airunner

AI Runner is a multi-modal AI interface that allows users to run open-source large language models and AI image generators on their own hardware. The tool provides features such as voice-based chatbot conversations, text-to-speech, speech-to-text, vision-to-text, text generation with large language models, image generation capabilities, image manipulation tools, utility functions, and more. It aims to provide a stable and user-friendly experience with security updates, a new UI, and a streamlined installation process. The application is designed to run offline on users' hardware without relying on a web server, offering a smooth and responsive user experience.

Coreply is an open-source Android app that provides texting suggestions while typing, enhancing the typing experience with intelligent, context-aware suggestions. It supports various texting apps and offers real-time AI suggestions, customizable LLM settings, and ensures no data collection. Users can install the app, configure it with an API key, and start receiving suggestions while typing in messaging apps. The tool supports different AI models from providers like OpenAI, Google AI Studio, Openrouter, Groq, and Codestral for chat completion and fill-in-the-middle tasks.

Starmoon is an affordable, compact AI-enabled device that can understand and respond to your emotions with empathy. It offers supportive conversations and personalized learning assistance. The device is cost-effective, voice-enabled, open-source, compact, and aims to reduce screen time. Users can assemble the device themselves using off-the-shelf components and deploy it locally for data privacy. Starmoon integrates various APIs for AI language models, speech-to-text, text-to-speech, and emotion intelligence. The hardware setup involves components like ESP32S3, microphone, amplifier, speaker, LED light, and button, along with software setup instructions for developers. The project also includes a web app, backend API, and background task dashboard for monitoring and management.

EvoAgentX is an open-source framework for building, evaluating, and evolving LLM-based agents or agentic workflows in an automated, modular, and goal-driven manner. It enables developers and researchers to move beyond static prompt chaining or manual workflow orchestration by introducing a self-evolving agent ecosystem. The framework includes features such as agent workflow autoconstruction, built-in evaluation, self-evolution engine, plug-and-play compatibility, comprehensive built-in tools, memory module support, and human-in-the-loop interactions.

OpenLIT is an OpenTelemetry-native GenAI and LLM Application Observability tool. It's designed to make the integration process of observability into GenAI projects as easy as pie – literally, with just **a single line of code**. Whether you're working with popular LLM Libraries such as OpenAI and HuggingFace or leveraging vector databases like ChromaDB, OpenLIT ensures your applications are monitored seamlessly, providing critical insights to improve performance and reliability.

ClearML Fractional GPU is a tool designed to optimize GPU resource utilization by allowing multiple containers to run on the same GPU with driver-level memory limitation and compute time-slicing. It supports CUDA 11.x & CUDA 12.x, preventing greedy processes from grabbing the entire GPU memory. The tool offers options like Dynamic GPU Slicing, Container-based Memory Limits, and Kubernetes-based Static MIG Slicing to enhance hardware utilization and workload performance for AI development.

Pipecat is an open-source framework designed for building generative AI voice bots and multimodal assistants. It provides code building blocks for interacting with AI services, creating low-latency data pipelines, and transporting audio, video, and events over the Internet. Pipecat supports various AI services like speech-to-text, text-to-speech, image generation, and vision models. Users can implement new services and contribute to the framework. Pipecat aims to simplify the development of applications like personal coaches, meeting assistants, customer support bots, and more by providing a complete framework for integrating AI services.

OSA (Open-Source-Advisor) is a tool designed to improve the quality of scientific open source projects by automating the generation of README files, documentation, CI/CD scripts, and providing advice and recommendations for repositories. It supports various LLMs accessible via API, local servers, or osa_bot hosted on ITMO servers. OSA is currently under development with features like README file generation, documentation generation, automatic implementation of changes, LLM integration, and GitHub Action Workflow generation. It requires Python 3.10 or higher and tokens for GitHub/GitLab/Gitverse and LLM API key. Users can install OSA using PyPi or build from source, and run it using CLI commands or Docker containers.

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.

