LinkRefine is a web application that helps users refine and optimize their LinkedIn profiles. By simply providing a LinkedIn profile URL, the tool fetches and analyzes profile data (such as the user’s headline, about section, work experience, skills, and more), and then offers AI-driven suggestions on how to improve each section. This makes it easier for professionals to present their expertise more effectively, attract recruiters, and stand out in their network.
- Clone the Repository
git clone https://github.com/Rishi-Jain2602/LinkRefine.git- Create Virtual Environment
cd backend
virtualenv venv
venv\Scripts\activate # On Windows
source venv/bin/activate # On macOS/Linux- Install the Project dependencies
- 3.1 Navigate to the Backend Directory and install Python dependencies:
cd backend
pip install -r requirements.txt- 3.2 Navigate to the Frontend Directory and install Node.js dependencies:
cd frontend
npm install- Run the React App
Start the React app with the following command:
cd frontend
npm start- The server will be running at
http://localhost:3000.
- Run the Backend (FastAPI App)
Open a new terminal and run the backend:
cd backend
uvicorn main:app --host 0.0.0.0 --port 8000 --reload- The server will be running at
http://127.0.0.1:8000.
-
Uploading Your Profile URL:
- Navigate to the Upload page where you will see an input field prompting you to enter your LinkedIn profile URL.
- Enter your URL and click the "Upload" button.
- The frontend sends a POST request to the
/linkrefine/uploadendpoint, which triggers the backend to process the URL.
-
Processing and Redirect:
- The backend processes the profile URL, generates a unique
link_id, and returns it upon successful processing. - The frontend stores this
link_idin localStorage and then automatically redirects you to the Review page.
- The backend processes the profile URL, generates a unique
-
Reviewing AI Suggestions:
- On the Review page, a GET request is made using the stored
link_idto fetch your processed profile data. - The page displays your original profile information along with AI-generated suggestions for improving sections like your headline, about section, work experience, and more.
- Each section includes detailed suggestions and improvements to help enhance your LinkedIn profile.
- On the Review page, a GET request is made using the stored
- React: For building a dynamic and responsive user interface.
- React Router: To manage navigation between different pages (Upload and Review).
- Axios: For handling API requests between the frontend and backend.
- CSS: For custom styling and ensuring a consistent look and feel across the application.
- FastAPI: A modern, high-performance Python framework used for building RESTful APIs.
- uvicorn: An ASGI server that runs the FastAPI application.
- Python: The main programming language used for backend development.
- LangChain: A framework for integrating large language models (LLMs) into applications. It orchestrates the interaction between your backend and the LLMs.
- Mistral LLM: Leveraged via LangChain to suggest projects, skills, work experience, and other profile enhancements.
- LLAMA 3B (from GRQ): Utilized for image-related tasks, such as analyzing profile images or generating image descriptions, to further enhance profile optimization.
- Make sure you have Python 3.x and npm 10.x installed
- It is recommended to use a virtual environment for backend to avoid conflict with other projects.
- If you encounter any issue during installation or usage please contact rishijainai262003@gmail.com or rj1016743@gmail.com