metagpt_quickstart.ipynb

{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "provenance": [],
      "include_colab_link": true
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "language_info": {
      "name": "python"
    }
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/leochenliu/doc/blob/main/metagpt_quickstart.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "# Installation"
      ],
      "metadata": {
        "id": "YaKfwGIgAx7p"
      }
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "hFbkYpBX0Iif",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "c60ba108-fef6-40ec-b44e-35ad71998fb8"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Collecting metagpt==0.6.0\n",
            "  Downloading metagpt-0.6.0-py3-none-any.whl (270 kB)\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m270.9/270.9 kB\u001b[0m \u001b[31m3.5 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hCollecting aiohttp==3.8.4 (from metagpt==0.6.0)\n",
            "  Downloading aiohttp-3.8.4-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (1.0 MB)\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m1.0/1.0 MB\u001b[0m \u001b[31m8.2 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hCollecting channels==4.0.0 (from metagpt==0.6.0)\n",
            "  Downloading channels-4.0.0-py3-none-any.whl (28 kB)\n",
            "Collecting faiss-cpu==1.7.4 (from metagpt==0.6.0)\n",
            "  Downloading faiss_cpu-1.7.4-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (17.6 MB)\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m17.6/17.6 MB\u001b[0m \u001b[31m30.1 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hCollecting fire==0.4.0 (from metagpt==0.6.0)\n",
            "  Downloading fire-0.4.0.tar.gz (87 kB)\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m87.7/87.7 kB\u001b[0m \u001b[31m8.4 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25h  Preparing metadata (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
            "Collecting typer==0.9.0 (from metagpt==0.6.0)\n",
            "  Downloading typer-0.9.0-py3-none-any.whl (45 kB)\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m45.9/45.9 kB\u001b[0m \u001b[31m3.6 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hCollecting lancedb==0.4.0 (from metagpt==0.6.0)\n",
            "  Downloading lancedb-0.4.0-py3-none-any.whl (81 kB)\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m81.4/81.4 kB\u001b[0m \u001b[31m6.8 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hCollecting langchain==0.0.352 (from metagpt==0.6.0)\n",
            "  Downloading langchain-0.0.352-py3-none-any.whl (794 kB)\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m794.4/794.4 kB\u001b[0m \u001b[31m36.1 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hCollecting loguru==0.6.0 (from metagpt==0.6.0)\n",
            "  Downloading loguru-0.6.0-py3-none-any.whl (58 kB)\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m58.3/58.3 kB\u001b[0m \u001b[31m5.6 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hCollecting meilisearch==0.21.0 (from metagpt==0.6.0)\n",
            "  Downloading meilisearch-0.21.0-py3-none-any.whl (19 kB)\n",
            "Collecting numpy==1.24.3 (from metagpt==0.6.0)\n",
            "  Downloading numpy-1.24.3-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (17.3 MB)\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m17.3/17.3 MB\u001b[0m \u001b[31m15.4 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hCollecting openai==1.6.0 (from metagpt==0.6.0)\n",
            "  Downloading openai-1.6.0-py3-none-any.whl (225 kB)\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m225.4/225.4 kB\u001b[0m \u001b[31m11.6 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hRequirement already satisfied: openpyxl in /usr/local/lib/python3.10/dist-packages (from metagpt==0.6.0) (3.1.2)\n",
            "Collecting beautifulsoup4==4.12.2 (from metagpt==0.6.0)\n",
            "  Downloading beautifulsoup4-4.12.2-py3-none-any.whl (142 kB)\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m143.0/143.0 kB\u001b[0m \u001b[31m6.6 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hRequirement already satisfied: pandas==2.0.3 in /usr/local/lib/python3.10/dist-packages (from metagpt==0.6.0) (2.0.3)\n",
            "Collecting pydantic==2.5.3 (from metagpt==0.6.0)\n",
            "  Downloading pydantic-2.5.3-py3-none-any.whl (381 kB)\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m381.9/381.9 kB\u001b[0m \u001b[31m5.4 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hCollecting python-docx==0.8.11 (from metagpt==0.6.0)\n",
            "  Downloading python-docx-0.8.11.tar.gz (5.6 MB)\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m5.6/5.6 MB\u001b[0m \u001b[31m26.3 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25h  Preparing metadata (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
            "Requirement already satisfied: PyYAML==6.0.1 in /usr/local/lib/python3.10/dist-packages (from metagpt==0.6.0) (6.0.1)\n",
            "Collecting setuptools==65.6.3 (from metagpt==0.6.0)\n",
            "  Downloading setuptools-65.6.3-py3-none-any.whl (1.2 MB)\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m1.2/1.2 MB\u001b[0m \u001b[31m39.3 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hCollecting tenacity==8.2.2 (from metagpt==0.6.0)\n",
            "  Downloading tenacity-8.2.2-py3-none-any.whl (24 kB)\n",
            "Collecting tiktoken==0.5.2 (from metagpt==0.6.0)\n",
            "  Downloading tiktoken-0.5.2-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (2.0 MB)\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m2.0/2.0 MB\u001b[0m \u001b[31m38.1 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hCollecting tqdm==4.65.0 (from metagpt==0.6.0)\n",
            "  Downloading tqdm-4.65.0-py3-none-any.whl (77 kB)\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m77.1/77.1 kB\u001b[0m \u001b[31m3.0 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hCollecting anthropic==0.8.1 (from metagpt==0.6.0)\n",
            "  Downloading anthropic-0.8.1-py3-none-any.whl (826 kB)\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m826.7/826.7 kB\u001b[0m \u001b[31m31.1 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hCollecting typing-inspect==0.8.0 (from metagpt==0.6.0)\n",
            "  Downloading typing_inspect-0.8.0-py3-none-any.whl (8.7 kB)\n",
            "Collecting typing-extensions==4.9.0 (from metagpt==0.6.0)\n",
            "  Downloading typing_extensions-4.9.0-py3-none-any.whl (32 kB)\n",
            "Collecting libcst==1.0.1 (from metagpt==0.6.0)\n",
            "  Downloading libcst-1.0.1-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (2.9 MB)\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m2.9/2.9 MB\u001b[0m \u001b[31m46.6 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hCollecting qdrant-client==1.7.0 (from metagpt==0.6.0)\n",
            "  Downloading qdrant_client-1.7.0-py3-none-any.whl (203 kB)\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m203.7/203.7 kB\u001b[0m \u001b[31m14.3 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hCollecting ta==0.10.2 (from metagpt==0.6.0)\n",
            "  Downloading ta-0.10.2.tar.gz (25 kB)\n",
            "  Preparing metadata (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
            "Collecting semantic-kernel==0.4.3.dev0 (from metagpt==0.6.0)\n",
            "  Downloading semantic_kernel-0.4.3.dev0-py3-none-any.whl (214 kB)\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m214.9/214.9 kB\u001b[0m \u001b[31m15.5 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hCollecting wrapt==1.15.0 (from metagpt==0.6.0)\n",
            "  Downloading wrapt-1.15.0-cp310-cp310-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl (78 kB)\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m78.4/78.4 kB\u001b[0m \u001b[31m1.5 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hCollecting aioredis~=2.0.1 (from metagpt==0.6.0)\n",
            "  Downloading aioredis-2.0.1-py3-none-any.whl (71 kB)\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m71.2/71.2 kB\u001b[0m \u001b[31m8.5 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hCollecting websocket-client==1.6.2 (from metagpt==0.6.0)\n",
            "  Downloading websocket_client-1.6.2-py3-none-any.whl (57 kB)\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m57.0/57.0 kB\u001b[0m \u001b[31m7.6 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hCollecting aiofiles==23.2.1 (from metagpt==0.6.0)\n",
            "  Downloading aiofiles-23.2.1-py3-none-any.whl (15 kB)\n",
            "Collecting gitpython==3.1.40 (from metagpt==0.6.0)\n",
            "  Downloading GitPython-3.1.40-py3-none-any.whl (190 kB)\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m190.6/190.6 kB\u001b[0m \u001b[31m24.4 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hCollecting zhipuai==1.0.7 (from metagpt==0.6.0)\n",
            "  Downloading zhipuai-1.0.7-py3-none-any.whl (7.9 kB)\n",
            "Collecting socksio~=1.0.0 (from metagpt==0.6.0)\n",
            "  Downloading socksio-1.0.0-py3-none-any.whl (12 kB)\n",
            "Collecting gitignore-parser==0.1.9 (from metagpt==0.6.0)\n",
            "  Downloading gitignore_parser-0.1.9.tar.gz (5.3 kB)\n",
            "  Installing build dependencies ... \u001b[?25l\u001b[?25hdone\n",
            "  Getting requirements to build wheel ... \u001b[?25l\u001b[?25hdone\n",
            "  Installing backend dependencies ... \u001b[?25l\u001b[?25hdone\n",
            "  Preparing metadata (pyproject.toml) ... \u001b[?25l\u001b[?25hdone\n",
            "Collecting websockets~=12.0 (from metagpt==0.6.0)\n",
            "  Downloading websockets-12.0-cp310-cp310-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl (130 kB)\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m130.2/130.2 kB\u001b[0m \u001b[31m16.3 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hCollecting networkx~=3.2.1 (from metagpt==0.6.0)\n",
            "  Downloading networkx-3.2.1-py3-none-any.whl (1.6 MB)\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m1.6/1.6 MB\u001b[0m \u001b[31m71.7 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hCollecting google-generativeai==0.3.2 (from metagpt==0.6.0)\n",
            "  Downloading google_generativeai-0.3.2-py3-none-any.whl (146 kB)\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m146.9/146.9 kB\u001b[0m \u001b[31m18.2 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hCollecting anytree (from metagpt==0.6.0)\n",
