Skip to content

Latest commit

 

History

History
853 lines (638 loc) · 36.9 KB

File metadata and controls

853 lines (638 loc) · 36.9 KB

DEVELOPER.md

This document provides instructions for setting up your development environment and contributing to the Toolbox project.

Prerequisites

Before you begin, ensure you have the following:

  1. Databases: Set up the necessary databases for your development environment.

  2. Go: Install the latest version of Go.

  3. Dependencies: Download and manage project dependencies:

    go get
    go mod tidy

Developing Toolbox

Running from Local Source

  1. Configuration: Create a tools.yaml file to configure your sources and tools. See the Configuration section in the README for details.

  2. CLI Flags: List available command-line flags for the Toolbox server:

    go run . --help
  3. Running the Server: Start the Toolbox server with optional flags. The server listens on port 5000 by default.

    go run .
  4. Testing the Endpoint: Verify the server is running by sending a request to the endpoint:

    curl http://127.0.0.1:5000

Cross Compiling For Windows

Most developers work in a Unix or Unix-like environment.

Compiling for Windows requires the download of zig to provide a C and C++ compiler. These instructions are for cross compiling from Linux x86 but should work for macOS with small changes.

  1. Download zig for your platform.

    cd $HOME
    curl -fL "https://ziglang.org/download/0.15.2/zig-x86_64-linux-0.15.2.tar.xz" -o zig.tar.xz
    tar xf zig.tar.xz

    This will create the directory $HOME/zig-x86_64-linux-0.15.2. You only need to do this once.

    If you are on macOS curl from https://ziglang.org/download/0.15.2/zig-x86_64-macos-0.15.2.tar.xz or https://ziglang.org/download/0.15.2/zig-aarch64-macos-0.15.2.tar.xz.

  2. Change to your MCP Toolbox directory and run the following:

    cd $HOME/genai-toolbox
    GOOS=windows \
    GOARCH=amd64 \
    CGO_ENABLED=1 \
    CC="$HOME/zig-x86_64-linux-0.15.2/zig cc -target x86_64-windows-gnu"  \
    CXX="$HOME/zig-x86_64-linux-0.15.2/zig c++ -target x86_64-windows-gnu" \
    go build -o toolbox.exe

    If you are on macOS alter the path zig-x86_64-linux-0.15.2 to the proper path for your zig installation.

Now the toolbox.exe file is ready to use. Transfer it to your windows machine and test it.

Tool Naming Conventions

This section details the purpose and conventions for MCP Toolbox's tools naming properties, tool name and tool type.

kind: tool
name: cancel_hotel <- tool name
type: postgres-sql  <- tool type
source: my_pg_source

Tool Name

Tool name is the identifier used by a Large Language Model (LLM) to invoke a specific tool.

  • Custom tools: The user can define any name they want. The below guidelines do not apply.
  • Pre-built tools: The tool name is predefined and cannot be changed. It should follow the guidelines.

The following guidelines apply to tool names:

  • Should use underscores over hyphens (e.g., list_collections instead of list-collections).
  • Should not have the product name in the name (e.g., list_collections instead of firestore_list_collections).
  • Superficial changes are NOT considered as breaking (e.g., changing tool name).
  • Non-superficial changes MAY be considered breaking (e.g. adding new parameters to a function) until they can be validated through extensive testing to ensure they do not negatively impact agent's performances.

Tool Type

Tool type serves as a category or type that a user can assign to a tool.

The following guidelines apply to tool types:

  • Should use hyphens over underscores (e.g. firestore-list-collections or firestore_list_colelctions).
  • Should use product name in name (e.g. firestore-list-collections over list-collections).
  • Changes to tool type are breaking changes and should be avoided.

Tool Invocation & Error Handling

To align with the Model Context Protocol (MCP) and ensure robust agentic workflows, Toolbox distinguishes between errors the agent can fix and errors that require developer intervention.

Error Categorization

When implementing Invoke() or ParseParams(), you must return the appropriate error type from internal/util/errors.go. This allows the LLM to attempt a "self-correct" for Agent Errors while signaling a hard stop for Server Errors.

