How to generate an OpenAPI/Swagger spec with Gnostic

In this tutorial, we’ll start with an OpenAPI document and end with a fully functional gRPC server. We’ll also create a RESTful gateway to the gRPC server, and create SDKs in multiple languages.

You might rightfully ask why we would want to do all of this, and there’s no better way to illustrate a need than by starting with a real example that is entirely plausible and definitely not made up.

Picture this: You’re tasked with setting up an underground bar in the far reaches of the galaxy. Interstellar travelers from far and wide look forward to drinks they’ve never even dreamt of.

Because this is the far future and, obviously, everyone is still using gRPC, we better set up a gRPC server that can handle billions of requests from light years away. gRPC helps us keep throughput high and latency low—both essential elements of an interstellar API. However, even civilizations that have mastered the Dyson Sphere know better than to use gRPC in the browser and other clients. So we’ll need to create an HTTP server to complement our gRPC server. Our users will need SDKs to query our endpoints.

There’s no AI in the Laniakea Supercluster of galaxies who’d be willing to code all of this token by token, so let’s help them generate as much of this as possible.

We’re working with enough acronyms to make our heads spin faster than the neutron star and the space jokes aren’t helping.

Let’s break this down step by step and park the science fiction for the moment. Here’s what we’ll do:

1. Create an OpenAPI document describing our API.
2. Set up a development environment using Docker and dev containers.
3. Install a handful of dependencies.
4. Use Gnostic to generate a binary protocol buffer description of our API.
5. Use the Gnostic gRPC plugin to generate an annotated protocol buffer description of our API.
6. Transcode that description to create a gRPC API.
7. Create our server logic as a Go package.
8. Generate a gRPC gateway to handle HTTP requests and pass these to our server.
9. Use Speakeasy to create SDKs in Python and TypeScript.
10. And finally, test all of this by requesting some spectacular drinks.

Example gRPC and REST API Server Repository

The source code for our complete example is available in the Speakeasy gRPC and REST example repository (opens in a new tab).

This repository already contains all the generated code we’ll cover in this tutorial. You can clone it and follow along with the tutorial, or use it as a reference to build your own gRPC and REST API server.

Creating an OpenAPI Document to Describe an API

As a start, and for the sake of shipping our server, we’ll create an API with only two endpoints.

The first endpoint is createDrink: Create a new drink based on the provided ingredients and return the drink’s name, description, recipe, and possibly a photo.

Our second endpoint is getDrink: Create a new drink based only on the drink’s name. Return a list of ingredients with quantities, a recipe, and a photo.

openapi: 3.0.0

info:
  title: Hitchhiker's Guide to Drinks
  description: An API for creating and retrieving drinks.
  version: 1.0.0

servers:
  - url: http://localhost:8080
    description: Local development server

paths:
  /create-drink:
    post:
      operationId: createDrink
      summary: Create a new drink based on provided ingredients
      requestBody:
        required: true
        content:
          application/json:
            schema:
              $ref: "#/components/schemas/IngredientsRequest"
            example:
              ingredients:
                - Gin
                - Tonic water
                - Lime juice
      responses:
        "200":
          description: Successful response
          content:
            application/json:
              schema:
                $ref: "#/components/schemas/DrinkResponse"
              example:
                name: Pan Galactic Gin and Tonic
                description: A refreshing twist on the classic gin and tonic, inspired by the Hitchhiker's Guide to the Galaxy.
                recipe: Fill a glass with ice. Pour in 2 oz of gin, 4 oz of tonic water, and a squeeze of lime juice. Stir gently and garnish with a lime wedge. Enjoy responsibly while contemplating the vastness of the universe.
                photo: https://example.com/pan-galactic-gin-and-tonic.jpg
        default:
          description: unexpected error
          content:
            application/json:
              schema:
                "$ref": "#/components/schemas/error"

  /get-drink:
    post:
      operationId: getDrink
      summary: Get a drink recipe by providing its name
      requestBody:
        required: true
        content:
          application/json:
            schema:
              $ref: "#/components/schemas/DrinkNameRequest"
            example:
              name: Pan Galactic Gargle Blaster
      responses:
        "200":
          description: Successful response
          content:
            application/json:
              schema:
                $ref: "#/components/schemas/DrinkRecipeResponse"
              example:
                ingredients:
                  - name: Ol' Janx Spirit
                    quantity: 1 bottle
                  - name: Sea water from Santraginus V
                    quantity: 1 measure
                  - name: Acturan Mega-gin
                    quantity: 3 cubes
                  - name: Fallian marsh gas
                    quantity: 4 liters
                  - name: Qualactin Hypermint extract
                    quantity: 1 teaspoon
                recipe: Pour the Ol' Janx Spirit into a glass, add the sea water and Acturan Mega-gin. Bubble the Fallian marsh gas through the mixture, then add the Qualactin Hypermint extract. Drink... but... very carefully.
                photo: https://example.com/pan-galactic-gargle-blaster.jpg
        default:
          description: unexpected error
          content:
            application/json:
              schema:
                "$ref": "#/components/schemas/error"

components:
  schemas:
    IngredientsRequest:
      type: object
      description: A request containing a list of ingredients for creating a new drink.
      properties:
        ingredients:
          type: array
          description: An array of ingredient names as strings.
          example:
            - Gin
            - Tonic water
            - Lime juice
          items:
            type: string
            example: Gin
      required:
        - ingredients