            "  Downloading anytree-2.12.1-py3-none-any.whl (44 kB)\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m44.9/44.9 kB\u001b[0m \u001b[31m5.4 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hRequirement already satisfied: attrs>=17.3.0 in /usr/local/lib/python3.10/dist-packages (from aiohttp==3.8.4->metagpt==0.6.0) (23.2.0)\n",
            "Requirement already satisfied: charset-normalizer<4.0,>=2.0 in /usr/local/lib/python3.10/dist-packages (from aiohttp==3.8.4->metagpt==0.6.0) (3.3.2)\n",
            "Requirement already satisfied: multidict<7.0,>=4.5 in /usr/local/lib/python3.10/dist-packages (from aiohttp==3.8.4->metagpt==0.6.0) (6.0.5)\n",
            "Requirement already satisfied: async-timeout<5.0,>=4.0.0a3 in /usr/local/lib/python3.10/dist-packages (from aiohttp==3.8.4->metagpt==0.6.0) (4.0.3)\n",
            "Requirement already satisfied: yarl<2.0,>=1.0 in /usr/local/lib/python3.10/dist-packages (from aiohttp==3.8.4->metagpt==0.6.0) (1.9.4)\n",
            "Requirement already satisfied: frozenlist>=1.1.1 in /usr/local/lib/python3.10/dist-packages (from aiohttp==3.8.4->metagpt==0.6.0) (1.4.1)\n",
            "Requirement already satisfied: aiosignal>=1.1.2 in /usr/local/lib/python3.10/dist-packages (from aiohttp==3.8.4->metagpt==0.6.0) (1.3.1)\n",
            "Requirement already satisfied: anyio<5,>=3.5.0 in /usr/local/lib/python3.10/dist-packages (from anthropic==0.8.1->metagpt==0.6.0) (3.7.1)\n",
            "Requirement already satisfied: distro<2,>=1.7.0 in /usr/lib/python3/dist-packages (from anthropic==0.8.1->metagpt==0.6.0) (1.7.0)\n",
            "Collecting httpx<1,>=0.23.0 (from anthropic==0.8.1->metagpt==0.6.0)\n",
            "  Downloading httpx-0.27.0-py3-none-any.whl (75 kB)\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m75.6/75.6 kB\u001b[0m \u001b[31m9.1 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hRequirement already satisfied: sniffio in /usr/local/lib/python3.10/dist-packages (from anthropic==0.8.1->metagpt==0.6.0) (1.3.1)\n",
            "Requirement already satisfied: tokenizers>=0.13.0 in /usr/local/lib/python3.10/dist-packages (from anthropic==0.8.1->metagpt==0.6.0) (0.19.1)\n",
            "Requirement already satisfied: soupsieve>1.2 in /usr/local/lib/python3.10/dist-packages (from beautifulsoup4==4.12.2->metagpt==0.6.0) (2.5)\n",
            "Collecting Django>=3.2 (from channels==4.0.0->metagpt==0.6.0)\n",
            "  Downloading Django-5.0.6-py3-none-any.whl (8.2 MB)\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m8.2/8.2 MB\u001b[0m \u001b[31m92.6 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hCollecting asgiref<4,>=3.5.0 (from channels==4.0.0->metagpt==0.6.0)\n",
            "  Downloading asgiref-3.8.1-py3-none-any.whl (23 kB)\n",
            "Requirement already satisfied: six in /usr/local/lib/python3.10/dist-packages (from fire==0.4.0->metagpt==0.6.0) (1.16.0)\n",
            "Requirement already satisfied: termcolor in /usr/local/lib/python3.10/dist-packages (from fire==0.4.0->metagpt==0.6.0) (2.4.0)\n",
            "Collecting gitdb<5,>=4.0.1 (from gitpython==3.1.40->metagpt==0.6.0)\n",
            "  Downloading gitdb-4.0.11-py3-none-any.whl (62 kB)\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m62.7/62.7 kB\u001b[0m \u001b[31m7.3 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hCollecting google-ai-generativelanguage==0.4.0 (from google-generativeai==0.3.2->metagpt==0.6.0)\n",
            "  Downloading google_ai_generativelanguage-0.4.0-py3-none-any.whl (598 kB)\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m598.7/598.7 kB\u001b[0m \u001b[31m49.6 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hRequirement already satisfied: google-auth in /usr/local/lib/python3.10/dist-packages (from google-generativeai==0.3.2->metagpt==0.6.0) (2.27.0)\n",
            "Requirement already satisfied: google-api-core in /usr/local/lib/python3.10/dist-packages (from google-generativeai==0.3.2->metagpt==0.6.0) (2.11.1)\n",
            "Requirement already satisfied: protobuf in /usr/local/lib/python3.10/dist-packages (from google-generativeai==0.3.2->metagpt==0.6.0) (3.20.3)\n",
            "Collecting deprecation (from lancedb==0.4.0->metagpt==0.6.0)\n",
            "  Downloading deprecation-2.1.0-py2.py3-none-any.whl (11 kB)\n",
            "Collecting pylance==0.9.0 (from lancedb==0.4.0->metagpt==0.6.0)\n",
            "  Downloading pylance-0.9.0-cp38-abi3-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (19.5 MB)\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m19.5/19.5 MB\u001b[0m \u001b[31m58.2 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hCollecting ratelimiter~=1.0 (from lancedb==0.4.0->metagpt==0.6.0)\n",
            "  Downloading ratelimiter-1.2.0.post0-py3-none-any.whl (6.6 kB)\n",
            "Collecting retry>=0.9.2 (from lancedb==0.4.0->metagpt==0.6.0)\n",
            "  Downloading retry-0.9.2-py2.py3-none-any.whl (8.0 kB)\n",
            "Collecting semver>=3.0 (from lancedb==0.4.0->metagpt==0.6.0)\n",
            "  Downloading semver-3.0.2-py3-none-any.whl (17 kB)\n",
            "Requirement already satisfied: cachetools in /usr/local/lib/python3.10/dist-packages (from lancedb==0.4.0->metagpt==0.6.0) (5.3.3)\n",
            "Requirement already satisfied: click>=8.1.7 in /usr/local/lib/python3.10/dist-packages (from lancedb==0.4.0->metagpt==0.6.0) (8.1.7)\n",
            "Requirement already satisfied: requests>=2.31.0 in /usr/local/lib/python3.10/dist-packages (from lancedb==0.4.0->metagpt==0.6.0) (2.31.0)\n",
            "Collecting overrides>=0.7 (from lancedb==0.4.0->metagpt==0.6.0)\n",
            "  Downloading overrides-7.7.0-py3-none-any.whl (17 kB)\n",
            "Requirement already satisfied: SQLAlchemy<3,>=1.4 in /usr/local/lib/python3.10/dist-packages (from langchain==0.0.352->metagpt==0.6.0) (2.0.30)\n",
            "Collecting dataclasses-json<0.7,>=0.5.7 (from langchain==0.0.352->metagpt==0.6.0)\n",
            "  Downloading dataclasses_json-0.6.6-py3-none-any.whl (28 kB)\n",
            "Collecting jsonpatch<2.0,>=1.33 (from langchain==0.0.352->metagpt==0.6.0)\n",
            "  Downloading jsonpatch-1.33-py2.py3-none-any.whl (12 kB)\n",
            "Collecting langchain-community<0.1,>=0.0.2 (from langchain==0.0.352->metagpt==0.6.0)\n",
            "  Downloading langchain_community-0.0.38-py3-none-any.whl (2.0 MB)\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m2.0/2.0 MB\u001b[0m \u001b[31m73.5 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hCollecting langchain-core<0.2,>=0.1 (from langchain==0.0.352->metagpt==0.6.0)\n",
            "  Downloading langchain_core-0.1.52-py3-none-any.whl (302 kB)\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m302.9/302.9 kB\u001b[0m \u001b[31m26.3 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hCollecting langsmith<0.1.0,>=0.0.70 (from langchain==0.0.352->metagpt==0.6.0)\n",
            "  Downloading langsmith-0.0.92-py3-none-any.whl (56 kB)\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m56.5/56.5 kB\u001b[0m \u001b[31m6.5 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hCollecting camel-converter[pydantic] (from meilisearch==0.21.0->metagpt==0.6.0)\n",
            "  Downloading camel_converter-3.1.2-py3-none-any.whl (5.7 kB)\n",
            "Requirement already satisfied: python-dateutil>=2.8.2 in /usr/local/lib/python3.10/dist-packages (from pandas==2.0.3->metagpt==0.6.0) (2.8.2)\n",
            "Requirement already satisfied: pytz>=2020.1 in /usr/local/lib/python3.10/dist-packages (from pandas==2.0.3->metagpt==0.6.0) (2023.4)\n",
            "Requirement already satisfied: tzdata>=2022.1 in /usr/local/lib/python3.10/dist-packages (from pandas==2.0.3->metagpt==0.6.0) (2024.1)\n",
            "Requirement already satisfied: annotated-types>=0.4.0 in /usr/local/lib/python3.10/dist-packages (from pydantic==2.5.3->metagpt==0.6.0) (0.7.0)\n",
            "Collecting pydantic-core==2.14.6 (from pydantic==2.5.3->metagpt==0.6.0)\n",
            "  Downloading pydantic_core-2.14.6-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (2.1 MB)\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m2.1/2.1 MB\u001b[0m \u001b[31m45.3 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hRequirement already satisfied: lxml>=2.3.2 in /usr/local/lib/python3.10/dist-packages (from python-docx==0.8.11->metagpt==0.6.0) (4.9.4)\n",
            "Requirement already satisfied: grpcio>=1.41.0 in /usr/local/lib/python3.10/dist-packages (from qdrant-client==1.7.0->metagpt==0.6.0) (1.64.0)\n",
            "Collecting grpcio-tools>=1.41.0 (from qdrant-client==1.7.0->metagpt==0.6.0)\n",
            "  Downloading grpcio_tools-1.64.0-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (2.3 MB)\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m2.3/2.3 MB\u001b[0m \u001b[31m57.8 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hCollecting portalocker<3.0.0,>=2.7.0 (from qdrant-client==1.7.0->metagpt==0.6.0)\n",
            "  Downloading portalocker-2.8.2-py3-none-any.whl (17 kB)\n",
            "Collecting urllib3<2.0.0,>=1.26.14 (from qdrant-client==1.7.0->metagpt==0.6.0)\n",
            "  Downloading urllib3-1.26.18-py2.py3-none-any.whl (143 kB)\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m143.8/143.8 kB\u001b[0m \u001b[31m18.1 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hCollecting motor<4.0.0,>=3.3.1 (from semantic-kernel==0.4.3.dev0->metagpt==0.6.0)\n",
            "  Downloading motor-3.4.0-py3-none-any.whl (74 kB)\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m74.3/74.3 kB\u001b[0m \u001b[31m8.6 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hCollecting openapi_core<0.19.0,>=0.18.0 (from semantic-kernel==0.4.3.dev0->metagpt==0.6.0)\n",
            "  Downloading openapi_core-0.18.2-py3-none-any.whl (82 kB)\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m82.4/82.4 kB\u001b[0m \u001b[31m10.4 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hCollecting prance<24.0.0.0,>=23.6.21.0 (from semantic-kernel==0.4.3.dev0->metagpt==0.6.0)\n",
            "  Downloading prance-23.6.21.0-py3-none-any.whl (36 kB)\n",
            "Collecting python-dotenv==1.0.0 (from semantic-kernel==0.4.3.dev0->metagpt==0.6.0)\n",
            "  Downloading python_dotenv-1.0.0-py3-none-any.whl (19 kB)\n",
            "Collecting regex<2024.0.0,>=2023.6.3 (from semantic-kernel==0.4.3.dev0->metagpt==0.6.0)\n",
            "  Downloading regex-2023.12.25-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (773 kB)\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m774.0/774.0 kB\u001b[0m \u001b[31m26.1 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hCollecting mypy-extensions>=0.3.0 (from typing-inspect==0.8.0->metagpt==0.6.0)\n",
            "  Downloading mypy_extensions-1.0.0-py3-none-any.whl (4.7 kB)\n",
            "Requirement already satisfied: PyJWT in /usr/lib/python3/dist-packages (from zhipuai==1.0.7->metagpt==0.6.0) (2.3.0)\n",
