OpenFaaS Integration Guide

Build event-driven, serverless knowledge pipelines using Aevum Encyclopedia's API. This guide covers deployment, Slack bot integration, and real-time sync patterns for the #openfaas community channel.

Slack #openfaas Integration

The #openfaas channel acts as a live deployment dashboard and interactive query interface. Aevum's Slack bot listens for commands, triggers OpenFaaS functions, and streams execution logs directly to your workspace.

Quick Start: Python Function

Generate a new OpenFaaS function using the Aevum template. This creates a handler.py pre-configured with API credentials and rate-limiting middleware.

faas-cli new aevum-knowledge-worker --lang python3-debian --prefix aevum
faas-cli template pull https://github.com/aevum/faas-python-template
faas-cli up -f aevum-knowledge-worker.yml

handler.py Structure

import httpx
import os
import json
 
def handle(req: httpx.Request):
    # Extract query from Slack event or direct invocation
    payload = json.loads(req.content)
    query = payload.get("text", "")
 
    # Forward to Aevum Encyclopedia API
    client = httpx.Client(timeout=5.0)
    resp = client.post("https://api.aevum.dev/v2/resolve",
        json={"query": query, "mode": "graph"},
        headers={"Authorization": f"Bearer {os.getenv('AEVUM_API_KEY')}"})
 
    return (resp.status_code, resp.json())

API Endpoints

All endpoints support JSON input/output and are optimized for sub-100ms cold starts. Rate limits: 120 req/min per function instance.

Deployment & Scaling