mirror of
https://github.com/hwchase17/langchain.git
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7378c955db
**Description:** adds support for github tool to query github releases on the configure respository **Issue:** N/A **Dependencies:** N/A **Twitter handle:** @macsdickinson --------- Co-authored-by: Chester Curme <chester.curme@gmail.com>
361 lines
15 KiB
Plaintext
361 lines
15 KiB
Plaintext
{
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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 Toolkit\n",
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"\n",
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"The `Github` toolkit contains tools that enable an LLM agent to interact with a github repository. \n",
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"The tool is a wrapper for the [PyGitHub](https://github.com/PyGithub/PyGithub) library. \n",
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"\n",
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"For detailed documentation of all GithubToolkit features and configurations head to the [API reference](https://python.langchain.com/api_reference/community/agent_toolkits/langchain_community.agent_toolkits.github.toolkit.GitHubToolkit.html).\n",
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"\n",
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"## Setup\n",
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"\n",
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"At a high-level, we will:\n",
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"\n",
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"1. Install the pygithub library\n",
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"2. Create a Github app\n",
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"3. Set your environmental variables\n",
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"4. Pass the tools to your agent with `toolkit.get_tools()`"
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]
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},
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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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"If you want to get automated tracing from runs of individual tools, you can also set your [LangSmith](https://docs.smith.langchain.com/) API key by uncommenting below:"
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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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"outputs": [],
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"source": [
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"# os.environ[\"LANGSMITH_API_KEY\"] = getpass.getpass(\"Enter your LangSmith API key: \")\n",
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"# os.environ[\"LANGSMITH_TRACING\"] = \"true\""
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]
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},
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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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"### Installation\n",
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"\n",
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"#### 1. Install dependencies\n",
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"\n",
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"This integration is implemented in `langchain-community`. We will also need the `pygithub` dependency:"
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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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"outputs": [],
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"source": [
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"%pip install --upgrade --quiet pygithub langchain-community"
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]
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},
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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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"#### 2. Create a Github App\n",
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"\n",
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"[Follow the instructions here](https://docs.github.com/en/apps/creating-github-apps/registering-a-github-app/registering-a-github-app) to create and register a Github app. Make sure your app has the following [repository permissions:](https://docs.github.com/en/rest/overview/permissions-required-for-github-apps?apiVersion=2022-11-28)\n",
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"\n",
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"* Commit statuses (read only)\n",
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"* Contents (read and write)\n",
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"* Issues (read and write)\n",
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"* Metadata (read only)\n",
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"* Pull requests (read and write)\n",
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"\n",
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"Once the app has been registered, you must give your app permission to access each of the repositories you whish it to act upon. Use the App settings on [github.com here](https://github.com/settings/installations).\n",
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"\n",
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"\n",
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"#### 3. Set Environment Variables\n",
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"\n",
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"Before initializing your agent, the following environment variables need to be set:\n",
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"\n",
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"* **GITHUB_APP_ID**- A six digit number found in your app's general settings\n",
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"* **GITHUB_APP_PRIVATE_KEY**- The location of your app's private key .pem file, or the full text of that file as a string.\n",
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"* **GITHUB_REPOSITORY**- The name of the Github repository you want your bot to act upon. Must follow the format \\{username\\}/\\{repo-name\\}. *Make sure the app has been added to this repository first!*\n",
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"* Optional: **GITHUB_BRANCH**- The branch where the bot will make its commits. Defaults to `repo.default_branch`.\n",
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"* Optional: **GITHUB_BASE_BRANCH**- The base branch of your repo upon which PRs will based from. Defaults to `repo.default_branch`."
