RAG_Techniques

RAG_Techniques

TLDR: This repository is a comprehensive collection of advanced Retrieval-Augmented Generation (RAG) techniques. It includes various methods for enhancing RAG systems such as query enhancement, context enrichment, advanced retrieval methods, iterative and adaptive techniques, evaluation, explainability, and advanced architectures.

2024-07-13 Github

cline

24,900
@cline

cline

TLDR: Cline is an AI assistant for the CLI and editor. It can handle complex software development tasks, use various APIs and models, run commands in the terminal, create and edit files, use the browser, and add custom tools through the Model Context Protocol.

TypeScript
2024-07-06 Github

aisuite

aisuite

TLDR: A Python package called aisuite provides a simple, unified interface to multiple Generative AI providers. It allows developers to use multiple LLM through a standardized interface similar to OpenAI's, enabling easy interaction and comparison of results. Currently supports various providers and offers installation options. Comes with an MIT license and welcomes contributions.

Python
2024-06-30 Github

RAG

RAG

TLDR: An implementation of the paper 'Searching for Best Practices in Retrieval-Augmented Generation'. Provides installation instructions and a way to run evaluations. If used, requires citing the associated paper.

Python
2024-06-29 Github

Building-llama3-from-scratch

Building-llama3-from-scratch

TLDR: This repository contains code to build the LLaMA 3 language model from scratch using Python. It explains the components of LLaMA 3 such as pre-normalization using RMSNorm, SwiGLU activation function, Rotary Embeddings (RoPE), and Byte Pair Encoding (BPE) Algorithm. The code shows how to tokenize input data, create embeddings for each token, implement attention heads, self-attention, multi-head attention, SwiGLU activation function, and generate the output.

2024-05-27 Github

multiagent-systems-with-autogen

multiagent-systems-with-autogen

TLDR: This repository contains code examples for building multi-agent applications powered by generative AI models based on the AutoGen framework. It is the official code repository for the book 'Multi-Agent Systems with AutoGen' and provides instructions for setting up Jupyter Notebooks and is organized into chapters with code for various concepts discussed in the book.

2024-05-12 Github

oumi

oumi

TLDR: Everything you need to build state-of-the-art foundation models, end-to-end.

2024-05-07 Github

awesome-llm-apps

awesome-llm-apps

TLDR: A curated collection of LLM apps built with RAG and AI agents. Features apps using models from various sources and includes projects in different domains. Also provides instructions for getting started and welcomes contributions.

llms python rag Python
2024-04-29 Github

firecrawl

firecrawl

TLDR: Firecrawl is an API service that crawls URLs and converts them into clean markdown or structured data. It offers advanced scraping, crawling, and data extraction capabilities with features like LLM-ready formats, customizability, and more. It also has SDKs for various languages and integrations with multiple frameworks.

2024-04-15 Github

RD-Agent

RD-Agent

TLDR: Research and development (R&D) is crucial for the enhancement of industrial productivity, especially in the AI era, where the core aspects of R&D are mainly focused on data and models. We are committed to automating these high-value generic R&D processes through our open source R&D automation tool RD-Agent, which lets AI drive data-driven AI.

Python
2024-04-03 Github