TEN-Agent

TEN Agent is an open-source multimodal agent powered by the world’s first real-time multimodal framework, TEN Framework. It offers high-performance real-time multimodal interactions, multi-language and multi-platform support, edge-cloud integration, flexibility beyond model limitations, and real-time agent state management. Users can easily build complex AI applications through drag-and-drop programming, integrating audio-visual tools, databases, RAG, and more.

ASTRA is an open-source platform designed for developing applications utilizing large language models. It merges the ideas of Backend-as-a-Service and LLM operations, allowing developers to swiftly create production-ready generative AI applications. Additionally, it empowers non-technical users to engage in defining and managing data operations for AI applications. With ASTRA, you can easily create real-time, multi-modal AI applications with low latency, even without any coding knowledge.

sfdx-hardis is a toolbox for Salesforce DX, developed by Cloudity, that simplifies tasks which would otherwise take minutes or hours to complete manually. It enables users to define complete CI/CD pipelines for Salesforce projects, backup metadata, and monitor any Salesforce org. The tool offers a wide range of commands that can be accessed via the command line interface or through a Visual Studio Code extension. Additionally, sfdx-hardis provides Docker images for easy integration into CI workflows. The tool is designed to be natively compliant with various platforms and tools, making it a versatile solution for Salesforce developers.

LangChain is an amazing framework to get LLM projects done in a matter of no time, and the ecosystem is growing fast. Here is an attempt to keep track of the initiatives around LangChain. Subscribe to the newsletter to stay informed about the Awesome LangChain. We send a couple of emails per month about the articles, videos, projects, and tools that grabbed our attention Contributions welcome. Add links through pull requests or create an issue to start a discussion. Please read the contribution guidelines before contributing.

Databend is an open-source cloud data warehouse built in Rust, offering fast query execution and data ingestion for complex analysis of large datasets. It integrates with major cloud platforms, provides high performance with AI-powered analytics, supports multiple data formats, ensures data integrity with ACID transactions, offers flexible indexing options, and features community-driven development. Users can try Databend through a serverless cloud or Docker installation, and perform tasks such as data import/export, querying semi-structured data, managing users/databases/tables, and utilizing AI functions.

Intel® Neural Compressor is an open-source Python library that supports popular model compression techniques such as quantization, pruning (sparsity), distillation, and neural architecture search on mainstream frameworks such as TensorFlow, PyTorch, ONNX Runtime, and MXNet. It provides key features, typical examples, and open collaborations, including support for a wide range of Intel hardware, validation of popular LLMs, and collaboration with cloud marketplaces, software platforms, and open AI ecosystems.

Open-Sora-Plan is a project that aims to create a simple and scalable repo to reproduce Sora (OpenAI, but we prefer to call it "ClosedAI"). The project is still in its early stages, but the team is working hard to improve it and make it more accessible to the open-source community. The project is currently focused on training an unconditional model on a landscape dataset, but the team plans to expand the scope of the project in the future to include text2video experiments, training on video2text datasets, and controlling the model with more conditions.

Databend is an open-source cloud data warehouse that serves as a cost-effective alternative to Snowflake. With its focus on fast query execution and data ingestion, it's designed for complex analysis of the world's largest datasets.

Free-one-api is a tool that allows access to all LLM reverse engineering libraries in a standard OpenAI API format. It supports automatic load balancing, Web UI, stream mode, multiple LLM reverse libraries, heartbeat detection mechanism, automatic disabling of unavailable channels, and runtime log recording. The tool is designed to work with the 'one-api' project and 'songquanpeng/one-api' for accessing official interfaces of various LLMs (paid). Contributors are needed to test adapters, find new reverse engineering libraries, and submit PRs.

