A Retrieval-Augmented Generation (RAG) application that analyzes a candidate's resume against a target job description to find skill gaps and provide learning recommendations.
- LLM: Meta Llama 3.1 (via Groq API)
- Vector Database: FAISS
- Embeddings: HuggingFace (
all-MiniLM-L6-v2) - Framework: LangChain
- Frontend/Deployment: Streamlit Community Cloud
- Parses PDF resumes and extracts text.
- Uses FAISS to perform similarity searches against a database of technical job descriptions.
- Leverages Llama 3.1 to generate Match Scores, Missing Skills, and Actionable Learning Paths.