Trending repositories for topic retrieval-augmented-generation
RAG (Retrieval Augmented Generation) Framework for building modular, open source applications for production by TrueFoundry
RAGFlow is an open-source RAG (Retrieval-Augmented Generation) engine based on deep document understanding.
The open source platform for AI-native application development.
:mag: LLM orchestration framework to build customizable, production-ready LLM applications. Connect components (models, vector DBs, file converters) to pipelines or agents that can interact with your ...
LLM App templates for RAG, knowledge mining, and stream analytics. Ready to run with Docker,⚡in sync with your data sources.
An enterprise-grade AI retriever designed to streamline AI integration into your applications, ensuring cutting-edge accuracy.
The official implementation of RAPTOR: Recursive Abstractive Processing for Tree-Organized Retrieval
💡 All-in-one open-source embeddings database for semantic search, LLM orchestration and language model workflows
Unified framework for building enterprise RAG pipelines with small, specialized models
The AI-native database built for LLM applications, providing incredibly fast full-text and vector search
Generative AI reference workflows optimized for accelerated infrastructure and microservice architecture.
An LLM-powered knowledge curation system that researches a topic and generates a full-length report with citations.
Awesome-LLM-RAG: a curated list of advanced retrieval augmented generation (RAG) in Large Language Models
A complete guide to start and improve your LLM skills in 2024 with little background in the field and stay up-to-date with the latest news and state-of-the-art techniques!
Fast, Accurate, Lightweight Python library to make State of the Art Embedding
An enterprise-grade AI retriever designed to streamline AI integration into your applications, ensuring cutting-edge accuracy.
RAG (Retrieval Augmented Generation) Framework for building modular, open source applications for production by TrueFoundry
The official implementation of RAPTOR: Recursive Abstractive Processing for Tree-Organized Retrieval
Embeddable vector database for Go with Chroma-like interface and zero third-party dependencies. In-memory with optional persistence.
Create your own GPT intelligent assistants using Azure OpenAI, Ollama, and local models, build and manage local knowledge bases, and expand your horizons with AI search engines. 使用 Azure OpenAI、Ollama...
Transformers 3rd Edition
RAGFlow is an open-source RAG (Retrieval-Augmented Generation) engine based on deep document understanding.
Setup and run a local LLM and Chatbot using consumer grade hardware.
[CVPR24 Oral] Official repository for RALF: Retrieval-Augmented Layout Transformer for Content-Aware Layout Generation
A complete guide to start and improve your LLM skills in 2024 with little background in the field and stay up-to-date with the latest news and state-of-the-art techniques!
Lite & Super-fast re-ranking for your search & retrieval pipelines. Supports SoTA Listwise and Pairwise reranking based on LLMs and cross-encoders and more. Created by Prithivi Da, open for PRs & C...
Awesome-LLM-RAG: a curated list of advanced retrieval augmented generation (RAG) in Large Language Models
Elevate user interactions with ChatFAQ: your open-source chatbot solution, offering the full spectrum of ChatGPT capabilities. AI + LLM + CMS
The open source platform for AI-native application development.
LLM App templates for RAG, knowledge mining, and stream analytics. Ready to run with Docker,⚡in sync with your data sources.
Metrics to evaluate the quality of responses of your Retrieval Augmented Generation (RAG) applications.
RAG (Retrieval Augmented Generation) Framework for building modular, open source applications for production by TrueFoundry
RAGFlow is an open-source RAG (Retrieval-Augmented Generation) engine based on deep document understanding.
LLM App templates for RAG, knowledge mining, and stream analytics. Ready to run with Docker,⚡in sync with your data sources.
:mag: LLM orchestration framework to build customizable, production-ready LLM applications. Connect components (models, vector DBs, file converters) to pipelines or agents that can interact with your ...
Unified framework for building enterprise RAG pipelines with small, specialized models
The open source platform for AI-native application development.
The AI-native database built for LLM applications, providing incredibly fast full-text and vector search
💡 All-in-one open-source embeddings database for semantic search, LLM orchestration and language model workflows
An enterprise-grade AI retriever designed to streamline AI integration into your applications, ensuring cutting-edge accuracy.
The official implementation of RAPTOR: Recursive Abstractive Processing for Tree-Organized Retrieval
An LLM-powered knowledge curation system that researches a topic and generates a full-length report with citations.
Awesome-LLM-RAG: a curated list of advanced retrieval augmented generation (RAG) in Large Language Models
Generative AI reference workflows optimized for accelerated infrastructure and microservice architecture.
All-in-one infrastructure for building search, recommendations, and RAG. Trieve combines search language models with tools for tuning ranking and relevance.
A complete guide to start and improve your LLM skills in 2024 with little background in the field and stay up-to-date with the latest news and state-of-the-art techniques!
Fractal Graph Desktop for Ai-Agents, Web-Browsing, Note-Taking, and Code.
