LangPort is an open-source platform for serving large language models. It aims to provide a super fast LLM inference service with core features including Huggingface transformers support, distributed serving system, streaming generation, batch inference, and support for various model architectures. It offers compatibility with OpenAI, FauxPilot, HuggingFace, and Tabby APIs. The project supports model architectures like LLaMa, GLM, GPT2, and GPT Neo, and has been tested with models such as NingYu, Vicuna, ChatGLM, and WizardLM. LangPort also provides features like dynamic batch inference, int4 quantization, and generation logprobs parameter.

Lightpanda Browser is an open-source headless browser designed for fast web automation, AI agents, LLM training, scraping, and testing. It features ultra-low memory footprint, exceptionally fast execution, and compatibility with Playwright and Puppeteer through CDP. Built for performance, Lightpanda offers Javascript execution, support for Web APIs, and is optimized for minimal memory usage. It is a modern solution for web scraping and automation tasks, providing a lightweight alternative to traditional browsers like Chrome.

Holmes-VAD is a framework for unbiased and explainable Video Anomaly Detection using multimodal instructions. It addresses biased detection in challenging events by leveraging precise temporal supervision and rich multimodal instructions. The framework includes a largescale VAD instruction-tuning benchmark, VAD-Instruct50k, created with single-frame annotations and a robust video captioner. It offers accurate anomaly localization and comprehensive explanations through a customized solution for interpretable video anomaly detection.

doc-comments-ai is a tool designed to automatically generate code documentation using language models. It allows users to easily create documentation comment blocks for methods in various programming languages such as Python, Typescript, Javascript, Java, Rust, and more. The tool supports both OpenAI and local LLMs, ensuring data privacy and security. Users can generate documentation comments for methods in files, inline comments in method bodies, and choose from different models like GPT-3.5-Turbo, GPT-4, and Azure OpenAI. Additionally, the tool provides support for Treesitter integration and offers guidance on selecting the appropriate model for comprehensive documentation needs.

ComfyUI-IF_AI_tools is a set of custom nodes for ComfyUI that allows you to generate prompts using a local Large Language Model (LLM) via Ollama. This tool enables you to enhance your image generation workflow by leveraging the power of language models.

Dstack is an open-source orchestration engine for running AI workloads in any cloud. It supports a wide range of cloud providers (such as AWS, GCP, Azure, Lambda, TensorDock, Vast.ai, CUDO, RunPod, etc.) as well as on-premises infrastructure. With Dstack, you can easily set up and manage dev environments, tasks, services, and pools for your AI workloads.

BigCodeBench is an easy-to-use benchmark for code generation with practical and challenging programming tasks. It aims to evaluate the true programming capabilities of large language models (LLMs) in a more realistic setting. The benchmark is designed for HumanEval-like function-level code generation tasks, but with much more complex instructions and diverse function calls. BigCodeBench focuses on the evaluation of LLM4Code with diverse function calls and complex instructions, providing precise evaluation & ranking and pre-generated samples to accelerate code intelligence research. It inherits the design of the EvalPlus framework but differs in terms of execution environment and test evaluation.

PySpur is a graph-based editor designed for LLM (Large Language Models) workflows. It offers modular building blocks, node-level debugging, and performance evaluation. The tool is easy to hack, supports JSON configs for workflow graphs, and is lightweight with minimal dependencies. Users can quickly set up PySpur by cloning the repository, creating a .env file, starting docker services, and accessing the portal. PySpur can also work with local models served using Ollama, with steps provided for configuration. The roadmap includes features like canvas, async/batch execution, support for Ollama, new nodes, pipeline optimization, templates, code compilation, multimodal support, and more.

BentoML is an open-source model serving library for building performant and scalable AI applications with Python. It comes with everything you need for serving optimization, model packaging, and production deployment.

Whisper-WebUI is a Gradio-based browser interface for Whisper, serving as an Easy Subtitle Generator. It supports generating subtitles from various sources such as files, YouTube, and microphone. The tool also offers speech-to-text and text-to-text translation features, utilizing Facebook NLLB models and DeepL API. Users can translate subtitle files from other languages to English and vice versa. The project integrates faster-whisper for improved VRAM usage and transcription speed, providing efficiency metrics for optimized whisper models. Additionally, users can choose from different Whisper models based on size and language requirements.

Gemini Next Chat is an open-source, extensible high-performance Gemini chatbot framework that supports one-click free deployment of private Gemini web applications. It provides a simple interface with image recognition and voice conversation, supports multi-modal models, talk mode, visual recognition, assistant market, support plugins, conversation list, full Markdown support, privacy and security, PWA support, well-designed UI, fast loading speed, static deployment, and multi-language support.

