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Harrison/GitHub toolkit (#8047)
Co-authored-by: Trevor Dobbertin <trevordobbertin@gmail.com>
This commit is contained in:
Harrison Chase
GitHub
167
docs/extras/modules/agents/toolkits/github.ipynb
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167
docs/extras/modules/agents/toolkits/github.ipynb
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{
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"cells": [
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"# GitHub\n",
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"\n",
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"This notebook goes over how to use the GitHub tool.\n",
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"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",
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"\n",
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"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",
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"```\n",
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"GITHUB_APP_ID\n",
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"GITHUB_APP_PRIVATE_KEY\n",
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"GITHUB_REPOSITORY\n",
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"GITHUB_BRANCH\n",
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"```"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"vscode": {
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"languageId": "shellscript"
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}
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},
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"outputs": [],
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"source": [
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"%pip install pygithub"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 2,
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"metadata": {},
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"outputs": [],
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"source": [
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"import os\n",
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"from langchain.agents import AgentType\n",
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"from langchain.agents import initialize_agent\n",
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"from langchain.agents.agent_toolkits.github.toolkit import GitHubToolkit\n",
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"from langchain.llms import OpenAI\n",
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"from langchain.utilities.github import GitHubAPIWrapper"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 3,
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"metadata": {},
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"outputs": [],
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"source": [
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"os.environ[\"GITHUB_APP_ID\"] = \"your-github-app-id\"\n",
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"os.environ[\"GITHUB_APP_PRIVATE_KEY\"] = \"/path/to/your/private/key\"\n",
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"os.environ[\"GITHUB_REPOSITORY\"] = \"user/repo\"\n",
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"os.environ[\"GITHUB_BRANCH\"] = \"branch-name\"\n",
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"os.environ[\"OPENAI_API_KEY\"] = \"your-openai-api-key\""
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]
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},
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{
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"cell_type": "code",
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"execution_count": 4,
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"metadata": {},
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"outputs": [],
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"source": [
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"llm = OpenAI(temperature=0)\n",
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"github = GitHubAPIWrapper()\n",
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"toolkit = GitHubToolkit.from_github_api_wrapper(github)\n",
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"agent = initialize_agent(\n",
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" toolkit.get_tools(), llm, agent=AgentType.ZERO_SHOT_REACT_DESCRIPTION, verbose=True\n",
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")"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 5,
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"\n",
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"\n",
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"\u001b[1m> Entering new AgentExecutor chain...\u001b[0m\n",
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"\u001b[32;1m\u001b[1;3m I need to figure out what issues need to be completed and how to complete them.\n",
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"Action: Get Issues\n",
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"Action Input: N/A\u001b[0m\n",
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"Observation: \u001b[36;1m\u001b[1;3mFound 1 issues:\n",
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"[{'title': 'Change the main script to print Hello AI!', 'number': 1}]\u001b[0m\n",
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"Thought:\u001b[32;1m\u001b[1;3m I need to get more information about this issue.\n",
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"Action: Get Issue\n",
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"Action Input: 1\u001b[0m\n",
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"Observation: \u001b[33;1m\u001b[1;3m{'title': 'Change the main script to print Hello AI!', 'body': None, 'comments': '[]'}\u001b[0m\n",
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"Thought:\u001b[32;1m\u001b[1;3m I need to update the main script to print Hello AI!\n",
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"Action: Update File\n",
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"Action Input: main.py\n",
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"OLD <<<<\n",
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"print(\"Hello World!\")\n",
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">>>> OLD\n",
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"NEW <<<<\n",
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"print(\"Hello AI!\")\n",
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">>>> NEW\u001b[0m\n",
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"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",
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"Thought:\u001b[32;1m\u001b[1;3m I need to read the current file contents.\n",
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"Action: Read File\n",
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"Action Input: main.py\u001b[0m\n",
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"Observation: \u001b[33;1m\u001b[1;3mprint(\"Hello world!\")\n",
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"\u001b[0m\n",
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"Thought:\u001b[32;1m\u001b[1;3m I need to update the main script to print Hello AI!\n",
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"Action: Update File\n",
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"Action Input: main.py\n",
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"OLD <<<<\n",
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"print(\"Hello world!\")\n",
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">>>> OLD\n",
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"NEW <<<<\n",
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"print(\"Hello AI!\")\n",
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">>>> NEW\u001b[0m\n",
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"Observation: \u001b[38;5;200m\u001b[1;3mUpdated file main.py\u001b[0m\n",
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"Thought:\u001b[32;1m\u001b[1;3m I now know the final answer\n",
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"Final Answer: The main script has been updated to print \"Hello AI!\"\u001b[0m\n",
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"\n",
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"\u001b[1m> Finished chain.\u001b[0m\n"
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]
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},
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{
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"data": {
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"text/plain": [
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"'The main script has been updated to print \"Hello AI!\"'"
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]
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},
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"execution_count": 5,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"agent.run(\n",
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" \"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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")"
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]
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}
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],
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"metadata": {
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"kernelspec": {
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"display_name": "Python 3",
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"language": "python",
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"name": "python3"
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},
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"language_info": {
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"codemirror_mode": {
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"name": "ipython",
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"version": 3
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},
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"file_extension": ".py",
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"mimetype": "text/x-python",
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.11.4"
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},
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"orig_nbformat": 4
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},
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"nbformat": 4,
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"nbformat_minor": 2
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}
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