            "Collecting dataclasses (from zhipuai==1.0.7->metagpt==0.6.0)\n",
            "  Downloading dataclasses-0.6-py3-none-any.whl (14 kB)\n",
            "Requirement already satisfied: proto-plus<2.0.0dev,>=1.22.3 in /usr/local/lib/python3.10/dist-packages (from google-ai-generativelanguage==0.4.0->google-generativeai==0.3.2->metagpt==0.6.0) (1.23.0)\n",
            "Requirement already satisfied: pyarrow>=12 in /usr/local/lib/python3.10/dist-packages (from pylance==0.9.0->lancedb==0.4.0->metagpt==0.6.0) (14.0.2)\n",
            "Requirement already satisfied: et-xmlfile in /usr/local/lib/python3.10/dist-packages (from openpyxl->metagpt==0.6.0) (1.1.0)\n",
            "Requirement already satisfied: idna>=2.8 in /usr/local/lib/python3.10/dist-packages (from anyio<5,>=3.5.0->anthropic==0.8.1->metagpt==0.6.0) (3.7)\n",
            "Requirement already satisfied: exceptiongroup in /usr/local/lib/python3.10/dist-packages (from anyio<5,>=3.5.0->anthropic==0.8.1->metagpt==0.6.0) (1.2.1)\n",
            "Collecting marshmallow<4.0.0,>=3.18.0 (from dataclasses-json<0.7,>=0.5.7->langchain==0.0.352->metagpt==0.6.0)\n",
            "  Downloading marshmallow-3.21.2-py3-none-any.whl (49 kB)\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m49.3/49.3 kB\u001b[0m \u001b[31m5.3 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hRequirement already satisfied: sqlparse>=0.3.1 in /usr/local/lib/python3.10/dist-packages (from Django>=3.2->channels==4.0.0->metagpt==0.6.0) (0.5.0)\n",
            "Collecting smmap<6,>=3.0.1 (from gitdb<5,>=4.0.1->gitpython==3.1.40->metagpt==0.6.0)\n",
            "  Downloading smmap-5.0.1-py3-none-any.whl (24 kB)\n",
            "INFO: pip is looking at multiple versions of grpcio-tools to determine which version is compatible with other requirements. This could take a while.\n",
            "Collecting grpcio-tools>=1.41.0 (from qdrant-client==1.7.0->metagpt==0.6.0)\n",
            "  Downloading grpcio_tools-1.63.0-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (2.3 MB)\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m2.3/2.3 MB\u001b[0m \u001b[31m76.4 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25h  Downloading grpcio_tools-1.62.2-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (2.8 MB)\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m2.8/2.8 MB\u001b[0m \u001b[31m76.3 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hCollecting protobuf (from google-generativeai==0.3.2->metagpt==0.6.0)\n",
            "  Downloading protobuf-4.25.3-cp37-abi3-manylinux2014_x86_64.whl (294 kB)\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m294.6/294.6 kB\u001b[0m \u001b[31m24.3 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hRequirement already satisfied: certifi in /usr/local/lib/python3.10/dist-packages (from httpx<1,>=0.23.0->anthropic==0.8.1->metagpt==0.6.0) (2024.2.2)\n",
            "Collecting httpcore==1.* (from httpx<1,>=0.23.0->anthropic==0.8.1->metagpt==0.6.0)\n",
            "  Downloading httpcore-1.0.5-py3-none-any.whl (77 kB)\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m77.9/77.9 kB\u001b[0m \u001b[31m9.5 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hCollecting h11<0.15,>=0.13 (from httpcore==1.*->httpx<1,>=0.23.0->anthropic==0.8.1->metagpt==0.6.0)\n",
            "  Downloading h11-0.14.0-py3-none-any.whl (58 kB)\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m58.3/58.3 kB\u001b[0m \u001b[31m7.0 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hCollecting h2<5,>=3 (from httpx<1,>=0.23.0->anthropic==0.8.1->metagpt==0.6.0)\n",
            "  Downloading h2-4.1.0-py3-none-any.whl (57 kB)\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m57.5/57.5 kB\u001b[0m \u001b[31m6.4 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hCollecting jsonpointer>=1.9 (from jsonpatch<2.0,>=1.33->langchain==0.0.352->metagpt==0.6.0)\n",
            "  Downloading jsonpointer-2.4-py2.py3-none-any.whl (7.8 kB)\n",
            "INFO: pip is looking at multiple versions of langchain-community to determine which version is compatible with other requirements. This could take a while.\n",
            "Collecting langchain-community<0.1,>=0.0.2 (from langchain==0.0.352->metagpt==0.6.0)\n",
            "  Downloading langchain_community-0.0.37-py3-none-any.whl (2.0 MB)\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m2.0/2.0 MB\u001b[0m \u001b[31m75.2 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25h  Downloading langchain_community-0.0.36-py3-none-any.whl (2.0 MB)\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m2.0/2.0 MB\u001b[0m \u001b[31m72.2 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25h  Downloading langchain_community-0.0.35-py3-none-any.whl (2.0 MB)\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m2.0/2.0 MB\u001b[0m \u001b[31m69.9 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25h  Downloading langchain_community-0.0.34-py3-none-any.whl (1.9 MB)\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m1.9/1.9 MB\u001b[0m \u001b[31m74.4 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25h  Downloading langchain_community-0.0.33-py3-none-any.whl (1.9 MB)\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m1.9/1.9 MB\u001b[0m \u001b[31m72.0 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25h  Downloading langchain_community-0.0.32-py3-none-any.whl (1.9 MB)\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m1.9/1.9 MB\u001b[0m \u001b[31m72.1 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25h  Downloading langchain_community-0.0.31-py3-none-any.whl (1.9 MB)\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m1.9/1.9 MB\u001b[0m \u001b[31m60.7 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hINFO: pip is looking at multiple versions of langchain-community to determine which version is compatible with other requirements. This could take a while.\n",
            "  Downloading langchain_community-0.0.30-py3-none-any.whl (1.9 MB)\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m1.9/1.9 MB\u001b[0m \u001b[31m50.7 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25h  Downloading langchain_community-0.0.29-py3-none-any.whl (1.8 MB)\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m1.8/1.8 MB\u001b[0m \u001b[31m11.3 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25h  Downloading langchain_community-0.0.28-py3-none-any.whl (1.8 MB)\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m1.8/1.8 MB\u001b[0m \u001b[31m58.3 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25h  Downloading langchain_community-0.0.27-py3-none-any.whl (1.8 MB)\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m1.8/1.8 MB\u001b[0m \u001b[31m60.9 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25h  Downloading langchain_community-0.0.26-py3-none-any.whl (1.8 MB)\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m1.8/1.8 MB\u001b[0m \u001b[31m57.9 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hINFO: This is taking longer than usual. You might need to provide the dependency resolver with stricter constraints to reduce runtime. See https://pip.pypa.io/warnings/backtracking for guidance. If you want to abort this run, press Ctrl + C.\n",
            "  Downloading langchain_community-0.0.25-py3-none-any.whl (1.8 MB)\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m1.8/1.8 MB\u001b[0m \u001b[31m55.4 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25h  Downloading langchain_community-0.0.24-py3-none-any.whl (1.7 MB)\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m1.7/1.7 MB\u001b[0m \u001b[31m45.4 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25h  Downloading langchain_community-0.0.23-py3-none-any.whl (1.7 MB)\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m1.7/1.7 MB\u001b[0m \u001b[31m56.3 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25h  Downloading langchain_community-0.0.22-py3-none-any.whl (1.7 MB)\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m1.7/1.7 MB\u001b[0m \u001b[31m53.0 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25h  Downloading langchain_community-0.0.21-py3-none-any.whl (1.7 MB)\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m1.7/1.7 MB\u001b[0m \u001b[31m54.2 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25h  Downloading langchain_community-0.0.20-py3-none-any.whl (1.7 MB)\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m1.7/1.7 MB\u001b[0m \u001b[31m70.2 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hINFO: pip is looking at multiple versions of langchain-core to determine which version is compatible with other requirements. This could take a while.\n",
            "Collecting langchain-core<0.2,>=0.1 (from langchain==0.0.352->metagpt==0.6.0)\n",
            "  Downloading langchain_core-0.1.51-py3-none-any.whl (302 kB)\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m302.9/302.9 kB\u001b[0m \u001b[31m27.4 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25h  Downloading langchain_core-0.1.50-py3-none-any.whl (302 kB)\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m302.8/302.8 kB\u001b[0m \u001b[31m28.6 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25h  Downloading langchain_core-0.1.49-py3-none-any.whl (303 kB)\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m303.0/303.0 kB\u001b[0m \u001b[31m28.8 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25h  Downloading langchain_core-0.1.48-py3-none-any.whl (302 kB)\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m302.9/302.9 kB\u001b[0m \u001b[31m27.5 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25h  Downloading langchain_core-0.1.47-py3-none-any.whl (302 kB)\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m302.2/302.2 kB\u001b[0m \u001b[31m29.8 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25h  Downloading langchain_core-0.1.46-py3-none-any.whl (299 kB)\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m299.3/299.3 kB\u001b[0m \u001b[31m25.2 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25h  Downloading langchain_core-0.1.45-py3-none-any.whl (291 kB)\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m291.3/291.3 kB\u001b[0m \u001b[31m25.7 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hINFO: pip is looking at multiple versions of langchain-core to determine which version is compatible with other requirements. This could take a while.\n",