    DrinkResponse:
      type: object
      description: A response containing information about a newly created drink.
      properties:
        name:
          type: string
          description: The name of the drink.
          example: Pan Galactic Gin and Tonic
        description:
          type: string
          description: A brief description of the drink.
          example: A refreshing twist on the classic gin and tonic, inspired by the Hitchhiker's Guide to the Galaxy.
        recipe:
          type: string
          description: The recipe for making the drink.
          example: Fill a glass with ice. Pour in 2 oz of gin, 4 oz of tonic water, and a squeeze of lime juice. Stir gently and garnish with a lime wedge. Enjoy responsibly while contemplating the vastness of the universe.
        photo:
          type: string
          format: uri
          description: A URL pointing to an image of the drink.
          example: https://example.com/pan-galactic-gin-and-tonic.jpg

    DrinkNameRequest:
      type: object
      description: A request containing the name of a drink to retrieve the recipe for.
      properties:
        name:
          type: string
          description: The name of the drink.
          example: Pan Galactic Gargle Blaster
      required:
        - name

    DrinkRecipeResponse:
      type: object
      description: A response containing the recipe and information about a drink.
      properties:
        ingredients:
          type: array
          description: An array of objects representing ingredients and their quantities.
          items:
            $ref: "#/components/schemas/IngredientQuantity"
        recipe:
          type: string
          description: The recipe for making the drink.
          example: Pour the Ol' Janx Spirit into a glass, add the sea water and Acturan Mega-gin. Bubble the Fallian marsh gas through the mixture, then add the Qualactin Hypermint extract. Drink... but... very carefully.
        photo:
          type: string
          format: uri
          description: A URL pointing to an image of the drink.
          example: https://example.com/pan-galactic-gargle-blaster.jpg

    IngredientQuantity:
      type: object
      description: An object representing an ingredient and its quantity.
      properties:
        name:
          type: string
          description: The name of the ingredient.
          example: Ol' Janx Spirit
        quantity:
          type: string
          description: The quantity of the ingredient required.
          example: 1 bottle

    error:
      required:
        - code
        - message
      properties:
        code:
          type: integer
          format: int32
        message:
          type: string
      type: object

Dev Container Configuration

Next, we’ll create a devcontainer.json file in our .devcontainer directory to configure our development container:

{
  "name": "Go",
  // Override the default dockerfile to use our custom Dockerfile
  "dockerComposeFile": ["../docker-compose.yaml", "docker-compose.yaml"],

  "service": "app",
  "workspaceFolder": "/app",
  "shutdownAction": "stopCompose"
}

For help with the devcontainer.json file, check out the official documentation (opens in a new tab).

Docker Compose

We’ll also create a docker-compose.yaml file in our .devcontainer directory to define our development container:

version: "3"
services:
  app:
    build:
      context: .
      dockerfile: .devcontainer/Dockerfile
    volumes:
      - ..:/workspaces:cached
    command: /bin/sh -c "while sleep 1000; do :; done"

This Docker Compose file defines a service called app that uses the Dockerfile in the .devcontainer directory. It also mounts the current directory into the container at /app and overrides the default command to start the server.

We use /bin/sh -c "while sleep 1000; do :; done" as the default command to keep the container running while we work on our server. This means we can start the server manually when we’re ready.

Starting the Development Container

For this step, you’ll need to have Docker (opens in a new tab) and the Dev Containers extension (opens in a new tab) for VS Code installed.

Start the Docker engine and open the project in VS Code. Press F1 to open the command palette, then select Dev Containers: Reopen in Container. This will build the development container and open a new VS Code window inside it.

This step might take a while the first time you run it, as it needs to download the base image and install all the dependencies.

Interacting With the Development Container

Once the development container is running, you can interact with it using the terminal in VS Code. You can run commands as you would in a regular terminal, such as go run main.go to start the server later on.

When we refer to running commands in the development container, we mean running them in the dev container terminal in VS Code.

If you think something isn’t working as expected, try restarting the development container by running Dev Containers: Rebuild Container from the command palette. You may also restart Docker to ensure everything is working as expected.

