wehub-resource-sync
952 lines
32 KiB
Plaintext
952 lines
32 KiB
Plaintext
{
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"cells": [
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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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"id": "bCIMTPB1WoTq"
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},
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"outputs": [],
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"source": [
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"# Copyright 2024 Google LLC\n",
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"#\n",
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"# Licensed under the Apache License, Version 2.0 (the \"License\");\n",
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"# you may not use this file except in compliance with the License.\n",
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"# You may obtain a copy of the License at\n",
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"#\n",
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"# https://www.apache.org/licenses/LICENSE-2.0\n",
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"#\n",
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"# Unless required by applicable law or agreed to in writing, software\n",
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"# distributed under the License is distributed on an \"AS IS\" BASIS,\n",
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"# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n",
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"# See the License for the specific language governing permissions and\n",
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"# limitations under the License."
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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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"id": "pPmcMNgZpo9V"
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},
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"source": [
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"# Analyze a codebase with Gemini in Vertex AI\n",
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"\n",
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"<table align=\"left\">\n",
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" <td style=\"text-align: center\">\n",
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" <a href=\"https://colab.research.google.com/github/GoogleCloudPlatform/generative-ai/blob/main/gemini/use-cases/code/analyze_codebase.ipynb\">\n",
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" <img width=\"32px\" src=\"https://www.gstatic.com/pantheon/images/bigquery/welcome_page/colab-logo.svg\" alt=\"Google Colaboratory logo\"><br> Open in Colab\n",
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" </a>\n",
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" </td>\n",
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" <td style=\"text-align: center\">\n",
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" <a href=\"https://console.cloud.google.com/vertex-ai/colab/import/https:%2F%2Fraw.githubusercontent.com%2FGoogleCloudPlatform%2Fgenerative-ai%2Fmain%2Fgemini%2Fuse-cases%2Fcode%2Fanalyze_codebase.ipynb\">\n",
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" <img width=\"32px\" src=\"https://lh3.googleusercontent.com/JmcxdQi-qOpctIvWKgPtrzZdJJK-J3sWE1RsfjZNwshCFgE_9fULcNpuXYTilIR2hjwN\" alt=\"Google Cloud Colab Enterprise logo\"><br> Open in Colab Enterprise\n",
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" </a>\n",
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" </td> \n",
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" <td style=\"text-align: center\">\n",
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" <a href=\"https://console.cloud.google.com/vertex-ai/workbench/deploy-notebook?download_url=https://raw.githubusercontent.com/GoogleCloudPlatform/generative-ai/main/gemini/use-cases/code/analyze_codebase.ipynb\">\n",
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" <img src=\"https://lh3.googleusercontent.com/UiNooY4LUgW_oTvpsNhPpQzsstV5W8F7rYgxgGBD85cWJoLmrOzhVs_ksK_vgx40SHs7jCqkTkCk=e14-rj-sc0xffffff-h130-w32\" alt=\"Vertex AI logo\"><br> Open in Workbench\n",
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" </a>\n",
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" </td>\n",
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" <td style=\"text-align: center\">\n",
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" <a href=\"https://github.com/GoogleCloudPlatform/generative-ai/blob/main/gemini/use-cases/code/analyze_codebase.ipynb\">\n",
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" <img width=\"32px\" src=\"https://raw.githubusercontent.com/primer/octicons/refs/heads/main/icons/mark-github-24.svg\" alt=\"GitHub logo\"><br> View on GitHub\n",
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" </a>\n",
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" </td>\n",
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" <td style=\"text-align: center\">\n",
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" <a href=\"https://goo.gle/40yTNki\">\n",
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" <img width=\"32px\" src=\"https://cdn.qwiklabs.com/assets/gcp_cloud-e3a77215f0b8bfa9b3f611c0d2208c7e8708ed31.svg\" alt=\"Google Cloud logo\"><br> Open in Cloud Skills Boost\n",
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" </a>\n",
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" </td>\n",
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"</table>\n",
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"\n",
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"<div style=\"clear: both;\"></div>\n",
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"\n",
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"<b>Share to:</b>\n",
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"\n",
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"<a href=\"https://www.linkedin.com/sharing/share-offsite/?url=https%3A//github.com/GoogleCloudPlatform/generative-ai/blob/main/gemini/use-cases/code/analyze_codebase.ipynb\" target=\"_blank\">\n",
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" <img width=\"20px\" src=\"https://upload.wikimedia.org/wikipedia/commons/8/81/LinkedIn_icon.svg\" alt=\"LinkedIn logo\">\n",
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"</a>\n",
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"\n",