            "  Downloading langchain_core-0.1.44-py3-none-any.whl (290 kB)\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m290.2/290.2 kB\u001b[0m \u001b[31m29.0 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25h  Downloading langchain_core-0.1.43-py3-none-any.whl (289 kB)\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m289.1/289.1 kB\u001b[0m \u001b[31m29.3 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25h  Downloading langchain_core-0.1.42-py3-none-any.whl (287 kB)\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m287.5/287.5 kB\u001b[0m \u001b[31m28.0 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25h  Downloading langchain_core-0.1.41-py3-none-any.whl (278 kB)\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m278.4/278.4 kB\u001b[0m \u001b[31m28.5 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25h  Downloading langchain_core-0.1.40-py3-none-any.whl (276 kB)\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m276.8/276.8 kB\u001b[0m \u001b[31m27.7 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hINFO: This is taking longer than usual. You might need to provide the dependency resolver with stricter constraints to reduce runtime. See https://pip.pypa.io/warnings/backtracking for guidance. If you want to abort this run, press Ctrl + C.\n",
            "  Downloading langchain_core-0.1.39-py3-none-any.whl (276 kB)\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m276.6/276.6 kB\u001b[0m \u001b[31m28.0 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25h  Downloading langchain_core-0.1.38-py3-none-any.whl (279 kB)\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m279.2/279.2 kB\u001b[0m \u001b[31m29.8 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25h  Downloading langchain_core-0.1.37-py3-none-any.whl (274 kB)\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m274.6/274.6 kB\u001b[0m \u001b[31m27.9 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25h  Downloading langchain_core-0.1.36-py3-none-any.whl (273 kB)\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m273.9/273.9 kB\u001b[0m \u001b[31m29.1 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25h  Downloading langchain_core-0.1.35-py3-none-any.whl (273 kB)\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m273.0/273.0 kB\u001b[0m \u001b[31m30.0 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25h  Downloading langchain_core-0.1.34-py3-none-any.whl (271 kB)\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m271.6/271.6 kB\u001b[0m \u001b[31m26.3 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25h  Downloading langchain_core-0.1.33-py3-none-any.whl (269 kB)\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m269.1/269.1 kB\u001b[0m \u001b[31m28.2 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25h  Downloading langchain_core-0.1.32-py3-none-any.whl (260 kB)\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m260.9/260.9 kB\u001b[0m \u001b[31m24.8 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25h  Downloading langchain_core-0.1.31-py3-none-any.whl (258 kB)\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m258.8/258.8 kB\u001b[0m \u001b[31m27.6 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25h  Downloading langchain_core-0.1.30-py3-none-any.whl (256 kB)\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m256.9/256.9 kB\u001b[0m \u001b[31m25.0 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25h  Downloading langchain_core-0.1.29-py3-none-any.whl (252 kB)\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m252.6/252.6 kB\u001b[0m \u001b[31m26.2 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25h  Downloading langchain_core-0.1.28-py3-none-any.whl (252 kB)\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m252.4/252.4 kB\u001b[0m \u001b[31m25.0 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25h  Downloading langchain_core-0.1.27-py3-none-any.whl (250 kB)\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m250.8/250.8 kB\u001b[0m \u001b[31m26.1 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25h  Downloading langchain_core-0.1.26-py3-none-any.whl (246 kB)\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m246.4/246.4 kB\u001b[0m \u001b[31m18.2 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25h  Downloading langchain_core-0.1.25-py3-none-any.whl (242 kB)\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m242.1/242.1 kB\u001b[0m \u001b[31m21.7 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25h  Downloading langchain_core-0.1.24-py3-none-any.whl (241 kB)\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m241.3/241.3 kB\u001b[0m \u001b[31m22.5 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25h  Downloading langchain_core-0.1.23-py3-none-any.whl (241 kB)\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m241.2/241.2 kB\u001b[0m \u001b[31m23.5 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hCollecting langsmith<0.1.0,>=0.0.70 (from langchain==0.0.352->metagpt==0.6.0)\n",
            "  Downloading langsmith-0.0.87-py3-none-any.whl (55 kB)\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m55.4/55.4 kB\u001b[0m \u001b[31m6.4 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hCollecting packaging<24.0,>=23.2 (from langchain-core<0.2,>=0.1->langchain==0.0.352->metagpt==0.6.0)\n",
            "  Downloading packaging-23.2-py3-none-any.whl (53 kB)\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m53.0/53.0 kB\u001b[0m \u001b[31m6.5 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hCollecting pymongo<5,>=4.5 (from motor<4.0.0,>=3.3.1->semantic-kernel==0.4.3.dev0->metagpt==0.6.0)\n",
            "  Downloading pymongo-4.7.2-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (670 kB)\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m670.0/670.0 kB\u001b[0m \u001b[31m20.5 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hCollecting isodate (from openapi_core<0.19.0,>=0.18.0->semantic-kernel==0.4.3.dev0->metagpt==0.6.0)\n",
            "  Downloading isodate-0.6.1-py2.py3-none-any.whl (41 kB)\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m41.7/41.7 kB\u001b[0m \u001b[31m4.2 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hRequirement already satisfied: jsonschema<5.0.0,>=4.18.0 in /usr/local/lib/python3.10/dist-packages (from openapi_core<0.19.0,>=0.18.0->semantic-kernel==0.4.3.dev0->metagpt==0.6.0) (4.19.2)\n",
            "Collecting jsonschema-spec<0.3.0,>=0.2.3 (from openapi_core<0.19.0,>=0.18.0->semantic-kernel==0.4.3.dev0->metagpt==0.6.0)\n",
            "  Downloading jsonschema_spec-0.2.4-py3-none-any.whl (14 kB)\n",
            "Requirement already satisfied: more-itertools in /usr/local/lib/python3.10/dist-packages (from openapi_core<0.19.0,>=0.18.0->semantic-kernel==0.4.3.dev0->metagpt==0.6.0) (10.1.0)\n",
            "Collecting openapi-schema-validator<0.7.0,>=0.6.0 (from openapi_core<0.19.0,>=0.18.0->semantic-kernel==0.4.3.dev0->metagpt==0.6.0)\n",
            "  Downloading openapi_schema_validator-0.6.2-py3-none-any.whl (8.8 kB)\n",
            "Collecting openapi-spec-validator<0.8.0,>=0.7.1 (from openapi_core<0.19.0,>=0.18.0->semantic-kernel==0.4.3.dev0->metagpt==0.6.0)\n",
            "  Downloading openapi_spec_validator-0.7.1-py3-none-any.whl (38 kB)\n",
            "Collecting parse (from openapi_core<0.19.0,>=0.18.0->semantic-kernel==0.4.3.dev0->metagpt==0.6.0)\n",
            "  Downloading parse-1.20.1-py2.py3-none-any.whl (20 kB)\n",
            "Requirement already satisfied: werkzeug in /usr/local/lib/python3.10/dist-packages (from openapi_core<0.19.0,>=0.18.0->semantic-kernel==0.4.3.dev0->metagpt==0.6.0) (3.0.3)\n",
            "Requirement already satisfied: chardet>=3.0 in /usr/local/lib/python3.10/dist-packages (from prance<24.0.0.0,>=23.6.21.0->semantic-kernel==0.4.3.dev0->metagpt==0.6.0) (5.2.0)\n",
            "Collecting ruamel.yaml>=0.17.10 (from prance<24.0.0.0,>=23.6.21.0->semantic-kernel==0.4.3.dev0->metagpt==0.6.0)\n",
            "  Downloading ruamel.yaml-0.18.6-py3-none-any.whl (117 kB)\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m117.8/117.8 kB\u001b[0m \u001b[31m13.9 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hRequirement already satisfied: decorator>=3.4.2 in /usr/local/lib/python3.10/dist-packages (from retry>=0.9.2->lancedb==0.4.0->metagpt==0.6.0) (4.4.2)\n",
            "Collecting py<2.0.0,>=1.4.26 (from retry>=0.9.2->lancedb==0.4.0->metagpt==0.6.0)\n",
            "  Downloading py-1.11.0-py2.py3-none-any.whl (98 kB)\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m98.7/98.7 kB\u001b[0m \u001b[31m12.3 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hRequirement already satisfied: greenlet!=0.4.17 in /usr/local/lib/python3.10/dist-packages (from SQLAlchemy<3,>=1.4->langchain==0.0.352->metagpt==0.6.0) (3.0.3)\n",
            "Requirement already satisfied: huggingface-hub<1.0,>=0.16.4 in /usr/local/lib/python3.10/dist-packages (from tokenizers>=0.13.0->anthropic==0.8.1->metagpt==0.6.0) (0.23.1)\n",
            "Requirement already satisfied: googleapis-common-protos<2.0.dev0,>=1.56.2 in /usr/local/lib/python3.10/dist-packages (from google-api-core->google-generativeai==0.3.2->metagpt==0.6.0) (1.63.0)\n",
            "Requirement already satisfied: pyasn1-modules>=0.2.1 in /usr/local/lib/python3.10/dist-packages (from google-auth->google-generativeai==0.3.2->metagpt==0.6.0) (0.4.0)\n",
            "Requirement already satisfied: rsa<5,>=3.1.4 in /usr/local/lib/python3.10/dist-packages (from google-auth->google-generativeai==0.3.2->metagpt==0.6.0) (4.9)\n",
            "Requirement already satisfied: grpcio-status<2.0.dev0,>=1.33.2 in /usr/local/lib/python3.10/dist-packages (from google-api-core->google-generativeai==0.3.2->metagpt==0.6.0) (1.48.2)\n",
            "Collecting hyperframe<7,>=6.0 (from h2<5,>=3->httpx<1,>=0.23.0->anthropic==0.8.1->metagpt==0.6.0)\n",
            "  Downloading hyperframe-6.0.1-py3-none-any.whl (12 kB)\n",
            "Collecting hpack<5,>=4.0 (from h2<5,>=3->httpx<1,>=0.23.0->anthropic==0.8.1->metagpt==0.6.0)\n",
            "  Downloading hpack-4.0.0-py3-none-any.whl (32 kB)\n",
            "Requirement already satisfied: filelock in /usr/local/lib/python3.10/dist-packages (from huggingface-hub<1.0,>=0.16.4->tokenizers>=0.13.0->anthropic==0.8.1->metagpt==0.6.0) (3.14.0)\n",
            "Requirement already satisfied: fsspec>=2023.5.0 in /usr/local/lib/python3.10/dist-packages (from huggingface-hub<1.0,>=0.16.4->tokenizers>=0.13.0->anthropic==0.8.1->metagpt==0.6.0) (2023.6.0)\n",
            "Requirement already satisfied: jsonschema-specifications>=2023.03.6 in /usr/local/lib/python3.10/dist-packages (from jsonschema<5.0.0,>=4.18.0->openapi_core<0.19.0,>=0.18.0->semantic-kernel==0.4.3.dev0->metagpt==0.6.0) (2023.12.1)\n",
            "Requirement already satisfied: referencing>=0.28.4 in /usr/local/lib/python3.10/dist-packages (from jsonschema<5.0.0,>=4.18.0->openapi_core<0.19.0,>=0.18.0->semantic-kernel==0.4.3.dev0->metagpt==0.6.0) (0.35.1)\n",
