Best AI tools for< Stream Inference >

vLLM is a fast and easy-to-use library for LLM inference and serving. It offers state-of-the-art serving throughput, efficient management of attention key and value memory, continuous batching of incoming requests, fast model execution with CUDA/HIP graph, and various decoding algorithms. The tool is flexible with seamless integration with popular HuggingFace models, high-throughput serving, tensor parallelism support, and streaming outputs. It supports NVIDIA GPUs and AMD GPUs, Prefix caching, and Multi-lora. vLLM is designed to provide fast and efficient LLM serving for everyone.

Local AI Playground is a free and open-source native app designed for AI management, verification, and inferencing. It allows users to experiment with AI offline in a private environment without the need for a GPU. The application is memory-efficient and compact, with features like CPU inferencing, model management, and digest verification. Users can start a local streaming server for AI inferencing with just two clicks. Local AI Playground aims to simplify the AI development process and provide a user-friendly platform for AI enthusiasts.

Outspeed is a platform for Realtime Voice and Video AI applications, providing networking and inference infrastructure to build fast, real-time voice and video AI apps. It offers tools for intelligence across industries, including Voice AI, Streaming Avatars, Visual Intelligence, Meeting Copilot, and the ability to build custom multimodal AI solutions. Outspeed is designed by engineers from Google and MIT, offering robust streaming infrastructure, low-latency inference, instant deployment, and enterprise-ready compliance with regulations such as SOC2, GDPR, and HIPAA.

Tangia is an interactive streaming platform that offers custom TTS interactions, alerts, media sharing, monitor overlay, and Discord integration for streamers. It provides streamers with a wide range of tools to engage their audience, including AI TTS in their own voice, memes showing up on stream, hype parties at every level reached, adding soundbites from Twitch clips, and leaderboards with challenges. Tangia aims to enhance the streaming experience by enabling streamers to create interactive and entertaining content effortlessly.

Be.Live is a livestreaming studio that allows users to create beautiful livestreams and repurpose them into shorter videos and podcasts. It enables users to host live talk shows, invite guests on screen, and customize their streams with branding elements. With features like screen sharing, on-screen elements, and mobile streaming app, Be.Live aims to help coaches, hosts, infopreneurs, and influencers consistently produce and repurpose video content to engage their audience effectively.

Vengo AI is a cutting-edge B2B SaaS platform that democratizes AI creation, making it accessible for everyone, from influencers and brands to entrepreneurs and businesses. The platform offers a white glove service that allows users to easily integrate sophisticated AI identities into their websites with just one line of code. By joining the innovative community, members unlock the potential to create, customize, and monetize their digital twins, significantly enhancing their digital presence and generating new streams of passive income. Vengo AI acts as a dedicated agency, providing a free service to help users monetize their content effortlessly by creating personalized, monetizable digital twins using advanced AI. The platform excels in providing advanced customization and personalization for AI identities, ensuring that each digital twin mirrors the unique voice and personality of its creator. Vengo AI also offers tools to strategically enhance brands by leveraging the power of AI, enabling meaningful engagement with the audience.

Beam Eye Tracker is an AI-powered webcam eye tracking software designed for PC gamers to enhance their gaming experience. It allows users to turn their webcam into an eye tracker, providing 6DoF head and eye tracking capabilities in over 200 PC games. The software offers features such as Eye Tracking Overlay for gameplay analysis, AI-powered performance comparable to high-end hardware devices, and compatibility with various webcams and mobile devices. Beam Eye Tracker aims to provide a seamless and immersive gaming experience without the need for bulky hardware trackers.

VidLab Store is an AI-powered platform offering premium tools to simplify video creation and editing processes. The platform provides various AI-driven solutions such as AI Short Video Generator, AI Voiceover for Video Creators, Embed TikTok Live for WordPress, Realistic Text-to-Speech SaaS, and TikTok Video Downloader Without Watermark for WordPress. Users can enhance their video content with advanced AI technology, making the video creation process efficient and effective.

Bento is a personalized 'Link in Bio' platform that allows users to showcase all aspects of their creativity in one beautiful page. Users can display their videos, podcasts, newsletters, photos, paid products, streams, and calendar all in one place, eliminating the need for multiple links. Bento is designed for creatives to easily share their content with their audience and monetize their work. The platform is free to use and offers a unique link for each user to customize their page.

BrandGhost is an all-in-one social media management tool designed for creators to grow their following and engagement. It offers features such as post scheduling, topic streams, unified feed, visualizations, and content recycling. With BrandGhost, users can automate content posting, manage social interactions efficiently, and maintain brand consistency across multiple platforms.