Intel® Extension for Transformers is an innovative toolkit designed to accelerate GenAI/LLM everywhere with the optimal performance of Transformer-based models on various Intel platforms, including Intel Gaudi2, Intel CPU, and Intel GPU. The toolkit provides the below key features and examples: * Seamless user experience of model compressions on Transformer-based models by extending [Hugging Face transformers](https://github.com/huggingface/transformers) APIs and leveraging [Intel® Neural Compressor](https://github.com/intel/neural-compressor) * Advanced software optimizations and unique compression-aware runtime (released with NeurIPS 2022's paper [Fast Distilbert on CPUs](https://arxiv.org/abs/2211.07715) and [QuaLA-MiniLM: a Quantized Length Adaptive MiniLM](https://arxiv.org/abs/2210.17114), and NeurIPS 2021's paper [Prune Once for All: Sparse Pre-Trained Language Models](https://arxiv.org/abs/2111.05754)) * Optimized Transformer-based model packages such as [Stable Diffusion](examples/huggingface/pytorch/text-to-image/deployment/stable_diffusion), [GPT-J-6B](examples/huggingface/pytorch/text-generation/deployment), [GPT-NEOX](examples/huggingface/pytorch/language-modeling/quantization#2-validated-model-list), [BLOOM-176B](examples/huggingface/pytorch/language-modeling/inference#BLOOM-176B), [T5](examples/huggingface/pytorch/summarization/quantization#2-validated-model-list), [Flan-T5](examples/huggingface/pytorch/summarization/quantization#2-validated-model-list), and end-to-end workflows such as [SetFit-based text classification](docs/tutorials/pytorch/text-classification/SetFit_model_compression_AGNews.ipynb) and [document level sentiment analysis (DLSA)](workflows/dlsa) * [NeuralChat](intel_extension_for_transformers/neural_chat), a customizable chatbot framework to create your own chatbot within minutes by leveraging a rich set of [plugins](https://github.com/intel/intel-extension-for-transformers/blob/main/intel_extension_for_transformers/neural_chat/docs/advanced_features.md) such as [Knowledge Retrieval](./intel_extension_for_transformers/neural_chat/pipeline/plugins/retrieval/README.md), [Speech Interaction](./intel_extension_for_transformers/neural_chat/pipeline/plugins/audio/README.md), [Query Caching](./intel_extension_for_transformers/neural_chat/pipeline/plugins/caching/README.md), and [Security Guardrail](./intel_extension_for_transformers/neural_chat/pipeline/plugins/security/README.md). This framework supports Intel Gaudi2/CPU/GPU. * [Inference](https://github.com/intel/neural-speed/tree/main) of Large Language Model (LLM) in pure C/C++ with weight-only quantization kernels for Intel CPU and Intel GPU (TBD), supporting [GPT-NEOX](https://github.com/intel/neural-speed/tree/main/neural_speed/models/gptneox), [LLAMA](https://github.com/intel/neural-speed/tree/main/neural_speed/models/llama), [MPT](https://github.com/intel/neural-speed/tree/main/neural_speed/models/mpt), [FALCON](https://github.com/intel/neural-speed/tree/main/neural_speed/models/falcon), [BLOOM-7B](https://github.com/intel/neural-speed/tree/main/neural_speed/models/bloom), [OPT](https://github.com/intel/neural-speed/tree/main/neural_speed/models/opt), [ChatGLM2-6B](https://github.com/intel/neural-speed/tree/main/neural_speed/models/chatglm), [GPT-J-6B](https://github.com/intel/neural-speed/tree/main/neural_speed/models/gptj), and [Dolly-v2-3B](https://github.com/intel/neural-speed/tree/main/neural_speed/models/gptneox). Support AMX, VNNI, AVX512F and AVX2 instruction set. We've boosted the performance of Intel CPUs, with a particular focus on the 4th generation Intel Xeon Scalable processor, codenamed [Sapphire Rapids](https://www.intel.com/content/www/us/en/products/docs/processors/xeon-accelerated/4th-gen-xeon-scalable-processors.html).

AIdea is an app that integrates mainstream large language models and drawing models, developed using Flutter. The code is completely open-source and supports various functions such as GPT-3.5, GPT-4 from OpenAI, Claude instant, Claude 2.1 from Anthropic, Gemini Pro and visual language models from Google, as well as various Chinese and open-source models. It also supports features like text-to-image, super-resolution, coloring black and white images, artistic fonts, artistic QR codes, and more.

ComfyUI for Photoshop is a plugin that integrates with an AI-powered image generation system to enhance the Photoshop experience with features like unlimited generative fill, customizable back-end, AI-powered artistry, and one-click transformation. The plugin requires a minimum of 6GB graphics memory and 12GB RAM. Users can install the plugin and set up the ComfyUI workflow using provided links and files. Additionally, specific files like Check points, Loras, and Detailer Lora are required for different functionalities. Support and contributions are encouraged through GitHub.

