LawGlance is an AI-powered legal assistant that aims to bridge the gap between people and legal access. It is a free, open-source initiative designed to provide quick and accurate legal support tailored to individual needs. The project covers various laws, with plans for international expansion in the future. LawGlance utilizes AI-powered Retriever-Augmented Generation (RAG) to deliver legal guidance accessible to both laypersons and professionals. The tool is developed with support from mentors and experts at Data Science Academy and Curvelogics.

LLMChat is an all-in-one AI chat interface that supports multiple language models, offers a plugin library for enhanced functionality, enables web search capabilities, allows customization of AI assistants, provides text-to-speech conversion, ensures secure local data storage, and facilitates data import/export. It also includes features like knowledge spaces, prompt library, personalization, and can be installed as a Progressive Web App (PWA). The tech stack includes Next.js, TypeScript, Pglite, LangChain, Zustand, React Query, Supabase, Tailwind CSS, Framer Motion, Shadcn, and Tiptap. The roadmap includes upcoming features like speech-to-text and knowledge spaces.

KitchenAI is an open-source toolkit designed to simplify AI development by serving as an AI backend and LLMOps solution. It aims to empower developers to focus on delivering results without being bogged down by AI infrastructure complexities. With features like simplifying AI integration, providing an AI backend, and empowering developers, KitchenAI streamlines the process of turning AI experiments into production-ready APIs. It offers built-in LLMOps features, is framework-agnostic and extensible, and enables faster time-to-production. KitchenAI is suitable for application developers, AI developers & data scientists, and platform & infra engineers, allowing them to seamlessly integrate AI into apps, deploy custom AI techniques, and optimize AI services with a modular framework. The toolkit eliminates the need to build APIs and infrastructure from scratch, making it easier to deploy AI code as production-ready APIs in minutes. KitchenAI also provides observability, tracing, and evaluation tools, and offers a Docker-first deployment approach for scalability and confidence.

Forge is a free and open-source digital collectible card game (CCG) engine written in Java. It is designed to be easy to use and extend, and it comes with a variety of features that make it a great choice for developers who want to create their own CCGs. Forge is used by a number of popular CCGs, including Ascension, Dominion, and Thunderstone.

The 'summarize' tool is designed to transcribe and summarize videos from various sources using AI models. It helps users efficiently summarize lengthy videos, take notes, and extract key insights by providing timestamps, original transcripts, and support for auto-generated captions. Users can utilize different AI models via Groq, OpenAI, or custom local models to generate grammatically correct video transcripts and extract wisdom from video content. The tool simplifies the process of summarizing video content, making it easier to remember and reference important information.

AgentNeo is a Python package that provides functionalities for project, trace, dataset, experiment management. It allows users to authenticate, create projects, trace agents and LangGraph graphs, manage datasets, and run experiments with metrics. The tool aims to streamline AI project management and analysis by offering a comprehensive set of features.

Lidar AI Solution is a highly optimized repository for self-driving 3D lidar, providing solutions for sparse convolution, BEVFusion, CenterPoint, OSD, and Conversion. It includes CUDA and TensorRT implementations for various tasks such as 3D sparse convolution, BEVFusion, CenterPoint, PointPillars, V2XFusion, cuOSD, cuPCL, and YUV to RGB conversion. The repository offers easy-to-use solutions, high accuracy, low memory usage, and quantization options for different tasks related to self-driving technology.

ComfyUI_Yvann-Nodes is a pack of custom nodes that enable audio reactivity within ComfyUI, allowing users to create AI-driven animations that sync with music. Users can generate audio reactive AI videos, control AI generation styles, content, and composition with any audio input. The tool is simple to use by dropping workflows in ComfyUI and specifying audio and visual inputs. It is flexible and works with existing ComfyUI AI tech and nodes like IPAdapter, AnimateDiff, and ControlNet. Users can pick workflows for Images → Video or Video → Video, download the corresponding .json file, drop it into ComfyUI, install missing custom nodes, set inputs, and generate audio-reactive animations.

This repository provides a comprehensive guide to understanding and applying artificial intelligence (AI) theory, including basic knowledge, machine learning, deep learning, and natural language processing (BERT). It features detailed explanations, annotated code, and datasets to help users grasp the concepts and implement them in practice. The repository is continuously updated to ensure the latest information and best practices are covered.

General Framework is a cross-platform library designed to help create apps with a unified codebase using Flutter. It offers features such as cross-platform support, standardized style code, a CLI for easier usage, API integration for bot development, customizable extensions for faster development, and user-friendly information. The library is intended to streamline the app, server, bot, and userbot creation process by providing a comprehensive set of tools and functionalities.

Jan is an open-source ChatGPT alternative that runs 100% offline on your computer. It supports universal architectures, including Nvidia GPUs, Apple M-series, Apple Intel, Linux Debian, and Windows x64. Jan is currently in development, so expect breaking changes and bugs. It is lightweight and embeddable, and can be used on its own within your own projects.

Transformer Lab is an app that allows users to experiment with Large Language Models by providing features such as one-click download of popular models, finetuning across different hardware, RLHF and Preference Optimization, working with LLMs across different operating systems, chatting with models, using different inference engines, evaluating models, building datasets for training, calculating embeddings, providing a full REST API, running in the cloud, converting models across platforms, supporting plugins, embedded Monaco code editor, prompt editing, inference logs, all through a simple cross-platform GUI.

The Apache Airflow Python Client provides a range of REST API endpoints for managing Airflow metadata objects. It supports CRUD operations for resources, with endpoints accepting and returning JSON. Users can create, read, update, and delete resources. The API design follows conventions with consistent naming and field formats. Update mask is available for patch endpoints to specify fields for update. API versioning is not synchronized with Airflow releases, and changes go through a deprecation phase. The tool supports various authentication methods and error responses follow RFC 7807 format.

