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zhaojingru-ai/multimodal-interview-system

Analysis updated 2026-05-18

71TypeScriptAudience · researcherComplexity · 3/5Setup · moderate

TLDR

A prototype interview system that generates questions from a resume and job description, then scores video answers using text, audio, and video together.

Mindmap

mindmap
  root((repo))
    What it does
      Match job template
      Generate interview questions
      Score video answers
      Build final report
    Tech stack
      Next.js
      React
      TypeScript
      Coze workflow
    Use cases
      Academic course project
      Graduation thesis demo
      Coze workflow research
    Audience
      Researchers
      Students
    Setup
      npm install
      Runs in mock mode by default

Code map

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filefunction / class

What do people build with it?

USE CASE 1

Build a demo interview flow for a course project or graduation thesis.

USE CASE 2

Try out multimodal evaluation of text, audio, and video answers together.

USE CASE 3

Reproduce and study a Coze workflow using the archived exports and templates.

What is it built with?

Next.jsReactTypeScriptPostgreSQLCoze

How does it compare?

zhaojingru-ai/multimodal-interview-systemmallydev2/discordlyricsmidudev/subvid.app
Stars717172
LanguageTypeScriptTypeScriptTypeScript
Setup difficultymoderateeasyeasy
Complexity3/52/52/5
Audienceresearchergeneralgeneral

Figures from each repo's GitHub metadata at analysis time.

How do you get it running?

Difficulty · moderate Time to first run · 30min

Ships in mock mode by default, real AI evaluation needs Coze workflow API credentials and a database.

The README does not state a license, so usage terms are unclear.

In plain English

This is a prototype interview system built with Next.js and a workflow automation platform called Coze. The README is written in Chinese, so this explanation is drawn from that source. The system is aimed at use cases like academic course projects, graduation theses, and research experiments involving AI-assisted interviewing. The core idea is that you paste in a candidate's resume text and a job description, and the system reads both to figure out which of seven predefined job categories applies (developer, data analyst, product manager, sales, operations, customer service, or HR). It then generates a set of interview questions along with evaluation criteria for each question. The candidate answers each question by recording a video in the browser using their camera and microphone. Once all answers are submitted, the system evaluates each response by analyzing three channels at once: the spoken text, the audio tone, and the video. After all questions are scored, it generates a final report that rolls up the individual results. This three-channel evaluation approach is what makes it "multimodal." The system runs in a mock mode by default, meaning you can go through the full product flow without connecting to any external AI service. If you want real AI-powered evaluation, you configure credentials for the Coze workflow API. The project ships with exported Coze workflow files and job templates archived in its docs folder, so others can reproduce the setup. It is built with Next.js, React, TypeScript, and uses either PostgreSQL or a local JSON file for storing interview sessions. A default admin login is provided for local development. The README emphasizes this is a prototype and research tool, not a production product.

Copy-paste prompts

Prompt 1
Help me run this project locally in mock mode without configuring Coze.
Prompt 2
Explain how the resume and job description get matched to one of the seven job templates.
Prompt 3
Walk me through how the three-channel evaluation of text, audio, and video works here.
Prompt 4
How do I configure real Coze workflow credentials to replace mock mode?

Frequently asked questions

What is multimodal-interview-system?

A prototype interview system that generates questions from a resume and job description, then scores video answers using text, audio, and video together.

What language is multimodal-interview-system written in?

Mainly TypeScript. The stack also includes Next.js, React, TypeScript.

What license does multimodal-interview-system use?

The README does not state a license, so usage terms are unclear.

How hard is multimodal-interview-system to set up?

Setup difficulty is rated moderate, with roughly 30min to a first successful run.

Who is multimodal-interview-system for?

Mainly researcher.

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