Mirror Flowers is an out-of-the-box code security auditing tool that integrates local static scanning (line-level taint tracking + AST) with AI verification to help quickly discover and locate high-risk issues, providing repair suggestions. It supports multiple languages such as PHP, Python, JavaScript/TypeScript, and Java. The tool offers both single-file and project modes, with features like concurrent acceleration, integrated UI for visual results, and compatibility with multiple OpenAI interface providers. Users can configure the tool through environment variables or API, and can utilize it through a web UI or HTTP API for tasks like single-file auditing or project auditing.

Wealth Tracker is a personal finance management tool designed to help users track their income, expenses, and investments in one place. With intuitive features and customizable categories, users can easily monitor their financial health and make informed decisions. The tool provides detailed reports and visualizations to analyze spending patterns and set financial goals. Whether you are budgeting, saving for a big purchase, or planning for retirement, Wealth Tracker offers a comprehensive solution to manage your money effectively.

QFurina is a powerful and easily extensible Python QQ robot backend service that provides a range of automation and interactive features. It supports multiple messaging platforms and has a robust plugin system, allowing users to easily expand and customize functionality.

README-AI is a developer tool that auto-generates README.md files using a combination of data extraction and generative AI. It streamlines documentation creation and maintenance, enhancing developer productivity. This project aims to enable all skill levels, across all domains, to better understand, use, and contribute to open-source software. It offers flexible README generation, supports multiple large language models (LLMs), provides customizable output options, works with various programming languages and project types, and includes an offline mode for generating boilerplate README files without external API calls.

The langchain4j-aideepin-web repository is the frontend project of langchain4j-aideepin, an open-source, offline deployable retrieval enhancement generation (RAG) project based on large language models such as ChatGPT and application frameworks such as Langchain4j. It includes features like registration & login, multi-sessions (multi-roles), image generation (text-to-image, image editing, image-to-image), suggestions, quota control, knowledge base (RAG) based on large models, model switching, and search engine switching.

LLM-jp-eval is a tool designed to automatically evaluate Japanese large language models across multiple datasets. It provides functionalities such as converting existing Japanese evaluation data to text generation task evaluation datasets, executing evaluations of large language models across multiple datasets, and generating instruction data (jaster) in the format of evaluation data prompts. Users can manage the evaluation settings through a config file and use Hydra to load them. The tool supports saving evaluation results and logs using wandb. Users can add new evaluation datasets by following specific steps and guidelines provided in the tool's documentation. It is important to note that using jaster for instruction tuning can lead to artificially high evaluation scores, so caution is advised when interpreting the results.

HiveChat is an AI chat application designed for small and medium teams. It supports various models such as DeepSeek, Open AI, Claude, and Gemini. The tool allows easy configuration by one administrator for the entire team to use different AI models. It supports features like email or Feishu login, LaTeX and Markdown rendering, DeepSeek mind map display, image understanding, AI agents, cloud data storage, and integration with multiple large model service providers. Users can engage in conversations by logging in, while administrators can configure AI service providers, manage users, and control account registration. The technology stack includes Next.js, Tailwindcss, Auth.js, PostgreSQL, Drizzle ORM, and Ant Design.

Awesome RAG is a curated list of retrieval-augmented generation (RAG) in large language models. It includes papers, surveys, general resources, lectures, talks, tutorials, workshops, tools, and other collections related to retrieval-augmented generation. The repository aims to provide a comprehensive overview of the latest advancements, techniques, and applications in the field of RAG.

New API is a next-generation large model gateway and AI asset management system that provides a wide range of features, including a new UI interface, multi-language support, online recharge function, key query for usage quota, compatibility with the original One API database, model charging by usage count, channel weighted randomization, data dashboard, token grouping and model restrictions, support for various authorization login methods, support for Rerank models, OpenAI Realtime API, Claude Messages format, reasoning effort setting, content reasoning, user-specific model rate limiting, request format conversion, cache billing support, and various model support such as gpts, Midjourney-Proxy, Suno API, custom channels, Rerank models, Claude Messages format, Dify, and more.

WeChat Bot is a simple and easy-to-use WeChat robot based on chatgpt and wechaty. It can help you automatically reply to WeChat messages or manage WeChat groups/friends. The tool requires configuration of AI services such as Xunfei, Kimi, or ChatGPT. Users can customize the tool to automatically reply to group or private chat messages based on predefined conditions. The tool supports running in Docker for easy deployment and provides a convenient way to interact with various AI services for WeChat automation.

New API is an open-source project based on One API with additional features and improvements. It offers a new UI interface, supports Midjourney-Proxy(Plus) interface, online recharge functionality, model-based charging, channel weight randomization, data dashboard, token-controlled models, Telegram authorization login, Suno API support, Rerank model integration, and various third-party models. Users can customize models, retry channels, and configure caching settings. The deployment can be done using Docker with SQLite or MySQL databases. The project provides documentation for Midjourney and Suno interfaces, and it is suitable for AI enthusiasts and developers looking to enhance AI capabilities.

ChatPilot is a chat agent tool that enables AgentChat conversations, supports Google search, URL conversation (RAG), and code interpreter functionality, replicates Kimi Chat (file, drag and drop; URL, send out), and supports OpenAI/Azure API. It is based on LangChain and implements ReAct and OpenAI Function Call for agent Q&A dialogue. The tool supports various automatic tools such as online search using Google Search API, URL parsing tool, Python code interpreter, and enhanced RAG file Q&A with query rewriting support. It also allows front-end and back-end service separation using Svelte and FastAPI, respectively. Additionally, it supports voice input/output, image generation, user management, permission control, and chat record import/export.