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"<a href=\"https://bsky.app/intent/compose?text=https%3A//github.com/GoogleCloudPlatform/generative-ai/blob/main/gemini/use-cases/code/analyze_codebase.ipynb\" target=\"_blank\">\n",
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" <img width=\"20px\" src=\"https://upload.wikimedia.org/wikipedia/commons/7/7a/Bluesky_Logo.svg\" alt=\"Bluesky logo\">\n",
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"</a>\n",
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"\n",
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"<a href=\"https://twitter.com/intent/tweet?url=https%3A//github.com/GoogleCloudPlatform/generative-ai/blob/main/gemini/use-cases/code/analyze_codebase.ipynb\" target=\"_blank\">\n",
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" <img width=\"20px\" src=\"https://upload.wikimedia.org/wikipedia/commons/5/5a/X_icon_2.svg\" alt=\"X logo\">\n",
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"</a>\n",
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"\n",
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"<a href=\"https://reddit.com/submit?url=https%3A//github.com/GoogleCloudPlatform/generative-ai/blob/main/gemini/use-cases/code/analyze_codebase.ipynb\" target=\"_blank\">\n",
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" <img width=\"20px\" src=\"https://redditinc.com/hubfs/Reddit%20Inc/Brand/Reddit_Logo.png\" alt=\"Reddit logo\">\n",
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"</a>\n",
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"\n",
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"<a href=\"https://www.facebook.com/sharer/sharer.php?u=https%3A//github.com/GoogleCloudPlatform/generative-ai/blob/main/gemini/use-cases/code/analyze_codebase.ipynb\" target=\"_blank\">\n",
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" <img width=\"20px\" src=\"https://upload.wikimedia.org/wikipedia/commons/5/51/Facebook_f_logo_%282019%29.svg\" alt=\"Facebook logo\">\n",
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"</a> "
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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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"id": "1EExYZvij2ve"
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},
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"source": [
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"| | |\n",
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"|-|-|\n",
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"|Author(s) | [Eric Dong](https://github.com/gericdong), [Holt Skinner](https://github.com/holtskinner), [Aakash Gouda](https://github.com/aksstar)|"
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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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"id": "7yVV6txOmNMn"
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},
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"source": [
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"## Overview\n",
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"\n",
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"Gemini features a breakthrough long context window of up to 1 million tokens that can help seamlessly analyze, classify and summarize large amounts of content within a given prompt.\n",
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"\n",
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"With its long-context reasoning, Gemini can analyze an entire codebase for deeper insights.\n",
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"\n",
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"In this tutorial, you learn how to analyze an entire codebase with Gemini 3 and prompt the model to:\n",
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"\n",
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"- **Analyze**: Summarize codebases effortlessly.\n",
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"- **Guide**: Generate clear developer getting-started documentation.\n",
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"- **Debug**: Uncover critical bugs and provide fixes.\n",
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"- **Enhance**: Implement new features and improve reliability and security.\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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"id": "hdMGtr18rFdL"
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},
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"source": [
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"## Getting Started"
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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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"id": "No17Cw5hgx12"
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},
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"source": [
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"### Install Google Gen AI SDK for Python and other libraries\n",
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"\n",
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"In addition to the [Google Gen AI SDK for Python](https://cloud.google.com/vertex-ai/generative-ai/docs/sdks/overview), we will be using [Gitingest](https://gitingest.com/) to load the repository into the prompt.\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": null,
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"metadata": {
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"id": "tFy3H3aPgx12"
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},
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"outputs": [],
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"source": [
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"%pip install --upgrade --quiet google-genai gitingest gitpython PyGithub"
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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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"id": "R5Xep4W9lq-Z"
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},
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"source": [
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"### Restart runtime (Colab only)\n",
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"\n",
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"To use the newly installed packages in this Jupyter runtime, you must restart the runtime. You can do this by running the cell below, which restarts the current kernel.\n",
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"\n",
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"The restart might take a minute or longer. After it's restarted, continue to the next step."