            "Requirement already satisfied: rpds-py>=0.7.1 in /usr/local/lib/python3.10/dist-packages (from jsonschema<5.0.0,>=4.18.0->openapi_core<0.19.0,>=0.18.0->semantic-kernel==0.4.3.dev0->metagpt==0.6.0) (0.18.1)\n",
            "Collecting pathable<0.5.0,>=0.4.1 (from jsonschema-spec<0.3.0,>=0.2.3->openapi_core<0.19.0,>=0.18.0->semantic-kernel==0.4.3.dev0->metagpt==0.6.0)\n",
            "  Downloading pathable-0.4.3-py3-none-any.whl (9.6 kB)\n",
            "Collecting referencing>=0.28.4 (from jsonschema<5.0.0,>=4.18.0->openapi_core<0.19.0,>=0.18.0->semantic-kernel==0.4.3.dev0->metagpt==0.6.0)\n",
            "  Downloading referencing-0.30.2-py3-none-any.whl (25 kB)\n",
            "Collecting rfc3339-validator (from openapi-schema-validator<0.7.0,>=0.6.0->openapi_core<0.19.0,>=0.18.0->semantic-kernel==0.4.3.dev0->metagpt==0.6.0)\n",
            "  Downloading rfc3339_validator-0.1.4-py2.py3-none-any.whl (3.5 kB)\n",
            "Collecting jsonschema-path<0.4.0,>=0.3.1 (from openapi-spec-validator<0.8.0,>=0.7.1->openapi_core<0.19.0,>=0.18.0->semantic-kernel==0.4.3.dev0->metagpt==0.6.0)\n",
            "  Downloading jsonschema_path-0.3.2-py3-none-any.whl (14 kB)\n",
            "Collecting lazy-object-proxy<2.0.0,>=1.7.1 (from openapi-spec-validator<0.8.0,>=0.7.1->openapi_core<0.19.0,>=0.18.0->semantic-kernel==0.4.3.dev0->metagpt==0.6.0)\n",
            "  Downloading lazy_object_proxy-1.10.0-cp310-cp310-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl (68 kB)\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m68.3/68.3 kB\u001b[0m \u001b[31m6.7 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hRequirement already satisfied: pyasn1<0.7.0,>=0.4.6 in /usr/local/lib/python3.10/dist-packages (from pyasn1-modules>=0.2.1->google-auth->google-generativeai==0.3.2->metagpt==0.6.0) (0.6.0)\n",
            "Collecting dnspython<3.0.0,>=1.16.0 (from pymongo<5,>=4.5->motor<4.0.0,>=3.3.1->semantic-kernel==0.4.3.dev0->metagpt==0.6.0)\n",
            "  Downloading dnspython-2.6.1-py3-none-any.whl (307 kB)\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m307.7/307.7 kB\u001b[0m \u001b[31m31.1 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hCollecting ruamel.yaml.clib>=0.2.7 (from ruamel.yaml>=0.17.10->prance<24.0.0.0,>=23.6.21.0->semantic-kernel==0.4.3.dev0->metagpt==0.6.0)\n",
            "  Downloading ruamel.yaml.clib-0.2.8-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.manylinux_2_24_x86_64.whl (526 kB)\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m526.7/526.7 kB\u001b[0m \u001b[31m41.9 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hRequirement already satisfied: MarkupSafe>=2.1.1 in /usr/local/lib/python3.10/dist-packages (from werkzeug->openapi_core<0.19.0,>=0.18.0->semantic-kernel==0.4.3.dev0->metagpt==0.6.0) (2.1.5)\n",
            "INFO: pip is looking at multiple versions of jsonschema-specifications to determine which version is compatible with other requirements. This could take a while.\n",
            "Collecting jsonschema-specifications>=2023.03.6 (from jsonschema<5.0.0,>=4.18.0->openapi_core<0.19.0,>=0.18.0->semantic-kernel==0.4.3.dev0->metagpt==0.6.0)\n",
            "  Downloading jsonschema_specifications-2023.11.2-py3-none-any.whl (17 kB)\n",
            "  Downloading jsonschema_specifications-2023.11.1-py3-none-any.whl (17 kB)\n",
            "  Downloading jsonschema_specifications-2023.7.1-py3-none-any.whl (17 kB)\n",
            "Building wheels for collected packages: fire, gitignore-parser, python-docx, ta\n",
            "  Building wheel for fire (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
            "  Created wheel for fire: filename=fire-0.4.0-py2.py3-none-any.whl size=115928 sha256=317e8a5c1ef7a91bb127893f476acad5be23a6f390afd7ef751f423cc624b0ab\n",
            "  Stored in directory: /root/.cache/pip/wheels/26/9a/dd/2818b1b023daf077ec3e625c47ae446aca587a5abe48e05212\n",
            "  Building wheel for gitignore-parser (pyproject.toml) ... \u001b[?25l\u001b[?25hdone\n",
            "  Created wheel for gitignore-parser: filename=gitignore_parser-0.1.9-py3-none-any.whl size=4955 sha256=af33eb9dff8f81dd993c170d9411e1b638336e174be30b6fe80823e27914b7f5\n",
            "  Stored in directory: /root/.cache/pip/wheels/74/1a/fa/30ef804eda1ccc7f64be4784b16a5eb0822be8c6345458b87e\n",
            "  Building wheel for python-docx (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
            "  Created wheel for python-docx: filename=python_docx-0.8.11-py3-none-any.whl size=184488 sha256=3cacbf4b1f19d3109151bd1538091253d3c8814526a5fa2e63706120c055eb7d\n",
            "  Stored in directory: /root/.cache/pip/wheels/80/27/06/837436d4c3bd989b957a91679966f207bfd71d358d63a8194d\n",
            "  Building wheel for ta (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
            "  Created wheel for ta: filename=ta-0.10.2-py3-none-any.whl size=29089 sha256=74c0cc767671461adeed79cf5cf38b25e4de6acbabe945db331852577cd07d63\n",
            "  Stored in directory: /root/.cache/pip/wheels/47/51/06/380dc516ea78621870b93ff65527c251afdfdc5fa9d7f4d248\n",
            "Successfully built fire gitignore-parser python-docx ta\n",
            "Installing collected packages: ratelimiter, parse, gitignore-parser, faiss-cpu, dataclasses, wrapt, websockets, websocket-client, urllib3, typing-extensions, tqdm, tenacity, socksio, smmap, setuptools, semver, ruamel.yaml.clib, rfc3339-validator, regex, referencing, python-dotenv, python-docx, py, protobuf, portalocker, pathable, packaging, overrides, numpy, networkx, mypy-extensions, loguru, lazy-object-proxy, jsonpointer, isodate, hyperframe, hpack, h11, fire, dnspython, camel-converter, beautifulsoup4, anytree, aiofiles, typing-inspect, typer, ruamel.yaml, retry, pymongo, pydantic-core, marshmallow, jsonschema-specifications, jsonpatch, httpcore, h2, grpcio-tools, gitdb, deprecation, asgiref, aioredis, aiohttp, zhipuai, tiktoken, ta, pylance, pydantic, prance, motor, libcst, jsonschema-spec, jsonschema-path, httpx, gitpython, Django, dataclasses-json, openapi-schema-validator, openai, langsmith, lancedb, channels, qdrant-client, openapi-spec-validator, meilisearch, langchain-core, google-ai-generativelanguage, anthropic, openapi_core, langchain-community, google-generativeai, semantic-kernel, langchain, metagpt\n",
            "  Attempting uninstall: wrapt\n",
            "    Found existing installation: wrapt 1.14.1\n",
            "    Uninstalling wrapt-1.14.1:\n",
            "      Successfully uninstalled wrapt-1.14.1\n",
            "  Attempting uninstall: websocket-client\n",
            "    Found existing installation: websocket-client 1.8.0\n",
            "    Uninstalling websocket-client-1.8.0:\n",
            "      Successfully uninstalled websocket-client-1.8.0\n",
            "  Attempting uninstall: urllib3\n",
            "    Found existing installation: urllib3 2.0.7\n",
            "    Uninstalling urllib3-2.0.7:\n",
            "      Successfully uninstalled urllib3-2.0.7\n",
            "  Attempting uninstall: typing-extensions\n",
            "    Found existing installation: typing_extensions 4.11.0\n",
            "    Uninstalling typing_extensions-4.11.0:\n",
            "      Successfully uninstalled typing_extensions-4.11.0\n",
            "  Attempting uninstall: tqdm\n",
            "    Found existing installation: tqdm 4.66.4\n",
            "    Uninstalling tqdm-4.66.4:\n",
            "      Successfully uninstalled tqdm-4.66.4\n",
            "  Attempting uninstall: tenacity\n",
            "    Found existing installation: tenacity 8.3.0\n",
            "    Uninstalling tenacity-8.3.0:\n",
            "      Successfully uninstalled tenacity-8.3.0\n",
            "  Attempting uninstall: setuptools\n",
            "    Found existing installation: setuptools 67.7.2\n",
            "    Uninstalling setuptools-67.7.2:\n"
          ]
        }
      ],
      "source": [
        "!pip install metagpt==0.6.0"
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "# Setup"
      ],
      "metadata": {
        "id": "7XCdpgd6A1Ej"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "import os\n",
        "os.environ[\"OPENAI_API_KEY\"] = \"sk-...\"\n",
        "os.environ[\"OPENAI_API_MODEL\"] = \"gpt-4-1106-preview\""
      ],
      "metadata": {
        "id": "cj6sVZuv2EXg"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "# Develop software with a one-line requirement\n",
        ">Note:\n",
        ">\n",
        ">Below is a breakdown of the [software startup example](https://github.com/geekan/MetaGPT/blob/main/startup.py). If you install MetaGPT with the git clone approach, simply run\n",
        ">```\n",
        ">metagpt \"write a 2048 game\"\n",
        ">```\n",
        "\n",
        "Now, let's get started! We will create a team of agents to write software based on one line of our instruction.\n",
        "\n",
        "First, import off-the-shelf roles"
      ],
      "metadata": {
        "id": "6MugWeLTUiX0"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "import asyncio\n",
        "\n",
        "from metagpt.roles import (\n",
        "    Architect,\n",
        "    Engineer,\n",
        "    ProductManager,\n",
        "    ProjectManager,\n",
        ")\n",
        "from metagpt.team import Team"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "f8b786ef-7657-4185-957f-01e64100205a",
        "id": "9jsUARgvUiX0"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "2024-01-03 12:31:42.346 | INFO     | metagpt.const:get_metagpt_package_root:32 - Package root set to /content\n",
            "2024-01-03 12:31:42.580 | INFO     | metagpt.config:get_default_llm_provider_enum:116 - LLMProviderEnum.OPENAI Model: gpt-4-1106-preview\n",
            "2024-01-03 12:31:42.582 | INFO     | metagpt.config:get_default_llm_provider_enum:118 - API: LLMProviderEnum.OPENAI\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "Next, initiate the team, equip it with agents, set their budget, and provide our requirement of writing a small game"
      ],
      "metadata": {
        "id": "akClyaySUiX1"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "async def startup(idea: str):\n",
        "    company = Team()\n",
        "    company.hire(\n",
        "        [\n",
        "            ProductManager(),\n",
        "            Architect(),\n",
        "            ProjectManager(),\n",
        "            Engineer(),\n",
        "        ]\n",
        "    )\n",
        "    company.invest(investment=3.0)\n",
        "    company.run_project(idea=idea)\n",
        "\n",
        "    await company.run(n_round=5)"
      ],
      "metadata": {
        "id": "Ifo_PxwnUiX2"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "Finally, run it and get the code!"