Hub is an open-source, high-performance LLM gateway written in Rust. It serves as a smart proxy for LLM applications, centralizing control and tracing of all LLM calls and traces. Built for efficiency, it provides a single API to connect to any LLM provider. The tool is designed to be fast, efficient, and completely open-source under the Apache 2.0 license.

Noi is an AI-enhanced customizable browser designed to streamline digital experiences. It includes curated AI websites, allows adding any URL, offers prompts management, Noi Ask for batch messaging, various themes, Noi Cache Mode for quick link access, cookie data isolation, and more. Users can explore, extend, and empower their browsing experience with Noi.

KuiperLLama is a custom large model inference framework that guides users in building a LLama-supported inference framework with Cuda acceleration from scratch. The framework includes modules for architecture design, LLama2 model support, model quantization, Cuda basics, operator implementation, and fun tasks like text generation and storytelling. It also covers learning other commercial inference frameworks for comprehensive understanding. The project provides detailed tutorials and resources for developing and optimizing large models for efficient inference.

Airdrop-tools is a repository containing tools for all Telegram bots. Users can join the Telegram group for support and access various bot apps like Moonbix, Blum, Major, Memefi, and more. The setup requires Node.js and Python, with instructions on creating data directories and installing extensions. Users can run different tools like Blum, Major, Moonbix, Yescoin, Matchain, Fintopio, Agent301, IAMDOG, Banana, Cats, Wonton, and Xkucoin by following specific commands. The repository also provides contact information and options for supporting the creator.

Academic_LLM_Sec_Papers is a curated collection of academic papers related to LLM Security Application. The repository includes papers sorted by conference name and published year, covering topics such as large language models for blockchain security, software engineering, machine learning, and more. Developers and researchers are welcome to contribute additional published papers to the list. The repository also provides information on listed conferences and journals related to security, networking, software engineering, and cryptography. The papers cover a wide range of topics including privacy risks, ethical concerns, vulnerabilities, threat modeling, code analysis, fuzzing, and more.

HackBot is an AI-powered cybersecurity chatbot designed to provide accurate answers to cybersecurity-related queries, conduct code analysis, and scan analysis. It utilizes the Meta-LLama2 AI model through the 'LlamaCpp' library to respond coherently. The chatbot offers features like local AI/Runpod deployment support, cybersecurity chat assistance, interactive interface, clear output presentation, static code analysis, and vulnerability analysis. Users can interact with HackBot through a command-line interface and utilize it for various cybersecurity tasks.

The NVIDIA AI Blueprint for Vulnerability Analysis for Container Security showcases accelerated analysis on common vulnerabilities and exposures (CVE) at an enterprise scale, reducing mitigation time from days to seconds. It enables security analysts to determine software package vulnerabilities using large language models (LLMs) and retrieval-augmented generation (RAG). The blueprint is designed for security analysts, IT engineers, and AI practitioners in cybersecurity. It requires NVAIE developer license and API keys for vulnerability databases, search engines, and LLM model services. Hardware requirements include L40 GPU for pipeline operation and optional LLM NIM and Embedding NIM. The workflow involves LLM pipeline for CVE impact analysis, utilizing LLM planner, agent, and summarization nodes. The blueprint uses NVIDIA NIM microservices and Morpheus Cybersecurity AI SDK for vulnerability analysis.

Mirror Flowers is an out-of-the-box code security auditing tool that integrates local static scanning (line-level taint tracking + AST) with AI verification to help quickly discover and locate high-risk issues, providing repair suggestions. It supports multiple languages such as PHP, Python, JavaScript/TypeScript, and Java. The tool offers both single-file and project modes, with features like concurrent acceleration, integrated UI for visual results, and compatibility with multiple OpenAI interface providers. Users can configure the tool through environment variables or API, and can utilize it through a web UI or HTTP API for tasks like single-file auditing or project auditing.

Kheish is an open-source, multi-role agent designed for complex tasks that require structured, step-by-step collaboration with Large Language Models (LLMs). It acts as an intelligent agent that can request modules on demand, integrate user feedback, switch between specialized roles, and deliver refined results. By harnessing multiple 'sub-agents' within one framework, Kheish tackles tasks like security audits, file searches, RAG-based exploration, and more.

The AI Governor Framework is a system designed to govern AI assistants in coding projects by providing rules and workflows to ensure consistency, respect architectural decisions, and enforce coding standards. It leverages Context Engineering to provide the AI with the right information at the right time, using an In-Repo approach to keep governance rules and architectural context directly inside the repository. The framework consists of two core components: The Governance Engine for passive rules and the Operator's Playbook for active protocols. It follows a 4-step Operator's Playbook to move features from idea to production with clarity and control.

Keyboard GPT is an LSPosed Module that integrates Generative AI like ChatGPT into your keyboard, allowing for real-time AI responses, custom prompts, and web search capabilities. It works in all apps and supports popular keyboards like Gboard, Swiftkey, Fleksy, and Samsung Keyboard. Users can easily configure API providers, submit prompts, and perform web searches directly from their keyboard. The tool also supports multiple Generative AI APIs such as ChatGPT, Gemini, and Groq. It offers an easy installation process for both rooted and non-rooted devices, making it a versatile and powerful tool for enhancing text input experiences on mobile devices.

PokeLLMon is a tool that allows users to set up a local battle engine for Pokémon battles. It requires Python version 3.8 or higher and OpenAI version 1.7.2 or higher. Users can configure the OpenAI API to enhance their battles. The tool provides a platform for users to engage in local battles by running the main Python script with their username and password for PokeLLMon.

**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.