GitHub Trends

#python#agent#android#app#automation#copilot#gui#mllm#mobile#mobile_agents#multimodal#multimodal_agent#multimodal_large_language_models Mobile-Agent-v3.5 is Alibaba's top GUI agent family using GUI-Owl 1.5 models (2B to 235B sizes) for automating desktop, mobile, and browser tasks like stock checks, bookings, or document creation with planning, reflection, and memory. Try free online demos on ModelScope or Bailian, or use limited-time APIs—no setup needed. It leads 20+ benchmarks for real-world use. You benefit by saving time on repetitive tasks, boosting productivity, and handling complex operations hands-free across devices. https://github.com/X-PLUG/MobileAgent

#python#deepseek#demo#easy#embedding#flask#gpt#huggingface_transformers#llm#mcp#multimodal#openai#qwen#rag#sentence_transformers#ui#vllm#vlm UltraRAG is a lightweight framework that makes building retrieval-augmented generation (RAG) systems simple and fast. It uses a low-code approach where you write just dozens of lines of YAML configuration instead of complex code to create sophisticated AI workflows with conditional logic and loops. The framework includes a visual development environment where you can drag-and-drop to build pipelines, adjust parameters in real-time, and instantly convert your logic into interactive chat applications. This means you can deploy powerful AI systems that ground answers in your own data—reducing hallucinations and improving accuracy—without needing extensive coding expertise or lengthy development cycles. https://github.com/OpenBMB/UltraRAG

#python#audio_generation#diffusion#image_generation#inference#model_serving#multimodal#pytorch#transformer#video_generation vLLM-Omni is a free, open-source tool that makes serving AI models for text, images, videos, and audio fast, easy, and cheap. It builds on vLLM for top speed using smart memory tricks, overlapping tasks, and flexible resource sharing across GPUs. You get 2x higher throughput, 35% less delay, and simple setup with Hugging Face models via OpenAI API—perfect for building quick multi-modal apps like chatbots or media generators without high costs. https://github.com/vllm-project/vllm-omni

#rust#artificial_intelligence#big_data#data_engineering#distributed_computing#machine_learning#multimodal#python#rust Daft is a powerful, easy-to-use data engine that lets you process large-scale data using Python or SQL with high speed and efficiency. It supports complex data types like images and tensors, works well interactively for quick data exploration, and can scale to huge cloud clusters using Ray. Daft integrates smoothly with cloud storage and data catalogs, making it ideal for data engineering, analytics, and machine learning workflows. By using Daft, you can handle big, multimodal datasets faster and more flexibly, improving your ability to analyze and prepare data for AI models without complex setup or slowdowns. https://github.com/Eventual-Inc/Daft

#typescript#agents#ai#embedders#genkit#llm#machine_learning#multimodal#rag#vector_database Genkit is an open-source framework by Google Firebase that helps you easily build AI-powered apps using a single interface to connect many AI models like Google Gemini, OpenAI, and Anthropic. It supports JavaScript/TypeScript (stable), Go (beta), and Python (alpha), letting you create chatbots, automations, and recommendations quickly with simple code. Genkit works well with web and mobile platforms, offers tools for testing and debugging AI features locally, and lets you deploy and monitor your AI apps on Firebase or other cloud services. This saves you time and effort in developing and managing AI applications efficiently. https://github.com/firebase/genkit

#python#ai#ai_art#art#asset_generator#chatbot#deep_learning#desktop_app#image_generation#mistral#multimodal#privacy#pygame#pyside6#python#self_hosted#speech_to_text#stable_diffusion#text_to_image#text_to_speech#text_to_speech_app AI Runner is a tool that lets you use AI on your own computer without needing the internet. It can do many things like **voice chatbots**, **text-to-image** generation, and **image editing**. You can also make AI personalities for more interesting conversations. It runs fast and securely, keeping your data private. To use AI Runner, you need a good computer with a strong GPU, like an NVIDIA RTX 3060 or better. This helps keep your data safe and makes AI tasks faster. https://github.com/Capsize-Games/airunner

#python#asr#deeplearning#generative_ai#large_language_models#machine_translation#multimodal#neural_networks#speaker_diariazation#speaker_recognition#speech_synthesis#speech_translation#tts NVIDIA NeMo is a powerful, easy-to-use platform for building, customizing, and deploying generative AI models like large language models (LLMs), vision language models, and speech AI. It lets you quickly train and fine-tune models using pre-built code and checkpoints, supports the latest model architectures, and works on cloud, data center, or edge environments. NeMo 2.0 is even more flexible and scalable, with Python-based configuration and modular design, making it simple to experiment and scale up. The main benefit is that you can create advanced AI applications faster, with less effort, and at lower cost, while getting high performance and easy deployment options[1][2][3]. https://github.com/NVIDIA/NeMo

#python#apple_silicon#audio_processing#mlx#multimodal#speech_recognition#speech_synthesis#speech_to_text#text_to_speech#transformers MLX-Audio is a powerful tool for converting text into speech and speech into new audio. It works well on Apple Silicon devices, like M-series chips, making it fast and efficient. You can choose from different languages and voices, and even adjust how fast the speech is. It also includes a web interface where you can see audio in 3D and play your own files. This tool is helpful for making audiobooks, interactive media, and personal projects because it's easy to use and provides high-quality audio quickly. https://github.com/Blaizzy/mlx-audio