Neural Search
Semantic search engine using transformer models for intelligent document retrieval.
Tech Stack
PyTorchHuggingFace TransformersQdrant Vector DBFastAPIReactDocker
Project Overview
Neural Search represents the next generation of information retrieval, moving beyond keyword matching to understanding the semantic meaning behind queries. Powered by state-of-the-art transformer models (BERT/RoBERTa), it provides highly relevant search results even for complex or ambiguous queries.
Key Features
Semantic vector search
Context-aware query understanding
Automatic document summarization
Multi-language support
Relevance feedback loop