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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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"outputs": [],
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"source": [
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"import getpass\n",
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"import os\n",
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"\n",
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"for env_var in [\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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"]:\n",
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" if not os.getenv(env_var):\n",
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" os.environ[env_var] = getpass.getpass()"
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]
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},
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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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"## Instantiation\n",
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"\n",
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"Now we can instantiate our toolkit:"
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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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"from langchain_community.agent_toolkits.github.toolkit import GitHubToolkit\n",
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"from langchain_community.utilities.github import GitHubAPIWrapper\n",
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"\n",
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"github = GitHubAPIWrapper()\n",
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"toolkit = GitHubToolkit.from_github_api_wrapper(github)"
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]
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},
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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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"## Tools\n",
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"\n",
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"View available tools:"
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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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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"Get Issues\n",
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"Get Issue\n",
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"Comment on Issue\n",
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"List open pull requests (PRs)\n",
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"Get Pull Request\n",
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"Overview of files included in PR\n",
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"Create Pull Request\n",
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"List Pull Requests' Files\n",
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"Create File\n",
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"Read File\n",
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"Update File\n",
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"Delete File\n",
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"Overview of existing files in Main branch\n",
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"Overview of files in current working branch\n",
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"List branches in this repository\n",
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"Set active branch\n",
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"Create a new branch\n",
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"Get files from a directory\n",
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"Search issues and pull requests\n",
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"Search code\n",
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"Create review request\n"
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]
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}
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],
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"source": [
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"tools = toolkit.get_tools()\n",
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"\n",
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"for tool in tools:\n",
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" print(tool.name)"
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]
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},
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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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"The purpose of these tools is as follows:\n",
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"\n",
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"Each of these steps will be explained in great detail below.\n",
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"\n",
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"1. **Get Issues**- fetches issues from the repository.\n",
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"\n",
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"2. **Get Issue**- fetches details about a specific issue.\n",
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"\n",
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"3. **Comment on Issue**- posts a comment on a specific issue.\n",
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"\n",
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"4. **Create Pull Request**- creates a pull request from the bot's working branch to the base branch.\n",
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"\n",
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"5. **Create File**- creates a new file in the repository.\n",
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"\n",
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"6. **Read File**- reads a file from the repository.\n",
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"\n",
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"7. **Update File**- updates a file in the repository.\n",
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"\n",
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"8. **Delete File**- deletes a file from the repository."
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]
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},
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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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"## Include release tools\n",
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"\n",
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"By default, the toolkit does not include release-related tools. You can include them by setting `include_release_tools=True` when initializing the toolkit:"
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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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"outputs": [],
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"source": [
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"toolkit = GitHubToolkit.from_github_api_wrapper(github, include_release_tools=True)"
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]
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},
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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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"Settings `include_release_tools=True` will include the following tools:\n",
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"\n",
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"* **Get Latest Release**- fetches the latest release from the repository.\n",
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"\n",
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"* **Get Releases**- fetches the latest 5 releases from the repository.\n",
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"\n",
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"* **Get Release**- fetches a specific release from the repository by tag name, e.g. `v1.0.0`.\n"
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]
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},
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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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"## Use within an agent\n",
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"\n",
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"We will need a LLM or chat model:\n",
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"\n",
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"import ChatModelTabs from \"@theme/ChatModelTabs\";\n",
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"\n",
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"<ChatModelTabs customVarName=\"llm\" />\n"
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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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"# | output: false\n",
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"# | echo: false\n",
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"\n",
