LittleHorse

https://littlehorse.io/docs
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LittleHorse is a distributed runtime and platform for orchestrating workflows, integrations,...
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### Clone LittleHorse examples repository and navigate to quickstart

Source: https://littlehorse.io/docs/getting-started/quickstart

This command clones the LittleHorse examples repository from GitHub and then changes the current directory into the 'quickstart' folder, which contains language-specific quickstart projects.

```Shell
git clone https://github.com/littlehorse-enterprises/lh-examples.git
cd lh-examples/quickstart
```

--------------------------------

### Navigate to Python quickstart directory and set up virtual environment

Source: https://littlehorse.io/docs/getting-started/quickstart

Changes the current directory to the 'python' quickstart folder. It then creates a Python virtual environment, activates it, and installs required dependencies from 'requirements.txt' to prepare the environment for running the quickstart.

```Shell
cd python
python -m venv .venv
source .venv/bin/activate # On Windows: .venv\Scripts\activate
pip install -r requirements.txt
```

--------------------------------

### Install LittleHorse CLI (lhctl) via Homebrew

Source: https://littlehorse.io/docs/getting-started/quickstart

This command uses Homebrew to install the LittleHorse Command Line Interface (CLI) tool, 'lhctl', which is used to interact with the LittleHorse Kernel.

```shell
brew install littlehorse-enterprises/lh/lhctl
```

--------------------------------

### Start LittleHorse Task Workers

Source: https://littlehorse.io/docs/getting-started/quickstart

Provides commands to start task workers in different programming languages (Java, Python, Go, C#) to process TaskRuns from LittleHorse's Task Queue. These workers are essential for WfRuns to progress.

```Java
./gradlew run --args workers
```

```Python
python -m quickstart.workers
```

```Go
go run ./src workers
```

```C#
dotnet run workers -f net9.0
```

--------------------------------

### Navigate to Go quickstart directory

Source: https://littlehorse.io/docs/getting-started/quickstart

Changes the current directory to the 'go' quickstart folder, which contains the Go-specific quickstart files for LittleHorse, including the executable entrypoint, workflow specification, and task workers.

```Shell
cd go
```

--------------------------------

### Navigate to C# quickstart directory

Source: https://littlehorse.io/docs/getting-started/quickstart

Changes the current directory to the 'csharp' quickstart folder, which contains the C#-specific quickstart files for LittleHorse, including the executable entrypoint, workflow specification, and task workers.

```Shell
cd csharp
```

--------------------------------

### Execute LittleHorse Workflow Run with lhctl

Source: https://littlehorse.io/docs/getting-started/quickstart

Demonstrates how to initiate a WfRun using the lhctl run command, passing initial arguments like first-name, last-name, and ssn to the quickstart WfSpec.

```bash
lhctl run quickstart first-name Obi-Wan last-name Kenobi ssn 123456789
```

--------------------------------

### C#: Comprehensive LHConfig Setup Example

Source: https://littlehorse.io/docs/server/developer-guide/client-configuration

Provides a C# example demonstrating multiple ways to initialize LHConfig: from environment variables, a file path, or a dictionary. It also shows how to integrate a logger factory for logging.

```C#
private static LHConfig GetLHConfig(string[] args, ILoggerFactory loggerFactory)
{
    // LHConfig setup from LittleHorse env variables
    var config = new LHConfig(loggerFactory);

    // LHConfig setup from path file
    var userProfilePath = Environment.GetFolderPath(Environment.SpecialFolder.UserProfile);
    string filePath = Path.Combine(userProfilePath, ".config/littlehorse.config");

    if (File.Exists(filePath))
        config = new LHConfig(filePath, loggerFactory);

    // LHConfig setup from dictionary
    if (args.Length > 0)
    {
        var lhConfigs = GetDictionaryFromMainArgs(args);
        config = new LHConfig(lhConfigs, loggerFactory);
    }

    return config;
}
```

--------------------------------

### Navigate to Java quickstart directory

Source: https://littlehorse.io/docs/getting-started/quickstart

Changes the current directory to the 'java' quickstart folder, which contains the Java-specific quickstart files for LittleHorse, including the executable entrypoint, workflow specification, and task workers.

```Shell
cd java
```

--------------------------------

### Run LittleHorse Kernel and Dashboard with Docker

Source: https://littlehorse.io/docs/getting-started/quickstart

This command starts a LittleHorse Kernel and dashboard in a Docker container for local development. It pulls the latest 'lh-standalone' image, names the container, removes it on exit, and maps ports 2023 (Kernel) and 8080 (Dashboard) to the host.

```shell
docker run --pull always --name lh-standalone --rm -d -p 2023:2023 -p 8080:8080 \
  ghcr.io/littlehorse-enterprises/littlehorse/lh-standalone:latest
```

--------------------------------

### Create and Start a LittleHorse Task Worker in Go

Source: https://littlehorse.io/docs/server/developer-guide/task-worker-development

This Go example illustrates how to create and run a LittleHorse Task Worker. It defines a `Greet` function as the task handler and then uses `littlehorse.NewConfigFromEnv()` to configure, `littlehorse.NewTaskWorker()` to create the worker, and finally `RegisterTaskDef()` and `Start()` to register the task definition and begin task execution.

```Go
package main

import (
	"github.com/littlehorse-enterprises/littlehorse/sdk-go/littlehorse"
)

func Greet(firstName string) string {
	return "Hello there, " + firstName + "!"
}

func main() {
	config := littlehorse.NewConfigFromEnv()
	worker, _ := littlehorse.NewTaskWorker(config, Greet, "greet")

	worker.RegisterTaskDef()
	worker.Start()
}
```

--------------------------------

### Run Registered WfSpec using lhctl Command

Source: https://littlehorse.io/docs/server/developer-guide/wfspec-development/basics

This command-line example shows how to execute a previously registered `WfSpec` named 'my-wfspec' using the `lhctl` tool, providing a value for the 'first-name' input variable. This command initiates a workflow run.

```bash
lhctl run my-wfspec first-name Obi-Wan
```

--------------------------------

### Install LittleHorse Kubernetes Operator with Helm

Source: https://littlehorse.io/docs/for-kubernetes/littlehorse/quickstart

Updates Helm repositories and installs the LittleHorse Kubernetes Operator, bundling Strimzi for Kafka management. This command specifies the operator version, namespace, image repository, tag, enables Strimzi deployment, and references the image pull secret.

```bash
helm repo update
helm upgrade --install lh \
    --version 0.13.0 \
    --namespace littlehorse \
    --set image.repository=quay.io/littlehorse/lh-operator \
    --set image.tag=0.13.0 \
    --set strimzi.deploy=true \
    --set strimzi.enabled=true \
    --set 'imagePullSecrets[0].name=littlehorse-pull-secret' \
    littlehorse/lh-operator
```

--------------------------------

### Create and Start a LittleHorse Task Worker in Java

Source: https://littlehorse.io/docs/server/developer-guide/task-worker-development

This Java example demonstrates how to set up a LittleHorse Task Worker. It defines a `MyWorker` class with an `@LHTaskMethod("greet")` annotated method that takes a string and returns a greeting. The `main` method initializes `LHConfig`, creates an `LHTaskWorker`, registers the `greet` TaskDef, and starts the worker to poll for tasks. It also includes a shutdown hook.

```Java
package io.littlehorse.quickstart;

import java.io.IOException;
import io.littlehorse.sdk.common.config.LHConfig;
import io.littlehorse.sdk.worker.LHTaskMethod;
import io.littlehorse.sdk.worker.LHTaskWorker;

class MyWorker {
    @LHTaskMethod("greet")
    public String greeting(String firstName) {
        String result = "Hello there, " + firstName + "!";
        System.out.println(result);
        return result;
    }
}

public class Main {
    public static void main(String[] args) throws IOException, InterruptedException {
        LHConfig config = new LHConfig();

        MyWorker executable = new MyWorker();
        LHTaskWorker greetWorker = new LHTaskWorker(executable, "greet", config);
        Runtime.getRuntime().addShutdownHook(new Thread(greetWorker::close));

        greetWorker.registerTaskDef();

        greetWorker.start();
    }
}
```

