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.

BreezeApp is a community-driven platform for running AI capabilities locally on Android devices. It offers a privacy-focused solution where all AI features work offline, showcasing text-based chat interface, voice input/output support, and image understanding capabilities. The app supports multiple backends for different components and aims to make powerful AI models accessible to users. Users can contribute to the project by reporting issues, suggesting features, submitting pull requests, and sharing feedback. The architecture follows a service-based approach with service implementations for each AI capability. BreezeApp is a research project that may require specific hardware support or proprietary components, providing open-source alternatives where possible.

PureChat is a chat application integrated with ChatGPT, featuring efficient application building with Vite5, screenshot generation and copy support for chat records, IM instant messaging SDK for sessions, automatic light and dark mode switching based on system theme, Markdown rendering, code highlighting, and link recognition support, seamless social experience with GitHub quick login, integration of large language models like ChatGPT Ollama for streaming output, preset prompts, and context, Electron desktop app versions for macOS and Windows, ongoing development of more features. Environment setup requires Node.js 18.20+. Clone code with 'git clone https://github.com/Hyk260/PureChat.git', install dependencies with 'pnpm install', start project with 'pnpm dev', and build with 'pnpm build'.

智元 Fast API is a one-stop API management system that unifies various LLM APIs in terms of format, standards, and management, achieving the ultimate in functionality, performance, and user experience. It supports various models from companies like OpenAI, Azure, Baidu, Keda Xunfei, Alibaba Cloud, Zhifu AI, Google, DeepSeek, 360 Brain, and Midjourney. The project provides user and admin portals for preview, supports cluster deployment, multi-site deployment, and cross-zone deployment. It also offers Docker deployment, a public API site for registration, and screenshots of the admin and user portals. The API interface is similar to OpenAI's interface, and the project is open source with repositories for API, web, admin, and SDK on GitHub and Gitee.

ChatGLM3 is a conversational pretrained model jointly released by Zhipu AI and THU's KEG Lab. ChatGLM3-6B is the open-sourced model in the ChatGLM3 series. It inherits the advantages of its predecessors, such as fluent conversation and low deployment threshold. In addition, ChatGLM3-6B introduces the following features: 1. A stronger foundation model: ChatGLM3-6B's foundation model ChatGLM3-6B-Base employs more diverse training data, more sufficient training steps, and more reasonable training strategies. Evaluation on datasets from different perspectives, such as semantics, mathematics, reasoning, code, and knowledge, shows that ChatGLM3-6B-Base has the strongest performance among foundation models below 10B parameters. 2. More complete functional support: ChatGLM3-6B adopts a newly designed prompt format, which supports not only normal multi-turn dialogue, but also complex scenarios such as tool invocation (Function Call), code execution (Code Interpreter), and Agent tasks. 3. A more comprehensive open-source sequence: In addition to the dialogue model ChatGLM3-6B, the foundation model ChatGLM3-6B-Base, the long-text dialogue model ChatGLM3-6B-32K, and ChatGLM3-6B-128K, which further enhances the long-text comprehension ability, are also open-sourced. All the above weights are completely open to academic research and are also allowed for free commercial use after filling out a questionnaire.

AI Paint Today is an API server repository that allows users to record their emotions and daily experiences, and based on that, AI generates a beautiful picture diary of their day. The project includes features such as generating picture diaries from written entries, utilizing DALL-E 2 model for image generation, and deploying on AWS and Cloudflare. The project also follows specific conventions and collaboration strategies for development.

Cactus is an energy-efficient and fast AI inference framework designed for phones, wearables, and resource-constrained arm-based devices. It provides a bottom-up approach with no dependencies, optimizing for budget and mid-range phones. The framework includes Cactus FFI for integration, Cactus Engine for high-level transformer inference, Cactus Graph for unified computation graph, and Cactus Kernels for low-level ARM-specific operations. It is suitable for implementing custom models and scientific computing on mobile devices.

This book aims to provide readers with a comprehensive understanding of large language model technology, including its basic principles, key technologies, and application prospects. Through in-depth research and practice, we can continuously explore and improve large language model technology, and contribute to the development of the field of artificial intelligence.

MING is an open-sourced Chinese medical consultation model fine-tuned based on medical instructions. The main functions of the model are as follows: Medical Q&A: answering medical questions and analyzing cases. Intelligent consultation: giving diagnosis results and suggestions after multiple rounds of consultation.

Gensokyo-llm is a tool designed for Gensokyo and Onebotv11, providing a one-click solution for large models. It supports various Onebotv11 standard frameworks, HTTP-API, and reverse WS. The tool is lightweight, with built-in SQLite for context maintenance and proxy support. It allows easy integration with the Gensokyo framework by configuring reverse HTTP and forward HTTP addresses. Users can set system settings, role cards, and context length. Additionally, it offers an openai original flavor API with automatic context. The tool can be used as an API or integrated with QQ channel robots. It supports converting GPT's SSE type and ensures memory safety in concurrent SSE environments. The tool also supports multiple users simultaneously transmitting SSE bidirectionally.

