A lightweight web application that helps clients evaluate consultants based on a job description, built with Next.js and Tailwind CSS.
Live Demo: https://consultant-evaluator.vercel.app/
This application allows users to:
- Input a job description
- View 10 consultant profiles relevant to that description
- See AI-generated evaluations for each consultant
- Filter consultants by various criteria
Each consultant evaluation includes:
- A basic fit score/ranking
- A short summary
- Key pros and cons
- Suggested questions to ask during interviews
- Job Description Input: Easy-to-use form for entering job requirements
- Consultant Matching: Displays consultants relevant to the job description
- AI-Powered Evaluations: Uses LLM inference API to generate insights
- Responsive UI: Clean interface built with Tailwind CSS and shadcn/ui
- Filtering System: Filter consultants by location, experience, or keywords
- Frontend: Next.js, React, TailwindCSS, shadcn/ui
- Backend: Next.js API routes
- AI Inference: Integration with LLM API
First, install the dependencies:
npm install
# or
yarn install
# or
pnpm install
# or
bun installThen, run the development server:
npm run dev
# or
yarn dev
# or
pnpm dev
# or
bun devOpen http://localhost:3000 with your browser to see the application.
/components- UI components including consultant-related components/pages- Application pages and API routes/lib- Utility functions and data
The implementation follows a modular approach:
- Created a clean, intuitive UI using shadcn/ui components
- Developed a form to collect job description inputs
- Implemented mock consultant profiles with relevant information
- Integrated with an LLM inference API to generate evaluations
- Added filtering functionality for better user experience
- Ensured responsive design for all screen sizes
The application minimizes unnecessary API calls while maintaining a smooth user experience.
- User authentication
- Saved job descriptions
- More advanced filtering options
- Expanded consultant database