🔥 大模型 & Agent 面试八股文完全指南 | LLM & Agent Interview Preparation Guide

收集大模型相关面试题｜agent｜上下文工程｜强化学习｜langgraph｜langchain｜rag｜微调

Comprehensive ML/AI interview codex with iterative system design, production-ready code, and 2026 standards. Includes LLM/GenAI, RAG systems, agentic AI, and algorithms from scratch.

Build realtime AI interviewer voice agent that joins meetings. It demonstrates integrating Deepgram (STT), OpenAI (LLM), and Eleven Labs (TTS) via WebRTC for natural conversations.

Agentic LLM System for Practicing System Design and other technical Interviews.

Prompt Concierge is an autonomous agent that interviews a user about a task, builds a knowledge bank, crafts an optimal LLM prompt, and keeps that prompt up-to-date as new production data arrives.

Ascend Flow (智流) is a multi-agent, adaptive learning system where specialized LLM tutors collaboratively plan, teach, generate scaffolded practice, and regulate motivation to keep learners in flow—bridging the gap from “understanding” to “solving” for coding interviews and foundational math.

Supplementary Material: This document provides the prompt for "Virtual Agents for Alcohol Use Counseling: Exploring LLM-Powered Motivational Interviewing" paper:

List of question that might be asked in interviews for AI, GenAI, LLM, RAG, Agentic applciations and more.

Several resources for LLM interviews, including base knowledge, pretraining, SFT, RL training, RAG, agent, VLM, newest research and so on.

AI-powered interview coach with RAG question bank, LangGraph agent, multi-LLM support, and voice interaction.

This is the source code of the paper "JudgeAgent: Dynamically Evaluate LLMs with Agent-as-Interviewer".

Agentic System Design Interview bot powered by WIRL workflows. Features an interactive Streamlit UI, tool-using verification agents, and automated LLM-as-a-judge evaluation.

Advanced Multi-Agent System powered by local Ollama LLMs This system uses multiple specialized agents that collaborate to: Extract and match skills Analyze experience and career progression Generate targeted interview questions Provide comprehensive hiring recommendations

Self-hosted open-source platform for AI-powered survey interviews. Voice-to-voice and text chat agents with semi-structured interview guides, multi-provider LLM support (OpenAI, Gemini, Scaleway), RAG knowledge base, and Twilio telephony. Built for qualitative researchers. Docker, one command, full control.

Scholar AI - An intelligent research paper interview system powered by Ollama LLM and RAG. Upload any PDF paper and watch two AI agents (Journalist & Author) conduct an in-depth Q&A session. Built with Streamlit, LangChain, and FAISS. 100% local, private, and free.

A complete roadmap to become an AI/LLM Engineer in 2026. Free & paid courses, 5 portfolio projects, interview prep, and resources. For software engineers with Python & ML basics who want to break into AI. Covers Transformers, RAG, fine-tuning, agents, LangChain, MLOps, and deployment.

This is the prototype for a LLM based Interview Agent

auto dm based on agents by LLM calling, focusing more on backend features, interview oriented, providing convenience for dm-player

An interactive AI learning \u0026 interview simulation platform built with Next.js, covering LLM architecture, Agent, and RAG. Your ultimate guide to conquering AI engineering interviews.

Voice agent prototype for structured clinical interviewing, with VAD-based interruption handling, modular ASR/LLM/TTS backends, and dialogue workflow control.

Built a stateful LLM-powered interview assistant using FastAPI and Groq, implementing agent-based memory, difficulty control, and multi-round reasoning to generate non-repetitive interview questions from job descriptions.

Full LLMOps loop assignments from Interview Kickstart Applied Agentic AI — evaluation, prompt improvement, golden datasets, and custom LLM judges using LangChain, LangSmith, and DeepEval.

A real-time, low-latency voice agent designed to conduct technical interviews. This microservice orchestrates a local LLM (Llama 3), a local TTS engine (Kokoro), and a speech transcription service (Whisper) to act as an autonomous interviewer.

Agentic, policy-driven LLM system that simulates a full multi-stage technical interview with adaptive difficulty, structured evaluation, and behavioral feedback — built using LangGraph, LangChain, and Gemini 2.5.

Intervu.AI is a voice-first, context-aware agentic interview coach powered by LangChain and LLMs, built on FastAPI to provide dynamic, real-time evaluation and customized question generation.

A unified autonomous AI system using n8n and agentic LLMs. It continuously scrapes NVIDIA engineering content, stores it in a RAG system, adapts my daily interview preparation, simulates interviews, evaluates responses, and delivers daily intelligence via email and a web dashboard

Fully autonomous AI interview platform. Features an LLM-powered ATS, a live conversational voice agent for technical rounds, and dynamic behavioral psychology tests - Built at Microsoft Office, Hyderabad (Forged Alumni).

A FastAPI backend that orchestrates multiple LLM agents to support executive search workflows. It can generate market intelligence, job descriptions, client persona prompts, client feedback, and interview reports, and it includes a project-based chat flow with file uploads.

SmartScreenAI leverages an LLM agent to automate candidate interviews seamlessly. It conducts a step-by-step interview process, starting with CV screening round and tailoring questions based on the candidate's CV and job description to help recruiters streamline hiring and improve efficiency.