AirSwap Protocols is a repository containing smart contracts for developers and traders on the AirSwap peer-to-peer trading network. It includes various packages for functionalities like server registry, atomic token swap, staking, rewards pool, batch token and order calls, libraries, and utils. The repository follows a branching and release process for contracts and tools, with steps for regular development process and individual package features or patches. Users can deploy and verify contracts using specific commands with network flags.

Agentic is a standard AI functions/tools library optimized for TypeScript and LLM-based apps, compatible with major AI SDKs. It offers a set of thoroughly tested AI functions that can be used with favorite AI SDKs without writing glue code. The library includes various clients for services like Bing web search, calculator, Clearbit data resolution, Dexa podcast questions, and more. It also provides compound tools like SearchAndCrawl and supports multiple AI SDKs such as OpenAI, Vercel AI SDK, LangChain, LlamaIndex, Firebase Genkit, and Dexa Dexter. The goal is to create minimal clients with strongly-typed TypeScript DX, composable AIFunctions via AIFunctionSet, and compatibility with major TS AI SDKs.

FalkorDB is the first queryable Property Graph database to use sparse matrices to represent the adjacency matrix in graphs and linear algebra to query the graph. Primary features: * Adopting the Property Graph Model * Nodes (vertices) and Relationships (edges) that may have attributes * Nodes can have multiple labels * Relationships have a relationship type * Graphs represented as sparse adjacency matrices * OpenCypher with proprietary extensions as a query language * Queries are translated into linear algebra expressions

KwaiAgents is a series of Agent-related works open-sourced by the [KwaiKEG](https://github.com/KwaiKEG) from [Kuaishou Technology](https://www.kuaishou.com/en). The open-sourced content includes: 1. **KAgentSys-Lite**: a lite version of the KAgentSys in the paper. While retaining some of the original system's functionality, KAgentSys-Lite has certain differences and limitations when compared to its full-featured counterpart, such as: (1) a more limited set of tools; (2) a lack of memory mechanisms; (3) slightly reduced performance capabilities; and (4) a different codebase, as it evolves from open-source projects like BabyAGI and Auto-GPT. Despite these modifications, KAgentSys-Lite still delivers comparable performance among numerous open-source Agent systems available. 2. **KAgentLMs**: a series of large language models with agent capabilities such as planning, reflection, and tool-use, acquired through the Meta-agent tuning proposed in the paper. 3. **KAgentInstruct**: over 200k Agent-related instructions finetuning data (partially human-edited) proposed in the paper. 4. **KAgentBench**: over 3,000 human-edited, automated evaluation data for testing Agent capabilities, with evaluation dimensions including planning, tool-use, reflection, concluding, and profiling.

LitGPT is a command-line tool designed to easily finetune, pretrain, evaluate, and deploy 20+ LLMs **on your own data**. It features highly-optimized training recipes for the world's most powerful open-source large-language-models (LLMs).

Chat Your Doc is an experimental project exploring various applications based on LLM technology. It goes beyond being just a chatbot project, focusing on researching LLM applications using tools like LangChain and LlamaIndex. The project delves into UX, computer vision, and offers a range of examples in the 'Lab Apps' section. It includes links to different apps, descriptions, launch commands, and demos, aiming to showcase the versatility and potential of LLM applications.

GPTQModel is an easy-to-use LLM quantization and inference toolkit based on the GPTQ algorithm. It provides support for weight-only quantization and offers features such as dynamic per layer/module flexible quantization, sharding support, and auto-heal quantization errors. The toolkit aims to ensure inference compatibility with HF Transformers, vLLM, and SGLang. It offers various model supports, faster quant inference, better quality quants, and security features like hash check of model weights. GPTQModel also focuses on faster quantization, improved quant quality as measured by PPL, and backports bug fixes from AutoGPTQ.

AiOS is a tool for human pose and shape estimation, performing human localization and SMPL-X estimation in a progressive manner. It consists of body localization, body refinement, and whole-body refinement stages. Users can download datasets for evaluation, SMPL-X body models, and AiOS checkpoint. Installation involves creating a conda virtual environment, installing PyTorch, torchvision, Pytorch3D, MMCV, and other dependencies. Inference requires placing the video for inference and pretrained models in specific directories. Test results are provided for NMVE, NMJE, MVE, and MPJPE on datasets like BEDLAM and AGORA. Users can run scripts for AGORA validation, AGORA test leaderboard, and BEDLAM leaderboard. The tool acknowledges codes from MMHuman3D, ED-Pose, and SMPLer-X.