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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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"id": "XRvKdaPDTznN"
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},
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"outputs": [],
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"source": [
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"import sys\n",
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"\n",
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"if \"google.colab\" in sys.modules:\n",
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" import IPython\n",
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"\n",
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" app = IPython.Application.instance()\n",
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" app.kernel.do_shutdown(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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"id": "SbmM4z7FOBpM"
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},
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"source": [
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"<div class=\"alert alert-block alert-warning\">\n",
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"<b>⚠️ The kernel is going to restart. Please wait until it is finished before continuing to the next step. ⚠️</b>\n",
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"</div>\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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"id": "dmWOrTJ3gx13"
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},
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"source": [
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"### Authenticate your notebook environment (Colab only)\n",
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"\n",
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"If you are running this notebook on Google Colab, run the following cell to authenticate your environment.\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": null,
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"metadata": {
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"id": "NyKGtVQjgx13"
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},
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"outputs": [],
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"source": [
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"import sys\n",
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"\n",
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"if \"google.colab\" in sys.modules:\n",
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" from google.colab import auth\n",
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"\n",
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" auth.authenticate_user()"
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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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"id": "DF4l8DTdWgPY"
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},
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"source": [
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"### Set Google Cloud project information and create client\n",
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"\n",
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"To get started using Vertex AI, you must have an existing Google Cloud project and [enable the Vertex AI API](https://console.cloud.google.com/flows/enableapi?apiid=aiplatform.googleapis.com).\n",
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"\n",
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"Learn more about [setting up a project and a development environment](https://cloud.google.com/vertex-ai/docs/start/cloud-environment)."
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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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"id": "Nqwi-5ufWp_B"
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},
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"outputs": [],
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"source": [
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"import os\n",
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"\n",
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"# fmt: off\n",
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"PROJECT_ID = \"[your-project-id]\" # @param {type: \"string\", placeholder: \"[your-project-id]\", isTemplate: true}\n",
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"# fmt: on\n",
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"if not PROJECT_ID or PROJECT_ID == \"[your-project-id]\":\n",
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" PROJECT_ID = str(os.environ.get(\"GOOGLE_CLOUD_PROJECT\"))\n",
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"\n",
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"LOCATION = os.environ.get(\"GOOGLE_CLOUD_REGION\", \"us-central1\")\n",
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"\n",
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"from google import genai\n",
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"\n",
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"client = genai.Client(enterprise=True, project=PROJECT_ID, location=LOCATION)"
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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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"id": "vbozY-XKee95"
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},
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"source": [
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"### Import libraries"
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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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"id": "NSCFmvOWBas9"
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},
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"outputs": [],
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"source": [
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"import os\n",
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"import shutil\n",
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"\n",
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"import git\n",
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"from IPython.core.interactiveshell import InteractiveShell\n",
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"from IPython.display import Markdown, display\n",
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"from github import Github\n",
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"from gitingest import ingest\n",
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"\n",
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"InteractiveShell.ast_node_interactivity = \"all\"\n",
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"\n",
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"import nest_asyncio\n",
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"from google.genai.types import CreateCachedContentConfig, GenerateContentConfig\n",
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"\n",
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"nest_asyncio.apply()"
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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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"id": "WNoOTMp2fe33"
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},
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"source": [
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"## Cloning a codebase\n",
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"\n",
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"You will use the repo [Online Boutique](https://github.com/GoogleCloudPlatform/microservices-demo) as an example in this notebook.the Online Boutique is a cloud-first microservices demo application. The application is a web-based e-commerce app where users can browse items, add them to the cart, and purchase them. This application consists of 11 microservices across multiple languages."
