AI Interview Agent Job Analysis and Dual-Mode Response Flow

ML & AI · flowchart diagram · NOASSERTION

This diagram illustrates a two-stage process for an AI interview agent: first, generating a professional job analysis, and then leveraging it in a dual-mod

Source: https://github.com/lanzeweie/ASR-interview-coder-llm/blob/cad6297ac1dc16063215e57c175239b2019d44ab/README/Mermaid.md
Curated by lanzeweie
AI Interview Agent Job Description Contextual AI Flowchart System Design LLM

Mermaid source

graph TD
    %% 定义样式
    classDef base fill:#f9f9f9,stroke:#333,stroke-width:1px;
    classDef input fill:#e3f2fd,stroke:#1565c0,stroke-width:2px;
    classDef analysis fill:#fff9c4,stroke:#fbc02d,stroke-width:2px;
    classDef dualStart fill:#e8f5e9,stroke:#2e7d32,stroke-width:2px;
    classDef action fill:#ede7f6,stroke:#512da8,stroke-width:2px;
    classDef output fill:#212121,stroke:#000,stroke-width:2px,color:#fff;

    %% === 第一阶段：数据准备 ===
    subgraph 用户提取准备
        direction TB
        User([用户输入]) --> Inputs[/岗位名称 / 岗位JD/]
        Inputs --> GenAnalysis[生成: 专业版岗位分析]
    end

    %% === 第二阶段：双模式响应 ===
    subgraph 当回答问题时
        direction TB
        %% 双开头
        StartDirect[模式 A: 直接回答]
        StartThink[模式 B: 第四层 智囊团深度思考]
        
        %% 加载动作
        LoadContext(动作: 加载岗位分析)
        
        %% 输出
        FinalOutput([输出答案])
        
        %% 连线关系
        StartDirect --> LoadContext
        StartThink --> LoadContext
        LoadContext --> FinalOutput
    end

    %% === 跨阶段数据流（虚线代表数据引用） ===
    GenAnalysis -.->|作为上下文数据| LoadContext

    %% 应用样式
    class User,Inputs input;
    class GenAnalysis analysis;
    class StartDirect,StartThink dualStart;
    class LoadContext action;
    class FinalOutput output;

What this diagram shows

The diagram outlines a system where user inputs (job title, JD) are processed to generate a 'Professional Job Analysis'. This analysis then serves as context for a 'Dual-Mode Response' system, which can either directly answer questions or engage in 'Fourth-Layer Think Tank Deep Thinking' before producing a final output.

When to use it

Use this diagram to visualize the architecture of an AI-powered interview preparation tool, a contextual AI agent, or any system requiring deep understanding and tailored responses based on specific job requirements or documents.

How to adapt it for your project

This diagram can be adapted by adding more stages to the analysis (e.g., skill extraction, market trend analysis), introducing additional response modes, integrating external knowledge bases, or incorporating feedback loops for continuous improvement of the analysis and response quality.

Key concepts