PySpur is a graph-based editor designed for LLM workflows, offering modular building blocks for easy workflow creation and debugging at node level. It allows users to evaluate final performance and promises self-improvement features in the future. PySpur is easy-to-hack, supports JSON configs for workflow graphs, and is lightweight with minimal dependencies, making it a versatile tool for workflow management in the field of AI and machine learning.

Tangent is a canvas for exploring AI conversations, allowing users to resurrect and continue conversations, branch and explore different ideas, organize conversations by topics, and support archive data exports. It aims to provide a visual/textual/audio exploration experience with AI assistants, offering a 'thoughts workbench' for experimenting freely, reviving old threads, and diving into tangents. The project structure includes a modular backend with components for API routes, background task management, data processing, and more. Prerequisites for setup include Whisper.cpp, Ollama, and exported archive data from Claude or ChatGPT. Users can initialize the environment, install Python packages, set up Ollama, configure local models, and start the backend and frontend to interact with the tool.

TokenFormer is a fully attention-based neural network architecture that leverages tokenized model parameters to enhance architectural flexibility. It aims to maximize the flexibility of neural networks by unifying token-token and token-parameter interactions through the attention mechanism. The architecture allows for incremental model scaling and has shown promising results in language modeling and visual modeling tasks. The codebase is clean, concise, easily readable, state-of-the-art, and relies on minimal dependencies.

Skyrim is a weather forecasting tool that enables users to run large weather models using consumer-grade GPUs. It provides access to state-of-the-art foundational weather models through a well-maintained infrastructure. Users can forecast weather conditions, such as wind speed and direction, by running simulations on their own GPUs or using modal volume or cloud services like s3 buckets. Skyrim supports various large weather models like Graphcast, Pangu, Fourcastnet, and DLWP, with plans for future enhancements like ensemble prediction and model quantization.

ChatGPT Desktop Application is a multi-platform tool that provides a powerful AI wrapper for generating text. It offers features like text-to-speech, exporting chat history in various formats, automatic application upgrades, system tray hover window, support for slash commands, customization of global shortcuts, and pop-up search. The application is built using Tauri and aims to enhance user experience by simplifying text generation tasks. It is available for Mac, Windows, and Linux, and is designed for personal learning and research purposes.

LangPort is an open-source platform for serving large language models. It aims to provide a super fast LLM inference service with core features including Huggingface transformers support, distributed serving system, streaming generation, batch inference, and support for various model architectures. It offers compatibility with OpenAI, FauxPilot, HuggingFace, and Tabby APIs. The project supports model architectures like LLaMa, GLM, GPT2, and GPT Neo, and has been tested with models such as NingYu, Vicuna, ChatGLM, and WizardLM. LangPort also provides features like dynamic batch inference, int4 quantization, and generation logprobs parameter.

ViiTor-Voice is an LLM based TTS Engine that offers a lightweight design with 0.5B parameters for efficient deployment on various platforms. It provides real-time streaming output with low latency experience, a rich voice library with over 300 voice options, flexible speech rate adjustment, and zero-shot voice cloning capabilities. The tool supports both Chinese and English languages and is suitable for applications requiring quick response and natural speech fluency.

LLMStack is a no-code platform for building generative AI agents, workflows, and chatbots. It allows users to connect their own data, internal tools, and GPT-powered models without any coding experience. LLMStack can be deployed to the cloud or on-premise and can be accessed via HTTP API or triggered from Slack or Discord.

LocalAI is a free and open-source OpenAI alternative that acts as a drop-in replacement REST API compatible with OpenAI (Elevenlabs, Anthropic, etc.) API specifications for local AI inferencing. It allows users to run LLMs, generate images, audio, and more locally or on-premises with consumer-grade hardware, supporting multiple model families and not requiring a GPU. LocalAI offers features such as text generation with GPTs, text-to-audio, audio-to-text transcription, image generation with stable diffusion, OpenAI functions, embeddings generation for vector databases, constrained grammars, downloading models directly from Huggingface, and a Vision API. It provides a detailed step-by-step introduction in its Getting Started guide and supports community integrations such as custom containers, WebUIs, model galleries, and various bots for Discord, Slack, and Telegram. LocalAI also offers resources like an LLM fine-tuning guide, instructions for local building and Kubernetes installation, projects integrating LocalAI, and a how-tos section curated by the community. It encourages users to cite the repository when utilizing it in downstream projects and acknowledges the contributions of various software from the community.

