All-in-one infrastructure for search, recommendations, RAG, and analytics offered via API
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Updated
Nov 3, 2024 - Rust
All-in-one infrastructure for search, recommendations, RAG, and analytics offered via API
🤖 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
A production-ready RAG (Retrieval Augmented Generation) system built with FastAPI, LangChain, LangServe, LangSmith, Hugging Face, and Qdrant for document processing and intelligent querying.
FastAPI Backend for a Conversational Agent using Cohere, (Azure) OpenAI, Langchain & Langgraph and Qdrant as VectorDB
Python client for Qdrant vector search engine
Comprehensive Vector Data Tooling. The universal interface for all vector database, datasets and RAG platforms. Easily export, import, backup, re-embed (using any model) or access your vector data from any vector databases or repository.
An app for people with short-term-memory 🧠
Insert data into a Qdrant vector database to train a chatbot on your own data. Designed to work with `librai-ui`, enabling custom data querying and contextual responses from the AI chatbot.
AI-powered virtual assistant for UTEC students. Leverages natural language processing with WhatsApp integration for seamless interaction.
A SvelteKit app featuring an AI chatbot trained on your data, using the OpenAI API and Qdrant vector database for contextual responses. Styled with Tailwind CSS, `librai-ui` pairs with `librai-server` to insert and query your data in Qdrant.
Ruby wrapper for the Qdrant vector search database API
SoniCMS: Cloud-friendly, high-performance headless CMS built on top of C++
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