🚀 Building an AI Resume Screener with GPT-4 + LangChain + FAISS

#langchain #openai #rag #streamlit

Hi everyone 👋 — I recently built and deployed a full-stack AI Resume Screener that ranks, scores, and evaluates resumes using GPT-4, LangChain, and FAISS. Here’s a technical breakdown of how it works!

🧠 What It Does

Upload .pdf, .docx, or .txt resumes
Paste a job description
GPT-4 scores and summarizes best-fit candidates
Shows results in a Streamlit UI with star ratings
Exports final shortlist as CSV

⚙️ Tech Stack

🧠 GPT-4 (OpenAI) — scoring, summarization
🧱 LangChain — for chunking & vector search
🧲 FAISS — similarity search
📄 Unstructured — DOCX/PDF parsing
🧑‍💼 Streamlit — interactive UI
🐍 Python, Pandas, dotenv

📂 Directory Structure

📌 Key Component 1: Resume Indexing

from langchain_unstructured import UnstructuredLoader
from langchain_community.vectorstores import FAISS
def embed_resumes_from_folder(folder_path):
    docs = []
    for file in os.listdir(folder_path):
        path = os.path.join(folder_path, file)
        resume = UnstructuredLoader(path).load()
        docs.extend(resume)
    vectordb = FAISS.from_documents(docs, embedding_model)
    vectordb.save_local("vectorstore_ui")

📌 Key Component 2: Similarity Search

def search_similar_resumes(job_desc, db_path, k=5):
    vectordb = FAISS.load_local(db_path, embedding_model)
    return vectordb.similarity_search(job_desc, k=k)

📌 Key Component 3: GPT-4 Evaluation

def evaluate_resume(resume_text, job_description):
    prompt = f"""Evaluate the following resume...
    Resume: {resume_text}
    Job: {job_description}

    Return:
    Score: X/10
    Summary: ...
    Fit: Strong/Moderate/Low"""

    return openai.ChatCompletion.create(...)  # GPT-4 call

💡 Why I Built This

I'm currently job hunting and wanted a smarter way to check how well my resume matches each job. So I built this for myself — and now use it before every application.
It saves me time, gives me confidence, and acts like my personal AI career coach.
🧪 Try It Yourself
🔗 GitHub Repository
🚀 Live App (Streamlit Cloud)