Chat-xiuliu is a bidirectional voice assistant powered by ChatGPT, capable of accessing the internet, executing code, reading/writing files, and supporting GPT-4V's image recognition feature. It can also call DALL·E 3 to generate images. The project is a fork from a background of a virtual cat girl named Xiuliu, with removed live chat interaction and added voice input. It can receive questions from microphone or interface, answer them vocally, upload images and PDFs, process tasks through function calls, remember conversation content, search the web, generate images using DALL·E 3, read/write local files, execute JavaScript code in a sandbox, open local files or web pages, customize the cat girl's speaking style, save conversation screenshots, and support Azure OpenAI and other API endpoints in openai format. It also supports setting proxies and various AI models like GPT-4, GPT-3.5, and DALL·E 3.

智元 Fast API is a one-stop API management system that unifies various LLM APIs in terms of format, standards, and management to achieve the ultimate in functionality, performance, and user experience. It includes features such as model management with intelligent and regex matching, backup model functionality, key management, proxy management, company management, user management, and chat management for both admin and user ends. The project supports cluster deployment, multi-site deployment, and cross-region deployment. It also provides a public API site for registration with a contact to the author for a 10 million quota. The tool offers a comprehensive dashboard, model management, application management, key management, and chat management functionalities for users.

L3AGI is an open-source tool that enables AI Assistants to collaborate together as effectively as human teams. It provides a robust set of functionalities that empower users to design, supervise, and execute both autonomous AI Assistants and Teams of Assistants. Key features include the ability to create and manage Teams of AI Assistants, design and oversee standalone AI Assistants, equip AI Assistants with the ability to retain and recall information, connect AI Assistants to an array of data sources for efficient information retrieval and processing, and employ curated sets of tools for specific tasks. L3AGI also offers a user-friendly interface, APIs for integration with other systems, and a vibrant community for support and collaboration.

Aiken is a modern smart contract platform for Cardano, providing a user-friendly environment for developing and deploying smart contracts. It supports Linux, MacOS, and Windows operating systems. Aiken is designed to simplify the process of creating smart contracts on the Cardano blockchain, offering a seamless experience for developers. The platform is named after Howard Aiken, an American physicist and computing pioneer.

TEN Agent is an open-source multimodal agent powered by the world’s first real-time multimodal framework, TEN Framework. It offers high-performance real-time multimodal interactions, multi-language and multi-platform support, edge-cloud integration, flexibility beyond model limitations, and real-time agent state management. Users can easily build complex AI applications through drag-and-drop programming, integrating audio-visual tools, databases, RAG, and more.

Griptape is a modular Python framework for building AI-powered applications that securely connect to your enterprise data and APIs. It offers developers the ability to maintain control and flexibility at every step. Griptape's core components include Structures (Agents, Pipelines, and Workflows), Tasks, Tools, Memory (Conversation Memory, Task Memory, and Meta Memory), Drivers (Prompt and Embedding Drivers, Vector Store Drivers, Image Generation Drivers, Image Query Drivers, SQL Drivers, Web Scraper Drivers, and Conversation Memory Drivers), Engines (Query Engines, Extraction Engines, Summary Engines, Image Generation Engines, and Image Query Engines), and additional components (Rulesets, Loaders, Artifacts, Chunkers, and Tokenizers). Griptape enables developers to create AI-powered applications with ease and efficiency.

AI-in-a-Box is a curated collection of solution accelerators that can help engineers establish their AI/ML environments and solutions rapidly and with minimal friction, while maintaining the highest standards of quality and efficiency. It provides essential guidance on the responsible use of AI and LLM technologies, specific security guidance for Generative AI (GenAI) applications, and best practices for scaling OpenAI applications within Azure. The available accelerators include: Azure ML Operationalization in-a-box, Edge AI in-a-box, Doc Intelligence in-a-box, Image and Video Analysis in-a-box, Cognitive Services Landing Zone in-a-box, Semantic Kernel Bot in-a-box, NLP to SQL in-a-box, Assistants API in-a-box, and Assistants API Bot in-a-box.

