A comprehensive chatbot application that provides intelligent job search and career guidance for students, powered by AWS Bedrock AgentCore and cutting-edge AI technologies.
| Description | Link |
|---|---|
| Overview | Overview |
| Architecture | Architecture |
| Detailed Architecture | Detailed Architecture |
| User Flow | User Flow |
| SMS Prerequisites | SMS Prerequisites |
| Deployment | Deployment |
| Post-Deployment Setup | Post-Deployment Setup |
| Usage | Usage |
| Infrastructure | Infrastructure |
| Modification Guide | Modification Guide |
| Credits | Credits |
| License | License |
This application combines natural language processing capabilities with intelligent job matching to deliver accurate, context-aware responses to student queries. Built on a serverless architecture with real-time communication, secure file management, and automated daily job recommendations.
- Multi-Agent AI System powered by AWS Bedrock with Claude 4.5 Sonnet
- AgentCore Memory Integration for cross-session conversation continuity
- Automated Daily Job Recommendations via email and SMS
- AI Resume Parsing with personalized job matching
- Real-time Chat Interface with streaming responses
- Intelligent Job Fit Analysis using semantic search and AI models
The application implements a serverless, event-driven architecture with a multi-agent AI system at its core, combining real-time user interactions with automated batch processing for job matching.
For a detailed deep dive into the architecture, including core principles, component interactions, data flow, security, and implementation details, see docs/ARCHITECTURE.MD.
For a detailed overview of the user journey and application workflow, including diagrams and step-by-step user interactions, see docs/USERFLOW.md.
For detailed deployment instructions, including prerequisites and step-by-step guides, see docs/DEPLOYMENT.MD.
For detailed post-deployment setup and usage instructions, including configuration steps and how to use the application, see docs/POST_DEPLOYMENT_SETUP.md.
For a detailed overview of the application infrastructure, including component interactions, AWS services, and data flow, see docs/INFRASTRUCTURE.MD.
- API Documentation - Comprehensive API reference for all endpoints, request/response formats, and integration patterns
- Post-Deployment Setup Guide - Configuration steps after infrastructure deployment
- User Flow Documentation - Detailed system architecture and user journey documentation
Steps to implement optional modifications such as changing the bedrock Model, adding more checks, or changing the frontend can be found here.
This application was architected and developed by Aryan Khanna, Aarav Matalia, Sayantika Paul and Lahari Shakthi Arun with solutions architect Arun Arunachalam, program manager Thomas Orr and product manager Rachel Hayden. Thanks to the ASU Cloud Innovation Centre and Career Services' Technical and Project Management teams for their guidance and support.
See LICENSE file for details.