Category Description HTTP Status MCP Result
Agent Error (AgentError) Input/Execution logic errors (e.g., SQL syntax, missing records, invalid params). The agent can fix this. 200 OK isError: true
Server Error (ClientServerError) Infrastructure failures (e.g., DB down, auth failure, network failure). The agent cannot fix this. 500 Internal Error JSON-RPC Error

Implementation Guidelines

Use Typed Errors: Refactor or implement the Tool interface methods to return util.ToolboxError.

In Invoke():

  • Agent Error: Wrap database driver errors (syntax, constraint violations) in AgentError.
  • Server Error: Wrap connection failures or internal logic crashes in ClientServerError.

In ParseParams():

  • Return ToolboxError for missing required parameters or wrong types.
  • Return ClientServerError for failures in resolving authenticated parameters (e.g., invalid tokens).

Example:

func (t *MyTool) Invoke(ctx context.Context, sp tools.SourceProvider, params parameters.ParamValues, token tools.AccessToken) (any, util.ToolboxError) { res, err := t.db.Exec(ctx, params.SQL) if err != nil { // Driver error is likely a syntax issue the LLM can fix return nil, util.NewAgentError("error executing SQL query", err) } return res, nil }

Implementation Guides

Adding a New Database Source or Tool

Please create an issue before implementation to ensure we can accept the contribution and no duplicated work. This issue should include an overview of the API design. If you have any questions, reach out on our Discord to chat directly with the team.

Note

New tools can be added for pre-existing data sources. However, any new database source should also include at least one new tool type.

Adding a New Database Source

We recommend looking at an example source implementation.

  • Create a new directory under internal/sources for your database type (e.g., internal/sources/newdb).
  • Define a configuration struct for your data source in a file named newdb.go. Create a Config struct to include all the necessary parameters for connecting to the database (e.g., host, port, username, password, database name) and a Source struct to store necessary parameters for tools (e.g., Name, Type, connection object, additional config).
  • Implement the SourceConfig interface. This interface requires two methods:
    • SourceConfigType() string: Returns a unique string identifier for your data source (e.g., "newdb").
    • Initialize(ctx context.Context, tracer trace.Tracer) (Source, error): Creates a new instance of your data source and establishes a connection to the database.
  • Implement the Source interface. This interface requires one method:
    • SourceType() string: Returns the same string identifier as SourceConfigType().
  • Implement init() to register the new Source.
  • Implement Unit Tests in a file named newdb_test.go.

Adding a New Tool

Note

Please follow the tool naming convention detailed here.

We recommend looking at an example tool implementation.

Remember to keep your PRs small. For example, if you are contributing a new Source, only include one or two core Tools within the same PR, the rest of the Tools can come in subsequent PRs.

  • Create a new directory under internal/tools for your tool type (e.g., internal/tools/newdb/newdbtool).
  • Define a configuration struct for your tool in a file named newdbtool.go. Create a Config struct and a Tool struct to store necessary parameters for tools.
  • Implement the ToolConfig interface. This interface requires one method:
    • ToolConfigType() string: Returns a unique string identifier for your tool (e.g., "newdb-tool").
    • Initialize(sources map[string]Source) (Tool, error): Creates a new instance of your tool and validates that it can connect to the specified data source.
  • Implement the Tool interface. This interface requires the following methods:
    • Invoke(ctx context.Context, params map[string]any) ([]any, error): Executes the operation on the database using the provided parameters.
    • ParseParams(data map[string]any, claims map[string]map[string]any) (ParamValues, error): Parses and validates the input parameters.
    • Manifest() Manifest: Returns a manifest describing the tool's capabilities and parameters.
    • McpManifest() McpManifest: Returns an MCP manifest describing the tool for use with the Model Context Protocol.
    • Authorized(services []string) bool: Checks if the tool is authorized to run based on the provided authentication services.
  • Implement init() to register the new Tool.
  • Implement Unit Tests in a file named newdbtool_test.go.

Adding Integration Tests

  • Add a test file under a new directory tests/newdb.