--------------------------------

### Define and Register a LittleHorse Task Worker in C#

Source: https://littlehorse.io/docs/server/developer-guide/task-worker-development

This C# example demonstrates how to define a task method using the `[LHTaskMethod]` attribute and how to set up and register an `LHTaskWorker` with the LittleHorse SDK. It illustrates the basic steps to create a worker that can execute a 'greet' task, including configuration and starting the worker.

```csharp
using LittleHorse.Sdk.Worker;

namespace Examples.BasicExample
{
    public class MyWorker
    {
        [LHTaskMethod("greet")]
        public string Greeting(string name)
        {
            var message = $"Hello there {name}!";
            Console.WriteLine($"Executing task greet: " + message);
            return message;
        }
    }

    public class Program
    {
        static void Main(string[] args)
        {
            var config = new LHConfig();

            MyWorker executable = new MyWorker();
            var worker = new LHTaskWorker<MyWorker>(executable, "greet", config);

            worker.RegisterTaskDef();

            Thread.Sleep(1000);

            worker.Start();
        }
    }
}
```

--------------------------------

### LittleHorse Kernel and lhctl Installation

Source: https://littlehorse.io/docs/server/concepts/user-tasks

Commands to install the LittleHorse command-line interface (`lhctl`) and run a local LittleHorse Kernel instance using Docker. These steps are prerequisites for executing the provided code examples.

```bash
brew install littlehorse-enterprises/lh/lhctl
```

```bash
docker run --rm -d --name littlehorse --pull always -p 2023:2023 -p 8080:8080 ghcr.io/littlehorse-enterprises/littlehorse/lh-standalone:latest
```

--------------------------------

### Add LittleHorse Helm Repository

Source: https://littlehorse.io/docs/for-kubernetes/littlehorse/quickstart

Adds the LittleHorse Operator's Helm chart repository to your local Helm configuration, enabling you to fetch and install LittleHorse charts for Kubernetes deployments.

```bash
helm repo add littlehorse https://littlehorse-enterprises.github.io/lh-helm-charts/
```

--------------------------------

### Configuring and Accessing LittleHorse with lhctl

Source: https://littlehorse.io/docs/for-kubernetes/littlehorse/quickstart

This section provides the necessary configuration for lhctl to connect to your LittleHorse cluster, including an example littlehorse.config file. It also includes the kubectl command to port-forward the LittleHorse server service and a lhctl command to test connectivity.

```Text
LHC_API_HOST=localhost
LHC_API_PORT=2023

```

```Bash
kubectl port-forward svc/quickstart-server -n littlehorse 2023:2023

```

```Bash
lhctl whoami

```

--------------------------------

### Clone and Navigate LittleHorse Quickstart Projects

Source: https://littlehorse.io/docs/getting-started/your-first-task-worker

Provides commands to clone and navigate into the LittleHorse quickstart repositories for various programming languages, preparing the environment for Task Worker development.

```Bash
git clone https://github.com/littlehorse-enterprises/lh-quickstart-java.git
cd lh-quickstart-java
```

```Bash
git clone https://github.com/littlehorse-enterprises/lh-quickstart-python.git
cd lh-quickstart-python
```

```Bash
git clone https://github.com/littlehorse-enterprises/lh-quickstart-go.git
cd lh-quickstart-go
```

```Bash
git clone https://github.com/littlehorse-enterprises/lh-quickstart-dotnet.git
cd lh-quickstart-dotnet
```

--------------------------------

### Register LittleHorse Workflow Specification and Task Definitions

Source: https://littlehorse.io/docs/getting-started/quickstart

These commands register the Workflow Specification (WfSpec) and Task Definitions (TaskDef) with LittleHorse. This process creates an 'identity_verified' ExternalEventDef, 'verify_identity', 'notify_customer_verified', and 'notify_customer_not_verified' TaskDefs, and a 'quickstart' WfSpec, which acts as a blueprint for a business process.

```Shell
./gradlew run --args register
```

```Shell
python -m quickstart.register
```

```Shell
go run ./src register
```

```Shell
# Use either `net8.0` or `net9.0`
dotnet run register -f net9.0
```

--------------------------------

### Create and Start a LittleHorse Task Worker in Python

Source: https://littlehorse.io/docs/server/developer-guide/task-worker-development

This Python example demonstrates how to implement an asynchronous LittleHorse Task Worker. It defines an `async` `greeting` function as the task handler. The `main` function initializes `LHConfig`, creates an `LHTaskWorker`, registers the task definition, and then uses `asyncio` to start the worker, allowing it to poll for and execute tasks.

```Python
import asyncio
import littlehorse
from littlehorse.config import LHConfig
from littlehorse.worker import LHTaskWorker

async def greeting(first_name: str) -> str:
    msg = f"Hello there, {first_name}!"
    print(msg)
    return msg

async def main() -> None:
    config = LHConfig()
    worker = LHTaskWorker(greeting, "greet", config)
    worker.register_task_def()

    await asyncio.sleep(1.0)
    await littlehorse.start(worker)

if __name__ == "__main__":
    asyncio.run(main())
```

--------------------------------

### Verify LittleHorse Kernel Connectivity with lhctl

Source: https://littlehorse.io/docs/getting-started/quickstart

This command verifies connectivity to the running LittleHorse Kernel using 'lhctl'. A successful response, like the JSON output shown, indicates that the CLI can communicate with the Kernel.

```shell
>lhctl whoami
{
  "id":  {
    "id":  "anonymous"
  },
  "createdAt":  "2024-12-17T00:12:10.693Z",
  "perTenantAcls":  {},
  "globalAcls":  {
    "acls":  [
      {
        "resources":  [
          "ACL_ALL_RESOURCES"
        ],
        "allowedActions":  [
          "ALL_ACTIONS"
        ],
        "name":  ""
      }
    ]
  }
}
```

--------------------------------

### Python Example: Create and Get UserTaskDef

Source: https://littlehorse.io/docs/server/developer-guide/grpc/managing-metadata

This Python example illustrates how to manually build a `PutUserTaskDefRequest` with `UserTaskField` objects to define a `UserTaskDef`. It then demonstrates creating the `UserTaskDef` and retrieving it using its name and version.

```Python
from littlehorse import create_external_event_def
from littlehorse.config import LHConfig
from littlehorse.model import *
from google.protobuf.json_format import MessageToJson

from time import sleep

if __name__ == '__main__':
    # Get the grpc client
    config = LHConfig()
    client = config.stub()

    # Manually construct the PutUserTaskDefRequest, specifying the fields we want
    # the UserTaskRun's to have.
    put_user_task_def_req = PutUserTaskDefRequest(
        name="my-user-task-def",
        fields=[
            UserTaskField(
                name="isApproved",
                description="Is the request Approved?",
                display_name="Approved?",
                required=True,
            ),
            UserTaskField(
                name="explanation",
                description="Explanation or comments for decision.",
                required=False,
                display_name="Comments",
            )
        ]
    )

    # Create the UserTaskDef
    client.PutUserTaskDef(put_user_task_def_req);

    # Wait for metadata to propagate
    sleep(0.5)

    # Get the UserTaskDef
    user_task_def_id = UserTaskDefId(name="my-user-task-def", version=0)
```

