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ContributeWorkerArchitecture

Worker Architecture and Dependencies

The worker shares code, models, and the database with the backend API, connected through a Redis broker.

Component Relationships

code.txt
┌───────────┐     ┌───────────┐     ┌───────────┐
│           │     │           │     │           │
│  Backend  │────▶│   Broker  │────▶│   Worker  │
│    API    │     │           │     │           │
│           │     │           │     │           │
└───────────┘     └───────────┘     └───────────┘
    │                                   │
    │                                   │
    │                                   │
    ▼                                   ▼
┌───────────┐                       ┌───────────┐
│           │                       │           │
│  Database │◀─────────────────────▶│    SDK    │
│           │                       │           │
└───────────┘                       └───────────┘

Backend-Worker Interdependencies

How Tasks Flow Through the System

  1. Backend API: Endpoints receive client requests and enqueue asynchronous tasks
  2. Broker: Redis-based queue stores pending tasks (with TLS support)
  3. Worker: Processes tasks from the queue and executes business logic
  4. Database: Shared between backend and worker for storing and retrieving application data
  5. SDK: Provides shared utilities and models used by both components

Code Dependencies

The worker depends on the backend code in several ways:

  1. Shared Models: The worker needs access to the same data models defined in the backend
  2. Database Access: Worker tasks use the same database connection/ORM layer as the backend
  3. Business Logic: Tasks often execute backend business logic in an asynchronous context
  4. Context Management: The worker needs to maintain the same multi-tenant context system

Example import hierarchy:

worker_task_example.py
# In a worker task
from rhesis.backend.app import models, crud    # Backend models and database operations
from rhesis.backend.app.database import get_db_with_tenant_variables
from rhesis.backend.tasks.base import BaseTask # Worker-specific task base class
from rhesis.sdk import client                  # Shared SDK components

SDK Dependencies

Both the worker and backend depend on the Rhesis SDK for:

  1. Client Libraries: API clients for external services (e.g., LLM providers)
  2. Shared Utilities: Common functions used by both backend and worker
  3. Type Definitions: Shared type definitions and interfaces
  4. Configuration Management: Loading and accessing configuration

Deployment Considerations

Package Structure

When deploying the worker, it must include:

  1. The entire rhesis.backend package
  2. The rhesis.sdk package
  3. Worker-specific code (rhesis.backend.tasks and rhesis.backend.worker)

Environment Configuration

The worker requires the same environment variables as the backend, plus additional worker-specific settings:

.env
# Backend variables also needed by worker
BACKEND_ENV=production
DB_HOST=postgres.example.com
DB_NAME=rhesis
APP_DB_USER=rhesis_app
APP_DB_PASS=...
LOG_LEVEL=INFO

# Worker-specific variables
BROKER_URL=rediss://:password@redis-host:6378/0?ssl_cert_reqs=CERT_NONE
CELERY_RESULT_BACKEND=rediss://:password@redis-host:6378/1?ssl_cert_reqs=CERT_NONE
CELERY_WORKER_CONCURRENCY=8
CELERY_WORKER_PREFETCH_MULTIPLIER=4

Managing Circular Dependencies

One challenge in the worker-backend relationship is avoiding circular dependencies. The system follows these patterns:

  1. Worker tasks can import backend modules
  2. Backend modules should not directly import worker tasks (use dynamic imports if needed)
  3. Shared dependencies go in the SDK package
  4. Base task classes, task organization, and worker configuration belong in rhesis.backend.tasks

Task Context and State

Because the worker executes backend code asynchronously:

  1. The tenant context (organization/user IDs) must be explicitly passed to tasks
  2. Database sessions must be properly managed (opened and closed)
  3. Any state or context that would normally be available in an API request must be reconstructed

This is handled through:

task_context_example.py
# In the backend API
from rhesis.backend.tasks import task_launcher

@router.post("/execute")
def execute_endpoint(current_user: User = Depends(get_current_user)):
    # Launch task with context
    result = task_launcher(
        my_task,
        arg1,
        arg2,
        current_user=current_user  # This automatically adds org_id and user_id
    )
    return {"task_id": result.id}

# In the worker
@app.task(base=BaseTask)
@with_tenant_context
def my_task(self, arg1, arg2, db=None):
    # Access context
    org_id = getattr(self.request, 'organization_id', None)
    user_id = getattr(self.request, 'user_id', None)

    # Use backend functionality with proper context
    result = backend_function(db, arg1, arg2)
    return result
OverviewMulti-Worker RPC