This project provides a multi-agent AI system designed to assist users in their job search. It targets individuals seeking employment by automating tasks like tailored job discovery, cover letter generation, and company research, aiming to make the job hunt more efficient and personalized.

How It Works

The system employs a Supervisor Multi-Agent Architecture, orchestrated by LangGraph. A central Supervisor agent manages the workflow, delegating tasks to specialized agents: JobSearcher, ResumeAnalyzer, CoverLetterGenerator, WebResearcher, and a ChatBot. These agents utilize custom tools for specific functions, such as web scraping (FireCrawl, Serper) and resume parsing, to deliver personalized career assistance through an intuitive Streamlit interface.

Quick Start & Requirements

• Install via pip install -r requirements.txt.
• Requires OpenAI API key, and optionally Groq, Serper, FireCrawl, and LinkedIn API keys/credentials.
• Environment variables must be set in .streamlit/secrets.toml.
• Run with streamlit run app.py.

Highlighted Details

• Leverages LangGraph for robust multi-agent workflow management.
• Integrates multiple specialized agents for distinct job-seeking tasks.
• Utilizes Streamlit for a user-friendly interactive interface.
• Employs external APIs (OpenAI, Serper, FireCrawl) for LLM capabilities and web data retrieval.

Maintenance & Community

The project is maintained by Aman Varyani. Contributions are welcomed via issues, forks, and pull requests.

Licensing & Compatibility

Licensed under the MIT License, permitting commercial use and integration with closed-source projects.

Limitations & Caveats

The project relies heavily on external API keys, which may incur costs. LinkedIn integration requires specific credentials and may have associated usage limitations. The "Future Improvements" section indicates ongoing development and potential for further enhancements.