This repository contains code for the paper 'Robust CLIP: Unsupervised Adversarial Fine-Tuning of Vision Embeddings for Robust Large Vision-Language Models'. It focuses on fine-tuning CLIP in an unsupervised manner to enhance its robustness against visual adversarial attacks. By replacing the vision encoder of large vision-language models with the fine-tuned CLIP models, it achieves state-of-the-art adversarial robustness on various vision-language tasks. The repository provides adversarially fine-tuned ViT-L/14 CLIP models and offers insights into zero-shot classification settings and clean accuracy improvements.

Spice is a portable runtime written in Rust that offers developers a unified SQL interface to materialize, accelerate, and query data from any database, data warehouse, or data lake. It connects, fuses, and delivers data to applications, machine-learning models, and AI-backends, functioning as an application-specific, tier-optimized Database CDN. Built with industry-leading technologies such as Apache DataFusion, Apache Arrow, Apache Arrow Flight, SQLite, and DuckDB. Spice makes it fast and easy to query data from one or more sources using SQL, co-locating a managed dataset with applications or machine learning models, and accelerating it with Arrow in-memory, SQLite/DuckDB, or attached PostgreSQL for fast, high-concurrency, low-latency queries.

LangChain.dart is a Dart port of the popular LangChain Python framework created by Harrison Chase. LangChain provides a set of ready-to-use components for working with language models and a standard interface for chaining them together to formulate more advanced use cases (e.g. chatbots, Q&A with RAG, agents, summarization, extraction, etc.). The components can be grouped into a few core modules: * **Model I/O:** LangChain offers a unified API for interacting with various LLM providers (e.g. OpenAI, Google, Mistral, Ollama, etc.), allowing developers to switch between them with ease. Additionally, it provides tools for managing model inputs (prompt templates and example selectors) and parsing the resulting model outputs (output parsers). * **Retrieval:** assists in loading user data (via document loaders), transforming it (with text splitters), extracting its meaning (using embedding models), storing (in vector stores) and retrieving it (through retrievers) so that it can be used to ground the model's responses (i.e. Retrieval-Augmented Generation or RAG). * **Agents:** "bots" that leverage LLMs to make informed decisions about which available tools (such as web search, calculators, database lookup, etc.) to use to accomplish the designated task. The different components can be composed together using the LangChain Expression Language (LCEL).

Ollama GUI is a web interface for ollama.ai, a tool that enables running Large Language Models (LLMs) on your local machine. It provides a user-friendly platform for chatting with LLMs and accessing various models for text generation. Users can easily interact with different models, manage chat history, and explore available models through the web interface. The tool is built with Vue.js, Vite, and Tailwind CSS, offering a modern and responsive design for seamless user experience.

MaskLLM is a learnable pruning method that establishes Semi-structured Sparsity in Large Language Models (LLMs) to reduce computational overhead during inference. It is scalable and benefits from larger training datasets. The tool provides examples for running MaskLLM with Megatron-LM, preparing LLaMA checkpoints, pre-tokenizing C4 data for Megatron, generating prior masks, training MaskLLM, and evaluating the model. It also includes instructions for exporting sparse models to Huggingface.

ChatGLM.cpp is a C++ implementation of ChatGLM-6B, ChatGLM2-6B, ChatGLM3-6B and more LLMs for real-time chatting on your MacBook. It is based on ggml, working in the same way as llama.cpp. ChatGLM.cpp features accelerated memory-efficient CPU inference with int4/int8 quantization, optimized KV cache and parallel computing. It also supports P-Tuning v2 and LoRA finetuned models, streaming generation with typewriter effect, Python binding, web demo, api servers and more possibilities.

PDFMathTranslate is a tool designed for translating scientific papers and conducting bilingual comparisons. It preserves formulas, charts, table of contents, and annotations. The tool supports multiple languages and diverse translation services. It provides a command-line tool, interactive user interface, and Docker deployment. Users can try the application through online demos. The tool offers various installation methods including command-line, portable, graphic user interface, and Docker. Advanced options allow users to customize translation settings. Additionally, the tool supports secondary development through APIs for Python and HTTP. Future plans include parsing layout with DocLayNet based models, fixing page rotation and format issues, supporting non-PDF/A files, and integrating plugins for Zotero and Obsidian.

MooER (摩耳) is an LLM-based speech recognition and translation model developed by Moore Threads. It allows users to transcribe speech into text (ASR) and translate speech into other languages (AST) in an end-to-end manner. The model was trained using 5K hours of data and is now also available with an 80K hours version. MooER is the first LLM-based speech model trained and inferred using domestic GPUs. The repository includes pretrained models, inference code, and a Gradio demo for a better user experience.

AirSwap Protocols is a repository containing smart contracts for developers and traders on the AirSwap peer-to-peer trading network. It includes various packages for functionalities like server registry, atomic token swap, staking, rewards pool, batch token and order calls, libraries, and utils. The repository follows a branching and release process for contracts and tools, with steps for regular development process and individual package features or patches. Users can deploy and verify contracts using specific commands with network flags.