AutomaticShorts is an AI-powered platform that enables users to run a faceless channel on autopilot, leveraging their following to generate passive income through ad revenue, sponsors, affiliates, and more. The platform automates the process of shooting, voicing, and editing videos, allowing creators to focus on monetization strategies and audience engagement. With features like series creation, video customization, performance analysis, and passive income generation, AutomaticShorts empowers creators to effortlessly grow their online presence and revenue streams.

Stream is an AI application developed by the Tensorplex Team to showcase the capabilities of existing Bittensor Subnets in powering consumer Web3 platforms. The application is designed to provide precise summaries and deep insights by utilizing the TPLX-LLM model. Stream offers a curated list of podcasts that are summarized using the Bittensor Network.

Stream Chat A.I. is an AI-powered Twitch chat bot that provides a smart and engaging chat experience for communities. It offers unique features such as a fully customizable chat-bot with a unique personality, bespoke overlays for multimedia editing, and custom !commands for boosting interaction. The application is designed to enhance the Twitch streaming experience by providing dynamic and engaging content for streamers and viewers.

Stream.Estate is a Real Estate Data API application that provides comprehensive property data analytics and market insights through a powerful API. Users can access real-time property insights to make data-driven decisions. The application offers features such as property matching, valuation systems, market intelligence, portfolio analytics, property search API, price evolution analytics, real-time property alerts, smart property sourcing, intelligent valuation engine, and automated lead generation. Stream.Estate is trusted by leading PropTech companies worldwide and offers simple pricing plans for different usage levels.

Yakkr Growth is an AI-powered platform designed to help streamers grow their online presence effortlessly. The platform automates time-consuming tasks such as creating engaging social media content, optimizing stream titles, suggesting hashtags, and generating event ideas. It also offers mentorship, consultancy, and a community for streamers to collaborate and succeed together. With Yakkr Growth, streamers can save time, boost motivation, and increase their chances of going viral, ultimately helping them attract more viewers and earn income on platforms like Twitch.

Auto Streamer & Course Maker is an AI tool that allows users to create and stream educational content effortlessly. It enables users to generate complete web courses with audio, supports over 50 languages, and offers customizable course presentation options. With Auto Streamer, users can break language barriers, personalize teaching portals, and control course density. The tool is visually appealing, with dark and light mode options, and allows users to define course length and content depth. Auto Streamer requires an OpenAI API key for text and audio content generation.

Wave.video is an online video editor and hosting platform that allows users to create, edit, and host videos. It offers a wide range of features, including a live streaming studio, video recorder, stock library, and video hosting. Wave.video is easy to use and affordable, making it a great option for businesses and individuals who need to create high-quality videos.

Swapface is an AI-powered face swapping app that lets you create realistic face swaps with just a few taps. With Swapface, you can swap your face with celebrities, friends, or even animals. The app uses advanced artificial intelligence to seamlessly blend your face onto another person's body, creating hilarious and shareable results.

Magicam is an advanced AI tool that offers the ultimate real-time face swap solution. It uses cutting-edge technology to seamlessly swap faces in real-time, providing users with a fun and engaging experience. With Magicam, you can transform your face into anyone else's instantly, whether it's a celebrity, a friend, or a fictional character. The application is user-friendly and requires no technical expertise to use. It is perfect for creating entertaining videos, taking hilarious selfies, or simply having fun with friends and family.

NewsDeck is an AI-powered news analysis tool that allows users to find, filter, and analyze thousands of articles daily. It leverages OneSub's intelligent newsreader AI to provide real-time access to the global news cycle. Users can stream topics of interest, access news stories related to over 500,000 entities, and explore correlated coverage across various publishers. The platform emphasizes ethical and transparent AI decision-making processes and is developed by a small team dedicated to revolutionizing news consumption.

superduper.io is a Python framework that integrates AI models, APIs, and vector search engines directly with existing databases. It allows hosting of models, streaming inference, and scalable model training/fine-tuning. Key features include integration of AI with data infrastructure, inference via change-data-capture, scalable model training, model chaining, simple Python interface, Python-first approach, working with difficult data types, feature storing, and vector search capabilities. The tool enables users to turn their existing databases into centralized repositories for managing AI model inputs and outputs, as well as conducting vector searches without the need for specialized databases.

Ax is a Typescript library that allows users to build intelligent agents inspired by agentic workflows and the Stanford DSP paper. It seamlessly integrates with multiple Large Language Models (LLMs) and VectorDBs to create RAG pipelines or collaborative agents capable of solving complex problems. The library offers advanced features such as streaming validation, multi-modal DSP, and automatic prompt tuning using optimizers. Users can easily convert documents of any format to text, perform smart chunking, embedding, and querying, and ensure output validation while streaming. Ax is production-ready, written in Typescript, and has zero dependencies.

