No.ed AI Agentic Layer Backend

Overview

The No.ed AI Agentic Layer is the core intelligence behind the No.ed platform, helping users find career paths, generate personalized roadmaps, and receive tailored job recommendations. This backend processes user resumes, extracts relevant skills, and dynamically curates career guidance content.

Features

• Career Pathway Identification: Suggests potential career paths based on user input and resume analysis.
• Roadmap Generation: Provides structured learning paths with relevant courses, resources, and milestones.
• Job Recommendations: Matches users with suitable job opportunities based on their skills and career goals.
• AI-Driven Content Curation: Extracts and recommends high-quality learning materials from various sources.

Tech Stack

• Backend Framework: FastAPI (Python)
• Database: CockroachDB
• Authentication: Firebase Google Authentication
• AI Components:
  • Large Language Models (LLMs) for content extraction and recommendation
  • Embedding-based similarity search for matching job listings
  • Resume parsing using NLP models
• Data Storage: Vector database for efficient similarity searches

API Endpoints

1. Root Endpoint

• Endpoint: GET /
• Description: Root endpoint for health check.
• Response:

  "string"

2. Generate Roadmap

• Endpoint: POST /roadmap
• Description: Generates a step-by-step roadmap based on user resume and desired role.
• Request Body:

  {
    "resume": "string",
    "role": "string"
  }

• Response:

  "string"

• Error Response (422 Validation Error):

  {
    "detail": [
      {
        "loc": ["string", 0],
        "msg": "string",
        "type": "string"
      }
    ]
  }

3. Generate Roles

• Endpoint: POST /recommend_roles
• Description: Generates potential roles based on provided tags (skills, interests, etc.).
• Request Body:

  {
    "tags": "string"
  }

• Response:

  "string"

• Error Response (422 Validation Error):

  {
    "detail": [
      {
        "loc": ["string", 0],
        "msg": "string",
        "type": "string"
      }
    ]
  }

4. Generate Job Recommendations

• Endpoint: POST /recommend_jobs
• Description: Provides personalized job listings based on user roles and experience level.
• Request Body:

  {
    "roles": "string",
    "experience_level": "string"
  }

• Response:

  "string"

• Error Response (422 Validation Error):

  {
    "detail": [
      {
        "loc": ["string", 0],
        "msg": "string",
        "type": "string"
      }
    ]
  }

Installation & Setup

1. Clone the repository:

   git clone https://github.com/your-repo/noed-agent-backend.git
   cd noed-agent-backend

2. Install dependencies:

   pip install -r requirements.txt

3. Set up environment variables:

   cp .env.example .env

   • Add Firebase credentials
   • Configure database connection
   • Add API keys for AI services
   • Example .env file:

     HUGGINGFACE_TOKEN=HUGGINGFACE_TOKEN
     GOOGLE_GEN_AI=GOOGLE_GEN_AI
     CLIENT_ID=COURSERA_CLIENT_ID
     CLIENT_SECRET=COURSERA_CLIENT_SECRET
     OPENROUTER_API_KEY=OPENROUTER_API_KEY

4. Start the server:

   uvicorn main:app --host 0.0.0.0 --port 8000

Future Enhancements

• Integration with real-time job market trends
• Advanced AI-driven skill gap analysis
• More personalized roadmap variations

Contributing

Feel free to submit pull requests or open issues for improvements!