  • Add pre-defined integration test suites in the /tests/newdb/newdb_integration_test.go that are required to be run as long as your code contains related features. Please check each test suites for the config defaults, if your source require test suites config updates, please refer to config option:

    1. RunToolGetTest: tests for the GET endpoint that returns the tool's manifest.

    2. RunToolInvokeTest: tests for tool calling through the native Toolbox endpoints.

    3. RunMCPToolCallMethod: tests tool calling through the MCP endpoints.

    4. (Optional) RunExecuteSqlToolInvokeTest: tests an execute-sql tool for any source. Only run this test if you are adding an execute-sql tool.

    5. (Optional) RunToolInvokeWithTemplateParameters: tests for template parameters. Only run this test if template parameters apply to your tool.

  • Add additional tests for the tools that are not covered by the predefined tests. Every tool must be tested!

  • Add the new database to the integration test workflow in integration.cloudbuild.yaml.

Adding Documentation

When updating documentation, you must adhere to the structural constraints enforced by our Diátaxis-based layout and internal linters:

  • Adding a New Data Source:
    • Create a new folder for your integration in the docs/en/integrations/ directory (e.g., docs/en/integrations/newdb/).
    • Create an empty _index.md file. This acts purely as a structural folder wrapper for Hugo. Do not add body content here.
    • Create a source.md file. This is the definitive guide. Add all connection details, authentication, and YAML configurations here. Ensure you include the {{< list-tools >}} shortcode to dynamically display tools.
  • Adding a New Native Tool:
    • Create a nested tools/ directory inside your source (e.g., docs/en/integrations/newdb/tools/).
    • Create an empty _index.md file inside the tools/ directory. It must contain only frontmatter and absolutely no markdown body text.
    • Add the tool details in a <tool_name>.md file in this new tools/ folder. Ensure you include the {{< compatible-sources >}} shortcode.
  • Adding Inherited/Shared Tools (e.g., Managed Databases):
    • If a new database inherits tools from a base integration (like Cloud SQL inheriting Postgres tools), create the tools/ directory with an _index.md file.
    • Map the inherited tools dynamically by adding the shared_tools YAML array to the frontmatter of this tools/_index.md file. This file must strictly contain only frontmatter.
  • Adding Samples:
    • Physical Location:
      1. Quickstarts: docs/en/documentation/getting-started/quickstart/.
      2. Integration-Specific: docs/en/integrations/<db>/samples/. Must include an _index.md with strictly only frontmatter.
      3. General: docs/en/samples/.
    • Frontmatter Requirements (Maintenance): To ensure samples appear correctly in the Samples Section, you must provide the following tags:
      • is_sample: true - Required for indexing.
      • sample_filters: - A YAML array used for UI filtering (e.g., [postgres, go, sql]).
  • Adding Top-Level Sections: If you add a completely new top-level documentation directory (e.g., a new section alongside integrations, documentation), you must update the AI documentation layout files located at .hugo/layouts/index.llms.txt and .hugo/layouts/index.llms-full.txt. Specifically, update the "Diátaxis Narrative Framework" preamble so AI models understand the purpose of your new section.

Adding Prebuilt Tools

You can provide developers with a set of "build-time" tools to aid common software development user journeys like viewing and creating tables/collections and data.

  • Create a set of prebuilt tools by defining a new tools.yaml and adding it to internal/tools. Make sure the file name matches the source (i.e. for source "alloydb-postgres" create a file named "alloydb-postgres.yaml").
  • Update cmd/root.go to add new source to the prebuilt flag.
  • Add tests in internal/prebuiltconfigs/prebuiltconfigs_test.go and cmd/root_test.go.

Testing

Infrastructure

Toolbox uses both GitHub Actions and Cloud Build to run test workflows. Cloud Build is used when Google credentials are required. Cloud Build uses test project "toolbox-testing-438616".

Linting

Code Linting

Run the lint check to ensure code quality:

golangci-lint run --fix

Documentation Structure Linting

To ensure consistency, we enforce a standardized structure for integration Source and Tool pages.

