Search Results for "backend"

Sonic is a super fast and lightweight, schema-less search backend that can be used in place of super-heavy and full-featured search backends like Elasticsearch. It is able to normalize language search queries, auto-complete search queries and offer the most relevant results. Being an identifier index rather than a document index, when queried it provides IDs that can be used to refer to matched documents in an external database.

...It might not make sense for every situation, but can be ideal depending on your search requirements. For example, qhen you want client-side fuzzy searching of small to moderately large data sets. Also, when you can't justify setting up a dedicated backend simply to handle search. ElasticSearch or Algolia, although both great services, may be overkill for your particular use cases. You can access all options above via Fuse.config. This is useful if you want to override default options for all Fuse instances. Fuse.js supports logical query operators. These operators are used for filtering the data and getting precise results based on the given conditions.

TNTSearch is a full-text search engine written in PHP, designed to be integrated into Laravel and other PHP applications. It offers real-time, efficient indexing and searching of textual data using SQLite as its storage backend. TNTSearch is highly configurable and supports features like fuzzy searching, customizable ranking algorithms, and boolean search, making it a powerful tool for adding search functionality to websites and applications.

...Its architecture is modular, separating handlers, services, and utilities to support customization and extension. Overall, rag-search serves as a practical starter backend for teams building AI search or question-answering applications on their own data.

FreeAskInternet is a self-hosted search and answer application that combines web results with large language models. A local SearXNG instance sends queries to multiple search engines and returns a broader collection of sources. The backend crawls selected pages, supplies their content to a configured model, and streams a synthesized response to the chat interface. It supports several hosted model services as well as custom local backends such as Ollama and llama.cpp. The web interface is designed for desktop and mobile use and exposes the service only on the local machine by default. ...

...The repo stores the full text of his essays (chunked), uses embeddings (e.g. via OpenAI embeddings) to allow semantic search over that corpus, and hosts a chat interface that combines retrieval results with LLM-based answering — enabling RAG (retrieval-augmented generation) over a fixed dataset. The app uses a Postgres database (with pgvector) hosted on Supabase for its embedding store, making the backend relatively simple and accessible, and the frontend is again built with Next.js/TypeScript for a modern responsive UI. By pulling together search and chat, it creates a useful tool both for readers who want to revisit or explore Paul Graham’s ideas thematically, and for learners or researchers who want to query specific essays or concepts quickly.

Snippetsource is a simple yet powerful repository to store code snippets or any other text content. SQLite is used as the database backend which makes fast indexed lookups possible.

A searcher and indexer to allow easy and fast locating of relevent information from a large collection of research papers. A Java backend with a web based frontend. Based on the Lucene indexer and searcher