Fueling-Ambitions-Via-Book-Discoveries is an Advanced Machine Learning & AI Course designed for students, professionals, and AI researchers. The course integrates rigorous theoretical foundations with practical coding exercises, ensuring learners develop a deep understanding of AI algorithms and their applications in finance, healthcare, robotics, NLP, cybersecurity, and more. Inspired by MIT, Stanford, and Harvard’s AI programs, it combines academic research rigor with industry-standard practices used by AI engineers at companies like Google, OpenAI, Facebook AI, DeepMind, and Tesla. Learners can learn 50+ AI techniques from top Machine Learning & Deep Learning books, code from scratch with real-world datasets, projects, and case studies, and focus on ML Engineering & AI Deployment using Django & Streamlit. The course also offers industry-relevant projects to build a strong AI portfolio.

Kafka-ML is a framework designed to manage the pipeline of Tensorflow/Keras and PyTorch machine learning models on Kubernetes. It enables the design, training, and inference of ML models with datasets fed through Apache Kafka, connecting them directly to data streams like those from IoT devices. The Web UI allows easy definition of ML models without external libraries, catering to both experts and non-experts in ML/AI.

lite_llama is a llama model inference lite framework by triton. It offers accelerated inference for llama3, Qwen2.5, and Llava1.5 models with up to 4x speedup compared to transformers. The framework supports top-p sampling, stream output, GQA, and cuda graph optimizations. It also provides efficient dynamic management for kv cache, operator fusion, and custom operators like rmsnorm, rope, softmax, and element-wise multiplication using triton kernels.

Qwen-TensorRT-LLM is a project developed for the NVIDIA TensorRT Hackathon 2023, focusing on accelerating inference for the Qwen-7B-Chat model using TRT-LLM. The project offers various functionalities such as FP16/BF16 support, INT8 and INT4 quantization options, Tensor Parallel for multi-GPU parallelism, web demo setup with gradio, Triton API deployment for maximum throughput/concurrency, fastapi integration for openai requests, CLI interaction, and langchain support. It supports models like qwen2, qwen, and qwen-vl for both base and chat models. The project also provides tutorials on Bilibili and blogs for adapting Qwen models in NVIDIA TensorRT-LLM, along with hardware requirements and quick start guides for different model types and quantization methods.

Llama3.java is a practical Llama 3 inference tool implemented in a single Java file. It serves as the successor of llama2.java and is designed for testing and tuning compiler optimizations and features on the JVM, especially for the Graal compiler. The tool features a GGUF format parser, Llama 3 tokenizer, Grouped-Query Attention inference, support for Q8_0 and Q4_0 quantizations, fast matrix-vector multiplication routines using Java's Vector API, and a simple CLI with 'chat' and 'instruct' modes. Users can download quantized .gguf files from huggingface.co for model usage and can also manually quantize to pure 'Q4_0'. The tool requires Java 21+ and supports running from source or building a JAR file for execution. Performance benchmarks show varying tokens/s rates for different models and implementations on different hardware setups.

FastRTC is a real-time communication library for Python that allows users to turn any Python function into a real-time audio and video stream over WebRTC or WebSockets. It provides features like automatic voice detection, UI launching, WebRTC support, WebSocket support, telephone support, and customizable backend for production applications. The library offers various examples and usage scenarios for audio and video streaming, object detection, voice APIs, chat applications, and more.

Candle-vllm is an efficient and easy-to-use platform designed for inference and serving local LLMs, featuring an OpenAI compatible API server. It offers a highly extensible trait-based system for rapid implementation of new module pipelines, streaming support in generation, efficient management of key-value cache with PagedAttention, and continuous batching. The tool supports chat serving for various models and provides a seamless experience for users to interact with LLMs through different interfaces.

FastLLM is a high-performance large model inference library implemented in pure C++ with no third-party dependencies. Models of 6-7B size can run smoothly on Android devices. Deployment communication QQ group: 831641348

ScaleLLM is a cutting-edge inference system engineered for large language models (LLMs), meticulously designed to meet the demands of production environments. It extends its support to a wide range of popular open-source models, including Llama3, Gemma, Bloom, GPT-NeoX, and more. ScaleLLM is currently undergoing active development. We are fully committed to consistently enhancing its efficiency while also incorporating additional features. Feel free to explore our **_Roadmap_** for more details. ## Key Features * High Efficiency: Excels in high-performance LLM inference, leveraging state-of-the-art techniques and technologies like Flash Attention, Paged Attention, Continuous batching, and more. * Tensor Parallelism: Utilizes tensor parallelism for efficient model execution. * OpenAI-compatible API: An efficient golang rest api server that compatible with OpenAI. * Huggingface models: Seamless integration with most popular HF models, supporting safetensors. * Customizable: Offers flexibility for customization to meet your specific needs, and provides an easy way to add new models. * Production Ready: Engineered with production environments in mind, ScaleLLM is equipped with robust system monitoring and management features to ensure a seamless deployment experience.