      ],
      "metadata": {
        "id": "qvDuF7LUUiX2"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "history = await startup(idea=\"write a 2048 game\")"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "7303cc1f-c9d5-4427-9300-28ed3dfe73a9",
        "id": "X3OLT2tVUiX2"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "2024-01-03 12:31:45.652 | INFO     | metagpt.config:get_default_llm_provider_enum:116 - LLMProviderEnum.OPENAI Model: gpt-4-1106-preview\n",
            "2024-01-03 12:31:45.654 | INFO     | metagpt.config:get_default_llm_provider_enum:118 - API: LLMProviderEnum.OPENAI\n",
            "2024-01-03 12:31:45.761 | INFO     | metagpt.config:get_default_llm_provider_enum:116 - LLMProviderEnum.OPENAI Model: gpt-4-1106-preview\n",
            "2024-01-03 12:31:45.764 | INFO     | metagpt.config:get_default_llm_provider_enum:118 - API: LLMProviderEnum.OPENAI\n",
            "2024-01-03 12:31:45.861 | INFO     | metagpt.config:get_default_llm_provider_enum:116 - LLMProviderEnum.OPENAI Model: gpt-4-1106-preview\n",
            "2024-01-03 12:31:45.862 | INFO     | metagpt.config:get_default_llm_provider_enum:118 - API: LLMProviderEnum.OPENAI\n",
            "2024-01-03 12:31:45.977 | INFO     | metagpt.config:get_default_llm_provider_enum:116 - LLMProviderEnum.OPENAI Model: gpt-4-1106-preview\n",
            "2024-01-03 12:31:45.979 | INFO     | metagpt.config:get_default_llm_provider_enum:118 - API: LLMProviderEnum.OPENAI\n",
            "2024-01-03 12:31:46.070 | INFO     | metagpt.team:invest:86 - Investment: $3.0.\n",
            "2024-01-03 12:31:46.074 | INFO     | metagpt.roles.role:_act:357 - Alice(Product Manager): to do PrepareDocuments(PrepareDocuments)\n",
            "2024-01-03 12:31:46.134 | INFO     | metagpt.utils.file_repository:save:60 - save to: /content/workspace/20240103123146/docs/requirement.txt\n",
            "2024-01-03 12:31:46.140 | INFO     | metagpt.roles.role:_act:357 - Alice(Product Manager): to do WritePRD(WritePRD)\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "[CONTENT]\n",
            "{\n",
            "    \"Language\": \"en_us\",\n",
            "    \"Programming Language\": \"Python\",\n",
            "    \"Original Requirements\": \"write a 2048 game\",\n",
            "    \"Product Goals\": [\n",
            "        \"Develop a user-friendly and engaging 2048 game\",\n",
            "        \"Ensure the game is accessible and responsive on multiple devices\",\n",
            "        \"Design an aesthetically pleasing interface to enhance user experience\"\n",
            "    ],\n",
            "    \"User Stories\": [\n",
            "        \"As a player, I want to be able to select from various difficulty levels to match my skill\",\n",
            "        \"As a player, I want to see my current and high scores to track my progress\",\n",
            "        \"As a player, I want an option to restart the game quickly after losing\",\n",
            "        \"As a player, I want a visually appealing game interface that is enjoyable to interact with\",\n",
            "        \"As a player, I want to play the game on my mobile device without any issues\"\n",
            "    ],\n",
            "    \"Competitive Analysis\": [\n",
            "        \"2048 Original: Classic gameplay, minimalistic design, not fully responsive\",\n",
            "        \"2048 by Gabriele Cirulli: Highly engaging, open-source, but lacks variety in game modes\",\n",
            "        \"2048 Hex: Unique hexagon board, innovative, but can be confusing for new players\",\n",
            "        \"2048.io: Multiplayer version, adds a competitive edge, but has performance issues\",\n",
            "        \"2048 with AI: Includes an AI challenge mode, innovative, but AI can be too challenging for casual players\",\n",
            "        \"2048 Animated: Features animations, visually engaging, but the animations can be distracting\",\n",
            "        \"2048 3D: 3D version of the game, fresh perspective, but controls can be less intuitive\"\n",
            "    ],\n",
            "    \"Competitive Quadrant Chart\": \"quadrantChart\\n    title \\\"User Experience and Feature Set of 2048 Games\\\"\\n    x-axis \\\"Basic Features\\\" --> \\\"Advanced Features\\\"\\n    y-axis \\\"Low Engagement\\\" --> \\\"High Engagement\\\"\\n    quadrant-1 \\\"Feature-Poor\\\"\\n    quadrant-2 \\\"Niche Appeal\\\"\\n    quadrant-3 \\\"High Potential\\\"\\n    quadrant-4 \\\"Market Leaders\\\"\\n    \\\"2048 Original\\\": [0.2, 0.7]\\n    \\\"2048 by Gabriele Cirulli\\\": [0.5, 0.9]\\n    \\\"2048 Hex\\\": [0.6, 0.4]\\n    \\\"2048.io\\\": [0.7, 0.5]\\n    \\\"2048 with AI\\\": [0.8, 0.6]\\n    \\\"2048 Animated\\\": [0.4, 0.8]\\n    \\\"2048 3D\\\": [0.6, 0.3]\\n    \\\"Our Target Product\\\": [0.9, 0.8]\",\n",
            "    \"Requirement Analysis\": \"The original requirement is to write a 2048 game. This entails creating a grid-based puzzle game where players combine tiles with the same numbers to achieve a higher score, aiming for the 2048 tile. The game should be easy to learn but challenging to master, with a simple yet captivating user interface. It should be responsive and playable across different devices and platforms. Additional features such as difficulty levels, score tracking, and a visually appealing interface are essential for enhancing user engagement and satisfaction.\",\n",
            "    \"Requirement Pool\": [\n",
            "        [\n",
            "            \"P0\",\n",
            "            \"Develop a core game algorithm that allows for tile movement and combination according to 2048 game rules\"\n",
            "        ],\n",
            "        [\n",
            "            \"P0\",\n",
            "            \"Implement a responsive design that adapts to different screen sizes and devices\"\n",
            "        ],\n",
            "        [\n",
            "            \"P1\",\n",
            "            \"Design a user interface that is intuitive and visually attractive\"\n",
            "        ],\n",
            "        [\n",
            "            \"P1\",\n",
            "            \"Incorporate a scoring system that tracks the user's current and best scores\"\n",
            "        ],\n",
            "        [\n",
            "            \"P2\",\n",
            "            \"Add multiple difficulty levels to cater to a wide range of players\"\n",
            "        ]\n",
            "    ],\n",
            "    \"UI Design draft\": \"The UI will feature a clean and modern design with a grid at the center of the screen displaying the tiles. Score and best score will be prominently displayed at the top. Buttons for restarting the game and changing difficulty levels will be easily accessible. The color scheme will be calming yet vibrant, with smooth animations for tile movement.\",\n",
            "    \"Anything UNCLEAR\": \"The requirement for the game to be 'written' is clear, but it is not specified whether additional features such as leaderboards, social sharing, or online multiplayer are desired. Further clarification on these aspects would be beneficial.\"\n",
            "}\n",
            "[/CONTENT]"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "2024-01-03 12:33:05.294 | INFO     | metagpt.utils.cost_manager:update_cost:48 - Total running cost: $0.038 | Max budget: $10.000 | Current cost: $0.038, prompt_tokens: 903, completion_tokens: 955\n",
            "2024-01-03 12:33:05.307 | INFO     | metagpt.utils.file_repository:save:60 - save to: /content/workspace/20240103123146/docs/prds/20240103123305.json\n",
            "2024-01-03 12:33:05.317 | WARNING  | metagpt.utils.mermaid:mermaid_to_file:41 - RUN `npm install -g @mermaid-js/mermaid-cli` to install mmdc,or consider changing MERMAID_ENGINE to `playwright`, `pyppeteer`, or `ink`.\n",
            "2024-01-03 12:33:05.321 | INFO     | metagpt.utils.file_repository:save:60 - save to: /content/workspace/20240103123146/resources/prd/20240103123305.md\n",
            "2024-01-03 12:33:05.328 | INFO     | metagpt.roles.role:_act:357 - Bob(Architect): to do WriteDesign(WriteDesign)\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "[CONTENT]\n",
            "{\n",
            "    \"Implementation approach\": \"We will utilize Python as our programming language, leveraging the pygame library for graphical rendering and user input handling. This will allow us to create a responsive and visually appealing interface. For the core game algorithm, we will design a grid management system that handles tile movements and combinations. We will ensure that the game is responsive across multiple devices by using scalable dimensions for the game elements.\",\n",
            "    \"File list\": [\n",
            "        \"main.py\",\n",
            "        \"game.py\",\n",
            "        \"ui.py\",\n",
            "        \"constants.py\"\n",
            "    ],\n",
            "    \"Data structures and interfaces\": \"\\nclassDiagram\\n    class Main {\\n        +main() void\\n    }\\n    class Game {\\n        -int[][] grid\\n        -int score\\n        -int high_score\\n        +start_game() void\\n        +move(direction: str) bool\\n        +is_game_over() bool\\n        +reset_game() void\\n    }\\n    class UI {\\n        +draw_grid(grid: int[][]) void\\n        +display_score(score: int) void\\n        +display_high_score(high_score: int) void\\n        +show_game_over() void\\n        +show_main_menu() void\\n    }\\n    class Constants {\\n        +int GRID_SIZE\\n        +dict COLORS\\n        +dict KEY_BINDINGS\\n    }\\n    Main --> Game\\n    Game --> UI\\n    Game --> Constants\\n    UI --> Constants\\n\",\n",
            "    \"Program call flow\": \"\\nsequenceDiagram\\n    participant M as Main\\n    participant G as Game\\n    participant U as UI\\n    participant C as Constants\\n    M->>G: start_game()\\n    loop Game Loop\\n        G->>U: draw_grid(grid)\\n        U->>C: GRID_SIZE, COLORS\\n        C-->>U: return constants\\n        U-->>G: return\\n        G->>U: display_score(score)\\n        U-->>G: return\\n        G->>U: display_high"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "2024-01-03 12:33:39.930 | ERROR    | metagpt.utils.common:log_it:434 - Finished call to 'metagpt.actions.action_node.ActionNode._aask_v1' after 34.582(s), this was the 1st time calling it. exp: \n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "[CONTENT]\n",
            "{\n",
            "    \"Implementation approach\": \"We will use Python as the programming language to create the 2048 game, leveraging the pygame library for graphical representation and user input handling. The game will be structured with a main game loop that processes user inputs, updates the game state, and renders the updated state to the screen. We will ensure the game is responsive by designing the UI to scale with different screen sizes.\",\n",
            "    \"File list\": [\n",
            "        \"main.py\",\n",
            "        \"game.py\",\n",
            "        \"ui.py\",\n",
            "        \"constants.py\"\n",
            "    ],\n",
            "    \"Data structures and interfaces\": \"\\nclassDiagram\\n    class Main {\\n        +main() void\\n    }\\n    class Game {\\n        -grid: list\\n        -score: int\\n        -best_score: int\\n        +move(direction: str) bool\\n        +combine_tiles() bool\\n        +spawn_tile() bool\\n        +check_game_over() bool\\n        +reset_game() void\\n    }\\n    class UI {\\n        -game: Game\\n        +draw_grid() void\\n        +draw_score() void\\n        +draw_best_score() void\\n        +draw_game_over() void\\n        +handle_input() str\\n    }\\n    class Constants {\\n        +GRID_SIZE: int\\n        +TILE_SIZE: int\\n        +FONT: str\\n        +COLORS: dict\\n    }\\n    Main --> Game\\n    Main --> UI\\n    UI --> Game\\n    Game --> Constants\\n\",\n",
