I built an AI console app agent in Node.js where a recruiter can select the best candidate for a position just by providing a prompt and send an email notification, all powered by AI.
LangGraph.js is a library for building stateful, multi-actor applications with LLMs, used to create agent and multi-agent workflows. Compared to other LLM frameworks, it offers these core benefits; cycles, controllability, and persistence.
In the app, the AI agent will select the matching job categories based on a prompt from the Categories.json file. Then, from the respective categories, matching candidates in the Candidates.json file will be selected based on their skills. The app follows a human-in-the-loop (HITL) approach, requiring human intervention before proceeding with certain tasks. If the selected best candidate does not satisfy the recruiter, they can skip it and ask for the next best candidate. If the best candidate is selected, an email notification generated by AI will be sent to the candidate. If the generated email does not satisfy the recruiter, they can skip it and ask for another one with different content.
We add tracing in LangSmith to monitor model performance, trace execution flows, and evaluate LLM interactions, ensuring they operate efficiently and meet expectations.
To get started.
# Clone the repository
git clone https://github.com/Ashot72/Job-Interview-Notification-AI-Agent-LangGraph-JS
cd Job-Interview-Notification-AI-Agent-LangGraph-JS
# Create the .env file based on the env.example.txt file and include the respective keys.
# installs dependencies
yarn install
# to start
npm start
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