AiTreasureBox is a versatile AI tool that provides a collection of pre-trained models and algorithms for various machine learning tasks. It simplifies the process of implementing AI solutions by offering ready-to-use components that can be easily integrated into projects. With AiTreasureBox, users can quickly prototype and deploy AI applications without the need for extensive knowledge in machine learning or deep learning. The tool covers a wide range of tasks such as image classification, text generation, sentiment analysis, object detection, and more. It is designed to be user-friendly and accessible to both beginners and experienced developers, making AI development more efficient and accessible to a wider audience.

Glide is a cloud-native LLM gateway that provides a unified REST API for accessing various large language models (LLMs) from different providers. It handles LLMOps tasks such as model failover, caching, key management, and more, making it easy to integrate LLMs into applications. Glide supports popular LLM providers like OpenAI, Anthropic, Azure OpenAI, AWS Bedrock (Titan), Cohere, Google Gemini, OctoML, and Ollama. It offers high availability, performance, and observability, and provides SDKs for Python and NodeJS to simplify integration.

Jupyter AI connects generative AI with Jupyter notebooks. It provides a user-friendly and powerful way to explore generative AI models in notebooks and improve your productivity in JupyterLab and the Jupyter Notebook. Specifically, Jupyter AI offers: * An `%%ai` magic that turns the Jupyter notebook into a reproducible generative AI playground. This works anywhere the IPython kernel runs (JupyterLab, Jupyter Notebook, Google Colab, Kaggle, VSCode, etc.). * A native chat UI in JupyterLab that enables you to work with generative AI as a conversational assistant. * Support for a wide range of generative model providers, including AI21, Anthropic, AWS, Cohere, Gemini, Hugging Face, NVIDIA, and OpenAI. * Local model support through GPT4All, enabling use of generative AI models on consumer grade machines with ease and privacy.

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).

Weave is a toolkit for developing Generative AI applications, built by Weights & Biases. With Weave, you can log and debug language model inputs, outputs, and traces; build rigorous, apples-to-apples evaluations for language model use cases; and organize all the information generated across the LLM workflow, from experimentation to evaluations to production. Weave aims to bring rigor, best-practices, and composability to the inherently experimental process of developing Generative AI software, without introducing cognitive overhead.

LLMStack is a no-code platform for building generative AI agents, workflows, and chatbots. It allows users to connect their own data, internal tools, and GPT-powered models without any coding experience. LLMStack can be deployed to the cloud or on-premise and can be accessed via HTTP API or triggered from Slack or Discord.

The VisionCraft API is a free API for using over 100 different AI models. From images to sound.

Kaito is an operator that automates the AI/ML inference model deployment in a Kubernetes cluster. It manages large model files using container images, avoids tuning deployment parameters to fit GPU hardware by providing preset configurations, auto-provisions GPU nodes based on model requirements, and hosts large model images in the public Microsoft Container Registry (MCR) if the license allows. Using Kaito, the workflow of onboarding large AI inference models in Kubernetes is largely simplified.

PyRIT is an open access automation framework designed to empower security professionals and ML engineers to red team foundation models and their applications. It automates AI Red Teaming tasks to allow operators to focus on more complicated and time-consuming tasks and can also identify security harms such as misuse (e.g., malware generation, jailbreaking), and privacy harms (e.g., identity theft). The goal is to allow researchers to have a baseline of how well their model and entire inference pipeline is doing against different harm categories and to be able to compare that baseline to future iterations of their model. This allows them to have empirical data on how well their model is doing today, and detect any degradation of performance based on future improvements.

Tabby is a self-hosted AI coding assistant, offering an open-source and on-premises alternative to GitHub Copilot. It boasts several key features: * Self-contained, with no need for a DBMS or cloud service. * OpenAPI interface, easy to integrate with existing infrastructure (e.g Cloud IDE). * Supports consumer-grade GPUs.

SPEAR (Simulator for Photorealistic Embodied AI Research) is a powerful tool for training embodied agents. It features 300 unique virtual indoor environments with 2,566 unique rooms and 17,234 unique objects that can be manipulated individually. Each environment is designed by a professional artist and features detailed geometry, photorealistic materials, and a unique floor plan and object layout. SPEAR is implemented as Unreal Engine assets and provides an OpenAI Gym interface for interacting with the environments via Python.

Magick is a groundbreaking visual AIDE (Artificial Intelligence Development Environment) for no-code data pipelines and multimodal agents. Magick can connect to other services and comes with nodes and templates well-suited for intelligent agents, chatbots, complex reasoning systems and realistic characters.