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"from langchain_openai import ChatOpenAI\n",
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"\n",
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"llm = ChatOpenAI(model=\"gpt-4o-mini\", temperature=0)"
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]
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},
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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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"Initialize the agent with a subset of tools:"
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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": 6,
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"metadata": {},
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"outputs": [],
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"source": [
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"from langgraph.prebuilt import create_react_agent\n",
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"\n",
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"tools = [tool for tool in toolkit.get_tools() if tool.name == \"Get Issue\"]\n",
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"assert len(tools) == 1\n",
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"tools[0].name = \"get_issue\"\n",
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"\n",
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"agent_executor = create_react_agent(llm, tools)"
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]
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},
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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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"And issue it a query:"
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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": 7,
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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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"================================\u001b[1m Human Message \u001b[0m=================================\n",
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"\n",
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"What is the title of issue 24888?\n",
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"==================================\u001b[1m Ai Message \u001b[0m==================================\n",
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"Tool Calls:\n",
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" get_issue (call_iSYJVaM7uchfNHOMJoVPQsOi)\n",
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" Call ID: call_iSYJVaM7uchfNHOMJoVPQsOi\n",
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" Args:\n",
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" issue_number: 24888\n",
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"=================================\u001b[1m Tool Message \u001b[0m=================================\n",
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"Name: get_issue\n",
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"\n",
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"{\"number\": 24888, \"title\": \"Standardize KV-Store Docs\", \"body\": \"To make our KV-store integrations as easy to use as possible we need to make sure the docs for them are thorough and standardized. There are two parts to this: updating the KV-store docstrings and updating the actual integration docs.\\r\\n\\r\\nThis needs to be done for each KV-store integration, ideally with one PR per KV-store.\\r\\n\\r\\nRelated to broader issues #21983 and #22005.\\r\\n\\r\\n## Docstrings\\r\\nEach KV-store class docstring should have the sections shown in the [Appendix](#appendix) below. The sections should have input and output code blocks when relevant.\\r\\n\\r\\nTo build a preview of the API docs for the package you're working on run (from root of repo):\\r\\n\\r\\n```shell\\r\\nmake api_docs_clean; make api_docs_quick_preview API_PKG=openai\\r\\n```\\r\\n\\r\\nwhere `API_PKG=` should be the parent directory that houses the edited package (e.g. community, openai, anthropic, huggingface, together, mistralai, groq, fireworks, etc.). This should be quite fast for all the partner packages.\\r\\n\\r\\n## Doc pages\\r\\nEach KV-store [docs page](https://python.langchain.com/docs/integrations/stores/) should follow [this template](https://github.com/langchain-ai/langchain/blob/master/libs/cli/langchain_cli/integration_template/docs/kv_store.ipynb).\\r\\n\\r\\nHere is an example: https://python.langchain.com/docs/integrations/stores/in_memory/\\r\\n\\r\\nYou can use the `langchain-cli` to quickly get started with a new chat model integration docs page (run from root of repo):\\r\\n\\r\\n```shell\\r\\npoetry run pip install -e libs/cli\\r\\npoetry run langchain-cli integration create-doc --name \\\"foo-bar\\\" --name-class FooBar --component-type kv_store --destination-dir ./docs/docs/integrations/stores/\\r\\n```\\r\\n\\r\\nwhere `--name` is the integration package name without the \\\"langchain-\\\" prefix and `--name-class` is the class name without the \\\"ByteStore\\\" suffix. This will create a template doc with some autopopulated fields at docs/docs/integrations/stores/foo_bar.ipynb.\\r\\n\\r\\nTo build a preview of the docs you can run (from root):\\r\\n\\r\\n```shell\\r\\nmake docs_clean\\r\\nmake docs_build\\r\\ncd docs/build/output-new\\r\\nyarn\\r\\nyarn start\\r\\n```\\r\\n\\r\\n## Appendix\\r\\nExpected sections for the KV-store class docstring.\\r\\n\\r\\n```python\\r\\n \\\"\\\"\\\"__ModuleName__ completion KV-store integration.\\r\\n\\r\\n # TODO: Replace with relevant packages, env vars.\\r\\n Setup:\\r\\n Install ``__package_name__`` and set environment variable ``__MODULE_NAME___API_KEY``.\\r\\n\\r\\n .. code-block:: bash\\r\\n\\r\\n pip install -U __package_name__\\r\\n export __MODULE_NAME___API_KEY=\\\"your-api-key\\\"\\r\\n\\r\\n # TODO: Populate with relevant params.\\r\\n Key init args \\u2014 client params:\\r\\n api_key: Optional[str]\\r\\n __ModuleName__ API key. If not passed in will be read from env var __MODULE_NAME___API_KEY.\\r\\n\\r\\n See full list of supported init args and their descriptions in the params section.\\r\\n\\r\\n # TODO: Replace with relevant init params.\\r\\n Instantiate:\\r\\n .. code-block:: python\\r\\n\\r\\n from __module_name__ import __ModuleName__ByteStore\\r\\n\\r\\n kv_store = __ModuleName__ByteStore(\\r\\n # api_key=\\\"...\\\",\\r\\n # other params...\\r\\n )\\r\\n\\r\\n Set keys:\\r\\n .. code-block:: python\\r\\n\\r\\n kv_pairs = [\\r\\n [\\\"key1\\\", \\\"value1\\\"],\\r\\n [\\\"key2\\\", \\\"value2\\\"],\\r\\n ]\\r\\n\\r\\n kv_store.mset(kv_pairs)\\r\\n\\r\\n .. code-block:: python\\r\\n\\r\\n Get keys:\\r\\n .. code-block:: python\\r\\n\\r\\n kv_store.mget([\\\"key1\\\", \\\"key2\\\"])\\r\\n\\r\\n .. code-block:: python\\r\\n\\r\\n # TODO: Example output.\\r\\n\\r\\n Delete keys:\\r\\n ..code-block:: python\\r\\n\\r\\n kv_store.mdelete([\\\"key1\\\", \\\"key2\\\"])\\r\\n\\r\\n ..code-block:: python\\r\\n \\\"\\\"\\\" # noqa: E501\\r\\n```\", \"comments\": \"[]\", \"opened_by\": \"jacoblee93\"}\n",
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"==================================\u001b[1m Ai Message \u001b[0m==================================\n",
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"\n",
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"The title of issue 24888 is \"Standardize KV-Store Docs\".\n"
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]
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}
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],
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"source": [
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"example_query = \"What is the title of issue 24888?\"\n",
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"\n",
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"events = agent_executor.stream(\n",
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" {\"messages\": [(\"user\", example_query)]},\n",
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" stream_mode=\"values\",\n",
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")\n",
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"for event in events:\n",
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" event[\"messages\"][-1].pretty_print()"
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]
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},
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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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"## API reference\n",
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"\n",
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"For detailed documentation of all `GithubToolkit` features and configurations head to the [API reference](https://python.langchain.com/api_reference/community/agent_toolkits/langchain_community.agent_toolkits.github.toolkit.GitHubToolkit.html)."
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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 (ipykernel)",
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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": "3.13.1"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 4
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}
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