6c17\u3092\u6559\u3048\u3066\u304f\u3060\u3055\u3044","response":"1. \u5929\u6c17\u4e88\u5831\u306e\u60c5\u5831\u3092\u53d6\u5f97\u3059\u308b\u305f\u3081\u306b\u3001\u5929\u6c17\u4e88\u5831\u306e\u30a6\u30a7\u30d6\u30b5\u30a4\u30c8\u307e\u305f\u306f\u30a2\u30d7\u30ea\u3092\u958b\u3044\u3066\u304f\u3060\u3055\u3044\u3002\n2. \u30a6\u30a7\u30d6\u30b5\u30a4\u30c8\u307e\u305f\u306f\u30a2\u30d7\u30ea\u306e\u691c\u7d22\u30d0\u30fc\u306b\u3001\u660e\u65e5\u306e\u5929\u6c17\u3092\u8abf\u3079\u305f\u3044\u90fd\u5e02\u540d\u3092\u5165\u529b\u3057\u3066\u304f\u3060\u3055\u3044\u3002\n3. \u691c\u7d22\u7d50\u679c\u304c\u8868\u793a\u3055\u308c\u305f\u3089\u3001\u660e\u65e5\u306e\u5929\u6c17\u4e88\u5831\u3092\u30af\u30ea\u30c3\u30af\u307e\u305f\u306f\u30bf\u30c3\u30d7\u3057\u3066\u304f\u3060\u3055\u3044\u3002\n4. \u5929\u6c17\u4e88\u5831\u30da\u30fc\u30b8\u304c\u8868\u793a\u3055\u308c\u305f\u3089\u3001\u4ee5\u4e0b\u306e\u60c5\u5831\u3092\u78ba\u8a8d\u3057\u3066\u304f\u3060\u3055\u3044\uff1a\n   - \u660e\u65e5\u306e\u5929\u6c17\u306e\u6982\u8981\uff08\u6674\u308c\u3001\u66c7\u308a\u3001\u96e8\u306a\u3069\uff09\n   - \u660e\u65e5\u306e\u6700\u9ad8\u6c17\u6e29\u3068\u6700\u4f4e\u6c17\u6e29\n   - \u660e\u65e5\u306e\u964d\u6c34\u78ba\u7387\n   - \u660e\u65e5\u306e\u98a8\u901f\u3068\u98a8\u5411\u304d\n5. \u4e0a\u8a18\u306e\u60c5\u5831\u3092\u30e1\u30e2\u3057\u3066\u304f\u3060\u3055\u3044\u3002\n6. \u3082\u3057\u53ef\u80fd\u3067\u3042\u308c\u3070\u3001\u660e\u65e5\u306e\u5929\u6c17\u306b\u95a2\u9023\u3059\u308b\u305d\u306e\u4ed6\u306e\u60c5\u5831\uff08\u6e7f\u5ea6\u3001\u65e5\u306e\u51fa\u30fb\u65e5\u306e\u5165\u308a\u306e\u6642\u9593\u306a\u3069\uff09\u3082\u78ba\u8a8d\u3057\u3066\u30e1\u30e2\u3057\u3066\u304f\u3060\u3055\u3044\u3002\n7. \u5fc5\u8981\u306a\u60c5\u5831\u3092\u3059\u3079\u3066\u30e1\u30e2\u3057\u305f\u3089\u3001\u305d\u308c\u3092\u79c1\u306b\u4f1d\u3048\u3066\u304f\u3060\u3055\u3044\u3002"}

GPT: 明日の天気を知りたい場合は、以下の手順を実行してください。

1. 天気予報の情報を取得するために、天気予報のウェブサイトまたはアプリを開いてください。
2. ウェブサイトまたはアプリの検索バーに、明日の天気を調べたい都市名を入力してください。
3. 検索結果が表示されたら、明日の天気予報をクリックまたはタップしてください。
4. 天気予報ページが表示されたら、以下の情報を確認してください：
   - 明日の天気の概要（晴れ、曇り、雨など）
   - 明日の最高気温と最低気温
   - 明日の降水確率
   - 明日の風速と風向き
5. 上記の情報をメモしてください。
6. もし可能であれば、明日の天気に関連する他の情報（湿度、日の出・日の入りの時間など）もメモしてください。
7. 必要な情報をまとめたら、それを私に伝えてください。