An enterprise-grade AI retriever designed to streamline AI integration into your applications, ensuring cutting-edge accuracy.
RAG (Retrieval Augmented Generation) Framework for building modular, open source applications for production by TrueFoundry
[CVPR24 Oral] Official repository for RALF: Retrieval-Augmented Layout Transformer for Content-Aware Layout Generation
Embeddable vector database for Go with Chroma-like interface and zero third-party dependencies. In-memory with optional persistence.
The official implementation of RAPTOR: Recursive Abstractive Processing for Tree-Organized Retrieval
Transformers 3rd Edition
LLM App templates for RAG, knowledge mining, and stream analytics. Ready to run with Docker,⚡in sync with your data sources.
RAGFlow is an open-source RAG (Retrieval-Augmented Generation) engine based on deep document understanding.
Awesome-LLM-RAG: a curated list of advanced retrieval augmented generation (RAG) in Large Language Models
Setup and run a local LLM and Chatbot using consumer grade hardware.
A complete guide to start and improve your LLM skills in 2024 with little background in the field and stay up-to-date with the latest news and state-of-the-art techniques!
Create your own GPT intelligent assistants using Azure OpenAI, Ollama, and local models, build and manage local knowledge bases, and expand your horizons with AI search engines. 使用 Azure OpenAI、Ollama...
:zap: Cloud-native, AI-powered, document processing pipelines on AWS.
Build your own Custom RAG Chatbot using Gradio, Langchain and Llama2
The AI-native database built for LLM applications, providing incredibly fast full-text and vector search
Minimalist web-searching app with an AI assistant that runs directly from your browser. Uses Web-LLM, Ratchet-ML, Wllama and SearXNG. Demo: https://felladrin-minisearch.hf.space
RAGFlow is an open-source RAG (Retrieval-Augmented Generation) engine based on deep document understanding.
RAG (Retrieval Augmented Generation) Framework for building modular, open source applications for production by TrueFoundry
Unified framework for building enterprise RAG pipelines with small, specialized models
The open source platform for AI-native application development.
LLM App templates for RAG, knowledge mining, and stream analytics. Ready to run with Docker,⚡in sync with your data sources.
An LLM-powered knowledge curation system that researches a topic and generates a full-length report with citations.
All-in-one infrastructure for building search, recommendations, and RAG. Trieve combines search language models with tools for tuning ranking and relevance.
:mag: LLM orchestration framework to build customizable, production-ready LLM applications. Connect components (models, vector DBs, file converters) to pipelines or agents that can interact with your ...
Radient turns many data types (not just text) into vectors for similarity search, clustering, regression analysis, and more.
The AI-native database built for LLM applications, providing incredibly fast full-text and vector search
💡 All-in-one open-source embeddings database for semantic search, LLM orchestration and language model workflows
Lite & Super-fast re-ranking for your search & retrieval pipelines. Supports SoTA Listwise and Pairwise reranking based on LLMs and cross-encoders and more. Created by Prithivi Da, open for PRs & C...
The official implementation of RAPTOR: Recursive Abstractive Processing for Tree-Organized Retrieval
Generative AI reference workflows optimized for accelerated infrastructure and microservice architecture.
Fast, Accurate, Lightweight Python library to make State of the Art Embedding
Awesome-LLM-RAG: a curated list of advanced retrieval augmented generation (RAG) in Large Language Models
Radient turns many data types (not just text) into vectors for similarity search, clustering, regression analysis, and more.
RAG (Retrieval Augmented Generation) Framework for building modular, open source applications for production by TrueFoundry
All-in-one infrastructure for building search, recommendations, and RAG. Trieve combines search language models with tools for tuning ranking and relevance.
Lite & Super-fast re-ranking for your search & retrieval pipelines. Supports SoTA Listwise and Pairwise reranking based on LLMs and cross-encoders and more. Created by Prithivi Da, open for PRs & C...
Embeddable vector database for Go with Chroma-like interface and zero third-party dependencies. In-memory with optional persistence.
RAGFlow is an open-source RAG (Retrieval-Augmented Generation) engine based on deep document understanding.
Transformers 3rd Edition
Unified framework for building enterprise RAG pipelines with small, specialized models
The official implementation of RAPTOR: Recursive Abstractive Processing for Tree-Organized Retrieval
Empower Large Language Models (LLM) using Knowledge Graph based Retrieval-Augmented Generation (KG-RAG) for knowledge intensive tasks
LLM App templates for RAG, knowledge mining, and stream analytics. Ready to run with Docker,⚡in sync with your data sources.
[CVPR24 Oral] Official repository for RALF: Retrieval-Augmented Layout Transformer for Content-Aware Layout Generation
Chat with your PDFs, built using Streamlit and Langchain. Allows the user to ask questions to a LLM, which will answer based on the content of the provided PDFs.
This repo provides sample generative AI stacks built atop the AWS Generative AI CDK Constructs.
The open source platform for AI-native application development.