Before pushing changes to integration pages:

Run the source page linter to validate:

# From the repository root
./.ci/lint-docs-source-page.sh

Run the tool page linter to validate:

# From the repository root
./.ci/lint-docs-tool-page.sh

Unit Tests

Execute unit tests locally:

go test -race -v ./cmd/... ./internal/...

Integration Tests

Running Locally

  1. Environment Variables: Set the required environment variables. Refer to the Cloud Build testing configuration for a complete list of variables for each source.

    • SERVICE_ACCOUNT_EMAIL: Use your own GCP email.
    • CLIENT_ID: Use the Google Cloud SDK application Client ID. Contact Toolbox maintainers if you don't have it.
  2. Running Tests: Run the integration test for your target source. Specify the required Go build tags at the top of each integration test file.

    go test -race -v ./tests/<YOUR_TEST_DIR>

    For example, to run the AlloyDB integration test:

    go test -race -v ./tests/alloydbpg
  3. Timeout: The integration test should have a timeout on the server. Look for code like this:

    ctx, cancel := context.WithTimeout(context.Background(), time.Minute)
    defer cancel()
    
    cmd, cleanup, err := tests.StartCmd(ctx, toolsFile, args...)
    if err != nil {
      t.Fatalf("command initialization returned an error: %s", err)
    }
    defer cleanup()

    Be sure to set the timeout to a reasonable value for your tests.

Running on Pull Requests

  • Internal Contributors: Testing workflows should trigger automatically.
  • External Contributors: Request Toolbox maintainers to trigger the testing workflows on your PR.
    • Maintainers can comment /gcbrun to execute the integration tests.
    • Maintainers can add the label tests:run to execute the unit tests.
    • Maintainers can add the label docs: deploy-preview to run the PR Preview workflow.

Test Resources

The following databases have been added as test resources. To add a new database to test against, please contact the Toolbox maintainer team via an issue or PR. Refer to the Cloud Build testing configuration for a complete list of variables for each source.

  • AlloyDB - setup in the test project
    • AI Natural Language (setup instructions) has been configured for alloydb-ai-nl tool tests
    • The Cloud Build service account is a user
  • Bigtable - setup in the test project
    • The Cloud Build service account is a user
  • BigQuery - setup in the test project
    • The Cloud Build service account is a user
  • Cloud SQL Postgres - setup in the test project
    • The Cloud Build service account is a user
  • Cloud SQL MySQL - setup in the test project
    • The Cloud Build service account is a user
  • Cloud SQL SQL Server - setup in the test project
    • The Cloud Build service account is a user
  • Couchbase - setup in the test project via the Marketplace
  • DGraph - using the public dgraph interface https://play.dgraph.io for testing
  • Looker
    • The Cloud Build service account is a user for conversational analytics
    • The Looker instance runs under google.com:looker-sandbox.
  • Memorystore Redis - setup in the test project using a Memorystore for Redis standalone instance
    • Memorystore Redis Cluster, Memorystore Valkey standalone, and Memorystore Valkey Cluster instances all require PSC connections, which requires extra security setup to connect from Cloud Build. Memorystore Redis standalone is the only one allowing PSA connection.
    • The Cloud Build service account is a user
  • Memorystore Valkey - setup in the test project using a Memorystore for Redis standalone instance
    • The Cloud Build service account is a user
  • MySQL - setup in the test project using a Cloud SQL instance
  • Neo4j - setup in the test project on a GCE VM
  • Postgres - setup in the test project using an AlloyDB instance
  • Spanner - setup in the test project
    • The Cloud Build service account is a user
  • SQL Server - setup in the test project using a Cloud SQL instance
  • SQLite - setup in the integration test, where we create a temporary database file

Link Checking and Fixing with Lychee

We use lychee for repository link checks.

Fixing Broken Links

  1. Update the Link: Correct the broken URL or update the content where it is used.

  2. Ignore the Link: If you can't fix the link (e.g., due to external rate-limits or if it's a local-only URL), tell Lychee to ignore it.