--------------------------------

### OpenID Connect (OIDC) Provider Configuration Example

Source: https://littlehorse.io/docs/user-tasks-bridge/backend/configuration

Example YAML configuration for setting up multiple OpenID Connect (OIDC) identity providers with the User Tasks Bridge. It defines issuer URLs, login labels, username/user ID claims, authority paths, vendor, tenant ID, client ID claims, and associated client IDs for each provider.

```YAML
com:
  c4-soft:
    springaddons:
      oidc:
        ops:
          # First OIDC provider configuration
          - iss: <issuer-url-1>
            label-name: <some-name-used-during-login>
            username-claim: <username-claim-field>
            user-id-claim: <user-id-claim-field>
            authorities:
              - path: $.jsonPath1WhereRolesAre
              - path: $.jsonPath2WhereRolesAre
            vendor: <vendor-1>
            tenant-id: <tenant-id-1>
            client-id-claim: <client-id-claim-field>
            clients:
              - <client-id-1>
              - <client-id-2>

          # Second OIDC provider configuration
          - iss: <issuer-url-2>
            label-name: <some-other-name-used-during-login>
            username-claim: <username-claim-field>
            user-id-claim: <user-id-claim-field>
            authorities:
              - path: $.jsonPath1WhereRolesAre
              - path: $.jsonPath2WhereRolesAre
            vendor: <vendor-2>
            tenant-id: <tenant-id-2>
            client-id-claim: <client-id-claim-field>
            clients:
              - <client-id-3>
```

--------------------------------

### Iterate Through Paginated TaskRuns

Source: https://littlehorse.io/docs/server/developer-guide/grpc/basics

This example demonstrates how to fetch and process paginated lists of `TaskRun`s. It uses the `bookmark` from a previous response to retrieve the next page of results, ensuring all available TaskRuns are processed in batches defined by `limit`.

```Java
package io.littlehorse.quickstart;

import java.io.IOException;
import io.littlehorse.sdk.common.LHLibUtil;
import io.littlehorse.sdk.common.config.LHConfig;
import io.littlehorse.sdk.common.proto.LittleHorseGrpc.LittleHorseBlockingStub;
import io.littlehorse.sdk.common.proto.SearchTaskRunRequest;
import io.littlehorse.sdk.common.proto.TaskRunId;
import io.littlehorse.sdk.common.proto.TaskRunIdList;

public class Main {

    public static void main(String[] args) throws IOException {
        LHConfig config = new LHConfig();
        LittleHorseBlockingStub client = config.getBlockingStub();

        TaskRunIdList results = client.searchTaskRun(SearchTaskRunRequest.newBuilder()
                .setTaskDefName("greet")
                .setLimit(5)
                .build());
        processTaskRuns(results);

        while (results.hasBookmark()) {
            results = client.searchTaskRun(SearchTaskRunRequest.newBuilder()
                    .setTaskDefName("greet")
                    .setLimit(5)
                    .setBookmark(results.getBookmark())
                    .build());

            processTaskRuns(results);
        }
    }

    private static void processTaskRuns(TaskRunIdList taskRuns) {
        System.out.println("Processing a batch of size: " + taskRuns.getResultsCount());
        for (TaskRunId taskRun : taskRuns.getResultsList()) {
            System.out.println(LHLibUtil.protoToJson(taskRun));
        }
    }
}
```

```Go
package main

import (
	"context"
	"fmt"
	"strconv"

	"github.com/littlehorse-enterprises/littlehorse/sdk-go/littlehorse"
	"github.com/littlehorse-enterprises/littlehorse/sdk-go/lhproto"
	// Use the gRPC utilities to inspect gRPC errors
)

func main() {
	// Get a client
	config := littlehorse.NewConfigFromEnv()
	client, _ := config.GetGrpcClient()

	limit := int32(5)
	req := lhproto.SearchTaskRunRequest{
		TaskDefName: "greet",
		Limit:       &limit,
	}
	results, _ := (*client).SearchTaskRun(context.Background(), &req)

	processTaskRuns(results)

	// For some reason GoLang decided to use `for` instead of `while`...
	for results.Bookmark != nil {
		req.Bookmark = results.Bookmark
		results, _ = (*client).SearchTaskRun(context.Background(), &req)
		processTaskRuns(results)
	}
}

func processTaskRuns(taskRuns *lhproto.TaskRunIdList) {
	fmt.Println("Processing a batch of size " + strconv.Itoa(len(taskRuns.Results)))

	for _, taskRunId := range taskRuns.Results {
		littlehorse.PrintProto(taskRunId)
	}
}
```

```Python
from littlehorse.config import LHConfig
from littlehorse.model import *
from google.protobuf.json_format import MessageToJson

def process_task_runs(task_run_ids: TaskRunIdList):
    print("Processing a batch of size " + str(len(task_run_ids.results)))
    for task_run_id in task_run_ids.results:
        print(MessageToJson(task_run_id))

if __name__ == '__main__':
    config = LHConfig()
    client = config.stub()

    results: TaskRunIdList = client.SearchTaskRun(SearchTaskRunRequest(
        task_def_name="greet",
        limit=5,
    ))

    process_task_runs(results)

    # the `HasField()` method is the proper way to check for presence of an
    # `optional` field in python Protobuf.
    while results.HasField("bookmark"):
        new_request = SearchTaskRunRequest(
            task_def_name="greet",
            limit=5,
            # pass in the bookmark from the previous call
            bookmark=results.bookmark,
        )
        results = client.SearchTaskRun(new_request)
        process_task_runs(results)
```

```C#
using LittleHorse.Sdk;
using LittleHorse.Sdk.Common.Proto;

public class Program
{
    static void Main(string[] args)

```

--------------------------------

### Example JSON Output for lhctl WfRun Execution

Source: https://littlehorse.io/docs/getting-started/executing-a-wfrun

Shows the typical JSON response received after executing a `WfRun` using `lhctl`, detailing the `WfRun`'s ID, `WfSpec` details, current status, start time, and thread run information.

```json
{
  "id":  {
    "id":  "69881bf9aaf84c2f84bdde7ceb2dd105"
  },
  "wfSpecId":  {
    "name":  "quickstart",
    "majorVersion":  0,
    "revision":  0
  },
  "oldWfSpecVersions":  [],
  "status":  "RUNNING",
  "greatestThreadrunNumber":  0,
  "startTime":  "2025-01-07T01:53:47.212Z",
  "threadRuns":  [
    {
      "wfSpecId":  {
        "name":  "quickstart",
        "majorVersion":  0,
        "revision":  0
      },
      "number":  0,
      "status":  "RUNNING",
      "threadSpecName":  "entrypoint",
      "startTime":  "2025-01-07T01:53:47.296Z",
      "childThreadIds":  [],
      "haltReasons":  [],
      "currentNodePosition":  1,
      "handledFailedChildren":  [],
      "type":  "ENTRYPOINT"
    }
  ],
  "pendingInterrupts":  [],
  "pendingFailures":  []
}
```

--------------------------------

### Confluent Cloud API Key File Example

Source: https://littlehorse.io/docs/server/operations/docker-compose/confluent-cloud

An example of the content found in a downloaded Confluent Cloud API key file. This file contains the API key, API secret, and the bootstrap server address necessary for connecting to your Confluent Cloud cluster.

```plaintext
=== Confluent Cloud API key: lkc-0595zp ===

API key:
XXXXXXXXXXXXXXXX

API secret:
xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx+xxxxxxxxxxxxxxxxxxxxxxxxxxxxxx

Bootstrap server:
pkc-n98pk.us-west-2.aws.confluent.cloud:9092
```

--------------------------------

### Create and Start a LittleHorse Task Worker in C#

Source: https://littlehorse.io/docs/server/developer-guide/task-worker-development

This section outlines the steps to create a LittleHorse Task Worker in C#. It involves creating an `LHConfig`, defining a Task Worker class with an `LHTaskMethod` attribute, instantiating `LHTaskWorker`, registering the `TaskDef`, and finally starting the worker to process tasks. Note: The provided code snippet is incomplete.

```C#
using LittleHorse.Sdk;
```

--------------------------------

### Install `lhctl` CLI on Mac/Linux via Homebrew

Source: https://littlehorse.io/docs/cloud/accessing-littlehorse-cloud-orchestrator

This command installs the LittleHorse command-line interface (`lhctl`) on macOS and Linux systems using the Homebrew package manager, simplifying the setup process.

```bash
brew install littlehorse-enterprises/lh/lhctl
```

--------------------------------

### Throwing LittleHorse Business Exception with Content

Source: https://littlehorse.io/docs/server/developer-guide/task-worker-development

