Project overview
This open-source project is an intelligent AI agent designed to serve as a personal professional assistant — capable of answering any questions about my background, experience, and technical skills. It represents a modern application of AI in personal branding and professional communication.
The system is built using Python, FastAPI, PydanticAI, PostgreSQL, and vector databases, with a Retrieval-Augmented Generation (RAG) architecture for precise and context-aware responses. Docker and Docker Compose handle containerization, while AWS supports scalable deployment.
With over a decade of experience in the software industry, this AI agent encapsulates my career into a conversational assistant that anyone can interact with directly — whether embedded in a website or accessed via API.
Key features
Natural Language Understanding: Handles complex, open-ended queries using advanced NLP models.
Contextual Awareness: Provides relevant, detailed responses based on my professional history, project portfolio, and technical expertise.
Real-Time Interaction: Delivers fast and reliable answers through an optimized web service.
Vector Search & RAG Architecture: Combines vector databases with retrieval-augmented generation techniques for accurate, up-to-date answers.
Scalable Design: Supports multiple concurrent users without sacrificing performance or accuracy.