{ "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=\"hwchase17/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/hwchase17/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=\"hwchase17/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/hwchase17/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 }