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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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"id": "GlDOs49qgStM"
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},
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"outputs": [],
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"source": [
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"# The GitHub repository URL\n",
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"# fmt: off\n",
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"repo_url = \"https://github.com/GoogleCloudPlatform/microservices-demo\" # @param {type:\"string\"}\n",
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"# fmt: on\n",
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"\n",
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"# The location to clone the repo\n",
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"repo_dir = \"./repo\""
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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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"id": "PAm1ly9pfIEX"
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},
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"source": [
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"#### Define helper functions for processing GitHub repository"
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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": 32,
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"metadata": {
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"id": "stNia6UaHau2"
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},
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"outputs": [],
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"source": [
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"def clone_repo(repo_url: str, repo_dir: str) -> None:\n",
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" \"\"\"Shallow clone a GitHub repository.\"\"\"\n",
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" if os.path.exists(repo_dir):\n",
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" shutil.rmtree(repo_dir)\n",
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" os.makedirs(repo_dir, exist_ok=True)\n",
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" git.Repo.clone_from(repo_url, repo_dir, depth=2)\n",
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"\n",
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"\n",
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"def get_github_issue(owner: str, repo: str, issue_number: int) -> str | None:\n",
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" \"\"\"Fetch the contents of a GitHub issue.\n",
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"\n",
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" Args:\n",
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" owner (str): The owner of the repository.\n",
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" repo (str): The name of the repository.\n",
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" issue_number (int): The issue number to retrieve.\n",
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"\n",
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" Returns:\n",
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" str | None: The issue body if found, otherwise None.\n",
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"\n",
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" Raises:\n",
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" Exception: If an error occurs while fetching the issue.\n",
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" \"\"\"\n",
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" g = Github()\n",
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"\n",
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" try:\n",
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" repository = g.get_repo(f\"{owner}/{repo}\")\n",
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" issue = repository.get_issue(number=issue_number)\n",
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" return issue.body\n",
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" except Exception as error:\n",
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" print(f\"Error fetching issue: {error}\")\n",
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" return None\n",
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"\n",
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"\n",
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"def get_git_diff(repo_dir: str) -> str:\n",
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" \"\"\"Fetches commit IDs from a local Git repository on a specified branch.\"\"\"\n",
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" repo = git.Repo(repo_dir)\n",
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" branch_name = \"main\"\n",
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"\n",
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" # A list of commit IDs (SHA-1 hashes) in reverse chronological order (newest first)\n",
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" commit_ids = [commit.hexsha for commit in repo.iter_commits(branch_name)]\n",
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" if len(commit_ids) >= 2:\n",
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" return repo.git.diff(commit_ids[0], commit_ids[1])\n",
|
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" return \"\""
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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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"id": "2947e8614485"
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},
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"source": [
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"### Create an index and extract content of a codebase\n",
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"\n",
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"Clone the repo and create an index and extract content of code/text files.\n",
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"\n",
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"Gitingest will extract all of the contents of the files into a long string and create a directory tree of the files."
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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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"id": "4eb417d380c9"
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},
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"outputs": [],
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"source": [
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"clone_repo(repo_url, repo_dir)\n",
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"\n",
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"_, tree, content = ingest(repo_dir)"
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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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"id": "JiVQB5SKekS0"
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},
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"source": [
|
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"## Analyzing the codebase with Gemini\n",
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"\n",
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"With its long-context reasoning, Gemini can process the codebase and answer questions about the codebase."