    • List regular expressions or direct links in the .lycheeignore file, one entry per line.
    • Always add a comment explaining why the link is being skipped to prevent link rot. Example .lycheeignore:
      # These are email addresses, not standard web URLs, and usually cause check failures.
      ^mailto:.*
      

Note

To avoid build failures in GitHub Actions, follow the linking pattern demonstrated here:
Avoid: (Works in Hugo, breaks Link Checker): [Read more](docs/setup) or [Read more](docs/setup/)
Reason: The link checker cannot find a file named "setup" or a directory with that name containing an index.
Preferred: [Read more](docs/setup.md)
Reason: The GitHub Action finds the physical file. Hugo then uses its internal logic (or render hooks) to resolve this to the correct /docs/setup/ web URL.

Other GitHub Checks

Developing Documentation

Documentation Standards & CI Checks

To maintain consistency and prevent repository bloat, all pull requests must pass the automated documentation linters.

Source Page Structure (integrations/**/source.md)

When adding or updating a Source page, your markdown file must strictly adhere to the following architectural rules:

  • File Name: The configuration guide must be named source.md. (Note: _index.md files are purely structural folder wrappers. Do not add body content to them).
  • LinkTitle: The linkTitle has to be set to the string Source always.
  • Frontmatter: The title field must end with the word "Source" (e.g., title: "Firestore Source").
  • No H1 Headings: Do not use H1 (#) tags in the markdown body. The page title is automatically generated from the frontmatter.
  • H2 Heading Hierarchy: You must use H2 (##) headings in a strict, specific order.
    • Required Headings: About, Example, Reference
    • Allowed Optional Headings: Available Tools, Requirements, Advanced Usage, Troubleshooting, Additional Resources
  • Available Tools Shortcode: If you include the ## Available Tools heading, you must place the list-tools shortcode (e.g., {{< list-tools >}}) directly beneath it.

Tool Page Structure (integrations/**/tools/*.md)

When adding or updating a Tool page, your markdown file must strictly adhere to the following architectural rules:

  • Location: Native tools must be placed inside a nested tools/ directory.
  • Frontmatter: The title field must end with the word "Tool" (e.g., title: "execute-sql Tool").
  • No H1 Headings: Do not use H1 (#) tags in the markdown body. The page title is automatically generated from the frontmatter.
  • H2 Heading Hierarchy: You must use H2 (##) headings in a strict, specific order.
    • Required Headings: About, Example
    • Allowed Optional Headings: Compatible Sources, Requirements, Parameters, Output Format, Reference, Advanced Usage, Troubleshooting, Additional Resources
  • Compatible Sources Shortcode: If you include the ## Compatible Sources heading, you must place the compatible-sources shortcode (e.g., {{< compatible-sources >}}) directly beneath it.

Prebuilt Configuration Structure (integrations/**/prebuilt-configs/*.md)

To ensure new prebuilt configurations are automatically indexed by the {{< list-prebuilt-configs >}} shortcode on the main Prebuilt Configs page, follow these rules:

  • Location: Always place documentation for prebuilt configurations in a nested directory named prebuilt-configs/ inside the database folder (e.g., docs/en/integrations/alloydb/prebuilt-configs/).
  • Index Wrapper: Every prebuilt-configs/ directory must contain an _index.md file. This file acts as the anchor for the directory and must contain the title and description used in the automated lists.
  • Architecture-Based Mapping: Map configurations to database folders based on the kind defined in the tool's YAML file (in internal/prebuiltconfigs/tools/). For example, any tool using the postgres kind should live in the postgres/ integration directory.

Frontend Assets & Layouts

If you need to modify the visual appearance, navigation, or behavior of the documentation website itself, all frontend assets are isolated within the .hugo/ directory.

Repository Asset Limits

  • Max File Size: No individual file within the docs/ directory may exceed 24MB. This prevents repository bloat and ensures fast clone times. If you need to include large assets (like high-resolution videos or massive PDFs), host them externally and link to them in the markdown.

