🤖 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.

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

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

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

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

From data to vector database effortlessly

Framework for benchmarking fully-managed vector databases

Generative AI concepts to hands on projects

Automated Deep Research with LLMs, web search, paper parsing, and didactic summarization.

Agentic RAG to help you build a startup🚀

Find your files with natural language and ask questions.

A virtual agent for your virtual books📚

Explore Multiple Vector Databases and chat with documents on Multiple LLM models, private LLM models