Document Search in C# without Elasticsearch
Build a full-text search engine in C# with keyword search, semantic search, hybrid ranking, and reranking. Index files and query them in 10 lines of code, with the index living on your own disk.
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Build a full-text search engine in C# with keyword search, semantic search, hybrid ranking, and reranking. Index files and query them in 10 lines of code, with the index living on your own disk.
Read moreImprove search relevance in .NET with cross-encoder reranking. Rescore your existing search results from Elasticsearch, SQL LIKE, or vector search, locally in C# and in your own process.
Read moreBuild a retrieval-augmented generation pipeline in C#: index documents, search them, rerank the hits, and answer with a local LLM. One NuGet package, start to finish, with every stage running on your own machine.
Read moreRun embeddings, classification and reranking from C++ with no libtorch and no ONNX Runtime: one header and one shared library that links only against libc. Works with C++11, C++14, C++17 and C++23, and takes four commands from nothing to output.
Read moreIndex a directory, then search it by keyword, by meaning, or both, from Python. One pip install with no dependencies, running on your own machine, with a worked example of where hybrid search goes wrong and what fixes it.
Read moreAdd keyword, semantic and hybrid search with cross-encoder reranking to a Qt 6 / QML application, running locally in C++ with no Python, no ONNX Runtime and no server. A complete working example with real results.
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