WeKnora is a document understanding and semantic retrieval framework based on large language models (LLM), designed specifically for scenarios with complex structures and heterogeneous content. The framework adopts a modular architecture, integrating multimodal preprocessing, semantic vector indexing, intelligent recall, and large model generation reasoning to build an efficient and controllable document question-answering process. The core retrieval process is based on the RAG (Retrieval-Augmented Generation) mechanism, combining context-relevant segments with language models to achieve higher-quality semantic answers. It supports various document formats, intelligent inference, flexible extension, efficient retrieval, ease of use, and security and control. Suitable for enterprise knowledge management, scientific literature analysis, product technical support, legal compliance review, and medical knowledge assistance.

Terminator is an AI-powered desktop automation tool that is open source, MIT-licensed, and cross-platform. It works across all apps and browsers, inspired by GitHub Actions & Playwright. It is 100x faster than generic AI agents, with over 95% success rate and no vendor lock-in. Users can create automations that work across any desktop app or browser, achieve high success rates without costly consultant armies, and pre-train workflows as deterministic code.

SuperDuperDB is a Python framework for integrating AI models, APIs, and vector search engines directly with your existing databases, including hosting of your own models, streaming inference and scalable model training/fine-tuning. Build, deploy and manage any AI application without the need for complex pipelines, infrastructure as well as specialized vector databases, and moving our data there, by integrating AI at your data's source: - Generative AI, LLMs, RAG, vector search - Standard machine learning use-cases (classification, segmentation, regression, forecasting recommendation etc.) - Custom AI use-cases involving specialized models - Even the most complex applications/workflows in which different models work together SuperDuperDB is **not** a database. Think `db = superduper(db)`: SuperDuperDB transforms your databases into an intelligent platform that allows you to leverage the full AI and Python ecosystem. A single development and deployment environment for all your AI applications in one place, fully scalable and easy to manage.

Automodel is a Python library for automating the process of building and evaluating machine learning models. It provides a set of tools and utilities to streamline the model development workflow, from data preprocessing to model selection and evaluation. With Automodel, users can easily experiment with different algorithms, hyperparameters, and feature engineering techniques to find the best model for their dataset. The library is designed to be user-friendly and customizable, allowing users to define their own pipelines and workflows. Automodel is suitable for data scientists, machine learning engineers, and anyone looking to quickly build and test machine learning models without the need for manual intervention.

Spandrel is a library for loading and running pre-trained PyTorch models. It automatically detects the model architecture and hyperparameters from model files, and provides a unified interface for running models.

AgentScope is a multi-agent platform designed to empower developers to build multi-agent applications with large-scale models. It features three high-level capabilities: Easy-to-Use, High Robustness, and Actor-Based Distribution. AgentScope provides a list of `ModelWrapper` to support both local model services and third-party model APIs, including OpenAI API, DashScope API, Gemini API, and ollama. It also enables developers to rapidly deploy local model services using libraries such as ollama (CPU inference), Flask + Transformers, Flask + ModelScope, FastChat, and vllm. AgentScope supports various services, including Web Search, Data Query, Retrieval, Code Execution, File Operation, and Text Processing. Example applications include Conversation, Game, and Distribution. AgentScope is released under Apache License 2.0 and welcomes contributions.

Nexa SDK is a comprehensive toolkit supporting ONNX and GGML models for text generation, image generation, vision-language models (VLM), and text-to-speech (TTS) capabilities. It offers an OpenAI-compatible API server with JSON schema mode and streaming support, along with a user-friendly Streamlit UI. Users can run Nexa SDK on any device with Python environment, with GPU acceleration supported. The toolkit provides model support, conversion engine, inference engine for various tasks, and differentiating features from other tools.