            "    \"Program call flow\": \"\\nsequenceDiagram\\n    participant M as Main\\n    participant G as Game\\n    participant U as UI\\n    M->>G: reset_game()\\n    loop Game Loop\\n        M->>U: handle_input()\\n        U-->>M: return direction\\n        M->>G: move(direction)\\n        alt Game Over\\n            G->>U: draw_game_over()\\n            U-->>G: return\\n        else Valid Move\\n            G->>G: combine_tiles()\\n            G->>G: spawn_tile()\\n            G->>U: draw_grid()\\n            G->>U: draw_score()\\n            G->>U: draw_best_score()\\n        end\\n        M->>G: check_game_over()\\n    end\\n\",\n",
            "    \"Anything UNCLEAR\": \"It is unclear whether the game should support saving and loading game states, or if there should be an online leaderboard feature. Clarification on these aspects would be beneficial"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "2024-01-03 12:34:46.156 | INFO     | metagpt.utils.cost_manager:update_cost:48 - Total running cost: $0.069 | Max budget: $10.000 | Current cost: $0.032, prompt_tokens: 1575, completion_tokens: 527\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            ".\"\n",
            "}\n",
            "[/CONTENT]"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "2024-01-03 12:34:46.167 | INFO     | metagpt.utils.file_repository:save:60 - save to: /content/workspace/20240103123146/docs/system_design/20240103123305.json\n",
            "2024-01-03 12:34:46.172 | INFO     | metagpt.utils.file_repository:save:65 - update dependency: /content/workspace/20240103123146/docs/system_design/20240103123305.json:{'docs/prds/20240103123305.json'}\n",
            "2024-01-03 12:34:46.177 | WARNING  | metagpt.utils.mermaid:mermaid_to_file:41 - RUN `npm install -g @mermaid-js/mermaid-cli` to install mmdc,or consider changing MERMAID_ENGINE to `playwright`, `pyppeteer`, or `ink`.\n",
            "2024-01-03 12:34:46.179 | INFO     | metagpt.actions.design_api:_save_data_api_design:117 - Save class view to /content/workspace/20240103123146/resources/data_api_design/20240103123305\n",
            "2024-01-03 12:34:46.184 | WARNING  | metagpt.utils.mermaid:mermaid_to_file:41 - RUN `npm install -g @mermaid-js/mermaid-cli` to install mmdc,or consider changing MERMAID_ENGINE to `playwright`, `pyppeteer`, or `ink`.\n",
            "2024-01-03 12:34:46.186 | INFO     | metagpt.actions.design_api:_save_seq_flow:127 - Saving sequence flow to /content/workspace/20240103123146/resources/seq_flow/20240103123305\n",
            "2024-01-03 12:34:46.189 | INFO     | metagpt.utils.file_repository:save:60 - save to: /content/workspace/20240103123146/resources/system_design/20240103123305.md\n",
            "2024-01-03 12:34:46.198 | INFO     | metagpt.roles.role:_act:357 - Eve(Project Manager): to do WriteTasks(WriteTasks)\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "[CONTENT]\n",
            "{\n",
            "    \"Required Python packages\": [\n",
            "        \"pygame==2.0.1\"\n",
            "    ],\n",
            "    \"Required Other language third-party packages\": [\n",
            "        \"No third-party dependencies required\"\n",
            "    ],\n",
            "    \"Logic Analysis\": [\n",
            "        [\n",
            "            \"constants.py\",\n",
            "            \"Contains Constants class with game configurations such as GRID_SIZE, TILE_SIZE, FONT, COLORS\"\n",
            "        ],\n",
            "        [\n",
            "            \"game.py\",\n",
            "            \"Contains Game class with methods for game logic including move, combine_tiles, spawn_tile, check_game_over, reset_game\"\n",
            "        ],\n",
            "        [\n",
            "            \"ui.py\",\n",
            "            \"Contains UI class with methods for user interface including draw_grid, draw_score, draw_best_score, draw_game_over, handle_input; depends on game.py for game state\"\n",
            "        ],\n",
            "        [\n",
            "            \"main.py\",\n",
            "            \"Contains main function to initialize and run the game loop; depends on game.py for game logic and ui.py for rendering and input handling\"\n",
            "        ]\n",
            "    ],\n",
            "    \"Task list\": [\n",
            "        \"constants.py\",\n",
            "        \"game.py\",\n",
            "        \"ui.py\",\n",
            "        \"main.py\"\n",
            "    ],\n",
            "    \"Full API spec\": \"\",\n",
            "    \"Shared Knowledge\": \"'constants.py' contains configurations shared across the project such as grid size and colors.\",\n",
            "    \"Anything UNCLEAR\": \"It is unclear whether the game should support saving and loading game states, or if there should be an online leaderboard feature. Clarification on these aspects would be beneficial"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "2024-01-03 12:35:16.727 | INFO     | metagpt.utils.cost_manager:update_cost:48 - Total running cost: $0.088 | Max budget: $10.000 | Current cost: $0.019, prompt_tokens: 1012, completion_tokens: 299\n",
            "2024-01-03 12:35:16.748 | INFO     | metagpt.utils.file_repository:save:60 - save to: /content/workspace/20240103123146/docs/tasks/20240103123305.json\n",
            "2024-01-03 12:35:16.758 | INFO     | metagpt.utils.file_repository:save:65 - update dependency: /content/workspace/20240103123146/docs/tasks/20240103123305.json:{'docs/system_design/20240103123305.json'}\n",
            "2024-01-03 12:35:16.762 | INFO     | metagpt.utils.file_repository:save:60 - save to: /content/workspace/20240103123146/requirements.txt\n",
            "2024-01-03 12:35:16.766 | INFO     | metagpt.utils.file_repository:save:60 - save to: /content/workspace/20240103123146/resources/api_spec_and_tasks/20240103123305.md\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            ".\"\n",
            "}\n",
            "[/CONTENT]"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.10/dist-packages/pydantic/main.py:352: UserWarning: Pydantic serializer warnings:\n",
            "  Expected `str` but got `dict` - serialized value may not be as expected\n",
            "  return self.__pydantic_serializer__.to_json(\n",
            "2024-01-03 12:35:16.811 | INFO     | metagpt.actions.write_code:run:128 - Writing constants.py..\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "## Code: constants.py\n",
            "```python\n",
            "## constants.py\n",
            "\n",
            "# Define the Constants class to hold game configurations\n",
            "class Constants:\n",
            "    # Grid size for the 2048 game, typically a 4x4 grid\n",
            "    GRID_SIZE: int = 4\n",
            "    \n",
            "    # Size of each tile in pixels\n",
            "    TILE_SIZE: int = 100\n",
            "    \n",
            "    # Font used for displaying text\n",
            "    FONT: str = 'arial'\n",
            "    \n",
            "    # Dictionary mapping tile values to their respective colors\n",
            "    COLORS: dict = {\n",
            "        0: (204, 192, 179),\n",
            "        2: (238, 228, 218),\n",
            "        4: (237, 224, 200),\n",
            "        8: (242, 177, 121),\n",
            "        16: (245, 149, 99),\n",
            "        32: (246, 124, 95),\n",
            "        64: (246, 94, 59),\n",
            "        128: (237, 207, 114),\n",
            "        256: (237, 204, 97),\n",
            "        512: (237, 200, 80),\n",
            "        1024: (237, 197, 63),\n",
            "        2048: (237, 194, 46),\n",
            "        # Additional colors for higher tiles if needed\n",
            "        4096: (60, 58, 50),\n",
            "        8192: (60, 58, 50),\n",
            "        16384: (60, 58, 50),\n",
            "        32768: (60, 58, 50),\n",
            "        65536: (60, 58, 50),\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "2024-01-03 12:35:59.816 | INFO     | metagpt.utils.cost_manager:update_cost:48 - Total running cost: $0.110 | Max budget: $10.000 | Current cost: $0.022, prompt_tokens: 1137, completion_tokens: 347\n",
            "2024-01-03 12:35:59.821 | INFO     | metagpt.utils.file_repository:save:60 - save to: /content/workspace/20240103123146/20240103123146/constants.py\n",
            "2024-01-03 12:35:59.825 | INFO     | metagpt.utils.file_repository:save:65 - update dependency: /content/workspace/20240103123146/20240103123146/constants.py:{'docs/system_design/20240103123305.json', 'docs/tasks/20240103123305.json'}\n",
            "2024-01-03 12:35:59.829 | INFO     | metagpt.actions.write_code:run:128 - Writing game.py..\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "    }\n",
            "```## Code: game.py\n",
            "```python\n",
            "## game.py\n",
            "\n",
            "import random\n",
            "from constants import Constants\n",
            "\n",
            "class Game:\n",
            "    def __init__(self):\n",
            "        self.grid = [[0 for _ in range(Constants.GRID_SIZE)] for _ in range(Constants.GRID_SIZE)]\n",
            "        self.score = 0\n",
            "        self.best_score = 0\n",
            "        self.reset_game()\n",
            "\n",
            "    def reset_game(self):\n",
            "        self.grid = [[0 for _ in range(Constants.GRID_SIZE)] for _ in range(Constants.GRID_SIZE)]\n",
            "        self.score = 0\n",
            "        self.spawn_tile()\n",
            "        self.spawn_tile()\n",
            "\n",
            "    def spawn_tile(self):\n",
            "        empty_tiles = [(x, y) for x in range(Constants.GRID_SIZE) for y in range(Constants.GRID_SIZE) if self.grid[x][y] == 0]\n",
            "        if not empty_tiles:\n",
            "            return False\n",
            "        x, y = random.choice(empty_tiles)\n",
            "        self.grid[x][y] = random.choice([2, 4])\n",
            "        return True\n",
            "\n",
            "    def move(self, direction):\n",
            "        if direction not in ['up', 'down', 'left', 'right']:\n",
            "            return False\n",
            "\n",
            "        rotated_grid = self.grid\n",
            "        if direction in ['up', 'down']:\n",
            "            rotated_grid = self.rotate_grid(rotated_grid)\n",
            "        if direction in ['down', 'right']:\n",
            "            rotated_grid = self.reverse_grid(rotated_grid)\n",
            "\n",
            "        moved, combined = self.shift_tiles(rotated_grid)\n",
            "        if direction in ['down', 'right']:\n",
            "            rotated_grid = self.reverse_grid(rotated_grid)\n",
            "        if direction in ['up', 'down']:\n",
            "            rotated_grid = self.rotate_grid(rotated_grid, reverse=True)\n",
            "\n",
            "        self.grid = rotated_grid\n",
            "        if moved or combined:\n",
            "            self.spawn_tile()\n",
            "        return moved or combined\n",
            "\n",
            "    def shift_tiles(self, grid):\n",
