{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# GitHub\n",
    "\n",
    "This notebooks shows how you can load issues and pull requests (PRs) for a given repository on [GitHub](https://github.com/). We will use the LangChain Python repository as an example."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Setup access token"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "To access the GitHub API, you need a personal access token - you can set up yours here: https://github.com/settings/tokens?type=beta. You can either set this token as the environment variable ``GITHUB_PERSONAL_ACCESS_TOKEN`` and it will be automatically pulled in, or you can pass it in directly at initializaiton as the ``access_token`` named parameter."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "# If you haven't set your access token as an environment variable, pass it in here.\n",
    "from getpass import getpass\n",
    "\n",
    "ACCESS_TOKEN = getpass()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Load Issues and PRs"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "from langchain.document_loaders import GitHubIssuesLoader"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "loader = GitHubIssuesLoader(\n",
    "    repo=\"langchain-ai/langchain\",\n",
    "    access_token=ACCESS_TOKEN,  # delete/comment out this argument if you've set the access token as an env var.\n",
    "    creator=\"UmerHA\",\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let's load all issues and PRs created by \"UmerHA\".\n",
    "\n",
    "Here's a list of all filters you can use:\n",
    "- include_prs\n",
    "- milestone\n",
    "- state\n",
    "- assignee\n",
    "- creator\n",
    "- mentioned\n",
    "- labels\n",
    "- sort\n",
    "- direction\n",
    "- since\n",
    "\n",
    "For more info, see https://docs.github.com/en/rest/issues/issues?apiVersion=2022-11-28#list-repository-issues."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "docs = loader.load()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "# Creates GitHubLoader (#5257)\r\n",
      "\r\n",
      "GitHubLoader is a DocumentLoader that loads issues and PRs from GitHub.\r\n",
      "\r\n",
      "Fixes #5257\r\n",
      "\r\n",
      "Community members can review the PR once tests pass. Tag maintainers/contributors who might be interested:\r\n",
      "DataLoaders\r\n",
      "- @eyurtsev\r\n",
      "\n",
      "{'url': 'https://github.com/langchain-ai/langchain/pull/5408', 'title': 'DocumentLoader for GitHub', 'creator': 'UmerHA', 'created_at': '2023-05-29T14:50:53Z', 'comments': 0, 'state': 'open', 'labels': ['enhancement', 'lgtm', 'doc loader'], 'assignee': None, 'milestone': None, 'locked': False, 'number': 5408, 'is_pull_request': True}\n"
     ]
    }
   ],
   "source": [
    "print(docs[0].page_content)\n",
    "print(docs[0].metadata)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Only load issues"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "By default, the GitHub API returns considers pull requests to also be issues. To only get 'pure' issues (i.e., no pull requests), use `include_prs=False`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "loader = GitHubIssuesLoader(\n",
    "    repo=\"langchain-ai/langchain\",\n",
    "    access_token=ACCESS_TOKEN,  # delete/comment out this argument if you've set the access token as an env var.\n",
    "    creator=\"UmerHA\",\n",
    "    include_prs=False,\n",
    ")\n",
    "docs = loader.load()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "### System Info\n",
      "\n",
      "LangChain version = 0.0.167\r\n",
      "Python version = 3.11.0\r\n",
      "System = Windows 11 (using Jupyter)\n",
      "\n",
      "### Who can help?\n",
      "\n",
      "- @hwchase17\r\n",
      "- @agola11\r\n",
      "- @UmerHA (I have a fix ready, will submit a PR)\n",
      "\n",
      "### Information\n",
      "\n",
      "- [ ] The official example notebooks/scripts\n",
      "- [X] My own modified scripts\n",
      "\n",
      "### Related Components\n",
      "\n",
      "- [X] LLMs/Chat Models\n",
      "- [ ] Embedding Models\n",
      "- [X] Prompts / Prompt Templates / Prompt Selectors\n",
      "- [ ] Output Parsers\n",
      "- [ ] Document Loaders\n",
      "- [ ] Vector Stores / Retrievers\n",
      "- [ ] Memory\n",
      "- [ ] Agents / Agent Executors\n",
      "- [ ] Tools / Toolkits\n",
      "- [ ] Chains\n",
      "- [ ] Callbacks/Tracing\n",
      "- [ ] Async\n",
      "\n",
      "### Reproduction\n",
      "\n",
      "```\r\n",
      "import os\r\n",
      "os.environ[\"OPENAI_API_KEY\"] = \"...\"\r\n",
      "\r\n",
      "from langchain.chains import LLMChain\r\n",
      "from langchain.chat_models import ChatOpenAI\r\n",
      "from langchain.prompts import PromptTemplate\r\n",
      "from langchain.prompts.chat import ChatPromptTemplate\r\n",
      "from langchain.schema import messages_from_dict\r\n",
      "\r\n",
      "role_strings = [\r\n",
      "    (\"system\", \"you are a bird expert\"), \r\n",
      "    (\"human\", \"which bird has a point beak?\")\r\n",
      "]\r\n",
      "prompt = ChatPromptTemplate.from_role_strings(role_strings)\r\n",
      "chain = LLMChain(llm=ChatOpenAI(), prompt=prompt)\r\n",
      "chain.run({})\r\n",
      "```\n",
      "\n",
      "### Expected behavior\n",
      "\n",
      "Chain should run\n",
      "{'url': 'https://github.com/langchain-ai/langchain/issues/5027', 'title': \"ChatOpenAI models don't work with prompts created via ChatPromptTemplate.from_role_strings\", 'creator': 'UmerHA', 'created_at': '2023-05-20T10:39:18Z', 'comments': 1, 'state': 'open', 'labels': [], 'assignee': None, 'milestone': None, 'locked': False, 'number': 5027, 'is_pull_request': False}\n"
     ]
    }
   ],
   "source": [
    "print(docs[0].page_content)\n",
    "print(docs[0].metadata)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.11.3"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}