anythingllm-docs

anythingllm-docs is a documentation repository for the AnythingLLM project. It contains detailed guides, setup instructions, and information on features and legal aspects of the project. The repository structure is organized into public, pages, components, and configuration files. Users can contribute by creating issues and pull requests following specific guidelines. The project is licensed under the MIT License and has been migrated to NextJS with the help of @ShadowArcanist.

This repository contains the Python source code for FINMEM, a Performance-Enhanced Large Language Model Trading Agent with Layered Memory and Character Design. It introduces FinMem, a novel LLM-based agent framework devised for financial decision-making, encompassing three core modules: Profiling, Memory with layered processing, and Decision-making. FinMem's memory module aligns closely with the cognitive structure of human traders, offering robust interpretability and real-time tuning. The framework enables the agent to self-evolve its professional knowledge, react agilely to new investment cues, and continuously refine trading decisions in the volatile financial environment. It presents a cutting-edge LLM agent framework for automated trading, boosting cumulative investment returns.

AvaTaR is a novel and automatic framework that optimizes an LLM agent to effectively use provided tools and improve performance on a given task/domain. It designs a comparator module to provide insightful prompts to the LLM agent via reasoning between positive and negative examples from training data.

Ebook-MCP is a powerful Model Context Protocol (MCP) server designed for processing electronic books. It provides standardized APIs for seamless integration between LLM applications and e-book processing capabilities. The tool supports EPUB and PDF formats, enabling users to manage their digital library, have interactive reading experiences, support active learning, and easily navigate content through natural language queries. By bridging traditional e-books with AI capabilities, Ebook-MCP enhances the value users can extract from their digital reading materials.

VSP-LLM (Visual Speech Processing incorporated with LLMs) is a novel framework that maximizes context modeling ability by leveraging the power of LLMs. It performs multi-tasks of visual speech recognition and translation, where given instructions control the task type. The input video is mapped to the input latent space of a LLM using a self-supervised visual speech model. To address redundant information in input frames, a deduplication method is employed using visual speech units. VSP-LLM utilizes Low Rank Adaptors (LoRA) for computationally efficient training.

Chai Builder is an Open Source Low Code React + Tailwind CSS Visual Builder that enables users to create web pages & email templates visually by dragging and dropping elements onto the canvas. It is a simple React component that renders a full-fledged visual builder into any React application. Chai Builder aims to simplify the process of building web pages and email templates by providing a visual interface for developers and designers to work collaboratively.

ShortcutsBench is a project focused on collecting and analyzing workflows created in the Shortcuts app, providing a dataset of shortcut metadata, source files, and API information. It aims to study the integration of large language models with Apple devices, particularly focusing on the role of shortcuts in enhancing user experience. The project offers insights for Shortcuts users, enthusiasts, and researchers to explore, customize workflows, and study automated workflows, low-code programming, and API-based agents.

Aixt is a programming framework for microcontrollers using a modern language syntax based on V, with components including the Aixt programming language, Aixt to C Transpiler, and Aixt API. It is designed to be modular, allowing easy incorporation of new devices and boards through a TOML configuration file. The Aixt to C Transpiler translates Aixt source code to C for specific microcontroller compilers. The Aixt language implements a subset of V with differences in variables, strings, arrays, default integers size, structs, functions, and preprocessor commands. The Aixt API provides functions for digital I/O, analog inputs, PWM outputs, and serial ports.

LeRobot is a state-of-the-art AI library for real-world robotics in PyTorch. It aims to provide models, datasets, and tools to lower the barrier to entry to robotics, focusing on imitation learning and reinforcement learning. LeRobot offers pretrained models, datasets with human-collected demonstrations, and simulation environments. It plans to support real-world robotics on affordable and capable robots. The library hosts pretrained models and datasets on the Hugging Face community page.

PDEBench provides a diverse and comprehensive set of benchmarks for scientific machine learning, including challenging and realistic physical problems. The repository consists of code for generating datasets, uploading and downloading datasets, training and evaluating machine learning models as baselines. It features a wide range of PDEs, realistic and difficult problems, ready-to-use datasets with various conditions and parameters. PDEBench aims for extensibility and invites participation from the SciML community to improve and extend the benchmark.

Lector is a text analysis tool that helps users extract insights from unstructured text data. It provides functionalities such as sentiment analysis, keyword extraction, entity recognition, and text summarization. With Lector, users can easily analyze large volumes of text data to uncover patterns, trends, and valuable information. The tool is designed to be user-friendly and efficient, making it suitable for both beginners and experienced users in the field of natural language processing and text mining.