Airchains is a tool for setting up a local EVM network for testing and development purposes. It provides step-by-step instructions for installing and configuring the necessary components. The tool helps users create their own local EVM network, manage keys, deploy contracts, and interact with the network using RPC. It also guides users on setting up a station for tracking and managing transactions. Airchains is designed to facilitate testing and development activities related to blockchain applications built on the EVM platform.

Awesome Algorand is a curated list of resources related to the Algorand Blockchain, including official resources, wallets, blockchain explorers, portfolio trackers, learning resources, development tools, DeFi platforms, nodes & consensus participation, subscription management, security auditing services, blockchain bridges, oracles, name services, community resources, Algorand Request for Comments, metrics and analytics services, decentralized voting tools, and NFT marketplaces. The repository provides a comprehensive collection of tools, tutorials, protocols, and platforms for developers, users, and enthusiasts interested in the Algorand ecosystem.

GOAT (Great Onchain Agent Toolkit) is an open-source framework designed to simplify the process of making AI agents perform onchain actions by providing a provider-agnostic solution that abstracts away the complexities of interacting with blockchain tools such as wallets, token trading, and smart contracts. It offers a catalog of ready-made blockchain actions for agent developers and allows dApp/smart contract developers to develop plugins for easy access by agents. With compatibility across popular agent frameworks, support for multiple blockchains and wallet providers, and customizable onchain functionalities, GOAT aims to streamline the integration of blockchain capabilities into AI agents.

Solana Agent Kit is an open-source toolkit designed for connecting AI agents to Solana protocols. It enables agents, regardless of the model used, to autonomously perform various Solana actions such as trading tokens, launching new tokens, lending assets, sending compressed airdrops, executing blinks, and more. The toolkit integrates core blockchain features like token operations, NFT management via Metaplex, DeFi integration, Solana blinks, AI integration features with LangChain, autonomous modes, and AI tools. It provides ready-to-use tools for blockchain operations, supports autonomous agent actions, and offers features like memory management, real-time feedback, and error handling. Solana Agent Kit facilitates tasks such as deploying tokens, creating NFT collections, swapping tokens, lending tokens, staking SOL, and sending SPL token airdrops via ZK compression. It also includes functionalities for fetching price data from Pyth and relies on key Solana and Metaplex libraries for its operations.

AirSwap Protocols is a repository containing smart contracts for developers and traders on the AirSwap peer-to-peer trading network. It includes various packages for functionalities like server registry, atomic token swap, staking, rewards pool, batch token and order calls, libraries, and utils. The repository follows a branching and release process for contracts and tools, with steps for regular development process and individual package features or patches. Users can deploy and verify contracts using specific commands with network flags.

This repository contains Airflow DAGs for extracting, transforming, and loading (ETL) data from the Ethereum blockchain into BigQuery. The DAGs use the Google Cloud Platform (GCP) services, including BigQuery, Cloud Storage, and Cloud Composer, to automate the ETL process. The repository also includes scripts for setting up the GCP environment and running the DAGs locally.

Airnode is a fully-serverless oracle node that is designed specifically for API providers to operate their own oracles.

The 𝓜𝓔𝓥-𝓑𝓞𝓣 is a revolutionary tool that empowers users to maximize their ETH earnings through advanced slippage techniques within the Ethereum ecosystem. Its user-centric design, optimized earning mechanism, and comprehensive security measures make it an indispensable tool for traders seeking to enhance their crypto trading strategies. With its current free access, there's no better time to explore the 𝓜𝓔𝓥-𝓑𝓞𝓣's capabilities and witness the transformative impact it can have on your crypto trading journey.

CortexTheseus is a full node implementation of the Cortex blockchain, written in C++. It provides a complete set of features for interacting with the Cortex network, including the ability to create and manage accounts, send and receive transactions, and participate in consensus. CortexTheseus is designed to be scalable, secure, and easy to use, making it an ideal choice for developers building applications on the Cortex blockchain.

This tool is a bot that monitors the performance of MEV transactions on the Ethereum blockchain. It provides real-time data on MEV profitability, transaction volume, and network congestion. The bot can be used to identify profitable MEV opportunities and to track the performance of MEV strategies.

Airdrop-checker is a tool that helps you to check if you are eligible for any airdrops. It supports multiple airdrops, including Altlayer, Rabby points, Zetachain, Frame, Anoma, Dymension, and MEME. To use the tool, you need to install it using npm and then fill the addresses files in the addresses folder with your wallet addresses. Once you have done this, you can run the tool using npm start.

Cyber is a superintelligence protocol that aims to create a decentralized and censorship-resistant internet. It uses a novel consensus mechanism called CometBFT and a knowledge graph to store and process information. Cyber is designed to be scalable, secure, and efficient, and it has the potential to revolutionize the way we interact with the internet.