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {
|
|
"id": "BY1nfXrqRxVX"
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},
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"source": [
|
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"### Load the Gemini model\n",
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"\n",
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"Learn more about the [Gemini API models on Vertex AI](https://cloud.google.com/vertex-ai/generative-ai/docs/learn/models#gemini-models)."
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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": 19,
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"metadata": {
|
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"id": "vB9gY3WruzK9"
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"MODEL_ID = \"gemini-3.5-flash\" # @param {type:\"string\"}"
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]
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},
|
|
{
|
|
"cell_type": "markdown",
|
|
"metadata": {
|
|
"id": "59f3c0bbef54"
|
|
},
|
|
"source": [
|
|
"### Create a context cache\n",
|
|
"\n",
|
|
"We will create a [context cache](https://cloud.google.com/vertex-ai/generative-ai/docs/context-cache/context-cache-overview) of the codebase so we don't have to send the entire context with every request, saving processing time and cost.\n",
|
|
"\n",
|
|
"**Note**: Context caching is only available for stable models with fixed versions (for example, `gemini-3.5-flash`). You must include the version postfix (for example, the `-001`).\n",
|
|
"\n",
|
|
"For more information, see [Available Gemini stable model versions](https://cloud.google.com/vertex-ai/generative-ai/docs/learn/model-versioning#stable-versions-available)."
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {
|
|
"id": "ee211faaf336"
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"system_instruction = \"You are a coding expert. Your mission is to answer all code related questions with given context and instructions.\"\n",
|
|
"\n",
|
|
"contents = [\n",
|
|
" \"\"\"\n",
|
|
" Context:\n",
|
|
" - The entire codebase is provided below.\n",
|
|
" - Here is directory tree of all of the files in the codebase:\n",
|
|
" \"\"\",\n",
|
|
" tree,\n",
|
|
" \"\"\"\n",
|
|
" - Then each of the files are concatenated together. You will find all of the code you need:\n",
|
|
" \"\"\",\n",
|
|
" content,\n",
|
|
"]\n",
|
|
"\n",
|
|
"cached_content = client.caches.create(\n",
|
|
" model=MODEL_ID,\n",
|
|
" config=CreateCachedContentConfig(\n",
|
|
" contents=contents,\n",
|
|
" system_instruction=system_instruction,\n",
|
|
" ttl=\"3600s\",\n",
|
|
" ),\n",
|
|
")"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"metadata": {
|
|
"id": "g3OtaszvJt9L"
|
|
},
|
|
"source": [
|
|
"### 1. Summarizing the codebase\n",
|
|
"\n",
|
|
"Generate a summary of the codebase."
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {
|
|
"id": "uMexx1Qtf1ML"
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"question = \"\"\"\n",
|
|
" Give me a summary of this codebase, and tell me the top 3 things that I can learn from it.\n",
|
|
"\"\"\"\n",
|
|
"\n",
|
|
"# Generate text using non-streaming method\n",
|
|
"response = client.models.generate_content(\n",
|
|
" model=MODEL_ID,\n",
|
|
" contents=question,\n",
|
|
" # Use the cached content\n",
|
|
" config=GenerateContentConfig(\n",
|
|
" cached_content=cached_content.name,\n",
|
|
" ),\n",
|
|
")\n",
|
|
"\n",
|
|
"# Print generated text and usage metadata\n",
|
|
"display(Markdown(response.text))\n",
|
|
"print(response.usage_metadata)"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"metadata": {
|
|
"id": "aCshJHPCYoxI"
|
|
},
|
|
"source": [
|
|
"### 2. Creating a developer getting started guide\n",
|
|
"\n",
|
|
"Generate a getting started guide for developers. This sample uses the streaming option to generate the content."