The Spring AI project provides a Spring-friendly API and abstractions for developing AI applications. It offers a portable client API for interacting with generative AI models, enabling developers to easily swap out implementations and access various models like OpenAI, Azure OpenAI, and HuggingFace. Spring AI also supports prompt engineering, providing classes and interfaces for creating and parsing prompts, as well as incorporating proprietary data into generative AI without retraining the model. This is achieved through Retrieval Augmented Generation (RAG), which involves extracting, transforming, and loading data into a vector database for use by AI models. Spring AI's VectorStore abstraction allows for seamless transitions between different vector database implementations.

RAGStack is an out-of-the-box solution simplifying Retrieval Augmented Generation (RAG) in GenAI apps. RAGStack includes the best open-source for implementing RAG, giving developers a comprehensive Gen AI Stack leveraging LangChain, CassIO, and more. RAGStack leverages the LangChain ecosystem and is fully compatible with LangSmith for monitoring your AI deployments.

Breadboard is a library for prototyping generative AI applications. It is inspired by the hardware maker community and their boundless creativity. Breadboard makes it easy to wire prototypes and share, remix, reuse, and compose them. The library emphasizes ease and flexibility of wiring, as well as modularity and composability.

Cloudflare-ai-web is a lightweight and easy-to-use tool that allows you to quickly deploy a multi-modal AI platform using Cloudflare Workers AI. It supports serverless deployment, password protection, and local storage of chat logs. With a size of only ~638 kB gzip, it is a great option for building AI-powered applications without the need for a dedicated server.

AppBuilder SDK is a one-stop development tool for AI native applications, providing basic cloud resources, AI capability engine, Qianfan large model, and related capability components to improve the development efficiency of AI native applications.

Sweep is an AI junior developer that turns bugs and feature requests into code changes. It automatically handles developer experience improvements like adding type hints and improving test coverage.

The Teams AI Library is a software development kit (SDK) that helps developers create bots that can interact with Teams and Microsoft 365 applications. It is built on top of the Bot Framework SDK and simplifies the process of developing bots that interact with Teams' artificial intelligence capabilities. The SDK is available for JavaScript/TypeScript, .NET, and Python.

This guide is dedicated to Large Language Models (LLMs) that you can run on your home computer. It assumes your PC is a lower-end, non-gaming setup.

Supercharge WordPress Content Workflows and Engagement with Artificial Intelligence. Tap into leading cloud-based services like OpenAI, Microsoft Azure AI, Google Gemini and IBM Watson to augment your WordPress-powered websites. Publish content faster while improving SEO performance and increasing audience engagement. ClassifAI integrates Artificial Intelligence and Machine Learning technologies to lighten your workload and eliminate tedious tasks, giving you more time to create original content that matters.

Chatbot UI is an open-source AI chat app that allows users to create and deploy their own AI chatbots. It is easy to use and can be customized to fit any need. Chatbot UI is perfect for businesses, developers, and anyone who wants to create a chatbot.

BricksLLM is a cloud native AI gateway written in Go. Currently, it provides native support for OpenAI, Anthropic, Azure OpenAI and vLLM. BricksLLM aims to provide enterprise level infrastructure that can power any LLM production use cases. Here are some use cases for BricksLLM: * Set LLM usage limits for users on different pricing tiers * Track LLM usage on a per user and per organization basis * Block or redact requests containing PIIs * Improve LLM reliability with failovers, retries and caching * Distribute API keys with rate limits and cost limits for internal development/production use cases * Distribute API keys with rate limits and cost limits for students

uAgents is a Python library developed by Fetch.ai that allows for the creation of autonomous AI agents. These agents can perform various tasks on a schedule or take action on various events. uAgents are easy to create and manage, and they are connected to a fast-growing network of other uAgents. They are also secure, with cryptographically secured messages and wallets.

Griptape is a modular Python framework for building AI-powered applications that securely connect to your enterprise data and APIs. It offers developers the ability to maintain control and flexibility at every step. Griptape's core components include Structures (Agents, Pipelines, and Workflows), Tasks, Tools, Memory (Conversation Memory, Task Memory, and Meta Memory), Drivers (Prompt and Embedding Drivers, Vector Store Drivers, Image Generation Drivers, Image Query Drivers, SQL Drivers, Web Scraper Drivers, and Conversation Memory Drivers), Engines (Query Engines, Extraction Engines, Summary Engines, Image Generation Engines, and Image Query Engines), and additional components (Rulesets, Loaders, Artifacts, Chunkers, and Tokenizers). Griptape enables developers to create AI-powered applications with ease and efficiency.