Running a Local Hugo Server

Follow these steps to preview documentation changes locally using a Hugo server:

  1. Install Hugo: Ensure you have Hugo extended edition version 0.146.0 or later installed.

  2. Navigate to the Hugo Directory:

    cd .hugo
  3. Install Dependencies:

    npm ci
  4. Generate Search Index & Start the Server: Because the Pagefind search engine requires physical files to build its index, hugo server (which runs purely in memory) will not display search results by default. To test the search bar locally, build the physical site once (using the development environment to avoid triggering production analytics), generate the index into the static folder, and then start the server:

    hugo --environment development
    npx pagefind --site public --output-path static/pagefind
    hugo server

    (Note: The static/pagefind/ directory is git-ignored to prevent committing local search indexes).

Previewing Documentation on Pull Requests

Documentation preview links are automatically generated and commented on your pull request when working from a branch within the main repository.

For external contributors (forks): For security reasons, automated deployment previews are disabled for pull requests originating from external forks for the cloudflare deployments. To review your documentation changes, please follow the Running a Local Hugo Server instructions to build and view the site on your local machine before requesting a review.

Document Versioning Setup

The documentation uses a dynamic versioning system that outputs standard HTML sites alongside AI-optimized plain text files (llms.txt and llms-full.txt).

Search Indexing: All deployment workflows automatically execute npx pagefind --site public to generate a version-scoped search index specific to that deployment's base URL.

There are 3 GHA workflows we use to achieve document versioning:

  1. Deploy In-development docs: This workflow is run on every commit merged into the main branch. It deploys the built site to the /dev/ subdirectory for the in-development documentation.

  2. Deploy Versioned Docs: When a new GitHub Release is published, it performs two deployments based on the new release tag. One to the new version subdirectory and one to the root directory of the cloudflare-pages branch.

    Note: Before the release PR from release-please is merged, add the newest version into the hugo.toml file.

  3. Deploy Previous Version Docs: This is a manual workflow, started from the GitHub Actions UI. To rebuild and redeploy documentation for an already released version that were released before this new system was in place. This workflow can be started on the UI by providing the git version tag which you want to create the documentation for. The specific versioned subdirectory and the root docs are updated on the cloudflare-pages branch.

Contributors

Request a repo owner to run the preview deployment workflow on your PR. A preview link will be automatically added as a comment to your PR.

Maintainers

  1. Inspect Changes: Review the proposed changes in the PR to ensure they are safe and do not contain malicious code. Pay close attention to changes in the .github/workflows/ directory.
  2. Deploy Preview: Apply the docs: deploy-preview label to the PR to deploy a documentation preview.

Shortcodes

This repository includes custom shortcodes to help with documentation consistency and maintenance. For more information on how they work, see the Hugo Shortcodes documentation and the guide to creating custom shortcodes.

include Shortcode

The include shortcode reads a file and optionally fences it with a language.

Syntax: {{< include "path/to/file" "language" >}}

Example: {{< include "static/headers/license_header.txt" >}} {{< include "samples/program.js" "javascript" >}}

Source: .hugo/layouts/shortcodes/include.html

regionInclude Shortcode

The regionInclude shortcode reads a file, extracts content between [START region_name] and [END region_name], and optionally fences it.

Syntax: {{< regionInclude "path/to/file" "region_name" "language" >}}

Example Markdown: {{< regionInclude "samples/program.js" "program_setup" "javascript" >}}

Example Code Snippet (samples/program.js):

// [START program_setup]
import { Toolbox } from '@googleapis/genai-toolbox';
const toolbox = new Toolbox();
// [END program_setup]

Source: .hugo/layouts/shortcodes/regionInclude.html

Building Toolbox

Building the Binary

  1. Build Command: Compile the Toolbox binary:

    go build -o toolbox
  2. Running the Binary: Execute the compiled binary with optional flags. The server listens on port 5000 by default:

    ./toolbox
  3. Testing the Endpoint: Verify the server is running by sending a request to the endpoint:

    curl http://127.0.0.1:5000

Building Container Images

  1. Build Command: Build the Toolbox container image:

    docker build -t toolbox:dev .
  2. View Image: List available Docker images to confirm the build:

    docker images
  3. Run Container: Run the Toolbox container image using Docker:

    docker run -d toolbox:dev

Developing Toolbox SDKs

Refer to the SDK developer guide for instructions on developing Toolbox SDKs.

