Oasis: The AI-Engine Screening Sandbox 🏝️

Oasis is an open-source, enterprise-grade candidate assessment platform tailored for AI engineering roles. Instead of testing candidates on generic LeetCode problems, Oasis drops them into a real, sandboxed "broken production" environment. They must use advanced tooling (LangGraph, MCP, RAG) to debug systems and pass an automated LLM Judge.

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🌟 Key Features

• Real-World Scenarios: Candidates are dropped into a dynamically provisioned, completely isolated VS Code (code-server) workspace with broken AI implementations (e.g., recursive tool-calling loops in LangGraph).
• LLM-as-a-Judge: Candidates receive async feedback from an automated judge. Grader scripts run inside secure, disposable Docker containers to prevent code execution vulnerabilities.
• Recruiter Intelligence: A command center for recruiters to visualize pass/fail ratios, average test times, and inspect the raw code / trace logs submitted by the candidate.
• Invite-Only Sessions: Securely generate single-use JWT registration links for candidates to take assessments.
• Crash Resilience: All metadata is persisted on host volumes. If a candidate accidentally closes their tab during a test, the system preserves their IDE container and provides a "Resume Session" button.

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🏗️ Enterprise Architecture

Oasis consists of the following components running securely via Docker Compose:

1. Orchestrator (platform/api): A FastAPI backend that handles RBAC, JWT authentication, and session provisioning. Uses SQLite mounted on a persistent Docker volume.
2. Frontend UI (platform/ui): A glassmorphism-themed, modern web interface.
3. Dynamic Sandboxing (Docker API): The orchestrator uses the Docker SDK to dynamically spin up an isolated, ephemeral codercom/code-server workspace and injects it directly into the frontend via iframe.
4. Asynchronous Graders (evaluator/grader.py): A Python script utilizing langchain and httpx to analyze the candidate's logic. Evaluation runs in an airgapped, disposable container using FastAPI BackgroundTasks to prevent RCE.

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🎯 Assessment Domains

The platform comes pre-loaded with 5 major AI engineering challenges:

1. Domain A (Agentic MCP): Debug a LangGraph financial agent stuck in a recursive tool-calling loop.
2. Domain B (RAG Systems): Fix a ChromaDB retrieval system suffering from hallucination due to poor chunking and high top-K thresholds.
3. Domain C (LLM Security): Defend a customer support bot against malicious jailbreaks and prompt injections.
4. Domain D (MLOps & Inference): Refactor a blocking PyTorch endpoint into an optimized, async global inference cache.
5. Domain E (AI SWE): Debug core Python algorithms using an AI coding assistant.

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🚀 Quick Start Guide

Prerequisites

• Docker and Docker Compose
• (Optional but recommended) At least 8GB of RAM for running the Ollama container locally.

1. Clone & Setup

git clone https://github.com/your-username/oasis-ai-screening.git
cd oasis-ai-screening

# Generate a secure secret key for JWT authentication
export SECRET_KEY=$(openssl rand -hex 32)

2. Start the Platform

docker-compose up -d --build

This will spin up the orchestrator and ollama services.

3. Log In

Navigate to http://localhost:8000.

• Default Admin Credentials:
  • Username: admin
  • Password: admin (Note: Be sure to change the admin password in database.py before exposing to the internet!)

4. Create an Invite

• Log in as the Admin and go to Recruiter Admin.
• Click + Generate Invite Link.
• Open the copied URL in an incognito window to simulate a candidate registration and experience the sandbox!

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🛠️ Adding Custom Challenges

Challenges are defined via a metadata-driven approach. To create a new challenge, create a folder under challenges/ with a manifest.yaml:

name: "System Design: RAG Hallucination"
domain: "Retrieval Augmented Generation"
description: "The company's internal wiki bot is hallucinating facts. Fix the embedding chunk overlap and the retrieval threshold."
difficulty: "Hard"
stack:
  - "LangChain"
  - "ChromaDB"

Next, add an evaluator/grader.py script to test their logic. The orchestrator handles the rest automatically!

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🛡️ License

Oasis is released under the Apache 2.0 License with the Commons Clause condition. This means the platform is free to use, modify, and host for your own internal hiring needs. However, you are strictly prohibited from Selling the software or offering it as a paid hosted service (SaaS) to third parties. See the LICENSE file for complete details.

Can the creator commercialize this in the future? Yes. The original copyright holder retains the right to offer Oasis under alternative commercial licenses in the future, but the open-source version will remain protected under this Commons Clause.