🤖 𝗟𝗲𝗮𝗿𝗻 for 𝗳𝗿𝗲𝗲 how to 𝗯𝘂𝗶𝗹𝗱 an end-to-end 𝗽𝗿𝗼𝗱𝘂𝗰𝘁𝗶𝗼𝗻-𝗿𝗲𝗮𝗱𝘆 𝗟𝗟𝗠 & 𝗥𝗔𝗚 𝘀𝘆𝘀𝘁𝗲𝗺 using 𝗟𝗟𝗠𝗢𝗽𝘀 best practices: ~ 𝘴𝘰𝘶𝘳𝘤𝘦 𝘤𝘰𝘥𝘦 + 12 𝘩𝘢𝘯𝘥𝘴-𝘰𝘯 𝘭𝘦𝘴𝘴𝘰𝘯𝘴

Represent, send, store and search multimodal data

Python client for Qdrant vector search engine

On-premises conversational RAG with configurable containers

An open-source intelligence (OSINT) analysis tool leveraging GPT-powered embeddings and vector search engines for efficient data processing

A completely private, locally-operated Ai Assistant/Chatbot/Sub-Agent Framework with realistic Long Term Memory and thought formation using Open Source LLMs. Qdrant is used for the Vector DB.

Context-Engine: MCP retrieval stack for AI coding assistants. Hybrid code search (dense + lexical + reranker), ReFRAG micro-chunking, local LLM prompt enhancement, and dual SSE/RMCP endpoints. One command deploys Qdrant-powered indexing for Cursor, Windsurf, Roo, Cline, Codex, and any MCP client.

Your fully proficient, AI-powered and local chatbot assistant🤖

FastAPI Backend for a Conversational Agent using Cohere, (Azure) OpenAI, Langchain & Langgraph and Qdrant as VectorDB

♾️ toolkit for air-gapped LLMs on consumer-grade hardware

Claude forgets everything. This fixes that. 🔗 www.npmjs.com/package/claude-self-reflect

An agentic AI application that allows you to chat with your papers and gather also information from papers on ArXiv and on PubMed

Build super simple end-to-end data & ETL pipelines for your vector databases and Generative AI applications

From data to vector database effortlessly

AutoMem is a graph-vector memory service that gives AI assistants durable, relational memory:

Generative AI concepts to hands on projects

Framework for benchmarking fully-managed vector databases

🐊 Snappy's unique approach unifies vision-language late interaction with structured OCR for region-level knowledge retrieval. Like the project? Drop a star! ⭐

DocMind AI is a powerful, open-source Streamlit application leveraging LlamaIndex, LangGraph, and local Large Language Models (LLMs) via Ollama, LMStudio, llama.cpp, or vLLM for advanced document analysis. Analyze, summarize, and extract insights from a wide array of file formats, securely and privately, all offline.

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