This example demonstrates how to throw an `LHTaskException` that includes additional content, such as the number of days until an item is back in stock. This content can be accessed by Failure Handlers, providing more context for specific business failures.

```Java
package io.littlehorse.quickstart;

import io.littlehorse.sdk.common.exception.LHTaskException;
import io.littlehorse.sdk.worker.LHTaskMethod;

class MyWorker {
    @LHTaskMethod("ship-item")
    public String shipItem(String itemSku) {
        if (isOutOfStock(itemSku)) {
            int daysUntilBackInStock = calculateDaysUntilBackInStock(itemSku);

            // The `content` of the `Failure` that is thrown will be an INT variable containing
            // the number of days until the item is expected to be back in stock.
            throw new LHTaskException(
                    "out-of-stock",
                    "Some human readable message",
                    daysUntilBackInStock);
        }
        return "Item " + itemSku + " successfully shipped!";
    }
}
```

```Go
package quickstart

import (
  "github.com/littlehorse-enterprises/littlehorse/sdk-go/lhproto"
  "github.com/littlehorse-enterprises/littlehorse/sdk-go/littlehorse"
)
```

--------------------------------

### Post External Event to LittleHorse Workflow with lhctl

Source: https://littlehorse.io/docs/getting-started/quickstart

Illustrates how to post an external event, identity-verified, to a running WfRun using the lhctl postEvent command. This unblocks workflows waiting for specific external triggers.

```bash
lhctl postEvent <wf_run_id> identity-verified BOOL true
```

--------------------------------

### Define and Register WfSpec with Greet TaskDef

Source: https://littlehorse.io/docs/server/developer-guide/wfspec-development/basics

This code demonstrates how to define a `WfSpec` named 'my-wfspec' that declares a required 'first-name' string variable and executes the 'greet' TaskDef with this variable as an argument. It includes the necessary steps to compile and register the `WfSpec` with the LittleHorse cluster. Ensure the 'greet' `TaskDef` is pre-registered.

```Java
package io.littlehorse.quickstart;

import java.io.IOException;
import io.littlehorse.sdk.common.config.LHConfig;
import io.littlehorse.sdk.wfsdk.WfRunVariable;
import io.littlehorse.sdk.wfsdk.Workflow;
import io.littlehorse.sdk.wfsdk.WorkflowThread;
import io.littlehorse.sdk.common.proto.VariableType;

public class Main {
    public static void main(String[] args) throws IOException, InterruptedException {
        LHConfig config = new LHConfig();

        // The `Workflow` object uses the DSL to compile the WfSpec
        Workflow workflowGenerator = Workflow.newWorkflow("my-wfspec", Main::wfLogic);

        // Convenience method to register the `WfSpec` automatically.
        workflowGenerator.registerWfSpec(config.getBlockingStub());
    }

    // NOTE: this can be static or non-static.
    static void wfLogic(WorkflowThread wf) {
        // Required input variable.
        WfRunVariable firstName = wf.declareStr("first-name").required();

        // Execute the `greet` Task and pass in `first-name` as an argument.
        wf.execute("greet", firstName);
    }
}
```

```Go
package main

import (
	"context"
	"log"

	"github.com/littlehorse-enterprises/littlehorse/sdk-go/littlehorse"
	"github.com/littlehorse-enterprises/littlehorse/sdk-go/lhproto"
)

func wfLogic(wf *littlehorse.WorkflowThread) {
	firstName := wf.DeclareStr("first-name").Required()
	wf.Execute("greet", firstName)
}

func main() {
	// Get a client
	config := littlehorse.NewConfigFromEnv()
	client, _ := config.GetGrpcClient()

	workflowGenerator := littlehorse.NewWorkflow(wfLogic, "my-wfspec")

	request, err := workflowGenerator.Compile()
	if err != nil {
		log.Fatal(err)
	}

	(*client).PutWfSpec(context.Background(), request)
}
```

```Python
from littlehorse.workflow import WorkflowThread, WfRunVariable, Workflow
from littlehorse.config import LHConfig
from littlehorse.model import VariableType, PutWfSpecRequest

def workflow_logic(wf: WorkflowThread) -> None:
    first_name: WfRunVariable = wf.declare_str("first-name").required()
    wf.execute("greet", first_name)

if __name__ == '__main__':
    config = LHConfig()
    client = config.stub()

    workflow_generator = Workflow("my-wfspec", workflow_logic)
    request: PutWfSpecRequest = workflow_generator.compile()

    client.PutWfSpec(request)
```

```C#
using LittleHorse.Sdk;
using LittleHorse.Sdk.Common.Proto;
using LittleHorse.Sdk.Workflow.Spec;

public class Program
{
    static void Main(string[] args)
    {
        var config = new LHConfig();
        var lhClient = config.GetGrpcClientInstance();

        var workflow = new Workflow("my-wfspec", WfLogic);
        workflow.RegisterWfSpec(lhClient);
    }

    // NOTE: this can be static or non-static.
    static void WfLogic(WorkflowThread wf)
    {
        // Required input variable.
        WfRunVariable firstName = wf.DeclareStr("first-name").Required();

        // Execute the `greet` Task and pass in `first-name` as an argument.
        wf.Execute("greet", firstName);
    }
}
```

--------------------------------

### CLI: Example littlehorse.config File

Source: https://littlehorse.io/docs/server/developer-guide/client-configuration

Illustrates the structure of a `littlehorse.config` file used by the `lhctl` CLI, specifying the API host and port for connection.

```INI
LHC_API_HOST=localhost
LHC_API_PORT=2023
```

--------------------------------

### lhctl Run Workflow - Second User ID Example

Source: https://littlehorse.io/docs/server/concepts/variables

An additional example of running the `variables-example` workflow with a different user ID (`obiwan`) to create more data for demonstrating variable searching capabilities.

```lhctl
lhctl run variables-example user-id obiwan
```

--------------------------------

### Pass WfRunVariables as Task Inputs

Source: https://littlehorse.io/docs/server/developer-guide/wfspec-development/basics

Shows how to declare `WfRunVariable` instances (string and integer) and then use these variables as inputs when executing a task.

```Java
public void threadFunction(WorkflowThread thread) {
    WfRunVariable myStr = thread.declareStr("my-str");
    WfRunVariable myInt = thread.declareInt("my-int");

    thread.execute("foo", myStr, myInt);
}
```

```Go
func threadFunction(thread *littlehorse.WorkflowThread) {
    myStr := thread.DeclareStr("my-str")
    myInt := thread.DeclareInt("my-int")

    thread.Execute("foo", myStr, myInt)
}
```

```Python
def thread_function(thread: WorkflowThread) -> None:
    my_str = thread.declare_str("my-str")
    my_int = thread.declare_str("my-int")
    thread.execute("foo", my_str, my_int)
```

```C#
public void ThreadFunction(WorkflowThread thread)
{
    WfRunVariable myStr = thread.DeclareStr("my-str");
    WfRunVariable myInt = thread.DeclareStr("my-int");

    thread.Execute("foo", myStr, myInt);
}
```

--------------------------------

### Initialize and Start LittleHorse Task Worker in Go

Source: https://littlehorse.io/docs/getting-started/your-first-task-worker

This Go code snippet demonstrates how to set up and run a LittleHorse Task Worker. It creates a new TaskWorker using a configuration derived from environment variables, registers its task definition, and then starts the worker.

```Go
package main

import (
 "github.com/littlehorse-enterprises/littlehorse/sdk-go/littlehorse"
)

var config = littlehorse.NewConfigFromEnv()

func main() {
 greetingWorker, _ := littlehorse.NewTaskWorker(config, NormalGoMethod, "greet")
 greetingWorker.RegisterTaskDef()
 greetingWorker.Start()
}
```

