Awesome LLM plaza is a curated list of awesome LLM papers, projects, and resources. It is updated daily and includes resources from a variety of sources, including huggingface daily papers, twitter, github trending, paper with code, weixin, etc.

The 'LLM Applications with Java and Spring AI' repository provides samples demonstrating how to build Java applications powered by Generative AI and Large Language Models (LLMs) using Spring AI. It includes projects for question answering, chat completion models, prompts, templates, multimodality, output converters, embedding models, document ETL pipeline, function calling, image models, and audio models. The repository also lists prerequisites such as Java 21, Docker/Podman, Mistral AI API Key, OpenAI API Key, and Ollama. Users can explore various use cases and projects to leverage LLMs for text generation, vector transformation, document processing, and more.

Daily-DeepLearning is a repository that covers various computer science topics such as data structures, operating systems, computer networks, Python programming, data science packages like numpy, pandas, matplotlib, machine learning theories, deep learning theories, NLP concepts, machine learning practical applications, deep learning practical applications, and big data technologies like Hadoop and Hive. It also includes coding exercises related to '剑指offer'. The repository provides detailed explanations and examples for each topic, making it a comprehensive resource for learning and practicing different aspects of computer science and data-related fields.

Exploring the integration between Nix and AI coding agents, this repository serves as a testbed for packaging, sandboxing, and enhancing AI-powered development tools within the Nix ecosystem. It provides a collection of AI tools with descriptions, versions, sources, licenses, homepages, and usage instructions. The repository also supports daily updates using GitHub Actions and offers a platform for experimental features like sandboxed execution, provider abstraction, and tool composition in Nix environments. Contributions are welcome, and the Nix packaging code in this repository is licensed under MIT.

Awesome Mind Network is a curated collection of open-source resources, SDKs, and tools by Mind Network, empowering developers and researchers with privacy-preserving technologies, Agentic AI, and decentralized infrastructure.

KCORES LLM Arena is a large model evaluation tool that focuses on real-world scenarios, using human scoring and benchmark testing to assess performance. It aims to provide an unbiased evaluation of large models in real-world applications. The tool includes programming ability tests and specific benchmarks like Mandelbrot Set, Mars Mission, Solar System, and Ball Bouncing Inside Spinning Heptagon. It supports various programming languages and emphasizes performance optimization, rendering, animations, physics simulations, and creative implementations.

AI-Catalog is a curated list of AI tools, platforms, and resources across various domains. It serves as a comprehensive repository for users to discover and explore a wide range of AI applications. The catalog includes tools for tasks such as text-to-image generation, summarization, prompt generation, writing assistance, code assistance, developer tools, low code/no code tools, audio editing, video generation, 3D modeling, search engines, chatbots, email assistants, fun tools, gaming, music generation, presentation tools, website builders, education assistants, autonomous AI agents, photo editing, AI extensions, deep face/deep fake detection, text-to-speech, startup tools, SQL-related AI tools, education tools, and text-to-video conversion.

AGiXT is a dynamic Artificial Intelligence Automation Platform engineered to orchestrate efficient AI instruction management and task execution across a multitude of providers. Our solution infuses adaptive memory handling with a broad spectrum of commands to enhance AI's understanding and responsiveness, leading to improved task completion. The platform's smart features, like Smart Instruct and Smart Chat, seamlessly integrate web search, planning strategies, and conversation continuity, transforming the interaction between users and AI. By leveraging a powerful plugin system that includes web browsing and command execution, AGiXT stands as a versatile bridge between AI models and users. With an expanding roster of AI providers, code evaluation capabilities, comprehensive chain management, and platform interoperability, AGiXT is consistently evolving to drive a multitude of applications, affirming its place at the forefront of AI technology.

hongbomiao.com is a personal research and development (R&D) lab that facilitates the sharing of knowledge. The repository covers a wide range of topics including web development, mobile development, desktop applications, API servers, cloud native technologies, data processing, machine learning, computer vision, embedded systems, simulation, database management, data cleaning, data orchestration, testing, ops, authentication, authorization, security, system tools, reverse engineering, Ethereum, hardware, network, guidelines, design, bots, and more. It provides detailed information on various tools, frameworks, libraries, and platforms used in these domains.