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {
|
|
"id": "e6Kns7vCYm1P"
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"question = \"\"\"\n",
|
|
" Provide a getting started guide to onboard new developers to the codebase.\n",
|
|
"\"\"\"\n",
|
|
"\n",
|
|
"\n",
|
|
"# Generate text using streaming method\n",
|
|
"responses = client.models.generate_content_stream(\n",
|
|
" model=MODEL_ID,\n",
|
|
" contents=question,\n",
|
|
" config=GenerateContentConfig(\n",
|
|
" cached_content=cached_content.name,\n",
|
|
" ),\n",
|
|
")\n",
|
|
"\n",
|
|
"for response in responses:\n",
|
|
" print(response.text, end=\"\")"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"metadata": {
|
|
"id": "hXurINu-jelb"
|
|
},
|
|
"source": [
|
|
"### 3. Finding bugs\n",
|
|
"\n",
|
|
"Find the top 3 most severe issues in the codebase."
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {
|
|
"id": "fy3AWPRgNhu_"
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"question = \"\"\"\n",
|
|
" Find the top 3 most severe issues in the codebase.\n",
|
|
"\"\"\"\n",
|
|
"\n",
|
|
"responses = client.models.generate_content_stream(\n",
|
|
" model=MODEL_ID,\n",
|
|
" contents=question,\n",
|
|
" config=GenerateContentConfig(\n",
|
|
" cached_content=cached_content.name,\n",
|
|
" ),\n",
|
|
")\n",
|
|
"\n",
|
|
"for response in responses:\n",
|
|
" print(response.text, end=\"\")"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"metadata": {
|
|
"id": "HCilrR6FjmfB"
|
|
},
|
|
"source": [
|
|
"### 4. Fixing bug\n",
|
|
"\n",
|
|
"Find the most severe issue in the codebase that can be fixed and provide a code fix for it.\n"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {
|
|
"id": "dwjDh0xGKE2r"
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"question = \"\"\"\n",
|
|
" Find the most severe bug in the codebase that you can provide a code fix for.\n",
|
|
"\"\"\"\n",
|
|
"\n",
|
|
"responses = client.models.generate_content_stream(\n",
|
|
" model=MODEL_ID,\n",
|
|
" contents=question,\n",
|
|
" config=GenerateContentConfig(\n",
|
|
" cached_content=cached_content.name,\n",
|
|
" ),\n",
|
|
")\n",
|
|
"\n",
|
|
"for response in responses:\n",
|
|
" print(response.text, end=\"\")"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"metadata": {
|
|
"id": "8w2pCULT_xKE"
|
|
},
|
|
"source": [
|
|
"### 5. Implementing a feature request using Function Calling\n",
|
|
"\n",
|
|
"Get the feature request text from a GitHub Issue URL.\n",
|
|
"\n",
|
|
"We will use [Function Calling](https://cloud.google.com/vertex-ai/generative-ai/docs/multimodal/function-calling) to extract the feature request data from the prompt, then call the GitHub API to retrieve the contents.\n",
|
|
"\n",
|
|
"Note: We can't use the previously created cached content, because tools cannot be added at runtime when using cached content, and the other prompts in this notebook do not need this tool."
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {
|
|
"id": "mMjOy0gJ1_xx"
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"FEATURE_REQUEST_URL = (\n",
|
|
" \"https://github.com/GoogleCloudPlatform/microservices-demo/issues/2205\"\n",
|
|
")\n",
|
|
"\n",
|
|
"question = f\"What is the feature request of the following {FEATURE_REQUEST_URL}\"\n",
|
|
"\n",
|
|
"response = client.models.generate_content(\n",
|
|
" model=MODEL_ID,\n",
|
|
" contents=question,\n",
|
|
" # Use the function as a tool\n",
|
|
" config=GenerateContentConfig(\n",
|
|
" tools=[get_github_issue],\n",
|
|
" ),\n",
|
|
")\n",
|
|
"\n",
|
|
"issue_description = response.text\n",
|
|
"display(Markdown(f\"# Feature Request\\n{issue_description}\"))"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"metadata": {
|
|
"id": "19455545f4c9"
|
|
},
|
|
"source": [
|
|
"Use the GitHub Issue text to implement the feature request."