--------------------------------

### Verify LittleHorse Operator Pods Status

Source: https://littlehorse.io/docs/for-kubernetes/littlehorse/quickstart

Checks the status of the deployed LittleHorse Operator and Strimzi Cluster Operator pods within the 'littlehorse' namespace, confirming they are running successfully after installation.

```bash
kubectl get pods -nlittlehorse
NAME                                        READY   STATUS    RESTARTS   AGE
lh-lh-operator-676687bff8-jdl56             1/1     Running   0          24s
strimzi-cluster-operator-6948497896-w7cx7   1/1     Running   0          38s
```

--------------------------------

### Verify LittleHorse CLI and Kernel Server Status

Source: https://littlehorse.io/docs/server/developer-guide/install

After the `lh-standalone` Docker container is running, execute this command to check the version of the `lhctl` utility and confirm that the LittleHorse Kernel server is active and reporting its version. Note that the server might take 20-40 seconds to start.

```Shell
lhctl version
```

--------------------------------

### Install User Tasks Bridge API Client

Source: https://littlehorse.io/docs/user-tasks-bridge/api-client

Commands to install the User Tasks Bridge API Client using various package managers like npm, yarn, pnpm, and bun.

```sh
npm install @littlehorse-enterprises/user-tasks-bridge-api-client
```

```sh
yarn add @littlehorse-enterprises/user-tasks-bridge-api-client
```

```sh
pnpm add @littlehorse-enterprises/user-tasks-bridge-api-client
```

```sh
bun add @littlehorse-enterprises/user-tasks-bridge-api-client
```

--------------------------------

### Run LittleHorse Java Task Worker with Gradle

Source: https://littlehorse.io/docs/getting-started/your-first-task-worker

This command executes the LittleHorse Java Task Worker using Gradle. It assumes a standard Gradle project setup where `gradlew run` is configured to start the main application.

```Shell
./gradlew run
```

--------------------------------

### Pass Hard-coded Input Variables to a Task

Source: https://littlehorse.io/docs/server/developer-guide/wfspec-development/basics

Demonstrates how to pass hard-coded string and integer values directly as input arguments when executing a task using `thread.execute()`.

```Java
String inputStrVal = "input string value!";
int inputIntVal = 54321;
thread.execute("foo", inputStrVal, inputIntVal);
```

```Go
inputStrVal := "input string value!"
inputIntVal := 54321
thread.Execute("foo", inputStrVal, inputIntVal)
```

```Python
str_val = "input string value!"
int_val = 54321
thread.execute("foo", str_val, int_val)
```

```C#
string inputStrVal = "input string value!";
int inputIntVal = 54321;
thread.Execute("foo", inputStrVal, inputIntVal);
```

--------------------------------

### Run LittleHorse Kernel for Local Development using Docker

Source: https://littlehorse.io/docs/server/developer-guide/install

This Docker command starts a `lh-standalone` container, which includes the LittleHorse Kernel. It's designed for local development, pulling the latest image and mapping necessary ports for access.

```Shell
docker run --pull always --name littlehorse -d -p 2023:2023 -p 8080:8080 ghcr.io/littlehorse-enterprises/littlehorse/lh-standalone:latest
```

--------------------------------

### Go Example: Create UserTaskDef

Source: https://littlehorse.io/docs/server/developer-guide/grpc/managing-metadata

This Go example shows how to programmatically construct a `PutUserTaskDefRequest` to define a `UserTaskDef` with specified fields and a description, then register it with the LittleHorse client.

```Go
config := littlehorse.NewConfigFromEnv()
client, err := config.GetGrpcClient()

description := "this is a cool usertaskdef!"
result, err := (*client).PutUserTaskDef(context.Background(),
     &lhproto.PutUserTaskDefRequest{
        Name: "my-user-task",
		Fields: []*lhproto.UserTaskField{
			&lhproto.UserTaskField{
				Name: "my-first-int-field",
				Type: lhproto.VariableType_INT,
			},
			&lhproto.UserTaskField{
				Name: "my-second-str-field",
				Type: lhproto.VariableType_STR,
			},
		},
		Description: &description,
    },
)
```

--------------------------------

### Execute a Registered Task Node

Source: https://littlehorse.io/docs/server/developer-guide/wfspec-development/basics

Shows how to execute a pre-registered `TaskDef` using the `WorkflowThread::execute()` method. It emphasizes that the task must be registered and a Task Worker must be polling for it.

```Java
public void myWf(WorkflowThread thread) {
    NodeOutput output = thread.execute("foo");
}
```

```Go
func myThreadFunc(thread *littlehorse.WorkflowThread) {
    taskOutput := thread.Execute("foo")
}
```

```Python
def thread_function(thread: WorkflowThread) -> None:
    thread.execute("foo")
```

```C#
static void MyWf(WorkflowThread thread)
{
    NodeOutput output = thread.Execute("foo");
}
```

--------------------------------

### Access LittleHorse gRPC Client and Put External Event Definition

Source: https://littlehorse.io/docs/server/developer-guide/grpc/basics

This snippet demonstrates how to initialize the LittleHorse SDK configuration, obtain a gRPC client, construct a `PutExternalEventDefRequest` protobuf with a specified name, and execute the request to define an external event. The result, an `ExternalEventDef` object, is then printed. This example uses environment variables for configuration and relies on pre-compiled protobufs shipped with the SDKs.

```Java
package io.littlehorse.quickstart;

import java.io.IOException;
import io.littlehorse.sdk.common.LHLibUtil;
import io.littlehorse.sdk.common.config.LHConfig;
import io.littlehorse.sdk.common.proto.LittleHorseGrpc.LittleHorseBlockingStub;

// All protobuf objects can be found in this package.
import io.littlehorse.sdk.common.proto.ExternalEventDef;
import io.littlehorse.sdk.common.proto.PutExternalEventDefRequest;

public class Main {

    public static void main(String[] args) throws IOException {
        // First, create an LHConfig. Using the default constructor loads the
        // configurations from your environment variables.
        LHConfig config = new LHConfig();

        // Get a gRPC client. Java gRPC has two types: "Blocking" and regular.
        // "Blocking" stubs are easier to work with as they are synchronous.
        LittleHorseBlockingStub client = config.getBlockingStub();

        // Build the request
        PutExternalEventDefRequest req = PutExternalEventDefRequest.newBuilder()
                .setName("my-external-event")
                .build();

        // Make the request
        ExternalEventDef result = client.putExternalEventDef(req);

        // Print the result in JSON format
        System.out.println(LHLibUtil.protoToJson(result));
    }
}
```

```Go
package main

import (
	"context"
	"log"

	// Littlehorse functions are found in this package
	"github.com/littlehorse-enterprises/littlehorse/sdk-go/littlehorse"

	// All protobuf data structs and gRPC clients are found in this package
	"github.com/littlehorse-enterprises/littlehorse/sdk-go/lhproto"
)

func main() {
	// Create a config using the environment variables.
	config := littlehorse.NewConfigFromEnv()

	// Load the client
	client, err := config.GetGrpcClient()
	if err != nil {
		log.Fatal(err)
	}

	// Create the request protobuf structure
	req := &lhproto.PutExternalEventDefRequest{
		Name: "my-external-event-def",
	}

	// Make the request
	var result *lhproto.ExternalEventDef
	result, err = (*client).PutExternalEventDef(context.Background(), req)

	littlehorse.PrintProto(result)
}
```

```Python
from littlehorse.config import LHConfig

# All protobuf models are in this package
from littlehorse.model import LittleHorseStub, PutExternalEventDefRequest, ExternalEventDef

# You can use this utility to print protobuf prettily (:
from google.protobuf.json_format import MessageToJson

if __name__ == '__main__':
    # Create a config object using the environment variables.
    config: LHConfig = LHConfig()

    # Create the gRPC Client (in gRPC, a client is called a "stub")
    client: LittleHorseStub = config.stub()

    # Formulate the request, which is a protobuf object.
    request = PutExternalEventDefRequest(name="my-external-event-def")

    # Make the request!
    result: ExternalEventDef = client.PutExternalEventDef(request)

    # Print it out
    print(MessageToJson(result))
```

```C#
using LittleHorse.Sdk;
// All protobuf objects can be found in this namespace.
using LittleHorse.Sdk.Common.Proto;

public class Program
{
    static void Main(string[] args)
    {
        // First, create an LHConfig. Using the default constructor loads the
        // configurations from your environment variables.
        var config = new LHConfig();

        // Get a gRPC Client
        var lhClient = config.GetGrpcClientInstance();

        // Create the request
        var externalEventRequest = new PutExternalEventDefRequest {Name = "my-external-event"};

        // Make the request
        var result = lhClient.PutExternalEventDef(externalEventRequest);

        // Print the result in JSON format
        Console.WriteLine($"External event: {result}");
    }
}
```

