aigverse is a Python infrastructure framework that bridges the gap between logic synthesis and AI/ML applications. It allows efficient representation and manipulation of logic circuits, making it easier to integrate logic synthesis and optimization tasks into machine learning pipelines. Built upon EPFL Logic Synthesis Libraries, particularly mockturtle, aigverse provides a high-level Python interface to state-of-the-art algorithms for And-Inverter Graph (AIG) manipulation and logic synthesis, widely used in formal verification, hardware design, and optimization tasks.

This is the official Clarifai gRPC Python client for interacting with their recognition API. Clarifai offers a platform for data scientists, developers, researchers, and enterprises to utilize artificial intelligence for image, video, and text analysis through computer vision and natural language processing. The client allows users to authenticate, predict concepts in images, and access various functionalities provided by the Clarifai API. It follows a versioning scheme that aligns with the backend API updates and includes specific instructions for installation and troubleshooting. Users can explore the Clarifai demo, sign up for an account, and refer to the documentation for detailed information.

sieves is a library for zero- and few-shot NLP tasks with structured generation, enabling rapid prototyping of NLP applications without the need for training. It simplifies NLP prototyping by bundling capabilities into a single library, providing zero- and few-shot model support, a unified interface for structured generation, built-in tasks for common NLP operations, easy extendability, document-based pipeline architecture, caching to prevent redundant model calls, and more. The tool draws inspiration from spaCy and spacy-llm, offering features like immediate inference, observable pipelines, integrated tools for document parsing and text chunking, ready-to-use tasks such as classification, summarization, translation, and more, persistence for saving and loading pipelines, distillation for specialized model creation, and caching to optimize performance.

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.

IntelliNode is a javascript module that integrates cutting-edge AI models like ChatGPT, LLaMA, WaveNet, Gemini, and Stable diffusion into projects. It offers functions for generating text, speech, and images, as well as semantic search, multi-model evaluation, and chatbot capabilities. The module provides a wrapper layer for low-level model access, a controller layer for unified input handling, and a function layer for abstract functionality tailored to various use cases.

AICSImageIO is a Python tool for Image Reading, Metadata Conversion, and Image Writing for Microscopy Images. It supports various file formats like OME-TIFF, TIFF, ND2, DV, CZI, LIF, PNG, GIF, and Bio-Formats. Users can read and write metadata and imaging data, work with different file systems like local paths, HTTP URLs, s3fs, and gcsfs. The tool provides functionalities for full image reading, delayed image reading, mosaic image reading, metadata reading, xarray coordinate plane attachment, cloud IO support, and saving to OME-TIFF. It also offers benchmarking and developer resources.

Adaline Gateway is a fully local production-grade Super SDK that offers a unified interface for calling over 200+ LLMs. It is production-ready, supports batching, retries, caching, callbacks, and OpenTelemetry. Users can create custom plugins and providers for seamless integration with their infrastructure.

LlamaIndex is a data framework for building LLM applications. It provides tools for ingesting, structuring, and querying data, as well as integrating with LLMs and other tools. LlamaIndex is designed to be easy to use for both beginner and advanced users, and it provides a comprehensive set of features for building LLM applications.

Embodied Agents is a toolkit for integrating large multi-modal models into existing robot stacks with just a few lines of code. It provides consistency, reliability, scalability, and is configurable to any observation and action space. The toolkit is designed to reduce complexities involved in setting up inference endpoints, converting between different model formats, and collecting/storing datasets. It aims to facilitate data collection and sharing among roboticists by providing Python-first abstractions that are modular, extensible, and applicable to a wide range of tasks. The toolkit supports asynchronous and remote thread-safe agent execution for maximal responsiveness and scalability, and is compatible with various APIs like HuggingFace Spaces, Datasets, Gymnasium Spaces, Ollama, and OpenAI. It also offers automatic dataset recording and optional uploads to the HuggingFace hub.

RAPTOR introduces a novel approach to retrieval-augmented language models by constructing a recursive tree structure from documents. This allows for more efficient and context-aware information retrieval across large texts, addressing common limitations in traditional language models. Users can add documents to the tree, answer questions based on indexed documents, save and load the tree, and extend RAPTOR with custom summarization, question-answering, and embedding models. The tool is designed to be flexible and customizable for various NLP tasks.

An open-source client package that allows developers to easily integrate the power of OpenAI's state-of-the-art AI models into their Dart/Flutter applications. The library provides simple and intuitive methods for making requests to OpenAI's various APIs, including the GPT-3 language model, DALL-E image generation, and more. It is designed to be lightweight and easy to use, enabling developers to focus on building their applications without worrying about the complexities of dealing with HTTP requests. Note that this is an unofficial library as OpenAI does not have an official Dart library.