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {
|
|
"id": "78e6df259be8"
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"# Combine feature request content and cached code content\n",
|
|
"question = f\"\"\"Implement the following feature request\n",
|
|
"{issue_description}\n",
|
|
"\"\"\"\n",
|
|
"\n",
|
|
"response = client.models.generate_content(\n",
|
|
" model=MODEL_ID,\n",
|
|
" contents=question,\n",
|
|
" config=GenerateContentConfig(\n",
|
|
" cached_content=cached_content.name,\n",
|
|
" ),\n",
|
|
")\n",
|
|
"\n",
|
|
"# Generate code response\n",
|
|
"display(Markdown(response.text))"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"metadata": {
|
|
"id": "TOk_Qe35b_cJ"
|
|
},
|
|
"source": [
|
|
"### 6. Creating a troubleshooting guide\n",
|
|
"\n",
|
|
"Create a troubleshooting guide to help resolve common issues."
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {
|
|
"id": "DKn85LS-v0iw"
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"question = \"\"\"\n",
|
|
" Provide a troubleshooting guide to help resolve common issues.\n",
|
|
"\"\"\"\n",
|
|
"\n",
|
|
"responses = client.models.generate_content_stream(\n",
|
|
" model=MODEL_ID,\n",
|
|
" contents=question,\n",
|
|
" config=GenerateContentConfig(\n",
|
|
" cached_content=cached_content.name,\n",
|
|
" ),\n",
|
|
")\n",
|
|
"\n",
|
|
"for response in responses:\n",
|
|
" print(response.text, end=\"\")"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"metadata": {
|
|
"id": "h23z0sTsj5pL"
|
|
},
|
|
"source": [
|
|
"### 7. Making the app more reliable\n",
|
|
"\n",
|
|
"Recommend best practices to make the application more reliable.\n"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {
|
|
"id": "yOBSulTPLUAo"
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"question = \"\"\"\n",
|
|
" How can I make this application more reliable? Consider best practices from https://www.r9y.dev/\n",
|
|
"\"\"\"\n",
|
|
"\n",
|
|
"responses = client.models.generate_content_stream(\n",
|
|
" model=MODEL_ID,\n",
|
|
" contents=question,\n",
|
|
" config=GenerateContentConfig(\n",
|
|
" cached_content=cached_content.name,\n",
|
|
" ),\n",
|
|
")\n",
|
|
"\n",
|
|
"for response in responses:\n",
|
|
" print(response.text, end=\"\")"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"metadata": {
|
|
"id": "uf1jNDpJj8u0"
|
|
},
|
|
"source": [
|
|
"### 8. Making the app more secure\n",
|
|
"\n",
|
|
"Recommend best practices to make the application more secure."
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {
|
|
"id": "Hy_mCyFVLlXU"
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"question = \"\"\"\n",
|
|
" How can you secure the application?\n",
|
|
"\"\"\"\n",
|
|
"\n",
|
|
"responses = client.models.generate_content_stream(\n",
|
|
" model=MODEL_ID,\n",
|
|
" contents=question,\n",
|
|
" config=GenerateContentConfig(\n",
|
|
" cached_content=cached_content.name,\n",
|
|
" ),\n",
|
|
")\n",
|
|
"\n",
|
|
"for response in responses:\n",
|
|
" print(response.text, end=\"\")"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"metadata": {
|
|
"id": "GFfwMOb6kYfw"
|
|
},
|
|
"source": [
|
|
"### 9. Learning the codebase\n",
|
|
"\n",
|
|
"Create a quiz about the concepts used in the codebase."