--------------------------------

### Install `lhctl` CLI from GoLang source

Source: https://littlehorse.io/docs/cloud/accessing-littlehorse-cloud-orchestrator

This command compiles and installs the `lhctl` CLI directly from its GoLang source code. Users must ensure their Go binary path (`~/go/bin/`) is included in their system's PATH environment variable for the command to be accessible.

```bash
go install github.com/littlehorse-enterprises/littlehorse/lhctl@0.10.0
```

--------------------------------

### Initialize and Start LittleHorse Task Worker in Java

Source: https://littlehorse.io/docs/getting-started/your-first-task-worker

This Java code snippet demonstrates how to create and start a LittleHorse Task Worker. It initializes an LHTaskWorker with a Greeter task, registers the task definition, and then starts the worker to listen for TaskRuns.

```Java
package io.littlehorse.quickstart;

import io.littlehorse.sdk.common.config.LHConfig;
import io.littlehorse.sdk.worker.LHTaskWorker;

public class Main {
    static LHConfig config = new LHConfig();

    public static void main(String[] args) {
        LHTaskWorker worker = new LHTaskWorker(new Greeter(), "greet", config);
        worker.registerTaskDef();
        worker.start();
    }
}
```

--------------------------------

### C# LittleHorse Task Worker Setup and Registration

Source: https://littlehorse.io/docs/server/concepts/variables

This C# `Main` method demonstrates how to set up and register LittleHorse task workers. It initializes `LHConfig`, creates instances of `LHTaskWorker` for 'send-email' and 'fetch-user' tasks, registers their definitions with the LittleHorse cluster, and then starts the workers to begin processing tasks.

```C#
public abstract class Program
{
  static void Main(string[] args)
  {
      var config = new LHConfig();
      MyTasks myFuncs = new MyTasks();
      LHTaskWorker<MyTasks> emailer = new LHTaskWorker<MyTasks>(myFuncs, "send-email", config);
      LHTaskWorker<MyTasks> userService = new LHTaskWorker<MyTasks>(myFuncs, "fetch-user", config);

      emailer.RegisterTaskDef();
      userService.RegisterTaskDef();

      emailer.Start();
      userService.Start();
  }
}
```

--------------------------------

### Initialize and Start LittleHorse Task Worker in Python

Source: https://littlehorse.io/docs/getting-started/your-first-task-worker

This Python code defines an asynchronous method `normal_python_method` that acts as the task. It then initializes a LHTaskWorker with this method and starts it using `asyncio.run`, allowing the worker to process 'greet' tasks.

```Python
import asyncio
import littlehorse
from littlehorse.worker import WorkerContext, LHTaskWorker
from littlehorse.config import LHConfig

async def normal_python_method(name: str, ctx: WorkerContext) -> str:
    return f"Hello, {name}!"

config = LHConfig()

async def main() -> None:
    await littlehorse.start(LHTaskWorker(normal_python_method, "greet", config))

if __name__ == "__main__":
    asyncio.run(main())
```

--------------------------------

### Register and Run LittleHorse TaskDef and Worker

Source: https://littlehorse.io/docs/server/concepts/external-events

This set of code snippets demonstrates how to define a `TaskDef` (named 'greet') and simultaneously deploy a corresponding `TaskWorker` using the LittleHorse SDK across various programming languages. The worker is designed to execute `TaskRun`s for the 'greet' `TaskDef` once a `WfRun` is initiated. The examples show how to define the task method, configure the LittleHorse client, register the `TaskDef` with the server, and start the worker process, including graceful shutdown mechanisms where applicable.

```Java
package io.littlehorse.quickstart;

import io.littlehorse.sdk.common.config.LHConfig;
import io.littlehorse.sdk.worker.LHTaskMethod;
import io.littlehorse.sdk.worker.LHTaskWorker;

class Greeter {

    @LHTaskMethod("greet")
    public String greet(String name) {
        String result = "Hello, " + name + "!";
        System.out.println(result);
        return result;
    }
}

public class Main {

    public static void main(String[] args) {
        LHConfig config = new LHConfig();

        // Create a Task Worker
        LHTaskWorker worker = new LHTaskWorker(new Greeter(), "greet", config);
        Runtime.getRuntime().addShutdownHook(new Thread(worker::close));

        // Register the TaskDef
        worker.registerTaskDef();

        // Start the Worker
        worker.start();
    }
}
```

```Python
import littlehorse
from littlehorse import create_task_def
from littlehorse.worker import LHTaskWorker
from littlehorse.config import LHConfig

import asyncio

config = LHConfig()

#define the task method
async def greet(name: str) -> str:

    result = "Hello there " + name + "!"
    print(result)
    return result

async def main():

    #create a task worker
    greeter = LHTaskWorker(greet, "greet", config)

    #start the worker
    await littlehorse.start(greeter)

if __name__ == "__main__":
#register the task def with the littlehorse server
create_task_def(greet, "greet", config)
asyncio.run(main())
```

```Go
import (
  "fmt"
  "github.com/littlehorse-enterprises/littlehorse/sdk-go/littlehorse"
)
func Greet(name string) string {
  result := "Hello, " + name + "!"
  fmt.Println(result)
  return result
}

func main() {
  config := littlehorse.NewConfigFromEnv()
  //Create Task Worker
  worker, _ := littlehorse.NewTaskWorker(config, Greet, "greet")

  //Register TaskDef
  worker.RegisterTaskDef()

  //Start the worker
  worker.Start()

}
```

```C#
using LittleHorse.Sdk;
using LittleHorse.Sdk.Worker;

namespace Quickstart;

class Greeter
{

    [LHTaskMethod("greet")]
    public string Greet(string name)
    {
        string result = $"Hello, {name}!";
        Console.WriteLine(result);

        return result;
    }
}

public class Program
{
    static void Main(string[] args)
    {
        var config = new LHConfig();
        // Create a Task Worker
        var worker = new LHTaskWorker<Greeter>(new Greeter(), "greet", config);
        // Register the TaskDef
        worker.RegisterTaskDef();
        AppDomain.CurrentDomain.ProcessExit += (sender, e) =>
        {
            // Close processes gracefully, for worker does a call to the server, and it could be some disconnections.
            worker.Close();
        };

        // Start the Worker
        worker.Start();
    }
}
```

--------------------------------

### Install LittleHorse CLI with Homebrew

Source: https://littlehorse.io/docs/server/developer-guide/install

Use this command to install the `lhctl` command-line utility on macOS and Linux systems via Homebrew. This utility is essential for interacting with the LittleHorse Kernel.

```Shell
brew install littlehorse-enterprises/lh/lhctl
```