Setup and run a local LLM and Chatbot using consumer grade hardware.
Minimalist web-searching app with an AI assistant that runs directly from your browser. Uses Web-LLM, Ratchet-ML, Wllama and SearXNG. Demo: https://felladrin-minisearch.hf.space
RAGFlow is an open-source RAG (Retrieval-Augmented Generation) engine based on deep document understanding.
The open source platform for AI-native application development.
An LLM-powered knowledge curation system that researches a topic and generates a full-length report with citations.
Unified framework for building enterprise RAG pipelines with small, specialized models
LLM App templates for RAG, knowledge mining, and stream analytics. Ready to run with Docker,⚡in sync with your data sources.
RAG (Retrieval Augmented Generation) Framework for building modular, open source applications for production by TrueFoundry
Generative AI reference workflows optimized for accelerated infrastructure and microservice architecture.
Fast, Accurate, Lightweight Python library to make State of the Art Embedding
Awesome-LLM-RAG: a curated list of advanced retrieval augmented generation (RAG) in Large Language Models
The official implementation of RAPTOR: Recursive Abstractive Processing for Tree-Organized Retrieval
Build your own serverless AI Chat with Retrieval-Augmented-Generation using LangChain.js, TypeScript and Azure
A complete guide to start and improve your LLM skills in 2024 with little background in the field and stay up-to-date with the latest news and state-of-the-art techniques!
RAGFlow is an open-source RAG (Retrieval-Augmented Generation) engine based on deep document understanding.
The open source platform for AI-native application development.
:mag: LLM orchestration framework to build customizable, production-ready LLM applications. Connect components (models, vector DBs, file converters) to pipelines or agents that can interact with your ...
An LLM-powered knowledge curation system that researches a topic and generates a full-length report with citations.
Unified framework for building enterprise RAG pipelines with small, specialized models
💡 All-in-one open-source embeddings database for semantic search, LLM orchestration and language model workflows
LLM App templates for RAG, knowledge mining, and stream analytics. Ready to run with Docker,⚡in sync with your data sources.
RAG (Retrieval Augmented Generation) Framework for building modular, open source applications for production by TrueFoundry
The AI-native database built for LLM applications, providing incredibly fast full-text and vector search
Generative AI reference workflows optimized for accelerated infrastructure and microservice architecture.
All-in-one infrastructure for building search, recommendations, and RAG. Trieve combines search language models with tools for tuning ranking and relevance.
Fast, Accurate, Lightweight Python library to make State of the Art Embedding
Fractal Graph Desktop for Ai-Agents, Web-Browsing, Note-Taking, and Code.
Awesome-LLM-RAG: a curated list of advanced retrieval augmented generation (RAG) in Large Language Models
An LLM-powered knowledge curation system that researches a topic and generates a full-length report with citations.
The open source platform for AI-native application development.
Tutorial on training, evaluating LLM, as well as utilizing RAG, Agent, Chain to build entertaining applications with LLMs.分享如何训练、评估LLMs，如何基于RAG、Agent、Chain构建有趣的LLMs应用。
All-in-one infrastructure for building search, recommendations, and RAG. Trieve combines search language models with tools for tuning ranking and relevance.
Akcio is a demonstration project for Retrieval Augmented Generation (RAG). It leverages the power of LLM to generate responses and uses vector databases to fetch relevant documents to enhance the qual...
The official implementation of RAPTOR: Recursive Abstractive Processing for Tree-Organized Retrieval
Redis Vector Library (RedisVL) interfaces with Redis' vector database for realtime semantic search, RAG, and recommendation systems.
A complete guide to start and improve your LLM skills in 2024 with little background in the field and stay up-to-date with the latest news and state-of-the-art techniques!
In-Context Learning for eXtreme Multi-Label Classification (XMC) using only a handful of examples.
EMNLP'23 survey: a curation of awesome papers and resources on refreshing large language models (LLMs) without expensive retraining.
Examples of RAG using Llamaindex with local LLMs - Gemma, Mixtral 8x7B, Llama 2, Mistral 7B, Orca 2, Phi-2, Neural 7B
Generative AI Application Builder on AWS facilitates the development, rapid experimentation, and deployment of generative artificial intelligence (AI) applications without requiring deep experience in...
Data and code for FreshLLMs (https://arxiv.org/abs/2310.03214)
Chrome Extension to Summarize or Chat with Web Pages/Local Documents Using locally running LLMs. Keep all of your data and conversations private. 🔐
Lite & Super-fast re-ranking for your search & retrieval pipelines. Supports SoTA Listwise and Pairwise reranking based on LLMs and cross-encoders and more. Created by Prithivi Da, open for PRs & C...
Minimalist web-searching app with an AI assistant that runs directly from your browser. Uses Web-LLM, Ratchet-ML, Wllama and SearXNG. Demo: https://felladrin-minisearch.hf.space
[Preprint] Learning to Filter Context for Retrieval-Augmented Generaton