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RestAI is an AIaaS (AI as a Service) open-source platform. Built on top of LlamaIndex, Ollama and HF Pipelines. Supports any public LLM supported by LlamaIndex and any local LLM suported by Ollama. Precise embeddings usage and tuning.
This Python project demonstrates semantic search using MongoDB and two different LLM frameworks: LangChain and LlamaIndex. The goal is to load documents from MongoDB, generate embeddings for the text data, and perform semantic searches using both LangChain and LlamaIndex frameworks.
AI-Assistant-Builder is a flexible platform that enables users to create their own AI assistants tailored to any profession or field. By customizing some data and values, users can effortlessly build specialized AI assistants such as an AI Doctor or an AI Lawyer.
Welcome to the "LLM in Production" repository! This project aims to provide a comprehensive guide and resources for deploying and managing Large Language Models (LLMs) in production environments.
A RAG system is just the beginning of harnessing the power of LLM. The next step is creating an intelligent Agent. In Agentic RAG the Agent makes use of available tools, strategies and LLM to generate response in a specialized way. Unlike a simple RAG, an Agent can dynamically choose between tools, routing strategy, etc.
Simple agents are good for 1-to-1 retrieval system. For more complex task we need multi steps reasoning loop. In a reasoning loop the agent can break down a complex task into subtasks and solve them step by step while maintaining a conversational memory.