Wunjo AI is a comprehensive tool that empowers users to explore the realm of speech synthesis, deepfake animations, video-to-video transformations, and more. Its user-friendly interface and privacy-first approach make it accessible to both beginners and professionals alike. With Wunjo AI, you can effortlessly convert text into human-like speech, clone voices from audio files, create multi-dialogues with distinct voice profiles, and perform real-time speech recognition. Additionally, you can animate faces using just one photo combined with audio, swap faces in videos, GIFs, and photos, and even remove unwanted objects or enhance the quality of your deepfakes using the AI Retouch Tool. Wunjo AI is an all-in-one solution for your voice and visual AI needs, offering endless possibilities for creativity and expression.

AI Runner is a multi-modal AI interface that allows users to run open-source large language models and AI image generators on their own hardware. The tool provides features such as voice-based chatbot conversations, text-to-speech, speech-to-text, vision-to-text, text generation with large language models, image generation capabilities, image manipulation tools, utility functions, and more. It aims to provide a stable and user-friendly experience with security updates, a new UI, and a streamlined installation process. The application is designed to run offline on users' hardware without relying on a web server, offering a smooth and responsive user experience.

Wechat AI Assistant is a project that enables multi-modal interaction with ChatGPT AI assistant within WeChat. It allows users to engage in conversations, role-playing, respond to voice messages, analyze images and videos, summarize articles and web links, and search the internet. The project utilizes the WeChatFerry library to control the Windows PC desktop WeChat client and leverages the OpenAI Assistant API for intelligent multi-modal message processing. Users can interact with ChatGPT AI in WeChat through text or voice, access various tools like bing_search, browse_link, image_to_text, text_to_image, text_to_speech, video_analysis, and more. The AI autonomously determines which code interpreter and external tools to use to complete tasks. Future developments include file uploads for AI to reference content, integration with other APIs, and login support for enterprise WeChat and WeChat official accounts.

Generative AI Pharmacist is a project showcasing the use of generative AI tools to create an animated avatar named Macy, who delivers medication counseling in a realistic and professional manner. The project utilizes tools like Midjourney for image generation, ChatGPT for text generation, ElevenLabs for text-to-speech conversion, and D-ID for creating a photorealistic talking avatar video. The demo video featuring Macy discussing commonly-prescribed medications demonstrates the potential of generative AI in healthcare communication.

AnyGPT is a unified multimodal language model that utilizes discrete representations for processing various modalities like speech, text, images, and music. It aligns the modalities for intermodal conversions and text processing. AnyInstruct dataset is constructed for generative models. The model proposes a generative training scheme using Next Token Prediction task for training on a Large Language Model (LLM). It aims to compress vast multimodal data on the internet into a single model for emerging capabilities. The tool supports tasks like text-to-image, image captioning, ASR, TTS, text-to-music, and music captioning.

Pallaidium is a generative AI movie studio integrated into the Blender video editor. It allows users to AI-generate video, image, and audio from text prompts or existing media files. The tool provides various features such as text to video, text to audio, text to speech, text to image, image to image, image to video, video to video, image to text, and more. It requires a Windows system with a CUDA-supported Nvidia card and at least 6 GB VRAM. Pallaidium offers batch processing capabilities, text to audio conversion using Bark, and various performance optimization tips. Users can install the tool by downloading the add-on and following the installation instructions provided. The tool comes with a set of restrictions on usage, prohibiting the generation of harmful, pornographic, violent, or false content.

ElevenLabs-DotNet is a non-official Eleven Labs voice synthesis RESTful client that allows users to convert text to speech. The library targets .NET 8.0 and above, working across various platforms like console apps, winforms, wpf, and asp.net, and across Windows, Linux, and Mac. Users can authenticate using API keys directly, from a configuration file, or system environment variables. The tool provides functionalities for text to speech conversion, streaming text to speech, accessing voices, dubbing audio or video files, generating sound effects, managing history of synthesized audio clips, and accessing user information and subscription status.

OmniAI provides a unified Ruby API for integrating with multiple AI providers, streamlining AI development by offering a consistent interface for features such as chat, text-to-speech, speech-to-text, and embeddings. It ensures seamless interoperability across platforms and effortless switching between providers, making integrations more flexible and reliable.

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.