Questionnaire Back-End

A production-ready backend service for managing questionnaires, equipped with robust authentication, authorization, and semantic validation features.
This project is designed with clean architecture principles, dependency injection (Wire), and containerized deployment (Docker + Docker Compose).

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🚀 Features

Authentication:

• Secure JWT-based authentication system.
• Access and refresh tokens for session management.
• Authorization:
  • Role-Based Access Control (RBAC) powered by Casbin.
  • Flexible policies with sub, obj, and act definitions:
    • sub → Subject (role or user ID).
    • obj → Object (typically API endpoints).
    • act → Action (GET, POST, PUT, DELETE, or *).
    • eft → Effect (allow or deny).
  • Example matcher rule:

    m = r.sub == "super_admin" || (g(r.sub, p.sub) && keyMatch2(r.obj, p.obj) && (r.act == p.act || p.act == "*"))
    

Polymorphic Comments:

• Comment system implemented in a polymorphic way.
• Supports attaching comments to multiple entities (e.g., questions, answers, users).
• Question Scoring:
• Built-in rating system for questions.
• Enables grading and evaluating user responses with custom scoring rules.
• User Agent Tracking:
• Logs API consumer’s user agent (browser, device, or client application).
• Useful for auditing, analytics, and monitoring user activity.

Semantic Answer Validation:

• Integrates with Semantic Answer Validator.
• Used to validate short answers against expected responses with semantic similarity.
  Example request:

  POST http://127.0.0.1:8020/check_answer
  Content-Type: application/json

  {
    "student_answer": "Artificial intelligence improves efficiency in many industries.",
    "accepted_answers": [
      "AI enhances productivity across different sectors.",
      "Smart systems reduce human errors."
    ]
  }

Example response:

{
  "similarity_score": 0.9,
  "accepted": true,
  "details": {
    "sbert_similarity": 0.7707,
    "nli_entail_count": 1,
    "nli_contra_count": 0,
    "nli_entail_avg_prob": 0.4999,
    "nli_contra_avg_prob": 0.0003,
    "keywords_present": true,
    "student_negation": false
  }
}

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📂 Project Structure

questionnaire-back-end/
│── casbin/                # Casbin model configuration
│   └── model.conf
│
│── config/                # Configuration layer (YAML-based)
│   └── environment/       # Environment configs
│       ├── casbin.go
│       ├── config.go
│       └── mongo.go
│
│── internal/              # Core business logic
│   ├── controller/        # HTTP controllers
│   ├── dto/               # Data transfer objects
│   ├── middleware/        # Custom middlewares
│   ├── models/            # Database models
│   ├── repository/        # Database repositories
│   ├── service/           # Service layer
│   └── validation/        # Request validation
│
│── routers/               # API routes
│── utils/                 # Utilities and helpers
│── wire/                  # Dependency injection (Google Wire)
│   ├── provider/
│   ├── wire.go
│   └── wire_gen.go
│
│── .gitignore
│── docker-compose.yml
│── Dockerfile
│── go.mod
│── main.go
│── README.md

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🛠️ Tech Stack

• Language: Go (Golang)
• Dependency Injection: Google Wire
• Authorization: Casbin (RBAC model)
• Authentication: JWT tokens
• Database: MongoDB (via configuration layer)
• Validation: Custom request validators + Semantic Answer Validator
• Containerization: Docker & Docker Compose

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⚡ Getting Started

1. Clone the Repository

git clone https://github.com/yourusername/questionnaire-back-end.git
cd questionnaire-back-end

2. Environment Configuration

• Place your environment-specific YAML configs under config/environment/.

3. Run with Docker

docker-compose up --build

4. Run Locally (without Docker)

go mod tidy
go run main.go

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📖 API Authorization (Casbin)

• Objects (obj): API endpoints
• Actions (act): HTTP methods (GET, POST, PUT, DELETE)
• Subjects (sub): Users or roles (admin, teacher, student, etc.)
• Effects (eft): Permission outcome (allow or deny)

Policies can be configured directly via Casbin adapters.

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🧪 Example: Semantic Answer Validator Integration

POST http://127.0.0.1:8020/check_answer
Content-Type: application/json

{
  "student_answer": "Sports are dangerous and harm your health.",
  "accepted_answers": [
    "Physical activity improves fitness and mental health.",
    "Exercise is important for maintaining overall wellbeing."
  ],
  "keywords": ["Exercise","activity"]
}

Response:

{
  "similarity_score": 0.0,
  "accepted": false,
  "details": {
    "sbert_similarity": 0.5345,
    "nli_entail_count": 0,
    "nli_contra_count": 2,
    "nli_entail_avg_prob": 0.0028,
    "nli_contra_avg_prob": 0.8741,
    "keywords_present": false,
    "student_negation": false
  }
}

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📦 Ready for Use

• ✅ Fully containerized (Docker & Docker Compose)
• ✅ Clean architecture (controllers, services, repositories, DTOs)
• ✅ Role-based authorization (Casbin RBAC)
• ✅ JWT authentication
• ✅ Semantic short-answer validation
• ✅ Polymorphic comments system
• ✅ Question scoring engine
• ✅ User agent logging

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