--------------------------------

### Register and Start LittleHorse Task Workers

Source: https://littlehorse.io/docs/server/concepts/variables

This snippet demonstrates the main application logic for LittleHorse task workers. It initializes the SDK configuration, creates worker instances for 'fetch-user' and 'send-email' tasks, registers their definitions with the LittleHorse server, and starts the workers to begin processing incoming tasks. It also includes graceful shutdown handling.

```Java
public class Main {

  public static void main(String[] args) throws Exception {
      LHConfig config = new LHConfig();

      MyTasks taskFuncs = new MyTasks();
      LHTaskWorker emailer = new LHTaskWorker(taskFuncs, "send-email", config);
      LHTaskWorker userService = new LHTaskWorker(taskFuncs, "fetch-user", config);
      emailer.registerTaskDef();
      userService.registerTaskDef();

      Runtime.getRuntime().addShutdownHook(new Thread(emailer::close));
      Runtime.getRuntime().addShutdownHook(new Thread(userService::close));

      emailer.start();
      userService.start();
  }
}
```

```Python
async def main():
  workers = [
      LHTaskWorker(fetch_user, "fetch-user", config),
      LHTaskWorker(send_email, "send-email", config)
  ]

  await littlehorse.start(*workers)

if __name__ == "__main__":
  create_task_def(fetch_user, "fetch-user", config)
  create_task_def(send_email, "send-email", config)

  asyncio.run(main())
```

```Go
func main() {
  config := littlehorse.NewConfigFromEnv();
  emailer, _ := littlehorse.NewTaskWorker(config, SendEmail, "send-email");
  userService, _ := littlehorse.NewTaskWorker(config, FetchUser, "fetch-user");

  //Register TaskDef
  emailer.RegisterTaskDef();
  userService.RegisterTaskDef();

  //Start Task Worker
  go func() {
  emailer.Start();
  }();
  userService.Start();

}
```

--------------------------------

### Register 'greet' TaskDef and Start Worker

Source: https://littlehorse.io/docs/server/concepts/workflows

This snippet demonstrates how to define and register a 'greet' TaskDef in LittleHorse. The 'greet' task accepts a string 'name' as input and returns a customized greeting string, printing it to the console. It sets up a Task Worker, registers the TaskDef with the LittleHorse server, and starts the worker to listen for tasks.

```Java
package io.littlehorse.quickstart;

import io.littlehorse.sdk.common.config.LHConfig;
import io.littlehorse.sdk.worker.LHTaskMethod;
import io.littlehorse.sdk.worker.LHTaskWorker;

class Greeter {
    @LHTaskMethod("greet")
    public String greeting(String name) {
        String result = "Hello " + name + "!";
        System.out.println(result);
        return result;
    }
}

public class Main {

    public static void main(String[] args) {
        LHConfig config = new LHConfig();

        Greeter greeter = new Greeter();

        // Create a Task Worker
        LHTaskWorker worker = new LHTaskWorker(greeter, "greet", config);
        Runtime.getRuntime().addShutdownHook(new Thread(worker::close));

        // Register the TaskDef
        worker.registerTaskDef();

        // Start the Worker
        worker.start();
    }
}
```

```Python
import littlehorse
from littlehorse import create_task_def
from littlehorse.worker import LHTaskWorker
from littlehorse.config import LHConfig

import asyncio

config = LHConfig()

#define the task method
async def greet(name: str) -> str:

  result = "Hello there " + name + "!"
  print(result)
  return result

async def main():
#create a task worker
if **name** == "**main**":
#register the task def with the littlehorse server
create_task_def(greet, "greet", config)
asyncio.run(main())
```

```Go
import (
  "fmt"
  "github.com/littlehorse-enterprises/littlehorse/sdk-go/littlehorse"
)
func Greet(name string) string {
  result := "Hello there, " + name + "!"
  fmt.Println(result);
  return result
}

func main() {
  config := littlehorse.NewConfigFromEnv()
  worker, _ := littlehorse.NewTaskWorker(config, Greet, "greet")

  //Register TaskDef
  worker.RegisterTaskDef()

  //Start Task Worker
  worker.Start()
}
```

```C#
using LittleHorse.Sdk;
using LittleHorse.Sdk.Worker;

class Greeter
{
    [LHTaskMethod("greet")]
    public string Greeting(string name)
    {
        string result = $"Hello {name}!";
        Console.WriteLine(result);
        return result;
    }
}

public abstract class Program
{
    static void Main(string[] args)
    {
        var config = new LHConfig();

        // Create a Task Worker
        var greeter = new Greeter();
        LHTaskWorker<Greeter> worker = new LHTaskWorker<Greeter>(greeter, "greet", config);

        // Register the TaskDef
        worker.RegisterTaskDef();

        // Start the Worker
        worker.Start();
    }
}
```

--------------------------------

### Example Keycloak OIDC Properties Configuration

Source: https://littlehorse.io/docs/user-tasks-bridge/backend/configuration/keycloak

An example `oidc-properties.yml` file demonstrating the configuration for integrating Keycloak with the LittleHorse User Tasks Bridge Backend. This snippet shows how to define Keycloak realm details, user claims, authorities, and authorized clients for OIDC.

```yaml
com:
  c4-soft:
    springaddons:
      oidc:
        ops:
          - iss: https://<your-keycloak-server>/realms/<your-realm>
            label-name: Default Keycloak
            username-claim: preferred_username
            user-id-claim: EMAIL
            authorities:
              - path: $.realm_access.roles
              - path: $.resource_access.*.roles
            vendor: keycloak
            tenant-id: <your-tenant-id-in-littlehorse>
            client-id-claim: azp
            clients:
              - <your-keycloak-client>
```

--------------------------------

### Initialize and Start LittleHorse Task Worker in C#

Source: https://littlehorse.io/docs/getting-started/your-first-task-worker

This C# code snippet shows how to instantiate and run a LittleHorse Task Worker. It creates an LHTaskWorker instance, registers the associated task definition, and then starts the worker to begin processing tasks.

```C#
using Quickstart;
using LittleHorse.Sdk;
using LittleHorse.Sdk.Common.Proto;
using LittleHorse.Sdk.Worker;

public class Program
{
  static LHConfig config = new LHConfig();

  static void Main(string[] args)
  {
    var greetingWorker = new LHTaskWorker<Greeter>(new Greeter(), "greet", config);

    greetingWorker.RegisterTaskDef();
    greetingWorker.Start();
  }
}
```

--------------------------------

### Run Commands for LittleHorse WfSpec Registration

Source: https://littlehorse.io/docs/getting-started/your-first-wfspec

These commands illustrate how to execute the workflow registration logic for different language projects (Java, Python, Go, C#) using their respective build and run tools, effectively registering the `quickstart` WfSpec with LittleHorse.

```Java
./gradlew run
```

```Python
python -m quickstart.register
```

```Go
go run ./src
```

```C#
dotnet run -f net9.0
```

--------------------------------

### Start Workflow Run with lhctl

Source: https://littlehorse.io/docs/server/concepts/external-events

This command starts a new workflow run for the 'greet-event' workflow specification using the `lhctl` command-line tool. It will output a `WfRunId` which is needed to post external events to this specific workflow run.

```Shell
lhctl run greet-event
```

--------------------------------

### Define a LittleHorse Workflow Specification (WfSpec) in Java

Source: https://littlehorse.io/docs/server/faq

This Java code defines a `WfSpec` named 'quickstart' using the LittleHorse SDK. It illustrates how to create an input variable, execute a task, and register the workflow with the LittleHorse Kernel. A `WfSpec` outlines the tasks, their order, exception handling, and variable passing for a workflow.

```Java
public class QuickstartWorkflow {

    public static final String WF_NAME = "quickstart";
    public static final String GREET = "greet";

    /*
     * This method defines the logic of our workflow
     */
    public void quickstartWf(WorkflowThread wf) {
        // Create an input variable, make it searchable
        WfRunVariable name = wf.addVariable("input-name", VariableType.STR).searchable();

        // Execute a task and pass in the variable.
        wf.execute(GREET, name);
    }

    /*
     * This method returns a LittleHorse `Workflow` wrapper object that can be
     * used to register the WfSpec to the LittleHorse Kernel.
     */
    public Workflow getWorkflow() {
        return Workflow.newWorkflow(WF_NAME, this::quickstartWf);
    }
}
```