以上の手順を実行することで、明日の天気を確認することができます。

You(weather): /jupyter
You(jupyter): titanicの回帰分析を行って
{
  "name": "run_python_code",
  "arguments": {
    "code": [
      "import pandas as pd",
      "from sklearn.model_selection import train_test_split",
      "from sklearn.linear_model import LogisticRegression",
      "from sklearn.metrics import accuracy_score",
      "",
      "# Load the Titanic dataset",
      "url = 'https://raw.githubusercontent.com/datasciencedojo/datasets/master/titanic.csv'",
      "df = pd.read_csv(url)",
      "",
      "# Select the features and target variable",
      "X = df[['Pclass', 'Sex', 'Age', 'SibSp', 'Parch', 'Fare', 'Embarked']]",
      "y = df['Survived']",
      "",
      "# Convert categorical variables to numerical",
      "X = pd.get_dummies(X, drop_first=True)",
      "",
      "# Split the data into training and testing sets",
      "X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2, random_state=42)",
      "",
      "# Create and train the logistic regression model",
      "model = LogisticRegression()",
      "model.fit(X_train, y_train)",
      "",
      "# Make predictions on the test set",
      "y_pred = model.predict(X_test)",
      "",
      "# Calculate the accuracy of the model",
      "accuracy = accuracy_score(y_test, y_pred)",
      "accuracy"
    ],
    "query": "titanic regression analysis"
  }
}
function(run_python_code): ---------------------------------------------------------------------------
ModuleNotFoundError                       Traceback (most recent call last)
File <ipython-input-1-c807f543bfd5>:1
----> 1 import pandas as pd
      2 from sklearn.model_selection import train_test_split
      3 from sklearn.linear_model import LogisticRegression

ModuleNotFoundError: No module named 'pandas'

Jupyter: It seems that the `pandas` library is not installed. Let me fix that for you.
Function python: Failed to load arguments as json
{
  "name": "python",
  "arguments": "!pip install pandas"
}
python function was called
function(python): Collecting pandas
  Using cached pandas-2.0.3-cp310-cp310-macosx_10_9_x86_64.whl (11.8 MB)
(snip)
Successfully installed pandas-2.0.3 pytz-2023.3 tzdata-2023.3

(snip)

Jupyter: Now that `pandas` is installed, let's run the code again.
{
  "name": "run_python_code",
  "arguments": {
    "code": [
      "import pandas as pd",
      "from sklearn.model_selection import train_test_split",
      "from sklearn.linear_model import LogisticRegression",
      "from sklearn.metrics import accuracy_score",
      "",
      "# Load the Titanic dataset",
      "url = 'https://raw.githubusercontent.com/datasciencedojo/datasets/master/titanic.csv'",
      "df = pd.read_csv(url)",
      "",
      "# Select the features and target variable",
      "X = df[['Pclass', 'Sex', 'Age', 'SibSp', 'Parch', 'Fare', 'Embarked']]",
      "y = df['Survived']",
      "",
      "# Convert categorical variables to numerical",
      "X = pd.get_dummies(X, drop_first=True)",
      "",
      "# Split the data into training and testing sets",
      "X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2, random_state=42)",
      "",
      "# Create and train the logistic regression model",
      "model = LogisticRegression()",
      "model.fit(X_train, y_train)",
      "",
      "# Make predictions on the test set",
      "y_pred = model.predict(X_test)",
      "",
      "# Calculate the accuracy of the model",
      "accuracy = accuracy_score(y_test, y_pred)",
      "accuracy"
    ],
    "query": "titanic regression analysis"
  }
}
function(run_python_code): ---------------------------------------------------------------------------
ModuleNotFoundError                       Traceback (most recent call last)
File <ipython-input-1-c807f543bfd5>:2
      1 import pandas as pd
----> 2 from sklearn.model_selection import train_test_split
      3 from sklearn.linear_model import LogisticRegression
      4 from sklearn.metrics import accuracy_score

ModuleNotFoundError: No module named 'sklearn'

Jupyter: It seems that the `sklearn` library is also not installed. Let me fix that for you.
```Python
!pip install scikit-learn

```