Skip to content

Latest commit

 

History

History
58 lines (41 loc) · 1.4 KB

File metadata and controls

58 lines (41 loc) · 1.4 KB

InterviewAlly

Note: This is an experimental app.

InterviewAlly is an AI-powered interview assistant. It uses Retrieval-Augmented Generation (RAG) to ingest an interview handbook and answer questions contextually using Groq LLMs and local embeddings.

App Screenshot

Features

  • RAG Architecture: Retrieves context from a local markdown knowledge base.
  • LLM Provider: Uses Groq for high-speed inference.
  • Embeddings: Uses local HuggingFace Transformers (all-MiniLM-L6-v2) to avoid external embedding costs.
  • Interface: Includes a simple web UI and a REST API.

Technologies

  • Runtime: Node.js, TypeScript
  • Web Framework: Express
  • AI Framework: LangChain
  • LLM: Groq
  • Vector Store: In-Memory
  • Embeddings: HuggingFace Transformers

Prerequisites

  • Node.js (v18 or higher recommended)
  • A Groq API Key

Installation

  1. Install dependencies:

    npm install
  2. Prepare the Knowledge Base: Ensure you have your source material located at:

    data/interview-handbook.md
    
  3. Environment Configuration: Create a .env file in the root directory with the following variables:

    LLM_API_KEY=your_groq_api_key
    LLM_MODEL=llama3-8b-8192

Running the Application

Start the server:

npx ts-node src/server.ts

The server will start at http://localhost:3000.