Maintainer Information

Team

Team @googleapis/senseai-eco has been set as CODEOWNERS. The GitHub TeamSync tool is used to create this team from MDB Group, senseai-eco. Additionally, database-specific GitHub teams (e.g., @googleapis/toolbox-alloydb) have been created from MDB groups to manage code ownership and review for individual database products.

Issue/PR Triage and SLO

After an issue is created, maintainers will assign the following labels:

  • Priority (defaulted to P0)
  • Type (if applicable)
  • Product (if applicable)

All incoming issues and PRs will follow the following SLO:

Type Priority Objective
Feature Request P0 Must respond within 5 days
Process P0 Must respond within 5 days
Bugs P0 Must respond within 5 days, and resolve/closure within 14 days
Bugs P1 Must respond within 7 days, and resolve/closure within 90 days
Bugs P2 Must respond within 30 days

Types that are not listed in the table do not adhere to any SLO.

Releasing

Toolbox has two types of releases: versioned and continuous. It uses Google Cloud project, database-toolbox.

  • Versioned Release: Official, supported distributions tagged as latest. The release process is defined in versioned.release.cloudbuild.yaml.
  • Continuous Release: Used for early testing of features between official releases and for end-to-end testing. The release process is defined in continuous.release.cloudbuild.yaml.
  • GitHub Release: .github/release-please.yml automatically creates GitHub Releases and release PRs.

How-to Release a new Version

  1. [Optional] If you want to override the version number, send a PR to trigger release-please. You can generate a commit with the following line: git commit -m "chore: release 0.1.0" -m "Release-As: 0.1.0" --allow-empty
  2. [Optional] If you want to edit the changelog, send commits to the release PR
  3. Approve and merge the PR with the title “chore(main): release x.x.x
  4. The trigger should automatically run when a new tag is pushed. You can view triggered builds here to check the status
  5. Update the Github release notes to include the following table:
    1. Run the following command (from the root directory):

      export VERSION="v0.0.0"
      .ci/generate_release_table.sh
      
    2. Copy the table output

    3. In the GitHub UI, navigate to Releases and click the edit button.

    4. Paste the table at the bottom of release note and click Update release.

  6. Post release in internal chat and on Discord.

Supported Binaries

The following operating systems and architectures are supported for binary releases:

  • linux/amd64
  • darwin/arm64
  • darwin/amd64
  • windows/amd64

Supported Container Images

The following base container images are supported for container image releases:

  • distroless

Automated Tests

Integration and unit tests are automatically triggered via Cloud Build on each pull request. Integration tests run on merge and nightly.

Failure notifications

On-merge and nightly tests that fail have notification setup via Cloud Build Failure Reporter GitHub Actions Workflow.

Trigger Setup

Configure a Cloud Build trigger using the UI or gcloud with the following settings:

  • Event: Pull request
  • Region: global (for default worker pools)
  • Source:
    • Generation: 1st gen
    • Repo: googleapis/genai-toolbox (GitHub App)
    • Base branch: ^main$
  • Comment control: Required except for owners and collaborators
  • Filters: Add directory filter
  • Config: Cloud Build configuration file
    • Location: Repository (add path to file)
  • Service account: Set for demo service to enable ID token creation for authenticated services

Triggering Tests

Trigger pull request tests for external contributors by:

  • Cloud Build tests: Comment /gcbrun
  • Unit tests: Add the tests:run label

Repo Setup & Automation

  • .github/blunderbuss.yml - Auto-assign issues and PRs from GitHub teams. Use a product label to assign to a product-specific team member.
  • .github/renovate.json5 - Tooling for dependency updates. Dependabot is built into the GitHub repo for GitHub security warnings
  • go/github-issue-mirror - GitHub issues are automatically mirrored into buganizer
  • (Suspended) .github/sync-repo-settings.yaml - configure repo settings
  • .github/release-please.yml - Creates GitHub releases
  • .github/ISSUE_TEMPLATE - templates for GitHub issues