langchain/docs/extras/integrations/toolkits/github.ipynb

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    "# GitHub\n",
    "\n",
    "This notebook goes over how to use the GitHub tool.\n",
    "The GitHub tool allows agents to interact with a given GitHub repository. It implements CRUD operations for modifying files and can read/comment on Issues. The tool wraps the [PyGitHub](https://github.com/PyGithub/PyGithub) library.\n",
    "\n",
    "In order to interact with the GitHub API you must create a [GitHub app](https://docs.github.com/en/apps/creating-github-apps/about-creating-github-apps/about-creating-github-apps). Next, you must set the following environment variables:\n",
    "```\n",
    "GITHUB_APP_ID\n",
    "GITHUB_APP_PRIVATE_KEY\n",
    "GITHUB_REPOSITORY\n",
    "GITHUB_BRANCH\n",
    "```"
   ]
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  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "vscode": {
     "languageId": "shellscript"
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   "outputs": [],
   "source": [
    "%pip install pygithub"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "import os\n",
    "from langchain.agents import AgentType\n",
    "from langchain.agents import initialize_agent\n",
    "from langchain.agents.agent_toolkits.github.toolkit import GitHubToolkit\n",
    "from langchain.llms import OpenAI\n",
    "from langchain.utilities.github import GitHubAPIWrapper"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "os.environ[\"GITHUB_APP_ID\"] = \"your-github-app-id\"\n",
    "os.environ[\"GITHUB_APP_PRIVATE_KEY\"] = \"/path/to/your/private/key\"\n",
    "os.environ[\"GITHUB_REPOSITORY\"] = \"user/repo\"\n",
    "os.environ[\"GITHUB_BRANCH\"] = \"branch-name\"\n",
    "os.environ[\"OPENAI_API_KEY\"] = \"your-openai-api-key\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "llm = OpenAI(temperature=0)\n",
    "github = GitHubAPIWrapper()\n",
    "toolkit = GitHubToolkit.from_github_api_wrapper(github)\n",
    "agent = initialize_agent(\n",
    "    toolkit.get_tools(), llm, agent=AgentType.ZERO_SHOT_REACT_DESCRIPTION, verbose=True\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "\n",
      "\u001b[1m> Entering new AgentExecutor chain...\u001b[0m\n",
      "\u001b[32;1m\u001b[1;3m I need to figure out what issues need to be completed and how to complete them.\n",
      "Action: Get Issues\n",
      "Action Input: N/A\u001b[0m\n",
      "Observation: \u001b[36;1m\u001b[1;3mFound 1 issues:\n",
      "[{'title': 'Change the main script to print Hello AI!', 'number': 1}]\u001b[0m\n",
      "Thought:\u001b[32;1m\u001b[1;3m I need to get more information about this issue.\n",
      "Action: Get Issue\n",
      "Action Input: 1\u001b[0m\n",
      "Observation: \u001b[33;1m\u001b[1;3m{'title': 'Change the main script to print Hello AI!', 'body': None, 'comments': '[]'}\u001b[0m\n",
      "Thought:\u001b[32;1m\u001b[1;3m I need to update the main script to print Hello AI!\n",
      "Action: Update File\n",
      "Action Input: main.py\n",
      "OLD <<<<\n",
      "print(\"Hello World!\")\n",
      ">>>> OLD\n",
      "NEW <<<<\n",
      "print(\"Hello AI!\")\n",
      ">>>> NEW\u001b[0m\n",
      "Observation: \u001b[38;5;200m\u001b[1;3mFile content was not updated because the old content was not found. It may be helpful to use the read_file action to get the current file contents.\u001b[0m\n",
      "Thought:\u001b[32;1m\u001b[1;3m I need to read the current file contents.\n",
      "Action: Read File\n",
      "Action Input: main.py\u001b[0m\n",
      "Observation: \u001b[33;1m\u001b[1;3mprint(\"Hello world!\")\n",
      "\u001b[0m\n",
      "Thought:\u001b[32;1m\u001b[1;3m I need to update the main script to print Hello AI!\n",
      "Action: Update File\n",
      "Action Input: main.py\n",
      "OLD <<<<\n",
      "print(\"Hello world!\")\n",
      ">>>> OLD\n",
      "NEW <<<<\n",
      "print(\"Hello AI!\")\n",
      ">>>> NEW\u001b[0m\n",
      "Observation: \u001b[38;5;200m\u001b[1;3mUpdated file main.py\u001b[0m\n",
      "Thought:\u001b[32;1m\u001b[1;3m I now know the final answer\n",
      "Final Answer: The main script has been updated to print \"Hello AI!\"\u001b[0m\n",
      "\n",
      "\u001b[1m> Finished chain.\u001b[0m\n"
     ]
    },
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       "'The main script has been updated to print \"Hello AI!\"'"
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     "execution_count": 5,
     "metadata": {},
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   ],
   "source": [
    "agent.run(\n",
    "    \"You have the software engineering capabilities of a Google Principle engineer. You are tasked with completing issues on a github repository. Please look at the existing issues and complete them.\"\n",
    ")"
   ]
  }
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