RAGLite is a Python toolkit for Retrieval-Augmented Generation (RAG) with PostgreSQL or SQLite. It offers configurable options for choosing LLM providers, database types, and rerankers. The toolkit is fast and permissive, utilizing lightweight dependencies and hardware acceleration. RAGLite provides features like PDF to Markdown conversion, multi-vector chunk embedding, optimal semantic chunking, hybrid search capabilities, adaptive retrieval, and improved output quality. It is extensible with a built-in Model Context Protocol server, customizable ChatGPT-like frontend, document conversion to Markdown, and evaluation tools. Users can configure RAGLite for various tasks like configuring, inserting documents, running RAG pipelines, computing query adapters, evaluating performance, running MCP servers, and serving frontends.

Mirage Persistent Kernel (MPK) is a compiler and runtime system that automatically transforms LLM inference into a single megakernel—a fused GPU kernel that performs all necessary computation and communication within a single kernel launch. This end-to-end GPU fusion approach reduces LLM inference latency by 1.2× to 6.7×, all while requiring minimal developer effort.

llmgraph is a tool that enables users to create knowledge graphs in GraphML, GEXF, and HTML formats by extracting world knowledge from large language models (LLMs) like ChatGPT. It supports various entity types and relationships, offers cache support for efficient graph growth, and provides insights into LLM costs. Users can customize the model used and interact with different LLM providers. The tool allows users to generate interactive graphs based on a specified entity type and Wikipedia link, making it a valuable resource for knowledge graph creation and exploration.

AIMNet2 Calculator is a package that integrates the AIMNet2 neural network potential into simulation workflows, providing fast and reliable energy, force, and property calculations for molecules with diverse elements. It excels at modeling various systems, offers flexible interfaces for popular simulation packages, and supports long-range interactions using DSF or Ewald summation Coulomb models. The tool is designed for accurate and versatile molecular simulations, suitable for large molecules and periodic calculations.

TopicGPT is a repository containing scripts and prompts for the paper 'TopicGPT: Topic Modeling by Prompting Large Language Models' (NAACL'24). The 'topicgpt_python' package offers functions to generate high-level and specific topics, refine topics, assign topics to input text, and correct generated topics. It supports various APIs like OpenAI, VertexAI, Azure, Gemini, and vLLM for inference. Users can prepare data in JSONL format, run the pipeline using provided scripts, and evaluate topic alignment with ground-truth labels.

The neo is an open source robotics research platform powered by a OnePlus 3 smartphone and an STM32F205-based CAN interface board, housed in a 3d-printed casing with active cooling. It includes NEOS, a stripped down Android ROM, and offers a modern Linux environment for development. The platform leverages the high performance embedded processor and sensor capabilities of modern smartphones at a low cost. A detailed guide is available for easy construction, requiring online shopping and soldering skills. The total cost for building a neo is approximately $700.

aigverse is a Python infrastructure framework that bridges the gap between logic synthesis and AI/ML applications. It allows efficient representation and manipulation of logic circuits, making it easier to integrate logic synthesis and optimization tasks into machine learning pipelines. Built upon EPFL Logic Synthesis Libraries, particularly mockturtle, aigverse provides a high-level Python interface to state-of-the-art algorithms for And-Inverter Graph (AIG) manipulation and logic synthesis, widely used in formal verification, hardware design, and optimization tasks.

aigverse is a Python infrastructure framework that bridges the gap between logic synthesis and AI/ML applications. It allows efficient representation and manipulation of logic circuits, making it easier to integrate logic synthesis and optimization tasks into machine learning pipelines. Built upon EPFL Logic Synthesis Libraries, particularly mockturtle, aigverse provides a high-level Python interface to state-of-the-art algorithms for And-Inverter Graph (AIG) manipulation and logic synthesis, widely used in formal verification, hardware design, and optimization tasks.

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.

AgentCloud is an open-source platform that enables companies to build and deploy private LLM chat apps, empowering teams to securely interact with their data. It comprises three main components: Agent Backend, Webapp, and Vector Proxy. To run this project locally, clone the repository, install Docker, and start the services. The project is licensed under the GNU Affero General Public License, version 3 only. Contributions and feedback are welcome from the community.

This framework generates fuzz targets for real-world `C`/`C++` projects with various Large Language Models (LLM) and benchmarks them via the `OSS-Fuzz` platform. It manages to successfully leverage LLMs to generate valid fuzz targets (which generate non-zero coverage increase) for 160 C/C++ projects. The maximum line coverage increase is 29% from the existing human-written targets.

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.