CV SCAN: AI-Powered Hiring Assistant
Introduction
CV SCAN is an intelligent hiring assistant designed to streamline the candidate shortlisting process by matching multiple resumes against specific job criteria. Hosted on Hugging Face Spaces, the app leverages Retrieval-Augmented Generation (RAG) to efficiently handle large volumes of resume data and generate contextually accurate matches for a given job description.
Features and Functionalities
- Multiple Resume Uploads: Enables bulk resume uploads in PDF format, facilitating batch processing for large candidate pools.
- Real-Time Feedback: Offers immediate responses and fit analysis based on resumes and specified job criteria, streamlining candidate shortlisting.
- Custom Dataset Flexibility: Capable of incorporating industry-specific datasets for highly tailored hiring assistance.
Fig. 1 : General Block Diagram
Retrieval-Augmented Generation (RAG)
RAG combines retrieval and generation capabilities, enhancing the LLM’s context management by retrieving only relevant documents before prompting the model for a response. In CV SCAN, RAG uses LangChain’s embeddings and Google Generative AI to retrieve the most pertinent resumes based on the job description or query, ensuring an accurate and relevant context for each query.
- Uses LangChain’s embedding and retrieval system with Google’s Generative AI embeddings.
- Embeds resumes into a vector database (Chroma) for semantic matching to job descriptions.
- Enables highly relevant document retrieval, helping the AI assistant to narrow down resumes matching the job query.
Embedding and Retrieval Process
Embeddings represent text data as high-dimensional vectors, capturing semantic relationships between words, phrases, or entire documents. These vectorized forms allow for efficient similarity searches across documents.
- Converts resume text and job descriptions into embeddings using Google Generative AI.
- Stores these embeddings in Chroma, a vector database, which allows the assistant to identify and retrieve resumes that closely match the job criteria.
- Uses LangChain to handle the embedding and retrieval process, ensuring optimal matching.
Prompting and Chat Interface
Prompting involves crafting queries to interact with LLMs, ensuring responses are both accurate and aligned with the user’s needs. In CV SCAN, prompting is adapted to guide the hiring assistant toward relevant and specific outputs.
- Dynamic Chat Interface: Allows hiring managers to input specific job descriptions or requirements, and query about particular candidate qualifications.
- Automated First Response: An initial prompt summarizing key candidate information based on the uploaded resumes is generated, giving an overview aligned with the job criteria.
- Conversational Flow: Subsequent responses and questions are handled in real-time, making the hiring process more intuitive and engaging.
Deployment
Deployment on a public platform enables easy access to the CV SCAN app for potential users. By hosting on Hugging Face Spaces, the app becomes accessible to a wider audience without additional infrastructure requirements.
- Platform: Hosted on Hugging Face Spaces, ensuring public access and streamlined hosting of the AI assistant.
- API Integration: Integrates Google Generative AI API for embedding generation and conversational responses, ensuring security and efficiency.
- User Interface: Built using Streamlit for a simple, interactive, and user-friendly interface, where users can upload resumes, input job descriptions, and receive immediate feedback.