The second edition of "PyTorch Practical Tutorial" was completed after 5 years, 4 years, and 2 years. On the basis of the essence of the first edition, rich and detailed deep learning application cases and reasoning deployment frameworks have been added, so that this book can more systematically cover the knowledge involved in deep learning engineers. As the development of artificial intelligence technology continues to emerge, the second edition of "PyTorch Practical Tutorial" is not the end, but the beginning, opening up new technologies, new fields, and new chapters. I hope to continue learning and making progress in artificial intelligence technology with you in the future.

This project provides a unified backend interface for open large language models (LLMs), offering a consistent experience with OpenAI's ChatGPT API. It supports various open-source LLMs, enabling developers to seamlessly integrate them into their applications. The interface features streaming responses, text embedding capabilities, and support for LangChain, a tool for developing LLM-based applications. By modifying environment variables, developers can easily use open-source models as alternatives to ChatGPT, providing a cost-effective and customizable solution for various use cases.

BetterOCR is a tool that enhances text detection by combining multiple OCR engines with LLM (Language Model). It aims to improve OCR results, especially for languages with limited training data or noisy outputs. The tool combines results from EasyOCR, Tesseract, and Pororo engines, along with LLM support from OpenAI. Users can provide custom context for better accuracy, view performance examples by language, and upcoming features include box detection, improved interface, and async support. The package is under rapid development and contributions are welcomed.

HMusic is an intelligent music player that supports Xiaomi AI speakers. It offers dual modes: xiaomusic server mode and Xiaomi IoT direct connection mode. Users can choose between these modes based on their preferences and needs. The direct connection mode is suitable for regular users who want a plug-and-play experience, while the xiaomusic mode is ideal for users with NAS/servers who require advanced features like a local music library, playlists, and progress control. The tool provides functionalities such as music search, playback, and volume control, catering to a wide range of music enthusiasts.

RunAnywhere is an on-device AI tool for mobile apps that allows users to run LLMs, speech-to-text, text-to-speech, and voice assistant features locally, ensuring privacy, offline functionality, and fast performance. The tool provides a range of AI capabilities without relying on cloud services, reducing latency and ensuring that no data leaves the device. RunAnywhere offers SDKs for Swift (iOS/macOS), Kotlin (Android), React Native, and Flutter, making it easy for developers to integrate AI features into their mobile applications. The tool supports various models for LLM, speech-to-text, and text-to-speech, with detailed documentation and installation instructions available for each platform.

Langfuse is a powerful tool that helps you develop, monitor, and test your LLM applications. With Langfuse, you can: * **Develop:** Instrument your app and start ingesting traces to Langfuse, inspect and debug complex logs, and manage, version, and deploy prompts from within Langfuse. * **Monitor:** Track metrics (cost, latency, quality) and gain insights from dashboards & data exports, collect and calculate scores for your LLM completions, run model-based evaluations, collect user feedback, and manually score observations in Langfuse. * **Test:** Track and test app behaviour before deploying a new version, test expected in and output pairs and benchmark performance before deploying, and track versions and releases in your application. Langfuse is easy to get started with and offers a generous free tier. You can sign up for Langfuse Cloud or deploy Langfuse locally or on your own infrastructure. Langfuse also offers a variety of integrations to make it easy to connect to your LLM applications.

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.

AI Hub is a comprehensive solution that leverages artificial intelligence and cloud computing to provide functionalities such as document search and retrieval, call center analytics, image analysis, brand reputation analysis, form analysis, document comparison, and content safety moderation. It integrates various Azure services like Cognitive Search, ChatGPT, Azure Vision Services, and Azure Document Intelligence to offer scalable, extensible, and secure AI-powered capabilities for different use cases and scenarios.

MicroCore is a collection of python adapters for Large Language Models and Vector Databases / Semantic Search APIs. It allows convenient communication with these services, easy switching between models & services, and separation of business logic from implementation details. Users can keep applications simple and try various models & services without changing application code. MicroCore connects MCP tools to language models easily, supports text completion and chat completion models, and provides features for configuring, installing vendor-specific packages, and using vector databases.

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.

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.

**Prompt flow** is a suite of development tools designed to streamline the end-to-end development cycle of LLM-based AI applications, from ideation, prototyping, testing, evaluation to production deployment and monitoring. It makes prompt engineering much easier and enables you to build LLM apps with production quality.