ComfyUI Portrait Master 3.1 is a tool designed to assist AI image creators in generating prompts for human portraits. The tool offers various modules for customizing character details such as base character, skin details, style & pose, and makeup. Users can control parameters like shot type, gender, age, ethnicity mix, body type, facial features, hair details, skin imperfections, and more to create unique portrait prompts. The tool aims to enhance photorealism and provide a user-friendly interface for generating portrait prompts efficiently.

Instill Core is an open-source orchestrator comprising a collection of source-available projects designed to streamline every aspect of building versatile AI features with unstructured data. It includes Instill VDP (Versatile Data Pipeline) for unstructured data, AI, and pipeline orchestration, Instill Model for scalable MLOps and LLMOps for open-source or custom AI models, and Instill Artifact for unified unstructured data management. Instill Core can be used for tasks such as building, testing, and sharing pipelines, importing, serving, fine-tuning, and monitoring ML models, and transforming documents, images, audio, and video into a unified AI-ready format.

Agent Hub is a platform for AI Agent solutions, containing three different projects aimed at transforming enterprise workflows, enhancing personalized language learning experiences, and enriching multimodal interactions. The projects include GitHub Sentinel for project management and automatic updates, LanguageMentor for personalized language learning support, and ChatPPT for multimodal AI-driven insights and PowerPoint automation in enterprise settings. The future vision of agent-hub is to serve as a launchpad for more AI Agents catering to different industries and pushing the boundaries of AI technology. Users are encouraged to explore, clone the repository, and contribute to the development of transformative AI agents.

LawGlance is an AI-powered legal assistant that aims to bridge the gap between people and legal access. It is a free, open-source initiative designed to provide quick and accurate legal support tailored to individual needs. The project covers various laws, with plans for international expansion in the future. LawGlance utilizes AI-powered Retriever-Augmented Generation (RAG) to deliver legal guidance accessible to both laypersons and professionals. The tool is developed with support from mentors and experts at Data Science Academy and Curvelogics.

LawGlance is an AI-powered legal assistant that aims to bridge the gap between people and legal access. It is a free, open-source initiative designed to provide quick and accurate legal support tailored to individual needs. The project covers various laws, with plans for international expansion in the future. LawGlance utilizes AI-powered Retriever-Augmented Generation (RAG) to deliver legal guidance accessible to both laypersons and professionals. The tool is developed with support from mentors and experts at Data Science Academy and Curvelogics.

Lawyer LLaMA is a large language model that has been specifically trained on legal data, including Chinese laws, regulations, and case documents. It has been fine-tuned on a large dataset of legal questions and answers, enabling it to understand and respond to legal inquiries in a comprehensive and informative manner. Lawyer LLaMA is designed to assist legal professionals and individuals with a variety of law-related tasks, including: * **Legal research:** Quickly and efficiently search through vast amounts of legal information to find relevant laws, regulations, and case precedents. * **Legal analysis:** Analyze legal issues, identify potential legal risks, and provide insights on how to proceed. * **Document drafting:** Draft legal documents, such as contracts, pleadings, and legal opinions, with accuracy and precision. * **Legal advice:** Provide general legal advice and guidance on a wide range of legal matters, helping users understand their rights and options. Lawyer LLaMA is a powerful tool that can significantly enhance the efficiency and effectiveness of legal research, analysis, and decision-making. It is an invaluable resource for lawyers, paralegals, law students, and anyone else who needs to navigate the complexities of the legal system.

ChatLaw is an open-source legal large language model tailored for Chinese legal scenarios. It aims to combine LLM and knowledge bases to provide solutions for legal scenarios. The models include ChatLaw-13B and ChatLaw-33B, trained on various legal texts to construct dialogue data. The project focuses on improving logical reasoning abilities and plans to train models with parameters exceeding 30B for better performance. The dataset consists of forum posts, news, legal texts, judicial interpretations, legal consultations, exam questions, and court judgments, cleaned and enhanced to create dialogue data. The tool is designed to assist in legal tasks requiring complex logical reasoning, with a focus on accuracy and reliability.

DISC-LawLLM is a legal domain large model that aims to provide professional, intelligent, and comprehensive **legal services** to users. It is developed and open-sourced by the Data Intelligence and Social Computing Lab (Fudan-DISC) at Fudan University.

This repository provides templates for software and digital work licenses that restrict usage in AI training datasets or AI technologies. It includes various license styles such as Apache, BSD, MIT, UPL, ISC, CC0, and MPL-2.0.

This repository is dedicated to summarizing papers related to large language models with the field of law. It includes applications of large language models in legal tasks, legal agents, legal problems of large language models, data resources for large language models in law, law LLMs, and evaluation of large language models in the legal domain.

AutoPatent is a multi-agent framework designed for automatic patent generation. It challenges large language models to generate full-length patents based on initial drafts. The framework leverages planner, writer, and examiner agents along with PGTree and RRAG to craft lengthy, intricate, and high-quality patent documents. It introduces a new metric, IRR (Inverse Repetition Rate), to measure sentence repetition within patents. The tool aims to streamline the patent generation process by automating the creation of detailed and specialized patent documents.

OpenContracts is an Apache-2 licensed enterprise document analytics tool that supports multiple formats, including PDF and txt-based formats. It features multiple document ingestion pipelines with a pluggable architecture for easy format and ingestion engine support. Users can create custom document analytics tools with beautiful result displays, support mass document data extraction with a LlamaIndex wrapper, and manage document collections, layout parsing, automatic vector embeddings, and human annotation. The tool also offers pluggable parsing pipelines, human annotation interface, LlamaIndex integration, data extraction capabilities, and custom data extract pipelines for bulk document querying.