--------------------------------

### Define and Register LittleHorse Workflow Specification in Python

Source: https://littlehorse.io/docs/getting-started/your-first-wfspec

This Python code defines a `WfSpec` named "quickstart" with an input variable "input-name" and specifies a "greet" task execution. The `main` function then registers this `WfSpec` with the LittleHorse platform using the SDK, loading configuration from environment variables.

```Python
def get_workflow() -> Workflow:

    def quickstart_workflow(wf: WorkflowThread) -> None:
        # Define an input variable
        the_name = wf.add_variable("input-name", VariableType.STR).searchable()

        # Execute the 'greet' task and pass in the variable as an argument.
        wf.execute("greet", the_name)

    # Provide the name of the WfSpec and a function which has the logic.
    return Workflow("quickstart", quickstart_workflow)

def main() -> None:
    print("Registering WfSpec and TaskDef")

    # Configuration loaded from environment variables
    config = LHConfig()
    wf = get_workflow()

    littlehorse.create_workflow_spec(wf, config)

if __name__ == "__main__":
    main()
```

--------------------------------

### Start a LittleHorse Workflow Run using lhctl

Source: https://littlehorse.io/docs/server/concepts/user-tasks

This `lhctl` command initiates a new run of the 'favorite-player-demo' workflow. It passes 'obiwan' as the value for the 'user-id' input variable, demonstrating how to programmatically start a workflow instance from the command line.

```Shell
lhctl run favorite-player-demo user-id obiwan
```

--------------------------------

### Example LHConfig Environment Variables Configuration

Source: https://littlehorse.io/docs/cloud/accessing-littlehorse-cloud-orchestrator

This snippet provides an example of the environment variables required to configure programmatic access for LittleHorse. These variables define the API endpoint, protocol, OAuth client ID and secret, access token URL, and tenant ID, which are essential for initializing the LHConfig object.

```Configuration
LHC_API_PORT=2023
LHC_API_PROTOCOL=TLS

LHC_API_HOST=<LHC_API_HOST>  replace me!

LHC_OAUTH_CLIENT_ID=<LHC_CLIENT_ID>  # replace me!
LHC_OAUTH_CLIENT_SECRET=<LHC_CLIENT_SECRET>  # replace me!
LHC_OAUTH_ACCESS_TOKEN_URL=<LHC_OAUTH_ACCESS_TOKEN_URL>  # replace me!

LHC_TENANT_ID=<LHC_TENANT_ID>  # replace me!
```

--------------------------------

### Define and Start LittleHorse Tasks in Python

Source: https://littlehorse.io/docs/server/concepts/exception-handling

This Python snippet demonstrates how to define various tasks (e.g., charge-credit-card, fetch-amount, ship-item) using `create_task_def` and then start the LittleHorse workers to process these tasks asynchronously. It sets up the task definitions and initiates the worker processes.

```Python
  await littlehorse.start(*workers)

if __name__ == "__main__":
create_task_def(charge_credit_card, "charge-credit-card", config)
create_task_def(fetch_amount, "fetch-amount", config)
create_task_def(ship_item, "ship-item", config)
create_task_def(cancel_order_insufficient_funds, "cancel-order-insufficient-funds", config)
create_task_def(notify_order_failed, "notify-order-failed", config)

  asyncio.run(main())
```

--------------------------------

### Registering a 'hello-world' WfSpec with LittleHorse Kernel

Source: https://littlehorse.io/docs/server/concepts/workflows

This snippet demonstrates how to define and register a simple 'hello-world' `WfSpec` that takes a 'name' string and executes a 'greet' task. It shows the implementation across Java, Python, Go, and C# using the LittleHorse SDK to interact with the Kernel.

```Java
package io.littlehorse.quickstart;

import io.littlehorse.sdk.common.config.LHConfig;
import io.littlehorse.sdk.wfsdk.WfRunVariable;
import io.littlehorse.sdk.wfsdk.Workflow;

public class Main {
  public static final String WF_NAME = "quickstart";

  public static void main(String[] args) {
      LHConfig config = new LHConfig();

      Workflow workflowGenerator = Workflow.newWorkflow(WF_NAME, wf -> {
          WfRunVariable name = wf.declareStr("name").searchable().required();
          wf.execute("greet", name);
      });

      workflowGenerator.registerWfSpec(config.getBlockingStub());
  }
}
```

```Python
import asyncio
from littlehorse.workflow import Workflow, WorkflowThread
from littlehorse import create_workflow_spec
from littlehorse.config import LHConfig

config = LHConfig()

def get_workflow() -> Workflow:

  def quickstart_workflow(wf: WorkflowThread) -> None:

      name = wf.declare_str("name").searchable()

      wf.execute("greet", name)

  return Workflow("quickstart", quickstart_workflow)

async def main():
print("Registering WfSpec")

  create_workflow_spec(get_workflow(), config)

if __name__ == "__main__":
asyncio.run(main())
```

```Go
import (
  "context"
  "github.com/littlehorse-enterprises/littlehorse/sdk-go/littlehorse"
)
func QuickStart(wf *littlehorse.WorkflowThread){
  name := wf.DeclareStr("name").Searchable()
  wf.Execute("greet", name )
}
func main() {
  // Get a client
  config := littlehorse.NewConfigFromEnv()
  client, _ := config.GetGrpcClient()

  workflowGenerator := littlehorse.NewWorkflow(QuickStart, "quickstart")

  request, err := workflowGenerator.Compile()
  if err != nil {
    log.Fatal(err)
  }

  (*client).PutWfSpec(context.Background(), request)
}
```

```C#
using LittleHorse.Sdk;
using LittleHorse.Sdk.Workflow.Spec;

namespace Quickstart;

public abstract class Program
{
  public static string WfName = "quickstart";
  static void Main(string[] args)
  {
      var config = new LHConfig();

      Workflow workflowGenerator = new Workflow(WfName, (WorkflowThread wf) =>
      {
          WfRunVariable name = wf.DeclareStr("name").Searchable().Required();
          wf.Execute("greet", name);
      });

      workflowGenerator.RegisterWfSpec(config.GetGrpcClientInstance());
  }
}
```

--------------------------------

### Get and Delete WfSpec by ID

Source: https://littlehorse.io/docs/server/developer-guide/grpc/managing-metadata

Shows how to retrieve a `WfSpec` using its ID (name, major version, revision) and how to delete an existing `WfSpec` from the LittleHorse system. Also includes an example of getting the latest `WfSpec` in Go.

```Java
package io.littlehorse.quickstart;

import java.io.IOException;
import io.littlehorse.sdk.common.LHLibUtil;
import io.littlehorse.sdk.common.config.LHConfig;
import io.littlehorse.sdk.common.proto.LittleHorseGrpc.LittleHorseBlockingStub;
import io.littlehorse.sdk.common.proto.DeleteWfSpecRequest;
import io.littlehorse.sdk.common.proto.WfSpec;
import io.littlehorse.sdk.common.proto.WfSpecId;

public class Main {

    public static void main(String[] args) throws IOException {
        LHConfig config = new LHConfig();
        LittleHorseBlockingStub client = config.getBlockingStub();

        WfSpecId wfSpecId = WfSpecId.newBuilder()
                .setName("my-wfspec")
                .setMajorVersion(0) // Set to whichever major version you want
                .setRevision(0) // Set to whichever revision you want
                .build();

        WfSpec wfSpec = client.getWfSpec(wfSpecId);
        System.out.println(LHLibUtil.protoToJson(wfSpec));

        // Delete the WfSpec
        DeleteWfSpecRequest req = DeleteWfSpecRequest.newBuilder().setId(wfSpecId).build();
        client.deleteWfSpec(req);
    }
}
```

```Go
wfSpecId := &lhproto.WfSpecId{
    Name:         "my-wf",
    MajorVersion: 2,
    Revision:     1,
}

wfSpec, err := (*client).GetWfSpec(context.Background(), wfSpecId)

// Get the latest wfSpec. Setting majorVersion is optional for this request
majorVersion := int32(2)

someWf, err := (*client).GetLatestWfSpec(
    context.Background(),
    &lhproto.GetLatestWfSpecRequest{
        Name:         "some-wf",
        MajorVersion: &majorVersion,
    },
)

// delete the WfSpec
_, err = (*client).DeleteWfSpec(context.Background(), &lhproto.DeleteWfSpecRequest{
    Id: wfSpecId,
})
```
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