Dependencies for Generating a gRPC Server Using Gnostic

To generate a gRPC server using Gnostic, we added the following dependencies to our development container:

• Gnostic (opens in a new tab): A compiler for APIs described by the OpenAPI 3.0.0 specification.
• Gnostic gRPC plugin (opens in a new tab): A plugin for Gnostic that generates gRPC service definitions.
• Go protocol buffer compiler (opens in a new tab): A plugin for the protocol buffer compiler that generates Go code.
• Buf (opens in a new tab): A tool for managing protocol buffer files.
• gRPC Go plugin (opens in a new tab): A plugin for the protocol buffer compiler that generates Go gRPC code.
• gRPCurl (opens in a new tab): A command-line tool for interacting with gRPC servers. We’ll use this to test our gRPC server.
• gRPC gateway plugin (opens in a new tab): A plugin for the protocol buffer compiler that generates a reverse proxy server to translate RESTful HTTP and JSON requests to gRPC.

Generating a gRPC Server Using Gnostic

To generate a gRPC server using Gnostic, we need to follow these steps:

1. Compile the API definition to a binary protocol buffer file using Gnostic.
2. Create an API definition in a .proto file.
3. Generate a gRPC service definition using the Gnostic gRPC plugin.
4. Generate Go code using the Go protocol buffer compiler and the gRPC Go plugin.

We’ve already completed step 1 by creating the bar.yaml file. Now we’ll compile the API definition to a binary protocol buffer file using Gnostic.

Compiling the API Definition to a Binary Protocol Buffer File

This step is necessary because we’ve found that the Go protocol buffer compiler and the gRPC Go plugin require a binary protocol buffer file as input. To compile the API definition to a binary protocol buffer file, we’ll use the following command:

gnostic --pb-out=. bar.yaml

This command compiles the API definition in bar.yaml to a binary protocol buffer file named bar.pb.

Creating an API Definition in a .proto File

Next, we’ll create an API definition in a .proto file. We’ll use the bar.pb file generated in the previous step as input. To accomplish this, we’ll use the following command:

gnostic-grpc -input bar.pb -output .

This command generates a .proto file named bar.proto that contains the gRPC service definition:

syntax = "proto3";

package bar;

import "google/api/annotations.proto";

import "google/protobuf/descriptor.proto";

import "google/protobuf/empty.proto";

message IngredientsRequest {
  repeated string ingredients = 1;
}

message DrinkResponse {
  string name = 1;

  string description = 2;

  string recipe = 3;

  string photo = 4;
}

message DrinkNameRequest {
  string name = 1;
}

message DrinkRecipeResponse {
  repeated IngredientQuantity ingredients = 1;

  string recipe = 2;

  string photo = 3;
}

message IngredientQuantity {
  string name = 1;

  string quantity = 2;
}

message Error {
  int32 code = 1;

  string message = 2;
}

//CreateDrinkParameters holds parameters to CreateDrink
message CreateDrinkRequest {
  IngredientsRequest ingredients_request = 1;
}

//GetDrinkParameters holds parameters to GetDrink
message GetDrinkRequest {
  DrinkNameRequest drink_name_request = 1;
}

service Bar {
  rpc CreateDrink ( CreateDrinkRequest ) returns ( DrinkResponse ) {
    option (google.api.http) = { post:"/create-drink" body:"ingredients_request"  };
  }

  rpc GetDrink ( GetDrinkRequest ) returns ( DrinkRecipeResponse ) {
    option (google.api.http) = { post:"/get-drink" body:"drink_name_request"  };
  }
}

Generating Go Code Using Buf and the gRPC Go Plugin

To set up Buf, we need to run the following command:

buf mod init

This command initializes a new Buf module in the current directory.

Update the buf.yaml file created in the project root with the following content:

version: v1
deps:
  - buf.build/googleapis/googleapis

We depend on googleapis because the gRPC Go plugin requires it.

version: v1
managed:
  enabled: true
  go_package_prefix:
    default: github.com/speakeasy-api/grpc-rest-service/bar
    except:
      - buf.build/googleapis/googleapis
      - buf.build/grpc-ecosystem/grpc-gateway
plugins:
  - name: go
    out: bar
    opt:
      - paths=source_relative
  - name: go-grpc
    out: bar
    opt:
      - paths=source_relative
  - plugin: grpc-gateway
    out: bar
    opt:
      - paths=source_relative

Update Buf’s dependencies using the following command:

buf mod update

Now we can generate Go code using the following command:

buf generate

This command generates Go code in the bar directory. The generated code includes the gRPC service definition and the gRPC gateway definition.