A composable, headless PDF viewer toolkit for React applications, powered by PDF.js. Build feature-rich PDF viewing experiences with full control over the UI and functionality. It is responsive and mobile-friendly, fully customizable UI components, supports text selection and search functionality, page thumbnails and outline navigation, dark mode, pan and zoom controls, form filling support, internal and external link handling. Contributions are welcome in areas like performance optimizations, accessibility improvements, mobile/touch interactions, documentation, and examples. Inspired by open-source projects like react-pdf-headless and pdfreader. Licensed under MIT by Unriddle AI.

Magika is a novel AI-powered file type detection tool that relies on deep learning to provide accurate detection. It employs a custom, highly optimized model to enable precise file identification within milliseconds. Trained on a dataset of ~100M samples across 200+ content types, achieving an average ~99% accuracy. Used at scale by Google to improve user safety by routing files to security scanners. Available as a command line tool in Rust, Python API, and bindings for Rust, JavaScript/TypeScript, and GoLang.

Trace is a new AutoDiff-like tool for training AI systems end-to-end with general feedback. It generalizes the back-propagation algorithm by capturing and propagating an AI system's execution trace. Implemented as a PyTorch-like Python library, users can write Python code directly and use Trace primitives to optimize certain parts, similar to training neural networks.

Langgraph4j is a Java library for language processing tasks such as text classification, sentiment analysis, and named entity recognition. It provides a set of tools and algorithms for analyzing text data and extracting useful information. The library is designed to be efficient and easy to use, making it suitable for both research and production applications.

OneKE is a flexible dockerized system for schema-guided knowledge extraction, capable of extracting information from the web and raw PDF books across multiple domains like science and news. It employs a collaborative multi-agent approach and includes a user-customizable knowledge base to enable tailored extraction. OneKE offers various IE tasks support, data sources support, LLMs support, extraction method support, and knowledge base configuration. Users can start with examples using YAML, Python, or Web UI, and perform tasks like Named Entity Recognition, Relation Extraction, Event Extraction, Triple Extraction, and Open Domain IE. The tool supports different source formats like Plain Text, HTML, PDF, Word, TXT, and JSON files. Users can choose from various extraction models like OpenAI, DeepSeek, LLaMA, Qwen, ChatGLM, MiniCPM, and OneKE for information extraction tasks. Extraction methods include Schema Agent, Extraction Agent, and Reflection Agent. The tool also provides support for schema repository and case repository management, along with solutions for network issues. Contributors to the project include Ningyu Zhang, Haofen Wang, Yujie Luo, Xiangyuan Ru, Kangwei Liu, Lin Yuan, Mengshu Sun, Lei Liang, Zhiqiang Zhang, Jun Zhou, Lanning Wei, Da Zheng, and Huajun Chen.

The Ollama Conversation integration adds a conversation agent powered by Ollama in Home Assistant. This agent can be used in automations to query information provided by Home Assistant about your house, including areas, devices, and their states. Users can install the integration via HACS and configure settings such as API timeout, model selection, context size, maximum tokens, and other parameters to fine-tune the responses generated by the AI language model. Contributions to the project are welcome, and discussions can be held on the Home Assistant Community platform.

rclip is a command-line photo search tool powered by the OpenAI's CLIP neural network. It allows users to search for images using text queries, similar image search, and combining multiple queries. The tool extracts features from photos to enable searching and indexing, with options for previewing results in supported terminals or custom viewers. Users can install rclip on Linux, macOS, and Windows using different installation methods. The repository follows the Conventional Commits standard and welcomes contributions from the community.

Honcho is a platform for creating personalized AI agents and LLM powered applications for end users. The repository is a monorepo containing the server/API for managing database interactions and storing application state, along with a Python SDK. It utilizes FastAPI for user context management and Poetry for dependency management. The API can be run using Docker or manually by setting environment variables. The client SDK can be installed using pip or Poetry. The project is open source and welcomes contributions, following a fork and PR workflow. Honcho is licensed under the AGPL-3.0 License.

OpenSumi is a framework designed to help users quickly build AI Native IDE products. It provides a set of tools and templates for creating Cloud IDEs, Desktop IDEs based on Electron, CodeBlitz web IDE Framework, Lite Web IDE on the Browser, and Mini-App liked IDE. The framework also offers documentation for users to refer to and a detailed guide on contributing to the project. OpenSumi encourages contributions from the community and provides a platform for users to report bugs, contribute code, or improve documentation. The project is licensed under the MIT license and contains third-party code under other open source licenses.

The Ultralytics YOLO iOS App GitHub repository offers an advanced object detection tool leveraging YOLOv8 models for iOS devices. Users can transform their devices into intelligent detection tools to explore the world in a new and exciting way. The app provides real-time detection capabilities with multiple AI models to choose from, ranging from 'nano' to 'x-large'. Contributors are welcome to participate in this open-source project, and licensing options include AGPL-3.0 for open-source use and an Enterprise License for commercial integration. Users can easily set up the app by following the provided steps, including cloning the repository, adding YOLOv8 models, and running the app on their iOS devices.

