705 skills found · Page 1 of 24
langgenius / DifyBuild Agentic workflows, RAG pipelines, with rich AI model and tool support on one collaborative workspace. Deploy on cloud, VPC, or self-hosted, so teams move from prototype to production without rebuilding the stack.
pathwaycom / PathwayPython ETL framework for stream processing, real-time analytics, LLM pipelines, and RAG.
pathwaycom / Llm AppReady-to-run cloud templates for RAG, AI pipelines, and enterprise search with live data. 🐳Docker-friendly.⚡Always in sync with Sharepoint, Google Drive, S3, Kafka, PostgreSQL, real-time data APIs, and more.
deepset-ai / HaystackOpen-source AI orchestration framework for building context-engineered, production-ready LLM applications. Design modular pipelines and agent workflows with explicit control over retrieval, routing, memory, and generation. Built for scalable agents, RAG, multimodal applications, semantic search, and conversational systems.
memvid / MemvidMemory layer for AI Agents. Replace complex RAG pipelines with a serverless, single-file memory layer. Give your agents instant retrieval and long-term memory.
llmware-ai / LlmwareUnified framework for building enterprise RAG pipelines with small, specialized models
oramasearch / Orama🌌 A complete search engine and RAG pipeline in your browser, server or edge network with support for full-text, vector, and hybrid search in less than 2kb.
OpenBMB / UltraRAGA Low-Code MCP Framework for Building Complex and Innovative RAG Pipelines
feyninc / Chonkie🦛 CHONK docs with Chonkie ✨ — The lightweight ingestion library for fast, efficient and robust RAG pipelines
AnswerDotAI / RAGatouilleEasily use and train state of the art late-interaction retrieval methods (ColBERT) in any RAG pipeline. Designed for modularity and ease-of-use, backed by research.
GiovanniPasq / Agentic Rag For DummiesA modular Agentic RAG built with LangGraph — learn Retrieval-Augmented Generation Agents in minutes.
Ontos-AI / KnowhereKnowhere extracts, parses, and outputs structured chunks ready for AI Agents and RAG.
pguso / Rag From ScratchDemystify RAG by building it from scratch. Local LLMs, no black boxes - real understanding of embeddings, vector search, retrieval, and context-augmented generation.
postgresml / KorvusKorvus is a search SDK that unifies the entire RAG pipeline in a single database query. Built on top of Postgres with bindings for Python, JavaScript, Rust and C.
darrencxl0301 / StageRAGA blueprint for building production-ready RAG systems that minimize hallucination, featuring switchable 3-step (Speed) and 4-step (Precision) pipelines.
mrdbourke / Simple Local RagBuild a RAG (Retrieval Augmented Generation) pipeline from scratch and have it all run locally.
pchunduri6 / Rag DemystifiedAn LLM-powered advanced RAG pipeline built from scratch
llama-farm / LlamafarmDeploy any AI model, agent, database, RAG, and pipeline locally or remotely in minutes
christopherkarani / WaxSingle-file memory layer for AI agents, sub mili-second RAG on Apple Silicon. Metal Optimized On-Device. No Server. No API. One File. Pure Swift
NVIDIA-AI-Blueprints / RagThis NVIDIA RAG blueprint serves as a reference solution for a foundational Retrieval Augmented Generation (RAG) pipeline.
