llama_deploy/examples/redis_message_queue

Using Redis as Message Queue provider

Note

This example is mostly based on the Quick Start, see there for more details.

We'll be deploying a simple workflow on a container running LlamaDeploy using Redis as the message queue provider. The Redis container will be started in a different container using Docker Compose.

This is the code defining our deployment, with comments to the relevant bits:

name: RedisMessageQueue

control-plane:
  port: 8000

message-queue:
  type: redis
  # what follows depends on what's in the docker compose file
  host: redis
  port: 6379

default-service: counter_workflow_service

services:
  counter_workflow_service:
    name: Counter Workflow
    source:
      type: local
      name: .
    path: workflow:counter_workflow

Note how we the deployment file contains the message-queue key to instruct LlamaDeploy to use Redis as the message queue provider.

Before starting the containers, two things to note about how LlamaDeploy is configured:

• We mount our application, consisting of the deployment.yml file and a Python module workflow.py containing the LlamaIndex code implementing the workflow, under the path /opt/app inside the container
• We set the LLAMA_DEPLOY_APISERVER_RC_PATH environment variable so that when LlamaDeploy starts, it will look under the /opt/app folder for deployments to create automatically.

We can now start the Docker containers using Compose:

$ docker compose up -d

When the containers are up and running, we can use llamactl from our local host to interact with the deployment:

$ llamactl status
LlamaDeploy is up and running.

Active deployments:
- RedisMessageQueue

Our workflow is now part of the RedisMessageQueue deployment and ready to serve requests! Since we want to persist a counter across workflow runs, first we manually create a session:

$ llamactl sessions create -d RedisMessageQueue
session_id='<YOUR_SESSION_ID>' task_ids=[] state={}

Then we run the workflow multiple times, always using the same session we created in the previous step:

$ lamactl run --deployment RedisMessageQueue --arg amount 3 -i <YOUR_SESSION_ID>
Current balance: 3.0
$ lamactl run --deployment RedisMessageQueue --arg amount 3 -i <YOUR_SESSION_ID>
Current balance: 3.5

Note: If you have multiple replicas of the workflow and control plane and only want one replica to process messages, set REDIS_EXCLUSIVE_MODE to true.