HR Interviewer Agent Overview The HR Interviewer Agent is a LangChain/LangGraph‑based AI interview system that automates the end‑to‑end hiring questionnaire workflow.
Loads a job description and a list of interview questions from a configurable JSON file. Interactively asks the candidate each question via a Gradio web UI. Evaluates answers in real time using a large language model (LLM) and generates follow‑up questions when needed. Produces a structured review of the candidate’s responses and a polished Markdown report. The project demonstrates how to combine LangGraph state graphs, LangChain LLM wrappers, and Gradio for a responsive, asynchronous chat‑style interview experience.
Architecture └─ scr/ ├─ app.py # Streamlit ├─ agents.py # Core LangGraph graph, Interviewer class, state definitions └─ requirements.txt agents.py defines the JobConfig dataclass, the AgentState TypedDict, and the Interviewer class that contains the LLM logic for asking questions, evaluating answers, reviewing the interview, and generating a final report. app.py creates a per‑session graph, handles asynchronous user input, and renders the chat UI with Gradio. requirements.txt lists the Python dependencies required to run the system. Setup Prerequisites Python 3.9 or newer Access to an LLM endpoint (OpenAI, Azure, etc.) – the default model is gpt-4o-mini git (optional, for cloning the repository) I