            "        moved = False\n",
            "        combined = False\n",
            "        for row in grid:\n",
            "            slow = 0\n",
            "            for fast in range(1, Constants.GRID_SIZE):\n",
            "                if row[fast] != 0:\n",
            "                    if row[slow] == row[fast]:\n",
            "                        row[slow] *= 2\n",
            "                        row[fast] = 0\n",
            "                        self.score += row[slow]\n",
            "                        combined = True\n",
            "                        slow += 1\n",
            "                    elif row[slow] == 0:\n",
            "                        row[slow] = row[fast]\n",
            "                        row[fast] = 0\n",
            "                        moved = True\n",
            "                    elif row[slow] != row[fast] and slow + 1 != fast:\n",
            "                        slow += 1\n",
            "                        row[slow] = row[fast]\n",
            "                        row[fast] = 0\n",
            "                        moved = True\n",
            "        return moved, combined\n",
            "\n",
            "    def check_game_over(self):\n",
            "        for x in range(Constants.GRID_SIZE):\n",
            "            for y in range(Constants.GRID_SIZE):\n",
            "                if self.grid[x][y] == 0:\n",
            "                    return False\n",
            "                if x < Constants.GRID_SIZE - 1 and self.grid[x][y] == self.grid[x + 1][y]:\n",
            "                    return False\n",
            "                if y < Constants.GRID_SIZE - 1 and self.grid[x][y] == self.grid[x][y + 1]:\n",
            "                    return False\n",
            "        return True\n",
            "\n",
            "    @staticmethod\n",
            "    def rotate_grid(grid, reverse=False):\n",
            "        if reverse:\n",
            "            return [list(row) for row in zip(*grid[::-1])]\n",
            "        return [list(row) for row in zip(*grid)][::-1]\n",
            "\n",
            "    @staticmethod\n",
            "    def reverse_grid(grid):\n",
            "        return [row[::-1] for row in grid]\n",
            "\n",
            "    def combine_tiles(self):\n",
            "        # This method is intentionally left empty as the combination logic is\n",
            "        # handled within the shift_tiles method during the move operation.\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "2024-01-03 12:37:39.137 | INFO     | metagpt.utils.cost_manager:update_cost:48 - Total running cost: $0.148 | Max budget: $10.000 | Current cost: $0.038, prompt_tokens: 1478, completion_tokens: 772\n",
            "2024-01-03 12:37:39.145 | INFO     | metagpt.utils.file_repository:save:60 - save to: /content/workspace/20240103123146/20240103123146/game.py\n",
            "2024-01-03 12:37:39.151 | INFO     | metagpt.utils.file_repository:save:65 - update dependency: /content/workspace/20240103123146/20240103123146/game.py:{'docs/system_design/20240103123305.json', 'docs/tasks/20240103123305.json'}\n",
            "2024-01-03 12:37:39.158 | INFO     | metagpt.actions.write_code:run:128 - Writing ui.py..\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "        pass\n",
            "```## Code: ui.py\n",
            "```python\n",
            "## ui.py\n",
            "\n",
            "import pygame\n",
            "from game import Game\n",
            "from constants import Constants\n",
            "\n",
            "class UI:\n",
            "    def __init__(self, game: Game):\n",
            "        self.game = game\n",
            "        pygame.init()\n",
            "        self.font = pygame.font.SysFont(Constants.FONT, 40)\n",
            "        self.screen = pygame.display.set_mode((Constants.GRID_SIZE * Constants.TILE_SIZE,\n",
            "                                               Constants.GRID_SIZE * Constants.TILE_SIZE))\n",
            "        pygame.display.set_caption('2048 Game')\n",
            "\n",
            "    def draw_grid(self):\n",
            "        for x in range(Constants.GRID_SIZE):\n",
            "            for y in range(Constants.GRID_SIZE):\n",
            "                value = self.game.grid[x][y]\n",
            "                color = Constants.COLORS.get(value, (60, 58, 50))\n",
            "                pygame.draw.rect(self.screen, color, (y * Constants.TILE_SIZE,\n",
            "                                                      x * Constants.TILE_SIZE,\n",
            "                                                      Constants.TILE_SIZE,\n",
            "                                                      Constants.TILE_SIZE))\n",
            "                if value != 0:\n",
            "                    text_surface = self.font.render(f'{value}', True, (0, 0, 0))\n",
            "                    text_rect = text_surface.get_rect(center=(y * Constants.TILE_SIZE + Constants.TILE_SIZE // 2,\n",
            "                                                              x * Constants.TILE_SIZE + Constants.TILE_SIZE // 2))\n",
            "                    self.screen.blit(text_surface, text_rect)\n",
            "\n",
            "    def draw_score(self):\n",
            "        score_surface = self.font.render(f'Score: {self.game.score}', True, (0, 0, 0))\n",
            "        self.screen.blit(score_surface, (5, 5))\n",
            "\n",
            "    def draw_best_score(self):\n",
            "        best_score_surface = self.font.render(f'Best Score: {self.game.best_score}', True, (0, 0, 0))\n",
            "        self.screen.blit(best_score_surface, (5, 45))\n",
            "\n",
            "    def draw_game_over(self):\n",
            "        game_over_surface = self.font.render('Game Over!', True, (255, 0, 0))\n",
            "        game_over_rect = game_over_surface.get_rect(center=(Constants.GRID_SIZE * Constants.TILE_SIZE // 2,\n",
            "                                                            Constants.GRID_SIZE * Constants.TILE_SIZE // 2))\n",
            "        self.screen.blit(game_over_surface, game_over_rect)\n",
            "\n",
            "    def handle_input(self):\n",
            "        for event in pygame.event.get():\n",
            "            if event.type == pygame.QUIT:\n",
            "                return 'quit'\n",
            "            if event.type == pygame.KEYDOWN:\n",
            "                if event.key == pygame.K_UP:\n",
            "                    return 'up'\n",
            "                elif event.key == pygame.K_DOWN:\n",
            "                    return 'down'\n",
            "                elif event.key == pygame.K_LEFT:\n",
            "                    return 'left'\n",
            "                elif event.key == pygame.K_RIGHT:\n",
            "                    return 'right'\n",
            "        return ''\n",
            "\n",
            "    def update_display(self):\n",
            "        self.screen.fill(Constants.COLORS[0])\n",
            "        self.draw_grid()\n",
            "        self.draw_score()\n",
            "        self.draw_best_score()\n",
            "        if self.game.check_game_over():\n",
            "            self.draw_game_over()\n",
            "        pygame.display"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "2024-01-03 12:39:02.588 | INFO     | metagpt.utils.cost_manager:update_cost:48 - Total running cost: $0.189 | Max budget: $10.000 | Current cost: $0.040, prompt_tokens: 2244, completion_tokens: 601\n",
            "2024-01-03 12:39:02.593 | INFO     | metagpt.utils.file_repository:save:60 - save to: /content/workspace/20240103123146/20240103123146/ui.py\n",
            "2024-01-03 12:39:02.599 | INFO     | metagpt.utils.file_repository:save:65 - update dependency: /content/workspace/20240103123146/20240103123146/ui.py:{'docs/system_design/20240103123305.json', 'docs/tasks/20240103123305.json'}\n",
            "2024-01-03 12:39:02.605 | INFO     | metagpt.actions.write_code:run:128 - Writing main.py..\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            ".flip()\n",
            "```## Code: main.py\n",
            "```python\n",
            "## main.py\n",
            "\n",
            "import pygame\n",
            "from game import Game\n",
            "from ui import UI\n",
            "\n",
            "def main():\n",
            "    # Initialize the game and UI\n",
            "    game = Game()\n",
            "    ui = UI(game)\n",
            "\n",
            "    # Main game loop\n",
            "    running = True\n",
            "    while running:\n",
            "        # Handle user input\n",
            "        direction = ui.handle_input()\n",
            "        if direction == 'quit':\n",
            "            running = False\n",
            "        elif direction:\n",
            "            # Perform the move action in the game logic\n",
            "            game.move(direction)\n",
            "\n",
            "        # Update the display with the current game state\n",
            "        ui.update_display()\n",
            "\n",
            "        # Check for game over condition\n",
            "        if game.check_game_over():\n",
            "            # Optionally, here you could handle the end of the game, such as asking the player\n",
            "            # if they want to play again or just exit the game.\n",
            "            running = False\n",
            "\n",
            "    # Quit the game\n",
            "    pygame.quit()\n",
            "\n",
            "if __name__ == \"__main__\":\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "2024-01-03 12:39:30.134 | INFO     | metagpt.utils.cost_manager:update_cost:48 - Total running cost: $0.223 | Max budget: $10.000 | Current cost: $0.034, prompt_tokens: 2839, completion_tokens: 200\n",
            "2024-01-03 12:39:30.139 | INFO     | metagpt.utils.file_repository:save:60 - save to: /content/workspace/20240103123146/20240103123146/main.py\n",
            "2024-01-03 12:39:30.143 | INFO     | metagpt.utils.file_repository:save:65 - update dependency: /content/workspace/20240103123146/20240103123146/main.py:{'docs/system_design/20240103123305.json', 'docs/tasks/20240103123305.json'}\n",
            "2024-01-03 12:39:30.162 | INFO     | metagpt.utils.git_repository:archive:165 - Archive: ['.dependencies.json', '20240103123146/constants.py', '20240103123146/game.py', '20240103123146/main.py', '20240103123146/ui.py', 'docs/prds/20240103123305.json', 'docs/requirement.txt', 'docs/system_design/20240103123305.json', 'docs/tasks/20240103123305.json', 'requirements.txt', 'resources/api_spec_and_tasks/20240103123305.md', 'resources/competitive_analysis/20240103123305.mmd', 'resources/data_api_design/20240103123305.mmd', 'resources/prd/20240103123305.md', 'resources/seq_flow/20240103123305.mmd', 'resources/system_design/20240103123305.md']\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "    main()\n",
            "```"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "# Done!\n",
        "When the run is complete, you should be able to find the generated code under the `workspace` directory.\n",
        "\n",
        "![Screen Shot 2024-01-03 at 8.51.36 PM.png](data:image/png;base64,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)"
      ],
      "metadata": {
        "id": "-GQSxODoUiX2"
      }
    }
  ]
}