TurboSeek is an open source AI search engine powered by Together.ai. It utilizes Next.js with Tailwind for the app router, Together AI for LLM inference, Mixtral 8x7B & Llama-3 for the LLMs, Bing for the search API, Helicone for observability, and Plausible for website analytics. The tool takes a user's question, queries the Bing search API for top results, scrapes text from the links, sends the question and context to Mixtral-8x7B, and generates follow-up questions using Llama-3-8B. Future tasks include optimizing source parsing, ignoring video links, adding regeneration option, ensuring proper citations, enabling sharing, implementing scrolling during answers, fixing hard refresh, adding caching with upstash redis, incorporating advanced RAG techniques, and adding authentication with Clerk and postgres/prisma.

GLake is an acceleration library and utilities designed to optimize GPU memory management and IO transmission for AI large model training and inference. It addresses challenges such as GPU memory bottleneck and IO transmission bottleneck by providing efficient memory pooling, sharing, and tiering, as well as multi-path acceleration for CPU-GPU transmission. GLake is easy to use, open for extension, and focuses on improving training throughput, saving inference memory, and accelerating IO transmission. It offers features like memory fragmentation reduction, memory deduplication, and built-in security mechanisms for troubleshooting GPU memory issues.

ONNX Runtime Generative AI is a library that provides the generative AI loop for ONNX models, including inference with ONNX Runtime, logits processing, search and sampling, and KV cache management. Users can call a high level `generate()` method, or run each iteration of the model in a loop. It supports greedy/beam search and TopP, TopK sampling to generate token sequences, has built in logits processing like repetition penalties, and allows for easy custom scoring.

FlashInfer is a library for Language Languages Models that provides high-performance implementation of LLM GPU kernels such as FlashAttention, PageAttention and LoRA. FlashInfer focus on LLM serving and inference, and delivers state-the-art performance across diverse scenarios.

This project provides a proof of concept for deploying a scalable, serverless LLM Generative AI inference engine on AWS Lambda. It leverages the llama.cpp project to enable the usage of more accessible CPU and RAM configurations instead of limited and expensive GPU capabilities. By deploying a container with the llama.cpp converted models onto AWS Lambda, this project offers the advantages of scale, minimizing cost, and maximizing compute availability. The project includes AWS CDK code to create and deploy a Lambda function leveraging your model of choice, with a FastAPI frontend accessible from a Lambda URL. It is important to note that you will need ggml quantized versions of your model and model sizes under 6GB, as your inference RAM requirements cannot exceed 9GB or your Lambda function will fail.

The collection of pre-trained, state-of-the-art AI models. ailia SDK is a self-contained, cross-platform, high-speed inference SDK for AI. The ailia SDK provides a consistent C++ API across Windows, Mac, Linux, iOS, Android, Jetson, and Raspberry Pi platforms. It also supports Unity (C#), Python, Rust, Flutter(Dart) and JNI for efficient AI implementation. The ailia SDK makes extensive use of the GPU through Vulkan and Metal to enable accelerated computing. # Supported models 323 models as of April 8th, 2024

Venice is a derived data storage platform, providing the following characteristics: 1. High throughput asynchronous ingestion from batch and streaming sources (e.g. Hadoop and Samza). 2. Low latency online reads via remote queries or in-process caching. 3. Active-active replication between regions with CRDT-based conflict resolution. 4. Multi-cluster support within each region with operator-driven cluster assignment. 5. Multi-tenancy, horizontal scalability and elasticity within each cluster. The above makes Venice particularly suitable as the stateful component backing a Feature Store, such as Feathr. AI applications feed the output of their ML training jobs into Venice and then query the data for use during online inference workloads.

YoMo is an open-source LLM Function Calling Framework for building Geo-distributed AI applications. It is built atop QUIC Transport Protocol and Stateful Serverless architecture, making AI applications low-latency, reliable, secure, and easy. The framework focuses on providing low-latency, secure, stateful serverless functions that can be distributed geographically to bring AI inference closer to end users. It offers features such as low-latency communication, security with TLS v1.3, stateful serverless functions for faster GPU processing, geo-distributed architecture, and a faster-than-real-time codec called Y3. YoMo enables developers to create and deploy stateful serverless functions for AI inference in a distributed manner, ensuring quick responses to user queries from various locations worldwide.

BentoVLLM is an example project demonstrating how to serve and deploy open-source Large Language Models using vLLM, a high-throughput and memory-efficient inference engine. It provides a basis for advanced code customization, such as custom models, inference logic, or vLLM options. The project allows for simple LLM hosting with OpenAI compatible endpoints without the need to write any code. Users can interact with the server using Swagger UI or other methods, and the service can be deployed to BentoCloud for better management and scalability. Additionally, the repository includes integration examples for different LLM models and tools.

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