A FastAPI service for semantic text search using precomputed embeddings and advanced similarity measures, with built-in support for various file types through textract.
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Updated
Jun 3, 2024 - Python
A FastAPI service for semantic text search using precomputed embeddings and advanced similarity measures, with built-in support for various file types through textract.
Java version of LangChain
A repository of code samples for Vector search capabilities in Azure AI Search.
Semantic embedding-based question-answering system that processes PDFs to generate embeddings for sentences, enabling semantic search and question answering using these embeddings.
The open source Firebase alternative.
Private chat with local GPT with document, images, video, etc. 100% private, Apache 2.0. Supports oLLaMa, Mixtral, llama.cpp, and more. Demo: https://gpt.h2o.ai/ https://codellama.h2o.ai/
An app for writers who thrive in a less structured environment. Neptune Project uses advanced semantic search and a customizable workspace to enhance your creative writing process. Capture spontaneous ideas, get contextual suggestions, and enjoy effortless navigation. Unleash your creativity with Neptune Project.
RAG Chat Assistant with MongoDB Atlas, Google Cloud and Langchain
Embeddable vector database for Go with Chroma-like interface and zero third-party dependencies. In-memory with optional persistence.
The GPU-powered AI application database. Get your app to market faster using the simplicity of SQL and the latest NLP, ML + LLM models.
Legal case retrieval challenge. Solution based on similarity search and learning-to-rank methods
An animal can do training and inference every day of its existence until the day of its death. A forward pass is all you need.
Fast, Accurate, Lightweight Python library to make State of the Art Embedding
Personalizing LLM Responses
Building a movie recommender app backend using MongoDB Atlas Search and local embeddings. Features include efficient searches, user interaction, and logging for debugging.
8 Lessons, Get Started Building with Generative AI and Gemini API
This repository contains examples for customers to get started using the Amazon Bedrock Service. This contains examples for all available foundational models
Modern columnar data format for ML and LLMs implemented in Rust. Convert from parquet in 2 lines of code for 100x faster random access, vector index, and data versioning. Compatible with Pandas, DuckDB, Polars, Pyarrow, with more integrations coming..
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