This repository showcases various advanced techniques for Retrieval-Augmented Generation (RAG) systems. Each technique has a detailed notebook tutorial.
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50+ tutorials and implementations for Generative AI Agent techniques, from basic conversational bots to complex multi-agent systems.
Welcome to the Llama Cookbook! This is your go to guide for Building with Llama: Getting started with Inference, Fine-Tuning, RAG. We also show you how to solve end to end problems using Llama model family and using them on various provider services
Sample code and notebooks for Generative AI on Google Cloud, with Gemini platform
- generative-ai
- llm
- vertex-ai
- langchain
TranslatedThis project is a tutorial on developing large model applications, aimed at beginner developers. Read it online at: https://datawhalechina.github.io/llm-universe/
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22 prompt engineering techniques with hands-on Jupyter Notebook tutorials, from fundamental concepts to advanced strategies for leveraging LLMs.
Overview and tutorial of the LangChain Library
Implement a reasoning LLM in PyTorch from scratch, step by step
A modular Agentic RAG built with LangGraph — learn Retrieval-Augmented Generation Agents in minutes.
- agentic-ai
- agentic-rag
- agents
- rag
Everything you need to know to build your own RAG application
- agentic-rag
- chatbot
- llm
- machine-learning
A collection of scientific methods, processes, algorithms, and systems to build stories & models.
- python
- machine-learning
- deep-learning
- pytorch
A complete course for learning Bitcoin programming and usage from the command
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📚 《Deep Agents 实战》—— LangChain 官方大使出品，基于 LangChain / LangGraph 生态，从零构建生产级 AI Agent 的完整指南
- agentic-ai
- ai-agents
- astro
- chinese
Repo for AI Agents The Definitive Guide
- ai-agents
- benchmarks
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- langchain
Comprehensive resources on Generative AI, including a detailed roadmap, projects, use cases, interview preparation, and coding preparation.
This repository contains various advanced techniques for Retrieval-Augmented Generation (RAG) systems.
- ai
- chromadb
- cookbooks
- faiss
动手学Ollama，CPU玩转大模型部署，在线阅读地址：https://datawhalechina.github.io/handy-ollama/
Build an email assistant with human-in-the-loop and memory
- agents
- memory