A comprehensive web application for auto-subtitling videos and audio, translating SRT files, generating AI narration with voice cloning, creating background images, and rendering professional subtitled videos. Designed for content creators, educators, and general users who need high-quality subtitle generation and video production capabilities.

Thinking_in_Java_MindMapping is a repository that started as a project to create mind maps based on the book 'Java Programming Ideas'. Over time, it evolved into a collection of programming notes, blog posts, book summaries, personal reflections, and even gaming content. The repository covers a wide range of topics, allowing the author to freely express thoughts and ideas. The content is diverse and reflects the author's dedication to consistency and creativity.

ChatWiki is an open-source knowledge base AI question-answering system. It is built on large language models (LLM) and retrieval-augmented generation (RAG) technologies, providing out-of-the-box data processing, model invocation capabilities, and helping enterprises quickly build their own knowledge base AI question-answering systems. It offers exclusive AI question-answering system, easy integration of models, data preprocessing, simple user interface design, and adaptability to different business scenarios.

LLM-Navigation is a repository dedicated to documenting learning records related to large models, including basic knowledge, prompt engineering, building effective agents, model expansion capabilities, security measures against prompt injection, and applications in various fields such as AI agent control, browser automation, financial analysis, 3D modeling, and tool navigation using MCP servers. The repository aims to organize and collect information for personal learning and self-improvement through AI exploration.

ALwrity is a lightweight and user-friendly text analysis tool designed for developers and data scientists. It provides various functionalities for analyzing and processing text data, including sentiment analysis, keyword extraction, and text summarization. With ALwrity, users can easily gain insights from their text data and make informed decisions based on the analysis results. The tool is highly customizable and can be integrated into existing workflows seamlessly, making it a valuable asset for anyone working with text data in their projects.

MaiMBot is an intelligent QQ group chat bot based on a large language model. It is developed using the nonebot2 framework, utilizes LLM for conversation abilities, MongoDB for data persistence, and NapCat for QQ protocol support. The bot features keyword-triggered proactive responses, dynamic prompt construction, support for images and message forwarding, typo generation, multiple replies, emotion-based emoji responses, daily schedule generation, user relationship management, knowledge base, and group impressions. Work-in-progress features include personality, group atmosphere, image handling, humor, meme functions, and Minecraft interactions. The tool is in active development with plans for GIF compatibility, mini-program link parsing, bug fixes, documentation improvements, and logic enhancements for emoji sending.

Ito is an intelligent voice assistant that provides seamless voice dictation to any application on your computer. It works in any app, offers global keyboard shortcuts, real-time transcription, and instant text insertion. It is smart and adaptive with features like custom dictionary, context awareness, multi-language support, and intelligent punctuation. Users can customize trigger keys, audio preferences, and privacy controls. It also offers data management features like a notes system, interaction history, cloud sync, and export capabilities. Ito is built as a modern Electron application with a multi-process architecture and utilizes technologies like React, TypeScript, Rust, gRPC, and AWS CDK.

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.

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.

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.

Jupyter AI connects generative AI with Jupyter notebooks. It provides a user-friendly and powerful way to explore generative AI models in notebooks and improve your productivity in JupyterLab and the Jupyter Notebook. Specifically, Jupyter AI offers: * An `%%ai` magic that turns the Jupyter notebook into a reproducible generative AI playground. This works anywhere the IPython kernel runs (JupyterLab, Jupyter Notebook, Google Colab, Kaggle, VSCode, etc.). * A native chat UI in JupyterLab that enables you to work with generative AI as a conversational assistant. * Support for a wide range of generative model providers, including AI21, Anthropic, AWS, Cohere, Gemini, Hugging Face, NVIDIA, and OpenAI. * Local model support through GPT4All, enabling use of generative AI models on consumer grade machines with ease and privacy.

