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45 search results found

Anything Llm ⭐ 7,602

Open-source multi-user ChatGPT for all LLMs, embedders, and vector databases. Unlimited documents, messages, and users in one privacy-focused app.

Danswer ⭐ 6,435

Ask Questions in natural language and get Answers backed by private sources. Connects to tools like Slack, GitHub, Confluence, etc.

Txtai ⭐ 6,143

💡 All-in-one open-source embeddings database for semantic search, LLM orchestration and language model workflows

Your AI second brain. A copilot to search and chat (using RAG) with your knowledge base (pdf, markdown, org). Use powerful, online (e.g gpt4) or private, offline (e.g mistral) LLMs. Self-host locally or have it always accessible on the cloud. Access from Obsidian, Emacs, Desktop app, Web or Whatsapp

Llmware ⭐ 1,859

Providing enterprise-grade LLM-based development framework, tools, and fine-tuned models.

Llm App ⭐ 1,573

LLM App is a production framework for building and serving AI applications and LLM-enabled real-time data pipelines.

Langroid ⭐ 988

Harness LLMs with Multi-Agent Programming

All-in-one infrastructure for building search, recommendations, and RAG. Trieve combines search language models with tools for tuning ranking and relevance.

Infinity ⭐ 936

The AI-native database built for LLM applications, providing incredibly fast vector and full-text search

Rag Demystified ⭐ 610

An LLM-powered advanced RAG pipeline built from scratch

Neurite ⭐ 589

Neurite: Fractal Mind Map

Fastembed ⭐ 531

Fast, Accurate, Lightweight Python library to make State of the Art Embedding

Generativeaiexamples ⭐ 458

Generative AI reference workflows optimized for accelerated infrastructure and microservice architecture.

Arxivchatguru ⭐ 446

Use ArXiv ChatGuru to talk to research papers. This app uses LangChain, OpenAI, Streamlit, and Redis as a vector database/semantic cache.

Agent Search ⭐ 295

AgentSearch is a framework for powering search agents and enabling customizable local search.

Start Llms ⭐ 271

A complete guide to start and improve your LLM skills in 2023 with little background in the field and stay up-to-date with the latest news and state-of-the-art techniques!

Llm Search ⭐ 271

Querying local documents, powered by LLM

Angle-optimized Text Embeddings | 🔥 SOTA on STS and MTEB Leaderboard

Txtchat ⭐ 183

💭 Retrieval augmented generation (RAG) and language model powered search applications

Awesome Llm Rag ⭐ 147

Awesome-LLM-RAG: a curated list of advanced retrieval augmented generation (RAG) in Large Language Models

Tonic_validate ⭐ 128

Metrics to evaluate the quality of responses of your Retrieval Augmented Generation (RAG) applications.

Empower Large Language Models (LLM) using Knowledge Graph based Retrieval-Augmented Generation (KG-RAG) for knowledge intensive tasks

Flashrank ⭐ 97

Ultra-lite & Super-fast re-ranking for your search & retrieval pipelines. Based on SoTA models like cross-encoders and more. Created by Prithivi Da, open for PRs & Collaborations.

Taskingai ⭐ 97

The open source platform for AI-native application development.

Llm Document Chat ⭐ 87

Using LlamaIndex, Redis, and OpenAI to chat with PDF documents. Supplementary material for blog post on Microsoft Developer Blog

Mistral Haystack ⭐ 79

Mistral + Haystack: build RAG pipelines that rock 🤘

Continuous Eval ⭐ 78

Evaluation for LLM / RAG pipelines, ready for CI/CD

Fastembed Rs ⭐ 73

Rust implementation of @Qdrant/fastembed.

Rag Using Langchain Amazon Bedrock And Opensearch ⭐ 47

RAG with langchain using Amazon Bedrock and Amazon OpenSearch

MongoDB Chatbot Framework. Powered by MongoDB and Atlas Vector Search.

Gpt Gradio Agent ⭐ 20

Build your own GPT Agent,get web resources and manage your local knowledge base with Azure OpenAI API (or OpenAI). 使用 Azure OpenAI（兼容OpenAI）创建自己的 GPT 智能助手，获取网页资源，并构建和管理本地知识库。

Gpt All Local ⭐ 15

A "chat with your data" example: using a large language models (LLM) to interact with our own (local) data. Everything is local: the embedding model, the LLM, the vector database. This is an example of retrieval-augmented generation (RAG): we find relevant sections from our documents and pass it to the LLM as part of the prompt (see pics).

Ai Starter Kit ⭐ 12

A Web app stack written in FastAPI, Qdrant, and React for creating AI projects

Fastembed Js ⭐ 12

FastEmbed-JS is a Typescript/NodeJS implementation of @Qdrant/fastembed.

Build Ragai ⭐ 11

AI-powered Python components and notebooks for leveraging Large Language Models from OpenAI and Hugging Face.

Semantic Ai ⭐ 11

An open source framework for Retrieval-Augmented System (RAG) uses semantic search helps to retrieve the expected results and generate human readable conversational response with the help of LLM (Large Language Model).

Aws Llm Sagemaker ⭐ 11

SageMaker Ployglot based RAG opensearch

Autonomous_general_agent_swarm ⭐ 9

chatgpt on crack

Examplify ⭐ 8

An offline CPU-first memory-scarce chat application to perform RAG on your corpus of data. Powered by OpenChat and CTranslate2.

Interactive Rag ⭐ 8

Using MongoDB Atlas + ActionWeaver, we can build a user proxy agent that efficiently retrieves and ingests relevant information. This agent presents the data to the user in an interactive and customizable manner, enhancing the overall user experience.

Nexaaione ⭐ 7

Arm you with all the essential tools to integrate AI seamlessly into your apps, regardless of the coding language you're comfortable

Kryten is a CLI tool to ask questions and get sourced answers from any .pdf, .doc, .docx, and many more documents.

Openai Embeddings ⭐ 6

OpenAI chatGPT hybrid search and retrieval augmented generation

Langchain Rag Linux ⭐ 5

Examples of RAG using LangChain with local LLMs - Mixtral 8x7B, Llama 2, Mistral 7B, Orca 2, Phi-2, Neural 7B

Fastembed Go ⭐ 5

FastEmbed-go is a Go implementation of @Qdrant/fastembed.

Related Searches

Python Retrieval Augmented Generation (58)

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