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {
|
|
"id": "l7jQIUwsNRH4"
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"question = \"\"\"\n",
|
|
" Create a quiz about the concepts used in the codebase to help me solidify my understanding.\n",
|
|
"\"\"\"\n",
|
|
"\n",
|
|
"responses = client.models.generate_content_stream(\n",
|
|
" model=MODEL_ID,\n",
|
|
" contents=question,\n",
|
|
" config=GenerateContentConfig(\n",
|
|
" cached_content=cached_content.name,\n",
|
|
" ),\n",
|
|
")\n",
|
|
"\n",
|
|
"for response in responses:\n",
|
|
" print(response.text, end=\"\")"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"metadata": {
|
|
"id": "Rjo1UrZwGLan"
|
|
},
|
|
"source": [
|
|
"### 10. Creating a quickstart tutorial\n",
|
|
"\n",
|
|
"Create an end-to-end quickstart tutorial for a specific component.\n"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {
|
|
"id": "FRwmRyDDFRMB"
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"question = \"\"\"\n",
|
|
" Please write an end-to-end quickstart tutorial that introduces AlloyDB,\n",
|
|
" shows how to configure it with the CartService,\n",
|
|
" and highlights key capabilities of AlloyDB in context of the Online Boutique application.\n",
|
|
"\"\"\"\n",
|
|
"\n",
|
|
"responses = client.models.generate_content_stream(\n",
|
|
" model=MODEL_ID,\n",
|
|
" contents=question,\n",
|
|
" config=GenerateContentConfig(\n",
|
|
" cached_content=cached_content.name,\n",
|
|
" ),\n",
|
|
")\n",
|
|
"\n",
|
|
"for response in responses:\n",
|
|
" print(response.text, end=\"\")"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"metadata": {
|
|
"id": "OAJ-kBCZnlH_"
|
|
},
|
|
"source": [
|
|
"### 11. Creating a Git Changelog Generator\n",
|
|
"\n",
|
|
"Understanding changes made between Git commits and highlighting the most important aspects of the changes."
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {
|
|
"id": "jdeWO8crnlH_"
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"diff_text = get_git_diff(repo_dir)\n",
|
|
"question = f\"\"\"\n",
|
|
" Given the below git diff output, Summarize the important changes made.\n",
|
|
"```diff\n",
|
|
"{diff_text}\n",
|
|
"```\n",
|
|
"\"\"\"\n",
|
|
"\n",
|
|
"responses = client.models.generate_content_stream(\n",
|
|
" model=MODEL_ID,\n",
|
|
" contents=question,\n",
|
|
" config=GenerateContentConfig(\n",
|
|
" cached_content=cached_content.name,\n",
|
|
" ),\n",
|
|
")\n",
|
|
"\n",
|
|
"for response in responses:\n",
|
|
" print(response.text, end=\"\")"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"metadata": {
|
|
"id": "7kUeIBfGyoX7"
|
|
},
|
|
"source": [
|
|
"## Conclusion\n",
|
|
"\n",
|
|
"In this tutorial, you've learned how to use Gemini to analyze a codebase and prompt the model to:\n",
|
|
"\n",
|
|
"- Summarize codebases effortlessly.\n",
|
|
"- Generate clear developer getting-started documentation.\n",
|
|
"- Uncover critical bugs and provide fixes.\n",
|
|
"- Implement new features and improve reliability and security.\n",
|
|
"- Understanding changes made between Git commits"
|
|
]
|
|
}
|
|
],
|
|
"metadata": {
|
|
"colab": {
|
|
"name": "analyze_codebase.ipynb",
|
|
"toc_visible": true
|
|
},
|
|
"kernelspec": {
|
|
"display_name": "Python 3",
|
|
"name": "python3"
|
|
}
|
|
},
|
|
"nbformat": 4,
|
|
"nbformat_minor": 0
|
|
}
|