Khoj is an open-source, personal AI assistant that extends your capabilities by creating always-available AI agents. You can share your notes and documents to extend your digital brain, and your AI agents have access to the internet, allowing you to incorporate real-time information. Khoj is accessible on Desktop, Emacs, Obsidian, Web, and Whatsapp, and you can share PDF, markdown, org-mode, notion files, and GitHub repositories. You'll get fast, accurate semantic search on top of your docs, and your agents can create deeply personal images and understand your speech. Khoj is self-hostable and always will be.

LangChain.dart is a Dart port of the popular LangChain Python framework created by Harrison Chase. LangChain provides a set of ready-to-use components for working with language models and a standard interface for chaining them together to formulate more advanced use cases (e.g. chatbots, Q&A with RAG, agents, summarization, extraction, etc.). The components can be grouped into a few core modules: * **Model I/O:** LangChain offers a unified API for interacting with various LLM providers (e.g. OpenAI, Google, Mistral, Ollama, etc.), allowing developers to switch between them with ease. Additionally, it provides tools for managing model inputs (prompt templates and example selectors) and parsing the resulting model outputs (output parsers). * **Retrieval:** assists in loading user data (via document loaders), transforming it (with text splitters), extracting its meaning (using embedding models), storing (in vector stores) and retrieving it (through retrievers) so that it can be used to ground the model's responses (i.e. Retrieval-Augmented Generation or RAG). * **Agents:** "bots" that leverage LLMs to make informed decisions about which available tools (such as web search, calculators, database lookup, etc.) to use to accomplish the designated task. The different components can be composed together using the LangChain Expression Language (LCEL).

Danswer is an open-source Gen-AI Chat and Unified Search tool that connects to your company's docs, apps, and people. It provides a Chat interface and plugs into any LLM of your choice. Danswer can be deployed anywhere and for any scale - on a laptop, on-premise, or to cloud. Since you own the deployment, your user data and chats are fully in your own control. Danswer is MIT licensed and designed to be modular and easily extensible. The system also comes fully ready for production usage with user authentication, role management (admin/basic users), chat persistence, and a UI for configuring Personas (AI Assistants) and their Prompts. Danswer also serves as a Unified Search across all common workplace tools such as Slack, Google Drive, Confluence, etc. By combining LLMs and team specific knowledge, Danswer becomes a subject matter expert for the team. Imagine ChatGPT if it had access to your team's unique knowledge! It enables questions such as "A customer wants feature X, is this already supported?" or "Where's the pull request for feature Y?"

Infinity is an AI-native database designed for LLM applications, providing incredibly fast full-text and vector search capabilities. It supports a wide range of data types, including vectors, full-text, and structured data, and offers a fused search feature that combines multiple embeddings and full text. Infinity is easy to use, with an intuitive Python API and a single-binary architecture that simplifies deployment. It achieves high performance, with 0.1 milliseconds query latency on million-scale vector datasets and up to 15K QPS.

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.

AgentCloud is an open-source platform that enables companies to build and deploy private LLM chat apps, empowering teams to securely interact with their data. It comprises three main components: Agent Backend, Webapp, and Vector Proxy. To run this project locally, clone the repository, install Docker, and start the services. The project is licensed under the GNU Affero General Public License, version 3 only. Contributions and feedback are welcome from the community.

This framework generates fuzz targets for real-world `C`/`C++` projects with various Large Language Models (LLM) and benchmarks them via the `OSS-Fuzz` platform. It manages to successfully leverage LLMs to generate valid fuzz targets (which generate non-zero coverage increase) for 160 C/C++ projects. The maximum line coverage increase is 29% from the existing human-written targets.

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.

The Azure-Analytics-and-AI-Engagement repository provides packaged Industry Scenario DREAM Demos with ARM templates (Containing a demo web application, Power BI reports, Synapse resources, AML Notebooks etc.) that can be deployed in a customer’s subscription using the CAPE tool within a matter of few hours. Partners can also deploy DREAM Demos in their own subscriptions using DPoC.