DeepEval is a simple-to-use, open-source LLM evaluation framework specialized for unit testing LLM outputs. It incorporates various metrics such as G-Eval, hallucination, answer relevancy, RAGAS, etc., and runs locally on your machine for evaluation. It provides a wide range of ready-to-use evaluation metrics, allows for creating custom metrics, integrates with any CI/CD environment, and enables benchmarking LLMs on popular benchmarks. DeepEval is designed for evaluating RAG and fine-tuning applications, helping users optimize hyperparameters, prevent prompt drifting, and transition from OpenAI to hosting their own Llama2 with confidence.

MegaDetector is an AI model that identifies animals, people, and vehicles in camera trap images (which also makes it useful for eliminating blank images). This model is trained on several million images from a variety of ecosystems. MegaDetector is just one of many tools that aims to make conservation biologists more efficient with AI. If you want to learn about other ways to use AI to accelerate camera trap workflows, check out our of the field, affectionately titled "Everything I know about machine learning and camera traps".

LeapfrogAI is a self-hosted AI platform designed to be deployed in air-gapped resource-constrained environments. It brings sophisticated AI solutions to these environments by hosting all the necessary components of an AI stack, including vector databases, model backends, API, and UI. LeapfrogAI's API closely matches that of OpenAI, allowing tools built for OpenAI/ChatGPT to function seamlessly with a LeapfrogAI backend. It provides several backends for various use cases, including llama-cpp-python, whisper, text-embeddings, and vllm. LeapfrogAI leverages Chainguard's apko to harden base python images, ensuring the latest supported Python versions are used by the other components of the stack. The LeapfrogAI SDK provides a standard set of protobuffs and python utilities for implementing backends and gRPC. LeapfrogAI offers UI options for common use-cases like chat, summarization, and transcription. It can be deployed and run locally via UDS and Kubernetes, built out using Zarf packages. LeapfrogAI is supported by a community of users and contributors, including Defense Unicorns, Beast Code, Chainguard, Exovera, Hypergiant, Pulze, SOSi, United States Navy, United States Air Force, and United States Space Force.

This Docker image for LLaVA (Large Language and Vision Assistant) provides a convenient way to run LLaVA locally or on RunPod. LLaVA is a powerful AI tool that combines natural language processing and computer vision capabilities. With this Docker image, you can easily access LLaVA's functionalities for various tasks, including image captioning, visual question answering, text summarization, and more. The image comes pre-installed with LLaVA v1.2.0, Torch 2.1.2, xformers 0.0.23.post1, and other necessary dependencies. You can customize the model used by setting the MODEL environment variable. The image also includes a Jupyter Lab environment for interactive development and exploration. Overall, this Docker image offers a comprehensive and user-friendly platform for leveraging LLaVA's capabilities.

The 'carrot' repository on GitHub provides a list of free and user-friendly ChatGPT mirror sites for easy access. The repository includes sponsored sites offering various GPT models and services. Users can find and share sites, report errors, and access stable and recommended sites for ChatGPT usage. The repository also includes a detailed list of ChatGPT sites, their features, and accessibility options, making it a valuable resource for ChatGPT users seeking free and unlimited GPT services.

TrustLLM is a comprehensive study of trustworthiness in LLMs, including principles for different dimensions of trustworthiness, established benchmark, evaluation, and analysis of trustworthiness for mainstream LLMs, and discussion of open challenges and future directions. Specifically, we first propose a set of principles for trustworthy LLMs that span eight different dimensions. Based on these principles, we further establish a benchmark across six dimensions including truthfulness, safety, fairness, robustness, privacy, and machine ethics. We then present a study evaluating 16 mainstream LLMs in TrustLLM, consisting of over 30 datasets. The document explains how to use the trustllm python package to help you assess the performance of your LLM in trustworthiness more quickly. For more details about TrustLLM, please refer to project website.

AI-YinMei is an AI virtual anchor Vtuber development tool (N card version). It supports fastgpt knowledge base chat dialogue, a complete set of solutions for LLM large language models: [fastgpt] + [one-api] + [Xinference], supports docking bilibili live broadcast barrage reply and entering live broadcast welcome speech, supports Microsoft edge-tts speech synthesis, supports Bert-VITS2 speech synthesis, supports GPT-SoVITS speech synthesis, supports expression control Vtuber Studio, supports painting stable-diffusion-webui output OBS live broadcast room, supports painting picture pornography public-NSFW-y-distinguish, supports search and image search service duckduckgo (requires magic Internet access), supports image search service Baidu image search (no magic Internet access), supports AI reply chat box [html plug-in], supports AI singing Auto-Convert-Music, supports playlist [html plug-in], supports dancing function, supports expression video playback, supports head touching action, supports gift smashing action, supports singing automatic start dancing function, chat and singing automatic cycle swing action, supports multi scene switching, background music switching, day and night automatic switching scene, supports open singing and painting, let AI automatically judge the content.