All-in-one infrastructure for building search, recommendations, and RAG. Trieve combines search language models with tools for tuning ranking and relevance.
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Updated
Jul 16, 2024 - Rust
All-in-one infrastructure for building search, recommendations, and RAG. Trieve combines search language models with tools for tuning ranking and relevance.
LlamaIndex in TypeScript
MemFree - Hybrid AI Search Engine
👑 Easy-to-use and powerful NLP and LLM library with 🤗 Awesome model zoo, supporting wide-range of NLP tasks from research to industrial applications, including 🗂Text Classification, 🔍 Neural Search, ❓ Question Answering, ℹ️ Information Extraction, 📄 Document Intelligence, 💌 Sentiment Analysis etc.
Fast protein structure searching or your money back
The AI-native database built for LLM applications, providing incredibly fast hybrid search of dense embedding, sparse embedding, tensor and full-text
Langchain-Chatchat(原Langchain-ChatGLM, Qwen 与 Llama 等)基于 Langchain 与 ChatGLM 等语言模型的 RAG 与 Agent 应用 | Langchain-Chatchat (formerly langchain-ChatGLM), local knowledge based LLM (like ChatGLM, Qwen and Llama) RAG and Agent app with langchain
🔧 Repair JSON!Solution for JSON Anomalies from LLMs.
Pinecone is a fully-fledged C# library for the Pinecone vector database. It aims to provide identical functionality to the official Python and Rust libraries. This is fork of Pinecone.NET.
Redis Vector Library (RedisVL) interfaces with Redis' vector database for realtime semantic search, RAG, and recommendation systems.
The RAG Experiment Accelerator is a versatile tool designed to expedite and facilitate the process of conducting experiments and evaluations using Azure Cognitive Search and RAG pattern.
Generative Representational Instruction Tuning
Contains examples of embedding Flutter in React apps.
VQLite - Simple and Lightweight Vector Search Engine based on Google ScaNN
RAG with LM studio, local LLMs, Scientific PDF text extraction,
A cutting-edge search engine project tailored specifically for the AI product
LOLA_ LLM-Assisted Online Learning Algorithm for Content Experiments
A basic LLM application as knowledge base. You can have the LLM answer your questions from the context you provide. Main steps: vectorization (embedding), RAG. 一个基本的知识库类型大语言模型应用。你可以让大模型从你提供的上下文中回答你的提问。主要步骤:向量化(内嵌),RAG。
RagE (RAG Engine) - A tool supporting the construction and training of components of the Retrieval-Augmented-Generation (RAG) model. It also facilitates the rapid development of Q&A systems and chatbots following the RAG model.
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