PyAirbyte brings the power of Airbyte to every Python developer by providing a set of utilities to use Airbyte connectors in Python. It enables users to easily manage secrets, work with various connectors like GitHub, Shopify, and Postgres, and contribute to the project. PyAirbyte is not a replacement for Airbyte but complements it, supporting data orchestration frameworks like Airflow and Snowpark. Users can develop ETL pipelines and import connectors from local directories. The tool simplifies data integration tasks for Python developers.

MD-Agent is a LLM-agent based toolset for Molecular Dynamics. It uses Langchain and a collection of tools to set up and execute molecular dynamics simulations, particularly in OpenMM. The tool assists in environment setup, installation, and usage by providing detailed steps. It also requires API keys for certain functionalities, such as OpenAI and paper-qa for literature searches. Contributions to the project are welcome, with a detailed Contributor's Guide available for interested individuals.

FlowGen is a tool built for AutoGen, a great agent framework from Microsoft and a lot of contributors. It provides intuitive visual tools that streamline the construction and oversight of complex agent-based workflows, simplifying the process for creators and developers. Users can create Autoflows, chat with agents, and share flow templates. The tool is fully dockerized and supports deployment on Railway.app. Contributions to the project are welcome, and the platform uses semantic-release for versioning and releases.

DocsGPT is an open-source documentation assistant powered by GPT models. It simplifies the process of searching for information in project documentation by allowing developers to ask questions and receive accurate answers. With DocsGPT, users can say goodbye to manual searches and quickly find the information they need. The tool aims to revolutionize project documentation experiences and offers features like live previews, Discord community, guides, and contribution opportunities. It consists of a Flask app, Chrome extension, similarity search index creation script, and a frontend built with Vite and React. Users can quickly get started with DocsGPT by following the provided setup instructions and can contribute to its development by following the guidelines in the CONTRIBUTING.md file. The project follows a Code of Conduct to ensure a harassment-free community environment for all participants. DocsGPT is licensed under MIT and is built with LangChain.

This repository contains the source code for the Apache Airflow website, including directories for archived documentation versions, landing pages, license templates, and the Sphinx theme. To work on the site locally, users need to install coreutils, Node.js, NPM, and HUGO, and run specific scripts provided in the repository. Contributors can refer to the contributor's guide for detailed instructions on how to contribute to the website.

Lumentis is a tool that allows users to generate beautiful and comprehensive documentation from meeting transcripts and large documents with a single command. It reads transcripts, asks questions to understand themes and audience, generates an outline, and creates detailed pages with visual variety and styles. Users can switch models for different tasks, control the process, and deploy the generated docs to Vercel. The tool is designed to be open, clean, fast, and easy to use, with upcoming features including folders, PDFs, auto-transcription, website scraping, scientific papers handling, summarization, and continuous updates.

Dify Docs is a repository that houses the documentation website code and Markdown source files for docs.dify.ai. It contains assets, content, and data folders that are licensed under a CC-BY license.

Code2Prompt is a powerful command-line tool that generates comprehensive prompts from codebases, designed to streamline interactions between developers and Large Language Models (LLMs) for code analysis, documentation, and improvement tasks. It bridges the gap between codebases and LLMs by converting projects into AI-friendly prompts, enabling users to leverage AI for various software development tasks. The tool offers features like holistic codebase representation, intelligent source tree generation, customizable prompt templates, smart token management, Gitignore integration, flexible file handling, clipboard-ready output, multiple output options, and enhanced code readability.

The Microsoft Semantic Kernel Documentation GitHub repository contains technical product documentation for Semantic Kernel. It serves as the home of technical content for Microsoft products and services. Contributors can learn how to make contributions by following the Docs contributor guide. The project follows the Microsoft Open Source Code of Conduct.

anythingllm-docs is a documentation repository for the AnythingLLM project. It contains detailed guides, setup instructions, and information on features and legal aspects of the project. The repository structure is organized into public, pages, components, and configuration files. Users can contribute by creating issues and pull requests following specific guidelines. The project is licensed under the MIT License and has been migrated to NextJS with the help of @ShadowArcanist.

RepoAgent is an LLM-powered framework designed for repository-level code documentation generation. It automates the process of detecting changes in Git repositories, analyzing code structure through AST, identifying inter-object relationships, replacing Markdown content, and executing multi-threaded operations. The tool aims to assist developers in understanding and maintaining codebases by providing comprehensive documentation, ultimately improving efficiency and saving time.