Implementing the gRPC Server

To implement the gRPC server, we created one big main.go with our endpoint implementations and business logic all in one. This will make a lot of people very angry and is widely regarded as a bad move. (🫡 Douglas Adams (opens in a new tab))

To make things slightly more confusing, we’re including OpenAI API calls alongside our focus on OpenAPI. The similarities in the names are purely coincidental.

The main.go file is too large to include here, but you can find it in the root of the example project.

Optional: Adding Your OpenAI API Key

If you want to use the OpenAI API to generate drink recipes, you’ll need to add your OpenAI API key to the project. Without this key, the server will return placeholder data for the drink recipes.

Copy the .env.template file to a new file named .env:

cp .env.template .env

Open the .env file and add your OpenAI API key:

OPENAI_API_KEY=your-openai-api-key

This file is included in the .gitignore file, so it won’t be checked into version control.

Rebuilding the Docker Image

We’ve installed a bunch of new dependencies and generated a lot of new code. To make sure everything is working as expected, we need to rebuild our Docker image.

This also runs go mod tidy to ensure all dependencies are up to date, which can take a while.

In VS Code, press F1 to open the command palette, then select Dev Containers: Rebuild Container. This will rebuild the development container and install all the dependencies.

Running the gRPC Server

To run the gRPC server, we need to start the development container and run the following command:

go run main.go

This command starts the gRPC server on port 50051 and the gRPC gateway on port 8080.

Testing the gRPC Server

To test the gRPC server, we’ll use the grpcurl command-line tool.

First, open a new terminal in VS Code by pressing ⌃⇧`.

This next step will use OpenAI credits, so make sure you have credits available before running the command.

Now run the following command to send a request to the gRPC server:

grpcurl -plaintext -d '{"drink_name_request": {"name": "Pan Galactic Gargle Blaster"}}' localhost:50051 bar.Bar/GetDrink

This command sends a request to the GetDrink endpoint with the name field set to Pan Galactic Gargle Blaster.

The response should look something like this:

{
  "ingredients": [
    {
      "name": "Ol' Janx Spirit",
      "quantity": "1 oz"
    },
    {
      "name": "Water from the seas of Santraginus V",
      "quantity": "0.5 oz"
    },
    {
      "name": "Arcturan Mega-gin",
      "quantity": "1 oz"
    },
    {
      "name": "Fallian marsh gas",
      "quantity": "A gentle bubble"
    },
    {
      "name": "Quantum hyper-mint extract",
      "quantity": "1 teaspoon"
    },
    {
      "name": "Zap powder",
      "quantity": "A pinch"
    },
    {
      "name": "Algolian Suntiger tooth extract",
      "quantity": "1 drop"
    },
    {
      "name": "Galaxy-wide famous Olives",
      "quantity": "1 olive"
    }
  ],
  "recipe": "In a cosmic shaker, mix Ol' Janx Spirit, Arcturan Mega-gin, and water from Santraginus V. Gently add fallian marsh gas to create a mystery bubble. Stir in quantum hyper-mint extract and a pinch of zap powder with a molecular stirrer (mind the speed, or you'll end up in another dimension). Carefully add a single drop of Algolian Suntiger tooth extract, ensuring not to evaporate your mixing vessel. Serve in a glass forged from comets' ice, garnished with a galaxy-wide famous Olive. Be sure to have your propulsion system set to the nearest recovery planet because after one sip, you'll need it.",
  "photo": "https://example.com/photo.jpg"
}

The photo URL returned by OpenAI is only valid for an hour, so be sure to open it in a browser to view it.

You may find that the terminal output escapes the JSON response, breaking the photo URL. You can use the following command to unescape the JSON response:

grpcurl -plaintext -d '{"drink_name_request": {"name": "Pan Galactic Gargle Blaster"}}' localhost:50051 bar.Bar/GetDrink | sed 's/%3A/:/g; s/%2F/\//g; s/%3D/=/g; s/%3F/?/g; s/%26/\&/g' | jq

This command uses sed to unescape the JSON response and jq to format the JSON response.

Generating SDKs for the gRPC Gateway

To generate a TypeScript SDK for the gRPC gateway, we run the following command:

speakeasy quickstart

Follow the onscreen prompts to provide the necessary configuration details for your new SDK such as the name, schema location and output path. Enter bar.yaml when prompted for the OpenAPI document location and select TypeScript when prompted for which language you would like to generate.

To generate a Python SDK for the gRPC gateway, we run the following command:

speakeasy quickstart

Follow the onscreen prompts to provide the necessary configuration details for your new SDK such as the name, schema location and output path. Enter bar.yaml when prompted for the OpenAPI document location and select Python when prompted for which language you would like to generate.

Now we have generated SDKs for the gRPC gateway in both TypeScript and Python.