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DEVOPS × AI SERIES

Automate RAG API Testing with GitHub Actions

Build CI/CD pipelines that automatically test your AI applications on every code push

Start Building
Automate RAG API Testing with GitHub Actions project preview
GitHub Actions
FastAPI

Difficulty

Intermediate

Time to complete

90 minutes

Availability

Free

BUILD

What you'll build

Build a GitHub Actions CI/CD pipeline for your RAG API. Learn automated testing, semantic validation, and quality gates used by enterprise engineering teams.

1. Set Up Your RAG API

Verify your API files, install dependencies, and test your RAG system locally.

2. Push Code to GitHub

Initialize Git, create a repository, configure SSH authentication, and push your code.

3. Create Semantic Tests

Write tests that validate answer quality, discover LLM non-determinism, and understand testing challenges.

4. Implement Mock LLM Mode

Add deterministic testing mode that returns retrieved context without LLM generation.

5. Build GitHub Actions Workflow

Create CI/CD pipeline that automatically tests your RAG API on every code push.

Your portfolio builds as you work.

Every project documents itself as you go. Finish the work, and your proof is ready to share.

PROJECT

Real world application

Skills you'll learn

  • Git Version Control

    Manage code changes, commits, and branches using Git fundamentals

  • GitHub Actions

    Create automated workflows that run tests on every code push

  • Semantic Testing

    Validate RAG answer quality by checking for key concepts and accuracy

  • Mock Mode Testing

    Build deterministic tests that verify retrieval without LLM variability

  • Quality Gates

    Prevent degraded content from reaching production with automated checks

  • CI/CD Automation

    Automate build, test, and deployment workflows for consistent releases

Tech stack

  • GitHub Actions logo

    GitHub Actions

    GitHub native CI/CD platform for automating workflows directly in your repository.

  • FastAPI logo

    FastAPI

    Modern Python web framework for building high-performance APIs efficiently.

NextWork's project-based approach helped me understand CI/CD in a way tutorials never could. Now I automate testing pipelines at work every day.

Sarah Martinez

DevOps Engineer

OUTCOME

Where this leads.

Relevant Jobs

Roles where these skills matter:

  • DevOps Engineer
  • Site Reliability Engineer
  • Platform Engineer
  • MLOps Engineer

DevOps × AI Series

You completed the series. Continue building your DevOps skills with Kubernetes deployments, monitoring, and advanced orchestration patterns.

DevOps × AI Series

Continue the Journey

FAQs

Everything you need to know

This is Part 4 of the 4-part DevOps × AI Series. The complete series includes: Project #1: Build a RAG API with FastAPI - Build the foundational RAG API, Project #2: Containerize with Docker - Package your API for deployment, Project #3: Deploy to Kubernetes - Orchestrate containers at scale, and this project (Part 4) - Automate testing with CI/CD.

We recommend completing at least Project #1 (Build a RAG API with FastAPI) first, as this project builds on that API. Projects #2 and #3 are optional for this tutorial. If you want to start here, the tutorial includes a 25-30 minute quick setup to create all the necessary API files (app.py, embed.py, k8s.txt) from scratch.

GitHub Actions is GitHub's built-in CI/CD platform used by millions of developers. It automates testing, building, and deployment workflows triggered by code changes. Learning GitHub Actions opens doors to DevOps Engineer, Site Reliability Engineer, and Platform Engineer roles. This NextWork project teaches you the same automation patterns used by Netflix, Spotify, and enterprise engineering teams.

Semantic tests verify that your RAG system returns answers with correct meaning, not just correct format. When you ask 'What is Kubernetes?', semantic tests check if the answer includes key concepts like 'orchestration' and 'containers'. This is critical for RAG systems because LLM outputs are non-deterministic. The same question can produce different answers each time. This NextWork project teaches mock LLM mode to solve this challenge with deterministic, reliable tests.

GitHub Actions is completely free for public repositories, which is what you create in this project. You get 2,000 free minutes per month for private repositories on the free tier. This entire NextWork project uses only free tiers with zero cloud costs. All tools (GitHub, Python, FastAPI, ChromaDB) remain free after completing the project.

Mock LLM mode is a testing technique that returns retrieved documents directly instead of generating AI responses. This solves the non-determinism problem where LLMs produce different outputs for the same input. In this NextWork project, you implement mock mode using an environment variable (USE_MOCK_LLM=1) that makes your API return deterministic results perfect for automated CI testing.

One Project. Real Skills.

90 minutes from now, you'll have completed Automate RAG API Testing with GitHub Actions. No prior experience needed. Just step-by-step guidance and a real project for your portfolio.

Let's Build This

Intermediate level